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+                    GNU AFFERO GENERAL PUBLIC LICENSE
+                       Version 3, 19 November 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+                            Preamble
+
+  The GNU Affero General Public License is a free, copyleft license for
+software and other kinds of works, specifically designed to ensure
+cooperation with the community in the case of network server software.
+
+  The licenses for most software and other practical works are designed
+to take away your freedom to share and change the works.  By contrast,
+our General Public Licenses are intended to guarantee your freedom to
+share and change all versions of a program--to make sure it remains free
+software for all its users.
+
+  When we speak of free software, we are referring to freedom, not
+price.  Our General Public Licenses are designed to make sure that you
+have the freedom to distribute copies of free software (and charge for
+them if you wish), that you receive source code or can get it if you
+want it, that you can change the software or use pieces of it in new
+free programs, and that you know you can do these things.
+
+  Developers that use our General Public Licenses protect your rights
+with two steps: (1) assert copyright on the software, and (2) offer
+you this License which gives you legal permission to copy, distribute
+and/or modify the software.
+
+  A secondary benefit of defending all users' freedom is that
+improvements made in alternate versions of the program, if they
+receive widespread use, become available for other developers to
+incorporate.  Many developers of free software are heartened and
+encouraged by the resulting cooperation.  However, in the case of
+software used on network servers, this result may fail to come about.
+The GNU General Public License permits making a modified version and
+letting the public access it on a server without ever releasing its
+source code to the public.
+
+  The GNU Affero General Public License is designed specifically to
+ensure that, in such cases, the modified source code becomes available
+to the community.  It requires the operator of a network server to
+provide the source code of the modified version running there to the
+users of that server.  Therefore, public use of a modified version, on
+a publicly accessible server, gives the public access to the source
+code of the modified version.
+
+  An older license, called the Affero General Public License and
+published by Affero, was designed to accomplish similar goals.  This is
+a different license, not a version of the Affero GPL, but Affero has
+released a new version of the Affero GPL which permits relicensing under
+this license.
+
+  The precise terms and conditions for copying, distribution and
+modification follow.
+
+                       TERMS AND CONDITIONS
+
+  0. Definitions.
+
+  "This License" refers to version 3 of the GNU Affero General Public License.
+
+  "Copyright" also means copyright-like laws that apply to other kinds of
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+  "Additional permissions" are terms that supplement the terms of this
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+
+  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU Affero General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU Affero General Public License for more details.
+
+    You should have received a copy of the GNU Affero General Public License
+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+  If your software can interact with users remotely through a computer
+network, you should also make sure that it provides a way for users to
+get its source.  For example, if your program is a web application, its
+interface could display a "Source" link that leads users to an archive
+of the code.  There are many ways you could offer source, and different
+solutions will be better for different programs; see section 13 for the
+specific requirements.
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU AGPL, see
+<https://www.gnu.org/licenses/>.
diff --git a/MANIFEST.in b/MANIFEST.in
new file mode 100644
index 0000000000000000000000000000000000000000..ff301d6837b1c0023b2a89ffb9839eac0a4e9db3
--- /dev/null
+++ b/MANIFEST.in
@@ -0,0 +1,2 @@
+include README.md
+include COPYING.txt
diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..712df71e9f77454cb27382619c10e7c8d601ce14
--- /dev/null
+++ b/README.md
@@ -0,0 +1,5 @@
+pystencils
+==========
+
+
+![alt text](doc/img/logo.png)
\ No newline at end of file
diff --git a/doc/conf.py b/doc/conf.py
new file mode 100644
index 0000000000000000000000000000000000000000..a56be9f74dcba06275d602dcd3f0349a6e7cbb0c
--- /dev/null
+++ b/doc/conf.py
@@ -0,0 +1,13 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+#
+import os
+import sys
+
+sys.path.insert(0, os.path.abspath('..'))
+sys.path.insert(0, os.path.abspath('../../pystencils'))
+sys.path.insert(0, os.path.abspath('../..'))
+from sphinx_doc_conf import *
+
+project = 'lbmpy'
+html_logo = "img/logo.png"
diff --git a/doc/img/arch_lbmpy.svg b/doc/img/arch_lbmpy.svg
new file mode 100644
index 0000000000000000000000000000000000000000..8781de5d5d61606dbfa6ea9944f7f45720ab1b98
--- /dev/null
+++ b/doc/img/arch_lbmpy.svg
@@ -0,0 +1,221 @@
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
+<!-- Created with Inkscape (http://www.inkscape.org/) -->
+
+<svg
+   xmlns:dc="http://purl.org/dc/elements/1.1/"
+   xmlns:cc="http://creativecommons.org/ns#"
+   xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
+   xmlns:svg="http://www.w3.org/2000/svg"
+   xmlns="http://www.w3.org/2000/svg"
+   xmlns:sodipodi="http://sodipodi.sourceforge.net/DTD/sodipodi-0.dtd"
+   xmlns:inkscape="http://www.inkscape.org/namespaces/inkscape"
+   width="118.61397mm"
+   height="113.13387mm"
+   viewBox="0 0 420.28571 400.86803"
+   id="svg6176"
+   version="1.1"
+   inkscape:version="0.91 r13725"
+   sodipodi:docname="arch_lbmpy.svg">
+  <defs
+     id="defs6178">
+    <marker
+       inkscape:isstock="true"
+       style="overflow:visible"
+       id="marker4549-8-4"
+       refX="0"
+       refY="0"
+       orient="auto"
+       inkscape:stockid="Arrow1Lend">
+      <path
+         transform="matrix(-0.8,0,0,-0.8,-10,0)"
+         style="fill:#000000;fill-opacity:1;fill-rule:evenodd;stroke:#000000;stroke-width:1pt;stroke-opacity:1"
+         d="M 0,0 5,-5 -12.5,0 5,5 0,0 Z"
+         id="path4551-4-9"
+         inkscape:connector-curvature="0" />
+    </marker>
+  </defs>
+  <sodipodi:namedview
+     id="base"
+     pagecolor="#ffffff"
+     bordercolor="#666666"
+     borderopacity="1.0"
+     inkscape:pageopacity="0.0"
+     inkscape:pageshadow="2"
+     inkscape:zoom="0.35"
+     inkscape:cx="-254.85714"
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+     inkscape:document-units="px"
+     inkscape:current-layer="layer1"
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+     fit-margin-top="0"
+     fit-margin-left="0"
+     fit-margin-right="0"
+     fit-margin-bottom="0"
+     inkscape:window-width="1920"
+     inkscape:window-height="1043"
+     inkscape:window-x="0"
+     inkscape:window-y="0"
+     inkscape:window-maximized="1" />
+  <metadata
+     id="metadata6181">
+    <rdf:RDF>
+      <cc:Work
+         rdf:about="">
+        <dc:format>image/svg+xml</dc:format>
+        <dc:type
+           rdf:resource="http://purl.org/dc/dcmitype/StillImage" />
+        <dc:title></dc:title>
+      </cc:Work>
+    </rdf:RDF>
+  </metadata>
+  <g
+     inkscape:label="Layer 1"
+     inkscape:groupmode="layer"
+     id="layer1"
+     transform="translate(-167,36.643246)">
+    <rect
+       y="-36.143246"
+       x="167.5"
+       height="301.42856"
+       width="419.28571"
+       id="rect3338-3-1"
+       style="opacity:0.17300002;fill:#bcc1c4;fill-opacity:1;fill-rule:evenodd;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1" />
+    <text
+       sodipodi:linespacing="125%"
+       id="text4140-7-5"
+       y="8.1217699"
+       x="322.69202"
+       style="font-style:normal;font-weight:normal;font-size:40px;line-height:125%;font-family:sans-serif;letter-spacing:0px;word-spacing:0px;fill:#000000;fill-opacity:1;stroke:none;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
+       xml:space="preserve"><tspan
+         style="font-style:normal;font-variant:normal;font-weight:bold;font-stretch:normal;font-size:27.5px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Bold'"
+         y="8.1217699"
+         x="322.69202"
+         id="tspan4142-0-5"
+         sodipodi:role="line">lbmpy</tspan></text>
+    <text
+       inkscape:transform-center-y="22.223356"
+       inkscape:transform-center-x="-30.809653"
+       sodipodi:linespacing="125%"
+       id="text5052-7-6"
+       y="48.293827"
+       x="189.64954"
+       style="font-style:normal;font-weight:normal;font-size:15px;line-height:125%;font-family:sans-serif;letter-spacing:0px;word-spacing:0px;fill:#000000;fill-opacity:1;stroke:none;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
+       xml:space="preserve"><tspan
+         style="font-size:17.49999809px"
+         y="48.293827"
+         x="189.64954"
+         id="tspan5054-5-5"
+         sodipodi:role="line">Collision</tspan><tspan
+         style="font-size:9.99999905px"
+         id="tspan4798"
+         y="70.168823"
+         x="189.64954"
+         sodipodi:role="line" /><tspan
+         style="font-style:italic;font-variant:normal;font-weight:normal;font-stretch:normal;font-size:12.49999809px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Italic'"
+         id="tspan4800"
+         y="87.060074"
+         x="189.64954"
+         sodipodi:role="line">- moments (SRT,TRT,MRT)</tspan><tspan
+         style="font-style:italic;font-variant:normal;font-weight:normal;font-stretch:normal;font-size:12.49999809px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Italic'"
+         id="tspan4802"
+         y="102.68507"
+         x="189.64954"
+         sodipodi:role="line">- cumulant</tspan><tspan
+         style="font-style:italic;font-variant:normal;font-weight:normal;font-stretch:normal;font-size:12.49999809px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Italic'"
+         id="tspan4804"
+         y="118.31007"
+         x="189.64954"
+         sodipodi:role="line">- (entropic)</tspan></text>
+    <text
+       inkscape:transform-center-y="22.223356"
+       inkscape:transform-center-x="-30.809653"
+       sodipodi:linespacing="125%"
+       id="text5052-7-6-8"
+       y="47.016239"
+       x="413.58612"
+       style="font-style:normal;font-weight:normal;font-size:15px;line-height:125%;font-family:sans-serif;letter-spacing:0px;word-spacing:0px;fill:#000000;fill-opacity:1;stroke:none;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
+       xml:space="preserve"><tspan
+         style="font-size:17.49999809px"
+         y="47.016239"
+         x="413.58612"
+         id="tspan5054-5-5-8"
+         sodipodi:role="line">Propagation</tspan><tspan
+         style="font-size:9.99999905px"
+         id="tspan4798-4"
+         y="68.891235"
+         x="413.58612"
+         sodipodi:role="line" /><tspan
+         style="font-style:italic;font-variant:normal;font-weight:normal;font-stretch:normal;font-size:12.49999809px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Italic'"
+         id="tspan4800-3"
+         y="85.782486"
+         x="413.58612"
+         sodipodi:role="line">- source/destination</tspan><tspan
+         style="font-style:italic;font-variant:normal;font-weight:normal;font-stretch:normal;font-size:12.49999809px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Italic'"
+         id="tspan4802-1"
+         y="101.40749"
+         x="413.58612"
+         sodipodi:role="line">- EsoTwist</tspan><tspan
+         style="font-style:italic;font-variant:normal;font-weight:normal;font-stretch:normal;font-size:12.49999809px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Italic'"
+         id="tspan4804-4"
+         y="117.03249"
+         x="413.58612"
+         sodipodi:role="line">- AABB</tspan></text>
+    <text
+       inkscape:transform-center-y="22.223356"
+       inkscape:transform-center-x="-30.809653"
+       sodipodi:linespacing="125%"
+       id="text5052-7-6-9"
+       y="174.15912"
+       x="236.01477"
+       style="font-style:normal;font-weight:normal;font-size:15px;line-height:125%;font-family:sans-serif;letter-spacing:0px;word-spacing:0px;fill:#000000;fill-opacity:1;stroke:none;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
+       xml:space="preserve"><tspan
+         style="font-size:17.49999809px"
+         y="174.15912"
+         x="236.01477"
+         id="tspan5054-5-5-2"
+         sodipodi:role="line">Specific Transformations</tspan><tspan
+         style="font-size:9.99999905px"
+         id="tspan4798-0"
+         y="196.03412"
+         x="236.01477"
+         sodipodi:role="line" /><tspan
+         style="font-style:italic;font-variant:normal;font-weight:normal;font-stretch:normal;font-size:12.49999809px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Italic'"
+         id="tspan4800-6"
+         y="212.92537"
+         x="236.01477"
+         sodipodi:role="line">- specific common subexpression elimination</tspan><tspan
+         style="font-style:italic;font-variant:normal;font-weight:normal;font-stretch:normal;font-size:12.49999809px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Italic'"
+         id="tspan4802-8"
+         y="228.55037"
+         x="236.01477"
+         sodipodi:role="line">- loop splitting</tspan><tspan
+         style="font-style:italic;font-variant:normal;font-weight:normal;font-stretch:normal;font-size:12.49999809px;font-family:sans-serif;-inkscape-font-specification:'sans-serif Italic'"
+         id="tspan4804-9"
+         y="244.17537"
+         x="236.01477"
+         sodipodi:role="line">- input/output of macroscopic values</tspan></text>
+    <text
+       sodipodi:linespacing="125%"
+       id="text4542-2"
+       y="338.70966"
+       x="372.24048"
+       style="font-style:normal;font-weight:normal;font-size:20px;line-height:125%;font-family:sans-serif;letter-spacing:0px;word-spacing:0px;fill:#000000;fill-opacity:1;stroke:none;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
+       xml:space="preserve"><tspan
+         style="font-size:17.5px;text-align:center;text-anchor:middle"
+         y="338.70966"
+         x="375.02612"
+         id="tspan4544-6"
+         sodipodi:role="line">Equations with fields </tspan><tspan
+         id="tspan4564-6"
+         style="font-size:17.5px;text-align:center;text-anchor:middle"
+         y="360.58466"
+         x="372.24048"
+         sodipodi:role="line">and neighbor accesses</tspan></text>
+    <path
+       sodipodi:nodetypes="cc"
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+       d="m 373.76305,263.98075 10e-6,53.57142"
+       style="fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1" />
+  </g>
+</svg>
diff --git a/doc/img/boundary_lists.svg b/doc/img/boundary_lists.svg
new file mode 100644
index 0000000000000000000000000000000000000000..06a6e5030aecfede2e69471eab11822baf45875a
--- /dev/null
+++ b/doc/img/boundary_lists.svg
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diff --git a/doc/img/collision.svg b/doc/img/collision.svg
new file mode 100644
index 0000000000000000000000000000000000000000..87798f3865a3506eaec789ae2d5d0dacc45040ad
--- /dev/null
+++ b/doc/img/collision.svg
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diff --git a/doc/img/mb_discretization/maxwell_boltzmann_stencil_plot.py b/doc/img/mb_discretization/maxwell_boltzmann_stencil_plot.py
new file mode 100644
index 0000000000000000000000000000000000000000..2284507a4db2a7e8376312285b3df3e8aa8f7bbf
--- /dev/null
+++ b/doc/img/mb_discretization/maxwell_boltzmann_stencil_plot.py
@@ -0,0 +1,58 @@
+# -*- coding: utf-8 -*-
+import matplotlib.pyplot as plt
+from lbmpy.stencils import get_stencil
+
+import numpy as np
+import math
+from matplotlib import cm
+from matplotlib.patches import FancyArrowPatch
+from mpl_toolkits.mplot3d import proj3d
+
+
+class Arrow3D(FancyArrowPatch):
+    def __init__(self, xs, ys, zs, *args, **kwargs):
+        FancyArrowPatch.__init__(self, (0, 0), (0, 0), *args, **kwargs)
+        self._verts3d = xs, ys, zs
+
+    def draw(self, renderer):
+        xs3d, ys3d, zs3d = self._verts3d
+        xs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, renderer.M)
+        self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))
+        FancyArrowPatch.draw(self, renderer)
+
+
+fig = plt.figure()
+ax = fig.gca(projection='3d')
+ax.set_aspect("equal")
+
+maxValue = 2
+X = np.arange(-maxValue, maxValue, 0.1)
+Y = np.arange(-maxValue, maxValue, 0.1)
+X, Y = np.meshgrid(X, Y)
+
+
+def maxwell_boltzmann(x, y):
+    rho = 1
+    m = 1
+    k_B = 0.5
+    pi = math.pi
+    T = 1.2
+    return rho * (m / (2 * k_B * T * pi)) ** (3 / 2) * np.exp(- m / (k_B * T) * (x ** 2 + y ** 2) / 2)
+
+
+if __name__ == "__main__":
+    from mpl_toolkits.mplot3d import Axes3D
+    MB = maxwell_boltzmann(X, Y)
+
+    surf = ax.plot_surface(X, Y, MB, rstride=1, cstride=1, cmap=cm.coolwarm,
+                           linewidth=0, antialiased=False)
+
+    for dir in get_stencil("D2Q9"):
+        a = Arrow3D([0, dir[0]], [0, dir[1]], [0, 0], mutation_scale=20, lw=1, arrowstyle="-|>", color="b")
+        ax.add_artist(a)
+
+        h = maxwell_boltzmann(dir[0], dir[1])
+        a = Arrow3D([dir[0], dir[0]], [dir[1], dir[1]], [0, h], mutation_scale=20, lw=2, arrowstyle="wedge", color="k")
+        ax.add_artist(a)
+
+    plt.show()
diff --git a/doc/img/mb_discretization/mb.png b/doc/img/mb_discretization/mb.png
new file mode 100644
index 0000000000000000000000000000000000000000..d5ab353515d5c6dcc2dbb5edd77c23dd7f622ada
Binary files /dev/null and b/doc/img/mb_discretization/mb.png differ
diff --git a/doc/img/moment_shift.svg b/doc/img/moment_shift.svg
new file mode 100644
index 0000000000000000000000000000000000000000..c28495995cf2339305b44dc19e08f02aadc90c59
--- /dev/null
+++ b/doc/img/moment_shift.svg
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diff --git a/doc/index.rst b/doc/index.rst
new file mode 100644
index 0000000000000000000000000000000000000000..a902b69c136f7e933aa9a31c8f9696a1461ffd9b
--- /dev/null
+++ b/doc/index.rst
@@ -0,0 +1,14 @@
+lbmpy
+=====
+
+
+.. toctree::
+    :maxdepth: 2
+
+    sphinx/tutorials.rst
+    sphinx/api.rst
+
+
+
+.. image:: /img/arch_lbmpy.svg
+
diff --git a/doc/notebooks/00_tutorial_lbmpy_walberla_overview.ipynb b/doc/notebooks/00_tutorial_lbmpy_walberla_overview.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..c9ade9495ba519e8214353edb8f7032e6a1e2948
--- /dev/null
+++ b/doc/notebooks/00_tutorial_lbmpy_walberla_overview.ipynb
@@ -0,0 +1,536 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Overview: *lbmpy*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Welcome to the documentation of the *lbmpy* lattice Boltzmann module! In this document we'll give you an overview  over the architecture of the package and will show you different ways to use it. You can find more \n",
+    "hands-on examples on how to set up specific simulations in the tutorial notebooks.\n",
+    "\n",
+    "You probably already have noticed that this is not a normal website. You are looking at an interactive IPython/Jupyter notebook. That means that the following grey code cells contain valid Python code that can be run interactively. You can run the code cells by hitting Shift+Enter. Make sure to run all of them in order, since variables and state defined in an executed code cell is used by the next cells.\n",
+    "\n",
+    "## Code generation and its advantages\n",
+    "\n",
+    "Now, back to *lbmpy*: Whats special about it? *lbmpy* is not just an implementation of different LB schemes in Python. Instead *lbmpy* is a package to generate fast C implementations. This is done by writing down the LB equations in a generic, symbolic way in a computer algebra system. Then the equations can be adapted to the specific problem, rearranged, and simplified. Basically you can think of this step as rewriting the \"paper representation\" of a method, such that a C programmer with no LB experience can implement it. \n",
+    "At this step one can already insert scenario specific information into the equations, like fixing relaxation rates, stencil, force model or domain sizes, such that the equations can be written in a simpler form that has less floating point operations (FLOPs). \n",
+    "\n",
+    "*lbmpy* was written after realizing that it is almost impossible to write a generic **and** fast LB code in a language like C++. In principle it is possible to realize abstractions with static polymorphism (in C++: with template meta programming) but in practice this leads to code that is hard to understand and maintain. And for LB schemes there are lots of model and parameters choices that one would like to write down in an abstract way. The following picture shows some of these options one faces when implementing a new LB code:\n",
+    "\n",
+    "![](../img/feature_optimization_overview.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Lets illustrate this with a simple example: Lets say you want MRT and cumulant collision operators for a two dimensional (D2Q9) and two different 3D stencils (D3Q19 and D3Q27). It turns out that abstracting the stencil specific code away by introducting a stencil class or even stencil-template-constructs already lead to performance degradations. When the stencil is known at compile time, one can do stencil specific common subexpression elimination that drastically reduces the number of FLOPs. Similar effects are also encountered related to the other implementation choices. Thus in *lbmpy* one completely specifies the LB scheme one wants to have, then the LB equations are simplified and optimized and a shared memory parallel C implementation is generated. In that way all the information one has about the scenario can be used at 'compile time' and the best possible compute kernel is generated. \n",
+    "\n",
+    "Now, enough of the theory, let's set up a simple simulation. The next cell simulates a lid driven cavity, all domain borders are wall, the upper wall is moving to the right. To run the cell click into and and hit Shift+Enter."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ldc = create_lid_driven_cavity(domain_size=(100, 40), method='srt', relaxation_rate=1.6)\n",
+    "ldc.run(500)\n",
+    "plt.vector_field(ldc.velocity_slice());"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Executing this cell probably took quite a while to execute, because in the background the method was derived, simplified and compiled. Running a few more timesteps now is faster, since the compiled kernel is already available."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ldc.run(500)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Above simulation runs C code, that was created by Python, compiled to a shared library, then loaded again into Python, such that we can call it like a normal Python function. We can actually have a look a the intermediate C code. Remove the comment from the next cell and run it: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#show_code(ldc.ast)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note that this code has the relaxation rate and array sizes inserted as numeric constants. This additional information helps the C compiler to generate faster code. Also, having the code in symbolic form makes it easy to generate code for different platforms as well: C(++) for CPUs, optionally with platform specific SIMD instrinsics or CUDA for Nvidia GPUs. To run the lid driven cavity on GPUs all it takes are the following changes:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU : 89.9 MLUPS,  GPU 58.6 MLUPS\n"
+     ]
+    }
+   ],
+   "source": [
+    "optimization = {'target': 'gpu', 'gpu_indexing_params': {'block_size': (16, 4, 1)}}\n",
+    "ldc_gpu = create_lid_driven_cavity(domain_size=(100, 40, 10), method='srt', relaxation_rate=1.6, \n",
+    "                                   optimization=optimization)  \n",
+    "\n",
+    "print(\"CPU : %.1f MLUPS,  GPU %.1f MLUPS\" % (ldc.benchmark(), ldc_gpu.benchmark()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Performance is reported in million lattice cells updates per second (MLUPS), i.e. the larger the faster."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this section we hopefully have convinced you, that code generation is a powerful technique that can give you code flexibility without drawbacks in performance. We have already demonstrated the flexibility with respect to target architecture (CPU, GPU), in the next section we show the flexibility in terms of supported LB methods."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## LB schemes\n",
+    "\n",
+    "In this section we demonstrate how to use advanced LB schemes like multi-relaxation-time, cumulant and entropic schemes.\n",
+    "\n",
+    "### MRT methods and its special cases\n",
+    "\n",
+    "For the lid driven cavity above we have used the simplest lattice Boltzmann scheme with a single relaxation time (SRT), sometimes also called BGK scheme. This method relaxes each moment of the particle distribution function with the same relaxation rate. This relaxation rate is used to control the viscosity of the fluid. SRT can be viewed as a special case of the more general multi relaxation time methods, where different moments can be relaxed to equilibrium with a different rate. We get back the SRT operator by choosing all MRT relaxation rates as the same constant. Actually *lbmpy* always uses the MRT representation, and by setting a single relaxation rate for all moments and after a lot of equation simplification steps, an efficient SRT kernel drops out.\n",
+    "\n",
+    "In a C++ code one would have to implement the SRT special case separately, since the C++ compiler could not do all the simplifications of the MRT code, even if the relaxation rates would be template parameters. This means that one would have to implement a separate SRT, TRT, and MRT kernel.\n",
+    "This is not required here, because of the automatic equation simplification. \n",
+    "\n",
+    "Let's look at the details of the methods we used above:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$1.6$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$1.6$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1.6$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{0}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.6$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.6$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1.6$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.6$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.6$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.6$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f2a17e5eba8>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ldc.method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "All moments are relaxed to their equilibrium values with the same rate. We can easily built a more complex method were we choose different rates to separately control viscosity, bulk viscosity and relaxation of higher order moments:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} - y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}^{2} - u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} + y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{2 \\rho}{3} + u_{0}^{2} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.5$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f2a169b64e0>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mrt_ldc = create_lid_driven_cavity(domain_size=(100, 40), method='mrt3', relaxation_rates=[1.8, 1.5, 1])\n",
+    "mrt_ldc.method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In principle we can freely choose all entries of above table (as long as the moments are linear independent) and automatically generate a custom MRT implementation."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Modern methods: cumulant and entropic schemes\n",
+    "\n",
+    "Recently more complex lattice Boltzmann methods have been published that improve the stability of standard methods. We demonstrate this by a setting up a shear flow scenario where the upper half is initialized with velocity to the right and the lower half with a velocity to the left. The y-velocity component is initialized with a very small random value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "domain_size = (100, 100)\n",
+    "yHalf = domain_size[1]//2\n",
+    "initial_velocity = np.zeros(domain_size + (2,))\n",
+    "initial_velocity[:, :yHalf, 0] =  0.08\n",
+    "initial_velocity[:, yHalf:, 0] = -0.08\n",
+    "initial_velocity[:, :, 1] += np.random.rand(*domain_size) * 1e-5\n",
+    "plt.vector_field(initial_velocity, step=8);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We choose a relaxation rate near the upper limit of 2. Three scenarios are created:\n",
+    "- BGK/SRT collision operator\n",
+    "- cumulant collision operator \n",
+    "- entropic stabilization\n",
+    "\n",
+    "For the latter two advanced methods the relaxation rates of the higher order moments are chosen as equilibrium (for cumulant) or subject to an entropy condition (for the entropic) scheme."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rr = 1.995\n",
+    "\n",
+    "periodic_flow_srt = create_fully_periodic_flow(initial_velocity, relaxation_rate=rr)\n",
+    "periodic_flow_cumulant = create_fully_periodic_flow(initial_velocity, method='mrt3', compressible=True,\n",
+    "                                                    relaxation_rates=[rr, rr, 1], cumulant=True)\n",
+    "periodic_flow_entropic = create_fully_periodic_flow(initial_velocity, method='mrt3', compressible=True,\n",
+    "                                                    relaxation_rates=[rr, rr, 1], entropic=True)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Run the following cell to see the results of the three methods after 1000 time steps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x360 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "periodic_flow_entropic.run(1000)\n",
+    "periodic_flow_cumulant.run(1000)\n",
+    "periodic_flow_srt.run(1000)\n",
+    "\n",
+    "plt.figure(figsize=(20, 5))\n",
+    "plt.subplot(1, 3, 1)\n",
+    "plt.title(\"SRT\")\n",
+    "plt.scalar_field(periodic_flow_srt.velocity[:, :, 0])\n",
+    "plt.subplot(1, 3, 2)\n",
+    "plt.title(\"Cumulant\")\n",
+    "plt.scalar_field(periodic_flow_cumulant.velocity[:, :, 0])\n",
+    "plt.subplot(1, 3, 3)\n",
+    "plt.title(\"Entropic\")\n",
+    "plt.scalar_field(periodic_flow_entropic.velocity[:, :, 0]);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, run above cell another time to simulate further. The simple SRT model will become unstable and yield NaN's.\n",
+    "Both advanced methods run stable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "domain_size = (300, 300)\n",
+    "yHalf = domain_size[1]//2\n",
+    "initial_velocity = np.zeros(domain_size + (2,))\n",
+    "initial_velocity[:, :yHalf, 0] =  0.08\n",
+    "initial_velocity[:, yHalf:, 0] = -0.08\n",
+    "initial_velocity[:, :, 1] += np.random.rand(*domain_size) * 1e-2\n",
+    "plt.vector_field(initial_velocity, step=8);\n",
+    "\n",
+    "sc = create_fully_periodic_flow(initial_velocity, relaxation_rate=1.9)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sc.run(4000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.quiver.Quiver at 0x7f29c3a44ba8>"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.vector_field(sc.velocity[:, :, :], step=8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/01_tutorial_predefinedScenarios.ipynb b/doc/notebooks/01_tutorial_predefinedScenarios.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..d3e56d66c9995b67c69919f4c7f1f27f161fc7a9
--- /dev/null
+++ b/doc/notebooks/01_tutorial_predefinedScenarios.ipynb
@@ -0,0 +1,630 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "nbsphinx": "hidden"
+   },
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'lbmpy.session'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-1-f547fe940a83>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mlbmpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msession\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mpystencils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjupytersetup\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'lbmpy.session'"
+     ]
+    }
+   ],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from pystencils.jupytersetup import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 01: Running pre-defined scenarios\n",
+    "\n",
+    "\n",
+    "*lbmpy* is a module to do Lattice Boltzmann simulations in Python. \n",
+    "\n",
+    "In this tutorial you will get a broad overview of *lbmpy*'s features. We will run some of the included scenarios that come with *lbmpy*, like a channel flow and a lid driven cavity. This tutorial uses the simple, high-level API of *lbmpy*, while the following tutorials go into the low-level details.\n",
+    "\n",
+    "The only prerequisite for this tutorial is basic Python and [numpy](http://www.numpy.org/) knowledge.\n",
+    "\n",
+    "\n",
+    "> #### What's special about *lbmpy* ?\n",
+    "> The LBM kernels (i.e. the functions that do all the computations) are not written in Python. Instead *lbmpy* generates optimized C or CUDA code for these kernels and compiles it using the *pystencils* module. In that way we get very fast LBM kernels, a lot faster than pure Python implementations and probably also faster than handwritten C kernels. This sounds complicated, but we don't have to care about all this background work, since all compiled kernels are available as Python functions again. Thus *lbmpy* can be used just like any other Python package.\n",
+    "\n",
+    "\n",
+    "## Lid Driven Cavity\n",
+    "\n",
+    "We start by simulating a fluid in a rectangular box, where one wall (the lid) is moving. This is called a 'lid driven cavity'. At the stationary walls *no-slip* boundary conditions are set, which enforce zero velocity at the wall. At the lid there is a *velocity bounce back (UBB)* boundary condition, which sets zero normal velocity and a prescribed tangential velocity.\n",
+    "\n",
+    "We don't have to set up all these boundary conditions manually since there is a function ``create_lid_driven_cavity``  that does all the work for us. This function takes the tangential velocity of the lid, which drives the flow. It is given in lattice units and to get a stable simulation it should be smaller than 0.1. The `relaxation_rate` determines the viscosity of the fluid: Small relaxation rates correspond to high viscosity. The `relaxation_rate` has to be between 0 and 2."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$1.95$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$1.95$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1.95$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{0}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.95$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.95$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1.95$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.95$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.95$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.95$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f49b98b4f98>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ldc_scenario = create_lid_driven_cavity(domain_size=(80,50), lid_velocity=0.01, relaxation_rate=1.95)\n",
+    "ldc_scenario.method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The *run* method of the scenario runs the specified amount of time steps. When you run the next cell, 2000 time steps are executed and the velocity field is plotted. You can run the cell multiple times to see a time evolution. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ldc_scenario.run(2000)\n",
+    "plt.vector_field(ldc_scenario.velocity_slice(), step=2);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Variations to experiment with:\n",
+    "- simulate with a higher ``relaxation_rate`` (i.e. higher [Reynolds number](https://en.wikipedia.org/wiki/Reynolds_number)), keep in mind that the ``relaxation_rate`` has to be smaller than 2. You might have to increase (``domain_size``) to keep the simulation stable and run more time steps to get to the stationary solution. You also might want to increase the ``step`` parameter for the plot, to reduce the number of arrows.\n",
+    "- run a 3D simulation by adding a third dimension size to ``domain_size``. The ``velocity`` property of the scenario is now a 3D field that has to be sliced before it can be plotted, e.g. ``ldc_scenario.velocity[:, :, 10, 0:2]`` generates a slice at ``z=10`` and plot the ``x`` and ``y`` component of the velocity."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##  Fully periodic flow\n",
+    "\n",
+    "Another simple scenario is a box with periodic boundary conditions in all directions. We initialize a non-zero initial velocity field, which is decaying over time due to viscous effects and the absence of driving forces or boundary conditions. In this example we initialize a shear flow where in one stripe the fluid is moving to the left, and everywhere else to the right. We perturbe this initial velocity field with random noise to get an instable shear layer.   "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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hA0aNGgVfX18olUoIgoDKykpUVFSgsrJSI5w+fRrJyclN0nBxcYGPjw/69+8PY2NjmJubi/uurq5GVVUVqqurUVpaiq+//rpJfGtra4wYMQK+vr4wMzODVCoV46njqrfPnz+PixcvNkmjR48eGDlyJAYNGgSpVApTU1OoVCqoVCoQkbhdV1eHhQsXory8XIxrY2ODMWPG4NVXX8Xo0aNx9+5d3Lt3DwqFAgqFAkVFRRrbWVlZyM7ObvF82trawtPTEyNHjkR1dXWz6Tx48AA1NTUtptG9e3eMGzcOnTp1Euty45Cbm4vU1NQW47dr1w5ubm6YOHEiLCwsoFQqxfqk3v72229x48YNjXj9+vUT67WtrS0uXLiA7OzsJiEnJwd1dXUt7h8AnJyc4OPjAw8PD8hkMvGaLi0tFbcTExNbPI6ePXvC09MT9vb28PDwEM9fXV0damtrUVdXh6qqKqxatapJXvr164fRo0dj9OjRkEgkyM3NRU1NjXhdNH5NSEjAiRMnNOILggB3d3f4+vpi0KBBUCgUKCwsRE5OTpOgUCieWg4ymQze3t7w8vKCi4sLSkpKUFpaKr6WlpYiIyMD169fbza+iYkJvLy8YGdnBw8PD9TW1or1qLCwUNxOT09/ajvTvn17BAYG4sUXX0R5eblGO1teXo78/Hz89ttvzcZ1cnKCt7c32rVrh969e8PS0lI8F43Px8GDB3Hp0iWNuI6OjvDz88Po0aPx4osvIiUlpUk7qw7l5eV47733NNp8Q0NDeHt7i23d48eP8fDhQ402tvFrXl7eUx9jNzQ0xNixY+Ht7Y3Kysom11ZRURGSkpJarN8mJibo27cv/Pz80KlTJ1RUVKC8vBwVFRViuH//Ps6dO9ckrkwmg4eHB15++WUYGhrCyckJVVVVKCkpaRKuXbuG0tLSZvPg4uICV1dX9OrVC926dUNpaanY96pDbm5ui3VKIpGgf//+cHZ2hre3NyQSidhvN35NSkpCfn5+s2lYWVmhX79+6NatG3r37g2FQoGCggIUFBSgsLBQ3M7Ly2vxXACAm5sbgoKCIJPJxDjqkJ+fj7y8vKe2lUZGRvD398fgwYNRVlYmXg+N29zk5ORm7yPU56Rv374IDQ1Fp06dxHaicbhy5QpiYmKalKGHhwf8/PwwdOhQKBQKVFVVidfUk+HMmTPNnk+5XI6BAweiR48esLW1hbm5ebPtzLMeZ3R0dISXlxf69euH8vJysZ/Kzs5GVlaWRp/XHLlcjtGjR8PDwwMdO3ZEVVUVKisrNV7z8/Oxe/fuZs/Byy+/jJEjR0IikUAulyMvL6/JMeTl5UGpVD41H/3794enpyf69OmD0tJSjfOovj7v3LnT4qPTxsbG6Nu3L/z9/WFjYyO2sep+p7S0FMnJybh7926L5Tho0CDY2NigX79+4vX55LVx9epVVFdXN5uGs7Mz+vbti0GDBqF79+4a90PqkJSUhJ9//rlJ3G7dumHUqFHw8fFBbW2teC+jVCrF+xj1v1evXo379+9rnAcfHx+MGzcO48aNg1KpRFJSkka8xiE1NRXLly/X2H/Xrl3x6quvYty4cRg+fDhOnjyJsrIyjetB3XfW1NTgl19+QWJiokYahoaGGDZsGEaNGgU3NzeUl5eL9x2N+436+nqUlJQ0yYNUKsXgwYPFNj83NxePHz8W25XCwkKN7ezsbFRUVDR7LtTlMnbsWAwYMED8vLpOZmdno6ysrMW4QEObP2XKFCxYsADu7u5P/ay+BEG4SkQeWn1Y2xHuXxHa+oxrc9/eaRPkcjmFhobShx9+qFd8/OvbkHHjxlHfvn31ii+TySgwMFCcBWxNUH/jpGvo0qULrV69mlJSUlqdBwsLi1bFt7OzI2NjY73jm5mZ0csvv9yqPFhbW4uzuvqGF198sVXxJRKJ3nkwMTGhmTNnNjsTqW3o06cPrV+/nhYuXKh3/seOHUv79u3TmNXV95zqE8/X15cOHTpEtbW11Lt3b7337+bmRnPmzGnVMQANM26tie/s7KxXvE6dOtEnn3xCWVlZtGDBAr3337NnT43ZM11D7969ad26dbR8+XK90zA1NaVp06a1+vrUt041Dvq2df369aOoqCg6deqU3vvu0aMHrV69mkJCQvROw8jISJxt0SeYmJjQjBkzaPr06Xqn0adPH1q7dm2TJwW0DYaGhjRx4kRatGiRXvGNjY0pPDyczp49q3eb3a9fP/rqq6/o559/1rscvLy8aMuWLeTv7693GgBadV0IgkAjR44kX19fveL7+fnRjz/+SJWVlSQIgs7xO3fuTGvXrqW8vDyKiopqVTn06tVLr/shMzMzmj9/Pv3555+tPp+bN2/WmFHVNbi6utKSJUv0jm9nZ0eLFi1q8uSHrqFjx46tig+0rl4CDW2NoaFhq9Lo0KFDq49D33aqa9eu9Mknn9DBgwf1it+3b1+KioqioqKif/t4CjrMuGq/CIg14enpCWdnZ1hZWYlBvRbGysoKJ0+exN69e8XPDxkyBOHh4Zg4cSKsra2RkJCAI0eOwNzcHGZmZuJr4+1PP/1U49uQIUOGYNq0aQgLC4O9vT3efPNNjf1bW1tr/PvmzZvYtGmTGP+ll15CeHg4pkyZAnt7e6Snp2PLli2QyWQthoSEBBQXF2scu4uLC4KDgxEcHIxr167hl19+gZ2dHezt7WFvb6+xnZOTg5kzZwJo+FYzJCQEkZGRGD58OCQSCZRKJfr06QOZTAYDA4NmXxMTE5GZmamRB0dHRwQFBSE4OBiPHz9GVFQUDA0NYWRk1CQQEXbt2qUR387ODhMmTEBYWBiGDx+O8ePHQ6FQwMTEBKampjAxMdEIFy9exPnz58X46m+6J02ahHHjxiE+Ph5vvfUWjIyMYGxsrLF/Y2NjGBoaYvv27aivrxfTsLa2RnBwMCZOnIgRI0Zg7ty5SExMFOMbGxuLwcjICCkpKTh16pTGcXh5eWHixIkICwtDaWkpwsLCIJFIIJFIIAiCuK0ON2/ebPLttampKUaPHo2AgADcvXsX586dg42NjbiuSb1tY2ODtLQ0LFu2TIw7bNgwREREIDQ0FObm5qipqcGAAQM04jyZ1rp168SZYysrK0yZMgWzZs2Cp6cnBEHAtm3bMGjQIHHtpTquOtTU1GD+/PliHnr37o2IiAhMmzYNzs7OAIAvvvgCVVVVkMlkkEqlTep1cnIyHj16pFEO5ubmGDduHIKDg2FkZIT169fDycmp2WBpaQlXV1eUl5fDxsYGERERmDdvHnr06CGm179/f1haWsLc3BwWFhYar+bm5rh06RIOHz4sfr5Dhw6YOnUqpk2bhhdffBGXL1/G+fPnIZfLYWBgIL423o6NjUVlZaXGcXh6eiIkJAQTJkzA119/jbNnz4rXxpOv2dnZiIuL04jfuXNnhIWFISwsDD169ICfnx8cHR1bDBEREfj9998hkUgwfvx4zJs3D6NHjxbXsvXo0QNeXl7imkkLCwuN7eLiYnz88cca1+bkyZMxY8YMsU6cOHECxsbGsLW1FetT4+3NmzcjNjYWAGBhYYHJkydj9uzZGDhwIARBwL59++Du7i6WvbqdVW9LpVKsWLFCzINMJsPo0aMxbdo0BAQEwNTUFGPGjEF2dnaTc6EOKSkpuHPnjkZZ2tvbIygoCCEhIZBIJFiyZEmz7ay6rTt58mST2c7evXuL7e3333+PmzdvNmln1dsXLlzAhx9+KJbD1KlTERkZCXd3dwiCgEePHsHd3V3jelL3HeqwbNky8UkAS0tLTJo0CbNmzcKgQYMgCAI+/vhjpKWlwdTUFGZmZjA1NRWDmZkZ8vPzsWPHDo2y9PPzw5QpUxAYGAhjY2N4eHjA0tKyxaBePw40PAEwcuRIhIeHIzg4GGZmZoiOjkZycrJGHHUfbGlpifr6erz11lsa52Hq1KkIDw/HgAEDIAgCTp06haqqKo24jdP46aefcPz4cTGNYcOGITw8HKGhobCyssKpU6eQkJAAW1tb2NnZia/qbXNzcwQFBYnX58CBA/Haa69h8uTJ4tpC9dMEjYP6fNrZ2SEuLg7r1q1r8XzevXsXHh4ezbbV6vP5xhtvICsrC0DD0wMzZszArFmz0Lt3bwBASkoKHj16BENDw2ZDXl4eTp48qVEnnZ2dERoaitDQUPTp0wcjRoxo0r41Dtu2bdN4Ysnd3R3Tpk3D5MmT4ezsjO+++w51dXVwdHSEg4NDkzamvLwc3t7e4rmcPXs25syZg27duolpjhw5UpzJd3Z2Fttq9fYnn3yCb7/9FoIg4NVXX8Xrr7+u0U45OTmJT06ZmJiIr+ptmUyGqKgojXLo2rUrJk+ejEmTJuHFF19EeHg48vLyWmwr9+7di48++ghAQ/8wf/58TJ06Febm5gAafj/B09Oz2b7PxsYGVlZWiIyMFJ+Cc3JyQnh4OGbOnCmez7t376KmpkZsZ58Md+7cwfbt2zXO5dSpUzFjxgy4ubkhOzsbZ86c0bgWntxes2YNUlJSADTc1wUEBCA8PBxjxoyBgYEBVq9ejYcPHzZ7P2ZkZISSkhKNvg8AOnXqJN7L9OvXD/3799e4d5FKpRr/TklJQUFBgUYacrkcI0aMQFBQEMrLy7F9+/Ym90DqtJRKJa5evYonOTk5ISAgAIGBgVi/fj2Ki4vFa0Hdd6pDYmJikxnXfv36ITQ0FGFhYUhPT8ebb76p0U+o23t1OHbsWJOZeE9PT0yYMAHBwcHYuHEj7ty5I7YrjdsbW1tbnDt3TmwjjIyMEBoaitdee018miQtLQ1eXl5wdHSEk5OTxqt6e9y4cbh16xbkcjnCwsIwf/58DB06VK91t/922o5w/4rQ1mdcn0alUpGrqyt17tyZPvzwQ0pOTtY5jdOnTxPQ8O3w6tWrKTU1Vec0/P39ycnJid555x26efOmzvEzMjJILpcTAHrhhRfovffeo0uXLmm1vkdt4cKF5OrqSps2bdJp7ZxaRUWF+M1Zly5d6K233qL4+Hid8rB582bx28C5c+fSb7/9RnV1dVrHVyqV1KNHDzIwMCB/f3/avXu3VuukGjt+/DgBDTNgERERdOzYMa3WOjemXsvg4eFB69at02lNCBFRamqquNbIwcGB5syZQ0ePHn3q+sMnzZw5kzp06EAffPAB3b9/X6f9ExHl5uaSkZERjR49mvbs2aPTvtVWrVpFVlZWtGDBAkpISNBpXQpRw3rhbt26id/KRkZGUkxMjNZrlYiIoqOjadCgQRQdHa3TmhY1lUpFHh4eZGlpSZGRkXTmzBmd6jQR0bVr1whomLUYNmwYbdy4Uac1z0Qkzlx16dKF3n33Xbp8+bJO5fnw4UNq3749rVixgh49eqTTvtXeeecdcRbryJEjWq2jbKysrIysrKxo5MiR9MMPP+i1FkfdRgwdOpS+/vprys/P1ym+SqUid3d3AhrWyC5atIjOnDmj0xryc+fOid92e3p60qeffkp37tzRKR+jRo2iYcOG0c6dO3VeH0vU8JsCEomExowZQ3v27NGrbr/xxhsEgLy9vWnz5s06l2VhYSEZGxuTq6srrVu3Tqs1yk9au3atWKeOHj2qc52qra0lFxcX6tatG61atYoePHigcx7++c9/kp2dHS1ZskSv/peIyMvLi7y9ven777/Xq15fvHiR5HI5hYWFUUxMjE79ntrs2bPFer148WL6448/dGqrMjMzSSaTUefOnen999+npKQknfOwdOlS8vHxob179+rcbxIRVVVVUa9evWjp0qU695tq0dHR4iza22+/rXNbqW7zZ8+eTZcuXdK53yJqWONqaGhIkyZNouPHj+t1Pv39/cnMzIxmzZpFcXFxOv/ORXJyMgmCQEOGDKEtW7bo/LsnRA1tPv41s/r222/rXB6VlZXk4OBAQMNTf9OmTaP9+/frdF+2c+dOjdnFZcuW6XR/q1Qqxd8dGTBgAH366ad07949rfdPRBQXFyf24d7e3nr14cOGDSNPT0/avHmzTutj1a5du0bdunWjdevWPfM3EP5doMOM618+OH1a+G8euCoUCjp79qzON6KNHT9+XOcf92isrq6OTpw4oVfDprZz50765JNP9Opo1O7cuaP3MRA1lMN1Y3nqAAAgAElEQVTy5ctbVRbr1q3TebDaWEpKCm3fvl2vBlpt27ZtFBMTo1enS0RUUFBAa9asoZSUFL3z8OWXX9J7771HFy5c0KtuqlQqOnfunM4dXWOpqak6/7jWk37//Xe9BryN4y9ZsoR+//13vY+lNXWBqOF8Hjp0qFXH8c0339DmzZt1+kGmxsrKyuiDDz6gK1eu6H1tKRSKVrUxREQ//vijXh2uWmZmpt43o2oHDhzQ68tBtVu3btG7776r8xd7ja1du5a++uorvb8AUCqVOt84PenmzZt6DRTV6uvr6ZtvvtH7GIga+ow///yz1f1Gax5xy8zMpPPnz7cqD7dv39a7vSciqqmp0etL78Zu3ryp1xfGauXl5bR06VK9+wwiooSEBIqPj29VWebm5uodl6hhoNOac0FEtHXrVp2/NG+stra21Y9dXrt2rVV9T3V1Ne3bt69VP7Tz559/tqpe1tXV0UcffaT34J2I6PDhw/T//t//o7i4OJ2/lCJqaCsjIyPpiy++0Pue6tatW7R27Vq9vsBXW7t2LW3dupVycnL0il9bW0uJiYl675+o4YvC1oxVngddBq7840yMMcYYY4wxxv7jdPlxJt3/A0PGGGOMMcYYY+w/iAeujDHGGGOMMcbaNB64MsYYY4wxxhhr03jgyhhjjDHGGGOsTeOBK2OMMcYYY4yxNo0HrowxxhhjjDHG2jQeuDLGGGOMMcYYa9N44MoYY4wxxhhjrE3jgeu/yb1795CTk6N3fCJCRUVFq/KQlZUFhULRqjRaq7q6GkqlslVp1NfXP6fc/HWUSiWysrJalUZ6ejoKCgpalQYRtSp+XV1dq9OIj49v1bWRm5uLuLg4lJSU6J3G1atX8fjxY73j19fXo6ysTO/4z4NKpcIff/zRqnaiqKgINTU1rcpHUlIS6urq9I6fkpKCLVu24PLly6iurtYrDZVKpff+gYbz2dp25vjx49i3bx/u37+vV35qa2uxZ88e3Lt3T+/juXbtGn799VcUFhbqFZ+IEB0djfPnz6OyslKvNCoqKlpdlj///DMuXLiAqqoqveKXl5cjLy+vVXlobTtXU1ODP/74Q+9jeB55eB4yMjLw8OHDVuUlLS2tVddobm4uLl26hNraWr3TaG1Z1tfXt7qtTEhIQEJCgt7pEJHe1+XzQkTYvn074uLi9L6/zM3NxYMHD1p1To4fP44rV660qk60VmvbOSJqVd8JtL7vIyIcPnwYKSkpbaK90YZ05cqVf3UeWrR169aVc+fO/auzoZesrCz07NkT0dHRuHLlCvLy8iCXy2FnZweJ5NnfFwiCgFmzZmHDhg1IS0uDIAhwdHSETCbTOg+lpaXo3r079uzZg1u3bqGkpARWVlawtLTUOo2NGzdi//79kMlkaN++PaRSqdZxgYabmP79++PMmTMoLCyEubk5bG1tIQiC1mls3boVS5YsQUZGBgwMDODk5KRVGarV1dUhLCwM169fh1wuh7Ozs87Hce7cOaxduxaCIKBDhw4wMDDQKb5EIsH06dOxfPlyJCYmori4GFZWVrCystI6DYVCge7du2P37t24ceMGioqKYG5uDmtra63Lc9myZfjhhx9QXV0NJycnmJiY6HQcBQUFGDx4MP78809UVVXBwcEBpqamOqVx6tQpDBs2DNHR0UhISEBWVhakUins7e21Oi8mJiaYOnUqFi1ahP379+PatWvIzc2FgYGB1tfXvXv30L9/f2zbtg0XLlxARkYGBEGAvb29VteYIAgYM2YMtmzZggcPHkClUsHR0RFyuVyrMgCAy5cvY968eVAoFLC1tYWNjY3WcdV5+OKLLzBhwgQcOXIEt2/fRmlpKSwtLbW+xhUKBXr27IkTJ07g0aNHkEgkcHBw0Kmd2bFjB8aMGYOTJ08iNTUV9fX1cHBw0LosrKyssGTJEixfvhxr167FoUOHkJCQgMePH0OpVMLGxuaZae3cuRPvvfce8vLyYG5ujnbt2unUxhARfHx88PPPPyM/Px9mZmawt7fXKQ2ZTAY/Pz9s2LABGzduRGxsLG7evImCggIYGBjAxsbmqXVTKpVi+/btmDFjBjZu3IiTJ0/izp07KC0thbm5OczNzZ+ZHwMDA/j4+GDVqlXYtWsXLly4gPT0dCiVStjZ2T2zHAVBwPnz5xESEiKei8uXLyMzMxNEBFtb22fWjYqKCvTt2xcnTpxAVlYWjIyM4ODgoFObnZycjFGjRuGzzz7DTz/9JF7jUqlUq2tcIpFgyJAhiIqKws2bN1FaWgpra2ud+r4jR45gyZIlKCwshJWVlc79lkwmw1tvvYVZs2YhJiYGt2/fRllZGaysrGBhYaFVGteuXUNYWBgyMjJgZGSkc98HAMuXL8eRI0cglUrh4uKi07UNNNycu7m5YdOmTbh48aLYXrdr107rfvS7775DQEAAzp8/j6ysLBgYGOhUJ4yMjPDqq6/inXfewfHjx3Hnzh2xLM3NzbVKY+/evVi2bBkUCgVsbGx0bm8BwNfXF3v27NG7XldUVMDT0xNr1qxBTEwMEhMToVAoYGJiolU/LggCZs6cia+++gqPHz+GVCqFo6OjTvczqampCAsLQ3Z2NszNzeHg4KBTvRYEAYmJiQgJCcG6devw/fff448//kBqaiqqqqpgbW0NY2Pjp6YhkUjg6emJdevW4eLFi8jMzIRMJtOpTt2/fx/Dhw/HunXrxLIsLCyEoaEhbGxsnnlMSqUSr7/+Oh49egQHBwed7sXUjh07hilTpuDhw4cAAGdnZ52vr9DQUPzwww/Iy8vTq9+5efMmAgICkJ6eDplMBicnJ53qgyAIOHz4MIKCghAVFYUzZ87g/v37qKqqgpWVlc73d/patWpV9sqVK7dq9WEiarPhpZdeov8mVVVVlJ2dTUlJSRQfH0/e3t4EQCNYWFjQ6NGjadWqVRQXF0dlZWXNpqVSqejGjRskkUjEuEZGRuTr60uffvopXbx4kerq6pqNV1ZWRpmZmZSUlETTp09vkodOnTrR9OnT6dtvv6WkpCRSqVQtHtPjx49JLpcTADIzM6Pg4GDatm0bZWVlaVUmSqWS1q1bp7F/Z2dnmjFjBv3jH/+gR48ePTONmpoa6tKli0YZBgYG0v/8z//QvXv3npp/tZ07d2rEDwkJoe+++44yMjK0Po6+ffsSADI2NiZ/f3/69ttvnxlfpVJRRUUF5eTkUExMTLPnIjw8nLZv304pKSlNjqW+vp4UCgU9fPiQ/vzzTwoMDGyShqOjI4WGhtLGjRvpypUrzdYLtdTUVDIwMCAAJAgCeXl50YoVK+j8+fNUX1+vVVmsWLFCY/8DBgygd955h2JjY6mysrLJ5+vr66mgoIDu3btHFy5coCNHjpCdnV2T4zA2NqZhw4bRu+++S4cPH6acnByxDEtKSujBgwd06dIliomJoSVLljSJD4BMTU1p+PDh9Pe//50OHz5MBQUFYhpFRUX04MEDunz5MsXGxlKfPn2axJfL5TR48GB688036eDBg5SZmdnsOa2srGxyPg0MDGjo0KH0wQcfUFxcXLNl8SRfX18xfo8ePWjRokV0/PjxFuPW19dTYWEhpaSkUEJCAu3du1ejjVAHFxcXCgsLow0bNtClS5eopqamyTFUVVVRfn4+vf76603Ow8iRI+njjz+mc+fOUXV1dZN81NbWUn5+PqWkpND58+fJ0tJSIw2pVEovvfQS/e1vf6ODBw+K55KIqKysjJKTk+ns2bO0d+9e2rBhA4WEhDR7PtX1tHfv3rRgwQLKzc1ttlxqamqoa9euYhwnJyeaOXMm7d69u8U4Tzpy5EiT62ratGm0Y8cOSk9Pb1J+BQUFdPPmTTpx4gRFR0fT2rVrydXVtcXjMDU1paFDh9KmTZuorq6OVCoVKRQKunv3Lv3+++908OBBWrt2bYvxHR0dKSAggD7++GO6efMmERFVV1fT48eP6erVq3T8+HGKjo7WqFONg0QiIVdXV4qIiKBvv/2WKioqSKlUUn5+Pt26dYvi4uJo9+7dtH79ejI0NGw2DZlMRgMGDKA5c+bQmTNnmpShur1bvny5RjwrKysKCAigDRs20I0bN0ipVGrEKS0tpfv371N8fDz9+OOPtGXLFmrXrl2zeTA2NqYhQ4bQ3/72N4qJidFoM+vr66moqIgePXpEmzZtahK3c+fOFB4eTtu2baPk5OSn9h1KpZL69eun0VbPmzePfvzxRyopKWk2Tl1dHeXl5Ylt3ebNm5s9ho4dO9KkSZNo06ZNdPnyZaqtrW0xH0FBQRrlGBoaSlu3bm1SJ1ty+/ZtEgRBrIMBAQG0ZcuWp8avq6uj/Px8Sk5OpoSEBIqIiGhyDCYmJjR8+HB6//336dixY1RUVKSRhrouZGdnU2JiItnY2GjENzMzIz8/P1q9enWz7UxlZSU9fvyYbty4QadOnaI333zzqWW5cePGZts6tdraWurevbsYr2vXrvT666/Tzz//TKWlpc8sR5VK1aTNt7KyoqCgIPrqq6/o1q1bTepTXV2dePwnT56kffv2kZeXV7PHYWtrS2PHjqUVK1bQsWPHmq0TKpWKbt68qdHmm5qa0pgxY2j9+vV07do1jWurJTNnztRoK2fNmkV79+6lwsLCJp+tr6+nnJwc+vPPP+n48eO0Y8cOWr16NZmYmLTYVnXu3JlCQkIoLi5OIx2FQkGpqal07dq1ZvtwdZ364IMP6Pjx41RcXCzGr6iooIcPH9KlS5fo6NGjtGPHDnJ2dm52/5aWluTr60vLli2j2NjYFq/zxtfniy++SEuXLqX4+Hit74VUKhUNHTpUTEN9j/7ZZ5/R1atXtToXly9f1si7g4OD2O9oc39MRDR58mSN68rf35+ioqKavT9WjxFSU1PFsvz222/F+/wnQ9euXWny5Mn05Zdf0vXr17XKjz4AXCEtx4YCteGpYQ8PD7py5cpfnY0WBQcHIzk5GUVFRSgqKtL5MbdevXqhrq4O5ubmqKqqQmVlpRi0ebzIwsICtra2MDAwQG1tLUpKSlBaWqrTo7nm5uawsbFBhw4dIAgCiAgqlUojJCUlNft4iru7O1599VUoFApcuXIFVVVV4nGoX7Upk65du6KmpgaOjo7i4zjV1dUar1VVVS0+xtChQwd07doVhYWFsLS0FB/7UyqV4nZNTY34rdiTXnzxRYwdOxaXLl2CIAhiOQAQLxQAePjwYbOPlw4YMADjx4+HnZ0ddu/ejbKyMjGUl5frdD4cHBxgYWGBmpoaFBcXo7S0VOu46vgmJiZwcHCASqVCXV0d6urqUF9fL75mZmY2+4iLtbU1Ro0ahZqaGmRkZEClUqG6uloM6vNRXV3d4uMphoaG8PDwwKNHj2BgYICioiIUFxfr9AiKubk5XF1dkZeXh8rKShQUFOj0OI0gCPD19UV6ejqISLw+dTkPcrkcHh4eUCgUMDAwQEVFhUbQ5njkcjkcHBzE2Ud1XWxcPwsLC5t9/NvIyAjDhw9Hr169EBcXh8rKSigUCpSUlOhUlpaWlujcuTNqa2uhUqlQXl4uBm3Lw9DQELa2tjAzM0NZWRlKSkp0flzNxcUFQMNTILo+Yu3u7o558+Zh165dUCqVqK2tFUNNTY24XVJS0mI9GTBgADp06IAHDx5ALpeLbVXj8KzHvnr06IHKykoQEQoKCnR6RE0ikSAgIACenp44cOAA8vLykJeXp9OjZlKpFP7+/igvL8ejR4+Ql5eH4uJireMDQPv27TF+/Hj88ccfUCgUOudBLpcjJCQExsbGuHXrlsY1oe67tKmf1tbWMDAwgFwuR0FBgc5958svv4wePXrgxo0bKC8vR1lZGUpLS3V+bN7Z2RkuLi4QBEFsKxsHhULRbJoymQyDBw9Gx44dcfXqVVRXV0OhUOjcXjs6OqJdu3YwMDCARCIR63JdXZ24XVZW1uJx9erVC+7u7rh586Y4i6tUKsWgUqmgVCpx9+7dZq8NV1dXjBs3Dmlpabhz5w6Ki4tRVFSE8vJynY6jQ4cOABra7vLycpSWlqK0tFSnxxhtbW1hbm6Ouro6FBYW6lwn3N3dUV5eDisrK/ERzCdDYWFhs/dWBgYGGDJkCFxcXHDr1i1IJBKNezFt78kcHBxgYGAAmUyGkpISFBUV6XQMdnZ2GDlyJO7duwdBEMT9Ns7Ds8rUxsZGbK+NjIw0+n71dmlpKfLz85vElUgk8PLygru7u7gcJy8vT6fzaGJigmnTpkEqleLChQsoLi4W72V06bvUTz8ZGBigsLBQ52vbzc0N7u7uSE1NFWcgG9/XAQ3LMy5cuNAkrp2dHcaNG4fx48fjH//4BxQKhcb9T+Pt6urqFo/L1tYWffv2RXZ2NiwsLFBdXY2qqioxnnr7aeXSs2dPGBgYiPXqyX6vtrYW5eXlLdbPzp07Y8CAAbhx4wZqa2v1am+9vLwQGRmJSZMmaf2Eg64EQbhKRB5afVjbEe5fEdr6jGvv3r1b/Gbbxsam2VklJycnevfdd+n27dsUGxvb4jdWzwqDBw+mTZs20YgRI1r8jEQiIVNT02a/NQ8ICKADBw7QjRs39M4D/vWNY48ePfSKK5fLKTAwkL7//nu9929qakqTJk2iGTNm6J2GVColHx8fsrCwaFVZNJ4V1iXY29vTwoUL6cKFC/Tyyy+3+DljY2OysrJqtgzCw8MpLi6OLl68qHf+BUGgoUOH0ksvvaR3/JdffpnWrFnz1PrStWtXsrW1bfKej48P7dq1iyoqKprM6qqDpaUldevWjTw9PZu817FjR1q5ciWlpaURETWZBVQHc3Nz6tSpEzk6OjZ5z93dnaKioqigoIB27NihVzkYGRlRaGgoHTp06KkzcM8K1tbW5Ofn1+L76uMwNjZuch78/Pxoz549VFlZ2ewsvTahe/futHz5coqLi3vq50xMTJqdoevQoQMtXbqUkpKSmp0tsbe3Jzc3Nxo9ejRNmTKlSRnOmjWLLl26RCqVilQqld7lKJFIaPjw4U+d1X1WGDRoEG3YsIE6deqk8XeZTEbt27cnT09PCggIaPKUjZOTEy1fvpweP35MRERHjx5tNn/t2rUjV1dXGjFiRJN2qEuXLrR69WrxKZfmZlRNTU2pS5cu5OXl1WRGRyqVUmBgIMXExFB9fT3dunWrSXyZTEYuLi7k7u5OY8eOpfbt22u836NHD1q/fj3l5eUREdHs2bP1rtORkZHNlgMAsrGxoV69etErr7yiMYOufm/x4sV0+/ZtIiL65JNPnrovmUzW7N979+5Nn376KaWlpTWZBdQlvPDCCy1eW4IgkLW1NXXr1k18wkUd5HI5hYaGUkxMDNXV1ZGHh4feeejTpw/NmjVL7/hAw0zy0/pwc3NzcnBwaPJ3MzMzioiIoLNnz1JGRsYz99PckyEWFhY0e/ZsOnXqFL3zzjvNxpPL5eTk5NTs/ZatrS397W9/E2eCnixrXYKbmxu9+uqresUVBIF8fHxoy5Yt1LNnzybvGxgYkLOzM7m5uTU5DnV7vX//fqqurqZff/1V72Pw9PSkzz//nF555RW907C2tqbg4OAmfzc0NKROnTrRoEGDKCgoqMn9jqurK3399dfiLOmCBQta3IeJiUmzT1TI5XIKCwujo0ePUkVFRbNxLSwsqFu3bjR48OAmbYSpqSlFRkaK/cbTnmDRtiye7F+1DYaGhhQYGEiLFi3Se/+9evWiFStWUP/+/fVOw83NjebPn9/se+bm5tS1a1fy8vJqck9mbW1NixYtohs3bvxHxlPgGdf/jCNHjqCurg5WVlawtrYWg7m5OSQSCV5//XVs2bIFhoaGCAoKwqxZs+Dr6ys+A5+VlYUTJ07A2NgYJiYmTUJ9fT08PDzE2Q13d3dMnjwZEydORKdOnQAAJ0+eREFBgbiurXEwNTXFl19+ibfffhsAMHDgQMyYMQOTJk2Cvb09AKC4uBj79++HRCKBIAiQSCQaQRAELF68WOPbuU6dOiEwMBCBgYEYNmwYrly5gvv378PExEQ8lsavZ8+exZw5cwA0fFM9atQoTJo0CUFBQbC0tBQX+xsaGsLIyKjZ17lz5+Ly5csAAFNTU/j7+yMsLAxjxoyBiYkJEhMTkZCQAJlMBplMBqlUKm7LZDI8evQICxcuFI/ByMgIo0ePRnBwMMaPHw9bW1vs2rULlZWV4vqCxq+CIGDnzp34448/xDQMDQ0xYsQIBAQEYPz48VCpVDhz5oy4Hu3JUFlZiS5duqC2thYmJiYICgrCtGnTMGrUKHHNbGxsLEpLS8X1r5aWluKroaEhli9fjo8//hiCIGDEiBEIDw/HhAkTYGZmBqBhDerhw4c1vqFr/CqRSDB58mRxpkYmk8HHxwcTJkxAYGAgnJyccPbsWaSlpcHIyEjjPKhDbGws3nvvPbFshg4dirCwMISEhMDFxQUqlQq7du2Cra2tuHbT1tYWVlZWkMlkICK4ubnh1q1b6NixIyIiIjBz5kx06dJFLNtbt27h7t27sLOzE0PjtY5xcXEYNWoU5HI5goKC8Nprr2HkyJEaazsOHDggrndR58Ha2lpMw9/fH0ePHoWdnR2mT5+OiIgIuLm5ifFTUlIQHx8PU1PTZoNCoYC7uztUKhWkUin8/PwwZcoUBAYGirMfhw4dQnFxcZM6qd6Ojo7GoUOHxH26uLggKCgIwcHB8Pb2RklJCX799VfxGKytrWFjYwMrKysYGBigtLQULi4uKC8vR48ePRAREYEZM2agffv2YpqnTp1CTk4OzMzMxGBubi5uf//991i8eDGAhhmgyZMnY+rUqfDw8IAgCKiursa+ffs02hZ1nbSwsIBUKkXPnj3x4MEDmJmZITQ0FOHh4XjllVfE9V83btxAWloanJyc4OTk1GQN7IEDBzBx4kT07NkT8+fPx8yZM5usQdu+fTtkMhnkcjnkcjkMDQ3FbblcjjfffBOXLl0C0DA7OWLECISGhiIoKAjt2rVDUlISEhISYGxsDGNjYxgZGYnbxsbGyMjIwJgxY8T9eXp6YuLEiQgLCxPb22PHjkEqlYrHYWtrq7HGbfr06di9ezd8fX3x+uuvw9/fX2M9fE5ODs6ePYt27dqJwcbGRqy3OTk54tMvQUFBmDt3LkaMGKGxj9OnT6O8vFwjjcbrkNRtRKdOnTBnzhxERETA2dlZfL+iogK//PKL+DSAo6MjrK2txX3U1NTAxcUFpaWlCA4Oxrx58zB8+HCNPMTHx+Phw4cwMTHRuCbU/46NjUVkZCSAhvY6MDAQU6ZMgZ+fn3jed+/eDXt7e/EY7O3txbIiIvTv3x+JiYl45ZVXMHfuXEyYMAFGRkZiHm7evInExERYWFjAwsIC5ubmGts3btzA4MGDxXo9ZcoUTJ8+HQMGDBDb9l27dqG+vr5Je6kOa9euxcmTJ8V9uru7Y8KECZgwYQJ69+6N9PR0nD9/vsn1aWlpCalUivT0dHTt2hUqlQru7u6IiIjAlClTYGtrK6b5888/o6ioCHK5XJyFbhy2b9+O6Oho8fP9+/dHSEgIQkJC0Lt3b+Tk5OCXX36BVCqFVCqFRCLR2AaA2bNna8xY9e/fH4GBgQgKCkK/fv3wxx9/IDs7W7yHUd/TWFpaQiaTYfPmzViwYIHY78ycORMTJkwQ611NTQ327NnT7HmwsLCAqakp3NzckJSUBJlMhnHjxmH69OkYP368uB7y+vXrSE5O1ugzbG1tYWJiAkEQEBMTg/Hjx0MikWDs2LGIiIiAv7+/RjuyY8cOCIKgcQ4bh+XLl+P8+fPi5728vBASEoLg4GB0794d9+7dw8WLF5vcx6i3c3Nz4e3tLcYfOnQoJk2ahNDQUDg5OQEAYmJioFKpYG9vD3t7e9jZ2cHCwkKsc3PmzMG2bdvQoUMHzJ49GxEREWL7AjTcF8bGxrZ4P6VUKjFw4EDxvrBfv36YNGkSJk6ciG7dugFo+OEi9VpidZ/TePvnn3/Gt99+K+7T2dkZQUFBmDBhAry9vaFUKnH48GE4OjrC0dERTk5OsLS0FI+hrq4OHTp0QHFxMcLCwjB//nwMGTJEY21mQkICHj58KNYl9T2NlZUV5HK52OYDwKBBgzBz5kxMmjQJ1tbWYhp79uyBtbW12EbY2dlptAFeXl5ISEiAp6cn5syZg8mTJ2vMCF6/fl3sE5q7r8vMzMSTv/PTs2dPBAQEwN/fH0OGDMHBgwdRV1fX5F5Ivb1y5Ur89NNPABruCceOHYuwsDCMHz8eFhYWSEtLw+nTp8X+pvG9lLGxMSoqKvDKK6+IT7707NlTPJ99+/aFIAg4cuQICgsLW+z7oqOj8d1334nH4OHhIbYRPXr0QElJCWJiYsQ6qa6XhoaGAICqqio4OzujuLgYPj4+iIyMbNLe/rvxjGsbUFxcTL6+vrRlyxZSKBR6pbFhwwZydXWljz/+mJKTk3WOX19fTz4+PvT+++/T3bt39cqDelbY3d2dVq1aRdevX9dqTWljvr6+NHLkSPruu+/ENYe6SExMJHNzc5oyZQr9+OOPWq0dfNK8efPIysqKpk+fTocOHaLy8nKd4hcWFpK5uTnZ29tTREQE/fjjjy2uT27J6tWraezYsfTDDz/oHJeoYT3b8OHDac2aNVqvfXjS3r17ycjIiIKCgig6OrrZNS1Po1KpaODAgfTyyy/Tpk2btF4j3Njly5dp6tSpFBcXp9UakOasXLmSNm7cqFd9ImpYux0YGEiHDh1qcU3Us7z77rvk7e1Nmzdvpvz8fJ3jV1RUkL29PfXq1YuWLl1KCQkJOl9b33//Pc2ZM4fi4+N1jkvUsI7P09OTZs+eTXFxcVqv7Wns+PHjNHr0aNq9e7fO15Xa5s2bKS4uTq9jICK6e/cuGRkZ0auvvko7duzQq17Mnz+f3N3dae3atZSamqpz/JqaGnr//ffp3r17OsdVO3DgAK1bt07rdblPUvpdyeUAACAASURBVKlUtGjRIoqNjdX72rpw4QKtWbNGY12yrnx8fCgoKIj27dtHFRUVOse/f/8+vfXWW3r3W0REkZGRNGPGDIqNjX3quv+WZGVlkbGxMQ0dOpS++OILevjwoc5pfPnll7R48WK9Zy0qKyvJ0dGRvLy8aN26dfTgwQOd09i1a5f41MHGjRt1Pg6VSkXBwcG0evVqrdfVPum3336jIUOG0DfffKNXW0lE9Oabb9LatWub/d0BbTx48IDkcjkNHz6coqKixKcgdLFo0SJxVlOfPriiooLCw8Pp+PHjerW1RA11qnfv3rRq1Sq9ro/6+nrq2bMnde/end599126ePGizm3FtWvX6PPPP9f7XBIRTZ8+nZYtW6b3NZ6amkpvvPFGq9ZdLly4kKRSKb3yyiv0+eef69x25+bmiuucd+/e3eLa96f56KOPqHv37vT+++/TjRs3dO4Dq6urqX379jR48GD6/PPP9WqnYmNjaenSpXT//n2d4z4v4BnXvx4R6fTLYM3Jzc2Fg4OD3vGVSqU4i6qv+Ph4dOzYUVzDok8eCgoKWnUcGRkZsLW1feYv1bWEiHDu3DkMHjxY518DVlP/YuvAgQN1/kVitaqqKr2PAWgoS/UsuL5u3LiB7t276/1LcTU1NSgoKBDXLOrjeVwbrfU88lBUVKTx7bCuMjMzUVZWhl69eumdRmuPo66uDkqlslXfrNbX1+v8S4rPW1pams6/GvukjIwMjZlqph+lUony8vJWnYvnoaamRpxR0EdaWhoMDQ3FmTR9tPb6zM/PR3V1td79L9DQh/fq1UtjllcX6nvE1hxHa8+FOh+tyUNqairMzc3Fp830kZOTA0dHR73jPw85OTk6/xJwYwqFAllZWeJs3l9FpVK16t70eez/xx9/xIgRI/T6hWkAyMvLg5GRkda/Et6c9PR0dOzYsVXns7Ky8r++79JlxpUHrowxxhhjjDHG/uN0Gbhq/XWHIAg7BEHIEwThVqO/rRcE4a4gCImCIBwWBKHZ/whJEIQ0QRBuCoJwXRAEHokyxhhjjDHGGNOaLvP0OwGMeeJvvwFwJSI3AMkAlj4lvg8R9dd2RM0YY4wxxhhjjAE6DFyJ6HcAiif+doKI1P8J3EUA/90PWTPGGGOMMcYYa3Oe58ro2QCOt/AeATghCMJVQRDmPsd9MsYYY4wxxhj7X+65/BSkIAjvA6gHsLuFjwwloixBENoB+E0QhLv/msFtLq25AOYCQMeOHZ9H9hhjjDHGGGOM/Rdr9YyrIAgzAYwHMI1a+IliIsr612segMMABraUHhFtJSIPIvJozc+WM8YYY4wxxhj736FVA1dBEMYA+Pv/Z++8w6JIun//nRlmgCHnJCqoKyqCimJgBRFBCYqCoAiKAQO7rptc85pd1zUHzDlhzlnWsGZMGBAwYEAk5wwzc+4fvtOX2QGdafZ31997+/M85+lS55yucOpUdVdVC6AfEZXX8xsdHo+nJ08D8AHwtK7fcnBwcHBwcHBwcHBwcHD8HXX+O5xYALcAtOTxeO95PN4oAGsA6OHj9t8EHo+3/j+/tebxeGf+o2oB4DqPx3sEIB7AaSI694+WgoODg4ODg4ODg4ODg+O/FnW+KhxGRFZEJCSiRkS0hYiaE5Htf/6bm3ZENO4/v/1ARH7/SacSkfN/pA0RLfifKsyXRFJSEhISElDP7unPQkTYtGkTbt++DYlE8nmFOkhLS8OdO3cglUpZ6QPA/fv3UVxczFo/KSkJrq6uiIqKwrp16xAfH4/Kykq1bMyZMwcDBw7EokWLcOnSJRQVFamlX15ejtWrVyMhIQEymUwtXTlXrlzBgQMHkJ2dzUqfiHDw4EGkpaWx0geAixcvYtiwYYiJicH9+/dRU1Ojto2VK1fiwIEDyMzMZJWHgoICPH/+nLVfA8DDhw+Rm5vLWr+srAxHjhxBQUEBaxtXr15FXFwcKioqWOlLpVLs2rULr1+/Zp2Hy5cv4/fff8fNmzdRXV2ttj4RYd68edi5cydev37Nqk0SExOxdOlS3Lt3j3WcuXjxIpKTk1n7REZGBubMmYPLly+jvLzOjTufZdu2bVi0aBGuX7+udnwBgMLCQgQHB2PmzJk4ffo0K/98+fIl3r59q7aeHCJCTEwMrl+/zsofAODChQvo2bMnJk2ahIMHD7Lyizt37qgdY2uTlJSE4OBg/PHHH/jrr79QVlamto2LFy8iPj6e9dhVXl6O2NhYZGVlsdIHgNevX6OwsJC1fkVFBcLCwjB16lQcP36cVcw9duwY/Pz8MGvWLJw6dUrt8hAR5syZg40bN+LZs2esY8SMGTNw/vx51nOB/fv349y5cygtLWWlX1RUhL1797IetwDg3r17SEpKYh2nqqqqsHTpUty8eZPV2AsAJ06cwM8//4zDhw8jIyNDbX2pVIro6GjMnTsXFy9eZNVPHzx4gPnz5+Pq1ausx7/4+PgGjb/Jycno3r07JkyYgF27diEpKUntudmiRYsQHR2N7du3Izk5WW39qqoqHDt2rEF9fN26dfDy8sLkyZNx4MABvHr1Si3/qqmpwffff4+YmBg8fPiQVbxLTk7GhQsXWLclANy6datB8/z/5xDRFysuLi70v5WsrCzS0dEhCwsLGjp0KO3atYuysrLUsrF69WoCQHp6euTv709LliyhBw8ekFQqVUm/srKSbG1tydjYmEJDQ2nLli30/v17tfKwe/du0tDQoB49etCiRYvo8ePHJJPJ1LLxyy+/ED5+WZoAkIaGBjk7O9PIkSMpJiaGbt++TeXl5fXq5+TkkLGxsYKNr776isLDw2nFihV048YNKisr+2QexowZQwDI2NiYgoKCaPXq1fT06VOVy5KVlUV6enoEgNq0aUPjx4+nw4cPU25ursr1MHPmTCbv3377LR07dowKCwtV1pdKpeTq6srUgZaWFn399dc0ceJEOnToEKWlpX3WxtGjRxXqMCoqinbu3Elv375VKQ8SiYQcHByoWbNmNGHCBDp37hxVVFSoXAYionPnzhGPx6POnTvT7Nmz6c6dOySRSNSyERgYSHw+nzp37kwzZsygq1evUlVVlcr6qampJBQKSVNTkzw9PWn+/Pl069YtqqmpUdnGzz//TADI3t6exowZQ/v376ecnByV9cvLy8nW1pZpSw8PD5oxYwadP3+eiouLVbKxd+9epj1tbGxo8ODBFBMTQ48fP1YpTkilUurQoQMTZ3x9fen333+nW7duUXV1tUp5OH78OAEgW1tbGjlyJMXGxlJ2drZKunKCg4MJAAmFQurWrRtNmTKFzpw5Q0VFRSrpv3v3jrS1tQkAiUQicnNzo0mTJtGJEydU7qOLFy9WiDH29vYUFhZGK1asoNu3b1NlZeUn9dPS0khTU5Nat25NP//8M8XFxX1W5+8sW7aMAJBYLCZvb2/67bff1GoLmUxGffr0USiHsbEx+fj40PTp0+no0aOUlpb2ybi3ZcsW0tDQIHd3d1q4cCElJCSoHfMjIiKY+wsEAmrXrh2NHTuWtm3bRklJSZ/1zVu3bhEAMjQ0pKCgIFq7di09f/5crXwMHjyYAJCTkxP99NNPdObMGSotLVVZPykpiUQiEbm7u9OiRYvUGi/kbNu2TaEtGjduTCEhIbRkyRK6du3aJ8c9oo/9s2vXrgo2bG1tKSgoiBYuXEhxcXGfHUNqx3wTExPq168f/fHHH3Tz5k2VYqZMJqPu3bsTAOLz+dS+fXuaMGECHTx4kDIyMlSqh6tXrzJjf9euXWnatGl08eLFz47btfH39ycA5OjoSD/88AOdOnVK5ThJRPTkyRPi8Xhka2tLo0aNogMHDlB+fr7K+kT/dy4jFovJx8dH7f5ZXl5OTZs2ZdqjadOmNGTIEFqzZg09ePBApfHn8OHDjD6Px6M2bdpQVFQUbd68mRITEz/btyQSCbVr104hVk6ZMoVOnz6t8nxk9+7dxOfzyc3NjebNm0f37t1TeV4q5/vvv1fwa11dXfLw8KCff/6Z9u3bRy9fvvxkf0tPT2fmZADIwMCAvL296ddff6VTp06pNBaHh4cTn8+nrl270qxZs+j69etqzQGqqqqoVatWCuUwMjIiLy8vmjx5Mh04cIBSU1M/WY4NGzYo1EGvXr1o1qxZdOHCBZXGv9LSUrKysiJNTU3q2bMnLVy4kO7evavWnGrt2rWkoaFBHh4erGN+QwFwj1R8NuRRA1ZO/qfp2LEj3bt379/ORr0kJSWhrKwM1dXVqKmpQXV1tUJ6w4YNuHTpkoJO+/bt0bt3b/Tu3Rtt2rTBmzdvUF5ejrKyMpSXlyuki4qKsGDBAqU3ScbGxvDw8EDPnj3RokULmJiYoKamRkmqq6tx6NAh7Nu3T0G/TZs2TB5cXV3x9u1bSKVSSCQSSKVShXR1dTXCw8MV3q41atQIvr6+8PX1hZeXF7Kzs/Hy5UtkZmYiIyMDmZmZCvLhw4dPvmnV0dFBnz590K9fP1RUVCA7OxtZWVkK19evX6OqqqpeG1ZWVvjmm2/QtWtXhXqU12Vqaio2btyopGdubo4ePXqgZ8+esLKygqGhoZK+XA4dOoQnT54o6PN4PDg5OcHT0xOdOnWCtbU1hEIhqqqqUFlZqXDNzc3FL7/8oqAvEAjg6uoKb29veHt7Q0dHBzk5OcjNzUVubi7y8vKYdG5uLp4/f473799/sh78/f0xYMAAVFZWoqSkBCUlJSguLmauW7ZsqbMumzRpAnd3dzg6OqJ169awsbGBVCqFTCZjRCqV4vjx41i6dCmjJxaL4eXlBT8/P/j5+cHa2hqJiYmMD0kkEqX02LFjFVafTU1N4ePjA19fX/Tu3RsSiQTp6ekK9VdbHj9+jGXLlin5UY8ePZi6rKqqQkVFRb2yadMmPHv2TMGGvr4+PDw84OXlhQ4dOkBLSwuVlZUKUlFRgcrKSnz48AFz5sxRqsf27dujV69e8PLygrGxMcrKylBUVITi4mIUFRUppK9fv47ExEQlGwKBAO3atYOrqysaN24MR0dHJib8Xfbs2VPnm1pDQ0O4ubmhVatWaNOmDczNzRl/KCkpQWlpKUpKShAfH4+rV68q6evo6KBbt27o1q0bGjVqhBYtWoCIFNqhuroaVVVVmDRpEvLy8hT0O3TowLSFra0tcnJyFPxQLiUlJUhKSsLZs8r/mxqfz0f79u3x9ddfw8bGBs2bN4dEIkFhYaGS/Pnnn/WuSLVq1QodOnSAg4MDvvrqK6Zf1e5rGRkZePq0/s8viEQidO/eHd9//z0sLS0V4qT8Kt8VUrsOvby8mHipr6+PFy9eKMUWuRQUFGDx4sVKb+11dXXRvXt3eHp6wtbWFmKxGLm5ucjKylKS9+/ff/LtuVgsRnh4OCIjI6GhoaHURysrKxEREaFgw8rKCn369IGvry+8vb2Rl5eHN2/eKMSm2vLmzRu8fPmy3jzo6+ujd+/eGDVqFEQikVLfqqysxO+//660Q6Vx48bo1asXevXqBUdHR4UYW1uqqqrw7NkzpRghFArRrVs3xoZYLGYmQ/IYJ08TESZNmoRr164x+k2aNIG/vz/8/f3h6enJ+K683LX9KScnB9nZ2UhISKi3HjQ0NODq6oqhQ4dCU1MT2dnZCuNednY23r59+8lVIS0tLURGRsLf3x/l5eVMfygqKmLSBw8erHNHhZaWFjp37ozWrVujXbt2sLKyYnRry+PHj3H79u0679+8eXN069YNTZo0QZcuXQBAYeyVp9esWaMUI4RCIbp06QJPT084OjrC0tISRKTgB/J0QkICNmzYoFR/Xbp0gZeXF3r16gUtLS0QETMX+/ucbP78+Qrxls/no1OnTujduzd8fHxgZ2eHd+/eoaysDKWlpUrX9PR0pTwAH/v5119/DU9PT1hbW8PMzAzFxcXIz89Hfn4+CgoKmOuDBw/q3Zmho6ODDh06oEOHDujevTuKioqQl5enJNeuXat3Zc/Q0BDt2rVDeHg4LCws6hx37t27h7t37yrp8ng8ODs7o2vXrrCzs0PXrl0hFAqZ+CCX6upqREZGKswLzc3N0bt3byZGFBUV4eXLl3XGqKysLKSnpyv5Q20EAgECAgIQGhqK6urqOuPM48ePUVJSUq+NZs2aISoqCu7u7owvyMet6upqJCcnY+7cuQo6+vr66NmzJ3x8fODj44Pc3FylOW1mZiaysrKQmZmJ9PT0T+6Qsba2RlhYGLp3747i4mIUFBQoSF5eHk6fPl2nLp/PR9u2bdG6dWv07dsXNjY2CjFOnj58+DDOnz+voGtsbIyePXvC29sbbm5uSm1YW8rLyxEREaGw40ke8/v06QNvb28YGRnVW8Z/Ah6Pd5+IOqr0Y1WfcP8N+dJXXJs3b67wpkVdEYvFDdLX19cna2vrBtnQ1NRskL6GhgZZWlqy0nV2dqb169fTu3fvWN/fx8eHDh8+THPmzGlQOZo2bdqg9hAIBOTk5NSgPABQeIOori+MHTuWNm/e3KD7d+jQgVmBYysODg4N0ufxeGRlZdVgGwKBoEE2bGxsGqSvoaFBurq6rPXt7OwoLCyMtb5AICB/f39ydnZmbUNLS4v8/PwaVA/Ax7fhDcmDfEWWjfD5fPLx8aFBgwaxrsfAwEA6efIkNW7cuEH10FCfsrS0JAsLC1a67dq1o3Xr1tG1a9calAeBQEBmZmas2zIiIoJOnDjRYJ8yNTVtkL5QKCSRSMRaX1tbm9q2bctKl8fjUZ8+fejgwYNKKzaqiqOjI61atYqOHTvGugwikYhCQkIUdvKoK9bW1jR27NgGtYWOjk6Dxw2xWEw8Hq9BNtiOv3Jp2bIl61inoaFB/fv3pylTprC+f+vWrWnJkiXUrVs31jYsLCxo2LBhDaoHHo/Hun/a2dnRwoULKSUlhfX9mzdvTgsXLqSpU6c2qBzydmFT/oCAADp16pTSrgt122LixIms44xcdHR0GqTP5/PJw8ODrl+//j/2PAU1Vlz/kf/H9f9X9PT0oK+vD6FQCJFIpHTNy8tTWh3T0NCAl5cXgoODYWpqihEjRkAsFkNHRwdisZgR+Z9Pnjyp8BZELBajX79+GDx4MPr06YOwsDDExcVBKBQq3F+eLisrQ2pqqlLeu3btiuDgYLRv3x7+/v7Q0NCAQCCAQCBQSAsEAmRlZSmdGxMIBHB3d0f//v3x6tUrnDhxApaWlrCysoKlpaWClJaWIjw8HMDHN7yDBw/GuHHj4OrqCh6PByKCpaUlDA0NYW5uDgsLC1hYWDBpc3NzbNq0CWfOfPzel6WlJUaOHImoqCjY2dkB+HhOzsjIiKk3HR0dhbSGhgYOHjyoUAYLCwsMGjQIgwcPRpcuXdC2bVvk5OQo6colJSVF6e25u7s7Bg8ejIEDB+LmzZuIiIiAlpYWtLS0oKmpqXS9du2a0pvvzp07IyQkBAMHDsQPP/yAhw8fwsTEBKampozI//z06VOsW7eO0fXw8MCoUaMQHBwMsViMxMREGBoaMr6pp6enlN6/f7/CWd2mTZsiPDwc4eHhaNWqFUaOHImkpCTw+Xzw+XwIBAImzefzIZFIkJ+fr+RT+vr68PPzg5eXF7777jtoaGgwvvT3dFZWltLZNz6fD3d3dwwYMABpaWnYsGEDNDU1FURejwCUVgD4fD48PDwQEhKCAQMGwNXVFRUVFdDW1q5Tnj9/rrQq1Lp1awwaNAihoaG4f/8+oqOjoa2tDS0tLeYqT2tqauLChQsKb74FAgF69eqF0NBQ9O/fH8HBwXj+/Dn09fVhYGAAAwMDhfTfVxoNDQ0RGhqKoUOHws3NDfHx8Th37hzz+7/rGxgYYMOGDQrt0bFjRwwdOhSDBw+Gubk5hg0bhoyMDOjp6UFXV5fxA7nk5OTgxIkTCvXYq1cvhIeHY8CAASgqKkLLli2V2qK2PHv2TOnMU5MmTRi/PnnyJDZu3Mj4Ye2rvr4+qqursW3bNkaXx+OhZ8+eiIiIQFBQEPT19WFhYQEtLS0YGhrWKefPn8edO3cU2jIyMhLh4eGwsbHB9u3b8ddffzF9yszMTKGP6erqYvTo0czqdYsWLTBq1ChERkbC0tISADBp0iTo6OgoxMna8bKkpKTOvuHo6IgBAwbAwsIC06dPV4grf5dDhw4pxFsjIyMEBwcjLCwMHh4eCA8Px927d5k4+Xd5+vQpZs+eDeDjeBEWFoYxY8agU6dO4PF4SExMhLa2tlLfrN1H09PTlWK+UCiEl5cXBgwYgISEBJw8eVKh/mpLQUEBfv31V0bXxcUFo0aNQlhYGAwNDVFRUQEdHR2mP9UWeT9LTExUOgfYsmVLhIaGIiQkBOfOncP8+fPrtKGlpQUej6e0k0BDQwPe3t4IDQ1FYGAgHB0dkZ+fz8Q2Ho+ncJXvzvg7FhYW6NevHywtLZGVlQUzMzMFf5KnjYyMMG7cOGYMb9KkCUaOHInhw4cz/0/99u3bUVVVpTTmydPx8fHMDhdtbW0MGjQIY8aMQZcuXcDj8fDw4UMYGxvDwMAAhoaGCld5ev369Qox383NDcOGDUNISAiMjIwwevRovHv3TiGu1JacnBzs2rWL0dfR0UFQUBCGDRsGT09PFBQUYO/evXX6s3wcvXbtmsJ8SCQSwc/PD2FhYQgICMCiRYuwcuXKOmOtlpYWZDKZUntqa2szq3J+fn6wtbWFVCpVmIfVlvT0dKVdGTo6OvD390dwcDAKCgowdepU6OrqQkdHR+mqra2NnTt3KsT8Ro0aISwsDGFhYWjXrh26d++OtLQ0GBkZwdjYGMbGxkzayMgId+/exZEjRxh9JycnjBgxAkOGDIG5uTmuX7+OzZs3w8TEhBFjY2OFP0+fPp1ZrdTX10dYWBhGjhzJ9PG7d+/C0tKSGSv+fn3//j0OHz7M5EEsFmPAgAEYOnQovLy88Pr1axw8eFApNtSOGenp6Up9QyQSMTHi2bNnOHLkiEJssrS0ZNIlJSWIiopi+mVgYCDGjh0LLy8v8Pl8EBHMzMxgYGBQZ7w2NTXFrl27cOXKFcYXBg4ciFGjRsHd3R08Hg8rVqyArq4uNDU1IRKJlK4CgQDx8fFK/btTp04YOHAgE3eLi4uV5rXy8hw/fpxZhbeyskJUVBSioqKY/n3mzBkmFtQWQ0ND5jpnzhwmRohEIgQGBmL48OHw8fGBhoYGHj16hLS0NIX5ZO10Xl6e0s4tAwMD9O/fHyEhITA1NYWnp2ed7SmXd+/eKe3E09LSgo+PDwYMGIC+ffvCxMREqa7+FVR9wv035Etfcf0cvXv3JuDjqmZgYCDt3LlTrTMVDx8+JODjW9H+/fvTvn371DqjQ0QUHR3NvDHx9PSkNWvWqHXONT8/n3kLqaWlRYGBgbR9+3a1znZOnTqVHBwcaMWKFWqfKSEiqqioIBMTE+rTpw8dOXJE5fMktdm5cycBH88fREVFUVxcnFpnAGQyGbMS6eLiQkuWLFHpTGlt5Oe2AFDnzp1pyZIl9ObNG7Vs+Pv7k5WVFU2dOpVevHihli4R0atXr4jH45GRkRGNGzeOrl+/rvZZhrlz5zLlsLGxoW+++YbOnz+v8hnT8vJyZpVeU1OT+vbtS1u3blXrfKj8XAifzycvLy9av349ZWZmqqwvlUqZN/xfffUV/frrr/TkyROV9YmIzp8/T8DHFShvb2/atGmTWv2CiMjT05OEQiEFBgbSoUOH1D4vnJCQQMDHs3PTpk2jpKQktfSJiKKioggAdezYkZYvX67yuTU5+fn5zMqyvb09TZo0ie7evauWX82fP5+Aj7swFi9erPZZ/KqqKrK0tCRTU1OaMGEC3bt3T22/3rFjB2lra9OwYcPo6tWrrM74eHt7M2/cu3XrRosXL1arn8pjhFgsprCwMDpx4oRaZ7eJiAYMGEBOTk4UExOj1hl6OdnZ2cx5YV1dXQoNDaXY2Fi1bP30009kZGRE48ePp4cPH6qdh/LycjI3NycA1KJFC5oxYwY9evRIrTaRr3RoaGiQr68vbd26lfLy8lTWl8lk5ObmxsS61q1b09SpU+nWrVsqn+c7deoUiUQiGjRoEF24cEHtc4BERF5eXkx7FhQUqK3/7NkzZiVr1qxZrMaNcePGEY/HI29vb9q5cyeVlJSopV9QUEC6urrM7oetW7eqXZaVK1cy85Dg4GDav3+/WvMhiURCLVu2JODjDpCIiAg6evToZ88Z10Z+vtTExITGjRtHV69eVbtNO3fuTCYmJjRhwgR68OCBWrpERLdv3yYA1LNnT9q9e7da54TlhIeHE4/Ho169etGOHTvUOitMRJSXl8fE/NoxQtVvEhARTZkyhZo2bUq//fab2mMO0ccYYWRkRC4uLrRu3TpWsS42Npbp3127dqWlS5fS69evVdaXyWTUpk0b8vHxYT03vXjxIgEgV1dXWrt2rVoxSk5oaCjj15GRkXT69Gm1xo309HRm94mBgQGFh4fToUOH1O7nDQFqrLj+6w+nn5L/zQ+uKSkpNGjQINq/fz/rxt+6dStt376dVYck+hhcBgwYQJs3b1broaA2q1evpmHDhtHRo0fVfmiWk5iY2KCD3pmZmZSamspan4ho0aJFrCaBcl6+fElz5syhlJQU1nn4/fffaenSpSp/COnv1NTU0JkzZ9T6eMDfOXPmDB07dox1PRQXF1OPHj1oxowZrB4OiD5+2KEhgVEmk9G3335LGzduVPsjQHIePHhAU6ZMoYcPH7L2zQULFtCGDRtY56GgoIDWrl2r9sNubc6ePUuXL19mNSEm+vjAt3DhQkpOTmadh3379tHUqVPp/v37rOpSJpPRypUr6fHjx6zzkJKS0iC/JiK6fv0661hL9PFFo6+vL23YsIHVRIzoY8yPjY1lHWtlMhnrdpCzYsUKGjVqFJ06dUrtFylyzp8/z1pXrj9t2jTWHwmRyWT0888/q/2wWpurV6+Sh4cHLV26Zcm0vgAAIABJREFUlNXDHtHHh4yG9O+amhqKj49vUHvGxcXRX3/9xdqGRCKhmJgYtV8m1ebixYu0Zs0atT9QKUcmk9GPP/5IsbGxrOdTV65coVGjRtGZM2dYx4k1a9bQ6dOnWT2gEBEVFhbS4cOHGxSnbt682aD5UFVVFa1cubJB7blmzZoGxwh1PjRaF+/evaOEhATW+jKZjCZMmEArV65UexFCTllZGb18+ZJ1Hog+xrpnz56x1s/KyqKRI0eq/bBam8WLF9O4cePUWoD4p1HnwZX7OBPHJyEi8Hi8fzsbHF8I/4Q/cD7F8d/If4tf/7eUo6HIZDLw+Sr/j4EcHP/fwMUIjn8adT7OxEVljk/CBSeO2vwT/sD5FMd/I/8tfv3fUo6Gwj20cnDUDRcjOP5NuMjMwcHBwcHBwcHBwcHB8UXDPbhycHBwcHBwcHBwcHBwfNFwD64cHBwcHBwcHBwcHBwcXzTcgysHBwcHBwcHBwcHBwfHFw334MrBwcHBwcHBwcHBwcHxRcM9uHJwcHBwcHBwcHBwcHB80XAPrhwcHBwcHBwcHBwcHBxfNNyD6xdKdXU1jh8/jnfv3oGIWNl4+vQpbt68ifLy8n84d/+7KC4uxps3b1jXIwBUVFQ0KA8SiQQFBQUNstFQZDIZjh07hhcvXkAmk7GykZSUhPPnzyMnJ4d1PhrSDsDH9szPz2+QjYYikUggkUgaZOPRo0dISkpi3RZAw+vyv4UbN27g9evXrOvjn6jHd+/eobKykrV+VVUVzp49i6ysLNY2ampqWOt+SeTm5v7rvp2YmIi8vDzW+tXV1cjOzv4Hc8SOf7segY910RAaEiPlvH//HlKptMF2GkJycnKD+rdUKsWHDx/+wRypDxHhypUrDZoD/BM0JNb+U9y+fRuJiYn/ql8lJSXh+fPn/1/NIwSzZ8/+t/NQLxs3bpw9ZsyYfzsbrLh//z42btwIXV1dWFpaqv0fNgsEAqxZswZDhgxBTEwM/vzzTyQlJaGwsBBisRgGBgYq2ezWrRtmzZqFgwcPIj4+HmlpaZBKpTAxMYFQKPys/oYNG3Dt2jUYGxvDxMRE7XIUFBRgxIgRyMnJgYmJCYyMjNTSB4BNmzZh9erVKCsrg4WFBXR1ddXSFwgE8PT0xNy5c3Hjxg28ffsWMpkMpqamEIlEKtk4ceIE+vfvj0ePHqGoqAiGhoYwNDRUOQ88Hg+BgYFYtGgRHj9+jMLCQujp6cHQ0FDlOn348CFGjx6NnJwc6Ovrw9TUVK324PF42L9/P4KDg7F8+XKcO3cOT548QU5ODoRCIYyNjcHnf/pdlra2Nnx9fTFjxgxs2bIFV69eRUpKCoqLi6GjowM9Pb3P5umPP/7AsmXLkJOTAz09PbXLQURo37491q9fj4cPHyIvLw9isVgt/4yNjcWsWbOQl5cHAwMDGBsbq+3bPXv2xP79+/Hu3Tvw+XxYWlpCIBCorJ+fnw9nZ2csWbIEFy5cQGJiIgoKCqCtrQ0jIyOV8jN27FgcPnwYJSUlMDMzg56enlplSE1NRWRkJLKzs2FgYKB2WwDAqlWrcPz4cQiFQlhbW6tVBwBQUlKCMWPGID8/HxYWFtDX11dLH/gYb7t164Y1a9bg0qVLSE5ORnFxMXR1dVXyyerqavTp0wd//fUXSkpKYGpqqnZdPnjwAI6Ojjh16hQSExNRXFwMfX19GBgYqKSvoaGBhQsXIiIiAlu2bMG1a9fw8uVLlJeXw8DAADo6Op+18eTJE3h4eODRo0coLi6GkZGRyveX88cff+DChQvQ0tKCtbX1Z2PC3yksLMTUqVNBRGjUqJFK48zfiYmJweDBgxEfH4/MzEyIRCKYmZmpnJeamhpMnjwZpaWlaNSoETQ1NdXOQ0JCApycnLBnzx7cuXMH6enpAAAzMzNoaGh8Vp/P56Nv37747bffcP/+feTk5EBbW1utOHXv3j388ssvKCsrg7m5udo+CQBjxozBrl27kJubCz09PbXH8ZycHMyfP5+1PwDArFmzMH36dLx69QoSiQQWFhZqtUlhYSF69OiBu3fvorS0FGZmZmrPA44fPw53d3dcvnwZqampqKmpgZmZmcr5kEqlGDVqFJ49ewaxWMxqXvfmzRs4ODhg69atuHXrFt6+fQupVKryXITP52P48OGYPHky7t69y6pvvH37FrNnzwafz4eNjY1KvlwbHo+HPXv2wNfXF9u2bcONGzeQmpqKqqoqGBsbQ0tL67M2CgoKMHLkSOTm5rKeF65cuRLffPMNkpKSUF5eDjMzM5VipBypVIqZM2eioqICtra2rOLU+/fv0bFjRyxZsgRnz57Fo0ePkJubC5FIpNJ8iogwYsQIXL16FTKZDFZWVirPSeUUFxfDyckJS5cuRVxcHJKSkpixT19fXyUf/emnnxAbG8v0LTZxpqHMmTMnY/bs2RtV+jERfbHi4uJC/1uRSCTUqlUrAkAWFhY0YsQIOnz4MBUXF9erI5PJKC8vj54+fUpxcXEUExNDPB6PACiJsbEx9erViyZPnkz3799nbFRXV1NaWhrdvXuXTp48SX379q1Tn8/nU5s2bWjYsGG0Zs0aKi0trTNPycnJxOfzCQDZ29vTd999R2fPnqXy8nKV6+Lnn39m7tu8eXP69ttv6cSJE1RSUqKSfnFxMZmZmTE22rZtSz/99BOdPXuWysrKPlmfBQUF9PLlS1q2bJlSHQgEAmrfvj198803tHPnTnr+/DnJZLI6bUkkEurSpYuCfuPGjWno0KG0adMmSklJqVdXJpNRWVkZXbhwQSkP1tbWFBISQitXrqR79+5RTU3NJ+vCz89PQXfYsGG0a9cuysjIqPfeubm59OTJE7pw4QJt3LiRhEJhnT6ho6NDbm5u9N1339H169cZGxUVFZSamko3btyggwcPUkhISJ36AMjMzIx69+5Ns2fPpoKCgjrzVFBQQMbGxoyOlZUVhYeH09atW+nNmzefLH9lZSVlZGTQ4sWL6+wTAQEB9Ntvv9GVK1c+6RvV1dXUvHlzRtfW1paGDx9Ou3fvrrcu/05cXJzC/bW1talnz540Z84cunz5MlVUVCjpSCQSysjIoISEBDp//jx17969zno0MjIib29vmjZtGh09epSqqqrqzENCQoJCjHBwcKBvv/2Wjhw5Qvn5+SqVIyIigtG3sbGhESNG0N69eyk7O1sl/Tdv3jA+paenR/3796f169fT69evVdInIpo0aZJC//7ll1/ozz//pMrKynp1Kisr6d27d0ysa9y4cZ11aWlpSQEBATR79my6cOFCvf103759CnoODg70zTff0KFDhyg3N7fefEgkEsrNzaXnz59T165dle5vY2NDAwcOpKVLl9LNmzcVyiSPUUlJSXT58mVas2ZNvX2rcePGNGDAAFqwYAE9efKk3vwMHz5cQc/Ozo5GjBhB27dvV6lNnj17xsR8IyMjCgkJoS1bttD79+8/qytn1KhRTJ/w9/entWvX0tu3b1XSraqqorS0NLKyslIoh56eHvn4+NDcuXPp0qVL9Y5ZcubNm0cASCgUkpeXFy1btoxSUlI+qSOTyaioqIhevnxJt27dorZt2yq1g1AopE6dOtH48eNp586ddcZ+iURCeXl5dPTo0Tr7tp+fH82fP58uX7782THMw8OD0XVycqKJEyfSxYsX64wvdZGcnEwCgUAh3g4ZMoQ2b95MqampKtkIDg5mYmx4eDjFxsaqHF+IiAoLC8nExERh7O3UqRNNnDiRTp48We9YUZvly5cr9c/o6Gg6ePAg5eTk1Ksnb9PXr19TixYtFGzweDxycnKi6Oho2rVrF7169are+EBEtGPHDkbX1NSUwsLCaNu2bZSenv7J+xcXF9OrV6/o9u3b9PXXX9c5F3F2dqbRo0fT5s2b6fHjxySRSBTsSKVSys/Pp7i4OKV5oa6uLvXq1YtmzpxJ58+fp8LCwk/Wpa+vLwEgsVhMffv2pXXr1n22f1ZWVtLbt28pPj6eDh8+TGKxuM441aJFCxoyZAgtW7aM7t27V6+9H3/8UUFn/PjxdPLkSZXnheXl5Uoxv1WrVjRu3Djau3fvJ9tEzsKFC5k4FRAQQOvXr6e0tDSV6+HEiRPk7Oxc73yqe/fu9MMPP9CBAweU2lPOxYsXFWKLu7s7zZ07l27dulXvfFAqlVJeXh49e/aMrly5Qn369Kl37Ovbty/NnTuXzp49W2/MSElJUYgR8nnE0aNHVeqb/wQA7pGKz4Y8+oKXiDt27Ej37t37t7NRL9OnT0dGRgZTmTKZTKFyHz9+jKdPnyroCIVCuLu7IyAgANbW1ti7dy8yMjKQmZmJzMxMlbfUaGhooH///tDS0mJ0MzMzkZubq3L+raysMHjwYHz48AFaWlqQyWSQSqVK10uXLqG4uFhBV1tbGz179oSfnx8qKirw6NEj1NTUoKamBtXV1Qrp/Px8JCYmKt1fKBTCzc0NPXv2xN27dyEWi1FVVcVIZWUlk3779i1KSkqUbIhEIri5ucHS0hIfPnyAVCpFXl4e8vLykJ+fr/J2TgsLC1haWsLS0hI1NTUoLi5GSUkJiouLUVxcjLKyss/aMDExQePGjWFiYoKioiIUFhYyouoWPjs7O7Rq1QpaWloKdSC/Zmdn17vVqG3btmjXrh1evnwJiUSCrKwstXxKIBAgMDAQxsbGeP36NTIzM/Hhwwe1tjjb2dkhMjISz549g0wmQ3l5OSoqKlBRUcGky8vLkZ2dXW+dNGvWDLa2tqiqqoJIJEJ+fj4KCgqQn5+v8rZ3sViMRo0awcHBAcDHbUWVlZWoqKhgrpmZmSgtLa1T39HRES1atEBeXh50dHRQUlKiJJ/bqiQSiWBtbQ0rKyuUlJQgKytLrS2QJiYm8Pf3R2FhIYRCoUId1pYPHz7UuU2Iz+ejQ4cO0NfXh6amJnR0dBT6l1xyc3ORlpZWZx7at2+Pbt264cWLFzA2NoZMJmP6tkQiYdIPHjyosy5btmyJPn36QCQS4cOHDyAiRk++3bqmpgYFBQW4f/++kr6Ojg68vLzg6emJuLg4lJaWIisrC1lZWWr5ZbNmzeDu7o7CwkLGL8vKylBeXs6ky8rKUFhYWK8NZ2dnyGQyGBsbo6KiAvn5+cjLy0NhYaHKbdqsWTPo6upCU1OT6Z9VVVUq6fL5fPj5+cHAwAAVFRUoLS1FaWkpSkpKFK6f80sbGxuYmpqiVatWkMlkCu0ob5e7d+/W2dfatm2L3r17AwCys7PB4/GYsa+2ZGRk4Nq1a0r6bdq0gb+/P9zd3bF7924UFxcrxMnCwkKV+7i5uTkcHR3RuHFj5r6181JcXIyzZ88q6TVv3hx+fn7w8/PD9u3bkZubi5ycHOTk5CA3N1fleKmpqYmvv/4aNTU10NDQQEFBASPFxcUq+QSfz0ezZs3g4OAAbW1tVFdXM+OnPP3+/fs6+6e2tjY8PDzg7OyMxMRECIVCJZ+WXwsKCurNT5MmTWBtbQ0TExOYm5srzGEAgIjw9u1bXL16VUFPIBCge/fuCAgIQJcuXbBu3TqF+Cj3SXn6U1sZ+Xw+mjRpgkaNGsHQ0JDpj7XLUFpa+slx2NHRERKJBFZWVigvL2fGjIKCApW3cjZu3Bi2trawtbVVaofq6mpUVlbWGaeAj33Dx8cHKSkpqKioQF5eHuNTqvZx+fywuroaIpFIwaeKiopUjjMtWrSAg4MDjIyMFOZz8vSbN2/w4MEDJT1HR0f4+fnByckJhw8fRk5ODrKyspCdnY2ioiKV7i234+zsDIlEAh6Pp/a8sHv37vD09MStW7egoaHBzMXk/qTqnMzGxgZfffUVmjZtCgAKPk1EKC0txZEjR5T02rVrh759+yIgIACrV69Geno6M8dWZ9yxt7dH7969mXm5fB5Se15XWVmJ58+f16lvYGAAT09PlJaWoqqqiplH5OTkqDy3FYvF8PPzQ2lpKXR1dZXmD3JJT0+vs5/w+Xy4uLigV69eCAoKQseOHVUuvzrweLz7RKSacVWfcP8N+dJXXFu2bFnv23FVxMjIqM6/19DQIBsbG3JxcSFDQ0OFf7O1taV58+bRhw8fiIjqfdOiq6tLzZs3JycnJ6V/8/HxoSNHjlB1dTUlJyc3qAwCgYBsbGwapN+zZ88G5cHFxYV5g1if6Ovr11nP/fv3pxMnTlB1dbXSG35VpXXr1rRw4UKKiYlhpW9jY0NTpkyhZ8+ekZubG+t6aNq0KQ0dOrRen2rUqBF16tSJzM3Nle4/e/ZsZkWl9gpcbTE2NqY2bdoo5ZHP51Pfvn3p7NmzJJVKKTc3l3UZdHR0KCwsjEJDQz/5O/mK0N/F3d2dtm7dSsXFxaSrq8sqDzwej7p3705DhgxhpS8SiWjAgAF06NAhcnR0rPc3jRo1Ijs7O6V/8/DwoL1791JFRQX9+eefrOvSyMiIRo0apbRTQB0xNTWlQYMGsdYHPu44qa8eVJX27dvXu/tER0eH7O3tleKQhoYGDRw4kC5evEhSqZRWrFjB+v6Ojo40f/58atSo0Sd/p6WlVWc7jB8/nh48eEDHjx+vU4/P55OFhQU5Ozsr+a2VlRX9+uuvzIpIjx49WJXBxMSEoqOjadu2bQ1qC2tra2Y3UUN8k42etrY2RURE0IULF2j27NkNyoNYLCZNTc16/93Q0FBhlVAuTk5OtHr1asrLy6Ndu3axureDgwP9/vvv9P79e3JxcWFdBgMDA/Lx8WGtb2trS7/88gt5eXk1qC7r8ntVpUOHDrR06VKKjo5mbcPd3Z1iYmLq3U0kl7rGDUNDQ4qOjqY7d+6wHsOBj+PG119/rbA7rK72quvfW7VqRUuXLqXs7Gw6c+YMq/s3a9aM5s6dS2/evGmQTwAf+3h9/6arq0vNmjVT2DUFfOybw4cPp5s3b5JMJqOxY8eyvr9AICBPT0/W+h07dqQVK1bQ9OnTG1QPfD6/Xt/W19enFi1aULNmzZTyHhQUROfPnyepVEr79+9nfX9tbW0KCQmp91lDPm40bdpU6d86dOhA69evp6KiIoqPj2edB11dXQoPD6fjx49/cgdUQ4EaK67qbW7nUGDMmDHIyckBj8cDn88Hj8djhM/nIy4uDtevX1fQcXJyQr9+/dCvXz9YWFggNjYWlpaWsLKyYq4mJibg8/koLS2FlZUVeDwefH19ER0dDV9fX4UzZFFRUfDz82P05SI//7Fy5Ur88MMPMDU1xciRIzF69Gg0b96c0TcxMcGUKVPA5/MhEAjA5/OV0suWLVP4yISuri769OmD/v37w8/PD9euXcPdu3chFAohEokgFAoZEYlESE5OxpIlSxh9kUgEHx8fBAUFoV+/fjA2NsaMGTOgqakJTU1NaGlpKaUXLFig8IawY8eOCAkJwcCBA2Fvb4+7d+/Cw8MDJiYmCmJqagpjY2O8ePECbdq0AQA4ODhg1KhRGDp0KCwsLBibv/zyC2pqaqCnpwd9fX3mKk/PmzcPu3btAgBYW1tjyJAhCA8Ph7OzM3g8HlJSUjBv3jzm/OvfhYjg4OCA8vJyiMViBAUFITIyEp6enkybDh8+HL169WLK/ffryZMnsWPHDibPdnZ2CAkJQUhICFxcXFBYWIhWrVrByspKQeQ+VVNTA1tbWwCAj48PoqOjERAQoHDOZciQIXB1dYWVlRWzYmhlZcWcXdm9ezdu3LgBc3NzREVFYcyYMWjSpImCf0yfPh1isRja2tp1XidMmMDsRtDS0kJAQAAGDRoEPz8/iMViXLt2DR06dICRkRGMjY2VrsnJyejcuTOAj2/JIyMjERkZiWbNmjH5mDJlCmQyGbS0tKCtrQ0tLS2F9LJly3Dp0iXm925ubggNDUVwcDBsbGzw6NEjtGzZEnp6egoi94fKykq4ubkxbyk9PDwQERGB4OBg5syOfLXBwsJCQeRn1CdPnow//vgDJiYmiIyMxJgxY9CyZUsmT/b29vj111+hra1dpwiFQoSEhDC7EfT19dG/f38MGjQIvXr1gkgkwp49e+Dj48P0KbmIRCJoamri2rVrWLt2LXNPc3NzBAUFYeDAgfDw8EBpaSns7e0V+rWGhobCn+fMmYP3798zNpo2bYqgoCAEBQWhS5cuOHfuHPP2XK4rT2toaODVq1dYvnw5o8/j8fD1118jKCgI/fv3R9OmTbF48WLo6enB0tJSoS7l55r8/PyQnp4OOzs7jBkzBsOHD4elpSVjs0uXLpg9ezbEYjEjOjo6TLqgoAADBw5kft+8eXOEhYVh0KBBTOwwNjZGVVUVTExMYGxszJz9l/vmjz/+iNWrV4PP58PHxwcjR45Ev379mHN0RkZG+P333xVitaWlJUxNTSEQCFBYWAgrKysAQO/evTF27FgEBAQonL8aMWIEvL29oaenx5zhrX09ePAgFixYAODj2/bAwECEh4fDx8cHQqEQWVlZmDp1ar1tqaGhgalTpyp8mMje3h7BwcEICgqCq6srjh49inv37jFjhHz8k6dTUlKwe/du1Mbe3h6BgYHo168f3NzcMH/+/HpjpaGhIQYMGMCs8vXo0QPDhg3DwIEDmfNXAoGAGbtq31uezsnJwerVqxXyYGlpib59+yIwMBBeXl7YuHEj+Hw+zMzMYGpqCjMzMyYtFAoxbNgw7Nq1C3p6ehgyZAiioqLg4uLCnBtzcXHB/PnzYWRkpBCj5FJTU4OmTZuiuroahoaGCAsLQ2RkJFxdXRkbo0aNgr+/PzN2ikQiBTl58iQOHTrElMHExAT9+/dHcHAwvLy8kJ2djY0bNzK+/PerpqYm+vXrx6wUmZubIzQ0FIMHD0bXrl3B5/OxZ88eZiVFPoeRpwHg2bNnOHbsWJ112bdvX3Tr1g0rV65kYqTcH2tLSEgIE/Pt7e0xZMgQDBkyBK1atQIAxMXFwdLSUiH/chGLxXj+/DlGjx7N3L9jx44YPHgwBg0ahEaNGgH4GG+1tLTqbY+IiAgcPnyY6Z/Dhw9HYGCgwrnMGTNm1NkOQqEQpaWlmDBhAvNbgUCAHj16IDg4GAMGDIClpSU2bdqEiooKxpdq+5RIJMKPP/6IFStWQCwWIzQ0FKNHj0bXrl2Zum7dujXmzZunkO/aIhKJ0LRpUxQVFUFXVxeDBg3C8OHD4ebmxtgYNGgQXFxc6p3TxcfH4+jRowrt2b59e/Tv3x+BgYGwt7fHqlWrYGFhAXNzcybWmpubQywWQyaToXnz5sjPz4ejoyPGjh2LiIgIhe9++Pr6wszMTGk+KE8nJSVh2bJlzO9FIhG8vb0RHByMvn37wtTUFLNmzWJ8ST7u1k5HRUXhr7/+YnwqPDwc4eHhzBh65coVZmWyLr8uKCjAunXrFOpBT08PvXv3Rr9+/eDr64uDBw8y/i4XCwsLiMViAMDIkSPx6tUr2NraYsyYMRg5ciSsra0Ze23atMGvv/7KzONqz+m0tLQglUoRERHB5FNbWxsBAQEICQmBn58fdHR0sGfPHuTn58Pc3JxpD3Nzc+Yc7fz58/Hrr79CV1cX4eHhGD16NFxcXJg8NGrUCDNmzFCaP8jnQ5qamggPD2divlgsRt++fTFo0CD06dMH2tra+KJQ9Qn335AvfcX1U1RVVVHjxo1JQ0ODvLy8aOXKlWqd+SIiOnXqFE2dOlVtvdp8++23tGfPHtZvSu7cuUPAx1WTMWPG0OnTp1U+WyMnJCSExGIxDRw4kGJjY6moqEgt/dTUVBIIBOTq6kqLFy9mVR/Tpk2jqKgounXr1ifPsNRHYWEh2djY0PDhwykuLq7e8wqfYvny5dSjRw/atm3bJ88614dEIqEWLVqQvb09TZ48me7du6d2Wa5fv04TJ06kFy9eqH1/OTNnzqTY2Nh6z11+jkePHpGmpib169eP9uzZw6ouoqOjKSIiguLi4kgqlaqtn52dTWKxmLp27UrLly//7LmWupg7dy61bduWFi1aRO/evVNbv7q6mkJDQ2nPnj1q9yk5e/bsIV1dXRoyZAirN6IymYw6d+5MlpaW9O2339Lly5fV9m3529zWrVvTjBkz6MGDB2r7ZUREBAmFQvL19aWNGzdSZmamWvofPnygkJAQ5i03GyZNmkS2trY0ceJEun//vtplKC0tpY4dO9Jvv/2m1nnQ2hw6dIimTJlCr169YqUvlUrJ0dGR/Pz8aPfu3SqfF6vNpUuXCPh41njWrFn06NEjtetCfibS1dWV5s+fT0+ePFHLxtOnT6lFixY0b9481uPfxIkTCQC1adOGpk6dSrdv31bLN/Ly8sjLy4u2bdv22fO09fHHH3+Qn58f7d+/n1Ufr6mpITs7O7K0tKTo6GiKi4v77HcQ/s6BAwfIyMiIoqKiWOkT/d+dXc7OzjRjxgyKj49Xqy7v3LlDZmZmNH78eNZj8JAhQ6hVq1Y0d+5cev78udr6aWlp5OjoyKx0s2H27NlMnNqyZcsnz9bWRUVFBfn4+ND69es/ew61PjZv3kxeXl60a9cuVn4pj/nyuenq1atVPn8u58aNGwqrq2wIDg4msVhMwcHBtHfvXrXnhc+fPyczMzP69ttvWedjxowZBICaNGlC48ePp/Pnz6s1hpaVldHgwYPp1KlTrOaERESrVq1iVlYPHDigdptKpVIKDQ2lTZs2sYr3RETHjx8nbW1tGjhwIB04cOCT5+7/pwB3xvXf59mzZ3j06BF8fX3V+vrsl8a5c+dgaGgIV1dXVl8TrK6uxrlz59CrVy/mDZW6JCUlQSwWK6zqqYtEIlH763m1KSoqgkgkatCbp5KSkgZ9rS03Nxfv3r1D+/bt1f6a4ZfEy5cvYWpq2qB+UVlZqdLXC+vjzZs34PP5aNy4MWsb6enpsLGxYa3/T/D48WO0aNGCtV+WlJQgISEB3bp1U/trwHJu3LgBExMT5jyxutTU1ODYsWPw8fFR+wu4/yRPnz5F69atWcU5AMxZx38CvDlUAAAgAElEQVSzb8rPvpqZmbG2ceXKFdjY2KBFixas9EtLSxEbGwt/f3+FlQd1KCkpga6uLuu6lEql2LJlC7y8vBR2YaiDTCZj7Qty5Ltr2PLhwwekpqaia9eurPtnSkoK7Ozs1P5aqZy8vDzs27cPAQEBrMfgjIwMZhWbDUSE5ORkODg4sPaJyspKaGpqNqh/nj17Fl27dmU9dv0TPlVRUdGgeUhWVhbi4uLg5+fH6mu+wMf2aEg9VldX4+zZs/D29mbdP3JycmBoaMjap2QyGdauXQt3d3e0bdv2X4vbt27dgpOTk1pfRK5NQ9sC+Pg1ejs7O7W/1P1Pos4ZV+7BlYODg4ODg4ODg4ODg+P/Oeo8uDbs1Q8HBwcHBwcHBwcHBwcHx/8w3IMrBwcHBwcHBwcHBwcHxxcN9+DKwcHBwcHBwcHBwcHB8UXDPbhycHBwcHBwcHBwcHBwfNFwD64cHBwcHBwcHBwcHBwcXzTcgysHBwcHBwcHBwcHBwfHFw334MrBwcHBwcHBwcHBwcHxRcM9uHJwcHBwcHBwcHBwcHB80aj14Mrj8bbyeLxsHo/3tNbfGfN4vIs8Hu/Ff65G9ehG/uc3L3g8XmRDM/6lEx8fj3PnzqGkpISVvkwmw8qVKxEXF4fS0lJWNv766y9ERUVh/fr1uH//Pqqrq9W28f79exARq/sDQElJCT58+MBaHwDOnz+PGzdusMo/AJSVlWH//v3IzMxknYeTJ09i3bp1ePToEaRSqdr65eXlCA4Oxvjx47F161YkJCSoXZ5Lly5h+vTpOHnyJLKzs9XOAxFh/vz52Lx5MxITEyGTydS28fTpU0ybNg0nTpxglQcAmDVrFr777jvs2LEDiYmJatfnu3fv4O/vjylTpuDAgQN4+fKl2j764sULFBYWqqVTGyJiXX45p0+fxrRp03D8+HHWvvngwQPW/UKuv2DBAly6dIlVnCEiTJo0CT/++CP27NmD5ORktf2quLgYKSkpDYozO3bswJo1a3D//n3U1NSorV9TU4ObN2+y0pVz+fJl7N+/n3W8q6mpwbRp07B9+3ZW9QgAycnJ+PPPP1FRUcEqDwCQnp7eoLbIycnBgwcPWOVfzrx58zB+/Hhs374dT58+hUQiUUs/MzMTw4cPx8qVK3Hz5k1W9bF+/XqMHDkSMTExuH37tto2qqqqMGvWLBw9epR1/y4uLmY13tTm6tWrDYp1WVlZSE5ObpBP5OXlNUi/vLwc6enprPUB4PHjx8jIyGCtX1ZWhgULFuDChQsoKipiZePMmTNYsmQJbty4gcrKSrX1pVIp5s2bh/379yMtLY1VHh48eIC1a9eynssAH32iIe355s0bLF26FLdv32Y9fr169YpVHcopLy/HqVOnWLclAGRkZKCqqoq1vlQqxY4dO5CUlMS6Pi9fvoxZs2bhzJkzyMvLY2Xjzp07KCsrY6X7r0BEKgsAdwAdADyt9Xd/AJjyn/QUAIvq0DMGkPqfq9F/0kafu5+Liwv9byUrK4v09PRIIBBQp06daOLEiXTy5EkqKChQ2caKFSsIAAkEAnJxcaHvv/+eDh48SB8+fFBJXyqVkpubGwEgACQSiahTp04UHR1NW7dupSdPnpBEIvmkjVWrVpGNjQ1FRUXRkSNHqLi4WOX8ExHV1NRQq1atyNnZmSZPnkyXL1+mqqoqtWzcunWLAJC2tjZ5eXnR3Llz6erVq1RZWamyjdDQUAJArVq1oujoaNq/fz9lZmaqrJ+ZmUn6+voEgPT09Mjb25tmzZpF58+fp8LCQpVs7Nu3j2kLeXt06NCBoqKiaO3atXT79m0qKyurV7+qqopatmzJ6Ddt2pQGDx5My5cvp1u3bqlUH0ePHmX09fX1ydvbm2bOnElnzpyhvLy8z+rLZDLy8PBgbNjb29OQIUNo1apVFB8fr1LbPn/+nDQ1NRkbYrGY3NzcaMKECbRz505KTEz8rF9OmTJFoS4NDAyoR48e9NNPP9Hu3bspKSnpkzbi4+NJQ0ODunXrRrNnz6abN29STU3NZ/Nem9DQUOrYsSPNmjWL4uPjSSqVqqVfVlZGTZs2ZcrQuHFjCgkJoSVLltC1a9c+6QtyZs6cSbq6uhQQEECrVq2i5ORkkslkKudBIpFQ+/btCQDx+Xxq164dRUdH086dO+nFixcq2UpISCCBQMCUQ09Pjzw8POinn36ivXv30vPnzz9ZN1KplJydnalJkyY0evRoOnjwIOXn56tcBqKPPiUSiZg44e7uTpMnT6Zjx45RVlaWSjaCgoJIT0+P+vbtS6tWraKkpCS16jIzM5P09PSYfhEZGUmbN2+mlJQUle3ExMQw9WhkZER9+vSh2bNn07lz51QaO0pKSsjS0pJEIhG5u7vTzJkz6fLly1RRUaFyORYvXkyNGzemcePG0YkTJ6i0tFRlXaKPMd/BwYFMTEwoJCSENmzYQK9evVLLRmpqKmlrazN1oa2tTd26daPvvvuOduzYoVKM+Omnnxh9gUBA7dq1o9GjR9PGjRspISHhs/29sLCQrKysFGw4OTnRiBEjaM2aNXTr1i0qLy//pI158+Yx+nZ2dhQeHk4xMTH08OFDleJNWloa2djY0NChQ2n//v0qjzW1WbRoEfH5fHJ1daWpU6dSXFycWv5QUVFBtra2ZGtrSyNHjqTY2FjKzs5WKw+bN2+m5s2b0/fff08XL15Uew4gk8nIxcWF2rZtS7/88gtdunRJbRu3b98mAOTo6Eg//PADnTp1ikpKStSy8fPPPxMA4vF45OTkRNHR0bRr1y5KTU1VqY8XFhaSubk5ASChUEiurq70/fff0759++jt27cq2Vi3bh3jU40aNaKQkBBavvz/sHfd8U3Va/+bNGmTznTSFhkXRAEZlV0BgbJBZKtMoaIgV1BRuYriQq5eEBFREVBABMoGoXuke2/KHsUyutI0adI0O8/7R2/O25C2JOm9V+77nu/n83zOKTnPc57zG8/4LbZTbm6uTWXSMo7w9PSkSZMm0eeff05JSUk29/Xt27dTjx49aM2aNRQbG2tXeyJqrs/x48cTABIIBDR69Gh6//336fz58zbFIURE0dHRJBQKaerUqbRjxw67fR8R0ezZs5m+8be//Y3i4uLssnelpaWMz/jxxx/p9u3bdr2fiGjDhg0EgAICAmjevHm0c+dOunDhgs3xhEajoSeeeIJpE7169aIlS5bQ999/TwUFBaTT6R4qY9u2bcTn82nMmDH0xRdfUG5u7kPt678aAArIxlyUQ3Zm+RwOpzuASCLq98+/rwEYS0RVHA4nCEAKET35AM+Cfz6z8p9/7/7ncxHtvWvIkCFUUFBgl37/ScjlcigUCiiVSgtqbGyEUqnEb7/9htzcXAseDoeDkJAQjBkzBiNHjkSfPn3A5XLR0NAAuVzOUENDAyQSCb755ptWR2J69OiBUaNGYdCgQejduzcEAgFqamosqLa2FpcuXcKtW7fa/AZXV1esWrUKb7/9NoRCIYxGowU1NTVh1KhRqK+vBwDw+XyMHj0a06ZNw9SpU9GnTx9otVqo1WoYDAYYDAbo9XqL+1OnTuGTTz5h3unu7o7x48djypQpmDJlCrp164b6+nqLsnvwfuvWrbhz546F7i4uLhgxYgTGjh2L0NBQPPnkkzAajWhsbIRKpbK4Xrx4EVu2bLH6/r59+2Ls2LEYO3Ys+vfvDycnJ8hkMtTX1zNX831UVBSuX79uJYPD4aBfv34YPnw4+vXrh5CQENTU1KCqqgqVlZWorKxk7q9cudJumxo3bhzWrVsHHx8f1NXVWVFubi4uX77cKi+fz0dISAjCwsIwb948NDY2QiqVQiqVoq6ujrmPiIhoc5TzySefxODBgzFz5kx0797direurg6lpaXIzs5uld/FxQWDBg3C0KFDMWfOHKhUKlRXV1tQTU0NCgsL2x3h69KlC95//3306dMH1dXVTBmaqaKiAuXl5W3yc7lczJs3Dxs3boSPjw+0Wi10Op0FrVmzBoWFhQyPl5cXxo8fj0mTJmHy5Mno3LkzNBoNTCZTq3Tx4kVMmjSJ4Q8ICMDUqVMxffp0TJo0CV5eXqivr0dtbS0kEgnq6uosrhKJBLm5ubh582ar3+Dk5IR+/fph9uzZCA8PBwDmO8zXuro6zJ4922KmsGvXrpg0aRImTZqE8ePHg8fjoa6ujmnLUqnU4j43Nxc5OTmt6uDv748RI0Zg4MCBmDhxIpRKpUU9mu/z8/PbHf3u0aMH/vGPf2DUqFFW9aDT6RAdHY3PPvvMov6GDh2KyZMnY9KkSRg6dCjkcjmjs/kbWt6fO3euzRmVHj16YNiwYZg4cSImTZoEnU4HjUYDrVYLjUYDjUaDCxcu4K233rLge+yxxzBhwgSGnJ2dGfvcGp04cQKlpaVW7w8ICMCoUaMQGhqKvn37IjAwEDKZzKp/1tTU4OjRo22WY58+fTB48GAsXboU3bp1s7Bz5vsTJ04gKirKgs/FxQWhoaEYN24cRo8ejX79+oHP51vYepPJxNjP0NBQKBQKAICzszPGjBmDadOmYdq0aejVqxfUajVUKhVTdg/S+fPnsXPnTgsd/vKXv2DChAmYOHEixowZA4PB0GpbMlNRUVG7qwA6d+6MDz74AE8//TQkEglqa2sZqqmpwR9//GHlf1tCIBBgypQpeP3112EymazeX11djbKyMsb3tQaRSIS//e1vmDJlChoaGph+ZabKykocPHiwVV43NzcMHz4cQ4cOxfz58/HEE088OOAPIsK6detw4MABAACPx8Po0aPx3HPP4bnnnsMTTzwBg8EAhUIBtVoNtVoNjUZjcS+TybB06VILmy8QCDBy5EiMHz8eEyZMQO/evZm+oNVqrSgiIgK7d++20P/pp59m+lNoaCiMRiOju8lksvgWnU6HoUOHMqsR3N3dMWnSJEyfPh3Tpk1DYGCgVRzxYCwRExODd955h3m/u7s7wsLCMHXqVCaOaGhosOjTZjL/2zvvvIOLF5kFg+DxeAgNDWX694ABAyCTySCXyyGTyayooqKizfoMDAzEyJEjERISgmeeeQaurq4W9tbc18ViMa5evdqqjODgYAwfPhwjRoxg7G3L9iSVSiGRSLBv375W40KBQIAhQ4Zg0KBBmDhxIjp37sx8izm2lMlkSE1NRXp6uhW/k5MTnn76aTzzzDMYPHgwJkyYAKFQaOX7mpqaMGzYMKZvuLq6Yvz48Ux9dunSBSqVCnV1dRbl2fJaVFRkZafM6NOnD5555hnmOzw8PKDX663oxRdfxI0bNxi+bt26YcqUKZg8eTLGjx8PZ2dnKBQKNDU1QaVSoampyeK+tLQUX3zxhcW7+Xw+hg8fjrCwMIwbNw79+vWDk5MTjEYjDAYDYy/N9ytXrkRycjLD37t3b0ydOhVTp07Fs88+Cw6HA5lMZpUnmKmyshKffvqpVRn4+Pjg2WefxZgxYzBo0CAEBARAJpNZxYRSqRQ5OTm4dOlSq2UpEAgwaNAgTJgwAcuWLQOHw7HoE1qtFg0NDXjxxRctVpWIRCKEhYVh4sSJmDhxInr27Nmq/H8VOBxOIRENselhWzPcFsa0OyxnXOUP/C5rheddAB+1+HsjgHcf9q5Hfca1W7duFrM+9pB5xM5RfgA0atQo6tmzp0O83t7e9Oabb9Lvv//eIR26detGffv27ZCMXr16dYjf2dmZ+vTp0yEZPj4+zIyNIzR48GBauHChQ7xeXl705ptv0pUrV2jgwIEOyeByufTcc89ZjPDbS56enrRq1SqLGVV7aejQofTFF184zD9q1Cg6dOgQrV692iH+wMBA2rhxI925c8dixsYRMo+MO0I8Ho/Gjh1LPj4+DvE7OzvTggUL6B//+EeHvoHD4ZBIJHKYv2/fvvT22287zD927FiKiIigVatWdeg7zDOZjpCTkxPNmDGDli5d2iEdAFisFLCXRCIRhYWFOczfqVMnWr9+PTND7igFBwd3iL9nz54WKz8cIQ6H4zBvaGgo/frrrxYzqva2h5kzZ1JkZKTDNv/pp5+mPXv20I4dOxz+Dg8PD1qxYkWHyrJXr140b968DtUF0OyDOsLfkX4BgIYMGUKhoaEdktHRNgmA3N3dHeYVCoW0ePFi8vPzc1jG6NGjHfZ9QPPqpaVLl3YotvT396fFixd3qBz79+9P/fr1c5jf09OTwsPDO6QDj8frUIwONLdrgUDQofoICQnpkA6dOnVyuE1xOByaMmVKh+JCMz399NOUnp7+b8unYMeMKw//GXBa+Tdq9UEO5zUArwHNMwePMjw8PAA0j1J5eHhYUW1tLS5cuGDBM2jQICxatAgvvfQSrl27hrCwMHC5XHh5eUEkElnR6dOnLdbg9+jRA0uXLsXixYvRs2dPzJ07F7dv34a/vz86derEUEBAADp16oTq6mps376d4R81ahRee+01zJs3D0KhENeuXXP4+4ODgzFt2jTcu3ev3VlALpfb6j4AV1dXTJkyBbNmzcLSpUuZ583l5+7uztxfv34dFRUVDC+Hw8GYMWOwcOFCzJs3DwcOHMC6desANI8wubu7M+Tm5gahUIiUlBSr98+aNQsLFizApEmT0KdPH5SXl8PLywve3t7w8fGxuF65csVilDIgIACLFy/GsmXL0L9/f0RHR+PIkSPw9fVFcHAwgoODERQUxFyDgoKwatUq1NXVAQAGDx6M119/HS+99BLc3NwAAH5+fgCaR9v8/Pzg5+cHf39/5v7u3bs4cuQIo0PPnj0RHh6Ol19+GZ07d8bFixexceNG8Pl8+Pr6wtfXF35+fsy9r68vDh8+bLE/Zty4cQgPD8ecOXPg6uqKV199FampqfD09LTgN1/VajX27NnD8Pv6+mLJkiUIDw9H//790dTUhI8++giurq4IDAxslX777TemLL28vLB06VKsXLkSTz31FADg7t274HA4CAgIsCrDoKAguLm5Yfny5cyo87hx4/D6669j1qxZ4PP5AJpnih7cl+bi4gJnZ2c4OztDo9G0Ous7fPhwzJ07FyaTCe+//77V77YgKCgI/fr1Q3V1NWQyGXx9feHv78/Upfn++vXrOH78OMPXv39/rFixAosWLYKvry9SU1OtZPN4PDg7OzPfIpVKrfYAurq6Yvr06Zg7dy6OHz+O06dPw8PDAz4+PvD19YWPjw9zL5fLERHxv4tfvLy8sGDBAixfvhxDhw6FRCLB9u3b4e7ujk6dOjF12PJ+z549MK+O8fb2xrJly/Daa6+hd+/eAJr3/D8IPp/P1AWXy211f05gYCDmzJmDuXPnYtq0adDr9fD29mbasvkbfH19kZmZafGe3r17Izw8HIsXL0ZQUBC+//57i9kSHo8HFxcXCAQCCAQCuLi4tDqL3717d8yfPx/z58/H4sWLcf36dQgEAnh5eVlRRUUFWq4S4vF4mD59OpYsWYLp06cjLS0NYrEYLi4uVv3KfP/9998zexKdnJwwffp0vPLKK5g6dSr4fD6Ki4st6tls48xXlUqFsrIyi2/o1KkTXnzxRSxcuBACgQAhISFW32kLOnfujMmTJ+P27dsWvqNlOQqFQhCRhb02Y/jw4Zg/fz5mzpyJXr16QSgUIigoyKo9BQYG4tixYxCLxQCafe2SJUuwcuVKDBgwAACwbds2AM3tzezzWpKHhwfeffddxkZ069YNr776KpYvX47g4GAAze2rpqaG0eFBSklJYWbAhUIhFixYgFWrVmHIkCHgcDg4efIkgGZb4+vry/gLM3l7e2PXrl0WqxHCwsKwfPlyxt4OGWLbJENrcHFxYXyHGc7OzhAKhUxdCIVC3L5922pFRNeuXfHCCy/ghRdewLZt23Ds2DHmNycnJ7i4uDBERKipqbF6f//+/TF//nyMHj0a48aNc+gbBAIBgoKC2t3r6OTkBC6X2+oedGdnZ0ycOBGzZ8/GmjVrGJvP4XCYNmkm84zfg++fNm0aXnjhBUilUvz1r38Fn8+Ht7e3FXl5eWHPnj0We0NHjRqFZcuWYf78+fD09MTAgQNRV1cHkUhkZaN8fHxw48YNxMbGMvydO3fGyy+/jGXLlqFXr15ITk7Gjz/+CD6fb2GnW7ar/fv3W3zHqFGjsHz5csyfPx8eHh6YOXMmLly4AFdXV4hEInh7ezMxpbe3N7OCzAw+n48ZM2bg5ZdfxtSpU3Hr1i0cOnTI/spEc38cOHAg6uvrcfHiRQgEAgsdzFeTyWSxuoTL5WLSpEl4+eWXMXPmTDg5OWHfvn1W8jkcDvh8Pvh8PnQ6Xatton///syKr6+//hpAsy12c3ODq6srXF1d4ebmBoFAYOWbnJycMHHiRLz00kuYNWsW+vbt69C5Bd7e3pgxYwaCgoJQUlICoNlet8wRzDFuUlKSRYzs7u6OOXPmYNGiRQgLC8OUKVOQlJRkERea/YU5LmxZlt27d0d4eDiWLVuGLl26oKioCBs3brQoQ7PPM9vu6upqqzhdJBJh1qxZmDdvHiZMmAAXFxe7y+HfAlszXDPBesb1GoCgf94HAbjWCs8CALtb/L0bwIKHvetRn3GVyWSkVqvbXFc/ffp0Apr3tnz44Yd0+fJli9+1Wi0pFIo2+a9cucKMPr366quUnp5u9WxjY2O7a+FfffVVZnb10qVLVr/r9Xqqrq4miURC9fX1JJfLSalUUlNTE2m1WlIqlRYzT3379qUNGzZY7OlraGggiURCMpmMlEolaTQaMhgMjK579+5l+EUiES1dupTOnDljsYevrq6uzf0Zer2eGTkbOHAgbdmyhe7cuWPxjEqlooaGhjbX5Zv3dvJ4PHruuefoyJEjVnsZ5HJ5u/uOQkNDicfj0ezZs+ncuXNWewd0Ol27+0yzs7NJIBDQsmXLKC8vr9VnFApFuzosWLCABAIBLV68mJKTk63qXq/Xt9um7t27R05OTtSlSxfauHFjq3vPGhsb290rs2HDBuJyuTR16lQ6efJkq8+2t3eoqamJRCIRDRs2jPbt29fqXk61Wt1uOezevZtEIhEzU90aamtrSSaTkUqlIr1eb1Um5v3fHA6HRo0aRd9++61Fu1KpVFRdXU21tbUkkUhIKpWSTCajhoYGUiqVlJubazUi+emnn1JRURHzLoVC0e5ekenTp5O7uzu99tprlJeXZ6WjVqsliURCDQ0NpFarrer73r17xOfzCWiewVmwYAGdOnXKokyVSmW7+1zWrl1LHA6HJkyYQIcPH7bat2cymdqtT7lcTkKhkEaOHEkHDx5sdd+fQqEgqVRKSqWStFqt1Xfu27ePKccuXbrQW2+9Renp6RbfK5fL27R1BoOBunfvTh4eHvTqq69Sdna21TtUKhVJpVJSqVSt1klCQgKjw1/+8hdav3495efnW8iRyWTt9g3zjOrw4cPp+++/J4lEYvG7VqulxsbGNvtncXExAc2zR1u2bKGqqiqrZ+Ryebt2f+XKlQQ0z6K98sorlJiYaPG9Op2OsflSqdTC5ms0GpLJZBYrBZ566in68MMPrWy+2f+1pse2bdsY/mHDhtHWrVut9n+1Z6e0Wi35+fnRkCFDaO/eva22P7Va3W5d7N+/n3g8Hs2dO5fi4uJa1VOpVLa7Ly4kJIT69u1L3333Xat7jDUaDalUqjZlpKenM+3ps88+a3UPnEQioaqqKqqurqbq6mqqqamhmpoaxu4sX77cYhZpwoQJtGPHDiovLyei5vqsq6trs11XVlYyM8udO3emt956y6p/yOVyqq+vb1PGZ599xugQEhJCX3zxBV29epX53WAwMN9g1r2uro6kUinV19eTRCKhLl26MDL8/f0pPDyczp49y9gqhUJhEUeYfYBZz5ZnRLi7u9OLL75IR48epYaGBouyVCgUpNPprOrEZDIxqxUEAgHNmTOHIiIiLNqWWq1ut39GR0cT0HwewcaNG+nGjRtWz7QXhxARTZw4kZydnWn+/PkUExNj9axOp2u3XV66dImA5v2tH374Yas6KBSKdmMRs40YNmwY/fDDD1RXV2fxuzkubMv31dXVkb+/P1Mf3bt3pzfffJPEYjHjaxobG9vd+/rVV18x9mXLli10//59i99NJhPV1NSQVColhUJBarXaoqyMRqPFar9hw4bRP/7xD7p+/TrzjEqlIrlc3qb/O3v2LBMDjBkzhn766Scrm20ug/r6elIoFKRSqUir1TIx7owZMyx815o1aygpKYl5p0ajIblc3mabKCwsZPr2jBkz6OjRo1Yx0cPiwpdeeolcXFxo4cKFlJiYaGXrdDpdu31DIpEwK9S8vb1p+fLlFB0dbfc+8o4Adsy4/isS162wPJxpSys8PgBuo/lgJu9/3vs87F2PeuLaHqqrq+mNN96gzMxMuzeMm3Hy5Ek6evToQw+AaAsmk4nOnj3rMD8R0c6dO+mZZ56hLVu20LVr1+zm1+v1NHr0aHr99dcpPj7epo3iDyInJ4c2bNhAFy9etJvXjI8++oh2795tZaBtRW1tLe3YscPuQylaoqyszOaDB1qDXq+nn3/+2a4Dvh5ERkYGxcXFdWjj/c8//0x37951mP/OnTtUVFTkMD8RPfQgq4chKyuLwsLC6IcffrD5sLMHsXjxYpo4cSLt3LmTKioq7ObXaDR04MABuw8IaYkvvviCli5dSufOnbP7gAyiZue/Y8cO+uOPPxzW4ebNm1RWVuYwv8FgoGnTptF7771Hubm5DtnLW7du0cGDBzvUJlauXEnr16+ngoICh3Sorq6mjz76yCKgtxdxcXEd8hkKhYKWLVtGZ8+etevwupbYtm0bjRw5krZu3WoRBNoKnU5Hs2fPpi1btjDJlb24d+8eFRQUOMRrRlxcnF0H8D0IpVJJaWlpDtcFEdGpU6daHWC0FZWVlRQcHEyLFi1y+HCmnTt30po1a6wGgmyFSqWiyZMn05dffulQeyAiOnDgAPXt25fef0Wsh6sAACAASURBVP99ysrKstv/mEwmmjBhAr3yyisUGRnpkK1LT0+n2bNnU0REhN2HTJpx8OBBEovFDtenQqGgnTt3OhyHEDUnzx3x4TqdjjZt2mQ1kWIPvvvuOxoyZAht2rSJSktLHeojX3/9tdXAoD04d+4cjR07lr777juriQxb8c4779D27dvp3r17DvGXlJRQv3796MMPP3TYb/z444+0a9cuh9uETqejvXv32n2gYUt89913FB4eTjExMf/RZLUl7Elc7TqcicPhRAAYC8APQA2ATwCcBXAcQFcAdwDMJ6J6DoczBMAqIlrxT95wABv+KWozEe1/2Pse9cOZ/j9ArVZDKBQ6zG80GsHhcMDlsv9lMItHByaTqcNtUqlUMtsF/iz8K77jz4bJZAKHwwGH09qOkv8ciOhP1+FRQFNTE1xdXR3mZ8vxXweFQgFXV1fweP+pXV3W+FfUp1wuh0gkcpjffPBTR8qBbZf/OjQ2NsLd3f1P1cFgMPyp/QJoPizxkVk+2wE8Cn3DnsOZ7D5V+D8JNnFlwYIFCxYsWLBgwYIFi/+bsCdx/e8eqmfBggULFixYsGDBggULFv/nwSauLFiwYMGCBQsWLFiwYMHikQabuLJgwYIFCxYsWLBgwYIFi0cabOLKggULFixYsGDBggULFiweabCJKwsWLFiwYMGCBQsWLFiweKTBJq4sWLBgwYIFCxYsWLBgweKRBpu4smDBggULFixYsGDBggWLRxps4vpvRG1tLSoqKjosp6P/125H+Y1GI/R6fYdkdBRNTU1QKBR/qg5SqRSVlZUO86vVauTl5cFoNDosg4igVCod5v9XQK/X486dO3+qDo8KampqOtS/5HI57t696zA/EeHevXvQ6XQOywAAjUbTIX6TydQhGyGVSlFUVNQhHVj8b3u4fPmywzKMRiOuXLnyp9uZjkKr1XaoHMx4lP+vexb/nehIDAA029uOtEsigkwm65AOjwLq6upQX1/fIRkdrQsW/3nw/mwFHjUoFAqkp6dDLBbDy8sLH3/8sU18tbW1KCwsREFBAQoLC1FYWIi6ujpcvHjRrvcTEW7evIm0tDSkpaVBr9fj8OHDdslQqVTIyclBeno60tLS8NZbb+H555+3mV+hUCA3NxdZWVnIyspCfX09MjIy7NIBaDaupaWliIuLQ+/evTFr1iyb+IxGI65evYrc3Fzk5uYiLy8PEokEly5dsluHqqoqpKSkICUlBd26dcOGDRts4mtoaGDq00wSicTmQEipVKK0tBRFRUUoLCxEUVERrly5gvDwcAwbNsxm/VUqFfLz85GTk4Ps7Gzk5OTg+PHjGDNmjM0ygOa6KCkpQVJSEsrLy/HDDz+Ay334uJXJZMK1a9eQn5/PUElJCX777Td07drVLh3q6+uRlpaG1NRUXLx4ESdPnoSXl5fN/ESE8vJypj4HDhyId9991y4d1Go1cnJykJqaiszMTPzyyy82f0dTUxMKCwuZdpmbm4vJkydj7969NvE3NjaiuLgYBQUFyM/PR0FBASoqKlBSUmKz/jKZjKmHvLw85OfnY8CAAYiJibFZhslkwuXLl5n+nZWVhc2bN2P+/Pk2y2hqakJeXh6ysrKQmZmJ6upqZGRkgM/nP5S3qqoKRUVFFnTnzh38+uuvGDRokM06mEFEuHr1KmJjY7Fy5Uq4urrazX/x4kUkJCRAKBTi9ddft4tfq9UiLy8PKSkpSEtLw7fffounnnrKLhkAIJFIkJCQgJqaGrz99ts26X379m2rspRKpcjLy7PpnUajEdeuXWN8VmFhIYqLi/H0008jNTXV7m8Amv1HQkICgoKC8Mwzz9jFa/Y1qampKC0txYkTJ+Dt7f1QPp1Oh4sXL1rY7LKyMmzatAl9+/a1SweZTIaMjAykpaUhOzsbv/76K3r27GmXDLMfj4+Ph0ajwTvvvGMXP9Bs+9PS0hAfH4+XX34ZISEhdstoampCSkoKrl69irfffhscDsdmXiLC9evXkZKSguTkZMyfPx9z5861WwciQllZGVJSUvDXv/4VTk5OdvE3NjYiLS0NSUlJeOqppxAeHu6QDpcuXWJshIeHh90yFAoFEhMTodFosHDhQrve/ccffyAjIwMZGRnIysqy29bpdDoUFhYyMpycnHDq1Cmb+eVyOfLy8pCTk4OcnBzk5eXh0KFDmDJlis0ygOYBRrMPv337No4fPw4XFxe7ZOj1euTk5CAhIQEDBw60uU0pFAoUFhYy/q+goAAGg8HuwSm5XM74rYyMDAwfPhxbtmyxSwYA3L59G0lJSRCLxdi8eTP+8pe/2C2jpqYG8fHxkMlkWLt2rd38TU1NSEtLQ0JCAhYsWIAhQ4bYLeO/Ef/vE1e1Wo2srCyIxWKIxWLk5+fDaDSCx+O1mSg1NTUhNTXVIlG9d++e1XPz5s2DRqOBVCqFj49Pq07DHESaE9W0tDRUVVUxv2dnZz/U2cjlcmRmZjL85g4NAKGhoZgxY0abvObgxxzAZmZmoqyszGI07+zZszYbp+rqasTHxyM+Ph4JCQmora2FSCRCeXl5mzxVVVUWSWp+fr7VaP/mzZvB4XBARO2WR21tLeNozQ4bAIRCIW7cuNEqjzkhaZmkXr9+3eq55cuXQ6vVorGxEe7u7ha/mZNCc5J6/fp1qxFRJycnTJ06FdevX0dQUJCV8zQHO+YkNTs7G2VlZRYjgs899xxCQ0Pb/P4HZSUlJSExMRHJycnMyOThw4dbTVqJCBUVFRZJamFhoVVd9O/fH4MGDUJjYyPc3NzarA+JRMI4udTUVIt29d133z00aSUi3Lp1i0lUU1JScP/+fQCAt7c3duzY8dByUKvVyM7ORkpKClJTU5GTk8PMTq5du7bNpNVkMlkMnuTm5lrVhUAgwJo1a6DT6eDs7GzBr9VqUVJSwjjYgoICXLlyBSaTyeK52bNng8fjQalUwt3d3aIs1Wo1iouLmT6Rl5eHmzdvWum6Z88eyGQyiESiVutVqVQySWZWVhays7PR0NDA/D5y5MiHBg/3799n7ENmZiZKSkoYGwMAx48fh1AotOIjIsTGxiIrK4tJrKqrq62e69q1K3r06IHy8nIEBQW1KqslNBoNUlNTERUVhaioKJSXl2PZsmU2J63V1dVITExEQkICEhISUFVVBS6Xa9PgmEajYQY/UlJSkJOTw8xYL1682Oak1WAwIC8vD7GxsYiNjUVBQQGICFFRUa0+r9PpcPr0aRQUFDBl2bIezRgzZgwMBgPu3r2LwMBAi8GEO3fuML7LnKSqVCorGUuWLMHt27cRGBgINze3h37LrVu3EBkZicjISKSmpkIoFOL27dsP5WvPRnz99detJq3mgYaWfau0tNRq1YGvry/CwsJQXV0Nf3//NhOmmpoaZpA3LS0NFy5cYHRYs2aNzUmrTCaDWCxm/N8ff/wBAMjKyrKJ32g0ori4mPGdWVlZ0Ol0GDFiBL755hubZADAzZs3ERMTg+joaKSkpECj0WD//v0PjSPMPqOl/zTHIr1798Zvv/1msw5NTU0Qi8WIiopCZGQk7t27hw8++MCmpFWn0yE3N5fxXbm5uTAYDPDy8sKtW7fs0iE5OZmxEXfu3MHChQttTlqJCJcvX0Z0dDSio6ORkZEBg8GA/Pz8dvkMBgPKysqYJDMjI8NipVZ4ePhDk9aGhgZkZ2cjIyMD6enpyMvLY2wMh8NBYWFhm/VpMBhw8eJF5ObmMomqOQ4yY8yYMRg5cuRD46mW/TMlJQVlZWXMb4cOHbIpLiQiXLt2DQkJCYiPj0dKSgoaGxvh6+vbZn2q1WrGf5r7+bVr16xiqk8//RQKhQIuLi5WPtj87oqKCiZJzczMxMWLFxk53t7eOHPmzEO/AWiOLcViMZKSkpCUlMTYtwULFtictOp0OmRnZyM2NhZxcXEoLi4GACQlJdnEb56AMJdlRkYGdDodBg8ejK1bt9ok4/8COI/yMpghQ4ZQQUHBv1xuQUEBoqOjIRaLkZ2d3eoyO4FAgAEDBsDV1dWKhEIhpFIplEoloqKibFqmx+fzERgYyBCPx8Pt27dx9+5dSKXSNvmCg4Ph4eEBT09P5urp6QlXV1fcuHED9+/fb7VDmyEUCuHv78/wtZRhMpmQnZ1tZdRag5ubG7y9veHj4wNvb2/m3sPDA927d0dlZSXi4uJw4cIFK94uXbpg5MiRcHZ2Bp/Ph7OzM0M6nQ4FBQW4ceMGamtrH6qHs7Mz/Pz84O/vD39/f/j5+UGj0UCn06GioqLNwFMoFKJXr15wc3ODu7s73NzcGBIKhaisrIRUKkVycrJNS3BcXV3RqVMnhvz8/JhR3dzc3IfyA81lGhQUhODgYAQEBKCyshJXrlyxaQmPu7s7fHx84Ovry5BQKIRer4ezszMSExPbXII6evRouLq6QiAQQCgUMuTi4oLq6mrU1tYiNTXVIjFpC0KhEJ06dUJAQAACAgLg5uaGmzdvQq1WtzsSGhwcDC8vL3h4eFiQu7s7ampq0NDQgKtXrzKJamvv7d69O9zd3a3IPOik1+tRWFjYZv8MCgqCn58fw2d+v7u7O2QyGW7evImioiKblhJ5enoy7dLPzw++vr5obGyEQqGAWCy2SljbK0szubi4QCqV4sKFC6irq3soP4/Hg7+/P1MXfn5+qKqqQkFBARobG9vldXJysujX5nsej4f8/HybbISHhwfD15IEAgGICPHx8TYHniKRiOkb5uurr76KlJQUREZGIjEx0SrhWrRoEbp16wYOhwMulwsOh8OQ0WiEUChEfX09EhISUFpaavVOLy8vhIWFMUFQyyvQPDilVqtRVFQErVbbqt5mu2RuSy3blIeHB2PPY2NjkZiYCLlcbsHP5/OxaNEi8Pl88Hg8q2tjYyN0Oh1OnTplk7006xQUFISgoCAEBARAo9EwAxG2wN3dHUFBQRb+a+7cuSAiREZGIioqyqp99O/fH7Nnz2aCYnM9AM0DKdnZ2ZDJZO3aiKCgIIhEolZthNFoRENDA8RiMSQSyUO/gcPhwN/fH4GBgejUqRN8fHxQXl7O9PO2IBKJ4OPjY+U/zXp4eXnBZDIhLi4OeXl5Vv1cKBRi+vTpFj6vZdtqampC586dkZ+fj6SkpFaXPfbt2xdPPvkkXFxcGDLLcHFxQefOndGjRw8mWX3wezgcDl577TU4OzvDyckJPB4PTk5OcHJyAofDwZUrV6DT6VBcXNymvfX29ka3bt0Yn9nSh7q7u8PX1xcLFy5kElWxWGy1/eD111+Hr6+vRb80t4mamhpwuVzcunUL6enprQ6m+Pj4YMCAARY+60EftnDhQiQmJiIqKgrJyclWOsyfPx89evRg7AOXy2WIw+GgX79+4PP5TLL64JYYb29vLF26FE5OTuByuUw5crlcGI1GZGRkoLi4uF176+TkBC8vL4hEIuZqvm8ZD7UXh7i5uVnJMPvT8vJyXL9+3aYtKM7OzvD19YWfnx9D5thUqVS2O5DXvXt3eHp6tmrnuFwufH198ccffyAhIaHViZ3g4GAMGTLEol2byTzbf+/evVZjytbg7e2NgIAAJh4xD/w+bHuXUChk6kAkEsHb2xsikQhubm6Qy+Xw8fFBVlaWRdLeEr1790ZwcLBFO2xJQUFBcHZ2RmxsLMRisdVEgEAgwAsvvAA+n8+Q2ebz+Xw0NTUhKCgIRUVFSExMbDUW6N27N/r06dOqfXBxcUHXrl2xcuVKm8rxzwKHwykkItumjInokaXBgwfTvwNyuZx+/fVXmjp1KvF4PALgEF2+fJlqa2tpy5Yt1LNnT6vf/fz82pU/evRo2rJlCw0YMMBhHbZu3UqvvfYaiUQih/h79epFpaWltG7dOgoICHBIRr9+/cjZ2dnhb+Dz+aTT6ej06dM0bdo04nK5dst4/vnnaf78+SQQCBzW4+7du1ReXk4ffPABderUyep3Ly+vdvnnzJlDRERFRUX06quvkqurq8Xv7u7uFBAQQBwOp00ZiYmJdPr0aXruueccKoeuXbvS5MmTycnJyeFyOHjwIFVVVdGXX35JPXr0sPrdxcWlXX5PT0/69ttvaejQoQ7rsGTJElqyZAm5u7s7LGPr1q00YsQIh/mXLVtGlZWV9NVXX9Hjjz/ukIzi4mK6e/cuffrpp/TYY49Z/e7h4dEu/7PPPksajYaOHj1K48ePt/qdy+U+tJ0cPnyY9u/fT2PGjHHoG7p06UJFRUW0du1a8vX1dUjGN998Q0ajkeLi4mjmzJlWOvv7+zss21Z66qmnOvyOL7/8ksLCwtrtw+1Rp06dHtp/HkZJSUmk1WopIiKCRo8ebfV7cHAweXp6tlsORESlpaW0evVqqzbI4/EeWk4Pa7cPIzc3N/r+++8pNDTUYRkffvghabVaOnbsGI0bN67VdzysrH/++WeaOXMm8fl8h3To2bMn+fn5dagsRo0a1SH/KRKJHG6PZlq1ahVNnDjRIZ8DoEN+10wTJ06kfv36dUhGR8vBx8enw99x7tw5Wr9+PQUHBzvEP378eDp69ChNmzbNYT8eGRlJYrGYFi1a5FDddO/enTZt2kS9e/d2uBxGjBjhcFwKNMeFJpOJcnNz6ZVXXrGKpwC0+m8tac2aNbR///5W7YOttHDhwg61i+Dg4A73j5EjR3bIRgwZMuTfkkv9KwGggGzMDf9fzri2RF1dHU6fPo2jR48iJSWFGeXq0qUL/v73v6OpqQlNTU1QqVTMvZm2bduGgIAAAM1T+ElJSdi9ezfOnj0Lo9GIX375BcuWLYNUKkV1dbUVPf7448x+qrKyMhw+fBiHDx9mRqc8PDxw6tQpqNVqKBQKKJVK5mq+X79+Pfr06QOtVovo6GgcOnQIkZGRzCzTsmXLsGjRIgv+luTj44PNmzcDaN57EBMTgwMHDuD8+fMwGAxwcnJCVlYWeDweZDIZ6uvrIZPJLO6XLFmCgQMHIjIyEqdOnUJMTAzUajVTxgMHDsScOXOg0+ksSK/XM3r++uuvzPP37t3DgQMH8MsvvzDLrbKzs9GtWzdIJBLU1dVBIpFY3E+aNAkzZ86EUqnE77//joiICMTHxzOzhr1798bnn38OlUoFlUqFxsZG5t78965du5hlRHq9Hr///jt2796NxMREAM3LIWfOnAmJRIKamhpUV1ejpqaGuR8wYIDF/puGhgb89ttv2LVrFy5fvozOnTujoqICJpMJtbW1qKqqQlVVFSorK5n7jz/+GJ07dwYAVFZW4rfffsO+ffuYpcuff/45Fi9ejPr6ekilUisKCgrCBx98gLq6Opw5cwbHjh1DcnIyMxPg5OSEb7/9FkQEtVrdKq1evZpZjmwymSAWi7F3716cOXMGer0eq1evxvbt21FbW2tBNTU1qK2tBYfDYfaM3Lhxg2nXLWcC9u3bB29vb6YtK5VKNDY2Mvdz5szB9OnT0dTUhMjISBw5cgTR0dHMAUCDBw/Gxo0b0djY2CYdOHAATk5OKC8vR0REBA4fPowrV64wOmzatAl9+vRh3t2SlEolRo0aheXLlwMAiAjp6en4+eefceLECWg0GvTp0we5ublMG3zwKpFI8NVXX8Hf3x9A8xKumJgY7NmzB9HR0TCZTNi1axdeeeWVVttUTU0NunfvbrH35datW/j555+xf/9+1NTUQCQS4e7du1Cr1Vb1YaY333yT2edXXl6OX3/9Fb/++itzcNzq1avxxhtvMP35wauHhwdjI3Q6HaKjo3HgwAFERUXBYDCAw+EgPT0dLi4ujG14kBYsWIBx48Yx33H37l3s3bsXe/fuRXV1NebNm4cTJ05Aq9Wiurraok9UVlZCqVTinXfewfnz53Hu3DmkpKRYHQY1bdo0ZuUDETEHmJhp6tSpWLRoEVJTU3Hy5EmcPn3aYtbysccewxtvvAGtVgutVgudTmd1v3PnTvj6+uL+/fs4duwYDh8+bHGo1Pr16zFixAiLdtTyfsCAAVi+fDliYmJw5swZREZGWozAu7q64s0334Rer4fBYIBer7e4NxgM+Oijjyz2bV68eBE//fQTDh48CKVSiU2bNuGjjz6CSqViyrClnfHx8cHf/vY3hr+xsRFHjhzBTz/9hOLiYvD5fFRWVsLT0xO1tbWorq5GVVUV47eqqqowf/58SCQSnD9/HlFRUVarRB5//HEMHz6c8acPBh4CgYCx+eXl5Thy5AgOHz5sMXO7Z88eBAQEWNiIljRjxgyLcxOuX7+OPXv2YP/+/aivr0dYWBgSExOhUCgY3c19zHy/Z88eODk5QSqV4sSJEzh06BAyMzMZmX//+98REhJi5X/N12HDhmHZsmVIT09n2lTLpfA+Pj549913mTZkbkct/eDmzZvh7e2N8+fP4+TJk4iNjbWY0Z81axZGjBjBtMUH6fHHH8fKlStx/vx5nD17FgkJCRb8XC4Xq1evBhHBaDTCaDTCYDAw90ajEW+99RaGDx+OmpoaHD9+HBEREcjOzmZkzJgxA4sXL7bwm+Z785aRlStX4ty5czh37hyys7OtZgznzp0LoVDYZjC6aNEiPP/887h06RKOHz+OY8eO4dq1awx/SEgIVq1a1abf0mg0+OabbxAVFYXff/8dCQkJFnEI0LzVplOnTjCZTK3ShAkTMHLkSPz+++84e/as1eopPz8/vPDCCzAajTCZTBZlaP57+/btCAoKgtFoRFJSEg4ePIjTp08zumzatAkTJkyAXC6HXC5HQ0MDcy+Xy9GnTx/G5ldXVyMiIgIHDx5kzkIQiUSIi4uDSqVieB+8rl+/Hr179wbQvJUsIiICv/zyCwoLCwEAGzZswBtvvIG6ujqGpFIpc+/t7Y1PPvkERISSkhIcOXIEERERzIw8h8PB4cOHwefzrWyc+X7ZsmUYMWIEkpKScPLkSZw5c8bCTgwePBgvvviiVXvWaDTQarXgcDjYv38/87xCocCRI0ewe/dupiwKCwvxxBNPMPGHOQYx30+aNIk536WiogK//fYbDh48yGwbGzx4MH755RfI5XLIZDKLejDTjz/+CD6fD7FYjGPHjuHMmTMWK2VWr16Nfv36WbXHpqYmqNVqDB06FC+//DJiY2Nx+vRpK5vv4eGBtWvXMrb+QTIYDPjss8/QqVMnxkbExMRY9PEZM2Zg5MiRbdqIbt264fPPP8ejDHbG1UFUVlbSd999R8888wwBoMLCQofk3L9/nzZt2kQvvfSS3bxGo5GSk5PplVdeIU9PTzp+/LjdMurr62nPnj00evRo6tq1K+l0Ortl1NbW0rfffkshISH05Zdf2sXb2NhIJ06coJdeeonc3d3J09OT5HK53ToYjUZKSEigF198kdasWWM3v0QioV27dtGzzz5LXC6Xrly5YrcMIqIbN27Q+vXrafHixQ7xm0wmSk1NpZdeeomSkpIc4s/IyKDw8HAaNGgQGY1Gu/hramroxx9/pDFjxhCHw6E9e/bYrYNZzpYtW2jIkCHU2NhoF6955HTt2rUUEBBA69evt/v99fX1tHfvXho3bhzx+XyqqKiwW4fi4mJ677336LHHHqMXXnjBbh2IiGQyGf3www80aNAgSktLc0hGRUUFffzxxzRz5kyH+HU6HZ06dYqmTJlChw8ftpvfaDSSWCympUuXUo8ePUir1doto6amhrZv304hISH02Wef2c1P1Pwdx48fpylTplBdXZ3NfHK5nI4ePUoLFy5kRvXXrVtn17sNBgOlpKTQG2+8QUFBQQQ0r6KxF1euXKGNGzdSz549KSwszC5ejUZDUVFR9MorrzAzdwkJCXbrQESkUCjop59+otmzZ9ttI4j+t48uX76cdu/ebTOfXq+nlJQUeuedd5iVCYGBgdTU1GT3+wsLC2ndunUUFBREb731lr2fQEREarWaDh06RM8++yzdvHnTbv7y8nL64osv6Mknn6Tnn3/eLl6DwUDp6en05ptvMissMjMz7ZLR0NBAR44codmzZ5NAIKAhQ4aQyWSymV+pVNKJEydo0aJFzCohR+KI8vJy+vvf/079+/engIAAUqvVNvPW1NTQvn37aNasWcys2LZt2+x6v8lkotLSUtqwYQP17NmTnJ2dqaqqymZ+lUpFZ8+epeXLl5O/vz8BoL/+9a926XD//n3atWsXTZ48mfh8PnE4HIdshEKhoH379tHYsWNp5MiRdvMTNa+QePfddykwMJCOHTvmkIySkhJas2YNDRgwgPR6vV28BoOBxGIxrVixgkQiEW3dutUufp1OR3FxcbRixQry9fV1OC40mUyUl5dHK1asoHfffdch/qysLFq5ciV5e3vbXZ9arZbOnz9PixcvJg8PD3ruuefs4m9p880rW+yNIxQKBUVERNDcuXNJKBTSwIED7bIRjyLAzrh2HBUVFZBIJB06pctoNDJ7JxyBRqPBrVu3HDqh0ow//vgDnp6e8PHxcVhGZWUlgoODHeLVaDRISEhAcHAwBg8e7LAOKpXKpkNC2sK9e/cgl8vRr18/h2UYDAbweB07z4yo/cMQHobGxkZmn5QjqKqqQklJCaZOneqwDkQEg8Fg0wmyrcFgMKCoqMiu05UfxP3799HU1IRevXo5xG/e3x0aGmrT6cptoaPt0ryqoSNtQqvV2n2yY0solUpwOByrA8fswb179/DYY485zA843jf0ej0yMjKQmJiIjRs3QiAQ2C3D3B50Op3FzLA9ICLk5+cjJCTEof5pMBiYE5pffPFFh3Qw6wGgQ23KaDTaffqr+d3Xrl3D+fPnMWzYMLtPP2/5/sLCwg7ZCKBjNpv+Ods0cOBAh2yEyWRCfn4+6uvrHba3jY2NiI6OxtixY5nVXfZAp9MhNTUV5eXlHdrjdvHiRXh7ezOrgeyBWq2GWCxGXl4ePvnkE4fKkohQXFwMHo+HAQMG2M1vNBqRk5ODuLg4fPDBBw89/K01NDQ0IDY2Flwu164T2B9ERUUFgoOD9gX7LgAAIABJREFUO+Q/796969AptmZoNBpwOByH/YZWq0VpaanD/VOv1yM1NRUBAQEO1acZrR2MaA80Gg3q6+s7FN/Gx8dj0qRJDvkdg8GAjIwMSKVSh07sBppjkOjoaIwaNQpBQUEOyXgUYM+MK5u4smDBggULFixYsGDBggWL/zjsSVwdn2pgwYIFCxYsWLBgwYIFCxYs/gNgE1cWLFiwYMGCBQsWLFiwYPFIg01cWbBgwYIFCxYsWLBgwYLFIw02cWXBggULFixYsGDBggULFo802MSVBQsWLFiwYMGCBQsWLFg80mATVxYsWLBgwYIFCxYsWLBg8UiDTVxZsGDBggULFixYsGDBgsUjDTZxZcGCBQsWLFiwYMGCBQsWjzTYxPUBNDQ0IDk5GV9//TU++eQTEJFDcoxGI4qKinDr1i2HdZHL5UhMTHRYBwAgIjQ0NDjMDwAGg8EhHUwmEy5fvowDBw4gIiLC4fc3NTUhOTkZEonEYRkAoNfrO8Sv1WqhVCod5tfpdCgsLHSYX6/XIy8vDxcvXnRYRkNDA2JjYztUFhqNBnfu3HGYH2guC4PB0CEZGo3G4Xfn5+fj+++/x7Vr1xx+v0qlQl5ensP8AFBfX4+qqqoOyairq3PYRtTU1ODs2bMQi8Ud0sFkMnXITgHN/dxRaLVapKeno7a21iF+o9GIkpISnD171mEdAECtVkMulzvMm5GRgd27d8NkMjmsQ3V1NcrLyx3mJyLcuHEDRqPRbl6TyYSrV6/i4MGDOHXqlMM6mPVwRIeWPnzbtm0OvbuhoQFisRhfffUVysrKHJIBNH9DR+rCjI60B5VKBbFY7FBZAs3fcP36dZSUlDisAwAoFIoO+2CFQuEQX319PeLj4/HFF1/g+vXrdvPLZDKIxWJs3bq1Q3GhVqtFZmamQzpoNBrk5+fjp59+wvr16ztclo76T5lMhvj4eHz55ZcdiofkcjkuX77sMD8A3Lt3r0M6AI6XgxkKhQIymcwhXp1Oh9zcXOzfv9/hNmWOj4uLix3i/28E789W4M9EfX09ioqKUFRUhMLCQhQWFlokmomJieBwODbJ0uv1KCwsRGpqKtLS0pCRkQEXFxfcuHHDZn2kUinS09ORmpqK1NRUlJSU4N1338WECRPs+q66ujokJCQgNjYWiYmJiImJwYABA+yWERsbi6ioKGg0Gpw+ffqhPFVVVcjNzUVeXh5yc3NRUFAAhUIBPp+P0tJSm9/d0NCAzMxMpKenIy0tDfn5+Rg0aBCysrLs+gYiwpUrVxAVFYWoqCjMmTMHa9eutYv/6tWriI+PR1xcHMrKyuwKYgwGAwoLC5GcnAyxWIzMzEysW7cOgwcPtolfrVYjNzcXaWlpSE9PR3Z2Nrhcrl1tSiKRMOWYlpaGkpIShIeHY8qUKTbLMAf1iYmJSEpKQkZGBhITE9G1a1ebZQDNTiYmJgYxMTGQSCRITU21i99oNCIvLw8xMTGIjo7G6tWrER4e3i4PEeHOnTvIyclBbm4ucnJyUFRUBK1Wi+HDh2P16tU2v7+pqQlZWVlITk5GSkoK8vLy8OWXX2LYsGF2yUhPT0dSUhKSkpJw8+ZNu4MYc/ATFxeH+Ph4DBw4EAcOHHgon8FgQFlZGbKzs5GVlYXs7GyUl5fD1dUVV69etUsHAFAqlUhISEBkZCTq6+tx5swZu/h1Oh0yMzOZNvHxxx9j/vz5NvGqVCpkZ2cz7TonJwd9+vRBQUGBzfy5ubnIyMhAZmYmsrOzoVQqceTIEbu+gYhQVlaG+Ph4xMfHo6ysDJcuXbKJ786dO8jOzmaopKQEer0eX3/9Nbhc28eU6+rqkJKSguTkZCQnJ6O8vBxXrlyx6zuqqqqQlJTE9PGhQ4faZPNra2stbH5eXh4aGhrg4uLi0ACbSqVCYmIioqKicPPmTcTHx7f7vEKhYPx3QUEBCgsLGfvI5XJtGljSarUoLS1Ffn4+8vLykJeXh2vXroGIMHz4cKxfv96ub7h79y4SExOZsly5ciU+++wzu2SYTCYUFRUhMjISsbGxOHLkCHr06GETr0KhQGZmJhNHFBQUYMWKFQgLC7P53ZcvX0ZaWhoTz0gkErt8eMtviIuLQ1xcHIgIaWlpdsloampCSkoKYmNjERcXh08++QQLFy5sl0etVqO4uJipy/z8fNy8eRMAMH78eHz44Yft8kulUqZNma8tBx+SkpJsjguVSiWys7MZH5yXlwcvL6+H+nCtVouysjKmTRcWFqKsrIwZ7N27dy/4fL5NOpih0WiQlpbG2NujR48iJCSkXR6dTofS0lKLPm72V2vWrIGHh4fN71cqlcjIyIBYLGYSrcTERPTt29dmGTKZDMnJyYytcnZ2tntAxdwuo6OjERMTgwULFtgVF5onEBITE5GQkIDy8nKb/WdNTQ3jf7OyslBQUACtVosdO3bY3KZqa2uRmZmJjIwMZGRkoKioCG5ubnbFhf/t+H+ZuCYlJWHdunW4cOFCm88IhULs2bMH58+fR2BgIIKCghAUFMTcu7m5oaCggDHsWVlZVjMGc+fORUZGBjw8PBjy9PSEh4cHBAIBamtrGeeQmppq5ei5XC769u2LxMRECxlmcnJyAtAckObl5SE2NhaxsbEoKChgRm+ef/55dOvWDU1NTeDz+eDxeK12ECLChQsXmCQvJyeHGeVNTk5uk+fIkSM4c+YMcnNzce/evVbLMjAwEAcOHIC/v3+rZA7mzUFoaWmp1QhzaGgooqKi4OnpaUEeHh5wcXFh9FOr1UhOTkZUVBSio6Pxxx9/MDqsWLGizfo2o76+HklJSUxScPfuXea39evXw2AwoKGhAc7OznB2dmbqAGg2iKWlpUyimpaWZjEayOfzERoaiqKiIri6usLNzY25uri4oKGhAVlZWUyimp+fbzWqOn78eKSnp8PT0xNeXl5MOXh5ecHNzQ33799nyjEtLa3VAHbAgAGIiYlhyq9lWfL5fBARbt26xQReYrEY9fX1DP+wYcPg7e2N27dvQyAQQCgUQiAQWNQD0GzgzYlJdHS0Rfs+efLkQ+sCaE68Y2NjERMTg7i4OEaPHj16YPHixa3yyGQy7NmzB9nZ2cjJyUFNTU2rz/n6+uKrr76Cn5+fFfn4+ECv1yM7O5tJCnJzcy3qw9XVFX379kVubi7c3Nzg5uYGd3d3uLm5QSgUgsPhQK/XIz8/n3G02dnZFjIWLVqE2tpaKJVKCIVChgQCAVOWRIRr164xAygpKSmMreFwONi1axfq6+vh7OwMPp8PPp8PLpcLg8GAuLg4JknNy8uDSqWyKodevXrhxIkT8PHxYcjX1xc+Pj7w9vaGs7Mz82x5eTkiIyMRGRmJlJQU5ltiYmJscrx3795lAqfExEQ0NjYCAPr164eZM2eCiFqVYx7MMtvbgoICqxn7Z599FrGxsRbt2nytr69nnH1mZiaKi4utZqA8PT3R0NCAY8eOQSQSQSQSwdvbm7k3l0NVVRUSExMRHx+PhIQEi/a1du1aaDQaSKVSODs7w8XFBXw+HxwOB2VlZYiLi2MS1dZm2rlcLhQKBXbt2sXUgfnq4+MDd3d3NDQ0IC0tjQkAH/RjU6ZMQXV1NRQKBdMuzXaGx+Mx5ZmSksK0ywftxNdff42rV69atEmhUAgul4vDhw8jKioKubm5jH19EMHBwdi3bx/8/PwsbL35b1dXV+bZ27dvIyoqimlTWq0WAHDo0CFG35YgIpw7dw4fffRRu8mxp6cnduzYgcDAQCsSCoXYvXs3xGIxM2DQGoRCIT788EMEBAQw5O/vj4CAAPj5+cHZ2RlyuRwpKSlMstpyFYdQKMS0adMYW2kmFxcXq8EJlUqFpKQknD9/HlFRUUz7WL58ebtJq1wuR0ZGBlJTU5GSkoKioiIr/zlo0CCIxWJ4eHjA3d2diSHc3d0BABcuXGD6VlpaGqRSqQX/0KFDcevWLUgkEqt4xtXVlemzVVVVTKKakJBgIefo0aOQy+UWdurBvm4ebDbHMmlpaUx7eOKJJzB9+nRoNBrweDw4OTkx/FKpFJs3b0ZycjLKysranF3mcrnYsGGDRX2aqbS0FO+99167bUooFOKnn37C77//bhEPmslkMiErK4uJZ0pKSqx0mTJlCuLi4hj/3dKPX716Fe+99x4yMzPbbJMcDgcJCQm4dOlSq23bz8+PiUsqKioY/5uUlMT4jXnz5rWZtN66dQs7d+5ETk4OiouLodPpWn1OqVRi8+bNFv3aTN7e3tBqtcjKymLsVF5enkVZ9O3bl0k8zfbJbKvMtta8CsVsp4qKiixmJr/88ktcv37dwm8KhUKrtmWeJY6OjkZsbCyzMicoKOihcaHZ/5oT1eTkZIu47q233kJ9fT1UKhVcXFyY/u3k5ISrV68iOTmZ8cGtrcDk8XhQqVT45ZdfGJ9rtvcikQiVlZUWiWprA91PP/00YmJi4OXlxfgrkUjEtC17BkL/K0BEjywNHjyY/l1QKBS0a9cuGjBgAAGwm7hcLgUFBTnEa+YPCAggHo/nsAw+n08jR44kkUhkFx+PxyOhUEju7u70+P+w997xUdXZ//9rkpnJTCaTSQ9JQKQIBIiAFBERkSYqxQdIUVCwoeKHVaR81xXr7lpREUX6ikAMSG8B0nudSe+VJKT3ZEqmnt8f7NxfhpmQmQm7srv3+Xicxwy5c973vNt5n3e5l5EjacOGDTR48OA+f+/k5ERCoZBEIhG5uLiQq6srSSQScnd3Jw8PD9q0aRMtWbKEHB0d7coHl8ulQYMG2V0OXC6X5s+fT8888wwJhcI+f8fn80kgEJCzs7NJPtzc3EgoFNKkSZPIwcHB5no0punh4WF3HjgcDjk5OdGYMWMGlIaXlxeJRKIBlaWXl5fd+k5OTuTu7k7Lli0jsVhs9T2dnJzI2dmZxGIxicVimjdvHk2dOpU4HE6/+o6OjsTn85k2LZFISCKR0Pbt22nIkCF258Xd3d1uXeBW/xxIXfD5fBo8eDDdd999dtWjsTxXrlx5x/7dnwwaNIi2bdtGgYGBff5GLBab9Cejb3B3dydXV1eaN28ejRs3zqr7cTgc4vF4JBAIyMXFhcRiMTk5OZG3t7fdeeByufTQQw+Rr6/vgNIYNWqU3XUpEolo+vTpNHfuXLttMPqbgbRJiURis58ziqOjI4lEItq4cSMtWLDAqv5pSYRCIW3bto3Gjh3b52+Mfrp32zK2K09PT3r//ffp888/p/vvv9/usvjyyy9p2rRpdpenl5eX3WXJ5/NJLBbT9u3b6emnn+6zXkUiEXl4eDDi6elJnp6e5OXlRW5ubncljhiIn+RwOOTq6kpBQUE263K5XGb8nD59us12GGMZsVhM7u7u9OOPP9KUKVPszsu6deto3759NGHCBLv0HRwc7PYRRv0FCxbQgQMH6KGHHrK7Pp599lmr/K1x7BQIBCQSicjV1ZXc3NwoKCiItm/fTj4+Pnbb4OLiYnc5ODo6Eo/HIz6fb3c5CgQCmj17Nj366KNW9dHb4whXV1cSCATk7+9vlw3GMXjatGkD8jFcLpemT59ud3zN4XBo2rRp/7K51N0CgJSsnBs6fvLJJ7hXOXDgwCcbNmz4l6Tt5OSEKVOm4M0338STTz4JjUaD4uJiZkVo/Pjx2LhxI8aMGYOAgABIJBI4OjpCpVJBr9czO5TLly8Hn89HRUWF2Vn5ESNGMKuyBoPBZAWNiDB79mwkJCRg2LBh6OjoMNndAwCBQIDRo0dDIBDAwcEBWq3WZLXJYDBg1apVEIlEqKqqsvoZFoPBAJ1OB41GAx6PBxcXF+Tl5fWpr9frodPpoNVqodFooFaroVar0dPTA5VKhfXr1+Pbb7/Fa6+9Bk9PT9y4ccPkzP+0adOwYMECDB48GO7u7nBycmLuD9zauWpqasLMmTPB4XBQVlZmtto4YcIEZteDiEyuGwwGDBkyBJ2dnaiqquoz33fKh06nw//7f/8PPB7PprIkIibNRYsW4dChQ3B2dkZVVZXZ7haPx4OXlxezE2fJvkuXLmHbtm1wc3NDdXW12fNyo0aNQkBAANMmNBqNSZt48MEHkZubi/Hjx0OlUqGiosLkOpfLxYMPPsjsvuj1epO8GgwGfPHFF5gzZw7a29tRV1dnZqdx1753ur3z4OTkhBkzZqCystKq508MBgP0ej1TLxqNBmPHjgWXy0V1dXW/z3fRP5+FM7YpY71eu3YNW7duxYwZM6BWq1FaWmqS1ooVKxAYGAgfHx+4uLjAwcEBPT09TL7WrVuHgwcPwtXVFdXV1WbPVwmFQgwaNAiOjo7Q6/VmdhoMBly4cAGBgYFobm62+PylcRfLUnvT6/UYO3YsVq1ahba2tj53jvsqU2N5fvHFF9izZw8effRRaLValJWVmdxvypQpmDRpEry8vJjdk97lIBAIoNVqzVa7e3N7fzL6hp6eHqjVajz00EPg8/lW1afRfmN9ajQa6PV6dHR0YMaMGQBu7Qrc3ofGjRsHiUQCLpfL6PdO74UXXkBoaCimT58OnU5nVg6DBg3C1KlT4ebmBoFAAADMbo8xjS+//BJisRg3btzocyfCEsb2PWXKFISGhmL9+vVwd3fHjRs3TPq4h4cHnnnmGfj6+kIikYDP5zP+BbjV1kNDQ/Hkk09CrVajsrLSrDzd3d0hEokY33R7uY4ZMwZHjhwBn89HZWWlxWe8nJ2dLT6DbvS9b7/9Nnbu3Il169ZBIpGgvLzcpH9Mnz4dc+bMQUBAAOO3e/t8JycnODs7QyaT9elre/uD28cclUqF2bNn46OPPsKmTZswffp0yOVylJaWMm106tSpWL9+PR544AH4+flBLBaDw+FAqVSCiGAwGHDu3Dm8/fbbWLZsGbhcLkpKSkzK46WXXsLEiROZGIDL5UKtVjNlY3z8RK1W48aNG2b9g8PhwMHBoU9fqdFowOfzkZiYCJVK1Wc5GPPcW5RKJXp6ejBhwgSkp6fj/vvvtxhH8Hg8jBo1ijkRYymOOHLkCP7yl79ALBajqqrKzG8HBATAz8+P2Qm7ve17eHjgjTfeQFdXF2pray3mwxLGfqrVajF79mwEBASgqqrK6r7V20/09PTgwoULePPNN7F06VI4ODigpKTEpA+//vrrCAoKgr+/PyQSCXg8Hnp6epg2OGfOHHzwwQd44403sHDhQmi1WhQVFTHXg4KC8PbbbzNxoZubm1lcKJPJ8OqrrzJ+4vayHDt2LLPrz+FwTMZwIsLYsWOxc+dOvPHGG1i0aBEMBgOKi4sZH+Dn54ctW7ZgzJgxGDx4MNzc3MDlck3yMW3aNDQ1NfU7ZvQeO7VaLdPHPDw8cP78ebz77ruYNGkSuru7UV5eztjJ4/GwYcMG3H///fD29oZIJAKHw4FKpWJ+s3v3brz22mvMc963+xPjjj1g/v4RIgKfz2dOCdTU1FiMJZydnZlyv11fp9Nh1KhRTExnTxyh0+lw4MABeHh4oKqqqs8+agnjGPzYY4/h2rVrWLFiBUQiESoqKpiTRgDg5eWFefPmwdvbGy4uLnB0dGTGPGM6Z8+exWeffYaAgAA0NjaioaHB5F5BQUEYPnw4XFxcwOVyodPpTMp76NChePXVV622/Y/g008/rf/kk08OWPVja2e4f4T8K3dcLdHS0kLffvstPfDAA+Ti4kLd3d1mvzEYDNTS0kJ5eXmk1WqZv/f09ND58+fpueeeIycnJwJA77//vomuVqul9vZ2qq6upvz8fCotLTW5XlFRQX/729+YnQ0ul0s1NTUm91YqldTY2EhlZWWUmZlJnZ2dRHRrB/nkyZO0atUqk5WuNWvWUENDA9XU1FBFRQWVlJRQfn4+ZWVlUXp6OmVlZRERUXd3N505c4Zeeukls53Ds2fPUlZWFmVkZJBMJqP09HRKS0ujlJQUSk5Opvr6epN86PV6ioyMpOeff574fD5NnDiRDAaDWVmqVCqqqamhvLw8k7/L5XIKDg6mp556illlCgkJsViWVVVVlJubSzdv3iQiotraWtq3bx899dRTJqt19913H+Xk5FBOTg6TF6lUapIPtVrNlGVISAg999xz5OzszKTx9ddfU3t7OzU2NlJNTQ2Vl5dTUVER5eTkkFQqpZKSEsY+nU5HkZGR9NprrzE7dyKRiNra2pi6VKlU1NLSQtXV1VRYWEhSqZTkcrlJOcbHx9OGDRuYXfXXXnvNrD3K5XKqq6ujwsJCKiwsNLne2NhIu3fvNlnxy83NNfmNWq2mlpYWqqiooKysLGptbWWulZeX05dffmmy+rt48WKmDrq7u6mpqYmqq6upuLiYsrOzKSMjg7E/NTWV3n//fbOd5JCQECotLaWioiLKz8+nnJwcyszMpPT0dEpJSWHafVtbGx07doyWL19usnsZGBhIZWVlVFxcTAUFBZSbm0tZWVkkk8koLS2NkpOTSafTmeSzqamJvvvuO2Yl+rvvvjNrkwaDgdrb26m0tJSqq6tN6iIuLo7eeustZkfa3d3dpL7UajW1tbVRTU0NFRUVkVQqJZVKxVwvKCigTz75xGTn0ugjdDodyeVyam5uZsoyKyuLioqKGP3S0lL66quvTOqSx+NRSUkJtba2Un19PVVVVVFpaSkVFBRQVlYWpaWlMW3OSFtbG+3Zs4fZmTDWZ2/0ej21t7dTeXk5FRQUENEt/3js2DFauXKl2W768ePHKS0tjVJTUyk1NZXpU8nJyZSUlER1dXVERNTe3k7Hjx+n5557zqQ+p06dSpWVlVRWVsa0CWNbMtZnb7q7u+nYsWP05JNPMqvpv/76q8lvtFottbW10Y0bNyg3N9ekPo3lsG/fPpoxYwYBt3bPetdX73KorKykzMxMxuerVCq6ePEivfTSSySRSJh8fPHFF9Td3U2tra1UV1dHN27coJKSEsrNzSWZTEbFxcVm6UdGRtLatWtJKBQSl8ul2tpas/pQqVRUW1tLubm5Jm2upaWFDhw4QE888QSz+/nqq68y13U6HXV3d1NDQwOVl5dTbm4u5efnM9fVajVduXKF1q1bR66urkw+8vPzyWAwUE9PD3V0dFB9fT1VVFRQfn4+yWQyam5uNrFPp9NRaGgoLV++nNkhsIRSqWTGP2M9nj17ltavX2920mPv3r0m403vdpWUlERVVVVm6dfU1NDHH39M/v7+5OfnZzJG9y7zpqYmysnJsWjf0aNH6bHHHmPq83YMBgN1d3dTeXm5SZtqaWmhQ4cO0YIFC5hxy93dnbq7uxlf2dzcTDU1NVRaWkq5ubmUnp5OCoWCVCoVhYaG0ltvvWV2OuKll15i+pIx773l9nxUVFTQ3//+d2Y3m8PhmMQaBoOBFAoFNTQ0MHFEe3u7SV1GRUXRq6++yrSJRYsWmZVhZ2cn3bx5kwoLC01sqK6upt27d9Pjjz9ustMVFhZGzc3NTL8oLS1lYpG0tDTGR6hUKrp8+TK98sor5OnpyehPmjSJ6uvrzWKZ7OxskkqllJKSYhZnyOVy+uWXX5g+/tNPP1msz66uLiorK7PY93rHhWKx2KT/9U7DUlyo0+koIiKC1q1bx8Rlt8eFxvZUW1tLBQUFZnEhEVFHRwf99NNPNH78eAJAlZWVFm1ob2+nwsJCxsby8nL67rvvaNasWSZ1sWLFCioqKjIZOzMyMig9PZ1SU1MpMzPTLP3q6mr67LPPaOjQoQSA4uLizH6j1+uppaWFCgsLTeKI7u5u+u2332jJkiXE4/EIAM2cOdNETy6XU1NTE1VWVlJeXh7JZDKT63FxcfT222+bnJo5d+4cGQwG0mg01NnZSQ0NDVRZWUmFhYWUkZHBxBHt7e0UHBxMK1asMImPhw4dSiUlJWZxiDE27B0XarVaCg8Ppw0bNpj4ql27dpFGo6Hu7m5qaWmhmzdvUnl5OeXn51NGRoZZfWq1Wrp06RItX76c2VVuamoyq0uFQkE1NTWUnZ1NCoXC5Hp2djZt3bqVOanY2+cb6enpocbGRiouLjaJI+5VYMOO6x8+Ob2T/Lsnrkb0ej1FREQwAZutdHR00OHDh2nFihVmgZA1GAwGysjIoC1btlh0tP3R2/EHBAQwA4K1aLVaio2Npffee49GjBhBL7/8ss02GGlpaaFdu3ZZHBCsoaGhgX744QfatGmTzbpdXV106tQpWrt2Lbm7u9P58+dtTkOhUNCZM2fohRdeoKCgINJoNDanoVar6dKlS7RmzRq76pPoVp0a7TAuVthKcXExffTRR/Tll1/apV9aWkqff/45TZo0ya6+UVhYSF988QU9/PDDFidL/aFUKunSpUv06quvkre3N4WHh9ucBtGt/pWSkkI7d+60S1+j0VBoaCi9+OKLZpMla++fk5NDH3zwAU2bNo26urpsTqOqqoq+//57mjlzplkgZAs5OTm0bds2s8ltf6jVagoLC6NNmzbR0KFDae3atTbf21ifr7zyCnl5eZlNTq2lvr6edu3aRRs2bLC4QGYNJSUltGPHDoqMjLRZV61WU2hoKL3yyisUFBREPT09dtnQ0dFB+/fvpwsXLtilX1dXR7t27aLHH3+cGhsbbdbv6emhixcv0po1a+idd96xywaiWz77m2++sdkGnU5HCQkJtH37dhozZgwtXLjQbhu0Wi2dP3+eKioq7E6jsLCQ9uzZY5duc3MzHTx4kObPn2+zzzcYDJSZmUmffvopTZkyhby9vS0uolubztatW+mrr76yWZ/o1rhz+vRpWrZsmcWFgv5obGykAwcO0JNPPkkrVqywWV+r1VJ0dDRt2rSJAgICKDY21uY0jOTl5dHBgwft1h9oXGhckF+7di0zGbIVg8FAiYmJlJiYaLNuc3Mz/fLLL7R06VLy8PAw23CwFr1eT2FhYXTixAm79Nva2ujw4cM0b948k8mpteh0OoqOjqY333yTnn32WZv1jYtEGzZsIF9fXzp37pzNaWi1WooG6sWrAAAgAElEQVSIiKA33niDpk6daldcSHSrTnbv3k0XL160S1+r1dLVq1fplVdesbig8p+ELRNXDvVx9OteYMqUKWTtWyJZLKPT6aBQKCCRSOzSJyKUlZVh5MiRVr/17F5Ep9OhtrYWQ4cOtTsNtVoNImKOEdqDwWD4r3hQ3njEzV7q6+vh6+trd1no9Xo0NTXBz8/PbhvuBkSWXyZki75er7f4Ehpr6erqYo5c/REQ3XqhSmBgoN1lodfr0draCh8fn7ts3b8XrVYLg8EAJyenP9SOgfoZrVZr81tL7zalpaUYNmzYgPrGvYBarR5Qe6irq4OjoyN8fX3volX/fjo7O+Hq6mq3jzAYDGhvb4enp+ddtux/D6VSCaVSCS8vrz/UjoH6KZ1OZ/KSLnvuX19fj4CAgAHZQER/uL/8T4fD4ciIaIpVvx3oxJXD4YwGcLLXn4YD+IiIdvX6zWwAFwBU/vNPZ4nos/7SZieuLCwsLCwsLCwsLCws/53YMnEd8FImERUDmPjPGzsCqAVg6T/0iyeiRQO9HwsLCwsLCwsLCwsLC8v/Fnf7zOJcAOVE1PerXVlYWFhYWFhYWFhYWFhYbOBuT1xXAwjp49ojHA4nm8PhXOVwOOPu8n1ZWFhYWFhYWFhYWFhY/ku5axNXDofDB7AEwCkLlzMADCWiCQB+BHD+Duls4HA4Ug6HI21ubr5b5rGwsLCwsLCwsLCwsLD8h3I3d1yfApBBRGb/4zERdRGR/J/fQwHwOByOxdeZEdEBIppCRFO8vb3vonksLCwsLCwsLCwsLCws/4nczYnr8+jjmDCHwxnE+ef7qjkczrR/3rf1Lt6bhYWFhYWFhYWFhYWF5b+Uu/IfpHE4HGcA8wG80etvbwIAEe0D8ByAtzgcjg6ACsBqupf/A1kWFhYWFhYWFhYWFhaWe4a7suNKREoi8iSizl5/2/fPSSuI6CciGkdEE4hoOhEl3Y37/i+gUCig0+n+UBsMBgO0Wu2A0mDXKW5BRP/xZUFEaGtrG3Aaf3S7vhcgIiiVyj/ajAHT0dGB7u7uP9QGvV4PhULxh9pwL0BEaG9v/6PNuCcwGAx/tAn3BDqdjvW3/+S/oU3I5fIBx2Qst9BoNH+0CQPGYDD8T/n8u7Lj+t+EwWBAbm4uoqOjYTAY8N5779mchk6ng1QqRUREBJYvX47AwECr9Hp6epCdnQ2pVMqIj48PIiIi7LJBJpMhMjISjz76KB5//HGrdevr65GWlsZIa2srEhISwOPxrE6joaEBKSkpSElJQXJyMhYvXoytW7fanA8A6O7uRmRkJBYuXAiBQGCTbnNzM+Lj4xEfHw8vLy988MEHNt+/vb0dsbGxiI6OxqZNmzBy5EirdZVKJaRSKZKTk5GcnAyBQICQkL5evH1nampqEBYWhilTpmDChAk26ba2tiIxMREJCQmorq7G0aNHwefz+9UjIty8eRNSqRQymQwymQxSqRRffvklXn31Vavv39nZCalUitTUVKSmpqKiogIxMTHw9PS0Og2VSgWZTIakpCQkJSVh0qRJ+Pjjj63W741cLkdkZCQef/xxuLm5Wa2n0WiQlZXF2ODm5ob9+/fjn09C9EtrayvS09MZkclkOHnyJGbOnGmT/QaDAXl5eYiJiUFVVRW++eYbODjYvg6p0WiQmJgILy8vBAUFWaXT2NiIzMxMZGRkICMjA5mZmeByucjOzrb5/kZ/GxkZiYCAAKxatcpqvdLSUhNfWVFRAalUCpFIZJMNer0eWVlZiI6OBo/HwzvvvGOTPhGhsrISsbGxiI2NxdatWzF+/Hib0gCA2tpaREZGoq6uDn/+85+tvndFRQXTL2UyGTIyMvDbb7/hqaeesun+arUaUqkUsbGxKCkpwYEDB6zyEbdz48YNREREYMiQIXjyySdt0m1ubkZiYiISExORnZ2N4OBg2PKui6amJqSmpjJjz+TJk/H111/bZIOxb8XFxSE+Ph5///vfbfL5vamurkZpaSnmzp1rsy4RIT8/H+Hh4Zg7dy4efPBBq/XKy8uRnp6OtLQ0pKenAwBiYmJsun9PTw/S09ORmJiIpKQkrFy5EmvXrrU1G2hra0NMTAxSUlLw6aefQigU2qRvjKeio6Ph7++PdevWWa2r1WqRk5PDtIesrCxcuHABw4cPtzUbMBgMyMjIQGNjI5555hmb9bu7u5GQkICoqCisW7fOah+hVCqRlZXF9HGpVAo/Pz+Eh4fbbINCoUBiYiKio6Mxb948m9tlS0sL0z9LS0sRHBwMZ2dnm+1ob29HREQE3N3dMW/ePJt0iQglJSWIiYlBcnIydu7cCS8vi6/MMUOv16OoqMgkvp0xYwZ+/PFHm/MA3OojMTExmDJlitU2GCEiFBUVITo6Gm1tbdixY4dVegaDAeXl5Uw8JpPJkJmZiTNnzmDOnDn2ZOM/D+MO0L0okydPpn81BoOBCgoKaM+ePbR8+XLy9PQkAASApFKpTWns3r2bli5dSq6urgSAHn74YTIYDBZ11Go1SaVS2rdvH7322ms0ceJE4nK5zL0BEIfDoYSEhD7TuN2G3Nxc2rVrFy1evJixYejQodTT09OnXmdnJ0VFRdGXX35Jy5Yto8GDB5vYAIDOnj17x3ur1WpKTU2lH374gVavXk3333+/if6wYcNIqVT2m4felJeX0+7du2nBggXE5/Np+fLlVulVV1fT8ePHacOGDRQYGMjYwOfzqby83Ko0Ojs76fLly7RlyxaaNGkScTgcAkBPP/30HfUMBgOVl5fT8ePH6e2336aHHnqIHB0dGRscHR0pJyfHKhuIiORyOYWGhtI777zD5GX48OGkVqv7taOyspKOHj1KGzZsoLFjx5rUx4kTJ/rUq66upnPnztGOHTto4cKF5O3tbdYexo8fT+3t7X22S41GQzKZjPbu3Uvr16+nwMBApgyNcuDAgX7zf/PmTfr999/p3XffpWnTphGPx2P0PTw8qKWlpf9C7IWxTT355JPE5/PpiSee6FensbGRzp8/T9u3b6eZM2eSQCBgbODxeFRcXNynbldXF8XExNA333xDK1eupGHDhpmV5cqVK0mv1/drh16vp5ycHNq9ezctW7bMxE+dPHnSpnKor6+nf/zjH7R8+XISi8Xk5uZG7e3tFn/b0NBA586do48++ogWLVpE/v7+ZnkAQPv376eurq5+720wGKi4uJj27t1Lzz33HJMPZ2dnqqur61OnvLycTp48Sdu2baMnnniC8W+95dNPPyWdTtevDXq9nrKzs2nXrl20dOlScnNzIwDk4OBgVf805uHAgQO0Zs0aE5/5zDPP9KtvpK2tjc6cOUMbN26k0aNHM2mcP3++z/uWlZXRyZMnafv27TRnzhzG9t4yd+5c6u7u7vf+CoWCIiMj6eOPP6bZs2ebtO1Dhw5ZnY/29nY6e/YsvfXWWzRy5EgCQGKxmJqbm++oZzAYqLCwkA4dOkQvv/wyjRo1yiQff//73++or1arKS0tjXbv3k0vvPACDR8+3ETfWh+h1WopLS2Ndu7cSUuWLCF3d3cmjTVr1lhdDkREOp2OEhMT6f3336egoCCb+2ddXR0dPXqUXnzxRfLz8yMANG7cuDu267q6Orpw4QLt2LGDFixYYGK/UWJiYvq9d2NjI509e5a2bNlC06dPN/G3gYGBpNForMqDXC6na9eu0bZt2+ihhx5ifP8HH3xglb5OpyOpVErffPMNPf300+Ti4kIASCgU0s2bN/vUM45fp06doi1bttCjjz5q0qYB0EcffWSVDUba2troxIkTtG7dOvLx8SEAFB4ebpWuUqmkiIgI+stf/kKPPPIIEws89thjfY6dKpWKUlJS6KeffqKXX36ZgoKCyMHBwWJcaM24oVQqKTIyknbs2EGPPvooU6cjRoywKo4oKyujI0eO0GuvvUZjxowxsePw4cNWlQPRrT6WmJhIH330EU2fPp0cHBxIIBDcsT5725Gfn08///wzrVy5knx9fRkb3nvvvTvqVVdX0+nTp2n79u00e/Zspi0Zxc3NrV8/dTu1tbV04MABWrJkCTk7O9PUqVOtjtHLy8vp4MGD9Pzzz9OgQYMYO8LCwvrUKS0tpZCQENq6dSs98cQTJJFIzPr3008/TXK53KZ83GsAkJKVc0MO3cPHFqdMmUJSqfSup1tRUYGoqChERUUhOjoaDQ0NZr8RiURYuHAhRCIRnJ2dzT41Gg2cnZ2RkpKCiIgI1NXVmaXxyCOPYMKECRAIBBAKhRAIBMz31tZWSKVSxMXF9XvEjsfjwdfXF76+vhg0aBDzncfjQSAQIDc3F1FRUWhsNHuhMwIDA/Hwww9DKBRCKBTC2dmZ+S6Xy3Ht2jWkp6f3e+xEIpHA29sbPj4+zKeXlxeqqqpw7dq1Ox4ddXBwgIeHB7y8vODp6WlR1q5di/T0dFy5cgWXL19GQUGBSRpbt27F2LFjweFwTAQAcnNzUVBQgLy8PFRVVVm0wdnZGRMmTICrq6uZCAQCNDY2gsPhICkpCVKpFHq93iyNyZMnY+TIkRCJRCbtQSQSoaGhAefOnUNZWdkdy9Hd3b3PMnB3d8fIkSORnZ2N69evIyEhwewYy4wZMzB79mzw+Xzw+XzweDzme0tLCyIiIlBWVoba2to+bRg7dizc3d0hkUggkUjg5uYGiUQCV1dX1NbWorCwEDExMf0eqRIKhRg0aJCJCIVCJCQkQCaTWSxDIxwOB+7u7vD29oa3tze8vLyYz4aGBkRERKCmpqZPfR6PBz8/P3h4eMDDwwPu7u7Md+O/V6xYgaysLFy5cgVXrlxBYWGhSRobNmzA1KlTmbbk4ODAfC8uLsapU6dQWlrapw0ODg4mNvS2QywWIysrCxkZGX22yd7peHt7w9fXFz4+PvDx8YGvry8cHBzQ0dGBjo4OxMbGoqWlxWI5Lly4EGKxmGmLLi4uJp9z5sxBa2srUw4ymcwkjZkzZ+KFF16Ag4ODmWi1WmRmZiIlJQUZGRl3zAcAuLi4wM/PD35+fvD394efnx+cnZ3B4/EYv3vz5k0zPX9/f8ydO9fERxk/9Xo9UlJSIJPJUF1d3W9Zenl5mflLDocDrVaLmzdvIiYmBq2t5u8GFIvFmDdvHlOOvfs5l8tFTk4O5HI5kpOTLY4ZADB69GgMGzYMLi4uEIvFjLi4uMDJyQk9PT3o6OhAZGQkMjIyzB4b4HK5eP755xkf3dtv8/l8FBUVIS8vD/Hx8f3WhUgkMuufXC4X5eXlaGtru6Pff/jhh+Hm5gaxWAxXV1eTT2dnZ7i6uqK0tBTh4eFIS0sz8xUjR47EU089BYFAACcnJzg5OTHfVSoV4+Mt1YORwYMHw9vbG25ubnB3d2c+JRIJbt68iUuXLqG+vv6OZeDm5gZPT09m7DF+ikQi5OXloaurC6mpqX0eMX/ggQcwZMgQJv+9y8LV1RWBgYGYPHkywsLCcPnyZYSGhpr0UxcXF+zevZvxLQBMxi61Wg2RSITU1FSEh4cjPz/fzIbp06fj4YcfNitHJycntLa2IiIiAqmpqf2O4a6urszYbRQvLy+UlpYiPT39jn7KxcUFgwcPNqkHo4jFYnR1dYHH4yEqKgrJyckWbVm8eDF8fHxMYhCjtLW1QaVSobi4GLGxsejo6DDT9/HxwaxZs8ziMZFIBCJCaGgoEhIS7jhucblcph30FuPfJk6cCDc3N1y9ehWhoaFITk42Sc/d3R07duyAo6OjmRARbty4AYPBgKSkJCQnJ1s8hjpp0iQEBgbC2dmZEWN+Ojs7kZWVhZiYGHR1dd2xPrlcrpmf8/b2hkqlgoODA7Kysvq0YeTIkZg4caJJGRpFqVQiMjISpaWlffo5ABg1ahQ8PDyYGMIoxn+PHDkSN27cwPXr1xEZGWlWp6NGjcKKFStM4hjjp1KpRHZ2NpRKJeLi4tDU1GTRhilTpsDPz4/xty4uLsz3GzduICYmxmKf6o1xzDDGIr1jXG9vb6xcuRLl5eW4fPkyrly5YjYOrl+/Ho899phZbMrhcNDe3o6mpibU1tYiKirK4vjF5/OxePFiszmGs7MznJycUFRUhPz8fCQmJt4xH8Ctfnq7zx80aBBGjBiB1atX96v/R8LhcGRENMWqH1s7w/0j5F+141pRUUFffPEFTZgwweLugbUyefJks50kW2T+/PnU3d1NBw4coMmTJ9uVxqOPPkrOzs522zBy5EhqbGykb775xmzF21r5+uuv6ejRo/T444/bbYelVWJbZOXKlbR+/XoSi8V2p2HcgbJXf+nSpRQaGkrPPfecyWq1LWJph9MWCQoKop07dzKr/fbIL7/8QtXV1fTRRx/1ucN2J3F1daX6+nr68ssvmR0YW2Xr1q30448/2t0vjHYMpCzXrl1Lv/76K82ePdvuNNLT0yk8PJxWrFhhV5sYNWoULVq0yOw0hi1iaYXWFhk6dCgZDAZKTU2l9evXm+1icDicfv3gI488MuC2rdFo6MqVK7RkyRKzXQhrZPr06TRx4sQB2bB582aznQdbZMSIERZ33m2R8PBwKikpoa1bt5rsvFsr999/P7333nsmK/62yqhRo+yqA6M4OzvTqVOnaNGiRSanUmyRbdu20fnz52nJkiV2p/Hxxx/TpEmT7M6Hr6/vgPomAJPddnvkkUceYcbwBx54wK40vvrqK9q+fTuzy2uriEQimjZt2oDyMWfOHLvHC6OUlJTQ3/72N7Pdd2vF0gkGW2Xp0qUDiiPmz59PcrmcDh8+TFOnTrXbBnvGbqMMGzaMfv75Z5o+fbrdaQzU3zs6OtKf/vQnZqfbHtmyZQtlZ2fTpk2b7K5bLy+vAeXjwQcfpClTpgwojbi4OCosLKTNmzfbFStPmDDhXzKXupuA3XG1noKCApw8eRIhISEmuyuDBw/GW2+9BaVSCYVCYfHz5MmTICKcOXMGp06dQkJCgknaixcvxsiRI9HT0wOVSoWenh6T71OmTMHOnTuZ38tkMuzfvx+//fYbFAoF/P39IZPJ0NzcjMbGRjQ2NqKhocHk+86dOzF8+HBcvnwZJ0+eRGhoKNRqNZPmE088gYcffhgqlQpKpRIqlcpEAgICcOzYMQAAESE+Ph4HDx7E6dOn0dPTAx6Ph9TUVGg0GjQ1NaG5udnsc/PmzcyzTGVlZThy5AiOHDnC7PotW7YMmzdvRktLC1pbW82kp6cH77zzDi5evIiLFy9a3C2cNGkShEKhSeM12kxEWLt2Lf70pz9BqVTi0qVLOHbsGK5du8bs+o0bNw7btm1DV1cXurq60NnZyXw3yuXLl8Hn8xEaGoqQkBBcvnwZPT09jA3r16/HsGHDTNpB7++zZs3CJ598AuDWsyDBwcE4fPgwcnNzmTb1+++/WywDo+zduxcdHR04c+YMzpw5g4qKCpNyeOSRRzB69GhoNBqLMmrUKBw+fBgAkJ2djaNHjyI4OJjZjefz+Thy5AhUKhU6OzvR0dGBzs5ORjo6OvDRRx9h9uzZAG49X3T58mXs27cP169fBwBs3rwZ27ZtQ0NDg0XhcrkIDg42aVOHDh3CqVOnmPKMiopidombm5sZMf775ZdfxsqVKwEAOTk5OHLkCI4fP47m5mYAwKxZs7Bjxw60tbWhra0N7e3tJt9bW1vx+eef4/Lly7hw4QKKiorM2pRxB753mzIYDMz3RYsW4cMPPwRw65TG0aNHceTIEWZn4oEHHsC+ffss2mCU48ePIyAgAMCt5+9+/fVXHDhwgNmZ3717N+bNm4fGxkY0NTUxn8bvY8eOxeeff47W1lacOXMGISEhiI2NZdq/QCDA3/72N6hUKsjlcigUCrPP9957Dzdv3sSFCxcQHR1t9pKW4cOHY9iwYTAYDBbFz88P586dY37f1taGI0eOYO/evSgrKwOXy0V1dTWICHV1daivrzf73LhxI+bPn4/o6GicPHkSZ8+eNXmZxIQJE7B48WLGR/X2VUqlElqtFrGxsczvb968icOHD+PQoUPMDm5cXBx8fHws+srGxkYsXboUr776KoqKinDixAmEhISgpKSESXPYsGHYsGED069v7+cKhQLnz5+Hp6cnMjMzERwcjJCQEJNdvzfffBNjxoyBXC5Hd3e3icjlckyfPh2fffYZpFIpTp48id9//93kZIFYLMamTZvM/HRv2bNnD/OMe09PD86cOYN9+/Yx48/XX3+NF154oc/+6efnh927d0Ov1yMqKgrHjx/H2bNnIZfLAQCOjo746aefoNFo0N3dja6uLrPP999/HxMmTMC5c+dw6tQpsxMaEyZMwGOPPYaenh6o1Wqo1WqT73w+n/EnjY2N+O233/Drr7+aPCd96NAhiEQi5tRBe3u7yeeLL76IF198EcCtdyocPXoUhw8fZup01qxZ+Oqrr9Da2sqMPb0/W1paEB4eDj6fj/z8fAQHByM4ONhkV2Tbtm0YPny4yThhLIOuri5MnToVw4cPx8WLFxEREQGVSmXSt4RCISZNmtTnuAUAR44cAZ/Px+nTp3Hq1CmzHZ05c+Zg9OjRTNndXp7jx4/Hnj17mHTj4uKYMVytVsPNzQ2pqano7OxkfMvt8tlnn+Hhhx+GTqdDREQEjhw5gvPnzzOxxOrVq7F69WqTOugtYrEYISEhqKysxO+//46TJ08iMzPTJB+bN28Gl8s16de92/Vbb72FVatWISMjAyEhITh58qTJ6YwJEyZg5cqVfY6/SqUS8fHx4HA4MBgMiIuLw+HDh5lYBgCOHz+OwYMHm7SB3rJw4UIEBgbi/PnzOH/+vNlJOjc3N8ycORM6nQ56vd6inDp1Cj4+PggNDcWJEydw6dIlkzhi1apVGDNmDJRKpYntxu9Tp07FV199xfw+MzMT+/fvR3BwMORyOQICApCRkYHm5mbGx/X+bGhowLfffovAwEAkJCQgJCQEp0+fNjndsHDhQjz22GMmvq23+Pv74+jRowCAkpISHD16FMeOHWP6hoODA44dOwadTsfEEMZ+avz35s2bcd999zGxTF5enklZjho1CtOnT4dGo4FWq2ViGON3R0dHxMTEQKfTISoqCsHBwSZ+CgB27NgBiUQCuVzO+Nze31944QW89tprAG69I+PMmTM4ePAg4uLiGB9x4MABph/cHt82NDTgww8/xPXr13Hp0iUUFxfjdown2PqaZM2bNw+ff/45ysrKmHGn94lCDw8PbNmyxaw99P48cOAA864clUqFU6dOYd++fUhOTgYA/PDDD1i2bFmfPn/o0KH49ttvzWy/l2B3XO3AYDCQTCajrVu30pAhQ4jD4dzx+TVL1NTU0K5du2jGjBkEgJYsWWKXLZ2dnbR3716aOHEihYaG2qx77NgxWrRoEfF4PAoKCrLq/P3ttLW10e7duykoKIj27Nljs75Op6OrV6/SihUryNvb2+rz9waDgTIyMuiTTz6hhx56iFkx+uqrr2y2obGxkXbv3k3Tpk0jR0dHqq6utkm/q6uLjh07Rk8//TRxuVxavXq1zTYYDAaSSqW0ceNGcnNzo/j4eJt0MzMz6YMPPmB2eWbNmmWzDVqtlkJDQ2n16tUkEAjo2LFjNqdBdOsZ0T//+c8UFBRk9fNOvWlvb6c9e/bQxIkT6dNPP7VZX6PR0Pnz5+nZZ58lkUhEjY2NVusWFxfTzp07adasWcxO0bZt22y2Qa/XU2RkJK1du5aEQiFlZWXZlUZUVBStXr2aFixYYLN+TU0N7dy5k9mNvnTpktW6HR0dFBISQqtXr2Z2pCdNmmSXj9Dr9RQWFkbPPvss/fjjjzbpqtVqunz5Mr344ovMc7bWPJd5Ozqdji5dukSLFi2id9991yZdo8/ftm0bDRkyhBwcHKiiosLm+0dERNDLL79Mrq6u9Oyzz9qkr9frKSkpid555x1mh8QWH9GbvLw82rRpE82cOdPm+lQoFBQSEkLPPPMMcblc+sc//mGTfmNjI+3bt4/mzp1LDg4OFBAQ0O8zdJbIysqizZs3k4+PD+3YscNmfYPBQAkJCfTyyy+Tm5sb1dbW2qSv1+spNjaWXn/9dZJIJLR27VqrdRUKBV28eJFef/11Zjfb0dGRSktLbbKhvLycvvrqK2aXZu7cuTbpG2ltbaVdu3bRuHHjbH4OnuiWv963bx898sgjNGTIENJqtTbpFxcX01//+lcaP348AaDvv//eJn29Xk9xcXG0ceNG8vb2JhcXlz6fxb8T7e3t9PPPP9PkyZPpjTfesOn+aWlp9Je//IV5TwSPx6Oqqiqb7t/V1UXBwcFMTLZo0SJbs8Cks2/fPpo4cSJdvXrVJl3jaZW1a9eSi4sLjRs3zmYfodfrKTo6mtavX08uLi70888/26RfXFxMX3zxBdOuBw0aRCqVyqY0FAoFnTx5kpYsWUI8Ho/+/Oc/26RvpKioiLZu3Uq+vr421WdRURF988039NhjjzFxxJtvvmnz/XNzc+mDDz5gTgakpKTYnAYRUXZ2Nm3cuJHmzJljl/69BGzYcf3DJ6d3kn/nxLU3er2eEhISrHqhQV9UV1fT999/T52dnXanYTAY7HLURtrb2+mXX36x2dHeboOtg//tNDc32/wAvJGamhrau3cvrVu3zq5AyEhxcTHl5ubard/S0kKHDx8ekA0qlcrqF0RZIj8/nz777DObJ+C96ejooOTkZLv1iW5NOmwdcG5nIHkgImpqaqKamhq7dFtaWujo0aO0bt06uyZLRjo7O20OSm+nubnZrkmjkeLiYpuDGCNqtZrCwsLo7bfftvpFdH1h68vXeqNSqejcuXOUkZExIBva2trs1tXr9RQfH08JCQl2p6FUKuns2bN2+wjjpKm/l+H1h1wut+olVX3R1NREERERA9I/cODAgOpTo9HYHcwZ6erqovr6erv1VSoVXbp0yaqX4NyOcdKzY8cO+vbbb+22oaKigr7++mubFulux2AwDEif6IpmYCUAACAASURBVFbAbuvL8HqTn59v08t8bker1dL169cpMzPT7jSIiMrKyuzWLS4upq+//pqOHDlidxqtra10+PDhAb1IZ6BxoUKhoFOnTg0orpPL5ZSUlGS3/o0bN+i7776jxMREu9NobW2l06dP261PdGsMtLddG+OINWvWUGtrq11pGAwGSktLo2vXrtmlb6S7u9suP3UvYcvE9X/+qDALCwsLCwsLCwsLCwvLvx9bjgrb/h//sbCwsLCwsLCwsLCwsLD8G2EnriwsLCwsLCwsLCwsLCz3NOzElYWFhYWFhYWFhYWFheWehp24srCwsLCwsLCwsLCwsNzTsBNXFhYWFhYWFhYWFhYWlnsaduLKwsLCwsLCwsLCwsLCck/DTlxZWFhYWFhYWFhYWFhY7mnYiSsLCwsLCwsLCwsLCwvLPQ07ce2DpqYmxMTEDCgNIoJSqRxQGi0tLSAiu/Vra2tRVFQ0IBs6Ozuh1Wrt0lWr1UhLS0NERMSAbZDL5XbrGwwGVFZW2qVLRCgrK8Nvv/2GnJwcu20AgPb2drt15XI5YmJiIJVK7dInIpSUlCA4OBgqlcquNAwGA4qKipCWlmaXfk9PD9LS0vDzzz+jvr7erjSICBUVFYiNjbVLHwB0Oh1kMhlu3rxps67BYEBJSQlOnDiBnTt3wmAw2G1HdXW13e3SyEB8hE6nQ0ZGht31CQAdHR24du0aurq67E4DgN1tEgCUSiXi4uJQV1dndxpNTU2Ii4uzW7+5uRmXL19GXl6e3WkAt/qIPRARKisr8fvvvw947BoIRp8fHR1tdxpEhOLiYnR0dAzIloH0zc7OToSHh6OsrMzuNDQaDTIzM+3WB2710ba2NrvvL5VKcfDgQbvblRG1Wj0g/dra2gHHQwPNAxHZHcsAQFtbGxISEgZkg8FggEKhsEuXiFBVVYWzZ89Cr9fblYZOp0NmZiZkMpld+sCtekhMTBxQfSoUCpSUlNitb2Qg8TERoaGhYcD3H2jfGCjt7e2orq7+Q234d8L9ow24FzAYDCgsLERiYiKSkpKQmJiIsrIyfP/995g9e7ZNadXU1CAiIgIRERFISEhAXFwchg4darV+R0cH4uLiEBUVhaioKEyYMAHHjh2zKR8JCQmM1NTUIDs726Y8KJVKJCUlISoqCpGRkRAIBFYFQkSEGzduIDU1FSkpKUhNTUVGRgY0Go3Nzl4ulyMhIQHR0dGIjo5GZ2enTZNGvV6PnJwcxMTEIDY2FnFxcfjwww+xefPmfnXr6uqQnp6OtLQ0pKenQyqVor29HSNHjkRubq5N+ejq6kJcXBwiIyMRFRWFGTNmYO/evf3qGSeIxnJMSUlBXl4eRCKR1QsRra2tSEtLQ2pqKlJTU5GWloa2tja8/vrrWLNmjVVpKBQKpKWlISkpCcnJyUhOTkZ7eztSU1P71dVqtcjLy4NUKmXKMTc3FzqdDkuWLMHGjRutskGlUkEmkzE2JCUloampCadPn7ZKH7jVr1JSUpg+npqaCm9vbxQUFNxRT6fToaioCBkZGYxkZmYyiyjBwcFwcLBu/c9gMKCgoADx8fFISEhAfHw82trabB68Ozs7TXxEYGAgTpw4YZVuU1MTUlJSmLpMT0+HRqOxum8ZJ+2966KgoABPP/00Fi5caFM+FAoFYmNjERERgfDwcGzduhXr1q3rV4+IUF1dzdw/OTkZWVlZGDNmjNWThN4+39gmysrK8PPPP2PWrFn96qtUKmRmZjL9KjU1FZWVlRg8eDAKCwutsqG3LZmZmQgPD0d4eDiGDx+OgwcP9qtXW1tr0rekUilaW1shkUjsWqw0GAxIT0/H5cuX0djYiP3794PD4dxRxxhI9/ZTGRkZ0Gq1VvkII3q9HtnZ2YiPj0dcXBwSEhLg5+dnc3BtnPBeu3YN169fx8KFC/HOO+9Ydf+CggKkpKQwUlhYiGHDhiE/P9/q+8vlciQnJzP5SE1NxZYtWzBp0iSr0zCWRXR0NKKiohh7PDw87qhn7JvGcSstLQ1ZWVnQaDTYvHkzBAKB1TYA//9iUFhYGMLCwvDdd99hwYIFVuvX1NQgNjYWsbGxiImJgbu7O1JSUmyywThBMvaNN998E6+//rpNaTQ3NyMiIgJhYWHIzMxEXFwceDxev3rGBWujj0hMTERhYSG+++47zJw50yYbqqurmbgwMTER8fHxEIlE/eopFApIpVKTdtnQ0IBt27Zh2bJlVt27paUFKSkpjK9MT09nxmZraWlpYWLjhIQESKVSzJ8/H5cvX7Y6jY6ODiQmJiIuLg5xcXGQSqU4f/48Ro0aZXUaAJh48urVq8jOzsaFCxcgFAqt1q+qqmL6VnR0NN59911s2bLFJhuampqYNpWSkoLY2Fj4+vralIZcLkdkZCRCQ0Ph6emJzz//3GrdxsZGxsfExcWhuLjY5tj0P5n/yYmrQqFAeno644ySk5PNVnZFIhGGDBmC+Ph4uLu7MyIUCk0G846ODkRHRzNOqXcQunHjRvj7+4OI+gwAFAoFEhMTmSBUJpMxq8QODg44ePAgurq64OzsDC7XtLrUajVkMhkzSU1MTDRbmZ01axba2tqQk5MDNzc3SCQSiMVik2Bbq9UiLS2NsSEpKQkajYa5fvbsWXR3d5vZQESIjY1lJgIpKSloamoyy+OIESNQWlqK9vZ2eHl5wcvLC56enpBIJIwdKpUKSUlJzEQ1LS0NOp2OSWPnzp3o6OiASCSCs7Oz2WTBONjHxMQgJiYG8fHxJnXq6emJefPmoba2FmKxGCKRCI6OjgBuTS737duHpKQkpKen97lrM2rUKBw+fBi+vr7w8fFhxN3dnanfnp4eJCcnIzIyEpGRkUhPT2dWRvl8Pn777TcolUoIBAKTPKjVakRERDCDU1pamsUdrEmTJiEqKoopR2NZuri4oLy8HNeuXWOCyL52Cvz9/XHixAl4e3vDy8uL+eTxeKiqqjKZlGRnZ5ut7D744IOoq6tDfHw8PDw84OHhAXd3dwgEAty8eRPffPMNUlJSkJ2d3edKpJubG3788Uf4+voyMmjQIEgkEtTW1prYkJmZabZKPmjQIBARoqOjGRs8PDzg7OwMAKioqGAG2sTEROTn55utzL7wwgtISkqCm5sb07+NbTImJgYffvghpFJpn6v8Tk5OSE9PR21tLfz8/ODn5wd/f3/4+flBIpFAq9VCJpMhPj4e8fHxSExMNNtxX758OaqqqtDZ2QmJRAKJRAJnZ2cTf6FUKk18hFQqZXwEh8PBnj17LPoIY59ITk5mJqvl5eVm+Zg6dSry8vJQX18PDw8PeHp6wtPTE87Ozuju7kZaWhpTFykpKRZPDUybNg1Xr141qQs3NzemjxntkUqlCA8PR0REBJKSkph6HT16NJ5//nmL5axWq5GZmWnSJiz10VmzZiEsLMzMBi6Xa5XPd3V1hZ+fHxISEsx8vlwux5kzZ5hJanZ2tol/MjJx4kScPn2a6VfGviUWi03qtLq6GuHh4QgLC0NkZCRaW1sBAFwut89Jq0ajwf79+xEREYH09PQ+Tyw88MADCA4ONulbvr6+8PLyMqkP4NYiSFhYGK5cuYLQ0FA0NzcDAK5cuWJxzDIYDIiLi0NycjLj8xsbG81+N3r0aBQWFqK5uRmenp6Mr3J1dQWHw0FPTw/S09OZ4CspKQnd3d0mafzf//0fcnJyIJFI4OrqColEYnHC0dnZiaioKFy7dg3Xrl1jdh58fX37XNzq6upCbGysib+1dKJn2rRpuHjxIpMHY98wBsotLS3MIlR8fDwyMjJM/KWTkxNmzZqFvLw8Jg+3j79EhIKCAiaYjomJMeljzz//PNzc3KBQKCAUCk108/LycPz4cWbxoq9TD87Ozvjll1/g7e1tMnYZ/SVwq26zsrIQFhaG8PBwJCQkMHHA7NmzMX/+fItpG6mqqjKZqFZUVJhc37t3L6qqqiAWi+Hi4gInJyezNkZEyMnJYSaq8fHxzEmMkSNHYv369Xe0AbjVT5KSkhAWFobr168jIyODufbdd9/B1dXVop5arUZGRobJRNXYH4yIRCIMHz4cycnJcHd3Z8YOJycnk9+1t7ebxIWlpaXMtbfffpsZv27Pf2VlJeLj45l2mZOTYzb+cjgcDBkyxKxduru7AwDy8/NNFvV639vIjBkzkJubi7q6OsZXenp6QiAQMBN2Y0yZmJhocSFs7ty5SExMhJubGyO9x66mpiaTyVV2drbJGDxmzBgMGjQIZWVlcHV1haurq8U2AdxaBLl69SquXr2KiIgIpq/+9NNP/U5a6+rqmLgyKirK5ISTt7c3li1bxsSWfS1oqFQqJCQkMH2j92bQBx98YNWk1XjiLTQ0FKGhoYiLi4NGo4Gjo2O/C401NTVMOcbGxqK4uNjk+uLFi6FUKnHjxg24urpCLBZbtTjznwpnINvs/2qmTJlC9h6LvBMpKSk4dOgQfv/9d7PBsj/4fD7c3NxARPDz80NeXl6/x5EcHBwgFAohEAgYISJoNBo0NjZafXSFx+PB2dkZzs7OEAqFUKlUEAgENh815HA4TICs0+mgUCisPrpitEEoFDKB8vjx4yGTyVBVVWWTHY6OjnB3d4dWq4VKpTKZLPeH8f4ikQhEBIVCYfNxKqFQCBcXF2YQXbJkCU6dOmVzeXK5XEgkEgiFQrS0tFh9nEkgEDBlaVwQmTRpEsLDw20+Uszn8+Hp6Ql/f3/4+vri2rVrNh+TM07ohw8fDplMZvPxF6FQyExiV61ahYMHD9p8fIXH48Hd3R0jRoxAQUEBOjs7bdI39k8OhwMPDw+bd7+MfcPd3R1PPfUU/P39sX//ftTU1NiUjkAggFAoBJ/PtxjY3wlHR0dIJBLGT7S0tNjtI4BbAV9CQoLNx7oEAgEkEglEIhHEYrHNJzeMZenk5AR/f39UVlb2e/TT0dERAoEATk5OjK/k8XhQKpUICAiweccGAOPrfHx8UFpaanM5ODk5MRPYxx9/HBcvXrTZ1/D5fEgkEnh5eUGv1/e7y87j8eDk5GQmPB4PS5cuZRa5bMHBwQFeXl4YMWIEnnvuOVy5cgVxcXEWJ+Djx48Hh8OxKBqNBmPGjOlzAeFOcLlcuLm5QafTQa1W23w8XCgUQiwWQyAQYNy4cZDL5UhKSrJ4bNLR0ZEJ4Hg8Hrhcrsl3lUqFBx98EFeuXLFp7AFuTQRdXFzA5XLtOp4uFovh6uoKjUYDg8HALFxYQ++xTygU4r777oO/vz9+//13m8vTmM7o0aNRVFSElpaWPn/r6OjItEM+n89853A4aG9vN5vk9QeXy4WLiwtEIhE4HA78/f1x48YNi4vfveHz+YyPMIqjoyMUCgWCgoIQHx/fZzzj4ODA2G/Mg/G7VquFi4sLSkpKbC5Ho680GAwYNGgQ8vLy+j3C6uDgYBITCoVCcLlceHt7Q6FQ2HzEvHdcN3r0aCQlJdk1hru6uoLP50OlUt2xPViCx+NBIpHA0dERWq3WZj/J4/EgFoshFovh6OiIZ599FtevX+/z1IOPjw9T/46OjuByucx3hUIBlUpl0yNJXC6X2RwxxtgjR45EWlraHcuyd9+43V+PHj0aAQEBCA0NtbhwzOVycd9998HBwQGOjo5wcHBgvgO3Fse6urpsflROIBAwfsa4oHovw+FwZEQ0xaofE9E9K5MnT6Z/JXK5nI4dO0bz5s0jDodDABiRSCQ0atQo8vb2Ji6Xa3LNKD/88AMtX76cBAKBxev9ybx58+jXX3+lp59+us979CfXrl2jzMxM2rx5M/n4+Jhd9/b2Jh8fH+Lz+Rb1R48eTSdPnqRly5aRk5OTXTbs27eP9Ho9hYWF0apVq8zuNXLkSHrkkUfogQceIHd3dzN9oVBISUlJtGnTJvL19bXLhq1bt9KlS5fo+eefJ2dnZ7PrDg4OZnV8u9TX1zP5eO6558zq5Mknn6Q5c+bQ+PHjycfHhxwcHEyuP/vss/Tjjz/SzJkz7coDAEpMTCSVSkUhISE0b948s+sTJkygqVOn0rBhw8jV1dXs+vTp04mIqKamhv7617/S/fffb1bW8+bNo4kTJ1JAQIDFdhESEkJtbW20d+9emjZtmtn1IUOG0JgxY8jHx8diu/Xx8SEiIp1OR1euXKElS5aYlBWHw6E1a9bQ/Pnz6cEHHyRfX1+zsvziiy9IqVTSb7/9RvPnzzeru0GDBtH48ePJ39+/z3arUChIJpPRpv+PvfMOi+ra+v93mGGAoVepdlRsWDAWRIOFqLHXJEaNGjUavUm8MTGJJqiJJibGFqOiWLAhxUJVRFAQu4iIikYRC50ZhjIwff3+8J3zMM6gM0PeG9/7O5/nWc85eGats3Zbe5+99zkuWUJOTk461zt06EDe3t5kbW2tV3/evHlMOk6ePEkjRozQ8sPX15fmz59PY8aMod69e5Onp6dOOu7cuUPp6ek0e/ZssrW11ZtXTk5OxOVy9frw9ttv08GDB2n06NFkbm5uUp2Kj4+nmpoaCg8Pp8DAQJ3r7du3f2Vetm/fnoiIsrOz9ealmZkZBQQEUNu2bcnBwUGvD4sWLaK5c+fqLQdDhMPhkFqtpnv37tHXX39NHh4eOr/p0aMHtWvXjhwdHfW29X//+99UU1NDe/fupcGDB+tcd3BwIF9fX3JxcWmyPJ4+fUoNDQ0UGRmpt30GBgZSv379qF27dmRvb6+3PJcuXUotW7Y0KR8AUHp6OhER3bp1ixYvXqxzn0GDBtGoUaOod+/e5OPjo9PGXV1dqVWrVibfHwCFh4eTQqGgxMREmjhxok4c8PX1pX79+lH79u311glHR0eqrq6mvXv30pAhQ/SWV4sWLcjKyqpJH0aMGEFvv/22TpszRiorK0koFNKWLVvI399f53rfvn3J39+fvLy89LaNjz76iAoKCmj16tXk6+urc93CwoKcnZ1f2b9HRkbS8uXLdWK1oRIUFERERFVVVfTHH3/opMPW1pbGjRtH/fv3p3bt2untNz777DMaO3asyWMALy8vunv3Lq1YsYLatm2r9zevsz1nzhyaOXOm3nZjqHz//ffUrVs3k/UXLVpE1dXVtHv3bgoKCtK5bmdnR+3atSMnJ6cm692WLVto8uTJr6y7r5JRo0Yx8Xbx4sU6YyZbW1vq378/dejQgZydnfW2ndTUVBKJRPTnn39Snz59dK63b9+eOnfuTO7u7nr7lS5dupBMJqMTJ07QhAkTdH5jZmZGvr6+rxwf79ixg9LT02nu3Ll665xAIGiy7wVAfD6fxo4da/L4GgAtWbKEwsLCKDg4+LXjv6bkxx9/pEGDBpms36lTJ+rYsaPJaQBAaWlpFBMTQ+PHj9dbXjY2Nq9sX3379v1ffZb6OwBwnQx8Nvz/csVVH0+fPsWBAwewb98+PHz4EO7u7njy5An4fD6zoldVVaUl77zzDrONLDExEVFRUUhKSmJW3FasWIE5c+ZAKpXqFRcXFwQFBQF48T7isWPHEBkZiXPnzkGtVkMgECA/Px98Ph/19fV6ZeDAgcw2BaVSiZSUFERERODEiROQyWT4+OOPma1nUqkU1dXVEIvFzJHL5WLo0KEAXmyfiouLQ2RkJE6fPs3MxF+/fh3e3t5a921oaGDOe/TogbZt2zJ5KRQKcejQIYSHhyM3NxeDBg3S+pCO5mMTlZWVqKysRF1dHUaNGsVcO3fuHI4cOYLY2FhmxS0xMRGBgYHM6nB9fT1zLpFI0K5dO3Tr1g3Ai3cHTp48icOHD+P06dNQqVTo1KkT8vLyIJVKUVdXpyW1tbWoq6vD2LFjwefzGT/Lysqwf/9+7Nq1Cw8fPsRvv/2m9S6ESqWCSCRCWVkZysvL4eDggF69egEAnj9/jujoaBw9epR518vBwYF5D0GTh5p81JwHBwfD2dmZuUdhYSH27t2LvXv34tmzZ1i8eDG2bt3KXJfL5RAKhUxe8ng8pk4BL7Z/paenY/fu3Th27BjkcjkePHgAX19fAAARoa6ujtGvqKhAjx494Onpydi4e/cu9u3bhwMHDqC0tBRjx47FyZMntfSrqqogEokgEomgUCjwzjvvaLWv58+fY8+ePdi9ezeePXuGlJQUra1nKpUKlZWVKCsrQ1lZGdq2bYt27dox1589e4aIiAimfXbt2hW5ubnMtqKGhgbm/hqZMGGCVj4lJiZi3759SEpKglKpRHh4OObMmcNcF4vFEIvFTPt2d3dHjx49tNJRUFCAnTt3Ijw8HCqVCsXFxVpblVQqFSoqKlBcXIySkhIMGTKEuV5fX4+TJ08iIiICKSkpUKvV+P7777Fq1SomxlRXV2uJra0tAgMDAbz4MMjx48cRGRmJtLQ0qNVqWFhYID8/HwKBgGkXL8uAAQPg4eHB+PjgwQPs3bsX+/fvR0lJCaZPn46DBw8y5dnQ0AChUAiRSAShUAgiYmIE8GJLXVxcHPbu3YvTp09DrVbj6tWr6NOnD5MHYrGYsSESieDn54c2bdpAoVAgPT0d0dHROH78OLPSNHDgQOzfvx9SqRQymUzrKJVKoVAoMGXKFMYHTazbt28fTp48CblcjqNHj2Lq1KmMD9XV1Vr1wcfHB126dGFsPH78GBEREdi/fz8eP34MHx8fFBQUgMfjadXrxjJq1CitbYEFBQXYu3cv9uzZg+LiYqxduxbffPONVr1r3Lbs7e0REBAAIsLVq1cRExOD6OhoZreKtbU1Ll68CC6XC5lMxogmP2QyGYKDg+Hq6srco76+HlFRUQgLC8OlS5cwb948hIWFMdeJCNXV1Uzb4nA4GDhwIG7fvo24uDjExcXh2rVrWvV8x44dcHZ2bnLg0LdvX632WV5ejgMHDiA8PBz37t1DSEgITp8+zVzXrL5UVlZCKBSivr5e653o58+f4/Dhwzhw4ADz7t2ZM2cwbNgwKBQK1NTUoKamBtXV1cyxffv28PPzQ0VFBeLi4nDs2DGcOXNGa/t5REQEFAqFjiiVSigUCkycOFEr5mdnZ2PPnj04dOgQxGIxtm3bxryLT//zsUVNvBUKhXBxcWHeXyUiXLt2DQcOHEBkZCQqKyvh7OyMZ8+ewdLSElKpVCcNNTU1GDp0KOzs7Jg6ERkZiaNHjzIrRd9++y2WLVum0741f9vZ2Wl9i4OIcP36dYSFheHIkSOor69HQUEBWrduzfxGKpWioqIC5eXlKC8vR69evdCiRQvU1NQgMTERMTExWmOZ8ePHY+3atUwdlMvlWvXT3NwcY8aMYe5/5coVHDp0CEePHmVWYq9du4bu3btDIpEwfa7mWFdXh86dO8PX1xdyuRypqamIjo7GiRMnmF0affr0wcGDB7Xu+7JMnToVHA4HDx48QGxsLGJiYrS2Cm/atAnBwcFMGjSi+btNmzbo3bs38/tHjx4hIiICERERKCwshIeHB548eQJzc3MQEWpra7X6DLFYzIwLJRIJMy5MTExk8vL777/H7NmztcaCDQ0NeseFmrI6ceIE9uzZg9TUVJibm+P58+dMDGgcbzXSv39/rXFEXl4e04eXl5djzpw5CA8PZ8pLs2NNIxwOB8HBwYy+UCjEkSNHsH//fubjkLm5uejWrRvTLhr3n2KxGN26dWO+7yKVSpGQkICDBw8iKSkJCoWCiREqlQq1tbWoqalhjjU1NZDJZBg7diwkEglOnz6NEydOID4+XmvXzq+//ooePXpApVIxolQqmfOOHTsyfXhJSQmioqIQGRnJ7Fbx8/PD1atXddpU4+O4cePA5/NRUlKC48ePIyYmBufPn2d2tP3444+YOHFik3XS09MT/fv3R35+Pk6ePImTJ0/i8uXLzIq8jY0Njhw5AjMzM6hUKqjVaqjVauZcpVJh+PDhcHFxAfBiHBAdHY1Dhw4hMzMTALBs2TKsX78eMpkMtbW1OvkpEAiM/l7Pfxp2xbUZqNVqysrKonnz5lFSUpLR+jU1NXT48GGaMGECdezYkeRyudE2SkpKaOvWrRQYGEjr1683Wp/oxexrWFgYhYSEkFAoNFpfKBTS7t27adiwYfTpp5+a5INaraZr167RwoUL6enTp0brS6VSOnHiBL333ns0ceJEk3woLy+nbdu2UWBgICUnJ5tkQ6VSUVpaGoWGhpqkX1BQQD///DP17NmTtm/fbpINpVJJp06donnz5pFMJjPJRmVlJW3evJn27t1rkr5CoaCEhASaOnUqFRcXm2RDqVRSfHw87d692yR9tVpNGRkZNHv2bMrOzjbJRllZGW3cuJHmzJlDarXaJBsNDQ104MABysnJMUm/uLiYNmzYQCNGjCCpVGq0fmlpKW3bto2CgoJozZo1JvmgWTGbPn06VVVVmWTj+fPntG7dOlq3bp3RunK5nFJSUmjevHnk4uJCubm5JvlQWVlJW7dupS+++MIkfZVKRefPn6fZs2dTamqqSTY0bWPp0qVG1ylNnPzqq6+oTZs2tGXLFpN8ICLKzc2lb775xuh+p6ioiHbu3EnvvvsuWVhY0DfffGPS/dVqNV28eJHmzZtHJSUlJunfvHmTli5dSvPnzzdaXywW06FDh2jSpEkkEAgoIyPDaBtExOz2MLVOyeVyiouLoylTptDBgweN1lcqlXTu3DlasGAB+fn5UX19vUl+1NTUUFhYGEVHRxutW1tbS1FRUTR16lRycnIyKeYrFApKTk6mGTNm0IIFC4zWl8lklJycTHPnziVnZ2e6ceOG0TYKCgro119/pb59+9LgwYON1id6ESPOnTtHH330ESUmJhqtX1tbS5GRkTRx4kTq1KmTSeNCIqLCwkIKDQ2lI0eOmKQvl8vpxIkT9P7771NNTY1JNu7cuUNfffUVrV692iT9yspK2r59Ow0cOJDu3r1rlK5cLqfU1FT69NNPycvLi8aNG2eSDwUFBbRu3Try9/enU6dOGa1fWlpKO3bsoKFDh5K/vz+pVCqj9EtKSigsLIyJt6aOPeDNzwAAIABJREFUyR4/fkw//fQTDRgwgOrq6kyy8aYAdsX1zaC2thZcLlfrAwjGUlNT0+THBAyFqOmPQxmC5sMx/yQSiUTnozXGIpPJdD6i8J+mqqqK+YgCyz9Pc9vGm+DD3xEj/mmUSiWqqqq0VhL/f4SIUFRUBG9v73/MB4lEgsuXL2PIkCH/aNtQq9UGf7FbH/X19SgpKdFaGf4naG46NCvExnw59e9Gs/rUnPYpl8u1VreNRaFQQCgUwt3d3WQbz549g7u7e7M+XNPceP13jAvfBP6OvlOlUul8MM6Y+2dnZ8Pf31/nw6XGUFdXBxsbG5P1KyoqYGNjY3L7rKurQ35+PgICDFts1AcRQa1Wm5yXbwLGrLiyD64sLCwsLCwsLCwsLCws/3GMeXA1fRqQhYWFhYWFhYWFhYWFheU/APvgysLCwsLCwsLCwsLCwvJGwz64srCwsLCwsLCwsLCwsLzRsA+uLCwsLCwsLCwsLCwsLG807IMrCwsLCwsLCwsLCwsLyxsN++DKwsLCwsLCwsLCwsLC8kbDPriysLCwsLCwsLCwsLCwvNGwD64sLCz/CG/C/yH9JvjQXNRqNVQq1T/tBgsLyxvMf0OsY2FhYfnbHlw5HE4hh8O5zeFwcjgcznU91zkcDmcLh8N5yOFwcjkcTq+/695/NxKJBKdPn8bBgweN1iUiPHr0CBEREZg/fz6uXr1qtA2ZTIaLFy9i/fr1+Oyzz6BWq422UV1djVOnTuG7775DcnKy0foaJBIJUlJSTPJBoVDg6tWr+O2333DkyBGT7i8Wi5GQkIDly5ejsrLSaH0iwv379xEWFoadO3ea5AMA1NTUIC4uDs+fPzfZhlQqxc2bN43WIyI8fvwYBw8exKJFi5CammqyD8+ePUNkZGSzBjElJSX466+/jNKpra1FRkYGfv/9d3zwwQfo06cPysrKTPahtrYW9+/fN0pHoVAgOzsbYWFhmDdvHgICAnDnzh2TfZBIJCaVZ2P++usvlJaWGvx7pVKJvLw8RERE4PPPP8egQYMwePBgo9unUqlEdnY2/vzzT8yYMQORkZHGug7gRZ0+d+4c1q5dC6lUapINIsK9e/dMipVyuRxXrlzBxo0b8d577+HZs2cm+aBWq3Hjxg0kJiYarSuTyXD58mVs3LgRU6dOxfXrOt3fa1GpVMjOzsaWLVvwzTffGN0+RSIRTp8+jdWrV+Pdd99FbGys0ffPy8vDnj17sGDBAowcORISicQoGyUlJYiLi8OKFSvwzjvvYOPGjUbpAy/qwoMHD7Bnzx7Mnz/fpJhfV1eH1NRUhIaGmuSDxsaZM2ewYsUKPHr0yCQbKpUK165dw9GjR03SB17Eufj4eNy7d88ovfLyciQnJ2PNmjUYN24cgoODIZPJDNYnIjx58gQxMTH4+uuvMWTIEJP7T80YIjQ01Og61Ziqqiqj86ExDQ0NOH36NMRisdG6RIS7d+9ix44dRtcpIsKzZ88QGxuLr7/+GsHBwcjMzDTaBw0NDQ24fPmyyfpEhJycHKP7z8Zo4r4p40IAKCoqwsGDB5GQkGCyDyKRCNHR0airqzNJv6GhAampqTh27JjJPqjValy7dg0VFRUm6d65cwc7duzAqlWrTB6TSSQSJCcn4+7duybp/5+EiP4WAVAIwOUV10cBSAbAAdAPwJXX2ezduzf9J5DJZJSZmUmhoaEUFBRE5ubmBIBOnTr1Wl25XE5Xrlyh33//nSZOnEgtWrQgAASABg0aRGq1+rU2hEIhxcfH0/Lly2ngwIFkYWHB2IiOjjYoDSUlJRQVFUVLliyhHj16kJmZGQGgVq1aUX19vUE2iIjUajXl5+fT77//TsOHDycLCwtauHChQboNDQ10/vx5WrNmDQ0fPpysra0JAFlbW1NxcbFBNiorK+n48eP0+eefU8+ePYnD4RAA+uijjwz2Py8vj7Zt20ZTp04ld3d3AkAcDodu3LhhkA0iIqVSSVeuXKE1a9ZQUFAQ8Xg86t69O6lUKoNtEBEVFxfTrl27aPz48WRtbU1btmx5rY5cLqerV6/Sxo0bafLkyeTh4cHUh+7du5NCoTD4/nV1dZSYmEifffYZ+fn5EQD67rvvjEqDSqWiK1eu0Pfff0+9evUic3NzevToUZO/l0gklJWVRZs3b6YZM2aQn58fU44a2bp1q1E+EBEVFBTQli1baPjw4WRubk7p6elN/lapVNKdO3do37599Omnn1Lfvn212hUA+vzzz4324fHjx7R161YaMWIEWVhY0L59+4zSl8lkdPbsWfriiy+oQ4cO5OHh0WT7lEqldP36dQoLC6NPPvmE3nrrLbK0tNRKAwC6cOHCa+9bVlZGJ06coOXLl9PgwYNJIBAw+r6+viSVSg32PzMzk1avXk3BwcGMP19++aVR+VBdXU3Hjh2j+fPnU8uWLYnD4VBubu5r9crLy+nkyZP09ddfU1BQkFZ+GBqnNDx9+pTCw8PpvffeIxcXFwJAp0+ffq1eUVERxcTE0NKlS6l///5a9Wr06NEG3bu+vp7S09NpzZo1FBISQra2toyNEydOvFJXKpXSlStXaMuWLfThhx+Sr6+vVn3o06cPKZXKV9p49uwZxcbG0ldffUVvv/022djYaNk4dOjQK/WrqqrozJkztHbtWho/fjx5eXlp6bdp08agfkcT6zZs2EATJkwgV1dXxsZnn332Wn2iFzE2OjqaPvvsM+rduzdxuVwCQObm5vTgwQODbIjFYkpISKCvvvqK+vbtSzwejwBQSEiIQX24hocPH9KOHTto0qRJ5OjoSADoyJEjBusrlUq6fPkyrV69mul3vL29qaGhoUkdoVBIKSkptHbtWpo4cSK1bNlSJ0acOXPmlfctKyujhIQE+uGHH2jUqFFa5QCAunTpQnK53KA01NXVUUpKCn377bc0YMAAJi+/+OILg/OB6EVffvfuXVq/fj0NHjyYuFwuXbp0ySj9/Px82rRpE40YMYIsLS0pKCjIoPJUKpWUnZ1NmzZtogkTJjDxwZB4W1VVRSkpKfTjjz/S2LFjmTGIRiZMmGBwGjQUFhbStm3baNSoUWRpaUnr1q0zSl8kElFkZCR99NFH5O7uTra2tlRZWWm0D9u3b6cxY8aQQCCgTz75xGDdsrIyOnr0KH3yySfUoUMHAkAWFhb05MkTg23I5XLKzMyklStX0ltvvUUcDofGjh1rsL5mTLd27VoaMmQIE7cN6T8bIxQK6ciRIzRjxgxydXUlPz+/18ZbIiKFQsHEunHjxpGzszNTJ+Lj4w2+v0qlohs3btDPP/9MQ4YMIT6fT+7u7lRXV2dUOt40AFwnA583OfQ3bR/hcDiFAAKISO8UKYfD2QngHBEd+Z+/7wN4m4hKmrIZEBBApsxevw61Wo2cnBycPXsWaWlpyMzM1JkJtLOzw7/+9S8IBAJYWVlpHTkcDpKTk3H//n1cv34dDQ0Neu/TsWNHdOzYEQ4ODnBwcICjoyNzFAqFyMrKQn5+fpMzJRwOB8OHD2f0GtuwsbFBTk4OioqKcO3aNTx8+FCvjXbt2iEgIAD29vaws7ODvb29lri6usLf3x/p6elITk5GcnIyHj9+rGVj06ZNaNmyJXg8Hrhcrpbk5OTgyZMnyM7OxpUrVyCXy3V88PLywtChQ2FnZwdbW1vY2dkxArxYdRIKhcjIyMDt27f1puOdd95B27ZtYWtrqyOVlZUoLi7G3bt3kZGRoXeW3tHRERMmTNCrrxEvLy9kZmYiJSUFqampqKqq0rIxbdo0BAcHg8/nw8LCAnw+X+u8RYsW6NSpE7Kzs5GQkICEhATcuHGD0beyssKxY8dgaWkJDoejJQqFAseOHcOtW7dw48YN1NfX682H1q1bo3PnznB0dNSqT5rzFi1awMrKCikpKUhJScGFCxd0ymTt2rVwc3Nj/H9ZOnXqxNhITExEUlISysvLGf3AwECEhoYyvpuZmTHHiooKhIeHIzU1VW9d0CAQCODu7o4WLVpoiebfunXrhrZt2+Ly5cuIj49HQkKC1uqor68v9uzZw/zN4XCY89raWuzatQtJSUmvXAVs7IObm5uOLx06dEDnzp1x6dIlJCQkIDExUcsHe3t7REVFgcfjaeVDY+nRowfq6uqQnJyMhIQEpKSkoLa2lrExc+ZMzJw5UycvORwOnj17xty3pqamyXRwOBy4urrC09MTHh4ezLFFixbIyclBamoqnjx50qS+i4sLfH194ezsrCMODg4QiUQQi8VIT09HVlaW3ro5c+ZMeHl5wdraWksEAgGsra3RsWNHiEQinDp1CqdOnUJWVhaUSiWj36lTJ6xYsQLm5ubg8Xjg8XjMuUQiwYEDB3D79u1XrvR36dIFPj4+cHJygqOjo87Ry8sLpaWlTNvIz8/X0ndycsIPP/wACwsLRjTtW61WIzIyEhcuXHjlqm7Lli3Rpk0bODs7w8nJiclHJycniMVi5Obm4sGDB7hx4wYUCoWOPpfLxejRo3XitL29PWxsbJCamoqjR4++cuXKzs4OLVu2hKurKyMuLi5wdXWFQqHAkSNHXru6/bK+RpydnZGbm4ujR4++cpXB3Nwcnp6ecHNzY9qW5tzc3BxXrlxBcXExLl++3GSsCwwMhI+PD+zt7eHg4MAc7ezs8NdffyE3Nxe3bt1CQUGBXn17e3sEBQUxfWdj4fP5KCgoQGVlJS5evIicnBy9q0dBQUHo3Llzk32Gvb09iouLcebMGaSmpur0nVZWVvjhhx9gZWUFS0tLRiwsLJhzBwcHXL58GWfOnMHZs2d1VgRDQkIwZswYvfWyuLgYhw4dQkZGxitXv2xsbJhY1zjuurm54ebNm4iNjYVQKGxSn8/n68RKTXna29ujsrIS1dXVOHfuHK5evarVtjVMnToV3t7esLGx0RFNjHB3d8f58+eRmJiIhIQErbL18/PDtm3bdGJsY+nSpQvOnz/PxJmXy2Px4sUYMGCA3jhTUFCABw8e4O7du7hw4YLemGttbY0JEyYw4xfNeMbW1hZ8Ph/x8fGIiYnR27Y12Nvbw8vLC66urnBzc9M6urq6ok2bNujRowcuXryIxMREnX6Hx+MhMjIStra2MDMzY0TTf5iZmaFTp054/PgxkpOTcerUKVy+fFmrfgwbNgzz5s1j8kAjXC4XPB4PNjY26N69O7KyspCUlISkpCSd3Ul//vknWrZsCS6XCzMzM+ZoZmaG+vp6lJSUICcnB+np6cjLy9PJh7Zt22Ly5Mla/cTLR29vbyZep6Wl6ZTJkiVL4O/vDz6fD3Nzc61xjLm5OVQqFe7fv4/U1FScO3dOp225urriX//6F9M+raysdM7feust3L9/n8mHS5cuaeXlggUL8O677zJ50Dg/Hj16hNzcXNy7dw+XLl3Suzpsbm6OCRMmMGN0zTi98TjZ09MT165dQ0pKCs6cOaMzxh02bBgmTpyoNR5tfHR0dETPnj2brJNvAhwO5wYRBRj0Y0OfcF8nAB4DyAZwA8B8PdcTAAxs9PdZvHjQ/Y+vuKanp9OUKVPIyspKZ2bSGFmzZg0NHjzYZP2AgAD6/PPPdWY3jZGPP/6YAgICTNYXCAQ6K1HGyvjx48nf379ZNqZNm6Z3NclQCQwMpG7dujXLB81Ku6nSqlUrndlVY2X16tU0atQoZsXcWHl55cQU6dy5c7PywsnJiSoqKmjDhg3M7Kqx0rVrV60ZSVPkyZMntGXLFurSpYvJ5alZNTFVunbt2iz9t99+m2pra2nnzp3Uo0cPk2z88ssv9MUXX2itGhgjtra2zU6Hg4NDs/QB0N69eyk4ONhk/eaWJQDav38/ffDBBybHqoCAAJo1axazG8UUOXz4MP3yyy86K62Giq+vL128eJHmzJmjtfJujGzevJmio6Np+PDhJunzeDz67rvvqFWrVibnw+TJk+n9999vVr/x3nvvkZ2dncn6prapxtLcmN2vXz969uwZhYaGkre3t0k29uzZQ1FRUTRs2DCT9AUCAQUFBTUrHZ07d25WuwCa34cHBQU1Ox3p6en0888/U/v27U3Sd3V1JXt7+2b50Nx4a2tr26x2AYB69+7drDH2y7u0TJGWLVuaPJbSiJubW7P0+/XrR2PGjGF2HpgipsZpjfTq1et/5Vnq7wT/0IqrJxEVczgcNwBnACwhooxG1xMBrCOiC//z91kAXxHRjZfszAcwHwBatmzZ+1UrBc2lrq4O8fHxOHr0KJKTk7VWiNzc3BASEoKGhgbU19ejoaFB67y+vh5ZWVlo3bo1Hj9+jIiICERERGjNEM6fPx/t27dHVVUVxGIxxGIxc15VVYXAwECEh4dDoVDg9OnT2L9/P+Li4hg/HBwcsGrVKkb3ZRtisRiHDh3CgAEDcO/ePRw4cAAHDx7UWhEYPXo0+vTpg+rqar3i5eWFpUuX4vjx44iLi9M7i96tWzfmAzBKpRIqlUrr/JdffsGsWbNw+/ZtHDp0CIcOHdJ6F/Stt97CsGHDUFNTg9raWtTU1GidExHy8/NRU1OD48eP49ChQzh79qzWrNbChQvB5/NRW1urVxYsWICvv/6a8eHw4cNa+dCuXTtMnDgRdXV1TdrIzMxEVlYWYmJicOrUKZ13gnr37g1bW1vI5XIdkUql6Nu3L7p164a4uDjk5OTo5COPx4Obm1vjyZyXJ3cQHx+Pvn37oqSkBIcOHcL+/fu1Zis//PBD9OzZk6kHjUUsFsPPzw/r1q1DbGwsYmNjtVZ8AcDMzAzBwcFQKBR60yGTyfDJJ59AKBQiLi4OhYWFOumws7ODg4MDiAhqtZrxX3Pu6OjIrGYREc6fP4+dO3ciNjYWCoWC2bGgUqlQVlbGSGlpKcrKylBSUoKQkBAoFArEx8frfa/YwsICDg4OzD00ND4vKCiAjY0NiAiXLl1CWFgYjh49yqzC7tmzB25ubigvL2d80JyXlpZiwIAB8PT0RFxcnN53Wfl8vlZ5vixqtRorV67EzZs3kZCQoHcngLOzMwQCgVY+NpbAwEDmHRwiwuXLl7F9+3ZERUVBJpPBw8MD6enpKC0tRXFxMUpKSpij5nzPnj0YMGAA5HI5EhMTsWfPHiQlJTHt64MPPsCwYcMgFAr1ipubG86ePYu8vDxERkbiyJEjOqtc8+bNg1wuh0QiYaS+vp45/+qrr2BnZ4djx47h9OnTOrtUXF1d0apVKyiVSiiVSigUCuZcE2dKSl5sziksLMT+/fuxf/9+rRWVH3/8EdbW1qiqqoJIJGKOmvNZs2Zh9OjRiImJQXR0tM6Kq7OzMwICAiCTySCTyZj20Pj8+vXr8PLyglgsRmRkJPbu3au1erls2TK0bduWua9QKNQ6BgcHY9u2bZBIJDhx4gQiIiKQmprKlIWzszO++uoriMXiJmN2TEwMAgICQETIzMzE7t27ER0dzdTrxYsXY/DgwaioqEBFRQUqKyu1ztu0aYPjx48DePHufmRkJHbv3o1r164BACwtLREdHY3q6mpG72X59ddfMXbsWKadhYeHY8+ePcz72h988AFmzpyJ8vJyLdG0MTMzM1y9ehVqtRqZmZmIiIhAdHS01m6ElStXgsvlMnnx8nHJkiX47LPPmDzZv3+/1ruD/v7+mDFjhlbfqdHXSH5+PjgcDhITE3Ho0CEkJiZqrZbNnDkTzs7OOn2Fpv8aP348vvjiC8TGxiI6OhpZWVladcre3h6DBw+GTCaDVCrVOUqlUiQkJKC0tBQxMTE4ceKEzk4ff39/tGjRgqmLjUUul6N3795MeSqVSiQlJWHnzp1ITk4GEcHJyQlJSUmoqKjQirONjzt37sTbb78NAHj06BF2796NPXv2MDtt5s2bh0mTJumUo+bczs4O6enpePr0KSIjI3H48GHcunVLKx0LFy6ESqVCXV0dJBIJ6urqGKmtrcXkyZOhUqkQFxens1IKvFi9dnR01Nt3aiQlJQXx8fHM7qWX6datG/h8vk6c0RxnzZqFdevWobCwEIcPH8bBgwe13qtt2bIlZs6cqTOGaTyuuXjxInx8fKBWq3H+/Hns3r0bsbGxzHhi9erV6NKlC8rLy7XalObvrl27om/fvjh58iQyMjJ0PrzH5XLRsmVLpo/R9B2Nz3///XeUlZXh+PHjyMrK0nl/0tvbGy4uLkxsbRxrlUolWrVqhX/96184efIkkpKStNqlho4dOzL3VKlUOsf169dj0qRJiI+PR2RkJJKTk7XaVteuXfHWW28x/cTLRzMzM6Snp+P48eOIiYlBZmamzq6C/v37g8fjMeOXl8c1n376KebOnYtjx47h6NGjyMjI0MoLT09PDBw4kBnfS6VSrfP6+nps374d6enpOHnypN6dSy1btoRAIGDGxY3zQKVSYezYsQgLC0NlZSWOHj2KgwcPar2j7OrqisWLFzP1p6amBtXV1Vp/x8TEMDHi5MmTqK6u1vKhS5cu8PDw0OqrGvdf3bt3N+n7Df9J/pEV15cG4KEAvnzp33YCeL/R3/cBeLzKzn/qHVeiF++47Nu3j0aOHEk8Ho/Mzc3p+fPnRtlQq9WUkZFBc+fOJVtbW5oyZYrRfgiFQvrzzz+pX79+BBi//16lUlF6ejrNnj2bbG1tKSAgwOB3dJRKJWVkZNDSpUupTZs2zGxNYmKiST7MnTuX7OzsyNPTk2QymVE2iouLaePGjdS7d28CQD/99JPRPpw/f57mz59Pjo6OZGlpSRUVFQbr19TUUGRkJE2ePJmZ7frXv/5lsP6TJ09o27Zt9M477xCfzyfgxWywMe90EL2oUzdu3KAlS5aQs7MzBQcHG6VfUFBAv/32G/Xv358pz9TUVIPvnZubS2vWrKE+ffow+m+99ZZR731pKC8vp/Xr11P79u3p999/N9iHmzdv0qpVq7R2Fvj4+Bj8XmZjRCIRbd26lbp27UpLliwxWK9xeWpm9QUCAZWVlRmkr1QqKTMzk5YtW0YdO3Zk0vHxxx8bnQYiooqKClq/fj21bduWzp49a7R+cXEx/fLLL9SxY0fq2rWrUeWpVqvpypUr9PnnnzPvX0dERBisX1dXR7GxsfThhx8yKwutW7c2+B06DSqVis6dO0ezZs0igUBg9LvbeXl5FBoayqwmCwQCo2JEYztffvklubm50QcffGC0flFREf3666+MH9euXTPaRlVVFW3bto169OhB/fv3N1qfiCgnJ4eWLFlCDg4OFBkZabS+XC6n48eP08iRI8nHx8eod/GJXrwbf/jwYRoxYgSZmZnR+vXrjfbh0aNHFBoaSm3btiWBQEAikcgofaFQSDt37qRBgwYRAFq8eLFR+s+fP6fNmzdTYGAgASAzMzMqKCgwWF8mk9GpU6fo448/ZnacTJo0ySgfNBQWFtKKFSvIw8ODkpKSjNaXyWQUExNDISEh1KlTJ6Nj/p07d2jFihXUtm1bAkC7du0ySE/znYq1a9dSv379mJW3Nm3aGBUjHj16RL/99hsNGDCAsWHsOEKtVlN2djYtXbqU3N3dicvl0tOnT42yQfTi2x2bNm2iLl260OTJkw3WE4lEdPDgQZoyZQrzHjyHw6F79+4ZbKO0tJTCwsJo5MiRzFhk+PDhButLpVJKTk6mTz75ROt7G8nJyQbb0KQlPDychg0bRmZmZuTj42NUeZaVldHOnTspJCSEWb3cuHGjUT4UFxfT1q1baeDAgQS8+P6KoTFCMxb54YcftHYYLlu2zCgfiIgePHhA33//PdM2DPm+gwaZTEZJSUk0Z84ccnJyIgA0ZswYo31404ARK65/14OqNQDbRucXAYx46TfvQvvjTFdfZ/c/+eDamMrKStq1a9drP5LxKiQSCUVFRRndeTcmPz+fzp071ywfjhw5YtJgTK1W061bt2jVqlW0aNEik31oaGig6Ohoys/PN9lGfn4+7dixw2R9qVRKJ06coKysLJP0JRIJxcbG0scff2zSC/A1NTUUExNDM2fOpJUrV5rkA9GLgHX8+HGSSCQm6T979oy2bNlCq1evNkm/qKiIdu7cSe+++26z6qVKpTL4oyn6fAgLC6MxY8bQ/v37TfZB8+EPU6iurqbo6GiaMWMG/fLLLybZyM/Pp19//ZWGDBli0kBIg0qlotLSUpP11Wo1ZWVlkVgsNklfqVRSWloa/fHHHybpy2QyOn36NC1YsMCgj+E1RU1NjdETbI25d+8e/fjjjxQVFWWyDblcTqdOnTL6A24aNAOjtLQ0k30gIrpx44ZJkzoa6uvr6datW83yobCwkKqqqkzW13xwyVTUajVduHCBbt++bbKNwsJC2rp1q0EfXtGH5iHWmEmdxsjlcjpz5gwtXLiwWW1cLpfT48ePTdYnejEBaurHX9RqNV2+fJm2b99ukn5paSmFh4fTuHHj6OjRoybZKC4upu3bt9P06dNNbhtKpZJSUlIoIyPDJH2iF3lx/fp1kyZ+pVIpnTp1ihYuXEjLly836f7V1dV05MgRmjp1qkn9n+ZDjd988w3NmzfPpHQQvSjTP/74g3JyckzSFwqFtG/fPlq4cGGz2uemTZtMmtQhevGhxk2bNtHo0aNNjnWa/tfQxYSXkcvllJKSQgsWLDB6oe1Nw5gH179lqzCHw2kL4Pj//MkDcJiIfuJwOJ8AABHt4Lz4esofAEYAqAcwm4he+eWl/62PM7Gw/FMQkdaHhP6v8iak47/FhzchHSwsLCxvOmysfAGbDyz/bRizVZj3d9yQiAoA+Ov59x2NzgnAp3/H/VhY/q/y39LZvAnp+G/x4U1IBwsLC8ubDhsrX8DmA8v/z5j90w6wsLCwsLCwsLCwsLCwsLwK9sGVhYWFhYWFhYWFhYWF5Y2GfXBlYWFhYWFhYWFhYWFheaNhH1xZWFhYWFhYWFhYWFhY3mjYB1cWFhYWFhYWFhYWFhaWNxr2wZWFhYWFhYWFhYWFhYXljYZ9cGVhYWFhYWFhYWFhYWGDSVgnAAAgAElEQVR5o2EfXP+XePz4MWpqakzWVyqVOHPmDEQikck2XvzXuf/3uXXrFqqrq03Wl0qlkEgkzfJBpVI1S7+hoQExMTF4/PjxP1YuRITMzMxm1Uu1Wt1sP27dutXs8mgub0LbUCqVzdInIlRWVjbLxuPHj/HXX381Kz+aU58AoKCgANHR0SgoKPjHykWtVjf73v8tderOnTvNslNZWdmsfgsAysrKmpWfdXV1zfahuUilUty+fbtZfUd+fj6ePHnyj9athw8fIjs7GwqFwmQbpaWlzS7P+vp6k/UBQCQSNcuH+vp6PH36tFk+NHccQUTNrgs3btxAfHw8iouLTbJFREhLS0NZWZnJPlRVVTW73ygpKfnHY25BQUGzxjIKhaLZY8LmjsmICOnp6f94vDQGbmho6D/tQ5OEhYWFzp8//592wyQePnyIjh074tixY8jNzUVVVRVsbGzg4OBg0H8ebWZmhg0bNmDKlCk4dOgQrly5gufPn4OI4OLiAnNz89faePDgAaZMmYJnz57B0tISHh4eMDMzbq5i8+bNSEhIgKWlJTw9PY3WF4vFmDFjBsrKyuDs7AwnJyej9AEgNTUV/fr1Q3R0NLKzs1FRUQELCwu4uLgYlJdEhL59+yIiIgJ//fUX5HI53NzcYGlpabAPcXFxmDVrFgoKCgAA7u7uBpWBBnNzc2zYsAEfffQRtm7dirNnz+LevXuorq6GtbU17OzsXpuW3NxczJkzB5WVlbC3tzc4/Ro4HA527NiBMWPGICoqCjdu3EBpaSnMzc3h4uJiUNkWFRUhODgYeXl5kMvlcHd3NyofASA2NhaDBw/GiRMnkJubC5FIBGtrazg6OhqUnvr6ekycOBH5+fkwNzeHh4cHuFyuUT4cPXoUy5cvR3l5OWxtbeHq6mpUXhIRlixZgnv37sHR0dHosgCAzMxMjBs3Dg8ePIBCoTA6LzkcDubPn48VK1bg9u3bqK6uhqOjI+zt7Q22oVAo0L17d/z22284f/48Hj16BKlUCmdnZ1hZWRlkIzQ0FJ9//jnu3LkDiUQCZ2dn2NjYGOyDra0tZs2ahW+++QabNm1CSkoKbt++DaFQCD6fDycnp9fmbUJCAqKjo2Fvb48WLVoYXRZKpRIhISFIS0tDbW0tXFxcYGdnZ5SN06dPY+HChSgtLYWVlZVJfnz22WfIysoCn883Kd7m5eVh2LBhuHfvHmQyGdzd3Q0uR+BFndqwYQMmTZqEs2fP4uHDh5DJZHBxcTHYjkwmQ6dOnbB3717k5ORAKBTC2traoHLUsHv3bkyaNAlXrlxBWVkZLCws4OrqalR+9OnTBzt27EBubi7EYjHs7Oxgb29vsA9JSUlYt24d5HI5PD09jcpHAOByuZgzZw4WLVqEtLQ0PHz4EFKp1Ki8FAqF8PPzw59//okLFy6gsLAQCoUCLi4usLCwMMjG0qVLcezYMcjlcnh4eBidDg6Hg379+mHVqlVISkrC7du3IRKJYGVlZXDM3rhxI6ZPn45r166hrKwMlpaWRsVchUKBbt264ciRI3jw4AGkUilcXV2NSktUVBRGjx6N69evo6KiAgKBwKi4zePxMGrUKISGhuLq1asoKSmBubm5UfUyLS0N06ZNw6NHj0BE8PDwMGocweFwMHv2bMTExKCmpgbOzs5GxXsAsLKyQkhICNasWYMdO3YgLS0N9+7dg1gshkAgeG0b4XA4iIqKwogRI7Bv3z5cvHgRT58+hUqlgouLC/h8/mt9kMvl8PPzw8GDB3Hnzh3U1tbC0dHRqJh78OBBjBw5EhcvXkRRURF4PB7c3NwMHgsolUosWbIEJSUlcHd3h62trcH31nDz5k106dIFcXFxyMvLQ3V1Nezs7AwazwEvYsTMmTPx5Zdf4tKlSygqKgKXyzUqHdnZ2RgzZgwePnwItVoNDw8Pg8pAA4fDwa5duzBmzBjmWaOoqIh51uDxeAbbag6rVq0qCQ0NDTPox5oZnDdRevfuTf/XaGhooKKiIsrLy6PBgwcTAC1p0aIFTZgwgX799VfKysqihoYGRletVpNIJKL8/HzKzMyk8PBw4nA4OjZ4PB716tWLPvnkE9qzZw/99ddfTfozc+ZMRs/BwYEmTpxI27dvp4cPHxqUnoKCAuLxeASAHB0dadq0abR//34qLS01OE+++uorxod27drRp59+SvHx8VRXV9ekjlKppIqKCsrPz6cLFy6Qt7e3Tj7Y2dnR8OHDaeXKlZSUlERCoVDHjlqtJolEQvv27dPS5XA41KNHD1qyZAlFR0e/Nj1qtZr69evH6PP5fHr77bdp9erVdOHCBZLL5To6MpmMnj59SlevXqX4+Hj65ZdfdNKgERcXFxoxYgStWLGC8vLymvRj7NixjI6Pjw/NnTuXjh49qjftGiQSCT158oRu3LhBx44dIz6fr3N/gUBAgwYNomXLllFMTAw9f/68SXvLly9n9MzMzKhPnz60fPlySklJofr6er06jcszIyODXFxcdHxwdXWlMWPG0E8//URpaWlUW1vbpA8bN27Uqgfjx4+nP//80+B6rVAoqGPHjowNT09PmjlzJh04cICKi4sNshEZGcnot2rVihYuXEhxcXGvrNcvM3r0aK28fOutt5i8lEgkTeqp1Wqqr6+nq1evEpfL1crH1q1b04wZM2jXrl10//59UqvVWroqlYqEQiHdv3+fsrKy6L333tNbJzt27EizZs2iP//8k7Kzs0mhUOj4oVKp6Pnz52Rvb6+jO3/+fDp06BA9e/ZMx3eRSER37tyh1NRUioiIoBkzZjTZNmxsbGjgwIG0bNkyKisr05sf1dXV5OTkxLSLhQsXUmJiYpP1UR8xMTE6aVi0aBHFxsaSSCR6rf7LMcLFxYWmTZtGu3btosLCQoN8SE9P16rXEydOpLCwMHry5InB6Zg1a5ZWnOvduzctW7aMkpOTm2xTarWaqqur6fHjx3T+/HmytLTUKQc/Pz+aO3cuhYeH07179/TWK5FIRAUFBbR06VK97XvcuHG0fv16unDhAkmlUr1+aOKVp6enlr69vT2NGjWK1q1b16Q+EZFUKqXS0lLasmWLjg/e3t703nvv0R9//EE5OTmkVCqbzEeFQkG+vr5M2xwwYACtXr2arl27RiqVqkk9uVxOpaWldPfuXdq7d6/eOt2pUyeaPXs2hYWF0e3bt7XsaWLlvXv3KDMzk4YPH66jb2ZmRt26daN58+bR7t27KS8vr8m05OXlkZmZGaPXt29fWrlyJWVmZurttzRpKCoqopycHEpJSaH3339fbzocHR0pJCSEVqxYQXFxcVRTU6NTnnV1dfTw4UOmfTYej7z77rv0888/U1ZWFslkMr2+KJVKqqqqovXr1+vcv2vXrrRw4UI6fPiwTpx5uSwrKyu1Yr6mjU6YMIE2bdpE2dnZevNQrVZTTU0NPXnyhMLDw3V8sLa2pqFDh9LKlSvp1KlTJBaLm/RDrVbTsGHDGF1zc3MaNGgQrVq1qslxxMvcvHlT6/4dOnSgRYsW0bFjx/TGKZVKReXl5XTr1i06deoU7dmzh0JCQpqMt05OTjRs2DD68ccfmb5MEx8ePnxIly5dopiYGBIIBHrrZffu3WnevHm0a9cuunPnjk76JRIJFRUV0TfffKOj37p1a5o+fTpt375dp128XB6FhYXk4+OjM44ZMmQI/fDDD3TmzJlXjiGIiDZv3szo9ujRg7799lvKysp6ZVwgIqqvr2fG+X369NFJh5eXF02ZMoU2bdpEV69e1SlXtVpNtbW19PTpU4qNjdXRt7KyosGDB9O3335LiYmJr+1/pk2bplWnBg4cSD/88ANlZGTobVcvl2dkZKTecaG5uTkFBATQokWLaP/+/a981mguAK6Tgc+GHHoDtjc1RUBAAF2/fv2fdqNJZs+ejUePHqGqqgoikQgikQhSqdRg/TZt2oDP54PP56OyshIVFRVGbdHq2bMnPDw8oFKpoFarIZPJdEQsFje5BaBNmzbo378/Hj16xMx+qlQqLVEqlbh58ybq6up09AMCAjBy5EjIZDI8ePCA+b1CoYBSqWRELBYjPz9fR5/P52PQoEF4++23cebMGUilUgiFQgiFQojFYoO3T/D5fAQEBEChUMDc3Bw1NTVaYuhWCh8fH7Rt2xZEhPr6ejQ0NGgdJRJJk1t9rK2t4efnh9raWpiZmaG0tBRVVVUG3VeThkmTJoHD4aCurg5yuVyvVFZWory8XEefw+GgT58+8Pf3R05ODpRKJYRCISoqKtDQ0GCwH15eXvDz84NSqQSHw0FDQ4OOSCSSJm1qykIoFMLW1hZisdik8uzZsye4XC7s7e315oNEIkFhYaFe/Xbt2iEkJAS3b9+GQCCASqWCVCqFTCbTOgqFwia3n3Xt2hUdO3ZEaWkpnJ2doVarddqGQqFAVlaWXv8HDx6MkSNH4vr16xCJRKivr9cSiUTCnDeVL+bm5ujSpQvkcjmcnJx06rWhscLd3R3u7u6QyWSorKyEUCg0antRYGAgGhoaYGNjA4lEgtraWkYkEolB5dqiRQs4Ozujvr4epaWlRsfJBQsW4OLFi7CwsGDu9/Lx6tWreP78uZauQCDAsGHDMHr0aHC5XBw/flxvndZIbW2tXh84HA569eoFhUIBZ2dnmJmZMfWocZ0SiURNbh3z9fVFt27dUFRUBFdXVyY+KhQKJmYqFArcunVLb/l07twZ77zzDoqLiyEWiyGVSrXqlCFxisfjoXv37pBIJLCzs0N1dTVEIhGqqqoM3sbI5XLRsWNHWFpagoggFotRVVWF6upqg9u4nZ0dXFxc4OHhAYlEgurqatTU1KC6utrgeu3k5AQfHx9YWFiguroaYrEYYrEYMpnM4HT4+PigQ4cOMDc319t3FRYW6o23Li4ueOedd+Dp6YmrV6+itrYWIpEIQqGwyTrUVBo8PT3B5/MhkUiYbdaG5iOXy0VQUBAaGhrg5OTExEeZTKZ1LCws1Fu+tra2CA4OhlwuR0VFBWpra1FeXg6xWGxwGvh8PkaNGoXS0lLw+XxUV1czUlNTY3C9cnV1hbe3N1Oemvqgb+zRFD4+PmjZsiWkUilqa2uZWGnoNmMHBwd4e3vDysoKVVVVqKqqglgsNjgNfD4fPj4+8PLyAofDaXIc0VQdt7a2Rvfu3VFfXw83NzcmrjQ0NDCxRiqVoqKiQq++mZkZevfuDeDF60lisRilpaVGjSv9/f0xceJEZGRkQCQSoaKiAhUVFQa3KwBo27Yt/Pz8UFNTw/ihaaOGbjnn8/nw8PCAp6cn6uvrteqVof2Xs7Mz2rdvDy8vL6YPV6vVjDQ0NCAjI0NHz8nJCSNGjMCoUaMQHR0NoVDI1Adjx/nt2rWDpaUlBAIBE6OqqqoMLhMul4s2bdowO8sa1yeNaMaM+rC2tkaPHj1QWVkJS0tLVFZWorKy0qjy9PX1xccff4yZM2fC3d3dYD1j4HA4N4gowKAfG/qE+0/Im77i2qlTpyZnrXg8HtnY2OidzVq8eDFdv36dkpOT9epyOBxycXEhPz8/HRu2tra0YMECun79OhERjRgxokkfXift2rWjefPmmayP/5k11cxKmyJmZmYUFBTU5HUOh0NOTk46KzoAqGfPnrR161YSCoV6Z2MNkRYtWtAXX3xB2dnZOjP8hoq1tTV98MEHWivLjcXGxobat29PAwcOJFtbW61r7du3p/Xr11N5eTkREQUGBpqcl+7u7jR58uRX+tmqVSsdH3g8Hk2cOJESExNJqVTS9OnTTfZh4MCB9PPPP7+yPB0dHfW2jV69etEff/xBQqGQVq5cabIP1tbWNG3aNLKysjJJn8Ph0MCBA5tciTRUWrZsqXdl2Zg69dNPP5mkb2dnR3PmzKG0tDStVfqX0+nk5KQzaw28WJlauXIlFRQU0OPHj03ywczMjIYNG0Z79+6lRYsW6Vzncrnk5eVFAQEBNHLkSB3dMWPGUFJSEjPr3pyyAF6s+Jmq6+fnR6GhoeTl5WWyjX79+tGcOXOalQZ/f39q06aNSbp8Pp/Gjx//yp0fwItVC32z7127dqUNGzZQaWnpa9Ohr+2ZmZnRqFGjKCoqisrLy01Kg4WFBU2dOpXi4+MpNDT0lb/Vt1tJk4cbNmygkpISnVVAY8Te3p4GDBjQ5HUul0uurq46OyLMzMxo5MiRFBUVRVKpVO+KjeZ3Li4uevslX19fWrduHRUXF9OFCxdMTgOXy6WQkBDq3bt3k/nt7e2td6zTpUsX2rRpE1VWVlJRUZFJ9xcIBDRjxgxKSUmhf//73ybZ8PX1pdWrV1NBQYHeevs64XA4NHToUNq7dy/9/vvvr/ytvp0IAKhv3760fft2EolE1KFDB5PSYWlpSZMmTaJvv/3W5PJ0cXGhBQsW6K1TfD6fWrVqRf369aNBgwbplPOMGTPo4sWLpFarKT8/v8l7aMZ8jo6OOvbff/99Onv2LKlUKlq4cOErfdXsAnhZAgMDaefOnVRaWmpSHlhZWdH06dPp1KlTtHbtWpPzEnjRZ+hbWdYIj8fTe93FxYU+//xzunnzJkVFRb3yHubm5npjlb+/P23cuJHKyspeGWdeJTwej0aMGEHff/99k7+xt7en9u3bk52dnU6dmD59Op07d05nd83/BjBixfU/s3n5v5TvvvsOUqkUjo6OcHJyYo5OTk6wtrbGF198gc2bN8PMzAwjR47ERx99hDFjxjDvphQXF2Pr1q1wc3ODq6src3R2dgaXy0VNTQ08PDwAAP3798e8efMwdepUWFtbMz7MmTMHQ4cOhaWlJSwsLHQkKSkJf/zxB/N7X19fTJkyBVOmTIG/vz+qqqrQunVrcLlc8Hg8cLlcLeHxePj222+1Zp29vLwwfvx4jB8/HoMHD0ZaWhpycnLA4/G0xNzcHDweD7dv38Zvv/3G6PP5fAwfPhwTJkzA2LFj4erqii1btsDe3h7Ozs5a4uDgAC6Xi+DgYJw7dw6Ojo748MMPMXv2bPTs2ZOxOXToUGzevJl5v8DW1pY5t7OzQ1FREfr27QvgxQzUxIkT8eGHH2LIkCHMHv6VK1dCLpfDysoKAoEAAoFA6/znn39GbGwsAMDS0hLvvvsu3nvvPYwaNQoCgQCFhYVo3bo1WrRowaxytWjRgimvsrIyeHt7g8fjYcKECViwYAGCg4O13o9ZuHAhxo8fz6zEa8Tc3Bx8Ph8nTpxAREQE83sfHx9MmjQJkyZNwoABA1BdXY2goCC4uLjA1dUVLi4ujFhZWUEul8PHxwe1tbXo1KkT5s6dixkzZqBFixaMzQ8++AC9evVi0t9YBAIBzp07h++++475fd++fTFt2jRMmTIF3t7eUKvVMDc31ylLTRvhcrkICAjAjRs34OTkxJRnjx49GJvDhw+HjY0N+Hw+LCwsdPKjoKAAX375JfN7e3t7jBkzBpMnT0ZISAisrKywadMmEBEsLCyY9tH4uG7dOqSlpQF4saI2cOBATJkyBZMmTYKnpydu3bqF7t2767QHzblEIsHSpUu1YkL37t2ZttGjRw9ERERALBbD2tqaqUeNZceOHdi1axcAwMLCgqlT7777LgQCAYqLi2FlZaVVl+3t7Zlzc3NzdO7cGSKRCDweDyNHjsSHH36IMWPGMO9/NTQ0/D/2zjssqmvr/9+pMAwzMEMHS0REFBULBERFsFCUjgiKoFjQFKMpV5MYE0tiL9eCGhOTqyaxBTXW6LVEMfbeeyEq0nsZpqzfH9w5P8ahzAy+r9685/M86zkHZtY+a++99tr7nL33GUREROj4gq2tLVMX6enpeP/99yEQCBAVFYUxY8Zg4MCBzB6biooKLFy4EBKJpEHp168fs6qiR48eSEpKQmJiIhO/2rdvjx49esDJyYkRW1tb5hq7d+/G/v374eDggLFjxyItLQ2tWrXSKdvZs2eDw+Ewe4fqHjkcDtavX49bt24x3+dyuejVqxciIiIQGRmJiooKHDlyRMeX6/p2fn4+YmNjGX03NzckJCQgISEBnTp1AofDgaOjIyorKxkfqutP5ubmSE9Px44dO5g0evbsifj4eAwZMgQtW7bEvXv30K5dOyY+amOk9lylUiEtLU1nVsLf3x+xsbGIiYmBq6srtm7diufPn9frTxYWFtiyZQsTb3k8HgYOHIjExERER0fDysoKxcXFzN7hl/surU+4urrir7/+gkwmw/Dhw5Gamoru3bszZT58+HB4e3vD2toaMplMR6ysrLBr1y7Ex8cDqF29MHLkSCQlJTH+QERYuHAhrKysGH9++Xzw4MHIzMwEAPTt2xfJyckYMmQIs6dPO4tvZWUFa2trWFtbM+dWVla4d+8efHx8ANSuOkhKSkJycjK8vLyYstXGfG09vNx3rV27lrFBe83o6GjExMQgKCgIWVlZ+P333yGXy5kYpz1KpVK8ePGC8eN27dohNTUVKSkpcHFxYdL8xz/+weyrrivW1tbgcrmYNm0a5syZA5FIhPj4eIwZMwZ9+vRh6oKIMG/ePJ1YWffI4/EwYsQI5mU4AoEAwcHBiIuLQ2RkJGxsbHDw4EFkZWXpjUUkEgk4HA7Wrl2L8ePHw8LCAgkJCRg3bhz8/PwYGxQKBRYtWlRvfWr/7tOnDy5fvgwul4v+/fsjOTkZMTExzH54CwsLtG7dWi8N7fHy5csIDg4GUDvjnZiYiOTkZPj4+DB2LFq0CEKhUG8MoD0fM2YMdu/eDaB2ZnHEiBEYNmwYUx83btzA8uXLdfy5ro8/f/4cbm5uICK4uLggJSUFKSkp8PDwYOpzypQpKC8v14sx2vOVK1fip59+YuoiNDQUCQkJiIyMhEQiwePHj2Ftbc3EFJFIpHMEgIiICGbVk42NDWJjYzF06FAEBgaCz+dj3759yM/P14m3dfeYL1y4EMePH0fbtm0xYcIEpKamwsbGhslDixYt8M9//lPHF7TjCaFQCLVaDVdXVxQVFcHT0xPjxo3DiBEjdNIYOnQoPD09mbZZt31aW1vjyJEjiIqKAgC89dZbSElJQXJyMtzc3Jg0Fi9eDIlEotOu60pkZCQOHz4MDoeDoKAgpKSkIDY2ltmvKpVK8c0334DH44HL5epJTk4OvvnmG9TF3d0dUVFRiIqKgp+fH9avXw+NRlNvvBSLxRgzZgx+/PFH8Pl8DB48GKNGjcKgQYOYfaYSiQTLli3T8yXteUVFBVq2bAmFQgE7OzskJSVh5MiROuOh9957D0OGDNHrs7R///zzz0hPTwdQ2+8FBQUhISEBsbGxsLGxQVFREWxsbJh6fLk+FQoFWrRoAaB2DDNu3DgkJSVBJpPhjcTQO9zXIW/6jGtjlJeXk7+/Py1YsMDgPXMvs3XrVpo8eXKjex4bQ6PRUKdOncjDw4OmT59OV65cMfrJybFjxwgAdezYkaZNm0bnzp0zOo3o6GiytLSkoUOH0ubNm6mkpMQo/Tt37lBwcDBt3rxZZ0+wMbz33nsUGhpKP/30k1F7ELUUFhaSXC6niIgI+vnnn/X28hjC1q1bac6cOZSdnW20LlHtPh1XV1dq27YtTZkyhc6cOWN0XezZs4dSU1PpxIkTJj9F6927N3Xv3p3mz59Pjx49Mlr/woULFBYWRtu2bWtwn1pTpKamklwup9GjR9O+ffsa3B/VENnZ2SQSiSggIIBWrFhhUhv95ptviMPhUJ8+fWjx4sX04MEDo/SrqqrIxcWFBg0aRBs2bDC6XRARrVu3jvz8/GjlypXMrL0xaDQaSkxMpCVLlpikT0R05MgRcnV1penTp9OtW7dMSmPJkiW0ZcsWo+tRy19//UVCoZAkEgnFx8fThg0bKD8/36g0PvzwQ3rrrbdo6tSpdOHCBaPbR2lpKclkMurZsyctXbqUsrKyjNInIlq9ejXxeDwaMGAArVq1ip49e2aUvkqlovbt21NQUBB9++23lJeXZ7QNu3fvZmZGTW2fcXFxNHHiRJPKkah2H5+Hhwd98803Bu8Pfpl3332Xhg0bRvv37693f3ZT5Ofnk1gspjZt2tDHH39MJ06caHLv28ssWbKERo8eTZmZmSaVg0KhoIiICFqzZk2jeycbY/PmzWRmZkZRUVG0ceNGKioqMjqN8ePH05o1a0yKUUREmZmZ1LlzZ1q4cKHRPq0lKSmJ4uPjadeuXQbtBX2Zx48fU+vWrWnKlCl09epVk2yYPn06DR8+nA4ePGi0LxDVjgvt7e0pJCSEfvjhB4P2zr/MmjVrSC6X05gxY+jAgQMmlcVnn31GBw4caHSvdmMcO3aMRo8eTadOnTJ5HDFkyBAaO3YsHT9+3CQ7bty4QR07dqS5c+eaFGuJiD766CPicDjUs2dPmjdvntH9V0FBAfn6+tKSJUsafP9CUyxevJhiY2NN9mulUklt2rShgIAASk9PN+r9M1r27dtHaWlpdPbs2f+V2dX6ALvH9fWjUqnA4/GMfqvkq6SkpAR//fUXPD09Tbbj+PHjcHR0hLu7u0n6CoUChw8fRr9+/Yx++6wWjUZj9Ns1X6akpMTot+/VJTc3FwKB4LU+gcrLy8Pz58/RpUsXk+uTiJrlkzU1NcjKytJ5Kmosza1Potqf9enZs6dRb2Ssy5MnT5g9NKaya9cu+Pn5wd7e3iT9oqIiaDQanafUxlJaWmr022/roo3/zfGJgoICo94Y+z/Bn3/+icrKSvTt29eoNyrW5ebNm+jQoYPJ+Xj+/DnUajVatmxpkj4AHD16FF5eXia9fR2o/dmQsrKyZvm1SqVq1pskiQhKpdLkegBq8yEWi5vlU1VVVUa/Qbcud+7cQXV1dbPi7auIdc1tVxcuXIC7u7tJb019VZSXlxv1pvH/iTRKS0shFouNfgN9XWpqaprl19qfL7O1tTU5jRs3bjD7sv9bISIoFAqTx4RA7a8LiESiZo2FNm/ejH79+umsODOGVzHOb65PlZ899PIAACAASURBVJSUoKKiAs7Ozian8SriTHMxZo8re+PKwsLCwsLCwsLCwsLC8r+OMTeuzZvGYmFhYWFhYWFhYWFhYWH5H4a9cWVhYWFhYWFhYWFhYWF5o2FvXFlYWFhYWFhYWFhYWFjeaNgbVxYWFhYWFhYWFhYWFpY3GvbGlYWFhYWFhYWFhYWFheWNhr1xZWFhYWFhYWFhYWFhYXmjYW9cWVhYWFhYWFhYWFhYWN5o2BtXFhYWFhYWFhYWFhYWljca3owZM163DQ2ydu3aGWlpaa/bDJPYvHkz5s+fj6dPn0KtVsPW1hYCgcBgfbVajS+//BKPHz+GSCSCjY0NOByOUTZcvXoVu3btgqWlpUn6AHDu3DlIJBKYmZkZrQsAd+/exaRJk/D06VMQEWxtbcHn841K4/jx4ygtLYWdnZ1JeaisrMSmTZtgbW0Na2tro/UB4MGDB1Cr1RCLxSbpK5VKzJw5E7m5ubC2toZUKjU6jSNHjmDVqlUoKyuDtbU1JBKJUfpEhLlz5+LevXsm+9SdO3ewdu1aEBHs7e2N8mkta9euxcWLF0224dmzZxg7dizu378PhUIBuVwOc3Nzo9JYuXIlVq9ejWfPngEAbGxsjPJLjUaDU6dOwdHRETwez6hra8nOzoZGozHadi1EhDVr1qCiogIODg4m1cWDBw9w8uRJODo6mtzG8/LyYGFhYVLbBGrLYf369RCJRCa38blz52LNmjXIysqCUqmEXC43Kj/5+fmIjo7G6dOn8eLFC3C5XMjlcqPq9vLly3j69CkcHBzA5Rr/TFij0eD7778HAJPTePz4MR49egQHBweT6yMjIwNKpRL29vYmpZGXl4dr167B0dHRpDwAtT4hFotNzkNOTg7Gjx+Px48fM/2vUCg0Ko0tW7Zgz549UKvVJsU6hUKBqVOn4tmzZxCJRJDL5Ubn5/79+8jOzja5XajVaowfPx5//PEHCgsLYW5ubrQdWVlZOHPmDJycnEyKMQCwZMkSnD59GlwuF/b29kbHzCdPnmDs2LF48OCByTE/IyODGc/IZDKjy7OqqgoLFiyAQqGAvb29SfEyMzMTf/75J2QymUljAKB2XGdra2ty2zpx4gTmzJmDvLw8mJmZmdQH7927l2lXpvhleXk5CgoKjB7D1OXKlSvg8/mwsLAwSV+lUuHhw4eQy+Um23D16lUUFBSYXA5KpRKzZ89Gfn4+ZDKZSeXx119/oaSkBFZWVkbrajl48CBEIlGz6qO5zJw5M3vGjBlrDfoyEb2x0qNHD/pvpbq6mtq3b08ACADxeDzy8vKiMWPG0Jo1a+j8+fOkUCgaTeOHH35g9OVyOQ0ePJi++eYbOnr0KJWXlzdpQ01NDWODvb09xcXF0bJly+jSpUukUqkMyscPP/xAPB6PevfuTbNnz6YzZ84YrKtlxIgRTD4EAgF5e3vTu+++S//617/o5s2bpFarG9U/efIkASA7OztKSEigtWvX0v3790mj0RhtQ5s2bWj06NG0ceNG+uuvvwzWv3PnDmP7tGnTKDMzk5RKpcH6RERLlixhyqFVq1Y0bNgwWrFiBV28eNGgMq2pqSFPT08mjZYtW1J8fDwtWbKETp48SdXV1U2msXPnTh2fCg8Ppzlz5tCxY8eooqKiSX2NRkMBAQFMXfr5+dHHH39MO3bsoNzcXIPK4fz588ThcAgAyWQyGjx4MGNDZWWlQWl8/PHHTD4AkLu7OyUlJdGyZcvo5MmTTaZTVFREDg4OOn7ZvXt3SktLo++++44uXbpENTU1jaYxevRokkgkFBUVRenp6XT//n2DbNfy7Nkzkkgk1LdvX5o3bx5dvXrVKJ8mIlq1ahUBIKFQSL1796Zp06bRgQMHqKyszCB9hUJBbm5uxOPxyNfXlz799FM6ePCgQb6g5bvvviNXV1eaNGkS/fvf/24yrtVHaGgo4w+RkZG0aNEiOnv2rMFtLC8vj+RyOVOfHA6HPDw8KCkpiZYsWULHjx9vskyWL1+u41NCoZC8vb0pLS2N1qxZQ+fOnWu0jf31119kbm5O1tbWFBMTQytXrqTbt28bVadz584lACSVSmnw4MG0cOFCOnfunMHlUFZWRvb29mRnZ0eJiYm0bt06ysrKMvj6REQbN24kAGRjY0OxsbG0YsUKun79usH5UKlU1KlTJ7KysqKYmBhatWqV0W1jx44d5ODgQKmpqZSRkUGlpaVG6RMRTZkyRa//HTduHH333Xd09erVJmNuTk4OWVlZEQDi8/nk7e1NEydOpE2bNtHjx48NKo+FCxcyNshkMgoLC6PZs2fToUOHDMpTfn4+SaVScnZ2ppEjR9JPP/1EL168MLgMiIgOHz6s49fW1tY0YMAA+uyzzygjI4OysrIazUtNTQ25u7uTQCCggIAAmjlzJmVmZjYZH+ty7tw5JuabmZmRv78/ffzxx5SRkUHPnz83KI33339fJx/t2rWjpKQk+uc//0l//vlnkzH//v37JBQKCQA5OTlRfHw8LV++3OD+l4jok08+YfypR48eNGnSJPr1118NrpOCggKSyWTMWGTUqFH0ww8/GDWe+eyzz0gmk1FCQgL9+OOPlJ2dbZCeFrVaTT179mTKUSqVUv/+/enzzz+n3377zaC8/PLLL0w5JiUl0bp16+jRo0cG26BSqcjT05O6d+9O06dPp1OnThk9rjxy5AhxOBzy9vamzz//nI4dO2Z03xMWFkZubm70wQcf0O+//05VVVVG6T948IAEAgE5OztTSkoKbdy40WB/1rJo0SKmLlxdXSk5OZnWrFlD169fb3JsTFTrU1ZWVuTh4UGTJk2iffv2GdV/ExGlp6cTAOrYsSN98MEHtGvXLiopKTEqjeYC4DwZeG/Iqf3+m4m3tzedP3/+dZvRII8fP0Z2djZyc3ORk5PDiPbvW7duIS8vr0F9sViM9957D+Hh4SgtLUVhYSEKCwtRVFSEwsJC5OfnY/Pmzaivjng8Hry8vNC1a1eEhYWhRYsWKC0t1ZOjR4/ijz/+0NO3srJCr1690KtXL3Ts2BEeHh4AgJqaGh2prKxEUlISiouLGV25XI4BAwYgJCQEwcHBMDMzw9OnT5GXl4e8vDzk5uYy53l5eXjw4AGuX7/eYDlIJBJERERg4sSJMDMzQ1VVFSorK1FVVcWcz5o1C48ePdLRa926Nfr164f+/fvDx8cHXC4XFRUVjJSXlzPnd+7cwdKlS/Wu7ebmhqCgIAQFBaFjx46wsrKCUqmEUqmESqVizpVKJb744gscP36c0ZVKpRgwYABCQ0MREhICuVyOp0+foqioCEVFRSguLmbOi4qKkJubi59++qneMrC0tISfnx86d+4MPz8/WFtbo6CgQE8uXryI27dv15uGUCiEl5cX+vTpg6ioKFRUVOhcX+tbv/zyC2pqavT0+Xw+unXrhm7duqFPnz546623UFxcrCcXL17E0aNH67XB3d0d/v7+cHd3h5+fH1QqlV5ZFBcXY9u2bSgsLKzXhu7du6N79+7w8vJCmzZtGJ+qK0+ePGnUp3g8HgYNGoQxY8ZArVbrtE+t3Lx5U8evX0Yul2Pq1KmIiYmBSqVi2oRSqURNTQ0ePHiAsWPH6ui0bduWaRf9+vVDVVUVFAoF1Gp1vTJr1ixs376d0W/RogXCwsIwaNAg9O/fH3w+H8+ePUNZWRnKyspQWlqqcywqKsL8+fOhVqv18t+jRw/07dsXXl5eaN++Pfh8PiorK1FRUaFz3LdvH3bs2KGjLxAI4Ofnh379+qFPnz5o27ZtgzMMSqUSvr6+ePHiBYDadhESEoLw8HAMGjQItra2KCwsRG5urp792jh1+fJlbNu2TS9tS0tL9OrVC71794arqyvs7e1RWFiIFy9e6MmdO3dQWVnZYH06OjrivffeQ9euXRmd7OxsRp4/f46srKwG9blcLsLCwvDRRx/B1taWiU91ZdWqVTh58qSOnouLC/r374/+/fvD398fHA4HZWVlKC8vZ0T7d35+PmbPnq0X8yUSCfr06YPAwEB06dIFbdq0gVqtRnV1NRQKhY5s2LABv/76q45++/btMXDgQAwcOBD+/v4oKytjYqPWF7RSVlaGzz//XK8s7e3tERgYiKCgIHTr1g12dnaoqanRubbWnt9//x3p6ek6+m3atGFsCAwMhFKpbHBgotFoEBwcjPv37wOo9cfAwECEh4dj8ODBaNu2LYqKipCVlaXT19Tte7KysnDhwoUG61MsFqNfv36YMGECBAIB0//WlSNHjjToE87OzvDx8cHbb7+NXr16oaSkhNErKChg/HTnzp0N+lPnzp3RtWtXDB8+HC1bttSrS4VCgW+//RZ79uzR0fXy8mLK0tvbu9FxSE5ODi5evKgXI+rSpUsXfPHFF2jfvr1O/6s97tu3D5s3b9Yrv4CAAPTr1w8BAQGwsrJCcXExk/e65VBYWIg9e/agtLS03uu3bt0a3bt3R1BQENzd3XVivTYvT548wc2bNxvMA5fLRWRkJN5//33w+XyUlJSguLgYJSUljGzbtg1PnjzR05VKpfD394e3tzfat28PNzc3lJaW6ulnZWVhw4YN9V6/Xbt26N27Nzw9PeHl5QWxWMzEt7oxb+fOnbh48aKevrOzMwICAuDv7w9PT0+mjatUKh3Jy8tDRESETn1qx4GhoaHo2bMncnNz8eLFC+Tl5SE/P585as9v3LiBu3fvNliWrVq1QkREBFJTUwHUrlrTSlVVFcrLy/HJJ5+grKxMR8/V1RX9+vVDv3790L17d1haWkKtVkOj0UCj0TDnarUaO3bswBdffMHo2tjYIDQ0FIMGDUJISAhkMhmeP3+uMx7V9r1aeffdd5kYAdT2F/369UNwcDCCg4Ph6OiIkpKSBvvfc+fO6fThIpEI/fr1Y/rgNm3a4NmzZ6iqqmJiW3V1tY4sXLgQZ86c0SmHTp06YcCAARg4cCC6d++uM36qOx4qLi5GTk5Ogz5lbW0Nf39/eHl5oV+/fmjdurXOmFQrK1eu1Ok/zczMEBAQgJCQEISEhMDNzQ05OTmMzdr8aM/Lysowfvx4VFdXM2nweDz4+vpiwIAB6N+/P/z8/IxetWIMHA7nAhF5G/RlQ+9wX4e86TOuLVq00HkCaKi0bduW5s+fTz/++KNJ+gDIysqKJkyYQD169DA5DXNzcwoJCTFZXyvaJ4jGilAopMTERNqzZ0+zbbC1tW22vkgkalYaTk5OJutaWFhQSkoKubm5maTP5XIpPDycvv7662b5w7Bhw6h3794mp2Fvb09jx441WZ/D4dCAAQOYGThjxczMjEaMGEFHjx4lHo9nUhpeXl60atUqWrZsWbP8gc/nk0QiMVlfIBCQl5dXs2xwdXWltm3bNisNR0dHk3W5XC716tWL3n777Wb5hHaW3xQZMGAA/frrrzRjxgyT8z99+nR68uQJubi4NKsspVJps+uiuTYIBIJm65va99Wt0+boe3h4mOxTPB6PIiMjadeuXWRhYWFSGlwul8LCwigtLc3kPDg5OdHUqVPJw8OjWWVhZmZmch2EhYXRjh07KCIiolk2WFpamqxrYWFBI0eOpOjoaJP0RSIRpaam0okTJ5qVBzc3t2aNh/h8PkVGRpKdnZ3JaYjFYgoMDGxWPqRSKdnY2Jika25uzsygNscGADormowVLpdLvr6+zbah7iocU6R9+/bNHheaGmO09TFs2DCd1ZumSHPHxwCoW7dulJmZ+T92PwUjZlyN22zIooODgwMqKipgb28PBwcHRrR/nzt3jtmzJBAIEBMTg7S0NAQFBYHL5eLYsWPgcrmQyWSQyWSQy+WMaP9OT09nZqY4HA4GDhyI1NRUREVFQSQSITo6GpcvX4aVlRWkUqmeFBYW4uDBg4zNHA4HgYGBSE5ORmxsLPLy8tCuXTsAtU9YBAIBhEKhjuTk5KCqqkon7yKRCGFhYYiLi8OpU6ewbt062Nvbw87OjhHt3zU1NZg+fTqj27FjR4wbNw7JycmwsbGBRqNhbBOJRLCwsIBIJNI5f/ToETOjo8XV1RUJCQlISEjA4cOH8fHHH8Pc3BxisRiWlpYQi8WMmJub4/fff9fRl0gkiImJwbBhw9C/f3+4urri6dOnOmVRV6qqqup9YtylSxfExsZCLpdj0qRJsLa2ZupUJpPp/L1y5UqdmYzAwECMHDkScXFxkEgkGDhwILKzs2FjY6Mntra2ePjwoc6srbu7O0aPHo3k5GQ4Ozvj+vXr+OKLL2BlZcX4UV3/kslk+Omnn5i9nQDg7++PUaNGYejQobCyssLYsWNx+vRpxvaXpby8HJs2bWL0hUIhoqKikJKSgpCQENTU1OD777+HpaVlvWVgbW2NgwcP6jw9d3d3x8iRI5GcnIyWLVti/vz5+OOPP5j29LIIhUJMnDiR0e/UqRPGjRuHESNGMHtWHBwcoFAodNpm3fa5f/9+ZGRkAAAsLCwwbNgwpKWlwcfHBxwOB//617+Y9Pl8vk7b0J4/fvxYzx/kcjmio6MRFxeHTz/9FNeuXdP5nMvlgsfjgcfjQaPR1Dv7LZPJEB4eDg8PD1y5cgUWFhaQSqWQSCR6xz179qCkpITRtbGxQWJiIpKSkuDn54f4+Hg8ePAAFhYWsLCwgFgs1jmvqKjQm5mys7NDfHw8EhMT4ezsDDc3Nz0bDUEgEMDKygo1NTXgcDj15kEqlYKIdGaegdp2NWLECAwbNgwtWrSAVCqFSCSCo6NjvbJ582bs2rWLKYPRo0cjLS2Nsb24uBgikQhOTk5wcnKCo6Mjc+7k5AS5XI6hQ4cy9dG/f39MmDABUVFRzN4+kUgEADA3N2diVN3z/Px8PZ+Qy+WIi4vD0KFDUV1djYiICIhEIlhaWkIikcDS0pIRiUSCffv26cRbqVSKuLg4JCUlITAwEKGhoXj27Bl4PB7MzMxgbm4OMzMzRqqqqvRmCblcLoKCghAfH4+OHTsiICAAAoFAJ0Zq/UEsFuP8+fM6KyK0+sOGDUNsbCymTJmC77//HlwuV+faWtFoNHjw4IGeP7z99tsYMmQIQkND0aVLF1NcChYWFujQoQOEQiGuXLlSb59jZ2cHkUiEDz/8kNFr06YNxo4di1GjRsHZ2ZmpGx6Pp9P31u1/z549iyNHjjBpuLu7IzU1FcnJyXBxcUFGRgbWrVunp29jY8OkM3fuXGYmQyAQICoqCqmpqQgODgafz2dWr2jr82WpqKjQidfa7wYFBWHIkCFwc3NDSEiIzjjk5fMZM2YwK5acnZ0xZswYjBkzBq1btwZQu58XqJ2p0fa5dY/V1dW4cuWKjg2WlpaIiopCQkICvL294ezsDGtraybvdctBLpcjIyMDN27cYPR79+6N1NRUxMfHQyKRYObMmThw4EC9MV+753vSpEmMfteuXZGWlobhw4cz+/skEglUKhWsrKwYsba2Zs4vXLiAS5cuMWnIZDIkJiYiJSUFvr6++PHHH3Hw4EFIpVIdPW06EokE3377LTNmAQAfHx+kpKQgISEBdnZ26NKlC4qKinTGYXVj3pMnT3Rm6Hg8HoKDgzFixAhERUXhxIkTOqvkuFwu+Hy+jhQXF+vYoE2nb9++iImJwd69e3HixAnY2trCzs5O7/j06VOdFRFeXl4YN24chg8fDplMxrRdHo/H9BVa0frEtWvXUFRUpGNDjx49kJiYiKFDhzLvHXgZLpfL7M9VqVR6n/N4PGZ1hbacOBwOzMzMdPpeoVCIwsJCvVlfPp+PAQMGIC4uDllZWZg9e7bO5xwOh+l/uVyu3thWa0NAQACio6Mxb948VFVVQSgUwtzcnIm32vOCggI8f/5cR18sFiM8PBzx8fHQaDRISEiAlZWV3nhIO6ZavXq1zriwd+/eGDlyJOLj42FlZYXevXvjzp07TP5eHpvW1NTUu4LNw8MDcXFx6NixI5KSkpgxttZ2bd9lbm6O27dvo6KiQke/bdu2SEhIQHx8PLy8vEx+58Arx9A73Nchb/qMa1Nr8vv27Utubm60YMECysnJ0ftcrVY3uob9ypUrBNTu5fjmm2/q3ZNZU1PT6N4I7exXp06daP78+Xr7ndRqNVVVVTWYl5KSEmafj6WlJSUmJtKvv/6qs8e2qXKYOXMmWVhYUGpqKp08ebJee6urqxvMh1KppNatWxNQu6/z448/pnPnzul8X6lUNmrH1q1bCah9Oh0XF0e//vqr3p6YysrKRstz4MCBzNMnPz8/WrBgAd27d0+nHBqrT+0TYVdXV5o5c2a9e0Ka2ssWFxdHYrGYRo8eTSdOnNCzVa1WN1oOT548IS6XSy1atKDPP/+cbt++rfedpnxKu3fMz8+PVq9eTYWFhTqfazSaRvNRXl5O1tbWZGVlRePHj6dTp07pXU+lUjVqw8qVKxmfqk9fm0ZDaDQaateuHXXp0oXS09OpuLhY7ztKpZKqq6sbrFPt3mugdibsnXfeoUOHDunkvbKykqqqqqimpqbePNXd/92yZUuaOHEiHT58mNk/plKpGi3LO3fuEFA766BdvfDy3jOFQtGoX06aNImA2lUcqampdODAAZ1rqtVqKisra1Dy8/N1ZmUdHBxozJgxtHPnTiZONOVTixcvJgDUokULmjp1Kl29elXvO43Vp1KpJGdnZwoICKCff/653r2oTfnUpk2bSCaT0YcfflhvuyCiRv2BiGjAgAEE1O4jTE1Npf379+vUh0qlajQfly5dIqB2NUpsbCxlZGTo7buqrq5uNI3x48cTUDuzOHDgQPr222919p+r1epG9yfm5OQws3h+fn60bNkyvX10CoWiUb+cN2+eTqxcvHgxPX78mPlco9FQeXk5lZeXU0VFBdNOqqurSaFQUFVVFbm7uzNpODs704QJE2jv3r1MeTRVn9999x0JhUJKSEigQ4cO1VtvjeVBo9FQp06dSCKR0Lhx4+rtu5qy4dChQwSAunbtSsuWLaO8vDy97zRVn0lJSUx9BgcH03fffadXn4355N27d4nL5dKgQYPot99+qzfPTcWIqVOnMnEmPj6eMjIydPpPjUbTaB5KSkpILBaTi4sLffbZZ3Tnzh297zRVlosXLyaxWEzjxo3T6/+1NObXKpWKXF1dSSAQUHR0NG3fvl0vTiiVykbL4bfffmNi9eeff063bt3S+45CoWg0H9oY4ePjQ8uWLdPbU6pSqZixSH22PHz4kFlNZG5uTpGRkfTjjz9Sfn6+ThqNMXLkSJJKpfTOO+/Q+fPn6x1HNJaPgoICZiaxU6dO9PXXX+uMhYhq/bqyspKqq6uZcq2b3po1a5j2bWlpSfHx8fTTTz8x4wmNRkOVlZUN5kWlUjEr1MzMzCgyMpLWr1+vMx6pqamhyspKJl69nJ/9+/czNohEIoqJiaH169frlGVVVVWjPqFdDSQWiykhIYEyMjJ09pgaOi5866236Msvv6z3fQBVVVWN1kfdVW7dunWj2bNn082bN5nPm6rP7OxsZv+3q6srffrpp3Tx4kWj37nRHGDEjOtrvzltTN70G9fGqK6upsOHDxu0ubohDh48WO/NiTE2TJ8+nS5fvmyyDWvXrqWRI0fSrl27jN64rmXv3r3N2uh99OhR+uCDD+jPP/80uTxnzJhB69evN9mOixcvUr9+/WjlypX09OlTk9LYuXMnHT9+3OT6rKmpofXr15v0ohItx44do4MHDxr9IgQtGo2Gli5dWu/Aw1AuXrxImzdvNtmfiGpfzFDfzaahFBYW0unTp5sVmN9//32aPHkyZWZmmlSe9+/fp27dutGXX35pciexZcuWZvlEZWUljRs3jnbu3GnQy73qIz09nbp27UrTp0+nM2fOGN1GNRoNff3113T06FGT23deXh7duHHDJF0tly9fNvjlYPVx//59Sk5Opt27d5v0gioiou+//57WrVtHRUVFJunn5+dTZGQkfffdd/XeJBnCli1baO7cufTw4UOT9BUKBQ0ZMoSWLl1q9IuhtGzatIlpG/UNrA3h4MGDJpcBUe1gbuPGjUa/6KQue/bsoUuXLpms//TpU4qIiKB169bpDKaN4fr16/TkyROTbaiqqqJRo0bRpk2bDH7p28tcvnyZ9u/fb3K/Q1T7kqnm9H23b9+m9PR0k8uRiOjHH3+kI0eOmByncnJyaPr06Q0+GDOETz/9lJKSkvQmEAxFo9HQ1q1bm+XXW7ZsoenTp9P169dN0q+pqaGePXvS+PHjad++fSb1PXv27KEhQ4bQpk2bTPILjUZDUVFRlJqaSr/99ptJ5XHt2rV6b1aNYfv27fTHH3+Y7FPPnj2jwMBAWrRoET148MCkNNauXUtTpkwxOda+Coy5cWVfzsTSKET05iwPeI2w5cDyMs31CZVKZfRPQ72JlJWVvdbX6LP8/aisrDT5Zy5YWP7OaDQak38K501BpVLpLBk2heb2v0QEtVr9X98H/13Gpsa8nKnZ3s/hcFpyOJyjHA7nFofDucHhcCbV851ADodTwuFwLv9HvmzudVn+d/g7NIhXAVsOLC/TXJ/4b+8wtbA3rSyvGvamlYWlfv7bb1qB2r6vuflobv/L4XD+Fn3w/8Wx6auoNRWAj4noIofDkQC4wOFw/k1EL7+3PJOIwl/B9VhYWFhYWFhYWFhYWFj+D9HsRzdElE1EF/9zXgbgFgCX5qbLwsLCwsLCwsLCwsLCwgK8ghvXunA4nLcAdANwpp6Pe3I4nCscDmc/h8PxfJXXZWFhYWFhYWFhYWFhYfn78soWeHM4HEsAGQAmE9HLP3Z5EUBrIirncDiDAOwE0K6BdNIApAFAq1atXpV5LCwsLCwsLCwsLCwsLP+lvJIZVw6HI0DtTevPRLT95c+JqJSIyv9zvg+AgMPh2NaXFhGtJSJvIvK2s7N7FeaxsLCwsLCwsLCwsLCw/BfzKt4qzAGwDsAtIlrSwHcc//M9cDict/9z3YLmXpuFhYWFV/9vzgAAIABJREFUhYWFhYWFhYXl78+rWCrcC0AygGscDufyf/73OYBWAEBEawAMAfAOh8NRAagCkEhv8g/IsrCwsLCwsLCwsLCwsLwxvIq3Cp8gIg4RdSGirv+RfUS05j83rSCilUTkSUReRORHRCebb/rfm5qaGvz5558oLy83OY2/y7OBp0+fQqPRvFYbsrKyoFAoTNavrKzE0aNHUVxcbHIahYWFUKvVJuu/Ch49eoQbN240y46LFy+irKzMZP2KigpUV1ebrP8qqKmpabYNt2/fxvPnz1+RRf+9qFSqZqfxuuMDABQUFDQr5hLR3yJmZ2VlNTtGNJeqqirU1NS8tuv/nSgpKXklbZSl+Wg0mtdeF0SEO3fuNKt9V1VVvREx+3XzKmL+6/aH1wFvxowZr9uGBlm7du2MtLS0122GSRw7dgzz5s2DQqGAk5MTRCKRUfo8Hg/Tp0/HsGHDsGXLFpw+fRpZWVlQKpWwsbGBUChsMo2rV68iNjYW9+7dg1KphKOjI8zMzIyyY8WKFTh+/DgkEgns7e2N/rHj8vJyLFmyBBKJBA4ODib9WPK//vUvhIaG4siRI7h37x6qqqogl8sN/pH6mpoafPDBB8jJyYG9vT2kUqnRNpw4cQJdu3bFnj17cO3aNRQWFkIkEkEulxuUJ4FAgKlTpyIlJQUbNmxAZmYm7t+/j4qKCkilUojF4ibTuHnzJjw9PXHo0CHcu3cPCoUCtra2RvnW5MmTsW3bNpSXl8PW1hYSicRgXaC24/T29sasWbOwb98+XLlyBbm5ueDz+ZDL5Qb9qPiWLVsQFBSEzZs348yZM3j69CnUajVsbGwgEAia1K+pqUGnTp2wadMm3LhxA2VlZbCysjKqXjMzM3H06FE4OzsbVPb1ERAQgHXr1uH27dsoLy+HTCaDpaWlwfpZWVno0KED1qxZg2PHjuHevXsoLy+HVCo1OJ309HRkZWXBxcUF5ubmRuchOzsbq1atgrW1Nezs7Exqnz/88ANOnToFW1tbyGQyo/Xz8/Ph5+eHP//8E/n5+bCwsICtra1RtixfvhyffvopHj58CLVaDQcHB4NipBa1Wo1p06ahpKTE5LI8evQoevbsiePHj+Px48dQqVSws7Mzyo7Y2Fjs2LEDeXl5EIlERpfDnTt3sGDBAvB4PDg7O4PPN35R1Zw5c3Do0CEIBAI4OTmBx+MZpU9EePvttzFz5kzs378fV65cQV5eHvh8PmxsbAyOEYcOHYJMJoONjY3RfqlUKuHl5YWtW7fizp07qKyshFwuN6qtb9++HYsWLUJFRQXs7e2NattAbawcO3YsLl26BD6fb1JZ3rp1Cz///DNsbW0hl8uN0tXyzTff4Ny5c5BKpSa18ezsbHh4eGD//v0m9b9aG3744QeUlpbCxsbG6D64uroa8+fPh7m5OZycnEyKU9999x1mzZqFnJwcmJubGz2e0Wg0mD17NsrLy9GiRQuD+qqX+fPPP7F8+XJwOBy4uLiY1D5jY2Pxww8/4PHjx9BoNHBwcDDKlocPH2LOnDng8Xgm2cDhcDB//nwMGTIE//73v3Hr1i2UlZVBIpFAIpEYVKYFBQXo0qULDh06hKysLBARHBwcjLJlz549yMzMhJOTk9HjGKB2HDF58mTk5+fDwcHB6PYNAAcOHMDq1asBAC4uLkb7BBEhJiYGe/fuRWFhISQSicFjSi2nTp1CaGgorly5gpKSElhZWcHa2tooO9asWYPbt2/DycnJ5PFQc5k5c2b2jBkz1hr0Ze0d/5soPXr0oP9WVCoVde7cmQAQl8slX19f+uKLL+jYsWOkUCga1FOr1ZSTk0OXL1+mjRs3EofDIQA6wuFwyMPDg5KSkmjJkiV07dq1BtNLTk5m9Hg8Hvn4+NA//vEP2rt3L5WUlDSZjxs3bhCXyyUA5OjoSCkpKfTzzz9Tbm6uwWWRkpJCAKhFixY0fvx42r17N1VUVDSpp9FoqLy8nB48eEAtWrTQKwc3NzcaMWIErVixgs6dO9douS5YsIDR8/T0pI8++oh+//13qqysbNKG4uJiun//PvXo0UPPBrlcTqGhofTll1/S3r17KS8vT0e/urqaHj9+TKdOnaL09HQ9fa24uLhQeHg4ffnll3T9+vUG7YiNjdXT9fDwoNTUVFq7di1du3aN1Gp1g/m5efMm8Xg8Rtfd3Z3Gjx9PW7ZsoZycnAb1qqqq6NGjR3Tq1CkaNWpUvXkQiUTUs2dPev/99+nHH3+koqIinTTKysro3r17dOzYMbKxsdHT53K51LlzZ0pNTaX09HQ6f/48aTQaPVsqKytp6dKlevotWrSgoUOH0tKlS+nMmTON+kNxcTFZW1sTh8MhX19fmj17Nl26dKne69WHWq2m3bt369ng6upKycnJtHr1arp69SqpVKp6y/Lx48d0+vRpCgwMbNAfoqKiaNasWbRv374G87Jv3z4CQHw+n/r27UsLFiyg69evG5wPIqIBAwYQAGrdujW9++67tHfv3ibbRV1u3rzJxIj27dvT5MmT6cCBA1RVVWVwGgsXLtTJv42NDUVHR9PixYvp7NmzpFQqG9Wvqqqit956i9Hn8/nk6+tLU6ZMoT179uj5YmM28Pl8CggIoDlz5hjsE2q1mgoLC8nf31/Pp7t27UrvvPMObdiwge7du9doeidPntQrh5iYGFq6dCldvHixXn+qi0ajoYCAAAJAYrGYIiMjadWqVfTw4cMm86Dl2rVrTL8jkUgoIiKCli9fTrdu3WrU9urqanry5AmdOXOGxo0bV69fW1hYkL+/P02cOJHWr19PhYWF9ab17NkzMjc3JwDUpk0bevfdd2n37t1UXl5uUB6USiWtWbOm3j5j5MiR9O233zYZK6urq6lNmzaMbufOnWny5Mm0Z88eKi0tNciOX3/9ldEXi8U0aNAgWrx4MV25cqXRa2tRq9Xk6enJxOqPPvqIDh8+3Ghse5kTJ04wNjg7O9OoUaNo06ZNen1VfWj74HfffVevLN3d3ZmybCjWaXn+/DmJxWJGt127dpSWlkabN29utN+py3vvvUcAyN7enkaNGkXbtm0zaAyjpaqqilq1asXYIJPJKDo6mpYtW0ZXr141qD60/Y6ZmRmFhobS8uXL6f79+wbboFKpqGPHjkx/GRoaSkuXLqWbN28aHLMvX76sMy7UxrpPPvmEfvvtN8rPz28yDW3MF4vFFBERQenp6fTgwYMm9ZRKJb148YJOnTpFFhYWej7h5ORE0dHRNGfOHDp06BAVFxfXm45Go6FZs2bp6AoEAurZsyd98skntHPnzibHmM+fP2diRPfu3Wn69Ol0+vRpg+pRy7x585jre3l50ZQpU+jw4cNUXV1tkL5CoWD6HTMzMxo4cCAtXLiQrly5YnB9HjlyRK8MExMTac2aNU3GXC1Dhw7VSaNly5Y0fPhwWr16NV2/fr3JMsnMzGTuLXx9fWnmzJl09uxZo8qyuQA4TwbeG3LoDV6a5O3tTefPn3/dZjTI3Llz8fz5cygUinrl/v37yMrK0tMTi8UIDAyEh4cHHj16hOrqamRnZ+PFixfIzc01eAlGnz594OrqCoFAgMrKSpSXlzNSVlaG8vJyFBUVNbjcmMvlonPnzhCLxejSpQuA2qdQSqVS53js2DG9pZ0cDgfdu3dHSEgIRCIRioqKmCfpLztZVlYWtm/Xfdm0ubk5+vfvj/DwcAQGBmLlypUoKChAfn6+jhi6HLNr165o2bIlWrZsCZVKpWN/TU0NSktLcfToUT09c3NzBAQEICQkBFevXoVCoUB+fj7y8vKQl5eH/Px8g5eceXt7w8LCAmZmZsjOzkZ2djYKCgx7Bxmfz0d0dDRkMhlqampQUFCAwsJC5mjoMmEbGxu0a9cOHh4eqK6uRmVlJSoqKhiprKzEkydPGlxe4unpCVtbWwiFQqhUKsYvDV3ibGFhgZiYGGYpUE5ODl68eIGcnBxUVlYalIaLiwt69+4NDocDhULB5F8rVVVVTaYhFArh4eGBXr16MU8Qtf6oPf/9999x69YtHb0WLVpg8ODBCA8Ph5mZGTIyMlBYWIiioiJGCgsLUVJSYtASn7Zt28Ld3R0VFRVMWZSUlBhUDlKpFBERERAIBJDL5dBoNIyo1WrmuGHDBj0fbd26NQYNGoRBgwbh+fPnuH//PjQaDVMGdc9v3ryJw4cP6+iLRCL0798fgwcPhr+/PzZu3AiVSgW1Wg2VSqV3vn//fhQVFemlERQUhLCwMGg0Gty4cQOlpaUoKSnRO5aVlTW6dMzCwgJt2rRBly5doFQqUVpaitLSUpSVlTHHxuqEw+EwdeHm5sYsuaubl7KyMuzcuVNP18nJCaGhoQgLC8PJkydRUFCg1z6LiooMWvpmb2+P9u3bo3Xr1qioqEBZWZmeNNbWrKys8NZbb6Fz586QyWRQKpU6+VAqlbh79y4uXbqkp+vu7o7Q0FB4e3vj7Nmz0Gg0Ov1VdXU1c3727Nl621mLFi0wcOBA8Pl8FBQUoLi4GC9evEB2drZe/TeEubk54uLiQESwt7dn/Ohl3zp8+DBevHihoysUChEQEICwsDCIRCJcvHhRp11qj4ZsReByuWjfvj18fHzA4/FQXV2NqqoqneODBw+Qn5+vp8vn8+Hr64sOHTqgpKQE1tbWUCgUOvpauXjxYr3Xt7OzQ//+/QEA1tbWEIvFen2nRqPB+fPncerUKR1dqVSK4OBghIeHo0OHDtiyZQvT19Xt97Ry5MgRva0uHA4HPXr0QEhICKqqqpj6rNvnFBYWGtT/WVpaon379ujUqRNUKhUqKyuZvkd7/vjx4wb7c09PT7Rp0wYWFhZo1aqVTnzSSnZ2NrZt26ZXDwEBAQgPD0dYWBi+/fZbpq8rLy/XOVZUVODFixcN9h+2trbo1KkTxGIx2rVrByKCWq3WibWVlZX45Zdf9HTd3d2ZeHv69GkUFBTojaW05zdv3sT9+/f10mjZsiWCg4Ph4eGBW7duQaFQoKSkRE9KS0ubjDVubm7w9fWFXC5n4kLdGHH//n1cuHBBT69du3YICwtDt27dcOLECRQVFTFjodzcXBQVFRnU71laWsLHxwdSqRQCgQBFRUUoLi5mjsXFxQbFyy5duqBPnz4wMzNj+j5tu9BoNNi7d6/eGNvOzg6hoaEYPHgwzM3NcezYMZ3y154rlUqUlJTo9X3A/x+jh4SE4O7du+BwOHptSis3btyod5zv6OiIgQMHws3NjZkd18b4umP0srKyRseJDg4OcHR0RNu2bcHlcuvtQ5vaUmhtbY2OHTuiR48e4HK5en6tVquxdetWVFRU6OjZ29sjNDQUgwYNQnBwsEkrqgyFw+FcICJvg75s6B3u65A3fcbV3d29wRm0pkQul9PAgQMb/FwoFFLr1q11nlICIKlUShMnTmRm5UJCQky6vlAopOjoaPrnP/9pch60+Wjfvn2z0jBEtDM6dcXFxYW++OILevDggc6TM1OkY8eOZGlp2eh3zMzM9P7n7OzM2LB58+YGda2srKhDhw569eni4kKzZs2i58+fExFRz549jbadx+NRVFQU7dy5U2/GxhiRyWQ0btw46tevX4Pfsba2prZt2+r939PTk1auXEnFxcWUm5vbpM9YWVnp/I/D4dCgQYPot99+I6VSSdOmTTMpDz169KCVK1dSQUFBk/XZlJiq7+LiQp999hndvn2bOnXq1KhPODk56f3fx8eHvv/+eyovL6fDhw83Kw/a8m6OvkAgaJY+j8cjFxcXk3SlUimNHj26WeXQtm1b+vLLL+mzzz5rVj6srKz02q8hYmZmRomJiXTgwAHKyMgw+fq+vr60YsUKvVldY8XNza1Z+p6entS1a9dG68zV1VXv/+3bt6elS5dSQUEBlZSUNMsGDoejM3tmjLRv357mzZtHT58+bVbb6NChA8XExJisb2ZmRtHR0TqzuqaIdtbJVHFxcak3phsiQUFBtHHjRrp3716z7I+Pj6fIyMhm+0R9K9QMEbFYTMOHD6d33nmnWTYIBIJm9TsCgaDelV2G6kZHR1NGRgYzo2qqNOUPfD6fhEKh3v/9/Pzo+++/p7KyMkpLSzPp2q6urjRjxgy6efNms/IA1I5XmqPfrl07k2K+ViwtLZsVr3v06EGLFy+m7t27m6TfokUL+vTTT2nTpk3NLsvevXvTiRMn/sfup2DEjOureKvw/1mSkpKQl5cHMzOzemXPnj3Yt28f830bGxvExMQgPj4eQUFBePbsGVatWgVHR0c4OjrCycmJObe2tkZ1dTWcnJwAAD4+PpgwYQISEhJ01qBHR0fD09MTlpaWsLS0hEQiYc4tLS1x+PBhzJs3D0DtE9bAwEAkJSUhNjYWMpkMubm5uHXrFgQCAQQCAYRCod75okWLdJ58Ozg4ICYmBnFxcejbty+2bNmCP/74AxwOh1mbrz3ncDh4/vw5du3apVN2IpEIAwYMQGRkJAYPHoyFCxfCysoKtra2jNjY2DDHhIQE7N69GwKBAJGRkRgzZgyCg4OZPUPdu3fHhAkTIBQKGbvrHktLS/H111/r2NCtWzfExcUhLi4OHh4e+Prrr6FUKmFnZ8eIra0tc/zoo4+wcuVK8Hg8REREYOzYsQgJCWH2ZdTU1GDq1KlwcnKCs7Mzc3R0dISFhQWKi4uZ+gwODsY777yD8PBwnX0dw4cPR2BgIGxsbCCXy5mj9nzDhg2YMmUKgNqn1KmpqRgxYgQcHBwAAM+ePcO7774LsVjMiIWFhc55amoqcnNzAdQ+WYyOjkZiYiKCg4MhFAqxbds29O7du16/NDc3x6+//or4+HgIhUIMHToUEyZMgL+/P1P3Go0GkyZNYp4UOjg4MGJvbw+hUIg+ffrgxIkTcHJywpgxYzB27Fi0bt2aKYeAgAAoFAqd/Ncth7/++gu9evUCUPuEdcSIEUhNTUXnzp2ZNFJSUqBQKOr1S6B2H/rt27d1fMLFxQURERGIjIyEVCpFRkYGZDIZI3K5nDlXq9Xo2rUrlEolzM3NERMTg1GjRqF///6MX44bNw7FxcVMOdQtD5FIhK+++gqzZs2CWCxGUlISxo8fj+7duzP2ODs7Y+zYseByueDxeOByuYzweDxwOBykp6frzGQIBAIEBQUhOjoaERER2LlzJ65cucLkncvl6pzfvXsXBw8e1CkHmUyGwYMHIzIyEj4+Ppg7dy54PB74fD74fL7e+dq1a5Gdnc3om5ubIyQkBDExMQgPD0dmZiYyMzMhlUqZ/ch1z+/evYuUlBQAtbMooaGhGDFiBCIjI5k93JMmTYK5uTmkUikkEonOUSqVYtq0aTh06BCA2libmJiIESNGwNfXFxwOB0eOHEFhYWGD+aioqMCSJbq/6Obk5ISoqCjExMQgMDAQixYtYvZLvtw25XI55s2bh6VLlwKoXYExevRoJCYmMk+qb968iYkTJzL7wbSizYtAIEBYWBizOqFdu3YYMWIEhg8fDjc3NwD/f/+m1m4+nw+BQMCcnzt3Drt379bJR8+ePRETE4OYmBiIxWLMmjWrwX7LzMwM06dPZ2IEAHTu3BlDhgxBfHw8OnTogO3bt+Py5ctMXNDGCQcHB1hYWGDXrl2IioqCQCBAbGwsJkyYgL59+zJtT6FQYNy4cQ36E5/Px08//YQHDx4wNgiFQgwYMAAxMTGIiIjA9evXsX//fqZNvnzMzc2Fv78/gNqZ6sTERIwaNYrxBwAYO3YsFAoFzM3NIRKJdI7m5ubYsGGDzoyMu7s7EhISMHToUHh6euLChQvMOyzqS4OIkJaWxswuCYVChISEYOjQoUyM+frrr/HkyZMG2+fFixdx8qTu+ywdHByYOOXq6ooVK1bo9X11+/KvvvpKZxb6rbfewpAhQxAXF4e3334bP//8M27cuKHn11o5fPgwRo4cCaB2NceoUaMwcuRItGnTBkDtuyzeeecdpq+xsLDQO58yZQru3LnDxKjQ0FAkJiYiIiICEokE27Ztg52dnU7+60peXp7ejKtIJEJwcDAzjpg/fz64XC4sLS2ZPk97bmlpiQULFuDIkSOMDWFhYRg+fDjCw8MhFotx7NgxqFQqnXjL4/GYc4VCgRUrVujYIJFIMGjQIERHRyMsLAxLly5FXl5eveMQgUCAAwcOMHEKqI2VoaGhiIuLQ3h4OPLy8rBy5UpYWVnVKyKRCAEBAczKHV9fX6SkpCAhIQE2NjYAascBbm5uOnGhrly6dElvdYmPjw9iY2MRExMDR0dHfPXVV7Czs4O9vb3OmEj7npBOnTrh1q1bkMlkSElJwZgxY3T63+DgYEilUlhbW0Mmk8Ha2lrn/OrVq0hMTGTKcOjQoRg5ciSz2kqlUmHMmDE6fd7L8ttvv+Hhw4c6+fDy8kJUVBSioqKQl5eHnTt31ju+FQgEKC0txdy5c3X0u3TpgtjYWMTFxcHT0xOfffYZKioqmDYlFAphZmbGnG/fvh3Hjh1j9K2srBAZGYkhQ4YgODgYd+/exffff8+MzV8+crlchIeHMysbXF1dkZSUhOHDh8PDwwNAbZ/Yv39/nT5T6w9SqRTbtm3D/PnzmbIcMmQIkpOT0bdvX3C5XDx+/Bhjx47V8+m6f69evRqlpaVMPoRCIfr378+MI7Rj1zcCQ+9wX4e86TOujVFTU0OtWrUiW1tbSktLo3//+99N7tN6mZ07d9K4cePo/PnzJtmg0WjIx8eHunfvTosXL6anT58ancb58+cJALVq1YomT55MmZmZTe6zehntfidHR0caO3Ys7dq1y6A9rlqePHlCnTt3psWLFxu1t7YuX375JfNEcOHChQbt56hLRUUFeXt707x58yg7O9skG7Zu3Uoff/wx3b171yR9jUZDvr6+NGHCBDp79qxR+xi1HDhwgIRCIcXExNCWLVuMqgctEydOpIULFxq0R6o+7ty5Q2FhYbRjxw6j24SW999/nyIjI2nHjh1G7ffSUlZWRra2tgTU7o/56quv6MKFC0aV6fz588nf35/Wrl3b4F6exlCpVBQREUGrV682aq9WXX7//XcCamcDhw0bRps3bzbalkGDBjFPuj/88EP6448/jKqXa9euMU+3k5OTafv27QbvRdSSlJREPj4+tHz5cpPa+LNnz0gqlVJCQgLt3r2bampqjE5jzpw5zFP2KVOm0KlTp4za41NVVUUdO3akjz76qNH3DjTGunXryN7eniZNmmRSG9doNPT2228Tn8+nAQMG0KpVq+jZs2dGpaHd7+Tl5UWzZ8+m27dvG6VPRDR58mSaO3cuvXjxwmhdIqKsrCxm9iohIYE2b95sdBuZPHkyBQcH0y+//GLUnm0tpaWlZG1tTW5ubjRt2jSj9q1pWblyJfH/H3v3HR5V0fYP/LvZTW9segKE0KUFIZRESkgnEAghJKE3KaIoFlBB0aCggCCKdEEUUBSkCdISpIN0DIQUCCGN1E3vye79+yPuebNsQrK7vq95nt/9ua65dmF3ZufMmZkzc86ZE4mERowYQT/88EOz1lrXp1AoqHfv3gTUXelevHixxvVS2Ud07dqVlixZonE/R1TXR0yePJnOnDmj1bq3mJgYEovF5OvrSzt27Gh0bfPzvPXWW8I4Yvbs2XT06FGN9mtOTg6ZmpqSt7c3ffvtt1rlQbnG1cnJiebNm0cnT55s9npIorpxYbt27YR6vW/fPiopKdEoD7t37yYXFxdaunQpJSQkaLoJREQ0ZMgQEovF5OXlRevXr6fU1FSN4l+6dIm8vLzop59+0uhZBvVFRESQv78//fjjj1qNQ7KyssjY2JgkEgn5+PjQ119/TcnJyRqlsXTpUgJAAwYMoFWrVmk8NisvLydbW1uytraml19++bnPo2jMpk2byNbWll5//XW6evWqxm1TuQ5+xIgRtHfvXq3KUtnnW1pa0sSJE2nfvn3NXsf/T4EGV1z/9cnp88J/8sQ1JSWFzpw5o/XAnIi0mpjUV1FRQXFxcTqlER0drfUkiahuwrds2TK6du2a1gu9KyoqdCoLhUJBe/bsobS0NK3TqK6u1nl/6Kq6ulqrAVh9f/31l1aTrPp0LYd/YsG/thM9pQsXLtCmTZs0PmDXJ5PJdMqDQqHQuSx37dpFUVFRWk3eieoGc59//jnFxsZqnZcTJ05QVFSUVpNFJU0eHtSQp0+f6lQnFAoFbd26VeMHW9VXXl6uUxkQEcXHx+t0zMjMzKQffvhBp7p54cIFrQfESrrW63PnztHvv/+u0aTgWdpMTOpLSkrS6IFtDTlz5oxO+UhMTKR169Zp9ACgZ504cUKneq1QKHTub2NjY7U+iUFU9xCcFStW6DSOSElJ0fgkTn0KhYI2btyoUx6SkpLoyJEjWk/2iOpO6uhyDM3JyaHvvvtO6xPPRKRzP0dEOtUHIqKoqCj68ccftW5fCoWCdu3apdMYICEhgaKjo3Xqs2NjY3WKX1ZWpnNZ7tu3T6dxxD9Bk4krP5yJMcYYY4wxxtj/OU0eztT0H1RjjDHGGGOMMcb+RTxxZYwxxhhjjDHWovHElTHGGGOMMcZYi8YTV8YYY4wxxhhjLRpPXBljjDHGGGOMtWg8cWWMMcYYY4wx1qLxxJUxxhhjjDHGWIvGE1fGGGOMMcYYYy2aODIy8t/OQ6O2bdsWOWfOnH87G1o5f/48rl+/DktLS1hYWGgcn4hw69Yt2NraQiwWa5WHsrIyiMVi6Olpf34iJycHpqamWsePj4/HJ598gtzcXOjr68PKykrj/MTHx8PY2BgGBgZa5SEnJwfz589HcnIyampqYGVlBUNDQ43SSE1NhUQi0ToPRITc3FydyjI7OxsKhULjvNdXXFysU/zs7GxkZGTA2toaIpFIqzS+//57PHz4EBYWFrC0tNQ4fk1NDWprayGRSLT6fQD47bff8Ndff2mdB7lcjpiYGNjZ2WldDsePH8e+fftQVVXbRgyRAAAgAElEQVQFKysrGBsba5xGTEwMrK2ttW7jBQUFkMvlWtdrAKiurta6jwKA/Px8xMXFwc7OTuvt+Oabb3D8+HGUlJTA3Nwc5ubmGsWvqalBeno6WrVqpdXvA8DDhw9RU1MDMzMzreITES5fvgxbW1vo6+trlUZ0dDS+/PJLZGdnQywWa1U37t69C6lUqnX7Sk9Px7Vr1+Dg4KB1vfrrr79gZGQEIyMjreLL5XLI5XKd6uXDhw+hp6enVbtU5uHy5ctwcHDQuiyTk5NRXl6u1RhCmYf3338f9+/fh1wuh7W1tcb7JDMzE1lZWbCystK6r0tISICFhYXW++Px48dYsGABUlJSUF1dDalUqvFx7LvvvkNUVBSqq6thbW2tcXy5XI7s7GyN+5b6zp07p/O48Pz581rlX+nixYvYtGkTCgsLYWpqCktLS432KxFhyZIluHLlCkpLS2FhYaFxn/f48WP88MMPEIlEsLOz06peyGQyGBsba10nCwoKsHXrVp3ycOzYMVy6dAlGRkZajYkUCgVu3LgBe3t7rY996enpqKqq0npsSUTYuHEjcnNzYW1tDRMTE63S0dWyZcsyIyMjtzXry0TUYoObmxv9p8rOziZLS0sCQM7OzjR+/Hhav3493bp1i2pqapqVxjvvvEOmpqYUGBhIa9asobt375JcLm92HnJycqhdu3Y0YcIE2r17N+Xk5Gi8HV988QV17NiRXnvtNTp69CiVlJRonMaYMWMIAAEgMzMzGjp0KL399tv0008/UWJiYpPbdPToUdLX1ydPT0/65JNP6MqVK80uQ6V3331XyINIJKKuXbvShAkTaM2aNXT27FkqKip6bvw7d+6QkZERDRs2jFasWEHXr1+n2tpajfIwZcoUevHFF+n999+nc+fOUXV1tUbxnz59ShYWFjRo0CBatmyZVuXw4YcfkpubGy1dupSuXr2q8TZUVFRQu3btqHXr1jR16lT6/vvvKS0tTaM0Lly4IOyL1q1b07hx42jt2rV05coVqqysbDK+XC4nDw8PCg4Opq1bt1JqaqpGv09ElJiYSAYGBgSA2rRpQ2FhYbRu3Tq6du0aVVVVNSuNiIgIsra2pvDwcNq2bRslJSVplIfi4mJq3bq1UBadO3emSZMm0ddff01Xrlyh8vLyJtN47733yNLSksaMGUMbN26khIQEUigUzc5DQUEBOTg40LBhw+jzzz+nO3fuaNTHEBF99dVX5OnpSV988QXFxcVp9PtERLW1tdS7d2+SSqUUEhJC33zzDcXGxmqUzuPHj8nY2FgoS0dHRwoKCqLIyEg6duwYZWZmNpmGn58fde3alebPn0+//fYbFRcXa7QdcXFxJJFIqEePHvTGG2/QkSNHqLCwUKM03njjDTI0NCQvLy/69NNP6fLlyxr1EzU1NdSnTx+hHIyMjGjgwIH06quv0vbt2+nOnTtNprdmzRoyNjYmPz8/WrlyJd24cUOjfqKmpoZ69OhBEomE3N3d6b333qPjx4832cfWd+jQIdLT06P+/fvTe++9R6dPn6aysrJmx1coFOTl5UURERG0e/duys3NbXZcpZs3b5JYLKb+/fvT+++/T1FRUc1qk/XNmDGDjIyMyMfHh1asWEFXr17VqM9OT08nY2Nj6tq1K7366qt04MABys/P1ygP+/fvF+qDnp4e9ezZk6ZPn04bN26ka9euUUVFxXPjl5WVkZOTE7Vt25amTZtGu3btooyMDI3ysGPHDjI1NaURI0bQunXr6N69exr3E7NmzRK2AwB16dKFxo8fT1988QWdOXOGCgoKnhs/OTlZ6CNEIhF169aNpk6dShs2bKBr164169gzYsQI6tWrFy1cuJCioqKaFae+rKwssrCwIADUtm1bioiIoPXr19PNmzeb3c7fe+89EovF5OHhQUuWLKGoqCiN2kZNTQ29+OKLQjna2NjQ8OHDaenSpXTkyBF6+vRpk2mcP39eZV84OTnRqFGjKDIyko4ePdpkGgqFgjw9PQkAGRoakoeHB7399tu0f/9+Sk9Pb9Z2/PLLL+Ts7Exz586lQ4cOadxfExFNnjxZyMOgQYNo0aJFdPDgwWYdL4jq2qeZmRkBIEtLS/L396ePP/6YTpw40ex2Onv2bDI3N6egoCBat24dxcTEaNQ2MjMzyczMjF588UVauHAhnTx5UqP6QET0/fffC/uya9euNH36dNq6dSvFxMRoPEbUFoCb1My5oaju+y1Tv3796ObNm/92NhqlUChQXFyM/Px8FBQUCEH57/379+P27dtq8UxMTDBw4EAMGjQIHh4eGDJkCGpra1FRUaESnj59irFjx0KhUAhxbWxs4O3tDR8fH/j6+qJDhw4q+VEoFMLZZrlcjo8//hjr1q0DAIhEIgwYMACBgYEYMWIE3NzchLM8RAS5XC5czVK+lpSUoH///igoKAAAGBgYYMiQIRg+fDiGDx+OHj16gIhQUFCA7OxsZGVlITs7WyU8ePAA165da7QcLS0tERERgWXLlsHU1BSVlZWorKxERUWF8Dpx4kQ8fvxYiGNhYYFhw4bB19cXvr6+6Nq1K4qKipCVlSWcIa7/mpycjCtXrjx3f4aEhGDt2rWwt7dHVVWVWpg/fz4uXLggfN/Kygre3t7w8/ODn58f2rdvL5RlbW2tEJRlmZCQAE9PTyjbnLm5OXx9fYWydHZ2FvZjdXU1qqqqhFfl+08//RR79+5VKTtvb2/4+/vD399fpT4QkVAflK8ymQzdu3dHWVkZAMDa2hrDhw9HYGAgAgICYGNjA6Du7HJFRQXKy8vVXn/++Wds3LhRpey6dOki1EsvLy9YWFggPz8fMpkMMplM5b1MJsP27dshk8nU9oGBgQH69u0Ld3d3BAYGws/PDyKRSNgW5XYcPHgQkyZNEuK5urpixIgRGDlyJNzd3SGRSCCXy1FYWIj8/PwGw+7du5GUlKSWByMjI/Tr109omz4+PqiqqlKrk7GxsZg2bZpK3Pbt2wt10tvbG1KpFDKZDDk5OcjJyUFubq7wPicnBxcuXEB8fHyD9VEikcDV1RURERF49dVXoVAohLahDJmZmQgKCkJtba0Qr23btkIefHx8YG9vL9TJmpoa1NTUoLq6Wnj/5ZdfYv369UJ8e3t7+Pv7IyAgAH5+frCzs2swf0plZWXo0KEDcnJyAACdOnVCUFAQgoKCMGTIEOEKj1wuR3l5uRDKysqE9ydOnMDq1atV0rW3t4e3tze8vb3h5eWFNm3aICcnR+hnlH2N8v25c+eQl5fXaD5dXFywfPlyhIWFoaamRmhTynD16lVMnTpVpfxfeukloW317dsXYrEYNTU1Km2i/vsPP/xQpY/Q09NDv3794OPjA29vbwwaNAiGhoaorKxUKQtlSE1NxeTJk1H/uGxmZoahQ4cKZdGzZ0/IZDJhu5X9nPL93bt38fDhw0bLwdjYGG+//TbeeecdiEQiteNOYWEhxowZI/QRACCVSuHl5SUcdzp37ozq6mqUlJSguLgYJSUlKuHkyZPYuXOnyu/q6emhT58+8PT0hKenJwYNGgQzM7MG+5jy8nJMmzYNaWlpQnwDAwN4eHgI/cyAAQOee2X6t99+Q3BwsPDbHh4eGDlyJIKCgtCzZ0/h6kj9Y6+ybSvfL1iwANevXxfSNDQ0xKBBg4S25ebmJpRh/fqsrN8PHz7E7NmzVfJlbm6OoUOHwsvLC97e3ujduzcUCoVanVL+e/Xq1Th69KgQXyQSoW/fvvDx8YGPjw8GDx4MIlI77tYPR44cUekj6tPX18fAgQPx2Wef4cUXX2yw39+9eze2bVO9GPLCCy8I+2LYsGGQSqWora0V+sr6r2VlZQgKChL6CABwdHQU+ilfX184OjpCJpMhMzNTCMo6nZmZiYcPH+LOnTuN7m8AmDRpEhYtWgQiUulnleHkyZPIzMxstBx69+6N119/HRMnThT6y/p95Y0bNxAaGirEMTY2hpeXFwICAhAQEIAuXbqAiFTGhfXHh/n5+di/f3+D22FiYoIBAwZg0KBBcHd3x6BBg1BdXY2ysjKhbpWVleHp06eYNm2ayrjQwMAAAwcOhJeXF7y8vNC/f3+UlZUhOztb6DOVIScnBzdv3sS9e/caLUcnJydMnDgR06dPF8ZVz/Y30dHRqKysbDSNbt26YeXKlXB1dW1wHHDjxg0cO3aswbht27aFh4cHPDw8MGXKFKFuKYNcLkd1dTWGDh2KxMREAHX99eDBgxEYGIjhw4ejV69eAICKigqV475yP+Tn5+PBgwf4/vvvG8xDhw4d4OHhAXd3dwwdOhSGhoYqYxhlOHjwIBISEhpM44UXXoC7uzu8vb0REhKC6upqtfb9+PFjTJw4USWenZ2d0LZ8fHzQvn17yOVyoU09G1auXIn9+/er1IeXXnoJfn5+8PX1hZubmzD+U257/f2Rl5eHr776CtXV1WrbYG5ujoEDB+Kll15CUFAQ+vfv3+g+14VIJLpFRP2a9eXmznD/jdDSr7i2a9dO5ayTJsHR0ZFCQ0NJJBJpnQYAatWqFYnFYq3i2traUnBwMOnp6Wn9+61bt6aOHTtqFVcikdC4cePot99+03oblEF5dVvTYGBgQBMnTqQLFy6Qo6OjTnlwcHDQqSy7deumcx6cnJxIT09Pq3olEonI3d2devXqpVMedK3T3t7eFBISQhKJRKvybNWqFYWHh+tUp3r06EHjxo3TaTsAqFwF1CTo6+tTeHg4rVy5UufylEqlOsXv0aMHicVi0tfXF4JEIiGJREJisfi55Wxubk7jxo0jHx+ff61Oubi40GeffUaRkZE6pSOVSsnU1FSn7TAxMdG5TinP8GsabGxs6N1336XDhw//I8cdXeK3bt1a5zxYWlqq1ENN+j1nZ2d69dVXtS5LXfdF/WBubq5TfENDQ63j9urVizZs2ECjRo3SKQ/aHnPqB2tra633wSuvvEI3btzQqS7Nnz+fFi9erNN2tGvXTqc64eTkRKGhoTqVIwDhqq42dWny5Mm0detWrX974MCBtHPnTpo4caLWadjZ2dGCBQtIIpFovT9at26tcveJpsHIyIgmTZqkU58/cOBAtTsF/i/3pzLoUif19PRoxIgR9Ouvv2p8h4EmoMEVV+0XiTGVtXGmpqaQSqWQSqWwsrKCVCpFVlYW/vzzT+E7BgYGGDNmDKZPnw4/Pz+cPXsWBw4cUEvXwMAAxsbGMDY2Rl5entqZUltbW4SGhiIiIgIrV67EqVOntMp/27Zt4eLionLmThNt2rTB2LFjkZmZiaSkJIjFYtjZ2cHe3l4IDg4OEIvF+Pzzz4V47du3x+zZszFjxgw4ODgIZ9AaolznVFVVhYqKCpXPJBIJ/Pz8EB4ejuzsbLz//vvQ09ODvb09HB0d4eDgILxaW1tj0aJFwu906NABc+fOxYwZM2BrawsAz11joLxq1NAZqV69eiEsLAwWFhZ48803NSvEv3Xr1g1jx47F77//3ugZYeV65ZqaGrXP2rZti3HjxqFHjx6YNWuWVnkwNzdH+/btkZGRofaZnp4eTExMYGxsDLFYjKysLLXvDBw4EBERERgxYgReeOEFIc9WVlawtrYWXq2trfHnn3+qXGl0dnbGjBkzMG3aNLRv3x4fffQRDh06pNV2mJiYwMrKCqampiguLgYAtGrVClZWViohMTFR5Y6IVq1aYcKECZgxYwb69euHXbt24ddff1VLXywWw9jYGEZGRg1e4bOzs0NoaCjCw8OxaNEi3Lx5ExKJBHZ2drC1tYWdnZ3wPjU1FQcPHhTidu3aFbNnz8bUqVNha2uL8+fPq1x9q0+Zh+LiYrX2Y2ZmhlGjRiE8PBzfffedyhWb5jI1NcXIkSMxZMgQvP7664220ecpKSnBo0ePGlyraGBgABMTE5iYmEBfXx8pKSlq3xk0aBDGjx+P0NBQdOjQAZWVlTAzM4ODgwMcHByEPsbBwQHnzp3DmTNnANTto1GjRuGVV16Bn58f9PT0sH79+kbLEqi74tJQ2zIyMkJgYCBCQ0OxdOlSJCcnq3wukUhgbGwMExMTVFdXC3en1P/c398fERERMDIyQkREhMrnyrZlamoKExMTpKWlqfX5HTt2xPjx4zF+/Hi89957OH78OAwNDdX6OUdHR2RnZ6vcETF06FC88sorGDt2LAwNDREbG9tgOUgkEhgZGcHY2BhFRUVqfZ2FhQWCg4MRERGBQ4cOYceOHcJnhoaGsLCwENYX6+npqV1VkkqlCA8Px6RJk9CnT58G1woaGhoK/UxxcTFKS0tVPjc3N8eYMWMQERGB69ev45NPPlFLozlkMhmys7MbXJMmEomEcqiurlbLg1gshre3NyIiIiCXyzF37ly1z01NTYX9mZycrHaM7datGyZMmICIiAhMmTJF5aouAGFtrbGxMRQKBfLz89Xy6OnpiYiICHTq1Al+fn4A6vqw+sdfZfvYvn07njx5AqCu3xg/fjzmzJmDgQMHQiQS4eLFi2rloKyXJiYmEIlEyM7OVvuOh4cHIiIi4OnpiT59+jRY1sp6VVVVpda+lGUZFhaGxMRErFmzBhKJRKjL9YOpqSkWLVokxHV1dcW8efMwadIkoS5ZWFgIz3Gwt7cX+lpluH79Os6dOyekMWjQIMyZMwfjxo2DiYkJtmzZ8tw+ojEikQhDhgxBaGgoNm/eLBzbzMzMhHGhcmyYmZmpMi40NDRESEgIpk+fDl9fX/zxxx9q40IDAwOhPpmamuLJkydq7bN79+6YMGECxo8fj4ULF+LIkSOQSCRCOdSvEwUFBfj222+FuN26dcPcuXMxZcoUWFlZqfTFUqlU6F/q9zW7d+9GTEwMgLpjxeTJkzF37lyhHty9e1dIw9TUVDj2K8cBenp6+Pnnn4XvSCQSjBw5EjNnzkRgYCCICF9//bXG+wKoG5sPGzYM+vr6Qj9kYGAg/L5yX1hYWGDPnj0qcT08PDBjxgyEh4fD0tIS7du3R1lZGUQiEaRSqbAdypCUlITLly8L8W1tbTF16lTMmDEDPXr0wIEDB7B9+3a1PBoaGgptXPn8kvqcnJwQFhaGiIgIvPvuu7h06ZJaGvr6+sKxtaSkRO3z3r17Izw8HL169cLo0aMB1JVz/XGQskxOnz6tMvbs2rUrZsyYgSlTpsDJyam5Rf9/o7kz3H8jtPQrrqmpqZSdnd3omrjg4GACQAMGDKBNmzaRTCZT+by0tJQSEhIoNTWVcnNzqbS0VOV+8rS0NJJIJASArKysaNasWRQVFaWyRiY5OZliY2MpPj6eHj58SI8fP6YnT55QWloaPX36VGVtp1gsJm9vb1q/fj2lpKQQEVFVVRXFxsZSQkICPX78mFJTUykzM5Nyc3OpoKCAZDIZOTg4CGl07dqVFi9eTDdu3BDuw8/NzaWcnJxG18atXbuWJBIJhYaG0qlTpxr83oMHDyg5OZkyMzOpoKCAKisrhfQVCoVwFVAsFlNAQADt2LFDpTwLCwspKyur0fvxDxw4QGKxmEJCQhrNQ2JiIj169IjS0tIoJyeHioqKVPJRf61u7969afny5RQfHy/ELyoqogcPHlBiYiI9fvyY0tLSVMoyNjZW5epU//796bPPPqO4uDiV/ZmYmEgpKSmUlZVFBQUFVFZWJmzXW2+9JcR3cXGhhQsX0rVr14Q8lpeX0/379ykuLo4SEhLo0aNHlJycTKmpqZSenk5JSUkqV6ednJxo3rx5dOrUKaEeZ2RkUFJSEj19+pQKCwupqqpKZc3F2rVrhfh9+vShlStX0uPHj4XPFQoFPXr0iAoKChos56qqKrK3tydDQ0OaOHEiRUdHq30vKyuLYmNjhe2oX7dTU1Np165dKmcFe/bsSR988AFdv35dSCs5OZny8vIarBMKhYLc3NxIJBJRQEAA/fzzz2prvQoKCoT2mZOTQyUlJSpt7+7du8Lv29jY0Ny5c+nMmTMq30lPT6f8/PxG16yEhoaSkZERTZ48mc6fP6/2vbKyMoqPj6cnT55QVlaW2v7IysoSrriYmprS+PHj6eDBgypr8VJTUyk+Pl6ok1lZWZSfn08lJSVUWVlJn332mbAdrVq1oqlTp9KRI0eENKqqqujevXt07949un//vhBiY2MpNjaW7t27p9JHGBgY0PDhw2njxo1CP5OdnU1JSUmUmZlJRUVFauu5du7cKcR3c3OjL774Qoir9OTJEyotLW2wHBUKBXXq1Inatm1Ln3zySYPrpPLy8ig+Pp6Sk5MpIyODcnNzqbi4WGjjV65cEfJgYmJCYWFh9Msvv6is61e2p6ysrAa3IyQkROin/Pz8aPv27Sr9VElJCSUmJgr1on7/QlS3Vld5l0GbNm3onXfeUelriUjoIxurU7NnzyZLS0t6/fXX6f79+2qfV1ZWCnUqOzubiouLVepscXGxcEXVzMyMJk6cSEeOHFFpH5mZmfTkyROSyWQNrs378ssvhasWYWFhdPjwYZXjpEKhoLi4OEpJSaGcnBy1Y59cLqfOnTsL+yIiIoIOHTqkkofs7GyhTsbGxtKDBw8oLi6O4uPjKSEhgX744QeVPqJNmzY0b948OnHihJCOsq9u6LhDROTv7y9cdfDx8aGtW7eqPCuiqKiIHj58SBkZGVRQUKBWFvfu3RN+v0OHDrRkyRK1NWzJyclCHhrqb2fPni2kMXjwYPrmm29U1hBWVlZSampqo1dD0tPThbWt33zzTYNrQZXHhsb6/Pp9hLJ9PnnyRPi8pqaG4uLi6PHjx/T06VOSyWQqx63q6mpydnYW2oa/vz99++23KmuPZTLZc8cR27ZtE64IXr58ucH6/+TJEyouLm7wM4VCQT169CCpVEpvvvkmxcbGqn1HJpNRXFwcPXr0SBgL5eXlUXFxMVVUVNDNmzeFcpBIJBQQEEBbt26lrKwsIY2mxoWjR48mAOTu7k5btmxR2x+lpaWUmJhIGRkZVFhYqFanUlJShHFE+/btafHixRQTE6PynczMTJLJZI32EfPnzydDQ0OaMmUKXbx4Ue17tbW1lJKS0midKioqIhMTE3J1daXNmzc3uH49JyeHnj592mgayj6ie/futGbNGpUyJKrbX/fv36f4+Hh69OgRPXnyhNLT0ykrK4vy8vKooKCAevfuLewPBwcHeuWVV1TGMvn5+ZSWlkZlZWUNlsXhw4eFcdD777+vMhZTSklJaXQcQUTk6elJYrGYRo0aRYcOHVLbX0VFRcI4Ii8vj8rKylTqeEJCgnBV2c7Ojl577TW6cOGCyneSk5Pp0aNHlJGRoda2iOqejaAsB1dXV1q+fDklJCQIn1dVVVFycjIVFRU1WA7Z2dlkYGBA5ubmNGvWrEbb1/8maHDF9V+fnD4vtPSJ6/MUFhbS4sWLG+wcm2vFihU0ffp0OnHihMYP8iGq6wBdXFwoNDSUdu/erTZxbo5t27aRm5sbLV++nB48eKBxfCKiX3/9tVkL/hsTFRUlHOjy8vK0SiM6OrrZi/4b8uDBA3Jzc6PPPvuMEhMTtUpjwYIFNGzYMFq/fr1WDxTKy8sTHu508+ZNrTqWtWvXUvfu3WnJkiUqk7zmqq6upsDAQPr0009VOkZN3L17lzZt2qTxQ0bq8/HxoaFDh9LatWvp0aNHGsdPTU2lFStWaPxgqfoWLFhAs2fPVjuZ1FxVVVW0efNmncph5cqVFBERQQcOHND4wTFEdSc6evXqRXPmzKFTp05p1c/s2bOHbG1tafr06XTgwAGNH5KhUCho/Pjx9Omnn2rdtrKysujo0aM6PUhi8uTJNHHiRDp48KDGD7cgIkpKSiJvb2/avHmzVg/CI6rr81977TW6ePGixm2TqK4s9+/f3+gEvzm2bdumU52Sy+U0e/Zs2rlzp0YPZKrv5MmTFBISQr/88ovW2zJ8+HDq27cvRUZG0u3btzXuL2NiYmjYsGG0adMmtUF1c3344Yf09ttv0/Xr17Xqr7Ozs8nT05O+/PJLrfuqGzdu0JUrV7QeiFZWVlJAQACtWLGCHj58qFUae/fupYCAANq+fbvWx/BTp05p9ZAtpaysLPrxxx+bfBjV80ybNo2Cg4Np165dWvXbhYWFtGTJkgYnSM21du1aWrBgAf35559a7VOFQkE//PCDVuNBpbi4OLp69apOk5svv/xS5aS7pk6dOkWdOnWiRYsW0ZUrV7TqLzdv3kzHjx/X6vhNVDcmW7lypcYPK6vvgw8+oDlz5tCZM2e0On7l5eWRh4cHffrppyoXUjQRFRVFu3bt0um4oStNJq78cKYWTKFQ6PSnbEpLS4XbdLSl/PMS/yZdy+GfUFNTo/WfqFDStSxramogkUi0fvw7AOTl5QkPYNIGEen0+/8EuVyOgoICnbbjn9AS6qWuf/KjqqoKEolEpzRSUlLQpk0brdNoCXUKqFsGoMufBfontqMllEVLqNe6loNcLkdmZibatGmjdRr/RDnouh0toT78E3nQ9c+XtRTl5eX/2p8LUWoJdaIlKCoqgoWFxX98WfwTfZ0ux++WQpOHM/HElTHGGGOMMcbY/zlNJq7/7mlVxhhjjDHGGGOsCTxxZYwxxhhjjDHWovHElTHGGGOMMcZYi8YTV8YYY4wxxhhjLRpPXBljjDHGGGOMtWg8cWWMMcYYY4wx1qLxxJUxxhhjjDHGWIvGE9cWqra2FuXl5f92NnRWU1ODlvy3gpvryZMnqKys/LezwQCUlJSgoqJCpzTS0tJQW1v7D+VIO7q2CyL6R9LQVVVVlc5p6CozM1Onbflv6KP+Kf8NZVFUVITCwsJ/Oxv/OiLSuZ/7b6gPwH/HdigUiv+K7SgqKkJ1dfW/mofS0lKUlJT8q3mora1FTU3Nv5qH/0TiyMhInRMRiUTDly1b9vuyZcveXLZsmUlkZOSlZz43XLZs2U/Lli1buWzZsknLli2LjoyMbPKosm3btsg5c+bonL9/w5ZMz8UAACAASURBVLlz57Bt2zYAgJOTEyQSiUbxRSIRgoKCsHbtWty+fRvZ2dmQSCSwtraGnl7zzjdkZGQgOjoabdq0gaGhocbbAACbN2/GnTt3YGVlBalUqnH8jIwMDBgwAOfOnUNqaioUCgVsbW2hr6/f7DQOHjyIixcvwtraGq1atdI4DzU1Nfj666+hr68PBwcHiEQijdM4e/Ys+vbti4MHD+LGjRtIT0+HXC6HtbV1s7aFiLB69WoUFBSgdevWMDAw0DgPsbGx+OWXXyCVSmFlZaXVdnz55Ze4f/++1vtTJpPhwIEDcHJygqmpqcbxgbq2kZubC0dHR622obKyEt27d8cPP/yAW7duISsrCyKRCDY2NhCLxc1K4+DBgxgyZAh+//13/PXXX8jJyYFEIoGVlVWz2ld1dTUmT56MO3fuoLa2Fvb29hq3saNHj2LatGmIi4tDaWkppFIpzM3NNUojNDQUe/bsQUpKCuRyOWxtbTWqW3fu3EFISAhiY2O1zsPrr7+OyMhIxMTEQCaTwcTERKP6mZ+fjyVLlqC6uhqOjo5a9VXbt2/HyJEjER0djfj4eBQVFcHU1BQWFhbNykdpaSl8fHzwxx9/ICsrC/r6+rC1tW12XwsAv//+O7766iuUl5fDzs5Oq/axb98+6Ovrw9raWuO4AHDv3j1s2LABYrEYTk5OzW4P9c2ePRs7duxAWloaAMDOzk6j41dGRgbee+89ncph586dOH36NIyMjGBvb6/RfgDqBoSurq7YsGEDLl++jOTkZFRVVUEqlcLIyKhZaZw7dw5nz56Fvb29xm0CqDvuTJ06FTdv3kRNTY1WfcTVq1exfv16KBQKODo6anXcCA8Px5YtW5CYmIiysjJIpVKN9klsbCxCQkIQFxeH8vJyWFtba7xPf/vtN6SmpqJNmzYaj4UAoKCgAG+++SaKiopgY2Oj1f5Yt24dFi9ejMTERFRWVsLGxgbGxsbNjq9QKLBx40aIxWKtxxG3b99GdHQ0HB0dtWoXRITg4GDs3btX6z4/LS0Nx48fR+vWrTXa/vq+/PJLXL58GcbGxrC3t9e4LPLz89GlSxfs378fd+7cQU5OjtDvNbetnzhxAjExMXBycmp2m66vtrYWL774IrZs2YJr164hPT0dCoWi2WM6ADh9+jT27dsnlIOm/RQRYdiwYfjuu+8QGxuLoqIimJmZwdLSstllev36daxYsQIVFRWws7ODiYmJRnkAgDVr1uDevXuQSqWQSqVa1W1dLVu2LDMyMnJbs76sPGuvbQAgBpAEoAMAAwB/Aej+zHdeBbDl7/fjAfzSnLTd3NzoP1V1dTV17tyZAJChoSF5e3vTihUr6M8//6Sampom4ysUCrp69SqJRCICIAQTExMaMmQIvfPOO/TLL79QcnIyKRSKBtOQy+Xk6upK+vr65OvrS1999RU9evRIo+24ceOG8NsdO3akuXPn0q+//kr5+fnNTuOTTz5R2QaxWEx9+/alV199lXbt2kUPHz5sdBuIiFJTU8nQ0JAAUOfOnem1116jI0eOUFFRUbPzsGjRIgJAtra2NHnyZNqzZw/l5OQ0K25ZWRk9evSI+vTpo7IdAEhPT4+6d+9OU6ZMoXXr1tH58+eptra2wXS2bdtGAEhfX588PT3ps88+o5s3b5JcLm9WPmpra6lHjx4EgFxcXOiVV16hQ4cOaVQO586dE/LeoUMHmjNnDu3bt4/y8vKanYa3tzeJRCJyd3enTz/9lG7fvv3c/fesu3fvEgCyt7enmTNn0sGDB6m4uLjZ8cvKymj16tVq+8LQ0JAGDBhAr732Gu3cuZPu37/f4L6oqqqilJQU6tq1q1oaxsbG5OHhQfPnz6edO3fSvXv3Gt0/u3btUqnT/fv3p4ULF9LRo0epoKCgye1QKBTk5eWl8vvt27enSZMm0aZNm+ju3buN1iWlu3fvkp6enko+3Nzc6PXXX6effvqJnjx50uS+mTZtmloeJk+eTJs3b6aYmJgm62dmZiaZm5urpGFlZUWBgYEUGRlJJ0+ebLK/mD17tpD/l156iT766CO6cOECVVVVPTceEVFNTQ2lpaWRs7Oz2v60tbWlwMBAWrp0KR05coQyMjIaTWf37t0qcc3MzMjX15c++ugjOnnyJBUWFj43H1VVVdSpUychfo8ePWj+/Pl04MCBZrevTZs2EQDq1KkTvfnmmxQdHd2sMlBSKBQ0YMAA4VgRGBhIa9eupb/++qvZbfTRo0dkYGAgbIeBgQF5eHjQwoUL6dChQ5Sdnd1kGpMmTRLiu7q60ltvvUVHjx5tdl+VkpIi9PlSqZRCQkJo48aNFB8f3+R2KBQKkslktGbNGrX6oDyOhYeH06pVqyg6OrrR/VpQUECtWrUiANSzZ09auHAhRUVFUWVlZbO2gYjol19+UTlWuLm50dtvv01HjhwhmUzWZPza2lpydXUVjhtDhgyhyMhIunjxIlVXVzcrD/Hx8SSRSFTKoEOHDjRp0iT65ptv6MaNG02mNWvWLJX4Xbp0oZkzZ9J3331HiYmJTe6TmzdvCnVy1KhRtGnTJkpOTm5W/pUWLFgg/P4LL7xAr776Kh04cKBZ5UhEVFFRQe3bt1fZjhdeeIFmzpxJO3bsoLi4uCa3Y9myZQSA7OzsaMqUKfTTTz9pdOwsLy8nJycnAkBubm704Ycf0uXLl5vs5+u7ceOGyrhQOZ6aP38+/fjjj88dExLVjQt79+5Nenp6NHjwYPr8888pJiZGo2P47du3hTxYW1vTuHHjaPPmzc2qC0R1x/DFixertU0TExMaPHgwvfXWW/Tjjz8+N73Hjx+Tvr4+icViGjJkCK1YsYJu3brV7PFUSUkJbdiwQS0PYrGYXF1daebMmbRp0ya6fv16o22+tLSUHBwchH4qNDSUtmzZotE4u/6YTBns7e1p9OjRtGLFCoqOjn5uv6lQKGjgwIEq/e2CBQvo8OHDzRqHPJsHFxcXmjVrFv3888/NHiP/EwDcpGbOO0Wk420HIpHIA0AkEQX8/e/FAEBEn9f7zqm/v3NVJBJJAGQBsKUmfrxfv3508+ZNnfL3v2nXrl3IyclBRUVFg+Hu3bt4+PChWjxLS0t4enrC1dUVpaWlICLk5eUhJycHubm5wmtTtxDo6+tj4MCBGDx4MNq2bdvgDr5w4QIOHjyoEu+FF17AyJEjERQUhBdeeAH79+9HVVUVKisrUVlZKbxXvh45cgTFxcUqaejp6cHNzQ1+fn6wsLBAWVkZioqKIJPJkJeXp/La1O0YYrEY7u7uCAgIgL6+PqqqqlBdXa3y+vvvvyMjI0MlnkQigbu7O/z9/eHs7IyioiIoFArU1taqhezsbGzfvl0lvkgkgpubGwIDAzF8+HBcvnwZWVlZyMzMVAnPbntDzMzMMGrUKDg7O8PW1hbV1dVqoby8XC0PAGBjYwM/Pz/4+/ujpqYG5eXlqKmpaTBcu3YNly9fVisHDw8PDB8+HG5ubkhISBD2ZUPh8OHDarfaikQi9O3bF76+vrCysoKBgQH09fWhUCiE25OU7+/cuYOffvpJJb6TkxNGjBiBkSNHYtCgQThw4EBjJ7pARFi7di1SU1OF+Pr6+hg2bBiCgoIQFBSElJQUnD9/HtnZ2WqhtLS0yf3h7OyM7t27w8XFBSUlJcJ+zcrKQn5+fpPxjYyMEBAQAGdnZ1haWgq3FZWUlKC4uFh4vXfvXoPxRSIRevfuDWtra3Tr1g16enooKChAfn4+CgoKhCCTyZ7bzs3NzTF48GD06NEDRUVFyM/PF4IyvabKo2PHjvD19YWpqSkKCgpQWFio8pqXl4eysrLn5qFPnz7o27cviouLkZeXpxIKCgqavH2tQ4cO8PPzg4uLCyorK1FRUaFSJ9PS0nD27Fm1eKampvD09MTQoUORnZ0NkUiEnJwcZGVlITs7G1lZWcjLy2vy9/X19eHp6QkXFxdYWloK2/7sPnleX6Xcp35+fjA0NERZWRlKS0tRVlYmhLi4OLV+SsnV1RV9+/aFoaEhevToAT09PbX2UVVVhSVLlkAul6uUv7+/P4KCghAYGIhLly4hJSVFpc+u33ffu3cPt2/fVvt9e3t7+Pj4oF+/fpDJZFAoFCrl8Gy9fF6ZduzYEf7+/nByckJ5eTkqKipUXlNTU3Hjxg21eGKxGP3798eQIUNQUVEBBwcH1NbWqhw3lfXj/PnzyM3NVUujdevW8PHxQevWrYXfy8rKEtp4dnZ2s25D7N27N3r16oWePXtCLBY32N+eOHECcXFxKvFMTEwwbNgwBAQEoGPHjnjw4AFKS0tV+gVlX1FUVIT79+83+PsikQi9evWCg4MDXF1dYWFhIZSBsiwrKipw//59xMfHq8U3NTXF0KFD0adPH5SVlUFfXx/5+fmQyWQqIT8/v8nbhTt06ABfX19YWFigsLBQLeTm5qKoqKjR+DY2NnB1dcXw4cOhr68PuVyuFjZv3ozs7GyVeN26dcOIESMQGBgIkUiEu3fvNliflPv42WOfshxffPFFeHl5oaSkBFKpFGVlZSptu/6rQqF47nYEBgaib9++KmMJuVyO2tpaFBQU4JtvvlGJo6enhwEDBiAwMBCBgYGIj49HYWGhSrz6ISoqCtevX1dJQyqVws/PD4GBgejSpQsuXryo0tc/G5paRta1a1eMGTMGbdq0UTl2K4/lFy9exG+//aYSx9nZWTiGu7q64vDhwyr18Nm6GR0d3eCxp23btvD29oaNjQ3kcjnKy8uRk5Ojcgx/3vFGqWPHjujVqxcGDBgAQ0NDofxqamqE98orz/XZ29sjICAAgYGBMDc3x40bN4TfVR43mpsHFxcX9O3bF7169RLGps/2uVevXsWjR4/U4rZv3x6+vr7o0qULCgsLUV5ejry8POTm5qq8NpUPPT099O7dG8OGDRPG2uXl5SqviYmJDeZBT08Pffr0wYABA6BQKNC2bVvI5XKV/Cv73MOHDze4HO7FF1+Er68vfH19MWTIEK2u6DaHSCS6RUT9mvXl5s5wGwsAxgHYXu/fUwBseOY79wG0qffvJAA2TaXd0q+4Kq+oahMsLS3Jx8dHq7hdu3alL774grKzsykgIEDrPODvqwq6xLeysqIuXbpoFbd79+60du1aSklJ0SkPEolEp32Bv8+yKc/wNxaMjY3V/s/V1ZU2b95MxcXFKmfXtd0XNjY2OqVha2urU/zWrVs3eCVSk6Cvr69TfABalYNYLKaQkBA6ceIE1dTUkJGRUZP15tn/69atG3399deUn58vXCHXJri4uNAHH3xAHTt21Cp+p06daPny5bRnzx6t4hsYGFB4eDgdP36cAgMDtUrD2tqa3njjDTp8+LBW8S0sLGju3Ll0/fp1mj9/vk71of4Z5cbCs3enAHVX11atWkXZ2dmNXoFrKpiamtL06dPp3Llz1LZtW623wdXVlaZMmaJTOYhEIuEqoDZBLBYLV2S1Cd7e3rRr1y6VK6qaBmNjYwoODtapHFq3bt1knRCLxWr/Z2RkRNOnT6c///yTFAoFSaVSnfJhb2+vddx27drRkiVLqFu3blqnYWFhQf7+/lrFNTc3p9mzZ9PVq1cpJCRE6zRefvll2r9/v07lCECnem1gYEDBwcEqd59oEvr3708bN25s8E4eTYOpqem/Et/IyIgmTpxIUVFR5Ofnp1Me6t9xoU3o1q1bg3eoNRX09fUpIiKCzpw5Q2VlZTrvCysrK43jKMcRJ0+eJLlcrlMbNzIyon79+mkVt127dvTJJ59Qampqs45/jYXWrVvThAkTdCrHtm3b0jvvvEO3b9/+X5tPQYMrrpovNlDX0M3QpMV36r4oEs0BMAeoOwPUknl7e6Nbt24wNjZuMFy4cAGnT58Wvm9ubo7g4GBERETAz88PSUlJWLp0Kezs7GBrawtbW1vhvZ2dHaRSKfr164esrCwYGRkhLCwMs2fPxuDBg4V70Pv06YPa2lqIRKIGQ2ZmJu7evauSb5FIBHd3d4waNQru7u5YtWoVjIyMYGho2ODrjh07kJmZKcS3trZGSEgIwsLC4OXlhV27duH06dOwtraGjY2N2mtycjLCw8OFMhg/fjxefvllDBgwACKRCAqFQriKYWBgILzWf3/s2DEkJiYKedDX14e/vz/GjRuH0aNH48yZM9i+fTskEgn09fUhkUhUQnV1Nfbu3atSDsbGxggICEBISAiCgoLw0UcfobKyEk5OTnB0dFQJDg4OWLp0KVavXg1DQ0OEhYVh3rx58PDwEPaFk5MTAgIChLw/GyQSCTZs2KByNaVVq1YYPXo0QkND4e/vjw8++AAPHjyAvr6+cNWzfoiPj8f58+dVtqNjx44IDQ1FaGgopFIp3njjDRgZGakE5b40MjLChg0bIJPJhPhOTk4ICwtDWFgYPDw8sHr1apw5cwZ6enrQ09ODSCRSeZ+bm4urV6+q5EFPTw+DBg3C6NGj4e3tjXfffVeoa8ryqV8vb968iby8PJU0TE1NERAQgNGjR0MulyMqKgr29vaws7ODvb29SigsLETv3r0BAO3atcPs2bMxc+ZMODo6CulNmDBBWI/k4OAg7EcHBwfY29tj0aJF2Lx5M/T19REaGop58+ZhyJAhQn47deqEUaNGwdzcHBYWFjA3NxeChYUFxGIxXn75ZWF/WllZISIiApMmTcJLL70EkUiEiooKPH36VFiXrFxDonx/8OBBrF+/XmgbERERmD59uhA/ISEBwcHBsLKyUgtSqRStWrVCUFAQcnJyAABubm6YMWMGJkyYACsrKwBATEwMzMzMhO8r86B8f+PGDXz44YcA6q7eBwUFYdq0aRgxYgQMDAxQXFyM0aNHw8bGptEwadIk4Qrb0KFD8fLLL2PcuHHC2dm7d+9i5MiRavVSGXJzc4VnAii5u7sjPDwc48aNQ9u2bTFhwgSYmZnB3t5e2If138+fPx979uyBRCJBSEgI5s6dCy8vL2HdUffu3RESEtLgfpBKpVAoFBgxYoRwpdHT0xMzZsxAaGgozMzMAAABAQGQyWQwNTWFqakpzMzMhPempqY4fvw4jh8/LmxDhw4dMHHiREyYMAHdu3fHlStX8PTp00b7a5FIhFOnTqn0EUDdVcZRo0Zh9OjR+OOPPxAfH99g2zYyMsK9e/dUrqaIxWJ4eXkhLCwMISEhqKmpwdy5c4XtfjZYWVlh2rRpSEpKEvqX6dOnY8qUKWjXrh2AujWHRUVFMDExgbGxsdprWloatmzZIuTBwMAAgYGBiIiIwKhRo2BgYIDRo0fD2NgYRkZGDR4/9+zZo3K108HBAWFhYYiIiICHhweOHTuGn3/+WWjTz7bx4uJidOrUCUDdXUavvPIKpk6dqrK239fXF6WlpWr9rDJcvXoVMTExKvuid+/eGDt2LEJDQyGTybBmzRq1PkL53sDAADNnzhTuqpBKpQgPD8fkyZPx0ksvQU9PD2VlZejcuXOj44hr167h6NGjwu+bmppi9OjRiIiIQEBAAJ4+fYq3334b1tbWDQYrKyuMGDFCWLM8dOhQzJw5E+PGjRPWWb700ksQi8Vo1aqVSlD2E3fv3sUHH3wAoK6v9/Pzw9SpUzFmzBiYmJhAJpPB19cXYrG4waCnp4ezZ8+qXXHt1KkTQkJCMGbMGMTHx+PQoUNCPXq2TuXn52Pt2rVCXIlEAn9/f0RERCA4OBiWlpaIiIiAvr6+Stuu/7p69Wqhbdjb22PKlCmYPn06evToAQA4duwY/Pz8hHGDWCxWeVUoFGrjCIlEAi8vL4wZMwbBwcH46KOPkJGRoZaG8v29e/fUxmSOjo4YM2YMQkJCYGNjg2XLlqn09cr9aGVlBQsLCwwfPly4c8jd3R0zZsxAeHi48AyQM2fOAIDKsbv+sTw9PR23bt1S245hw4YhODgYAwcOxEcffSTUQeU+qB+++eYblbtLOnXqhIiICERERKBnz574/vvvER0d3eAx3M7ODklJSfDy8gIAdO7cGXPmzMG0adNga2sLoG4Nav190VA4e/Ysnjx5orIdPXv2REhICMaOHYuMjAzs3r1b5XhR/7hRXV2Nzp07Q6FQwNnZWRhHODk5qfQRxcXFjY6n/vjjD1y5ckX4vpGREQIDAxEeHo6RI0ciPj4eq1atUjle2traCu/NzMwwYMAAFBcXw8DAACEhIZg1axa8vb2FY9fQoUPh4OAAU1NTmJiYqL1eu3YNv/zyi5AHGxsbhIWFYfz48Rg8eDCSk5NRUFCgsg3KvlcZ1q9frzIubNOmDcLCwhAeHo4BAwZovH73f1VzZ7iNBQAeAE7V+/diAIuf+c4pAB5/v5cAyAPqblN+XmjpV1yfRy6XU9euXcnU1JTGjx9Phw4dooqKCo3SOHz4MPXu3Zs2bNig0ZrS+saNG0fA/5zl3rFjB2VlZTU7flxcHIlEIrK2tqZZs2bR6dOnm722RmnmzJk0dOhQ+v7776m0tFTTTaD8/HwyMzMjQ0NDCg4Opt27dze53uxZ69atI6DuSvfkyZPpwIEDGuWlurqaBg0aRKtXr6bc3FxNN4GIiA4ePEhA3dXEWbNm0cmTJzVav0ZE5OnpSQCoV69e9PHHH2u0do3of9YsOzo60htvvEEXL15s9poQpTlz5hBQtx4lJCSEdu7cqdFaiNzcXOGscps2bWjevHl04sQJjdrH4sWLVc6Kaqq8vJz69u1LK1eubNaavYZs2bKFjIyMKDw8nH777TeN96VCoaBu3bqRr68v7dmzh8rKyjTOw4kTJ8jOzo7efvttiomJ0Tg+EdHw4cOpb9++9PXXX2u1puXBgwfk6OhI77//PiUmJmqVB+X6tYEDBwp3YWiioKCAevToQZ9//rlG/Vt9q1atIhcXF/r4448pKSlJ4/g1NTXk4uJCjo6O9Oabb9K1a9c0aptERNHR0cJZ7j59+tDHH39Mt27d0igdLy8vEovF5OvrS1u3btV4n16/fp3Mzc1p1qxZdOnSJY23gYho+vTpJJFIKDAwkL7//nuN++usrCwyNDQkW1tbmjdvHp07d06jdYBEdc9WmDBhAp0/f16rbaiqqhKusLu7u9MXX3yh8TMivvvuOzI0NKSwsDA6fPiwVn1E3759ydjYmMLCwujXX3/VuJ84c+YMOTk50ZIlS7Run6NHj6bu3bvTqlWrKD09XeP4GRkZwh1N/fv3pxUrVlBsbKxG+2XhwoWkp6dHPj4+9O2332q0tpSIqKioSFiPeezYsWY9a+RZ3333nXDsGzt2LO3evVujsZlCoRDWLHfp0oXee+89+vPPPzU6hh06dIgcHBzo3XffpQcPHmi8DUREY8eOJaDuiv348ePpp59+avZ6SCKi2NhY4argu+++q3EfRUQ0d+5cGj9+PP3xxx9atc+CggKysLAQ2ueqVas0rt8rVqyg4OBgOn78uMb9C1HduNDZ2ZmMjIwoJCSEfvrpJ42e10FU96yMnj170ldffaVxnSb6nzWuFhYWNH36dDp58qTGdfv69evC1dk333yTLl++rNW4ShfQ4IrrPzFxlQB4DKA9/ufhTD2e+c5rUH04077mpP2fPHFNTU2lffv2aTUYVcrPz9eqQSs9ffqU5s6dS0ePHqXy8nKt0jh58qRWk9X60tLStI5LRHTp0iXau3evxh2CkkKhoOXLl9OpU6c0Hjgo1dTU6NyQd+zYQWfOnNHqgElUd/BfuXIlJSQkaJ2H33//XavJqlJRURG99tprdOzYMa3r1N69eykyMlLjhzrVV1JSolU8paqqKp3354ULFzR6MNazSktLNZ6gPevx48c6tc3a2lq6f/++TnnIzc3Vuk4T1Z3k27JlCz158kTrNCoqKnTen/Hx8TqlkZ6eTmfOnNFqAKS0fPly2rhxo9b1QiaTaTVZre/x48c6Hbdqamrohx9+0GoQpnTt2jWKjo7WqV5peqL4Wbdu3aINGzZoNVFTunTpksaT9vqysrJo7969OvV36enpOtVJuVxOd+7c0Wks8uuvv9KGDRsoNTVVq/gKhYJ2796t9UkpIqKcnByd6iQR0WeffUZHjhzR+tj34MEDWr58ucaT9voeP36sU7t4+vQpvf7663T69Gmtx0Nnz54VbrfXlrbjOaWoqCjauHGjTu1Tmwsp9cXHx2s1Wa0vOztbp3LMz8/X6sJYfb///jtdunTp/3yyWp8mE1edH84EACKRaASAr1D3hOHviGiFSCT65O+M/CYSiYwA7AbQB0A+gPFE9LipdFv6w5kYY4wxxhhjjGlHk4cz/RNrXEFExwEcf+b/Pqr3vhJA2D/xW4wxxhhjjDHG/v/SglbbMsYYY4wxxhhj6njiyhhjjDHGGGOsReOJK2OMMcYYY4yxFo0nrowxxhhjjDHGWjSeuDLGGGOMMcYYa9F44soYY4wxxhhjrEXjiStjjDHGGGOMsRaNJ66MMcYYY4wxxlo0nrgyxhhjjDHGGGvReOLKGGOMMcYYY6xF44krY4wxxhhjjLEWjSeujDHGGGOMMcZaNJ64MsYYY4wxxhhr0XjiyhhjjDHGGGOsReOJK2OMMcYYY4yxFo0nrowxxhhjjDHGWjSeuDLGGGOMMcYYa9F44soYY4wxxhhjrEXjiStjjDHGGGOMsRaNJ66MMcYYY4wxxlo0nrgyxhhjjDHGGGvReOLKGGOMMcYYY6xF44krY4wxxhhjjLEWjSeujDHGGGOMMcZaNJ64MsYYY4wxxhhr0XjiyhhjjDHGGGOsReOJK2OMMcYYY4yxFo0nrowxxhhjjDHGWjSeuDLGGGOMMcYYa9F44soYY4wxxhhjrEXjiStjjDHGGGOMsRaNJ66MMcYYY4wxxlo0iS6RRSLRFwBGAagGkARgBhEVNvC9JwBKAMgB1BJRP11+lzHGGGOMMcbY/z90veIaBaAnEbkCSASw+Dnf9SKiF3nSyhhjjDHGGGNMEzpNXInoNBHV/v3P/RJihAAABWZJREFUPwG00T1LjDHGGGOMMcbY//gn17jOBHCikc8IwGmRSHRLJBLN+Qd/kzHGGGOMMcbYf7km17iKRKJoAA4NfPQBER35+zsfAKgF8GMjyQwioqcikcgOQJRIJIonoguN/N4cAHMAwNnZuRmbwBhjjDHGGGPsv1mTE1ci8n3e5yKRaBqAIAA+RESNpPH079cckUh0CMAAAA1OXP9fe3cTold5hnH8f5EYLGlAEz+wxqqlWZhFTSGEgC5sKCGmIXFRQbHgQuimC4WKWjelgotuWhcKElTqQltFGxUVMdiU6sbUj4gpaWkUayXitKhYKURs7y7OM3QYJiIzZs6D5/+D4T3PM4d578XFPO99vt6q2gvsBdi8efOCf0+SJEmSNB1LulQ4yQ7gZmB3Vf37BPusTrJmdhvYDhxeyvtKkiRJkqZjqfe43gmsYbj891CSuwGSfC3J022fs4EXkrwGHASeqqpnlvi+kiRJkqSJWNL3uFbVN08wfwzY2bbfBC5eyvtIkiRJkqbri3yqsCRJkiRJX7ic4HlKXUjyD+BvY9fxGc4A/jl2EdI85lK9MZPqkblUj8ylenOyM3l+VZ35eXbsunHtXZKXqmrz2HVIc5lL9cZMqkfmUj0yl+pNT5n0UmFJkiRJUtdsXCVJkiRJXbNxXZq9YxcgLcBcqjdmUj0yl+qRuVRvusmk97hKkiRJkrrmGVdJkiRJUtdsXBcpyY4kf0lyNMktY9ejaUpyX5KZJIfnzK1Nsj/JX9vr6WPWqGlJcl6SA0mOJPlTkuvbvLnUaJKcmuRgktdaLn/W5i9M8mLL5UNJVo1dq6YlyYokryZ5so3NpEaV5K0kryc5lOSlNtfFGm7jughJVgB3AZcDG4Grk2wctypN1K+AHfPmbgGeq6oNwHNtLC2XT4EfV9VFwFbgR+3/o7nUmI4D26rqYmATsCPJVuDnwC9bLj8ArhuxRk3T9cCROWMzqR58p6o2zfkanC7WcBvXxdkCHK2qN6vqE+A3wJ6Ra9IEVdUfgPfnTe8B7m/b9wNXLGtRmrSqereqXmnb/2L4QHYu5lIjqsHHbXhK+ylgG/BImzeXWlZJ1gPfA+5p42Am1acu1nAb18U5F/j7nPE7bU7qwdlV9S4MTQRw1sj1aKKSXAB8G3gRc6mRtUsyDwEzwH7gDeDDqvq07eJaruV2B3AT8N82XoeZ1PgKeDbJy0l+2Oa6WMNXjvGmXwJZYM7HM0tSk+SrwKPADVX10XAiQRpPVf0H2JTkNGAfcNFCuy1vVZqqJLuAmap6Oclls9ML7GomtdwuqapjSc4C9if589gFzfKM6+K8A5w3Z7weODZSLdJ87yU5B6C9zoxcjyYmySkMTesDVfXbNm0u1YWq+hD4PcM92KclmT2I71qu5XQJsDvJWwy3nG1jOANrJjWqqjrWXmcYDvJtoZM13MZ1cf4IbGhPflsFXAU8MXJN0qwngGvb9rXA4yPWoolp92jdCxypql/M+ZW51GiSnNnOtJLkK8B3Ge6/PgB8v+1mLrVsquonVbW+qi5g+Bz5u6q6BjOpESVZnWTN7DawHThMJ2t4qrwCYTGS7GQ4MrYCuK+qbh+5JE1Qkl8DlwFnAO8BPwUeAx4Gvg68DVxZVfMf4CSdFEkuBZ4HXuf/923dynCfq7nUKJJ8i+GBIisYDto/XFW3JfkGw9mutcCrwA+q6vh4lWqK2qXCN1bVLjOpMbX87WvDlcCDVXV7knV0sIbbuEqSJEmSuualwpIkSZKkrtm4SpIkSZK6ZuMqSZIkSeqajaskSZIkqWs2rpIkSZKkrtm4SpIkSZK6ZuMqSZIkSeqajaskSZIkqWv/A50llgpfaDanAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "width, height = 200, 60\n",
+    "velocity_magnitude = 0.05\n",
+    "init_vel = np.zeros((width,height,2))\n",
+    "# fluid moving to the right everywhere...\n",
+    "init_vel[:, :, 0] = velocity_magnitude  \n",
+    " # ...except at a stripe in the middle, where it moves left\n",
+    "init_vel[:, height//3 : height//3*2, 0] = -velocity_magnitude\n",
+    "# small random y velocity component\n",
+    "init_vel[:, :, 1] = 0.1 * velocity_magnitude * np.random.rand(width,height)\n",
+    "\n",
+    "plt.vector_field(init_vel, step=4);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "With this initial velocity field we create a simulation scenario:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "shear_flow_scenario = create_fully_periodic_flow(initial_velocity=init_vel, relaxation_rate=1.97)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.quiver.Quiver at 0x7f49b5074630>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "shear_flow_scenario.run(500)\n",
+    "plt.vector_field(shear_flow_scenario.velocity[:, :])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Instead of plotting a single point in time we create an animation. For this we first have to \n",
+    "define an update function that runs a few time steps and returns the field to plot.\n",
+    "This function is called ``iterations`` times, then the animation stops. \n",
+    "To cancel the animation while it is running, hit the stop button in the IPython menu bar."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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0aBFWrFiB7du3IygoSHQ/MzMzMW3aNNjZ2aF27dqoU6eOyMmQnJyMAQMGCC8Aw7DZxMREfP/998Ji/eLFC5E8OzsbI0eOBGMMHTp0kFwfx3EYPnw4GGNwdnaWlXfq1El44cjJ+ReflZWV5EWv0+lQunRpYYE3HCs6nU6k7MntQup7Nbt06SJ5ljVr1hReGNWqVZM4WXiDmDGGcuXKScKW9u/fL8hLlSolO194T27VqlVllbGwsDAwxtC0aVNFJ01gYCAqVKhg1NC6fv06fvrpJ0U5x3HIyMhAXFycrFeW4ziJomlIcHCw7JrDo1arMWnSJKNK3axZs3D//n1Fub+/P37++WdF+evXrzF16lSj9+LHH39Ebm6uotzb29uoYurv72/0BX3t2jWja+fr16+Nrn25ublGHRAACpQrOTh4QkJCjD7L3377zeg9unTpEj5//qwoP3v2LC5evKg4Zo8dO4YFCxYgKCgIz58/l3xu//796NixI+zs7NCjRw/069cPv/zyi3DNfn5+IkPM0tJSFKVx7NgxIVSPl+vfs0ePHomMUcYYdu/eLchTUlKE9Y8/7O3thXWI4zh4enqK5CYmJvjtt99E12CoiLZv3164r69fvxbtFPEH79xKS0vD9OnTJfKWLVsiNTUVOp0OO3fulOwWMZYfFcJxHG7evImOHTvKKsXz58/H27dv4ebmpqg4f/PNN1i6dClMTEyMKtiGhkTFihXh5OSE/fv348mTJxg6dKjoHgQEBAjvtezsbBw+fBiMMZQoUQI+Pj6SNSI1NRXm5uaoVq2abAqHRqOBnZ0d6tevr6j3zJkzB82bN1dUvv39/dG2bVtZ5yWQv4Z27txZ0eh9/vw5+vbtq7jZ8OzZM4wdO1Zx/QsLC8PUqVMVzx8aGgonJydcunRJ1vC9cOECWrdujZEjR8Lb21vQCfjzBQUFSZ5ju3bthPfS6dOnRXPGxMQE/v7+wvffunULVatWFcnPnTsnyF+9eiVEDfHHpk2bBHlaWhoGDRokkvfs2VOY0xzHwdvbWyQ3DNW9fPmy5Df4+PgI8tjYWEnEQd26dQVHRG5uLn744QfJ+NW/zs2bN0vkpUuXFvSnR48eye7AVq1aFU+ePEFiYiJmz54tO09UKhU8PDxw/PhxtG/f3uicqlWrlsSpVa5cOYwYMQJbt27FnTt3EBISIsg6dOiAoKAg5OXlgeM44R01ZswYWFpaYunSpaLQff49HxUVhdKlS+PEiROi8aS//nfo0AHXr1+XHZeFCRmkf4IzZ86gXr168Pf3h5ubG0xNTbF//35B/v79e9SsWRM7d+7EwIEDYWlpKdq1UqvVaNWqFXx9fWFtbY0yZcogIiJCdI7hw4cLL9Lq1auLQikAYPXq1YLXtUGDBpLF7+rVq7CzswNjDI0bN0ZKSopI/uHDB/Tr1w+mpqZo1KiRRJ6bm4thw4ahQoUKqFu3rqyS7e7ujoYNG6Jq1aqS6wMgeNrKli0ruxN8+fJldOrUCVZWVrLK65s3b2Bvbw9zc3PZna2cnBwMGTIEKpUKO3fulMgBCMqGu7u7bLjQzz//DBMTE/Tu3Vt2d/DMmTOwsrJCvXr1cPr0aYny9+jRI5QpUwZFihSBk5MTbt++LfpMUlKSsLBaWFiga9euIoWK4zg0atQIjOXnI82ZM0fyouzVqxcYY2jTpo2s8jhlyhQwxjBkyBBZ5XTdunUwNTWFq6urRKbRaLBv3z5YW1tj1apVEnlGRgZ++eUXNGrUCHPmzJHIExMTsX37djRr1gzDhg2TyD98+CDsUkyfPl3i3IiJicHixYvRsGFDLF++HGfOnBHJ379/j6FDh8LW1hbLli3D2bNnRfK8vDzY2Njg22+/hZubGyIjIyWKQosWLdCpUyf07NkTWVlZEiNlzJgxaNeuHZo0aYL09HSJ4+DixYto0aIFKleujBcvXsgael26dEGjRo1w8OBBxMXFSeTXrl1DmzZt4Obmhrdv30rkQP58+e677xSNILVajV69eiEoKEhWDgABAQHCeJdzovDj0cbGBqtXr5YdTwMHDoSZmRk8PDxkDbpVq1bBwsICNjY2ePbsmUR+6NAh1K1bFxYWFqJ1kefx48do06YNGMvPFzI0OtPT0wUPuJOTk0Rp4zgOM2bMgIWFBfr06SNrcG3YsAE1a9bEd999J6s4nj59Gm3atEGrVq1kd1siIiJgb2+PevXqyRqt6enpGDFiBCpVqiT7vDiOw/z581G8eHGEhYVJ5EC+MVaiRAnFXfcLFy6gatWqsvMSyL+PDRo0wIgRI2R/Y1JSEpo3bw4bGxtF54CdnR2KFi2KGTNmyI6F8ePHg7H8MDgXFxdcunRJZHT6+vqKFK2+ffuKHDa8gcIbN0FBQaI16s6dO4JBWq1aNYSHh4vOHxsbKxhJlpaWIkMRyI/Q0Q8LNAyr1+l0ImOxVq1aknfluHHjRL/B19dXJN+2bZtIXqlSJXz69EmQ37t3T6Jcr1ixQpAnJyejXLlyInn9+vVF75suXbpIFFlvb2/hXvFpA/qHtbW14Ay/dOmSrDJcokQJ/Pzzz0hPTzeqNH/zzTeoV6+e0c8oHWXLloWnp6fkPvHK/Z49e6DVahEfHw8LCwvRvZo0aZKwnnIch6ZNmwq7b1ZWVpIUkrFjxwoRL7zhoM/WrVvRpEkTQe8xNFpv3bqFVq1agTGGVq1aSRzJiYmJ6Ny5s3BPDOe+TqcTUkiaNWsmcfAC+btdvPGzadMmiZNm7dq1ojkxc+ZMUe5vYGCgyElTunRpLFiwQBgvoaGhwj00NTWFt7e3aI18/fq18Lfm5uY4duyY6PypqakoVaqU8JnNmzeL5BqNRrQzOGDAAIleMXjwYNH16c8HABKDdPv27SL5mTNnRPJ27dqJfsOrV69QokQJ0e/QX0dzc3Mlu5fjxo0TXefYsWNF8uLFiwv53gCwZ88eyXjVd3S8evVKdrzXqVNHMOqqVaumOC9atGiB77777g/NKX58z5o1C4wxNGzYUJRuUKtWLRw/fhwajQaVK1dGp06dsG7dOkHOR28A+Q73Ll264OTJk2jZsiXMzc2xb98+/J1gZJD+cfQHGb8wqFQqYdLxBoL+YWVlJYTX7ty5UyKvVq0a3r9/DwC4e/eu7EThFafU1FSRB4wxhu+++05QzDiOw7fffiuS//DDD6KF0d3d3aj8+PHjInnnzp1Fit/bt29FO1O2trYiRV2j0QgvBsbyvVuGi7uLi4sgL1eunGRx118wLCwsJDupz549Q5EiRYTPrF69WiTPyckRdscYY+jdu7dE+Rw2bJggr1ChAs6fPy+S79ixQ3Qf7O3tRTuUkZGRQg5DvXr14OjoiEuXLomuoXnz5mjZsiXWrFkjG3Ixd+5cDBkyRNEQefLkCQYOHKjokU1OToaHh4dinoJWq0VQUJDRnZDExERFQwnIH1NKHl+egsKz/wgFhW7m5eUhLS3N6GdevXpldKft6dOnRs/z8eNHpKamGs1/iouLK/A6/wo4jlMsvgTkv6jlnDc8KSkpqFOnDvr3749Vq1bh7t27ouvWarWi0L8qVarg0KFDos/oh0sVLVpUCNXiMVxbPD09Rfful19+EclHjhwpWltu3LghygtycHAQ/eZPnz6JdpN69+4tkmu1WjRt2lSQd+/eXWK08lEBjOXvqhsWi9FXGlu3bi0xzH/77TdBLme0xsXFCetjuXLlJI4YjuPQuHFjQdkyXHcA8fr4008/ScbX3r17BXnLli3x7t07kfzly5fCfTQxMcGcOXNE90mn04nCWWvXri151rNmzYKZmRk6d+4Mb29v3L59WzSWQ0JCYGlpCVdXV4lTFQA+f/6MFi1awNXVVTb9Q6vVws3NDe3bt5d1COqf4+rVq7Ly27dvo2/fvhg+fLjsPI+OjsaKFStgaWkpu6Odnp6O3bt3o2TJknBwcJDcZz6loU+fPjAzM5NNk9m6dStOnDgBxhhGjx4t+Y7Dhw/j8OHDggPX8FnduHEDixcvFnZ9NmzYIJK/efMGI0aMEOSNGzcWvS+zs7PRtWtX0c6Wo6OjyFD47rvvUKlSJcl7Pzg4GBzHoW/fvrCwsJDoHubm5ujVq9efUq6bNm2KOXPmyMrq1KmD0NBQPHz4UFY+Z84caDQapKenS/Qea2trUQSaod5To0YNREdHC3LDHa9GjRqJjNZz586Jwknr1q0rcrDExcUJKSKM5Rs5hw8fFj2rvn37is7RuHFjXLx4UZD7+fkJsooVK8LR0RGbN28W1pAXL16gatWqqFGjBjZu3Ch5r2dnZ2PEiBGoV6+ebHQdkB/WXLRoUdF59bl16xa6deuG6dOny8qjoqLg4+ODmjVrys7b9PR0nD59Gubm5kIutj46nQ4HDhxA9+7dYW9vL/tuDAwMhKenJ4oVKya7YXH+/HmsXr0ajDGsW7dOIg8PD8eaNWvAWL5Ba7jGf/78GbNnz0aFChVQtGhRXLt2TSTPzc2Fs7OzEJ78ww8/SPTDESNGCBs7jIkdKED+Gm3oTLK1tcXJkyeh0+kwc+ZMVKtWTTak38LCQngH/NHDMLTacNxdvXpVMSpCzhlcWDAySP84iYmJ+Omnn2RzS1avXo2MjAwsWbJEMgitra1x9+5daDQazJs3T/K3DRs2REJCAtLS0mRDgLp16wa1Wo3Y2FjZnBQnJydwHIdPnz6JwhD1JxPHcUhISMCPP/6oKE9NTYWHh4ckfGfMmDFC/sKyZctgaWkpkvfr109QPPfu3SvywjGWXySCN6oePnwo8S7VqFFD2GlNT09Ht27dRHLDnebVq1dLwpzmz58vLH4PHjxAt27d0LBhQ0E5tLGxEQy/rKws/PTTTxg/fjxGjRqFQYMGoVevXiKP4pkzZ7Br1y4cOXIEv/76K8LCwkSG2/v373Hjxg3F0EC+2IYxCsoz1mg0BS4cf5eF5a+koAIYSgoskK/AGSsk8Pz5c6O5QAkJCYWeK/SfQKvVGr3u5ORk/Pzzz/D398exY8dw8eJFXL9+XRjfiYmJ6N+/P9q0aSMo1yVLlsSwYcOQnJyM5ORk2RCmnj17IiUlBVlZWejdu7dEbmdnh5SUFGi1WkyePFki//7774XnyRfB0j969eolGFvnzp0TOcsYY+jfv79gSEVEREjCPPv37y946JOTk9GrVy/Ri/yHH34QxoNWq8WcOXNEu15t2rQRjbegoCC0a9dOWEOrV68uOByB/PHn7OwsGP8WFhYixTozMxPLly/H0KFDYWNjA3Nzc0yYMEE0J06fPo3ly5dj2rRpGDx4MBwcHERrzYsXLwRDiD/0K2Xn5OTg6tWriImJUQzrffr0qdF5FBcXV6CjSs5Q1ScyMtJoWDEAiTJpyKlTp4w6amJiYhAYGGj0O5ycnERrsU6nE/3/kiVLJGHm+o6G3NxcieM2JydHlPPdt29fSfVfjuOEOTl06FCjKSajRo3C4MGDFd83/fr1Q40aNSSRJDzNmzeHSqXCkCFDJDv3WVlZwpi2sLCAg4MDAgIChOip1NRUSW6ftbU1unTpglmzZmHnzp2iUFC5w3Be8odKpcKUKVMUFWx7e3u8fv1aEn7NGIOZmRn27t2L1NRUDBw4UCIvX748wsPDkZmZiTFjxkjkNWvWxMuXL6HRaCTONP7v+Z218+fPy+ZPTps2Dbm5ucjOzsbYsWMxcuRITJ48GV5eXli1ahV27twp6Dbnz5/H7t27ER0dLbsW5+bm4uDBg0admKGhoUbnZWZmZoHh/mfOnDH6jo2OjsadO3eMfsfatWuF/5b7LZs2bRKcL2lpaZKd1GvXrmHr1q0A8iOADNPbEhMT0atXL0G/efr0qWhXm+M4NGzYUORsN4xQatmypSgk2ZB+/fph3Lhxivfb3d0dVatWFW006HPkyBEwlr/jLhdFl5aWJujCxYoVg6OjI4KCgoQ5nJ2djUmTJsmO+/Lly6NDhw6iOhdyc6dt27YSZw0/j728vODq6irR1xljGDRo0N+ioBIjg/TPERwcLPE28sfcuXMxa9Ys2SIFJUqUwMKFCyXGGn+0aNFCEr+vfwwfPhzOzs6icAb9Y9GiRdixYwe6dOkim1i+YcMGhIWFwcPDQwgV1T82bdqE5ORkBAYGYuTIkaJC0xhgAAAgAElEQVT8Psbyw5n4qoWrV6+GnZ2dyKM4c+ZMAPmT7MqVK/D09BSFGjg4OAiLYHx8PIKCguDq6ip46m1sbIQXOMdxePPmDQ4ePAg3Nze0bdsWpUuXFnmo+TLdV65cwbp16zBu3DgEBARInhfHcUhKSsLjx48VvYrEX49OpzP60jOWxH/9+nWju31OTk6KrWgSExPRvHlzxfznJ0+eoHXr1orOgpSUFHTu3Fk2JItn9+7dRnMIAUh2Qv6pcBwnes7Z2dl4/fo1bty4gcOHD2PDhg3YvXs3dDodNBoNXr9+jcuXLwtVDvv374+hQ4ciISEBWq0WMTExOHnypFCYo0mTJujUqZOwNnz+/Blnz57FkiVL0LdvX1SqVAk9evQQ5bNdv34dvr6+6NevH8qWLYthw4YJ18hxHCIjI7F9+3YMHz4clStXhrOzs8ixk5KSgtOnT2PGjBlo1qwZRo0aJZLrdDo8ffoUGzZsQL9+/eDo6ChxYmRkZODy5cuYN28exo8fLxsenJSUhIsXL2LVqlWKReTy8vIQGRn5ty1K8XfHUEmMiYkRhe8BEMaOVqvFoUOHYGdnJzJIP336JBiPFy9eRKdOneDn5yf6Dv7zCQkJWLJkCTp37iwylPWfb1xcHFauXIklS5YI/yYXpfL582dhneOLOSmxbt06RUPl3bt3cHFxUVzT/Pz8MGTIEJGyrM/ChQthb2+POXPmICgoCC9fvhTmA8dxmDp1Klq1aoUePXrAyckJs2bNgo+PD3bv3o0TJ07AwcEBderUQZ06dVC7dm3UqFEDVatWRcWKFVG2bFlYWFigWLFiKF++vKzuUrp0aXTs2BENGzYURUbxx5gxY+Du7o6ePXsKlWH19a7jx48jMDAQXl5e6N+/v8gpVbFiRTx69AgfPnxAcHAwdu7cCU9PTzg4OKBJkyYoU6aMyMhXq9WIj49HVFQUbt26hXPnzsmmL/yTMFZI6sWLF6IcUB5+fJw7dw4tW7aURHmp1WrodDrcvHkTTZo0ka3HkpKSgpSUFLi5uaFz586S8c87+mJiYjB8+HDs3btXJNcP605LS8OmTZtE8+zKlSuyURH8tfv7+xst7rlx40acPXtWcV7u3LkTI0eOxIkTJ2Sj3J4/f44SJUrA1tYWY8aMwdq1a3HlyhXB4Z6Xlwd7e3tZfb948eKoUqWKbAVw/aNNmzaKzqBWrVrJptz9NyGD9E8QHx8PFxcXtGrVSnYrnn/InTp1kpWXLFkS3t7ecHZ2FlUA5Y/vv/8e4eHhWLduHXr27CnxbMyfPx95eXkIDQ3F3Llz0aJFC5GcT2BPSUnBkSNHMGbMGJQvX17wpugvrDExMdi4cSO6desGc3NzmJiYiIwAjUaDGzduYO7cuWjatClUKpUkJyEtLQ3Hjx/H+PHjUaVKFaG0tz6fP3+Gv78/Ro0ahWXLlslO3k+fPuHgwYPYt2+f4uTOzs7+xy/8/2sY26nMzs6W5KjoM3XqVNmXEJCvqBctWlSxf+mqVatgZWWlaLR2794dxYsXl4xXnlatWqF48eKyDgwAGD16NIoVK4adO3fKjsenT5+iSJEi2LRpk+J43bVrF+bOnWvUKH/37p1s3ikhJjc3V5Lrrs+nT58kHngevsWBUtg6H8mgVB0UyK9QaCyaQaPRGN2lI/47PHv2THHNiIiIwKhRo1CtWjWJgq3RaHDgwAHBUWtobOp0Ohw/flzYxWvXrp0kMiUqKgoTJ04U3vuGu1QajQZnz56Fg4MDTE1NUaNGDcmY5jgODx8+hLe3N9q2bYsaNWoYHbexsbE4f/78n15DCor4+G9GhOh0OiQlJSEqKgqhoaE4evQotm3bBl9fXyQlJUGr1eL9+/cIDg7G7t27MXfuXDg6OmLLli3Cdaanp+PevXvYu3cvZs+ejcGDB0scmBkZGbh//z727NmDZcuWKe4863Q6wSHxTyQxMVExIigqKgoODg6ykQ58UcYiRYrIFu/88uWLUBRRrm1aSkoKXF1dwVh+6oPhe1Kn02HPnj2C/iqX2vD582dMnjwZZmZmaNq0qey79t27d3B3d0eJEiVka2kA+eM7LCwMXl5ecHNz+8taFBU0ZlJSUoxWdf706RMuXryIW7du4dmzZ3j//r0ohejLly9YvHgxPD09MXnyZDg7O2Pw4MFCmH2zZs1QsmRJlChRAtWqVZN15lSpUkWSv//fhAzSvwi+ifWRI0ewcOFCDBgwAHXr1oVKpcK4ceOQk5ODBw8eYOvWrRg1apRQcbR8+fKIiIgQdgH37NmDMWPGCJ69wYMHCwOOr9Y4d+5ctG7dGiqVCjt27BBdx6dPn7Bnzx44OjqiQoUKkhAnnU6He/fuYdGiRejataukGACQv4AfP34cM2bMUHy5vXv3Dvv27ZNt0A38/55vxiazTqf7xy7s/6sYex4cxxndCZw/f76ogp4+mZmZsLKyUtwpXL58OYoXL67oZKhVqxaKFi0qmz/2+PFjMJZf2EGuqJV+ruLs2bMli75+Fb5Ro0ZJFNTQ0FDRzr5cJWW+QEa/fv1kjZn4+HioVCr06tVL0ZhKTU1FkyZNClQoqUE38X+dmJgY7Nu3T2IIchyHS5cuoXv37ihXrpxkLj569EgogMcYExXb4gu71a9fX7SjwJ9Do9Fg//79opoIKpVKUOA4jsO1a9ckuYP6LZxevXqFefPmiUJeTUxMhOIo2dnZOHfuHCZNmiRKZSlWrJhgRGVnZyMsLAy//PIL3Nzc0LVrVyFlRb+IkiE6nQ6ZmZkFhlYT/0x4p4UcfDXzsWPHSmQJCQmYMmUKTE1NMXr0aIn8ypUrQiEsW1tbkQ7BcRz8/f2F8Wlubi5yFnIch6NHj4qiDA3D4R88eIB27doJcsNzpKSkwMvLS7RhYxiae/v2bTg6OgrpF1WqVJGE5d+4cQMzZ84U9Vs1bK2Wl5eH58+fIygoCAsXLsTAgQOxZ88e2Xv6V/NX68o6nQ5xcXG4e/cujhw5grVr18LNzQ0jR46UpBP8tyCD9C9CyauUmZmJe/fuyRaqSUhIwNmzZ7F161bZ8Jq3b99i7969CA0Nld1KT0xMxLFjx5Ceni4r12g0Qsl0JY8fn+dSULEVMhz/d8jOzlbcrdRqtUYNmgMHDijK7t27hxkzZijKBw0ahKlTp8rK0tLSwJi4LLw+fOGq2rVryypMfDU/w3YPQP7Y1C8NP2/ePEmFY/1w8q5du4ruz9evX0XFc+rUqSMK4+M4TqSkVqpUSVIkYtOmTSIvo1yuG98Wp0GDBooLfsOGDdGoUSOjhadcXFwK9GJyHGd0x5og/o7k5eXh3r17WLdunaTtUmJiIrZu3Yp27drB3NxclHKRk5MDPz8/UcVN/bXs3r176Nevn8hQ7NSpEziOQ15eHvz8/CT5xIwx3LlzBzqdDrt27ZKVT5kyBUB+WxzeKaV/VKpUCSkpKYiMjJTNe+TXK7VaDVdXV8VwuhMnTiAkJASNGjVSLE6yfv16zJgxA+3bt0fLli3RoEEDVKtWDWXKlBF2aitUqIDevXtj6dKl8Pf3R0hICN69eydy0h09ehTnz59XdDZnZGQgNDTUqE4QExNjVJ6VlaX4/TwF5ROTTiJGp9NJ9Eg+DNbDwwMNGjSQFIS8f/++YKiVKFFC9N7JycnBypUrhZxEMzMz0ZyMi4vDiBEjRGNQv/L7mzdvJC1Z9A3a9+/fS5w3ZcuWFcJZv379ikmTJklS3o4fPw4gX89ZvXq1JJ2Mb/mm0Whw5MgRkTHLH3wLwQcPHmDSpEmStLtixYrh6dOnQru+YcOGwcbGRtI3deXKlXj69Ck8PDwwZ84ceHl5YcGCBVi8eDGWLl2K5cuXw9fXF3PnzsWaNWsQGhoqm6up0Wgwffp0SXFBfYKDg7Fu3Tqju6jXr18vMD2osMNyjUEG6V+ARqOBg4OD0YEyffp0o0nDo0ePVgwDy83NRZMmTRRj97Ozs9G0aVOjye0//PCD0fNPmDDB6N8vW7bMaO7Anj17JN4kfS5cuGA07+nBgweKYXZA/uJmrBlwYmKi0YmYlZVlVK7RaIx+v06nM2ok6HQ6o2F+Op3OaJihVqtFUlKS4mKk1Wrx6tUrnD9/HuvXr5cNi4mKisLMmTPRtm1b2WcZFxcHOzs7UUEofe7du4eWLVsqXqO7uztsbGwU5U2bNoWlpaXsDmJycrKwiMu1ANFvV6DfH5DHx8dH9LIwDIEbPXq0ILewsMCCBQtE95JvmcNYfg/RUaNGifI49MvXFy9eHA4ODqKFe9WqVYLc1NRUEl2QmJgoMmpr164t6fOlX47d2tpadrfXyckJjDGjRqmTkxNatmxp1Il05MgR4cVtjOTkZMUohoKcVLGxsUbHPJDv4DAWJXH69GmjxW4+ffokyQUyxFj/YCBfwTa2Nt+4ccOochwTE2M0RDc1NdWo8c9xXIFKQEH30djaASg7HHmMre2/5+8TEhKM3uMXL17g/fv3ivc5ODgYW7duhbe3N6ZPn47NmzeLdjf9/Pxgb28vGGT61TQ5jsOCBQtEyuD69esFeV5eHqZOnSrKN+zRo4dwvdnZ2fDx8RFVRTUxMRGiPTQaDS5cuCApEDhmzBjhHNHR0ZL2EeXKlRNyyjIyMrBx40aJ8qzfruT27dsSxbdNmzbCPEtLSxNVruYP/Zw8f39/iVylUgk9V798+aLYgmLgwIH4+vWrbJ9SPmy4c+fOQq9US0tL9O3bFzt27BDtrPEFZDp27Ihz587JjgtfX1/07t1bcdx//vwZ7du3N6oTODs7iwqAGbJt2zajvdGvX78uGwHG8+HDBzx+/FhRnpqaarQQYUpKimLfcSB/zhjr0RwbG2t03j19+hTBwcGIiYmRXZ/Onj2LyZMno0ePHmjQoAHat28v6FAcx2HTpk2i8aY/Z3Q6naTvrv7OZF5eHiZNmiR6p02cOFGQ5+bmYubMmUIILf/O4+e/RqPB8uXLRdEEjDFhl5/jOOzbtw89evQQyRcuXCic4+bNm5gyZYpoTjVp0kRYN+Li4rBmzRpJ3iTvTOY4Dr/++qvEIB0yZIhwjvT0dNkeo/rzNiwsTHIO/ehEjuNEldD1jxIlSmDHjh14+fKlULnaxMQEzZs3x/jx47F79248efIEGo0GEydOFNaEvXv3Sp75p0+fwFh+JXXDvHeeo0ePoly5ckaLv40dO/a/tqv770IG6Z/g2bNncHZ2xpMnT8AYkxTDyMjIwOjRo/H69WtUr14dAwYMEClnHMfBzc0NYWFhKF26NPr27SsJQdqwYYOgDA8aNEiy+F+4cEFYWIYPHy6Rv3r1CkuXLhW8U4byzMxMrFq1CqVKlcLIkSNlk7q3bNkCGxsbxf6Whw4dwvfff48+ffrIVnkNCQnB0KFD0bVrV1mF5cWLF5g4cSK+/fZb2dyrtLQ0eHp6olmzZrJGMcdxWL16taSnmz5HjhxB9erVRaXb9bl9+zYqV66sWE0uIiICNWvWlLRD4Pn06RNq164NLy8v2R2+rKws1KpVC/b29ti8ebPkRctxHOrVqwczMzM0aNBAkk+p0WiEno1Tp06VKPlqtRr29vYwMTGRbUeg0+kwYsQIVK9eXfYZcRyHUaNGoVWrVrK/n+M4dOnSBZUrV5a9xzqdDrVq1UKNGjVkczW/fv2KMmXKwMrKCtu3b5fcw6dPn8La2hoqlQr79++XnOPSpUvCgu7v7y95kR84cEBQrBYtWiQ5P98ag+81a8i5c+eEF03NmjUlEQ9xcXGCQmxhYSHrvOD70jHGZF8Ib968Ec6xdu1axWqEpqam6N69u6KhNm7cOFSoUAE3btyQlet0OnTo0EGS+6bPs2fPUL9+faxZs0bxM927d8ewYcNw9OhRWcVq7969KFOmDHbs2CFrdN69excNGzbE999/LztmYmNjMXjwYJQqVUrWSaLRaLBgwQIwxhT7CwcEBKBMmTKYP3++rPzSpUv45ptvMHHiRNn7/eTJEzg6OmLYsGGy8yIxMRFubm7o1auX7G/UarVYt24dOnTooLijc+HCBTRv3lzRKAwPD0fr1q0VlfPo6Gh06dJFUTmOi4tDjx49FMdDTk4O+vTpo5gDDeS3vRo3bpyiU27q1KmoX78+5s6di7CwMMn3LF++XJhf7dq1kxQp029NM23aNMn80m8Ir6+U8rx580YwOPv37y85f0pKiqiCpWFRILVaLWr9xe9s8nAcJ6pgaW1tLXEIzZw5U6RsGs6vwMBAkbxfv36i64yKihIZ1cWKFRO1IsnLy0OtWrVE32H4zjasDmtqaiqqGhwUFCRRii0tLYVnn5KSIjIy9I8WLVrgxIkTGDBggGwhxhYtWmDevHnw8PAQGTotWrRAUFCQMD8ePHggVNguWbIk9uzZI/oN2dnZQl/bWrVqya5zq1atQu3atVG3bl1ZR/WRI0fQs2dP1KlTR9YovHfvHsaPHy8bdgnkz5m5c+eiXr16ss4mtVqN1atXo3HjxoqO+O3bt6Nly5aKhW727NmDJk2aKKahHDhwAMWLF4erq6usYXzy5EnhHpuZmcHLy0u0Dl+/fl2Q9+3bV7K+xMTECLvpcrpfSkoKihcvDsbyOx8Yrn/6c8bCwkIS7stxnMiJI1czRN9Q69q1q0S+ceNGQW5hYSF5T9y8eVM0Fg0rZCclJYkKgw4dOlRyjXw/WcbyndGGKTGLFy8WjfO5c+eK5Hfu3BHJzczMRC1utFqtyDDnj/79+wsOGRcXF9k5xesDfKFO/X8vU6YM5syZg7dv3yI+Ph7169cXvoOvRs2PXY7j0KdPHwwZMkRYFwxrWixevBjLli0TOm9s2bJF8jwKGzJI/yAcxwkhOPoLvJubmzAI+MbIlpaWwsLg4eEhfAffh0rfs6uvWN27d09SZU6/OXpCQoKk0bb+osBxnMQ7xHtSeXhvKH8YKn4HDx4UyTdt2iSSv3z5UhRCZJjDkpeXJyrY5OnpKbmX/CRi7P+3lNFHP8evZ8+eEqM2PDxcuIYWLVpIdhOys7MFD1flypVlwyV5z7SFhYVs2OrKlSuFa3B0dJTsaOgvWtbW1tiwYYPoOjMyMlCpUiU0adIEs2fPRkhIiOR3jho1ClOmTFHMITxy5AiWL1+uqFR++PBBkn+hT0ZGhlGPsFarNerx1Wq1QjU8QzQaDTIzMxWV8qysLMTGxiruNCUnJ+POnTuKCnFCQgK2b98uhKAb8uXLF7i6ugohdoakpKSgQ4cOCAkJUQyZadiwIa5cuaKYZzNgwAAcOnRI0Tt56tQpLFiwAL/99pusHAAmTZqEhw8fKrbnefz4MR48eGB0x+7r168F7njl5uYaDXlTq9U4ceKE0e9o1aoVWrVqhZ9++knWUaO/q9y6dWvJfdFvnVC5cmXJjrH+vC5SpIikj93ly5dFa49hUawPHz6IFHzD6o6Ga4+3t7fkN+iHcS5YsEAi5w0tw7Wb58qVK4L8xx9/lMzN+Ph4IVzSwcFBNueR30XQb4elz7hx48BYfssYuSgPPke6aNGisoXBoqKiBEVmyJAhEgVap9MJu2oWFhaYO3eu5DpcXFxgZWWFvn37YsuWLRLj+eTJk6hcuTK2bNki61R8/fo1mjdvrpgSkJOTgzFjxojen4YcPXoUtWvXVozEOXfuHPr27Svp3ckTFhaGJUuWoGzZsrLfER8fj/Xr16NMmTKSXtZA/pxatGgR7O3tZRV4juOwYsUKODs7o3jx4rJr2a5duwRjbNeuXRL5pUuXhDBIOSdHZGSkEAZZpEgRyfNOTU2Fra2t8LxtbW0lu4jNmzcXvbNbtmwp9EsEoBha3LhxY/z000/o2bOnrLxevXrYvXs35s+fL5H16NFDuB/79+8XyUqUKCGK+Hnw4IFI3qhRI5GhkpSUJGq116FDB9GY4zhOVNG/Z8+eEmcSvxvFGMOAAQMkY07fsO/Xr5/kWX/69ElwkH7zzTeyRus333wjzEs5Z9CKFSvAWL4Tx8bGBtu3bxdd55MnT2BtbY0xY8ZIwtf5Z929e3dMmzZN1lnGcRy2bt2Ktm3bKr5PLl++jI4dOyruJIeFhWHhwoVC1wRD4uLicOTIEVStWlX2HDk5OTh06BA6deqEM2fOyF7j3r17MWvWLIwfP172HMePH8eaNWtQv3592d95+/ZtbNiwAWZmZrIbDu/evYOvry9UKpWskzYjIwMeHh4oUaKE7FjhOA7jx49H+fLlUbRoUdmCSq6urkKebIUKFXD48GHR8545c6akt2/VqlWxcOFCvH37VvSekTNYlTpuVKpUCUFBQbh9+7asfMyYMcjJyRGNV/1j5cqVsve8sCCD9E9w5coV2Ya2fPn2R48eyeaV8Fv9Hz58kF38jx49CiB/wdFv7M4vXrzCm5aWhpYtW4rk5ubmgmKYkZGBQYMGieQWFhZCqFJWVhZmzZolkfNhFbm5uaIwQ/77+dwdjUaDPXv2iPoemZiYCKGIHMfh2LFjktLr+uEQd+7ckVQH1lcovn79KulD6urqKkx2juOwcOFCkbxjx44iherGjRuiHMDy5cuLDLO0tDSMHz8enTt3Rq1atWBubg4vLy/RS+jgwYNYsmQJFi5cCC8vL6xbt06kLLx69QpXrlxBVFSUrMGj1WplS/nrYyy8B/hn9hj9dygoZ6igyqa8oa/T6WRzvvVfZnItEfTl8fHxEuMgLy9P5AxJTU2V7OQaCx39u1FQiPmKFSswb948rFixAhs3boSfn5/gcMjNzcWgQYNEzjpTU1OsWrUKHMdBrVbL9lxbvXq1UGp/9erVEoccv6PLKzKGPdf0jdZTp05JQiT1HXL37t0Tisvxx759+wT558+fJX2g9UOd1Go1nJ2dFc8P5Jf61y+2Yeh9f/jwoajnomEUTXp6OiZPnixUfJXbMdq/fz9+/PFHdOrUCZUqVZI4FSMiIrBjxw6sXbsWS5YswZYtW0TjMDc3F1evXsWzZ8+QmJgou85ER0cbdXAkJSUVmBNYULGujx8/FrjGFdTL+e7du0ZDxNVqNQ4ePGj0O7y9vYX1QS6kcvv27UIOt1xY/bVr14RxkJSUJPnM27dv4eDgIKxnsbGxot+dnp6OmjVrKu6YZ2dnw9LSUrEfIp8e4eHhIfvM3r17B8byjdVTp05J1tWIiAioVCqYmJjgu+++w9q1a0X3PTw8XDIvq1evDjs7O0yYMAGLFy+W3YW1trbGrl27cPPmTUnHAFNTU8FAv3PnjqSveNOmTQUn8K1btyQ6xYgRI4Tfcf36dYnepO9sMiySw687PHKh04a79oGBgaLNgM6dO4ve+3xU17hx4zB48GB0794dGzduFD3nW7du4datW4qpVDk5OUbbjQH5jh5j78W8vDxFB6v+dxgjKSmpwDZTSm3XeG7fvo3U1FTF3/r27Vs8fvxYsb5Fbm4uTp48qXgejuOwefNmZGVlKb63Zs+eLbRrkoPvoa1E+/btJU5VferUqYOxY8fKRsjpdDrUqVMHpqamGDBgAM6dOydap7KysiS2hLm5OWxtbTFu3Dj4+PjI5rDzR7du3WT7djOWHwIcExODbdu2oWzZshK5YXpTYUIG6Z8gMjJStvk7Y/k7iS9evJAkdfOL74ULF7B3715Jg2nG8kN5zpw5o9gcunz58rh//77EGOWPGjVqIC4uDm5ubrJNcPkwlaNHj+Lbb79VlEdHR2PmzJkSpa5GjRr4+vUrsrKycPDgQfTv31/0AipfvrwQqvDy5UusWLFCZHRaWVkJO115eXn49ddfMXXqVKGZtomJichjmpycjMOHD2Ps2LHCteg3YgbylZ3Dhw9j6tSpaNasGXr37i0xOtLS0nDz5k1s3boVc+bMUfS089XHCjIQif8sxhZJtVpt1MA/c+YMfvvtN8XvmDVrFpYtW6a4I7xr1y507NgRJ0+elFVwdTodOnXqhAkTJihWFtZqtbC3t8cvv/xiVEkODAz8XVXtlAqn/Z3hOA4ZGRl4//49Hj16hODgYMTFxUGn0+Hjx48ICQmBn58fvLy8MHToULRq1Uoo8hIZGYnAwEB4enqiW7duwsuUbxf19u1bHDhwAJMnT0bz5s2FXSHeC56ZmYlLly7B09NT8DCbmJgInnqO4xAREYE1a9YIfZTNzc1F4cPp6ek4duwYRo8ejTJlysDc3FzS//jZs2dYvnw52rRpAzMzM0lucHZ2Ns6ePYuJEyeiSpUqsu2Fvnz5gsDAQDg7O8PHx0d23H79+hVnz55FQECA0bmRnJz8f955BcDonONDreWMaN5hMmvWLNn0B41GA51Oh5UrV4oilnjUajW0Wi2uXr2Kli1bSoxCjsvvhZ2Xl4c1a9bAxcVF8h36obwRERGinVC+1ZsSb968ka0xwBMSEoLTp08rjqHAwEAEBAQoVuPdvHkz1q9fL+R/699DrVYLX19fzJ49G56envD09ISHhwc8PDzg7u4ONzc3ODk5YeTIkejYsSOqVq0qCmWcOXMmfHx80LdvX4nybGtri4SEBAQEBGDYsGGSHu6LFy8GkL+zuHDhQkl/df4e5uXl4cKFC3B2dhYcWiYmJqI0i8zMTBw/fhxOTk7CeQxTUfgWUfv27cPEiRPh7u7+P7lG/16M1RTg27IokZ2dLRvdxqPRaDB48GBJwUJ9AgICFIsmAvkO4G7duik6pnU6HWJiYhSvkx/HOTk5spFcxgx7jUYjKRilT2RkJHx9fRWdcv7+/rCzs8OsWbPg7++PJ0+eiMbSnDlzhHFsYmICS0tLlCpVChUqVED16tVRvXp1xVB8XicfP368bF9fxhhmzZr1tzBKySD9g+Tl5cHHxwddu3ZV7EE6YsQIdO7cWXYQFC9eHKtWrcLQoUNF4Sf8Ubt2bYSFhcHX11d2u/7bb79FdnY2QkJCMGnSJMni3atXL+h0OqSnpyMgIAA9e/YUXYd+PiifZ9qwYUNZOf9ydXFxQcmSJcEYQ+/evUVKT3JyMmaxRgcAACAASURBVPz8/PDDDz/AxMQEHTt2lCxg+sZpgwYNJJNep9Ph/v378PLyQseOHWXDL3Q6HR4+fAhfX1+jnr2vX78WWCiE+O9QUDEUJa9pbGwsvLy8FB0HP/74I5ycnGTDeNPS0lC1alU0b94c+/btkyiFX758EZqwu7i4SEKWeIOTMYb69etj+/btEgfF3bt3wVh+TomLi4tsWNXRo0fBWH4ouVIo74sXL2BpaYn169cbNSQWLVpUYAU9/tr/l1HyYvNtC86cOSObV5aamopLly5hyZIlss8iMTERR44cwcyZM2WVC76P8uzZs2U95RqNBqGhoVi1apXibmBsbCyCgoIUFS+dTodnz54V2F7p76Ac/K/CcRy2bdumON8+fPiA7777TlS0SJ9Xr16hTZs2qF27tuxz+PLli1CMRW4+5ubmwsPDA4wxuLu7y57j7t27gpPWMN+WJzIyEsOHD0fx4sWNKsM5OTk4ceJEgbtYf1fUajVevXqFq1evws/PT1SU5uXLlwgICMDkyZPRsmVLtG/fXgiP5Xuje3l5CffSsGBeREQEvL290bRpU1hbW0vCl3NycnDy5EkMGzYMderUkV1X8vLycOXKFcyePfsfXbncWITRrVu3FA05juMwefJkSV42j1qtRp8+fWBraysr1+l0QsEwJQfxwYMHYWJiIhvmDuTre61bt0aHDh0Uf0NoaCjKlClj1Jnz6NEj2NvbF+hY+G/2C+cdWJmZmYrvlWfPnuHUqVPYsWMHlixZgkmTJmHAgAFo164datWqhSJFisDExAStW7dG48aNZSt1T5w48S/rufpHIYP0LyA3Nxc3b97EihUr0KNHDyFR3NTUFKdOnRLt8Om3p+B3MnNycnD27Fm4uLiIwkC+//57YQBGR0dj+fLlotyIyZMnC9fAe/1Gjx4tnH/58uWi6/zy5Qu2bt0qJKIb5oNyHIfw8HB4eHigSpUqkvAz/reePHkSjo6O2Lhxo+z9iI+Px7Zt22SL2/C8fPmywNYVBeXJEX8fjC3Qe/fuVQy1+fz5Mxo0aICzZ8/KyqdMmYKSJUvCx8dHYhB++fJF8F4PGDAA9+/fF8lPnz4tzJVKlSph2bJlIicFXwhJf76dOXNGMOgiIyNFXsdy5cph8eLFIsVPv/KmqakpxowZI9rd0Ol0ouiA/v37i+Q8fOh+ly5dFHdcd+zYgSpVqhTYh3TDhg1k0BD/WF68eCEKrdYnNjYWP/zwA6pXry6rXB0/flwoHiJXeOzw4cMoUaIEGGOyxdGCg4OFKB25Ii3Pnz8XvaMNC/akpqZi6tSpwq6gnZ2d7O8bOXKk8Bm53Ge1Wo3z589j9OjRsLa2VjR89flfd1QB+TqBkuH98eNH7N+/X1FviIqKwvHjxxXXxszMTMWih//rcBxntJq6h4eH7HsJyC/KZmlpKes44ThOqEPyyy+/SORarRbDhg0DY0y2hylf2JMxhooVK8qe/+jRo8Jmitw1xMXFCSHac+bMkf2OvXv3wtzcHKVKlZI16rRaLXx8fGBubi5Jq9AnMjISo0ePltQr+LvDcRzS0tIQHR2NnJwcZGdn48GDB9izZw9mzJgBOzs7lClTBqNGjSrUtCIySP8CDHdwNBoNwsLCsG7dOgwbNgxhYWGCTKfTITw8HMuWLUP79u3Rrl07ZGVliZpvX7t2DW5ubqhevbqQTK6/wxMVFYWlS5eiadOmwotZf7HJzs7G0aNH4ejoiFu3bgGQ7lK9efMGa9euVVzctVotbt68aXRwUkjrPwtjRszbt2+NtuUZO3asxCDkiYqKgoWFhWJ7Dr7Ix6BBgyQ7AfHx8UIEQeXKlbFjxw7Rzvu2bdtERmW3bt0QHBwsnGfo0KEiedGiRTFx4kRERkYKlekMPYV169bFpk2bkJ6ejkWLFknk/He8fPkScXFxkjxGExMTjBo1SvDG6xvG/I7qjBkzROvGkSNHRNETu3fvltyrmJgYMJZfudKYl7dXr16KnmQejuNE6xJB/B1Qq9U4dOiQbFRERkYGfvrpJ1hYWEgql3IchwMHDggRPEuXLhXJs7Ky4OrqKopA0jfQsrOzRXLGmMg40Wq1WLRokSi8VL9Aik6nw6ZNm0SFQ/R3a/h6CoYpOhcuXBA+Ex0dDScnJ9HuRfXq1YX3rEajwdWrVzF+/HhRRc5OnToJa6JOp0NsbCx+++03bN++He7u7ujbty9at25tNByS+Ofy7NkzuLq6yu76ff78GZ07d1bcvTx48CDMzMxQokQJ2WI/+pWn+dok+nL+3c4Yky0Upl//o1u3bhL5qVOnhMJ1ZmZmkkind+/eoV69esJ3nD59WiTX6XSYO3euIB8+fLjkHDExMaJqwXKRd48ePcKQIUOgUqlQt25d2d1kjUaDR48e4eeff4azszMuX74s+cyf4fc4mQvq3ZuWlqb4PXx7MqVQ/f8GZJD+BfTq1ctoKN3p06cl5ap5vn79itevX2P27NkSGa80JiYmipL29Xn79i04jsOkSZNk5fwiopSXxBMQEGDUg3rlyhWj8vDwcKPG6+vXr43mICQmJhqdTFlZWUblGo3GqJzjuAL7Kv4TPMh/hsOHDyvK4uLi0KpVK0Xv87p162BlZaVYaIMvDjNo0CBJ0YEXL14Iil7x4sWxceNG0cvPsCx7mzZthB1ZrVYrKRxWt25dIYcqPj5eUk7d1tYW/v7+0Ol0+PDhg8SgtLGxwYEDB5Cbm4ucnBw0aNBAJK9YsSI2b94s/I61a9eK5Kamppg8ebJg8HEcJymO06xZM1FZ9ry8PEmutmH1RI7jhKqxFhYWin1G+/fvDysrK9mwVZ7g4GDMmjVLUc6TkZFRYA9MJdRqtdHexUB+VWFj8y4hIcFon1IAsnl++hjrRQjkN2g3dg1paWlGQ7g4jiuwoE9BXueClI1/wo53fHw8zpw5g8DAQMnv+fLlC5YuXYrKlStLxiXHcTh8+LBQY2DgwIEieXJysqhSu6mpqch5Fh8fL1kj+MKDQP7zNSwuqG9MajQaSZ/BokWLCmOb4zisXLlSso7o98+9fPmyaOeUsfxCPfx9SEpKwujRoyU1H/QrT589e1ZSzKdixYrCb9VoNJJeqYzlV/3kd5ZiY2PRtWtX9O7dG2PGjIGnpydWrVqFPXv2CJXfg4KCsGvXLkXFVKvVIigoyOiYfPbsmdE5lZubW6DiW9DaUZDy/U9/n/M58L6+vvD19ZU8j4SEBEyaNAkmJiay1WVDQkKEiD25XOgtW7YI7+W+fftKzq3fx7RIkSKiNZLjOCFsnT8uXrwo+g7D96ZhJd9z586JIpRatGghkr98+VJURZ0xJoqAyszMxMCBA0VywyrfAQEBopS5Hj16iORJSUlCmxT+OHfunOgzV65cgZ2dneh7DPsoL1++HO7u7li+fDm2b9+Ow4cP4+rVq0L7v4SEBEybNk22pRbPnj17JC2UDBk8eLDR8P7AwED4+voqygsbMkj/BElJSQgICEDp0qVha2sr2THkE70XL16M4sWLy4ZEHDt2DMHBwWCMyXpUQkJCcOzYMTDGZIthxMTECO0R5Hr1paen4/r160L/R0N0Oh1u3bqFRo0aKfYlCg8PR48ePUSNlfWJiorCxIkTFcMYPnz4AG9vb9n+ckB+GNP27dtljXL+Go8dO4bp06fLyoH8ynyurq6K8nfv3mH8+PGKkzk9PR0TJ05UfIllZWVh9uzZikatWq2Gt7e3YqNrnU4HHx8fxUbe/KK1YcMGWeOf4zj4+PigT58+wq63PhEREXBwcFAM5/z69SscHR0li6k+3bp1k+0HyZ/f0tIS06ZNk5U/evRIMPbk8kD4Fh81a9bE7du3JXJ+0S9WrJjEAElPTxfa9qhUKkmo9927dxV3LgBxD0TGpKFD27dvlxi0+s9Zv0ciY/nV7/QLKqnValH+tZyn9tKlSyK54Q4OAKHnJmMMgwcPlsiB/x8iXL58eVy4cEF2vPLtWJR6c3IcB3t7ewwaNEhWDuSvbT179kSvXr0Ux/zq1asxbdo0XLlyRdZg+/jxI+rXr68YJpeamopx48Zh4MCBsnnEvHJcoUIFxV5+T548Qd26dXHq1ClZ+atXr+Do6CjbIw/IVwSWLFki+zyAfEdBQECAbLsqnrCwMFH6hCGJiYmYMGGCojwzMxOenp6Ka1N2djZ8fHwU1ya1Wo0tW7YoGs0cx2H37v/H3nWHRXVt3wNYQMUCdlER7IaIJdiiYkM0NjQqahJb7L0rKhb02RUVjSWxi11Ro1iwN4wKgl0UBGnS68zAzNz1+2PePW/u3HPuvF+S96J57u+b70vcTLtz7jm7rL3WTsUAf8+ePYoFDDEY4rFQBgQEwNPTE97e3sz7e/HixSCEoG7dujLWWUEQ4OPjA0IInJycZOdoYWEhNm/eTO8NU9ieIAi4c+cO7Syy1nVWVhbtnhJCZIRogiBIklbWWTly5EjqHzRokMxvvI/Y2trK1vTDhw8l+5Qp7FilUlH5HUIMbPGma8KYSdOUiAcwMPwaB/G1a9eWdHzy8vJkZIhiAU2cj1yzZg0IMXSkPD09sXv3bklR6unTp3BwcEDnzp2ZrMcZGRkYPXo0Bg8ezFyTgiDg4sWL6Ny5M7dQ8+HDB3Tv3p1bAM3IyMD8+fO5PBJ5eXk4duwYcy0ChvM4PDxckfwpNjbWLHkUT4YMMCTlvPELwMA8e/bsWe59f+rUKXTu3Bk9evRgfk4RHfTFF1/I4g5BEKh+vbOzs+w663Q6bNy4kXs/qNVqBAYG0rVkqledl5eHixcvUv1N01hdrVbj9u3bVDudECJJlESk4Hfffcc9t9++fUvXIiEEw4YNk/gzMzNx/fp1ek/Vr19f4tfr9UhISKBFHEtLS1kRpLCwEN9//z19D5YU2tmzZ6m/Z8+eMr9Go6HFMkLk0oeAvKhuY2MDX19fur4jIiLovd+oUSOsWbNGMgaVl5dHERxdu3aV6dgDhhGkWrVqoXr16kySxODgYAqvViKg+ivtc0L6B8zb21uyyAYPHizZXETtShH/7urqKmn1nz9/HhYWFrQqWrlyZUmF59WrVyhTpgy94cqUKSPRNsvOzpZQRZcqVUqysej1evTu3Zs+v2TJkrINcsmSJfT5JUqUkM1QiDejhYUFrK2tZTTkUVFRKF26NCwsLFC0aFFZN0KtVqN+/fqwsLCAlZUVlYwxvY7iZzRlqASAjRs3Uj9LZ++3336jftYcQ15eHiV94iXNIhsyLykVA6pOnToxO0aXL18GIYa5YFaXMDMzE9bW1ihTpgyWLl3KhHx06dIF06ZN42pxrlu3jjn3BAA7d+5U3GhErValwPnx48eKnZ6zZ89yq9p6vR6rVq3iyjKkpKRg5MiR3AP+zp078PT0xN69e5n+LVu2oHnz5li0aBHz9xk1ahScnJwwfPhw5uHcqVMn2NnZoVevXrI1rtfr0b59e1haWuKbb76RVXKBfwl89+zZU3Y4A4bNnhBD92bIkCHMgkKbNm3QsWNHDB06FLGxsbJELzY2Fvb29oqEXfv27cOGDRsUu4K3b9/G3bt3uTNDIjSHVxwBDNdk3rx5ijT4Q4cOhYWFBVq1aoWAgADZ9xGTDPG6mR6ixnBrV1dX2boPCQmh/vLly8uKLbGxsZRQztraWnZNNBoNHB0d6R7MIrnp0aMH3d9YBcHFixfTvcUYXilacHAwTYRYe1NCQgKtnLNQMnq9ns4/BQQEyPyAIRGysLDgFhhEPesBAwYwf/MXL16AEENXnlU91+v1VGPPz8+P2Xn69ttvYW9vj8GDBzPn7Hbu3ImWLVtyYeDh4eFo164dZV83tZSUFHh5eXFhpRqNBgEBAejVqxfTLwgCfvrpJ3h5eXGTjDNnzmDRokXMuU3AEBSuW7cO5cuXZ0KGk5KSsGzZMnz11VfMtaBWqzFv3jwMHTqUWRwVi4rjxo1DtWrVmMna4cOHqQ4p61rev38fHTp0ACHsrlZSUhLtxLq5ucmKg4IgSNhnvby8ZGd6u3btJHGNWCg4fvw4BEGQSB0VL14cixcvlqwZY01FT09PWWIuEr0RwiZ9CgsLQ4kSJUCIvGsGGDrelStXho2NDXMuUafToUWLFrC1tUXv3r1lfgCYMGEC1Z1kWWBgIGxtbWUdM9Hi4uJQunRpdOrUiUvA5uLiwiVKAkA7iF26dGE2K27fvg0XFxduUp2QkIBu3bpxk161Wg1fX19mIwMw3PfHjh3jFssEQcCZM2ewePFi7n398OFDSgTHsnfv3iEoKAheXl7M65SZmYndu3dj/vz5TH3vgoIC7Ny5E3v27GFymgiCgKCgIBw4cIDbkHjw4AF27NiBTp06Mf3v37/H2rVrUbt2bWbxVaVSwdfXF2XLluWeyz4+PihevDhTyxoA/Pz8UKxYMVhYWGDo0KGyfdi4OGBcKBo4cCDi4uIQFBQk8dna2kq0bZ89eybx29nZSbTD09PTJcSnVlZWXN6Ov9I+J6S/0/R6PYYOHSpbRMZyJNu2bZNURAkhEtrqS5cuSaq2hEhFmp8+fSrzd+7cmQa76enpMm2iDh06SOZRTWVn3N3dqV+v10tmAAgxzKMY+027Ry1atKDVNkEQcPbsWQnLcOPGjelBKwgCbty4IYFV1KlTR3JAPXz4UCI9U61aNUkwEB8fL4FMlC1bVgKP1ul0EmhI8eLFZbOMwcHBEjiFMQwKMFRjPT096fcYP368ZPMUBAGbN29G//798dVXXzGJZ548eYJ9+/bRh2niplarER0dbVYz7PeaIAiK1VrAAI39I+/xR83ce7OqfsbPZSWKoqWlpTErk6K9efMG3333Hdf/+vVrtG7dmkvOlJ6ejrp16+LMmTPYsGEDswssJl2HDx9Gjx49cO3aNcnvfe3aNVqBzcvLQ7t27WTdQ9MOdWRkpASay4Op/RWQzrCwMEUm6+XLl6N169Zwd3eHh4cHvL29afArCAL8/Pwke0vlypUlBStjMgtCCOzt7SX6wTdv3qQENIQQlCtXTnIPhIWF0YRU9BsnU5GRkRIotb29vWQNvn37Fp6enpKk2Dihys3NlVTX7ezsJH6xSyEmrLa2trKA5tatW1RzsVixYrLuf3p6Orp3707PEWMNZ/E9Nm7ciK+++gpWVlYSjWbRHj9+DF9fX3z33Xfo37+/LPFXqVQIDg7G1atXcffuXSaTaFxcnCIEMjc31yxE0hznAI9t29iUCiSAIQBW+hwicZ+S3b17V/E1eNdItNjYWBw/fpx7b+Tl5WHHjh3cIL+goIAmYqz7Ojc3lxvgA4Z13b17d+71PHnyJFq1asUtam3cuBF2dnbo168ftm7dipcvX0rea/78+bK4p27durh69Sq0Wi2mTJkiixnE8zAnJ4eS2IgP44QpMzNTcp5bWlpKzvP8/HzMnTuXdu4sLCwk6Am9Xo9ly5ZJJGFMETcnT56UjEeY+hMSEiTKBsZ7jmjbtm2jEG3W6ERGRgbWrVuHPn36wN3dnVnIjYuL4yKqAMM6MHdm/juwZXPMqebeQ6fTmX0Npc+hUqkUGXyTk5ORl5eneLZFR0crXqu0tDQuGz/wr26pkikVaAFwmwGirV+/nntPZmVloVOnTty9Jy4uDjY2NqhRowa8vb2xadMmyRhcTEyMLBcgxNAgiYmJQXx8vGzkp0SJErRwlpaWJkNx2djYMNF2f6V9Tkh/h6lUKkyePJkOWxs/LC0tcfHiRZw6dUrCrmn8OHbsGEJDQ9GzZ0+mf+fOnTh9+rRsdk18BAQEIDIyUjLMbfzYvHkzcnJy0K1bN65fEASsXr2aqVO6YcMGAIYKnamANCGEYtBTUlIwa9YsmeSMWMnX6/UICgpCt27dJIm5MT14YmIiVq5cKfku/fr1oze2IAi4d+8exo8fTwO3li1bSjZRtVqNoKAgDBkyBLa2tqhevbosYcjOzsapU6cwZswY1K1bF7du3ZL9roWFhXj48CG2bNkiqS6x7K+mx/5scjMXEGdkZODEiRN49eoV8+B49+4dFixYgDZt2mDt2rWy5OHt27fQ6XTo2LEjihYtCi8vL5w+fZquRXHNCYJA772mTZvi4MGD9G+M140IQ2zdujX3YBAEAXXq1MEPP/zA1EYTTavVmp0T/5hMr9fj3bt3uHXrFgIDA7F69WpMmjQJgwYNQmRkJHQ6Hc6dO4elS5eid+/eFM5kZ2eHsLAw6PV6nDp1ChMmTJB0fBwcHGj1+datW5gxY4Zkb2nQoAG9jgkJCfD395fscW5ubjQw0ul0uHz5Mr7//nvasXF3d5f8hklJSVi9ejVFqnTo0EE293vjxg0MHToUJUqUQIsWLWQBYE5ODvbu3YsuXbow5bDE99m2bRv69u3L1azNycnBxYsXZfC7/zUzl/i+ePFCEZ4cGRmpCOV89uwZfHx8uP60tDTUrVtXMdDfunUr5syZw/XrdDqcPHmSW6RT+o45OTmK752UlKS4T0RHR3P3Ur1ej2fPnuHt27eIj49HamoqcnJyUFBQQHkaIiMjceTIESxZsgTe3t5o3LgxmjVrhri4OAiCQKXdxAC5ePHikuT8zp076Nu3L40ZXF1dJZDTyMhISaHItAuakZGBsWPH0uebyvsIgoBDhw5RuCmrQ5iZmYlx48bBwsICQ4YMYV6L9PR0+Pr6onHjxorIIkEQ/q1iy6dqpmRGpsYb1RJt/vz5ijrcFy5cYHZHRdNoNFzJGdG2b99uNj5Qmr38o6bVas3ec0rvL46NmGr7zpgxAwsWLMCgQYOYsXyRIkXw008/oVOnTsxcoFy5cmY5Gv6b9jkh/Z0WFxeHTZs2Uaif8Y9sZ2eHK1euYNGiRbIOJiEEpUuXRmhoqCwRM65sPHv2DMePH0fnzp1lfhsbG7x+/RqxsbHw8fGhG6vx86OioqDX63Hx4kX06tVL8hmNobliJc/4c1hbW0sgJI8ePcLIkSPpgi9WrJikKqlWq7Fv3z60atWKJuWm0NyYmBjMnz+fVnFMYa1i4CYSO7CgpxqNBidPnoSXlxd3k9NoNDhz5gxXFkB8r/+mjtRn+3MtMTGRu7m/ePEC48ePR2BgoGxWDTB0zUqVKgVHR0eMGTMGJ0+elMzW6XQ6CfOuq6srlixZItGOTEhIkBRhKlSogGnTpkng6jExMTSJIcTAlrl27VrJexUUFEg6eP369WNCnsU5mho1aihWabt06YIJEyaYPXg/pgPo/2PJyck4f/48tmzZIqumi5IPw4YNQ7du3SSdNGPyj5YtW6JHjx6yglJMTAxWrVqFpk2bMoOb3Nxc7N27F506dWLOmwqCgNDQUIwePZo7r5qTk4NffvlFcY47ISHB7O/zdydrMWdKxUCNRqM4lpCSkoJatWpxuykpKSlwdHRkjpYAhvOydu3aXDRGQUEB2rVrh2rVqnE/w6FDh2BhYcEdTwAMEOgaNWooBrEajYYJc/wYTafTMQstz58/x/Lly+Hl5SVj/I+KisL48eNhY2PDHJO4fPkynYdl/V6hoaFo0qQJihQpwhyDSUtLww8//ABra2tuN/vevXto1qyZYpEnMzPzP5rM/NVmyodgbGLnj2eJiYkoVqwYt5iak5ODsmXLcjkAAAOEfPLkyVz/1q1b4eLiwvXn5uaiUqVKXI1TwADnN8dMb66D+lebWOS9cOEC/P39MXbsWLi7u6NKlSpYvnw5fv31V0yfPh1NmjSRNIgcHBy4Y2L/bfuckP4J9uHDB+zcuROenp4USuLi4oK8vDxKuDB27FgJ2+dXX31Fq4rXr1/Hd999J4G+urm50Srnq1evMGPGDNohFLuEYtVQo9Hg4MGDaNOmDfW3adNGcnC/e/cOc+fOpTqnxtBcwLCYL1y4gB49etC5MNODPyMjAxs2bECdOnXQpEkTZhU2PDwco0ePRrNmzZhVw8LCQpw4cQLDhg3jsndmZmZi//79ijCQjIyM//nA7FM3VsIo2uHDh3HgwAFm4eD+/fuoVasW+vbti40bNyIiIkKyFoz1RevVq4exY8fiyJEjFGYXHBwsgYJaWVmhbdu2WLZsGR48eICMjAwmOqFOnTqYPXs2QkNDZVIu4qNp06bYtGkTUlNTsX79epnf1tYWM2bMoJ2Pffv2ySqaEydOlByeqampKFasGP2b6dOnMyFQS5cuBSEG0iYlVtcJEyZwA+6/gwmCoLh3JCUlKTJ8vn79WrGjkZCQoLj3/JWw+L+73b9/nxu86vV6DBgwgEk8AhiQTa1atULp0qWZiZ6YTBJCmLOuWq0WHh4eIETKoCuaIAgYPnw4CCFo1aoV8zMEBwdTZBULsivOmRJCuJ05wDDv+uWXX350kLs/Yrw9KzU1FevWrWOScun1euzdu1dGeGP8mhs3bmRqyop28eJFGfuq6WsoqSh8ylZQUIAzZ85w/ZcvX8a3337L9S9btgx2dnZc/+zZs7lrHTDwYhDCnocGDCg9Qgi6d+/O9Gs0GlSvXh2lS5fmfgaRJ4VHjJefnw9HR0ds3LiR+xpJSUno0qUL1y/a72Wk/09bZmamJJ5PS0vDiRMnMGHCBDRo0AANGzZUhDz/t+xzQvonW2ZmJg4cOIC+ffti6NChkoPPuMNXtGhRGb19RkYGNm/eTEkJTLuAYidS1ExiEfSICWGJEiUk86ymr+Hm5sZlzY2Ojsbs2bOZhy5gOAQuXbrEHbYHDJUzc5j9zwnlp29qtZo71yXOt/36669MAo9Dhw6hYcOGmDlzJq5fvy4J5HNyctCsWTMQYmCdmzx5Mk6fPk0rrZcvX5YkaXZ2dujduzfWr1+PR48eMZNBQggaNmyICRMmYPr06Uw/IQRVq1bFoUOHJPOJxo8BAwYgPj5eNgslJpTDhw9HVFQUtFot/Q7Gj2LFimH48OHIzs6GTqdDo0aNmInr8uXLKTRPJDoRH40aNUJYWJjkeops3YQYZtF5SdnIkSPh4uJiNnFikfR8ts/2n7Rbt25xbdJA/wAAIABJREFUu4L3799HmTJlmB1kQRAwceJEEEKYjMhiskoIwZdffsl8/ujRoynCh5UcGctcsIjrRFZTQggGDhwo89+5c0cCqzMtephyOuzcuVP2GjqdDqtXr0axYsUksjGmptVqcfr0aW63/u9mKpVKsQinNO4A/D1klViWkZHB1QcHDMman58f06fX6+Hq6or27dsz/Tk5ObRJwioWZGZm0jnbwMBAmb+goICOYowcOZL5HiJaqW7duky/MccJ6zf+8OEDSpUqBUIIk9QO+Bf53sqVK5l+rVaLDh06oF27dky/aAEBAVx5x4/dEhMTP4oO8OeE9E8w08BQtLy8PKjValy7dk22Waanp2Pbtm2IiYlBbGysZNhZ1B8dP348hQqa0lFHRERgypQpdM7N9IDMysrCjh076CA4qyPy9OlTuhGzFqNxRcVccmmuMqRWqxU3fZ1O9z+hxfexmtK1jYqKwrlz55gFBEEQ8P3332PIkCG4evWq7G9iYmJQrlw5lCtXDj/++CMuX74suRdE9mJCDIRV3t7eFJaanJwMZ2dnSSJmZWWFqVOnQqfT4fjx4zK4PCEGzbSEhAQJy6vxw9vbG8nJyZg3b57MZ2dnRyupZ8+elZGSubm5UXiXWq2WzYlXqVJFUqgJCwuTdGPFDqfx9TZl0BO/w8mTJ2lCaio9IybOxu+Vn58vkXzo3Lkzs9MnsmTyDmDAEMg4ODhw/campNFpzszpc+bk5Jid11YiVgLMB6NKhBuAYY1/Lp79cRMEgctSqdfrsXjxYvzwww9Mv5iMlixZkrkejJldWUzrc+fOpX4W86qxrEzVqlVlflMkgynj88mTJyV7hSnraEREhIRox9HRUeIvLCzEkCFDJO9hOucaExODtm3bUj9Lpi0+Ph6LFy+Gg4MD7O3tP4+m/M0tLi6O+xuLpJY8Zvtnz56haNGiEk1eYxPXfMOGDZl+sZPPuh8AA6md6F+yZInMv2fPHur/+uuvZf6IiAjqL1q0qOysELuj4t+w9KZFmRNeUvz8+XN6Zi5atIj5PcU4ok+fPky/TqejhSQlsrPk5GRs375dkbzxj5hWqzV7FvNYzj8W+5yQ/gHT6/VITExEpUqVuJtCcnIyvLy8mN1KwLBAduzYATc3N2bQk5SUhIiICJQpU0Y2YwEYkt4PHz6gdOnSTJZVQRAowxYPppeVlYWuXbtyNSjz8vIwevRoXL58menXaDT4xz/+waWRLiwsRGBgII4fP8706/V63Lx5U8Z+a2wxMTHYv38/15+Tk6P4fJ1OpwhNAcAkOjI2HuRDNHOwHqUZhuDgYEVtqMePH2PVqlXcwDg9PR1LlizhwmDz8/OxcuVKLnnArl27sG7dOqbumyAI+Oabb+Ds7Mw83NLT06kO17hx42SfUZQ3IoSgXbt2knUsCIJEPqlevXqSJOrNmzdUg5QQw7ym8b22Y8cOSRBnbW1NpSMEQcCPP/4oS+RE5IFer8fgwYNl/rZt29KE0TjQFR+VKlWiB8+LFy/orGjx4sVBiKFLaixfJHZWjEnQjA9oQRBk5GEtWrSQfE9BECQseVWqVEFOTo7sWhu/ztq1a5mFJrHb6uzszF2zIlMmr8taWFiIRYsWoVWrVkzRdcAwe758+XLufIpOp8P48eMV77urV69iyJAh3MRVpVKhffv23PfQaDSYNm0abt68yfRrtVoEBgYq7h3Pnj1j6lIaf4atW7dy/YABgq5kvOq9aLyip2gsKRZjMxeIsM4WY0tISFAsWkVERODcuXPc+ddjx47hiy++YKJq9Ho91ddkzatlZmZStnhWl+Lt27fo378/Xfem7LExMTESNIOplEhGRgZmzpxJE0Y3NzeJX6VSYfHixRLyLOMiiFarRUBAAIXzEiKX8Dl//ryk+/nNN99I/HFxcdi5cycNjh0cHGTX++rVqxQ9ZWNjIysCa7VaTJgwgb7HsWPHZNfqw4cPaNmyJRwdHVGtWjWsX79eluCfPXsWISEhir+3kj4nYH7eTqVSmS0kmfMrsa4Chj3KXDHLnF/pGgiCYNbPs/fv38PPz4+LLsrIyICfn59iTHHhwgW4uLhwv4O4h7OKQDqdjvKTsODMKpWKaohWrFhR5s/NzUWTJk1oQdg09lOpVGjatClsbW1haWkpY7jX6/Xo0KEDqlatiiJFijDfQySgFAvRpsoGu3btojPElpaWsvguJiaGogkJIfD395f4BUHAmDFj6Bgbi2QsPDyc8qsMHz5c5geAtWvXghC5FqvxtRg4cCAsLCwwb9485t+EhYXBx8cHZ86cYcaJgiBg6dKlivwCcXFx8Pb25q4HUcv0Y0Y+fU5I/4D5+PjQudBevXrJNqCjR4+iRIkS9GF6Q4WHh8PW1pYG3Nu3b5f4P3z4gDp16qBSpUoghGDEiBESf0FBATw9PSlRUMeOHWWfYfbs2ahSpQoIMcytmgawgYGBsLe3R7FixeDi4iIL/B49eoSKFSuibNmyqF+/vqwCk5ycjHr16qFixYpwdnaWdRsKCgrg4eGBKlWqoHr16kx2wFmzZqFKlSqoUqUKE/px6NAhVK1aFRUqVGDi3CMiIuDs7Ax7e3tmYJWdnY2WLVuibNmy3MBs6NChijpT/v7+qFChAjcpvXHjBipWrMglncnIyEDFihWxbt065obh4uKCYsWKcQ/ZYcOGgRDChUlv2rSJGQiJJs5i8GZtNBoNJk2axE14ExIS0L59e27h5erVq6hTpw73+/v6+qJatWpMtjyVSoUWLVrAzs6O+fkePnyIkiVLolSpUszZZVHvt3jx4ihTpoykm6/VatGnTx9aZTUVk9doNGjfvj0IMcx/2tjYSKDsgiCgX79+tPNSo0YN2eH6888/gxDDnIyLiwucnZ0l6zwvLw+1atXC1KlTsWTJEpQtWxZt2rTBw4cP6d9cu3YNhBj0OitVqkSDjb1799J7et26dbCxsUGPHj0QEBAAQRDw/PlzbN26lf7NzJkzMX78eMyaNYu7lnbv3o3t27cjJiaGGzQ9e/aMsnXzbNy4cUyyEdHEZN7CwgI9e/aUJU379++HpaUlLC0t4efnJ7svIiIiaJLv7e0t25vS0tLg4OAAKysrNG7cWFZMKSwsRKtWrWBra4uqVasyD/oxY8bA3t4e5cqVY6JAtm/fjkqVKsHW1pa5d9y+fRtOTk4oVaoUk9gkISEBLVq0gI2NDbMyrtVq0bt3b5QuXZq798ydOxcVKlTgBvmHDx9GlSpVuJICUVFRqFy5MlNnFTAEh3Xq1MGKFSu466Ffv35o164dV1pq/fr1mDZtGrfbfPPmTa6OKmBA6/Tv35/7/Hfv3mHx4sXMTgtgSF58fHzg7e3NnA9WqVRYsWIFli1bxtUz/OWXX+Dv78/VZQwODsbq1auZ5yxgCCqnTJmCGTNmMIufCQkJmDRpEpYsWcLUbdRoNPDz88P48eOZ+pqA4Szs3r07dx+PjIyEq6srd/5Uo9Ggdu3acHR05Mq+dO3aFYQYeDB++eUX2X3n4+ODEiVKcJPSHTt2oFq1atz51kuXLqFVq1aUzd/UIiIi8P3333NnF+Pj4zFs2DDu76DRaDB69GgMGDCASza0YsUK/Pjjj5I9WDS9Xo/Tp09j5MiRzHtKEAQ8efIE3377LRc5lp+fjwEDBnCL0GLHnlekF7Valdicnzx5wkQDiPb+/XvMnTuXeU/p9XqkpqZi27ZtzLWq0+mQl5eHNWvWYN++fbLrXFhYCL1ej82bNyMkJERWVBT9Bw8exIULF2TFEZ1OB61Wi4sXL2L//v04duyY7HMWFhYiPDwca9euxf3792XFdJ1Oh4SEBKxevRqhoaGy2EMQBGi1WmzevBkXL16UoQxFO3XqFAIDA7kkY5GRkdi4cSM3tsrLy8PixYu5GveAAc7frVs3brJ48OBBEGKQPpszZ46sGHPjxg1YWVnB2toaGzdulMVpcXFxlGiRJf2Vl5eHBg0aoFSpUihTpgxXu/avts8J6e80QRBkGp+mAsSmM2aenp6ShWKq8VmuXDnJBnbt2jWZtIyxHElcXJyke2RaFS0sLJTo7IlBtbGNGjVK4jeFARmL14tdF2O7cuWKBJK4bNkyif/Jkye0AkUIkQUlr1+/lszZmc7VxsbGom/fvtRvGiyo1WpJ5dnb2xumFhgYSCvPHh4esps1JiYGderUoVUu066QTqfDnDlzYGdnhxo1ajC7kHfu3MGUKVPwzTffMJkPs7OzcffuXdy9e5dZ+X306JGi1EBcXBwOHTrEDRgzMzOxb98+Rfr5w4cP/yE2QHNwECWmNp1OpyjEnJSUhDlz5nC/38WLF9GjRw/m3KMgCJg5cyZat27NrDir1Wq0b98erq6uTLbEjIwM1K9fHz/99BPevXsnC8Byc3PRtGlTpKSkYNiwYdizZ4/k8BQEAePGjYMgCMjIyEDlypVRr149bNu2jSamFy5coAd/WloamjZtCkIM86gis66HhwciIyPpc0TIU9euXRETE4O0tDTMmDFDppHr7OyMkSNHQq1WU3ZtlrEgS3/ElNYaYIAZr1u3Dvfv32euHdP9z93dXRLgnT9/XgLJ7t+/v+T3Dw8Pl+gLm7LnxsXFoWrVqtTftWtXybVJTk6mvwNrf05KSpJoIJsWHVNTUzFmzBjq79evn+T76XQ6SjRFCEHfvn1l1+DMmTN0xql79+6y9R8fH09njE2J6ABDYCnqMtatW5cJ0b5z5w769OmDatWqMaF1eXl5OHToENauXctF0aSkpJgduTBn5kYu/h1YtDmIt7k1CZiXhVF6jdzcXEXCq9DQUOh0Ou4IS3p6Ot69e6e4V4qFJp5pNBrFTsnLly8V9Vpv3rypCGP/+eefsXPnTty7d09WIC4oKMCYMWNQpkwZlCpVSlYgzczMpMRQLNRXUlIS7byx4ru4uDgas5QrV072/OTkZPr6hBBZgVStVqN3794UkcNaz/Pnz6eFLtaZ++TJE6r5yCviiMU2nl+tVmPRokXcJCU5ORn79+/nrnmtVosDBw58FEQzv9fM3e/mOtxpaWlm9wRzr/FnjnmZey2lvUmMDXgWFxeHs2fPcl/jypUrqFy5MsqUKQNra2t4enpKCqQhISGScZ25c+dKnv/27VvJyIBIqvqx2eeE9HeYVquVBCLiQ+zAabVaTJ06VUK6Ij4CAwOh1+uxfPly2vk0fohd0D179siEbMVNXKfT4ebNmxLxZvFRo0YN5OfnIzk5Ge7u7jJ/hQoVKOOWMb7e+DuISfGpU6foULr4sLW1pQlZdHS05HAghEg6ARqNBkuWLJGwCxcrVkwibXHnzh2JzIaVlZUkaMrLy8PmzZsl8himld1Xr15hwoQJFDppCvvS6/WULa5IkSJMooeCggKcPn0aAwYMYFavAUPQFRoaqphYfbbfb+aCWiX4kiAIOHr0KNeflZXFJDsRLTo6GkePHsWwYcOwe/duWaAj3hNXrlyBhYUFypQpg1GjRuHmzZsQBEHy2Y0ZeO3t7bFgwQIkJSVJ/uby5cv0b4oUKYKxY8fi/v37kkMvLS2NkqCULFkS/v7+zGBZZDJ0c3NThGZ6eXlxuxLG9t+al8zLy0NSUhKioqIQFhaGmzdvUgIOQRAQFBSEefPmoWvXrrSo5eXlhYKCAuj1emzatAnu7u6Sop0IxxQEAdu3b5eRShnLdVy8eFGmkWyMUomLi8OsWbMkguTGBT+9Xo+TJ0/Czc2N+kUhctESExMxc+ZMmjiz5K4uX76Mjh07ghDChFPl5eVhy5YtqFOnDhcanJKSgg0bNjDnCkUrLCw0C+391E1pDxEEQfH+EARBET4uCAJmz56t+P5t2rRRDJJXrlyJEydOcP16vd7saMnHYHq9Hs+fP8eJEydk11ytVmPTpk2oXLkyc8wmKiqKFoJYiff169dpkYbVkb9y5QqNrViInBcvXlBCOlZXTKPR0KSYB6UXO1Y8khqxCLpu3TqmXzSlMZ1P3czN5h87dkzxLNm4cSMXFQIYEAlKRVSNRmP2flSSVgIMXeRPkZvEmNdAEARcu3YNixYtQseOHWnMIDIXi+g301h+ypQpf+VXYNrnhPR3miAIuH37NgYNGiSpTIhV7vz8fGzdupV23owTwrS0NGRmZmL58uUyDVEx4crPz8fGjRvpbJ7xY/v27RAEARcvXpRIvYgPcSbgw4cPmDNnjqSLYLwQBUHAhQsXZK9h3IVMT0/HokWLJNUVUzjRjRs3JN3i/v37S/w5OTlYvXo17eZ269ZNtgmEh4dj4MCBsLS0lMzwiSbOerm6uuKLL75gdsoyMjKwZs0atGrVirtZJiUlwd/fnwkNNv68/07F/7N9Wpaamorx48dj1apVuHnzJrNTEhQURBOUZs2aYeHChbh3755kPfj6+krul1q1amHhwoWSQovxTJtYiBk2bJiEeMEUYVGiRAn4+PhI1q5p4atly5ay7sj9+/epv1KlStx5SfFz82Y+RQsJCWHqof6VJggC4uLiEBQUJEGJAIbASCwmVKxYUZa0vXjxAgsWLICjoyMsLS1lUMPo6GjMmzcPFStWRMmSJWVkMjk5Odi4cSOcnJxQqVIlWaVbEARcvXoVHh4ecHJyYhYN0tLS4OvrixYtWnDnckNDQzFlyhRuh06v1+PGjRv/swRL5r73gwcPFHU5L126hG3btnH9V65cYWrQihYSEqJI9BUeHg5CCDep1Wq1qF69OpdEBjDsPzzGUdHMEQx+LKZSqXD06FEurHbSpElcSOr9+/dRrlw57u915MgRWFhYcP3nzp2DhYUFF2Ypku0pzX5PnDhRUQpEEATuXvt3MHPalPPnz1cksxwxYoTi7Py0adO4JGaAoVNfp04dbtcwJiYGNjY2isRdzZo1444yAAaUDo8bRTQlluKP0QoKCnD37l2sXLlSMuahUqlw5MgR9OzZkxZxeTDmv8o+J6R/giUlJcHPz48mj8bkNDqdDqdOncLXX39Ng0bj4ej8/Hxs3rwZNWrUoH7jWU6NRoPt27dLOoR2dnZ0TkYMhjp06ED9xYsXl2DE09LSsGDBAlo1tLKyksxCiq8hdlQtLCxkulFZWVlYvnw5xamz5k9CQ0PRo0cPEEIkpC6iqVQqbN68GQ4ODlyx5devX+PHH3/kkowIgmBWckar1SrqDH62T9fMBaV79uzBDz/8gBUrVuD06dOIioqSJJPPnz+nRaAiRYqgWbNmmDBhAg4cOIA3b95AEASqjWb8KF++PL777jsEBgbiw4cPdO7U9NGyZUts27YN8fHxkiKO8aNHjx7IyMhAWFgY029nZ0c7dc+fP5f5RWZEEXIjCIKEbVBEAbBm2gkxEEAcOXKEew0PHjwILy+v3/sT/aWm1+sRHh7ODGJETWg/Pz/mXFVBQQEOHz6MBQsWMNeZTqfDyZMnuXJYgAF6r6Txmp2drcjEKH7Ozya3HTt2KN7/ffv2VZRd6NatGyZNmsT1e3l5oXXr1ly/OEvOI4ASZWNYM6rAv+YCWdBt4F/kZm3btuV+BpVKxZ0v/RSNp08JGGb3lFAtmzZtko34GNvq1au5JDKAgbzJGDFhagUFBTLEw9/JzJEwTpw4UXHEp0ePHorFFQ8PD9SrV4+bUIoNCB48XRx34M3J3rp1C4QQTJ48mfsZypcvz9UlBoA5c+bg66+/5u65ubm5aN26teKe/Pz5809uz05NTcXWrVvxzTfffFTzpH96QkoIqU4IuUYIeUEIeUYImfLPf19MCEkghDz+56O7udf6VBJS0bRaLU6cOAEvLy9mdSk0NBT9+/eHlZWVjFWxsLAQe/fuRYMGDUAIkWmEin4Rxjt27FjZ69++fZsSErAoqjMzMympCo8Q4NatW/Dw8EDLli2Zh39ubi7Wrl2rOKAdFhYGX19frr+goICZsBqb0pzOZ/t7W3x8PE6ePIl79+7h3bt3ko5Sfn4+Ro0ahS+//BI9e/bEhAkTsHr1ahw5cgShoaFITEyUdTCLFy+OL7/8EgMHDsSSJUuwZs0abrJYoUIF9OrVi8m+KxZzZsyYgZiYGMlstPgYMGAAPWBFsiPjx9ChQyUzxKZSD6VKlcLRo0clXTJPT0/Z69SuXRv+/v70HhYZFY0fw4cPlyReL168kCSt586dY15/UQKDR1AlWl5enmJH6rN9tv+PmXamjU2lUqFKlSrcZF4s3PBIj0R/p06dmP7Y2FhYWlqiZMmSzHMvISGBciWwNEizsrLoyAiPcEiUbKlTpw7Tf+PGDYpy4NnatWtRr149rh8Al3jqUzRzsFAltl+xeK1kH1Mw/mebObjwxIkTFSVIOnXqpJjsubi4oEyZMtwuacOGDUEI4cJmxfuBR14looNq1KjBRJUcOnSIoo9Y8XZ+fj4973iFj4EDB4IQQpn5Te3x48cghHAVKABDp9icQsPHOK8p2sf02f4TCWkVQkjTf/63LSHkNSGk4T8T0pn/7uvgE0xIjc34RzZN/KKjoxEQEEAPPmONTr1ej1OnTqFz586SeRdxY9bpdDhy5AhcXV0lUATjTeH+/fvo0aOHZDM2nmvJzs7GP/7xD8lNZtoxCA0NlQQIpsmlSqWSsFp+ahWiz/bHTa/XIy4ujgmfBgwQtzVr1iAwMBDXr19HVFQUhck+ffoU7du3x9dff43+/ftj8uTJWLFiBfbs2YOEhARs3rxZQpZlb28PFxcXeHh44OTJk1yNUUIIBg8eDH9/f67fw8MDISEhktlA8eHg4IBbt26hsLBQIuMgPqZOnUrv23PnzjFfW+ygCIIgQS6ICadxIhgdHS2bNf/++++RnJxMizIXL16U+MuVK4eoqCikp6fTAP3mzZvc7yq+jlarpWQehBgkclgHrViZbtKkiWJHatKkSYqd1v+WfdYv/vQtOTkZgwYN4vpF1AIvsBw6dCgIITIGbNHE7mXlypWZfuP9hAVXX7JkCfWzumoiyzkhBI0bN5b5jdEQFhYWzHGB7t27079hJWLZ2dmwt7dH6dKlmd8BMIzY8JLuz/a/ZTNnzlSUzunQoYPiHGGtWrVgbW3NLQKJ5yevSyoi8pycnJgxgpOTE13vLFhtz549qZ+FOlizZg31jxkzRuZ/9eoV9ZvKLInWokULEGIg1GPZ8ePH6TnKs2+++UZx7wIMrM6fzbz96Qmp7ImEnCaEdPm7JqRJSUlmqyMLFy5UDOx27dqF4OBgyb8JgoCcnBw6O2UK09Hr9VS2QdR0Mr3pjWG9AwYMkMFYjQO1GTNmKFbLNm7ciFevXnH9p0+fZgoTi/b48WNFLH5qaqpsNszYCgoKmBTtogmCgJcvX3L9AMyKhP87umZK9kcC3zdv3ihen5SUFMWuslarxblz5xSZ3i5fvsw8XHJzcxEfH4+XL1/K1ml6ejpmz56NGTNmYOnSpbI1cvToUZQqVQrly5eHi4uLZGZEp9NJBOnFDqH4GRMTE9GqVSuJ35gp9erVqxQiLj5cXV1p93Dv3r2S+W2xuyAWUg4ePChjqS5SpAglPwoNDaXkGeLDysoKU6dOhSAIyMrKolVe40f79u0p++GsWbNAiEGrTXyvypUr07X6+vVrWFtbo2XLlpRgx9LSEsOGDaNzzFOnToWFhYVE83TQoEFo2bIlIiIiIAgCGjZsCBsbG4qQqFu3LlJTU9G8eXM8fvwYOp1ORpJ24cIFCIKAK1eu0CRZ1G0jhKB3795Yt26dbM2IrNUWFhZceKooU8PSOhTt9u3b+OWXX7Bu3TpmtV6v1+PIkSOKe+OlS5cU9xXAMBurdO9t27ZNESb76NEjxb1HpVLJ9mdTU4LpAsrdP8B8N8McM6w59tk/sjelpKTg2rVr3NfIz8/H+fPnuX5BEBAcHKzIGDps2DCmxihg6MSLMHsW6VNsbCy991q2bCnzp6amUqIPQojsc2g0Gsm9Y0qOJs5+igUyUzZlQRDQoEED+h5FihSRdXSGDh0q4XIwTawjIiIkexkr8TZGfvDWw/fff49GjRoxfYABBqt0P3348MGsxuhnM2/JycmK11GtViM4OJiLIhMEAefPn1dEit28eVNxX3N3d4efnx/XX61aNZQoUYI53lRYWEjXO4s4KCsrS1IgNe2S5uTkSAqfO3bskH0/a2trEGIgymQljCLxlbW1NRwdHWXXwhgVZG9vLyNIMiYOtLGxYaJ5xPuexS0A/EtSjhDCjT+rVq2KokWLcn+LmJgYlClThrtHC4KAc+fOKaIBrl+/ztWYF40nmWVsSjH8x2D/0YSUEOJICIkjhJT+Z0L6jhASSQjZRQgpZ+75H3tCevDgQXTq1ImLMX/w4AH69u0rCYKNLTExER06dICrqyuaNWsmew21Wo1evXrBw8MDFhYWMjITkfVPrKzu3LlT9h4HDhxAt27dYGVlJaOCBgzd1M6dO6NChQpM/bX4+Hh4enqifv36GDx4sMyvUqkwePBgtGjRgjl3JggC5s2bhw4dOqB79+4yP2DQI+zatSs6d+7M9IeGhsLLy4tbxYqPj8eIESO4fpVKhXnz5nFfXxAEbNq0Cb1792b6AQPZhKkOrLGFh4crzrtkZWUpVsm+/PJLFC9enHsADR8+HISwaewBICAgAIQQJoMwANy7dw+EECZhRnh4ONq2bYuGDRsyn/vu3Tu0aNEC1tbWzIrr48ePUbNmTVhaWuLXX3+V+QMDA+nhY3q4aTQajBw5km76pr9hdHQ0FYMnxACpNQ72bt68KUtajQsT58+flwSjhBAJc9+tW7co1E5koROZWgHDYVKxYkWULl0avr6+KFKkiER+o7CwEC1btsSUKVNw79491KhRA5UqVcLcuXPpb7lixQqsWrUKeXl56N27N4oXLw5fX184ODjg3LlzSE1NRa9evQAY5uREMo7Ro0ejePHiCAgIwPbt2zFq1Ci8efMG5cuXx4gRI1BQUIDhw4ejZMmSOHXqFMaOHYsiRYqgZcuWcHd3pzNC9+7dQ4M7HgvlAAAgAElEQVQGDZCYmEj1/VxdXWXd0dzcXAiCgBUrVmDGjBk4ePAgl0AlMjISP/74o2KRRGQS5wVmV65cgY2NDVxdXZnEEgkJCahfvz7KlSvHLNZoNBr07dsXVlZWshEHwHBfT5gwAXXq1IGXlxdzjw4ICEDr1q0pe7mpXb16Fd27d+fOQr158wbDhw+Hs7Mz05+VlYU5c+agYcOGTL9Op8OqVavQqlUrbsCyd+9emaSNsV2/fh2DBw/m+mNjYzF69Ghu4i/KWvHeX5yd5OmgioWUAwcOMP0XLlwAIQTTp09n+gsLC7FhwwYsXLiQ6U9KSsLhw4cxffp05v4SGxuL69evY/To0Vi6dKnM//79e0RERGDw4MH46aefZJDWlJQUREdHY/jw4dixY4eMBTcjIwNv3ryBj48PNmzYIGNWzc3NxevXrxEQEIDp06dj9+7dMjbjp0+f4vz58+jfvz/OnTsng5LGxsbi5cuXGDx4MHbu3Mm8r54/f45Zs2Zh1qxZTIhiQUEBNm/ezL3OgiCgWrVqsLe3564VkfGeV0ApKCjA2bNnuRIW+fn5CAkJ4RLJZGdn4969e7h27ZpMNxgwFEAjIyNx9+5dZqf6w4cPePPmDc6fP8+E26alpSEuLg4HDhzAhw8fmEXk169f49ChQ0hKSmIm9tHR0bhy5QpevXrFJSC7desWV2cV+JeWK29Oc/78+SCETypz4sQJEEKwYMECpj8mJgaEGAgieebj48MlsCsoKMD06dOxatUq5nVMSEjAwoULMXXqVISFhcn8r169wsqVK+Ht7Y1Xr17JCmpRUVFYsWIFvL29cevWLRm7dUZGBqZMmYLx48dj7969SE1Nle1PY8aMga+vL3x9fWWIPMCAWtiwYQNGjBiBvLw8WaEpKCgIW7Zsgbe3N96+fStrSGg0Gvj4+GDYsGG4ffs287fatWsX5s6di0OHDjHXY15eHnx8fLBixQpusvf48WNMmzaNm1CK0GPW3gX8q9OrFJ9mZmbCw8ODuyYLCwvh4+MDZ2dn5n33sdh/LCElhJQihDwihPT95/9XIoRYEUIsCSHLCSG7OM8bTQh5SAh5WKNGjf/SZfj/W3Z2tkR2hUXSIyYRhBBmQGNKnmJa/f31118lflP22tevX0uCbVOsvSiCLfpLlCghI2QQMfRiZde0yrR+/Xrqt7CwkB3m169fl3xG04Po3bt3Erpp04QqNTVV0oUy7TYnJydLtABN59qysrIklTLTWQBBELB161bqZx304eHhFH7CmjlRqVQUvsmaHwIMm0rFihURFBTE9CcmJsLHx4fbTT9y5AjWrFnD9AEGpreZM2dyE9aYmBhMmTKFqbMJGDakWbNmccmgBEHgBpyA4QBT6hKlpqZi1apV3KD34cOHGDBgADMAEAQBW7ZsgYuLC3PTzsvLw7fffotq1aoxq/tRUVGoV68eKlSowCShuHv3LsqVKwc7Ozvs3btXFoxduXIF1tbWWLVqFU6ePCk72O7du4fmzZsDMCRix48fx9GjR+nrxMTE0CA2PT0dYWFhGDVqFKpVq4Z9+/ZBo9HQAFKn0+HRo0coKChAlSpVQAjBkCFDJAGgOIN69+5dum579uxJ7524uDiaXJ06dYr+zfDhwzFx4kRkZWVJfgeNRoNixYqhbt26OHz4MAoKCpjJWWRkpGQu9Y9aWlqaIiPopUuXULduXbRp0wZ9+vTBiRMnJO99+fJlynhsa2srY7R8+vQphSCz5vJTUlIkxQpTCQG1Wi3Ze0yr+Pn5+ZSkjeXPzMzEhAkTqN+0m6xSqSRdb1bCFhgYSCHbLEbKZ8+eUS1VVlGzoKCA7o882SNRvstUJ1u0jIwMzJw5k1vMunLlCnx8fLizRlFRUZg6dSpXUiU/Px/Tp09nBrafipkjUzPHSPqxMOPu2rVLkWk4JCQE8+fP5yZiBQUFaNasGfesiImJQfHixblQ0Lt376JIkSIoUaIEMykW92Ie8dqDBw9QokQJFCtWjEnulJmZSeMNV1dX5l4mEtLVqFGDmbCKyaCTkxN3L/Tw8ICnpyfTBxiKMAsXLuTeM5GRkZg2bRoXUpucnIypU6dyCX8KCwsxf/58szOyf5UpnSGCICj6xU4f72/E88vce3wqJv7WvCJQYWEh5s2bx51zBQyIJRsbG9SqVYupIHH06FGKIuEV/j4G+48kpISQooSQi4SQ6Ry/IyHkqbnX+Zg7pHv37kXlypVpsNGoUSO6wQqCQEXtjR9iwCIIAlatWiUjVvniiy/owbd792588cUXstd4/PgxAMPB4e7uLpmzM+6QRUdH45tvvpHNp4nVU7VajREjRkhmyggxQCpF27Ztm8xvPIAeHh5Og2rjwFm07Oxs9OnTR+Lv2rUr9YtagcZBo+n8y5s3b+Dl5UX97du3l/j1ej32799PGY7btGkj24w+fPiA8ePHw8rKCm5ubszN6vbt2/j666+5c3NarRb79+9Hnz59uNBdjUaDS5cufVKb4X/TzInWK0HJBEFQpODPyMhgEnmJ9uTJE3z55Zdc/4ULF2g1+dGjR7LDwbg6qtfr0bJlS9StWxe7du1irofY2FgKwWvevDmTldrPz0/S+T18+LBk7QiCIJGNql69uqygkZeXJ7lH+/Xrx7zOolams7MzF5qfkpICKysrxYPP+LP9p+3OnTtYv349hg4diiZNmqBcuXJUiF6v12PdunVo1KgR/e729va0yq3X6+Hr6yuBZNvZ2dEquYiKMN6Dy5cvL+n8hISESPbgKlWqSAoqKSkpGD16NE2aWV3S06dPo2bNmrL9XbSMjAw639i0aVPmdb169Srq1avHRNEAhn1nxYoVaN26NTdxSklJgb+/v6Kc1d9Z6oqXYImmNK4CGJALSmt+3LhxihqnM2bMUNRcfPDgwSdzbkRFRSmOx0ycOJFqIJqaIAho3rw53NzcmH69Xg8HBwcQQphJvCAIVJGApXEKgCoazJkzh+lfuHAhCGHPHQKGQpqFhQX3+QDg7++vmNj/L1t0dLQiUc7169cRHh7O9f/2229MtJ9oOTk5mDVrltkxDSW/OO72d7LMzExs3bqVGSfFxMRg5MiRsLKygrW1tVmG5b/K/vSElBBiQQjZRwjxN/n3Kkb/PY0Qctjca33MCSlgCAb9/Pxo0LNnzx6J/86dO2jZsiUNaGrWrEkPRp1Oh507d8rmvkS5E41Gg7Vr18qIV8S2vU6nw65duyRJMSEEVatWpRWm+/fvo3Xr1hK/tbU13eizs7Mxd+5cSUBraWkpqX5evnwZLi4uktcw3kwyMjIwbdo0yayeKbzuwoULlD2YECLr0onwDfE1WNpeV69epdBNVsCcl5eHxYsXo0SJEjRoNbUXL16gd+/eXMkZQRDw66+/KlbytVqt2cTqs/01Zm6OTuy+JiUlMZNIMSDPzs6Gk5MT2rVrh927dzMhLo8ePYKlpSWttG/evFm2LsaPHy+5bwYMGCDpYKekpMgKPr1795YEYsYdNvH+XLp0qSR5MCZDIYTAzc1N1mmePHky9Ts6OjI76Xq9HlZWVrC3t+d22kX7K/TLCgsLqTSPsb148QLLli1DkyZN0LRpU8nvkJ2djYCAANSvX59eX+PnZ2dnS+SsJk6cKHltnU6HPXv2UFkdFuw+PDwc7dq1Y3ZJAUOH0MfHB0WLFuXuPXfu3IGLiwsXAq3RaODn56cIE3z//r0iicnf2czxOPDgcKINGTJEUZu6e/fuzPlV0bp166aoHzpkyBCu3AtgmFVTkhP6lFjnk5KSZLBnY9u3bx9+/PFHrn/u3LlwcnLi+sUZd97MntgM4M2Fi/PvSizijRs3psV/lkVFRX00Xe8/28wVpp49e6bIdxEeHo4BAwZwXycqKgoVK1bkal3n5ubCysqKi/gADIRLSvOxw4YNw7Rp07hJ57Fjx+Dr68t9vlarxdmzZ7n+T9XevHmDYcOGYciQIX/1R2HafyIh/fqfgU8kMZJ4IYTsJ4Q8+ee/nzFOUHmPjz0hFe3Dhw+YOHEiateuLavECoKAo0ePolatWiCEyISac3JyMH/+fDpjV7duXUlgnZKSQrt7YkBpTHiQm5sreT4hBP7+/pL3P3z4MK3Ss4Ku6OhoDBgwgPq9vb0lfp1Ohx07dqBixYoghNB5N2N79eoVevXqBULYcw2FhYXYvHkz7Ozs0KVLF+Z1fPHiBbp164YOHTow/TqdDtu2bUO/fv24G8379++50DPR/q4HyWczmLkDNT4+Ho0aNUKfPn2wdetWZufi3r179J4rWbIkhg8fjps3b0rWnTFckxADsdGKFStoYBsfHy9LOIsXL4558+ZRAq0RI0bIUBBlypTBzz//DEEQEBsbSztwxg93d3fakdm2bZvM7+DgIIHPHzx4UOKvXr06EyIkwkNdXV0ViXScnZ0/yuTn7du3zO6NIAgICQlBnz59mNDY3NxcrFmzhgsLV6vVWLt2LZycnJjkPOI+37FjR25h5OXLl1i4cCF37yosLDRLjvR37mIqmTl5j0aNGil2QatUqaJIXOXi4qKoqdikSRM0bNiQe/2bNWsGS0tLGc+DaCL0m5cE+fn5wc7OjqtxevHixY9OxF7JlNapRqNRZOd+9uwZfvjhB67/1q1bcHV15frDwsJQpUoVLlpArVbDyclJ8TPu3Lnzb9dBE02n0yl+t9TUVEU0Uk5ODsqXL89d6yqVChYWFhgzZgzzfXQ6HaytrVGzZk0uqsDR0RFFixbljgmJDLzGsa6xiaNmvKQzKiqKW2AUzc3NTfGeu3DhwicbS75+/frfIkH6b9ufnpD+mY9PJSEVLSoqiov512g0WL9+PRo2bMgM9OLi4vDdd99xq+zPnj2jeoSshC82NhaDBg0CIQamUdP3UKvVWLFiBWxtbVGsWDEmROnOnTtwc3ODhYUFnjx5IvMbd1R5FTKxo8qbVUxPT8ekSZMUA69z584pzuRkZmaahWB9tr+v6XQ6Rcbj5ORkeHp6wsPDAzNmzMCePXvw8OFDSecsMjKS0tKLcMvx48fj9OnTNFlkwe5r166NZcuWIS4uDhkZGZT90zShXLBgAVJTU5n6oIQQeHp6IjMzExERETJf165d4e/vTxO+jh07SvwdO3bEkSNH6D0cHx8ve43mzZtj2LBhyMzMhCAIePv2rexvqlatKiNiEJkNCTHI57ACCpVKBUIIfHx8zP5W5pip/wpTYjNUqVSK1f/MzEzFWWuVSqX4+uZmn/5XTakDqNfr0aBBA+5ayszMBCEEW7duZfoLCwthYWHBLYQCgL29PWxtbZmMowAoEskUBSWaCCM1HlkxNhFG+uWXXzIToUWLFtF7jmUPHjxA6dKluXNmOTk5ZlniPyYzdw/wSJEAw/7PS0TE1+bp0Yp25swZRb+5meGP2cztMVqtFjNnzlRMyB0cHPDTTz9x/Y6OjqhatSpXx9XZ2RmEEMyfP5/pF9neGzZsyLznxAKOjY0Nc9zFWKZp165dMn9ISAj1r169WubX6/UU2bhhwwbmZxw1ahSKFCnCRUaEhobC2dlZEf5648aNz/v9/8M+J6T/ZUtPT1eEw/3222/44YcfuBj84OBgNGzYkJvw3b17Fy1atOAS5CQnJ2PUqFEYN24c06/X63HgwAEJ06ipxcTEMDcB0bRaLSIjI7l+4OMS4/1sH589fPgQx44dw+nTpxEcHIwrV67g9u3b+O2335CYmIjFixfD3t4e9evXR7t27dC/f39MmDABS5YsocREosaYMdy1bt26GDhwIBITExESEiKThSHEQO61evVqaLVauLu7MxPK+vXr4/nz59izZ4/M5+bmhoMHD0KlUiEpKUnG8mt6b5pqlfbq1YsGC+np6fjll1/o5yfEQLMvHoJ5eXk4dOgQlZQRH8bBxKFDh5CRkYHy5ctL/sbKygr169eXkCSZwn/Xrl0r+21evHgBQgxEQ0pSHnl5efjHP/7xh9fCZ/v7mxJDeXJyMghhs8gDhuISIQTVqlVjVv1jY2Ppembp7qrVauqfNWuWzK/T6STwfBYKyhihxOrmGo+9sGYPRdZVQgiTmE0sKDVp0oT5HXU6HTp16qQoA/J3MnOFro+x+/PfMlHZQKnI06VLFwwePJh7HcWEkMfSK7IxOzk5MYkIRbQcIYTJgD548GDJeWlaTJkzZ46kwGs6cyoy04rnoqn8WEpKiuQcYxWr2rRpwzwvRdu+fTuNB1hklQUFBbC2tkb16tW58ONFixZh8uTJism/OUmv/yX7nJD+Qft3qh9KQRsA2c0mCIJko0hNTZUkoFqtVjbfYJwgCoIgI9fZvn275P+fP38uuUmOHTsmuTHUarXk7+/cuaOolffu3TtFYoj8/HxFUgdBEPD+/XuuH4BM68rUzHVNP+Wq559h5tYqb4ZK/G0uXbokmafMysrClStXcOTIEQQEBGDx4sUSra6QkBCMGjUKQ4YMQZ8+fdClSxcqcJ2bm4uJEyeifPnyKFu2LGxtbWFjYwNPT08UFBRApVJJ5h7FR+PGjen9dObMGUmXkxADsY0ouZCTkyNL9gghksNl7969Mv/48ePptYqPj4ednZ3E36BBA3qt9Hq95GATD2njTsbMmTNBCKE6hEWKFKGzhG/fvsXu3btBCMGkSZMoTHjGjBkADPPV3bt3R6lSpXDw4EE6i+3m5kaLOvXr10f//v3h4OBA36tUqVK08LVv3z60adMG3bp1k3xOY1KQe/fu4eHDhxIIsYODA9zd3WXQrODgYPo3PEiUXq9Hv379FAtb5mZ+AZjVXgPAhY6JFhYWprj2s7OzzbKkmiO9Mbc3mSvAfcxVdLVazZX5EM2cxrNSoqTX61G0aFHu7P6DBw9oMsi6jufOnaPrcfPmzTK/MVt127ZtZdc6Ojqa+m1sbGRrLikpSXLfmMIZjTUXCSFo0aKF7D3EGWQLCwtUqFBBtl6MA/CaNWvKkomMjAzqHz16NPM69enTB05OTjLJGcCwvm7duqU4J/vZ/rtm7p7h+QVBwMqVK7loPMCgj/3FF19wE6WlS5fS4icreReJnywsLJjs4Mbr9auvvpKhQoz1x6tVqyYrshijjxwcHDBjxgzJPbN//37qr1ixInr37i1Zu0+fPqX+kiVLwt3dXbbujflZmjdvLkPlGY/cODo6yljaHz16JEmKWXD7tm3bghCD9ripAgVggJcTYiAD5RVJ5s2bx9QdNraMjAzFMyQ7O/ujlnP5d+1zQvoHLDIyErNnz+YutKSkJPz0008S5lpjU6vV2LJlC5o3b86EiQmCgA0bNmDKlClMjU/AQFG+atUq2NjYMKEPjx49wrp161CqVCmm1l9iYiKWL1+OL774glm5FaULevTogWXLljE/Y0BAAEaNGsXUOQUMBChz587F5MmTmf5Hjx5hxYoVGDt2LNOfmJiIbdu2cQ/i/Px8HD16lEs1r9frcenSJUUYz4MHD7B9+3au/+XLlzh37hzXn5iYqLip5OXlceEtgKFooQT1e/nypeIBFhoayn1/nU6HrVu3MpkPk5OTsWbNGrRp0watWrWS+c+ePUvnn0uVKiUJTMW5ORGeQ4hctufMmTNwdHTkdgdPnTpF5xbFA9LYLl26RBmUCSEoW7aspFjz6tUriXQHIdIZa7VaTedNeJ9BPJx5nyEoKEjid3R0lBSZHj9+DEtLS9SqVQuVK1eGjY0NLSC9ePECT548QcmSJXHhwgVaWRYD56ysLNSpUwdff/01dDodtmzZAkKIRFeybt26aNiwIVQqFZ4+fYoSJUrgq6++okH+wIEDYWlpialTp6KgoAAuLi6oVq0aJcAJCwsDIQR16tRB7dq1MX78eJQsWVJSNY6KikLVqlUxadIktG7dGmXKlMG0adNk6wEwMIB7eXmhZ8+eOHnyJDOZio2NRadOnRShdefPn0fFihXh5eXFhMHm5OSgTZs2WL58OfM9BEGAv78/atasyU2YDhw4gPbt28sq6KLduHEDkydPxoQJE5j+mJgYbNiwgSncDhgCgcDAQPTo0YPp1+l0OHfuHIYNG8b0AwYtXSUq/sePHyuyTr57945LlgQY1hiLKE40rVarmNSPGDECVlZWXGja1q1bYWFhwdQIBQzFTCsrK+6MZmpqKpo0acJlTf3111/h7u6OSZMmMQPs3bt3o2fPnujfvz8Tinn8+HF8++23aNy4MYKDg2XJ4O3btzFo0CA4Ozvj1KlTskA/LCwMAwYMQO3atbF9+3YZsdTbt2/RsWNHNG/eHLNmzcLTp09lHR9XV1d4eHigZ8+eSEpKkiXoM2fOhIeHB5o1a4bY2FjZWa7X61G3bl04OTnh/v37zM7W5s2bUb16ddy/f59xFQ3fs2zZstwij16vR0BAgOJs+NWrVxURXiEhIYqJ0vnz5xEREcEtDgcFBeHx48fcrlFQUBAiIiK4n/H69et4+PAhF9qs1WoRFBSEhw8fcotAt27dwtOnT7ldLUEQcP78ecUC+KNHjxSLOGvWrIGlpaUsCRItJCQElpaWTIQKYCBmqlmzJjcJ+e2331C6dGkuNPnq1asoV64c/Pz8mFDvEydOoHLlyhgwYAAzLtm/fz8cHR1Ru3Zt5m+1b98+1KlTB/b29szYNigoCDVq1ICdnR1+/vlnmT88PBylSpVCzZo1ZZwngKFDXqxYMTRo0ABt27Zl/lZdunRBvXr14OzszCyI7dy5E05OTrC3t2cWwwoKCmBrawsHBwcuwdHcuXNRoUIFrF27lpkwFhYWomrVqvj++++5jamTJ0+iS5cu3IQzISEBVlZW3DNEq9XC0dERjRo1YvoBw5oVNc8/ZvuckP5Oe/LkCe1WiMy4xqbRaOhMZ/HixZnJ4saNG2mQy9LUMq78Wlpayg6CqKgoCiUiRD6grVKpJCy83bt3l72HKOBMiAGGaHpQLFmyhPqrVKkiu2mMsfp2dnYyptGUlBQKZypdurRsA9VqtahXrx5NeEw3x/z8fPTt25f6TZ+fmZmJWbNmgRADhNC0sqzT6eh1Llu2LPMQCQkJgbW1NSpWrMjs2nz48AFOTk5cXTJBEDBy5EgulT1gCIqUiBpWr16NRYsWcf3e3t5cVrnExEQ0btyYCY0RBAG7du3C0KFDmQmpIAiIjIzEqlWraFfO1PLz87F161Z4eXkxr09BQQH8/f3x1VdfMQ9hlUoFX19fVK1alRkoZGVlYezYsShatCiTRTQjIwPe3t7cey0nJwfffvstCDHMi5j+RoWFhfReXLRokWyNCIJAO4MrV65kdsvGjRsHQgwQJuOENyYmBmq1GlOmTIGPjw+io6Ml2nDp6elwcnLCwoULodPpoFarZUFC48aNUa1aNTrPGRwcLPkO4my5p6cn1Go17t27J1nHq1evBiEGCG5QUBCioqIkQbdKpaL7RMeOHZGens4UCSfEMEv7/v17LtwrJCTk/wULVKrqJiQkYMOGDdzu4o0bN+jeMmbMGNnae/XqFYVc9+3bV/a7Z2Vl0Q56zZo1ZXuTGOSLe7RpoC4IgkSH1DQZ0mg0mDZtGvWbzuPm5ORIdJxNC1KCIGD//v2UtIqVKNy6dQsVKlSAlZUV897KyMhA48aNYW1tzQ2QZ8+ejQoVKnAD8BcvXqBt27ZMHwD8/PPP8PT05Aa/169fR9u2bbljGrGxsWjXrh03qDPXHTaHbDHXaTcH7zSHrMnPz+d+RkEQkJeXx/0M4vPS0tIUv+eHDx/MXofk5GSzZDTmSK+USFju3LmDVatWcZFK4v3i7e3N/U06dOiAkiVLckmounTpAkIIpkyZwvxdevToAUtLS/To0YM5Rzp8+HAUKVIErq6uzCLThg0bUKRIEdjZ2WHHjh2y65GYmEj3whUrVjD3J/EsmDlzJvN7vnv3DoQQZoEeMPzmzZo142qSAwaSqrZt28r2DNFevXqFtm3bKuqMKiHvBEFQ3Kfz8/MVC9xi0YS33t68eYPExETuvfXixQu8ffuW26yJjo7G/fv3ueeMWq3G4cOHJXuO6Wzsrl27kJuby/2MR44cQW5uLvczPn36FP/H3nVHRXG97dmloygI9gJiVySW2BV711hQCfYusaCi0dh7Q41dg4qxl1ij2EVFjQrWiChYsVFEUTosu/N8f+y5NzM7987ml/ZpwnvOnpOTV3ZnZ+fe+5bnfZ6YmBhV1YRz586p7g+RkZFmIbfSkRiWZWdnq+5xHz58QPv27RU62FIbPnw4lXRkWXh4ODQaDTP5/5QsLyH9g5aWloZBgwZBEAS0adNG4T9z5oxMo9O00rVv3z7Z3Im1tbWMYe/gwYMyjT0pjA8wVrg6dOhAtQ4JNIIsvujoaPTp00ehdUoYKFNTUzFixAhZd0oQBMpqJooiFi1aJGPnFQQBu3btotdw9uxZqhlGXtIHPi4ujg6vk5e0C6vX6xVMpaZdypMnT8qgF6YLKiUlhQbsgiAwxd9Pnz5NGYIPHDig8GdkZKB///4QBIHZRQaMwXHhwoW5+lnZ2dno27evKqyZ10EAjM8Lj2HRYDAgODiYu6klJCT8LvjjnzVzAZM5Uo0nT56oXuelS5dUoY+7d+/mdmkIjImnj6fX6zF8+HAuNFOn06Ft27aKw4ccqJmZmWjWrJniHrx69Qr16tXD/fv3uQF53bp14eTkxO1SEXmYIkWKMBleV69eTZ/v1q1bKw5QaVHIysqKGfiTxEsQBAwZMoT5W5LiVdeuXbkH5L59+9CtW7d/BGIaHx+P8+fPY+PGjZg0aRK2bNlCP1cURWzevFmmEypl19br9ZgwYYKMoVha0DEYDBTeTF6mHeH169fL9ldTBEZ4eDjc3d2p3xQhkpWVRTVGBUFgztNeuHCBzvay5pwyMzPh4+MDQRC4zKShoaFwcHBgzkcCxr2pa9euTCin9Lv8G0cazD2n5iS8njx5orqvHTlyhJtUAEYGbLWuBI9E6VO0c+fOYenSpdw9XK/XI3/+/BgxYqmUFx8AACAASURBVAT3WapQoQK0Wi23OFGnTh0IglFPnJUsktlEGxsbZldLSnazbds2hf/OnTvUzyOoatOmDezs7GTjJ1I7evQomjVrxn12EhISzHJo/FvN3B6iJqkniiI2bNigWtxZuHChKpJs+/btqmvq0aNHqgnkv5l0jiBFPmXLS0j/pO3duxdOTk7MQPf9+/d0eLt8+fKKxXr58mWZ8L00YCIBl1SHtGDBgrRiZDAYsGbNGjqXRl7SDtKBAwcUOqdSMqMHDx4odEqlyXVWVhamTJkik5ypU6eObMGeP3+eQjoFwTjjJ/V/+PABAwcOpH5PT0/Fgj906BANymrWrKnwv337lh5E9erVY/4OO3bsQP78+bmSMXFxcWjRogXVcTU1URSxceNGLnQPMFa61KBxoij+YabDf+sm+E+b2n0URVE1IWYdVLdu3cLYsWORkZHBPQgbNGiAwoULM/Vxgd8IS2xsbJjaart376brw9HRUTHrcv36ddkabdmypexa379/L/NbW1sr6PIJykBa3DK9V1ISqEmTJjG/C4Evq2kmAv/cvLYoirh9+zbGjRuHMmXKKGbrHzx4AF9fX2g0Gtjb2yu6PxcuXKCEM3Z2doqiUGRkJL788ksIghGBYbq+U1JS0K9fPwiCEUHCer62bdsGOzs7eHh4ML9DbGwsatSowWWBNRgMmD59Onf0AzAGempyVzqd7rOVKFAzczPGISEhqtwEv/zyiypB38OHD1XhdFeuXEGZMmW4ha4tW7agevXq3GLjt99+i1OnTnE//1M6F8wVPSMjIzFq1CjuNRsMBlhbW6tKiri6uqJ48eLc35XEKzyyHVIAGjlyJNN/6tQpCIJxXp9n1apVU5WlOXfu3GfFaPxXmrlZ+0WLFqlCtkeOHIlp06Zxn6XJkyejUaNG3Jn95cuXw83NjUvqeezYMZQoUYLbWHjz5g2qVavGhbWTpJe3XgHziIpP2R4/fvxJFx7zEtK/wJ4/f86dBQCMhEHOzs5M+EVGRgat5JcoUUIBL3jz5o2Mscw06IiNjZXBbk0Ttvfv39NOriAIsLe3l0E9SGJLKLAFQVAMZ9+6dUvW6TTdDNLT0+Hv70+7ESy4zrFjx2gHhiVinpCQQL8na7MgCaO9vT23+vjkyRPUq1ePO6up1+uxaNEi1S6c2pxnnv377Nq1azh48KBq4FevXj2UK1eO2+EksEytVoulS5cq3ksKPRUEJevgy5cvZf78+fPLCBSys7NlnTpBENC8eXMZ3Ek6p0uSX+mhPHPmTJlfEJSQs549e8r8rKDvxIkTNDlTWythYWGqHbm/w3Q6HbdDThJT1mhEbm4uVq9eDUdHR0yePJnpX7x4MWxsbJikOYCxqFCgQAFu5ycyMhIVK1ZkymkBxnOgX79+qnNnaokL8GlK7PxZM0cIuHHjRm5yAhgLpjxpCcAIc7WwsOCiV3JycqDVatG3b19mIEckZypVqsRExzx48ACCYCRCYyVZx44dg1arxYoVK5h70MqVK7monE/NzMGS37x5w5wHJCaKIgoUKMAc2yBWsWJFDB06lOvv1q0b6tevzy0gbN26FU2aNFFdK6zRl/+K3b59WzXZ3rp1K/z8/LhQ21OnTsHOzo6r40oIxho3bswsFEVFRUEQjEzyLLmVxMREWFpawsLCAvPnz1dAsnNzcynqLyAggJk8duvWDRYWFpg5cybzOdiyZQtcXFy4RYnExET0799fFfL8b9yL/wnLS0j/IYuPj1ftKly9ehWVKlViLgJRFLFnzx64uLigUqVKioNRFEVs27aNsoGyBMDPnj1LO5mLFy9W+F+8eEFZOIcNG6bw63Q6LFiwANbW1ujVqxfzO5COr7e3N9P//v179OnTB19//TXTT+Yd1Zg5Y2JimKxv0utUI10gn5Nn/w0LDw/HjRs3uL+5Xq+Hp6cnateurZjdJLZz504IgpFxcOzYsYrD2DSh7Nmzp2z2JScnR4FkGDt2rOwwJTqG5GVraysj0SJQNumrWbNm9Fq8vb0VfltbW9q1/emnnxR+QZCzkppCWC0tLRXMgqGhodTPI5MAjDBjHsnY/6c9fPiQC7V7+/Ytxo8fz00KHz58iEGDBnErzM+fP8fy5cu5n52amsqtzAO/zSPm2W924sQJ5uw7sWvXrkGj0TBny4HfGHLr16/PvLeiKMLJyQn29vbc34aQtvFQA4R0rVatWgoWW4PBQFFOFSpUUAThmZmZsLe3hyAIGDx4sCKAvn37NiwsLDBu3DhmoqAGX/zULCUlRbXLmpqaytWSJdamTRtVSRdvb2/Vjvju3btVZytFUfykO0h/1iIjI1UJzJ4+fQo3NzcugWNGRgYKFiyIihUrMsmK9Ho9TQh9fHwUz6coiihfvjwEwcg5wiJdIogUQRAwevRoxe/dpUsX2Rlo+ntLJZQ8PT0VDZbTp09Tf+3atRUd3czMTBpL9+jRg9ktHT58OBwdHbFp0ybm8xIeHo5x48aZZV/PM7nlJaSfkGVmZqoOwr99+xa+vr5MnTLA2GXs1asXfHx8mP709HQEBATA1dWVWcERRRE7d+5E6dKluXMvDx8+RNOmTbnQjczMTHz33Xd4/fo193uEhISoHipqcIk8yzOpnT9/HocPH8aLFy+YyWRGRgY8PDxQqVIlzJkzh0mqdPbsWXpANW7cWDGLl52dTWeQBUFgdkvr168vS+aqVq0qmy2TkuOQl7e3N02OpLps0oSQVIlNZ607deqElStXUoIlKY0+gaTl5ubSe0KgauTl7u6OR48e4cmTJ5QAY9asWYprKFSokIzMh9DYkxeruAUAQ4cOhYODw2cpM6FWsNLr9apBdV6x63+z+Ph4VeIWIncyY8YM5r1NS0uja4U1TiGKIuVRIJJSpkag6i4uLsx5UKlcEos1uk2bNtTv5eWlKHhI/e7u7oo5+K5du1J/o0aNFOcfQUCVKFECP/30k+w+hIWFoV69eliyZMlnj+4xGAxmRy7MyS+pScuRz/g327NnzxASEsLdo7Kzs1G+fHkMHjyYm7iT8Q5fX19m159wHlhYWGDu3LmKz5JKvri5uSkaJKas9oQdntiaNWtk/i+++EKGfDFlvS9UqJCsm0o0e6WF2dWrV9Nny2AwyGb/bW1tsXLlStmzMWnSJOp3cXFRjNoQLW6y5lnInJYtW6Jw4cLYtGkTs3B77do1bNq0Ka+bKrG8hPQTMHNBjCnLH2sWSAoHCgkJUczDSTfq8PBwxawVCUwBY+Jr6k9KSqLvaTAYFHAFvV4v6yywNn5z1X9zMyp5wd7fa+YYGj9+/Mj9NwaDAU+fPlVUn0VRREpKCmJiYnDp0iUZUYQoiggNDcXBgwexZ88ebN++Hbt375b9znv37kXHjh3Rr18/+Pv7Y/bs2bJnPTMzkwZ8Li4uaNu2rYK46uHDh7IOZfv27RVdsA4dOlC/jY2Nglxr+vTp1G9lZYV27drJErXly5fLDsGWLVti4cKF9JmWMmqTbsrMmTPpYb1+/XqZv3v37rJuCdFLJeRElSpVkq2XkydPwtLSkiaVNjY2soAjOjoaGo0G3333HYX/SgN4wgYsvYb69esjKCiIFslSU1MV86xWVlZMSCEJ8onuLMv0ej02bNjwp9b17yGhMHfgm+o+s8zc2sjbm/641axZk7JQs4yQ+wUEBDDvM+lgWltbM2fHGjRoQJ/X3r17K84mMgMsCALKli2rONvGjh1L/RqNRoFiCggIoH4LCwt4e3vL1qYULm9ra4smTZrIoMhEh5gk1q1atZJ1Vi5cuCBbc/7+/rJ7Jd176tSpI4N2v3z5EiEhIThy5Aj279+PPXv2qHYIX716pfosm5udNEcSpVaI/j1+c/N75tYp8Hmv1bi4OAQFBSEsLIyZLIqiiF69eqFEiRKYOnUqswBLND5tbW0xefJkBXu2tOjo7OysaIDcvXtX9jz6+PjIfhdpsiYIAqpVqyY7I6S6v6R4u3btWupPSkqSjaiUL18e48ePp8+WTqdD4cKFqb9YsWIYOnSorFjRokUL6re3t0efPn1ksceiRYtk19C2bVucO3dOdo1SQrzKlSsr7oO0yOzo6KhAE126dEl23puOmomiiEaNGsHV1RVBQUHMYllcXBwiIiI+62f2f7G8hPRPWG5uriqjV25uLi5evMjdxEVRxLNnz7j04YBR63TevHkKohNi0dHROH/+PHr27Mn0v3v3DuHh4ahcuTLzOnJycnDp0iV07NiR+RmiKCIsLAzfffcddu/ezfyMiIgIbNmyhas5+PjxY5w7dw5z585l+pOTk3Hz5k2uX6fTISYmhjvbIYoi4uLiuDp2gHHWR23ONyMjQxXKkpOTo9q5NRgM3MP092wm8fHxqv/uzp07qofx4cOHVefPdu7ciYMHD3I/e/LkyRg0aJDs/4uiiDt37mDhwoVo0qQJSpUqJSt0GAwGbN68GV9++SWFnUmp+g0GA3744Qc4OzvTjdl0Bvrp06eyGeg+ffoorm/fvn10xtnV1VURUGZlZaFdu3YQBOMcJ4tUYdeuXfQzWElSVFQUJe9ikcu8fv2a+u3s7BTzYC9evKABpSAoSX/IIU2+hyms/d69exAEgcKRypYtK1uvDx8+RIUKFTB9+nTky5cPBQoUkB3yb9++hbu7OyZNmgRPT09YWFjI1sO7d+8gCEYI1IgRI2hlmpjBYKAH8NChQ2lwK30mo6Oj4e/vj3z58qFMmTIUSWFaaTcYDKhRowasra0xdepU7nM9efJkVar6nJwcLF++XDXIPXv2LJNZm9ijR4/g7+/PZVaMi4vDwYMHuWMAWVlZiIyMxMyZM5l+0rXhdYoBI+JDyk5uah8+fOAy5ALGvYk3GwsYzxk1dm9RFM0G+mp7z/z581GxYkVuInP48GGULFmSSzRy//59lClThjuyQjQZWdwCgBEep9VqMXHiROYe1717d9ja2qJz585MPdvBgwcjX758cHV1RUxMjGIfnTdvHhwcHGBpaYmIiAgFzG7dunUUdrtnzx6FPzg4GPny5YOFhQWmTJmi+Hwi32Zvb4/27dsr/G/fvoVWq4WlpSU8PDyYIzl169aFIAgoU6aMonhCkhCSQEh/a71ej5UrV9KCnKOjI1O+Jzw8HD4+PnBzc+Oio27duoXWrVtz0VFJSUnw9fVlasUCxoL0wIEDuaQ3ubm56NOnj+o5PGDAAERFRXETz8DAQERERHAlit6/f4+NGzeqkmFt375d9ax/9uwZF6UGgOpJ887rrKwszJs3j3mf4uPj8e2336Jt27bcPWX79u2wsLBAmTJlmHtjcnIySpcuDUFgj28ZDAZ88cUXEAS2TJooinREhCWnBfw2QlKqVCku6kCj0UCr1SogswDg5eVFzxuW/nvXrl2pn6W/SeS2NBoNqlevrngeCFGgRqNBgQIFFPtjQkICPau1Wi2TUVmqX84apZMWinhjBc2bN4cgCOjbty/zPt66dQsajQY1a9Zk5hKiKMLX1xe1a9fmPk8GgwGtWrVC9+7dmX7AeL+qVatmtmD0/215CekftJSUFNSsWRPffvst05+YmIh+/frJYHem9uOPP8LS0hL29vbMgOnKlSvQaDSwtLRksr/GxsYif/78sLKygrW1tYIAIisrC+7u7rTaxGIT7Ny5M12Yfn5+Cj/RISVdIVM7fvw4NBoNrK2tmTqcr169Qr58+WBtbc1kmTQYDKhWrRpsbGxQuXJlhR8ABg4cyPVnZmZiyZIlsLGxYb5/eno6tm/fDnt7e/Cep+PHj8PJyQnNmjVj+u/cuYMKFSpwKbPT09NRt25dGYOx1PR6PapVq8adjdXpdLCzs8PQoUOZneXU1FQ4ODigb9++zIP4/v37sLOzw1dffaX4+5ycHAr3bNq0qWJTPH/+PBo2bAgHBwemsHJMTAwWL16MevXqoVSpUswud0REBHr37o1ChQox53c/fvyIGTNmwMHBgRm0khnpIkWKMKn6AWMy5OHhwdVqzcrKQseOHfHNN99wg5URI0Zg9OjR3MT9m2++waxZs7hkPD179sSWLVu4xaH69evj1KlTzPkbURRRtmxZDB06FLt27VL8TgaDAd7e3ihXrhy2b9+uSCCITImtrS2Cg4OZQWOTJk2g0WiwceNGRbCTm5tLD8+goCDm70DmZjZt2oTTp08rrpFo+K1btw7Pnj3jEofo9XpkZ2f/rm6JWuAXHR2NkiVLwsvLi5loPHv2DFqtFk5OTkyCifT0dArXZJERGQwGVK1aFRYWFmjVqhXzGrp37w5ra2sUL16cuTbnzJkDW1tb5MuXT3E/MjIysHPnTtjb28POzk7hz8rKwvHjx2Fvbw8nJyfmcxsaGooSJUqgTJkyzOuLiopC7dq14enpyfTn5uaiY8eOaNmyJdMPGIN4Fm8AsQkTJsDZ2ZmbqOzZswcODg5c7ck7d+7AycmJOx/45s0bVWbOsLAwGYLH1A4cOIAnT55wn8cDBw4otHmldubMGURFRXHhoJcuXcK1a9e4iVJ4eDj27t2LO3fuMK/x3bt3GDVqFG7dusW9Rm9vb1y/fp17jw8dOoTp06crkEvE0tLSUKtWLUWXhlhsbCw6dOiATp06ya4xIyMDU6dOpUVDKysrZlft8uXLVNM3MDCQ+RkkKW7cuDHTv3TpUlrQY33Pw4cP0wSBNVv45MkTWvRjkY8BgIeHB6ysrJhSfACwadMmWFhYoHTp0sz9KSsrC4UKFYKdnR0zkQJANbFZJGOiKGLMmDEQBLYE3ZMnT9CxY0eULFmSKzvz+vVrTJo0SZVzJCQkhJnIEbt48SJWrVrFXTMnTpzAqlWruEnO7t27sX79em6ha+PGjfjhhx+463b9+vVYtWoVt8i0efNmTJ8+HcePH2de4+HDh+Hr64uff/6ZiV65d+8eqlevjlOnTjGJz7KyslCyZEmcOnWKeXYAxvM8ODiY26g4ffo0BgwYwL1GURTRsmVLnDt3jruuL168iHnz5qlKP61atYorZwcYzzG1ZorBYMCXX36Jpk2bcv/NiBEj4Obm9snPtOYlpH/Cdu/ezUzSAGOiRFgrWYf9vXv3ZBqgphj169evo0qVKjLohHRh3rhxA127dqXJpGn36dGjRxg5cqSsO+Xl5UX9ycnJmDRpkkx2xtHRkQbCer0eCxcuRO3atalfq9XKKot79+5VyMZIA+EHDx6gQYMGMuiD9FDPyMhAly5dZLIyppsHOcTIy3RG5P79+zItVNMqvsFgoFTwlpaWzMT/2rVryJcvHwoVKsTceHJycuDl5YVatWopfMRmzZqFIUOGcP1t27bldphfvHgBrVbLZdHcvHkzKlWqxBQKT09PR8+ePbFo0SLmpvbkyROEhYUhKipKVXxdFEWz4uxv3rxRncF5/fq1KvQxISFBdaYwOTnZrJi3Gu18dna26oxRVlaWqvRFYmKi6vXFxMSo3p979+6pSm9cuXIFVlZW3ISXkC3MmTOH6SdwXJYeKgC0atUKgmCc22F9D9KdLVCgAHPWisCBbW1tmTBcMq9XunRpVfZTFtnF32Hnzp1D69atIQiCQhvVYDDI5oBM5+Zzc3NpJ5hU0qXPjiiK+Pbbb2V7k2kSv2PHDmi1Wuo37XI+e/ZMJollSpojDV5N905iN2/epOgD1m+am5sLLy8vODs7c+/TmjVrVBPSiIgIVSmO34PwMAeV/Cd0kv9XM/e9zHWVSRGEN9sqTXh4Aav036uZwWAwS2Ck1iUHjNfJI/wj+//58+cVxZ1Tp07B0dER1atXR+/evbF+/XrFd963b58Mgklm24llZGTI5vAHDx6sOCukSBk3NzcFxJEUxwXByPJtmpARhlaynidOnKi4zpYtW9J/M23aNIWfENg5OzszNcsjIiKg0WjQrVs3ZsIaEhKCMWPGICQk5G8nKDP3/Jqbx1VbszqdTtWfkZGh6v/48aMs2TWdD/748aOsMJySkiJL2nJycmTnZHx8vCL+kZ5RSUlJimKMVPM0NzdX8fdRUVGyeMZ0jRoMBtVEETDPAs563/8v+xT3YFPLS0j/pPFo/gHjAz116lSULFmSuTnEx8fDy8sLgiAwu2+hoaEyHVHpZxGdUjs7O+qXdihFUcSmTZtkfkEQZNXPU6dOyQ4JU2hCbGysgqxl2bJl1J+bmysbYGcF0xcvXpR9xuzZs2X+lJQUGRZ/0aJFivuwdetW2uWVzhoQe/nyJU3eWWyLoijC398fgsCWpAGM0D9ra2sulCcxMRH169dn+gBj8KIW1K1atYrbMbp69aoq1fy2bdu4kEOdTvefmS/4FEyNgAUASpUqxe2kJCYmgsByWXb06FGaELISRukc68aNGxV+6RysKfwa+I0NVBAEJgRIWlxyd3dXVFNFUaTFpS5dunCfu1GjRuH06dNM399hUVFR8PPzY3amL168iKpVqzI7Fnq9HvPmzaNJp+nIgCiKmDdvHr0nLDTMkSNH6B47bdo0hf/Vq1c00V+xYoXCbzAYMHjwYAiCwAyAyWdoNBqu3NXr169RvHhx7u+Rm5vLhRyT76kmYfApmrk9Lzc3V1UzGjB2htWgm8uXL1d9jidOnIgtW7Ywr0Wv16NNmza4cuUK82+vXr3KhTh/SiaKIh4/fmy20FisWDH07NkTFy5cYN4PMufq5uaGQ4cOKf6NlIimQYMGiqKdKIp0HdnZ2TG7h6RgZ2FhgWXLlik+IyEhAVqtFgUKFOCi1ry8vNC+fXvmcyGKIubOnavKlP1ftqtXr6qy2fv7+3M7/KIoolWrVggMDGR2bUVRRNOmTdGvXz9u0blz585o3749fv31V6Z/7Nix+Oqrr7j76KFDhxAQEMBF7RgMBly+fDkv3vobLS8h/Qfsxx9/5MIGdDodAgICYGdnx6ySxsfH06oeiz03KiqKCruzOowPHjyAp6cn9ZsGJvHx8bTLIAiCYsZFp9Nh8uTJ1M+ChoWEhMDJyQmCYCRbMV2wr1+/psQSLFioXq/H1KlTIQhKHVViFy9ehJOTEzp06MD0v3//Hg0aNOBCz0jHQ23W69ChQ1Qmg2X37t1T3YzUKlBqVbLk5OS8Te4TML1ez51/IlatWjVuJ0IURVhbW3Of0ZiYGLqOpAQKxPbs2UP9nTp1UvinTJlC/QULFlR0e7t16yYrDpnODBNyGPIy1QSUzswIgoDOnTsrOuJklk4QBG4Bxs/PD25ubma7Pn+18dZfTk4OlixZgrp16zI7/L/88gtcXV3h7u7O9B89ehQODg4oX748c51eu3YNLi4uzJEFwBgIe3h4cOf89Xo9fHx8MGPGDO53+/7771UTrJCQENUZc3Pdvs/NSDFUrUPRt29fDB48mNup2rFjB4oWLcqd37179y40Gg3mzZvHfC6IpmK/fv2Yz/qSJUug0WgQEBCgKChmZWXB1dUV3bp1Y8YGYWFhZveiT8WuX7+uijzJyMiAu7s75s+fz30OJ0+eDCsrKxkRnNQiIiJo95XVmRRFEVWqVEGRIkW4sOW1a9fC09OTe19fvHjB7P5KP+PfbOY6edu3b1eNj9atW4cGDRpwYboHDhyARqPB4MGDmc8LYYIvW7Ys9u3bp7jfhGzJxsYG3333nQIxEBkZCY1GA41Gg/79+yu6m0lJSShYsCA0Gg369OmjgKYbDAbUq1cP9vb2mDRpEhNmu2TJEnz55Zc4cuQIF023a9euf91++09ZXkL6D5k5uvF9+/Zxu616vR5z585Fvnz5mLCdzMxMfPPNNxAEAd99953Cn5WVhdGjR1PoGmt+LTAwEJaWltBqtdzNgjCbsapcsbGxlFmTNSCek5NDr4E3m7F3717ky5ePe7jFxMTA09OT22nMyMhQ1TAVRZE55G96nXn277Q3b96YlfRo3Lix6lp1cHDgFj3S09NpssbqrISHh1O/h4eHIvAKDg6WJYSmc1TSwpAgCOjatavs+/j4+Mj8zs7Oss6XKbxeEATs37+f+gcNGqTwmyIWCFmGIBhZTVlrnUDk1dYiANW5mr/DXrx4wa1+f/jwAT4+PlwExYMHD1ChQgVERkYy/Y8ePUKFChW488nv3r3DV199xX3+dDodgoODudcuiqJq0P9vtL1796omnPPmzUOxYsWY84bAb3JOlStXZnZNUlJSYGtrCwsLCy65C+nKderUiYkYIAy/lStXVnRe3r17B1tbWwiCUYPUtFtKmLMtLCwwfPhw2e+bmJiIYsWKoWHDhggKCvrkZ7/U7OHDh6raoNnZ2WjRogVzTICYv78/Bg4cyC0uREZGokGDBqpyc5s2beIijYB/f8L57t071e948uRJDB48mLvHJSYmwsHBAU2bNmXukzqdjq6Hr776SjFfKooiatWqBUEwEnzNnj1b9nuKoogmTZrIOuWm8ZoUBeTi4oLVq1fLYraBAwfKzqeAgAAZWdCSJUuo39LSEn5+frJ1d+3aNerPnz8/pk2bJtuDcnJy6J7wxRdfYP/+/Yp4Yfny5ShatCgWLlzIXLeiKOLIkSN5mtMMy0tIPyEzh/G+cOECTp48yfUfOHAAHh4eXGz/zz//jEKFCnGrXOHh4XB3d+cyhsXFxaFFixZcZsycnByMGzdOlTlzx44dqkLnt2/f5ooyA8ZNVS0wk2ov5tl/y1gaglILDQ3lzmcCxsKMILC1BomfVGBZidjLly9VE06pILcgCNiwYYPMv3r1apnfzc1NVnyZOHGiakLZv39/hb9Dhw50PUgPc1KcKlGiBK0Um75/kSJF4OjoKCNUIPBX8ipXrpxitnHIkCEQBOMcF48ACjBqlX5KJoqiakD74cMHVZhlYmKialfrw4cPqtDH/9q+ZY70KjQ0FI6OjggMDGR2HBISEugoR9++fRXJq16vp/wCNjY2WLduneIee3t7ywo8pgXfGTNmUL+7u7uiGCvV7rW1tcWmTZtkn0Hg2GQ9jB8/niZFer0eHh4e1G9nZ4epU6fSazh79iyFyNvYEaTEvAAAIABJREFU2MDHxwcnTpyg7P0tWrTA0KFDsXz5cpw4cQLPnz//LHU2TecNTU0URdW4BzAmvf/1YnJcXJwqKiUmJga1atXCtGnTuEknWQ+tW7fGiRMnFM9TYGAgfV5btmypKLJIUT5arRZDhw6VxWsnTpyQnR8lSpTAli1baMwaFhamOMN8fHyoxu7t27cV/vLly+PgwYOU8dzGxkbmL1CgABYuXIiMjAxkZWWhTJkyMr+dnR0mTZpE9w9fX1/F38+ePZuuS9PvUK1aNezevZt+h9zcXMpi7ODggG+//VYRs+7fvx+Ojo6YMGECVz/40aNHn8Xc519peQnpZ2bm4CSxsbHM+QeyWF6/fs1k2yWBUkpKCubPn8+sFuv1euj1emzatIl58JH/Z64LqSZPIv0uefbfsJycHLx48UL1d4+MjMTOnTtVg44JEyZg8eLF3KCMzCnx5IFEUaQHFIt4KDU1VVa9Nb1eU302U9INKfEHqfBKK6iLFy9WHLZSGKdU75B0VooWLUoPUilJjyAIGDJkCPz9/SnBiK+vLyXvEgQBW7dulWlwEm224sWLQxAEWlgi/vj4eBn8n1yDr6+v7F5Iq9QeHh7M3ywhIQGCIDAZPfPsv2HR0dFo1qwZ5s+fzx1pIeMkpUuXxrZt2xTF1j59+tBnrXjx4orExZTjwFQzcf/+/TJ/hQoVZAFiZGSkIniVfsbjx49lfq1Wi3nz5tH1cOvWLZnf1tYWw4YNo2vi2LFjivf38/Oj10hGWcjLysoKc+bMgSiKOH/+PBwcHBTB84kTJ/D27VtcvXoVhw4dwoYNGzBr1iz4+fmhZ8+e3G4lYVTn7Z86nU4VNi6KIn755RdVP2++jxhrdl5q5lAVvwcq+VdoCv8ZQqHf+29Mk5FXr17h7t27uH//PmJiYhRM50lJSahVqxaqVq2KAQMGYM2aNQo+g4MHD8oSqQULFsjWQ1xcHGUmFwQBVapUkRUVs7OzaReUvMaNG0fvqcFgQM2aNWX+WrVqUTItor0p9VetWlVG6kl0xcmrcuXKmD9/Pj2HTJFAbm5umD59OiVEnDBhgszv7OyMiRMn0j2G6LCSl42NDYYMGULj1hcvXlBkA3m1adNGhmA0HW8pU6aMTDrs2rVrMjJPOzs7xQgNIT3VaDTo3Lmzggzw3r17cHV1xejRo3Ht2jUu0++/yfIS0j9oDx48QOfOnZmdEqmZq3DodDpVYoXc3Fwu+ypgrDJHR0dz4b6EnW/8+PHc90hOTsaECRNooiiKcrH5Dx8+YPfu3dxZm9TUVNy7d4+rB5idnY13795xacxFUURmZiaX1AMwHiI8OB15DzWtPsA8C6E50e0/uvjNPQNJSUmq/4Yc5Gqff+rUKdWD9tSpU1yotCiKOHHiBJMwCjAeUuvXr0ffvn0VHZ6MjAxs2LABY8aMQdu2bZmwq8uXL6N58+aoX78+fvjhB+ZnLFu2DI6Ojujfvz/ze4iiiE6dOqFEiRJcpt3r169DEAQsXbqU6dfpdNBqtahUqRKXxEWr1cLe3p45a/z69WtKYNOzZ08Fk+T58+cpq3Xbtm0xe/ZsWXAXFBSEokWLwsbGBmXLlsW2bdtw6dIl6p85cyaKFClC5zTPnz+PvXv30vsxduxYFCxYkCaMW7duRVRUFJ2VGTlyJLp37w43NzcIgoCJEyfKri8gIAALFiygsClThvCNGzfCwsICs2fPptVr6fXHx8cjf/78cHFxgVarpazbL1++lD2//fv3p7qHCxcuVNwn4De5KLWO9aBBg1SJwgDzMGyDwaC6RxsMBjx//lw1ECYdqT/6GaIocqvgxMyxNf6e7s/fFZyY2xeTk5O5Gtfr1q1DQEAAswgKGAmbBMEI4WN1l2/cuEGDuhUrVij2HzLHKQjGWU7TayX6v4Jg5Dcw9WdmZlL2aWtrayZhihQVwNKflBL/sfYNKVS+b9++Mp8pTLFRo0ay31Gn01H+BVLgka61W7du0VEa6XdMS0vDnDlz6HeTJiHS3yo1NRWbN2+mSUKdOnWYSd+DBw9Qq1YttGrVipnQiqKIUaNGwdvbm7uWgoKC8PXXX3ORLNeuXUO7du24f5+ZmYmGDRuqohimTJmCmzdvcs/Tp0+fYuXKlara8FOmTFHtNO7bt081FomOjsaMGTO45/GNGzfQqVMnxRn0/PlzbN26FSNGjICnp6eMQBIwNgukHfcaNWooigdJSUm0O2dtbc2MiaQJ26ZNmxT+zZs3c59X4Dd5HkEwdidNvyeZBSXXYFrcvXjxouyZNNWAlo62CIKA4cOHy/wxMTEy9nNPT0/ZfXj37h2VKBIEI/RW+kwbDAZ6BpKXKVGVlEBQEJSEeE+ePIG1tTX1s84xMroiCAL69++v8CcmJsLFxYX+lqxiChnjcXR0ZBZv379/Dx8fH/Tt21eVhXvTpk0YOHDgJ99xzUtI/6AR4V1T2B0xvV6PgIAA7rxZbm4uDh8+DDc3N24iEBUVhbJly8LBwYGZTCUkJKBChQooVaoU84HPzs5Gs2bNUKZMGVhYWDCFd7/55huULFkSlpaWzM7RunXr4ODggOLFizOhuGfPnkWhQoVQrlw59OrVS+F/9uwZypcvjwoVKqB169YKv06nQ9OmTVG5cmU0adKEeR/Gjh2LatWqoWHDhkz/jz/+iJo1azL/Pi0tDaGhoahXrx6TbEav1yM0NBSNGzdm3kPACJVu3749cz4XMMpPeHt7MxmCAeM9bNWqFTZu3Mg86LZv347y5ctj27ZtTBjblStXkD9/fi6U9Nq1a7CxseHO7BHtNRZRzo0bN6h4c6VKlRT+6OhoDBgwAIULF4ajoyNz03vx4gXGjh0LR0dHbtIbExODhg0bcue9AOCHH35QZRt+8+YNZs+erYoSWL16terGvH//fq7sCmCE1fKq/AkJCbh37x7OnDnD/J3u3r2LZ8+e4dSpU8xZxZMnT+Lly5c4ceIEnj59qgh+N2/ejGfPniEkJAQTJkxQwHwWLFiAu3fvIjg4GFWrVlUEAqGhodDpdKhatSpGjBihSGLS09OxYcMGWFlZYfny5Ypn8d27dxAEAdWrV0dgYKBCgic5OZkerlu2bGEGO+Hh4QgKCsLDhw9x9epVblCWlJSEyMhIbrLz4cMH5M+fn6sNDBiDAmdnZ+4zlZWVBU9PT5QqVYp5EJOZ4TJlynD38SFDhqBy5coKsjdiy5cvR40aNVCxYkWFjxR6atasyfSnpqbi9u3bqFWrFurUqcP8+6tXr6Jhw4Zo27Yt8/MvX74MHx8f+Pj4MNfF48eP0bdvX/j7+3PXTefOnWnXjWV9+vThak8+efIElStXVgTPxN6/fw9/f38sXLiQ6QeMhRhT9nWpEVkr1vyfKIqoW7cuAgMDuZ2/+vXrIzAwkCtH1LdvX8yfP18Gf5fa7NmzMXHiRKxcuZL5PK9btw49e/bE3LlzmXNhe/bsQaVKlTB9+nRmMkWS6lGjRjHRRc+fP4ejoyO8vLyYBb2YmBi4urqiQIECCr3yxMRE+Pv7U2hzhQoVoNfrkZ6ejilTplBJIWkCIQ3ODQYDVq1aJesYzZ8/X/YZoihi7Nix1N+iRQvFNd65c4dCKQsXLqyIRXQ6HTw9PaHVamFlZSUr1BEjCA4bGxusXr1a4U9ISKCavzwJtq+//ho2NjZMhAvwW1xXunRp5vN2584d2Nvbw9bWltlICAsLowSPps9bZGSkjHhu7969Mv/Hjx8RFBRECxy8NXf06FEULVoUY8aMYfpJUtqrVy/mvqfT6dC4cWN06dKFKbMmiiKaN2+Orl27MouJxO/t7c1VNSB/v2DBAq5EWZs2bTBq1CjmGdClSxfUrl0b/fv3Z56lQ4YMQZEiRTBo0CCZvAuxhQsXQhCMkoumkoqAsXhMEu4ZM2YorjEtLQ3FixdHmzZtMHDgQGZBcOrUqShWrBiGDh3KjM/fv3+PwoULo3fv3sxrBIxz8nXr1lV0T4mJoogBAwZwzyfyORMmTFCF67dr1w7W1tb/OG/D/2p5CemfMB7MiNjmzZtRpUoVpi8jI4POdLEkX+Li4ihJkCAI2LZtm8z//Plz+Pj4UB28QoUKyTafFy9eYPLkyXRzFARB1qF8//49lixZgsqVK1O/t7c39efk5GD16tVo2rQp9VeoUEF2Ddu3b0fXrl2p39HRUXYNYWFhVCybwBakm09CQgK6du1Ku062trayhW8wGPDNN9/Qape9vb0iINi7dy89LFlafG/fvqUzA+XKlWP+FoRsqUGDBkz/hQsXIAgCM+EGjFqogiDA39+f6V+xYgUEQeCSmpDDvFmzZsyAhkBUevbsqZjXS0lJQdmyZVGsWDF89913ikRp165d6NSpE8aOHYsNGzYoOgzJycmIjo7GpUuX8PPPP3MTCIPBgNu3b6t2Yd+9e6faydHr9Wa7LZ/jDBTP1OYJb968qZAZISaKIqpVq6Y4pMi9Wb9+PQRBYAbger0e9vb2qFixIvNezpw5E4IgYODAgQpfbm4uXausOe+MjAwKMeIxWZ48eRLe3t5/SbcuNjZWlYQkKSkJEyZMQK1atRSBlyiKWLBgAf0+Z8+elflzc3MxYMAAquNsurb1ej0GDx5MO0xFihRRfKcZM2bQbrZGo1GsvZCQEFnAb1oASElJkcHfWMHjt99+C0EwsiqzjLCP8s4ZnU4HJycndO/enekHgAoVKnCD38zMTHh4eCgISoi9fPnydxHuqK1rg8GgCrU0h2wxB/M0d06b0xd+/vy5KgFJUlKS6vx6Tk4OV2aEmFrCDhj5IVjdWWKvX79W/Y2fPXuGvn37Yv369fT/iaKI2NhY7NmzB/7+/qhTp46MHfvVq1dU21j6kibFoigqZs+bNWsmC3xTUlJkeueFChXCuXPnZPdcOpsoCAIWLFgge67evn0r63p16dJFkfARaTdBMMI8TRMRabfdyclJIZ1FEghBMEKjTbuHb9++haurK12Ppgnlzp07UaRIEdSsWRPdu3dXINuSkpJw584dhISEICgoSFU+JioqiisfRt5LrbCalJSkisp48+YNhdGy7PHjx6p/f/fuXdVnPjw8XBU1Eh4ersoV8uuvv9IkTKfTKfaPly9fYsKECQCMz5fpOZGRkUHj6tTUVGaRumfPnkhPT4fBYGCeM1u3blWdXU5PT8esWbO4fgD46aefVPe23wNjT09P/9PnaXJysiqx2KdieQnp32wLFy7kBvE6nQ59+/ZF4cKFmQ8cqT7zkqGjR4/KIDnSIFEURaxfv54GXIJglHGQWnBwMK2ckoRPGlRduHCBzpuRl7QrEhcXh9q1a8v80u6SwWBQ4PlNoS4XL16UfQdTEpTU1FQZJIoVXJBqmCAIzC7wrVu3YGtri/z58yt8gHHzqlixIrNLQaxdu3bciqQoinB1dWVKeQBGspoCBQpwoUZNmjRBkyZNmN3TN2/eoESJEswqH2Ds+B07duyTh2L8G00t4Xz06BG3Sg8YySN4HXmSZJAD19S6dOkCQRCwZs0ahS86OpquBRbUn8CItFqtIuDJzMykf2tra6uACOn1euovXbo085AnxRsePP/vsFevXnEP20OHDsHBwYFJoJSeno527drRro1p0PPhwwd8+eWX9DubQsV1Oh06duxI/Sz2cWmgzdq7bt26RaFfrNn6jIwMlC1blllsI9axY0cF/FpqAwcO5ELlAaB3797coOn169effFXd1OLi4pjnALG0tDQsWbJEtdixcuVK1UR3z5493NEBURRx7tw5bhL+R2fBzO3x5op9AMwye2ZkZCAtLQ2iKCI0NBRHjx7FqVOncP78eVy5cgURERFU/kwURTqja2FhgRo1amD48OEIDg6WzQxKZ/6srKzQtWtX7N+/n36f58+fy/TSnZ2dMXPmTFkhghSNyXuMGjVK1qGMjY2l68jW1hZTp06VFW9FUUSzZs0gCAJKlSqF4OBgxf0cPHgwLCws8PXXXys6gzqdDr6+vvDz88Pp06cVhVdRFD9rJuQ/a+ae3xs3biiK4eRvRFHEsmXLcOvWLZmf/D65ubno27cvgoKCZPEp2bNyc3PRtm1bTJkyRRZjkWfdYDCgU6dOGD16tCx+la6F8ePHIyAgQJbkGwwG+jtfv34dq1atUvzGpiMtefbnLC8h/ZtNFEWz1WF/f39uNezDhw9o2bIlChYsyGRovH//Ptzd3SEIAsaOHavwh4WF0aqfjY2NIun55ZdfULRoUbrZm8LfHj9+jCpVqlC/aSU9PT0dX331FfVPnz5dcQ3Lli2jfpZA+/Xr1+kg/fLlyxX+jx8/0sBw165dCr8oivTA4rFg7ty5k9mlIHbt2jV8+eWXTB9ghOqoVbGnTZvGZdBct24dF3JhMBjQtm1b7kzLjRs3zHYI8uyvt9TUVNXZ7vPnz2Pq1Klcf+fOnRUFIGIPHjyARqNB48aNmf6RI0dyO/Y5OTm0gNO8eXOFX0qcxIJoS8kYunXrJvNJSZsEQUCrVq0UgQZBZAgCe76I0Obnz59flbBIjfzkr7aYmBg0bdqUuT5JUVAQBKZgenJyMi26HTp0SOHPyMigM4KmHRPgN8iVIAg4c+YM8/rWrFkDQRC4HYszZ86gaNGi3O8XERGBESNGcP3Hjh1T7YZ8bnIyycnJqsWgnJwc1K5dm8vOCxgZpcuUKUPZOU0tNDQUtra2mDt3LvM9bt++DXt7e8yZM4cJ31+1ahU8PT3x888/K94/Pj4eAwYMwIkTJ7jz8p+DRUREYOnSpbh06RI30SVoDi8vL2zcuFFRdBFFkSLFypYti7Vr1yoKBTExMbC0tKT6kqzO3eDBg6mfVSg4fvw4nJ2dsXz5cubvefPmTYwfP16hXUksJyfnX4Xe+V/txYsXqnO1p0+fxvTp07l7yeXLl1G6dGkEBgYyC5k3b96EVqtFixYtcOLECcUauH37NiwsLFC4cGHMnj1bERPdvXsXlpaWsLS0RJ8+fRQFhcePH9OiR7t27RQMwh8+fECJEiUgCALat2+PkJAQ2doURRFdunSBvb09hgwZwuz+njhxAvXq1UNwcDB3Pdy7d48b6+VZXkL6SZi56ppOp8OIESO4xBrv3r1DixYt4OrqyjzMXrx4QYe4WXMyr169ognf4MGDFf6PHz/STgJrTlOv11PYKe8327lzJywtLblB+N27d1G4cGEu7Cg5ORk1atRQELVIr6FHjx7YunUr0w8Yq2BqQTJrHkJqahUwtc36119/5R5mGRkZChhunv39Zg4mM3DgQG6RKC0tDWXLluUmpITUwcvLi+nv168fBMHICmpqWVlZtDhjbW2t6HqQDiTpcpp2r6SsnBqNRtHlkXb8BEFO5kBmRKUv01EBaSdDEATs27dP5r9z5w71NWjQgNvVqVatmuqs719t6enp3D2WIDl4BErJycmoVasW9/dOTk5GtWrVuHOQ2dnZaNiwIZfYRxRFdO/endlhJTZlyhSuD4CiuyA1c6yin5oRRnc1f+fOneHt7c2dCyUFyDJlymDHjh2K/Tc+Pp6OerRq1YqpmVi3bl0IgpG4hYU2IIVYV1dX7N+/X0FGRPQK69Spg1OnTsn8ZFbRzc0NCxYskJ0tYWFh6NixIxYvXowbN258dr8fseTkZKxYsYJJFEVs//79+PLLL7Fv3z7uXtG9e3d0796dy08QHR2N1q1bq66Bn376SXW/+VyKAH+XvXjxAtu3b+feo48fP8LDwwNDhw5FeHg4U4WhQ4cOsLS0RO/evZlyXyNGjKDFSlbyP27cOHp2VKtWDT/++KPs/CPjC6QLPnz4cFnHc9q0abKzqXHjxjh48CBdP99//73MX6FCBaxevZrGX6ZyLmXLlkVgYCBFW0hJiMi63rJli6yA8s0330AQjGzXI0eOVOzpsbGxKFmyJAYNGoQrV64wn7v3798zZ3v/C5aXkH4mJoqiWTZef39/blCTkZEBX19f9O7dm+nPzMxEnz594OLiwjwYcnNzMW7cOGi1Wi4cavXq1bCwsOCKz586dQpOTk7c6tGDBw9Qu3Zt7uGQlJTEJe4BjMH86dOnuf7c3FxVyZn/+qH0OdjvgaWpsVIDxu4mD34NGIMXQRC4MzSkGz9t2jSFT6fTUURBjRo1FP6nT5/KGAJNuwF79+6VHYqmHX9TGYvg4GCZ31Rr1LSAQ3QZyUtKQJKYmKhISJ2dnWXVaKkkgCAYZ7GkMCkpq6kgsNkHAaBgwYKfnA4piyGa2Pv377mkZoAR2jp58mSuPzExUZHcS+3Dhw+qENHfI2fxbzFRFDFjxgz4+fnh7NmzzM72s2fPaHGkRYsWOH36tGz/NhgMMomimjVrKkYqpDOHlpaWmDhxoqw4KGUTFQQjx4K0+3bz5k2Zv1mzZrIu+88//6wIkElRWRRFGb+CpaUlevbsSaG+27Ztoz5HR0d07doVq1evRlRUFEJCQjBnzhysX78e+/fvR1hYGB48eICkpKTProsXHR2teu5+/PiRW3Qg9v79+7yz24zFxcXB398fwcHB3JnpsWPHwsrKCh07dsTWrVsVsdKlS5eolImnpyfWrFkj+zevXr2SzfnWq1cPu3fvprDXDx8+oFixYtRvYWEBHx8f+vumpaWhdOnSsjVTvHhxLFq0CB8+fEB6ejrKli2rOKM6d+6MixcvIjMzE5UqVVL4y5YtixUrViA5OVnGWE1eDg4O8Pf3p2M2pn5bW1sMGjQIt27dksnmSNfnuHHjEB0djfT0dNm8NLkP0q6pVKu1cuXKCgJBg8GADh06oH379ti1axc3XlbTtP5cLS8h/ZeZWrdNFEUEBQVxK5GiKGLp0qUKsWOpbdq0iQlNI3b06FEmtI1YRESEaiXz6dOnqpAGtbmfPPt07ffIVjx48MDsjNPKlStVu9FJSUnw8PDg+lNSUuDq6soloHr58iVNulgdcSllPSshXbVqlewgNDU/Pz/ZYWUqUN62bVuZ35S9tEaNGjJ/x44dZf6SJUsqEkayZgwGg2ymnLwI4c+bN28Uf1uxYkXZrGuRIkVk/0aj0aB169Y0EH7+/LnMb2FhwayWk3tsrnjwKZm5Yojacwn8uwi7/qxFRkbi+PHjuHnzJl6+fKm4t9nZ2ZQ7oFChQhg4cCCOHTsmC6Sl3AEk6ZQWcEw1PgVBwKBBg+he9OrVK5l0gyAIqFixIi0MGAwGmeSLIBjJbKRcDZ06dZL5LS0tKUqHsI2arpdFixZBFEW8e/eOSjhJ1wthPF6yZIni+q2srLBmzRrMmDFD4RMEIw/EmTNnkJCQgPDwcPz0008IDAzEqFGj0LFjR9SvX58JaU1JScG2bdswePBgbkf26dOnzJEaYmlpaVymYnI/Wey5UlMj6gHMyyNlZWWZXWfmziJzs7qiKJr9N+b8BoPB7L9hxUEGgwGpqal4/fo1Hj58SL/Lmzdv0KNHD3z11VcYNWoUFi1ahB07dsjm1i9cuEBRAUWLFoW3tzfWrl1Lr0On08HLy0v2rLVv315WZDEtiNra2mLx4sV0XW7cuFHxTDZq1IgieUx1fwXByEdAikVHjx5V+EuUKIHly5dDFEWcPn1a4S9evDhmzZqFjx8/4vLlywq/s7MzpkyZglevXuHhw4eU7Vm6ZsaMGYNHjx7h48ePiqKtVqtFr1696Dkm1T6W7j179uyBKIq4fv26rOhMkt758+fTZ5OgpKT7hpSRODExke4N+fPnR//+/RVEggcPHkTHjh0RFBT02Y1d8CwvIf2DFh8fj1mzZnHn+3Jzc7FkyRImbbbUfk9lz1yg8/z5c9VNVhRFVR09ALJZF1Y1PioqisIjWNeTnp6Oy5cvA2BXbkRRVGWVA6AKpwWgSlQB/H06on/WzB2AvI4ysezsbNUZMABmn7OoqCjVDvu7d+8QGhrK9ImiiJiYGGzfvp3526ampuL777/HqlWruFqwCQkJ6NKlC5feHDDCtlu1aqXaDerQoYMqLHvixImwsrLiBiUEWs6SMBJFESNHjqREX6bwJcLMSpIp03np1NRUdOvWDSVLloRGo0GhQoVk/ri4OHh5eVEon729PY4cOUL9r169gru7O6pXr04TWinzdXx8PBwcHKjOXIMGDVCkSBFahEpKSoIgCLRD27BhQ3Tr1o125t6+fUsDAPLv1q1bh3nz5gEwwom0Wi1l1iZEP4TkBABcXFzoTLpGo8GzZ89w//59uieQhJRU0hcsWKDo4gKgZGmtW7fmynmsXbtWwY4rtZ9//lm160js9wSo5mCR5vZg1hyh1H4P6dj/x/70ez7T3HdTm+eMjY3FunXrFGyVOTk5FN4mCEbYq+n+/ubNG9pR0Wg0srVC3kPKbxAQECD7PqIoyjRA69atq/idCYxQEIydDtMi1Pbt22XJpGlCJWVuFQRBxmILGLvuZC0IgqDQAzeFCUoZ90VRlMEYBcHYDSbP89GjRynLM3k1adIEFy5cQOPGjZkJa/PmzemznJ2djSNHjqBnz540UenUqZOiM5aZmYlZs2bBxsYGvr6+zPPq1atXqFGjBoYMGcI8Z0RRxPjx49GvXz8uHPHy5cto0aIFt6iemZmJRo0aqRalv/vuO9y+fZv7XF+7dg0rVqzgrseMjAwMGzZMtWg/ffp05rw5scOHD3PlyXJzc7Fjxw7m94iNjcXWrVsxYMAAuLq6yrQvY2Nj0b59e9mz1KZNG9lnJCUlyVQRHB0dFXDpkJAQWVHStLmQkJBAZykFQcCIESNkn5GTk4OaNWtS/xdffKGYtWzZsqWsgCMtgBC4vfSZNN0bvL29ZX5T3hEy8y9dE9JrJBwM0oRVWsgg8kHkZWNjI4ufWEmvVBIxOTlZUfg1ZdslbPbk1a9fP5mfqCMQf+3atRXn1MWLFylng4uLCzM+njJlCk1oWTF+dnY25s+fj8DAQO589KdkeQnpH7RNmzZBEPhaUbdu3YIgCPj666+573Hp0iWufhxgDGAHDhwIPz+2+2sCAAAgAElEQVQ/pj81NRW9evVC/fr1mULNBGbbvn17rsbn6tWr0alTJxQoUIAZWBw9ehSNGjVC3bp1mcQ8N2/eRJMmTdC9e3eMHj1a4X/58iV69OiBAQMGMOdDMzIy4O/vDz8/P7Rp04Z5jcuWLYO/vz9XC/DQoUMICAhg3mudTocbN25g4sSJTLhvSkoKHj58iICAAKxYsULhF0URYWFhGDNmDJcAY/ny5ZgwYQIePnzInMHw9fVlzhMQGzZsGHr06MGV0vjxxx9RuXJl7N69m+kPDw9HoUKFaGJhar/88gucnJyYrK7p6emYP38+ChQoAE9PT4XfYDBgy5YtqFKlChwdHblzePfv38cXX3yhOge3d+9eHDhwgOvPzs7GypUrVRPSAwcOqM5/3r9/H0FBQdygJTMzEz/88IMiuCUmiiJWrVqFuXPncgsJu3btwo4dO7gzgSEhIdixY4dC25H8d2hoKAIDAxEdHS1LuFJSUqDX63HlyhUsX74cCQkJOHr0KE0IXr16hcTERISHh2PVqlX49ddfcezYMRrIx8TEICwsDHfu3MGyZcvovkGCq6ioKCxYsAAxMTGoVauWgrn55cuXOHjwIEaPHo3mzZvjyJEjisDM09MT1atXx8iRI7Fr1y7FfV67di2aNm2KXbt2Ye3atdyZpOXLl2PZsmXcRO/Dhw80ieCZu7s78uXLxy1EZWZmYsyYMUzNQsD4bI8cORLdunXjHtYLFizA2LFjuXDcHTt2YMKECbLCgdQuXLgAf39/+Pj4KHxZWVl49OgR/Pz88O233yruZVpaGl68eIFRo0Zh7dq1zILclStXMGvWLOzevZvJhnv69GksXLgQJ06cYI4rXL58GaNGjcLly5eZ9zEtLQ116tThFgbu3r2LIkWKKAoD2dnZWLBgAYXw8RAJwcHBsLa2VgTXxH755RdYWVmhfv36zOJvWFgYBMEIi2N14om/YcOGTObnZ8+ewcLCAl5eXggICFAEhTqdDm5ubmjSpAm++uorJoKjY8eOqFKlCho1asTsPhL5oNq1azOLsiQpdnd3V9xHg8EAX19fmmCMHDlS5n/8+DEtYGm1WkrMR1hypR0vErhGR0dj2LBhCvg9eUm1UI8ePaqASZrqYd+8eVPW6WWNBZEkwMLCAlWqVFEUNhMSElC8eHFYW1vD2dmZWYANCAigwTkLWREeHg6tVgtnZ2csXrxY4U9LS0O5cuXg5OSEXr16MecgfX19YW1tjdq1azPPoVmzZtFrME2ss7OzacFTq9XKuvU5OTkIDg6WyTxJ46moqCgMGDBABnk1HSsRRRG7du2iCWOrVq0U15eTk4Nhw4ZBEIwyd6xzcO/evdBoNChZsiRzLvfatWuwsrJC6dKlmbwaDx48gK2tLcqVK4dJkyYp/M+ePYO9vT3Kly+Pjh07Ks6Qly9fIn/+/Chbtiw8PDwU+9abN29QoEABFCtWDKVLl1ac92/fvkWhQoVgb2+PUqVKKbryKSkptMtZvnx5xfx9bm4uJapzd3dHhw4dFIUqwkbv5uaG8uXLKzrzhCeiaNGicHFxUdxHnU5H+RrKli3LLMRfvXoVFhYWcHd35/ITzJs3D46OjujTpw+zsGowGNClSxd4eXlxz9K4uDg0b948T/blz74+5YRUp9Nh586d3JlEvV6PAwcOqHalCLyPBQ3Mzc1F79696cZiaqmpqRg2bBitmJlWkd6/f48FCxbQQ8fS0lL2wCYnJyM4OFimQyqVBsjKysLOnTtlOmS+vr7UL4oi9uzZI4MemLLUHj9+HGPGjKF+d3d3mT8yMhKjRo2iFbvSpUvL/BkZGRg4cCDtyJj6AaMWINmgWffpzJkzVIu1evXqCn9WVhbdvOrXr6/wA6Baq82aNWP6CbSsePHizAOAsBi7ubkx2dnIzEGVKlUUG5soinQW6osvvlBsKmlpaShfvjytFJomAEePHoWLiwtq1KiBMWPGKILO169f49y5c9i5cyeCgoJUpQru3r2r2lHJzMw023H5L876qM165OTk4Pz581y/v78/d4/ZtWsXMyAAjEFBgQIFZL+nlGa/RIkS3O5ip06dUK1aNeazQDR1TTtBxH744QfUrFnzL5lvOXnypKqG5I0bN7hFHMBYyOEFyAaDAYMGDaJ7j2lBj7DvkgDR9D1EUcSIESNoIM6CZwcGBtK9xc7OTuEnhSQSwJqujdzcXNpNt7GxYf4epBvg5OTE9G/duhWCYCT3YXV9CESuatWqzL1rx44dEAQjo7JpgebXX3+Fp6cnunTpIusgSC0nJwdnz56l6BmWRUREKKDrUgsKClLtUE+ePFl1XxkxYoRql3zs2LHIyMjgvse6detw//59rj8iIgJBQUFc/5s3bzBo0CCuPy0tDR4eHtwiWk5ODlq1aoUtW7Ywk6T09HT07t0btWvXZhYML1y4QCVPCEt9fHw89u7dCz8/P1kM4OXlhY8fP+Lx48cySSPysrCwkK2Vw4cPy7R2SVdNaqR4L40DpOeUXq9HixYtuJ9BvoO0Ozhz5kzZb5qVlSWDV3fs2FFxFg4dOpT6q1SpouAIkKoBODs7K2ZX58yZQ/22traymeQnT57IJPA0Gg1CQkKo/9q1a1i0aBGGDx+OVq1aoVy5cky+i6ysLBw8eBA9evTgIpbS0tIwZcoULuqNFFVZTQpiGzduVPUHBQVxZewAY+ExJCSE+0yvWrWKSSYm9S9dupTbiV63bh1Gjx7NLTZu3boV7du3566ZkJAQlClTBmlpacxruHfvHqytrREfH8+ERqempsLV1RUhISHcoqqfnx/GjRvH3ZsePnyISpUqqSL3Zs+erSoRpdfrmY0SqZHCpZp9LrKAeQnp/7NNnz6dG5CmpaVR+AMrsY2IiKDJWsOGDRX+zZs3y7DsUiFiURSxePFi2UFhqnUaFBQkOwRKliwp24AuX74s0xC1srKSHZjv3r2Dh4eH7DNMtcGk+mKCoCR5CQ0Npd/B0tJSsXA/fvxIK7g8aQSC+a9VqxbTT2QXWFqvwG9EM3PnzmX6e/ToAUEQmCydoijS61+0aJHCHxcXB0EwMqqyZm9DQ0NpNZRFejJ69Gj4+voiNDRUcW8IEVbe7Nrfa2qVx9jYWCxdupTpMxgM6NOnDzcxJMkCq1ObkZGBUqVKYfjw4cy/JYyErJmsyMhICIJRXJ5lJAk6duyYwkeCNkdHRyZ0jyRAM2bMYL43YJ7h+K+0lStXMjv/gLHSTiSzpPA4YpGRkciXLx+3G/Hs2TMKmXRxcVH4s7OzaZBsY2PDvIbBgwdDEIzQNpZt3rwZgmAkv2DZlStXVH/L27dvQxAELFmyhOnfvXs3bGxsuBDEzp07Y+3atczA0xyM+Z8y6f5mMBiYib30v7dt2yaDIZsWT7Zu3Sq7H6bBXHR0tKKILH2PP3KvzHUvUlNTVYszoihytaqJXbx4USHrRiw+Ph779u3D6NGjERsbi82bN2PJkiWYMWMGAgICMGLECPTp0wddu3bF3LlzYTAYEBgYKIsPBME471u3bl1aYDh06JBMKkoQjPN0M2fOpPdp+vTpMr9Wq0WnTp3o/kLm/qX/pm3btrh9+za9fulso0ajQadOnWTw6iNHjsiSyX79+smkp86ePUuv09PTE3PmzJEVh+fPnw8nJye0bdsWM2bMwLFjx2iHVBRFXLhwARcuXMCtW7fw5MkTJCUlmR3V+bPFW3N+c+e+OSZrtaKiKIqqUH6DwaDKaqzX62lMm5KSoii0GAwG+rxHRkYqnn1RFOnvd+jQIfz888+K6yUFgRUrVmDdunWKLidZL4sWLcLcuXMVBYpz587h/fv3OHDgAKZPn664hrS0NPzyyy9ISUnBmjVrmGuYMPV//PiRSxaax4vym+UlpP/PZo49NysrC126dFHIKxB7/Pgx3N3dYWFhwZy9OH78OK1gsiCrW7dupQkTSxx+7969dKZOEARFUnT16lUZzMSUFTQhIYEGuIIgKCrlRK6F+FnBKkkYBUFgzp+Eh4fD0tIS9vb2zHuUmJiIQoUKoV69ekx/VlYWSpYsiQkTJjD96enpsLe355I9jRs3DqVKlWJWrwn0sEuXLswDZM+ePcifPz+3Gtm/f3/8+OOP3HkUc3O1eaZu5jp5Z8+e5R68BoMBkyZN4pJ8PXr0CKVLl2YmOwAwadIk5poBjJ1rZ2dnWFtbM/+WVOt79uyp8GVmZtLOG4tkZOnSpTQwMw2UdTod7Ro2atRI8bdz586la3HQoEEKP5Gz4JEZAcaOlVpn86+2RYsWcSvEDx48QMGCBblwd6Lr+sUXXzD9hJGZl3BGRETAwsICVlZWTH9iYiIKFCiAUqVKMf05OTkoXbo0OnTowPSLogg3NzduFT0rKwsODg5cMpiNGzdi3bp1TJ9Op1OF4H+KlpubCz8/P1UZkTVr1qBYsWJYsWIFc20/evSIzkuyxlgIKmX8+PFMdFNCQgKGDRsmg76a+j93LcIzZ85g0qRJWLduHUJCQhAZGan4ThcuXICNjQ3y58+P9u3bIzAwEBEREbLfRTpD27BhQ6xZs0ZxxhPmUxcXF0yaNEkxS0eguk5OTpg4caIiRomPj4eLiwuqV6+O1atXKxAnz58/R/v27bF48WJmAS8rKwuPHz/+T6J7fq9dv36dm4Dr9XrMmjULISEhzDWZk5ODNm3aYNy4cUykRFZWFqpXr46GDRsiODhYcWalpqaiQoUKKFKkCAICAhTv8fHjR7i7u8PKygrdu3fHkSNHZNeanp5OC4eNGjXChg0bZPslYb0VBOOs5/fff6+I2Tdt2gSNRoOmTZsy9XZTUlLg5eWFsWPHIiIigvksZWdnm0Wh/dstLyH9DEyn06ky3yYkJKB27drMjgbwWyeVxz4qTVpZlfKTJ09Sin0WoUxERASFBn///fcK/6tXr2gXc+3atQp/VlYWnXVhBdCiKNK5CGlVVGqBgYEQBIFb9QsODubO0QJGiAhPhxAwwn14G+6yZcuY87WAsWBQvnx5brVwxowZXFp7g8HAJc36L5soimY37dTUVNWugyiKWLFiBbczRBineTDtjIwMdO/eHVqtlgmpvX//PiVkYZERSNl4TWdo9Ho9hdiZEiMBxvVE1mvr1q0V/i1bttD3ZjEBS0knTNfbo0ePZJ0I033HlGXR1C9lUaxQoQJz5m7ixIkoVqzYP6a1Joqiarfg7Nmz+Oabb7j+iRMnMjVjiZEZQF5xY+rUqbCwsOD+/YoVK1ClShWuf+3atcz5fGJTpkxRlaxRg3w9ePDgswqADAYD5s+fj82bN3Oh7Ddv3oRWq4Wrqyu+//57RaE2NzcX1apVgyAIKFasGFauXKlITMksoIWFBYYMGaKYMSZkR3Z2dggICFA8yxs2bIAgGInHfvrpJ1kgnpmZiQYNGqBHjx44cOCA4rOjo6Px9OnTz+p3MbXMzExs2LAB4eHh3MJAbGwsWrZsiSVLlnBnuI8dOwYvLy/s3r2bCX3MyspC7969sWnTJm6n6eDBg7h+/Tr3fv4b5TP+V3v9+rXq87Z79278H3vXHRbFtb4PXUCwFxQNIsbeFXtMVLB30URFxdhrImoSO9bYu8YWOxYUxS6i2HvBgtiliFTpLGV35/39sXdO5sycGbz35uaa+/N7nn1yrx+7OzvlnK+83/vOnz9flcDs3LlzKF26NCZMmIB79+4pPuvx48ewsbFBuXLlMH36dEXRICIigsaYTZs2xdatW5nEU3w/ISbW2e+//x7Xr1+n33P37l2mcdKoUSOsW7eOJpa3b99myJxKliyJ8ePH486dOxAEAU+ePGE0tq2srNCjRw8cOnQIOTk5SE5OZiRpzM3N0a5dO2zfvh3p6ekQBIEhW7K2tkaPHj1w8OBB+nyHhYVR8rAqVapg9uzZeP78OXMepk+fjmrVqsHPz0/1XL979+5vq01ckP3pCSkhpAIhJJQQEkEICSeETPzHvxcnhJwjhLz8x3+LFfRZnxPSj7eMjAycOnVK1S8mRryKLmCacShevLhq8HLlyhU4Ojpi6NChXP+9e/dQvHhxLnkHYKpCOjs7Y/jw4Vy/KC6/YMECrj8vLw8tW7ZUTbqNRiPat2+vytAnCIIq5BYwVae0mGq1gmet6uCjR480IYpaMj3/H00LLSDa9u3bNYmPsrKy8NVXX6ne63q9HmPGjEG5cuW4m7BOp6ObC0/mIC4uDo0bNwYhJm1Bud27dw8lSpSgMHL5dwQEBFCoW7FixRT+efPm0Y2tYsWKis+XbnyNGzdmfIIgMCyIclmYrKwsRupCTgR24sQJJuHs2rUr45dqN4rwNmnAKddelJOwACb4GyEEbdu2Vd1Y1ciz/lMmQqt4ptfr4enpqZrU6nQ61KpVS7ULmZubq9phBUwBsdq6Kn4+j1xEtNevX2sGKH+X+SHR7ty5g2fPnqn+pri4OJQtWxZWVlbo2rUr/P39FYUPX19feg86OjrC19eXmbMKDg5m7lN5YvrhwweG9Mfa2hrjxo2j65PRaESTJk2o39bWFr6+vnSfMBqNDNOtPDl++fIlRRY5ODjA29sbJ0+eRH5+PtLS0uDu7o6SJUuiU6dOmDNnDk6fPk3RMMnJyQzz9d/VCmJvBgpmoM/Pz//bn4e/wkJDQ3Hx4kXVdfX27dtwdXXFwIEDsXv3bkW8o9fraSGzXr16WLhwoaKbLDK+EkJQq1YtLFu2jNmD16xZwzxzbdq0wd69e+leLhZxxFfhwoUxfPhw3Lp1C4IgKN5PiGkWeNmyZUhISGBmgKXPbd++fXHq1CnatOB9xqJFiyg/gvxVtGhRDB8+HEeOHOHKphUqVAheXl64ePEiw/otXX+GDBmCc+fOcWVxGjVqhJUrV+L9+/cwGAyMVFTDhg2xbNkyprj++vVrVKtWDSNGjEBwcPD/VEHlP5GQOhFCGvzjfzsQQl4QQmoQQpYQQn7+x7//TAhZXNBnfU5I/1xLSEjgsqqJFhERoVmJv3//PndWVbSHDx8qAmSpvXjxAt26dVP1x8TEKKQ0pJaQkKCgCJdafHy8ZoL3MVqYn+1fs4+ZUz1x4kSBlb3hw4drBioxMTEoUqSI6rXU6XRo06YNypYty/Wnp6ejY8eOIIRg2LBhCv+7d+8oOx4hSoj6o0ePULFiRepfuHAh47927RoDYe/Zsyfjv3TpEqODJmeRvXr1KjP3XaNGDcZ/8+ZNZjNzc3Nj/NevX2f8ciioPOEsXLgwk9yvWLFCsWFK1wwpMYj4krJuymUsCFFqja5bt476/Pz8FNcAAHbu3Kk67/bfsMTERE1yiidPnmgGzzwyM6nxGHKl9v8p6H737h2qVq0KOzs7uLu7Y/jw4Vi3bh3DUHvx4kXmObGzs0O/fv3w9OlTAKbCi4uLC3MfWlhYYPLkyXQN6tatm+JerVatGn3mly9fzg0ug4ODASifRfE4xOJBRESEQufUwcGBsv0eOXJE8f7ixYtjx44dSE1NZUhyxFflypWxbNkyuLm5wczMDA4ODihXrhyqVq2Khg0b4ptvvqHnSRAExMfH4/r165T1e+jQoVzNQkEQcOfOHfj5+akGuNnZ2apM7+JnqMGURStIekKt6y09Bi0zGAwFFmAKCuD/DB3Sgr7jY45TS5M7NzcXMTExNCHft28fpk+fjqVLl2Lr1q04fPgwLly4QIswHz58oPvaF198gW7dumHWrFk4cuQIfR6CgoKYed+6deti6tSp9HlITExkuoSEmHg5xJGU/Px8SvAofea+++47WkDp0KGD4p4uX748Hjx4AEEQFLq+YsInkoaJ0Fnpy8bGBhMnToROp4Onp6fCb2VlhREjRiA6Opr7/ooVK2LTpk3Izc1V6IMSYiLDDA4OhiAI3KS3VKlS2Lx5M/Lz8/HkyRMFyZe4T+/duxd6vZ77HWZmZvD29kZGRgbi4uIU+sRmZmbo168fvf/Pnj1Lr1Xx4sXh4+ODkydP0mspCAKWL1+OcePG4dixY3+bEYE/PSFVvJGQIEKIByHkOSHECX8krc8Leu+nmJAajUZs374de/bs0YRJCYKA4OBgzSDlzp07mhpuH2sfUwEvqOMgblJqCV1WVhZSUlLw/Plz1e5UfHw8wsPDVROK9PR0xeC41PLy8jQX4Y+Ban5qZjQaC9ycCtqEMzMzNQkCgII3+rS0NM2g12g0amqIhoeH4/bt26oL265du+Dr66t5Py9cuBATJ05U9RsMBhQvXlw1EZFuaLx7Pj8/nwaZvJk7vV6P0aNH0+6knIrdYDBg5syZtDMiJ8MRtYVFIhxCCDNjp9frsXTpUto9JYRg2bJljH/OnDlMBXTAgAGMf9y4cfDw8OAmrIIgoHfv3mjVqhX1y8l0+vfvT1kzxWqu9LqPHz+esk47ODjAzs6OYYMcNWoUDaJtbGzQrl07fP/998znSzfKKVOmYMCAARReFRISwviHDx+OH374gblee/bsof5atWrh3r17imsVGhoKOzs7zUQuPDy8wETvs/17ZjAYCizk8ebuRNPr9fD392dGLd6/f48RI0agbdu2aNCgAVxcXNC+fXsm4Y+Pj6dyJoSYOpDyWevFixcz99q8efOY/UGuJ+jp6cmsxS9fvmRgfuXKlWNGJHJzc5ln3crKSjEXPWjQIOY75FJQUrQDIUTBCDx58mTGP2jQIOr/8OEDg3Yg5A8ugoyMDErWJ3117twZ586dQ5MmTRjCQen7xespMqf/8ssvVI6kX79+XIKZnTt3wtnZGUOGDOHu79nZ2Rg4cCD69++vut8dOnQI3bp1Uy1eRkVFoX379prQ2vbt22sWP2fMmKHJ2HzlyhWsXbtW1Z+SkqJgCZaawWDA2LFjVTXTBUHAtm3bFIVK0XJycrBp0ya0bNlSUZxNTk5GQEAARo4cCTc3N4oGMxgMWL16NZo3bw43Nzda8OzTpw89V/n5+ZTITnyVKVOGkSFKS0tDixYtmL+Rj2ysX7+e8Y8dO5Y5zlu3bjFFlqZNmzIx29u3bxlt3FKlSjHIBHGeV5qwStl+ExISULp0aeYYpGNe8fHxCv/gwYPpeYiLi1P4GzduTOOWxMRERmeVEBPrsxi3ZGZmMqzThJg6pKLslSAIikKWhYUFM4cvEvvJ90HxGKUzq+Lrq6++Yta/S5cuMQW38uXLK3IJqZ6qlZUVjh49yjw7er2eMmVbWlqqjpV9SvYfTUgJIS6EkGhCiCMhJE3mSy3o/Z9iQgqYkrf69eurwksBkyA2IXzJAcC0gNjY2KBq1aqqn5GZmYk1a9bQqi/vM9auXasKgxUEAbt27cLMmTNVj/XChQtYunQp6tSpw13onzx5gunTp2PIkCFcSHBMTAx++uknbNy4kaullJKSgqVLl+LAgQMYMmSIwp+Tk4OdO3ciMDCQ6wdMbKNHjx5ViIqLdv36dRw+fFhVR/Tp06c4cOAAjh07pviNqampePfuHXbv3o0XL14oKrBv3rzBixcvsH37dmRlZSn8ly9fxrlz57B69Wpu8eH9+/cYM2YMli5dqkrN3aVLFyxYsEA1IVyzZg26deumKp0QERGBL7/8Env27OH6IyMjUbNmTa5ESGZmJtatW0cr7Dx7+/YtevbsCVtbW9Xk2Wg0omPHjqr6noCpezZ9+nTVgkVcXBwmTZqkSmev0+mwY8cOeHl5qXZa37x5g969eyuEqkXLzMxEp06d4Obmxi2+GI1GeHt7o06dOqqfMW/ePLRo0UIV8rtr1y60bNkSzs7OXMKiM2fOwN3dHV5eXpgzZ47Cf/PmTQrVk2rvigWZp0+fYuDAgVi7di2++eYb5hhev36Nd+/eYejQoVi7di22bdvGJG0HDhxAYmIivL29MXfuXLx//57pakyePBnh4eHo3bs3FUWXFkP69euHNWvWoF27dpgwYYIC2nX58mXUqVMHvr6+8PHx4eoJnjhxAkOGDEG3bt3w7t077jmOjIxEjx49NAXo3dzcYG9vr5owpaenY//+/apQWkEQ8Pvvv2uykwYGBuLMmTNM0i61ixcv4sSJE4xkltQePnyIffv2Ye/evYrjNBqNiIqKwrZt23Dv3j0FXD0jIwNpaWn4/fffERkZqdC41Ol0iI6Oxq5duxAbG8udNz9x4gQOHz6MyMhI7r26ceNG7NixQ3XtCQkJgbe3t+o4w5UrV+Di4qIo7uTk5OC3336jCd2UKVMYf3JyMiZMmECLJl9++aXis5OTk2lXx9raWnEvGY1GGhxaW1tz+QfEboSDgwMmT56s8IvEYsWLF4eHh4eiCy7ORJcsWRJubm6K7mJsbCzs7e1RrFgxODo6Ks5TXl4eatWqBXNzc9jb2yug13q9nhaYrKysFDPfycnJqFu3Lg08pQgjQRCwY8cOpiPj6upKO6M//fQTHBwcFMFxWFgYZs2ahapVqyp8hBCmEx0aGooGDRow/i1btjDH+OrVKypNVqhQIW7RMSAgABYWFnB0dORqzqanp6N27dqwtbVlEgipiTDsevXqcRmHT58+DUJMEEweY31MTAzKlCkDV1dX7tqu0+nQsmVLODo6cvXhc3Nz0bdvX3oM8n0sLi4OXbt2BSGmUQzpGEB6ejoWL15MeQWsrKwou3pWVhamTZvGFEcIIYz+vCAIOHnyJKNawOMECQoKogVVa2trxdqXmZnJSOzwyBTFZ8LCwoKbWG/atIn+hp49e3JHUggxFTSrVaumICES2eNtbGzg6OioKGKLKB5ra2uFfA5g4jwhxNQ1tLCwwPz58xm/FKVjaWmJXr16MccYGhrKdBerV6/OJNWPHj2is56VK1eGo6Mjg5RKSUmhrM/if+UoIJE9XbymcoWF8PBw+txaWFjAy8tLcR5FiLGVlRVq1qypuN8EQaCEoKVLl+bGl5mZmWjYsCFsbW01R9I+FfuPJaSEkMKEkHuEkF7/+P8flZASQkYQQu4SQu7y5qc+FSuoa5Wfn4/p06cz1ONyW7VqFdUF44JrKoAAACAASURBVJkIbeP9jSAI8PPzow+WnMAlJycHGzZsoNUq+SxZRkYGgoKCmE1JGpRkZ2fj3LlzTLdGKjZtMBhw8uRJyoBH/lGxk9qJEycYSnc5y+2lS5cY6Rl5ch4VFQVfX18UK1YMZmZmcHFxYfwGgwEjRoyAm5sbzM3NuUyVfn5+qFq1KiwsLFCuXDmF/8KFCyhdujQVipYvCs+fP6cVwUqVKikC6NOnT9OOW+fOnXHo0CHGf+PGDfr7evbsqej+paWl0UpYx44dFQmMwWCgQV2rVq0Ui3deXh4NGBo1aqRIGG/duoUyZcrA1tYWvXr1UlSvs7KycPPmTWzZsgUrV67U7EAXxLj5MTNBf5VpddoB7a4OYKqkqhWCANPzp5akiP6QkBBNmGdOTg5FWah1FaKiopCenq5aCMjLy9PUk9OC2F27dk1BSiRe/3v37nErqvHx8Th79iyXYRcwBWVffPGF5vlPS0v7U/Rq9+7dizVr1qj6xW4tL1ETBAGjRo2Cubk5d05X1CEVA3r59+j1evj4+KBChQowNzfnMhL7+vqiZs2asLCwQOHChRX+jRs30gDTyspKEYQ/efIE5cuXByGmDqE84BAZdsUqPi95F8mxKlWqxNU1FDvederU4cItxcCqSZMmirXvzZs3tNvRpUsXpvN2+PBhTJgwAZ06dcKXX36pEKcX7dmzZ+jatavqPih2dXhddMAUHLq5uakSmCUlJcHZ2RnR0dHcgmt6ejrKlSuHN2/ecO9ZQRDQokULXLp0SZVgbsGCBZgzZ44qGurmzZto3LixKg/B+/fvUaZMGdy8eZO7DiQlJaF27dqYNm0at4ATERGBunXrwtXVVXGeUlJS4OfnR1m358+fj7y8PFy+fBlz5sxBq1atmESoadOmiI2NxbNnz7iQZisrKyb4Pn78ONMRI4QoCMIOHjzIdHuqVavGnGu9Xk/HKMRERL7XSMnSeElxdHQ0ndsnhCjksHJycuDu7s78Tnk3Sfp7nZ2dmUQqIyODIYNzdHRkCkSHDh1ivt/a2po+jyIioF69elRGyszMTLHXJyUlYfPmzWjXrh3Mzc25z6vBYMDvv/8OZ2dnVc6Qt2/fonHjxggKCuL6dTodOnbsqFqIMxqN6NevH3bu3Mkt9gmCAB8fH2zcuFE1Bh45ciQWLFigyuMwevRojB8/nluwFP3dunVTlToaN24catWqhQcPHnCf6x9//BF2dnYICwvjHuPs2bNRokQJvH//XkEsBJjktooWLUrjI7ndunULVlZWePLkCZcxPjs7G7Vq1ULXrl0RGhrKPUaRGO327dtcBKMgCOjevTt+/fVXLswe+OO+1Npv4+PjVblXPjX7jySkhBArQshZQsgkyb/9T0B2/0oTgyYeUyZgClbd3NxACOEuLv7+/nQjKF68OLMAC4KgYMyUipsLgoBJkyYxfnm3Vz5kLoc4Xr9+nYF3lC9fnvGnp6ejSpUq1F+6dGnFb5DOrMnfD5gY9NQSWsBUwRZn9po1a6bwG41GWuXizbcajUYalPbo0UPhl0IUq1SpooA7iRqmYrVNDpuV6qN5enoqgtJDhw6BENOs39q1axWdwZ9++gkVK1bE7NmzFbBdQRDw6NEjJCQk/O2gzp+SFTQfm5WVpQmJj4mJ4XZKRdu/f7/qbHRGRgZat26tmthu3bpVFTmQkJCAEiVKqH5v586dVTVQZ8+ejS5dunB969evh6WlJbciq9frQQjhdqNE+yuhQ927d1dN9l+/fo1ChQpxu3MAO+O3efNmhT8wMJD6O3TooPCHhYXRYpWrq6vCn5mZSRMF3toHgBLnqHXjxYSyevXqXL9IgNWiRQuuXyw4DhkyROHPyclBkSJFULJkSUUHID09HR4eHhg2bBiOHj1aoM5mQc+Q1vuzsrI0/Tx9ZqlJIZzx8fEKqSxpEpeRkYHdu3cz98yjR48UsEXpucrJyfmnjoFnV69e1TxHCQkJOHv2rKo/JyeHi1ASLSMjg84Xyi0rKwunT5/GlClT8M033yAqKgpbtmzBvHnz8MMPP8Db2xudOnVCkyZN4ObmBj8/PzreIE9YxYRTXBv279/PJKPkHx0hKaJg/Pjxis/o1q0bDbKfPXumgB9XqVKFJhL5+flo1qwZ4y9dujRN6ARBoIUVacIpFo8FQWDiDHNzczRp0oTKeSUkJNCib5EiRdCkSRMMGjSIJnz379/HtGnTMHv2bMyfPx9LlizBypUruYVCQRAQGxuLixcvao58JSQkqMKCAVNSqYYuAUzdXLVkUPRrjZPl5ORovl+n02mOCel0Ok2iuOzsbFXEl+jXQq7odDqq781LmnNzczFu3DgYjUY8f/5csbYZDAbMnTsXaWlpOHbsGLf7uGnTJrx//x6rVq3ijpqJ8jB+fn64fPmyIjZ79uwZFi5ciKCgIJw9e5a7D4l6vHL0i2ipqama9wnwv0WM+acnpIQQM0LILkLIKtm/LyUsqdGSgj7r/3tCCpgeHDUNUsBUfatRowZXYxQwBU1iBVQOyxIEgWFGmzBhgsIvShoQwoeISJNaW1tbxaYqVoHEhV4++/fw4UMKj7C0tFQsHBkZGbQLwAvaBEGgg+xq94u44ckZRUUTN1Y18fjWrVuDECUsAzBB9sTfd+HCBYVfnHMqWrQot9o3btw4EGKaHeItrM2aNUO3bt24C1ZGRgaCg4P/ZynAtexjSJS0NlTgjzlvLbt3755iLkxqT58+RevWrVWTntDQUJQpU4YbPAiCgMWLF8PKyoq7qWRkZKB58+Zo0KAB97MvX74MKysrLhMwAAov4yUi4kjBrFmzuO+tX78+bG1tuV3vH3/8kbteAKZAQQw61SSaGjZs+JcRFhU0W71gwQJFIU00QRAoBE9arJP6xYSOpwcL/AEZbdq0Kdcv6snyimUAKCtjr169uH5R4kcNXv7TTz+BEKKq+1qvXj3Ur1+fe50DAwPRvHlzbvcxKyvro57Bv9revn2LM2fOqB6bmLxMnDhRdYRi8uTJcHFxoUQnctuxYwfq1KmDffv2cdfeW7duacqQ/DftYwqTH/M3V69exdq1a7Fv3z6EhITg4cOHiI2NZfYwUcO8WrVqGDhwIFatWoWrV68y3RyxqG1tbQ0PDw+sXLmSQQFlZmbSebsSJUpg5MiRuHDhAnPexcK5vb09BgwYQNmKRduwYQMtCE+dOhU3b95k7o+ZM2eibt26+PHHH3H8+HFFRy0kJAShoaGIi4v7XNj9Fy02Nlb13BmNRgQGBqqOVsTHx+Pnn39WFILE/x0cHIyuXbti165dzD4q3iNr1qxBtWrVMGPGDEbnU/zv3LlzYW9vDy8vL+zbt0+xF4tERnXr1oWfnx8ePXrEHMeZM2dgbm6O0qVLY8SIETh9+jR9DvR6PVJTU1GlShUUK1YMgwcPxvHjx+m6In7Otm3bUKdOHcydO1e1KxwWFqYpZfe/YP+JhLTlPwL0R4SQsH+8OhFCShBCzhOT7Mt5Qkjxgj7rc0L6cZaYmKg5iH/q1CkUKlSIG1gLgoBp06ZpdhDFKrulpaVigxYEgSF24D0wYlBECOEmVtu2baN+XiX80qVLMDMzQ7Fixbi/7/nz57CyssJXX33F9b979w7W1tb4+eefuf6XL1+CEKWmomiTJk1CpUqVuEHOtWvXQAhRhTCOGTMGlpaW3FkNAKhatSqmTZvGXazfvHmDgICA/1ebYExMTIG/NyoqqkAISmhoqGqyBZiqqkOGDFHMn0ht69atsLGxUWWm3r17N+zt7bkaloIgYMWKFbCwsODCOUWCJUIIVx83IyODElDI4WeAKfAW4ZK8gpW0u8e7b8VkVUqqJFpUVBR978mTJxV+kQnR1tZWAWNMT0+n723YsCE3YG/Tpg2KFSumCtf6KxMd8T5Qs7dv38LW1pY7nwiYChKWlpaqsi2RkZGwtrZWyOeI9uHDBxQuXBje3t5cf3p6Ouzs7LBkyRKuX7xWavfo2rVr0bZtW64PAGrXrq1KNHfp0qVPTlIgPj4eL168UF0jBEFAr1694OLiggULFnBlpK5evUr3s0GDBinOXXp6Op31c3Z2xrp16xjki9FopM+mm5sbNm/ezOyLgiCgffv2KFasGKZMmaK4z1NTUzF27Fjs37+/wM7y39VE7XQtds+wsDCMHj1atcMuCALGjBkDHx8fnDlzhnsvnjhxAl27dsW+ffu4sMXY2FjMmzePSUSkptfrC2S4/mymGEuLsPDGjRuYOnWq6sz/xYsXUadOHSxZsoQLPz1z5gwKFSqEXr164ejRo4rivFh4c3Nzw6xZsxQwW3E0zMbGBj169MD+/fvp/SAIAsNs6+bmhp9//hl3796FqFHds2dP6re2tkbnzp2xbds2JCUlKTRGxc+YMmUKrl+/DqPRqJCUKVKkCAYMGIDDhw8jKysL4eHhTJffwcEB3333HQ4dOkQLV9LmT82aNTF79mw8fvyYITmrXLkymjRpgiVLlnBRGUajUbXb+newPz0h/TNfnxPSj7eCNrbz58+rQvsEQcD06dNRqFAh7qKv1+vpA8ubIxTZ7wgh3LkHKfnEtWvXuMcwZMgQEEJUq9a+vr5wcHBQ/X2//PILQwAjt7Fjx2pCBdu2bavKHrx3715mflZqt2/fRqlSpRQwMNG6dOnChfsBps1yw4YNqsf0v2Za89SizZo1q8DZzQ4dOqgSOAEm9moHBwfs2LGD609NTaXEDjyWVp1ORyFeNWvW5PqHDx9ONw859CgrK4tho5WTbWVmZlL2O0KIIinOzMxkNAzl909GRgbDQCp/plJSUmhATQjhQolEKKl8rhtgZVl4OqJSFkK5TFNycjKzMfOIxnr37g1CTAzCPFRARkaGatf3P2Fqs4GiLVq0SLMAMmnSJE32aF9fX4apWG5TpkxRlb8BgMGDB2s+O3JpIakdOXJEEy7OQ3V8ymY0GtGnTx9UqlQJo0ePRlBQkCLpSUpKQpkyZWinvmfPnjh9+jTzHMjli7p27coUJKXIHkIInJycsHLlSho8Pnz4kIGilitXDitWrKBBcHR0NB31MDMzQ7du3XDu3DkaXIosmra2tujTpw8OHjxI35ubm4vJkydj6tSpCAgIUCWk+l83vV6vOYMPoED/ZzNZdHS0pnb3/fv3MXToUOzZs4c765ybmwt3d3fUrVsX8+fP55KgjRkzhnYSly5dqkAFzZ49myLl2rdvD39/fwaZIUXblShRAuPGjcPt27fpvS/GiOJLrt8p5TshxCTB1LdvXxw+fJjLWE0IgYuLCyZPnozz588rmG/FY/3666+xbNky7vvFtWHKlCno168f129rawtvb2+GXV7u7927Ny5cuKCQzSGEMN3dsLAwhsSsXr16mDdvHhMzrV69GjVr1sTPP/+Ma9eu/a0QdJ8T0o80vV6PmTNnYvr06Th79uzfRtdHamqD0cAfSakacU1ubi7at29PNafkJrJ5qSV9YhCtBj/Ozs5G7dq1Vb8/JycHjRo1Uj3+rKws+Pr6qvpjYmI0gy8tNs/Xr1+rzlvcv39fk5hK7XwB/1vaggEBAQUWRcaMGaNKtACYzkeVKlUYCnW57dy5E4TwIZSAqWMlkkvwWOUiIyPpxlOqVClFN+7169fMxjN37lzG/+LFC4b18osvvmA+Q8o4yUMFxMXFKVgrpceZmZnJyLoQQhjoq9FoRPfu3Rm/HJYq37jlMHkfHx/qk8vGAGC03CpWrMjcpwaDgZkLL1q0KANxiouLY77b3t5eUWSSEqGpJXKVK1f+ZIo1eXl5mnJVaWlpjDSB3D58+KDa4QRMYxdyMjSpXb9+XRP+qQVLLojc61MznU6HadOmYdy4cZg/fz62bNmC48eP486dOxSCr9PpmJlBKysrfP3111i0aBENgkUmTunriy++oMRtycnJjPyE+GrVqhWioqJgNBoVc4mEmMZGRDKZH374QeEvUaIELYRt2bJF4a9evTqdTVy5cqUigPby8kJISIgigC5VqhQ6deqE2bNn4+bNm/j1118xatQoWsxYsWIFtmzZgv3793M7J+Jvvn37tmrxFDAlLloyP2qwSun107KP0efUso9BT/y7hGl/Bqz5r/wMkYE3MDAQFy5cwP379/HmzRukpKTQ8/Xs2TO4uLigZs2a6N+/PxYvXowzZ84wYy3ieICYVE6ZMgXBwcH0msbExKBUqVL0b2rVqgU/Pz+aDOXk5KBevXrUb2Zmhnbt2mHHjh3Iy8tjGKXFl6OjI4YNG4bIyEjuLLCYkJ08eRLZ2dmoWbMmN2mcNm0aEhISFDqp4svDwwMPHz5kiKekr169euHSpUuUoVj6ql27Ns6ePYvo6GiFpAwhBAMHDkR8fDyys7OZ3y++unXrRs/z9OnTFX5HR0esWbMGeXl5iI2NpcU0+atZs2aIiIhgeEmkr3r16lH0iLTbWrJkSQwaNOijYrT/tn1OSP8JS0tLo8GkhYUFunTpopg3SE1Nxc6dO3HmzBk8evRIcwHNzMzUHEjOy8vT3Dz+TBMXNi3m4MzMTM3Zr7i4OM1k4u3bt5oJ2vPnzzV1BR8+fKjqA1CgVud/IgHU6XSan/sx1SmtyiVgStYL0potSGc2Pz+/wPPDg7cBJljU1q1bceXKFdXPCAwMhKurqyZRwYgRI1C+fHnVz7hz5w4IUbI1ixYXF0c1NHn3UWRkJJydnelCLA/Gk5KS8NVXX1G/HK6alZWFoUOHMtAaKTQoPz8fM2fOpDPNhBCGPdRoNGLp0qVUqoIQdnZQEASsWbOGod0vWbIks0Zs3LgR7dq1o35ra2smQNy+fTsluhE3fan/zJkzKFmyJNO9kQaBUVFRsLKyYgTQpWtQWlqaQn5ASsgSGRmpSDils9fR0dGMv0aNGoxeHvCHfAMhJmgTT6JBRGSokS4BpuemIA3fv8oKCrQLCtQ/1Sr2x2hcq60bop07d07RhU5NTUVoaChWrFgBb29vjB8/nt4jqampDIJALHxIO5iJiYlUO1N8zZ8/nzleERIvvrp27cokVNu3b1ckrNJk7u7duxRJQIgJDiiVpEpLS2OQCIQQ/Pbbb4w4vbxr88MPP9DigiAI+Pbbbxl/37596frI6+p4enoiLS0NOp0Oo0aNUgSlrVu3RmZmJvz9/eHr64uePXuibt26tFvbsmVLxTWNjo7GihUr0LRpU+54AWDa+/38/Lj6zqJdunQJ/fr1U/W/e/dOEx6fk5ODYcOGqfoFQaBENWr2+++/q8LXARO51Pbt21X9mZmZqozQ4jHMnDlTswh06NAhrFixguszGAw4cuQIw0otml6vx40bNzB//ny0adOGFi6ys7OxePFiDB06FF26dIG7uztcXFzQoUMHuu68f/+ecl1Inxkpc/abN2+YvYsQggULFjDnU6qKICZq0o5paGgos7fUr1+fId158eIFs39KyaUA070mErkRYoLNS8eSIiMjFUnhihUrqP/p06eUqVh8jR07lvpF9lupv127dvSeP3fuHLP3EWLSKRXj7NOnTyv87u7utCN85coVxedXrFiRNjsiIyMVha7ChQtTMjGDwYBOnToxfnNzc/z888/0frh8+TKVwxJfVatWZXIBueasnZ0dU7jOz89n4gxCCObMmfPJIwo+J6T/pCUmJlLImlQnSmqnTp1CkSJFVGcaAdMNU6pUKUb4Xm4eHh5wdHRUrY4LgoBnz54VuAAfPXpUFf8fGxuLGzduqC7CGRkZOHPmDDZv3syl3s/Ly0NQUBCePn2K9evXKwIro9GIy5cvIyoqCsuWLVP4BUHA48eP8fr1ay4DoCAIePv2LSIiInDq1Clu8hcbG4vw8HC8fPmS2xFISEjAkydPoNPpFAWAzMxMJCcnU6y+fLO+efMmEhMT8ejRI25wtnnzZkRHR+PSpUvcoPL06dM4dOgQjh49qhq0enl54eTJk6rVq3Xr1mHGjBmqA+1RUVFo3bq1KjQvNjYWLVu25EpkREREwNfXF1WrVuXCNwFToNCrVy8QQlTlUvR6PVxdXTF16lTVgGHGjBlo06aNKmvcsWPH4OnpiTFjxnCv87Nnz/DTTz+hcePG3IQ0Ly8PFy5cgKurK6pXr879jvj4eJQtWxalSpXidln1ej0aNWqEYsWKoX79+tzPGDRoEE2MeeyZS5Ysgb29PWxtbbnQ08OHD8PW1hbOzs747rvvFP7bt2+jTJkyqF69Oho3bqzwR0dHo3r16mjRogXKli3L+LKyspCbm4vmzZujbdu2cHJyYgKfZ8+eITIyEt27d4enpyf69+/PbGS3b9/Gnj17MGDAAHz11Vc4duwYM0caEhICHx8f9O7dG40aNUJcXByjW/j69Wu4uLigR48eqFOnDsLDw5Gfn8/cE/Pnz0erVq1QsWJFPHnyhPtczZkzB5UrV8aJEydUCz6NGjVSZacFTM+2FpOkuH5qFXNevHiBpKQkVUbLmJgYvHnzhisdAJj2iydPniAuLo67NqWlpeHBgwfIz89XzLLp9XpkZ2fj0aNHyM3NVewDHz58QH5+Ph48eIDMzEzFeUpOTsbr169x9+5d1bVl27ZtuH37tiriZ8mSJThw4IDqeQwJCUHbtm25hcSUlBTajd+2bRv99+PHj6N69epMsCTfK41GIxMcm5mZKWYxnz9/zgS38mJoVlYWw+IuJ4YSBIHp2FStWlVxL4jQfDMzMzg6OiqKonv37mWOUa7HGhUVxWiByvXAs7KyGG1J+Szxhw8fmK6LnBwrICCAkV0pU6YMDAYD0tPTsWjRIkVwbGVlhbS0NCYJlfodHR2Z9Vmv12PTpk008S5VqpRCa1okZ7OwsICTkxN3n4mMjISrqyvKlCnDjTWMRiN69+4Ne3t7jBw5kruXiqMEAwcO5M593rp1i87/8dAxCQkJcHFxQdOmTbkjHzk5OWjTpg2cnJwUyBjAhBITZwm/++47xT6XkJAALy8vEGLqhEvXDJ1Oh40bN9L7sWjRonRdjYqKQv/+/RWasVKisg8fPsDX15dBp8g5P/R6PaZPn06LKDY2NoqGRkxMDL788kv6GfIGg5wThMeWvmLFCuYY5OvOvn37qL9EiRKKYwgKCmKSMXncIuU/IIRg7dq1jF8OfZUXOUQSK/HVsGFDZg+Uz3uWLFmSSbpFIkpCTLq65ubmTGL/22+/gRBTMVbsZm7atIn6pUm7OFoj5YFITU2l6hji+93d3Zl9UK5gUapUKeYY5RBlCwsLZh8GTPeMdP0TCxyfsn1OSP8Fi46OxrfffqsZ7Dx//lxzdsdoNGLw4MGYOXOm6t8sWLAAvXv3Vk1kDhw4AHNzcy55iyAI2L17N602yaGSOTk5CA0NRY0aNWBpaQknJyfGn5mZiQcPHqBjx46wtLSEhYUF8xk5OTm4efMmnRtwdHTE+PHjme8PDg6mOqMlS5bEN998w3zH2bNnKaGRk5OTQn7h5s2b2Lx5M2xsbODs7KyAFyYmJuLHH39ElSpVULZsWRQvXpzZyARBwODBg+Hu7o4iRYqgcuXKisVx4sSJtKPVtWtXRdI9cOBAunj8/PPPCmHz/v37UxiIn58fTp48ySzQa9asoRW1KVOmKBjaXr16RReM4cOHK2DVUh3SPn36KLqLer2eEmx4eHgouq3nz5+nMJPmzZtzCwJhYWGYO3eu5hycwWBAUFCQZjf4/fv3/3a3+GNNC8JoMBg0IdjZ2dkIDg5WfX5zc3Px6tUrVY1LQTAJz6sR2QCmbu706dNVK+mJiYm4fv26JgQ+PT1d8xhycnIUwaHUjEYjXr9+XWCXS6tqKr+e0k4fr+snFne0umZiEqrV6YiPjy8Q0fDTTz+pkgEBpvWFR9okfb+1tTV3TtZgMGDYsGFwcHBAyZIlce7cOcafn5+PUaNGwcXFBeXKlVPoPAuCgIkTJ8Ld3R3FihWDk5OT4jrMnj2bdsNr1qypKCxu2bKFah+2aNFC0Um+ffs2DXjat2/PSGkApoCkaNGisLKyQpcuXRR+AChdujSsra3RsWNHLvpF7MZ37NhRMTeWlpZGIXI9e/akv08QBAQEBDDQMznpniAIOH/+PHr16gULCwtVArLDhw/D3t5eEZSKduXKFdjY2GDPnj2qjLfi3sVDIz158gSWlpY4ceIEF5admJiIokWLYs+ePVw9QkEQ8PXXX1N4I89+++03VKtWjZkhldqLFy/g6OiI3377jdvxT05ORr169eDl5cUdaXn79i2aNWsGR0dHxaxzVlYWVq5cCScnJxBC6CxzeHg4Vq1ahc6dOzMdp2rVquHNmzcQBAFBQUHMvLiYQEjvw5SUFIVeqXxe+uXLl6hYsSL1u7q6KtYOKfzZxsZGUbSUd+akBQ7AtF6Imr2EKGffc3Jy0Lx5c6YAIr0W+fn5lKyNENNsofQYU1JSmA5k8eLFacIpCAL279/PJP+2trZ0D7p06ZJijMPCwoLptut0Ohw+fBheXl6wtbXlxmyAKbH39vaGmZmZKkeCiJJZvXo11x8fH49atWph3rx53GcmLy8P7dq1w4wZM7j3oyAI+O677+Dr66sqdzRy5EgMHTpUVT94/Pjx6Nixo+oY1fjx41GzZk0EBgZyn5kRI0agcOHC8Pf3VxTbpCRGmzZtUhQLBUGgpH47d+5U6LkKgoB+/frB2dkZERERCs1b8fc1adIESUlJWLRokeIY16xZA2dnZ+Tm5mLhwoWKgt/jx49hb2+PwMBAbN26lXuM4m9YunQpVxYuOTkZlSpVgpeXl6IQJtqzZ89QtGhRzcLup2SfE9J/0QqCWf4VlpeXh6ZNm3IDKsC0iIsVNVGzSWryGRhpBV/OPEYIYeakxGRP6pfrlC5fvpzxyyt6t27dYuAR8q5WVlYWs8lUrlxZ8Rv69Omj6Zceg5ubm8IvFdx2cXFRPLRShmBLS0uFNpj0+wkhCibjCRMmMH75Rrpx40bqc3R0VJBCiTqkhBB07txZkeBMmzYNXB8JwAAAIABJREFU5ubm6NChA/z9/ZlELT8/H6Ghobh//z4iIyO5XZS/q33MLNHHyC6kpaVp0tEDUGVhFAtFOTk53ORWrMoajUZVFIPBYIBer1cl+xIEASkpKZpQ6KtXr6omgIIgaM4nas3DR0dHqwYMsbGx3AQHMEnlaBU3CpLa+bPs3bt33E6JaNevXwchRHVWVTrjxyNbmzNnDvVLi3GiSSv1PMms0NBQ6re3t1cEh7GxsbTbYWFhoShG5eXlUcksMzMzBYLCaDQy0C95kC8IAvXb2Ngogsf4+Hj6/TVq1FAEn+KsctmyZTFjxgz6DCQlJSEwMBABAQE4cOAA/P39cejQIdXnLCYmRvX+B0xJoxbD58GDBzWLXdLAXa/XK/5W2t0ATKMD0mP9/fffmf1eTNhECw8P1yw+C4IAf39/VT9g6hppzXclJydryr/l5+dj+vTpqsXrnJwcbNy4UfFbAdN9dOXKFcyaNQsdOnRASkoKLcjNnDkTo0aNQu/evfHVV1+hevXqWLVqFQDTc16pUiVmfyPENH8oQrQjIiJQrlw5xm9jY8N0a6QdN/E1ZMgQWijjwSAbNmxIO+b5+fnMKIZY4BbXTB5Lqp2dHU2sDQaDgpDGysqKdlHfvHmjSMydnJzg7+8Po9GIjRs3wsPDg748PT3h6emJI0eOMOc5NTUVN2/exPbt2/HTTz+pMu9nZmZi3759io6X1MLCwjS1bWNiYjSfmeTkZE2d0/T0dC5xkWhZWVmaI1Q6nU6TiC0nJ0dzX8rNzdUkttPpdJrKEtnZ2YoGiNQyMzPRuHFj1TgiKyuLwuvVkvaNGzciIiJC0WQATPfc9u3b8eTJE2zevJm7PwcEBODevXtYtWoVZfyV/8b69evj5cuXqgidsLAw1WKdaJcvX/7bxH2fE9K/ucXExGDcuHGq/oMHD8LMzAzDhw9X+IxGI4WYEKJk0M3KymLgQnLZlOzsbKbyJxeHNxqNzDwcDwIpahqqBW27d+9mNiG5hYWFUX+7du0U/sTERNqh5HVLPnz4QIOuKVOmKPxr166ln8+T35BWh3v06KF48KXzAjytQDHpd3Z2VmwwgiCgSZMmKFu2LA4cOKD47MjISKxYsaLAGa6/m6nBgkUTBEGTRAYwBSlaGxZg6mIOHDhQ828OHDigqvEImIKVFi1aqM6CJycno0OHDooOm2hJSUlo06aNIngRLTIyEtWrV1etNF+5cgUVKlRQ3XBmz56tyq6dmpoKZ2dnVeKbCRMmqCZr27dvh6enJ9d38uRJWFtbq8q6eHt7q/7ev9IEQUCdOnVUA7/MzEwUK1YMhQoV4gYuHz58oN0lXic7Ozuboid4OqWCIFD4HE/6BwBFP6jN9olszPK1VzQxGeCtfVKJHh4TuCi10L59e0UyHBQUhLZt2+LQoUOflDRMenq6JuGgIAjw8fHBtm3bVMl7Nm3ahKZNmyIkJIT7XIlsmGfOnFHteG7btu2Tn9f6dywnJwf+/v44evQoLl26hMePHyM2NpbpKj5+/Bhly5aFm5sbvLy8sGDBApw8eZJB0hw8eJDeg3Xq1IGvry/OnDlDi4nSGMTS0hIeHh7YsGEDgyQSdcYJMUEflyxZwiRbCxYsoIlwx44dsW7dOro2GY1G+Pj4wN7eHm3btsWsWbMQHBxM1/Ps7GwsWrQIa9aswfHjxxEeHv5J6sv+L5qcTE9uUsQJj7BTvIZRUVG4ePGiAqGSnJwMQRCwYcMGrF+/XlHsNxgMyM7ORqdOnTBw4ED4+/srSL1yc3PRsmVLVKxYEaNHj8bJkyeZZ0AQBDrr7e7ujnnz5uHhw4f0twmCgAsXLsDCwgIVKlTAuHHjEBISwswGGwwGdOzYEU2aNMGvv/6q6KYaDAYYDAYcO3bsk+FU+Fftc0JagGVlZX3yF7kg2YLVq1ejdevWXF9OTg4NangVq6ioKAq94gXvItyIEMKdd3v37h2d86lWrZrCn5WVRQft69atq/AbjUa4u7urJpzAH0khL+kGQJNuNfhj48aNQQjB7du3Fb7AwEAQYiKX4ek7dejQAYSYhvd510EMOH18fBTBi16vh6OjI+rUqcOtgF27dg0jR44skLDo72KvX7/mUspL7f79+6p6saLt2bNHNRkCTIv80KFD0aZNG9W/efv2Ldzc3FTRBUajkTLiqXVvTpw4gaJFi6J3795c/61bt1CxYkU61yW3Bw8e4IsvvoCdnR03yLl37x7Kli2rID4S7fLly7C3t1d9LsRZGzXoltjh4qE94uPjYWtrq8pc3a9fP1haWnLvza1bt4IQgsGDB3PfO2LECJQoUUKV9fuvFKDfsmWLJuHQrFmzuIUy0SZNmgRCiAL2JZo4B6kGSRVF19WKBmL3SE0WZvLkySCEr0ULAPXr11ctDrx9+5ZeJ9757tWrF8aPH8+FfBfEtvrfMoPBgC5dumDYsGGMZITUwsLCYG5ujgoVKmDt2rWK66/X6+lc59dff81FJ4iFxObNmyM4OFjxPX379kWZMmWwYMECxbkyGAxYvHgxzp0798mSWf0ZFhERoVkcePHiBYYPH47du3czbK+iicWDnj17YteuXdw4bPfu3WjVqhVWrVrF3Z+vX7+OESNGICgoSFWn9N69ex9F3vX/3QoqsDx79kwzWT979qyqpJvRaMSvv/6Ks2fPcve66OhoeHl5YefOndx7avfu3ahXrx4WLlyoKGgLgoABAwagRIkSGDx4MAIDA5l7ISMjgzZWateujV9++YWRS4mLi6OQc3Nzc7Rs2RILFy6kiWVSUhIdqyLEBNcWRyRiYmK4BEMVK1bEuHHjEBwcjLy8PEZqjRDTjPHAgQNx6NAhZGZmIiUlhZkHrVGjBmbMmIF79+7Rtef48eOwtrZGmzZtsHr1ak3irU/VPiekBZggCBgyZAiaNWuG2bNn4/r163/LxUuE2fDsw4cPqF69uqrW5vXr12Ftba2a1B4+fBiEmGZDeCbCTl1cXLj+M2fOqHZAxe9X6zIAf7CzLly4UPPz1Toh06ZN48J1AVNSQQjBhAkTuO/95ptvQAjh6hTq9XpYWVnB09OT20W4du0aPDw8VLtrfyfJhhcvXmjKBQAmiMqcOXM0/2bo0KGq3R7AlCgVL15cMyH18/NT7WgDJoid2DniBfIZGRlUWqV06dKKoNFgMGDatGl0cwgICGD8giBg/fr1tDPPQzDs37+fzgrxEtpTp07R7huP+OjixYvUzyMJuXLlCoXr8+ZMjx8/To+fd2+KUHWexqXBYKCkTjxiqPnz54MQE4yUByubOHEiCDHNPPOCj2vXrmHKlCl/SVJaUEKQlJSk2UV/9+4drKysVOFxcXFxsLa2ViWUSEpKgrW1tSqkMyoqCoQQ7vwiYFp7ixcvrhostm/fHj/88APXd+/ePdSuXZsbRBoMBlVppf+mpaamYvjw4Vi4cCFu3LjB3YsjIyNpkbRevXpYv369osMr7aqVKVMGixcvZgLds2fPMgFihw4dGPj369evGYKZli1bMh3VuLg4SjZkZ2eH8ePHM5Dnx48fo1ChQihXrhwmT56sgD+GhIRg+/btePny5d8GbvdnG4/IS27/K8Xa/7SJsitaFhAQgAsXLqiuiaGhoejVqxdOnTrF/ZuYmBhUqlQJP/74I3c9jI+Pp1wiAQEBin0nIiICtra2+OKLL+Dn56cYQRCbA3Z2dujfvz9Onz7N/KZx48YxaDxpcqrT6Rj2+0KFCqFbt27Ytm0bEhMTERkZqZBbKVGiBLy9vbF//35cuXKFYQ8WXxUqVMDIkSOxbt06hlxM+qpbty7mzp1LuUjkLwcHB8yYMUOhjSy+bGxs0KtXL1y5ckVBfEWIiR184sSJuHjxIhYuXKj47lmzZjGJ66dsnxPSj7C8vDyaeIjVi969e2Pz5s10tigqKgpjx47Fhg0bcPfu3QKD87/aCroZIyMjNQmWdu/ezZ3RFM3X1xdFixZV9fv4+CgYQaXm7e2tyTj83XffqXZAAVOnUk44JJrBYECVKlVUg7YLFy5w2eQAUwXV1taWW8EFTJA6teN68+YN6tWrp1olfvz48ScFd1OzgiQrAFMCNGjQIM37bNasWShTpozqdUhOTkahQoUUBFtSE2d2PTw8uH6plINUjkS0W7duMcyc8uv6+vVrRutMLkOQkJBAiWYIMVG6S4OmzMxM9O/fn9kUpHIVBoOBmUsmhCh0bLds2cIQeMhlCkJDQxlxbDn89dWrV8zMlXx28MOHD4xchTwpTElJoRtfnTp1FOfwxo0b9L28hFUaGHTv3l3hlwqg8+QR0tLSQIhJxuNTMK1ZK8AkL6L1HH///fea81bfffed5rxX+/btVYPE9+/fc+dXRRs3bpzqDPStW7dU2YH/WyayDWdlZanOdz1//pze34ULF0anTp2wdOlS3L17l54n6aiHGMT6+Pjgxo0bEAQBqampCk3BYsWKYfbs2bSj2bFjR0Xw1717d3ot5c8xISaynNDQUAAm6K/UZ25uDi8vL1pckOuU1qlTB0uXLkVsbCz0ej169OgBQkwzun369KGzZnq9HlFRUThw4ABCQkLw4MEDREVFISsr628RdH62P98eP36M8+fP49mzZ9xZZIPBgKFDh8LDwwNz585FaGioYl9PTEyEs7MzypQpgzFjxiA0NFSx7ojFxIoVK2LOnDmKrvSOHTvo/dy+fXsEBQUxnyHl7HBycsKsWbOYxFM6d29ubo5OnTohMDCQrq/SQpJYTPrxxx9x//595OXlMcRV0uR06dKliIyMVMg0id/j6emJEydOwMbGhpsUlihRAkuXLlVIwoj5wJo1a3Dq1Clm3xZf33//PZKSkhAREcFNWmfOnIn8/Hzk5eVRtKL01bx5c7o/SBmKpS8nJyf8/vvv0Ov1GDBgAPdvKlSo8EmMymjZ54T0Iy01NRU1atRgLrC7uzszd3n+/Hna9bC2tkbz5s0RERHBfE54eDhCQkJw9+5dvHr16pMgRxKtINFcPz8/1Q1PJBZQq8JlZGSgUaNGqp+dlJTEDV5Fi4qK0uyuXbt2TZME4MyZM6q+3Nxc1YBR7Iap2bfffqt63p4+fao6jC61ggh6PqYj/zGJ7b/a2X/79i3dGLQCY0LUoYnAHzA3NWZZKR07D/4s3cx4MNWzZ88yJC5y5rk7d+4wyaic1fn9+/do3rw5s6mcOHGC+rOzszFw4EBmU5HO5hmNRvz8888MEVeFChWY67t+/XqmUirKMIh27Ngxhb6i9B66f/8+8/lyf0pKioKAQ95FkCfMchM7zGLAL3/mZ8+eTf22traKLoac6EtO+CL9fGtray5zqAiRUoPZP3/+/JNBEBSkFf306VPNdf7evXuaa4B8D5GbmhwUAE2I/J+VvBQE5dNK6LOzs3Hs2DHajTUajVi9ejUNDK2trVGkSBE4Ozsz0Nnbt28r9AgHDRpEr4UgCAw/AiEmUr2LFy/S3y0NngkhKF++PHbt2kXv5/DwcGYtsLKywrJlyyjUPCMjQ9FVmThxIiWDMRqNdAZYfPXs2ZOOhgiCoHgWmzRpQtlXc3NzGQ4GQggqVaqEq1ev0jl6uSZi+fLlKXTy7t27CAwMxMqVK/Hjjz+id+/eaNeuHbdAIRLpDBs2TPV6xsbGahatc3NzVccDxN+rpQEKQJO4CQCOHj2q+azcv39fdXYdMK2PavP8gOmaaWkfAyZ0i9q4gXgMagy4APDo0SOMHTuWW+iNjY3F/v37MXbsWIqqyMvLw4YNGzB16lSMGjUK/fv3R5cuXTBgwAC6ruh0OuZeKlKkCGrWrEmLI+LniCNG4v08YcIEZk8XpXPEv6lVqxYD/dTpdEzB1s7OjkHgCIKArl27MsnelClTmO+Qa+/26tWLFoEEQWDYjgkxkTmKSJvc3Fw0aNCA8Xt4eND4LTY2VpF0NmvWjCZ0N2/eVCSdVapUoY0lf39/bjIqohvkciyEELRt25buwXLJGUJMKA1RWu3s2bOKpLZMmTL0HCYkJDCM1ISYOqRLly6l53DevHmK7xg0aBCNQ3U6HR1Dk7727NnzyResPiek/4RFRUVR+nTxRpRbSEgIZT5s1KiR4gbIzs7G0KFD6aKh1X0aNWoU6tevrxp4GQyGAm8wo9GoGTAYjUZkZ2drBg0fPnzAs2fPkJyczN0MkpKSkJ+fj5MnT3IhNqI2ohpsTdTbU2OdEyUuYmJiVM+XyFb6z3SmxapUfn4+9zymp6cjIiIC79+/V034Vq1ahczMTNWZqv379+PVq1eq51cQBEydOlUTmrV582YEBQWp/vaUlBQMGTKEywQKmM7/mDFjuIlgcnIyxo8fD3d3dzRt2lT1GFavXg1CCA4ePKj6O4oUKYKmTZuqBsGenp6wtrbmzsMJgoDp06ejVKlSqFu3LjdoCAoKQocOHVCuXDluh/Tdu3dYuXIlLC0tYWdnxy0yPH/+HBYWFihUqBBXhD0nJwflypWDpaUl7O3tuYmEh4cH3VSkCatoomi1mZkZlyhL1C60tLREx44dFf4HDx7AwsICNjY2qFmzpsKflpaGIkWKoHDhwopucnZ2NlJTU1GzZk2ULFkSjo6OjF+n0yE0NBQeHh4oV64cChcuzPgFQcDKlSvRvXt3lCxZEjVq1FAwCH///feUrOuXX35RMEN//fXXaNmyJSwsLLBv3z6cPXuW8S9ZsgQVK1aEmZkZ9u/fj/DwcMVv7Ny5M6ysrLB48WLu+hUXF4fKlSurziQBwNy5c1GpUiXVDuE/szlr/a3RaNQs9hiNRq7GsfyzP4Y5WmriuqX2PpE8Rg32mJycjCdPnmgm1OvWrUNMTIxqIer8+fNYtGiRpk5phQoVGMhxfHw8tm7dim7dutEC7qBBg5j3PXr0iNHnLF68uCIJCA4OZhIynuyNlOFVvmYYjUamo1KsWDHFnOLo0aOp38zMTDFPLsqWia+NGzcy/vDwcOYY5fDpjIwMTa3UrKws5hjl5Fc3b96k0juEmGbLjEYjDAYD9u3bpyhOVapUiSJ2MjIy4O/vj549e9KYxdXVVSF/k5WVBT8/P9jZ2aFy5cpc5up3796hadOmqFy5MpdFWxAE/PDDD3B2dlZlVz1w4ADs7e1VoeKPHz+GnZ0dVq5cyV0TUlJSUKlSJUyePJlbpNHr9fDw8ECfPn24rMiCIGD8+PGoUqWKQmJJ9IsydosWLVL4c3JyMG3aNFhYWKBdu3bMvWQ0GnH8+HGKrnFycqLPxIsXL+Dj46NgLJYW45KSkjB69GgmmZGPrQiCgEWLFlGSxqJFiyrWvuzsbKYLx5MTkXb2eXwOYWFhNGlt2bKlYm18//49HekoWrSoAi6fnJzMJI3ycYSEhAQGvSAfN3v58iUDXe3Xrx/jv3z5MlOYdnV1ZdbenTt3MudZPmMvLbiKL6kEz9ixYxV+KfGhqKxgb29PkUxSWTAxlipVqhR9dl1cXGis8eDBA7ouik0wGxsbCj8WBAG9e/dWHIO0MBAbG8vkKoR8OogjLfuckP6Tdv/+fdjb28PLy4uB4knt3LlzcHJyUgRiUtu5c6fqbI9offv2RZUqVVSToaCgIMXDKLWDBw+ibNmy8PHxUfiMRiOOHDmCxo0bw9XVFdOnT2f8mZmZCAsLw7fffgsnJyeUKlWKSXjS09Px9OlTSvzSunVrJtHIy8vD1atXsXXrVlhaWqJLly6KgOD06dM4efIkbG1t0alTJwXp0enTp3HhwgU4ODigdevWqF69OhNc3bp1C9u2bUPNmjVRu3ZtdO/enQlQk5KSMGLECHzzzTcUHiINnvV6PRo3boz27dvDzs4OR44cYTaijIwMFClSBO3atYOtrS3Onz+PO3fuMMFZ+fLl0aRJE1haWmLv3r3Iz89nrpevry+cnZ1BiFLgGTB1TwgxdZrkounidRKDCh7BjCAIFNolD+oAU+dY7Mh17dpV4QdMAcfy5cs1IdEGgwG7du0qsJOjVfzIzc0tEBEgnj+15NtoNCI5OZlLtS7a69evceDAAVWZm/DwcFy4cEEBlRXt3bt3uHbtmiopT2ZmJq5du4ZmzZpxCyAGgwEhISEYOHCgKjtuaGgo1q9fz9U4A0yb/tWrV7kJLWAK6p89e6ZKOqTT6RAVFaVKCW80GhEbG8to4UlNhDXqdDoF5FwQBHqd1FhGMzIyVK/h9evXkZKSogqDB0xSNgWRtT19+lQzUZw+fTpKly6t2kFcsmQJypcvz9X7A0yFhdKlS6NNmzYKaKter8e0adNQp04dNG/eHGPHjmX8RqMRs2bNQqdOneDq6gpPT0/FrPjcuXPh4+MDCwsLTJw4UREc/vrrrxg7diysra0xefJkRcK1YsUKjBw5EhYWFpgyZYoicNu7dy+6du0KCwsL/PDDD/D392cCs1evXqFUqVIoWbIkRowYgSdPniieX2dnZzg4OGDgwIGKZ18QBDRr1gyEEHz77beK8/f777/TwLBv37703x8/foyFCxeiRYsWNMDmvT8nJ4dCBL29vbnXet++fTAzM8P48eO5oxHBwcEgxASL42kmPnjwAObm5li4cCGXvCghIQGOjo6YPXs2d87XaDSiQYMG8Pb2xsqVK7nHOHPmTLi4uGD58uXcZ+LBgwewsbHBpEmTuIXL1NRU1KtXD61ateIifUQmb0tLS0VCbDAY4O/vT/cQDw8PCIJAZ4S9vLwY1IiTkxPT4d2xY4dCtkWeMF66dIlJIOQz74IgMGz6Tk5Oin3gxo0bTOdKjppIS0tjEnf57zQajejcuTP1y7VQgT/gpoSYCBjl12rWrFnUX7p0aeZa6fV6jBw5kvrt7OwYuOr169eZ5L9QoUIUHh4YGMgcu1iMlK477969w5IlS6iuMCFKiTjAtC+IEje8kRTAFBcWLlwYvr6+3PsxLS0NDRo0wIgRI7jFKpFMasiQIarEOEuXLkWfPn24RJCAqdPYunVrVbK348ePo3Llyti7dy/3GI8fPw4bGxusW7eOG1Ps37+fFkR567uY9A0bNowrXebr6wtCTNru8j1S1CElhKBTp04YNWoU49fr9bTTHBISgh49ejD3s16vR8eOHdGqVSu8efMG3bt3Z2JnQRAwfPhwdOjQAenp6Rg+fLiiGXPgwAGYm5sjOzsbixcvViAPMjMzUbt2bVSvXh2HDx/mjm3cunULNjY2qFGjBiOj9Cnb54T0X7BTp05xK0tSE1v0WvbvMuwFBwdrwlTfvn0LKysr1URj0aJFdPGbMWMG4xMEQQEXkj5URqORBiPiS04qJNf2kld/RYZJ8dWgQQPGf/PmTcZfoUIFxp+VlUXJKwgxDYfLgyYpdMHa2loBr5XDP6SVU0EQaLVR3ES8vb2Z94uVQEJM0I6mTZsySYpIjiNWC/v27ctcdykExNraGitXrmQ+/+TJk8wmKa8mrlq1CoQQlCxZEuPGjWM6tXq9HhcvXsTly5dx48aNAgfbPxU4hyAIBTLEiULiWpaamqogHJKawWBAfHy8atIoBrhPnjzhJuJiwiQmd3KTssXyOuh6vZ7CadVg3yI6Qi2RF++lguDYf/W1FQRB9Ts/lfssICAAlpaWqonvzJkzQYgJUsU7ZikJBY9QTTpLy+t0L168mPrNzMwU3bkDBw4wa5O8AHru3DnGLw/SL168yPjlMkjh4eGMv2/fvszvjI2NZfzjx49n/CdOnGDWPrG4IQgCZRcuVaoU3N3dMWzYMG7CmJycjD179mDr1q0Kn2hnzpxhoIdyW7NmjWbxYvbs2czzK7+Wfn5+jD83N5eBua9cuVLR5ZEmK5cvX9aEgebk5HB1wKW2YcMGTUbaxMREhca11IxGI/z8/FS74QaDAXv37uXK+xgMBty9exeLFi1C9+7d6W8/deoUJk2ahMGDB6Nr165o3rw5qlWrRu8zQRCwevVqphslJnvivSxPRgkxdbuPHTtGv//t27dMQmtpaYmpU6fSwq7RaGTk1QgxSaxJE0I5jLFx48ZMbCQyf4uvSpUqMcmSXAu1ePHiFA2UkZHBQF0JMXWs/P39kZ+fj3nz5qFEiRIoUqQIHB0d4eDgAEdHR6a4nZycjEuXLmH9+vUYM2YMvvrqK1U95rCwMEyaNElTm3r//v3cUQfRHj9+rAn1T0xM1Jxb1+l0mjqkWtra4jFqaUADBetRa93vgIlhXK1ALsLh1UamDAYDOnTooKqVqtPp4O7urooIS09PVyX5FP2LFi1CUlISd2/Py8uDv78/nj59ioCAAC6x5W+//YaMjAwsX76ckYoR7fXr1xgyZAhevXqlikrbs2cPhgwZonqcn5p9TkhVLC8vDydOnFBlQP0UgqqPgaeOGjVKdfYyPz8f9evXByH82b+3b98yzGLyJOHx48fMZrRs2TLGHxUVRaEHhBDFg6HT6Zh5OCmsQbSvv/6a+nkQaVHjiRDClfmQblQ8ZlYfHx/qb9iwoeK6SucF7e3tFYmHdN7C3t5eQTkunbeoU6eOIrCRbrQ8gheRLnzIkCEKaN2TJ08waNAgnDhx4m9BjgSYIENySJjcgoKCFMG13EaMGFGgcHarVq1Uu6DAH9IvWjNHAQEB6Natm6o/JSUFXbt2Vd2cBUHA8uXLFd0tqQUGBmLJkiWq/pMnT2q+X2RHVLPVq1errhV5eXlMcCg3XtdItISEBFXN2FevXqkiSBITE1W7kn+lxcbGokePHqp+Eb2ghkKRFszksGXA1PkS/UOHDlX4o6OjacGLJ3mVlpZG19eSJUsqCphpaWn0/ba2toq15eXLl0wALe8kSI+vXLlyiqLJ0aNHqX/ixInM2mg0GlGvXj1YWVnB19eXSaZTUlLw6NGjAjkJ/kyTHhtPpF5qz58/x/z582nyxvv73r17Y+fOnaqFlQULFmDjxo30msj/5tq1a0ww/CnEC3+2hYWFYfXq1di3bx/Onz+Px48fIyEhgTknkyZNgqWlJRo0aICRI0di69atePjwIS0BCAZAAAAgAElEQVSgSbk5ihQpAi8vL2zfvp1BT4is3YSYoI1Tp07FnTt36DkNDg6mz0GRIkUwePBgnD59mu6JV65cobDp0qVL4/vvv8exY8doUUGEXRcuXBienp6YP38+Ll26RNEhI0eOxLfffotp06Zh27ZtCA0NRVRU1P+0ZM/fwQp6prKzszX/JjU1VVPSMS4uDi9evEBiYiJ3bC49PR1GoxHLly/Hnj17FEUxcVyiVatW8PT0xKpVq7iSNN7e3lSNYd26dYrRK5FdWGQwvnTpEr33srKykJGRgbp166Jly5ZYvny5AgnCQ4Z8qvY5IdUwf39/WFtbo127dli9ejU3kP7Ume1iYmKwZ88eVf+DBw9gaWnJYOClJh3S5nWtfvnlF+rnEZDMmTOHCWrktnnzZurnzfSdPn2a+kePHq3w37t3j/p58w4PHz6kfh7hgthhJETJZgqAmc+Rz43o9XqmaionMjAajXQ2x9nZWVGt0+v1cHBwUJWFePDgAVxdXVWr75/afZeZmVlgkWTLli2qpEaAqZvg6uqqmaCJxANqXZX8/HxKrKCGVHj8+DHKlSuHL774gusXIZeE8KHWgOneq1SpkqpOZUpKCrp16wYLCwvujF1+fj7VseTJowiCgIULF8LMzIzLhiomu4UKFVKdM1+wYAGaNm3K9QmCgMGD/4+9946K6gq7hw9FEFAUERW7okassWOD2HuvKEbFEgRj7yXWIGpsWEhUNHZRY4td7LFXVBRRUUFURKXXmbn7+2O+c3Lv3HPu+P7eRE3ePGvdtVw+MMzcOfecp+xn74FCIpLk5GS4u7tzfYCxgyjqUm/ZsoWbhAFGeFqpUqWECUtiYuInC/ZE3XFqX3/9tbA4IkkSqlatCgsLC2F3q06dOiCE4JdffuH6acFNxJRLZ854cHwAcHd3ByF8zdfMzEzNvZdKWhFCuN0KKm00btw41V6ze/du9OrV64sMds6cOYOJEydqkj316NEDxYsXx8aNG7lr7ciRIyDEOCPH60TFx8fD1tYWtWvX5s4jvnnzBi4uLpgyZQpXmiQ2NhahoaFfFKnhX21v377F1atXhZ9Rp9NhwoQJmDJlCs6fP88tqh47dgxubm6YOHGiIgml9uLFC5QtWxb9+vXDgQMHVLDE58+fw9PTE5MmTVJoS1J7/fo1goODGXvxf/a/M3Nz8OZ4T8x9B1qcK0lJScJzUJIknDhxQrhPHzp0SKEtKjc6x92yZUv89NNPuH//vuJnXr58iRIlSsDCwgJ169bFjBkzcPHiRfZZ5DqmhBjJFMeMGYOTJ0+yMSYPDw9FLFmzZk3MnDkT169fh8FgUMTRtEDp6+vLCitPnz5VQO9r1KiBWbNm4fbt219cnKhl/yWkZozCtuhVtWpVTJkyBX/88Qf0ej1ev36Npk2bon///ggNDdXstnwuM9c9mz59ulB43WAwMMkb3mfLzMxkrKC8wC0jI4MldbwubG5uLpuv4DH4SZKEmjVrghCigrNSo7BbERFB2bJlQQjhzudQWJuzszN3s6PEGuXLl1cdrCkpKWxd9O3bV/Xgv3z5EoQQODo64u7du6rXvnTpEhwdHYXdrStXrpjVYfuS7OTJk5owWvpdjhs3TvgzP/74IwhRQ8ipPXr0iHXteXBcg8GAb7/9FoQYYZC8+3fp0iUGteYF8mlpaejevTv7bk0rlpIkYe3atWzmiTf7e+XKFZQpUwaEEC5x0cuXLxkDJy+hTU9PZyyhPLinXq9n5Ak8ZADwJ5utSEOXogdEHdLBgwerSJHk769QoULczw4A/v7+cHBw4CadMTExLNHhWVRUFAICAr6Ig3ThwoWa0LVly5YJCxLAnwU9EYs3hRKKiF6WLVsmXOsAMGjQIBBChNCzQoUKwd7enjuve/78ec1kuGXLlpgwYQL3e3j16hX3dz6FRUREaM6QA0ZGb2tra/Tv359blIqMjGTzqzVq1FAl5JIkMfSQpaUlRo0apUos/f39FegfU9gcjR0KFSqEJUuWqM4PX19fFClSBLNmzVL9rl6vx65duzST6n+6fczz/eTJE82fi46O1kxS/knn599tz58/NxsLbtmyRVMZICYmBgsWLNAsMowdO1ZYqNLr9fD391dJkVFLSEiAj4+PsJAcFhaGb7/9luvPzc1Fq1at4Ovri/Pnz6vWzYkTJ2Bvb4/OnTtj06ZNKtIpyg5fqlQp+Pn54dChQ2z9vHr1SpFUlixZEkOHDsWePXuQlJSEiIgIlUZowYIF0atXL4SGhuLkyZNcDdF8+fKha9euWLx4MeMaMb1cXV0xa9YsxhViejk4OGDAgAE4ePAgV3ZG3ln9Es5ULfsvITVj8oVqehUuXBgBAQG4f/++YgaibNmy8PX1VTzcJ0+exOrVq3Hu3DmzMgGf2rKzs4UBEWDchBwcHIRQS0ocwRvCB/6chRJBLHfs2CFMaIE/WUkPHz7M9YeEhIAQItxIR40apSJMovbhwwdhdxUAYziUM5hRe/36NQgxChPzquBnz55Fnjx5uHA+wDgjoaVP+CVZbGys2fc6d+5cLuya2oULF0AIH3oNGLv5lJWOl0RlZWWx4gQhRNU5Np1XKleunOo1jh07ptDwNJ1TefbsGWrUqMH8tWrVUvgzMjJYwksv+eFLWWrlzJqmsOGTJ0/CxcWF+U2TupiYGMV7MC3UZGZmMgkdQtTkFpIkKZgCebBl+kyJurO///47C6Z5RmefRZ07Gszz5oAePnzIAn1eYJGdnQ0LCwvVCMDnsLdv32oe4omJifD39xf6k5KS4OLiIuz4JiUlwdbWVshS++TJE+TJk0c4OhISEoJKlSoJ32P16tUxefJkri88PByVK1fmBu0GgwELFiz4IgOY9PR01K1bF8WLF8egQYOwfft2FZvoy5cvFfwCzZs3x+HDhxUdnIEDByqe47Zt2yoKh3KZKUKMcE8K4wWMAb58ZMXR0RHLly9nnZGUlBSFHnDp0qWxadMmthY+fPjA2EZtbGzg6+ureBbPnDmDPHnyoHbt2pg9e7aKA+DRo0eaDMj/2f8do53es2fPqqD71J48eYKKFSsiICAAFy9e5D7blFzqu+++EzZXevbsibJly2L37t3c16DF2h9++IFbLKBEZEOGDOEWyiiTcffu3VWFfEmS2Dyvl5cX9u3bp1j/MTEx7Ll3c3PDvHnzFAVlubSctbU12rZti3Xr1iExMREZGRkquZS8efOiffv2WLNmDc6dO6fYU+hlZWWFxo0bY/bs2dyEkOYEq1at4uqYVqlShekJy2MTeo0dOxZpaWmMyMjU3759exb7yhF/8qtevXrCouWXZP8lpB9hGRkZDHolvzp16sQeqJs3byrmLQkx0siHhoYyyn/5vGKxYsXQsmVLxWA9/bmsrCykp6cjJSXlk0F6zAUeK1eu1Jz969+/v5CuXZIkNG3aVAixpPNIvKQPMFbdypYtK5xXS05OVmlKyi08PFzIRgoA5cuXF5LotGvXjjETmtqTJ09gaWkpnJULDQ3VhEt/KYGETqcz+/0nJyejbNmyQgkNAGjbti0sLS2F3RNKcuXs7Mz9e97e3uz54DFDy+eFCSEqhr/AwECF3zQ5DgsLU+n2ydf0w4cPVRqf8vnr1NRUFdFX/fr1md9gMDAIrrx6KYcRbd68WXVoyRPaq1evwtnZWeGXJ21v375VwXvk1WY5oQy9TJ+bCxcuKGafTbuYclp+FxcX1fdAn0fTz08tPT2dfUZTmQpACaOvW7cu9zmg1WgRqURYWNgX0z0ypzUsKtRRE6EBqPHgttRu3bqlCW/v06ePsAB68uRJIfGIFinV/9TMwfgkSVJ0COPi4hAUFIQFCxYgKCgIQUFBqk71mzdvFDIZFhYW6NixoyJxN9UEtLOzw9KlS9nniomJUewHefLkQYcOHRhZjpzhXB7Yyc9sKuFGr3Llying2aYBopOTE5YvX87ew549exR+GxsbxeiIXIKDEGNnhjJyPn/+HFWrVkWePHng5uaGFi1awNfXV0Fmk5OTg7i4OFy/fh2HDh1CaGiokADKYDDg4sWLmmycojOYmpY+JwCzzNla58vH+OlMncgkSVKQIfFMS0oKMI57iJI+wFhkEknYAUYETkhICLcQlJ2djevXryMkJIQhvvR6PSND8vf3R0BAAEaOHIlx48YpCuHbtm1j+265cuXQrVs31aw+nUekSdKMGTNUSSNFXVhZWWHQoEGqbue9e/fYzK6np6dq7CE7O5t1+8qWLYt9+/ap5s8pt0a+fPkQGBioiHOzsrIUz3bv3r0Ve/3z588VGsRubm64fPky81MGXnniSWNPSZLQu3dv1TM3ceJE5Obm4tWrV6pOpZ2dHXuP4eHhKhIvS0tLBAcHQ6/Xq55XQowdTvpcrFy5UuX38vJiz9Vvv/2m8pcrV46RusXExCiguYQYyTzXrVvH9mz6/cmvSZMm/cey+7+9vpSEFDAGHab05+XKlVNg3sPDwxWBXvny5RUPu8FgUHRwChcurNhQ9Ho9VqxYwR42a2trzc0xPDxcE67yVxLdGAwGzeQ4ISFBU+bm1q1bmoynhw8fxtWrV4VB0C+//KI5X6BFzJKbm8udFaMHgkis+8mTJ+jXr5+QsObOnTsYNGiQcC7i9evXOH78OLKysoTfhSRJ2L59u+bsZXh4OJ4/f64ZIO7du1fz+3769Kli05ZbTk4OBg0ahMGDBwshTpIkwd7eHr6+vtz3YTAYULx4ceTPn587k/jmzRsG/XZ2dlYlE/Hx8ZgyZQpjKOzRo4fCn5qaip07d6JevXoMKiufqzQYDHjw4AFLCC0tLTFhwgTFa+j1ehw/fpw9f6VKlVJ9lpSUFEUVlDc/Jhe758HI5c+4j4+Pyr9582bmb9Cggcp//fp1RdAgf4+5ubmIjo5mxa8iRYooAv6cnBxcvnwZlSpVYgGw6Wc8cOAAvLy8YGFhgcKFC6v+/sGDB5mMRLFixVT+48ePM53RkiVLql7/7Nmz7FBv2rSpKoi9fv06m6329fXlSgfQtTJw4EDuXNCtW7eQL18+TdKlsLAw9OzZU5O44lOYuYTMHKxQK/jV6XTC7qper9dMIOQs0CK7efOm5vv/448/EBMTI/yZ3NxcjB49mtvhzcnJwebNm1G7dm0VCuDs2bMoX748ew5cXFxU32NUVJQiODMt/pnqjPJkr+SagjwdUlPNQtMuQ3R0tKLrsWrVKoU/OzubFW8IUeuQymW7CDHKUJgaheYTotZ9TE5ORps2bZjf3d2dfRdxcXGq4LtcuXKqmOTixYtMI7Rs2bJcRvCUlBSMGzcOlStXFhYcw8PDUadOHWHCFxsbiwYNGgj1sjMyMlC3bl2h32AwoFWrVrh27Zpw3fr7+2Pr1q3CuGjlypWYPHmy8DMcOXIEjRs35s7sA0ayKicnJ678DmCMY4oXL47Bgwer4qXHjx9j9OjRcHR0ROnSpRnLbXR0NPz8/FC7dm1FgUReyMrOzmYap9TPQxpR5nBCjNI0vKKd/HziyY69efOGnYFdunThJjK0uFyqVCluo4IiaKytrXH69GnV9yUvxGzcuFG1f8j9c+bMUf2+XJ2AV7yWF4oaNmyo+P309HRFp7FIkSKKNX/79m1FwmtpaamQR9u4caMq4ZNzsEyePFnllxNqfv/994pkmRBjg4reZ0ri5eTkxBAWFhYWbL2cOnWKrQNKCEYIQVhYGABjQt+gQQP23qlfJCH3Jdl/Cen/wK5fv85YY2vUqMGFwu3atQsWFhZwd3fnwkAlScLcuXNBCMGwYcO4G+vz58/Rrl07VKpUiRtMvX37lnWTRF1FwEhl3rNnT2FVMiQkBJ06dcIPP/ygqqLn5ORgz549CAgIgK+vr6pK/+7dO9y8eRNBQUGoXbs2QkJCFIldSkoKrl27hm3btqF27dpYu3atgrTIYDDg6NGjOHfuHDw8PLB48WL069dPkZgdOHAAkZGRaNy4MaZMmYK5c+cqqMp///133Lx5E61atcKwYcOwf/9+BVX6iRMnsHHjRgwYMABt27ZFTEyMAj67YcMGTJo0Cd7e3vDy8sLz58/x7Nkztjlu374d9erVg4+PDxo0aIBz584B+LObTCGmQ4YMQaVKlbjfxfDhw9GqVSu4uLhwO8iPHz+GnZ0dypUrh9WrV3O/p65du6JAgQKYN28e13/s2DFYW1tzZ8FycnIwd+5c2NraqpI8uaWmpiIwMFAzQD1+/Dg3WKF/Jz4+HpGRkdzCgSQZtSsvXbqEd+/eCSvdERERiIqKwuHDh7lBxatXr3D8+HEsW7YMb968UVHXZ2ZmYsOGDdi2bRs2bNgASZIU61+SJGzbtg1bt25lcFPTbtDZs2exfv16VK5cmXs/oqOjsWrVKpQsWZLbEXj//j0WLlwIT09PbuCSm5uLxYsXY/jw4SrtSPp+Nm7ciMDAQOGc5dmzZ7FhwwYhZDYqKgr79+8XEgu9efMG4eHh3LltwAgnvHDhgibt/cWLFxETE6Mqprx58wbJycm4fPkycnNzVcFGdHQ07t27hxMnTgirtjt27MC5c+c0i2AbNmwQklgAYBqfouBy69at6NGjhxAdERwcjLZt22L27NmqpFGSJKxevRo+Pj6YMGGCKrDT6/UIDQ3F5MmT0adPH8yZM0dRfJQkCevXr8fy5ctRr1497NmzR7VWQkJCsHnzZnh4eGD37t0q+HNQUBAr0mzevJnpIFObMWMGNm3ahGrVqmHRokWIiYlRBOI7d+7EoEGDULduXUyYMAE6nU7RXZIkCUWKFEHDhg1VkjHU/Pz84OLiImQipgmffI46JycHixcvVgi3N2nSRPW76enpGD16NCwsLFCvXj1uwe3ChQuwtbVFq1atuIlQZGQk8uTJg759+3JlNF69egU7OzsMGzaMuz/n5uaibNmyGDp0KDcwBoB+/fqhTZs2GD16NHfP2rJlC5ycnDB27FjufhEfHw9HR0f06tWLS5Ck0+nQpk0bVK9enYsy0ul0GDFiBAgx6jKa2rVr11iBp3r16gyRkJGRgZkzZypQIfnz51fAJCVJwtatWxXfFY+gS645y0uq379/z4JnV1dXbgGWdnasra25YwQ0CbGwsOAWkY8dO8b8PBj9zZs3WcOgUaNGqu/y9u3brNBXtGhR1TN/5MgRFv9ZWloq9o2kpCQFAo4QwhKx48ePo3379goJOQsLC0XC+fTpU0yZMoWNfllYWGD+/Pmqz3D9+nXGayHiBjh48CBsbGzg7e3NRZ/k5OTAw8MDPXr0EMqFLF++HN26dRPOckZGRqJt27b4/fffuf7MzEx4eXlhy5YtwgK2h4cHVq5cyV0LkiTB09MTY8eO5caver0ejRo1Qvfu3bnNhvT0dHz11Vfw8vLiotSePHmCggULombNmtyRhoMHD8LCwgLly5dH27ZtVfeRzoe7urqiYsWKivdoMBhYIahPnz4oU6aMQoKI6pQWLFgQERERqFOnjkKOSZIkeHt7o1WrVkhISEDPnj1VhJ4rV66Es7MzK1R4enoq3mN8fDxcXV3Rs2dPhIaGomLFimbRBV+C/ZeQciw9PV34oO7atQv29vaaMMfVq1cLkwdqK1as4M4dUpMkSVNnCjBuLFoB27fffouhQ4cK3yfVwRORcrRv355toKbSFwaDARUrVlTAF+TJHiWwkWPiTYMab29v1ikhxCi7IreffvpJNaMjf+hOnz6tqkTJZxIoeQrd4C0sLBTkFadOnVL8boUKFRRV9H379in8Xl5eqFu3Lqs6JiYmKvyNGzdW4PkBKKrXNWvWxMCBAxVBi7zaVr58ecyfP1/xfcXHx7NqWNGiRVUV+nfv3sHV1RX29vYYPny4EK6UnZ39Rc0um3svKSkp3OBKbjt27BCyQwPG55gyOPIsPj4eOp0OP/74I/cZoeiElJQULlLhxo0b7N+8Z/nWrVssOed1kBISErgzNNQMBoNZiRxzEDhzkP8vcUbwr7Lc3FzN+7d+/XrUrl1b2N2bPn26MFkClBBz3vx7jx49mJ83UjBkyBDF/hEZGanwyxnMCVGzPVPSKrq/tW/fXuGX6zw7ODjA2dlZkcDLNY4dHR1RpEgRRVKXnJysSFSaNm2qKJDqdDo2C02hd/L1tG7dOvb7VatWVUD/dDodHj58iD179mD27NmYPXu2cC1euHCBS1hHLSwsTBNJtGDBAk242sKFC7lBMb1XoaGh3GCOnkX379/XRAcZDAYuA73cQkNDhXPCgHF/ESF5gD9n17VYRo8dO8ad6ZYkCQ8fPsTKlSvh7e3NOvIGgwG//PILunTpgpYtW8LDwwPVqlVTJMWSJLHnhF6NGjVSdPUzMzMVqBJnZ2eVjjuVXqHJ3g8//KAoQDx48EARK/Tp00fR/Xv//r0CwdakSRNFopKSkoIKFSowf+XKlRVdr7i4OMXvu7q6KsgGt23bpohFChQowArUR48eVY162NnZsQJIamoqLl68iJCQEIwYMQKNGjVCwYIFuciQnJwc7Nq1Cy1atBDGf9nZ2ZgxY4aw0AYYk3MtLe/Y2FhhJxowPp/moM3mzh5zZ7w5YrSHDx9qojMePHig+Rlu376tgNeb2tGjRzXHHZYsWYKRI0dy9yVJkuDj44M+ffpwk/6srCw0atQI+/fv5xbSUlJS0L9/f/azpn8jMzMTa9euRW5uLg4cOKBqBEiShF9++YUVjHga81euXGHx0T+FQfq/hJRjkiRh8ODBaNq0KZYtW6Za9Dt27IBOp8ODBw+Eh6gIRvUpLSgoSHNO8dq1ayCEcCtxgLFDSTfYuXPnqvymMzqmwfWvv/6qGVBRlkd6mcq+vH79WgE5aNOmjcKv0+kUkC1TAhpJkhSHTPHixRX34+nTp6qEVj5TRSuu8isoKIj5X7x4ofKbdrzkM0i2trYq2Kw8KG3RooVqno8yoVaoUEH1u5IkMT08rWDmU5u5zS85OVnYcQGMn6tbt24YPny48GdOnToFGxsb4Ywu1cCzsrISQiJTU1PRrl07rtwQtcjISFSuXFk4GyVJElatWiWUTgGM60yrQJWVlaU5ZyhJkiJ44pk5dm8tWOhfOS/4T7K9e/ey2RyenTlzBoTw5awAZcGKx+Atn9caNmyYyn/y5EnmL1q0qOo7uHz5smJvMU2uTQtyO3bsUPgPHTqk8JuynJvuv6bnQFRUFPPZ2Nio9h95QW/GjBmKvfXixYv4+uuvMW3aNK5cx19tWq/P82VkZDCpLdHvjh8/XhMeunv3btbV5v1MQkKCZtH532BHjx7F7NmzsWnTJpw/fx5xcXGKJEKn06FLly6wt7dHmzZtsGjRIhUMPCIigiWbderUwZIlSxRF3dzcXMbhYW1tjV69eiE8PFzxGvLiUK1atfDLL7+w4qwkSejbty/zU8QA/RtUx5EQI4lNu3btEBwczNA3wcHBcHBwQK1atdCvXz/Mnz8fv/32Gx49egSdToc7d+4gIiIC9+7dQ2RkJB48eICoqCjN2XKDwWD2zDZ3jv5f3LP/p2buHpk7F7UY1rOzs7Fv3z6hPzExEc+ePcPbt2+5cjK0CLZ69Wr06dMH27dv5+4XO3bsgK2tLTp06IANGzaoEv0HDx4gX758qFixIqZOnYobN26wv/VPk5X6LyEVWGZmpoLIqG7duggMDFQs0CVLlqBMmTLw9/cXQgw/p5mbXdLpdChQoIBwzkin07FZMB7DbUZGBksIebNq2dnZKFq0KLuHpvImkiQx+AkhBGvWrFH9jXbt2jE/L6iXMyVOnz5d5ZfP0Jhi6HNychQJr2mH4dy5c4qAzd3dXVFJlwdshBhZGuX3QJIkBvEhhHC1RmnC2rlzZ9XmodfrUaZMGXz33Xdc+YwvMZEwGAyaVUfA2Lnv0qWL0E/JiURw0tu3bzMKdV6VWZIkjBw5EoQQ1K5dm/sacXFxLAgRSdWEhYXBwcGBS8wDGGGt3bp1g4WFBTf4kCQJmzdvRv78+YUs1vfu3UP16tW50F3AWGXu3LmzUPIoOzsbfn5+qmSEml6vx/jx4xVEJ3IzGAxYvHgx1wf8OZMqMq0q/IcPH4R74rNnzzRnIz/FutYiPwGM99bBwUFYyc/KykK+fPlUc77y3y9YsCAI4TMd63Q6BtHz9vZW+Q0GA/NXqVJF5c/IyGAzZ/nz51fd68ePH7O9J2/evKqOxu3bt5mfJ2tFJbEI4TOo+/n5wdHRUUWcApjvjvzd9vr1a01iGcA4CtG/f39hYrB7927Y2Nhg7dq13O/37du3yJMnD+bNm8c9a3NyclC3bl0uVBgwPpsi37/FHj58iHPnzgk5ElJSUtChQwfMmjVLGPzPnDkT5cuXR1BQEBe5tnPnTtjZ2bF5dNPvat26dShWrBjGjRun0mWkMiVjxozB8ePHVc8QRVmYi6X+LabX681yj2RnZ39xccenMK3mTkREBH7++Wdux5YSDfHkZKifFlSsra3RokULBAcHK15r0qRJbC+2srJC8+bNsWrVKlYoNyVDKlu2LCZMmIDLly//o9bufwmphsXGxirkGehVpUoVzJw5E7du3cKwYcMUMI0OHTpgzZo1bDFFRkZixIgR2LhxI6Kjo7+4B9kctJjCwkQQZgrXady4MddP52UJIdyu8erVq5n/ypUrKr+cMY2n1ynvUvDYbuWsZry5FKqRSghRBd60g0wv027KrVu3mM/FxUV1j96+fcv8vA4z9Xt7e3MPgVu3buHQoUOq//+cJtIXo7Z582ahrAvwJ1lB7969uf7jx4+zWRvTjjpgTGQoAywhRJXUGAwGfPfdd8zPmyW6ffs265xbWVmpXkOn0ynYcnnv4+LFi4wJtlWrVip/UlISq8q7uLioAjJJkrBy5UrY2trCxsaGG8CfP38eJUuWhJWVFffZefHiBerXrw87OztuwSItLQ2dO3dG+fLlufuOTqfDoEGD0K9fP5UPMN7Lfv36CZPpjIwMdOzYkesDjOREhScAACAASURBVAU7EYvr/v37ERgYKPxdESP3pzat9wgY5we1OuxDhw4FIWJJKjpjySMXAf5EUIgIKSjjMm9WWKfTsZk5Pz8/lf/JkydsjfOSSirHFRAQwH3t5s2bq2a4P5V9zDnarFkzzRnhgwcPghAj0Q+v6JKRkcHITXx9fbnFFcq63alTJ253Y/To0bCyssLcuXO5Ae2IESPg7e0tLHpERET8owLK/6nx4Ipyy8zMxJkzZ4T3QKfTCTtLgDGJOHfunLDb+KXFY3+3bd26VZPkTZIkDBs2TLPQmJaWBn9/f80OrjnIcHp6uibkmMqciEyrmKjX6zU7n1qd6ytXrig6jHK7evUqOnTogBUrVqgQMZIksTnuqlWrYuLEiTh9+jQ793NycuDp6akoEMpzhczMTNStW1eVa3z99deYNWsWrl+/jtatW6v8hBhJmxYvXowxY8Zw/SVLlsTo0aPNMmR/CfZfQmrGzp07p6J5JsRIET927Fi8e/dOJQUhh4ZMnjwZa9asYUF24cKF0blzZwQFBeHChQvIzMxktPefQwbEXEv/5cuXKFu2rND/+vVr2NjYcCFpgDHpsrW15cpHAMYKqYODA6ysrLgHflZWFgoUKAArKyvufExGRgbs7Ozg5OTE3SBpF8AUzkutadOmIETJgkbt3r177LvksaX+8ccfzM/rIFO2VB8fH+4Gt3//fgwbNuyLkX8xZykpKdxODrW0tDS4urqiXr16XP+rV6+YpAnvfppSmlPWOGqJiYmMPZYQI8xRbnq9XkUssWnTJsXPHD58WCHPZNr9fPPmDby8vJjfwsJCESwaDAYEBgYq2A5NYcMXLlxAmTJlmN+UmCghIUExn92rVy/V55g3bx7r3vOSvpMnTzIGPh6JSFxcHL7++msQQoRkV1RfmYdMAIAJEyaAEKLSgqM2atQouLu7c30GgwHly5cXJlo//fQTXFxchIFDy5YtNSWTPpWZo8rfv38/F/lA7cyZM3BzcxP6qTavqNCzf/9+EELYvJqpTZw4kVsso1alShVYWFhwg5GEhAQQokZ2UFu2bBk8PT2FM1BahFJ/t7179w6DBg3C1q1bhe+DQprt7Owwd+5c1Vmn0+kYgsfKygrz589X7cVyqGetWrVUsOm1a9cyv5ubm0qr+c6dO8zv6empmsuLiYmBlZUVHB0dERwcrDrDjhw5gkqVKgllQswxNP9n/3fs4MGDmDhxoiZE/tChQ3BycsKSJUuEe1tQUBAKFiyoCUdt1KgRunbtKowfr169Cjc3N2HyJ0kSateuLZzx1+v1jNSHZxcvXsTIkSOFCJzhw4cLlRmOHDmC+vXrY+PGjarfT0tLQ9WqVVG+fHlMmTJFNZspH0Nzd3fHxIkTWcFDp9MxjVR65c+fH926dcO6detw9+5duLm5cXOF6tWr4/vvv1cgCuVXhQoVcPToUQXzOL2KFy+ODRs2ICcnR8FZQi9XV1eEhob+I+LM/xLSjzB5F49eXbt2ZRWcpKQklV4ZIQRlypTB3r17IUkSNmzYwF1oQ4YMYYPsjo6OKFGiBOrVq4cuXbpgxIgRmlIpwKfRsvz11181/YMGDRJCCgFjlf+bb74R+v38/FC1alWhf/jw4cIkBwC6dOkiZHnU6/VwdHQUvr8BAwaAEMKFTtEOQoECBbjkM3QGjBfwA8ZuYOPGjYUbf1RU1BdVoeXBX+UWEhICV1dXoX/atGkghE/gIkmSAn5t2tHJyMhgCRS95EF2eno6ozLnJZM6nQ79+/dXPV/yKuyaNWtUwtTyDtjNmzdV0k6enp7Mn5ycrKpS5suXjwXEkiRh9uzZqr8hJ6s5duwYg2HSS86u+urVKzRv3lzhlzPdGgwG/Pjjj4q/YcqEe+PGDcXnMCUQyczMVHwXpkE0YExGqJ936IeHh4MQI9s4zyhhzsiRI7l+2sXmdZ8BI9Te3t5eKLm0Y8cOs4RPn8KysrI04akGg0GTeMtgMKikPOSWnp6O4sWLC7sRBw4cQOnSpYUdpO7duwvZtTMzM5EnTx4hVHLVqlVfBBeCyE6dOgULCwvky5cPgwcPVnXSJElSkOmUK1dO1QmmCT29vLy8FGQ58jlgQoyjKXKilHfv3imKU3Z2diq2Xvm+5uTkpBoRkO9btWrVUiGFKJyvUKFCmD59uqJAFh0djfr166Nfv35YvXo1IiIi/hGB5+c0c2euudnN7Oxss11rrXEEwBgzahUT3r9/rzi7EhISMGzYMPj5+WHevHnYuHEjTpw4odh75NBPmlDdunVLNUbUpEkTEGKEdW7dulX1WeLi4lgDZeTIkdykkyLjvLy8uJ81IyMDlpaWqFy5snAPadWqFcqVKyckT+rWrRvc3Ny4xTRJkuDu7g53d3cuEzDVSq1UqRL27Nmj+s4pstHJyQnjxo1TID2io6MV0m9ubm6YM2cOWxc8WRd3d3c8e/YMKSkpCkkZelWuXBknTpzAw4cPUaBAAZXfw8MDN2/exJUrV5isHb0KFy7MCpZ3795VSNIQQlCxYkWG8Hj//r0qaS1QoAB3ZORLtP8S0o8wSZJUAth0EdKW/JMnT1SC9oULF1ZUiFatWqXwFytWTEFGcvv2bQYDJMTY1pcHs8+ePcPSpUvx3XffwcvLC66urlyYK7Vz585pVvg/tsJtbgO/e/euJsvgvXv3hIEpYIQlDRgwQOinOmki27hxo2bS3LFjRy7kODs7GzNnzhRCTGmH1FRbjtquXbvg7u4urBLu379fCFmUmzlCmvT0dLOVcHOdHL1ej/nz5wtp3AEjqzKPnAUwrgEaWPGqnlSknRB15xIwVkzl3UtTCOH169exZs0axUEgX/txcXE4deoU6tWrpyjmyD9/dHS0SlfQVH8sLCxM8QzK74ckSXj06BGbT+V99ykpKYrZclMNtIyMDAVRlYeHh8KfmZmJJUuWMH+pUqUUAWRqaip+++03lnAWLFhQsb7S09Px+++/w8nJCYQYteZM51H27NnDJBbs7e1V6/PEiRMsUC9QoIAqgH3y5AlDDpQuXRqmlpGRgRYtWoAQNTM2tc6dO6uKBnKjv+/u7s7twFH4U5s2bbhr++bNmyhQoIAq2ZbblStXEBQU9NmLPuaeXXNs6lrBxLt377iz89SmTp0qPCMkScK0adOEv/sxs2IfQ9pjDub//PlzVUEwJycHs2bNQoUKFeDm5oYaNWpwYa0zZsxgz9KoUaNUa11OTPf111+rihgPHjxQnLcXL15UJCSZmZkKRMXPP/+sggvKuxL+/v4q7ccVK1Ywf9u2bVWFyLt37zJ/zZo1VQWihIQEhhwpU6aMCrFw9+5dth8ULlxYMS+ekpICf39/VKlSBW5ubqhevTo3QaB745AhQ4Rdp+zsbBULvKlRqS2RhYWFafr37Nmjmezt379fE6555swZYRELMK7FzZs3C/9GamoqxowZI0zqdTodevToIWRH1+l0mD59OmbOnMn9nA8fPoS/vz/KlCnDEjlJkvDbb79h4MCBaNiwIYsjTYnyYmNjUatWLUX8afpdpaenM14OS0tLLjs1RWUQYhwX4sVGFPX31VdfcUelaEHSzs5OSOhHmzQBAQHc+02LQZ06deLu8bQR1KhRI+4+Q8/RypUrc2c3qYxQiRIlVHFYamoq0wd2dHRUjXtRZAohxrlOuWyLwWBQaAcTQhSNoxcvXijGigghCtnEkydPKopYhBiL+HTv2rJliyrXcHR0ZEmzXKNVLkNEZQcjIiKYugXdFwghmD17tvpL+sLsv4T0I42Kzdra2iIsLAzOzs748ccfFT9z4cIFNrNDW/Wmm9KiRYtAiJGGv2LFiqoH8e3btwxrXrBgQcXhJkkSTp8+zbobNjY2XKgoYJzBypMnjyZhyZAhQzB8+HBhRXDGjBmYOnUqzp49q6qCpaSkYPv27QgJCcH8+fPx6tUrBRPphw8fcPbsWezduxcBAQE4ffq0AnaWm5uL48eP4+rVqwgICMDatWtx+vRpxf04cOAAnj17Bj8/PyxYsABPnz5VJG+7d+/Gu3fvMGDAAMyZMwcZGRmKwzg4OBiPHj1Cnz59MGnSJOh0OsX8xJAhQzBlyhR069YNEyZMUCWG48ePR4kSJTBr1iz4+/urkrkNGzagYsWKWLt2Lfr164cLFy4o/HSuYO7cuWjdujU3ac/JyYGbmxv69+8vJNc5cOAAGjVqpJl0jx49Wpg4A8aknpdAyW337t1cIW3A+H1du3YNe/fu5f6MJElITExEcHCwcP4vPT0dwcHB2LVrF2Mrlj8fer0e27dvx8qVK9GqVSskJiYiOjpasa7Onz+PESNGYMKECVi0aBEMBoOiIxETEwMfHx/MnDmTaR+mp6ezAystLQ1jxozBmDFjULRoUXZQ0vdhMBiwfPlyDB06FNbW1tzA49ChQ+jfvz/y58/PhUrevXsX3bp1Q8WKFbmQ1YSEBPTq1QtNmjThEjdlZWUhICAAnTp14rIRGwwGLF26FN7e3kJkwP79+xEQEKCSa6J2/fp1zJw5U/j7z58/x+LFi4Vad0lJSVi1ahV3zVHt11WrVgkld44ePYq1a9ciMTGRG4xs3boVq1evFlbXKYuyVgevV69eIITfAQaM+3VQUJAwAD98+DCmT5+O48ePc4PLkydPYunSpQgLC+M++5cvX8aWLVuwaNEi7Nu3T1EAlCQJ165dw9GjR/Hdd98hKipKca8kScIff/yB69evw9/fHzdv3lQFlwcPHkRUVBR8fX1x8OBB3L17VxFcrl+/HmfPnsXQoUMREhKC7OxsRXIYGhqKCxcuICAgAAsWLAAABcFPcnIyvL29MW/ePGGAvWjRIgwZMgQTJkzg+jMzM1GpUiWu5jZFDuXPnx8NGzZU/S5g3PtcXV1RokQJ7kyZTqdDkyZNUK1aNW7xT5Ik1K1bF998840Kvk/Nw8MD3bt3x9SpU7mJSP/+/dGzZ098++233Pm70NBQeHh4wNvbm1vQS0xMRP78+TF48GDVOqHWsWNHNG/enKuFCgCbNm1CmTJlMGPGDK7/6tWryJcvH/r06aO6zwaDASEhIShQoABKlCihWO8GgwHr1q1jSZC1tTW3aHnt2jVUqVIFlpaWCs1EuQUHB8PS0lLIoB4REQFbW1t4eXlxSY7ev38PZ2dnVK9endsVy83NZQUKnv6lJElo0KABSpcurYrNqHXu3BnFihVDz549uet18ODBsLe3R506dbjaw7QxUbhwYRXzelxcHOs+EvInp4XBYMChQ4dU6Br5qITBYMDevXtRv3595ucV4dPT09m+1rVrV+5nfPToERwdHdGsWTNhwahjx45o1aqVsEC9efNmdOzYUTU2Qy0zMxNdu3bFwoULhQWGmTNn4qeffhIWEPbs2YN58+YJO6RRUVH49ttvFfJqcnv79i2aN28ulISKjY1FlSpVhCSLp0+fhqOjo3Bsatq0abCwsICXl5eK+Cw9PZ0VB8qUKaMiDbx+/TpLFp2cnFQ8DCEhIYoOpqnEHSUxGjFiBKpUqaIaq6BotOjoaLRr1w7lypVT3Gc6/3/v3j2MGjUK9vb2mozBX4r9l5ByTKfTqdjYAOM8Je2mvXnzhpvI0erG1atXhVCuWbNmoX379sLKeU5ODvz8/HDw4EHhe6RdR9PuAmU5rVevHrp16yacDzMYDChUqBAsLCy4QtcA2Obo4ODAPShLliwJS0tL2NraIn/+/AqtNiq5Qjtezs7Oqkp+vXr1GGlUkSJFVPA/Hx8fNidXpEgR5M2bV6HHNHfuXMZi6eTkBGdnZ4XO6Ny5c5E3b15YWlrC0tISbdq0USRkgwYNgpWVFZsRDggIQIcOHVhi+sMPP7BDmhCjdMPYsWOZeLlc55QQgu7du2PChAkKTTw5y6+XlxfGjRunSO4jIyOZv1q1aiotP+DPblHx4sW5QdejR49QokQJrFixQhOupZVwfmozGAy4evWqMGFJTU3FgwcP4Obmxu2g6XQ6REVFYeDAgRg7dqzKL0kSzp8/j5cvX6Ju3bpcHUFaAIiMjOTq88kLADydw3Xr1ikSWtN7HxYWpkntf+XKFU3YaUJCgvAwBoz3gCcKLjdzsFZzHa5/Mvzv2bNnmvqVGzZsQL9+/YQBVVBQEAgh6Nu3L9dP4f6E8Fl027dvz1hweXOk7du3Z914a2trVSeiR48erDNmb2+vCvS7d++u2B+dnJwUgb6vry+DhxUtWhQuLi6Kv7Fu3TpYWVnBwsICBQoUQK1atRRal3q9nn0+e3t7NGnSRDXLShEJ9vb26Nevn6pDSQMvR0dHVfHmt99+w9ChQ+Hn54cZM2YImViTkpI0O+GxsbGayI8TJ05oPocHDx4Uolz0ej3OnDmj0gGU27t379iZIDItBBFgTPjM6ZLLzzaenT17VvNzvn79mkteBRiLYOHh4ZgxY4bqNU6cOIFWrVqhZcuWaN26NXdmWj5L26JFC1USkpmZyVAbDg4O3O9Tjm4ZN26cat//+eefmb99+/aqvU1OcFi7dm1V1+vo0aMKZMrJkycV/l27dik6UqdOnWJ7Ay2AUb+tra1iPR86dEiBkLOysmLPSkZGBs6cOYMVK1Zg6NChaNCgAfLnzy8soJw5cwZt27YVkv5IkoQ5c+YIiSYBY0FSC5kRGRmpqQqRlpZmVpbGHP+IOVizOfSFJElmX8Mcyk+LWAmAZoyt1+u5ZHDU4uLi4O7uLmzo7N27F3Z2dkL49pgxY2BjY4M3b95wFRY6dOiAEydOICsrSxW/6PV6hhBLTk7m8jxMnTqVvTdzmq9fiv2XkAps4cKFqFixooqOnB5Mx48fR0BAAM6cOaMK2mbMmGH2cBGRVMhNi2Xsf2s3b97UrHYCYMQrIvF4ebLVvXt3ld8U5mwaXMuF3QlRy7Zs27ZN4W/ZsqXCbyrLUqxYMcV3IT+geO9hypQpKr98tlEuLE8vDw8Pdi9ME1J6H+Qbrek8oGlHSQ6/KFWqlKpaKEkSypUrh3z58gmDshs3bvyta+X/xR4/fqw5kxoREQEnJydhghwVFQVXV1dh5yQrKwtdunQBIURIvnD79m2UKFFCBZuVG5V2ESV+er0ec+bMEc4JA8ZAb+TIkZrJ25EjRzShZomJiZrfocFg+MeIW/9T7MiRI5pBF9UhNQ1cqVGqfQsLC27xcevWrezZlsPLqcn3tzx58qgCRFN4uSmfwLp16xR+KrRObf369Qp/mTJlFPu4qQ5p8eLFVUkhhX4RQrhSTZ06dWJJxu3btxU+vV6PChUqoG7dupoJ4+e0p0+fagbW8fHxQmIuaqKCLjUtVtN/g929exfjxo1DWFiYsNvl7++PggULIiAgQEUUAxjPA0tLS9jb22P8+PEqZEpGRgZcXV1BiBHeuG/fPpV8i7u7OwgxQq+nTp2qSARycnIYIZ6VlRW+/fZbRVwXGxvLitv58uXD0KFDcfnyZfY3qB54wYIF0alTJyxevJidb7GxsVi6dCnWr1+PXbt24dixY7h06ZImVP1jdEjNFQM/9yjC/wUz9x2I1js1LQ4YvV7PoLwGg0H1faakpLBEdOPGjdiyZYsihqDvTZIk9OrVC+3atVOQvP0T18d/CanADAYDO2xpUvbTTz8pAmh/f39Wnf7uu+9w8uRJ6HQ6trj279+PKVOm4MyZM8Lq7+eylStXalaHAKNeJCEEp06d4vqXL1/O7g8PQrN7925FsmX6gMhlU2hXWW5v375lw/WEEKxevVrhz8rKUgyAm0Jc5Dp8hKjn2eTvn1Y95RuMKZmVpaWlIuiKjo5W+F1cXFQQwho1aigCRtN7QGVxnJ2duVqR0dHRKFGihNk5s09pmZmZmsnVmzdvUL58eaEkRFRUFOvoiOZs6AyGfPaCWmpqKpo1a8buK6/7eejQITb8z5PckUu7iGRRXrx4wWYpRcn1rl274OzsLJRPevfuHXx8fITQWUmSsGPHDrRq1Up4gERHR2PYsGHCanFaWhpXJ5KawWAQMuVS+4+tU21paWlwc3MT3vf09HTkzZtXWDRJS0tjsC0ewiQ9PZ2tUZ5sVnp6Ovt9XtIbFxenmbDK5yMJIfjhhx8UfsqySy/eeAcl4LK1teUG2DVq1ICFhQX3LDl58qRZ1MbfbeZImW7fvo0ePXoI36PBYICDg4Nmd7JFixaaSemCBQs0tXwTExP/kcHjx1p8fDx27NghTPwlSULHjh0xZcoUlVYutQULFqBo0aIICQnhImY2bNgAS0tL+Pr6coucCxcuhLW1NYYMGaKCVev1enzzzTdo0qQJNm7cqCoMRkdHY9WqVbh79+6/QoLHnM4oAM053I/9GZ1O98XFvZ/TcnNzVUVlup70ej1GjhyJWbNmcePAlJQUVKxYEXZ2dujTpw8OHDiguLcfPnxgM7EUrXLkyJF/XBH7v4RUw96/f6+Qb6CBwTfffINffvkFr1+/VrD40cRiyJAhOHr0KLKzs9lgdb58+dCpUyesXLlSoUeakpJiFvrwd5g5UXgAGDduHDp06CD0U53OokWLchd+UlISG97mdZgorJd2N3mbvZzExnRmA4BCosO0y2UwGFhARwhR4fgpzp5eEyZMUPhNmZFNkyPTgI8HD6Sfr1q1alx4ibe3N/LlyydMeM6dO/fFwGwB43cmmqUCjEF43bp1YW1tzT34YmJiUKJECRBihDCb2oMHDxTU56bSH4mJiQq9rmrVqqleY8WKFQoWWtN18fr1a8W6mTJliuo1du/ezSrmVatWVQWM79+/V4hZ82ZN9+zZwwL68PBwlf/ly5eM/IcHGdbr9fjpp5+QN29e4Xzw+fPnUb58eWFCGh8fj5YtWyqYfOWWlZWF4cOHCyu9BoNBc3ZZkiRNUi6tvU0rMNLr9V9EkC6COFLr1KkTt+BBrU+fPiCECO+vj48PCCFCciEqzSM6C2nBy9bWVrWn07EMus5NE0pJktgad3R05HZsqEyBaTJLrUCBAliyZAnX9yXAvU+dOoUpU6YI11JGRgYIMZKsiX6mUqVKcHR0FAbgQ4cOhZWVlRCWu3XrVhQqVIgL+weMhdnvv/9e+Pezs7O/iHv5d1laWpomU3V2djZWrFghRJBkZWXB39+fqzMOGIuCkyZNEsI3Y2Nj/xHzdR9jWVlZZhPOI0eOcBsIchs1apRZmLmXl5dmIfPp06dm9aRFJIr/VJMkiRunUt93332H4cOHIzw8XBUzJyQksNioZs2aCAwMVOzZERERyJs3L9vPnZycMGzYMMYufu3aNTYiIm+SfP/997hy5coXcZ6as788ISWEbCCEvCWE3Jf932xCSDwh5M7/f7X/mNf63AkpYEy6KFGR6dWpUyc8ePCAQUlMr4IFC2L79u1cndJy5crBz88PO3bsQOvWrfHVV1+hR48emD17Nn777Tc8evTosx9CixYtUjCdmlpubi7s7OxUiZzcaIeJx9QGGCVdCOFD2oA/5zhFsEvq/+qrr7gPHE1eypQpo9oAKCSPEONguemckDxhdXV1VQVscp1SHkuwJEmwsbFRMKSZWoMGDbjJyucycxCU5cuXw8bGhnuvc3NzGeFWxYoVVf74+HgFJblpkSIyMlIliSKfo4mNjVXJK/n7+zO/TqfDyJEjFX45cRFg1I41fV7lcML09HQMHTpU4TcNuA8fPqx4DVMd0YSEBJZIEEJQpUoVFfX+2rVr2Xy1i4uLKnGLjIxkMjeOjo6qYCwrKwvjx4+HhYUFChYsyA0M9u/fD2dnZ5QsWZK7l8TExKB27drc7hz9G3369BESG0mShFGjRgmTXYPBgEmTJnF9ALB9+3ZhsSU+Pt6s5NWnMHOHeGhoqOac74EDBzR1SCkLrCj4o7DdyZMnc/1UgkBUOOzQoYOw+AOArTHR91SzZk2ULl2au76Sk5O5ZEWf0h4/fqw5HpOeng4rKysh0ycAVnSeM2cO10/JaMqUKcOd25s/fz57TnlJ0Y0bN0CIESXEW+86nQ729vYYPnw49z3m5uaiX79+wu7h/3X7N3Qt/yrT6/Xo0aOHMDkHjHtrnjx5GCsrz2bPng1nZ2fNGcyiRYtyi7nUwsPD4ebmptmlGz16tHBWFjA2Ts6ePSv06/V6zflurQ6twWDQXDta86mHDh0SzvAuXLgQTZo0wapVq1Q/k5KSwqDjLi4u8PPzw+nTp9n5fOnSJcZZQq969ephyZIliIuLE8pHlihRAuPHj8fMmTO5fhpjf0x3/HPa35GQehJCanMS0gkf+xr0+hISUkAt10IIQZ8+fdhivnTpkqoykTdvXjZ7lJyczNUmIoSgX79+ePbsGbp3767y5c2bF3369EF6ejquXLmCc+fO4fTp0zhx4gSOHj2K33//nauf+VeZVtWSmqenp+bmFxgYiEKFCgk3pYMHD4IQIuxEXLp0CYQQLFy4kOs/deoUCOHDMgEwqZGffvpJ5ZN3OHmsfHLq7x07dqj8t2/fZpsBr2OYmpoKQsQzjpIkCVmSP4fl5OSgY8eOQv/p06dhZWXFlQKRJEkh69K+fXuF/+3bt2zGh17y6un9+/dVyWjBggXZM/bo0SOFJBK9KAtgSkqKQluTXoMGDWLvLzg4WLXZV6xYkQXUd+7cUSW81tbWDPaXmpqqSlblxRZJkrBt2zaV/NPPP//MPufTp09Vc8Xy7lNubi5+/PFHRRHMlLTp2rVrintp6s/IyICfnx/z85g5Dx8+zCjheVqgiYmJaNSoEQghCt1F+fc9duxYEMKHTANGUiCR7Atg1KEz1VClFhUVJUyEACOs25ycyKewpKQkzaAmJycHEydOFPp1Oh1KlCghRKxQ2K5ojvXs2bMghAjnHH/88UcQQhRkRXIbOHAg8uTJI6zqN2nSRIUskb+3zx3gJCUloWLFiprBNUXZDBo0iHsOydlPQ0JCVH6qmUsIQf369VVrUj4rXLp0aRVagp4DtDjFC6ApYmPQoEHc4pG/vz9KlCihIuoBjM9iYGAgzpw5sRm8lwAAIABJREFU84/ogvxn/++2fft2TJo0SaUvKregoCDY2NggMDBQGHeVLFkS1tbWQmZ/GvPWq1dPKClXoEABWFtbC5EDlOhKxBwNAHXq1NGUrdq/f78msVBUVBRj7OfZzp07he9PkiRMnDhRmHgGBQVhzpw53L35zp07cHBwQI8ePXDs2DHFGSAf97O0tESrVq0QGhrKYsTIyEiVlmjRokWxYsUKFqfwcoVmzZohPj6eoS7lV5EiRRAcHIysrCz06NFD5Tcn1/Sl2F+ekBpfk5T9NyWkkiShb9++qi+5devW7GGV0zjTq3r16qwiGhsbqxCrp4uQShLodDoMHDhQ4bezs2Mzizdu3FAIbNPFzmMp1el0OHz4MPr06SOUPACgSToDmGcwo/pZWnb79m0MHDhQ6M/IyICTk5Mw8NTpdHBychJ2GDMyMmBjYyOEfixZsgQODg7cKvqHDx9AiBEuzPuslJWvRYsW3If5ypUrIIQIO0QxMTGaHaK/0tLT07F//37h4SFJEo4cOaLZTZg5cyY32QSM65fOKNSvX1/lP336tEKPzxTefPz4ccybN08BpZWvv1u3buHAgQOMdZkQJYnVmzdvcOvWLdZxpxcN/nJzc/Hs2TOMGTNG4ZcnPO/fv1cEj4QoibSys7Nx+fJlhXaXnMjFYDAoOpeEGDXQ5EyMjx8/ZrPXNKmWr63nz59j9uzZzJ8nTx5FAPv27VusXr2aFbgsLCwUa1un02HNmjUKWLNphXn37t2KxNr02bh//z7bSywtLVUBdHp6OiM0y5s3L5eNkVZiRevlypUrsLa2VhUmqL148QIWFhZCfeHr16+rknW5paSkoFSpUpoIjvj4eLOws09hIpZFatu3b9f0DxgwQMiImZubCycnJ2G1/syZM3BwcBDCHQMDAxVEbqa2dOnSzxrIpKam4saNG3j06JEQ/k3ZWX19fbkJMt0T8ufPz4UXjxo1ij0rHTp0UJ01CxYsYP6mTZuqYIh//PGHIuGcNWuW6p5RKJ6rqytmzJih8tNOd/78+bF06VLVe6TakXnz5uUWMSMjI2FtbY1GjRpxocFnz57FggULsGPHDs2OUkZGhqamdW5urmYBxlyBwpzf3MyhFjMsYNy7tDpykiRpstMC5pnJo6OjzXbeTPkwTP2///676ixOTU3FsmXLMGvWLEyePJk7KiFPdqpVq8btLiYmJjJujWHDhnHvB01aihYtytUp3rlzJzufxo0bx/0cFD7q6enJXRNTp05lZyTPn5aWxgrcojU1YsQIFC1aVIgWDAsLQ+nSpYXfeVhYGKpXry7cO0aNGoWvv/6aq2OanJyMwoULw8XFhVvwohKOhBgVGuTv8cOHDyhXrhzz9+zZU9HgMSWsa9q0KXs2ePlGmTJl2DmdkZHBtGblcQbleklOTlYg0QgxEnmZcrB8ifYpE9LnhJC7xAjpdfqY1/lSElLAuFl89dVXcHJyQlBQEKytrRUSInKNqkaNGiF//vyoU6eOYgO+ffu2QmTb2dlZAcMxGAz4/vvvFQtJDifMzc1FUFCQAkcurz5FRERg7NiximCV6suZ2oMHD+Dk5MTVQaTWvXt3BAUFCYkhJk+ejO3bt3O11bKzs7F161acOnUKc+bMUR1yOp0OR44cwb179zBgwADExsaqIBTHjh3Dq1ev0LlzZwaLk9/P3377DRkZGWjevDkLPOW/P2/ePBw6dAgNGzbE3r17VZvSyZMnYWNjg969e2Pnzp2qg9rX1xfW1tZYvHgxQkND8fLlS4X/8OHDqFKlCq5du4Zly5apAv/k5GQsX74cly5dwvz584Wd5MDAQOzYsUOzQPDzzz9rMjPTiqZo06GdZpEOqSRJ2LRpkyab7N27dzFw4EAMHz6c63/27Bnatm2LHj16cGce3717h4EDB6J3796ws7NjRYinT59CkiRkZ2dj2rRpqFevHmrWrMnm6p48ecKC9vXr16NkyZLo2LEjKlWqBMD4na9evRoGgwHnzp1DhQoV0Lp1a1hZWbFDPzU1FR8+fMCLFy/QpEkTeHh4gBC1RmVGRgZ8fHxQs2ZNEEK4B1FgYCAqVaoEKysrLF++XOU/cOAASpUqhUKFCnHh7Pfu3UP58uVRqlQpLtT73bt38PDwgJubGzp16qTyGwwG9O/fHxUqVFAxT1NbsmQJ3N3d8c0333D9x44dg4eHB5o3b871P378GB06dBB2zLOysuDj4yOE2sfHx2PcuHEIDAzk+iMjIzFt2jSuXApgZAH39/fXlPsYOHCgUDYI+JMFXEToFBcXJ9QYBYxd2H379gkp81++fIkTJ04gIiKCO0ebnJyMS5cu4eDBg7hz545i75IkCZmZmbh37x5CQkLw4cMHBWGaJEnIysrCs2fPsGjRIjx9+lQBXdPr9UhPT8ebN2/g7e2Nc+fO4e3bt6xrTAPvhIQEeHp6Yu/evZAkSUGYERUVhb1792LRokVMo1P+WV+/fo2oqCicOnUKmzdvRk5Ojqpwd/78edy6dQsbN25ETk4ON7DcsWMHNm3aJAw63717h/Hjx3O/B0mS8PPPP6No0aLCAumjR49QtmxZYWFwz549aNiwoRD2vGbNGnTp0gVdu3blooJ27tyJ7t27o3nz5lx4dnx8PGrUqIEuXboI0TDt2rVD7969hfvz/v370ahRI5UeITWDwYA6depg8ODBwvU6fvx4fPPNN9z7LEkSZs+ejcKFC3OTuvj4eAwcOBD58uUTIg9SU1PRpk0bYbceACZMmKA5NxgYGIj58+cLE9MlS5Zg+vTpwo796tWrMW7cOCFMfufOnfD19RUWyq9fv4527dphyZIl3PuUkpKCKlWqYPr06dzE3GAwoGnTpujVqxcXFaXX6zFo0CCUK1dONZeak5ODjRs3okqVKrCwsOCeLY8fP2Yde1EiSJMdLy8v4VoYMGAA6tevz9VzBYzJlBZCJTw8HH369MH06dOFz+WQIUPg4+ODN2/ecBP0DRs2YOzYsTh+/Di3KBcTE4M5c+Zg5cqVQpRNaGgofvjhB2EMeurUKUybNo3L4QAYCzkTJ04U+sPDw9G1a1chJ0ZwcDDc3d25+4Jer4eXlxecnJy459CtW7dga2sLOzs7rhYqJVXMkyePSj84LS2NoaCsrKxQrVo1RfwaFRXFcglnZ2cUKFBAcQbdvHkTNjY2qFWrFtq0aQMLCwvN5/ZLsU+VkBYlhFgRQiwJIT8SQjZo/O5wQsgNQsgNUfX9c9m9e/fQpk0bAMbuIm+uq169eti4cSNiYmK4Xb1jx47BysoKs2bN4mqXSZKEGTNmwMrKSsis+vjxYzRr1gx9+/ZVvIe0tDScPHkSs2bNQosWLWBvb89lP0xISGDVm5IlS3KDqcTERMZw6+Pjw90Q6AxcpUqVMGbMGNUhQx8UQggGDhyoOqjc3NzY/E779u3RunVrxSHRtGlT1ulp0KABPDw8FAFVx44dUbVqVRBCULZsWfj6+iqqyzVq1MBXX33FkvNff/0Vw4cPZ4lQ9erVUbp0aZbgX7lyBXFxcWxzpDqlFEo6bdo0/Prrr2zzuXv3LqtO0fsUHBysCIDnzJnDYKLNmjXD9OnTVZVR2nGrXLmyUMS5YMGCKFq0qLB6++rVK4wfP144k5eWloZp06ZpVm4/1syRcOXm5rLZk6ioKFUAJEkSDh06BMD4PJjOYBoMBty/fx/Hjh1DeHg4ChUqpEjWc3NzkZSUhFmzZuH9+/do164dRowYwfzZ2dnIzs7GsGHDABgPhiZNmrAqql6vR3Z2Nvr27csOgdOnT7O1RZOBvn37Kta0/FDNysrCsGHDhB3n7OxszJw5U0j4k5ubqzl/qNfrcf78eeEhIkkSYmNjNckpsrKyNDuEkiSZ1TE1R6hljp337+yumXvtc+fOYebMmcLq+tGjR4UdWsAoDk8IEc7Qfv/998ibNy9sbGy430O3bt3g6uoKe3t7VjyRW4cOHVil28XFRZXMtG7dmkE5y5Yti9atWzOfJElo3Lgxkz6ixDvyM6dZs2aMVKlIkSKoU6eOAt42ffp0NGzYEA4ODrC0tETXrl0Vz1F6ejrs7e0Zsqd9+/aqAuevv/7K9jcPDw9uANyuXTtYWFhg/vz53Pvo5+cHPz8/TRkMc+MjWvOV79+/10T7xMbGanbV4uPjNfc8g8HA7bCY/g0tS0pKMvssmdMSTE1NNUtWqEVAlp2djVOnTnG76WlpafD394ePj4+m/JilpSVatmzJfY3c3FyUKFEClpaWbP83NVoo7N+/PzchpDPR9erV46K/KElYuXLluMUBmgTky5cPGzduVO0hVOrN0tISISEhqqRVjoSjEEv555N3tkxh9A8ePEBISAjGjh2L9u3bq3R5qUmShLCwME3Cn1u3bml+148fP9bsZJtjds7KytL0S5L0j4CAmjNz5Hk5OTmaTN0vXrzQ1CBet24ddu7cKZwN9/T0xLZt27gJ+8OHD5EvXz5s3bqVWySiXeynT59y47rVq1ez2fmPkZn8EuyTJKQf6zO9PneHNCwsDGvXrlUcZrRyJ0kSli5dir179yqqQ7GxsQyz/urVK+5iX79+vVmY1rJlyzT9kiSZTS5yc3NVD1NmZiaaNGkCLy8vLFiwAHfu3OG+R7rYra2tWfXc1KioOzGBRlKrU6eOAlJgGnCYYt1XrFih8NMZNXp5enoq/NOnT1f4TeGPNFiTX/J5Lrl0CD3ESpUqxRIo09engSPdPHJyclT+WrVqKYIbKutCLx4JQK1atUCIkViJF9hIkgRLS0tNttPPYRkZGZqHXnh4uOo7oyZJEpYvXw5LS0sEBwcL/VZWVihRogT379y4cYMVVnikWTk5OVi1ahVsbGy4iUdWVhaysrIwduxYVKhQQfU36Dp4+/YtvL29VZ02eZB6//591XyXfF+QJEkVUJoGwabP4b/l0P9S7dGjR5qJyMOHDzU7rJQULU+ePNwAXA7L4nXCf/31V8XeYIrAWLNmjcJvimah86H0KlasmGK98HSU5V1YCgOVX6YFDLo3EWKEj5smVnItU29vb+59aty4MapWrcpNuHQ6nbA78iktMzPTbABvqrMqN0mSuEghuf2bJTD0ej2mT5+O8PBw4Z61a9cuFCtWTDjvS2WMatasyS28ZmVlMdb8oKAg1d/R6/WMVdrT01NVxNDr9ay4UqlSJdVznZubi5IlS4IQwtXOjYuLQ/78+eHk5IQpU6aoinW//vorfvjhB+zduxcxMTH/ir37Yz7Dv+Fz/l1Gi9sie/PmjWbRNywsTNjlBoyknvT+v3//XvFakiT949ijP1WH1FX277GEkJ0f8zqfOyHNzs5G9erV4ejoiICAANVwdFxcHAoVKoTChQtjzJgxqord2bNnUbVqVUydOlUlBm2uAvV3WUJCgllBZgAYMmQI8ufPr6m/RiEDph0uanKm0dmzZ6v8VGyaEKOwummVSC4cTwhRwft27dql8JsGRKNHj1b47ezsFPMjFNInv+TJt2lAaFr1lCRJoZNqYWGhKhLIE9KvvvqKuzlVqVIFhKglTqilpaVpzuF+DqMQL5GtXbsW1tbW3AQ8JydHQQ5kWrXPzs5WECQFBASoXmPTpk2ss12kSBFVFywpKUlBFMbrBN66dYvdex4xgpykqEWLFtzPmZ6ejkmTJsHFxUX4XN27dw/NmzcXIh70ej1++eUXLmEJtadPn2pWzHU6ndmZ7//sf2YGg4EhYnim0+lQuHBhNGvWjOvPyspi6AkeWU5GRgZDkBQvXlzlT0pKUshWmXaVnj17ptibevfurfDHxMQo/EWKFFEkXTqdjv19WhAzTZrofCYhRNGhpfby5UvmF40keHh4aM76fgr7mG46j7yL2pkzZzT3u5cvXwrh79S0yFeAf3fCChjPBK351eDgYHh7ews7xceOHUPevHmF7Nt0ltfX15d7L0+fPg1CjISUvO7ili1bkC9fPq52LiXACQkJ+ddoNn8Ma7M5jpAnT56YbYz826RdPrXJ966EhAT88ccfCt4K+c+1b98evXr1wvnz5/+RhYK/PCElhOwghLwmhOgIIS8JIUMIIVsIIfeIcYb0oDxB1bo+d0IKGOc+5Qy6TZs2xbZt2xicZN++fYpDv3bt2ggODmbVueXLlys6cBMnTsTVq1chSRJ0Oh3Gjx+PgQMHIjQ0FI8fP/4iFpEkSfDw8NCsCAOAg4MDChcuLIQ0TJgwAYQY6fB5GP3ff/+d3Rsek1p0dDTzOzs7q5K5qKgoxb03hU4sW7ZM4TdlI5UHW7QyKz+ITAlwateurTqo5AEj7zPQpNvCwkLIiOzm5qaaIZBbZmamkJTk7zItmMqdO3dQsmRJLnuoXq9nsChCiKprkJiYCE9PT+avUaOGwv/q1SsG26KXXBYnJycH/v7+Cr9c+gUwEupQAiZC1Dqier0egYGB7LnOkyeP6vPGxsYyeBghhAt9P3DgAGP+5elIJicnY8yYMbCyskLnzp259/Ls2bOoWbMmatasye3QpKamYsqUKXB3dxfOXYWHh6Njx47CgPbt27dYtmyZcH0ZDAZNpmzgy9CU/BymJUkAGDUotRINulZF5HJ0D5KTZ8ltwIABbA3yAkg5yRdvbrt27drM7+Pjo/LLi4b9+/dX+eV7II9p3GAwwNbWFt26deO+fwBfhKzVhQsXNAPjlStXom3btpp+GxsbzVk0UeELMJ6pjo6Omt2ORYsWaSalX0Js8HfapUuXND9jYGAgl4CH2rRp07B48WLhawQEBGDVqlXCmchZs2YJodWSJP3j5GVEa5VacHCwqgsst6SkJJQvX17zO5kyZQoX4UTNXFEPMBbmRPDl/4uWnZ2N06dPC+97z549Ua9ePWzfvl0VE7x48YI1imrWrInQ0FCzRGBfkv3lCelfeX0JCSnwp86Y/HJxccHkyZPx9OlThcQCvWxsbNCzZ08cOnQI/fr1U/lLlSqFMWPG4NSpU2jRogX7/2LFiqF3795YuXIlIiIioNfrkZSU9EkPo7S0NE39KWr29vbCoXjAiGEnhC87AfwJ0RFV1w0GA6vg8wb89Xo9Swjr1Kmjukdy2RZbW1sVZFLOdkqIGq5GJWnoxetgUUbWIkWKcJNumpBqzao1bNhQs3L8qW3Tpk3cjjZgLCJQynJTfbDU1FR07NiR3S9TuZ/79+8rmOdM18bVq1dVTNROTk5s03358qUqWSWEsMPMYDBg8eLFKmkXecLw5MkTJmdCL3mH32Aw4Oeff1bA0d3c3BTByPPnz9G5c2fF2pJ33g0GAzZs2KCQsfn/2Lvq6KiuvXsmHoIkEAESEhIguLskEChW3K1QoFCkpRSKy8O1QAspWoIXL1K0eHAI8iEJbkkgRCY2kdG7vz9m3fPunXvOHd57FXiPvdZd673+yMydK+f8dG9bwqoXL16gR48e1L5v3z6Z3Ww2IyoqihKURUVFKe7F06dP0blzZxBCsG7dOoXdZDIhMjISnp6eXOr9u3fvolGjRtxZ09zcXEyYMEHVmbcnN2Fv5vhDxrFjx1QTd9evX0ehQoW4Af3//d//gRC27BRgrdwRQhASEsK0r127lj5DrNZi6d7FegbWr19P7axqyLNnz0CIdeSCdx8rVKhgdxb5z4a9YCEyMlKRkJRC1MPmtbiJezyP9VkkleO1LSclJYEQQufaWWjfvr1MIsoWJ06csDtH+t8Me441i11YCrVkwIcW7L9LgpD3LErtaiSG27dv564rgLXF2c/PjzmOIGL37t3QaDSqiZbvvvuOuX9JwRsbk+JDu4eXLl3i3seJEyeiRo0a2L59u2KsJCkpiXbeBAQEYOHChTLf01bxo1ixYpg4caLdOff3AR8D0neAyWSSST1IjyZNmiAuLo62/kmPwoULY9q0aUhMTFRItohH2bJlcfToUe7nh4SEYMWKFShWrBj8/f1Rs2ZNtGnTBgMGDMC4ceOwfPly1Zf9z6xs2GsjPXLkCAoWLMglpBAEAcWKFeOKtgOgmo08R6FevXoghDDnK0VnjxDCXHjFgJkQdjua6AwSYtWLZaFEiRJcZw+wOoQhISGq7ZRqWco/A7xnwmg0UgkE2wBKOvNJiLW9T5qde/XqFapVqyZ7dqUVl0OHDsmCPPEQ2322bNlCqeqlh7jZnT9/XqFTSgihlPBpaWlUqkR6aDQaJCQkQBAE/Pzzzwr9L0L+WYF9/PgxJZGRHmIG2Gg0YtGiRShQoIDMLiWCiYmJUbzL0gxxTk4Opk2bJvutttXR8+fPy2b3ypQpI7vW2dnZmDhxItUqLV26tGINiI6OpveDJU6u0+kwbtw4ODo6ombNmszN/Ny5cyhbtizatWvHfF6ysrIwcOBA1WTLmjVrVLV21VrCHj9+rJrlfx9alO3JYIh6rWqoV68edzRCEASUK1eO61ymp6fDxcUFXl5ezPMQ52AJIUy5CzEp6ObmxryegiDAz89P9ozb4n2QE7hy5QrXcQaAoUOHonDhwtxOk4YNG4IQ9ngAYNVjJcSaiGYF5l9//TUIsTJispK54ryus7OzYlZYRPXq1REQEMAN/KOiolQlerKysrjyaB/x34Vjx45xR0AAayKREKLKQl66dGkULVqUK/MjEqLxlBp+/fVXEGIlY2TBYrFQ0kkeGePVq1fh4OCAtWvXcs9z8+bNqj4iYO3kUBsLMBqNXCZd4D8LZtV87OjoaO6as2PHDlSuXBm//vqr4vtzcnIo4Wfp0qURGRkpaxWPioqS+RgFChTAV199hRcvXsBisSi0zgmxEnXNmzfvvQ7cPwak74iHDx/K2jMJsepTio7g3bt3FQ51y5YtaeXrxYsXdOBePLy8vGigpdVqFdpCLi4uuHLlCgCrTEJoaKjC2RbZHaWsm3PnzkWPHj1Qvnx57lwiABw9elQ1a2Kv5cMeGUVcXByXal9EixYtuDMhADBhwgSudAVgdTS8vb2Zm3hGRga9jqzBcXEGVaPRMKsct2/fpi87b/A8ODgYERER3Jd8/vz5VB/qzwbP0RGRmZmJSZMmMTcprVZLg7HAwEDF7zlx4oQsSLKdG963b59Mz48QQom7BEFATEwMtm7dKpMsKl68OHWiU1JSFK22hPyzamMymfDkyRNZBVbqQAqCgJcvX2LSpEmKd1TE27dvsXnzZpkWqpTMKDMzE0eOHEHx4sVlSSVx3kiv1+PUqVOyCquDg4OMAe/ixYsKDTFpZf3BgwcKsi4pG2RGRgYmT54sW2ukyRaRTE0q7WTL5nj27FmUKlWK2m2rq8nJyTSRQwjBzp07ZXaLxYLx48dTO4vp99KlS7TazXIEDAYDhg8fLpP3scX27dvRtm1bpg0AZsyYgV27dnHtkyZNUp2Ht1gsqhUli8Vil0X4j4C9mf3169erOksLFy5kyguJ6NKlC7clHLDOqNeoUYNrr1KlCjp37sy1d+7cWVWS6o9Ier59+1aVYCorK0uVVXTt2rVcOSrgn0zmrODZYrHQNjcWl4EgCDJtYla3grTLiZWg2bhxI7Xz5DxE/yAyMpJpX7p0KTQaDbcanZeXh1q1aqnqiOp0OtVunPz8fNVxDYvFYnef+Yh3g721R+06nz9/HiEhIdx1Qxx34knDiBV7QtiElAaDgaoohIWFMb+jTZs21H9iscSKxJiEKLupAOt+KhZyeJ0Bx44dg5OTE4YMGcK0G41GjB49GqVLl1aV72revDk3MMzPz8f333/PtAHW4FBNvz0yMpJrv3btGoKDg5m/XxAEui7VqlVLpiAByEfa3N3dMXfuXOqrCIIgCzo1Gg1WrlxJuwieP3+uSL6rtbO/L3jXgNSB/I+jfPnyZOHChbL/ptfr6f+uWrUqWbJkCSGEEI1GQxwdHUlcXByxWCyEEEJKly5Ndu3aRRwc/nkpc3NzicFgIIQQUrRoUXLixAkSEhJC7Uajkbx9+5YQQkilSpXI9evXSceOHakdAHny5AkhhJB79+6RcePGkc6dO5Np06aRPXv2kEePHpHExETFb8nMzCSDBw8mn376Kdm5cyfz91osFtKpUycSFRVFBEFg/pu5c+eS06dPk6ysLKb99OnTpG3btuTFixdM+/Hjx0njxo1J6dKliclkUtgvXrxIKlSoQJo3b06ys7NlNrPZTI4fP04qVqxIWrVqRXQ6ncyel5dHDAYD8fT0JC1btiQajcaaWZHA1dWVEEJIy5YtSYECBRS/8+bNm4QQQgYOHEjS0tKI0WiU2QVBIBqNhsydO5dcvXqV5OTkKH5DkyZNSJ06dUhMTAxJS0tjXoe0tDSSlJREXr9+rThH6e998eIFycvLY9q3bdtGAgICyC+//MK0E0LImjVryI0bN0iTJk0UtqJFi5JvvvmGeHp6kq5duxKNRiOzt2zZkixbtowUKVKEFCtWjLRr105m79KlCxk8eDApWbIkKVWqFHF0dCStW7cmhFjfh5o1a5JmzZqRChUqEH9/f+Lo6Eg6dOhA3weDwUBycnJItWrViIODAylVqhRxc3Ojn5Genk4OHTpEKleuTAghJCgoiBBCSM+ePel3PH36lFSrVo24u7sTPz8/QgghAwYMoOfo7e1NqlWrRvz8/IiXlxchhJChQ4fScyhSpAhp0qQJ8ff3JwULFiSEEDJkyBBSqFAhQoj1eWnRogUpW7YscXd3p98vfWcbN25MwsLCiIODA3F2diYRERGkcePG1F6hQgXSvXt34urqSlxcXEiNGjVIp06dqN3T05OMHTuWeHp6EhcXF1KuXDnSr18/atdoNOTbb78lFSpUIC4uLqR06dKy30gIIc2aNSN9+/YlLi4uJCgoiPTv319m9/X1JVOnTiVubm6kTJkypFu3bjK7g4MDGTlyJPHy8iKVK1cmLVq0ILaoWLEicXNzI40aNSKVKlVS2LOyskh8fDxp164dKVCggMIuvr81a9ZU2ESkpqaSjIwMrh0AOXHiBNc+YsQIUrp0afL06VOmfc2aNaS9IeROAAAgAElEQVRUqVJk//79THtubi55/vw5c20ixPr+JyQkkNTUVO4amJKSQt68eUMSEhKY9uzsbFK+fHlSoEAB5nnm5+eTWrVqkYoVK5Jbt24p7EajkTRt2pSUL1+eZGdnk0ePHsnsFouFREREkKpVqxIAJCYmRvEZjRs3JpUqVSKCIJDbt28r7L179yYWi4Xk5+eTuLg4hd1kMpH/+7//Izk5OSQ+Pl5hF/epxMRE5vqm1WpJaGgo6dq1q8ImokmTJqRChQpcu9lsJhkZGcRsNitsgiCQ0NBQ0rhxY+Lp6amwJyQkkM8//5xUrFiRLF++XHGv3r59S7p160bq1atHlixZQkqUKKH4DF9fX9K+fXsyZswY0rRpU8XvzMjIIL179yY9e/YkTZo0Udjz8vJInTp1SHh4OClVqhTzNzo5OZFGjRpx9xE3Nzei1+vJvXv3mHZCCKlduzapXbs29UtsMXjwYBIUFMS8j4QQ8uOPP5KAgABy/Phxpl2n05GHDx9yv1+r1ZLY2FjmfSKEkOTkZPLo0SPu+5SUlEQeP35MXr9+zbSnpaWRBw8eqJ7DtWvXyI0bN7h+zaVLl8i9e/e47/3bt2/JyZMnSX5+Pvc7zpw5Q7RaLde+cOFCEhgYSE6fPs20nzx5kgQEBFCf0hY+Pj7E1dWV+T4SYr2OERERpHbt2szzePr0KRkwYADp0aMH8518+vQp+fbbb0mNGjVIq1atFL81Pz+fdOvWjdSqVYsMHz5cse4QQoiXlxfp378/6dSpE0lJSVHY09LSSL9+/Uj9+vVlfrEUDg4OpFy5ciQ0NJRp12q15Pbt26R79+4Kn4UQ69rzww8/kAoVKtA93Ra//PIL9cNZqFixomwPt4VGoyF79+5l2urVq0dKlixJduzYoXjnNBoNWbZsGXFyciL+/v6K9a19+/bUFytcuDAZPXo0vU4ajYasW7eO+iGOjo6kevXq9P8HBwcr4hUXFxfmNfog8S5R6x99vE8VUsCaHYyIiECpUqWwY8cORQVREASqjRkdHc3UJ1q8eDEIscqPsKqXz58/R4kSJVCpUiVERkYqMhoWiwVz5syBRqPB0KFDFVXKxMRETJs2Db6+vnB3d1dktg8fPiyb0+vatSvzt4rtrBqNhjk7aTQaaUW4W7duzAqjv78/PD09UbBgQezcuVNBEFKmTBmqMzp79mwFKUflypVpK1WfPn0wf/58WUuSj48PbaWqVKkSTp8+TatJBoMB/v7+KFOmDP2taWlpyMzMpBnkmjVrwtnZmfbji5UgMeM/c+ZMODo60tbHuXPn4ujRozJWOU9PT3oOAwYMwKpVq2QVI7GS5OLigrCwMIwePVqRwd64cSO8vb0RFBSEJUuWMO/Hxo0b4eDgwG1/jomJQUREBFfXErA+n2qVGMBaJVQjuMnOzsaWLVsU7X/ic5qRkYHk5GRZi/P9+/fp7JXRaMTTp08xatQoHDp0CIIgYOvWrfDx8aEySbdv38aRI0do1Wffvn3w8fGhLMsxMTF49uwZgoKCYDabkZqail69elG9yNjYWMTHx6N48eI0K3r//n2MHj2ayq88e/YMAQEBsmrAvXv3YLFYkJOTg4cPHyI0NJTZamSxWBAbG4vGjRtz263j4uLQu3dvphwNYJ1nmjhxIlMrD7C+xytXruS2gmdlZWH//v2K6qgIs9mM69evq86kvX79Glu2bOHa8/LyVJlHzWazatuYIAjMNlEpeERN7wJ72d4tW7agbdu23Hfm2rVriIiI4LZ6XbhwAU5OTlzSomXLlqFEiRLw9vZmSn5MmzYNtWrVQrFixVC3bl2FfcqUKVSaqlKlSrJKhSAImDRpEu06qFu3LurUqUPtRqMREydOpMRt5cqVQ1BQEO3GsFgsmDx5Mvbt20crf+3bt5dVGpYvX47t27fTVvi+ffvKZJqeP3+Ob775hpJ7tWzZEt27d5f9ht27d9PWvnLlyimY0MXrVLhwYW5rn9FoRJcuXbB06VKmHbB2yqi1q/4nsPccvUtVwd4M67vY7X3Pu5Dq2Ps3Y8aM4erqAtZKc8eOHbljQGfPnkXz5s25eqa3b99G6dKluRWjO3fugBClxJsIUcu0Xr16zM4CkWQyODiYKR/z6tUruLq6okiRIlzdW/F5Z2mnA0Dfvn2h0WgwcOBA5nU4ceIECLHOA7PumcFggK+vr+pc5KlTpxAREcGdzX/y5AmaN2/O1aE2mUx2dULfJ9h7Lu3xDKhVKAVBsNutZ69LRa07Y+jQoRg3bpzq96vh7du3qv9m165d3N+fkJCAwYMHU7lJW3z//ffo06cPs4PFYrEgPDwc3bt3x969e9+7Z4IF8rFl91/Dy5cvZZu6IAiyRS0lJQUTJkzg/r0gCOjZs6eqZtn9+/ftDqQfOXJElVBIr9djy5YtsraQhIQE/PTTT1i5ciVWrlyJVatW4eeff1YsuikpKTRICw0NxaZNmxQP882bN2mg5+npyXwhpG2F1atXV3yPLbmMrXPcoUMHmb1WrVqy86hTp47MTgjBwYMHqd3Hx4f+d2dnZzRp0gR16tShi2PdunVlf9uvXz9Ur16dtvlt3rxZ8fkFCxaULX5SrVVCrPMU0ha2t2/fyuysZ+PevXvUziNeyMrKQvXq1Zm2vxrSe6DVajFz5kxF215eXh5MJhMWLlwIFxcXhWSFVqvFq1evqDSLraMrCAIuX76MAQMGgBACb29vRSB/69Yt7Nu3jzoYtnPGMTEx0Ov1mDFjBpydnRXav2IwmZ6ejhEjRuDrr7+W2aUzaYmJiZg3b55sY7VtsRHnN0TY06JLSkpStWdlZam2Q5rNZrtSER8aM+T7BL1eD3d3d+78ukj44+LiwnQoTp48Sd/rXr16Kexbt26VrQ22TLy2OqK9e/eW2UUWc+khdVymTZumsEv1rX///XeF3XZWtHHjxjK7LdlZRkaGrDWMNccZHx8PR0dHfPrpp8zr+KGB5xyK+F8mHjpz5gyXTR6w+jZBQUHc9kmx1XTx4sVMuyhlFBwczHzn0tLS6LPIY+QVW6N5yT7R7+DNt69YsQIlSpTgBuUXLlxQTeR9iHiXtvz/JLn4EXyoKSyYTCZm4UvEkydPmCMG7ys+BqTvAIPBgK1bt9IXzpb84bvvvsOqVavoAinNtjx48ADjx4+XVQd1Oh3N2PCY49TmZUT8WRmPwYMHo3r16ti1axd3IRKZvLy8vLhVOW9vbxoMsmQPpDqRVatWVXzXt99+K3OGbDcIqWQBIQQ1atSQXZPq1asrHC4pwUq3bt0Udqlupih8Lz1sWRZFllPxsJ3HEwSBzie5uroy53JNJhMKFCiATz75hHkdRfwd8gk5OTlcmvxdu3bB19eXWdl48OABnY8IDg5W3NuDBw/KSIps52xPnjxJRcpZgXxaWpqMvbply5aKc7h8+TKdUQkICFBsmIIgYPPmzfDx8YGjoyOzGpqXl4c5c+agQIECzOoPYE06jBw5UpWx8O7du6qEAuKcrRr+V6VX/k7Ym4EPCwtDo0aNmDZBEFCxYkUQwmbRNRqNsllf270gOzubJgZZa098fLyMUbpQoUKy5yspKYkSX4mHlE1ZEAQFGZ/tjKWt1jPLSRelbZycnLgJkl69etm9lu8D8vPzVUm4rly5gkWLFnHtN2/e5JLAANa1niUhJcWHUMngwd4a9eDBAy6jN2B9ZkNDQ7nPkVarBSFKVnIRer0ehBB88cUX3O/w8fFB27Ztude5WbNmCikxKaZMmcKVcfpQYU/eas6cOar2M2fOqL43AFQ17UV8yM/++4oP6Zp+DEjfEdOnT0f58uWxf/9+xQ1+9eoVChQogOLFi2Px4sWKYHLixIkghCAiIgK7du2SLbYvXrxA06ZNMXnyZFy7du1vr2ikp6fjyJEjdh/iQYMGoWjRoqoMsaIzxZM0GDFiBDNQFLFixQpqr1SpkuLa2FYIbDcpcehePBo3biz7XaNGjZLZPT09ZS2tjx49ktmLFi2qGN4X2RUJIahSpQrz/omBsdom17hxY1Vyp78aJpMJq1evZraqJCQk0CxyoUKFZNfEbDZjyZIlMoIvabY7MzMTAwcOlF3X0NBQel9yc3Nl11Q8pMRBBw8elBEPESKvjGdnZ2PUqFHQaDTUbutE3r9/X6aHaqvBKAgCdu/eTZnuKlasqHC2dDodZs2ahYIFC8Ld3Z1ZGXn8+DH69OkDjUbDJJMSBAGHDh1CnTp1sH79eua9yM7OxuLFi1Xbbx8/fqyaKbVYLHbblj5CCXv6v+vXr1ftiBETdyL5nC3EltvAwECmferUqfQZZY14SHVK69Wrp7Dbvmu2RCnr1q2T2aOjo2V2k8kkC5pZLK6iHnSVKlW41+Hy5cvcitRfCUEQcP/+fa594sSJ3LEJi8WCunXrMjWHRbRs2RKjR4/m2jds2KBqFwSBqff63wJ7/k1OTg6OHTvGtZtMJrRo0UI1sefj48PU7BVRtmxZVVm7wYMHq7aQvk8Sbe+CV69eqTKSr1u3TlVLdM2aNahVqxbXHhsbiyJFiqgG6UuWLMGwYcNUz3P9+vV2CbP+bv/4Q4HBYMDs2bM/uD3/Y0D6jsjMzKStHk2aNKHstyIWLFhAN20vLy/MmDGDLlx6vV4mieHr64tJkyZRJ/vcuXM0012iRAkMGzYMR48ehV6vh8lkwuLFi7Fo0SIcPXqUSlj83WjatKnq/BgAFCpUCPXq1eP254s6oOHh4czfdOTIEXrNWM6MqP1GCEG1atUUi9XgwYNVna158+bJ7LazYjqdTmZntREtWrRItXoAWCvBTk5OqpvgggUL3ouWFzFAqlChApycnGSBoMViwapVq2TyLVJGycePHyta/FxdXekM3+nTpxEYGKgINpctWwbAWn0oV66cwi7Kpmi1Wnz22WcKuzhLCliZo22/o0CBAjTRoNPpMH78eIVWqbTV8NatWwgLC5PZpU6i0WjEqlWrZC3pkydPll3Hly9fYvDgwXB0dAQhBF26dGFeZ7Hlu1atWoqANyMjA7Nnz0bRokVRunRpZjfF7du30bNnT5QsWZLJdGg0GrF161ZERERwHamkpCT88MMPqu2/76JL/L+IzMxM7pwXYHWwPT09uddPp9PBy8uLWeEHrIzIIjM1ayxCKm01YMAAhV2c2SPEyhhtu87m5eWhWLFi9N+w5m0XLlwIQqxMj7wKWJs2bVTHTARBUJ0D+6swY8YMrqahKEHBm2XdsGEDCCGK1n4R4mwh7zrk5+cjMDCQ2b4tYteuXYrkmC1s97H/JryLb2Ovmmc7mmELNakpAHZ5Ft43qK3bGRkZqFu3Lve6XrhwAc7Ozti7dy/THh0dDScnJ3To0IFpT0pKoklbXlff8uXLQQjhSruYzWaMGzcOFStW5P4OwMolwetSkuJ98I//KmzYsIH7vM6cORMBAQF2OzLeJ3wMSP8F2M70dO/enWaMDQYDypcvL7N7eHhg3LhxePPmDe7cuQNnZ2eZXaPRoHXr1rh69SrWrFmjcLQLFiyI7t274/Tp0zKZBi8vL4SFhWHkyJFYvXq1KnGIIAh/+AtqNptVs8wiihUrppizk0L8zbbBvQhRQy8kJIQZ1B4+fJheE9aCKp2hkmpBihAdDDERwJKnEKnPixcvzrSL4tE1atTgZu8mTJhgV7PV3lD/H4mHDx9ixowZsqoiYG03i4iIoNdk+PDh1PbgwQNK3iQeDg4OeP78OSwWC5YvX66QRSKE0N99584dNG7cWCGN5ObmBq1Wi7y8PMybNw9t27ZVfMaBAwdgMBgwYsQI2gZum0jIzs5Gv379FDZC/ikNs2/fPlm1Rzzat28PwNp6+8UXX8gqq4RYq/NmsxmCIODXX39VyC95eXlRZ/vNmzf4+uuvZe+6k5MTXScEQcBvv/2mmD2WEoelpKRgypQp9NkTr4EUFy5ckF0r24RNXl4efvrpJyqjs3HjRsVz8PTpUwwfPhyurq5MciNBEHDs2DGEh4dzq/e5ubmIjIxU1YBMTEx8L5Itfxbsra9z5sxR/TfTpk3jBjnAPztJeAFdq1atQAjB/PnzmXZRkqRhw4ZM+5QpU+gax4JWq4W7uzvU9uNjx45xv/+vRGpqKjdRKs7ssjoV8vPzaXu1mCCTIisriyagRG1kKSwWC2rVqgVCCJo3b878frEaLiWOkkKv1yMkJIS5V4m4ffs2NzgQ8b8uy/K/FJD83//9H1cmSK/Xo1mzZtzOhVevXlGeDVZ3zYsXL+h+y6pu5uTk0H3M19eX+R2rVq2iexRrJEWn06Fjx44gxEr0ycLr16/RtWtXFCxYkLsG5ufnY/Pmzfjuu+/sto1/aM9HdHQ0N9jfuXMnQkJCmNXp5ORk6m/16NHDrozj+4CPAem/gLy8PPj7+9MXzMfHBxMnTqSVCzFDKnVU161bR8vmYqZZPFxcXLBt2zYabH311VeKgHXt2rWwWCzIzs5Gs2bNFM707NmzodfrMX/+fNStWxeVK1dG6dKl4evri4IFC2L48OHMF9BiseDkyZNMBl0ROp1ONVCy1z5hTzB9//79qvp3+fn50Gg0XLa6+/fvgxB+q6x0MWTNuR49epTaV69ezfwOkQWY91tEwXPb4E6Kn3/+WTUw/ytgNBqxZMkS1KhRA4QQdO7cWfZcXLt2TVaddHNzo46NIAg4cOAAJRgSj27dugGwPgdxcXGIjIyUaXwSIq/qCIKAHj16MANWEbbvSEBAgCwZceLECVnA6OrqSkmmROIh23dIDAZfvXqF1atXK+bqRBKO1NRUbNq0iWZ8xUOcC9br9dixYwedjRUPqYbZ77//TllJxUPaovfo0SPawivapRWV/Px8jBgxQqbX2qZNG9m9ioqKkgX/tlpzInGIaA8LC5PZc3NzMWjQIHqvWFp1v/76K201b926tcKu1Woxe/ZseHt7K6q/IuLi4jBw4EAMHTqUaRcEAQcPHrQ7e/ShQ00XErA6Drx2bcBKnlSiRAmuXdx3eHN1YqcJb67u9evXcHJyUp1hHzZsGAYOHMi1i2vA3wVBELBp0yYFc7aI6Oho+t7Hx8cr7FL9YinxkwjpeEinTp0U9h07dlA7KwDIzs6mzn25cuWYv2HZsmUghHADf7PZjHr16nEDXsCaVFOrwH7Eh4UnT55wg5FLly7B09OTOZMrCAJN0LKe15ycHOoLEEIUevQ6nU7W1Td79myZ3Ww2y0gnGzRooPiOn3/+mdodHR0VvmRCQoLsHGy1OgVBwLp161CkSBHFPir9jHHjxqFo0aIoUKCAghRSEAScPn0aixcvRr9+/dC+fXvFb01OTsadO3dw7do1REdHK+x/BdSC5AMHDqBjx45MH1en08HNzQ3u7u7M6vHQoUPp9fX19bXLU/F342NA+i9C+pKFhoYqKndSh9vNzU3GxGY2mxVVJumgt9FolFWoCCFYtWoVtefl5Smc3RkzZgCwPtB79+6VEcEQQhTD6BkZGfjhhx9olYfHZmcwGNCqVSvVeZY5c+bg/v373Jdpx44dSE5O5lZHfv75Z1y/fp0b9F67dg3169dnUnprtVpcv34dhBCm9IXBYMCePXtACEG7du2Y5yiyTAYHBzPbXtLT09G8eXMEBQVxz/HZs2cy5l4WxDk0i8Wi+u/0ej1XogKwZizVRMujoqLQqlUrWpW3hVjhDwkJYWYa169fT5+b7777TmGXCl0TQhTJjHPnzsHFxYUGW7ZSFy9fvoS3tzc0Gg1t7ZUyIaanp9OK3rBhw+Dg4IBZs2ZRu9lsxieffEI/mxXQLl26lAaihBBFNeHatWuygNS2WqHT6WSySJUrV1bcM+k7GBAQoGillQbVXl5eilbZixcvUnuBAgUUAumZmZl0/trZ2ZnZota0aVMQYq2+sroVJk+eTB0BlozP3r176d+zZE8ePHgAjUYDV1dXJvPzmzdv4OvrCw8PD6aDn5+fj4YNG8LLy4s7zzV9+nRuK7JOp0PVqlVlVXpb9OrVC/Xq1eO+U3PnzkXp0qW5rKcHDhyAn58fs2ImhT15BXtsx3q9XrUNUKfTIS8vj1vZ0uv1WLZsGbcrxWQyoXLlyrh+/Trz35jNZpQtWxZLly7lEsp06dIF33zzDbcSfuHCBSxcuJA5xwpYK4harZbb+peXl4erV69y2y1NJhN27NihOhs4fPhwLFy4kOkwPnr0CB4eHtw5td9++w1FihRB4cKFFRUUo9GInTt3olSpUihZsiR+/PFHhX3Tpk2oV68eypYti1atWik+f+vWrejWrRuVbLPF5cuX8dVXX8HDw4Npt1gsmDdvHhwdHZnOPWCVRAkODkabNm2YdgAYPXo0evbsybW3atVKNfEwYcIElClThtn+D1j3dD8/P1XH1mw2q84sCoLA/XwRRqNRldjRaDSqfobBYFC1m81m5Ofnc89TEATk5eWpnoNUQo4Ftb1669at8PPzY8rlifjhhx8U7PMiTCYTevfuDWdnZ+Y5vn37FqNGjYKbmxvGjh2rsIuKC87OzvDw8GAqLZw7dw7Ozs4oWrSogqk1Ly8PT548QXBwMDw9PWUybyJev36N3r17w93dHdWqVVPY8/PzsWrVKjg6OqJIkSJMP/HRo0dwdnaGg4ODbHxIhNFopGoLtrKBImbMmAFCCMqWLctcO86fP099hkmTJimuRWpqKuWJGDdunKJTzmKxoFOnTggLC2Pez40bN6JEiRLcLqKrV6+iePHiXNWMGzduwNnZmbtPdenShRZNbOMRscuQl2h73/AxIP0XYTKZEBoailWrVjHlABISEuDh4YF//OMfTCKLZ8+ewcPDA3369GHOqqSlpSE4OBhly5bF2LFjFQ+YwWBAz549aYXK1hnU6XSYOHEinJycUKpUKVn14eDBg4p2Q1uaf8D6gokMph4eHswFT6/Xo2jRotBoNLKgWYqaNWvC19cXDRo0wNu3bxWLd40aNVC/fn24u7vjypUrCsfZ398fn3zyCRwcHPD999/j8ePHtO0gKysLHh4etGIdEREBk8lEX/q8vDxUrVqVVoF8fX2RlpYGQRCoAys69X5+fvDw8MCpU6cQHx9P570OHjwIf39/NGjQAE5OToiMjMTBgwdl5zlkyBB89tln0Gg0+OKLLzB16lSZA2wwGDB27FhUr14d9evXx2effaa4Tunp6RgyZAh8fHy4BFDp6enw9/fntrUA1krI+PHjFQGOCK1Wi0GDBnGJqCwWC44ePYqKFStydb327NmDFStWMOdSnj59isuXL+Pw4cPw8fGhmrCAVdqmbdu2OHr0KDZu3IgXL16gTp06tKV8+/btCAgIwM6dO7Fs2TIIgoC+fftSJ/3ChQuoUaMG1q5di2XLliErKwvh4eG0Apufn48FCxbghx9+wObNm3H8+HFoNBqZDqhWq8W5c+dw7tw57N69G05OTgp6frPZjCdPnmDr1q0oXLgwc5PIzMxEVFQUgoODmZUts9mM9evXo3Hjxsz2P8A6K9alSxdF5lnE6dOnMWTIEMVsqoi4uDh89913XH00rVaLuXPncu0mkwlRUVEyVmlbnDlzRpYQsMWjR49UuyCSk5NVOwd0Oh23vdJgMKBcuXKq83Tt2rVDzZo1ufbJkyfDz8+PO9Kwd+9eeHl54ezZs9zzDwgIkD3HUpw9e5YGKazq4MGDB9G3b18EBgYyJU8OHz6MefPmQaPRICwsTFHhPH36NA4cOAAXFxe0bNlS9lstFgtu3ryJuLg4FC5cGKVLl0aFChWorq0gCHj69Cnt6nFyckKzZs1k1ZKUlBQIgkATLHXr1oW/vz+15+XlQa/XY8WKFXBwcECDBg0U5EsZGRl0TwsMDGTqWr98+RItW7aEi4sLd69Yu3YtCCGqEgUzZsyQaUDb4vHjx6rzhVqtFjdv3uTa8/PzkZmZye1msVgsyMjI4GpHioGWWstsdnY2UlJSuEmUnJwc1aSkveSG2WxWtbds2RL169fnfv/YsWMREBDATSJt3rwZhQsX5t4Hi8WCDh06cDuODAYDWrduzSTgAqzXp0ePHihWrJiiYgZY196RI0fCx8eHmazKz8/H7Nmz4eLiwtT+BayJ8FKlSiE4OJi5V16+fBlhYWHw8/NjJusEQcBXX30Fd3d3ZjIOsAaEnp6e3GTYxo0buXJ5IrKzs7l7OWBdw9UCWkEQkJKSoko8mZSUxNXKBqy/49mzZ9z3RqfTIT4+njuXazQa8eLFC24HiCAIePLkiaoG8ZMnT2jhhYVHjx5hxIgR3Gf6xYsX6NChA/depKeno3Xr1sznTTzHIUOGqCYut23bxv38devWoVixYtz7cPHiRRQtWpQ7+5yTk6OaXDlx4gSTbE5E7969ER0draq1+r7gY0D6b+DixYuqWXPRYeZh3bp1XNZFwNpyp9YeZTabMXjwYNXNNS4ujju3mJycjN9//x0LFy5UOAiCIGDMmDG0OhMeHs6UGxGrj4QQlClThrmJiyRQhBC0atVK8UKIMzfiYev8S1tIXVxcEBAQQLNTgiDI5hELFiyIwoULY9q0afTvixQpQgNSZ2dnjBw5Ek2bNqXVzs8//1z2/SEhIfDw8KDB2MuXL2V2BwcHeHp6yjJkti2iLDa6Pn36UDtPlHzQoEEgRN7+aYs7d+6gffv2qplXe3iXWVWewyVCr9fLKvtiG6qUfTIyMhL5+fl48+YNhg4dCgcHB0Xm/unTp7hx4watltasWVP2XmVmZiIhIYFev8DAQFn2MjY2FoIgYN++fQgJCYGnp6ds4Z4xYwYEQYBer8fSpUvh7e0tc1jnzp1Lvy87OxszZ86U6aUuX75ctsllZWXJKlCbNm1SPNPS8xdnX3mIjo7myj4B1iBejeU1MTFR1a7T6VTtFouFORctxfssNfNHMC7a+4ywsDBuNUgkJHJ0dGTe59u3b9P3Xmxvl2LXrl2ytcPW4Zk7d67MHhYWJrN/8cUXirltaXA9ZMgQeHt7U58uCZQAACAASURBVGItQogsIbZmzRp4eXnRljixW0REVlYWypQpAy8vL2q3bR2+ceOGrL2cNacaExND21V57aTZ2dmIjIxEvXr1PpgZSHuzaB/arNofhbi4OAVBoBRr1qxRJbD55ptvQAh7zAYAHR1hVf6kf1+hQgWmXfresSqcOTk5lGuA17557NgxEEJUR3Gio6NVE3If6vNhb838dwKf//RdsrdP2dPrtmf/T++VvWv2Z7IH22OKf5/wMSD9E/AuL5e9wMAeXbPFYlF1ZsXv+VdfpFOnTmHixIk4ceKEqrP66aefUgeHda5ShtpKlSoxMzxi2yUhBB07dlScq5TIiRCl7IFte7KPj4/sXCpXriyzEyJnerMNJgmRs8YKgiBz1litrJcuXZLZWZk+6awqryUuNTUVxYoVw/Lly5l26Tm9i0btH4lbt25h6tSpiufh+fPnGDhwIBwcHODr6yu79qIkioeHBw3mpZt3UlISBg8eLJullG7e+fn5mDdvHgoUKEDttrInd+/eRfPmzandttposViwZ88ehISEgBCCwYMHy+xisLp8+XL4+Pigdu3azI0hKysLc+fORVBQEJcYQKvVYubMmVyCLsBakWJpndqe00e8P9ixY4eqgzVlyhSEhoZy7eIIB2v+SRAE2TyybZU1Ly9PxhjdsWNHmf3t27cyxmtCiKxikpKSItMxte2IsVgsaNSokcxevnx52XecO3dO9o56e3srfodIFkQIQenSpZnX4cGDByhVqhT8/PxUn3GLxcLtzvirER8fzz3X9PR01e6A+Ph4JpGYCEEQ7LLFfshQ26MEQVDVbM7IyICvry832IuPj4ebmxu3myglJQWFChVC06ZNud9ft25dFCpUiHsOYsJdTeJlzJgx3KBZxIcmU5KSksKtyoqdTNKkrS2OHz/OJVkCrMGqLUHfR3yEiI8B6b8BtUXm6NGjzE1MEATMmzePOY8FWCUvPhRphdevX8PLy0tVV04kHPL19ZXN0UrRoEEDEGKVI2BlxVu3bk0dHVabkW2F1XYhlP69WMmVzinYViicnZ0Vi7HY1kuIdcbAdo7BYDDQKoVGo2H+DpPJRBka1RiRN27cqKo1+VfCaDRi9+7ddOZZGiwmJCRg2LBhMukUMdA3m83YsGGDbA6TEIJBgwYBsFZXFy9erHCkxeqoSKAkBpHiERAQQLPZaWlpGDlypIxAybY6evXqVZkEjbOzs+z9MpvN2LJlC51ZJYTg9OnTsmuQnZ2NefPm0Uq/rZYpYK1Sjh07Fh4eHlyCrtjYWAwdOhRVqlRhJnkEQcCVK1cwbNgwbnVIEAScO3dO1dGzN6P8Ef867CUI3rx5gx49enDtcXFxcHBw4M7qi6RohBBmICayeBNCmF0ztiRgtmttZGSkzG7b8n/v3j3Ze1y1alXFd4wdO5baixQpwvwd4r9xc3PjXrP4+HhUrFiROeryd8BkMjGTDYIgICoqikvG9ezZM5QvX57bhvjkyRMEBgZyHXeLxYJhw4apVs9yc3NVWy0/dNir2mzatEm1XXXKlClcGREAmD17tuosbXR0NEJCQrh2QRDQokULu7Phr1+/5trfR1y+fJlZFTabzVi9ejWqVq3KtCclJaFLly7w9vZmFlOys7NpJxQv6Xrz5k3UqlVLNekeHx+PqVOn2i3YfEzc/nfiY0D6b2Dr1q3c2YE5c+agU6dOzDmOo0ePwtnZGePGjVNUDFNTU1GiRAl07twZJ0+eVLxwe/fuxenTp/9SeRAezpw5Y7et8/Dhw3B1dWXSiYsQAwbevEnv3r2pI8T6HGnAWbZsWcXmYatDahtA37hxQ2YfMmSI4jvE9h9C/ikPYguRaEeN/fDbb7/lsiuKEAThL3XW0tPTsW/fPixfvpy2vKSkpGDevHmy6rNIWJCUlIRvvvlGId1SpUoVmEwmnDhxQsbMJw0GX7x4gejoaJQtW1ZhFwPeBw8eUAkL22PlypUwGo1Yvny5rIXQtjr68uVLWYu0eIjSL6L+Z9WqVWV2KVGITqfDggULZPqMZcqUkW3Ujx8/xpAhQyhBUoECBWQBryAIOHHiBNq0acMNePPy8rBhwwZKnc8iZUhJScH333+P0NBQWfVeipcvX2LWrFkYO3Ysd6N+/PixquC8eD4f8a/DngRW//79VbURO3fuDI1Gw2w7EwSBJu7GjBmjsItSIeIzZktWZjKZZM86a2ZZJMAihM3wmp+fj0qVKtHnnAWTyYSWLVsyz0GKtLS0v53p0WQyYdOmTRg8eLDifUlPT0f37t1BCGGOqly5coVKZbACprt376J48eLQaDRMH8BoNFL2U14lODk5GfXr11e9TgaDgTnf+N8Ci8Wi2pmQlZWFCxcucO06nY5bQRVhz/4hVrB5Cc8TJ04gPDyc2akRExNDiYFsiW8EQcAvv/xCk7LSsRwRp0+fpqzuLB9Jp9NhzJgxdOSJlYzQarUYN24cXF1duUl5QRAQHR2NoUOH2m3r/xiwyvEhzI8CHwPSfwv79u1DhQoVmBvKs2fPQAhBUFCQYvBf6lx4e3tj9erVsgdl37591DGoUKECIiMjaRtkUlISgoOD4ebmhk8++QQLFy5ETEwMdWJSU1ORnZ393ryIq1atonIZPISHhyMsLIxb1RH193r37s20f/bZZ/R6sVphp0+fTu2ilqQUGRkZ1O7g4MAcDI+KiqL/hsdQOWfOHBBCVKUbbt26pWgZ/auh1+tx5swZTJkyBfXq1YODgwP8/Pzw/Plz3Lp1C4MGDVIEm76+vkhNTcWOHTuYOqOEWJmizWYz9u/fj/79+yt0PEWNRbPZjEuXLsmo3qXV0aysLPz666+KVu2SJUsiPz8fx44dQ4sWLWQVHbE6mpGRgWXLlinOX6zavHnzBhcvXlSwXBNirWzfuXMHOp0OCxculAWi4iG2Gd26dQs9e/ZUyNuIM1P5+fmIiopClSpVZHbpvX/+/DnGjx8vm7Fu1qwZfQ8sFgtOnz6NXr16UT3TSpUqyQLG3NxcbN26lbYs+/v7K8hQkpOTsWLFCtSrVw9eXl7MDoxXr15hyZIliIiI4Dq4r169wpo1a1QDDZ1O996sPe8bRLIvHh4+fMjVAAWsVQ1eMAn8c9/QaDTMtfTcuXP0OWORbOXl5dGgtlGjRszvuHnzJpycnODs7Mw9T61Wi5CQkL9V/kWExWLB8+fPZUlKg8GA9evXIyQkBBqNRlGBjI6OprODQUFBimu5e/duOi/LqiRfu3aNJstYdr1ej06dOoEQwp2hfPToEUJCQuDt7c3dFx88eIDatWsztQelUOvG+V+AvQSbvbnBDwWPHz/G0qVLERERIdOTFpOv4liAr6+vbA3XarUYPnw43a+LFSsmYx1OSkpC586d6drh6OgoK8TodDqFVKEtSeChQ4dkYwe2JH25ublYsGABHY0KDQ1VsO1mZmZixYoVNCnGClgtFgtu376NpUuXolOnTqrJCvHa/LftV4IgcAPPLVu2qJKlvS/4GJD+G3j48CEIsbISslroxLkcZ2dn/Pjjj7IH/+TJk7IXuFatWrJsj211p2zZsjRQevToESWHEI9q1aohMTERDx8+pKyyRYsWRZkyZVC7dm0MGjSI2YKh1+tx8eJFxQIihb15RbUX+l1aWdq2bataEZwyZQrc3Ny4rcxim1j9+vWZ57JmzRp6nXhyBPbINsQqamhoKNdBuHDhAlxcXFQddkEQVBki3wX2FtAjR45g27Zt2Lt3Lw4fPoxTp07R6k1CQoIiSCpYsCAlxoqJiWFWFqWB/t27d+Hr6yuzS9lDBUHA+PHjZXZ3d3fZ3OWGDRsU3yFtXbt06ZJsbpQQImvxSUxMlLXZSh11s9mMU6dOoWDBgjK7yDT75MkTzJs3T9EuLJJ/vX37FkuWLJFtoIQQtGjRgi72q1evVlzHihUrUufm+PHjCp1SX19fOouUkJAgm3slxMpkLbY5mc1mjBo1SmZ3dnaWOc+HDh2SzTZrNBoZmU1iYiLatWsnI7P57bffqN1sNiMyMpImxwghCnmnuLg4zJkzh7bF20oriSyv8+fPR3h4OHN2WmR63bJlC9V6ZUEQBK401H8L7L27anNXgLVbhCdrIAgCIiIiuO204t+z7qMIUQKrWbNm3M8QE29qvyUmJoa7zgmCoCoHosYOKwgC7t+/z12D4+PjsXjxYnz++eeoU6cOChYsKAu+9+7dK9PmlTK0CoKAmTNnyhJpM2fOlNltW6MnTJgg+/4zZ87I1p2RI0fK7Dk5ObSCTAhhtgOfP3+eJqlYMhqCIGD16tVwd3fnstSazWb8+uuvaNSokarGuPh5H6EOe9dIbUTCYDCo/n1aWprq358/fx47d+7Epk2bsGbNGixfvpyOfBkMBkybNg3ly5dX7HOAdS+TjqwQQmQzzc+fP5f9rW3CKz4+XpE4lhKz6XQ6tG/fXmYvU6aM7PcsXbpUlrh1cXGRMdE+evQIZcqUkX2G1E8TBAGzZs2S+QO2mtwPHz5Et27dZMndzZs3yz7jp59+wsiRI9G1a1c0atQI5cqVw8qVK+nn3L59G5GRkdixYwdOnDiBmzdv4tWrV7Qb0WAwYPPmzbhz5w434Lt48aLq7HtSUtIfQhCo0+m4/DJz5szh8r6MHj1aIQH5PuJjQPpvwGQywdnZGYULF2YGOitXrgQh1qrb4cOHZZk4QRAQFhZGXx5bqum0tDQ6b0gIUYjdXr16VfaCSh3BvLw8DBkyRPaCixurxWLB8ePHMXnyZDRp0oRWknh02jqdDp999hnXgQGAX375RbV19/fff1fNQm7cuFF1QR4/fjyzRQSwBtTTpk0DIQTR0dHMfyNqLdasWZP7PaJTzpOfyM/Ph6Ojo+rcg16vp/IUZrNZVUtPLVA3GAyq1OLHjx/HxIkTuZnfH3/8UXbvBwwYIGPkXb58ObU5OTkpKr7z58+X/b2tBpo0wCfEmjGVVkOk+priZjVx4kRqT05Ops9u//79qZSFeL3MZjMqVqwIQqxC223btkXx4sVlv1eUIypRogSKFCkCLy8vWfu77TUoVKiQbKOIiYmR2V1dXWVMirm5ubKg28HBQaEf1rFjR9ln2NLm257Drl27ZPYbN27Iqry2TNc5OTkoUaIEtS9YsAC2kLarT506VWEX3w1bR0WE+G4QwibcuXPnDq3OihVuKURJFEIIvvzyS8Uzb7FYaOtjnz59mJvxwYMHUbt2bXTr1o2Z+EpJScGcOXOwa9cu5js1d+5cDB8+nPtu79ixA926deNu4Ddu3EDbtm3/kIqevdndd6nW2NMgVgtab968iaCgIC4RzJMnT+Dh4cFl+dbpdOjbty/Kli3LtOfm5iI7Oxu+vr7M5IFer0dycjL69+/PvFcmkwlnzpzhylZZLBaMGzcO06ZN466fzZo1g7e3N3r37o2oqChZtcZisdC1w8HBQUEoZDAYaIXFy8tL4Tzm5eWhYcOGNMFj236flpZGn2dC5GzGgPX+jBs3jpvgefPmDfULbJ1m8Tv2799Pg1pbO2BtzRfb+9etW8e8RiIzM0+/V6vVokWLFqhUqZJiXRKxY8cOHD9+nJskevnyJVdTEbCu4/aC4atXr6qOH+n1eq4cE2BtfVabwdXr9Th37hx3DtViseDx48eqagcvX75UnVN9+PChatvvqVOn8MUXX3C1Srdt2wZ/f3+MHj0aly5dUqwhUs17T09PxTO1bds22X5ru8aeOHGC2hs0aKD4fHG+nRBrcto2IZSZmSlLfNr6qoIgyHg8lixZoviN0uQqq0PswIED1M4qLKSkpNB3wsvLi9mq26JFC/oZrFn9FStWULuXl5fC73n06JGMKdzNzQ1Tp06l+4bBYKC/083NDQ0bNsSoUaNkHQpDhw4FIQTVq1fHmDFjcOjQIZlfsmTJEhQuXBht27bF/Pnzcf78eVlwu337dlSuXBlt27bFhAkTFGRaZ8+eReXKldG1a1emT717927VmehWrVohODj4vRj5U8PHgPTfxPbt27mMmqmpqejduzf27NnD3FzPnj2LatWqYfHixUxHbf/+/XB2dsbo0aOZztThw4fh6OiIsLAwpuj9li1bUKBAAZQoUULWwpGYmIjFixfL2GdZQuL379+nm7ufnx9zY8rLy0OpUqXg6urKnLUBrJpnwcHBdH7PFnXq1EGbNm1Qp04dpoaTt7c3Ro4cidDQULp5itfTZDKhWLFiqF69OoKCguh3SDNEYutniRIl0KJFC6SnpyMhIYH+m+XLl6NZs2YIDAxEw4YNcf36dZw7d45W9DIyMrB+/XqUK1cOtWrVwoYNG7Bo0SKZRltcXBwSExNRv359jBgxQqbzJyIjIwORkZFo2LChgilTRHJyMooXL87U9xQhMnaGhoYyA9fdu3fDw8MDFSpUYG7mDx48QHh4OAghsudCRHZ2Njp06IDq1aujWLFiipYvi8WCwYMHY926dXB3d2fe17lz5+LLL7+E0WhEmTJlZAtrQkICunXrhrp168JkMmHbtm0yp+LGjRto3rw5atasifT0dPz222+yKkdKSgq++eYbNGzYEPfv38ewYcMUWb+LFy+iV69e9B34xz/+IbMLgoDFixfjyy+/BCFKkhfAGvgPHDgQjo6OikoHYN3A+vXrB09PT6ZOZmZmJj777DMEBwejQ4cOzGBt1KhRqF69Olq0aMEMZpYuXYqGDRuiSZMm3GCuefPmaNiwIfP9jI2NRdu2bdGgQQOmPTMzE3369EHjxo2ZdovFgvHjxyMiIoLrmP78889o06YNN2t87tw5dOnShfv3Dx8+xNChQ7lJq8zMTMyYMYPr0NWoUQOenp7c90WcIecRyYmOCo/52mQyoX///lTb0xYJCQkYO3YsmjRpwpRiev78OdavX4+IiAhK6iWFVqvFpUuXUK5cOXTo0EHhKIlMrDVr1kSvXr2YVbGUlBS0aNEC4eHhKFmypILB0mw2o0+fPvDy8kKNGjWYslTz589HkSJF0KFDB+Ys64kTJ6geMyFEQeyWnp6OmjVrokSJEtBoNMyk25gxY2jLL6sr5vr163RP6tu3L/Oei3tSoUKF0K9fP+zfv1/27C1duhQuLi7c+3Xw4EG0adOGW2mOjY3F0qVL0bJlS6Y9OTkZ27ZtQ8OGDZnPbF5eHn755RcMHDiQGQhZLBbs3r0bkydP5iZyT506hQkTJnDZvO/fv4+vv/6a27mUmpqKL774gtutY7FY0LNnT1U28E6dOqFx48aIjIxkvrtDhw6Fh4cH9zovXLgQrq6u3O84cOAAXF1duUnee/fuwcfHB02aNGHaU1JSEBQUBA8PDyZhoslkQq1ateDt7c3VgR4yZAg8PT3Rrl07pn3Tpk1wd3en4yK2ePnyJVxcXODo6Mj9nTVr1gQhVikkln8za9Ys+syHhoZiwYIFsuf+7Nmz8PPzQ/PmzZmcJUlJSWjXrh2qVq3KfB4MBgNmzZoFb29vJhuwIAhYtmwZunfvrqj4i9i3bx8mT56MKlWqMNfZ27dvY+HChShcuDCTkTgpKQnz58+Hj48PcyREr9dj9uzZCAoK4uqAfv/99wgJCeHO4W/evBnBwcFcDoVTp04hKCgIVatWZb53jx8/RmBgIDQaDQYMGKB4d81mM4KDg0GItZvpyy+/VEgudujQgSazmjdvjnXr1skSjGJ3iZ+fH8aMGYPbt2/LzvX06dMoVKgQpk+fzuwUSUxMxNdff83dK3NyclSTQM+ePUNiYuJ7T3r4MSD9k6DWmgRAdUMArM6SGqKiolQ/IzY2lulMA9aF6ObNmxg9erTCGdu8eTO8vLzg5+eHChUqcBdDqWRKx44dFb/XZDLRzFahQoUwfvx4xWIhbb2sWrWqImMrJa+pXLkyatSoIVvYpa2Xfn5+qFu3rqwiJwZf0gxc9erV6XmIDJZiltDX1xcBAQEyh6xKlSq09VGj0aBMmTKyc7x//76sNbJBgwaKayVtU61Tpw7zfixdupRWpFjBpth6Mnv2bMyZMwfz589X3Bez2Yzvv/9etSp97949ZsVNirlz5yoq8yISEhJgMBgwcOBAWZXh2rVr+OyzzxAYGEgXYtHxfPjwIQYNGgRnZ2dZe6ter4cgCIiJiaEVVSmbstFoRG5uLtLS0jBp0iR4eHigadOmslYbMQt57do1tGnTRvb3X331FbULgoCDBw+ia9eu9FkNDw+XLf4WiwW//fYbTVh07txZUUkRBIE+H1988QXXcQSAiRMnqjJFLlu2TJVZ+5dfflGViTlz5oyq/d69e1wdPcDaVs8T8wasVTO1NiSz2WxXgujP1HdLS0tTbfPMy8tTvf6iKLsaJk+ezK0kSQmDWK1ST548oZl3VqJq79699J0nhOD48eMy+6xZs2RazJUrV5bZp0yZomibkzptP/zwA0aMGCEb86hWrRq1nzp1CtOmTZPJbxFC6LqSk5ODZcuWKfSapYFIXFwcZs6cKeva+fHHH2XnefbsWVklpXXr1or7vm3bNioRRQhBeHi4wsFdvnw5Dh06xE1QGI1GbnJURGxsrF2CDx4rvAh7sjT29n57rZz2Wvv+U01De3Z772xsbCyOHz+OjRs3MtfHHTt2oFWrVihTpgyTZGvy5MlwcXGBn5+f4r3R6/Xo1asXfQ5sCcP0ej169uzJ7R4xm8346quvKNkcK4mzfv162uLp4OCgqLo9e/YM1atXp99hm8AQBAFLliyhLd7BwcEKkkqtVouePXuiRo0aKF68OEqVKoWrV6/K/s2pU6ewYcMG1TV6165dqvcrLi7OrjqDVDOchbt376ruYxaLxe57dfLkyf/Ibu8cjxw5ovrO7N69W/U6rV27VvW9nDt3riLIlGLmzJlYs2YNd79bv349VqxYwd1Pr127hmPHjnHXnuzsbLsznv8LLfYfA9IPGH+02K4gCMjLy7P74CclJaFgwYIICgrChg0bmC/ZzZs36YLepUsXphMhDSj79u2r+F5p6zIhSjZe2xkIT09PmRMjkiJJDynT7suXLxV22/bHGTNmyOysIF8kqiBELjwvxaBBg0AIUW2ruH//Pho1asStov4RUGspFpGSkiL7N6mpqVi9ejXCw8OpGHlubi70ej22bt0qIyGSOqsxMTHo1q2bbDZLWrm9fv062rVrJ7u+0vkzrVaLqVOn0sQGi4jk+vXrVBOXECJL0hgMBlqVENl/d+/eTe1iVUuv1+Pnn39GaGioLKEhdTLy8/OxYcMGDBs2jDqMts6UyWTC6dOnqZ3n2InX1t77+b+wAb3vyMrKUiWPOXfuHBwcHLj3asGCBSBEPn8lhdT5tmVBNhgMMsfYVu80JSUFxYsXl70/UmK1pKQkhV2aUMvLy5PNEYuHlBBk06ZNCpIy6RppNBrx3Xffyey2STmj0YgNGzbI5sVY7ZaCICA5ORlXrlzBL7/8gr17934Q78CLFy9UxzTssbV+CL/x30FiYiK3tffp06fo3r07s8VSnJUtUKAAc5wgPz8fw4YNUyRYpHbp6JJt0k4QBKxcuZImi1htty9evKAt2v7+/kz/5enTp5g+fToCAwPRp08f1ftoMpk+CFIZKbRaLfc3PXz4EBs3buTa79y5gw0bNnA/WxCE/2qW6I/49/AxIP2IfxkzZ87EypUruZlq4J/ziv3792cGrEajkW4YlSpVYlKB+/v703/TqFEjhQMvncUlhOD7779nnoN4BAYGylqQBEFQ6GXaMu3evXtXZmc5UlevXqV2KRmGFLm5uahWrRo8PT251wywBinr1q1TzVj+GcjKysKpU6doEKbT6bBt2za0a9eOzjs2aNAABoMBr1+/xvTp0xUER+KmfOrUKdlch22wfvXqVbRt21ZhF3UWMzIy8I9//AOFCxeW2aWyPDExMYpgVpoMEFuCxTY/QggiIiJkG2hmZiYWLVpE5zWDgoIUWdSkpCT84x//gI+PD5ydnZkSHwkJCZg5cyb8/f25EkZv377FsmXLMGvWLO4mnp2d/ZGI5AMEb14PsK5zVatW5TKFp6amUhmRI0eOKOx3796l1Z7g4GCFXSQjEg/bOdPo6GhZB4eXl5fM/vbtWwVJmK08lm1Q2qpVK8V57NmzR5ZgZFVtTCYTtmzZgtDQUISEhLz380yAte160aJFzNGZ2NhY9O7dG7NmzWL+7cWLF1G/fn3FjLmI3NxczJ49W5XszmKxcGeg/xvAm3kGrK2Ubdu25c5fi2MZvMBmw4YNcHNz43YExcbGonr16ggJCeEmB8+cOYOqVati5cqV3PO0WCw4efKkajfG+waz2YwHDx4o9pOMjAxs2LABLVu2VPhTRqMRe/bsQfPmzeHi4qLg3TCbzdi3bx+aNm0KV1dXZmt+ZmYmIiMjUbFiRcV4gQhBEHD9+nXs27fvP/yVH/Gh4WNA+jdBjZHVnsbS3413oUvv2bOnKuFIcnIyCLH25PNIRURHydnZmbnpdO3aVRZs2jo4x44dkzlarJkVKVFF48aNFXZBEGjbnJOTE9c5EJlTt23bxrQD1g22SJEifwjb2n8CMWu/adMmDBs2DNWqVYODgwMWLFiAgwcPonfv3gqJl2LFiuHMmTPo1auXQnaFEGu78+vXr2kl2PYoUqQIXr9+jW+//ZZpL1iwIJ49e4bZs2fLiBTEo1ChQnj79i1u3LihaFMkxKqPmJiYSKsxtnqnjo6ONJh88+YNJkyYoAh4pQQXN27cQP/+/WUtlVLH02w24+jRo+jUqRNt+bZlANTr9di7dy/at28PR0dHBAYGKlpM8/LysGfPHnTr1g2enp7MWR+9Xo+jR49i6NChzKAFsDpFt27dYkoX2d77j/hjYduuZ4urV6/SZAsLIsHU4cOHmfbFixeDEIKAgACmfcyYMfQZXbRokcK+aNEiamfNiMbGxsreBRYb4+bNm2lQWrRoUeZz9PDhQ0ocxKp8iTCbzdi+fTt3BvGvgtlsxp07d7B69WpZ9XUAOwAAIABJREFUFU2v12Pnzp1UX9q20iMGohqNBgEBAYpOiSdPnqBbt24gxMrQzfrejRs3omTJklztaovFgj179qBFixaqvoLJZLLbNv8hw2QyqQbk9+7dU91zb9++ze1OAKz3+rvvvuPOL4rncOjQoQ967TSZTLh27RoWL16Mdu3awdvbm643ubm52LVrFzp37kyTXx06dKC+W0JCAqZPny4j2pNWlTMyMrBkyRJZYss2CXD37l0MHz6ctuX3799fcY7i/h8aGgofHx/mLLrou0RGRiIqKuqPvEQf8R7gY0D6B4CX6f3999+5PeOzZ8/mZvbmz5+POXPmMAOXU6dO4aeffnqvNyFBEBRyN7Z48OABCFGyEUohBhW2xDQihg8fzs3qA//UhBWdKNYMwbJly+i/4TEKT5o0CYRY55p4EOV8bOdEbLFnzx7m8P+fBbPZjPz8fFy8eBFz5sxBu3btmDqbU6ZMkTG3Sg+NRoNjx47BbDbjwIEDMlIs8fj1118BWO+9LRsvIYRmmAVBwO7duxX2RYsWQRAE3Lhxg5LRSI+FCxciPj4enTt3lgWJUif68uXLMmkH6fHtt9/i0aNHGDJkCN10pUeXLl1gMpmwZ88eplZp1apVYTAYkJSUhHnz5im+p2jRonj9+jXN7o4cOVJGRe/o6EirnwaDAYcOHUK/fv1kUhFS5szMzEzs2LEDvXr1opUnW4ZUrVaLnTt34vPPP4efnx9atWqlICHR6XQ4duwYJkyYgAEDBjCdW4vFggcPHuDAgQOqbcQfskP2d4OVaJCiV69eXMZPs9mMsLAw+Pr6Mu16vZ629rJY0y0Wi4wZmrX+nDhxglZSpZ0IUkiDUh4pj06nQ58+fZjkSX83cnJycObMGcyePRutW7emQbgYxMfGxmLMmDGy9bFr1670ub9//z569eolqxZL9y+tVotvv/1Wtj6x5galchq2PBDiiIEoLcVj042Li8P48ePRsmVLuwzO9mZmP3TYW5cyMjLsXoP30Z9SW4vNZjMSEhJw9epV7Nu3D5GRkZg0aRIGDBiAFi1aoFq1apg/fz7mz5+P1q1by/YZjUaDzZs349ChQ+jbt69sdpsQaydGWloajh8/Lku4ikf9+vVhMpnw8OFDjBw5UvH3tWvXhslkgsFgwI4dOxSdbCVLlqSJ2bS0NKxevVomUaPRaGQEb1qtFrt378aQIUOoJFv9+vVliSCLxYKXL1/i6NGjWLJkCQYPHoz58+e/9yQ+HyHHx4D0P4DRaMSoUaO4g8w9evTgCqIvXboUZcuWZTqIr169gkajQXh4uIK4xmKxoFmzZihUqBBGjRola4sQBAErVqzA6NGjsWbNGkRHR8sYYVn4M5zMdxEdvnjxIpd9V0TFihVRvnx5bsA/ffp0EEJQo0YN5sJjNptp8MELasV2W3d3d1V5CNusoC0EQUDdunXfaU6Ed22MRqPqAnrp0iXcuXOH+ff5+flo27YtPD094eHhARcXF+o4ubu7Y/78+bKKsvSYPHkyvWcDBgxQ2KdNm0a/Z+/evYrqac+ePan93Llzigpn7dq1aXLl4cOHVHxePMqWLUvbv7VarYJkJSQkhNpNJhOtPohHUFAQdcru37+v0An19fVFZmYmYmNj8e233yp0SD08PBAfH4/k5GRMmTJFofXr4OCA69evw2Kx4IcfflC0eRPyT2mXc+fOISQkhBkwi7/PlmyLEGu7sngP5syZowi6mzdvToPNK1euoGHDhjJHoUqVKrRSl5mZialTp6Jhw4a0mu3v70/JM8S26pkzZ6J169bw9PREoUKFZK2DmZmZOH/+PFauXIlhw4YhPDxcUZ01m82Ij4/H+fPnsWXLFlWCpY9QR2pqqmoy69mzZwgMDOTaY2Nj4e7uzpVVSU9Pp0yRPCKntWvXghCCTz75hPs9q1atgkaj4SYSxTbAyMhIRdtubm4udz8ErEk9nvwWYJUyWrVqFZN0KCEhAY0bN0aVKlVQuXJluneEhoaiTZs2iIqKUjjOhBBMnz4dgJWUxPadK1myJF3PN2/erLA3adKErsXR0dGyBBQhRMYFkJKSoujsaN++vew37N27V5bsq1mzpiwpnZWVhXXr1tG5X1dXVwXLfmpqKo4fP445c+agU6dO+PTTT+2SMNnC3t79Lj6DvUDgXYJktZEgwH4QqdVqVbu5TCaT3fne/2fvu6Oiutb299BRFFAjIhZssTc08FOjYhdRATsoAhYExYYN0RgRayxgA7GhiQ2MBcSOvYEoooAoCoIgIqj0MsPMeX5/zHf2nTPnnCHf/W7JzfVda69k+Q4zp+zy1ue5ceOGqK6qqopHL6Qq6enpCAgIEGxHAoDo6GhMmDABR44cEUTp/vnnn9GwYUO0b9+eYkvMmDEDy5cvx6ZNmyjqvvowMzPDlStXKBWJ+tizZw8+fvwIb29vXrWTvr4+nj59ivz8fCxcuJC3ZgwNDfHq1StUVlbCz8+PN+d1dHToGj506BCvh52Qv/XKZ2RkCAa32R51hmHg7+/P62Fv27YttWuTk5NhbW3N4y53dXWFTCaDXC6Hn58f7O3tYWtrC2tra3Tu3BmWlpaYMWMGiouLcevWLcybN4+2okVGRuLWrVtISUnB169fUVlZicWLFyMsLAxPnz4VnFOhoaHYs2ePKMDU3bt3sXPnTlFf4d27dzh27JioDfr161c8e/ZMdF39EWwQQDnnX7x4USsQ1r9Lvjmkf6dUVlbCzs4ONjY2gvqKigrUqVNHtL/k+PHjIETZ9yY0kVgSbQcHB15JUEZGBl2Ao0eP5mx4MpkM06ZNowvT0dGRGrIMwyA6OhqrV6/GxIkT0a1bN1GnkM1kaSqHefv2rUbAj5SUFNHy1MzMzFrRDLt27SrKMQr8jbZBE4Jbp06dYGhoKOqYS6VS6Ovri4IRAcpnYWlpiSdPnmgst71586ZGxDyGYUT7JgDle3VzcxM9rNnMYps2bbBs2TI8evSIs0GFhobyNndra2satFBFRmbHokWL6PxjSwPVHSH2ns+cOcP5Xi0tLTRq1Ig+2+fPn9MAQLdu3eDn5weJRILHjx8DUEaq2b7T5s2bIygoCIT8rVSWYRjKBVi3bl1qwLHZVwDw8fGh18A6lqooqEePHuXdg6rR8Pz5c8rByw5VLt+qqip8//33HL26ka/O9atOYs+ubXYMGjSIM2/S0tI4B2j37t05a7yyspJTcsxGrFVFNbjQpEkT3rxTfdempqa83tcLFy5Qfd26dfHgwQOOPjU1lT5fPT09Xu90WVkZzcpJJBLBiogtW7agW7duaNWqFRYuXMjbx549e4Zly5Zhw4YNOHfuHO/vq6qqcP78eR79kKpo0j158gTr168XNWwzMzOxevXqWktua5M/YgiIUd+wIpVKRUnNWdHEhQwoe/uFuP4A5TXeu3cPurq6gj2LNTU1qKmpQffu3QW5SKVSKaqrq9G/f3+Eh4fz1kRNTQ0KCwthaWlJsx+qz0Uul+PevXto2LChYFk5izSuo6ODn3/+WdDoU62I6dChA3x9fXH9+nX6flXRV9kxf/58Whmjrl+8eDHnGtUNeHXkT5a6gZ3z6qicERERHL362fj06VNOdcazZ884+tzcXBo0IISPtl5WVsYJxgnR16hyV3bv3p3njBYWFqJly5YwNjZG48aNMWTIEJ5Ttn79eri6uuLUqVOCAfP3799j6tSpoq1Fcrkcy5Yt0+jsnT9/XrCqiRWZTIaJEyeKnrdVVVXw8fERtT8qKytx8uRJDkidqigUCjx+/BidO3cWRV9l7Sz1vZGVly9fQldXF4sWLRI8s+Pi4mBoaIgmTZogLCyM95nbt2/T4K5EIoGNjQ0CAwMpJUhsbCwv+EuIMkB7+vRp3Lx5k+eIWVlZ0SRGXFwcry1F1R5NT0/nVUup8q6WlJRw5iMh3LYnhmGoncoONsDDyrp16zh69eqLu3fvcnrcBwwYwHlORUVFnAB2o0aNeAG1KVOm8GwaVbtIla+VEKXTvWvXLrr2s7KyeM9BIpFgxowZlFVAFfNCX18f1tbWmDt3Lk6cOAG5XM6ptOvatStWrlyJhw8f0vn74MED6OjoQCKRwNbWFvv27eOszezsbDRs2BB6enoYM2YMjh49yll7xcXFsLCwQIMGDeDk5IRdu3YhOTmZ3kNRURFatWqFVq1aoW/fvpg0aRInwPn161cMHz4cBgYGmDBhQq3n0b9Lvjmk/weJiYkR3VS/fPmCc+fOiUZ8Hz9+jKCgIFGD6uTJk3BxcRFt+t+9ezc6d+4sCJetUCiwePFi1K1bl0cfU1xcjM2bN9PIlbOzM+/vX716RTcac3NzUaLzPn36wNzcXPQePT090a9fP1FAgClTpmDhwoWYM2eOYGSoV69eOH78OFxcXAQPhTFjxqBfv35wdnamv6F6uERFRWHUqFHo1asXfHx8UF1dzTHGPn78iKKiInTs2BGjRo1CUlISdu7cyblfhmHw/v172NjYYP/+/YK8k4CSe23mzJmi3Gn379+HlZUVGjduLFhiVVVVRUGcxowZI/gZdRAf9gBiy75UnRAdHR0EBgZyNvcbN25wMqdeXl6ce83OzoapqSnmz5+Phg0bwtzcnDM/KyoqYGVlhWnTpqGqqgpWVlYc1Fo2wzpo0CAkJyfj1atX8Pb25txDUFAQLCwscPbsWVRVVWH8+PGca7h06RKMjY1x4cIFJCYmwtbWlqN/8+YNGjdujEOHDsHX1xf9+/fn6EtLS9G7d2/Mnz8fjRs35hGCKxQKTJs2jUZmu3fvzjMUtm3bRhGc27Zty3MUrl+/jhYtWkBPTw8WFha8vtDMzExYWlrC2NgYjRo14vXCVFZWwsrKCt999x3q16/PO2AZhsHkyZNhbm6OunXrCiJVbty4EU2bNkWdOnUEy0GvXLkCCwsLGBoaCmalsrOz0aZNGxgaGgoGfWQyGfr164c6deqIBnxYPsLo6GhB/Z49e1CnTh0cPnxYcA+5c+cO6tati1WrVglmEQoKClC/fn2MHTuWh67MSrt27TB37lxBw5ntDxfbnzZv3gxC+D2CrDAMg5CQENFS2urqapw/fx7jxo0TDSI9e/YM3t7e8PPzE9RnZmZiwoQJmDx5suA9srySCxYsEOTHrKqqgr+/P1xcXNChQwde/yeLWNqlSxdMmTIFXbt25aH53rp1C+3bt8fEiRMhkUjg6OjIWTO5ubno27cvbGxsaIBI9VySy+WYOnUqPVNYJG5V2bNnDzU827RpwwsQJiYmcva1bt268Rw+VfJ6dhgbG8PT0xP5+fkYNGgQ3dtat27N6wv09/enVGKzZ8/mzcnz589TvIBFixbx7iElJQU2NjaoX7++YFlzYWEhhg4divbt2wueq1KpFK6urujZsyenqkRV1q1bhx49emDy5MmC+jNnzqBDhw6C/MaA8uy2tLRE9+7dBat1ZDIZWrVqBT09Paxdu1YwWKMKSNe9e3cePy6LXl+3bl1s2LCBV8HEvmtTU1PB3sy7d+/C0NAQOjo6uHTpEk+fnZ2NZs2agRBudQ4r5eXl6NatG4yMjNC5c2feWckwDCZOnIh69epBIpEIgkr98ssvdD4JIeTevHmTVqAYGxvz9pDPnz9z5uOwYcN4pfAsJRQ7OnbsiOjoaPpbYhnMunXrYtGiRTTgzo4GDRogKCiIBmuSk5M5ztzkyZM5Z1VJSQk9QwhRtnyoB4kGDx5Me0NdXV15z2Hp0qUUHXvQoEG8DN3JkyfRrl07SCQSdOrUiTefnj17hlatWqF+/fpo0aIFz8778uULOnbsiIYNGwr2jSoUCgwaNAimpqYwNDQUrCKZN28eDZ5u2LCBdw/79++n1Q2dOnXiBTESEhI4z3nUqFGcM1cqlfLeUceOHREcHEzfuXpVFmuDOTs7IycnB66urjy9trY2xo4di9evXyM4OJin19XVxeLFi1FSUoIHDx5wdKamppg1axadl5WVlbSyy8HBgWczMAwDR0dHTJky5U9dwv/NIf2TSnV1tcaJo1AoBBE/WWH5wDR9/8GDB3klKampqZg+fTrGjh2LoUOHYvz48YIRxLVr19LF4e/vz9sEFAoFpW1p3bq14LX07duXs5mqR+4HDRpE9T/++COcnJw4G+7gwYPpRmNhYYEffvgBR48epfo9e/ZAT0+PRqU7derEMSQKCwthYmJCy06MjIx4Rt+KFSs4PYXqvVEVFRXw9PSk92pkZMR7FllZWZwern379vGeRWpqKge1tn///jwjOzIyEjo6OhgwYAA2btyIxMREzgFRXl4OLy8vdOrUSZRT6+PHj2jUqBHc3d0Fyz/Y0qHBgwcLOirFxcXIz89HRkYGj5ssLS0NK1asQLt27WiUly2rKigowObNm9G6dWv07NmTRujY95mfn4+AgAA0adIEHh4eALg8kTU1NYiIiICNjQ1WrlwJQGnYqBrx+fn5WLNmDQIDA8EwDDw8PHjO2ps3bxAdHY3KykqYmpoKcvmWl5fTLKUY2EV1dTX69Okjyp8mk8ng4OAgClQjl8sxe/Zs0Yy5QqHA6tWrRZEG2bJITRn3iIgI0d8HlA6hpuqCtLQ0jai/Hz9+FHUUAWVGRxOKpkwm01gloVAoNGZAGYYRLYcDlJkcMWcZUB7ip06d0vgdx48fFy2DrampoWBmQqjY7969o73G6uWZgLL0unfv3nTNq5dEX7p0idNPrZ65jI2Nxa5duzhldap7S1paGmJjYzmGsbm5OXUGa2pq8PHjR55hfPz4cU6G8uLFixy9vb095zpKS0s5GX1dXV1eFlQ9U6LeA5aTk0PRhlUNNn9/f2rkshRc5ubm8Pb2xtWrVznXWVZWBgsLC/j4+AieWTKZDCEhIXBxcRHNvFVXV+OHH34QbRNhGAaenp6CJZas7N27VyO42IULFzSuixs3bmistLl586bGMtxr165pbB05f/68IAIqKwcPHsT27dtFS7vXr1+PHj16YMCAARgzZgzWrFlDnUKGYeDr68uZC6pnskKhoFRIhCjB6FT3YIZhcOrUKY6jpb6HPXv2jMNRrt5bX1xczKFLsrCw4DiLDMPw5rx64D4qKoqjNzMz47xTNtOs+pk2bdpwbLKFCxcKOpwDBgxAfHw8UlJSaAa0WbNmmDt3Li5fvkznXklJCebMmQM9PT0sXbpUkHM5OTlZ1BFjn4WTkxOmTZsmeN6Xl5fj7NmzopliuVyOoqIiNGjQQLTMs7q6Gj179hRtOZDJZBgzZowol2lNTQ2cnZ15PMyq1+Dm5iZ61snlcsyYMUPQrmK/39vbG97e3oKBfjajb2VlJVqiHRgYCH19fUydOhV3797lPWuWa97U1BRTp05FREQEp/Lm3r17IETZ/sPaMLGxsfR68vLyUK9ePTRs2BCTJ0/GwYMHOXuAQqGAjY0NXFxccOHCBcEKkrCwMEF7hpX8/Pw/tTMKfHNIv8nfIY8ePYKhoSEmTZqEa9euCW50Dx8+pBuwt7e3YImA6oY+a9Ys3iJX5ZckhI9gu3r1ao6+efPmnIX68uVL3mGgvimqouwSwi85yc/P5/QcCqEm3rx5k9NfJGRER0dH04b8tm3b8gyikpISxMfHIzw8HMuXL8eYMWMwYcIETiYhJSWlVgoANvOoSfz9/WtF+lU9fBmGQWJiIgIDA2FjY4OePXtSI/7Tp0/YuXMnx7AOCQmhf3fnzh04OzvT56Ovr88B83r69Cnc3Nxo0MDCwoKzkRcXF2Pbtm302XXs2JEXhX3+/Dnc3d2hp6eHVq1a0YOVfXYKhQJXr16Fvb09TExMaEmTqgPAouaOHTuWRu3VS+ZY0CXWSRNz+tlnW1t/Um1o2kIGiKrU9p7/3WjOfxXR1JZQUFCA5s2bi/ItXrx4ERKJBNbW1oL6ZcuW0XWjDqomlUoxcOBAqtfX1+fskZ8+feL1Ky9dupTqMzIyaKZJdbDOVHZ2NocWiR0sjY1CoRBExdbS0qJzNzc3lwPSww5HR0d6HY8ePRIEG3N0dKRz9OTJk5g6darg2LhxI6RSKQ4fPoy4uDjRPiqpVMrhORaSt2/f1lquVhvuQm0gQrWtu786OJhMJkNmZiZu3ryJw4cPY82aNXR9MAyD9PR0hIWFYcqUKTAzM0ODBg0o0r5cLseVK1fg4eFBsQhMTExof7pcLkdYWBjnvCHkb32JbKBOncpowoQJ9LnHxMRwOHEJUWaz2H09Pz8fw4cP5/UMt2zZklK7hIaGomfPnjAzM+P0OBoZGSEqKgolJSVwdXXFzJkz4efnh+3bt+Po0aO4dOkSEhISkJ2djatXryIgIIAGb4Vk+/btGnvzs7KyNAYlAWVvsqY5/+7dO40BCgAae78/ffokukfK5XLk5+fXiv6uKQADQBBxV1VqO0vFQNhYefr0qca+56tXr2oM8vz++++4c+eOqMN37do1XLhwQbQ95O3bt3jy5InoNchkMtHS8r+SfHNIv8n/ShiGQVRUVK1ACcuXL4eOjo4oLyPDMHTD79evn2DER7VfRp1DEuD3BgQHB/N+Q7Wp3szMjGcsqFPDCNFqsKV97MEmJKrXItZzUlZWhqVLl0JbWxu///674GfU5Z8FOqUqMpkMSUlJOHz4MHx8fPDzzz+jpKQE0dHR8PT05PDBmpmZ4fXr1zh16hTs7e05kWxCCCZOnIivX79i165dlAJCdWzfvl0jmi0bDc/MzMTChQt56IDss1UoFLhw4QLNULFDNeNXWlqK3bt30/JbIaNfHTV35syZvOf18eNHbN26FZ07d8b3338vmFErLS3FsWPHMG7cONFIMcMwePr0aa2O6jf5z5KEhASNmeSAgABYWloK6uRyOUW3XrduHU//+fNnjvGsnplLT0/ngHA5ODjw9Kp0DYQQTibi69evPBTMNm3aUD3DMDh8+DAP3GTjxo30M5WVldixYwePl1jVOWQYBqmpqQgKCoKdnR3NDM2fP/8/xkGTSqWCzmZ5eTnOnTsnSsn0/v17bN26VTTjyAa6anN0/4rCMAxevnwpSKtSXV2NqKgoODs7o3///rwAXFJSEubPnw9TU1OYmZlxAgksN+iUKVNosFMVS4B95suXL6fOa9OmTXktKjdv3sTatWsxePBgGBoaomPHjjzbRyaTIScnB/Hx8Th37hxCQkI0Vnb8J0hFRQXu37+PoKAgBAUFcRylwsJCREREwNPTE99//z1v3n/58gUnTpygrTFCVTAFBQU4duwY5s+fr7HaoLCwsFZwq2/y15FvDuk3+YcLwzDo16+fRkCiwsJCmtUU27xZcCZdXV1BrtL4+Hhq/IjRujg7O9PPzJ8/n6eXy+WcpnmhKFhVVRU9tDw9PUXvaePGjSCEcEqUhCQpKYnXz/GvkqqqKjx+/Bj79u2Dp6cnevfuzQHa6NKlC0aMGCHYr2VgYIB9+/bxUGjZ0apVK9y+fVsQWY8QgoEDB+Ls2bM026k+pk6divv372P8+PE8qHlCCObNm4fy8nLs3buXBzxECKGlvunp6ViwYAEPTXfYsGFgGAYKhQKxsbGYMGECB2XQ0tKSlhhXV1fj9OnTHKdbT0+PU6LK8reNGzeOPq9t27Zxnnd1dTUuX74Mb29vNGvWDEOGDOFFqxmGQXJyMnbs2IHp06eLRoMrKytx9+7d/4pI6X+aaIquKxQK0Z5AQOkUtm3bltdvzUpaWhrNFgn1C7PgKYQo2xKE/l7VWVR1JgHlnqCO2KmelUlPT+dkpdq2bcvbv8rLy7F582baAqGOEqv+m7GxsVi+fLlo2fu/WhiG4azN9+/fIzIyEr6+vujbty/WrFlD7/nDhw8ICwuDvb099PX1YWVlxSlB/vTpE/bu3UuDbkLgOqmpqVi9ejXatm0r2mNcXl6O8+fPIyQk5D/Gcf9nSHl5uWiGqqqqCidOnBClmvv8+TN27tyJvn37CmbKGIZBfHw8fH194erqKprlkkqlePjwoWjp6Z9ZGIbB169fkZiYiHPnziE4OBiLFi2Ck5MTfH19ERcXh7CwMMyaNQvdu3enZ56VlRVyc3Nx5coVLFu2DD179uTsE4cOHQLDMHj27Bk2bNiAfv360bNbX1+flpDK5XI8fPgQa9aswQ8//ACJRAJdXV1ef+/Hjx8RERGBuXPnonPnzvD19RV8pzKZDMnJyTh//vyfvgz1m/xx+Yc7pISQw4SQAkJIisq/NSCEXCeEvPmf/5r+ke/65pD+Z0pZWVmtCLrPnz+HoaGhaNkj8Lemf7ZnUF2+fv1KN8a1a9cKfkYVdVAsc8nSx7Rr1070WliEWzHUPuBv/UViFDOqolAo/lccWbVR6WRmZiI8PBy7d+/Gpk2bsGrVKixcuBAzZ87E5MmTYW9vj86dO/Ng3lXH6NGjkZqayqMnYAeLZvv27Vte1kVXVxcJCQkAlAaAusNoZGSEd+/egWEYXL16lYdq17hxYxQWFuL69etwcHDgQb03a9YM+fn5cHNz4+kI+VuPz5gxYwSv3cjICImJidi6dSsFLlEdEokEd+7cQUJCAubNm8fpUWJHUFAQqqqqcPbsWUyePJmHcMgCNBUWFuLo0aMYP348J8Pbtm1b2sv04cMHHD16FNOmTaMOvKGhIacHpLCwEFFRUVi2bBn69OkDXV1dBAUFcd67TCbDs2fPcOjQIcydOxebNm0SnFcymQwvX76slQ/zm/xzpKioSON6T0lJwfTp00X1V69ehba2tmhPcVRUFLS0tKCvry/4O8nJyTSQNHHiRJ6eBcJj56oq2iYrMpkMK1eupOtPLOBYUlKCdevWwdjYmAMYVZtDpcmwZBhGIxpySUkJsrOzUVZWJvg7hYWFSEhIQHR0NPbv34+AgAB4eXnBwcEB1tbWaNasGYYOHYr169dj/PjxnKoQQpR9is+ePUNgYCCPlsrc3Bw5OTkoLi5GeHg4hg8fLoocmpmZiY0bN6Jbt25Ub2try7n3nJwchIZdYFSfAAAgAElEQVSGYtSoUTAwMKDfr/48srKyEBkZiaVLl4oCc32TvwnDMBxcBqF5olAoaFBCJpNpnJNlZWUaW2iys7N5701VHjx4gHv37on+xqlTp7B//35cu3YN6enpvEzhqVOnsHDhQvj4+MDb2xtz5szBrFmz4OHhgenTp6N///5o2rQpGjduzAvOqp67QsFn8j8B5h9//FGQt5sQJbr8rFmzBGnQCFH2sx85cgSTJ08WPE+PHDmCnJwcHDt2DLNnz+ZUMhFC4ObmBoVCgc+fP+PGjRvYsWMH3Nzc0KNHD+jp6aF+/fq0MoVhGHz58gUpKSm4du0ajhw5go0bN2LLli3/ERnW/+Zgk6r8MxzSAYQQKzWH9BdCiN///L8fIWTLH/muv5JDyjCM6MJ49OiR6IRkKTOEpLa6/z+zXL58GadOndL4mQULFqBly5Ya6RAaNWqEOnXqiEZPMzIyQAhBixYtRA3CzMxMEEJqpX758ccfKYm6mNTU1ODEiROiOk28aE+fPhV9pywQg62tLXx8fBAWFoaHDx/SA1EqlfL6YVWHtrY2Nm3ahJiYGMHso6OjI6RSKbKysmgJoepg4eJzcnIES23ZcunPnz9j6NChPP3BgwcBKKPZU6dO5elPnz5N75MFL1EdqkinQvQ07N9nZWXB0dGRpw8JCcHnz58RGBjIA08hREnt8uXLF8ybN0/wALa3t6c8pEKHe/v27VFSUoKnT58KHtDGxsZIS0tDeXm54PVpaWlRapWDBw+iQ4cOou8gLS0Nc+bM4WW3x40bB6lUCqlUiqNHj8LPzw8ODg5o3749dHR00KVLF9pr8+bNG1y5cgUHDhzAmjVr4OHhgQkTJtByYhYwKDc3FykpKbh//z5iYmL+lATyfxWprc9pz549GqlfWNonsX6spKQkmJqaCtK6sLJlyxZIJBLR1oSMjAzcunULFhYWgg60aj/b169fsXfvXmpwZ2Rk8NoqVIVFzlZHK2XF1dUVffv2RWBgIBISEniAbmz2RldXF2ZmZujYsSP69euH0aNHw9HRESYmJqL7o7u7O48fmR1eXl6IjY0VXNf6+vqIj4/Hy5cveRQZhCgDZXl5eaioqBDcn5s0aUIBsSIiIngZKAMDAwr2V1BQgHXr1mH06NGcjLerqyvNRD98+BDHjh1DcHAwVq1ahTlz5mD8+PH0TCouLkZaWhq+fPkieh7m5eVpNJCLi4tr7V/X5IgByuxzbTRHtQXPYmNjNTqMLG+3mGRlZWH9+vWi91pZWQlbW1vRCq7Kykq0bNkSv//+u2hmtk6dOpg2bRqP4gdQrgcdHR0YGxtj/PjxOHDgAId3/tWrV7ygZ9OmTdG3b1+4uLhg8eLFonOWHargTqpDIpFgy5YtCA4OFrQHevbsiY8fP2L9+vWC+jlz5iAxMVHQFiCEYP369bh79y4PaZgda9aswYcPH3jtAuwYO3YsZDIZ1qxZI6hv0KABEhISkJycjI4dO/Ko3Agh6Nu3L3Jzc+Hl5YV+/fqhT58+sLa2Ru/evWFlZYUePXrA3d0dJ06cwLhx4+Dt7Y21a9ciNDQUZ8+exYMHD/D27Vt8+PABLi4uWLNmDc6cOYO3b9/y1k5gYCBWrFiB2NhYwbURGxsLV1dXXLhwQdAP+PLlC8aMGYPjx48LrguFQgEvLy9ERESIlvbv2rUL9+/fF13XDx48EESj/zMJ+WeU7BJCLAnXIX1NCDH/n/83J4S8/iPf82d3SMPDw9GqVSv06dMHTk5O8Pb25vQSsSApnTt3xqhRo3ggJSkpKRgxYoRg7xCgjLDZ2dmJ/n5AQACHdkNVsrKysGDBAo0omDKZTJSol5XaygM1RZ8UCoXoZv9HDNsVK1ZoRMkEgD59+ghC9LPCMAxatmwpipTJyuDBg7Fnzx6NWYzHjx/jl19+0fhbmpzs/Px8jRQRcXFx0NLSgqurq2C/0alTpwQ355YtW2L06NHw8PAQzB5aWlri0aNHCAkJEXSmWF6qyMhImtHT0tKizg4Li//gwQOa2dTX16dQ5g4ODmAYBu/evaNGma6uLi1hHj16NBiGQXl5OeUZZQ0pQpSZRfb5ubu7Uz1b2qta7rhz507e9Ts6OtJ5Fhsby+t3s7W1pe81MzOTZzh26dKFHiJSqRS2trYcvSoyKcAH06pTpw4HXfHy5cucQ1xLS4tDtSHEe6baa11dXY1evXpx9EuXLqX3yDAMB32VEGXWS7XccO/evRx9v379OPvP7du3OaAdbdq04SB/vn37lmOAGxsbc7JzNTU1mDZtGtq3b48OHTqgU6dOCAkJ4ayf48ePw9PTE6tXr8bu3bt5vbVv377FgQMH8OzZM0HQDYVCgbt372pck7X1atUWHf9XRaZrq4b4I/2Dubm5HEAwdXn48CFWrlwpihSZmZmJ4OBgmJqa8rKNbPZozpw5iIyMRJMmTTjltnK5HOXl5fj+++9RUVGBL1++YPr06TQgJpfLUVhYCH19fcEgqkKhwNOnT0GIkhZG/XkwDEP5e01NTbFt2zbeu1Pt5SdEmd1xdXXFiRMn8PnzZ/j7+4sa5pMnT+ZwGLOjXr16NBC0fft2nn7GjBn0WtkqGdVx/Phxen1PnjzhGMZaWlqcPtpPnz5xMq/a2tqcLLMqajM71M8T9WDd1KlTOe/p0aNHnHWtr6/PyZ5KpVKandXR0YG5uTm6d++O0NBQep/bt29Hs2bNMGPGDJw6dYrXM/n161e0aNECmzdvFsxaKxQKuLu7Y9GiRaL2w40bN9CzZ0/R4IlUKkXLli05HNSqUllZCS8vL4wfP15w7ygvL8epU6fQoEEDwSqsmpoaSjU0b948wdLylJQUGBsbo2nTpoLVVffv36fo0qNGjeJVhV2/fp0DGjZ48GBcvHiRPucrV64IBh7ZUtWNGzcK6tUdM6F/b9OmDcLDwylVk+owNDTE2bNnkZubyzmP2dGjRw98+fIFlZWVGDlyJE/v4OBAn9fcuXN5ejc3N7qvhoeH8/TTpk2j+hcvXvACRba2tvQ8Lisr452FjRs35oDICaEZz5w5k+4fV65c4dlFOjo6WLduHWQyGfLz8wVB1wghmDJlClJTU3lBdCMjI/Tt2xfe3t44deoUjhw5wnm+w4cPx9atW5GUlASFQoG0tDT6royNjeHu7o5Lly7RBEVeXh61O+rVq4eZM2dy0HzLy8vh4eEBQgilnVI9GxmGwfLly0GIMsjl7e2N69evc9ZGQEAAJBIJunXrRjlUawsc/auF/Isc0mI1fdEf+Z4/u0OqyvvYq1cvHoXCzZs3oa+vDxcXF0HD6PXr1+jVq5do2ceTJ084RMbqcunSJQ7Br7r88ssvWLt2raA+NjYW7du3h4uLi+DfMgyDXbt28Xge1a9/xIgRonDgT548ga+vr2iP0JUrVxAVFYX9+/cLPp8DBw4gJycHe/bsQXp6Ou/QyMnJwcyZM7Fz505cvHgRZWVlHPoF9rrt7e2xZMkSFBQUCPKesRGwsLAwwV4euVyOgwcPYvPmzbC1tRW8lzt37tAovNAhnZ+fT0tSnJ2dBQ9A1WintrY2ZsyYwenlEjoctLS0MH78eNy9exdLliwRNMTY6/n111/pYcUSZqvyUj158gTa2tro2rUrEhIS0LdvX/Tp04ceDvn5+TAzM6O0Lnl5eWjRogXNaLBUKGZmZrh37x4AwNramr4ThmEwc+ZMGBoaIiIiAjKZDM2bN+e8s5CQEBCi7HO7c+cOTE1NOU7H3bt3oauri6lTp2LRokUwNjbm9Fzm5OSgSZMm+OGHH9CmTRvUqVMHGRkZVF9VVQVra2tavqirq8uLXs+aNYsadRKJhGfg79u3DxKJhB5y6hnx+Ph4aGlpUadUPStUWFiIhg0b0r9XL0lXKBSwtram73DOnDm8Nejl5cU5NNWDHIcOHaL60aNH86Kuz58/5xgA6hUG1dXVtG+xd+/enGfICms8t2vXjodIDPzNeG7YsCGCgoJ4a/zKlSv0GTs5OfH6Fj98+AAjIyO0aNECP/30Ey+6yzAMunbtimnTpokG1ry9vbF9+3ZBHaAEIxML6gHKIJFYxQOg3AOFHCxW8vLyKDCIkJSUlGD9+vVwcXERRHeVyWTYs2cPAgMDBTOSLMicv78/WrZsiZSUFJ6RkZSUBCcnJzg4OMDV1RVxcXEcXsXCwkIMGzYMEydOhK6uLj59+oQ7d+5QZEy5XA4XFxdK07V+/Xr62+zesH79eupsNW/enOfEnDt3jtMuMHHiRE4m4c2bN7y9y9LSEidOnKDPVigLompgCvWuW1tbU2eCNejY0a5dOw42QVBQEM9wVt2nb968SecrIUq6M1XJysqCsbEx3Ts2bdrE0VdWVqJLly400CcU3JwyZQp9Tj///DNPv2PHDvr7QueIKrq9paUlzxmrqqrivId+/frxnC3VvYc9i3x9famdsmDBAqqrX78+/Pz8OHv4sWPH6Ltq3bo1r0/w9evXNGj43Xff8Uq/KysrYWlpCR0dHWhpafGA6AAlVyobXHVwcODtLcuWLaPZRWNjY14w7OTJk5znMGHCBM58VEfo19HR4XCUS6VSXuDT0NAQmzdvpk6Aemk3Ozp27IgDBw7w5uMfHRKJBFOmTOE4QaqDxVrIz8/nVfuYm5vTzLNMJkO7du2go6ND35c6f62TkxMkEgm1F/r06cM5SwIDA6kdQogSJ0K1CuzSpUuc3x8wYADnXWVlZXFKhtXtYZlMxgF1s7Cw4FWRqfa/a2trY/fu3ZzzUr2iqnv37pwz//bt27xnOHToUPqcKioqBJ9z586dERoairKyMkEAR/Z6XF1dMWnSJEG9qakpZsyYIRgsY9dPQEAAfv/9d0F9q1at8NNPP1H6H/XRoEEDuLu74/Xr17ySaG1tbYwePVoUhPHfIeTP5pASQjwJIU8IIU9atGjxL3gEf78UFxfDysoKkZGRok6bKhGykPwz69vlcrnGkpaamhpRSPGIiAjMnDkTa9asES3PYUuQxAy+sLAwEKLM4AmRU7MRcUKUWTJ16O4TJ07QQ6d3795wd3fn6C9evIhWrVrBwMAAZmZm+O677zgR17dv32LYsGE0I9aoUSPs2bOH6hmGwdatW+Hm5kY3evVStffv3+PkyZN006xbty7PCCgvL4eDgwO9F3VyekDppKgegOo8oAzDcL5D9SCcPXs23r9/j8uXL1Ojy8TEBEuXLuUEA169ekWjZHXq1KGAA6zI5XIcO3YMMpkM33//PaZNm8abH7GxsfRAWbFiBS8DlZSUhNLSUmqMqjtz2dnZOHnyJDZu3IiqqiqOs8gwDB49eoRp06ZR3jfVzCLDMLh16xbGjBmDuLg4VFdX8/hrX79+jZkzZ+L9+/e4dOkS9u/fz9HX1NQgJCQEeXl58Pb2FixxzMjIwJs3b2BhYcEDeAGUBlFycjKMjY15Rid7nc+fP8f3338vCJQFKAFL+vfvL0hnBCjn5rhx4wTJyAGlMzZ79mxMnTpV0NkpKirC8uXLBd8hoDzIN23aBHd3d9E94MCBA5g9e7ZoGXl0dDTmz58vukc9fvwYy5YtE83uZWVlwd/fX7T3r7i4GD/99JNov3lVVRUCAgJw8eJFQQocmUyGdevWYe3atdi/fz/vPhQKBbZs2QJHR0fBHjuGYbB//378+OOPokG1HTt2oH379oLvQKFQUOA1IdqXsrIy2tM8atQonp6do+xaV+fhy8rKwqFDh+i+od7jXlpaipcvX3Iy2Xv37uXdo2pftYmJCWQyGWfOqWcGN2zYwPmOhIQETtbNyMiI44DIZDJOTyQhSgAx1X1y27ZtvCzFjz/+SINZL168EAQqY/f+27dvY968eZx/19PTg729PQ4cOIBPnz4hOjqaEtQ3b96c48wCyr1jxYoVIITAzs6OF+CQSqW4ceMGCFE6zELr5tmzZ/jxxx/h6OgoOCfevHkDHx8fjB49WlCfl5eHzZs306oSdSkuLsbu3bsxceJEwb+vrq7Gzp07MXnyZMHrYxgG27Ztg52dnWjp89atW9GhQwecP39e8BrYMs7BgwcjJCSEx7HLci6yo2nTphg5ciTFEIiJieG9Qy8vL+poJCQkcIILOjo6lCoMUNKQsLze7Ni0aRO91tLSUvqe2TFq1ChqpzAMA3t7e47eyMiIBkkBCJaCDhw4kO5VZ8+eFawmcnZ2phgZ6ga+qqNy//59ujeIjXr16gn2Vn7//fdYuXIljh8/zgFl1NLSwtSpUzkUOWvXrqXUUC1btuQFT0+cOIELFy6AEKUjph6sevDgAdLT09GtWzd069aNF0h6//49EhISMHnyZHTo0IEXuJRKpbh27Rp+/PFHtGvXTrB16tatW7C1tUX79u0F52R8fDycnJzQvn17waBccnIyXFxc0KpVK0F7NSMjA25ubmjYsKFgdQjLtaytrY01a9bwzony8nLqEFpZWQkmUFauXEnfgZOTE27evMlZO6oVSTo6OhgxYgQOHDhAn+eZM2co8Bw7OnXqhAULFiAqKgqXL1/mgT1KJBJ07doVXl5eCA4O5gU4DAwMMHDgQKxatQoxMTEcp7dBgwaYPHkywsPDqQ3GVpdZWVkhODhYI7rxv0v+VQ7pX7JkVyaT1cpp9leVuLg4WFtbCzqarLCgRAsXLhQ8+E6ePEkXkJDhn5SUxFmA6r9VVVXFiVJ27dqV9x3jxo3jfMfVq1c5+tjYWI7eycmJ9xvqmcnk5GTOZ86fP8/ZTExNTTlRPrlcjpUrV3LI4wnhZr6Ki4sxevRoTJw4Eb6+vggODsaZM2fw+PFjfPz4EQqFAhkZGejQoQNCQkIEqUcAZVlvt27dBFGJVWX79u218uWp6hmGwZs3bxAWFobJkyfD0dGRRkorKysRFRUFNzc3NGjQAHp6epyo27t377BhwwZavtS/f3+OMZWbm4sNGzbQSOjy5cs511FVVYXjx4/Tg3fz5s0AlMYZ+/wyMzOxatUqNG3aFL6+vgCUB5lqScvTp0/h4+ODcePGQS6XUwoaVXn9+jW2b9+OsrIy+Pn5Ca7vqqoqVFZWYvPmzRp7gg8cOKBRf+bMGY36W7duadxfkpKSNL7DrKwsjcGwL1++/J+CZX8VIAaGYTSCkyQkJIgG7qqqqjB27FieI8jK06dPYWJiAjMzM8HntW3bNlFHsLq6mgfSpWrQvX//nscjqgpYlJOTIxi5Zyt5qqur4enpyeupbt68OZ1XLH+vOhgaizZeU1ODgwcPCvKdrl69mj4jNuinPjp06IB3797h7du3vNK9evXqoXXr1rC2toa9vT2cnZ1Rr149TJkyBREREby2D4Zh0Lp1a2zYsEE0SBIaGgo/Pz+N62bSpEka193WrVtF919AmRUScwYBpVOrqZfrzZs3Gvsr3717pzHQnJWVpbFEPD09XePfP378WCMX6/nz5xEZGYlnz54JPofg4GC4u7vDw8MDHh4emDFjBmbMmIGAgABUVFRg5cqVaN68ueCcqq6upkED9eHr6wu5XI49e/YIZsuHDx+OyspKJCQk8HhGCVEGaW/evImKigraLqI+unXrhg8fPiAmJobnQKg6EomJiaIZUHao91fWq1cP1tbWcHNzw5YtW3D69GlaqWNlZYXAwECkpqZy9oldu3ZBW1sb06dPF8WXsLa2xuzZs0X3sLi4OIwePVrjnPX09NRI5bdp0ybRoB0A+Pj4aOQa9fX11dgjv379ek7/rLrs2LFDY3nprl27NPK1BgcHa+xJ/uWXX3Dy5EnRdbNp0yb4+fmJlpjv2LEDI0eOxKFDhwSd8sjISDRr1gzu7u747bffeEj6SUlJMDIygq2tLVatWoVLly5x9oiCggK0bt0aY8aMwZYtW/Dw4UPO+axQKDBz5kwEBAQgPj5ecH+7fv06z3b9s8m/yiHdSrigRr/8ke/5szuk/82SmZlZq0FqZWWlkWcuIiIChCgBYYSysJWVlbQUpEePHoLfo+pwCpXbqlLDEEIEszGqfRBjx47l6auqqjBq1Cj6mUOHDvE+U1FRgZ9//plmUtWNS1YKCgoQHR2NlStX0s3njxr2paWltfaivXz5slbACXWRy+V48+YNzp49i3Xr1mHSpElYsGAB3rx5g19//RXu7u4ch7tjx47IzMzE8ePHMWHCBF7p0uHDh/H161eEhYXxQAsaNWqE3NxcSKVSnDlzBvb29px+y169elEnLTU1FYsWLeL0yfTv359utlKpFBERERg2bBgnKKF6/wUFBQgKCqIZHFNTU3rwsc89Ly8PO3bsoLQWbAmn6nspKSnByZMnMWnSJDg7Owv2R7Ok74cPH661J/Cv4sx9E2VgUhV0S10eP36M+vXri9L5sL2RbC+1qkilUjg5OdH5rZ5F/fz5M6dP7LvvvuPMrby8PF6f2Ny5c6m+sLBQsJyM7assKyvDhg0beM6ilpYWkpOTIZVKER0djalTp3IQpdlx4cIFmun19/fHpEmTYGVlRUsACVEC//z222+IjY1FUlISPnz4IBgMiY+P1xgkqaqq4mXz1EUTUi8rtdFI1LZ2Nek1BaD+20ShUKCgoADPnz/H5cuXcfjwYdy+fRsMw+DTp0+4ffs2QkJC4OPjgyFDhsDc3Bxubm748uUL7ty5g+DgYEyfPh1dunShqMaDBw9GQkICjhw5gkWLFmHgwIG09YCQv1GXbd26FbNmzUL//v15/LnNmzfH/Pnz4e3tjYkTJ2LQoEHo2rUrzM3NaaWAgYEB7O3tsWLFCqxZswYbNmzAtm3bsHv3buzfvx8HDx7EmDFjsHDhQly7dg05OTm8eXHv3j3s2LFDIyNBeHi4KH8tK5o4kAFlNU1twefa5nxFRYWgQ1tQUICbN2/iyJEjgr+Rl5eHmJgYjddYUlJSK9jOP/u8/L+saaD2dV1b8LegoEBjEKyqqup/xcrwnyr/cIeUEHKSEPKREFJDCMklhMwkhDQkhNwgStqXG4SQBn/ku745pP+5Ul1djcWLF2tchKdPn4ZEItG4WbFZxV9//VVQf/ToUXqQCPWxAcCgQYNAiBLgQWjTLCsrQ+vWrUGIEk1V7H5YOpQ5c+aIXm9WVhYmTpyIhg0b/iHgppqamloPi/+ryOVyFBUVISsrCzdu3MC2bduwdOlSuLm5oVevXrxIsKWlpSA1CiHKhvkRI0ZwSvhUh6urK5ycnESh4vfv348lS5YIIt3WqVMHSUlJOHr0KPr168fT16tXD+/evUNaWhqWLFnC40PV19fHixcvUFNTgwsXLsDJyYl3nSwwT3FxMQ4fPowhQ4ZwHGLVEtzCwkIcOnQI9vb29H7at2/PMWrLysoQHR2NuXPnonXr1tDS0kJMTAzn+TMMg9evX+PgwYOYPn06fH19RcvtsrOzcevWrW8O619MHj16pJGXef369WjVqpWgTiaT0fYIIUyB8vJyDjK2ahk8oNy7Zs6cSfVNmzblGTcREREcoK0RI0Zw9EVFRVi9ejXH6Rw5ciTnM5WVlThz5gwmTZpE+/dMTEwE+48ZhkFBQQEePnyI3377DVu3btWYpf53Sk1NDbKysnDnzh0cO3aMZpIUCgXS09MRGRkJf39/2NvbY/ny5XRtKxQKvHr1CkeOHIGXlxd69+7NA+lj94Zff/0VCxcu5ACLqUtxcbHGLNd/gxQVFQmeq5WVlYiPj8e+ffs4QFOA8hlnZGTgzJkzWL16NcaPH8/LlhUVFSEuLg5Hjx6Fv78/vLy8BAHT2GqKjIwMPH78+D8uwKBQKFBSUoIPHz7g1atXSEhIwK1bt3Dq1CmcP38eMTEx2Lt3L5YtW4ZJkybBxsYGTZo0gZ2dHa5du4awsDDMnz8fgwYNomd406ZNkZKSgnfv3uHMmTNYtWoV7OzsaHsRi+APKHEoLl++jI0bN2LixIlo06YNpkyZwnHGGIZBXl4eYmNjsXPnTuzYsaPW1rNv5+VfQ/6oQypRfvZfK71798aTJ0/+5b/7Tf7vUlNTQ3R0dIhEIhH9zNmzZ8mtW7fI7t27RT/j4OBAnjx5Qt69e0f09PR4+s+fPxMzMzNibGxMCgoKiI6ODu8zV69eJSNHjiSdO3cmKSkpgr9z7949MnDgQDJixAhy+fJlwc9IpVIyadIkkpOTQxITE0WvmRBCbt++TSorK8moUaM0fk5VAIg+r+rqanLjxg1ibm5OzM3NSePGjYm2tjbnM0VFRcTLy4vk5OSQ0tJSUlJSQkpKSkhZWRnnc/Xq1eP9Gyuurq7E3d2dzJkzh7x9+5ajMzExIffv3ydGRkbEw8OD3Lp1i6MfNGgQuXLlCrl//z7x8fEhaWlpHL2fnx+ZN28e2b59OwkLCyNVVVUc/f79+4mRkRFZtWoVeffuHe/awsPDSW5uLvnpp58Er3379u2kvLychIaGkvz8fJ5+1qxZZNSoUeT48eMkJiaGSKVSjv6HH34gJ0+eJJcvXyZnz54ld+7cIQzDUH39+vVJfHw8qampIVeuXCFXrlwh9+7dIzU1NfQze/fuJXPmzCEpKSnk7t275N69e+Tu3bvk06dPhBBChgwZQmJiYoi+vj7Jzs4mT58+pSMxMZEoFApy/fp10qtXL0KIch1lZmaStLQ08urVK/Lq1SsyYcIEMnr0aN79VVVVkdzcXGJgYECaN28u+Iy+yb9PNK1vQggJCAgg8+fPJw0aNODp5HI5cXV1JaWlpeTixYs8vUwmI+7u7uTkyZNk9+7dxMfHh/fbe/fuJYsWLSIKhYLExcURGxsbzmfy8/OJl5cXiYqKIoQQkp6eTtq1a8f5TGFhIdmyZQvZu3cvqa6uJlevXiXDhw/nXU9FRQWJiYkhkZGR5OPHj+TGjRtEX1+faGlpid5/cXExMTExEdQBICkpKaRz586C3/H161eSkpJCmjdvTpo2bUr09fU5+tzcXJKamkpkMhmpqakhNTU19P9lMhkpLCwkOTk5pLCwkDRp0oSUlZWR7MkkNrEAACAASURBVOxskp2dTT58+EAYhiG6urrEzc2N6OrqkqSkJPLixQtSUVFBf2Pq1KnE2dmZJCQkkLi4OBIfH0+Ki4sJIYRoaWmREydOkKFDh5LHjx+T+Ph4OoqKiqh+8uTJpKamhqSnp5Pk5GTy4sUL+l9bW1ty6NAhzhmnUCjIp0+fyIcPH0hBQQEZOnQo797/W0UulwvaA6wAIAzD8M5RVWEYRuOcrampIbq6uqL6yspKwjAMMTIyEtU/fvyY9OnTR/C9VVRUkF27dpHWrVuT9u3bk3bt2pG6detSfXFxMZk3bx5RKBSkbt26pE6dOqRu3bp0yOVycuDAAfL582cilUp5Z+4fESMjI1JeXi6oMzU1JR07diRpaWmkqKiIp+/Tpw+xtbUlL168IM+ePSN5eXkc/bhx48icOXPIq1evyMuXL0lqaipJTU2l32VlZUXOnDlDqqqq6HrMzs4m79+/J9nZ2SQ3N5csX76ceHt7E4ZhSHl5ObV72AGA2NnZaXyP/26p7WxgHTFN91Dbd/wniEQieQqgd60f/CNe6z96/NkzpBkZGbh48aJolKy0tLRWrq3/Znny5EmtWUQ/Pz8eWqG6DBgwAFOmTBHVMwyDHj168PpD1WXx4sUYNmyYxs9IpVJMnDhRsCSzurpaY8Q0MTFRY5/FypUr4ebmhnPnzgnOG1V4cy0tLTRp0gQ9e/aEnZ0dZsyYgVWrVmHp0qWiJNj6+voICQlBREQEh7idHfPmzYNMJsPevXt5JXoGBga4f/8+5HI5tm7dyuvhadmyJQoLC8EwDPbs2cPLkPbr149GOSMiInjlfU5OTjTKeffuXd73jx8/nuqFEOeGDh0KhUKBwsJCLFq0iKfv1KkTysrKEBkZKQilb2JiguTkZLi5uQlS50gkEly4cAFhYWGiaJ9LlizB69evabZdfdjY2ODr16/w9vYWhOtv0KABEhMTER0dDUdHR3To0IHTZyWRSLB79258+PABW7ZsgY+PDxwcHGBlZUWzxWPHjkVJSQlu376N33//HQcOHMCWLVvg5+cHT09PLFq0CEVFRSguLkZeXh6ys7ORkZGBV69eISUlBc+fP/+nZ+y/ibAwDKOxbKumpkZj1YlCocD8+fMFS39ZuXXrFho1asTr02b/vrq6Gr/++iuMjY1pL7bq77PZztzcXHh7e6NXr150vnz8+FEQxby0tBT5+fm4ceMGAgMDRedXUFAQRo8ejUePHgnq58yZg++++w4uLi44evQopzxXoVBwev0bN26MXr16wcHBAfPmzUNAQECtFBrqPY3qa1PT37u7uwtSbLDr9siRI/D09BTV//bbb7h06RK6d+8uWF0yd+5cfP36FYsXL4aTkxOsra1hYWFB9/EGDRrgxo0buHz5Mnbt2oXg4GAEBQVhx44d2L59O7Zt24YDBw4gNzcXMTExSE5OFj174+LiNPbA5ubmaiwzBZSo85pKDBMSEjT2JCoUCg6qrZBs2rRJMPvOSnh4OA9xVV0mTJjAA1NUlZCQEBw4cED0Xl69egU7OztBahkAFEBwzpw5oj2MdnZ2qFOnDuzs7BAUFISUlBTONQcEBHDmQrNmzTB48GB4e3sjODgY69atEzzPVW0FsYqlRo0aITg4mIN0yw5tbW2EhobyKMTY0aVLF9y5cwc9evQQ1I8bN04jN7qzs7MgcwA7Bg4cyLt31VGvXj2EhISgffv2qF+/vuC53a1bN4wbNw42Njbo168fBg4ciCFDhmDEiBGwt7eHg4MDJkyYgJEjR2LGjBnw9/fHrl27EBkZibt37+LNmzfIzMyEo6MjlixZgvDwcCQkJPDss+XLl2PhwoU4e/asYC9uVFQUpk2bhtOnTwuuu4KCAgwfPhxhYWGia8/FxQWBgYGivbTr16/HmjVrRNdmZGQkdu/eLdjj+mcR8s/oIf1HjT+7Q8rSVhgbG2P69OmIjo7m9K+Vl5ejZcuWGDRoEDZs2MBrNi4rK4O7uzsCAgJw7tw5ZGRkcDY+uVyO6Oho3LlzB8nJyfjw4YPg5qpQKER71sSasFn5+PGjxn63P1Lf/8+UM2fOCCJsqsr27dvx22+/afzMyZMnsXz5co3GdkVFhSC1AivV1dWUrkSodOrt27eYNGmS6G8kJiZCX18fAQEBgr1QLK0AIUoIeUdHRxw9epRuIGfPnhUFWiBEiQCs7sSwo127dggNDRUFYvD390dCQgKsrKw438ceaFFRUcjMzOQANbCk24aGhhSoQ7XfjUVCbNiwIXJyciCTyTjOIuuUNW3alN5jaGgor8zW3Nyc6q9fv87j8DQ1NaVGxevXr3lk3Pr6+pQgXf0a2cH2zNXU1GDy5Mk8PUt1AQB79uzh6cePH0/XblxcHM9p7dKlCz1oCgoKeLxnDRs2pFQcMpmMU4JJiJKehuUkVOUcUx2q81sVwZodw4YNo2AlDx484PX+tmjRgqIUFhQUoHfv3mjTpg26du0KGxsbDBs2jOoZhsGKFSswbdo0rFy5Env37kVUVBTHuLt27RqCgoJw584dwXLM/Px8XLhwQeP+o4nYnr1OTVJRUVFrOVdtDvg/ohystu/4I32LX758gVwuFzWOnz17BoZhsG/fPsHfu3jxIj58+IB3795h4sSJvM/Ex8dj27ZtAJROh4uLC8fwSk1NRe/evTlBt8zMTLx//56Wp+rr6/OA4wDlM37x4gU1NNWNKoZhOABzgwYNQmxsLOcaheZ0t27dsGzZMly/fh2hoaGieyMhyqCakNFKCKF7rVArQufOnfHu3TvExcXx1gwhykAUwzB4//49h2eUHSzmQFVVFf7f//t/HJ1EIkF4eDi9RyFexxUrVtDnwOIuqI5OnTpRwJisrCzBYJednR3tY7Szs6P/bmJigu7du2Ps2LEICAhAWVkZjhw5AolEgl69emHZsmW4cuUKh0+0tLQU9evXh52dHaKiogTnrru7O3r16oXY2FieDlA6rEZGRjzuYtX50rx5c9jb2wsa+FKpFAsWLICJiYlg/3ZFRQXOnTsHQpS0WOrntUwmQ2lpKXr37o0GDRpwOJZZycvLo7QlAwYM4JVTv3nzBlKpFJaWliBESR2jCiaYkpKCtLQ0DqWHlZUV9u3bh5KSEiQnJyMmJgZr167lva+mTZvCwcEBHh4e8PT0FJ23qvNI6N9btGghCDjG3tOSJUt4PbSEKOl8Ll26hB07dvAQjwlRBle/fPmCU6dOCQZgWfT3Bw8eCLbneHp6QqFQICcnR5ADdOzYsaisrER1dTUPMZm9LxbZXJ3WhR3e3t6oqqrC48ePBR1yPT09BAQEoLCwUJS2RUtLC25ubpyWB/Z5t23bFo6Ojli9ejUHnI7dM+bOnYuIiAjk5+dTyjz2d0eOHInQ0FB6XpaWllK7RFdXFw4ODoiMjKRno1QqxZYtW+g12dnZ4fTp05y9+PLly/Tahg8fjsjISI7+9evX0NLSgq6uLpycnHD+/Pk/Xck5+eaQ/v2ydetW3kZQr149TJ06FefOncPVq1d5DoSxsTFmz56NgoICfPnyhWNcm5iYICAggOPUska9tbW1YK/lhAkT0K1bN8HeExbFVgiEBwDS0tIgkUjg7e0tqJfJZDAxMYGNjY3oM8jKytIYTf348SPevn0reOjU1NRQgmp281EXllQ4NzdXNLsYHx+Pq1ev4ty5c4LfwYLfBAYG4ty5c4LfcebMGezZswceHh6C+jt37sDT0xNNmjQRjHClp6djwIABIIRLps5KeXk5hyevXbt2PN5ac3NzwU1RW1sbgwYNEs281alTB/7+/jzyZnY4OzujtLSUbmg6OjqYNWsWzapt2bIFACg8vIGBAQIDA3H16lUQQnDw4EEAyvliYGAAPT09bNmyBTKZDPr6+tRR+vr1K1q2bAmJRII1a9agsrISenp6NGtSU1ND+3lnzZqF5ORkSCQSjtHCZoGHDBmC/fv3gxAukMtvv/1Gnx8LiX/69GmqZ53++vXrU1h+lmKGvcYWLVpAIpHQQ2rp0qVUr1AoMHToUM7zU83OAoC/vz/vcFZ1qs6fP8/Rt2nThsOTmZWVxTkgv/vuOw5tiFwu57zrunXr8qDop0yZQvW6urocoxbgOs0SiQRr167lOF5JSUmcvcvd3Z3TG1tTU8MxRAYMGMBD6FMFFGvWrBnCwsI4B9yOHTs4c3jJkiWctfPo0SNoaWmhTp06GDduHI4fP865xs+fP8PCwgJ9+/bFuXPnBPeQkSNHYvr06aJ70C+//AJPT09Rh+/hw4fw8PAQdRjfvHmDn376SVRfXFyMwMBAUadaJpMhKioKR48eFdQzDIOLFy9izpw5otnRu3fvIjg4WJST+u3bt9i/fz+aNm0qCNpTVFQEPz8/2NraUjTz8vJy+ntyuRzz5s3DuHHjYGxsTB0AVZ7R1atXU/CwJUuW8H7jwIEDlLbFwMCA54jcuHGD9pUSogxGqe7F2dnZgnuXjY0NoqKiwDCMaJZHdZ6L7Y8rVqzA2LFjebp69eohPDwcDMPgp59+4ulHjhxJgymRkZE8/erVq+ncSE1N5fSjE0IQGhpK77GsrIxn3KtzbA4ZMoSjVwfHU7/GMWPGcII9165d49kb7P0BSkdNPZvWsGFDbNy4ka5N9hxTHbq6upgwYQKys7Ph7+/PcdwtLCzw888/0yDDuXPnOEBCw4cPR2JiIr3G3NxcjpMycOBADnCPQqFAhw4dqO3UtGlT3L59m/Mcxo8fz6niWbVqFWfv2LBhAyd40KFDB6SmplL9xYsXYWBgwAHX8vT0pI73+/fvQQjhgPmxDgyL7m5sbAw9PT1OdpF1YDIzM3lgYqqjbt26ojRHf3Royug3adIEwcHBgp/V1tbG+vXrUV5eTm0AU1NT+k4tLS1plpbFclDFaxgyZAh18FkqJtW15+HhQd9FeHg479p8fHzofGSDVKpj+vTpdL+urKzkBaBtbGw4/b3qa6ZevXqIiIgQXTOEKMERWZtZnSuVHU5OTkhNTUVRUZHoc+7Tpw8iIiI0vsv69etzAv3qo3fv3hSfROhv3d3dBYPg7HtZvHgxj5FCVb9kyRK8fPmSR83F6hcsWICnT5/+KfpwyTeH9O+XCxcu8BZLhw4dMH/+fFy4cAEpKSm0zKdhw4aYPXs2rl+/ThebXC7HkCFD0LlzZ4SFhXGikKzs2LEDx48fF42Kv379WtQYSkpKwpAhQ0SJb0tKSmBvb8/jemRFLpfDw8MD69atE30Grq6ucHNzE9UPHDgQ9evXF4xA1tTU0E27Y8eOvGhNUVERpk+fjvr168PCwoJXZlZZWYmgoCCK2qilpcVrjn/y5AmWLFlCD1U2A6AqrGNOiDIbp/6sGYbhlGOtWrWK9x27du3izIMFCxZwFnhqaqogcbuzszMtPROKBBKijIAvWbIEM2bMQOfOnem/6+rqwsfHh/79/fv34e3tjYcPH8LIyAgGBgbYv38/vY6ysjLMnz+fwqNbWlpi3759nPvYtGkT1aempnIyg4AyyKHqPKk7QnFxcYiNjYVcLodcLudlrj99+oTw8HCkpqZCoVDwDC6ZTIZffvkFz549Q05ODnx8fHjPeu/evUhKSsKFCxcE597Zs2eRlJSEn3/+GaNHj+ZttA8fPsSNGzcwZMgQ9O3bl+cIvH//HqGhodDX10eXLl140fWqqioEBQXBwsICrVq14vF5MQyDvXv3onPnzmjatKlgCc2pU6fQp08fNG7cmAdCAyiz5cOGDUOjRo0ov5+qpKSkwNHREY0aNeLw67FSUFCAadOmoVGjRoK8agqFAt7e3mjcuDHOnz/P0wPAxo0bKQKq0GF1/PhxNGnSBLt27RJEdr59+zbMzMzg7+8vWJ738uVLmJmZwdXVFSdPnuQ5lXl5eTA3N4e1tTVcXV3x+++/c66jtLQUFhYWMDAwQKtWrXD58mXO31dVVdH919HRkXeNMpkMtra2IIQItgUwDEPpIc6cOSOonz9/PgghgjynLN0TIcqMn7pUV1fj2LFjdD2rc+ixIFes4d2tWzfedwDgAICxwSNVUeU6NTU15Z0zqsBwrMGoKhkZGTwnRrU0l2EYXobB0NAQt27dop/x8/MT3Nu8vLxQWVmJBw8eaKz+6Nq1Kw12qeuaNWuGBQsWwNnZGc2bN6f/bmBggMWLF1PjNSoqilN5YGtry5mXeXl58PT0pMa7j48PJ5ChUCiwYsUKeq9CSOohISE0AynEgRwTE0P5KVW5N1lJTEzErFmzRP8+NzeXlv6uXLmSd1ZVV1dTurVRo0YJlqP6+vpSm2TTpk28AOvGjRvpM2rQoAFmz56N2NhY+iz279/Pew/a2tro2bMnoqKicPr0acF36eLigoyMDNy6dYvjCLLzhaUiS09P57V0aGlp0aBaZWWlIH/n0KFDacVEr169ePo6depQwCOhTDRrvyUmJnIo6YQ+c+bMGVFgP/Zsbty4ca2ZTUKIaAtIy5Yt0aJFCzg6OnIcHhMTE/j7++PNmzcYOnQoAgMDqdOlra0NX19fGqSYN28eQkJCkJ6eDkKUDrZqYiMkJAShoaEoLy9H/fr10adPH855dvv2bUpzJLSPfvz4Ecv/P3vvHRZF9qyP1wxZRBEEFSOCiqBrFgyYxYAiihnTGjDngC7oukYW8wcToitgTqiYQDBnVAQxC5hAkCBJRGaGeX9/zK/Pnaa7x72730+491rPUw/uVk9Pz+kTqurUed9Fi1iyhtv55ESpVGLevHksaJw3b55gLQkICGCVA7NmzRL06dDQUJbIHj58uMDfjYqKYuO6ZcuWAnqZhIQExpJQqVIl7Ny5k/cd2dnZPHqtLl26CI4NDBkyhNn19fUxYsQInl89Z84c3hxpYGAADw8Ptsu5du1aQZ8n0gSjv/76K1asWCG6k0ykSVh37dpVtPKBUzMzM0EsUn58lacI0x4X3bp1w7Fjx/7tQSn9CEj/uiQlJcHa2hrDhg3Dnj17BDxKxcXFmDFjBqKjoyWz348fP/63d4K/I4sXL9YJSz59+nRUrVpVEq6fK4Xo16+fqJ1bnInEna3yjk75ttyzZw/Prk15AGjOspQf6NoTjUqlwoIFC3gZRmNjY14p9Pv375ljq63agevr168FqLCcVq5cGVu3bsXhw4dBpMmeenh4YOfOnQJHfsqUKZDJZBg9erQk71ZeXh4aNWr03XJHMRJpbVGpVKLUJhwdTPlALCcnBwcOHIC3tzfmzJnD+6xCoUBUVBQmTpwIGxsbNuFz13z58gUHDhyAu7s76tati6ysLN4OjVKpRFRUFEaOHIlGjRohJycHubm5vN2Bjx8/YsOGDejYsSOePn2K27dvC0o637x5g4CAAFy5ckXyPEZRURGePHmC9u3b6+RO69u3r05UzJEjR/Ky8uVlxowZOvlily9fjpcvX0rad+zYoZN7LSIiQid3240bN3SWvD558kRnuf779+91npHPzc3VWRL09etXneWyYv3vvysKhQIvXrzAqVOnRCtMiouLcfr0aUycOFE0cfft2zcEBwejS5cuognD/Px8TJgwAS1bthR91kePHsHW1hZyuVyUiHzbtm3MkZk1axbP9uXLF54jRES8ufbLly+CJJarqyvvty9atEhAuK7NmRoTE8MqDTjV09Nj/VKlUuHw4cOwsbHhXVO1alVGYyPF61ihQgWGfH7//n3RclciTXnb48ePRelniDTnQdu1a8c7b1a/fn0sXLgQd+/e5TmX7dq1g6GhIaZPny5Ks3PgwAEYGRlhw4YNklU7enp6CAoKEtg46d69OzZu3ChpX7BggWjik5OgoCBe1UZ5CQ8Pl6xqAjRJwYMHD0raDx48iNDQUMmxEx4ejoCAAMkzpMHBwRg3bhwuXLgg6rcEBQWhSZMmGDduHIKCgnDnzh1ekHDw4EEWaNWpUwetW7eGu7s7xo8fj2XLluHcuXO83XJtdXZ2xpUrVySd586dO+PNmze8ChFtrVWrFu7cuYOQkBBJ53zq1Kn48uUL47Uur4aGhti4cSMSExNFgwhOJ0yYIFpuq63GxsaCQEMul6Np06YYP348duzYgVWrVjHbTz/9hBUrVvDWBaVSCSsrK9SqVQsbNmwQfW9LliwRrWLhJD4+HgMHDpQ8/qRWq+Ht7S1JGadWq3k7l+Xl+vXrmDZtmuTGyYQJE7B48WLJPjls2DD89ttvkvZJkyZh2bJlkva5c+di5syZkn7m0qVLMWjQIEnqrU2bNqFFixaIioqSTL5aWFjgl19+EU3y3Lx5E0Qa7tmdO3cKzmm+e/cOBgYGMDMzg5eXF/744w/eGfji4mJWWl2jRg0MHz4cO3bswLNnz6BWq6FWq1lQLpPJ0LRpU0yaNAl79uzBkydPoFKpWGm4TCaDo6Mjfv75Z+zcuRPx8fFQKBTYtGkTu/+QIUOwefNm3L9/Xyduwb9afgSkf0Py8vL+T3AD6RLtUkQx2bt3LxYuXChp58olpBboly9fsiyjGK3L169fGQm2vr6+6D20Syz79Okj+h3agBW+vr48u1KpRFhYGK+McsSIEczOQffv2bMHP//8My+bGRAQAECTpYuNjcXNmzfx4MEDPHnyBMnJyUhLS0NOTg6+fPmCXbt2ITY2VifX3ty5c79Lbvzly5e/RA+Qn5+Pe/fuISwsDP7+/khOTkZpaSnu3r2L9evXY+DAgey8SVBQEMrKyvDgwQOsWLECLi4urFytY8eODODp3LlzGDduHC+jze3KKhQKnD9/Ht7e3sxZ1dPT473nhIQEzJ8/n+0u6+np8XYECwsLERYWhp49e7LvDw0N5f2utLQ0bNy4ke1yDxs2DGq1mhcMZWZmIiQkBO7u7rCxsUFycrJg8SorK8P9+/exZs0aHDt2TBIcQK1WIycn57vv4HvnN/6vzy3/SaJUKnUG5xcuXJAEacnNzUWvXr0E1QicXLp0CRYWFqhbt65oAiggIIDNgdx8wklxcTHbEeNUG+glKytLUMpvb2/P+tbbt28xYcIEwQ4oR3/15s0bzJgxQzT73q1bNyiVSmzcuBEtWrQQBVYxNTXF+fPn0b9/f7Rs2RKNGjVCzZo1YW5uzkvyGRgYoFGjRvDx8UFgYCBOnDiBhIQEnvPt5+cHf39/dla2vBQUFGDq1Kk6cRMiIiJEKxK027P8Tnt5EatY0Jbv4TZ8jwv1784Lf5dT8Xv27zmw79+/R35+vuR9rl27htOnTyMyMhJnzpzB2bNncfbsWZw7dw7nz5+Hv78/Fi5ciKlTp8Lb2xseHh7o0qULWrVqhYYNG6JWrVpo06YNWrZsibp16woSHXp6eqhatSqvbLi8SiWHtVVqR0pPTw/GxsYwNTWFnp4eDA0NYWdnB1dXVwwfPhzz5s3D+vXrcfDgQSxYsAB16tTBkCFDsGHDBly/fp2X2FKr1fj555+xevVqyeTj69evERoaqrNfJCYm6nxv3ztLzwU9uuy6+t2XL190fj4hIUGnXbvqSkx0gVcB0AmQBUBn4hbQVMnp+n3x8fE6k6+3b9/WCfR148YNXLp0SfId3r17FyEhIXj16pVoO7169QqrV6/GpUuXRBMShYWFCAwMxKVLl0TxGtRqNc6cOYPU1NT/6A2wPxuQ/qB9+SF/SZ4+fUpGRkZkb28valcoFGRtbU337t2jRo0aiV7j5eVFERERlJmZSdWqVRPYY2NjqWfPnmRsbCwKa65Wq8nb25sOHz5MDg4OAjoSIqKCggLy9vamc+fOUaNGjejFixeCa5RKJYWFhdHKlSvp/fv3dOfOHXJxcRF95qysLLp16xbdunWLvLy8qF27dqLX/SuktLSUCgoKKD8/n/Ly8iglJYWeP39OJiYmlJaWxuhEMjIyiIhIX1+fPDw8KCcnh+Li4ujbt2+8+40cOZIMDAzowoULlJWVxbPZ2trSihUr6OLFixQZGUkFBQU8+/jx42nChAl08OBBOnr0KGVnZ/PsAQEBNHr0aDp48CCFh4dTUlISz7569WpatGgRxcTE0P79++nkyZO8dz527FgKDQ2lT58+0fHjx+nIkSN08+ZN4uavxo0bU1xcHFWsWJFev35Np06dolOnTtGdO3cIAOnp6VF0dDR1796diIg+fPhAFy9epJiYGIqNjaXc3Fzy9PSk48ePM7oApVJJjx49otu3b9Pt27fp0aNHFBwcTN26deM9OwD68OEDPX78mCpXrkyurq7/rff4Q/7nSllZGV2+fJl69uwpak9JSSEPDw86ePAgNWvWTGCPjo6mESNGkL29PcXFxQnsR44cIR8fHyosLKTly5fTr7/+yrNHRUXRlClT6N27d0REdOrUKRowYACzJycn02+//UYHDhxgY+XixYvseRUKBZ07d47CwsLo3LlzpFKpiIho1apV5OfnR0QaCov4+Hi6d+8eozZ59+4dmZmZUUxMjIBmhrtvcXEx09q1a1OFChW+257/aQKAPn/+TGlpaZSfn0+dOnXiUTCoVCpKS0uj1NRUMjU1FW0LIg11U2lpqST9zQ8Rl2/fvlFubi7TnJwccnZ2JhsbG8rLy6PPnz9Tbm4uff78mT5//kw5OTmkUqnI29ubANDXr195mp+fT1lZWVS5cmVyd3cnQ0ND0tfXJ319fUa9kZeXRzKZjCpXrixJt1FSUkImJib/yqb428K1R15eHvMZ8vPzycDAgNzc3Cg/P5/S0tIoPT2d0tPTKS0tjbKysmjWrFnk4OBACoWC3r17R2/evGFqYmJCixcvZtQ2ACgzM5PZzc3Nyd3dXfR5vn37RkVFRWRlZfWvbIYf8m+QP0v78iMg/SF/SYDvcyMtXbqUVqxYIXldXFwc9ezZk/Lz8yWvGTt2LJ08eZIKCwtF7d++faMePXrQw4cP6evXr6L3KSsro6VLl9LatWvp+fPn5ODgIHovhUJBe/bsocuXL9PRo0f/NPfT99oiIyNDlF+UE5VKRYcOHaIKFSqQubk5MlKtTQAAIABJREFUmZubU+XKldlfAwMDunHjBi1YsIDy8/MZD1f5gFIul/P4NbXFzMyM3NzcKCIigsTG/Jw5c6igoID27t0rsFWpUoV2795NGzdupFu3bgnsbdq0oSVLltD06dNZ8Kstffv2pXHjxtGYMWMEz0xE1LNnT5o4cSLNnDlTEAgTaYLNlStX0o4dO+jKlSuC32hqakphYWH08OFDOn36ND179kxwj3Xr1pGDgwMLQssnJlxcXOjo0aOUkJDAAtD79++zoNjAwIBOnz5Nrq6u9OTJE3r8+DFPCwoKqHfv3nTixAmqUKECFRYWskU5NTWVUlNTKTMzk/z9/al58+a87wZABQUFlJ2dTRYWFmRpaSl4/h/yP1cKCwvp+fPnksFKSkoKDRo0iM6cOUN16tQR2FNTU2n48OGUm5tLycnJgrnmy5cvtGzZMtqyZQt17NiRrl27JrjHs2fPaPny5XTs2DFq2rQpPXr0SDAfZWdn06FDhygsLIwSExPp2rVr1KFDB9Fn/vTpE8XFxdHLly9p8uTJZGZmJvn7v+e85+bm6uzzqampVKlSJbK0tBSdZ5OSkqigoIAMDQ3JwMCADAwMeP9+/vw5ffr0iQUl2lzO+fn5lJ6eTrm5uVSvXj1q2bIlZWRkUFpaGn348IHS0tKopKSEqlevTosWLaKysjJKTU2llJQUSk1Npbdv35JKpSI3Nzdav349ZWdn8xx2Ths3bkwnTpwgc3Nz+vz5M2VkZFBmZiZlZmZSRkYGlZaW0uzZs3W24/8V+TO+xX+CfI/LNCcnh4yMjCTfaUpKCj1+/JgcHR3Jzs5OwK364MEDOnDgAFWtWpUsLS2Zcv99+fJl2r9/P1vPuV0m7tmSk5MpPz+f9PT0SF9fnwoKCnjc2kQaDm4LCwvKzMwUrM0mJibUqVMn+vr1K71584bS09N5vkOTJk1o2LBh9OnTJ7bOvX37lq2ZXbt2pUWLFlFubi4bSx8+fGD/trS0pMOHD1PlypVZsiEnJ4f9+/PnzzRhwgRq0aIF77lUKhWVlpYyvnExfucf8p8lPwLSvyHfvn2jlStX0oQJE6h+/foCOwA6duwY9e3bV5IYOT09nWrWrPnPftT/aPn69et3s+KLFi2iwMBASXtOTg516NCBXr58qfOadu3a0fXr16lGjRqS1x05coQyMzNp9uzZvP9fVFREFStWZIsgNzEbGxsTEdH9+/epZs2aZGNjI3rfVatWUVlZGU2aNEn0moiICBo7diy1bt2anJ2dmWpfu3v3bpo0aZLo/blAVSaTUXp6uug1zZo1o6CgIBo1ahS9f/+eZ6tWrRpFRUWRkZERDR06lJ48ecKzz549mzZt2kSJiYnk5eVFqampzGZgYEAxMTHUuXNnSkpKou7du/N2P62srOjhw4dUu3Ztev78Obm4uPCSB7Vr16ZHjx6RpaUlJSYmUocOHXik89WqVaPExESytrammJgYGjhwIH39+pXZTUxM6P79+1S/fn3atm0bLVu2TLBbfuTIEWrZsiX5+vpSRESEoG0mTpxIvXr1opkzZ1JmZqbAbm9vT/Pnz6dZs2YJFmwiIj09PdqxYwft2rWLpOYtT09PcnJyoosXL1Jqairl5uby7FZWVrR69Wp69uwZZWVlUXZ2NvubnZ1NSqWSpk6dSi4uLqRUKqmkpESgNWvWpD59+rCMfnk1MDAgMzOz/2ii8B8iLsXFxZSWliZZTaJQKMjPz488PT0lg8T79+/TpEmTaPfu3dS69X+t/SqVijm7CQkJ9Ouvv1L//v1p4sSJRKRJmFlZWfEc4idPntDVq1dpypQpFB8fT9bW1lSvXj3R7w0PDye5XE7e3t6igcSSJUsoPT2dZsyYQW3bthXYt23bRuvXr6fu3btT9+7dqVu3bryKmZiYGHJzc6OKFStSvXr1yNbWlqffvn2jSZMmUVFRkejzfU/kcjnJ5XK2O1xeqlatSjk5OZKfb9myJSUmJlJZWZmovW/fvpSdnU0ZGRn06dMnwRzTuHFjcnZ2ptLSUt54//r1K/t369atqVmzZlS5cmUyNTWlihUr8rS0tJQeP35MDg4O1KBBA6pWrZrgXZw/f57q1atHjRs3Fn1Pr1+/ptzcXHJ2dpYMCI8ePUoeHh5sbSwvMTExVKtWLWrcuLGoPTMzkw4cOECzZ88WBGCcTJ8+nSZPnkw//fSTqL24uJjWrVtHS5YsYTtz5eXy5ctUoUIFyUonALRu3Try8fGR3LXes2cPGRkZ0bBhw8jAwEBgv3r1Kq1bt47GjBlDHh4egqRLdnY2OTg4UOPGjalHjx7UvXt3cnZ2JkNDQyLSVOC0bduWEhISyNDQkBo1akSOjo7k6OhITk5O5ODgQP7+/nTq1CnR5yPSrE1S/U5PT4+qV68u6TMMHDiQoqOjeestJw4ODlSpUiXRqg0iImdnZ3rw4IHkd9etW5dVbYiJg4MDpaamkkKhELWbmZmRpaUlqdVqFnxyyiWkLSwsqF69emRhYUHGxsZkYmLC+/vmzRv6+PEjNW/enGxsbKhGjRo8VavVNHv2bLK3tycnJyfW9pUqVSIiTR+ZN28eyWQy6tChA3Xo0IGqV6/Oe85jx47RxYsXqW/fvtSjRw9B8iEjI4OmT59OXl5e5OHhIbADoEmTJlHLli1pxIgRVKVKFUFbbNq0ib5+/Urjx48X9W9jYmLo2rVrNHnyZKpdu7Zkm/875c8GpD/OkErIoEGDIJPJ0K9fP0RFRQnq0KdMmYJKlSphxowZogAn8+bNQ/v27REaGipao75jxw4sX75c8lxKfHy8TvCa4uLi/xVE92KAIuVFjI9MW968ecO4wcTkwYMHiIuLAwDROvzY2FgeZHl5iY6Ohrm5OcLDw0WvuXv3LjuD4uXlhUuXLvGuS09PR4sWLUSBGry8vLBo0SIsXrxYFK2XU3t7e0neMW9vb0ybNk0UAdHOzg4PHjzAzJkzRc+CTZw4EcXFxVi8eLGoPSwsDGVlZdiwYYOAnkFPT4/B9h89elRwtkdfX5+BHN27d0/ASyaTyRhFzvv373moopxyKKdFRUUCzjAiwpw5cwD8F+F6+Wfs0KEDO99x/PhxATqilZUVAzg6duyY4P4ymYwhOL548UL0/BLHzZafny9KJt6oUSOkpKRAoVCIgnZUqFCBgZlIEYaPHz8ehYWFOHz4sCjCY8OGDXHt2jU8fPgQVatWRa1atfDTTz+hS5cuGDRoEKZMmYJXr16huLgYnp6eGDp0KHx9fREcHIyYmBgkJyezM2Rbt27F2rVrERMTIwqWcf/+fZw4cUJ0LAGacy+3bt3Seable2eHvsdRXFJS8t0zd987E/f/gqf0e9d87xlLSkq+y1WqDXgkdn75+PHj7HsUCoXg3NbOnTtx79493v/TPpt14MABjB8/XvK3REZGwsrKShQ8CvgvnuWuXbsK5mAOEZ3rp23btkV4eDjvPH16erqA57NJkyaYNWsWTp8+jcePHzNqGiktT8uira1atYKXl5eorW7duoiJiREFbyIijB07Fvn5+TyeZm1ds2YNysrKJMF4VqxYAbVazaNK0taBAweisLAQN2/eFEV3NTc3x9GjR5GVlQVbW1vRe9jY2ODgwYM8nmUzMzO0aNECQ4cOhZ+fH8LCwhjqcrVq1TBs2DDs3LkTL1684KG1V6pUCQ0aNMBvv/0mOkbHjh2LatWqISAgQPTMbHR0NPT09DB16lRRsC+1Wo0qVaqgWbNmomBjarUa48ePh76+PpYtWyY4m8c9a926deHk5CS4B2e/c+cOZDIZfHx8BCjf3DUDBw6EpaUlNm/ezPsebl64desWiDQItps3b2a+SklJCTubyYE0VapUCRMmTMC1a9eQn5+P9PR0JCcn88AbiTRnr3v27Im5c+di48aNomta+fVHymZmZiaJ4GpnZwcPDw8BqjGRBpF706ZNGDdunCgSsIeHBxISEjB58mTRe69cuRJZWVk8BFvt5924cSOKiooYn3l5nT17NhQKBX7++WdRe4sWLZCamorw8HDJse7n54dnz56J/j6ubTZs2CDJz06kQagtTy1DpPHL3NzcMHfuXAEVXP369TF69Gjs3LkTSUlJKC4uZnOXgYEBunXrhvXr1zPQIuC/qNyMjY0xaNAgHD58mOf3cjzLhoaGGDp0KM6fP89bmxITE0Gk8ae8vLxw8eJF3rpSXFwMMzMz6OnpYdCgQbh8+fJ/3HlS+gFq9Ndl9+7dAvjxBg0aYPPmzcjLy8PDhw95MPREGpS4I0eOoLS0FCUlJbzBWLlyZUyfPh0JCQnsO8aOHcsGsJubG44cOcJbpLds2QIiDTrdH3/8IQjcrl+/jkaNGmHv3r2ijldeXh6WLFkiSR2jVqsFfJnl5cWLFzrJ7TnUUinJz8/HzZs3JYPO0tJSJCcnCyhGtJ8xMTERo0ePljw0funSJcycOVMSvTA2NhbTpk2Dg4OD6G+5c+cOBg8eDCIhpQugcQZbt27N3mX//v15gE+FhYWiyIIODg6sv+hC9PueOjg4CEjXOa1YsSIOHTrE6G+INIEJRyHTokULBurD2V1dXRk9wIgRI6BSqdjCS6SB2Oecp6VLlwLQgAdxv6FDhw5Yt24diAibNm1i75HjBnVycoKfnx+IiIdYyTmE1apVw/jx40Gk4frjZO3atSDSIDh269YNRBreMu59xMTEsGfkAtsOHTqwvp+WlgYzMzO2YBERateuzaghVCoVmjZtKliQtB11jnZBW7URoMvTaBARJk+ezBaH1NRUgb1z587MIVKr1YxsnVM7OzteAMG1DadVqlTh8bHu37+flzjQ19eHv78/Q1F8+fKlALSjf//+LFAoKytjHMic1q5dG9u2bWP3KE+dYG9vjz179rDfyVEn6Ovro2vXrggMDOShRz5//hwVK1aEo6MjNm3aJACJKioqQosWLTBgwABJIK+pU6cKOFS15dSpUxgyZIgkeuTr168xePBgybknJycHM2fO5PHeaYtKpcKWLVt0zm8JCQmiCOHaz7Bo0SJJ5yA1NRWbN29mfL/lJT8/H6dPn4aTk5No8KxUKhEeHg4nJyfJOTQoKAju7u6oX7++aAIhODiYceUtXrxYYD927Bjat2/PHKbw8HCe/datW7xEk4GBAfz8/Nhc++HDB9FEl5WVFX755Re8f/9e1P5ntUKFCoIxxWmlSpWwfft2xoFcXgcMGIDPnz+LIrfKZDIEBgZCrVYjLi5OYDc0NGSJqsLCQoFjbGhoiP3797N24tpQW1euXMnGVHnHl0hDU8Eh/MfGxgqCE319fSxcuBCFhYUoLi4WpUzR09ODt7c3EhMTMWDAANF2qFGjBn7++Wf4+voKfkfHjh0RHByMz58/Iyoqiuf3VKpUCb6+vgxVNDs7m4eia2ZmhjVr1vDW3c6dO7Pv4LjStUHFxo8fz+PtdnJy4s3RGzduROvWrVnyViaTYe7cuWycx8bGon79+hgzZgyvr3HoxBkZGTA3N0fPnj1562r9+vVx+PBhqNVqWFtbo379+oIkiIWFBZYuXYo2bdpALpfD3NxcdO2XQp3+f6W67s+NP6lrXFxc8PbtW8EawOkvv/yCsrIyUe5z7T4vlmAxMTFhNIAcOm35/hocHMzGjFgCfcKECay/aFPycWpra8sSY9p+j7YOHToUaWlpOHnypKhdT08PPj4+khyfXL/y8PAQ+PnlVRdlS7169dC5c2fR+a1ChQoYOnQoAgMDRdvBxsYGvr6+ePr0qei4trOzw++//46srCx0795dkMxydHTE1q1bJRG3/9VCPwLSvy6cQy01GfTp00eSq6patWqYO3eu5G5X3759kZycLMjMGBoawt3dHS9evAAA+Pr68jr90KFDeRnL4OBgEGkmfU9PTwHa2MmTJ6Gnp4cmTZqIOlXXr18HEfFIzLXl8uXLkMvlOH78uKg9JiYG5ubmkrQu9+7dg729PUxMTNjupLYUFBRg0KBBMDExEeXyA4ANGzYwxEZtfjxOtCe9Bg0aCJy2wsJC3oQxb948wT04HitOZ8+ezXMgtUmoOa1SpQr279/PUHh1TVgmJiYwMzMTzXRWrVoV8+bNw/Dhw+Hk5MQjeDc3N8eWLVugUChw/PhxODs7Y9u2bQx6v1mzZgy9Lz09Hc7Ozjh69ChUKhWGDx+Obt26MQdUpVLBw8OD8VGdPHkSHh4evESGr68vI1p/8OABRowYwWuH/fv3Y82aNVCpVEhMTMTIkSN59oSEBEydOhXFxcVISEiAp6cnz56bm4sxY8YgIyMDcXFxcHV15e0MqVQqTJo0CfHx8YiNjUXjxo0FwcTSpUsRERGB/fv3w9raWgDTvnfvXqxatQp+fn4wMTHhkbYDGsS8UaNGoX379pDL5Th9+jTPnpGRgd69e7M+Ux4hWqFQYMCAAWynev78+YJgY8aMGQy1edSoUQJk5Y0bNzLk5379+gkQXiMjIxnRddeuXQX0Lk+ePGFZXxcXF0FAV1xcDFdXV9ZHYmNjUV44vkQ7Ozvs3r1bkOxZuXIliDS0HL6+vgKKnCNHjoBIkzzo378/9uzZw9sNiYuLY0mB6tWrY+jQoWxeAzT9lXPkZDIZRo0axUM+ViqVDPW5Tp06uHz5suA3tG3bFkSaBEv5HRBAQ83DzbdiCbtly5aBiNCrVy/RXczQ0FAQaRIKYgHl7du3QaTJpouhZ+fm5rIEidjcpVarWdKyVatWot+hTZeiHdxwsnr1at66Uz54j42N5c03o0eP5tlzcnIEjuuGDRt414gFUto8mVI7+ra2tjh37hzu3Lmjc37U09PjofKW12bNmsHR0ZH1B04rVqyIxYsXIysrC5s3b0aTJk14FSReXl6sT8XHx8PR0ZFReBkYGGDTpk2szYuLi9GiRQvGeVixYkVERkby2sHT05MltMzNzVllCCf+/v6sOsLCwgLXrl3j2Q8cOMDGrZmZmeD+cXFxzK6vr4+AgADeepabm8vj4OzRo4dgN5qjj+DG5tSpU3k+g7e3N28dksvl6NmzJ/744w/k5eVh4cKFksmBpk2b8nhvtdXIyAg+Pj4CKjZOa9eujX379iElJUXSZzp48CCUSqWogy+Xy7FgwQIUFxfzfmP5/hYbGyvJi8vNFVu3btXZH8Uqmcrrn+Eg/TNqYWGBdu3aCajnOHT6Hj16wN/fnwWP+vr6mDlzJrKystC8eXN4eXkhNDQUAwcOBJGGq5OrqvPx8cGQIUNw9uxZeHp6gogwd+5cNtcHBwfD3d0d58+fR/369WFsbMyCTQB4+PAhXFxcWOBpYWHBQ8kvKChAq1at2JixtrbmJQ7UajXc3NxYssrCwkIwj8+YMQP29vasD5VP7v3jH/9AgwYNWNtwVUKcREVFMSYGIs16Fh0dzexv3rwRBJTDhw/Hq1ev2DOWr9oyMTHBtGnTmG/l6uoqqL4wNTXF2LFjcfnyZYwbN0703crlcnTp0kUyCcRp+Xntv6sGBgY6eZ7NzMwwffp0nTR0/wqhHwHpX5eioiLe4iaTydCgQQMMGTIEq1atYllrzubg4ICRI0di/fr1uHTpEnJyctCxY0eYmprC1dUV8+fPx+HDh5GSksJKPSZOnIjhw4dj8+bNuHv3rsCpiYiIwJEjR9hnysv79+/x6dOn70J6l5SUSJbWvXz5EuvWrRPdOVQoFJg7dy6GDh0q+tm3b9+ibt26qFGjhqg9KiqKBe1iuwgcdxKRJltU3mncu3cvb2dxwoQJPHt8fDx69OjBG3xHjx5l9m/fviEkJISXbZXJZDxHoqSkRLRkZu7cuaxd3759K5qhItJk2NPT0/Hrr78KbDVq1IC7uzv8/f1x6NAh3o54r169cPToUfbOOecuLCwMcrkc06ZNQ3Z2NntO7Xe8e/duTJkyRXJnCNA4P7ooZtLS0nR+/suXL6L2d+/e4cGDB/j27ZugDP358+dYs2YN68vaJZffvn3DqVOnMGrUKMTFxaG4uJgXaCkUCkYsHxsbi+zsbEGg9fbtWwQGBiI0NBQJCQmiQcrbt29x6NAh7N27F0eOHBH9bWVlZRg7dqwoeT0nTZo0EdBwaEuHDh2wfPlyybHXu3dvndxqQ4YMwYoVKyTLOSdNmoTAwEBJ++LFixEUFCRZcrpx40bs2bNH0n7o0CHs27dPslT00qVLrNpDTOLj43HixAlJ+pvk5GScOHECHz58EG2Djx8/4tixY7h58yZSU1MF809ubi4OHDiA0NBQhISEYOfOnbzxUFhYiN27d2Px4sXw8vLC8OHDebyrX79+RVBQEDw9PWFubo5x48YJuHO3bt3KKh8CAwN5319WVobw8HC226PtqAGa8RgeHs7mlvJ9iaN04crHu3fvLrD7+/vz5gvteUmtVmPz5s28MtaGDRvy3ufVq1d5CSwifsJNqVTijz/+EJSwawe2OTk5aNmypWDu0t4F5Sp1yqunpyeKioqQnp6u86jBgAEDJEv/rK2t4ebmhlmzZvE4VZ2cnLBixQqWxFAqlSy4rly5MpYuXcpLQnDv9qeffkLt2rUFwR635i5evBj16tUTlC9r/9Z69epJUlUsWrQI9erVk3Tu1q5dCzs7O0maj127dqFhw4aSR0sOHjyIhg0b4sGDB6L2iIgI1K5dG8ePHxcdV1FRUahUqRIWL14suvPPJQfatWuHf/zjH4JrXr16BQMDA8jlcrRo0QKzZs3CsWPH2A5oTk6OYD2tU6cOevTogalTp2Ljxo2SZZpEmmCPq34R0x49emDhwoWSdnt7e+zbt4/t6IvpyJEjERwczKNy01Y9PT0MGzYM/v7+Osu827Rpw4ItKZXJZDA2Nhb8/8aNG2PChAkIDw/HggUL2P+vVasW5s2bh5s3b7Kx/PjxYzYWVqxYweYxbu4vKyuDpaUlPD09ef1K+/27urpi9erVPB9K2967d2/JjQdAM27ENg0ATQLU3t5esk8HBgaicePGktQogwYNgoODgySn/bRp01CvXj08fPhQ1P7bb7+hatWqbOe1vOzatQuGhob49ddfRX2WM2fOgEiTmHz06JHAzrV/jRo1sGbNGkFyMzs7m5U1d+nSBaGhobx1T6FQsAqNChUqYODAgQgLC2NVQWq1mtfnLS0tMWTIEOzcuROvX7+GSqXClClTeP2ndu3aGDZsGLZs2YK4uDhs2LBB0O8cHR0xevRobNmyRXTTpEaNGujTpw+WLFmCI0eO6OQ9/1cI/QhI/7qEhYXBx8cH27dvx+3btwWOV0JCAoKCgnDr1i1Rp6ywsBBJSUn/K854nj17VvJ3pKamonbt2pKcpREREdDT0xMQw3MSHBzMso1iHHChoaFsMrCwsBAErZGRkbxyrRYtWrCJuKysDFFRURgwYABv4bG1tWVZths3bmDy5Mlo2bKlIEs/f/58qFQqzJs3D3369EHv3r3h5uaGHj16oFu3bujSpQs6deoENzc3NGrUCF5eXli1ahXOnz/PI0YGNBn4n376CcuXL9fJq7Vv377v8nZ972zd9yQ3N5fXjiqVCo8fP0ZISAgmTJiAbdu2sTYsLCxEZGQkZsyYgUaNGsHW1pY5MWVlZbh79y4WL17MynWnTJnC7stxlY4ZM4YlFtauXcvsZWVluHLlCnx8fFhWfMGCBbxn/fDhA49ntF27drwgSa1WIykpCStWrEDLli1hYGCAGzduCILxzMxMhIeHY+TIkRgyZIhkmWhOTg4iIyN1ktcDmoBNl0g5lJyU33EUew5doivZAPy5s4//V0SlUiEuLk6SOP3p06fw9/cXPctfVlaGEydOoF+/fqJJvaKiIixZsgT29vai7+TZs2fs7GF5Z0itVuP48ePMwS9fafLt2zcEBATwSii1g8mPHz9i3rx5vOy4vr4+C5aeP3+OCRMmCEowzczMkJKSgm/fvmHKlCmiO1J6eno4e/YsLl68qDOD36xZM7i5ucHQ0BCVKlVCtWrVULduXTRq1AjNmzeHi4sLXFxcYGBgADs7O4wYMQK///47oqKieHPk5cuX0bBhQyxdulSyRHr58uVYuXKlJGdsaWkpFixYoLNE7fDhwzo5Z6OioniJjfISGhoqWeINaJxfXZ+/deuWTq7SR48e6cRUePz4sU57QkKCzvvfuXNHJ29jbGwsLly4IJnAPnnyJAICAhAREYGkpCRBIunQoUMYMmQIpkyZAn9/f2zatAnh4eE4f/487t27h6CgINStWxcODg5o3rw5nJ2d0alTJ/Ts2RP9+vVD165dde6Wc6orkCTS7GB/7x5iZw/lcjmsrKzg6OiIDh06sLFlaGgIR0dHeHp6wtfXF3v27MHNmzfx+++/w8DAAO3atcOiRYsQGRnJC2hKSkrQokULzJ49G7du3RJNMO7fvx9//PGHZII4JydHsBtfXr7Hxfm99URXn87MzOQlA8tLTEyMzjEVGBios0+GhISIVrhwsm/fPoE/pS0HDhxgO55Sdm1+8/Jy8OBBhIeHSyZfjx07ht9++00y4D579izGjx+PyMhI0Y2dW7duoXfv3li3bh0ePXok6AOvX79G+/btMXv2bBw5coSV6HOSm5uLjh07YtSoUdi0aRNu3LjBizmUSiUGDx7M5tbo6Gid7/PfJX82IP2BsvtD/pakpKTQly9fRDn2iIj2799Pe/fupUuXLknax40bRxs2bBCg3xIRPXz4kAYNGkTv37+nmJgY6tGjB8/+9etXWrNmDQUGBpJSqaSoqCjq1asX75oPHz5QSEgIhYSEUGZmJvn4+FBwcDDvmpKSEkpISKD79+9TXFwc3b9/nzw9PSkgIEAnBP33oN+JNHyh+vr6krQv/69EoVBQQUEByWQy+vDhA7169Ypev37N/r5+/Zp8fHyobdu2dO/ePbp37x7dv3+fvnz5QkQaLtFJkyZRbGwsxcTE0O3btxnypIWFBV29epUyMjLo1KlTdPr0afr48SP7bldXV4qKiqLuVGJFAAAgAElEQVRbt27RkSNHKCIigvLy8ph9wIABFBERQfHx8XTo0CE6fPgw7/MdO3aky5cvU25uLo9nlBMrKyuKj48nGxsbunfvHp08eZJOnjxJycnJ7Jrg4GDy8fEhhUJBd+7coaioKIqOjqZHjx4RkQbZ7/bt21SlShUCQCkpKXTz5k3GK/v8+XPy9fWltWvX8t55dnY2PX78mJKSkujVq1c0b948Sf5doj/XJ37I/xwBQN++fZOkLklNTSWlUimKkKtWqykkJISePn1K//jHPwT2goIC8vPzox07dlBSUhI5Ojry7BkZGeTn50d79+6lhg0b0tOnT3nopFlZWbRhwwbatm0bFRcXU48ePejixYus/xYXF9Px48dp7969jA6mbdu2dPPmTTIwMCC1Wk1JSUl05coVunLlCl2/fp3y8/PJxMSEYmNjqX379gwBmKNseP/+PfurVCopKCiImjRpIto2eXl5DPVSSgoKCqhSpUo659mysrJ/+vz5Q/69UlRUREqlkuRyOclkMoHK5XJ6+PAhlZSUMEof7v9zqlarKTY2luRyOdnZ2ZGZmZkAfbWkpIRiYmKoRo0aVLt2bbK2tiYrKyuqUqUKm7eTkpIoLS2NGjZsSHXr1hVFBE5KSiJ7e3vJeUGhUPD4Tf83ilqtprKyMlEU4h/yfQF0Uxx9z/4/RX7QvvyQ/xg5ceIEDRo0SHJgRURE0MmTJ2nfvn2i9uzsbBo2bBg1bNiQdu7cKXrNy5cvacaMGaRUKunq1aui1yiVSjp9+jTt3LmTFixYQL1799b53Hl5eWRqaspg2v+qKBQK0tPT0+lQ3bp1i+RyOZmamjKtWLEiVahQgeRyOZ09e5Y5ixx/njaX3ufPn0mhUJCZmZko/YFcLqcqVaoI6Eg4adu2Lb1+/ZoXRHJibGxMU6ZMob1791JBQYHAXqdOHZo/fz6tWrWKRwnDib29Pa1evZr8/Px4ASQnVlZWFBoaSuvXr6dr164JeEblcjmFh4fTzZs36fTp06Jcp+PGjSNnZ2eKioqiy5cvC9rAysqKdu3aRampqSwA/fTpE++aKVOmkI+Pj4BnlKOKqVChAkVGRlKbNm3o3bt39O7dO3r79i3vr7m5Oe3Zs4cHv65QKCgvL4+po6MjVa5cWfAbfsj/XsnJyZHk0SQiunv3LsXFxdGsWbNE7ffv36fZs2fTtGnTaNSoUaL337x5MwUFBVFoaCgNHDhQcE1KSgqFhYVRWFgYeXt705o1awTXlJWVUWJiIl29epUSExNp1apV/3Qqge85XaWlpWRoaCh5TWFhIZWUlFCFChWoQoUKgnk2Pz+fMjMzSaFQiGpBQQHl5ORQfn4+1alThypVqkR5eXmUn5/PNCcnh1QqFY0fP54MDAwYZ6K2WllZ0a+//kplZWX0+fNnpnl5efT582cyMTGhiRMnCoIbtVrNaF6qVq36v8IB/SF8uiUxyczMJGNjY0namYSEBCosLKTq1atTjRo1BJQhkZGRVFhYSMbGxmRkZERGRkbs30REly5dIrVaTQDI0NCQlEolKRQKKi0tpdzcXEpLS6Pi4mJq2LAh2djY8Pr8p0+fKCcnhypWrEjDhg0jmUzGoyv79OkTZWZmkouLC02YMIEKCgro06dPTLOysigzM5N69OhBkyZNosLCQh7HKPfX3t6e5s6dS2q1mr58+UJFRUW8v6WlpdSzZ8+/7YP9kH+v/AhI/4YAoE2bNtHo0aPJyspK9JrIyEhydXUV5Q0iInr69CnZ2dlJZoYLCwvJzMzsx+Lz/0tiYqLkLiuRZnLfuHEjzZ8/XzKwA0BHjx4lZ2dnHmeeGB9qXl4ee3cPHz6kJk2aSHKabd26lZo0aUKdO3cWfV9hYWF0+fJl8vT0pF69egm+q7i4mNq1a0d6enrk5OTE1NHRkWxtbUlPT4+OHz9OQ4YMEf1+ExMTMjExoeLiYkYGXV6qVatGPXv2pP379wtspqamdOzYMXr16hXNmTNHYB85ciSFhYXRzp07aebMmTybTCaj48eP08CBA2nPnj0CrlQTExO6ffs2NWvWjI4cOUKjR4/m8fmZmJjQ3bt3qWnTpnTu3DkaOXIkL1iUyWQUExND3bp1owsXLpCPj4+ANy0gIIAWLVpEJ0+epPnz59Pbt295dldXV4qOjqY//viD/Pz8BEGziYkJXbhwgY4ePUrbt28Xbb9hw4ZRSkqKJM+omZkZOTg4UHJysmjQTkTk5OREderUoaKiIsrPz2cBKMfzZmBgQH369KHWrVuzzHJZWRn7t1KppLKyMho0aBBVqlSJl5wwNTUlAwMDys3NJTMzM8m++kP+58qfyZY/ePCA2rRpI3lNXl4enTlzhkaPHs3uVf6+arWarl69Ss7OzmRqakoFBQU6EyRxcXHUokULyV2Q3bt3k4uLi+Qu6Zw5c6hatWo0atQo0eB29+7ddPjwYerUqRO5urqSs7Mzbw599OgRubm5kY2NjYCD1NbWlkxNTal79+705s0bIiIyMjIiU1NTFqAaGRlRamoqj/+4vMhkMtLlC33PbmJiQnK5XPI7LCwsyM7OjpRKJX39+pWn3759I2NjY3J1dSU7OzuWvNTWN2/ekFwup65du5KVlRVVrVqV/bWwsKCcnBw6cuQINW7cmBo3bkw2NjaCvnT8+HGqVasWtWrVSvRdPnnyhDIyMqhr166igZRaraawsDAaPHiwIDji5NSpU9SwYUPBTj8nT58+pXv37tHYsWMl1/E1a9bQqFGjqE6dOqL2rKwsio6OJm9vb8ndx0uXLpGdnZ0kd65SqaTw8HAaPXq0ZLCzb98+qlu3Lrm6uoqOy6ioKIqJiaHhw4dT69atBdc8evSIxo4dS127dqVu3bpR586decHnmzdvqGnTplSlShVq2rQpNW3alJo0aUJNmzalxo0bU3p6OrVq1Yry8/OJSLOO16hRgwWoMpmMTp48Kcqd/WdEX19fknuXSNOny3N+c8K1e/nk8Z+1ExFVrFiRDA0N2c54eTEyMqK6deuSsbExC6zVajVbLz99+kSVK1em5s2bk7m5OS+Rb2pqSklJSfT06VPG6WpjY8PToqIimjdvHjVo0IAcHR3Z2OH6NgCaM2cOmZiYULt27ahdu3ZkbW3Ne8YjR47QnTt3qFevXtS5c2eB75eWlkZLly4lLy8v6tmzp2DdBjRcp+3btycPDw/Rdf2PP/4gPT09Gjp0qOhu/L179yg+Pp7GjBlDpqamku3975QfPKR/U8aMGQNjY2NMmzZNlI8rMDAQZmZm8PX1Fa3ZjoiIgI2NDbZs2SJaW/7gwQM4OzsjJiZG9MxXTk4OfHx8JM9nAprzB7o47L53tkAXpQsn3+PR+579exx7AHSeQQDAo8sRa6vw8HCd91i/fj1CQ0Ml7UFBQWjWrJnk2UKOD6tjx46Ijo4WPMOXL19gaWkJIg1K24ABA7B3717e2Y1z586JnmUxNjZG8+bN0bt3b50Q43Z2dqI8nUSEbt26Yfv27QydVVutra0RFxeH/fv3CxDliDQQ6UqlEidPnhTlOd2yZQsA4Nq1a6I8eBx40LNnz0QRCvft2wcAyMrKgru7u8C+cuVKAJozc2Iw7gMGDGCgJOWBrog0AAAcwuu9e/cY2BinMpkMp06dAqBB0RWj0PHy8oJSqURBQQFDwNVWS0tLPHz4ECkpKQK+RE5nz56Nz58/M4Tb8mpra4u4uDhJvkOOvkAKtZRIQwEUEBAAmUwGCwsLODk5oUePHhg1ahQWLlyITZs24cGDB2jZsiU8PDywaNEidt6JOwdUVlaGmTNn4rfffkNUVJTomeQTJ07g6NGjkmPq9evXuHPnjuRZVaVSqZMuBdB9bgkQ59vUFoVC8bfnnu/Z/wwGwPee4Xv30AUuxt1f1xoAQBTgS1t+//13nWfPfX19dc6Pq1evRps2bSSBMXbu3MnQksXOR3PAIjKZDN27d0d4eDjvLKRCoWDn0Ik0yJEuLi5YuHAhIiMjkZOTw1CRpfR71Fpdu3aVRMZv2bIldu3aJYkwO2/ePOzatUvUpqenhw0bNmDWrFmS43rp0qXYvXu35LN169YNkZGRklQdhoaGWLJkiSRQj1wuR61atdCuXTtee7Rt2xZjx45FQEAATp8+jaCgIBBpUELd3NywevVq3Lp1i52fKywsROXKlVG1alVMnjwZly5dEvTfESNGwMzMDDNnzhQFZ4qIiIBMJsPQoUNF8RBKSkpgZGQEJycnnD17VnQOmT59OoyNjbF06VLRM7NqtRpWVlZo27Yt47kW63OGhoaYN2+e5BnFzp07o3bt2ti+fbvoGXCu3zZr1gwhISECIL+SkhJUq1aNrc9+fn4CH0KbPkUul6NNmzZYvHgxoqKikJycLAn4JZfLUbduXUnucU7FeLG1+7zU5zt16oSNGzeK8pAaGRlh27ZtkoBm1apVw7Vr1yTZKKpXr47r169LojKbmJggLCwMM2fOlHz2YcOGYe/evZJ2MzMzrFq1Siftio2NDRo2bChpNzQ0FAVk43hIZ8+ezQOlItLQA3l7e2Pr1q14+PAh8vLyGBeskZERevbsiQ0bNuDJkyesb3Pgc5UqVcKoUaNw+vRp3rzPAXxWqVIF06dPx/3793nj4v79+yDS4KjMmzdPcGa2uLgYpqamqFKlCnx9fQXI/P8JQj9Ajf66nDlzhsdZKJfLMWzYMIYElpyczCDkiTRBxcyZM9mB5PI8TjVq1MDmzZt5AeCmTZvYAti5c2fBwevo6GhYWFigQoUKWLZsmQCs4eXLl3B0dESLFi1EUQMLCwvh6emJadOmSQae69evF8D8a8ubN2+wZMkSSXtBQQGWLFki6dgVFRVhx44duH37tqi9rKwM8fHx8PT0lPyOpKQkODk5SQLFXLt2DZ6ennBzcxN9jitXrmDEiBEg+q/gSlvu3LnDoLkNDQ2xYcMGnpP57Nkz3kJPpCF3P3PmDNRqNbKzs2FnZyfqTOjp6aFz586M/uGvaJUqVQT8mdr9cuXKlTxnSNupsre3R0pKCrZv3867H4e8OWjQICgUCly5coW32HATLIfamZaWxpy5qlWrskn+l19+AaBxKDmUTFNTU0ZPMHXqVNaOXDAql8sZSFGfPn1YW2sjFTs6OrLn5wARzp8/z+zawT83JjMyMtjv0obl5965Wq1m99XWPn36MIds0qRJAnuNGjXw9OlTAJoEkNg72Lp1KwAN8rUYBDvHdwiI02jUr1+fQeqvWLFCYDc2NsbKlStRUlKCixcvijrfvXr1woMHD/DhwwfRRbhq1arYtm0bVCqVgOqoUaNGGDNmDG7dugUACAgIYH2pY8eOWLNmDR49esQWyRs3bjDk8ZUrVwoAHzIyMlCnTh307dsX165dEzidCoUC/fv3x/jx4yUBK9avXw8fHx9JEJekpCQMHDhQ4CRykpubi7Fjx0o6oyUlJVi2bJnOwPnkyZOidCucZGVlYeHChZL2vLw8HtWCmD0gIEASdEOhUOD8+fPo16+fqOPOcWRWrVpV8h7nz59Hx44d4erqKolCyRHcr127VvA9sbGxrL9UqFABO3bs4F3z8OFDBtxEpAFWmjJlCqNk+vDhg2iSp2LFihg3bhxiY2NhY2MjQAP+76iuYNTJyYkR04uNXX9/f8lg0dzcHKdOnUJ8fLyonXO8v379KvoMlpaWuHDhAgAIOC25tuLQtH///XdROpEOHTrg2bNnuHHjhiTa+6hRo/Ds2TMeB2h5dXV1Rc+ePUW/w8TEBN27d4eHhweb+zm1trbGtGnTcPXqVVy5ckWAotujRw+cOnUKKpUKubm5gt/p5eXFSyiPGjWKBzrUpUsXHsIrx/PJ2W1sbBAeHs7WifDwcHh7e/OC85EjRzLf686dO+jXrx8Prdfc3ByBgYEoKSlBdnY2OnbsiMmTJ/PQT2vVqoWtW7eipKQEnTp1gru7uwCB38LCAgsXLoS7uzt++ukntGvXThT0y9LSEqampjA1Nf1bHLt/VR0dHSWpQIyMjLBx40ZGUVRe7ezsEB8fz+Nx1dZ27dohPT1dFNlV267Nba6t9vb2ePz4sSR/u4mJCXbv3g21Ws2bV8r3uXfv3gmQyjk1MDCAr68vjh8/LoqCTKSZfxYsWKATtM3Q0BA1atTQSfOjr68vmeiqVasWunbtKho0m5mZYeTIkQgKChL1S5ycnLBu3Tp8/PhRlHqmR48eiIiIgFKpxLRp03hzg56eHoYPHy6JJv7vEPoRkP51keroXEeQytYaGBhg4sSJPAdfW6tXr46NGzfiy5cvootLr1692ORcntLE2toa27dvZwipS5cuZTaZTIbJkyfzsuCRkZHM3rRpU+ZUc5KSksI6+dKlSwWOSHFxMVucxIjb1Wo1WrZsCblcjt9//120HYcNGwZ9fX20atVKdCdhxYoVbMIW4+rT/g2Ojo4Ch+rNmze8Sa08mq9KpRIM9t9++433W8tDbhNpMosc6ibH+ymmLVq00Jn5/p4aGRlh/Pjx6N+/PwwNDdGpUyfWHjKZDJMmTUJ2djaCg4NhZmaG8ePHw8fHh/WlK1euANCgL5qZmWH+/PlITEwEkSZo5hAfi4qKUK9ePSxYsACfP39G3bp10b9/f+Yoq9Vq9OrVC1OmTEFeXh569eqFoUOH8t6Zv78/PD098enTJ8yZMwf9+/fn2U+fPo22bdvi9evX2LlzJ9q2bcvLOnMJlBs3buDixYuoXbs2bwe5sLAQzZs3R2hoKB4/fgwTExPGqcY9o7u7OxYuXIhnz56BiHDw4EHe+160aBHc3d1x9uxZEGl2LbXlwIEDcHBwwOzZs0GkSQRpJ2sSExN5CYC6devydnwKCgqYs8EtKpzDyUnz5s2ZXV9fHxs2bOD1t9GjR/P67LRp03i7gevWreMlNzw9PXkBX/mA1MXFhfUDQLPzqL0A1q9fH9u3b+cFbtqk6JUrV8bUqVN5sPscTymnzs7OCAgIYEi169at49mNjY3h7+/PvuPcuXO8BdTZ2RknTpxg/SU5OZk5CmZmZvj99995fUWhUDBHoWHDhqII3NxOdNu2bUV3W7lx3apVK9GdXo6P0NbWVhQZlZvDK1asKIrimJaWxt6jdvtzUlpaCltbW8jlch66tLa4ublBT08PTk5OolypCxYsYM4QV2mgLQcOHGBtXLNmTQEa5rNnz3iopYMGDeLteGknkjidMWMG7xptLlRO3d3dWZtL8ToaGxtjwYIFkmuhtupy+GrVqiVamcG921OnTuHXX3+FXC5nu1Xce9uwYQMUCgWioqKgp6fH4/G0t7dnidJPnz7B0NCQcdsSaWg/uHGnVqthZ2fHQ3R3dXXl7VwPHjyY5/y6uLjwEDNXrVrF241q0KABL8l69uxZnmNbsWJFbN26lY2Zt2/fCtqpW7dubNyq1WpB4lMul2PIkCG4e/cuAAgSq5w2b94c69at4yXRxVRqh5abK6V2+4g0SbmrV69K2ocNG4bk5GTJ7+B2Q4cMGSJqNzExYUjMUt9Ru3ZtLFmyROdv1EVh9M9QscCR49Y0NTVFhw4deP3G0dERJ06cgKWlJaytrTFy5Ei2HlSoUAGBgYFQKBTo3bs3atSogRkzZrDPa1eBLVu2DFWrVsXEiRPZvQcPHswSwGfOnIGpqSmP+mbatGnMZ/jw4QOMjIx4/tXkyZPZPK5SqVCzZk2WPCbSrGXaiLu9e/fm9fmffvqJR6nk6+vLC+grVqyI4OBgtp6K+WY9e/ZkO/dPnjwR2Ll5KTs7GyqVSjSYtLS0xNKlS5GZmSnJS8vtZuqiIDIwMBBNxv139HuI0jVr1tSJKt2uXTscPXr0T1Uq/jOFfgSkf11evnwpWZpHRLCysuItfuXV3NxctHxSe+ANGzZM8rN+fn5Yu3atwGZmZoa+ffsiJSVFkKEyMDCAvb09c5D37NmDypUrsw5tYmKCkJAQNpgjIyN5JaIzZ87kBRjR0dGoWrUq+2x8fDyvjaKjo9kCaGxsLCjnio6Oho2NDbt/eS7Su3fvolOnTsxenjqhoKBAwO9Znhbk6dOnguxTcHAws5eVlWHQoEGCdtTmGY2MjBQd9JUrV8b+/fuRmpoququlrXXr1hU8h5WVFUaPHo2DBw/i+vXreP/+PWtvKysrLF++nJWaZmRkMG5OIo0zpJ01/vr1K3P2ly5dip49ewqccG4nKT09He7u7oKdJe22nT9/vqBESXvC2r17tyD4V6lUrM2ioqIE1ABqtRrx8fHIz89HQkKCAL7806dP2Lp1K969e4ePHz8yJ4mTDx8+IDAwENHR0fj27ZuA+7G0tBRnzpzBpk2bUFpaCn9/f5SXb9++4dq1a0hISICnp6eg3EytVkOhUODy5cto27atKEXE169fsWTJEjRq1Ei09OXLly9o37496tSpI1riXVJSgl69eqFWrVpsx1FbFAoFvLy8UKdOHcTExAjsHE+qnZ2daJIG0BCKOzk54dSpU6I7Z0uWLEGbNm1w7Ngx0ZLRtWvXonPnzggPDxfdYdy1axfc3Nywfft2UbqUyMhIuLu7Y+3atbh586agr9y9exf9+/fH/PnzsWvXLly7dg0ZGRnsWV++fAkPDw94e3tj2rRp+OWXXxAREcHs6enpGDhwILp06QJnZ2e0bt0aJ06cYPfPzc3FwIEDYWtrCz09PdSrV4+XcCsqKsLgwYOZI+bi4sJ71yUlJRg5ciQbqx07duSNBy7rzNlbtmzJs6vVaqxatYrZbW1tBeMtJCSEfb+JiYng+AR3pIO7R/mk3oMHD9C1a1eeA6S9m1xaWorVq1fz5pzevXvz5vAXL14InJWpU6eydlYqlYLdciKNY8q903379kmugadPn8bLly91lsVVrFhR8qhBkyZNMHnyZCxduhRubm68z4wbN46VjCYnJ+Pt27fMeXdxccH58+fZ78jJyUF+fj7mzp0LIsKIESN4/VahUCA3NxcXLlwAkYaeqvz7ys3NxcOHD0GkSWSV39X+/PkzS3TNmzdPkEDIy8tj70Ps88XFxdizZw+INJza5UvSFQoFTp06BSJNwF9+/lSr1bh27RqINEHJuXPnBGOf41Q0NTXFrFmzBH3u9evXLGi2tbWFn58fb9y8f/+e59dYWVlh+PDhCAkJQWpqKjIyMnjJLE4tLS3RrVs3TJ06VXLnTXutlLLp6+uja9euOncVu3TpItpnObW2tsbgwYN1BgI1a9ZE//79JXcRiTS+lthvLf+8YveoXr06evfujeXLl2P8+PG86/v06YOtW7fi5s2byMvLw+3bt0GkScr069cPMTExUKlUePbsGVQqFTIyMli7hYWFsfn8/fv3UKvVKCoqgkwmQ//+/XmUcllZWSgrK8Pnz58hk8ng6+vLm8MKCwtRWlqKly9fwsDAAP/4xz94/UmlUqGwsBAXL16EkZER9u7di/KSl5fHeEBDQkIE9s+fP7NkUWBgoKC/5ubmsp3s6dOnC9aR/Px85ud2795dQJlXXFyMQ4cOgYhE+XlVKhUuXrzI2l67coOT+/fvs6RdgwYNsGPHDt6a+PTpU5YclclkcHNzw+HDh9mzvnr1iufrm5iYYNCgQdi/fz/y8vLw/v179O7dW9C3PDw8EBQUhDt37mDcuHGi82aPHj3g5+fHW6vK34ejTZLqo1WqVIGrqyvWrl37Xbq4f6bQj4D0r8uWLVtgYmKCZs2aYejQofD398e+ffsQFxeHvLw8nDhxAjVr1oSrqyvGjRuHlStX4sCBA7h79y6ysrKQmJiITp06wdvbG7/88guCg4MRHR2NFy9e4OvXr8jNzcWcOXOwZs0ahIeH49KlS3jx4gVbpJRKJY4ePYro6GjEx8fjw4cPgsGalpaG7OxsfPnyRec5JbVajZKSEmRlZSE1NVWwUObn5+PWrVsIDg4WlNYqlUpcvnwZM2fORMeOHVkAxUl6ejr8/PxgaWmJTp06CXZBr169ypwqa2trXnastLQUISEhLBtIRFi9ejWzf/z4EcuXL+c5bTKZjJWmFRUVYfr06YKMpr6+PtuxCAkJkTxj8PPPPyM9PV20XKL8AiiTyaCnpwdbW9v/j73vDIsqy9ZeRY4SBQEJogiKqI2ooAgGbBTF1jYHtM0559Da5oxgaAWMqIgBFAUjKCjYBhBtE6ggbWxBJWeq3u9HTe3L4ZxTzJ25M9P3fq7n2Q+lq8I5++ywwl7vi+7du2P8+PFYt24djh8/jtu3b+Po0aOQSCRwd3fHmjVrcP/+fV5fpKSkwNnZGQcOHBCtG0tMTERoaKjSurTU1FSl+oqKinqjYUJOTHV1NdLT03mcYTU1Nbh79y7Wrl2LyZMncwypmpoa3Lp1C/PmzYO9vT3niC4g33D2798PHx8fqKioYMmSJRx9Xl4e9u7dCy8vL7ap1r43RXZj3LhxMDIygoGBASPYVtxDcXExoqKiMGbMGJiYmGDEiBGQSqWcTUUmk+HZs2fYvXs3BgwYgD179oge5ayqqsKWLVuU1mFMnDhRKTfawoULlXK3bdu2TZTrD5BHfpXVFiYlJSmd85mZmUq5SOvjsv1PR1P/O1JdXY3s7GxBYvXKykrcvXsXwcHB+PXXX3l98vbtW+zduxd+fn6YNm0aT//w4UPMnz8fjRo1EuRSvn//PsaMGQNNTU3MmDGDp09OTmb1Q7179+Z8v1QqRXR0NMvK6ejocAyuwsJCBAcHo1mzZmwtGjhwINNnZWVh/vz5nPWR6L+4fouLizF27FhOhkLRFHXbO3fuFK1b9Pb2xu+//y6anVQ0RaZaVVUVlpaWcHNzQ79+/TBlyhSsXr0aISEhaNq0KTQ0NNClSxcsXboUcXFxnDFYXFwMY2Nj9OrVC8ePHxcMksTExMDLy0sUcwEAxo8fr5Qj+OTJk4iLixPVJyYm4syZM0o/f+rUKVH9smXLlOqDgoKUfv+BAwdw4sQJ0fs7duwYQkNDRednRJ4CDZIAACAASURBVEQENm7cKDq/jx07hunTp+P27duCv3H8+HH06dMHgYGBePToEW+fiYqKgoODAwYPHox169YhNjYWb9++Zd+VkpICDQ0N2NrawtvbG2PGjMGqVatw6NAh3LhxA8nJySzIraKiAjMzMzg7O6Nbt24YMmQIpk+fLlqe0qBBA9jY2MDZ2VlpCYy6ujqMjY1Fj4BramqicePGgo6xoaEh2rRpgx9++AGzZs3iZGutra3Rp08fLFu2DCdPnsTz589ZgMLc3BzDhw9HaGgoXr16xQn42Nvbo0ePHggLCxPkA128eDFmzZrF9rW6cuXKFezcuVPUmcjMzMTZs2dFx8zr16+RlJQkqAPkpyhqB7/rSlJSklJe7SNHjvCCy7Vl5cqVgidIFDJlyhRER0eL6hcvXswrE6gt69evx7Jly0RLO4KDgxEQECCIAwPIj4B7eXkhJiZG0K66fPky7O3tsXbtWl6QCAAePHgAAwMDjBo1CtHR0by1682bN9DV1YWHhwdWrlyJW7ducYJZBQUFMDc3h52dHUaOHIk9e/YgPT2d7e9VVVVo1aoVjIyM4OPjg0WLFiEyMhIvXryAVCqFTCZDr169oKenB3d3d4wfPx47duzAtWvX8OHDh78MJ/nf65B+Q9kVkNzcXDI1NRVFcPv/kRMNABUXF1ODBg14uvLycjp+/Dg1b96cvLy8ePpbt27R6tWrqU2bNrR9+3aOrqamhk6ePEnr16+nnJwcysjI4KDrVVdX04ULF+jXX3+lhIQEsre3p0ePHpGenh4RyVHcUlNT6cKFC3T+/Hn6/fffydjYmO7du0dNmzYlAPTp0yd68uQJPX36lJ48ecLa999/T4cPHyaJREKVlZWMBkDxurKykjIzM8nc3Jy8vb1FIdzT0tLIzs6OTExMRPsvPz+fDA0N/+2oyqWlpfTq1St6+fIlvX79mkaPHk3m5ub07t07xkV69+5dSk1NpTlz5tC6desY5+vVq1cpPj6e8vPzqVGjRnTnzh1q1KgRXb9+nc6ePUsxMTGUm5tLREReXl507do1qqiooJiYGDp58iRdvXqVoed169aNrl69SuXl5RQTE0MnTpygq1evMpQ/Ozs7evDgAenr69ONGzfo1KlTFB0dTV+/fmX3cuHCBerbty99+PCBLly4QDExMZSQkEBVVVVEJKeuSUxMJG1tbXrz5g0lJCTQ9evX6fr164zzdPny5bRu3Toiko+958+fU1paGqWmplJqaio9fvyYgoODacKECZx+BEBfv36lrKwsys7OJj8/P8G5oHjvN/Ts/11SWlpK6urqgoibNTU1FB8fT+3btxec43l5eXTw4EEaOHCgID/t8+fPaevWrdS/f3/q168fRweAkpKSaNOmTaStrU1nz57l6GUyGV2+fJmCg4Pp6tWrdOrUKQ4at1QqpcTERDp+/DidOXOGysrK6MaNG9SlSxf2+cePH1NCQgIlJCTQzZs3qaSkhMLCwmjChAkEgD58+EAvXrygFy9eUGZmJnutp6dHp06dIhMTE6qsrBRsmZmZ1KxZM+rcubPgnvj582d6+fIlubq6iiJDf/r0iQBQo0aNBPVEcuoWMXqM2n31r+R8rG9eV1ZWKkW/ru/6/tPrRn2/Xx+NydevX0lfX18UjfmPP/6gsrIyatiwIRkbG/P64vPnz3Tz5k0yNDQkQ0NDMjIyIkNDQ2rQoAEbW3fu3KEHDx6w99R9r5aWFh0+fJg+ffpEDRs2ZByjitd6enpUXV1N69evJxMTE7KzsyNbW1uytbXljK/MzEy6cuUKtWnThlxcXMjY2Jh3PwkJCWRpaUlOTk6C/aagIzI3Nxfts+rq6v/THJ712crl5eWiPK5ExBCo/9HPl5SUMFtRSOpbV+rzBT58+ECmpqaiSM0fPnwgXV1dURTz3NxcqqmpIUtLS9HrKygoIFtbW8ExVllZSX/++SfZ2Nj8pW2Ob7Qv3+QvJ8roA2QyGZ07d44yMzNp6dKlgp/PzMykffv2ka6uLnMq6soff/xBFy5coKysLNqwYYPoYgWA3rx5Q5qamkoNob+CyGQyKioq4vDiKVphYSHl5eXRmzdvKC8vj7777jvKy8ujly9f0suXL5kjpqWlRcOHD6eCggK6e/cu+3+FDBgwgKysrOjatWuUmZnJ0enq6tLPP/9MDx8+pIsXL1JRURFHb21tTStXrqSLFy/SxYsXedQ0lpaWtGfPHoqIiKDY2FgelLyGhgZzcKOiogS5UpcvX04NGjSg06dPC1KzWFlZ0ZYtWygpKYkSEhIoKyuL957BgwdTnz59KC0tjdLS0ig9PZ13LZs3byY3NzfKysritOzsbCosLCQtLS2KiIigfv36Mf5XBc+g4m9VVRVNmDBBlBrhm/z/KfUZV+np6WRjYyMa2MrIyKBTp07RggULePQCRHLjLDY2lm7cuEEbN24UNIKqq6vp3r17lJSURAEBAUo5RquqqqikpETQGP+/LFKplMrLy6miooIqKirY6/LycjIzMyM7OzuqqamhsrIyKi0t5TRra2vBPpXJZGxdVGZAf5NvQlR/cEAqlZKKioroexR2fe2/df9PMSYrKiqoqqqKR0dUVlZGxcXF5O7uTkTE4T9X/JVKpTRmzBiqrq7mcG0raM+qq6tp4sSJpKOjQ8XFxVRYWEhFRUWcvz4+Pjx6RalUyuafmpraN97u/+XyzSH9J+XcuXPk5+cnGvlIS0sjFxcXUf379+/JzMxMNPpVXl5O6urqSiOO/+qI719R/p4ocXl5OWlpaYny7NWVr1+/KjWqkpKSyNPTUzCSB4C2bdtGfn5+5OzsLPj53bt3U1lZGfn4+FDbtm15zyw2Npb27NlDDg4O1KxZM9aaNGlC6urqlJaWRj/++CMRyY0VLS0tzt+qqiq6ffu2KCcYkZyzS4yj1MTEhBwdHen27duC+ilTppCGhgbt3r2bxxumqqpK58+fp0+fPtHy5cvp48ePHL22tjalpKSQRCKh5cuX08WLFzl6NTU1SkxMpDZt2tDOnTtp48aNVFJSwnnP3r17afLkyXTt2jWaO3cuPXv2jKP39fWluLg4ys7Oprlz51JcXBzvGm7dukUWFhY0e/ZsOnPmDO8e/f39KTAwkMaOHUvJyck8vUQioaVLl9L+/ftZ1reu6Ovrk76+PpWWlvK4ThViYGBAXl5ebAOtvb6WlZXR27dvqXnz5jRkyBAyMTEhQ0NDMjAwIENDQ9LT06O0tDQyMzMjS0tLwbWhPqfmm3yT/67Ul8V49+4dNW7cWFR/7tw56tWrl+C4lEql9Msvv1DXrl3Jy8tLcD/csmULff36lTp06EDt27enxo0bc9bzq1ev0ubNm8nGxoZsbGzI1taWvbaxsaF3795R//79iUjObVi3AaDo6GgqKSkhNTU1zr4BgKRSKVVWVpJEIiEVFRVRbkZdXV3S0NCg0tJSdiqjtlhYWFDDhg2ZkV/boa2qqiILCwtq3749aWpqco6pyWQyysjIIFVVVerRowdZWVkxTkUdHR3Gqfju3TvG8angUjQwMCCJREK5ubl07NgxatWqFTk7OwvykB4/fpysrKzI3d1d8Fmlp6fThw8fyMfHRzDTW11dTUeOHKHBgweLOgjR0dHUunVrwZMCRHK76ePHj9SnTx/RPTsyMpL69OkjGtDLyMig6upqcnFxEdQTyffcXr16idpXt27dYuNISF6+fElPnjwhf39/we8oKCigHTt20MCBA8nFxYV3L2VlZTRt2jRq164dde/enVq2bMl5T3FxMQ0cOJDMzc2pdevW1KZNG2rdujULjn/69Il8fHxIXV2dGjduTI0bNyZra2v2uqamhkaNGkVVVVWkr69Penp6nL/l5eV0/fp1pTyj9Ul93LtqamqkqqoqandoaGiQoaEhlZWV8fZ8Irlt0bhxY9LS0uIFgBQnq0xMTKhly5akqalJEomENSKirKwsKikpIRcXF3JwcGD7s6JlZ2dTUlISWVpakqurKzVu3JisrKzI0tKSrKysqLq6mmbNmkXW1tbUokULatmyJTk6OnKCfdu3b6fCwkJyd3cnd3d3nh3522+/UUxMDPn6+lLnzp15/kBZWRmtXLmS/P39RW3M7du3k6urK3l7ewva+9HR0aSrq0s9e/YU1D9//pyysrLIz8/vL+svfOMh/Sdl7NixSjmqdu3ahSZNmiA8PFywnis5ORkODg6i5/vz8/PRtm1bJCYmil7DiBEjRLkxAXkNUN1C79py8+ZNpXx/Hz9+rJfjTtn3AxAEPaktb968UVqTVlJSwkFWExIhhMnasmDBAqX3MW7cOAQHB4uep58+fTpat26Nq1evCuoVqMudO3dGeHg4j0bn+fPnDBjJ2NgYgwYNwr59+/Dy5UvGodm7d29ezYqqqirs7e3x/fffcyDohZq7u7so2ENAQABu3rwJPT09ns7BwQFZWVl4/Pgxr96MSA4mIJPJkJmZyYP0JyIcOHAAgLxmWah4/sSJEwDkNW910VmJCEFBQQDk9TQ///wzDyly5MiR7LmcOHGCx6tma2vLam8ePnwoCJqhQIH+8uWLIGqyh4cHSktLIZVKceTIER6ynkQiYaAN165dE+xnBwcHvHz5kocwW7sNGTKEA9RVt6mrq3OQPIXGg4WFBXtta2sLLy8vBAQEYMWKFQgLC8OOHTtgZmaGHj16YO7cuTh48CBSU1PZmCwsLES/fv2wfPlyXLp0SbBWNTAwEJGRkaI8o8nJybh7967ofPn06ZNozZNChOptaouyGloAolQpCpFKpf80R/I/yyEK1F9vW999iNU+KeTr169KwShkMpnSGi8A2LNnj9J7HT9+PAfRuq4MGjQIM2bMEK27njx5Mg+orbYoUOmNjIwwZswYxMTEcNbQly9fcpBEGzVqhH79+mHt2rW4cuUKPn/+zKi7hJqZmRkHi0CoWVlZcRCH6867n376SZCTkUgO2rNq1SrR9dfc3JwBKgk1bW1tURDD2uu72O8TyWsuhTgntbS0YG9vD09PTw4KsKGhITp37oxJkyZh586dSEhIYKBKinreFStW4Nq1a2wMFhQUwMDAAPr6+hg+fDhOnz7NA18aOHAgdHR08NNPPyElJYW3RijwFAYOHChYW/j582eoqKjAzc1NlId0zpw5MDU1RWBgoGAt/adPn6CqqoqRI0eK1gaOHDkSDg4OovZZQkIC1NTUEBAQIMiXWllZiYYNG8LCwgIrVqxgqPt1+4JIjgS+fPlyPHz4kHM/GzZs4IzRYcOGITQ0lNkFp06dEhzLPj4+mD9/viAv93+nKav/NjMz49Ha1G4KUCYx/aRJk5TuhaNGjRJF4CYiuLm5Yd++faJzSltbG0uWLFFaL9y8eXNBm6Z2U4ZAa2hoyMMgkUgksLOzg5+fH+bPn49169Zx1o3mzZtj9OjR+PXXX5Geno6KigqGQ6Krq4u+ffti165dePHiBRsLtZkRpk2bhhs3bnDGZEhICIgIdnZ2+OWXX3g29927d9lvBwcH8/bO0tJS6OjooGXLljh06FC9e85/QugbqNE/Lvfu3WNgFERcjipADsZSG4XR2dmZ53gGBwcz49vLy4tHXRAbG8smw7Bhw3ggKg8ePIC7uzvU1NSwdOlSnhP04cMHjBo1Cvr6+jh48CBvYa+srMSGDRvQqFEjUac3KSkJ1tbWosZIfn4+nJyceAi7CikqKsKIESMQExMjqC8rK8OuXbs4yI61RSaT4fbt27CxsRF1bF++fAkzMzNs2bJFUJ+amoru3bvDxsaGR20DyBE/Bw0aBCI5sEhdBz0tLY1DbeDr68vZoDIyMhhPn6IZGRlh9uzZePbsGT59+oQffvhBlAvPxsYGFhYWSrnyVFRUROG9ra2t8f333wtSI2hpaWH//v1YvXq14Gc7duyIvLw8HD16VPD7J02aBKlUiuTkZEFjaOXKlQDk4C+Khb329yhAiqqqqjiohgrHeMiQIey5K56BYmEmIrRo0YIZPFu2bGF6BcK1pqYmA6tRGBCKhV/hVP78888A5EZKbQ49xXW2aNECX758gUwmg7e3N+8eJRIJjhw5AgCiG7CHhwfy8vJw6dIlweeooaGBvXv34sOHD3B0dBR9Fk+fPsXYsWMF9Zqamli2bBnCwsJEudOcnZ2xZcsWjuFZ+36dnZ2xf/9+TnBDRUUFbdu2xYwZM3Dy5En8+eefmDNnDojkhnjXrl2xbds2ZGRksGcVFRUFIjk/6bp163g8ozk5OdDV1UW/fv1w/fp13twuKSmBh4cHpk6dKjivZTIZ5syZg0WLFok6ZGfPnsXcuXNFnbGioiIMGTJElGO5pqYGs2bNEgQSAeTOaFBQEIcjsa6kpKQgNDRUVF9VVYWAgABRZ6+yshKTJk0SpJUB5ABk69evx5UrV0SvMSYmBqNHjxYNDrx69QrGxsaifKrPnj2Dg4MDAgICBKllUlNT4ePjA01NTezbt4/3O2lpaejfvz+I5I5ZSEgIx5h69uwZBgwYwBnHEyZMYNfz/v17QVRUXV1dDBo0CEeOHEHPnj2Vro+KsSqm09XVFXXmtLW10bt3b1HwplatWiEwMFDUcPX19cXNmzfRuHFjQb2fnx/evn0rSg/h6uqK58+fY8KECYJruIGBAQ4dOoSwsDDRPvD29kZkZKRSNGN/f39RWhdFa9iwoaBTrqamBnd3d/j7+7OAmKJpaWmhf//+CA8Px40bN3h0dC1btsSOHTsY0nFdJ8fT05MDGLNy5UrOOl3XMd2/fz8HVbRx48YICwtjgZ/Lly8zu0Zx7VOnTmUB6cePH2PJkiUYM2YM+47mzZvj+PHjqKmpQX5+PqZNm4Zt27ZxApO9e/dGYmIiZDIZpk+fjkWLFnGeqUQiQZ8+fXD+/HksW7YMo0eP5qBgK5qDgwO+//57dO7cmfFtCzUNDQ1BHs6/tynj7TU1NeXROdVuI0aMYLzgQt8bFBSEpUuXCs45PT09RERE4Pjx44LXr6mpibCwMKSlpYlyfM6ZMwdfv34VBZRUzJkRI0YIXoOamhp+/vlnbN26VXTempubY/HixRxQuLrN0tJS6ZwikgeRlQWK1NXVRdGamzRpgj59+giiNZuZmWHKlCmIiIjg2EaKsdajRw8cO3YMZWVlmD59Oo8Savr06SyRExwczAHpsrKyqhc48d8t9M0h/cdFiJxeMYCDg4MRHR0tqO/QoQPi4+Px4cMHQf3IkSORk5MDmUzGW/h1dHSwYcMGZoDV3cSbNm3KoYmozUNKJN+QaiN/1r5GFRUVrF+/nmM4vXr1ihntenp6PPTB0tJSFn0yNDTkIbHJZDJ069YNampq0NTUFERSmz9/PtsAhbj4IiIi2ILj4uLCy9g8e/aMsyAFBgZy9OXl5RyYegMDA9511M3qmZmZce51+fLlvOekoqKC8ePH4/379wyKX6wp23QUTcyY0tfXx+LFi9mzrm2wqKmpYeHChSguLmYUQLUXT0dHR+Y4x8fHg0huuCg2an9/f4b49uHDB+jo6KBr167MuR43bhwbD5WVlWjZsiU6duyI4OBgEBF++uknjnE6fPhwODo64u7duzAyMkLv3r05hun27dtZ306YMAFOTk4cqo2EhATo6Ohgz549iIuLg66uLicz/ubNG8btlZ+fDxUVFRw8eJDpKyoq4OzsjK5duyI7OxutWrXCjz/+yBnTQ4YMgY2NDc6dO4fu3bvDysqKk6nbsGEDNDU1sWDBArRq1QoqKiqc7Pvly5dBJA8gKcbtwIEDmdPz/v17qKiocDaHJk2asAyVTCbjRWw1NTWxdetW1ldChsDAgQMZRYMQB3KrVq1w6tQpSKVS5izWbkZGRli0aBFycnLw+vVrnl4ikaBnz544evQoSkpKBDdxU1NTrFu3DhUVFYLZei8vL5w/fx4AeJH71q1b4+DBg4JUIVpaWli4cCHHMXz69CnT29ra8taeiooKlg1ydXUV5AFVkKZ37NhR8BTItGnToK6uDhcXF8GsXWhoKLS0tNCoUSPBLMvdu3ehp6cHNTU1XL9+naf/888/mRGgQK2tLVVVVWjfvj20tLTQvXt3wUzq2LFjoaOjAyMjI8Fr2L17NzOGNmzYwNP/9ttvbG2xsLDgfUd+fj4nw9C7d29eAMDNzY3zLIcOHcoxZKZOncobC9999x2Sk5MBAIcOHRJd93x9fVn0/x9tTZs2Fc30WFpaYvfu3YxXWGhe5eTkMGqI2ka8qqoqVqxYgYqKCrx48YKN1drzNjg4GFKpFJWVlTA2NuYE4xSGu2KN7Nq1K2/OLVmyhGUrhLJdffr0YTQUx44d4+kbNWqE48ePQyaTceZM7dazZ0/cvXsXUqlU1HD28/PDtWvXlO5V9vb2HJ5WoaaME1FDQ4ND3VO3OTo6Ys+ePaJ7Yfv27REXFyd4SodI7uhFRkaKBvS0tbWxePFiTmCzbmvRooVSnlLFdSjjxSUiQe7K/8mmjBrH1tYWISEhzAmqO6Znz56N/Px89qxrr/WNGjXCuXPnAMhPhRERB4W7ZcuWLDlx8OBBEBEnK9+6dWtG76fgO689Z5o1a4b09HQAcvtRX1+fM2aMjIw4yYu6p4Xqzhmh006urq4siLhv3z6eXk1NDfPnz0dBQQHu3bsn2IdmZmYs0yj2rG1sbLB9+3Y4OzuLPgtTU9N6WRrqG0v1tfoCdT4+PqJZYgMDAyxZsqTeU5D/DqFvDuk/LhcvXuQ5jLWbiYmJUgJlT09P3kavaJqamli4cKEg4bhiUsfGxopmvUaNGoXc3FxERkbydMbGxjh58iQA+bG7uot/r169GB1FRkYG54iniooKdu/ezfrgw4cPHC5WfX19ZoQAcqh+V1dXjr52FrimpoZ3zOrYsWOcft61axdH37VrV05G5MGDB7xs0a5du5j+y5cvvCOcGhoaiIiIAAAW7RTqx5kzZ6K8vBxRUVGix0J0dHQwefJkZvyKTfpmzZrByMiI8/+2trZYuHAh7t+/jzNnzuDIkSOchWz9+vXMAX/w4AHS0tIYsbinpyfnqHZubi5+//13PHz4EETyCGdtZ08mk7GNwMnJCZMmTeIZwIpjQqtWrUJAQADvGNO7d+9QU1ODjIwM9OzZk5dNKSgoYI7ZyJEjecEDqVTKMmkhISG8bHVhYSHCwsJQWVmJnJwcHs/o27dvsWLFCnbMq25GvKKiAocOHcKKFStQWVmJn3/+mWdcf/z4ERcvXkRiYiKmTp3KyxqVlpYyB7Vbt2688ajgUpXJZFBRUcG8efN42a9bt26xZ9mvXz8exUJycjIzTjt16oSMjAyO/vHjx4xsvE2bNrzTC2/fvmUZqVatWuH06dOcaygoKGBHo52dnRESEsKBmq+qqsKMGTOYfvPmzTzuNcXa0qJFCyxevBjJycmc8RAWFgYiubM9evRo7N+/n0Mlo6A7aNSoEXx8fDB79myEhYUxY+XOnTtQUVGBjo4OmjVrhi5dumDSpEksW/rs2TNOxkpDQwPjxo1jfZmTk8PZZPX09BAeHs6u79OnTxx6CFtbW858KSoq4mRyWrRowdmUKyoqONxvTZs25QTzampqODyjRkZGHJ5lxXE7hTEokUgQGxvL6eMHDx5w9pDFixdz9Lm5uRx+zjZt2nCeo1Qq5TladSlDLl++zDF47OzsOM86NzeXlynp0KED2wOkUqngUdimTZuykwnHjh0TdURGjRqFuLg4UaoORavNd137mf7www/Yu3cvNm7cyOkLDQ0NDB06FAkJCZBKpUhISEBsbCzrb0tLS+zatYsFQDIyMpCUlMTGvZOTE6f8orCwEPHx8Th79iyI5IZ1XZqga9euISUlhenrlsqkpKQwTkMnJydeZv3hw4fM+baxseHN6+zsbBboNjQ0xJEjRzgBvy9fvjDORVVVVcybN48TGKipqWHzkkh+xLduoOTUqVPMWdLW1sbUqVPx/Plzpo+Li+M4ICYmJhwamOvXr/MySlpaWvD19UVgYCBOnTolatfo6emhQ4cOSp0pIlKabVKsKcqM8MaNGyt1EnR0dODi4iJ4vLn2fFaWOSOSOwJiJ1UUc17IbpBIJGjWrBl69OjB4SBV3PuPP/6InTt3Yu/evbh69SoLqCsysFeuXEFZWRmOHDmChw8fMiffysoKe/fuZc5aXFwcsrKymM2goGlSyL1795Cdnc0CnAEBAZwj99nZ2Xj27Bm2bdsGIsK0adM4p02Kiopw79495vRNnjyZdxolMTER4eHhIJJzF9eljEtJSWHBIA8PD96x57S0NHZs2dramjdnMjIymF5TUxMbN27k2DUfPnzA6dOnWf/27NmTE+QuLy9HeHg4e05GRkbYuHEjx244ePAg57i/m5sbTpw4wX4nMjIS7du3Z3oVFRX4+fkhKioKlZWVuHjxIu/UgLq6Onr37o39+/fj0qVLnNOWiqaqqorOnTtj5syZgpl2RWvSpAmHfkioKcuWK/T1UdX9q4W+OaT/uMTExHAGoIJXa/To0Vi5ciWWLVvGnD0VFRVYWFigXbt26Nu3LyZNmoSpU6eyhVdDQwOWlpZwcXFB165dMWjQIAwfPhy6urrQ0tJCw4YNYW9vjzZt2qBz587o1asX+vXrB0dHRzRt2hQtWrRA69at4ebmBg8PD3h7e2PQoEEYMmQIunXrhi5dusDDwwPt27fHd999BxcXF6xevRobNmzAyJEj4efnh06dOqFly5awsLCAg4MDkpOTERkZiZkzZ8Lf3x+tW7dmk3bWrFmoqanBtWvXMG/ePHTv3p05W7q6uiwDefv2bcyYMYNDCmxqaso2wAcPHmD06NEcx11dXZ3xxGVnZ8PPz4937GPw4MGQSqUoKiqCv7+/YIRJcbRMzGknImzatAmvX79WOpldXFywePFiwc3I3t4eHTp04Bwn09PTg7e3NxYsWIDIyEjGOZaZmQmJRAJra2vMnz9fsP5u79691RHIxQAAIABJREFUsLGxwc6dOwV59gCgV69eOHjwoOgRwPj4eISEhCjllqpr6NSVhw8fKq2NKysr4x31KCsrQ1xcHH777TcA4AQNcnNzsW/fPnTv3p3Vciquv6qqCrGxsRg2bBi0tLRw+PBhAP/FIVpSUoKjR4+iZ8+ekEgkCAgI4PxuTU0NEhISMH78eBgYGEBbW5sZiorvKC0txblz5/DTTz/BxMQEbdu2RUlJieAR9+PHj2PcuHEYPXq06DF0xXWtW7dOVB8UFCRI9K2Qtm3bYseOHaL97O7ujtDQUEG9TCZD3759cebMGcFxIJPJMHPmTCQkJIj+fmBgINLS0kT1Z86cEcw6KiQlJYXnxNaWzMxMpTyrnz59QkFBgejvl5SUoKioCBUVFYLvUZCyv3//HpmZmUhLS0NiYiJnXObn5+Phw4eIiYlBcHAwfvnlF06QJDc3F1euXMGmTZswdOhQ+Pv7c44Pv3nzBkePHsX48ePRtGlTtG3blmNQvXz5EkFBQfDx8YG6ujocHBw4Bt2zZ8+wdu1altExMDDg9OmTJ0+wcuVKzhHuqKgopn/+/Dl+/vlnzlH3ESNGsP7Izs7GvHnzOKcitLW1WTa+qKgIEydO5DkALVq0QG5uLgs+CfEwOzo6IicnB7du3RI9yqqhoYHg4GCew6qnpwdLS0s4OjrCzc0NXbt2ZU6QovZq4cKFOHToEO7du4eioiIMGzYMRHJHb9GiRbh+/TqnzqmiogKmpqZwcnLC9u3bBcfW1atXYWFhgZ07d4py9Pr6+mLr1q2iNVSBgYFYtWqVqP7UqVOYN2+e6PdHRkZi0qRJouv3zp07MWLECNHa7DVr1qBv376i5Sm//vorvL29RXEjjh8/DhcXF5w/f15w3sTGxsLKygobN24UrPe9desWtLW1MXz4cMTGxvKCjo8fP4aKigpatmyJuXPnMudIIW/fvmWnBlxdXTFlyhQcPHgQT548QU1NDQoLC9l4lEgksLe3h5+fH+bNm4fQ0FDcuHGDF9zV1NSEg4MDfHx82NostOcrgluenp6iyQANDQ3Y2Niw0y9C3+Ho6AgfHx/evFFXV0eLFi3Qv39/LFq0CEuXLuU4D61bt8bYsWOxZ88e3L17FyUlJSwQY2dnh4kTJ+LkyZOcsbt69WqoqanBz88P4eHhvH31zp07aNCgAebOnStYk19eXg57e3sEBweLjsk+ffogMjJSdK2dMWMGLly4IKgD5EeoxUquAGDz5s0swC8kQUFB2Llzp+jv7927F4sXLxYsFwCAw4cPY9iwYaLcuVFRUejUqRMnsFJb4uPjYWdnh+joaMFrePToEfT09LBixQrBefnx40eoqanB398fSUlJvO8oLS2FoaEhmjZtivXr1/P2xerqajRt2hTa2toYMGAAjh07xvkdmUzGMsGOjo6YMWMGYmJi2FiQyWTo0aMHG59du3bF0qVLcf78ebaOKwLUirH2ww8/YOXKlYiKikJWVhYn6aKvrw83NzeMGDECq1evRmRkJNLT0+vFKvhXy9/rkH5D2RWQ2NhY0tfXJ1tbW7KysuIhA6alpZFEIiFLS0tq2LAhDznr3bt3JJVKycTEhHR1dXkIbJWVlaSqqqoUYfdfKULcVwCooKCAcnJyyMLCgkOFAoDevn1LDx8+pMzMTJowYQIZGRkx/devXyk5OZmSkpLo9evXtHv3bsarBICePHlCV69epWvXrtGjR4/o6tWrDCGvqqqK7ty5QwkJCRQfH093796l6dOnU1BQEEkkEioqKqLU1FTGl3nnzh369OkTHThwgMaOHUt//vknZWVl0atXrxhFh+K1v78/zZw5k6qqqqi8vJwHaV5SUkJPnz6lwYMHMx5RExMTDlJaWloaPX/+nNzc3Kh58+aCKGbJycmkpqZGHTp0EEU5e/ToEbVs2VIp51hRUZEot6WiL/9RrimpVEqlpaWc76+srKS0tDRKSUmhBw8e0LJly9hz+eOPPyguLo7i4uLo+vXr5OHhQZcvXyYNDQ368uULnT17lk6ePEk3btwgqVRKM2bMoF27dhEASktLo6NHj9KJEycoLy+PiIhGjx5NR44cIZlMRklJSRQeHk5nzpxh6HsODg6UlpbGkGYjIiIoMjKSg+p7+PBhGjNmDH39+pViY2Pp3LlzdOXKFSorKyMiIlNTU0pNTSVbW1v6+vUrJSYmMh7S58+fExFRq1at6ObNm2z8FhYW0qNHjyg9PZ0ePnxI6enpVF1dTZcuXRJFYCwoKKCSkhJB5FEAlJOTQ02aNBH8rEwmo+LiYlGUSsXC/FdFy/vfLMrmz9u3b6msrIwcHR15uqKiIoqPj6eysjIaNWoUT5+VlUVRUVGUkZFBO3fu5PDeKda/U6dO0eXLl+nYsWO833j27BmdOXOGzpw5Q2PHjqW5c+dy9C9evGBz8dWrV5SSkkJWVlaca09OTqZbt25RcnIyaWpqUnx8PBtjnz9/poyMDMrIyKDMzEzKyMigkpIS+vXXX8nBwUGUjuHLly9ka2tL7dq1owYNGpCuri5vXN6/f58kEgm1aNGCdHV1eX1TVlZGp06dou+//16Uay8nJ4fevXtHnTt3Fn0+L1++JGtra6UI01++fFHKBf3Pch4WFxcrpXL6+PEjWVhYiOpfvXpFTZs2Fb3H169fk52dnag+JyeHbGxsRNeG7Oxssra2Ft1jMjMzydLSUvQenjx5QgYGBqJUQOnp6VRRUUFt27YV7McHDx7Qq1evyMnJiRwcHHjvefLkCV25coWh29ra2lLDhg3Z/chkMtq8eTOpqamRpaUlWVhYMDRhfX19kkgklJKSQqdOnWL62s3Y2JgA0IoVK0gqlZK1tTXZ2Niwv8bGxiSRSOjhw4cUEhJCjo6O1Lx5c3J0dCRbW1uOPbZ9+3bS0NAgNzc3atOmDY9mKTMzk27cuEE9e/Yke3t7wWcWExNDnp6eomPy1atX1KhRI1GezNLSUpJIJIIUTwqpb0zXxx1bn74+ntT6uHfrmzN5eXlkamqqdF22tLQURQF/9eoVWVlZifZBRkYGmZiY8GhlauslEonguk8kX3c+fvxIXbp0EbzG169fU1paGvXu3Vtw/Xvz5g3Fx8eTj4+PoD3x5s0bunDhAnl4eFDr1q15z+LDhw8UHR3NUJjr2g3FxcV04sQJNo4bNWr0l+Qj/Ub78k3+Y6LM8KuoqKDXr19TixYtBPXFxcV08+ZNcnFxEZzAgJw/9P79+9SzZ0+l/FT5+fmkoaEhuFD8X5GKigr6+vUrffnyhZGDK4xOxd+MjAzS0tKiAwcOUHZ2NqWkpFBKSgqlpqZSVVUVqamp0ZkzZ8jAwIAuXrxIcXFxHOoVR0dHunTpEiUmJtLJkycpPj6epFIp03t4eNCRI0fo9OnTdPToUcrIyOBco5OTE0VERFBUVBQdPXqU3rx5w9FraGiwgERERAS9fPmSd5/jx4+nvn370q5duygpKYnz+0RyCPrjx4/T/fv36fr165Senk511zYrKytav349C66kp6dTdnY25z3NmzenAwcOUHV1Nb17947evXtHb9++Za/fvXtHEomEoqKiyNPTk3edAKimpoaqqqpIR0fnL7k5fJN/nShb+xRBv9rBvLqSlZVFTZo0EXU6CgsL6ePHj+Tk5CT6Hfn5+VRaWqqUqqW+a/0m3+SbfBMhqampoeLiYioqKqLi4mJq3rw5C+LLZDIqKSlhPKWFhYXk7OzMWfNkMhmVlpZScXExc1jFglXf5P+G/L0O6f9Iik4ikeQQUTERSYmo5u/54b+6pKWlkaurq+iG/e7dO7KyshLVl5SUCGZHFaLge/y/mAlRZuRoaWmJOqNEcq7HPn36KP1uW1tbsrW1rfc6FItgVVWVKF8sAMrNzSVzc3NBfXV1NT18+JDc3NwE76uwsJASEhLI09OTzMzMePq3b99SXFwc2dnZUZMmTcjW1pYThX/27BnFxMSQhoYGa+rq6uz1ly9f6MaNGyxaWlZWxhzQr1+/suyghYUFqaio0Pv373nXYGlpSdra2tS6dWueTiKR0IgRI2jMmDGC3JrGxsa0YcMGcnd3F+TnNDMzo/DwcAoODqbQ0FAeP5+WlhadPHmS1NXVKTs7m96+fcv7ju3bt5OnpyfJZDK6cuUKzyFt3bo17dq1i4jknFu3bt3iOaS7du2iwYMHU2VlJR0+fJjnjBobG9PVq1cpMTGR1q1bJ8id1qpVK2rXrh116dKFp6v9PWZmZjRx4kSqrKykqqoq9ldBMK6trU2DBg0iT09PMjAwIAMDA2rQoAFpaWlRUlISOTk5kbOzMzVu3Jg3/7Ozs8nCwkI04vv/Izfx/yZRtvZJJBKlzigRUdOmTZXqFeNJmRgZGdX7O4rrqU+kUikBEM2iVFZWUl5enqjzqwgwent7C2aCCgoK6MCBA9SqVSvGw1j7ugBQUFAQVVdXs2yZgkdQkXk5ceIE3bp1i/T09Bh/p66uLvv3y5cvKT4+ntTV1cnAwIBUVVU5nIYFBQX06NEjUlNTY9mu6upq1kpLS+ndu3ekra1Nzs7OjHtRMffLy8vpw4cPpKmpSe3bt6cGDRpQTU0NSaVSkkqlVF1dTS9evKDq6mrq2LEjNWnShNTU1Djt4cOHVFBQQFZWVtSpUyfGT9ygQQMyMDCgFy9e0OPHj8nOzo5l/SwsLFj2Kj8/n/Wji4uLKA9po0aNyN3dXTBI+/jxY8rJySEfHx/B9QcAnTx5kvz8/ERP8ty/f589H7Hx8OLFC2rXrp2gnkhue3333Xei69zLly/J0tJSNNCcl5dH5eXloidcqqurKS0tjdzd3QX1AOjSpUvk4+MjaDcAoMjISPLy8hK8TwC0b98+atmyJbm7u/MyiABo69at1LBhQ2rbti3j2VSITCaj1atXk5qaGsvu2tjYMM5OqVRKK1asYCeqFONE8VpPT4+OHz9Oubm5pKmpSVpaWqSiosJ4diUSCT169Ig+f/5M+vr6ZGJiQhUVFRz+3Pz8fCovLydra2vS19fnOKAVFRVEJOcRbdasGWloaDDns6ioiO29Kioq1KxZM2rQoAH7bHFxMYeT1MLCgpo3b041NTXs9xV/CwoKqKamhtq2bUvW1tac61dRUaGSkhL6/fffycjIiDw9PcnIyIjDQ6qnp8c4yZs1a0aOjo6Mh9TCwoI0NTUpISGBbt68SS1atKAWLVpQ8+bNOWO/qKiIdu3aRe3bt6eOHTsKrr3Hjh0je3t76tChg+A6efv2bVJXVxe1IbOysqigoEB0TuTl5dGbN29E9UVFRZSRkUEdOnQQ1P+vkr/nXG99jYhyiMj0733/X72GFJCjNHbs2FEQPRaQn3339PTk0bko5PHjx/D29haF46+pqYGfn59SPr9ly5Yx9E0hiYiIEOXhAuRF47XBOOpKYWEhD9xB6DuUyaNHj5TWLD59+lSUmgGQ16Uo4yGtrq7moK0KyezZs3kF9bVlwIABotQKgBzgZtq0aaKcqz4+PnBwcMDq1avx6tUrnl6BnOro6IgJEybgyJEjyM7OZhyktWkRiOTADR4eHhg+fDiWLFkiChShaGL8efS3GpyZM2eKwp//8MMPePHihWjh/OHDhyGVSnkAU/S3upqbN28C4INc0d9qaxTzo6amhkOFpGghISGsnyIiIng1a/3792fjJzU1FQ4ODhy9vr4+q837/Pkzq0er3SZPngxAXrsaFhbGAe6gv9XeKepfMzIyBEGqXF1d8fnzZ1RVVQnSVBDJQYxev34tCOOuaGIokUJNQ0MDjo6O8PPzw4wZMxAYGIglS5ZAVVUVLi4uGD9+PPbu3Yt79+6xut1Xr17B1dUVs2fPxvnz53l1SVKpFLNmzeLVstSWqKgo3L9/X3TeZmRkKOURLSkpUcpvDPzP8IwqE8Xcqu89/0r93/Oe+nhK66vtyc3NVdoXubm5SrmgFTXWYqKgxxHjGFWgqR8+fFjwXmQyGVxdXfH9998jIiJCcK3//vvvoa6uDi8vL6xduxZ37tzh1E/XRtM0NTVFt27dMHv2bOzfvx/37t3DzZs3BZFN9fT00Lx5c3h6evJA5eo2MWoGRasPLbN79+5KETO9vb2Voq/a2dnVew316ev+voqKCiwtLdGxY0cMHDiQAy5lZGQELy8vTJ8+HXv37kVycjIDmFFTU4OHhwcWL16MuLg4tneWlJTA1NQUurq6GDhwII4ePcqr7Zs0aRJ0dHQQEBCA69ev88ZmSkoK1NTUMHz4cNy9e1dwvNjb28PX1xdJSUmCY27JkiVwcXERraO/desWGjZsiG3btgnW85aXl8PIyAjjx48X3K8BeR2/h4cHzpw5I1jLP3bsWJiammL+/Pk8YDrgvyjCOnXqhMDAQB5gjwIMSEtLCz4+PtiwYQPu3LnD5lBttHQ1NTW4uLhg1KhR2Lp1K65du4azZ88K1sGam5ujffv26NGjh1K7QLE/KxtryoA7mzdvzgEaE9ovlfGYOjg4YPPmzaLXqK2tjbVr1yoFB1Xgoyi7x/r0EolEtB9MTU3RqlUrDrinova5T58+WLBgAQ4ePMj4ZiUSCVq2bIlx48YhLCwMjx8/hlQqxcmTJ0EkBysbNGgQ9u/fz6FxVGCM2NvbY8mSJQw4USFFRUXQ09PDd999h19//ZVny9bU1KBRo0bw8vLC2bNneeNVJpPB1tYWvr6+HODRv5LQvxPUiP6POaTZ2dkcmHZfX1+OY1ZWVobQ0FCmHzNmDM8oSElJgZaWFoe+o7ZkZmaiTZs20NLSwubNm3mb/Z9//omRI0dCT08P+/fvF+T627hxIxo0aMCQdWuLTCZDXFwcGjRoIFq0/uXLF+jo6CA6OlpQX1lZibZt22L//v2C+qqqKkycOBHz588XNMyqqqpw4MABeHt7ixqoqampMDY2FiTRBuTgJQqqDqGN4+3bt3Bzc0OTJk0EN8CsrCxWFD548GBeUXp2djYCAgLYxjB27FiOE//u3TseWl7Hjh2xa9cu5Obm4uvXr6ILs5WVFQYPHoxOnTopXTSVGVO9evXCggULBI2VJk2aIC0tDWFhYYLfMX78eFRXVyM2NhampqY8/a+//gpAHnQQ4tlT8HO+e/dOENlw27ZtAOTjpC7SHJGcQkIxLmojhiruxdramhnChw4dYgadiYkJe33q1CkAchqO2puX4nWXLl1QWVmJvLw8uLu7M73i86qqqoznbsqUKYKbfMeOHZGfn4/Dhw+LQqgvXboU9+/fR8+ePQU3OB0dHQQGBmLChAmi/HLGxsYYOHCgUvoEQ0NDQfRGdXV1uLq6YsSIEWjRogX7f1VVVXh4eGDFihW4ceMGCgsLGRG3uro6o96o7UDu378fRHIU323btvGcy6dPn0JNTQ1Dhw5ljnxtqaqqgp2dHRYuXCjIsSmTyTBkyBBs2rRJlEd027ZtCAwMFAV+unXrFtasWSOql0qlmDJliihYBiA3GpUFqg4ePKg0YHfv3j2cPn1aVK9A8VbmlE6dOlWQdkbx+V9++YWH0Ftbf+bMGfz000+i/fD8+XNYW1uLBj6Lioqgq6uLuXPnCgYB3r17h3bt2qFhw4YIDw/n3cvr16/Rt29fEMmpQfbv38/5nj/++IPDG2lgYIBJkybht99+g0wmQ25uriBVh6GhIUMcrf15saYMndXU1FSUJ1QBWCIW9DM1NcWaNWsEqY6I5Ii+4eHhGDBggKDDaWhoiGPHjmHChAmiqKsLFizAhg0bRNcWBb+wMrRiX19feHl5Ke2j+tA4FetF3f9TUVGBq6srBgwYwONlVFNTg4+PD3bv3o3ExETMnDmTo2/SpAlWr16NnJwclJSUYN++fRwD38PDA5GRkWyeRkZGcgJ+np6euHjxIht38fHxjOaMSA6EFRUVxRzT9PR0xMTEsD3E3NwcgYGBLBDyxx9/4OTJk2zPVVVVRUBAAAPFKSkpQVhYGIen1N7eHjt37mQ2WkhICBYsWMC5zy5duiA8PBxlZWU4duyYID1Xx44dsXXrVoSEhLDAYt336Ovrw93dHZ07d1aK4qt4LmI6PT09UUCyBg0awN3dXXDPJyL06NED06ZNE3VIp02bhj179nDQZ2u3uXPnIi4ujsOyULsNHz4caWlp8PX1FbyHVq1aITU1FQEBAYKIyurq6tiyZQt++eUX0Wto3rw51qxZI2h3KJqrqyv8/f0Fgd0UzcLCol4uUmXPSVtbG/b29oLP2tnZGQEBAZg6dSoPRMvBwQErVqzAzZs3sXv3bg4Fjra2NsaMGYPk5GTIZDIcOnSIAR8RyVHQa4/XS5cucfqhW7duuHHjxt8VUP13Cf2bHdLXRPSAiNKIaFJ97/+rO6Rbt24VHHxDhw7FixcvcOPGDZ5OR0cHa9asQWlpKeNRrK1v3Lgxzpw5wwZJbfRFxeRRUHcA4G3Sffv25cA2BwYGcvQTJ07kRAtv3rzJiU4tX76cY9Tk5eVxnJhNmzZxBrBUKkXr1q2ZIbBmzRreAA8ICGCb8Pjx43lGU1BQENO3b9+eR1KflJTENhYdHR1cunSJo8/Ly4Ouri6LDPv7+/PoTmrDt6upqWHLli2cqGpd0mE9PT1s376dBQBq0zvU3giGDRuG33//nVFcCDVVVVVRQ6b2YiZmTDk7OyMyMpKz2Ciaubk5Tpw4AZlMxtscibiUI0IcdsuXL2fP69GjR1BRUeEYTFu3bmV99OXLF5iZmcHc3JxlQVesWMH01dXV8PDwQIMGDTBhwgQQyWHea4+HKVOmQF1dHYGBgWjfvj2aNm3KCUIoKAumTZuGc+fOQVVVlRPNu3v3LtTU1NC1a1e8e/cOLi4umDlzJtPn5ubCzMwM1tbWuHbtGtavXw8bGxtm7EulUnh4eEBDQwMrVqxgcPSHDh1i36GghejcuTPmzJkDIrlBpLhOBZ2Lvr4+Qz/V1NRk9DDPnz8XfI4dOnRAZmYmampqBDdYVVVVzJw5E1++fBHNVFtZWSE4OJhdl1Dz8vLCrFmzRPW6uroYPHiwoE4ikaBLly44fvw4b4NWVVWFv78/oqOjUVlZyeMT7NixI8eoXL58OZuTurq6WLp0KWdunz17lo35Zs2a8VBB3759y/qpU6dOPKewpqaGoXf37NlT0KEbO3YsIxAXQmjcsmULDA0N4erqKug0X7x4EY0bN4aVlZVgFuX169dwdHSEuro6h0JEIeXl5WzeLl++nKcHgFGjRsHQ0BBubm6cdUsha9asgbm5OTQ1NQW5Ts+fP8+e1ahRo3hBy9evXzN6CwMDA4ZgrpDq6mpYWFiwZ9WhQwdGzaSQumtP9+7dORkhobXH1tYW+/btQ0VFheDao2iOjo5Kx/Pf07p27SpK0WFlZYXQ0FC2JtVt3bp1w9OnTwX5ConkhnNubq4oX+Hw4cPx5csXFBcXCxqlPj4+LBNSl36MSG443rp1CwAEg5YaGhpYs2YNKisrsXfvXsFrUFBD3b9/X7SPfvjhB9y/f19pRqxnz5680yd1W30ZWmVNIpHweCVrt8aNG2P9+vWixv13332H06dPi3KltmnTBtHR0YKncIjkAcrg4GBR3luJRIIhQ4YwGhGhZmhoiEWLFintR0NDQzRs2PCfGtP1NWWBhSZNmmD37t2C1yiRSDB58mTk5uZy0LsVzcDAgCU3hOieanO0K+hgajcTExOG2CtkA2tpaSE0NBQymQx5eXmC2VEFfYxMJhMcjy1btmR2sNBpKFVVVSxZsgRlZWWC16gYa5GRkYLXqGitW7dWOhaI5IjlYkEkRauPcuWfbY6OjqInMxTjtXaAunbz9PTElStX/hKOKf2bHVLLv/01I6JHROQl8J5JRJRKRKk2Njb/hi74x2XHjh2iXFiqqqro3bs344+q26ytrbFt2zaew6lovr6+ePTokeBxCFVVVSxbtgzl5eW8rJxiQVBw0QUHB/P0zs7OLFJ++fJlXkTX19eXGY7Pnz/nGaZjxoxhGY38/HzePUyZMoU5nTKZjGe4Dh48mBM9X7RoEUffqlUrDh/gyZMnOZNNTU2Nww2Znp7OW/xdXFzY0dr8/HxBMm9fX1+W9VFki4QWpOTkZBw4cED0uCuR3AkQWtyJ5At87969ecaIRCJB9+7dcfjwYRQVFWHLli2cCH7r1q05x5EuXLgAf39/pp80aRLHyH758iXLyKuoqGDz5s0cp7u6uhqHDh1i/JQ7d+7kjekLFy4gLS0NRIRVq1bx9Hfu3MHXr18xePBgDBkyhHdUKicnBzk5OXjx4gWcnJx4BnZZWRnLUE+fPp131Pvx48eM5/bDhw9Yv34909XU1CA2Nhb9+vVjGdMdO3ZwxtKzZ88wfPhw7NmzB4CcmqkudcvVq1exdOlSFBUVITExERs3buToP378iEuXLqGiogKnT59G9+7dOUcmy8vLsXfvXhQVFWH+/PkwNzfnZQi3bt2K1NRU2NraQlVVFb/88gvHUQgKCsLEiRPZs/Tx8eFkr8LDwzlUSU2aNEFISAibd9evX+dkc4yMjDBnzhx2rD0jI4OTKdHW1sagQYNw+vRpFgxTZLQUa0qXLl2wfv16pKWlQSqVcjg4ieTR2jFjxiAkJAQ5OTm8II2Ojg7c3Nzw888/o7S0lB39q91MTU1x+PBhyGQy3L59mxeQ69WrF8tSvH79mhPd19LSwvbt29naUlhYyJkvlpaWnON9NTU1HG44R0dHjlNZ1+BycnLiHKECgLVr13LW7LqlEefOnWN6XV1d3gmOzMxMTia8NoezYizVdqR8fHx4GcqhQ4cyvZ6eHu83du/ezenDYcOGcTLC9+/f5xj46urqHL7WvLw83skGQ0NDzhHekSNH8p6lhoYGVq5cifLycoSEhIgG1KytrTFnzhyl62O3bt0E98JmzZph6dKlSEtLw7x58zjBUS0tLYwfP55xfR44cICTZW3YsCF27NjBqDBu3ryJwMBANmasrKw4VBjv378umm5QAAAgAElEQVTHpk2b2JiwsLDgnBqSyWTYsGED4wmtzeetkNDQUOY0amlpYefOnZw1Mjo6msMTOn36dM7akpycjODgYLbfeXp6cqgssrKysGrVKmbgmpiYYN++fWxOlJWVYebMmZzso5+fH6dkaO7cuZw9XVtbG5MnT2ac0KtXr+YZ2Hp6ehg9ejSuXr2K3bt3CzpDEokE7du3x7Bhw0QzVoq9Sex0SO331Jf5U+YYm5mZKT1RZGhoqPQYqGJNVfYbEolENPuoaGJOq7q6Opo3b462bdvyfkNfXx8BAQEIDAzElClTOKUfqqqqGDx4MJKSklBYWIhZs2ZxuOptbW0RFhbG5v/GjRs563SXLl04CY0TJ07gxIkT7Br69evHOcV3+/ZthIeHswBAv379OIG/9+/fY8+ePWwv8/Ly4qyhUqkU27Ztw44dO0Akz1g+evSIN2cUFIoNGjRgp50UcubMGVy4cIFlcmfPns058p+YmIjQ0FBmK7dp04bRXgFyG3bdunXMcdXQ0MCyZcvYvCsoKMCcOXMwdepU1k8ODg6IjIxkc3fWrFk8vufu3bsjLi4OUqkUv/zyC6ZMmcJ53hKJBL6+vjh58iSCgoIwdOhQzrxUtA4dOiAgIADe3t6i/oSxsTELSiobb8rKBerTd+zYkZ0S+08J/ad4SInoFyJaoOw9f/UM6YMHD0Qjeerq6rCwsKj3/L6yAaaurq40yubg4KCU/HnYsGGimTktLS3s2bNHNFNiZ2eHtLQ0nrNYe2HLy8tDaGio4KLbv39/lJWV4cqVK4KLtq+vL0pKSvDkyRPB6FLTpk3x+vVrfP78WbRGISgoiB1nE9KbmZkhJSUFv//+O8zMzATfY25ujsuXLwtG2Wo3Pz8/zgZpZGQENzc3DBkyBEuWLMG+ffuYYWlqaooff/wRQUFBSE9PZ8aCIirr7OyMTZs28YzfkpISaGlpwdXVFefOnROsixk3bhxatmzJIup1JScnB+bm5jzy6NoyceJEnDhxQlT//v17LFiwQOnCFBkZyasDq66uRmpqKmQyGaqrqzk1v58/f8bOnTsxdOhQdoREkXGsqKhAREQEvLy8YGlpyZxNmUwGqVSK3NxcbNy4EXZ2diAiFp1VSFlZGcLDw9GlSxcQybMlir5T3MOXL1+wb98+Vhd69OhR9tuK98hkMjx//hxbtmxB9+7dcfv2bWRlZYnWNufn52PXrl2idZTl5eVwcnISPCIOyGug7O3tce7cOV5fK2qonJycEB4ezst6SaVS2NnZoVOnTuyIWG2prq6Gk5MTBgwYgBMnTvBKAaqqqtC9e3dMmjQJ0dHRvCOrUqkUkyZNwpIlSxATEyOYPdy0aRM2bNiAmJgYZGVl8cbr8ePHERQUhKioKNy7dw8fP37kvCc+Ph779u1DREQEYmNjcfPmTTx8+JDNiwcPHmD//v0ICwtDaGgoQkJCsHfvXhbEePXqFQ4fPowdO3Zg1apVmD17NsaNG8cMro8fP+LIkSNYs2YNJkyYgJ49e6JTp064d+8eALkhcuTIESxcuBC9e/eGtbU17OzsWL1+RUUFDh06hMmTJ6Nt27ZQVVWFnZ0dqwOTSqU4dOgQRowYwU4MGBkZcQILERER6N+/P8tQSiQSzvHeixcvwtfXl2OgDxs2jPXTo0eP4O3tzdlnDA0NmVGXl5cHX19f3j4ycOBAVFZWoqamBlOmTBHchxSnWSIjI0UN57lz5yIvL0+05llTUxNubm6co4kmJiZo164dBg4ciPnz52PXrl04deoUC87WDmwo6qsAORaCQr9s2TKkp6fzMuYSiQRWVlbYsGGDIA/pmjVrYGBggHXr1vHGPPBfa+yiRYsE9QDQr18/jBs3TrS2etOmTejdu7doTW50dDS+++475uDVlZSUFNjY2CA+Pl5Q/+jRIzRo0AD79u0T3AMyMjKgqqqK2bNnC2b9s7KyQCTPdt6+fZunf//+PePD3rRpE68u+OvXr9DR0YGqqir69OmDiIgIjtNcWVnJjhYaGxtj+PDhCA8PZ46KTCZDz5492XgwNTWFv78/Nm7ciMTERJSUlGDlypU8e8TV1RVjxozB1q1bsWXLFkHj2dzcHJ06dcKQIUPYnBKybRwcHJTWPjZs2BBNmjQR1GloaMDBwQHe3t68eaWuro5WrVphyJAhWLlyJcf+UlNTQ7t27TB16lQcOnQIT58+5RwrbtGiBWbNmoXY2Fg29h48eAAieVBg8ODBiIqK4qzl1dXVMDc3h5mZGVasWMGzGQBg+PDhsLGxQUhIiOBx+wMHDsDa2lqUhzQnJwcNGzZUylPasmVLltUUkoCAAKxatUq0ZCA4OBijRo0SnXMpKSno0KGDKBZKcXExLC0tlWJ8ODo6Yu3ataLlGX5+fujbt68oHsu8efNgbW2NAwcOCNbB7927F6qqqhg5cqQgZsrly5dBJA8er127llcvnJ6eDiJ5sKVr167YuXMnx3ZQzGsieVDC398fQUFBePLkCbNNaiePzMzM0LdvX6xZswaXL1/GtWvXeEEcc3NzdO/eHTNnzsTkyZMFx7uxsTHatWuHQYMGYeHChYLlN/8uoX8XD6lEItElIhUAxX97fY2I1gC4LPaZvzLti0z2/9j7zrCorq7te4ZeVZogIAhIRwUEBaMoYsOKsfcSgw1sGGKM3dhNxN5RMWqi0YgajQUVC3YRrKCACIKAdBjazPp+8M7+5nDOwVzP8+V5876f67rWNeiCM+fss9sq+74VWLJkCSorK2Fubs44OZWfzZo1w/79+5GTk4OmTZsyREMl5UazZs3w8OFDvHv3Djo6OtDV1WWfyp+zsrKQnZ2Npk2bQkdHB1KpFGpqauyzuLgYeXl5cHJyAhFxEP+UqH9aWlpo164dQy5rqF27doWtrS3y8vKQn5/PPvPz81FWVoZ58+bByMgI7969w9u3b5GZmclUQ0MD69atg4GBAdLS0pCSksL01atXMDMzw549e6Cnp4eUlBQ8e/YMT58+ZZ8WFhY4ffo0tLW18fLlSyQnJ3NUIpHg8uXLaNGiBaMmefHiBaMoSU1Nxbx58zBt2jS8e/eOaWZmJvs5Ly8PM2fOhJeXFwe9TfUzPz8frq6u8PDwgI6OjqCeO3cOenp6cHJyQqtWrXjolK9evUJcXBwCAgLg4uIiiJK2d+9eeHt7o127doL2Fy9eIC0tDcHBwaLIlidPnkS/fv1E0YBzc3NBRI3y3BUUFMDExKTRvq1EllRKaWkp4uPjoaGhgV69erH/r62txbVr13DixAn8/vvv2LlzJ0JCQgDUw77/+eefiI6ORmxsLAAgISGBocClpaVh165d2L9/PwoKCgAAf/zxB/r06QMiQkJCArZv347jx48zVN6vvvoKe/bsAVDPV7dnzx4cOnQIxcXFAOrRRZOSktCyZUtUV1fj3LlzOHz4MM6dO8euMWnSJOzbt4/d461btxAbG4szZ84w5N7o6GhMmDCB0yYpKSm4ffs2EhIScPv2bYwbNw6RkZGi7SiTySCXy0X54/7880907dpVkJ9NiZo8ePBgQRTJoqIiZGVlMT7YhlJZWYm6ujpRlEuhd/xZ6tGw8/Pz4eDgwLNVVFTg0aNHKCgowKBBg3gor+np6bh+/Tpev36NBQsWcN67XC7Ho0ePEBcXh1u3bmHRokXw8fFh9pqaGty7dw9xcXG4evUqfH19sWbNGvYdNTU1ePToEW7evImbN2/i9evXOHnyJBwdHQHUj8OXL1/i0aNHePz4MR49egQbGxvs3bsXWlpaqKurQ1ZWFt68eYO0tDTGxdy1a1dMmzYN1dXVjIKh4WeLFi0YwqeqamhoQCKRgIgQFxcHMzMz2NraCvIJPnnyBBkZGfDz8xNEGVcoFNi0aROCgoLg4eEh2C8vX76MoqIiDBo0SJTz8MSJEwgMDISRkZGgPScnByUlJY3S4SQlJQkijSslJSUFrVu3Fh07b968gbW1tegc/ebNG5iYmIiiIL98+RIGBgaiCLSJiYnQ1NSEq6uroP327duoq6tDly5dBO1xcXH4+PEjQkJCBNE+L168iJSUFAwbNkzwXV27dg1XrlxBcHAwfH19edyPSv5OPz8/+Pv78zhVc3NzMXfuXDg5OcHDwwPu7u6wt7dn16mpqcHUqVOhoaEBBwcH2Nvbw97eHnZ2dqxvrVq1Co8ePWLIskq+0pYtW8LExARXr17FmjVrOPyiyp+tra1RVVWFcePGoWnTprCzs0OrVq3Yp5LPcvHixUhLS4OrqytcXV3h4uICe3t71mY3b97Ezp074evrC19fX7Rr146DjF9dXY05c+bAx8cHPXr0EESYPnToENTV1dG/f3/BcZOamop79+5hyJAhojyev/76KwYNGiTa3+7duwd3d3dRntL3799DU1NTdE9AREhLS2sU2fvdu3eivLQAkJ2dLYjorJQPHz7AyMhIdFyXlpaitrZWlKtVoVDg1atXjTIz3L59G/7+/qL28+fPIzAwULSdT5w4gQ4dOog+5+HDh2FpaYmAgADBNXvv3r2QSCQYMGCAIN9pVFQUysrKEBQUhPbt2/PG5rJly1BeXs76W8uWLVl7KhQKzJ49GwDg6uoKNzc3uLq6svaqrKzEjBkzYGhoyJgclNoYp/1/Wv5jPKQSicQOwKn/+qc6gCNE9ENjf/NPdkg/y1+TxugnZDIZZDKZ6OahqKgIHz58EN081NXVIS0tDebm5o0OKplMBm1t7c+bbwGpqKjAs2fPkJSUhOTkZAwfPhz+/v6oqqrC7du3ceXKFcTFxeH+/fvw8vJCXFwcNDU1cfnyZZw4cQKnT59GYWEhAGDhwoVYuXIlXrx4gejoaMTExCA3N5d914YNGzBr1iycPXsWO3fuxJ9//sm5l6+//hobN27Ezz//jB07duDJkyccu42NDe7cuYMLFy5g9+7dSEhI4D3PoUOHYGtri5iYGBw/fpw5qkpxc3PDpUuXcOPGDcTGxuKPP/5AUVER53fmzZuHpUuX4t69e8wBTUhI4Pze999/jxUrVqCurg7v3r1Deno6T42NjbFnzx6Ym5v/ay/ns/yvFaLGuT1lMhk0NDREaVSICEVFRaJzJ1A/99bV1YluVD/LZ/ksn+U/IXK5nFGxqAoRobS0FEVFRTAxMeEFb4kIVVVVKCkpgUKh+MxD+r9c/mM8pESUBqDtv3udf5oUFRU1yuVWUVEhyoMF/O/nC2zs2ZTZRzH5FE+euro6yxA0Jo19x39KPrUB/ZT9r1y/pKQEHz58ENTc3FyUlpYiJCQEJSUlSEpKQlJSEl6/fq0soUdERASuXbuGRYsW4datWxwOTnt7e8ycORPTp09HbGwsj4u0V69esLa2RocOHXDv3j3e/fXs2RN9+/aFm5sbUlJSeHY7Ozts2LABx44dww8//CDIQxodHQ01NTW8fv0aL1684NmHDx+OESNG4PDhw7h06RLPGdXV1cXx48dx5coVRERE4MOHD7xr9O3bFz169ICFhQWHB01VJkyYgNu3b8PW1hZZWVk8rlMAcHR0hL+/PzZs2ICamhrU1tayT5lMhrdv30JbWxszZsxA9+7dYWRkxMYKEeHevXtwcXERDbSUlZVBX1//c5Dlf6h86r19as6SSCSNOqNA/dz7T3FGPzW/VVdXQ0NDQ3S9KCkpQU1NDUxMTASvk5+fj7dv38LU1BQmJia8NbeoqAi3b9+GtrY2y/Cq/qylpYXLly+jurqabZwVCgUUCgWICAqFAm/evEFGRgY0NTXh4uLCxrSSa7S4uBgvXryApqYm/Pz8IJVKmV2pL1++RHV1NTp16gQzMzMoFArGQyqXy5GZmYns7Gy0bNkSfn5+0NTUhLq6OjQ0NKChoYHKykrcvn0bBgYGaN++PaysrBgXqfLz5MmTUFdXZxnB5s2bc9r1yZMneP/+Pdq0aSOYtZLJZLhx4wb8/f1FqzseP34MZ2dn0X76/v17NGnSRHTvU11djYqKikb7cGFhYaP24uJiNG3a9F/++7y8PJiamor2y+zsbDRv3lw0KPTmzRtYWlpysqKq8uzZM7Rs2VIw8wnU87k2b95cMAsN1L8nPT092NnZCY6Lx48fQy6Xo2XLloLPoeQQNTQ0hIGBAfvU09ODVCpFamoqnj59CuD/zkeq1ygrK8PDhw9RU1MDU1NTaGlpobKykiUSKioq8OLFC1RUVMDb2xt6enqcygrlfqSyshK+vr4wNzdHYWEhioqK2GdRUREUCgU8PT1hZ2fH/q64uJhdRznu/fz8GMe6qpaVlaGwsBBOTk6s+kxZ2gnUzz2vXr1CaWkp/Pz8YGdnx+Eh1tPTQ0VFBS5cuAALCwvGZ2phYQELCws2Bg4cOMDGvqOjI69vP336FFlZWejYsaNgv6ysrMSTJ08EqwqU8qnqi7y8PNH+AtTPk43xTys5af/Hy1+p6/1/rf/0M6RE9fX5ISEhojyfp0+fpuHDh3NAelQlJyeHRo4cKXgeRikRERGCZ0WUEh0d3ag9Pj5e8AyYUtLT0wXPJiilrq5OlC5AKUoOSDER4/lStTfGxff27Vse+q6q5OfnM3ALIZHJZHTkyBHRMxC1tbW0fPly0TMO1dXVNGXKFFE+2YqKChowYABt2bJF8F1//PiR/P39acKECbRr1y568uQJ57xFVlYWubi4kKenJ/Xv35+mT59Oq1evppiYGLp27RpdvnyZzM3NSV1dnTQ1NUlbW5t0dHRIT0+PDAwMSF9fv1EkN3t7e1GALalUSt99950oEIW5uTnduHFDENgEqEf7KywspFevXnFg8pVqZmbGkJ8b0q7gv87VqZ6JvXDhAu/MmyqSblpaGu9Mm6WlJRsDMplMEKTqwIED7BpHjhzh2d3c3Ni51tu3bwu25/Tp00mhUFBsbKwoMMesWbNEkf2U2pADVV1dnSwsLKhdu3bUq1cvRu2gpARavXo1XbhwgZ3TunHjBtnY2IieAS0vL6chQ4bQ/v37RSlNduzYwQF/aCj37t0TnbeI6hGNG6NLkcvlgqixqtIYHQvRX+P4/N8gn3rOT/GtNsbhTFT/rsTOdxHVA4g1tgbk5OTQqVOnRO8zLy+PIiIiRNfB3Nxc6tmzJ0VFRQmeuS4oKKDWrVtT37596YcffqCrV69yzi2WlpaSnZ0dNW3alHx8fGj06NG0dOlSOnLkCN2/f59yc3N5lAjW1tbk6elJPXv2pJEjR4qCKjWcixqzf4rHVAzJUnWubAwIR11dncfj3FA/BaTTcN7S0NCgVq1aUUBAAI0ZM4bmzJnDwFOaNWtGAQEBNHPmTNq1axclJCRQWVkZhYSEkJqaGvn6+lJERASdOXOGc6Z29+7dpKurS4MHD6aDBw/y1ua0tDQyNDSkiRMn0vXr1wXPyLu7u9OUKVMoOTlZsM+MHz+eJkyYwAF1UpU1a9bQkCFDKCkpSdB+5MgRCgwMFMVbuHDhArVr106Ux/Tq1atka2tLmzZtEpzH4uLiyMjIiObMmSPIkX7p0iXS0tKigQMH0uHDh3mUdjdu3CCgHoBx9uzZPL7oBw8ekFQqJX19ffL396fp06fT7t276e7du1RRUUFJSUnsbLmWlhY5ODhQYGAgTZgwgRYvXkyrVq0SPGcrkUjIwMCALCwsPkkp8ykMFEtLy0b7o6OjY6N0diYmJrRw4cJGuXmnT5/OAadrqM2bN+cBDjVUZ2fnTyLhigEKGRgYkKOjI2/PYWNjQ71796Y5c+bQrl276Pz58wyrxMXFhfGQPn36lPWvbt26kZGREY0aNYpiYmJ4+/LQ0FBycXGhlStXCs6lixYtooCAAPrll18EzwuvWrWKQkJCRHErVqxYQePHjxc9q/vfLfjvAjX6K/pPd0iLi4vp9u3bbBH45ptvOBOKXC6nxMRE1tm3bNnC2xSUlJSQiYkJmZmZCXLZVVVVUbdu3cjKyooH109U7yzOmjWLbGxsBA8jK/mJrK2tGZhHQ3n8+LEgUqjqNYyNjenSpUuibfHFF19wkG8byrRp02jRokWiG5o9e/ZQ//79RQng7969S/b29qKLkxJyf9++fYJ2uVxOFhYWNHjwYEF6iJqaGurUqROZm5vT3r17ee+psrKSoV0GBARQbGwsZxGrrKxkh8YlEgkFBATQtm3bGIpvdXU1zZkzhzfRde/enb7//ns6ffo0h9NWaGFo6MgpVVtbm9avX89Bb1TVYcOGUXl5OcXGxvIOvWtoaLB+d/v2bd4CZWBgwEBiXr9+zdvU6erqMoCVwsJC6tu3L+/7//jjD9bGQnD88+fPZ+0YFRXFDvYr77V169aMqujPP/9kCJGqiHXKvpmSksJZOJQL6oQJE4iofswq+WRV1djYmN68eUMKhYJ+/PFHQUTlSZMmkVwup7i4OEGwMKlUSps3b6b09HT69ttvBRdqiURCs2fPpq1btzYKaGZpaSkaYGjRogUFBgZyAgxKlNyVK1fSgwcPqLy8nCFwa2lpUUhICP3666/McVEoFLRt2zYCQO3bt6e9e/fyxl58fDxpamrSV199JUj6XlBQQCYmJrR69WrRcevn50f79+8XdajCwsLol19+EZ0XDhw4QMeOHRO0ERElJSXRzp07G3XoVq5c2ahDt3PnTobEKiSnTp1q1DF//Phxo0TjSqTJxmTJkiWN3sPy5csbDQru2rWLNm3aJGq/fv06devWjUMJpip5eXlkaGhIu3btEmyruro6MjExIT8/Pw6SsVJkMhn5+/uTRCKhfv360Z9//sm5TllZGYdaq3379rRq1SrWr8rLyzkol8o+7e3tTWFhYRQTE8PomMT0U86ir6+v6JjT09Oj8PBw0Y2vsbEx/fjjj4Ko9sq5KCoqilasWCGIpAmAZs+eTZs3byZXV1dBe5s2bWjz5s2MD1to7hg6dCjNmzdPFIRKS0uLgoODRQF7lPNUQ77Dv9KWEomE2rVrR2PGjKGFCxdyAnJqamrUrVs3ioqKogcPHtDdu3c565WdnR0tX76cMjIyqLq6mh48eMChpgoMDKTTp0+zdffp06e0f/9+9r1ffvklJ3iWlpbGHDoAPMf0/fv39OzZM7aGBAUF0a1bt5i9uLiYnj9/zt6Vm5sbHTlyhH1/TU0NPXjwgAUOmzZtSpGRkRx+8jt37nDmYFUOUqJ6dGvV4IKWlhYNGDCAYmJiqKSkhJKSkngBDDU1NerYsSN99913dPDgQVF6G6lUSg4ODo0CNwEQBX5S9umBAweK2nv06EGbNm0SZReYPHkynTlzRnTMjB07lu7cucNQ/Rtqp06d6MGDBxQZGSnY35o2bUq//PIL/fjjj4J0SQCob9++tHv3bho2bJigU6umpkaTJk2iuXPnitJCaWlpUZ8+fUQBPlX7vlhQX6liDr6+vj55enryOIIlEgl16NCB5s6dS3v37uUFyjt27Mj2FPfv36f4+Hhma968OX3//fcswJeUlER3797ljKmLFy+ytTEtLY2uXLlCQP2+b8aMGY2ua/8dgs8O6b8uQrxlZmZmtGfPHqqrq2MIaqr6X+diiah+EdfX1+csLkOGDOE4TP7+/hxY8Llz53I2LuHh4WwwC/FrxsTEMHhzTU1N2r17N+cZnj9/ztBLNTU16eDBgxx7ZWUl+fj4kJqaGqmrq9OePXt47TBkyBA2ca9evZq3OVy0aBFbACdNmsTLihw9epRNFj4+PsyJU8qzZ89Y9q5JkyY8pLWKigqOozRhwgQO1yoRcQimTUxMeHD948eP50xobdu25QQAhDhnnZycaPfu3SSTyejcuXOiC0e3bt0EeUxV1dPTU3CzpKamRhMnTqQ3b94IkrYHBAQw1LiG2UmpVErr1q1j72PdunW8yVMVsbbhM2hqanLa4Pnz57wJVxWt9+PHj4zmREmtMGfOHGavra1ljlxYWBhpamqSu7s7pz8rI519+/alvXv3klQq5WwkYmJiCKiPeL548YJsbW1p1qxZzK6MGuvr6zOEU1dXV+YwlZWVsb44ceJE6t27N6mrq3NQiQcMGEBAPdK0cmyMGjWKbVZU21G54dHT02Pca8ogVUO1tbWl69evU01NjejG2MLCgnbt2sXQgIVUTU3tkyTdYtFefX19GjNmDGvHhn8zc+ZM5viojimJREIDBw7kvIvJkyczh9/MzIxDsUFEtH37drYh8vb25mUqbt68SdbW1gTUcwc3zNAVFhYy6ptx48bxMgyqtC0TJ04UzBKuXbuWtLW1adiwYYL248ePk42NDXXr1o13faJ6FExvb29ydHTkbEaVUlRURH369CEDAwPRgKCyT0dFRfHsRPXUDGZmZtS7d29BpzQmJoYcHR3J2NhYMKN9584dhvYZFhbGC6Z9/PiR2c3NzXkI3AqFguM8dO3alYdEOWjQIM78GBwczKFv+Pbbb3n9ydHRkaKioqikpESwvynV1dWVQ4EkpGZmZqLZS0NDQ4qMjBQdE76+vhQfHy+KpD5o0CDKzMykNWvWCNpDQkIoNzeX/vzzT0H7F198QWlpaZSbmytIVaIMJisUCjafNBzP33//PVVXV3MoPFTVzc2Nbt261WjlxYgRI+jEiRONzhtCFSwNVZWH+u9QMScLqHdcN27cKOrU9+zZk65duybKHqB0TIV4cZV/n5CQIEhJBdQHP6OjoykpKUnQrqGhQePGjaPExETRgGHTpk0pPDy8UQYETU1NNvf9q9rYGuDs7CzKWatEaP748aNg1rBJkya0b98+UigU1Lt3b569WbNmjFZwwYIFPLuOjg7t37+fFAoFHT9+XPAeIiIiqKamhiFCN1QlF3Jtba0gQ4K2tjZt3bqVFAoF9enTR/Aabdq0oYcPH4qyMAD13LzR0dGNtrNQkL2hfoqO5d/Vxio3pFIp9e/fXzSb7e3tLcrdq6OjQ5GRkTyk7f8uwWeH9F8XMfJlANSuXTvRSVEqlVJYWBhdvnxZMKpjbGxMR44coaKiIsHIkfdR3UYAACAASURBVIeHB4sGCmXNgoODWQlwWFgYzz558mS28dm3bx8v2hoREcE2NQkJCbxMT2RkJHN68/PzeXxe06ZN4/CQNrzH4OBgTkZlxowZHHurVq04GZl9+/ZxFnplJkrpaN27d4+3Affw8KBXr14RUX30XShiPHToUFYyocr1p6r9+/enly9fUlRUlGiJpqmpKU2cOJFatmzJs6mpqZG/vz99++23vJIPY2NjCg8PZxnIiIgI9hwSiYTGjBnDKYU+ePAgc0oNDAx42YwHDx6w7J+RkREvo11eXk6LFi0iPT090tPTo7i4OF6f3rhxI/Xs2ZMkEgnPaSeq54Q9duwYAaB58+bx7Pfv36fr16/T8uXLydPTk/FmKiU3N5dlvDp37szhCM3Ly6Off/6ZZajfvXtHkZGRzP748WOKiIigPXv2MOdh2bJlzNF49+4dffPNNxQdHc3abfXq1ZzM0t27d2nbtm10/vx5IqrnwG0YZElOTqY1a9aQTCajQYMG0eDBgznl5EVFRRQaGkrJyclkZWVFFhYWHBh4uVxOI0aMoCVLlnDGnKrDM378eE6AwdDQkH744Qc2LubNm8ejfGrRogUtXbqUsrOzafv27YLRWjs7O4qIiKDNmzeLbng8PDxowoQJolkSTU1Nmj17tmhGvlOnTnT+/HnBsmhLS0vasWMHVVdX0+bNm3n24cOHMzj8ixcvchZaAwMD2rp1K+vTKSkpnLmnVatWHIe4rKyMw0Pq5eVF6enpnHep6th37NiRVx0xdepUzsLdsIRKmUUG6sveG0L5q2ZpDA0NeaVSubm5nLlp+/btHLtcLufwzQo5pZMnT+a0UXx8PMe+d+9e3pylevTg7t27HCdDKpXSqlWrWDsXFhbysgc6Ojq0YcMGNo9/+eWXvHepnKPS0tJo/fr1jWYHRowYIdgfDQ0NafDgwbRu3TpOOwD1m/8vv/ySzpw5Q7W1tTRs2DBOcLZ58+a0Zs0aVja+dOlSzrEDOzs7Tvb9+PHj1LVrV2Zv2bIlh2f05cuXNHz4cDaujIyMOMc8ampqaMiQISxgpaGhQWvWrOEEAMLCwjib9NGjR3NKXTds2EALFixgjoCLiwuncun48eM0adIk8vPzI6B+o7ty5UpWnvfw4UPq378/x1Hw9vZmGfri4mLy9/fn2KVSKY0fP54FGbp27cppB+X7VnKRjh49WjAjpaGhQQMGDKCQkBCytLQUzdI2a9as0eMj/y/0U6WmqvOCkIrxvytVeTymsd9prMxUdYwI/b8yaCvEc9qkSROaMGECLV++nDcuNTU1aezYsXT37l3Ky8vjlcM6OjrS4cOHWZ9U7c9AfdZMdT1cuXIlJ2vXr18/TuDtt99+4+zPunXrxgkcvnjxgiZPnsyypC4uLpzrV1VV0ejRo1n1V5MmTejUqVOc+Ss8PJz27t3L5qi5c+dyylHXrl1LK1asoJCQEALq1y/V7zh69ChNnz6dcUarq6vTkiVL2DUSEhLoyy+/pM2bN7NAh729Pavc+vDhA3Xp0oVmz55NXl5e7FmDgoLYfN65c2caPHgwBQQEcNq7X79+dO3aNRo2bBh16NBBMFvs5+dHPXv2JFtbW9E1V09Pj7S1tf/WcSM2XoH6eXjFihWfPGLzdws+O6T/ushkMnbWS0zFIn1A/YLaunVrUXu/fv0oKChI0KapqUnr1q2jcePGCdpbtGhBV69eFXWKvb29KT09ndavXy84afbp04eKi4spJiZGMPozZMgQqqyspMuXL/POwwH1BMoVFRX0/Plzwcnfx8eHPnz4QIWFhdSrVy+e3cjIiG7evEkKhYIWLVok+AyhoaFUU1NDcXFxgu2sr69Pv/zyCxUVFZGnp6fgNUxNTenEiRMcHr2Gg7hFixb03XffsQVIXV2dcTwuXLiQDh8+TPfv32eTmaurK4WHh/POhERFRZFUKqU+ffrQ8ePHec5aQUEBqaur07BhwwTPpBARDRw4kPr16yd63uv333+ndu3aNXpGwM7OrlGuqTlz5tDmzZtF7RUVFRQUFMQ781tUVMScw7i4OE5Q4dGjRzRhwgSOA6o8V5yVlUWzZ88mXV1dXjlgTU0NJSYmssWo4WKmUCgoKyuLZsyYQZqamrRixQre3ysUCrpy5Qp1796d7OzsOJky1cU3IyODFixYQBEREez/fv75Z95ZDblczs6rBgQEiPKQXr58mczMzCg2NlbQ/tVXX5Gmpibjemz4XMrNSGBgIJ04cYJTWVBXV8fmDjc3N1q8eDElJiZyNs/KDKebmxvNmDGDTpw4wb6npqaG2rRpQ5qamtS+fXsKDQ2l3bt308OHD6m6uppqa2vJ19eXmjdvTgEBAfT111/Txo0b6ezZs5SamkoymYwGDhxIrq6u1KNHD5o4cSJ9//33tHPnTjpz5gxlZWVRREQEdezYkXr37k0jRoyg0NBQioyMpE2bNlF5eTnt2LGDAgMDqWfPnhQcHEz9+/enkJAQ2rRpE9XV1dGZM2eob9++FBgYSH5+fuTp6Unu7u4UHR1NCoWC7t+/TyEhIdS5c2dydnYmY2NjMjExYcGGjIwMGjFiBHXo0IEFzVq1asX4IQsLC2ny5Mnk5eXFNoaOjo7M6ayqqqI5c+aQh4cHW8xtbW3Z2FIoFLRy5UpOJrlJkyacc+bR0dG8OX7v3r3Mfu3aNV6wTNUpTU9PJ3d3d45dR0eHLly4QET1FSzBwcG8ecvLy4uVYwlVdwD1kf+PHz9SamqqaCmaj48PJSUlccrctbS0yMbGhjp06EADBgygmTNnskyIRCIhBwcHGjJkCK1YsYJiY2Pp7du3VFtby57D29ubFi5cSDdu3OD0aeV9enl50ebNm3nnEpX8mfb29qJl1l26dCEjIyP66aefePMrUX1Vk5qaGs2fP18QL0ChUJCBgQHLigrJnDlzyM3NjQUSG8qNGzeoadOmoqXmdXV1pKenR/Pnzxct0/b396euXbuyoGpD+eqrr8jc3Jyio6MFS6xXrVpFUqmUxowZI3iNn3/+mYD6c3Dr16/nZUhUSwO/+OIL2rFjB+d9pKamsjGhpqZGXbp0oTVr1lBSUhIpFAoqKChgRyuU/cLd3Z2+/vprOnDgACUlJZGdnR2vvzVp0oQ6d+5MU6dObbSs2MLCgnN9If2Uw9jYBl1DQ0OUu9zU1JS6dOnCAhOq6uTkRGPGjKGoqCg6ffo0x+F0dnammTNn0unTp6mkpIQUCgXbM+jr69OoUaPo9OnTnH67cOFCAkDW1ta0atUqXkAtISGBAJCDg4MgX7VCoSBzc3OysbGh3377TfBoQ2RkJBkZGdHhw4cF7SkpKaSurk5r164VPYf+xRdf0Pjx40WPbuzZs4c8PT1Fz5hXVlZSs2bN6Pfffxe0ExH179+fwsPDRcfMrl27qG3btqLjMiMjg3R0dGjFihWC11AoFGRjY0O+vr6iHMFDhgxhx1iE9mjK92VhYUGRkZG8I2Zbt25l/cHOzo7mzp1L8fHxrF0bBhetra1p7NixtG/fPnrz5g2tWrVKcJ/7xRdfUFhYWKOVVc2aNfvk+XNTU1OKiopqFM/l7xT8p3hI/xX5J9O+EBHCw8Nx5swZxivatGlTpoaGhoiLi8O7d++gp6eH5s2bQ1tbmyH7aWtr49WrV3j//j2aN2/O+IJU2zkvLw/FxcVwd3eHhoYGqqurUVVVxT6Li4thaGgIHx8fyGQylJaWoqSkhPPZqVMneHh4oKCggPGLKlWhUGDq1KkwMTFBdnY2T62srLBkyRLU1tYiIyMD6enp7DMrKws+Pj5Yu3YtPn78iNTUVLx+/RqvX79GamoqsrOz0aFDB+zcuRM5OTlISUlBamoq4ynNzMyEvb09jhw5gpKSErx58wavX7/mfMrlcuzduxfm5uYcnlFVbd++PcLCwlBRUYHCwkIOipvyZyU3KBEx5ERVraysRE1NDVq3bg0jIyM0a9YMRkZGMDIyYkimsbGxqKurg4uLCxwcHHh8WZmZmYiPj0dgYKAoNPlvv/2Gjh07ivLLpaamoqqqSpRbEgDi4+PRuXNnURS2lJQUWFlZiXKOKb+ndevWovaMjAzY2tpy/q+mpgZJSUnw9vaGRCJBWVkZDAwMoFAocP36dezfvx9APe2KKjfW2bNn8dNPP+HatWsIDw9HVFQUu2ZaWhrWrl2LAwcOoKamBqNHj8bhw4eZPSkpCcuWLcPJkycBAIGBgbh8+TK7/vv377FmzRrs3r0b1dXVsLGxwYsXLxjyo/L7V61ahbt37wIAzp49i759+7LvUCgUuHjxIrZv345z587B3NwcT58+5aE719bWIj4+HidPnsSDBw8QGxuL5s2bi6JoExGSkpLQokULQc4xAFiyZAkmTZoEGxsbni0pKQl79+7FtGnTBLnVEhMTceHCBYSEhMDJyYlnT01NRWJiIgICAgRR+fLz85GVlQU3NzdBJFblPCOG2Ef076FC/10il8tRXFwsyFcnk8mQmZmJ4uJi+Pr6cu5foVDg7du3ePHiBcrKyjB06FAOsqVMJsPTp0/x6NEjfPz4EXPnzuWga5aUlODBgwe4e/cuUlNTsXz5cg5fXUFBAe7du4e7d+/i3r17mDZtGgYMGMDs+fn5ePDgAR48eID79+/D1NQU27ZtY9/x8eNHJCcnM3qmlJQULFy4ED179gQR4ePHjxzKobS0NCgUCqxevRoGBgYM0bIhyqWhoSH69OmDsrIySKVSphKJhP2snP/Nzc0ZxVbDd3/58mXo6enBw8NDEJk1LS0NCQkJ6NGjhyhK5LZt29C5c2dRDtCrV68iPz8fX375pSBKZW1tLZYtW4Z58+aJorPv27cPPj4+ot9RWFiICxcuYOTIkaL9+8yZM+jRo4couuqTJ09gbGwsyDsJ1CP+Pn/+HJ06dRK0A/XckkOHDhW9h/3792Po0KGiCK6bN29Gz549RSnTVq9eDWdnZ/Tv318QRXbRokXQ0dHBqFGjeGsBAERGRiI/Px/BwcEICgrioYpGRkbi0aNH8Pf3h7+/Pzp06MD5nUWLFuH06dPw8PCAh4cH2rRpAw8PD1hZWUEikWD9+vXYunUrHBwceGpnZ4djx45h4cKFjHvUxsaG8/Pz588xd+5cDv+o6s+FhYWYNm0arKysOJyMSi5SABgwYADMzc3h4uLCUWNjY9TW1mLQoEHQ0dGBj48PfHx84O3tzZkvFy9ejDdv3iAoKAhBQUE8/sq7d+9i48aNGD58OIKDg3mIxUSEyZMno3///qLv6cCBAwCAMWPGCNpzcnKwZ88ezJ8/XxQRee/evejfvz+aN28uaH/+/DlkMhnjDxeSixcvomfPnqL2xMREODs7i46Z0tJSFBYWCvY1pSQnJze6N0pKSoKLi4sol+nr16+hoaEhuN4C9ajNV69e5XFMK6Wurg7r1q3DpEmTBKnc5HI5Zs2ahT59+qBXr16891FbW4vhw4fDy8sLgwYNgpubG+d7ysvL0b17dzg5OaFr167o2rUrWrVqxX4nMzMTXbp0QevWreHl5QVPT094eXnBwcEBUqkUcXFxGDJkCOzt7dG6dWuebt26FVu3bkWLFi0E1cLCAi1atGgUWfrvlr9K+/I5Q/q/UORyuShKpkKhoMLCQtHsj7L+Xwxdt6KigpKTkznnjFRFJpPR06dPOSV4Db///fv3dOvWLUE0MaWUlJQ0ir77WT4tVVVVlJCQwANmKSoqop9//pmGDRvGKwHOzMykFStWsCi3paUli7KXlZXR1q1bOeVGNjY2LCPx7NkzGjNmDCdCbWBgwDI6SUlJvBJBqVTKytTfv39P4eHhvMy9ssS4traWfv75Z15maeDAgez+CwoKaP369bwovTK7RlTfR2NjY2nChAksGq+lpSUIDpaTk0NnzpyhJUuWUN++fdn5ls/yWYTkr/SNxlBx/+o1Pstn+Tvk30WF/lQG5lPo25/6+3937Py79r/6O/+/iFhbyOVy+vDhAz158kQwa1lTU0Pv37+nxMREUTRmhUJB5eXllJ2d3Sjq+z9d6urqGu0zVVVVjdorKysbtX9qTP0TBJ8zpH+v0D80k/BZ/ncLEaGwsBCZmZlM/f394eXlhfT0dNy5cwd3797FnTt3kJiYCDc3N1y5cgUlJSWIjY3F6dOnER8fj7q6OgDAli1bMGXKFMTGxmL//v34888/WTZfIpEgLi4ODg4O2LJlC3bv3s3jAD1//jzMzMywatUqnDx5Eg3nkx9//BE9evTAsmXLcOLECd7zTJs2DYsXL8batWuxc+dOVFVVceydO3fGxYsXcejQIaxduxZpaWkcu46ODp4/f468vDxs374dx44d4/CsAsCUKVOwceNGnD9/HidPnsS5c+d4XKQHDx5EcHAwy2YpNTs7m/3OokWLsHTpUpSXl7NMvVI/fvyIwsJC1NXVYdasWY3y6H2Wz/JZ/jNSU1OD0tJSyGQyVFVVoaqqiv2s/ExPT8fHjx9ZJqG8vJyj+fn5ePPmDQwMDBAYGMi4NpVaXl6OtLQ0lJSUIDAwEJaWlozDVPlZWlqK58+fo0mTJggODoa2tjYncy2VSvH06VOUlZXBzs4Onp6eMDQ05GhJSQkSEhJgZWUFa2trmJqa8ngs79y5g5YtW8LCwkJwf5KTkwNDQ8NGeUQBQEtLS7RN6+rqGs20fGpv9O/aP8XxXltbK5pNA/7++/+nCBFBLpejrq4OtbW1qKurQ11dHWQyGeMC1dfXZ5V3Si0oKMC7d+9QV1eHoKAglJWVIT8/H3l5eexTaR88eDB0dHSQm5vL0Q8fPkAikSA4OBiWlpacv83Ly0NRUREAoEWLFujSpQvj+1XlOy0qKoJcLoezszO8vLwgl8s53N81NTWorKxERkYGnJyc0LFjR+jo6PC4iF+8eIHc3Fw4OTnB29sbZmZmjCdWW1sbMpkMv/zyCxwdHeHk5CRYhZOcnAxzc3PRqqjS0lLo6uqK9iuFQgGJRPI/ot/8HfJXM6T/Pfnb/wEil8sxb948LFmyRLBM6MOHD1i1ahVWr14tOLnL5XIsWLAAK1asEJ3cDxw4gFGjRomSnMfHx6NDhw6if5+amgorKyvRko3i4mJIpdJGCXPz8/NFB5nyGo1trj9FyPspe3FxMZo0aSI6UEtKStjkIiRlZWWora0VJcquqKjAhw8fYGdnJ2p/9uwZfH19Ra8fHx+PoKAgwXsoLCzE2bNn4evrC0dHR95CmZOTg2PHjjEyZgsLC5ibm8PAwAASiQTp6enYt28f6urqGIm68ue6ujqUlpaCiFBcXMwc0IqKCnb9GTNm4OLFi7h79y7y8/M53+3h4YHly5eja9euSEpK4t17aGgoHBwcYGVlhYKCAp49MjISJiYm6NatG16/fs2zjxkzBr169cLJkydRWVnJs7u7u2PmzJn48OED2rdvj1u3biEnJ4fZmzZtiuXLl0Mul8PW1hYtW7ZESkoKs0skEmzatAlVVVWoqakRLFf+/vvvYWFhgdjYWFy/fp3njNra2mLDhg3YuXMnli1bxmk7pcyaNQuGhoawtrbmOcRKWbhwIV68eAEtLS3mzDeU1q1bQ11dHXFxcaw0XLVM3MjICL/99hskEgkCAwPh6+sLd3d3ziKWlJSE6OhoDB06FB07duT1JyLCTz/9hC+//FK0ROnGjRvw8PAQHbdZWVkwNjYWnTeqqqoglUpF5yWgfn4TIwFX3uf/r4vvf1I+tTmvrKxstMw/Pz8fBgYGoiV3mZmZqK6uFj0K8Pr1azx48ABBQUEwMTHh2VNSUhAdHY22bduibdu2cHR05PSb1NRUfPPNN7CwsICVlRUsLS2ZWllZIS8vD8OGDYNUKmVk9/r6+uxnuVyOY8eOcca1MtqubB/VfwuJVCqFmpoaamtrRX/HyckJr169EgyqAUDLli1RXV2NjRs3il6jTZs2uHnzJs6dOydol0gk0NLSEp2DlE6W8j41NTWZc6r8zMzMxJEjR9C0aVO0bduWlcx6eHjA3d0d5eXlcHBwQNu2bREQEICAgAB06tSJlQirqamxtSwkJATBwcG88uGwsDCoq6tj0qRJ8PT05N3nli1bkJOTg5kzZwoeYzl+/DiePXuGWbNmCa7bv//+OxITEzF37lzBowWHDx9GamoqIiIiBO0bNmxAaWkpIiIiBJ2L9evXo6CgAHPnzhW8vx07duDFixeYPn264LGK6Oho3Lp1CyNHjkTXrl15Tsjhw4dx5swZVtKrLBVWypEjR3DgwAG0a9cObdu2Rbt27eDk5MSuc+zYMaxfv56NAeW4UH4+ePAA3377LXR1dQX148ePuHr1KuRyOe/elSKRSBodE6ampsjPz8ehQ4cE7V5eXsjLy8OmTZsE7S1atMDXX3+NH374QXRczZgxA5WVlYiOjha06+vrY+3atfjxxx9x5MgRwd8xMjLCkCFDsHv3bty4cUPwd9TV1WFgYCB4DUNDQ3ZE5/379wAAExMTODk5wdnZGc7OznByckJRURHGjx8PBwcHVq7u5+cHNzc3qKmpoaKiAq6urggICEC/fv3Qu3dvjt9QU1ODPn36IDg4GGPGjIGFhQXnPuRyOSZPnoyRI0eiZ8+evLVTLpdj7ty5CAsLg4ODA+85ZDIZlixZggULFogea/gfIX8ljfr/Wv/pJbvK9HiHDh3IzMxM8FC4QqGgJk2akIODgyhBs52dHbVt21YUyGbQoEHk6+tLGRkZgvbFixeTn5+fKKfQb7/9Rj4+PqL2169fk4eHh2h5LhGRh4eHIBehUgYMGEC3b98Wtc+ZM4d+/fVXUfu2bdtoxYoVoiUHly5douHDh/PoXJSSlpZGXl5ePLoCpchkMrK0tBTkeiWqf09WVlY0e/ZswRJghUJBbm5u5O/vT8ePHxcsGQoICCBDQ0MaPXo0nTx5kkczoQTmMTQ0pO7du9OCBQvo1KlTlJ2dTUT1QBVocMhcV1eX7O3tafz48aKozu3ataPExETBA+86Ojp04sQJUigUtGvXLp7d1dWVASWcPHmSB/QQEBDASj2EEJfbt2/PSqqrqqo45PRAPcWOKmDP2rVrefegCmR06tQpHtKcKr/ikydPeGATkyZNYvb8/HzePTg6OjKgiNraWkE+Q1XEYSG4/G7durF2iI2NFQQCW7JkCRHVlzqLcZ4p6Um+++47UWABLS0tCg0N5aA86ujoUKdOnWjOnDl09OhRSk1NZUBdlpaWNGvWLLp16xanVG727NkklUpp0KBBFBcXxxtbMTExZGhoSIsWLRKEfX/8+DFZWVlRdHS0YAmcEtStIQ2TqowZM6bReWH9+vV0584dUfv58+d5qLKqkpmZyUFKFRJVaiIhOXv2bKMlhvHx8aJgHUT16KyNgYjJZLJG20h5j42VW+3Zs0cQhEcpe/fuFT0eQUR05MgR2rJli+h3xMXF0aBBg0SfIz09nVq0aEEbN24UvI/S0lIyNDQkPz8/2rlzJwdZlqh+3Lm4uJBEIiFvb2/69ttvKS4ujo1LhULB4UTU1tam9u3b0+TJk2nz5s10/fr1RnlIDQ0NBcHxlGpmZkYRERGiqKfOzs509OhRUbokOzs7unTpEgeVWVUNDAzo4MGDdPr0aVGwnTFjxtDly5dFqV2MjIxo8+bNtGnTJlHqFWdnZ1q3bp0o2CFQD3DzKRodAwMD0WcF6sFUGnJcqqmpkY+PD82aNYuOHTvGocnR1NSk4OBg2rNnD2VlZVFtbS3FxcVx1iglUJVCoaDa2lp6+fIlAfUggaNHj+ZQGtXV1VF2dja712+//ZaDgC2Xyyk3N5eAerCWhlzIcrmcUlNTWbuuW7eOs3eQy+V08+ZNdv1FixZx+qwSNE35bFOmTOHtLd69e8fQ/7t160YnTpzg7AuKi4vZezQzM6OZM2fSzZs32Vwjk8k4yPx2dnYUGhpKx48fp4KCAqqpqeEh82tpaZG3tzdNmjSJNm3axEGFFXuPYjZnZ2caPXq0qH3KlCmi1DESiYQWL15Mr169EmQXAEDh4eGUk5ND8+fPF7T7+/vTmzdvKCYmhoOOrbrmHTx4kK5cuSIK3tm2bVs6e/YsLVu2TBQgNDAwkLZs2ULjxo0TRbFt27YtzZ8/n6FbC2nTpk1p0KBBgtROqiqEAK2vr08BAQEUERHBQcBWU1OjgIAAWr16NSUnJ5NCoWAUWlKplHr37k1Hjx6l8vJytgYr+XtdXFxo165dbJ+ptA8bNoxDF6ja54mI2rdvT8bGxrRly5Z/XBkvPqPs/uvyyy+/kKOjI2dABgUFsXOVGRkZZG1tzRBgJRIJzZ07l3UguVxOPj4+jHhYR0eHR/I+ZcoUxl1mZGTE4Y0kItqyZQuDaLewsOBt/q5evcog3q2srDgop0T1tARKIm4LCwueXS6X09SpU0lHR4eMjY0FN5crVqygVq1akY6ODuNiVJWDBw+Sj48PSSQSQS6++Ph46t69OwH1HKINz4xmZ2czJElPT08e9UJdXR2bWA0MDAQ3oLNnz2bO1ODBg3kE8atXryYTExMC6pH+1q1bxznTcOjQIQ4SpY2NDW3YsIGdWbh+/TqPpkNXV5eGDh1Kx44do+fPn4tuVLS1tenbb78VtFtYWNCOHTsEFyc1NTVatGgRay+lw6v6t6qInw0Rl52cnDjt0HDxadWqFceZvHTpEseup6fHOUP88uVLnsP6888/M3tJSQnry0qHbfTo0cyuUChYPwgICCA1NTVydnbmTJrKxU1JCm5gYMB5hl9//ZW1vXIxvnjxIrO/evWK3aPyMywsjNlramp4xPU2NjaczdC0adN470npjBLVIx0LveN9+/YRUf0ZW7FFbeTIkZSRkUGdOnVqdNFr2bKlIC2B0jndvHkzDznV3d2ddu7cSeXl5VRaWsp5Tn19fVqwYAHnfatuAjw8POiPP/7gzE0bNmxgPKNCzszZs2fJ3t6eJBIJhYWF8SDlNgrP1wAAIABJREFUX758Sf7+/qSmpkZLlizhLY5VVVU0ZMgQUlNTozVr1gg6jWvWrCGJREIrV64UdLZOnTpFzZo1o/nz5wv+fUJCAnl5edGoUaMEF+e3b9/SgAEDqFOnToLnk6qrq2nmzJlkbW0tGgzbtWsXaWpq0tmzZwXtp06dIgsLC5o/f77gM1y/fp28vLzI29tbEPn11atXFBgYSLq6uoJzX0VFBfXr14+Aeh5GZQBMVZTBMC0tLVq0aBEv8Ldw4UK2mTMyMqJly5YxpGkiop9++onjRGlpadGwYcPo3LlzVFtbS8ePHxdEQtfV1aU+ffpQZGSkKM2GgYEBhYaGijqTvXr1ojt37pClpSXPJpVKKTw8nIqKiqhnz56C9sjISJLJZKIb54kTJ1JpaSlDpm2oPj4+9Pr1a3r16pWgXV9fn2JiYqimpkZ0DVC+F6F7BOpRX5cvXy6KBq98L4057QDYeP07VfmehDbmmpqa1K9fP1JTU6NWrVrx5sEuXbrQqVOnqEWLFuTs7MxBytXV1aV58+ZRTk4ODRw4kBwdHTn25s2bU1RUFMlkMlq6dCnPUVJdS0+fPs1ri6ZNmzLqCyUia8O+MmLECEpMTCQiImNjY16ftLS0pGXLltH79+9FnZuWLVvS/PnzBVF6VdtQqD+rakOMBFXt1KmTKPevrq4urV27lkpLSwUDHxYWFmyfKcR93rx5c4ZCq0pJpVQdHR2KiYkhIi6qrKqGhoZSdXU13blzR9DeqlUrevz4MZWVlYnS7YWGhlJlZaUor62uri7t3LmT8UALqYmJCY92UOg6f/eYUX3vQuNGT0+PJBIJWVhY8FgrjI2NacGCBWRkZEQeHh4c/lt1dXWaPHkypaenU9++fcnb25uD6u7s7Eznzp37x5x3xmeH9F8XoYwWUL8YL1u2jH788UdBu6OjIyUkJNC1a9cE7SEhIVRQUED5+fmCi/SCBQuotraWFAoFL7KkoaHB4VUcOnQob3CpUmc0JAPX09PjOL2XL1/m2LW1tTnQ3Hl5eZxFQU1NjW28ieqdjIYEzg03h6NGjeLYAwMDOdHKhnyGpqamnKzJ3bt3eW309ddfM8dfJpPxosHNmjWjgwcPsoEotBGwsbGhw4cPk1wup5UrVwrCxOvr61N4eDgdOnRIkDPWxMSERo4cSfv27eNlzdq2bUtbt25lzzpmzBj2vps2bUpr1qzhbAw3bNjAHLqG/HVE9Q6jkifL09OTRw3z4cMHmjRpEgH1Dl3DjWldXR2Fh4dTu3btSF9fXxBEYP369ewa+/fv59nPnDlD+/fvpxYtWlBwcDBvoktJSaEVK1bQq1evOEBGFRUVVF5eTiUlJWyD2LVrV0ZvcffuXaqrqyO5XE6LFi2i9+/f0/Tp02nNmjVEVO8EKil2oqKi6M6dO7R48WIaOnQoEdVn0pQbiZMnT9Lu3bvpm2++odatW7M2VvaXhw8fUmhoKHXp0oV0dHR4QZr3799Tjx49WCBp6dKlHHtNTQ35+/uzDY+9vT0Pir579+4c593Pz49DxTNy5EheNNfY2JjmzJlDz549owULFohu0PX09HjBC1Vt2rQpjR07VnBu0dPTo2+++YYyMzMF6ZwCAwNZJqMhOb22tjYtXbqUtWPDDX7Lli0Z9xtRPfWE6jP4+PjwqIJUF+fg4GBO9UJJSQkLIgH1vMKqWRKFQsHJlg8bNowHnKHKpRocHMxzxLZv387s7du352WSb926xZ6hRYsWvCqSvLw8NvdoaGgI0hap8m+GhobystHK8QbwOZqJiFf5EBERwcnU3Llzh9OORkZGnGqV8vJyXtWBtbU1/frrr2z8qkb1Vee+b775hnJzc2nJkiWC/UkqlVJwcDBt376dNz9qaWnRwIEDKSYmhp49e8bL5jg7O9PWrVtZIOOLL77grDWdO3fmVFdMnTqV8xxffPEFJ2u8Y8cODoiZq6srhzf2/v37nCxLs2bNOBU1ZWVl5OjoyHlf33zzDSeA2q1bNxo/fjzrE0pnVfUeg4ODGT2Djo4OBwAtKiqKPD09aeLEiew7OnbsyHgXr1y5QpaWljRixAg2/0ilUpoxYwZ9/PiRcnNzSVdXlzp06MDWCqA+g7xkyRIqKioiY2Njat68OeNCVaqBgQGFh4czJ0SMNqVh5vQ/rdra2o3S6VlbWzc6/9nZ2Qny6irV2NhY0NFSVbHAgVLV1dU/6fwbGhoKzuGGhoY0duxYmj9/Ps9h1NXVpalTp1JycjJlZmby3oW3tzedP3+eFAoFKRQKat++PcehGjJkCKcS7quvvuJwtg4fPpwzx27dupVDa9W9e3dOAPjOnTvUvn17Foxv1aoVW2eJ6rPEHh4eNHLkSNandu/ezZn/unXrxui1gHraK9V5dsqUKTR8+HBauXIlm3eOHDnC7Bs2bKBOnTrRTz/9xKqG/Pz8WIDw3LlzLPus6pxOnjyZCgoKKCMjgwwNDSkwMJAiIyPZXKmhoUHh4eGMS9rW1pa6d+/OoSOSSqU0fPhwcnFxIXV1dTIzMxNcN8UqHv5Tqqam1igNUo8ePURBo/6Tgs8O6b8u2dnZomWUQP2m38XFRdAmlUpp3rx5ghEooD7SduXKFdGJs2vXrpSTkyPKMzp16lSqrq7mELur6urVq0mhUNDZs2d5jpZUKqUdO3YQEdGDBw94UV1Ve3p6OmfCUqqy/La4uFiwlGr06NFUXV1NdXV1NHfuXJ7d1dWVlSj/+uuvvHvU0NCgXbt2EVF9hqDh4grURxCfP39OVVVV1KNHD8F26N27N719+5Y2bNggaG/WrBmNGjWKrl27xhwEAwMD6tixI3311Vf0008/0aVLlyg7O5vatWtHGhoa1LVrV1q1ahU9fPiQ43ivXr2a9PX1acqUKXTv3j2es5aRkUG6urq0YMECTvZBVbp27UoRERGiXFz79++nQYMGiZYYKvktGyvPnjp1qih3JhHRvXv3aOjQoZz7l8vlHP600NBQlsmurKyktWvXcr5ToVDQyZMniajeiQ0ODuZlsB4+fEgVFRU0e/ZsGjt2LO8+EhMTKS8vjyZMmEDBwcE8+6NHjygzM5MOHDhAlpaWvAxXbGwsK3Pds2cPrVq1imMPCwvjLHxVVVWcLJ+DgwMtW7ZMtJ3Mzc0pJCREMLMml8vJ2NiYbGxs6NixY7y+UFNTw7gzAwMD6ejRo5z2rampYcEoNTU18vf3p8WLF9ONGzeourqal1FXV1cnd3d3GjVqFK1du5bOnj3Liyzr6uqSq6srBQcHU0REBK8sUCKRkKmpKbm5udGuXbvYJkNV1dXVycvLi+7cuUNhYWGCY2rUqFGUl5dHy5Yt49l0dHRo27ZtpFAo6NChQ7wMipWVFUPmvn79OtuUK7Vdu3Zs3khJSeEF7Dp16sQ2XAUFBbxMdKdOnViAqKqqikaMGMGxe3h4sBJ3JUey6qbS3Nyc8ZwS1ZfiqgYW1NXVOc7ggwcPOE41UJ8lV2Zr8/LyeGV5So5movogUmhoKK8du3fvzrLdf/zxh2Cp2pgxY6i4uJiKi4t5VQHa2tpkampKU6ZMocLCQlZirqGhQa1bt6Y+ffrQzJkz2fyXlJREampqpK+vT0FBQbR06VK6dOkSGy/K4ICOjg59+eWXdPToUV7GfPPmzSSRSKh///508eJF3pjIy8sjiURCvr6+gnai+iCJubk5xcTECNq3bNlCampq9N133/F4ShUKBb1584a1nxDXs0KhoOnTp1Pz5s0Fy7AVCgXl5OSQRCKhyMhIXrWP8p6GDBlC7du35/EUKu0nT54kXV1dioqK4gQolI5GaWkpSaVS6tatG0MfV4ry993d3UlPT4++++47zgZf2beUfdvBwYGioqJYQK+iooLq6uo42dg2bdqwObysrIw+fPhAK1as4PQZW1tbmjZtGv3yyy+UmJgoyB+uqalJvr6+NHbsWOrbt6/g/KAcJ5/iGf1U6eSnMluf4mQU4l9XtQntOfT19alTp040c+ZM+uGHHzhBGmtraxo3bhwdOHCA3r59y44BAf/XCY2NjeX0y3nz5hEAat26NW3atIlXCq9Manh4eNDvv//O6/NyuZwMDQ2pdevWLLjbUEaPHk1GRkaivLlHjhwhqVRKy5cvF0UvtrW1pT59+gge/SCq38OZm5uLsioQEbVt25a+//573ncon+n48ePUpk0bHq+u6jPb29vTDz/8wAnIqdpXrFhBbm5unONzCoWC7T2UZeQjR47kBJKU11MoFNSyZUvS0dGhmTNnspJYVYTbwYMHs33iV199Rbdu3aLS0lL6+PEjffz4kRMEVVdXp+7du9O6devo6tWr9PDhQ1bNoqrGxsbUrVs3mjRpEifQJDRuxALVnxozUqmUQkNDeVy3/0nBZ5Tdf11evHiBTp06MSSwv0P09PQYYlhDadasGczMzBggT8Pf8fT0hLm5OUM7y8vL49iHDRsGU1NTxluXnp7OAXuZO3cuLCwskJycjNTUVKSmpnJAbRYuXIg2bdogISEBr169QkpKCtLT06FQKAAA06dPx6hRo3DlyhXGP5qSkoKSkhIAQFBQEDZt2oSLFy+y71d+VlVVwdzcHCdOnMDTp0+RnZ2N9+/fM83JyUFeXh6mTZuGoKAgpKenM+5VpZaUlEAul2PixIkoKytj6GVKjj3lzzo6OigrK4OxsTFMTExgamoKExMTGBsbMwCBS5cuoa6uDu7u7owrTVVycnLw6NEjBAQECPLwAfVcfR07dhS1p6WlQUdHh3eQXVWePXsGNzc3Ufvbt29hbW3dKIBJdna2KBcqUA/E1ZCTrLS0lAEsVVdXo7KyEs2aNUNtbS2OHj2Ks2fPIiYmhgE6VVZWQlNTEwcPHsSSJUsQGBjIAz7IzMzErFmz8Pvvv+PAgQMYP348x3779m1MmDABqampuH37Nvz8/Dj2mzdvYuzYscjIyMCpU6cwaNAg3nOEhobi9OnT+Prrr7Fr1y6OnYjw9OlTTJ06Fffv30d6ejqnXZTtVFNTg+joaJw6dQpnzpxhoCG//vorhg0bxrmmEjxGoVBg8+bNmDVrliBoT0ZGBo4dO4bZs2cLAsXcvn0bZ86cweTJkwXBCS5cuIBz586hR48eCAgI4IF2XLlyBX/88QcDLHFxceGAbSUmJuLSpUuwtbVlamJiwu41KysLt2/fhqmpKczMzGBqagpjY2MGNFNeXo7k5GQYGBhAX1+ffSq/Qy6XIysrC2pqakzV1dXZz5qamiAiDsKo6s+tWrWCvr4+A+wqLi5GUVERiouLUVFRgV69ekFLSwtE9UBeyjnh/fv3qK2txbhx49h7Ki4uRlpaGt68eYM3b95AQ0MD4eHhzF5SUoIXL17g+fPneP78OdTV1bF06VL2XkpLS5GUlIQnT57gyZMnqKmpwY8//siAVsrLy5GUlIRHjx7h0aNHyMrKwpYtWxg/rEwmQ3JyMh4/foxHjx4hOTkZ8+fPR0hICIB6xNKXL1/i6dOnSE5ORnJyMlq1aoUNGzZAW1sbNTU1yMjIYDzPr1+/RlZWFr7//nt4eXmhsrISHz584Kmuri7CwsJYm6m2r/JT+X7z8vJgaGjI3qMq+qhcLkd8fDxatWoFa2trQZCqO3fuQEtLCx4eHoIIkgUFBbh69Sr69OkjOv8dPnwY/v7+osBy9+7dQ25uLvr37y84pogIS5cuxbx580QB8rZt24aOHTuKcirGx8fj/v37mDNnjugcunnzZgwfPlyUt1HJsx0UFCRoB+oBa4YOHSqK8nr58mXY29vzgG6U8uzZM7x8+RKDBw8WbIv8/HysX78e8+fPFwQjLCsrw9ixYzFlyhT06dOH96wymQydO3dGjx49MHr0aLi7u3PsVVVVcHd3h729Pfr06YPevXvDycmJ3UtlZSUD+unYsSP8/PzQsWNHeHp6QktLCyUlJXB3d8eHDx/g5OQENzc3jurq6sLLywsFBQUwNjbmcIUquRnnzJkDmUwGfX19DsiVpaUlKioqsG3bNhARTE1NOVyLFhYWyM7Oxv9h773DosqWtfFqmoxIEFAQAcGMmCMgRhwDiI45i2EUs2POKGbHMIYx62DOkRkzBgxjJCdRMpJzbpp+vz/61+v2Zu+N55tz7znn913reeqRmerevcNatapq1X7fU6dOkZGREeMvVQd9ys3NpTVr1pC9vT3jcVTnQtXX16e+fftS/fr1qV27dtS+fXtq374944QkIlq6dCmlpqZSnz59qHfv3uTg4MB5Vi9evKAjR47QyJEjqX///rx1QKFQ0MyZM2nEiBHk7u4uOB5PnjxJBgYGPN5klSQmJtLZs2dp6dKlooCPvr6+NHPmTNG44+zZs2RtbU29evUStBMRbd++nZYuXSo6Z169ekV2dnaiHO1Eyvvh6uoqao+JiSFbW1tRkD0AFBoaSu3atRM9xsuXL6lz586iQHxv374lTU1N6tChg6A9Li6OLl68SLNnzxYEwvr69St5e3vTxIkTadiwYTwg04yMDOrcuTP16tWLPD096YcffuCs3Z8/fyZHR0eys7MjFxcXcnV1JRcXF2rWrBlJJBK6f/8+DRgwgDQ1NalZs2bUunVrat26NTk6OlLr1q3pxIkTtGPHDiJSgptZW1uzsd2gQQO6cOEChxGASAnYpAJVNDExITs7O/L19eXx5v4r5B9F2f2ekApITEwMFRQUkI6ODmlrazP4aB0dHdLS0qLs7GzS1NQkAKRQKEihUFB1dTXnb1Vw4ODgQOXl5VRaWkplZWXs37KyMmrevDk1a9aMR2qel5dHRUVFNH78eDI3N6f8/HwerLZUKiUfHx/S1tamiooKSk1NpeTkZEpJSaGUlBSysbGhiRMnkkQiIYVCQenp6RQfH8+0U6dO5Onpya45Pz+fJadxcXHk7OzMIUSurKyk+Ph4lqC2bt2aBg0axOwAKCcnhyWnhoaGNHz4cI6jBkAZGRmUkJBAmZmZ5OHhIbhwy2QyyszMJENDw+/0Gf+EAKCsrCxegFVdXU0PHz4kf39/atGiBa1fv57ZSkpK6Pjx47R7925KSUmhJ0+esAULAAUEBNCKFSsoKiqKtLW1KTY2lpFeV1VV0d69e8nX15fKysrI2tqavnz5whaJiooKWrduHe3atYsUCgW1b9+ePnz4wMaITCaj9evX0/bt2wkAWVpaUlJSEmeMXLt2jWbNmsUKKMHBwZyFqrS0lDZu3Ei7d+8muVxO3t7edPLkSc71V1VV0enTp8nPz4+SkpLo7t27NGDAAN79UygU9OLFCzp79iwNHjyYvLy8/uaT+C7/rwjwz1FS/CPH+C7//fK/5Z5/6zqrqqpIKpWKjlEVWrEYLUxubi5VVlaKJiBpaWlUVFRETZo0EVzbv3z5QqWlpdS4cWMeei+RMulXKBTUsGFDQfuXL19IV1eX6tevL1ggSUtLI1NTU9HkpqSkhAwMDETvUXV1NStqi8n/lrH0LVFtBtQsRFVVVVFycjLFx8dTSUkJeXl5ccZbQUEBJSYmMm3Tpg316dOH2RUKBWVnZ1N6ejpTNzc3wQIuAKqsrKSioiKqU6dOrYji/4x865kXFxeTnp6eKO1LQkICGRgYkIWFhaD9xYsXZGxsTM2aNeMl1ZWVlRQQEMCS0Pr163Pu5+fPnykuLo6D6m9sbFwrtdG/Wr4npN/lu/w/Ljk5OVRcXMyptmdnZ9Pjx4/p0aNH9Pz5czp8+DBz9lFRUeTv709nzpyh9PR06tq1KwUFBbEiy759++jgwYOsM2DSpEnk7+9PRESvX7+m5cuXc6DVFyxYwGDfX7x4QT4+PhQREcHse/bsoYULFxIR0bt372jy5MkUHR3N7MeOHaPp06ezc5swYQIFBwcz+6pVq2jz5s1EpCyYzJs3j86dO8fs3bp1o9evX7P/vnPnDs2dO5eSk5PZ/4uKimIVfblcTufPn6eNGzfSly9fiIhowIABdPfuXc59jYqKorNnz9K5c+coOTmZcx/UBQClpaVRSEgIJSYm0rRp00QDoe/yXb7Lv17kcjkVFxdTdXU11atXj0pLSyknJ4dpbm4uZWdnU2FhIXl5eVFFRQVlZWVRZmYm40z8+vUr43t2cXGh3NxczjFycnIoNTWVysvLady4cdSgQQPWzVNcXMy6euLj48nIyIjGjBlD+vr6PIqvnJwcSk5OJktLSxo8eDALsPX19cnAwID09fUpNDSUjIyMyMrKSnC3OC8vj7S0tASTOaL/osGpjbLpu/y/LQCotLSUNDU1SUdHh/Lz8znJX3p6OmVkZFDPnj2padOmlJiYSAkJCSyBTEhIoISEBOrWrRtNnDiRUlJSWJdKfHw8JSUlUXV1NVlZWdHUqVOppKSEk4Cqc5l369aNWrduTRkZGey3MzMzGWWNhoYGde/enWxsbDhdcurdcnK5nLp06ULdu3cXLCaUlpZSdHQ0OTg40ODBg6levXpkYmLCkjcDAwN6//49AaAmTZoIUhFVVlZSeXn59w2SvynfE9L/BgkPD6emTZuKcrQFBgZSz549RZ376dOnacKECbW2O3Tv3l208pKQkEB2dnai9oKCAjI0NBT9fVWrb20k0d8ikf5Wxf9blaN/t/1b5/8t+7f4Fr9VUf1H7KWlpVReXs52zlV/l5eXk42NDUmlUoqJiaHY2FiKiYlhf1taWtKNGzcoISGBHj58SI8ePeIkdOfPn6cffviBLly4QP7+/vTu3Ttmq1u3LoWEhBAA2rVrF508eZLDf2diYkIxMTGUn59Pq1atouvXr3PO29DQkL58+UISiYSWLVvG4xIzNTVlu5sbN26k7du3c3jRjI2NKS0tjXR1dengwYO0bNkyHv9efHw8NW7cmO7du0fTpk1jPGEq8ff3p0mTJlFKSgotWLCAbty4wbF7eXnRzZs3qbq6mi5dukQbNmzg8JxKpVIKCwujVq1aMb7Ys2fP0sePH9lnWrZsSe/evSMdHR2KiYmhkJAQjubm5pKJiQk9ePCA7O3tGW+sqltCpQCoTp06JJFIBFvDVZKTk0MGBga1JrZfv36ttUUqPz+/Vi6yyspK0tbWFj0H1ZrwfRfgu3zLPxYXF5OBgYHoZ1JTU0kmk1GjRo0E15nY2FiKioqiunXr8lRfX58iIiLo+vXrbA6pzyfVTkpoaCiZm5tTSUkJFRcXMy0pKaGKigrGXZqfn08ymYx3DsbGxpwguaZoaWmRk5MTxy/UlHbt2lF5eTnFxsaKfqZfv3707NmzWvlOrayseH5OTOrUqcNaVhs2bEhWVlZkaGhIO3bsIENDQ+rYsSPjIW3dujXjuvTw8CANDQ3q1asX9e7dm9q2bctZ43bv3k2pqak0YsQIQS7kR48eUWhoKE2ePFmQezYyMpLevXsnyrH+5csX+vjxIw0fPlxw3ISHh1NSUhINHjxY0AcFBASQnp4e9e3bV/C+HDlyhJycnMjZ2VnQfuvWLbK2thZt737y5AmZmppS27ZtBe2vXr0ifX190RbS169fk0KhoK5duwruUr148YLy8/Opbdu21KhRI941BgYG0pcvX6hBgwZMLSwsWGvu3bt36dWrV5zXJTQ1NdnfqtcUjI2NOfNBXevXr086OjqUmZnJ4+5WcdfXNic8PDzo3r17opzcrq6uNHToUFqxYoXgZ6RSKe3bt4/y8/NpzZo1gscwMzOjc+fO0cGDB+n27duCn7GwsCA/Pz9auXIl5eXlCX5GKpVS+/btSSznUPGUFhQUEAAyNTWlJk2acFq6HRwcaO7cuVReXs44SJ2dnTnc83v37qWIiAjy8vKifv368dbwd+/e0cePH2ns2LGCxaTExETKyMigbt26CZ5nYmIi6erqUoMGDQTtsbGxZGtrK5qv/DvlH01Iv4Ma1SJnzpxBy5YtORQb6jJ37ly4ubkJgiQAQLdu3eDp6SkIfgIoUcZGjRolysG5b98+jBs3jgfSoJInT55g5MiRovbs7Gx4eHjweDPVZeTIkaLnByhpVcR4TgFgx44dPAAHdfH396+Vb/D+/fscgJmaEhwcjM2bN4vyCSYnJ2PWrFk8IA2V5OfnY9iwYaJcq8XFxXB3dxflIC0uLoaLiwvWrFmD4OBgHrhAQUEBOnToAA8PD/j6+iIgIIBD4ZCTk4PmzZvDysoKbdu2Rb9+/TB27FjMnz8fmzZtwvv37wXBoyQSCVauXIlPnz4JcpL16NEDeXl5iI2NRe/evXn2HTt2AAAiIyMxevRonl0FdBAREYF58+bxkDRViM7h4eFYu3YtD/1QBfrz4cMHrFq1ikdFoqJLCQsLw7JlyzgomESERYsWAVACPq1duxYdO3bk2N3d3QEokUJ3797N6IFUampqygCg/vjjD0yfPp0H8KICWsjIyICvry8PrGLu3LnsOT1+/BjdunXj2PX09BhCXWVlJZYtW8a7j+bm5gzxMzY2lncfVOrl5YX09HT8/PPPMDQ0RPfu3TFjxgz8+uuvePz4MQMcSEtLQ7169TBhwgTcuXOHB54CKPnIxo4dK8pP+fvvv2PIkCEc6h51+fTpEwYNGoSEhARBu0KhwJgxY0T9GgBs2rQJqampovbLly+L8isDynFTG/9xfn4+BylVSNTRi4WkNv5OQAl0IQbmAQCpqamifgVQAl7UxlP6j5xDbVytgBINXcy/A0o+15p0WTXtt27dqpUHeuXKlaJgaC9evECfPn1w4MABQVqZyMhIWFhYYMCAAfD19cX9+/c5AC1fv36FmZkZpFIp7Ozs0Lt3b0ybNg2bNm3C+fPn8ezZM4agWVNVfH3qPKY1dc6cOdi5c6eoffHixXj69KkokM3QoUORn5/PA7lSqbW1Nd6+fYuYmBhRug4fHx+kp6cL8kUTKQFxTp06hYcPH/K4lFVav359HD16VBSEj0gJkLNkyRIOGrCQ1vS1KtXS0oKTkxMPCNDIyAienp7YtWsXPnz4gPj4eLYeWFlZYe7cuXiMvdxbAAAgAElEQVT69CmbK4WFhdDX14e2tjYDBlQfXxUVFTAyMoK1tTV2797N47eVyWQwNDRE+/btBakp8vPzoaGhgT59+vCQ0AHg1atXICJRH3f69GkQKZFn1QFsVHL//n0QKWnihBBI3759y9ag+/fv884vKioKREpAqF9++YVHNfflyxeGxjt8+HAcPXqUM0dTUlIYOquJiQl69uyJ+fPn48SJE3j//j2SkpI4CLkqNTExQcuWLdGvXz/BmEGlkydPFp0zRkZGuHz5siDwHJESZOfx48cIDAwURNfW1tZmDAXLly8XPMbo0aNRXl6Od+/eCYJ7Ghoa4u7du0hJScH69esFkZXbtWuH6OhonD9/XhT5uHfv3rh//z58fX05lCfq2rp1a/z6669YunSpKCiQtrY2xo4dCzc3t1rnlRCAnImJCQYOHAg/Pz9cuXKFAW7p6+tj6NChOHXqFAOhKysrg4mJCfT19eHt7Y2XL19yxlZZWRn09fXRq1cvwXGXlJSEOnXqYMOGDYKc0bdu3UKTJk04dHj/KULfUXb/vrx8+RJTpkxhcNRSqRTr1q1jKHYFBQUYM2YM44esV68ej6dzzpw5jFeoadOmPMe3f/9+NgE6derEC+7u3r3LiLbd3Nx4KGexsbGMSLdXr168pLKsrAxbt24FkTJ5qYniBiiRW01NTdG+fXsOH6NKbt68ifbt28PBwUEweH3x4gU8PT1hZmYmmLR/+vQJU6dOhba2NgeBUiVFRUUMiXf16tW8pFOhUGD79u0gUnLSCZ3juXPnoKmpCRsbG0F0xNu3b8Pc3BxSqRRz5szhHSMoKIg5Mzs7O+zZs4ehEgLKxUcdqdLe3h7Lli3DmzdvoFAokJWVxfhi1bVRo0aYN28esrOzeYkOkZKPU0XvUpNn1NraGk+ePGHnUJNPy8vLi1NkUI1Tlc6bN4/jzGrSR0ybNo13j9Ttzs7OnGcREhLCsVtYWHAcYk5ODmdR0dfX5/BeyuVy3gJaM5CoiTqtTssA8GmMFi9ezLHX5D1zdXXl2MvLyzkJqbGxMQcGH1CiEKsfQ53mCFAG7+qLkqWlJaKiopi9uLiYxyVmYmLCQQYVQp4mUiJDbty4ERcuXOAktcbGxvD29sa9e/cgk8kQFRXFqCWICB4eHhwOYZlMhsmTJ4NIGYAuWrSIh+x88OBBSKVS6OnpYceOHTyezoCAANjY2MDIyAgnT57kLYwhISFwdXWFiYkJrl69ipqSmZmJ8ePHw8TERJC/uLq6Gr6+vqhbt66gHQDu3bsHXV1d3jhQSWhoKBo3bsyhwlKXhIQE/PDDD/D19RVMxgoLCzFnzhxMmDBBsBClUCjw66+/wtnZWbRg9/TpU1hbW/PQIVUSERGBxo0bc+i01OXz589wdnbGokWLBBPjzMxM/Pjjj+jcubOg/5XJZJg+fTrq1KmD3377TbBo5+vry+aDUAJ/8uRJtsaNHDkSL1684NyvW7ducVBNnZ2d8csvv7BE/NmzZ7wijEQiQatWrTB//nwEBQVx6BRUKpVKMWXKFLx9+1YwgbK0tMTp06chl8sFEzA7OzsEBgYCAK9YRaSk5VJREQmhQmtoaGD79u1QKBQ4duyY4Jzs1asXMjMz8fHjR0G7np4eTp8+LUg/ptL27dsjNjaWcYYL6ZgxYxjqqpi6u7t/E31WiL5MSL91HA0NDcHPGBkZwczMDJ07d+bRCTVv3hy+vr7o0KEDJkyYwEEMNTExwdq1a5GVlYWhQ4di2rRpHLuzszOePn0KAFi1ahW8vb0ZEq9EIsHkyZNZfOTv789ZK7S0tPDzzz+z+Oavv/7i+EeVXeUDc3NzOQm5RCLBuHHjOOvR6NGjOdfv5OQEf39/VhxcvHgxh25JKpVi0KBBuHTpEsrLy7Fr1y7B8dCiRQssWLAAy5cvF0Ua1tDQQM+ePQWp5jQ0NDBlyhQEBQUJft/e3h4PHz5EeXk57/kQKWmGVH5EKGZp06YNm9dCRWxTU1O2uVBzPVbpsmXLUF1dzaMVVGmjRo0QFhaGnJwcwQSPSJnQlpaWihZeNDQ04OfnVysThpaWluA1/N0584+q2NwyNjZGhw4deBRYTZo0ga2tLUaPHo0tW7ZwuEY7duyIK1euwMPDA3PnzsWZM2cYDU+DBg1w9OhRVFVVYdWqVVi4cCGOHz/Ovjt27FheoeTfKfQ9If37okr0amr79u0RHh7OFvGaumjRIlRWVuLDhw88m76+PtuVKiws5FWFLC0tWYKiUCh4fFvNmzdnUNQAMGXKFI69bdu2nJ3MX3/9lWdXH6BBQUE8Z6leJc/OzuYEIlZWVhzaA3VocyJlFVhFqqwSVWBMpHT8u3fv5thrUtcMHTqUk+jUvI9WVlac3daKigoexPu0adM4AWSPHj049rp162Lbtm1sd23FihW8Z1W3bl38/PPPSExMREBAgKCTsbW1xaZNm5CWlsbhopJIJBg8eDBu3brFAl31YKRVq1YICAjgBH1Lly5lNBcjRozgFR8uXLjAEroZM2bwAmj1XdLhw4fzgtvi4mIMHz4ctra2aNGiBY86prq6Gj4+PozYvCbdgOpZqcjZ9+/fz7M/e/YMS5YsgYWFBRYsWMCzx8fHY/bs2Rg8eDD69+/P2/krLCyEj48Pli1bBnNzc8Y1phK5XI6VK1eyIos6T6FKjh49inXr1oGIBJOAhw8fwsfHB0SEPXv28OyxsbEs2Jk4cSIvkSkqKkLfvn1BpOTerHmOgJKvUDVePD09ed0FI0aM4IwnW1tb7Nq1iwVUNTk+1bVHjx4swaipvXr1woMHD1h1X13r1auH/fv3QyaToaSkhMdb1qZNG06yUpOYfeDAgZzd0kmTJnHs3t7enJ3Emr5nyZIlnKT3xYsXnPmyceNGTjKVl5fHCVa2bdvGeRYKhYJDu7Vx40besxo/fjyzL1y4kJesqXNJjxgxgjce1bmkO3fuzEvqs7Oz2TnWr1+fN2cUCgWbsxoaGrziBgBMnDiR/Yanpyev6r1//35mF0rua/I09+zZkzMmKyoqeGTsw4cP5yTQNelxiAgdOnTA77//joqKCkH6MalUih49euCPP/7A5cuXeePJ2dkZx48fR1FREZKTkznnoK2tjZkzZ7LAWKFQwN7enu1eaGtrY/ny5ZzxNHz4cM5a5OPjw7lX27Zt46ynffr04ezmPn78mLNOWFhYcAp+WVlZ0NfX5+yALl68mEMJ0aRJE3Tr1o0lCg4ODhxexhEjRsDW1pazMzVv3jy2u+3n5wcDAwOMGDGC0T7Vq1cPly5dAvBfRUEnJyfOLqqTkxOeP3+OhIQEECmT4Jrzs1OnTrh37x5bh4R4CRs1agQbGxtR3/Kv0Jpjsaa6u7sL7gyqrnvt2rW84q1KzczMcOjQIbY+1FQTExPs2bOH7Y4Kjelp06ax3U8htbKywvbt23lUSupqbGwsatfX18fw4cMF6ZxMTU2xfPlyJCYmIjY2lhdzeHl5Mc7a6upqWFlZsWRKQ0MDS5cu5XTaeXh4cObEihUrOD5448aNHGqtmlzPd+/ehYmJCTuPpk2bcpL21NRUGBoaMs5qdcpAQLleN27cmK33qnGqvh56enrCyckJv/32G+NuVff1a9asgZmZGebNm8cKuQ0bNmRr/+XLl6GpqYnevXtj9+7dLEnv3LkzwsPDGdVL/fr18eOPP3I6ybp06YLnz5+zzokGDRrwdnMbNGggSAH0n6QtW7YU5cU1MjLCwYMHa+0C+lcJfU9I/748fPgQkyZNEnTs2tramD9/vmhLRKdOnfDkyRPR6o6qWifEn6mrq4uLFy+iurqaw2mkUnNzc9bGtnfvXp7dzs6OBRv379/nOTUHBwdWAYuNjeVV8WxsbJjTKSgo4O1q1atXj+2EVlVVYciQIbx7o76jsXHjRt45qgeHQufYpk0b1uqXmprKq75LpVJs3boV1dXVkMvlgvexYcOG+OOPPwBAtAWqefPmePr0KSIiIthzNjY2houLC2bMmIG9e/ciMDAQVVVVcHR0RJ06dTBkyBAcOHAAnz594gTAq1evhpWVFdauXSvYPhcaGgpLS0scO3ZMcDcGULZ3C+1GqeSXX37B2rVrRe3FxcVwdXUV5TEFlC3itbUQvnr1CkuXLhW1KxQKDBo0iAXvQr+1Zs0aJCUl8dpRVPLs2TOcO3cOK1asEPwN1c5VzV1c9XPw9vYW5C9VyaxZs7Bu3TpR+/jx41FeXi7Y9gIA/fr1E7UBQLNmzUTbUYuKimBiYgJ/f3/B68/NzYW2tjZ69OiBa9eu8cZDdnY2CxRsbGzg7e2NM2fOsAA7Ly+PF7RJpVI4ODjghx9+wNGjR0XJ41u0aIGAgAAMHDiQZ5NIJPDx8UF+fr5g5Vl9t1SoRdLBwYEltZcuXeLZnZ2dWcHryZMn0NPT49iHDh3KkpDg4GAWtKt06tSpbNzFx8fzgvJZs2axhTc7O5vHtert7c3udXl5OaZNm8axe3p6svGsUCiwY8cOTotXu3btOLv+t2/f5vhPU1NTTpdIVFQUmjVrxvkN1Y4coJyvNf1n27ZtOUVB9aRZpcuWLWPXERwczPPhenp62L17N+RyOSorK9G9e3fOObZo0QJ9+vTB48ePAfyXf7SwsEC/fv2waNEinDx5Eu/fv0d5eTni4+OhpaUFW1tb/PTTT7h+/Tpvx9jNzQ0NGjTA8uXLBfk3Dx8+DF1dXcyfP1+wDTw3N5fxlAoVeWQyGQYOHAhbW1t23upSUVGBo0ePQkNDA5s2beIFYNXV1Syhc3Z2Fmw1LygowOLFi6Gvr48LFy7w7KqCUf369eHp6cnrOMrLy0N1dTV+//13GBsb48aNGxx7YWEh4zQ0MjLCkCFDOK92lJWVsbb9WbNmwdDQEHv27OEkxVFRUZDL5bh69SqICI6Ojrh+/TobU8HBwUhLS8OnT5/YM3d1dWWvowQHB+PNmzd4/fo1p+DTtm1bbN++HQ8fPsSdO3dw7tw53u6VoaEh+vXrhylTpmDJkiWiO0uampqwtLQUtKn7mtrsQrt7KjU2NhZNWlV+qLbv29rawsnJSdSuqakp2kKura2N1q1b8/jX69SpA3d3d8bRm5CQwM6xbt26GD9+PK5fv84SxoqKCkyfPp35lRMnTnA6nhQKBStQuLm5cTpgVFJeXg4DAwO0b98eHz584NkrKysxbtw4WFhYCHaOVVRU4PLly5BIJNiyZQtvrVIoFCgpKYFUKoWbmxuvmwhQvk5z//596OvrC3a6qNbQWbNmYdiwYbxCeGFhIeMKNTU1ZTGbSoqKilgS7efnh0GDBnF8cFlZGZuHhYWF0NXVxfbt2zlz5suXL+zahg8fDmtra9ZyDChfSVJ1xF28eBFEyp3mw4cPo7y8HCEhIQgNDUVqaiqSkpLYvDAyMsKsWbNw4cIF3L17F3fv3sWdO3d4O9uWlpbo168fZsyYgeXLl9fKkau+sSGkte3mmpubix67S5cugq3v/0qh7zyk/5zs37+f5s+fL2rX09Oj8vJyQZu2trYgeIJK7O3tKT4+XtQ+ZMgQ+uOPPzggMOq/u27dOtq7dy9lZmby7GZmZnTy5EnasWMHvXv3jvfCuqWlJd25c4cOHTpEjx8/psTERI69fv36dO/ePQoMDKRr165RZGQk4xclUoLZ3LlzhyorK+no0aMUFRVFcXFx7MV1iURChw8fJnd3d9qxYweDpE5OTibVWBs5ciQdO3aM9u/fz7j3UlNTKSUlhcrKysjc3Jxu3LhBX79+pQ8fPlBBQQFHCwsLycXFhX766Sd69uwZO7eaY9nT05OCgoKobt26VK9ePY6qoN+fPn1KcrmcHB0dqUGDBjyAgczMTIqNjaVu3bqJcly9efOGOnbsKAqznZKSwtDcxCQ1NZWsra1F7dnZ2YK8cyoBlLyNtYHZFBYW8ngt1UUul1NFRQXVqVOH8vLy6OnTp/Tjjz9yPlNcXExSqZSWLl1Kixcv5nELymQy8vf3p3v37tG1a9d4v5Gbm0vu7u70ww8/0NatW3n26Oho6tGjB82bN49DR6OS1NRU6t69O40cOZJ2794teB8WL15MUVFRdO/ePcHrLCsro4ULF9LmzZsF72lRURHVrVtXFPArPT1dlNvtW7QIMTExVFpaKgqo8fTpU/r06RP16dOHx29HpEQSDgwM5HDn2djYsPN88OABXblyhaEI1tTMzEx6+PAh6erqkra2NqO1Uv1raGjIUIpV4DEA2N89e/ak5ORkKisro4qKCiovL2f/yuVy8vHxocTERMrNzeXNW01NTVq3bh1lZWVRcnIyZWRkUGZmJqOyMjU1pe3bt1NZWRnFxcVRUlISQ2ZMSkoie3t72rNnDxEpeeNUFFSxsbEUGxtLrVu3psOHD5OWlhYlJiZSREQER52cnOjUqVMMzCM0NJRCQkLYv7a2tnT16lXS19en4uJiCg0NpeDgYAoJCaHg4GCSSCT0559/Uv369amyspKio6MZh2lYWBglJiaSv78/ubi4kFwup4SEBIqOjubo4MGDac2aNaRQKOjr16+UlJTE0aqqKtqyZQs1aNCAUlJSOHRgKm3dujUNGDCAUlNTGfUCEXH4mK2srKiyspJSU1PJwsKC6tWrxxvLAOj169fk4OAgyr0ZERFBWlpajC+vppSVlVFgYCDj0BOSO3fuUOfOnUXBOKKioig5OVmQekklW7dupblz54qixx47doxatmwpyncYHh5Ox48fp507d4r6cT8/Pxo6dCg5OTkJ2hUKBeMAFQNxunv3LrVq1YpsbW0F7YWFhXTr1i1GySYkO3bsoAkTJoj6kO3bt5O1tTWNGTNGEHBv27ZtFBUVRQsWLBD0M3v27KEDBw7QuHHjaOzYsdSqVSuefcmSJdS5c2fq378/9e/fn7p27crGz5YtW2j16tWkpaVFbdq0oU6dOlHnzp2pU6dO1KpVK1qyZAnt27ePiJQAOXZ2dtS0aVNq1qwZNWnShM6ePcsB2CNSguw1bNiQzMzMKDg4mEpKSnjnrUIbzs7O5tmkUilDQM3NzeV8R33dl8vl9Pz5c9LT0yM7Ozsez2mdOnVozZo1ZGFhQU5OTtSiRQtq2bIltWjRgho3bkyampo0d+5cysnJYXySNTl6AwMD6fz58zR8+HDq27cvb7xVV1fT/PnzaezYseTi4iI4Dvz9/cnCwoIGDBggaE9OTqZLly7RokWLROfdxo0b6aeffhKddxcvXiRDQ0MaPHiwoL2yspKmT59Ox48fF+U6ff36NWlpaVGnTuJ4Nc+fPydXV1fROVNZWUlJSUnUrFkz0WNERkZSy5YtRY+Rnp5ORUVFjCNaSI4cOUITJ04UpYbZsmUL2dvb04gRIwTv6c6dO+nhw4fk7e1NQ4cO5YEWXbx4kSZMmEAuLi40aNAgGjx4MDk6OrLnd+3aNRoxYgQREdnY2FDXrl2pS5cu1KVLF+rYsSMdO3aMFi1axDmmubk5NW3alBwcHOjNmzccUMb/G9HQ0KB58+bRxo0bRbmc/yflO8ruPyEpKSm0bds2qqqq4sCyq/5OS0tjiFwdO3YkLS0thl5WUFBAWVlZVFxcTO3ataNu3bpRXl4eZWdnc+DktbW1adGiRWRgYEApKSmcpCwtLY0GDBhAy5Yto69fv3L4Q798+UJpaWm0fft2GjduHC8oi42NpczMTLpw4QL179+fEhISGDG8SjMzM+ny5cvUvXt3KikpoaioKBa0RUZGUlpaGh07doy6d+9OgJLaQj2wi4+Ppw0bNlDv3r2JSInU+/nzZ4buFh0dTePHj+fwlFZWVlJCQgLFxcXR58+fydLSksaMGcO57wCosLCQUlNTKSsrq1YE4+/y90WhUNDt27cpLi6Oli5dyrFVV1fT0aNHae3atXT9+nVyc3Pj2MPCwmjs2LFUv359CgwM5B135cqVtGPHDvrtt9/Ix8eHY8/OziZ3d3cKDQ2lmzdv8ng9ExMTydXVldLS0ujq1as0fPhwjj0/P5969OhBkZGRdOTIEfrpp59417Z161ZatWoV/fzzz7Rr1y6eXcVN+tdff1FcXJzoPbp//z4lJSUJ/sZ3+c8UAFRdXS0aoMlkMqqurhZFMC4vLyeZTCZatJHJZFRUVCSILKr6/cLCwlqpAVQJ/re4Sr/L/50AtaOtfwst/VvHKC4upsLCQtGiYVFRESUkJJCpqako8bxCoaCcnBzS09MTTaz/EfnWtVZWVoomEERKP2trayt6jCdPnlDbtm0F6S+qq6vpzJkz5OjoSG3atOH9Tn5+Pp08eZIhlNrb23M+Ex0dTQEBAQwVuGHDhmRpacm4LJ88eUKxsbG8AnK9evVIT0+Pbt++TQDI2NiYTExM2L+q77948YKMjIzYd2oijmZkZFCdOnV43JkqqaqqIk1Nzf8VCOPfGkcKhYIVuNSlqqqKoqOjqaCggBcflJeXU1hYGH38+JFCQkJo5syZ1KFDB2bPy8tjRbzQ0FAqLy+nffv2MX5OuVxOiYmJLJaNiYkhMzMz8vX15ST2MpmMvn79SmlpaZSWlkY6Ojo0ZMiQ/9HnVlJSIjpuiIjevn1LTZs2Fd0UOHLkCFlaWlKXLl14RYKCggJasWIFWVtbM2TfJk2asLUoICCA/P39ydzcnKdGRkb022+/UUlJCenr65OOjg7p6uqyf9X/dnBwoP79+//Lx/f3hPQ/XKqqqqioqIjq1avHsykUCsrKyiJNTU3B4EdFPNywYUNBiOeqqipKSUmhxo0bCw481cIoRtJLpHQstVFPfMuZfZd/jwCg8PBwunz5MjVr1owmTZrEbJWVlXT27FnauXMnpaWlUVRUFCd4evbsGc2fP5/CwsKoV69e9OTJE85x9+3bR8uWLSOZTEZnzpyhCRMmMHt5eTlNnDiR7YqqKItUkpmZSf369WM8penp6RynnJ6eTj169GD8oLGxsZyKaXl5Obm7u9PLly+JSLmT2LNnT861HzlyhGbNmkVERMePH6dp06Zx7DKZjMaPH09Xr16liRMn0unTp3n3r7q6mvz8/MjPz48+ffpEDg4OgvdZJpPR6dOnaejQoaIJynf5Lt/l3yMAODvxAwYMIC0tLaqqqqKkpCT6/PkzR0eOHEkjRoxg/x0XF8dRQ0ND+u2336iqqorxMKprfn4+DRw4kKZMmUI5OTmMy7HmvwMGDKAxY8ZQRUUFlZaWUklJCdP8/HxKTU2l5s2b05QpU0hXV5fReag0Ly+PUT8I+R2xJOK7fBeVyGQyKisrY4UzAJSamsoo5WJiYqhOnTq0YcMGqqyspLCwMNYlEhISQpGRkWRjY0N37tyhvLw8+vDhA338+JE+fPhAUVFRVF1dTRKJhH755ReysbHhdKKkpKSw83BwcKD58+dTRkYGSz4/f/7M6S5s3749eXp6UlZWFqWmprIENCsri32mSZMmNG7cOCIiNqdKS0vZ39nZ2VRZWUkzZsygdu3asSRNXVNSUqhhw4bUoEEDwcLV93j3n5PvCel/k9TGw1ZeXk66urqiAzUjI0O0XYKIKC0tjRo2bChqLy0trbXN85+t+n6X/3/J169f6f379/ThwwcKCQmhhQsXUu/evQkARURE0JUrV+jy5csUGxtL/fv3pz///JOkUikVFhbSkSNHaO/evZSenk5ESq45VXtIcnIyLV26lC5fvsx+68mTJ9SrVy8iUiaTU6ZMYS2wdevWpfT0dNb6kpmZSV5eXvTmzRsiImrRogVFR0ezY6Wnp1OfPn0oJiaGiIhsbW05reJ5eXnUs2dPlqzq6OhQaWkpG9tyuZyGDx/O4SLLyMjgtBleunSJxo4dy9q2X79+zeHzqqiooFGjRtGdO3eIiER3cCdMmEAPHjygLl26sOtRF5lMRqdOnaItW7bQoEGD6NChQ6LPKz8/n8LDw2ttV/ou3+W7KEXVGl5dXc00OzubioqKKDc3V1CLi4vJxcWFioqKKDk5mWlKSgpVVlaSkZER9e3bl0pLS+nz58+UmJjIeRVGIpFQp06dKC0tTZT/s0OHDlRUVESfP38WPfd58+bRH3/8IfoqjpaWFi1cuJAOHTok2I6qOpcOHTrQhw8far1PEomENDQ0yMLCgurXr89RExMTOnnyJOnr61OXLl2oQ4cO1Lp1a2rdujXbudm6dSsVFBRQnz59yNXVlRdjPHr0iLKysmjIkCGCO0JRUVFUUlJCXbp0ETy/pKQkUigU1LhxY0F7cnIyaWtri8ZGMTExZG5uLlisJ1K2xHbq1Em09TAkJIRatGghyseYkpJCVlZWorFTQUEBGRkZicZN39qBlsvlol0aRN+O22QyGWlpaYn+fnZ2NpWUlJBMJqPKykqmqv+Oj48nKysrysrKoq9fv3I0LS2NjIyMyMvLizIyMlgCWlpayo7fpk0bsrOzY91wNUXVen3v3j1SKBQ8u1QqpT179tCZM2d4rdkqadeuHR0+fJhmzJhB4eHhgp/x9vamKVOm0PDhwyknJ0fwMzNnzqRGjRqJcpkSKedvcXFxrR1RKtHX1ydbW1uysbHhqLm5Oa1evZrs7OyoW7durM1WvdPhxo0blJqaSl5eXmRjY8M7dmFhIUVHR1PXrl1Fn21BQUGtHTbfGjv/qfH+dx7S/yapDT45NDQU48ePF+X53L17NxYsWCCKcrV+/XqsXr1aFKjmypUrWL9+vag9MjISa9asEbUrFAr8/PPPonZACWohxvEJKGHWa9JCqMvt27d5L6ury7NnzwRfiFdJSEhIrTx6nz9/5qD71pSvX7/WykeYm5uLu3fvitqLiopw4cIFUbChoqIiHD16lPMyvboUFhZi165dePr0qSBnYV5eHtatW4fdu3fj999/x+3bt/HixQtERkYiLy8PGRkZmD17NkaNGoX+/fujc+fOaNKkCTp37ozg4GAkJibCy8uLAxQhlUo5PKI1AV5sbW3ZPX/58iXMzMw49nbt2s5hQ6wAACAASURBVLHrffz4MQ8Yxc3NjZ3/y5cveSARM2fOZPbIyEgOhD/Rf3GMAkrOtaZNm3Lso0aN4tzfmtx87du3Z3aFQsEDoDEyMuKM6bt37/IAyNSpe0pLS3lcZsHBwZzn9OrVKw5YRk0U3srKShw5coQhVRobG/MohD59+oQjR45gypQpaNGiBfT09DjI01VVVbh//z6eP3+O9+/fIzo6GsnJyRxU5dDQULx580bUZygUCoZgKiZ37typFcQgOTlZFHRJJd9C57t+/XqtAFqvX7+u9RwTExMFaZxUIpPJBDkE1UWMO1MlKpAYMamJnFtTioqKavWNMpmsVo5nAJxx+HfO4VvXkJCQUOtzjIiIqPU5vXv3rtb7HBQUhAsXLoj6v8ePH2PRokU4fvw4Xr16xQP7efToEVxdXeHp6YnJkydj0aJF2LhxIw4cOIBLly7hzz//hIGBgSCSefPmzXH27FlRkBwXFxeEh4eL8ge2atUKnz59wqpVqwTtenp6uHXrFtLT03k8yCodOnQoysrKkJSUxPOj9P8B3Zw5cwbV1dXw9/cXPIalpSVevXqFhIQEUSqKhg0b4tGjR3j8+LEoJYienh42btzI84c1VQxN18rKCv3794e3tzcDSNHS0kKPHj2wfv16PHv2DBUVFUhPT4e2tjb09PQwatQo3Lhxg8OFq0LB7tatG86fP8+LD3Jzc6Grq4uffvpJcG1X8XCqo92ry+vXr2FmZobff/9dcGzv27cPDRs2xO3btwXHpL+/P5o2bcpBUlaXW7duoUOHDoJgQQDw559/ws3NTRDJHVDyXvft2xdXr14VjI1u374NFxcXbNmyBWFhYbxruHnzJpo2bYrhw4djw4YNuHHjBj5//sx8zY0bN6Crq4sGDRqgZcuWcHFxgYeHByZNmoQFCxZgw4YNory69vb2OHbsmCgf9siRIxEdHY3OnTsL2kePHi0KbEekRH3OzMwUXFOJlKBQKiqw+Ph4HjgdEaFr167Iy8tDWVkZo/WrqStXrkR1dTWeP38uSJkklUpx8OBBZGdn47fffkO9evV4n5FIJFi+fDk+fvwoSrdGpEQQPn369Df5fWvOS4lEAkdHR3h7e+PQoUN48OABQ5Ju3749fH19Odz1KuT1du3a4ciRI4LAiT/++COWLFkiujbOmTMHN2/eFPX5M2fO5LBx/KcIfUfZ/fsSHx+P48ePo6CgAB07dkT9+vU56H5VVVU4cOAAwsLCQKRE1q2JHnj27FmsX7+eLWrqkNyAcqFWIenOmDGDF/xFRkYyom2hpDI3NxdnzpwBkRJ5saa9uroaL1++BJES2VZoAIeFhcHOzg7Tpk0TDLw+ffqE/v37Y9iwYTxaBEC5sPz000/o0aOHaDK2ceNGtGrVShDZsKqqCkeOHIGlpaUgUhygdP4GBgaCPKaAMqGVSqVYvXq14Dl+/vwZhoaGogiOycnJsLGxgb29PQ4ePMgLMLOzs+Ho6AipVIr+/fvjxIkTnASipKSEJVQSiQQtW7bExIkTsW/fPqSkpKC6upoDN65ypnPnzmVB3siRIzn2IUOGcAJVdR5SqVTKqAJUoo5mrKOjg/fv33Ps6vxUEokEf/31F8d+9+5dzu+r+P1U8urVK07AqEJ6Vl3/u3fvOLQM6sTM2dnZCA4O5lAq7Nq1i9kzMzPx9u1bODs7M/ukSZOYvbi4GE+fPuVQZHTt2pVzfs+fP+dwsVpbW/Oe8cWLF9kiXqdOHV4B4tmzZywolUgkHNoI1XmoU7II0cZER0czpDxtbW3Gg6gu6nQkRMriwMuXL5n99evXkEgkMDU1xahRo3D8+HGOb8nJyUGvXr1gbGyMNWvW8BYuhUKBzZs3Q0NDA3PnzhXkH37z5g0kEgmGDh0qmPB8+vQJTk5OcHNzE0z60tPTMWbMGHTs2FGQH7OsrAy+vr5wdHQUnHOAMuhq3LixaLEpPT0dFhYWvLGskvz8fDg7O/PGqkqKi4vh7e3Nmysqkclk2LZtG3bu3CloB5R8rNOnTxdNSpOTk9GnTx/RglxpaSlcXV1FEZlLSkowZMgQHl2WSsrLyzFlyhRs2bJF8BwUCgUWL14MDw8P0eR89+7dsLa2xuHDhwX94+XLl0GkpEo5f/48L0EICgqCRCKBRCJBx44dsXLlSjx58oQdKyIigkdhZmVlhSFDhiAsLAxJSUmCCdIPP/yAiIgI5OXl8VBNJRIJfv75Z5SVlUEulzOqJXVdtGgRSwZqUqCpjq9CA169ejUP2dXc3Jz5wVOnTgkiWM6ePRtyuRzv3r0T5JU0MTHBs2fPUFxcLMilqvJVaWlpjFNcSL28vLB58+ZaUTY7deqEJk2a1IpQq62tDXNzc2hqatYaWOvp6YlyQEqlUlhbW/OoJIyMjODh4QFPT09s2bKFw7dsZWUFPz8/JCQkYN68eTh+/DiaNGkCImXCO3v2bLb+b926FWfOnGHJfePGjXHt2jUWn5w/fx6HDx9mx+7ZsyeH6zkoKIjDQDB69GgOWnFSUhIWLVrE7FOnTuWs1zKZjEOdNWnSJN6Gw6FDh5jd3d2dt15euXKFFUAtLS2xfv16Tnzz8OFDDuKpjY0NZs+ejT///BNlZWX466+/GJ+kuhoYGMDd3R1Xr14V5O61tLTEqVOnkJycLEgtM23aNBQVFaG0tJRHYUJE8PPzg0KhgEKh4CEFExHmzp3L/Iy3tzfP3qFDB1boFmIv0NLSYujSDx48EEya3dzcUFRUhLS0NEE0ZIlEgl9//RUKhYLDJ1tz3j1+/Bhr1qwRHesNGjSAn5+fYEKsPl+sra1rRb5VXZepqSkPGV5Iha65Tp066Nq1K37++WcOh66hoSGmTZuGCRMm4MSJE3j//j1DsDcwMMCKFSuQk5ODLVu24Nq1a8jJycGGDRtARBg0aBBbWy9evIibN2+irKwMQ4cOhYGBAY4cOVJrofJfLfQ9If37snbtWhApaVhUC5GGhgY2bNgAuVyOGzdusAGtGlz169dngeWXL194Fd/OnTszx1leXs6r+g4bNowTDNSkLaiZtC5fvpxjr5l01qReWLBgAcceExPDWYRrJqWlpaWcyezl5cULaFQcVERK0uWawa96AG9ra8vhsap5jgYGBjzo8M+fP3OuYcmSJZxEoqqqilO17tChAy/AVXe8Qhx3a9as4fyGubk5/Pz82CKmgl9XV01NTcyYMQM5OTnIyMjgOaQJEybg+fPn7H6rByuDBw/mLLCAMknR1taGVCrFL7/8wnMku3btgrm5OaRSKYdWRyXPnj1ju5BCfIeJiYlwdXVF3bp14ePjw7MXFhbC09MTXbp0QY8ePXi/L5PJsHDhQowePRqOjo6CxY/Dhw9j2bJlMDY25lTTAWXgHBAQgFWrVqF9+/acBEwlb9++xZw5c7Bo0SLs2LGDZ//y5Qtmz56N3377jZOwqiQ3Nxfr1q3DwYMHMXjwYJ69qqoKhw4dwsaNG9G/f3+eHVDSEM2aNQu9evUStH/58gVDhgxB8+bNBSvjMpkM7u7u0NTUFORBBYBx48aBSBng7d+/n5cY1+TF1dXVxbBhw1hidv78eY5dT08Pc+fOZYlhTR49CwsLzm5oZWUlJ7g2MzPDtWvXOOegXhwwNTXlXYt6gcTExAQBAQEcuzpPs7GxMe7du8exBwcHM7uRkRGngAEox6OK+sbAwID3fYVCwQIuHR0d3Lp1i3eff/rpJ0gkEmhoaOD06dM8++HDh5mP3rZtG8/+9u1b5h+nTp3KSwjz8vJYVd7V1ZW3E6pQKFiBw8rKinEI1jxHlT85cuQIz37s2DF2n3744Qde8SAkJIQT9Pz666+cNaKqqorD/WhnZ4eTJ09yxpz6s1Y9z/nz5zMftXDhQp7/69ChA/bt2weZTIZz585xbPXr14efnx8rtsXFxXHsLVu25BRqavpwe3t7Dtc0oFwLVYmYoaEhzweuWLGCk6jNmzePc41Xr17l2Js0acIplMTFxUFDQ4MTcG7dupXNmYqKCsZJqDpXe3t7xMTEsGP06dMHurq6HDq4qVOnMl+oWgvbt2/PxoWOjg4OHDgAhULB7qO+vj569uzJjlGvXj34+/sjMjKS/b+6detyYg9jY2Ns2bJFdNdMfa7VZv9nVYgmT31d9PHxEU0gevXqheDgYEFKFi0tLaxevRplZWUcbnP1MXvq1CkoFAoOd6+6Dzx//jwUCgVevXrFsxsaGuKXX35BZWUlysrKBHfrPTw8WNeJEK2WVCrFsGHD8PDhQ0bpUlM1NTUxZMgQ+Pn58WwODg7Yu3cvCgoKOPOaSOnj161bx3bUysvLOcULMzMzHs2Qi4sLu446derwfPiCBQs4z0KVrKrkzJkzHHvXrl058V14eDg0NDRY4UFbW5uzY11cXAwzMzM4OTmhQ4cOIFIm96qNGYVCAWdnZ5iZmbEkS0tLi3V+Acp1RiqVYsSIERgzZgzzH6qODlWh3d7eHqtWrWLXO3jwYGRlZTEeew0NDXTt2pWzAzpgwABERkZyYuCaMbmVldW/nYdUPVmWSCScJF5bWxtr1qxhHWr6+vqcmH3AgAGCG0H/DqHvCenfl927d3N2dNS1X79+OH78OK9NUTVATpw4gdevX3OI21VqZ2eHqKgoJCcnCzq1nj17oqCgADKZDB4eHjz7uHHjWCC8cuVKnn327NkscFJVvtV13rx5zOmEhobyKkPqSWlubi4aN27MsXt6erIFtrq6mteyoV5BA/jJnoWFBadVMiAggGPX0NDAwYMHmT0xMZHH69S7d28WmMlkMnTr1o1j19HRwZ49e9h1CLVrWVpawt/fn7WEqDv+Nm3aYMSIEdiyZQuKi4tRUlICGxsbGBsbY9iwYTh48CBiYmI4bRg+Pj5o2bIl9uzZw6nGquTJkydwcnLiBd4qUSgU6Nq1q2CiprL7+vqyVhghSUlJwYwZM0TtqvMU2jFTyR9//CG6WwMoF8Lz58+L2gHU+n0AuHfvnmibY1FREe7fvy+6q/by5UskJCSItqS8f/8eVVVVojtSMpkMCoWCcfGKSW0t4nK5HEFBQaL2jIwM0d18QLmLOnnyZE5VX13i4uJgbGyM0aNH48qVK7zdt8TERE4w0qhRI/Tt2xfz5s1DQkICcnJyBHekXF1dERoaioqKCg43pUonTJjAduUnTJjAs8+ZM4cVzDZv3syzr1q1iiUB169f581rdQ7Ojx8/coJnqVSKw4cPs2tMS0vjLKyampqcpLK4uJgFOarvnzlzhtllMhmn60AikeDYsWPMrlAosG7dOs45bt68mXOfr1y5wklipkyZwkn2QkNDOcTyNQO2nJwcTgBkYmLCaRGUy+WcXX8i5a6f+m/8/vvvPL/19OlTZld1f6h/pnPnzggJCWG/oUo4tbW1YW9vDzc3N6xfv57NQVVFvkWLFpg8eTIOHjyI9+/fs+JjXFwctLS00LVrV+zcuZM3dyoqKtCzZ084OTnh1KlTgsWoffv2oV69ejh48KDgqxHp6enQ0NDA7NmzBdvYcnJy4OXlBUdHR04SqJL8/HwcO3aMtfHVFLlczgo1Xbt2FWyHCw0NxcqVK3ljTSURERGorKxEhw4d4OzszDtGbGwscnNzERERAU1NTZZoqiQ5OZkl+WPHjkXLli05nNB5eXl49OgRKioq8OjRIxARxo8fz35HLpfj3LlziI2NRWlpKXR1daGjo4OlS5eyNef06dO4c+cOwsLC4ODgwIJUHx8fREdH48KFCzhw4ABOnjzJi1+6d++OGTNmYP78+Vi4cCFnbKurmZkZ7O3tBZO2f0SlUqngbrNKW7VqJbh7SKRMPLy9vUV3d/v164djx46JnvuAAQPw6NEjODo6CtpbtGiBW7duYcSIEaLnN3z4cKxevZr3/21tbTFs2DD4+fnhzp07bF4aGxtj3LhxuHjxItuxz8vLw6BBg0BE6N+/PwICAjgFL7lcjoMHDzK/LNT9kJaWBi0tLQwePFhwLcnMzMSYMWNgb2+P8PBwnj0vLw/nzp2DhoYGjh49yrPL5XLEx8dDU1NTtAPu06dPuHXrFnR0dHgcoqo5UV1dDW9vbw7Ps0q+fPmCkpISVFRUoE6dOnj48CHvGlXdQStWrMDgwYM5hb+CggK8efMGCoUCX79+hba2Nvbt28fmXXV1NW7evMn88sCBA2FlZYXLly+zz1y6dAl//fUXiouLGQ+ppaUl9u3bh/Lycly+fBmnT5/GvXv38Pz5czb2NDQ04OHhgdWrV8PPzw9+fn7w9fUVzBtMTU3RvHlzODk5/e2iUG2dEQYGBrwuFZUaGxvj7Nmz//bdUvqekP5zUlZWhnbt2gk+ZEtLS6xdu1Z0kEyePFnU6RkbG2Pt2rWibQLt2rXDsWPHRAeul5cX7ty5I+q0p0+fjqioKMGEmUgZWBYWFsLd3V3QPnXqVMjlcqxcuVKwRcHDwwMVFRW4ceMGmjZtyrsHqncM4uLi0L9/f17VycjICEFBQSgvL8eCBQvQo0cPWFtbc46zePFiVFdX48yZM5g8eTIGDhyITp06wcbGBrq6urC2tsabN28QERGB1atXY9myZVi4cCFmz56NGTNmYPLkyTh+/DgqKipw8OBBnDhxAleuXMGDBw/w119/ISoqCqmpqaiqqsKzZ8/w6NEjJCcnC7bFZWRk4N27d7W+TxceHl7rhE9PT6/1+8C33yWr7T1dQBn41QwGa4pQy566VFdXf9NxKRSKWt+LO378uKjty5cvtSbNmzZt4rTz1pQRI0YIEnCrZOLEiQgLCxO137x5E7GxsaJ2ALzW+v9uqe2dREAZSNT2zt/79+9x/fp1hIeHCyb2gYGBWLhwIVatWoVNmzZhz549OHLkCM6cOYPbt28jKCgII0eOxLBhw+Dp6YmBAwfC3d0dvXv3xtixYxEUFIRRo0Zh4MCB6NGjB9q1a4cmTZqgQYMGcHFxwdu3b+Hj44OhQ4fCzc0Njo6OsLS0hLa2Nnr37o2UlBRs2rQJEydOhLu7O1q3bs12lcaMGYOSkhL4+/tj7ty58PT0hJOTEwtQf/75Z8jlcgQGBmLNmjUYNWoU2rVrx9rBt23bBoVCgaioKOzatQve3t7o3Lkzs6uSkYyMDJw8eRLz58+Hm5sbO/6BAwcAKH37zZs3sXbtWgwaNIi9b7Vx40YAyjH+4sUL7N27FxMnTkTLli0hkUgwefJkNo9jY2Nx5swZLF68GH379oWpqSnat2/PdgazsrJw9+5d7Nq1C9OnT4ezszOsra3Z++xlZWV49eoVLl68iO3bt2POnDnw9PTE6tWrWdExJCQEgYGBuHHjBn7//Xf8+uuv2LJlC2snT0xMxIcPHxAaGoqoqCjExcUhISGBBahFRUX4+PEjsrKyROf1+/fvWaAsJJ8/f671XV3V86rNbzx9+rTWQlhKSso3C1n79u2r1QdeunRJtOAHKHfdhwwZUuv89vX1rfUYALBu3bpa52dYWBinaCAkR48erfVarl69yusKUJfAwEBMnTpV9LmEhITA2toa27dvFyyQhoaGgojQsWNH7Nixg1fACwoKYmtx69atMW/ePFy/fp0dq+aueN26deHq6gofHx8cOnSIdYHUVFU7cG0J6T+r32pX1tbW5sQaqnZMW1tbtG7dGu3atYOxsTGaN2+Ovn37YvLkyVi9ejUOHTrE3s0fN24cxowZgx07duDhw4c8jIy7d+9i0aJFePLkiWgnzdKlS2stfJ4/f57zakxN+fr1Kw4fPlzrvNu5c2et+B0BAQG4fv26qB0APDw8ah2rT548ER2rqrkWEBAgeB+ys7ORkZGBiooK0VczsrOzUVFRUSuuAqD0hapCnJhs3ry51thl6dKl2Lt3r2jB/MSJE7C1tYWfnx/vFT1AGQdKJBLo6+vD09MThw4d4syt7OxsTjeIhoYGHB0dMXHiROzZswe3b98WbGP+R1Xs3XEiwo8//lgrZsP/tPyjCel3lF0BkclkNGbMGLpx40atn9PX16eysjJBm7m5OVlaWlJSUhIVFhZybFKplIYMGUKampoUExNDnz59osrKSma3tramJUuWUGZmJoWFhVF4eDgjqyci6tu3L/n5+VF0dDQFBwczOG4VUtrkyZNp7969FBYWxlBZ379/z0h1Z8+eTQcOHGCore/fv6d3797R+/fvKTc3l6ZOnUrHjh0jhUJB0dHR7PsqdNc+ffrQtWvXSFdXl4qLiyk8PJxCQkIYNHh1dTUFBAQwYu+8vDyKjo6myMhIioqKooSEBFq/fj2Hn6qiooKSkpIoPj6eEhISqE2bNoIk5wCotLSUioqKRInDv0vtoqIVEkI5lMvldO/ePfLw8ODZANDy5ctp5syZgnQoT58+pblz5zK03Jrf9fDwIH19fbpy5QrPXlBQQI0bNyZvb2/avXs3z56UlET29va0ZcsWWr58ueD3LS0taf/+/TR9+nTB6x46dCgNGzaMJk+eLGgvLCykw4cPCx5fJQqFggD8r+XHBYRR/ABQWVkZyeVyQR5PmUxGWVlZpKOjQ+bm5jx7QUEBJSUlkaWlJY+OCgClp6fTp0+fyNHRkfd9hUJBiYmJFBERQS4uLjx0TgCUkJBAISEh5ObmxqPLAEBfv36lDx8+UKdOnQT9SklJCYWEhJCVlRXZ29sLXn9aWhqVlZWJErwDoLy8PFH00O/y90VsXKpELpeTRCLhzVsA9PnzZ7KwsCA9PT0O1yGREkH89evXFBcXR3PmzGHI4irJyspilBdlZWW0du1aHrprYWEh41WsrKwkb2/vb6Ks1jwPdfkW0mZmZiaZmpqSlpaWoP3du3dkbGxMTZs2FbSfOnWKDAwMqFevXry5KJPJaMmSJWRpaUlOTk7Upk0batSoEbv3sbGxtHr1arK2tqZGjRpx1NLSki5dukS3b99mHKLqWrduXbp27RqVlJSQoaEhGRsbk56eHuNQrKyspDdv3pC2tjYZGhpSixYtGB2OVColhUJBkZGRpKmpSc2bN6dmzZqRpqYmaWlpkZaWFmlqalJGRgbp6OhQs2bNyNLSkoeW+52HVPn/q6qqSFtbmzcWi4qKKDAwkNLT02nmzJkciiG5XE5//fUX3b17lwIDA+mXX34hFxcX9t3Kykp69eoVPXjwgB4+fEjGxsb0559/co6fnJxMQUFB9Pz5cwoKCqJBgwbRzp07OedZUlLCiTk7depE06dPF70WFe2LGD+wSmpj1CAiio+PJzs7O9HPqFgNevbsKYjwvGfPHoqIiKCOHTtShw4dqE2bNsyfAKDx48fT69evefOmUaNGZGxsTDNnzqSYmBiS/J/27jwuiivbA/jvgg0iIIKKGxqjEcUYVIjGBI0Ljuv7qGhMMG5RR3RenJhkRI27cY8Sl0RnNIlL3MYYExM1alyiCGIEZFUQI4IiIIuAiGzdfd4fTdd0UdXNvElCk/F8P5/6CNxeqtuqW/dU3TpHCDRo0ACOjo7SUlZWZjELOGCISXbs2IFRo0ZZfNzvgcu+/AbKyspQVFSEwsJCFBYWoqCgQPrZuPj4+KBnz56K9NqZmZlwcHDAmjVrIIRAamqqbLlz5w6mTJmCcePGQafTIS0tDUlJSUhOTpaKDoeEhEi1HAsLC5GQkICEhATEx8fDxcUFH374odSh6nQ6/PLLL7h27RpiYmLg5eWFKVOmyD5PUVERYmJiEBUVBR8fHwwYMEDWTkRIS0tDVFQUOnTogG7duim+E61Wixs3bqBBgwZ47rnnVL83rVaLR48eqRbWZr+/zMxMpKamqgb0V65cwZw5c3DgwAFFavL8/HwEBgZi5MiRmDVrluK5q1atwpo1a/Do0SNFp/zgwQN069YNbdu2RUREhOK533zzDcaMGYPhw4fj+PHjivalS5fiww8/xNixY2XlZ4yCg4OxYcMGTJgwAXv37lW0b9u2DW+//TamT5+OHTt2KNofPHiAVq1aYfr06WZLtWzevBnnz5/Hd999p9oOGAZrw4cPt1jDlzFWOyorKxWBl16vx82bNxEZGYn4+HjMmjVLOo4+efIEUVFRiIiIwOXLl3H58mUEBgZiy5Yt0Gq1iI+PR0REhLTcuXMHLi4uOH/+PFq2bCmruRgdHY2MjAwAgJeXF/bs2YP8/HwkJydLdRVv3rwpldry8vLCJ598Ar1eL9UlNa1RmpmZCa1Wi61bt6JXr16orKxERUWF6r+enp4Wy0MwpqakpAQPHjyQnVQjIiQnJyM0NBShoaEoKirC3r174erqCp1Oh2vXruH06dM4ffo0IiIi0KxZM1y5cgWtW7dGdnY2Tp06hR9++AFnzpxBYWEhAODAgQMIDAxEcnIyfvzxR/z444+4cOGCdAHn+eefx6VLl5CVlYVLly5Ji+mFl6lTp2L58uWyOqaxsbH45ZdfYIxbgoKC8O677yIjI0NR9sn4c+fOnXHw4EG4ubmhrKxMdSkvL4evry9atGhRi/8b/2K8Qmgu2C0pKcGTJ0/g6OgIBwcHRfD98OFDVFRUQKvVqi46nU762cfHBw4ODrXxsSS1GpAKIYYA2AzAFsDnRLTW0uP/KAHp762melY1nfVlT5/Hjx8jLCwMjo6O6NOnj/R3IkJ4eDg+/fRTnDt3DjExMfDw8JDas7OzMX/+fOzZswdBQUHYvn277HVjY2MREBCAtLQ03L9/X3GVaMuWLZg9e7ZqfU6dTochQ4bg7NmzGDx4sFSv1HSdvby8kJGRAX9/f5w9e1bWnp+fj2effRbFxcV4+eWXcfnyZcXzPTw8UFRUhG7duiEmJkbxvfj4+CAmJgZdu3ZFbGysoj0kJARz5swx267X6+Hp6QmdToc7d+4o2gHDCR1PT09cvnxZ9Qqx0RdffIGpU6fyvsvYf6CkpATZ2dkoKCiAr68vhBAoLCxEUlISbty4gRs3biApKQlZWVnYtm0bmjdvjsjISGmJjo7G48ePodFosGPHDjg4OEgBOsHZxAAAIABJREFUaExMDLRarfReY8aMQfv27XHlyhVERkaitLRUti5OTk4ICQnBqlWrZINlU126dMH06dMxZ84cVFZWqj7Gz88P7u7uFmddtWvXDhkZGaioqDD7GBsbG7Rq1Qqenp5wdXWVLY0aNUJ0dLR0cnDAgAHw8vKCu7u71BfdunULZ86cwcCBA9GhQwdFH0VEOHXqFPz9/c1epU1JSVF9rlFN9ddrak9PT8czzzxjtv3x48eq9VGNarrS9d9Gr9fj4cOHePDgAXJyctCjRw84ODggNTVVmmEXHx+P+Ph4VFZW4uTJkygrK5NdiczNzQUAtG/fHocPH0ZsbCxOnz6Ns2fPIj8/X3ovZ2dnbN26FcnJyTh58qTqsXjRokUoLCzE0aNHpRM2plq2bIndu3dj+vTpSE9PV/1MY8eORc+ePTF37lyYi1H++te/IiEhARcuXDD73fTv3x9RUVEoLi42+xiNRoNGjRqhbdu2cHNzkxZXV1e4ubmhUaNGOHLkCJydnTFo0CD4+vqiU6dOsv0jNzcXP/zwA4YNG6Y6AwgA7t+/jxYtWpjdNv+bx/u1VocUhiD0NoB2AOwAxAHobOk5f4R7SI3Cw8Mt1uE0vUG6uqysLNq8ebPZ5+7du1c1K6pRdHS0aoIFo+LiYtqzZ4/ZdiIym+3TyFKCFiKSJV5Qc+vWLYv3Mdy7d89ie05OjsV7AwoKCix+/8ab4s158uSJxXt+ysrKamy39Po1tZeXl1NRUZHZ76C8vJxu375N4eHhdOTIEdq6dSstWrRIqq1aVlZGFy5coCVLllDv3r2lJAPG+xxKSkros88+kyXJ2rlzp+z1N2zYICVZqFevnqJUx759+6T7hf38/BTraJo1ddq0aYp206yBb7zxhqL9b3/7m9Su9vqmGaNbt26taDfNnGhvb6/YXqKiomT3ZVS/50Wv10tp8m1sbFQTNJgm2DJ3T53xc1iq8bly5UrVLL+mjCWbzNW+/bVqupc4Ly+vxsfUdK+tWnIZU2lpaRbvly0oKKixhqel+w6Jar7ft6Z7pmu6r7um+32NJRRqeow122v6jJb6PiLDPc2WXuPGjRsUHx9Pubm5qusSGhpK27Zto08++YQ2b95MGzdupJCQEPr4448pNzeXvv32WwoMDKS+ffuSp6en1E+1aNGCIiIizNYhbdGiBcXHx9O+fftkmYSNi0ajoWPHjtHly5fJ09NT9b6qN998k8rKymjVqlWqGWIbNGggZfy9ePGi6vt4e3tL9w1/+umnqu9jrGVaWFhottbhuHHjqKSkhDZu3Gj2PrAePXrQsWPHZCW21Jbq7W5ubtS7d2+aPn06hYSESJlR27RpQ1OnTqWDBw/KMjhPmDCBmjRpQrNnz1bUayYy3Efbo0cPOnr0qOo+sm7dOho1apTZ+rYLFy6k6dOnm+1nJ0+eTHPmzDG7/4aEhEgVD9R8++23UukQNeHh4XTw4EHVNiJD0rXqCXZMxcTEmE1ASGQ4Hp09e9Zs/37p0iXas2cPRUdHq/aBx48fp3nz5tHSpUtpzZo1tHHjRvr73/9Ou3btorNnz9Lu3bvJ39+fXnjhBWrWrJmUYMrBwYH27dtHGzduVM3/0a5dO0pNTaWPPvpItcxRy5YtKTU1lfbt26dax9TW1pZOnTpFcXFx1KdPH9Vtb9KkSaTX6+nOnTuqeUqcnZ2lez1TUlJU75kcMmSI9H9vTLpWfVm8eDHp9XoqKCgwu38vWLCAdDqdaoJP030qKSlJtQyO6WJMEmbav3h7e9OECRNo/fr19OOPP1KvXr1ICEGvvPIKrV27lq5fvy7bBo8cOUKenp60efNm1XtZKyoqKDAwUDUJldGePXss3vN/4cKF321c8WugtpIaAXgZwGmT3z8A8IGl59T1gPTRo0dSRrxFixaRv7+/IumMMVDr2bMnBQUFKTrHpKQkSk9PJwC0bt06xXvcuXOHPvnkExJC0O7duxXtDx8+pBMnTpCNjY1qqY/Kykq6ceMG2djYmL0xvbi4mBwdHVWfT2QYjHh7e5sNasvLyykgIIC2bNmi2l5ZWUnBwcG0dOlS1XatVkvbtm2jv/zlL2YHd99//z2NHTvW7AD52rVrqt+/UWZmJvn6+prNvPrkyRN6/vnnzSaaqKyspBdeeIE+/fRT1XWorKyk7t2704wZMyg8PFy1JEr37t3ppZdeotmzZ9OBAwcoNTVVVjLgxRdfJBsbG3Jzc6N27drRwIEDpQN9cXGxrHPXaDSyjKN5eXmyzrJLly6ygXpGRoasttXQoUNl63jr1i1Z7cspU6bI1v/27ds0evRoqf3jjz9WtA8dOlRq37Rpk6w9KSlJVmc1KChI1n79+nXy8fGRsqr6+PjI2rOzs+nZZ5+VEl3Y2trK9iWdTkdeXl6yotTVg6WZM2fKssxVLxtx5coVWbIL05rCRqbfcVhYmKI9KSlJeg1z25IxMF+2bJlqe15eHk2aNIns7e3N7pNff/01zZs3jz788EPasmWL4sBVUFBAU6dOpZMnT5o98CxcuJA+/PBDswFbYmIieXt7mz3ZVFlZSd7e3vTZZ5+pDuoqKiooKCiI3nnnHdWTRTqdjj7//HMaNWqU2YQYcXFx5Ofnp5p0hcgQaPn4+CjqwZq2jx07VlFKyrR9wYIFFBkZqdpOZKg/qVYr1ujy5cuy7LzV5efn06JFiywGhbNnz7Y4QAgODrYYeC9evJiSkpLMtq9evVpR8sHUpk2baP78+VLQVN2uXbvI39+fdu7cqTpIOnnyJDk7O9PAgQNpyZIldPLkSdn6RkZGSoNbOzs7euaZZ6h3797S95qamqpIYtOpUyeptuPDhw8VCfh69epFmZmZRGQ4BlWvR9i+fXsp269er1fUIdVoNLISFGvWrFEMMEePHi39vxw8eFCRrdje3l5KtBQdHS0FcaZLt27dKC8vj/Lz880mCQwKCqLKykp67733VDNh2tjY0Pr162nv3r1mg1VbW1uaOXMmvfbaaxbLUHh4eFD//v0t1l4EzJd/ad++PQ0cOFBRM9Xb25s+/vhjio6Opv3799OuXbtkx6P9+/dTZWUl6XQ6OnTokFTOzc7OjubOnSvbrs6fP0+bNm0iANSqVStFyajY2FiaOXMmAYYSOdW3/fv371NISAgBIH9/f0WG2ZKSEun9AwICVPet8+fPE2DIYqzWbiy7EhgYqNr/XL9+nYQQ1LdvXzp9+rRi/zceKxo3bkxTp06lEydOyMYWKSkp0kkDIQQ999xzNHLkSFq4cCFdu3aN7t69q6guYNyW8vPzVTOpP/vss1KgV1JSIstCDhiyFxs/i06noxEjRsjaGzduLEuyZFrL1biYJixUO/nSt29fKZA8d+6cLIEPYDgZbkwadufOHdXtvXfv3lRSUkKVlZWK+uzGZfXq1URkCFbVvic7Ozvau3cvnT17VlGFwXS/mz17Nk2aNMlsQAsYSua8/PLL1K9fP7PZnY2L6RjFdJ/805/+ROvWraPIyEipn3FycqK3336bYmNj6cCBA/TLL7+QXq+nYcOGkY2NDU2dOlVKnHTmzBmp/3733XepVatWsuSOcXFxUntwcDD17t27zpR7MUItBqSvwTBN1/j7RACfWnpOXQ9IN2/eTIAhJbdxsN+xY0dp8BMeHk6AoXaWsYDx6NGjpbPNubm55OTkJNvQly9fLnVcWq2WvL29pbOyQgjFldDJkydLZ7nq1aun6Li3bNkiHeDs7OwUZ/TCwsKk9OcajUaRPTA7O5uaN29O9vb2ZGtrq6jlZwzEjIMJtaB10qRJUoegVstv48aNUvvMmTMVQemFCxekdRw0aJBi8JqTkyOdQevYsaPijKter5euDDZs2FB1kD9u3DjpDOK0adMUA+DVq1dL7R4eHrRt2zbZwaN6aZr27dvTsmXLpKuMGRkZsvYGDRrQ5MmTpbNcer1e6phtbW3p7bffVmS+MxZ+b968uWow9N5775G9vT21adNGtaPZuXMnubq6kouLi2r2t4sXL1KXLl3I1tZWtaRKcnIyDRgwgJo3b07p6emK9qysLBo5ciQNGjRINZgrLi6moKAgev/99+mDDz6QtRmvIgUHB9PKlStp/PjxsvaSkhLS6XS0YcMGWrp0KS1YsEAajBrbc3Nzad++fTRr1iw6fvy44ux0XFwcXbhwgaZOnUoRERGKdUxOTqakpCSaMWMGnTp1is6fPy9r12q1Usbmzz77TDXgfPDgAR06dIjmzp2rCHiN0tLSaMyYMaop8I3Gjx9PEydONNtuHDz7+/urBiLHjx+XAgB3d3f661//KjsZc+/ePanfaNWqFX355Zey/U6n00nlnDQaDa1du1ZxMm3EiBFS3zRp0iTFfrls2TLpPfr3768Ido4dOyZlEff19VUM6tLT06Uanl5eXoptrry8nLp160ZCCOmsfnWvv/46OTk5UYsWLVSv1q5cuZKaNm1KjRo1oujoaNXvsUWLFlS/fn3VbTo1NZXatWtHQghZSRmjsrIy8vPzIwC0ZMkSRTuRoQ+vV68eBQQEqJ7sWr16NTk7O1Pnzp0VsxaIDLNbGjVqRE5OTqpXdG7fvi31zwEBAYq+Qa/XS1cXHR0dad68eYpMi6a1pOvXr0+vv/46nThxQjpWvfPOO7L+rVmzZjR37lypD/viiy9k7W+88YbshJGxFqDxOBccHCy7KlRUVCTLOD9t2jTZd2XaxwOgrl27UlZWluwzmAak1YNRIsOx0nQdhw0bJrv6FhYWJmvXaDSyfTgnJ4ecnJzIyclJGnT6+vpKxxK9Xi8Nrvv16ye9jvEqDhHRlClTCDBchWrdujUBhlJAp0+fJiKSynwAkA3kO3XqRJGRkRQZGWl2INyuXTs6fPiw6lUv0wG42oD5/7NYKvViPC6qtTVr1oy++OILKi0tVc2wO2HCBGl7qn7ywcHBgbZv3y59j9Xr4jZv3ly2/+7du1fW3rZtW1m22sTERFl7mzZtZP19eXm5bHt0dnamjRs3yk4q9ejRQ/Yavr6+9PXXX0v97PTp0xWfsWHDhjR+/HhKTk5WDeaGDBkiBbfVt0dvb2/ZMS83N1cWHA0ePFg2rqmsrJSNPX18fBR9tGlpGycnJ7p69aqsffXq1bJ1WLx4saz95MmTsnZPT0/ZOqSlpVGDBg1kV1pNL7yUl5dThw4dyMHBQZq91L17d9nVP+M6mtbl3bhxo9S+du1aAgzHQQ8PDwIMdeSN39W5c+dk26DpNhEWFkZFRUVmK2XUr1+fFi9eTB07dvyP94n/7+Lm5iabDVK/fn16//33yd7eXrryOnDgQKl9/PjxlJeXR76+vqTRaGjUqFFSEN+kSROpb6kLUIsB6VgoA9JPVB4XBCAKQFSbNm1q4Sv4zxkPHtUXV1dX+umnn1TPuAKGg1FhYSF9++23qlOA5s+fT3q9nhISEhQds42NDe3fv5+IDIPwTp06ydpNz9gSkSK1uqOjozTNk4gUBaIdHR2ls9JEhmkjprUA7e3tZR1zZmamrKaSra2t7Ey8VquVBmTGpfqV1Pfff1/WPmPGDNnguPpUildeeUV2JTQlJUV2cGjcuLEsGCgvL1eU15k1a5ZsQDNjxgxZu7u7Ox08eFA6wB05ckTW7uLiQsOHD5cCt6ysLHJxcaGGDRvS0KFDafXq1VLZGuP3MHz4cHrppZdo+/btqlcZdu3aRYMGDaLExETV7e3JkyfUp08fs2e1KioqaMGCBRavlERHR8um6lZnrAdoiVowbKqwsNDidBEisphWnYgsTr82snbNrF/L0hWxkpISi99hVlYWHTp0yOx3cPPmTfL09KQpU6bQ7t27FYHMgwcPFAPPF198UbpSWFpaSl26dJG1+/n5yU72jBo1Stb+/PPPy7a96vWF27ZtK0u5b6znZlw8PDxk7deuXZMNqFq1aiUr12N6IgowDOJNz95rtVpZSa5mzZopSiiY9o9ubm6KkgDr1q2T2hs0aKC4dcF0wGVjY6OoLXv79m3ZVbXqV8VLS0ulgRZgGDSaXrHW6/U0adIk2WeofjXX9EoUAPrLX/4im2J769Yt2dQ8Z2dn2rp1q9TH6nQ66UqJg4MDderUicaMGSPN/iEiWrp0KWk0GnrllVdo/vz59MMPP8i2z7i4OLK3t6eAgAD6/vvvFftvUVER9erVi4YPH646vVOv19OKFSuoQ4cOZqc5pqSkkEajUdTuNP2uR48eTX369FG9opWZmUnbtm0jjUajOLFKZOhzLl68SBqNhvz9/VWnKR89epRmzpypOM4ZnTp1inJycsjf35969OihmLETFhZGcXFxdO/ePRJCSCWGjBITE+mbb76hyspKqRyS6T6XlZVFGzdupPT0dKnO5TvvvCMF7xUVFTRv3jw6evSoNBB3dnamjz76SDreBQcH04oVK6QrjIAh2Hj33Xfpzp07tGTJEpo0aZJ0AtR06dChAw0cOJB69OihqD9efbFUE9FSUNy5c2ez9d3d3d3pwIEDir7JuAQEBFBeXp6idq9xfZYtWybNyKpe+kWj0dCmTZtIr9dTRESEomSeEILmzZtH5eXl9PDhQ0XACciDwtmzZ6uu48svv0yxsbF07tw5KVBp2rQpjR8/nr788kvpRMr9+/epe/fu5ODgQDNmzJDtj8b/6/nz55OjoyOFhISoHk/i4uJICEELFy5UnbqckpJCo0ePJj8/P9XjTWZmJn3++edkb29PP/30k6K9oqKCIiMjyd7eniZOnKi6X545c4ZGjRpFTZo0UZ2effHiRcrPzyfgXyW1TEVGRtLdu3dpxYoV1KlTJ8XJspSUFAoPD6eCggICIJs5RmSYofLll19SWVkZDR06lJ5//nnZ8bCyspLWrl1LycnJ0omzyZMny8YoK1eupAMHDlBiYqK07ZrWfl23bh198MEHtHXrVtl24eHhQatWraI1a9bQa6+9RmPGjKGXXnpJdbtwcnKihg0b/sfBq6XnNWnSRHV6tXG7Xrx4cY23bdQG8JTdXyc2Nla1465Xrx59/vnnFB0drXq2r1u3bpSZmUnz589X3Uhmz55NoaGhqnVCbWxs6ODBgxQeHk4dOnRQtDdo0IDCwsIoMjKSXnjhBUV7o0aNKC4ujhITE1V3DldXV0pMTKScnBwaNGiQot3Z2Zmio6NJq9XS//7v/yra7ezspKB4//79qkG3cYrbjRs3yMvLS9EeFBREOp2OSkpKaMKECYqdydvbW+q4t2/fTgMGDKD27dtL72VnZyddTY6Li6OZM2fSuHHjaNiwYeTn50ddunShUaNGUWZmJpWVlVFISAitX7+eNm3aRFu3bqUdO3bQrl27pKsy58+fpxMnTlBCQoLZjjs2NtbiTm1uurDRw4cPLQZZOp2uxnu5agrk/p0aouyPr6b7Q27fvk3ff/89hYWF0Y0bNygrK0t2giYhIYGCgoLorbfeovHjx9Prr79OAQEBFBgYSElJSXT79m0aOHAgvfDCC+Th4SGdEHJ0dKQDBw5Qbm4uDR48mDw8PGQDvwYNGtBXX31FpaWlNHHiRGrdurXsQOro6EjHjx8nvV5PixYtoo4dO8qe7+LiIp0Q2717N7300kuKk1HGWnWhoaE0fPhw2dTEpk2bSrMSUlNTacqUKdS5c2dp8Ny4cWMp6C0uLqZFixZRv379pKlzzs7O0pUU45TjN998Uxqc16tXTxbsXLhwgebOnUv9+vWTZqosX75cak9NTaUtW7bQn//8Z+rZsyc5ODjQq6++Kg2GSkpK6PDhw7Ru3TqaMWMG/elPfyJvb2+pTimRIcj56quvaPv27bR27VqaN28ebd++XQo4U1NTKTQ0lCIiIigqKopiY2Pp+vXr0hXtkpISunr1qsU6pAkJCRbvxb13716N9evUrkBXb7f0Ho8ePaqxdueePXss3nP8008/qQajpkaOHGmxpuKSJUvon//8p8XXWL58ucUTShkZGXTo0CGLr7Fy5UoqLi422/7+++9brMs6depUmjFjhuy+T1MTJ04kDw8PWr9+vWoAHxgYSIAhCF2wYAHFxMTIto+AgABpv3JwcKC+ffvSggUL6Pjx4/TgwQN69dVXzQ68O3furHr/YvWBsrk2cwErYLhv2NK9fv3791cdtxiXUaNG0UcffWS2vVu3bnTw4EFyd3enZs2aUdu2balz587k6+tLvXv3psGDB9O3335LkydPpokTJ9KyZcto3759dOXKFcrLy5O+wxMnTtDq1aspOjpa9VYlY14HSzVCjx07ZrH+b35+vsWp+kSG2QuWtvcrV64oZhNUN23aNIv34gcHB9d4Ijs4ONji2OS7776z+FkfP36selubqZpqjK5fv15xUtHU6dOnyc/Pz2zt18ePH5OTkxO9+uqrdPjwYdXjsHGqu5OTE40ePZp27twpm1Kudi+rRqOhrl27UmBgIL3xxhsW9xtzU+0Bw1XkYcOGmd0vqs8qqW2orTqkQoh6AFIA+AO4DyASwJtEdN3cc/4IWXaPHz+OcePG4fHjx6rt7u7uyMnJUW1zdXVFcXGxLJufKS8vL9jZ2SExMRE6nU7WZmNjg6CgIJSWluLy5cu4deuWrL1hw4bYtm0bHjx4IKXKNs2C1qxZM/z444/IycnBxYsXcfHiRfz8889S5r6WLVsiPDwcGo0GoaGhuHjxIkJDQ5GUlATAUKvo0qVLeO6555CYmChlYbt06RKys7Ph6OiIs2fPolevXnj8+DEiIyOl9PkREREoLCzE3r17MX78eACG7GPGOqbGZdiwYfjHP/4hZRvLz8/H9evXkZiYiOvXr6OiogIfffQRXF1dpc+l1+uRnZ2N9PR03L17FwMGDDCbzYwx9tupqKhAQUEBCgoK0L59e6nMhl6vR35+PrKysqTSFUOHDpVK4lRWViIjIwNpaWlIT0/HvXv3MGnSJCmDplarRVpaGlJSUpCSkoL09HTMnj1bKtGh1+uRnp6OhIQEJCYm4u7du1i0aJEse3RWVpZUhuPevXtYsWKFLIPno0ePEBUVhZ9//hlpaWlYsWKFrGSPVqtFQkICIiIikJycjEWLFilK+mRnZ+PKlSu4du0aZs6cqchArdPpcPPmTVy9ehV9+vRRzcCs0+mQmpoKAGbrPxo/89OUIfS3QlRzhsqasto/evQIDRs2/NXv82vVVGc0KyvLbHkKIsKJEycwePBg1TqkxcXF2LBhAwICAtC1a1fFZ4mLi8OqVavg5+eHV155Bd26dZO9zs6dO7Fz5060b99esbi6umLKlClITExEo0aN4OLiItUYdXFxgVarxeHDh0FEsLOzg5OTk1THUgiB/Px85OXloV69emjTpg2EEHjy5AlKS0vx5MkTFBcXo6ysDF26dEGnTp3w6NEjqSxfUVERCgoKoNFo8NZbb6F58+bS301L99nb2yM4OBhNmzaVlfww/iyEwNixYy3Wgf1v8e9syzVtiyUlJXB0dPzV7/N7q+lz5Ofnw83Nzex6pqWloaioCF27dlVtz8nJwerVqzFs2DD07dtX0c8UFBSgf//+cHd3R9euXaWlU6dO0Gg0KC0tRZ8+fRAdHQ0AcHNzg7u7O5o2bQp3d3e4urri9OnTuHfvntnPYGNjA71er9rWrFkzHDx4EP379zf7/N9TbZd9GQZgEwwZd3cS0SpLj6/rAaler8exY8eQlpYmq2109+5dZGdnS4/z9fXFkCFDkJqaiqSkJNy8eVNKG9+0aVNs3rwZZWVlUgHf2NhYPHr0CADw1ltvYfPmzYiPj8fVq1el5c6dO7C1tcWhQ4cwZswY5OTkICIiAuHh4bh8+TIiIyPh5OSEixcvokuXLtDr9UhOTpaCxtDQUNjY2CAsLEwauJWWluLnn3+WAtC8vDycPn1aNnDLycmR2tPS0vCPf/wDrVq1ktqJCLdv30ZoaCiuX7+ODz74QFFgXq/XIyUlBVevXsWIESPM1knLysqCo6NjjQd/xhhjjDEjrVYLIYRqgKHValFcXCw7mc2YtdUUEOfl5SEzMxPu7u5o3Lix4mTSjRs3EBUVJQXMpv8KIRAbG4uMjAyUlJTAxcUFFRUVKCwsREFBgfRvcXExFi5ciAULFtT6Sc9aDUj/v+p6QGpJeXm5rAivq6srRowYAcAQkN27dw/JyclISkpCZmamdDYOMAR1aWlpUnDq5eWFwMBA2evn5uYiMjISMTExeOutt2RBofH9r127htu3b2PcuHGqG3l6erpUj0pNRUUFHj58aLEWWE07EGOMMcYYY6xuIyI8efIEdnZ2qrMnfk8ckDLGGGOMMcYYs4p/NyDlm1UYY4wxxhhjjFkFB6SMMcYYY4wxxqyCA1LGGGOMMcYYY1bBASljjDHGGGOMMavggJQxxhhjjDHGmFVwQMoYY4wxxhhjzCo4IGWMMcYYY4wxZhUckDLGGGOMMcYYswoOSBljjDHGGGOMWQUHpIwxxhhjjDHGrIIDUsYYY4wxxhhjVsEBKWOMMcYYY4wxq+CAlDHGGGOMMcaYVXBAyhhjjDHGGGPMKjggZYwxxhhjjDFmFRyQMsYYY4wxxhizCg5IGWOMMcYYY4xZBQekjDHGGGOMMcasggNSxhhjjDHGGGNWwQEpY4wxxhhjjDGr4ICUMcYYY4wxxphVcEDKGGOMMcYYY8wqOCBljDHGGGOMMWYVHJAyxhhjjDHGGLMKDkgZY4wxxhhjjFkFB6SMMcYYY4wxxqyCA1LGGGOMMcYYY1bBASljjDHGGGOMMavggJQxxhhjjDHGmFVwQMoYY4wxxhhjzCo4IGWMMcYYY4wxZhW/KiAVQiwTQtwXQsRWLcN+qxVjjDHGGGOMMfbfrd5v8BobiWjDb/A6jDHGGGOMMcaeIjxllzHGGGOMMcaYVfwWAeksIUS8EGKnEML1N3g9xhhjjDHGGGNPgRoDUiHEWSFEosoyEsDfAbQH0A1AFoAQC68TJISIEkJE5ebm/mYfgDHGGGND88CgAAAFRElEQVSMMcbYH5Mgot/mhYRoC+A4EXWp6bEvvvgiRUVF/SbvyxhjjDHGGGOsbhFCRBPRizU97tdm2W1h8msAgMRf83qMMcYYY4wxxp4ev+oKqRBiLwzTdQlAGoAZRJT1bzwvF0D6f/zGtaMJgDxrrwRj4G2R1S28PbK6hLdHVpfw9sjqkrqwPT5DRE1retBvNmX3v40QIurfucTM2O+Nt0VWl/D2yOoS3h5ZXcLbI6tL/kjbI5d9YYwxxhhjjDFmFRyQMsYYY4wxxhizCg5Izdth7RVgrApvi6wu4e2R1SW8PbK6hLdHVpf8YbZHvoeUMcYYY4wxxphV8BVSxhhjjDHGGGNWwQFpNUKIIUKIm0KIX4QQ8629PuzpIoRoLYT4SQiRJIS4LoSYXfV3NyHEGSHErap/Xa29ruzpIYSwFULECCGOV/3+rBDi56rt8ZAQws7a68ieDkKIRkKIr4UQyVX95MvcPzJrEUK8V3WsThRCHBRC1Of+kdUWIcROIUSOECLR5G+q/aEw2FIV38QLIXyst+ZKHJCaEELYAtgKYCiAzgDGCSE6W3et2FNGC+BvROQFoBeAt6u2wfkAzhFRBwDnqn5nrLbMBpBk8vs6ABurtscCANOsslbsabQZwCki6gSgKwzbJfePrNYJIVoBeAfAi0TUBYAtgEBw/8hqz24AQ6r9zVx/OBRAh6olCMDfa2kd/y0ckMr1BPALEaUSUQWAfwIYaeV1Yk8RIsoiomtVPxfDMNhqBcN2uKfqYXsAjLLOGrKnjRDCA8BwAJ9X/S4ADADwddVDeHtktUII0RDAqwC+AAAiqiCiQnD/yKynHgAHIUQ9AA0AZIH7R1ZLiCgUwMNqfzbXH44E8CUZXAHQSAjRonbWtGYckMq1AnDP5PeMqr8xVuuEEG0BdAfwM4BmRJQFGIJWAO7WWzP2lNkEYC4AfdXvjQEUEpG26nfuJ1ltaQcgF8CuqinknwshHMH9I7MCIroPYAOAuzAEokUAosH9I7Muc/1hnY5xOCCVEyp/4zTErNYJIZwAHAHwLhE9svb6sKeTEOJ/AOQQUbTpn1Ueyv0kqw31APgA+DsRdQdQAp6ey6yk6t68kQCeBdASgCMM0yKr4/6R1QV1+tjNAalcBoDWJr97AMi00rqwp5QQQgNDMLqfiL6p+vMD49SKqn9zrLV+7KniB2CEECINhlsYBsBwxbRR1RQ1gPtJVnsyAGQQ0c9Vv38NQ4DK/SOzhoEA7hBRLhFVAvgGwCvg/pFZl7n+sE7HOByQykUC6FCVIc0OhpvTv7fyOrGnSNX9eV8ASCKij02avgcwuernyQC+q+11Y08fIvqAiDyIqC0M/eF5IhoP4CcAr1U9jLdHViuIKBvAPSFEx6o/+QO4Ae4fmXXcBdBLCNGg6tht3B65f2TWZK4//B7ApKpsu70AFBmn9tYFgqjOXK2tE4QQw2C4AmALYCcRrbLyKrGniBCiN4BLABLwr3v2FsBwH+lXANrAcBAcS0TVb2Rn7HcjhOgHYA4R/Y8Qoh0MV0zdAMQAmEBE5dZcP/Z0EEJ0gyHBlh2AVABTYDi5zv0jq3VCiOUA3oAhQ34MgD/DcF8e94/sdyeEOAigH4AmAB4AWArgKFT6w6qTJp/CkJX3CYApRBRljfVWwwEpY4wxxhhjjDGr4Cm7jDHGGGOMMcasggNSxhhjjDHGGGNWwQEpY4wxxhhjjDGr4ICUMcYYY4wxxphVcEDKGGOMMcYYY8wqOCBljDHGGGOMMWYVHJAyxhhjjDHGGLMKDkgZY4wxxhhjjFnF/wEdg8kQJXERZgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def next_frame():\n",
+    "    shear_flow_scenario.run(50)\n",
+    "    return shear_flow_scenario.velocity[:, :]\n",
+    "display_animation(plt.vector_field_animation(next_frame, step=2), iterations=50)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Vortices are created between the two layers. This phenomenon is called [Kelvin-Helmholz Instability](https://en.wikipedia.org/wiki/Kelvin%E2%80%93Helmholtz_instability). For a better visualization of the vortices we can plot the [vorticity](https://en.wikipedia.org/wiki/Vorticity) of velocity field:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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GFJy30Pclvgsj1xBo25F3PsP1a/buuyUiBlVumkKCnHEZazv4vgYTMCMmW+iOldix/V4e6Od5nHeP8fiJnHMF11kz87CZ70f9IiqEEEIIIYQQYlG0EBVCCCGEEEIIsShaiAohhBBCCCGEWJRFNaKWc5Fcnn1PjN8hRzQcNMZ9m+8PNuJH7Oxu4LECud3dP9/ip/Evo2Ypoj2KJWL2NwcTmtc7F2I1aAFZ++q35faw9jFj+/w6NXdZLBkyVsv+nATXfqvyDKe1iOwTOKGMuphAEm+mI+1A23DwMQ1ohVFvZmbW7krxTHPlhTrNDk4AdWt7rwtLAyScZsnBcRwiiaurdVk2tj5mXJUVDWNEJMfAZ+GfZz9DmDkG6nWwS4jU8xKOnXOJaOSw/9F+jppQbILscYL+DXXfZmYV6rNJH65AC07fI4G5A0L1eDCgolbx+nxAL34ox4a08yJW1ITmS/+CynuIOc7UiMIYkgY28MD5MV0Y1oP6TzJuu/cReUF5HTqJgbrnapvdLnPnneghgjEz9KDXZc/eNnvxfEemNJjuXln0Hk/HYJ9l2k5sF+j7YWaW4SLy6N+prlniWMDaLfS1nEnfc+2f9XNf5EBdN9GRZohJPam4g/Gr8zF1yLvCo19EhRBCCCGEEEIsihaiQgghhBBCCCEWRQtRIYQQQgghhBCLooWoEEIIIYQQQohFWdSsKOXSUIAJiKsezQ5YcneI6UhMRNCMxydqbyxJRG3ORNew063xSUu4fquCejS3IaYXzQ4SoxOzImTYTJeNq2nhfagdzEhCzXeJZJye2DZiOFCT66wnYkiScRfD+lDkfqHGnxkawfhQHfxggOZEzZWvp70sL6S98PWsLiDmfIBtX29zAcYngQT19NZclceuNq0LGbdlWRr8KwCNHqhJFJgcJTbwgNnCMGNw8uZFZnMMjLx5EaknYiQSMFJ70YkYurCLmjMWuGMTT44KPC/QXMzMGxgxQ6PQu3CGWRFtbs4YjxwK5jJoXpQ6chFY1rOY0uQos3rGgIsJmJZgUnszM2tgfGAmJmiMhGNKM21ExPvnDJ7fA++6zJnB+ZgRLoua2+C7MGROBNvMHGvaRypm6BghMC9wBoV0fg0xeG+YPw/EjOTdg+8V9n5CT6GKNoxyP36Ln/+3OrcHqwL6GjMBc2Zi2BfNLOP4gMZEZmYV1M2Mm9DAiBmXDTh++ZjUBBoqQb+ICiGEEEIIIYRYlNAvoimlPzGzc7s2C+5zzm+mlB6Y2W+b2efN7E/M7N/NOX9wO6cphBBCCCGEEOJl4Xl+Ef1Xcs4/nXN+88n2r5nZ13POXzCzrz/ZFkIIIYQQQgghnslH0Yj+spn9wpP//1Uz+z0z+9Vn7pHLxM+oobgug12Yvgy+ceaJcTGGnM903mX8lPvHfGk+cT7Tn6eLCSIJ11FrVO+JHg80oUx7Maxgm2hEURNK2ykWRJ75DX0s77QpkeTRRMvjypjep4XE7SvQRbZeV7Rqy46+anxMU5dldUD0wnSIx758OPuj104eDmXZ8dLHVKj/fEw0oo/K468fltubrd9n3ZZlDdHFV+eliDXtDi7GxrIsXfljpU3ZuKtT37ir0zIm9b5x+35DhTCwCX2GaNIimirUjeZAu0C9khnTpc3UKX/SoJrHwIVW02OeG2fgpUq1bqhJJjJEVxbR6tK5A24T/TNq0Hw1k/tcV47beG/IzcAy1F+aWXaJ7ufpsm4Mpi2dwPV9OhYEYiI+DE7b7EPGBvSCfvh3mtCxneELEdB/RvSgkUbJp50obg6MwTPnJCg7xGoyGXPGkAHG9LhdB/SfXjdKzgfbDnmRuLUGtKXU+H0q0H9WLVmKQVk6dC4koV6caTvdwcmYh/rThnQSpi1FZuqSo00sm9n/mlL6Rkrpy0/K3sg5f9fM7Ml/PzPvFIQQQgghhBBCfJqI/iL68znnt1NKnzGz300p/cPoAZ4sXL9sZrbe3J9xikIIIYQQQgghXiZCv4jmnN9+8t8fmNnfNLOfNbPvp5Q+Z2b25L8/+DH7fiXn/GbO+c12dXozZy2EEEIIIYQQ4hPL5EI0pXSaUjr74f83s3/NzP6emf0tM/vik7AvmtnXbuskhRBCCCGEEEK8PEQ+zX3DzP7mk2THjZn9jznnv5NS+j/N7HdSSl8ys2+b2a9EDvhhX4mEambzyWkjxgUsJmZ6BPUQ4XZCI4zp/LruGpiZUkAn/VIwO6kyMnGPzcyqY7mNxkRmZhXovTFJtZk3JxrW/iIwYTL7k47T4gfa0mQdZD9uxIXGIuRBYBkxX0DjodXaJ0/frssbfwe2765Lox0zs7ttWXbW+phtXT6sNctiD4zkhh3gIV/2axfzqCsf+nt7//XG+5cnxfbFuTf6OX5QGv1075cNpTv1A1G/Ls952xITJBibKmJ0ki6uiu289/fU9qWhUbU/upB0LK8zEbeuiHmY7xQRc6BIBviJbSPJ51k1aFxDO+R0n50a4yI+QLeJf1bPb0xkRsZKNqZMQY4dMWsJvUecsQg5fI3vZlIPvr/JdXozxIiRDsRgonlWVhOjMCxrvLNOBpOjxIxGsJ6WOPSgiQk7Z3ddE/9u5vsRe386Yykf49+FxHAmYEQ0wCsBDQuvywJmXeivhG050rZZu40Mi4E+4kLY3NSZRLGDTR8LVxfMDNQf+tkGd2YWbF/lflU/3QZZNW7KQWIGHAtgjEk1MTgCA6PckX6+QbMiv9BJHZwgMTdz6yxirJbxHMm4k7GMmCrOXcdMLkRzzn9sZj9Fyt8zs1+ad1ghhBBCCCGEEJ9WbihZhBBCCCGEEEIIEUMLUSGEEEIIIYQQixJN33JjTH3rHtGLVAN8q0++/0ZdZmJJ4gMahAq+/x7ZN+uoU3AnExAW8ezDnzhuRBMaSLiOWk8zs3pXxtQHH4PPmMjfrN+WJ8B0pE4fQrQWU4mhuf4zoCPFephWC8+nmdZ/tium/yxv9NnG39T7m1KM+/r6oth+DbbNzF5rz4vte7UX9J5W5bE2yT/0GgaIgXTiDh7W5Ug0okOpi3y3u+Ni3rl7Vmx/9/5dF/P2vbLs4d2ynu7Ui4+GTXnOI9FqofbJX4FZjcmse6KpPZT3NHdEIwpJsmvUoZhZ6kFHOhJRFbxeMBk419UFEq7flrbfh9yIvnPumDjn2PRYIX3l9JiHY0gmB0s3cMOothO7NdMU4is10Hao7hD3IVpAvD+oQzQzG1vs1+V2IknsXdnKjwUp4ySJtP/cTMeg5osdC8vIOVtT1oNaMt7PAxpbp+cl9xhiBqb/hKGp3/h6UCM6El+IDHXTKRsW4qOK6Dhn/jzk+g2bqk7LBWMDI7QnOsVFL5eAt4Wfk0f6cETD7Y+FZcyCwsUEPGtGPBZZe4wtzGd7f4JVX/ajtCHjbQdacJwDmFmC9ZIRfwmvCyb3vcHxjOhImRY9gH4RFUIIIYQQQgixKFqICiGEEEIIIYRYFC1EhRBCCCGEEEIsihaiQgghhBBCCCEWZXmzog+JWZmZAEK9gUKGRnBcJkQGrS0TIqPwmBljuJNEDS85PyfqZRcaSHQ8dSqMm0qwfiPGRGb+OlnSc3g21cHHOHMicn4ucTUxK8KE15kY/TgDC2qwAfu5RMyBfdizQnMiYlaUmrLRNa1v3Kt12SlO1t645t5mX2y/sr5yMZ/dPC63V+X2G+0jt8+rTWlg9KD2hkanqTyfDTYCM6vgIY/khnXgOHCJrhNm9nAszXfeaE9dzDur0qzo9dW5i3l9U17Hn2wfFNtvb++5fS7X22J7bJgJAA7VWxezBlOCmpgS5L58NnnvzafysTQrYgYI2JQbZm4wlRg9+b+DRkwmqkDfMzSZo4nb4dikmpgDCNtxGdwYHDB6YwM3etswczNmCuKDYDtiGoXvwoCxCDV0cdc5XU/kWGxMSW15XWiIY2ZWgQnZcChvctWR/gkvKNq00NGFjO2GhkaE1MBDx20zZ2CU18RIDU1LwNQETU7MzBm4oOmQmTcrGlfEZAjKmBFRfwIxJy7EzQNwDsCIzE0R2m4j49AM2FTVG2mSHQNjChqVkaHcjcGGc3I6L4YqWP+scZuZWJXbdecvAttcTca3qg+8j3CNgOsT0j1xTTAwIy40NxvJPG8AQyM0JmJlxKFq1rqB9VmZFQkhhBBCCCGE+CSghagQQgghhBBCiEXRQlQIIYQQQgghxKIsqxFNVi59I58Ts4y78LEy/QYbvhFn305Hvv8O5Hn1+2EMqxe+EaffVrvswz7kpvRJN6b3nCKgYWI6ixrki83ex1SltM3rnsxrQQaWuBoTt5N6JvWfkRh201HvydpOXd6giui56qbsFKuVF0mfgib0bO31gqgJ/czaazk/A1pJ1IR+tn3o9nm9Lve5X3l96gncnxXpfERl6Er2ubwXZ7lzMZvUw7aPaSGmJQPPGrJib+uynm3j6/12+0qxfVXfcTGWUBjjG2Xqy8a97oimFvSfmeg/8xGexeWlPxbWS8bp1srryFUppBubaW2P02Ib0QQFdH5Mw+Q0L6yvuSGYDbgBXfcMZo3JAQMAmtwdxh3cDh8exrwE58OfZ7k9kvE2QRl757vLmuuXgGXkfEbYsWc54tHXoAM9FxEiNtCPKjbhAA156snNwH7N5hcVajnJw2nLi3d6UFI2oka09Q0OY8aVjxnWZVm/Jvp/1H+ekhiQ+3NfiEAfxhCmcXQ6+Il//3HHmhOD5xIpDFwnBR8X1Xs+W0eaRnJwaMosxL0KSbNFHwGmI616HPNYzLO3zbz/DMZQW5mAzw2+Uun7AN+hTLfsNL8BjSjRozrImDLXf0a/iAohhBBCCCGEWBQtRIUQQgghhBBCLIoWokIIIYQQQgghFkULUSGEEEIIIYQQi7KoWVFOYFAxU7jtcmQz8S2onJkY2JkJsLzQzvTIx1SYPD1gXuE041TsPZ2IPCQ+x5CljInMQsJ39zzJvagOCbZZReVmT0wJhm15MGdSYN4Hhhl3uDKa0BljYJvUm1DgT2JqMCuqG3/D2hbMd1qvst+2pXHNaeMNg86aA8T4G3+nLp2jTuHhMOOfDXSkljSUDaj8W+I404Ir2UhcE2oow20zswGcrjrigLCH69pXOxdzqEsDkg6MPAZiplFBB/gTF2F2lUvjn4SuPmZW9S1s+8ztq65sB8zoBM2KnHmRmXNgqFbeeKVal+ZEzQqeFTExyTUYndBk5dMmE3h70uBjsK/RcXrG+DpnTJ5NyFgEzdemDdroSwKvgx4bDQAhiBm/QXccVz4Gnx99nzvDjcnTo6CZEzV3cvVMv+STq4i5MpWbdeMPXu1hP2JKZiO7eDwWPCtyrFxDRyIx2I/RnGhgZkVoRLTxMf0GjIhO/D3uYDztty7EmROxd757fIH2RY1ZsO1MmBfxmAUnaBF3GWowOV2Nu1/OrIjNf2CbjO04B6dGdDj+B0zvmOnRCIZGVUfe3/XENjE4coZGbM6LZkqk8aQZaw0WFIphrks3hH4RFUIIIYQQQgixKFqICiGEEEIIIYRYFC1EhRBCCCGEEEIsyqIaUbNUfJcdSu4b+S6ZffIfSBiL36hTHVHge3RMwpvwnAdygphwl1QbS6aOBPQPc7kJ6QJ76PBs6oOPaUoZIn2ewxq2aeJqOB2mWWqmNVWT+k8zpwGN6D8riKlqonmEsqbxGqE1lK1qH7OqMMaLGRqIYfrKEcQfRxBbdOQm7yGmZdpOEI9tSExHhWBwfm4fT8eEYDOooGHWsL2t/dFf31yU53LPi1W+PZTnt8Ms7WZWH8qY5kB0m4dyv7bzz7way2eed3sXg+LJfOX1sqkpr6MGvWzDNKKQoHsgei7U6WCfNvMaHKb/SaDBd3pGM6LzYyETWn46uJOyOQQ0Xk7zGBrPSEUR7dqEPpYO/y7h+nS9KXDdFenoc+R3dGjAVzw9nbLwCDFjzfSWZWNuVj6mWZeNOR39GFj1AY0owLTW6FOB+k8zsxF0o6gZHda+XtSEoh7UzAwl7kwjij4Q49o/4BFfP+xZRZr2lP7TzGtE2ZiCBPrI1D5h3OnM6NOsjJ30VL9m2k7nF3KLOlJoFyPVcqKOmtTTwbsQ3k/s3YNtCfWgZubWPomtI1A7T/xyIjj9J3uceA9vUDKqX0RJ7oAcAAAgAElEQVSFEEIIIYQQQiyKFqJCCCGEEEIIIRZFC1EhhBBCCCGEEIuysEYUoN8ho26HxUzX43cih0cdKcsRit+Nk/NBNYaTtUa0sOw68fwC9XAd6YuTl4rmS8J8riRHKOp92Hf3qAkdmF5kBd/zszyiqN0kWk6D3J1M74maUNR/popoeyAG9aAspiH1JBBDYa5KRj/6RrgbSs3SRbV2MS08QNRJMva5rPeM5OQ8Hcv8lZvkRRxt4FgD9AnUp7LzOR+9wPh8KJPUXY3+XhxAsNhBQsue5f+E/nlv7e/FG/fKofo7Rz907w7lOdd7oi/blUkaqz3RmqJulOhIXa7R3sdgjtJ0LGOqgx9wK8gvWJO8bSNqRDvSh0Fr6nRi5nPL0aaE42sovWYg//McZuQMNSOaUPbnZxy/qP7to2tEI3nuxsD7nMmlIhMB9z6P6N8ILk9tYJ4y1tNtcmxBI030lQP06+pIdNSgOaP6MoDK/DDXYkP6I54z6Fp7dg0wvPZbov+EnKDoAXF9bMwp7GMQmrM9Mh/DsYDNC6b0npG5ICGmG50jgJ6ZR9TFkHFnQl9Px1Lo/Gz+73KCMh0pakTJoIIx1VwdKfQRzCNas/dTYJ2DZhb8V0Po5+T8cIHCU0RDP2J5YbFtVz4o0v8Y+kVUCCGEEEIIIcSiaCEqhBBCCCGEEGJRtBAVQgghhBBCCLEoWogKIYQQQgghhFiURc2KUs5W758qZ1kCZRTwM0E/qrsjemuq40YRLxM9g8iZGRq5XLAYQ12GAgpwTI48vcePsSqacYNC6vjpaiL/Xh3KY9XErAhhxgXDtqwcjYnMvDkRNRxoA0ZE9XQMGgSheREaCpkRQ6OIlwB5VgO0244YEVlfGuuMpJ30oD4/kg65G0oDnEdN6TLxbn3m9jmr98X2SXV0MSfgWrUhGepr6MTMKGkEJ4CB/P2tg+vcg+mQmTcnOkfHDTO7Gst7gWZPuG1mduCDXMGdVXkvXrl36WLe3cE1XK5cTHNVHqve+2uowFQojcTdY18+Pxv8wJiP5fNK+/IZV2t/L+pNeQ1D558VGrFg0nEzsxGNKMi4ndHQIpB4nA7Cc4bKKVMfFhMYk2nydDQrYmMeJolnxkSB8cuNRfhaYU5EaNxBnH/cboGE6zUbPPFdzcw9cJeAoRE1+oFujefHjX/Kbfae67blQ2ZmKGjKxMyKIq98nKMRrzViVlT+OzVcQmNBP1QZDKX0XU1NXoDQdeKzYaYr0P5pd3SGLhMnQ/YJjSfzpmeEgIlVyKxougzHBnYrMh4sYjJKxhS874lcBNaD/dXMLMG7hb4jsJ+7bX9+FbRlNDwyY+OZPzaeDhqcmpF1DbsXMD6EmhczKyJloapm7SWEEEIIIYQQQsxEC1EhhBBCCCGEEIuihagQQgghhBBCiEVZViM6mjW7p8IcTPBsZlY15dp4DOgoEvu2Gz6DxqT2Zv4bf5bo2CXGDSR6xc+kWZ50lgZ9EpZwd3qv0PfeIR0p1htJBo5Jjb3Mz2lCXdJx81phIs9zOpPMNKINPI2WfC8PMfg9v5lZVYFGlGiqmIaq/HdfhjqKYSCJmKHekSVrBjHDsfedBDWsTe2FdG1dipSayrfmdVM+sHVdbm9q/9A39bP3MTNbQUNYk4bRQgfFa2JlIxH3YBnTkfYgkGLazh6EHYeheea/m5kdAzHInbUXUl+9siu2d1de0NJclmXtlb+Gel9qfJvetwvUjebOP+NUP/s6mPY0of4zoH9j4wVq/6i2P6A1YtoixIXcmH4rAOrWUA9q5jWhTPMeGPNw3IloRN3rgOq5ppO7Y8xIdKRej+frwUGXSZqcnjjynovoDgM6RK8RJXMk1/5Ju0XNF9PmzrkG5uvRTmyT+ZmPmdYtM6Y8Kcymn4OZ15/SIRjrYe0L5wERbTNeREB7Opsb8gIJ4Tp/RKw7sU2qYfN25//CtKY4tyL9MUG7ZO+RDP0PddQVaf8VrGtqb5FB2lLEMMQX1eP0Nfh3IdOUB96FkXMk6BdRIYQQQgghhBCLooWoEEIIIYQQQohFCS9EU0p1SukPUkp/+8n2n0kp/X5K6Vsppd9OKREDbiGEEEIIIYQQouR5fhH9S2b2zQ9t/zUz+/Wc8xfM7AMz+9JNnpgQQgghhBBCiJeTkFlRSuknzezfNLP/2sz+45RSMrNfNLO/8CTkq2b2V8zsN55Z0ZitOjxVylZE2JpRScvE8WCCMa78ehpF/tWKJFWGMtx+ckblJhPjwuHRF4Dqd51gOJLRnBD4U0LI0GiO4UbAxAFF0PXBV4xCbaZhx8Tew9YffFyDgQozQABzoqr1ym006kjEoCekG58wAiBeLaSSQBL7QMyUcdJ1EDMoKbcrYsqExk0YwwyOcJ+29jE1xpB6MIaZFdXUzQDOJ3B/mMkRgs9iDHQkrJcdB8+Pne/ZtjQw2r/iP1I5nJcuX+2FH0Daq9JJpDpuXUwFxgXpQNwWBswYjg5yLLE2mIDRGDRfIPcLYkYS48avgOkFHW9xvHc52ZnD3XTi9lDfr3F72qwIjYnMzCo0K2J9DesJ9BnXH4hpzljB+5xcQ4aYTMahXGMMMTRCfxKWoB7eUdQMK2Cqgm3HPStqmgMFzNAIuzUzYoH7HDIWjJgVsRiYRfrrZM9z+tgR3PlQoyvYpu3r2dvXdU+bCrlrjfzUE6g35Mo06x5GZoc3VA0amTHzG9evIu9c8o6A9p8jhkbMrBRjyHskw5wSjfLQzMjMG3hhHzLzZq58XMSXj68nwT2kZkVw46kxEb532bgzsz1FfxH9b83sP7Onj+5VM3uYc/7hLf+Omf3ErDMQQgghhBBCCPGpYnIhmlL6t8zsBznnb3y4mITSpXBK6csppbdSSm91/eXM0xRCCCGEEEII8bIQ+TT3583s304p/RtmtjGzu3b9C+n9lFLz5FfRnzSzt9nOOeevmNlXzMzu3vmJG/oOQAghhBBCCCHEJ5XJhWjO+S+b2V82M0sp/YKZ/ac5538vpfQ/mdmfN7PfMrMvmtnXJo+Wzaru2Xot/80/SdYMH24z3WGzA/1nS3Skm1LM0G99Pf2m3G9Ys+/aYb/AcjsiD/Q/PAc0OeQ37uevJQj9Rryk6qYT9+I36wPxXx42GEO+l8eyFdFCgSa0JnqpBJoNpot0x44k1o4kj3Y6inkaUXc+NCbQbuckvA4k6EZ9GclP7+phusjIs8JjRWKY/s0PTfPqQepA+8JjMd0tlp3cObiYiwel/nN/4V8B7WU5LtZ73yHbHjSFLsIs9WVfyw1m+iY7YdNhGtFI8m3UyEX0P2w8QynnTK3dJKSfuWMzjRCWkZgEZagHNTNrmgG2p/XYuM3AMWYg1zkMZUPoey+MHKCPoK7UjOj8yPkMMJ9gOlLXH8n8AnVgIQkfakYDekY2Qwu9v+e85Kk2EaqN6CJn6j2niNwv3kem63E6TXqsGVpOp4UlDyYQ4zwpuEBvkpBXRIDQXMbthNuRuQ0rnJ63ZNSiUw03zrV8CL5HuK8BvGugz45EY16Vr2HLnb8XFbbbhszhIrpzN7ki4zbc04rpSOE9y967xsoCfJQ8or9q18ZF/8iuNaO/+RHqEkIIIYQQQgjxKSHkmvtDcs6/Z2a/9+T//7GZ/ezNn5IQQgghhBBCiJeZj/KLqBBCCCGEEEII8dxoISqEEEIIIYQQYlGe69Pcj06edHVxWmpMim4+WXmEuvFr7nFVKn2brb8d/baM6U59PT2IkXvM/x4QZYfMi5xi3SxkYIQ5byOmBPO08M54qDo+e9vMn59L2G1mw6Y8ocxMo1owUGm94hrNiaqamBXN0OFHDI3QZGsuoSTxLqEzaf9onsGSNeNlkWO5skCy91APRp+AiDlEoG2jwRGrh8dM1+MMjAJGSVhWkzaJ9TKjmBUYzmxa75Kwu9sV28f73hjmcF62lXbnx8WqJ50UY47EpaEImPd3UEy27QwlzGYlK6eDMCYDD7iSuRA6bGO9kyHciCJiVgRjHhoTmZmtVuWzWpOYpgajt4DxiX+d+4vo0KyItP8ODIx60nYGcPdw5jJmlmswH6TmNhVsuxBnkJg6H+PaFw4NgdcBNdZxxjXB/Vw9zz934PUEYib2ocdBIyJyTWMzw2RoZsykEZEZMT1C87rpfaihUGQO5/aZNtyju92QoREyx+CInokzdJzekR4bY8h7xJWxGJyY4LunJ/MzKKvISgwNjcYjqQdjQoZGvuHi25w1gXrA9+7NtRP9IiqEEEIIIYQQYlG0EBVCCCGEEEIIsShaiAohhBBCCCGEWJSFNaJGE8I+C6rJwTIWA99pV53XvKR9qYupdl7TVG/KW1Tv/S3rzsqyCr7/7k786bnE3tOXwHHfhE8nTI7oR0Jf87NDQWLeGjShTBczwAfq/dZX7DSiK6KjW4GGiSVlR40o0dqh/oJpJiKaPUyMHkkIH7nv2HaY7qoH3VU3eKFT15VlA0kkP4L+YeyZwAZ3imRBn9g2szRHUzJX9+ROOSCSJho0uO1eR0r2wRiqEYUyFoPtADWjZmabbdkhL+/78exwXgpPmkv/zOsD7MfG9XoiGTjR7VsVeObPluHysoCOKFLP7ainYtBxGzSOqAc1M6uhHbREO4964pPWix5b0Ii2JOs5jotjYKw6juW4cyRj1b4r29uxJu9h6Ec9ZoQ3sxHOzyd7J8NX7WPwWZBDuXch+idQAm0y0gbdrGCOjjPKlCY6oGGN6J+ZVtdppOfqPwPjdGT8d+N9YC4R0n8G3mvutgcGNHYs3C8S83HC9J8BKb/bj2lEcfyK6EhRM0q9N2AexWJGGD9QM2oW04iOLczhyKovo74+IkK+8uulqp/ng6JfRIUQQgghhBBCLIoWokIIIYQQQgghFkULUSGEEEIIIYQQi6KFqBBCCCGEEEKIRVnWrCgly+3TtS/VO4PKmImOUw9iamaU0YMzwECMFSAhayZGGRWYE1V7n8i9PpRlVVcqiBM6mJhZ55JdT4uDqQzY7Uazp0/WPSspNTmh6gDb4HnBLnNYQ7VrH5PX5cHSyj9PNCJqiClHBWYCzKwIE7U3xBhm3ZRC7S0x91jXZcymLmMacuwKntVIHkwPhh9Hoj7f9WUb3HVe6b5ryv0OJOZ4JA4RwIguEhOJ3FlZIiYAIVcO5w0RaMixrN6T+0UMjVx7R3MN82YazBwFTWgGYpQxQntnt88ZZp35dnu8Xz7P9sKfT7MvY6gRC9zDhEYG7JGj2ULEvIgRMcOa0U5DMWg+MtfXA58xaTtYVjU+poG2g8ZEZmanq9LE6rQ9uhgcv1bErKiBshFcaND8w8ybFV31/h27qnE882PnLpUxONabmXUw5SEeIcRIh5mSgdkIGnOZN9eJmBdF2socAy0+K5jRUCNGb3j/2D2ucZuMi/jqYQZCgWfljYh8SMSsaMqIyIyY+MwwIrpNXyl8GJm0nohPDV4n62vO9Chwemh2dps4IyIS4wyNSGMeYe4ywHx/JPN/3AfNi8zMxg7qWZP1yQFimKERDKdoXmTmDYwiBm2kGmv2EUc2j34RFUIIIYQQQgixKFqICiGEEEIIIYRYFC1EhRBCCCGEEEIsysIaUbPcfujD/8HrPFD/yeuB76vJR+0uue9I6h1Bd0h0J9aVepr64DVVqSu/i05wXQk/0jazxLIzuyAUGPiQWPpYl97aRbhP3wNSU9S8XJdBNSjVJfrPYVNWPGzJVa1A29b6GNSE1kTbibrMtiHJ3RtM7u71UndX+2L7rDm4mC1oqrZ1WU9ED8E0VQf4oH83+PZ1CTqri8bf+PO6LLtgWh7UI5GE9Bk02qFkyBFCGtEZx5orQ3Gal2kdqdNPsQ4LOki8n9dlENP4iryexR9qteqfuW1mtrtb9onjPaIRvSqPVXfsb5plO60P0NfI+aFOfyTau9sVUQERjejUPhHZPut72HYiGtHaj2frdlrPjprQu+3exZxB2brybaelYuGnDORv36hxvyAaUdSNnlcbF4P6592RCKaAlPx7eIB+PiYy5sGzGahGFHWk5b+T2+d1o2R8i8jo/Pt85jt/Qv/J6oloOyMa0ZD+M6DBvzH9J8RE9J7uHU+ewxxNJoPpF33M9LFQv8jPDxsC8dqAZ+H8CQK6UjZHityLm9KaOh0p04hOxPREI4o+H6grNTPru7KTDExHuipjxg2J2YOO1A+vzpuB60indfFjO++3Tf0iKoQQQgghhBBiUbQQFUIIIYQQQgixKFqICiGEEEIIIYRYFC1EhRBCCCGEEEIsyqJmRblK1p09NRCoSfLT6gjGP8xkyAnLiaAfjIjM+zOY9ZAAvmNBUG/l1+7VhAK8JUnZ0ZQjk3p9Yuhp444xYHoRM1khInGovPYePs6sCK+BmxXBPisvfK9W5bNCYyIzswaMh1pi3LGCmBNi3HFvtSu2X11fuZgHq8ti+6z25h5ruBl1wOlkgAfRYaZhMzvksoyahkBieSbeR5H9QIyIUGjf98TcA9uuOxYz3ECHCxfimWnccWNEzCAmQhI1K4I62J8HMQE26egjOCH1ZHjHIYQZetWnZXs63vPPvLkqT7I++JPGa8V7UzFTJrwsZo6CY2fE7IOM0a4N3hZz2yheOxu2wRCkISZWaMhGzdfAiOg+jIFmZvebchw8IS8ANCuqoBGMpHHvIQv7WePdNM778iWxqcmYV2+L7TpgdLJPzNAI+k3EJJAYGo1gzoLmHpmY/SUoY/Mfd1msfQWadqivBcyKcD7mjIiYyVDEiAiPRWPQiMiHOCOigFmR28f8O5TGQFkFbQD/ndU712gH3+fM6BCNiEbyzscYNr0dBqzHvyOceZ4zt2HzMzQ0Iu8nuD8sZs49rWYP1CWjTT8HnGt15Dkc+wa2/T0+dmVM15H52aqMGdfkmYPJ0LBiRkRoaORCrN0ETFgJ+kVUCCGEEEIIIcSiaCEqhBBCCCGEEGJRtBAVQgghhBBCCLEoi2pExybZ/sHTb4jbK/8dcvsYdIiYBP26pmIrkfV0Bh0d+9AddUNMR5T7UouSUXtqZulYagETJLKuL/130y18kz22/oProcVv7FliaNCUMI3EdB55vx/T44GcsiIaUdSFoSZ02BKt4hae59rfY9SEtq3XCK1BC7VufMzddamFekD0n6+tL8rt9sLF3AFN6AZvjnm9FCZzZ9qBDtsteZ6o4WAa0Q6EOixmU5fnvKt9G0SNC0smjWU3JtuE+xOSziypGSVMSrPIM8dhh15nfubmkzLQedB7Ae1r5dtFA33rcOZfE8fL8jqanb+uqn+2CC135ATxOskbymnn2Z9TUdsWyBrP7nsgH71/teChAho+Jld1ujky/ldOI+rfl6iDv9MeXAxqQh+0ly7mQVOW4RhoZrZKZdup4F09kgHtCA/5imRcP6lOyuPM1MXP0t8dWSOETerNgFpm0FjVpOHi8O8v0+nFqe4cCXhHsMbt+hbVbD9bpxnSf7LnMkMjynSbXv9JqsH3HKkH+xbT16MvRQsxDdEzYhnTPEaIeD6gFpHpDvuhhm1fzwBlOCcxM+tBr+j2adi7EOY2ZJ5X19P9vEnT9xTvO9OIosY9MqZExhh8Vj3z54A53KH349CuL+dsu87P4Xabsmy/J2sNpyP17WJc4ZqFPPOtKwqhX0SFEEIIIYQQQiyKFqJCCCGEEEIIIRZFC1EhhBBCCCGEEIuihagQQgghhBBCiEVZ2KzI7OozT9e+7bkXu27AfKe98DHNvhQrp56Ig5tyjV25ZLpmVUIzFCJ0x4KBmSfBPgMI3zu/T3UEMfWBJO49YgJZcg2gO8Zk0mY+iT3D+W0QvTzmL6+8P4+7Yc6saEMMEcCcqFn5+9W2aETkY7ZoyrHyphyvbUrjoTfW5y7mM6vHxfaD2ht3nFa+buToMnuDINzmJf9FmOkRMldkX0HVkbbkCJjvsJhFzYki9USufcb5OG8bYvyAjjgpYHrEXHyw16Tk2yAag9UnxAzrbrnfkRjPVcdn37CGGavBuMOa9ohjecSIZUEiXkV+wJ1n1oImK8wMZV2Xz++k8S5zp3U5nt1rvInbg6YcO88qb1a0AQe7OtAhcJy8Gtcu5gTq3ZCXD5rDUfORGxswyrGczwrAnMsZVLGXLBoakYYMBwuZFTEChlmuzUVMtSI/bwSMuJwRUeD80Lzrej+MIcY1MJ9oSAwa56zq6TkI9j00CDQzW4HJVlP5emu4hoE8rBHG++Pox/bjULbb/eCXAHswwLkiBjiHrtyvY6ZHPZjbgFlRR95zaGhErxPmwWze0uLzZGZFKRJTluHzZDFocNSSDooxDDQr6sjz3A3wrHr/rM67Tbm98ePrBZTtN94wrkdDoxV55ifzXrz6RVQIIYQQQgghxKJoISqEEEIIIYQQYlG0EBVCCCGEEEIIsSiLakRza7Z//en33P2Wff9dro03LOntY0ym7r+pTz0k0l6TS63KYyUiWkr78pv+1LEM03B+TUD7N4L+gWSfr3qM8fcioV6EiFVcAmf2GTfsxxJpg0yHalMwoe2wLa9h3BINxxqSQK/8wdeovWh8zN11qVl6HfSgZmafWz8qtlEPamZ2vy71Uag9ioI6plUu63EaUjO7gnvaMdFvANSNMh1pJGYAHQdLXO00jbgd0ojOEDJHWVJHiszQlVJtLAikiJw9pk2Evz2SIcVpqmqixx7ulP2vu+e1KfUBNPiBbuTkUeQinPQahcxm/mbcomYUnxc+G6Ztc809pL0j7wjQsq3Is8Kx8g7RiN5rduV2vXMxOC6eVT7mNJV1R8ZOHOMuif5+M5ZjaW3zhJEj3Oie6KgxufxIks1jWWZjJzaEGTr0zAYD1I1STXngWBPHpsefo/8k7RbrSTQmT8ZgGWqmzcxq0I2iHtTMbAV9ZNv6+cVpe4Rt307vQBn2tS1OosxsDZOtlmhEI9pm7EeH0c95d0Op/bscvBbwsi/LLjqiKTyWZTuiI92DjvR4BI3hQPoeaE1ZjNORsvYPMB1pAxpfGoP6XTLp3YJ5Cj5P3Dbzc0P2fGs41kDGKnzmV6N/nud9qRF9eNy6mPc3J2XMxsc8Xpf17Nf+WN1u3pJSv4gKIYQQQgghhFgULUSFEEIIIYQQQizK5EI0pbRJKf0fKaX/K6X091NK/+WT8j+TUvr9lNK3Ukq/nVLyv9MKIYQQQgghhBBA5BfRg5n9Ys75p8zsp83sX08p/ZyZ/TUz+/Wc8xfM7AMz+9LtnaYQQgghhBBCiJeFSWVpzjmb2Q9dX9on/8tm9otm9heelH/VzP6Kmf3GM+uqsx1ffSr+HTbEBADMijB57XVZub1+5GNqMDCqiBlQhmOl1p9P1ZZi4NQRYySoO6OxyNobzmSXlJ0YEaHpBfFnwGNTQyM8PPP2wPzSXodvmEM8k9YzgK592MC9Wfv7h+ZEmDjazGwDZXdW/gTvr0rzjNdW3qzotbYse1D7mLt1aXq0ST4JNcKMh0Y0hgkYDoxwkzt2k4GB/D0Jk1t3ROh+BDODbvDXMKApxwyzosSMiCIGPXMMN27KmOimmGFQEqmH7ZKh79MY3O6IYURVtoOGmIfVm7If92e+7XS7sqzqpy8U872nkYzbMFaSPN/mmnvEMCgC3emjNzpaLb4imFkRlNXErGUFZhm4bWZ2AiYqd4kREZoTnVV7F3Oayro3YFbE/vKNZ3yWvaELmiBVAbOiiLkHSxKPZkUDNSKaNg/DInwfhFoNaxdwWZn0kXmNmx0/MPBgWcCsyLVlNidxRkTTZl117dtFC+ZE25V/n2/BDPGMzC/utmV7v9/6PnIXTL/uwETqrPZ95gTMudpExlt4DqxN4lxhn72BEJrZPOpPXMxjNLepvXHNCkx8zmtvaFRX5bHQBA/Ni8y8WREaE5mZjfuyXtzHzKyHuUxP1hoGp9yQsROpyCQcTY7QnAjHVjPfDtY4uTazDYx52AYYzNzyciwv9NHaP/P3NqfF9vc3d13MO+s7xfa7pJ7LnW8HEUIa0ZRSnVL6QzP7gZn9rpn9YzN7mHP+4R3/jpn9xI/Z98sppbdSSm8NF5ezTlIIIYQQQgghxMtDaCGacx5yzj9tZj9pZj9rZn+Ohf2Yfb+Sc34z5/xmfeeUhQghhBBCCCGE+BTxXK65OeeHZvZ7ZvZzZnY/pfTD39Z/0szevtlTE0IIIYQQQgjxMjIpQEspvW5mXc75YUppa2b/ql0bFf1dM/vzZvZbZvZFM/vaZF1Nts2rT7+hP2z9N+yHVVmGmlFWNjb+e3nUjTZXJElwj8JIcqwVaER7/4046jQRpwc1sxF0o+waaKJ2PHZAa+c+a2e5o0GWQD5rd5BcyDZsQctwUh682pBk0quyjGlE70Ay6ftrr894bV3qPT+zeuxjmrLsNHChTP+5Au0TJns389pS1G1eZn8D3xvK7/D3KIg2n/x4pHqR8lioBzUzO4KOArfNzHpMHk00G4a6ZC+O8tyUhulF04TO4YauAe8oakZpDNNOHuGZV75doBZrOPF9trtbVl5BvUzPjgMYjQGIFNBd6OzmFnk2Tngb2AfPJ6K9Y7cL7hfTEaGeiyVYR40S6tbMvE7zjGjnz0BntQE9bx0QRO8z8RFIpaZqIPXM0cjtGh+zb8t6DgPRsg0BLRuUZdQ4Mr19pJ1GdJtz2iQ9FmwTneaklpm0SYxJpA9j20Y9qJlZA/rPVePbzgY0oSetb7f3wF/i3sprOR+0pbTs1dZLze415TwA5wWoszYzO3UaUX8NNbxEmS8E6gNRG2hmdj6Wek+mXzypSu0fGy9amFQy7eRNwPSfYw/zf9I/se+h14WZ19myeZTBFA2v28xshPuD9dRkH9QBYxsw822FxdSBjo3z16vWt4uHq/KZf3Z95mK+t75XbP+TzX0X896+/Or1W5Nnd820E4rZ58zsqyml2q5/Qf2dnPPfTin9AzP7rZTSf2Vmf2Bmvxk8phBCCCGEEEKITzER1yWaGYEAACAASURBVNz/28x+hpT/sV3rRYUQQgghhBBCiDDPpREVQgghhBBCCCE+KpFPc2+MVdPbP/3ggx9tv7vxeWgetWXZsfU6uhFye44rkudrVa6xNw99THtZfoufUDN6XVpurv3a3UkgIK8X04hm0ISyfKmRXHh+J1+EkgOWLqnqQLNBYoZ1eQLDhsSARtTWZUWYM9TMbA2aDczpZWZ2BpqNByuvycQcofdqpsc4wrb/7h71UaiNMvPf5mMuKTOvFTjC82uN6GUx7x6rFxoCyx2FmtB9T/TYoK04Ej1G15VluZ/WiCbUPrE2GdEwvQz6z9sicG/m5xoFDQ6RUSeQmdQrP2AMd8q23B1AM0rzikJMR/RlUER1rpGxc4ZulGnwMYdk5PzmgJq567Jym40XWIZ6MzOvS8NxiMeQnKVwQhtIYt26pNaelmhEayjrsh+393Wp2bsc/dzhoi5fWrvaj4uXkBNx2/j3kdPXk7FzAE0jvg+cZtSMaDsDjYe27VsSngfaIOpIWf5b3Ie1bdSEoh7UzKyBGOYvgZpQ1IOamb0CZQ9WXv+J84vXmnMX82pTxtyvUCNK8oiCXpD1KxzOmCJzjxpRlud3LPsNy5HONKoItmWck5iZ9XA+qNNkus0RykamowbvFDYn6Q+wRiBeAz3sR/swNSAowfEV7x/z+TipppdeOAazeegJaPvbQH7ljvz+eAXj4GebRy7mDShjGukfbEpt6f82eTbX6BdRIYQQQgghhBCLooWoEEIIIYQQQohF0UJUCCGEEEIIIcSiaCEqhBBCCCGEEGJRFjUr2tad/fP33/7RNkuI+p22LHu3OXUxh6Y0E8gtSWjbgOiZmAGtQUO8uiQi8eO06H+sUHlfbhIvGRvBwGhs/PmB3wxP3A4wnbkzKxqIeQBc+kDuF5oT9Se+nuGkrKjegMEFMSvagsHA2cobUdxrwayICKVfacqyuyR5NCYSZqD5z+DcGMzOQCR+nzwbLNqDq8m7g29v56m8ySzJMp4fGhOZme2GsnHvSdLnXVfGHDofM/RoVkScMdBQAC+Lusn4IvERmWFglIm3QQJjh9yRsakqW3e18gNP2pZl/Rns0/mB0fl0kL6XyPiFoEHcTRkGzSLS1hc8P2ZohAZGFTG9QIM28oqwFi4EzYkamzYrqpIfTDtoqBvyokPjlU01bcTSEOe+NSSoX1XEuAn2q0k9FZj04H3PzFAoBdrttB+Jf/nMNC9y3Y+eM2yiWRG5BjQnQmMiM7MaynDbzGwFBkabhswvwGzqhJhPncH84l5DDI1gfoHGRGZmr9ePi+37YHx4RtrSSXp2nzEzq51Bob8XHTSMzejnUauImQ3MLw7E0OuQy7nCjhiDnTSluc6hL/c51OQ6q7KsrpmhEfQjZvoF77DxSAwdBzBPYmaNYEqG22Zm/ebZE3M23uLYtB7XLgaNNAfyksAxeUOMrjawW03O5whj3oPsja4e1GV7Z+3/nf6uK4ugX0SFEEIIIYQQQiyKFqJCCCGEEEIIIRZFC1EhhBBCCCGEEIuyrEa0Otq/cPqdH22zhKindfld+bZ9xcV8ry2Tpl42WxezB93ouPJr7mEN34h/4L/BXl2ATiGgGcVPuVEPakY0TORPAhnFFUyeAZKDmumnAqcMn/wb+WTderjNA9GIGmpC16DPWHl9xmlbPvM7jdc2oIbjrCbJmuGbeqYRwhiWYPp+VZ7PGfmmvoVnwxNMl/tdgeBnjzfdzPagtdhnr8+4GsoY1IOamV31ZcxV5zUcu2O5X3ckWusOGiZJHo2aQtSMhuRJ0ozePJGhiiUMxx2JyCsfQYNPdDpVXZYNJ6AZPfp6K9K+XAxqVtl1Om2bDwnpRrFuNgZDWcaYBfWfTFPuks+TmAH+Jj3e0N+oB7gZxAohROV0dD5mA/p/TAh/vV9ZhtrY62OhttPHoMaxZu0fy7ChsHvhBsvADWMNGS+dPU7UcjKtHeo/IxrRwD4JNLUsBu8f07Y1dXmhbU20w3U5D9jWfl5wAu/8O2R+gZ4TZ8SD4hR0yqgJPSP655OqfA9HdNRrci8OuTz2QPwwjtD+UVdtRvSLZB61xr5W+WM16dk6avY8mZ4ScUN7RGtN6skwt+mJ/8UlzG16oiM9gG60B40tG28jrOAeM38THM+Ydr6Ge7FmbRBiTokG+SzB3Jm0nVcrv6aLoF9EhRBCCCGEEEIsihaiQgghhBBCCCEWRQtRIYQQQgghhBCLooWoEEIIIYQQQohFWdSsaFN19oXV9360fb++cjEndSmIZcLydV2Kdt8mAvVHzUmxfWi8ocu4AlHxipg4gKHR6pwI5g8g+o8knAYTh0QEzQkS91ZETI2mBFQXjV4y/lbYsAZRtvd/sh7Micatv+/Nuixbt+Wz2rbMrAhE0K03CsAE08xMAIX3TNyNCYBH4hLVQdlABOBnkHR6nfxN7XK53ziWhggsQfElmBVdDBsfM5ROUpe9NyK6BHOiyyNJSg3mRD1J+mxgSuOMicycU5PzDqBOAaRM3D5zDIx883fjDJoXmZllGAuqVbk93PFtqcMxjpgp4UuLdE9/LuxPrngNc02F3M24ncadyQnioZgxRg8XjwnrWdmRxBwN6/Hn2EHnb2Fw6FljcufiYzowz6DHhnMeyEPHMRdNmsxi5iJoqkINUyYgHmDzhsXITqQfOSLmSSTGXUfg3nhDI1YvzH8qP7FCw5uaTL4a2K+tiIkVlKEJDCvjMXAs9+++vVXQBmsS4yBmMr4ef1Pd/SKNp6LWix+diBFRBDe9CIyLoYpIHxl35dtmR8z0+q4cdw5duc/h1C+zDmNZxsZkHL/YeBajnF/zfoTzWX/Orm2T9n9KDLwi6BdRIYQQQgghhBCLooWoEEIIIYQQQohF0UJUCCGEEEIIIcSiLKoRrS3bg+qpto99Y4zfp7MYTLDLkul+py7reVifuJiuKXV0Y0u+0waN6LD135G3oBttdqjtdLuEdHQoZcjkw3f8bDzX5Dt3eMqoBzUz6+H2dHf8sYZTSEJNNKLrTflsTtalLvK0LbfNzO6ARvRu4/WfmHCaJWJ2Gg6iRzqpymO9CttmZveq8v5syPfyyMXo6zkHHcf7Q6kYeW+44/Z5NJwW2x90vt0+PJYC3sdHoiM9lm17d/A60u5QXldmGlHUhBL5iNMUSv/5yWGmvgzl15nomnA31Iimje+f/Vm5Uxp8m0Q9Pcm37nT6Ee18CJY7fWosJ/u4ojmaJjMbR0jKPvrnsIdxZzf4seAKtOlX45rElGUseXo1QsNA7R3RtiEDudArePftiaZqn9tnbpt5LRa7XyM0DOYjgDpSplObYpaOzSwmZg7o33AsZ+fjXn1M54d6z6lzI8zR2JrF9IIRzW8E1BezdoExODSh1tnMa++GwPkyrXUHZUfyQJ0W3JhefFq/6PuRj8H7jn2NXSeWjazd4n60bQdiXOMJxBzIvQDd6KOh3D72fv6468ux6ar3Y9Vx+/zPoWv9sbr6cVlv9vPr+7BI2ZD3Oeqbmd75ZKa+WL+ICiGEEEIIIYRYFC1EhRBCCCGEEEIsihaiQgghhBBCCCEWRQtRIYQQQgghhBCLsqhZUWXZNoUw27tMjPX589dLhO6YxPif1F7c/V5dGsMcGm/QgAZGaF5kZtZvSpFze1luo3mRmRl47zhzDQrTZMMTHL3m2ZkTdac+pj/Nz9w2M8sn5T1crb0L03YFZkUtbDfErAjKTmofgwZVLbqlmE9mzZJbI8z0ooWE6jURYGPCX9YGB9jtcS7b1/vErOj73d1i+yExK3rcleZE50ffbi/2Zdnx4BvGiML7npjSOLOiGVnYZV70yQJz2JNulGEwIt3RMvydc6zAxK3xFedNWdbfIW0STC+aKx/jDOKYYVDAwyRiKhcynXE7zYhhRizQH7vBv58OYJZxScyKLoZyTHlcb13MCRiysTEY/7Q9gnlRGzCl6UjIJRionI/+Gh6O5Vh5PngTN7zOHalnB+ZOR2LEMqDxChkXXbsImQzNMCKabWgEMWT8R4NE1tZdP4bbdTNWQTEjIjSaMvMmOYfBT3v3MHFC8y4Wc1n5mM0I8xSYO1SVH/OGsZzv1IE7xgy99vBwzokRF/ab89H3ESxj9wLLsM+Yme3hPuN974kR3QDj10jGsxHmJDliVoTzmCiRvgbHGuFeXBITyCOUXR79/bvsyjncxQkZt9dlDDOZe9yUz/OyeeRirurLYvuMOACewHi/SjfVs/WLqBBCCCGEEEKIhdFCVAghhBBCCCHEomghKoQQQgghhBBiURbViI6WbE+SAH+YFpJk36188tXPwjfOI9FtomaPafhqKHuv9t/v70A32q38LcPj9yegESUapvoA214W6RJOM+kAShyJ/McG+Gx8OPH3AjWhqAc1M2s2kPR27b8j34ImdNuU26dEI7oFweyaaI82qaxnRZKpo2YJ29J1PWXZCY0pbzTTY7wPug6mx3hnLDWgf9q9Wmx/5/jA73Ms93nv4AW9D/elfuvxzus89vtSczCQRMwGiZgT0Qih/iGkZZYm9KUH2wFqRs3MUEKSj6D/YfWC3ix7ibT1qP8h7a3elzGV7+bzCGk78fwCO1GdH2wSLRRqqDqiu8Lk6eed1xF90JQ3mo3BTCuPdJAs/Sqhtn/6QQykLaH26THRtr3Xl2Pn+73X4F/0ZT1M23aEe9gRjWjnNKJEywZlqGdkz9OVRTT5TA86R4PMJF+orSPzN7yuyspnTGwYLBlqT5k+Fd7D5B6jzhD10GZmbVU+493g2/YltIsN0chtoE/g/JGBbfmQfb1r6BOrwEv2SJ7DVQZtYiY66qHs58ynAvvNo94Pwuc96A7JxBM1jnt4NofeN4weylAPamaWYd5C9Z+u3foQ54UQ0VVHgOaVSbvtoL097Py92INu9KLz9/jxtpwLPtz4Z/XGupxDPmr9nPL15nGx/aC+cDH366ti+5S8I9rQBNGjX0SFEEIIIYQQQiyKFqJCCCGEEEIIIRZFC1EhhBBCCCGEEIuihagQQgghhBBCiEVZ1KxosGTvf8hkoCYKYmZUgGzA3OYeJGM1M+taED1vp+tlhkbvQRL2Xe2NHoYGjrUutwdy7PoAAv8jMftAXweWTB00zmPrgzAf8bDxMXlbHqw+8ULk9aYU2p+svfHQSVuWnYA50bYmBkdQ1rps9PzZzKEDkf+e/C1mHEvBdUuazh6E7Y9IIuHv9feKbTQnevtw3+3zzh4MN/ZefP54DyYAOy9iH/bQtY/+OlM3bYwhcyJBny80FdY9M4xfCfoa9YaABpda3wBHMFLrmRsKcgiMr3O5pfaP5hmZ9MUR+iyafZh5k5ALYlb0sClNL9ZkDK7h2Qxk7NzDuzhiMofv/C77ackljK/ngzcrerc/K7c7b8TyqCuvkxk3XfXleLrriKER3Od+8PdiGCbMiZgRET5jarJyS0YsEU8t9j6A6xjRZIv0YTJLcSUJ3M5w28xsgGOj0ZSZN+tqKn+syPxigLlDR8ad/QiGQTBfPK3ApdJ8H2HzYuTIjg1mRWjwZebNih4Nfn7xfl+a2aAxkZnZ+8dyv8dHH3MJ5jpovnM8+n7eg2nPiMZEZt6IiJkVwSOm7d+ZfvmQmyDR84M+Q0zTro5gxHXwMecnYHp0snUxH4Ch0fsbb1b07qocK19rvFnRAyi7T9ZdpwnXBN91MQz9IiqEEEIIIYQQYlEmF6IppX8qpfR3U0rfTCn9/ZTSX3pS/iCl9LsppW89+e8rt3+6QgghhBBCCCE+6UR+Ee3N7D/JOf85M/s5M/sPUkr/nJn9mpl9Pef8BTP7+pNtIYQQQgghhBDimUxqRHPO37UnH/rmnM9TSt80s58ws182s194EvZVM/s9M/vVZ9V1zI39affqj7ZZ0uAqlDS7PG2WWPgEvsV/pblyMYf1tEQ2Qd0Pib7gsi6/he/bst5h5b/nH7vybwBOr2dEw8Q0JaBhZXKpcQXnjNtmVm0gqfKaaDlXZdmm8TqiKU3oimiPMMk5S3qOydQrIl5EbUUkAftINMl7uIkPSULz94byO3vUg5qZffv4WrGNmtC3r/w+7+7KelEPama2uyrLetSDmjlNaOqndQrSg4owgXaQoH1lJ1wjycoTtFuiL0swfqEmzYzoRtnQCbr8G9OMBsDToRpbLCPjP+oOe6KpOnSgESU+B0w3h6AmDvVw13WXWrE1vOPZ2D7maY3oFRgdMI3oY9CyMW0bakKZXvYKtG2H3p/PEcoGohEdIZF9Rs1oQDsW0ZEuqX9jOk2sO4OW0mljzWubmRGDa/+3CLbBPvvnif4Sh9G3i3No/2f1vtjG/mBGNKLkRYz6VKbPPoyoEfXeEdhvLgbf/s877Ec+BjWh50cfcwFzlwNoQjuiEcV5seG2mZ+3sH7kxk4f4vcJ6KjnQAd3CGH9HPTOA7kX5wcYk/d+TH60LZ/VeydeI/qDTakRfXXt9Z+vr0qN6IPGx9yB9m72/7oYxnNpRFNKnzeznzGz3zezN54sUn+4WP3M89QlhBBCCCGEEOLTSXghmlK6Y2b/s5n9Rznnx8+x35dTSm+llN46f9//GiaEEEIIIYQQ4tNFaCGaUmrtehH613PO/8uT4u+nlD735N8/Z2Y/YPvmnL+Sc34z5/zm2YNFs8UIIYQQQgghhHgBibjmJjP7TTP7Zs75v/nQP/0tM/vik///RTP72s2fnhBCCCGEEEKIl43IT5Q/b2b/vpn9PymlP3xS9p+b2V81s99JKX3JzL5tZr8yVdF+bO2P9p/70TYKuc1i5gZoQsOE297QyKuV79SlodGhJQl2N9M/GqOh0a4ut7uGpG8G85hQ4t6IeL/2QQmOX638PV2tys+mNytiVtSWZactJq8129RlPWhWxBKl4zNmCZ3Z80MwMTomeL6OqSCGGANADCaBNjN7p79bbH/7+KqLeXtfmhN9f18mXH9v5+t9vCuF5budNxwY0Jzo6NsOml+FBP0MmROJCDPMi4woNbzHCmnbaGBEzNec+Ujy9dRQVB+njWEot+Rx4Q03iKEL9Gs0yDEz6/rS0GLX+fdclbyxD9KDaduu9ePrti7HNBzvIwZyaIpkZrYbynHwcvDj4g6Swl/1JKYvY3advwY0Jzr0/ny6rizrSQy+0zMaGoXMinyIMye6KZM5ZtaCRiusHtjN9fNAux3IvRjBwCiP/kJzezMOYwP0m27wz3MPbee88X3m1Jk1ltuR+U/FzG0AHN/MvHkSmheZ+T7C+hH2G2ZEhP3m8uDrORzA0Av6zNgRZ0007SRtx81l2O1yLxJSz1JzG3LskC8SNG06Be7RAMqP/4/AwOiSzCkfbrfF9rvbOy7m++tyzssMjc5av6aLEHHN/d/tx79qf2nWUYUQQgghhBBCfGp5LtdcIYQQQgghhBDio6KFqBBCCCGEEEKIRVnUxnY/tvZHF2/8aBu/pzczu9vsim32Tb3TnQT0g0x3glrAltRzAufYr8h37UBdoWbU13s8wvfyrf+bAEsEPUWq/IfvFSQrb4muYt2CtpNpRJuybMWeDWhEG6f/jAhaPJjQeaQJp6ebM+pG2T6oCX2nP3Mx3zvcK7a/f7jrYt7dl4mDH+7L7/DPd157sYfv98c901GU1576mToKRHpQcZNMtCeexBuqoNJm6PsNGVPWZUUjEwQl6Fvkz7KQa56fs9sJs5X7EHc2EZ0TA84HtXdmZj1oFQ+V1465asmNR90c02CuYPxfVah/Y3re8vx6Mrb3oOE7jn7cPsL5HYbpmD3Ryx5Rd0W0bANoQpnHQ8YyHKdZW4LbQ9ubF1KTmOl2GtLIQT20WqwHKyYyTtS5ZqJtxrbct0RHOk5rTYcG2hfTUYNgvCMx2J5Qb2xmdtGU73ScIzWVb/8N9AnWRxA2/8F+g23dzGwPGlHWR65A/7k/Eh11h9pEX88A85TcYX8gAy62/4i3xVz958c433HnF5nqM60pvmpIu8X73B2IjhT0vExH+sEGdKSbUxdzZ3VwZRH0i6gQQgghhBBCiEXRQlQIIYQQQgghxKJoISqEEEIIIYQQYlG0EBVCCCGEEEIIsSiLmhUd+sb+0cPXfrR9uvJmRadtWXan9eLXbT1tmsOMh5ARFMLdOG1E1FReeY8mPpgcmZFArTxgsusfUzZVT0XMimowS2rrabOiFYnB/VhMdQMKcGYshWWXIzH6ydMmHHtI8nw++qTUH3SlCPudozcreu9QGhq9v/fC7cf78hyv9qUA/Lj355sPcO2Y4Nm8OdFsQwshliTQBqk5xWQ1ZJxEA6MVMcnBeitfTwXGDlXvjz71qiG+It6cgprAoOEYuYHOrMgfbKzL/XpyDWblWJSJMQaavDCzFnxHoBFLBHwvs2Ozd+wA54ymQ2ZmPdyfY+/fNT2UsfcwmhM5YyKzSXOikBELu303ZUQUAc1QWL14OhGDI5g60GYSMOIawQCHmT4ObVl53xCjn6Z85t3g5zYHMBpq6un238I+NTErqnAOR0Y47BPMTAz7BDNlcoZexKyrg/bfE7MuLHNGRGbz2r8blBc0IrqpPhMyHrqZet29YJ0N7ykZ85yhETHJ7GG+erXyc/AP1t7kNIJ+ERVCCCGEEEIIsShaiAohhBBCCCGEWBQtRIUQQgghhBBCLMqiGtF+qOz9h3d+tP249drO9aos2678N8ebpodtH4P6RaYjxW/zGfgtfh/QkaJOALUrjCMmVzev98TkzWYxjSheZ810pFjPjHtjxrQM8O050X9ejaV2kmmEcD+W9LmDJOeH7Jv3RV9+1/6wO3Exj7pSN/rouHUx54eynou9/17+AN/U96j/xG3z+k8jOgqvC3Ah0oSKF5+b0ozS9g9/Y21IEOhGmZYTh/t88OdTOS0UBLBLiOiIEHadcKxM3hGorRts+h2WydiJmrNj5evBdwtq4vB9xY9N3iuoO2Qa1mFaI+f0n0TbiZpQpv90ekVsA2ZeE4fPJqCLvDU93E0ycfw5ulIz36+pjhSeQ0hH2hD9G2jKK9SYm/fawG0zP//C9s/mVZE+gbD2j/NMpm2epX+eof80I2P3HP3nLWmdb5Xb0qdG+lEA2tzQi4T500C76JmOtJ23pNQvokIIIYQQQgghFkULUSGEEEIIIYQQi6KFqBBCCCGEEEKIRdFCVAghhBBCCCHEoixqVmRDsuH8qYHLQETjxxaSprbeBKYFQ6O28cmHV1C2arxZESYbZqLxOaY9LNk2gsdiiY7xyCkxQf/zq5VHcklo7NCQa+ggGfI++YTOCAroD6Nvcm1VPiuW0BlhhkaHoax7N/jzu+pLY6Tzzrevy2MZc3X09RwOZVl38NeVj3APQeydUCBuRgwufMjHbk4hxG0xx8CI7BPqIthliUFJhnE618S4BvoxGo7RPox1sFdGxMQEx38yuGcwnhjZCYGJCXuvYNlY+ZOu8J0aMEaKgO9YZtw3wjtrYMY1EIPGLGbMiIg8nCkjFguYE0XMWhgv+vh/Q+fn7g6b6+A9ZX0N+mPuSR+BtjzUPgbLEjErSmBWlKDpzDEmYlB/NjRuosZlcELMDO4m2raZe163ZkTEeNH7yE3hFgk3Uw81CcRlVkVi2Jw2gH4RFUIIIYQQQgixKFqICiGEEEIIIYRYFC1EhRBCCCGEEEIsyrIa0ZwsHT609iXfE2Py3J58q9835WkfWq8RrUHvg9tmJEEx0WliGSbsngtKeZgmx+V8DtQbSXRM9QWowSH1dKCvQU2mmdmuLrWTqP9syD2eowk9Dl571EH2+UPvzw/L9p2POR7Lsr7zxxqPUEbackJtETRTp7Mw8w/n06J1EIIR0YyyfoSWAEzziINwS4RO+KdaEpNBK5Mb0EYxvU1ANzrrz8T0OqGAaScDB8+oIyKXVRHdaLkP0ecFfA5QE4rnch1THttpPc1r5FgMagpRt29Gnqk0cs/HLZ0fHQsQFoMPh+jfMsz9UFdqRi4L54tzNXyTByJlAU1taA7C2v9tteU5mscXva0vydx7MaNdUu+DSP8j6BdRIYQQQgghhBCLooWoEEIIIYQQQohF0UJUCCGEEEIIIcSiLKsRNfiumH1PjGVEk4l5oEbM12hmI2hLO6IRraAsET0q5kWryPlgWSRXFOprmOYFiWhpqNYUzmccieYR9A7d4E/okMrmwjW1z74XkbysDMzNOpC2g7lQ+95fJ+o9B5IjbkRNKMuNNER0YDM0Qp8SvcMNpVO7MWak4xUfFzN0o2x8xTaY2d9l8Z1A3hHWPDuG6hAjWpqb0kvhdQaOzXJNp1xjgd8PdfCBjo7vLHoJ+DwDcwd63522c6b+c2psN7uZsfwFGycX5bZ0pLTeQO5MiKHvDKycCaknDh1ibnub0i1H67mJfT7OekXJx3yf9YuoEEIIIYQQQohF0UJUCCGEEEIIIcSiaCEqhBBCCCGEEGJRtBAVQgghhBBCCLEoi5sVFTBDBDA7iJgJYKJhM3MJiTMmqTZv0MOMKCD/taXaq9gTGvTg8p4owvFsIqYON8YMM6Xrsuffb5ZZBU1WjmYVxGQoYFaR0ZyItAtnRBEwvaCXGUla/wnjxprpDGOF28S105mHlunRx0DEvIjtFujDGfsw69P43sChCc2MzPwgR01D/v/27jdWtqus4/jvmTmnFa4aSoAGoUo1haTxBZCbYkIgJFhsieGqiaaN0UZJKgkYiW8K+kJCYlJRjJoYTQ2NmEABo4TGoFLxD2+s9rY28qfUllrkwk0rkoi9/86ZmccXZy4586znnL3uvvus+XO/n6S53eusvfeaWXutmTUzz7P73GW8Jutd903si8etssnZa0Rx9iIrX1fj8kRERVmWrGjVEhGRaKW9vs95vFRq5pSapEd9zl2j5eswcMT4RhQAAAAA0BQLUQAAAABAUyxEAQAAAABNtY0RdV36b9Ir4jMsi3mJsR9ZnF+MLU2W5TH+1IsA0CRGteK4McAgARvcfgAAEztJREFUve9xTbxPn5CEoQL9+t5gPVaJ/ZfGag0TIxSvizT+s9XNytdA1aUS68SbZmdxWMUY7lmnQjE9ZOM8XsxZnSKwuzv2uwZxpUegT4xXRexkNqf4rGP+T3IPFBdK+pHwEU0yyXVbxH9mV3KMI00Dbw+/mLP4/+I5rZi3s/MQ/4neltmfXEvYEH3fo/GNKAAAAACgKRaiAAAAAICmOheiZnavmT1rZl/YV/ZCM3vAzJ6Y/3vN0TYTAAAAALApar4R/VNJt4Sy90j6rLvfIOmz820AAAAAADp1Jity98+Z2StC8QlJb5r//4cl/aOkuwZs16WpSXRSkVghu4l3sV+aeCgcJyarqEhG4lmUb5EcJTv3pUcH906O0icQueZkFYkoOveRZDHJRUVijCs5WcUQiYgkyaaL26Pp4X+XJJtYd50s2UgPHsdsMoZnYSb0JMGMj8N2NqmEYxdzQeKochWRBGmfnuM1zilZsp3iOh3H15WaZEVJnR6vI6m4X8WFkSYVKsoqkjvFc6WJy7rrFHN7xXGq5vYNmMcBYJ31jRG91t1PS9L835cM1yQAAAAAwCY78mRFZnanmZ00s5PTM2eO+nQAAAAAgBXXdyH6jJm9VJLm/z57UEV3v8fdj7v78fGxYz1PBwAAAADYFJ0xoge4X9Idku6e//upoRoU4zoGi3PqG0ca42CS2JTYxuI4aWxn3E5ulF4TxJc3uvv8QxgoltLiE9g3tqdPjFBmA+OG6uKlKuI/J+VhRjuL+412F/8+3knaE46THdemiw2sGQ5FPKgkHy22L8aDStJsO26Xz0Ws41tlg4pjh3PHONN56eLmQOM1e76IGz1E1VyVFR4eR5pO0UUscfdxq66LqteMpKxqXqxJdnD4dhHrme2T1Cke1hU6jwPApqm5fct9kv5Z0qvM7JSZvV17C9CbzewJSTfPtwEAAAAA6FSTNff2A/705oHbAgAAAAC4Ahx5siIAAAAAAPZjIQoAAAAAaKpvsqIjs9RkGn1veh73q0ggVPM4a/IQ9UpsUrPPUIkeBkqCUZODY5kJLJaZGKbvc2PTkGQoS0R0YbHO+EJZZ3w+bF9YPFlMXiRJ41AWExNJks0O305luVBGi8eebZWVpiER0fTqJFnR1d11pleFfbYXz53n2ArJbtLENcMkNDqyZHCbqsd8UfV6EK/lrE5Nn1ckveul71zakQCNBHJtVL0mrBDmIeDKxTeiAAAAAICmWIgCAAAAAJpiIQoAAAAAaGrlYkSHim04spiDPvEsFeE/qYHifYZ6Lo4s7qTPcVcsBqZljEtVP4Sbwo+mZZUY/7l1rqyzdXZxe3y+PPl4Jxx3N8SIZueeLNaxpI7NLr1OKvRNFiMay6ZXlXUm37VYNnleWWf0vMXtGEc6TeJcYxxpdm37OJ4rC/oti9DAAHNRPqbt0M1aVfkIWs3BKzZvr7rBciOk+y3xjUG8tHs+BmJLcZRWPdZ6U65/vhEFAAAAADTFQhQAAAAA0BQLUQAAAABAUyxEAQAAAABNrVyyok0Jvl2w5IDnlQq4XqW2VMqev1bXaU3f2bRsjE0Wt7fOlnViIqKts0kioguL26NJUaVIPBSTE8W/S2VCI8vqTLvrFAmNvKzjMelX0nezkAxodlX5Gd3WhcWy3Z0kodHuYtnu8xe3LUlWNJ3Fc5ePodhtVJ7bR2G/nklqNnIOXqah5rzsOKuUiGggK5+wsKficVUlIkrm9l7HqajTW4+kWqFOVV8lF0afLl616wLDGyzJV7hYBjtuj2swu26t6g1iv2O3xDeiAAAAAICmWIgCAAAAAJpiIQoAAAAAaGrlYkSjTY0XqbKG8ZSbqOW1UxP/E2NCRztlnRgTun0mqXMuxHbuZucK27MkTieGJobYztFOEnu6Mwt1yuDJ0c7iyUe7SYDlLCkrGrj4XHgSXznaWvxMzi+Un9GNdkZhe1zWmSzWic/f7iy5mIo+T+qEuFFPZ+7wOLPrtuis7iprOXdeKTbwNWIdrrdesWI18WY183/XPgeVxeM0unbyeShsZtNiLEsqlXW6H1Tfy2sdrssrQVWMdM1YC28d0u6NdXqOtU41cZzZ14bxvU3FWKuKNa0ZjwPiG1EAAAAAQFMsRAEAAAAATbEQBQAAAAA0xUIUAAAAANDUUpMVXdGJiHDFqwl8t0l5cY8vVCQiCmXjC0mSoWlRVKoYWzE50TgkJxqfL08Uy8bnJ+VxQ5ntlnX6JCvSVplkyGOyou2yjk0Wp8vRJHlOZ+OwPTp0W5KsIrHCJHTELMuQEGfz5GNGLzq0JhsKMIy+r/k1r/FDJdnqk4jIqpKQhX0qjpsOz6pkLR37SFVPUJ/+iodNzxIOnCZQCfNXXZ2sUvdx+iRxy/Be9PJUJWuMYy15C1AmUMyO03Hc5Nh9E4x16plkKL7Gz8bJyeMYKd/aFOMmS4xUk9Cob+ImvhEFAAAAADTFQhQAAAAA0BQLUQAAAABAU0uNER0Kv93HOqiKfwgxoVvnywt367nF7e0z5YFGu93nKmIFsliLUDZKYi1GIXRztBtiRC+UB44xoaNzscGSnbuwWJDFiE5CmScPdBweaBIjqu3FqdCu2i7bE2JhbVo+Lovn95opNn4e2D1ZTZMJbRo7OTt1jBepCPSomTqZXzdL9po6RB8f5XXSJ440j6/sjtkeIpaz93FDLFuco3ufq0a2T01MaLFPiEmriZHLYt5HYa5K6xx+XEnSqKY9w8SRRus4d/Z5z90n/jO7tmO8Zxr/Ob304+TtOXw7269qjilOlBw2llVc26NReaD4Pi+LEY2xpdnbliKONDlOX3wjCgAAAABoioUoAAAAAKApFqIAAAAAgKZYiAIAAAAAmmqerCgN9l2oMMx51jEAHBsuBK2PJuVFOj63WLb9XFFFW2cXDxSTBUllEHt6g+I+N0ZPxu9oEhJGTBYr2aw8cKyjSZJxYBrKdsuERl6TrCjut1VOe0XioaTN8dij7FzBVrzBepoEo/tm0kWigDS5wWLhLOvQ+NCzcxXZR3repRpra5mvn0MlH6xJ0JPexL4mqUrXPkrmyiLxSXnuqkQsFQlUirKhhnBNUqFYpyIRS9qdXceVyiRDSQKVmNAorROfnyNMaNS1y7Lfux7Z+IuJiLLEhzXX/6T7ODVJFocaa+W4HmaweUw8lI2jqkREoU6y6rOxddaZbYVxNGBCO74RBQAAAAA0xUIUAAAAANAUC1EAAAAAQFNtY0Q93Gg2+83z6NJ/Y59Ztd/dY7PVxCPFmNDx2fKijDGhW+eS+MoQyzDLbj48jgE2SfumIbYzqdJLRSxNbJ8lN2LWKHxONk4CIGJspyeBHsU+WXBKONc0+YxuN7Q5xn9KGhU3fV48zlY658UY0fLcZdxVdjf1zoIybjR7BSgune47t2fXDnMu+hgq/jM7UE3sZE38Z13sfJgvJvHvyT4hnD3uI2VxdMlrxFAxonEuyGLKO+I0832669SdO+ySTO3xtcaTvpqNwxOUvNR0tW+vrOO1L7twG4bkF7G5PeNBa/JLLLzXV9k32fVf7JPVifGf6XEq6sTxmI2jUCcd5/Gai3NDRS6JTM0YKeI/sxjR8KYjj/8M29tlHYvHSeoU46gS34gCAAAAAJq6rIWomd1iZo+b2ZNm9p6hGgUAAAAA2Fy9F6JmNpb0h5JulXSjpNvN7MahGgYAAAAA2EyX843oTZKedPen3H1H0scknRimWQAAAACATXU5yYpeJulr+7ZPSXrdYTuYFoN98xsCx8Lu4G6SYmAVxcD70c7i37fOl/uMQ1kWHF8TfB7HRHZD56EUySnieIyJk1Qm8fHtLBHR4gPLgv6L2WIy0GSQ3JQ63qjaY6IkSZotlo0mi9s+KT/7G+0u1hnvlI9hvL1YNtsu2zeK10XFTdlnSbaK2J9ZQos+CWWYp9HSUSZ9KROmJImRQuKhcdiOrwdSmaxotJuM84oEKkMlK6pJmOIhQUmcP2bZ/B9es2oSEaVvBeMc0/OrlZEq5sWa+asrOVHFMVrOk0Ody2bdicFiAqF0n6JOea4yWVdSJyYiqhlHPRODFXWKsZe8l6h5baxI1hWTFcX3hlLZ5lnynPa5EJLu06jnBXU534imiRKLSmZ3mtlJMzs5PXPmMk4HAAAAANgEl7MQPSXpun3bL5f0jVjJ3e9x9+Pufnx87NhlnA4AAAAAsAkuZyH6kKQbzOx6M7tK0m2S7h+mWQAAAACATWXe82arkmRmb5X0e9q7/e+97v6bh9U/fvy4nzx5svf5AAAAAACry8wedvfjXfUuJ1mR3P3Tkj59OccAAAAAAFxZLuenuQAAAAAAXDIWogAAAACApliIAgAAAACaYiEKAAAAAGiKhSgAAAAAoCkWogAAAACApliIAgAAAACaYiEKAAAAAGiKhSgAAAAAoCkWogAAAACApliIAgAAAACaYiEKAAAAAGiKhSgAAAAAoCkWogAAAACApliIAgAAAACaYiEKAAAAAGiKhSgAAAAAoCkWogAAAACApliIAgAAAACaYiEKAAAAAGiKhSgAAAAAoCkWogAAAACApliIAgAAAACaYiEKAAAAAGiKhSgAAAAAoCkWogAAAACApliIAgAAAACaMndvdzKz/5b0VUkvkvTNZifG0Oi/9UXfrTf6b33Rd+uN/ltv9N/6ou/W0w+4+4u7KjVdiH7npGYn3f148xNjEPTf+qLv1hv9t77ou/VG/603+m990XebjZ/mAgAAAACaYiEKAAAAAGhqWQvRe5Z0XgyD/ltf9N16o//WF3233ui/9Ub/rS/6boMtJUYUAAAAAHDl4qe5AAAAAICmmi9EzewWM3vczJ40s/e0Pj/qmdl1ZvYPZvaYmX3RzH5lXv4+M/u6mT06/++ty24rcmb2tJl9ft5PJ+dlLzSzB8zsifm/1yy7nVhkZq/aN74eNbNvm9m7GXury8zuNbNnzewL+8rSsWZ7/mD+OvjvZvba5bUc0oH999tm9uV5H33SzF4wL3+FmZ3bNw7/eHktxwF9d+BcaWbvnY+9x83sx5bTalx0QP99fF/fPW1mj87LGXsbpvV9RMeS/kPSzZJOSXpI0u3u/qVmjUA1M3uppJe6+yNm9j2SHpb0E5J+RtJz7v47S20gOpnZ05KOu/s395V9QNK33P3u+YdB17j7XctqIw43nze/Lul1kn5BjL2VZGZvlPScpD9z9x+el6Vjbf6m+JclvVV7/fr77v66ZbUdB/bfWyT9vbtPzOy3JGnef6+Q9FcX62G5Dui79ymZK83sRkn3SbpJ0vdJ+jtJr3T3adNG4zuy/gt//6Ck/3X39zP2Nk/rb0RvkvSkuz/l7juSPibpROM2oJK7n3b3R+b//3+SHpP0suW2CgM4IenD8///sPY+XMDqerOkr7j7V5fdEBzM3T8n6Vuh+KCxdkJ7b7rc3R+U9IL5B39Ykqz/3P0z7j6Zbz4o6eXNG4ZOB4y9g5yQ9DF3v+Du/ynpSe29N8WSHNZ/Zmba+/LjvqaNQjOtF6Ivk/S1fdunxMJmLcw/hXqNpH+ZF71r/nOle/lp50pzSZ8xs4fN7M552bXuflra+7BB0kuW1jrUuE2LL8KMvfVx0FjjtXD9/KKkv963fb2Z/ZuZ/ZOZvWFZjcKhsrmSsbde3iDpGXd/Yl8ZY2+DtF6IWlJG2t4VZ2bfLekvJL3b3b8t6Y8k/ZCkV0s6LemDS2weDvd6d3+tpFslvXP+ExisCTO7StLbJP35vIixtxl4LVwjZvbrkiaSPjIvOi3p+939NZJ+VdJHzex7l9U+pA6aKxl76+V2LX4Qy9jbMK0XoqckXbdv++WSvtG4DbgEZratvUXoR9z9LyXJ3Z9x96m7zyT9ifhZy8py92/M/31W0ie111fPXPwZ4PzfZ5fXQnS4VdIj7v6MxNhbQweNNV4L14SZ3SHpxyX9rM+Tasx/1vk/8/9/WNJXJL1yea1EdMhcydhbE2a2JemnJH38Yhljb/O0Xog+JOkGM7t+/kn/bZLub9wGVJr/Nv9Dkh5z99/dV74/luknJX0h7ovlM7Nj8yRTMrNjkt6ivb66X9Id82p3SPrUclqICgufBjP21s5BY+1+ST8/z577I9pLxHF6GQ3EwczsFkl3SXqbu5/dV/7ieRIxmdkPSrpB0lPLaSUyh8yV90u6zcyuNrPrtdd3/9q6fajyo5K+7O6nLhYw9jbPVsuTzTPPvUvS30oaS7rX3b/Ysg24JK+X9HOSPn8xdbakX5N0u5m9Wns/Z3la0i8tp3nocK2kT+59nqAtSR91978xs4ckfcLM3i7pvyT99BLbiAOY2fO1l2F8//j6AGNvNZnZfZLeJOlFZnZK0m9Iulv5WPu09jLmPinprPayIWOJDui/90q6WtID83n0QXd/h6Q3Snq/mU0kTSW9w91rk+VgYAf03ZuyudLdv2hmn5D0Je393PqdZMxdrqz/3P1DKvMjSIy9jdP09i0AAAAAALT+aS4AAAAA4ArHQhQAAAAA0BQLUQAAAABAUyxEAQAAAABNsRAFAAAAADTFQhQAAAAA0BQLUQAAAABAUyxEAQAAAABN/T+2Rc+PI/JoiQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scalar_field(vorticity_2d(shear_flow_scenario.velocity[:, :]));"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "###  Variations to experiment with:\n",
+    "- make an animation of the vorticity\n",
+    "- increase the ``relaxation_rate``. What is the maximum relaxation rate you can get before the simulation gets unstable?\n",
+    "- use an entropic method to get to higher relaxation rates:\n",
+    "\n",
+    "```\n",
+    "entropic_shear_flow_scenario = create_fully_periodic_flow(initial_velocity=init_vel, method='trt-kbc-n4',  \n",
+    "                                                          entropic=True, compressible=True)\n",
+    "entropic_shear_flow_scenario.kernel_params['omega_0'] = 1.999\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Channel\n",
+    "\n",
+    "In the last part of this tutorial you learn how to modify the boundary handling of scenarios.\n",
+    "Therefor we set up a channel flow and place some objects into it.\n",
+    "\n",
+    "The channel will be driven by a constant body force e.g. gravity which acts in x direction. Along the flow direction periodic boundary conditions are used whereas the walls are modeled with a *noslip* boundary condition."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "channel_scenario = create_channel(domain_size=(300,100), force=1e-7, initial_velocity=(0.025,0),\n",
+    "                                  relaxation_rate=1.97, optimization={'target': 'gpu'})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As in the last scenario, we specify an initial velocity here. Instead of passing a velocity value for every cell we specify here a constant for the complete domain."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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jjz+83D179mBAQADntmzZEt966y3BPP32228F8/T06dNeGbljxw5enrZp0wbfeecdPHfunJe7ZcsWrzx977338MKFC175tH79el6edujQAd9//33BueyqVau88nTRokV45coVL3fp0qU899FHHxXN06SkJK+57Icffog3b970cufMmcPL08ceeww/+ugjvHXrFnoyffp0Xp726tULV65ciWlpaV7uyy+/zMvTJ554AlevXo3p6ele7t8FAFxABc+GSvqI/p8hPz8fHA4H9/Xdu3fhwoULEBMTAw0bNgSNRsN9Ly8vD5xOJ/d1WloaXLx4EdRqNTRs2BBiYmK47+Xk5IDb7ea+vn37NsTExHCvGxUVxX1Pp9Pxttxv3boFarUaYmJioEGDBhAREcF9Lzs7m/f+b968CTExMaBWq6FBgwa8FTNP98aNG9x7iI+P5+1A0C4iwrVr13guvQom5JL3GxcXx1vZol232w1Xrlzh3m9cXBxvBYp2XS4X55LXpVeVhFy1Wg1qtdprVYl2nU4nXLp0iXtdz1V62nU4HHDp0iXudWNjY3mr6bRrt9shJSWF+7Op1WreCjntVlRUQEpKCufFxMTwVrJp12azwcWLFyEmJgZiY2MhOjqat+JMu+Xl5Ty3b9++nIuIoNPpONdqtXL/29VoNPDEE09wq7JutxtycnI412Kx8NxevXpxrtPphLy8PM4tKSnh/v3Ur18funfvzrkOhwMKCgo412w2c65Wq4Vu3brxfkdFRUXc18XFxdx7iIuLg86dO/N+R3q9nvvaYDBwrxsfHw8dOnTg/bmNRiP3dVFREfe68fHx0K5dO+57ZWVlUFxczH1dUFDAe92EhATue6WlpWA2m7mv8/LyuNdt0KABtGrVivc7Ki0t5b7OycnhZU7z5s15f26LxcJ9rdPpuL/jBg0aQNOmTbnvGY1GsFqt3NdZWVm8fGrcuDH3Pb1eDzabjfs6MzOT5zZo0ID7XmFhIdjtdu7re/fu8d5vXFwc9738/HyorKzkvr579y73fuXy9M6dO7z3oFarue/l5uaCy+XivvbM0+joaN7vSChPyd9FZGSkqEvylPx+pfL05s2bvNcVy1OAP3c26NdVkqfkf+v0roJnnl69epWXp/ROgZBLXrd+/fq8FX3PPL18+TL3fuvXry+Zp5cvX+ZyTC5P6YyMjY3l7WTSbmVlJeeSPBPLU5K95M+mVqsV5alarYaoqChRl+Qpyb2oqCjR7LVardy/idjYWOjTp4/iPH388cc51+VyQW5uLueWlpby8rRHjx5VylPi2u12KCws5Nzi4mLOjYuLgy5duvB+R3SeGo1GXvZ27NiR9zsyGAzc13q9npeR7du3575XVlYGJpOJ+7qwsJD7u4iPj4c2bdrw/tx0nubn5/PytHXr1rw/N52nubm5vIxs0aIF9z2TySSYpyRz5PKU/NkaNGgATZo04b5nMBgk87Rhw4bc94qKiqCiooL72jNP4+Pjue8VFBTw8jQ9PZ2Xp1qtlvc7oueyaWlpvNeNjY3l/Y7oPPXMXjpPc3JyvPKUzl46Tz1zLzU1lTeXpatpxOan5O+Y3tGVy1N6R1dsLks+48XyFBG5PCX/LpTmaVxcXJXyVGwuS+cpyQex7CXzU3ouK1UZ8tCh5Gn1fo2HfUc0IyMDo6KiRFcHaW7fvo2RkZGiq4M0165dw8jISHzhhRcEVwdpzp8/L7k6SHP8+HGMiYnBiRMnCq4O0hw5ckRydZDmwIEDkquDNLt378a4uDjR1UGaL7/8Ehs0aCC6OkizefNmbnVQaLeFZs2aNZKrgzTLly+XXB2kWbhwoeTqIM28efMkVwdp3nzzTcnVQZqpU6dyuy1Cq4M0EyZM4FYHhXZbaMaOHSu5OkgzYsQIydVBmsGDB0uuDtL06dOHWx0U2m0huN1u7NGjh+TqIO126tRJ0eqgy+XCtm3bYt++fXHNmjWCO90Eh8OBrVq14nZbhHa6CXa7HZs2bYoDBw7EDRs2YE5OjqhbXl6OjRo1wsGDB+OmTZsEd2YIFosF4+Li8KmnnsLPP//ca7eFxmQyoUajweHDh+MXX3zhtdNNo9frUa1W4zPPPIPbt2/32ummycvLw+joaBw5ciTu2LEDjUajqJuZmYlRUVE4evRo2TxNS0vDyMhIHDt2LO7atctrp5vm+vXrvDyVyt6UlBSMiorC8ePH4w8//CCZp2QXmey2eO500yQnJ6NarcZJkybhjz/+KJm9P/30E2o0GnzllVfw4MGDknn6ww8/YP369XHq1Kn4888/S+bpzp07uTz95ZdfJPN0y5Yt2KhRI3z99dcFd1toPv30U26nOzk5WdJdsWIFVzkkl6eLFy+WrByieeedd7jKodOnT0u6s2bNkqwconnttdewXbt23G6LlDtp0iTJyiGacePGSVYO0Tz77LOSlUM0Q4cO5fJUqHKIpn///lzlkNBuC8HtdmPPnj2xV69eopVDtPvoo49KVg4RXC4Xtm/fXrJyiOBwOLB169aSlUMEu92OzZo1k6wcIthsNmzcuLGiPC0rK8P4+HjRyiEas9mMWq0Whw0bJpunBoMB1Wq1aOUQTX5+PsbExHB56rnTTZOdnY1RUVGilUM06enpGBUVpShPU1NTMTIyEseNG4ffffedZJ5eunSJVzkkNZclu8hilUM0R48e5eayQpVDNIcPH8bY2FicPHkyHjx4UHIuu2/fPtRqtaKVQzS7du3C+Ph4nDZtGv7yyy+S2bt161bJyiGaDRs2KM7TVatWSVYO0SxdulRxnv5dgMIdURVW44HXxMREvHDhQrX9vKpiNpshKChI8nwHwWQyQd26dSXPdxCKi4shODhYsVuvXj3RsxU0RqMRQkJCFLuhoaGi5w9oyPmvf5IrdVaNuXwQkTtncj9dt9sNJpNJ8uwKweVyQUlJieTZFYLD4QCr1Sp5doVQWVkJFRUVkudRCBUVFeBwOCTPoxBsNhu4XC7J8yiE8vJyAADJcyMEq9UKPj4+kudGCBaLBWrWrCl5boRQWloKfn5+is6NlJSUQEBAgKIVVLPZDLVr15Y8W0e7VcnTOnXqKHL/aXn6T8zef0qW/dPcqmZvcXHxfc9Tp9MJFotF8hw2obKyEmw2m+RZQILdbge73a4oe6uap4goeWaPYLVaQaVSKcresrIy8PX1VZSnFosFatWqpShPS0tLwd/fX1GelpSUQGBgoOI8VZq9VcnTBzWXrWqe/pvnsn93Pv1dqFSqi4iYKOuxB1EGg8FgMBgMBoPBYNwPlD6IsvYtDAaDwWAwGAwGg8GoVtiDKIPBYDAYDAaDwWAwqhX2IMpgMBgMBoPBYDAYjGqFPYhSVFRUgNIzs1V1q/IemMvch8VFxAfm0m1ApHC73bxr66VwuVy8a+ulcDqdvJYhUjgcDsVuZWUl7zr8++Xa7XZeG6j75T7I3GN5ylzm/jX3QeapUtflcinOXqfTqTh7q5KnDofjH5Wndrv9ochIlr3M/adQIykpqdp+2KZNm5ImTZpUbT+vqmRnZ0OXLl0gLS0NfH19QavVit4OdvfuXejWrRvcu3cPatWqBRqNRtS9efMmPPbYY5CRkQF+fn4QGxsr6l66dAn69OkDWVlZnCt2k9iZM2fgySefBJ1OBwEBAZLu0aNH4amnngKdTgeBgYGgVqtF3UOHDsHIkSMhNzcXgoKCICYmRvR2sL1798Lzzz8P+fn5EBQUBNHR0aLuN998AxMmTICCggKoW7eupLtt2zaYMmUKFBQUQHBwMERFRYm6GzduhNdffx2KioogJCQEIiIiRN3Vq1fDnDlzQK/XQ2hoKISHh4u6y5Ytg/nz54PRaISwsDDJG8ref/99eP/996G4uBjCw8MlbzqcN28efPjhh2AymSAiIkLypsOZM2fCypUrwWw2Q1RUlOTNsdOmTYN169ZBSUkJREdHS950OGnSJNi0aRNYLBaIjo4WvelQpVLBCy+8ANu2bYOysjKIiYkRvWVWpVLBc889Bzt37gSr1QpqtVr0VkSVSgXDhg2D3bt3Q3l5OcTGxkreijhw4EDYv38/VFRUQGxsrOitiCqVCp544gk4dOgQ2O12SRcRoWfPnnDkyBGorKwEjUYjenstIkLXrl3h2LFj4HA4vPrT0jidTujcuTOcOnUKXC6XVz9FmsrKSujQoQOcO3cO3G43aLVa0dsWbTYbdOjQAVJSUmRdi8UCiYmJcOXKFQAA0Gq1orctmkwmSExMhBs3boCPjw9oNBpRt6ioCDp06AC3bt2CGjVqgEajEb2ZMTc3Fzp16gRpaWmybkZGBjz66KOQnp4ONWvWlMzTW7duQY8ePRRl75UrV6B3796QlZUF/v7+khl57tw56N+/P2RnZ8vm6R9//AFDhgyBnJwc2Tz95ZdfYMSIEZCbmwu1a9cGtVotmjn79++HMWPGQF5enmz2fvfddzB+/HjIz8+XzdPt27fD5MmTobCwUDZPN2/eDK+99hoUFRVBvXr1IDIyUtRdu3YtzJw5E/R6vWz2fvTRR/D2229zN05K3Tq5ePFiWLBgAXfDrFSevvPOO7BkyRJFeTp79mxYsWIFmEwmiIyMlLw5dvr06bBmzRooKSmRzd7JkyfDhg0boLS0VDZ7x48fD1988QWUlZXJZu+YMWNgx44dYLVaZbN3+PDh8N133ynK08GDB8PevXvBZrNJuiqVCvr16wc//fSTbJ4CAPTq1Qt+/fVXRXnavXt3OHr0KOeK5anL5YIuXbrAiRMnwOl0glarlczTjh07wtmzZ8Hlckm6FRUVkJiYCBcvXgRElMzTsrIySExMhMuXLwOAdJ6azWZITEyE69evg0qlknQNBgN06NABbt68CT4+PqDVakUzMi8vDzp16gR37twBX19fyTzNzMyERx99FO7evSubp3fu3FGcp9euXYNevXpBZmYm+Pn5gUajEc29CxcuQN++fSE7O1s2e0+ePAmDBg1SND89cuQIDB8+HHJzczlXLEcOHDgAo0aNUpSn33//Pbz44ouQl5cHderUkXS/+uormDRpkqL56ZYtW2Dq1KlQWFgom6fr1q2DGTNmKMrTlStXwty5cxXNZf8uFixYkJ+UlLRJVlTS4+V+jYe9jyjin70YAQABAOvUqSPZC2rMmDGcW7duXXz22Wfxyy+/FOwFNXz4cM6tV6+eZC+ogQMHcm5oaCiOGTMGv/nmG8FeUL179+bc8PBwHDdunGBfU7fbjV27duXciIgI0V5Qbrcb27dvz7mkF9SePXu8ekG5XC5s2bIl50r1gnI4HNikSRPOleprarfbMS4ujnPr168v2gvKZrNhTEwM58bHx4v2NbVYLBgeHs65Ur2gzGYz1qtXj3ObNGki2tdUr9djUFAQ50r1gsrPz0d/f3/OJX1Njx8/7tULKjs7G2vWrMm5rVq1wrlz5wr2Nb179y7WqFGDc0lf0zNnznj1y7tx4waqVCrObdu2Lb777ruCfU1TUlI4DwC4vqYXL1706mt3+vRpntuxY0fRvqbJycmcp1KpsHPnzrh48WK8evWql/vzzz/zXKm+pnv37uVcHx8f7N69Oy5btkywr+nXX3/NuTVq1MCePXuK9jX94osvONfX1xcff/xx/PjjjwV7661fv55za9asyfU1vXfvnpf78ccfc26tWrWwX79+uHbtWszMzPRylyxZwrl+fn5cX9Ps7Gwv99133+Vcf39/HDRoEG7cuFGwr+ns2bM5NzAwEIcMGYKbN2/GvLw8L/e1117j3Nq1a+PTTz8t2td00qRJnBsUFITDhw/HrVu3YlFRkZc7btw4Xp6SvqZCefrss8/y8vS5557Dr776SrCv6eDBgzk3JCREsk90nz59ODcsLEy0T7Tb7cbu3bvz8lSsT7Tb7cYOHTpwrlSfaJfLhY888ggvT0lfU888dTqd2LRpU688/fHHH73ytLKyEhs0aMC5Un2ibTYbxsbGci7pEy3U17SsrAwjIyM5V6pPdElJCYaEhHBu48aNRfuaGo1GrFOnDudK9YkuKCjAgIAArzwV6muq0+mwVq1anCvVJzo9PR19fX15eUr6mnpmZGpqKvr4+HCuVJ/oK1eu8DKS7mvqmU/nzp3juaRPtFBf0z9R1rGGAAAgAElEQVT++IOXkaSvqVCf6F9++UUwT4X6mu7fv5+Xp1J9or/99ltenj722GOifU23b9/Oy1OpPtGbNm3i5SnpayrUJ3r16tW8PCV9ooXy9MMPP/TK03Xr1gnm6YIFC3h5KtUneu7cuZwbEBDA9TUVytM33niDl6ekT7RQX9PJkyfz8pT0NRXK0xdffFEwT4Xmss899xznBgcHS/aJfuqpp3h5Onr0aNG5bP/+/Tk3NDRUsq9pz549OZfMZYX6mpJe4cSNjIwU7RPtdruxTZs2nEv6RAv1NXU6ndi8eXPOpftEe+apw+HARo0aca5Go+H6mnrmaUVFBWq1Ws6V6hNttVoxKiqKl6ekr6lnnpaWlmJYWBjnKu0TXZ2Awj6i7EGUgp7keQ7PyS89yfMcnpNfepLnOUhYk8nv9OnTRV0y+SVhTU/yPIfn5Jee5HkOz7CmJ3mew3PyO2TIEFHXM6z79u0r6npOfnv06CHq0mFdUFDAm+R5Ds/Jb+vWrUVdz8kv/dDsOTwnv3TQeA4S1mTyGxERIeqSyS8Ja/rh1nN4Tn7pSZPnoMPabDaLegD8yW9RUZGkS4e1TqeTdOnJ7927dyXduLg4Lqxv3Lgh6dKTX8+HZs9Bh7XnQ7PnIJPf5ORk3kOz0GjWrBnOmjUL//jjD95Ds9Agk98TJ07wHpqFRuvWrbnJ7zfffCPptmnTBufPn49nz57FrVu3Srr05Hfjxo2SbocOHXDBggWYkpLCm+R5Ds/JLz3JE3K7dOmCH3zwAV67dg2TkpJEXc/J71tvvSXq1qhRA3v06MFNfulJnuegJ7937tzBV155RdT1nPyOHz9e1KXzNCMjA0eNGiXq+vn5Yf/+/XHdunWYlZXFm+R5DpKn69evR51Ox5vkeQ7PyS89yfMcJE8/++wzzM/Px86dO4u69OS3sLCQN8nzHJ4Luc2aNRN1PSe/9CKk5/BcyKUnbp7Dc/IbHBws6npOfv38/ERdkqfff/89WiwWyX8/ZCF37969qNfrJV2Sp/v378ecnBxJl5783rt3T9Ilk99Dhw5hamqqpEtPfi9fvizpNmrUiFvIPXv2rKTbpEkTfPPNNzE5ORmPHTsm6TZr1oxbyKUfmoVGixYtcM6cOXjixAneQ7PQaN26Nc6dOxdPnTqF3333naSbkJCA8+fPxzNnzuCXX34p6ZKF3PPnz+PmzZsl3cTERFywYAFevHgR16xZI+l27NgRFy5ciJcvX8bly5eLenSeXr16FRcuXCjq+vj4YNeuXXHp0qV448YNnDdvnqhL8nTZsmWYmpqKM2bMkHR79uyJK1aswDt37uDUqVNFXV9fX+zduze3kEtvAHmOmjVrYp8+ffCTTz7BjIwM3gaQ56hVqxb2798f165di1lZWbwNIM/h7++PAwYM4PKU3gDyHAEBAdxCbm5uLm8DyHMEBgbi0KFDuTx99NFHRV2ykLtlyxYsLCzEdu3aibp0nhYVFWGLFi1EXbmNseoCFD6IsjOiCkFEuHfvHqSnp0N6errkOQS328156enpkmcLXC6XYtfpdMLdu3c5FyXq+h0OB+91pdzKykrFrt1u57x79+6JegB/lr4QNyMjQ9ItLy/n3MzMTEnXarVyblZWlqRbVlbGudnZ2ZJuaWkp5+p0OknXbDZzbk5OjmI3NzdX0i0uLubc/Px8SddoNHJuQUGBYrewsFDS1ev1nFtUVCTpFhUVca7RaJR0CwoKOLe4uFjSzc/P51yTyaTYLSkpkXTz8vI4t7S0VNLNycnh3LKyMsWu1WqVdLOzsznXZrMpduXOhGRmZnKu3Bkw2pU7A5aRkcG5UmfAEJHnSp0Bq2qe0q5cnip1nU6n4uz9p+WpzWZT7D6oPLVYLIrztKSk5IHkqclk4ty8vDxJl85euTw1GAzc35mcS+epXq+XdKuSp4WFhX8pe+XylM5IuTzNzc3lXIvFct9cnU6nOE9pVy5Ps7Ky/pL7d+Spp/t35anSLHtY5rLkdauSp3JuVfL0Qc1lq5Kn9FxWLk8fCpQ8rd6v8bDviBqNRnz++edFV7roEhuDweC1cyhWsqjX6712DslKl2fJYlFREfbr14+30iVWslhQUMBb6SYrXUIli54rM/SubWpqKs/Ny8vjleZKlSzm5ubySnPpkkXPEhudTsfbZaR3bdM9SmyysrJ4q+JSJYv37t3jleZKlSympaXxSnOlShZv3brFK80NCAgQLVm8du0ab/eSXunyLFm8dOkSrzRXqmTx7NmzvNJcstIlVGJz4sQJXmlucHCwYMmi2+3G33//nVeaK1ay6HK5vHb46JJFusTG6XR6rUiHh4cLliw6HA6vFenIyEjBkkW73Y47duzguaTEZt++fbwSm4qKCtyyZQvPVavVgiWLNpuNV0ILIF6yWF5eziuhBfjfkkXPEnCr1YpLly7luWIli2VlZbySL4A/SxbfeOMNrxKb0tJSr9VrsZLFkpISnDlzJs8VK1k0m804bdo0nitWsmgymXDixIk8V6xksbi42KsSQ6xk0WAw4MiRI3muWMmiXq/Hp59+mueKlSwWFRXhgAEDvPJUqGSxsLAQH3/8cZ4rVgJeUFDAO+ogVbKYn5+PiYmJvDwlVTCeJYu5ubm80lypksWcnBxeaS7JU6GSxezsbF5prueuLU1GRgavNJcuWczKyuK5d+/e5ZXmSpUs3r59m1eaS+/a5ubm8twbN27wSnMDAwNFSxYvX77MK80leUp2bWnOnz/PK82tU6eOaMniyZMnvfJUrGQxOTmZV5pLV8HQJYsul8trh0+sZNHpdOKBAwcE89SzZNHhcOAPP/zgladCJYuVlZW4c+dOwTz1LFm02+28IwkkT0kVDF0ubrPZcMOGDTyX3rWls7e8vBw/+eQTnkuXLNLZa7VavXYD4+PjBUsWy8rKcNGiRTxXrGTRYrHg/PnzeS69a0u7JSUlOGvWLJ5LV8F45qlnZRu9a+uZp3S5LcD/VsGcOnWK5xYXF3tVYpBd27Nnz/Ly1Gg04ujRowXzVGguO2zYMJ5Ldm2F8pTeOSRVMGTX1jNP6aMOnlUwnnlKV8F57tp65ildmutZBUOTl5eHCQkJPLdXr17cri1NTk4OrzSX7NquWrXK6/iNTqfDhg0b8rKX7Np6Hr/JzMzkVcyRXdt169Z5zWXT09N5FR5+fn68XVuaO3fu8EpzpfL07wJYaW7VKSwsxLCwMNG/eJqcnBwMCQlR9BefkZGB9erV423Xi3H79m0MDg7GYcOGcdv1Yly7dg2Dg4Mlz7ESLly4gMHBwYq260+cOCF7jpVw5MgR7oP0m2++ETx3RThw4ACGhYWJ1v7T7N69W/IcK82OHTswKiqKK3/yrP2n2bx5s+Q5Vpo1a9ZgbGys4AepJ8uXL0etVit6jpVm4cKF3Aep0DlWmnnz5kmeY6WZMWMG9xAjdI6VZsqUKZLnWGleeukl7oNU6BwrzejRo7lzrJ4fpJ4MGzYMExISRM+x0gwYMEB0UciT3r17S55jJZBz03T5k5SbmJgoeY6V4HK5sHXr1twHqdA5VoLD4cBmzZqJLgrR2O12bNSokeQ5VkJ5eTnWr19f8hwrwWKxoFqtFv0gpTGZTBgZGSl5jpWg1+sxPDwcBwwYIHqOlZCXl4ehoaGS51gJWVlZWK9ePclzrIS0tDQMDg4WXRSiuX79OtatW1fyHCshJSVFcZ6eOnVK9hwrITk5WfYcK+HQoUOii0Ke/PDDD4rzdOfOnZLnWGm2bNnC5anQOVaaTz/9VPJeAJqVK1dKnmOlWbx4seiikCfvvPOO5DlWmlmzZinO02nTpkmeY6WZOHGi5DlWmueff17yHCvNiBEjJO8FoBk0aJDkOVaaPn36cHkqdI6VQM5Nk0UhoXsBaLdjx46ii0I0LpcL27RpI3kvAMHhcGCLFi2we/fuoudYCXa7HRs3bsw7GiWGzWbDuLg4yXOshLKyMoyNjRVdZKcxm80YHR0tuihEYzAYMCIiQvJeAEJ+fj6GhoZKnmMlZGdn8/JUai6bnp6OwcHBvKNRYqSmpmJwcLDoohDN5cuXMTg4WPIcK+HMmTNcnoqdYyUcPXrU62iUGIcPH5Y9x0rYt28fb5Fdai67a9cuyXOsNFu3bhVdZPdkw4YNootCDwvsQfQvYDAYJP/iaYqKihT/xRcWFkp+kNIUFBRIfpDS5OfnS36Q0uTl5Sk+wJybm1slV+qDlCYnJ0fyg5RGp9NVyZX6IKXJzs6ukiv2IeZJVlaWYvdBva7nbsX9cN1u9wNzpT5IaZxOp+SiEI3D4VC8Gmi32yUXhWhsNpvkBymN1WqV/CClsVgsis9wlJaWSi4K0ZjNZskPUhqTyST5QUpjNBolH2JoqpKner2+Snkq9RBDU1BQoDh78/PzFWdvXl6e4uz9N+dpVbP3YcjIf2v2Ks1Tl8v1wPJUalGIpqKiQvIhhqa8vFxyUYimrKysSnkq9RBDU1JSIvkQQ1OVPC0uLq5Snko9xNBUJU+LiooU5+k/cS77IPK0qtn7d89P/y6UPoiqUKLe+n6TmJiIFy5cqLafx2AwGAwGg8FgMBiM6kOlUl1ExEQ5j11WxGAwGAwGg8FgMBiMaoU9iDIYDAaDwWAwGAwGo1phD6IeOBwO2au6CZWVlbJXdRPsdrvsVd2EiooKyau6aWw2W5VcqWu9acrLyyWv36axWq1VcpWWgz8ot6ys7IG5SmEucwmIWCVXrp0Bwe12K3ZdLheUl5crcp1Op2wrGcLDkqdK3QeZp//W7GV5ytx/qvsgs7cqeSrXSobgcDgUZ29lZaXi7LXb7Yqztyp5WtW5LMvTB5enDzM1kpKSqu2Hbdq0KWnSpEnV9vP+Kt27d4dDhw6BzWYDtVoNtWvXFvQQETp37gy//fYb2Gw2iI2NhcDAQEHX5XJBYmIiHDt2DOx2O2g0GggICBB0HQ4HtGvXDk6dOgWVlZWSbkVFBbRt2xbOnj0LTqcTNBoN+Pv7C7pWqxUSEhLg4sWL4HK5QKPRgJ+fn6BrNpshISEBrly5Am63G7RaLdSqVUvQNRqN0KZNG7h27RogoqSbn58Pbdu2hdTUVFCpVKDRaKBmzZqCblZWFiQmJsLt27fBx8cHtFot+Pr6Crp37tyBLl26QFpamqx7/fp16NatG6Snp4Ovry9otVqoUaOGoHvhwgV4/PHHISMjA2rWrCnpnjx5Evr16weZmZng5+cHsbGxou6RI0dgyJAhkJ2dzbk+PsLrQgcOHIARI0aATqeDgIAASXf37t0wZswY0Ol0EBgYCGq1WtTdsWMHjB8/HnJzc6F27dqgVqtBpVIJup9//jm8/PLLkJeXB3Xq1IHo6GhRd+3atfDaa69BQUEB1K1bV9L96KOPYObMmVBYWAjBwcEQFRUl6i5evBjmzZsHRUVFUK9ePYiMjBR13333XUhKSgK9Xg+hoaEQHh4u6s6ZMweWLFkCRqMRQkNDISwsTNSdPn06rFixAoqLiyE8PBzCwsIEPQCAl19+GdauXQsmkwkiIiIgNDRU0FOpVPDiiy/Cxo0bwWw2Q1RUFNSrV0/UHTVqFGzduhVKSkogOjoagoODRd3hw4fDV199BRaLBaKjo6Fu3bqi7qBBg+Dbb7+FsrIyiImJgTp16oi6ffr0gb1794LVagW1Wg1BQUGibo8ePeCnn36C8vJyiI2NlczTLl26wK+//goVFRWS2et2u6Fjx46QnJwMdrtdMnudTie0b98eTpw4IZu9lZWV0LZtWzhz5gw4HA7QarWSedqmTRu4cOECOJ1O0Gq1onlaUlICbdq0gUuXLoHb7ZbMXqPRCAkJCXDt2jXZ7C0sLIS2bdvCzZs3AQBAq9WK5qlOp4P27dvDrVu3QKVSSbrp6enQsWNHSEtLgxo1aoBGoxHN0xs3bkDXrl3h7t274OvrK+mmpKRAr1694N69e1CzZk3QaDSiGXnq1Cno27cvZGRkQK1atSTd5ORkGDRoEGRlZYGfnx9oNBrR3Dt06BAMGzYMsrOzZfN0z549MGrUKMjJyYGAgADJPN25cye88MILivJ0y5YtMGnSJMjLy4OgoCCIiYkRddevXw+vvvoq5Ofny+bpxx9/DDNmzICCggLZPF26dCm89dZbivI0KSkJ3nvvPSgqKoKQkBCIiIgQdd966y1YvHgxGAwGCAsLk8zTN954A5YvXw5Go1E2T6dMmQKrV68Gk8kE4eHhonkKADBhwgRYv349mM1miIyMhJCQEEFPpVLB2LFj4fPPP4eSkhLZ7B0xYgR8+eWXUFpaKpm9AACDBw/m8lQue/v27Qt79uwBq9Uqm709e/aEgwcPymYvAEDXrl3h8OHD3PxUKns7deoEv//+O1RUVIBGo5HM08TERDh+/Ljs/NRut0Pbtm3h9OnT4HA4JOenNpsN2rRpA+fPn5edy1osFkhISICUlBRwuVyS2WsymSAhIQGuXr0KiAgajUY0T4uKiqBNmzZw48YNAJDO05ycHC5P5dx79+5Bx44d4c6dO7Lz01u3bsGjjz4Kd+/ehRo1aki6V65cgR49eijK07+DBQsW5CclJW2SFZXcaHS/xsN+a67D4UCbzYZbt2716jvn2bKBuBs3bpTtfVRZWYk2mw1XrVrFc4VaNhD3ww8/5PU+6tmzJ65YsYJ3xThxk5KSeL2PhFo22O12tNlsOHfuXK/eR6tXr+a1bCDuG2+8wet9RFo20Df5EfeVV16R7X1EXLoXVkBAANeygb6dr6KiAm02G44aNYrXS27o0KG4efNm3m2nxKV7C9J9POnbTon75JNP8nrJCbVsIG6vXr04l/Tx9GzZYLPZsLy8nNerlW7ZQN92Stx27drxesmNGTPGqwWOzWZDq9WKLVq04Fy6ZQN9O5/NZsOysjJs3Lgx55KWDXQfT7fbjTabDUtLS7F+/fqcS7dsILedEtdsNvN6tQq1wCGuwWDg9WoVatlA3MLCQgwODuZc0gKHbtngcrnQZrNhbm4u1q5dm9dLzrNlA3GzsrJ4vVobNmzo1bKBuHfv3uX1ahVq2UDcmzdv8noLNm3a1Ktlg9PpRJvNhpcvX+b1aiUtG44fP+7lnj17ltfHTahlA3H/+OMPnktaNtB9PInr2bNQqGUDybIff/yR5wq1wCGuZw9YoZYNxP3yyy8F85Ru2UDcTZs28Vyhlg0k99asWeOVp54tG4hL9yGk+3gK5enChQu98tSzZQNx6b6udF9koTydMWMGL09Jywa6BQ5xp06dystToZYNxJ0wYQLnivXxJO7YsWN5eSrUAofk3ogRI3h5KtSygbiDBg3iXLG+yMR94okneHlKWjbQeUrcbt26cS7pi+zZsoHkKd2rVaxlA3Fbt27tlaeeLRtInv7nP//h5alQX2SbzYYWiwXj4+M5V6hlA52narWac4VaNhC3uLgYIyIiOJdu2eCZp0VFRbxeraQFzsGDB73yND8/n9erNS4ujuvj6Zmn2dnZvF6tQi1wiJuens7r1SrUx5O4t27d4uUpaYGTnJzslZFXr17l5alQH0/inj9/XjBP6T6exD158iTPJX08hfL0t99+88pTzz6eJMsOHjzIc+m+yJ7u999/z3OF+ngS96uvvuJlZKdOnXDRokW89mPE/fzzz73y1LOPJ8myTz/9lJenQn2RibtixQpengr18STu4sWLeXlKWuDQfTyJ+8477/Bc0seTboFDsmz27NleefrJJ5/wWuAQ97XXXuPlKenjKTSXnTRpkleeis1l6T7ZdB9PoTx99tlnedkr1M6RuEOGDOHl6bBhw7xa4BC3b9++Xnkq186xugDWvqXqLFmyhBcGQoP0KxszZoysSya/no3ahQaZ/Ho2FhYaJKwHDx4s65LJb79+/WRdEtZ0U3exQSa/3bt3l3XJ5JduQiw22rdvj++99x7vIU1skMlvy5YtJT06rJs0aSLrkslvXFycpEtPfqOjoyVdevIbGhoq6dJhTT94CQ168uvr6yvpkrBevXq17O+WTH5Xrlwp65Kw/uijj2TdgIAAHDJkCG+hRWyQye8HH3wg65Kwph8ixAYJa3oBR2yQyS/9ASk2yOT37bfflnVJvzL6w1RskH5lb775pqxLJr/0B6/YIJPfKVOmyLpk8kt/SIsNMvl96aWXZF0y+X3++edl3QYNGuC0adPwueeek3XJ5Hf48OGyLmliT3/4iw0y+R0wYICs27JlS5wzZw7vwUtskMkv3dRdbJAm9l26dJF1yeS3ffv2si6Z/NIPaUKDztOmTZvKuqSJfYMGDSRdMvldunQp7yFNaNCTX3rRS8wlC7n0g5fQoCe/9MOU0KAnv3K/WzL5/fjjj2Vdf39/HDBggOI8HTx4MC5btkzWJZNfJfMckqf0Q4TYqFOnDo4YMQLff/99WTc4OBhHjhypKE9JL3N6sUdskIXcOXPmyLrh4eE4btw4nDlzpqxL8vT111+XdaOjo3HChAn46quvyrpqtRonTpyIL7/8sqyr0Whw8uTJvAUnsVG/fn2cMmUK7wFJbJBe5qNHj5Z1SS/zZ555RtYleTp06FBZl/QyHzhwoKzbokULnD17Nvbp00fWJb3Me/bsKeuSPO3atausS3qZd+jQQdZNTEzEpKQkTEhIkHVJL/PmzZtLevRCbqNGjSRdsY2x6gQUPogK7/cyRDGbzWAwGBTV05tMJjAajYrq/4mrpP6/Km5xcTEYDAZFZwWKi4vBaDQq+rMZjUbFvwej0QhGo1HRuQKDwaDYJa8rdwYBETlX7lwBcQ0Gg6zrdru59yt3rsDlcnHvQc51Op2cizL1/w6Hg3u/cm5lZSX3unLY7XYwGAxQXFysyDUajWAymWTdiooKMBgMilybzQZGoxHMZvN9dcvLy8FoNEJJSYki12AwQGRkpKxrtVq58l6lrlgJFk1ZWRkYjUbRciIai8UCRqNRtBTO0zUYDKIlYzSlpaVgNBpFS6VoSkpKwGAwiJYw0pjNZsX/3omrJE+JW5U8rUpGKnld8m+tKhl5v12DwQAGg+G+5yl5XaV5qiR7H1Se0q5cRtLZK0dlZSX3fuUgGfkg8lTp6xK3Knl6v3PaarWCwWCA6OhoRa7RaJQs1yWQjFSSZcQVKyelIRmpJMtIRoqV9gq5YuWvNCUlJWA0GhWVXBJXyTlH4io5y1rVPDUYDPd9LluV3Pu/MJeVc91uN+caDAZwu90PVdkuDyVPq/drPOw7oiUlJajT6XDDhg2CKzzJyclcaQlxPXeXhMpFzGYz6nQ6r10gsmJOl4uYTCbU6XReq4tkxfzUqVOcW1xcjDqdzmsHhqzw0OUiRqMRdTodrzwM4H9XzM+fP8+5BoMBdTqd18qeULmIXq9HnU6HEydO5K3adOrUCRcuXMgrFykqKkKdTsfb/aBXzOlykcLCQtTpdLxyBnrFnF7hKSgoQJ1Ox1uB8ywX8XT79+/Pc8mKOV0ukp+fjzqdjreqRq+Y06XPeXl5qNPpeLsUpPT5k08+4ZXq5ebmok6n4+361qpViysXoUv1cnJyMDs7m1eaK1b6rNPpMDs7m1eaS5eLkNJnt9uNOp0OMzMzeaW5QuUipPl5RkYGrzS3du3aOGzYMF7ps9PpRJ1Oh3fv3uXtUpAVc7pchLi3b9/mleaSFXO69NnhcKBOp8ObN2/ydojJivnOnTu50ufKykrU6XR49epVXmluSEiIV+mz3W5HnU6HKSkpvNLcsLAwHDduHH733Xdc6XNFRQXqdDo8e/Ysr5SMlD5///33XKmezWZDnU6Hx48f55WSRUVF4YQJE3Dv3r1c+V15eTnqdDqvki+h0mer1Yo6nQ4PHTrEc2NjY3Hy5Mm80ueysjLU6XS4d+9enktKnw8dOsSV6lksFtTpdLhr1y6eS1bM6dJn4m7bto3nkhXzI0eOcKV6paWlqNPpeOW2dJ7Spc8kTz13l8iK+bFjx7zylC63BfjfFfPjx4975emiRYt4LlkxF8pTz92ahIQEnDdvHp45c8YrT2fNmiW4Yi6Up5671GTFnC59JnnquVNCVszp0meSpy+++KLgijl9lIS49G4yvWJOlz6T7KWPOogdJSF5Su8Qix0lIXnau3dvXp6SoyR06TPJU3qXgj5KQpfqkTylS3PpoyRCeUrv+pI89Sx9JnlKl+b6+/tzR0no0medTodZWVm80lz6KAkp1SPZm5GRwdv1pY+SkNJnkr3p6em80lyh0meSp3fu3OGV5tJHSUj2kjxNTU3l7RCT6o+vvvqKK30meXrt2jVeaa5Unl66dIm3m0wfJSGlzyRPz507J5indOkzydOTJ0965Sk5SkJKn0meJicnC+bpvn37uDwl7uHDh73y1PMoCcne/fv3C+YpfZSEZK/n8QVSTSeUp/TxBQDh0meSp5999hnPJdV0dOkzydN169bxXFJNRx8lIXnqWf1EqunouSzJU88qJaGjJCRP33vvPZ4rdJSE5Olbb73Fc4WOkhCXPjoG8L/VdBcuXODyiWQvfXQMQPgoCcleupJH7CgJyVO6MlLsKAnJU7o6R+woCclT+qgDXU1Hlz6TPKV3iOlqOjpP/y6Aleb+NdxuN3bs2FHwDJEnLpcL27Rpo+gv3uFwYIsWLbgySvqD1BO73Y5NmjTBfv364Zo1a3g1756Ul5djgwYNBM8QeWKxWFCr1QqeIfLEZDKhWq3mzhDR5zc90ev1GB0dLXiGyJO8vDyMiIjgPkjpmndPsrKyMDw8nDtDJFXznpaWhmFhYYJniDy5ceMGhoWFCZ4h8iQlJQXDwsJw7NixXmeIPDl9+jRXRrl7927e+U1PkpOTMTIyEl966SXeGSIhDh06JHiGSIg9e/bwzhCRD10hvv76a9RoNPjKK6/wPkiF+OKLL7B+/fpeZ4iE+PTTTwU/SIVYuXKl4BkiIT744APeGSIp99133xVcFBJi9uzZgotCQrz22mu8M0RS7sSJEwG3ChIAACAASURBVLkPUnpRSIhx48YJniES4tlnn8UOHTp4LQoJMXToUK6Mkv4gFaJfv36Ci0KeuN1u7NmzJ3eGSKrsx+12Y+fOnQXPEHnicrmwXbt2gmeIPHE6ndiqVSvBRSFPKisrsWnTpoJniDyx2WzYqFEjwTNEnpSVlWH9+vW5PKUXhTwxm80YGxvrtSgkhMFg4PLU8wyRJwUFBRgZGSl4hsgTnU6H4eHhXotCQqSnp2N4eDiOHDkSd+zYwTu/6UlqaiqGhYV5LQoJcfnyZcV5evbsWa6Mkl4UEuLYsWNcGSW9KCTEL7/8IrgoJMT+/fsFF4WE2LVrF1dGefDgQe4hRoht27ZxeUovCgmxceNGblHol19+kcze1atXCy4KCfHhhx8KLrILkZSUhM2aNfNaFBLirbfewhYtWijK09dff11wUUiIyZMnc4vs9KKQEC+++KLgopAQo0aNElwUEuKpp57iFoXoRXYhnnzySS5P6UUhIR5//HFFZZRutxu7du2KPXr08FoUEnITExMFF4U8cTqd+MgjjwjeL+JJZWUlNmvWTHCR3ZOKigps3Lix4KKQJ1arFePj47lFdqm5bGlpKWo0GsFFIU+Ki4sxJibGa1FIiMLCQoyMjPRaFBIiJycHIyIiuDylz8N7kpGRgeHh4YL3i3hy+/ZtLk/pRSEhrl27hmFhYYL3izwMKH0QVaFMqcr9JDExES9cuFBtP++vYLfbwWq1Kiqvq6iogIqKCkWlGOXl5eB0OhWVjpArpJWU7VksFlCpVJI3pxFKS0vB19dXcTlIrVq1FJWvmM1m8Pf3V1S2ZzKZIDAwUPSGM5ri4mIICgpSVJJIynLEbi2jMRgMUK9ePdGbyDzdkJAQRSUN5IZWJW5RURGEh4crKvmpiltYWCh5+2F1uAUFBZK3Nf7/uEpKuv5pLiJCYWGhYreoqAiioqJkXbfbDXq9XpFLyheVlCA7nU4wm80QHh4u61ZWVkJZWdl9z1ObzQaVlZWSt1YSqpKnpJWDkjy1WCzg4+MjehMlDcvTqrsPQ54+DNnL8vTBuVXJ06pmr9IjHQ8qT+12O5SXl4veGExTlTytylyWtBdROpdVmqcPai5rMpkgICBAUfZWNU/r1Knzt2bv34FKpbqIiImyHnsQZTAYDAaDwWAwGAzG/UDpg6j8Mh+DwWAwGAwGg8FgMBj3EfYgymAwGAwGg8FgMBiMaoU9iAqg5Bryf7uLiFVylbTCAPjz7ERpaaki1+l0gsViUeQ6HA6wWq2KXHJ2QgkVFRWK2kUA/HnOQsk15AB/nrNQ0i4C4M8zbkquFgf480yGkuvCAf48kyF3BfhfcUtLS2VbNdCukqvmAf4861EVV+mxA7PZ/I9zlcLch8Otap4qdd1ut+LsdblcVcpTcl5WjsrKyiplr9I8JWeGlfCg8tRqtSrO07Kysn91nip1H5aMZHn673Ufljytylz2QeWp0rnsw0yNpKSkavthmzZtSpo0aVK1/by/yvLly+H111+HvLw8CAoKgpiYGNHD/4sWLYLZs2dDXl4e1KlTR9KdP38+zJ8/HwoKCiA4OFjyUoFZs2bB+++/D4WFhVCvXj3Jiw2mTZsGH374Iej1eqhXrx5ERESIuhMnToRVq1ZxF0GEh4cLuiqVCsaNGwfr1q0Do9EI4eHhov28VCoVjBw5EjZv3gzFxcUQEREhephepVLB0KFDYdu2bWA2myEiIkL0ML1KpYL+/fvD119/DSUlJRAVFSV6kYmPjw/06tULvv/+eygpKYHo6GjRg/cqlQq6du0K+/fvB4vFAjExMZIH7zt27Ag///wzlJWVgVqtFj14j4jQrl07OHLkCJSXl4NarRa99MTpdEJCQgIcPXoUbDYbxMbGih7Sr6yshFatWsHJkyehoqICYmNjRQ/pl5eXQ6tWreDMmTNgt9tBo9GIHtIvLS2Fli1bwoULF8DhcIBGoxE9pF9cXAwtW7aES5cugdPplHQLCgqgdevWcPXqVXC5XKDVakUvU9HpdPDII4/AjRs3wO12g1arFT3Qn56eDu3bt4fU1FRAREn35s2b0LFjR7h9+zaoVCrQarWih/9TUlKgW7dukJaWxrlih/9Pnz4NvXr1grt370KNGjUk3eTkZOjXrx+kp6eDr68vaLVa0YtXDh06BIMHD4aMjAyoVasWaDQaUXfPnj0wfPhwyMzMBD8/P4iNjRV1d+7cCaNHj4bs7Gzw9/eH2NhY0YtXtmzZAuPHj4fs7GwICAiQdD/99FN4+eWXIScnB2rXrg0xMTGi7sqVK2HatGmQm5srm6dLliyBmTNnQn5+PgQFBUF0dLSo+95778Hbb78NBQUFULduXUl3zpw5sGDBAigsLJTN3unTp8OSJUugqKgIQkJCJPN08uTJsGLFCkV5On78eFizZg3XG1HschKVSgWjRo2CjRs3QnFxsWz2Pv3007B161YwmUwQGRkpmacDBgyAnTt3gtlsls3T3r17w3fffQelpaUQFRUlmafdu3eHvXv3gsVigejoaMk87dy5M/z0009QVlYGMTExonnqdruhffv28Msvv4DVapXMU5fLBW3atIHk5GSw2WygVqtF89ThcEDr1q3h+PHjsnlqs9mgZcuWcObMGVnXYrFAy5Yt4fz581BZWSmZvSaTCVq2bAkpKSngcDhAq9WK5mlRURG0atUKrly5Ai6XCzQajWie5uTkcHlKslcsIzMyMqBt27aK8vTWrVvQoUMHuHXrFgCAZJ5euXIFunTpAmlpaeDj4wMajUbUPXv2LDz22GNcnmo0GtE8PXbsGPTp0wfu3bsHvr6+ku7hw4dh4MCBkJGRATVr1pTM03379sGwYcMgMzNTNnt37doFzz33HGRlZcnm6bZt2+CFF15QlKcbN26EiRMnQk5ODgQGBoJarRZ1V61aBa+++irk5uZC7dq1Qa1Wi+bT0qVL4c033+Tmp1IZuWDBApg7dy7k5+fL5uncuXPhvffeU5Snb775JixatAiKiopk57JTp06F5cuXg16vl8xelUoFL730EqxevRoMBgOEhYVBWFiYqDtmzBjYsGEDFBcXc64QKpUKRowYAZ9//jmYTCbZuezgwYNhx44dirK3T58+sGvXLtm5rEqlgsceewz27Nkjm6cqlQq6dOkCBw4ckM3Tv4MFCxbkJyUlbZIVlVyte7/Gw96+xWazoclkwszMTF5/rejoaK+r3ol79+5dXn8todYZ5eXlaDKZMDU1lddfi77qnVzfTtyrV6/y+mvRV72T69utViuaTCa8ePEir79WgwYNuKveyfXtZWVlaDKZ8NSpU7x+SqR1xpEjR7jr24l79OhRnit01bvFYkGTyYQ///wzzyWtM+ir3om7b98+nit01XtpaSmaTCav3oatW7f2uuqduNu3b+e5Qv1US0pK0GQyefU2bNeunddV78T17G0o1E/VbDajyWTCZcuW8Vyhq96Ju3DhQl4PKqGr3k0mE5pMJpw3bx6vB5XQVe/EnTlzJq8HFWmdQa56d7vdnEv3ihXqp0q7//M//8PrV+XZOsPlcnHu2LFjOZfup0paZ9DuM888w7mkn+ratWu51hlOp5NzBw8ezLn+/v5e/VRpl+6vRfqpbty4kWud4XA4OLdHjx6cK9RPlbjFxcXYsWNHzqX7/5HWGZWVlZybkJDAuXQ/VXLVO3GNRiM2a9aMc+n+f+Sqd7vdjiaTCQ0GAzZs2JBzhfqpEreoqAg1Gg3nhoaGcle90z39TCYTFhQUYFRUFOeS1hnffvstr5+qyWTC3NxcDA0N5VyxfqomkwmzsrKwbt26Xnm6Z88erzxNT0/HwMBAzhVqnUEy8vbt2+jn58e5Qv3/iHv9+nX09fXl5alnP1WSpykpKejj48O58fHxXv3/iHvmzBnev3eh1hkkT//44w+vPH3jjTd4/VSJ++uvv/JcoX6qJE9//PFHrzz17KdKXM/ehqR1Bt3/j+Tpjh07eC7p/0e3ziCuZ29D0jqD7v9H8tSzt2H79u29WmcQd8WKFV556tn/j+Tp4sWLeXkq1E+VuO+++65Xnnr2/yPZMHv2bJ4r1E+VuHSvWLr/H2mdQecp3SuW7qcqlKcvvPACL09JGzjSOoN2R44cyctTz9YZdEbSvbf9/Py82sDRLt17W6ifKp2ndO/twMBArg0caZ1Bu3TvbZKndBs4Ok/btm3Ly1PPfqq0S/feJnm6fft2wTxt1KgRL09JP1XPPNXr9ajVajk3JCTEqw0cycjCwkKMjo7mXLqfqmee5uXlYVhYGC9PSRs4zzzNzs7m9d4W6qdK3IyMDF7v7ZiYGK4NnGee3rlzh9d7m+Tpjz/+6JWnN2/e5PXe1mq1Xm3gSEZevnyZN5cl/VTpNnDEPX/+vNdc1rMNHMnIEydO8LJBqJ8qcT37dAv1UyUZefDgQZ7bvHlzrzZwxP3hhx94rlA/VZKRO3fu9MpT0gbOM0+3bNnCc4X6qZKMXL9+vVeeevZT/bsA1ke06ixZsoT3Fyo0SPPrgQMHyroBAQE4aNAg7Nevn6xLJr90s2+xQcL6sccek3XJ5JduDC42SFh36tRJ1iVh3a5dO1mXTH4feeQRWZeEdfPmzWVdMvlt3LixrEvCOi4uTtYlk1+64bjYIGFNNxwXG6T5Nf0hIjbI5Jde5BAbZPJLh73YaNy4MU6fPl3WA/hz8ktPrKRG8+bNcdq0aYrcli1b4tSpUxW5jzzyiFczarHRtm1b3uROarRv3x4nTpyoyO3QoQNOmDBB1iOT3/HjxytyH330URw3bpysSya/9MO92CCT31GjRsm6ZPJLLwSIDTL5pZtyi41atWph3759eZNcsUEmv3QDb7FBJr/0hFhskMnvE088IevWrl0bn3rqKd7kWWwEBQXh8OHDsXv37rJu3bp18ZlnnsHOnTvLusHBwfjcc89h+/btZV0y+aUXOcQGyVN6Ui42yOT3P//5j6xLenY2aNBA1iU9kOkFEbFB8jQyMlLWJZPfkJAQWTcuLg6nTp3Km5SLDTL5pSfaYoMs5Mp5AH9OfpXmabNmzaqUp/SCotRo3bo1TpkyRZHbpk0bnDx5siK3Xbt2OGnSJEVuYmKi4jzt1KlTlfKUfmAXGz4+PtitWzd8/vnnZV2ykDt69GhZ19fXF3v16sVbCBAbNWvWxN69e1cpT5966ilZ18/PD/v3789bsBUb/v7+OHDgQHzyySdlXbKQ27dvX1mXzGV79eol6wYFBeGwYcOqlKf0woXYCA4OxpEjR2KHDh1kXbKQSy9yiI3Q0FAcO3YstmrVStYlC7lNmzaVdUme0gvMYoMs5NILImKDbIzJ9UB+UIDCB9GHs/nMQwwigsvlUtRXzO12g8vlUnRW4d/sulyuf9R7eNCuEpxOp2K3Kq/7T3sPLpdL8dmkB/m6SlySDX/n6/4VV8n/dqvyun/l37CSvocP+j1UxX0Y3kNVXCX8X8hpJfwTs+xhcP9pearkz/ZXMudBuVX5t6ak925VsuFhyL2HIZ8epiyriqvU/9tQ8rR6v8bDviNqtVpRr9djeno6BgUFcasKQmVnxL19+zZv1yoqKsqrjLesrAz1ej3euHGDV5orVHZmsVhQr9d7lTPExsbi5MmTeWVnxD137hyvnIHsvNFlZ6WlpajX673KGeLj43HatGm8srOSkhLU6/Ve5QxCZWfE/emnn3guKZOgy87MZjPq9Xrcs2cPzxUqOyNlMF9//TXPJWW8dNkZcbdu3cpzSdkZXcZbXFyM/4+9846Oqtrf/neSkEYS0utMaKkkmYEQuiBNQIp0FQELUuSqIEi5cFETQRAQUBRRLIgNRWyIgogCgnRCkyEQMumTMumTPmW/f3j3efees8/MHl+ieN/zrHXW7y5/H8FFec6e7zzf/RgMBvTWW29RrEajEcXOKisrkcFgQK+99hrF4tgZGePF7Pr16ymWFTurqKhABoMBZWRkUCyO8ZKxM8yuXLlS4KRiZwaDARkMBvTss88KLBnjxbEzq9UqsOQ3k6zYGcmSU2wc4yVjZxaLRWDJb+/I2Fl2djZC6I/IF2anTJkisGTsLCcnR8SSk15W7MxkMgksGc3FSQYydtba2iqwZDSXFTsjWTKa6+XlJYqdtbS0IIPBgMrLy6lvrcgYL46dkSwZzcXfvJGxs+bmZmQwGFBpaSk1OWXFeJuampDBYEAlJSXUN1H4m7dPPvkEVVZWUmxRUREVzQ0ICEDTp0+nYmeNjY3IYDCggoICKppLxs5w5Bd7pE6no6K5wcHBotgZZrOzs6loLit2hv1Uq9VS0Vzsp2TsDHvk5cuXqWguK8aL2fPnz1PRXFbsDPup7aoDjp2RforZI0eOUCwrdob99Mcff+T2U9tVB1bsDLN79uyh2MTERLRs2TIqdob91HbVgRU7w35qu+rAip1h9vXXX6dYVuwM++krr7zC9FMydoY9cs2aNRTbq1cvUYwXs6tWrRL56Zo1a9Dly5dFfrp06VKK7d+/vyjGi1nyW0z8zdv69euRVqsV+Sn5DSIrxkv6KZmcwN+8bd68WfBTkiW/kXPkp2RqAX/z9vrrrwsrFKSfkskunGTYtm2bsEJBsmS6AH/z9tZbbzH9lPyGi/RTvEJBeiT5rZW3tzeaMGECFeMlWTIFgP10586dwgoF9tOysjIqmuvr64umTp2KPvzwQ2QwGER+Sn4Thb95+/jjj0V+WlxcTEVzWTFe7KeFhYVUNBd/8/b5558LforZ3NxcKlVF+imO/GI/vXXrFpUCwN+8ffXVVyI/vX79OhXNxUkG1ln26tWrVGKAtZKG/TQzM5M6yyqVSkk/PX36NHWWxStpZIwXs8eOHWP6KbmShv300KFDFIuTDGSMF3uk7aoDayUNs3v37qVYvJLG8lPbVYekpCTRShr2yPfee49iU1JSBD+1ZW1XHVgraX+XQI7m/nmtWbOG+o2395u5atUq1L17d67f+KVLl6LU1FQhv22Pffrpp5m7iCzNnTsX9enTR/QiZWnmzJmof//+aO3atejq1at22fvvv194kZK7iCyNHz9e2EXMysqS5BBCaOTIkcKLFO8ismS1WtHgwYNFu4hSbP/+/dGIESOoXUSWLBYL6tmzJxo1ahT1ImXJZDIhtVqNxowZQ+0istTS0oISExPRuHHj0I4dO4QXKUtNTU0oNjZWtIvIUn19PercuTOaNGkS9SJlqaamBkVHRwu7iPhFypLBYEBKpVJ4keIPMSyVlJSgyMhI0S4iSwUFBSgiIgLNmDEDffbZZ8JLl6Vbt26h8PBw9PDDD6MvvvhCeJGypNVqUXh4OHrssceooRBLmZmZKCIiQjQUYunUqVPcEZYjR45Qu934QwxLBw8eZA6FWPrmm2+EodChQ4eEly5Ln332GXMoxNLOnTuZL1KWtm/fjhISEkRDIZa2bNnCHAqxtG7dOuZQiKUXXnhBeJGSQyGWli9fzhwKsbRw4ULBT8mhEEvz5s1j7naz9Oijj6J+/fqJhkIsTZs2jbnbzdLEiRPRoEGDRLuILN17773Cbjf+EMOS1WpFQ4cORcOGDaN2EaXYAQMGCLvdeBeRJYvFgnr16iUaCrFkNptR9+7dhd1uPBRiqbW1FSUlJYmGQiw1NTWhuLg4wU/xUIil+vp61KVLF9FQiKXa2lrUsWNHNGXKFGooxFJlZSVSqVSioRBLZWVlKCoqCk2bNo0aCrFUVFSEIiIihN1ue36ak5Mj+Cm5i8jS9evXUXh4uGjIztLly5dReHi4aCjE0tmzZ5lDIZZ+/fVX5lCIpUOHDnH76b59+5hDIZb27Nkj+Ck5FGLpww8/ZA6FWNqxY4cwZCeHQixt3bpVGAo58tP169czd7tZysjIYO52s7RixQrUo0cP0VCIpcWLFzOHQiz961//Yg6FWHr88ceFIbujs+xDDz3EHAqxhNcpNmzYIAyFpDR27FjRUEhK99xzDxo6dCg1FGLJarWiQYMGiYZCUmyfPn0EP7V3ljWbzahHjx6i3e47RbwfRBXoL/y6Ni0tDZ0/f/4v+/n+rKqqqiRvyvr/hUUIQXV19W1ncX2L1I1hpMxmMzQ0NEje1kjKZDJBc3Mz141hLS0tYDKZJG9gJNXc3AwWi0XyBkZSuJZA6qZEUo2NjeDi4iJ5UyKphoYGcHNzk7wpkZTRaAQPDw/J2w9tWU9PT8kbDUnV1dWBl5cXF1tbWwvt27eXvNGQVE1NDfj6+nJFiWpqasDPz48rFl9dXQ0dOnTgZv39/bnioVVVVRAQEPCPYv8pnvO/zLaln9bW1kre1kjKYrFAfX09t582NTXZvf0Wq7W1FVpaWri811k/RQhJ3lJLqrGxERQKBZf3NjQ0gKurK5f31tfXg7u7O7ef8npvW/lpbW0t+Pj4cPspr/c666e87J3ikbL3/rPYO8VPjUYj91m2sbHxtvtpS0sLmM1mLj/9O6RQKC4ghNIccvIHUVmyZMmSJUuWLFmyZMmSdTvE+0HU8chKlixZsmTJkiVLlixZsmTJuo2SP4jKkiVLlixZsmTJkiVLlqy/VA4/iCoUCpVCoTiiUCiuKxSKawqFYuF//3mgQqH4SaFQZP/3/zoOVf9DZDAYuK86NhgMTv24/7+zCKE2Ya1WK1RUVHCxZrMZqqqquFiTyQTV1dVcbEtLC9TW1nKxzc3NUFdXx8U2NjZCfX09F9vQ0AANDQ1cbH19vbDX6khGoxGam5u52NraWmhpaeFmW1tbudiamhowmUxcbHV1NTdbVVUFZrOZi62srOS+8t4ZtqKigrumwFnWGS/7p7G8+l9l7wQ/tVgsUFlZycU646etra1t4qdNTU1t5qeNjY1crNFo5Pbeurq6NvHempoabu9tKz+tqqqS/fQOYnn1v8q2lZ8ihNrET81mM7ef3slyTU9PtwtkZGS0B4CTCKFVGRkZHwHAuxkZGT8DwFMAoEUIPZCRkREFAPekp6cftvdj7dixI33u3Lm36T+97fTxxx/Dgw8+CLm5udCuXTtQqVSSC/3vvvsuPPzww5CXlwceHh4QFRUlyb7xxhswZ84cyM/PB09PT4iKipJc6H/llVfgySefhMLCQvDy8rLLrlmzBhYtWgRFRUXg7e0NkZGRkuyqVavg3//+NxQXF0P79u0hMjJScvF+yZIl8Pzzz4NerwdfX18IDw+XZJ966il46aWXoLS01C6rUChg9uzZsHHjRigrK4MOHTpAWFiYJDtz5kx47bXXoKysDPz9/SE0NFSSnTp1Kmzfvh0MBgMEBgZCcHCwJDtu3Dh4//33obKyEgIDAyEoKIjJuri4wD333AMfffQRVFVVQXBwMAQFBTF/DVxcXGDQoEGwZ88eqKqqgpCQEMkFeYVCAf369YOvvvoKampqICwszO7Se8+ePeG7776D2tpaCA8Pl7xwBCEEGo0GDh48CEajEcLDwyUX5M1mMyQnJ8Phw4ehvr4eIiIiJBfkW1paIDExEY4dOwYNDQ0QGRkpedlTY2MjJCQkwG+//QaNjY0QFRUluUxfV1cH8fHxcObMGWhqarLLVlZWQkJCApw7dw5aWlogKipK8iKTsrIySExMhMzMTGhtbQWlUil5kUlhYSEkJSXB5cuXwWQygUqlkrzIJCcnB9RqNfz+++9gNptBpVJJXiKl1WqhZ8+eoNVqwWq1glKplGQzMzOhT58+cP36dUAIgUqlkrz05NSpUzBw4EC4ceMGAACoVCrJS09++eUXGDZsGNy8eRMUCoVd9sCBAzB69Gi4desWuLq6glKplLwg5euvv4YJEyZATk4OuLm52WV3794N999/P+Tm5gqslEfu3LkTZsyYAXl5eeDu7m6X3b59O8yaNUvwXqVSKel7mzdvhvnz50NBQYFDP127di0888wzUFRUBF5eXnb99Pnnn4dly5Zx+emyZcvgueeeg+LiYvDx8YGIiAhJduHChfDiiy9CSUkJ+Pn52fXTefPmwcsvvwylpaUO/fSRRx6BLVu2QHl5uUM/vf/++2Hbtm1gMBggICAAQkJCJD1y/Pjx8O6770JFRYVd73VxcYGRI0fCrl27oLKy0qGfDh48GHbv3s3lpwMGDIC9e/dCTU0NhIaGSl44olAoIC0tDfbt2we1tbUOvbd79+5w4MABqKurs+u9FosFUlJS4PDhw2A0GiEiIkLSe00mE3Tr1g2OHj0KDQ0Ndr23qakJEhIS4Pjx49DY2GjXe+vr6yEhIQFOnTrl0E+rq6shISEBzp49C83NzaBUKiX9tLy8nPLTqKgoST8tLi6Gbt26waVLl8BkMoFSqZT0U51OBykpKXD16lWHbFZWFqSmpsK1a9fAYrHY9d7Lly9D7969BT9VKpWSfnrmzBm46667ICsrCwDs++mxY8dgyJAhcPPmTYfsoUOHYOTIkZCdnQ0uLi6gUqkkPXLfvn0wbtw4wXvtsZ9//jlMmTIFdDodtGvXzq5H7tq1C6ZPnw65ubkO/fTtt9+GRx99FPLz8x366WuvvQZz586FgoICh2fZ9evXw9NPP811ls3IyIBnn30WioqKHPrpihUrYOXKlaDX6x366aJFiyA9PR1KSkrA19dXklUoFDB//nxYt24dlJaWOvTeWbNmwaZNm7jOp9OmTYM33ngDysvLHfrppEmT4O2333bopwqFAkaPHg0ffPABVFRUQFBQEAQHBzN/Df4OZWRklKSnp+9wCPJcrUs+APAtANwDADcAIOK//ywCAG44+nfv9PoWo9GI9Ho9ysvLQ6GhoUIvD6unr66uDun1epSTk4MCAgIE1t/fX+jpwxUXtbW1SK/Xo5s3byJfX1+qK8r2Svaamhqk1+uRVqul+knJnj58JTtmr1y5QvWT4t5Tsqevuroa6fV6dOHCBapPj+zpwxUXVVVVSK/Xo9OnT1N9eqze08rKSqTX69Gvv/5KdRmxrmSvqKhAer0e/fTTTxSLr2Qne6UwO4pfnQAAIABJREFU+/3331Nsp06dRFeyGwwGpNfr0VdffUWxXbp0EfX0lZeXI71ejz799FOKZV3JXlZWhvR6Pdq5cyfFxsfHi3r6SktLkV6vR9u3b6dY8kp2W/bVV18V9UrZ9vSVlJQgvV4v6ifFV7KT9UJ6vR7p9XpRP6ltT5/VahVYsp8UQNx7arFYBHbx4sUUa3slO8mS/aRk7ym+kt1sNgvs7NmzKdb2SnaTySSwZD8p7j0le/paW1sFdurUqQLL6ulraWkR2Pvuu09gce8peSU7yY4YMUJgyZ4+XHHR3NwssHfffbfAkj19uOKiqalJYPv06SOwuKePvJK9sbER6fV6VFxcjLp37y6wrJ6+hoYGgSX79Ly9vUW9p5gtKiqi+vTat28v6umrr69Her0eFRQUUH16rN5T7Kf5+flUn56fn5/Q02frpzqdjurTw72nZE8f9tPs7GyqT4/V04fZrKwsqk8P+ynZ04f99OrVq1Q/aUhIiKj3FPtpZmYm5aesnj7sp2fOnKH8FPf0ffvtt4L3Yj89ceIE1adH9vRhP8XsL7/8IvLT+fPno++//17kpwcOHKDYjh07inr6sJ/a9j2zek+xn3722WcUy+rpw+yuXbsoFveeHjlyRPBI7L22/aSsnj7sp1u3bmX6KdnTh/1048aNFMuqa8N/L1evXi3yU9u6NsyS/aQAIKprI72X7CcFAFFdG+mnZD+pQqEQ6tpwvRDpp2Q/KfZTsq6N9FOyn5TVe0r6KdlP6urqKqprI9kJEyZQfmpb10b66ahRoygW17XhigvST4cMGcL0U1xxQfpp//79KT+1rWsj/TQ1NVXkp2RdG8kmJSUJrJeXl1DXxvLT2NhYyntt69qwnxYWFqKOHTtSfmpb10b6aUREhMhPybo27Ke5ubkoODiY8lPb3lPM3rp1C/n7+wusv7+/qK6N9FMfHx+BZfWeYj+9du0a1U8aHBwsqmvDfnrp0iWqnxT76Zdffiny03PnzlH9pOHh4aK6Nsz+9ttvTD9lnWVt+57JujZbP7Xte46OjhbqhWz9dN++fRTLqmvDHvnFF18w/fTw4cMiP7XtJ+Wta/srBG3RIwoAnQCgAAD8AKDG5v9X7ejfv9M/iK5bt476DWU92KyHDx/ukMWHX9I8pR5s1gMHDnTI4sMvWQQt9WCz7t27t0MWH35JU5Z6sFmr1WqHLC6pJg/EUg8+/MbFxTlksVl37tzZIYvNmjw8Sz3YrMnDs9SDD7/k4VnqwWbt5+fnkMUl1aSBSz3YrElTlnpwF5wjDuAPs37ssce4WJVKxc127NgRPfLII1xs586d0cyZM7nYrl27Uh9U7T2xsbHooYce4mITEhLQtGnTuNhu3bpRBzZ7T0pKCvVh2d6j0WjQpEmTuNjU1FTqIGjvSUtLQ+PGjXPI4cPvmDFjuNh+/fpRB0ypx1k/HTRoEBo6dCgXO3jwYDRo0CCHLD78DhgwwCHbrl07dM8991BDA6kHH37T0tIcsp6enmj06NFIo9E4ZPHhlzwQSz348BsfH++QxX5KDiOkHl9fXzRlyhQUHR3tkMV+GhkZ6ZDFh1/y8Cz14EEuOYyQevDh19vb2yEbGhqKHn30UepALPXgw68jDsA5P1UqldxsdHQ0t5926tSJ+vBp7+nSpQu398bGxnJ7b3x8fJv4aXJyslN+OnnyZC62R48eaOLEiVxsz549qaGmvad3795o7NixDjk8yL333nsdsi4uLmjAgAHUsNQeO3DgQDRs2DCHLPbTwYMHO2TxIPeuu+5yyGI/7du3r0PW3d0djRw5EvXq1csh6+HhgUaPHo169OjhkPXy8kJjx45FKSkpDlk8yE1MTHTItm/fHk2cOBHFxMQ4ZH19fdHkyZOpYYTUg78Yi4qKcsiyvhj7KwWcH0S5LytSKBQ+APAlADyDEOJbxvjj35urUCjOKxSK885kuu9UtWvXDnx9fbm6wtqKdXd3d5rl6Svz8PAAX19frr4yZ1hPT0+nWZ5usz/D8nSbeXl5cbPe3t7cbPv27cHX15erg+zPsDzy8fFpM5anl9VZ1tfXl7sjqy1Zni5DhUIBvr6+XF2GzrAuLi7crKurKzfr5uYGvr6+XH2KzrDYy3h6b/8Meyd4JA+Lf9x/mp8645E8P25b+SlmeTzyz7A8csZ727dv3yYe6ayftpX38nikMyz2yNvNtpWfYtYZP+XxvbZi7wQ/bavzqTMe+WfOvW11Pr3dfopZ3j8Tf5t4Pq0CQDsA+BEAFhP/7H8umtvS0oKMRiMyGAxUNDcsLEz0lT9mS0tLqWguK77a3NyMjEYjKioqoqK5UVFRwlf+OG6F2by8PCqai+OrBw4cEOIBTU1NyGg0ouzsbCqai7/yJ+OrmNVqtVSUrEuXLmjhwoXo8OHDQtwKs5cuXaKiZKyv/BsbG5HRaERnz56lJjHx8fFoyZIl6NixY0KECrPHjx+n2G7duqHly5ej48ePCxGqhoYGZDQa0eHDhyk2OTkZrVixAp08eVLE2sZ4NRoN+s9//oNOnz4tRKgwu3fvXort0aMHev7559G5c+cEtr6+HhmNRvTJJ59QbFpaGhVfJdn33nuPYnv37o1Wr14tRKhIdtu2bQJHxlevXLkisEajERmNRrRp0yaBxVPPl19+WYivkuzatWspduDAgWjDhg3o+vXryGq1IqvVKrDPP/+8aOq5adMmIb5KssuWLRNNPbds2YJu3bolYhcsWCCaem7dulWIr1osFoElo2R46vnGG28I8VWSJSf/eOpJxlfNZrPAkpN0T09PNHbsWPT2228L8VWSHT9+PDX1HD9+PBVfJdmRI0eKpp7vv/++EF81mUwCS0ZzWfFVzNbV1VFTYdY6AMmS0VwcX/3kk0+EuFVraysyGo2otraWmt4GBASI1gEwW1NTQ30bxloHwL5XVVVFpQvwOsCXX34pxFcxW1FRQaULyHUAHLfCbFlZGZUuwH767bffivy0uLiY+jaMtQ6A2fz8fCqay1oHwL6Xk5NDRXM7duwoWgfAbFZWFuWnrPgqZq9cuUL5KWsdAHvk+fPnqSgZjq+S6wCYPXnyJOU5eB2AjK9i1jbGm5ycLFoHwB75ww8/UCxeB2D5qW2M13YdgPS93bt3UyxeBzh//rzIIz/44AOKtV0HIFlyLYK1DkB6JLkWwVoHINmXX35Z5KdkfJVk09PTKT+1XQcgPXLFihWUn+L4Kl4HINlFixZRforXAXB8lfTI+fPni/yUjK+SLPmtK2sdgGTJbzFZ6wCkR5LfIOJE1DvvvIOKi4tF7OjRoynvtV0HIP2UTEOQforjqyRLRnN9fX2FdQAcXyX9lEyBsdYBsEfW1dVRSQTWOgDpp2Q0lxVfxb5XXV1NfRuGE1F79+4VeW9FRQUVzQ0NDUWzZs2i1gEwW15eTqULWOsA2CP1ej0VzSXXAWy9t7CwkIrmKpVKNH/+fMpPMavT6ahkV3R0tGgdAHvkzZs3qSQC9tNDhw6J/PT333+nUmCsdQDse5mZmUw/ZZ1lT506RXkOax0As8eOHaPYpKQktHz5cmodAHukbYyXXAewZb/99lumn5LrAJjds2cPxdquA/ydgtsVzQUABQB8CACv2vzzjQDw7//+738DwAZHP9ad/kEUa+vWrczfeJY2btzI/Ru/evVq1KtXL2oPREqrVq0S9kDIFylLS5YsQf369aP2QKT09NNPC3sg165ds8vOmTNHtAcipZkzZ4r2QKR0//33C3sg+EOMlMaPH49GjBiBtm7dKrxIpTRq1CjRHghLVqsVDRkyRHiR4j0QKXbAgAHCHgh+kbJkNptRr1690IQJE6g9EJZMJhPq3r27aA+EpZaWFpScnIymTJlC7YGw1NjYiBISEoQ9EPwhhqW6ujoUExMj2gNhqbq6GnXp0kX0ImWpvLxciICReyAs6fV61LFjR2EPBH+IYSkvLw9FR0eLhkIsZWdnI5VKJRoKsXT16lUUHR0tGgqxdOHCBWGvjhwKsfTbb78x90BY+uWXX5hDIZZ++OEH7j2QL7/8EiUkJIiGQix98sknwlCIfJGy9N577zGHQixt27YNaTQatGrVKupDDEubNm1iDoVYWrt2LXMoxNJzzz3HHAqxtGzZMsFPyaEQSwsXLhSGQo78dN68eWjQoEHUUEhKjz76qGgoJKVp06aJhkJSmjhxomgoJKXRo0eLhkIsWa1WNGzYMDR69Gi0fft24UOMFDtw4EDRUIgli8WC+vTpIxoKsWQymYQIJTkUYqmlpQWlpKQIfoqHQiw1NTWhxMRE0VCIpfr6ehQXF4emTZtGDYVYwkMf26EQSxUVFahTp06ioRBLJSUlqGPHjqKhEEsFBQUoOjpaNBRi6datW9x+qtVqkUqlEg2FWLp48aKwV0d+iGHp1KlTzDsiWDpy5Ai3nx48eJA5FGLpm2++EYbs5FCIpc8++4y6I8KeR37wwQfMoRBL27dvZw6FWNqyZQvq0aOHaCjE0ssvvyy6I0JK6enpzKEQSytWrGAOhVhatGgRcyjE0vz580VDdinNmjVLNBSS0vTp0wU/xUMhKU2ZMkU0FJLSuHHjREMhlqxWK7rnnntEQyEp9u6770Zjx46lhkJ3ing/iCr+YKWlUCjuAoDjAHAVAPAd1ysB4AwA7AGAaPhjb3QqQshuJ0ZaWho6f/683Z/vTlBdXZ3kbXcy+//GIoTAaDRys/X19VzRJ6vVCo2NjVyxI7PZDC0tLVyxI5PJBGazmSua09raClarlSuag6/Y54lLNDc3g4uLC1cspqmpCdzc3LiiLo2NjeDu7s4VSXGGbWhoAE9PT66YSX19PXh7e3PFTNqKNRqN4OPjwxXbayu2rq6OOzr4d/8dltk7h70T/NRisUBzczOXn5rNZmhtbeWKUDrjvS0tLYAQ4vJeZ/3U1dX1b/VeZ/3Uy8vrb/XeO8Uj24r9p3iDzDrPtpWfOsO2lZ/+HVIoFBcQQmkOOUcfRG+n/ikfRGXJkiVLlixZsmTJkiVLlvPi/SDKfVmRLFmyZMmSJUuWLFmyZMmSdTskfxCVJUuWLFmyZMmSJUuWLFl/qeQPogzp9XrgjSwXFxf/41hetQWLEHKK1ev1XKzVaoWSkhIu1mKxQGlpKRdrMpmgrKyMi21paQHeiqLm5maorKzkYhsbG6G6upqLra+vh5qaGi7WaDRCXR1fE1NtbS0YjUYutqamBhoaGrjY6upqaGxs5GKrqqqgqamJi62oqIDm5mYu1mAwCDu7jlReXg6tra1cbFlZGZhMJm7WbDZzsaWlpdxsSUkJWCwWbtZqtToG4Q+PdIa9E3xP9tO28V6LxcLtvWazmdtPW1tb28xPq6rsXmchqKGhwSk/ra2t5WLr6uqc8tP6+noutrq6mtt7nfHTyspKbj+tqKjg9lODwcDtp+Xl5X+7n5aWljrlp7yss376v+y9vPq72TvhLGs2m7nPsneyXNPT0/+yn2zHjh3pc+fO/ct+vj+rL7/8EsaNGwc3b94EAACVSiV5AcGnn34KkydPhuzsbHBxcQGVSiV5AcH7778P06ZNg5ycHHB1dbXLvvnmm/DII4+ATqeDdu3agVKplLyAYPPmzTB37lzIzc0Fd3d3u+xLL70ETz31FOTn54OHhwcolUrJCwiee+45ePbZZyE/Px88PT0hKipKkl26dCmsWLECCgsLwdvbGyIjI5msQqGAp59+Gl544QUoKiqC9u3bQ2RkJPOiAIVCAbNnz4a1a9eCXq8HHx8fiIiIkGRnzJgBmzZtAr1eD76+vpKsi4sLTJkyBbZu3QqlpaXg5+cH4eHhkuzYsWPhrbfegrKyMvD394fQ0FAm6+rqCsOHD4edO3eCwWAAf39/CAkJkfxxBw4cCB9//DFUVFRAYGAgBAcHS7J9+vSBPXv2QEVFBQQFBUFwcLCIw78Oqamp8PXXX0NVVRWEhIRAYGAgk0UIgVqthv3790N1dTWEhoZCQEAAk7VYLNCtWzc4ePAg1NbWQlhYGPj7+zPZ1tZWiI+Ph8OHD0NdXR2EhYVBhw4dmGxTUxPExcXB0aNHwWg0QkREhORFAUajEWJjY+HEiRNQX18PkZGRksv/VVVVEBcXB6dOnYLGxkaIiIiQvHilrKwM4uPj4ezZs9DU1ASRkZGSFwUUFhZCYmIiXLhwAZqbmyEqKkryogCdTgfJyclw8eJFaGlpAaVSKXnxyvXr10Gj0cCVK1egtbXVLnvx4kXo1asXXL16FcxmMyiVSslLWk6fPg39+vUDrVYrsFIXZB09ehTuvvtuuH79OlitVlCpVJKXtBw8eBDuueceyMrKAoSQXfabb76B0aNHw82bN0GhUNj1088//xwmTJjA5acffPABPPjgg3Dr1i2HfvrWW2/Bww8/DDk5OeDm5gYqlUrSI1999VWYPXs25ObmQrt27eyyL7/8MsyfPx/y8vLAw8MDoqKiJNn09HR45plnoKCgQGCl/PTf//43LFu2DAoLC8HLy0uSVSgUsHDhQnj++eehqKjIoffOmzcP1qxZA8XFxQ799JFHHoENGzYIfmrPIx944AF49dVXufx0/PjxsH37digtLYUOHTpAWFiYJDtixAh47733oLy8HAICAiT91NXVFe6++2746KOPwGAwOPTTfv36wWeffQaVlZUQGBgIQUFBkmxqaip8+eWXUFVVBcHBwRAUFCTisDQaDezbtw+qq6vteq/VaoVu3brBgQMHoKamxq6fmkwmSExMhJ9++smhnzY3N0NcXBwcOXIEjEYjhIeHS/ppfX09xMbGwvHjxwXvlfLTmpoaiI2NhZMnT0JDQwNERkZK+qnBYIC4uDg4e/YsNDY2QlRUlKSf6vV6SEhIgPPnzzv009zcXEhKSoKLFy86ZG/cuAFqtRouX77s0E8vX74MPXv2hKtXr4LJZAKVSiXpp2fPnoW+ffvCtWvXwGKx2PXT48ePw8CBA0Gr1Tr000OHDsHw4cO5/HTfvn0wevRouHHjBgDYP5/u2bMHxo8fD9nZ2Q6996OPPoKpU6cKfqpUKiX99J133oHp06eDTqdzyL7++uvw2GOPCX5q73y6YcMGeOKJJyAvL8/hWfbFF1+EBQsWcJ1PV65cCUuXLoWCggK7fgoAsHjxYvjPf/4DRUVF4OXlZddP//Wvf0FGRgYUFxc7PMs+9thj8PLLL3OdZadNmwabN2+GkpISh346YcIE2LZtG5SVlYGfn5+kn/4dysjIKElPT9/hEOS5Wvd2PXd6fUt1dTXS6XTo5s2bVO+dl5eXUN+Br5CvqqpCOp0OXb9+neq9wx2EZH1HZWUl0ul06Nq1a1TvnY+Pj6i+o6KiAul0OnT58mWq987Pzw9NnTqVqu8wGAxIp9OhzMxMqqepQ4cOQn0HvkK+vLwc6XQ6dObMGaqnyd/fX1TfUVZWhnQ6HTpx4gTVe8fqwSotLUU6nQ4dOXKE6mkKDg4W1XeUlJQgnU4n6lMKDQ0V6jvwFfJ6vR7pdDr03XffUWx4eLiovqOoqAjpdDpRNyjuwSKvmy8sLEQ6nU7UDapUKoX6DnyFfEFBAdLpdKJuUHzd/IEDB4Qr5PPz85FOp0NvvvkmxbLqO/Ly8pBOp0NbtmyhWNyDdfjwYeEK+dzcXKTT6aguOwB2p6tOp0M6nQ5lZGSIerDI+g6r1SqwK1eupFjb+g6LxSKwixcvpljb+g6z2SywTz75JMXa1neYTCaBnT17NsXa1ne0trYK7MyZMyk2LS0NZWRkCNfNt7S0COz9999Psbb1Hc3NzQJL9ogqFArUr18/qtO1qalJYEeNGiWwZKcrru9obGwU2CFDhlCs7XXzDQ0NAkv23pGdrrgOqb6+XmB79uwpsG5ubmjYsGFUfQfub8vJyUHJyckCS3a64ivka2trBZbsvSM7XXEdUk1NDdLpdOjWrVtU7x3udN2+fbtQh0T6Kdl75+XlJdR34Dok7KdZWVlU7509P9VqtVTvHdnpauunV65coXrvfH190ZQpU6hOV+ynFy9epPyU1emK/fTs2bMiP8WdrrZ+evLkSar3LjAwUKjvsPXTY8eOMf2UrO/AfvrTTz9Rf85Zna7YT/fv30+xZKcr9tPi4mKk0+nQV199RbGsjmzsvbbdoKxOV+y9tt2gpJ/aeu/bb78t8lPb+g7svVu3bqVYXN9Bdrpi792wYQPFsuo7sPeuXr2aYuPj40Wdrvjv5apVqyjWtr6D9NOlS5cy/RTXd5B+SvYyA4g7XUk/JXuZsZ+S9R2kn5K9zAAgqu8g/fTBBx+kWNv6DtJPyR5RVkc26adkjyir05X002HDhjH9FHe6kn46YMAAyk9t6ztIP+3Vqxflp0OHDqU6XUk/VavVlJ/i+g5ch1RXVyew8fHxTD/FdUjYe2/duoU6d+5M+altfQf23uzsbBQVFSWwuCObrO/A3nvjxg0UGhpK+SnudLU9y2q1WhQQEED5qW2nK/beq1evIl9fX4FldWRjP7106RLy8vKi/BR3utr66fnz55G7uzvTT/FZFvvpqVOnqA5nVqcr9tNff/2VOsvijmzyLIv99Oeffxb5Ke50tfXTAwcOSPopPstiP/3mm29Efoo7XW399PPPP2f66XfffSfy0127dlGsSqUSdbr+XYLb1SN6O587/YPounXrqN9Qqadnz55UUb29p3fv3mjgwIEOOWzW5GFU6sGH3969e3OxAwcOpA6uUg8+/Go0GocsNmvykCv14MNvQkKCQxabdUxMjEMWH37JA7HUgw+/pIFLPdisSQOXevDhNzAw0CHr6+uLJk+eTBm41IMPv+SBWOrBZk0ecqWewMBAqpjc3hMUFCQ6fEg9ISEh3GxYWBh64IEHuNiIiAjRB0qpJyoqCk2dOpWLValUaPLkyVxsp06d0KRJk7jYLl26oAkTJnCxMTEx1Adge098fDwaO3YsF5uYmIjGjBnDxSYlJVEfrO09arUajRgxgovt3r07dWi09/Ts2RMNHjyYi+3Vq9dt91N8+O3Tp49D1sXFBd11110oLS3NIYsPvz169HDIOuunw4cPR4mJiQ5Zd3d3NGLECGrAIPXgwy95IJZ6PD090ZgxY5BKpXLIYj8lh7tSDz78ksNdqQcffv38/Byy+PDr7e3tkMWDXHLAIPXgw68jDuAPP+X1Xmf8NDQ0lNtPw8PDudnIyEin/HTKlClcbMeOHbn9tHPnztSHWntP165duf00Li4OjRs3jotNSEhwyk/vvfdeLjYlJcUpPx0+fDgXm5qaSg1A7T1paWlo0KBBDjmFQoH69OmD7rrrLi62X79+qG/fvg5Z7KfkIEDqcXV1RYMGDeL20yFDhlBDA3vssGHDULdu3Ryy+CwbFxfnkPXw8ECjRo1CXbp0ccg646f4izFyuCv1kINce33JbSXg/CAq74g6qfbt20N0dLRkNIaUj48PqFQqru4gX19fUKlUXL1tzrAdOnSA6Ohorp4hf39/UKlUTrE8vW0BAQHcbGBgIKhUKq5+zeDgYLsRFhbL0/EWEhIC0dHRXGxoaKjd6N6fZcPDw0GlUnFFLCIiIiA6Otohh1mVSsXFRkVFgVKp5GajoqK42cjISC5WqVRCRESEQ06hUIBSqYTw8HAuVqVScbEuLi6gVCohNDTUIYvjoSEhIQ5ZHA+ViliTwvFQHtbd3R1UKpVkJJCUh4cHREdHc7Genp6gUqkko9ukvLy8QKVSSUYNSXl7e4NKpXLKT3k63pzxXj8/P6f9lKfjrUOHDk77KU9nprN+Gh0dzeWnQUFBbeKnznqvvYg1qbCwMG4/xawzfsrL8vppZGQkt59GRkZy+6lSqXSK5fVTXo90xntx3D4sLMwhi/30TvBee3FsLGe99+/2U3yWbQs/jY6O5vJT7L08fuoMi73XGT/lYbGfOnOW5fHTtvLe0NBQiI6O5n5v/m3i+bR6u547/RtRHHGpq6ujprfR0dHoySefpKJDmK2urqamt6woptlsRiaTCRkMBiqai6NDhw8fFqJDmC0pKaGiuawoJmYLCwupb85so5gkm5OTQ016baOYJHv9+nUqzpCSkkJFMUn28uXLVJTMNopJsmfPnqWmNrZRTIQQMplMyGQyoePHj4smeGQUk2TJiBqe4JFRTJIlI794grd27VohOkSyX3zxBTXBs41ikuxHH31EsYMGDaKimCT7zjvvUNM+HMXE0SGSff3110UTPDKKSbIbN24UTfC2bt0qRIesVqvAkrEzd3d3NGrUKCo6RLL/+c9/qGkfjmLi6BDJPvvss9S0D0cxcXSIZMkYLznBw9Ehkn388ccFloxi4ugQyU6fPl1gcRRz165dwmSQZMkJPSuKSbJklAxH28noEPYGk8mEhg4dKrABAQFCFBNHhzDb2tpKRcmCgoJEUUySJRMOrCgmZltaWqhv2cLCwtDjjz9ORYcw29zcTH1zxopiYraxsZFKIrCimJg1Go3U9FalUomimJitqamhorkdO3YURTGxj1RUVFDRXHt+WlpaSkVzWVFMzBYVFVF+Gh8fj5YsWUJFMTGbm5tL+SkZxbRlb9y4QaUWbKOYJHv16lXKT22jmCR7/vx5pp/iKCbJ/vbbbxRrG8UkfcQ2ota7d28qikmyP/zwA+WntlFMkiUjv6woJsmSKxSsKCbJkisU2E/JKCbJbtu2jfLToUOHoi1btghRTJLdtGkT5ac4ipmTkyNiX3rpJcpPcRQTx+BJH3nuuecoP7WNYpIsGeNlRTFJ9umnn6a+PbGNYpLsnDlzRH5KRjFJllyLIKOYOAZPsuQ3qWQUE68VkSz5zWSHDh1EUUzST++55x7KT22jmCRLJidwFHPPnj1CFJP0U/IbueDgYFEUk2TJb9lCQ0PRrFmz0FdffcX0UzKaGx4eLkQxcQye9FMyiUBGMW29t76+nkp2saKYmK2traWSXdhPDx48KPLTqqoqKprbuXNntGDBAipA+pK/AAAgAElEQVTajtny8nIq2YXXin7++WeRn+r1eiqaGxcXJ0Tbbdm8vDwqmpuYmIiWLl2Kfv31V5GfZmdnU9HcpKQk9O9//5t5lr127Rp1llWr1WjlypXo1KlTIo+8ePEi5Xvdu3dHzz33HDpz5oyIPX36NMWmpqaiF154AZ0/f150lj169CjF4mh7ZmamyMsOHjxIeWSfPn3QmjVr0OXLl0UsGfkl/fTq1asC+3cJ5Gjun9frr78uvEjJ33iWNm7cyHyRsrRmzRo0cOBAtH79eupFytJzzz0n7DRkZWXZ/e9dtmwZGjJkCLXTIKUFCxYwX6QszZs3D40YMQK9/vrrwotUSo8++qjwIsX7ZFKaNm0aGjNmDPUildKkSZPQfffdh3bs2CHsk0lpzJgxop0GlqxWKxo+fLjoRSrFDho0SPQiZclsNqN+/fqhBx98kNrPZclkMqFevXoJL1K8T8ZSc3Mz6t69u2g/l6WGhgaUkpIiepGyVFdXh7p164Yee+wx6kXKUlVVFUpISBC9SFkqLy9HcXFxaO7cudSLlKXi4mIUGxuL5s+fj77//nvhQwxLeXl5KCYmBj355JPUi5SlGzduoJiYGLRgwQJ06NAh4UXK0tWrV1FsbKzoRcrS+fPnhR0xcijE0okTJ1BCQoLoRcrSzz//jJKSkkRDIZb279+PUlJSRC9Slvbu3Yu6d++OVq1aRb1IWfrkk0+YL1KW3nvvPWEoRL5IWXrzzTeFFyk5FGJp8+bNwlDI0Yt07dq16K677kLr16+nhkIsvfDCC2jQoEFo48aNDv10+fLlgp/i/VwpPfPMM2jYsGHo1VdfpYZCLM2fPx+NGDGCGgpJadasWWjUqFFo27ZtwlBIStOnT0djxoyh9nOlNGXKFOG+A0d+Om7cONF+LktWqxWNHDlSdN+BFDt48GBhKGTPTy0WCxowYIBw3wEeCrFkMplQ7969RfcdsNTS0oJSU1PRjBkzqKEQS42NjUitVovuO2DJaDSipKQk4b4De95bXV2NEhISRPcdsGQwGAQ/JYdCLOn1ehQbGyvcd2DPT/Pz81FMTIxoKMRSdnY2iomJEQ3ZWbp27RqKiYkRDYVYyszMRHFxcWjx4sXUUIilkydPMofsLB05ckQYsuP9XCkdOHBAdN+BlL7++mvmkJ2l3bt3M4fsLO3cuZM5ZGdp+/btovsOpPTqq6+K7juQ0vr165lDdpYyMjJE9x1IaeXKlcwhO0uLFy9mDtlZevLJJ0VDdinNnj1btJ8rpZkzZ4qG7FK6//77RUN2KU2YMAGNHz+eGgqxZLVa0ahRo0RDdil26NChovsO7hTxfhBV/MH+NUpLS0Pnz5//y36+P6umpiaur+ll1nkWIQTNzc23nbVardDa2soVmbBYLGA2m7niamazGaxWK1dkAl8tzxOZMJlMoFAouCJora2t4OrqyhVBa2lpATc3N262Xbt2krfHkWpubgZ3d3du1sPDgyva1tTUBJ6env8o9p/yd01m//fZtvJThBC0tLRw+anVagWTycTlpxaLBSwWC5efms1mQAi1iZ+6uLhwsbKftj37T/m7JrMyS6ot/dSZsyyvn/4dUigUFxBCaQ45+YOoLFmyZMmSJUuWLFmyZMm6HeL9ICpfViRLlixZsmTJkiVLlixZsv5SyR9EZcmSJUuWLFmyZMmSJUvWXyr5gyhD+fn5YLFYuNi8vDywWq23nc3NzQXe2HRbsTqd7razCCHQ6XRcPyZCCHJzc7lYq9UKeXl5XKzFYoH8/Hwu1mQyQWFhIRfb0tICxcXFXGxTUxOUlJRwsQ0NDVBWVsbFGo1GMBgMXGxdXR1UVFRwsTU1NVBVVcXFVlVVQU1NDRdbWVkJtbW1XKzBYACj0cjFlpeXQ319PRdbVlYGDQ0NXGxJSQk0NTVxsXq9Hpqbm7nY4uJiaGlp4WKLioqgtbWViy0sLBR2lx2poKAAzGbzbWed9dO28N7c3Nz/We/l9Uhn/BQh1CZ+ajaboaCggIttbW2FoqIiLra5uRn0ej0X29jYCKWlpVxsfX09lJeXc7HO+mllZSUXW11dDdXV1VysM35aUVEBdXV1XGxb+WlpaSk0NjZysc54r7N++k/yXmf8VD7L/iFn/fSfcpZ1xk/vZLmmp6f/ZT/Zjh070ufOnfuX/Xx/Vt9//z0MHz4crl27BhaLBZRKpeRFDHv37oXRo0fD9evXwWq12u0C+vjjj2HChAmQlZUFCCG77HvvvQf3338/3Lx5EwDAbm/Qtm3bYMaMGZCdnS30HkqxmzZtglmzZkFOTo7Q6SV1acNLL70E8+fPh5ycHKF7S+rShlWrVsHChQshNzcX2rVrB0qlkskqFApYsmQJLF26FPLy8sDDwwOioqIk2aeeegpWrVoF+fn54OnpCVFRUcwLHhQKBTz++OPw4osvQmFhIXh5eUmyLi4uMH36dFi/fj0UFhaCt7c3REZGMllXV1eYNGkSbNmyBYqLi8HHxwciIiKYFzG4urrCvffeC2+++Sbo9Xrw9fWF8PBwJuvm5gZDhgyBd955B0pLSx2y/fv3h127dkFZWRl06NABwsLCJP8bevXqBZ9++imUl5eDv78/hIaGMlmFQgEajQa++OILMBgMEBgYCMHBwUwWIQTJycnwzTffQGVlJQQGBkJQUBCTtVgsEB8fD99//z1UVVVBcHCwZA9ba2srxMXFwY8//ghVVVUQEhIi2cPW1NQEMTEx8PPPP0NNTQ2EhoZK9rDV1dVBTEwMHDt2DGprayE8PFyyW62qqgpiYmLgxIkTYDQaITw8XLJzq6ysDGJjY+HUqVNgNBohIiJCslutoKAA4uPj4ezZs9DQ0ACRkZGS3Wo5OTmQmJgI58+fh8bGRoiKipLsS7t27Rqo1WrIzMyE5uZmiIyMlGQvXrwIqampcOnSJWhpaYGoqCjJXsuTJ09C37594cqVK9Da2gpKpVLyIoZffvkFBg0aBFevXgWTyWS31/LAgQMwbNgwuHbtGpjNZrs9wV9//TWMGjUKtFotWK1Wu967e/duGD9+PGRlZTn03g8++ACmTJkCN27cAAD7frp9+3aYPn06ZGdnC32KUuyWLVvgscceg1u3boGrqysolUpJP123bh3MmzdP8FN77AsvvABPP/005ObmCqyU9y5fvhyeffZZyM3NBXd3d7veu3DhQlixYgXk5+eDh4cHKJVKST+dM2cOZGRkQEFBgUM/nTlzJqxbtw6KiorAy8tL0k9dXFxgypQpsGnTJiguLob27dtDZGQk00dcXFxg7Nix8MYbb4Ber3fovcOHD4e3334bSkpKwM/PT9JPXV1dYeDAgbBz504oKysDPz8/ST91cXGBPn36wMcff8zlpz169IA9e/ZAeXk5BAQEQEhIiOSlPSkpKfD1119DRUWFXe+1Wq2QmJgI3333HVRWVtr1U5PJBHFxcXDw4EGorq6G4OBgu34aGxsLhw8fhurqart+ajQaoWvXrnD06FGora2FsLAwyV7L6upq6Nq1Kxw/fhzq6ursem95eTnExMTAyZMnBT+V8t7i4mKIi4uDM2fOQENDg13vzc3NhcTERDh37pxD783KyoKUlBS4cOECNDU12fVe0k+bm5tBqVRK+umZM2egT58+cPnyZWhtbYWoqChJPz127BgMGDAArly5AiaTCZRKpaSfHjp0CIYMGQK///47mM1mu+y3334LI0eOFM6y9rz3888/h3HjxsH169cBIQRKpVLST3ft2gWTJ0+GrKwsALDvpzt27IAHH3yQ6yy7detWePjhh4WzrL3z6YYNG2D27NmQk5Mj9MhKsRkZGfDUU0+BTqezez4FAFixYgUsXrwY8vLyHJ5lFy1aBMuXL+fy0/nz58Pzzz/PdZZ99NFHYc2aNQ7Ppy4uLvDAAw/Axo0boaioyK6f/h3KyMgoSU9P3+EQ5Lla93Y9d3p9i8FgQFqtFl29epXqEcVdjK+99ppwTXR5eTnSarXo8uXLVI8o2R2Gr4kuKytDWq0WZWZmUj2irO6wkpISpNVq0blz56geUVYXo16vR1qtFp0+fZrqvfP29hZ1hxUXFyOtVotOnDhB9d6xuhgLCwuRVqtFR44coXrvfH19hcoTfE10QUEB0mq16NChQ1TvHe5i/PDDD4Vr9/Pz85FWq0X79++n+pT8/f2F7jB87X5eXh7SarVU5xxIdIfpdDqk1WrR7t27KZbsDsPX7ufk5CCtVot27dpFsbiLkaw8uXXrFtJqtWjHjh0UGxYWhmbNmkV1Md68eRNptVqq7xPgjy5GXHmCr92/ceMG0mq16JVXXqFYsjsMX7uflZWFtFot1U8HEt1hWq0WabVa9Pzzz1Nsp06dqC5Gq9UqsMuXL6fYLl26UN1hFotFYBctWkSxuIsRV56YTCaBnT9/PsWS3WG4jw2zs2bNoljb7rCWlhaBnTFjBsXi7jDcxdjU1CSwZJcdwP/tYsSVJ42NjQJ73333MbvDcBdjQ0ODwI4aNYpie/bsKVSeWK1WVF9fL7CDBw+22x1WV1cnsP369bPbHVZbWyuwZI8oq4uxpqZGYMkeURcXF6HyBFdIVVVVIa1Wi65du4bi4uIE1tXVVVQhVVlZKbCdOnUSWDc3N1GFVEVFheCnZI8o7mJ89dVXhQop0k/JHlF3d3ehQsrWTy9evEj1iLL8tLS0FGm1WnT+/HmqR9TT01NUIYX99MyZM1TvHe5i3LFjh8hPf/vtN5Gf4gopXHlSVFSEtFotOnr0KOWnPj4+osoT7Kc//fSTyE9tK6Swn5IdngB/dDHiyhNcIYX9lOycs/VT7L25ublIq9WiPXv2UGxgYKCoQgr76YcffkixuIuRrDzBfvruu+9SbGhoqKhCKjs7G2m1WqrvE+D/djGSlSfYTzdv3kyxkZGRQoWUrZ+uW7eO6afff/+94KfXr19HWq0WZWRkUGzHjh1FFVL479qKFSsotnPnzkLlia2fLl68mGJxF+Phw4dRa2srMpvNAvvUU0+J/JTsFSf9lOwGBQBRhRTppw8//DDF2vaKNzc3C+wDDzxAsbhCCleekN47YcIEisWVJ7hCivTTe++9l2JTU1OpyhPST4cNG0axthVSRqNRYO+66y6mn+LKE9JPyR5RslccV0iRfkr2iGI/JStPqqurBY8ke0RdXV2FCilceUL6Kdkjiv1006ZNQoUU9tPff/+d6hHFveKkn+Kz7JUrV6geUbJXHFfyYe+9dOkSCgwMpPwUV0jhSj7spxcuXKB6RD09PYXKE1whhc+yZ8+eFfnpuHHj0Ntvvy1USGHvPXnyJNUjSvaK2/rpr7/+SvWIsvwUn2V//vlnqkeU7BXHfoq998CBA0w/JXvFsZ/u27ePYnGvOFkhhf2U7KPHfop7xbGf4rMs2Z+M/dS2Qgr76fvvvy/yU9wrbq+S768QyD2izsv25ST1JCUlUeXz9p6UlBTqgGnv6d69O+rduzcXm5qailJTU7nYtLQ0pNFoHHLYrMmDqz22X79+KDEx0SGLzTo2NtYhi826S5cuDlls1iqVyiHbrl07NGzYMOpALPXgw29ISIhDFps1WQQt9eDDL3kglnqwWXt4eDhksVmTh1ypx8fHB02cOJHrz42vr6/oQCH1dOjQgZv19/dH48eP52IDAwO52eDgYKoc3d4TGhrKzYaHh6MxY8ZwsZGRkWj06NFcrFKpFB3CpJ7o6Gg0YsQILrZz585U8bu9p2vXrqLDndQTGxuLhgwZwsXGx8ejQYMGcbHdunWjDo32nuTkZG4/1Wg0qE+fPlxsjx49UFpaGheblpaGunfvzsX27t0bpaSkOOSc9dMBAwZQQwOpxxk/dXV1RYMHD0YdO3Z0yLq5uaGhQ4dSB2KpBx9+w8LCHLJ4kEseiKUefPj18/NzyHp5eaGxY8dSB2KpB/speciVevAgl+fPgq+vLzfr5+fnlJ/yss74aVBQkGhAJ/WEhIRw+2lYWBi3n0ZERHD7aVRUlFN+OnLkSC62U6dO3H7apUsXbj+NiYlxyk/vvvtuLjYxMRENHDiQi01OTkb9+/fnYtVqNerbty8X2717d24/7dmzJ+rRowcX27t3b2oQIPUoFArUt29flJSUxMX279+fGhpIPS4uLmjgwIEoJibGIYsHueTAVurBfqpUKh2yeJBLflkm9WA/ff311+12QbeVgPODqLwjSkihUDjsa/T39we1Wg0REREO2cDAQNBoNBAWFuaQDQ4OBrVaDSEhIQ7Z0NBQ0Gg0EBwc7JANCwsDjUYDQUFBDtmIiAjQaDQQGBjokI2KigKNRgP+/v4OWaVSCRqNBjp06OCQValUoNFowNfX1yEbHR0NarUafHx8wNXV1W4nW6dOnUCj0UD79u0dsl26dAG1Wg1eXl4O2a5du4JGowFPT0+HbExMDKjVavDw8HDIxsXFgUajgXbt2jlk4+PjQaPRCL9e9tiEhARQq9VcbGJiIqSkpAisVNxDoVBAt27dIDk52SHr4uICSUlJ0K1bNy42OTkZ4uPjHbKurq7crJubG6SkpEBMTIxDtl27dtysu7s7pKSkQNeuXR2yHh4eoFaroXPnzg7/nHt6eoJarYZOnTo5ZL29vUGtVkN0dLRDtn379qBWq4XIvT3W19cXNBqNEKO3x/r5+YFGo4HIyEguP9VoNBAeHu6QDQgI4GaDgoJAo9Fw+WlISIhTfqpWq7lYZ/w0MjIS1Go1BAQEcHsvj58qlUpQq9Xg5+fnkO3YsSNoNJo28VONRtMmfqrRaMDd3d0hGxsb65SfqtVqoT/UkZ864708Hvln/DQxMfG2sn/GT+Pi4rj9NDY2lstP1Wq1U37apUuX2+qnXl5eoFaroWPHjtx+yuO9Pj4+oNFohNjn7fLTDh06gEaj4TqfBgQEgFqtdspPQ0NDuc6yvN7rzFk2PDwc1Go1l59i7+U5nzp7luX10+joaO6zbMeOHUGtVnP5aefOnUGj0YC3tzeXn6rVauHX+I4Vz6fV2/Xc6d+IYjU0NFDTW9tYIana2lpqepuYmIiWLVsmxGBIVVZWUtNb21ghqbKyMuTt7U1No1auXCnECkkVFRVR35zhWCGOwZDKzc2lJr2pqalUrJDUjRs3qDiDbayQ1JUrV6gJk22skNS5c+dE06h169YJMRhSx48fp6ZRtrFCUocPHxZNo8hYISkyHsyKFZIiIxV4GvXaa68JMRhSH330ETWNwrFCHIMh9c477wgsjhWSMRhSZOSXjBXiGAypjRs3Ciz+ZnXHjh1CDIbU6tWrBdbb21sUKyS1cuVKgWXFYEiRsTNfX19RrJDUv/71L4FlxQpJkTFeHCskYzCkHnroIYFlxQpJTZo0SWBZsUJS5NSdFSskRU68WbFCLKvVSn3TR8YKcaSbZMkJslKpRE888QT6/vvvhQgilsViQd26dRPY6OhoIVaII4hYJpMJde3aVWA7depExQpJtbS0UEkEHCv8+eefRWxjYyM1vY2NjaVihaSMRiO16oBjhceOHRP5aXV1NbXqYBsrJGUwGKhVB9tYISm9Xk+tOtjGCknl5eVR0VzspzhWSCo7O5tKLdjGCkn9/vvvQjQX++nq1auFWCGpzMxMyk9tY4WkTp48SfnpgAEDqFghqV9++YXyUxwrzMrKErFkPNj1v9+skrFCUuS6BRkrvHXrloj99NNPKe/FsUK8IkOKjKi5u7sLsUIc6SZFRn49PDxEsUJSmzZt4vZTcoWCFSsk9dxzzwls+/bt0aRJk6gVGVJLly6l/NQ2Vkjq6aefFli8IkPGCknNnj1bYFmxQlLkWkRAQIAQK8QrMqSmTJkisEFBQaJYIamxY8cKLF6R+fLLL4UVGVLDhw8X2LCwMPT4449L+imZWouIiEBz5sxB+/btY/opueoQFRWFnnjiCbR//36mn5KJMZVKhf71r3+hAwcOMP2UTC1gP8UrMqRaWlqob866dOmCFi5ciA4fPizy06amJhQZGSmweEXml19+EflpfX09teoQHx+PlixZwvTTmpoaatWhW7duaNmyZej48eMij6yoqKCSXcnJyWjFihVMPy0pKaGSCHhF5vTp0yKPLCgooKK5PXr0oGLapHJycig/7dmzJ0pPT0cXLlwQ+ZNWq6VWHXr37o1Wr16NLl68KGIvXrxI+Wnfvn3RSy+9hK5cuSJiT58+zfRTvCJD6ujRoxQ7cOBAtGHDBiGmTerHH38U+ekrr7yCbty4gWxFrlvgb1a3bNnCPMv+1QI5mvvntXXrVru/8aQ2bNgg/MazXqSkVq9ebfdFSmrVqlWiXVMpLV26FI0ePZrajZLSggULRLumUpo3b55o11RKjz76qGjXVErTpk0T7ZpKafLkyXZfpFhWqxWNHTtW2DVlfYgh2ZEjR6Lp06dTu6YsWSwWNHjwYNGuKUsmkwnddddddl+kWC0tLahv376iXVOWmpqaUFpaGpozZw61a8pSfX096tGjB5o3bx7zRUqqpqYGaTQa0a4pSxUVFSglJYXaNZVSSUkJSkpKonZNpVRQUICSkpIkX6SkcnJyUFJSkuRQiNT169dRcnKy5FCI1KVLl1BycrLkUIjUmTNn7L5ISR07dky0ayqlQ4cOCS9S1lCI1L59+4ShEOtFSuqLL75Affv2lRwKkfrwww9Fu6ZSeuedd9DAgQMlh0Kk3njjDWEo5MhPN23aZHcoRGrt2rV2h0KkXnjhBbtDIVLLly8X7ZpK6ZlnnhHtmkpp/vz5gp+yPsSQmjVrljAUcuSnM2bMQJMnT5YcCpGaOnWq3aEQltVqRffddx968MEHJYdCJDtq1CjR7j5LFosFDR061O5QCMtsNqNBgwahRx55BO3du9eu97a2tqJ+/frZHQphNTc3o169egm7+7YfYkg1NDSg1NRUyaEQqdraWm4/raysRCkpKaJdU5bKyspQcnIyWrBgAXMoRKqoqAglJSUJQyF7fqrT6QQ/ZQ2FSGVlZaGkpCRq11RKV65cQcnJyZJDIVLnzp2jhuz22BMnTtgdCpE6fPgwNWS3x+7fvx/16tVLcihE6ssvv7Q7ZCf1ySef2B0KkXr//feFITtrKERq+/bt1FDInjZv3iz4KWsoRGrdunV2h0Kk0tPT0YgRI6hdUymtWLFCtGsqpcWLF9sdCpF66qmn7A6FSM2ePRtNmDBBcihE6uGHH7Y7ZCf1wAMP2B0KkZo4caIwZHd0lh09erTdoRDJDh8+nMtP/w7xfhBV/MH+NUpLS0Pnz5//y36+P6vW1lbJ28Jk9v+NRQiByWS67azVagWLxSJ5G5sta7VaJW9YI4WvPrcXq8Aym81CvJuHdXFxsRurwDKZTA4jGCTr5ubGdWtaa2srtGvX7h/F/lP+nMuszN5prLPeazab28RPEUJc7D/NT/+J3vtP+bMrszJ7p7Ft6ae8Z1ln/PTvkEKhuIAQSnPIyR9EZcmSJUuWLFmyZMmSJUvW7RDvB1H5siJZsmTJkiVLlixZsmTJkvWXSv4gKkuWLFmyZMmSJUuWLFmy/lLJH0QZunXrFrS2tnKx2dnZYDKZuNibN2+C2WzmYm/cuCHsJzpSVlaWU6zVauVir1+/7hTLE/NGCIFWq+VmeX9cq9XKzVosFrhx4wYXazKZIDs72yEHANDS0gI5OTlcbFNTE+Tm5nKxDQ0NkJ+fz8XW1dVBYWEhF1tTUwPFxcVcbFVVFZSWlnKxFRUVUFZWxsUaDAYwGAxcbFlZGVRWVnKxJSUlUF1dzcXq9XqoqanhYouKiqCuro6LLSwsBKPRyMXm5+dDQ0MDF5uXlweNjY1cbG5uLjQ1NXGxOp0OmpubudicnBxoaWnhYu8UP20r7+X1SGe9l3dtxhnvdYbNysri9lNe1mw2w82bNx1yAH/sat26dYuLbWpqAp1Ox8U646dGo5HbT2tra7n9tLq6GkpKSrjYysrKv91PS0tLoaqqiot1xk+Li4uhtraWi3XGTwsKCqC+vp6LzcvL4/Ze2U+dZ+WzrPNn2bbw0ztZrunp6X/ZT7Zjx470uXPn/mU/35/VTz/9BIMGDYKLFy9Cc3MzKJVK8Pb2ZrL79++HYcOGweXLl6G1tRWUSiV4eXkx2b1798KoUaPg6tWrAuvp6clkP/74Y7jvvvvg999/B7PZDCqVCjw8PJjsu+++C1OmTIFr166BxWKxy77xxhswbdo04S+FUqmUXLbetGkTPPLII5CVlQUAf3R8Si1Qv/TSSzBnzhy4efMmKBQKSVahUMCqVavgySefhOzsbHBxcQGVSsVctlYoFLBkyRJYtGgR5OTkgKurq132qaeeguXLl4NOp4N27doJHV22cnFxgccffxyef/55yM3NBXd3d0nW1dUVHnroIVizZg3k5+eDh4cHKJVK5kUXrq6uMHHiRNi4cSMUFBSAp6cnREVFMVk3NzcYOXIkvPbaa1BYWAje3t4QGRkpyQ4ePBjeeustKCoqgvbt20NkZCTzQgo3Nzfo168fvPfee6DX68HHxwciIiKYrKurK/Ts2RM+/PBDKCkpAV9fX0nWxcUF1Go17N69G0pLS6FDhw4QFhYmeSlGt27dYO/evVBWVgb+/v4QGhrKZC0WC8THx8O3334LBoMB/P39ISQkhMm2trZCbGws7N+/HyoqKiAwMBCCg4OZbFNTE3Tt2hV+/PFHqKiogKCgIMkerbq6OujatSscPnwYqqqqICQkBAIDA5lsZWUldO3aFY4ePQo1NTUQEhICAQEBTLakpARiY2Ph119/hdraWggLCwN/f38mW1BQAPHx8fDbb79BbW0thIeHQ4cOHZhsdnY2dOvWDU6dOgVGoxEiIiLAz8+Pyf7++++QkpICZ86cgfr6eoiMjARfX18me+HCBUhNTYVz585BY2MjREZGgo+PD5M9efIk9OnTBy5cuABNTU0QFRUF7du3Z7I///wzDBw4UPDTqKgoST/94YcfYMiQIfEABioAACAASURBVHDp0iVoaWmx66dfffUVjBw5Eq5cueLQe3fv3g1jx44V/NSe9+7cuRMmTpwIWq3WoZ9u374dHnjgAeGgo1KpJP108+bNMHPmTGEIZo9dt24dPP744w79FADghRdegPnz53P56fLly2HhwoVcfrpgwQJYtmwZ5OTkgJubm9A3aysXFxeYM2cOrFq1yqGfuri4wIwZM+DFF1+EvLw88PDwELppbeXq6gqTJ0+G9evXQ0FBgcBKeeSYMWNgy5YtUFhYCF5eXpJsu3btYOjQobBt2zbBTyMiIiR/3AEDBsA777wDxcXFdv3Uzc0NevXqBbt27YKSkhLw8fGB8PBwST/VaDTw6aefQmlpKfj5+UmyCoUCkpKS4IsvvnDovVarFeLj4+Hrr7+G8vJyCAgIkPRTs9ks+KnBYODy04MHD0JlZaVdPzUajdClSxf46aefoKqqCoKDgyEoKIjJVldXQ5cuXeDIkSNQXV1t13vLy8uha9eucOzYMaipqbHrp4WFhRAXFwcnTpxw6Kc6nQ4SEhIEPw0PD5f0U61WC8nJyYKfRkRESPrpxYsXoXv37nDu3DloaGiw66enT5+G3r17w4ULF6CxsdGunx49ehT69+8PmZmZDv30xx9/hMGDB8OlS5ccst9++y0MHz6cy08/++wzGDNmDFy9ehVMJhOoVCpJP921axdMmDBBOJ8qlUpJP3377bdh6tSpoNVqHfrpa6+9BjNmzBA+kNpjN2zYALNmzYIbN24AgP2zbEZGBjzxxBOCnyqVSsmz7IoVK2DBggVw69YtcHV1BaVSKemnixYtgiVLloBOp3PIPvHEE7By5UrIzc11eJZ95JFHID093aH3/h3KyMgoSU9P3+EQ5Lla93Y9d3p9S2lpKcrMzETnzp2jeu9Y/ZV6vR5lZmais2fPUr13uL+SvFq7qKgIZWZmotOnT1O9d2R/Jb5au7CwEGVmZqLffvuN6r1r166dcLU2rirIz89HmZmZ6NixY1TvHau/Mi8vD2VmZqJffvmF6r3z8PAQXa2t0+lQZmYm+vH/sPfe8VFV+f//a9J775nQ0gMhEJJAgGRCb5kRK2JBBBERsWHBxQKrYmHtsiq4qFgQBAFh6A5CyEBIMumQBmmk997n/P5w791zZ+6dudmPbb+/eT0e9/HYdZ+bIIHnnHvu+9zXqVOcniamv5J+tfb169eJRqMhSqWS09NE960x1S8lJSVEo9GQQ4cOsRz+3aGm+2rt4uJiotFoyL59+zgsX39lYWEh0Wg0nA5PCPStXb16lWg0GvL5559zWL7+yoKCAqLRaMg///lPDsvXX5mXl0c0Gg157733OCxff2Vubi7RaDTkzTff5LAeHh56fWvZ2dlEo9GQrVu3climv/LgwYNsVYFGoyEajYZs3ryZw/r4+HD61rRaLcvS/XTAf/ormb61oaEhln388cc5LN1f2dvbSwYHB1n2kUce4bBMf+WJEydIX18f6e/vZ9mVK1dy2LFjx3L6K/v6+liW7gYFfu2vpPvWenp6WPb222/nsLr9ld3d3Swrl8s5bFhYGKdvrbOzk2Xnz5/PYXX7K9vb21lWJpNx2MjISE7fWltbG8vSPaLAf/ormZqYlpYWlo2Ojuawun1rzc3NLEv33gH/6a9k+tYaGxuJRqMhmZmZnN47UH1rTH9lQ0MDy9K9d3R/JdO3xvg0IyOD+Pr68vatMVUFtE/p3jumv5LuW6uurmZ9Svfe8fVXMj5Vq9Wc3jumv5Ku3aqsrCQajYakpKRweu/o/kpdn547d47Te8f0V3788cesT8vKyohGoyGnT5/W86luVQHj0+PHj+v5lKndYqoKGJ8eOXKE8zPj669kfEp3IjPuZWq3dH367bffCvqUqd26du0a0Wg0nA5PgL+/kvHpJ598wmGZ/spvv/2W9Wl+fj7RaDTkgw8+0PMp01+p69O3336b16d07VZOTg7RaDTktdde47B8/ZVZWVlEo9Fw+j5pnx46dIitfmH+rj333HMcVre/cnh4mGWffPJJDuvv78+p3aJ9um7dOj2f0v2VAwMDLLt69WoOO2bMGE7tFu1TuhsU0O+v7O3tZdk777xTz6d07Rbt01tuuYXDMv2VTO0W7dOFCxdyWKaLnemv7OjoYNnZs2dzWKa/kqndon1K94gC+v2Vra2tLBsbG8vrU6Z2i/ZpZGQkh9Xtr2xqamIdGRoaqudTunaL9unYsWM5PtXtr6R96u/vz2F1a7dqa2vZtayXlxfHvbr9lYxP09LSiJubG8enurVbzFpWrVYTR0dHjk91+ysN+ZSp3WJqDJm17C+//KLnU90aQ8anZ8+eJRYWFizLdLHTtVvMWvbkyZPEzMyM417dGsPS0lKi0WjITz/9pOdT3RpDxr0HDx7k9Sldu1VUVEQ0Gg3Zu3cvh3VwcNCrMWR8+uWXX+r5lKndYnzKrGV37typ51MxNYZ/RGDqER153njjDc4PVOgaN24cmTp1qig2ODhYT3JCV2hoqN4CU+iKiIggUVFRotgJEyboLUaFrqioKBIRESGKnTx5st7CVeiKiYkhgYGBoti4uDjOIlfoYmRNS1noYha/9AaDITYhIYGzIBa6mMUvvSAWuhhZ0wtioYtZ/FpbWxtlGVnTohW6GFmL+TnY2trqLRKELjs7O9Ff197eXvTXdXR0JAsWLBDFOjk5iWZdXFz0biiFLjc3NzJv3jxRrLu7O6d03dDl6elJ5syZI4r19vYms2bNEsX6+vrq3QALXf7+/iQxMVEUGxAQQGbOnCmKHTNmDJk+fboodiQ+DQoKGpFP6aJ6Q1d4eDiZNGmSKHb8+PF6i1Gha+LEiWT8+PGi2EmTJuktXIWuKVOmkKCgIFFsbGzsiHwaEBAgip0+fTpng0HoYnzq6elplGUWv66urkZZZiOXXhALXczil14QC13MRi69yBW6RuJTGxsb0d4biXtH4lMHBwfR7Eh86uzsLJp1dXUV7VM3N7ffxadeXl6iferj40OSkpJEsX5+fiPyaUJCgih29OjRon06duxYvU1NoSswMJDExcWJYkNCQkhMTIwoNiwsjEyePFkUO378eDJx4kRRbGRk5Ih8GhYWJoqNjo4mwcHBotiYmBgybtw4o5xEIiFTp04lo0aNEsXGx8cTPz8/oyzzYIzeYBC6mI3c7du3G+1a/T0CkTeipjOiVKysrODg4AAHBwfBjjEvLy8kJSUhMDDQKOvj4wOZTIaxY8caZf38/PRYobFHqVQKmUyG0aNHG2VHjRoFmUyGgIAAlhXK2LFjIZPJ4O/vb5QNDAyETCZjx00MsSEhIZDJZPDx8THKhoWFQSaTwcvLyygbEREBmUwGT09PODg4CI6yAMD48eMhk8ng7u5ulJ04cSKSkpLg5uYGBwcHwVEWAIiKioJMJoOLi4tRdvLkyZDJZHBycjLISiQSREdHQyaTwdHREQ4ODoIjMhKJBFOmTIFMJoO9vb1B1szMDLGxsUhMTISdnR0cHBwEx2nMzc0RGxuLhIQEUezUqVMxffp09tcgxFpYWGDatGmIj49nWaExHUtLS8THxyMuLs4oa2VlhenTpyM2NpZlhcZ0bGxsMGPGDMTExBhlbW1tMWPGDERHR7Os0EiPnZ0dEhISMGnSJKOsg4MDEhISMHHiRKOso6MjEhISMGHCBJYV6g1zdnZGYmIixo8fb5R1cXFBYmIiwsPD2b9rQiM9bm5ukMlkCAsLM8p6eHggMTERISEhRlkvLy/IZDIEBQUZdaS3tzdkMhnGjRv3p/o0KSkJo0aNMsqOGTMGMpkMUqnUqMvGjRsn2qfBwcGQyWTw9fUV7VNvb2+jbHh4OMe9Ynzq4eFhlI2MjIRMJmN9asy9Yn06adIkUT4F/uNesT5NSkpif78M+TQmJgYymcyoI83MzBAXFzcin86YMcMo+9/4dOrUqaJ8quteIUdaW1uL9injXtqnQuxIfGpvb4+ZM2ciKipKlE8TExM57hVypJOTExITE0W518XFBTKZDBEREUZZV1dXJCYmIjQ01Kgj3d3dIZPJRPnU09NzxD4Vs5b19fXVc6+Q9/z9/UX7NCAgQG99KsSOHj1a9FqW8amYtWxQUJBon4aGhiIpKUmUT3XXsr+VTydMmDCitaxMJmPX33/ZiLlb/a2uv/oTUSadnZ2cp2G6Ix10WltbOU/DJk+eTF566SV2pINOY2Mj52mY7kgHnZqaGs64bWxsLGekg05FRQU7bkuPdOTk5OixJSUl7HgY85SQHumgU1BQwI6H8Y100NFoNJxdGN2RDjpqtZpl+UY66Jw7d45l6ZEOZjyZzokTJ1iWeUpIjyfToceD+UY66NAjFcxIx6effsqOdND54osvWNbW1lZvpIMOPfLLjCfTIx103n33XZalRzqYcTo627ZtY1lmRG7Pnj3seDKdl19+mWWdnZ0NjnTQY2fMePLevXtJa2urHkuP8bq7u5P777+f7N+/nx2no7NmzRqW9fDwIA888AA5cOAAOyJH5/7772dZLy8vsmrVKvLjjz+y48l06FEyHx8f8tBDD5EjR46w43R06NFcPz8/snbtWnL06FHS09Ojx9K7+VKplKxbt44cP36c9Pb2cjitVst5gsiMJ588eZL09fXpsfRu89ixY8njjz9Ozpw5Q/r7+zns8PAw54lcYGAgefLJJ8nPP/9MBgYGOOzQ0BBnaiEkJIRs3LiRHZGjMzAwwHlyFh4eTp599lly4cIFPba3t5cziTB+/HiyadMmdkSOTldXF+dpWGRkJPnb3/5GLl26pOfItrY2ztOwSZMmkZdeeomkpaXpsU1NTZynYdHR0eSVV14hGRkZen6qq6vjPA1jfKrRaPTYqqoqdjyM2dV+7bXXeH16/fp19skZ85Rw27ZtJC8vT4+9du0ax6e6xz3oZGdn8+5qM8c96KSlpXF8yhz34PPp+fPn9XxKH/egc/r0aQ6re9yDDj0ezIwn08c96NDHLZjjHp9++ik7nkznq6++4viUOe7Bt7v/2WefsaydnR3rU2Y8mQ498st33IPOW2+9xbKOjo7kzjvv5Bz3oLNlyxaOT3WPe9DZtGkTyzLjyfRxDzr0GC/fcQ869LEIxqf0cQ869LEI5riHkE+XLVvGst7e3pzjHrqhR3OZ4x5Hjx4l3d3deiz9JJU+7sHnXnrSg/Ypn3vpKYsxY8ZwjnvosvQ0BONTZjyZztDQEOcpm+5xDzoDAwOcJ2e6xz3o9PX1EalUyrK6xz3odHd3E29vbz2fMsc96HR0dHDGbZnjHnw+bWlpIU5OThyf0sc96NTX1xM7OzuWZY578Pn05s2bnMku3eMedMrKyjg+ZY578Pm0qKiInQLjO+5BJy8vj/3+ZmZmrE/51rLp6ekc9+oe96CTkpLCca/ucQ86Z8+e5fiUOe7BjCfTOXbsGK9PmfFkOgcOHOCsZXWPe/yZgWk097/P+++/b/AHT+ett94S/YN/9dVXDX6Q0tm8ebPeOR+hPPPMM+S2224ju3fv5r2JofP444/rnZsUytq1a/XO+QjlwQcfNPhBSmf58uXsOR++mxg6t99+u965Sb5otVoil8v1zvkIsQsXLjT4QcpkaGiIzJkzh3PORyiDg4NEJpORRx55hD3nI5S+vj4yY8YMzjkfoXR3d5Np06aRDRs2sOd8hNLR0UHi4uI453yE0tLSQmJiYjjnfITS0NBApkyZIvhBSqe6uppER0dzzvkIpaysjERHR3POTQqluLiYREdHC24K0cnPzydTpkwR/CClk5mZSWJiYgQ3heio1Wr2g5RvU4iOSqXSO+cjlBMnTrAfpHybQnQOHTpkcFOIzvfff0+SkpIEN4XofPXVVwY3hejs3LmTzJs3T3BTiM6HH36od85HKNu3bze4KUTntdde0zvnI5SXXnrJ4KYQneeff549N2nMp08++aTeOR+hrFu3jvWpMfeuWrVK9Dmf++67j9x7772Cm0J07rrrLoObQky0Wi1ZunQpWblypeCmEM0uWrSIrFq1ihw6dIj3JobJ8PAwmTt3rsFNISaDg4MkKSmJc25SKP39/WTmzJmCm0J0enp6SHx8POfcpFA6OzvJ1KlTBTeF6LS2trI+5dsUotPY2EimTJkiuClEp6amhvUp36YQnYqKChIdHS24KUSntLSU9SnfphCdgoICEh0dLbjJTicrK4vExMQIbgrRuXz5ssFNdjrnz58n06ZNE9wUonPq1Cm9c5NC+emnn0hCQoLgphCd/fv3s5vsfJtCdL7++muDm0J0Pv/8c4Ob7HR27NhhcFOIzrvvvsv6lG9TiM4bb7zBbgoZ8+krr7xCFAqFqLXspk2bDG4K0Xn66afJ7bffLrgpRGf9+vXsuUljPl2zZg25++67BTeF6KxYsYLdZDe2ll22bJnBTSEmWq2W3HrrrQY3hWh2yZIlBjeFmAwPD5P58+eThx56yOha9s+I2BtRya/sH5OYmBiSkZHxh32//zZDQ0OCIxUm9v/GEkIwPDwsmtVqtaLeAKbVakEIEc0CEBxDoTM8PAyJRCKaNTMzExwt+SPYoaEhmJubi2b/V/7cmFgTa2L/b+xIfDpS9wLifDpS9/7ZPjW518SaWBPLl99zLQv89j79MyKRSDIJITFGOdONqCmmmGKKKaaYYooppphiiim/RcTeiP41b6NNMcUUU0wxxRRTTDHFFFNM+X82phtRU0wxxRRTTDHFFFNMMcUUU/7QmG5EeXLt2jX09vaKYq9evYq+vj5RbEFBAfr7+0Wx+fn5GBgYEMXm5eVhcHBQFJubm4uhoSFRbE5OzojY4eFhoxwhBFlZWexsuzE2OztbFKvVapGdnQ0xo+bDw8PIyckRxQ4ODiI3N1cU29/fj4KCAlFsT08Prl27Jort6upCcXGxUQ4AOjo6UFpaKoptbW3FjRs3RLHNzc2oqKgQxTY2NqKqqkoUW19fj+rqalFsbW0tamtrRbHV1dWor68XxVZVVaGxsVEUW1FRgebmZlFsWVkZWlpaRLE3btxAW1ubKLa0tBTt7e2i2JKSEnR2dopii4uL0dXVJYotLCxEd3e3KNbk05GzYn0KANnZ2aLdK9anI2FH4tOhoSHRPh0YGEB+fr4otre3F1evXhXFdnd3o6ioyCgH/OrTkpISUWxbW5ton7a0tKC8vFwU29TUhMrKSlFsQ0MDbt68KYqtq6sbkU/r6upEsVVVVWhoaBDFVlZWoqmpSRRbXl4+Ive2traKYq9fvz4in3Z0dIhiR+LToqKiEfm0p6dHFPt7+lQsm5eXJ9q9ubm5v9ta9vfw6Z+9lh2JT//KMd+yZcsf9s127ty55eGHH/7Dvt9/mwsXLmDatGlIS0tDV1cX/Pz84OjoyMuePn0aiYmJSE9PR09PD9sDx5ejR49i9uzZyMzMRG9vL/z9/QU7gPbv34+FCxciKysLfX198Pf3F+xJ+/rrryGXy5GdnY3+/n5IpVLB7rNdu3bhtttuQ25uLgYGBgyyH3/8MZYtW4b8/HwMDQ1BKpUK9pn94x//wP3334+rV69ieHgYAQEBvB1lEokEr732GlavXo1r165Bq9UiICCAt0tMIpFg8+bNWLduHYqKikAIMchu3LgRjz/+OIqLiyGRSBAQEMDbJWZmZob169fjmWeeQUlJCczMzBAQEMB76Nzc3ByrVq3C5s2bUVpaCnNzc0HWwsICy5cvx9atW3H9+nVYWFggICCA94C6hYUFbrnlFrz55psoKyuDlZUVpFIpL2tpaYn58+fjnXfeQXl5OaytreHv7y/IJiYm4uOPP0ZlZSXL8h1mt7S0xLRp0/DZZ5+hqqoKtra2gqyFhQWmTJmC3bt34+bNm7C3t4evry8va2ZmhsjISHz99deorq6Gg4MDfH19BV/iER4ejn379qG2thYODg7w8fHhZYeHhxEaGooDBw6grq4OTk5OguzAwACCgoJw5MgR1NXVwdnZGd7e3rxsT08PAgMDcezYMTQ0NMDV1RWenp68bEdHBwIDA3Hy5Ek0NjbCzc0NHh4evGxzczMCAwNx5swZNDc3w93dHR4eHry/BzU1NQgODoZKpUJLSws8PDzg7u7Oy1ZUVCAkJATnz59Ha2srPD094ebmxssWFxcjIiICKSkpaGtrg7e3N1xcXHjZvLw8TJw4Eampqejo6IC3tzecnZ152YyMDEyZMgWXLl1CZ2cnfHx84OTkxMtevHgRU6dOZX3q6+sr6NOzZ89i5syZSE9PR3d3t0GfKpVKzJo1C5mZmejp6THo04MHD2L+/PnQaDRGffrdd99hyZIlyM7ONsru3r0bS5cuFeXTHTt24K677mJvdAMCAgR9+u677+K+++5DQUEBhoeHIZVKBTsft23bhgcffBBXr1416tOXX34Za9euRWFhoVH2ueeew4YNG9ibNkM+3bBhAzZu3Mj6VCqVCrIPPfQQXnjhBdanUqlU0L333nsvXnnlFdy4ccMga2Fhgdtvvx2vv/46ysrKYGlpadCnixYtwj/+8Q+Ul5cbde/s2bPxwQcfoKKiAjY2NgYdOX36dHz66aeorKw06FNzc3PExMTgX//6F27evAk7Ozv4+fkJ+jQqKgpfffUVqqurYW9vDz8/P0Gfjh8/Hnv37kVNTY1B99I+ra2tNejTwcFBBAcH4/Dhw6ivrzfo097eXgQGBuLo0aNoaGiAi4sLvLy8DPr0xIkTaGxsNOjelpYWBAYG4vTp02hqaoK7uzvc3d152fr6egQFBUGlUqG5udmgT6uqqhASEoJffvnFqE9LS0tZn7a2tsLLywuurq68bH5+PiIjI5Gamor29naD7tVoNJg8eTLUajU6Ojrg4+Mj6N5Lly4hNjaW9akh9547dw7Tp09Heno6u5YV8unJkychk8mQkZFh1KeHDh3CvHnzRK1lv//+eyxevJhdnxry6ZdffolbbrkFOTk5Rn366aef4o477mBvdA2tTz/44AMsX76cXcsKrU8B4M0338TKlStFrWW3bt2KNWvWsA8VDPl006ZNWL9+PQoLCwEI+1QikeDJJ5/EU089JWotu3btWjz//PNG17J/RrZu3Vq7ZcuWnUZBMa/W/a2uv3p9y82bN4larSYXL14kPj4+bDcPqJ4kpt6hsrKSqNVqkpKSQtzd3VmO6Z2je5LKy8uJWq0m58+fJ87OzhxWtyfpxo0bRK1WE5VKRezt7TndR7o9SaWlpUStVpMzZ85wOkfp3jmm3qGkpISo1Wpy8uRJtnOUYXV7koqKioharSbHjh1jO0ch0JN07do1olaryaFDh9iOPOj0JDGvGC8oKCBqtZrTIweqJ+njjz9mXzGen59P1Go1+eabbzisjY2NXl1Obm4uUavVZPfu3RzW1taWrXdgXjGenZ1N1Go1+fTTTzmsnZ2dXl2ORqMharWa0zkHqndu9+7d7CvGMzIyiFqtJtu3b+ewjo6OenU5V65cIWq1mrz22msclun8pOtyLl++TNRqNafvEwK9c5cuXSJqtZrTT4d/984xdTltbW1Eq9UStVpN1Go1efrppzmsh4cHWbFiBdm/fz9pb28nQ0NDLLt+/XoO6+npydbldHZ2koGBAZalu0GBX3s8V69eTQ4dOkS6urpIX18fy65YsYLD+vr6cupyenp6WPbuu+/msP7+/px6h+7ubpa97bbbOOyoUaM4dTmdnZ0su2TJEg47ZswYTr1De3s7y9I9ogDIuHHjOHU5ra2tLJuYmMhhg4ODOXU5LS0tLDtt2jQOGxoayqnLaWpqYtno6GgOGx4ezqnLaWhoYNkJEyZw2AkTJpAXXniBrXeoq6tj2eDgYA6r26FcU1ND1Go1SU1N5XSOAr92KL/88stsvQPtU19fXw6r26FM+5TucMa/e+foeoeKigrWp3SHM92hzNTllJWVEbVaTc6dO8fpcGY6P+l6h+vXrxO1Wk3Onj3L6Rzl61BmfHrq1Cm2c5T2KV2XU1xcTNRqNVEqlXo+ZepyGJ8WFhYStVpNDh8+rOdTpt6B6Z27evUqUavV5IcfftDzqW5dDuPT7777jsPydSgzPv3yyy/13Ktbl8P4lO7wZHyqW5eTlZVF1Go1+eijjzisvb09ufXWWzkdypmZmUStVpN33nlHz726dTnp6elErVaTN954Q8+nTL0D49O0tDSiVqs5fZ+MT5m6HF2f/u1vf+Owrq6uenU5zN+fjRs3cli6Q1nXpxs2bNDzKd2hPDg4yLJr167lsN7e3py6nP7+fpalu0EZnzJ1Od3d3aS3t5dl77nnHtE+vf322zlsQEAApy6nq6uLZeleZgBk9OjR5LHHHmM7lDs6OliW7hEF9DuU29raWHbWrFkcNigoiNOhTPt0+vTpHFa3Q5n2Kd3hTPuUqcuhfUp3OAP6Hcr19fUsGxoaqudTukO5traW9enYsWM5LNOhzPi0urqaZekOZ0C/Q7mqqop1r5eXF4fVrcthfHrhwgVO5yhfhzKzlv3ll184Hc60T3XXsj///LOeT3U7lJm17OnTp/V8KpPJOB3KjE+PHz/Odo4yPtWty2F8+tNPP7Gdo7o+ZepyGJ8ePHhQz6dMXQ7jU2YtS3fM0z7dsWMH69O8vDyiVqvJnj179HyqW5eTk5ND1Go1+fzzzzks3aGs69MdO3bo+VRsXc7vHZh6REce3Q8yocvf359MmTJFFDtq1CgyefJkUeyYMWNIVFSUKHbcuHF6C0yhKygoiISHh4tiQ0NDSUhIiCg2PDycBAUFiWInTJigJ1qha+LEiWTUqFGi2EmTJhE/Pz9R7JQpU/SkLHTFxsZyNhiELmbxS28wGGKnT5/O2WAQupjFLy1loYuRNS1aoYuRtZjfA0tLS9GslZWVaNba2lo0a2NjQ5KSkkSxdnZ2oll7e3tOObqhy8HBQTTr5OSkd/MpdLm4uJCEhARRrKurK5k5c6Yo1t3dncyYMUMU6+npqOpRLgAAIABJREFUSeLj40Wx3t7eejfLQpevry+Ji4sTxfr5+Yn2aUBAgGifjh49WrRPx44dq7fAFLqCgoJIRESEKDYkJISEhYWJYsPCwkT7dPz48WTcuHGi2MjIyBH5VHeRK3RFR0frbdgKXbGxsXobDHwXs/ilNxgMsfHx8ZwNBqGLWfzSG7ZCF+NTepErdI3Up2L9NFKfiv26NjY2or+ura3tiHwqlh2JTx0dHUX71NnZWbRPXVxcRPvUzc1NtE89PDxE+9TLy0u0T318fEbkU90ba6FLKpXqbWoKXaNGjSKTJk0SxY7Ep4GBgWT8+PGi2ODg4BH5VHdjVeiKiIgggYGBotjIyEi9TVihKyoqikilUlHs5MmT9TZsha6YmBji6ekpimV6z411w/4egcgbUdNoLpXMzExkZGTAzs4Og4ODvPPcAQEBkMvlcHd3Z0dqBgYGeNnRo0dDoVDAxcUF1dXVsLOzQ39/P+8899ixY6FQKGBvb4+6ujqDbFBQEBQKBaysrNDQ0AA7Ozv09fXxsiEhIVAoFDAzM0NTUxPs7OwEz2uFh4dDoVBgeHgYra2tBtnx48dDoVCgv78f7e3tsLOzEzy3MHHiRCgUCnR1daGzs9MgO2nSJCgUCrS1taGnpwe2traCv4YpU6ZAoVCgsbER/f39BtnY2FgoFArU1NRgcHAQNjY2vKxEIsG0adOgUChQUVEBrVZrkI2Pj4dCoUBpaSkkEgmsra15z2SYmZlh5syZUCgUKCwshLm5OaysrHhZc3NzJCQkQKFQICcnB9bW1oKshYUFEhMToVAokJmZCTs7O1haWvKe37C0tERSUhLkcjnS09Nhb28PCwsLXtbKygqzZs3CokWLkJGRYZC1trbGnDlzMH/+fGRmZsLe3h7m5ua850JsbGwwd+5czJkzBxqNBvb29jAzM+NlbW1tMX/+fCQmJiI7O9sga2dnh/nz52PGjBnIycmBvb09JBIJ73kTBwcHLFy4ENOmTUNeXh47UsTHOjo6YtGiRYiJiUF+fr5B1tnZGYsXL8akSZNw9epV2NvbgxDCe47F1dUVixcvxsSJE3Ht2jXY29tDq9Xysm5ubliyZAnCwsJQVFRkkPXw8EBycjKCgoJQUlICe3t7DA8P85558fLyQnJyMsaOHYvS0lLY29tjaGiIl/Xx8YFcLkdAQABu3LhhkPXz84NcLoevry8qKioM+lQqlUKhUMDDwwNVVVUGfTpq1Cg9nwqxjE8dHBxQW1tr0KeBgYFQKBSwsbFBfX29KJ+am5uzPhViw8LCoFAoQAhBS0uLKJ8ODg6ira3NoCMjIyOhUCjQ3d1t1KdRUVFQKBRob29Hd3e3QUdGR0dDoVCgqakJfX19BtmYmBgoFArU1dVhYGDAoCOnTp0KhUKByspKDA8Pi3Ivc9bSkE9nzJgBhUKBoqIimJubC7Lm5uase/Pz82FlZWXQvYxPNRoNbG1tBX1qYWEBmUwGhUKBtLQ0ODg4CDrS0tJStE+trKwwe/ZsLFiwwKhPGffOnTtXlE/nzZuHpKQkZGVlifJpQkIC615DPl2wYAHi4+ORm5tr1KcLFy5EbGysKJ8uWrQI0dHRKCgoMOhTFxeXEfs0PDxclE+XLFmC0NBQFBcXi/JpYGAg614hR3p7e0Mul2PUqFFGferr6wu5XA5/f3+Ul5cb9Km/vz8UCgW8vLxQWVlp0JEBAQFQKBRwc3MzupYdM2YMFAoFnJycUFNTY9Cn48aNg0KhgK2trVGfBgcHQ6FQwMLCAo2NjQbZ0NBQKBQKAL8eezHk04iICCgUCgwNDbFrWSFHTpgwAQqFAr29vejo6BDl046ODnR1dRlkJ0+eDIVCgZaWFvT29oryaX19PQYGBgyycXFxUCgUuHnzJoaGhkT5VKFQIDAwUFTH8W8Z02ju/yHt7e2cEQVmR4EZtaXT3NxMnJycCMAdtWVGw+jU19cTOzs7AvCP2tK5efMm+zTMzMyMJCYmckbD6Ny4cYPdvaVHbZnRMDqFhYXskzO+0TA6ubm57O8BPWrLjIbRSU9PZ1m+0TA6Fy5cYFlra2t21JYZZaBz5swZluUbDaNz9OhRlmVGbenRMDr0OBszGrZ79252NIzO119/zbL0qC0zGkZn165dLMs3akvnww8/ZFlm1Pbbb78lzc3Neuzbb7/Nssxo2Pfff8+OhtH5+9//zrK6o2G6ocfO6FHbjo4OPZYe49UdDdPNo48+yrK6o7a6efDBB1lWdzRMN8uXL2fZgIAA8uijj7KjYbq59dZbWZYZDWNGbXWzaNEiltUdDdMN/UQhKCiIM2pLR6vVcna8mVFbZjRMl6V3m3VHbekMDQ1xnshNmDCBMxpGZ3BwkLPTqztqS6e/v58EBARwdmjp0TA6PT09nKdhuqO2dDo6OjjTBbqjYXRaW1vZ6QJ61JYZDaPT0NDAThfwjdrSqampYZ+GMdMG9GgYnfLycvb4AvN0jB61pVNSUsKO29I+ZUbD6OTl5bHjtnyjYXQyMzP1fPrRRx+xxxzopKamcnyqO2pLR6VScXyqOxpG5/jx4yxra2urN2pLhx5no0fD+Hz67bffsiw9asscc6Dzr3/9i+NeZtSWOeZAhx5Rc3Z2JnfffTf55ptveH1Kj/y6urqSe+65hzNqS+f111/n9WlbW5se++KLL7Ksh4cHZ9RWN8888wzLenl5kVWrVpEff/yR16ePPfYYy/r4+LCjtl1dXXrsQw89xLJ+fn7k4YcfJkePHuV173333ceyUqmUM2qrG3o0d9SoUWT9+vXsqK1u6KMOxnw6Z84clg0MDOSM2tLRarWcJ5PMqO25c+d4WXrKIiwsjDz77LPsqC2d4eFhznSZ7qgtncHBQc5TtsjISM6oLZ3+/n4yevRolmVGbdPS0vTY3t5eztMwetRWl+3q6uJMF8TGxpKtW7cSjUaj57K2tjZ2uoBv1JZOU1MTO13A+JQ+NkantraW41PdUVs6lZWVHJ8yx8aYUVs6paWlrE/Nzc3ZUVvm2Bidq1evsj5ljo29//77vGvZrKwszlqWGbXl8+mlS5c47l24cCHZsWMHe2yMzrlz53h9yhwbo3Py5EmOT5lRW+bYGJ3Dhw9z1rJLly7lHBuj8/3333N8etttt5EvvviC16d/dGAazf3v8/777xv8wdN5++23Rf/gX331VXLnnXdyzgsK5cUXXyTLli0T/CCl8+yzz+qdFxTKE088Qe677z6yb98+3g9SOuvWrSMrVqwgP/zwA+9NDJ3Vq1eTBx98UPCDlM69995LVq9eTQ4fPsz7QcpEq9WSu+66y+AHKc0uXbqUPPLII0SpVPLexDAZHh4mycnJZP369ex5QaEMDg6SBQsWkA0bNpDTp0/zfpAy6e/vJ3PnziVPPvkke15QKL29vSQpKYk8/fTTvB+kdLq6ukhCQgLnvKBQ2trayMyZM8nzzz9PLl68qPdBSqepqYlMnz6dvPDCC0StVhtk6+rqSHx8PHnxxRd5P0jpVFVVkfj4ePLyyy+T9PR0g+z169dJfHy84AcpncLCQhIfHy+4KUQnNzeX/SDl2xSik56ebnBTiM7Fixf1zl8L5ezZs3rnr4WiVCr1zl8L5ccffzS4KURn7969BjeF6Hz55Zd656+FsnPnTiKXyznnr4Xy4Ycf6p2/Fsr27dsNbgrRef311w1uCtF5+eWXDW4K0dm0aZNonz711FMGN4XoPProo5zz14by0EMPGdwUorNixQqDm0JMtFotufvuuw1uCtHs7bffTh555BHBTSEmjE/p89dCGRoaIgsXLjS4KcRkYGCAzJ07l3P+Wih9fX1k1qxZgptCdLq7u4lMJhPl0/b2djJz5kzBTSE6zc3NZMaMGZzz10Kpr68n8fHxgptCdG7evEmmTZsmuClEp6ysjEybNk1wU4hOcXEx61O+TSE6eXl5ZPr06Zzz10LJzMwkM2bMENwUoqNWq/XOXwvl3LlzBjeF6Jw8edLgphCdI0eOGNwUorNv3z7RPt2zZ4/BTSE6u3btIsnJyYKbQnQ+/vhjg5tCdN59913RPn3jjTf0zl8LZcuWLeSuu+4S3BSi88ILL7Dnr42tZTdu3GhwU4jOhg0bDG4K0Xn44YcNbgrReeCBB0T5lJBfN8YNbQox0Wq15I477iBr164lR48eNehTrVZLFAqFwU0hJkNDQ2TRokUGN4X+zIi9EZUQnkfgv1diYmJIRkbGH/b9/ttotVret9eZ2P87y/zBE8sCEDVO8HuxWq0WEonkd2H/V35mJtbEmtj/ffav4N7f06cm95pYE2ti/yj2f82nf0YkEkkmISTGKGe6ETXFFFNMMcUUU0wxxRRTTDHlt4jYG1FxWwSmmGKKKaaYYooppphiiimmmPIbxXQjaooppphiiimmmGKKKaaYYsofGqM3ohKJZLdEImmQSCT51D/bIpFIqiUSSfa/r8W/7y/zj01ubi46OztFsTk5Oejq6hLFZmdnC77qWTcajUbw9c26yczM5H0VPV8yMjJ4XxnPl/T0dN5Xu/PlypUrvK9g1w0hBGlpabyvSv+/sFqtFmlpabyvP9fN8PAwrly5wvuact0MDg4iPT1dFNvf34/MzEzeV4/rpqenB1lZWaLYrq4u5ObmimLb29uRn58vim1pacHVq1dFsU1NTSgqKjLKAUBDQwNKSkpEsbW1tWxVg7FUV1ejvLxcFFtVVYXKykpRbEVFBW7evCmKLSsrQ21trSj2+vXrqKurE8WWlJSgoaFBFFtUVISmpiZR7LVr19DS0iKKvXr1KlpbW0Wx+fn5aG9vF8Xm5eWho6NDFDtSn3Z3d4tis7KyRuTe38OnGRkZv7lPR8KO1L1XrlwR7VOx7h0aGhLt3oGBAWRkZIhie3t7odFoRPs0JydHFNvR0YG8vDxRbGtrq2ifNjc3o7CwUBQ7Ep/W1dXh+vXrotiampq/hE9rampEsSPxaWlpqWifFhcXo7GxURRbWFiI5uZmUexIfFpQUPC7+DQ3N/cv4VPTWpaIduRI1rJDQ0Oi16d/5RjtEd26dWsrgN0Abt2yZcs///3PkgBcIISs2LJly6dbtmwRZcm/eo8ok8uXLyM2NhYXL15EW1sbvL294eLiwsueP38e06dPR2pqKjo6OuDt7Q1nZ2de9tSpU0hMTMTly5fR0dEBHx8fODk58bJHjhzBnDlzkJaWhq6uLvj6+sLR0ZGX3b9/PxYsWID09HR0d3fDz88PDg4OvOyePXsgl8uRmZmJ3t5e+Pn5sV1eutm1axduvfVWdmHm7+8POzs7Xvajjz7CsmXLkJ2djf7+fkFWIpFg+/btuO+++5Cbm4uBgQFIpVLY2trysq+++ipWrVqF/Px8DA4OIiAgADY2Nrzs5s2bsXbtWhQUFGB4eBhSqRTW1tZ6rJmZGZ5++mls2LAB165dw/DwMAICAmBlZaXHmpub49FHH8XGjRvZhYMQa2FhgQcffBCbNm1CcXExgF+7uiwtLXnZZcuW4ZVXXkFJSQnMzMwglUp5WUtLSygUCrz++usoLS2Fubk5pFIpLCws9FgrKyvMnz8fb7/9Nm7cuAELCwuDrEwmw/vvv4+ysjJYWlpCKpXC3Nyc99cwbdo07NixA+Xl5bC2toa/vz8va2FhgejoaOzcuRMVFRWwsbGBv78/76F+MzMzTJw4EV9++SWqqqoMssCvXbfffPMN23vm5+fHyw4PDyM0NBT79u1DdXU17O3t4efnx3uof2BgAEFBQTh48CBqamrg6OgIHx8fXranpweBgYE4cuQI6urqDLJtbW0ICgrCsWPHUF9fD2dnZ3h7e/OyjY2NCAoKwsmTJ1FfXw8XFxd4eXnxsjU1NQgODsbp06fR2NgIV1dXeHp68rLl5eUICwvD2bNn0dTUBHd3d7i7u/OyhYWFGD9+PM6dO4eWlhZ4eHjA3d1djwN+XeBERUXh/PnzaG1thaenJ9zc3HjZK1euICYmBikpKWhra4OXlxdcXV152ZSUFEybNg2pqalob2836N4zZ85g5syZuHTpEjo7Ow369NixY5g9ezYuX75s1KcHDhzA/PnzRfn022+/xeLFi5GRkYGenh74+/sL+vTzzz/H0qVL2YWZIXbHjh248847jfoUAN555x3ce++9yMnJMerTbdu2YeXKlcjLy8Pg4CCkUqmgT1966SWsWbMG+fn5GBoaQkBAgKBPn332Waxfvx5Xr16FVqs16N7HHnsMTz31FK5du2bQp+bm5li9ejWef/55FBUVsayQI++55x68+OKLKC4uhkQiMcjeeuutePXVV1FaWgozMzMEBAQIOnLhwoV46623cP36daM+nTVrFt577z2UlZWxLJ8jraysMH36dHz88ccoLy+HlZWVIGthYYGYmBh89tlnrHulUimv98zNzREVFYXdu3ejsrIStra2go4Efu2v/frrr9kOXyFWq9UiLCwMe/fuNerTwcFBBAcH44cffkBNTQ0cHBzg6+vLy/b29iIwMBCHDx9GbW0tHB0dBdnOzk4EBgbi6NGjqKurM+jT5uZmBAUF4fjx42hoaICzs7OgT2traxESEoJTp04Z9WlFRQVCQ0NZn7q5ucHDw4OXLS4uRkREBFQqFZqbmw36ND8/HxMnTsT58+fR0tJi0KeZmZmIjo7GhQsXjPo0NTUVcXFxSE1NNbqWValUmDFjBtRqNbs+FVrLHj9+HElJSbh8+TI6Ozvh6+sr6N4ff/wR8+bNw5UrV9Dd3W3QvXv37sXixYuRnp6Onp4eg+794osv2L5fYz799NNPcccddyArKwt9fX2QSqWCPn3vvfdwzz33sD719/cX9Ombb76JFStWIDc316hPt2zZgoceeohdyxpiN23ahEcffZRdyxpy7xNPPIHHH38c165dg1arFfTpn5HftEcUwBgA+dR/3wLgGTH/X/r6q9e3lJeXE5VKRX7++WdORx7+3dVH11zcuHGDqFQqcubMGU5HHni6+kpLS4lKpSKnT59mO/KYa/LkyeTll19mX8teXFxMVCoVOXHiBNuRx1y6XX2FhYVEpVIRpVLJdjoxV1xcHKer7+rVq0SlUpEjR46wnU7Q6epjXsuen59PVCoV+fHHH9lOJ4Dbfcq8lj03N5eoVCqyb98+ttOJYXVfy56dnU1UKhX55ptvOL9WpvuUfi17ZmYmUalU5IsvvuCwfN2n6enpRKVSkc8++4zD0l19TM1FWloaUalU5KOPPuKwfN2nly5dIiqVitM5B4GuvtTUVKJSqcgbb7zBYfm6T1NSUohKpSJbtmzhsHZ2dnqvZT9//jxRqVScvk/gP92ndFffuXPniEql4vTT4d/9e/Rr2bVaLVGpVESlUpHHH3+cw+p2nw4NDbHsI488wmFdXFzY17K3tLSQgYEBll21ahWHZbpPmdey9/X1sSzdZQfod592d3ez7F133cVhPT09Oa9l7+zsZNmlS5dyWLr7tKuri7S3t7Ps4sWLOayvry/7Wvbu7m7S2trKsnPnzuWwut2nzc3NLJuQkMBhAwICOK9lb2xsZNmpU6dyWKb7lHkte319PctOnjyZw+p29dXW1rLs+PHjOaxu92l1dTXL0h15wH+6+pju06qqKtaRY8aM4bBM9ynT1VdRUcGydEceoN/VV1ZWRlQqFTl79iynI4/xKd3VR/uU6chjLqarT9enJ0+eZDvyaJ8yXX20T48fP05sbW05rG73KePTo0ePsn3PjE91u/oYnx46dIjjU7r7lOnqY3y6f/9+PZ/qdvUxPv3uu+/0fKpbc6HRaIhKpSJfffWVnk+Zrj6m5iIjI4OoVCpOJ7KuT5maiytXrhCVSkU+/vhjPZ8yXX2MTy9fvkxUKhV59913eX26Y8cO1qdqtZqoVCry1ltv6flUt/v04sWLRKVSkVdffZXDMt2nO3fuZH164cIFolKpyEsvvaTnU93u019++YWoVCry/PPPc1i6q4+puWD+/jz55JN6PqW7T2mf0l3LwK/dp3RlG+1TuhuU8Sldc0H7dMWKFRzWzc2NU9nW09PDsnfffTeH1e0+7erqYlm6lxn4tfuUrmzr6OhgWbpHFPhP9ylT2dbW1say8+bN47B092lPTw9paWlhWZlMxutTpVJJent7SVNTE8vGx8fr+ZSuuWhoaGBZunOU8Sld2VZXV8eykZGRHFa3+7SmpoZlQ0NDOWxwcDCnso326dixYzmsbvcp7VN/f389n9KVbbRPvby8OCzdfTo0NESuX7/OrmXd3Nw4bFRUFKeyraSkhKhUKnLq1Cni6OjIYZnuU6ayraioSNCnMTExnMq2a9euGfUpU9lWUFBAVCoVOXz4MLGwsOCw8fHxnO7TvLw8olKpyIEDB4iZmZmeT+nKtpycHKJSqcjevXv1fKrbfZqVlUVUKhXZs2ePHqtb2cb4lO5EZtyr233K+PSTTz7h9emHH37Idp8yPv3ggw/0fGqo+/SPDH7LHlHw34iWA8jFr09LXcV8nb/6jajuTYTQ5enpSaKiokSx3t7eeuISunx9ffUWjUKXn58fCQsLE8UGBASQkJAQUezo0aNJUFCQKHbs2LF68hS6goKCyKhRo0SxISEhRCqVimLDwsL0Ng2ErvHjxxNPT09RbGRkpJ6Uha5JkyYRJycnUWx0dDSxs7MTxcbGxnKkLHQxsqZFa4jV/YAWuszMzESz5ubmZPr06aJYCwsL0aylpaXoX4OVlZVo1traWjRrY2MjmrW1tSXTpk0Txdrb24tmHRwcSFxcnCjW0dGRxMbGimKdnZ1JTEyMKNbV1VVvwSZ0ubm56d0sC10eHh6iferl5UUmTpwoivXx8RmRTyMiIkSxUqlUb4EpdI0aNUrv5l7oGjt2LBk3bpwoNjAwkIwePVoUGxwcPCKf6m4aCF0RERF6i1yhKzIyUm/DVuiKiorS27AVuiZPnqy3YSt0xcTE6G3YCl1xcXGcRa7QNVKfiv37bm5uPiL3imV/T/eK/bq/l0/t7OxG5N6R+FQs6+TkJNqnLi4uI/JpdHS0KNbDw4NMmjRJFOvp6Tkin45kLSvWp/7+/qLXsiPx6ZgxY0hgYKAodty4cXobq0JXcHAwCQgIEMWGhoYSPz8/UWx4eDjx9vYWxU6YMEFvw1boYh6MGesG/z0CkTei+vMl4vIJgFf//S/6KoB3AKziAyUSycMAHgaAUaNG/Zff7o+Jo6MjpFIpgF9H5fjmz4OCgiCXy9HX18eeFWhoaOCdPw8NDYVcLkd7ezt7VqC+vp53/jw8PBxyuRyNjY3sWYG6ujre+fMJEyZALpejqqqKnf+vra3lnSmfOHEi5HI5rl+/zs7019TU8M6UT548GXK5HAUFBeycfnV1Ne85lilTpkAulyMrK4v99xE6FxIXFwe5XA61Ws1+Xz5WIpFg6tSpkMvlOHfuHACAEILq6mo91szMDPHx8UhOTsaJEydgYWFhkJ0xYwbkcjkOHToEa2traLVa3rMp5ubmSEhIQHJyMr7//nvY2dlheHiY91yghYUFEhMTIZfL8cUXX6ClpQVDQ0O851gsLS0hk8kgl8vx6aeforOzE4ODg6ivr9djmREvuVyOd999FwMDAxgYGOA982JtbY3Zs2dDLpejpqYGhBD09/fznnmxsbHB3LlzsWTJEpSXl8Pc3Bx9fX285w1tbW0xb948zJ8/n2V7e3t5z8fY29tj/vz5mD17NsrLy2FmZoaenh7es4kODg5YsGABEhISWLa7u5v3LI2TkxMWLlyIqVOnoqKiAmZmZujq6kJbW5se6+zsjEWLFmHKlCks29nZyXvuxtXVFYsXL0ZkZKRR1t3dHYsXL0Z4eDgqKyshkUjQ0dHBe0bHw8MDS5YsQWBgIKqqqiCRSNDe3s573tzLywvJyckYNWoUy7a1tfGe5/Hx8UFycjJ8fHxQXV0NiUSC1tZW3vM8fn5+kMvlcHV1RU1NDSQSCVpaWnjP8wQEBCA5ORkODg6ora2FRCJBc3Mz73me0aNHQy6Xw8rKCnV1dZBIJGhqauI9zzN27FjI5XIAYP8cGvNpf3+/UZ+GhIRALpejs7OT/bNlzKdNTU1GfTp+/HjI5XJUV1ezP1dDPk1OTkZZWRn7+y/ETpo0CXK5HIWFhezvqZB7o6OjIZfLkZ2dzf67C7k3NjYWcrkcly9fZr+vIZ8mJyfjwoULAIR9KpFIEB8fD7lcjtOnT8Pc3NygT6dPnw65XI6jR4/CysrKoE9nzpwJuVyO/fv3w9bW1qBPExISIJfLsWfPHjQ1NRn1aXJyMnbt2oX29naDPk1KSoJcLseHH36I3t5eoz5NTk5GfX09hoeHDfp0zpw5kMvlonw6d+5cLFy4EBUVFQZ9amdnh/nz52POnDmsn8T41Bjr6OiIhQsXIj4+3qh7nZ2dsXDhQsTGxhp1r6urKxYtWoRJkyaxX1fIp25ubli8eDEiIiJE+zQoKEiUT5csWYIxY8aI9qmvr68onyYnJ8PDw4NlhXwqlUqRnJwMZ2dnoz4dNWoU5HI5bGxsRPtUIpGwf2aFfBoYGAi5XI7BwUH2z6GQT4ODgyGXy9Hd3c3+eRFiw8LCIJfL0dLSYnQtGxERAblcjtraWvbnKuTeyMhI9u+PsbVsVFQU5HI5iouLRfs0NzeX/X0S8mlMTAzkcjkyMjLYX6OQT+Pi4pCcnIzU1FT2JkrIp9OmTYNcLsfZs2dhZmZmdC0rl8uhVCphaWlp0KfMWvbgwYOwsbER9Km5uTkSExORnJwMuVzO3tv8JSPmbhU6T0TF/m+611/9iSiT1tZWduSL77E8ncbGRnbky9zcnB1zYh7L06mtrWV3ZPkey9OpqKhgR2gtLS3Zx/LMiCmdkpISduTLysqKfSzPjETRKSgoYEe+rK2tyeLFi8knn3zCu1ui0WjYXRVbW1sil8vJzp07SXV1tR576dIllrWzsyO33HIL+fzzz0ltba0xj0UrAAAgAElEQVQee+7cOZalx5zq6+v12BMnTrCso6MjueOOO8hXX31FGhsb9dhDhw6xLDPmxIyY6oYev3BxcSHLly8n3333HWlpadFj6fFgZszp+++/J62trXosPVLh4eFBVqxYQX744QfS3t6ux9IjasyY08GDB0lHR4ceu23bNpb19vYmq1evZsecdPPyyy9zdibXrFlDfvrpJ9Ld3a3HPvfcc5ydyUceeYQolUrS09Ojx9JjvAEBAeTRRx8lJ06cIL29vXrsww8/zNmZZMac+vr69Nj777+fszP5xBNPkLNnz5L+/n499s477+TsTD799NPsiKlu5HI5Z2fymWeeIefPnyeDg4N6LD0eFhERQZ5//nmSkpJChoaGOJxWq+WM2+qO7Ouy9O44M+bEjOzTGR4e5uw2MyP7zJgTnaGhIc6EQ0xMDGdkn87AwABnpzcuLo68+uqr7JgTnd7eXnbki3nSQ4/s0+nq6mKfhtEj+8yYE522tjbi6urKsroj+3SamprYkS96zIkZMaVTV1fHjnzxjezTqaqqYqcLLC0tybx58wR9ev36dfZpGN/IPp1r166xkwi0T5kRUzrZ2dnsz4FvZJ9OWlqank/pkX0658+fZ1lmZH/37t3siCmd06dPc9xLj+zr5qeffmJZ3ZF93ezbt4/jXmZkv7m5WY+lx4OZkX0hn9LHLeiR/ba2Nj2WHlHz9PQkK1euFPQpPfJLj+x3dnbqsVu3btXzKTOyr5tNmzZxfEqP7OuGHuNlfMqM7OuGPhbBjOyfOnWK16crV65kWd2Rfd3Qo7m6I/u6ueWWWzg+pUf2dbNgwQLOk57nnnuOpKSk8LL0uK3uyD4drVbLOb6gewRKl6WfCuqO7NMZGhoi4eHhLMscgWJG9ukMDAxwphZ0R/bp9PX1sZMI9BEoZmSfTnd3N/s0jB7ZZ45A0eno6GCntRif0iP7dFpaWthpLb6RfToNDQ3stBbjU3pkn87NmzeJtbU161PdkX06ZWVlHJ8yI/vMiCmdoqIijk91j0DRycvL4/hUd2SfTkZGBmctyxyB4lvLpqSkcHyqO7JP5+zZs7w+5VvLHjt2jLOWpUf2dXPgwAE9nzIj+7qhj7rpjuz/2cHvPJrrS/3npwB8L+br/K/ciH7wwQcGf/B0tm/fLvoH//rrrxv8IKXz0ksvcc5qGMrzzz9PVq1axZ7VMJSnnnqKPfvGdxNDZ/369exZDb4PXTpr1qzhnH0zlBUrVnDOaghFq9WS5cuXG/wgpdk77riDc1ZDKENDQ2Tp0qVk48aN7FkNoQwODhK5XM45qyGUvr4+smjRIsEPUjo9PT1k3rx5nLNvQuns7CRz584lL730EntWQyitra1k9uzZ7Nk3Q2xjYyNJSkrinNUQSm1tLUlKSuKcfRNKZWUlkclknLMaQiktLSVJSUmCH6R0rl27RpKSkgQ3hejk5OSwH6R8m0J0rly5YnBTiE5KSorBD1I6Z86cEX1WQ6lUsh+kxkZofvzxR4ObQnT27t1Lli5dKrgpROerr74yuClEZ+fOneTOO+8U3BSi89FHH3HOvhnKP/7xD4ObQnS2bdvGOftmKFu2bDG4KUTnb3/7G+fsm6Fs3LjR4KYQnQ0bNoj26dq1aw1uCtF58MEHyfr16wU3hZhotVpy7733GtwUotm77rqLPPnkk4KbQkyGh4fJrbfeyjn7JhTGp4Y2hZj09/eTxYsXc86+CaW3t5fMnz9fcFOITldXF5k7dy7n7JtQ2tvbyZw5cwQ3heg0NTWRWbNmifJpXV0dkclkgptCdKqqqkhSUhLZtm0b76YQnRs3bhCZTCa4KUSnqKiI9SnfphCd3NxcMmvWLM7ZN6FkZGSQOXPmCG4K0UlNTTW4KURHpVIZ3BSic+LECYObQnSOHDlC5HI5+eyzz4z6dN++fQY32ens2bPH4KYQnc8//5zdZOfbFKKzY8cOg5tCdN577z3RPn3zzTcNbgrR2bp1K1mxYgX7HgdD2bx5s8FNITrPPvuswU0hOk888YTBTXY669atI4888ojgphCdVatWGdxkZ6LVasl9991ncFOIZpctW2Zwk53J8PAwue222wxuCjEZGhoit9xyC3nmmWcEN4X+zIi9EZUQnkfVdCQSyV4ASQA8ANQDeOXf/33Sv+/CywGsJYQY7TSIiYkhGRkZxrA/PYQQ3regmdj/O8v8efuz2f+V3y8Ta2JNrIn9LViTT02siTWxJva3Yf/X1rJ/RiQSSSYhJMYYZ/SMKCFkOc8//td/9av6H8lIfrAmdmTsn/39TayJNbEm9v+P7J/9/U2siTWxJvb/FfbP/v4jZf/K4S+XMsUUU0wxxRRTTDHFFFNMMcWU3ymmG1FTTDHFFFNMMcUUU0wxxRRT/tCYbkR5otFoeF9/zpeMjAze15/zJT09nfeV5nxJS0vjfaU5Xy5fvsz7mnK+XLp0ifc15XxJTU3lfU05Xy5evMj76nHdEEKQkpLC++pxIZbvdeK60Wq1uHDhAu/rxHUzPDyMlJQUUezg4CBSUlJ4Xz2um/7+fqSmpvK+elw3PT09uHTpkii2q6sLV65c4X1NuW7a29uRkZEhim1paYFGo2HPJBhKY2MjcnJyRLF1dXXIy8sTxdbU1ODq1aui2KqqKhQWFopiKyoqUFJSYpQDgLKyMly/fl0UW1paivLyclFscXExKisrRbGFhYWC9Ue6uXr1Ku+r3fmSn5/PW3/Bl9zcXN5KC75kZ2fz1lTwJSsri7emgi+ZmZm/i0+vXLnyp/tUrVaL9mlqaipv7QNfUlJS/lT3jsSnQ0NDon06MDAg2qe9vb1Qq9WifZqWlibap+np6aLY1tZW0T5tampCdna2KLa+vl60T2tra1FQUCCKvXnzpmifVlZWori42CgH/OrT0tJSUez169dRVlYmii0pKUFFRYUotqioCFVVVaLYq1ev8tZq8KWgoIC3KoMveXl5vHVCfMnJyeGtCOLL7+XTjIwM3noevozEp2lpabyVO3y5dOmSaPf+Xj4dyVr2woULf4m1rBif/pVjvmXLlj/sm+3cuXPLww8//Id9v/82WVlZmDx5Mn7++Wc0NTXB3d0d7u7uvPPYly5dQlxcHM6dO4eWlhZ4eHjA3d2d9+v+8ssvmD59Oi5cuICWlhZ4enrCzc2Nlz116hRkMhlSUlLQ1tYGb29vuLi48LJHjhzBnDlzkJqaivb2dvj4+MDZ2ZmX3b9/PxYsWIBLly6hs7MTPj4+cHJy4mW//vprtq+uq6sLvr6+cHR05GV37tyJW2+9Fenp6eju7oafnx8cHBz0OIlEgo8++gh33XUXMjIy0NPTA39/f9jb2/Oy27dvx7333guNRoPe3l6D7KuvvoqVK1ciOzsb/f398Pf3h52dnR5rZmaGzZs34+GHH0ZOTg4GBgYglUpha2urx5qbm+Ppp5/GY489hry8PAwODiIgIAA2NjZ6rIWFBdatW4ennnoKBQUFGBoaQkBAAKytrfVYS0tLrFy5Es899xyuXr0KrVYLqVQqyC5btgwvvvgirl27BkIIAgICYGVlpcdaW1tDoVDg73//O4qKigD82hdpaWnJy86fPx9vvPEGiouLIZFIDLIymQzvvPMOSktLYW5uDqlUCgsL/WPmVlZWiI+Px4cffojr16/DwsJCkLWwsEBMTAw++eQTlJWVsay5ubkea25ujqioKOzatQvl5eWwsrISZIFf+3a//PJLlJeXw9raGlKpFGZm+ntvw8PDCA8PxzfffIPKykrY2trCz8+Pl+3v70dISAj27duHmzdvGmS7u7sRHByMAwcOoLq6Gvb29vDz8+P1SFtbG4KDg3H48GFUV1fDwcEBvr6+vGxjYyOCg4Nx9OhR1NbWwsnJCT4+PrxsdXU1QkNDoVQqUVdXB2dnZ3h7e/OyN27cQEREBE6ePImGhga4uLjAy8uLly0sLMSECRNw+vRpNDY2wtXVFZ6enrxsTk4Ox6dubm7w8PDgZa9cuYLY2FioVCo0Nzcb9GlKSgri4+Nx/vx5oz49c+YMEhIScOHCBbS1tcHLywuurq687NGjRzF79mzWp4bce+DAAcyfPx9qtRodHR0G3fvNN99gyZIl7MLM19dX0L3/+te/sHTpUly5cgXd3d0G3fvPf/4Td955J9LT09HT02PQve+++y6WL18uyqevv/46HnjgAWRlZaGvrw9SqVTQpy+99BLWrFnD+tTf35/Xp2ZmZnj22Wexbt065ObmYnBwEFKplNen5ubmeOyxx/DEE08gPz/fIGtpaYnVq1fj2WefRUFBAYaHhw26d/ny5di8eTPrU6lUKujTpUuXYuvWrSgsLARg2KcLFy7Etm3b2Js2Q+ysWbOwfft2lJSUwMzMDAEBAbyOtLa2xvTp0/H++++z7hViLS0tERcXhx07duDGjRuwtLQ06NNJkyZh165dKCsrM+rTyMhI7N69GxUVFQZ9qtVqERERgT179qCyshI2Njbw9/fnZQcHBxESEoK9e/eiqqoKtra2gmxvby9CQkKwf/9+3Lx506BPOzo6EBwcjEOHDhn1aXNzM0JCQnDkyBHU1tbC0dFRkK2treX41JB7KyoqEB4ejhMnTqC+vt6gT4uLi1mfNjQ0GPRpfn4+oqKicPbsWaM+zcjIQExMDFQqFbuW9fDw0OOAX2/Apk2bhl9++cWoT3/++WfMnDkT58+fR2trq0GfHj9+HLNmzcLFixfR3t4OLy8vQZ8eOnQI8+bNQ2pqKjo6OuDt7S3o071792LRokW4fPky614hn37xxRdQKBRIS0tDV1cX/Pz8BH36ySef4I477mB96uvrK+jT999/H3fffTcyMzPR29sLPz8/QZ+++eabWLFiBbKyslj38vlUIpFgy5YtWLVqFbuWFVqfmpmZYdOmTVi7di1yc3MNrmX/jGzdurV2y5YtO42CYl6t+1tdf/X6ltLSUqJUKsmxY8eIj48P280Dno6t4uJiolQqydGjR4m7uzuH1e3YunbtGlEqleSnn34izs7OHJbp2GKqQQoKCohSqSSHDx8m9vb2HFa3Yys3N5colUpy8OBBtp+UuZiOLaYaJDs7myiVSrJ//362n5S5dDu2NBoNUSqVZO/evWw/KXNNmTKFrQbRarUkPT2dKJVK8vXXX7P9pMyl27GVlpZGlEol2b17N4eT/Ltji64GuXTpElEqlZweOYbV7di6ePEiUSqV5KOPPuKwZmZmZObMmZxqkAsXLhClUsnp8AT4O7bOnTtHlEolefPNNzksX8fWzz//TJRKJfn73//OYfk6ts6cOUOUSiV58cUXOSzdscW8nv7kyZNEqVRy+j4B/o6t48ePE6VSSZ566ikOq9uxpdVqiVKpJEqlkqxfv57DMh1bO3fuJDU1NWRwcJBl16xZw2F1O7b6+/tZ9oEHHuCwTMfWF198QRoaGkhvby/LLl++nMM6OTmxHVtNTU2kq6uLZW+//XYOy/TFMtUgHR0dLKtQKDisbsdWa2sryy5cuJDDMn2xTDVIc3Mzy86ePZvDenp6cqqWGhsbWXbmzJkclumLZapB6uvrWTYuLo7D+vj4kIceeoitBqmpqWHZyZMnc1g/Pz+2GqSnp4fcvHmTZcePH89hAwICyLp164hSqSS9vb2koqKCZYODgzns6NGjOVVLZWVlLDt69GgOy3QWnj59mvT395Pr16+zPvX19eWwgYGBnKolxqfHjh0jHh4eHDYkJIRTDVJYWMj6lOl7Zq6wsDBO1RLj0yNHjrB9z7RP6WqQvLw8olQqyY8//sj2kzJXZGQkW7U0NDREcnJyiFKpJD/88APbT0r7lK4GycrKIkqlknz//fd6Po2OjiavvPIKWw2SkZFBlEol+eabb/R8GhMTw6kGuXLlClEqleTLL7/Uc+TUqVPJa6+9xlaDMD7dtWuXHhsfH8+pWkpNTSVKpZLs2LFD0KdMNUhKSgpRKpXkvffe0/Opbv/2L7/8QpRKJafDk/GpbjWISqUiSqWSvPbaa3osU7Wk61O6P5n26YcffshWLZ06der/Y++9o6K61j/uL23oHWZgaKIIAmLv2EERmCNqbLEj0hTRa4yJiYk9GqMxmhivMTFNE0uMFRVBUBFEEQsqvQlI773v9w/X7HeGOTMcf+uae9/1znets9ZdK587jjB+zp7nPHs/JCIiQmrep9inPUctXb9+nURERJANGzaw+lRy/rb430RYWJiMTyVHLXV2dlI2ODhYiu05f7u9vZ2y/v7+Mj6VHLUk6dPFixdLsT3nbzc1NVFWci5zT59WVlaShoYGykrOEQVk52/X1tZS1sfHh9Wnp0+fJrW1taS6upqynp6eUmzP+duSPp04cSKrT8+fPy/j0zFjxsj4VHLUUklJCWWHDRvG6lPxaBBJnw4cOFCKtba2lhq1VFBQQFknJycp1tbWVmo0SH5+PmXt7e2l2D495m9L+lQ871l89Zy/nZWVRVnxvGfxJZ6/LfZpRkYGXcuK55OKr57zt1NTU6lPxfOexVfP+dsvXrwgERER5MKFCzI+7Tl/W+zTv/76S8anPedvi3165swZOp9UfPWcv52cnEwiIiLIqVOn6HzSnj4Vz98W+1RyzrH46jl/OzExkURERJAff/yR1aeS87cTEhJIRESE1Ix5sU/F87fFa1mxTyVnIovZnvO379y5QyIiIsj+/ftl3Kto/vY/Gfwn54j+p67/9S+ie/bskfkAsl2GhoYyizt5l7GxMXFxceHEmpiYkAEDBnBizczMZBaN8i4+n0/69evHibWwsJARorxLKBTKLEblXdbW1nS4c2+Xra0tEQqFnFh7e3sZ0cq7+vXrJ7PIlXf179+fGBsbc2IHDBggI2V5l4uLCx0a3dvl5uYmI2V51+DBg2VEK+/q+SXmP8GqqKjI3Mz/E6yqqipnVk1NjQwfPpwzy/V11dXVOb+uhoYG59fl8XicWS0tLc6/C21tbalh7oouHR0dMnjwYE6snp4eZ1ZfX5+4ublxYg0MDDj71MjI6J351NHRkRNrbm5OHBwcOLEWFhakb9++nFhLS0vOPrWysiI2Njac2LfxaZ8+fWSKsPKuvn37EnNzc05s//79ZRa58i4nJydiYGDAiXV2dpYp2Mq7Bg4cSDQ1NTmxgwYNkikayLvehU8BvDOfcnXZ27Bv497/BZ9qampy/l28jXt1dHQ4u1dXV/ed+bTnl2V519v41NjYmDg7O3NiTU1NZb6Ey7vMzc05r2UFAgHntaylpSXp06cPJ9bKyorY2tpyYm1sbGQKAfIuOzs7zj61t7fn7FMHBwfOPnV0dCQbN27sdT75uwg4fhHtdXzL/59ibGwMBwcHAG9a2th6yt3c3MAwDJqbm2lveFFREWtP+eDBg8EwDGpra2lveGFhIWtP+bBhw8AwDMrKymi/96tXr1j7xEeMGAGGYVBYWEj3d+Tn58v0iauoqGDUqFEQiUTIzs6mrRt5eXkye2lUVFQwZswYMAyDly9f0vac3Nxcmf0xqqqqGDduHEQiER4/fkxbj3JycmT2m6ipqcHd3R0MwyAhIQFaWloghLDuyVNTU8OECRPAMAxiY2Oho6Mjl1VXV8ekSZPAMAyuX7+OnJwcdHd3Izc3V4bV0NDA5MmTwTAMLly4gMLCQnR1dbHuTeHxeJg6dSoYhsGff/6J0tJSdHZ2su4L1NTUhIeHBxiGwc8//4zq6mp0dHSw7mPR1taGp6cnGIbB0aNH0dDQgLa2NtZ9LDo6Opg2bRoYhsHBgwfR1taG1tZW1j2Eurq68PLygkgkwp49e0AIQUtLC+ueF319fXh5ecHX1xc7duyAmpoampubWfcbGhoaYsaMGZg2bRp2794NNTU1NDU1se6PMTIygre3N6ZMmYK9e/dCVVUVDQ0NrPtjjI2N4ePjgwkTJmDfvn1QVVVFfX09695EU1NT+Pr6YsyYMdi/fz9UVVVRV1fHupfG3Nwcvr6+GD58OGpqaqCqqora2lrWfYwCgQAikQhubm6oq6uDiooKampqWPfdWFpaQiQSYcCAAaitrYWKigqqq6tZ95BbWVmBYRj07duXvm5lZSXrvhsbGxswDAMbGxvKVlRUsO557NOnDxiGgUAgQH19PVRUVFBeXs66R6dv375gGAYmJiZoaGiAiooKysrKWPfo9O/fHwzDQFdXl+5zLC0tZd2j4+TkBIZhoKGhQdni4mLWPTouLi4QiUT0swjI9+nAgQPBMAza2tp69emgQYPAMAzq6+t79enQoUPBMAwqKyupFwsKClj36IwYMQIikQivX7+mrmPzKQCMGjUKDMNIOUmeT0ePHg2GYZCWlkZbDeX5dOzYsWAYBk+ePFHoU1VVVerTxMREaGpqcvLp7du3e/XpxIkTwTAMIiMjkZ2d3atPRSIRLl++jFevXin06ZQpU8AwDM6ePYvi4mKFPhW797fffkNlZaVcn2ppaVGfHjt2jH4m2PZki30qEolw6NAhtLa2KvTp9OnTwTAM9u7di+7ubrk+1dPTg5eXFxiGwfbt2xX61MDAADNmzICXlxd27dql0KeGhobw9vaGh4cH9uzZA1VVVTQ2NrLu9Rb7dOLEifjyyy8VutfU1BQ+Pj4YO3YsdeR/yqe+vr4YMmQIdaQ8n1pYWEAkEsHFxYWTT0UiERwcHKgjq6qqWPc8in1qa2vbq0/t7OzAMAwsLS179am9vT0YhoGZmRll5fnUwcEBDMNAX1+fOlSeTx0dHcEwDDQ1NalPS0pKWPebOzs7g2EYqKioUIfKc6+rqysYhkFHRwd1aG8+bWho6NWnQ4YMAcMwdI0DyPfp8OHDIRKJUFJSQr0oby07cuRIMAyD/Pz8XteyYp+mp6fTtSybT1VUVKhPU1JSaAu7Ip+KRCI8evSItuez7XFWU1PD+PHjwTAM4uLioK2trdCnYvdGR0cjMzNTLquhoUHXsleuXEF+fr5c9/J4PLqWFW/54eJTX19fWFtbyzD/M+HybfU/df2vPxEVp6qqilZkeTwe8fLyIt999x1t75FMWVkZfcLF1i4pmaKiIlqR1dLSIiKRiLZL9kxubi5tOxC3Sx4/fpwUFxfLsOnp6fRpmK6uLpk9ezZtl+yZlJQUWikRt0v+8ssvpLy8XIZNSkqSqrKJ2yUrKipk2Li4OMoaGhqShQsXklOnTpGqqioZNioqSqrKJtku2TNXrlyRqrItXbqUnD17ltTW1sqw586do6yZmZlUu2TP/P7775Tl8/lk5cqVtF2yZ3744QfKitslL126RBobG2XYw4cPS1XZgoODyZUrV0hTU5MMu2/fPqkqW2hoKLl27RppaWmRYSVbfu3s7EhYWBhtl+yZTz75RKrKFh4eTqKiokhbW5sMK9l21rNdsmdCQ0Olqmzi9nM2VrKVzNnZWapdsmckW3PF7efidsmemT17NmUHDRpE2yW7urpkWG9vb8qK28/F7ZI9M2XKFMqK2yUfPXokw3Z3d0u1fInbz8Xtkj1ZcXVcsl1S3H4umc7OTlqZlmw/F7dLSqajo4NWhdnazyXT1tZGn5yJ288l2yUl09zcTKu34nbJr7/+mrZLSqa+vp5uSRC3n3/zzTckOztbhq2pqaFbEiTbz9l8Wl5eTp9wiX0q2S4pmeLiYrolQbL9nK3ym5+fT7ck9GyX7JnMzEzqUx0dHdp+XlJSIsO+ePGCttD2bJfsmeTkZPq50dfXJ/PmzaPtkj0THx8v5VPJ9vOeiYmJkfGpuF2yZ65du0bZnu3nPXP+/HkZn4rbJXvm1KlTUj4Vt5+zufenn36S8qlku2TPSLYHS7afs/n0wIEDlO3ZLtkzki2/tra2tP2czb2SWyh6tkv2zMaNG2V8Km6X7BnJNt6e7ZI9s2rVKsqK28/F7ZI9s2TJEsqK2yXl+VRyq4O4/VzcLtkzvr6+lBW3S8rzqYeHh5RPJdslJdPd3U3c3d0p27NdsicrfpIq9qlku6Rkurq66FNByfZzcbukZDo6OugTObFP9+7dS9vPJdPW1ka7FiTbz8XtkpJpaWmhWxJ6a5dsbGyk3VqS7edsPq2traVbEjQ0NMi0adPI4cOHSW5urgxbUVFBtyTweDzafi7e+iOZkpIS2kKrqalJfHx8pNrPJVNQUCDj02PHjrGuZbOzs2l3gWT7OdtaNjU1lfpUV1eXzJkzh5w4cYJ1LfvkyRMpn4rbz9nWsvfv35fx6e+//04qKytl2NjYWMpKtp+zuffGjRtS7l28eDE5ffo061r24sWLUmvZZcuWkbNnz7L69PTp05Q1NzcnK1asIOfPn2f1qeTWDIFAQAICAsiFCxdY17L/dKBszf2/59tvv1X4i5fMgQMHFN5IJfPFF1+QwMBAuu9AUbZv367wRiqZTz/9VGrfgaJ8+OGHZO3atSQyMpL1RiqZdevWSe07UJTQ0FCFN1Jxuru7SUBAgNS+A0Xs8uXLpfYdyEtXVxdZtGiR1L4Deens7CTz588nn376Kd13IC/t7e1k9uzZcm+kkmltbSUzZ84k27ZtY72RSqapqYmIRCK5N1LJ1NfXEx8fH6l9B/JSU1NDvL29pfYdyEtFRQXx8vKS2ncgL8XFxcTLy4vTvoOCggLi5eVFDh48yHojlUxOTg6ZMWOG3BupZNLS0siMGTPId999x3ojlcyzZ8+Ij4+P3KKQZB4+fEhEIpHcG6lk4uLiiJ+fn9yikGSio6PJ7Nmz5d5IJXPt2jWFRSHJXLhwgcyfP1/ujVQyZ86cUVgUksxvv/2m8EYqmePHj9OiENuNVDJHjhzh7NODBw+SlStXcrqRfvnllyQwMJBcunSpV5/u3LmTBAcHk6tXr/bq0y1btpDVq1fLLQpJZtOmTSQsLIyTT9evX6+wKCSZNWvWSJ1JoCiBgYFSZxLIS3d3N1mxYoXUmQSK2MWLF0udSSAvnZ2dZMGCBZx82tHRQd577z2pMwnkpTwhtrYAACAASURBVK2tjcyaNYts27aNnkkgL83NzYRhGKkzCeSloaGB+Pr6kt27d7MWhSRTW1tLvL29pc4kkJfKykri5eUltygkmdLSUuLl5SV1JoG8FBYWkunTp0udSSAveXl5xMvLS+pMAnlJT08nM2bMkFsUkkxKSgpnnz569EjqTAJFiY+Pp0V2tqKQZGJjY6XOJFCUGzdu0DMJ2IpCkrl06ZLCIrtkzp49SxYuXCi3KCSZkydPKiyyS+ann35SWBSSzNGjR2mRvTf3Hjp0SGGRXTL79u1TWGSXzK5duxQWhSSzdetWhUV2yWzevFnqTAJF+eCDD6TOJFCUsLAwhUV2yQQHB5MPPviA01rW399fYZFdkl2yZInCopA4XV1dZOHChVJnEshLR0cHmTt3rsKi0H8zXL+IqpAej6rfZUaMGEEePXr0j/15yiijjDLKKKOMMsooo4wyyvxzUVFRSSaEjOiNU84RVUYZZZRRRhlllFFGGWWUUeYfjfKLqDLKKKOMMsooo4wyyiijjDL/aJRfRJVRRhlllFFGGWWUUUYZZZT5R6P8IsqShw8fsh6VzpbExETW0RNsSUhIYD3+nC337t1jPf6cLXFxcaxHmrPlzp07rEeas+X27dusR5qzJSYmhvWY8p4hhCA6Opr1mHJ5LNsx5T3T3d2NqKgo1hERPdPV1YXo6GjWI817pqOjA9HR0axHmvdMW1sbYmJiWI8075nm5mbExsayHmneM42Njbh79y7rOImeqa2txb1792TGSbClqqoKCQkJnNjy8nI8ePBA5qh0tpSUlCApKYkTW1RUhMePH8scq86WgoICPH36lBObl5eH58+fc2JzcnLw8uVLTmxmZibS09M5sWlpacjMzOyVA4CXL1+yHu3OlufPn7OOymDL06dPWcdfsOXx48es44TY8ujRI9aRFmx5+PAh65gKtiQmJrKOnmDL/fv3WUdPsCU+Pv6d+ZRtPA9b3sansbGxrCMi2HLr1q23ci8XnxJC3olPOzs7Ofu0vb0dt27d4uTTlpYWxMTEcPbpnTt3OPm0rq4OcXFxnNjq6mrOPq2oqEBiYiInR5aWlnL26evXr5GcnPwf92l+fj5SUlI4+/TFixec2KysLKSlpXFi09PTkZGR0SsHAKmpqawjONjy/Plz1lEZbHn27Blnnz558oSzT5OTkzn7NCkpibNPHzx48M58+jZrWbbxPGy5e/fuO1nLvo1P3+ValotPxWtZLj4Vu5eLT/+Xo7Zt27Z/7A/74YcftgUFBf1jf97/NS9fvsSQIUNw7do1lJaWwtDQEAKBgM4ukkxycjJGjhyJGzduoLy8HIaGhuDz+axsQkICxowZg5s3b6KiogLGxsYwNzdnZWNjYzF+/HjcunULFRUVMDExgZmZGSt748YNTJ48GTExMaiqqoKpqSnMzMxY/26XLl2Cp6cn7ty5g+rqapibm8PExISVPXPmDLy9vXH37l3U1tbC3NwcxsbGrOyvv/4KhmEQHx+P2tpaCAQCGBkZyXAqKir44YcfMGfOHCQkJKC+vh4WFhYwNDRkZQ8fPoz58+cjMTERDQ0NsLS0hIGBASv71VdfYcmSJXj48CEaGxshFAqhr68vw6qqqmLHjh1YsWIFkpKS0NzcDKFQCD09PRlWTU0NmzdvRmBgIB4/foyWlhZYWVlBV1dXhlVXV8f69euxZs0aPHnyBK2trbC2toaOjo4Mq6GhgZCQEKxfvx7Pnj1DW1sbrK2toa2tzcouX74cH374IVJSUtDR0QErKytWVlNTE/Pnz8cnn3yCFy9eoKOjA9bW1tDS0pJhtbS0MHPmTGzbtg0vX75EV1cXbGxsoKmpycqKZ4qmpaWhu7sbNjY2dO5WT3bSpEnYt28f0tPTAQDW1tasrKamJsaOHYuvv/4amZmZUFFRgY2NDZ2l2PPnMGLECHz77bfIysqirHhOmGTU1NQwdOhQHD16FNnZ2VBTU5PLAm9mqh0/fhy5ublQV1eHjY0NnaUrma6uLjg7O+PXX39FXl4eeDwerK2tWdn29nYMGDAAJ0+exKtXr8Dj8WBlZcXKNjU1wcnJCX/++ScKCgqgpaUFKysrOn9SMrW1tXBycsK5c+dQUFAAbW1tuWxFRQUGDBiA8+fPo6ioCLq6urC0tGRli4qK4OLigkuXLqG4uJiybM7JycmBm5sbrly5gpKSEujr68PCwoKVTUtLoz4tKSmBgYGBXPbp06cYMWIErl+/jrKyMoXuffDgAUaPHo3IyEiUl5cr9Ondu3fh7u6O6OhoVFZWwtjYWK5Pb968iUmTJiEmJgaVlZUKfXrlyhV4enri9u3bqK6uhpmZGUxNTVnZc+fOYcaMGbhz5w5qamrA5/Pl+vTkyZMQiUS4d++eQp8CwE8//YTZs2cjPj4e9fX1EAgEcn165MgRzJs3D4mJidS98nx64MABLFq0CA8ePEBjYyMsLS3l+nTXrl1Yvnw5kpKS0NTUJNenqqqq2LJlC1atWoXk5GS0tLRAKBSy+lRNTQ0bN25ESEgIHj9+jNbWVlhZWcn16Zo1axAeHo6nT5+ira1NLsvj8eDv748PPvgAKSkpaG9vl+teTU1NLFy4EJs3b8aLFy/Q2dmp0Kd+fn74/PPPqU+tra3l+tTb2xs7d+5EWloada88n4pnNIuLYIpYd3d3HDhwgBbB5PmUx+Nh1KhROHToELKysqCqqgpra2tWVk1NDcOGDcP333+PnJwcyrL5VFVVlfo0JycH6urqctnu7m64urri559/Rm5uLjQ0NOT6tKOjA87Ozvjtt9+Qn58PTU1NuT5tbm7GgAEDcOrUKbx69UqhT+vr6+Hk5ISzZ8+isLBQIVtZWUl9WlhYCB0dHQiFQla2pKQEzs7OuHjxIl6/fg1dXV0IhUJW5+Tn52PgwIG4fPkyiouLFfo0MzMTgwYNQkREBEpLSxWyKSkpGDZsGCefJiUlYdSoUdSnRkZGctey9+7dw7hx4xAVFdXr+jQ6OhoTJ07ErVu3qE9NTU1Z2YiICEydOhWxsbG9+vTvv//G9OnTqU8VrWX/+OMP+Pj4IC4uDrW1tQrde+LECfj5+SEhIQF1dXUK17JHjx7F3Llzcf/+fTQ0NCh078GDB7Fw4UIkJiYq9KmKigr27t2LpUuXcvLp1q1b4e/vj0ePHqG5uVnu+vS/ke3bt5ds27bth9445am5EsnIyKBPRsLCwqSeilpbW0MkEoFhGEydOhV5eXm0khccHCxVbbe1tQXDMBCJRJgyZQqysrKQmZmJrq4uBAYGSlVx7O3t6etOmjQJaWlpyMnJQWdnJ1auXClVbenXrx9lJ0yYgBcvXiA/Px/t7e3w9/eXqqCIh9UzDAN3d3c8e/YMBQUFaGlpgb+/v1TleMCAAfT9jhs3jlbnGhsbsXLlSqkKr4uLC33dMWPG0KcdtbW1WLVqlVRl083Njb7fUaNG4f79+ygvL0dFRQVCQkKkfvaDBw+m72HkyJG4d+8eKisrUVJSgrCwMClWPKyeYRgMGzaMiujVq1fYsGGDFDtixAj6ukOHDsWtW7dQX1+P7OxsfPTRR1KseFg9wzAYNGgQoqKi0NjYiNTUVHz22WeUU1FRwZgxY+jrDhw4EDdu3EBLSwuePXuGHTt2UFZyWD3DMHB2dsa1a9fQ1taGpKQk7N27l7Jqamp0uDLDMHBycsKVK1fQ2dmJ+Ph4fP3111KseGAywzDo378/Lly4AEIIbt++jW+//Zay6urqdGCySCRC3759ceHCBQBAVFQU/v3vf1NWPKxe/LrW1ta4fPkygDc3iRMnTlCWx+Nh6tSp9P0KBAJEREQAAC5cuICTJ09SVktLiw5XFolEMDU1xfXr1wEAZ8+exZkzZyirra0NDw8PyhoYGODmzZsA3izQxe8d+H+H1YuHNmtra+PWrVsAgJ9//hlXr16lrOSwel9fX2hoaCA2NhYAcOzYMfpnAIC+vj4dVu/t7Q0VFRXcvXsXAPDtt9/i9u3blBUPqxezXV1duHfvHgDg66+/Rnx8PGWNjIzg7e0NkUgEb29vtLa24v79+wCAvXv3IikpibImJibw9vYGwzCYMWMGGhoa8PDhQwDAzp078fTpU8qKh9UzDAMvLy/U1tZC7NrPPvsMqamplBUPq2cYBtOmTUNlZSWePHkCAPj444+RlZVFWQsLC/j6+kIkEmHatGkoLS3Fs2fPAAAbNmyQejpgaWlJPwseHh4oKiqiT0bWrl0rVcUXD6sX+zQ/P5/6NCQkRKrabmtrC5FIRH2ak5ODjIwMdHd3IzAwUOqJZJ8+faR8mpGRgezsbHR2diIgIECq0t23b1/6OZ8wYQJevnyJvLw8tLe3Y+XKlVLV6/79+9PXHT9+PFJSUvDq1Su0trbC399f6qmdk5MT/ey6u7vj8ePHKCoqQlNTE/z9/aV8Kh5WzzAMxo4dS31aV1eHgIAAKZ8OHDiQvofRo0fTp8dVVVXoWeAVD6tnGEbKp6WlpVizZo0UK/apSCTC8OHDcffuXVRXV6OwsBDr16+XYocPH05fd+jQoYiJiUFdXR1ycnKwadMmKXbUqFH0/Q4ePBjR0dFoaGhAeno6Pv30U8pJDqsXiURwc3NDZGQkmpubkZKSgu3bt0uxkj51cXGhPk1OTsYXX3xBWfGwejHr5OSEq1evoqOjA/fv38f+/fspKzmsnmEYODo64uLFi+ju7sbdu3dx6NAhyqqrq2PixIn0/To4OODvv/8G8GbRffToUcpKDqtnGAa2tra4dOkSAODatWv46aefKMvj8TBlyhT6M7O0tKT+unTpEn777TfKSg6rF4lEMDMzoz7966+/8Oeff1JWS0sLnp6e1HtGRkaIjIwE8GaBfv78ecrq6OhIsbq6uoiOjgYA/PLLL7hy5QplxT4ViUTw9fWFpqYmYmJiAADHjx/HjRs3KKunp0d96uPjA1VVVdy5cwcAcOTIEfr/A974VJKV9Ok333yDuLg4yhoZGUm5t62tDQkJCQCAffv24cGDB5Q1NjaW8mlTUxP977t27aIOBKR9On36dNTX11M3b926FS9evKCsubm5FFtVVYXHjx8DADZv3izVFSMQCKR8WlZWRn26ceNGqU4XS0tL6mlPT0+8fv2advmsW7dO6gmq2KcikQgeHh549eoVUlNTQQjB6tWrpbr2bGxs6GdsypQpyM3NRXp6Orq7uxEcHCz19NLOzo5+xiZPnozMzExkZWWhq6sLAQEBUk8Z7e3t6ed84sSJSE1NRW5uLjo6OuDv7y/lUwcHB6m17PPnz5Gfn4+2tjasWLFCyqeOjo5Sa1nxk+bm5mb4+/tLdSs4OzvT1x07diwePXqE4uJi1NfXIyAgQKqrwNXVlb7u6NGj8eDBA5SWlqK6uhqBgYGQjJubG2VHjRqF+Ph4VFRUoLy8HKGhoVLskCFD6M9sxIgR1KevX79GeHi4FDts2DCptWxsbCxqa2uRl5eHjRs3SrEjR46krztkyBDq08zMTGzevJlyKioqUmtZNzc31i/9/0S4npqrnCMqkT179tDBsIouHR0d4ujoyInV1dWlw5J7u/T19YmDgwMn1sDAgPTt25cTa2RkRPr06cOJNTExIba2tpxYU1NTYm1tzYk1NzcnQqGQEysQCIiFhQUn1tLSkpibm3NiraysiImJCSfWxsaGGBoacmL79OlDh0b3dvXt25cOje7tcnBwoEOje7scHR2JqqoqJ3bAgAGcOADE2dmZM+vi4vJOWFdX1/84q6KiQgee/ydZVVVVzqyamhpnVl1dnfPfTUNDgzPL4/E4/y40NTU5fx60tLQ4f860tbWJk5MTJ1ZXV5eze/X09N7Kp/369ePEGhoaEnt7e06ssbExsbOz48SamJgQGxsbTqyZmRmxsrLixPL5fM4+tbCwIHw+nxMrFAqJqakpJ9ba2poYGRlxYu3s7Ii+vj4n1t7enujo6HBi+/XrRzQ1NTmxjo6ORE1NjRP7Nj59G/a/7ci3Yf+/6NN35d535VOu7Nv49G3Wsnp6em+1ln0XPjUyMnorn3Jdy76tTy0tLTmxb+tTMzMzTqy1tTUxNjbmxNra2pKwsDBSWFj4j3+nAsc5osrWXIlkZGQgNzcXfD4fTU1NrPtNRo0ahYCAAPTv358+4m9oaJDZQyJ+arZq1Sr06dMH9fX14PP5qK+vl2FVVVUxbtw4BAQEwNraGo2NjeDz+aitrZXZb6Kqqorx48cjMDAQfD4fzc3N4PP5qKmpkdlDoqamhokTJyIwMBAmJiZobW0Fn89HdXW1DKuuro7JkycjMDAQ+vr66OjoAJ/PR2Vlpcz+DQ0NDUydOhVBQUHQ0tJCV1cX+Hw+6/4CHo8HT09PBAUF0fYVc3NzVlZTUxPTp09HUFAQurq6oKqqKpfV0tLCjBkzEBQUhLa2NmhoaMDU1JR134K2tjZ8fHwQHByMhoYGaGlpwcTEhJXV1dWFSCSilUEdHR0YGRmx7i/T09MDwzAIDg6mLTKGhoas+yEMDAzg5+eHoKAgFBUVwcjICAYGBqysoaEhZs+ejeDgYOTk5MDU1BR6enqseyeMjY0xZ84cBAcHIyMjA3w+H7q6uqz71kxNTTF37lwEBQUhNTUVAoEA2trarPsszMzMMG/ePPj7+yM9PR0CgQBaWlqsLJ/Px4IFC7Bs2TLK8ng81v1wFhYWWLhwIRYtWoTMzEwIBAJoaGiw7t8QCoVYtGgR5s6di5ycHAgEAqipqbHu37C2tsbixYsxe/Zs5ObmQiAQQFVVlZW1s7PDkiVLwDAM8vLyaKsS214Pe3t7LF26FN7e3sjPz4dAIAAhhHWfnYODA5YtWwZPT08UFBRAIBCgu7ublXV0dMTy5csxZcoUFBYWQiAQoLOzk3UPibOzM5YvX47x48fj9evXEAgE6OjoYN1D4urqihUrVmDMmDEoLS0Fn89HW1sb6x6SQYMGYcWKFRg+fDjKy8vB5/PR2trKyg4ZMgQrV67E4MGDUVFRAT6fj5aWFtb9e8OGDcPKlSvh6uqKqqoqhT4dOXIkAgIC4OjoSNtVGxsbZVjxU7OAgADY29ujrq5Ork9VVFQwbtw4rFq1CjY2NmhoaACfz0ddXR2rT93d3bFq1SpYWFigqamJk09NTU179emkSZMQGBgIQ0NDtLe39+rTwMBAaGtrK/SphoYG9am6ujoIIZx8Sgjp1adeXl4IDg5GW1sb1NXVYWZmxspqa2vD29sbwcHBaGpqgqamplyf6ujowNfXF8HBwaitrYW2tjaMjY3l+lTs3vLycujp6cn1qb6+PvXp69evYWhoqNCns2bNQnBwMPLz82FiYgJ9ff1efZqZmQlzc3O5PjUxMcF7772H4OBg6lMdHR1WVuzTlStXcvLp/PnzsWzZMmRkZEAgEEBTU/M/4tP3338fCxYsQFZWFgQCAdTV1VlZa2trLFq0CO+99x51rzyf2traYsmSJfDz86PulefTPn36YOnSpfD19aU+BcDK9uvXD8uWLcO0adN69Wn//v2xbNkyTJ06lfq0q6uL1acDBgzA8uXLMXHiRBQVFSn0qYuLC1asWIGxY8eipKQEfD4f7e3trKybmxv8/f0xcuRIlJWVKfTp4MGD4e/vjyFDhvyffNrc3MzKjhgxAgEBAXBycuLsUwcHh17XsmPHjsWqVatgZ2dH17LyfCp2r1AopD6Vt5adMGECAgMDYWZmhpaWFrk+VVNTo+tTSZ9WVVXJ+FRdXR1TpkxBUFAQdHR00NnZqdC9Hh4eCAoKAo/HQ3d3t1xH8ng8TJs2DUFBQfQJoyL3enl5ISgoCJ2dnVBTU+vVp0FBQWhpaQGPx5O7ltXR0aFr2bq6OoU+1dXVBcMwCAoKwqpVq2BpaSnDvOtwbc1VPhFlSUVFBX3CpaOjQ/z8/MiPP/5ISkpKZNji4mKipaVFgDfV+jlz5pATJ06QsrIyGfbVq1f0CZe+vj6ZO3cu+fXXX0lFRYUMm5WVRSuyBgYGZP78+eT3338nlZWVMuzLly+JiooKrRi9//775I8//iDV1dUy7OPHj6UqRkuWLCGnT58mNTU1Muz9+/cpa2pqSpYtW0bOnTtH6urqZNjY2FjKmpubkxUrVpDz58+T+vp6Gfb69euUFQgEJCAggFy8eJE0NjbKsBcuXKCspaUlCQwMJJcvXyZNTU0y7J9//klZKysrEhISQq5evUqam5tl2J9//pmyNjY2ZPXq1eT69eukpaVFhv3+++8p26dPH7J27VoSGRlJWltbZdivv/6asn379iXr1q0j0dHRpK2tTYb94osvKOvg4ED+9a9/kZiYGNLe3i7Dfv7555R1cnIiGzduJHfu3CEdHR0y7KZNmyjr4uJCPvroIxIXF0c6Oztl2PDwcMoOHDiQbN68mSQkJLCygYGBlB08eDD59NNPSWJiIunq6pJhly5dStmhQ4eSzz//nCQlJbGy8+bNo+zw4cPJtm3bSHJyMunu7pZhGYah7KhRo8jOnTvJkydPWNlp06YR4E0FfsyYMWT37t0kJSVFhu3u7iYTJkwgwJsKvLu7O9m7dy958eIFKztixAjKTpgwgezbt4+kpaXJsF1dXcTNzY0Ab6r1kydPJvv37ycZGRky77Wzs5NWptXV1cnUqVPJwYMHSVZWlgzb3t5OOxw0NDSIp6cnOXToEMnJyZFhW1paaKWXx+MRLy8v8t1335H8/HwZtrGxkXYXaGpqEh8fH/L999+TgoICGba2tpZWZLW0tIhIJCLHjh0jRUVFMmxlZSV9wqWtrU1mzpxJjh8/ToqLi2XY0tJS2jGgq6tLZs+eTU6cOEFKS0tl2MLCQsLj8Qjwplr/3nvvkV9++YWUl5fLsDk5OURdXZ2TT9PS0mh3gaGhIVm4cCE5deoUqaqqkmGfPn1KP4/GxsZk8eLF5M8//2T16YMHD6R8unTpUnL27FlSW1srw965c0eqWr98+XLy119/sfr05s2bUj5duXIluXDhAmloaJBhL1++LOPTS5cusfr0zJkzUj4NDg6W69Nff/1VyqehoaHk2rVrrD49duwYZe3s7EhYWJhcnx46dIiy9vb2JDw8nERFRbH69Msvv+Ts023btlHW0dGRfPDBB+T27dusPv34448p6+zsTDZt2kTu3r3Lyq5fv56yrq6u5OOPPybx8fGsPg0JCaHsoEGDyCeffELu37/P6sgVK1ZQdsiQIeSzzz4jDx8+ZGUXLlwo49NHjx6xOtLPz4+yI0eOJDt27JDrUy8vLymf7tq1izx79oyVnTRpEmXHjRtH9uzZI9eno0ePpj4dP348+fLLL0lqaiorO2TIEOrTSZMmKfSp+Amiuro6mTJlCvn666/l+lTcXdabT1tbW2kXGI/HI9OnTyfffvstycvLk2GbmpqIQCCgPvX29iZHjhwhr169kmHr6+tpt5aWlhbx9fUl//73v1l9Wl1dTQwMDGR8+vr1axm2rKyMdgzo6OiQWbNmkZ9++onVp0VFRbRjQOzTn3/+mXUtm5eXR32qr69P5s2bR3777TfWtWxGRoaUTxcsWEBOnjzJ6tPnz59L+XTRokVyffro0SOZteyZM2dYfXrv3j1Wn7KtZaOjoynL5/OJv78/+fvvv1l9evXqVcpaWFiQVatWyV3L/vXXX5QVCoUkKCiIXLlyhdW9J0+epKy1tbVCn/74449STz/XrFlDbty4werTfzrg+ERU+UWUJUeOHCEhISEkIiKC9RcvmYMHD3L+xX/55ZckPDyc3Lx5k/VGKpldu3aR9evXk1u3brHeSCXz+eefkw0bNpDY2Nhe2c2bN5MPP/xQ7o1UMh988AH56KOPyL1791hvpJJZu3YtvZEqYru7u0lwcDDZsmULefDgAeuNVJINCAggW7dulfslRpyuri6ybNkysn37dvL48WPWm6M4nZ2dZPHixWTXrl3k6dOnCtn29nayYMEC8sUXX5Dnz58rZFtbW8ncuXPJl19+SV6+fKmQbWpqInPmzCFfffUVSU9Pl8sRQkhDQwOZNWsWOXDgAMnMzFTI1tTUED8/P/LNN9+Q7OxshWxFRQWZOXMmOXz4MOuNVDLFxcVk5syZcm+kkikoKCAzZ84kR48e7bUdJCcnh/j5+ZEffviB9UYqmbS0NDJr1iy5RSHJPHv2jMyZM0fujVQySUlJCotCkomLi6M3UrYvMZK5deuWwqKQZK5fv66wKCSZixcvKiwKSebs2bMKi0KS+f333xUWhSTz008/KSwKSebo0aPUp2xfYiRz6NAhhUUhyezfv5+sXbuW3Lx5s1f3fvHFFwqLQpLZunUrZ59+8sknCotCktm4caPCopBk1q1bp7AoJJnQ0FCFRSFxuru7SWBgoMKikCS7fPlyhUUhcTo7O8mSJUvIzp07e/VpR0cHWbhwodyikGTa2trIvHnz5BaFJNPc3EzmzJkjtygkmYaGBjJ79mxy4MAB1i8xkqmtrSV+fn7k4MGDvfq0srKS+jQ3N1chW1paSmbOnCm3KCSZoqIiMnPmTLlFIcnk5eWRmTNnyi0KSSY9PZ3MmjVLblFIMikpKQqLQpJ59OiRwqKQZBISEhQWhSQTGxursCgkmcjISLJ48WJOPr18+TItCvXm07/++ouzT0+dOqWwKCSZX375hbNPjx07prAoJJlvv/2WrF69Wu6XGMkcOHBAYVFIMnv27FFYFJLMjh07FBaFJLNlyxaFRSHJbNq0iWzatImTT9evX6+wKCSZNWvWvJVPFRWFJFl/f3+FRSFxurq6yNKlSxUWhcTp7Owk77//vsKi0H8zXL+IKg8rUkYZZZRRRhlllFFGGWWUUeY/Eq6HFSnniCqjjDLKKKOMMsooo4wyyijzj0b5RVQZZZRRRhlllFFGGWWUUUaZfzTKL6LKKKOMMsooo4wyyiijjDLK/KNRfhFlSXx8vNSgdkWJi4tDYWEhJ/bOnTsoWVAioAAAIABJREFULi7mxMbGxkoNgFeUW7duoaysjBMbHR3NeoQ0W27evMl6LDRbbty4wXocfs8QQnDt2jXWI+7lsWzH1vdMd3c3IiIiWI+i75muri5ERESwHkXfMx0dHYiIiGA9Mr5n2tracO3aNdYj43umubkZ169fZz0GvmcaGxtx8+ZN1mPge6a2thbR0dGsR7v3TFVVFWJiYljHavRMWVkZ7ty5I3O0O1uKi4sRFxfHiS0sLERCQoLM0e5syc/PR2JioszR7mzJyclBUlISJzYrKwvJyckyR7uzJT09HU+fPuXEvnz5EikpKZzYlJQUvHz5khP79OlTpKWlcWKTk5ORkZHRKwcASUlJyM7O5sQmJiYiNzeXE5uQkMDZp/fu3ePs07t370oNdVeU27dvc/ZpTEzMO/FpVFQUZ59GRkayjiJhy/Xr19/KvWwjQ9jYd+HTzs5OREREsI7r6Jn29nbOPm1paXkrn0ZGRnLyaV1dHaKiojj5tLq6mrNPy8vLcfv2bU5sSUkJZ58WFRUhPj6ek09fvXqFxMRETmxubi4ePnzI2aePHj3ixGZkZODJkyecXJaamopnz55xYp8/f44XL15w9mlqaion9vHjx2/l06ysLE7sgwcPOPv0/v37yM/P58TGx8ejoKCAExsXF4eioiJO7O3bt99qLVtaWsqJvXXrFsrLyzmxUVFRrCNO2BIZGfnO1rJv49O3Wcty8anYvVx8+r8c5RxRlmRnZ2PYsGH4+++/UVRUBF1dXVhaWtI5mJJ58eIFRo4ciUuXLqG4uJiy4jlDkklOTsaYMWNw5coVlJSUQF9fXy6bkJAAd3d3XLt2DSUlJTAwMICFhQUrGxsbi0mTJuH69esoKyuDkZER+Hw+K3v9+nVMnToVkZGRKC8vh7GxMczNzVnZixcvYvr06YiOjkZlZSWMjY1hZmbGyp4+fRq+vr6IiYlBZWUlTE1NYWZmJsOpqKjg119/hZ+fH27fvo3q6mqYmZnB1NSUlT127Bjee+893Llzh87FMjY2ZmUPHz6MhQsX4t69e3TOoJGRkQyrqqqKffv2YcmSJYiPj0d9fT0EAgEMDQ1lWDU1NWzfvh3+/v5ITExEQ0MDLCwsYGBgIMOqq6vj448/RmBgIB48eIDGxkYIhULo6+vLsBoaGli/fj3WrFmDpKQkNDU1QSgUQk9PT4bl8XgICgrCunXrkJycjJaWFgiFQujq6sqwmpqaWLZsGTZu3IjHjx+jtbUVVlZW0NHRkWG1tbUxb948bN68GU+fPkVbW5tcVkdHByKRCFu3bkVKSgra29thbW0NbW1t1tedPn06du7ciRcvXqCzsxPW1tbQ0tJiZSdNmoQ9e/bg5cuX6OrqgrW1NTQ1NVn/bu7u7vjqq6+QlpaGrq4u2NjYgMfjsf7MRo0ahW+++Qbp6ekghMhl1dTUMHz4cHz77bfIzMwEANjY2EBDQ0OGBd7M3/z3v/+NrKwsqKqqwsbGBurq6jJcV1cX3NzccPz4ceTk5Chk29ra4Orqil9++QU5OTlQV1eHjY0N1NTUZNjGxka4urri999/R25uLjQ0NGBtbc3K1tbWwtXVFadOnUJ+fj40NTVhZWXFypaXl2PgwIE4c+YMCgoKKMvmvcLCQgwePBjnzp1DYWEhtLW15bI5OTkYOnQo/v77bxQWFkJHRwdCoZCVTU1NxYgRI3Dx4kW8fv0aurq6EAqFrM558uQJRo8ejcuXL6O4uBj6+vpyHZmYmIhx48YhIiKCzvyVx96+fRsTJkygPjU0NKSzEXsmMjISU6ZMoT5V5N7Lly9j2rRpiIqKQkVFBUxMTOT69Ny5c/Dx8cGtW7eoT01NTVnZkydPgmEYxMbG9urTH3/8EbNnz6Y+NTc3h4mJCSv73XffYf78+YiLi0NtbS0EAoFcn+7fvx+LFi1CQkIC6urqYGFhwepTVVVV7Nq1CytWrMD9+/cV+lRNTQ2ffvopVq1ahcTERDQ2NsLS0lKuTz/44AOEhIRw8mloaCjWrl2LR48eobm5GVZWVnJ9umLFCnzwwQfUp/Lcq6WlhQULFuCjjz7q1afa2trw8/PDZ599hpSUFLS1tcn1qY6ODry8vLBjxw48f/4cHR0dsLGxkevTKVOmYPfu3dS9NjY2rD7V0tKCu7s79u3bh9TUVHR3d8t1L4/Hw+jRo3Hw4EGkp6eju7tbrk/V1dUxYsQIHD58mH5pk+dTFRUVDBkyBN9//z0yMzOhoqIil+3u7qY+zc7OVujTjo4OuLq64sSJE9Sn1tbWrGxzczNcXFzw22+/IS8vT6FP6+rq4OLiglOnTiEvLw88Hk8uW1lZCVdXV5w+fRqvXr2CpqYmrK2tWb1XXFwMNzc3nD17FgUFBQp9mpeXhyFDhuD8+fO9+jQ9PR3Dhw/HhQsXevXps2fPMGrUKOpTPT09uevThw8fYuzYsbh69Wqv69O4uDiMHz8e169fR2lpqUKfRkdHY/Lkybhx4wbKy8thaGgo16cRERHw8PDAzZs3UVFRoXAte/78ecyYMYOTT0+dOgWRSISYmBhUVVUp9OmJEycwa9Ys6lMzMzO5Pj169CjmzZuHu3fv0rmt8tayBw8exPvvv4/4+Phe3btnzx4sXboUCQkJqK+vl+ve/0a4zhFVnporkZcvX9KK28aNG6WqOObm5vD19QXDMJg2bRry8/Px/PlzEEKwbt06qWqLhYUFZT09PZGVlUVFHxYWJlVBEQqFlPXw8EBaWhoyMjLQ1dWF0NBQqUqHtbU1RCIRRCIRpk6diufPnyM7OxsdHR0ICQmRqgbb2tpCJBKBYRhMnjwZT548QV5eHlpbWxESEiJVie3Tpw9lJ02ahKSkJBQUFKCpqQmhoaFSFdO+ffuCYRgwDIMJEybg/v37eP36Nerr67F69WqpqmL//v3BMAxEIhHGjx+PuLg4lJaWoqqqCuHh4VI/eycnJ/q648aNw+3bt1FeXo6ysjJs2LBBinVxcaHvd+zYsYiKikJ1dTWKiorw0UcfSbEDBw6k72H06NGIjIxEbW0t8vLysGXLFil20KBB9D2MHDmSPhHIyMjAjh07pNihQ4dSdtiwYbh8+TKam5vx4sUL7NmzR4odPnw4ZcUL8ra2Njx58gT79++XYkeNGkXfr3ih39nZiQcPHuDw4cOUEw+kFr/uwIEDcfr0aRBCcO/ePRw9epSyqqqqGDt2LP2ZDRgwAGfOnAHwpojx448/SrHu7u70dfv164dz584BeLPo/u233yirpqaGCRMm0PdrZ2eH8+fPAwCuXr2KP//8k7Lq6uqYOHEifV1LS0tcvHgRAHDhwgX89ddflNXQ0MDkyZPp+zUzM8OVK1cAAGfPnsWlS5coy+PxMGXKFPoeDA0Nce3aNQBvFujXr1+nrKamJqZOnUpZHR0dREZGAgB+/vlnREdHU1ZLSwuenp5gGAa+vr7Q0NCg//2HH37AnTt3KKujoyPFqqioICYmBgDw3Xff4f79+5TV1dXF9OnTwTAMfHx80NnZSV/r4MGDkPSjvr6+FNvS0oJ79+4BAPbt24dnz55R1sDAADNmzIBIJIKPjw/q6+vpn7t7926kpqZS1sjICDNmzADDMPD29kZVVRUePnwIANi6davUU1ETExN4e3tDJBJhxowZKCsrQ3JyMgDgk08+kXrSaWpqCh8fHzAMAy8vLxQVFeHp06cAgI0bN0o9kRT7VCQSYfr06VI+Xb9+vVSlWyAQSPk0OzubPsEICwuT6q6wtLSUYtPT05Geno6uri6sXr1aqspsZWVFferh4YEXL14gKysLHR0dCA0NlXoSZ2NjQz+PU6ZMwdOnT5Gbm4u2tjaEhIRIPTHr6dNHjx7h1atXaG5uRkhIiIxPxezEiRORmJiIoqIiNDQ0IDQ0VMqnDg4O9LM7YcIE3Lt3DyUlJaipqUFYWBgk4+joSP+tubu7U59WVFRg/fr1Uqyzs7OUT8XFxOLiYnz44YdSrKurK33d0aNH4+bNm6ipqUF+fj4+/fRTKVbsU5FIhFGjRtHulqysLPQsgA8ZMoS+7vDhw3HlyhU0NTUhNTUVu3fvlmKHDx9O3++wYcNw4cIFtLa24unTp/jqq6+k2JEjR9L3MGTIEPz111/o6OhAUlISvvnmG8qJfSp+XTc3N5w5cwbd3d1ISEjAkSNHpNixY8fS9+vi4kJdd/v2bRw/fpyyqqqqGDduHGUdHByoT6OiovDLL79QVk1NDePHj6fv197ennrx2rVrOHXqFGXV1dWpexmGgZWVFS5cuAAAuHTpEs6ePUtZDQ0NTJo0if7d+Hw+Ll++DOBNwUPsYeCNTydPnkxf18jICBEREQCAP/74g/5vQNanurq6uHHjBgDg119/xc2bNymrpaUFDw8PyvJ4PERFRQEAjh8/jtu3b1NWW1sb06ZNo/82JX36/fffIz4+nrK6urqYNm0adWRXVxf16aFDh6jXAEBPT0/Kp21tbYiLiwMAfPXVV9RVwBufenl5UbahoQEJCQkAgC+++AIvX76krKGhoZRPa2pq8ODBAwDA9u3baXETAIyNjeHt7U0dWVFRQZ2/ZcsW5OXlUdbExETKp8XFxXjy5AkAYNOmTVLdIGZmZlI+LSgooN04GzZskHrKyOfzpdayOTk5tBsnPDxcqhPDwsKC/h48PT2RmZmJtLQ0dHd3Y/Xq1VIdE0KhkH7GJH3a2dmJkJAQVp+K17LPnj1DTk4O2tvbERwcLOVTOzs7qbVscnIy8vPz0dLSgpCQEKlOAXt7eyn3PnjwAIWFhWhsbERoaKjUU/p+/fpJrWXj4+NRXFyM2tparFmzBpJxdHSkr+vu7o67d++irKwMlZWVWLdunRQ7YMAA+rqSPi0pKcHGjRulWBcXF8qOGTOG+rSgoACbN2+WYt3c3KR8euPGDdTV1SEnJweff/65FDt48GD6uiNGjGAtUvwT4XpqrnKOqET27NlDB8Mqung8Hh2A3NulqanJmdXS0qKD6nu7dHR0iJ2dHSdWV1eX2NjYcGL19PTowObeLgMDAyIUCjmxRkZGxMLCghNrbGxM+Hw+J9bU1JSYmppyYs3NzYmxsTEnls/n06HRvV2WlpZET0+PEysUCom2tjYn1sbGhmhoaHBi7ezs6NDo3i6unzHgzRB5rmy/fv3eCevg4MCZ7d+/P2fW0dHxv8qqqKi8E1ZVVZUzq6amxvlnpq6uzpnV0NDg/Hvj8XicPw9v61Oun19tbe238qmtrS0nVk9Pj7N79fX1OfvU0NCQWFpacmKNjIyIQCDgxJqYmBAzMzNOrJmZGTExMeHE8vl8YmRkxIm1sLB4Jz61trYmPB6PE2tra0vU1NQ4sW/jyLdhuX7Ogf8Nn74r9r/t3rf16btyL9ffm4aGBufPw9u49135VEdHh7NP32Ytq6+vT6ysrDixBgYG78yn5ubmnNi3Xcty9alAICDBwcG9znR/FwHHOaLK1lyJZGdn4/Xr1xAKhaivr5fZF6KqqooJEyYgJCQErq6utPWyrq5OZq+HmpoaJk2ahNWrV8PR0RHNzc0QCoWoqamR2euhrq6OKVOmYPXq1bC3t6ftP1VVVTL7NzQ0NODh4YE1a9bAysoKHR0dEAqFqKyslGF5PB48PT2xZs0aCAQCdHV1QSgUory8XGb/hqamJry8vBAWFgZjY2MQQiAUClFaWiqzd0JLSwszZsxAWFgY9PX1oaKiAktLS9Z9ADo6OvDx8cHatWuhqakJdXV1WFpasu7X0tXVhUgkwtq1a6GqqgoejwcLCwtWVl9fHzNnzsTatWvR1dUFbW1t8Pl81vdgYGAAPz8/hIeHo6WlBXp6ejA3N2fdB2ZkZITZs2cjPDwcDQ0NMDAwgKmpKeu+BWNjY7z33nsIDw+nrcsmJiasrKmpKebNm4fw8HCUlpbCzMwMRkZGrPvLzM3NMX/+fKxbtw4FBQUQCAQwMDBg3Q8hEAiwYMECrFu3DtnZ2bQdjW0/hKWlJd5//32sXbsWWVlZtB2NbS+alZUVFi1ahNDQUGRnZ8PKygra2tqseydsbGywZMkSBAYGIicnB1ZWVtDU1GTdB2xnZ4elS5di5cqVyMvLg5WVFXg8Hivbt29fLFu2DEuWLMGrV69gZWUFdXV11j0ZDg4OWL58ORYuXIiCggLa1sS2J8PJyQn+/v547733UFhYCCsrK6ioqLDuh3N2dsbKlSsxa9Ys6gZCCOv+jYEDByIgIAAikQglJSUQCoXo6upi3b8xaNAgrFq1CjNmzEBpaSmEQiE6OjpY9yIPHToUq1atgoeHB8rLyyEUCtHe3s7KDh8+HEFBQZgwYQIqKyshFArR2trKus9u5MiRCAoKwrhx41BdXQ2hUIjm5maZfXYqKioYM2YMgoODMXLkSNTU1EAoFKKpqUlmn52KigrGjRuHkJAQDB06FHV1dRAKhWhoaGD16fjx4xEaGoqBAweioaFBoU8nTpyI0NBQODk50dbL2tpaGVZdXR2TJ0/G6tWr0bdvX9rKXl1dLeNeDQ0NTJ06FWvWrIGtrS3a2to4+dTCwgKdnZ0QCoWoqKhg9en06dMRFhYGMzMzdHd3QygUoqysTKFPDQwMFPpUW1ub+lRLSwtqamoKferr64u1a9dCXV0dGhoacn2qp6cHhmEQHh6O7u5uaGlpQSAQyPXpzJkzER4ejra2Nujq6sr1qaGhIfVpY2Mj9PX1YWZmxsoaGxtjzpw5CA8PR01NDYyMjBT6dO7cuQgPD0d5eTlMTU3l+tTMzAzz5s3DunXrUFRUBD6fD0NDQ1af8vl8LFiwAOHh4cjLy6OtwGw+tbCwwMKFC7Fu3TpkZmYq9KlQKOTsU2trayxevBjBwcGU1dLSYmVtbW2xZMkSTj61t7fHsmXLsGzZMuTn5yv0ab9+/bB8+XIsWrSIuldNTY3Vp46OjlixYgXmz59P3SvPpwMGDIC/vz/mzJmDoqIiWFlZyfWpq6urjE+7u7tZWTc3NxmfdnZ2srp3yJAhCAwMhKenZ68+HTZsGAIDAzF58mRUVFRw8qm7uzuqqqogFArR0tLC6tPRo0cjODgYo0eP5uTT4OBgKZ82NjbKsOJuptDQULi5uVGfsq1lJX3q7OxM17LyfCpeyzo4OCj0qeRa1s7OjvpU3lpW7FPx/U+eT3k8HqZNm8bZp+K1rLidVd5aVltbG97e3li7di10dXWhqqoq16c6OjrUpxoaGtDQ0JDL6unp0bUsIUShT/X19eHn54e1a9eio6MDOjo6cteyhoaGmDVrFsLDw9Hc3Aw9PT25PpVcy4aEhEAgEMgw7zpcW3OVT0RZUlZWRnR0dAjwpvK8YMECcvLkSVJVVSXDFhUVEU1NTQK8eZK3aNEi8ueff5Lq6moZNjc3l6irq9NKyZIlS8iZM2dIbW2tDJuenk6fcJmZmZHly5eTc+fOkbq6Ohk2JSWFVj/4fD7x9/cnf//9N2loaJBhk5KSpColAQEB5OLFi6SxsVGGjYuLo6xQKCRBQUHkypUrpKmpSYaNioqirLW1NQkJCSERERGkublZhr1y5QplbW1tyZo1a8iNGzdIS0uLDHvu3DnK9unTh6xdu5bcvHmTtLW1ybC///47Zfv160fWr19PoqOjWdnjx49Ttn///mTDhg0kNjaWtLe3y7CHDx+m7IABA8iHH35I7t69Szo6OmTYffv2UdbFxYV89NFH5N69e6Szs1OG3bFjB2Xd3NzIJ598QhISEljZTz75hLKDBw8mW7ZsIQ8ePCBdXV0y7IYNGyg7bNgw8vnnn5OkpCRWdvXq1ZQdMWIE2b59O3n8+DHp7u6WYf39/Qnwppo8evRosnPnTvL06VNW9v3336fs2LFjyRdffEGeP3/Oys6ePZsAbyrP7u7uZO/eveTly5esrLe3N2UnTpxIvvrqK5KWlsbKTpkyhQBvKs+TJ08mBw4cIJmZmTJcd3c3GTt2LAHeVJ49PDzIwYMHSXZ2Nis7dOhQArypPE+bNo0cPnyY5ObmyrCdnZ3ExcWFAG8qzzNmzCBHjhwh+fn5MmxHRwetTGtqahIfHx9y9OhR1ipmW1sbrQpra2sThmHIsWPHyOvXr2XY5uZm2omgo6ND/Pz8yI8//khKSkpk2Pr6elqR1dXVJXPmzCEnTpwgZWVlMmxNTQ0xNDSklee5c+eSX3/9lVRUVMiw5eXlRFdXl1ae58+fT37//XdSWVkpwxYXFxMtLS1aeX7//ffJH3/8werT/Px82jFgbGxMFi9eTE6fPk1qampk2KysLPqEy9TUlCxbtoycPXuW1acvXrwgKioqtPK8YsUKcv78eVJfXy/DJicnc/ZpfHw8ZS0tLUlgYCC5fPkyq09jYmIoa2VlRUJCQsjVq1dZfXrt2jXK2tjYkNWrV5Pr16+z+vTvv/+mrJ2dHQkLCyORkZGktbVVhj116hRl+/btS9atWyfXpz/99BNlHRwcyL/+9S8SExPD6tMjR45Q1snJiWzcuJHcuXOH1acHDhygrLOzM9m0aROJi4tjdeTu3bspO3DgQLJ582YSHx/Pym7ZskXKp59++ilJTExkdeTGjRspO3ToUIU+DQsLo+zw4cPJtm3bSHJyMqufVq1aRdlRo0aRnTt3kidPnrCyS5YsoT4dM2YM2b17N0lJSWFl586dK+XTPXv2kBcvXrCyvr6+lJ0wYQLZt2+fXJ96eHhI+XT//v0kIyNDhuvu7ibu7u7Up1OnTiUHDx4kWVlZrOzw4cOpTz09PcmhQ4dITk6ODNvV1UUGDhxIferl5UW+++47uT4VP5nU1NQk3t7e5PvvvycFBQUybFtbG316p6WlRUQiETl27BgpKiqSYf8f9t47LIp7ff+/l96RKqi4YmJijMZuYu8Nd9OOJiaWY9BYYoIdSTT22Es09go2bIAiiIg0BUVAkQ7SO1KkSmffvz84884MO7s7fq9jkvP77Ou6uD75nNzXZFl275l5nnmeu76+nnbO9PX1yaeffkpOnTpFCgsL5bS1tbX06QJDQ0PyxRdfkLNnz5Li4mI5bWVlJe1wGRkZkX/961/E1dWVlJSUyGnLysroEwOMn54/f57Xe4uKiugTA6ampmTmzJnk0qVLvNeyubm59IkBxk/d3d15/TQ9PZ3jp3PmzCHXrl3jvZZNSkqifspcy964cYPXT2NiYjjXso6OjsTLy4v3WjYiIoJqbWxsyIIFC8itW7d4vTckJITjp4sWLVLop3fv3uX46ZIlS8idO3d4/fTmzZuC/fTKlStUa29vT5ycnEhAQACvn7q6usr5aWBgIK+fHj9+nGrfe+89smrVKhISEsLrp381ENgRVd+I8nD8+HGyfPlyhX94NocOHRL8h9+7dy9xdnZWeBPDZseOHcTFxUXhiZTN5s2byS+//EIeP37Me3Jks379evLrr7+SyMhIldq1a9eSjRs3kujoaN4TE5sVK1aQLVu2KDyRMshkMvLjjz+Sbdu2kdjYWJXaxYsXKz2RMrS2tpL58+eTXbt2kaSkJKXalpYWMm/ePLJnzx6SkpKi9Pdqamois2fPJvv37+c9kbJpaGgg3377rcITKZvXr1+TmTNnkj/++INkZWUp1dbU1JCvvvqKHDlyhOTk5CjVVlRUkBkzZpDjx4/znkjZlJaWkunTp5OTJ0/y3sSwKSwsJDNmzCBnzpzhPZGyyc3NJTNmzCDnzp3jvYlhk5GRofREyiY5OVlpUYhNbGws+fbbbxXexLCJiopSWhRiExYWRk+kfDcxbAIDA5UWhdj4+fmRBQsWKLyJYXPr1i2lRSE2169fV1oUYnPp0iVaFOI7kbI5d+6c0qIQmxMnTgj208OHDystCrHZv3+/0qIQm127diktCrHZunUr9VNV2l9//VVpUYiNi4sL2bhxo8KbGDarVq1SWhRi4+TkpLQoxCCTyciSJUuUFoXY2gULFigtCjG0tLSQ7777TpCfNjc3kzlz5igsCrFpbGwks2bNIr///jtvUYhNXV0dmTlzpsKiEJuamhry9ddfC/LTyspKMmPGDIVFITZlZWVkxowZgvy0uLiYTJ8+XWFRiE1+fj6ZMWOGwqIQm6ysLPLVV18pLAqxSUlJIV9//bXCohCbuLg4pUUhNtHR0UqLQmwePXpE5s6dq7DIziYkJERpUYjNvXv3lBaF2Ny+fVtpUYiNh4eHYD91d3dXWhRi4+bmRn766SeFNzFsTp06pbQoxObIkSOC/fTAgQNKi0Jsdu/erbQoxOa3334jP//8s8IiO5uNGzcqLQqx+eWXX5QWhdisXr1aaVGIzbJlywT76Q8//KC0KMTWLly4kOzcuVPQtayjo6PSohBDS0sLmTt3rsKi0N+N0BtR9bIiNWrUqFGjRo0aNWrUqFHzX0HosiJ1jqgaNWrUqFGjRo0aNWrUqPlLUd+IqlGjRo0aNWrUqFGjRo2avxT1jagaNWrUqFGjRo0aNWrUqPlLUd+I8hAaGorU1FRB2qCgIKSlpQnS3r9/H5mZmYK09+7dQ3Z2tiDt3bt3kZubK0h7584d5OfnC9L6+PigsLBQkNbb25t33XR7CCHw8vLiXcnPp/X09ORds98emUwGDw8P3jX77WltbYWHhwfvOvz2NDc3w8PDg3fFfXsaGxvh6enJu+K+PXV1dfDy8uJdRd+e2tpa3Lp1i3cVfXsqKytx+/Zt3lX07SkrK4Ovry/vKvr2FBcX4+7du3Ir4/koKCjAvXv3BGlzc3MRGBgot16ej8zMTAQHB8utl+cjLS0NDx48kFsvz0dKSgrCwsLk1svzkZiYiMePHwvSxsXF4cmTJ3Kr6PmIiYlBdHS0IG10dDSePXsmt4qej8jISDx//lyQ9vHjx4iPjxekDQsLQ1JSkiDtgwcPkJKSIkgbHBzMCYBXRmBgIDIyMgRpAwICOGHxyvhf8lMAuHnzJu/6/vYw3ssXccKn9fT0/K/7aUtLCzwM9UDdAAAgAElEQVQ8PHjjRdrT1NQk2E/r6+vh6enJGxnSntraWty8eVOQn1ZVVcHb21uQn5aXlwv205KSEvj5+clFe/BRWFgo2E/z8vJw//59QX6alZUl2E/T09MRGhoqyE9TU1Px8OFDQdqkpCQ8evRIkJ/Gx8cjIiJCkEc+f/4cUVFRgrRPnz7F06dP/+t+GhERgbi4OEHa8PBwJCYmCtI+fPgQycnJgrQhISFv5Kfp6emCtG/ip/7+/sjJyRGk9fPzQ15eniCtr68vCgoKBGlv377NG7PCx61bt/5WP2WuZflioNrDeK8QP/0no84R5SEnJweDBg3C5cuXkZWVBR0dHXTp0gWamppy2hcvXuDjjz/GlStXkJOTAz09PZph2J74+HgMGzYM169fR25uLvT19RVqo6OjMXLkSHh4eCA/Px/6+vro1KkTrzY8PBxjxoyBl5cXCgoKYGhoiE6dOkEkEslpg4KCMH78eHh7e6OwsBBGRkawtbXl1fr5+WHSpEnw8fFBUVERTExMYGNjw6v18vLC1KlT4efnh5cvX8LExAQdO3aU04pEIly9ehVSqRR3795FSUkJOnToAGtra16tm5sbvvjiCwQEBKCkpARmZmawsrLi1Z48eRIzZsxAYGAgysrKYGFhAQsLCzmthoYGDh06hG+++QbBwcEoLy+HpaUlLCws5H4vTU1N7Nq1C3PmzEFoaCgqKipgZWUFc3NzOa2WlhY2bdoER0dHPHz4EBUVFbC2toaZmZmcVltbGy4uLli4cCHCw8NRVVWFjh070twrNjo6Oli2bBl++OEHPHr0CNXV1bCxsYGpqamcVldXFwsXLsSyZcvw5MkT1NbWwsbGBiYmJnJafX19zJkzB6tXr0ZkZCRev35Nc/PaY2BggOnTp8PFxQXR0dE0F9fIyEhOa2hoCKlUig0bNuDp06eor6+nGXt8x500aRI2b96M58+fo6GhAV26dIGBgQGvdsyYMdi+fTtiY2PR1NSELl26QF9fn/d3Gz58OHbt2oX4+Hiq1dPT431/P/nkE+zduxcJCQloaWmBnZ0ddHV15bRaWloYNGgQDh48iKSkJLS2tirUikQi9O/fH4cPH6YXDl26dIGOjo6cViaToW/fvjh+/DhSUlIAtOWzamtry2kbGxvRt29fnDx5kl5kKNLW1taib9++OHPmDNLS0qChoQE7OztoaWnJaSsqKtC3b1+4ubkhIyMDWlpa6NKlC6/25cuX6N+/Py5cuIDMzExoa2sr9Mjc3FwMGjQIly5dQnZ2tlJtRkYGhgwZAnd3d+Tk5EBXVxddunTh9b2kpCQMHToU165dQ25urlLvjYmJwYgRI3Djxg3k5eXBwMBAoZ8+fvwYo0ePpn7KaPl8LyQkBOPGjcOtW7dU+qm/vz8mTpxIb0iNjY0Var29vTFlyhTcuXMHxcXFSr33+vXrkEgk1HuV+enFixfx2Wef4d69eygtLUWHDh0U+umpU6cwffp03L9/H2VlZTA3N4elpSWvnx4+fBgzZ85EUFAQysvLYWFhAUtLS7nXqqGhgb1792L27NkICQnBq1evFPqppqYmtm7dinnz5uHBgwcq/XTdunX4/vvvERYWptJPV6xYgSVLlqj0Uz09PSxevBhOTk6IiIhATU0NbG1tFfrpv//9b6xcuRKRkZE0m1GRn3711VdwcXFBVFQU6urqYGtry+unBgYG+Pzzz7Fu3TqVfmpoaIgpU6Zg06ZNiImJQUNDAzp37qzQT8eNG4dt27bh+fPnaGxsVOqnI0eOxM6dOxEXF4fm5maahdoeXV1dDB06FHv27KF+qsh7tbW1MXjwYBw4cABJSUlUy+enGhoaGDhwIA4dOoTk5GTIZDLY2dnx+ikhBP369cPRo0eRmpoKQohCbXNzMz766COcOHECL168gEgkUuindXV1+Oijj6ifMlo+j6ysrETfvn3h6uqK9PR0aGpqKtSWlZWhX79+OH/+PPVeOzs7Xo8sKCjAwIEDcfHiRZXXp5mZmRg8eDDc3d2RnZ0NXV1dmgnbnpSUFHzyySe4evWqSj+NjY3F8OHDcf36deTl5Sm9lo2MjMSoUaPg6emJ/Px8pd778OFDjB07Fjdv3kRBQYFSP71//z4mTJhAbzKNjIwUeqSPjw8mT54MX19flX7q4eGBadOmUT81NTVVeC17+fJlfPrpp/D391d5fXr27Fl8+eWXuH//PkpLSxX6qUgkwrFjx/D1118jMDBQpZ8eOHAA3377LYKDg/Hq1SuF17J/B0JzRNVbc1nExcWBeX3r1q3jVKQ7dOiAKVOmQCqVYsqUKcjJyUFMTAwIIVi7di2n0mFmZoapU6dSbVpaGu00rFq1itNds7CwgIODAyQSCSZPnozk5GR6gbtixQpO1dbKygoODg6QSqWYNGkS4uLikJqaipaWFixbtoxTXbW2tsa0adMglUoxceJEPHv2DOnp6WhqaoKTkxOnCmpra0u1EyZMwJMnT5CVlYX6+nosW7aMU63s3LkzJBIJJBIJxo8fj/DwcOTm5qKmpgYrVqzgVOns7OwgkUgglUoxduxYhIaGoqCgAJWVlVi1ahXnvReLxVQ7ZswYBAYGori4GKWlpXBxceFo7e3tIZVKIZVKMWrUKNy9exdlZWUoKirC+vXrOdp33nmHakeOHAkfHx9UVFQgNzcXmzdv5mjfe+89qh0+fDhu3ryJ6upqpKenY8eOHRxtz549qXbo0KHw8PDA69evkZycjL1793K0H374IaRSKSQSCTX6hoYGxMXF4eDBgxxtnz596HGHDBmCixcvoqWlBU+fPsXRo0c52n79+tH3bNCgQXBzcwMhBBERETh16hRHO2DAAHrcfv36wc3NDUCb8bu6unK0gwcPpq/3ww8/xMWLFwG0FTEuXbpEdSKRCEOGDKHH7dGjB9zd3QG0XXRfu3aNox06dCh9vd26daP/3sfHB15eXlSroaGBYcOG0eN26tQJHh4eANoKHj4+PlSrqamJ4cOHU621tTU91rVr1+Dv70+1WlpaGDlyJNV26NAB3t7eAIBLly4hKCiIarW1tTFq1CiqNTQ0hK+vLwDA1dUVDx8+pFodHR2MGTOGvmfa2tr0v3vq1ClERERQra6uLsaOHUu1QNsJFQCOHj2Kp0+fUq2enh7Gjx9Pv2/Nzc0IDg4GABw8eBBxcXFUq6+vjwkTJtDjvn79Gg8ePAAA7N27F8nJyVRraGiIiRMnQiqVwsHBAVVVVQgPDwcA7Nixg1MVNzIywqRJk6i2rKyM/j5btmzhVLpNTEwwefJkSCQSODg4oKioCFFRUQCA9evXcyrSpqam1E+nTp3K8VMXFxfOUxAdOnTg+GlGRgbtNKxevZpTDTY3N6ceOXnyZKSkpCAxMREymQwrVqzgPIFgaWnJ8dOEhASkpKSgpaUFy5cv53S22vtpTEwM0tLS0NTUhGXLlnE6UDY2Nhw/jYqKQmZmJhoaGuDk5MTx006dOnH89PHjx8jJycHr16+xbNkyjp926dKFfn/GjRtH/bSqqgorV64Em65du9LPLttPy8vL4ezszNHa29vT444ePRr+/v4oLS1FcXEx1q1bx9EyfiqRSDBq1Cj4+vri1atXyMvLQ/uido8ePTh+6u3tjaqqKmRmZuK3337jaHv27Elfw7Bhw+Dp6Yna2lqkpqZi9+7dHG2vXr3ocT/55BNcu3YN9fX1SEhIwIEDBzjaPn360OMyBY6mpibExMTg8OHDHG3fvn3pcQcNGoQLFy6gtbUVkZGROHHiBEfbv39/qh0wYAD10PDwcJw9e5ajHTRoEH3P+vTpgwsXLgBoK2Iw/8zA9tP3338fly9fBtDWgbpy5QrViUQifPLJJ1Rrb2+Pq1evAmjr0jN+CbT56dChQ6m2S5cuuHHjBoC27g/jgQDXTyUSCTp27Ej99Pr167h79y5Hy/ZTc3Nz3Lp1CwBw+fJlBAYGUq2WlhZGjx5N/xZGRkbUT93c3KhXAW3ey/ipVCqFjo4O/e+ePn0ajx8/plodHR2MGzeOHlckEiEgIAAAcPz4ceo/QJufjhs3jv5uLS0t1PMPHTqE2NhYqtXX18f48eOptr6+HqGhoQCAffv2ISkpiWoNDAyon06bNg3V1dUICwsDAOzcuZPzxJyhoSH102nTpqG8vJz+Plu3buU8BWdsbIzJkydT72X76YYNGzjdQBMTE46f5uXl0admfvnlF84TaO39NDMzE7GxsSCEwNnZmdOJMzc352hTU1ORkJAAmUyGlStXcp5AYPyUuZZNTExEcnIyWltbsWzZMo6fWllZcfw0NjYWL168QHNzM5ycnHj9VCKRYOLEiYiOjkZGRgYaGxvh5OTE6bzb2trSz8L48eMRERGB7Oxs1NXVYdmyZZwOOXMty/hpWFgY8vLyUF1djRUrVoBN165dOdenISEhKCwsxKtXr7BmzRqOtlu3bhw/ZZooJSUl+Pnnnzna7t27c/zUz88P5eXlKCgowIYNGzjaHj160OOOGDECt2/fRmVlJbKzs7F161aO9v3336ffn2HDhvEWP/4KhG7NVeeIstixYwcNhlX2o6mpSbp27SpIq6Wl9UZaJqhe1Y+2tjbp0qWLIK2uri7p3LmzIK2enh7p1KmTIK2+vj6xsbERpDUwMCDW1taCtEZGRsTKykqQ1tjYmJibmwvSmpqa0tBoVT8dOnQgJiYmgrTm5ubE0NBQkNbS0pLo6ekJ0lpbWxNtbW1BWhsbG6KhoSFIywRyC/kR+lkAIPgzBkDwZxeA4O8EAMHfNQA0xFzIT7du3d6K1t7e/m9/DUK1IpFIsFZDQ0Pw+6uhoSH47/am3vs2/FRHR0fwZ11XV/et+WnHjh0FaQ0NDd/ITy0sLARpTUxMiJmZmSBthw4diKmpqSCtubk5MTIyEqS1sLAg+vr6grRWVlZER0dHkLZjx45EU1NTkFbtp20/b+Knb0v7v+TTb+KnIpHojfxUqPZtXctqa2sL/py9LT/V09MT/N18Uz99k2vZN/FTodeyb+KnZmZmxNHRUWUO8tsAAnNE1Y/mssjJyUFpaSnEYjEqKyvlZjK0tbUxYcIEODk5YcCAAWhoaIBYLMarV6/kZjJ0dHQwceJELFu2DL1790ZzczPEYjHKysrkZjJ0dXUxefJkLF++HO+//z5aW1shFotRUlIiN2ehr6+PqVOnYsWKFejevTsIIRCLxSguLpabszAwMICDgwNWrFhBH28Ti8UoLCyUm50wMjKCRCLBypUr0bFjR2hpaUEsFiM/P19uFsHY2BiffvopVq1aBXNzc+jo6KBr1668z/abmpri888/x+rVq2FkZAR9fX107dqVdwarQ4cO+OKLL7B69Wro6enB0NAQXbp04T2uubk5/vWvf2H16tXQ0NCAiYkJOnfuzDuvZWFhgRkzZmDNmjVobW1Fhw4dYGtryztfYG1tja+++gpr1qxBfX09LCws0LFjR97Zro4dO2LmzJlwdnZGdXU1rK2tYWVlxTuLYGtri2+++QbOzs4oLy+HjY0NLCwseOfAOnfujFmzZsHZ2RlFRUXo3LkzzMzMeOcW7OzsMHv2bDg7OyM3Nxddu3aFqakp7wxut27d6KO42dnZ6NatG4yNjXlnHLp37465c+dixYoVyM3NhVgshqGhIe+8bo8ePTBv3jz89NNPyMvLg1gshr6+Pu88xPvvv4/vvvsOS5YsQX5+PsRiMXR1dXnnIXr16gVHR0fMnz8fhYWFEIvF0NbW5p1F6927N+bPn4958+ahqKgIYrEYmpqavLMTffv2xffff49Zs2bh5cuXEIvFEIlEvHPA/fv3x8KFC/H111+jpKQEYrEYhBDeubVBgwZh4cKF+Ne//oWysjKIxWK0trbyzq0NGTIEixcvxqeffory8nKIxWI0NzfLzQwznY8lS5bAwcEBFRUVEIvFaGxslJtxYzrJS5cuxcSJE1FVVQWxWIz6+nq5GTcNDQ2MHDkSS5cuxdixY1FdXQ2xWIzXr1/Lzbhpampi9OjR+OmnnzBixAjU1tZCLBajpqZGbsZNS0sLY8aMwU8//YRPPvkEdXV1EIvFqKqq4vXT8ePHY9myZRw/raio4PXTCRMmYNmyZejTpw+ampogFotRXl6u1E979uyJlpYWiMVilJaWyvmpnp4epkyZghUrVuDdd9+FTCaDWCzGy5cvlfpp165dIRKJIBaLUVRUJOenhoaG1E9tbW2hqakJsViMgoICOT81MjKCVCrFypUrYWlpCW1tbYV+amJigs8++wyrVq2CiYkJ9PT0VPrpqlWroK+vDwMDA9jZ2fEe18zMjPqplpYWjI2Nlfrp9OnTsWbNGhBCYGpqqtBPraysqJ82NjbC3NxcqZ9+/fXXWLNmDWpra2FlZaXST9esWYOKigp07NhRqZ9+++23cHZ2xsuXL9GpUydBflpQUAA7OzuFfioWizFnzhysXbsWWVlZSv3U3t5esJ++++67+Pe//w0nJyeq/W/46QcffABHR0csXLgQBQUFKv3U0dER3333HfVeRX760UcfYcGCBZgzZw6Ki4uV+mm/fv3w/fff45tvvlHppwMHDsSiRYswffp0lX46ePBgLF68GJ999hn105aWFjkt20+nTZum1E9FIhGGDRuGH374AZMmTUJlZaVSPx0xYgSWLl2K8ePHq/TTUaNG4ccff8TIkSOpn9bW1sppGT91cnLi+Gl1dbWc92pra2PcuHFwcnLCwIEDqZ/yXcsyfurk5IS+fftSP+W7ltXV1cWkSZOwfPly9OrVS+m1rJ6eHvXeHj16UD9VdC3L+KlYLAYAhdeyhoaGmDZtGlauXEkfAVZ2LSuVSrFq1SpYWVlRP1V0Lcv4qZmZGXR1dRX6qampKfVTQ0ND6OvrK/XTL7/8EqtXr4a2tjaMjIwEXcsy/51OnTrxeq+lpSW9lm1uboaZmRlsbGwUXssyfrp06VLeR3vfNkIfzVV3RHkoKiqiXStLS0vy73//m9y4cYNUV1fLaXNycmjXytramjg6OhJPT09SU1Mjp01LS6NVVhsbG7JgwQJy69YtUltbK6dNTEwkIpGIAG1V1EWLFpHbt2+T169fy2mfPXtGqx9dunQhS5YsIXfu3CH19fVy2sePH1Nt165dydKlS8ndu3dJQ0ODnDY4OJhq7e3tiZOTEwkICCCNjY1yWj8/P6p95513yPLly0lgYCBpamqS03p5eVHte++9R1atWkVCQkJ4te7u7lTbs2dPsmbNGvLgwQPS3Nwspz137hzVfvjhh8TFxYWEhYWRlpYWOe2xY8eotk+fPuSXX34hjx8/Jq2trXLa/fv3U22/fv3Ir7/+Sp48ecKr3b59O9UOGDCAbNy4kURHR/NqN2zYQLWDBw8mW7ZsIc+ePSMymUxO6+zsTIC2yujHH39Mtm3bRmJjY3m1Tk5OVDts2DCyfft2Eh8fz6tduHAhAdqqqCNGjCC7du0iSUlJvNo5c+YQoK2KOnr0aLJnzx6SkpIipyOEkBkzZtAq6tixY8n+/fvJixcveLVSqZRqx48fT37//XeSnp7Oq504cSKtuE6aNIn88ccfJCsrS04nk8nIyJEjacV1ypQp5MiRIyQnJ4dXO3jwYFpFnTZtGjl+/DhvBbG1tZX06dOHAG0dLKlUSk6ePEkKCgrktC0tLeS9996jFdfPP/+cnDlzhhQVFclpm5qaaHXcyMiIfPnll+TcuXPk5cuXctr6+npaQTY2NiYzZswgbm5upLS0VE5bW1tLq7empqbk66+/JhcvXiTl5eVy2srKStrhMjMzI99++y25fPkyefXqlZy2rKyMGBsbE6CtgzV79mxy9epVUllZKactLi6mXStLS0syd+5ccv36dVJVVSWnzcvLo10ra2tr8t133xFPT09e783IyCBaWloEaOtgzZ8/n9y8eZPXT5OTk+kTA506dSILFy5U6KfPnz/n+OnixYuJr68vqaurk9M+efJEzk/9/Px4vTc0NJRqu3XrRn766Sdy7949Xu+9d++enJ/ev3+f13u9vb2ptkePHmTlypUkODiY10+vXbvG8dPVq1eT0NBQXj91c3Oj2l69epG1a9cq9NMTJ05w/PTnn38mjx494tUePHiQavv27UvWr1+v0E937dpFtf379ycbNmwgUVFRvNrNmzdT7aBBg8jmzZsV+qmLiwvHT7du3UqeP3/Oq12+fDnVDh06lGzfvp3ExcXxahcvXkz9dPjw4WTnzp0kMTGRVztv3jyqHTVqFNmzZw9JTk7m1c6cOZN675gxY8i+ffsU+unnn3/O8dMDBw4o9NPJkydTP504cSI5dOgQyczM5NWOHj2a46eHDx8m2dnZcjqZTEY+/vhjArR1sBwcHMixY8d4/VQmk5F+/fpR75VIJOTEiRMkPz9fTtvS0kI++OAD6qefffYZOX36NK+fNjc3k3feeYd2sL744gty9uxZUlxcLKdtaGigHWVjY2Myffp04ubmRkpKSuS0r1+/pp0zExMT8tVXX5ELFy6QsrIyOW11dTXtcHXo0IF888035NKlS7ze++rVK/oElpmZGZk1axa5cuUKqaiokNOWlJQQAwMDArQ9ETB37lxy7do1Xj/Nz88nurq6BGh7ImDevHnEw8OD10+zsrLk/NTLy4v3WjY1NZX6qa2tLfn++++Jt7c3r5/Gx8fT72Xnzp3JokWLiI+PD6+fRkdHU62dnR354YcfFPppWFgY1YrFYvLjjz8Sf39/Xj+9f/8+1Xbv3p0sW7ZMoZ/6+PhQ7bvvvktWrFhBgoKCeP30xo0bVPv++++T1atXk5CQEF4/vXjxItV+8MEHxNnZmTx8+JDXI0+fPk21vXv3Jj///DMJDw/n1R4+fJhqP/roI7Ju3ToSERHB65F/NRDYEVXfiPJw8uRJ4uLiovAPz+bw4cOC//AHDhwgGzZsIJGRkSq1u3fvJps2bSJPnz7lPTGx2bZtG9myZQuJiYlRqd20aRP57bffFJ5I2axbt47s2LGDJCQkqNSuWbOG7N69W+GJlEEmk5Hly5eTvXv3ktTUVKXHlMlk5McffyQHDhwgaWlpSrWtra1k8eLF5ODBgyQjI0OptqWlhXz//fcKT6RsmpqayHfffUeOHj1KcnNzlWobGhrIvHnzFJ5I2bx+/ZrMnTuXnDp1ihQWFirV1tTUkNmzZ5MzZ87wnkjZVFRUkNmzZxNXV1feEymb0tJSMmvWLHL+/Hnemxg2hYWFZPbs2QpPpGxyc3PJ7Nmzibu7O++JlE1GRgY9kfLdxLBJTk5WWhRiExsbSxwdHRWeSNlERUUpLQqxCQsLU3oiZRMUFKS0KMTG39+f/PjjjwqLQmxu376ttCjExsPDQ2lRiI27uzstCvGdSNm4ubkpLQqxOX36tGA/PXr0qNKiEJuDBw+SX3/9VZCf7t27lxaFVHnZ9u3bBfvp5s2blRaF2Kxfv57s2LFDYVGIzdq1a5UWhdisXLlSaVGIQSaTEScnJ7J//36VfiqTycgPP/wg2E8XLlyosCjEprm5mTg6OiosCrFpbGwk8+bNI8ePH1fpp3V1dWTu3LkKi0JsampqyJw5cwT5aWVlJZk1a5bCohCbsrIyMnv2bEF+WlxcTGbNmqWwKMQmPz+fzJ49W2FRiE1WVhaZM2eOwqIQm5SUFOqnfDcxbOLi4mhRSJWfRkdHKy0KsXn06JHSohCbkJAQpUUhNgEBAbTIrsp7fXx8aFFIlZ96enoK9tOrV68qLQqxuXDhAlmzZo3CohCbs2fPKi0KsTl+/Dj1U1XaQ4cOKS0Ksdm3b5/SohCbnTt3Ki0Ksdm6davSohCbDRs2KC2ys3FxcVFaFGKzatWqN/JTZUUhtnbp0qVKi+wMra2tZNGiRUqLQgwtLS1kwYIFgq5l/w6E3oiqlxWpUaNGjRo1atSoUaNGjZr/CkKXFalzRNWoUaNGjRo1atSoUaNGzV+K+kZUjRo1atSoUaNGjRo1atT8pahvRNWoUaNGjRo1atSoUaNGzV+KyhtRkUh0ViQSlYhEogTW/2YuEokCRCJR2n/+r9nbfZl/LYGBgXj+/Lncqmc+7t27h/j4eEHau3fvIikpSZDW19cXKSkpgrS3b9/GixcvVOqAtgDrjIwMQVpPT09kZWUJ0t64cYN35XV7CCG4evUq72pqPu2VK1d4V/23RyaTwd3dnXd9f3taW1vh7u7Ou5K/Pc3Nzbh8+TLvSv72NDY2wt3dnXfNfnvq6urg7u7Ouzq/PbW1tbh69Srv6vz2VFZW4vr167zr8NtTVlYGDw8P3nX47SkuLsbNmzflVtzzkZ+fD29vb7kV93zk5OTA19dXbm09HxkZGfDz85NbW8/HixcvcO/ePbm19XwkJyfj/v37cmvr+YiPj0dwcLDc2no+nj9/jtDQULm19Xw8ffoUYWFhgrSRkZF49OiR3Ip7Ph49eoSIiAi5Ffd8PHz4EFFRUYK0ISEhePr0qSB/CgoKEuynAQEBiIuLE6T19/dHYmKiIO2dO3eQnJwsSOvj4/NGfpqeni5I6+XlJdhPPTw8kJOTI0h77do13liA9jDey7fqn0/r7u7OG53SntbWVly+fJk3DqU9LS0tgv20qalJsJ/W19fD3d2dN7akPW/ip1VVVbh27RpvFEl7ysvLBfvpy5cv4eXlJRfXxEdhYSG8vb0FeW9ubi58fHwE+WlmZqZgP01LS4O/v79gPw0ICBDkpwkJCQgKChLkp7GxsQgJCRHkkc+ePcPDhw8F+2l4eLggP338+LFgPw0LC0NkZKQg7YMHD/D06VNB2uDgYMTExAjysvv377+RnyYkJAjS+vn5Cb6W9fHxQWpqqkodAHh7eyMtLU2Q9ubNm8jMzBSk9fDwQHZ2tiDt9evX39q1rBA/lclkuHz5suBr2cuXLwu6lv1Ho2qbEYBRAAYASGD9b7sBuPznn10A7BKyGel/Zdi+25QAACAASURBVGsusxbazs5O5dZLZi10t27dlK6PJuTPtdDdu3dXufWSWQutan00IX+uhWZHoSjavMashWbWRyvbesmshWaiUJRtvdyzZw9nfbSyrZdbt27lRKEo23q5bt06AoAMHDhQ5dbLVatWcaJQlG29XLp0qaAoFEIIcXR0pFEoqrYIf/vtt0RDQ4OMHDlS5dbLL7/8kkahqNoi7ODgwIlCUbb1cty4cURbW5tMmDBB6dZLmUxGhg0bRnR0dGgUiqLNazKZjPTv35/o6uqSqVOnKt0i3NraSnr16sWJQlG09bK5uZm8++67RF9fn3z66afk5MmTCrcINzY2kq5duxJDQ0MahaJo62VdXR2xtbXlRKEo2iJcU1NDLC0tiYmJCZkxY4bSrZcVFRXE1NSUmJqakpkzZyrdellaWkoMDQ1pFIqyLcKFhYVET09PZRQKIX9GRqmKliLkz8godhSKoq2XCQkJRCQSqYyWIuTPyCh2FIqiTZaPHj3i+Kmvr69CP2Uio8RisdJoKUL+jIyyt7dXufWSiYxSFS1FCCGXL1/m+GlwcLBCjzx79iyNQlG1Rfjo0aPUT1VtvWQio9jRUoq0TGSUqigUQv6MjGKipZRtvVyzZo2gKBRCCPnpp584fqps6+X333/PiUJRtvVyzpw5NFpK1dbLGTNmEE1NTRqFomzrpUQiERQtRQghEyZM4ERLKfPTESNGUD89dOiQwi3CMpmMDBo0iOjq6iqNliLkz8goPT09pVEohPwZGaUqWoqQNj/t1q2byigUQtoiozp16qQyWoqQtsgoKysrThSKIj9lIqOYaClFUSiE/BkZxUShKNsizERGmZub0ygURX6am5tLdHR0VEZLEdK25Z3tpx4eHgr9NDk5mfqpqi3CTGRUp06dlEahEPJnZJSqaClC2jYN4z/RUkwUiiI/9ff3FxQtRQght27dEhSFQkjb9mCwoqWUXcsykVFMFIqyLcJMZFSvXr2URqEQQsjvv//OiUJRFC1FSNuWX7afKkvE2LRpk6BoKUL+jIwaNGiQykQMJjJqyJAhKrcIL168mIhEIvLJJ58ITsT4q8B/c2uuSCTqBsCHENL7P/9/KoAxhJAikUhkCyCEEPK+quP807fmPnv2DBEREQCArVu3cioShoaGmDhxIqRSKRwcHJCXl4eoqCgQQrBx40ZO1dbIyAiTJk2i2oyMDFrBWrduHae6amJigsmTJ0MqlWLq1KlISUlBXFwcZDIZXFxcOFVQU1NTTJkyhWrj4uKQlJSE1tZWODs7cyqbZmZmmDp1KiQSCaZMmYJnz54hNTUVzc3NNAyXwdzcHA4ODpBKpZg8eTKePHmC9PR0NDQ0wNnZmVMptLS0pNpJkyYhLCwM2dnZeP36NdauXcupkFlbW2PatGmQSqWYOHEigoODkZeXh6qqKvzyyy+c997GxoZqJ0yYgICAABQWFqK8vBwbNmzgaDt16gSJRAKpVIpx48bhzp07KCkpwcuXL7FlyxaOtkuXLhztrVu3UF5ejvz8fOzYsYOj7dq1K6RSKaRSKcaMGYMbN26gqqoKWVlZ2Lt3L0drb29Pjzt69GhcuXIFtbW1SEtLw++//87RvvPOO5BKpZBIJBg1ahQuXryI+vp6JCUl4ciRIxxtjx496GsYPnw4XF1d0dzcjNjYWJw8yc0F7tmzJz3usGHDcPr0achkMkRHR+PcuXMcba9evehxhwwZglOnTgEAIiIicOHCBY62T58+9Hfr378/zp49C6CtY3blyhWOtm/fvvS4vXv3hqurK4C2LpiHhwdHO2DAAHrc9957DxcvXgTQVon19vbmaAcNGkSPa29vj8uXLwNoq676+flxtEOGDKHazp0749q1awDaKqYBAQFUx4SZM1orKyv6Gq9fv46QkBCq1dDQwNChQ6m2Q4cOuHnzJgDg8uXLCA8Pp1pNTU0MHz6c/i0MDAzg4+MDAHBzc0NkZCRHO3LkSHpcbW1t3LlzBwBw+vRpxMTEUK2WlhZGjx5Nj0sIwb179wAAx44dQ0ICfUgF2traGDNmDD1uY2MjAgMDAQB//PEHUlJSqFZHRwfjxo2jf4va2lr6u+/fv5/zxISenh7GjRtHX8OrV68QFhYGANi1axencqyvr48JEyZAIpFAIpHg5cuXePz4MQBg27ZtnGqwgYEB9dNp06ZRPwWAjRs3oqysjGoNDQ2pn06bNg2ZmZl49uwZCCFYv349p7NlbGxM/dTBwQGpqamIjY0FIQQuLi6cDpSJiQnHTxMSEpCYmIjW1lasXbuW01Xq0KEDpk6dCqlUiilTpiAmJgYpKSlobm6Gs7Mzp/tjbm7O0UZGRiItLQ2NjY1Ys2YNr59KJBJMnjwZ4eHhyMrKQl1dHZydnTl+amVlxfHT0NBQ5ObmoqamBi4uLmDD+KlEIsHEiROpn1ZUVGD9+vUcra2tLf0sjB8/Hn5+fnj58iVKSkqwefNmjpbxU4lEgnHjxuH27dsoKytDQUEBtm/fztF27dqVHnfMmDHw9PREZWUlcnJysHv3bo62W7duHD+9du0aampqkJ6ejgMHDnC03bt3p5/zkSNH4tKlS6ivr0dycjIOHz7M0fbo0YMed8SIEXBzc0NTUxPi4uJw4sQJjvb999+nxx02bBjOnDmD1tZWPHv2DGfOnOFoe/XqRY87dOhQeqwnT57g/PnzHG3v3r3p92fgwIH0WGFhYXB3d+doP/roI/oa+vTpQ/00ODgYN27c4Gj79+9Pj9uzZ0/q4wEBAdSrGAYOHEiP+8477+DSpUsA2p4U8PX15WgZP5VIJOjatSv1/Fu3blH/Adr89OOPP6bH7dixI32NN27cQHBwMNUyfsq8Z2ZmZvQ1uru7U09htIyfSqVSGBoa4vbt2wCACxcu0Gs04E8/ZY6rq6tLf5+zZ8/i6dOnVKulpYVRo0bR44pEIty9excAcOLECcTFxVEt46fMcZubm3H//n0AwOHDh5GcnEy1Ojo6GDt2LH3P6urq6O9+4MABzhMTurq6HD+trKzEw4cPAQB79uzhdO309PQwYcIE6nulpaV49OgRAGD79u2cJxsMDAw42sLCQjx58gQAsHnzZk7HjO2nDg4OyM7Opk+3bNiwgfNUgbGxMUeblpZGn275+eefOd1/xk8lEgkcHByQmJiIhIQEyGQyODs7y/kp23ufP3+O5ORktLS0YM2aNRw/NTMzox45ZcoUREdH48WLF2hqasKaNWs4XW8LCwvOteyjR4+QmZmJ+vp6ODs7czrOjJ9KJBJMmjQJDx48QE5ODmpra7F27Vqw6dixI+f6NCgoCPn5+aisrMS6des4WltbW4727t27KC4uRllZGTZu3MjRdu7cmfrp+PHj4ePjg9LSUhQVFWHbtm0crZ2dHf08jh07Fl5eXqioqEBubi527drF0YrFYvoZGzNmDHR1dfF3IHRrrqD8TwDdwO2IVrb79xVCjvNP74ju2LGDBsOq+mEC5VX9iEQiwVoNDY030tra2grSampqCtZqaWkRGxsbQVptbW0a7qzqR0dHh1hZWQnS6urqEktLS0FafX19YmZmJkhrYGBATE1NBWkNDQ2JsbGxIK2xsTExNDQUpDUxMSF6enqCtB06dCDa2tqCtObm5jRgWtWPhYWFIB0AwX8HAIL/vgCItbW1YK3Qz9ibaoV+J4C2SvXb0Ar9vv9TtEzw+39b+zb8VCQSCf5baGhoCNb+/9lPma68EK2BgQHp0KGDIK2hoSExMTERpDUyMnojP9XX1xek7dChA9HR0RGkNTMzI5qamoK0b8tP30T7tvxU6GcXeDM/fVtatfe+mfZN/fRNrk//1/xU6HfoTf1UqD+8ybWsoaGh4GtZIyMjMnfuXIVPUbxNILAjqoW3jEgkWghgIdBWIf0n061bN0ycOBEAEBUVJTdDoq+vT6v4dXV1tOvx5MkTuZk8AwMDWkmqqqqiXZxHjx7JzXoYGRlh8uTJkEgkKCkpoZW3sLAwuVkPY2NjWknKycnBgwcPALTNGLSf32B3UNPT02kXJyQkRG4mg+mgSqVSJCQkIDIyEoQQBAcHy81OsDuoT58+pd3ewMBAuZkBS0tLWh0KDw+nFTKmW8OG3UENCgpCamoqWlpaOJVVBhsbG1pJ8vPzQ2ZmJpqamhAaGiqnZXdQvby8kJeXh4aGBlqJZNOlSxdaMWVmTuvq6jgdMAZ2B/XcuXN49eoVamtraReIjb29Pa1QHT9+HDU1NaiqquJ0yxiYDqpUKsWBAwfQ2NiIiooK8D1NwO6g7ty5EzKZDOXl5Xj27JmclumgOjg44LfffoNIJEJpaSmeP38up/3www9ppXDHjh0QiUR4+fIlp2rM0KdPH9px3rlzJ0QiEQoLC5GYmCinZTqoI0eOxJ49eyASiZCfn8+pMDMMGDCAdnAPHDgAkUiE3Nxc3nkTpoM6cOBAHDx4EACQnZ0tN28iEoloxb9Pnz60g5KRkSE3b8LuoPbs2RPHjh0D0DYv1X7eRENDA8OGDYNUKkX37t1p9zo1NVVu3oTdQbWzs6MdkuTkZLl5E01NTYwaNQoSiQQ2Nja0Q5KQkCA3b8LuoJqZmdGOc1xcnNz8nra2NsaOHQuJRAIjIyPamXn+/Lnc/B7TQWU6uNevXwfQ9gRJ+/k9XV1djB8/HlKpFIQQeHl5AVDsp0wVv6GhgXY9FPkp473V1dXUTx8/fiw3Z8d+IqW0tJR2xcPDw+Xmltkd1IKCAuo1Dx8+lJudY/tpRkYG7eLw+Sm7g5qcnIyIiAiVfiqRSBATE0O7vXx+amFhQT0yIiKCPj2jzE8lEglCQ0ORnJyM1tZWBAUFyWk7duxIPdLf3x/p6elobm7mPCXAwO6gent7IycnB42NjfRcxKZz587Un65evYqioiLU19dzOmAMdnZ2VHv+/HmUlZUp9NNu3bpRPz116hSqqqpQXV1Nu0Bs2B3UQ4cOob6+HpWVlbQDz4btp7t370ZLSwtevXrF6awxsDuoW7duVeqnzBMpQvyU6aCOGzcOu3btgkgkQlFREecJCAY+Py0oKEBSUpKclumgDh06FPv27YNIJEJeXh7naQmGQYMGQSKRYNCgQUr9FPizg9q3b1/88ccfANrmT9vvomB3UD/44APqp+np6XKz0+wnUt59913acX7x4oXc7LSGhgZGjBgBiUQCsViM06dPA1Dsp8wTKWw/TUxMlNtFwe6gWlpa0k53fHy83Pwe+4kUY2Nj+gRPbGys3Pweu4Oqq6tLn+BR5adA294OAIiOjpbbL8HuoDY1NdGnjCIjI+VmnBk/lUgkqK2tpU/lREREyM04szuor169gr+/PwB+P2WuZaVSKYqKiqjX8Pkp+4mUrKwsej0WGhoqN1/M+KlEIkFKSgrtigcHB8vNATMdVKlUiri4OPrkYlBQkNwMLruDGhUVRbu9zDU4G/YTKQ8fPqRPzyjyU0YbEBCAtLQ0hdeyjJ9KJBL4+voiKytL4bUs00GVSqW4ceMGCgoKVPqpRCLB2LFjoaenJ6f5xyDkbhXyHdFUALb/+WdbAKlCjvNP74gy5OfnE11dXQK0VawWLVpEfHx8eJ/Dz8zMJFpaWgRom4H64YcfFM6UpqSk0K6VWCxWOlMaFxdHKxr29vZKZ0qjoqKoVtVM6cOHD6mWeQ5f0UwpM/8K/DlTqug5/Nu3b1Nt7969lc6UXr9+nWqZmVJFz+FfuHCBalXNlJ46dYpqBw4cSDZt2qRwpvSPP/6gWlUzpbt376YVQeY5fEUzpVu2bKFaVTOlv/zyC60eqpopXblyJa0eqpop/eGHH2j1cNy4ceTAgQMKZ0odHR1p9VDVTOk333xDq4eTJ08mf/zxh8IZqC+++IJWD1XNlE6dOpVWD1XNlI4dO5ZWDz/99FNy6tQp3hkomUxGhg4dSquHymZKmflX/Kd6+K9//Yu4urryzkC1tLSQXr16EaCtE65sprS5uZm88847BIDKmdLGxkZiZ2dHAKicKa2rq6NVYVUzpTU1NbQiq2qmlJl/Bdo6LI6OjgpnSktKSmjXStVMKTP/CnBnSvlmoLKzs+lTAF26dFE6o8/MvwJtM1DKZkqZ+Vchfvr06VPqDapmSsPDw6mWPVPKpw0KCqJaVTOld+7coVpVM6Wenp5Uy54p5fNIZv6V7aeKZkrPnDlDtcxMaXR0NK/2yJEjHD9VNlO6b98+6pGqZvR/++03qlU1U/rrr79SPx0xYoRSP129ejX1U1UzpT/++CPVqpopXbBgAfVeZqY0PT2dVzt79mzqvapmSqdPn069V9VMqUQikfNTRd2Q8ePHUz+VKpkplclkZPjw4QRo64R//vnnCmdKZTIZGThwIPVTZTOlra2tpHfv3tRPlc2UNjc3k/fee4/66ddff63UT7t160YAqJwpra+vpx05VX5aW1tLu2GqZkorKyvpEwPsmVI+7y0rKyNGRkYEaOtYK5spLSoqok8BqPLT3Nxcjp8qmylNT0+X81M/Pz9e701KSqJ+qmqmNCYmhnqDqpnSiIgIqmVmShX5KTP/yvipspnSu3fvUm2vXr2U+unNmzc517LKZkqvXLlCtapmSl1dXalW1Uzp8ePHqVbVjD4z/woImyn9K4HAjuj/643oHnCXFe0Wcpz/lRvRM2fOkM2bNysdJmY4duyY4D/8oUOHyPbt2wUNE+/bt0/lcgaGnTt3kt27d5Pk5GSV2q1bt5J9+/YpXc7AsHHjRnLgwAGFJ1I2P//8Mzl06BDJzMxUqpPJZGTNmjXk8OHDChfjsLUrVqwgx44dU3gTw9Da2kp++ukncuLECYU3MQwtLS1k6dKl5PTp0woX4zA0NTWRRYsWkbNnzypcjMPQ0NBAFi5cSNzc3BQuxmF4/fo1WbBggdLlDAw1NTVk/vz55NKlSwoX4zBUVFQQR0dHcuXKFYWLcRhKS0uJo6MjuXbtmsLlDAyFhYVk/vz5Ck+kbHJzc8n8+fOJl5eXwkUODBkZGSqXMzAkJycrLQqxiY2NpcsZFC3GYYiKilK5aIwhPDxc5XIGhuDgYJWLxhju3buntCjExsfHR+VyBgZPT0+Vi8YYrl69qrQoxObChQsqF40xnD17VuVyBoYTJ06oXDTGcPjwYcHLGQ4cOKBy0RjDrl27BPvptm3bVC4aY9i0aZPSohCbdevWKS0KsXF2dla6aIxBJpORlStXKi0KsbVOTk5Ki0IMjJ+eOnVKpZ82NzeTxYsXK100xtDY2EgWLlyosCjEpq6ujixYsEDpojGGN/HTyspK4ujoqHTRGENZWRn1U0WLcRiKi4uJo6Oj0kVjDPn5+WT+/PlKF40xZGVlke+//17pojGGlJQUsmjRIqWLxhji4+NVLm5kePr0qcpFYwyPHz9WubiRITQ0VOWiMYb79++rXNzI4Ovrq3LRGMPNmzcF++m1a9eUFoXYXLp0SbCfurq6qlzcyHDy5EmyZcsWpYvGGI4cOaJycSPD77//rnLRGMOePXtULm5k2L59u8pFYwxbtmxRubiRYf369UoXjbFxcXFRWmRnkMlkZNWqVUqLQmzt8uXLlRaFGFpbW8mPP/6odNEYQ0tLC1myZInSRWN/J0JvRFUuKxKJRO4AxgCwBPASwEYANwFcA9AVQC6AGYQQlXvT/+nLitSoUaNGjRo1atSoUaNGzf87QpcVqZwRJYR8o+BfjX/jV6VGjRo1atSoUaNGjRo1av7Po/F3vwA1atSoUaNGjRo1atSoUfN/C/WNqBo1atSoUaNGjRo1atSo+UtR34jy4O/vj4iICLlVz3zcuXMHUVFRgrQ+Pj50Nb8qbt26RVdJq8LT0xNxcXGCtDdu3EBiYqIg7dWrV5GcnCxIe/nyZbx48UKljhCCCxcucEKelWnPnz8vt9qdD5lMBldXV7nV7ny0trbC1dUVeXl5KrXNzc04d+4cJzxaEY2NjXB1dZWL1eCjrq4Orq6ucrEafNTW1sLNzU0uVoOPyspKXLhwQW4NPB9lZWW4dOkSJ8BaEcXFxbhy5YpcBAcf+fn5uHbtmtzKeD6ys7Ph4eEhtzKej/T0dHh5ecnFdfCRmpoKb29vuagkPhITE+Hj4yMXlcRHbGws/Pz85FbR8/Hs2TP4+/vLxSrxERkZifv378utrefj8ePHCAoKkosM4SMsLAwhISFyK+75CAkJwcOHDwVpAwMDER4eLhdFwse9e/cE+6mfnx8iIyMFaX19ffH06VNBWm9vbxozpQovL6838tOEhARB2mvXrgn2U3d3d96YIj4uXbrEG6vRHsZ728cUKdK6ubnJxRTxwfhp+5giPlpaWnDu3Dm5WA0+mpqaBPtpfX09XF1d5WI1+GD8tH2sBh9VVVU0SkYV5eXlgv305cuXcHd3l4vg4KOgoECwn+bk5ODGjRty8Ud8ZGRkvJGf3rp1S5CfJiUl4fbt23LRHnzExcXhzp07gvw0JiYGd+/eFeSn0dHRCAgIEKSNiIhAYGCgID8NDw/njWviIzQ0FA8ePBDkp0FBQYL9NCAgAI8fPxakvXv37hv5aXR0tGA/FXote/PmTcTGxgrSenh4ID4+XpD2+vXrSEpKEqS9cuUKUlJSBF/Lvomfto8pUqQ9f/68ID9lrmWF+Glra6tgP/1HI2Sj0X/r539lay6zQppZua1sW11wcLCgCANC/lwhzV65rWhbHbNC2s7OjixZsoT4+voq3FbHrJAWi8Uqt9UxK6Tt7e3pym1F2+qYFdKqIgwIadtKiXYRBoo20O3YsUNQhAEhbZt7ISDCgBBC1q5dKxdhoEi7bNkyzsptRREGhBCycOFCQREGhBAyd+5cQSu3CSHkq6++4kQYKNu8/OmnnwqKMCCEkEmTJtEIA2Wbl2UyGRk1apSgCAOZTEYGDx5MtLS0VEYYtLa2ko8++ogTYaBoW11LSwt5//33iY6OjsoIg6amJmJvb090dXVVRhg0NDSQzp07Ez09PeLg4ECOHTumcFvd69evibW1tcoIA0IIqaqqImZmZsTAwIB89tlnSrfVlZeXE2NjY5URBoQQ8vLlS6Kvr68ywoCQti2aOjo6NMJA2eZlJl5KVYQBIW1biTU0NFRGGBDStpUYAiIMCCEkMjJSLsJAkZ8+ePCA+qmyCANCCAkICKB+qmrzMhMvpSrCgJC2bZf4T4QBs3lZkZ+eP39eUIQBIW0bLCEgwoCQtg3rYEUYKNu8zMRLMXFciiIMCPkzXqpXr14qNy///PPPgiIMCCFkxYoVgiIMCCFkyZIlgiIMCCHku+++o36qavMyEy8lJMLg888/p36qavPylClTiIaGBhk+fLjKTfZjxoyhcVzKNi/LZDLyySefEE1NTTJmzBiyb98+hZuXZTIZ6devHyeOS9EmeyZeSltbm0ycOJEcPHhQ4SZ7Jl6KieM6fPiwUj+1s7Mjurq6Kv2UiZfS19cnEomEnDhxQqGfVldXEwsLC+qnp06dUuinTLyUoaEh+eKLL8jZs2cV+ikTL2VsbEzjuBRtsi8oKCC6urrExMSEfPXVV0r9NDs7m/rpzJkzyaVLlxT66YsXL6ifzpo1S+km+/j4eCISiYiFhQWZM2eO0k32TLyUlZUVmTdvntLNy2FhYTQSxtHRkXh5eSn008DAQAKA2NraqvRTX19fAqiONySEEA8PD3otqyzekJC27cGMn6raZM/ES3Xv3l3l5uXDhw8TQHW8ISGE7N27l/qpqs3L27ZtIwA33lCRdv369fRaVtXmZSZeiok3VLZ5mYmXUhVv+HeA/9bW3P8m//StuZGRkTQYds+ePZzqKjvUXSKRoKCggAZtb9++ndOB0tPT42izsrJoqO7WrVs5lU12qPu0adOQmppKK/cbN27kVCDZoe7Tpk1DfHw84uPj0draig0bNnCqikyou0QiwbRp0/Ds2TMkJSWhpaUF69ev51T02KHuDg4OiIiIwIsXL9DU1IT169dzKm/sEOKpU6ciLCwMGRkZqK+vx6+//sqpOLFD3adMmYKgoCDk5OSgpqYGmzZt4rz35ubmHK2/vz/y8/NRWVmJrVu3crSWlpY0hHjSpEnw8fFBcXExSktLsXPnTo6WHUI8adIkeHp6oqysDEVFRdi7dy9Ha2NjQ7UTJkzA1atXUVlZidzcXBrqzdCpUyeqHT9+PC5duoSamhpkZmbiyJEjHG2XLl1oCPHYsWPh6uqK+vp6pKam4uTJkxxt165dqXbMmDE4deoUmpubkZiYiLNnz3K07FD30aNH49ixY5DJZHj+/DkuXLjA0bJD3YcPH46jR48CaKscu7u7c7Q9evSgr+Hjjz/G8ePHAbR14m7cuMHRskPd+/fvj1OnTgEAHjx4gFu3bnG0vXr1osft3bs3/X2CgoLg6+vL0TKh7lKpFD169KBh4v7+/rh37x5H+9FHH1Gtvb09Ll68CKCtwts+bJoJdZdKpejUqROuXLkCoK1qywRqMwwcOJBqra2tafD4jRs36HefgQl1l0qlMDU1pcHj7u7uYHseO9RdKpXCwMCAvk8XLlzA8+fPqZYd6i6RSKClpUXfp7NnzyIxMZGjHT58OD1ua2srDR4/efIkp7vGhLozf4vGxkYEBAQAAI4cOcLpmLFD3aVSKaqrq2ko98GDBzlVWybUnTluWVkZfU/37t3L6WyxQ90lEgkKCwvpe7pjxw5OB0pXV5fjpzk5OYiMjAQhBNu2beN06dmh7hKJBC9evKCV+02bNnG6PwYGBhxtYmIiYmNjIZPJsGHDBk6HnB3qPm3aNMTExCAxMREtLS349ddfOZ1sY2NjqnVwcEBUVBRSUlIE+Wl4eDjS09PR0NCA9evXy/kpWxscHIzs7Gy8fv0aGzZsABt2qPvkyZNx79495Ofno6qqClu2bOFo2aHukydPhq+vL4qKilBeXo7t27dztIyfSiQSTJo0CTdv3kRpaSmKi4uxZ88ejpYd6j5x4kRcv34d/6KOHAAAIABJREFUr169Ql5eHn7//XeO1tbWluO9ly9fRnV1NbKysnD48GGOlh3qPm7cOLi5uaGurg5paWnUqxjs7Ow43nvmzBk0NjYiKSkJZ86c4Wi7detGtaNHj8bx48fR2tqK2NhY6j8M3bt3p9pRo0bR1/j06VNcvnyZo3333Xfp94ftpxEREbh+/TpH+95771HtwIED6fkhLCwMXl5eHO0HH3xAtWw/DQ4Oho+PD0f74YcfUm3Pnj3h6uoKoK27dvfuXY6W8VOJRIJ33nmHnkvu3LmDwMBAjrZfv370uHZ2dvR39/b2RmhoKEc7cOBA+p7Z2Njg6tWrANq6YI8ePeJoBw8eTI9rZmYGDw8PAG1PaUVGRlKdSCTieK+RkRFu3rwJALh48SJiYmI4WsZPpVIptLW16fvk6uqK+Ph4qmX8lHm9hBD6Pp06dQopKSlUq6mpiREjRtDjNjU10XPU0aNHOR0zLS0tjBw5kmpra2vpOerQoUOcJ7q0tbUxevRoqi0vL8eDBw8AAPv37+c8paWjo4MxY8ZQbXFxMcLDwwEAu3bt4nT/2/tpbm4unjx5AkIItm/fzuno6+npYfz48VSbkZGB6OhoEEKwefNmzpNM+vr6mDhxIiQSCSQSCZKTk/H8+XOFfsq+lo2NjUVCQgJaW1uxfv16jp8y17KMlvHT5uZmrF+/ntNxNjEx4VzLPnr0CGlpaWhoaMCvv/7K6faamppi6tSpkEgkmDp1KkJDQ5GVlaXQT9nXp/fv30dubi6qq6uxefNmjtbc3Jzjp35+figsLMSrV6/w22+/cbSWlpac69Nbt26hpKQEJSUl2LVrF0drbW3N8VMPDw+Ul5ejoKAA+/fv52htbGzoZ3f8+PEwNDTE34HQrbnqjigLplMn5IcJlP87tR07dhSkE4lEgrUaGhrE2tpasNbKykqQVlNTkwZBq/rR0tIi5ubmgrTa2trEzMxMkJbpIgnR6urqEmNjY0FaPT09YmBgIEhrYGBA9PT0BGkNDQ1pGLWqHyMjI6KhoSFIK/T3AiD4/XpTLRP0LeRH6GcBALGwsHgrWqGfXQCCvxMABH/X3qZWqDcA/wzf+7u1b+KnIpHoH+GnQj/rb+qnQr/HTMdJiFZPT48YGhoK0urr67+Rn+ro6AjSGhkZEU1NTUFaob/Xm2rflp8K/fsCb89738RP30T7T/BItZ++vffsTf1UqFZTU/ONvFfoZ/1Nr2Xflp/OmjVLZX7p2wACO6Iq41v+L8FULoG2CmT7+Q2mei2RSFBfX0+raQ8ePJCb32CqLVKpFBUVFbQ7ERwcLDeTwVSvJRIJXr58SauOgYGBcnMW7Op1Tk4OrZDdu3dPbh6CXW1JS0ujVce7d+/KzThYW1vTCkp8fDzt4Pr5+cnNIrCrLdHR0XSW1dfXV+4ZfHb1Ojw8nFa97ty5I/f+s6vXQUFBSE1NRUtLC/z8/OS0YrGYVun8/PyQmZmJxsZGuW4ZANjb29NKoaenJ/Lz81FfX4/79+/LaZnPgEQiwZUrV1BcXIza2lraBWLDrl6fO3cOr169QnV1tVwlGPizei2RSHD8+HHU1NSgoqKCduDZsKvXv//+OxoaGlBeXi5XNQbaqtfMe7Zz507IZDKUlJTgyZMnclqmeu3g4IDffvsNIpEIxcXFiIqKktMOGDCAVumYLnNBQQGePXsmp2Wq12PHjsXu3bsBAHl5eZzuHsCtXo8cOZJ2pLOzsznVaEbLVK+HDBlCOyiZmZmcTiDQVr0eNmwYpFIpBgwYgEOHDgEA0tLSOJVrgFu97t27N+1ep6amys04s6vXPXv2xLFjxwC0zUC1nwthV6+7d+9OOxkJCQlyM87s6rWdnR3tzMTGxsrNhTDVa4lEgo4dO8LNzQ1A27xU+7kQdvXazMyMdoajo6Pl5uzYT2IYGhrSznBkZKTc3LKBgQGtSGtra9MuzuPHj+Vm59jVa0II7eKEh4fLzc4ZGxvTDl9DQwNu374NQLGfMtqq/4+9746q6sy73nRQELEixRZ77yV2Y0E4d1Ymk8xkJl+SaZkVnWRakkkymUlTY68oUkSKIFUUlGJDQEGqVAEpUqQX6R3u8/1xv+fxHO895x7elWTyru/ute5f2esE771nc/j9nr13WxvbTsTFxan5i/nT64aGBnafx8bGqnnc+NPrqqoqxMXFAVBtil70rVE95TgOT548YffujRs31Ly9/Ol1fn4+2zhI6SnHccjMzGQbXE16amNjw+73Bw8eIDc3F0qlUu1EASA8iREXF4fCwkJRPZ08eTLTnJiYGJSWlqK/v5/93uKDnsRQKBSIiIhARUWFqJ6+9NJLjBsUFITa2lp0dXWpnVQAVCcxKJf6Mjs6OthnwsecOXOYnrq7u6O9vR2tra1qpxoA1UkMel1nZ2d0d3fj2bNnbGPEx8KFC9l1jxw5gsHBQTQ2NiI5OVmNu3jxYnbdvXv3ytbTAwcOQE9PDzU1NcjIyFDjrlixgm0y6FakqqpKsN0Dnuspx3HYuHEj09OKigrk5OSocdesWQOFQoG1a9eyDUpZWRny8vIEXKqnHMdhxYoV7DRQSUkJCgoKBFwDAwN2EmPx4sVwdnYGABQVFal5nOlJDIVCgblz5zI9LSgoUMuMMDQ0ZHo6Y8YMuLm5AVD5+V/0ONOTGAqFApMnT2Z6mpOTo5YZwT/ZZm1tzTbDWVlZapkRJiYmTE/Hjh3LNsMZGRmoqakRcPl6amFhwTbDaWlpar5l/sk2ExMTdtImOTlZLQdi5MiR2LlzJziOg56eHjtpk5SUpJYDwT/Z1t/fj4iICADAvXv31LIdqJ5yHIeOjg6mCfHx8Wr+Yv7JtubmZvaMpUlP+Scxampq2HPT7du31TIYxo4dyzSyrKyM3bua9JR/sq2wsBDJyclsS/2iB3fixIlM97Kzs9kGNyoqSs3/OmnSJMZNTU1lJ2I06amtrS3Thnv37iE/P1/yWZZqw61bt1BcXIyBgQG10weA8GTb9evXUV5ejt7eXnZKiQ/+ybaQkBDU1NSgu7tb7aQCIDyJsX79ehgZGalxfjKQ89fq9/X6qW9EKSorK9kmSpufp7i4mE1OqZ/n7t27Gs+fP3r0iOjp6RFAu5/n4cOHbKIxb9488umnn4r6eR48eMC42vw81NMKqPw8X3zxhaifh3paAe1+nitXrjCuNj9PQEAA42rz83h5ebFJ2Jo1ayT9POfOnWOTMOrnycvL08ilnlY5fp7vvvuOTcK0+Xm+/PJLNgnT5uf55z//ySZh27dvJ6dPnxb18/zlL38hAAR+nvLyco1c6mmlfh4XFxdSWVmpkUs9raampszPU1VVpZH7xhtvEAACP09NTY1GrkKhIAAEfp66ujqN3O3btxNAtYWQ8vMolUqyYcMGAkCrn4d6WgHVZoH6eZqbm9W41NMKqLYFb731FgkICNDo5xkcHCSzZs0iALT6efr7+8nUqVMJ8NzPc/nyZY1+np6eHmJra8umw9TPo8lL2dnZySa91M8THh6u0c9DPa2Adj9PU1MT25Zr8/PU1dURMzMzAqi86VJ+nqdPn7JN1LRp0yT9PKWlpcTQ0JAA2v081NMKPPemi/l5qKcVeO7nEfOmp6SkCPRUys8THx/PuNTPI6anN2/eZFxtfp6IiAjGXb58Ofn6669Jenq6Rn2inlYAZOXKleTbb78lmZmZGrnU00r1dN++fSQ7O1sj183NjXFffvllcuDAAVE9PXXqlEBPDx06RPLz8zVyDx06xPR006ZN5OjRo6J6+s033zA9pd704uJijVzqaTUyMiLbtm0jp06dEvWm/+1vfxPoqbOzs6g3/f3332d6umvXLkk9/e1vf8v01MnJibi6uorq6ZtvvkkA1Vb3Zz/7GfHw8BD1Ur766qtMe1999VXi6ekpqqcODg4CPZXypm/atIkAqlMyb7zxBvH19dXoTVcqlWT16tUCPfXz89Oop9TTSvX0N7/5jaSezp07lwDQ6k2nnlZAtSV99913SWhoqEbtpZ5WQHvWR1dXF9vIacv6aG9vZxsuftaHJu199uwZ21rZ2dmR3bt3i+ppQ0MDO1U1efJkyawP6mnl66lY1kdZWRnTU21ZH48fP1bTU7Fn2dzcXKY52rI+0tPTGVdb1gf1tALasz6op5U+y0plfVy/fp1xtWV9hIaGCvRUKuvDz8+PaSTN+hDT0/PnzzOutqwP6mmlWR+HDh0S9aZTT6ucrI8fG5C5EdX9IaoBXl5eWkMJKNzd3WV/8GfPnpUMeeHj5MmT5OTJk6J/xPBx9OhRyZAXPg4cOCAZ8sLH3r17JUMJ+Pjyyy8lQ14olEol+fzzzyVDXvjcf/7zn5K/SCmGhobIP/7xD8mQF4rBwUHyt7/9TTKUgKK/v598+OGHkiEvFL29veSDDz6QDHmh6OrqInv27JEMeaHo6Oggu3fvFv0jho+Wlhaye/duyZAXisbGRrJ7927JUAKKmpoasmfPHsmQF4rKykry5z//mURHR4uGElCUlpZqDXmhKCgo0BryQpGdnS05FOIjPT1da8gLRVJSktbQLIq4uDitIS8Ut27d0hryQhEVFaU15IXi6tWrWkNeKEJCQrSGvFD4+/trDXmh8PHxka2n58+flxwK8XHu3DnJoRAfp0+flhwK8XHs2DHJoRAfBw8elBwK8bFv3z5y7tw50T9i+Pjqq68kh0J8fPHFF5JDIQqlUkk+/fRTyaEQn/vRRx9JhrxQDEdPBwYGyIcffig6FOKjr6+PfPDBB5IhLxTd3d1kz549kiEvFMPR09bWVrJ7927RoRAfTU1NsvW0rq6O7N69WzLkhaKqqor8+c9/lgx5oSgrK9Ma8kJRWFgoW09zc3O1hrxQZGRkaA15oUhOTtYamkWRkJCgNeSF4s6dO5JDIT6io6Nlh7xERETI1tPQ0FDJoRAfgYGBZP/+/aJ/xPDh6+srORTiw9PTU7aeurq6Sg6F+HB2dpYcCvFx4sQJyaEQH4cPH5YcCvHx3XffSQ6F+Pj6668lh0J8/Pvf/5atp5999pnkUIjP/eSTT4i3t7esZ9m///3vokMhPgYHB8lf//pX0aHQfxty/xDVhRXpoIMOOuiggw466KCDDjro8L1AbliRrkdUBx100EEHHXTQQQcddNBBhx8Vuj9EddBBBx100EEHHXTQQQcddPhRoftDVAcddNBBBx100EEHHXTQQYcfFbo/RDUgKioK8fHxarHQmhAREYF79+7J4l65cgVJSUlq8f2aEBoaiuTkZLW4aU2gJc9yuAEBAcjIyFCrBdAEWggth+vj44OcnBytXEIILly4gLy8PFnc8+fPo6CgQCtXqVTC3d1dLTJeE4aGhuDu7q4WGa8JAwMDcHV1VYuM14S+vj64ubmpRcZrQnd3N9zc3NQi4zWhs7MT7u7uanUdmtDa2goPDw+1ug5NaGpqgqenp1q8vCbU1tbC29tbLV5eE54+fcrqF7ShrKwM/v7+atUemlBcXIyAgAC1WiVNKCgoQHBwsFoNiCbk5uYiNDRULbZeEzIzM3HlyhW1CiZNSEtLQ3h4uFrEvSYkJyfj+vXrahH3mnD//n1ERUWp1YtoQnx8PGJiYtSqnTThzp07uHXrllp0vibcvHkTsbGxajVQmhAdHY24uDhZ3GvXriEhIUGWnoaHhyMxMVGWnl6+fBkPHjyQxQ0ODh6Wnqanp8vi+vv7y9ZTX19fZGdny+J6eXkhNzdXlp56enoiPz9fFtfDw0O2nrq5uaG4uFgrd3BwEK6urmr1R5rQ398PNzc3lJeXa+X29PTAzc1Nrf5IE4ajp21tbfDw8FCr69CE5uZm2XpaX18PLy8vNDQ0aOVWV1fD19dXlvZWVFTAz89PrdpDE0pKSmTraWFhIYKCgmTpaV5eHkJCQmTpaXZ2NsLCwmTpaUZGBq5evSpLT1NSUnDt2jW1+jtNSExMRGRkpCztTUhIQExMjCztjY2N1Virpwm3bt3CnTt3ZGlvTEwM7t69K0tPr1+/Piw9vX//viyNDAsLk62nISEhSElJkaWRgYGBSEtLk8W9dOkSq7rSBl9fX1YzqA3e3t7D0tNHjx7JfpYtLCyU/Sz7Yp2cJlDtlfMs+5OGnESj7+v1vyU1l8ZNjx49mvz617+WTEylcdPaoscJIeT27dssevydd96RTEylcdM0evzy5cuiqX00btra2pr84Q9/kExMpXHTNHpcKuGPxk3b2dmR999/n0RGRoqm9jk7Owuix6Ojo0VT+44cOcKix2liqlhq3969e1n0uLaEvy+++EJWjQ4hhHz00UcselxbYuqePXsENTpSiam///3vWfS4tsTU3/zmN4LocamEv9dee01WjQ4hhDg6OrIanW+++UYy4W/r1q2yanSUSiVZu3atIHpcLDFVqVSSZcuWCWp0xBJTh4aGyLx581j0uFTC38DAAJkxY4agRkcsgbqvr49MnjyZGBoakldeeUUyMbW7u5tMmjRJUKMjltrX0dFBxo0bR4yNjYmDgwM5c+aMaAJ1S0sLsbS0JKampsTR0VEygbqxsZGMHDmSmJmZsRodsQTqmpoaYmpqymp0pBKoKyoqiJGRkaBGRyy1j1ZRWVhYkNdff534+PiIJqbSKiptNTqEPK+ionrq7+8vqqdJSUlMT9966y0SGBgoqqe0iorqqVRianR0tKwaHUIICQsLE+jplStXRPX00qVLghodKT29cOGCrBodQghxcXFheipVo0MIIcePHycAyNSpU7UmptIqKlpLJlajQwgh//nPf5ieaktM/eSTTwh4tWRSiakffvihoEZHKjH1vffek1WjQwghb7/9tqwaHUIIef311wV6KpWYynGcoEZHSk+3bdvG9FQqMVWpVJL169cLasnEElOVSiVZsWKFrBqdoaEhsnDhQkEtmViNzsDAAJk1a5asGp2+vj4ydepUQS2ZWGJqT08PsbGxEdToiCVQd3Z2kvHjxwtqdMQSqFtbW4mVlZWsGh1aRUVryaQSU2kV1YgRI1iNjlhiamVlJTE2NmZ6KpWYWlpaSgwMDLTWkhGiSoSnekprdMT0NCsri+mpVC0ZIc+rqLTV6BDyvIqKX0smpr03btxgekprdMT0NDw8XFBLJlajQwghQUFBTE9pjY6Ynvr4+Aj09Nq1a6J66urqymrJpGp0CFE1VoBXSyZWo0OIKjWdPstK1ZIRokruxf+rJZOq0SGEkM8++0xWLRkhz6uotNXo/DcAXWru8JGUlMQKeJ2dnQXF7vwyZo7jUFdXxwp4T5w4IZhAGhoaYuPGjaxMtqKiAg8ePAAhBEePHhVMFWkZMy3VLS4uRlpaGgghOHjwoGD6Z2xsjC1btrCf4dGjR8jMzIRSqcR3330nmNKZmJiw4mZalJ6bm4uhoSHs27dPME0zMzNjxc0cxyE5ORkFBQUYGBjAvn37BFMvWsZMC9gTEhJQXFyM3t5e7N+/XzDtGTlyJCu3d3Jywp07d/DkyRN0dXXhwIEDgvfewsKCcR0dHRETE4PKykq0t7fj8OHDAu6oUaNYuf2uXbsQHh6O2tpaPHv2jBV1U4wePVrADQ0NRUNDA+rr61n5NsWYMWNYcfPOnTsREBCAZ8+eobq6mpVvU4wdO5YVN+/cuRM+Pj5ob29HRUUFPDw8BFxaxsxxHHbs2IHz58+ju7sbJSUlrFCbYuLEiay4efv27XBxcUF/fz8KCwvh5+cn4E6aNIlxt23bhlOnTkGpVCIvLw+BgYECrq2tLfuObd68GSdPngSgKvIODQ0VcGkZM8dxWLduHXuf0tPTcfXqVQF36tSp7LorV66Ei4sLgOcbPj6mT5/OuEuXLoWrqysAVeH2jRs3BFx+GfO8efNw/vx5AMDdu3fVyptnzZrFuDNnzoSXlxcA1ZQ5Pj5ewJ07dy7jTpkyBb6+vgBUW7sXC+7nz5/PuDY2NvD39wegOgWRmpoq4C5atIi9Z+PHj2fvf1hYGB4+fCjgLlmyhF131KhR7P0PDg5WK6Jfvnw5e8/MzMxw5coVAKrt2ovl8itXrmTX1dfXx7Vr1wCoTivwt1V6enpYvXo1+3kHBwdZobmnpyfKysoE3LVr17LrdnV1saLtFzf6+vr6WLduHft5W1pamJ6eOXNGsCkyMDDA+vXr2XXr6+uRkJAAADh58qRgm25oaMi0V6FQ4OnTp0hKSgIAHD16VFDWbmRkhE2bNjFuSUkJUlNTQQjBoUOHBJsXY2NjbN68mXHz8/PZhP27774TbEhe1NPs7GxkZ2djaGgI+/fvF2wyTE1NBXqalpaGR48eadRTMzMzgZ7ev38fRUVF6Ovrw759+9T0dPv27UxP7969i9LSUnR3d+O7774TfBfMzc1Zub2joyNu3LiBiooKdHR04NChQwLuqFGjBNxr166huroaLS0tOHbsmIBraWmJXbt2geM47Nq1C2FhYaivr0dDQwNOnz4t4FpZWTE9dXBwQGBgIJqbm1FTU8N0gmLMmDECPb148SLa2tpQWVkJd3d3AXfcuHFM93bs2AFPT090dXXhyZMnuHDhgoA7YcIEgZ66urqir68PRUVF7N6nsLa2Zt/dV155Bc7OzhgaGkJ+fj4uXbok4NrY2Ai49PdOdnY2QkJCBFx7e3v2+W7YsIG9TxkZGex+ppgyZQq77urVq3H27FkAzzd8fEybNo19d/l6mpiYyO5nipdeeolxFy5cyN7TuLg43L59W8ClespxHObMmQNPT08AwO3btxEXFyfgzpkzh1132rRp8PHxAaDa2t2/f1/AnT9/Pvu32dnZsd9n165dQ0pKioC7cOFCdl2+nl65cgUZGRkC7pIlS9h1R48ezd7/kJAQZGdnC7jLli1j1+XraUBAAB49eiTgrlixgnENDQ0REREBQLVd42+r9PT0sGrVKvaeKZVKREVFAQAuXLggOE2lp6eHNWvWsOv29PTg5s2bAAB3d3fBRl9fXx8vv/wy47a2tiI2NhYA4OLiItjSGxgYYN26dYzb2NjIfvedPn1asHnn6ynHcaipqWGf1bFjxwQbckNDQ4GelpWVITk5GYQQHD58GB0dHYxL9ZR+FoWFhez0nSY95T/L5ubmIisrC0qlEvv27dOop/QeysjIQF5eHgYHB7Fv3z7BttfMzAzbtm1j101KSkJhYSH6+/uxb98+waaVPstSPY2Pj0dJSQl6enqwf/9+wXfB3Nxc8Hx669YtlJeXo7OzEwcPHhRwLSwsBHoaGRmJqqoqtLa24ujRowKupaUlHBwcmJ5evXoVdXV1aGpqYs9oFKNHjxboaXBwMJqamlBXV4czZ84IuC/qqaWlJf4bkJuaq9uI8nDgwAFWZKvtNX78eNlcWj7/fXOH8zP8UNxx48bJ4unp6ZGxY8fK5tLSaG0vfX19Mnr0aFlcAwMDVjCt7WVoaEjMzc1lcY2MjFgZtbaXsbExMTU1lcU1MTEhRkZGsrimpqasjFoOV+7nK/ffBYCMHDlSNlfueztcrtzPF1AVs8vlyv2ODZcr93s+XK7cew2Qfw8DPw3N+aH09KegvcP5LH4oPbWyspLFNTAwkH0P0U27HK6hoaFsLTEyMhqWnhobG8vimpqaEgMDA1lcMzMz2Z/ZcLg/lPbK/RyGy/0paK/c7y7w09DTH0p7fwoa+b9NT3+IZ9nh6Km+vv6w9HQ4z7Jvvvmm6GmsHxKQuRE1hA4Mc+bMwRtvvAFA5Zd60bc2duxYNl3t6upCZGQkANXmhT+VB55PYjmOw7Nnz9jUKyYmRjBFAlRbMDpFqqurYxufyMhINY/DpEmTGLeiooJtESIiItS8CLa2tmwyVFRUxLay4eHhav4CugVTKBTIyclBeno6CCG4cuWKmg9g6tSp7Lrp6elskhUWFqZ2/n369OnsuomJiWyS9eIkGABmzpzJrnvnzh0UFRWhv78f4eHhatzZs2ez60ZGRqKsrAy9vb1qU2MAmDdvHnvPwsLCUFVVha6uLja15GPBggXsugEBAairq0N7e7vaxg4AFi9ezH5eLy8vPHv2DK2trWxjxMfSpUvZdc+dO4eOjg40NzezCScfK1asYD/vyZMn0dvbi4aGBrXtHgDBJPbQoUMYGhpCbW2t2jSavwVzcnJiE7/q6mq2XaLQ19dnW7Dt27eziV9lZaXa5JpuwRQKBbZu3cq2LWVlZXjx9AP/VMH69evZdLCkpASZmZkCLv9UwerVq3HixAkAQFFRkdqUm3+qYNmyZWzjUFBQgLy8PAGXf6pg4cKFbJKYl5entmHkb8HmzJnDtuLZ2dlq/g1TU1M2iZ02bRrbimdmZqr5N/inCuzt7dnGIT09XbCNBISnCiZMmMA2DikpKWp+OP4WzMrKim0cHjx4oOaH458qMDMzQ1BQEACV//RFfzHdgtHNAN3gxsfHq3ncrKys2CR2aGiIbdBjY2PVfGv8UwU9PT1sg65JT/mnCtra2hATEwMAuHHjhpoXjX+qoL6+nulpVFSUmr+MvwV7+vQpu8euXbum5gPjnyooKSlBYmIiCCGIiIhQ83bxTxU8evSIbWU16emUKVOYNmRkZLBTLpr0lL8Fe/DgATvlEhYWhhdBTxVwHIe4uDgUFhZiYGBA7VQDIDxVEBMTg9LSUvT19bEtEB/8UwVXr15FZWUluru72e9DPvinCoKCglBbW4uOjg72+fHBP1VAPeZtbW3sdycf/FMFbm5uaG9vx7Nnz9ROSwDCUwXOzs7o7u5GY2Oj2nYPEJ4qOHLkCAYGBgSnnyhePFWwb98+AJr1lH+qwMHBgW2vnz59iuTkZAGXf6pg69at7DRQeXk50tLSBFz+qYINGzYwPS0tLVU7hcHfgr388sts011cXIysrCwBl3+qYPny5Th16hQAlU80NzdXwOWfKli8eDE7PfPo0SPk5+cLuGJ6mpOTo+ZF5p8qmDFjBtzc3ACoTvC86EXmnyqYPHky09OMjAxEwkSqAAAgAElEQVS1bIcRI0YwPbW2tmYnklJTU9WyHfh6OmbMGFy8eBGAZj21sLBgempubo6AgAAAqu30i/5i/qkCY2NjtsFNSEgQnMIDhKcKqH4AqpNBL2Yw8LdgfX197Fno9u3baj5g/qmCjo4O9ix08+ZNNR8w/1RBU1MTe76Jjo5W8/by9bSqqordY5ryD/inCp48ecKeWcLDw9X01M7Ojt1rhYWFbCt79epVNf/r5MmT2T2clZXFtrJhYWFq3lOqpxzHITU1lZ1y0aSn/FMFCQkJyM/PF32W5Z8quHnzJkpKSkSfZfmnCiIiIlBRUSH4fcgH/1RBSEgIampq0NnZqXYCAnh+qoDjOKxatQoGBgZqnJ8M5Py1+n29fuobUYqysjJiaGhIAJD58+eTzz77TNQXWFhYyDZRixYtIv/617/IgwcPNPpNcnJy2JRiyZIl5D//+Q9JSUnRyE1LS2PcZcuWka+++oqkp6dr5N67d49xV65cSb799lvy8OFDjb4Q6lPV09Mjq1evJvv27RP1plCfKvWmfPfddyQ3N1cjNyQkhE111q9fTw4dOiTqTbl48SKb6mzatIkcOXKEFBYWqvEIIcTDw4NNdbZs2UKOHz8u6gukPlXqCzx58qSoL5D6VI2MjMiOHTuIs7OzqC/w22+/JQCYN+Xs2bOivsB//etfBFBN1J2cnIirq6voJOof//gHAVRTcoVCQdzd3UV9gdSnOmLECPLqq68ST09PUV8g9amam5uT1157jXh5eYn6AqlP1cLCgrzxxhvEx8eHNDY2auT+/Oc/J4Bqmv2rX/2K+Pn5iXpTdu3aRYDn3hQpn/WWLVsIoN1nTX2qgHaftVKpJEuXLmWT2d/97nckLCxMo4+F+lQBlY9Fymc9MDBAXnrpJQI891lfu3ZNo4+lr6+P2NvbE0Dos9bkY+nu7ibW1tYEEPqsNflYOjo62ER26tSpzGetycdCfaqAymf9t7/9TdRn3dDQwDYr2nzW1KcKPPemiPmsy8vL2WZfm8+a+lQB7T7rvLw8oqenR4DnPmsxPaU+VUC7zzoxMZFxqc9aTE9jY2MFeirls46KimJcbT5r6lOV47OmPlV9fX2yceNGcuTIEVGfNfWp8n3WYr7As2fPytbTY8eOMT2lPmsxX+D+/fsJAIHPWswXSH2qJiYmWn3W1KdKfYFubm6ivsAPPviA6ak2n/Uf//hHAqi2jq+99hq5cOGCqC/w//yf/8P0VJvPmvpU5fisqU+V77MW017qU7WysmI+a02+QKVSSdatW0cA1cZPm54uX76cbaSkfNZDQ0NkwYIFAj29cuWKRl8g9akC2n3W1KcKaPdZU58qoPIF7tmzR1RPOzs72TaM6qmYz7q1tZVtaKnPWkxPm5qa2GmeGTNmSPqsa2tr2bZcm8+a+lQB7T7rkpISpqcLFiyQ1NP8/Hymp9p81pmZmWp6KuazTk5OZlxtPuu4uDjG1eazpj5Vvs9aTE+vXr2qpqdiPuvAwEDGpT5rMT319vYW6KmUz5r6VOX4rKlPle+zLi0t1cilPlXqsz5z5ozos+yPDeg2ov9z3L9/H8eOHQPHcZg+fbokNzExEadPnwbHcZgyZYok98GDB3BxcWGbECmkpqbCzc0NTk5OsLW1leRmZGTAw8MDTk5OmDRpkiQ3KysLFy5cgKOjIyZOnCjJzcvLg7e3NxwdHTF+/HhJbmFhIS5evIhdu3Zh7NixojxCCEpKSuDv7w8HBweMGTNGkltRUYHAwEDs3LkTo0ePFuUqlUrU1NQgODgYO3bskDwTPzQ0hMbGRoSGhmLHjh2wsLAQ5Q4MDKC9vR1XrlzBtm3bYG5uLsrt6+tDb28vwsPDsW3bNowYMUKU29PTA0IIrl+/jq1bt8LMzEyU29nZCWNjY0RFRWHLli0wNTUV5ba2tsLS0hI3btzApk2bYGJiIsptamrCxIkTcevWLWzcuBHGxsai3Lq6OkybNg2xsbFYv349jIyMRLlPnz7FvHnz8Omnn2LdunUwNBSXmSdPnmDlypX49ttvsWbNGknu48ePsWnTJhw9ehSrV6+WnPDl5eXB0dERLi4uWLVqFfT1xQPCs7Ky8Itf/ALe3t5Yvny5JDc9PR1vv/02277q6emJclNSUvDee++xbYEUNykpCR988AHb1EpxExMT8fHHH0OhUPlnpbj379/Hv/71L7aFkOLeu3cP33zzDRQKBWbNmiXKA1TT+++++45tLKRw//59HD16VJae3r9/HydPngTHcZg6daok98GDBzh79iycnJwwefJkSW5ycjJcXV3BcZxWPU1PT4eHhwccHR1hY2Mjyc3MzISnpyecnJy06mlubi68vLzg6OiICRMmSHILCgrg6+uLXbt2Ydy4cZLcoqIi+Pn5YdeuXVr1tKysDAEBAdi5cyesrKwkuVVVVQgKCtLqMRoaGkJDQ4MsPR0cHERLSwvCwsKwfft2ST3t7+9Hd3c3wsPD8corr2DkyJGi3N7eXgwODuLatWvYunWrpPZ2dnbCyMhIlp62tbXB3NwcMTEx2Lx5s6SeNjc3Y/z48bh58yY2bdokqaf19fWYPHky7ty5gw0bNkjqaXV1NWbPno2PPvoI69atk+SWl5dj6dKl+PLLL7F27VpJPS0uLsaGDRtw6NAhrFmzRlJPHz16hJ07d+LMmTNa9TQ7OxuvvvoqPD09sWLFCknuw4cP8etf/5r5XKW4qamp+N3vfgeFQoElS5ZIallycjL27NkDjuOwaNEirXr6j3/8AwqFAvPnz9eqp59//jk4jsPcuXO16ulXX30FhUKB2bNni/Iod9++fVAoVDkHUrh//z4OHz4MjuPw0ksvSXITExNl62lSUhLOnDnDNstSSE5Oxrlz58BxHOzs7CS5aWlpcHd3h5OTkyw9PX/+PJycnGBtbS3JzcnJka2n+fn58PHxgaOjo2w9dXBw0Pos++TJE1y6dAkODg5a9bSyslL2s2xdXR1CQkKwY8cOjBo1SpQ7NDSE5uZmXL58Gdu3b5fU3p8ydGFFOuiggw466KCDDjrooIMOOnwvkBtWpOsR1UEHHXTQQQcddNBBBx100OFHhe4PUR100EEHHXTQQQcddNBBBx1+VOj+ENVBBx100EEHHXTQQQcddNDhR4XB119//aP9z9zd3b/+05/+9KP9//6niIiIQFlZGezt7SXN/gBYHYi9vb3WeOSQkBDU1dXJ4gYGBqKpqQm2trZauf7+/mhtbYWtra2k2R9QlTF3dnbK4np5eaG3txc2NjZauefPn8fg4CAmTZokaeAnhLAodmtra63cc+fOwdDQUCtXqVTi7NmzMDExwcSJEyW5Q0NDOHv2LEaMGIEJEyZIcgcGBnD27FlYWFhg3Lhxkty+vj64uLjA0tISY8eOleR2d3fj3LlzGDNmjKQhHgA6Ojrg5uaGcePGSYaRAKqwovPnz2PChAmShnhAFVbk5eUFa2trrYXHtbW18Pf3h7W1taR5HlCFFQUFBWHSpElazfNlZWUICwuDjY2NZHAJoAoRiIiIgK2trWRwCaAKJ4iOjoaNjY1Wbk5ODm7dugVbW1vJkBNAFa4RFxcHOzs7yYApQBWucf/+fdjb20sGogCqoIjk5GTY29tLBqIAqqCgjIwM2NnZaeXGxsYiOzsb9vb2kuEpgCq6Pz8/H/b29pKBKICqCqWoqEgW99q1aygrK4OdnZ1WPaV1IHK4ly9fRm1tLezs7LRqZFBQEBobG2VxL126hJaWFtl62tHRIVtPe3p6ZOmpp6cnBgYGYGNjI6kjAODu7g6lUilLe11dXWFgYCBLe11cXGBsbPy96ung4CDOnDkDc3NzjB8/XpLb39+Ps2fPytLTnp4enDt3DlZWVlr1tLOzE66urrL0tK2tDR4eHpgwYYJkGAmgCivy8vLCxIkTtWpvfX09Ll68KEt7q6qqEBAQgEmTJmnV3vLycoSGhsrS3uLiYkRERMjS3oKCAkRFRcnS3tzcXNy8eRN2dnZa9TQzMxN3796VpadpaWm4d+8e7OzstOrpgwcPkJycLIt77949pKeny9Leu3fvIjs7G3Z2dlr19Pbt28jLy5OlkTExMSgsLJTFvX79OkpLS2U9n4aHhw9LT2tqamRpZHBwMOrr62VxAwIC8OzZM9jZ2WnVPT8/P7S1tcnSUx8fH3R3d8vW0/7+fll66uHhMSw91dfXl8V1cXGBkZGR7GdZU1NT2Xo6cuRIrXr638A333xT+/XXX7trJcqJ1v2+Xv9b6ltoNPXIkSPJz3/+c8m4dhpNTePavb29RePaaTS1nLj2mJgYFtf+5ptvEn9/f9H6CxpNPWbMGPLWW2+RgIAAjXHthDyPph47dix5++23SXBwsMa4dkKeR1PTuPbQ0FCNce2EEHLu3DkW1/773/+eXLlyRWP9BSGEnDhxQhDXHh4erjGunRBCDhw4ICuunRBCvvrqKxbXvnv3bhIVFaUxrp0QQj799FMW1/7BBx+IxrUTQshf/vIXQVz7rVu3NMa1E0LIn/70J1lx7YQQ8s4777C49o8++kg0rp0QQn75y18K4toTEhJEuT/72c8E1UOJiYka49oJIWTHjh2CuHax6iGlUkk2bNggqB4Si2tXKpVk5cqVgrj29PR0jfHnQ0NDZNGiRYLqIbG49sHBQTJ79mwW1y5VPdTf30+mTZvGqocOHDggGtfe29tLbG1tZVUPdXZ2kgkTJrDqIam49ra2NmJlZcXi2o8fPy4a197c3EwsLCxkxbXX19cTMzMzYmxszKqHxOovqqqqiLGxMasecnFxIZWVlRq5T548IYaGhoLqIbH6C1pbNWLECPKzn/2MeHh4kJqaGo3c7Oxspqe0ekhMT1NTU1n10C9+8Qvi5eUlqqcJCQlMT9944w3i6+srqqe3bt2SXT0UEREhqB6S0tPg4GCBnopVDxFCiK+vL9PTd999V1JP3d3d1aqHNNVfEELI6dOnCQBibW1N/vjHP4pWDxFCyOHDh9Wqh8T09JtvvpGtp59//jkBQKZMmUL+/Oc/k5iYGFE9/fvf/04AkGnTppG//OUv5ObNm6J6unv3bkH10J07d0T19He/+x0BQGbNmiVZPUQIIW+++aagekhKT1999VVZVW6EEOLg4MCqh2iVmxh38+bNTE+lqoeUSiVZs2aNoMpNrHpIqVSSJUuWyKoeGhwcJHPnzpVV5UZrq/jVQ2JVbr29vcTe3l6gp2LVQ7S2ysDAgFUPiVW5tbe3k7Fjx7Iqt2PHjolWudHaKn71kJie0toqvp6K1V9UV1cTExMTYmJiQhwcHCSr3MrLywV6KlU9VFRURPT19WVVueXm5hI9PT1Z1UPp6emyq9xobRW/ekisyu3OnTtqeiqmvZGRkYLqIakqt8uXLwuq3AIDA0X11N/fX1aVGyGEnD9/XqCnly9fFtXTM2fOMD2VqnIjhJCjR48K9FSseogQQvbt2yeryo0QQv7973+zKjep6iFCCPn4449lVQ/9NwCZ9S261FweEhISWFmvh4eHoFxYT08Pq1atYsWz/ELsc+fOCcra+QXWHMehurqalfU6OzsLCoP19fXx8ssvs+s+efKElfWePHlSUMBOC6xpoW1hYSHS09NBCMGxY8cEBez8AmuO45CTk4OsrCwMDQ3h6NGjGBgYYFwjIyNs3LiR/QxpaWnIy8vD4OAgjhw5Iihg5xdYcxyHxMREFBYWor+/H0eOHBEUsJuYmGDLli2Me/fuXZSUlKCnp4cValPwC6ydnJxw48YNlJeXo6OjgxVqU5iZmWHbtm3suuHh4aiurkZrayvOnDkj4I4cOZKVXTs5OSE0NBT19fVoamqCq6urgGtubs7Krh0dHXHp0iU0Nzejrq4O58+fF3BHjRrFyq537doFb29vtLW1oaqqipVkU1haWrKy6127dsHd3R1dXV0oLy+Hn5+fgEsLrDmOg4ODA86cOYP+/n6UlJQgMDBQwOUXWO/cuRPHjx+HUqlEYWEhQkNDBdxx48Yx7rZt29j7n5eXp1Zwzy+w3rRpE06cOAFAVXPyYsmytbU147788ss4ffo0ANX0+saNGwIuv8B6xYoVOHv2LABVFPzt27cFXDs7O8ZdvHgx+6zu37+vVkRPC6w5jsO8efPg4eEBAIiLi2P3HcW0adPYdWfMmIELFy4AUE2vXyyXpwXWtJrJx8cHgGp6/aKOzZw5k90/1tbW8Pf3B6CaXr9YGE8LrDmOw9ixY9nnevXqVeTl5Qm48+bNY9c1Nzdnn2toaCgKCwsF3IULF7J/m7GxMftcAwMDUVJSIuAuXryYXRcAKz/38/NDeXm5gLts2TJ23f7+flae7e3trVbsvmLFCnbdzs5O3Lx5E4DqxERdXZ2Ay9fT5uZm3L17FwDg6uoqKGvX09PDmjVr2HtWW1uLe/fuAQDOnDmD1tZWxtXX12faq1AoUF5ejgcPHoAQglOnTgkK2A0MDLBu3Tp23aKiIqSlpYEQguPHjwsK2A0MDJieKhQK5OXl4eHDh1AqlThy5IhATw0NDbFp0yZ23YcPHyInJ0ejnhoZGTE9VSgUSEpKQkFBgUY9NTY2xtatW9lnERcXh+LiYvT29uLo0aOC99bU1BRbt24VlKqXlZWhq6uL3c8UZmZmTHs5jsP169fx9OlTtLW1wdnZWcAdMWIEtm/fznQ6LCwMtbW1aG5uxrlz5wTckSNHMj11cnJCQEAAmpqaUF9fz+5RCgsLC4Ge+vr6orW1FdXV1fDy8hJwR40aJdDT8+fPo7OzExUVFbh48aKAO3r0aOzatQsKhQIODg5wcXFBb28vSktLERAQIOCOGTNGwD158iQGBwfx+PFjhISECLhUTzmOw86dO3HkyBEAqpqTFwvux48fzzRy8+bN7P3Pzs5m9x0F1VOO47B+/Xr2uy8jI0OttH7SpEnsu7Bq1Sr2uy8lJYU9x1DY2toy7tKlS9lnlZiYyO47ismTJzPu/Pnz4e6uWmjEx8ez+45i6tSpjDtz5kymp3fu3MGDBw8E3OnTp7PvOV9Pb9y4gbS0NAF35syZ7Lo2Njbs92RkZCQyMzMF3NmzZ7Prjhs3jn2u4eHhyM3NFXDnzp3LuJaWlggODgag2gYWFBQIuAsWLGD3hKmpKftcg4KCUFxcLOAuWrSIXVdfXx8REREAVKfVysrKBNylS5ey6w4ODiIqKgqAasP39OlTAXf58uXsut3d3ex3qqenJ2prawXcVatWsfestbUVd+7cAQC4ubmhsbGR8fT09LB69Wp23bq6OiQkJAAAzp49i5aWFsalekqvW1lZiaSkJBBCcPr0aXR0dAi4VE8VCgWKi4uRmpoqqqfr169n3Pz8fGRkZECpVOLo0aPo7+9nXENDQ8HzaWZmJrKzszE0NIQjR45gcHCQcY2MjJj2KhQKJCcnIz8/HwMDAzhy5AiUSiXjGhsbC55PExISUFRUpFFPTUxMBHp6+/ZtPHnyRKOempqasudTJycnREVFobKyEu3t7ez5iGLEiBEC7tWrV1FTU4Nnz57BxcVFwKV6Sp9lg4OD0dDQgIaGBnaPUpibmzM9lVO/+ENBbmqubiPKA92+yXnRQnk5L1qW/L+FO5x/23C4Y8aMkc21srKSzbW0tJTNHTVqlCyenp4eK6PW9qKbIblcU1NTWVwDAwNiZGQki2toaEj09fVlc+W+X3L//4CqdF4uV+57AIAVfct5yf0cANWGTi7XwsLiB+HK/T4CYEXqcl7DuX+Gc18Oh/tD6chPQSN/Ctr7Q+npcL5ncrVXT09P9n2hp6cn+94crp4aGxvL4hoaGhIDAwNZ3OFo5HC4cn9WYHh6OhzuD6Wncn+3Aj+cng7nueGnoL06PR0+96fwLPtT0NNf/epXotv4HxKQuRGVPjT+/xkWLFiAt99+GwAQHR0tmMoDqo0OnYh0dnaySda1a9cEU3lAtdGhU5mmpiY2oQwPD0d7e7uASzc6CoUCNTU1bEJ5+fJldHd3C7jTpk1j3LKyMjahDA4ORl9fn4BLNzoKhQKPHz9mm4GgoCDBBB8AZs2axbjZ2dls0xoQECCY4AOqqSKdkKWkpCAnJwdDQ0MICAgQTPABYP78+ey6CQkJyM/Px+DgoNo0GlBtdCj39u3bKCoqQl9fH5ta8rFkyRL2WURGRqKsrAw9PT1qm0BAtdGh1718+TKqqqrQ2dmpNrkGgJUrV7LrXrp0CfX19WhtbVWbXL+4Iff09ERLSwuePXuGyMhINS5/quji4oLOzk40NDSobQ1f3JAfP34cfX19qK2tVdsa8jc6CoUCBw8exNDQEKqrqxEbGyvg8jfkTk5O2LdvHwCgsrIS8fHxAi6dKnIchx07duDAgQMAgCdPniAxMVGNS6eKmzdvxuHDhwGo/EcvbhjpRkehUGD9+vVs6lhYWKg2EedvyFetWsWmjo8ePcLDhw8FXP6GfOnSpWzqmJubq7aNHDFiBNvSLFiwgG0RsrKy1Kbn/A357Nmz2RYhPT1dbXpuYWEBBwcHcByHadOmsY1PSkoKioqKBFz+htzW1pZtEZKSklBaWirg8jc648ePh6+vLwCVr+nFzSV/Q25pacm2svHx8aisrBRwx40bxzYvZmZmCAoKAqDaZNTU1Ai4/A25gYEBu8du3rwpODUCABMnTmTf88HBQYSHhwMQ11PK7erqYvfN9evXBVN5QLghb2lpYfeNNj2tra1l98KVK1cEG1FAtdGhXP69EBISIjhhAgg35MXFxWwzoElP+Rvy3NxctmnVpKdz5sxh/7b09HRkZWVBqVTi0qVLanrK35AnJiaykytSespxHGJjY/H48WP09/ezz5oP/oY8OjoapaWlknpKf17q6RXTU/6GPCAgAHV1dWhra2MbIz74eurt7Y3m5mZRPaUbcoVCAVdXV7S3t6OxsRExMTEC7osb8lOnTqGnpwd1dXVqW0N9fX22peE4DocPH8bg4KBGPX1xQ753714AmvWUbsjp9pTqaVlZmdqJDf6GfOvWrTh06BAAoKSkRG3DKKanjx8/RmpqqoBrYmLC9HTt2rXsRAzdRPFB9ZTjOKxYsQInT54EIK6ndEO+aNEitkHXpKf8DfmcOXOYnmZkZCA/P1/A5W/Ip0+fzjY+qampePz4sYDL35Db29vD09MTgOqkzYubS76eTpw4kZ1eun//vtrm0srKiumplZUV28pq0tOxY8cyPR05ciQ75RIbG4vq6moBl78hNzQ0ZPfYrVu31E6N8PVUqVSyeywmJkaw5QSEG/Le3l72zBIZGYlnz54JuLa2tux73t7ezrbtERERghN7AGBvb8++5w0NDew5RJOeTpkyhXGfPn3K7oXQ0FDBRhQQbshLSkqQmJgIQgiCg4MFG1EAmDFjhmB7mpKSAkIIAgMDBRtRQLghf/jwITu5EhAQINiIAsINeXJyMnuWvXTpEl4Ef0MeHx+PgoICDAwMqJ1UA4Qb8hs3bqCkpAS9vb1qJysA1Yacfm4RERGoqKhAV1cXwsLC1Lj8DXlwcDBqamrQ3t7Ofs/yQfWU4zgsXrz4J+cfFUDOX6vf1+unvhGlKCkpYdNQ6nHLyMjQ6HF49OgR0dPTIwDIqlWryN69e0U9bg8fPmQTijVr1pD9+/eTnJwcjdwHDx4QQDXxXbduHTl48KCox+3u3buMu2HDBnL48GFSUFCgkUu9pwYGBmTz5s2SHjfqPaUetxMnToh63AICAgigmvhu375d0uPm5eVFANXEd+fOneTMmTOiHjfqPZXjcaPeU1NTU8JxHHFzcxP1uNHtt5mZmVaP25dffkkAeZ7hf/7znwR47nGT8gxT7ynfMyzmyaDeU0tLS+YZFvO4Ue+plZWVVs8w9Z7yPcNingyFQkEAeZ7h7du3E0DoGdbkyeB7T6nHLTw8XKMng+891eYZ5ntPtXncqPcUUHncpDzD/f39ZOrUqQR47nET8wz39PQQW1tbAjz3DIt53Kj3FFB53KQ8w9R7Cmj3DFPvKaDdM1xXV8e2z9o8w0+fPmUbG22e4dLSUraFX758Ofnqq69EPcMFBQVss6/NM0y9p3I8w9R7KsczHB8fL9BTKc/wzZs3mZ5Sz7CYx416T6nHTcozTL2ncjzD1Hsqx+NGvadUT6U8bqdOnWJ6qs0zfOjQIYGeSnncqPd0xIgRzDMs5nGj3lO+Z1jM40a9pxYWFswzLKan77//vkBPpTzDv/3tb5meUs+wmMeNek+px03KM0y9p+PGjSPvvvuupMeNek/leIap91SbZ1ipVJLVq1cTQOgZ1uRx43tP7ezsyO7du0U9btR7Cqg8blKeYeo9BZ573MQ8w9R7Cmj3DFPvKQAyc+ZMSc9we3s723Bp8ww/e/aMbV3nz59PPv30U1HPcENDA9soU89wUlKSRi71ngIgixcvlvQMU+8poN0z/PjxY6an2jzDubm5TCOpZzgrK0sjl3pP5XiG79+/z/R0/fr15ODBg6KeYeo9leMZpt5TAwMDrZ7h0NBQpr3UM1xSUqKR6+fnx7R3x44d5PTp0+TJkycaudR7amxszDzDYs+y1HtqYmJCHB0dJT3D1HsqxzNMvadyPMM/NqDbiP7PkZKSAhcXF3AcBxsbG0lueno6PDw84OTkBGtra0luZmYmvLy84OjoiAkTJkhys7Oz4ePjA0dHR4wbN06S++jRI1y8eBG7du3SmhhYWFiIS5cuwcHBQWsKIPUl7ty5U2sKYEVFBUJCQrBjxw7JZD9CCKqrq3H58mVs375dMtmPEIKGhgZcvXoV27Ztk0zrUyqVaGlpQUREBF555RXJtL6hoSG2gdmyZYtkWt/AwAAGBwcRHR2NzZs3Sybw9fX1wcDAADdv3sTGjRslE/h6enowYsQI3L59Gxs2bJBM4Ovs7ISVlRViY2Oxfv16yVS91tZW2NjYID4+Hi+//LJkUl5TUxOmT5+Oe/fuYe3atZLpd3tPvcIAACAASURBVHV1dVi4cCE+//xzrFq1SpL79OlTrFq1Cnv37sXKlSslE+3KysqwZcsWHD9+HMuWLZPkFhUVwcnJCa6urli6dKnkhC8/Px9vvPEGfH19sWjRIkludnY23nnnHbYlleI+fPgQ77//PhQKBebOnSvJTU9Px1//+le2UZXipqam4tNPPwXHcZg1a5YoD1BN+r/88ksoFAq89NJLWrn79u2DQqHAtGnTtHKPHDnCPLHauCdPngTHcbC3t5fkpqam4uzZs3BycoKtra0kNy0tDW5ubnBycsKkSZMkuRkZGbhw4QIcHR0xceJESW5WVha8vb1l+WXy8vJk62lBQQH8/f3h4OCgNYG1uLhYtp6WlZUhODgYO3fulJVSHRoaih07dmjV07q6Oly5cgXbtm2TTEolhODZs2ey9bSjowPXr1/H1q1bJfV0cHAQfX19iIqKwpYtWyT1lG5Fbty4gU2bNknqaW9vL0xMTHDr1i1s3LhRq56OHj1alp62tbVh4sSJiIuLw7p16yT1tLm5GVOnTpWlp/X19Zg7dy4++eQTrF69WpJbXV2N5cuX46uvvsKqVaskNbK8vBwbNmzA4cOHsXz5cklucXExdu3aBRcXF1l6+tprr8HLy0vrdiU3NxdvvfUWFAoFFi5cKMnNzMzEH//4RygUCsybN0+Sm5GRgQ8++IBtVLXp6ccffwyFQiFLT//9739DoVDlBmjj7t27FxzHYfr06ZLcBw8e4NChQ+A4DlOnTtV63RMnTsDJyQmTJ0/Wyj1z5gw4jvte9TQ9PR2enp5wcnLSqqfDeZbNzc2Fr68vdu3apfVZNj8/H35+fti1a5dWPS0qKkJAQAAcHBy06umTJ08QFBSEnTt3ak2pHo6e1tbWIiwsDNu3b9eqp01NTQgPD8crr7yi9Vm2ra0N165dw9atW7Vqb09PDyIjI7F161atCdE/VejCinTQQQcddNBBBx100EEHHXT4XiA3rEi6fEcHHXTQQQcddNBBBx100EEHHb5n6P4Q1UEHHXTQQQcddNBBBx100OFHhe4PUR100EEHHXTQQQcddNBBBx1+VBh8/fXXP9r/zN3d/es//elPP9r/73+KsLAwPH78GPb29pKhB4CqNqW0tBT29vaSoQcAEBAQgMrKSlncixcvoqamBvb29pIBCYCqWL6+vl4W19PTE8+ePYOdnZ1kQAKgKkJub2+XxXVxcUF3dzfs7OwkAxIIIXB2dkZ/fz9sbW21ck+dOgWlUgkbGxtJrlKpxPHjx6Gvrw8bGxvJIIOhoSEcP34cRkZGmDRpkiR3YGAAx48fh6mpqVZuX18fjh8/jpEjR2LixImS3O7ubpw4cQIWFhaYMGGCJLejowOnTp2CpaUlxo8fL8ltbW2Fs7MzxowZg3Hjxklym5qacO7cOYwbN05rKEttbS3Onz+P8ePHaw0RqKyshLe3NyZMmKA1EOvJkyfw9/fHxIkTtQYOPH78GMHBwbC2ttYaOECL5SdNmqQ17CUrKwvXrl2DjY2NZDgBoAp0iImJgY2NjWQ4AaAKq7hz5w5sbW0lwwkAVR1LQkICbG1tJcMJAODu3btISkqCnZ2dZDAMoKoESEtLg52dndYgg+joaGRmZsriXrt2Dbm5ubC3t5cMkQFUMf+FhYWy9DQ0NBTFxcWyuIGBgSgvL5elp35+fqiqqpKlkT4+PsPS0+bmZtjb22vVSHd3d7S1tcnS03PnzqGrqwu2trZauc7Ozujr65Otp0NDQ7K4tDJJm/ZSPTU0NNSqkYODgzh27BhMTExgbW0tye3v78exY8cwYsQIrdyenh6cOHEC5ubmWrW3s7NTtp62tbXB2dkZVlZWWvW0ubkZ586dw9ixY7WGstTX18Pd3V2W9lZVVcHLy0uW9paVlcHPz0+WnhYXFyMoKAgTJ07Uqqf5+fm4fPkyrK2tteppdnY2IiIiMGnSJK16mpGRgejoaFl6mpKSglu3bsnS08TERMTFxcnS07i4ONy/f18W9/bt20hJSZGlvTExMcjIyIC9vb1WPY2MjEROTg7s7Oy06unVq1eRn58vSyMvX74sW0+DgoJQVlYmS0/9/f3x9OlTWVxfX1/U1tbCzs5Oq55euHABjY2NsrgeHh5obW2VraednZ2yuGfOnEFvb68sjTx9+jQGBwdlcWkNktxnWQMDA63PsoODgzh+/DiMjY21auR/A998803t119/7a6VKCda9/t6/W+pb6Ex1vyIe7HKkLS0NNkR9/fu3VOLZBarDLl9+zarDNEWcX/9+nUWcf/aa69JRtzTGOtRo0aRN954g/j4+IhG3NMYa0tLS/KrX/1KMuLew8NDEHF/6dIl0Yh7Z2dn2RH3R44cYRH377zzjmTE/d69e2VH3H/xxReyIu4JIeSjjz5Si7jXFFtPCCF79uxhEffvv/8+iYyM1FgZQgghv//972VF3BNCyG9+8xtWGSIVcU8IIa+99pog4v727dsaY+sJIcTR0VFWxD0hhGzZskUQcR8fH68x4l6pVJK1a9cSAGTevHmSEfdKpZIsXbqURdx//vnnohH3Q0NDZN68ebIi7gcGBsiMGTMIALJ06VLy5Zdfikbc9/X1kcmTJ8uKuKe1ADTifu/evaIR9x0dHWTs2LGyIu5bWlqIpaWloK5JLOK+sbGRjBw5UhBxL1bXVFNTQ0xNTVldk1TEfUVFBTEyMpIVcV9cXEwMDAxYXdPp06dFK0Py8vKInp4ei7g/c+aMaGUIrbgyNTXVGnGflJTE9JTWNYlF3NOKKzkR91FRUQI9vXDhgqiehoWFscqQ119/XVJPL126pFbX1NTUpJF74cIFAqjK0H/9619L6qmLiwvT07feeosEBgaK6unx48dl6+n+/fsFdU2XL18W1dP//Oc/TE//8Ic/kCtXrojq6SeffEIAkEmTJpH33nuPREREaKwMIYSQDz/8UFZdEyGEvPfee0xP9+zZQ6Kjo0W19+233xZUhojVNRFCyOuvv04AkOnTp5O//vWv5Pbt26Lay3Ec09O///3vJDY2VlRPt23bRgCQ2bNnk48//lhST9evXy+oa7p3756onq5YsYIAIAsWLNCqpwsWLBDUNSUnJ4vq6axZswR6KlbX1NfXxyqutNXf9fT0EBsbG1Z/J1XX1NnZScaPHy+r/q61tZVYWVnJqr9ramoi5ubmsurvamtriZmZmaz6u8rKSmJsbCyovxPT09LSUqantK5JrDKkoKCA6am2+rusrCzZ9XfJycmy6+/i4uKYnmqrv7tx44ag/s7T01O0/i48PFx2/V1QUJBsPfX29mZ6SuvvxPTU1dVVdv3dyZMn1ervxPT04MGDTE/fffddyfq7r7/+Wq3+TkxPP/vsM6antP5OTE9/bEBmfYsuNZeH2NhYVuzr6+uLhoYGwX+npd8cx6GlpQV37twBoJrivFgYvHTpUlY8W1dXx4p93d3d1QrYaek3x3GorKxkxb6urq7o6uoScPml30VFRUhNTQUhBGfPnhUUsNPSb1qUm5eXx4p9nZ2dBQXsL5Z+Z2RksGLf06dPCwrYDQwMsG7dOnbdpKQkVux7+vRpQQH7i6XfcXFxKCoqQm9vL86cOSP4dxkaGmLjxo2Me/PmTTx58gRdXV2s+JqCX/pNS4CfPn2K9vZ2VnxNYWxsjC1btjBuSEgI6urq8OzZM1y4cEHANTU1ZQXhHMfB398fTU1NaGhogK+vr4BrZmbGCsI5joOXlxdaW1tRU1OjVobML/2m9SNdXV2orKxEcHCwgMsv/XZycsLp06fR19eHsrIyXL58WcClpd8cx8HR0RFHjx6FUqlEcXGxWsExv/R7586dOHz4MABVnc/169cFXFr6zXEcXnnlFVaUnpubixs3bgi4Y8aMYQXhGzZsYFuUrKwsVnxNMXbsWFYQvmbNGpw+fRqAassYFxcn4PJLv5ctW4azZ88CUEXXv1gCP3HiRMZdtGgR+74kJiaqlcDzS79nz54NDw8PAKqS8rS0NAHX1taWcadPn86+L3fu3EFmZqaAO3nyZHAcx+pMfHx8AKiqJ14sdp86dSq77oQJE+Dv7w8AiIqKUit2p6XfHMdh9OjRCAoKAqAqHi8qKhJw+aXfI0aMYEXpYWFhePLkiYBLS785joOhoSGuXr0KAAgJCUFFRYWAyy/9HhoaYt+XgIAAtbL2BQsWsH9bT08PYmJiAKhOeNTX1wu4/NLv1tZW9n3x8vJCc3OzgMsv/W5oaGDfl/Pnz6O1tVXA5Zd+P336lH1fXF1d1QrYV61axa5bWlqK5ORkUT1dvXo1e88KCgqQnp6uUU/19PQEepqZmYns7GyNeqqvr49169ax6yYnJyM/P19UT9evX8+um5CQgMePH6Ovrw/Ozs6CfxfVU/pvu337NkpLS9Hd3Q0XFxcB18jICJs2bWLXvX79OiorKyX1lF43LCwMNTU1aGlpgaenp4BrYmIi0NPAwEA0NDSgsbGR3R8Upqam2LZtG7uHfHx80NLSgrq6Ovj5+Qm4I0aMwLZt25hGenh4oKOjA1VVVWrl8lRPOY6Dk5MT23aUl5ez+4PC3NwcO3fuhEKhgKOjI44fP47BwUGUlJSw+4Ni1KhRAu7BgwcBiOsp1V6+nj569Ig9b1BYWVkxPd24cSPT0+zsbNy6dUvApXrKcRzWrl3L9DQjIwN3794VcMePH8+0d8WKFez3b0pKCu7duyfgUj3lOA6LFy9mepqUlISkpCQBd9KkSUx7582bBzc3NwBAQkICUlNTBVwbGxv2vZkxYwb7vsTGxuLhw4cCrr29PeNOnjwZ3t7eAFQnPLKzswXcKVOmMK61tTX7vkRHR+PRo0cC7rRp09j3fMyYMQgICACgOuHx+PFjAXfGjBnsuubm5ggJCQGgOuFRWloq4M6aNYt9z42NjXHlyhUAqhMe5eXlAu6cOXPYz6BUKtn3JTAwEFVVVQLu/Pnz2XX7+vrY98XPzw91dXUC7sKFC9l1Ozo6cPPmTQCqEx6NjY0C7pIlS9h1m5qa2PfF09MTLS0tAu6yZcvYdWtqapCQkABAdWKuo6NDwF25ciV7z8rKyvDgwQMQQuDi4oKenh7G09PTEzzLFhYWIi0tTXBijs9du3Ytu252djaysrKgVCrZRpJCX18fL7/8Mrtuamoq8vLyMDg4iNOnT0OpVDIu1VN63cTERBQUFKC/v5/dSxSGhobsWZbjOMTGxqKkpAQ9PT3s2YTCyMhI8CwbHR2N8vJydHZ2wtXVVcA1NjZmz7Icx+Hq1auorq5Ga2srzp8/L+CamJiwZ1mO4xAcHIz6+no0NzfDy8tLwDU1NWXPp05OTrCzs8N/A3JTc3UbUR4OHDhAAMh60QJkOa+xY8fquP9vwvRDcC0tLWVzaRm1nJe5ublsLi2ulvMyNTWVxdPT0yNGRkayuPr6+qy4Wg5X7s9qYGAgm0tLtuW8jI2NfxCu3PcWUG3SfojPd+TIkbK5FhYWsrnD+e4O554YPXq0bO4PdQ/r9HT478NwuMP5LIbzfRjOd3I43/UfSk/laom+vr5s7RuORv5Qeir39wTww+npcLg/lJ4O53e2Tk9Vr5+C7v0UuD8FPR3O92w4evrLX/5S9GTRDwnI3IhKH8L+/wyLFy/Ge++9B0A19WpqahL8d7qdUCgUaGtrY9P+0NBQtSkSfzvR2NjIpv1BQUFqG1H+dqK6uppN+y9duqS2EeVvJ0pLS9n21M/PTzDBB1TbCf4EPyUlBYQQ+Pj4CCb4gHA7kZmZybanXl5egikSINxOpKSkICcnB4ODg/D29hZM8AHhdiI+Pp5NnF6ciAOqaRp/I1pSUoLe3l5cvHhRwONvJ+hGtKKiAl1dXWrbSLrtpT9vSEgIampq0N7ezrZLfC7dTigUCly8eBGNjY149uyZ2jbyxe0E3Yo3NjaqTc/5216O43Du3Dl0dHSgrq4O165dE3D52wmO43DixAn09fWhuroaUVFRAi5/28txHA4ePIihoSFUVFSwaSgFfzvh6OiI/fv3A1B5NOlmn4K/ndi+fTub9hcXF6ttLs3MzNi2d/PmzWzTWlBQoLa5HDlyJOOuW7cOx44dAwDk5eWpbS7524kVK1bg1KlTAFSbgRcn7XTby3EclixZwrZDDx8+REZGhoBraWnJNg7z5s1j26G0tDRkZWUJuPztxMyZM9m0/8GDB8jLyxNw+dveKVOmsGnm/fv3UVBQIOCOGzeObRFsbGzYNDM+Pl5tyzlhwgT23R0zZgyb9sfGxqpN5a2trRnXwsKCTftv3ryptuW0sbFh3xtTU1O2mY+OjlabytvZ2bHvuZ6eHsLCwgAA169fR21trYA7efJkxh0YGEBERAQAla/pxak8fzvR0dHBpv2XL19WO2FC9ZTjODQ3N7PtUHBwMNra2gRcup2gE3w67Q8ICFDbiM6dO1cwwb9//76ontLtBJ3g0+2pJj3lbydycnLY9tTb21uwEQWE24m0tDS2PfXy8lLTU/524t69e2x7SjdGfFA95TgOd+7cQVFREfr6+tROd7y4nYiMjERZWRm6u7vZtp7P5etpWFgYqqqq0NHRobaNfHE7cenSJdTX16OlpUVtG8nXU47j4O3tjebmZjQ1NbHtEgV/O6FQKODq6or29nbU19ez7xsF1VP68546dQo9PT2oqalBZGSkGpevp4cPH8bg4CAqKyvVToIYGxsLtr379u0DoPJovngShL+d4OtpSUmJ2ubSzMyMbXu3bNnC9PTx48dsE0UxYsQIdnqGr6ePHj1S21yam5sz7urVq9mmNScnBykpKQKuhYUF09Nly5ax7VBmZiZePNFmaWnJtr0LFy5km9b09HS1UyP0pI1CoTqNQrdDycnJaqdGxowZw/R02rRp7ORKYmKi2qkRqqccx8HW1pbpKT0xwMeECROY9o4fP57dC5r0dOLEiex7Y2lpyZ4tbt26pbbl5G97zczM2LNFTEwMnj59KuDa2dkxrr6+PtPTyMhI1NTUCLhiehoeHq52Ym/q1KmM293dzb7fYWFhaidMXnrpJfbdbWlpYc8LISEhaidMZs6cya5bV1eH2NhYAKoN7osb0Tlz5rB/W0VFBdu2+/n5CTaiADBv3jx23eLiYiQlJYEQAl9fX8FGFHiupxzHIS8vj21Pvb29BRtR4PnJRYVCgfT0dGRlZWFoaAje3t5qz7LLli0TnO6j29MXN4zA85OLCoUCsbGxePz4seizLF9Po6Oj8eT/svfdUVWd6foPXUAU6dXeYsXesYvCPjN31kwmmTWZZCWTMZOZTGYmmYz5qYli7wU7KiI2sCAqRUSKNAHpvRfpAtKln+/3B/f7cjaHs/cmN8nNvfc8a+21krUeN4dzvv2cj/f9nvcpLkZHR4fS6Q56cpFy79+/j/LycrS1tbHvb4qBJxe9vb1RU1ODpqYm1q1X5Crq6ZQpU352/lEepPy1+kNdP/eOKEVubi7rMIn5tdLT0wnQX0EV82tRP6kUvxb1k1K/lpC/gPpJFf1aqvwF1E8qxV9w584dAvT7C8T8WteuXSPAd/5XIb8W9ZNK8WtRPyn1Fwj5taifVIpfa9euXQSQ5i/YunUrq2yJ+bW++OILVjGjfi1V/gLqJzU1NSXvv/++oL+A+kkV/Vqq/AXUTyrFX/CrX/2KANL8Wps2bSJAv1/rz3/+s6Bfi/pJ7e3tBf1ain7SMWPGkM8++0ylX0vRTyrm11L0k06cOFHQr9XT00MmTJhAAHG/VldXF7G3tyeAuF+L+kmB7/xaMTExg3KpnxQQ92tRPykg7td69eoV6yiI+bWonxTo92vt3r1bpV+rtLSU6OjoSPJrUT8p1dP9+/er9GtRP6kUvxb1k2ppaZGVK1cK+rViYmKYnlK/VkFBwaDcsLAwpqfUr1VUVDQol/pJpegp9ZNK8WtRP6kUvxb1k+rr64v6tc6cOaOkp6r8WkePHiWANL8W9ZNSPfXy8lKpvdRPOnLkSObXUjV7gPpJ6ewBIb/WZ599xvSU+rVUeWU//vhjAvR7ZcX8Wu+99x4B+mcPUD1V5ZWlflI6e+DBgwcqtZf6SW1sbET9r9RPamdnRz799FMSGBioUk+XLVsmWU/nzZtHgP7ZA59//jkJCQlRqafUT0r1NDQ0VKWeUj/p5MmTyZdffkkiIiJU6in1k7711lvkq6++IpGRkYNyFf2k06dPJ19//bVKPW1rayNmZmZMT7du3UqeP38+qEY2NTWxrpWDgwP55ptvVOop9ZMCIHPnziU7duwgiYmJgn5SAGTBggWC/lfqJ6WzB/bs2UPS0tIG5RYWFhItLS2ioaFBli5dKqin2dnZTE+XL19ODh48SLKzswflpqSkKOlpbm6uEo+Q7/yk2traZPXq1eTYsWMq9ZT6SamenjhxQqWeUj+pjo4O2bBhAzl16pTK2QN+fn48PT1z5ozK2QPe3t5MT8VmuVA/qeIsF1V7WeonNTAwEJ3lQv2kUma50NOZRkZG5O233xbU0x07djA9FZvl8lMD6o7o90dqaio8PT2xadMm0el36enpuH79OjZt2iQ60S4rKwu3bt2Ck5OT6DTRvLw8+Pj4wMnJSXSiXWFhIe7cuYMNGzaITrQrKyuDr68v1q9fLzqlrrKyEn5+fli3bp3olLpXr17h0aNHWLNmjeDkOUIIXr9+jYCAAKxevVpw8hwhBG1tbXj8+DFWrlwpOHlOLpejq6sLT548wcqVKwUnxNGORGhoKFasWCE49a2npwe6uroIDw/HsmXLBLldXV0wMjJCZGQklixZIjj1raOjA2ZmZoiOjsbixYsFJ7nRaW+xsbFYuHChILepqQmTJk1CfHw85s+fLzidrb6+HrNnz8bWrVsxd+5cQW5NTQ0WL16MvXv3wsHBQbC6Vl5ejjVr1uD48eOYNWuWILekpAQymQzu7u6YPn26IDc/Px/vvPMOrl+/jrfeekuQm52djQ8//FBSNTAjIwN/+ctfWOdTCKmpqfjyyy/BcRwmTJggyE1OTsbWrVvBcRzGjRsnyE1KSsKuXbvg4uKCMWPGCHITExNx4MABcBwn6v1ITEzE8ePH4eLiAhsbG1Hu6dOn4eLiAisrK0FucnIyLly4ABcXF1hYWAhyU1JS4OHhAWdnZ1E9TUtLg5eXFzZt2iQ6TTQzMxM3b97Exo0bRfU0NzcX3t7ecHJykjRNVKqeUu/2+vXrRSeEVlRUSNbTmpoaPHz4EGvXrhWd5FlfXw9/f3+sWbNGVE9bWloQFBSEVatWCeopIQQdHR0IDg7GypUrBSd59vX1oa+vD0+fPsWKFSsEtbe3txdaWloICwvD8uXLBfW0u7sbBgYGePbsGZYuXSqqpyYmJoiKisKSJUtE9dTGxkaSnjY3N2P8+PGIi4vDggULBDWyoaEBM2bMwJYtW0T1tLa2FgsWLICrqyvmzJkjqE+VlZVYuXIlDh8+jNmzZwtyS0tL4ezsjHPnzmHGjBmC3IKCArz99tu4evUqpk2bJsjNycnB+++/z7qZQtzMzExs3rwZMpkMkydPVskD+vdPf//738FxHCZOnCjITUlJwZYtW8BxHMaPHy/ITUpKws6dO8FxnCQ93bdvH/P3i3GPHj0KFxcX2Nrair4GNzc3uLi4wNraWpR7/vx5ODs7w9LSUpCbkpKCy5cvw9nZGebm5oLcoehpRkYGbty4gY0bN4ruZbOzs3Hr1i1s3LhRkp7evn0bGzZsEN3LFhcX4+7du9iwYYOonpaXl+P+/ftYt26d6F62uroaDx48wLp160T1tK6uTrKeNjU1ITAwEKtXrxbV0zdv3kjSU7lcjp6eHoSEhMDR0VFUTzU1NSXp6c8Z6mFFaqihhhpqqKGGGmqooYYaavwgkDqsSHXJTg011FBDDTXUUEMNNdRQQw01fgSo/xBVQw011FBDDTXUUEMNNdRQ4yeF+g9RNdRQQw011FBDDTXUUEMNNX5SaO3cufN7/2MNDY1SV1fXP7q6un7i6ur68c6dO92F+O7u7js3b978vX/eT4Xbt28jIyMDdnZ2ggZkoD9iJScnRxLXy8sLhYWFsLe3FzQrA4CHhwfKyspgZ2cnaFYGgIsXL6KyshL29vaiZuVz586htrZWEvf06dNoaGiAvb294KAIADhx4gSam5tFuYQQHDt2DG/evIGdnZ3goAhCCA4dOoTu7m5Rrlwux4EDByCXy2FnZyc4KKKvrw/79++HhoYGbG1tBbk9PT3Yv38/tLS0RLmdnZ3Yv38/9PT0YGNjIzjQ4c2bNzhw4AAMDAxgbW0tyG1tbcWhQ4cwfPhwUW5jYyOOHj0KIyMjWFlZCXLr6upw8uRJjBw5EhYWFoLc6upqnD59GqNGjYK5ubkgt6ysDO7u7jAxMYGZmZkgt7CwEB4eHjA1NRUdZJObm4tr167B3NxcdJhCRkYGvL29YWFhITrIJjk5Gffu3YOFhYXo4IX4+Hg8fPgQVlZWooMXYmJiEBQUBGtra9GhNxEREQgJCYGNjY3okIanT58iIiIC1tbWokMaHj9+jOjoaNjY2IgOyPH390dcXBxsbW1FBzrcv38fycnJsLOzExzoAPRHAqSnp0vi3rp1S7KeXrt2DQUFBbCzsxPVU09PT5SUlMDe3l5UTy9duoTy8nJJ3PPnz6OmpkayntbX10vS05MnTw5JT9vb22Fvby+qp4cPH0ZnZ6coVy6X4+DBg+jt7YWtra0gt6+vDwcOHAAh5AfV066uLuzfvx+6urqwsbER5HZ0dODAgQPQ19cX1ci2tjYcPHgQhoaGohrZ1NSEI0eOSNLT+vp6HD9+HCNHjoSlpaUgt6amBqdOnZKkp+Xl5Th//rwkPS0uLsbly5dhYmICU1NTQW5eXh68vLxgZmYmaTDYrVu3JGlvSkoK7t69C0tLS1E9ffHiBfz8/CTpaWxsLAICAmBlZSWqp5GRkQgODoa1tbWonoaF0TdhagAAIABJREFUhSEsLAw2NjaiehocHIyoqCjY2tqK6mlAQIBkPX3w4AESExMlce/du4e0tDRJeurj44OsrCzY29uL6umNGzeQn58vSU+vXr2K4uJiSRp5+fJlvHz5UhL3woULqK6ulqSnZ8+exatXryRx3dzc0NjYCDs7O1HtPX78OFpbW0W5hBAcOXIEnZ2dkvayBw8eRE9Pj+S9rBQ97e3txf79+6GpqSnK/e+Aq6trtdjfhQD+a/EtAEoBmEnl/0+Jb6ERAlJGU9MIARqzIjSaOjY2lo36FxtNTSME9PT0yMaNGwVHU9MIATqaWihmhUYIKI6mVjXqn0YISIlZoRECUkZTnz17lo36f/vttwVjVmiEgJTR1DRCQErMCo0QMDExIe+99x7x8fFROeqfRgiYmZmR999/n9y5c0dlzMrf/vY3Nur/ww8/JL6+vipH/dMIASsrK/LHP/6R+Pn5qRz1TyMEbGxsyObNmwVjVmiEgJ2dHfnzn/9MAgICBh31T8h3EQKjR48mf/3rX0lQUNCgo/4J+S5CYOzYseRvf/sbefLkyaCj/uVyOVm+fDkBQCZMmED+8Y9/kKdPnw466l8xQmDSpEnkiy++IOHh4YNyFSMEpk6dKhizohghMG3aNLJlyxYSHR096Kh/xQgBGrMSGxs7KFcxQmD27Nlk+/btJD4+ftBR/21tbcTc3JwXs/LixQvRCIH58+cTV1dXlTErihECNGYlNTVVMEJAQ0ODLFmyhOzbt09lzAqNEJASW1VUVES0tLSIlpaWaGwVjRCQEltFIwSkxFbRCAHF2CpVekojBBRjVlTpKY0QkBJb9eDBA6anNGZF1ah/GiEgRU9phICU2CoaISAltopGCEiJrTpw4IBkPd25cyfTUxpbpUpPt2zZwtNTodiqv//975Jjqz755BPJsVUffPCB5Niqd955h8VWicWs/OIXv2B6KhRbRQghGzZsYHoqFrPi6OjIi61SFbMil8vJwoULJcVW9fX1kdmzZ0uKrert7SVTp06VFFvV3d1Nxo0bJym2qrOzk9ja2kqKrWpvbycWFhZMT4ViVpqbm4mJiYmk2KqGhgYyYsQIpqdCMSu1tbXEwMBAUmxVRUUFi2QRi1kpLi4m2travNgqVTErNF5QSmwVjReUEltF4wUVY6tUxQBGRkZKjq0KCQmRHFv16NEjXmyVUMwKjRc0MDAQja2i8YJUTy9fvqwytorGC0qJrXJzc+PtZb28vFTq6aFDh5ieisVW0XhBKbFVNF5QMbZKlZ7+1IDE+Jb/0tRcDQ2NUgDzCSH1Uvg/96m5ISEhLDDY29sb9fX8X0sxrLe5uZmFAN+4cQONjY08rmJY76tXr1gIsJeXF1paWnjcGTNmMG5FRQUiIyNBCMGVK1fw5s0bHpeG9XIch6KiIjx//hyEEFy6dAldXV087pw5c9h9s7KyWKi6u7u7UggwDevlOA4pKSksBPjChQtKIcCKYb1xcXHIzMxET08PLly4wOPRsF76nj179gx5eXno6upiAdUUA8N6nzx5gqKiIrx58wYeHh5K3GXLljHuo0eP8PLlS7S2tiqFC2tpabHwc47jcO/ePVRVVaGxsVEprF1bW5sXfn7jxg3U1dWhvr5eKaxdR0cHq1atYq/Bw8MDjY2NqKmpUQpr19XVZUHpMpkM586dQ1tbG4tzUISenh4LP+c4DidOnEBXVxfKysrw6NEjHldfX5/HPXjwIORyOYqLixEYGMjjGhgYYP369eA4Ds7Ozti/fz+A/kgUuo4pDA0NWfj5unXrWKh6Tk4OQkNDeVwjIyM4OTmB4zisXLmShapnZGTg2bNnPO6IESNY+PnSpUtZqHpqaiqio6N5XGNjY8ZdsGABC1VPTExEXFwcj2tiYsKC0mfNmoWzZ88C6O9evnjxgsc1MzODs7MzOI7DtGnTWKh6TEyMUgC7ubk5Cz+fMGECLl26BKC/2p6ens7jWlpaMu7o0aNZIHZ4eDiysrJ4XGtra7bGrKysWKh6SEiIUgC7ra0t45qYmLBQ9aCgIKUAdnt7e7YWhg8fjtu3bwPo73QODGAfO3Ysu6+uri7u3bsHoL8yPzCAffz48ey+lAP0V+arq6t53IkTJ7J13tXVxULVfXx8UFdXx+NOmTKFvYbW1lYEBwcD6D9l8vr1ax73rbfeYvetr69n63AwPZ0+fTrjVlVVsXV45coVtLe387izZs1i3OLiYhaqfvnyZXR2dvK4c+bMYa83NzcXCQkJIITA3d0dPT09PO68efPYfdPS0pCcnIy+vj64u7uz+CiKBQsWMG5CQgIyMjLQ29uLCxcuQPH7WUNDA4sWLWKfRVRUFHJzc9Hd3Q13d37RWUNDg6enT58+RWFhITo6OnD58mUeV1FPOY5DQEAAysrK0NbWBk9PTx5XS0uLBaXTAPaKigo0NTUphbVra2vD0dGRvWfe3t6ora1FQ0ODUli7jo4OVq5cye7r6emJ169fo7a2VimsXVdXl6e9Fy5cQGtrK6qqquDr68vj6unpYc2aNex3O3XqFDo6OvDy5Uv2XU8xbNgwrFu3DhzHgeM4HDlyBL29vSgpKWHrmMLAwADr1q2DTCaDi4sL9u3bB6A/qoKuYwpDQ0OsX78eMpkM69evZ3qam5uLp0+f8rjDhw+Hk5MTZDIZVq1ahSNHjgDo70hGRETwuCNGjGDc5cuX49ixYwD6IzuioqJ4XEU9XbhwIU6ePAmgPzbk+fPnPO6oUaOYns6ZMwenT58GACQkJCAhIYHHNTU1ZXo6ffp0pqexsbFITk7mcc3NzeHs7MxisugeICoqCmlpaTyuhYUF09OxY8eyPYAqPaVcGxsbtgd4+vQpcnNzeVyqpxzHwczMjO0BgoODUVBQwOPa29uztTtixAi2BwgICEBJSQmPO2bMGMYdNmwY2wMMpqfjxo1ja1dDQ4PtAXx9fVFVVcXjTpgwgXF7enrg7+8PoP+USW1tLY87efJkxm1vb0dQUBCA/lMmDQ0NPO7UqVMZ9/Xr12wdXr9+HU1NTTwu1VOO41BbW4vw8HAA/adM2traeNyZM2ey+5aVlSE6OhqEEHh4eKCjo4PHdXBwYO9Zfn4+4uPjQQjBxYsX0d3dzePOnTuX3Tc9PR3JycmQy+W4cOGCSj3lOA5JSUlIS0tTqaeKe9mYmBhkZ2er3MsuWbKEvd7w8HDk5+ejs7OT7QsoNDU1sXTpUnbfwMBAlJaWor29ne0LKLS0tHh7Wbpempubce3aNR5XW1ub7WVlMhl8fHxQU1OD169fs30BhY6ODhwdHRlXLO7ox4LUqbn/1Y5oCYBkAEkANqvgbAaQCCBx9OjRP96f3j8AaIislItW26RcNKj+/zp3KO/ZqFGjJHNHjhwpmUsrn1Iu2nWSchkYGEjmDhs2TBJPQ0OD6OjoSOZqampK5kp9rVpaWpK52trakrlSfy+gv+r6Q7+3AFjY+A/9+Q5l3RgZGUnmDmXtDuWZoJ1YKddQnsuhcNV6OvT34cfS06Gsh6Gss6GsdUNDQ8ncoTzzUrWEdvClcKXq7lC5/9P0dCjcoejpUNbCULR3KHo6FO5Qnp8fS3vVejp07o+lvT8HPX333XdVdpZ/TEBiR1T4sLQ4lhFCqjQ0NCwAhGhoaOQSQiIVCYQQdwDuQH9H9L/4835UzJ8/H59//jmA/irSwAq+YpezsbERISEhAPq9SgM7orQyNFgVaWAFn3Y5ZTIZXr58iaioKFaVH9gRpZUhjuNQUFCAuLg4VpUf2BGlXU6ZTIbMzEzWET1//jyvI0orQ7Tak5yczDqi586d43VEaZeT3jc2NhZZWVno6enBuXPneD+fVobofSMiIlhHdGDFaWBl6PHjxyguLkZ7e7tSBV+xyymTyfDw4UO8fPkSLS0tShV82uWk79ndu3dZR3RgxUmxy8lxHOuI1tXVKVXwdXV1WaXdxcUFHh4eaGpqQk1NDetEUQzscip2RAdW8PX19XmVdtoRLS0tVarg0y4n5dKOaFFRkVIF39DQkHUuN27ciAMHDgDo9wkNrODTLqdMJsPatWtZBT87O1upgq/Y5XR0dGQd0fT0dKUKvrGxMau0L1myhHVEU1JSlCr4o0aNYtXzefPm4dSpUwD6PUUDK/impqasIj5r1iycOXMGABAXF6dUwVfsck6dOpWtw+joaKUKvqWlJVu7EyZMYBX8Z8+eKVXwFbuc9vb2rPIZGhqqVMG3tbVla8HS0pKtw+DgYKWOKO1yymQyGBsbs3UYGBiIwsJCHnfs2LHsvoaGhmwdPnz4UKkjSrucMpkM2trabB3ev39fqYKv2OUkhLCO6J07d5Q6olOmTGHczs5Otg5V6elgJ0yuX7+u1BFVPDWieMLk6tWraG5u5nEVu5z0hAnQ71Ua2BFVPDVSVFTEOqIXL15U6ogqdjlzcnJYR/T8+fNKHVFaaec4DqmpqUhJSVGpp7TLKZN9d8Kkt7cX586d41XwFU+NcByHyMhI5ObmDqqnA0+N0BMmHR0dSqdRqJ7SzyIgIAClpaVobW1VquDTLid9Db6+vqisrERTUxPr7FNQPaUdKNoRra+vV6rgK54a4TiO1xH18fHhcQd2OWlHtLKyknX2KWiXk2qkYkd04GkUfX19np7SjmhxcTHrRFEonhpxdnZmHdH8/Hw8fvyYx1Xscg48YUL3EBSq9DQjI4PtIShGjhzJ9HTgCRO65imonnIcx+uIJiYmIjY2lselXU6ZTIbZs2czPY2Pj0d8fDyPS/WUdkTpHiAmJgZJSUk8ruKpkYkTJwrqqZWVFVuPiidMwsLCkJmZyeMqnhqxtrZmHdGQkBDk5OTwuIpdTlNTU9YRDQoKUuqIjhkzhj0/RkZGrCPq7++P4uJiHlexy6mnp8c6on5+fnj58iWPS/WU4zheR5TuTRSh2OXs7u5m69DHx0epI0pPjXAch7a2NrYOb9y4odQRVTw1MvCEycCOKNVTjuNQXV3Nvtc9PDyUOqIODg7sviUlJYiJiWEn9gZ2ROfNm8c+i7y8PNYRvXDhglJHVPHUSHp6OpKSkiCXy3Hu3DleR5TqKb3vixcvkJ6ePqieDjw1Eh0djezsbHR3d7POPgXVU3rf0NBQFBQUqNRTemqE4zgEBQWhpKQEbW1tSqf7BnY56QmT5uZmpdN9iqdGOI5jHdGGhgal032Kp0Y4jsPYsWPxs4aUv1alXAB2AviXEOd/ikc0IyODdaPoWXlVvs+kpCQCSPN9xsTEEEDaWfnQ0FACfOf7FDorHxAQQID+Dg89K6/Kp3Tv3j0C9Fck/+M//kPwrPyNGzcI8N1ZeSHf5+XLl1mVhp6VV+VTOnPmDKv+vPvuu4K+zyNHjhBA2ln5PXv2sGqVmO9z+/btBOj3KX3wwQfk7t27Ks/V/+tf/yKANN/nZ599RoB+3+fHH39MHjx4oNKn9Mc//pEA3/k+Hz16pNKn9Pvf/54A/b7PTz/9lAQGBqr0Hv36178mwHe+z8ePH6v0fbq4uBAAZNy4ceTzzz9X6fskhJC1a9cS4DvfZ2hoqErf57JlywgAMnnyZPLll1+q9H3K5XIyd+5cAvT7Pr/66isSGRk5qE+pr6+PTJ8+nQAg06dPF/R99vT0kEmTJhEAZObMmWTr1q3k+fPnKj2iY8aMIYC477Ojo4NYW1sTAGTu3Llkx44dJDExUaVH1MzMjAAgCxYsIK6uriQ5OXlQ309jYyMxNjYmGhoaZNGiRWTPnj0kLS1tUG5dXR0ZPnw4z/eZkZGh0iM6bNgwoqmpSZYvX04OHjyo0vf58uVLoqOjw/N95ubmKvEIIaSwsJB5RKmPXpXvMysri3nuqY9ele+Teu51dHTIhg0bBH2fz58/Z9or5qMPDw9n2ivm+3z8+DHTU9l/+uhV6amfnx9PT4V8n7du3WJ6Kuajv3LlCtNTMd/nuXPnmJ5SH70qn9Lx48dZlV7M90lPCEnR0x07djA9FfPR//vf/+bpqZDv8/PPPydAv+9TzEe/efNmAkjzfb7//vsE6Pd9Uh+9Kt/nb3/7W56eCvk+ZTIZAfg+elXau379egJ85/t8+vSpSt/nihUrCCDuo5fL5WTBggUEEPd99vX1kVmzZhFA3Eff29tLpkyZQgBxH313dzfz3FM9VeX77OjoYB5RMR99W1sb84jOnz9f0PfZ3NzMOohiPvqGhgZiZGQkyUdfW1tL9PX1Jfnoy8vLmefe0dGRHDp0SKWPvqioiGhra/N89Kp8nzk5OURTU5Pn+1Slp2lpaUxPqY9ele8zISGB6amY7/PZs2dKeqpqL/vkyRO2l6U+elV72YcPHzI9/eUvfyno+7x9+zYB+D56VXtZLy8vJT1V5ft0d3cngDQf/cmTJ3l6KuT7PHjwINvLUh+9qr2sq6srAaT5Pv/f//t/BJDmo/+pgR+7I6qhoWEIQJMQ0vqf/70BwK7ve7+fE3JycuDj4wMnJyfR6Wx5eXm4e/cuNmzYIDqdrbi4GPfv38e6detEp7NRD8vatWtFp6hVVVXB398fa9asEZ2i9urVKwQGBmL16tWiU9QaGxsRHByMlStXik5Ra2trQ0hICBwdHQUnoxFC0NXVhbCwMCxfvlxw2hkhBHK5HBEREVi2bJngBDO5XA4dHR1ERUVhyZIlolMeDQ0NERMTg0WLFglye3p6YGJigufPn2PhwoWiU3Otra2RkJCAefPmCXLfvHmD8ePHIykpCXPmzBGdmjtt2jSkpKRg9uzZolNz582bh2+//RYzZ84UnZq7YsUKHDx4ENOmTROdmrthwwacOnUKU6dOFZ3y+Ktf/QoeHh6YPHmySh7Q/0y899578PHxwcSJEwW5+fn52Lx5MziOE/U85OTk4PPPP5dUDczKysKWLVvAcRzs7e0Fuenp6dixYwc4joOtra0gNy0tDfv374eLiwusra1FuUePHoWLiwssLS1FuadPn8amTZtgYWEhynV3d8emTZtEpxKnp6fjypUr2LRpk+hkzMzMTFy/fh0bN24UnYyZnZ0Nb29vODk5iU7GzM/Pl6ynRUVF8PX1xfr160X1tKysDA8ePMDatWtFp11WVFTg0aNHWLNmjaj21tbWStbT169f4/Hjx1i1apWonra2tkrW046ODoSGhmLFihWietrX14fw8HAsW7ZMkCuXy6GpqYnIyEgsWbJEUHv7+vqgr6+P6OhoLF68WFRPjY2NJelpV1cXLC0tER8fj/nz54tOzR0zZgwSExMxZ84cQW5bWxumTJmC5ORkODg4iE7NdXBwwLZt20T1tL6+HkuXLsW+ffswffp00am569atw8mTJ0X1tKKiAr/4xS9w8eJFTJkyRSUPAEpKSvC73/0ON27cwKRJkwS5BQUF+OijjyR5yHJzc/HZZ59J1tOvvvoKHMdh9OjRgtyMjAxs374dHMfBzs5OkJueno49e/bAxcUFNjY2gty0tDQcPnwYLi4usLKyEuSmpqbCzc0Nzs7OonqampqK8+fPw9nZWZKeenh4SNZTLy8vbNy4UXTKe3Z2Nm7duiVJT3Nzc3Hnzh1s2LBBdC9bUFAgWU9LS0vh5+eHdevWieppeXm55L1sTU0NAgICsHr1atG9bH19PYKCgrBq1SpR7aUnblauXCk6ube9vR1Pnz7FihUrRLW3p6dHkp4SQqChoYFnz55h6dKlontZPT09SXra29sLIyMjxMbGYuHChYLcnzO+97AiDQ2N8QDu/+f/agO4SQjZK/Rvfu7DitRQQw011FBDDTXUUEMNNdT4/pA6rOh7d0QJIcUAZn/ff6+GGmqooYYaaqihhhpqqKHG/038vNJP1VBDDTXUUEMNNdRQQw011PhfD/UfomqooYYaaqihhhpqqKGGGmr8pNDauXPnT/bD3N3dd27evPkn+3nfF1evXkVmZiZsbW1FzdWXL19Gbm4u7OzsRM3VFy5cQFFREezs7ETN1WfOnEFZWRns7e1FB1ucPHkSVVVVsLOzE+UePXoUr169gr29vahp++DBg3j9+jXs7e1Fjdj79+9HS0uLJO6ePXvw5s0b2Nvbiw7B2L17N7q7u2FnZyfI7e3thaurK/r6+mBnZydo2u7u7oarqysAiHI7Ojrg6uoKLS0t2NnZCQ7BaG9vx+7du6GrqwsbGxtBbnNzM/bu3Ythw4aJchsaGnDgwAEYGBjAxsZGcLBFbW0tDh8+jOHDh8Pa2lp0CMbx48dhZGQkyi0pKcHp06cxcuRIWFpaCnLz8/Nx/vx5GBsbw8LCQpCblZUFDw8PjBo1Cubm5oLc1NRUeHl5wcTEBGZmZoLcFy9ewNvbG2ZmZjA1NVXJA/rD1+/evQtzc3PRoRKRkZF48OABLCwsRIdKhIaGIjAwEJaWlqIDfR4/foyQkBBYWVmJDqDw9/dHeHg4rK2tRQdQ3L9/HzExMbC2thYd/nPnzh3Ex8fDxsZGdFjFzZs3kZSUBFtbW9FhFV5eXkhPT4ednZ2onnp4eCAnJwe2traieuru7o6CggJJenr27FmUlJRI4rq5uaGiokKS9h47dgw1NTWS9PTw4cNoaGiQpJEHDhxAc3OzJO7evXvR3t4uqqdyuRy7du1CV1eXJO11dXVFb28v7O3tRQcQubq6ghAiqqednZ1D1lMdHR3Y2toKcltaWrB7927o6emJchsbG7Fv3z5JelpXV4eDBw/C0NBQVCOrqqpw9OhRGBkZwcrKSpBbVlYGNzc3jBgxQpRbUFAgWU+zs7Nx6dIlSXqanp6Oq1evYtSoUaJ6mpSUhJs3b8LU1FR0SE9cXBzu3LkjSU+joqLg5+cnSU/DwsLg7+8vSU+Dg4Px5MkTWFpaiuppQEAAwsLCYGVlJaqnDx48QFRUFGxsbET19O7du3j+/LkkPfX29kZiYiJsbGxE9fTatWtIS0uTtD+9cuUKsrOzJe1PL168iPz8fEncc+fOobi4GPb29qJ6eurUKZSXl0van544cQLV1dWS9PTIkSOoq6sT5VI9bWpqkqSn+/btQ1tbmyQ93b17Nzo6OiTp6a5du9DT0yNZT+VyuSi3q6sLrq6u0NTUhK2t7c9uWJGrq2v1zp073UWJUkbr/lDX/5T4FhohoBh5kJ2dPejY7djYWAKAaGlpkZUrV5IjR46ojDygEQLa2tos8qCgoGBQblBQEBu7LRYhc//+faUIGVVjt2/evCk5QsbDw0NyhMzZs2d5ETLu7u4qx24fO3aMjd0Wi5DZt2+fUoSMqrHb3377LRu7TSNkVI3d/uqrr5QiD1SN3f7b3/6mFCGjKvLgT3/6k+TIgz/84Q9KETKqxm6//fbbkiNkOI7jRcgIRR6sW7dOKUJmsBgDuVxOli9fTgAQe3t78umnn5KAgIBBYwzkcjn5z8xgMmbMGMEImb6+PjJz5kxJETK9vb1k8uTJkiJkurq6WITA5MmTBSMPOjo6iI2NjaQImba2NmJubi4pQqapqYlFCIhFyNTX17OAagcHB8EImZqaGqKvr8+LkFEVefDy5UsWYD9//nzBCJmioiKipaXFi5BRFXmQk5NDNDQ0JEXIpKam8vRUKPIgPj6e6alYhExERARPT48ePaoyQiY4OJhxaYSMKj198OCBUuSBqggZHx8fpqdiETJXr17l6alQhMyFCxckR8icOHGCF3kgFCFz4MAByREyO3fulBwh8/XXX/P0VCjy4B//+IfkCJk///nPPD319vZWqacffPCB5AiZd955h+kpjTxQpae//OUvmZ6KRcg4OTkxPRWLkFm5ciWL5BKKkJHL5WThwoUsQuYvf/mLygiZvr4+Mnv2bF6ETHBw8KDa29vbS6ZOnSopQqa7u5uMHz+eFyETFhY2qJ52dnYSOzs7SREy7e3txNLSkhchExUVNahGNjc3ExMTE0kRMg0NDWTEiBEsQmbbtm0qI2Rqa2uJgYGBpAiZiooKoqenJylCpqSkhGhra0uKkMnLyyOamppMT/fu3asyQiY9PZ3pKY2QyczMHJT74sULxl2xYoVghExUVBTTXrEImadPnzI9FYuQ8ff3lxwhc+fOHckRMteuXeNFyAjtZS9evMj0lEbIqNLTU6dOKUXIqNLTw4cPK0XIqNLT3bt38/TU09NT5V5269atkiNkvvjiC6an7777Lrlx44ZKPf2pAYnxLd97au73wc99am5QUBALdr9z545SUPqECRNYQGxzczOCgoIA9FezBgb7Tpo0iYXU1tbW4unTpwD6w4UHBvtOnTqV3be8vBwREREghODatWtKwb7Tpk1j9y0sLER0dDQIIfD09OQF+wLAzJkzWQBvVlYW4uPj0dfXB09PTwz83GfPns3um5SUhOTkZPT09CiF6gL8EPjnz58jPT0dXV1duHbtmhJ3/vz5jBseHo6cnBy8efNGKdBcQ0MDCxcuZK83ODgYBQUFaG1tVQo019DQwOLFi9l9/fz8UFZWhqamJhYkTaEYAi+TyeDj44OqqirU19crBZpraWmxEHiO43Dt2jW8evUKtbW1ePTokRJXMYj40qVLeP36NaqqqhAYGMjjamtr84KIz5w5g9bWVpSXlyM4OJjHpSHw9L5HjhxBV1cXSktL2Rqi0NXVxZo1a9h7tm/fPvT19aGwsJCFTlMMGzaMhcA7Oztj9+7dAPrjh6KionhcfX19rF27FjKZDOvXr2dh7dnZ2Urh5wYGBiwEftWqVThw4ACA/rH8A8PPhw8fjg0bNoDjOCxbtgyHDx8G0N/pHKgLRkZGLAR+wYIFOHbsGID+APbU1FQeVzEE3sHBgYW1x8fHIyMjg8c1NjZmIfDTpk3D6dOnAfR3RbOzs3lcExMTxp00aRILa4+KikJeXh6Pa2ZmxkLgR48ezUKuw8PDUVRUxOPSEHgawE5Drp8+fYrS0lIe18rKigXGm5qawsvLC0B/xb+8vJzHtba2Zmth+PDh7BkLDAxUCkpXDIHX1dXF7du3AQAPHz4lBqhbAAAgAElEQVTEq1eveNzRo0czLgDcu3cPQH+3dWBQ+tixY9k67+7uxoMHDwD0dwcGBqWPHz+erXNFPfXx8UFrayuPO2nSJPYa6urqEBISAmBwPZ0yZQq7b2VlJcLCwlTqKQ2BpwHskZGRIITg6tWr6O3t5XFnzJjBfrfc3Fw8f/4ccrkcnp6ekMvlPC4NgZfJZGx99/b2wtPTEwNB9ZTjOCQkJCA1NRXd3d3ss1bEvHnz2H0jIyORlZWFjo4OpUBzADw9DQkJQX5+Ptra2uDt7c3j0RB4et9Hjx6hpKQEzc3NuHPnDo+rqKccx+Hu3buoqKjA69ev2XenIpfqqUwmw/Xr11FbW4tXr17h4cOHPC7VU/p6PTw80NDQgOrqagQEBPC42tracHR0ZPc9e/YsWlpaUFFRgcePH/O4iiHwMpkMx48fR0dHB8rKytgaotDV1cXq1avZ73bgwAH09vaiqKgI4eHhPK6enh7TU47jsGtXf3Jdfn4+IiMjedxhw4Zh3bp1Snqak5ODmJgYHtfAwIBxV69ezfQ0MzMTcXFxPK6hoSHT0+XLlwvq6fDhw5meLlq0CEePHgXQ3+lMSUnhcUeMGMG4c+fOxYkTJwAACQkJSE9P53GNjY2Z9s6cORNubm4AgOfPnyMrK4vHHTVqFJydncFxHCZPnsz0NDo6Grm5uTyuqakp09Nx48bhwoULAICIiAgUFhbyuObm5oxra2uLy5cvA+g/kVJSUsLjWlpaMu01MzNj+5snT57g5cuXPK61tTXjjhw5EtevXwfQv0+srKzkcRX1dNiwYewZ8/f3R01NDY9rb2/PuJqammzP4ufnh/r6eh53zJgxbI319PQwPb137x4aGxt53HHjxrF13tbWxp6b27dvo6WlhcedOHEiew2vX79m+5Bbt26hvb2dx508eTK7b3V1NUJDQ0EIwY0bN9DZ2cnjUj3lOA6lpaVMT728vNDT08PjTp8+nd03Ly8PsbGxgnpKX296ejpevHiB3t5eXL16VWkv6+DgwO5L9VTVXnbu3LmMGxMTg4yMDHR2drLPWhELFixg3NDQUOTm5qK9vR23bt3i8ehelnIDAgJQXFyMlpYW9j2ryFXUU19fX5SXl6vU06VLl7L73rp1C9XV1airq2PrgkJLSwvLly9n75lY7NOPBalTc9UdUQXQAG8pF+2KSLloCPP/Ru5Q3gczMzPJXFNTU8lc2nWSco0cOVIST0NDg3WopHANDQ0lcTU1NcmwYcMkcbW0tIiOjo4krra2NtHU1JTMlfp+0W6alItWiqVcUt8DAKxaLeWS+jkA/V0hqVxaXZdySV1jQH8VUyqXdgN+aO5QnrWhPMND0Qa1ng79ffg56KnU9auhoSH5GdLQ0JD8bGpqarLTAWKXlpaWZD3T1tYmWlpakrhSNXqo3B9LT6W+X8DQtHcoeir1uxUYmvYORU+Hss5/Dnr6Y2nvz0H3fg56+mNp71DWzlDW71D2sh988IHKU4c/JiCxI/q941v+N2LRokX497//DaDffzSwgk+rHBzH4dWrV6wydO7cOV5HdGCFuby8HM+ePQMhBKdPn+ZV8AdWmAsLC1llyM3NjVfBH1hhzsrKQkJCAvr6+nDixAleR3RghTklJYV1OU+cOMGrIilWmDmOQ3x8POty0u4ShWKFmeM4REVFITs7G2/evGHdJYqBFeaQkBAUFBSgpaUF58+f53H19PSwdu1acBwHjuMQEBCAkpISNDY2su4ShWKF2cXFBb6+vqioqEBdXR2uXLnC4+rr67OOnYuLC7y9vVFTU4Pq6mqlDi6tMNOuoZeXF+rr61FeXq5U9VKsMDs7O+PSpUtoampCSUmJUhdBsWO3adMmnDlzBu3t7SgsLFSqeo0cOZJ14TZu3Ijjx4+ju7sbubm5Sl0ExQrzxo0bcfDgQcjlcmRmZip1ZRUrzOvWrWOV9tTUVDx58oTHNTMzY5XgVatW4dChQwD6u5FhYWE8roWFBVtjS5YsYZ3L+Ph4PHv2jMelHTuO47BgwQJWaY+JiVHqDChWmGfNmsXW1rNnz5Q6rYoV5rfeeotV2kNDQ5GUlMTj0gqzTCbDhAkT4O7eb18IDg5GWloaj6tYYba3t2edy8DAQGRmZvK4EydOZFxLS0tWfX348KFStV+xwmxiYsKqr76+vkrVfsUKs6GhITsdcPv2baXuqWKFWUdHh1Xab968iYqKCh5XscJMCGGnA65du4bq6moeV7HC3NnZCX9/fwD9/qO6ujoel3bsOI5Da2sr63JevHhRqYKvWGGuq6tjHf9z587xOqJUT+nrraysZKdGBuqpYoVZJpOhuLiYnRo5efKkkp4qVphzcnLYqZGTJ0/yOqK0wkx/t/T0dNblPHHiBK+Cr62tzTst8eLFC9blpGueYqCeRkdHsy7nqVOneFxdXV12WoLjOISFhSEvLw+tra1szVPQjh193oKCglBcXIympia25imGDRvGTkBwHAc/Pz+8fPkS9fX1bM1TKOqps7Mz7ty5g6qqKtTU1Ch1cA0MDJieuri44Nq1a6irq0NlZaVSB5fqKcdxcHZ2hoeHBxobG1FWVqZ0IsbIyIinp/T7t6ioiHXrKUaOHMnjnjx5Ep2dncjLy1PqIowaNYppr5OTE44cOYLe3l5kZWUpdWVNTEyYnjo5ObEuZ1pamtIpF1V6mpycrHTKxcLCgnGXLVvGOpcJCQlKp1ysrKzY57tw4UK2tmJjYxEdHc3j2tjYsOfHwcGBra3IyEilTqudnR3jTp8+HWfPngXQ79Ec2GkdPXo0W+eTJk1incuQkBClTivVU47jMGbMGNa5DAoKUjq5Qk+f0VMj9CTBo0ePkJOTw+Mqnj4zNTVlenr//n0UFBTwuPT0mUwmg5GREftev3PnjlL3dPr06ex90NPTY9/r3t7eSt3TmTNnsvvSnw0A169fVzqNonj6rLu7m5228vT0VDqNQjt2HMehra2N6Sk9gaUIxdNnr1+/Zt/r58+f53VEB54+q66uRnh4OAghOHv2LK8jOvD0WWlpKaKiokAIgZubG7q6uhhXUU85jkNeXh7i4uIgl8tx8uRJXkdU8fSZTCZDRkYG63IO1FMtLS04Ojqy10u7+N3d3Th58qTSXlZRT2NjY5GZmYnOzk7WradQPH3GcRwiIiJYl/PMmTM8Lj19RrnBwcEoLCxEc3MzW/MUdC9LuQ8fPkRZWRkaGhrYmqfQ19fn7WXv3r2LyspK1NbWKnVwFU+fubi44ObNm6itrR1UTw0NDZmeuri4wMLCAj9rSPlr9Ye6fu4dUYqYmBgCSPPchIWFEUCa5yYwMJAA0jw3vr6+rOpBPYyqzohT36cUz83ly5dZlYZ6bhobGwflnjlzhlV/xDw3R48eZdWqDz/8kNy7d0+l33Hv3r0EALG0tBT13HzzzTcE+M7DKOS5ob5PMc8NIYR89tlnBOj3Owp5bggh5OOPPybAd56bJ0+eDOq5IYSQ9957jwDinhtCCPnNb35DgO88N6o8jIR85/ucOnWqoOeGEELWrl1LAHHPjVwuJ8uWLSOAuOdGLpeTefPmEaDfc7N9+3aVnpu+vj4yY8YMAoh7bnp6epjvk3oYVXluFH2fYp6bjo4OYm1tLclz09bWRszMzHieG1UexqamJmJsbEw0NTWJo6OjoOemvr6eDB8+XJLnprq6mujr6zMPo5Dnhvo+pXhuCgsLWSdIzHOTnZ1NNDQ0mOfm3LlzKj03KSkpBOjvxFDPjSr/eFxcHE9PL168qNI/Tn2fip4bVZXcx48f8/RUyHPj5+dHAGmeG29vb6a91HOjyj/u6elJgP7uyu9//3tBPT1//jwB+jsm77//Prl9+7ZKPaW+T3Nzc+ZhVKWn9CSPpaUl+eijj8j9+/dV+h137NhBABBra2vypz/9iTx48EClnm7ZsoUAILa2tuSTTz4h/v7+KvX073//O09PAwMDVerpJ598QoB+//hnn32m0sNIyHe+T6qnISEhKvX0t7/9LQFAJk6cSP75z3+q9DASQsgvfvELAvR7GL/88ksSERGhUk83bNhAAJC33nqL/Pvf/xbUU0dHR6anX3/9NYmJiVHJpb7PWbNmCXoY+/r6yKxZs5iefvPNNyQhIWFQbm9vL5kyZQoBQObNm0d27txJEhMTB9Wn7u5uMm7cOAKALFiwgOzatYukpKQMyu3s7CS2trZEQ0ODLF68mOzdu5ekpaUNym1vbycWFhZEQ0ODLF26lOzfv1+lh5H6PhU9jKrmcTQ0NBAjIyPePA5VelpbW8v0dM2aNYLzOCoqKpieis3jKC4uJtra2kxPT506pdI/npubSzQ1NSXN46C+T6qnQvM4EhISCPDdPI6LFy+q9DtGRkYyPRWbxxESEsL2sr/+9a+Jp6enyr3so0ePmPbSeRyq9rLU9ylFT728vJie0nkcqvTU3d2d6ekf/vAHwXkcbm5ubC8rNo/j0KFDbC/70UcfCc7j2LVrFwG+m8fx4MEDlXtZ6vu0sbEhn3zyCXn06JFK7f3nP//J9rKffvqpoJ5++umnBOj3jwvN4/jvANQd0e+PiooKBAYGYvXq1aITwaqrq/H48WOsWrVKdCJYfX09QkJC4OjoKDoRrKmpCaGhoVixYoXglC+gf7pgREQEli1bJji5C+ifGBsZGYklS5aIcgkhiI6OxuLFiwWncRFCoKOjg+fPn2PhwoWCEwsJITAwMEB8fDzmz58vyO3r68OoUaOQmJiIuXPnCk716+3thaWlJZKTk+Hg4CDI7e7uxtixY5GWloaZM2cKcjs6OjBlyhRkZGRg+vTpgtz29nY4ODhg69atmDp1qiC3ubkZS5YswZ49e0TP7zc0NGDt2rU4fvw4Jk6cKMitra2FTCaDu7s7xo8fL8itrKzEu+++i+vXr2Ps2LGC3LKyMnz00Ufw9fXF6NGjBblFRUX461//Co7jYGdnJ8gtKCjAv/71L7i4uMDGxkaQm5ubi+3bt8PFxQVWVlaC3OzsbOzbtw/Ozs6i1cCsrCwcPXoUzs7OohMhs7KycPr0aWzatEl0ImRWVhbc3d2xceNG0YmQ2dnZ8PT0hJOTk+iUx5ycHNy4cQMbNmwQnfKYl5eHO3fuYP369aKTGwsKCnD//n2sW7dOdHJjcXExHj58iLVr14pObnz58iUCAgKwevVq0WmMVVVVePz4MVauXCmqva9evcKTJ0+wcuVKUT1tbGzE06dPsWLFClFuW1sbwsPDsWzZMlHt7erqwrNnz7B06VJRPZXL5ZL1VEtLC7GxsVi4cKEoV19fX5KeyuVyjBw5Ei9evMDcuXNFtdfCwgJJSUmYM2eOoJbRSZCpqamYNWuWILezsxOTJk2SpKdv3rzBzJkzkZWVhbfeekuQ29LSgoULF8LV1RVTpkwR5DY2NmLVqlU4cuQIJk2apJIH9E/N3bRpE86ePYsJEyYIcqurq/Gb3/wGnp6eGDdunCD35cuXeP/993H79m2MGTNGkFtSUoJPP/1Usp5+8cUX4DhOVE/z8vKwbds2ODs7w9raWpCbnZ2N3bt3w9nZGZaWloLcrKwsHD58WLKenjx5Eps2bRKdbp6ZmYnz589j06ZNonqalZWFK1euwMnJSXTCbnZ2Nq5fvw4nJydRPc3NzYWPjw/Wr18vOjU3Pz8f9+7dw/r160X1tKioSLKelpaWwt/fH2vWrBHV08rKSgQFBWHVqlWielpbW4vg4GCsXLlSdC/b0NAgeS/b0tKCsLAwLF++XFRPOzs7Jetpb28voqKisGTJElGN1NDQQExMDBYtWiTK1dPTQ1xcHBYsWCCqp0ZGRkhISMC8efNE9dTMzEyyntra2iIlJQWzZ88W5HZ1dWHChAlIT0/HjBkzBLk/Z6iHFamhhhpqqKGGGmqooYYaaqjxg0DqsCLVf8KroYYaaqihhhpqqKGGGmqoocaPAPUfomqooYYaaqihhhpqqKGGGmr8pFD/IaqGGmqooYYaaqihhhpqqKHGTwqtnTt3/mQ/zN3dfefmzZt/sp/3fUAIgaurK16/fg07OztB07ZcLse3336LlpYW2NvbC5q2+/r6sH37drS3t8Pe3l7QtN3T04Pt27ejq6tLlNvV1YVt27ahr68PdnZ2ggbvN2/eYNu2bSCEiHLb2tqwfft2aGhowM7OTtDg3dTUhG+//Rba2tqi3Pr6euzcuRO6urqws7MTNHhXV1dj7969GDZsGGxtbQW55eXlOHDgAAwMDGBjYyPILS4uxtGjR2FoaAgbGxtBg3dubi7c3NwwfPhwWFtbC3IzMjJw/vx5jBgxAlZWVoLc5ORkXLp0CSNHjoSlpaUgNy4uDl5eXjA2NoaFhYUgNyoqCrdu3cKoUaNgbm4uyA0PD8fdu3dhYmICMzMzQe6TJ0/g5+cHMzMz0aESAQEBCAgIgLm5uehAHz8/Pzx58gQWFhaiAyju3LmD8PBwWFpaig6guHXrFqKjo2FlZSU6/MfLywtxcXGwtrYWHVbh4eGBpKQkWFtbiw6ruHDhAtLT02FjYyM6KOjMmTPIycmBra2t6GCLkydPoqCgAHZ2dqKDLY4ePYrS0lLY2tqKDrY4ePAgKioqYGdnJzrYYu/evaipqRHlEkKwa9cuNDQ0wN7eXlBPCSH49ttv0dzcLElPv/nmG0l62tvbi23btqGzs1OU293djW3btrEBPEIa2dHRgW3btkEul4ty29vbsX37dgD9cUNCGtnc3Ixvv/0WWlpaonra0NAAV1dXSXpaW1uL3bt3S9LTyspK7N+/H/r6+qLc0tJSHD58WJKe5ufn4+TJk5L0NDMzE2fPnoWRkZEoNyUlBRcvXpSkvQkJCfD09JSkpzExMbhx44YkPY2IiMDt27cl6WlISAju378PU1NT0YE+gYGB8Pf3l6SnDx48QHBwsCQ9vXfvHsLCwmBhYSGqp97e3oiMjISlpaWonl6/fh2xsbGwsrIS1dMrV64gMTERNjY2onrq7u6O1NRUSXp69uxZZGVlwcbGRlRP3dzckJeXB1tbW1E9PXbsGIqLi2FnZydJT8vLyyVx9+3bh+rqakl6unv3btTV1YnuTwkh2LlzJ5qamkT1VC6X45tvvkFra6vkveybN28k62l3d7eoRnZ2dmLr1q3o6+v7QfW0paUF27dvh5aWlii3sbERO3bsgI6ODmxtbQW5dXV12LVrF/T09EQ1sqqqCvv27ZOkp2VlZTh06JCkvWxhYSGOHz8uSU//O+Dq6lq9c+dOd1GilNG6P9T1PyW+hY7Z19XVJRs2bCCnTp1SGXlAx+xLGdF94MABNqLbxcVFcET3zp07eSO63d3dVUYe0DH7UkZ00zH7iiO6VUUe0DH7I0aMYCO6VUUe0DH7dET39evXVY7ofueddySP6KZj9qWM6KZj9s3NzQVHdCuO2adxM6pGdCuO2Rcb0d3X10dmz57Ni5t59OjRoJEHvb29ZOrUqSzy4NNPPyUBAQGDjuhWHLM/ZswYwRHddMw+ADJu3Djy+eefq4w8oGP2AZAJEyaQf/zjHyQ0NHTQyAM6Zh8AmTx5Mvnyyy9JeHj4oJEHDQ0NLIR86tSp5KuvviKRkZGDcmtra1lo+vTp08mWLVtIdHT0oJEHdMw+ADJz5kyydetW8vz580FjDOiYfQDEwcGBbN++ncTHxw/KpWP2AZC5c+eSHTt2kMTExEG5dMw+FOJmkpOTB40bePHiBQuUXrRoEdmzZ4/KuBk6Zp9GHuzbt49kZGQMyqVj9jU1Ncny5cvJwYMHVUYe0DH7WlpaxNHRkRw+fJjk5uYq8Qj5bsy+trY2Wb16NTl27BjJz88flHvt2jXGXbt2LTlx4oTKyIOLFy/y9NTNzU1l5AEds6+np0c2btxIzpw5Q8rKygbl0jH7VE/PnTtHysvLB+XSMfv6+vpEJpMJ6ikdsy8lvuuLL76QHN/1l7/8RXJ814cffqgU36VKT3/3u99Jju/61a9+xYvvEtLTTZs2SY7vWr16tVJ8lyo9Xbx4MdNTofguuVxOHBwcJMV39fb2kmnTpinFdw2mpz09PWTChAks8oDGdw2mp11dXcTe3l5SfNebN2+IlZWVpPiulpYWYmpqKim+q7GxkYXXi8V3vXr1ihgaGvLiu1TpaVVVFRk2bJik+K7S0lKio6MjKb6roKCAaGlpSYrvysjIIBoaGpLiu5KSkpj2isV30Qg+KfFdNIJPSnwXjeBTjJtRFd917949pr00vkuVnt64cYOnp0LxXTSCTzG+S5We0gg+xfguVXpKI/gU47tU6SmN4NPX12fxXaoiZLZv3y5ZT//1r38pxXep0lMawSclvotG8EmJ76IRfMbGxixuRpWe0gg+ExMT0fguFxcXnp4KxXfRCD6x+C7FCD7F+C5VETI/NSAxvkU9NVcBjx49go+PD7q7u1l4sSJoaDHHcaisrISfnx86Ojrg6+urxFUMLS4sLERgYCDa2tqUQrQBfmhxVlYWQkJC0NzczILjFaEYWpyUlISIiAi8fv2aBR1T0NBixWDfmJgY1NXVsaBjRa5iaHFYWBgSEhJQU1OD0NBQHpeGFtNw4aCgIKSkpLCQeUUohhbToPTMzEy8fPkSUVFRSlzFEHgfHx/k5uaipKQEsbGxPK5iaLFMJoOnpyeKi4tRWFiI+Ph4HlcxtFgmk+HChQsoLy9HXl6eUji3np4eVq9ezV6vm5sbampqkJOTg+TkZB532LBhvIDjw4cPo6GhAZmZmUhLS+NxB4YW79mzBy0tLUhLS0NmZiaPOzC0ePv27ejs7ERycrJSkPfw4cNZYLyzszO++uor9PX14cWLF8jPz+dxjYyM4OTkBJlMho0bN+KLL74A0N9tLSoq4nFpCDzHcVi9ejW2bNkCoL87UFpayuMaGxuzEPhly5Zh69atAPqD0svLy3lcExMTxl20aBGraIaHhyuFfpuZmbHA+NmzZ8PV1RUA8PTpU9TW1vK4FhYWjDtt2jTs2bMHABAcHIz6+noe18rKigXGT5gwAQcOHADQ33VobGzkcW1sbBjX3t4eR44cAdCvE4oB4cB3IfAcx8HS0pKFy/v5+fECwoH+EHj6/BgbG+P06dMA+jsUnZ2dPO7YsWPZGtPX18eFCxdACMHdu3fR3d3N444fP56tc01NTVy+fBmEEPj4+KCvr4/HpSHwHMeht7cXV69ehVwuh7e3NwZ+J0yZMoXdt729HTdu3EBvby98fHwwENOmTWO/2+vXr3H79m2Vejpjxgx236qqKty/fx+dnZ24d++eEnf27NnsviUlJfD390d7ezv8/PyUuHPmzGH3zcnJQXBwMFpaWlhwvCLmzZvHuKmpqQgLC0NjYyMCAwOVuIp6Gh8fj6ioKNTX1yM4OJjH09DQwKJFi9h9nz17hri4ONTW1uLp06c8rqamJpYsWcILSk9OTkZVVRXCw8OVuIoh8A8ePEBGRgbKy8sRGRnJ4yrqKcdxuHPnDnJyclBaWoqYmBgeV1tbG46Ojuy+165dQ2FhIYqKihAXF8fjUj2ln8WlS5dQVlaG/Px8vHjxgsfV1dXl6emZM2dQVVU1qJ7SEHj6DB09ehT19fXIyspCamoqj6uvr88LjN+7dy+am5uRnp6OjIwMHtfAwICnvTt27MCbN2+QkpKC7OxsHtfQ0JCnp19//TV6enqQmJiIvLw8HtfIyIjH/ec//wkAiI+PR2FhIY87YsQIbNy4ETKZDGvXrsVXX30FAIiNjUVJSQmPa2xszLiOjo74+uuvAfSfdHn58iWPS/WU4zgsXryY6WlERAQqKyt5XFNTU6aRc+fOxY4dOwAAoaGhqKmp4XHNzc3h4uICjuMwY8YM7N69G0D/qZi6ujoe19LSkmnk5MmTsW/fPgBAUFAQXr9+zeNaW1sz7pgxY3D48GEAgL+/P5qbm3lcW1tbtsasrKxw/PhxAP0d37a2Nh7X3t6ecU1MTHDq1CkAgK+vLzo6OnjcsWPHMq6hoSHOnTsnqKeUq6Ojg4sXL4IQgtu3b6O3t5fHnThxInt+5HI5rly5ArlcDh8fH8jlch53ypQp7L4dHR24fv06+vr64O3tjYF466232DpvamqCj48Penp6cPv2bSXu9OnT2Wuora3FvXv30NXVhbt37ypxZ82axe778uVLPHz4EG/evMH9+/eVuA4ODuy+eXl5ePz4MVpbW/Hw4UMl7rx589jvlpGRgadPn6KpqQkBAQFK3AULFrD7vnjxAs+ePUNDQwMeP37M41E9pfeNiorC8+fP8erVK4SEhChxqZ7KZDKEhIQgMTER1dXVCAsL43HpXpZy/f39kZaWhoqKCjx79ozH1dLSwvLlyxn33r17yMrKQllZGaKjo3lcbW1t3l72xo0bKCgoQHFxMZ4/f87j6ujosL0sx3Hw8PBAaWkpCgoKkJCQwOPq6ury9rJnz55FZWUlcnNzkZSUxOPq6enx9qf29vZK7/9PAalTc9UdUQXQYHAp1+TJkyXxNDQ0yKRJkyRxNTU1h8SdOHGiJK6WlharAItd2trarPsmduno6JCxY8dK4urq6pLRo0dL4urp6RE7OztJXH19fWJtbS2Ja2BgwDqAYtfw4cNZxVrsGjFiBKtYi10jR45kFWuxy8TEhOjp6UnimpmZsa6e2GVubi6JB/RX2aRyaTdAykW7tlIuqWsBgOQ1BvR3l6VypT4TQH83RCpX6jM8VK5UHQGka9lQuVOmTPnB76uhofGjae+PpadS18PPQU+HDRs2JD2Vqg+GhobEzMxMEtfIyIgYGxtL4o4cOZIMHz5cEnfUqFGsAyh2mZqashMVYpfU7xRgaHoq9XMA+jvGUrn/m/VU6nM5VO7PQU9/DO5Q9VQqdyh72R9LT4e6l5W6fvX09NgpCbFr2LBhkp9NfX19yXsoQ0NDyfu44cOHk927dw96OuTHBiR2RIUTY/+PYdmyZfj222/R2trKKlv5DzoAACAASURBVHAUBgYGvApoTk4OIiIi0NjYyCpwFAM7VWlpaYiOjkZdXR3OnTvH4xoZGbEK6KZNm/DixQvExcWhuroaFy9e5HFpp4pyo6OjkZSUhPLycly5coXHHTVqFOs+OTk5ITw8HGlpaSgpKcG1a9d4XBMTE1YtdXJyQnBwMLKyslBQUIBbt27xuGZmZqxaumHDBvj7+yMvLw85OTlKXQ8LCwtWAV2/fj18fX1RVFSEjIwMpcqblZUVq4avW7cOPj4+KCsrQ0pKilInw8bGhlXH1qxZg+vXr6OyshIvXrxQ6gzTTpVMJsPq1atx5coV1NbWIjY2Vqk7MXr0aFZtWrlyJdzd3dHQ0IDIyEilbi/tVFHu6dOn0dzcjPDwcKVu74QJExh3xYoVOH78ONrb2xESEqJUIaOdKtphPHToELq7uxEUFKTUcZg6dSrjLlmyBHv37oVcLsejR4+QkpLC406bNo1xFy5cyLqGvr6+Sl1Zxc6/g4MD6xrevn0bubm5PK5i53/atGmsyn3z5k2lzoBi53/ixInsGfPy8lLqtCp2/u3t7dkz5uHhgYqKCsajnX/6GVtaWrJnzN3dnVftH9j5NzY2Zs/Y2bNned1TxU6VTCaDgYEBe8bc3NzQ1NTE49JqKcdx0NbWxrVr10AIwfHjx3kVfC0tLTg6OrLXK5fLcfPmTRBCcOTIEV4FX7Hzz3EcOjs7cfv2bcjlcrYuKBQ7/xzHoaWlBb6+vujt7cXBgwd5HVFdXV1WLXVxcUF9fT0ePnyI7u5uHDx4kNcRpZ0qet/KykoEBgaio6ODfdYUAzv/JSUlePLkCdra2nDs2DEed2DnPzc3F+Hh4WhqaoKbmxuPa2hoCCen/9/eeYdFdW3v/z0iHSuiIqCJKUaTmJio0dhLbJkx0UmMiTE9FjQaY9eoaAR7xQr2GlvsxgI27L13ERFBEbGACAizfn8M59wzM6d5b4L6/a3P8+wnwn1vmHu3vHvvtfbaqylMJhM+/vhjnDp1CjExMbh79y6mTp1qp5Vn/lu0aIEjR45g//79uHXrFiIi7EtV5Jmq5s2bY//+/Th8+DASEhIwZ84cO60889+sWTPs2rULx48fR1xcHBYsWGCnFf3UZDKhadOmiIqKwunTp3HlyhUsWbLETuvr6yt5ZJMmTbBx40ZcuHABFy5ccMp6iJkq0U/XrFmDK1eu4MyZM063ckqVKiX9HWvcuDGWL1+OuLg4nDhxwimT4e/vL2kbNWqExYsXIyEhAUeOHHHKDAcEBEh/Fxo2bIh58+bh1q1bOHDggNNNm6CgIOn3p379+oiMjERKSgr27NnjlJ2QZ/7r1auHadOm4f79+9i5c6dTtlee+a9Tpw4mTZqE9PR0REVFOd2ekWeqateujbFjxyIzMxObN292yjjIM/8ffvghRowYgZycHGzYsMEpgyv6qclkQs2aNTFs2DAAthsQp06dstPKM/9VqlTBiBEjAAArV650ysrKM/9vvfUWRo8eDcBWo+l4y0We+X/ttdek37GFCxc6ZVrlmf+XXnoJkyZNAmCr0XS8uSLP/JcpU0b6HYuMjERSUpKkc8z8+/r6YubMmQCA6dOn22VPHTP/Pj4+0u9YeHi43W0Ux8y/q6srFixYACLCxIkTkZaWJmnFzL/4/xkALF68WNVPxcy/yWRCdna2lLFU8lO596anp2PVqlXIzc3FqFGj7DKijpn/u3fvYu3atXjy5AlGjRpllxF1zPwnJSVh48aNyMzMlOZaxMPDw85Pr1+/ji1btuDRo0cYN26cndbT09POTy9fvozo6Gg8ePBAmmsRx8z/mTNnsHv3bqSmpkq3c0R8fHzs/PTYsWPYt28fkpOTMWPGDDuto58eOHAAhw4dQmJiImbNmmWnLVKkiJ2fxsTE4NixY4iPj8e8efPstMWKFZP8tFmzZoiOjsapU6dw9epVLF682E4rz/w3adIEmzdvxrlz53Dx4kWnGzziXlbUrlu3DpcuXcLZs2edbuXIM/+NGzfGqlWrEBsbi5MnTzrdchT9VNzLLlmyBDdu3MDRo0edMsPyzH/Dhg0xf/58JCUl4eDBg043beSZ/wYNGmDWrFm4c+cO9u7d63RzsVy5cnb7U61a4ucCI6fVf2o87xlRkbCwMAL+U7u3adMm1WjC4MGDCbBFA7t27UpbtmxRrB8hIurTpw8B+rV7RETdunUjwJYF6dGjB23fvl2xfoSIqEOHDlIUrGfPnrRz507F+hEiovbt2xMAqlixIvXp00e1do+I6PPPPyfAVrvXr18/2rt3r2L9CBGR2WwmAFS5cmXN2j0ioo8++ogAW+3eoEGD6NChQ4paq9VKderUIQD0/vvvU0hICB05ckSxHsNqtVK1atUIAFWrVo2GDRtGx48fV9Tm5ubS22+/TYIgUI0aNWj48OF08uRJRW1OTg69/vrrUu3eiBEj6MyZM4ra7OxseumllwzV7j1+/JgCAgLIxcWF6tWrR2PHjqWLFy8q/v+Vnp5OJUuWtKvdu3z5sqL2wYMHVKxYMXJ1daXGjRvTpEmTVGv3UlJSqFChQna10Gq1Jrdu3SJPT0+pFlqrdu/GjRvk5uZmqBb66tWrVLBgQbvaPbVak/Pnz1OBAgXIy8tLtxb6xIkTUjTQYrFo1u4dPHiQAFsmRqyFVqvd27VrFwHGave2bt1KgLFa6HXr1hFgrHZv+fLlBNiy4GIttFqtyfz58wnQr4UmIpo5cyYB/6mFVqvdIyKaNGkSAfa10Eq1e0REo0aNIsCWidGqhSYiGjp0KAG2TIxWLTQRUf/+/e38dOvWrap++uuvvxKgXwtNRNSpUycC9Gv3iIi+++47AvRroYmI2rZtS4B+7R4R0aeffkqAfS20mrZp06YE/Kd2T60WmoioXr16BPynFlqtds9qtdIHH3xAgH4ttFjLaaQWOicnhypWrCjV7mnVQou1nHI/Vavdy8zMpMDAQEO10I8ePaJSpUqRi4sLNWjQQLN27+HDh1S8eHG7Wmi12r3U1FQqXLiwodq95ORk8vLyIjc3N91a6Js3b5K7u7uh2r1r164Z9tOLFy9KfqpXu3f69GkpE6NXC33kyBHJT/Vqoffs2ePkp2q1e1FRUQQYq4XesGGDnZ9q1e6tXLmSAFsWXK8WetGiRQTo1+4REc2aNYsAWxZcqxaaiGjKlCkE2LLgP//8s2otNBHRmDFjCLDdKhJroZXeoSAi+uOPP6S9rFgLrea9AwcOJEC/FpqIqGfPngTo10ITEXXp0sWwn/74448E2G7TaNVCExF99dVXdn4aExOj6pGtW7cmQL8WmoioRYsWkp8OHDhQtRaaiKhhw4YE6NdCW61W+vDDDyU/DQkJUa2FtlqtVKVKFQL0a6Fzc3OpUqVK0l5Wqxb6WQCDGVE+iDpgtVpp+vTpqhMvJzc3l6ZOnWpo4nNycig8PFz1ECMnOzubwsPDVYvg5WRmZlJ4eLjqIUbOo0ePKDw8XHUhlfPw4UMKDw+n2NhYXe29e/do6tSpqg86yblz547mg05ykpKSaObMmaqHGDnx8fEUGRmp+gCJnNjYWJozZ47qIUbOxYsXNYvg5Zw9e1azCF7OyZMnafHixaqHGDlHjx7VXEjlHDx4ULMIXs7evXs1F1I5u3btotWrV6seYuRs376d1q5dq7qQytm6dStt2LBBdSGVs2nTJs2gkJz169drBoXkrF69WjMoJGflypWaQSE5y5Yt0wwKyVmyZInmQipn4cKFmkEhOfPmzdNcSOXMnj1bNSjkSEREhGpQSI7VaqUZM2aoBoUctdOmTVMNCsnJycmhKVOmGPLTJ0+e0OTJk1WDQnKysrIM+2lGRgZNnjxZNSgkJz09ncLDw1WDQnLu379PU6ZMUT3EyElJSTHsp7du3dIMCslJSEigyMhI1UOMnGvXrmkGheRcvnyZ5s2bp3qIkXP+/HnNoJCcU6dOaQaF5Bw7dkwzKCTn0KFDmkEhOfv379cMCsmJiYnRDArJ2bFjh+oDeY5s27ZNMygkZ/PmzYb9dMOGDZpBITlr167VDArJWbVqlWZQSM7y5cs1DzFyli5dqhkUkrNw4ULNoJCc+fPnawaF5MyePVszKCQnMjJS9YE8OaKfqgWFHLVG/TQ3N5emTJmiGhSSI+5l1YJCckQ/VQsKyXn8+DGFh4erBoXkiH5qZC/74MEDzSC7nNTUVM2gkJzk5GTNoJCcmzdvagaF5MTFxWkGheRcuXJFMyj0rDF6EOXHihiGYRiGYRiGYZh/BKOPFak3qGEYhmEYhmEYhmGYfwE+iDIMwzAMwzAMwzD5Ch9EGYZhGIZhGIZhmHzFJSQkJN9+WEREREiHDh3y7ef9N4SGhiI2NhZlypSBt7e3pjYkJATx8fEICAiAl5eXqo6IMGjQICQlJSEwMBCenp6a2v79++POnTu6WqvVir59++LevXsIDAyEh4eHqjYnJwe9e/dGWloaAgMDNZ9zzs7ORu/evfHo0SMEBQXBzc1NVfv48WP07t0bWVlZutpHjx6hd+/eyMnJQVBQEFxdXVW1Dx48QN++fUFECAoKQsGC6p2GUlNT0a9fPwiCoKtNTk7GwIED4eLigqCgILi4uKhqb968iSFDhsDV1VVXGxcXhz/++APu7u4ICAjQ1F66dAkjR46Eh4cHAgICUKCAejzo7NmzGD9+PDw9PXW1x48fR3h4OLy8vFCmTBlN7aFDhzBjxgz4+PjA398fgiCoavfs2YPZs2ejUKFCKF26tKZ2x44dWLhwoSHt1q1bsXTpUhQpUgSlSpXS1G7cuBErV65E0aJFUbJkSU3tmjVrsHbtWhQvXhwlSpTQ1K5YsQKbNm2Cr68vfH19NbVLlizBtm3bUKJECfj6+qrqAGD+/PnYuXMn/Pz8ULx4cU3trFmzsHfvXpQqVQpFixbV1M6YMQMHDx5E6dKlUaRIEU1teHg4jh8/jtKlS6Nw4cKa2gkTJuD06dPw9/dHoUKFNLWjR4/GhQsXUKZMGfj4+Ghqw8LCcOXKFQQEBOj66dChQ3H9+nVdLRFh8ODBSExMNOS9AwYMQHJysmE/TU1NRVBQkKaf5ubmok+fPnjw4AGCgoI0/fTJkyeSn+p5b2ZmJnr16oXMzExdP83IyEDv3r3x5MkTXT9NS0tDnz59YLVadbX37t2T/DQwMFDTT+/cuYMBAwbAxcVFV5uYmIjBgwejYMGCCAwM1PTI69evY9iwYXBzc9PVXrlyBWFhYXB3d0dgYKCm750/fx5jx4415KcnT57E5MmT4enpqeunhw8fxvTp0+Ht7Y0yZcpo+si+ffsQGRlpyHt37dqF+fPno3Dhwrp+GhUVhcWLFxvy002bNmHFihWG/HTt2rVYs2YNihUrBj8/P03typUrsXHjRkPeu3TpUmzdutWQny5cuBA7duxAiRIldP10zpw5iImJQcmSJVGsWDFN7cyZM3Hw4EFD3jtlyhQcPXrUkPdOnDgRJ0+ehL+/v673jh07FufOnTPkvSNGjMDly5cNee8ff/yBuLg4Q346ZMgQJCQkIDAwUNdPf//9d9y+fRsBAQG6ftqvXz/cvXtXd3+am5uLvn374v79+7raJ0+eoE+fPkhPT9f13qysLPTu3RuZmZkIDAw05KfZ2dm6Hpmeno7evXsjNzdXV3v//n307dsXAHT3pykpKejfvz8KFCigq7116xYGDRpkyE+fFUOHDk0KCQmJ0BUaedHonxovwqu5a9asIQDS8/JazyH/+eefBNia99aqVYtGjhyp+pLY3LlzJW2dOnVo9OjRqq/iTp8+nQBbo9/69evTuHHjVF9xnDBhgtS8t2HDhjRhwgTVl8RGjBghNe/Ve15+yJAhBNgapzdt2pSmTJmi+pKY2JbGyPPyYlsaT09PMplMNHPmTNWXxMS2NOLz8pGRkaoviX3zzTfS8/KtWrWiOXPmqL4k1qZNG7vn5bVexW3ZsiUBoMKFC1ObNm00X8UV29IULVqU2rZtS4sXL1Z8Xl7elqZ48eLUrl071Vdx5W1pfH19qX379qqv4ubm5lLlypXtnpdfuXKl4qu4OTk5VKFCBel5+R9++IFWr16t+DKj2JYGBp6XF9vSIO95+Y4dO6q+iiu2pYHseXm1VxzFtjTIe15eq1XS3bt3qVChQnbPy6u9inv79m3y9PQ01CpJbEuDvOfltVoliW1pIGuVFBMTo6gV29LAQKukkydPSo2qK1euTAMHDlRtlXTo0CFJW6VKFc1WSbt375a0YqskteflxbY0MNAqSWxLI39eXu0VR7EtjZFWSQsWLLDzU61WSREREZKf6rVKEtvSiH6q1SpJbEsjb5Wk9sq42JZG3ipJ7ZVxsS2N2CpJ61XcHj16EGBrnG4ymTRfxe3cubPkpy1bttR8ZVxsS+Pt7a3bKklsSyO2StLyU7EtTeHChaVWSWp+2qxZM6m1R9u2bTVfxa1fv76hVklWq5Vq1Khh56dqr+KKbWlEPxVbJan5acWKFQ21ShLb0kDWKkntVdzMzEwKCgpyapWk5KcZGRlUunRpQ63nxLY0yGs9p9UqSWxLAwOt58S2NDDQKklsSwNZ67kdO3YoemRcXJzkp3qtki5duuTkp2qv4optaeDQKknJI8W2NMhrPafVKklsSwNZqyS1V3Gjo6MlrV6rpI0bN0oeKbZKUvPTVatW2fmpVqsksS2NkdZzYlsaI62SxLY08tZzaq/ijh07VtKKrZLUXhkfPny4k5+q7WXFtjTu7u66rZLEtjRi6zmtvazYlkbeKknNT8W2NEZaJbVr107yU71WSRaLxc5PtVolPQvA7Vuenr/++otat25NgiBIxiAOx83vsmXLpEXVcZQvX97OrBcuXEiffPKJotZx8ztnzhwymUyKWsc+oTNmzJB6HjkOxz6hkydPlvrNOQ7Hze+4ceOocePGilrHze/IkSOlXkqOw7FP6LBhw6Q+do7j/fffl8zaarXSoEGDqHbt2opax81v3759pR5N8qFk1j169JD64zlqHTe/Xbt2papVqzpplTa/HTt2pPfee89Jq7T5/f777+mdd95x0ir1CW3Xrh299dZbTlqlPqFt2rSRNkPy4bj5zcnJIYvFIh1E5cNx8/v48WOyWCz06quvOmkd+4Q+fPiQLBYLvfzyy05aT09PatmypWTWKSkpZLFYqFy5ck5ax81vYmIiWSwWCgwMdNLKzTo5OZmuX79OFouF/P39nbSOm98rV66QxWKhUqVKOWkdN7/nzp0ji8VCJUqUcNI6bn5PnjxJFotFOjjLh2Of0MOHD5PFYqEiRYo4aeV9Qh8+fEh79+4li8VCPj4+TlrHze/OnTvJYrFIh2z5cNz8btu2jSwWi7QplA/Hze/GjRupdevW0qZQPsTNr9gndM2aNdS6dWtpUygfjpvf5cuXU6tWrRR/319++WWpr11WVhYtWrRI1U8dN79z586Vehw7DsfNb0REhKqfOm5+p0yZIh2UHMebb75p1yd0woQJUpDKcTj2CR01apSqnzr2CR0+fLh0AHMcjpvfwYMHS8Evx+G4+e3fv7+un4rtzXr27Ckd7By1jn1Cu3XrJgXV5EPc/MoDuZ06dVL1U8fN748//igdGOVDafPbvn17evvttxW1jpvftm3bUqVKlZy0op/KA7kWi4XeeOMNJ63j5jczM5MsFgu99tprTloPDw+7QG5aWhpZLBYqX768k9axT2hqaipZLBYpYCgfjpvfW7dukcVikQ648uG4+b1x4wZZLBYqU6aMk9axT2hsbKymn37xxRdSIPfChQtksVjIz8/PSevYJ/TUqVNksVikg7N8OPrp0aNHyWKxUNGiRZ20JUqUsOsTun//frJYLFLQUj5EP121ahWlpaXR7t27yWKxSIds+ShdurRdn9Do6GhNP5UHcv/++29q3bo1ubq6OmkDAwPt+oSuXbuWWrduTS4uLk7asmXLSn1CMzMzaeXKldSqVSvVvay8T+iSJUs097LyPqHz58+XgvOOQ+wTKu5lIyMj6eOPP1bUOvYJnTZtGjVv3lxRW6lSJSmQm5OTQxMnTqQmTZooah37hI4ZM4YaNWqkqBX9VGxvFhYWRg0aNFDUOvYJDQkJobp16ypqHfuEDhgwgGrVqqWodewT2rt3b6pZs6aTTikx1r17d6pevbqT1khiLL8AH0SfHjFjqDUEQaAmTZpI0WWtUaBAAWrRogX9/PPPhrQtW7akb7/9Vlfr4uJCrVq1oi+//FJXW7BgQWrTpo0UOdEarq6u1K5dO9WNm3y4ubnRt99+q3q4lQ93d3f68ccfVTdN8uHh4UGdOnVS/GV0HF5eXtS1a1fFDYvj8Pb2ph49etCbb76pqy1UqBD16dNHilprjcKFC9PAgQMVD0mOo0iRIjRkyBDFxddxFCtWjIYPH6546HAcvr6+NGrUKMXDgePw8/OTIo96o1SpUoa1ZcqUMawNDAw0rC1XrhyNHj3akLZ8+fKGta+99hqNHDnSkPaNN94w5A2A7RAiRmv1xjvvvEPDhg0zpH3vvfdo8ODBhrTVq1eXosB648MPP6R+/foZ0tapU4d69eplSNugQQP69ddfdXWCIFDjxo0pODjYkLZ58+aG/dRkMkmZPa0h+qkYidYaBQsWpM8//5w+//xzXa2rqyt9+eWXqodm+XBzc6P27durHm7lw93dnb7//nvVTZN8eHh4UMeOHVU3QvLh6elJXbp0UQy+OQ5vb2/q3r274qHOcfj4+FCvXr3o9ddf19UWKlSI+vfvT2XLltXVFilShAYPHizdqtAaxYoVoz/++EMx4OM4fH19aeTIkYoHCcfh5+dH48aN09UBNj8dM2aMIa2/v79hjwwICDD87y1btqzhf+/LL79s2E9fffVV6YaA3qhQoYJhP61UqZJhP61cufJT+WlISIghbbVq1ej33383pK1Ro4Z0o0Fv1K5dm3r37m1IW69evafy065duxrSNmvWjDp27KirFf30hx9+0NW6uLjQJ598Ql9//bUhrcVikW6paY2CBQtS27ZtVQOW8uHq6kpff/21amBRPtzc3Oi7775TTb7Ih4eHB/3888+qQT358PT0pM6dOyseFh2Hl5cX/fLLL4oJCsfh4+NDPXv2VAx8OY5ChQpRv379DPUr/jcAH0Sfnn379tGQIUOcokhKKfLdu3crmlOhQoWkrIuYIt++fbuiOYlRQvmVo61btypu9sSsixglJCLatGmTojk5RgmJbFfklMxJzLqIUUIiotWrV1OnTp2ctEpXjlasWEE//fSTk1bMuohRQiJbk2mljaE86yJe91y4cKHixtAxSkhku/b8xRdfOGnLli1LXbp0ob///lu6nhQZGUmtW7d20sqjhOKVo+nTpytG/+RZF1E7ZcoURdMTo4TyRtwTJ05UzJCIWRcxSkhku66itOGsVKmSXdaFiGjkyJGKBvn222/bRQnF6J/SYd8x65KVlUVhYWGKm1Mx6yJGCTMyMigsLEwxO+GYdXn48CGFhYU5BQbErIs8Snj37l0KCwtzyuDKsy5ilDA5OZnCwsKcgghKWZfExEQKCwtzyso6Zl2sVivFx8dTWFiYU2ZAfn1ezLrExsZSWFiY0wZZnnURr89fvnyZwsLCnLKn8uvz4nXPc+fOUWhoqFME383NjZo1a0ZTpkyRrnuePn2aQkNDnSL4Stfnjx8/TsOHD3faeDtmXYiIDh8+TMOGDXMKeihdOdq/fz+FhIQ4ZUS9vb2pdevWNGfOHOm6Z0xMDA0aNEjRT8Wsi3jdc8eOHTRgwAAnrdL1+W3btkmlA/LhmHUhItq8eTP99ttvit7reH1+w4YNUpmBfPj6+tplXYhs5R5KgUvx+vyqVauk654rV65UPGiXKlWKfvzxR1q9erXkvX/++Sd9//33Tlql6/OLFi1S3BgGBARQp06d7K7Pz5s3T7puKx/i9Xm5n86ePZs+++wzVT+VX5+fOXOm4qHcMetCRDR16lTFbIrS9flJkyYpBkQdsy5EROPGjVPMkDhmXYhsV6+Vsh6OWRciorCwMMUssniDSMy6ZGdnU1hYmGJmWMy6iDeIRD+tUqWKk9bx+nxaWhqFhYUpBgbErIt4g+jevXsUFhbmdHtGfn1e9NM7d+5QWFiY040YedZFvEGUlJREYWFhTllZpXKkGzduUFhYmFMAV/RT+Q2ia9euUVhYmFOmVV6OJN4gunLlCoWFhZGvr6+in8pvEF24cIFCQ0OdghPyciTRT8+cOUOhoaHk7e3t5KeO1+dPnDih6Kfi9fmZM2dK1+ePHDlCw4YNc8qIijeI5NfnDxw4oOqnYjmS6Kd79uyhwYMHK+5lHa/P79q1SzFwKfdTcS8bHR1Nffv2ddKKN4gWL14s7WW3bNkiXXVV8lP59fmNGzdS9+7dFf1ULEcS97Jr166VrsUq+an8+vyqVaukEi9HPxXLkUQ/XbZsmeJBW+n6/JIlS6h9+/aKfupYjjR//nzFpJHS9fk5c+YoBjnLlSvnVI4UERGheCjXuz6fn4APov8d06ZNU514R8aPH2+3kGpNfGhoqOpC6oi4IRMXUrU6NCKSImp6dWhERL/88ovdQqpWh0ZE0mbIcSFVQtzgOC6kSoibFr06NCKSrihXr15dsw6NiKhx48aG6tCsVivVrl3bUB2a1WqlqlWr2i2kanUTubm59NZbbykupI48efKEXn/9dcWF1JGsrCx66aWXFK/iOvL48WMqU6aMtJBq1U2kp6eTn5+foTq0+/fvU9GiRQ3VoaWkpJCPj4/iQupIUlISeXp6SgupVh1afHw8ubm52S2kanUTV69eJRcXF7uruGp1E+fPnydBEBQXUkeOHz8uLaRadWhEtk2D2kLqyM6dOwlwvoqrxJYtWwiwBYV++OEH1To0ItuCrbaQOrJs2TICbEGhjh072gWFHJk3b57qQurIjBkz7PxUrQ6NyBag9eF0SQAAIABJREFUMbqQitlsvTo0IpIyH/LSBjWtuMmqWLGiZh0aEUkbJ706NCKSsg6VK1fWrEMjIulWjFjaoFaHRkRSAE6vDo2IpEOgWNqgVodGRNSkSRNDdWhWq5Xq1q1r56dqdWhWq5WqV69uqA4tNzeX3nnnHam0QasOLScnh9544w1DdWjZ2dlUvnx5xaCQI5mZmRQYGGioDu3Ro0dUsmRJyU+16tAePHhAxYsXtyttUKtDu3v3LhUuXFgxKOTI7du3ycvLi7y8vKTSBrU6tISEBHJ3dzdUhxYbG0sFCxaUguxadWgXLlygAgUKKAbZHTl16pSdn8qDQo4cPnyYAOUguyMxMTGSnzoGhRzZtm2b5KdikF3Ne9evXy/5qfwqrhIrVqyQ/NQxyO7IwoULCVAOsjsSGRlJgHKQ3ZHw8HACnK/iKiFmvkU/lQeFHBGzzkpBdkfEgKFSkN0RMQioFGR3RLxB4xhkV0IM1jkG2ZUQD4ziDSQxyK6EeAgUg+xae9nmzZsrBtmVaNCggWKQ3RGr1Uo1a9Z8rq7iOsIH0f+ShQsXqi6kjsybN8/QxFutVpozZ47qQuqonTVrlupCKic3N5ciIyNVF1I5Yg2U2mMacrKysigiIkL1MQ05GRkZFBERobqQyklPT6fIyEjVhVTO/fv3NRdSOXfv3tV8nEjO7du3DRd037x5U/NxIjlxcXGaC6mcK1euqD5O5MiFCxc0F1I5Z86cscuuaHHy5EnNhVTO0aNHVR8ncuTgwYOaC6mcffv2aS6kcnbv3q0ZFJKzY8cOzYVUTlRUlGZQSM7mzZs1F1I5GzdutMuuaLFu3TrNhVTO6tWrNYNCclauXKm5kMpZtmyZ5kIqZ8mSJZoLqZxFixapLqSOzJ8/XzUoJMdqtdLcuXNVH3tz1M6ePVs1KCTnafw0JyeHIiMjDflpdna2YT99/PgxRUREqAaF5Dx69IgiIyNVg0JyHj58SLNmzVINCslJTU21y65okZycrPk4kZzExETDfhofH68ZFJJz9epVzaCQnEuXLmkGheScPXvWsJ+eOnXKLruixbFjx2jt2rWG/PTQoUOqj705sn//fs2gkJyYmBjDfrpz507D2ZXo6GjDfrplyxbNILucTZs2aQaF5Kxfv14zyC5nzZo1hv101apVmkF2OcuXL5feu9Bj6dKlmkF2OYsXL1YNCjmyYMGCp/JTtaCQo3bOnDmG/XTWrFmqQXY5op+qBdnliH6qFhSSk5mZSZGRkf+4n6alpdGsWbMM7WXv3bunGWSXc+fOHc2gkJykpCTNIPvzgNGDqGDT5g9Vq1alI0eO5NvPYxiGYRiGYRiGYfIPQRCOElFVPZ16YyyGYRiGYRiGYRiG+RfggyjDMAzDMAzDMAyTr/BBlGEYhmEYhmEYhslX+CAqIzMzk7Ws/T+vJaKn0mZlZRnSWq1Ww9rc3FxkZ2cb0ubk5ODJkyeGtTk5OYa0T548QW5uriFtdnb2U2mtVqshbVZW1lNpjdb0P402MzPzudAahbWsfVG1/6b3GvXT3Nzcf81P/y3vNeqRT+u9/4afPi/eaxTW/t/XPu+4hISE5NsPi4iICOnQoUO+/byn5fLly6hTpw5iY2Ph5uaGwMBAuLi4KGrPnDmDBg0a4Pr16/Dw8EBAQAAKFFA+1x89ehRNmjRBfHw8PD09NbX79u2DyWRCQkICPD09UaZMGVVtdHQ0LBYLbt68CW9vb5QpUwaCIChqN27ciK+++gqJiYnw8fGBv7+/qvavv/7Ct99+i6SkJBQuXBilS5dW1S5ZsgQdOnTArVu3UKRIEZQqVUpVO3fuXHTt2hXJyckoWrQoSpYsqaqdPn06fvvtN9y5cwfFihWDn5+fqnbChAno378/UlJS4OvrC19fX1XtyJEjMWTIENy9exclSpSAr6+vog4Ahg4ditDQUNy7dw9+fn4oXry4qnbAgAEYPXo07t+/j5IlS6JYsWKq2p49e2LSpEl48OABSpUqhaJFi6pqu3TpgunTp+Phw4coXbo0ihQpoqr96aefMHv2bKSnp6N06dIoXLiwok4QBHzzzTdYsGABHj16BH9/fxQqVEhV+8UXX2DZsmV49OgRypQpAx8fH9XP8Omnn+Kvv/7C48ePERAQAG9vb9V/b4sWLbB+/XpkZmYiMDAQXl5eqv/exo0bY8uWLcjOzkZgYCA8PT0VdUSEevXqYceOHZLWw8NDUWu1WlGrVi3ExMQgJycHQUFBcHd3V9Tm5OSgRo0a2L9/P3JzczW1WVlZqF69Og4fPgwiQmBgINzc3BS1GRkZqFatGo4fPw4ACAoKgqurq6L24cOHqFatGk6fPg1BEDS1qampqFatGs6dO4cCBQogKCgIBQsWVNTevn0b1atXx8WLF+Hi4qKpvXHjBmrWrInLly/D1dVV0yOvXr2K2rVr4+rVq7p+eu7cOdSvXx9xcXFwd3dHYGCgqu8dP35c8lM97z1w4ABatGiBGzduwMvLS9NPd+7ciVatWiEhIUHXTzdv3owvvvjCkJ+uXbsW7du3R1JSEgoVKqSp/fPPP/HTTz8Z8tP58+cjODgYt2/f1vXTmTNnokePHrhz5w6KFi2q6aeTJ09Gnz59kJKSguLFi6NEiRKq2jFjxmDQoEGS95YoUUJRBwDDhw/HsGHDkJqaquunv//+O0aNGoX79+/Dz89P00979+6NCRMmGPLTbt26YerUqXjw4IGun3bs2BGRkZFIS0uDv7+/qp8CwHfffYd58+YhPT0dZcqU0fTTL7/8EkuXLkVGRoamnwqCgNatW2PlypW6fgoAJpMJ69atQ2ZmJgICAlT9VBAEfPTRR/j777+RlZWl66cNGjRAdHS0Ie+tXbs2du3ahZycHE3vzcnJQc2aNbFv3z5dP83Ozkb16tVx6NAhWK1WBAUFafpp9erVcezYMRCRpjY9PR1Vq1bFqVOndP303r17qFq1Ks6ePavrp3fu3EG1atVw4cIFXT+9efMmatSogUuXLqFgwYIICgpS9chr166hVq1ahvz0woULqFu3Lq5duwZ3d3cEBASoak+dOoVGjRrh+vXrklbNIw8dOoRmzZrhxo0bunvZ3bt345NPPpH81N/fX1W7detWfP7557h586aun65fvx5ff/01kpKS4OPjo7k/XbFiBX744QfcunVLdy+7aNEidOrUyZD3zpo1C926dUNycrLu/nTKlCno3bs37ty5o+un48aNw8CBA3H37l1dPw0NDcXQoUORmpqqu5d9VgwdOjQpJCQkQldo5Gndf2o87+1b9u3bR2XLlpUawxYtWlS1t2BMTIxdc3ut3oI7duywa24v9hZU6oW1bds2Kl68uF2TXrXegn///bddc3uxSa9Sb8F169aRp6enpPX395d6Czo+I79q1Spyc3NzatK7fv16p2fk//zzT7vm9lq9BRcsWGDXjLlcuXLUpUsXxd6CYr8scWj1FpwyZYqd9tVXX1XtLTh27Fg7rdhbcMeOHU5Pww8fPtxOK/bCUnpG/vfff7fTavUW7NWrl5327bffVu0t6Ni4Wau34I8//minlfcWlD/Lnpub69SMWa23YFZWll1ze63eghkZGXbN7cXegmFhYU4tkR4+fEiffvqppNXqLZiammrX3F6rt2BycrJdc3ut3oKJiYl2ze1dXV2l3oKOz8jHx8fbNbfX6i147do1u+b27u7u1KxZM8XegpcvX6bq1atLWrG34PTp051aIp0/f96uub28t6BjW47Tp0/bNbf39vZW7S14/PhxeuONNyStVm/Bw4cP2zW3F3u1KrVEOnDggF1ze63egjExMRQQEODkp0otkXbu3GnX3F6rt2BUVJRdc3ut3oKbN2+2a24v7y3o6KcbNmywa26v1Vtw9erV5OHhIWnF3oJKLZGWLVtm56fy3oKOfrpw4UI7P5X3FnT009mzZ9s1t3/55Zel3oKOfir20haHvLego59OmDDBTqvVW3DEiBFOftqrVy/FlkiDBw+202r1FuzTp4+Tn6r1FuzWrZudVqu3YIcOHey0Yp9spZZI33zzjZ1WrbdgdnY2ffXVV3ba6tWrK/YWfPz4sV1ze63egmlpaXbN7bV6C967d4/MZrOdn9atW5fGjBnj1BLpzp071KxZMztt/fr1ady4cU5+euvWLWrcuLGd9zZq1IgmTJjg1BLpxo0bVK9ePTvv/eijj2jy5MlOfhoXF0e1atWy895mzZrRlClTnPz0ypUr9MEHH9j5aYsWLRT99MKFC/T+++/b+anJZKKZM2c6teU4c+YMVa5cWdJ6eXnRJ598QrNmzXLy05MnT1KlSpXsvLdVq1aKLeaOHDlCr732mqQtVKgQffbZZzR//nynlkgHDx6kl19+2c5727Rpo9gSae/evRQUFCRpixYtSl9++aWin+7atYv8/f3t/LRdu3b0559/OvlpdHQ0lShRwslPly9f7uSnW7ZsoaJFi0paPz8/+u677xRbIm3cuJF8fHyc/HT16tVOfrpmzRo7P/X396eff/5Z0U9XrFhBrq6uklbcyyq1RFqyZAm5uLjY+WlwcLBii7m5c+fa+elLL71EXbt2VWyJJPbSFkf58uWpe/fuii3mJk2a5OSnPXr0UGyJNGrUKDtthQoVVP30WQHuI/r0OC6U8vHhhx/Srl27JO2QIUMUdYIgUN26dWnfvn2SVmyS7jgKFChADRo0oEOHDklasUm6krZx48Z09OhRSeu4UMoXi2bNmtGpU6ckreNCKV8sTCYTnT17VtK2adNGUevq6kqffvqpXQ+pli1bKmrd3NzIYrHYLUBNmjRR1Lq7u9MXX3xh12dPvumXDw8PD2rXrp1dX6hq1aopar28vOibb76xW1Tkm3P58Pb2ph9//NGu15N8gZCPQoUKUceOHe023nLTl4/ChQtTly5d7Dbefn5+itoiRYpQ9+7d7QIZcnOWj2LFilGvXr3szF++gZUPX19f6tevn7SZzsnJUf177ufnR4MGDZIMPT09XVVbqlQpGjp0qGTSKSkpqlp/f38aMWKEZNIJCQmq2oCAABozZoxkvJcvX1bVBgUF0cSJEyXjPX36tKq2XLlyNHXqVGlzKjZJVxrly5eniIgIacMpNklXGq+++irNnTtX0opN0pVGhQoVaOHChdJmT2ySrjQqVapEy5Ytk7TLly9X1b799tu0atUqSbtgwQJV7bvvvkvr1q2T/t5ERESoat9//336+++/Je3kyZNVtdWrV6eoqChJKzZJVxo1a9aknTt3StqhQ4cq6gRBoDp16tDevXslbf/+/VW19evXpwMHDkjaHj16KGqV/LRz586KWhcXF2ratCmdOHFC0opN0h1HwYIFqUWLFnTmzBlJKzZJdxyurq7UsmVLu2CKPDgjH25ubtS6dWu7nnzyA4J8uLu7U5s2bex6nNavX19R6+HhQV999ZWdn9aoUUNR6+np6eSn7777rqLW29ubvv/+e7tNujzYIR8+Pj7UoUMHu413uXLlFLWFCxem4OBgu423PCghH0p+Kg80yEexYsWoZ8+edn7q7u6uqPX19aW+ffvaBSfU/p6XKFGCfv/9d8lPMzIyVLUlS5akkJAQaYOcmpqqqi1dujSFhoZKfpqYmKiqLVOmDI0ePVra9MbGxqpqAwMDacKECZL3njt3TlVbtmxZCg8Pl7z32LFjqtqXX36ZZs6cKXnv3r17VbWvvPIKzZ49W/LT6OhoVW2FChVowYIFku9t3LhRVVuxYkVaunSppF21apWq9q233qKVK1dK2sWLF6tq33nnHVq7dq2knT17tqr2vffeo40bN0p/bxyD6PJRrVo12rp1q6R1DKLLR82aNWnHjh2S1jGILg5BEKh27doUExMjaR2D6HJtvXr1aP/+/ZLWMYgujgIFClDDhg3p8OHDktYxiC4OFxcXatKkCR0/flzSOgbRxSH66enTpyVtu3btVLVms5nOnz8vaS0Wi6LW1dWVWrVqZRdMkQe75cPNzY0+++wzu+C0PIAtHx4eHtS2bVu7AIk8KC0fnp6e9PXXX9sFSN577z1FrZeXF3333Xd2AWd5sEM+fHx86OeffzbUi/TfBnwQfXoSExOliJOXl5dqBoHItpEWI/haGQQiouvXr0sZ0UKFCtHnn3+u2oj26tWrUkZUK4NARHTx4kUpIyrPyDpGvIhsET0xI6qVQSCyZUjEjGiJEiXo22+/VcwgENkabosHIK0MAhHRnj17pAh+6dKl6aefflLMIBARbd++XfrFEjMI69evV2wCvmnTJkkrzyAoNQH/66+/JK2YQdi8ebNiE/AlS5ZI2pdeekk1g0BENGfOHLuFVMzIKmnlGQetDAIR0fjx4yWtVkaWiCg0NFTSamUQrFarXcZBzMgqZRBycnKoX79+douuWgbhyZMndht/MSOrlEHIysqyW6jEDIJjRpbIlhn46aefpMXxgw8+UMwgENk2emK2V55BcMzIEtkO2V988YW0kNauXVsxg0Bky+CKGQd5BuHChQtO2gcPHlCLFi0krVoGgciWnRCzCGIGYeLEiU4ZBCKiu3fvUp06daSFVMwgyA8cIikpKVKmVcwgTJ061S7YI5KcnCwdKNzd3VUzCES2rIe4AMozskqNvZOSkuiVV16R/FQtg0Bk81MxmOPt7U2tW7dWzCAQ2fy0dOnSkp+KGQQlP42NjZUyoqKfKmUQiIguXbokHVS0MghEtg26mBEtVqyYlEFwvA1DZMuQiBF8X19f1YwskS04IvqpVgaByHaDR/TTUqVKqWZkiWy3csQIvlYGgciWyRB/LwMCAqhTp06KGQQiorVr10raoKAg1QwCkS3b6+inShkEIqJ58+ZJWq0MApF9xkH0U6UMAhHRxIkTJa1eBmHkyJF2ftqnTx+KiYlx8kgiopCQEEn71ltvqWZkc3NzacCAAXZ+OnDgQDpw4ICin/bs2VPSamVks7KyqGvXrnZ+GhIS4pSRJSLKzMy0C2KLGdnjx48r+ul3330n+WmNGjUoNDTUKSNLRPTo0SMp6CLPyJ45c8ZJm5aWRq1bt5a0derUodGjRztlZIlsfmoymez8dOzYsXYBcZF79+7RRx99JPlpw4YNacKECXYBHJHU1FQpKyv66aRJk5xuwxDZ/LRmzZqSnzZt2pSmTJmi6Kd37tyRDhTu7u7UvHlzmjZtml2wR+T27dv05ptvSocYMSObkJDgpE1KSpKC46KfRkZGOt2GISK6efOmFMyRZ2TlgXaR+Ph4KSPq4+NDFouF5s2b55SRJbLd9hEzovKMrJL3Xr58WcqIFilSRPV2IZHtto8YdBf9VOl2IZEt2Cz30/bt29Py5csV97LHjh2TMqKinyrdLiSy3eARM6Li7cLVq1cr7mV3794t+am4l127dq2i927dutXOT9UyskT2gWmt24VEtmyvqC1XrpxqRvZZYvQgqnxx/f9Tbt++jebNm8NkMqFBgwaq9Q2A7W5/q1atYDabUa9ePdX6BgCIj49H27ZtYTabUbduXdWaBQC4fv06vv32W5jNZtSuXVu1ZgEAYmNj0aFDB5jNZtSqVUu1DkHU/vLLLzCbzahRo4am9urVq/jtt99gNpvxwQcfqNYWiNq+ffvCbDajWrVqqjUA4mcYOHAgzGYz3n//fV3tkCFDYDab8d5776neqQds/58NGzYMZrMZ77zzjqY2ISEBw4cPh9lsxttvv62pTUpKwogRI2A2m1GpUiVNbXJyMkaNGgWz2Yw33nhDU3v37l2MHTsWZrMZr7/+uqoOAO7fv4/x48fDbDbj1Vdf1dSmp6dj0qRJMJlMKF++vKY2IyMD4eHhMJlMeOmll1R1BQoUQFZWFqZNmwaTyYSgoCBNbU5ODmbMmAGTyYSAgABVrYuLC4gIERER+Pjjj1GmTBlNrYuLC2bPno2PP/4YpUqV0vwMHh4emDt3Llq0aIGSJUtqan18fLBgwQI0b95csx5DEAQUK1YMixYtQvPmzTXr26xWK0qXLo2lS5eiWbNmmjVrYm3qsmXL0LRpU82atezsbLz22mvo3r07mjRpolqHBtjm96233kK/fv3w0Ucfadb1pqWloWrVqhg6dCgaNWqkWYd279491K5dG6NGjULDhg0163qTk5PRpEkTmEwmNGzYUNNPk5KS0LJlS5jNZtSvX1/TTxMSEtCmTRuYTCbUq1dP10/bt28Ps9mMOnXqaPppXFwcfvrpJ5hMJtSqVUvXe4ODg2E2m1GzZk1dP+3evbvkvXp+2qdPH5jNZlSvXl3TI69evYoBAwbAbDajatWqmtpr165h8ODBMJvNqFKliqY2Li4OQ4cOhdlsxrvvvqvpZTdu3DDsp4mJiQgLC4PZbMabb76pqb19+zZGjRoFk8mEihUrampTUlIwZswYmM1mVKhQQVUH/MdPTSYTXnvtNU1tWloaJk6cCJPJhFdeeUVTm5GRgcmTJ8NsNmv6qSAIePz4MaZOnQqTyYSyZcuqal1cXPDkyRNMnz4dJpMJgYGBmtqn8VNBEDBr1ix8/PHHKF26tKbWzc3NsJ96e3tj/vz5aNGihaafAkDRokWxaNEiNGvWTLO+jYjg5+eHJUuWoFmzZpr1wmK9qVE/feWVV9C1a1c0adJEswY4MzMTFStWRK9evfDRRx9pem96ejree+89DB48GI0bN9b00/v376NWrVoYMWIEGjVqpOmnKSkpaNSoESZOnIgGDRqo1uoCwK1bt/Dxxx9Lfqq3l/3ss8+k/aneXrZdu3aSn2p5b1xcHH744Qdpf6rnp506dYLZbMaHH374j/nplStX0KtXL8lP9by3f//+MJlMhvaygwYNkvanRvzUZDKhSpUqml4WHx+PP/74A2azGZUrV9bU3rx5E6GhoTCbzXjrrbc0tc87Ahl8heufoGrVqnTkyJF8+3kMwzAMwzAMwzBM/iEIwlEiqqqn4/YtDMMwDMMwDMMwTL7CB1GGYRiGYRiGYRgmX+GDKMMwDMMwDMMwDJOv/E8HUUEQmgmCcFEQhCuCIPT7pz4UwzAMwzAMwzAM83+X//ogKgiCC4CpAJoDqATgS0EQKv1TH4xhGIZhGIZhGIb5v8n/khGtDuAKEcUSUTaAPwF88s98LIZhGIZhGIZhGOb/Kv/LQTQAwA3Z1wl533shSUxMROfOnXH16lVd7fXr19G5c2fEx8fraq9evYrOnTsjMTFRV3v+/HkEBwfjzp07utpTp04hODgY9+7d09UeO3YMXbp0QVpamq724MGD+OWXX5CRkaGr3bNnD7p3746srCxd7c6dO9GjRw88efJEV7t161b06tULubm5utpNmzahb9++MNKGaO3atRg4cKCuDgBWrlyJkJAQQ9qlS5di+PDhhrQLFy7EqFGjDGlnz56N8ePHG9LOnDkT4eHhhrRTpkzBjBkzDGknTJiA2bNnG9KOGTMG8+fPN6QNDQ3FkiVLDGmHDh2KFStWGNL+/vvvWLNmja6OiNCvXz9s3LhRV2u1WtG7d29s2bJFV5uTk4PffvsN27dv19VmZWWhe/fuiImJ0dU+fvwYv/zyCw4cOKCrTU9PR9euXXH06FFd7f3799GlSxecOnVKV5uSkoLg4GCcO3dOV3vr1i0EBwfj8uXLutr4+Hh07twZcXFxutrY2Fh07twZN2/e1NVevHgRwcHBSE5O1tWeOXMGwcHBSE1N1dWeOHECXbp0wcOHD3W1hw4dQteuXfHo0SNd7b59+9CtWzdkZmbqanft2mXYT6OiotCzZ09Dfvr333+jT58+sFqtutr169djwIABujoAWLVqFQYPHmxIu2zZMvzxxx+GtIsWLcLIkSMNaefOnYtx48YZ0kZERGDSpEmGtNOmTcO0adMMaSdOnIjIyEhD2rFjx2LevHmGtCNGjMDixYsNaYcNG4Zly5YZ0g4ePBh//fWXro6I0L9/f6xfv15Xa7Va0adPH2zevFlXm5OTg549eyI6OlpXm52djV9//RW7d+/W1WZmZqJbt27Yt2+frvbRo0fo2rUrDh8+rKt98OABunTpghMnTuhq7969i+DgYJw9e1ZXe/v2bQQHB+PSpUu62oSEBHTu3BnXrl3T1V67dg2dO3fGjRs3dLWXL19GcHAwbt26pas9e/YsgoODkZKSoqs9efIkunTpggcPHuhqjxw5gq5duyI9PV1Xu3//fnTr1g2PHz/W1cbExODXX39Fdna2rjY6Ohq//fYbcnJydLVbtmxB7969Dfnphg0b0L9/f0N72dWrV2PQoEG6uhcGIvqvBoDPAcySfd0eQLiCrgOAIwCOlC1blp5X5syZQwBo/Pjxutpp06YRAJo2bZqudvz48QSA5syZo6sNDQ0lALRkyRJd7aBBgwgA/fXXX7ra3r17EwD6+++/dbW//PILAaAdO3boan/++WcCQPv379fVfv311wSAjh8/rqv97LPPCACdP39eV2symahAgQJ09epVXW3jxo3JxcWFbt68qautXbs2ubq6UnJysq62atWq5OHhQffv39fVvvnmm+Tt7U2PHj3S1b7yyitUpEgRysrK0tRZrVYKDAwkPz8/ysnJ0dTm5uZSyZIlKSAggKxWq6Y2OzubihUrRuXLl9f9rBkZGeTj40MVK1bU1T548IA8PDyoSpUqutqUlBRyc3OjmjVr6moTExOpYMGC1LBhQ11tXFwcFShQgFq0aKGrvXjxIgmCQK1bt9bVnjx5kgDQV199pas9ePAgAaAffvhBV7tr1y4CQMHBwbraLVu2EADq2bOnrnbt2rUEgAYOHKirXbZsGQGgP/74Q1c7b948AkBjxozR1c6YMYMAUHh4uK524sSJBIBmzZqlqx05ciQBoEWLFulqQ0JCCACtXLlSV9uvXz8CQBs2bNDVdu/enQBQVFSUrrZjx44EgPbs2aOr/fbbbwkAHT16VFf7xRdfEAA6e/asrvaTTz4hQRDoypUrutomTZooN056AAALhUlEQVSQi4sLxcfH62rr1q1Lrq6udOvWLV1t9erVyd3dnVJTU3W1lStXJi8vL0pPT9fVvv7661S4cGHKzMzU1ZYrV458fX3pyZMnmrrc3FwqXbo0+fv7U25urqY2OzubihcvTuXKldP9+Y8fP6ZChQpRhQoVdLVpaWnk5eVF77zzjq42NTWV3N3d6YMPPtDV3rp1iwoWLEj16tXT1V6/fp0KFChATZs21dVeunSJBEGgTz75RFd7+vRpAkBt27bV1R45coQA0Hfffaer3bNnDwGgTp066Wq3bdtGAOjXX3/V1a5fv54AUL9+/XS1K1asIAA0dOhQXe3ChQsJAI0aNUpXGxkZSQBo0qRJutrw8HACQDNnztTVjh49mgDQ/PnzdbXDhg0jALRs2TJd7YABAwgArVu3Tlf722+/EQDaunWrrjY4OJgA0O7du3W133//PQGgQ4cO6Wq//PJLAkCnTp3S1bZq1YoEQaCLFy/qaps3b04FChSg69ev62obNGhABQsWpKSkJF3tswTAETJynjQiUvwvAjUBbJF93R9Af63/zvvvv//v/y//L8nOzqZt27ZRRkaGrjYzM5O2bdtmaEHLyMigbdu2UXZ2tq42LS2NoqKidA8TRLbNfFRUlO5hgojo3r17FB0drasjIrp7966hQygR0Z07d2jXrl2GtLdv36aYmBhD2sTERNq7d68hbUJCgqGDMBFRfHy8IaMhsh1Ujhw5YkgbGxtLx44dM6S9cuUKnThxwpD24sWLhsyOiOj8+fOGNppERGfPnjV0yCeybQSMmCiR7RB2+fJlQ9pjx44ZCh4Q2TYY165dM6Q9dOiQoY0xEdGBAwcoISHBkHbfvn2UmJhoSLtnzx5DG24i2wHTSLCDiGjHjh2UkpJiSLt9+3a6d++ers5qtVJ0dDQ9ePBAV5ubm0tRUVGUlpamq33y5AlFRUUZCriIfvr48WNd7dP4aXp6umE/ffjwIUVFRekeJoiI7t+/T9HR0Ya89+7du7R9+3ZdHZHNT3fu3GlI+zR+mpSUZNhPb968adhPb9y4QQcPHjSkjYuLo8OHDxvSxsbGGjpgEz2dn166dMmwn164cIHOnDljSHvu3Dk6d+6cIe3p06fpwoULhrQnT56kS5cuGdIeP37csJ8ePXrUsJ8ePnzY0MaYyBZYu3HjhiHtvn37DAWEiWx+anTDvXv3bsN+unPnzqfyUyOBEdFPjQSlRT99+PChrlb0UyMBl6ysLMN++vjxY9q2bZtusJuI6NGjRxQVFaUbnCH69/w0NTXVsJ+mpKQY9tPk5GRDB1YiW4DGSLCQyOan+/btM6S9ceMGHThwwJD2+vXrhv30WWL0ICqQgTSwEoIgFARwCUAjADcBHAbwFRGp3jOoWrUqHTly5L/6eQzDMAzDMAzDMMzzjSAIR4moqp6u4H/7A4goRxCErgC2AHABMEfrEMowDMMwDMMwDMMwwP9wEAUAItoEYNM/9FkYhmEYhmEYhmGY/w/4X17NZRiGYRiGYRiGYZinhg+iDMMwDMMwDMMwTL7CB1GGYRiGYRiGYRgmX+GDKMMwDMMwDMMwDJOv8EGUYRiGYRiGYRiGyVf4IMowDMMwDMMwDMPkK3wQZRiGYRiGYRiGYfIVPogyDMMwDMMwDMMw+QofRBmGYRiGYRiGYZh8hQ+iDMMwDMMwDMMwTL7CB1GGYRiGYRiGYRgmX+GDKMMwDMMwDMMwDJOv8EGUYRiGYRiGYRiGyVf4IMowDMMwDMMwDMPkK3wQZRiGYRiGYRiGYfIVPogyDMMwDMMwDMMw+QofRBmGYRiGYRiGYZh8hQ+iDMMwDMMwDMMwTL7CB1GGYRiGYRiGYRgmX+GDKMMwDMMwDMMwDJOv8EGUYRiGYRiGYRiGyVf4IMowDMMwDMMwDMPkK3wQZRiGYRiGYRiGYfIVPogyDMMwDMMwDMMw+QofRBmGYRiGYRiGYZh8hQ+iDMMwDMMwDMMwTL7CB1GGYRiGYRiGYRgmXxGIKP9+mCDcAXA9337gf0cJACnP+kMwTwXP2YsJz9uLCc/biwfP2YsJz9uLCc/biwfP2T9POSLy0xPl60H0RUAQhCNEVPVZfw7GODxnLyY8by8mPG8vHjxnLyY8by8mPG8vHjxnzw6+msswDMMwDMMwDMPkK3wQZRiGYRiGYRiGYfIVPog6E/GsPwDz1PCcvZjwvL2Y8Ly9ePCcvZjwvL2Y8Ly9ePCcPSO4RpRhGIZhGIZhGIbJVzgjyjAMwzAMwzAMw+QrfBDNQxCEZoIgXBQE4YogCP2e9edhlBEEYY4gCMmCIJyRfa+4IAjbBEG4nPfPYs/yMzL2CIIQJAjCDkEQzguCcFYQhO553+d5e44RBMFDEIRDgiCczJu3oXnff1kQhIN587ZMEAS3Z/1ZGXsEQXARBOG4IAgb8r7mOXvOEQQhThCE04IgnBAE4Uje99gjn3MEQSgqCMJKQRAu5K1xNXnenm8EQaiQ93smjoeCIPzK8/Zs4IMobIs2gKkAmgOoBOBLQRAqPdtPxagwD0Azh+/1AxBNRK8BiM77mnl+yAHQk4gqAqgBoEve7xfP2/NNFoCGRPQOgHcBNBMEoQaAUQAm5M3bPQA/PsPPyCjTHcB52dc8Zy8GDYjoXVkbCfbI559JADYT0RsA3oHt947n7TmGiC7m/Z69C+B9ABkAVoPn7ZnAB1Eb1QFcIaJYIsoG8CeAT57xZ2IUIKLdAFIdvv0JgPl5f54P4NN8/VCMJkSURETH8v6cBttCHQCet+caspGe96Vr3iAADQGszPs+z9tzhiAIgQA+BjAr72sBPGcvKuyRzzGCIBQGUBfAbAAgomwiug+etxeJRgCuEtF18Lw9E/ggaiMAwA3Z1wl532NeDEoRURJgO/QAKPmMPw+jgiAILwGoAuAgeN6ee/KueJ4AkAxgG4CrAO4TUU6ehL3y+WMigD4ArHlf+4Ln7EWAAGwVBOGoIAgd8r7HHvl8Ux7AHQBz867CzxIEwRs8by8SbQEszfszz9szgA+iNgSF7/FzwgzzDyIIgg+AVQB+JaKHz/rzMPoQUW7e9aVA2G6OVFSS5e+nYtQQBMEEIJmIjsq/rSDlOXv+qEVE78FWItRFEIS6z/oDMboUBPAegOlEVAXAI/B1zheGvFr5lgBWPOvP8v8zfBC1kQAgSPZ1IIDEZ/RZmKfntiAI/gCQ98/kZ/x5GAcEQXCF7RC6mIj+yvs2z9sLQt51s52w1fgWFQShYN5/xF75fFELQEtBEOJgKzFpCFuGlOfsOYeIEvP+mQxbvVp1sEc+7yQASCCig3lfr4TtYMrz9mLQHMAxIrqd9zXP2zOAD6I2DgN4Le9lQTfYUvXrnvFnYoyzDsC3eX/+FsDaZ/hZGAfyatRmAzhPRONl/xHP23OMIAh+giAUzfuzJ4DGsNX37gDwWZ6M5+05goj6E1EgEb0E2zq2nYjagefsuUYQBG9BEAqJfwbQBMAZsEc+1xDRLQA3BEGokPetRgDOgeftReFL/OdaLsDz9kwQiPiGDgAIgtACtsixC4A5RBT6jD8So4AgCEsB1AdQAsBtAEMArAGwHEBZAPEAPicixweNmGeEIAi1AcQAOI3/1K0NgK1OlOftOUUQhMqwPdjgAlvQcjkRDRMEoTxs2bbiAI4D+JqIsp7dJ2WUEAShPoBeRGTiOXu+yZuf1XlfFgSwhIhCBUHwBXvkc40gCO/C9jCYG4BYAN8jzy/B8/bcIgiCF2xvw5Qnogd53+Pft2cAH0QZhmEYhmEYhmGYfIWv5jIMwzAMwzAMwzD5Ch9EGYZhGIZhGIZhmHyFD6IMwzAMwzAMwzBMvsIHUYZhGIZhGIZhGCZf4YMowzAMwzAMwzAMk6/wQZRhGIZhGIZhGIbJV/ggyjAMwzAMwzAMw+QrfBBlGIZhGIZhGIZh8pX/B6a9K8V1SEJxAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "channel_scenario.run(10000)\n",
+    "plt.vector_field(channel_scenario.velocity[:, :], step=4);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a 2D [Poiseuille flow](https://en.wikipedia.org/wiki/Hagen%E2%80%93Poiseuille_equation) where a parabolic profile of the x velocity is expected for the stationary case."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "vel_profile = channel_scenario.velocity[0.5, :, 0]\n",
+    "plt.plot(vel_profile);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The stationary state is not yet reached, you can run more time steps and see how the profile gets closer to a parabola.\n",
+    "\n",
+    "\n",
+    "### Modifying boundaries\n",
+    "\n",
+    "Lets first view the current boundary configuration:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x216 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def draw_boundary_setup():\n",
+    "    fig = plt.figure(figsize=(10.0, 3.0))\n",
+    "    plt.boundary_handling(channel_scenario.boundary_handling)\n",
+    "    plt.axis('off');\n",
+    "draw_boundary_setup()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In above plot you can see that the *no-slip* boundaries at the top and bottom of the channel, otherwise the channel is empty.\n",
+    "\n",
+    "Since an empty channel is pretty boring, lets put an obstacle in it. We start with the simplest option: a rectangular, solid block. The rectangle is specified as a slice, similar to advanced *numpy* indexing. The ``make_slice`` function can also take ``float`` as indices for specifying the slice relative to the domain size. The following cell puts an obstacle into the domain that has one third of the channel height.\n",
+    "Additionally we have to pass a function that defines what should happen at the boundary (here ``noSlip``).\n",
+    "By default, the name of the function is also the boundary name."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.boundaries import NoSlip\n",
+    "\n",
+    "wall = NoSlip()\n",
+    "channel_scenario.boundary_handling.set_boundary(wall, make_slice[0.2:0.25, 0:0.333])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When plotting the boundary handling again, we see the rectangular obstacle:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x216 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "draw_boundary_setup()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When setting and plotting boundaries the domain is actually 2 cells larger than originally specified. These so called 'ghost layer' slices are one cell thick and are automatically added at each domain boundary. They can be used to set boundaries and are also used for communication when running distributed memory parallel simulations.\n",
+    "When specifying the slice, keep in mind that the domain is actually slightly larger. When plotting the simulation results the ghost layers are automatically removed.\n",
+    "\n",
+    "To convert a cell back to ``domain``, the same method can be used. To demonstrate this, we cut a piece out of the obstacle:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x216 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "channel_scenario.boundary_handling.set_boundary('domain', make_slice[0.2:0.235, 0.0333:0.3])\n",
+    "fig = plt.figure(figsize=(10.0, 3.0))\n",
+    "plt.boundary_handling(channel_scenario.boundary_handling)\n",
+    "plt.axis('off');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To add non-rectangular obstacles one can also pass a mask array, which is ``True`` for cells where the boundary should be set. This is demonstrated in the next cell, where a sphere is placed in the channel."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x216 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def set_sphere(x, y):\n",
+    "    shape = channel_scenario.domain_size\n",
+    "    mid = (0.5 * shape[0], 0.5 * shape[1])\n",
+    "    radius = 13\n",
+    "    return (x-mid[0])**2 + (y-mid[1])**2 < radius**2\n",
+    "\n",
+    "channel_scenario.boundary_handling.set_boundary(wall, mask_callback=set_sphere)\n",
+    "draw_boundary_setup()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we run the simulation to see the flow aroung the obstacles:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "channel_scenario.run(10000)\n",
+    "plt.vector_field_magnitude(channel_scenario.velocity[:,:]);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "###  Variations to experiment with:\n",
+    "\n",
+    "- increase the Reynolds number. You might also have to increase the resolution, and/or use a more advanced method like cumulant or entropic stabilization\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/doc/notebooks/02_tutorial_boundary_setup.ipynb b/doc/notebooks/02_tutorial_boundary_setup.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..5edd33b9dba75673c1c64c28228aa382af7f68aa
--- /dev/null
+++ b/doc/notebooks/02_tutorial_boundary_setup.ipynb
@@ -0,0 +1,369 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 02: Setting up geometry and boundary conditions\n",
+    "\n",
+    "In this tutorial you will learn how to set up boundaries for your LBM simulation. \n",
+    "We begin with simple setup for parametric geometries, then we'll see how to set up spatially and temporally varying velocity boundary conditions.\n",
+    "\n",
+    "## Geometry Setup\n",
+    "\n",
+    "Lets start with a 3D simulation of a pipe. The flow should be along the x axis, with a circular cross section \n",
+    "in the y-z plane."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "domain_size = (64, 16, 16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sc1 = LatticeBoltzmannStep(domain_size=domain_size, method='srt', relaxation_rate=1.9, force=(1e-6, 0, 0),\n",
+    "                           periodicity=(True, False, False), optimization={'target': 'cpu'})\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For now the flow should be driven by an external force which we already specified. Additionally we have enabled perdiodicity in x direction. Now the circular pipe needs to be created. Therefor we use a mask callback function that gets x,y,z coordiante arrays that have the same shape as the domain. The callback function has to return a boolean array, where the boundary is set in cells that are marked with True."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def pipe_geometry_callback(x, y, z):\n",
+    "    radius = domain_size[1] / 2\n",
+    "    y_mid = domain_size[1] / 2\n",
+    "    z_mid = domain_size[2] / 2\n",
+    "    return (y - y_mid) ** 2 + (z - z_mid) ** 2 > radius ** 2\n",
+    "\n",
+    "\n",
+    "wall = NoSlip()\n",
+    "sc1.boundary_handling.set_boundary(wall, mask_callback=pipe_geometry_callback)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we plot a cross section through our domain to see if the boundary setup worked. A slice has to be passed in to specify which plane of the 3D domain we want to plot."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f360ea22c88>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.boundary_handling(sc1.boundary_handling, make_slice[0.5, :, :])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now the setup is complete. We can run it and look at the velocity profile in the pipe."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f360d3a2208>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sc1.run(500)\n",
+    "plt.scalar_field(sc1.velocity[domain_size[0] // 2, :, :, 0]);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Boundary Setup\n",
+    "\n",
+    "Now instead of creating a periodic, force driven channel, we want to drive the flow with a velocity bounce back boundary condition (UBB) at the inlet and a pressure boundary at the outlet. We want the inflow velocity boundary set up to already prescribe the correct, parabolic flow profile. That means we need a different velocity value at each cell.\n",
+    "\n",
+    "Again, we set up a scenario, but this time without external force and without periodicity. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sc2 = LatticeBoltzmannStep(domain_size=domain_size, method='srt', relaxation_rate=1.9,\n",
+    "                           optimization={'target': 'cpu'},\n",
+    "                           #optimization={'target': 'gpu', 'gpu_indexing_params': {'block_size': (16, 8, 2)}}\n",
+    "                           )\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now another callback function is required to specify the velocities. This callback gets a boundaryData object, that can be used to get an array of `linkPositions`, `fluidCellPositions` and `boundaryCellPositions` of all boundary links. The object also behaves like a dict where the boundary data can be queried and set by name.\n",
+    "Which data one can set, and how its called depends on the concrete boundary condition. The UBB has `vel_0` until `vel_2` data for the x,y and z components of the velocity.\n",
+    "\n",
+    "This example also demonstrates how to change boundary parameters during simulation. Here we introduced an activate flag: when True a parabolic inflow is set, when False no inflow velocity is prescribed. \n",
+    "We'll see later how this is used to turn the inflow on and off. With this technique also time dependent boundary information can be set. Reconfiguring the boundary is costly when running GPU simulations, since the data has to be transferred from CPU to GPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "512"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def velocity_info_callback(boundary_data, activate=True, **_):\n",
+    "    boundary_data['vel_1'] = 0\n",
+    "    boundary_data['vel_2'] = 0\n",
+    "    \n",
+    "    if activate:\n",
+    "        u_max = 0.1\n",
+    "        y, z = boundary_data.link_positions(1), boundary_data.link_positions(2)\n",
+    "        radius = domain_size[1] // 2\n",
+    "        centered_y = y - radius\n",
+    "        centered_z = z - radius\n",
+    "        dist_to_center = np.sqrt(centered_y**2 + centered_z**2)\n",
+    "        boundary_data['vel_0'] = u_max * (1 - dist_to_center / radius)\n",
+    "    else:\n",
+    "        boundary_data['vel_0'] = 0\n",
+    "    \n",
+    "    \n",
+    "inflow = UBB(velocity_info_callback, dim=sc2.method.dim)\n",
+    "outflow = FixedDensity(1.0)\n",
+    "\n",
+    "sc2.boundary_handling.set_boundary(inflow, make_slice[0, :, :])\n",
+    "sc2.boundary_handling.set_boundary(outflow, make_slice[-1, :, :])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Lastly we can use the callback function from above to set the pipe geometry. This is intentionally done at the end of the setup to overwrite the in- and outflow boundaries in the outermost slices."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "32"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sc2.boundary_handling.set_boundary(wall, mask_callback=pipe_geometry_callback)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To see the full setup, a few slices through the domain are plotted"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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JOsX2MkmnZJ4DwB7RTwAkhX4CAMWhtKUBEXF+M6tOTrgWAEWOfgIgKfQTACgOeb+pEQAAAAAATSGQAgAAAABSQSAFAAAAAKSCQAoAAAAASAWBFAAAAACQCgIpAAAAACAVBFIAAAAAQCoIpAAAAACAVBBIAQAAAACpIJACAAAAAFJBIAUAAAAApIJACgAAAABIBYEUAAAAAJCKnAKp7a/ZXmR7oe2ZtrslVRiAjoV+AiAp9BMAKBxZB1Lb/SRdJakyIkZKKpE0IanCAHQc9BMASaGfAEBhyfWU3VJJ+9guldRd0prcSwLQQdFPACSFfgIABSLrQBoRqyXdIelNSWslbYmIJxuPsz3ZdpXtqurq6uwrBVC06CcAktKafkIvAYD2I5dTdg+QdI6kwyUdKmlf2xc2HhcR0yKiMiIqy8rKsq8UQNGinwBISmv6Cb0EANqPXE7Z/aSkv0VEdUTskvSYpI8lUxaADoZ+AiAp9BMAKCC5BNI3JX3UdnfblnSypCXJlAWgg6GfAEgK/QQACkgu15A+L+kRSS9KeiWzrWkJ1QWgA6GfAEgK/QQACktpLi+OiG9L+nZCtQDowOgnAJJCPwGAwpHrx74AAAAAAJAVAikAAAAAIBUEUgAAAABAKgikAAAAAIBUEEgBAAAAAKkgkAIAAAAAUkEgBQAAAACkgkAKAAAAAEgFgRQAAAAAkAoCKQAAAAAgFQRSAAAAAEAqCKQAAAAAgFTkFEht72/7Eduv2l5i+7ikCgPQsdBPACSFfgIAhaM0x9f/UNJvI+L/s91FUvcEagLQMdFPACSFfgIABSLrQGp7P0nHS5okSRHxnqT3kikLQEdCPwGQFPoJABSWXE7ZHSSpWtL9tl+yfa/tfROqC0DHQj8BkBT6CQAUkFwCaamkf5B0d0QcI+ldSdc3HmR7su0q21XV1dU57A5AEaOfAEhKi/2EXgIA7UcugXSVpFUR8Xzm+SOq+w/gAyJiWkRURkRlWVlZDrsDUMToJwCS0mI/oZcAQPuRdSCNiHWSVtoemll0sqTFiVQFoEOhnwBICv0EAApLrnfZ/bKkhzJ3sFsu6eLcSwLQQdFPACSFfgIABSKnQBoR8yVVJlQLgA6MfgIgKfQTACgcuVxDCgAAAABA1nI9ZbfdmrqrotVjp3RemsdKgDpt+ZlE+3LjoNWtHnvr8n55rASo05afSbQfT4+d2uqx456ZksdKgDpt+ZkE8oUZUgAAAABAKgikAAAAAIBUEEgBAAAAAKkgkAIAAAAAUkEgBQAAAACkgkAKAAAAAEgFgRQAAAAAkAoCKQAAAAAgFQRSAAAAAEAqCKQAAAAAgFQQSAEAAAAAqcg5kNousf2S7VlJFASg46KfAEgK/QQACkMSM6RfkbQkge0AAP0EQFLoJwBQAHIKpLYPk3SGpHuTKQdAR0U/AZAU+gkAFI5cZ0h/IOkbkmoTqAVAx0Y/AZAU+gkAFIisA6ntMyWtj4h5LYybbLvKdlV1dXW2uwNQxOgnAJLSmn5CLwGA9iOXGdKxks62vULSw5JOsv3TxoMiYlpEVEZEZVlZWQ67A1DE6CcAktJiP6GXAED7kXUgjYgbIuKwiCiXNEHSHyLiwsQqA9Bh0E8AJIV+AgCFhc8hBQAAAACkojSJjUTEnyT9KYltAejY6CcAkkI/AYD2jxlSAAAAAEAqEpkhLXRTd1W0euyUzkvzWAkKTVt+dtAx3DhodavH3rq8Xx4rQaFpy88Oit/TY6e2euy4Z6bksRIUmrb87ADtATOkAAAAAIBUEEgBAAAAAKkgkAIAAAAAUkEgBQAAAACkgkAKAAAAAEgFgRQAAAAAkAoCKQAAAAAgFQRSAAAAAEAqCKQAAAAAgFQQSAEAAAAAqShNu4BCM3VXRavHTum8NI+VIF/a8h4Dubhx0OpWj711eb88VoJ8act7DGTr6bFTWz123DNT8lgJ8qUt7zFQaLKeIbXd3/YfbS+xvcj2V5IsDEDHQT8BkBT6CQAUllxmSGskXRMRL9ruKWme7dkRsTih2gB0HPQTAEmhnwBAAcl6hjQi1kbEi5nH70haIolzygC0Gf0EQFLoJwBQWBK5qZHtcknHSHo+ie0B6LjoJwCSQj8BgPYv50Bqu4ekRyV9NSK2NrF+su0q21XV1dW57g5AEaOfAEjKnvoJvQQA2o+cAqntzqpr9g9FxGNNjYmIaRFRGRGVZWVluewOQBGjnwBISkv9hF4CAO1HLnfZtaT7JC2JiP+TXEkAOhr6CYCk0E8AoLDkMkM6VtIXJZ1ke37m3+kJ1QWgY6GfAEgK/QQACkjWH/sSEU9LcoK1AOig6CcAkkI/AYDCkshddgEAAAAAaKusZ0jRsqm7KvKy3Smdl+Zlu4UmX99foD26cdDqvGz31uV8PKOUv+8v0N48PXZqXrY77pkpedluocnX9xcoZsyQAgAAAABSQSAFAAAAAKSCQAoAAAAASAWBFAAAAACQCgIpAAAAACAVBFIAAAAAQCoIpAAAAACAVBBIAQAAAACpIJACAAAAAFJBIAUAAAAApKI07QLQdlN3VaRdAoAiceOg1WmXAKAIPD12atolAChQOc2Q2h5v+zXbr9u+PqmiAHQ89BMASaGfAEDhyDqQ2i6R9GNJn5I0XNL5tocnVRiAjoN+AiAp9BMAKCy5zJCOkfR6RCyPiPckPSzpnGTKAtDB0E8AJIV+AgAFJJdA2k/SygbPV2WWAUBb0U8AJIV+AgAFJJdA6iaWxYcG2ZNtV9muqq6uzmF3AIoY/QRAUlrsJ/QSAGg/cgmkqyT1b/D8MElrGg+KiGkRURkRlWVlZTnsDkARo58ASEqL/YReAgDtRy6B9L8lHWH7cNtdJE2Q9EQyZQHoYOgnAJJCPwGAApL155BGRI3tKyX9TlKJpOkRsSixygB0GPQTAEmhnwBAYck6kEpSRPxG0m8SqgVAB0Y/AZAU+gkAFI5cTtkFAAAAACBrjvjQjSzztzO7WtIbCW+2t6QNCW+zveDYClOhHdvAiCi4u3rQT9qMYytMhXRs9JIPKqT3rq04tsJUSMdWkP0E2dmrgTQfbFdFRGXadeQDx1aYivnYil0xv3ccW2Eq5mMrdsX83nFshamYjw2FjVN2AQAAAACpIJACAAAAAFJRDIF0WtoF5BHHVpiK+diKXTG/dxxbYSrmYyt2xfzecWyFqZiPDQWs4K8hBQAAAAAUpmKYIQUAAAAAFKCCDqS2x9t+zfbrtq9Pu54k2V5h+xXb821XpV1PLmxPt73e9sIGyw60Pdv2sszXA9KsMVvNHNt3bK/OvHfzbZ+eZo1oHfpJYaCf0E/aO3pJ4SjWfkIvQaEp2EBqu0TSjyV9StJwSefbHp5uVYk7MSKOLoJbdM+QNL7RsuslPRURR0h6KvO8EM3Qh49Nkr6fee+Ojojf7OWa0Eb0k4IyQ/QTtFP0koIzQ8XZT2aIXoICUrCBVNIYSa9HxPKIeE/Sw5LOSbkmNCEi5kra1GjxOZIeyDx+QNKn92pRCWnm2FB46CcFgn6Cdo5eUkCKtZ/QS1BoCjmQ9pO0ssHzVZllxSIkPWl7nu3JaReTB30iYq0kZb4enHI9SbvS9suZ02YK7nSfDoh+UtjoJ2gv6CWFr5j7Cb0E7VIhB1I3sayYbhk8NiL+QXWn/Vxh+/i0C0Kr3S1psKSjJa2VdGe65aAV6Cdor+gnhYVegvaKXoJ2q5AD6SpJ/Rs8P0zSmpRqSVxErMl8XS/pcdWdBlRM3rLdV5IyX9enXE9iIuKtiNgdEbWS7lHxvXfFiH5S2OgnaC/oJYWvKPsJvQTtWSEH0v+WdITtw213kTRB0hMp15QI2/va7ln/WNKpkhbu+VUF5wlJF2UeXyTplynWkqj6/8gyPqPie++KEf2ksNFP0F7QSwpfUfYTegnas9K0C8hWRNTYvlLS7ySVSJoeEYtSLispfSQ9bluqe49+FhG/Tbek7NmeKekTknrbXiXp25Juk/QL25dIelPS59KrMHvNHNsnbB+tutO0VkiaklqBaBX6SeGgn9BP2jN6SWEp1n5CL0GhcUQxXdoAAAAAACgUhXzKLgAAAACggBFIAQAAAACpIJACAAAAAFJBIAUAAAAApIJACgAAAABIBYEUAAAAAJAKAikAAAAAIBUEUgBAUbL9E9v/nHYdAACgeQRSAOgAbF9gu8r2Nttrbf+X7XFp15UU25NsP91wWURcFhH/O62aAABAywikAFDkbF8t6QeSbpXUR9IASf9X0jnNjC/de9UBAICOjEAKAEXMdi9J/yLpioh4LCLejYhdEfGriPh6Zsx3bD9i+6e2t0qaZLur7R/YXpP59wPbXTPje9ueZXuz7U22/2y7U2bddbZX237H9mu2T26mrtNtL86MW2372gbrzrQ9P7P9v9j+SIN1/W0/Zrva9kbbd9k+UtJPJB2XmQHenBk7w/YtDV57qe3XMzU/YfvQBuvC9mW2l9l+2/aPbTvBtwIAADSBQAoAxe04Sd0kPd7CuHMkPSJpf0kPSfqmpI9KOlrSKEljJH0rM/YaSasklaluxvVGSWF7qKQrJR0bET0lnSZpRTP7u0/SlMy4kZL+IEm2/0HSdElTJB0kaaqkJzIBuUTSLElvSCqX1E/SwxGxRNJlkp6NiB4RsX/jndk+SdK/Sfq8pL6ZbTzcaNiZko7NHO/nM/UDAIA8IpACQHE7SNKGiKhpYdyzEfGfEVEbETskfUHSv0TE+oiolnSzpC9mxu5SXagbmJlt/XNEhKTdkrpKGm67c0SsiIi/NrO/XZlx+0XE2xHxYmb5pZKmRsTzEbE7Ih6QtFN14XiMpEMlfT0z0/v3iHi66c1/yBckTY+IFyNip6QbVDejWt5gzG0RsTki3pT0R9WFcQAAkEcEUgAobhsl9W7FdaErGz0/VHWziPXeyCyTpO9Jel3Sk7aX275ekiLidUlflfQdSettP9zwtNhGzpV0uqQ3bM+xfVxm+UBJ12RO192cOf22f2bf/SW90Ypw3ZQPHE9EbFPd96ZfgzHrGjzeLqlHFvsBAABtQCAFgOL2rKS/S/p0C+Oi0fM1qguH9QZkliki3omIayJikKSzJF1df61oRPwsIsZlXhuSbm9yZxH/HRHnSDpY0n9K+kVm1UpJ/xoR+zf41z0iZmbWDWgmXDeuv7EPHI/tfVU3e7y6hdcBAIA8IpACQBGLiC2SbpL0Y9uftt3ddmfbn7L93T28dKakb9kus907s42fSu/fdGhI5qY/W1V3qu5u20Ntn5S5+dHfJe3IrPsA211sf8F2r4jY1WAbknSPpMts/y/X2df2GbZ7SnpB0lpJt2WWd7M9NvO6tyQdZrtLM8fzM0kX2z46U9+tkp6PiBWt+T4CAID8IJACQJGLiP8j6WrV3ZSoWnUzjVeqbmayObdIqpL0sqRXJL2YWSZJR0j6vaRtqpuB/b8R8SfVXT96m6QNqjv99WDV3fCoKV+UtCJzV9/LJF2YqbVKddeR3iXpbdWdGjwps2636mZkh0h6U3U3Vjovs70/SFokaZ3tDU18D56S9M+SHlVdqB0sacIejh8AAOwFrrsPBQAAAAAAexczpAAAAACAVBBIAQAAAACpIJACAAAAAFJBIAUAAAAApIJACgAAAABIRVMfLp43vXv3jvLy8r22v+rq6r22LwAAAKAYlZWV7dX9zZs3b0NE7N2dIjV7NZCWl5erqqpqr+1v2rRpe21fAAAAQDGaPHnyXt2f7Tf26g6RKk7ZBQAAAACkgkAKAAAAAEgFgRQAAAAAkAoCKQAAAAAgFQRSAAAAAEAqCKQAAAAAgFQQSAEAAAAAqSCQAgAAAABSQSAFAAAAAKSiNO0C8mncM1NaPfb0vrPyWAkAAADQfrwx9I+tHjs5j3UAzJACAAAAAFLRYiC1Pd32etsLGy3/su3XbC+y/d38lQgAAAAAKEatmSGdIWl8wwW2T5R0jqSPRMQISXckXxoAAAAAoJi1GEgjYq6kTY0WXy7ptojYmRmzPg+1AQAAAACKWLbXkFZI+rjt523PsX1skkUBAAAAAIpftnfZLZV0gKSPSjpW0i9sD4qIaDzQ9mRlbs41YMCAbOsEAAAAABSZbGdIV0l6LOq8IKlWUu+mBkbEtIj0EWmOAAAei0lEQVSojIjKsrKybOsEAAAAABSZbAPpf0o6SZJsV0jqImlDUkUBAAAAAIpfi6fs2p4p6ROSetteJenbkqZLmp75KJj3JF3U1Om6AAAAAAA0p8VAGhHnN7PqwoRrAQAAAAB0INmesgsAAAAAQE4IpAAAAACAVBBIAQAAAACpIJACAAAAAFJBIAUAAAAApIJACgAAAABIBYEUAAAAAJAKAikAAAAAIBUEUgAAAABAKgikAAAAAIBUEEgBAAAAAKkgkAIAAAAAUkEgBQAAAACkosVAanu67fW2Fzax7lrbYbt3fsoDAAAAABSr1syQzpA0vvFC2/0lnSLpzYRrAgAAAAB0AC0G0oiYK2lTE6u+L+kbkiLpogAAAAAAxS+ra0htny1pdUQsSLgeAAAAAEAHUdrWF9juLumbkk5t5fjJkiZL0oABA9q6OwAAAABAkcpmhnSwpMMlLbC9QtJhkl60fUhTgyNiWkRURkRlWVlZ9pUCAAAAAIpKm2dII+IVSQfXP8+E0sqI2JBgXQAAAACAIteaj32ZKelZSUNtr7J9Sf7LAgAAAAAUuxZnSCPi/BbWlydWDQAAAACgw8jqLrsAAAAAAOSKQAoAAAAASAWBFAAAAACQCgIpAAAAACAVBFIAAAAAQCoIpAAAAACAVBBIAQAAAACpIJACAAAAAFJBIAUAAAAApIJACgAAAABIBYEUAAAAAJAKAikAAAAAIBUEUgAAAABAKloMpLan215ve2GDZd+z/artl20/bnv//JYJAAAAACg2rZkhnSFpfKNlsyWNjIiPSFoq6YaE6wIAAAAAFLkWA2lEzJW0qdGyJyOiJvP0OUmH5aE2AAAAAEARS+Ia0n+U9F8JbAcAAAAA0IHkFEhtf1NSjaSH9jBmsu0q21XV1dW57A4AAAAAUESyDqS2L5J0pqQvREQ0Ny4ipkVEZURUlpWVZbs7AAAAAECRKc3mRbbHS7pO0gkRsT3ZkgAAAAAAHUFrPvZlpqRnJQ21vcr2JZLuktRT0mzb823/JM91AgAAAACKTIszpBFxfhOL78tDLQAAAACADiSJu+wCAAAAANBmBFIAAAAAQCoIpAAAAACAVBBIAQAAAACpIJACAAAAAFJBIAUAAAAApIJACgAAAABIBYEUAAAAAJAKAikAAAAAIBUEUgAAAABAKgikAAAAAIBUEEgBAAAAAKkgkAIAAAAAUtFiILU93fZ62wsbLDvQ9mzbyzJfD8hvmQAAAACAYtOaGdIZksY3Wna9pKci4ghJT2WeAwAAAADQai0G0oiYK2lTo8XnSHog8/gBSZ9OuC4AAAAAQJHL9hrSPhGxVpIyXw9ubqDtybarbFdVV1dnuTsAAAAAQLHJ+02NImJaRFRGRGVZWVm+dwcAAAAAKBDZBtK3bPeVpMzX9cmVBAAAAADoCLINpE9Iuijz+CJJv0ymHAAAAABAR9Gaj32ZKelZSUNtr7J9iaTbJJ1ie5mkUzLPAQAAAABotdKWBkTE+c2sOjnhWgAAAAAAHUjeb2oEAAAAAEBTCKQAAAAAgFQQSAEAAAAAqSCQAgAAAABSQSAFAAAAAKSCQAoAAAAASAWBFAAAAACQCgIpAAAAACAVBFIAAAAAQCoIpAAAAACAVBBIAQAAAACpKE27AAAAAABIyrx58w4uLS29V9JIMQGXtlpJC2tqav5p9OjR65saQCAFAAAAUDRKS0vvPeSQQ44sKyt7u1OnTpF2PR1ZbW2tq6urh69bt+5eSWc3NSanvxjY/prtRbYX2p5pu1su2wMAAACAHI0sKyvbShhNX6dOnaKsrGyL6marmx6T7cZt95N0laTKiBgpqUTShGy3BwAAAAAJ6EQYbT8y70WzuTPXc6pLJe1ju1RSd0lrctweAAAAABSNq6+++tCbbrqpT762f8IJJwzZsGFDSb62n29ZX0MaEatt3yHpTUk7JD0ZEU82Hmd7sqTJkjRgwIBsdwcAAAAAbXb0vzw5avP2XYndO2f/7p1r5t906oKktperOXPmvJ52DbnI5ZTdAySdI+lwSYdK2tf2hY3HRcS0iKiMiMqysrLsKwUAAACANkoyjLZ2e9ddd90h5eXlIz/2sY9VLFu2rKsk/eUvf9ln1KhRwyoqKoafcsopg6urq0skacyYMUMvueSS/pWVlUMHDRo0Ys6cOd1PPfXUwQMHDhx51VVXHVq/zU9+8pODR4wYceSQIUNG3HHHHb3rl/fr1++otWvXlr722mtdBg0aNGLChAkDhwwZMmLs2LFHbNu2zUkeez7kcsruJyX9LSKqI2KXpMckfSyZsgAAAACg8Pz5z3/u/vjjjx/4yiuvLJ41a9brCxYs2FeSJk2adPitt966aunSpYtHjBix47rrrns/bHbp0qW2qqrqtYsvvrj6c5/73JB77rnnzVdffXXRz3/+897r1q0rkaSHHnpoxaJFi5bMnz9/8dSpU/vUL2/ozTff7HbVVVetf/311xf16tVr94MPPnjA3jvy7OQSSN+U9FHb3W1b0smSliRTFgAAAAAUnj/+8Y89Tj/99M09e/asPfDAA2tPPfXUze+++26nd955p+SMM87YJkmXXnrpxueee65H/Ws+85nPbJakUaNG7RgyZMiOgQMH7tpnn32if//+O5cvX95Fkm6//fY+Q4cOHT569Ogj161b13nRokUf+oSTfv367fzYxz62Q5KOOeaY7StWrOi6d446e7lcQ/q87UckvSipRtJLkqYlVRgAAAAAFKK6+brW69atW0hSp06d1LVr1/fvENypUyfV1NR41qxZPefMmdOzqqrq1Z49e9aOGTNm6I4dOz40udilS5f3X1tSUhJNjWlvciowIr4dEcMiYmREfDEidiZVGAAAAAAUmpNOOmnbr3/96/23bdvmt99+u9Ps2bP333fffWv322+/3b/97W97SNJ999130HHHHbettdvcvHlzSa9evXb37Nmz9qWXXupWfxpwMUj0Al8AAAAA6MjGjRu3/TOf+cymkSNHjujXr9/OMWPGbJOk+++//2+XX375wKuuuqrTgAEDds6cOXNFa7d57rnnbpk2bVpZRUXF8MGDB/991KhR7+ar/r3NEXvvM2MrKyujqqpqr+1v8UWtnyo/ve+sPFYCAAAAtB9vDP1jq8fGxXfksZIPsz0vIiqzff2CBQtWjBo1akP982L/2JdCsGDBgt6jRo0qb2odM6QAAAAAihbhsX1r9xe5AgAAAACKE4EUAAAAAJAKAikAAAAAIBUEUgAAAABAKgikAAAAAIBUEEgBAAAAIEG2R1966aWH1T+/6aab+lx99dWH7uk1CxYs6DpmzJihw4YNGz5o0KAR559//kBJmjVrVs8TTzxxiCQ99NBDvW688cZD8lv93sXHvgAAAAAoWg888MConTt3JpZ7unbtWnPRRRft8aNkunTpEr/5zW8OWLt27bq+ffvWtGa7V1xxxYCrrrrqrQsvvHCzJL3wwgv7NB7zhS98YYukLVkV3k4xQwoAAACgaCUZRlu7vZKSkpg4cWL1rbfe2qfxuqVLl3Y57rjjKioqKoYfd9xxFcuWLesiSevXr+88cODA9+rHjRkzZkfj1/7oRz86aOLEiQMk6dxzzy2/4IILBowePXpoeXn5yJkzZ/bK7cjSQSAFAAAAgIR9/etfX//YY48duHHjxpKGyy+77LIBF1xwwcalS5cuPu+88zZefvnl/SXpiiuueOv000+vOP7444+4+eabD96wYUNJ01v+HytXruz6wgsvvParX/1q2Ve/+tWB27dvd76OJ18IpAAAAACQsAMPPLD2c5/73Mbbbrvt4IbLX3rppX0nT568SZIuv/zyTfPmzeshSV/5ylc2vvLKK4s++9nPbpo7d27PY489dtiOHTv2GDDPPffcTSUlJTrqqKN29u/ff+f8+fO75e+I8iOnQGp7f9uP2H7V9hLbxyVVGAAAAAAUshtuuOGtn/3sZ73ffffdVuWu8vLyXV/96lc3PvXUU38tLS1VVVXVh64jbcj2Hp8XglxnSH8o6bcRMUzSKElLci8JAAAAAApfnz59dp911llv/+xnP+tdv+yYY45599577z1AkqZOnXpgZWXlNkl65JFH9tu5c6cl6c033yzdvHlzScNrSpvy2GOPHbB7924tWrSo68qVK7uOGjXq7/k8nnzI+gJf2/tJOl7SJEmKiPck7fEbBgAAAAAdyTe/+c11DzzwQFn987vvvvvNiy66qPyHP/zhIQcddFDNgw8+uEKSfvvb3+537bXXDujatWutJN18882rBgwYUPPyyy83u+0hQ4bsHDNmzNCNGzd2/sEPfvBG9+7dI9/Hk7Rc7jg1SFK1pPttj5I0T9JXIuLdhoNsT5Y0WZIGDBiQw+4AAAAAoG26du1ak/THvrQ0Zvv27S/VP+7fv3/Njh073n8+dOjQ95577rmljV9z7733rpK0qvHyM888850zzzzzHUm66qqrNkraWL9u3Lhx2+67776VbT+K9iOXN6ZU0j9I+nJEPG/7h5Kul/TPDQdFxDRJ0ySpsrKy4BI7AAAAgMLV0meGIl25BNJVklZFxPOZ54+oLpACAAAAAPLo0UcfXZF2DUnI+qZGEbFO0krbQzOLTpa0OJGqAAAAAABFL9dzqb8s6SHbXSQtl3Rx7iUBAAAAADqCnAJpRMyXVJlQLQAAAACADiTXzyEFAAAAACArid3+GAAAAAAgvfbaa13OPPPMI5YtW7aoftnVV199aI8ePXYvWrRon+eee65nz549d+/cudOf/exnN915551rJWnMmDFD169f37lbt2617733nr/0pS+9de21125I70jyj0AKAAAAoGi9dkXvUbu3bUws95T0OKhm6I835PRRMrfccsuqiy+++O3t27e7oqJi5KWXXrpx2LBh70nSgw8+uPz444/f/tZbb5UcccQRR1155ZUbu3XrVrQfn8kpuwAAAACKVpJhNOntbd++vZMk9ezZs7bxuq1bt5bss88+taWlpUUbRiUCKQAAAADsVd/61rcOGzZs2PABAwZ85NOf/vSmfv361dSvmzhx4qCKiorhRx111Mhrr712TWlpcZ/USiAFAAAAgATZ3uPyW265ZdWrr766eO3atQvmzp3bc/bs2fvWj3nwwQeXL126dPHy5ctfvuuuuw5ZunRpl71TdToIpAAAAACQoD59+tRs2bKlpOGyTZs2lfTu3bum4bJevXrVjh079p05c+b0aLyNQw89tGbkyJHb586du2/jdcWEQAoAAAAACerVq1ftwQcfvOuXv/xlT0l66623Sv70pz/1Oumkk7Y1HLdr1y7Nmzevx5AhQ3Y23sY777zTadGiRd2HDh36oXXFpLhPSAYAAACAFDzwwAN/+9KXvjTguuuu6y9J11133ZoRI0bslOquIb399tv77tq1y+PGjds6ceLEzfWvmzhx4qD6j32ZMGHCho9//OPb0zqGvYFACgAAAKBolfQ4qCbpj31pzbjRo0f//fnnn1/aePmjjz66ornXvPDCC6/lUFpBIpACAAAAKFq5fmYo8otrSAEAAAAAqSCQAgAAAABSkXMgtV1i+yXbs5IoCAAAAADQMSQxQ/oVSUsS2A4AAAAAoAPJKZDaPkzSGZLuTaYcAAAAAEBHkesM6Q8kfUNSbXMDbE+2XWW7qrq6OsfdAQAAAED7VlJSMnrYsGHD6/+99tprXebOndt90qRJ/ZPYfr9+/Y5au3ZtacN9DRkyZMTQoUOHf+c73+mze/fuJHbzvu9+97tld91110GS9KMf/eigFStWdE5q21l/7IvtMyWtj4h5tj/R3LiImCZpmiRVVlZGtvsDAAAAgLbq/bObRm3cuT2xj7s8qGv3mg0X/MseP0qma9euta+++urihsuGDh363vHHH789qTqa2tfq1atLP/e5zw3asmVLyfe///01Se3jG9/4xvsziz/96U97H3300TvKy8t3JbHtXGZIx0o62/YKSQ9LOsn2T5MoCgAAAACSkGQYzWV7s2bN6nniiScOkaRJkyb1v/baa/tK0qOPPrpfZWXl0N27d2vNmjWlp5122uCRI0ceOXLkyCOffPLJfSVp3bp1JWPHjj3iyCOPHH7BBRcMjGh6nq9fv341995774r777//4NraWtXU1GjKlCmHjRw58siKiorh3/ve93rX1zJmzJih48ePH3T44YePOPvssw+vra076fVLX/pSv8GDB4+oqKgYPnny5MMk6eqrrz70pptu6nP//fcfsHDhwu4TJ04cNGzYsOEPP/xwr1NOOWVw/f4ff/zx/U499dTBTRbXjKzfnIi4QdINkpSZIb02Ii7MdnsAAAAAUAx27tzZadiwYcMlqX///jtnz57914br//3f/331Mcccc+QJJ5yw7Zprrhnw61//ellJSYmmTJnS/+qrr37rtNNO27Zs2bIup5122hHLly9fdP311x963HHHbbvjjjvWPvzww71mzpzZu7l9Dx8+/L3a2lqtXr269Oc///n+vXr12r1w4cIlO3bs8LHHHjvsrLPO2ipJS5Ys2Wf+/PnLy8vLd40ePXrY7Nmzexx99NE7fvOb3xywfPnyhZ06ddKGDRtKGm774osvfvvuu+8++I477lh5/PHHb6+trdUNN9xw2Jo1a0oPPfTQmunTpx80adKkDW35XiX61wIAAAAA6OiaOmW3oZ49e9befffdKz71qU8Nu/nmm1eOGDFipyQ988wz+y1btmyf+nHbtm0refvttzs999xzPR977LHXJWnChAlbpkyZsseLROtnUH//+9/v9+qrr3Z/4oknDpCkd955p2Tx4sXdunTpEkcdddS7gwcP3iVJI0aM2P7Xv/61y0knnbSta9eutRMmTBh4xhlnbDnvvPO27Gk/nTp10uc///mN99xzz4FXXHHFxhdffLHHY4899rdWfpskJRRII+JPkv6UxLYAAAAAoNjNnz9/n169etWsWbPm/RsERYSqqqqW9OjR40Pn5Hbq1LqrLRcvXtylpKRE/fr1q4kI33nnnW+ee+65WxuOmTVrVs+uXbu+v4+SkhLV1NS4c+fOmj9//pInnnhiv4cffviAu+++++Dnnntu6Z72d/nll28844wzhnTr1i3OOuustzt3btv9jpL4HFIAAAAAQCstXbq0y49//OND5s2bt/ipp57q9Yc//GFfSRo3btzW22+//eD6cX/5y1/2kaSPfvSj70yfPv0gSfrFL36x39atW0ua2u6aNWtKL7300oEXX3zx+k6dOumUU07Zcvfdd5ft3LnTkvTyyy933bp1a7MZcMuWLZ02bdpUct555235yU9+snLJkiXdG4/p0aPH7i1btry///Ly8l19+vTZdeedd/a99NJL23S6rkQgBQAAAIC9pra2VpMmTSr/13/915Xl5eW77rnnnhWXXXbZwO3bt3vatGkrX3zxxX0rKiqGDx48eMRdd91VJkm33XbbmmeeeabH8OHDj/zd737Xq2/fvu/Vb6/+etUhQ4aMOPHEEytOPvnkrXfccccaSfra1762YdiwYX8/6qijjjziiCNGXHrppQN37drl5mrbvHlzyfjx44+oqKgY/vGPf3zoLbfcsrLxmIkTJ2748pe/PHDYsGHDt23bZkmaMGHCxr59+743evTov7f1++Hm7tCUD5WVlVFVVbXX9rf4oma/1x9yet9ZeawEAAAAaD/eGPrHVo+Ni+/IYyUfZnteRFRm+/oFCxasGDVq1PszdWl87EtHM3HixAHHHHPM9q997WtNzpAuWLCg96hRo8qbWsdNjQAAAAAULcJjfo0YMeLIffbZp3bq1Kkfmk1tDQIpAAAAACArixYtWpLL67mGFAAAAACQCgIpAAAAgGJSW1tb2/qbySCvMu9FbXPrCaQAAAAAisnC6urqXoTS9NXW1rq6urqXpIXNjeEaUgAAAABFo6am5p/WrVt377p160aKCbi01UpaWFNT80/NDSCQAgAAACgao0ePXi/p7LTrQOvwFwMAAAAAQCoIpAAAAACAVBBIAQAAAACpyDqQ2u5v+4+2l9heZPsrSRYGAAAAAChuudzUqEbSNRHxou2ekubZnh0RixOqDQAAAABQxLKeIY2ItRHxYubxO5KWSOqXVGEAAAAAgOKWyDWktsslHSPp+SbWTbZdZbuquro6id0BAAAAAIpAzoHUdg9Jj0r6akRsbbw+Iv5fe/cX+lddx3H8+eK3jcKKpf6K2FYqWLmLnDLEWIitiGnSuihQKiQCbwwMiljeRIEX3VhdSDTcygvLZGmNkErMKG+mMxdqS1rD2q+ZW5T058K1endxTvRz+679+X63z/n+vs8HfPmez+d3fpw3vPidL+/vOefz21pV66tq/fz8/LiHkyRJkiQtEWM1pEmW0zWj91bVA5MpSZIkSZI0C8ZZZTfANmBvVd05uZIkSZIkSbNgnCukG4CPARuT7Olf10+oLkmSJEnSEnfG//alqh4DMsFaJEmSJEkzZCKr7EqSJEmSdLpsSCVJkiRJTdiQSpIkSZKasCGVJEmSJDVhQypJkiRJasKGVJIkSZLUhA2pJEmSJKkJG1JJkiRJUhM2pJIkSZKkJmxIJUmSJElN2JBKkiRJkppY1rqAs+mxDV8/5X1v5w9nsRJJkiRpQP751tYVSIBXSCVJkiRJjYzVkCbZlOS5JPuSbJlUUZIkSZKkpe+MG9Ikc8BdwHXAWuCmJGsnVZgkSZIkaWkb5wrpVcC+qtpfVUeA+4DNkylLkiRJkrTUjdOQrgIOLBov9HOvkOSWJLuT7D58+PAYh5MkSZIkLSXjNKQZMVfHTVRtrar1VbV+fn5+jMNJkiRJkpaScRrSBWDNovFq4OB45UiSJEmSZsU4DekTwKVJLk6yArgR2DmZsiRJkiRJS92yM/3Fqjqa5JPAj4A5YHtVPTuxyiRJkiRJS9oZN6QAVfUQ8NCEapEkSZIkzZBUHbcO0dk7WHIY+N05O+CJXQj8qXUROi1mNp3MbTqZ23Qyt+lkbtPJ3M6ut1SVq6HOiHPakA5Fkt1Vtb51HTp1ZjadzG06mdt0MrfpZG7TydykyRlnUSNJkiRJks6YDakkSZIkqYlZbUi3ti5Ap83MppO5TSdzm07mNp3MbTqZmzQhM/kMqSRJkiSpvVm9QipJkiRJamymGtIkm5I8l2Rfki2t69FoSbYnOZTkmUVz5yd5OMlv+vfXt6xRx0uyJsmjSfYmeTbJbf282Q1YklcleTzJL/vcvtDPX5xkV5/bd5KsaF2rXinJXJKnkvygH5vZwCV5PsnTSfYk2d3PeY4cuCQrk+xI8uv+M+6d5iZNzsw0pEnmgLuA64C1wE1J1ratSifwTWDTMXNbgEeq6lLgkX6sYTkKfLqqLgOuBm7t/8bMbtheBjZW1eXAOmBTkquBLwFf7nP7C/CJhjVqtNuAvYvGZjYd3l1V6xb9yxDPkcP3VeCHVfV24HK6vztzkyZkZhpS4CpgX1Xtr6ojwH3A5sY1aYSq+hnw52OmNwP39Nv3AB88p0XppKrqhar6Rb/9N7oP7FWY3aBV5+/9cHn/KmAjsKOfN7eBSbIaeD9wdz8OZjatPEcOWJLXAdcA2wCq6khVvYS5SRMzSw3pKuDAovFCP6fp8MaqegG6xgd4Q+N69H8kuQi4AtiF2Q1ef+vnHuAQ8DDwW+Clqjra7+L5cni+AnwW+Hc/vgAzmwYF/DjJk0lu6ec8Rw7bJcBh4Bv9LfJ3JzkPc5MmZpYa0oyYc4lhacKSvAb4LvCpqvpr63p0clX1r6paB6ymu5vkslG7nduqdCJJbgAOVdWTi6dH7Gpmw7Ohqq6ke3zo1iTXtC5IJ7UMuBL4WlVdAfwDb8+VJmqWGtIFYM2i8WrgYKNadPpeTPImgP79UON6NEKS5XTN6L1V9UA/bXZTor8N7ad0zwCvTLKs/5Hny2HZAHwgyfN0j59spLtiamYDV1UH+/dDwIN0XwB5jhy2BWChqnb14x10Daq5SRMySw3pE8Cl/SqEK4AbgZ2Na9Kp2wnc3G/fDHy/YS0aoX+GbRuwt6ruXPQjsxuwJPNJVvbbrwbeS/f876PAh/rdzG1AqupzVbW6qi6i+yz7SVV9BDMbtCTnJXntf7eB9wHP4Dly0Krqj8CBJG/rp94D/ApzkyYmVbNzR0+S6+m+RZ4DtlfVHY1L0ghJvg1cC1wIvAh8HvgecD/wZuD3wIer6tiFj9RQkncBPwee5n/Ptd1O9xyp2Q1UknfQLcgxR/cl5f1V9cUkl9BdfTsfeAr4aFW93K5SjZLkWuAzVXWDmQ1bn8+D/XAZ8K2quiPJBXiOHLQk6+gWEFsB7Ac+Tn++xNyksc1UQypJkiRJGo5ZumVXkiRJkjQgNqSSJEmSpCZsSCVJkiRJTdiQSpIkSZKasCGVJEmSJDVhQypJkiRJasKGVJIkSZLUhA2pJEmSJKmJ/wA53EZae4acPAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f36003d6668>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.rc('figure', figsize=(14, 8))\n",
+    "\n",
+    "plt.subplot(231)\n",
+    "plt.boundary_handling(sc2.boundary_handling, make_slice[-1, :, :], show_legend=False)\n",
+    "plt.title('Inflow')\n",
+    "\n",
+    "plt.subplot(232)\n",
+    "plt.boundary_handling(sc2.boundary_handling, make_slice[0.5, :, :], show_legend=False)\n",
+    "plt.title('Middle')\n",
+    "\n",
+    "plt.subplot(233)\n",
+    "plt.boundary_handling(sc2.boundary_handling, make_slice[0, :, :], show_legend=False)\n",
+    "plt.title('Outflow')\n",
+    "\n",
+    "plt.subplot(212)\n",
+    "plt.boundary_handling(sc2.boundary_handling, make_slice[:, 0.5, :], show_legend=True)\n",
+    "plt.title('Cross section');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We run the channel for a few steps..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f36003bbd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sc2.run(20)\n",
+    "plt.scalar_field(sc2.velocity[:, 0.5, :, 0])\n",
+    "plt.colorbar();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And then switch off the inflow..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sc2.boundary_handling.trigger_reinitialization_of_boundary_data(activate=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f36003190b8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sc2.run(50)\n",
+    "plt.scalar_field(sc2.velocity[:, 0.5, :, 0])\n",
+    "plt.colorbar();"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/03_tutorial_lbm_formulation.ipynb b/doc/notebooks/03_tutorial_lbm_formulation.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..c82369874d29dffc5055aa247597bd89a1142219
--- /dev/null
+++ b/doc/notebooks/03_tutorial_lbm_formulation.ipynb
@@ -0,0 +1,573 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.jupytersetup import *\n",
+    "from lbmpy.session import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 03: Defining LB methods in *lbmpy*\n",
+    "\n",
+    "\n",
+    "## A) General Form"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The lattice Boltzmann equation in its most general form is:\n",
+    "\n",
+    "$$f_q(\\mathbf{x} + \\mathbf{c}_q \\delta t, t+\\delta t) = K\\left( f_q(\\mathbf{x}, t) \\right)$$\n",
+    "\n",
+    "with a discrete velocity set $\\mathbf{c}_q$ (stencil) and a generic collision operator $K$.\n",
+    "\n",
+    "So a lattice Boltzmann method can be fully defined by picking a stencil and a collision operator. \n",
+    "The collision operator $K$ has the following structure:\n",
+    "- Transformation of particle distribution function $f$ into collision space. This transformation has to be invertible and may be nonlinear.\n",
+    "- The collision operation is an convex combination of the pdf representation in collision space $c$ and some equilibrium vector $c^{(eq)}$. This equilibrium can also be defined in physical space, then $c^{(eq)} = C( f^{(eq)} ) $. The convex combination is done elementwise using a diagonal matrix $S$ where the diagonal entries are the relaxation rates.\n",
+    "- After collision, the collided state $c'$ is transformed back into physical space\n",
+    "\n",
+    "![](../img/collision.svg)\n",
+    "\n",
+    "\n",
+    "The full collision operator is:\n",
+    "\n",
+    "$$K(f) = C^{-1}\\left( (I-S)C(f) + SC(f^{(eq}) \\right)$$\n",
+    "\n",
+    "or\n",
+    "\n",
+    "$$K(f) = C^{-1}\\left( C(f) - S (C(f) - C(f^{(eq})) \\right)$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## B) Moment-based relaxation\n",
+    "\n",
+    "The most commonly used LBM collision operator is the multi relaxation time (MRT) collision.\n",
+    "In MRT methods the collision space is spanned by moments of the distribution function. This is a very natural approach, since the pdf moments are the quantities that go into the Chapman Enskog analysis that is used to show that LB methods can solve the Navier Stokes equations. Also the lower order moments correspond to the macroscopic quantities of interest (density/pressure, velocity, shear rates, heat flux). Furthermore the transformation to collision space is linear in this case, simplifying the collision equations:\n",
+    "\n",
+    "$$K(f) = C^{-1}\\left( C(f) - S (C(f) - C(f^{(eq})) \\right)$$\n",
+    "\n",
+    "$$K(f) = f - \\underbrace{ C^{-1}SC}_{A}(f - f^{(eq)})$$\n",
+    "\n",
+    "in *lbmpy* the following formulation is used, since it is more natural to define the equilibrium in moment-space instead of physical space:\n",
+    "\n",
+    "$$K(f) = f -  C^{-1}S(Cf - c^{(eq)})$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Use a pre-defined method\n",
+    "\n",
+    "Lets create a moment-based method in *lbmpy* and see how the moment transformation $C$ and the relaxation rates that comprise the diagonal matrix $S$ can be defined. We start with a high level function that creates a useful default MRT model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{2}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{0}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{3}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{4}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{5}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{6}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{7}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{8}$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f088c1a4d68>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.creationfunctions import create_lb_method\n",
+    "method = create_lb_method(stencil='D2Q9', method='mrt_raw')\n",
+    "# check also method='srt', 'trt', 'mrt' or 'mrt3'\n",
+    "method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The first column labeled \"Moment\" defines the collision space and thus the transformation matrix $C$.\n",
+    "The remaining columns specify the equilibrium vector in moment space $c^{(eq)}$ and the corresponding relaxation rate.\n",
+    "\n",
+    "Each row of the \"Moment\" column defines one row of $C$. In the next cells this matrix and the discrete velocity set (stencil) of our method are shown. Check for example the second last row of the table $x^2 y$: In the corresponding second last row of the moment matrix $C$ where each column stands for a lattice velocity (for ordering visualized stencil below) and each entry is the expression $x^2 y$ where $x$ and $y$ are the components of the lattice velocity.\n",
+    "\n",
+    "In general the transformation matrix $C_{iq}$ is defined as;\n",
+    "\n",
+    "$$c_i = C_{iq} f_q = \\sum_q  m_i(c_q)$$\n",
+    "\n",
+    "where $m_i(c_q)$ is the $i$'th moment polynomial where $x$ and $y$ are substituted with the components of the $q$'th lattice velocity"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1\\\\0 & 0 & 0 & -1 & 1 & -1 & 1 & -1 & 1\\\\0 & 1 & -1 & 0 & 0 & 1 & 1 & -1 & -1\\\\0 & 0 & 0 & 1 & 1 & 1 & 1 & 1 & 1\\\\0 & 1 & 1 & 0 & 0 & 1 & 1 & 1 & 1\\\\0 & 0 & 0 & 0 & 0 & -1 & 1 & 1 & -1\\\\0 & 0 & 0 & 0 & 0 & 1 & 1 & -1 & -1\\\\0 & 0 & 0 & 0 & 0 & -1 & 1 & -1 & 1\\\\0 & 0 & 0 & 0 & 0 & 1 & 1 & 1 & 1\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡1  1  1   1   1  1   1  1   1 ⎤\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   -1  1  -1  1  -1  1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  1  -1  0   0  1   1  -1  -1⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   1   1  1   1  1   1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  1  1   0   0  1   1  1   1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   0   0  -1  1  1   -1⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   0   0  1   1  -1  -1⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   0   0  -1  1  -1  1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎣0  0  0   0   0  1   1  1   1 ⎦"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Transformation matrix C\n",
+    "method.moment_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left ( \\left ( 0, \\quad 0\\right ), \\quad \\left ( 0, \\quad 1\\right ), \\quad \\left ( 0, \\quad -1\\right ), \\quad \\left ( -1, \\quad 0\\right ), \\quad \\left ( 1, \\quad 0\\right ), \\quad \\left ( -1, \\quad 1\\right ), \\quad \\left ( 1, \\quad 1\\right ), \\quad \\left ( -1, \\quad -1\\right ), \\quad \\left ( 1, \\quad -1\\right )\\right )$$"
+      ],
+      "text/plain": [
+       "((0, 0), (0, 1), (0, -1), (-1, 0), (1, 0), (-1, 1), (1, 1), (-1, -1), (1, -1))"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pystencils.stencils import visualize_stencil\n",
+    "visualize_stencil(method.stencil)\n",
+    "method.stencil"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Define custom MRT method\n",
+    "\n",
+    "Instead of using a pre-defined method as above, in this section we are looking at lower level functions that allow for a complete specification of all method table entries:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$0$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$0$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$0$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} - y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}^{2} - u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} + y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{2 \\rho}{3} + u_{0}^{2} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{2}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{2}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{3}$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f08356199e8>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.moments import MOMENT_SYMBOLS\n",
+    "from lbmpy.stencils import get_stencil\n",
+    "from lbmpy.methods.creationfunctions import create_generic_mrt\n",
+    "\n",
+    "x, y, z = MOMENT_SYMBOLS\n",
+    "rho = sp.symbols(\"rho\")\n",
+    "u = sp.symbols(\"u_:3\")\n",
+    "omega = sp.symbols(\"omega_:4\")\n",
+    "\n",
+    "method_table = [\n",
+    "  # Conserved moments     \n",
+    "  (1,    rho,  0 ),\n",
+    "  (x,    u[0], 0 ),\n",
+    "  (y,    u[1], 0 ),\n",
+    "  \n",
+    "  # Shear moments    \n",
+    "  (x*y,       u[0]*u[1],                   omega[0]),\n",
+    "  (x**2-y**2, u[0]**2 - u[1]**2,           omega[0]),\n",
+    "  (x**2+y**2, 2*rho/3 + u[0]**2 + u[1]**2, omega[1]),\n",
+    "  \n",
+    "  # Higher order\n",
+    "  (x * y**2,    u[0]/3,                        omega[2]),\n",
+    "  (x**2 * y,    u[1]/3,                        omega[2]),\n",
+    "  (x**2 * y**2, rho/9 + u[0]**2/3 + u[1]**2/3, omega[3]),  \n",
+    "]\n",
+    "method = create_generic_mrt(get_stencil(\"D2Q9\"), method_table)\n",
+    "method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Instead of manually defining all entries in the method table, *lbmpy* has functions to fill the table according to a specific pattern. For example:\n",
+    "- for a full stencil (D2Q9, D3Q27) there exist exactly 9 or 27 linearly independent moments. These can either be taken as they are, or orthogonalized using Gram-Schmidt, weighted Gram-Schmidt or a Hermite approach\n",
+    "- equilibrium values can be computed from the standard discrete equilibrium of order 1,2 or 3. Alternatively they can also be computed as continuous moments of a Maxwellian distribution\n",
+    "\n",
+    "One option is to start with one of *lbmpy*'s built-in methods and modify it with `create_lb_method_from_existing`.\n",
+    "In the next cell we fix the fourth order relaxation rate to a constant, by writing a function that defines how to alter each row of the collision table. This is for demonstration only, of course we could have done it right away when passing in the collision table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$0$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$0$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$0$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} - y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}^{2} - u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} + y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{2 \\rho}{3} + u_{0}^{2} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{2}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{2}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.0$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f083567f0b8>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def modification_func(moment, eq, rate):\n",
+    "    if rate == omega[3]:\n",
+    "        return moment, eq, 1.0\n",
+    "    return moment, eq, rate\n",
+    "\n",
+    "\n",
+    "method = create_lb_method_from_existing(method, modification_func)\n",
+    "method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Our customized method can be directly passed into one of the scenarios. We can for example set up a channel flow with it. Since we used symbols as relaxation rates, we have to pass them in as `kernel_params`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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5tm3bIjQ0FAkJCUhJSbEoB39/fzzyyCNISkpCUlKS5NE+Z2dndO/eHYMGDUJSUhIGDx4sOQcvLy+xnU5ISIC3t7ek8jY2NujRoweCg4ORkJCAoUOHSs7B3d0diYmJYg7mHvOaCg0NRWRkpHjclJpD27ZtkZCQgISEBCQmJiIgIEByDsHBwfDz80NCQgKio6Mlj465uLggPj4ew4YNQ0JCAgIDAyXnEBQUhCeffBIJCQkYNmyY5H3Tzs4O0dHRCA8PR3x8PLp06SI5B29vb4waNQpxcXGIi4uTPPJKRAgODkZsbCzi4uIkHzsBwNHRESEhIWIO+vMrKVxdXdG9e3fExcUhNjYWXbt2lVReX487deqEuLg4DBkyRHKMTp06AWhcp3FxcRg0aBBCQkLMrt9t2rRBu3btkJWVBUdHR8TExGDQoEHo0aOH2cfQQYMG4eOPPwbQeH7av39/REVFoVevXmad2wmCgLi4OOzatUt8r0uXLhgyZAjCw8PNOrcKCQmBj48PiouLxfe8vLwQExODgQMHIjg4+KHrZOjQofj+++8N3nN2dkZMTAyioqLQr1+/3xzx9PDwQFBQEK5cuWLwvoODA4YMGYJBgwahb9++v7leu3fvjlOnTqGmpsYodlJSElJSUhAfH9/ifqtUKtGpUydcvnzZaJ5Op0NJSQlycnLQtWtXi/bd/2sCteJnHMPDw+nEiRN/dBomEREmTJiAyspK9O/fH/369UOfPn0kneAXFxdjxowZGDZsGIYNG2bRrT7r16+HVqtFbGysRbdt1dXVYdWqVYiLi5N88qGXlZUFhUJhViNgChEhMzMT4eHhFt+yUFhYCFtbW6tuG8vLy0NgYKDFtzpVVFRALpdbdDum3u3bty2+FRJovC2lpqbG4tsIgcZbnr28vCSfvOjpdDrk5+ejffv2FudQWFgIZ2dni25V1svJyUGXLl0svuXrzp07AGDVLXiXL18WL6pY4v79+6iurrYqh+LiYnh5eVm8HrRaLe7fv29VnaqoqICzs7PF9RoAqqurLbrlW6+urs7iWyH1tFqtxbe2Ao37hqXbQY+IrFqP1pZvLTkw9nuzdv8GGr9Ix9Jb6AHg7t27qKiosOr4uW/fPri7uyM0NNSi/ay6uhoffPABhgwZgoiICIvazQ0bNmDr1q2Ij49HbGys5OMHESEtLQ1yuVy8OCV1neTn5yMkJAR9+/YVL3KFhYVJaoO/+OILvPjiiwgLCxMvFkZERJh9rkpEiIiIwNGjRxEcHCzGGDx4sNmPzZw/fx6hoaEgIvTp0wcpKSlISUlBeHi42ecWTzzxBJYvXw6FQoEBAwYgNjYWsbGxGDhwoNXHxd+DIAgniSjcrM9yx5UxxhhjjDHWGuh0OjQ0NFj1/GVhYSEcHR0t+t4UvW3btiEsLMyiOzqAxs7ztm3bkJiYiHbt2lkUY/ny5dBqtUhKSpL8XTpA43crzJkzRxwltmZA4P8X7rgyxhhjjDHGGGvVpHRc+d/hMMYYY4wxxhhr1bjjyhhjjDHGGGOsVeOOK2OMMcYYY4yxVo07rowxxhhjjDHGWjXuuDLGGGOMMcYYa9W448oYY4wxxhhjrFXjjitjjDHGGGOMsVaNO66MMcYYY4wxxlo17rgyxhhjjDHGGGvV5BkZGX90Di1auHBhxoQJE/7oNH7TwYMHMW/ePDg5OcHf3x+CIEiOcerUKSxYsABeXl7w8vKyKI93330Xubm5CAwMhIODg+Tyhw8fxmeffQZHR0f4+/tDJpN2TaOhoQGTJk1CSUkJVCqVRTmsWLECmzZtgpubGzw9PSWvy4KCAkyZMgWCICAwMBAKhUJyDm+//TbOnj0LHx8ftG3bVnL5EydO4L333oNcLkdAQIBFOWRkZODEiRNwdXWFh4eH5PVQWlqKZ599Fvfv34e/v79F22L37t346KOPIAgCVCoVbGxsJMf49NNPsX37djg6OsLX11fycuh0OrzwwgvIy8uDl5eXRdvj+vXrmDJlCnQ6HQICAqBUKiXHWLp0KdatWwcXFxeLlqO+vh7PPfccSkpK4O/vD0dHR8k57Nq1C/PmzYOtrS38/f0hl8sllSciTJ48GZcvX4a3t7dF6zIzMxOzZ8+GXC6HSqWyqG6/8cYbyMrKgoeHB9zd3SWXv3DhAt544w0AgEqlsmh7zpkzBwcPHoSrq6tF7UxpaSmef/551NXVQaVSwc7OTnIO3333HVavXg0nJyeL942XXnoJhYWF8Pf3h5OTk+QcsrOzMXPmTNjY2CAgIEBynQKAr776Crt374a7u7tFbZVWq8WLL76Ie/fuISAgAPb29pJzOHv2LN59913Y2tpCpVJZtByLFi3Czp07LV4OnU6HSZMm4datW1CpVBbt47m5uXjzzTchk8ksPnZ89913WLVqFZydnS2qVwAwY8YMnDlzBp6ennBzc5NcXqvV4m9/+xtu3boFX19fODs7S45RWVlp9TGsvLwczz77LB48eACVSmVR3aqtrcXEiRNRWloKX19fi/YzAJg2bRrOnz9v8ToFgOXLl2P16tVwdHSEn5+fRdv29zgeAsBrr72GCxcuWHwsARqPaQsWLICdnZ1F55wAUFNTg+effx4VFRUWb2MA+OKLL3DgwAFx/7fEgQMHsGDBAnH7WLI8eXl5mDFjBpRKpcVt8rVr1/D+++9blcfly5exePFieHl5WXSctsTMmTOLMjIyFpr1YSJqtVPfvn2ptauvr6eOHTsSAPLx8aGJEyfS9u3bqba21uwYWq2WunTpQgAoODiY3n77bTp37pykPDZv3kwASCaTUUxMDH3++edUUFBgUQ5eXl70zDPP0ObNm6m6utrsGB9++CEBILlcTtHR0fTJJ5/QtWvXzC5fWFhItra2BICCgoLo5ZdfpgMHDpBWqzU7RlpaGgEgR0dHGjFiBC1fvpxKS0vNLr9t2zYCQAAoLCyM3nrrLTpx4gTpdDqzyut0OurduzcBICcnJxoxYgQtXbqUbt++bXYO+/btE3Po2LEjTZo0iXbu3Ek1NTVmx3j22WcJAAmCQAMHDqR33nmHTp06ZfZy1NfXU6dOnQgA2dvbk1qtpvnz51NeXp7ZOeTm5pJcLicA5O3tTePHj6c1a9ZQeXm52TEWL14srosePXrQG2+8QYcPH5ZUJ1JTUwkA2draUlJSEn355ZeUn59vdvmioiKys7MjAOTv708TJ06kLVu2SNo35s6dK26PiIgImj17Np07d87s7VFbW0uBgYEEgNq2bUtjxoyh7777ju7du2d2DitXrjRal0eOHDF7XTY0NFDPnj3F/Ss9PZ0WL15MRUVFZuewdetWMYeuXbvSK6+8Qnv37qW6ujqzY8TExBAAsrOzo+TkZMnb89SpU2IOHTp0oBdffJF27twpqc1+6qmnCAApFAqKjY2lTz/9lK5evWp2+ZKSEnJyciIA5OvrSxMmTKDNmzdTVVWV2THmz59vVKfOnz8vqa2KjIwkAOTi4kKPPfYYffvtt5LqVG5uLslkMgJAnTt3pilTptDPP/8saf+cM2eOeNyIiYmhTz/9lK5fv252eZ1OR/369RP3jccff5xWrVpFFRUVZse4evWq2FZ16tSJXnnlFcnHns8++0w8Bg8ePJjmzp1LFy9eNLs8EVFsbKzB8Wvp0qV0584ds8uXlJSQs7OzWK/++te/0qZNmyTVq927d4v7R7du3Wjq1Kl08OBBSetCfy4AgPr160ezZs2i06dPm103iYgmT55ssD7nzJkjqX4TEb3wwgtijKioKJo7d67kGLNmzRKXpX///vTOO+9IXpYNGzaIMYKDg+nVV1+lAwcOUH19vdkxbt++TQ4ODuI52vjx42nt2rVUWVlpdgwiIo1GY3A8nDdvnqT2k4ho/fr14vKEhobS66+/Lvm4XFtbSwEBAQSA3Nzc6PHHH6fvv/+eysrKJOXy1ltvie3H0KFD6YMPPqBLly5JipGdnU2CIBAA6tKlC02ZMoX2798vafvU1dVRhw4dCAB5enrS+PHjad26dXT//n1JuSQkJBAAatOmDY0ePVpym0z072Okl5cXPfXUU7RhwwZ68OCB2eV1Oh317duXAFBISAi98cYbdOzYMWpoaJCUhxQATpCZfUOh8fOtU3h4OJ04ceKPTqNFzzzzDAoKCpCTk4O8vDyDeS4uLkhJSUF6ejqSkpJMXnU8ffo03njjDdjZ2eHChQu4ePGiwfzg4GD86U9/wqhRo9C9e3eTOUyfPh0nT56EQqHAli1b0Hx7Dhw4ECNGjMDIkSPRsWNHo/IFBQUYP3485HI5Ll26hGvXrhnMd3R0RFJSEtLT05GcnAxXV1ejGJ999hk2b96M2tpaHDhwwGh+WFgY0tPTkZaWhl69ehldKdRqtUhKSoJMJsPx48dx7949g/menp7QaDRIS0tDXFycyatqq1evxqJFi1BUVIRz584ZzJPL5RgyZAjS0tKQlpaG9u3bG5UHgDFjxqCkpAQ//fST0Xr09/dHamoq0tLSEB0dDVtbW6Py+/fvxzvvvIOrV68arUdBEBAREQGNRgONRoOQkBCTV0wnTZqEc+fO4cCBA2hoaDCY5+TkhLi4OKjVaiQnJ8PHx8eofE5ODp577jmUlpYiKyvLaL6fnx+Sk5ORkpKC4cOHm7yC/O6772L37t3Izc3FzZs3jeaHhoYiJSUFKSkpiIiIMBoZKCsrw4gRI0BEOH78OB48eGAw38bGBkOGDIFarUZKSgo6d+5s9Df+9a9/YcWKFaivr8fPP/9sNN/T0xPJyclQq9WIj4+Hi4uL0Wc0Gg2qq6tRWFiICxcuGM3v1auXuD369u1rdGVy+/bt+OCDDyAIAk6ePGlULx0cHBAfH4/U1FSkpKSYvFtiwoQJuHr1Kqqrq3H48GGj+R07doRGo0FqaiqioqKMRrZPnz6NqVOnAmjcts23h0KhQFRUlLgcnTp1Mvobb7/9Ng4fPoyGhgbs27fPaL6npydSUlKg0WgQHx9vVCeKioowduxYAMDVq1dx/fp1oxj9+vWDWq2GRqMxuY/PmzcPa9euBRFh3759RvtX27ZtkZiYCLVajcTERJNXeWNjYwEAN27cQG5urtH8sLAwMYd+/foZbc+1a9fiyy+/BAAcOnQINTU1BvOdnZ0RHx8PjUaD5ORkeHp6Gv2NsWPHori4GCUlJfjll1+M5nfv3l3cFgMGDDC6Yn748GG8/fbbAIAzZ86gtLTUYL6+Tmk0GqSkpMDb29vob0yZMgW//PIL6uvrsX//fqP5nTp1EtuqyMhIo/3z6tWrmDhxIgRBQF5eHi5dumQwX6FQIDo6GmlpaUhNTUVgYKDR3/jwww+xY8cOyGQyHD58GJWVlQbzH9ZmV1dXIzU1FTKZDNXV1Th48KDR3wgLC0NaWhrS09NN1qmVK1di2bJlkMlkuHbtmtFyKJVKxMbGisvh6+tr9DdGjhyJyspKyGQyHDlyBBUVFQbz3d3doVarkZaWhvj4eKOR1J9++gnvv/8+BEFAXV2dye3RtWtX8dhjqk4899xzyM3NhSAIuHHjBnJycgzmy2QyREZGitu0S5cuBvOzs7Px0ksvAWg8zpw5cwYlJSUGn7G3t0dcXJzYVjU/dsyaNUs8duv3UZ1OZ7QukpOTodFokJCQYNDmlpSUYPTo0eLvLbV3KpVK3EeHDRtmcLfCwoUL8cMPP4i/l5WV4dSpU0Yx9G2mRqNBVFSUwahhQkICtFqt+Pvdu3dx5swZoxhBQUFiHk1jbNy4EZ9++qnBZ+/fv49jx46ZvSxPPvkkbty4YfBZIsLevXuNYri5uSEpKQkajQaJiYlo06YNjh07htdff93os0Dj8aD5cUipVCImJgYajQZqtRrt2rXDa6+9hpbOnVs6HoaFhYkxvL298cwzz5gsr1+ePXv2GL3f9Fhy6dIl7N69W5zXdP/Vv75w4QIKCgoMYigUCgwZMgQpKSn48ccfYW9vL37e1M/KykqTda1r167o3LkzioqK0KZNG8hkMoNyzV8fOHDA6FzFzc0Nzs7OcHFxgbu7O2xsbMTPm4px/vx5o3M/GxsbuLi4wMvLC56enrCzszMor89LP+Xl5RkdWwRBQNu2beHl5QUfHx84OjqKZfXlm75Qh1SVAAAgAElEQVS+cuWK0b4jk8ng7u4OHx8f+Pr6wsHBAXK53OSkUCiQlZWFzMxMgxj+/v5imzx06FCLR+xNEQThJBGFm/Vhc3u4f8TU2kdc9SOUD5s8PDxo8eLFRlcrmo4+PGwKCQkxGSM+Pt7sGMOHD6cLFy4YlL9w4YLZ5T08PGjhwoVGOUycONGs8jKZjP785z/TzZs3DcrX1NSYnUO3bt1o+/btRtvi/fffN6u8o6MjzZgxw+QVaF9f34eWFwSB4uPjTY6Ir1q1yqwcOnToQJ9++qnJq3n6EZDfmhwcHOiRRx6h06dPG5U/fvy4WTl06tSJ3njjDZNXNx9//HGztuXgwYPp66+/NrrKeufOHbNysLW1pZSUFNq7d69RDtOnTzcrhouLC/3lL38xObKvH9F62OTv708ZGRlGdaLpaO/Dpr59+9LWrVuNcujRo4dZ5R0cHOjJJ5+kwsJCg/I//fSTpH1jyZIlRvunfsTZnBwee+wxunz5skH5q1evmp1DcHAwffbZZ0Z1e9KkSWaVt7e3pxEjRpjcv8zNISgoiGbPnm10h8Inn3xiVnmFQkFxcXGUmZlplEP79u3NiuHh4UFTp041urtg3bp1Zi9Hjx49aMOGDUYjO0OHDjWrvI2NDT322GNGd0mcOXPG7Bzc3Nzogw8+MBoRf/LJJ82O0bt3b9q/f79B+bKyMrPLy+VyGjt2rNG+MXPmTLNjuLq60kcffWS0HG5ubmbH6NWrF+3Zs8eg/PLly80ur1AoaMyYMXTjxg2DGH369DE7hoeHB7377rsGdfvgwYNmlwdAPXv2NKpXjz76qNnlbWxsKDk5mX755Rex/M2bNyXl4OLiQuPHjzc4F5g6daqkGB4eHjRp0iSDO6psbGwkxfD29qbJkyeLI1pffvmlpPL6fWTixIlUXFxMROafFzad9O3e+fPnDe76kjIJgkADBgygTZs2iaN2lkwqlYqef/55i8sDjcd2c9tKnv4zp7Zt29Ls2bMl3an0W8Ajrv83Vq5ciXv37uHrr782uqrXo0cPJCUlISkpCZGRkSavTFy7dg2bNm1CTU0Nli9fjuzsbIP5Li4uiImJwfDhwzF8+HB07drV6Krzxo0bcf36ddy9exczZ840mKdQKBAZGYmEhAQkJCSgd+/eRqMQ9+7dw3fffYeGhgYsW7YMJ0+eNJjfs2dPJCcnIzk5GQMHDjT5rOP+/ftx7tw5XL58GZ988onBPA8PDyQlJSE5ORnx8fEmn+/QarVYuHAhGhoa8I9//AO3b982WIbBgweLMbp3725ypPL06dM4fPgwduzYgU2bNhnM69q1q7gMUVFRJkdLAWDZsmW4ffs2pk2bZjAi1LZtWyQkJCAlJQWJiYkmR2IA4MqVK9i1axe+//57gyvv+ivm+quZwcHBLT6fsn79ety4cQMvv/yywZVjX19fcWRu2LBhLT7LcefOHaxduxYnTpzA4sWLxfcFQcDAgQPFq/bdunVrMYc9e/bgypUrWLp0qcGVTHt7e8THxyMtLQ1qtbrF9VBTU4Nly5ZBEAS8/vrruHv3rjjPw8NDHMGIi4tr8Vmw48eP49SpU7h16xZmzJhhMO+3rrg39fXXX6O+vh47duzA+vXrDeaFh4eLMUyN5gCNV4P1I5T/+Mc/UFhYaLAuhg8fLo5+q1QqkzmsWrUKpaWluHLlCj788EODee3atRPrxNChQ00+K3nz5k2xPi9cuBCnT58W5ykUCgwdOhRqtRpqtdrkaCvQOHJ8/fp1lJaWYvr06Qbzmo4axMTEmKxXFRUV+PbbbwHAqG7rr47r12VQUJDJHA4dOoRz586hqqoKr7zyisH+5efnB7Va/dC6vWDBAgiCgE2bNmHLli3i+033L41G02LdzsrKEkeep06diurqanGem5ubOIKfkJDQ4nNbK1euFK/wr1ixwmBez549xW3Rv39/k88nXbt2Ddu3bwcRYc6cOcjPzxfn2draIiYmRrwToaU7QzZs2ICbN2+ioKAAs2fPNpjn7e0t3g0xfPhwk3cilJSUYPXq1dDpdFi7dq3RyEnPnj3FGAMGDDD5rOWePXuQk5ODhoYGTJ8+3WCk0tbWFtHR0WKba6pe1tbWYsmSJdDpdMjNzTUa5fLy8hLb/Li4OJN3+pw4cQLHjh2DTqfD6tWrje726dGjB1JSUpCcnGzyzhAAWLJkCaqrq9HQ0IAZM2agrKxMnKcfydLfoWKqbl+8eBF79uyBTqdDXl4e/vnPfxrM9/b2FsvHxcWZ3B5r1qzBnTt3oNPpsGXLFmzbts1gvv5OArVajX79+hnVq6KiIrF9IyLMnTvX4A4wW1tbDBs2TKxX7dq1M8ph586duHr1KogINTU14nOQeh4eHuJoq6k7XB48eGCwP1y7dg1z5841+MzD2u0jR44YjDSdPn0aCxcaPvIWGhoqxjC1jy1atMgg7+bHQeDfI4sajQbh4eEG50TZ2dlGd/hcvHgRH3/8scF73bp1E2M0r1vff/89ysvLDT5fWVkp3jmjp2/3NBoNYmNjxXYvPz8fW7duhSnvvfeewWiuo6OjwV0i+js0tmzZYjTqq2fqeNi/f38xl7CwMJSVlRmMfjfvJ1RWVmLatGkG73l7exssz6lTp3D+/Hmj8k1fL1682OiYpr8bKykpyeDunJZ+5uTkYN68eQa5tG/fXjwW6HQ6yOVyg3LNXxMR3nrrLYM7RxwcHDB8+HC4u7ujc+fOaNOmjVEHqnmMlStXGp1D9+jRA4GBgQgNDRXPE5rH0el04uu9e/cabX8fHx8EBweje/fu6NixI2QymVhGp9MZvd6/fz927dplEKNNmzbo3r07goODERQUBLlcjoaGBoNJq9WKrw8dOmQ04urk5IThw4eLfZuAgAD8XnjE9f9QQUEB2dnZkbOzM40YMYIWLVpkdEX1YW7cuEF2dnakUCgoKiqKZs2aRYcPH5Z0f73+6nP79u3p2WefpXXr1kl6lrC4uJgcHBysWo5x48YR0PhMy4wZM+jo0aOS7onfu3cvAY3P5jz11FO0Zs0aSc871NXVUVBQENna2lJiYiJ9/vnnRqNHD6N/3io0NJSmTZsm+TmU8vJycnNzE59P+Oabb6ikpERSDgsWLCDg38/YHj9+XPKzBcOGDSM7OzvSaDS0aNEiSc8hEhGVlpaSk5MTeXl50dNPP00bN26U9JwUEdGOHTsIaHyW8dVXX5X87BsR0SuvvEKCIFBkZCTNnj2bsrOzJT1bVF9fT126dCEHBwdKS0ujRYsWGY3cPMzhw4cJAAUEBNDf/vY32rJli+R1MW7cOJLJZDRo0CB6//33JT3fStT4/LednR25u7vTuHHjaNWqVZKfBXrzzTfF/dOSZ870ddvV1VV8Hknqszf6Z9969+5NM2bMkPT8ONG/n4tydnamUaNG0fLlyyU9A0hE9O233xLw7+f3pO7jOp2OBgwYYPCMmJRnMomITp48SQDIz8+P/vrXv9KGDRskPwulHxXp168fZWRkSG4n7t+/T15eXuTg4ECpqan01VdfSW7zN23aREDjKM3EiRNp48aNkpdj7NixJAgC9e/fnzIyMiQ/S1VRUUHu7u7icixYsEDyM3v6u59UKhVNmDDBou0xYcIEq7aH/jl2e3t70mg0Fi3H6dOnxWOopfVK/6xujx49LHp2kYjo6aefturZVKLGZ/1sbGwoPj6ePv/8c0nfl6E3bNgwUiqVlJiYSPPmzZP0HQ16o0ePFp+//uijjyg3N1dyjPfee4+AxjtzMjIy6OTJk5LXh/5uqoCAAHruuedo27Ztkr5ngcj4eCj1Owr0Zs+eLbbjb731lkXPP+qPaW5ubjR27Fj64YcfJB9PiIj+9Kc/iXXNkmMrEdHGjRsJAAUGBtJzzz1HW7dulXyMv3PnDjk5OYnfbbJkyRLJ61ar1VK3bt1IoVDQsGHD6KOPPpL8nLxWq6WuXbuSTCajyMhIevfdd+nMmTOSz5s6d+5MQOPdnq+88gr99NNPv9voqimQMOL6h3dOf2v6T+i4ZmZm0r59+yR9uUhz+/fvpy1btkh+yF5Pp9PRsmXL6OLFi5J3WL3jx4/T3r17La6YNTU19M0334i3y1hix44dkk+mm7p69Spt3rxZ0kPoza1evVrySWhT2dnZkr9sprmNGzdalUN5eblFXwrQ1NmzZ+nQoUOST1ia2r17N+Xk5FhcXqfT0apVq+jWrVsWx8jPz6etW7dKPsA39dNPP9Evv/xicb2sra2lb7/9VnIHq6kTJ05YtT3061Jqp72p7Oxs2rdvn6ROXnPr1q2T3Dlq6sqVK5K/SKm5LVu2WHTyqXf79m1av369xe01UeMXsEn5srTmtFotrVy50qKTTr3z58/Tjh07JH3pW3ObN2+mrKwsi5ejpqaGVqxYYdU+fvbsWdqxY4dV+/iWLVus2sfr6uqsPv7l5uZadMLc1L59++jkyZNWfYnK2rVrLeok6tXX19P3338v+YJtUxUVFbRmzRpJX7DVXFlZGf34449WxaipqbG4Q9XUjz/+KOnLMk3Zt2+f5A5Ic7/H8ZCo8TzJmnacqPGYZsnF7Kaqqqpo5cqVVh1biRovwFnTjhE1Lo/UL9Fs7urVq7R69WrJF6Wbys3NtWjApKmzZ8/S/PnzrToPlUpKx5VvFWaMMcYYY4wx9n9Oyq3CZv+DH0EQlgiCcFsQhHNN3vunIAg5giBkCYKwThAEkw8GCYJwXRCEs4IgnBEEgXuijDHGGGOMMcbMJuU/0y4FkNjsvV0AQomoJ4BLAEx/h3ejGCLqZW6PmjHGGGOMMcYYAyR0XInoAIC7zd7bSUT6rz7NBGD6qzUZY4wxxhhjjDELSRlxfZinAGxrYR4B2CkIwklBECb8jn+TMcYYY4wxxth/OeN/bGYBQRDeBKAFsLKFjwwiokJBELwA7BIEIefXEVxTsSYAmAAAgYGBv0d6jDHGGGOMMcb+g1k94ioIwhMA1AAepxa+opiICn/9eRvAOgD9W4pHRAuJKJyIwj09Pa1NjzHGGGOMMcbYfzirOq6CICQCmAYglYiqWviMoyAIzvrXAOIBnDP1WcYYY4wxxhhjrDkp/w7nOwBHAHQVBKFAEISnAXwBwBmNt/+eEQRhwa+f9RMEYeuvRb0B/CwIwi8AjgHYQkTbf9elYIwxxhhjjDH2X0vKtwqPISJfIrIhIhURfU1EnYgo4Nd/c9OLiJ799bOFRJT86+urRBT269SdiN79/7UwrUF+fj7u379vVYzLly9Dq9U+/IMtICLcvHnTqhzKyspQVlZmVYybN29Cp9NZXL6urg6lpaVW5XD79m2rctBqtbh165ZVORQUFKCurs7i8kSE7OxstHAnvllu3ryJGzduWFweALKysqyuE8eOHbNqXVRXV+PcuXNWrYvi4mLcuXPH4vIAcOXKFau36aVLl6xajjt37li9f+Tm5qK+vt7i8rW1tbh06ZJVOeTl5aG8vNyqGNnZ2WhoaLC4/L1796xuM69evYqamhqLyxMRLl68aFWdKC0txd27dx/+wd+Qn59v1fEHaNym1qioqLB6OQoLC63aR4HGbWrN9qipqUF+fr5VORQVFVnd7l66dMmqugkAv/zyi1X7mFarxalTp6w6HldXV+PMmTNWb5MTJ05YlYdOp8OhQ4esajsB4Pjx46isrLQqxuXLl62uY3V1dcjMzLRq+wLA2bNnce/ePatiVFRUWH2MB4Bz586hurraqhi3b99GUVGRVTF+j3YdAK5fv25VnQUa20Rr8ygoKLA6hrXkGRkZf2gCv2XhwoUZEyb8Z30JcUFBAbp06YIDBw6grKwMnp6ecHV1lRTjxx9/RGJiIs6ePYv6+nqoVCrY2dmZXV4QBLz44ouYOXMmioqK4OLiAl9fXwiCYHaMhoYGBAcHY9u2bSgrK4OXl5fk5di6dSsSEhJw6dIlyGQyBAYGQqEw//vAZDIZ4uLi8M0336CsrAze3t6Sczh8+DCGDBmC3NxcKBQKBAQESM5BrVZj4cKFKCkpgYeHBzw8PCTlcO7cOfTs2ROnTp1CTU0N/P394eDgYHZ5QRDw8ssvY/LkyWInQaVSwcbGxuwYOp0OwcHB+Oabb5CXlwelUgl/f3/I5XKzY5w5cwa9evXCrl27UFxcDCcnJ/j4+EiqV19++SVGjhyJY8eOoby8HF5eXmjTpo3Z5RUKBUaNGoWMjAxcvHgROp0O/v7+UCqVZseoq6tD586dsX79ehQXF8PZ2Vnycvz8888YOHAgTp48ierqavj5+cHR0dHs8oIgYPLkyZg6dSquXbsGhUIBlUolaXtotVp06dIFmzdvxp07d+Dq6goPDw9Jy7F161ZER0fjzJkzFtVNhUKBkSNH4r333rN4OW7fvo2goCDs2bMHJSUlcHd3h7u7u6Tl+PTTTzFmzBhkZ2ejvr4e/v7+ktpMuVyOPn36YNmyZbh58yYcHR3h5+cnKYeTJ0+id+/eOH78OO7fvw8fHx84OzubXV4QBEydOhUvv/wyrly5Iq5LKe2VTqdDt27dsHHjRovX5eHDhxEREYGsrCyLjj8A8Oqrr2Lq1KnIy8uDvb09/P39IZOZ/2SSIAjo2bMn1q1bh9LSUnh6esLd3V1SDhcvXkRoaChOnTqF2tpaqFQqSXUbAD7//HOMGzcOubm5kMlkko8fcrkciYmJ+OKLL1BQUGBRvbp//z6CgoKwc+dOlJaWwsPDQ/K6+PnnnzFgwACxo+Tr6yupbgLAZ599htGjRyMrKwu1tbXw9/eHvb292eVlMhleeOEFTJ48GefPn4dWq4VKpYKtra3ZMRQKBcaMGYPp06cjJycHDQ0NFsUYN24cpk2bZnF7IQgCZs2ahSeffBKnTp1CVVUVfHx84OTkZHYMANi+fTuGDBmC/fv3o6SkBG5ubpL316qqKnTu3Bk//PAD8vPzoVQq4efnJ6kNlsvleP755zFp0iSLty/QeAGxZ8+e2L17N27fvo22bdvC09NT0vIolUokJSVh9uzZyM3NhSAIks93AGDHjh2IiopCZmYmKisr4ePjAxcXF0kxiAjBwcH44YcfUFhYaNG5giAI+Pvf/46pU6fi6tWr4nmolO0DAEuXLsXIkSNx8eJFAEBAQIDkdbJu3TpoNBpcvnzZovYMABYvXowxY8aIyyL1GNWSmTNnFmVkZCw057PCH91z/i3h4eF04sSJPzqNFumvYhKRwfTSSy/h559/Fj8XEhKClJQUqNVqREZGihu5srIS169fN7h6QUSor69HfHy8eOVKLpcjKioKGo0GarUaXbp0ET+fl5eHBw8eQBAEyGQyccrNzUVSUpL4OZVKhdTUVKSmpiI6Olps6Gtra8XGAWjcyfTTvHnz8MUXX4gxQkNDkZqaCo1Gg/79+4snIoWFhbh37x5kMpmYhyAIICLExsaioKAAAODg4ICEhASkpaUhJSVF7AASEc6fPy/mLpfLxZ87duzAxIkTxRx69uyJ9PR0pKWloXfv3mLeJSUluH37tlhOH0MmkyElJQXnzjU+Vu3s7IykpCSkp6cjKSkJbdu2FWNfvHgRDQ0NButRJpNh7969eOaZZ8TPdenSBampqUhLS0NERITYAJWXl4ujmk0bNkEQMHbsWJw+fRpA4wE8MjISGo0GGo0G3bp1Ez9/5coV3L9/X6xLOp1OvGI3duxYMaadnR1iYmKgVquRkpKCdu3aAWg8iOXm5qKhocFomj9/Pr7//nsxhouLC+Li4pCcnIzExET4+fkBaBxxKS0tRUNDA7RaLbRarfj66aefNhhN8fHxQUJCApKSkhAfHw9XV1dotVpxBExfTv/6zp07eOyxxwyuHIaEhCA5ORlJSUkYPHgwlEoliouLcevWLTQ0NECn00Gn04mvDxw4gDfeeEMsr1QqER0djeTkZCQnJ6Nz584AGg+iWq3WaF0SET766CODdeHn54fk5GSo1WrExsbCyckJd+/exc2bN8X9s+lPIsIjjzwirgtBEDBgwACo1Wqo1Wr07NkTgiAgNzfXYKSj6b5+6dIljBo1Svzd2dkZCQkJUKvVSE5OhqenJ+7fv49r164ZldW//uSTT7B06VLx/Y4dO4o5DB06FEqlUhzRbJ4/EUGr1UKtVosj0IIgICIiQowRGhqK+vp65OTkGLVz+ungwYN4+eWXDZYjPj4earUaSUlJ8Pb2RmFhIUpKSoy2g/73V199Ffv37xdjBAUFiW3mkCFDoFQqcfbsWaO/rY9VWloKtVotjhgoFAoMHjxYjNG1a1eUlpaKV5xNxfn222/xySefiDl4enqKdSI+Ph4uLi64ePEiamtrjdal/vWYMWMMRqD79u0rrss+ffrg/v37BvtP8+PvlStXMGLECPF3Jycngzrh5eWFa9eu4cGDB2jJvHnzsGDBAvH3Tp06iW3N4MGD0dDQgMuXL4vbW6/p6/T0dOTm5orrcsiQIWKMoKAgFBQUoKyszOi4oX+dl5eHxMREMZ6bmxtSUlKg0WiQkJAAR0dHXLhwwWRZ/eulS5dizpw5YoyuXbuKx5+IiAjcvXsXt2/fNsi9eawnn3wSR48eBdDY7g4aNAgajQapqano2rUrLly4YDDK1Hx9lJWVISYmRhy5dXR0RHx8PDQaDVJSUqBUKsXjW0t27dplsH94e3uL9TIuLg7FxcWorq42qktNf77zzjtYt26dGKNz585Qq9XQaDTo3bs38vPzW9w/9fV71KhRBnfd9OnTR8zDy8sLFRUV4v7U/CcRoaSkBGlpaWLbrT+OpaSkID4+HnK53ODvmZqysrLwwgsviDnY2NggKioKycnJ6NevH1xcXFosr2//f/75Z7z11lsGMYYMGYLk5GR06tQJAQEBICKTxw79dOTIEUyfPl2MIZfLMWjQIERHR6Nnz57o0KGDyb/d9PW1a9fQfGClb9++6N+/PyIiIsTjekt5NDQ0oLa2Fn/+858NRl3bt2+PgQMHYtCgQejduzeUSmWLueinOXPmYM+ePWIMZ2dnREREYNCgQYiIiEDbtm1b3Cb66fTp05g2bZpB/Q8LC8PgwYMRGRmJoKAgADAo03Rb6df5xIkTxWMW0HiOMHjwYAwaNAjh4eGwtbVtsY7pX+/cuROzZ88WY9ja2qJfv34YPHgwBg8eDG9v79+s7/pj2yOPPGJwt0KXLl0QFRWFwYMHIzQ0FDKZrMXju/71nDlzDPY9Dw8PREVFYejQoRg4cCDs7e2N2vGmv1dWVuLo0aOYOnWq+J6DgwMiIyMRExODqKgouLm5obmmbdGNGzdQVlaG8ePHi6PISqUSERERGDZsGKKjo+Ht7W1w/q6PIQgCqqurcePGDeh0OjzxxBMoKSkBANjb2yMyMlKM4ebmZlDW1M/q6moMGjRIrLNOTk5ITEyERqNBcnKy5IGdJst7kojCzfrwwzb+Hzn17duXWrMuXboQGv9HrdlT27ZtafTo0fTDDz/Qli1bJJcHQJ07d6aXX36Zjhw5QomJiZLLOzs706hRo+ibb76hzMxMi3Lw9vamp59+mjZs2EDPPPOM5PIymYwGDx5M//znP+ns2bMW5RAQEEAvvPAC7d69m2bPni25vEKhoLi4OPriiy/oxo0b5OfnJzmGp6cnjR8/ntavX08rVqywaDmCgoJo8uTJtHfvXoqIiLAoRvfu3WnatGm0du1ai8oDoF69etH7779Pf/rTnywqL5PJKDIykv71r39ZnIOTkxM98sgjFtUp/dSpUyeaPHkyOTg4WFReqVRSfHw8Pf744xbnoFKp6Nlnn6UOHTpYVF4QBIqIiKCnnnrK4hycnZ1p5MiR1KtXL4tjBAYGWrUeBEGg/v3708CBA62qE+np6RaXB0AdO3akqKgoi8srFAoaNmwYubq6WhzDx8eHhg8fbtW6HDhwoMV1Cmg8/lhyzGg6BQcHU48ePSwub2NjQzExMVbl4O7uTmFhYVbF6Ny5M9nZ2Vm1PYKCgqzKwdbWllxcXKyKYWk71zwPa2PwxBNP/9uT/rx+7ty5lJOTI6k/BeAEmdk3/F3+j+v/KltbW9ja2hpc5RAEAXV1dSaffWjbti2Sk5ORmpqKhIQEHD16VBz5bH6lVz+S25yvry9iYmIQExODsLAwyOVyKBQKg6tVD6NQKMRRXyISbzcwVUFa4u/vD39/f/j4+ECpVMLGxsbgCpo5Odjb28PGxgaCIMDGxka8kmiuBw8e4O7duyguLkZdXR0UCgUaGhrMWgdA462WpaWlKC4uRkFBgbhe9FcQzaG/YldfXw8iMrhltWke+pG/5uzt7RESEoJu3bqhc+fOsLOzg52dndHotSAIJp8D1I/06UeAq6urYWdnJ446N51qa2tNPivl6+uLtLQ0pKenIzo6Gs899xwcHBygUCjE+qV/fffuXVRVGX+B+MCBA/HII48gPT0dHh4eYg76ck1fFxYWGq1fpVKJ4cOHIz09Hampqfjqq69gb29vMAKvf02/Xv03tS4TExPFEf0VK1ZAp9MZrUuZTIa6ujqTy6EfkU9NTUV5eTnWrFkjrufmVzFrampMPhPk5eWF+Pj4h+7jAFp8Bqdbt26IiooyuA3O1BVQrVZr8jk+pVIpXtGtqqrChQsXTC6DIAioqqoyWd/9/f2RkpKCAQMGYM2aNUbtnH4iIpPP9ctkMgwePBipqak4f/48zpw5I5ZpWq9lMhlqampMPoPn7u4OtVqN1NRUbNu2zWTZpvuHqX0sLCwMqampqKmpwbFjx4zy18doaGgwOZKpVCoRGxuL1NRU5OXloaqqqsVRwtraWpPPh3p6eiIpKQk+Pj44ePCg+L6UOtG1a1dERUVh3759v/k8rv7uhuZkMhl69OiB4OBg/PTTT+K202veXpni6OiIbt26obS0FEql8jdHCVtqQz08PMTHRprm0DzWb7XjKpUKrq6uBrfKmcqlpRyUSiU6duyIW7duiZ+Rui48PT3h76fXu88AACAASURBVO+P/Pz837wNmohafNa2e/fuuH37NmpqakyOluh/1tfXm4xhb2+PPn36IDMzU1yfLU0PHjwwuSwqlQr29vbIy8sTY5hqMwVBQGlpaYv7WHZ2ttjGN79rST8BMPmdEUqlEiqVCjdu3ICNjY1Rm980hk6nQ3FxsVEMJycn1NTUQCaTwcbGBgqFwuRdXPoYpvYhW1tbaLVaKBQKKJXKFvOQy+XinQXN6deXjY2NuCy/FefmzZsmt60+hlKpNFgWU+ukvLzc5LOl+nMr/TlaS9tFv05a+h4MhUIhxtH/7aZ3+TV9XVJSYvLYKpPJxPWqX56W2nOtViveTWEqF30+TcuamkpKSky2AYIgtBhDP1//uqysrMW2SL9M+rvumrbn+t+1Wi1qa2tNlm/6t/R5ADD6e9Z+54AUzY8LUjg6OsLHxwdeXl4mR5F/N+b2cP+IqbWPuJqi0+lo0KBB4hWIjh070uTJk2nPnj1UV1dnVox79+5RmzZtxBi9evWit99+m44fP04NDQ1m5fDzzz8bXAnp0aMHvfbaa3Tw4EGqr683K49XXnlFLO/g4ECpqam0cOFCKigoMCuHBw8ekK+vrxjDz8+PnnnmGVq3bh1VVlb+Ztn6+nqqra2lRYsWGSxH79696c0336TDhw+TVqttsbxWq6Xa2lq6f/++wci4i4sLPfroo7RkyRIqLCx86DI0NDTQN998Y5BDv379KCMjw+zt0dDQQD179hTL60fjNm/eTFVVVQ8tT0S0Z88esbydnR1pNBpatGgRFRUVmVWeiGj8+PFijG7dutFrr71GmZmZZi0DEVFNTQ35+/sT0DgCFR8fT/Pnz6ebN2+ancO5c+cMtsWYMWPohx9+oPLycrNjLF68WIzh6elJTz31FG3cuNHsdUlENG7cODFGQEAAPf/887Rz506qra01q3xNTQ2pVCoxRmhoKL3++ut05MgRs9fngQMHxPL6Eb2PP/6YLl++bPZyTJgwQYzh4eFBTzzxBK1Zs4YqKirMKl9RUUFubm5ijD59+lBGRgadOnWKdDqdWTGWL18ulndycqJHH32Uli9fTiUlJWYvx5AhQ8QYXbp0oalTp9LBgwdb3Meby8nJIZlMJq7L4cOH0+eff07Xr183O4fp06eLObi7u9MTTzxBP/7442+2VU3V19cbjMCFhITQa6+9RocOHTJ7OQ4dOiSWl8vlFBMTQx999BHl5uaavRx///vfxRht2rShxx57jFasWGH29qirq6OOHTuKMQIDA+n555+n7du3U3V1tVkxTp48adRmzpw5k06ePGl2vZo5c6ZBm5eSkkLz58+n/Px8s8rrdDrq16+fGEN/l9DDjj9N5eXlkY2NjcGxePr06XT06FGz9/Ovv/7aaDkWLFhg1nFUb9SoUWIMX19fmjBhAm3atMnsNq+qqop8fHzEGH379qWZM2dK2s+zs7NJEAQCGkdok5OTacGCBZLa/6Z3BLm6utLYsWNp1apVZrdXREQLFiwQY/j4+NCECRNoy5YtZtdNIqKFCxcanJf87W9/o+3bt1NNTY3ZMXbs2GHQ9o4fP542bNhADx48MDtGUVGROOpvb29P6enp9K9//Yvu3LljdgwioqFDh4q5DBw4kGbPnk3nz583e9sSGbbjvr6+NHHiRNq6dauk9VpdXS2e88nlcho2bBh98skndPXqVUnL8/777xtsn2effZa2bdsmKZfS0lJydnYWc4mOjpbclhIZHmP1+56Uczcior3/j73zDo+q2v7+90zJpEzaJJnJZGYS0gtNigFpgZCEFJLgteDl2qWoXFGuiApKEcWgggoKUkRAQEAFBCkiIIJIC0Wq9JqEkEbKpE1Z7x94zp3JJJAz473yu+/+PM9+5sxw1srae6/dCz/9JOiQy+WUkpJCM2fOFJUuJSUl5OXlZdfnaKl9sVqtQv/VYrGQ2Wwmk8lEVVVVdvWATqejESNG0Pr162/rt7b6SkpKSKlUCjoiIyPppZdeoq1bt7a6/9QcELHi+pcPTm8X/i8OXLdv30733Xcfvfvuu3TixAlRFQdPXl4epaen0+zZs1vdSDclNzeXsrOzac6cOXT58mXR8kVFRRQfH08jR44UXWHwzJw5k7p3705TpkwR1UDyNDY2UufOnemBBx6gzz//XFQDybN06VJq164djR07lnbs2NHqyQMes9lM3bt3p4ceeogWLVpE169fF23D6tWrKTExkd566y06fPiwUz7x8MMP09NPPy26YeS5fPky9e7dm/Ly8ujUqVOi5YmIli9fTg8++CAtW7aMKioqnNIxZswYGjFihOhOAo/JZKL09HQaM2aMqIGNLefOnaPExESaPHmy0/mxYMEC6t+/P3388ceiG2Wehx56iP7xj3/QihUrnErPS5cu0T333EOvvvqqqMGRLTNmzKCMjAyaM2cOXb16VbS82Wym/v370/PPP+90nu7cudPp7UU8o0aNoiFDhtCKFSvo5s2bouXLy8spMTFR9IDZlqVLlzo1+WDL4MGDaciQIfTVV1855ROFhYXUvn17eumll2jbtm2i6zsiokWLFlGPHj1o6tSpdOzYMafKx5AhQ2jQoEG0YMGCO04QNkdFRQW1bdu2VZ2qltiwYQN17tyZJkyYQPv372/1QNOW0aNHix4w29LY2Eg9e/akoUOH0nfffUc1NTWidRw7dkyIR2snS5syd+5cl8o5EdELL7wgejLHFqvVSn/729/oxRdfFDWRb0tjYyNlZWXR66+/LmrS1RaTyUQ5OTk0fvx4p/3CarXSk08+SS+//DLt3LnTqfqCiGjatGkutetERPv376fMzEyaO3euU2WN6FY9/sADD9C4ceNETco0ZcmSJfTwww/T0qVLqby83CkdNTU1lJKSQm+++Sbl5+c7Vf8QEX3wwQeCLWVlZU7puHz5MiUmJrpU9oiIHnjgAXrsscdo1apVoibpbZk4cSKlpaXRrFmznO5zzJw5kxITE2nKlClO930mTJhASUlJ9P7779OpU6eczp+miBm4ssuZ/mT4bSauYDKZRN8WZgsRoaGhQfRNkLY0NDTAzc3NYeuDGOrq6kTfSmcLv31GzI2xTampqRF9058t/JZvV/KjsbHRpTgQ3dp+LfYWuqY6XMnLu0UHX1+5osNisbiUloDr5Zzo1kUWruj4M+oaV3VYrVa7bVXO8Gfkh6s6/ld8wmQyCds9naWhoUHULa1NoT+2xrqi489of1yNB+B63W02m+22yTqrw9Vy/mf4N3/swln+jLr7bmiDeB2Aa3H5M225G3T8L9riqs/zdrjafwNcr4uAW5d3ir1ZvSmu9utbQszlTGzgymAwGAwGg8FgMBiM/zpiBq6uTSUwGAwGg8FgMBgMBoPxH4YNXBkMBoPBYDAYDAaDcVfDBq4MBoPBYDAYDAaDwbirYQNXBoPBYDAYDAaDwWDc1bCBK4PBYDAYDAaDwWAw7mrYwJXBYDAYDAaDwWAwGHc1bODKYDAYDAaDwWAwGIy7GjZwZTAYDAaDwWAwGAzGXY100qRJf7UNLTJv3rxJw4cP/6vNcJpjx45h+vTpkMvl0Ol0kEqlonXMmTMHP/zwA5RKJTQaDTiOEyVvsVjwxhtvoLa2FgaDAXK5XLQNhw8fxvz586FUKhEcHCzaBgD44osvcOrUKej1enh4eIiWr6urw4cffghfX18EBQU5ZcPPP/+MgwcPIjQ0FG5ubqLliQgzZ86EXC6HVqt1yoZff/0VGzduREhICLy9vZ2yYdKkSaioqIBer4dCoRCt45dffsEnn3zikl+++uqrOHLkiNP5cfHiRbz44ouora1FSEgIPD09RdvwxRdf4Ntvv4VCoUBISAgkEnHzcFarFWPGjEFhYSG0Wi2USqVoG86ePYv33nsPCoUCOp1OtA0AsGzZMuzatQsajQZ+fn6i5S0WC8aPHw+j0Qi9Xu+Ubx8+fBizZ8+Gl5cXQkJCnPLtTz/9FPn5+VCr1U7Fw2g04uWXX0ZDQ4PTvr1t2zYsWrQInp6eTsfj3Xffxe+//47g4GD4+PiIli8rK8O4cePAcRz0ej1kMploHRs3bsTatWuhUqkQGBjoVDymTZuGa9euQafTOVXnlpWV4e2333bJt7dt24bvv/8earUa/v7+ouUBYObMmbh8+TL0ej3c3d1FyxuNRkycOBFSqRR6vd6p+m7v3r348ssv4efnB7Va7VR+zJs3D/n5+U77lcViwdixY1FeXu50nl69ehXjxo0DAOj1eqf6A9u2bcPs2bMhk8mcbj8WL16MFStWuNQGzZo1C6tXr3ZJx2effYZly5ZBIpFAp9M5VVbXrl2L999/HyaTCSEhIU756MWLF/HMM8/g5s2bUKvV8PX1Fa2DiDBs2DAcOnQIHh4e0Gq1TpXZb7/9FjNmzIDJZIJOp3MqPvX19Xjsscdw9epV+Pv7IyAgwKkys2zZMnz++eeQSqVO54/RaMSwYcNQXl6O4OBgp/pdADB//nxs3rwZPj4+TvXFAeD06dOYOnWqSz7b0NCA119/HSaTyek+vdVqxVtvvYW6ujoYDAan0rW+vh6TJk0S2jln4mLL5MmTiyZNmjSvVS8T0V0bunTpQv+XsVqtlJiYSADI19eXHnroIVq0aBFdv3691TrOnz9PMpmMAJBGo6EnnniCVq5cSeXl5a3WMXXqVAJA7u7ulJmZSbNnz6bLly+3Wt5sNlPbtm0JAGm1Who6dCitWbOGqqurW61j3759BICkUin17duXpk+fTmfOnGm1PBHR008/TQAoIiKCXnrpJfrpp5/IZDK1Wr64uJg8PDxIoVBQZmYmzZs3j4qKikTZMHnyZAJAer2enn/+efrhhx+ooaGh1fJGo5HUajUBoK5du9Jbb71Fhw8fJqvV2mods2fPJgAkl8spNTWVPv74Yzp//nyr5U0mE8XExBAA8vHxoQcffJAWLlxIhYWFrdaxadMmAiCkxdChQ+nbb7+lysrKVut44IEHCABxHEf33nsvTZgwgX799Vcym82tkr9+/Tp5enoSAPL396fBgweLLl9z584V4tGlSxd68803ac+ePa22wWq1UlJSEgEgPz8/Gjx4MC1ZsoRKSkpabcOFCxeEMt6uXTt67bXXaNeuXaJ8+9133yUA5ObmRgMGDKBZs2bRhQsXWi1vsVioffv2BICCgoLoiSeeoFWrVtHNmzdbrePgwYNCWrZt25bGjh1LP//8s6h4jB49WvDtlJQUmjFjBp0+fbrV8nV1daTT6YR4PP7447Ry5UqqqKhotQ5b377nnnto/PjxovySiOjRRx8lAOTp6Uk5OTk0d+5cunbtWqvlb968SX5+fkJ998ILL9APP/xA9fX1rdbx9ddfC3VuUlISvf/++3Tq1ClRdc3DDz9MAEilUtGjjz5KK1asEJWWlZWVpFKpCAAlJCTQq6++Srt27RKVlhs2bCAAJJPJKDk5mWbMmEFnz55ttTwR0bPPPiu0w4MHD6Yvv/ySSktLWy3f2NhI4eHhBIBCQ0Pp+eefp02bNlFdXV2rdfz222+CX3Xs2NEpv5o+fbqQp71796a8vDw6duyYqDzNzc0V+gMZGRmi6wrbtFAqlXT//ffT/PnzRfl3SUkJKZVKuzbo888/F9UGXb16lRQKhaDjb3/7m2g7iouLycvLiwCQh4cHZWZm0qxZs+jcuXOt1tHQ0EBt2rQR8qVXr170zjvv0KFDh0TlyyOPPCL4R0JCAr388su0detWUWV+9erVgo6AgAAaMmQILV26VFR7VF9fTwaDQShzSUlJlJeXR7/99puo+Lz//vuCLeHh4TRy5Ej6/vvvyWg0tlpHZWUl+fv7C3VpdnY2zZkzR1T/lYho/Pjxgi2dOnWiN954Q3TZu3TpEsnlcgJAOp2Ohg0bRmvXrqWamppW67BardSnTx/BZx966CFavHgx3bhxQ1R8Xn31VcFns7Ozae7cuVRQUCBKB58/np6elJubSwsWLBDdH37ppZeEvs8jjzxCy5Yto7KyMlE6eADkUyvHhtyt9+9OunbtSvn5+X+1GS0yfvx4FBUVwWq1thhOnz6N48ePO8jee++96NKlCwoKCuDr6wur1QqLxQKLxQKz2Sw8WywW7NmzB1VVVXbyUqkU9913H3x8fCCXy+1ms5tmck1NDdauXetgQ4cOHdC3b19cuHABgYGBzcry4dixYzh27JidvJubG/r16weNRoOGhoY7zmStXLkS1dXVdr/FxsYiKysLp0+fhlarhVQqhUQigUQiAcdxdp/Xrl3D119/bSfv7++PrKwshIaGoqioCAqFAhKJxE6P7fPq1atx5swZQZ7jOHTv3h25ubk4c+YMZDKZ8G5zoaqqCvPm2U8K+fj4ICMjA+3bt8eZM2eElSKO4+wC/9uOHTtw8uRJOx0GgwE5OTmoq6uDxWKBRCIBXzab5kVDQ4NDOgBAfHw8evXqhWvXriEwMBBEBIvFYudb/PPJkydx4cIFBx2dO3cWZhP9/PzsfJIPFosFJpMJO3fuhNVqtZOXyWRITExEQ0MDtFotvL297WTNZjNMJhPMZjOKiopw+vRpBxv8/f2RkJAAjuOg0Wjg5uYm/F3bsmE2m3Ho0CGUl5c3Gw8ACA4OFsoGH3fbz4aGBmzevNlBPjAwEJ07d0ZjYyO0Wi3c3NxgtVpBRA6f586dw6FDh+zkeb9yd3eHj48P/P39b1sR//jjjygtLbXToVKp0KNHD9TU1CAkJARubm4tytfU1GDdunUO8UhISIBWq4VCoRBW7ni7beNARDh+/DhOnDjhkJ/dunWDyWSCXq+Ht7e3XfybpsWmTZtgNBrtdPj5+SEuLg5yuRwhISFQKBQt1pelpaXYuXOnQzwiIyOhUChgMBiEFf6WdBw+fBiXLl2yk5dKpUhISIBCoYBer4ePj49DPGzDunXrYLFYHHxCrVYjKCgIISEhkMvlzfqD1WpFYWEhdu/e7RCPmJgYeHh4QK/XO9S5tnlBRPj1119x5coVO3kvLy+0adMG/v7+0Ol08PT0FN631cXrW7FihUMZDQsLg1KphMFgQHBwsENdY/t5+fJl7Nixw8EnoqKi4OPjg9DQUPj6+grv28ry7Ny5E+fPn7f7zd/fHyqVCqGhoc2u/DXVt2zZMphMJrt3dDodVCoVDAYD1Gq1sLrUnC3Xr193KOcSiQTBwcEICQmBwWAQVrmapiX/fPDgQZw6dcpOh0KhgEajgcFgEFZBW8pPIsLGjRsd2kBPT09otVohP+RyeYt1jdFoxKZNm9AULy8vwQZ+RZiv45qGq1ev4siRIw46fH19odPpEBISApVKBQAO7Qb/fOrUKVy9etVBh7+/P0JCQoR611auaTh69Gizdbe/vz+0Wi2Cg4Pt+kZN635eR9P05OOi1WqF3R9Wq9WhDeHbo1OnTjWrg99hxu8WICIHWf750qVLDvU3ALi7u0Oj0UCtVkOlUkEikTjI8s+lpaW4fPmygw6pVCrUO4GBgXBzc3OIB58uJpMJv/32m4MOPl3VajUCAwPh7e3dbJ7wui5cuICbN2+2GJ+goCCoVCo7P2uqq6CgAAUFBQ46JBIJgoKChDh5eHg4tMu8LWfPnkVlZSUaGxsd9Pj4+Aj5w+/waerrJSUlKC4uRmNjY7O+5ubmBq1WC41GA41GA5lM5lDuTp48icbGRhARSkpKHOohiUQCjUaDkJAQaLVaeHl52ZX5srIyoa9FRKiurkZFRYWDLYGBgdDr9dDr9YK/8TInTpxAdXW18FtjYyOuXbvmoCMgIAAGgwEGg8Fup051dbWDX5hMJly8eLFZO0JDQ2EwGIQ8bomSkhKsX7/e7jepVIqePXsiOzsbAwcORGxsbKtWpzmOO0hEXe/4IsAGrq4QFxfXbMf7v4lEInHomDAYDAaDwWAwGAzGX4FEIsETTzyBvLw8qNXq274rZuAqfmMzQ2D48OEoLS297Qrd9u3b8eOPP9rJ3XvvvcjNzcU999yDXbt2QS6XQyqVthjy8vJQVFQkyAcEBCAnJweDBg1CQUEBLl++3OzKHh/Kysowe/ZsOxt8fX2RmZmJvn374uTJk8J5maarhHzYvn07fvnlFzsdCQkJyMnJga+vL8rKyu54nmLOnDkOM5uJiYnIyMjApUuXhFXC5lZzrFYrrl27hu+//95OXiqVokePHoiLi4PJZBJmeflgO+tssViwdetWh5lib29vpKamwmq1QqPRwMvLy2HmjtdTWVmJVatWOcStffv26Nq1K+rr6+3Ovza3OrZ161aHFdfg4GBkZWVBJpPB09MTCoWixfw0Go2YMWOGQxzS09PRs2dPXLx4EUql0m61uennd999h127dgnyMpkMffv2xaBBg8BxHAoLCyGVSiGTyewC/5vFYsG//vUvmM1mQUdsbCzuv/9+ZGRkYNOmTZDL5Q7ytmHXrl1YunSpIO/m5obU1FTcf//98PHxwZEjR4S/x5cFWxukUilmzJhht5qjUqmEsrF//34AaHEFXiqVorq6Gm+99ZZdWhoMBgwaNAhxcXG4dOmSsApvuwPA9vnXX391WAVp27YtcnNzUVtbCzc3Nzu55sL8+fNRWFho59e9e/dGjx49UFpaKsx8thTKysrwySef2NnA70bw8fGBQqGAu7u7g+2237du3eqw2tmxY0ekpqaipKRE2BHBv99cmkybNs1ud4inpyfS0tIQFhYGIhL8sqk8Hy5cuID58+fb2RAREYHc3Fxcv34doaGhd9wVsWrVKhw8eFCQl0gk6N27Nzp06ACTySSkZUs2WK1WTJ482W5m3dfXF1lZWQAAjUYDDw8Ph7S0TYcTJ05gxYoVDvHo1auXcDaJT8uWwsqVK+1W+PhV/ODgYOHsK1/nNldXmM1mTJs2zW5i08PDA7169YJUKkVkZCSUSqWdXNPPkydPYs2aNXbxUKvVaNu2Lfz8/BAeHi6sltrOqts+r1271mGlMi4uDr6+voiKinI4n950dt5qteLDDz+0yw+ZTIZ27dpBpVIhKioK/v7+Lf59juNw8eJFfPXVV3Z6/f39YTAYEB4ejoiIiGbrXNv03Lx5Mw4cOGCnIzw8HGq1GtHR0cKZtdvl6UcffWS32iKXyxEZGYnQ0FDExMTA19e32d1G/GdZWRmmT59uZ0NQUBB0Oh1iYmIQEREh1Dcthb179+Kbb75xiIder0dcXByCg4OFMmZbV9o+L1++HHv27BHk+d0QsbGxiIuLg4+Pj0M/xlaPVCrFBx98gHPnzgk6vL29ER4ejri4OERHR8PDw8Oh3m/6/MYbb9jVmz4+PoiJiUFCQoKQFk3bjKafEyZMsNuh4ePjg/j4eCQkJCA8PLxFHbbPs2bNwt69ewUdSqUScXFxSEhIQHR0tIOO5vRt2bIFixYtEnS4ubkhOjoaCQkJSEhIgJeXl4NcUx2VlZV47rnn7PI2NDQUCQkJaNu2LTQaTbN9TFt9UqkU06ZNs1uhUyqVgo6oqCi7nW0t5fGGDRuwcuVKu3IYFhaGtm3bol27dggICLhtH4XjOKxevRr79u1DWVmZoMfT01NI25iYGMGW5sK5c+dw6tQplJWVOZTdkJAQQQ+/86S5Mrd161Y0NDSA4zjs2bPHbkcRn0exsbGIjo6Gp6enQ5m/fv06jh49KqTBlStXHHa7qdVqxMTEICYmRug/2tY/Bw4csGtXq6urBZ087u7uiIyMRHR0tOD7PFVVVQ67wurr6x12XshkMrRp0wZRUVFC+3A7rl27hmXLltn9xvdFBw4ciMzMTGFn0Z9Ka/cU/xXh//oZV5PJRNHR0eTm5kbp6ek0Z84cUecviP59NjQsLIxeeukl2rFjh6gzY0REr732mt3Z0O3bt1NjY2Or5RsaGigsLIykUin169ePPvzwQ1FnQIiIduzYIeynHzRokFP76Z966inh7Majjz5KX331laizvjdu3BDOs8THx9PLL79M27ZtE3VGdcqUKXbnLT777DNR5y2qqqooICBAOOM6ceJEOnDgAFksllbryMvLE85a/fOf/xR99o0/Z6tUKumhhx6iZcuWiTq3RkQ0b948IQ7vvPMOnTx5UpS81Wqlrl27kre3Nw0ePJhWrlxJVVVVonScPHmSOI6j0NBQGjVqlOgzz0T/zs+OHTvShAkTRJ9Lslgs1KFDB+HstjNl49ixY8KZl8GDBzt1TuT1118nABQVFUUvv/yy6HqioaGBQkNDSSaTUUpKCs2aNYsuXbokyoatW7cKZ/GHDRtG69evp9raWlE6HnvsMQJAiYmJ9M4774g+v1dRUUE+Pj7k5eVFDzzwAC1ZskTUWUYioqVLlwp17qhRo2jbtm2i6ksioszMTAJA3bt3p6lTp9Lx48dFxeP69evk4eFBHh4elJubS59//rmos9tERAsWLCAAFBwcTEOHDqV169aJOl9mG4/27dvTuHHjaO/evaLqqtLSUlIqlSSTyah///700UcfiTqPT/Tvs7r+/v70j3/8Q/Q5W6J/nzmOjY2lMWPGiD57bTQaSaPRkFQqpeTkZKfK+c6dO4Xzwo8//jh9/fXXou4EIPp3OW/Xrh2NHz+e9u3bJyo/rFYrdevWjeRyOaWlpdGnn35KV69eFWUDX8b4eKxevVrUOT+if9fd4eHhNHr0aNH5QUS0e/duIS3eeOMNys/PF1XGiIjy8/MF/54wYYLo+yaIiAoLC0mhUFB0dDSNHTuW9uzZIypPiG61I+3atSO1Wk3Dhg2jDRs2iGrTeSZOnEhubm6UmZlJ8+fPF11nEBFdvnyZ5HI5xcXF0WuvvSa6zPM8/vjj5OHhQYMGDaJFixaJOmfLc+rUKeI4jqKiomjMmDGiz8fzPPzwwySXy2nAgAE0e/Zs0T5PRLRnzx4CQAaDgUaOHElbtmwR1XckunVfTGxsrFD+PvnkE9HtLBHR8OHDhX7s2LFj6ZdffhGdLpMmTSIAFBISQsOHnnIkmQAAIABJREFUD3eqvR4xYoRwhnnUqFH0448/ik4THog44/qXD05vF/6vD1zPnz9Pq1atEt042bJ9+3anKlMei8VCn3zyCZ04ccJpHSdOnKBly5aJGiQ2ZdmyZbRx40ZRl1nYUlVVRRMnThR9oN6WdevW0SeffCLqIgpbzGYzTZgwgTZv3ux0PHbt2kULFiwQdQmFLVarlT777DM6cuSIS/m5ceNGpxpGnvXr19OVK1ecli8tLXW6cebZvXs3HTx40Ol0sFqttHTpUrp48aLTNly+fJmWLl3q9IUEREQbN250qcK3WCw0e/Zs0Rfv2HLq1ClasWKFqMuYmrJ27VqnOm089fX1tGDBAtGXTNhy8OBB2rBhg9Plk4ho5cqVoi8iseXmzZs0f/580RNztuzatcupjoQtCxcuFD2wsaWsrIxmzZrlUvnYuXMnrVy50iW/WrRokVMDG56amhr68MMPRV3y1ZRDhw7RV199JXrAbMuaNWto586dTsfDYrHQ559/Lnrgb0txcbHL5fzo0aNOTRLasmfPHpfKGBHRL7/8IvqCx6bs27dP9AREU06cOCF6YqopJSUlTg/KbPnxxx9FTwA35dixY3Tq1CmXdJjNZtEXMTXHgQMHXOq7Et1qV5yZJGrK1q1bXeqLE926iNHVMUFDQwN98sknoi+os8VisdBHH33k1GQPT11dHU2fPt1l3+cRM3BlZ1wZDAaDwWAwGAwGg/FfR8wZV/H/yRODwWAwGAwGg8FgMBj/RdjAlcFgMBgMBoPBYDAYdzVs4MpgMBgMBoPBYDAYjLsaNnBlMBgMBoPBYDAYDMZdDRu4MhgMBoPBYDAYDAbjroYNXBkMBoPBYDAYDAaDcVfDBq4MBoPBYDAYDAaDwbirYQNXBoPBYDAYDAaDwWDc1YgauHIct5DjuBscxx23+U3FcdyPHMed/ePTvwXZJ/545yzHcU+4avj/JRobG1FUVOSSjitXruDmzZsu6SgrK3NJvqqqCo2NjS7pqK6udknebDaDiFzSYbVaXZZ31Qaz2eyyvMlkcklHRUWFS/KVlZWoqalxScelS5dcSssbN26grq7OaXkicrlsVlRUuJyf5eXlLskbjUbU19e7pKO0tNSlvCAiFBcXu2RDRUWFS/kJAIWFhS7Fw2w2uxyPsrIyl+vK4uJil+LR2NjocptRUVEBi8Xikg5X2x2TyYSqqiqXdPwZZdTV/LBYLLh+/bpLNpSXl7vchl65cgUNDQ0u6fj9999d8gsiwpEjR1zSYbVaceDAAZft2LNnj8tt6b59+1xuC48fP+5yW1RWVoZDhw653MfZu3evy35WUFCAs2fPuqQDAA4ePOiyvxYVFbmctsAtv3e171dQUOBy23Dz5k3U1ta6pMNoNLrc1tbU1LhcrzqDdNKkSa1+efLkyRUAFgK4f9KkSbP/+G0ygJNENHjy5Mk6AKmTJk3aaivHcZwKwHIAiQDmA1g+efLkJZMmTbptT2vevHmThg8fLiY+dyUSiQQDBw7ErFmzcO3aNXh4eCAkJAQSSevnDUpKShAREYEffvgB169fh5eXFzQaDTiOa7WOcePGYdy4cbh27Rq8vLwQEhIiSt5oNCI+Ph67d+9GbW0tQkJCoFQqWy0PAB9//DFeeuklFBUVwcfHB8HBwaJsaGxsRK9evXDo0CHIZDIYDAbIZDJRNqxcuRJjxoxBTU0NQkJC4O3tLUqeiJCTk4O9e/dCoVBAr9dDKpWK0rFhwwYMGzYM5eXlUKvVUKlUouQBoF+/fti6dStMJhP0ej3c3d1FyS9fvhxDhgzBpUuX4ObmBp1OJyoeZrMZcXFx2LRpE8rLyxEQEICAgABRNrzzzjsYMWKE0MDp9XrI5fJWy5eUlCA6Ohq//PILbt68iaCgIPj5+bVanuM4vPjii3jzzTdx5coVuLu7iy6bN27cQHx8PA4dOoT6+nrodDp4enq2Wh4A3nrrLbzyyisoKChwqmxaLBZ07NgRW7duRU1NDbRarWi//vHHH5Gamup0XnAch6eeegrvvfceCgoKoFQqodVqRcWjpqYGMTEx+Pnnn1FZWQmNRgNfX19R8fj666+Rk5MjdK71ej3c3NxaLS+RSHD//ffjk08+QWFhIby8vETHo6SkBLGxsdi7d6/T+TFv3jw8/vjjOH/+PKRSKfR6vai6TiKRoH///li6dCnKysqgUqkQEBAgKh5Xr15Fu3btcPToUafrmZkzZ2LEiBFC+dLpdKLKl0QiQUpKCpYvX47y8nIEBgaKri+LioqQkJCAw4cPo6GhATqdDh4eHqJ0LF68GH//+99dyo+HH34YH374oVDOxfpVQ0MDYmJi8MMPP6C0tNSpPD1y5Ag6duyI/fv3o6qqCmq1WnQZW7JkCbKzs3H48GEYjUZotVpRfQGO4/D222/jySefxG+//Ya6ujpotVp4eXmJ0jFu3DgMHz4cR44cgdFoRHBwsGg78vLy8I9//AMHDhxAZWUlgoKCRKfHt99+i9TUVPz888+4ceMGfHx8EBQUJCpfCgsLERsbizVr1uDy5cuQy+Wi22SFQoEBAwZgypQpOHbsGBoaGqDVakW3R9999x2Sk5Px008/4caNG/D19RUdH6lUio4dO2Lu3LlCm6LT6US1KQDw5ZdfIisrC/v27XPaXy0WC+Li4rBq1Sqn++AA8Pbbb2Po0KF2bYtCoRCl4+TJk2jfvj3y8/NRW1sruuwAt+qBuLg4bN++HVVVVU61k1arFR07dsSWLVtQU1OD4OBg+Pj4iNJx8+ZNtG3bFgcPHnS6feCZPHly0aRJk+a15l1O7OwBx3FtAHxPRO3++H4aQF8iKuI4TgtgBxHFNpH5+x/vjPjj+9w/3vvqdn+ra9eulJ+fL8q+/yZGoxFmsxlWq9UuWCwWh9927NiBZ555RpANCAhAWloakpOT0bdvX/j4+MBsNsNiscBsNgvB9vvrr7+OrVv/PSeg0WiQkpKClJQU9O3bF/7+/iCiFkNhYSHuvfdeYYZErVYjIyMD/fv3R79+/eDt7X1beSLC1KlTMXPmTMGGxMREDBgwAAMGDEDHjh3vWLHV1NQgLi5OWAnQ6XTIyspCWloa+vXrBy8vL3AcB4lEAolEAo7jHHTOnDkTL774IgDA29sb6enpyMzMRGpqKgIDAyGVSiGVSlu0xWQyITY2FhcvXgQAdOvWDbm5uUhPT0dcXBxkMpkg35KOlStX4pFHHgEA+Pn5YeDAgcjOzhbyUiKRQCqVCnFoitVqRadOnXD06FEAQEJCAnJzczFgwAB07tzZ7u/z8rbfOY7DN998I9ggk8nQp08fDBw4ECkpKWjTpo0wM8jnne0zEcFkMqFr164oKCgQ4pGeni7khZ+fn+C/ROTg01arFTNnzsSMGTOEeEVHRyMjIwPJycno3r075HI5LBaLUCZsPy0WC4qLi9GvXz/BJxUKBfr164fU1FQkJycjLCzMoVw1/Rw7dizWrFkj2BAfH4/MzEwkJycjMTERMpnstvE4f/48+vXrJ8j7+/sLPt23b1+oVCpBrrkyYbVaMXr0aKxYsQLArQ7qfffdh6ysLPTv3x9xcXFC2jfNAz6UlpaiU6dOwqqpWq1GZmYmMjIy0LNnT2HQc7uyOWfOHEycOFGIR+fOnQV/6NChAziOazYOtumSnJyM33//HQDg7u6O5ORkZGZmol+/ftDr9XbvNvd59OhRZGRkCDZoNBpkZGQgLS0NvXv3hre3d7N+ZJs/U6ZMwYIFCwQd7dq1E3wqMTEREonktjoaGhrQp08fYXXLzc0NSUlJGDBgAJKTkxEREXFbeavVil9++QWPPvqoQzz69++PpKQkIR62/tTUt8aMGYOvv/7aLj/S09ORnJyMzp07g+O426al0WhEYmKiUFd6eXkhNTUVqampSElJgUajaTEv+bBp0yY8/fTTgg2RkZHIyMhASkoKevToAYVCccc6/9lnnxXKl1QqRa9evTBgwACkpaUhKipK0N2cLHBrl80999wjrJr6+/sjPT0dqamp6N+/P/z8/BxkmurZtGkTnnji3xu1YmNjkZGRgdTUVHTr1g0ymeyO8Rg1ahRWrVollNEePXogNTUVAwYMQGzsrS6Lbfo1fa6vr0e3bt1QWloq5EdycjLS0tLs8qM5f+Cf9+3bh4cffliIh1qtFvK0b9++UCqVd+xPfPDBB5g7d66gIzw8HGlpaejfvz969Ogh1Lm29WzT5yFDhghtDwC0bdsWKSkpSE5ORpcuXSCRSIS+By9nG6qrq5Geng6j0SjouOeee4S+RMeOHQGg2X4M/3z16lU8+OCDsIXX0bdvX7Rv3x5EZNcfaqrjzJkzdv4NAB06dEC/fv3Qt29fdOjQoVkdJpNJeL5y5YqdbwG32rHk5GT06dNHaI9bkjebzaipqcEjjzxit4Kl1WrRt29f9OnTB927d4enp2ezsrY6X331Vbt88fLyQu/evdGnTx/06tULarW6WVnbsGHDBsyaNUvQwXEcOnXqhD59+qB3795Ce9Rc3vDfq6urMWTIELtdPMHBwUhKShLi4+Hh4eAjts+1tbX44osv8M033wg6FAoFunXrhr59+6J3794wGAwO/mmrq6amBpWVlXjsscfsVsVjYmLQr18/9OnTB506dYJMJmu2f9DQ0ID6+nqYzWbMmzfPzhZ/f3/07dtX0OPr69tsW8CvKvI7JmzLr0wmw3333Yf+/fvbtS229YbJZEJdXZ3wu8ViwYgRI3D48GFBT8eOHZGWlobU1FS0b99eaBv4UFdXJ8SL1ztr1iy7eqBt27ZCvcyXYR6z2Yy6ujq7+hUAFi5ciLffftuu7GRkZGDAgAHo1KlTs33XpmPG8ePHY/bs2UJ69O7dG9nZ2Rg4cCCio6Md5FuC47iDRNS1Ve/+CQPXm0TkZ/PvFUTk30RmDAB3Inr7j+9vAqgjog9u97fu9oFrbGwszpw581eb8f8F/ACQL4yt2drDv88PZG2fjUZjq7ZrtCTPcZyorbb8QNw2NDY2/iXbLBgMBoPBYDAYjP8UsbGxwiC2Z8+et92hImbgKm6PpfM0t2zV7IiZ47jhAIYDQGho6H/SJpcRu81ALFKpFDKZTFgB5Gdu/n+EP7Mh5jwLP7vl6jkaftbMFXg9DHv4mUUGg8Fg/GfhJ175nWLOyPL9EaPR2GodHMcJcrZ9mvLy8lbV/xKJRJBrqqe1ZxflcrkgY/ssk8lw9erVO9ph+35zOlpzdvF2NshkMpSVlaGysrLVOpoLJpMJ165da5WOpvnBP1utVly9evW2Onh/sPUJ2+fKykq7FfnW6LFdJJBIJKLOx/MytvJms9np87G2OhjOYbvj5M/s5/0ZA9dijuO09O+twjeaeecagL423/UAdjSnjIjmAZgH3Fpx/RPs+4+xc+dOEJFdQWmu8EgkEmzatAkDBw4EcKvS6NevHzIzM5GUlITQ0FCHiqO5LaYDBw7Ehg0bANzaWnr//fcjOTkZ8fHxdttqWwpFRUXo0KGDMAiLjIzEwIED0adPHyQmJkIul99Rx5QpUzB9+nS7eKSmpiIpKQl6vf6OaVZXV4euXbsKq5W+vr5IT09H7969kZSUZLddo+nWO/77t99+a7clMigoCKmpqejTpw969OgBpVJ5261SFosFQ4YMwYULFwQdMTExSEpKQlJSErp27Wq3xbU5Hb/++itGjx4tyLu5uQlbevr27dvsFtem27+efPJJu21BCQkJwhanrl273nH725YtW/D8888L8jqdDhkZGejduzd69eolnBdqut2Y/7RYLOjSpYvQyKlUKmF7a69eveDr62u30t1cmDp1Kvhz8p6enkhLS0N2dja6d++OoKAgu5Xq5j4LCgoQGRkpNPjdu3fHoEGDkJKSAoPB4FCWmspLJBI8/vjjWLp0KQAgMDAQOTk5yM3NRfv27eHl5eUQh6bxOXv2LDp27ChUrJ07d0Zubi7S0tIQFhbWbNlq+tsLL7yAJUuWAAA8PDyQmpqKnJwcdOvWDYGBgc1u+bZ9Li8vR/v27YWtWXq9Hjk5OUhPT0eHDh2EcyNN7bD9bc6cORg/fjyAW41uz549kZOTgz59+iA0NPSO8QCAHj164MSJEwBuHWcYOHAgBg4ciE6dOsHb29tOprnPI0eOoGfPnoJPdunSBbm5uUhOTkZkZKRdvjXNB/772LFjheMISqUS6enpyMnJQZcuXRAYGOjgg031mEwmxMXFCVvgIyIihPxs37493NzcWpTlw08//YT09HS7tMzNzUWvXr0QHh7eoj/ZpseIESMEn/Dx8UFGRgYyMjLQvXt3+Pv7O+SBbV5IJBLU1tYiLi5OuLirTZs2yM3NFeoohUJxx/p648aN+Pvf/y7kR/fu3ZGVlYXevXsjNjZWmHy9nY5hw4YJW549PDyErbFJSUlQq9W3Pc7AcRyMRiPatWsnbHkOCQnBwIEDhXrKw8Pjtn7NcRw2b95sF48uXboIRxrat2/fqvbvueeew/Lly+3KaFJSElJTU6HRaBzSv2k5aWhoQHx8PG7cuNXFCQ0NFbbR9+jRA+7u7rf1CYlEgl27diElJUWIX48ePdC/f38MGDAAMTExzfYlbOs+juPw2muv4b333gNwq/0cMGAA+vfvj9TUVPj6+ja7Q8j26AwRoUuXLsJWxZiYGGE7P98PaDoIaTpJX1ZWhrCwMBiNRkgkEvTu3RspKSkYOHAg2rRpYzcYak4eAI4ePSpsKfb09ERKSgrS09ORkZGBgIAAOx0tLRLs3LkTSUlJAG61X7wNaWlp8Pb2tutPtcT+/fvRrVs3AP/exp6Tk4OUlBQolUq7o0MtUVBQgIiICAC36qy0tDSh/vb397+jDcCtTn6HDh1QWVkJqVSKpKQkZGdnIycnRzhP3ZrFkilTpmDChAkAgLi4OGRnZ2PQoEFCn6I1Oi5fvozo6GiYTCYolUoMGDAAubm5yMzMhJ+fX4tHoGypqqrCyJEjhba5bdu2yM3NRW5uLu6555472kJEuHHjBq5du4Zu3brBYrHA3d0dKSkpyMnJQVZWFtRqdYtHyoBbR9N4Hx09ejSWLVsG4FZdmpWVhezsbPTs2dOhTbDVdePGDRAROI7D2bNn0atXLwC3Bty9e/dGVlYWsrKyHNpY/rm+vh7V1dXCdyJCVlYWDh48COBWfZiRkYHMzEz06tWr2Xq9vLwcJpPJTu+0adOELboKhQJ9+vQRjnpptVoA/+7v2V7UZ1u/Llq0CO+++67w/d5770VaWhoGDBiA6OhohzRtLo0nTpyIOXPmALjVVvbq1QvZ2dnIzs4WjmD86dzpXEgzZ1baADhu8/19AK/98fwagPeakVEBuAjA/49wEYDqTn+rS5cu9L+A1WqltLQ0euSRR+irr76imzdvitZx5MgR6t69O+Xl5dHp06edsuNf//oX9ejRg/Ly8ujkyZNktVpFyZeXl1N4eDg9+uijtGrVKqqsrBRtw0cffURRUVE0evRo2r59OzU2NoqSN5vNFB8fT126dKEJEybQvn37yGKxiNKxadMmUigUlJ6eTjNnzqSzZ8+Kkici6t+/P4WGhtJzzz1H69ato5qaGlHyu3btIg8PD8rKyqJPP/2ULl68KErearXSfffdR926daMpU6bQ4cOHRefnF198QbGxsfTKK6/Qzp07yWQyiZKvqqqi+Ph4euaZZ2jdunVUW1srSp6I6JVXXqGMjAyaO3cuFRYWipY/e/YsxcbG0ssvv0y7du0is9ksWsfQoUMpLS2NPv30U7py5Ypo+cuXL5PBYKBnnnmGvvvuOzIajaJ1jB8/nrp06UKTJ092Ki/r6uooLi6OHnzwQVqyZAmVlpaKtmHt2rWCPziblo888gilp6fT7Nmz6erVq6Lli4uLKSoqikaMGEEbN26kuro60TrmzZtHiYmJ9Pbbb9OxY8dEpyURUWZmJt1///20aNEiKikpES1/4cIFioiIoJEjR9KWLVuooaFBtI7p06fTvffeS2+//TYdPXpUdDysViv16dOHsrOzaf78+VRUVCTahjNnzpBer6dhw4bR+vXrnSrj7733Ht1zzz00YcIEys/PdzoeGRkZNGfOHKf86sKFC2QwGGjYsGG0bt06p8rorFmzhDJ65MgRp/wqJyeHcnNzaeHChVRcXCxavqSkhBISEuif//wn/fjjj0751caNG6l79+707rvv0qlTp0TLExFNnTqVcnNznS4fREQjR46kp556ir777jun/IqI6Omnn6Z//vOftG3bNtHtl60dL7zwAm3fvt1pHXl5eTRs2DDauHEj1dfXO6Vjy5Yt9MADD9DSpUupoqLCKR01NTWUlZXlUj+RiGjatGkux6egoID69+9P06dPp/Pnzztty5tvvklPPvkkrV271qlyS3Srjb7vvvtoypQpTtWlPM899xwNHjyYli9f7nQebdmyhTp37kyTJk1yqq0nIiotLaWoqCiX+hy2fYbFixc7VY5LSkpIp9PR4MGDaenSpVRWViZaBw+AfGrlOFTUGVeO477CrZXTQADFACYCWAtgFYBQAFcAPERE5RzHdQXwLBEN/UP2aQDj/lD1DhF9cae/d7efcW0tVqsVZrNZ1M2WTbFYLKJvrm1KZWWl6JvHbDEajVAoFKJv8bXlxo0bUKvVTstXV1cLt3Q6y5kzZ6DX60XftMfT0NCA8+fPIz4+/o6zji1x8eJFBAcHi77Z0taGyspKl9KyoqIC/v7N/u9VraK+vl6YnXeWhoYG0bfyNbWBn6F0FqPRKOo2y6ZUV1cLK7vO4mpe1NXVQSKRuJSWVVVVom8VtIX+uFBI7A2JttTV1UGhULiUlrW1tU6XbQDCBU/Olk3eBn4l0VlqampcSkuz2YzGxkaX0qKqqgpKpdKl/Lh586aom76bYjabUV9f71Ja/Bll1NX8oD8uWXElPxoaGuDm5uaSXzU2NrrUFwFu5Ykr/QDgVjlz9bgV/bESxnT8eTr+F235M3wN+HP83tU+D/DntJN/Vp/B3d3d5foE+A9fzvTf5H9l4MpgMBgMBoPBYDAYDHvEDFz/s7cLMRgMBoPBYDAYDAaD4SJs4MpgMBgMBoPBYDAYjLsaNnBlMBgMBoPBYDAYDMZdDRu4MhgMBoPBYDAYDAbjroYNXBkMBoPBYDAYDAaDcVfDBq4MBoPBYDAYDAaDwbirYQNXBoPBYDAYDAaDwWDc1bCBK4PBYDAYDAaDwWAw7mqkkyZN+qttaJF58+ZNGj58+F9txp/Ghg0bsHv3bmi1WiiVStHyFosFb775JqqqqqDT6aBQKETr+O2337B7924YDAan5AHgyy+/hEKhQEBAADiOEy1/6tQpHD9+HHq9HlKp1Ckbtm7disDAQKfjcOXKFVy/fh2BgYFOyQPA3r17ERAQALlc7pT81atXUVxcjICAAKdt2L59OzQajdM2HDhwAJWVlQgMDHQqLwsKCvDzzz8jNDTUKRusViuWLFmCwMBA+Pj4iJYHgPXr16O6uhrBwcFOxeHkyZPYs2cPDAaDU3EgIixatAh+fn7w9/cXLQ8A+/fvx/Hjx2EwGCCTyZyyYeHChfDw8HA6L0+fPo3NmzdDp9PB09NTtDwAfP311ygsLIRer3cqHg0NDfj444+hVCqhVqudikd+fj42bdoErVYLb29v0fIAsHjxYiEezviE0WjERx99BG9vb6fj8euvv+Knn35CSEgIvLy8RMsDwOeff46bN29Cp9M5VddWVFTgs88+g0qlcrq+//nnn7F3717odDp4eHiIlgeAefPmobq62ul4lJWVYfbs2fDz83O6fGzbtg07d+50uv0GgE8//RQ3btxw2q+qq6vx9ttvw83NDSEhIZBIxK895OfnY8mSJfD29oZGo3EqLVatWoWtW7dCpVJBpVI5pWPWrFk4ePAgAgICnK43p02bhqNHj7qkY/r06di3b59LvrF06VKsWbMGHh4e0Gq1TuXL4cOH8c4774CIoNPp4ObmJlqH2WzGCy+8gKKiIqjVaqfb1BUrVmDVqlVwd3d32s+MRiNGjRqFmpoahISEOF32v/rqK2zYsAE+Pj5O16VGoxGvvvoqzGaz02kL3Mrnffv2ITg42Om0PXfuHObOnQs/Pz+n49PY2Ij3338fbm5u0Gq1TumwWq2YOXMm5HK5032nuro6zJ07FwEBAVCpVKLlbZk8eXLRpEmT5rXqZSK6a0OXLl3of4nCwkJyd3cnANS1a1eaMGEC7du3jywWS6t1fPDBBwSAZDIZ9evXj9577z06duwYWa3WVskbjUZSq9Ukl8spNTWVZs6cSRcuXBAVjxkzZhAAioqKotGjR9P27dupsbGx1fLV1dUUEBBAfn5+NGTIEFq5ciVVVlaKsuGtt94iuVxO6enp9Nlnn1FhYaEo+aqqKvL396f4+HgaP3485efntzoNefLy8sjLy4sefPBBWrZsGd28eVOUfHV1NalUKkpISHDahtdee408PDwoNzeXvvjiCyotLRUlf/LkSeI4jqKjo2nMmDH0yy+/kNlsbrW8xWKhhIQEwYaFCxdScXGxKBtGjx5NAKhTp040ceJEOnjwoKh02LJlCwEgrVZLw4cPp/Xr11NtbW2r5Wtrayk4OJjc3d1p4MCBNHfuXCooKBAVh9dff50AULt27WjcuHG0Z88eUeX6xo0b5OnpSUqlkv72t7/RokWL6MaNG6JseOeddwgARUZG0ksvvUTbtm0TVS5NJhNFRUWRRCKhXr16UV5eHp04cUJUXuzatYsACPFYuHAhXb9+XVQ8nn/+eQJAer2eRowYQevXryej0dhq+draWgoJCSEA1KVLF6fq2R9++IEAkIeHBw0cOJDmzJlDV65cERWPJ554wi4e69atExWPyspKUqlUxHEcdevWjaZMmUKHDh0SlR+rVq0iAOTt7U0PPvggffHFF6LzY9CgQYJfvfjii7Rlyxaqr69vtXxJSQk5sOAxAAAgAElEQVQplUqSSqXUp08fmjZtmmi/WrJkCQEgX19fevjhh2nx4sWiy0d2djYBoDZt2tDIkSNp06ZNVFdX12r50tJS8vb2JgB077330qRJk+jAgQOi/Oqbb74hAKRQKCg9PZ1mzpxJ58+fFxWPZ555hgCQn58fDR48mBYvXiyqzjWZTBQTE0MASKfT0TPPPEPffvutqDa4oKBA6MtERETQyJEj6fvvvxfl3/n5+QSAAFBMTAy9+OKLtHnzZlF5smPHDjsdo0aNok2bNomq/23tCAsLoxEjRtCaNWtEpUdxcTF5eXkRAAoICKC///3vtHjxYlFlzWq1Urdu3QT/SE1NpenTp4suKx999JEQn3bt2tGYMWNo27Zt1NDQ0GodZWVl5OPjQwBIpVLRI488Ijo+RESvvPIKASCJREL33XcfTZkyhfLz80WVmaKiIvLw8BD8dejQobR69WrRfcZRo0YJaTtgwACaOXMmnTt3TpSO06dPk0QiIQDUsWNHGjdunOg+k20+GwwGevbZZ0WXHSKiF198kQCQRqOhp556ir755hvRaTJx4kSh7zR06FD67rvvqKamRpQOvp2Lj4+nsWPH0s6dO8lkMonSQUQEIJ9aOTbkbr1/d9K1a1fKz8//q81okdmzZ6O0tBRWq7XV4fvvv8fly5ft9Hh6eiIyMhLh4eHCypXFYoHZbIbFYrELNTU1WL16tYMtPj4+iImJQUxMDCIiIm67Erlhwwbs3bvX7je1Wo24uDjExcXBYDBAIpEIMzC2MzEcx6G2thZvvfWWnby7uztiYmKQkJCAuLg4eHl5geM4cBwn6LL9XLVqFX7++WdBXiKRICIiAu3atUO7du0QGBgIqVTaYqiursazzz5rZ4PBYED79u3RoUMHYWZeJpM5BP73BQsWYP369YK8v78/EhIS0KFDB0RHR8Pd3b1ZeblcDplMhtraWgwZMgQWiwUAIJPJEBERgfbt26Njx47w9/dv0QY+LFy4EGvXrhVsCAgIQGxsLDp06IDIyEi4ubnZ2czHn38uLy/Hc889Z5eOYWFhaNu2Ldq3b4+AgABIJBJIpVK7T9vnvLw8nD592s6XoqOjkZCQgJiYGLi5uTWbh3z+/vTTTw4+GRoaivj4eMTHxyMoKMjufd6P+FBcXIz333/fTj4wMBDh4eGIj49HZGSksDrRVJ5n6tSpqKysFL57eHggPDwcMTExiIuLg7e3t8Pft9Xz/fffY+fOnXY2JCQkQKvVIi4uTphFb+7vcxyH8vJy5OXl2clrNBpERUWhTZs2iIyMhEKhaPbv85/Lly/Hb7/9JshzHIdOnTohMDAQcXFxCAoKciiLtlRVVWHatGl2v/n4+KBt27YICQlBTEyMMOttW+/bPu/YsQM7duyw0xEaGirIh4WFQSqVCjJNGxTg1qrSzZs37XTExsZCp9MhJiYGarXaTtZqtdrpKCwsxJdffmknr1AoEBoaipiYGERHR8PHx8dOtunn9u3bcejQITsd/v7+CAsLQ0xMDMLDw+Hm5uYga/v82Wefoba21k6HVqtFZGQkYmJiEBISAo7jHOT4zytXruDrr7+2k5fL5YINUVFR8PPzc0gD2+dNmzbh+PHjdjr8/PwQGRmJ6OhohIeHQy6Xt6jDYrFg5syZMJlMdjr4vIiJiYFGowEAh3zgw5kzZ7BmzRo7eXd3d6F8RUZGQqlUNivL61y3bh1+//13h3jwNvB+1dQG/rvZbMZHH30Eq9Vqp0Ov1ws+ERQU5BAP2/w4ffo0vv/+e4f8iIiIQFRUFKKjo6FUKh3y0/Z548aNOHPmjJ0OLy8vREdHIzo6GmFhYZDL5S22/2azGfPnz4fZbLbTERAQgKioKERGRkKn04HjOFgsFlitVofPa9euYcOGDWhKSEiI0I9Qq9WCTHPh0KFDOHr0qJ08x3EIDQ1FREQE2rRpAz8/PzsZ2/6I2WzG9u3bcf36dTsdUqkUYWFhaNOmDcLCwuDt7W0nazab7Z43btwIo9Fop0MmkyE0NBRt2rRBaGgolEqlINdc2LhxIxobGx3sCA0NFYKXl5fd3+eDyWSC2WzGtm3bUFdX55AeOp0OYWFh0Ov18PX1tdPBy/Jh//79KC0tdciXoKAgQUdgYGCzdvDh/PnzDv4FAN7e3ggNDYXBYIBGo4FEInFIUz4YjUa7vpVtuhoMBhgMBmH3Q9O84T+NRiP27dvnkDd8fEJDQ6HX6xEQECDUM037q4WFhSgsLMTVq1cddHh4eCA0NBRhYWEICQmBTCaz83OLxQKTyYSTJ08KdWnTutg2fwwGA3x9fQVb+PJWVFSEoqIiEBFqampw6dIlB1v8/f3Rpk0btGnTRli9tC2zR48eRWNjo1AHnD171sFX+PowPDwcYWFhcHd3F+qN0tJSnDt3zq5eKy4uxrVr1+x0SKVSoa8QGRkJb29v4f1jx46hurrart2tqalxaBv4/l90dDSioqKgUqlARKiursaRI0fs3iUi1NfX48CBAw52hIeHIzY2FtHR0fDz83OQs+XSpUtYvHix3W8qlQoZGRnIzs5Geno6fH19HdK9KRzHHSSirnd8EWADV1eIjY1ttpJhMBgMBoPBYDAYjP9fkclkePzxx5GXlydMLjaHmIGr+ENIDIGsrCx07txZWMFqKdiucq1fvx4XLlyw0+Pn5yfMPmk0GruVtaYrbbW1tfjwww/t5BUKBXQ6HXQ6HdRq9R3PAB09etRh9lsikUCj0UCr1UKr1cLd3R1A8yszVqsV3333nYNeDw8PBAcHQ6PRCOehmpv5JiKcO3eu2dkv/hxDYGCgMPvddLaY/+3w4cPNxs/Pz0/Yc+/p6dnszKbFYkFJSQnKysoc5CUSiXBmxs/PD3K5vMUZ0gsXLjjMQPFpwevgV4eamx0tLS1t0QaVSoXAwECoVCooFAqHGW/+s+msm206BAUFISgoCN7e3naziLbp+Pvvv6OioqLZvNBoNFCr1cL5oebysqCgACdPnnSQVyqV0Gq1CA4OdvAHXhcRoba2Ftu2bXOQ9/T0FPyRX4G3lbX93Lp1K2pqauzk3dzcBJ+2PQfc9O8DwO+//2636sznQUBAgBAHfga0qSwRoaGhAZs3b242DdVqNYKDg+8Yh8OHDzvsxpDL5YINISEhtz17ajKZ7FbveQICAhAQEICQkBDBBsBxJwVw6/x505lZhUIBlUqFkJAQ4fyr7Yq5bQCAdevWOay4BgUFwc/PD3q9Xqijmq7c86GiosIhHnK5HCqVCjqdDnq9HkqlssVdABKJBPv377dbvQZulQeVSgW9Xg+tVguZTGYn01TPsmXLHFYcgoKCoNFooNfroVKpbitfXFyMdevWOaRlQEAA9Hq9XVrapoOtnt27dzuULf7crF6vR3BwMGQyWYs6OI7DkiVLHFak/P39hTaDL5vNyXIch4KCAvzwww928jKZTLCBX71pTpb/vnPnTpw9e9ZOh7u7u5Cfd4oHACxatEjY3cLD+4TBYIC/v3+L6chxHK5cudJsPLRarV08bNtu27yVSCTYtm2bQz2hVCqh0+kQGhoqtN8ttf8cx2HOnDl2K+AcxyEoKAgGgwFhYWHw8fFx2CFj+1lQUICVK1fa2eDm5ga9Xi+shCkUitvuWNq1axd2795tp4Pvh7Rp0waBgYGQy+XN9kH452XLluH8+fN28QgODkZYWBjCw8OFeDS324kPH3zwgV3bw68K8itgHh4et92xJJVKMXnyZLvVOH53RkREBEJDQ6FQKBx2SzXVMWXKFLsdO+7u7ggLC2u1DrlcjtmzZ9stZPC7KyIiIhAeHt7sDq6mun788Ue71XSJRAKdToeIiAhERkbCx8en2XS0DRUVFQ474vz9/YWdBXxb2HQnl216GI1GfPDBB6iurnaID7+qz+dNS33VgwcP4siRIw7lXqVSCfGx7e/y/v3/2Hvv+Kiqrf//c6ZmZjIpk0I6oQdIBVIgoQWQUCLKVRRQVFBEBEW8qBQxKgrSEUQpV6SLgNSHJjHSDSH0FkgCCRBCSe/T1vcP7jnPTArOmfC78rvPfr9e+3XOTGats/bea+91ztklfAKArVu3QiqVIjMz0yq+S6VS+Pv7o1mzZmjevDk0Gk29s8kyMzNx6dIlSCQSVFZWWvkr33YDAwPRrFkz+Pr61mm7HMfh4MGDqKmpET5nZWWhurr6sX5fOw6cO3euToy7d++elS0qlQr+/v7CDCe+P+Q4Dunp6SgpKbGaoVVTU1NnNFsikQj9mZ+fnxBfysrK6r1fNplM9Y6Iu7u7C/G+9ogrf32ehw8f4sCBA3X+Hh0djcTERCQmJiI4ONiuNbQNYuuc4r8j/betceXXsUmlUurRowctXLhQ9PrSmTNnCuuN7FmTaLm+xdvbm9566y3Ra69+/vlnAkAcx1FMTAzNmDGDzp07Z/M6DJPJRCEhIQSA1Go1Pfvss7Rs2TK6deuWzTbs2rVLWMfh7u5Or7zyCm3YsMHmNZ5ms5m6du0q6AgKCqIJEybQ/v37bV5jw6/nw7/XTTzzzDO0YMECunLlik1lYTabqXv37oKOVq1a0XvvvUd79uyxuT42b94syOt0Oho6dCitWbPG5jVPxcXF5OrqKtRFYmIi/fDDD5STk2OTPBHRwIEDCQApFArq06cPLVq0SNTaEX7NtEQiodjYWJo5c6aoddsXLlwgjuOEdRaTJk2iQ4cO2bzOwtIfdTodDR8+nDZu3EiFhYU25+G7775rVB6qqqrI29ubAJCXlxe9+eabtH37diorK7PZhh9//JEACGsJ58yZQ1evXrXZBrPZTFFRUcK6GXvWvFy4cEHoGzp37kwzZ84UvUaLXy/s4uJCw4cPp02bNolaP24wGKh58+YEgNq3b0+TJ0+mP//8U9S6qqNHjxIAksvl1LdvX1q6dKmo/omI6N133yUA5OnpSaNGjaIdO3aI6mctfSI0NJQ+/fRTSktLE1WW+/btE9pmv3796PvvvxedD34Nk7354Pc0wL/XhX366aei1/Nv27ZN6GcHDBhAy5YtE72vwdChQwkA+fj40JgxY0SvceX3RQBA0dHR9NVXX9HFixdF5WPnzp3CGvAXX3yR1q1bJ6qfISIaPXq0cA/w4Ycf0pEjR0TfA/Br2bt3704LFiwQfR9y69Ytksvl5OjoSEOGDKGNGzeK3uOBj59eXl709ttv0759+0StwyT63/uAwMBA+uCDD+jw4cOiyoKI6ODBgwSAmjVrRhMnThRdnkREWVlZJJVKydvbm9555x367bffRO0vQPS/9WJZpmLXLBIRTZkyhTiOoy5dutCcOXPo+vXronXcvHmTZDKZUDd79+4VXTdERK+//jpxHEddu3alefPmiV5TSvS/ZavT6ei1116jbdu2iV6HSUT0xhtvCHtpJCUl0dmzZ0XvKcLHN8v2W1BQIEqHZZy17NfFxCcioo8++ogAkIeHB73xxht2lQu/Z45Go6HBgwfTqlWrRO9RMnHiREHH888/b9c+J0Qkao0rG3H9D3Lu3Dn88MMPGDBggF07cBERXF1dceHCBbRv396uNxinT5/G0KFDkZiYiIiICLt2i7t06RJWrVqF/v37C+vVxJCamoru3btj9uzZ6NGjhzC6aytEhN27d+Ozzz5D//790bFjR9E7TR4/fhyurq5YunQpEhIS0KxZM9E2rF69GuPHj0e/fv3QvXt30TuxpqamQqvVYsmSJUhISECLFi1EyfNrpqdPn45+/fohMjJSdDns2rULI0aMQP/+/dGtWzfRdZGdnQ0vLy9s27YNvXv3Fr3bpslkQk5ODtauXYuEhAS7dnk+cuQIFixYgIEDB4ouQ+BRm+jfvz+WLl2KmJgY0bvhms1mZGdnNyoPR48exejRozFw4EBhFocYiAhZWVlYv349EhIS7OpfMjIy8Mwzz2Dx4sXo1KmTXX1Deno6fvzxRwwYMMCuvsFgMEAulyMlJQWxsbF27bx64cIFjBs3Ds8++6xd/gAA165dwy+//IK+ffvatXtkdXU13N3dcfz4cURFRdm1E+6ZM2cwefJkJCYmIjAwULQ88Kh9btmyBc8884xdOyyXlZXB398fJ06cQFRUlN272CYlJSExMRFNmzYVLQ882oF927Zt6NOnj107LJeUlKB169ZIS0tDx44d7YqdZ86cwaxZs5CYmAhvb2/R8gBw//597N27Fz179rRrR/yamhq0bNkSFy9eRLt27ezKR1ZWFqZOnYqBAwfavat+ZmYmtm/fjvj4eNExg6e4uBjHjh1DTEyMXX4FQJh5FRYWZveIjl6vx9mzZxEaGmq3jvz8fBw9etTuNgIAeXl5WLhwIXr16mV3mRIRgoODcefOHbt9FHiUn0OHDjWqbgwGA3r27IlvvvnGrljAc/v2bRw8eBBxcXF27VQPPGo3UVFR+Oyzz+zugwAgJyenUe0XePQfLV555RVs2rTJ7n7dYDBAq9Xi2LFjiI6Otiu+mM1mVFRUYO/evXbdhwOPdhWWSCSN0mEPbI0rg8FgMBgMBoPBYDD+44hZ42rfqxQGg8FgMBgMBoPBYDD+Q7AHVwaDwWAwGAwGg8FgPNWwB1cGg8FgMBgMBoPBYDzVsAdXBoPBYDAYDAaDwWA81bAHVwaDwWAwGAwGg8FgPNWwB1cGg8FgMBgMBoPBYDzVsAdXBoPBYDAYDAaDwWA81bAHVwaDwWAwGAwGg8FgPNWwB9f/IESEmpqaRumorKwEET0hixgMBuMRT6JfaawOs9ncaB0mk6lR8gBgNBobbYPZbG6UDoPB0Cj5J6HDaDQ2Oh96vb5R8k9Ch16vb3Q+qqqqGiUPPIrfjaGmpqbRZVFWVtbosigqKmp0Oy0oKGiUPAA8ePCg0Tru37/faB337t1rdHkUFRU1+v7QbDY/kfzcv3//ibT7kpKSRttSWFjY6LI1GAyoqKhotC3l5eWN1lFdXd3osjWbzY3u24mo0XHuScRre5AmJSX9xy9qK8uXL08aPXr0323GE4PjOLz00kvYsGEDysrK0KRJEzg5OYnSkZ2djejoaGRkZICI4OfnB7lcLkrH1KlTsWvXLiiVSvj5+UEqlYqSv3HjBsaOHQuj0Qh/f384ODiIkgeAr776CmfPnoW3tzecnZ1Fy1+5cgWLFi2Cq6srvLy8wHGcaB0LFy5EXl4emjZtKroMAeDatWtYvnw5mjRpAjc3N9HyALB48WI8ePAATZs2hUwmEy2flpaGzZs3w9fX165yrKmpwfTp0wVfsKcc582bh1u3biEwMBAKhUK0/Pr163Ho0CH4+vqKbg8AcPjwYSxbtgwuLi7w9vYWnYeCggKMGzcOZrPZbl+YPHky0tPT4eHhAXd3d9Hyx48fx+TJk2E2m+Hv7w+lUilax9ixY3H48GFoNBr4+PhAIhH3XjI7OxsvvvgiCgoK4OHhAZ1OJ9qG+fPnY8GCBaiuroavry/UarUoebPZjP79++P48eOQSCTw9/cX3S4uXryIAQMGIC8vD46Ojnb1D19//TW++eYblJaWokmTJqLbltlsRq9evXDkyBGYzWb4+fmJrtP09HQMHDgQd+7cgVqthre3t+g6nTZtGhYsWICSkhJ4enrCxcVFlLxer0dcXBxSU1OFfIht43/88QdeeOEFIR8+Pj6i62PChAlYsmQJiouL7cpHdXU1oqOjcfLkSRiNRrvq4/fff8dzzz2HnJwcKBQK+Pr6io6dH3zwAebMmYMHDx7AxcUFHh4eosqCiBAVFYXffvsN5eXl8PLyglarFWXDjRs3EBERgYsXL0Kv18PX11d0DN+xYweee+45XL9+HQDg6+srut9csGABxowZg+zsbEilUvj6+opu6zNmzMD777+PGzduQCKR2KXj22+/xciRI5GZmQkAdt1T/fbbb4iPj8elS5eg1+vh4+MDlUolSkdJSQlat26NI0eOoLi4GB4eHqL9nOM4DB06FPPmzcPt27fh4OBgVyw4fvw4YmNjG5UfiUSCXr16Ye3atbh37x6cnZ3h6ekpuu3//vvv6N27NzIyMmA2m+Hr6yu6D5JIJOjZsyc2b96MoqIieHh4wNXVVZQOANi0aROGDx+OnJwcKJVK+Pr6ii7b0tJSdOjQAWfOnIHJZLKrLwKAAQMGYPfu3aiuroaPj4/oWMtxHIYPH45ff/0VNTU18PX1FV3HZrMZ/fr1w4kTJ8BxnF3xmufzzz+/m5SUtNymHxPRU5s6duxI/238+eefBEBIYWFhNGXKFDp27BgZjcYG5cxmMxmNRtLr9TRs2DBBXqlUUkJCAi1evJiys7NtsuHixYuCvKurKw0fPpw2bdpEJSUlNudj0KBBBIDkcjk988wz9N1339Ht27dtlk9JSRFs6NixI82YMYMuXbpEZrPZJnmz2UwdOnQgABQYGEgTJ06kY8eOkclkstmGbdu2EQBSq9X0j3/8gzZs2CCqDMxmM0VERBAACg4OpqSkJLpw4YLNeSAi2rx5MwEgrVZLw4YNo19//ZUqKyttlq+pqSFfX18CQFFRUTR79mzKysqyWZ6IaNy4cQSAvLy8aOzYsZScnEwGg8Fmeb4clUolDRo0iNasWUNFRUU2y9+4cYOkUikBoOjoaNF50Ov1FBAQQAAoICCAJkyYQIcPH35se6rNa6+9RgBIpVLR888/T2vWrKHCwkKb5Q8ePCj4c9u2bWnKlCl08uRJUf7csWNHAkAKhYL69+9Py5cvp7t379psQ3JysmCDp6cnjRw5knbs2EEVFRU26xg6dKhVPj7++OO/7JssKSwsJCcnJwJAEomEYmNjadasWaLa9saNGwUb1Go1DRo0iFasWEF5eXk252Pw4MGCDi8vLxo1ahRt27aNysrKbJIvKCggrVYr6AgNDaXJkyeLKot169YJ8gqFgvr06UOLFi2izMxMm/PRv39/QYeHhweNGDGCfvnlFyouLrZJ/u7du6RSqQQdwcHB9Mknn9CRI0dsbuNLly5tVD7MZjN17dq1Ufm4ceMGyWQyQUf79u3po48+okOHDtmcj/nz5wvyMpmMevbsSXPnzqUrV678pW/y8bdz586CDmdnZxoyZAj99NNPdO/evcfKm0wmMhgMlJmZSXK5XNDRtGlTeuedd2jXrl0NtlP+2jU1NVRVVUXff/+91T1EeHg4TZkyhY4ePVpvWZhMJtLr9VRVVUXl5eVUUlJCL7zwgiAvlUqpW7duNHPmTDp37lydsrCULysro+LiYnrw4AG1atVK0OHg4EAJCQm0aNEiunbtWh37DQaDcP3i4mIqKCigrKwsoa8AQBqNhp599ln6/vvv6ebNm3XyX11dTRUVFVRSUkKFhYV0//59unTpEjk4OFjpSExMpKVLl9KNGzes8lBTU0OVlZVUWlpKRUVF9ODBA8rPz6erV69a2VFfXh5nw927dyk3N5fatGljVaaxsbE0Y8YMSk9PJ5PJJJRDdXW1UA8FBQWCjlu3btEbb7xhVbdBQUH0wQcf0IEDB6i6utpKR0VFBZWWllJhYaGQlzt37tDOnTutdOh0Oho6dCitWbOG7t27Z+VPlZWVQp1a2nL79m0KDw+3yk9cXBx9/fXXdObMGTKbzYJP87ZY6uHt+emnn6xs8fPzo9GjR9P27duprKysjp7KykqhbIqKigSbQkND6/RBCxcutPI1y3tkS12lpaVUXFxs1R8DoDZt2tDEiRMpOTmZampq6vgsb1dNTY2gr7S0lFq0aCHocHFxoZdffpnWrl1LDx48eGwfwOs0Go00depUQYdcLhfyIyY27N27V9DBx9qvv/6azp8/b3OsPX78eJ1+YPbs2XT58mWbdWzYsMEqXj/77LOi4zUREYBTZOOzIUdP8bTTTp060alTp/5uMxokJiYG169fF4bLzWaz1Xl93z0OjuMgkUggkUjAcZwgK2ZagUwmg4ODA9RqNVQqFTiOE/RaHrOysuqdJuDg4ACNRgNHR0coFApIpVJIJJI6x4KCAty4caOOvEKhgFarhZOTE9RqNWQymVWSSqXC8ffff68zrU8ul8PR0RGurq5wcnKCXC5vMF27dg0XLlywkpdKpYK8s7MzlEolFAoF5HI5FAqFkORyOWQyGTZs2FCnfNVqNVxcXKDT6aBSqazkaqeLFy8iPT29Th60Wq1gg0KhEOyonWQyGX766Ser6RYcx0GtVsPZ2Rlubm5wcHCwkqmtKzU1FVeuXKm3HnQ6nVCXtcuATwUFBdi/f7+VvEQigUajgZOTE1xcXKBUKustQz4PmzZtqjNlxMHBAVqtFs7OzkIeeBm+DvnzlJQUFBUV1fFl3ga1Wl2vD8hkMsjlcly+fBk5OTl1fEGpVEKr1UKj0Qi/52Us/bKgoKCOL0kkEshkMqjVamg0GiiVSiv/rX08ceJEnTLgZVQqFdRqdb1tSSqVQiqVIj8/H/fu3UNt5HI5lEql4Iu1+wnL82vXrtWR5/U7ODgI9vD9Au9vfKqoqEBhYWEdHRzHWfld7bfMlm/RCwsL653GJJFIBD/iRzQsy4s/N5vNDU4x4+uOt4GX4QMaf67X6xucdmfpOxzH1dHBp6qqqnqnQXEcJ+jgR9zqC65ms7lBGyQSidB2+HzUJ280Ghuc+mzpx3y8qC3Pl0V98Png/Zcv+9ryvB0N5YPXweejdgykf09Ja+hewzI2WOajduxsKA5yHCfI835pGTstbWkIvq1b2sAnk8lk03Q4/vq8Dfx0cTHxm9fB22DrtWvr4P3anmnzfJ9iyz3L43TwNth7j8n3KU/zPSrjv4cn4W+W99iW/ahYHZb9APBo5osYu/g+ke/TTCaT6KUOfN/Oxyme2naYzWaUlpbWq6NTp05ITEzEwIEDERER8djRdo7j0omoky22sQfXRhAUFISMjIy/2wwGg8FgMBgMBoPBeCqQSCSIjY1FYmIihg8fDh8fnwZ/K+bB1b7JyAwAwM8//4yampp6R0AaGhXJzvhbrPoAACAASURBVM5GQkKCoEOn06Fbt27o0aMHoqKioFKphN82lD799FOsW7cOwKM3K2FhYYiLi0OXLl3g7e1d76iv5bG8vBwjRoywGhXx8/NDTEwMoqKi0K5dO0gkEuGNL3+0PN+0aRN27dplVR5t27ZFZGQkOnbsiKZNm1qNGBiNRqtUVlaGjz/+2OrtjUKhQFhYGCIiIhAWFgZ3d3cYDIZ6k16vx86dO5Gammplg1arRUREBEJDQ9G+fXs4OjpCr9dDr9cLcnwqLS3F/Pnz69Srn58fIiIiEBwcjFatWoHjOCs5y7R//37Ufrkil8sRHBws2ODp6Wl1bX6DDX7zgsWLF9exwdPTU7ChdevWkMvldWT5z9u2bavzAkWpVCI0NFSwgS/L+my4cOECtm3bZiXPcRzatGmD8PBwhISEIDAwECaTqd6yLC4uxpw5c+rkoXnz5kJdtmrVCgCs6s/yfObMmXXe2gUEBKBjx44IDw8XfLK2HxiNRhgMBqxYsQKXLl2ykvf19RX8sX379pDJZIL/8bJ8OnDgALZu3Wol7+Pjg44dOyIyMhKhoaFwcHCw8mfL48OHD/HBBx9Yyet0OkRFRaFTp07o0KEDnJyc6m1L/HHhwoU4fvy4VR3GxsYiJCQEUVFR8PPzsxoJqj0alZ+fjzfffNPKhuDgYERHR6NDhw5o164dpFLpY6fgrFy5Eps2bRLkXVxc0KdPH7Rt2xYxMTFwdnau88bV8rPJZMILL7yAhw8fCt916NABcXFxCAsLQ5s2bYQRqdpvX/nPp0+fxtixY4XvtVotEhISEBQUhM6dOwtrk2qPGlt+N3PmTKv6DAoKQs+ePREaGoqQkBDhDbLlaLNlMhgMSEhIEGYByOVy9OzZExEREYiKihLWaVomvq/n0/Hjx63y0aRJE/Tp0wehoaGIjIy0mhHTkI5p06ZZ9bMdO3YU+unWrVvX+X3tz9XV1YiPjxc2JlGpVIiPj0doaCji4uLg5ub2lzoOHDiAf/7zn4INAQEB6NatGyIjI9GhQwdh9LsheYlEgvHjxyMlJUUo85iYGERERKBbt25o1qzZX8bOkpISdO/eXRg9dnJyQo8ePdCpUyd06dIFTk5OVjGyPh2//vorpkyZYuUTUVFRiIuLQ0hICORy+V/G3jfeeANHjhwRfCIuLg6dOnVCt27dhDXIliOvlud8PmJiYoSR+CZNmiAuLg6xsbGIioqympXR0MyM3bt345133hHyER4ejsjISPTs2ROtW7cWRllqy1mmSZMmCfcQSqUSnTt3RpcuXdCjRw94eHhY/dZSn2Xq0aOH0Oe6ubmhc+fOiI+PR0xMDDQajZVcfecGgwHBwcHCJk3+/v6Ii4tDfHy84FcNzW7hj+Xl5Wjbtq2waU7Tpk3Ro0cP9O7dW6jThuT5c71ej6CgIMGOgIAAxMfHIz4+HmFhYVazEho6SqVSxMbG4uzZswAexW/ejsjISDg4ODRYDpbnU6dOxcKFCwE8mvnVtWtXxMfHo3v37nB2dq63Lmp/d/78eXTp0kXwj7CwMMTHx6N3795o3rx5vXVZ21f0er1V/ep0OvTs2RO9e/dG586doVKpGvRP/jw3Nxd79+7F5MmTBVsiIiIQHx+PXr16oXnz5lZto3Zb4TgOZ86cgUQiwfvvv4+rV68Kbb979+6Ij49HXFwctFqtVXu3TPfu3UN+fj4kEgnOnDmDqVOnCra0adMGPXv2RK9evdC2bdsG7+EvXLgAs9ksfDdu3Djk5uYK/WlcXBy6d++Obt26wcXFpU4fWFxcjJycHCHuSaVSbN++HWvXrrWypXv37ujevTvatm1bJy5cv34dlZWVVrqvX7+O6dOnCzp0Oh26du2Kbt26Cc8SfH9bWVkprOG2jJV3797FJ598IuhQq9WIiYlB165d0aVLl3r3dqgdt9PS0jBu3Djhs5OTExISEpCYmIh+/frZvf/LY7F1TvHfkf4b17iOHDmS2rdvT1OmTKHU1FRRazKJiPLz88nDw4MGDx5Mq1evpocPH4q2Ye7cuSSXy6l37960YMGCOmtS/oqKigpq0qQJ6XQ6GjZsGK1bt+4v5/fXZvbs2cI6gwkTJtD+/ftFre0sLS0ld3d3kkgk1KVLF/riiy8oNTVV1LrGOXPmCOsUXnjhBVqxYgXl5OTYLF9RUUFeXl4EgEJCQujDDz8UnQ++HLRaLQ0aNIi+++47un79us3rC/Lz80mj0QhrhSdPnkwpKSlUXV1tsw0JCQnC+tC33nqLNm/eLGp959dffy2sXRs2bBitXr1a1PqGPXv2CGvG/vGPf9Dy5cut1jj9FTdv3iS5XC6sb/ruu+9ErRUxGo0UFBQkrJ2ZN2+eqDWZRETTpk0jjuMoMjKSpk+fTidOnBDli7du3SKFQkEBAQHCmrfy8nKb5YmIJk6cSCqVigYMGEBLly4VVYZEj9qUm5sbtW3bliZNmiRq/SDPxo0bSaVSUWJiIi1btkzUuneexMRECgwMpPHjx9OBAwfqrD/6K+7du0dOTk7UvXt3mjt3LmVkZIi24V//+hfpdDp69dVX6ZdffhG19p2nd+/eFBwcTFOmTKE///xTdF9/69Yt0mq11K9fP/r+++/p1q1bom1YsGABNWnShN58803atWuXqL6J6NG6rKioKOrYsSN9/vnnwvo2MVy5coUcHR1p0KBB9OOPP/7letD6+PzzzykgIIDGjx9Pv/32m2ifMJlMFBISQnFxcTRnzhy7fOLs2bPk4uJCw4YNE70nBM/06dMpKCiIPvnkEzpx4oRonzCbzRQdHU29e/emJUuWUG5urmgb7ty5Q15eXvTKK6/Qli1bbF73bcnevXupWbNmNHHiRNH7CfB8++23FB4eTp9//nm9a2tt4auvvqKoqCiaOXMmXblyRbQ8EdGiRYsoMjKSvv76a7t17N27l9q1a0dTpkyhtLQ0u/Ly8OFDatmyJY0ePZr27t0rKoZbMnToULv2SLDkjz/+oFatWtFHH31Ex48fF+2nRI98tXfv3pSYmEgrV660q90TPdq7oVmzZjRhwgRKSUkRHZN4evXqRb1796bFixeLus+zZOfOneTn50djx46lffv22VVHVVVVFBgYSH379qXvvvvObluef/55CgkJoalTp9oVX4iIRo8eLcRae/pVokf7MDRv3pzef/99OnjwoF06iNga16ea3NxcBAQE2C1fWFgItVpt106+PEeOHEF4eLjo3Qh5srOzce/ePURFRYneVRF49LJk8+bNiIyMRLNmzeyyIT09HTdv3kSvXr1E77zH27B06VJhRM2efKSlpeHy5cvo06fPY6dANITZbMa3336LTp06ITo62q7dbJOTk/HgwQP06tULHh4eouXv37+PTZs2oW/fvsLoshiICMuWLUNUVBTCw8NF77AHAFu3boW3tzeioqLs2pHu6NGjMBgMiI2NtWtX49zcXFy4cAE9evSARqMRLU9E2LlzJ7p06WJXHQDApUuXwHGc8LbVHhsOHTqE6Oho0TsD8ty5cwfV1dVo0aKFXfLAox19W7RoYbcNRqMRGRkZaNeunV3lAAB3796FUqm0a1dknszMTAQGBtq9Q6LBYMCtW7fQvHlzu224e/cuHB0d7e6nASArK0sY0bSH6upqPHz4EH5+fnbbkJeXB1dXV7t9Ani0E25gYKDdPlFZWYmKigq72yfw6F+e6HQ6u/ppnrt378Lb29tueb1ej8rKSrtiHk9xcbGw5t9eioqKhNEleykpKbFrJ3xLSktL7dqJ3pKysrJGtTHg0b9JcXR0bJSOyspKODg42N1WgUdxoLKy0q44ZklZWRkcHR0bVb/8usrGlktxcTGcnZ0bbUtZWVmj2g3w6H5J7E7gteFnljXGb81mM3JzcxEYGGi3DiLCtWvX0Lp1a7vzYzQace3aNbvvWyz5j65x5TiuDYBNFl81BzCdiBZa/KYHgB0A+N18fiWiL/5K93/jgyuDwWAwGAwGg8FgMP7Da1yJKANA+L8vLAVwB8C2en56hIgGNvZ6DAaDwWAwGAwGg8H4v4X9cxLqpxeALCLK+ctfMhgMBoPBYDAYDAaDYQNP+sH1ZQAbG/hbZ47jznEct5fjuPZP+LoMBoPBYDAYDAaDwfgv5Yk9uHIcpwDwLIDN9fz5NICmRBQGYDGA7Y/RM5rjuFMcx5168ODBkzKPwWAwGAwGg8FgMBj/P+VJjrj2A3CaiO7V/gMRlRJR+b/P9wCQcxznXp8SIlpORJ2IqFNjdgBkMBgMBoPBYDAYDMZ/B0/ywXUoGpgmzHGcF/fvvZI5jov693ULnuC1GQwGg8FgMBgMBoPxX0qjdxUGAI7j1AD6AHjb4rsxAEBEPwB4AcA7HMcZAVQBeJme5n8gy2AwGAwGg8FgMBiMp4Yn8uBKRJUA3Gp994PF+RIAS57EtRgMBoPBYDAYDAaD8X+LJ72rMOMxlJWVYfPmzSgpKbFbR2pqKi5cuAB7B6zNZjOys7Ptvj4AFBYW2n19ADCZTKiurm6UDQaDoVHyZrMZJpOpUTqMRmOjbWjsxIOnQf7vtqGx9VhdXd0oG4gIhYWFjbIhLy+vUT5NRLh48WKj8nH79m3k5ubaLQ8AaWlpjerfDAYDkpOTodfr7daRmZmJM2fONKos/vjjD9y+fdtueb1ejx07dqC8vNxuHZcvX8bx48cb5d979+5tVH9fXl7e6JiVnp6Ow4cPN6q/3Lp1K65du2a3fGFhITZs2ICCAvtXKB0/fhwHDx5ETU2N3To2btyI8+fP2+2bZWVlWLFiRaN88/z589i6dWuj6vTAgQM4cOBAo+L4li1bcOTIkUb5xc8//9zoNrJlyxYcOnSoUf1vcnIy9uzZg8rKSrt1ZGdnY+3atWjMpqREhBUrVjQ6Fhw7dgy7d+9uVH6MRiNWrFiBrKwsu3UAj9rdgQMHGtXuTCYTVq1a1ej4dvToURw7dqxR/vbw4UNs2bIFpaWldusgIvzyyy+4d6/OlkKi2LFjB/Lz8+2WN5lM2LFjR6PyYg/SpKSk/+gFxbB8+fKk0aNH/91mPDGUSiUmTZqEMWPG4I8//sDDhw/h5uYGNzc3/HsJ8F9SUlKC0NBQ/PTTT8jMzIRUKoWfnx9kMtsGzzmOw2uvvYavv/4a+fn5cHFxgZeXl83XB4BTp06ha9euyMnJgUajgZ+fHyQS29+BcByHhIQE/Pbbb5BIJGjatCnkcrnN8gCwbds2jB07FhUVFQgICICjo6MoeQDo168fTp48CUdHR9F5AIA9e/bgnXfeQXV1NZo2bQqNRiPahmeffRZnzpyBq6srfHx8RNUDAKxZswYzZ86EVCpFYGCg6HLMz8/H4MGDUVFRgcDAQLvyMGzYMFy+fBne3t5wc3P7a4FafPrpp9i6dSucnJzg7+8vugw2bdqEyZMnw2QyoVmzZlAqlaLk79+/j5iYGNy+fRs6nU50e+A4Dq+++ipWrFiBqqoqBAQEiC7HjIwMhIaG4vLly3a1CY7j8M9//hMffvghcnJyoFarRfu02WxGmzZthIDo4uKCJk2aiCqLw4cPo3Pnzjhy5AhKSkrg5eUFFxcXm+WlUik++ugjjBkzBmfPnkVNTQ38/PygUqls1iGRSBAREYGlS5fi+vXrkEgk8Pf3t7mPBIDTp08jJiYGO3bsQF5eHhwdHeHt7W1zWUilUnz22WcYOXIkjh07huLiYnh6eooqC7lcjsjISCxYsAAXL16EwWCAn58fHBwcbNZx6tQpdO/eHb/88gtycnKgUCjg6+sLqVRqk7xCocAnn3yC0aNHIyUlBQUFBdDpdKJillQqRWRkJObPn4+zZ8+iuroaPj4+UKvVNufj6NGj6Nu3L9avX4/s7GzRcU+lUmHChAl49913ceDAAdy7dw9OTk6i/FsikSAmJgbz5s1DWloaysrK4OXlBScnJ5vzcfLkSfTv3x8rV67E1atXYTKZ4OfnB4VCYZO8UqnEV199hdGjR2Pbtm3Izc2FUqmEr6+vzW1dq9WiX79+SEpKQkpKCh48eABnZ2d4eHjYXBZGoxFdunTB/PnzkZqaipKSEnh4eIjy7zt37iA+Ph7ffvstzpw5g4qKCnh5eYmK5devX0ffvn2xZMkSnDt3DlVVVfD29hbV/969exfx8fFYtGgRTp8+jYqKCnh7e4uyQyKRIDY2FnPmzMHx48dRVFQEd3d3uLq62qzD2dkZr7zyCj7++GPs3bsXeXl50Gg0ouIRx3HYt28fXnzxRaxatQrXrl0DEYnyMeCRn8XFxeGbb74R8uPh4SEqPxKJBGvXrsXw4cPx888/48aNG5DL5aL6HwCQyWTo3Lkz5syZg5MnT9rV7iQSCVatWoWhQ4fi119/RW5uLlQqlah2Azx6IdmpUycsXrwYFy5csCs+qVQqvP3223j//fdx6NAhFBYWwt3dHTqdzmYdHMdhzZo1eP7557F3717k5+fDyclJ9L3L9u3b0a9fP+zZswd3794VrUMikWDhwoUYOnQoDh8+jKKiInh6eoryE57PP//8blJS0nJbfss9zUtNO3XqRKdOnfq7zWiQXbt2oaSkRBg5s0z1fUdEOHv2LJYvt64bT09PREREICwsDEFBQUKj5uum9nHWrFlWb5+VSiVCQ0MRHR2NqKgoeHh4QCqVQiaT1Xs8ffo0Ro0aJci7u7sjOjoasbGxCAsLg4ODA+RyORQKhdXR8nzAgAFIT08HAOh0OnTs2BFxcXHo1KkTNBoNFAoFlEqlkGp/3rlzJ15++WUAgEajQVhYGOLi4tClSxe4uLhAqVTCwcFBSJaflUqlcJOdnZ0NjuPQqVMnhIaGokePHvD29raSrS9JpVKsXbsWI0aMAAB4e3ujY8eO6Ny5MyIiIqBWq+Hg4ACVSiXIWJ7LZDIQEdq1a4eMjAxIpVJ07twZ7du3R7du3eDl5SXIWCb+O/6hZPXq1Xj99dcBAM2bN0d0dDQiIyPRrl07aDQaQU6tVlsd+Ru2yspKBAQEoKCgQLghad68OWJiYuDs7Ay1Wm2VeJ2WN3yvv/46Vq9eDalUil69eiEqKgpBQUHw9PSERqMR5Cx1yOVyoXOzzENERASGDBkCZ2dn4QHOUs7SFt7Pr169irZt2wIA/Pz88NJLLyEyMhJyudzq93z+Lc9lMhn0ej2aNWuGvLw8KJVK9O/fHy+99BKIqMH6q/357bffxqpVqwAALVq0wJAhQxAbG4uKiooG/Zg/VygUOHPmDAYOHAjgUWferVs3vPDCC9DpdJDJZEL7aSjJZDKMGDECfH+nVqvRv39/9OrVCwqFAlqttsH2zB+vX7+O1157zapdP/vss2jVqhV8fHwEv5dIJJBIJFbn/OclS5Zg+/b//W9lgYGB6NevH3Q6Hdq2bQuZTAaJRAKO4+o9ms1mjBgxwmo0JywsDJGRkQgMDESzZs2EGwWO44Rk+fnSpUv47LPPBHmpVIq4uDj4+vqiY8eO8PLyEn5vieXnH3/8Eb/99pvwWa1WIyYmBs2bN0dERAScnZ3xOMxmM8aPH2+VDy8vLwQHByMkJATt27eHUqm0GtWo3U9fvXoVs2bNstLbunVrtGnTBuHh4WjRogU4jrOSs5zBQERYu3YtDh06JMjLZDK0b98e7du3R1hYGLy8vOqNM3wymUz48MMPrUZOnJyc0K5dO4SHhyMkJAQajaZOvLL8fP78eXz//fdW+fD19RVsaN26NaRSqZVc7eOqVauEeMHTsmVLhIeHIzQ0FL6+vkK584mXN5vNqKmpweTJk61G51QqFdq2bYuwsDCEhITA2dnZSr52On36NNauXWtlg6urK0JDQxEaGoqgoCAoFAphNk59On766SdcvHjRSoe/v79gQ2BgoJAPSx38eU1NDZKSkqzyIZVK0aZNG4SGhiI4OBju7u5C3VnK8scrV65g9erVVjao1WoEBwcjODgY7dq1g6OjI0wmk5Ws5fmePXtw7NgxKx06nQ4hISEICQlBq1atIJfL65Xlz1euXImbN29a6fDx8RHaR/PmzcFxXIM2mEwmzJ07t85oTdOmTQUdAQEBQlnUp8doNOKbb75BVVWVlY7mzZsjODgY7du3h6+vr+BLDdkyf/78OiPQAQEBQpn6+/vXqdfaxzVr1iAzM9NKB99nBAcHC+VR2ycsz48ePYr9+/db6XBychLy0qZNGzg4ODzWR0tKSjB79mwrHTKZDK1btxbK1c3N7bFtpbKyEqtWraozsu/l5SXo4Puv+torEeHmzZvIysqqkx+lUol27dohJCQE7dq1g1arrbffMJlMOH36NIgIR48exZ07d6z0+Pv7IyQkBMHBwWjatKlgi2U/dufOHdy+fRtEhKKiIuzbt89Kh0ajQfv27REaGoq2bdtCrVbXe89eU1MjfE5OTrYa6eQ4Di1bthT6ET4+8b9/+PAhsrKyrHRmZWXh+PHjdco2NDQUYWFhaNWqlRAn+dlU5eXlVvGhtLQUW7dutdLh6uqKsLAwhIeHo23btsLLivLycpw/fx61qaqqwrp16+roCA8PR0REBNq3bw+FQvHY0fvc3FxMmzbN6rt27dph4MCBSExMROfOnW16UcFxXDoRdfrLH4I9uDaKNm3aNGr6EsN+FAqFEHzsQSaTQaFQ2D0VRiKRQKVSwWAw2DWtUSqVQqVSQaFQ2DXNVC6XCw+1JSUloqdsKRQK4SHQYDCInp4klUqFB1GFQmHXFBylUik80Obl5cFsNovWIZPJoFarUV1d3ajppQwGg8FgMBiMJ4ebmxsGDRqEzz77DAEBAQ3+TsyD6xPZnOn/KqGhoXBxcbEaOeATPwpR+7uSkhLU9zCuUqng4uICnU4HR0dHq1GI2seMjAw8fPiwjg7+IcDBwQESiQRGoxEmk0k48udGo7HBm3yJRCKMKEokEhgMBiHZ+pJDIpEII3Imk8mutSP8KBD/Bq82tjyk8DrqW0PDl8NfIZVK6304NpvNqKio+Et5vt5ql53JZLJ5/ZvlqAwPXye2rC2oT16v10Ov16O4uNgmG2pjMplQWlpq89oGvi4tqampQU1NDYqKiv5SXiqVguO4OnVmNBptsoF/UWA0Gu1alyWTyYSZBLzdYtbcKJVKqFQqODo6wmw2W7UrW9qXUqmEo6Mj1Go1lEplnbbN+3NDZSGXy6HVauHo6AiNRmP1dtzyzX1JSUm9OjiOg1arhZOTE7RarTAaU3t0zmw2Iycnp9726eDgAGdnZ2EmAGA9SsmnmpoaXL9+vY68RCKBk5OToMNyKnXtssvPz0deXl695eji4gIXFxdotdo6/aslFy5cqDOSw5eDi4sLXF1doVQq64wY8+dVVVU4c+ZMHb1yuVyQd3Z2FnzbUgf/OTc3t96XQhqNBq6urtDpdFCr1fXGID6dPHmyTj4kEolgg06nE/rr+mJXWVlZvTHLwcEBrq6ucHNzg1arFfJR30h8RkZGnXxwHAcnJye4ublBp9MJcctSzvI8OTm5TiyRy+XC1GUXFxchbtWXCgsL8eeff9bJh6OjI9zc3ODu7g6NRtPgjASJRILz588jJyenTlm6urrC3d0dbm5uUCgUVvK1Zzns3r27Tj4cHBwEG5ydnYV81NYhlUpRXFyMlJSUOvngy9LDw0PIh1QqtZLlzzMyMuqMHEulUiEf7u7uUCgUgkxtHVKpFMeOHaszCqZQKKDT6eDh4QE3NzerfNSnZ9++fXVGOh0cHODu7i5MTW0oH/zn3bt314nFKpUK7u7u8PT0FNpYfWXJn+/fv79OLKxtR0M6+OOJEyfq+LhcLhfs4GffNDTrRSqV4saNG0hLS6vjX3yZenh4QKlUPtZHzWYzfv311zr+4ejoCA8PD3h6esLJyanBdiKRSFBVVYXk5OQ6MU4mkwk+5uHhUae9Wbbb69ev4/bt2/WupeZt8fDwgJOTU739BvBorS3HcaioqKgTU6RSqVAu7u7uQh9m2X/l5eUhJydHuAeqzxa1Wi34vLOzc53+88yZM9Dr9YJNlZWVddqvZR+g0+mgUCgE+aKiIqt9BjiOg8FgqHfQRKPRCP2ZVqsVfn/t2rV67zfLysrqfCeXy4V+2dnZWajP+mIqgHrvQ6VSqRAfXFxcrEZMa8dKg8FQZzYN8Gjktn///khMTETfvn1FLSP4Sx43zejvTh07dqT/Nj766CMCQFKplHr06EELFiygzMxMm+XLy8vJ3d2dAJCzszO9/PLLtH79eiosLLRZx4YNGwgAASCJREKdO3emL774gtLS0shkMjUoZzQaqbKykoqKiqh169aCDrlcTj169KCZM2fS6dOn6+gwmUxUXV1NJSUldP/+fbp16xbNnj1bkAdAWq2WBg0aREuWLKFr166R2WwW5A0GA5WVldGDBw/o1q1blJmZSWfPnqUmTZpY6fD396eRI0fShg0b6N69e1Z2V1RUUEFBAd25c4eysrLo0qVL9Nlnn1nJS6VS6tKlC02fPp2OHDlCNTU1RERkNpupurqaiouL6e7du3Tjxg26cuUKpaenk5+fn5UODw8Pevnll2nlypV048YNQb6mpkaQz87OpsuXL1N6ejpNmzbNSh4AhYSE0AcffEC7d++m0tJSIiLS6/VW8hcvXqS0tDQ6ePAgOTk5Wck7OjpS//79ad68eXT27FkymUxkMBiotLSU8vPzBfnU1FRKSUmhhISEOjYEBwfTe++9R9u3b6fCwkIymUxUUVFB9+/fp5s3b9KlS5coLS2N/vjjD/r444/ryDdp0oSGDh1Ky5cvp8zMTDKbzaTX66mkpITy8vIoMzOTzp8/TydOnKDVq1fXkXdxcaHnnnuOFi1aRBcuXBD8gddhmY9jx46Ri4tLHfnnn3+elixZQpcvX7byJ7PZTFVVVVRUVER5eXmUnZ1Nffv2tZJ3d3enl156iVasWEHZ2dn1tgc+T+Xl5bR27do6fjBs2DD66aef6Pbt23/ZJo1GIwUFG1kCxgAAIABJREFUBQnyTk5ONHjwYFq2bBndvHnzL+WJiH799VdBXiaTUffu3WnWrFl07tw5q/w/jmeeeUbQ0axZMxo3bhzt2bOHKisrbZLPyckhhUJBAEipVFJCQgItXry4wTKsj4ULFwo2BAQE0Lvvvkt79+6lqqoqm+TNZjPFxsYKbbp79+40Z84cunr1qs3lkJ2dTTKZjACQm5sbvfrqq/TLL79QSUmJzfmYO3eukI/w8HD69NNP6eTJk4/tY2vno0OHDgSAVCoVDRo0iFauXEl379612YaLFy8Sx3EEgAIDA+m9996jgwcPCn2bLUydOlWIFd26daN58+bRtWvXbJY3GAzUokULAkA6nY5GjBhBW7ZsEfo2Wzh69KhQlqGhofTpp5/SqVOnbK5PIqJx48YRAHJwcKDExERauXIl5efn2yxfXV1Nvr6+BID8/Pxo7NixdODAAVFleejQISEfMTExNGvWLLpy5YrN8kREkyZNIgCkVqtp8ODBtGbNGiooKLBZ3tKvfHx86J133qH9+/eLykdhYSFptVoCQO3bt6epU6dSWlqaqPq4evWq4JvR0dE0c+ZM0WWRnp5OAIjjOIqNjaU5c+aI8k0iooyMDJJIJFZ21I4Zf0VJSQm5uroSAGrXrh1NnjyZUlNTbW7rPHws9vT0pFGjRtHOnTtt7nt5+Fgkk8moT58+tGTJEsrNzRWlo6qqinx8fIQ4MGHCBEpJSSGDwSBKz4IFC4R7xL59+9LSpUvp1q1bom3x9vYW7vHeffdd0e2OiOjbb78VYkLPnj1F33sTEZWWlpJOpxPazpgxY2jPnj02xyaet956y6pclixZQjk5OaJ0rFu3rlHxhYho3759go6WLVvSxIkTKSUlhfR6vc06Vq5cKegICgqiSZMm0aFDh0T7CoBTZOOz4d/+cPq49N/24FpeXk4jR46kdevWiQo0lmzevJkmTJhAycnJopyLx2AwUNeuXem1116jjRs32mXH+vXrqUWLFjR27FjauXOnqBsQokcPH23atKHOnTvT9OnT6ejRo6Lz8q9//YucnJzoueeeoyVLllBGRoaoQKPX66lVq1bUtm1beu+992jnzp2ibkqJHr0AUKvVlJCQQHPnzhUeEm3FYDBQUFAQBQYG0qhRo2jjxo2ibqSIiBYvXkwKhYJ69OhBX3zxBR07dkxUWebm5pKDgwO1bNmSRo8eTT///LMoG4xGI4WFhZFOp6PBgwfTkiVL6NKlS6Lq4vXXXydHR0fq168fzZkzh9LT08loNNosv3jxYlKr1dS3b1+aPXs2nTp1SpT8uXPnyNHR0e56NJlMFBkZSb169aJvvvmGzpw5I/qGZc2aNdSpUyeaOnUqHTlyRHR7MBqNlJCQQG+++SZt3bqViouLRckTEaWmplKvXr1o3rx5dOXKFVF1yDNjxgwaPXo07dixg8rLy0XLV1dX0wsvvEAzZ860emEhhrS0NBo6dCitX7/e7n523rx59NFHH9GRI0dE+RJPTU0Nvfbaa/Tdd9+JviHhSU1NpdGjR9OuXbtE37zyzJ07l2bMmEHnz5+3qywrKytp5MiRtGbNGnr48KFdNvzxxx80ceJEu25meGbNmkWLFi0SXgaKpbS0lMaMGUPbtm2zyy+JiJKTk+16YLZk3rx5tGzZMsrLy7NLvqqqiiZMmNAon7h48SJNmTJF9E2uJbt27bLrIdGSVatW0ffff0937tyxW8eyZctEv4CozerVq+mHH35olB379u1rdHncunWLJk2aREePHrWrz+FJSkqijRs32hUDeFJSUujLL7+0u98gehQXJ02aJPqFX20OHjxISUlJdPr06UbZMnHiRNGDPLXZuXMnTZ8+vVF9QGFhIb355pu0efNmu8vFbDbThAkTGhVfiB4NpM2ePdvueG8ymWjUqFE0f/58un79ut12EIl7cGVrXP+PYTKZhOkU9lJcXNyoYf/y8nIYjcZG6cjKykLTpk1F7RRqSUlJCcrLy4VNQezh2rVraNq0qehdbHmKi4tRWFiI5s2b223DmTNn0KZNG1E7dFqSmZkJhULx2LUHj6OwsBC5ubkIDQ21y6dMJhNOnTqFDh06iN4Rmefy5cto2bKlqF0TLcnPzxemfdqDXq+H0Wi0uw6AR9Om7b0+8GjquuUUU3sgokbJMxgMBoPBYIiFbc7EYDAYDAaDwWAwGIynGjEPrvYPuzEYDAaDwWAwGAwGg/EfgD24MhgMBoPBYDAYDAbjqYY9uDIYDAaDwWAwGAwG46mGPbgyGAwGg8FgMBgMBuOphj24MhgMBoPBYDAYDAbjqYY9uDIYDAaDwWAwGAwG46mGPbgyGAwGg8FgMBgMBuOphj24MhgMBoPBeGpp7P+bfxL/r/5p0PE02MB0/H+jg8Fg2IY0KSnp77ahQZYvX540evTov9uMJ0JhYSGGDh2K+/fvw8PDA66urqJ1bNy4EVu2bIGTkxO8vb3BcZwoeaPRiKVLl8LNzQ06nU709QEgPT0dDx8+hKenp+jrA4DJZEJycjICAgIglUrtsuHy5cvQ6/VwcnKyS56IcOjQIfj4+Nhtw40bN1BcXGxXPfKcOnUKnp6ekEjse390584dmM1mODg42CVvNptx69YtODs72yXP26DVau3yBQB48OABOI6DXC63S95kMuHq1avw8PCwSx4A0tLS4ODgALVabZf8w4cPsW/fPgQGBtqdj+3btyMvLw/+/v52+UN1dTVmzJgBtVoNHx8fu+rj6NGjWL9+Pdzd3e0uz3nz5uHcuXPw8fGxq31WVlbi3XffRUVFBfz9/e3y7SNHjmDu3LmQy+Xw9/e3q43PnDkTycnJ0Gq1dvW1lZWVePXVV5Gfn48mTZrAxcVFtA2///47PvvsMxgMBvj5+dlVFlOmTMGePXugUCjg5+cnuiyKi4vxj3/8A3fu3IGLiws8PDxEl8X27dsxbdo0VFRUwMfHB46OjqLkAeDdd9/F3r17AQB+fn6i29mDBw8wcOBA5ObmQqPRwMvLS3Q+Nm3ahClTpqCkpASenp529ZtjxozB9u3bYTKZ4OvrC6VSKUq+rKwMCQkJyMjIgFKphK+vr+j+IjU1FSNGjMCDBw/g4uICd3d30WXxr3/9CzNmzEBZWRmaNGliV1v/8ssvsWLFCtTU1MDX1xcqlUq0jmnTpmHdunUwGo3w9fW1q43MmjULK1asgF6vt7ud/fLLL0hKSmqUj9+8eRMvvvgiHj58CJ1OBzc3N9H1QkQYNWoUjhw5AoVCAV9fX7v6v71792LKlCmoqqqCj48PNBqNaB0mkwnDhg3DuXPnoNFo7I5Le/bswbRp01BdXQ1fX1+74rTZbMbw4cNx/vx5ODo62tWnA8CWLVswc+ZMGI1Gu32lqKgIQ4YMwb179+Du7g43NzfROogIo0ePxqlTpxqVnw8//BCHDx8W7hvE9iVmsxlvvvkmrly5AldXV7viA8/nn39+NykpablNPyaipzZ17NiR/puYOHEiASAA1K5dO/roo4/o8OHDZDAYbJJ/+PAhaTQaAkC+vr70zjvv0L59+6i6utpmG8aNG0cAKCwsjL788ku6fPmyqDxkZWWRRCKhoKAgmj59Ol28eFGUPBHRkCFDyM3Njd5++21KSUkho9EoSv7KlSsklUqpe/fu9MMPP9CDBw9E2zBmzBjS6XT01ltvUXJysmgbHjx4QGq1mqKjo2nhwoWUl5cn2oZPPvmEPD09afz48XT8+HEym82i5G/dukWOjo40ePBg2rp1K1VVVYm2oV+/ftS1a1davnw5FRYWipZfuXIltWrVir744gvKzs4WLZ+Xl0dubm70+uuv0++//04mk0m0jr59+1J4eDjNmzeP7ty5I1p+165dJJPJaODAgbR+/XoqKysTJW82m6lTp07k6OhIw4cPpx07dohqk0REJ06cIADk7u5Ob731Fu3fv5/0er0oHWPHjiUA5OfnR+PHj6eUlBSb+xYiourqavL19SUA1KZNG/r444/pzz//FFUnR48eFfq4yMhImjFjBl28eFGUb0+aNIkAkFwupz59+tDixYspJyfHZnmj0UhBQUEEgLRaLQ0ZMoTWrVtHBQUFNus4f/68kA9fX196++236X/+539EtbHPP/9c0BESEkJTpkyhEydO2FyeJpOJ2rdvTwBIJpNRfHw8zZ8/n65fv26zDefOnRNscHZ2piFDhtCaNWtE9ZlTpkwRdAQGBtK7775Le/futbksDAYDtWrVysovkpKSKC0tzeaySE1NFeRVKhUNGDCAli5dKsovPvzwQ0FHkyZN6PXXX6fNmzdTcXGxTfJ6vZ5atGgh6AgODqaPPvqIDh06ZHNbPX36tCAvk8moZ8+eNHfuXLp8+bLNbeSrr74SdLi4uNBLL71Eq1evpnv37tkkT0TUu3dvqzodO3Ys7d69myoqKmySr6ysJG9vb0FHeHg4TZkyhY4ePWpzLM3LyyMHBwcCQBKJhGJjY+mrr76is2fP2lwW2dnZJJPJhPLs0aMHzZkzR1R55ufnk0qlIgAklUqpW7du9M0334jqt2pqaigwMLCOj586dUpU//naa68JOlq2bEnvv/8+/fbbb1RTU2OzjgMHDjS6zRuNRmrXrh0BII7jKDo6mr788ks6c+aMqL587dq1gi2enp70+uuv05YtW6ikpESULW3bthX8pEuXLjRz5ky6cOGCKFvWrVtn1f5HjhxJv/76q6h4X1NTQwEBAVbtd968eZSRkWGzDqL/jXF8rP3www8pJSVFVMzfuXOnoMPLy4tGjRpF27Zto/Lycpt1HDlyRNDh4eEh1E9paanNOizLtVmzZjR+/Hjav3+/6HsgAKfIxmdDjp7iKQ6dOnWiU6dO/d1mNMiLL76IGzduAPjfqSL1Hfnz8vJyZGdn19EjlUrh4uICNzc3uLq6Qi6XQyKRgOO4OsfTp0+joKDASl4ikcDNzQ3e3t7C2z6FQiEkuVwunN+/fx+rVq2yklepVPDy8oKfnx+aNGkCBwcHqFSqBo8LFixARkaGIN+kSROoVCoEBATA09MTarX6sSkjIwNffvmlIM+//fb394e3tzc0Gg3UavVjj9OmTcPly5cBADKZDMHBwaiuroa/vz+cnJzqyNQ+z8vLwz//+U8rGxwdHeHq6tqgDbW/+/bbb3Ho0CEAAMdxCA8PR3l5OZo2bQpXV1c4OjpCo9HUe3R0dERxcTFGjBgh2BAYGAh3d3fI5XJ4eXlBq9VaJUdHxzqfp06dKtjg7OyMZ555BteuXYO/vz+cnZ3h5OT02JSamopx48YBABQKBQYOHAiNRoO8vDy4urrC2dm53uTk5ARnZ2coFArExsaivLwcANC1a1e8/PLLWLduHdzc3ITfPS59/PHHwmiKv78/hg8fDq1Wi+TkZMFOrVZrdbQ8P3nyJCZPniy0hfj4eLzyyivYsGEDiOix9cDX5ZtvvomSkhIAgFqtxrPPPos2bdogOTkZKpWqwcS3iT///BNbtmwR6tLZ2RnPPfccbt++Db1eD6VSCaVSCYVC0eDxhx9+QHFxsaDD1dUVXbt2xbVr16DT6aBUKiGXy4Ukk8msPt+/fx+7du2yatvu7u7w9vaGwWCATqeDXC6HVCqFTCazOvLn6enpyMzMtNLh6ekJAEL/JJVKIZFI6hz583379kGv11vpcHNzg1wuh5ubG7RarSDD922W56WlpUhNTUVt1Go1XF1dhbbFcZyQeHk+ZWVl4datW1byHMfB0dERLi4ucHV1FUZ4+DfEvCx/furUKdTU1FjpkEql0Gq1Qtt43MhfZWUlLl26VOd7mUwGFxcXoR1JJBKrqYaW53fu3MH9+/fr6FAqlUL74UdDascc/vP/Y++846Mqs///udMy6b0XSAhpJBDSSAFpIqGEYAGlCqiIsICsInbBioJgoSiCNEFgBQQpAkpzaVIDBEIoISEklPQyKZOZ8/sje+/OzUxg7gz7k93v8369zmvuTOacOU+99ynnSU5ODpqamoxs2NvbCz7Y2NhAr9ebfEjQaDQoKCgw0pfJZEIbdHBwgEKhEGy0fL1z5w6qqqpM5gXflg3TodfrRUJEyM/PN7klU61WC/2hra2tkS4vGo0GJSUlRvp8XvA2lEoldDqdkb5Op0N5eTk0Gk2reeHg4AA7OzvIZDKRDcPrW7dumUyHUqkU7l22trZCPrS009DQYPQMwGNrayvkpUqlMvKfv66urkZ1dbWRPt9G+L5RLpebzAe9Xo+ysjLU19cb2ZDL5cK9ys7ODhzHtVomd+7cgVarNZkXhmVqygafP8XFxSbrt0qlEpUJX59b6hMRiouLjfoswzLhbQAwWb+JCHfv3hXug4YoFArhnm1vbw+O44x0eamurjbZ3vn6xadHLpff88G+ZR/OY2dnJ9jhV/tN6Tc2NuLGjRvQ6XStlg1fV/n0tOx/SkpKUF1dbdSH8jg4OAhtX6VSGdnQ6XTIz88HAGi12lZ94Z8HTPlSXl6OsrIywaYpX/g6z6eJ79N5G9evXxfVr8bGRuj1eiM7NjY2gi98vefL9Pbt2yKber3eZH3j7y/Ozs7CfRIACgoKjNoaEZlsfxzHCWnhn9Hq6upQUFBgst+pq6tr1YazszNcXFygUqmMvsOj0+lw5swZo88dHBzQt29fDBw4EP379xeeI1qD47iTRJRwzy/x32UDV8uJiIgQDeAYDAaDwWAwGAwG4/863t7eGDRoEN588020bdu21e9JGbgqHpRz/xeZM2cOqqurRbP0rb1yHIf9+/dj4cKFgr5CoUBERARiY2MRGxsLd3d30Sycqdnrzz77TLSSIJfLERYWhujoaISHh8PZ2RmNjY0mRavV4saNG9izZ49RWpycnBAWFobg4GAhFqqurg719fWoq6sTXZ8+fVpYnTJErVYjODgYQUFB8PHxgY2NDerq6qDRaERSUlIirFS3xN7eHm3btoWfnx8CAwOh0+mg0WhQW1srer127ZrJmSKgeYUoKCgIbdq0gbu7u/C7vK5Go0F5ebnJ1W+geeasTZs28PPzQ3BwMIjI6Pdra2tRUFBgctYaaF4tCwwMhL+/P7y9vVFbW4uamhrRa1VVFYqLi03qA80N3tfXF+3bt4der0dNTY0wU85LRUWFyZlIoHmW1sfHB2FhYfDw8EBlZSWqqqpE0pr/PCqVCu3bt0dYWBg0Gg2qqqpQWVkpiKkZ5pb4+fkhPj4eCoVCpMuLqZlHQ5ycnJCcnAxfX19UV1eLfK+qqkJFRQVqa2tb1Xd1dUV4eDji4uKg1WpNlsXFixdbzceAgACEhIQgMjISrq6uojbBS25uLnJzc410FQoF2rVrh7CwMISEhMDb2xtarRaNjY1oaGgQvf74449GM6gqlQqhoaGIiopCWFgYvL29odPpoNVqodVq0dTUJFzn5ubi559/FunLZDKEh4cjPDwcUVFRCAoKElZNdDodmpqaRNfr1683WiUMCAhAWFgYYmJiEB4eDpVKJay6tFwNamxsxDvvvCOaoVapVIiNjUX79u3RsWNHeHl5mVz54K/PnDmDpUuXinwIDAxEWFgYOnXqhIiICNEMvSlZvnw5jh49KujL5XLExcUhNDQUsbGx8PX1Ff5mapdMU1MTpkyZIupjvLy8EB0djZiYGERHR983Ju/06dP4/PPPRZ916tQJ7du3R1xcHIKCgoSYopb3DP76q6++wqFDh4TPnJycEBcXh6ioKMTGxoriyw1XnHlpbGzEs88+K2pjERERCAsLQ3x8PEJDQ0Wr3y1FJpPh4MGDonSo1WokJCQgIiICCQkJcHV1NblDyPD6vffew/HjxwUbQUFBiIyMREJCAqKioqBSqYx0DW3U1NTgmWeeEdqoXC5H586dERERgaSkJPj6+hrptZQdO3Zg/vz5gg/u7u6IiYlBXFwcYmNjhZVSwx0ELd9Pnz4dJ0+eFGyEh4cjMjISXbp0Qbt27YTdC6Z05XI5ampq8MQTTwjtQ6lUomPHjujUqROSkpLg4eFxz90MMpkM+/fvx6xZswQfXF1dERMTg8TExFbT0fJ63rx52Lp1q2DD398fsbGxSExMRGRkpLDry5Q+Ly+99BJycnIEG23btkViYiKSkpLQtm1bkzqGQkQYOnQoysvLBRvt27cXbAQEBNyzTshkMjQ1NWHo0KGi+1BYWBgSEhIEG/eql3zbGTFihGgVOyQkBPHx8UhKSkKbNm0gl8uNdncYthmZTIYZM2YgKytLsOHt7Y2EhAQkJCQgMjISCoWi1R0i/GcbNmzAihUrBBt2dnbo3LmzULYtd5qYkrt372Ls2LGifiQ8PFzwxd/fX/R9U31HXV0d3nrrLdHKrYuLC+Lj45GYmIjo6GjY2NgY6Rnaunz5MrKysrB69WqRL3y/kZCQIIp7bWlDr9cLfd+WLVtw9epVwY6zszPi4+ORkJCAmJgYqNVqk3YKCwuFZ82SkhIjX/h+MDExUZQv/N+B5phwflcAx3H4xz/+IXoGb+kLv5LN65eUlCAnJ0dk98KFC9i1a5dgQy6Xo0OHDoiPj0d8fLxwxgSvk5WVJXpW4zgOVVVVRrsn27ZtK9gIDg4W9GtqakR1k/+8rq4OS5cuFa3E+vn5IS4uDvHx8Wjfvv19414LCwvx2muviT7r1KkTMjIykJGRgYSEBIvPcWkVc/cU/xXyvxTjqtfrKSkpidzc3GjkyJG0YcMGSfv8iYhOnDgh2s++adMmSXvRiYheeOEFAkA2NjbUp08fmjNnDmVlZZkdK1BYWCjEg6hUKurVqxd99NFHdOzYMbPj6aZOnSqKwcjMzKQvv/zS7JiFW7dukYODg2AjLCyMXnzxRVq/fr3ZcT4ffPCBKGaqT58+9Mknn9DRo0fNSkdtbS0FBAQINgICAmj06NG0fPlyun79ulk+fPfdd4I+x3EUGxtLL7/8Mm3ZssWseFONRkOBgYGCDRsbG+rRowe99957tHfvXtJoNPe18fbbbwv6+FccylNPPUVffvklnT59+r7xSidPniSO4wR9uVxOiYmJ9Pe//502b95Md+7cuad+Q0MDhYaGinwIDw+n559/nlauXEnXrl27b52YPHmySD8iIoLGjx9Pa9asoYKCgvvmwdGjR43KYdq0abRlyxYqLy+/r75er6fk5GRBPzExkV5//XXas2ePWWVARLRnzx5RPOQrr7xCu3btMjvmjIjoiSeeIADk6+tLY8eOpXXr1lFJSYnZ+rdu3SI7OztSKpXUu3dvmjt3LmVnZ0uKI1q2bJnQHl588UXasmWL5Jjh/v37k0wmo65du9Inn3xCZ8+eleTD7du3yd7entzd3WnUqFG0bt06s8rRkBUrVgixe2+//bbkWF8+HXZ2dpSZmUlLly6VHAfPxwCGhITQ1KlT6bfffpMU60ZEtHDhQiE+9osvvqCrV69K0tfr9ZSSkkKenp40btw4+vnnnyXVSSKiy5cvk1wup4SEBPrggw8k3W94PvroI7K3t6cnn3ySVq1aJaleEzXHC8fExFC7du3o73//Ox04cEBS/DcR0fnz50mhUFD37t1p/vz5kvOSqDkdzs7ONHz4cFq/fr3kZwC9Xk+pqakUEhJicTpKSkrI0dGRkpKS6KOPPpLcxomaY/IVCgX16dOHFixYYFY/25K1a9eSWq2mjIwMWrp0Kd26dUuyjaVLl5KtrS1lZmbS999/LynOl+cf//gHqVQqSk9Pp8WLF1NhYaFkG+fOnSO5XE4pKSk0e/ZsSTG2PHz8ZHBwML388suSYx55pk+fLrSVlStXWnQGSF5eHimVSurUqRO98847kuLRDRk3bpzF5wwY+qJQKCgmJobeeustOnbsmEW+PPfcc+Tg4GBVvmRnZ5NMJqNOnTrR22+/TX/++adkX/R6PSUmJpKHhwc9++yzkmNKeV599VWysbGh/v370+LFi+nGjRuSbXzyySfC/WH+/Pl05coVyTYmTZoktJ+FCxdKOnfAEEiIcf3LB6f3kv+lgWt5ebmkg5hMsXfvXsnB/oZUVFTQa6+9Rr/++qvkhw+eBQsW0IwZMyQ9lBtSVFREGRkZ9Omnn9Lx48clH4pERDR79mwaO3YsrV692qKbTHl5OQ0cOJBmzpxJBw8elBxETtT8gD5s2DBasmQJXb58WfJNqra2lvr27UtTpkyhzZs3W9Shz58/n3r37k3vv/8+HThwQPLhTPn5+RQREUGjRo2i7777jnJyciSlQ6/X04ABA6hXr1707rvv0p49eyQPUr744gtKSEigadOm0aZNmyQ/eFy6dIkSEhJoypQp9NNPP0nW1+v1NHHiRJo6darF5XD8+HGaNGkSbdq0yaIDroia82HVqlUWHfJF1Pww+tlnn1k0KOA5ePAg/fzzzxbdRHnWrVsneaBpSGVlJa1du9aicuA5c+YMHTp0yKK+hWfXrl0WPYzz1NbW0vbt2y3qI3kuXLhg0aDCkAMHDkgetBtSVVVFhw8ftiovL168aFE/bcixY8csOnyOp6KiQvIhYS3Jzc2VPGBuycmTJyVPPhii0WgkH0rTkhs3blh0iJ0hFy9etKpeETW3UykHyZji1KlTFj/L8Jw+fdqqPo+oua1aMvA25NatW1bXUaLmftyatkLUXL7mTsC3hk6no3379llV34ma8zYvL89qX37//XeLnvUMOXv2rNX5UlFRIekQM1Po9Xras2eP1e3nt99+s6od63Q62rFjh+TnPlNIGbiyGFcG478UvV5v1RYMrVZr8b9v4X9fp9NZZcNaH4jI4uPXGQwGg8FgMBh/LSzGlcH4P4C1cQPWDBj53/+rfWCDVgaDwWAwGIz/GzzgiFkGg8FgMBgMBoPBYDAeLGzgymAwGAwGg8FgMBiMhxo2cGUwGAwGg8FgMBgMxkMNG7gyGAwGg8FgMBgMBuOhhg1cGQwGg8FgMBgMBoPxUMMGrgwGg8FgMBgMBoPBeKhhA1cGg8FgMBiIkl+FAAAgAElEQVQMBoPBYDzUPLCBK8dx1zmOO8dx3BmO406Y+DvHcdxXHMdd4TjuLMdxcQ/qtx9mGhsbkZ2dDSKy2EZ5eblV+gCs1mcwGKaxtm3p9XrodDqrbGg0Gqv9KCsrs0qfiHD79m2rbJSXl6O6utoqGwUFBdBqtRbrExFycnKsys/S0lLcvHnTYn0AyMnJsSoviAjHjh1DU1OTxTaKioqszouTJ0/i7t27Fuvr9Xr89ttvqKurs9hGQUEBTp06ZVU6jh49ihs3blisT0TYtWsXampqLLZx584dHDp0yKr+4sKFC7h06ZJVefHnn39a3dYPHz6Mqqoqq2wcOXIEtbW1Vtk4ceKE1Tays7NRXl5ulY2ioiLk5+dbZYOIcPLkSej1eqvsXL582er0aLVaZGVlWX1funz5MiorK6325cyZM1b7kpOTY3WdLS0txeXLl62yodfrcfz4caufG06ePGnV/UGn0z2QfJWKfObMmQ/E0KxZs14GkEZE82bOnLnExN/7A+gHIBnAaQALZs6cufReNpcsWTJz/PjxD8S/vwq5XI4RI0Zg5syZuHbtGhQKBQIDAyGXy822kZWVhdTUVOTl5UGtViMwMBAymbQ5hxdeeAFHjhyBh4cHvL29wXGcJP0zZ87ggw8+gKurKwICAiTrA8Ds2bNx9epVhISEwMbGRrL+nTt3MH36dDg5OSEwMNAiH9atW4ctW7YgMDAQrq6ukvWJCK+88gqqq6sREhIChUIh2cbp06fx/fffIygoCC4uLpL1AWDx4sWor69HUFCQRflw5coVbN++HaGhoVCpVBb5sGbNGtja2sLd3d0i/dzcXOzcuROhoaFQKpUW2Vi8eDEqKirQtm1byW0CAIqLizF9+nQ4OjpanJfffvstli1bBgcHB4vaJgAMGjQIhw4dgp2dHYKCgiTbKC4uRkJCAq5duwY7OzsEBARItrF27VqMGDECRUVFcHJygp+fn6T84DgOzz77LL744guUlpbC09MTHh4eknzQarUIDw/H77//jtraWvj5+cHR0VGSjcOHDyM5ORnnzp2DTqdDYGCgpP6G4zi89dZbmDx5Mq5duwalUomAgABJfbZMJkPHjh2xdu1aFBcXw8nJCT4+PpLy89y5c+jYsSP++c9/orKyEl5eXpL6C47j8OGHH2LMmDE4e/YsGhsbERAQAFtbW7NtKBQKxMXFYfHixbh27RrkcjkCAgIk9Xvnz59HbGwsdu7cieLiYjg6Okq6B3Ech48//hijRo3C0aNHUVlZCW9vbzg7O5vtg1KpRJcuXTBv3jxcuHABTU1NCAgIkFQvcnNz0blzZ2zevBkFBQWwsbGBv7+/2e2M4zgsWLAAQ4YMwcGDB1FaWgo3Nze4u7ubnRdqtRr9+/fHe++9h6ysLNTX18PPzw92dnZmp6Ourg5RUVFYuXIlrl69CplMJrlMz549i86dO2PHjh24efMm7O3t4evrK6l+//LLL+jZsycOHDhgUV4Azffz9PR0HDp0CBUVFZLbCABs27YNPXv2xKFDhyxqZ0DzgCY6Ohp79+5FSUmJRWkhInTo0AE//PADbty4ATs7O/j5+UnqxzmOw9tvv40XX3wRFy5cgF6vl1zPgeaJnrCwMOzbtw9lZWVwd3eXfJ+Xy+V4/vnn8cYbb+Dy5cvgOA6BgYGSn5muX7+O8PBw7N+/H2VlZfD09ISbm5tkX1544QW89tpryM3NFXyR+tyRnZ2NmJgYHDx4EOXl5fDy8pL8HKlSqZCSkoKFCxciPz8fKpUK/v7+ku4vHMfhzTffxIQJE5CdnQ2dTmdROc+dOxcjR47EuXPnoNVqERAQALVabba+TCbDpEmT8Morr1iVrwAwa9asYlNjR1NwD2qkzHHcdQAJRFTSyt+/BbCfiH781/tLAHoQUXFrNhMSEujECaPF24eG06dPo76+/r7fO3LkCF555RXhvaOjI/r27YtevXohJCQEHh4eUCgUkMvlUCgUghi+f/zxx3Ho0CEAgJubGwYOHIjHH38cISEhICLY2tqKRK1WixrCjh07MGDAAABAWFgYhg4diqeffhrt27dHdnY2HBwcBLG3tzdqRESE2NhYnD17Fm3btsWwYcMwfPhwREdH48aNG6isrISjo6Mgpiru9u3bMXDgQKjVagwaNAgjR45E3759oVKpcOrUKdjb2wv69vb2JjvszMxMbN26FUFBQRg+fDhGjBiB6Oho3L59G7dv34aDgwMcHR3h4OAAtVptdOO4ffs2goKC0NjYiNTUVAwfPhxDhw6Fp6cnzp07B4VCIfjg4OBgsjOZN28eXnnlFTg5OeHJJ5/EiBEj0KNHD1RXVyM/Px/Ozs5wcnJqNR90Oh3atWuH/Px8dOvWDaNGjcKQIUPg4uKCy5cvg4jg4uICFxeXVgeVK1euxJgxYxAcHIzRo0dj9OjRCAkJQX19PXJzc+Hq6go3NzfY2dmZvHnqdDqEhISgvLwcQ4cOxZgxY5CWlgaO41BQUICGhga4ubnBxcWl1Q518eLFmDhxIrp27Ypx48ZhyJAhcHBwABEhKysLbm5ucHNzg729vUkfmpqaEBwcjKqqKjz99NMYM2YMUlJSwHEciouLUVZWJuRDa+n4xz/+gaFDh8Lf3x8jR47E6NGjERUVBaB5wsfGxkZUnqbq1IABA7Bjxw4EBgYKdSomJgYlJSW4ceMGbG1tYWdnBzs7O6F9GdopKSlBUFAQ6urq4OvriyFDhuCZZ55BcnIysrOzodVqYWNjY1JUKhU4jsOGDRvw9NNPAwC8vLzw+OOPY8iQIejcuTOuXLkCpVLZqigUCiiVSkyYMAGrV68WbAwePBhPPPEE/P39UVdXJ+pP+GvDz/R6PeLi4oSVFH9/fwwePBgDBgyAo6MjbGxsIJPJIJfLIZfLTV5nZWVh8ODBQt6Eh4dj8ODB6NKlC3x8fKBQKCCTye4p8+bNwzfffCPYSEpKQmZmJtq0aYOQkBDI5XJwHAeZTAaO40TX/OvgwYNx5coVAM2Dlh49eqBHjx6IjIwUPWDz+i0lPz8fjz/+uOCDk5MT0tPTERMTg8TERDg5OQn6hhi+X7FihSgd/v7+ePTRRxEdHY34+HjY2NgYzVQbvicijB07FlevXhU+i46ORpcuXZCQkIDIyEjI5XIQkSC8Hi8FBQUYO3asoC+Xy5GcnIxOnTohJSUFQUFBou8TEfR6vej96tWrsWbNGsGGvb09UlJSEBcXh+TkZLi5uQk6er3e6Fqv12PixIkoLCwUbPj4+CA+Ph7JycmIj4+HWq0Wfb+l5OXlYdq0aaK8CgsLQ0JCApKTkxEVFQWO46DT6UR6hu/Xrl2LjRs3CvoKhQIdO3ZEcnIyunTpAn9/fxCRSKfl9bRp00Qr6U5OTkhISECXLl2EetGarl6vR1FREaZMmSJKR0BAAJKSktClSxd07NhRaIstbfDvd+7cie+//15ko0OHDkI62rVrd8+81Ov1mDt3Lo4cOSLoq9VqxMXFISUlBV26dIGHh4dJPb5cdTodJk6ciFu3bgk2XF1dkZycLJSpnZ2dqD61fK2vr8eoUaNEK+l+fn5ITU1FSkoKYmJioFQq71k/a2trMWzYMNEOi7Zt2yI1NRXJycmIjo6GTCYzsmHYVhobG/H000+LVl2Dg4ORmpqK1NRUREVFCTYM21fL6wkTJgh9DtDc3tPS0pCSkoJOnTqJBmyG+oav3377LdatWyd8z9nZGSkpKUhLS0NSUpJogqJlX8Fz9epVjBs3TnjPTz6lpqYiLS0Nvr6+orpjagzQ0NCAl156SbQyGBgYiLS0NKSmpgr19F42ioqKcPjwYXz55ZfCZzY2NkhISEDXrl2RkpJiNLFpaEev1yM7OxtA8zOXYd4GBgaia9euSEtLQ4cOHYwGw7ydu3fvCnU0NzdX5ItKpUJCQoKQJt6Xlmm5ePGisCpJRJg9e7aoL2vTpo1QztHR0cLzEm+noqIChYWForLev3+/qC9ycHBAcnIyUlJSkJycLEzW8jpXr15FXV2dyEZhYSE+/fRTwYZcLkfnzp1NlrNGoxHdR3hKS0vx7rvvimx06tRJsBEYGGik05KzZ89i4sSJwntbW1v06dMHAwcOxMCBA43qW2twHHeSiBLM+u4DHLjmASgHQAC+JaIlLf6+DcBsIvrnv97/DmAGEbU6Mn3YB64RERG4dOnSX+qDTCZrdVuIUqkUDWRNbUMJDQ0VdQg8tra2wsM+L4WFhSgoKBB9r2PHjnBwcMDhw4dFn6vVajg6OgoDON7Wzp07Rd9zc3PDkCFD8O2334o+5zhONJDlpaSkBOfPnxd9t1OnTggMDMS2bdtEn8vlctFAln89ffo0KioqRN/r27cvjh07htLSUpENOzs7Ix8A4ODBg6Lv+fn5ISEhAVu3bjXKRycnJ2Ewy8v58+dF+a5SqZCRkYFLly6J0mdraysM3gxFrVZj+fLlot/q2rUrevfujVmzZons8oNYXvj3//znP2HYvkJDQ4XVmQ0bNgjl4OLiIsy48jPJbm5uUKlUmDt3rqBvb28vTIikp6cLnyuVStHvG8rBgwdx8uRJ4bvh4eEYM2YMSktLRbYVCoXJfLC3t8fKlStF+ZCQkIDRo0fjnXfeMdpixNcpvj44Ojri7t27uHjxouh7MTExCA8Px08//QRTqNVq0YC2sLDQaCsjP5i93zZJlUoFlUplcguhk5OT1VuTFAqFVduBGAwGg8FgMKSSkJCAgQMHYty4cfccCP9VA1c/IiriOM4LwB4Ak4nooMHftwP4pMXA9TUiOtnCzngA4wEgKCgo3to9//9JUlJSTA76WqLT6UzGC3AcJ1qx0Ol0aGpqkhyfwHEci2FlPFQ8iDrJ6rUYw5UDS+D7GaB5tVuqHZlMJqyYtlyZMhelUin0eS1X5cyxJZfLRTZaW825V4yrUqmESqWCQqEQ6pip1ZjW4t5kMpkw2cCvCPEYXjc2NrZqQ6lUCivu/Ay9qR0FlZWVaGhoMOmDjY0N1Gq1sGrPC2+LvzZcHWjpg1qthlqthlKpNLnyLJPJUFtbizt37rTqAz8xarhq3nIV/ObNmybzgp9ctbOzg0qlMmmDr7MtJ5f4dNrY2AgTSIb3U1749xUVFSZjVOVyueADv1OppS4v169fNzmRpFKpBB8M09HSFsdxyMrKMpkOtVotSoep35fL5aipqcG1a9dMpoO3we8KaU1u375tckJNoVAIeWFjYyMqg5Zlkp+fb7JMVSqVMLHH101TdYLjOFy7ds1kWzW0wbfTlrsseLl+/brJWD++fvM2+HxuKUDz6qApP/h2qlarRX7wtgxtlpSUmIzDlsvlRjtsDMvd8Fqj0Ygm1Q3/plKpBDstdw4Z2rnXWQMKhULoMwxXKVv2PU1NTUaT+Dx8/2cqPYbU1NSIVglbwuetjY2NaFcXb4+IhDramo3WfOFfNRqNaEL4fr603KkINK9KGt6XWrtHmeqTAaC+vt6oz7jXfZy3wZczx3EoKyszWT/vtWhlmB6tVovy8nKTZdWaDYVCIeTrvbZ36/V6k3WF4zikpKRg4MCByMjIQIcOHe65dV7KwFV6gF4rEFHRv17vcBy3GUASAMNlqUIAhsPtAABFJuwsAbAEaF5xfVD+/Scw3GpzL5YvXy5s3XB0dER6ejoyMjLQr18/kzFg/FYcfiCr1WrRq1cvnDlzBkBzpezWrRv69euHfv36CVsjGxoaUFdXZ1KOHj2KGTNmiH7Hx8cHvXv3xqOPPooePXrA09MT1dXVqKmpMSmzZ882WmF2dHREt27d0KNHD6SmpiIkJAR1dXWorq5GVVUVqqurBcnJycHnn39ulF5vb290794dXbt2FbZs1dbWinR5WblypVG+y2QydO7cGd27d0daWho6d+4MhUIhpMXwtaKiAq+++qrRw6C7uzu6d++ORx55BF26dEFQUBBqa2sFPUP5448/hC2ZhoSGhop84FfLqqqqUFlZKVxXVVVh4cKFJh+iIiMjkZaWhsTERHTo0AH29vaoqKgwkpycHKxfv95IH2heteS3WsXGxkIul6OsrAxlZWUoLy8Xrrdu3YriYtM79SMjI4WtfJ07d0Z5eTlKS0tRVlYmvObm5uK3334zqa9SqRAbG4u4uDgMGTJE5IOhbNmyRbTdzJCwsDAkJSXhkUceQXJyMiorK43yITc3F6tWrTKpHx0djbS0NCQkJCApKQm2trZGZVlTU4Nly5bh2LFjIl2FQoGEhAR0794d3bp1Q2JiIpRKJerq6qDRaASpq6tDWVkZRowYIapTKpUKqamp6N27N3r16oXExETIZDI0NjaioaHBSLZv347XX39d0Oe3dPbp0wd9+vRBUlKScPPQ6XTQarVG8tJLL4l2HYSHh6Nv375IT09H9+7djeLg+H6mqakJOp0OlZWViImJESbZHBwc8OijjyI9PR3p6elo06aNyXw23D64e/duZGRkCH+LjIxE//790b9/f3Tt2tWseOpJkyZh0aJFAJpXtnv27CnYCAkJua9+Y2Mj2rdvL+wOCQoKwoABAzBgwAD07NnTrHjAQ4cOoWvXrgCayyItLU3Y+hQREWFW7NrUqVPx1VdfAQA8PDwwYMAAZGRkoE+fPsJW43vR0NCAdu3aCVtTExMTkZGRgYyMDHTq1MksH/bs2YPHHnsMQPPqfb9+/YR7j7lxYmPHjsWKFSsANG9JHTRoEAYNGoSkpCSz4u+qq6vRtm1b1NbWQq1W49FHH0VmZiYGDhwIHx8fs3zYtGkTnnzySQDN2wQzMzORmZmJRx55xOwY/WeeeQbr168Hx3FITU0VbISFhZmlX1VVhbZt2wJovu/169cPmZmZ6N+/v9kxkYYhO23btkVmZiYGDx6Mrl27mh37Z1ivEhMThXTc78GQh4gQHx+Pu3fvCtvoMzMzMWjQILO2BgIQzhUAmnex9O3bF4MGDcKAAQPMjmu/evUqwsPDAfy7bg4aNAj9+vUzO27w4sWL6NChA4B/lwlvw9z6fePGDbRr1w5Ac3/Tp08fZGRkSNrmaNhWZTIZUlJSMGjQIGRkZJjdXwDAiBEjsHbtWgBAu3btBBtdu3Y1O25w586d6N+/P4DmPvyxxx7DoEGD0L9/f3h6epplQ6fTITo6Gjk5OQCA2NhYoe+Jj483O+529erVGD16NIDmbc+Gz77mlo9Op0NUVBRyc3Ot8uWHH37AqFGjBF/4vjA9Pd1sXxoaGhAaGipMBiYlJQm+dOzY0exynj59urCjzN/fX7DRs2dPs88g2Lp1KzIzMwH8e1zB131z45EPHz6MtLQ0AP/e4puRkYEBAwaYXfd/+uknDBkyBEBzfevbty8yMjIk1TfJmJptlioA7AE4GlwfBpDe4jsDAOwEwKH5gKY/72c3Pj6e/ttpbGykPn360NSpU2nPnj3U0NAg2ca2bduoTZs2NGHCBNqyZQtVV1dLtvHYY4+Rs7MzZWZm0ldffUXZ2dmk1+vN1j916hRxHEdOTk40YMAAmjNnDh0/fpy0Wq3ZNkaPHk0AKCAggEaMGEFLliyhnJwcs/24desWOTo6kkKhoOTkZJoxYwbt2LGDKisrzfZh8eLFBIA8PT3pqaeeoq+//prOnTtHOp3OLH2dTkddunQhABQREUEvvvgirV27lgoLC8324eTJk8RxHMlkMoqLi6OXX36ZNm3aRHfu3DHbxqhRowgAKZVKSklJoenTp9OWLVvo7t27ZulfvnyZVCoVASB7e3vq1asXvf3227Rjxw4qKyszy8aYMWMIzaEBFBgYSEOHDqX58+fT0aNHqb6+/r76OTk5pFQqRT689dZbtH37diotLTXLh+eee44AkI2NDXXr1o3eeOMN2rZtm9lpuHnzJtnZ2ZFSqaSuXbvSW2+9Rbt375bUxubMmUMymYy6dOlCb7zxBu3Zs4c0Go3Z+jqdjmJjYyksLIwmTZpEP//8M1VUVJitT0SUnZ1NLi4uNHjwYPrmm28oLy9Pkj4R0ezZsyk6OpqmT59Oe/fuldxX6fV66t27Nw0cOJAWLVpkkQ/5+fnUvn17eumll2jbtm1UW1sr2caSJUuoa9eu9Mknn9DZs2cl9XM8Q4cOpREjRtDatWvNrouG3Lx5k5KSkujNN9+kI0eOUFNTk2Qby5cvp0GDBtF3331HRUVFkvX1ej2NHDmSpkyZYvG9Jz8/n/r06UPz58+nK1euSNYnIlq2bBmNGTOGNm/eTDU1NZL19Xo9jRs3jt577z06deqUReV5/fp1Gjx4MC1dupRu3bolWZ+IaOXKlTRhwgTauXOnWf2bKSZNmkSzZs2iM2fOWJSO0tJSGjx4MC1atEjSPceQgwcP0jPPPEM//vij5H6G57vvvqMXXniBtm3bRnV1dRbZmDVrFk2aNIl2795tUd0kInr99ddp0qRJtGvXLovL5P3336fnnnuOtmzZYlF/Q0S0atUqevLJJ2nlypVm34NbkpubS4888gh9+umndOHCBYvqh16vp6FDh9KkSZPo119/tThPNm7cSOnp6bRw4ULKz8+3yIZWq6V+/frRyy+/TL///js1NjZaZOenn36ifv360aJFi6igoMBiXwYMGEDTpk2jvXv3WuzLypUrKTMzk5YuXUrFxcUW2bhz5w51796dZs2aZXF/ptfr6amnnrKqbyciGjduHL344ou0bds2Sc8sPDqdjjIyMmjy5MlWtUEiIgAnyMwx5wPZKsxxXAiAzf96qwCwlog+4jhuwr8Gx99wzVMRCwCkA9AAGEv3iG8FHv4YV3PQ6/Wi7SWWUFFRAWdnZ4tt1NXV4dy5c4iLi7PoFFygOabT3t5eWMGTikajwU8//YRu3bqhbdu2FqXl+PHjqKysREpKCuzt7SXrA8DGjRsRGRmJyMhIi3y4efMmDh8+jEceeQTe3t4W+bB161ZhRc6clZeWlJWVYcmSJcJqopRTQnlWrVqF6upqpKamIiYmRnK9uHXrFubOnSscKODv7y/ZhxUrVkCj0Qirw1J9qKqqwpIlS5CamiocdiOVP//8E7W1tUhOTrYoHwHgjz/+QMeOHSWdcmpITU0NSktLW13RNIe7d+/CxcXF4tOZgeZ+xtJTroF/rwRLOZWwJfX19cIWRUtpbGy0+KRsAMI2aEv7SqA5LyzpJ1v6YU0+8Pd2a21Yo89g/Cd5EPXzf80GYF2bZ7785335X0nPg/LjXzb+/8e4/if4Xxi4MhgMBoPBYDAYDAbDGCkDV+n/cJDBYDAYDAaDwWAwGIz/j7CBK4PBYDAYDAaDwWAwHmrYwJXBYDAYDAaDwWAwGA81bODKYDAYDAaDwWAwGIyHGjZwZTAYDAaDwWAwGAzGQw0buDIYDAaDwWAwGAwG46GGDVwZDAaDwWAwGAwGg/FQwwauDAaDwWAwGAwGg8F4qJHPnDnzr/ahVZYsWTJz/Pjxf7UbFrFw4ULk5ubC398fdnZ2kvXLysrwj3/8A23atIFarbbIh6ysLNja2lqsr9PpcOXKFbi7u1ukDwBFRUUAABsbG4ttXLx4ES4uLpDL5RbpExGysrLg7e0NjuMsslFWVobKyko4ODhYpA8AN2/ehL29PWQyy+eLysrKYGtra7F+Y2Mj9Hq9xXkJAHV1dVAqlRbrA0BVVZVVdQJorluOjo4W69fX1+PSpUvw8vKy2Mb169dx5coV+Pr6Wly3Dh48iOLiYvj5+VlsY+XKldDpdBb7UVtbi6+++gru7u7w8PCwyIcTJ07gl19+gb+/v8XlsnLlSly+fBlBQUEW1Q+tVotZs2aB4zgEBARY1NaysrKwbNkyuLi4wMvLy6L8XLZsGY4fPw5fX184OTlJ1tdqtXj11VdRU1ODgIAAi/LixIkTmDdvHlQqFfz9/S1q819++SX2798PZ2dni/KioaEBL774Iu7evQtvb2+L8uLo0aN4//33odPp4O/vb1FefP7559i+fTvUajX8/Pwk1wutVotx48YhPz8fbm5ucHNzk5wXFy9exLRp01BfXw8/Pz+LngvWrFmDFStWQC6Xw9/fHwqFQrKN9957D0eOHIGjo6NF90SdToeJEyfixo0b8Pb2hrOzs2QfamtrMXHiRFRVVVmcF1VVVZgyZQoaGhosbiP19fV4+eWXUVtbi4CAAIuelYgIb7/9Nm7evAk/Pz/Y29tLtgEAq1evxr59++Dp6Qk3NzeLbFy9ehWzZ8+GWq2Gv7+/xc8aH3/8Ma5fv46AgACLygYATp06hcWLF8PBwcGq++OHH36IgoICi5+lAeDkyZNYtGgR7O3tLb7PEhHefPNN3Lp1yypfNm7ciM2bN1t1f7l48SI+/vhjq/r2oqIivP7665DJZAgMDLSoL8nOzsa8efOsrm8AMGvWrOKZM2cuMevLRPTQSnx8PP23sm/fPgJAMpmMHnnkEZo7dy7l5uZKstG9e3dSKpXUv39/+v7776m0tFSS/q+//ko2Njb05JNP0qZNm6i+vl6SPhHRo48+Sl26dKFFixZJ/n0iohs3bpCTkxONHDmSdu/eTU1NTZJtLF++nDw9PWny5Mn0559/kl6vl2xj2LBhFB4eTh988AFdu3ZNsn5dXR35+vpSeno6rVmzhmprayXb+O2338jX15emT59O58+fl6xPRDRx4kRKT0+n9evXU11dnWT9xsZG6ty5M02fPp0uXrxokQ+nTp2i2NhY+vrrr6msrMwiGwsXLqRu3brR999/T9XV1RbZeP755yk1NZW++eYbi/1ITk6mjh070ieffEJ5eXmS9TUaDXl6elJwcDDNmDGDTp48Kbl+XrhwgQBQQEAATZkyhQ4cOCC5nSxbtowAUFBQEE2dOpX2798v2cbw4cMJAEVERNDrr79Ox44dI51OZ7Z+XV0d+fn5EQBKSkqijz/+mLKzsyXlx5EjRwgAqVQqSk9Pp8WLF9PNmzclpeP1118nAOTq6kojRoyg9evXU2VlpY7xeJMAACAASURBVNn6Op2OoqKiCAC1adOGJk+eTHv27KGGhgazbZw7d444jiMAFBcXR++99x6dOHFCUl7MmjWLAJBSqaRHH32UvvzyS7p69aqkdHTs2JEAkLOzMw0dOpRWrVpFd+/eNdvGhQsXhHQEBQXRSy+9RNu2bZPU/3344YcEgABQbGwsvfXWW3T48GGz66der6e4uDhRXsybN48uXbpkdn5euXKF5HK5UC+eeeYZWrVqFd25c8fsdHz11VdCOtq1a0eTJ0+mnTt3kkajMdtG3759heeClJQU+uCDDyT1GRUVFeTq6koAyMHBgQYPHkxLliyhGzdumO3DoUOHhHT4+fnR888/T5s3b6aqqiqzbSxcuFCwER0dTTNmzKCDBw+SVqs128Zrr70m5EVqaip99NFHlJWVJamNTJo0iQCQQqGgXr160bx58yQ/Z73xxhuCjd69e9P8+fPp8uXLkmysWrWKABDHcZSamkoff/wxnT17VlJa8vLySKFQEACKjIyk6dOnS85TIqIePXoQAHJzc6MRI0bQunXrqKKiQpKNTZs2CWXTtWtX+vTTTyX35Yb9qI+PDz3//PO0ZcsWqqmpkeTLhg0bjHy5cOGCxb54eXnR2LFjadOmTZKfPZYuXWp1vpSWlpKjo6PQp06cOJF27Ngh6XlOr9dTWloaASAnJycaMmSI5L6diOiJJ54gAGRnZ0eZmZn03XffUVFRkSQ/EhMTCQC5u7vTqFGjaMOGDZLrGxERgBNk5tiQa/7+w0lCQgKdOHHir3ajVaZNm4aioiJwHGckAPDTTz+hoaFBpBMeHo5BgwZh0KBBcHR0xGeffQYbGxsjUalUyMrKwk8//SToKhQK9OrVC0OGDMHgwYPh4eGBL774AhcuXICjo6ORODg4YOzYsSgtLQUAuLi4YMiQIRgxYgS6desGmUyG0tJSvPrqq3BxcYGLiwucnZ2FaxcXFxw5cgRvvvkmAEClUiEjIwOjR49Gv379hFW3H3/8EQcOHBDpGcqMGTNw8OBBAIC/vz9GjhyJZ599FpGRkULaxo0bB3t7ezg5OcHZ2VkQJycn2NjYICMjA3V1dQCAiIgIjBo1CiNGjECbNm0AALt378aGDRvg5ORkJM7Ozrh06RKmTp0q/F5aWhpGjRqFIUOGCLOb06dPh0ajEflgeP3tt99izZo1AAAHBwc8+eSTGDVqFHr06AG5XI4zZ85gwYIFQrpdXV1F187Ozujfvz8KCgoAAPHx8Xj22WcxbNgwYZVr7ty5yM/Ph7u7uzCzb3hdWFiIXr16AQBcXV0xfPhwjB07FnFxceA4DsXFxXjnnXfg4eEhrJ4Ziru7O+bPn48PP/wQAJCamornnnsOQ4cOFVaTV65ciePHjxvpGkqPHj1w7Ngx2NjY4IknnsBzzz2Hnj17QiaToampCS+88ILgc8s0uLm5QalUIjw8HLW1tbC3t8eQIUMwbtw4dO3aFRzHYevWrdi2bZuoLvD1k5f8/HwMHjzYqG6mp6dDpVJh4sSJ0Ol0cHBwgL29PRwcHATh3+/btw+ffvqpqF4MGzYMQ4YMwaVLl7BkyRJh10Jrr+vWrcOvv/4q2AgNDcXQoUMxdOhQ/PjjjygqKoJKpTIpSqUSKpUKX331lVAvAMDb2xuPP/44EhISsGfPHqhUKigUCiNRKpVQKBTQ6/X49NNPYdife3h4IDMzE0SEmpoaqFQqyOXyViU/Px+bNm0S9Vd+fn547LHHkJeXBx8fHygUCsjlcshkMuHV8PrgwYM4e/asyEb79u3Rrl07NDY2wsvLS6THC8dxwvUPP/yAmpoakY3ExETU1dUhICAArq6uQj/L6xpel5eXY/PmzSJ9pVKJ6OhocBwnzJa31m9zHIezZ88iKytLZMPJyQleXl5wd3eHr68vVCqV0Wy54fsdO3agqqpK9HcPDw84OTnB19dXyAsAonLjr6urq7Fnzx60hF+R8fHxEfouXqflDT43Nxe5ublGNtzd3eHj4yOsgur1ehCRydfDhw+jtrZWpK9QKODh4QFvb294eXnB1tYWer3epNTU1ODPP/808kGlUsHb2xve3t7w8PCAXC4XdHQ6ncjG9evXRe2Dx97eXvDB1dUVAES6/LVOp8OZM2eg0WiMbLi6usLb2xuenp5wcHAAEUGn04l09Xo96urqcOrUKSN9mUwGT09PeHl5wdPTEzY2Nka/zb8WFxcjLy/PyIZarYaXl5dQv2Qymcm80Ol0uHjxIsrKyoxsODs7C3nh7OwslJ8pOXz4MJqamkT6HMeJytTe3l74vqEtIkJ9fT0OHTpk5INSqRTK1MvLC0qlUtDhhX9fUVFhsl7Y2trCx8cHPj4+8PT0hEwma/UBtrS0FMeOHTOy4eDgAB8fH/j6+sLd3V1ol4bthH+tqKgQnk9a2vDz84Ovry/c3NyE1SRTbbWpqQm//PKLkQ07Ozv4+vrCz89PSMu92Lt3r1HZqlQq+Pj4CL7cb7fTlStXjOopx3Hw9PSEn58f/Pz87rtzrLa2Ftu3bzf6nF+xNCc9165dQ25urlEfKJPJ4O3tLaSntZVLvV6Po0ePAgAKCwtb9cXX1xceHh4mfSkqKhL6jcrKSlRXV4v+znEcvLy84Ovra+QLX7anTp2CVqsVfCouLjbpC1/feF94/dLSUly5ckX0/dLSUqOxgVwuh5eXl1D3DXcQXLhwQbgn8nZra2uN8hYA3Nzc4OvrCx8fH2HnU01NDS5cuGD0XY1Gg4qKCqPPXV1dhTzh+9XWuHTpEs6dOyf6TKFQoHv37sjIyEBGRgZCQkLuaQMAOI47SUQJ9/0iwFZcrSEsLEyYdbRErNGXy+XUu3dvioyMtEg/MDCQXnvtNfr5558t0vf09KQpU6bQyZMnafz48RbZSExMpK+//poKCwstzofu3bvT0qVL6b333rNIX6VS0eOPP04bN24kHx8fi2z4+/vTa6+9RnPmzLFIX6lU0uDBg2nz5s3UpUsXi2zExMTQvHnz6Ndff7VI397ensaNG0eHDh2iYcOG3ff7/CqMoQQHB9P7779Pp06dsrg8Q0ND6cMPP6S//e1vFtvw8PCgyZMnk62trcU25HI5RUdHW6xvWL+stcGECRMmTJgwYfLfJh4eHvTpp5/ed8cS2Irr/x8WLVqE0tJSo0wFmmdm5syZI5pVkcvlSEtLw8CBAzFw4EDIZDKsXbsWDQ0NgjQ2NgrXubm5RrP+QPOs/aOPPorHHnsMpaWluHXrFqqrq03K1atXodfrTfofFBSExMREODg4wM7ODhUVFUZSVlZmNDNkiJOTE3r06IGgoCBh9qa8vNzIzr3qWbt27RAbGwtfX19UVVWhsrLSSPhVY1PY2dkhJiYGUVFRsLGxQVVVlZGUlZWZnFniadOmDXx9fdGpUyc0NDQIv2voT3l5uTDzZorAwECEh4ejTZs2qKqqEvLBMD90Ol2r+kDzCldycjJsbGxQVlaG0tJSlJWV3dd/HrlcjoiICMTExKC2thalpaUoKSlBSUkJysvL71kOhj6EhobCx8cHZWVlKCkpQWlpKe7evYv6+vr76gNAcHAwIiMjYWdnZ5SOlqs397IRFxcHmUyGyspKVFRUCGVRUVFxX184jkNERAQSEhKg1+tRW1uLmpoakZSXl6OystKkvlwuh6+vL9q0aYMOHTpAp9Ohrq4O9fX1qK+vF66vXbuG27dvm9QPCgpCQEAAAgIC4OnpiaamJjQ2NkKr1aKxsVGQP/74w2T5hoeHw83NDcHBwfDz8wPQPLuv1WrR1NQkSH19PdavX2+k7+7ujvDwcHh5eSE4OBhqtVpYTWopeXl52L17t1Eedu7cGU5OTggNDYW3tzcA06taer0ee/fuRXZ2tsiGs7MzOnbsCA8PD7Rr1w52dnYmV3J4WbJkiVEdiYiIgLu7O9q3b4/AwEBhRcqw3+XfFxUVYfXq1SJ9GxsbxMXFwd3dHWFhYcKKFACjvpuI8Pvvv+PIkSMiG0FBQQgKCkJwcDCCg4OFlY/W2tS8efNEZSqXyxEfHy+UiYeHh2iFtuV1YWEhFi5cKLLp7e2NiIgIBAQEIDQ0FDY2NiZXjnn55ZdfsH//fpHd+Ph4uLm5ISoqSlj1NVyxbvn6zjvviNLh6uqKTp06wdfXF2FhYbCzszNaQTeUvLw8fPbZZ6J0xMTEwMPDAx06dEBAQICw6t9Sl/9sw4YNotVnW1tbxMfHw9vbG5GRkXB2dm51FwD/+uqrr4pWswICAtC2bVuEh4ejXbt2wo4EXqelfmFhId59912jdPj6+iI6Oho+Pj5GOi1ft2/fjo0bNwr6arUaERERCAkJQYcOHeDk5GQyDYbXn332GXJyckTlERwcjA4dOiAsLAxqtdqkPi86nQ5Tp05FY2OjYMPT0xOhoaHo0KEDQkJCoFQqRbsgWu6KuHXrFmbNmiXKCw8PD0RFRSEqKgpBQUFG9arldU5ODhYtWiSy4eXlhcjISERFRQnt/F71+/z581i2bJnIhqenJyIjIxERESH4wdd9w10V/PW1a9ewePFikQ0XFxdEREQgMjISwcHBQloM25HhdU1NjbCLybBsw8LCEBkZidDQUOFsinvFNH799de4deuW8F4mk6FNmzaIiIhARESEWbGv//znP7Fr1y7RZ25uboiIiBCeT+4XE1lRUYHPP/9c9JlCoUBoaCjCw8MRHh5+33MMcnNzceDAAaOdEp6enggPD0dERIRQxqbQ6XT4448/0NTUhAMHDoj+plQq0b59+/v6kp+fj2vXrgn+tPSF70/5umJqB82hQ4eEtlJfX2+0Oq9WqxEeHo7IyEiEhYXB1tZWZOfOnTuieyLHcfjzzz9FfRHHccIzU2RkJDw9PUV/O3HihGh1leM4XL582Wgl19fXV2g//v7+Qj2vqqqC4ViK96+goMBoJdbT01OUJ3z5tFZv9+zZg3379ok+i4qKElZbk5OTzYrBZSuuDwEbN24k4N9xVmvXrpUUI6rX64VYBZVKRb169aLZs2fTyZMnzY47O3HihGjmIyQkhMaOHUsrVqwwO57vhRdeENkICgqiYcOG0cKFC+nMmTP3jVOqrKwkb29vQV8mk1Hnzp3pb3/7G61bt86s2Bw+XpgXNzc3GjRoEM2ZM4eOHj1KjY2N97XBx7HwEhERQePHj6fVq1fT9evX76uv0+koISFB0Oc4jmJjY2ny5Mm0YcMGs+IC8vLyyMbGRmQjJiaGJkyYQD/88APl5eXdM1ZCq9XS559/bjSj1b59exo9ejQtXryYsrKyWi2TpqYmunv3rlCvDCU4OJiGDRtGX375JR09erTVeOja2lq6cOECOTs7i/Q5jqPo6Gh67rnn6LvvvqNz58616kd9fb3JlWE3NzcaMGAAffjhh7R37977xp8YxlkBIFtbW+rZsye98847tHv3brNitp599llBX6FQUGpqKr355pu0e/dus2JxtFothYeHCzaio6Np6tSp9Msvv5gdV3n16lUhtsnT05OGDx9OK1askBTb+f333wvtKzk5mWbNmkXHjh2TFOc6dOhQoRyGDRtGq1evlhQDWF1dTV5eXgQ07wCYMWMGHThwwKz2yfPbb78RAFKr1dSvXz9asGCB5Jh0Pu4tICCAXnzxRfrll18kxWTW19dTQEAAyWQySktLsyhebf/+/aL+/8cff6Ty8nJJ6XjppZcIAHXq1InefvttyTHHGo2GfHx8yM7OjgYPHkzff/893b59W5IPfDsNCQmhadOm0b59+yTH3I0ZM0aIH/zqq6/M6m8NqampIU9PT/Lw8KCxY8fSli1bJJ8xwKejY8eO9O6771oUiz5hwgRSKpWUnp5O33zzjeTYa61WSyEhIeTm5kbPPvssbdq0SXK838WLF4njOGrXrh298sordPDgQcmx7MuXLyegOfZ61qxZdObMGcl5MW3aNCHOb86cOXTp0iVJ+kRETz31FMnlcurZsyfNnz9fUvw2z8CBA0kul1P37t3p888/lxzfSkQ0cuRIAprj8j/88EPJcbZERLNnzxbuxa+88grt379fcjs5efKkqM9Yt26d5D5Dp9NRhw4dhLNVPvvsM7p48aLk9HzzzTdCHzphwgTavn27pFhuon+fecC3/S+++IKuXLkiyQYR0YIFC4Rnz0mTJtHOnTsln++h0WjI19eXVCoV9e3blxYsWCC5HyL6d7x+WFiYxeV8+fJlksvl5OLiQsOGDbPo3tDY2EghISGkUqmoX79+tGjRIiooKJBkg49P5ePD58+fL7l8GhsbqW3btsLZA1988YVF7ZhI2orrXz44vZf8Nw9cV69eTX/88YfkSs1z4cIF+vvf/047d+606CAgvV5P48ePp/Hjx9OaNWskHd7Ac+bMGercuTNNmjSJ1q5dS/n5+ZJtzJw5k3r16kXvvvsu7dq1S9IhKUTNg62MjAwaPnw4LV68mM6fPy/p4Y2IKD8/n1JSUmjq1Km0ceNGyQ9vREQ//vgjpaWl0RtvvEE7duywKPh89OjR1L17d3rrrbdox44dkjur8vJyCg4Oph49etAbb7xBW7dulTSwICLas2cPOTo6Uq9evejNN9+krVu3Ss6PN954g7y8vCgjI4M++ugj+v333yWVKz8pEx0dTS+88AItX76ccnJyJN1cy8vLKTIykjIzM4UJDCmH5xA1H6DDl+muXbssOiTql19+obFjx9IPP/wg6VADQ7755hv65JNPJE1KGaLX62nmzJm0bt06KikpsciHkpISevfddyUdmtOSP/74g7755hvJN1BDVqxYIXmgaUh9fT3NnTvXoodxnqysLFq9erXkgy4M2bRpEx04cMDi/r+xsZG+++47i/pcngsXLtC2bdskP3Aa8uuvv9L58+ctzkutVksbNmyw+PA0IqLc3Fz6448/LK6XRM0TCZYcysej0+no559/lnz/MuTGjRsWPega8ueff1pVHkREO3futKqN6nQ6Wr9+veR7jyEajYbWrl1rVb2orq6m1atXW9znETX3F8uXL6fi4mKLbej1elqxYgXl5ORYbIOIaMeOHVb1GURE165dox9++MGigzQNWbFiBZ0+fdqqenbu3DmLD+pp6Yslkwktfdm4caOkA8haotfrafny5RZN0hiyf/9+2rdvn6QJ3ZZcuXLFosOlDCkuLrZo0GzIpUuXHkgZE7GtwowHhF6vt+p46wdhg4gsPkb9Qdp4EOloamqy6t/IaDQa4ZAeS7l79y7c3Nys+nc4/LH/luapVquFRqOx6N8o8DQ2NkKhUPzldYvBYDAYDAaDYTlStgpb/gTM+J/H2kHrg7DxIAYWD8LGg0iHtf/71NL/G2aIYeyEpfj7+1ulr1QqrRq0As0nLVoLG7QyGAwGg8Fg/Pdg/ciEwWAwGAwGg8FgMBiM/yBs4MpgMBgMBoPBYDAYjIcaNnBlMBgMBoPBYDAYDMZDDRu4MhgMBoPBYDAYDAbjoYYNXBkMBoPBYDAYDAaD8VDDBq4MBoPBYDAYDAaDwXioYQNXBoPBYDAYDAaDwWA81LCB6wOiuroaOp3OKht6vf4BecNgMP7TWNteiQiNjY1W2WhoaLC636mpqQERWWWjqqrKKv3GxkZoNBqrbFRUVFhdJiUlJVbp19fXo6Kiwiobt2/fhlartcrG9evXrSrT2tpaFBcXW+XDjRs3UFtba5WNixcvWlW/NRoNrly5YpUPN27cQFlZmVU2Ll68iIaGBov1iQjZ2dlWlWllZSVu3rxpsT4A3Lp1C5WVlVbZuHnzJurr6622YW3feevWLattlJeXW91vabVa3LlzxyobAFBcXGx1P15RUWF1enhfrKWsrAx1dXVW27G2zgPAnTt3rK6zWq0WRUVFVvuSl5dndTnn5eVZfa98EGmxFPnMmTP/sh+/H0uWLJk5fvz4v9oNs7h79y5iYmKQnZ0NjuMQFBQEpVIpyca7776LNWvWwMHBAW3atIFMJm1eoaamBk8//TSICKGhoZJ/HwB2796N/8feeYdFcbZt/5xdYOm9F0ERMAioICKIdBEWFrAlRsXYSxKN0SS2qGjQmBhrzBM1akRNsEdNLFhiQWM0YuxiC3aU3pa+e31/kJ2XdQGZId8Tv++d33Hcxw67e5173X3mbqxYsQL29vawtbXlbA8Aq1atwv79+9GuXTtYWFjw0pg6dSr++OMPtGvXDqamppztlUolhgwZgmfPnqF9+/YwMDDgrFFWVobk5GQolUq4urrySs+cnBx88sknMDc3h5OTExiG4ayRlZWFb7/9Fs7OzjA3N+dsDwBnz57Fjh074OrqCkNDQ14ap06dwt69e+Hq6sorPQHg119/xY8//ghnZ2de+QoABw4cwHfffQcrKyvY2tryStPNmzfj66+/hq6uLtq1awexWMxZ47PPPsOaNWsAAM7OztDR0eFkzzAMhgwZgj179kCpVKJdu3aQSCScNGpra9G9e3dkZWXxbneysrIQERGBhw8fQk9PDw4ODpzbntTUVMyePRv5+fkwNzeHlZUVp3xhGAa9evXCgQMHUFlZCQcHB87l9N69e/D19UV2djYAwMnJiXNaLFmyBJMmTcKTJ0+gr68Pe3t7TmkhEonQq1cvbN++HYWFhbC0tOTcBubk5MDT0xN//vknqqqqYG9vz7m+rVixAiNGjMDdu3cBcE8LLS0tBAcHY/369Xj69CmbFlzy9PHjx3B3d0dmZiaKiopgYWHBuf1at24dBgwYgKtXr7Jpoa+vzykeUqkUS5Yswf379yESieDg4AAtLa1Wa5SWlqJDhw44ePAgnj9/DkNDQ9jY2HBKi4MHDyIsLAwXLlxAWVkZrK2tYWJi0mp7hmEwbdo0TJ48GdnZ2VAoFHBwcODUXmhpaSEgIAAbNmzAo0ePIJFIOJfviooKdOzYERkZGSgoKICpqSksLS05pcWDBw/g4eGBc+fOoaysDDY2NpzSAgBu3rwJb29vZGVlQS6Xw97ennN78eDBA3Tq1AkXL15EZWUlL42qqiq4u7vjxIkTvOMiEokgk8mwdu1avHjxAqamprC2tubcr23duhWDBg3CvXv3IBKJ4OjoyKmcAw0Dbx4eHjhx4gTKy8tha2sLY2NjThoA8Pnnn+O9997Dw4cPIZFI4OjoyOt+1t3dHWfOnEFFRQXs7OxgZGTE2Zf58+fjgw8+wIMHD6CjowMHBwfO/f2LFy/g7u6O8+fPQy6X8/JFJBIhMTERq1evxrNnz2BoaMjr/mXZsmUYOXIk7t27B4Zh4OjoyLmfS09Ph0wmw82bN6FQKODo6Mj53mPx4sV499132XR1dHTkdR+lYv78+bkpKSnrWvNdpq1P7v836d69O128ePHfdqNZCgoKoFQqIRaLIRKJMGXKFGzevBkAoK+vj+joaCQmJiI+Ph6WlpYa9qpZBkNDQ2hpaeHevXtwd3cHEcHOzg5vvfUWhgwZgu7duzdbuCsqKiCRSNiCO2HCBKxduxYmJiZ4++23MXLkSPj7+zdrr1QqIZfLYWhoCIZhUFNTAycnJ+Tn58PX1xejR4/GkCFDWnzIkMvl0NLSYgv+/fv30bFjRwBAr169MGLECLz55pstNoDFxcUwMjJiG9rDhw8jNjYWABAaGork5GQMHDiw2U6hqqoKCoUCBgYGbFxXrFiBDz/8EGKxGH379kVycjISEhKavfEpKSmBgYGBWiMwbtw4fPfddzA2NsagQYMwfPhwBAcHN9kI19bWora2Vs0HAAgJCUFmZiY6duyI4cOHY/jw4XB2dm7Sh/Lycujp6al1OAqFAh06dMCjR48QGhqKkSNHYuDAgU3ezCoUCrZMNfahqqoKDg4OKC8vR1xcHEaNGoXY2NgmGzy5XA5tbW2NB7GKigo4ODigsrIS8fHxGDFiBKRSqYYGEaGkpATGxsYaDVllZSUcHR1RXFyM0NBQDB8+HAMHDtQoG3K5HEqlEvr6+hoaVVVVcHJyQmFhITw8PDBkyBC8/fbbcHNzU/teYWEhdHR0NNJTlc7t2rVDSUkJLCws0L9/f7z55psICwtjv1tVVQW5XA4dHR02PRr7ohoUqa2thZ6eHmJiYjBgwADEx8ez5bSwsBBEBC0tLYjFYmhpabHXIpEIZ8+eRXBwMABAR0cHUVFR6NevHxISEmBtbY3a2loUFxez3xeJROy16nXZsmWYOXMmgP9pd5KSkhAXFwdLS0sUFxejtraWtReJRGAYRu3vuLg4nDx5EgBgYWGBuLg4JCYmIjo6Gnp6esjPz2dtGr+qrouKiuDp6cmOkLu6uiIhIQEJCQkIDg5GZWUlKisrWZumws6dOzF+/HgADTfqAQEBrIanpydevHjBfqZ6ffl6+PDhOHjwIABAV1cXUVFRSEhIQHx8PIyNjVFeXo6XaVxPSkpK4Ovry846WFlZIS4uDjKZDNHR0aisrGRnABv3nY2vf/rpJ0yaNIn9293dHTKZDPHx8fDz80N5eTmIiLVRXTcOY8eOxfHjx1n/evbsifj4eMTHx8Pe3h41NTUgIiiVyiZfi4uLERISws7y6enpISIiAnFxcWyeKpXKFsPevXsxe/ZsNh5WVlaIiYlBXFwcAgICoK2tDYVCwX5fdd34vUmTJuH06dOshpubG6RSKWJjY+Hu7g4tLS0oFAo128Z/l5aWom/fvmw8VOVCKpUiNDQULi4uICI1u5fD0aNHMWvWLNYHfX19REREQCqVonv37rC1tVX7fn19vYZGSkoKDh06xGrY2toiJiYGkZGR8PX1haGhYYs+1NbWIiEhQW1G38vLC1KpFEFBQfDx8YFIJNJIh8bXd+7cwdtvv83aa2trIyQkBH369EHPnj3Rvn17tgw0lRcKhQI7d+7EokWLWA0zMzP07dsXoaGhCAoKgpmZ2SvLRWpqKnbs2MFquLi4ICYmBkFBQQgMDIREImmyXDa+njBhAjIzM1kNHx8fREVFISQkBN26dQPDMGr1cts+sgAAIABJREFUQWXb+O/hw4fjwoULrIa/vz9CQ0MRGRmJzp07a2g0FcaPH49ff/2V1fDz80N4eDiioqLQuXNntfr9cn1VXS9evBjr1v3P/banpyeioqIQGRmJbt26sfcKzdkDwMmTJzFixAhWw97eHlFRUYiKikKvXr3UHipetlW91tTUIDAwEIWFhQAa6ryqfERGRsLKykrt+81df/nll/jmm2/UyqnKF1U5ber3G18XFhYiICCAXTlibGyM8PBw9OnTB2FhYWr3cc3pEBFmzJiB7du3s+97e3uzvnh5ebFtd3NpUlFRgQcPHiApKYltt42NjREWFoaoqCjWl+bsiQj5+flQKBSYN28ejh07xvri4+ODyMhItrw19rvxtWoVDhHh999/xyeffMJqWFlZITw8HJGRkQgKCoKBgYFa+VTpFBUVsW1+SUkJBg0axKatRCJBcHAwIiIiEBYWBhsbG7XfJyLU1NSguLiYfb+mpgaDBg1iV0ppaWmhZ8+eiIqKQkREBFxcXFqVx0FBQeyqBRMTE8TExEAmkyEmJobzgC3DMFlE1L1VX35Vxf43g5+fH73OdOrUiQC8MohEIgoJCaFly5bR/fv3Wftjx46x35FIJGRhYUEikUjDvmPHjjR37lzKzs7W8CEpKYkAkLGxMbm4uJCzs7OGfefOnemrr76i58+fa9g/fPiQAJCOjg7Z2dmRt7c3mZmZqdnr6urS0KFD6ddffyWFQqGhMWXKFAJAenp65ODgQF5eXqSjo6OmoaenR8OGDaNjx45paCgUCmIYhgCQgYEB2dvbN5m2urq6NHjwYDpw4ADV1dWpaaxYsYJNa1NTU2rXrh25urpqaBgZGdGIESPo2LFjVF9fr6bh4uLC+mpra0seHh7UoUMHDQ1nZ2f69NNP6fbt22r2+/btIwCkpaVFlpaW5ObmRv7+/tS+fXsNjfDwcNq0aROVl5eraURGRrL52b59e/Lz86M+ffpo5KuhoSGNGjWKMjMzSalUsvbXrl0jAKStrU02Njbk6elJvXv3psTERHJyclLTsLGxoY8++ohu3Lih5sPo0aPZvHByciIfHx8KCwuj/v37k6Ojo5qGlZUVffjhh3TlyhXWvqysTM1PBwcH8vT0pMDAQIqJiSF7e/sm8/XgwYNsvs6fP1+t7FhZWZGLiwt5eXlRz549ydLSUiNN/f39afny5fTs2TMiIjI1NWU/E4vFZGBgQJaWluTo6EgdO3YkAwMDDQ1LS0saP348HT9+nNavX99kXZZIJGRkZETm5uYkFos1vqOjo0NSqZQ2bNhAnTt3brZdYBiGtLS0mm0zevfuTRMnTmxVG9NSu9OSD68KEomEwsLCeNsDIDMzM/Lw8GiTRlN1iGt4ufxzDTo6OqSnp9cmDX19/TbHQyKRtFmjrUHVXgtBCEIQghCE0DiIRCIKDg6mL774QuM+uTkAXKRWPhv+6w+nLYXX/cHV3d291Rlpa2tLo0aNol27dlFNTQ0R/c+DDpcQFRVFN2/eZH3o3bt3q221tLQoISGB9u7dS7W1tURElJWVxen3O3ToQJ999hk9fvyY9eGdd97hpNGuXTuaM2cO/fXXX0REVFJSwjkdbGxsaMqUKfTkyRMiUn/QaW1wcHCgWbNmUUlJCRGRxgN7a0KPHj3oP//5D9XU1NCmTZs42xsYGNDw4cPZQYGuXbty1nBzc6OFCxfS48eP6eTJk5ztAVDPnj1p7dq1VFJSQv379+el4evrS6tWraIrV67wslfl64cffkgjRozgrcEwDEVERGgMnvDxpS322traTT4ccwkODg5tstfV1SVra+s2abw80MA1iEQisrOza5NG40EIvsHW1rZN9np6em1+8GyrD9ra2rzaqcbhVeVaJBKRlpZWi4MqzcVDZSuRSEhPT69ZDQsLi2bttbW1SVdXl/T19cnIyKjJwVwATZYp1WCQRCJh7Y2MjJq019XVbbKNEIvF7CCFoaEhmZiYNDtgYWJi0iofTE1Nm02LprQbazT2oyn75gYRGIZh46JKz+bi0VwaN9bR1tYmiUTSbDxeFRrrtPR7rdVqi70QhCCE/3vBwsKCkpOTaefOnVRaWtqq5ylweHAVlgq3gYqKCrUlPe+99x67hEa1vEsqlUIqlaJr164ay0vr6upQUlKCiooKVFRU4OrVqxg2bJjad8zMzBAaGoqwsDCEhYXB29tbTae0tBQFBQUoKipCUVERFi5cqLYEB2hYW+/t7Y3AwEA2dOzYEQzDoL6+Hvn5+SgoKEBBQQGePXuGMWPGaGxEF4vF6NKlC3r27ImAgAAEBQWxy4HlcjnrQ3FxMW7cuIHJkydrpJe1tTWCgoLY4OfnB11dXSiVShQWFqK0tJQNJ06cQGpqqkY8unTpgt69eyM4OBjBwcGws7MD0LCss7i4GGVlZSgtLUVZWRnS09Px/fffq2no6uoiICAAISEh6N27NwIDA9l9LS/7UFpaiq+//ppdsqdCR0cHPXr0QO/evVkNU1NT1NTUoKCgACUlJSguLkZxcTFKSkqwcOFC3L59W02DYRh4e3ujV69ebHB2dkZpaSkKCwvZ/FRdL1iwAPn5+Rpp6uTkhMDAQAQFBSE4OBg+Pj7Iz89nbRuHhQsXoqKiQkPDwsKCLReRkZHw9PRkf7e4uJj1paioCIsWLWpSw87ODr169UJQUBBCQkLg5OSkkZaqkJKSonHAh0gkQrdu3RAcHIzevXvD19cXenp6qKiogFwuZ+uIKkydOlXjwBRbW1uEh4ezdcXKygo1NTWorq5GVVWV2qtcLkdycrKaH6olN6plXl5eXqiurkZdXR27DFx1XVdXh/z8fMhkMrWDdDw8PBAdHY2+ffsiLCwMRIS6ujq1JYj19fXsdVZWFoYMGcLaq5Z0xsbGIiYmBs7OzqisrGx2OaZCocCaNWuwePFiVsPFxQVxcXGQSqUICwsDwzCoq6vTWLbXOLz11ls4e/YsgIa6HhQUhLi4OMTFxeGNN95AZWUl22m8vAyQiFBQUABfX192SaeZmRliYmIQHx+Pvn37wtDQELW1tc12REqlEjt27MD777/PxsPT05NdHhsYGIjq6mqNZVgvXw8ZMgSHDx8G0FBPIyIiEB8fj7i4ONjb22scxvJy/6da8qxaKuzo6Mj6EBERoXGgReNlxqrrrVu3QnU2g0gkQmBgIBISEiCTydCxY0fU1tZqLHF+edmzTCZDRkYGAMDc3Bzx8fHscmVtbe2GzruZpdsMw+D58+fo0KED245369YNiYmJSEhIgI+PD2pqappcNt44PmvXrsWECRMAAAYGBoiJiUFCQgLi4uJgaGgIpVKptmS9cRxUREZGsksxXV1dkZSUhMTERAQGBrLL18ViMavxMrm5uWjfvj1qamogFosRGhqKxMREJCYmws7ODgqFQs2+qS0xGzduxOjRowE0lEuZTIakpCRER0ezcW/JBwDo378/fvrpJwANS7/79euHpKQk+Pr6QqFQqGk05UNFRQVcXFxQWFgIhmEQHBzMpoVq7/DLafkyv/32G3r16gWgoZ1QbQmIjY2FkZGRmn1zGkuXLsVHH32klhaJiYkICQmBgYGB2vaB5jRGjBiBtLQ0AA3tvqpsBwYGQk9PT6NMNqUTERGBEydOAGjowxISEhAbG4ugoCDo6uqqleWXy7ZqCXBQUBB+//13AA31NCEhAX369EFISIiGRnMhNjaWrWdWVlaQSqWIiYlBREQEu92mpa0JADBt2jSsWrUKQEM9iYyMhFQqRXR0NLtss7Hdy68Mw+CXX35B//792fdUy+GlUik6deqkUbea0pHL5XB3d2eXozs5ObEavXv3ZpcbN6XT+HrWrFlYtmwZgIY+MSwsjNWxt7dvlUZubi7c3d3ZvlG1RUAqlSIwMBBaWlotxkfFu+++iw0bNgD4n74xPj4eMTExamewNJe+dXV1uH//Prp168YuFVb1K1KpFD169NBou15+VW1xSU5Oxt69ewEApqam7LaJvn37wsTEpNnyodoqwDAM9u/fzy73F4vF6N27N9u/uLq6NtkvAA33t0qlEgzD4OnTp+jcuTObtt26dWO3oqieM162VygUavf0ZWVleOONN9j7n86dOyMuLo7dzqJqB1vK52fPnsHd3Z3tUzt16qTWFnDd7yosFf4XuHfvHtnY2NCQIUNo69atlJ+fz1lj0KBBZG5uTv369aMVK1bQ5cuXm1ya2xzZ2dnsiLxUKqXPPvuMjh07RmVlZa3WWLx4MQENMz0DBgygJUuW0OnTp0kul7daY+jQocQwDPn4+NCECRNo8+bNdO/ePbUlrS2hVCopMDCQdHV1KTQ0lGbPnk2HDx9u9cgNEVFlZSU5OTmRsbExxcbG0ueff05nzpyh6urqVms8fvyY9PX1ycTEhKRSKS1atIgyMzOpqqqq1RoXLlwghmHIwMCAIiIiaM6cOXT48GF2lrc1/PLLLwQ0zLb07NmTPvzwQ9qxY4farPer2LFjBwENI+tdu3aliRMnUlpaGt25c6fV+aLSEIvF5OvrS++//z79+OOP9ODBg1Zr7N69m4CG2Y6wsDCaM2cOZWRkcCqju3btIqBh9mrw4MG0Zs0aun37dqt9ICLasGEDMQxD/v7+NGPGDDp27BhVVla22p6IaM6cOWRiYkIDBgygtWvXUk5ODid7IiKZTEYeHh40ZcoUysjI4FS2iIjkcjm1a9eOIiMjaenSpXTr1i1O6UBE9Ntvv5GlpSUlJyfTtm3bqKioiJM9EdHMmTPJy8uLZsyYQZmZmRpL+V9FfX09de3alWJiYujrr79mV2Nw4c8//yR7e3saM2YM7d27V2MZfmv49NNPqUePHrRgwQL6888/OadlXV0dde/enQYOHEhpaWm8+oHz58+Th4cHffTRR3T69GnOaUlENGPGDIqOjqZvvvmGHj16xNm+traWAgMDady4cXTgwAHO5ZKooVz5+/vTwoUL6fr165zTkqihjvXv3582b95MhYWFnO3r6uooMjKSJk+eTL/++iu70ogL169fp4CAAFq0aJHaaicurF69mmQyGW3YsIFevHjBSyM5OZlGjBhBe/fu5dQfq6isrKTAwED64IMP6MSJE7zK1b1796hLly40a9YsOn/+PKf7ExWZmZnUrVs3SklJoUuXLvEqF0eOHKFu3brRvHnzKCsri5fG77//Tp6enjRjxgw6e/asxtah1pCbm0tubm40ceJEOnToEK96olQqKSwsjAYMGECbNm2ivLw8zhpERMuWLaOAgABKTU2lq1ev8kqTvLw8cnV1pdGjR9PevXupoqKCly/Tpk2jsLAwWrp0Kd25c4eXxpMnT8jV1ZUmTJjAuw0iInr//fcpKiqKVq1axatfIWrYguXh4UHTpk2jkydP8qo7SqWSwsPDaciQIZSenk7FxcW8fJk2bRpJpVJas2YNu+KQK4sXL2bThM99CxHR1KlTKTw8nJYtW0Z3797lpdEYCDOu/31KSkpgZGTE+1St+vp63Lx5E15eXpxPX1Nx9epV6OjowN3dnZcGESEjIwNeXl5wdHTk5UNNTQ1OnTqFgIAAzqfrqSguLkZ2djZ8fX05n3Sm4vHjxygoKICPjw/vPLl+/ToUCgW8vLx4a5w+fRoGBgbo0qUL5xP+VOzduxfW1tbw9fWFrq4uL40tW7bA0dER/v7+vE8V/ic0du3aBUdHR/j6+nI+hVfFkSNH4OzsDHd39yZnBFrDuXPn4OHhwfuUZqChvnl6evLOV4VCgUePHqF9+/a8fSgrKwPDMLxOW1ShOgm4LScC5ufns4d/8KG6uhr19fW8yxUA9kAwvu0n0JCefE7RVKEafeZbtoGGEX4uJ+c2RXV1Ne+2Amjoj1Szbm3R4Fs3/ikN1SwF33YCADur2xZeBw3VzHBb0qKuro7X6fqNqa2tbVP9ABruM/jeG6hoax1RaUgkkjaXr/r6+jbHRy6X8z7tX0VVVRUkEkmb6v0/6Ytq5rwtvA7tKQB2ldTrUH/+CY1/Il0bw2XGtc0PrgzDOAHYDMAWgBLAOiJa+dJ3wgDsA5Dz91t7iGjBq7T/X3pwFRAQEBAQEBAQEBAQEGg9XB5c2zYc2kA9gGlEdIlhGCMAWQzDHCWimy99L5OI4v+B3xMQEBAQEBAQEBAQEBD4X0Tb1gMAIKJcIrr093U5gFsAHNqqKyAgICAgICAgICAgICAA/AMPro1hGMYFQDcA55v4OJBhmCsMwxxiGKZzE58LCAgICAgICAgICAgICGjwTywVBgAwDGMIYDeAKURU9tLHlwA4E1EFwzBSAHsBuDWjMw7AOABo167dP+WegICAgICAgICAgICAwP+j/CMzrgzDaKPhofUHItrz8udEVEZEFX9fHwSgzTCMZVNaRLSOiLoTUfe2nFIpICAgICAgICAgICAg8P8HbX5wZRrOqt4A4BYRLWvmO7Z/fw8Mw/T4+3cL2/rbAgICAgICAgICAgICAv//808sFe4FIBnANYZhLv/93iwA7QCAiNYAGAhgIsMw9QCqAAym1/kfyAoICAgICAgICAgICAi8NrT5wZWIzgBo8T8EE9FqAKvb+lsCAgICAgICAgICAgIC//sQp6Sk/Ns+NMu6detSxo0b92+70Sx37tyBsbExxGIxL3siwtOnT2FsbMzbh/z8fGhpaUFLi/8YxMWLF2FjYwORiN/K8QcPHuD69etwcnLC3yvCObNjxw5UV1fDzs6Ot8bWrVuho6MDS8smt0+3is2bN8PMzAwmJia87IkI6enpsLGxgYGBAW8/9uzZA2tra+jr6/PWOHToEMzNzdukcezYMRgYGMDQ0JC3xvHjxyEWi2Fqaspb49ChQyAiWFhY8NbYvn07xGIx+O6dr6+vx9q1a2Fubg5zc3NeGjk5OdizZw8cHBx4p+nBgweRnZ0NJycnaGtrc7ZXKpVYtWoVtLW1ede3W7duYd++fbC3t+cdj/T0dDx9+hROTk682i+5XI5Vq1bBxMQEVlZWvOJx6tQpnDlzBvb29rzryapVq1BRUQFHR0defcHDhw+xfv16mJqawtLSklc8du/ejUuXLsHOzo5Xu6NQKLBw4ULU1tbC0dGRV35cv34dGzduhJGREWxsbHjFY8uWLcjKyoKNjQ2MjIw429fX12PevHmorKyEg4MDdHR0OGvcvn0bq1evhp6eHuzs7Hj1i3v27MGvv/4KS0tLmJmZcbYHgCVLluDp06ewt7eHnp4eZ/vKykrMmzcPRAQHBwdeefrXX3/h66+/hoGBAWxtbXnl6fnz57Fjxw6YmZnBwsKCdz39+eefYWlpybvtPXfuHPbs2dMmjbt372L9+vUwMTGBtbU1r7hUV1dj4cKFEIvFcHBw4H3ftX79ety/fx+Ojo7Q1dXlpXHlyhX88MMPMDc35503RITFixdDLpfzbjsA4MSJEzh48CCsra153yvU1dVhwYIFbJnne2++fft2XLhwAXZ2drz7t+zsbKxZswZGRka8645cLkdKSgpEIhHv/qWmpgazZ89GXV0dHB0ded0zyOVyfPrppyCiNuVxS8yfPz83JSVlXau+TESvbfDz86PXmc2bN5O5uTmNHj2aDh8+TLW1tZw1pFIpxcbG0u7du3nZ5+TkkLW1Nc2YMYNycnI42xMRTZ8+nZycnGjevHn08OFDzvZVVVVkZWVFrq6uNH/+fF5+7NmzhwCQh4cHffbZZ3T//n3OGt988w0BIF9fX/rqq6/oyZMnnDUWLFhAACgkJITWrl1LhYWFnDVmzJhBYrGYpFIppaenk1wu56wxZ84c0tbWpqSkJNq9ezdVV1dz1li6dClpa2tTYmIi7dq1i6qqqjhrpKWlkUgkoujoaEpLS6PS0lLOGnv37iUAFBgYSCtXrqRnz57x1vD29qb58+fTzZs3OWusW7eOAFCnTp1o5syZdOHCBVIqlZw0Jk2aRACoc+fONHv2bLpw4QIpFIpW2ysUCvL29iaGYahnz560aNEiun79Oic/srOzSSQSkZ6eHslkMlq3bh3nNJ0/fz4BIHt7exo3bhz9/PPPVFlZ2Wr7uro6cnNzIwDk7+9PCxYsoD///JNTPE6cOEEAyMDAgPr160cbN26k58+fc4pHcnIyAaD27dvTpEmTKCMjg1NdKSwsJCMjIxKJRNSrVy/6/PPP6dq1a5zioSpXRkZGNGDAAPr+++85xUOpVFJwcDABIBcXF3rvvffo4MGDnPLjzp07JBaLiWEYCggIoAULFtDFixc5lc3U1FQ2P2QyGX377bf04MGDVtsrFAry8fFhy9Xo0aNp165dVFJS0mqNGzduEMMwBIB8fHxo+vTpdPLkSU5946JFiwgA6ejoUJ8+fWjp0qV08+bNVuepUqmkwMBAAkAWFhb09ttv0+bNmznl6dOnT0lXV5cAkLu7O02ePJkOHTrEKU937txJANiy+dlnn3HOU1V7ZWBgQAkJCZzztHHZtLa2puHDh9O2bduoqKio1Ro1NTXk7OzM1tP33nuPDhw4wKlfrKioIGtra/Ye4cMPP6SjR49yqutVVVXk4ODA5smUKVM4ayiVSvL39ycA1K5dO5owYQL9/PPPnPv4Dz74gACQmZkZDR48mLZs2UL5+fmcNE6ePEkASEtLi8LCwmjJkiWcyjlRQzvu7u5OAMjV1ZUmT57MuQ0lIlq1ahUBIH19fZLJZLR27Vp6/PgxJ42ysjKysLAgAOTp6UmffPIJnTp1iurq6jjpzJw5U6095tOv3L17l8RiMQGg7t2707x58+iPP/7gVPeUSiX5+fkRAHJwcKCxY8fS3r17qaKigpMv48ePJwBkbGxMgwYNok2bNtGLFy84acyYMYMAkK6uLkmlUvrmm284tQNERO+99x7bliQlJdF3331HT58+5aTREgAuUiufDRl6jbeadu/enS5evPhvu9EsW7duxahRo1BXVwcAMDc3R1JSEt58801ERES8cmTjxYsXmDVrFjZu3AgAsLGxwYgRIzBmzBh07NixVT6cOnUKI0eORE5ODhiGgVQqxbvvvou+ffu2anRGLpdjwYIF+PLLLwEADMOgb9++GDNmDGQyWatGrI8fP46ZM2fijz/+YN8LDQ3FO++8g4EDB7Zq5HzOnDlYvHgx6uvr2fcCAwMxbNgwvPnmm6+cRT137hz27duHL774gn2PYRiEhoZi6NChGDBgwCtHvlesWIEnT55g6dKl7Hva2tqQSqUYOnQo4uPjWxz5vn37NrZv347y8nJ89dVX7PuGhoYYMGAAhg0bhvDw8BbzJS0tDc+fP0dlZSUWLFjAvm9mZoY333wTycnJCAoKanb0Li8vD99++y2MjY1BRJg2bRr7mampKQYNGoRhw4YhODi42ZHevXv34saNGzA0NISOjg4mT57M5ouuri4SEhIwZMgQxMbGNlk+ampqkJqaCj09Pejr60MikeCjjz5CZWUlgIZ8CQkJweDBgzFgwIAmZ0CPHz+OU6dOQSKRQEdHBzo6Opg1axarAQCenp4YOHAgBg4cCC8vL400WbBgAerq6qCtrQ0tLS0oFAqkpKRAqVSy33FyckJSUhL69++P4OBgtZHEixcvYvfu3RCLxRCJRBCJRHj+/DnWrl2r9jv29vZITExEYmIiwsPD1dJk5cqVyM3NhUgkAsMwYBgGv//+O44fP66m0aFDByQkJCAhIQHBwcFs23H//n189913bLqpXjdv3oynT5+qafj7+0MmkyEhIQE+Pj7s99PS0nDr1i2175aWlmLNmjVq7+np6SEqKgoymQzx8fGws7MDABQVFbHtQ2POnDmDs2fPqr3n5OSE+Ph4yGQyhIeHszMBP//8M86cOaOh8e2336K8vJz9m2EY9OjRAzKZDDKZDN7e3mw8pk+fDqBhsFXFgwcPsHPnTjVNQ0NDREdHIz4+HlKpFDY2Nqy/+/fvZ+1VneCBAwdw+/ZtNY127dohPj4e8fHxavFYvHgxCgsL1TrR2tpafPPNNxpx69GjB+Li4hAfH49u3bqBYRhcv34dmzdvhlKpZAMR4erVqzh58qRGfkRGRkIqlSIuLo7993Br1qzBvXv31DQUCgX27NmD58+fq2nY2NggNjYWUqkU0dHRMDExwbNnz7B8+XIoFAq1UFpaivT0dI14eHp6QiqVQiqVolevXtDR0WFnJFS29fX1UCgUuHz5slo/AABaWloICgqCVCpFbGwsvL29UV1djblz57K2Kvv6+nrs27cPhYXqZzcaGxsjKioKsbGxiImJgaOjI44ePYqMjAzWXhVKS0uxa9cujXg4OzsjJiYGsbGxiIiIgJGREebOnYuKigoNjRs3buDChQsaGn5+fqwPAQEBuHz5MrZt26YRh/r6ehw5cgTPnj1Ts9fV1UV4eDjrh5ubG1auXIlHjx5paNTV1WHr1q1q7ZUqT/v27YvY2FhER0ejpKQE3377LWvbODx//hy//PKLRjzeeOMNNj+Cg4Oxfft2XLlyhS1LjcPNmzfx22+/qdmLRCIEBgayGi4uLvj8889ZG5WO6vX333/HtWvXmkwLVdm6desWTp48ydo11lAqlTh9+jSys7PVNAwNDREVFcVqfP3116ivr1erG43DmTNncOPGjSY14uLiYGVlhbNnzzZrT0S4cuUKzp07p6YhkUgQHh6OuLg4PHnyhPWbiNReVdcvXrzAnj3q/4CDYRj07NkT/v7+KCkpgZWVlYb9y69btmxR6xOBhr7ExcUFZmZmcHR0hEgkalHnjz/+wKVLl9Q09PX1YW9vz2oZGBio2bysU11djbS0NI1yZmVlhQ4dOqB9+/ZsO9ycDhHh5MmTuHPnjkbauri4oH379nB2doaurm6zfhARioqKsHv3bg1fbGxs0L59e7Rv3569n2zOD6VSiZ9//hl5eXka6aLyRTV7+fLvN76+du2aRnsoFovh6OgIFxcXODs7w9jYuEWN3NxcHDp0qMn4ue11AAAgAElEQVT4ODs7w9nZGebm5mp2jcuaUqnEkydPNPoXoOGZxcXFBe3atWPzp7ly++LFCxw5ckRDo1u3boiLi0NcXBz8/f15z3IzDJNFRN1b9eXWPuH+G+F1n3H18PAgAE0Gc3NzGjVqFF28eLFZ+8OHDzdrHx4eTj/++OMrZ8liYmKatG/fvj198cUXrxzFy87ObtYHa2tr+vjjjyk7O7tFjYkTJzaroa+vT8OGDaOjR49SfX19k/bV1dXN2uPvEcX4+PgWZy+/+OKLFjVUM4/bt29vdtTbzs6uRQ0jIyN655136MiRI03GZceOHS3aAyA7OzuaNm0aXb58ucmR0aCgoFdqdOjQgebOnUt3797VsP/jjz9eaQ+AnJ2dadasWXTr1i0NjaFDh7ZKw8zMjMaOHUsnT55UG4nMz89vlT0AEovFFB0dTRs2bFAbxZ89e3arNfD3KPzs2bPp+vXrrIahoSEnDQsLCxo5ciSrsX79ek72qjIyatQodgbU29ubs4apqSktWLCAqqqq6Pjx45ztAZCbmxv9/PPPRESUkJDASyMpKYlycnLor7/+4mVvZGREX3zxBdXU1LAzDFxDly5dKDMzk4iIlz3DMDRu3DgqKCig5cuX89KwtramtLQ0UiqV7MwR1xAREUE3btygn376iZe9np4ezZ49m+RyOYWFhfHS6NSpE+3fv58uX77My15bW5sGDRpEOTk5NHLkSF4a9vb2tGjRIsrLy+NlD4CCgoLo8OHD7KoBrsHQ0JCGDRtGOTk5ZG5uzkvD2dmZ5s+fz6uNUIUePXrQzp072VkZrkFHR4fi4+Pp+++/5+2DkZERjR07luLi4nhrWFlZ8a7fjctFREREmzQcHR3ZWbK2pEdb7AGwKwaEIIT/TUFfX5/Gjh1LeXl5Td5fvwpwmHH95xcq/y9i+PDh7LpvFXp6eggNDUVUVBT69OkDLy+vZu3t7e3h7++vMSIDNOwX+uGHH1BUVIRx48Y1O3vbt29fHD16FAqFQu39nJwcfPbZZzh69ChSU1MREBDQpL1qluXYsWMan+Xl5WH//v148eIFPvzwQ3Tt2rVJDX9/f+zduxe5ubkan4nFYrx48QK//fYb7O3t4enpqfGd+vp6DBo0SGPmRIWDgwPMzc0hl8tRUFDAzjw0xt3dHXFxcThw4ECTGh06dICNjQ0UCgXKy8ubnDlNSEjA7du3mxyZAhpGD0UiEZ49e4aioiKNmUI7Ozu89dZbePjwIX7//fcmNRQKBR4+fIhTp07B3t5eQyM8PBzW1tZ48uQJmlttoEpPLS0tjBs3jh0pAwAjIyO8/fbbKCsrQ15eXpNlCwByc3ORmZkJABg/frxamgYEBKC2thbl5eUoKyvTGG1XUVVVhfv37+P06dOwtbWFh4cHgIY8T05ORlVVFSorK1FZWYnTp09rzBwADTPJpqamqKurQ3FxMTsr3rVrVwwbNgw1NTWoqalBbW0tjh07pjYjr8LHxwd9+vRBSEgIOnTowL4/dOhQVFZWsrMXtbW12L9/v4a9gYEBIiMjERMTg759+7Iabm5uGDFihNoIZlFREQ4fPqyh4ebmxo76h4SEsDN0SUlJ6N69u9oI5q1btzTyVltbG2FhYezIpWrFhZ2dHUaNGgUAau3MwYMH8eLFCzUNW1tbxMXFQSaTITIykt2bExUVpbFiQS6XY/v27Rrx8Pf3Z2dMu3btCoZhkJ+fz/rQmMuXL2uM1BsaGqJv377sbKe1tTWAhjI1evRoDY0dO3aozbiq0lI149qrVy+27Rs1ahQ7aw00zFDk5uZqzCjp6OggPDycnTl2dnYGAHTu3BmjR4/W0Dhx4gTu3r2rpuHg4MDOgIeFhbH5OXjwYBQWFoJhGHYWXalU4rvvvlPLH5FIhODgYCQkJEAmk8Hd3R0AUFtbizFjxrAz+CqdW7du4ddff1XzwcrKCvHx8UhMTESfPn3YPbhxcXFwc3NjVwKoXnft2tXkLHxSUhISExPh6ekJhmHw9OlTjBkzBmKxWC1UVlZi3Tr1LUZGRkaIi4tDUlISYmJi2L3/YWFh0NHR0dDIysrSaD87deqEfv36sXVBJBKhpqYGY8eOhZaWFmurut6yZYtaX6KtrY2IiAj069cPCQkJ7EqA+vp6jB8/nrVTnfVQWVmJ1avVz4K0srJCQkIC+vXrh8jISDY/R4wYgaqqKjV7LS0tXL58WaOee3l5oV+/fujXrx9bN86fP49x48ap2aq0du7ciXv37rH2YrEYYWFh6NevHxITE+Ho6Aig4awM1UxFY3uGYbBs2TJ2RZcqP6RSKZKSkiCVSmFsbIz79+9rpKVKIy8vD5s2bVKLh62tLRITE9GvXz+EhYVBIpFg7dq17J7Al8PVq1eRkZGhpuHq6oqkpCQkJSUhMDAQ5eXlkMvlbHlUBdXfmZmZOH/+vJpG586dkZiYiKSkJPj5+eGnn36Cq6srWzdeLt/Hjh3DlStX1DS8vb3Z1S5+fn549913oVQqWY2Xw8mTJzXaLA8PD1ajqqoK27Zt07BT1VORSITLly/jxIkTahqOjo5ISEhAYmIiTpw4odZGNKWRl5eHH374QU3D2NgYsbGx8PX1xfXr16Grq6th9/L1unXrUFFRwWqo2h0zMzPo6OjAzMxMra1q6vXcuXMaM8iOjo4wNjaGi4sL7OzsoK2t3aS96rqmpkZj1Ym2tjZsbW3ZmUVDQ8MmbRtfZ2Rk4Pr162o6pqamcHFxgYuLC2xsbCAWi5u1ZxgGhYWFGmVeW1sbTk5OarO2LfnBMAx++OEHjRUT1tbWcHFxQYcOHWBubt6kL41fL1y4oFFWjIyM1GZtVeW7OT8ePXqksRJGV1eX9cPFxQUSiaTF8nbnzh2N/l5PTw8uLi5wdXWFk5MTJBJJk3Fo7MeWLVvUNGxsbCCTyZCYmIjIyEhee/F50don3H8jvO4zritXriSRSEQ9evSgWbNm0YkTJzjtDSgqKiIrKyvS19en3r1707Rp02j79u2Uk5PT6n0KK1asIABkaWlJffr0oenTp9O2bdvozp07rVqPr1Ao2P08NjY2lJCQQKmpqXT06FEqLi5ulQ+3b98mbW1tAkBOTk40ePBg+vrrr+nPP/9sdpb1Zb766it25KZjx440evRo2rx5M6d1+J9++imr0alTJxo/fjylp6dz2v/37rvvshru7u40duxY2rp1K6f9GmPGjGE1nJycaNiwYbRu3TrKzs5udb6q9iYBDTOBSUlJtHTpUrpw4UKr93stXLiQ1TA0NKTo6GhKTU2lU6dOtXq/6+bNm9VG1KKioig1NZUyMzNbXdYzMjJYDSMjI5LJZLR8+XK6cuVKq/eMHD16lNWwtbWl5ORk2rJlC+Xm5rbKnogoPT2d1fD29qaPP/6Yjh8/zqnOzpo1i4CG2Y7o6GhasWIF3blzp9X2SqWSAgIC2Po2atQo2rNnD5WVlbVa48GDB2x98/Pz47X/RlXf9PX1KTExkdavX8+pnqj26gIN+zInTZpER44c4ZSW58+fJ6Bh1j0kJISWLFnyytUdL6Pa/2NpaUnvvPMO7dq1i1NalpaWkpmZGQENe+NTUlLo0qVLnPaJbdmyhYCGvT8DBgygtLQ0Kigo4BSPyMhIts35+OOP6cyZM61uO4kazjrQ0tIibW1t6tu3L3377bec9/irVq3Y2dnRhAkT6PDhw5z3/3Xr1o0AUEBAAH3++edNruhoiezsbGIYhgwMDGjgwIH0ww8/tLofejkezs7ONGXKFDp16hSntFQqlezKl8DAQPryyy+bXN3SErm5uSSRSEhPT4/69etHaWlpnM9L2LVrFwENM/5jx46lAwcOcN57qJoJdXNzo08++YTOnTvHqZ0gIgoJCSGgYa9famoq5z3gtbW15OLiQgzDUHBwMH311Vec01Mul5O1tTWJRCIKDQ2lZcuWcT4Ho7q6mhwcHIhhGAoKCqIvvviCc3vTuP3u0qULzZ07l7KysjiflTBlyhT2/uD999+nI0eOUE1NDScN1R7XtrQ79fX17FkF3bt3p88++4yuXLnCOT6qPa5WVlY0cuRIXns5y8rKyNzcnEQiEYWEhNBXX33FqW9VMX36dDZt33vvPcrIyOCctrdv3yaRSES6uroUHx9P3333Had7DSL1Pf/+/v6UmppKV69e5Zy2qtUtqr4hMzOTU3tG9D/3k506daLp06fTb7/9xllD5YenpyfNnDmTV1vSEhBmXP87dO3aFQUFBbxPDSwpKcHx48fxxhtv8Dqli4jg4+ODx48fw8HBgdepZc+ePcPUqVPRo0cP3qcC37hxA2lpaejVq1eTs6Gvoq6uDgUFBUhPT0dISAjs7e05a6hm9rZt24bQ0FDY2tpy1igsLIRIJEJ6ejpCQ0PZkX0uqPYzbt68GSEhIexsDxfy8vJQXl6ONWvWICQkBJ06deKcL+Xl5bh16xaWLl2KkJAQdO3alXMZq6+vx6lTp7Bo0SKEhoaie/funE/pJCIcOXIECxcuRGRkJPz8/HiV9dOnT2Pp0qXsKgau6UF/7zdZv349+vbty852cEE1+7tv3z5ERETwOm3wzp07iImJwerVq+Hr68vrRMkLFy7gm2++gVQqhYODA2d7pVKJiooKHDx4UG3/Jhdu3bqFIUOGQCaTsTN5XFGtKomJieF1ymdlZSWsra1x5swZ9OzZk9femkuXLmHRokWIj4/nVSaAhnbj0KFDajOzXMjNzUV0dDRWr16NTp068fLhxo0bbFryOaWeiCCRSHD+/Hl2VpQrDx8+xNixY5GQkMCrXAINe7r379/Pe/SeiGBoaIhLly6xs6Jcef78OYYNG4adO3fy6ouAhvMOtm3bhujoaN6nVcvlcmRmZiIwMJBX2a6vr4eLiwtu3LiBN954g3daDBo0CFu3boWTkxNne6AhLT799FPIZDJ2BQZXbty4gS+//BJxcXG8/2vAzZs3MX/+fMTHx6utUuLC48ePMWTIEGzbtg0uLi68NOrq6mBnZ9emMgoAT58+bVMbDjTkzdSpUyGTyXjXWfp7pcnZs2cREBDAe4/j9evXsXz5csTFxfH+7wEKhQJWVlZtTts7d+5gz549iIqK4v3fIR48eIB3330XMpmMdztSVVUFb29vZGdnsyvauFJfXw8PDw/cvn2bXfnDlerqanTr1g2zZs1q9fk7/zcRDmcSEBAQEBAQEBAQEBAQ+K/D5XAmfv9ASkBAQEBAQEBAQEBAQEDgv4Tw4CogICAgICAgICAgICDwWiM8uAoICAgICAgICAgICAi81ggPrgICAgICAgICAgICAgKvNcKDq4CAgICAgICAgICAgMBrjfDgKiAgICAgICAgICAgIPBaIzy4CggICAgICAgICAgICLzWCA+uAgICAgICAgICAgICAq81woOrgICAgICAgICAQBupq6trs0ZtbW2bNWpqakBEbdapqqpqs0ZlZWWbNerq6v6RdJHL5f+IRlvTVi6XQ6lU/ut+5ObmQqFQtEnjv404JSXl3/ahWdatW5cybty4f9sNAYH/GgqFAiIR//Gk+vp61NTUQFtbm7fGs2fPIJFIIBaLedkTES5evAg7OzswDMNL4969e8jNzYWVlRVvjYMHD8LY2BiGhoa87B8/fozff/8dTk5O0NLS4qVx5MgRKBQKWFhY8LIvKSlBRkYGnJycoKOjw0vj3LlzqKiogKWlJa+0rKurQ0ZGBhwcHHiXqxs3bqCkpIR3OhARTp06BWtra94+PHr0CHl5ebx9AICLFy/CzMyMtw8FBQV4+vRpm3y4fv06DAwMeJcHuVyO+/fv8y4PAHD37l1oa2tDIpHwslcoFLh69Sqsra15+/DgwQPU1tbCwMCAlz3QkJ+Wlpa827qnT58iLy8PZmZmvONx/vx5GBoaQldXl5d9UVERsrKyYGdnxzsev/32W5vaiNraWvzwww+wsLCAsbExLx/OnDmDzMxM2Nra8spTIsL8+fPx7Nkz2NjY8NK4fPkypkyZgvLyclhbW/OKy0cffYRVq1YhPz8fJiYmvNJ0x44dGDlyJB49egRtbW3Y29tzztvS0lL4+voiKysLNTU1sLe3h56eHicNAJg4cSJWrVqFvLw8GBsb8+qTz58/j8jISNy9excAePclISEh+OWXX1BaWgpra2uYmJhw1liyZAk++ugjPHnyBPr6+rCzs+N8z5WVlYWwsLA2xScvLw9du3bFlStXUFdXBwcHB85twOPHj+Hn54ebN29CoVDA0dGRc79w4cIF+Pv7IysrC2VlZbCysuKVrm1l/vz5uSkpKeta9WUiem2Dn58fvc6Ulpa2yV6pVFJNTU2bNB48eEDV1dVt8uHQoUNt8uPSpUv0yy+/UG1tLW+NlStX0qlTp0ihUPCyv337Nn366ad09epVUiqVvDSWLl1Ky5Yto0ePHvGyLyoqosTERFq/fj0VFhby0li3bh0lJSVReno6lZeXc7ZXKpUUHBxMgwcPpt27d1NlZSVnjQsXLpCpqSkNHz6c9u/fT1VVVZw1xowZQzY2NjR+/Hg6fPgw5/JVWFhIhoaG1LFjR5o2bRplZmZSfX09J43ly5cTwzDUs2dPWrRoEV27do1T2airq6OOHTuSgYEB9evXjzZu3EgvXrzg5MO+ffsIALm5udHUqVPp119/5VxPwsLCSCKRUExMDK1evZoePHjAyT4rK4sAUIcOHWjy5Ml05MgRzm3G0KFDSVdXl2JjY+mbb77h7MPDhw9JW1ub3NzcaMqUKXTs2DHOZeLjjz8mXV1dkkql9J///IcePnzIyb6kpIRMTU1ZH44ePcrZh+XLl7M+rF69mv766y9O9rW1tdShQwdydXWlSZMm0cGDBznX0R07dpBEIqE+ffrQ0qVL6ebNm5zKtVKppMDAQGrXrh2NGzeOdu/eTSUlJZx8OHfuHGlpaVHv3r0pNTWV/vjjD85t95tvvknW1tY0dOhQSktLo9zcXE72Dx48IF1dXerWrRtNnz6djh8/zrlcz5gxgwwNDUkmk9GqVasoOzubU1qWl5eTtbU1ubi40Lhx42jnzp2c2/6NGzeSSCSiwMBAmjt3Lp05c4ZTG6FUKql79+5kZGRECQkJtHr1arp9+zaneJw/f54AkKOjI40aNYrS09MpPz+fUzzGjBlDAOiNN96gDz74gA4cOEAVFRWtti8qKiJTU1MCwDtPN23aRAAIAPn6+tKMGTPoxIkTnOp5VFQUq9G5c2eaOnUqZWRktLqePn78mCQSCavRrl07GjNmDO3cuZOKiopapVFfX09eXl6shrGxMSUlJdGaNWsoJyen1XGZN28eqyESiahnz540b948OnfuXKv6U6VSSdnZ2SQWi1kdR0dHGjNmDO3atYuKi4tbpVFbW6uWrhKJhKKjo2n58uV069atV5ZVhUJBtbW19OOPP7IaAMjT05OmTZtGx44de2U5UWm8ePGCLWcAyMLCgoYOHUpbt25tscwrlUpWo6qqSi0+qr5x1apVdO/evRY16uvrqaamhiorK2nChAmshlgsppCQEPr888/pypUrzaaJyo+6ujqqqamhd955h9XQ0dGhqKgoWrZsWZNtQH19PVVVVVFpaSkVFBTQs2fP6OHDh+Tr66uWrm+88QZNmTKFDh48SHK5vMV0/acAcJFa+Wz4rz+cthRe9wfXcePGUVRUFO3cuZPXQ1tBQQEFBATQli1bON+Uq1i2bBlZW1vT7NmzeT1wlZSUkJeXF1laWtKUKVPoypUrnDV27drFNgATJkyg06dPc7qJUSgU1Lt3bwJAdnZ2NHnyZDp79iwnjdOnT5Oenh4BIA8PD5ozZw7nh9jk5GS24gYFBdHy5cvp8ePHrba/dOkSOTk5EQDS0tKi2NhY2rRpU6sadxVz5sxhfdDT06OBAwfSjh07Wt14/PXXX2odnqGhIb399tu0Z8+eVne8y5cvV+t4jYyMaMiQIbRnz55W+VFaWkpdu3ZVawhNTExo2LBhtHv37lbdzGzYsIHMzMzUNKysrGjUqFG0b9++VsVFVaYah/bt29MHH3xAx44de2Wd3b9/P9na2qrZqx6EU1NTW+xcVAwZMkTDB2NjY3rzzTdp8+bNr7w5/OOPP8jZ2VlDw8vLi2bMmEFnzpx5ZdvxySefkI6Ojpq9oaEh9e/fnzZu3EjPnz9v0f7p06fUqVMnDR+8vb1p5syZdPbs2Vf6sHLlSjIyMlKzNzIyogEDBtD333//ygEBpVKpUaYap0NmZibV1dW1qLFz506ytLTUSIekpCT67rvv6OnTpy3aExH1799fw4dOnTrR1KlT6fjx46+8QT5z5gzbRnC96VExdepUDR+cnZ1p/Pjx9NNPP1FZWVmL9vfu3SM3Nzc1e7FYTMHBwZSamkoXL158ZblesmSJWhsBgCwtLentt9+mTZs2UV5eXov25eXl5OPjoxEPHx8f+uijj+jo0aOvbP/T0tLIxMREzV5PT49iYmJo2bJlrUrLiIgIDR+cnJxo9OjRtG3btle2MxkZGRpthEgkoh49etDs2bPp3Llzr/Rh5MiRGj4YGRlRYmIirV69+pXl8vLly022Ec7OzjR27FjasWPHK8vljBkzSFtbW6Ot8/Pzo5kzZ9KZM2datM/NzSVXV1cNH3R0dCg8PJw+//xzunXrVosaX375JRkaGmpo6Ovrk1QqpRUrVrxysKp9+/Ya9gDIwMCA4uLiaNWqVfTkyZNm7devX0/6+vpNaujq6lJ0dDQtXbq0xYfHptrKxmUjMDCQUlJSmr3XOnDgAIlEomY1AJC7uztNmjSJDh8+3GRdjYmJIYZhWtQwMzOjt956izZu3KgxCXPz5k3S0tJq0f7lduPmzZtqGhMnTnxlPFTBxcWFJk6cSPv372f7ErlcTlpaWq+MR+M8TkhIoP/85z9sn/bFF1+oPXS/KjAMQwEBAZSSkkKXLl0iIiJHR8dWx0MV3Nzc6IMPPqCMjAxKT0/nFA9VcHBwoLFjx9KePXuoV69evDRcXV1p8uTJtGLFCs5xaFyHIyMjKS0tjffEUmsAhwdXYY9rG7h//z6OHTuGsWPHYvTo0Xj27Bkn+3v37uH8+fNITk5Gly5dcPjwYc4+3Lx5E3l5eVi4cCG6dOmCFStWoL6+vtX2ZWVleP78OQoKCrBixQrExcXhyy+/5LSXICcnBwBQWFiItWvXYvLkyVi5cmWr93rU1dXhyZMnABrW269duxZz585Fenp6q9fvP378mP2927dv4+uvv0ZKSgpOnjzZ6nioln0ADUunFi9ejJkzZ+LGjRutss/Ly0NxcTGAhiW7hw4dwqxZs/Dxxx/j8ePHrdJo/FtVVVXYtWsXpk2bhunTpyM/P/+V9iUlJXj06BH7d0VFBdLT0/Hxxx9j7ty5KCkpeaXGrVu31PK/vLwcP/74I1JSUvDll1+ioqKiRfuamhrcvn1b7b3S0lJs374dq1evxvfff//K8vXo0SMNX/Pz87Fv3z7s2LEDR44ceWXZuHbtmsZ7OTk5OHXqFE6ePIk7d+60aF9QUIDnz5+rvUdEuHbtGv5Pe/ceVWWd7gH8+wBbROIibtyoaF7QZaSYDqPNNF6yvHTUvNVopWI66VqjkzU1pdN0gjOrzqpjNa6h5eSUa7TSLp4uLo9jOoJZeSHBUkSQq1cGEeI+gBue8wcbBhGF/dsm74rvZy0W+315n99+9t6//b7vs9/fb5OcnIzk5GSUl5dft420tLSr1pWVleH48eNITU29os+1pry8vNW+k52djZMnTyIjI6PN1zQrK+uq57uiogJpaWlIT09Hdnb2dZ/L2tpaZGdnXzOH9PR0lJaWXjeHs2fPXjW3qLy8HOnp6Th16lTTPuR6WvYpADh9+jSys7ORl5fX5tylwsLCq/KsqKjAmTNncP78+Xa9v7Kysq5aV1BQ0PTeb6tfl5WVXXU/1dXVKC4uRlVVVbv2mTk5OVetq6yshNPphM1ma3PIWk1NDfLz869YV19fD1WFn58fQkJC2hwKeO7cuVaPM/7+/nA4HG0ONRMRnD59+qr13bp1Q1hYGAYNGtTm8L2ioqKr5t/5+vqiZ8+eiIiIQJ8+fa4bD6DV91ZwcDBuvfVWDB8+vM2hlWVlZVe9/2w2G3r16oWhQ4fitttuazOH5vvrRgEBAejXrx+GDx8Oh8Nx3fiamhoUFBRctT40NBSDBg3CyJEj2xw+2Nrr6ePjg7CwMAwZMqTNx6Gqrb6H/fz8EB4ejsjISPTv3/+6bRQVFbV6bGl8LoYNG4bevXtft41rnYMFBwdj4MCBiIqKQlhY2DXjnU7nNedjBgUFNbXRnr7VmoCAAAwaNAgjRozA4MGDW93G29v7unMfbTYbBg0ahKioKIwcOfKa79W2jo99+/bFbbfdhujoaAQEBFyVQ3vOI4ODgzF48GCMGDECAwYMuOrv7ZnD6eXlhf79+2Po0KEYMWJE05BoHx8fOJ3Odp8DNvb322+/HXa7vWm9O/M3G/vroEGDmvprXV2dW3NRRQQOhwN9+/bFwIED4eXl5dbjaNSzZ0+Eh4dj4MCBUFWjNvz9/REcHAy73W40n7ZPnz5Yvnw5nn/+eTzyyCMeTWO7odpb4XbEj9WvuO7Zs0ezs7ONh6bm5OTonj17NDU1VYuLi43a+fDDD3Xbtm2alZVl9GlIaWmpPvvss/rhhx+6dXWxuU8++USfeOIJ/fTTT42GyNbV1enixYt1zZo1+o9//MNoeOvBgwf17rvv1hdffFEPHz5sdAV7+fLlOm3aNH399dfdHlaqqlpQUKB9+/bVWbNmaXx8fLuGwLT0xhtvaEhIiM6dO1fXr1+vp06dcnsY4E9/+lPt0aOH/vKXv9QNGza4PZzx2LFjKiLqcDh0wYIFunnzZreH8T399NNXfJL62WeftXklqLnKysqmKxmjRo3S559/vt3Dmxpt3bq16ZPy6dOn61/+8he3RiiGVnAAABWGSURBVCU0DrsGGoZ7rVixQnft2uXW0OnGYbre3t46YcIEfe211zQzM7Pd8aqqCxYsUKBhNMKyZct0x44dbr1Hzp49q126dFEvLy8dP368vvrqq3rq1Cm3cnj22Webcli+fLnbOZSVlWlISIh6e3vrxIkT9fXXX2/XFbHm4uPjFWgYqvbrX/9aP//8c7eGETYO/bbZbDpp0iSNj493e5TKp59+2tQfHn/8cd27d6/bo23Gjx+vNptNp0yZouvXr2/Xld7mGvtUv379dNWqVbpv3742rza3FBMToz4+Pjp58mRdv369Xrhwwa34/Px89fX11d69e+vKlSs1MTHR7Rzi4uJURHTcuHG6bt06t48///rXvzQsLExDQkJ06dKlRlNe3n33XQUahqa++OKLmp6e7lZ8fX29jh49Wrt27apz5szRLVu2uD2FKCkpqalfP/HEE/rVV1+5fSxvHC5455136tq1a90aTqqqevHiRfXz81NfX1+dNWuWvvPOO24PH3/11VcVgIaEhOiSJUt0586dbr0ely9f1sjIyKarTY8//rju37/frX3+nj17rriK99RTT+nBgwfb/XxWVFQ07W+Bhqvvq1atciuPEydOaGBgYFMbdrtdf/WrX7W7f5aXl2taWpr+/Oc/b2rDz89PZ8+ere+++267RnDl5eVpenq6xsXFXXH17M4779RXXnmlzWNQdXW1njhxQjMyMjQ5OfmKETvh4eH6m9/8RhMSEq77nj9//ryePHlST506pTk5OXr//fc3teHr66szZszQjRs3XnPUUX19vaampmp6erpmZmZqbm6uvvfee1c8nqioKH3hhRf06NGjrZ4nFRYW6okTJ5rayMnJ0aysLA0NDb3i9VmyZIlu37691WNaenq6pqWlaUZGhmZlZWlOTo6ePn1ap02bdsXjmT59ur711ltXjR4qKSnR1NTUpuciKytLc3Nz9cyZM7py5corrl5PnDhR161bd9VUnOzs7KbH0dhGYx7NR2x4e3vr3XffrX/605+uOO+rqqrStLQ0zcrK0jNnzmh+fr4WFRVpeXm51tTU6D333NPUxoABA/Tpp592631zI4BDhamzMf3woDl3T7xaqqioMB7y3SgnJ8ejNkpKSjQ5OdmjHc6BAwf022+/NW7D6XTqhg0b3J5n1VxSUpJu3LjR7RPq5tatW6c7duwwnqORm5vb7iHB1/K3v/1N33vvvXbPbWqptLRUY2NjNSkpyfj12LFjh77zzjt66dIlo/jLly/rK6+8YjSPsdGhQ4d0y5Ytxs+DasMwvpSUFOPXIjMzU7du3er2CXlzH3/88TVPktqjqKjI4xwSExM1OTnZOIfGuWKevBYpKSken9h89NFHbn8g1lxmZqbu2bPHo+9W2L59u9sfoDRXWFioH3zwgdH3ETTatWuXHjp0yPi5rK6u1vj4eLfnfDeXmJio77//vlsfLjZXX1+vf/zjHz16PY4cOeLxCfMzzzyjv//9743fHwUFBTp8+HB95pln9PDhw0ZtvPnmmx59oKPa8OFxUFCQPvzww+2eXtOS0+nUyMhInThxosbHx193iPT1xMXF6ZAhQ3T16tWalJRk9Jzk5uZqjx499OGHH9aPPvrI+P0ydepU/cUvfqFr1641ft++/fbb2r9/f33yySfd/mCkUWZmptrtdl24cKFu27bN6PGUlpZqnz59dM6cObp582ajiz6FhYXqcDh07ty5xm188803OnToUH3uuec8Or56yp3CVdTNS883U3R0tB45cqSj0yAiIiKiH7Ha2lrYbDbjb4gGGr7tul+/fh4Nq8zPz0dISIjxt3YDDf+Cpqqq6ophsybOnz+P3r17e/ScFBUVISAgwPib0IGGYceFhYVtDp1vyz//+U84HA6PH09gYKBH/72hrKwMNpvN6JueG33//ffw8/Mz/kZyoKGfdOvWzTj+RhGRZFWNbte2LFyJiIiIiIjoZnOncLXITFsiIiIiIiKi1rFwJSIiIiIiIktj4UpERERERESWxsKViIiIiIiILI2FKxEREREREVkaC1ciIiIiIiKyNBauREREREREZGksXImIiIiIiMjSbkjhKiJTRSRDRLJEZHUrf/cVkQ9cfz8sIv1vxP0SERERERHRj5/HhauIeAN4A8B9ACIBPCQikS02Wwrge1WNAPA6gJc9vV8iIiIiIiLqHG7EFdfRALJUNUdVawG8D2Bmi21mAtjkur0NwD0iIjfgvjvMxYsXkZKS4lEbX3/9NQoLC43jCwsL8fXXX3uUQ0pKCs6cOWMcX1FRgYSEBNTX1xu3kZaWhlOnThnHO51OJCQkoKqqyriN3NxcfPfdd8bxALB//34UFxcbx+fn5+PQoUMe5ZCUlIQLFy4Yx5eUlGDfvn0e5XD8+HFkZ2cbx1dXV2Pv3r2ora01biMzMxOpqanG8aqKxMRElJaWGrdx7tw5HDlyxDgeAA4cOICCggLj+EuXLuHLL7/0KIejR48iLy/POL6yshIJCQmoq6szbiM9PR3p6enG8XV1dUhISEBlZaVxG3l5eTh69KhxPAB8+eWXuHTpknF8QUEBDh486FEOR44cwblz54zjS0tLkZiY6FEOqampyMzMNI6vqanB3r17UVNTY9xGdnY2jh07ZhwPAPv27UNJSYlx/IULF5CUlORRDocOHUJ+fr5xfHFxMfbv3+9RDseOHUNOTo5xfOM+wpPziMzMTKSlpRnH34jziLNnzyI5Odk4HgC++uorj/YRhYWFOHDggEc5eHpeWFZWhoSEBKiqcRuexDa6fPmyx214cg4ANJxTlZeXe9RGTk4OnE6ncXxlZaVH54WWo6oe/QB4AMBbzZYXAohvsU0qgPBmy9kA7G21/ZOf/EStavz48QpAi4qKjOJTUlIUgC5atMg4h5iYGAWgKSkpRvEFBQVqs9l07NixxjnExsYqAN22bZtRvNPpVLvdrv369TPOYdOmTQpA165da9zGyJEj1c/PT8vKyoziv/jiCwWgK1euNM5h9uzZKiKakZFhFJ+Xl6deXl46bdo04xx++9vfKgDdvXu3UXxVVZUGBARoZGSkcQ5//vOfFYBu2LDBuI2IiAgNDg7Wmpoao/gdO3YoAF2zZo1xDvfee696e3vruXPnjOJTU1MVgM6fP984h8cee0wB6KFDh4zii4uL1dfXV8eMGWOcw0svvaQAdOvWrUbxdXV1GhYWpr169dK6ujqjNrZs2aIA9KWXXjKKV1UdM2aM+vr6anFxsVH8wYMHFYA+9thjxjnMnz9fAWhqaqpR/Llz59Tb21snTZpknMPq1asVgO7YscMovqamRoODgzUiIsI4hzfffFMBaHx8vHEbkZGRGhAQoFVVVUbxu3fvVgD61FNPGecwbdo09fLy0tzcXKP4jIwMBaBz5swxzmHFihUKQL/44guj+LKyMvXz89ORI0ca57B27VoFoJs2bTJuo2/fvmq329XpdBrFb9u2TQFobGyscQ5jx45Vm82mBQUFRvHJyckKQGNiYoxzWLhwocfnhT4+Pjpu3DjjHF544QUFoB9//LFxG7W1tXr77bfra6+9prW1tUZt/PWvf9XBgwfr5s2btb6+3qiNqKgoHTVqlO7atcsoPiEhQX18fHTKlCl6/PhxozZmzpyp3bt31xUrVhjVHJmZmerl5aXDhg3TnTt3GuXwQwNwRNtZd3rHxsZ6VPjGxcXdDiAiNjZ2u2t5BIA+sbGxf2+2zQoA78bGxpa5llcB+GtsbOy/WrYnIsvi4uLejIuLW2az2Xo/+eSTHuX3QwkICEBERASmTJkCb29vt+PtdjvKysowf/58DBgwwCiHoKAgBAUF4ZFHHjHKwd/fH7W1tZg5cyYiI1uO7m6fHj16QFWxdOlS+Pn5uR3v5eUFX19fTJgwAdHR0UY5hIaGorKyEo8++ih69Ohh1Ia/vz+ioqJw7733GudQWlqKBQsWIDw83KiNoKAgOBwOzJs3DyYDEoKCglBVVYW5c+diyJAhRjmEhITAZrPh0UcfRZcuXdyOt9ls8PLywuTJk3HHHXcY5RAaGorq6mosWbIEQUFBRm34+/tj9OjRGDt2rFG8w+FASUkJYmJiEBYWZtRGYGAg+vfvj9mzZxvFh4SEoKKiAvPmzcPAgQON2ujevTtuueUWLFq0CD4+Pm7H+/n5oa6uDjNmzMCwYcOMcrDb7XA6nVi6dCn8/f3djhcR+Pn5YezYsRgzZoxRDmFhYSgrK8PixYsRGhpq1MYtt9yCyMhITJ061Si+cR/x0EMP4dZbbzVqIzg4GHa7HQ899BC8vNwfMBUYGIjq6mrMmjULQ4cONcrBbrdDRLBkyRJ07drV7Xhvb2/4+Phg0qRJGDVqlFEODocDVVVVWLx4Mbp3727Uhr+/P0aNGoUJEyYY59C4z+/Tp49RG4GBgQgPD8cDDzxgtM8PDg5GZWUlHnzwQURERBjlEBISgq5duyImJgY2m83teF9fX6gq7rvvPkRFRRnl4HA4UFNTg5iYGAQGBhq10bVrV9x111342c9+ZhTfq1cvlJaWYuHChXA4HEZtNJ4Xzpgxwyi+R48eKC8vx7x584zPC7t37+7xeeHly5dx//33G58X2u12qCoWL16Mbt26GbXh7e2NyZMnY9q0aUaPA2jY5y5atAjjxo0zen8BwODBg/G73/3OuG83nov84Q9/MN5P+Pv7IyYmBsuWLTM6hvr7+2PgwIF4+eWXMXz4cKMcfmhxcXH5sbGxG9qzraiHl+NF5GcAYlV1imt5DQCo6n832+Zz1zYHRcQHwD8BhGobdx4dHa2eDrUjIiIiIiIi6xGRZFVt19WrGzHH9RsAg0VkgIh0ATAfwPYW22wHEOO6/QCAhLaKViIiIiIiIiIAcH/sWAuq6hSRlQA+B+ANYKOqnhCR/0LDmOXtAN4G8I6IZAEoRkNxS0RERERERNQmjwtXAFDVnQB2tlj3n81uVwN48EbcFxEREREREXUuN2KoMBEREREREdEPhoUrERERERERWRoLVyIiIiIiIrI0Fq5ERERERERkaSxciYiIiIiIyNJYuBIREREREZGlsXAlIiIiIiIiS2PhSkRERERERJbGwpWIiIiIiIgsjYUrERERERERWRoLVyIiIiIiIrI0Fq5ERERERERkaSxciYiIiIiIyNJYuBIREREREZGlsXAlIiIiIiIiS2PhSkRERERERJbGwpWIiIiIiIgsjYUrERERERERWRoLVyIiIiIiIrI0Fq5ERERERERkaSxciYiIiIiIyNJYuBIREREREZGlsXAlIiIiIiIiS2PhSkRERERERJbGwpWIiIiIiIgsjYUrERERERERWRoLVyIiIiIiIrI0Fq5ERERERERkaSxciYiIiIiIyNJYuBIREREREZGlsXAlIiIiIiIiS2PhSkRERERERJbm40mwiPwPgBkAagFkA3hUVUta2S4PQDmAOgBOVY325H6JiIiIiIio8/D0iuseAMNUNQrAKQBrrrPt3ap6B4tWIiIiIiIicodHhauq7lZVp2vxEIBwz1MiIiIiIiIi+rcbOcd1CYC/X+NvCmC3iCSLyLIbeJ9ERERERET0I9fmHFcR+QeAsFb+9Jyqfuba5jkATgDvXaOZu1T1goj0BLBHRNJVdf817m8ZgGUA0K9fv3Y8BCIiIiIiIvoxa7NwVdV7r/d3EYkBMB3APaqq12jjguv3RRH5BMBoAK0Wrqq6AcAGAIiOjm61PSIiIiIiIuo8PBoqLCJTATwL4H5VrbrGNv4iEtB4G8BkAKme3C8RERERERF1Hp7OcY0HEICG4b/fishfAEBEeovITtc2DgBfich3AJIA/J+q7vLwfomIiIiIiKiT8Oj/uKpqxDXWXwDwH67bOQBGeHI/RERERERE1HndyG8VJiIiIiIiIrrh5Brfp2QJIlII4HRH53EddgCXOjoJohbYL8lq2CfJitgvyYrYL8lqfug+eauqhrZnQ0sXrlYnIkdUNbqj8yBqjv2SrIZ9kqyI/ZKsiP2SrMZKfZJDhYmIiIiIiMjSWLgSERERERGRpbFw9cyGjk6AqBXsl2Q17JNkReyXZEXsl2Q1lumTnONKRERERERElsYrrkRERERERGRpLFwNichUEckQkSwRWd3R+VDnJCIbReSiiKQ2WxciIntEJNP1u3tH5kidi4j0FZFEETkpIidEZJVrPfsldRgR6SoiSSLynatfxrnWDxCRw65++YGIdOnoXKlzERFvETkqIjtcy+yT1KFEJE9EjovItyJyxLXOEsdwFq4GRMQbwBsA7gMQCeAhEYns2Kyok/obgKkt1q0GsFdVBwPY61omulmcAJ5S1dsA3AlghWv/yH5JHakGwERVHQHgDgBTReROAC8DeN3VL78HsLQDc6TOaRWAk82W2SfJCu5W1Tua/RscSxzDWbiaGQ0gS1VzVLUWwPsAZnZwTtQJqep+AMUtVs8EsMl1exOAWTc1KerUVDVfVVNct8vRcELWB+yX1IG0QYVr0eb6UQATAWxzrWe/pJtKRMIBTAPwlmtZwD5J1mSJYzgLVzN9AJxttnzOtY7IChyqmg80FBEAenZwPtRJiUh/ACMBHAb7JXUw15DMbwFcBLAHQDaAElV1ujbhsZxutj8BeAZAvWu5B9gnqeMpgN0ikiwiy1zrLHEM9+mIO/0RkFbW8euZiYhcROQWAP8L4AlVLWu4kEDUcVS1DsAdIhIM4BMAt7W22c3NijorEZkO4KKqJovIhMbVrWzKPkk3212qekFEegLYIyLpHZ1QI15xNXMOQN9my+EALnRQLkQtFYhILwBw/b7YwflQJyMiNjQUre+p6seu1eyXZAmqWgJgHxrmYAeLSOOH+DyW0810F4D7RSQPDVPOJqLhCiz7JHUoVb3g+n0RDR/yjYZFjuEsXM18A2Cw65vfugCYD2B7B+dE1Gg7gBjX7RgAn3VgLtTJuOZovQ3gpKq+1uxP7JfUYUQk1HWlFSLiB+BeNMy/TgTwgGsz9ku6aVR1jaqGq2p/NJxHJqjqI2CfpA4kIv4iEtB4G8BkAKmwyDFcVDkCwYSI/AcaPhnzBrBRVV/s4JSoExKRrQAmALADKADwAoBPAXwIoB+AMwAeVNWWX+BE9IMQkV8A+BLAcfx73tbv0TDPlf2SOoSIRKHhC0W80fCh/Yeq+l8iMhANV7tCABwFsEBVazouU+qMXEOFn1bV6eyT1JFc/e8T16IPgC2q+qKI9IAFjuEsXImIiIiIiMjSOFSYiIiIiIiILI2FKxEREREREVkaC1ciIiIiIiKyNBauREREREREZGksXImIiIiIiMjSWLgSERERERGRpbFwJSIiIiIiIktj4UpERERERESW9v/6YNDMmoA05QAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ch = create_channel(domain_size=(100, 30), lb_method=method, u_max=0.05,\n",
+    "                    kernel_params={'omega_0': 1.8, 'omega_1': 1.4, 'omega_2': 1.5})\n",
+    "ch.run(500)\n",
+    "plt.vector_field(ch.velocity[:, :]);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Bonus: Automatic analysis\n",
+    "Above we have created a non-orthogonal MRT, where the shear viscosity and bulk viscosity can be independently controlled. For moment-based methods, *lbmpy* also offers an automatic Chapman Enskog analysis that can find the relation between viscosity and relaxation rate(s):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$- \\frac{\\omega_{0} - 2}{6 \\omega_{0}}$$"
+      ],
+      "text/plain": [
+       "-(ω₀ - 2) \n",
+       "──────────\n",
+       "   6⋅ω₀   "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.chapman_enskog import ChapmanEnskogAnalysis\n",
+    "analysis = ChapmanEnskogAnalysis(method)\n",
+    "analysis.get_dynamic_viscosity()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$- \\frac{1}{9} - \\frac{1}{3 \\omega_{1}} + \\frac{5}{9 \\omega_{0}}$$"
+      ],
+      "text/plain": [
+       "  1    1      5  \n",
+       "- ─ - ──── + ────\n",
+       "  9   3⋅ω₁   9⋅ω₀"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "analysis.get_bulk_viscosity()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/04_tutorial_nondimensionalization_and_scaling.ipynb b/doc/notebooks/04_tutorial_nondimensionalization_and_scaling.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.parameterization import ScalingWidget\n",
+    "from lbmpy.parameterization import Scaling"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 04: Nondimensionalization and Scaling\n",
+    "\n",
+    "## Short version\n",
+    "\n",
+    "Play around with the widget below and make sure that.\n",
+    "If you can't see the widget start this tutorial interactively in a Jupyter notebook.\n",
+    "\n",
+    "- max lattice velocity $u_l < 0.1$, ( smaller means smaller errors)\n",
+    "- relaxation rate should not be too close to 0 or 2, otherwise simulation might get unstable. Keep in mind that advanced models (MRT, Cumulant, Entropic) can simulate more \"extreme\" relaxation rates."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            button[disabled], html input[disabled] {\n",
+       "                background-color: #eaeaea !important;\n",
+       "            }\n",
+       "        </style>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7416d2fe82094b4cb5095b2da3236da2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(Label(value='Scaling', layout=Layout(width='200px')), Select(options=('diffusive…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "p = ScalingWidget()\n",
+    "p.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Long version\n",
+    "\n",
+    "There are three different scaling/setup strategies available. In all strategies you first have to first fix the parameters of your physical setup. These are in this example:\n",
+    "\n",
+    "- typical physical length\n",
+    "- maximal physical velocity\n",
+    "- kinematic viscosity\n",
+    "\n",
+    "Additionally a first guess for the spatial resolution $\\Delta x$ has to be made, either by directly specifying it, or by selecting how much cells should be used to resolve the typical length. \n",
+    "\n",
+    "In the **diffusive scaling** approach, the relaxation has to be chosen/guessed. Valid values are $\\omega \\in (0,2)$, where values too close to the interval boundaries might lead to instable simulations. From this information the time step length and the maximum velocity in lattice units is determined. Compressibility errors and Ma-number errors get smaller with smaller lattice velocity. When using diffusive scaling, lattice velocities are decreased by a factor of 2, when doubling the spatial resolution. However also four times as many time steps have to be done in this case.\n",
+    "\n",
+    "The **acoustic scaling** approach lets you choose a fixed value for the maximum lattice velocity (choose something smaller than 1, or better smaller than $0.1$ there!). Doubling the spatial resolution in this approach has the following effects: time step length decreases only by a factor of 2 instead of 4 as in diffusive scaling, the relaxation rate is chosen automatically and may tend to instable values, and since the lattice velocity is fixed, the compressibility error and Ma error remain constant.\n",
+    "\n",
+    "The third scaling approach lets you choose $\\Delta t$ freely, while relaxation rate and lattice velocity are determined automatically.|"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example: Channel Flow\n",
+    "\n",
+    "To illustrate these concepts, we create a scenario which is defined in physical units.\n",
+    "We use the `Scaling` class, that provides the basis of the widget shown above.\n",
+    "\n",
+    "![](../img/channel_with_dimensions.svg)\n",
+    "\n",
+    "\n",
+    "| Quantity                        | Value                        |\n",
+    "| ------------------------------- | -----------------------------|\n",
+    "| Viscosity                       | $10^{-6} \\, \\frac{m^2}{s}$   |\n",
+    "| Time to simulate                | $3\\, s$                      |\n",
+    "| Max. inflow velocity            | $2 \\frac{cm}{s}$             |\n",
+    "| Resolution of cylinder diameter | $30$ cells                   |\n",
+    "\n",
+    "\n",
+    "The typical length of the scenario is chosen to be the cylinder diameter, that is resolved with 30 cells."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "DiffusiveScalingResult(dt=0.0002436647173489281, lattice_velocity=0.02923976608187137)\n"
+     ]
+    }
+   ],
+   "source": [
+    "cm = 1 / 100\n",
+    "sc = Scaling(physical_length=0.5 * cm, physical_velocity=2*cm, kinematic_viscosity=1e-6, \n",
+    "             cells_per_length=30)\n",
+    "scaling_result = sc.diffusive_scaling(1.9)\n",
+    "print(scaling_result)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the diffusive scaling approach we fix the relaxation rate and compute the time step length and the lattice velocity. Here we have to check that the lattice velocity is not too high (smaller than 0.1 as a rule of thumb).\n",
+    "From this information we can determine the number of time steps corresponding to the desired 3 seconds simulation time."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAEAAAAASCAYAAADrL9giAAAABHNCSVQICAgIfAhkiAAAAdJJREFUWIXt102ITWEcBvCfaRYWSj4yNlJKWSglS2WwsJoi1ixYKKVZKKVkNjJiN7GUBTtlJUpKPkpRV74mhSbTiBpyWchXY/H+Z5j7eY5x7z3lPvV2Tuc8z/95ztf7/g9dzMIujOA2PmEKF+pwl2AfLuMFvqCMO9iLnjq6k7iB8dB8QAnHomancoGHUfwzRpsY7Y/zb3ARJ3AOH+P4JcyrofuGe8Edjgu7H5oJrOhQLrAZq4PQ38RoCwZU39HleB3anTV08+vUOx6asx3KVYVmRo1wJLQjOTTrQnO9nbkafg9zwPfY/sihGYjto3+c5U9U5eptgUkvdsf+tQa8Q1iAhdiAjdLFD7cgU55cM+j3d6/a6dBdacJ7G7zpcRV9Bcg1J6ODoRnF4oyaPuzAc2nmXl+QXLmNDgT/qTTj5sVKfMWTouTKYzQY3MdYlsekAqWos7QIubIaHQ5eSePgWfAuai0qQq4sRkeD80C2b2uN2q9hj9+N0N125qpsCbfHEEG34ZXUg8OktHzBHpzHT6mxKNeoPxacaQziFG7hJd5Lk+AmrJJWhq141uZcMxgye2mqHGM5uFO4WVF/Lc5Ivf2k1JCUpX+BIfWfVqtzddHF/4pfDR3Y7I2xrpsAAAAASUVORK5CYII=\n",
+      "text/latex": [
+       "$$12312$$"
+      ],
+      "text/plain": [
+       "12312"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "total_time_steps = round(3 / scaling_result.dt)\n",
+    "total_time_steps"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Alternatively we could have used one of the other two scaling strategies:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "AcousticScalingResult(relaxation_rate=1.9577133907595927, lattice_velocity=0.012000000000000002)\n",
+      "FixedLatticeVelocityScalingResult(relaxation_rate=1.6949152542372883, dt=0.0008333333333333333)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(sc.acoustic_scaling(dt=1e-4))\n",
+    "print(sc.fixed_lattice_velocity_scaling(0.1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The scaling class also computes the Reynolds number and grid spacing for us."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left ( 100.0, \\quad 0.00016666666666666666\\right )$$"
+      ],
+      "text/plain": [
+       "(100.0, 0.00016666666666666666)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sc.reynolds_number, sc.dx"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "All *lbmpy* functions get their inputs in lattice coordinates. For geometry information this means, that all quantities have to be passed in cells. So physical quantities in meters have to be divided by dx first."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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VVVX15p6qv7VIOedd99rDhvdI+f5zIs7u9UhLlwLsY9rqkpKdscQEACiK8qE3RUTE7Etnz8g5j2zq8WbNmrW4qqrq9drt1v741bZs1qxZPaqqqvrXt8+MDAAAAApJ6NA2uUcGAAAAUBiCDAAAAKAwBBkAAABAYQgyAAAAgMIQZAAAAACF4aklwD7HI1d3rvb74zGsAAB73/z58zuce+65gxYuXFhd23bdddcd3qVLl63V1dX7P/vss+Xl5eVbt2zZki644ILV3/3ud5dHRIwaNWrwa6+9tl+nTp22vf322+mzn/3syuuvv/71hs9EQwQZAAAAFNL8a3pUbd34RrP9XlvW5eCawT98vUmPdL355puXXXbZZWs2bdqUKioqhl9xxRVvDBky5O2IiEmTJr108sknb1q5cmXZoEGDjv7c5z73RqdOnXLzVN92WFoCAABAITVniNHcx9u0aVO7iIjy8vJtO+5bv3592f7777+tffv2QozdIMgAAACAZvKVr3zliCFDhlT27dv3r84777zVvXv3rqndN3bs2AEVFRWVRx999PDrr7/+1fbtLZLYHYIMAAAAaKSU0k7bb7755mXz5s2bs3z58lnTpk0rf+KJJw6o7TNp0qSXFixYMOell156/gc/+MFhCxYs6LB3qm5dBBkAAADQSD179qxZt25dWd221atXl/Xo0aOmblvXrl23nXDCCRumTp3aZcdjHH744TXDhw/fNG3atAN23MeuCTIAAACgkbp27brt0EMPfefhhx8uj4hYuXJl2dNPP9311FNP3Vi33zvvvBMzZszoMnDgwC07HmPDhg3tqqurOw8ePPg9+9g1C3IAAADgfZg4ceLLn/3sZ/veeOONfSIibrzxxleHDRu2JWL7PTJuueWWXu+880468cQT148dO3Zt7fvGjh07oPbxq6NHj379pJNO2tRSn6HIBBkAAAAUUlmXg2ua+/Grjek3YsSIt37/+98v2LF98uTJixt6z3PPPTe/CaVRhyADAACAQhr8w9dntXQN7H3ukQEAAAAUhiADAAAAKAxBBgAAAFAYggwAAACgMAQZAAAAQGEIMgAAAKCRysrKRgwZMqSy9s/8+fM7TJs2rfOll17apzmO37t376OXL1/+nieM9u7d++iKiorKioqKyqOOOmrY+PHjD9+8eXNqjnPWuvvuu7t++ctfPiwi4q677uo2Y8aMTu/n/XfeeedBAwcOHNauXbsR06ZN69xQvwceeODA/v37D+/bt+/w2vO9Hx6/CgAAQCGdeN+JVeu2rGu232u7duxa8z+j/2enj3Tt2LHjtnnz5s2p2zZ48OC3Tz755E3NVUdDpk6duqBXr14169ata/fpT3+635gxY/pNmTJlcXMdf8yYMesiYl1ExEMPPdStpqZm3YgRI95q7Ps/8IEPbJ48efKiK664on9DfWpqauILX/hC38cff3zBgAED3qmqqhp64YUXrn0/5zEjAwAAgEJqzhCjKcd75JFHyj/ykY8MjIi49NJL+1x//fW9IiImT5584MiRIwdv3bo1Xn311fZ//dd/fdTw4cOHDh8+fOivfvWrAyIiVqxYUXbCCScMGjp0aOXFF1/cL+e8y/N17dp128SJE//8xBNPdFu5cmVZRMRXv/rVnsOHDx9aUVFR+YUvfOHwiIj58+d3GDBgwLDRo0f3Gzhw4LATTjhh0MaNG1NExM0333zoUUcdNayioqLy3HPPHRARMWHChIPHjh3b94knnjjg17/+dbevfOUrRwwZMqSyurq6Y2Vl5dDa87/wwgsdhw0bNnTHuo499ti3qqqqtuys9qeffvqAfv36bamsrHy7U6dO+YILLlj9wAMPdGvktzoiBBkAAADQaFu2bGlXu6zk9NNPP2rH/f/2b//2ykMPPdT9F7/4RfkXv/jFvhMnTlxcVlYWV111VZ/rrrtu5ezZs+c++OCDL1599dX9IyJuuummw4877riNc+fOnfPxj3987fLlyzs0po7u3btv692799vV1dWdpkyZcuCiRYs6Pf/883Pnzp07Z+bMmZ1/+ctfdomIWLJkSafx48e/tmjRouquXbtunTRp0kERERMmTDhs9uzZcxYsWDDnpz/96Z/rHvv0009/87TTTlt78803L5s3b96cYcOGbSkvL9/6zDPP7B8R8aMf/ajHxRdf/MbufP+WLl3aoXfv3m/Xbh9xxBFvv/LKK436zLUsLQEAAIBGqm9pSV3l5eXbbr311sVnnXXWkG984xtLhw0btiUi4ne/+92BCxcu3L+238aNG8vWrFnT7tlnny2fMmXKooiI0aNHr7vqqqu2NraW2tkbjz322IHTpk07sLKysjIiYtOmTe3mzZvXacCAAW/37t17y/HHH785IuKYY47ZtHjx4o4REYMHD958/vnnH/nxj3987ZgxY9bu6lyXXnrp6z/+8Y97jBo1aunDDz980B/+8Ie5ja2zvprrSintehpKHYIMYJ/znW6b3319w9r9d9Kzbar7/QEAYN8zc+bM/bt27Vrz6quv7lfblnOO6dOnz+3Spct7fmlv1+79L5ZYs2ZNu1dffbXD0Ucf/da9994b11577fIbbrjh9bp95s+f36FDhw7vnq+srCxv3ry5XUTEU089tfCXv/xl+UMPPdTtn//5nw9fuHDh7J2db9y4cWtuueWWw++7774NRx999KbDDjus0YFLXX379v2LGRjLli3rcPjhh7/zfo5haQkAAAA0kwULFnT44Q9/eNiMGTPmPPnkk11/85vfHBARceKJJ66/5ZZbDq3tV7tM40Mf+tCGO++88+CIiPvvv//A9evXl+3qHOvWrWt32WWX9Tv99NPXHnLIIVvPOuus9XfddVePdevWtYuIePnll/d75ZVXGpy4sHXr1njxxRc7fOxjH9vw7//+78s2bNhQtm7dur84b5cuXbauX7/+3cygc+fO+ZRTTll33XXX9b300ktff+9RG+eUU055c/HixZ3mzZvX4a233kpTpkzpfuGFF+5yRkhdggwAAABoBtu2bYtLL720/ze/+c2l/fv3f+fHP/7x4quvvrrfpk2b0m233bb0j3/84wG1j0/9wQ9+cEhExLe//e1Xf/e733WprKwc+vjjj3ft1avX2w0d/5RTTqkYNGjQsGOPPXZonz593v7P//zPP0dEXHDBBesvuuii1R/84AeHVFRUVJ5//vlHrV27tsFApKamJl188cVHVlRUVA4fPrzyqquuWtmjR4+/mGExZsyY1RMmTDhs6NChldXV1R0jIsaOHbu69nz1HXfSpEndevbs+VczZ8484Pzzzx904oknDoqIWLx48X6nnHLKwIiI/fbbL7773e8uOfPMMysGDRo07Lzzzls9cuTIRj+xJCIiNeaOqHva8B4p339OxNm9HmnpUoB9jKUl72VpCQBQFOVDb4qIiNmXzp6Rcx7Z1OPNmjVrcVVV1buzAVri8att2de+9rWe69atK/v+97//6p4+16xZs3pUVVX1r2+fe2QAAABQSEKHvef0008/6s9//nPHqVOnLmjpWgQZAAAAwE498cQTL7Z0DbXcIwMAAAAojCbPyEgplUXE9Ih4Jed8bkrpyIi4LyK6R8QfI+KSnHODNysB2Jna+0G4V4Z7YwAAQETzzMj4fETMrbN9S0R8L+c8KCLWRMTlzXAOAAAAgKYFGSmlIyLinIi4vbSdIuLUiHig1GViRJzXlHMAAAAA1GrqjIx/jYj/JyK2lbYPjoi1Oeea0vayiOjdxHMAxHe6bX73T1vSVj83AMC+KqU04oorrjiidvtrX/taz+uuu+7wnb1n1qxZHUeNGjV4yJAhlQMGDBj2qU99ql9ExCOPPFL+kY98ZGBExN133931y1/+8mF7tvrWYbfvkZFSOjciXss5z0gpfbi2uZ6uuYH3XxkRV0ZE9Dpgd6sAAACgrZo4cWLVli1bmu1pnB07dqwZN27cTh/p2qFDh/zoo48etHz58hW9evWq2VnfWtdcc03f8ePHr/z0pz+9NiLiueeee88N4MaMGbMuItbtVuFtTFNmZJwQER9PKS2O7Tf3PDW2z9DollKq/Yt0RES8Wt+bc8635ZxH5pxHdu/UhCoAAABok5ozxGjs8crKyvLYsWNXfetb3+q5474FCxZ0OO644yoqKioqjzvuuIqFCxd2iIh47bXX9uvXr9+7D8EYNWrUe6bbTpgw4eCxY8f2jYi48MIL+1988cV9R4wYMbh///7D77333q5N+2Sty24HGTnnL+Wcj8g594+I0RHxm5zzmIh4KiL+ptRtXEQ83OQqAQAAYB9xww03vDZlypTub7zxRlnd9quvvrrvxRdf/MaCBQvmfPKTn3zjM5/5TJ+IiGuuuWbl2WefXXHyyScP+sY3vnHo66+/Xlb/kf/X0qVLOz733HPzf/GLXyy89tpr+23atKm+FRBtUnM8tWRHN0bEdSmlRbH9nhl37IFzAAAAQIvo3r37tosuuuiNb3/724fWbf/Tn/50wJVXXrk6IuIzn/nM6hkzZnSJiPj85z//xgsvvFB9wQUXrJ42bVr5Bz/4wSGbN2/eaTBx4YUXri4rK4ujjz56S58+fbbMnDnTWoaSZgkycs5P55zPLb1+Kec8Kuc8MOd8Uc55S3OcA6BWW7j5ZVv4jAAARfalL31p5T333NPjzTffbNTv1f3793/n2muvfePJJ598sX379jF9+vT33Cejru0PBW14uy3bEzMyAAAAoFXr2bPn1o997GNr7rnnnh61bcccc8ybt99++0ERET/60Y+6jxw5cmNExAMPPHDgli1bUkTEkiVL2q9du7as7j0z6jNlypSDtm7dGtXV1R2XLl3asaqq6q09+XmKpFlvjAKwN9WdsXDD2p0G2oVgBgYAQLH8wz/8w4qJEyceUrt96623Lhk3blz/73//+4cdfPDBNZMmTVocEfHYY48deP311/ft2LHjtoiIb3zjG8v69u1b8/zzzzd47IEDB24ZNWrU4DfeeGO/f/3Xf/1z586d630iaFskyAAAAKCQOnbsWNPcj1/dVZ9Nmzb9qfZ1nz59ajZv3vzu9uDBg99+9tlnF+z4nttvv31ZRCzbsf3cc8/dcO65526IiBg/fvwbEfFG7b4TTzxx4x133LH0/X+K1k+QAQAAQCGNGzduVkvXwN4nyABahfqWZezLy00sIwEAoCGTJ09e3NI17Mvc7BMAAAAoDDMygFardtbDvjQzw0wMAABoGjMyAAAAgMIQZAAAAACFYWkJ0OrtajlHcy49sXQEAKBtmT9/fodzzz130MKFC6sb0/+uu+7qVllZ+daIESPe2p3zde7c+Zi6j4BtiwQZAAAAFNIdX5xW9dabNc32e22nA9rXXP7dk/foI10feuihbjU1Net2N8hAkAFgFgUAQEE1Z4jR2OP94z/+Y8+77767R0TEJZdcsuqTn/zk2pqamrjgggv6z549u/OAAQPe+q//+q/F5eXl2z772c/2fvzxx7uVlZXlD3/4w+svuuiiNb/+9a+7Pfvss+W33HJLr8mTJ7/42GOPlf/kJz855J133kn9+/ff8sADD7xcXl6+benSpe3/9m//tt+SJUs6RkT84Ac/+PPpp5/+Zt1avvrVr/Z88MEHu7/99tvpnHPOWfu9733v1eb8fuyr3CMDAAAAGuG3v/1t53vuuefgGTNmzJ0+ffrcSZMmHfL666+XLV68uNPVV1+9asGCBXPKy8u3fec73zlk5cqVZY8++uhBCxcurF6wYMGcb33rW8tPP/30N0877bS1N99887J58+bNGTZs2JYxY8asmT179tz58+fPGTx48OYJEyb0iIi4+uqr+5500kkb5s+fP6e6unrOscce+xczOKZMmXLgokWLOj3//PNz586dO2fmzJmdf/nLX3Zpme/M3iXIAAAAgEZ4+umnu5x99tlrDzzwwG1du3bdds4556x56qmnyg877LC3zzjjjDcjIi655JI3nnnmmS7du3ff2rFjx22jR4/uN3HixG5dunTZVt8xZ8yYsf+IESMGV1RUVE6ePPng6urqThERzzzzTPkNN9ywKiKiffv2cfDBB2+t+77HHnvswGnTph1YWVlZOWzYsMoXX3yx07x58zrt6e+iY2hEAAAM3ElEQVTBvsDSEgAAAGiEnHO97Sml92zvt99+MXPmzLk///nPD7zvvvsOuvXWWw999tlnF+z43iuvvPLIBx54YNFxxx23ecKECQdPnTq1vLG1XHvttctvuOGG13fnsxSZGRkAAADQCKeeeurGRx99tNuGDRvarV+/vt2jjz560Ec+8pENy5cv7/DrX//6gIiIe+65p/vxxx+/cd26de1Wr15d9slPfnLdf/zHfyydO3du54iILl26bF2/fv27v4tv2rSpXd++fd/ZsmVLuu+++7rXtp9wwgkbvvOd7xwSEVFTUxOrV6/+i9/fzzrrrPV33XVXj3Xr1rWLiHj55Zf3e+WVV9rEZAVBBgAAADTCiSeeuOniiy9+49hjjx06YsSIoZdccsmqHj16bB0wYMBbd95558EVFRWVa9asaX/99devWrt2bdmZZ545qKKiovKkk04afPPNNy+NiBgzZszqCRMmHDZ06NDK6urqjjfddNOro0aNGnrSSSdVDBo06N37YNx6661Lpk6dWl5RUVE5fPjwyj/+8Y/7163lggsuWH/RRRet/uAHPzikoqKi8vzzzz9q7dq1ZXv7e9ISUkNTY/am4T1Svv+ciLN7PdLSpQAAANBMyofeFBERsy+dPSPnPLKpx5s1a9biqqqqd5dSFPHxqzTOrFmzelRVVfWvb1+bmHYCAABA6yN0aJssLQEAAAAKQ5ABAAAAFIYgAwAAgKLYtm3btrTrbhRZaYy3NbRfkAEAAEBRzF61alVXYUbrtW3btrRq1aquETG7oT5u9gkAAEAh1NTU/N2KFStuX7FixfDwD/Ot1baImF1TU/N3DXUQZAAAAFAII0aMeC0iPt7SddCyJFgAAABAYQgyAAAAgMIQZAAAAACFIcgAAAAACkOQAQAAABSGIAMAAAAoDEEGAAAAUBiCDAAAAKAwBBkAAABAYQgyAAAAgMIQZAAAAACFIcgAAAAACkOQAQAAABSGIAMAAAAoDEEGAAAAUBiCDAAAAKAwdjvISCn1SSk9lVKam1KqTil9vtTePaX0REppYenrQc1XLgAAANCWNWVGRk1EfDHnPDQiPhQR16SUKiPipoh4Muc8KCKeLG0DAAAANNluBxk55+U55z+WXm+IiLkR0TsiPhERE0vdJkbEeU0tEgAAACCime6RkVLqHxHHRMTvI6Jnznl5xPawIyIObY5zAAAAADQ5yEgpdYmIyRFxbc55/ft435Uppekppemr32pqFQAAAEBb0KQgI6W0X2wPMe7OOU8pNa9MKfUq7e8VEa/V996c820555E555HdOzWlCgAAAKCtaMpTS1JE3BERc3PO/6fOrp9HxLjS63ER8fDulwcAAADwv9o34b0nRMQlEfFCSmlmqe3LEfHtiLg/pXR5RCyJiIuaViIAAADAdrsdZOSc/yciUgO7P7q7xwUAAABoSLM8tQQAAABgbxBkAAAAAIUhyAAAAAAKQ5ABAAAAFIYgAwAAACgMQQYAAABQGIIMAAAAoDAEGQAAAEBhCDIAAACAwhBkAAAAAIUhyAAAAAAKQ5ABAAAAFIYgAwAAACgMQQYAAABQGIIMAAAAoDAEGQAAAEBhCDIAAACAwhBkAAAAAIUhyAAAAAAKQ5ABAAAAFIYgAwAAACgMQQYAAABQGIIMAAAAoDAEGQAAAEBhCDIAAACAwhBkAAAAAIUhyAAAAAAKQ5ABAAAAFIYgAwAAACgMQQYAAABQGIIMAAAAoDAEGQAAAEBhCDIAAACAwhBkAAAAAIUhyAAAAAAKQ5ABAAAAFIYgAwAAACgMQQYAAABQGIIMAAAAoDAEGQAAAEBh7LEgI6V0ZkppfkppUUrppj11HgAAAKDt2CNBRkqpLCJ+GBFnRURlRHwqpVS5J84FAAAAtB17akbGqIhYlHN+Kef8dkTcFxGf2EPnAgAAANqI9nvouL0jYmmd7WUR8X811HnDAX3jf074h/hyvLKHygEAAGCv2/L3ERFxVVzVwoXQmuypGRmpnrb8Fx1SujKlND2lNH3jxo17qAwAAACgNUk55133er8HTem4iPjHnPNfl7a/FBGRc/5/6+s/cuTIPH369GavAwAAgJaXUpqRcx7Z0nXQOuypGRl/iIhBKaUjU0odImJ0RPx8D50LAAAAaCP2yD0ycs41KaXPRcTjEVEWEXfmnKv3xLkAAACAtmNP3ewzcs6PRsSje+r4AAAAQNuzp5aWAAAAADQ7QQYAAABQGIIMAAAAoDAEGQAAAEBhCDIAAACAwhBkAAAAAIUhyAAAAAAKQ5ABAAAAFIYgAwAAACiMlHNu6RoipbQqIt6MiNdbuhb2mh5hvNsKY912GOu2xXi3Hca67TDWbcveHu9+OedD9uL5aMX2iSAjIiKlND3nPLKl62DvMN5th7FuO4x122K82w5j3XYY67bFeFNklpYAAAAAhSHIAAAAAApjXwoybmvpAtirjHfbYazbDmPdthjvtsNYtx3Gum0x3hTWPnOPDAAAAIBd2ZdmZAAAAADs1D4RZKSUzkwpzU8pLUop3dTS9dC8UkqLU0ovpJRmppSml9q6p5SeSCktLH09qKXrZPeklO5MKb2WUppdp63e8U3bTShd68+nlI5tucp5vxoY639MKb1Sur5nppTOrrPvS6Wxnp9S+uuWqZrdkVLqk1J6KqU0N6VUnVL6fKndtd3K7GSsXdutUEqpU0rpuZTSrNJ4f6PUfmRK6fela/tnKaUOpfaOpe1Fpf39W7J+Gm8nY/3TlNLLda7tD5Ta/RynUFo8yEgplUXEDyPirIiojIhPpZQqW7Yq9oCP5Jw/UOcRTzdFxJM550ER8WRpm2L6aUScuUNbQ+N7VkQMKv25MiJu3Us10jx+Gu8d64iI75Wu7w/knB+NiCj9HB8dEcNK7/n30s97iqEmIr6Ycx4aER+KiGtKY+rabn0aGusI13ZrtCUiTs05V0XEByLizJTShyLiltg+3oMiYk1EXF7qf3lErMk5D4yI75X6UQwNjXVExA11ru2ZpTY/xymUFg8yImJURCzKOb+Uc347Iu6LiE+0cE3seZ+IiIml1xMj4rwWrIUmyDlPi4jVOzQ3NL6fiIhJebtnI6JbSqnX3qmUpmpgrBvyiYi4L+e8Jef8ckQsiu0/7ymAnPPynPMfS683RMTciOgdru1WZydj3RDXdoGVrtGNpc39Sn9yRJwaEQ+U2ne8tmuv+Qci4qMppbSXyqUJdjLWDfFznELZF4KM3hGxtM72stj5f0ApnhwRv0opzUgpXVlq65lzXh6x/X+iIuLQFquOPaGh8XW9t06fK01DvbPOMjFj3UqUppIfExG/D9d2q7bDWEe4tlullFJZSmlmRLwWEU9ExIsRsTbnXFPqUndM3x3v0v51EXHw3q2Y3bXjWOeca6/tb5au7e+llDqW2lzbFMq+EGTUl+p6lErrckLO+djYPmXtmpTSyS1dEC3G9d763BoRR8X2aavLI+K7pXZj3QqklLpExOSIuDbnvH5nXetpM94FUs9Yu7ZbqZzz1pzzByLiiNg+m2Zofd1KX413ge041iml4RHxpYgYEhEfjIjuEXFjqbuxplD2hSBjWUT0qbN9RES82kK1sAfknF8tfX0tIh6M7f/RXFk7Xa309bWWq5A9oKHxdb23MjnnlaX/UdoWET+O/51ibqwLLqW0X2z/xfbunPOUUrNruxWqb6xd261fznltRDwd2++N0i2l1L60q+6Yvjvepf1do/FLDNlH1BnrM0vLyXLOeUtE/CRc2xTUvhBk/CEiBpXultwhtt9A6uctXBPNJKV0QEqpvPZ1RJwREbNj+xiPK3UbFxEPt0yF7CENje/PI2Js6c7YH4qIdbXT1CmmHdbPnh/br++I7WM9unTH+yNj+83Dntvb9bF7Smvg74iIuTnn/1Nnl2u7lWlorF3brVNK6ZCUUrfS6/0j4rTYfl+UpyLib0rddry2a6/5v4mI3+Sc/St9ATQw1vPqhNEptt8Lpe617ec4hdF+1132rJxzTUrpcxHxeESURcSdOefqFi6L5tMzIh4s3ReqfUTck3N+LKX0h4i4P6V0eUQsiYiLWrBGmiCldG9EfDgieqSUlkXE1yPi21H/+D4aEWfH9pvDbYqIy/Z6wey2Bsb6w6VHt+WIWBwRV0VE5JyrU0r3R8Sc2P5UhGtyzltbom52ywkRcUlEvFBaXx0R8eVwbbdGDY31p1zbrVKviJhYetJMu4i4P+f8SEppTkTcl1K6OSL+FNvDrSh9vSultCi2z8QY3RJFs1saGuvfpJQOie1LSWZGxNWl/n6OUyhJqAoAAAAUxb6wtAQAAACgUQQZAAAAQGEIMgAAAIDCEGQAAAAAhSHIAAAAAApDkAEAAAAUhiADAAAAKAxBBgAAAFAY/z9UBO0Vest/YQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "domain_size_in_cells = (round(6*cm / sc.dx), round(2*cm / sc.dx))\n",
+    "domain_size_in_cells\n",
+    "\n",
+    "scenario1 = create_channel(domain_size_in_cells, u_max=scaling_result.lattice_velocity,\n",
+    "                           relaxation_rate=1.9, optimization={'openmp': 4})\n",
+    "\n",
+    "obstacle_midpoint = (round(2 * cm / sc.dx), \n",
+    "                     round(0.8*cm / sc.dx))\n",
+    "obstacle_radius = round(0.5 * cm / 2 / sc.dx)\n",
+    "add_sphere(scenario1.boundary_handling, obstacle_midpoint, obstacle_radius, NoSlip(\"obstacle\"))\n",
+    "plt.boundary_handling(scenario1.boundary_handling)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally we run the simulation and create a video of the velocity magnitude plot."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<video controls width=\"80%\">\n",
+       " <source 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gsxihahQVG8fTTxaiB5lFtv8WoQToH4/0zq9TrpELV19NPa2s6nyp1EPpEdQoqNoZQ1RA0G4J/00xqKFAFQXgn22+mJJEOAs0SSKMfRJL1EkhQVtOorTI6kI1OSvTkm7k5ChWrRJL/nUT6WJIQX///+wWCOGKYHxwMcH3Tb0zmCYI6666666666666+OED/4SC0OAAgxPpBLG/yUI9iTJESY4HIAAIBJ9g95B1cAShio6DGGG2eeL/uMD4QamWqnqOLCMf/+7l//CVwPQAAQBRkBPFB1MAtTg52DjZYblHqxcGSUChr/cA8HJHOKcuhxeL/fbwAWSgYFqzp0gooRvv/wD+vY+DainVTszqohA0GGAsYxGyGoxGgKyM6IgbFrOi3ItfKtNPzqr2opslR5ChkCP/22/Oo0xToJkiQ/t//jBSEyRP/t9vt06EkiQ45FkIC6UIGKz/bGkh8CgMUG9/tjSRPggYGWv2z8SSBdYVYCAGDqiSEC5UYKBZiSVGCgWYkkXBAMaYkhFHGCzEkqO6clfRJK+nJ9OS+UpJqCSSaghiSdGMSS5lxJLOjBQkk9KOMSSeg/zq9p11ZKnUeZDFGR1C5Ud0WrRUZU6e22dWDiiVC/wJ+JUd4aYwYlR1QdFFMaigpGgDoKB8227pp09Rj/XVDfffd3B0UbO9NPFqCkGiDco8ttn9dNNMWoFMOsBZjK/pnJAzDQGlc6jTUbVOoryhdf/0/W3//x/AgS9dVEkqjaOoXqXkST+f//sOCqa1VUMGRx3LCIYXumCWuuuuuuuuuuuuuuvhAA4eFhsKCajN3WF9D+BhgWGYA+MUjjTRWqBtY1EaWn+df5yEV50emR1X8SpuVZOSJ/okkXeJU3GMyEkqMUC8SSKYx0SSF6jGNKGkhcqCAGZdfGkIJPGDB0v7uJJUYDBZiSQvUYKGmJJUdjTEkI/rJCtRJPNZJsEkL3iSXeJJeghiSEe8SS434kkV0EDEkhQWQ2hjEkiHjfnIUOCMfRKuPlQklZTqF/DGNzkguhIAgBgsMWoTiqwSONNNP85IfCgMBQ0KFqHzICAYLOn28WrXMv22xahLdYH1GPTT8JkgrDQ//22/xJIX+P4kkPEY3EjjSQgJ1gLDBAA/p40kICHWBuCggAdvp41Qgh1gOhQzPz/pi1CCHWDcq9NPFqB8NRpUbf51EDg2uLUhHLtt+1JhSUjqUhl+H/2HBVPXjAV+/pglrrrrrrrrrrrrrrr+GAQ/Y8LTh+mctC66qGGB50yMYxiPyra2trOpCD1raIp19OoVr6dFHmPyJJ8iEkmvNEkKLuiSEjGNMaSJ8EAxp9fGkh8DLA0ONCtV8SSJPGMNwUSSJ4CAYLAxpCPkf7fnJDpQOxTEkuLpUNWI6u234khBc6TovlRyRR9EkiBwd8SSIc/EkiH0EMQSBYV1gLxihJLgvGKEEgWU6wbQxUIcKCH2C49cEgzJNP8QS7JieRuYkPgFEJDgkxRIRomI0UMrbb00xpIXDwwAGIgLTbbt0xpITiBGAgAAjGgAfXTiyQB6/MCqAoBjQAPbbtpl4tEAu5VgIBgs6a92xatDFDa6fi0QDWcgfUFP7eJJD4EY4xwxJIX+GKkSQi0sSSoLwQMSQpqo7EkhEWYDpQQMbhQVA6sG7TTTT85ChERmDT51CC6AX86lwyiIlBdonmnnL0VzMNPqmCmuuuuuuuuuuuuv//jw+FIABAACAJQAHCJFUJ7kHD3yAIDEpY+cGGC5xefBD2ugf4cJEAgA1OH0Xw5mqvMCt4JCB0J00dXJ/rq19AjZnYAXAiRy60/33g6YExEBPaqc3wLShwwAXECDldhw8qk/feABwh7DcepJ/oX1hmAOIhJRiNBWR+VSESra2tra2qTVI5Iw1aLVLJVtt+dFAryo9E7jUIGJC9l4mJC58MdGkguhIDGCz6+NJBMLFVAegwJECk6zd3DJIbAPf+/waDgZwEqa7btjSRJwDJ1z8/8aqYGbDtbbbb004/8/w5XXuhbL22+P+P6PXXvpOiZfx/7G19V72P5tE9OjFx51LjEWogeZft+EkUBiV0f+mnpp6Dxws4DFXR/6fT5I9tvTTGkIauZ229ONJNXgh7bemmNJBDjqC6Xtt+NJDgjF0Y+34kkOCPJUGSQK50f/9MF8e350QQ5mItRhkdXt9MWSHQKA1UdtvTTDJINl7/009NMRaIttvpiyQLpgRg4xlU229NP+vUR5A7dLqsSBxoaaZvOn//j4drVdYG5g9cHbg7dOD/l//GqnG516+v1BxkBi/N28H/LxaOEqFTA5NDCHTtu3/X/oFRDQMo00/xJCB0jGCh8aSLjFSn/EkqMUZCSEd4kmNwQMSQoh4/xJIgcG0R///gj3xZKxU4VoY2jhv8SSnkYoxCAhKDqgXjGKYQDgKaBW9fTBTXXXXXXXXXXXXXXXCzDgHWCZbL7KeHxIaGhUaf50dn8nVnU6Iz6JXU5Cv6ck9DKJyS0qckuVEKJSJkipQ9kM4Jp7fEMtOj4aZZEtfCuI+MOe987MNWze6aY0hjWIyI+34ZJBItB7//uD2Dr174B/P7zfqtX6m9QmCcCRCk5uXufuWwyQoAovQygR7nvt9udi/CsxhjgFl4On393exMWkPLGEMouF6hXxe7r3cvglM6rOeCUwOsBxQGAWT4Iv2AcXwd++wUWBJs/FxIseggIuHBHhR8c0cDQpDU55eKTQSMgQBB0mBAIEYPwWoGuCMEADXLB9zcCyyUBJl//9SOkKxW7u6AZG94ec+3sVhEAMoGCQIgFgx1JxUnVJwaZXuEtRaMCAJAHUDFgokPWKux1WdN3OdFoQFHhuO22/7YtRv0RqtNNPx//6DPmxfKjIWigO+UgeONqn+LUFhUSBy0Ipaafi1B1kSrPTt4tQLM6APyDGdNP22xpCgdxeHAYLDTTbtt40kLeHGNCqf4kk1R2NoaSO8mX9saSQi5/bbGqGMJjcdP7bYlELg/k6oHlGqjGDIrf41SWDw4H9Xp0xpIk+ggH+niSQnQRgtjBQ0kNgH4Gg9pr8XKAPeZgVUHI2DomKtsHG443FtMHPx//+I/qV9931V6wPhgGHJ098v/Ev+77v93ExOG23ppinBGd1A2one305nloklt5SaJNiJJzEk9TOGKbvEuEEdYCzLEkuPpmED+qYK6666666666666668PgH+w2HOusYAoFmSEkPnQklDpajbQdZEnU+PPucEQoNZkZKJHFNLFkqEOIqUszgp0EdinAhUhxAvBD7fjSQKUB1gbilXb/9f/Qd7u7O4MiQxTb9tpp8fOf+h3VJU11SGGgDKYH9GlzdNMMkIAfzGj+/+4iEhgK1P12LrhFPgZpRSbcuodWOb3jVV8lgUEKDgms49eQvn9z897hjrM/UJgPKvVU4VtQbmYzGoBVqpzn0Ag60ZR0QRR0AwXtEAwh+XogMJAGRaJmkgTV8gHGCAAEAYAAQCQ84EAARAAyki4L0/YA/tBB154WWYAAgDh+JwVAxYWwmggTO4eIBCbjxl+/5JiRWTTqh7kcJESDQWhlUozlYnWOgGiZIAZkibv7ZgaB4fry2v8WwgAXBcCAALAC2eIkhF3zC2wZdoHf5sX0RwBSxHtgktQqBayDQAAgFuHMgACAOvf//XQuocAPKM5HQq8PRCNvqLZ7h8eSvVCBAyRwcAdSqRjSoC+HGzUaBzAe0ADp658HYZf//1kyxdpbvEuXfVHZqBzkLFSPgxKX+OvRxPTund//+h5L+rTSqoygPuOP2k0///rORtevVdUPHTT9NP//6CGq11rUYw8P6adf//r6r6+sYwQD9NP//+ta1rWtaw2OB8NtvTFv//+ta11WutQUMD47bbZNT///obXVda1DYcHtemmmn/+GCoEhK47Kv//oFm/Eqp////QLL3irn+mNUJV0B8uae23jSTkYhjr+22JJghgvEkyoaUJU2NFooStQVB79PxpIdMtQQP+mJJcbjBQZUJIa+mn/4GUYCAtm+mn1UVFYz/Qc1pVWDEGA50bm83TFtNMaTAziA+AdbfTTWNJB0LmQeA/441jSQJnwFEJHK9fiyQTCxVQHwMFh0+3i1A77KI6aaafbGkgXcVAIBgs/t4vAsodYHyAUl2z+qaYkhRcd0SS0O6JJivRJJfeJJFGN+JJei6JlNkamFD9MFdddddddddddddf/D48KBSAA4EFJQ5Wxfj6kCRP++BjPpScJ8sHUUjn/QBghpJxbP5YyBMl/7/xfDuX8STUTlALg62JyXy1v8AoBcg5YS9T8p4oyg9Ah1Uc4wbqCLXLBdwGKAAIAB9gp5B1B/ABZKDBqc6beSSfvv4AcDFCrapz26f9A4KaUEQVzH9iOEQwxzEL9H//NHlxifnSomKRKVdvxThF6A2rt/NIGGSlRiS5lMSEHrKiSUtRJIIcdVQQxJIgH0diSQKUHWAsx2NJAkSQBvUAYEar+3/yj9D93Lj7u7itwMsIDDpttz/t64mv560sYZKcqwiwjiLly2lQphHMC6QqlJu8vbVLUlFRx7LJSNl0qbi8xCEKyEetQB315XpjOIEA84kCHTjKTOiA45kYpnADWGKQs6DB33Qqia+OkWID1muSQRMQMggh0CgBuUIAA0ChYkRLFgNmyKADHBywX4HsVsw0M9thefhzDVk39vGDMw2dNyYDor/u5uAbEUA42PDBj0B7gjpAAoRzCqJNdKWA4nGfUAcegKOupjSCuf/FAAD1wAAgQyAhGQjUc5MH/jGvKVzre5VXhhwgADQMCogYAA0DgVDbYGdVNwQQhJYeMQgm9Ar/vEU52IPj//0CsOngACYJ8QAAQFQAFQgAB8B0QAAZABQCZYcAAyACgEy/IAQcHyw4CDg2X+Povh0GgQQOAAcAAEB/WXAHwxUec48as4uer3gDDTORzLOzrv1AWSgcXVO1cJc/8EISkCEJSARM0n2oBwn+8f7UuT7wwHsS/Z/9QymYCEPi/lDJXKJXySwlTg1WvGMWFLYhaENXX3mD5eXhWkCtJqWmGYAAcABwGKJgNqqXCgdMBhYC2TgJ7iDZ/wE/kNnPbpLD84uJ+uuqxfqG3A5G3qb/X/9EOIL6qtV5EBmf1t/9f+hpF6r90Gde23///Uleq+9LQZa/t///XVfXetJ+BmP2zmbY1QO92RJ7f4VIUAW9mwFF/pfxpmY1QSgxUHQdA7bfk6Z1AO3qgaoPDjUY5Fj9PFqFlSIVf6YlTZRuLRQssaCQ00/+P+Podd33+pED5f04+FQ/xx+q9dRigYNftm6yKcB22joz9VUnMSWjRWCnGaV+v/Ff+QL993mQb0aogHBbB57ebu9vjjX/RidaWvDY4wY1QIagcQGEgMD4zc3brTFvDJIKkOJf0/8DOEB8APbTppm+NIQT6JGvTTzkgTLYKIYNFqPMhLTTp+dQMZjFU6OSEs6wEDBeJIUGomQIBgsxJK8bQkloqG0JJaKgXniQDs46QJtEYLKiWEzChs6mCmuuuuuuuuuuuuuu+Zh4GRshpQxQkh0srJiVLj2SbTkl7zkl9RJC3iSXTISSFBXoklqokm0SSFFBTIaSKDoGWL7dwyQoBMXEIHrXpp1/qgZDCfP3Lf/aXJl2Msibdwssm9wsPTh5IqIWQ4yVVynUhxgMJgQQAQKeDj+t3Fl0h7B2kVR0TQM6bGDx2h8aKDjwAw3IYlHbeEKv9FrQb1bk3IFgkidTynZGkcAw64mgALEQ4XSUSWHbIJpNriaA0uFAQQWEBQEcFF59WMl4BG7iAsDD2V4GFHxY6Wsbf/5mG6M139NUh9IRwagA8NM5HMsrOu8PUBZKBxdU6Vwhp/2Gn3AATRANShzOgXEkmbZg2BkI4PP4Ae3aiA8tdxB5vAJepB5a7kPNQPz6TFhv7hvdFn/+fP9fNQALjVXX161QEAH9VFoQAh7xVhB+vTTp///QYM7V9b6//8ga7Tu98iWvp9R4Q/0N96Pfdj9vid//4Kp0I4fVNOcPl8OWlpJda9UMtfd37HhkkMMumnp//b9vCag2vJ//9OjqEXoc/+P5O7vve/qij/J//+VD+/qq14Ho/ppk40hAWVLAhh0P+Tk4kk2DFcSSqadQzk4bOLyZxqH6eHDm/rgqEmg6l+nOoVtxkBnvr/9DTb+u/Jl7bdv+I/6HV60tcWw2O23+JJCgqNCgUMbIBTHQBAkCFNirt7bY1RnwPDg5aX08SSF6BHGdTfkR1BrMoolVFXJyQNZyAh0bKCZZVQJJlu38ROGHhQcW4bPAIm9PxJCAmHKqFNFMcEcRwYKb39ME9ddddddddddddddcLMNAeIKy1+tfiIEhgKH8Vvh+LVzJ22/EqJaPKsSr1OSejxJL9OQoh/RJIr9KQofKAklXRuoMkJ+7Z/4khDkRijRJCh/IVWH/8xY7vv70FV76f5Umc4mwhOHkTkM2JGFmzUpEgq6xtMlgS0EAIMhtU07P6DTcZAAUwvT4TT2GxDNoO/hPZy6Qo4APMwEhAheyKkTSLJAugq/4Sf7/MCyVDy9MN11///ZhwMWO/AARDKIVhiaOB/DKjbS+YTfZ/wTf4NJCS1DqiS8qv4kkT+fw+IiKCow0WvXo1+qm9Z1Eh/DznREq///Qd77/Mv7f//0fv376OZ0Rg/kWoZjr9vx/4/Hle9/VVQ7X22///3el31qqqonkOgel7cnB9xpCATTOiBDA4Uf8nB9xpISoKgPHBr9PxJJMBA0SSLQ7DdRahkyAhgZn9tts6jDLPEEgHYe1YZDaG4ypkZ/3FM4KmQ0r/dzEgpDQG40xagPUchkIy+3nRgK2VYdBs4kkQ5JkJJEPpYlRWLYIBiSRPyCAYtTflXpp51NhVz4LNEhV0REhl4rKhSgTW6ID43k/iSECdCrGiSUxjMvw/9hoZXoWCWT39MEtddddddddddddf//PhQKcABAGRAMq6JB+acto8N+hSAICnOcwPJyV/6HixBxbhxJAAE4T8wxddYhl5Nn02giBHttRgsp9vjIM5V/YAAQCuM9K//2jwGC3ruPZRwAIT9B/ABeQMMV+HjyiT997IHVrVYkKjI1PJnwJgnWeLWzluhi8fhh/CGHhYbob65ad3DBoNDwOfth9WV+0QVhNFfT/pp6adOmriV1OrvOSKN51CwrU6iH1Ek3I3aBMW2/zkKBZR1nTYGccgyALP+H4xjyvve+sNXFTv38YcVwGFSL91vVeC4BSCp03L045iP++1e1PbfVpai4fyKnKASLUJC1pwpkjPDUnZ5gqZ506Zkyib7oUFTpAGHHpPhNxsqLK/xmFDlYxRe6l/g/Xw7t6qsjDvGwZeUR5LUDKKT/4Nj0Tc/0AsoanHvCGHEdn/4InhBAEXShHam+36JaFaQKX7XzBPfhxnYIFZ7VNCccGLbCpHPxMN11/ybKz8gQDkMAB9YlMPWEuNctH/4FgAJhd4+HU4/iCejoCsTj4eduu9T/7zzHWY3WjMchgKHChiyBhGqgMu+w/wAvpugM1GXfY/wMvuZdsQjW3Fqtba1pZcfAxjDW//8//+X0EDZMvtVrTr7dr/+vJ1XX1Xr7/Npt/8f0P60detKu3ppi0Yb8x/p///Xd33ct63H2rUomXtt0/8f9Zc97WdVWuQPv6deGJQCFwr2jY1k2LKtLarQaP7RtqGSQiT06f+3/GKEp9OpOzjSRPlQdPpp6aYkkMKAIfEkIkCBnY0mMFAZ10+2NJghgYTL8/PxpIh/DWv7bZ0cEYY6AM9RuCEkOqDZytNNP43CKZgbX7v5iQWShIqGKEkl9TEh4Mg2htCmUaQ9GL/eLQkFp/IiJfbxkQCIt1DQZX2zf/j/yCPW+q1G9Ekjf7JSXG4bIyEG79tvFSgRU3EVCWv1mJDtFEEMUyANWyrAQ3r4kkPgFD0SSHv/oyUPD8Om9vxTCQUahdevpgnrrrrrrrrrrrrrrr4fwgAbGhYMCmdvu4zTuGDQ3v9Z/X7Rkjop8uTr8Tq9WiOF0Jf/0/0y/bbaM4lRXU6KPsiIyOSEs6Hi0UI7UZV6fi8NAjpA/biFmMRagTTMUcAgh5+tOvyZpEztgQcaqrmbx5A+BQXAwjad8Xz8/Pf2mM7e1YbI/rC58TSmUZ7bwQBQ1nak7nOV2S6d2JGdI7N8ywQABcBoDQoY4YKleVKgCC+xYHABhSpc/os5APMXCwZvz8TXwqJwBcfAU3IWFGpo8q/O1/954i5iC31EPKa9kxHYy1pBDN4lPL3lWZY4VUq3OQvCCFzKMtOIYkADTDEhnBwZ73zLIaYEAEA+goDAAFEOATTVkwcOezDPwGa7kLkGCfgOHwSiN8eBT+dTEfAiWMgE+5/xDAOHYIAAdoAAgNRFJuLYHYCk0HMRZthBd2BwATLA7wGt2B0M8vgwGDbaUAARJH/IgHHoIYALQyDkCLvtkGGzdoABGC5cXB3GDdLL4lxjFtSnJWlDmYqgwEAAQY2QYZbiAwVKBYIgTmCgBxrKDenAMNxon9oiI0uAi5BvToCIZkn2iIJJd3yl/+AviF4h14NWInTm//BhrqF/iZJCMqdyTAgojBgAEBLxbt7ef1NCt2/88iwFLB+BSjiAf/Xypbysi8qtA1iB6B6ZNTLuVGoUfowH6aeJUhGIwY0kYZRGVpp+ckaWNDJChCVW/7X/i6afjSQwyRen4kkGWyFMbQ0hEuZf2xpJeCGBnuntirGklsPHAwP2mng78HfjSR5QQMDAqn3P38SSG8XwWce4+H0OE11kzSwMDOApVtsVfi1BKVxIDDwH3bn+mTjcEJTqBtSpMvu9YokNKNkd9tvxLsx2WYkU3iSFD+RGKEkheyiMUJJNnKhJCCHsTrcjZRDTgID9U0zEgaxSFREiQLOqBJJv+JJX8SSDUkAxmQlwjNThwG/6/jj9V7pPzvG234tEBXxLLb/EkhRUy/4f+4p3e993d27hqCn9fTBLXXXXXXXXXXXXXXXwh8P2PChfCimNvlYfdwxwFEBBEH1ZWnVlbbZ41tCHOhJCC5OhFidXadFW5CaOcj/pp6aexa2iIGdXSI6vUSvp1NkSoRgV/WaJ0Zw7Q+Yf/RNh0m7p87/P/9MUNNKIQbf3dv7hR8gHDD+s/LWnrycu6aHHXOir+puteNSGOsnfH9cIAEJg8IAi6ciyXEBIAEuCUNYfpkfiNgDTBEDWdz/qslxQ6RzdTEaBEDIttBSpw4tuRMCo8jc+BAIAxYMDAAIkB8sRF+Iw4quj9LAXwKMylaQQIJGDkfpkD2H/X51Jb2IHu7fEH8omFarjdT4FYYCBCCxyT8ODetukULkdh+Ogtf9Uv/1+tudvpOK3gO5aHywMDyAcDFOdOdfi9aqpJotECIPTjIEPb/TC6g+I//08dJ1tttt+I//0G5s175Hfbt0///oFNfy4dc6Ilni0URxztttt4tQrUd52F8aSzkMd/22xJIHb9w3oZIUFRFF//6aYb8Fh7bfiyQB35MT1Aw7Is/FXpp3vfH/Q3NnrrgYZgc8rdvp///Q8SJ593dIuWBgfgOZtirOZKvImLcnDJIBN2kVa//pppgYXByffwa8lSdnEkMCErqC/RJIgenQ3D9AL4WT9/br8aSCYHCqiwX/2zkKC04QHjlmwK91lFSEYK5EgT///wVTMNJ/p5yRD3tXOpvxjEkmpzsaSHEeTL+2ZxzvzYM7I6wLwjPXM0Xdtvt8f/6Dm+lzpbb/OiBhkpkJUQ0G9FqFhU0F/2/vHxH7HGvzrv27g8UNhaxfqmCOuuuuuuuuuuuuv//6QoFOAAkQqoBQp2d6IFkXC/gCCk47pjGhtyhgv/3xi64Y8Vz7nirvY9eGDr8WTwBE4DkEVIZHeF3+/QAmFIslwpZy+XzWrP8EgQQ9bVCwnPUj4k/eLAwaqpP7TtVc+qRGBlbIcFE5V1le1B+1BIT9f+/hgAs1BwxOVNPJpP33/hAA+GAMeUQ/Koc9isMKlisV4Y4KGAPAl/rH8Vn9YLrWFrKiO0Rzra1tbW1tZVaOj0YoSpv+NRRJ5YIB/ppiSEC5X8STpY3AgUQA44YLA2DNz/N3fxswJQwGqQZHIhOf46u7jq5e3y8aSCEw6oDCwgOSA8/d/ydWcaQgLooQJBxELPO+34x4160C8TdqkuGgioO0iyywLWKssFv8ef+h1+58rrA4B6AYBnbx/0y7Nx27dYXUEIMML/9tvA/IDMZeX5Nt24//jrve/f3iIoKBx9rxaggUOoDIUYA++fWxagpGiGmMAfmMp86hBOtDQMYDFqHAHgWGCB2/zojmRULURIjpj9OmLUD9NwMyE6bbbb//xH6Dt70neBnQnVvTTp///Xv3e7u8uOBliDw+2fv6aeGSQBt2QrNf+mnpkMi6VZ/8aSKGNop/2xpJyEBBAw68n2wd+NJAmn0QsYGF3Tz8HfjVAutVgJwWdPbb5yQjmZGnUPDJEb3+Mf6BWXd6RaafnRB9kkQtWox9NPC8v/bb22+39ts6hP6Mp1eJkdSYdc6hWp0dHJIRMjIWiCOXP9s6kI5OirOS9pyXqdT5GnU+Ui//+w4TnXt4KDA6gXNBtWxdMENddddddddddddd94eEPhD2Gwo34YFM7cIJnMREgwAGgEvZrOxlXwWsXWsLWVZyGmWTrSJkzre1tVOt51X86KPKliVF+CBnJBdEhxxiSRT/Ekl4ujGJJBkaAFhjAf/VRXHHd6RdfuqgwC0YCjcdXN3fN2xpDBCQ64AMAIHKAPbunGqjSQzkG0B8B/TxJIp55yQXSQGqp0SVVq0LIcBZo6gKB3t+NJAxgpYaCmm234ZJAUVFU/+npwWN22/FkIEE6w6+234kkBRVVBfLGkghKqguv9saSEOrcyGq/bbGkl9Az/TxViixqhKMYHYUGGV/xqgWWEYCTAw5WX02xVttjSQ+UA64a7ye5+/nJBWNAkXRJIk4MUnJEP/EqLoyjqbI0WqsfTTzqbEdnUPmTjFHW9otrOTeybWdS4mTW0Zzq1SI6LinWlR1MQe///Yczsc/nXBRgcGDdWx7DZOcJh2uuuuuuuuuuuuuuvhD4Q9wkpWVNV9zAmczC0bO8aGGAAV4AN8qPg8TI1M1hYtraMbGs6Irzq+U6rFOrTyrEoodjzzkjyvEkiTSjVBUhRIaf+l+jVCSRJoNriSEE6XiSTVG50NJNYLMFA/7Y1QQlOqAyjBoO2b26awyoISg6r6f/gTBgcw1N+ni0QEYWVUAQI87baafUfx/ruXOq69njQUPLbfpp///QKp1fTT///oN6Xd42jL9tsWoKQaIEmMTb9tsWoKxogSZl9vFogGMNAPqIyp/i1CwqCcN19tvGqJHBuG69NtvGqpEN6fbxpCh8yEYay9PbbEki5Ux//5Fv3ffu7ggdEkIKZUVHJBWaERihqi6Cfp6aYklJkSsqFUWrt/TTOtickT8U5IfDI85IvcnUXedFE8e1nW1q7RGjoqTFq0ddTqv51V50UJmozwmo17/t7ff//9DiV7djn8PqYIARYC4OgoQdAoUQ+00w7XXXXXXXXXXXXXX/pgIwLFhbgAeAAIAnAC4E1UlnASgJ7/ACtggtHEoOpQEOMv0SarwAuAAIAuAC+EVXlnQTg/3+AcoAwPQW2g6gQSgYFqzp15RR++B/wh8A+xpDCZzQDJ6zwpjMBwADYAcDzKZiAAEA6DOFwJuBavFoCMr8Vm6C1UdBGWhBqNbW1tCEms63tVOowyctZ1V4tHAryoide23hNQM6k/TTTT009OhagV6oQ2f7bbeI//0OpV1rXQMz/tf//QcrWYj8gp/tti1DZlHQi023nMnM8WowyyNV/bOiEznTWdFLS0Wp8SL+mdQ6MsRDKOolxGUdQluhGUdEPkSILqF1l//b0i/TTFqJcpF9PFqF1l6mn+dRvyRHRAusmJ1PjTojtFooNdkx9NPOp8b/8fpbvu+/fzEWjjLQ38mk1razqI486jDJyE1Xp//x7REmqtbW1tbW1tbWPUmfp/9r//8VHpUtfRJemSZ7/A4AAgHACHpkKwnDSHg6BQgnCZVZBBsNUPojOaqTDuuuuuuuuuuuuuuu/D+wMABoEAYAAvAIDuQBLdJ1NEnQRvsrUBwGIuIhgcYjSuv/+G1tbW1tbX/x/ZAhwAENRC1VmvIYhbvb+AYi4iGBxqNK6g0OG2hra2t99r/+HYECUeAAhqIWqs15DEJd7QXoBiLiIYHGo0rz//hpE1tbW1tbW1/8dsKBBgAIaiFqrNeQxC3e30AxFxEMDjUaV1//2hzTW1tbW+//xsPoEg8ABDUQtVZryGIS72h9AMRcRDA41Gldf/8MiX2tra2tr/4/sgS4ACGohaqzXkMQt3t/AMRcRDA41GldQIlocUk1tb777//GHYYJR4ACGohaqzXkMQl3tD6AYi4iGBxqNK6//4ZEuOd99999//jthgkHqAAhqIWqs15DELd7fQDEXEQwONRpXX//In8P+CBDgAUYYJIllZRNViuY//Q1DNdddddddddddddf8ofDh8dAAbJm0JspVZl08SSucbF//97p+pfwmI1AACASsfgQDnbCENbn+pX+3VGekBacoJP/+6415B4+LN/3CiRIAMSFeNdyr/Bh1C9ddddf9TbwcMKBgACpuDtPDvpljSxaQV//3hDJKGaYbVV7XH2r6QIZRZiFMwNXv13oEwKShFaAbDsuUEwBiIRGArFUogPEbv9DgqNcTDSkrclB/WGOX+JL5Agc7wx6zOyCrRudgXQxhsJXjaXIwjG8Gv9OIGHLHztL7fYxDDuFb7777+Or6PuvYaAASB8orRX1PVRJWODvmQGDEbRJbYWogKeLiDTQh0zTqvYif33ohyNFKURut9B2NPAudxTRCtuWeIUmO0MECxs1CIl3Xvh4QfLjG0m8if/ABBIIwK4iSFDyMle9HkPjoPS+JPwsMP4ihlPNB2krf6khILyoRxp+Fhhz48v8PHw8AR+oBCx6Evxbf3eWK2MzTpO/e4Vvvvv/4fThQLQAEQDU4UkITaSqqcsMFsHgAJEoEMLSWip4uZo3DjIwMIvqXZOZMgVxdptJSgUpvb5gAgCERFLEfRU4ng2dg96cboZjcDDkM3ZBMevfVhX/7QEUVolpdDjz1oi9+Al6C9DLNVUNv688IL0xT4j5qJZILmkP/l4ZswzH5YMY5/5++JQ3LtBWkpb4dkJBeUhBZ/E3x/PfqG/XXXXX/Vi9H4UCwADEWYABgIJjWniH2COgEZQBTCqsER7DDfv+8CFTyEXE7BOlMfwTBhhDGrHBmmxP1J+4ZM0BBxGurcfX7///UkJR0ormnj9phhyhMdVy9/BhyrJIHMEL5JntWI+BhCJo8oeRq15jzWfFgMDZlJTsFeyboQGBr6dhsw7r/wINA2CGPLseuhNFUPCWNYrHU1j/9/+mFVagdHqNC/t/3/hpngCHCq1i8rzX/94fjGvKVzra5V/DDqFxQACN9999/2UnOeL9hiAA0N4UFBG6Wxo4ro74ANsQGihpPEtLEBX/uSCENMC+Jvuctoq9vmABACGRFNGIqschq4K3wnasmZIa+4GClO35BsflEV5V/++KAhI4TrVvVLv//D8zMZ4mF1dKdSPiUMp9oK8tbQw8w+pfwn0BHFeLcZS8SKWiEb8Ar0F7QRp7Kh9/ebCD9MYTkfNVcwIJTa6D/talBIKhSEGibJ98H9wzfffff1y6PqvYaABaJgAYGN1hzTDzdoCSagOYVIZPcMSZ9wAw2ZyKI/PIatzdAYt2vTxLPU6739/9BlGaQIW9l8pan+/ACwQy4NIEtwWQU0h/xYMEqq9aZVvbrEGCTmrA32F1bgQ5VwIZd4j/v0Wxv5ynF9YYfmFe1BYzeePyvbTTMCOBJ04nVV74P5h+/+Ez+EEUF2Qx5drUUorqh6ExWPOMStExP7+/zMxv+5Vcqu6hh1Ctdddf//ThQJQALFCKAFBD+YJElXifugCgZhGsSYJ11xVFRXxxnACBx1YFi59Z3/QepMoGFx1LsQBAE4FQwR3JauoUf/+8QNI5gAymLmgrq9PAxZk+b8e5xdO8/cCXwR6/xpIThKv/vBiMmi4Et1U5pJQn4IaD4ZyizFayWvcgwSctcAb4U0SzcyBqz/+//IbEPD4fl0WJkn7TYi4dF8WhT0Bh+a3gEcDbsnEyrPM3jdS+1X9UMPDD/8PBsD/XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXfXXXXXXfXXXXXXXffXXXXXXXXXXXXXXfXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXgAAALoQZo4F+AZvSDj+lf0r+lfzTZfL7h7oX+hxJM/E5InLFbQh/Sv7V5hBNQIKRX4EPUFOGxxC/kVJmzVk83mQp5OteL8XwMvUvJBi17zeI8Rw7qEcnhp/WaWEsaIX6+9Xm83l8q95/PwRagQfAg178nXuH/F16X1DQRRe4QEw1mmzL3mrovWvk6I3ivq319z0T2KJ569eGULOiKLUf+2XwINfVjiHx3issfQruP+I8Rx9fcEPgt7wsfgi3iUN1DmS5q9eTzLe8it5qyIQ1QIJ+CcvBD4JaxcEPhsvi16sQvViIiDMSi99E9xtEc4nx+TIi9UOrgn+E4UxNZb2i9N7s6L1yFQjpd6v8T4ny1H6xNZkI7yRGJQn3H5oRwrjrxaP3jojPG/6Gd9e+vjGKYg8qcJ/fYlX8vB1/wh+r/V5cei1LPuKr3PRehPo/S9e4vxdem6p0L/l8vlroIPNOJ4JPDXwihL8VV6c+if+veWuva59evSQquUIw18v/9dH6NhDXuTwmPrCPhHg4BD5ufWbsJYjS4bjF6+hXr03Wri/P5/0Xuq9ETa6168R4zx3hJCH7EK/YY4PhdT5IJ6v4QV/BBz72r+1e4KDVifH3khLEIvW/+vX+Hte58Rrnr3FaXNwSNGfhI/iai9ZKhGvVYrhevVNmxN4urSEvJS8EcMZL8tL69J3ACYmW9eiOdf8/ki/m+hnVCIhCe4kUrnE6jq/2+rpKdxlWoUTdmvPnYZhHPeeYcglqdaaN0VuSPonV0f1ZZIkT9f8IeFtavJJmhbIiPWWsvl8snjuiv9b/RL/W+omM4MKv9e3EzSS/KreVW8TWI8V4WQn+MRJFYxZ07N5OzQR+NhSvXBR8QhT3tejMsZnRWhzo/R/QpystbrMr79XicsFPhHLWvXrELW/fuJ37rUEXhH0I+Ed+SCbr54LuI54JMN4YxEEMmGInkDUAEbV3/f/b5fN5vEeWCrD3hHzebxHgj8I+bzeI8fAAADnkGaVAX4BP18kCl39/fyxHIg53yfJQ5bScvy/Kr/L0v6tC+qFvEWv5vQrr5Pkrk6RX7V5OW+XpZOTtXrk6kX/fe37GKv6FEvFEqHBxDr8rVenyZH9SdTf0tUb8Xoi71eh0VVyehPSery6E/Eq/wjCfNT+ZFtjCbxXMtS5KEdfVWvpOI+Ivnt8/4MSL3hmveCnrl69e9pe9G+bwVnWLgf+/F0XvmvuHRyP75q9el9G6Tm/ROqiP0XuBTVurvvhjp+DLjEd8/gWanTgJJLxuuJ+kTuB60buiF7i5ICfRX7+I6I8Ftexk86Q0KJifXr9Xr8QhCUYj2MYiO/AWTq/BkbwdE2sv8O7ozorvpUTu17xPwa/JR+kx/y5MEesI/Bn+CeEeaXl/QlzGI1ivRekWtyetS9IKPJ2i+NPauc2CPqpU2cvJ1hP8693d9q8nE8E/xNLw38T8tH7xOn/4/b/Q7oRoJq6xCC98Vvw38GNFrwr8XXt/q95sVfdYcJ4SZAgq/B+0bq7V6pelrAThfBP8V8V8d+0fr5e1zcC0T2i9XLWJyC2ENQkvglrAw7HQ3y8JtX/W/kq8KSP8T8T8qCH+CtX4BHBtFfgmI4bqDFHjHhj4YReq+VE72WoEdfHaN1X4p1xKP3xPxKvC5fu/QnqEL9L1XWTWcRE8VXN81eCIU5abvDIngZi/lqhXGLSLg2Bii956I1ccr44lUy8IeDEMY2JL8i74lEf4lWKtEfhXl6pvQ3vDVEy+CWF/5apLuJ4he3/wpaeJtnDRe76Fu/CwrgfOr45viEKeuasP/hJH7x7rieHVfhXrRH7V6te+f4nob8lH7xta3/Cj/v5rRfxK7v4n/mwSEVVV6wV+FUZjRYR9P5/aI/nCmX/+sHIIOAkhDwrvj0d626nQl+fZ/RP3Wy8LUj/hf499VXVdSclYe1yeBJDCFd83fi/yIvVjAtcPq/fRKv32rdq1Y78MU/6wSD87DMLCFkFLXP8Xes/U+G/S9oOZcJovqte5+vvpawgO4d76Xq709XAQ8vOhTwly5f+7QTcl+Wm+dE6Xlov/POuX0jdWJS9UGmi92t9MXHGu/XF5O78EFEv+iEWXBhReDBobmP0aq4r4ha6M7h347lk6V649G6Sv9Xqll57vuqSI5e4Z+EvVyJuW++5bgh+E/iPjO/v7gg+EviPkwx1/ECFnwSYb+SiI34j5viPlwXYc+EfiPm+I+CH4R+I+b4j4+AAAADfkGaYC/AML6DD1pS8kT6FN8snSO+MV2+T9X6iurqplaHX9QjySc0lSS0xKI98snJW/U36E/61/3yVE1cI9/xMNDiHX5JhLfr0noV36+uoiWq65LhPqE17r+f51z6/q4iugQ3f6ukfpRCuuJ67OwvBBm1m/oMer19iia++bqIviLrtf+GX8vg59aJe6hDx/wj8eviEXviL+uJXqrhocjv0T6J0tSVgzP2BbXYWozd/d+Lr3QL/xKE98Jgk7vmMXmpzeBJCi94IRXYCLCVY70BRoj9V+ie8M/P8/oHfr6/iPiEfscTf4WWv16CvlVvRfkV+iBHonoi6F+uuIRHNcd/Jl/+r9E6kv1hsWhLnhvXE1jqM/wt4I+uvoC/6v4N4VGI/KV4T/QMaEpUUv+bqxLYqhXd8t38tV9wj3oz+i1y1Vzdr1VIisdA/E2X//x/xvsDb6+te6E9fwl0hfX6K14R/1f+iNGdXeh3eC4ngkS9XPfL8Tr9XPWiftf/QgR1Xz/r1F/+16ue+P7h/uCPv7N8JuFMD2IoWgzSrjalTron1/6M3WiPJ6/iMJ/CebLvkp93XL4IvYYHYonwfBhGY3+v/iflRv1k3yr0z//R+hTteoYj6kvXo1/2vjtddYKxPYEsL+F/h11xaGP4Jgz+ivfoj+C8IeGfgx/CqO742rA2hf075ZMvwn+DD4bhTnr0VrvjeIvQ8EWtb4xGNnVgqJjEQS43xHxW/EG+MrmvCo6sKUV/DXz/ak7nw1xRL1/CYhb+643sEx9VVd71RmMIKJNL/6fBGgRkVd6wzVivV/CT7he+RE75PnirBu+76+uxRBfYCRUJe6rl+a7R++eqion0EH+SSuS/6p/o/vGpF6uL7Ap+whRf9iVWFaEN1CyvVv3ordureFvjtc28I/uvj87C8KiFjN0GPe6J369+vfo3dgUq9LquUlui5fqZRJy1l1jC9fX1zUBB/JLzwv8V6L17r68OquRYqwl8F1X1xMIL2EFGfVbb/hBQZ2Q6Y+mn+ORI58UsXX4pS3LJX4MDdV0Bho9dgJUd80nLDXwpQIPWjd333JxCv1clcn1xFDFvQpaqX5e54Y+K0WP9f+neCfXPLf33xMEHwyIX5sQtCFvv77vu+rievk7khn/CGHfrBZ1/Pgg9868CBhuuhEP4jhj5PiPlwYYN/k+I+Dz5PiPj4AAAA8VBmoAvwCgL5oVXxiBU5r/X+v4MuSI5flqp5OauT/v7+/5ZOXqXrQRrr+WHvQt5PRuvk8mTpCOvkn5e51fvV+9XvkV69HOktTWIXqXqWuVehvmmxGTEV67iO++SuSt0Tpqn6/iV759fonSVGVuhf/1Sqv1/JXfE52F4dxXtfE0FOk+rfpfkrqTmxRPzfoR1cT/2AofYQr3c3evqGL79Zdf694vWPXsyLF4L+v69e664mHeZC4/v9rL2I8SIpc3RPu/+vQp7qOrZFby0TuwJfsnx/wj8/4tDRdYtS/x4EAV4QJWYV4Mfg7oR3YGsv6y8XRO8N1roHPr6XzawV9/N83wlC91NzV6CLniaJ30v5Pqr7/nQhihCrwSl8OlVvlrl8f9iV6hxPt/HfJNke/k7AT4RR/dv3+CChUV73QHkM+DPDv67hFBU6XpoRzIXegh7VS2vfL1CK5da947S+/i9/y4Qq8+PfsqP7xObgU87DcLl//vdDut8+vT4rXVDEEDfgh8GL7Ml/4KF4e/KQmql9XukvBwIQl/BYENf3QI18tVKvjoE7+J/XvG17y5OBhzsNwp6MmSoO/0ZpvRLRFBnVaGMfq/pojyciv1avXL8vcE6sU/BtraqsEg1VVSoq4eoz+CT8q90CfVgUaJ3X1r1dr1YnIdh+HfQSeIuCC1+jPb7BOcEOjd8vBOfwj1/XP4NAr4Ismn4M/woveDui868qJ1VF1S9L1fWid2BVC/evd69Q2NimhQUsLY6ierB78MIl36wwEZNcFEnxFYYoj+Fn03T+q3ROrPRf/Kr1yK9V9hf4KslxPkDO1/4d+CGH+I/RXm5vk+TwYfDFCH8FYroDGI+JvNq4lGe+I8Pm8I7WI/kLWUKoI98qJ48Lb1qgz+Fl6sM4IvBHrX0i8drX2+4jrn5EK6ul76R+6AkikXvtfViQj4k9UcMK/R/U/TCPUT19cuxXhkES986CHZ2CeCD0HOr1by5PQjqFK8Ypcz2u4lFfX6vXoue6+uvXpbm6hGThKuTwiKRevl+Ph+x35/J+X0/O176X3i6tWCH+vVhiveBgEr3gSK31xsUuY1+iP4HsEHxgIbvvWKq/6veV/E9/feD78nyXxFilqomCJ+qK/syN18tc/3WEtL38EFX+LV/i7ptX6qufuVXk4tWPi6++0fvvGL77l5ob5ZOX9XivicV8KiJL+7vAjb5YM/viMQv19Yhequ77/uJ7+/v7+/vvgs+bE6+XBR1/PgQNfNgwwV/Lid/P8R8uDDBZ8R8/xHwY/EfP8R8fAAAA9hBmqAvwCqL5pV8VEL5Yb9BK8R6I8nJfJE3LOMQj1cnzfJ9TYMeu/7+WHtUNeRfonS1JfSFdfJr+TnlqeTkR2O4yIqJtdfzwQ2aj9+pU8lE95vqvr6Ru+l76Xv175r9fW/n+fuE6wKvf/UX9rVdr18iK99dyK/yV98IwRei+/6/kkuIq4ruI+bHEEe91981+i98+//Dmlz0rnYCb9+r9cq2vk+bqEtV69b67qLhjmm9Dc1eupO+vJ6+/yXVVJWGX4Z4onw/6BP60IqvBKd33fGlfgUa5Vlonfr70l68Fp/0I7w6Xw+XzV7XEa94bS94Zq8EdaHufrX0tr7l5fl9tDG7AWI/sCE0dl8t1CKNFv2ENcNfxHoR8laonfa+/Xq78MiUev0T3i/yL2KJ+KXvE16T0O6GsEuLs1BO/hD9fJ+hj+Dl+C6i3rtetfKi919dL6Xv0Tvlr1751i13fzyY06E+8KhPwn8EIT7A8h+sSHd/w0X/+TtC+r1qf+6rBi0EmKr8Negxrll0X7V6ti/AiG8GBuwVAsvv77Am5LhC9DugU64FWGN5c9D+/X89HgkEXu3iS9YKO77u3fpbn7AwhGuq5ETpcSf4vweC+gvvUEYuqq+Ok6b5bv6FrqeuX5UTvl67f6HdBM/wRBO9+7gh8ExuoxX6+wKL8NfHn878IvJ9/Df/LWCwM/Ir/o3+pK5vC4WQlsbzd7Dq1+iPjiQoq50Eav1+USvdcmdez0/4JuEJOdHevyfpAQMMxEQvfCDM7viiWlggclBH11h2va/8L/pFf4u81G7y+pF7r+W6gl8HAJ/heG14+hPRfZK1rk6Anddwl0BzHIQ/ghX5N2mnXfon6r8O0XroFdF7zC16jkrxtF18iv0vTEdgjoQ/a9/x/hA3R/Vw+X/wYUPevQrpqNV+iEu+awR/k6id1/ghCF+vda91orHmBFLY0b4a1iAj4SXk1hcNL3wSfPBFqCIlVnRE+rq0M+SBBHHfGTtt/CCJ79vWG/gsmLu/l7BECEEZX3Miq3/xmvRO8TV743xlDXkyUZy+HvCIIPFhihy/w7zxOEWrfr2vjewf/l+VcvFa7WvA4DfDUEvd3u98YiPXxQJbvu+RfQBDQIC31wTa9869fKv+onrlwaGQlzHIrNuoQRGLwyP+dCHxi3+fELXOiPD3P8/6E/v0bupbyawlrulyeuI69f9BVr+vX8l/ciK98slxC9BFy9yydS2Oq98n8XX3FyeiPiFHmSv67rmtn7vvrlgn+N+W7mrvuRLPwU/5sZ94Juv4gRwefL8R8uDDBt8vxHwd/L8R8fAAAANuQZrAL8AqYhaGIFV6wOOCP0GbxnJfNJyRPL93yIYx8nyL3UR1XzRHLdcElyXzL/5KXza/iOLV/nluleUcQr1+r/MvS1CKv6E7/hjmkf/6F/q1Xozuub5kO74jf69J69S/1/0AkfX1a3JF3XxCPF1ES1r+l+r+8NcyEvWq9P6N0R0jdMKJv/nxRPQY+BIr3YV9/d9/te698lY9eDH4N97r1cSiP4rDK/Q94xfrlJUQjd7r75OwLonvRO7+x3vW+vF0XvAlUXvpX8CDV/iOl8V8QpaAj+nQrvCOTBP8J/ZtdIMQ1yfJJegi51rX6lv1aS+bBmJ9LtUZu/slG7sSP7hH4leriPiETvkXtfyerUuIvwchP4vy16s+8K/Bb6At4Z9DXP1b5Y/qr/B57n8CRQ73yq18tbE3cy9XLXLXr79F9+i7dA9Da9094mvSC2EhH+hegr8Xt+6D9b/WuuOwjlwgW7ghQSfuscTi7hnwVfDnwk0V9Vfk/S/BDRO+17uHvterl8IfnmL/4LsLk/vX0E9Y71Swr/0Tr9c0RhHL3JXJz16Ef8JOqHgm8CYCJFY8EIf+P+XyUIY38t+r0v5OL8FwGuCbiPCOT6wiXwuXwu/HpXrjfBwGd+FPiO/uuFfC4QxsSm54LQVq3xvyyYRoV1CF+f4mvR+goxdX6Cu61esHRlfCGFB9zL9tviAlv4qn+r16N+uEPRF6sP/Qay//o7SCifCG+1SomCwE/wv4jBNyfJXmqvGLSrgpVYKfhEX4R9T/EVxHyIR3gpEeHdZHKMj9ojFfCOq4aw3kqZep6WCQiqovHPwSE1UqyXueuXk8CKGvdF95d6CvkSv44ljFL03VV0r+qvJhkML3YCJBgvfDEOv+sVWvtE6vXvcEfVfnYnd84xCCEc9+CQu75eei59dAy1YL0vi8XV+uuEvGKJ2I7iYe56zay79E8eET1hdovS0EF4MKP3gbhK1rhFJEr4pEIv4hX+EFc+M+ReqnV5LmkwTG6hiuM8FJviPipLnhznr0d//Pr16X5frtCO61Kn2vda/+J+1/ddct12X+S9D2rlnusQsO8vyy1OhDkn/fit/fKjP3avLX4J+KJ6lV5LXrgy+X6ubELAgfL8n+EP82Czr+fBVxCwXf4rJ8/z/EfLguwW/P8/xHwZfP8/xHx8AAAAOIQZrgL8Any+IQJmhgQtL4qJ8EY13/QactcstxC93J3XfQ4nXU14EH4FPVWiV8sE3JL0vVzfJ2C/PUTLolX96K986vf3Uer9cOZsVzfNt5JF75PrwZvw7tfXxEtROqn1fsB0+gEf6fr6lRnqsEJXf70/BONRey/P+veCP0D/14xE1VcODkNX8Zzo3UOJX0vIhHfr7FE6/+aQYiiHL+gjWDsIL1evVyo3f1oR1CyK8lgd91wR+hbT/JnoR72l94+veFxK94+vvC/xvwIII0cya4ZwR93y8CL+GFf4pe+Zer17sBS65viL5KsTRn8EfX/xS9D/oax+vTPCxZaub+XBCdG7wiPXvEn9n9n8TrgsRovhhYvK/0TvVe+16++wEXR+qgO4IetEroV6J6+u8E9F7eFeYILWCZdf3Lt1WhPug7X0mEfy1y65fVevX3+pU+NmpevrR4vG6f/XDG9ehvaW9YuuOte+uW/QU79eVFoNF7m6kQn+11X9aonS8niHXG3ovgwAwwzugi8vokeIwjBIS938L0RysJ1f/Xz99VSI93DK93E9xPxqseBKDPhwI3w0hLPBtVKvGq9do34vgcYJl/8I96OztCO6xRDL7dV6+Jfd+ExsgxVfwNAZ+VFeq+g+FqHEu7wchLwQ0VyuL6Gk+X7QrpNm+SCniPNlr8CM0JcccFgQ3vSLhk3zdRO+LE62IqgThasPiPPRH9CZNtX/V7oFNXvtf1cC7Cr/QnonCYSr1f0pvBDqq15xFUQng665wZm8Eozw66wpQpiq5Kn8Lrx+8R8QXoFPrR3/RZ/ZUR/iehnrRO6ietXrDg+uCeHhqCIVOhUYrS/Qzvyk1Vrwh80lV9go1cRJdyc3j6N+qCPwv8Im+LQnvhe8R9u+I6fpfDz8R8ZReoW/vBmEIeXPq8uoIiaq2/0T2X/6/UqybRaGIzvQ4kd8nSXxevBz14FQV3ycvy1xnoIY6Ps7pU686v8yvpefxpN+0rnQEH1W/8QvUfDumvS90sEZ78ELky0aL0kXVdrXgYhK9+Czd3d9374xECiysYxELhlGuFJbrn4RpL/cIdAR119fWjv1J1FXXVcOVPebXc/L9r1+jVVguqVctdVE3cyvBfm381hjP2r+nOMRwvZPiCe+rWUYrV8QT8urfglwQZfiu4TX+v4KvrPifmwTdfz4KP8HXz/EfBz8/xHwc/P8R8fAAAA5NBmwAvwCgiFh3AbPwHz1/D7+ZBLvpXv1/LySclVN+hjydotfLQhfl+WSgMf5OohEf5JcBA/+gIHuI8BSYef6CLTWKyF//Q56uI+q7Xp+Ve+WxSlx1dbr0r5v5LHL/Bb9cnyL/X698R83YIdX3y+Bl9gNX39/y3yeCevdA/ovfIr1f3LBd0jPJ69Qonf/Qb9FE9gQQrQohfDWsPawZ/nRGp8mvfVWBfJ3J3+C71E3xMFL/R+uoS8JrxfwnlwI1F7Gyj/hFNWRV6JXj/nr3g3r3YCJKvRGCj3wQ+j1E1EVX8usHPRomWwKYlfePE+J+P/aN70eT5vRO6BTr0J7y0Tv16sI7r69r6GdBN4Jxu7vvl9I3VWiNJVo/V3Xr77Xq5V74le8JVeRfE6/ROqtevLQ3vG6xVG6V/gkFLX0KcsR6DOUX94KXdX5KCHiTlri/tf4oleBEr/v7hJHesn4voVQrr5UfvVflYuveVr7xvoCD8f3/CXERnoW0QX/wR0RtYRgr/YIyO7u0t0jP+v+pccvjuMVpKnQKg6r9BP8ENZ2hL9QYYuW/hB1USjfvT9NE73Xr5a00XvBwBlhT0JqJ3XonhpmWvhmiseJ10hD65oisokEN3v3n12vV6v6H+DoM1fQon4IFbwThxHZ4XDC5/hOvRnl1X2MVgyLP177qoCjgmfhANdcgxHXJ151fwwI1wriu77vyhCs3zVf4W6vv8gvoCCEOoj4/4j4JVfL4c/VYIQmvVr0E/hD1/Eo3fL8T+j91AhQTLqCtF+rk6iPAvfpCH8FPwQ7w5upOlpfN0CHJjqviybeI+yo7+h8vL8avddVw72i/iuphyCV7r+leWhFD79fX8TXDy/vdEfoD37BfWpMJcWym7PHfOFIIdaW84Iari9ClrwRCNV5loI1c90Zy+WvpfEq2MVA3+VXxxCjvrn2CTu714Iyu7vSrmMr+319hksmI1hCjv8Jd94dq/jfYGP26v4R1zwlyT8suKq1Zqv5tdoVlS+dCYq20Tugr6q8EVH7wOQlT3gaDrfXF6Nf4QRHy+BJwh69jFLzf5vrrXqv7755MGxJaWCXEZeXu6w5v5KtX+Jq427vS/il+dUq+qVFFIswxaVApvqwQa0q9Gef7p5eJim18EtgkyfN/cR8QhjyiFoQuIWS/vgz+b7GI9/CGIX8+Cb1z4MME/+Ky/R0CeL+I+XBhgu+N+I+DP434j4+AAAAOVQZsgL8Aq4hcQvgKH4CV2IWHfQS79XmL9fojydL1ciJ18l9In465K5Pk+T5FfvV+9Xm5e4mHa0PaXkRLzcndIU8txFXJKIV4xblCFk9X+Rer0V6v/Xrwf6oDSviYK6iP16ubX9YRyVCKJ3X8Tr/wI/wOehS9a9XJ9I7nYKPgvyDFt1/HwU8izFDET2OJ91CFevdw9l//XvH7r1xP4Jci4n7AU/uWtpe7ZOwnpc3v9e8GP9FqxLDMEq/kGIMKmXA41c3xP4n4b+FfyeLycIor+Btr2X/warwqEPJX1W1399UD2hHdUvT8TD3SCLfq5P6uFxCHOVydSXjT+y+PH+35fhHr9e1+vY4k1W+El+Vhqvb/q37+x1e7l+VCXPjYL+q9BTv0Xu9Sp4Fz5Py12j94lr3la94v8qxfL8Tr/GKj/1Faq4r7Rm+/EO+WI8hFrDnoNxROXJ8m3J6DHj5aqGe4dRXxRPhY/zfEdfXXLXa9XoS3xPi/z12vVwMsMDovf9WjvBQMvd3e3gxq50CMsR2jfql6vwgb9CXkxX2CGT0bpuWs/f6N0Ez8TINvf7O99L9c1YIxNZS36Gf68YrT+CT4Uo6VE68EZlf4EC6fow5f9avNtonfL4NgSwzoT3aF9Jnq9dT+iPeBuJ6dYwnhwgJ7u73v7wiFAQme9j5NV/QoiK/idejPXJ8R7GIvfPeI/IivVaJ+I4K4UXEcZ6E9NtKz5uwRjPGaXPN48UhT+GVq5EyXffq/cTXq/R6/+l74jw3+kXv16s3xWuFd1/3fL5Pm9g5BXDvFo9V3b6wRE1WaXENX+WUUt49oU/USv6oR6rq6w2K/Qvvtfnx/YFH5snCi926seM1pyF//+BQh30XvhdZVp+tboV8kvRnJbr7V5OVFyrBeEEXLfMOu9/kvLXxVz+Si/k5JNhhe+Irjl6udDuh3tBN5fQzu51y+0U6Ipfr8ERdV94ZaJ0nSL3eux4KPgWq9rj4jCCiGlbf8YjEI5KuCcKIjlck1S9dVFdfX4NhCGsdQp1/LIIWuJQzoV9HeudWk5Z9OT/v9E75ZuWreuWqnV/1f9XoUrTvvur1f9f9T/LDnLfLeqF9Xr/zfaRHk+SgYHXKS/u677i+/rrbRn+XGKcixXF9/fV3iFoQrUYhL0q8QhTwS47N8X3JUv3JgeMGn1iMv0IWvmwVdfz4LOI4Lv8Rm+X4j5/g0+X4j5/g0+X4j5/j4AAAP7QZtAL8AoS+IpfEa/hxfFwVDkHrHgw/Ez8uuX7nvll5Pk+SrjPBrm5YJfQnpriPk+SrBT70I6uebAwvf9er16vd6K/Xr+Spf/lglyb0qupOSrCfwrXvrvV74nf94EXf/r/5Fe+bwY8UTXKrwVjl+vlX311CXX19fh3v6rnxRPgX/QIfYFH2I9693ondyq3fXJ9L3gnPWCPr+hCvX8EPob6SgrRPfEr7sCiZfSeub4hTp81ehHugU5VxcO+BbDIIxu75jzBDqM7iu3RK7Yjtpe7Rq5ugLI9G7rX30pUZEw31/rw0CSGLqXnr0P6a9XFXhiCS7/64hBD580mHR/gpCfx8vF/CiL3x3X39/dI3dp9/QPn11QR1YHMWi933QEPXBZBOusXRozklzVGjXNVzWMQoV3rr9FvXdaKr12j97fi+/de+16xiu/zq/gIYy9+idJXWJaEu8I+9e7+9X717v2/oIdCXFoNtjFvXq8nr369VD6vFjEEB9kxl+STtEcuwK9Fi9VevXxJyy4FIfLjq9VSrF1a9XLXJ5Mj/BEKWvuuFx0N7xvmGXvwRwRVXc8Jy3v4b+Ff/c6vjkRnkFDVfy9Sr++VXugWAjrF6w0GMbFh332u4b+N+bXfVA7LO/gX4JsJBL4RkpivyGVdZxYI7vtXL5z/fkq/g4Dqt4jv9X7Db2vGVhsm/D4MvBqDH0X5/kr1/9onfE4xffr3hXT+BXhvF5OafhjoRq4QR3kyLwTQT73vd3iwgCG9/viPGClfwxuh/sN0Z+9Xlwn8tCf/L89cTfP1CPUT1e/4Y9F6u17xe8XVojFQRVVVesUukZEfwKVW38QQmq8CeI8Mq8dV5K0R+x9f+CIR83jxPhcL+N6/r0d/Cq8M0XqoX6+vrRnvDHO8KjEJuS869J6EpQa9JDMQNYIqERXWiR8cv+IWTnVy8Tq+s9DfVYFcJfE0Lel8bXsUT4R4hUuDL0vgi9Bf1or4slexT53zsJwtzoMdF+CHVfvdEjeeCPqsX6lTGIgN2RkVHwFc8Qpcr561N3fn+BPDCLY6AUYOr7Xr9eqg6utC8ulocprbrvE8dJ14N9Ovhr1eSx1FlO+qvtCu6C9FyrS8IMEJ1XzH614GoWib6wYBMDeElY1xf4LwwhFXWveEK/617qXq+v9F/13f0BK9gIsMI/KtQt1XyS4NsKCli+eI9DukoETQnpL/tG74lYviYm9FY71e69V6K+IX5scjK8vq8OvWVDeuhIlen+ItH+W+JqtDGJ7Bx7l71er1eCXCWb1/JfV3MMQ6/38T8TiF+JmwXP7m7gu/xX+I+bBB1/Xz1zYNsFR4La+f5/iPlwWYLfn+f4j4Mvn+f4j4+AAAAPJQZtgL8Ap/oFDSr5pa1fr18ZN7H7uC7kiO1r5USpOT5PkXuoj5O4SRX+JloD36/nhTkhhfJ+id80R62+JRX+VXt/o2VafVI/dc1d8TBYX//5KsH/4hX+TwvpdTq9P+ude7AZPte++kTvk7hbv7lR+6As6rWsQiFy0v+Jgs6k6XsUT4Z3y/P4Kd8nevd8m1fEdAw9e14mCP0LvFclZfgj9geQj3P2I0/Df9GFefH4lCz4sMiOgK4xCO6XpV91r3g59gKEtL4xGbwz8Eote+TrXuvxmH/Q/8+f3q4+iVJcRVgIU6I3z+nWIr3l+eiOeVq3hv7P8R8Yvyu65fie/vX3f3aEplufuXv8Nfib4ELrhP1yn9F6LxGxiC2/evdd9oT1+rfL2BNH+br7xRKfnRGLXLG/LXKidV/cqE94Gj3NXF+Or3jlRvh/7BcKkX/b38JcyCbxXo7RgxBIP5EqJjPWr1y+cv6J1+i/rYn50V/tX8CII8HQ7uHvQlX+eSgY17r+IX0p2MQ98LioZj8M0Mc/Ld3fhX2BBm6r7q675qCYRXuqX/ggH+CIM/L8tYNqExKqXhms2/QrqGLi3/foveDADHBN5Cu/4R6hHw1vtkVddgjve54l16v8qv8vxPQEAEPWr9y1hXjFv4MxyL3jUv656oSI6E6f8nE/BXDXEx2hCvYxRd/krDXWGQyHQp8ReFIIqrufHIjyl//+EF7whV6wxvGhHod6H1fsGOCP0Nfz59QVErVa1qteNN0FbEbvqviFf5AQ9VfEKUlwQiK5wQkd9jxHxn6XvE1/J690BdGdXEVo79Ct6r3qv4I/BDqvsv++uyXlRH65RyEarA1Cer+RH76V/1/4uvVpdL0M1QL9WBPob0mghrXVOtavXa9RyfBDh64tWkfKShHwvF1qqqqk7Qju/v71+dSqdfy3zUvn8DKGPA4ggR8x4GcECnT4j4tcqX/S/Fq/QVfgsWT0v/Qvt4e6ufPrnTr0RyQcSXO8F45Xo7C8EOb9/giDCr+8F51i619+iNJhaj94cr3QE7rA1ZV7XCMmMRBnxk3wtMiOfr3er1USv/k8n4hXun+K7+/v+IQlr4joCS+oqHOWep5PRu+VWPtG6Qn3X0t3or/Egiu/fX6sawbdWMn9yz3G7rn+eW4nq1frgo9HeL6u17qtUR6v7u+XVXq/gegnPssXfXq8E3ydozd392IX4iu5BC/J8nyIY/0r13rjfu4MPvFf5hCE182I/z4U7/nwXYJvrFaEwT383z/EfLguwT/P83z/EfBZ8/zfP8R8fAAADWkGbgC/AKMviKELCIhfARtAoaDa5O+i//Pdxfy1yzciGv1Fdx3ydRHyVYBAd8SiPBN6E9JcnyIQ8lc1/fq+el8XiFk1RXinxPBTdSbS91IvfNfNfPfdYPfxKJ19fJVRiPF1y6EwV3WOX79fdBOvV6J7w3xRPh/4f3xa98T4Jd4T/E9AcfUvX7NezfEeH9V/r+C2tH9+vvC+Wgf1ir0JzHgW0uY6Ay0bLwSjPDIjwUjlcl6RO8SZXOgIMEV3+9DkR/BSJrD/wb/hKHfQRtPia91qw+Qm7r0KeuIUqyTBGJQmLxPxOsTtf/EfCFl//pfy4Lx/wr0Df+hXdA9/E0/4KOqwX+gKPsCH/X33XKvfr77rTt9SK/Vyebqvlsvv/Jr5tv4JvCGCiprvV/18fa+K9e+XqEep+tf9fVK/z1g4+MoT/wJQY8KfCVG74nX/yonXyo70v6f+/CPOw3C3oJdH4VmM76wQ0Tqr+f567r0T9jlv8IK9c/ggDKFsSC3aY8FHw9vlQh/lrkXv179e+KXqfwewTLX/8IUJfw97/jPN6BuNMTd+Vgh6rF9oj/avYgnwIQR8GwZ8KG6dF/1Mv64zwTjsbORTneDEbLyoR3hLuufGL756wbBGHLF4rjvHSnWvj/UV13YZ+Hqvv4YBTd3d3d73b47zG8IfhGStCOvCPz0fvG64SvNgj4R+GZPVPK8dyHVf0iPJhyQ1VWMV31gxHT+HRCvJhHLhEMfr3hciL3YGNd1i392BT53riUV/nh3nnL/+j2qoqJ9BJ6rX8g5Usq26XxPyW9esJkr0fryfNvBgEJsyhwYt8QtdoXv2K2/dG6vRu7H1iv6upEnxeIRnr4vwU1esBIgkRzprCP8D+DC/Xp9KUWzpvvH+uaCH171ROvTXsnpf/rSBKLWvte/VryafYJKPLXF61q4RgoxCI9YFuAxqM58NRFS9fX31ehLnU1DFfvBn1/BD2ivN6Geu51Yr16t0Xute6XrRHl7X/uv/1/2BFyXGx16v8sEOqO96r4k7q5ftXruXAQwX8BIBlEfwOAZvlBFd9jvpfEq+KVd5uq6uW+WtXgpv7vweF8GxfuIELfJB38ohfDOX6wx1/Pgm/z4MMFfxfyfEfLg0wWfF/J8R8GPxfyfEfHwAABANBm6AvwChr4iRfNMvi9fcHgpBxonJPyRdRXV9fySV/Eq/cIwV+rfJJYJ/ffr11E9fy2MXF8y9VUr9xHfJy/LBd1fIpU6+tYr9eq4u+VX6hPwKLxC9An1Wvda99L313DHzK91w56F9N6+i+vk+RDO+Re6Cvw38L/H0XsUQibwQ/BrXvAgm+Ivlrpe/XvkXvdetf669XXBP6O/hur6+Edfq5f+DsX2Bb9cgonwuXFE9MMo+WMUd8x4KwwvS2Aj6J3ereBJdciJ3gnFr3YCXH+Cc+vLXtf65OGOKRam9Cfz+iVeCcIAiI7u7mEEZJj+3iF+T5FipfP4r4pXj694nr/5PZkWOXpIR0nKveEtbEIfd0B/D/6Fe7+zV68nL/8G0JcnyRXoItFeYJbuuSu6f/Tr1dr70J8K/G/174n5/H16TC3x2TJt68vBQjd4QwoIQX6ilbJ6r7694V+LrVYutR3SCTyYRL8smEhPxMnor6qoX71/4KvcNav75a9Zq5ZMvDbEC/1r9atlhRVrOwSwjcXWG8uSgl3y169FeEybvd3rwECGwSm3fd28E8Ed328EJZbrwhRHr1eTH6wwE0L7sPBdF/1OidWGqxYuXv4JqM/xKvXo3j9fV698t+i94KgIedhuE/n5cUTE+QNXvqGEJl4eQIbvsdYI+qv47QxCC2/h9q9cv5Sbuq1eTBIEfCnwpkwRiPB/8SH62+h/oI0XqoK1frRO+WvX3wUwp8Rz9RcVuhL+MEfJeXeKQKrvd3d7398NSYQ/o36sF9e7CIW+I8L17y6zZOde+dF6qVfHWid+vfr3w/CnxFdU0h7V4JCVq83HgiqunXCqRGPlvDi+KRnNfKr+G8lCfjNVE+K9Qh4dyYjjme2d3fCPyqx19gl1X4U7wnwTinve/UKfEeh/aWXRYr1QjpvJqvboz9yIj1XVxHVfS91r18lV16P3xCKdKsCfug76qQYqT9gx9aK3yq8h3hT5hSzZFXghIurfonr1Rvlct1J0BEr3QG74GjWBT+H694KSLl5+vAwhrwP4MEfvC34he+WqBLXvuqXrQv/hDJQQAh+EVWfCvLEVaJ0na/+Jv0I9WCEpBJL1Rf/0Ib6Re+RfdAp9Bn2C2veBB+CCveB8qRMYorMvwJIY8DWGLt0Z/lute7tX+eS/ubGEG3xCw18bovSc39aGdd69K/ub1f9Xq5avmEEPDXavWGn+ry0GN4qiuXmr3py99AiP1+d93V8mBsCfgbAnr9Cn+f7+1f9X6llrV4e+KL/fq54IMT9d/P993L994hfu7Bo+/q/v77v7vqGfkwphH5hC38uCjr+fBdxHPgowr8Knh+J+f4j5cGGFvhb4j5/iPhv4W+I+f4j4+AAAADwkGbwC/AKgIQKniEWJEL4HXMvi4KuSqkm5ZOW+eXkQnvk+TqKloDzgr9erStfIr/S9P9fXPJ8lx3dyXCKv8SvQtzR+TN69VTda9XNXJ2CvIMRws+v8/YDzJ2CL30IW+T9XkrreFvXoTX83Jeydgt9dUD7XCK98/evdxS92IEL3b9/g7Ey8nYHP8R83za/BIZ73IKsEdHzF83l+F/hejdef4b0//jUJz+BbSPl5A8jN39jvYSqnXmpc+sTrgrFojvm+KWLoCiLWLq+r6/iIWuqEE4pZfQu0TWE77u++T5JH3ojdgUTq3d9mLJh/r/VQWRKN3lr3Wid3EL3eve1Jj6Eueeit0FX4IN1oR3X8PQnULLFdaL03oWO6sViaDlBDt9fVVgn+G/0iZVc/doreJ/P+vfE/E6/rlxyo6xitXOpupOpPl1XCSM3yr6XJR5XwdIR3QQwl0gq1+r3uveL/r0IPrqgU/mQ7tvPEq/dr0lA93cFPgRAr3orqw3rDk3VeFPWU2q+fza00J6t173XsW682LYozHoJ8NxYl33f4P2CO77mv65OsX1XVbufm7RnvDQRrDARQ+vCf/wxx3fX6J1YY1y/ddonfonviV6uBBROzsEcI8TECiYR5kHGK4vwVj/b+1f9f1z/F1g8DMnN4IR3hcLeLBehb+CE+OQi58TEcfDOzxr+HvsEZVqrqx/qEKsCOdX8UEFY8ICvC0hHe94ZDTu994zIr1T9Wi/PD3yUbvJV/C2ul614je6L/7X/yyiERQ3VyNp9D2iMx/FiPquf5t/giCC1V69X8Jm1xM/Qt1V3yfMveDsNeCF+Ny5c3Oi9S/h7CNDcuiYlb8laCj45dS19DfzIrycnYPVJQbCqE/vJvJRX3+r/r97Vi2Gnrrgg1/BYF1qtaqq+v0I6jD//116S1+lz/bb3VScvxJu7vkN3fQBIwaLl0EBCL7wL4JF7vWLXVK98qvVV83zITXiM/DSI9XEQx6viF6nvDGTl+60gQ1r9WCl7/Rur0Uqa/XuwUrXJrG6BAZF14MlrATHW+MUUdYxCC5l0CL13Wvda/qwIv26v0v9/f8V8QhLYhcYiX6Ao+oi7j4c9H/EdoV369+jdXaLl9rmKoI+7/Xq5Fj1yq/6/6Ag/1f9X6/v7V8cT6etCWO6xi4sQvXBSuXpfN3y13f3LWBKCe/i56+uDL5KT6+++Wa5/n6n+8Qv3F3f3BR9Yr/J9CF8N/5sGW/lwYcQs+C7BP/go0eF5Pk+J+f5cF2Cz7+T4n5/gx+/k+J+f4+AAAADlkGb4C/AKYvi4UwCI4NOW+X5fn31/LfJLcV80mBt/EwVcl8lr5qsO5LllGIOfyVN1r/qIlf9P+Cz175vmV/17ql7ouXlrA3k+X5/B/WLwLeq0aUnoSVdcysfNX7/hLmhbQlel+hRPuidXEdg/99cqLqi//+BByWAwfftsHhfvxxCf/EfS9JgVPhjCPN6PCWNo/q4lW9fderBbv+gT6oCSEUTulXuvr61rwU64tC7HxK0q4ZDV6NWNKiN8tPn0bv17wUiV7wmli6ggWLwQ1i9/ioKBiu/UQrnWrngbfcIfKisdRKK3YENdGr3X0Sja6EPr8Ifv4rw2Fvn+S+J+Xfxq8y9r70qoG/x9Yv1j+JokVcLQpUQixXxl4LcI4N6EdrqXsCX6kRW+Xr6k8PZN17wvlxTt8q3V9fRqL3699L3hGvfAjeMwTeiNXXgj6++3BR1XVUq3fgyJ4IEr1698yJ3zL1eveer3gyCKE90Cx/Kjv0MDWk/+JQjvlr0b3WixdWi97q3xvwivqHsQIqPb38J8XF56CeeI8E5t3d9qwZ/DNGeTlrTscsd95a//X9YLgmhPr4IqG4d9rrrT6+uu/krYn4P87CsIL7Qc7uF99cJ+Qa738Sv/BR75edCnvl9HumCHwQBGsKccTKvwjV/MEfCu8MGXrq75L4+FrnhDjq+bJ8UT8E173d35Kof8R7hny/Jqh+tjqyc7r39PwTUV/Z/iaoNrrrrfwTwzhvLXEdEqvwTjuiGRGPm+IV/BFV/BIgQ9VfEKTeBB+183xnWv+vtf0R6rr0fvl7Ayrv77oGNF/6f2iP0WvdDfXb/MIe8JiEJi9O/X0y58EfaacF5sUhCW4peq5/nV7vV/16q0Jz+EPm9/f3r/sQqwklfwh9iFesNZX/3wwORb1d16P+LS+glFjlHeOlevviOvwTekJN3eMXX0Cju+75a+JL3fhX4PwUeD8EHgUwWeTNgk/Mh/ylk/RNLUDTxb3rCI74WRv7/gkXpqxrH9FcqgL760Z/F+g+IRRXdeq4hTp8T4U+DysXgUBAJbu7u7uReIXwMoak5K9CPz83f1FIW2IV/Ga+Nr0Z/j/BRhz0JqfvrQo6SerEmMq+/5Bym3u9f9y/q/UsJXw9uhd/1evV4jW8NUI/T/q/rRHtcurny9RKtjibfL8sdWrwVX96I0WIQp2MWxH9/cFXzCEeJ1nwQf4EH4j5cFGDv4j4ED4j4+AAAA65BmgAvwCpCFg86QeYrkl5fl+X5flm5O4rt+/9Xvl+WuWE7qGfXq5PpYq5L3RXu41G6rhGW++LvkqpeuGukEehX+4r6y/8mxjv6iP16vrlvAl9cX9gMnpP0R+gOJVfv6+pOtFKvrJd8lxvywjzQ56+7frXry8USvDOuXGK9/iUXLFE+O+MycSjd8lcq91FdBD1/GfNC3NCnFo7+Cv1L0AuVWCH4X+F/jfhP+id9L3hEn6Pr4dxsoX+AZeP+E/hMR4XycqN6XCPsC37ifkhPiMUs9xSLF8ct4tYHDgju+/ydxmrA3/0+r/8W/Z/LVvE0T2OJUcd43nfw/+NXvkBFd+PVRVP+su9qTEfhGuJ+HkKqFbmriELeT0JqO6QYj0rwO7Qntc4GL5FXaL3xdPC/kw/8M/l82qvqt1PCHR/y1n1QXESYjv4F5GZ4jCPCSHtQhaEI94utVv8TGXV9oJP+v/Cm+/l6j/l/Xvib7RX6hfoFFHftewoGtKoEquU1fRS3iXvxMEQxa+64Q9excIkw6M1gYfgZdYT/zesaI89fbFXvBWW6eq+uQYhjXKvOrlYR9Q/6CqEv0Ev6v6J1+HA38Iz2BNoR3xFYNgW52H4SqLvu9OhRNcTGYIPgo+BON8RrAihNdV9ctVL1oEH/n/Rf9AgE+DAf4Wq/sZJhmjuXWif9V/PymNIvIuE+eN9D/z4h1xnyeGvTE9A11pIQ/oYCG93YLkV6qFfCnef9BP0aiPJ6P2LdN/Dlf+I5f/7sHYhX/X/qr1UiJlCvwkt4JwSia11V/wW1XWt/KvC/5UZq6V8QpM4I/hfJYN/j6/qrV+pJPRev1fsDL76peoxerl6Zlfwc/mhNc/FdIXFJ4TFLqqqp8E5u+TiJb++bde/RO8telx2raR37BSf5V/0Gfyq9nYVhPqfkxCChs1+aveYIL0ngjMq7nnrFJzlNNmatcvAnVy/XKhymuXgZwxr/oBTgmQnupETuu+17574iXmQlyV/wp8lzzfLy3hv63hd9B814ar3g4r2MULKj+YxESv8l3VU6M8lfsiK+OX1cR1HdxStikfEL83zInY4nl6N4NsKfVXV3S+eT0d/1/foh1SehTSXovidc3Jz/LIOJvil6QhXkv67+8uFe4r4hPP1hxr3X31fNgdAj8/xPUTiiTYe/vmEIj8uF+vr6+vr6l+EPlELiFv+q+vqL+F/kxX+X4Q/EL4ZxAhZ8En3l+sHWFfivxEEMNfGf4OsLfBL8EfwS/C8AAAPtQZogL8AqC+LhEv/Fx4IQ1u6Rg0pibpCa5fn+WX1f9f9xi937f1q6lgu5ESLX9ck4xXrEI7MmA4aEdLU3f3VV3cMwr6GvC/J3J1XVdaEd7XydAj3UT1Gr3y/P8vy+BNr2u++aSo7fNr/5qqE4U5oYELJtehXQX+G/hWvfN11xPzor+ERPgxEeSveT4EHf/JDXNXNXr1L4j4iK4levi/BTk6XqsCf8TRPdP+vroG/wU64RBIJ3fLwK9TpVgJEIK/aojVlr3QHv0FhPX1ondP4RS94KT/HfEKVO4eMTkXCPSE98QsVesVCie4ru17uqqlirpC/xHq8mAkQhWBt/JeCU/VIzVj/6Ed5dYr5fxHsMVf4R751+WqCvwQarvD/XN/EQj69jkW1DF9jF1iF61er0Jeus6LfLP6CEVLrRHp/oj9UCQpsXKld1Vr3UvWitfE3i69Irvxihfxb3XqrRu9V6qCeTE64PvEYS4q+P6Ah+rQRrv7bvn+/kiukEM/QLHeGSyVL1m6qT0Xx4Zr+vRSr8FgRrQzwZDPDhl/48Ir3iu/lk9e6Agi+q2pomCQy193wj6H9jF18vQDJFS3r77r/mXPErkwSCnfb8Xd939fXfq8lavLQJgU1y+CDXNXgjFrVSqPYI+gyI/Qj97oj3t0/g3zsPwk/4a3BEGFXTri6v2AhQQ1Qz1d89YKBviBtV0OVLvOHl/4dGoveGK9N6Edb6h/Ow7CHPf3X8RXE3p36CVTcLFM98XghqDtU/C/wR+oiue9TEd8mK+Ft4zXMveCVeH14g98IIrxGCqjdCnG/J932hfS3CETh8y94bJ8nm76iviPjkZzwyK8474zzGRn8Z8ZrT8utm7AQIY6DJvFOl4ij9WT4S0IR619YU7XogQtrvkekuvz1l6/m8EJlXf9Xq4iXlxS9T/oj44l3eXfOCQu75fMCMu7yyfVa+vuqRO8RvYIsUxPQPdYLatjc3w9j71Xsvgt+CgCwQKPeGBCFycTJ6P73VpsERarQp/nX519fX1Ppf18WsVaKveGa5eB7DyLl4FEECseBRDnQClBV0VdOr9Kv7rRX+LV6whxspemetXKybXx2dhZwQcTS70EevdH6+7xDqhgjw41Ongs+BSMiXxiiusYiPl4H8JXWvda/8iia0V9/C3wt83hVfEK+OX/4iF+Wq0X8f6Fe7b8MasdRX/XxXoj6/vurdX7vvV/BXV8cTeUYrT1XdyIr/J8+MRFf54IqGK+0JykwRZqklf38T+hDY4lpupfiZ7yl1UncvJBR8YIXroQsZz/f31f3BV8whfDOIELPgoyXwXHhuEPivgy+M+K+DL4z4r42AAAAD4EGaQC/AK2IXXxkEnoLNGdIn4q4v5e43v+X5UR5+aq1eS4mDBfJS+l7ul6/rlRe1zdL51/r/XySer9yK9cSr9zL+7i0R4Y9DXhFfEoV01Ar69/m9199LH/Uqb4ili+qqJROriUfvnXq5fAk9f+CGhGX693FV6E/rmhzmjF8T8SvfonVxa9r+SuuT5Piv16fBD6A3/Qq6A71jlctdL3zL3yL3YGPq/74S5pVzf9cRGao/V69eBN3Ui5dSIneN+EfhX4b+CH4Tr2uvwV/icQhKVUH4Dn+wpWqJ3qvqwdifBmLRPUuIhDXJ65NeviIY/qTrv0NtE8QC277vv8II3MtwgjP8YrngcVWBL9LSXl8KifCNFc8aF6xIvoFpfEfHfpX+ZEi+K/RO+a+Vfefr/wJY2sE4/XWjnTXFfhH8dCNR0gxCdX2jdV9YVxy66J9f3P1ZDbvrk7Xr5r4nFE1c6vWHKxa/XtVxVdKW+RerlQn36J2vCPwUh/4FZCGhLmnsP6sJ0Eajuvk8FG6+5Pn+5OX5flrj+0He/oEQzxGn8+ueIrVBDq5fj78E9a1r4+E+0Fe8CDrBrqgR/P/qh2q1zxPgiHbv36+8GbXrX2r+iu75PV69E/r5179XvifhH0HqsDGDDxgexseeJ+VhjVgRVv5K5L4N87CcJrv/pf9fQS1RN6aCnfPEZq1WHNrqGESvivEolV1kL1Xzycvuv/lqgdm/RO+F/H/C9Ccq5kR6p75kTqHL74Js7DsI8911XV8bzeENcQg091Lr4XZ1VfGFV7xHoK/EfGfEVfuG+r8RQjuusEoQ8I/FOXBpRXlS/CfP89VzruPu5kfp8cE1iZ8Eorx7qojxhvmxiECOFR1wSmRH84zw+buZXdBD5MlX+vfEovdAWxyL3ivnS1WkiPJ6O8tAp/CCHVCX99XxKwyrn8EI3Lly9OuVDHq4hXmr8IZNhJFfwZhhFvVVv9erL8lHeT1ebgRIS+/jXrzVcqta1eCz4GYmOQo9KxirYrF1fwPYIPAghZF7wRhCawevyfJ9OljuhL0NU2WrP3l/hmiP+gk0JdXc9c8f6CPda9WbJpLF4V+OL4CgeMUV18JIleBXJNcI9/csVhnCogm/m9C/xHoR79Wr0bvtTqvkRek7X9UB69XJaLXavKMWlRBy2O+HPiPQvrxGs1WL9COq/07vV/v7RP1yXz/L3LL6viFOR30OJV5b5MuF/hL6sGTRn8FR/BsXwIxflRG+XX+uvXJ4hcQuIUfaIhcYrTYhe5+uX4f+8EX+O/wh/n3jv8FH+fB9hb4U+beEvlwfYX+FPhj4c+FPhj4+AAADn0GaYC/AKevhGhC0vjUChjX8HW6G/+Re+T5PakJ+v/Jy9/f8tr5Ff5IjiYRuob5P1etlROnqJu5UfvksQt8lDkS3URKv4KeWT5eb5pLhHrtXwz8T4Enr9Eirk+TqRF75EUqeNr/XtWuJ4X5kf8J8qEdJUi91EfN+vrwvWLsG/r6mrA+m+J8CSEK5vVe1xevYha6RPvRl75vaWLsC/gmxeTQn5UJ8eir48Dn1/ilk5Eb3QN92E6L3QMfqvVgQQiivfEeTeBBrF4FUq92ArwujZVi/yZPv/+/5oTEItCFn9H9+v4qwxEXfd+uGYIEIr4z5LwftYviVi8FIvWFcnRz7UW/wmPrN6j17r1/8MO7/iL5a7RIvn8ZRev175l7xeuEoR4r5p3/Vcd3XoR7wKX6utH90yr1WBF99dr6qi/163V11q/X4UX6N6uWsF4lDdM9gaQj39+34FaEfQzq4Wl6Q/qdYvHDEMxRnIvfLLguCKO/gy+CI9L9F7whRIvHdcTo3fr2ub6k7/AwaDbr8kJIfJCSBbe80JoBH9fBnQhDbsDT9ui//9cX5N3dYK/gVYaEKuvttppvsEnVXv0Z+q9tXm9H7wQ/AjB+sX8V+O8GzQljxIZmsM0K7vp/B7nYfhPj4ToMev5L5kGnuwPIf+wSE1V5OLxi++J8GwRlxY6nw0Gd5aL1ZPqvj9evBRzsNwkIX54TqNQUfvMTdz4wQr1QmU2q8cIRX8Zu4IZeb56wqHb0r5Ve9CIfriNwRCVXyvGL5kKfqI1QPv8QiP4EP4V+hGIU1qgv8V83uvPRXrKbwiKRWkxXx3zZKhJX+J1/XDCFdDHoI9b3BvXrVVGxdKhnzHEi93eqVK4pXmw1vD1X18T4Kwx1aPLX/QfKvda96XQT+M1w34o+LiTY36I/Qn+r+Lfw5BEX68Riafr6/BhQrugOAhepfE4hfAdYWrAlhzoBUgwRzp1z1HeEl8Z1o7/Cdev4aFLHeCEir+loP1y91OrqupOhi6CHwIjXvA6Vi+OBLd93dyLxSIa64SiVf7+X2RE6KL/9I/dwh3N3CSK/er5P3hDv+EK4iCitDMrrRequsFha5l5Vv6vFL+v/nX8SMRfjEL0CrWNS99/oz3zQRrl0Jinte/7rKkKe+fqfr+L7l6ln0VXiL7qIgs5/B9rqTnxCHP4vEIrRO+7n5/n+eRJcTBb9CEWJf89Aq9c9cFR4J5PjPmr65q4L/jPg8+M+F4AAAA6pBmoAvwCnegUN+Tu7ELBf6CrV62iukI/E3Foj/E9xff3L8vyy7SL3xHcZ8i98n6vXLC1TQ3cyvN0ryL76l61eX7qvB/vhFXhHmhTCPFE6+Jvll9e6iOj1i18Qveia/q+Tu+JV/i0TLwEPqnrSRXKbX9dP4RgqEL+ry1NfFeC8b4KX2BHf696av8T8/hE+KJ8G+uXwJvffdCR3WpVnxHQOcJc0M4GXQhFutXPjl7wn8K5cEehqtZ8RKHSPgWQ94IxS9rPDTRO8aKrGV+Uv0S/upd4+vdRHWveCf8dCtxWOR/T+hLeTEF//e715hjv/RHxiiu/xCueBT+CmvfJr76Agjer8Ij/brJ9rrR+6VYv1jn6xz5kbq516l8br3/X3iPgrCfYPaO+lwI1e/Vq4eQh4TukfqrQnprrT4JXHVJIliv0r5vHUI7xleqgT/Ga49X+PRHoYij3uVcIV7pBC+L6Agr4jsK179F7xPxP4GpDI5CXob1iEWb0XoR76+he6LQS6uSbibxvoR6JQl+gdAgWKTn60bsn7UI//ovUPZhNjk3vWoTEIJz4ut5L1jRPiR27u+8HL975Vy+RG6sd75cbR38I1f4TRXOoI+u/Ryr/X8vod0j+CfOwQwhcLoPN398L1Ed/UR8R1EAlOq6i9X6AwgvVzrqpPuTBEEftFeuOQh7w6O8GtH68KL9EeRcuvfoneC4+dh+EO0HOirF4tfD3hAeCMTqrXVdSdv4NvgRQj47T5VBGatXkwgesTr1/VgIUEHz/S90Cn1fhTVXVA7CPX47CfL7UTfd8RqhMXh1F6rw+b+s2+EPhL4yvQx75qxFe+T5OwnR8uwl7H+675F/XOrwQ8fSfGb88qxl6fk78NFlrQh7HLMqJwbh5Fyq5e3XvAsD64hH/5stfjNZ/UHiHNCfoJsRWK694rlQzvlX5Jy3gSOMV6xC+muXgK8EC94FUMK/g3C0l91ov7f+OYmyhy2lq4S9F/F/PpdiWjCnavlRPeq+lr7iF94SMveKrXgRv618ILFiF+WuS6nRP9a91yjlduvr70dsQr8FO+I8Zhz0Xp81G79Tql9EOqSr8EWxytVVdct3q8i+JilycK3oS8T8/r0mHn39gsL3evn/Qp5eTFLiiftX7l7/niKoFA3aXVcpBS1zQ/8/oIPEYEL88RgMAtCF++r+4xf/LD3z/E/QhfAl5fxC9e1+ewUYjBRh75/veb4wRBHNf3zYKMP/P8T8b8Ffz/E/G/C0AAAA9JBmqAvwCuVoFDwR+gvU2FcX6GfiKi+v5Ve3xPNyb/V+oiCqpYj166k65a+5651frkGL/3EVcV398MDkJ/hTl1/Nte8nJJzo3dRfxK98Wva117X6xzwK++qr6/BL1/C/MhLx2f4R16NVevUOV+6A+5OT6RO+ZexRPzKVPrx+/rD78EPf/hWi5eENYFH0Akxe+X38RJhmidCnN/HehL/yWDHWBbVr++qoCKfr6/G0bviF7wv8f2/Ojs/WsYvLwI/wbhr38/yJe6CVZdg5r3gzP4PxaEd8nl1hH8VCfxHNEehfS9AhJu6XwGcvAtEvAh/iF6q+vq17r8tWdgS699r7xf5/wRb3f4oRd93/DCJ3VWvi1++L77L8v6L3l16J3wxCdRELdAiM7/Wu4lc/hCi91EVf4JC3t1j/ui90DHXonfIvYxT49YItc/ixdYuvt/16P2vdE74GQEZtVK8hOvqTXPCWOQV38HterC6XW/e+179dRa7rwU+/u+/ukEP9i/UqsX69e69+veb1D/U3X4KhP6Fv5OOJFd/R5t0bqHswq+ywovCuBB39UkgnfvjNErkBIOd9y9TdVW2r/oj3yL36/r1fHLb5V/dw6hrvFex/4Q8wLMbicDtVB9dBWjZdfm+eid+vvn38E66zsPwp9L+PsR8Z3+gw/dSer163rtGfqvtf9Sq/zq/6/+J8Eh60+wj+J+LR+9hzwzqvwYCOpFfpF0twiiP1Mvde14WRHzsEMIiCb+l8l4coIdK/dXiM50R6uSSgZZH4Kg4zVrWIhMT0U1YS9Qv4YJ6fyVXXL5Qp5PX2Dv399Yyr1Uu19CHhX4vame8KgiCKqvDwuIBH1V/H6qK60KfqMV+oQ+K8EKV/m+SqiekJqkuun+vfS9818Ieb5N0tYS9Bb1/DEKCEWE/qgQoEVd366tUIermV7HE74hUtP09V1uCMu75jwNYOOtFi7Bu6zfEfJ6BPunqhHquva/Cv4pYR7rXu+pQQitV7rXutFy6+gRLww1yriccp6dr4nwJYQ8HYKARnd/ugEyDJe6dE7pnXuwlV+5e+Su8FVCWd6/OwJ/r64V5b+EO5KruIRu8NazE8FHwEJVOo5TUr4WV65ETvdemuIq5paDQUQlsQuIX4r9EeGPhDv5UZiWtF6TA6cUtVL19dDiV/8/z4pa7V5q1e/hn4Q+8KOu1frV6voUTJWr7+LkFLdl1fPyQz9dx3SGNJ38uIV9TyL/X/V/eIXEL8/f9/cX8M/4Wx/+O/zCFl+8JcQs9Ao9c3+BgwT1yfFfL81fXBl8V8vwc/FfL8LwAAAOEQZrAL8AqohZxC+AicFXLEdIOPVyL1cl8t1G1y/LXPJ6vXJ3Gd98TBHyo/V2jVXLfOjdLdddvm75+7q43uVCXPRV/1copf0R/4L+WTavC/qIrk+ZYu5pP+VF79X6jRfd934EHv4nELv6Ru+l6uRHi9r0boHOExC/NClxK9VRNUAkel+TH62qoFp6XwguVjEQV1jkX2KJeOJpk8nwI9YqwIYn5K5uh/rRO2vwS+j1dRPpq+IX0IR3fCCI3gI3dQhVA3+PoRF5axeGeKIXoE/X/wjrwOYK0eLwLKBR3fd8x+CPu9/EiOgMOsnoG4n5UT2v6qTrRm6CNYvjoU5o+tC3nqMQzvlRe3z/X0QvyVRxPhN9Atr3uveP3wui983g4CCv4MPxFv+Rf+HQ70J5fC3+l4MAUIR0KCEeEsuUUul5EbvA2VirVerlRe+fqN+J/X36+p/r1L+uelX9ghDXfJQfqVJH8CdC3ob36LVesoSwX7xWslBR7yf197H/fhHXPdQn0Shr9hwiv4Fb48CD4qhHeI/onvjZH+CIi1+64RFsLkw6IhFa+jl8UQIbusF/WHqNVTK/Sgiu+90Jr11dcvxK1XP+hP/BBsUTJi8un4LhKEdnYfhYUTCf/EINP86ufEVgTwR+xfxPVfdWBJCqvT5/4/yfQmub2EPB7koGNXvEZDsNwxWgl0dt/F1UV0hHUnz4tQrVKnhcIoQ/hAny9C6v0O9Qz0ENUUJ9ay/XvDohe8J6xle8Z+I+I8mude6BKq4qHvQ14nCfwmZDK/XL3d3+b3GdzYxSW58JeCmiMa4a1fwx8IVe8TRe6+wwClX3hpJdRHlEIvVivkS9WR44n1YjVddq/wpBL4T7u73d2hDl1J1qxdUr/JS/xxPrrV+/5QSd3y8DSDbx1CZfonS73yIr1XBPkyVaGOdVdfWi91+BaHeB+HY5TXYxi7FYT+F65eDMMeBJBhXJ4rdBXavtCWLsCXobK2dFTFsKCX2hrFY6gI9D361993l1R699r1DlNSsQvQEcEV8ldozzjkLXxeCIknJ8KQUehXuters3d3f1r/rV8cu1VF4pfnqpbvV/iJ76pk675oJvXqvU6TX/LXIrncny9S9fzwd3ff39g8/Lr/X/yoINp/+WTl+f4nEK4zvq/uC6+95v8CFu+XBR/nwXYLvp/xZ4L5/lwtgv+O+b4NPjvm+PgAAADeUGa4C/AKQIXXxEGfoJeha5EM6XlsQivHK71z4xcfGKrycntfq8E2XNyxPSJ87mXphivbGLy+X5UXKksTEq+IRFXJ/dx3eitt/gosO17v+X5aGI3sQsnNdxxCu/tZOJxi36ja0J+TwIPwLP59d3Vsnz3zQmIR1Cd6N6YQTQxWb0/16TG1cy//+C8Srnj8mCl/P4R/PeBH6/8COffffr3698iJ0Er/QnpONVtcX45Z1fGrn+LXuwCZ6/4joHP3RPeWvvivjlfwv/Repf+BXSLl4FMFS90BRCCy677XqXf8yFP4X+GfxXxS9CXMj9ilvkj9CTF3fgso8c/RH+IBES7u58II1+4QRI58IeD0VfEI/VUT4ZCPhcI9gVxPYo692evd/gj1xKxfBB0GtVPfo3vlXqwahFC+tY+L/CCFVC4hDYSV145BDf6rvyOnXXVIT3xUluvuxte7/hH4+S9Y/UIeIe/tE77Xq5awiEfHhPfwJ3XDHoJ9CPJVeT+v/qrr+/u6Heu/QQ6sCUCHsHVC36HLwTAg8KflRu8NCN/0X//4hep/gkGLW7vhHT6v4VQbyhXRKwSvwRUOfwUGNrXygo6rqqVPlRHvlr16XBZ7+/wwHflQ0qfC/koz1qidJxS94MBOdh2CXyhJ778NVc8QahC3p+QV4FsE4ITKq39tEfsBFglqvqWvX/z1ih9Zd4bC2On5a/XPjiS5R/zr1LCHROkf+dhuEOW+LQWeEn8MeODKO32hD72N/YhX+I+IV/B4lb8FAnVdVj+X4ihT+HQ34WlItV8nX471CfWhL3p1x3YHkd2E8uq/lf6GagnwyjD614fJ4J1JcZXGfHezYhDHLXb/8OjuyCezfgq197xVb3Q3+MUuW8wm8FAUgl8EWt2q9CHKwj8N1fvV6sFnqbr+efhCsCiC76BCe73u77bXq4YV5BcpOmrTrg6gn77IdDnO6qr6r4mtPwKRMcis6+JXLEL9gk7u+OJZp3wI4U8HIYupZ60d/QSlxa38CB4jBNp3YffUq+6lRPfr1clYEj8YixfCHgcQhdS9X7Ld6EPVWi/76rk9CWt+JwT9IIdNyo/KvLJy4hfZ/lrliL1/1xD/gnV/NWr1XJf1L3L1LVSzV9avE4MFBRf39/f39gSvf884hfie5++O7g6rmoFGIwTYOr5q+ubBFg7+BI+F4AAAANLQZsAL8AqYhAscFT/hHSirl+W7je9D48ghfk/V/kRe+bqSDOpLqRek+6ie5etcvl+dE/JUyvZf/4LbifpaxS3X+vfr3697Xj+/16i/y1ovVzyXDfprl4E3r+q5OZe1+v4IvW86+JxBPd1gc+IW6YjpG60bvmvC/f1v++J8M0fsUTjifqyfAj/n9l+kbvm6hKuaCkYju/wv4GfS/8Drpr9YRq5WEfifl+X4Kz+F/x+MRy4dOgHjXLwM4hZeLV4z0B7E9dZfzIV3UESv1q5BLxPX+Gh+7uf2xVrBBIMd+MXnxivYvifiOwJ+sJ/ibxeslF69kWLwL3wUCL2dCO6Xote6+htCe6jVfwQi64WhIQsMrk9fWu61/3L8qN7qX7X3QM6L3UvUnusXi99r3zr2vTqgSDlfoN+h47rRO8Hm3xH8vie/gRgSEWsugr2Rc8l3Xf3k/X/Re+X7/X3z/Or/a98J9BEN1wz2Cf4NNYr5vk1iq9XE7/BERay6FBCCsJejO8Mb8wh3+CEqufJWyK+OJejf2r131rlfdZTfr+/R36hTt64KUXvlk7Q7rf4Iq19nYIYJs1BJisE2sGPwK/58JI1ft/DJVfwchPf/6FPfOjvXLJUvbF3gj/oT2/16d/oZrOwQwTaoIP89P9CO8NCviMvg5//o7/SI/hTT5cEZq1eu+n8V8MFRWr1/19heidWyIvdgX/YkVjiXpvFegU7HE3/V6wUBKCfifDIyqcEpHfd9jxJa4pe+K+I+EvhCs2vV5qb8RR+rLvJV+tX61eT0T/wwhDwTLxOq77R36pEf5arV4rpFz+DMPeEleb5KP+68X2oRPfBhBJYjP9ZPhJeCahneDgR4Nv61r4/HKz7wi1fwJ4WRe8EY7wVjPiKxmtmRHicTrg6go9FavX395Sr3t0uEpN/BQrGMRMf4Qqqq/9XqtXnrviELff/wgjfgq9G79fHWvi6eqkr1/ilqtX+TvoUT+v7vkrR2kqfu/i0R4J13yXr/v716TlRH6fqXv+W7+/Xzor9RKvS+fvivRHgu5fl+VCG1yev8YpyC2IXELiF77rku+9X751/88F33mzf4EDr+ewUYjBRgu+s2KEwUzX982CjBf8b8HfxvwtAAAADhUGbIC/AKUX/rQJnmXx4g+77uRfGxIhYILBPy//oI9CXJ9V6HflHLquX+IwIe7iFfv/V4I8b+WsI/lvlxSxGyT8tcqLzqv+onrX/gIHfN2h3c3Wr9OveDWvQSet6wnoUTVxOn9e+Jl9fe1XIid4/v/fN1cIovXUSr1gpr3698Sidr9Yrq1fp6xVHfw3+ZCPwRej38T/XqL//Qhe9XquhS4ha3X313CnyeNoneEfxC983YEGvXxPsTLgU/gQT0/7J/fyQ18RBH93E998QhL+AhfQDR9RnUarddciN1YI94Z1s3hnXEo742U1O8FIIETvBmKXLwQiFy9f174j7Xx0DcWiHSsfXqf6N0JV/LCO9E/T69BF9LhBgi7vHPiEZ/BgX5PivQ1Gz0n4te6hXwR0V/DonyD0XugV7FEIv16X1KnhAR80+D0M9A39fhALQlxS1CeTNUiGRVy9gJoEl5cuEaE/Pj/16sP+oX3x/QxFBreKvw58KfHdWaPBhXoR1Vo/dBHteDYEgiRmRktCPFfFofFCe6EPNp9/eifk7Xvs3VUvAlNffPJn1Q8Wi/vF6xnxlF7wt8muXp+mfHsUXRZFe7eaFQ3iMau4hCXxiIrFXq/gVNZNDiXG0dE7Xx+vj9E8S+h7/r2vuuK8KIEfVYvYXn9DDKM7BDDOxEdhbfSCl7wQBDwdsERFXTr6v8vVIz9cnLVQQo/dav1SvXCHrvwz8LhivV/JV/1/+v+oQRP9a98ZnYdhn0FKjG/lI95H8V4UEdQoS7/GVfxRteC3+r4onwagnBJqqv19H12v60e8nwmEKwzlxmhxOvhFf9g7P8kL8kIeC4Sq+qv5X48n9U33Mh3dX8bjloL9AcfQK/W616l/RXqoZ61/1q/kr2sNestH98R4jLt/a/8MaqDCCj9fLVRKEP7E3WiPdzX0i/ksBcg470Xqy179E6+ZH6zvR53Xoz/AjQS97/Q6q+uXv6+5utCcu0Zctagg6XidLxOMV611P4ENL88EZlz+BLD3QZP1169LYLaP3er30vOiHYQcE2nX/SH+/Xpbr4he+EPA3fjMQvxkZf39/VQWdo3fr79eq7U6jrq5fnlv71f9X6dXxxN/1eKvgs+OqfqN8CAWMvgs/7+/vu/vq8YhAXWTYhEf3N8UMVXgw+PzZ8E2/lwXYK/lx2KEwVxPyYKsFnwh8R8GHwh8R8dAAAAONQZtAL8Aqy+LiBCwVcsV6BA/pdSRHL3Eq/cny/LJUncd836K/zQS8vl1y/PEdInfSvE3G3yo7yciJld6K9XEQSY38tv+9iUTrqJxCyf+vVQKa91yiF+Jvn+XoBQ+pb9e9JF/fNCQhWY3COflvRcYTfVzwr8u/0R5Ovpe919XMvfNr9e+Ip/VYEP2AwfdordR3gTK946va5foBFi72vm+IggxNF6I9GeuNriUdisCj8Djra6B2J6L6iNV6Ed4Tr3j/690H/TCfz6/QsyeCdKZR4WHfaJ3jK9+veTWDcT9oxe+T5Mv/8JcTQhCXPxdF//Rb161Xojy4So7Vg0L4MqEP1CyNfqRU68LLF4GP8b8Tv/oq6EUL7sFPv7/H0TuwLNYvBT8UJXqwVQRd3fXDX0qJHr0TscS99eFPYCHC/f7XgRwnXCHw1CnCMJ+COq5Vb7MvkrifpEfX/g6Eb/R+633fXVAqordS+wjrP+4frF/iPicUT5KviFXQE3Lp1hFeCcP7+DYOCFr5t5YTQrrhjDHxTjt8Qt6+lVaKlWvsI175eq+I+a+VerP34b/OjvXo/dDvX5KN3k+M/PS/p/oVN1wjg4CE2EMJYF34GGCETpJOeCUtKrrodLXXgu/F9V1d80i+EV6bgk8KC/jfaV6X6N1Yvv/OwQwv8I8yDD4haweiN9XXHK3g5Dfz1cyEPXKr2IX4R8CkCNDUyeLoR1YKRCL0vN8tv4rPDMLckKcR4ET8R8mIQSHPPDIZ8EH7Qp+j/GewyG0VvDGl8i+JMeaUUQsmb4KgpDG8IYNwh4TJ79CdXoV3Wr/C3wh8Qr+EeMVJ+putHdWhyv8kr/RWXm3zyejf+CBCHhj5cIUE+i+WavuKp/oc+OVJNdX+ryYMQQIrm+pvkr17Xqi96q/whLWi9XAgQx8V6NebdCn+6qdH7qbr7C3wQVY8FykwPff6v5fgnEeDsNIvVzohUkoF6Re6H/1f5ZRsfTqOYr2/4VFLXJjlvFcl+t7EL73lNVfx3cJIhU8gQ+EOoaV8QuMRLHYDbBBJU/XfJ895PzdSIr9VWBR/CUM/CC/60buqX1+iv4IB+OV6bvV8ciWxi2MYTen/jlt7LHV1cJK8M+jvCVX1Xyoj1VK9jFd8QvUl13y16vXq/f1or/aI8leIRHDfwpcvf8sTyydVV9XBF8EHzYKuIWfBVg7+f5cFWDz5/gQfn+PgAAAD1kGbYC/AKiIQKHIvjYJvQVaKwT/BjhL0ZsUuIX5US1erT818RXEL0PehrfrbwjkwQZsBA8YghqTql8lciO/YOcnL3Gq9VE+BX0vlk9f+Dv3Hd6vWsPl//m/y9/1y1z4xfXy3yfVbJr61+vSCFd1C+OJ868X8Tr+sEeCXE5MuVXwjXP8WvdxtDES9XFIsq2T5v16sP/DPf9DFerwIPwdvwJI7wJPwS9fLrtHROr175IVEI8ohYv16+JXu/rxinolUUivHEm+bsAi4S7+4uvrkRveEaxeFdZ/n2KIXGyh/LGceCuCju+7seGQsvSYzeDkI+VfIh3fHQovmQ2sYvoio2Shdev+/TxYr8ReBaYITO/F1HI0c9ER3PArnrZ9f/Wtw+EfD4/xdH94uvv19+vrx9e/WOa+PWvC4Y7lRuxC1ov38vkr1UAlQR9A6CHwQQmMV3+f5ZOWi//16HvfoRU1i8j+TvQ7vl+0WLfL9Ta+f2bqT5fDJ/EnQnvF115RPhGiV4Xq/gj+CPYxT5FVRHUR4qsXm1Qz0Ea+eCEEOvBBQj0JX1UK16CdS+tVhCtfrKbdCHrvq5sF3wLgjqVEj9apUTEP5V79entAp60L7sT6FV7rWL0NkxPoCDq+E+O8CUPhH1e13FXgjyKviOdDH+J+dFf51fwNAMdfF1X8djYudrx+6/is7CcE+QyCj1yVgnojeE9cQr6wYH/Alh/sBPgvu7+X9Ge8PBNCX8CkDGuO6/GD1/WN1xS9WeiP4Q9L82dhuEuRBrviPk+IXvkj+Jri0V/AhBOqAghDoUTr6EL0KV8UT4FAHng1BPuqkRn66xX4lX6hNHfwYfP+I+bpiaxle9OTQj9eqmeGOSPy/bRW+TwTm/Qx+xvpl+dXOonql7rV/D34e+bwt6FrxVHf0O6k66fX0EfiHJhKvdAnr3Tq8nE/DEP4mhL16NeXu66oFdGfsM+6RMu9X+Ee9f4onwWVeqVX/V6rV+vyzd30B1BZ4NwsQXe/BFqgW16rAklr1/0tj2EZYK/78EeCTW3/XfUtaZQtu/BJ8J17wx7+wh8Nep+rxC3QCVBp4NQ583690vWvjqVeq+Rf+I4tib7/qtBZoJPQRvf15Cu/q/1foI17qr5OxAaV/AsBDGIh8bGLi1wxP1OiP8ivJcT39cTQFGhbQU+hVisZ+vZF6TDBZfV/1fFL+r1UX19/fjEc+IynerEtvBV8nctX3/P8+IXr6fEIQ1FEwc6fcvf39/f8v6EMYxEabEK+ub5VxfBn89jsT82DD/PgiwV/LfF/P8uCLBZ8IfP8GPwh8/x8AAAPkQZuAL8Ao6+Ii8Bw8QuIWLELS+YEIa1V4Z9CbSetb8K5fVpuXqWI9DHq6V5e6wKPwLf5e4mTRK4j5vAg8cTqCKtCaiPvnl5PkQh4gQsg5FftfF4xf79f/q/Wv6qO64e4lH79arF/E5biUK6vk4levpe616qiun+SbiVerAcKuoR+dexCpL1eqqq4ZriK5r1exCv4lF7ELrq8YievLrk/XvpSq6hZYvDfx+sCyLRaxiu94La94M694EMR4EH4Ev4IxPQH8fjiEE+O/5fTXoZf96Eo/XsSveJ9/yRGhfxNClxxCzq3ge/jET1eid8KdgWfesc+EPiPCPwj/rhHXL1g/DXsJeP+K1X19RNcnyQsIWuJk4368783X/iFr7vDGVcOdVHLHKr6+omrR9Pgo9hMWj93r7oGfrrLXqHEl+vCVf+BS+xMnLWn19C356J3x0I8TiFn5fi0Xvi74ifLRHrH0Z/b+16+RE7X++Jtld/cR19aKVKq17uVW60Xute6+p+votYuvxe3X9fYbBV3y4TWb4f+w4IoXvLssJYVqE+EZvrCXoMfiI/1z1gUtYQXhb0N9a93YI+q91E+Civey2OJ90/UX4YoS/g+C/fi3y8CB9AQfn3/fFb/QrKFMG2uFEE3rCHxAz0o7Agf0OfwO7V6wQlqkbx1XqtX61/4KNVq9cvyr3y3gwBGhPSar36P3X8vzfV4YNnYRhHhRBjt/3sVXwlUUtfIrsQogc4IeX4r/4xWxuHf33x/x9v/7Rnrn+f4noD4Bh60d65V7wyFvBCI+Hq475pOOzsMwv9ZhCCnfJ4nFcTfPWGSa4Q0RzpBLoZ9E38OVh0I7/MTVXxdZPhChL+TfN4KQlWl6C3jviK/vJRnrhSGPj/Ql/CaRK8fl4vHIQk58d7GfCWMUQ9NeMEdC319dcny1k+/iMvNjEJvr/4Whfkk4hain4nf1hH4R3WhX/EHkFEubm14v0BzBN4MQl4vfoXyr6/uwKuHPiM/2qyfEaGIYkZdVL19+uWXylrlR8umbr6BFXXgo3gUfgXR3QC1D3gtHdAUQ10q9fq/xPyor+Wv8YrTXf5KK11oMNCnJJlxGfeP32gm8lfX1/J4ivSaEfEfCCpUTikTq9X/X9dr/u1fv60djvn5oYGLe/VoRv7Efb6lXvn+J6+vrk4n5/mRH7A31f5Verv9XiLlhZcnJfeXH1q/V/LP2jPquVHfGKwbHgeBPyyDFdsYtu9EfrR30/Fz8XDXwpd9/f9oc3394herk5/i8QvWjPv9Xv6vR3gg+Fv8If51/ECFnwxhv4Y+cTBTEfLhjDnwx8f8EPwx8f8fAAAAEBEGboC/AKMIWGhCwY8nyfJvkqXtBxq5egEb8CXrlsQtcR1GdfzL3g//EQ5hXNiaL0nKiP+ryjkTfEK5frC/wV5u6f94GHXNJzov4J8I/BLrlviV6epJLAnwRXfi1f1z/Or/Or3gVf9WAjxPxNL4n9X+Zf9w93olQu/5fQup8I++QQuIX9CL6+EUfq4v9GvjF9dOvfS9Kv+pvdexi3ugU64j1R+8CHXvAgvX//yAjNu+VckKiEW+JrliaNluNXviV7/XwzjEVn/L/+t/Ag/A3/A769E7sDWP+vpE94T/EfN4d3hoI/CaG5eBFBVXOjd0C/XLr/wIY9e7AV4f+bXFcJiFk41e/XsQuIRUhNE1hjeCCvdAQPxyM58UCUzvu/F8V8YilWVxPX4CLCPgXBFej+8e6xdWocSvscTY8EfWBw+8GOaTl8e0K6V+P/DykWQlUI3cTr4R+JuoRQ3Lwpugj38RPuhXVWiHTfU61J1WD6CQqr/NPJfQcr1+j+8X8vzj/F/T9ut0Tqf69jEU+V4OhG/D31rif0I6n8O6/X0I+tddcX8I/Eob3wyveCD2CJS8QvRXIgg8vMiuqpqwx8X+r5ZOde+J+f4lCe+dFfxe8cJ82TPQ598RwlcMdQUdgMD8GWmgEAtBdi8uNeEt1Xl/+IxCHM+BP+GZbvrDHw5BJ1VjHEI9tfcnKve3Xr3yqx+v6GISCQbojH6L+vRurg2Ra8drmkfwhnYVhOoQ+Xv7ifmjuL9d3E98hgte8YolzmXBzRGXwwCIqrv4EMPoj/oj3yq9dq90QEPjAvfN0tYR1x1DEVLK38KZ2G4Q4j4r+rjavQY6I9FafiUZ65KoP64j4j18Qb4Q8GtW6Aw/Akgn83uEl7rXutXKqIRcvDHuG+9E/0E3XoveNzCCawJAIIR9er19YhZqEUWUnc1iRXaq3l/SEP826v71/+vV0jfvEhH5u7RXdE+MoveOfiPwt3Eq/Yn8GG/69ffr32vXp1xNXAoQl6J18TXzdIXUVzoU8ta5fOideI44ne+STlrC4rX/QGcEEVuh7/avu/hL0K6uJv4v0W9+jXq7rxV393Ly+Si9Y5R3wL4xxJ6/13COIXwZm8G4Q8F4aRe8WIiOexxN+gnt/AoQkIWX4jCObBYT7m5F75ETq5UTqoLe4Y6hhFiVRCnyIXGKTOk4iLr7+o5X2vwvXdfQOfeitfraXqS19Ubv19rl/lruTJvur0R4mur0LebBVhf6shKvvkV5cTXq05blv0KfuXuiFd8Q/ifl+Wa/v18T8TK1ieGPhO/v7+77vuX5epevEL9/eIX7+/uIX+v4d/w7/hb+hmfEdfz4Jv8+CrBn84mHYj5cFWDT4j5/g5+I+f4+AAAADpEGbwC/AK2vitf6/18lr5oK+WKqaQQuIW+WuWxC9fc3eg53evfwTct8uv0a9Dlv8q9Pc3ej9WCnfE/Eovdwj30vl9CV/QhZL69GeCXCeT16hCpMcrviFl5gSld934/VL3cIeEfzeCnrrnsBn17vXtX/QCHL+id/fS+IR4lCf1xOv74mhCqO0Juo342uXsAQj+Ju45COqgT8UTjib+Ed81cvy6wR42S/wf/Ao+gEaP6C35u4JIR4n+hyO/RONxldeuYxC4whzf3gW6J3gTa94E3e0iN1r3gn+F/QZXz/E6/XvderhfGxPLwbhLwYiqsKfHegp6+uuSEuoriew3i8GAvwSCPhAgh3/oj/Isc+I+SuVe8G/4jwTiZvQnvfwvvCvV/+hD0OJaeq17r6dHfoMhFX+CZCnhL+9Cal3RX+JXrGxPov0FG+Tu7X61a+VFfwwvGOXuXdF7wi/v9erBt8L0V6whkx+E7hXFLXSK/61WEhPhKveEOX//4yK9DP/aI9jFuV1VxXf1J9ov/uvVvll5PRfi6yBm8lCf+EPiK94jeehnfC0JLgohjoBsZLAnZeM+Ii0sn8iEviFXghfgzL0PL1+Cr47eqI8lRK9Lwj4EAFfiqE9fqVMbKaGXxPWjd+jddQUZ2H4Rr+EJP+Ik6QW6N9XxCi6J689gyw5l/qHP4quHNcK/g5Dvg7D9doR+bifB8CVCW8lf/EVjzK3jQ149L01SZ2F4W+XpBjpPR2nvqp0Kf5viqwl+auEfL+EfQ3tjAR1rfvX/V1RPikivVAiBX4qvaW4isfvG5q4X+Wu9iZy//+nXZKrlrQh/nxRPxHw1QhUtL4peElJgu/Nv9F7oHpkfonFP4KkOeEeSb5busvL//5e/wSD7u+oiwj7+67VCP/reuX5Kw3rmV8YpCLmOJTq8tXrAR4FBF7wPIEL4W6SmFELenDHy31j6LV916FPWEKtLX9u76r6P617sSEOggI8CsFvB1V7wIojwIYQ8EIjwQhCuSu1f4he+X5Yb5JPxyO7ehCJ3cl3y8lXrevWpK/arTmwoEsUtc0lS/LQ5cdLWjvKIRy4GhCy5cvJv+b5K+wxQ7u+e67n6+wQDeom61er4J6E0J/8kT2CQVd7y8yvVgQtXXfdTz8TjFv8v4JD6q89TwQVxf/d89r/uJlu+/v7/tBRrwLmlxvri+Cb/Jivmwh/mwK2/lwVcRPBl8uEN/EfP8uDLBZ8R8R8/wY/EfEfP8fAAAAD9EGb4C/AKWIWFF8VS+IYa1UFAhZ+l/J0vdxFdK8vL3Hoz/L8tcsnJ/8n/UkEPKhfXzr18t1PfoZUnJXo/V6/+16X1/jFvfLL1fr3yQjxMR6PURi82E9ct8qFMXsSvU+pv179F98ju+qipKlrRV/XKr/gkLu7/Kr/FojngR9DFL66pflcivC3Eyctej1F2DHNUI/CKN38vJWJ+Nr3xCxeE/j/dWMX3xPg9r3gz1j/QHv0Ak/xP8McTJcTLi6L09+IX4RX1VCKv8Sr/EqdfxaLmPAj17XEv8I4ha6Ru+EPH/dE9iiV4R44le8MivD6oYhLvWCcNawf9e+EJMCD8CCL3o+hXfNCnKhOXz1xKL18WjdF8+tsEj6DUot3+CKjet/BAhDmOVnfEL7EK/xCv4O++wQ/ivtC+7Azi+y+xP9e34tr3hH5dYIfx6xeqJ1+jdXP8SveSvVhMKoT3wxCPF2MRHfuEb5d/1gm/oXeI8EhNVKnzIxVa6F/BaI9v7+7qasPfvoIrVV+q93fg0S93KreJd+veWveWreCfeDwJosXivQI691/GoV0j/hLhGhhBrmTqL6+ta8Mfh2sLafJxG4KDarqv/BBnrQh6s4jXy5PSv/Ret36sdMvX8qt9r77Xv198v69fFoa/2veI+GgTeGPQV9CV0fT5IQhKwC8fhCh0WDrwiBSRaETJYomOqWsCxrBLQxzwQ6wl7+gRDutWPLX92q/vlV/I/17qCFX6hP5ap0V+v47POT9V6+esHwYQQ7OwRwhxnydd6EexkRxCCH5vIKrXxPt0X/9FZjFFPsv/gw5f8CBggBF3djGKPulnhP8V+r4RVH8/b/PPSC/z4xWm8HgLVrwoviK4SrC/2CPwR16ThaEeRG7vq7vlj+Lk4msGIQ+EFf9X+SsC38Ca/Awgp32HDeTdRVVCtUPy+i971m3z/DEI8XiFxC96J3xsI48PdbE3d3grFIU/f8tcsnE/CnxXhA3Q/4yjv8nX0n4Q9e/euT41em5IY+e4S8IZPUygTG5M9Cn+X5aqTuO7Xvrl+JRc/zfNjiXa6H17wNIELWF0/gpDSP1+vS474U/LC/zckzy9dlejPV3Jp1dr3U/hIXd/gTDeD7Jg/Miv4KR3hkZJtxGLwxyS1EXhndd8let/BB+VGerFH8Me3Qnuifm+ZE75qvRf9sQr9qr+DQmIV45bzDkS6UYi0qDohe/vq+I5ER+vr7kq69Kv7tTq7J/Xr7m5e6RHk5Zaur0JeUYrTw3zIr30to2rQx75epeuqpXmpH65+eJ5YKr+/v7+/v78QjD7KIX5Zf+fu+rxiEW7AZDgQ1/Pgm/wIXz/LgqwefP8CD8/x8AAAQQQZoAL8ApgxAotFerYxbxS+ZD7wYev+pOvuZerkm5b5flkEL8ncId/eiPC3LCfq+IWql65ul+XbEd6L0nLeBH4wm+/6ELjld6qREfv64UEItCkJZriZeX9a9VtWX4l3hOjddAl1USjdY5XfS8Tr/4nELJ17/S9VTdg/osUnL4HP6CK9r/wd6wd9cstP5uuGuWb0Wv/PoUTMORuXyrl88nL8+IWn8R8i91FdTfJS617X69L/glyZ/gU/YDBE9AbwzXIidC9RNv/4v4nX1+hNfzaEr0j+Lri1rGKXMlXAh0V/A1pe6AUPrtfC2v/C/wz8bQjvCvwj6Ag+vrRarBnXLxMEhd3v4ZCXhP0BT6/7I+zegrRO6iUb3xkLP+18X8t8tf5UhLxPq54LvxCNf4j4Q3xPWmveD9rFr66BGPvH/CoR8SscQ690L+FNUBuBv8NV6J1YIvzwtUKq/WvddiFriZeGPjK9F6JqXVd6+vif7XoqEd6axfL4KP2ilV4RE3iS/r10B7D3UvSMsWqXXu0J69f/CKxdQUInXzfBFCXoXljl1jCffF1UEfgm+GvQa9Dq98MVxa1Xr17+6N4nELX/KiP4G4IK9YcJ8i9vuWtV98smzy5KF9WICFC3CbpGTqEa9DOrhyEqgs69YCIFPXBAh/b/m4le+ZXrTmyMhLSq/W5ruK8FrRn/Vzo9XPBFrB4EOnVj5VevX/cREZKL/Gzyy1xlF//38Orr4muT9DO+GM7D8IcIfHyCF3l/koLdJeryaxODarVUR4MKufq3hXXCGX/9X8GoIfAwgr7k6Ga7Qh/1/fo//1/WIJ4jeP1xUnCkKiliuWfi/G71V+vsDCCQm6rxgr46qmrQU8R8G4LwSdVZ19eOJ2+VE/WKor+TXr/z17f8uI1zVxkK8QidQ5deYR8R4aovSYjXLNi/ny13UX1J1o3fa/+T9X6iUV5McWua+f5PJ+fHEtteEPhI6L1cMQj61P9cRO+9by+iPXOCIyrvWE/fd13Ed6vLXWPzbC0lB8T1ynIPhJ/y8mIWQQv3Xci+IBEZ945rxAlEYc2u0Z/1euW38/UvWhPdM3RPRidAg9fWbu8Yr1iFMQa+EfDZvBGORe8PhRe8IhBG77Xvtev0Xpzs8M1y1z0hCERyl3EL3QCKavjER6rCRUdiqNXu5/EL5ETun6/j0dvAvdXGQtjERnGMQqOMU1v7GK/yIn/lV8cr16r+bdHf54duIqohXv0WvluxOW5JeSTiUIf5FexCI8QuORbF8T3F9fX1q+OW3UTV6va/h1/1V1iaEvNic/oV41y1+r92r991c19Xzer/P1o7938SuVXEyeiPDPwld9p9339/f9/c3ozQU/BB82CjiFgQvn+XBdg8+f4EH5/j4AAAQuQZogL8ApS+IixCxa+Ogq5b5YQEL8qDlfKr9RKvNzL31VwgrwRWEctgQd8vctcqM83o7nzK/sk6+JVrXxPy2KXqIV4V5UJzxODnVBv11oSv5aG+utCaFLiCaELiFricYh160kVve+boGNerkvicv/E/xdcvQHn1+BB6+dYtfr+tr5oUELJy3XdBvNXJxK9iCf1f4mhBPgcfgJH4DB/q6+roTXuvVf4L9X/fh/9+BBNJyVgQRq9C7/q4ml8b8Wj9VdVNEWhP9c691GrlrkhNXxqj7WlXhVcx8Siy8FmsCn6AedGquvHpe8tYvdfVitY/r9epcI6LmMbKP6P8JVidZP6J6qAQobQjtrwtCPCPxuv6EI5ciFk5MYipZVf0T4RonVyzZKO/zeCZI3a4e9LCFdaERzrupEWLwkW6B/1T2hLdA/CPRK9W1WFa9WE0veDsNLF8TNyoZ63/CNxff34hHu9a+EUXv16rAwa4Yqtemy/0I73q1rpEf5PkXqq6yfClH7+uW/Rfe697a98vhXJz9P0fqv+NRHOoKMcQj3p/o14RueuRBPsQTiF+EVqTC2sE30ojE0bKS/5EKeTA5G31aO9YaJ5Kv5Kv1JJuvfa9fa9XavVxaF91XgqHeGmsXhL9o3rwIAehE7I8Qwzn69Cr/BV2Bu9hnfF9F/FeFCq3WtRFFL10MQ41L4hS/grL4fZr311+EfgiFXVKxL6J369+i+rlXqXg2oW+q9f9X7E6Xh6TmrhbwhhDiPjESLGLy+K/vDixxC++IXu667pUeKfi+wiu1yeqXX4xClrwoboNCtcIwdF6rwmvDeuCIEVV31guWqVcCGCn1Rkq5K9Xa/rlV/lX/y/P4HYCr4J/Qv1+xKE9v9e/Xr9f1wpCP/JiFsUvcZdfWvRfH+JCHy1z/lNqvBaIVqwtrkxC+H6vVgELAu+CYZ8qvdRNYU3Q/4c1jxv0i95K9VA52/hiEe1eb16PwiEvDIQroEWqq/tIj1U/6vJxGKJ8ul9daK/kq/QR9RvhAvQ8N9dL4uT16X1ff8J/jkT188TvEeiPjiXI1UDM1X9clkBBQ4hd+6XKQcSMq5WWbu/BSGFy8GYeov/69fLM/4R4hCf4hcQt3xFQkveEdcUhHXQrN+ruXude6ZV98vk+TWI2v0XNeCkdrBH1fwShBa+KXroJ6x2QQpeuWn/CfIiPiF75aBvReuwzqh2+S8GQjwUVzFejP+t/VCX81a+1byZuI+FER/hD4YrnVvmiee66GK7QuIWvlrmuTv75dUTurkuXv6fFKsYTfEK1ELiFV3L3L3q/2r/LVz3XLz/LDHy3x/q/3HCiTZFEyL575ZBinIpUGfl+EO+pevr6+vrxC/f39/fd9d/iFk6gj+9Y37wxl+sEmJ+CX4Q+sMZvjPlwXYf+EPiPjPgk+EPiPjPj4AAARfQZpAL8ApwhYTXxDDWqgx9e+T5OpurXuq674lXlfLyiF/RH/V/mXoaXLoS5Nyov5OeudCOiOXFLJ1XP1JNy1gS+/6uNlfzK//6I/6/hLlschN69W18T8sTYVr01xuKJxC3y4gnqL+VDGupuqReruqmu+hCL8Suf4lf1gQev+wGDt/o3QpxNr+KoTQt6xde/XqwjXq5f74lCOxCvGLviF+EawO6xi+qutroaK+bqEPmWL5qfxt8u/6Xgh1gR/g566+gEGN3VQtCNdDELd6ELYpYixdE6/Xr5V6vU6lv4ZXMYwkuNjEJSy+EQRm3cyKtAKH1S90CrX760TvCv2RXPF+gII/oVWLr6ifBDvh1Hy8HIKFi8FIifmhTjbrRq+EZLhWR3/pI/qyasIH+bwoRWvku4WQyOdgW6LHP1l4PK++XwLousCCPQl/CIle8Mj17yOqDYT8IbwU9bjM2Owt6JnlqJV/m+J7htF74Ri8+q7y0Oa+li6iFe9MQfd93J6P3iRav1/LXLL6I/gYPRAl4Y+br/zfPRu+CiEeNq4K0PykqGevqvDFeqgQViq4pdTehGV1SN18vVr/rX6sHHwfeq7iu2kV+ohX8Pb6V/k+eqEhu8XXvtF/0OAg+HdaoT159cOQqvhhe+CC8NZa1aI1BMbVa1f8Ehnfc0uCH1f0r+Dur7pQLP817+er/av45K/4KNa6q/2CPqrF5Kv19aJ19ovY4lerLV/jdewtVgRdeCMWq17wsJXpOEvFYRHIl6XCH3r3xa91F9/xXxkvoTmiLCNGfvr0R+ojwUfDUE+7u7u7a4bBWChXxRPUvhoIIrNcOgcQ8rvlQh/sEnVf9C/T+FPU98T8T0B2Ax/CUiwQ9CXPCoKJeEIUqFEbvhXFL3L3zWSjtEcT4n+CTu7nyIjyezO+vV/mV69Fc1wRaK/g9BD4GQFEvF1zL/r+JRurdF72L8bV4Y5MciXn2T4j9Ce/8mIfiRi94ZCVYktZaFRd/0r/q+/1fHKk5WT5Tq5LjHXo/KtQv5qI98qO/pq821CoxXq+WbjLxPo+e7n5Pm/QjqsJilfHE38ZviVeSvwUh5F7sBFgg6Avh5e7BnXu7Xugyq9H/iiYaELE5tl8SdWpCbv6gjEPd7En08P0fXLyZfYNxSKdPnXu7XuhB6x1cvDQnqEUTKsCOO1+i94dC1Xo3dlr3ovd96L1ClNiGIp8jFYjCfJIMW0ohf1bfEcuhFY32BMCl8qEZ8YorsfOuV0939j9U8gxFPldIMRF/f39P3PBAuI9a90X1y2Gf+MRmnxC9DPyXXaqX8N/ifI7yiFebReotF7pH76r74I/qtHtVlxtX3ff99/fV/WhD/E9S9cghbu5KiaXxMP1333ff3xHfp/d3fYKj6v8QuIX55Lvv7+u+bT36X9f/MhDkEX3vL94j/PhLL9YQ/z4FjiOfBhh76PBPN9Yjfy4SzfJ8QI5cGWH/iPl+L+T4n4I/iPl+L+T4n46AAAESUGaYC/AKsIQKFEL4oQTVdViFpfEQTcqCb/LfKiZXzq8dy1gVf6t8vyzc38EHobaudXsv/6NVZa5fJ8/9cv39I3fLfS9dST3E/Lr/EE2vllrV4U5UfPGehNfraTlrCPXXYhfnQQ6uWrj8QvUTfr3ye0vfIveP9Av9LVaP1cqv6L8vcN1g/+BL9gMmr1svUUjd8kJiEWqiaEI96ExdavIIWTlr0Z9VU+MX8upl93Ci98iJ3QR+FtL/wuRF76viawZ0XPWPHd/f4PT676xGELlxCI/l/iL4n5ef4v50e+EUcPmWzHbb/geWid0AUEKL7wKK8HvELWxHhH5/hH4R/oR3vXEYohXjFfP8M78SCopb38QiPWGv6lV2GPf3E6/Q6YhO42uN1y1PiaCbz4mveCDP4IhTv3+ZXrnXvC2sGvpBhCXyev/o8bXgn/SteNo3eP+E/gpq5XDK91iO73d74Y/SROocSIe/eiRYok2biVi79v8I8f3yXfxKP0Vuivaxl1c90bohd3XKhD0q5vTRe0vanSsonfy1vXdc9WBp9/X2hPgkoX3i9clZSeCgFEI/Jx98EK9r+sOa5IldhrL3eBY9fZxSEP3avefe699r1evfKvRGX5aE98SiRfonVzIQ8I/8cgylU6/DiM/wWfBB8NfBNQom71qI8witfdeiOWueKRYvBO1i32EHar/BYRWPlRHxxJffz5Of55MW0V/hHGxJIR+wZ0bvmp6QKx2NnLguvHjdU9IRl4ZCKJ3wgiPCNQhjkL9iCe/v6vVevT8n6Fx4ji/ibw2vCUwi95f48LCoIlfXDYJdjiU68GUEfVeVV4CH/oz3XY5fiuJ+J+CRCX6htEf0f4msvxP0/Ian8LQlUl3P8Iz3EIvd6tEXBDXEVUShD+6v16oGo7rGDPmV/jlfHEpN4K/gVQQ/gjrq9WF69Va/rDT9UJfww/C3rnzUR6f8JfYpYiuti58aK6ByGKaz/hshCKv5rsIlV75t/+M5f/17ymqp/GfFUd5aj0I7rRWOpEXq4usRX/2r2/4R4heri/iPlq/vvYhf96K8ry8EhHvKOC/2t1fT9aFPXOvTYcy1DKKnvE1y8WEPiEWKTaV/J9ut6O8I/MIWS7xSyZd+iPWEt7ZTbv7qvrvKXoKpC+0uEuv/CAjXgUvh7jFHfWxCtV4FX4LR3gpCHgjCC90BLEdaJ3la97S/1zavDX33NdVXZf9f17iF6/BEd37+CKiP8qMxVAZh+1+82aohCX6RlfGLSKIX0EF6n/V6M/Wr0KVdR8ohH6Ax4VELIKXELEDib1Ui94nVCc6/ROpdyIj1y9z+j/KivKMW9CCXjlP7ddcsl8/KrwQl//uu6pEeX+r7+uQct/1fHLf55V1q/yq94FLJbEoTnvnrlgsrk5fli++riBC4hcQuu4qCz5MKf5sKdfz0CjBr9v+/nrmr65sFWC75vn+Dv5vn+F4AAAETUGagC/AKeviIlfFxAhYTELHL+L5Yj0HH/X/yVcV8klS1yrVcvy36v82v1/8yv3DC9CfL8sKcqJ1er3y6/+VXlf6L0QIV/LXLdAJHfwpy/or9cZ6P/oTXq9akw3Qjt/ycTikZ4hZHy8n3l9Av2KRXWyq9cqv86v4PfgT694FPjFxQp8RxKE9FXOvX8lRNv58QuOII98ar/PXqW8P/k+Tf18nX168FOxiKej1xa1v+vX3iPg3+Dk/zo3fGIjwj6GvVdiFxS0v/i5b1qS07rr1ei//1gWBq6+E1MvGI5rLIuApQ4iR3YDl+Dtb/xCM/Yjwj8J17x9erk91esM9/0MRR32YxKKenAshREi33r1ZN4EPl/4KdBB4RuWUQheIWThH9C38I+mJ/WquJlwplfzb5oIEKffcUIu+76wdC1euIXqf9UC8ShddBET06y60T0mNr2u/wzRe/RIrvm4EJBKOQj9c/cI998I9wj9Udhs8ozIRMleiV+tXujuX9egx338v6vXLS/+dFl9+nv5Kp+pupJOE/KdCe+Xwv7g/XvG1eqDFF7xnzfpCOvgsQjoRqHcYh98Qt3BX8WvXQY7/Qmvh74pG7enovTrx3++5sEuu+piitV1+JiLvu+qvrXurROrnlw6SrhnsL/EfEfCHoEOuHIS9BFOp1+Cr4LPgqx0wrrsIAwxRPhD7C1XfR6vEeK6qtfl/kwY/DL+zCt3WGF4e12r/avdfyy8b7dcPdSfEfoX0r+GISqEFKr4nELVyd/f2tXXf89Vo8efEDyCFrJ10BBFdBj4SEGJe/h8t3d1wh4Y40hQ6fN4RDIIyVWx4HEF8Ruv+oI0V8ZOEqqXL4yjd4Yr3XWFcuDjCNXVRO/+tE7EE933fej92t83wgrxBPrf/wiCT4iuVCnKwjLqvtghvux+r+ON83oIfCCK/oFi86r/oBogTe4zvXuiEloR6Ea9ehnwSF1X3fJxCN33JxN2EMRj/hsZ4GEKVhsREZ/x/SCnWrMYqv4Q1Qteb5t6Fr7X9E/r8M/HNH701eTEYX/5ZKpf9XXo7dixPXPhwf8st3XJVBvr+658vwShTwUhiqBD6+j0IfyYcELJxKK3y93L4Ls+Xd+9VoRmKGIgRXTjIq3dU4JO75+r+Vely/n+XwpQnvDFXr1zYpWfDfw2vBWMX/h8cvSL+xCjqqrV4d/5ZLnq4jt6oTRtV6E1+iV0AhHWCw6JmPdFzHf0691r3yL36J3QRr3XWHaE9XCG/8QuIX4ivRv3uv4d5cQsohHiuT5EI6trqb5q5L5F7uLL3feXu7uTr6+5e5Fe+J/V6FK+p+tXmGIXjwxyRuJoj+Jq/6vd/ehT/aKx2C/JyK91aviier60R/nlr6+9FevVlXH9aK/XdSq/6M98TBD9cs3yXKhT9/fJ394hZvl9Xgp+I+fDH+K+SwJGIoGGCv5cIb+J+S/vmrgs+I+J+Df4j4n4VgAAABChBmqAvwCfiFjRC4hbELCK+IggX8I9IOP8lckTy/LEP5v16H8I79C2m50K68DpifV6uIV+9XraluPpf44l36iaXxq+L3V8UvxCJ+E6iUV4gcQbeT1tF+ghVcSvfE4he4R716/kuEO71828N+uW8GqxyP51XLG64nrBnkuGkboWGIXe+WEqj65cQtcnxOMQr3y16949VtVQP/X1o9fQIrvv8T8fa+EfA9ggRe8f8HvwIfwJPfzQjy4hcYikItJcuv7wQ17X/ia94RxfE/onVxK5/hEEnd8lUcqt4Ekq5eBXHeDv4EHT+rxNGi8P7r6+vqkW9YEf4HEFAIy7vn8MBGsm8Id/oKahKotD+n4le18bvieO/X6v4KK+8Gwj5kS+OVnf9b1y6++gESJRe+KRX7Asn8edF7y19dD/Q/06J3YNw/4KaK/VY4hkxd+tXqusVvBwDpBB+uEK64tBXsYuq5Ve/Xo3L14L9VJ3oc9VSxUub/W8vEkPu+utn+NRfda90LoneCDQohfEa4rwhWLGSiUjSrS9NL3RaJFqtfNRn+CiFLgr7/lQvq4R+Xwl8JUXvCFXdHDCy/WrfEaxV6FdJ3+hHUv75fkqtF7r/RXr174muWu5H+vYon430E/gp7Br7CfwcDK4muFIT4YoXFyJfDXsML0uSra0TXolXgQdYGrjEMC/z9Ac/grku/5Vjbvm7/BwEN16viiS/2r1YPSS+vvifiV7f18Sjv8EnlybBXfHQjUMI3YhFxC4xb0/hTrvHUXuqXr2u9Hjz+CEQq71QR9z9fghFK+/CRFfw8TWKCoPwWL3oJfJWqvhFTS519v4MwQ+HwQ9hDdxPxMvHYol+J1syL36J3hMvyLlDHL8b8bfr1+hLRD8IwQiL3Z+ryYujP9Ajqq3l2/B38M7wKAyuW6vrR3PBEP/V/i/i69F6GbiJaQ5COnuJnwiGKwyrsDGEOgi7v7irwQfiKEK/k8d6CfxSqyg575uesm64TX8v1xUguPG8MrifwSir33cyj8EZN3JiTFZLP/Rv1hN9g7Sv6Fq/YX9/gg9wQTV3QGcDB1o/dKvdMf5KxVlr0lAno74omGBCxOWhH5MRXqX39oz3gXAv8/USvar+pUJOncX0OCPm+OfgoXgbAUVgePxN4LRi96XjD1XMMRWvF4N+dhRMJck3xi+I6AoBDwUJBHMfol8Yr3rb8CoL7CXwQbX9WD8IIr96/6BJrB/WLEL8Z4K3r45fxfLfHwqIW/ra+SsI7xOWwI+azel6EfFfEUbuvr8DYGb5KELJssSIR5OLhgQpyPkRX/V4r0b/fLevjv64jkq5oy+CDli/j+X5cQuIX7+/vu+/7iO4d+L+8IfWfEa+XXX8+CD/PYLsN/F/WEN/Lm38+BwxHy3w58X8vxHxHz/BD8X8vxHxHz/HwAAAA5dBmsAvwChegTNEiFUYIVzDFF3gkX8K2BSCSFv3ffL6tXL8vcXIOW9ZSQTF///R7/KvXcTXPr7+XqVCnxivU3JFfXE676wNuub5vkh/0Ef1i6J14mryiFru/Qx/iV7qNxC3cRXSxVcId/hvJgIGiufKr1xKL8ri1fwZ1fXfiFhblhXn/rl+0TPiFt/q/xNb3yL3j9YRr3QOd8SvVxOOJd8USXOD/WJ+BJr3YCzL80J+hr4hGci/hPte+dbMSSPtfCamX4F2r9AJn4PfYC79/cT4RSJ3QE8T19axSYKfYH0I9/Xr9HfG75eCUMVn1f37f4TELNywnggLl+EIQjb+EPCohCnqgU+w+JRe7m+KVz2vCLqvr6/tF6TCeuP8GGxxBDT+B4/r2/gyhA8P/FoMd+i3hNefWWh3e2rfa9v5f5PV671VV13zob3V9a91S9PjdcR4W1xHhDT+DCFahGvRarDW8Z+IReqnBHd+eMpl6u1/3Ed6HMd5uqrFVj/cm697r6sWWuXxP56xdC+mwdBiEuMk4YXqwpugl76yVeIWnCwJrtV1Wt4MS6FOU8Pu/ld30MUe+x4K+/xervu/BDrDAivV/tX7GBqT175V6YbFoi3jWr/F0l67Aph9dXxEMV+Gc3ouafnIIVVX6ufOr/LriOsP/CXXBTgoI93d3uVjtYLKKx4QC6pVwLYJ5KmQh/1/fr/pgjxESfFz3zeP1hD5KvCYhcQs1aLUb2vVxGr+ue+vNQx/1/WFTK+sHIc0V/ByCFXb/RWfEoz16v316/6hDqNqwXhvoHesXQlvZfGUTr9e3/ClSTV9cX5N78GYYVzwz7Bj71eupOauf4i8Jm61d4j4Q+I9Cfijebb54tcpNP069f53hIQr1/QpbqSTkrDmJte9CG716O50XJ0uJXvPxxLteGRXhkNfEVisnoT/xuGBC9cq4jkp/wS3ffe/6EXlGIwaZf51Ze7m9C/ePKuX69eBoBN06udAduMRHtiFxxPvCNFfWEf4fC3kCFc9cQvfS/nxWEFxHF13hHfJ8iEdfgjPu7/ol6GK+f9b+BCE938yLG1/FCF+O6hpXxiJ75J+VH6qqHa1aXE7+SpOuq0Iik7Xv17q++sNCYgUS+onr+e7MJm9Xgvqfqrv65apXxinIt1yClieJgw7+/uuxBHfd+IXELiEKXzxF3L1Bn9YY/zYWz/4Mv89gowX/4Y38f8t8Gnx/wc/H/HwAAAEYEGa4C/AKeIWEvQaeCBf0X/5awR0d9f3y1yoY9c6v86/n5KXJor1cQbu75fl+X5eomqlkwINEevV9fMivCPLCeEKE9IKWT65ZfQrvk6iLt7++VFeqlriflV6wFLvmhH0WNHej2lru+udBDvly///4on41ffE9wjJvW19L1UDHL1WhKP/+qA0rsCT7ehCM/mhH0NaKXxK9EVr6b0bu5fRMcTv8qI2IX4teocS/frfwE/6roL1rr6CNe6kXuwc1i7/CPf6L1LvlwY/G6wd/B24TT/XNiFfy0//iUXqwjRdSWETL0vonojAgJfY4nnwip7Xbb/gQRIIy7vkqk9LAS/9e8CikTvpWri0Tqw1kqKVzqVe61KnhveBBotYucvy8CCCLwuEkbvDtZSC2FG+hPiZuX5Yr5MP/O0E+/X3z/rFT5IIPgg8G7Rpffgg/Er1VoWxVgS65jt+ye77Mde1WGNYZa97/rFEcHUK+r1wj+tXcKouUXY//fdc6CD/Kr76lV5OJvv9CdeCgR8smer+WveWvfG9QS9BLVfV169XBkhnQmOhN867hterhcx93WGl0HPjv66ifQQffgdF9ol/tX+1/Ngg9Oisda+OsEnVWOxwYVjoICli7CAQVqyfJkxvoEYd+WqhlHf00d+tf9fVfoR1cKQpwQav93YFChddtK/QKtWl9r2OJ+RWOQIzaq/3JyAkEKu+IUleC3WHvggy7Mr9VPy/FS0ejv1wxxat3D+IX4Y/Re76vXq4pe+T9Fjzl+Gf/krnoYhApv0D/4WN5oJDO728EYWscQqvjZVd4MQ+iMeYeiPuv6/kX9cv6v8qvfKCIXWv/0T/qvXhZ+EtVaJ+Faq70Xr0kXr5Ply//Ez8TXN8lV+2CMRqr/ICHqr3o3zL/4jxIQ8FJvBuJ6AYYEHuEFY7Wqte+X26sWDnsV6hle+l7xwnxVH68dRM9cEcL5fxEj7uX1aXCKRe8Gffv4T/VVdUClIZ+bKPV+gRUV+tUqjEUmc65F8qvJQkM9fVeeiePCXzJF79ehcYusUsnUxf69C4utnu7t5eCQde7y4qrHgy98tfXfFVzonartXvlrClX8le9Jf/S/rCYzwyEOwEaCqIO8Lvk1ehCyYR+EaEvfEIQVK8El76v/tCMpFfF3zoT1UCldfi9Yz4JoJC7vlrwfdd8mC0MeFwhI+TiH/4rDN/f3ycQv/16uuw0O1yxi6/BJe7mToBDLwEwVCK/W9YID9WhJF9ctOidegRYheoIMYp7/iFWMVL8lXJ6v0zq9XPb3F4d/9He8TRHvCH50R6W19gJ83g41uvd14Qqx11UvV/LQpEeIXqdX6nk58UQtJe607vrn6nV6wWFV0O/eXeJyXaN0l6L3er3Wr93Lc3f8k336vd908P/X39dyfE3L8vyoYxiFxC/LPV9339+IVdra/+b5Ie+8n+IX8+GP8I/Lgsw99Hgrv4j5cMb+EPkwUYf+X4j4j4Q+CP5fiPiPhD46AAAAP0QZsAL8AqIhYgQs/oFjwSXzL4ml896cTcRL6CNdxNcvy9gIWtd8q+ZYoK+eTl+fFIzZrrvRXrml4tX11ova6++XA+9fomXzQmIQmKFEPXr+fDPX932X//qNQQ9jF3xBPxOMV3k2l6uSrAl7GI72qp64noDX8GPwc/+rrioIfRal1XtfonS8T/1P8er+hK9XE/o166Re+Re+r4hE75tf36L3z/E9fQ/dg59+3+FRCO7ELHUWiN8kmGNcI41Hcy/A4sEd78x4HUML3gS6t4EsUvdgMnfo3ugb/BaL6Ak1c6nXvDNYteLq3i/h/0BVPXoTviVfoIIhU8M/CW3/nYXh9eXNfWF/tILRviev5ETfXBJRLv1xVK+MWxXr7xzXqwb/Am0XzrRW8n5PJRnnX6KdKy0TvBdXv1i/UqeSid5O/gwhbjflrje4Rit0JasJZLeb6XxPqhnfKCHu/fKilTrvl8/x41X8T8T8arwrXvhFF6sIUfvGccQwrv4jv4KIS9CTJ8qs+GUbv6uGULYrCGMxeTJQW6xS44mnTr6+wYBhH7Ti8M96v0/r6c/LINjZFnhmtpX8ECCnQj6Lf4QQTr4JMXLInyIj/BUvdQQK9VD1+tdcSXwgrwW5e0OfGKr+DH4fq/y95Lv8GHugSVXfT4FTpfr1/92MUe8VPl3869XLfSF9O/4S4tEeThlFehxPqqKxRMlaLHn4TIIVa8JXWtVCddq/hk3mXhCYRd9bBK73d/NeB1aEv8G6sfEy8t8vUENYIq5VhP+v+gS0Vqx2n/CdwhQhbFEtL1qsRXqyaXyzpLHjpOJn4muHPDJ1c+0T/y1QTo3UOJ8dqoakyazZMU9/wj6PUnFTYj7+EKP3kXX4nPllNu/BGvDd934T9ZDKuWtf/q+v/DX4lW+K+K8nrQl+kerBiE+5ZVdwIfiPl+MonpH/Cq/m/oNeuuVCWv0KzpV/VcmnfOiekwl9Fl5K4irARYItWL/grBAixU99er0XpH/C3q8o5H1jF+K5vCtEe14mCXu5Sj+Mm8o7d01lBDt3yyaXpoT14Ogt8IoqdaiVTLyojVj/gzCCL3hcdd/ao3T+j/3/DPJXJ1URQYEVgwJ+hF/tX61Mv5QSd3MiqX5cCBjPD3wh8Vqte7AjhLvXpNhLL/945FxYhTU8ny1fFbXgoFw0v77iKkvr5t//L9onfLVCK90I1YZov/lrnrifAr8UuIRnNUtX1fBBhPFCFr69FOuStEe7A/BlXi+f5/lRWkv91eX1eHe4v/uuuq65L+/5flxCxPf3BN8Z8v1YnPgq6/nwIH+fBVh74wTDtff9/XE/EfLguw/8d83xHxHwSfHfN8R8R8fAAAA9pBmyAvwCoCFmXx9L49AoYn9Xov/EcEdc/dd/aE1XLNciL1VEVcl8tfXKtfLKIVVxC9BRy3yonTDle9cnddKivT5vul/J8nKv+o1XMcT/4HHr+GRyE3hW4lCO717vV+4lEOncq5fP8uIWSq/WpMI5BCPiFqgY6wZawIPwKeFBCLN62hMcTo7dQijPiFxxPuob+L9CV9iFvde6hDr8FP5lKngl3xco4heV0Bz7X4SEKegYv+v1ffwyi5fKuYxi8vARNXdgO9K7wc/BrXt/oj/q6rA4ie1+5MEPX/sR1Or9Qyi71sMfEeJ/oR3R69teBUzsOwuMQWvH2C3WEa9v+qBAXzDPwRGd+/xCp0+I+IrBSf9C5/k/ROvL9166Ajqq1fsBLg4Wf58Yq9WEtYNgdQ36FxVbDEZy1X19UgoRPlWKulY+dWPuTE5t0fvEu8M74R6CPwlvg4hPhlCfQt1JyodW++r1fwEcK8JfVFesIKXf3XvHurAnhfxGi//069DWPEKTgihKoQWq4Q+EFbdVopG/Vuh2OeEDNIQ/QLz9d4PnWCuhDHgpX34Q1iPh7ev68qfa+P179fdrePSL/GxKs6lRO/Xv174Won9f/whCa4Q/j1fX/xatE3o8ed/oQ8vJ0BBGK/hIQr+I/EfEeJHfEIneQci98eCPqr+Hwir+FwjiiegmkIeuXGL7vV5LAiAXe/oSesMPoEP4SrheHy//oa0/E+jfNXLdASwxXoIPXIjv1GVw5+jv2AxwX+CUFPXfLJqr+MdV9fi/XZ3h30JrXwQr2/58EIYRGHsWR3e7u/Ccd3fd3f8l+jP3PJyq/z/Or3RgXeBCBp0GvjOuV/0f8vP8/jNv9er1/8CDDPotTVKrdTr02svX6GP19zy+i/rCwnHE3xROMV7G1n/nrDHHEI254uinTW4d+DEEHgrBB8VIv0d/n3/DIhXPZSIkryVzH6JfsIe9a/Fk3fd0uTL3deCju+759fEr0+mj9l//8IarVscprtjF9iiegFeCZX8G4e8N/KFl6hSyZf6L+3/DnJNyfIjMk7UydSrf5URiyfpfGaEv4j0KrlpZcxHffKr/ov/kX/cMfEL0mDWv/RetEfyVftFXoni9/w0v4j6wjXrubuvk03ES7WT717r6NRO716vX911X8/z/av6d398Vg2PBFlfuhPiWpevqVEfvXu9Tr66WCrq+OJEjy3hI/esVX9LN6v3cghTkdcvJBJ3F/Lc/U/xP3iF+8Quvn+e+/u+4Kfi/vEf5sIa+bAhcQs+CjBH8X9YQ38/ERHy4KMEnxfy/P8R8FPxfy/P8R8fAAAA8BBm0AvwCrr4m18Xr+Cm+hiCyxTd/LS+JQpiXpF75KqReqoiuRWt/9dcvzVy/Kr2/mgs7q+ri/ibt69e6de+RerkvlV7EL8taKrzdK8P+hdorlk9DH7icYr3+J+f4nELfr11JWC/fLVRtaor+DVa5fwc/B3gv7V/lxS+hfxK5dATxfxe/ut/kWV8ngn+H+v7EK6wIde8omsPjqwd/iUMzEMVx1zVxHYIffRf/0EWfFrl8Lgku7vljkXkq4FGuXsLLzLjBCJ3QH31r3XeCcT4fEr36lTxe8FOq1f4nGzznxiIMsjJ4Mwgid8f4nXAkZ2GYJ7D+1+g13y/CHggrF+jX+T5egr8F2q0J98iK3QFUT8n6J7wj97xvwT/BT+G/jNc/8VWEJeq9r4PocwpQ2KJy7+TZflpcmgsxLS+CcTLYF11hHJv4IRHUEdWG/gk+Shvef8HEE/fUvVVoqHPfPV+r+sGAr1Qnq382rte+19Pi+67+N8noEdDe664WhL16ThCWwhpfFLFE6hLqtVXSd8vhZIZn/RH6A3tFfwXm+cE5HfrVjoED6oh3f1qx4IBCsdPrwXVc14VUvonrx9F75V68GINJeEEXoZFEPJxV+uafEgjBaRVq97ngmICaqrWt9dfaHoz3QYGeYQitrHfw9vCH4pXxqqnXwUdV1VjoDWCG+Xp5OX4vE6THE+vN1/8PwTc+vCP2TqT8End3O4vqSlhsIdVoQ/Ud/WHxyK+T0sBc/0VnQEECD1X2jP9q/YJ11q9cSivXMi9dwYo3Zf/0V/EYIH5tehNeEvoqJPN4JO7ufEIiZcM/ZvZFY1Qe90E6FPWqvfIi92BZq91q/hgR86E/rCHfjteifriUTrx1H/War2LYSdoeT/3EoNuV6EVE12vnr0K79e+Ve8KlReqw5xxC38x5OTpgrV5MPhbwuEvCYS9KvXvZkV4IL0XL4iuTXEOhEq8Ed3d8fkzLqfXLVLqfqWstffr14SEr+l/WIFr1cnhH48R4ZHL1eid+vRB3gk9Hv+t9fCD7v9GehiIXDLxijDXMa5YS8CkJBCJd+LsExfEJerkRu6i7wiruGARFd/sYqxisLr4j0l/eq/xxCalrh0v/8l6FtWJr+ukT9v0JWL1QjqXEev17uVYvlv5e5Kq6/lV8QQsgxXqq4JcK0d5i/3/y/U/zX/L9oQ9c1XFK/X8tXLEXwQ/H1ycvc/V9eIX5ZO+77v5+77++Cb/EY76wl/mxHX8+BA182C7Bf/iN/PUMRHy4KsGnz/EfBz8/xHx8AAAANvQZtgL8ApwhYsQgUOCsv/LxXL8s9xFboW8RxPy/L8993yQVctc69dxa9XLGcSr/Kr5f69F/fKveBR9xKuQX19a18t86N2IWxRJqO4S7+5UWLw3Xr6vlviV6uJ8CD8Cjguq1euJ3/8Sr+BJ/ErK7lV3xe/kpfXh/4Z+GTfN6r1aE3gzo+XyW/zBJ7wU0DPXNr/9BPt4MuufCJC8x/p8DnWQS1qveC/4IRNejRdgdxKxeG5Lv8FI2sXVzz0Tqw77Az0V/VerifD4JkXvD4IETvDO8CABCzsMwT4d3zoMe+VdeBGEonUOU1L/CHxXi65KuC+p0RdBDwQ/VHfxItH6XF0K7y17Xhf2/QEv4ZoT6hxCPWuJmXpODyCj65fuqnv65q5flv1+8v5UT32veXJT1iev8QhIXWXFKsV38FkLXSLUJVLfJVX19lP1+DL1Ih3+4iu6y9fd2Bla988mK1z+qFvVBOvW/4JtzdV036U2D81YMqHP5NYIh32ivJ3VVfExGEtv+H/Q+PPoXr/zGkXCFozHhmr9fig15d8iI/hQFiLzOuNA8h9X8F4ZlJ9f/foR1aaP/oFwN/16TGewIff8P2TP1Qokaa+SvRHPtX8EoS8Xv0R8UT8iv83goo76wV/wWhf516bBN3/8UvT3e/4cfm+n6+XP4oTe978FIgFhN3vd3+1+OJu+7u/wR+wINWL5/nkqFvnoUQipf4xHQNq9XkwzriUbqz0euvxfX9W+//EYewjQnxfhgY7+7rm7flXEV3SI9V1yq/tq/6v0hKJ3yVYFmhPXwgr+b80/F1hEV2AqwUeMCEubvxNDnhrjEE3iPW83y4E4J9BYvUqseWrlWFPf40X8cvdwlrnhnqLVzEIj+e6AuhhH74Q9myfr/36M8r/gg4j9FvS5OsFghevAU3fE9UA2gW+HIKbvu+78c83o2W/v6tX7v4IKEK1GKk/hkd8t8/zIQ8Q/1eGBCPXEK9L+MX6FZeBl32i9Va1XSvXq/eiv3oj96v1F9asS8v6K/U8U/4IaG+tF/VhHL3LjslxPcT3F/aFP8va9/dK/er/PV3E3JT34KevrEL7EIidO5+/ufwEAJpf/P9yd933f2rffd98RgwoX0FPz4jXy4IOv58FXf8+CrBV82I389xER8uCjBX8T8/xHwYfE/P8R8fAAAADkEGbgC/AKGviYPl/El//QaYxyu3c8nL8s1gQffVzfJJcTXL8voSr/L4FXIviIL/1ySzV9/YFvPy1cb+r0OJv86vWBX/FQV8Sva/Xq9ESpXCvfq/xC01lpe/Xq6vmlqN60d/iV/jidzfCNq/UX4L8E1CM+6+6de9iV74v/5/1zFP4tE75V6t/ZPKTqFPpE6uI8FPf9jEJv83UEPhXjiT0foCr617XwQoIVBTxHSEeF/qh/UX/wIFHfOSe4xV7oBihBX6BZUjdB70SiOdX1rFWFaxeCkT4LxPgnPJhnfOuvhQEJ3fIvwIYY8Pj8UT1/BxnYTgl9BRvB3rZ+wel+IRH/ROpYGzEeBtCSv4HtK/gYslT9aPFWWvfr3nybfj692Bp+Cf0CkENiF60SL4Ry//wU3oZ18lXF/Fosf5/ifl13LLy+986E9LuvVxcj8K4KfIRJL0zrFpfq42TlvkV/uuRevbXvlk3Re970EV741Cf9QuivJwUQT4LT/IghV14xRPEdxiux4O9c6teTqqdFfrVjx35a6RO+Re675axvwvxseqXxwQX5J66gg9c0/OiV4YCnh4qI/X1av3f6K/gpN8Vr5ATiK1Vd/RNXt/Mr/FeMCGNiTSRGrVCHqgr+/k/XlXnrjf0Xrx+9P5/huCznBJ1WqwiZEe9E/X98PeBNBaj94PQR+CkEPX19aM/QLslB4GPX0vl3k0/0M/DixnQZ6L8WTd7u/BX8FK8M2Td7+W+VCOl4lFevV/1ei//Mjs6+tX6YvyfNX/kq/yq9up9Ey+kV/kkoEQHHpYe9CbntRF0gg/fXr+tP5ZcS0XvCvxW6/dWquQcSIcRdrcEde8NhL4per16tGR+quGBhLv8khfQj9Hik5EK/P39gjFbvlJg0G9z9uhPqsGZF61+vULl5FvgUATKzFEmpwIFW/qwFWFu9e7Cle+EPkRuriVeHhSK0uRHsRVhAQCIjvvXav0AyCIndRdcqIlXBhV/CdHvWVdpIndUvpPRfyDFxfCnxF3xXNDg4h774jX6Wz1ardCH+q2kSLGK0/zfN+CG779dZa9V6v+r/q9VorzDkS/f9q/V1eivjCXrGIjtJ6vBZer9av8i/lvBDd9u++Xv769XvToct75Ynlgp5Z72Md/f8vy0IX58Qvz0IRHiF6+vr6+v7++7+/tXgs+fEf4Q+bBBgqEwXzYjfx/y4IMFnxHx/wY/EfH/HwAAA35Bm6AvwCuiFgkX8SX/+TlQe+Scs1Tdc1RP4I+7tNywX869jle+vib4nELLer1cQv69XkqJ6/iUV6FEwZP+uL6i64n55KiOtG7qTpvr+I76f/6P+uJ9CVfwe17wJ9e7AU/v21xUEvq0nNL/z1xP6v4bfxOMRF7GK8X2r+69+vfMtWv16+5OJrYQp/wS81bEL31S/Re+IXsUSqL//jZ5mVxis+6AbNZP4LxS+8N1y8GP1X2/n/+RE+eD0J9gdxfQEer9YISO+/XiifBH6As/VH+fE0tguiK4/oN9rwIEEuTW2reBD9AvrHPHifFtfb+0TrXEd6a9rhD6B2I619dAWRPX0+OJX2KJ6P6q6AlrwukJ72FfBjscQQ0/wJEOaob1Zpe7l9Xk50FGwgo61f0/ff3869r/HKmN/9SpJhSvfLVCaP3VIvdfX1+FvhJ/r7sDKEeze/x/f94Ini9ypr+ExS/FQr8voQ+OJVO+i3gsJXaLypdr2/kXv17qe+X5fnlGx+Ksnwcgyhe9E6P8wita+EiCWmlV/9SYFE3g/4hDBCS4NvQ8R0b4OhWOJFdG/lJd8vLO//BeDi6XGx87Qr6M0X6Ex5+wUmrVVVXvZrx1ar5KAijuv4IPNBCKVVvXNXHa1Ag0L/4IQ3+hHfq/UYv6sNkk5l6sOvwaaybwW/huCiu71eqwUF1VVXf4TRK+T9EeXBF8P65UJ51rRH8UVe767X/6/+0X90H90CX0tHYQcOegzUYvBb8Nogrd+77uTlRn+lebFZKj0PT1S+KcnoR+sn1BQe7u996p4bELP6P4ibr9BJ79fy4boveEat4R1koveEkr6/sYpdTp7eKJrDYWXvDYY8GYQ8Rd369Vfr6+uh7DNXv8L8kq9UOyl8EQh945MvvXXr7BGM3fvpX/V/AiBFX8CIE0XrxCvFj7wh1/8uIR7wiTwqlf5In0KeGuRBH8RmEIQ7xNepd1IMRnv9rWucCATGISEXp0I6DjBDd9zxVel9EexCLjFH2SReZbYjeqh6EFc9DPBqqL//3bu/tUZ8ctpq0N6Gi//361Llq8i/QjKIf816v199XCGORKVL1e+IV5RiK0lQf9FSLyV6tfq1fNyRH3zy8kn+Dr/LfBP9+hjRfx3f2hTfcFXx3+EP8Z9YOvrPYIsEfziYLYn4v5Plvgk+EPi/k+Cn4Q+L+T4+AAAAPOQZvAL8AoK+dAiYhEQsy+NrA4/ARfV/QhYLC//y8s/ov/1fqI/X/cV3dcvy/1xN9K/gddcsFvavJcSuXzq9u0J6ub5KrXr5PqSo1X/RX61ervT+sUGVxN8T8mIQhxHEfUqX0J7wInr617r66Ow3BEv6wl+aXmQcevRay//CPzonYhWcUT8b4NSr3gS/z/e+5K5KqEuvsC/71imrRcuh5/BUK/X3wQoIZQTXNQhBFLzL36t8l4YCK98SivhFHmS23/wONGmugIq6+vsEI6ukbugJ4Z/WL9YvEfBDXt/GL1YMhOMV6+JMW942UdyMp0g5WEPwYQSWKy4JaJ3ixK+8K/nX36J3xCvv4Q+IRIvhj4yeqQlutEbo7XvD+l/Xy6FVxPwNELCCFl9CerZ16b1bXky/8t+ICG77uubfz12iPLxNdoXG8fUqVjQT+LDfia94mveJr1cbdQuj11C2d9fwpzda+/X0X65RFXNy3VdV1SFP1q/Ravff6+/Uqr4m8X8XrhVDcv16sFLhQQv6IdKsHuEF8KIr+CkT/WP3y6+VDH8EPX6I/f4JC64jvnRe+wRXfel/8qJ18qL1Za9Xr3oL+WhvdfxCN0LDEW1X32vT+i5p+JRv+CALWqLXqFewXkV+wJYQV+4j8wiqrwYBMtV3zeUQi/xsoXOUf4Z8NhOT0K7rvnV/lRXrUEImte9jETsUS/174UR2OgctE74fgm43yUR/DCl5fBGGCdVvUd6kQp6odRXriPYYRe8Fvw2P38I3Uk1wIPwhVQmvVidP+CZ+NgkGvd/eRAoEPd3d3TL4KCO+77eF1rB3fwipvRP/r/4iX0d+9F3ScXT/vlRu+fp8n6/6K9v9BB4f9Bu5XgnFbu7veb+5UKY8LaqVXuwPY5cu9XrZvPRe6Bj69a34U1yK/WrlWCkLov9fq9afz1hEd0BbDnwlLgoAgw7ghoXHr1aTwQjN3rzS13fydUq0PRot/1noX3690/VdVruN6+tf9ap1qf4RxRNYXMrnhEIePEVzozybVWDGhMoe5JFl8vgkvvCP/0If5cYoM7LJV4lcv0Uy/BR+SuRG7r6kXrqGMYju3UEGIVq8F2MxC4hfYq+ZGeccj+htesXYT+G69XVriNCMtYPBH33iMlAnq+mp9Hfv7+5kT/xSt81XqxQ5ffP08EuEaFv4bq8uX9K8noc8t9dyDlpqv7++W/rgo+b5fmGLSJ8t1F4hEPkQv3P2jN9+Agn9939/cEPzfL/ic31hb/GfWDjv+CT5vjP8Rv4v5Pgj+b4Q+L+T4I/m+EPi/k+PgAAAOjQZvgL8Aoi+eBGL//NUvXLyfJZfr9B55uWuWrj6fPwY1qlTXy6/l5orBj7uqA2651ToJ+hOeFPRvRFctX8TQxXvXSJ3zfJ+vdwoyu+UQrq4nr6+vr69fCMI+hLwljnIIJ+RCOxRPzS8/xfz+D1VgRe/67X2OJjt8R8yv8698y91HdaxXxdjiF11E+CbT/QS1BJYrfN814V9gp0X//wMAv7QXv4CBrK7Az+0li+NrBH8N/DNG7wz8L6wn6B36/174YWsYrvXBN8VT+CiCXYjsCiMxCKXOBv6rpWOgfn9vX/xKJ1rgk1Onigh8Zen2Al13L8/6L7wv8Njegc0buvS4IPhDWCv4f9gnB3jiHL66+tYvCHf8I8REaESVCsQ8RibGIdeXDPf38+v/lkXo983xPyoe75PFUTq2607oHPqWrBmWn/CtxXej9CnoY9er9wnLZBCv2F/Q/8svL+j9XKvfEr1br32vdUvYolry9aE93PT/hLi6wLvGeqqq243pW8JsERtVfxb/Qhz5ZaAw6oOehfwdULbwUVY1Xojnyq/ygiu+9UExCJ1U65fKvXyycFaF10X4yvdr5R2d4SELVAKHfKrRHo8ecn1/w2Qyqq/BNVVrXLuI+fw6rx4Q9hDfiu8GILgUfPrmQj/sd8NI743JibL/+v+gKoJ/lQh+gj/X9ct86L1DYn/SWGdXFond/iv6CXQnXfPCNBjNxfyoIvfNXo369X+HkX/2iuVU6I/Vq0Xk92j9QthLULfCHoM3r/woM3fd3fd9vkF3fd/tdgzq/WifriV79WX686N6Ev19fr9zeL7u7u/HH7rvXvk+C+FvifQn8TzS11qgl1Nbrwr8WTxfxvxFC38ZxxCf3hwtcl5/hUVXJ8V39AwovezQ96E5q9XifMEt3Kl+rCAvwsfxartF7517y1frR36+gZVcmw2MX/hMISdoz/r/w3RegnvBCV3fVP9arB98DkXGIQ5lH60qriYzX2sXhisX61J6/q5cnul/1yIr4xbGMW3xC140Zfo35LhFe7/l+fvhrkQt5BxN6y5sT+TuT5K5EMirte6CNF7q77XvTsUvzoj/G1URjFviicQt3P89VEy3/o7wvokvoS0mXEV36GP3PNRX8T3J88nq5YpbuqEIr6+vvgs+uX7+/nk7IEnfiFrv7xC4hcQqxikxzGLfvVsYt8QuIXGLbvk+C/5cIb+SuN+8GWCz5MIZPhH6wI2C34j4R+C/4j4R+MgAAA3RBmgAvwCjL4nX8UIWIXxKBQ0GJf/75/k775flQvvlV5LkX/zVyfMbu5KiVeS4T6Bj+WCjVF6bliF1E4hGdXXXVd8l31y/99YEFQUiiF616flXvlXvifjUTv/k+eT/pe6iFerikWLV/V+IXqX5a41e1/4Ef1CPxcEmKy+vv16qC+ue+J+J8CO9dxHgReIWtr6rBOJov//hf0BV3694X0vicv/+sFPxbGehXiJOI/QT6JfEdcknN4I/9YX2Nc9jt8eCO93MirgUxnuuYrGd+Dnr4n614IfYCBFzL/47FE/FLYrBiDJYvhKuCpBLoT5kEcv/niaFYvCuX13NcIdcYjd8l+vSX96E+7de8ut0TroCj8EYlCYvDderH6f6N0JilxiP9+hHXwlXNKT1+/Qvov0FIvRfte6nXvkRevuuq5Vit8+vdhH0Ch9KhPXn/r1VfRfWveJr11aE9CvSN0uL+LwgT3/llRu8uagPK18/gUK82vCPV0xCv1EddLm18dxl869WfJk+XDNgMn39At9cu6F9FdK/peG6GPfaufKr/q/z+BVFeT8T4R3z/E3jvyy+i+xxIv7wil7434/9Ce+Lqg+4XrqpZ/Rc0Rza/lXCX4T+CDvwZAlBGKqqpUq62IWL4JsbOaCd+E/0IeTkRGP16TCNF6uIR+qg78UEVZ4UaLF8DTC3wjxqM/Qz1q9X/MjPXJ7FK/d3zfr/4Q+Hvb/R3+Nugj7frRP45V74R8MC+4EWuVeqgnR+rgZ4R9elrhD0f2/n+StpDGPBCaS0WIXivxK94T9jwsj3VX4c68bV/H16rZ+2ehuPaHd4Ivkr1cE8LaxJPVf+fJkrkrQx74joGYhH7qvGu8RocTfEE/q942r44l7edVhkLIveGREr/Q54W1n9BePG+go9dm7vWXLquE0Xq5PDZkJaTQIfgj9gkX9iiTWqAr+nXOeFfhH4kML3qjf61/+v5K+gSQREWvoS5ZPiBRB8/ictPd7/8MaL/L6FZfq/gaa5Kq5wF1wgrwfp/BJ+I1y3JxPxHWitLgUctAX/WjPilhgYQfp0T4mohE6L5Pmm9Cn+5OTqI68cTeTiOuCAQrhTu61/+v7+TkWKr/1eTARmCP4T7n0X5bGIVb5cQsFH+Kwl8/zYQ4jnsHHvnoEmCv4j59Zq+uauCz4j5/g5+I+f4XgAAA9hBmiAvwCp4CBxGB56/18+v8YgUX/VoKi//z3ExHoa/U3VG7uuauVXu4nqSrm64IfQt/1/CF/f8/zzdIY/er1cZIuJ6a/1L1+Diiv0qv03BNkV8mKXuIr19JdycSjd8vz39XNfNv9H/XLVxN19fT6+LhT0XoTFE4xCF9fNJ2iv8X8X8T0B99fUyxfLW696Nr5l7qEuuvXtf3cTOPYbqtfglubT/r4jqO+IqwcpBhzsQN3+veCj8KgkLu+WNVnW6ASPXW8G2viF7x1e8HNe8bRHrCOsE49E7wQpexxK/6B/6+l18dWxfwyhJ142UVmRB8RiifhiG+O8EHwpVpVzaI1WI36J7oG4nwSj1bw2JVvu9iV8ocQjPXwRauENYpcEfoC/67xuQUQvgjrF/4YJ1DaLF8Qr9KvdF7XwThJ73vqEeZDe+OnuO/+N8KqI9CWJBCyadaWuI8JEHPRqv7fHHXsYuq07qJXvBgJ8LUXq4uTFl1+vZyFXzq0tD+dji8I+hffIj9Jwl8JddUH9bKi91OvV6tMsIUpC/fLoUzfyq9doz12r9RsuHCeqP/sFYxf969l/vnr198q96r7sC2LrNoUT4/8vyovYmLFYUvQQ9i2EaReLXrsBQ9cO12CEbVdaS1FamJqqwu58FehiHCtugXUd3YkQit4MByt0BCCCseCQM1k/QIzaryr6+K7X2IX0l90BHIvvlkGxacXzK8KVCfX8lYI8vJL6LHiFzBZa97x+8EISrJBQM1VVVX6wQkVd+/uZX+J14NaO/wQIv/YI/ifia9CP1X88lQd/kGquy//7wVQY4T+/k4nwxXox1iH4Vy8leCgRVVVVv+CUmq1W+6kl6E/kX9XBAva/833RXr1ehxDXnS2vqj91BSvdBqveNaPXhOid8DPCXV6wjWj++ym3dVX0Qm7n9E572Xw1V+oY+TxFFf9XmoJ0fuoTkfOoI935/hD2f5/hmEu0Tr+FL6rn5fEeg/8b6+4EDX698ivECiX4VHb+GPHfdehgUsR6E5oz0Es9pbnXqxwkxd34PB/hg/hLNcI9aE5fEm7uhCI/Ymuyl3fjwh4R65uhSyc3w+hVkLfdS0/WOwNRcQvygkLu99dwtVAdAy7vraXuomvXPNUMdaLF8OeBhN4bNv/rh/4TXN9SVcnyXejZV6v9q8l9cyviFxC4hbvh/lj+RfHyInV6LFV8myLn+757v717v+X5FeauH/qr6+uEbRe+Wr6+vr60IbrsQvyzXw99YINfCXyYazf4KN3y2BA4hZ7BFhf5PhL73i/lr65r4Y+T4S+O+CT5PhL474WgAAAPHQZpAL8AqQhYOC//1zoOfvlX/UtXFr+W5F75K9X+Re6kk5fl7jflruuWDC2Veq9E7voQru9X383ydzK/er5f/69F57uWTl+laFuZFaPXN/r1c2KJkqTqpOdE6hSv41E7X61r/XydgcxsnQIiu/3cIfIvSev75V70X5/nXLX/xcEoon5Pmqu+a/Xt9xa9XL8/y169jFX1clcnyL3cEHzeJr2+apOJ+JRe8F/oDf+GUEKhTiIrmnuI769D+1yze2vdAv6r/pfV+LIcnrGTzqMWQxqcf4FEEG/BTXXgxGLXg5+DneH6EOa+bzkWNXFL8vjPiPqn/4MwWfDSL3wQQx6t1HfET8i9Kur+XGLfwY6sEJe/oGP2JVq4j5kTq4R6kV/lXq1XuwEmXv+0f1UBP9E9fUT4f+Cf4Ia94Jfhv478Idx+v4U4WxBCO65bhFC+r0Tv16Z4Q2hTXUvV9d+CLu/VxPhkSry4zJ6P7yj1bxtfS4vi368oRkwcFrCGE+O+K+K/jNeif60RCHkq+pbqP6kxxN8YS0VPAnepui0XuqV+te6XqvterTvte+19+veN/P8uX/+F7D5UP7qVG6sL0Xv17qLVrri12C+hD+F30C8TVX1o3+pfllwjR3scSXo/4RX9Ycoj337LXKvfOveWvfKvfKi99IvVz+CFQp69WCMvxPyq94T12i989euURhgwIarv4UFVxdUtUBdCiJ3Toz+CWqVdVT+P/EfEfDHwTY2cmIu9jfuTl/Qrv179F74muVH7yfCHxwV+F17FsLE/QjzyV1c8IcK9gs+HPxyCL9wgrHxW39XrCYYBFqt8n1gy/sirugjkwW/BaG/BSGUJaSq/RHrnV6wplxuEueR/wj6F3rl+foHcgrd9W+76LVjrV/mRH/X/6/l4tF74rzBNX8U6wMwIEJdVBX0E9eiPeF6J2v/j9Vit8F8LbwhjJLvq9Gf5FYqpu5ZKv6XrxtCe8fpfy4vXE3kFK9cIdgJkHC93rFWT8IwsKR4S++wSBDd30/Er3z/Ki9+uYrCaQnq4tG9+vfKr6/ReoW9lcT6E1hPWCEKVhXXPBBXGerH0rFDER76+HMIKWi2/6WE4rwIBVidLN8hvJXq016r0U6zv7ruMXvhLGLfwIpFeauS4jELDtaP0XyROPyVfc/fVydRKGf+JviK5leq4LtJWL7l9c9Vct/Vq/Us98RSEK8FPoQ8T8/f33eMRLYxEviFxC4hfvu+/77vv+4K/mrr5sJdfz4IPkwY/E/OIgviPlwWYK/ifiPn+DD4n4j5/j4AAAA2tBmmAvwCtYHHBgX/+Qcg0KNoupKqIXv1f9XnqJV/Ag+4uFOSFKVW8GYiuS+SR/KiP89CFdc8tavE13gQfUTjEVL8Em1dTL++aqmluEa4v9G6QYr36+q+b5EX/yfIvdRF1zLiff8J+i9HevT+jd8ncV31c18XiEJH/eN+L13+Dvv+hCEOvXvkXviK9F74jwW6uLm4K0OyhLio7mrEZfQ/sYou3onxHs/0veFz9hnXoS/w+ufwNZVk/gSanT4UWL9E7yfBTV+gOvr6CXwv8E/w78P6S+iddQj1ouvBh/RarhiH/Xv0TpMIcv82CMmsEI60dzXFRKJH11XQCJL0DirnhkbJ6N36+dAQQTL3X8vhmvRFgY/ZBq94n8n69WGPy3hrT/zsNwoIWM9BRpPRDIq4NKN3mIjXl5eotHb7XuoRVm1/qPV5PRO9ul8vyovvl7i0dvAoE7Ynv7E5u163X52GYS4SQSimoMqrCeb16XSugUev5Ym4jwp8IJCmIvF/u1/Z3hM6H/rXYGf1y3xnPXftgjCG71fav9oj/KiviiVWDASr+C70ICHUv2CM+qv7OiPjiS+/2vffSEVV6qr+e+fWE/8J42LXoWEL3z9r6MwREV2t/XxVYkvQIdeCWq6r3/IIVfgp+BuBWCOtbHWv6qTwkIXsYpMTqNnVMug389VJ4QycTYzDzI/g8/Da9jib9gdcJc9il74S+uX5ER/k7mvwVdVqtV38hkZ/NX/xCvJx3jQt7SEuVxfWjflrRf1o/gn+Efy/Ivu3+BDQ7oJuIQX90iozy7J83yIQ/6I8nove698RNWhL3YPxPf0/UM3iWiZY2JZ+7J6DnJ6r/wT/daGRVQVr3X+v5MLmRe8b1+reL1xvQgOdX1LXLNgjBh4ZC1UCf3r3X8KwT/fYsVu+7teG9dmPe60uinR++RE7y+gU+te6CPwUUJ/0CLjiEV6ELb7/CIqvX+IW61f4UV4KPvlRMlXAQQn9b6+El7xyV/Ile60TrsN+/v2vyCEJ8MisYvviETvkX9ClcFv4xRXe1ya94NKxfq/eviR/r/uLV/nu5+1X/6vvv+Sr4MfWp71ea+uVeu5Vf5av76u/ARB8QsGvxPLiFxC/LiF+XELiF+7vg0+8If5q4r4NPrHb+Wvriflwxgv+X4/4NPl+P+PgAAA55BmoAvwClr4uJwEDicBE4M7iUHu+X+uWaoiqiOsxd313y1gQf+uMqri177gk5J+REeX16QQsnJ1fzfr3gzEovVX3ViFdaovOlgn5f/eCHVfy7o3SDkT6qkRXn564n5UR/ASP5fnXute9lXv16RfyCEd1ur3g17/hl/FRObQolX6J3yfq9c3QKcvL4GP8T8ai5fGr3svgRV6fYRGL2+TugvWKrQYWLV8t88r/MOe8I1EIJ9Fc03IvV69JzSUDsT1o3da910/0JZjtmdRjF/OgFXXvByEtYZ6ueF1WCH4dEouU2T4f65PX/XXH1wh4NAlCXEfNE4a169LWiNJ4I6rpklxkX0HhHV9C2jd4SrG+J+PVkmF94uid+ryYZH/PJi+viqws6qClCerj16E/xi8onByCpCbqx1alyVeqEZeWtOuRBBvDf4nXK9civNyKVK4iXPrF/CoYRekEEOfAmIX5VbGLf4peuwW6of/kyV6Nue7KE77qtCmPHdeHKuariqVcUuX36r3QPzy+i95/t/CPnDOJiU+g3WKwnxa9WG/61VdYrXqdIugdibsG5b7Q7q58USvi/Bc0J7ww+oe+IX/jQR+EuT6/++0I7pL7XvTk26w/8vxYmF65L6yYvmQTZfgiHO92O5Vf4v5fCARQv3wihDnjQj4EIGMnJ8Yr/BEj/+G1d7LjiCNfKr9TfLXL8TWj3gu34JDLX6Fr6wt+aP4tD3sYhFjGKQjc+Etvwx6DCK+uCTk4ihxCcvhbwQ/LR3/V71Rv36vXo/6w8/Ddcvl8N0Vt/oJdCQhD74mEfR70utCn9tXrBehPSdpr4K10BDJWfv9Gf9X+Zf09iutiPi/P+0d/G0WWNnou+0If1X/3JYIQZ+GN1r3wkvb+D+ExCLfy5MIVcRQPQh2BVJ39uvd69Q4kT/WIRCZyVesIb4zw6HPBmHl74UrH9/BXC3wjpSehWU+GRX6E+8el68m9C0VybEiPDI5e+X5+vq7f8Ldwh6nSTA9CUTvBkJXMYxQZbIyjXOw0sWEFAf3FDL2+n1wpGu7+/rRGK9e/V69H73V7GLYxivGxCroDWO6+tEcy//xD/hb4UL/y38Zr5feSusJHXqqXvX/2qVEEK8Qvf3EK8tWr2MW9P+FhCuFLS7/tXruu5alXuvrnuJV5xiq9v+F/hT4W7nwYYX/x3EcJfLiv82Cjr+ewbe+fBhgs+TW/n+avrmwYYLfn+f4Ovn+f4XgAAAA2lBmqAvwClL4mJELEr4usD7sv/2CMNO+0G/Iid3Ed12/eiv+r1yWu4m8FOCnkrSrkiKiZBCEOXmrDNH/8nfJg9or/3g16/h/0Xonmrk+TuIQjscTf9el4v4vuFZX/I/pFel9L+/m4RhX16bm/RerFbqaqCWsPfDH5upJML0K7wU/F16uJ/+JvBj8CH8CvrBG66Xvk8STsBEhFF75l75lKnh/XPVh0M2/4fxWbWq+texC6+KrLvC/XEhD8IgkPu74tWdeBL+EQl5kvdAn9g799dIR3QEn0/S9P0svEo/d/6LfEKIHAR+veSvf2lwbwS9V1VjV8f86M3gpfy1oT8tVOiRfDQIrv3xivVYIa91rXYZ9heveE6xeEaK3xN5nXE+EfxEmTT/hLmlELXS9fHYyJl9XEy11hOhHV6GZXcsQ/pHq1S6J2m6iV6l4yvfLfoT1b3na9+vQxx0r4a69De8XvG+/yUSpf7VGbwn7pCGrSl5VerhVX7pXuwxVjwJHwp9a579F98vpr18vj/veFf6G9WKwidi6Ot7od0J9/fUqEOS43vBbApfBwJ66S4IOv8cTqqivFV/2BDr0nLS/XvlrcEgnVf/FQp2vVcJwpUyI/kJ+CIjvvLwn8L+BcBf5oIarvXEL/0I+KxkSvGq9ghqvxr9on/nRO/X8u3IIiRvcaob8VcKilu4+FMMNWK5fivYqsDYGVfw4fq0KYrm6/1/4VMr/DlC2LL6b4Z60ZjsF/vX/f1av0q/qmGeguI6EOR/Anw56E9HL/5Lwp+b4pBB+oQqg/Xqwj8XocQ+vGrxdH7y0V/Nq+uJ/X/6/6E5X/BD6I0uIy130hT9ovXVB/8vuhPe69IsV8cSr4ol/CXhReEjovfr/HEiu2KIRv694kLVsReDAfBH6J0vSEfvzd33ForlLpPuupkXq9F95/i/uid8er9BH4j5NDkWkUYq2+fxfGEhEqi2LxHv7HT8ShHQl6FvG5cThCiHS8DUJRH18RruJ+EEWJ19Yu1WXzInfr1cslcoxHd8cvJ1wSiN/z2sFWCLvvqvx/pl70bPJUsZfiFh7lhP15UWrnuVeiBiEnyKhCEHwghf0V69X64Kv+viMQvf3/SHP9QIPxPy4IvrPhLiFnwXYKvifn+I+XBhgr+J+f4j4MPifn+I+PgAAAM9QZrAL8AqohZsDjkELBhcqDXSctCEQhEvor/q9YIfg9y0AhfUmT1//wb/l7iUToJeSuSbkWPNcT8Sr/KryLm17XNr1YZz4O9fd6K5t/hTpHeNxYiJ5v8v//yW/i/vuLoUT8Shj9RP3dRVUH9c0lcmClITl+r/PBBmzeievmkw2de8K7++J9i1y+JXvR/1vVSdwx3VcixeCl/EdfX1F3o9cMwrzdTSciO1aERGTL6N3xHxSL3zXYEEb8i94EA6Lli/MeBjSmboBF17wchDwIIpZeDf4OV4MXe1XoV0uHvX4e0JQRFGFlyVXMhXfMvS6o/UutW/VonBb8CiPRH8Ki19+vq3ROpfq2vmWL4xYvHjpdV6TDoR89fdAQxat1rF19fXqvRe6DO6An4e9Has2Qnttf83/dcqCXavjV75UXqwhXtfr3QGVVUk/LXKj9Pn44n3x+K1CXFR3o/RT/+wSjEktJLeJXzq+KU5HcV1qx1ku/J+l39ZK9fMi98y+y/X69MKJT5fQCR4XY5/vf/qFeLvCtBupeeJou8G4n0/G0EHvlri/idf+BqF1sIfJXH/OivrXV70/0Tr7+5Bsb74uFBC1evQpyUtlrxpUZ/Z74RXtYKxYFYGa9vAndXK2a9JXxs/Iu9hOTJQx/tXkx/9F79F6sEPwT4U9ehe/quqRm6/iPDHwKwT8TrkvGrwR/hyXtX9uXl8EgXrE68Ehlr7OwRwmIWriZ/QS6MGIUDEXnvpWJKXXN+GPsnzeFRHl1z3lN8J1k9g599aViiS5sDXQu9cGsE2KydfoY/XItLXtL694EcMb/RW8P6xO+NRXuvwgv1f5fDGTCoqhxDe+PhW4uUYhbTEnrHn9DOmwRPCCpZ+2222mmgkoK3LApv2+8vlwjri5KhibaR3ov/6Lrxo6uIQh/iF72JhP0JeNfrN6N0q8FH9a8BBCfiQSXfMiquJhLWJCP5BQIrvxz2aTdcqqNkqboGFFrGIofZZsYjX/VvObGLz1fdwjXNBYv9cIfxaNFe38i/ku+vvq+MuIV7vRWgn6kvq+TucUTHcR3EQZ/V339X3wIfy4Iuv58FnELB18+sR8usGnz/EfBz8/xHx8AAAA4lBmuAvwCqCFg+5Z7AQP5Pk6kQcfw/l5bwd65YKeTEL+vfJ8kQvnXpvV7wU0V2X5uZfBfXv1/Jgv3YH337f4buaf17uTwh+b6rm/+WqiEbprhderiV7X+v1fX+IV3tIv7uEOgSBDpnxiitu+97f8Mej/n4iTJq0qur9CO6m6m+bwv1/XrXxeMRffErmNf+F65Vg94hf0bq6XpaB7mwj8GAI4X5PmlwlkzfXyat5OT9F7w/8J5vQmnXAQNXeBRCHgjomXQGMV7S+rBfxi436Ed4b9AQ/WvdfX5RKL13JeCDCvr1ei9/Mt6R68dW/xyI/pecner99X/E0MRFTKMUuJVwYn+fyiVb4lffOvq4levirr/Rut/SEv4MRaK3xMvLMvdG6GBBMvSGtPl16GV4j9IYxVa91aLl9r0vL8T8T4It1/LjiQvVHHy79CerL9V9I/CPz5cVhIQhd8Vv/Fdci9J69a+0TX3Iuu60Mel8v2rycvxK1+XqqwLlX8HXuI+1esVX9L5f194INcsRhfVcJegymToCCWvQrprZV9EYvW6GP+rxFw/8/sXvLiOvqENLgZOlDHrl89fHitctevqwj+JXvj/i9foW0LDETU2N3zr19z7oS9ehz3j/i4s+77v4msFZewGqM8IMENVW/6N+q8cSveB1EeDOhL+CUMq70N6k6F+tCHr175fnl4hHaFLnRek55d19J6vEfVTq/2jPXGKx8d8d4Y+DjJQbo365vifBUkXv0X/6vddVJ0tdo3/b8d+I6hmFV8Sj9v+L9FefMl+rwSGVd/mV/AoikZ65a25a/C+sXrhGvRX8vCMSMeou/b9eKIIfxPT+Q/QR+ENevfJT+BJhbnieavRek9Xr0MeTl6lmqJRevH/dH6sjV9f0KJ7rrVzwt8IfEfVXocTc8JhL4638LwqIWT0JToRr+hHqy7+d/oR13Esrv6FaoJ16qBuKV64iqh6QUQqXCKrEpX8eErFLb/gi5a9WvqtPwIzVjwFQJROxizL1xcNfFAi7vfXDkyy+OV3Rq15a91q93GxGDn8Z8RY4m/z4pbwYYJ/v17yV72Req9Eeq5fRXq/uuq674hf4xFsYxbkR69DXq8I+hD1fLUvur/dVE1fp+NxBKn9FaQYrT96K8Futcvy/L8vy/LiF+e+eKELBl82CDfyYKMV81gwwV/LggyfHfLfBZ8T8d8GPxPx3x8AAAA6NBmwAvwCrL46DHkil8t4HDPUR8n/UnVfJI243rBf6i0HHrlghsV747nV9ffgIDiER1xavdOr/J1XcVNxf/aLVgI/3oS53oj/Ewt6E9Phbd8VyfJXN3MhGruEV7qE17EL8TL/evVydwoixd8nonfr3f3ffDHo/ScQvTW6943+vqHE+mHI3vk/vBDq9Frq/lxxPvhHwe/Ah17sBb0Tvlxi39k9rrV+vr+boH/r6/B966sBT4fxXy++TVH9J6N74j5PmqwJomi//+GdcIoT4xezFveBRqdPhjsDrVvDFaqgMf4muRCO8brCNXOgj8Ma4va8b6o/VQIrFu+FPQz2IWIww/+9HrytWiF1E3g3P0BRP1ol5OW1x0lUF+T20viPvvBq6wM4IewEaF+/ta9G6kuX19fVoveCnCV1EcVfoT2NlDTLZS1onSYiYZe/A0UY6i7193L8tdzcqvNn1f3ob3ar3eid4n5cRhDCXJiEeagiXw/R6i8fl6QQf01fuP+0T8nP1COKJ8FDV8cQ4SvQ8i/+W+WTE19WgvWgvd8LWCPVgnXhLJ6FvFdIRV/+uXcinWfaJ/EL8qI9c942hr1gyDHhz19ARwjJsl+je+JXpOCfoC7QuchL0K613oT1Xr3XX1jPUTFWJ/SK3bHAi7u1YToY9c9v50V/n/V+gbApV/iN/J6oj+PHfFeHwTeDsCzVXXLdFE4hb4uhsWbCp4RwxX1yWPxVRVLDnVm/nvjCCHfiF7Y6sGwvoINX7/0T9cyvXor/G+CjXF/r+qFm+168lf3Uf1ovdcKrktek+/vE0foqgXd9/yU/bBIMaa2Lq1eT1j/N9L3hPQ4m/mr1Z6O/0i5/hH0/NlxFE6HPl9CX91elk8R9XoKPLX1av11tI/eHdYn4mi9WEK95vj/sd1NebILycdvDYS6Arhz4j4+GPmxGXLl+6uXlRstcVrlfJXF3iA5XoTnocSemUuEQkveerw78T6N1dr1dI/vpEan8RWDii9rl/A7CcYiDPn1wjBQsb44Et33fj/GIkXxV1a9Imr6qGEV/BsvjEd8Qry//ojfGfGQQery4zNpzVfy2qiNG6ueqnkqWhSuS0bvQnxiFsQuIWSgFxXob1r1f9X/V43u+7rQj/yq/X9K0T6vddc8gxCTkUdhz4R66S6/qql6vr6/km7++770EHgmELCHzV+CDJ94e6/nwVfWfBFhv4/4v5fiPlwRYc+P+L+X4j4Ifj/i/l+I+PgAAADtEGbIC/AKqviIJ9UEr169N6M83on6uSfAQmZ/IvfIvVURXJLYCb0vib5YfxWX0XquSnydc39ckRUahHUIVIlx3ejvXIvfJ1ESCCfQmCzmRnl9F6epevsB6++716T0V6X6v+r2MVX6hHVcT6CK/+EYdsJZbFZea+VE7HE++KxRPzLG8fuoRxyE3kwc/B3ugS69CPa5JPH9b6L3QEH13xK9+vVwnBNqvXWvfHKnSXwgvvG0TrwjoSQSPfikVnwJNEzHg5DyxSYLf6I9c3QE8/hujReE6xWv/CtH7wn+b46hbEJ6hHwSidV1XsYvNCHo7Sdk6q6lRLdAbfV9AmfhMb49oj/KveLr3xOuEurAjhD42TG/CutpCevPQr2OJXqxNYvC/wR/By/Bv8E/J/X4Judh2EhCz6Hb343pAm6u+pfpn3ctAz1YE3Iu55OX5UX3gjCPjzoreNq3j/6IVPEvzusYrdfnYdhQYh164Ur1avXvbjL5+/0Ev36vWDj4JKK3SFda/61/04ISO/FdSfaO32idWWilRlsC6Fe/vXu+srXt18K9wji9dgkqtX+xZNVWq33avJ2r/q9cvz/CKseDAXWb0CgLeCYSCQTqv6yi/bRn6ZF7r615F7X3yr3yrlO/4UX/VwjxFjFV/D/7BFLR/L2Xy/Hi6GLcxCvwKgI0dz45Ec8Tr1/5RmMRSZzqN5kC/wzjEZJzqlY66qvll9F79Ce+RCO3/D1aO8RyX4IqrWsQvgRKNXgwN8Z8ZWBCDKt8XT/v0b/lHIvfCC/8EPoCyCn4/5utXxxN7tVe6hntAS7f8Mbcd6E1YxGC55HcYiCG2PB+qoHP51exxCf/EfJWC8y98Ui94V+ai/1/Xr2OZabw2cEnVWOgmOvl+J83oI6y6f8KCFifRWiaFZb0EntLLaK+v+gZ1eqvwIYY/QnugWroXrPXr3V/CZKwt6DL6J8ZxRPUXXHL2/DKrBUF4IvU6qy66lu79CjJJyIT119fxfx/wkr9CQl1y5Vi3X/gRdcRiEZ7+q42Ha/iUL6uJ7iboJibuIQjqvRcxS/V/ATwTVjXCYGUNKxrBv1jm+EIpEv4XCC/OgbhasU1YiORH7wWLffiFfQOxnWvQQilmxX4j9ei6wRCHff4349YvnXuun/VhIfV6v3or1z917PL8ghYMN6rX/eid1r+xRLvVX+VXqv5/1eWue6goXXL/1P33ff39/fPXBp9iPx3+bDWvnX8+CrBb83z/EfLgqwXfN8/xHwZ/N8/xHx8AAAA1hBm0AvwCqiFgx5KGIPeieVH75b5bfxF8R3Hd9cnzGNu5KlrAg/Aq65YILJQt5OT5fkr0M6Xml5+5aEKlELiFaXJr9FYvknFItiiS54mHsVRa/lx2hRPyfoZ79eq4Q/pfoveGd7d3DPxO//lxyjnuv1eRfycSvXxMP3xXonfMr/y82viK9CescSf/+LXLx/5UR+gMfr6BN/XvH/m+Re3vEfN4Ld/CwhFjL/Ll9F8SdXxXhf4X+DEL9g5oneGRfhqi9jSXzHgaV4EEV4LfYCXXR0r9fXk9L/69CPeCsX4LReuvwTnXqwY/6qLR+64dxWM5fnqwEufWE8K/L0C2iP4WFfJY4m/xSJ1cV8tUN1ko/VQFnJ6N369WI+Et8FcO+gj0nonX6vP6He+9Xzr7qdfSZXrvvtXrM/JXvlJ3fy/Fr3zyZ6P0vPT/hUQh9+rSbq0T5hl7/Rmlrv0RifAvPwSdXoLeBQDHhJIrFdzei+rFuV/wthvLcXF4Re/q8EZa1RM/Wr3y1y/P1DNZKP1Yeqx+CjWuq/+1/J6N32vVz+WitfKvv17w73/CNwjJxaPXhtQhhAVJURWGzo3a5Px5a7V8Ytv1foFgb6+w6/EGv0J/+ifk1Ru9V6ul76Xv17wzXr4Kt98FOCahPfaI9YwRjFFG3gtEfGa/v0b/zK8mFflo6dE5a6RP9C9cSr4xWox8Wi9+i90wuuVYEoCHCo5dQjtSciMlXBaIqgIYjwXF+Xz/LqrriESvD+TjUV/hWSwW+te665/EUfv17xGH/R3kXpSehDH1J1Vyy8nS1g9CHk1YFU9C3bkuOJNnKnxCua/V65FfyVeTZPDZN8dN8XDd6L02TXoV6l9ScngYi3QEAfr5cv+HBoN/YCqAk9/jKLLxoi7NRH7E+giE+vpLuCZCXyftf65zrrnVOvEojl8V8drmn+Iri4Jape6derpfXgQP631zxGT9KWJggvGI3LwHiBgd3/IsUl6v11fQhFfUJ10CUe77vsUIQxeBN+Bhq/xHfYhfVE/BHadcs/dcT0BfLuvWMr/1en8ter4hUDVdcXLcIKxLWr3XBXeiP3q/evXyy9yXU2AuMoxCzkXg15JKuW+D/5sFHX89g44jg5+IOgvNX1wc/E/B/8T8LQAAADokGbYC/AKV6BE0YviEZ9fUSIXL/xPDPoL/v1/EWKonTck3u01lEIU75JLhCqv5JcGOxCwQUKoItEcnyIIV/fNLYPNcsTejv1Vvrv1a18T8TBNevSiERfS97r3ydA59cnEr3UJ/E/E/EyP6XvaRe6mV+vrMXd0uvX6vfLfCMLDFJR44USrHEJ6+TFE44l+oUQi6+u+JrifAgm8HvsBT/BTqwLP6+S+I/R+pfr1CFdr+E+aE/R2xS1xCEP8nQGH8UrnhNWKJ8L64tCzJi1+PAopE6raV/CKX2uJ17y6oC2J6dCG617r8SKXvhDsDb9k8N6wIP3R+hvkXtfr1+j9Xr1+vSZN19fhMvhMqN7xp/LRmtf16xfq8nL42vebXdrHv8I74j/x9Ce6Ap4Y9evpei14j4rr5PpBDMX2iv7L6dcq98q98q9iiFHO8Sva5bV4vlrHvHEr3hd44n7wjvgSYY9D//FK93Ca5RRf/qTkQSetNX+Ut312rH2vj5V7fxKv5dYCE+qKx4EA3hT4S9jARKVfdIkVUCFaq9FlfLXr7xv0H/E16F+LvDOOwnkwTnk7V/tEeuWuNRW+XsIhHr8IPwWAg18FKEv8vz9fXNyoR3lr3yL1YXwzj8dwl0GRt9VnKrFcvhWr1xtYJhfjsg4hb42UcXIjPhcFap+od6hHsDCHZOX5bsBK/nxvLfBDDW/xcXxHi3fSI/yeBGrWXwZP4zwKYq8ElX828Kjvm+EPHiFfwS/SV/hSr+jk6G69E/I69H7uD1e8Jpegn6RXvoEhFXpVXLgoquq9/mRn8HYhWPJVirP7v6vmRIqwZ+gI/r6/FfFa8EQ9V36rr+0IeufsCSG+ws+vr6E16HfQt5NGy+TvSN0/JNYQoU/QW9H9fXWDsJeOJ0I9fYf/DXiKFvWI0MRRhln617sHL8R8KC7xqRNdAxBFl/gg/54W9XkEK0TiUXpFuIo3is+tUM+fUy+fT/jiFHfJ14j4lFzHxC38RRY/696F2v0Tq4aR3rTmOT2AhQx39d88Oaq/xMvL9/o3tfOjtXo3SUBUaO3gbBK9jEQKKja8YpCJkVeEAQ3vjng7DGuFA76krdX8ZXuw3Xu+hiu1WFglWDA2OW3zfERHPC/LN/xCK94jEWq91LLgyCO+9Cv3yxnxFoSi980FX/SI1/9xlPJ8+BAoS8Fi69dfcRYha5Y74Nfl+bBh1/ECFnxGC35vn1iPlxGC75vn+I+DP5vn+I+PgAAA7tBm4AvwCv4CJw96CVT+vS8ki5NDOn5Zrkrkv1ehyLaSgKP++WFC//SK8fYSxA5CN57iaGIr55BC91+r1oi5dwgr99cR81VyYK698TDHoT1P5l6JvkqkK6/X3UQr44n3UQvT8+KV9Qj4FGvUuXr66/Re/XpK1Ykz9/wTevVydxCEdXMi9VTfEL3i/zSYKxaLleEK94W1gUfQHkqxzqX9G75vm/XuoQ7A6+vv6Qm38EMMej980noT0XdV6EN+reL+GfYEX3oneCH0CnXGoXpVGoofZbJVwQjJcIb0I6A2jfhJBDpaCvw9vBhhJfU/N80bg0yWA7T+PKhbfF+I/Pb+a+b5NVxUmM0vQnr60Ic6GVjnX1rF1yneGfj+vk9ERsur+65ftFa+esFv9UqprtXr1/r4vxH1RIrqdC+8FnxXzZ7gOXeEPCtQxfIhbeGXXrFFE/S68w539V+CQmqvdf3VMvQFtrH+0TpF94pFrBF6+4Y8Zr179e8d+X5UfvK17517x+TP74XsGvxdC6jsIzGvf4I+7tWygkNWrFdrn6/lsUvs/6J+rDQI0V/BtR3eq95FWCisYpf/o3fL8i9e3XKvfq3j9csL3whQQBh5bEu++b5UIe9lrlVz4nGKW2PBcFUV/CXwnrk+Fvhbwcg3RU7vgmBxxyNyqwIPvXpeJ1+vV2j9Cl38XV8IcZ8nl0r4ZBFWvvm8F1X8JBAEt33d3zGIQhuOJJ3dtorPBpVr9G/LhP8GKO3goXhH8Sv/CnvV+whRHmoEgEHqkfvgnha+TlvH0e9Y31IidNqL1qtZV83j1WE1WhyFPS/+Kvm8N/M/N83zfHa9H/V6/qpFesZhV/yv+e4+qjIj53/8svEfr3hNVQN/RvjB1CiaHLfqJXvHUV/HVfxFekx9e8WDL50Euhf5BSC+IWTJrwRCKrw/BCTVfnQ31q9V1XV+MRhlkZdctL4mk8MgQvxHzyc94QURsMfGfCSEvXE9QjC4hYr16uXqdToi4vXatdL8qK/gQPgVhK0qri4hEsYxSWdPjAQkd+OeAiQUXy3torxAhfhDqGO9UqiF7IX57rhblr79Ff1V4jCG+X7RurvwQVbX3riP575Vfq17rV/MqqdXu5lebiMQuMX1jlpVEL86tXNC4hVNiKEvfoj+M+Oq369L6vEVoj1Xa+VXksMVer6GISDVMniK+tEZDXxPxX913/oJPIIXEK9fEYxWmK76vrxCqCfWI+K+L/wUZPkwxgj+I+J+EPgn+I+J+EPgn+I+J+EPhWAAAAEB0GboC/AKSviYlfFTKuK1XyL4+Cb0FP1pT8iFJUuleflrl9O+RF75PAg+4QXuqrQtX8DTqwEj+WsFP5flghx1Hc6HObkq4jvQp6fNrFvmqcQqSXz2v4wci3+VX+WGvQmpPXp9Lxm76r/vk7BPvieonFL8ShnVgT/y4ha6/XqqbJ6r/o/dRnzKxXLfr/4RhXmV4zEZLkr19Y5bS9fEdg31/34M/hlVy+FSr3gx/L7Kid9L1dL0mG8ghfhWG9UJ6f194sRNcQideN+EfhP4TokV5aLt8vwui5jwZ1y8FdcugMI7rX3WpUrBnrLRu+RXPivjNdaJ3YHGsXf4I/gtw9zV6H9J0voipfnQpqwqJ8pUcqdgTx/f2KfifhVona+ib3rgu/hSuVG79e+17X69VAXdYPQuhfeDsP63JQjvC9Y5fr2KIVeDH4K/6CHQTehr7+SXu7l71922pUqgJNX1vE1y/Iva+NRO+fSwhLfL6EVxHYCBDff434T2diSKAvyo/QgX/+b0M6r17r7nRO6kWvlV5FfCKO3f3EdxW/1fwgvlrTn4/xfwb/gbfCGERbFkzkRvXo8v83oQ5eCujP/Ly1y/P4Igj4EgX8IeGwx8V4EgQhrGOkptfCfyoj/cvIvrxesvfhHDOPxuIDHhEM9etiKQl75QRCHSd2PC4vX8nL2BcAh+qv0L1QX/F+DP4EmhL+xKvfgkNqv65flROrte+e+Hd/wzc6E9Jnr1+CQuqvPxCM9VPTwIP8PfAqEBEV33eUIIQx5RSvv9FfxlX8MH7VE75viviLxT/RXqgJOuLluN/ROxCmzkDPWhJ02vwjzxnovonSEk1VV9ffusGnGIgk4+MUPMjHgTRXQTmM01+Jd3/E0X/+/X+vhBe8KmXugIevR+8Ul/5NZqK/hsIq9YU36J/otcvCFHfwtxRO1+FRCyiF9iZvRGiPQoq79e7lV75V/JX4PRSF68mrAo5MEAJLww1esZ8d9Vf9f1i65eEQxv+H8Ia9G9+inV7okVZa9P/gVeT1/liftEvfgjK95lHgoKiv1a+u/t/jVfoMrxGYcS7XnFK/hEMXg6PDV6v6q8lCH8Sr16N17o/eCGsc8X/Uqv19dAI4T4H4uufV/ikS/gUQ94HUPeEBnYRrK6BDu2TVyX1dYMDY5DR3yNqIX4YQj/QIwgr9f3D9a/mzasR70br5br8IUXvv7XpLHtEeq179Xu4nvxCK8UjKfj4ItuX0L/P8lcvKxDv1y6v144lX+Wl8+OV2xi0fiFscoXskdl+Wpe9Ff9Xgn+T/ruI767k5UEGPuXuStXvvELiFxCKam+Cr5Pmw1/mwXdfxn3g6wT/4rfyHQJ5Pn+L+sHWCz4j5/i/gu+I+f4v4yAAADoUGbwC/AKWIQKHGL4hXnXxtr4sEw/d9VYgp5L9Eebl+WuJn5P/lRXoUstAU/gj9RPXDmOoTUTpI3dpL3eidVSIj3yfS9LvX0IWV/SLn7iva6hCuI7iqEK+uTlhzCFDXisVqqv0M75PdY3yL3ghzcWveBB45fZf+JiVi1/d69e6L36vvqle6l6/n+Vfw7hbfovXZq9FXCmKJ9iPjOoWQiL5r4usCD8CH8EPw78GvwI/L//XS9XIvVzL3VVffPDeTJUQhfRHr6/QjvYherCfoGPxte8f6BT664ZMfd4zN8lfG6wQil6t1rwlVirAVYnufv+OQr58d0q94aL1ycbCnoT1P+WgbYrTviq8EpFXVasVYHMX2X2EvZvf0JCvQk699r3uCK774ghHT+asXl8Eg3Vc1YXycv6EdDfCV8MYxBGdquL7qJ5Pk+T6QYYq5+51bweapC+pfG6f183yIvXl1r6qmTwuGUJ6sVrjfCo1e/XvDPFsJE56EqhiXhKSx+r/iohf18vftoWlXlRHvGV6ueudFjHg69xGOIV768GHqKZHfS+foNot9fL8qL335q+qgU/Gbf8LCIn42turuLXgn+Gf6EMrvHIioKb5VeTtX/X/xfxPxN6BghbPGCVj/Goz1iX4QJNxkj/Q7oXwyeS6i6BAChBF/CPwny/LJ10hngl+EfhkTfL1G/KiP4YEor+EiyCifBOOV/DYc8eCNF749Eb9fxHq1neFeeEeT4vq/l+wSlrVV7/aI9YUEYxRR+9Dne/igp4r4MAnfoQ/yVh8d0Dv4jWKoW/lq/p1p1UnjHLwZwlzxW3F9fgh7uz5PoElV2PCJPDpKx9CMvYmub9f9w2r/N4XHVhsZWEvhD59vwXtDe7gouheZ/wReCMQq5UlwxvpG6IqJr0Xqw+KR++VffH9gUfevd/kq9bXRfmXmyZfQNwp82/4d2L7i5dwRm1XmXLk3q/EIQMsid0vj9L5hO76A4AhRZ3on6J74nzZVVdjENNbkh3+Mkfx8Or/ypEeZYXPKjd4KT/r7wU+wZ69F79cvBd8DYJ1wqBPCi5sIIgyySq3/w0KBCR3454GMFXgXQUfJFXN8LIe+IXELl/+vKSuVCn+e8FR4JK7/vvCW13ondWr/E/KvSVq81avJWhPYpZBy3sYv8P+rzX3fVtS33z9y3yz2vQJtXUGnxAhfm/je4Mfir6wQdfz4Jv8GfxXyfEfLguwW/FfJ8R8GXxXyfEfHwAAAD9EGb4C/AKcvi5V8Va+KsQuIWCEv1+go8WvkrkxC1yIQ8VxKM/XXLXJXIj9/XJ+ry4Ofy9ASfXDvob3hTXq8uyfPfoId8lcl8lcktel+X0Vi7hDv7l/V7XxMj/gk9CfS9X6Ed1EKVK9Xk9X675eo3sBs+5e5a9e7rukWLr6CH5l67ibfw7DHNFZP696ovUOJvT/oQvxH9dIV2KJ+IXvKa/pfCPgto/V6+rmxC7+kTscSL9XL5K9XJVeIV0/hGFORF6Z/r0IcciPXN83hf4X44n7wQ+gb6f6E5/Agl8P17X6xeNFa/V+wPIQ7Xu+8hHffGfSN7HEr3gpr3qi9IX/wcYR4iXmhD0LYqorv+J8DSL7ARoXRv/a+8SdYugY7xFE7wqf5vIFPhRG74hfTaPVgKcN9/YzJidv8xlrDuxaDdXzozT4cyVod3YW/r77Xup+uuJ8vqEZksIRPX0l8Jr1X9/f4/M/4R4SqoYQR6XBHWo+pEEnJOkd9fr32CGkl9PUXqrpEfHE38F1Ffwt8KfDGqIXzZsXvLp/od0I+hPqGQjqhbLe8XrdE6qdfda9E4fLrKYHvwzQhyTuu17uXHI3juMV2KrV+pasgf85aw1xcaXn7wTfhGvQjxXr32vYxWovlViuJ+Vfe+/gf4S4u6j6xebQmJw8MR+/BDffvib0TwIo/fuLJu+7uwKYZrifBELV9YMv4U9/WreQnwovYiUYZ8CvVyuXxxaxne/XaN3y3hgN7/hHi5vj+ZH6uIvAt+oU8Hz1w/HKx8EHkEVhAlcnd9T1hcV4fonawz/FPxPy7sHK7XxCV79e/XqwRYW5/nk3Rer0e/6vEF+ZYXBbBPVVXVp8n9f17VpKPhbL//0BT9aGZvYlX6j/IRXva/RO8PhCuVH7xIujk4t/SX9/Tr0mkj9+vfBPCN3N/kzDIkskS1xmnpYJxWqqTr9L1PXdSdXXoV1YMwxWN1xXmoW9DifVn9x3f0Nordg1CKtR3vCYKoY9GeL8Eta9V5roI5hiGX6AQB6XxPX9Iv/kXvlRcx0AzgI4ISu++vCSmoLl8cqqHp3l/zQ19erz+vdCP39oRleG9+j/PaqtH7wNwlfGuJBaOxiNzHgQwQIjngbQRdAG7AQHX1r09z1f1CyGvjES1YfXQF/1ondcN/86tXL4ao7TV3k1z9yoZ3V9fX9o/d/cnxPsyJ4088/evjqVX669X7jVf9X6n6+uVcQqEviF+SXlhn5MFH8EnVXhC6Qp7vm9XquvV+/rjL0V4Y+XAjZNVeM9Dn7rvmEK/n+8Qr7vu4Jv82FPk1l+sFWvmwx658FmC34n5PiBEFcuCzBd8T8nxPwZfE/J8T8dAAAAPRQZoAL8ArGB3xK+dBroJuSI6vlqpbFLQxGvLydRHxCP91EeDHJUT0/XDXoS8J3EIZ1cncRMIV0MW+MX1DFSeqmxyKlnXy9RCv4Ld2hNevQlxCKVIW5JC/J/XV8nc11CPX19fX8vy30hHX6O9Yf/FLVXOiP8lcXCnNC1RSsfKvfX699K0gom6A86wj8CeGPAkjOgOPr6+pb68qugL4lX+kWKhC6/hX16WwIldT+itEDkadXxH0vVhf2BV9l/BAsXgnCOsX+gVuhsSfDMV9AJ+W9/h7xXwhrKJVuq6urAQftUMc8HoT9mXutfda91ovda91UFGxCuYxEsfE9XXo7dhUX4NBvxvYNWvd/jnr7xxMXVL+tNE7oF9e6fy191q52Cn39EFoXF4qhHdAz9CfX1r3gk1xa9CXEScJRFxcThDJWhXa7u+S7lR+7l+Ze1y69iiS/g59S/L0CT474QXyI3d/f3KCISq/viOvrXuhPr67euCQUtfQlcLIL9XCXxq98JdgSfb1hPHVV73UsvL+gg+/6wPHwUUV+gRCOvqutEfof6+v5fZEf02Ka9v+ElfD/2hPZ3hHxQh3ve6w/8E+vMTVfgj6q/6v26vJqr3zr1YSoS58Jq/Zfx1cGvwx4+if18T1onfL8vy1iaL3xHk+1v9DuhX0E+6j4RXiaKx39fUR8lYh/aFOfqnXJV/1519f/CPQOgVyc3x/wwiv4OWjv0BzBmiN8qve2vKnz/aEdI/4SFI8RQTxnJKMUTp/w/8Ld6xxLu71wlu9+oW8R8Ieus+XEm8EFenqRX6XrROv0XvBkE4ZGK8Uno/orykXXtVyAi6q+v/B6I8E4wEYjd2+JJd/y/L4zeLr+uTw2MRe8fqwMPxHz6xvGI5MfuHvGO6/lX9Yj8HsOYZ5f/0V/utUI6vBR1XVXJaDFGik5e9Gf4mfJrDJvnrj/mQ/qX/m3hr8v6K9er+TWLwyMWxEUb5N+hXyStCOiF8Tr/x/wvBGL3e/xSznQPzWv0TvdXvCnPFqXEh79f9AxDHSG9aJ2MVfEJct1PPh74e3V1l34Iuq8i+vqoF79tfedrr2uxhkX3gSKt4Fyva2EfCCIFFkZR0v8OggRI5jF5jXCH0AkQQdcta/xCLdfQOPzYhXEc8NVOrSXOi9P6FdX1jvy1dfa9LaFq/csVfWCzXEQRdY4gtX8Rmzlk+TtCurdf/q/gmq93y8/6vE9Xf3/avD/q5+rxP+TFf9/f3YhYn4JPvLn/zf5hC38uCDXxHwSfR4fivifn+I+XBph/4z4n5/iPgk+M+J+f4j4+AAAAOMQZogL8AoK+SLXxuv4pfNBnyVyRF0gQP8ny/LNaEIvf1yVYGXLgn9x/eiPBNhL6V+vdsREei/rl6lRH+JXpV/JeivLxKv3at3P1cJCFhPdF9Lf4EH1EIndfzLHP198y9dWvdxffY4n3UbqvrBr2v9RXX4K/YHn8RIIWCD0L6MupRxBnvju4e8M64lFeuJ+J8I/BWEPB38bvC1e+l8XcEnh2pU8P9f1xULc3c0J3L136+8K192BX44n6bAu0Jy8CCGF7xeTPROmL//43IvmhTmxCxNol5qPUXXjEa54KT+n4p12ie8a5OMvk8K0bvPvDuTGvz9cn+j90BX9euDzhIQvyIr/EYhZPXoysEm93rr5PZEO76ur6uvQnvVfe2ve69fJ7IviuVWOorobrl7AQITRunzUfoWEIX86nT9a+X2qw/vDOnz8X0hj3yK/X9/PXKidL6L3gII6ueDbrDX0vo7+O6r/Jv0b1ei++Ws/39/gY0O6F8Ef+OL/4IevAs/Cso179Avy9q98vyoj1z/Oi90gUorEouUm8V9KiR/b9uXiflrnXqf4octa1hPi5PvCesfiuEiBG93d1yIz+CEoIarv0DUf1q5KMU2P4Jgn4LKL/vRH+NV7w2FKoDyBJQl03aFdfLXKi9v4F2E7i70Jlri6hjsZmxiRWPDUEV3u3wkCEjvseEXWEqL3xNW9cyEd8nhmvU/dHeSv51/0CddCtcsmCo8L/Mv0e/YTrURooKaqqrWq7+U3yelQxCBJojvhtAh6q/hVXQ2rHT9XXHd6J3WsXghGV0j9dAnXX4zvBa+6/1e8muD+F/mu4r5KmnrRnr170T6R+qgRl/XvjZd1e+0f8p3hjLm516VfOici+idJpoU9Cl/XqSVT6XjcQvhl+j16Pl8SCTu+Y1x8MfGfS91MvX6L/9F/FYsQr+PwuIWr5vRXl7/Q73t+F/94Z+6F+rBgvBw1iy/wjUVrhHxiNzGuFInoBGgmr0Tv179X90V8cTKv5/ifiapCugeeveCr9Q4jsfGfHS88JDEJ5yX5vRvy3o3fondiq98t93hw6L1eieOsEV34+ElW5T//X/dqlS5V79f9wjBVvjEceZPS+WL9COi/+WQcpsdKOVXu+CT4z5NOrrv777m+W77tDH7vv7+/v74f1jPvFf43/HfefHbvgg+L+sVv4/4n5MGmHPi/l+P+J+CD4v5fj/ifjoAAAOsQZpAL8Ar6+P8Bs9/ghDSSTu0FnJ8n6I8vLIIX5Vivkuoz5O475P0V75atUR9v6ugr6XqqT5Fim5166ievwELlX6/7/SRe6pe+Ikv7/ngo5pOrw7WPVTImpOJ/XroBI+vrrr9elS+i9fLC3orx+IzF/ivp9fzondRXWid7Ef44le+OV7/GIt/Ap17r6C3wKVerAg1ik6XuwO5/krD/X98bC/FSYewgMW3gR/hqrlLw/6Bz61fqJ6i/0XuoZxaKbDL8eFOj6y7wbvsBSi0Tu9Ec1vHL3QEX11hHWC/r+Fhi+riMQsnFU9RHodQm8TyIY/Xe3VArE9HP4S0OZZ06/n+IqoS7hD4hE75L516+E0Lyrj5vQQ6EfQnpRCy4Ncd6EV1J1XaX3fOj+ui7wT67V+vqRY/jsmVfJ8R4yj9MPY4KlMe3v4VuEqp/BHr0F/dhnG4Z/Ih3XfVa5dT9dVondP9r3xP6L/51foHRfBYXyfnR+1xP+jekrrllO/XCPF/Oh7YxdKovsTjiE9FYZ+PyLwbi0IfoKi1y6+rRHl5Kwv+L8Ej8frBgMxcapX/Cau8xZOJv0I74msX8HAFmEuoUfhT4QCaGv+jJV5cYoV+pV5PD2shfl+fx1CH+e7AjAQ64u8G474ey/BX/ei/fYNxHei91/PQ5Yq+uf+CuEv+WKxdHrHO1UQvivNLWtYkR1r/GKL39qsFVU/kDgISO7uxVRHgi9X33XWPN4heI1hJK/iN39/eid8y98TfBHCfLNzybob369EPEQ7VzwmSRcaiYhfBWSSolDO+leXBOGKxvy6oGuSvwKG/XpH/D3V+jlRkReO/q/X1yDiCr0OVXxxJcc7jb5Fe3/+hfr4leovr/IMVLpPRXkf8I+rwhz0vpCG6E1i66L/9IR3yzL4tFKmIRED12sTAizCd34FcFHxixfLr789E/+r/E3hL0CFGG3uQbh/InDi15+X9/85tcLe+P4a54rdG90C0T0179gRfsqsey1iDa4n8Dc0XsYoWFkNr1gb4HgLeD0OfDkmK0OIIvfE1zYxHdqwTUJpF5PB7mwXYf9CHvN+Wavo1Ey8nxB6X+uT8E76DPwV+pUR7r64jBR38nV4hFxCyYETDVWryUs6/+S6+q61erqSp/nrlRHvllv68YpyLyiF64K/qyURu/v+/v7+/vEIY8QrXifiaEL8RXf39xV8FX1Rsn3v1z66/jPgq/r65Puvr64j4v6waYK/v5vn+L+C37+b5/i/jIAAAA95BmmAvwCs4CDwYL5orlrl7ie+UQvyfoOfoctu4zv9qhCuuJV4K/ROmuTvk+uXX9CFvmu6+WQQi2vifhOFuaxRBaic2fm+kM7qIV65v79e6mkoBAia4vX34EX8t8i9JcKfIivIIX42Ermk5oU6xC+BB9wlVQp1/MidWG6vXF9fU3gQxV4O/gQ/YC/rHNXXXX1XFa/8N74lXhygQaqIQR6N5rwchGsJ0EO8L7wz2vC95yyehPuwlXu9erk+KRnPili8TWOVgn+CH8RDPN8cjvGv9Ff9GeuIRu/tfG9g/J0J+LG/r7wj8f+dF75PiljnxnxCJ3zXjtXKvd3VgJcP9/fJh/8PQlcd9IrQpqiP+jP3gjltH5d19qxXEdrXJ7EoX3prFXa98X4K9jEQ2dT9cv/hrr+IzUXvF7whhG/GI+qELIv+hdH6EPQQf9Xupl8Vspbv+fyFk5TdV3BD4PAii9VfXrWGaSULRdejdXPVA5fS1hWj9+CIYtfu+EhEM/onUdH6DeqXp7sfRK71MqI8xnf4ZlI79eD/Xbu+sGI3su7uTl+f9WPBJ8TriN9BSj8qXH+HPqhHjzP7ky/19XAtwjUMr0tTy4v6VYrEr9C28EAm6jvf5WIVfpgk7u5JxNdq/hZyDicTvxHgl42c0U7r/fWif84/1X99/onScEMJehfRNz1iNZcToQjP4nf9Dav47l+CGCiGPwjV6quhw/omRfGI3eFxC9Wf4nfJ+iv6LdSdROMX2v174+ExCLQhZvk5p9ixBa1VV8Jr9m3fyfS2fN8cr/FVYEddSeGNU6EP8lcn0veDER5fndYqj/zu77R+vtGevV/j/17FsQK6hbnQnpd78EYT1UEN6aEPEfRf/7065a5v0Of9Xl7Qnq4n4hY12BRVer/NXaK9UCOr9aus7wvyyX3bG9r314JSKtV1YfKRaqs9e9q6+q6+vq/l+JtfFmJu9f+BfBIj94GsEnySWBFonXf3/KY+7oYqTnk0d/OCBX+EIVELYhZbWslF8VyL++7/2/lQr3l3m0/BsvA5H1wjCSPFjEQtMsYiCJHMdAKcGXX13yUl+6m7/m7m6BlQ22KX4SRn+SuRXhy516r5dUX/myXPfdY59dPk0K75Pn9pX6Ah+ge9cT+Cav+otUqKKXvV/iVSp133Vsiv1q9YPsL8vehLyX/d9q/6vWar3WhFd6Jl8iLlN6vJ2v93cTp/7477uWHvWKu4n+77+/v7/uuT5O5MQtCF+vr6nwPmXv5YIPl3m+sRv5BCy/ebr+K+CH5Dw/P/iMnxPy/E/Jgyw78IfE/L8T8EPwh8T8vxPx0AAAAPAQZqAL8Aoa+ZAiihVfNEr4mCy4iL5flxCybX0hPVUR1/SvYha4mEvR3k8EVV3hXSq/5OpojlQzpOe9pXluO+ahCvuEYVEITNgwwn9ciM/zfN818/cfVIb1q/XWBJ4xfX6/6jOu3yddQnU0Q8HXhPqtq8T8L17X6L2+I/kxhLvXE1YC5J69gLX3okXcT3fVL3UR19dYb68O4U5oV9Hv8SvS8R83hX0C/WX5fhGvVwRqdMYhJMY8CbBGTd2Phjvu17mX50B3CvU3QFcM3YCRCvfWHzQpzYpcQsIr4hFTKMRg4D59XxXcZ3oz3gnCNZ6P7oWNXuvrrF/BDBFu7xb/EXd7v/BCR33OgWiv0Trv7l6/B8tf1g1DNX+bfBIiVnYI4WELCOBg45AkNd/ostlv1EL46+/56q+r8W0J7x9e+X5/P617fNq/o9Kv8ZRO0/E/r3yxGFe/gQDEkZkZnYJYQ46hCyClqgR6x+TN9Ofr2T2r9B5+m67l569f44nHqgXUfugl6IEPhGSgV+tCO90Xvte+aQexC9outZ2CWEfQSOk1d3a+v1eI8E/d3fbXgUev/BqWIqdDP9Tq9+r/H+MDfQoEf6E/+bqHlfHSl4r/hKjPXLWz13Jxu/BgB5zsMwjUXLS9cdxHgSKCT+DwTfXoUQQq77KTdy8vgmFo79g2BirdDtev6yhJe8KhJF70F5675vBgCGFeJROquP4QrCf4pX3/1r2MRSd14oYCUju7it38i434j0VeFC+M3Wjfrm+K8XruqBXQnr20TuwKZZPXobt0XptKZboWi1+CMlVvWJPT/+bw+TwqWub5uv2kI6/X5vm/iPCus+XbxxD2763X/6vfoVUO3F3qhrtfQIq64gXclV/lJtNLlRn+dXxRNjiVqTDmR33viAjvQ+i//6/vH0LZ8KI+c6G1el26/rVE68RhHtXirlRGl7Xq8OVqpU+KtvJ2hTlVSufV3r3XYxQ7H2vi0V9Y+FaseBtBMi94HMGS91ayl4R6h/wRUV87+GCfH+DrXSvexHsRDAhcQsuai3JNO9vXUoIuq9+hHdARf690Cf4Vrl+inVWQmv/AzQRd3ImMULPjLxiEJZjwGqDTwb/16q17qpeIviOoQQv94TEePJBXc6HZTc9cyK/68q+v+9X617r+eqpf9av11lq83ESckEmqE/r1ym6Ruq6XupbsvrRP/q/zovVz+B0Cqvjlpuv4hXq/rk7gy77lur+655xCy333Bt9ZcT8+CD/PgwwXfGfEfLgwwX/GfEfBp8Z8R8fAAADwUGaoC/AKkvi4kQsGC+a+kHv1yTctcv8RUR8kvLCvJNfC3JI/n/X9fa+LV5amV+4icQvcI/LCvMhfQr6Fdfr3yVzY4lm/zEu+/oQuuWJrjegEX/V76+T6Re9k6jtX9LifGK+XcEsJ8yvPgmwncIVyInfqVP16ua+L+eqASYzsCOI70Xu/wI+u6HEql8gheqqXuuuWEuafmhHiVyk67At+/te77+yjexHwiqwM9Ca/U6dQl2vYQo3diPZjr3g5OreDk/gr64Q/BSNRPnxSxzXE9YIfhlL2/4R4iGORfncIK53q5eC+hMXQYL2NGondBJq54Mi1QRL7XtK/gUAksXgwNPyL15fQGkEKI3V9S+J+Ge/gqzsOwhxWKWhC4hZBC+AgaClX6EtWbE4IN5JQoW0f5PpWPBh7+7k5r0J+X5V6sEHogQXuuu1+ef+ixTv4EDOw7CNxyCTa+EsUtDEW81CanSN1QSefte/RO+f5+gY6xdH66lRe77xIZ+J9iZe179e/Xv17f4IhS1tCQuEyYNFeM50oQtYvCGBJEmFO/f/grPLpInVVr+uRX6tX+VXxxCmws6+v/BQE0XvBJR/y4JvWjPXonX699L0mDAC/nYdhHkvhOsJ4/iNYPv0Cago9bL/9IQ/gxHq+/L8On+1frX/z1y/CPhijvWPon6wvX/xnghGIrzWBRSIxXonVy1wjCPF2IRaudeqolF6O8EmtX6wR1reuK+T4nf0r+Ekr1hCCIju7u9jugm+hFX8KL9Ffq5cI/lRO8Rk9XqzZK18VwjCgwh71fCHQIqqq/8PiiVX4IfQZ9V+hD4xQsfIxXHhBXPCoi6kulXuv6X/jRVYVovfr3idZtWBhq93y+v9/9LCHFzevRfniuYcvT8pf1u72/iJaXq/k9Lrkx/X69+vfEq/jGveEAgi/17+Or+IxPeL+dhWEOJQUaXnsYtybhletdKvSv5+7+W+dDO8GHoBbcYohytfPrk9/PWBpBYj9rBqFNYvA1gi6teugT1eKzqsWORe8ht/w5qi//Xxdz1Yj86FJV8EJVr9WGf3WI1tLF+ve3k+vsLfwE9xiiRII/4xELmY8Bxgi8Fu+XuJ765+/9fyYMPUIISlWtEY+bX2rHhmr3gwoU8EwxV6Wr/R+8LfZFeSpe9f9/UTV9Xq9cqv1eKXuIV+lvurpXgis1C3lwhk6Q7rp0c6Ku6vVfXN38/ySiln5a5e+Cpf931L6cnziFje/v7+4Mf8f14nN/gk6/ivlwYYL/8TivifkwaYO/ifg/+J+OgAAAQkQZrAL8ApoxAodsQsYIWdfEoexBTyKxLyRHPJgbd3N8ngU/cZ3Xd7eXoYiO3y9xsNYewl0vfJ/a+ZXl51/Vwmr9/y6+XGL7ELWXd18tjkV2hr0d/mhPqT0I+VyK++v5quLXr5egGmZet/E4hZuX5r6hf0foVELiF7iuor5PpCG+IxxPviPDP5K0LRe61ljiV94EE3gz+CPrjdfdgI8b396J1evfNS/XugW4bHI/pFmxSE1Fr4Rqgd6wPO7As/CvxtDO8fvD4n3R28PhdcqwbjPErwiK8PiFl+vj1XL9Tqrm+kb3xXgnPeCkkJc2KIWXpexC0MW3xX96Fo/RJf+FIYxiGFo/gdfX1/Kj91F9DvhE/hEX4TaxeE6xVpa11r4KPdSpKsI5UI7wnXvF0WLy/0Ld4KQije90Tv19I/gozsOwvxl0X0CfuoV58lBRrqjCkZb75aBJLd7FVo0XSr3QOuk+u76tH638Wi98snG9AV9VIv/0T9YQN+id861XJW6G+8TRO8T8T6B+fwTASISXwkivXFIta/Xv1bXzL3YENRGWides3VVoQ/ggr0m39gk6q18q91C9cqvjiWovArBFHfoEyV+oql4a6/RPHz/onuhIQrZf0dryvHsUvb38KcGaCeUlpYomN8Xvfd0uQCz8G/5e6BCId+/er96M/hjey9Sq/yL18/s90N9Ql4PpRuqkJ9f+hHeffL7r3694Rr3wNaNlCYhBPqLri7xvw3jPBFvdi8MfDHT1DHWhj+HZKr8WLrlkqE6wZB9Hr41X+JqtG7wZjvBGI8GY6qOLqwI/1Rf/LYxG98euXxcJcX8nzXc6L1fXOj9Fv4YqgvkGKLvWMGeMkM79YdCMOVm1cN9B71q/VVQ/eEq9nfwl8Nar7Ai69f9Buveh3zfonQjz1zb/l+ueLxwXBELVevC4pYvrqI1hzozHxHxCueDt9AR9cpiPd+cR4z3Xcnf31QV+hfnoT3YGH2b31iK9Xav11WrHX1ondWv9r5jPftYR551/4E/XaH9L4ISVr0nq56as6kkrQp+pKwGZXscTq6l6G+/zBxe8Lby0f3Zvf2b4Qy1oW7xTqwY1/1fhir52GnCXPECEFZtJe7J19q0vy8snixW77vGL+fIveBfDGt/wUhDXDC+CP+vScsmHvXWf58nCUNc90OoIsRJP1+eLQhutE6/R/dgnN+vno/hyveBg4xRR0qjEZ68Brgim9f9xqud83Eex3x2MR/+wE+aHueIzb7Ru+REb7XqvU6emi9dxFL/XXjleqrXpqmirZIJ82X6rLd8mCqifvSrn+Jk9XiueruXkgn/wZOX77+8Qhx8iFxC/E/P8/394hcQuIVYhZO/uuvr6gv+hCEzfWCTr+fBRxCz4MMF3xHyfEfLgwwX/EfJ8R8GnxHyfEfHwAAA8ZBmuAvwCiL5osQgVOQQsCDy/L8tc/6GtiFrljeWC717uIXvk18lv+vV65VfL//8v1LzK/cd3zXCcMcqGvCy+b1/QoqyvROkuJ+de+X5UfLsBhlXu9E7wKexyz13EIsXf4+r7/tpfC/Mj/hfr2T5EM75Pm8N/CdFcquuJ+J717wxrB38HfsBJiV7vX2KJXVK/Wvdfh/4TwrzRXob0ZcajZbr5N0bqoGvrr17ym6Bz8tH6hKnzgRQQLXnr3wgveeuYrPvC27As9X+rX8EP5oT9SpiFl9FbXU3zfLF1ql/BKK3fd06WBx+BB7/VnpVQsT44T5u//Lqv2kXr4itUI7wn+euWSgb+vwJ2l77+Gs7BDCFx13CVCFriK9BTpLFYz/D1DqrDLvtF74le/RSq+VeqnXupegl/RHq9f7r+gn6/n+VE75V9uuGF6qn8/y0J63rB8hHQlxSCMX6JFXFI9UX/9arCa6DJelrnXviVeJEIc7y1zkva991yonfPVRfSE+FdYKB/h4/gkdYMCIW/xPp02oJO/Uqfa+rG8Wxgu3XCPBOgr2EOZO3/yonUeVeL+b09ckbg5oY5/fLdV1/LfIidfP4NAnXKhL1wxjZTx18aiRVUl9o3XhXWDYOonZ2COE+Eb/pawxlefoIRT+rklfgkV0BDDPxPy12hz1xOIXwUBFCe8Ew35pMKjPKEF6+P+f4hE8e0vVy/E1x8K89eitN2j9fr4m5iiH1ehHURXPWM+OWtqHgV3d3vfd+QHit8ZXFIz/IvVj6L1474Q/FYhVdBlVhPCz/r0XsYpaV5cdpor+P+ydfzawfP8EA7yjEKfwTm8MwSd3euIV/iFeTnRPyYVz8J/L1y8IQnz/3z+X8svRAyq/0I6IvQp+6V6ruuJ5qy0Xq4quJX82Sr+KfYP8tcJCFrmRHveXFaoQpV58t/ehXdfz+DheBQovda5fOuesCqOWta65a/1xP7HIsf2IvF1/jibn2r1oKIT/X9XBV6Xlwvyr03q/uiPa/m9E6l6e/pCfeCH0Cv1+pCO/4lX83xHvX1YGj4CIrfGK9Vya+upJV9Vy/LjkX3f31YKQ0j/vCpkKfwmIXsYiK8J/8iGvKvlRnlxW+JWr05Vf+Hvhqjeq5flocu3z/NVa/61f77DLV/1/iiVOMX11NjEV3qwPNX6++CHNRe81WL7ksEVCuibXufvV6vrlkr6+/q56+uCL5fn6hPr6+p1xHBL97/zCF3gh8+O+8+Cj/Bb9PBD6Ew/EfEfEfLg2wT/L8/xHxHwWfL8/xHxHx8AAAAPMQZsAL8AsK+eCvpB7r5K6V5eX5+ov5Z+TqI+TqI65BCv5YT9HeGbA4+5faiPsYie6i+tXsUr7YiSnXpBC/EwWWvesX0va+T2l75F/8yxdAr75MEV3+rteqo2TB318SiRYxbl1GIr/r/9e+boCDhTmQnKHL+/vxRPUJfEdfhWjFTf69jiXf5fnxRL8CSKkXE/z1snyfJr9E7r6+uFRCwl6O/oSvfq/zqx4Ekm/7v7Ee9W7EhHv7+xGn/865Ykgl+HaJlWPJ4/dgLmr9AZxvTo3dfV+CcWvQz69iFJgRwgvkUqX2sXgRf9Xovdv2OFK3Zl3ff41+WuscSX94wJfFfIhHXn1xP69W6Fv1o2Yl4WzsNwiIQaXx1CFhIn73fonfa9dKaq/BF6Ve+ersu7vt/AkCL5f175/m9m+esPVfX+v75Fa8b8T8T8v4ExEi64TFIfYxb9g5ovS9rXUTFfVXXaHd1ax/15VtrqWTay//yYOgzuuJ7MEELfsQGu9E/r9ernl5aype/BOKWtax3d8I4QEoL1WB7V3zdInRS5sFgrd3fd9vy3froCOr7+XVf4xozz+i/7g58OBXwSBHp/GUXqPOL+NRP1ok3P8Wjdv4FWEahObi/F7z0L6+df/rlE9Xgi4xCC2/QgIXYLxcnon/n33+HioS9ejf61esonfWj/8eG/Jk5ZOI38E8I3/ER3otybmxcgJaok8i/pexPX1/mI77xnx1Ffw8Nrkqv4mXjvN+I/RP+Svfr/9WLwXHRuhN/xvoe82jgh1qzoE5ik1V0QV4JqIx8Qr4xSY58V8RuuboJ+hO/RP+I1hD8ZWZ+TWOyctUHaP/r6l+1f4qH81C6/QjvwXSZ1raZcnV6FPY5Un8lXkuWhRL18viKvXo+Y60WdXL0CnVAh9eLd2sTKbOCDVC6uX6C1d8Ic8UIQRmfrW4IZ/3JPRou065P0Tvpe8GS8HC8BEGxSvVcJor68CjV/AUIaWXgUwprAsgmk8DeCpF7wMoKKy0Z/LqwJtH/1L4MtWBN9QkiuUIXqr2HFf4IIS9CbxVhpLV8TV6Fd+s1YTLfonafnXvCZfCZEf36nV4n+vVyrfwEBV8YiPXsJK5S/8hJ6l+WS/qb4S+I+EF6uLV4U9D2hKrQ7LrRuv6q0XLzV68CBuv5/lrLX91avV6v+rFXJV/f3JiFfgS9dq/sTBNXJ0r3dV6I8l/y9T9fz3SP193LX3wYd6/1/8vy19iFxiGWMQvcT396v398X31P19cFXwh81ggxFguwVCYLYQELNf3zXwWfCHwcfCHwtAAAADfUGbIC/AKMvkihC4hYlfFa/gy9B793JLy1UXXL8vyz8/yoryc9cSjPC3MhtQpyS83cQhXdqsU3Kv7qdF/r5ep1/JTIv+4zvXu/uJXq5f/lROgv+tv5JaifnReuo3qLXLwI+7/iafU6v8nhH9d0tdTwUcuOJvrwETl+uT2vBD8M9e+v9f3gRxUmBVr3QCJfWjXvperjEWLwvhiqR+hDBDq4T8CBrAo6sBk1+Vujd+vvD55n4aCvwvhBC50RW/+GQwvSUqM3YM/esXc/uid4XrF4XrFXFU/0ToKOTEK8Qi6/7/iqw2eJwMYa13/P8Qid0CsVfE1jO/65EX3i69rz/CdfeFg1CL/m4i17UIqsFPwTfBD/6/175fte+X43oF4n4nX69r9e+fx/u1fVYNOq/wsryr2vLXvEnR/dgbQz39+34FCEe0K9JWgn30vQpyIJZ+q6WSu1+vXy/PVwU+B4DPQSfgiob3hheI+wj2BrHoV3Z+vlXvmVuwd0XZ3q/f0CjhtiF+R8j/kfI/ssJYVqETuvtBHsQhcJ+QY7u6wc/BT/QhOtctVKOU3FV8qveCgJ9RNvFhgFX0EatVYvkX1O+I6iur2vAjo3QlcJxnoI2iqBh8NUZ+78MVevJVeuLwQ1XTrjRPy1y/on/l+esHAZrJkw+vF6qIk5ZMHgRhfBHn7Q3qXurExf//NRqvF4vEemE69G/4Lw8v7xvwt8MfD3oN5PR3hfnl9F74m+eK4sEVVW54VaI/hT8yNl8R8R8R8QCGq8f2b4zwyQERK1fxhum+hvr8Z+EPGfCGsIiPG747o3r66yj/jfl9Uf9P+Ht/0L6fEb25RxAgt+4qTRfktdxdUDNS6Xi9YUoW9YWXQ1eqv4j5Kvv4Ebwhh1YU2hLxC+vqq2EHf1XX1r3Wp03yfgYq6sYp6y8EaXtf+BTDyL3gSwQL3gUwWeCD2ClTY6j/rb6VXr1/i3V7fhHCPa9FUDL+i9P3J6GN4J9UEUj9LgoEr7wEZW58JIhFmIV+CEdLdd/er9/d3xPf2/eit8JVYHfXN4NsE/LWFvy9yo3VX8v9Ln/jflrl6n61frV59GkwdYK7ua+/kr+Wbv9X6l/V++S+uIk5IKPrv7vASGVL+IXELiFxiCVupcQr+77g0+X8QhPgpxXy4JuIWfBtgqEwTwj8/y4NsFnwh8/wY/CHz/HwAAAD5kGbQC/ALAvhGE+0GHm0oUsHdE7u1eSpJrifn+XqJ+XwEDr1eqk/V/k7hDuJoYtvl/RGgp2pdqTZL5f7uLR3+VX6lV+tXxi+oQvh/81XEfq91E7+Jgo5ZnuzL3695CfrHK5kSK/nXLq+v6oCDV5OZF7J/X8cr3xMJClhywK/vXu/v7+/wv38VWmvVgca90B39fX4EUR4E+vv1uV2jP+vVxXxnh/BTsTJgx7/q/svoLevrrLp/IhLfr3w2vvi0XMfBRvCQ/Xtfoh0y//yLl1l/4d/Iie8E41WrD9E7Xh4JQnyVcchfQjggglK773xeGNehj/Mr39YY1RfhMvjfYE99/6L3wivfEfBkvdalSqmrVG6l6fjvgloX5S5g3RO6Bz8X18R8PQjUdEYMdYb+H0gikXuJsI5OrVegtWvtev0Xq5fkrnXpMte7jfCWsILxm+1Ksqvxvz/EhFe+BaRo5CPDSvfCWT2//QVyr1bsHde8GC9pW1krvV4rzBDdydfq/X1u7+u+WTpe6EhnrvA1B9Ffdf4Y9wbeDILeK/LVQh8/yyC2YR/uuERceTPF4E/jPVWEsd69+CI2kl1cgKCO+77ngpL19Yuq+q6wUdV1XLHEx9dyeqvq55a5VesJVesOBFCcvi/CKsaTv4e5f77RO3/eqEer0X3yr2+UGAdhOoXQ3Kb79e916JsSIV9fV396FP1NWLq/QFMM9X471onej/q9cTl///Ql75OgTjqwd7qf50R/i/FfFnXvkRO+Re8GAmE/Qnvnl+NXiQQK5Wkbe6bwh1oTeOoj3TIr9av1CPWi/8EwmTiEI7rocQ6Ty1yeid1wsIRbHI6dVzrVVaL3Vfq/uv4jBOOtPL9R3Whz/EOq/Ah/BD1xXiFb4Q+hNVr+ule8E4SR4vIJ6B6l7xT83zVefn+f5IZpNe6qT0EU6G1aDT0//AwCLGEOQjc6iegnqu/XL4pFldgUUvd9i36k9fycHUJr7R2ifV69FaNuunQUrwbfBB8GWhijvqrAkjP0XP4EkEy94EMOeD0NfJW69V6/qm0foLvX36za9iV7wZ/SRPeG65euq6RYqoN+zLoHVW8CAIJd+MULK3xC+D0QjP83QIxS91r2l+Xnkv+M7jscQazSrx3zeHTIQ8O+jv6q8nr2u9fER/ehjH69+vj9F5Uq/nqv0T7X9eiP+v6qWhSxDS9HqCn18au9fyYJPQY931KS7+9Gfr65BS/P0jqx10KJfWr4olVXJX8sGeDDJYDSeIQQeIXr+eueL7gz+79eAQXJ90Bi9c+Czr+fBhgqEwX39tfr7+6+uJ+XBlgu+T5Pjfgz+I+N+PgAAADX0GbYC/AMvcTXL8teg40ghVXJBjy30vSXMvTVE9xtcSrnxa868trrr1f4joCH6Xua1xPBSKJk3X1bXv7Xta+l7X1JfVgOGvdzd/xPYDh3691r86JVzwt6Bf7At4X4iEl8T8vxK98+OX6SpqFEr5r4joEeu6qbwExrSXqwd9YHP/EojVy+I9yd/Yr8kKehfSej+hC4/EIUksCjRe38SvX19I3dgWT96939r0J9fj/0j74xXy+EVy+STmr19Rf5fRm6iFc61iZa1i7mXvmhQUQt82IWEPBFd3d/kRL9RSp08G+vRW7+wjV+gp6+r8V+XwnvjK5L1RovtWkzb4/4YgoXXrvpdaI/Wr+Mr2/+q8CFR+3z18tcv694n7fgj+ia/oYiiW4lWiBDr6E0b58TeLq3oR4heI1wLyJFCPDXUUgn3XdgccJCF+kEs5fq/VddevfJ8yL4vl/XrphnpUV+u9CPBRWL4n7tf/Jb/BOZa1r7vhD1749BPpL1q6CeP8EQQ3LnVgzf2iv4Ygiu+xfoQ/qr+lEWDYGPYXCFehL4on7QnvBAWtKR/oY9v4EeCd/HX/WiuVzeNq5rn/sxNVLUJ9Ov+oR7CgIe+TCIQR+8EIW+GZcIfPt/C8Oej91xWEgmrvn+IQp/ZFe1XH/o7FYR68OBIEZlXf5FeqhDqTw5q+TC/4bRerFfC34jrX8mJoj0/4brQvv1qKpxVVrWt+UYXqvDOqGE6rwYUKZ8Rrjvw7/V7oT6G/ZugSm6+m+kSukJ7xAjFE44hHt4jVAv+Kov+tX+dEevX9P4IIey/EOJJ9/86My7iFSpZKtS+JRHkr6E5PBGJ3ex8MV69N0ivQlH6/CG3/BFqjeJuVCO+6r6191vqvBJ+TwIz+LkVTgPEG3gUQRI/eDsOVzzcddwWIv+4RxKyP9BJoa9BXpvXpWthsq9S+f3krQju68V8ER0XtfWMRBWRMYr14EEMXy1USv69fz83cI3QGEZ8R8Rv+CX19e6N6bnrD1FfScV4hEfTq/UqvFVyiEdyv+Ci7v1/9xFxPfVRc1fX88opXJgwEQUf3L4Pj9y9gTKFP91gIbNy3V4hfv77vv+REeKf8Fv0M7+Dn1zYELfy4IuIWfBhgu+T4n5/lwYYL/k+J+f4NPk+J+f4+AAAADcEGbgC/AKkvj9fxy+Lgty0HO+T5Ju1r5UZ+42r+6+X5ZORH7uM7+9X7+oiueC/6qasEOXl/65Hz9il7ruTuTurvWoKNF7iV6xC3l3UR19Pviu6/nvAmrwJ6+dc/oTiFrr6XvperZF7wQ9/wV8q9Qha66k+RerLXsUSscTf5q+udFf42vXugNPr6Xr6+tG9XS94dLCoxC/oWEIhcjlc6IuAgaLyKvjVi6ARNe6iUTvif16qBPRO8I6wQn8EPw38EPFEO/1rwOISRa/BH3ex8VeIoxU9Cb6Ru8HYR+S6hiCb0Nc/BKR33ffwcNEjlXHIydb1c9vqRHfq1c+fWPxfwij+1TQLX0CujFSsu8EJaqbqTVf8vxOOIQX74n5V9dBP4n5/n/DC9Ci+Ohb0KfXUiO54FhfaLFXEfGdV1/o/vEl9vxNYry7wKRfBV8frlRu+f4le+J6QhF6qBr8T+BmQiOdcK8yCvSerwhUyCjlV1UnSq9+i9Xr77XvCPoCX662/NR3qwXhLqGvHVf4muWq0bpB7ILtveaFZ2COEdUOqQQsJ1QKBzvu9+qpNVhzXOvexf6I11Oi9+ifuonpNHfwbBn9He+OoTjSkL9/oV3VyYLgznYfgl68Q+lrRfCO+YEQYVe/QEML6r/kRn/V6qLxir/4+sGjr0V/168N65ugqNurk54Jub4kEZ9VZeDX0FQgjPWjo7+6v3NjiCLvQwE1a1VbvHaoX6FfBM/QjxP9Xrpe+IXvF8Wy+14Qq/X4gJK/ilQ4nf9X/XoI/V5cx/CpPBT+kRj0vFfAhfAuBbEKlwK/wc1ffUny3x1XBmv79erE0eLxPztXrCHHEu0nr/516uIgn/2SqdCsvnV6HLehxK3iM9e8I0XLwbgoR/3hPXFL/4pXk2leTGVfqAioe9CXie9cugk51d7XzL75vk8FDvn11P4RXgvEeCcMfJJ6K9eiv8t5H8mvBoPQlqXh+iPXBVBJj2rNf194SdY+jd4XVaXgQFjlNd8Yu58OexWuK75ZKietWmqvLvC+CXZa+fu+RE75Fe61erie/qJ75PVKoomC77fhr19LdPffX19fxPc+OW110OW0whZMmCjqdf/L1L1/LJ8Qv8QsGHyY7/FfJgQPjs+Hv8+DLBL947fxPzfEfLgywTfN8T83xHwV/N8T83xHx8AAANAQZugL8ApJf/pAoYhNfFQa8nyS+hbVcTXOr/L+rYxby8iP1ciuk5UIeCflReiNL5V7qIluVX679f1cIr+X1f6u46Cj1vLzzVr3xCv8R1Ee14IfdXxK/6jdL/X1gj7vl1yPpqqiuvwngmwj9F8I+4vv76GE+l5b9E75Pk6BP6Hi9/yUAjR3gWQ9rAg9H7wJNe8Cb8CuWqq8FNEKnhvv+CeuqnRfHy+BT+D3r5bwZl8K/DPW7r2OJU6eF69YomsBA8XOaniscfwh83xVEcqwFSE1Y765AS3fd8qeNo3a/X3hoIQS+hb0uf+EN/CSEOfMiRfEIsV4FEv6vT1H6zvx5976L3QMQj16+LroEV345X1xN2CET2E/QIvX8l8EkN8THrvxiFartFjffUncnyr3yr3i3Kvk8L8UT86sUq4/xWqYU7DIXXuiQR9V7rXvk+XxOn8ChBXyKnWte7iFftVf4le61fr1z/y1qvfLfE/E6/Re79vgi+GOKJflBD2GvcV1P4veJr2/wTmVNU1TX2dghglf2gpUmBDaEOdIngmdcT8tUIyctev/174npArvhT45Hl4qCMq194Yoz96/6utO+dEffwX52HYJ82r+/2/m/EBpV1X48XXL8qJ/on7/V65/iemr0ZerHn8O+/uEEJ69NEfoFPr60Tt/qxBM/HfvrR3riPipMRp42D4EHiieM9aJ88LekGUduwgCXr+L8h6wajqxIle8EQbRO7BVnwl8PYJsr8TR3krQh74747x4i6u87r1/1CNWB1CyP1YyvViPZlWEeKJ61bx2+EoJvsn7f+jdVdeiMbr/noUSMMlWry4FkF2ueugn7VH6s+l1+EMRwJkEfku+f0buteqqXuvweCF75PsWXd93jFfLFIjOOIVmnfAwhboDyFvJ9FXvlXqvX9c8lBvios3ILe/gx52FHBNWLHquq6ELWL9C9aV8vxHxCxeB7z1OjPQpZByG/3d/JWCfT/h+p16fb+evQztX69+vVf19/X19eKXoH/rVvl6ia56FL13fJXLgwwV3L3fer9/f2vf3933Ljl1r4uQUqxBL6594O/xC9xPXJXN8CF9YKMnyYMMH3zfeDDB/83wIXzfGwAAA19Bm8AvwCoL4+LXxVL5oNur5e++W+WXkqtBr9VEdyQQ+hNpfRqrRb5VaKwjROv16vxy3+X+qi1eTqrjO+Cjtb2u0J/V9dTzZV7Xhn/8nyXctctc/U/g768L+gFH6W676RX6Ag4Vf6L0K3F9RtCFschGl+T2l7sCO62ToF/r+vr565/i6x28CSVYtdRKJBJnWv174iCX0e/QM9VG/JWDuiv2AUsy+779E98lZV8lWBZCPhH7r14O4IxO75eHQULKXNRO9CV94OQijd0CuveL+Eev175oc5Ym4v8EI3d0qS/+MBKM3e7vHxC6WGJOo1Y54MfQCpE9a9XL2BTG9uvd0rd/ei94v4JdDiQ8Pt/0SscT15hEi+dE9XCHgtBHVAxovdOpU2vDkOYSxfdP5ER/v7XLXb3yq94X+9Yyj99r1cq+8Lte3+r+TTdv8MVfwx36/o3SU6P3hgTT+BgQj3XC/oI1Xo7QhXXJfd9oKd9r36+/X3yr01BChf+vyfCGuJ+X1+0M7oIbf6l0JYQwxg1fgnL+hL9ObqvnBNd/VXrH0bq5ete+euWuJ8w9H7xAX/R//on+v4he1WCwCKi94LPo/tXWhj9a9T/8IYJvQ97pb5qwThdGTrQGkEPV12jP+r0MW9cX4eCPS3zVgQ8uZ1XWDDBOvFBPfG9cV8R1CXQa/Cvh70DAdvAnQUh/whL1XYf9a9+iv+r/or9fiPcLy5jeb8MK/xF8vX47v+Cfo2qrw+FP5BxBDxvh5X+GPhD4jEKFbXhRdclC6//XuoyTE/hKeusEQQgo5fnV/b61fulel8X3FS1d11gWwcfEITH83zUTpzstUt8G0FGQqGdV4JSu+77/E9a94IK14Kvg+6XBV8CVkwK4W8EI4EZ3vfL//8OeN/aN18vz/H+xqF18ZWCCrngQKvjUe5nfXhOjNv+H+eIwR0Z5Ke/XuusGHHIrOvhZGj1z0q+rB7xyyI03LVgj2IRbf8PZsTvLcSjZd/yq/f8+v/kxS369E+rz+rVg0EQTr6RGJbCX5Udir5an6v7V6FK5eXrVjvxi3m+uSCjB1Qh9f+DQt4PqvjFPjfaIx9qkXtGbGK0xjEW+IX58QuIWP+Cv5hEvhHECFnwTf5v8GmCr4Q+I+DD4Q+I+DD4Q+I+PgAAAA6dBm+AvwCjiFjRCwUegl79WhL0M/+r9xFeryXKitVxNc/cT8vy3yXzfJWyQQ+hPS1PFdfod3f8nYMX3yiiXiFlEKkS4QvruK/R3gk26wj/RL1USvWIWWq8uuvk+ZYrqLqouuN+fwKPwKdXPnXq7V6uFEV7w/3/CQhYQxtWvCP0J7vrRO66FL8SveAleOW9ffN+vq5ugZ+kl7017uCOuJRexRLbwIfwIv5fVGlXS9510Cv4eMvZ2CGHfQWqX7r7/r4tE7GKa8tfDP4JC7ulWwCE+1xiuZdcnQL/X19fhnWCn4JX8XiFNfAxhL4QvWsCHWLwdlRHrC++KhPlxBMThXNtXpa433wsAgOX4e/+bDCiv/009NN8YiL7u+4tW719VE+MCN8X5xaO1ZHbwchSCCqVev0I70e8M/L+auEoTf8Mci9Lya4mVFb4j5vkXq7VuwLIuuSS4/r6+qWLVcy98T9onroCSPQvuidrwRBwYtft4hh++EeJk9BOvi7r8Ja5I75eatuI4lDn9i1fuH+x3oMCPAgB6qn6+hPFEIqq+tHbHsQkLIr/XCWDDfoJ1eGK9vfrm/ivBP0i49/37EaSXAvEvBifwyWsMtUqJ2r9/yy8tUBQBT4Mgl1/BH8d6Bf4J30HnWeiP4nXr7dcPr48IYSXwojxS4R36LUZiPjqudgy19aeMREdeCerngTQ7VTX6M91Dvh4X1CPcJor2uEIIvBPRe8WDTXw7QhaxNE634Rwx8foTWT6N6EexCv8Ia/BIJ1V8dJ5bwaBRGd4SXjPWr+EBPUcjvJyI3eUR4XEeLEo/UOJLlXgt/Kif6iLf8MfH4RaF2PDq8ENDH8Kp3ffF1za4zrifkuu9qsIjEXvCNFbsC2u9e82bVf3goCUMDl1E+ryLwnrwRCFXeqpEfxdFy8I1yVa1eWtETp8lVq90BxBNk9U//yfN7XvvFb9D3xvjXwIUEXo1Vk32hXfdcvyk6r5fI6r8Pd/o+WvhHGLt0DE/QCZC3gUQQIveBPBQve6919fWjPV/zyYyhPTP9BB0E/dXKh/IuGNYgX7rFVRHy+DL8JLHxC/EIkV+id1+Siva5NfxPMhLW/0FGgn+JfWhrz89ev+4/HLaq1YlXEdjkL2vBQSGu1ToZy11Vy991oUx19UiPfav34hep+vr78Utc/U/zwY/9ycqM3y2MRj42IWK/5MQqgy/zf564v5MGHEI8+CjBUJgnmrjPm+XBRgs+Efm+DH4R+b4+AAAA7NBmgAvwClDECa5OIUtBa+M1/D3oKtEeiWj/Qj9XU3L1Fq/yzev/k60Vu5O/qI64KOW/RHjeVXquJ/v6++CnQleuole6qhS3698ntdwh396xVU111cL/E9gM/3+BB+Bh19Vor9f69BB6LUR6N1cq+6174lX/W+MJ98WvSVMvdwh1MsXhv4Iev9f+G9CFfgdRFW9YjWBR+BVPv/HEJfx/x/x/4qCL0JvdxMvq/gIn4HGvdALX4O98V+ie8Ll8fm4RR2PhFcx+i5jwgECk3fgjqdNddYUfhw+vvoDWJvF/mhUQs3GxWi9aO/yGI7/BV8CtQh+oSVzwOBK7X1YK/UR4fF/oS3QMz3n+d1x69VCQVeGBEi4gHGsT6+l2v9A79fw8hl4R6Rauo1H6dfovRfoZ1YKO+q+6XTojHgQt1Ea+67+0Lik7RO89evCfoDoF+x/uIvnRK+Isn1W/oTO6CIva8GyFezsEcIeg9XxKG5YhepZMNV6sQrqSLoCmsQslfX+hn/SXxXr18vz0OJ++L+LxxMqzwKAJ7sEgY8PfjUXr7Ru/XVVovvAsUIHdCWBA3QFAJzcV/Gr4qsGb+0Leud3fjiEcbV6q/cZfasV6J/9e+NrCuvQ3/xi9XCWNl9J6FdfL+iZZ2CGEfnwhr62kFqi+ZXsQpc2AqR1er/MCKq79AIUF6I7r8NE+f7RP9Wv/lX/z+Cv4Y+GKF/+TqPRnrDopey//+CMOI8q473Rn/X8nEQl8K8X8bWCkQv+ohe6dX6iPAmBBHZ4ZCHoL+ejPvBmC8GAIOvzV/v9f36K9eif67xq6B/6+nRXp/r1+ifrhCEvhUv/UIIX88PjP6670MfqJ6+tX/V64jd9uq+j+pfiFfqfoTuterE0JOnlN1N1EI3dfT16O/y/E/E9QVQkKWFlXd1aMlVNf2T1PjkRKxY4luzGLv1yJf8Goc1nlCndo71ivxPYMff0vjvhT5/gQCISdvDHxP4E6HvVp/Q6rr61c6l6+vq+vr8EGuJvnRX8GYpf+DMJVyS1CK9tfXu4+TJrlQt6fwKUI8iI8KarXt2vb6+tE7wg6r7hBe1YayL3g0/DCxjGIrOsQhD8GYi/V4iwEcPkv6hL4U+Et/DEFOWuY7frXoutf0OJeXyq8ltIrFdIjy3Xy134KMFN/f3q/Wr9ferHV3dVy/E9z0+/uLV6FEyVxHq8GGBYLiF+fELiFvv56EL9V19RHf39wa/eBY38th7EYKMGvzfLf3zYKMG3zfAhfN8LQAAAA7hBmiAvwCjL5I8QuviYtfMg08Or5ULqFOT5Pkk50Mr4tXxi3vlWq2e+SX1eCfl9lrtEvE/dzXqjvVRPUq/6k18uupawEHuohX6rfzdwh+rwSYn2Ecvol65cUTN9clVNdaL2IVy2A7691KvdV0AsfX0/j698y/7EB75l8fEIzwRXxNgENouXgLevSc0nr3YE8/x3hWvX3Q4l3717qTr6rwcf1jlYd1s3yQ96PXl/rURUSjddQyr/o7FUAvfgV/6I/v+vvCfwvVyTColepf/Xy4ycufeGgwveCAI3yoneI+F/xKJmKzkVz4rqHoUL//fL8t8snoTXxcr/6Bg/ClY5a4U+wTBRDI54Nq360VvlWLwf6wi0JbxpfCIny0bvF179fVhf9o/eGS/P4I6NFrZVvl84vf6J3z+F6L3gQQvr11+id8IQjUb8T3Gyc6P18T1Oj94IHa/nXKL9Nod0o5Ex6VdI/aSm5OX4lH73XmXEtffr1YIVVRqN1r9H7wXVfqFOl60Ii+16i//r3RAQeGB+/kC9SMqxlWMqxks34nCs7BDCHy8IoIdXOiV9SL5o6wM/t+1Qx+w9va/Xr4v2WsfXqqEV7qE+vwQUNf9XrP+dEi+EdZs3m9fXTy8E4hWMqxlWMyMyaEfRL/EVwhWBIJVgyFdjfsMfNV6H1F4EDWBP1QIPQ5Sd/LLo6EMfL8iv0xaK9YLvhvJw31rVYjVDtP/Ow3COBAyf39hWgp3X8i9G5tiEQpBfJ6XQNQp4FcEbrWXlsQvX4KPqr+EN4KfQE/XNJS/o3b/RNQ56H1FeCMj3sk83d+CwRr/w8KoYq98NeLGeDMPq/TXk1xfZQ2veEAhro+uRe3XS9WGa94S1iH4Ur0nF9Ql4Lh0OfFU+T+v+T0R6v60R/BMJ+deocraC/6vVHfhr5aP+vX/qva4r8GYY8SkfvEV6JqSHfj/QjLx9eq5ETviarV/q/V/1/JgTQTfFAhEu745WI0ufm9HS9Fq/QTaM/wKUE/aFOSXkLqutcutcvCVe8JfC3f610Dbr58YvscrP9YMwwj5eDMLfNVgvEozzV+ShLPEZNVfOwk4JfQTeRffQIa91qVOhVE7r/XpOIxys6+TEL8UidJy96vVffdfxHsJI79fcZfCEFW3dz9a+O6X/uif6/1fELXL8TiiXJVq8l9K+Luoitv5/kh/EYu/0pLl6vv7WXiccrSRbjZfV+9X7/bgQP6vELiFxC/c/f39wdfNgo4hZ8G2DoRDsR8uDjB58/wIPz/HwAAAD/kGaQC/AKSvmiQggSV9tvEehDyYH/BTzoI/oQvyzdL+LwLvuNV65ZeI7iviPjPB76mgiwnqp5u0R/lm6Xoi4m7/6wOOW9Hf7gi9CavF7sI++uVDOvAm8QqXicQt+ve0ve17X6++TL8n69IMV6+f5/BCde9CfAg/Ag/At6vXpeZehHlQuKOxvyfLrF5fQq/UTjF/vi8Ut7/N8yt4JS/IvfJ83QLd869eLo7yYEf2Avw2hHd12Iff1CXXDL/m9C3te69/JxOvl+EcYo77JVFKa/qlXAkiNcI/xNdeFd2Bho0XhfdA31of8ImPu/BeElv8V8ReTVA6Xdo1dhb3q/whC/LiFkwT7oWkJbzH6IX7XvEVqsEXXz9As5PSf/1wQV8WhHfICW77vvhRX/9NPTrl8CX7AY4ml8fry0fuxPHEk/ugdhle6+gv6E17wQ1rr+EvCCROscQ17xW08+jv8Qid8LIkUMcI1xfcKycl9II1eHfh813Xc1dXyoY9NZI7yirx9Hiri7xfwU6oC2b4nw98/scBQrN+W8Phnf6GF0I8T8Wh/XxvUaiv11xfQY9fcZr+IL/3oQ/6M/yyjl8q3XfN6+/X33eP9AR8mDbdhEE/jhKE1XaN3QIUtVsQvb/XoR/qGPhj9DSJfDnwx8NRvLXUlh99l9A2Nk9Uvv6+u+/lQz/69fr/4msCQCPx7Ql/Trh7EykxctP/1Q7qevnYIYQ4U78QvwhVfQJle1Iv4hf/J0H9cyDT9WCQu70y+CMj3dzoCz8G/4rVAQAzor9AnC/XJ6M/pK/z1g2Cd5dc3j14Ry8tYeHI3QjxaP0/+1H1P1+BT+xXg6srv8GXwIHwIhPDOsGYf80EZtVYqush9+Cr5d4IQwi1WPStNxCvW2r/oj/HQj2j9XE1xV8i9JXfotonBGIuqQp5K/hGuTEKXE6nvx1FY8UauJvIJ8aq517oE/za5Ed7pk9eoKoR5Z+605/Wp8f8X7vq0Iz9a91IjPdoJY4hVefE1fL/4IfgTwWeDEOXiKL1V+I+miv5uKZfa61euCKEb4gYiXL5Vab1v6+bXdYeE9z/dVy4JjIneBWNjlZ1jFpEsH4QXvBmGFrwShD5F74lE6LXh78EWLi/QqIWLX8mLoV1+j1X3V9a942veP9gtCC91/q94CBGLF83s9E/f/RH/V/tXjbAXtFeCn6u6uX7kv+Wl86EP3LJ6L/HE2u9Xxi3gx0zEd9Yc7v77V/tX+Xu6peurn1fq/p/LM79Ff7N1URssFOt4Jj+Covy/L8vy/LXf3V33/LiFxC/f391ehT0lhHgw+T7w7/mwI2T5MFHEc+CzBd9YY18oiCeX5vlwWYL/k+K+b4NPk+K+b4+AAAAD/UGaYC/AKngJHGL4rELr6gu6qoj5P0Hn+leatWupZ/V/1eubqK+RXQRYnLy1UTEVIsf9e6km5fif/A7kRf+DH8qviFoQiExYM/6K/xFXNBDifXPX11yz7one698y98ixVYLdctc6v4EvWBR/F9AffUq91LtebffXov/mhX1qxCxOZ+bdhH3/Er36J18tDF97EyZV9fJ1CXX1rF8Rb/rAn5K+irr68couRHT5u4JIZ4lH6TCff89RKnSq6wNwquNXLGI40194CZSJ7wMPwOJsYjHx65P194X1hn4X9ARfRPTE9kDOMnLh1FcML3xC99ondHJ0xXUX1L01+jdXIvQjxKE9fE/E4hZ6/Jn9F6rBp/Xvv4r6QynXpXrtF+eKPr7V6wyLpePoraxPXvEuV8P6vXDC98fXG1RfX19fQ0Sr/CCNF8ZCPLfy1CvX8ShfVujvWJf6EPOl36qnydv5fTy/95RCMlOuSVTq8eq43ziUfvlX3wr8b8WvfC/sRXP4KBPQfOsWMXl0IHeCARLzeER69j2KC5oO7eK61CVReIQ9/Ey8EN0GF1r3Y4UvRV13y2EBiFP3fX1av8ysfq34vquq+WX16rBmCPv3gbBYX1SXhDjiH3/ROvifBDhTggQuLG+vhjWDrfcEXwhiifjOi+wj7E1qKtr5MYhQX+fEL2Apy9gRF20rO6VKuD50OJHVBf169tMX70r56wVBdCe+FPBCbq0TvBGFMXOaOvhP9G6XhDOwzCfJfCPTIgo0na1S/i/BERV72IUKrJZhSvVg7A3AlLu5MEc6QdAIkF9ehj9h3+ryej/rAmAzrP6de617whrjUfv0T9er/r+i//oVUK8f896IhfVUkvo7k3F3YFgM1grEeIJ4JvxFYf/N0AhQIPgiEIU7onr6/tf1UM9dcRVfoI+ei9fq9DFdvNROrhqEvRWl/5ZvR2iMSrwViEKf/xG6Xqb4n50R7w98eJQl/1fzOq72utb/SLFNy7/V/tEeqgyhXkmp72/0ep8T+0KcocQi1565Scv6v8Tjib2IV45adEwTfArg28COCKqF0fuwdiV6IEQjVQQQpUkbugk8jwhuTvsPCdVdK50vT9SdJdwguWvBtxyKzG94MtYGmiP4fa864EkLeCkII/X6EdXELypbUvJJ6GND6/l9BG+v5sT8SpMIawcccrOsQuIVHVx0ISev/1/8t+r98gomqWCz1Oro+X1fqIRHkFLjl2up6FEL9qx3KiPjkJNj9A2VVonTCF+IRngrrnFLQxb4hev5+vrkGKr3aor9ywZf99X19fX1zCEQ5KIXEL99X1zCEKNQGPy4Q18R8T8GHyYQ38R8T94KMFvz/EfE/Bh8/xHxPxsAAAPjQZqAL8AqghYlfGSL4hhrVQR3otR/JXJ8knL8vz/E9xfy/LJgv6/+I7hLu4dwjjBSFJLlxC/LP6L/qSTlV8QS6GL/Lgca9QpYK8I+gS8QSXXxNcvxKJ2MXV9IvVWvXyAjqvFKIW+f5/i/QmuWtVeFOLQnpBSx2JaN3rN2rGIJvASvELiFrC9e+REf5LwQvw7kGI714Fk2KJ6A9pcutcutc3hsi98Sid8Sid2AyQz2EPyQmKR3ilviaFLNQRovSetf+LonVaPVwj8/UWtYxXf4lFfwJZJcJ/C/wr8N5MK74bxspsOngKUMAju7u/gQgjvifwx/QjvCuvXq4j4qEuXELiFkEEv4u+Jnu6wbUdy1g4/g4/EZfjP8Yhz1Xovvl8Hte7hhFcqgTiaoGonxa8b917xfwUj/0fal/336Fd8SvYokTx5+/hRFrX6EdC/E/NfE42FZkqoQpfzZd/fJS+dBLL5fCn5a5ZOXwiq4Q8f/RfUl/wLh/BR8EH4j4iSg8Cj4bRvZ2COEeLxC1xeMhR3x37uH174/oIehTl9akz0Z/5L+pEKfqRX/V+tFeyfpf8vLY4n6sfXvCfyi7w7k4n54WFQqIejkMXIgk+LhDFE+Chy4ivRfaFPWCctYKvcR1RuqvJV5uVE7wzvYR8KBvf/xHxH2h/aX174mu0M6uX4QzsPwlwhiFk4z4xBZpeSMuKRH6cxd3jFB505lwQ/C3qI+RX8HYbRH8GIXkqXrRHximzvj0VysPUfvJRHpfDFjmUZXXsLzVBVCNwhNUVLiK91rUTxPyyUCEIdGJ1J4gd8n6I/6vT/BJWqv4j4iiPXL+iv3BH3q9vk/B6Fqx+SwM+Th6FqT60TpOSX0dpsSEKwSipbrrxyEe1/8JeCUm/QhX61f9Hel/3MrHhwFHcncv10DkJS8RehGMRbegsiPCVxXfS/+S70TroEZqw56fof9uI0VXmr61fr6Vb0OJcy/kr1eTF/D4JkVuwE2CquVW6BSfr67xGsCT7Aq0XoV2RCHsQuIXuaIoqXt5ei69URjrr0Z67k9F7qfqde7ikXuxTXvAvBS18Mqx8vgRxngTQl4PQwveHwkvS+v58RzsXiELhr5uIQQf9a8mtqqDGvBCId+u56L/3KhPePr3/V+KyYGT8JIkWIXELEerzcVddXBBDPwjnr1V/o3VfXMi/61YxS4pb5+r6tEfr6v5a05q4d/5I/Tu5e+ql7+/FLXN4GQ/z9ss3PJcXBB8I33d9/QMi9c1y+BUP8/z4hcYhztIuJ9cJ+IQk1PcP/CPxn+biOfBRv4MPlx2KEQTxPwYfCHxHwYfCHxHx0AAAPkQZqgL8ArYhAoFyL4qCbCO/Q2ozkXu5p+W3y8ghb5Pk+RXhdfEo/RPotS8/hH4R/oY8vLL0vfJVyd33y8Tr+hBC6+LXprileuRE75l/CvLFYvWLo/VidXyaE1cbVRe/0IeT5ebf9+iv+v/hFeuwFr8Cn1/f1URCYxH1CPo3et8/69fKvXsTeFd7Xj69+vy7Ag6oCD/RXxROsGeroHde6J6/AhvX3XSFd8VCghHsQsuhdl//y//+WivXr0/Hr4oYrPMY5fvA4rwLfwMO+ToGvr6+tEi1Xr7w7/vhXwuvD4Yqn616TBmEV72vkhHi5BC1xNiF+WqCO8SvJunp/Mh/6X/zIU/xAIru7vq4YjNXyfFIkc+X5/n3y+1ig2NQl6XhfWN+wjWLaxqwhXuoZJd3fxnwkjPjiRW+IXrRO+f3XvnrH/Anh34JkSKEeEfhH4R1/3G98vE1cPIKx65pc1GjnQQoxU8ur0IaVLFdr5UXuvr+J+J8JlRyoy8XJjfhn8fr/4/r8EPX694QXhBSLCP+0KdCPz4It4QJEbydzcncnSIixdYJOq/677rk9perlmwQ0N6sUFvBwDiuJ8VrP3xGghqEfzsJ58ufW/wgjkvhjwxrCHsV6+uK20Oq1yxWuX8Eb/MR39i34EJW19XrPV/peVMYjYr4m9FQR/4t1XQhw77xcuBIDGdhOEOEPklFE3fjiBa3Wi9XJEcf5U77rl+VCK+b8Ehbu7eD3fDngnBP+hD9AewUq/X3FK/pr/57wUfBACuXCYjw2kJ6QYohyr4ahHi75Pk+Ir6vXvtei6hG9i+wmJpYbGBGr/N6XxXsRrhjrBSCkEXVe7Fe3+J+Xw1rjVbtgv6Y/4hE75vDebCG38IQpzVS1fHYsVawJoQ9c3XSI/yXSr3x/3VbqvqJ8cqwj9jfieun/4JRE+K3gQgUQmIWue/+SIL/7aEym5bxPvvl+JrC3X8noR+XAggqRe8CCCZe9G8V8Z/Rf2/pflZPinT/hN/45f8Qt/Vc3olWX/xlZeTe3XdeiFSXi/LrDRzH3fhoSrlP/wLoa8GYQXvBiGq9E79e/XqsCX74g7wwIQmT1ta4jXrz69Gv+i37AiZPl5EaL4he1/XDCv8IfCEnr/oO+r+Wa50Jf5u7+I78UsNV9f6I36tL61I74iX0Zi+RWP1/8vYK6K/er/Eo35NniqX56uofrhD75VeTluuuWrn6nrnsQirHEq/X34hcQsg5EV4b+EPRnq77+/5fl+XX+IXEL3ffiFru+4JvhD5sMf5sMcRz4LOIWCL4Q+XCG/nEQTxHy4MMOfCHxHxHz/BD8IfEfEfP8fAAAD90GawC/AKWIWLELEL4y18yDTwz6E2hDlQQeI5L9Hf9X+SQQiO7je+Tk+T6Rer1/8kFPLVxOKWuXvvSk9fxHLr5fiVfX9CFk9erkhblr0dpPVov0Ir0Ve61el/iFqotek9e+l76Xvpe+SZfE/P1CKL3gzr1YEvvwOvX+OREjIqWyVzQRYnNevd2r/LQpflV64v9b2OJXu4e71i71jnesWr+T/R6wc/mkwfl6AQovqeul6GuX0JkwjR28S17pNemvROkHIrmXil8CDRX8Hde8Cn+EUbsYuv194ZV7WOIT3h/4f9gawj2GtjI0hHLwI4IviLwh9pE9XP0BpCPwpCvLIIWuW70WqvRO6NV5fQm3gio3dRCuaoDAX38cjd+Qjvxiu+IXwTk+bwJb7AdIT/8aN8W+gV0J7oX8TlxNep/olSP+udG6vR+p/CSFOhTl6n+LQ3pON6hGvQkyeJ1eienpv9Du2/JT5qrkpdz6rkRe+Und/EWquFUfKu179e8S1l4RzK++oQXuojr6/nriEbt/wnxaFnS+dffKteDD4IPYKNYS9oReIzVmFaquW+S6qsCgEJeVWK9er174+sL/j8vw3/4KlK/0Xr9CO8CAGIR4LFi+CzFQjjEc+ROvFfCiM9V+69pr9f3hDE1LS+bEIQe+CVq/QFMoJLvudS+Co3QIAor6+XX/y2u9Ef9E75fnriEXpeJvDwT9C75PNXvhTOw/CFwv10KJ+MQYiuuqiexmuKjPV/1f/wSJXeGTlveqAh+oJsnqlAgAif+DsP+FPaGd3Ph6iuVxl4X+HQosr5LL//CXJ8m/+rRu6rqI67xfz+4U/Qm6I4nf/zq9YXoU/WTe+gRhDp+vuFOoZ6/XwWghRX6BkO7P67qP7YL64RV/mV7z/CFe1+vYomTn+GIT5uvq+1nvR2pfz8Z8dfSGP9VWr1UIq/c69S+LxxL2qv5Ed/GfSV6slf+HN+vq5/17xP9f1hDXL8FEJ19fz4hXFbf61+pkkoIlpfP88iw30Z+pe5+5e+n9z4IvgRQadgMEGHYbCCP0nEov+gVtf+fWIr+qBaFYS4hf4hccupaWSoQRHqxOT1vdBzd/VRGDqveBICSvXE4hEeOVm/y+D8KIveCcZ8nZC994Qr+CHXvkwj/RXvLvISvBEZ379Sozz8iL3yL1cnUQjvjlkVjkTbELjF/6AuhDELH8sM2/f4G/f/or/rb9bVyf1yfIhXfJdcnLKIWhSyV1USiv1q9Xq8E+s+vtqxJ6+O+q1er7q+ue4n4mxS1ywTfG99y9/cvUvX1Lqv+eevr+4Kvjfmwt/iflwQf58HWHvjflwti/n+XBRh/434Q+f4JPjfhD5/j4AAAOzQZrgL8ApS+IpfNr6iBCziFsQgVLXxUFHLfKheURc1cs+Bt7/viVf51eT0V+oy3/BB6FtLyoQ9c8/KjdNcQivdyXy4hX8T8v6K9q+7rhXlhNehN3EycWhHVUTQxXeXk+Re/rREeKQYvLqN+Vc/y/dYFX4Hv8b1aJ+FhCFlJJfE3xKJ1YM8mJ0v0W8RxKEdjFsfFr1fjCf/n1/8Tfr73+b5ETvk+Re180n9AWT9fX5wx8d4Y+BD65/HEr1ckI8TOOR/Qjy2MRTXSrgUa5eBX+Dnr/X9L47wv8LlRu8L1+eCH4Z659e8J175l6uPRe8N/AzgQEXqoFvqLkL//7aGMb6hTxGEeWTlQl5OWriUV+o3rviV69Ca9F/NxG/hL2K8MiPiqqO8efsCuN8Mj/EhHX6N3hUIr2OJsY4mZfgp+H/Sq/wwCG78XhD19aEdeK/E/r7wJIRR+9YV4RXr4V7AtKMz5NuXusFxr7XviF7oM5e172vhGsK6oCkEfDHwx83zdf1iaEd8EUI8XJ/cO/yUGtcQh/da1frUbVdaGf8mTte9E7A016Xalr+RC++bHYh4rpeGoS4INcCh16K/TB53AieGP0tSaEInROoI61V67MIVddqlXAi/BD6sEd7u54Nsm5Lv/X/hZb/qte6ia218SehP/Hb4LvteviEK7wh+GMSw/CS4v7hTvQWi7huEOPvVWYxRT7qZX8CBV2MUSPTLj9rhWCjwM4L/xYjVdVN6v8bWCAM+GFXJXoX3lXicvDUJ8nf8bCPCvhHVRKM/hf0CkVpYyTqXrrDYil/4FEF+/1Yute8h7w4/If21y8XiqgwhR/ffd0vTF//Qmtfz4vS5/2T5O9DHu5FfvV+9edeelw9LVxnQuhLHX0E/hIlZj3kq83r+Ge8QvS0KVxtclxPhEqGP4TKi5+4lX+EVfwJVX+JXuplfr+WX1f2VXqgPIMOolHyv168mYWwk9ofxfsT8uslD3vuS5+5OonuXv7k6fonwp0uBEr1DEULPrYxb68CrUqVgpC0j+S9OhitMSYSUKVJOIXEL3q3etr0qrrk7BkEqwlxiM961W9Zcubv/4hCe1/jlPdYhb5r9GexxJ+93zXwQfP1XyZK/rN7+lqtW+fuMxyJYxi3MQtWj9/er3aF1fJSwR/E+inSJHK7fJKIIZrejv1ghu+9jlabGLbEL1P1Ir9gmzCFgg+J+K58QuIXEL33d9/XNfBN/mxPz5v8IfBgJh2bNv4/5cEGCz4j4/4MfiPj/j4AAAQxQZsAL8ApK+kCR45fEq0U8CD4JcE++W+VFeIqSuRH6q1f1N3fy3gZev+pfv7Vp+T4iE/RWj8I/DNe9awQ5Liauf5f0MqXk7kR36k61eTl+WrA24n1fuEoI8VRXquXiUI6qlXuuufELfJJcIfIilT2Sv+X4mufqPXLS/4E34M9v4jvX/Wr9cI+hNWIWhCy4V+GdbEr3Yn0hNf2M3l9lLiF+pRC/F6+6EL9IR1cnnrXxVYZ+CHWCR3hmi9WP+Lr3gRfYDL9AIv8K+DMvxkJ8tCFkEKq3qg3riLvXu1lqJXqfxv2t/iVz4xFpFWBhMDH4EdeBHoneBlq5XIvdAx9aMVPG/C+s+TiUJyobKP6C6VcCKEPDe7HH8HJfZ+gJ50K7a8JQjUSj98uIWIEKk1/+ryL+qIJRcx4crUq4a+o5DI51rHPm8Gf9e+N8CD6Xxwn41C+8Ii/CJaxP4WXvpe6rwZVbx3wr1/a1D3XZcjvgyhH742bhWvRb+Hgh58Ri9XL6cnVUBv68p/Cnp0MjxGJfxFc9YX1X0P/CC9IOIT3wUInQj/6Cb/SJF8XZf/6sCR8JaoIaqKib75/ltfXgdgh2C4MdNo3/LV5tNe+f4u1/8Sv/j+wR+hWs2n/r4QxxCTf4azsEMIcGiDkWaP//BEF34qmHzVwxXBFXod1f4vFdyLqK8DSvBP8GPwRvr60IfwdDMcSIfU3LKvjUV+gJAP/IM6+3obEi50+dE68HP4YhK4U764jpV6qil6bRIrfwbNWYxEW5TwwIAlGxiitvPxRCLfX4NQTAiOq6dcNhdEfwlVKvqlSquu/V/iaoUF5ORF7xq38q9LwpCN69iERd/evdff3y5NDiCb+TF89ZvhkV8R814OX4I/gWwUgkNWrOnRH6eTTRf9Qqiv0s+kiPK/hCEeSNoKJCXrlRnn4h3vVAvNNX89Ln0Ic8IaCCKDMyc/b+ON+i/+1fxn5lfoTq2Dm6BHX1ZtjidW/gyhP0TvuJ2OQ1/bVvLRLV4ISO/eT1brv0Me9qXEfiUV9/0OJ2xCpRxL2moCOFNJSfS9cvoS9aavv+GBy2moJ5F3GAhu9xTysVQjr7RnruTl8wnxX5fJQ3vDAhe8V6xfd938vz+BDr/HEs8mXB+FvDIQ8KivmRur1/1XXKKIL8vO8Jci1Efdg/zZdrBFiAUEd93+8GH9GviFfy9zoTVevfIidW0vfJfEeBmq2IXEL8JfJ6L+if/V/n+e60V/vqW3/DnEWORaW8vy+i1/eLy80mqFdXaL+r75L4nHLb7V6FLfq9Xq/XMKVoNcnyS+jteX/N9X1Ut1L19Sd9X9cTzwRcs3xX3d9/f39/Uuq/EL8tiF+/n+/vEL91yV392IQWNQOfN/k/xFc+OxC/nwdcQjwRfEfOJgnmx2KELEfBD8R8R8IfP8EPxHxHwh8/x8AAAPxQZsgL8Aw4hYrdBr8lSb5P2leeouhCyr4r5PiK4hE/CPoW0ZhHJhGrxHPr/qJ+WuVDOkwT6+uVH/fraTBn7AID6AWNX6m0v+AhdXIr38J8svo7T4R3ic6+J6vq6GIY9Yhe4R+WTmvpe9rqI7Ag5BCOltccv/WrnWrnX19RPSP7LCZf/iZBi+krRakxPzUV7L//Pf11yoV1VCKL2IIRYhV1G4xE9X/SL2OJ981WP9a113xa93F9fVL3UV4Fbbb9e765PEYS5b5Za4vQlH7petG7uJ6jUXL4lWPiQSd3zGMW+MJF/eBb0/hFW8CjRHrpe6BfWLw/8RuvqXqviPj/BCEQSC93y8CGBApfCKEd44q92E/Y32/cSvtfwoIW18biFkbwjy+j1Kv0VqwlpcMeuGpMvw9Hfr/f6HRVkr7wpRSq/UqqrrfwiJ8I7xGuFUfuokEW93McQ1Ktff144k5F/A9ZPQQuhIYgnzGvjZOEV6uFavkrR3+1vJ69fN3oIV2/QLtLv611eCj4YkLu65eqRW6nX10DH1L0/X1r3i69WK/N1osXg2+f5snBRCfCNXCOK9f/1hD4QCUdffIhj16vSrf9HY9v9e8lE7r+VF75V6XLXrwjp/aE9WSi9+jd8I3w1nYXhDgwutBB64IvhLFfYOPYuid13X1z7mqvqUEgh33Ost70IU1IxdeDEvzmu9+CGCPu7+M+EPgSgh7av6q/VSdonV692BDD/fXC8uEKCPZf//a+IrhZBLoR4UmuEJMmsmJ5/jZMMk8Vy/wzCGCQe7u6U3gxi6M98FHhcPgoKq1WqpV4lGf5zdVjiXo7VV9L/qN+WsOUXrsHZP17x4Y8N0Wpn8OQlxiN0nJilifQlpuJpeCkISOvIId3fhsd8dv/46lwbfhmr+DEEPhAiv19F9fWvXyyYXCH2hPvGde/jjSP+H9nnwiCQhHf4IQtWqv4TEfVruJRu69V9VFL+y//1ssu3S+LrEfEfNvEewL+sCBhLil6S+f0NaksTqx5aESr1mBKhfrnJ6X/aEd8X1/Fy4WF/PLYC5BxpvhnuJlzbwhggVfE/dxKvdfWi9qpfr6/DRPBsIp/yYJx2sf0fu4lE7uVE6r16HuSO9X+T2kWr5ftGroHB6wRC0NYvu6pG7v7hD4Qxi4vhBYsYv/QEcLYxf5OSrFD4KF/JvWiUIXGI2pMleqvr6D33Rf9fWiRfEr/5aXJ/PVS/fy1erVy16P+UQrQKlf3dyV9X3J+hD9avddc/ctVP1aK913c9r58Quvi4Ku77+5OJ+JxC/LL/z2IXELiFgy+bHf4n5a4MhMPzY7fxHy19c2DDBZ8R8R8HHxHxHwtAAAA+xBm0AvwCrCFifQKnxC6+KYR1UED/vDOJ5Zelf9E/8knNfP8tXHq/y0+J/loQuIX5Pk6m+eH8I9foe8/Kh3fOvVyonf0OW/zy7SL369N6vil+Jtdc/r30r/S/hLlvlQmr9Fr4lfzevRfKh3dxvyr18SvYxUqk6Xuor2vC/X8n1yor65fwJKRe8DOK8CT8Cjt/1UUhDw9Wgi/XEVoU/6I/6v3yCFxxNuoR9iby/m+b9er16/via9Hy+I6Ak/Bv6ARNe8CP/Qp4VEI8t6LWOX3RcvEovV61LcXdSoh0+J+E1y+E1rGI5MBQyvgTa1l//RO/V+gOoR6fr8I6xPwn8EPwT/BD+bqvj1yxKteCAEO74pMR6CXxnwIJ9/UK8Izr+T0Wq9aq+tVevXqfwp8IY5CjUNGOMRHMnxCL1c9vwEsHKoFNCW7Am5PVqwT8v/++F/wnRO9iFeTHZH+gk8I8Wgj3xaL0nCNcavT8iL0/oZ1eidXcn/cmSj9pf6lRffr369+vfL8q9JhnS+dX7ifDnxCWLxT1+idr9erAgAqhH/kk4n9C3l4qLXy9z3U96oc9UDId0P9f3132itfP8q9Xr3y1giDtY76UmEa98ECEdnYJYQ/5pOCj4JPCGSwh/QSqJfVSehj4xFWvBP+XwUar8HwjWCCM/G9S9fWidfr1869XKhPVU/XjiV6sFik4WQzUKcKIbF3ff8smTiiHdZsZ0jP4JTdZt78PIEl3d/vHyku9civ4I/oLgkKuv8YjGkw4KkXqqrRP9S/Lfor1g0BX4Qo/+j/hKtBD6XpeIhQQvxvxPyzVCUTUN591TE9S+WjP5hRrv8SK7Agggk4WV/B60V+gGyBRVqs+T1/4QE3698yJ0+14IPwhCXIr38RYihL1xK/iMFI5Xk6qrQzutF515Vc+VXviboNfCFH1WOd7aN/qCVe6171Rcx5HXr0uH8JcQi9YhfiZbBx7f2IvH1enl4J77xlof2Iip+iUM/19T1dL3X8si8EX4lX8GBvCWhxLt0LDOOIUVyd+JXLXhEMeCMEHydBmvQyv0JckuSI4zX/ify16Jf9Ev5uvu+VGeWpetH7xiRerKdeodmqZ9ilHfRiq+KJZ6A7gw8FZl7wV1qawINX6j67XoX5MUsTzybXl1QoR1rfVXFfSNf9fyc1ZK9JtdIIdSdaKx1IpU/W2MX15BCI93HxFB3BCv57km++6oLpF7tfia5ZOkR6FE36vE4LqK8EXrUX2iPr5Vftn+3d/3XL8912KVrerwX/GXf31fX19f38vcs3yd/cQuJ4IfjPvC2vib5LBRg2+sLb+J+S/vmwYYL/l+J+Dr5fifhWAAABDtBm2AvwCmiFixCzDECxXgjf8X3PyVyfNPy1y6/6iUPeUQv6v8i9+rwnyo7zYIaO0vq0Rgj1y/Ohnfy8svq9c3QMcohe4RqvwKvGIq/+JX+OW9ev8Yr1XNCXo7xK/VooUTr/9Gv/JUWiP1q+IU9K6n+VE6/RerpXqtZfNW3Jy9wzWD/4EXr/wMfoDj6+vXxkJVLE4R1icS+J0J1X4xCHe+de6nXLEE/G/Kr/re6BXqh/HE31VQwveCn4fyVE+Jy0hPg41TEr214QhUQvy0IQnHL6EeJrhEEnd8xjiHNZl4whJd4EuuXg79AIf1aM9c3hFeE614qsUi5H8N7wIgZRcqwdhi8ZqmI6PROhL0WpRBPy0uo2xiKb9Hv4eriEM7ELvkBvrDFF7qJ8GdX+XwiJ7ApvuJRfVYFf+vXh/vv8MetX8FW/QjpODhConQX56uL8EG+EEG7tf/MiVMvP8/7rl+9XxMi5q11J8vWhnVony9aPF7a++de7E+7Xvi17xLXvF/F5aGhLr1XonebXBRCXLXDfxfzyYaof3QYrF1Sx2ORIL/2l7xZZvQh/u/Qp75a6pf+BoCSEvr/9fF+vq9e6DlYr4muXsE4N+/t0L7wRevrN1UnDWJYThIQvw98FWLhAuW+K7gy8Kaq0TurivCHVdVWtYdVr4hGfwYrwRvwQspN34Z+EdZM3r6uS7AgghRX6HcTOSWhwOF/PxSFd8kJL9CYtcIfx8mCDXovdtRZfgl/RHrnvtX8UKy+sJxUEnwyCMju7/JMEkFB6qtVVKuGwz0AiwYzdoU9X9aEv4GYJotSrBLqi/+EuORHtv41e11wnyS5f3Np/mK+5i/9icnoU/glEXyK/hZ/r/HLTrsMfBN4EcGKK3gdQc9RX0iP0VfLdBo3YXdYj8+v/0L7y0Tq4iu4S9ar+vroYTevXpNCPiYjCYgEm9+8GIS8HYrtCVf8hFXWN3yfJ7N4kmOIR6xxIhy2/hbstFdJui9ddYU9DxdZX+veTDnzXBgixVlozzL/u75df/OhH/tf+3Xr8qoURexxOjviRHhneIEr15KvWFwYeBxAgfDS94SNK/0JeF65Pl76jJPJcZcD3ySiN3feuW6XJ9ffXKp08R8avCPwieuI6AZwEgEh73fvBRu7u7vXxKI9l//8E4Q7AToauwKNEf599a96UOCEe/viP1/3fbyZfyfrfwUVOot/dXOuSrWsu/vX3yInfa9MuFPGLixCs/DFbEK/f30KJgiEItcQr1z2svuhde6+wjk5EK6vR+/XvP8SavX81dcQifrQlFbvuomJqVXhsQv4JD6q8mXXraXkm9Cv//LXav1q/X1fb9qr1yd2r/q/y4hdc8sb6K8NcT9/cIf1fX3L39/cvxMvdiF7v76vrn7xCw38JfJm18y/nsGGCP4S+82/n+a/vmwXYc+Evm+f4KfhL5vn+F4AAAQfQZuAL8ApwhYkQt+gSNOvkQt4IFgj6O5JYN/etSc6Gd86vE+i/+qqIl9EaufwPP4m+WXkhX0Nau1tFeit+rRa+JQS/8s3IivLghy3CPfjiFv8vyr/6oQqXm/+RE/BBfFcuOV3ocTr4n5fifiZOl6rhDv79X8l/X8qK94EH4Oev7/5IS5fl/Q3pbl7BCpPVvLiPQqr4v4muJugK4n4n4m7m+Jkw/14d1fXE1hF1jfifg7+BBrH8CGffxEJfFUCGhPXcqvVxMTV/KhGv1v8K4xFLh1HgW/hSveBHa+7AXfELW6N3hf4Z9A/44n14f6/XrGoS+fGZcNFPQCDDCN3igl4nI/4S517X6L/uWYQtcTS3CPv64jdWrmRI5rjPSUORukuRCH+EvC4jwItFL3QTr3f3+hngvG3Quj911QM/XXOvteN+69Y4hr9Q1jiXf4lE6n8HUJf86H++XELLhD8K4llPLhDXMidXrU/dfa5/GIJCu9vll7CWu/n8LifnmxPoH+lXDaE92Cl4yJFUN3X0EfUvVIRFWBCBd4Qwjxc3HoexXolfo+X6Jma/i+WvscgktdUit396v4GAZLWvfL9zVfjaL3ui9JS9G/r6uGM7C8JcEljmEJlEf5BSrWX+sEMERdVfu76BIatX+lfwT1eSjrwQCFfx31V7oJtWOtE8fa98vyr1ei9JyXhkd13yfEQlxGIRXVRHyT5NVoXGn4sEQhVVXKwjvBOM6Yzw0bXDIPQSVWjPQucM0fRX4LQQgjqqqxXo36sL+mlfuWuJ+JxCKfOCYEaP32ifviKw1XutermhPkv69by5NZMRULqxVBFX6M9ZYIrvseidRl8IfC3hejv+r+6M92/X8tcEN+vfovdgZ6Lf08cSX14WS/8McUQjhN/xVdZf6Pb9WmxfwVhLwyb9Gb2db+zol7q+qr1/b+IVvmV/jFc+VHe8ZV/CGWo35F7oM/EZMFLXoWv+SaifGUV/hjobWVeCQj7mX+CMm72JPqpb1RnrlkoeEEXvia4vHE68muf9XvGrsBUg87ie4z4qqmRe6uUWwpeFRSCPyTCEe7COrhD8E13e795BiFBoYkZfgmE9zq/tq58q9dSovdKveMEyZPitYJKLliF6B2JXuwGKO8O1fwuOvaRvxGmhbw/hH39/lS9NQMKNlfaJkqVguGoTL5FidLDD6erBuEqrq4a+EETptqfJk9Xh769FeqLk5Pk+I9L4hCO+Su6Vev+3L3faP1L19fXil715V4/ELJSP1q/Wv4mtXh6vr9UJf04r0I5Uql+Wq5biO/q7HLc/V5anxi3u+hC9Ac+IX54e+OXf8vd/f33ff92IXEL19+IX5/n+4KfrWN+8Ma+WuT5MCB74Jvj/rDG/ifm+XBNgg+P+X4n5vgl+P+X4n5vj4AAAAPpQZugL8AsPlDWqgnELJy3yyvk/1/8kvgk7vari5NH8DHkGIl/iF75Fi7hCCP0LqTBDrl/Q575a55rCZkJfqbrkv6+vEE9wrTX+olXk9eqoyEX8Sjsil/Iviby1qUv/8nG4heo1DOtf4xXrGKfI91r0myeCf4FbVciXi+wFr7+/uXvquFl/GZ8q/R2KqX9erlROri174tesUSlEL1169jib9Qt9L3hWveBP7/+l68CDRe/XvSrYi8G4n5IXL//S+JrBjjuVevjdcIwWovYwnXgU2r+BVGeBNy+je8MrwvrCO+O7Aki0Xt/42do6Yz7Hw15d+hHeX+ggZFQV5e43uVBHu5kL6l8TiCCFr/sK4n0J98/37oR3yL34Irvv8KfEIxVMYuv1vXL8T8Tv/sDCdDX6BPVvDITVtf6/1/4miOfrFb/vBdk564OoU5fnq+EORDMx7N+vf0+WJV75F6SgW2Xd+SvVUvxSEudAhJ1q3WierhGqBn6krDe8d8RXvEa4KPCGEOEfjUX38tg6oT3hpV69T+EP1q/RIojuu0EHkwdetFfr7hJX7qvBJ1Xu4he6rqute+Verlrl+J+LqtDX6DPxm+T4UhH/gs+T4U+HKu/DBY7aL1Xghfh/vnnoYhgvfwZvoCuJ/BRXdd3JUtrq/V9X15q/n5aL/+jv+CI61X/oV8q9XDHgo2/hqEuIRO7hBYsYvqHLeTiEWq4peq/9Fzz6F+Fuv+yErwUCNV1V/Ci83XDYMQUInVzKx8d4WDSL5jcZ8m+GfhHuEO/uJ+f5UIeWoVQv/T0KJclApr1NfhH0Sv5epcmuKiC//ci4V/BuvCIr8hnf5Mnq/wQIrnwkrnQGcGaO3QU9/f1oR++RF66Cde8te+fxS8ZRe9CKpVen/CNxheqrnk4j5pMmKoMhTwUhLwViPC69L2bq/bQx5131jff4KsmxKEv+v/S3/WHjzv+EeWa+bDFC+iaQTly5ufx+xRNWs1gKUGyGd4Iwl4VNv37Alr5F6Z/wpxCvfxuSqVcIa50Kel9+32hZS7vvXu9FOroYVerlRerlXv16vVzwIH49Eel4L9YJwkj95a9fLV853hf1aK5vIT5N//Ir+FqJfGKKO+MRHrCCo2Nvp+gNA3wbaw+IRYurk9f9y1xGIU+Ri4xQhewGKFu6u4vq6rV5/Qp4XEIfF/EdV347v+r6u++9OXlRn7ie9Xq5VfELJfI/4Y+K/y0X/6J/vl3XKagtxRL9F7uq/tXxSyfLyxD/hj4zlm/6Qh5O4zv7+/uKf6FvBJ83zYjF/JgTv8+DLBAeG5fm+XEYz5vlwZYJvm+Efm+Cv5vhH5vj4AAAAPfQZvAL8Apa+Ig+qWvQeaudX7lihxOtdavYhXVxfUtcs/q/6vBRWv65f1/fOiZUIV3YP/yeH93MjvNy/KvdxuKJctRXVq/xEMctl//Qt4vK6rxiEP+W4/v+J+WTpW+T9G7pkluEfqsGKR+9BFe9BHwIvwf+wGPVzt0SLtiV/r516Fl/E5cX6K/U/osg4m/QDbyWBLfeid9L3694Ifh/4/rwmqf9cTDnLa+JQR6xyv0mNr1eiVFejdXG/GrfHLy8C7RcvaX3hasXgSX4E30BREqnW/r1XMjd4ZS9+vSL+q0V6ET+BPDHg7+N1k0/zBp7wjxaCvWIJnqE7sbi/Vv9eTrh7riPjq9G70WTC3qfxNF79fa8TXsUSrWH43v7pf4om8Zt/BlCXFq2IXuGV6e4VoZHhvFpbXrNj8laDHSLul6+VXrv5+goMR/fIixSYnjifdAxd8b4Z696r8EGsRrB0DCFV8Mo7361VBL4Q2X/9F7y18RXL6oKfrl+J/V/ApbuM7F+8ER3ffrBJ1Xvl35f6+3+rScq98vy+j/P916F94QVYn8MQjwWdclWiueEAhXHL3b36yrFJXn7MatSVL+hSVV4HOrHgtJ4VLVydhIhCu/oCEI6pUq8J/aJ+qZq9WxCtL166gv1/3BP31pXxULCiDXjl18Z1L+vdL+vSeixp19glMq1VVV7wwEeqBIRV2YxQ5ln+M6YpX1mC4IQcIjmsXl8IVf5vHE/BIJVf/wv8X1oQlWvr+VX+Jxiux+v/iawLQM+5e5Zeby/j4U5Lq+n6uNqEaqT4QxCyE+mwQ4X/stX/X/qr4wm3oOeCf0AiQIfw33NW3XF1SC/XfBcvS4p+2i98fCny6d4Qo/XcSsp34bStriMpHd/BT8J5KG+tCnkfzor1iqvWC/3o6d8iV/1eWp0bvJpr853hT4oRCZ8fgmGXu73gmu+7vlQp5K5aCdFfHE3qsEnd3NfE/r+ul68MguRe6AYoFhe2lyK9ZK+IZ4heoUsRyS+t/wRkd8yKi1ci7id4OBf3KvScvl1ej5zHKHY6N3yr/wI4YV6wiO8260Z+tXhn1b9HeSpOuuIRHm4isQIrECPwSFd+vwWd33fd6pcuhT/av+i38CAXy0VvtenqEOvrVj4W8DGsYv/xF6c18vCsLfjlvLgnxVxFcnc3hL1ybVV1zIz4peonqeuIV8Qs3L8s4pV88MVxC/8qir5b/Cz/krV/lir1fEKoIPhHk7kQp6uXEKfHgJZ/f3iF+/v7+/l+X5fl++7+5O8QsO/CPxHyWCT3z0BA9cEXwj8R8lfXPX1wRfCPxHwX/CPxHw7AAAA7BBm+AvwCmL4iQQsQIX9AmaDEQhL3/8q9E1J19zTct8Wr1g5y8mvm+aCzl/V65Z6m65rievuJ+WsH/X6tfwryxGDvHjFeqEEv4nEK/ifnXsQvxKJ1c1VX183xCO/sktxPyq/oSr3YCx9/er/LCvoXVL/XxMLL4/GIY74glVxa9r/2JVqrXvkXvakwn8M9fNXo/VxN1CS92Lqx2Ea+79v8L+i1CV9PqPXv0TZrnhMxd3hAktDJ7fxim/IuBj9AJGreCeid4b0/176XvCfx9e8P/Gk8I1iqwc+9Yurvggxi+6+/ufsd2/oJbwT9IKt9r3hf8Tv46i/BJHT6I750Rz4j5l74he8E/sBO+9H+d6vWHwr+vvE1qt16TBDrOfHE/4xddriiX2I4ohlrg64X4tC+svwjXzXEL0uXT/Q7r5Kqdaria7tXg/r3hrXEVxKF98fLvWFa94V1Q/eJ/B18JwpXfCKFueEK9NWvdcR6CDyU81kHK/cVffQIa94qvfovvtE779179eqoM6yn+VCXmwcgv+EIS4QQl/hDX+k4MK76r6CWTZq9WnXx3iy9gQRNdkHar5Xd+MUe8x4EH4Iy6+fwzqwLAYxxIrt4U/P8I1y1y+y+EAj4Q3wvPxC9Cd/x9VKhvfr0+teuURyAhNqr+Ju7/Cf93vVASTeCheEpjXd/ghu7+RLm8wjSoEMNfCIIzrWx+jPXMiPPQO/py9oI9YohnDvGI/RS/BD3dz9GeSpUZ6ym+Zc/yS4Lav7+DkM9wl26v011r/qdexRPhE3qhPVjPyU/16u0TqwR/gphwv/6EvWIxGN+Hc+lVSId/9XmvRU70EaO/jvnr+TkvR1Yt+IX6J2KJ1+v4c5K2qrQnby0Zn4JN33H0TOkXJxGXEk9r/0R7sHIbRX7R7xZPBKEvBSCBYtrxnxXpVl/ovfr/O8OfKuI0R/wTlvd76/MTd3ejGUYQUuJ1/TeP61tXLq7z0fvHl8UXsMAo8DUCq1/jiWdeHQVfDXgtDXwhVBD1q91q/XXOrwrXdatLXFP+vRL+StfKpkrBo0enXBkL679G68JUX/er9gQn3SsdIEWIX5/ifnV6qdXgktZ8vqSuRE6Xrfza4rXqrkuf9fy5avddDkV2Oue+CWriOkZj5ZfV+9X7BQWn3or1cn2r9aI/Wr9r3dVy33fXor1cqvBT8nfyoc/3a/1/p/xC/PIl/qeDf58Mf5sPdfz4MP8+HsFfy4Y38/xHy4ewWfEfP8R8GPxHz/EfHwAAAA8pBmgAvwCmiEChIQvhFWJsBA4MC//xPJfoa/Ulcljlt3G+QT8vxKp10XwJ+7qCzlk5fiUTtf6/XpcEP5KqpfXvq6lrAj9/wuIQ2EcI4n/kQx72JXuonGK71zS4b9zWIRXVRvxPxPzVg7+BR1URCz4nQl4Vfxfz/SEPXEr3UI2/6f18nsnhNWute1/v+hCuuJ8Eon5UV5MGOEuJxiL6GrAtBFdfGrv8WtjGLFt4FWvdgOWsvB+boCuJ+Jr/E0TugZ/KqsDqFe/v7fv/XsbK0ZsYiiHK+EJMSkM7Fsc9Q+OIGV6/VOm/mugIYhe+0T12zomvhZa/BER336hJY5t4eiq56wJPoC37Ay/DOqB36+/v7N7CHt0Lv0D38MrH1zxHxXwgjd4zfAkQjcXEv+P5a5aXys2qpc3eBQCEnCPz6/R28aWehde68USryUfvNrgwQQeFL0F3ov/+T1/9Yv1r4uX1qK7QUevV6qWXB4uhAQ6+hPrk5ftH+XlyYv1BjQ4gv2vq+GoV4QQlN8VVhrLoQidE+CkjWuq1Xfwi6Xgp314I34JXWShTy8yvJz9Rf2vfa+rME64TR6xs8q/0b/uvb/Xv0Xqw1hLhqRNfqr/kky1rr+aJL/8MhIiqutWv1coYojj+CEZ6N5BXxTEbv470b4Q1hwJ+NiRn274voI0IYlqNxC/PfHIX/oWG+tE75V7wWfIasE/f8Lejv8krr0Wrf8/CKIxKX+/+IQh/snVXySLQIvwL4KUV2/1Zvj+fRbrqoXXrFE9BFr2/4SFLFXCiP/xm14Rz4M5BG78Hcd3fd3f4Zj+77u7/DdUq+r9BuiP1SI/Wr9a98vyq/xPxOKJrJ3+hP/CFFbybzPxH9EeuSqBB8Ql95K9I/4erQRMmX/+Yv/2Udu7peublQp+nXr9H6hxN6oCblxNe/X/gjCy94TFb+vCYS8K69ekf8LVy3o9pc+SxGWrnxR0TpcV8BZAQPtXJMEYU8OjugZrrvLrR5X/BDzL1cnYIgovvBIRWP1vv5fvX6MxhBRlllbb/4aglLd7v14EoIq3Qr1L2E2vfIid+vVqivXEK9YNAwrHwl8ZOKJeIJL3UvXeD4Jw3fPifX12MQjHO4zqRev0fux/vv1frV+vrxCr7xS1WiMSilfU9c/fNzwv6FtL6tJiavr+vUiVlIhHj5Eb9Vo6VFvkqXrV+/5VeTn7+0XELVSq8tLNywQfG/1P19y9/xPy/LiF+WhCGL7vuYYqviF+/uDD7w1/iPi/vBVgu+sNb+f4v6wVYL/l+f4v4Mfl+f4v4yAAADqEGaIC/AKeIWfAQO8D31/BivnQei+VX+f51f51/PWv7qafl6+tHc8HPoBG5eRE6Cq+/ROvtb6+JvkV+5om4TR3quRf3zfSI8Ff2OXf516emI6k6fq5f7jZlxPVgMc8M+htQpyoR2OJ3xi3+X4v4v4v4lE6+aul7wjV+oa6n8E/X/6L3zr3xK9fE36L1P9BDKHvQVqJ5uoiXh1EzfCK5fFgjLu42irQCpEqLJVpAgUqzwW+gMfrRu66wvrP8TvN9jLwIwfXq2CBe+Ikf6CTw/mxGDfl/9ewc0Fe6BD+VEKn38NK5rgq1Y+CAhnfXaL3gtr3Qf9Bf0EdLw6EUL7XJoneE2sXifxKI14I6L0mCbLm+DIHUL+j1WCKva+kXUbyoLOduvVyq9vvsQtYR+Eq9WFPxCP3xSL1Zy+dr1Y3Qt9S0hPQM/qj68Z8/4PIUVRvTrjwSH3d26oFHv8I44vy4MsqCDmT1Tvll3z991zozq0RFyrBsI7hKXtW+WTH0XvCderde9ibwgt/1n/BEhnQpxF4Q1lxr8EZ0FWLV28lAY6FP0n0pCO/wlpV/QEwJfPdBPJz+Q/jfl+L/E1xnxMOfJWgnUWX4X/Rq1+C2ta1ueDp+OJ89YIRivfFfFIU/hb8iK/iApjpw48n8KHRn6OEVYxxCCH1+vdNfr+Qcimyt/r/GxJJFSsuuWTj4X+XJRet/z93xCM94RLPhdIQ/wsr+BDCdUBBBPjiddCav8TdRv33Ak1l08LeV/wv8n/ofai/+ElEeCQ1798QCjd3d3dyvRGPk+S18tVf16o3/1/8Qr1g8C3sR0EvjKE8q0G/X0HfUf6CV56Jl4LATo7G9alf8Kcl/WFMnFVy09vBLkv3LjxHyehn/pXPlr17wrRe8+6hBX6rpcYoyybovq/BJV/m8TrCorw2EMUT4Mcr/hcQhM2hCK/wpJ4JDPu8y+XX9cuv9tz6EPtrlrEHrkRe6CZOveFE6O54Q0MRBLS2IVdAl+N+ExXs3xC9+icqEv+GPugJdCeocQt+xvy75K6Ro5VA0qx0BU9IShTGMUuXPVFv6av6Iiv8niMnon7HItpMDHVj4QsYjOmXlxS+iq8Rgqr0MfVLL6Et5cVguf1Xd1aEdXav3ffiFxCqhCquS6/tXu42Yciq8M/Cd/fLy+YTIX/9EaJEK1rvlh34U/q+5e/vg2+qJjPkwx/mwt82fBtxCwTfnh+N+8Ib+cQsR8uCbBd83xHz/Bn83xHz/HwAAAA7ZBmkAvwCo4CBzYCBxS+IKGnfBQX/+flm2vkRO+Iv1exC6/vllXxHUR1r0Ffq9d1yq890r1U3Xdz4hXVRqL//HE318Tr9W8CD6AVtXxyu2IWC2olX6/6GI3x8TjF993yr0lRUvLVoPoTl3UGfSI/y/G0viegKo/qbrqpv172S+ZE75vC+voQj/E9Ac9LwfkR+rBv3+CQKPe8E3Ndgl+Gd8I/FgkCe72MbPFsr4HGiZ+gc/Cghe+OV79El4mreCEvxnxnQFc/SE+Xrm/iqqHV7awr/BRXGVl7+BQgooGe6hFe+KNveuGlXMfIiN+CG75F/EK+uM17565+gMP6Ei3fd/h8WuVUBhBP1+C6hHdgWa13E+P+COi90D8y9VRAIt7983WvfE9Q1T+BAgo+7lQ7snpf+j96giu++/tYq5JK75ekK6q96z6r9lRekq0J14yva/38HkEPrlPg+Wv0O7vVyxSrHE06V/f1Xhaivte1e+1iqpeq61i+Pkx34nx77gtQ35+vdg79jdP+Gq4xfCQS2lJmq9KsCCW/BIENVf8FBVqtVv4Ky+qI/h75/hChPdAXAwvUqX9uWtG6uf4mSwNgE+Z/o0oJuJBEEVrZ83iXJQCDC3hReEP0URqq9WPm+ZFf0GkXlxiII5nJq0b8nE1gRAR1yo/dQn4QH+O/Fb/hzFbf8TybrvvV7oDmCIl36Siq/RH/V/mvCdf+BJCKL88COCFFbw6EV/r+XVEesJb4S8EHxy8gQXrwdAlhqtCzJXr/yVaJL+Ff+/gpfgvsVu/DJqwx64nCX9X8HgYloIhXr6XyUTvQX8E5kJY9quLROr1/neFRiO9RRfhXx9Fx34sY7+7l+r5KDNGylx+fnk5Pn6Aggq60J7rV/mXviP1/+v4IMUKqi64hZ1eCHu96067v0KfpuXtDfdAjJVB/0Or3QgYvdBR69Bnf65fFrleCcKeGxS9IOQjvKIR/Bb+CuHRxBN74hE/8t4QEL2X/io5flehFeAoCq+IRBX4lcxhBHB/jG3/VRP1rV1onfa/qwSrp+rQn/f0gRaeBAvT/jERf+CcYryadjltNwjDAhYzC3v0/PPXb/RH7lV/KfvRX+Juov4RsUvyL/9X/RHiPQv8Ocyv8nYIfX1q3kqxeX4mvdhUTE+IFO+7+tXurkqXvn569XxCLLffq8EX33Ed/f31fd9/f3/LP39/PBZ828v3hjJ94Ouv514ETEYIsEfy7zfWGMvyiIbiPlwRYJPi/n+b5/gp+L+f5vn+PgAAA6ZBmmAvwCsCFgxL//Ny1yyclbVVN3J8lV3UvxKDj/L8vgYcGGyr1c9fXLfJ2CGvVci/rlX+vmkELVa98qv8q/+JV5eIgtqWuX59dfyol9fLV9ctbovfJ80lxvffE/F/F/Eq/gR8FK5delp1euJ+f57oBJ1e+Re+Re6Y76ROrm8EO664msGaQvuwCag4Xr4RQSygo4qrBjvdBVnw6CTu52+EVMirge0tFfgT6seBJCHQY9fX0v6J3h9+Ea/PhBSp8ILHPDK9/BP7Aj/BvV/lrhAEJXfj6f5OBCgmwchDVxUL9gXy9fX4v7o3ZfX9X1wVa7N+BSCy90AswTeNOveFnulvqfwJGTDPWEf0BPBD43dBn443tghErVfVx++oisKdfoV3wJEE2DLfL8tcvyUl9G69OsVk7+esvsDHrLvBOI8F4Q9jUJ75ZOBShzENDXV69EfeVIJVdsb8quVgVyVfVTeDAVr9FYk7Xor0Nz1it8FUE+2hj3YNRdYUN4N6sVUuMRA36lXBUkd/Blr15UlWWvz93fVBH1onv19fPeej9jYnLsQBBROrJh/kisSGVTqvDAeBDrV6wvQhisJ0V/SV+mK6/Egk82rBWGF/8nw17GgjLqr+BlBH+hT1ur9a98T8tcq98tdIb/9G7oH/pd/o7QRP+eon8WTd930Ynh5dBxScd9Iz16vfEeDHl//R28MhNXuurkRHuoflwpQn0nBPCvavEUIyF/70IaXBCGkL8OmCgju7u7u3hmFCbvu7vu+3gpycnU/f3oz9a9fq/iv6v8IIvfICUqrVa066fX8qv2DcI+OycT6HrlWavfLDC47Xp66rQRSa/QiaJv6+r+kEE6XKv/1/1yLx/X/cGHhDdAqE9D/Q34+i98l5zeCUJeFsvor53hu9FYn8EZN3qbswzdy9lLu6dhL+CAShOXjfQXKievCHx34my//+GVrv8Jjkd/HjlKuK4J4ZuIk9FarE5MhPCCRsx0BMHL3RDr3gUqN3gav2iZKkuLDgU6ASQf8GlHKs+Rerkqvp1f2fr+IWLEK+4IvDI7470OX988Ea4jR+iM+uvF0I75euukaLHKal/Bc+56wQqevr+ebn8uCzLrVDWKvBGbVXvu+VWfa/l5avX/fWEdcvf3wY1L1yCF+kKf611/JJy9y/E1394hfv7oYhF/v7+4L/vAu6+fDH+bBB1/Pgw4hCZ8GWCX6EQT382I38/xHy4JME3y/E/P8R8Ffy/E/P8R8fAAADeEGagC/AKIvnlEIFDhJfE+B9wWl//l5Yi4iub9C3/V5eX56uN+SqARuTkgp9XvlkuJXpul6vV5v+vnRXrl8CnpfwX1r1XE/OiMVyq9c97/r3yL3yfr01RPX11nMi/6BL6+uCgYSvV69b+Wu/lV/i/j17FE74tiV74nGInupK0THE//EdQssXxC94Xr2virrkw58mn+hVQS81VMhvVQEHVBesVdoT3uqKcWSe6+CEFHd93zGXwNMCj9e8GdcvAgjNcT1xNYd+GSeGfhnJh/Y5XrG/MYxQZ2WXwpeDgHEE+krdff3fVozfKrdUuz0K/BFd+/w18LePrVL5F94Pa94EPW6O3lonvDInwj8XXvFk6ByEawT/BTRe+J9iOgjkfwYQ16P0I1Lb/MEtVSb5/tfE/L+hPeLr3jeLZF7r616ewW87FsawcAWoKfQ7/cSrnWiPJQCJ/L11gyFeCA2tf9H8fJ8i9PmC/hv8f8J+FfydD/XXBlBNqYfVV4Kz3QT9XQxDGn6VXrBxRH7yHd/ZxS91Xmq+OJCytH1t/Iif1+vdfy6/Xr50XugX16tFR+8MO8OYKH8O+CgZeJEoz1zeCleEvghBB4KLItb4xHb4W1gsg7ov/nRH/RH6a+XJ9f/VSqx0BFr0mcvXQoh3Jw/D+SivF2hFYI/sws2qqv5JPRn+fxmn+jv4dBHpfvtG6vRf9RPX2wZo7dEDPi/UP/CdeidXBXDl6F/isMiF2V4KBTvu+54Ziu7vXWBNr19avEZvhjjiE16C0mb4z0d+KoS95KEdVOjv1r1evfq+/4fJ9r4R6Ev8sT91oIfrn6/194dr3h34R+ei9XDF86vIOJFbXhkKeEwxvuOmwRYb4xCfyVxXgkCG7vJUSXu9Xz+HDoT3iaL3mEK6uXoGb8SF/hDS4NtjERLsUSzjibnjR3hkIIrS4zD/orRXSxzXdSd+BVoZfwXNFvrsKd8UEKxeElXJW6/kqX49WxCtRS/EeBDyX2ORLTcTDY4g+9YR1lxFxFda4qpK0EvHYR9/fXP1o/6uI7+9EfGIpqdiFxC45dsQT13cXO3vghy/F0Jef0Meavv6Djvl6/i79XmEIrWuCn/BDRHn7rqfvq/l1/8+IX5/n+fELiFxC4havgp+I+fN/mx33iPnwRYLPkzb+f4j5cEWC35/n+I+DL5/n+I+PgAAA0JBmqAvwCoCFiRC+Al8y+aDDnrll5JOS+e7j0Gn71f5flg05/6GIReWojrRX6+vrr1arv4i7AI2EoM+JXq4lTp8SvavifiUTsQt7JdaP3WCOq79gUdcsnKr1xPg7+CX4JcE+q+iOXqEV6uW+Jt/J9eN3xHzLF4IVr/5b7+E0XsUS/CvwvXt/DsEgomXiOgU/iF7HEv+sFVF98oJN7i74tbHgTa59YK+rdAdfWveDf4EH3DHQN9ZUhHvCPxOTBT8F61xuj97Gr2/gsxC/GVg6BZBLs14KSVSfT+F/6IVZk/vBR/XDFfJrhKTwV+gzloHo/w7rE/Cf9e8TXroM6wl34b7/rEPL/+QY94Jcm13fXfZD7v9e8Eh6XyVze3WM9Ar3yoWVPKJWL49eky17FvPrXC/T4Y6O7+Bogh9FlEVaGPJcJq5IOUfZN3SpVt1Y6ZKf692Ewh3fUn2i97qVXx9cbPgtXhWhPeCuvQTeYRWq2+vpwRm3dzqWu1f5NeD1a4nrBv85KVeCQTqrmvDWu5O0bvbr0XpOWsIYKvIdVVf1UiEPdV0BFCiEt4UCHzGEVreBMBPeuG4iuI+OxsSbPvBKCHwYhf5ayL5ZBxDXriUXsXKEoo0RvCOXgrgmqLm5K1Qh/iERzpC/LV/m+auGEV/LV/FaqscQj2l9H/6C6K/6/8bRuvCpr4K4c9DbRdUCgRu7u7/PbKR33o3UqvVBv0E9VyVBFr1qgKoZ65lk6P0j4Ry93Jy9QM8Pr9HaJ16pBJ+nV7uEV/JsnxHqj95dctY+r1VzWAhQ93+PCHX8RD3ERHghLd3eX0KyvSN3evlN3evte1vr3caCje73seCbWNJ0Cn8ai98evVQYBZ0DAZ6OiuY5bbWPtX+VX8PmX9UBTHdasdaI/Wr9RNei/gm5F7yEXpeVGyVeWvBRd3u/n1j4CAG+B+CfiiXWvRIhHfxHg31a3XBHgho716t5d69vV9jEOPl+pNcV9AuVUBfHSW69fJfEK9CF3/+r4xbSUSr0MQ1+lELC3iLvu+FrdCsrrV4jkV7qSS/rV/1f56vgx+bvu++xCxHE4hYNPlwl/mwtiRCwZ/JhDfx/y4KsFvz/H/Bl8/x/x8AAANfQZrAL8AoK+WBLL/8vpycs/oPP1N11XfL3Gorny/Eq/UT8unifur9Xgs5V6udGf9eoQr+dexivU1SS/daP1aKr1p+B5wTar1ar044neuVE6+X5b1X30vdV1S91Sxdwh83gtyV1cJor/E1xKv4O+/4JfX0nJ4EHJ/z9QurHxfxPg3L8SiMa/xi4v175F73+S+I6Agrrr0XpOJRaxxPKn/BRxiI/U2l/wz8I6/wJFCWeGQiuSrgd6i28vz+gOtE94J+v8YuP2BZXYZE9xHhn4Z/onVX12v/wSid3d+/ghBJ8R4R+DoGEE2Jd4IRtb/L9oR7wo174z4aWJ14aRIvhJfeCn4Q+UV597P8br/wj11+J+J1YG/4uhpU8ENE6vXvJXvS+BWgp/5ZF9/F/F+hNc3y66D2tUI75fkR0yWReNCPiaJ3vWNXjKL3393jfi3DfoX0Vky9od++W/RH6nV7sFQS7H+xKk5b5NVsKo/fHr3xfp+I/r3l42LFfLWJrUFGjK/gjP/MvBnQzvDPx/wTVfwlRXrCFWOgWBj5+g3/RPxY2NUtWxMFPOUj314WChOq+I9nQh7p8IISBbSuft/0Z8UST3gTAvq9VaIx1GfHfCyEsxuTG+LRHiuJm9F74N0EugnX30GD9fX5hSGv11grDCK+v/E6qIRO+LrC/wV/DoX+FflV/l+WI4T9i0Xq4Trgxh4v9fEeCcXu93eTa6BBCZt33deLM77v8K1YqvrRHk5L3V64TrBDwjFmxv6fQurui+wY+gn61as1Z6z9eCmid1+I/GQQr+fyb3foyRfVpMT+1f5bw/rk8INHeubHEI9YhFfaG9MX0gjeFRy5/Fr4U8IhL4xevFYJPBRe7u76Vl7QjPS+WsL/k8ND1y6DAlHyrKkXvH6xeqgm8CICJesQvRaM/wh8LeFxni/zL1ilkqkV/i0KeHNCKxObRK9Da6BdU6V6FXxijLLMeBiGotjXKvgIIJrF4YJ3L0evSVH9ui/76qFPhRWMQt81CEZ4xbeWr/PKIR4d9Hay//z1EId18y9X1QF0Zdav8st6v3q+KX0PxSyPm5hiL/Bdf396v1q9V9UiP1d31zwIf9T9fXE9/f3iF+/v7+8QsGnzYJMnyYEDXwc/E/N8HPxPzfBz8T83x8AAAANpQZrgL8Aoa+Jj8BA4xfPBWX/+Qv/LL8vyxAhaL836D3/pX7jO5Z6if0JboDTrbgvvRurnvnRnJOZFf5F/1r/uupeuXlV9XxvcI9/S9PBXyTXGovUvtEv8brkr5fnv/de7ml5OuuWSvrRe64J8Ja5rw/scTN99xOIWnzz/L8vxfstO+Tyr9E79e6hj6ugZr5rr9COvoJ9rwVw9qhvXmy839cV5RHjfxnhejVXCKK+NU9jaY1T15FwKIS8H9fHg5J2AmWid3Nrl/Ba/pfeF/h/4f+Ck+OJX/hvVgIkfjl11COJl8DF6hrFE/BBD2IovRHq2MRr9A9+BPr3xalT7Xqz/nrmEGd9375Ne6k1UR+NS93J39y16E+8EYT8I7oH/r6i+l7CPwIHwrXvjyXf83gtwUrl0EG9F6lrtF68m8HNXrte+erWTn8/L//1Go/Y4n3QmteDDY4n3wnrt9f4tjhXeGcf/QbqvVkb6HRSejPY4lX6v7RX8CQKX/yr/qKqmI6fq16evxCvCuG8X/hDCb+6069f/Kr+BDVOpQrpYuqEv0Dgd4GIEHwjdaN46vr/Xq9eqvz0XvL8J4c+P5yFrXxHujPLyI7+CkLb8d34HYEJTarpUR/pX/V65kd8bOJwTj0JQhOl2r/oj9XJWvSYa+E/xXxCF92Bvr1HYVhb6zY/ClBZ60pMXV6wSUIf4jxFX+I1+v6xoW9jfCVCeqpf0Ifp+/4lHfGL/WOy3Hd/wVwvrT/lJ/X/Eeher8IjN3LR93+LiO77vwirx5aqNriER/1/8Re94KF+jv1ETDiEdvYvyoEZ3vqTgjhfW75V/FfJy9ChvhPXoR7w3qgbun/jiHb4xp/NvXr1/6Sv7WOJb7HErxd4dCXgrEdgLEEHxXm/EehS/+DuF/hK7iPVvlX3nonfF/F1hCjv1IXu/pf/E/E2vBmI8WIriaHI2rFKoZ+EsD0Ve8MFxijLIyKvgh7vfoBcArWXg+OsvGV6SrXLspfnVruCLv8FwjEIuMVXrRkTvBxmvhruslCamxtX8TksX8L6uSuaTqTNu4jtUI7vnuvBdlEIsOfLtItX8l82ySboV0Xc1civ33fBD8R6I8nxXUvfV/fdxYhe7h7/Nn/xG/ivvGf5sPdfxPwVfFfL8f8FXxXy/H/BV8V8vx/x8AAADV0GbAC/AKMvidfxQhYrARPX+v4LBC1zoOfl5flxCyclVN8n0rz3ErHO5UV+9XOpOvrgz59fL8vzyfXoz/q9XJJy9V+i9Vyor9/etoJPXpfQj0Ry3yr1L7xiJ6n9Vui91GdV1+CXYhX1Oiv19fXp/0/9qr6+E4JcJZObsBd/mk/4te6hFa+fwe+gNNe+JXr5PS8T8utCOgc9V91r0mCd+CcNfBTBLSyYK/k+H/hPv+uN3+CQ+7mRVHKPdLeBp6vvE/4xfeC/0B3EZP1///DdGfXUQrHhX42vXifgjr3gl/C3s3y4uLLzXwgjdXBlBHk/r6TAwm8IazfK0Tq5194E78IKRPm9iq0/198vUfa8Mvx/wvVzoHNYvE69e7An0fvBafoCb18J+CesXevVwcQk/5RS1zRmqIxVaFMVV12+7rlvniNJF75UX3z+xft9gY33r3jdUCn5lfPW1i2OevEYJPQ1qyLwRfT6TV+4m+0Z75V/WCSr/o79US7+qV+qV/JBFd977Vu0P7lX0RQF3WJ4tjvQTbevBT8LuegPPrxiGnxjwx6mQl/B0Kv0Z/WXn/X1evW+E/GxfpBbCAU01CnFzZ8avtD314KOrn65ayV7qHu/S4DABbLiwhjc0P+DMEv6M9YIR/t+mr1xPxNevfOi9jZQ34t4v8TZ3goyfDVGfEL1N09eqVcHIYISq/K6r8S5BRPhoF3gzBP4KRvkEor1kyrnvsOgzVyqBgBL+LXr4vf8PF//iF4IP4su70nfyoU1YJV6JdNzYTr36/xxO/jqv5tVoWlT1Rnr0f/jMlAUAJ65ejL1v9BLofX8T6OlSr6ufC5PG/G/LvYn5kfpMJP5rwmEtd6L3xnxCJ3y+XWCgMwUaoR8m5ASF3d4nDQe8NExxDtveN3hMUi9fPBY/y93+CMm717rlJYBdgK6nRFsDSEFkVeEkCG7u8c0t81GP81iFfUMfDisew18LSP5oZEIsZiavEdVcUhnu/vXupupauVFf9G8dX1IivXr/vV+9F7uIRnr1auE8QuIX5lff+/mRXxC9cED+SNELXIvKvLLfLcT1LjFHfd3E/PNbPNfIIWDL5e5+/v7xC939/fd/cGnzYa6/nwYa+Dn5/iPlwTYNPn+I+Dn5/iPj4AAAA1pBmyAvwCtCFgzX8d0g09cn6vfL+rfLr/5asDzgg9CXr1eN0VCOrlRHrlksP5ORe+l7ql6TnV6uNRXpdSr3o/gp1YCFwSar3jvQe9at81c03Kvf1xOvl+X7vaRO+SWgd0V+uxC/Er0mE/xcEl9r9E7GEr7ELdgtycvgf/xNcb8SrHxK9Xr1c3tIvvZOpHd/hyvVgjUnE9wZovUvDNcvgjhFc1L0f69Xr6vkGI31Y//WPovX4JC3uaXGrOmLJNTugEjV3QYSmboUK61bwIO+bwvvmrP1snVXWCD7CHxHwVQ3xyvP6+qvr8E76mVqeG8vi/i39o0b5174le/+KxRCGpsBrhCqiuqVuvrX3WhPvBeN6AqhFZdfRPQr4R+6N3YGcfWCc/ghIhfeHxXxF8H0J1Mid1xHDUb/3W2xW7vmXtfOva+17ufrUizXc/WsXV9S9a98l08voT0mXiJT5X6vWEMKcVCOldXdzoc/yK9c6vY4l79AUPQeSO/dKx3glu+78XdK8lc2697G/KvfoveGaPFXEr1HYThMQsm3HF//BIEtVZWFy1YLRf3XaCD/or+6v4EcVv7q4jwIH8EgmtUq6oiVX96wi5VfSwg6vfL9r1c/xN8I/BLCr/Xvi4V6KLWvhglJ/qoVr0Z+gO4ex0gSCVObxQXV+xO+M+CzwSgr9l9n9V/3DS9WqJ3yzbDCE91DcLClhTjaw0vk7kxC0sL81V+OglJqqqt7vrjKx/0El7xq1/2EPf9/Mv+qvRLxHrvg9hz0L/F4hSLBT/BDQpi87Rnk5K4hHel5Pz+Z+6Ev1J4z4Q/LWFtcSjfuvrXtf/BvDfIhNRvdVoIfrX6k5Kwj1uJ+P0OIJF3kqWs+XCPw2EvGhKCzu0voU/uueWwI4ry/arjfjkL/4r0GASWMW5iideBBSvWExSK/QEUIdKiP7on+p1/XPBXQKPWtdARhavjFFdj9b+CatOujLHu/v7CFfzXBJ26LFiM5EmzK/c6I1116/v1/CQhC4YXEaGNqoi16X175a9X71/1Kiv7P19fWidJzK/Wr/q/o/6/xCwa+uevq0L8uuW7+1V7FL93ct3wb3XfN393z/PiFxC/f33cHH3gg6/nwIW/lwVYNfl+J+TBVg2+X4n4Ovl+J+OgAAANnQZtAL8AqYhYsQsF6/m5/lksHf6QcfHE7UOJ1JyyctWBz/KrwYPl65150taXz1yVzeieC/+r1cl8qv8vcbV/f3wVCloUvyS3COMU9K+W+eW2EvpfnUyx+tf/EX98tcI+DH8XBPzXgt/N83zVf1rljkfWvhHHEJc+L8E78CG/A5vGKK7911+PNS/rBTWLX+rlr5f16uLrBavhmCDmnqIXqwLuuIVzoEemof/6LrwIATXZjEV7+BRXgXa+8IhpYqyUb1UBl9gfQr+ie8I/CfoHNYviV68O+gcm6/AwtH6qA9gwRYvhL4agmu9UAlwtP/8QiOfaxfP6PVT+tccjdiF+IX3yr1dr3X4NtY+hL+9+hXe2vV6E9Wj+EB1VP8EO//FYRul6xCwh65a8MaEIIPqJqp/urjZe7rk5UN92B3CPf5959Y/Xr2OJ9b8XzsNwmIWShtDurFpetfonRlaGP9q/VrF+id7dVCPXvn6HI5yJV1hTNcvafy+QX8fjifvjb50XqPFhegT/hL1b4ujyE1YX0/47C5yEd//U/X0L/aEfoQpb8QrFL9Xqg36Yjw0EteBQMj/McQj2+derlkX9ci+v17wqX9C+/RO9V7f6HdCN6P0uCHeTHYJAogi3hQiFPWDX+iPV6EpPwRVXfsBRgm8EIvwUBPwjkwXmRP41HPDJT4Z+0K/Kr9ek4uqLQvq7Xqf6CnQsv4S++b47XN5f/wSD6rrwgIV/hJGe/V67XvPX/hkII7mu/sBNghVuyC67ROl0XuDPtpCe+Sy//e/gQYX+Ebi++uvnkuN669CvnzV6L/HE38Jb7RXrl7BnV5uJMTd9BMyPFr1+bwVAjhf5OReivVKiV/JVX+hn7vXq5Efugbk8I+wKa77FE9BtYxFLiZaG+42vV6oGfoMhBe8JjviF/WSidT+COF/hNfOhHV5e7kw80fq50Xq5UTq4/oEOsMccQt6wKtX+RXxxLplwn+Ilfer3gmDcL/CXKbu6XPol9cWw4vYQW23/45Y53NL6/+JqtH/jF2+Lrkie4WGI+5L8Icn6HPN8vr/uJiPly6u9r/fDXwv8tctgX8lc/E1XDXwv6FOTd939/f3JfJ390MW/fDf+M4hYV+sd/mwQZfvBxxCz4JsF/+O38V8vy4JsGnxXy/Bz8V8vx8AAAA2FBm2AvwCpCFvA/58C/gxL//fKg8/3+rS+r36LH7ilfwV6e9XcT8Sr9xPy6+XsDLgo5O5O/v+Sfn7i0Z++fpX7mmEK+u3XL8Shb44n+CL16W6RuqpflRO/RfXyS8Wvfr3YHsJ/L8+MRn676yZ/rjUd/iVf4n4lXgj1XuxW/Xq5vmr175pH/a+f5fCr8Gu2/3yqVPJ1za94IfQEPtVqXBz+Gfgrgjvu4j/GL75l7wV+wKvoG/wv8Iq+FwSCd3zHg7gj7vkq0AofgnSnS7AUfwW4j0bqwSr2qwb/BtQm+IRH8EUEPr0l6P86AniPnrFtGYurXqXuid4+sWsEHXvhBXPhr4rfJGeevRFAzr3WvezYoleXWH/tVj6P14rCHEI3fNE3GTej9Jmyf8t8vyoV2vdfVUsy+Xy58+qBv6+rvDfHRpaVCXyVVYJ9YZyXOvRBfVfKId8non/UEVJL/3P+r1y/av+r36v3N3EK/UR19YJbvu/FL6L75ftfeWvfr0mN1gjwl8L4bLVT9f2ueTB6THI1IuCgf4Kt5KFsV2jPfr30id+vpcSX4usJzD6qulhPhmK9ejO0V9ddcqHZVhw/oI/DKEpl2E0ZzHEpX8CMCPqkR6HEv3pr/eQMQSY2NF9O78FNEfXwiiOfL0CGr9Wr32idQ5VqxsaLl/VwV2Fl2XXN8ZiF8JBL8FJtVVVVV3+wSkVVqunXpX669f/HK/gh/HeDUGfhT86K/TPJ0v+4RuxgF+6GhlergT4Kv86BX3do+bTS2OgeiFebiEI75qwjRevNr0d8bKM+OIL/L2C9eT7oR+uWTBuDLr+EPgpgmXhr9XXL6N+vXqwv8SkJ682lrqy/V5M28KjvZvZsn1/+l+CT0Tp/QhzGKGcn6XJF65AYkRSprqderCIjxO7B6v0J/8vgi+DIEE2J1YHENVySVEq8FHqxXq/gcNLAn4S1xepVZf+GIWBER3d4t8Ja1qvv1/8/f39/x9DEd7YxTkYxiF+Za+bEL39xMlQj1ojwVbWuM/k1xF64v+E+5Z8UsYtuopEfrXvmV+vGLYrmV4m1gq+btXkp+uXlk9X6l76u8QrQNV3oU/Usvf39/fy4xEv8uMW3d/fz/LBx/hD/NhjL94KvrB18V8vy4NsGnxXy/Bz8V8vx8AAADM0GbgC/AKovmiV8XBgX/+udBr9ctXEyv4jX2vzwV/Bfrk7iJajVf6V+/5fl9iUT8Ej+RH75JrkloCJkuLxCEJMUr+ZFe+aq+5q5aqscQt+4nHEu5XLBA/pF7qa8Zm5KwIeSppOJ8BC/iUM7X9YK8Xf1+i1j+/4exW/R+iPxRK7A+6HErqxxLv8X4Gmr+DDWBFEeBF/LJteJX0veJrF82v7wJJa5fQnx/xwIYftUX10arzXC3xSM/s/hWveFa94b4onw3Ra+N+cEhXfz4hUD4Kfil+pb6X3j8mE/hf4T+Cc+uK9f64j7A4+36/YrG6srhKEeaI5pr16b0WxJzozfEq1bdctcZa4iSVfo3WvD4RR/azVRO8a1cscT6RKBJ/To/ewjrk4IH8fEdSVKgh33JQJxPg337Lu6xj19r3yvu/E60I/Ql67RPSYnJhn4b0dh2FcHesJ0EKifXor0MeZf+BHW0rrwZLw9l0/vyZOX4vX8mG3+hfZ2FCsBIWw/Sp1oZ0I6Rb36aW/h1+nS+S6jflQx7XwirOg2fwh6ivAjAiQtngwGKlXiflRnpfyd/LWIr3zr1DYkvfrBDWvvHKFBCz2E8b6EufFXgp+y6+WsNj6wLwK/BEv0EnrCtFesJgmR38IgjV3xMnoR4k5L4T8PgwvwSCFraCdYQ9YQoexWX8R8R1+CTWI9eKJ+IrC5PiNfq8vaN+WoTq4Ke3sWxBP0FC4mu2LKJVar7rV79E/83gj+EaL1jiaO44nXxd+iv2C9+nVBn5Kvr9e8KayVz+O1wTwV3/oR+qkvkVzwYhC8S/tH6vRX6QexRP6vVxtWDMNq9DifY4n2qwOPwTgm+GPDIY8SOgj9Wif8E+VbqrF0CHXLXFK/y2q4TrkVvD4IPG5u0ToK61euJBR3fdzIq4MBKvrjYjXCuuHg6ghu+VOhFXeKxXJiFfUOfCtZc9xEE+lTrmscQg5x9V2sVqvV/Nkq755BC1y98GVSL3S9av3/avVdr9X7iVfvV5fV4O139SIU58mIV/EYhe++/v7+5e/ubuDH6EfXXy4IOv56Bt658JYLvqu/n+avrmwRYL/l+f4PPl+f4XgAAA5FBm6AvwDGr+WpYja6Aq+tBhutW3yaufItX3JgnwaV9evicQuIWSi+9EfwJFXmEL3CfxKL/4le1/1E0viYJ7my/zfJcV3aJq6AhKuVcrTxv1F3XVA59KsXX83QE3118nEr//42CHNlvXpPXqp/F/Cvf69X1638Eff9UB91X0l4czUD/1osXzYxb4gkXr+uG4cwx+bqZHae+r+tCvVg19gX/hHeI1wuhJ2xqu/gX5e78L/H1fpJfdDK90/XXoR7XzL36lSbBTv0L7SwSWvQ6uglXvSv0TpX3o/zWsv4IyKu36M2//DdFfvVq2J+J8wtE76Xq4QVz4Q+OvtE7zaL//5+v/aRfa/Xpd6WDH/CcLcd8VfFVxyE1QxFpV7X3savSevVqjMeSiRdmfdd9YMH9/fonyI3SP51j6/XxiFfUQvdcRlovzwm/FhPxO9/F17wT9/wpxXy4pFuwc/avH0V0T/tRVge6HP8tc/zd/Wi/61fVZvcOInX6L3yr32veXWf8v2vY4lffC9VoX1UsJfWDv8E/i83LEr9Wrl1dgcz//aGZV6/vD/wVBFX+esI5uVe8le+4jKqGRv58N/BTCYxE9S/hLkl5fQ1WqgJIXrB8GQQ9Vf5gQmWt6rrYY+CbGoXc9Be6D6l5fGvwnQjvhf4JkJb4Rrgshb5fXo3l8EVGfELVwgiMdQltcE3wMH9XPCPxf5qoOhil/4LdcI+Sv+p6qI6uqibpArQnq4noHaXL9BLoW9Den9CejifrzeIFbvu/Pp96v58vN0Fcnq/teqEv4W9fxdYqiP8T0LCfRQj0J0T9f/pfgrhbuENL9Cn+le/RYpi/U3EfJ0BXHdfYMfej931pyer/SK9L9e+I8R32Lq54kMLl4ZBAid+vdMd8ehnQt8gxDbfExWkjPfJfyeCHqvuvwThSqdF7qVe6vpvv8d8NUftUvjkTTVg/q/z1hUd4VHeGRHxF8+2onX8L/Hevv79cuwMVe8FHwNQnGKIcMmuNhpZa4T0SL4QBLd934vlXrrV+vomaorwVJHbX/g3J1CH6M/b1uv8QvXSf4X6j/tcneE9YGIN12r36v9K9Xq9cqvWH11qlRPxCvEL3aviF7nXu+q0V4Y+P+l1aI9X/LXoneJJ1Ii/rSXpriY0Yjq+IJ78YjK8MfCfyXIhjner4xbfX1Bb9YrCPxHzYETr+Cb4T+J+f4JfhP4n5/gl+E/ifn+F4AAADq0GbwC/AKSviY3ASOIELiFh3VBK8uqvJ0jfv0bv16K5d/y9K9UBP9fYJ/gRMnL+it4f/Eq/QFP1wQ+j/rHVfx2fiPkQp5uet651/r9YpeT0omvr7Aj0fu5oIvvHfm8iscjW19fN8ktRPUT1qdJMBF66XvkvCnXza/lru/b/BJjsnr3yL19fMvfN4vVd4XfgnfxKKdKoD7+/tE75F7x/xte8irmRe8P7+uZF6sCkCOG8EGXmkrkHI33ye14XoveN+EaJFJxuNi4tlfA4nUzeCMIL3hsJeFV5NYN/QH08nSGe+I9179F7w3Xv+l7/MP8CYoXGE+xiOTMsQtDF9E+vv190Wj9W/gJcViEMXg3P8ai948/nGonvLX32vvHl3zZLv/Jd/188RhN/JrEx/FE+FfhHiiV4RfX0/gm4olMMcVYhCZn5M/UhPST+T60EPV2i++W14La5f369fa96r79e/Ryp8qze3fr0vKvY4nWLYQKxUJv+RfCV4R+LxOSgi1/d5Taqe4Ibd+r96sdzau+18+v179ffr6Xi0Xvj8cT7y17wj8K0JirEYS4v4uTDP+NoXk5Z8cJ8N/B8LQp+gbPo4jr0uBwBx8b+v62lfyiVfoK69ffr77Xr4te+LRe8tHb4qjsJwlX80n1fG+hz1yIc9bKCG7/b8XRey/XwnWqv2AlwQq5pvgpBHd3os6AQQMVevRn68UQq+Cj4Lkf/jAmr/OjP+v6r60TviVf9exCuQbH4v0bvCGE665JPj/rl+REf4zEKXIhfiKweBtXJOIrCY756wyX3RXqhFEfHE3u6XscTR26gj6khXurnk+8dR+i8nxTVlDEIEnH1cTRarrcEl2tjw6vR5K99alWeJMsVcV+v8cTeTCg+XJlFxIN3Du1/8NwkOV3lELEei/r0b0umiPfoQ9ZdVOr1kq/YIfxXzIsc+Tx/wuvCtFi6Bv6+oT6/icYrufEeIXhhy48d4R+TXHwoIWQQsV697q5dJS+CMRu7+nJzfaEu8COEK5a4TrSrBFnw6KR/+cV43XEXx8M1xnS9Lgoona5wWV7X6x8v3cEEJa4R/hBEp10K/X3cSvis5pb++TZvBWIlFEyckM6ov42uRb34P9Lj9CO+VekqvDVF/jib9y9yK+KX55RS1gQv6tNfDfz+j/m+WuvQh6vX9VJ+r/LeyUOW/6vIKWxSwQ/G/LXECF+SXuIvgg3jfl+XNifiPmsE2Cf/Pk+TNiviPlvgt+O+I+DL474j4+AAAA0hBm+AvwClL4mJELr4jX8GK+RBroov/LEr1DkZ2u5ZeRF6uWuTsC/lwY+wN9FesGfuLRn+WCbkocvr5O5pbiZRCuvXv16TpF7L/88vq1fWiwoKWbmR7R/NiFq9COrmkwafl+J8Dj9iVy6AXehC3cIL1rn0X/zdgb6x7+xRPxvxsEGbeIz+ie+IXv16uIXvE6wfUXvnxi31+veHq90BC9a91onfLjFL3raXvCP5F7tE7+3/kX6LXxa98IwQ81jifqrXviF745Ef0I/Xq5FbsCT7/CNF7wzXqHSzMV4hawguojod6Xpevr6+jPr6/AiZNibGzzJCnNfMhWV+i980/q0TgpE+CcT6F1k2v6HIVv8R1L1r3X1rl19fWhvvBF6+vz7L//K/BjhQQtiFjvUyTd3hL41/P8/UShkXgvycqJ1V9OvdS+EqLF4ovyISyuLvPhfkquMzYmkRCHr1fu/1f7RHxi2JaiVfFE9aKx4OhXhqr0urXt/dagk6r3z3694vefW3DNC8fl3gnKr32r/f6/7YTXv0T/6vWDQSju8Im8T+O8MDsUQ7+evRmP18V3XE3l+XRf/69CqhUQgn4Lfh/HvhD6+kO+T5EIe+XwmeuEfhnwJAI64ixCKXPBYv/1euJ/V+o5EeQQsnF/JC4hYUwcLXwiiudTfFKx8JfCXSqzwJAvxLrVCHriP0X/hX8R4miuextcTb/RHsYq/+de7QO0JfvXsUTr+EueX4SwTawbpCHlv7E+/v+MrBL/XrxGukd/heTJRO8mqDPsM8US74dhb4n0Lt8kR8txctdYTEI0pPX9P+ubrV/GZcJpE6Xj4WELE4pVz169598iFPJp2rwTBn00fKsCMFa9H7z5eFs+3f/stDifa/o7+L0EF5bf69fwUevupETvkrBs/Bx14Iq3xCvWCcaDwKeCysel1a9JQTq/z9av196939/ZhiEsaWCLVKtgOGiN3+c0GHa9JYG0IIz3T/KvdTyer96v3q/z3X1q+MX3gIA2IWfApYKr5KlV/nvkV+pFe9H7i/nv1f9XlFK0auCv5Lvvk6Qx8Qp7Jd/f399339/f1wZ/Pid/Jgm6/nwYcQiwY/FfN8R8GHxXzfEfBh8V83xHx8AAAOTQZoAL8ApYhYWXyw76CX4T5a5fnkELXJVRCEdQ5bfEfJdgMHXq2u4mHPR3jOSua7iJ38qEfL58Qt8ivVxXf3q9cSiv4L6vd/oSr/r3X1+D38sNrm0J5UM5L5vm+b9Du+aSuuXX/xOv7vXvib5uorw//m51fX8P1NdCsvr79fdTSfXNfaL1c/z44m3g9+Cv4O+utXuoQ6jpVX3xfo/x8P1xX1g/P0DNdfX4R+EdcKo/fCoI+75eBhBEreDvWhS96yc1cVXoV0nCCE99UX/Bv4WXHdP+ejazUWq5leIoCXrDXxGs4V8X8SL+FgRiNVi+Zb64R5e6wb/wSCdVboDSFevq+vr66w3RO8F7qgjXoZFL8dVxXb42JDTLZiIzddEyXfcrCW7+X216ZddCFdrw0tfJr/426+vwcP5Pl/Qn3hHC3FdeIQuR8NdYutSbEy61uhjVpUT75P9f/L2BDErHrl6j65egEOMRn+L+Jq4ruaeu+SHcHfwvxUf+vo0vhXJwirpa98+hmXUqvJz1yyUMCXgm+EQ7No0mxKL0g2L9v+EhiN6uLr5LiYziu+Qn6//hxIj1p3x+uFQYUVnVozyeiv4IQxjZQ48aLvj0Tr20TrvU6S9/oX3QKQjC9cn1xcVxFXgi1rfGKFwqjG+b4hCm8HJvm8FQvzV/Vf6/rjvCorX+/F0XvLr1/XaI9VN5N7fUPoX3yeEQsjdC/+Xfx4xQvW+sFsKCC1X51WJ/ojyYiiP8y94fHeH15fj95NYl/Khf/HUT/QV3koveK11WT8JoIdC1fl3rJ6DL/on5l9IjkvVU2hD1V3yK5+vfS+8lH7wiugW+wKvy0XvJxxJsfzFROqpvNX/jvqryYsJL3scvfFVwvCgha+QQsR6+n613EoZ2MVA6vr7CZ9V3dvr8FYSkvX/d/CtVDUnFo71k/C1cTiEZJ8fC3y/8TNy/a96aLmJ8NPwPw/XFgXQQLFjFSzGsBKwGdXLsEBESLXGf2vfa9LsTVaK/ei93SKxjFH2iOeBfHfEfEX6Ffhv5f3+jvP9ejdMsOL8EtYqd+sf5b9X/V+p/ieomS4lfHcWvfaLyo1xclgIzDHy26vEZ69Jbguu+77kR9aIhH4rn61foGBUNiiL4Z+X4UELrqb5KEL9/fd9/f9yCEFniF+/v7+/uG/l+FL++T7wVdfz4KvrD3y/C338vxHw78vwt9/L8R8O/L8Lffy/EfHwAAADeEGaIC/AKuIWQQtL4uxCwSegt+fpCPx1SVcQi93N33URJgx+BD4onoDL6k7iYfx1CWk0peS7ioh//PPgn9/ehHdav4Ocnyv+H8Rn5JOkTq9ffr1evXy45RW/xPxPy+Bf6/rk/Xu4juK6iO4Q6B769f4pZX/DuO/y5KL03JXJ8R83zfEeG98Irlr/4lcvjegz6/Br397rjuv4n6ute6eZ/BLDHN80mtct4j6r0nN8nVL2IWul92BpH9AprF1rFfHo+WN3L3gYX4EEZXa+363g/ft9Abwn19fwkhV+gnnf8L8lc8nUnN1oalS9cvaRbUv/dDG+JVvBLVuwEifs/wJG+X26XCH8Z8Yid8Qva/+ZeiMmbEaf8JcR80ghHm3QtyauTSrkQWYvtF6uW8Luxy6+Wl3F6+WbJQnv16Jf+dhmELhDvkELfoIe6DettE6I9Ecq2pNNCHruT15Urh/qE6wffB0I8GQ6lawpXL6r75V6fPR+kf8JHYTri/B3qgZ625O0K7qf3X867COf0KfqVX6nvl+Xxx0X/jfjdYPqsfBHq8BKhXVTEqdOgQ/if0bv16/RfXYEkFdYf7/h3Za9C489IJXxSFMa/+/IWsTri/jfB8HfBUG5OEMYqWc8NgqQn/wYojnUJ3iv6EdXKvfP6r3zovfE4mJy/gs/vDPhntG6T62kdOhH/a9rvxiMI49VEEu/GKISC3xHxSpVwZVcqtE/31Wr16/+EvgrrD1H7GK9MuENeifvu7g7rE9/wqIWIp+tC+iFxWiPfSI+EFNjH+nwIIz6RGOgcmt/ydfEeNr3hHVGB98E6vWHRPVIS91+Z+T0HQn0vXb/hHlV4Q9fS9T9IY8vN0BRCCL1YX1kdVfhj5aO9cR8ti3vQonHE0y5/gn+T4Jh8EPo3t66K36J79fnZalWTYGATrufCSMO+7tt2/2Xu6XcWisfKi5jwtrE/0Tvnrlrgi7KC7X8i8K6xPy5eLhrVH/eqO/jtcT0Te6Fe7LR/S4U+BAa+19a4T9cJgZQwiexiIkx8QCG78c6DWar660dH/jFt4EhfNQhdf7+SH+WIzVeu5PQjpeJ8HOX7tHu6rlkV1NfEK8FHxHorxVBNr0lyq9XfX1yf1wU+iPFfEfL3P8GnxHy4MOv5r+gTeufBNgr+I+fWI+XBhgs+I+f4j4MfiPn+I+PgAAAA4pBmkAvwCqCF8Bw9fzCFlL/xOg0xBN0vdzRnL4D+4hZeSsBrewEXVu83d96uSL5fBD8GOuWF/RfxWKydL0vJ3EVUnVScv6Ef6tXxCvFK5PV+pvH/Df9Fef6sBL16ueGPR/zYr7yYU+O3YED3oV3UlV3gl/JW/U6L18Sv/i0TugEjk6lsDD77/0JR37+/4RhbmXoi/tZubJ93/3VdSInfJ8nbCnf8nzScvz9L2H/a+CH9yevSYLXr/ELXVcKw/3l//ieIrmRXJMJ+wIL7hdaoXFxbFef8CiCJG7v71btV7wj8E9fVzfN+hXS8vyScXCnEI/RHHItXv3rUvov5O0Ii+L8HI/oCCP6/YTX3wj8Uid5fgSAireDULfrF/eEKtNv42ve69fKvdAQXWXCfFRlaHuXxsmSjOT1aHd4OKKkWperWau16sEtSpiiSf2uutXmy/lXr9HbxeShPrxbk/vBPzvCnHfDVcPeCfv6Qmqwn9tWjuup0Oj1U8tjwz3/Or+BCE+D74MhGv0X/hKif6YSl9F9XE1Rn19fX1wqLhOVGEmEslwnFYRcvaDGUu6v+r/av+ivk/qN/kxwe8Lg1R//on69evJ9tfa+kTpeE8n9f8JcJ9wnN8m2hfRXCHhPWyejVQEsb0MeT9esM69CH+EcYo61Y8EQf6DP5F79Xov/+NiVd7BH8I/oQ/6/rNV/nrklGoSG/d8Iwj/zIz/Er2/5L/DGai51/eHtYORGqAufwSrwLpvIEKwfBm664jwc/BeugI+8SN8KZvXqyvwp8FJvh2GL47N9Lt9d39q9dojVh4vzq/Qv1q/X4yvda98R4dz4IQ+hbWKJn54SqVXjs1a9KK+WtDH61frV/EV7r8GYr9C4vJXuwJde7/HLX9cdWTN698V8JLF48MfPDuCj+iv59+jdWfJyf0MQopBvXLQ4kd8nfpF7XEavl+b/qpeWTHaGIaD3idLDNE7HElwyeX4Vq/jRC9YhGL/Hw7WhL+fLy1na9+jd+vuplKl9ot/AWAtT5jEQuGTXFhINK5rDYTifjkS/xy98Rfq8+DDQxCz0asP6ELLzw7yxHoR6771XvDH8l39AECBDW38qvWMyev+tXiLileI5oJt18Td3tq/2ryer9RLu/r7ifniMC9lvgv6+q7+/liO+7n+DP5cEH+bBV1/ECFgz+TCW/n+I+XBZgt+f5/iPgy+f5/iPj4AAAAO9QZpgL8AxXJdaD35eX5Z+SrAok+TuO+Snzd+it4I34MfgzwUWGNXEd6I9cl1JJxa/+devi1fGL6Tq6mrmk+7hHf8EHoX0TehXda9XMr44n3zSbVVCK9/XEr3gZfYBAdcq9fo/fr1Yd39r/f8MevRFismSvSc1vl0TpOb5q/rxiLfXxK3+dcviehPr60SK7AQp/m+Ze+Ze19a+Wv+JX98IwmKRbHE3mtiIp6zX9VDiudUrnwgsTKuQP+gX+o/6Xq4VR2YyWD/vAo+gEGEuvpCkIrsF/uu6yerf19l9n96ERd/sUveWvdAR/kLCvEI+WIXELEcdWqP11r0i+pu0IirBSF/h2uesM/jd/CFeiXqojwVCV6vXu5Vbsd7+/wL2rASYT7NXq2kXpOBBhmgd/hLrr0LYiH4j9dyd17oKZScvy/oT75S93XXyK/gtq/QKRHzb+0R6x3X38Sr/Ivdy9QihLPOqyUTp3/Cdxlcsm6G94v7VXFrV+jdEXyXc1QrfL4EIqM/go+EuvNrRUTvlXr55KB20fq5F63/CwhCZBRPUIonfcVhF/gjvd/bXwRGd969Ef9Xn5fYnwWBnphOsJE1xOhfeCAPfq/jPp/o3Xs/yInSYT1j+d4TEITCfku/xNFYk5AQiFXf5VY9ly///L8ter+Hgr478IX6/8HJEfv1/rhHqhv5/0brqVerl+J6Aw0WLwVWVVX4dhTnricUvtR3NIMUTx/BPRH6BV1UsUCK7u7ewh7EdNeEv6I/6/vJ8CGI8OZM2qG1Yuoju75fBUHYTrR+iPXpLCdFq81fzdieqqtXpGIq8YiKjv0COq714Lu7tNeYuwzvCHf6I9UBFHdEN1ovda/617f9boS/kCPhL4S9CfXWIon/J8TxRIrCVatPzy8fWqP8iLiP+5u/6lrv0O7oBHgo8X60J7wVCboR6vFE44lXxCyZNjiUs/QHH1EfHwryxulJ6GfN/r1jEQuP8uEEWvb/SE2uIideimPu6u0X7xVWriUbvlX/YFtVWhP+vw2vKXw1rv4utmriOtE6q4f9F/dy1tonXgl16t1ouXg20uLhDCChR9lt//BEa97/CyJHPBMIWLxAqW5+q7YnvQnruIR631N8d0Bh9REgpetDH64bGI94ntG6tFksPZqiFf7m9Xxy271fvV5b/uq1bEI8nPDm2ry4ir369WTL6J+a9X+5a0R+uPr64K/m5a5Pkn7++778YhF/vELiFgx+b/BB/mw11/PXBl8R8R81fXNgqwV/EfEfBx8R8R8LwAAADwkGagC/AKwIQKFNQDl34IR+7tBXU0RcTPpfJ8i9VRHX8lCFEtNRPgR9YO6v4EH8sEL+ZHbvXrw9rpCuvk7176XuqXojll1XuikpXNGTVyv4mGfQv8RmyaXqjd9fN3FX0sXtY4n/uEJhSI/iV74n4le+dYrvXupV66ivBPR+v5H8Kw2/5uab1rr6u+T2StG+bsN64lexhLvr4RxxPugLvrXq4u+kTvkvivBD/rAjeun/CXNLzXxEf8mF/hX4b+bVgpCaPr4lFyxympfwM5lOnh4KL3mojaX1i0vrHPB2K6A0l6+tGfqJX3Ra911id/19IIovdA+wqIWQYvtfwgMUmN0BTP19E+Uf8aie8X81e6174jXDEnzehC9fP86sda94Ns+fJj8KcdLcVJdob1acd2h3VyL32vVyr0i+Ve331U18TLo6P1Z69WL66/fxP4HWEuKkqkXvCeEORDnov1N/ydTdyBMqSW767Vj7RHrtern7hmsCZRXeDD0EvWS79r83L4RorSjibb/hMWxJM5F9fSUGRfX53HYZozlDEQSel3gQxoCHCqvfa/qpUR8Yqv7PfForfH9ghdYw1CiF8SEaxn9E79fSYR9A9r0j/64TXCfWBJ2KIJ7DK8TXotf+EQmr1SEPu+pqpxQjd73r59dhHS4uI+fEL0BIBn4WE/Ir0OJ94XHeD0IeEUhbmv0R/tEfrvn/RO+WXi0L7f8LeiPWXLcfE8JdxEn+M7wfHBIEgRXf8YhS1fav0J9fhD5Rlc3xPgmq+vG/C1XrlX/kon/iV6qkV/ieomqhmvR+3/CNxPfiF+etay47i7x2sOkRH1+r1gh6xnrLt8nWGxC94v0DOvRFder9fTov/Gbf8LCFifRWKely4rJ1fod+bk8HoW6BaIuqqgTifFZfQ9OvS/8Ulf1V75PhLf8J+r3zyjkRpiXIkTvXX2uXuCPqpUZLamrkXxKM94bQJC7vmMv+M/yScTJhLWDb0D/IX/9Hb2EPjkR/nrBkFYUXz2MW8RiNevSLWJ1ydY/3EL6sHzR/eBSOvvAQAld/DEEhLu9GKjERzJ4EMMAhu/F4EMNO7+gM4IJKKJvlk5sIRbt/bb2AjwwjMdAJ/0DT10IVyP+GP8CtVpvX9ar0y+0bv0Xr9evAzUTquJV+9fyV2OR2mJqmRHoQuIWd/w/8Zv3N3ojydTiiaHE3oYQW1VLv67rmwZYf/7i/mu+/7+/v55+8Qsn333ffBB/l/xXz/Lgo6/ivlwUYLPn+f4n5MFGC35/n+J+DH5/n+J+OgAAAEBkGaoC/AKuviphCwQLrQSeatfzckVy3y9yzcnVTiFqgL/p4aw1iPV+h2fkk2u4jqSTlQ5/65fnluKu47qOR27mvidf9PXEwnzRJfm/Qt4/kQx/qS4i+Ve+WsD+bXJr/qLV5NS93dV1+ya+kV6/qXr6DNf/CMNYIuv/CWbEZBRPpSVJiifpG7FE/IvVzVXXEoveChL30veDfjifdgKurncqxdOiS9rql6/R+rBX+ShCw58TpRFaJ3xHyeF/hP2BbDPYSr3a1xvgS6F5VhT4up08QkTquu9fXzIRHNfS94IWsU3C2v4a+hyF++aK5JFgZ39gexvY4/Yz0GvX3fhPT+HPiuoQQrojBCkNc8CCHfk8tCu8/yV68FK8N/0M9ClRXcdLhPQ2H6YD+bu7sMTBKjdm+RCO7mU6j0RFb7Vu/vXu9e66yd/r2vn3/8qviFtfF/KvfPXPr9CYugfj17ynr16TDZcWwkT9nYK4R4hBLuuTCfFE1hv2/erP16J2q5O6kuVDH7ZV/Vx9Ww/fq/6/rBRxxDvfuHFfvRouwq17ta9S3VVi6942veWit4nXr264D5zsNwh6BF77vgrQVaK9bT4boQ/yeT7oj1p+qEPS437mvRL4/4R8I/jMcQfNeEgWq/tfEIzy7fzrFfP+vv19uv74R9H7ELVAZc+1569XouU9CAQIQ+8HYM/ti/lrkRHrBeLtfq9er/ov/tf1ejMU/jvh7wuCZC38G9cvn60Z5ef4m8NB/4TxbGehXllyUE++esj9teiS+J/+N1yq/g76r1fwYfhAEpHd3e9IvCHYXEeEPkq/yIj1zVQMR1YRoveO9gI8HPlq/wjv+uWX16rBEBV7CAmGOWTFqKfgjgpK2tVVarv3ICIm7u7k9r8ElVrnxiqx0DMR6L8tYiifrk9UR/E6r6CO8RvF0Lel6r0w4nXhDXBTCJf7+QQsR6O/qvV6EdXgjqqqVJv9JCOl5Z6n8MULi+Ve8f9hmslXugRhJXxC9Bn1aK54zeF6J/wuK8WEIItLW+CHWvqz5fQQ/dS2vifC/x7QnMeHanTXguEdaK/zr3QJ97EfEa4Iuu0dzd/LQPwwr9KvVhnXPCYxbzVon+v55rYmu/dfb+lOroCOfwQ6y7wJXwFIJRda0N0R9f+DsECM/gVQRK54IKxfr3Wv+nV6sCDxy26lu45CXMcu3UJKx4LOMW58RDnLE5qvJWjdJXX13WvhfXPrni7rV+tX61fu1fvV7HE0q3ESil61bELfMr1f80Oej/l9XlvrClG7X991eiPVaLnvvHE36n6/nvC3riPq9XrmV4J/mquvrxCxPf33cT8Ff1hHE/Ngo6/i/kwWYJ/8EGL+f4r7wcYNPn+K+Df5/ivjYAAAPLQZrAL8Api+NihiBQTHicBB6XxMFPoX/5Irlvlvk7iKuK6iu4Q6kR+61ck0JqomHcVR3J/Xr6Qjq5K6RO+T5p+VernV9f/Pf111aK/f8X3GS8Tr/+H9UL6Tmn5JLjvm6BH3zcmiyYFP4Gn4CdLXL0H/c14I/gr2IWFPRuxi3m5leYv/82ldzYonvscQn0mP9Av9a3qov5VrHE+8HfoEPwVfJ8H7vOvpe+Re/Xqw3v6X8JilxC4xfRHoT369E+vvm70bvisn9cVwp8QrnQO0vdEy0H/UIouWJUe9oBY6x3xHerr7x3wn+XXlFfEIU3x3yfJ4+veG/i/YG9Ir+BPwrzT1ERHoTl4QrFNxaFd8b4IxKExVyr3QMxPX4R2sPetfiPiEK7xderkXqoH+qAQ4b6D1fdfWvVhPVFfVbX4S4j+xCPJVdVXF1tRDwImRCjoi8iN4+79C+/Xvun+vfr7qEV7scH9fE9gMsMfP9r36+KfLzV+DI1Yn5/wnb/hKqQvq5K4Sk2q262eOr+0M6Tlq4u8EwvsJF6JR38FAjX/695PQ0RVFXyK1cnl+X2Bf2d4S+/qwIO8fvl6N70NtOX/w7rRqXz1y12gg/kr++/1f7X/jgj+hPd8nq/yonfE/N9r36J32vfL+vqyhL0q4F/tYR/qEf0fp+/SiuK8SF7qZEffEdZy+cvhkf+vfPjFv0BWBf4e+CDIMRUv+C0KfBH4fEq5JYP8ghfi/DFe1+vQqKXqJXoR4Q8TV/iu+hiq9YECr4QlFGmX7bdY+BEDHjgp8Sr9AhHV6FfrmrCYyJpjL4mFfQnv16N2In06yv5VyR8Co1v6oj+DUQr+Cf4d+ExOuJ/0T/6//XuwT/HhhflY83i8w5DRnkb6pG7yD+vr8JV/JjfwZ49hmq1+GMurBb+dBR6N4Av/hESWX0kRyl6SMcIGyK7iJ9UIfwh71eSgX+u8gKpOTqJ9UL/44t5PlXYG0MdcPYj2ZyZaERSehEUl9XddlLu7XhcT4OIIxL3e/jqueK+Ko3da92H/f3fWhL9BXKMxpXoW5P+saIq54ZELJ6v47P2iciXq312CnVxHg0ouvAjFXvA+CV7XC4H0EC9jER8x4EsJIkfwLYIvAqgoXouwNghC9Vwkiv1CFcQhHfJ2AmVV8Merz6xGnK/tem7+J64u/rxij/mMYiWxCpRCwR/NpxGtU91L945TYmxxKxKhNPMKWCP475Vy/gWD38Td/fd9+IWCT474n7wx1/PhrfwR/QiHYz4n5fifkwcYf+O+J+X4n4I/jvifl+J+OgAAAQWQZrgL8Aoa+SFsDDg0qTrm50CB/l+VYvloQqRMGP5O47T8ehLGOXRdNy+BB/LCnq8ThjNQzJyTV9aERTiEUueesBI7HKS3rqt1/3CHU1iFdYLeX/+EvR3kGE+/V5+aI9fXU0nMjPa+l7qZSp1yDld+oRXLq9fJ4EP8t7KvfS9+pU7iPml+uEYU9F/+rxGKo7zWKxAxCvX693DC9NgaTo7/aJ3QE/eC34KX0Ah9dL3Y8R1r3iUveC3vwn8FPqLvhGCH0f14ivfr0vFU/0bvCvwj6Anhle61y6HfD/wzRXxRONlNgtidyfX/rh0CsNdaJLq17rVulXuwY+9e+kTvGBBY5VA/1qseFvRe/Xr5pOZYo/m+vif0b3gRzo7nzq3RgkvdhMYvd8xP24a/qvolCO6l7L7fsZ7XsK+gnhyuI9BNonNQzpOv75ZcX8K/PkVSz9zIQ/cZ4HivT4v5ft36E9CdRCF1Lgj+H/hvfr0XyS6oIP9V3+jd8/j6Kx4+r1zq9YCEE9ARjdRHQgV16rCnVcRLyo/a+1aGToSTIuJpivvblvRGnwQ9eBJ9RBRj38EPwj6BmdEyqqu4tXP1f51fHE++L8EwT+Eevr6jvJBILVa/3wXzeJFUv/0I990MVqKuJ+dW8brgrhX0fq9ev16MwQBIl3+Jsr78WJ8En5vKT7BCKVd8v1yxPYG0NycT8vg2Dd0L9TfL+j/xuXmRl4X+PrRUR+xQIvv5ZOeuBFzsNwlxcn1hre2gp0V/XeBw+FKvT8Kcv8NxENAlu/e7Hw18nV+FH+hH65l6q+gbiKyh7wQ/DYxHd4d4xXydO4c+Wbg7hPnk+b0Xv1eIXwmCKur9Bf12MQgXSrQEsUr+ETeEXexHYJ/feFR3hsUvdL145/Z3zv6f2j//V65ZOJ6DbrgSYRXL/36/r/Lr0TpOEor0Ke61/QpaqJ6u6/0XviugJYS7BHR+7P7+/b4I9Dib1zeMUg5lkkvE4T7l/9FeIfr8+vcEJlVeCJejFTwj+kSKvRIsYpMOsqgGZxiKMsrGMUV58QqVc0avUvhFe17/EAkPe+SpV9a92/UQiP3Xd3kzbfsMeF18ZiF+dGeES/z+gj1cn6viFr4niV7v7L+WqDbBD1UqutGbVSev/DP9F9eBAF+BUrfXgXQgiV4FMNIleBBBJ4FsEC94GEEHXd9WDwIy7EIb3UIYhfhD4QrnhYQsu8TejdJ93aEZVei9LgyrFdgSgr+v69f/Kvdy1fN3Yhf1frX8OfP6EvJ/zIj+0jeJclFY6JVKnc1XE9SdWr+BcDPgRgjXfT9WjMieeue7+uGfhC/vRG7/u+pxC/FxPPJVozdfX9w1/h7Cv0Ilr5sCt1/Pgu4jg1+X5/iPlwaYL/l+f4j4NPl+f4j4+AAAAO7QZsAL8AoK+SKXxMVgh2viECJ4n2JLiTuCvkjOWX1fqI6/lrku5aqJrlgp5ER/6ql6+RYr7qpbwHjoYqWV+v/1f3Rf1cVLWveBB4on4RgnoLb6q4pfn6J3zK83Fr2v9fWuI/idcv1E9AUaJ2/m/+RHeSwPP5rsBw4ILHYzpXv19+vvkWLFE68FfoM16vxy6rB3XvBD8M75b9e+l74jv+Ze8E/+hC6/hf0XsUv69N6P6/VqyZ+viPCJOgT/CvX6FddAt+F/wiheXgZ+vfwzREq4fCHglEeH/g5XgzrFWEaN3grFw8KIXELLzVitehKReaK4kQbVaqqXMGfix+trVvEj/0bv175/MT4gEV34/wwsXwh1J6r3QFP1KvW+WkfvaBGXVXKy0K79e8b8b/XqoC72vmELWEriEL6e46sN69De8R9V6I6+vrqbuIQU8V6913sX7o/XxK98lVOvfOva1iZ/R/SZaJ1j2MXt7+Eie//xGL6/jepe/kl0X2ehxBJsKvuE/BN7CgIO5u9Ff9E7yOTtHKn6+rL8e8U6xT53hMYhZsa6At1eT6uPifMMvdYIdYbKr9AWRt/OX//5/0V+urusNAtVj9f16N16r3kr75flvlRe+D+EeE/hmhC9faydd61GcJlO9/ifDRq2bwSvzOsXrtCv1xvhgSjv4IC9S75LrOEfiFrwXhD4d+l/L3XL8vxCJ1cCLCPGfd19clC18Si9L6K8WMRFeubXH+sM5vG6qJ8FjVqr6/iL4pepf3xOKJn4lerCGFOfX69Jzr021N16VdO7u8v/zKxri5PAljOgIJt/E+E/WjMdRNZ6/qu8Krz0Xv16bNl9f3wIMI88ny/P4rqtV/BJ1VyR693EIRWOJkT4mhS2ub6pX8QrrRcqxv5fPrNQl8WT/Il/1qgQn/V5H/CPq8nXySCFn9G78ERdV78Ehqr5kTqf0aqHKeheerLqvta8D6C7wLYKEeq5azegX0R+nV/jaqEr9FTK8P3VzoJqTZPhDf8I8sRy7/rnvNlwTi6oFLXq6X36++Re+l8ZPX/BB8FVF94HgSiP8QCW93u7kR1GIhcfwEKC5Ei+WbBBRXq9XPmRf3wgiv4e3o3zIz/NVSU69GeG+eZ/NP6+kfzor45VBP6+8cu/QIqI/d/L1Ez19ffV30Dr8yEviFl9f1g2wx6vfUZXVBKCG7rSMtTXz6/Rn6iVYupZrnV/ng8EL1E9xMTd9/39z9/cGnyYSzfWCriFnwbYNPivk+XBtg1+K+T4Ovivk+PgAAABBBBmyAvwCr4CVwecvyoPRS8sm15KLH/X/ydRC9Q5bXoT8vgU/ywj6O8d6K8+0hDVyIzy9L3ySP9FcpfKidiFxC1gfdCFdcR83/cZ39/cT4EHJgQ8JcQhLQx6EdXJW699fN8R8i9Xq9VE/E/E+BT/Er3UTf1X19dcsi/3/CYpHmXzI//mV5dV6UcSQj7HEMtSP5F6xyJv8ldL3ht/FeGe/qxi+xxK94Pfgl+COi94O694EPjEZqLy1Y+SsEYnoI+vVffE/LCPNXNXNN6G9J6vG4Jfl9gT8lB/WGfz4lTZwWhBS3lXh8dJQHP19aEX/Xq9E9+vUv0XtfwrxH8gxfReTeURVxiudyLzJ4GMqLF1E+LE/PWf4n52vdRYIt79eDYyEd6r0vr14Z+69fr14IfwsjdCXNriZMQhdiFkxeL6Xr6+vZPl+VEeu1b519WL/r1v4/fNSv8t0BkAgXy/qVX6+8f8I+wObRYu4R7/L8L8Wxgv6EekJ9+hfYhcYuq4r4r4rxf+ML9/JJ/cyFP3q8vP892BLHq9cT0EBfgg1X1L1alTqVX6v7X3y3jCovV694nneEhbOkdPhBHexfb5UToRXgYfhvWBBF3b16Hf+1/+r/dVC/hQbViVWNDmJjTfgQQIvh/6FIRyrVyctdr369XAnwpUL3gxyYr0JxXCHiaF94Yy7L0CsfXKhj1UI1QIh6O/kF3TIiPjib/F+GQQITl4dCPpLnPiUbt1b9P86sdMVIOVTXgQat8HOdhuE+exyC2pP8mK4ys4pX3/dgrXY74WYre7v+FASkd3d7/Hwh2GfSGeGD+EslRHQEMV8viN4/iFV8i/+Rf9gpa/oQrXj4VFLfEx/hQTVVVVVVVVVVueGV89E+v6/BAIQjP4G1K/yVxLI7/O1eq/k7C4tX6dZfIvdAnVYayafjeuEfyhPsH/tew3vBGXwTmQnoZ+bSrJ3vr6XeYUhhMNXJ6F+6+hvrVuvxle8QEPJrF8ZK6Z6Bp6H7yaO8M/LxfxfWv65EIa8vy6rRnJctX+XCSKO+r2/iERVhGuWuSJRe8D6CRF7wLoJN1yL2uSpOe+EPHZ6B2IRX6mV+tE6FxC18vSE9Lc/2hnVh09evqwn1X1moXXhr4FwIrvrhuIRL/CCIRZ4FEMVl9BXXIv/m71fT82OW3Wr93dBYR1o7HxHhk3zQ7ev8Qquk16cv//3XclgiP2le3WBd/EoQx86v+v65bfxFCF+lfulfvV+9FeCTW9CEd71V5L+6vlrZEIee5ep+tWOr61Y66GK7WKVPcqv1PLfJfDnzYQq0vUTcRQhcQuIXuL+LifQx4Jfi/uxGcZ3k+K+sMf58FWG/i/q/r66+I+K+T5cFWHPi/m+I+K+T4Ifi/m+I+K+T4+AAAA/NBm0AvwCmr4+JELeC3iFmsBk9fFwUc0vSDz/SvNcvz9T/Ze7+VXvkXq5Pm/R/75gW+wEL/V5L+5PlgruK/vm6kl+TAQOTerilen/8ytXojYha0I+EYR5kdiFRRJrfJ/VTdcr4rvuqj/l+L8Cb6AQun9XpXyIn/DNe38T8SvYonX8I8yO8g5fUKWPHE2kukK6T17wvrkr16uVF756wWqqHevrqwXpGYqopF7sDufv9/deri/k+JP78sLhLmrmjbqK9FOlUC3ePojeE/hn4Zr1c/wiheXgSa5eGfYHMId/f3L4K/xtYZ+Whkc7E17xqWLoHP5vBO0Xtfr0Jcci1E+vSckSvkV7qKvCYnwmXoGYnr6XrrDJ8UQhf4hYnXDgiqBR7+5fDNG94+vefeCUJ/F/E/CfiP34j8EHXCHCEtaE9Ji9+hrnjN8qEeqtCWKya9BR/r9EeS9F7qWsNevqW33d8lKv8cWszWLHEieDHV6LF6XihXhAnxNcTZ2HYQ/uCahC/CV8V8VNugl0VSJLWhj9J/KvX69J6/8HzRf+DL3Cm/CXwh35/xV8qJ6uIRe+K+Kxb8vBj/Qz2dgnhD0CLqrQ/+dn/RPfor1iyzevRC8eCnwQ0Obwc1c8EJbsDWEfl7+5etE/T5v9Xr1/8/QQD/x/cT4MF4eofEq86I9L9E6u/TRO6kXLqLRcr4n2J+BLhH/iUJ7uLq4XRMr9ejs1ctNQzo/eO2MQxpKrrclV9BQvh5K5Vg9CfxPy/Er3wj4Jgij94U9iX9I3fJ4RHeDOjv4Ja98L/CPyoj+Eav0zK/jq97P9r1aVcF8MVzYmhLxD+CL7RHviqubwh8NSb34gIAlu7u9/Ir+TwsKrCVX+b4jvriPiPCfwhxbl9dgdQjVgfQ36on/1e7pf+kviF+eKL/9RG6E/9LtiOrov/xRBGqxi3PDozxf4lEYugQil6uT4pXrkXvBCK7As6zfJ7HUfs7vsXkwhX9Vq63+CQU99QsKQuZ+6L3SForRV5hm01rRIrFKQixyjDJonBWEKzFrJ8m/Qn96CP6O/hBUO5UVI7wjc98/6vIIW+eb0T3uU1VmvkvBITd6tfE+Eevi9f+BTD3gdwSI/SUNF9atPz1QO/VQ/WjvVa9PkaN4pckT0Dn4byUC5+DShOvA6UTtcM658IIhCStt/+M+FPdE6TlviK4hFeq64j4YR2Kr64e5+uuaJ9Du+16k1HyfaE99+Mr1L9G74mt6rV63RX+1eulf58UuvnV5rtHvMMVpKg16vFLl5KXqpPmufuX4mqAh+v4mItHgkyYQ+evrxC9RMH32I5/8GXX89gowa/G/Nf3zYMMF3xvwd/G/C8AAAQIQZtgL8ApohAmcHa+b20Ni+vkqpJ7iVi+XELXLNpL1YLd1JLgv/EozwS6oX0nV1JT5NCulwJyR3qov7V/lvA85Ljvm6An/CAhem4lfwx6EvFar13ononmQjqqK6/RPkuu+L6hHwIPwKfwOOr16VfWv0V79fwmIWuab0JaEqmQjscTHb5KXzYonoCCL68npf9XxOKJvCGsCr391yfIveUnyL1L9ehnmk5p31xaXhKqAnieh3r6+ojr7/G/hPwI9CzIqXJ8lYijd4e+P76v20bvDpfB6E9/CSueHX8UsXh/4Vwzcd/FZMvq/6v3CCxzX6vVS9fgi1m+f898IEK7/BdRI58RrvvPrFZsOjfE/179ehfk/kwS4itBFiXq/QWMvrV+5P0dv0T1ei+/X1Zq9r9exRInleC3r/ELjFN+rEUTtc4QycvYFtd+/6xdF7HEq28G/8IYTXwlXoa0mWvR1SIIOeiK/cVWiIsXT/asfL7fkLJy9Qyr1gUD9B/4IOOIfe+X5UK75K7R+7vv/XvP8T34RgnGLWtfZ2CeEdUEuxi61/jEV3+1aqYfROu+LCCIE59Vf9vrwEDEErS3fllu7vw2VX6B/u6/Rnm7V60/hVC2P1ehxONl//xsod9v8XXP4nXJ7L5aGdfovb/Qrs7BLCPJiF665UFu8Equ9FasTXopVxBLv8ta/V+9Ge+IV/n8cjEd78af9X+1fpiV7HLfqHegIAb60VjrX/yfN4IxC94NwhnZSKeYJq9cQjPMORF9b+DuEe0fpOeI0LraR/z8JbWDPviEZ8nv/6v4EvWIq+thmECbu/jpKCxOl7CNG73X98nlo/ePr+9nX/hsI+fJhj+id869v4KYez/a/Qt8v/WhDy6OCUTWqquvOK+mI3d4MqvjFE6JVwqToCGTrRm+fzE+kV+q6XvWe+I8J69e8mSgKpZ/Rf7/hQUt3+Tilk9C8/+vHa8EIhVW5L4Iqrv/VzIV1ckgxb3y9xPVddYihfdA7XWid1r1ZO/VFfHPYk4nxLy//yP+HOLVrza9E7XmQIi1XmBfmwbepUKrVcfjF989YuCQu75eCcMK/g7CUm1097VbGoW5k+2q7uy/XWr53371xG/4TFLF+v75df/oZ77Rc3gjOi9r/wi0bvkRSrPDL8EJewyTXUvQKBCL3gQKtrifGIgrH/L4L8EkZ4hCEvESZV1PVLdmMhr1f6GYxFcieD34O/gp/JeDagl0OVy/59dI/eq98l8nslcTr/a8tVN0tWhPbq8whYL9fkRcqtO7+voEVE7rXpL+/5/nkw0l/N6v3U3JBX1JXE/E9oc+IVRPf39wTfdC8V8uHOv58FXrnwYYJvquL+f4j5cGGCf435/iPgs+N+f4j4+AAAADpEGbgC/AK3g9wV8kq+oznrlQcixCIpak7AQPv/l5fl6je+COghieSqkl5+uudX6ln5kdjv6erB/oQrrRe4Zgs5q9EcrmBFd/t/r1VS9+vVUt0Ag/X11gUdX9SK/Wi9WOfzVyq8MVUuGviviscOX6+RE79e+IxRPhP4uvfr12BxCPgTaP3X2Devdr399VL2D/399YIfgjq+/m7pYoSuaIXxFfGet/Qlek0viF6sL/G0RvdexxK94Zr3htoveCPvXk4jTv9/dL7wIu8Kazfk+SlxXDAxV6T5eEojiEbr5K4nWF8/ixfj/hH4/dHSP2kgLYMP4SEXfd/wh8R8iN1cq+8OLxXxBUVq2r9E6n+i9XBNCvC1DEL1J/RZSrWeuTpBJq5P6yfDO+X5fn6Be4j18eCJUOIRX8Jbz0Nbx/z0bvHrz/L+DgEgiRmRnughhJfCVcd9IKv4J6yqgjr8v/9evX6lFEd1pRuHh/YJGhD9hEIK/goN6r+KxLXvCPHsYTtlhLD9cJCEE/175lal7/rV+rdHEovdcXgxaHOeCF10CTqrzdq9CERpr4/wWC0JfwTC5MKfjfZ1ff+via7RvdfxPxf6++PxbMFVRtfXC9BnLbxKwj/EUFf+HtP+hxBQWqx0BBCKvXZSbvyb9f1YFICijt9q8uCMR40Z4dBSitfo3T9+DAEcMXz9oXaKqELqZG+d14jrBKHf4YRn+RX6E+vxTriKsCyGFesJk8nya9HeSwfpEeqjPlvhGEan60VpvvnXrz4jR0VnhsR8SCI27seE/j/gUD4xGV/BWbwqaWiC1frvk8FesbQnpxy0vdIj9d+v/GYT7XpvvLR/16PGk8Eghden67VCv1UQv+4y+VXMcSldJh7Jj9ct5DWv0JfGTkxvtX9VexxNtfwwIX56ELNk/PdloU5LX11WiZdWuXgXvy/a1+CTu+WOJZp9bcK+BfBAjsdALEHHV+Oonfr36+KynRe6Hn60d9V8mG6vWXWUd8VDPdc8y15N0Tsn14d3+Lq3i/glrXhbS+q50WvBFV/A8VK2uEZESLEIiO/ggBDd9yb1/V6/65LvvQlpNCPBLhvuL9CvWIW+Re+X5UXr/Vf8XdTyVEoj9av1xt2rENfWlE8slL3ybr/uSa9X8P1Y18/XLf39/6K8opYd6Qp4QXJ+BGev/l+Wvl7xC98vd1fXEdwV/L+I5vrBd1/Pg+4hZ8EmCr4z5PiPlwUYK/jPk+I+DD4z5PiPj4AAAD3UGboC/AKcvjdf6/iV8Rr+dfEsNbuCtfSJ1evV0ry8vzd13/q1ctev/1f9X+T2JR3+buM2+pe7oYokaUyVx/dwV9I3fJ7V3NKMV66+vXxOIWT1/8RVxkRfBWMX19L3uvfr3xCxdgvyVOvXxfgVfgTfgYfQCxxdxMFtM3yfNXN4d+H/h3r/f/34KdYr0Cn4JtYFkt6J7J+pU8P/DfX9VCMMDkNJnvmhT/iEI79eZaBjriJOLxqO1Xgj9AXwRL1434hr3k9Acz9J9V0FqEd4uvfr14IcJjkXFiFiLhLwtscQSvTriwxXuswjd1xSNHPiFc+IWLrrBCL+LQlq2NROrKde+JXpOEFf9E7oD+I8EOste8RvifnXvfxvoHvrrjoYqErpc6Coe8e96rfgiCW73k2fr+5e19+vXiP2veE9jFWP1N2FQx3JWI6/8fXvpHesu8I/gTEOi7CGEeKQVKknStQ5ZrxO8L/CeM5OuSpEOevXvl+ZG79F77Xq5f1fHEKbO61d4Z3hqsUvJ+vvlXq4RoezC+361CZ0Fw0yzeDXzLGda8ZisE8FAQd933PAjwR3fc8FJ7XJYJOqv8vV9aJ3Wr/L+r/r+hym6b4lFf5/JqtFf4Y6UpdV4a/F/PJyIV369eYei98F6EdCnG+B13l3USgj3notfP0xPtLHiFjOtvDzriUMeuK8M/CYukvoj1y/E/P+i/7BwBJ7/mrmV/BWIV8v/6Ln8FtFfX6I9+v/JXxXaEd1E3xKJ0JcX8knob0ufeqP+fjq5PGrwR5McK8KEFDL3d++CY+uTr8NZcv4rww/FVfx2buGhSz0F9ZP6FvrzZl8Pk1VeNlJqq5K6+ZCH8JiFf2lfwz9tX6H/k61e159cngjNWnimXxm+X5b5bsCTXtv8LfPy3qi6m8EOtYv0SKXnQh6uZXkqkX/6vWf+uY6vwyT0kXugY+l6iEf/jq9insYtvk+WUWwsOoKhb4wvmT8qCvXloxU9qfBdROkwQ9/+J+BfBFrBH/ApgiRe+IX3y/r3WvdcguLMw57ojynd+L+E1C/q9erz+ivVxMm6t5aN0tBc3WtdCoIu714EavvAUDWLCCg6eV00/jERLLXDEf+idJ6/+frnr60NbEKfOGxHgj1Ud7oQ8L9fPLfebLp16J32rXhDdf69Y5bVxd+r/PS7/0d+4mq7vqojrkvhf4+9E6SutwRXfef1fpVfrV/AhBFXl5e9XjK4X+P+7v7++r6/uXiau/v7+/uCb6yY37xn+YR38uCbr+fBJxHPg4wv8f9YrfxHz/EfLg4wx8f8vxHz/EfDvx/y/EfP8R8fAAAADxkGbwC/AKIIWl8k3oEjSiFisCDg0wbv5J+VX+WuWe4Q75uWC+5qf6PF3ES/X1gceIWS/v70V5hCI/iYV5oX9er1ik5t/1yovfJXOv9c8694FuvdgM3399VE9SdSdfcLfEKxdwjBaIX3ROrZPileXCf9FfFK/n3/3r7oCl6+vwItYvlt7Lr3UciReP9gY/za5uF70fq9HeEOLRmrBrkW8d0DH19fX1/3w6i5eAga5fBEvvAgPqO8HXqRep6qvVyoRr2XX/YXr3YX6v6XwhCwxfRPCSF1P4Iu71VxyGfO6WJlX/gWfzVQZF9BkX2C8ehPu370Tu/vocT18ILF1CVc6N3Uta/L8vyoT3t1hoZ6onXg3H7+CiEuavQ/03S9E+ryv5AUBItlvLZb8pOTr7+m+9F7uVe7lXu4le6C34le+EfBX6Z+k+4n5l7x350TpOS8vzq8GwGhEi8IYUEIJ1pIp7wS/ajl8l99ctSoJdWBCV8snOj90GvUcjt0XqsNUbuwO4IVivuuWuJrPzfD/2C8RQvv7e/hIfDcqdtv1gXaFZXgjx3kEO9/orVgn/dcsuBYFT4Igv4MAn4Wq8g3GlK/pnk7QjpuD9EyzsEcIVCs39DqCFVQ2ry+uaKw58E2qhTVASwvN2AnQR+Jy89YeCqENemiP8nwp4McnJ7Xyybq9cLo1QvWh/TXaL3X+togXICWqJI7+bu/jPCaqgdh/qbxNEelhGEQwCEju7t5tYj5v0i/l9E7wyIXvCT8MfCBUXqxmrAmn716uIRGPiIa+OeI1l8P4//CZPk+IV/iFf8EXVX+YEPVX8FIjsC/7BBBH3d+xgnr9Ev1f9fnjxy94bGVn1k+TJwii/7iV/jideq/61crzCHvC9R8IL+71eQcq5u36l+l/5MtD6Pl+i++RE6uT4zzDPgkk9HfqZWqg6JkrhLnlpYj0TrX0CitV1XyWtCO7+66wS3fd9+9e+fr8BsHxynpleBTCngTw10AiQRITl4FcFG/kk9f9FCd4WViEUuPClWriPhCGfRHkwxQu0vod3sqsa60Vj8EJdV6rAo+gR/lu9E12SuvAqte8FR/iARXd3p1GKXK+EEaKq5+6vR+xC9/aMr9+//DfwnV/iIcvn0kV69G7/v8VVr7RvEliqP18iJFjlevnV8cp9ruVX7l7+3vuJ+H7AiZtUL/E196FP316v1J1V8iv1y1OryX9818GC79P/XPxPcT39/f39+MQpXxC931fX9wa/Yjk+TAwZ/8GHrnwYYLfn+O+XBhgu+f474M/n+O+PgAAA7BBm+AvwDG9IED/SvfJLzq/y/L8vy9xPy3ydxCO+uT7jvm+axCMei4mC9eiTfVfUqO/Vq+l9fyXXer9zSVNIv4K+SuRe/ROrm+IV/16ngn988i/+JXvlV8QiPupuZCeuoRgt6k4j47oFen9Xz4onsBniuxHv7/Ag8v/+u5a6RO+b5KX6L0K3ovSDlpkPuW18I4xW+va+TsBDj+wp7EPvvECccTf43EoovwLNX30vbDCJ3bFL0nEonVQOfhdr7wz8EJ17x4he+IRO+aGV9II+jvBEI3d8YiCHKVeFO4QRnPiEUqz6Uqdv4fFo7ERgxfzq/6xzwMnuVCOxBKvlvnQmL5/CIlE7x/wyJ6AphFe6/haEl8Uj5ScdCJf6/7QyKuX0Xr616XJRW+Wsul/4K/dq+OU+kV8iv4pfKsVLuLr0TpK+tF7q9rwLkI+vVxmvmoch+97a9r+OfyV6CjxliQT96K/xPgsor1Vo/eHgp4JieGuv/lQwqeb+vVX4KvV+DLv+ElWAgBuv/nQTil/9ejfBEM3dvBTVzoCDLd/WrljkQ5HIwbya9f9R/yq/y+T+iv4JB6K/wj4b/HfDGLlHMFX9In/17sDCNr0bqovp+wd6fwIsJVzeh/f4omvXr9Y8bYHcQhjEtaJ3yr/rrifhdFY6AjAvrVe/XvnxBPhkIEOq/C4X81Ebr/X/QIdVondyr14LionZ2CGExSy2CHXPXoIVXr+d/DklAQfXJye0C4U7u7396fYKfTFdw/3r/quoro3xoQRO7A8hj4zx/Oy1YHHXr/xFX/V75K5M7DcKc8jX43QsE4SVetX8MpEYv0RjfgWPgThCs8OiFeTpEeIoCSEEXurRekduGvmq95Kv4Q+TJx0J1y26LF1q93Ey+CQi1t+iCuYSac/2OROaWgmPvm8NjEWOVj0vdA3V5KvfoS/2r1YEnXon/g474TGIS/MjiF/RHrQTk1RGrPl6Qp/0Tvk+TwTUXtXeveBa0IUuRxLNOo4k15MuBDCSPll//1gtDXXa9+jePifiUd5aCdCX9VabmRuhgQs1BihdVkxPoZ7wT/0Uaq8J+giZevGQRb3fwKVXxiIK7+Aiwwv5eWSwL/55qBcT4iuMgi9CXiOWu0MzH6+/X1ei95PgoonXWr/LPUqvXr/ruuqtH6DHLV+6RHuu+XHLY7je775V8Sr9av31z1fV8vNBXy7+/DjiRC/f3iFie/v7gv+QRxfy4KuIWfBdgs+P+f5cF2C34/5/gy+P+f4+AAAA61BmgAvwChr5I/A94hfSBM9YGHKvi0NYg17uomK5Ncv+r3gccF3JfJv/0pV8ajd8Sj9r9WKqLRHxi+vmvdFeQQTXFwXbXcdfJr9E9r+/Xr+n8/gYd8i99dRnX19aKx4f15CPeE+aFnxPLf19c/4hHPfGifAnm8CKIrHNe8CD6A9+pa5L9E7X+/4KOL/viUV7r7AvhPv8L/C9EbwnXvE17wz+Orgh8CjQvMfIuYlqukNRm6r9E7wu8cSannghaxebr/f8KjCFS9YhY/AifisYhD5/k8GvwIPwZ6wlrF+gXn6L+PR/a/Xvhv4rxAjwZCOohdVzSV9dereJr1Y8SvVh4EEJiFk9CejfVKmutDOvaqklgqtXr17q1boe0Vz5l77XLoFO1/WFuqiPSbIFfYkFCnTv7iOjevxNXKwqfxfxPxde39IR0LDEFXvdhXWLx3JVaCT9av1S/qv7k5q57w8Eap0NfqFvAjUR9X690HwS9gXwQzeveP7/BEKWstCmHaCuUJL8UbcuPd/jzbvu7vwgodjX2200+CEt1ddoz3WrkmjfP86L3wiitVfh78b6SL3hkCH8KeyfP9oV339/PXr3g2BOjdnYJYe9BDNPUQCK77H6/r67Qh7sBUgnVvl+fovyUZ65Yn0J7wThNe3/7Eojyr+38EsP+hdTr4SRnL4hEeRXwRo9eIJb/kuCO8ivBLRu8P6WviiFeuXV/BKL8EoV+fsCDv0bt/onQn6E9LoTH4JQh9VzbeEIrxgjfNFeBHXh03QEEZ4a1QV9CfdIneXeGQh4Xy43VAnoT/5fhPrRG6/1/17XzCN2wj6F9VRcVvWK/r0/KYm00e0OkqTr6H/RqxNcx8Qte35vxCxVxFZqO9Vr/0FFfGrbof8Zt/AoeKwlc69GYhVr7r0vL8/VoU/y9fX0CqvdBiveDzjlNdYhfkWvL8CCGF94F8ECP2sDODjXvAlhxE7xikoFPrRf/ov+wJtXuqV7sC+l+W/F4d9H6+f9Cu+68EXVfV4Ieq++1c8n9X/W/YRr3X0E/6mTwQfAmfhZXMQvg5GSctXFo3+77kxCK/ib0EOvwIBPjJX/BD6P/s1E6/Xvllvrn3/eBSo0VV/LVx/erRAxDT5yoTgwwQ3r3WiflX8l6I/2rzikR/OS77vV7SXPNy/LBV6p0Vf6/8HRdcv4KH9zr/uf556vrkEL94hZPRWgq+UR+CHL9YGDr+fBdxCz4MMFfxfyfEfLgwwWfF/J8R8GPxfyfEfHwAAA1VBmiAvwDG+g90R6Lb5e4vvQh65flm5PiO47v+SRfGwXcnVIvb5NXlv71fELX/Lr+hC4pa6V6vRX7+/qZWriYLVzaJ38lRXWsXzX6v8X8v3r50XuwGyI7+9G758cvvl/RXmf8F3WOJf/yfr1Y/quEMUT0H9V1z+CPViq90BW9fXQ4hF6qhDpev4jX8Lv+EahGqhHrQvLwJPGLOmIRFdAv+Xa8J+gj8L168CD1j4EH2wgi12xXUR0J9P4EFr2v/0adriJqXn+Get/4hE6Ca++I8BAiPZEWL0X4jr8SJ6DLR3OtX8JtE7zhHzawr8I16sFoKl660Z+tSp19axebWBBCfgQwQoWx0BhDPWjP0b1/C0KciEvCtS1kKhz67l7BL7/opXf+vvnUqz7RffL4nePr1YzVHq/gbvj/xHiPiN5ieSj+dP1oR3XteBGhYYh7vCndKu0EOq9X9JXqr/Xtfonv175ZPR36AuAh+JQnvF7wh/QrteMy1Xgw49kE/zb3rUKCEF5e/dajfKOd9YEd65Yjr6xfVdV1q91VaaJ/1Xq7vD/wKgf8IPoP7GxY0ulXl+ffNz8F6CGUJc8b6CseKsGHqbqZCn6ilfqTwQlV+gMIIevqvl+WhC/ErXwz4KtcVXN4fFb3pH/4RCsuMyP4TQrXXCXPLlx+ISFvXJ3EdaM/dXm/O6ruhfwxqgsG+l6HewR/hDf/j/iC3j8tgRavdTo3Q7ugn+KxqKI1XhdXhj0Ud1MhTnzIveF6pVXHaI+uM+rRXkrV+tX2lmMvU/iPC+KsVvjs7DsOrG1ifnHIEC2krV7xLrB2GPDNHzFWBX1mG3YE8QivJl9/f2/cq9D3oT+K79vzOZeFvgRvzoIZXgeQ94EMMIrVz9CNY6iP+r1z1juv/GULc3fBZ8nYFsOK+Nc3fHO7dw98IQT/Lm9yeEifEeBMokWOU1K8DiCBkd/z1yyYS6/vnViS/J7/19RV8/wnBR6N1VaL0lSVo91q8lihfevd6v+rxNX1aOx1wUrn6+q+usl3f39rfJjkKsfF9SyVory19/XNywVehTSXL0CovX1yr/X/UbiF6uS71y13fd9/39/fV/f3iF+4KP8If594jefBR/gy+XeK+I+DH4/4j4Mfj/iPj4AAADjkGaQC/AKyX/4hAoehCwYcn0hb3ye0vj9fxHEq/UT19clze6v+iv8nQEH8n6vCy6mhnpE77XvJr17uI75ee7l+XXzy3HQU4nG7XcyxXzeq99L1+v/lRek0J1/f9oJK/UZ1/Ea+oJu1v4Rf63+J1/1E9gUSyc17ona+Re9r5Nd69+vV38qLl8vgh9AIER0T19fU6J1dL3699L14J8J+hPSP+Of9XL83cTeBJ1sSjNdA19fhX2BV+Gfgh+HfYEHv/9HMngxoteCEReO/J1XT9X4X+GWhXY4ke8/gn1xEE2Dg/UR1EL861i+IRCpl/Bj/yCEXrrR/nTFq3zq3hMI/EyjiScXXxXYCZBN2Cujd818t8iL6sSt798EEFHXzoZ4vuTbQnvl8mson5172J8f38X4R9fgoeIRWlz12hHfa9r9erdC+/X3YHMN1wKCGRdXCowgVnSFuupL9BTp8I9fy3BB1aFv4Q+K+I/JXo3uw2FEeOdA6+Jr2b4f4WHBFD3/tFReGvQR6EMEvwR68wzVX6I/yL/7RX6ib7V/1/5av4IA34MAQ+K9aL/f6vjZwvwcUnLVsf116Ge+DlEy64e9BPNEY6CEjvtfyLBeeMBCRV3PdXyf14JRPVTV6M/6/rAyAn7BsBHk4hF75vCMER1X7x/9fy19fVoR3wZQTP7+e8XsWhKSMVwR1/WT46CMRqt/lV/1fr7gj7/HvyfVf+CkOL3xF4ii+dAj1hSvQSehdol/KIJWqr8MkNWqrBCIQruorwhrm+bw71xXjFekWvqfqdX6tX8VrFepV6sTvhjr8VvhH4mTjoKb1eUUiKVc19V1+q9XgoLu+7mUbX0V69ffP2BP/CfhDJQOgghfZPqv9CH6Dvp/tX+BIh30JtGXaCDnX1V8RjlZjePAnfi1z0vi9f+D8ESL3gaQYdALcCB0AmwdfJJUb0/X4Qo/VpVwkrnhj5NC2EnaHNUF+iV86JL8FFVVVVVjlPAw3rCVerLRO9te6mX1LAkYjGKJaV4Iw4iRYxWfvirsENe6eIv6+ojuKvZvlgn9fVX3r1dr3332uTxy8scumSrXphSuq1fr61Y68QtXFyckEC8MUJ+Rl/fu/k5LEL1L19xfehT9LVROKVdffV8TcRBXXKv9f9gCGCzCF75O/uW7+5CelX8TBX8gj8I/4j5sFHELPg2wWfN8R8R8uC7Bb83xHxHwZfN8R8R8fAAAANgQZpgL8AowhY3AQOXAZ+TBPgy3Qc6Tk6Sl5/lk55OReqoj5PAg/kviVeDHtel57Xyr3z9XWB10KVL6/qnV6X691EXcIr+Cnlky6oP/aXv175K5K9eoYrN5cCj8Cn7AUYmqVek6Xvm3/BYIWT17w38EPw/8Evw38EPoFNevi174vsBmv5F7xXoFfv7++ub5O4cgh5ooYtKq+N+JR31/iFd8QvRFgRy/r2Nx5kZvAx98NfxS9r7X12G/QKvWjdWF38Z4KT+CH8dBLoT+CIa77/ICUzvu++T9f/0EEI+YhT54QXvAx+oQRfn2vXiXE4EwYsUmX9ohU6+vr60Jen+id5fzL2/hTxmCj0INV18i9ffk3i6F94mveJr1cnyonfLv+sC0+vo5PDSXtdS2uOkXugf17rR28lE7wj340DJBVSNN6I9dr3UWuXz169+vfFr3xfoX8K9BQX4KKFv4WCnxNcTVWh3eBI+hPs9P9feEMFGBB67k8EZ+gmqVfFZd0M10hfZfv9H70FV7wqE74lDOv172L34RBz3wzzy+h8eL+r0IfEKSnBucENV37ASII/n81CH6aricQvxMtS1zeFSVgwzei+ov8K4MsEz/MetfE1h0nh3Xgk6qxdBF4ohmq5YcdarxxuplTpYr1E+HNZvXeN1wUIvXtK/hrfr46k2vw76EvE8WCKq+5vglaVnh0lcR3CHcnxCCHfEIvVl/LVjwj3E9vdB+rlcZ5fi/xO//NRXvCeSgn6/hCCfTBDVd9PJ6f+9CH7lV7wcZsf61/7JXiz7vu9KxYCBBgj9VApSN7wgWUWy2eE/yIt/Jov+/XAjQ76L+K9BTq9F9390id19za6/Z/DDRcqGKk5jlPTvBH1hb+BNBEj94PQ9WEKN0m1E0DH0+1+CXEwRC9V6sGOtJfHTa90vitYS+Fvgo+xCJfEK8QiJdBBerde7Ctel9f+j1cqK8opFa7Ir2/4JMRRu8PVq7nvb/Xq59clfeuqVzHLjHxOORMXUSvd6vfav8qv88V3XfYKCQSXLfrlJWr/LVd19/d1fjlaYvlmrV4LdUZ513+Cgvy/L8vy33JxP39/fd/f31c/f3iFgl+J+8I/51/Pgw4hYLPifrNr4gQgSxHy4KME3xPyfE/P8FfxPyfE/P8fAAAADu0GagC/AK6IWCH0ErS+to7kieX4nf8z5ohCO7jOmIpdcFHL8q9EWDH399dInfNJyq+IWsDqIRX6ietXk5pBxOv1/BRreDvNX3+Qnv7onfSlT5pOJ+XqJRX7hlTppOJ17sBj+39lxC/dVFde19X6jutWgk0X/uXvoUSlHE3xBK+WTdffJ4ZfzfonUv/Deq64nFEL4P94EeveBN+HxqN3QCBDPYKfU3hDVfXDvofU33f8WhXfJ8+ORWffCP0r6+Gb5tegxr9E9jiVbwil68J641H7wO9csXs+KvCojfhPWn+vvHZKAg0SLwzJd8EvLeGEhrfEfFIZHK5PAl/AttEi6AVonq6wQjfBWH0LfsDSJ7E+/u0Z++sM8USX6AgwQ3fIvwhXq575f0R/E/E0ftfr3g1DPh8I6/+EkIigq6rvVXr3g6J/PpeJo/XoR+r6eeesdXvDhK6QirfEfYEsQhrvCIR8vf6GezsEcFVfgXBCBA8vL9r3y/LWOr1Y/Xov+4J/Bh8FBkL91BRS8EghCO8RuohGl5xHyeP5vh/7CGRnv75295oTQnYIYKcF/7Qaen4SX2Ce7+qvXoQ/VdWjsdWvWKRDfz/E/Oj90BEBr4SC/QJ9cKeDINyVr3XRf+v9E7dcCquWdh+HvQQzTr4Q1+r+CDQhZaAQIKfFn6vr6vqJ+VDP9QvXP0Iy4J14EP7dVHq/wn0vVL3QUr26v8G1ezsOwS+ULPf4bL1VZSdAjCHRfydasewjeHwyYlYvqb4vqZe6nr0X/URb1BC/D5qxDm9f+q/+VE/vcO4J+dCZeLJv3Qh6ef7+T5vjvhYENV38YO8aaqrr6l6+r7CIbXuqX9dL3gxC0mgxfEVx6L3UR4ivVwhDvoS8VjKHP9K+u7BF3d/T/VjuIxiIgefwQfl1Xr/V/1q514ol9Wr9H/BV8qK/g7DnyIsroP16smJ4JId9CbRO2gl1ckml+i9+veOdK+GcQvgSfqva5spd3r38PiL3qtf9a/+58u3/BHsq5Sdr7GLpUu0Vtda9VAhJ5OX/FYS6AqfAxUR/hBFj4hfiviJfQj/Wv+tf9z1y/FfGdRXXjiC76/+bsCubffBT6FdVKvfL1dV/PQpa7X8lRPX1Or1Ub3q/XPciv2AjavVAwFL0E3omV+vSW331tUKXqeudld/z6/+eTi6v+JiatXgp+9O+STv77AQz7/v7+/ul/rv7uu/v7+/uC35l/rxGfAkdfz4MOI58GGCv5cRr4gRD8R8uDLBZ8/xPz/Bj8/xPz/HwAAANRQZqgL8Ao6+aJXwmCUFW77uxIIVwd+hr9SV6vLy1y9RqvfL8stxndfEdTIvQWcqEdEL5kV5bl7++uXXy9ct/dSVND7/n7Rby8uIJX6JeT172vde+T5KoP/Zr4lF6+f5/idf3sqJ0GPLjF9iFupl6tk6hTqFtYf9v9H6n8T8/g/Xgx+DWuXgv+BDfg/fg7F+TXIjd8y98Qvb/gh9Hesu7BDriV7EKa45Z0ReNXMUX/+sFvX9Y34vWP+Cf0C3iia4X8CWtfD3nCHjwgvfGL0i+fz/iERzwTjdfonfNBLQMgih7fq9cggzvu/XCX1EdAcfgJUIeBL/q5eES/r7Xj/695vk+XrDfrBuGPCW+dCOxxN7X9eCMW7vor8M69CO+HvGYSEIs3LCXoU/hZ+DCj1rXJ3fpvu/19XGorfCPyy1CvxdWEgjWFvjfkokXz/qVVYuvSPxoG7Ow/CvCN4rG92MQInb5Fz1gQt9/LLy/ordQ/1FyXYIRK1/6tF+qoa8NLxAnfWhnfKvfr7oJ62ff6N6GX/CWlRf/DmhxCxtK2l6T16Tn+F0LY8ElXrHfYrE5odBH5Le4IO9XrmRvb7gxRNZ2CGEeIiL5fQQjxW18l81UB/BShDutGbr6CCl4v0EfBx6LRX6/175vHhBe1gQf8qLlP6Ed4KMKckK/7Xs1cgIxOqv0CZI/+gdBDoCAGvAhCOw8Ca6+oT60Z/DGqIL+T6RO8J17017O/zIr/NPxEE6wzQhFfoEorrnqFvhz4pDHOhP9Ff9XrhL5OwQhPqRerCuuVerEd/3xMnCEE+QXXL8vWiMfLdfy0OV8vkk5Vy11+DkEG/dHirIryUX/hDJbq71X/QIfQn8GEE/SHOVWCIrvufghu/14S/Fr3QFqvda68GWhC1gxHdAdQsU73665YigT1fqRCTp1r2NxeS0d+vX8FO6EOSciJF4j4rWBqSLXxAJbvu/WIXwL5Kr+eu0Z/bV4jJvB7rtFf4Qgm5aXE/yomUnr/p1fsMdfq/XQpX8nX1/P9q9dq8VTwWevVUt2FhLK7/lRH71fv+VX+XuShS/q9bq/2ryc8Gv/LdxPxPyzVP19fXBz8ojivmwRe1nwKGCv48RD8R8uBawWfCHz/Bj8IfP8fAAADqEGawC/AKjgIHhBAor7beKXxGv4IPQVaGeJQp/l+VXu434lXn5OtF/XN80EPoS0Ry/L9ycldfJ8kvoR/rXquVEe8DfRf9xKviERIldU6L+CF/yYnNYLySClxCMry7yrwQ/iNf3eiuYha7V7qEdVf4EH0AhR/WvfKv/179eqg/V4KOLXvnXsUT1F45fSWCt1UV815/gh7/XrHK9fE+D/4EE0q/rpE7qEv174zf8OYR1i8ufJd3qjv8b4EMSi5a4nXLsBqmV8cqv8iN3hf5694T+GcmPMi9WwzjZebwRhrwUkXvCP0KRnJMCCNXv0T75l7sBEhXteoIIX4lC+k4RlWJ8zfrqIVz4hEfXCX3CiEOfCCxz0M+VFcp/3hkTNi6P3QM6lTrrn+OQjvnV67Je/yr8qwPJfAnhvX/f364Whha8ZhHiUXsQsJbq5Lc6FPilon6X+jseGNV/OvfL0C0f19L1+evXk3cWi93FdhH8+qWHNV6N3s697XbCCK53fZ+3caHgSGWstDeEHCNdeiv9r/66mV/k/BH1X3Vr3WvdWvvIJ8TugJAMen8HWsOUJ7CWFhwtf/BHpeK81iFXVjgkvd/be38EQha+hjiPFUFe/8TV4vBhJ3LjXzeDmCEVpJP5PX4yr/L6on+uT1Onyq98Sr1kC/YaBah7FCiGdjUcmHXa/u4ruvi0OyzsEMI8Ygt0uEvlotVyxuatnzIj9urpahLzwS1Wuqp1XE/y+HDV6Ef+VX/X9c/g2DKE92Oq/z3lFeFfvXon/1eV/UL/CGGA78fT6kXuoQ1fFeCoIIrGvsEhdVqsnwyF0IfXg6Bp0Lq/Sq/mr/7V/pF/2MBWvdhvJxC94nWK+wt8IK/yL1YQ9DRXXtfhcYiWhDS8NjPBOa6v59f45Epv1f5FequuSvRX6BJ77y+gS0XuhPp+n6v4q+erCJvhCGPl9HaT0aKdfy1SEeKf9VWOJv8k2JgjLu7HQGUMeM+TLhDnIWvRXxubtVie3+GPhHBsLQyLvd39/c1YnWBaS9XEq9YFEV0ApQlqj38PhDwyEIs8XQlF8MLwj38CFDH1lxy+LQjvC9XVT9hFL3a/Er1U1QpT3GImqqK7iIQ4axxN4ZGI/o/n+S6un/fKhH5RSuT1f7V4uvrriFeGfjvkte+i//0KJc3av1P893ExF8PfCH9fX198nfd9/3Xf394hfngn+EPiPl/wIW/lwTf4MvlxGvifn+XBNgs+f4n5/gx+f4n5/j4AAAA9JBmuAvwCp4Cxwd2Ct91XJXJNy/Lrr/QebwOeW4iqBfRXr1fuK+SCPE/E/G6pHiNr+7m75biUTroAnNFf9f+BvyXoj9zd693or9zdyQ+v/0epPRuulXurXqpCfl+JRuky7uIrl9r5JOVF75V6TAw17wKvwN/5fl7k+LV69FSr1BB61eqvJXdz2MRPYxbl0zXyL2viF75PC/wvr5KG/BB6Bb6+ta6QnrrpE75u4a+aGdCZMI0N66E17qSr0TrEKuo2vXxQhegFn8DCTXG/xdevugZ+q66X6J1Y/2H6LrXXjJT0DbqwlXPWEPX19fT9RKFd19BKvdfxylSFRCPJ63ugQ5ubyay0JfsMVTrdojngmLrhST5ARCnfj/Ivfr3xfovaBAixVgnOj/fE/onvj9fr7HEr7wy74v4le8GQhe+MvBN89CPfr7rRe8HFF68RRm+CDxGFeNmwVb9DaiPQ7vwR1X6q1Sry/LXLJYFH2b3yY3S+0Xtfr3xPesXg2+I+I+O/P8SiZVxHUIIT3ihavvxIMjiizbyw/XCxf//ifCHxH+sRiPQl6+WwkTv7/kRP/Sv7a+P16uSuX5axf4mShdC38ILwx+EZscMx7HCHRZFe/WoUwcZfveL611N81YZZRLvrza17qlWu/RH+Vel3Xq5/BQGf0J/0vTN8KL3povrsCn18V4jr+zsJwhxkR6CnTXoseIwnXvCYnyZlwrGMRqvAshfwlRmPCXqT2JuoT+J+J8OP5McS0VOv49H7w7vhBcq9X/X/p0/4T5Jq+uN7Ql/tCHrmV/iFf4S+O6QoEha1Y1uC342jP4Z68GgIgQ9Vc6/FfHarX54Y+Kd0N1i/lcnHS4KAhCopZfjOeTiWR3//E/Eq/zq9YZSvS4R+tX8hqr+O+S6P+J8utJF6y/++X/9Hf5lf0/lrhCF677n8EVZr55vkq0bvlutEeWjiVehxNz8End3rAhgo+ENYOtV6L1UEwj4xIr1h6v/GaeD66O/yIz/r/4FKGvvJnL4j/Xf1v5UMcv6rRerD3wQVfwfcYpcrELWAhQsiy8CCIXtYZ/h0IfOid8q9XPWV9gz9cjr0N7+3/DVcb9YX/ozHkr0ub4NPsikTEIh6Rio8tfyer/LQ4m/z0vi7FL19947v9DGhr43ktX98qFvV83q8txtVPJfd/X33hrDWsb9KvWuvvX9U/393yfJVT9fc9Dlt1q+KV1y9/fE8kNfG/Jcvf39SyCEEHKIXELJf33dfX13UP/G/5/8+Ixv1gw6/nw1hv4+ubHY75PlweYc+P+FPk+CH4/4U+T4+AAAAPHQZsAL8AqS+JoQuMQKLxHq+IVQW8qO8/NVSScv9ct3LvieTkqgJP5P0d4a6QvoQ5f4ipJr0K7qWT65VfX8nNW6K/cd3ojQ8/4qgT5RCyVr3j/zCLvu/5tfXtL3QJ/1IMW+up/nvnt/r3ySP9E/Dpf/0LrvviUTpNCV6vW/U/X1Oid8Xr+sBI7x9e/X3UJdfydatXVc9aE+BZCXgUzIveBJN4FGveBL65dEiocSJ/9cnzfUP+j1fq9r4leuuuJqwGC/jqXzVhf0E6I5a8fXvD9YvD9W8P649H18Ir3gSav48JKx8VWI/qVXiPg/16Ed8nifyLqGBCKkJqJXr9FeqAxBFCW7A3CfBwkK7XDkiJ2uCLXPqoan+N6tU64EZ19cJ+CcM+GQQ+f594ZE/JXBEvSCiZMCHX3gQwjXEL3wkiOQq/75a4nwUYj0FXLX3qv1VaCz1yVWsWvl6ROwUBDu/lmoHPpflvG/lR/9BQX1CHT44m/jPy+beHwui++DZDCqhTBxrifl+X+X0E6i6/kq6r0Mf7V+6XxfL8vyr3yyc/yr/ogVR/9hYJ9aO/X1+Iyc9Lw3/QQ91wmv6wIDrhj4YhBLxHQCH9fQW9zd4KD6rqqVV8Sva/Vyu5/X/hfjkcsmPBkvlqqXtYLIIAd+cO1qjdXa94qidT+LzsEMJ4GD/WGhHf3y5PWghmiKmXxv+rAncYiDvmriOojwoGAREVd9cT9AJsF/WCQ2qvdSyc/gmCvw78TWGwh8V0BZBVl///R//J9r0mDIVCnwo+HV7Xx83d+ERXRgh4YEeDb81ZwR7wnAhBzp+hPrr1fwsE/iFfuH+jnrGiqwj8SEvFfGaX/qveOXo3xEKfE+hLRXXhsRfKhj9/QR/PWO+g583gqdYS9RfTy4LQki5edovfCK92BZ6/r1/4QfhCrliiGfw1CeAgMJ9/Kr6/RmK9X1fV1Ir1xOOJJhl3cIy4mi5eDkECL3qr+ENW126vLitcf4I+/4SELCHresn279CuqpCFd9Vr7r6/BVtcnjFe2IXwE+O8CKEPBqGEJz+DEML+60I6TDQ9HfGK7S0qE/qgbra+gw6E/hLpBO8nRLv+Vfdh31Xejd8T8i98Qiv4JvgdOOU1KxC2/0Z4qkT4jrR06VTfNT/hP574Q+r71Xtf1xCI/cZNU69E8iv3N3yP+E/hj+gpV++vV75+rxS4pe5dL31LCGCLCfw1fS/7ARhfvELI/vEL9/cEXy4bwr9vN4hfz4e98+CLCnw19ZsUIh2I+XBFhX4a+N+f4a+Gvjfn+PgAAA5pBmyAvwCrCFgm9BL0byzikKd2BHxXfcSrEvIvdgbfxHgr9AT/XBLy3aOvdc/r2vpE72q6Re9pXvlV5KiaEL8Srkvq/cdDPLEYVx3E0MRHvJ0i9JhtyjFLj/P89d9AIv19S0n+XiITf8UX/9H7xOXF0TvMJXpeJ+T5V74nqJk6/XvkRO6hLr61i1X3cN/E/EouXgRRUuBT/d5NP5od+riZ+JX2v1iqo3Xwv8T4EESi9rj/wL/2JROrk+lbXUIeG6uVk4onw/8EPX65fLvhGEfQWR33h/rr4i8UvCfw+JkfwlCoha4ma+sSonBwJ38PfDSFRsQp6cF4Wrl1gV8q92ATcNoreWit4fCNUC0X19a9Xr11aufHIkXz9gV96o3Uvn19o/ePot7fwRIUyFKlQmsQTfCNcTQsguZL1rdGeT0broCCIk68E3uIpfOiZfEXUvX0/YF8T56L7217qGeg+64nGKe4x4WXUIeIr3ismH6xU/gRgSCFr7OwRwiI+wEV7L764mqW8RQSfwhifQ55akV+pOuril5VvVi6+teqovrrlXvn+WSvonwxQuL4n5/l8VriEI7f4IiLX0JX1S3wx0CDXCVehvVmrUVg21gV9YMtYPvtoz/q/WQjv6+tX7+tX6191a9JhAK+BWAgoeRERMKVi/Xv0bq5L7Qjt/52CGEeXq5f+Iu/z4r0ErniOMRhTR2vBH3dvAu98d1xF4a/J3oz9xNVr/EL6E+HhfhLJh03hUYhPVxF5Py/fgmGQjf3EdNQro/o/goEeDYR0BICHX4yCSq745SW+KJxxL7+BTD6sy//9k9/f0Cb4rWfvXugbiF6T1/2BfE7/V5OFoJ+vC4hWOwaju1v0I/WCGr/Er+xiiNueDCivWVyl//RO3xHVRfjPkd39Buhf/1e+FIfxLifQxz9XkuI+WapVeqhH0rwIIJvAmgopfXVTi4+18GkFHdZS9X1od3VL3SovdfXrwKwjX618SuV4LxnQCTBF4LQtXLXfmr+uWWh9CXkfwKkEmlJ9er+OSJ0mMr3691q9Cl+EPirrRn/V4vkrF0LbL//v+Cj79Cu/XpeW6+/rsct36v1Er+7++JffBMuXWKvrbrLV/vvVjq1euWUQiNanZXf3/E9dCFaiFxy36/1exSy4JsFH/f38/y6/6l+WxCCDUQuIXrur+47uCr582IX8+C7iEJnwTYK/lzYoRBPEfLgwwWfCHz/Bj8IfP8fAAAADl0GbQC/AKSvmsQsJiFpfNBnySXKg1Vcvy9S9gOP8tjFX/6vJghr3xH3BNz/KvSjEIvPc18iKxJyq+KV932vfQhbXNq9YEHXJ8qv1Muoef/ly4vWTdxq93VcT8vcsnr1evVUyxVyXxaL3o690Aj/Sr3X4F2vUMQi9fWxCEv3DHxUJiFkELEY2i9PaE9/To3dfX/dS4hb5K5r6Xvkv6r66oFfq/Am/BSJRO1/CvExI5CfRQomTi64vXEwnjF98bXCK5roEZPC/x9G7wn8L/C/W/4tVy42JaFtjc9Tq+M6YS6jOi17x3xFe9UTuwEKE6wu/hCFRC2IWRfxGEdehb/rHPBgkbvikR/hIEt33fc+ka+MRX7wECM8C+M6AUpV7wV9fo7/fQNwj4TOvdgWwj3r3dL3hMvh/0DkfXgiu/fw7oUvWhEVY0fJgUwQo/VwtDvoXeJ9BDv16Tkr9fL7L93k1kflyc3j/zL0i/8ZWLzf17FEkIvOIzfD/2CwkjPx+95oROATwPH4Rrjaw18VqghuubdC3ibZO/vRo9cvp9UrH6tJuvXhH4v3Bv47eShPeIyYn8RClAPgX8Vipb365K4xcs2MQy9X9iPgTIJSu+77H2ryVSJ3y/L8t7KvfavWCoL9hj7CdcMY6PDjxryFriL4j4QQS7OwRwlgYN7FVT1hDGXghCi1uViKvVTUIRAosuHavXCmsEwRoEJdV+OCkO9B4wIxWqsS89VDKL1YLAnV/WvfN4d+Vo/fMvS8u/ioR4iIf8aXxP9GaXBCI+K6hCTHvwUgj8FwS6+v9f9xPy9fcbWFH0DMIVnXjK9Npq9YcC0I8RO/47E67BGVV3uusQJQh6HK6ZLia9XqmX6R36hHr7hNXup/n8JrxOqBTn4ehEv/6vDPaEZdaKx6Kue8EFX6mXLoMVfXyz0Vm7vsBmgQl7uRH66hm+I9GXpuBUgho9G6KL/+vyqVe8IaxHw0/BZ8F2sGqXPjlHfF54KxXghGI/fJLhCiPfLWiWMhGdMZEG7gPcQry8nyVggomU2P9a91o3dUvVj9UBSCHwhiFxC+QUvKvq9tuN/iFeJ4jrqwFn+FoXvhPlrN/Xute7+uqjVi1xt0KRH3/LKKW6j+1m+C2uTkk5bX9cvy1QFHeCDfoS8GV8nKgg2v8QjObl7l7++a77/v7gw+XEa+XAlb+XevmwZYLPkxG/iPn+XBlgt+f4j5/gy+f4j5/j4AAAAQoQZtgL8Ari+Kl8EIa1V4JdHV7EIQ4jk+S+kV/kvlrl+W+XELJgQfcd39/yfJDmFaGseEcuEfjct/y/Kgg93LOu5kXpOXEK65fl6ia5UV5F+r3UZD30v/L8I/5uJROkuEf1euWW4xerk/XtfNfLJxKLl86v8T0Asd/0yr3yVyQsIW/R7ddfdaJ1YQ/ojS1LXLdQjjl9r4m7YjyrqI6ZOte6el8m+ZbEKlXExOOIX3gUQh83qveBPr7/5ewFGFe/4j6QjoSFIricEO7/ivjvk8Z7iZOXGL74le+JtVLBKjv4Jy6/8BA+9Gd8itWFdYV+Fat4tVwgi98Ir1DZ+XgjCEmM/omuwr7BOeukK75oS5a4lF7EI98SidiFr++7/NRe8UValfLJ4IC6/V/BkI+GEYqzGIz3xiPzHgUwh4Kwgvz5dLy7Xrwvv0X3QOQj1XRPX12v/CW8OUaPXEq/6/8nwJIZ31Cnw0iPCvFob1cb3E3YOPhD/Vwr4jLl/IhDeHzdhs0lxSMxrqfw1+9fL8ShPvlUqvnXvi0X3uvvO19Jn+F/z0v8Qt0JDXm1l1gsD32CcVWta+hLAQGXlrCnt6xHwx8PZ8+r5eReu4xFfvV+7Xr5F6916XDq6h+sO/HetCe2qxsvL1oYZkQR9ay//36Cb1QKAhJd+T0LS9FfJgt1YI/gmXon2hz44lx/noCX61/LUEdcLeShvdQY+Ko3THYZhEv/98RVd11fJrO/0EmK4hGr4qng86uVgtGVxQIi6qnVeC2YQq9/q/QT9d7q/2v649F7wQBlF6uJRu3/6EVhvfFL3Wr+Sr1x0Krfqu64yoRrtHfwWBfx/wuKBGbd2+K8V3+r3hn4KQnvwLwKFfrRHkq0dzqF+ryfr/r+tm8E4S8WvhHxndcNr3XXFL2v1Y7gihiuEVgSerfIiPenLhsf4dW/m61frKXd1m+nVVXo3X2hPfr10Fd7G9aI8JE+v/+IlrviEX94Uor3l/olSP7VvE77rZUIeq1erjl/2CP2EqvQ4m+MJ1Q4kQ56RYQhn4MQp0AkQZfJfoT1v/wl8JVfqBkQszyGa5qB38I/7L+voZXk+TJcqFRVt1UvX6FoTlV/QIheOVmN418I6+XEKe+QWvzwIIWXvBuGFi8eEPYpek7Xq5MQsgpnoZPYBPkQ55a1aTa3/4Q/zdK9+t6vqvwkffxmT0v/8IfEfiEXvisUuMVyJ8MK99IzyVKvS3L3or/JDjr75qfJ18Xfq7+tE6r6sMevoCN+1eq/I1fuXHLbqJ6657T8Sj9V/erGIJ+REeWtEaGPm+Nvq/5EXPXq/UnfV+MW8lcvE/q/erziFhn67+7+N+7l7ARH5aELiFm+xCz9/f3Dny/WTF/LhDE/Ngq4hYIvk/PDsZ8mEMUI4j4IfhH4/5/gh+Efj/n+PgAAAOzQZuAL8ApYhYSXzWIXX1BH6CzR90hH5+WuX5fl+WhC1yf1ydwh398E/Lv9XxC3oTLslVJT5uao2uWl/ildespqjIR5YXuJk4n5ZPX3VfS91FVQKfXXKivVxvUTWDFb+fwKf9ErwKJ8Ut7Irw4X/l/BjiK65Z+/l/W+KV1Wsvkrpe+q5lb5q5Pl+LRe+J8M61916lxP0BpG3cOfNj2G6rX4VqJ6+l3/GegxfuLrnpfF4xS4/xaLl4N65dgE/q7tmochF/LXvDfoHPrXuvovr6Gb/GxLRm8Ffegox3yevm9gexPc/cqN3QCHDNVDELV45HfKUYvpPWonBoJRO8HVEf4hb/CSI58Qrns9UAlRPWhPyq0XtLk+ICsmIH6/+PX2sG3Xvj/AzL5PTpeHNehRVVx6O/gvC/wSIVXfCPCvxtcTJxfoSh/XXPupUk779cnf1y0upUIy7pXdRK9XGIr/GeI3tdAR/lF4on56wUboSGutCO6uqgu18FffCP1cb3PJ3WEKG9Vggr03oh1E18lV0/VIz+C43ggavVfUur9feGK++IVpKterHhPL//XL0HQtJjPkoneL/FK8J8OUdhv9CL9AQPjvxkbt9hj6aGPjFD5G+IRR1joCm8w/xj9G5CNda7nWUm76CW/VKvqlS7X9evXyKxWKq9YQ/Cv69WEQ0hNdQrNwxnYVhDiOoQQU7GLr5Kp5qGdr1VaLFPxdZf6M9cgJN7uYxQ0AyIyr4mqw+kR/igRFVd/YlUFK4Ow3dSd6EP9q9cTWCwL3gjBBWNoT18svCkJcklLCHPLnonzwmI+I+RX+asKhbxfWBzByF/UniGr9fUSrnz9RvcP/JJjcTUGEKcRVc+ZV6K09Cw1awWiq39S1oU/UiuY4nUtBsT0EfmEfJ33zI/Vk0tRWeuFqkn4isbQn8RvdXVaGMdav1r/r+JlEL4Mt7q/h0FXgQQReBBDVVC9Y49YqhLzegg0LVxmWCIe78es39GqvrtXkrXumuvocuolF7wVOhynpasCibw+TwVjpuSfHUJ6xbDT2hauhiC9onPk9a8FFEeXb8rvkXvmqihhF7rRHxCvEKtcVd7q/Wv4rDWThiFq1fELG4v+ry61X19c9c3aI8vIiv6Ut9VEQTrvr0Q6j7qvvrl+X1V8QvdYper+XT+r4he4mvV69Xg19CHrBFq+hChdZRCyd/cnP8/3iF7vvtcT4hYL/mrl+sCd1/Ph7/PgywV/LXN8giCeI+XBJgs+L+X5/gx+L+X5/j4AAAP8QZugL8Aqq+JiF8kjwIPgg9BJp+WM5PkQrprifkWq5fl+XudXl5F75v1eCHCOI5bFLP0v4i+rjaoDP+X9f4haqI7iruFoIMTl0Ve+eVfG4gmuXEIj9HXvav66Xv0Xug/Xr/vq4V+J+LXqwJPwPe/VOu13r3xCI8Kr4mWgT5b+3vE79Ff5e4vGLeuEV7EKz8vUX8l1EL3Uyy+TFEroN/KZe8L/H16ue3/jiF38CXXvJ6+gjRIuolYuuukTvmV/EYSuJ+pr4rau++X9CUqiF8DXV9cTr3x+MVfXv4V1l3YFH2EOT9/9cqGK9Y2fl0AwwQK/jzeqEd1+BK3gRQivfoxb5F6EeLr4i4n5UPqb1vEYOBWT9qGIz0M7GKel+oWWOVQCz9RPXr4jwQhFC8t/+ERPQNz9aJfr01+KJ8EKrifDISWLHEJy6hJerDmuJvArhn4JoR4RxCLXF0IW7hle9CbuEK5L9CavLiPQSc+T5TVrr50XMaaB3/HiF74iTLlwQ6HE3Pn8HBvFUJ7Xm+I9QVXyQpyycI90iv4W3xlci9frV+jePdf139oY8tKiv0BKN1Wku/Nl5V79e9tF77+derH/n6AnhOvR+o7l/CFe+PROscQyvvgg11CXCHwRIf3w0r3wt4ItYr8JdxCvW69E92MQi/g9fhj6dr5TdVjiEFdfq91+y/cnr3wj4LAnr9CekGysj33Jwwh3UdghhDhDuIQW74bXqEK7+sdq/3rTR8p+Jvm1xX4JjeEqM54O0Uj3vBKCDXDuCIt7t0AhQXoQ/VdDa9faviF+VX+0V6oCID+sG4Kle6As/E6HIr1eqEfhbiEXr4i8tF75Yrlvj0Z/jVfXgpHa4Q0V/ECPIK8MVZ1q52BNKr9av4OulwagtRHk21e+TyVf4y8apOToO60J+SE+Il+XNQt/Ea9EabEkXrx4qSuT0I/rhr8MAkxig/xyukJfxhZeffXWJr1Zn4Sr+8NV/DPJX/ETdotqL/vojE+EaFP8vyr/uVX7kV+uuX4lX6iMcTfw1iMIm8CWCbzUePeKr1PrR+loDOCVHeFOIlrl25N7yUEOk+Wv5eorr70XvBkO+Ra+XEL8qv4ISLl4KTeCEci/9CPk9kQjugR5hCEv7V7rhn5cu+STkRHPCVWL+Xk82+TsEgSRe8DZociY3x3YC5CnXXr/wn66rV6vkr+IrioXELVd+iv3SvXL+rXifyfLJ6EdddctVL39dCFeKV9xGMXF3L1/r/qfrV7rV5PR3kFLDX/JXLXPF/Vff3z8l8tcTKIRGcQt3zVq8M/8v3933FfLcvf1L8suAld19fXBP8IfPhjFfLgg/wYiYdmx2L+f4MfhD5/gx+EPn+PgAAAD7UGbwC/AKuIQKHIvjKX76rXxmv4LeWXpD//on+4heu4ifl+WepF7usUT83zQQ0FaEtfOvVyoz3y/LQ4hr1Ut2tej/71fvV9vXfPfq8VcKQnyo7wrxPxOv+v5aFLiF+XGIZq+RF7+tv5KVYP8n/Gor/Eq/gx9QiuXYDX933P36qSJ8urhqFOJhCgnql78YvqELXL4H/+iP8Xe9cldL3X19DsneIIc9Y4m3gTcvL2Aix9ehHoaqWuLQvr4lelq191/NVx9LrV9cbCuNUP5Z9b65eAlRi94GNeBz117onugWrotEi6H+tW7BLXu9YvC/x/wRiawLNC8vBqCD4S8ekTqxXwl8JfRa4iFK5tBHX/y9hHLUSi9NjPgo+Dj8Zv4SonpX8v9oR7xI/wILvBGf3R+loFe11+BI3l44hnj0vCWuZe8COPhu6r0PvWxS9Eaf/yWu5Ltd8tIJR/t938snL5dcqE98i91HzVCPUy94Igx8VS/rPRu3+jPDGCCgm1Y7478kV9cnyUKXGIIcu5/ArE8CwbowrrRXvVe+WuWIweF7KXrnfwxCfobfSQCG94INf8JL3i8Wuwv9rpul1CHgWd56EP1LvAiGmV76RHl7Xq5V7XL+EaK/QFACjXPfoT3w74JtcyHd8ngQA0vZ2CGFKhCr79Bbo6uhii75f/BhWvBggSd3diFCV6K8J75ARdVfwOoKdf/gjEaq/RfX8staFvIvhJE75kXvH9eX4vJwpCXJ1Gd93y8QvfCXWtu9Wn4vsI1c6Ku4R76wQiPiPII6KKQhnyeCknhBeO+ChddU/xNYc/P4IQlv5fE+gI4i8ZRelHK7/BJCXN3dXEUOXeYn6X/4QfYjPxRLv8EOTr+9nrBF+FPFat/GNX8IehZepepetE/vP17X+9f070PloBA9fwnyf96KxiFnqVCe7W/Rr/ohkkwiJ8NC/CAnv+f5ep0T/br1aL1q+v5eK+l/19fWCTu73hUJeEKL10DH4UoSxv/zVf9Ge6gSIT9XkELPX51Jkoj1pq8t/6J3d9fQX+I9aP2tfwIwQ61rXwjr9a1/iiT08R4bCyL3hkQvVzIQ8mUXfEoT10GeeeElxGiP+jPNXQpapfi5uSsKLsDMu2XuXELWWreHRkmXrj6rA8ExivbEbUYpMy+FFSrWv/tf1s/t9xsEf9cRySYLfyfLJ3J6v3r/uleYQjP7V61RXi61ehCwyIWatHq8TRHvZFf57oNVOovf5e5e/rV+nV5b7pieu+W7+tWO+q0Z4Kvmr6+vsCAXv+X5cQuIXELiFxC998s98Fnwmv58E3ELBb9YY0JghhARxHy4MsE/wr8/wWfCvz/HwAABBJBm+AvwCrYCBxa+kGngq54niPkN3dPm78End2+X5flrl+WTk+RYvk+bqM64T5Yz0Jq8XXvCOueuf5f0EO+T5aqeXku5Ed5eVesQQtL41f+Bh6/xCwvyxHo9q9anX9YTyeh3dxP9ffKvSfJQUCH0j9X9xuIWqjZMHf5/l/q4aRH7pXggu/0WvF17s/vk/GInq41e+X9X8BQr58Qt6r30vfS98ncKe1+pU8GK+J6l9FvCVF67AZPwIr6AzjevHEMbv3JBB6E3r/JpfE1cSidfCOvjfhPXC4CBJl//8CefoBW+un/0DH4beOJ+xRK8FNXxRN+i98TQ2U839hC7JqwKdE7tCewFyEfikK6FuJ+JQnojlR4q51fyO9uvV/k1/8Ka4JsEJnfv1BAjX+MRYt8TNXP6OveBJrF1UlgVVWI1YM/QEfT/BEV3e54b+Gt8Sjd46vXtZf/4R5fl+LvquEauFULruVFe/Wqz66XvNZXfFegw/ese9MEp933fvFiX3fRKKVZ86xugTiVboJ+7XpcR7Az8USt96tVRCK/RfURJzb+CSEfRr/CqF5fP8I/L8ff+Mwmu/oH3r7ju/v70O7z6qWueXJRX6DYdrC260J74XkwIAchH/go6g+R3Pis71hoIfDHw0id8MSetRG6I99oj4xQvaLHgxfjelsPiy3f19jPgSNUDLdX13tI3fr0mCZIe95aMVPC4WRex0oapOuqRu+kTr4axLDcIiFxS/EVg41XjiBa0bUX1q9YEASr4hRdr4KpKAkg4BFVdzVB66I446iP4Qqx8i95avYxb+z+n9oT3g6BP0Ct9d4V365fMr1wtCPJ+iPJXLxF2IcRxMmhdYVEeLFF7vxFEf5pMEtHfeCEENm6qrBXuoR6ftgv71fs1f9x3xK9WJXwh0CWvdcj+GIWrlf8XiQh4JxxC7usJ0Z+rBERV38lXr1/1Sv8/z/PI3uXJ9f/WShL/q92J99ZPQKV0v69Vav1r/wlp/AsQpyV8VlzcSjPXyL/5VeuVEf5fQmsdtfE3UN+V/oufXgpCHgpDCL3X8Qid1/F/Ohf6w5r16jvCPEL+X5uS3/WXrvr0MsV6JU2WjtWM+KSK/ivUd0EuOJZo74KKv8WufGKz6sC+HPBSGPDpPhZerdG66VFeqj8Yinxob9WLEEz9SZaJfXxH63+VEy+VcqzerR/Xk+Io3eMr1aIjv4Pv6tiFfwgtUIX4iqAx+vr8IUT86/hn5bCuJtq+TvulkuWq5BS4hfia9e+eYYt4e+MxP+NvWu9akFLV89SxIxbwv8Z9dxNS/L8tXLL399X1/fd/ct2hTw79YbxXzYj/Pjv8v+CTXzYIvrD3xny4jfy47J83xHy4awx8Z8R8T83xHw78Z8R8T83xHx8AAADz0GaAC/AKUviIlfHyiFxCxC+aCblQce6liOSM4msCD+WCYUQW4Q5ZNqJEL8tYPev6wc5KmQx8cTfqO6ioV5YTEKa3z4hfi175Vf4nELXJXS9+vdRRLvmEK/i+gIvy/WsGvX+IWqv54S4mfiUfonLn5UbpOJV9dxPyq/6/xBOMX1bXyL30vVcECxeF690CesVv/EI7xROv/F9f1hOrPAg/Bz1/XJCK6iZvR31/dhvLiUvRPoyVLjdcTH+BZouSrgaxyu6AcdY3QMqt4GPWyUt4Q3x3WL1jfYEmjd4IeOIVcvhlTrxsr5fDHgjEfFVxKN14EMIont1UFCNqEeE0N7FExfF2v1f1k5ZMFA1e8HH4xGc1UE0mrggilKmr5Og0/DmsCLVqx9C26Amh/rr0bpM+lgYOveCOS7+gnocQjv5srr4U5fi0J6+X9byl//1zdPL/0Wrz+x9Du+/fuSn13yVQT6q7X3h6vXhM/RvnaO3jfn+ct9r1evVQQor9BH4QFdQZdduqhiFPqoV6nug16+pYn4nk7DftEQh/VXn5+gX+pV7q+pa5/0X/Wj91r1ZNPx2u0O/tZ4ahJcChDXQCQ3YGIMd6H9XrVUXF+Eiarqqwz+IrAQZPBf8EO6DgQ60Z/1evX9+vS09UBSAtoS8mT+j98IycLQrgQv6Ed1a9PxX6ExkRn+J0MQpX6+hwg296WGYQxxN64S+kV/AggtBGTVUq4GMF/y+tX+3XKjPXCfXNx6E9K/hqFfrB3j7ghu5yVWvlRn8F47XX5euO5OCaqATIO/HVY8lX+VX/X9ei/8IasCHX9ZdcSi97dvvV6p1d4OMKv+TYiuIviUVytlRHmxak5AQiFXc/rRVf5fnV+pegzRH61fw5vbQl/CXoJvqEVesbXuo/rRu61yrEUJ6Hn/KIJdej1E/0snyV9fcVfKhn6qVXscSK2rzd35/h8II57oD6BIROk5PiocrnqEL5l7y1c14yCPu+F/LhwX1P2CevuhZ17o/xw3tewt8EQry1y8lXKwLJOgE6EPBuFl7wThLwiEvC/9E6sZ8Rkq64Sgg5JeTf6KVvCXoDNU7i13FVdordUvdxEmn8i93CXeQjv8EAhaxC9TdzLXZdjl2krV6qlfq0V/kRHrCmGtiMct5ORFeXkugOehC393oV3ev+9F/1P1/FxFRcg5f/lq6gst51/+iPKKVyVdVffXq/cbil7lq1q7k9Xgn+SuKXXiF+WTv4uTkruC37zf583+I+bD33nwSYJvrNv5c2/nEQQxHy4JME/y/EfEfP8Fny/EfEfP8fAAAA/VBmiAvwCqCFxC0IWJXwhBLyy1L5dcvyy8lcnc3ySc6Dzycvy/L0Agd3Ed6/964hXh/CNDeia0EH6u7ul/fV3V8l3dXCfUtcvXeAtffBFhGgj04ogpzVF/LQpZPWXb+l1IvXYO/69r+Xl60Xvi+wGD7/A7idXxOk+ZG50uRehp/1i/6FtJlyWE6J0lxvVonXyq/z/FrmPlutXXcOeyeF+vde8E/XevXxfX0ul4Q6fr6+voheva8ZCgpZRiOUl2X/+tfJRa83xVb/rUnreS5v0b1cT8MrmMQvgbxoIy7u3YBWSeBB+CvjEa58699L75viljnjRHj8mCd/WvhPw2EUdvBMChe13DK91CHX4EbVJeDRb+kEOhPjfjcYQbynoHdF6Lul7qbV8/QEguT+oUhyX3yxyFdilZ+FpMCCXtB4EIt73arBWCdF8eGx6J3nOvuwMobXr3rJ8IlXviFrrBER34vEa4/wxutG7rXt/wly1cyE5Vy/CK5S/WehPZf/0R5fVMll+XXoJdIuS56hDyCUN7oHdffr19r75V79ey//r3i/itUgj1+Fq94j4jVKhHbXgohHib5fn+evQ94zehiFAOM1EkTrSo35V8tV9zIr1honUQr9fQX0/175flk1XpMCkDG+TzbrX/w14Qwh63+IrpBFKvqZH+GP0SvCnoMenjblBIKd9y1XMr65Y7wc/Cz319G+CJeEKpVXU+l3Xpcuuf5fl+175Ufq4qepPhRDOhLhCsCAIQ2KS/vpfyehOdPxaEPJxK14ZEeGCa4sMhBe1wiFzXlDivrwJtXvkQh5Knk5f0JesEIe8o6fjoR4SXvj5+Sf0VpuX5ZF0DkIVj3XEdRXw2hX/BjX54N6K54E0FMTxVVGzCiccS7eCfDfFL0no7H65p8IjvBWEFeZf998nUR0ioZ3hKr4xQMzkTJYzXJ9I//1euf5LoFeH38it/Mv6eV4J73u7vr9ZKJOWVXz6T9CO6+/b88lx3xN8t8lYKQ54KQx4Jwx8RBBclfNYR+lS7ogkpIpK/0Sx4iv/BBXmXlRn/V/tX7R1fv+SuSShvr6NQ3LwRQSd3c6wUd33dMqqJhlEcrBSvDPwRiq5/0R5a0V5fR3hLkjs+riLsGgU+IqwKB0IMub177XuwzXqv8RRXpcKdDF/xCrEL8UjPVgMUJd9VPE+jvDdSK8nJ0/6tJ9VJ82IX5kb3a1yL4nuIV8QvURJ693OrXXF8sEP3y36+Pl61fvlu1fv66r665LFL3F9/Tq/6vJfV8FPL8vyydIQ5Xf392v9c3r/4mI+e+Cn5vmxH+L+8Pe+egTYJfm+XEb+K+X5a4Jvm+I+K+X4K/m+I+K+X4+AAABBJBmkAvwCvr4ivYa1UEPoS0g5G/u5YU4lGfGLjnyrUQv/kXviMew/X1rCHoKNCfrVDiGvJxPz/Lr5UI7HLv8slSI7/J3MvTVEq/0r3cI1cbN1DHoW0vq0UvQnGEEK/USjd/Jy/OvfL8Te3dwh3+CH4f0q9HTpUBv9fT9V3H/F9AIH1q9+jdC6+JkfoShrxnol/1e/ri1OrEL1CKJ3xK91E/F4xcV8i9LccsXxn1VFL6J8muP/Axhqq+vqJXun+KRnhPlrllFIXG89v4u18FqLFhIk3zdv/Aym8CiZe7AZ5fi8QvgpL4R+FcmHV+jFT4herA4cQivwKAwEN34qyHXLxQvr6EejenROhb6qJhTQ4l3/CAIbv3/Rr4xXboD6RFl8i9WBbr61v62vwiJQnLxPxYlfe6+xxKsY4mZesP/41e6ghxRDLu6r6GV7FEIbI4lX6X4EBCo5C35f/6uFUE6ri0dMlXVCa/r1jT+gp3y9y+neBxXc3y65JepkeL9YpMtHc+N/XvElXqy190LBb0DfQ4l7qoFXwJnxO/Qi/wWI3QjxNVCNXCt39fYIvyS+grURcTN34FD3FIU+lwJmtVYk5a5PlVvluterhvoKK9O+RX+FIV4Y1/8YhvXwhQ4hLRPkNWtawkEi6rqvFuRdxXgnf9ZKM/hLXL8taqlXVesYo/55cKb1xRD5Prr9F1WbXMhnQlUISX/H1uhffr1YQ+I+Kr0TziNarVfFVy65p+gJPwolfw9Ma7v0GQR3d3crE6WDCwUM+qxiMaTD4KOqqq3xRN1IiPJ6L+sEnoP+tF6saIrLv0ToT4yuSTv79pH6TiIioZRn6Fzd31D36K8nghM77eEPxCvXEK5+r+COiv4Rq+8HYLwJwc6fsM79eqoZRXPBNrm8YEEbpBRN8TCXFXzL0gpFqmpOJR/5Pr/4gYoEx/mP3EghNe/d/hMV13ciEdEUn2xKEt0E/Wrqxz6eTiqsCXXu9ehb8Yt6+xSuIwj+WWsstC0eyDiCkoscSXlSfif0V+0GPiVeQcSK7dRPXjiRWnegMINsn6X+sXgSQVVyq13wz8ls+KIWvmuIicN5KDNcqoL1yuwp14NvgXuIV4hV4EurnyVWvdRt+ifh31eS+/+IQl/iF687u4ilhDEL3WjXoYjCXL9RK5jrRX60JOuJ4xG7qFMQuIX4hf1olVq9Wxc/JDAxbYhZX7/OitLQmrE/IhXfr3y1823XLMKRarV/1fp1eW/ue7jYc5L9HaV+EdXozzVrn7dEevV/l7uxS9XVUr90r9z1y3X+ivJXr5a9Xt8vDncIXff3/ev/lsQvzyXff3981AEQ33eDCrw58JfWGP8X94S/z4MMO/CX+FN/FfL8uDDD3wt8V8vwR/C3xXy/HwAAADt0GaYC/AKsMQKLFCEWJXxEE/LfOi986vEcnydaL/5Nc3JxKvfP4EH4Hn8tjF/+TuEO9Xhr0LtLj/61EehTy8vzzfLeryl//xC2uvGLerAJzq/vV4W9CajsXROnuN77ELiF+WTtG6SwI/oHOQQsq/8H+qAVJ+per7gghLlsQiyXz4uhPRdRaGZWKX5/iV72JvLrBOWTD++XGI7vNicjv4U4mFuJXq4VXLXDcLr/wO4RRzqPAzpe8H68GP4lCGLw/VyTNWKhxK94KdcTrrxsS+Srws7u/xFZPjPjNO/QWSw/6DJlxNyozf9aI/xCxUORmd+ocRSp8Uv/iFd4L6+8CX8Hf3Ql5N/P8TXq5OgIL8N/iQRbu/a/8IbXhjeM7+DyEeL1/JUXJy/EovVwpJ655u66pfevnQS1XVPnqvZd34Q+iL0/o7Xy/H/Pr9Xx04fyCqvEbwdAshGp74R/rhH4RVjGy048Iegx664pYoz0Fvyf390jv3r469fa9fL9/r369+vfa98tcTr5fhH4X7A4+/yJDe38M/oR1cNdhDCH/X6GpV9TL+GsdJNdIMdCs/orz+hD1gjaEPXLjFC/1KuC1/Lp5Z1c8Cdr1fHEj7JHzdr36988voT+7mvi7a/CPGdRmMXHOwQBDrvnvde64you6AnmV+gQVfahaDIZl+F8Lgy74U9AyBFVdOvC4I+q+PC1GSrjq18vUUv/lXurvlqgKAEtC28V6i+xp6xNeuvw5hK46atG6uS64p+JycXVAxEdJEI7/DwlX8nHEl/fE0OUuIu8DCCXwIII4vBqCa8RRehb8cie+T57rR+vk9EXv0XvEV6i///q0w+QIzG3fX/VvBnrCohEfqVXq7r0T/tL/FElzzr3xSv8iv+v8YijnqdeRF/9K8Ris2Xiif0EnhauK29e4IQm7vi/BGTd6l5SkVd6+q/utXqoxekHEq/6/pfEzbXgUwXI/XQRr7rXpMtF7wW1fO8L+tSCCWlXf14Jbu7u/fyUIeapauL7BN6llxG8drhGl4JyeDUMeGxnwgixVzyVzHeFRC0IWJovql75JMHHwNmvRiI64FoT4EEQjxd89av0OGdfwgrGIVrgXVJzyc8P12/7f9L+Tk8J6uKk9G7ul6Xl7+pcUuMWxiFxCq+RWIukVC3hz+++RX8K6HE6Oy31/2hjyfPclcl/dSxohflhj47/0Z5Lvv7+/v7Bd+Wb67+/v7+4tcvDPxv4hYr5xHPgg/wRfD4iCeI+XBdhz4IPn+CH4IPn+PgAAABBRBmoAvwCmL4jX8UIQJnB56EvJyTcvy/LEc3zfr+CLF5eX5UTvlqp7qXHLqaoirivkk/5d/+hPQHH8tYEHdaO9cQidCXLr4lHYl9CbR/oR1/Vwiidjl18/xK91Fy3GScn4IzrX8v75Vf51foBA1cqwGfv4TELPy1gh+FcRhPb/lqNxCI8QvxKtjif/A++ouqBPrk7Avl7/m8M/DOl9Xg99fyouXj/cR2/hsevdAYzwnxOIWXiV6219L9Cei60TrrRNlcLqdRhBHLi7bf8CzU6isKPoDz+JQjq2l7ubuZe71Ksrm9/D/f1VSotUNlFZl/CFW/QFqhHeCH+vfGoIWIY+9Fsv/8uhKDLehK5q4le77yfjEITquGq/Rr9QopUlwJf4QQtyqCnr7DZ+/vXqy1by9+FaL0t/gKz8TfAgQr6NXxa9/ilqwI3Vf8M6fHAor0Jt8n6xSriB+T5f0nNMgkx8vUR1ovda9VI/X3E9xfhFed+dovfr1UDv43WGhNbXiPxNcGELcaj98/wqi9LxS9frKJ7QUe/X9pfqgh6He4hCeVbvvXvDVek9fXzr18/wvKv64YhSoIK4a1/iiCZbYhFfzYhfCwJiNVXVarDb+XwIT+VCmPBn8ENX8fBJ3eLwr8GFld8uFPivmeuX6iUTry1756wv8FH9Cf3sl8VC/E/PLTERXFkqvX6v3H1si8ql+GP/iPCHfw+Cvu7u7veiysSO81EfHSkU/wjlx37fwLYKfGUI6StX6179e/X9LhELULfsGgEnu0TvEjF7y+gauTnhe5p+0fqzVef/FhL5r50Kf6V/yXfWFq/+I+I+IV/BrV6oBQgR+tX7hL51/Va98aisdDwn1+E82EMM398/oTXr6Kv5y/+CH4EEIdAawh13X1oIPXq98mKJ+JrArBbqP6E/Gcv/6Fv4Y9LWX4To3VjFv0rwlRehe9fFXzcQj9QucMqxkTg2CKCT+VyL5/62l6uSqQe8LVf9XrBF6i7r6zd34muXhcIawQhjrF5HvwqKIer1fu5thBF/jFv3JS/teWscrEf0IY+zE3ddr3vru9faxfLW6P79ffr3QdJ6a9WCoIIr7/61tjkZm1YR+CUIIv/CFe+IrnRn64IH/PhPL6vr5EVzoMUW+uowhN3/VgOAM+GNL+smrBL7J7iv177vMEl/iF8CWTyCF/dc1S/LBBQTo79/kr/xP4hXlqIQjuv0vk/RKrk7nXLrkxXuJ/V79XxC4pVQ5F11yjFsT1avtfV4dr70djv9EVif5eWbiZeWJ9Ge7tX186P2IXGIVb4vwZHgn/9X38iI8l9Vf39/fz/PiF+/vEIQvuUQriUt/zQT/4jL94S/zZtfNgm/z4MMF31jt/PXEfLgwwX/L8/xHwafL8/xHx8AAAAP5QZqgL8Awhf/lQUqf0Krq1aIuI/X/U1Vq8/Kr/L4O/cT3JYhVfNDAhDYU5e4vvQQ75Zekf9XGTcv8QIXqb+FhCHnpFE3hfeNq823eFdcqEem9Cn/q4/GKk971Zyd/fVg/yCEVnuEcYt/l+f4lX1/4EXjFZudaJ0FlRKL3xK98/z6+f5egFrWpL1br+JrmRO8L+gIPqJRevA9/AQNe8CCbwIJjF3eOJ9jiWfXg3E7+IhfiV6b0eo7pEz/EqlXhNcvjVMirgZ6KZ/WruxoRRMu5u1riP194R+Ef0iN7r61/4IfgYuNRzkWNdAWPwwveCcJybW/hWEuJrllVcIy4nFevfonqwt1wwT1BIiRz4W/W9Vr7uugbfAkiegb0Nr7VvCYR8TRurF9e8mEev17w/XqGKfHrN8ZrBwDqEeJr5+E+oZR8rtiP1/EaoJd+rb+Ve7lrwRXffL8nLevql8/xOvl6ZaqX0Xyl8MnQuLy7xb8W+wMf7XpfRe8ZvgwhH6GLeWtFcrrqCCvWvLie/v9BLuue4rv7dHj9avfL8q++W9tfV698bv+tOqD4Q6W+GIR/9Dc93DlcIVjKxdaJ3WvSejtO+vwuWqvoCQ6oBClQ5jwIdWPxfd930Cr4E4Rqv6AvDscSK7fr/uEpede/X1cq9eBKBXIvB/8GmFuEPtF742WtF6M4sEVVq58t82MU2FTWHCfRBXhxAsNd33d3e2OIR2K4rwVUJY+PVKuBFBX8qM9eiP1X6L/9Xria4nxVCel5qxFehfkvKIX/bq/ZF3r3ar0VU69v8pN38RXP3D9clZqMx1Ir0IVLwXa90d/B2G/BmH/GF3/1onfLeEMXwRwxej/+5vRbT4ZBFjEQdlvRf/+uuqr+SqhDrQj/oTeHA51HRWEjy6aEvT/hOpK4uxCv5b9Fr2GF6qiV/XgiJu9S43dXE0EdYr4S0q50Z+w+LV/JX/UIq+OJdqXhX2Akw4i92GRS94VCFckx2ElDN8uE+/+zrtUEemGIQln6qfEqtPoI+gh8EAnqscQWzfXwmr4xfVgnCHghq54RDCxVyo3Vz/ov5BCKfAqKWV/1fN6L3eidfJ0DAIV6I9Voz/OuYqgcCUeXhD4ivSbVX9iRHcZ3giu+xiF1xH4L93PEil9Kr0KeGb/0PfvV/lRWqnX/XeyVyycV4Pkh3VVL1dl7u7lRXscvuo3r60R/m+TFL4FLv4jFE4pftf9TwRfVzzYndyIsSrgjyd9avfonSXKiv11f39/fddL51fHLbvRHu/vRWJBCwV9SfXfV9S/Lr/5b5b+Tv7xC4he7gv+T7wx/mwRb+XBlv4L/k+sIb+I+I+C/5Pl+I+I+C/5Pl+I+I+OgAAAELkGawC/AKcIWhCBQojA29fzjERX18VBZz7/+WTkQRZW1Q4nf5F75pOXuJrk6+vsBUqQQsN3oX0Voq9L3XL/1d8qHf3y6vfSK5VxUi+q56uJ71eI9X7kgr/HK6VMUiP5dc10OUe68Qv6f98tc3onQHmj/617rXqEL3CCN0O8sYv6HEPvfF/P6P8Ir3xeMRPVyK/yfJ8i99LFWF/h/8mu/wcCflqvwca0I8H9H6H6iUJyjvRq+Vda4+H1fG5sFuPAmwRle7mUdAMUylvBz7AYfvRu716qBv6/DNYvDNE6qBrrD+uPRe8C4EcZOln+GvhD7QjvnXteIq369i2EPQrxOIQV+L7hFHyoQTQxfeqLmKy65ZvQpvH/tYu4letcGGja1xWiP8KdRnxEnP4SoI90Hwj1XTfYL/i/i0jdiiZMXrB0PscQxe/jPwdQpy/GovV69NuCEa7u9RfaDDy8tfL6P8+e6vrrb+0XsUT5a95taH/Gr1UHaE90IDF8GEKCl+e+L8EnoMenR4qqIi/sQvcI3V9zIKP2s+bWy/P8vi/obW/wzWP+2h/b/8RROrhqEhaF0d+EERyqgkXDrWL47whoUTdOrRK7giL1Xl+CP4b0T7/4Y13+C39+Sgg/hBd6Ev0BOBF4OBSI1dghu+9donfr18yL32vS8dfSP2NlZGSuKhNcIfXfwhxIKdaqq3veqrtia9EfoCSI6DS8OIEhnd3c8JiHe+q/4ql1BMCQSq7/DqIx+iP1EK/WiPJz1xdc6Gv0wmr9eKJrEte+Zeri+9BL8Ir++Tvrml9BevEVeJ5/Kan8+uFYjdR38YhT766whvk+IX/hf4Ixfwzv4nqTHEJvVS9XVQV1Qv1/Eo/X69DdcT6tNhn4IS+Cv0CmrHgjHWv+uRf/F9AbwU9a+MYpKJ1wzqgz8IewVgh6N6+oXRO6nBJ3d/B0GUJnfFInVxy9Id4Y+hyLtJ5Bq1rnQ6VeiZiXk6rqu5a5UZ/lV6fz/KvfKveFzovVgsHL0td1q/YCpAvdxKL3c692hCxd6JF8y944I36O9egs8MDkFfS8kq8tX/BHd3elRO6S/1KhXdUr9fSovuq8Z+VH7xP9eqoQ6nXLwIFX8Cx+XwJYjX+OJZudxq94CMDMva/+Vf9RPxNi2ELQu/4rk+TX6FuV4JBL73/RK7BYXGIwrvVgNQEPgXBaExeWvuzZORG/LxXgh9QwisXev75ZOVXmeFfBDf8tYnriNcqELXIjRfJVhCi+qvrr1/3r/uRXquu0R6GLf4ihxC3upV7rV/1fHLeQQtYKjwSevSclP+sRl7q5f1f5e5PlsYrT/PKIVYxb1fBT8i/+WTl7l7+/v+dDm7ie/EL9y9/f33fXf1dQUfL8+Gv8V8mDbfy2CrBL8omCubDW/ifn+S+Cb5viPifn+Cr5viPifn+OgAAAD7EGa4C/AK3gccF3aD1YhXS+eK9Xrkm5/n6iawY57joU9CWlvRej1891Eod18vy14I+75S+i/7mX813dwjdgMf3r13959/ywuHvQuo6onFEHP5a9XxCuT17uK+b5ugb0XvksQrxi6nwY+tb/G0dh2EhCyL4mEl/Vdctc6DT/CPgUfgZ9CEZ+6LOrperiPm8N9f38+BD+Dl7/QjKFeJy//2viYjPiuqL/CvBbjSBMPss/gYQiuX65VxXg1yYNx6M3hmrnhd/qVGS5PC/waiV6+EcYhJcy+K+KxRNv9Bp4T4tBHr5ZeW/Q3/lq30id8kvrbw/6BTLVfSokXiatXEVxSEN8NVy/L42vdAZ6L3Wi95vivuvvde8MhPxte8fxxK9r/wR/TiH8HkJXCtcbiFmrQuLG7R0VO7Rv+q96rla97vvlrnQ5y+pKlfd+D6+76C28M/krtH6WoJ6tgpRexkolyrzafwVQjf1r0vFq2vj79F6TPWf7Runf31aHPKOJVOvavVyK/dI6VaA6BzoFwW18q+Ovr+X4leviVf4u6G/CeqgxQvrxG38EEJL/4c+EP1ID9cuwIHvvGax4S6iPGUV5y/qKgr+GyyruHPBz+jBDd7TjZwQ3fZ4OHWI1z1Wv/nrlXq5LxPr6ZUL/jZZUWTat/wk/vv+P9CETpeKov//61v/3R4yfhFCEnQYTrXrkoCCIV/BAvBBMIu/4Id3dq5Nfo7+w57DasSXHd6N1ct1N8JdAughErW8umtVju/4R4xejP8U4jj/hT5Mnr/9cpTbu+IXKuauIrAhlVzxvL4NcI/5qvWIfccvV6L+sKG8ctfV4YHovuwI/svuqf8JClirEaf6PKny8zpQRjkZ/D8pN30BpHdbqv5J6ikZ5uFEdvCTRX/V/VEeTJrP+J8Me/sR7kt/wrc818mNSEtXo2ea/uW8N0IebibpjkXvM6HEu1ciuVp3gtBAveCMIIuXxCJXhIRd8h3hwUstRH4Iivd7LL/9oz5h//6Ed7Bu6B7xGRU9Sm3evlvTloENCe+J7hjwJAcRe8ODl75V1iCGdcvhOj/8Lmpfo3fEKlWtWJOSG3/JcUj/lrV5OlfeGDa68E1EY8DtrA40QyjL8v+uJivVHp+9e6te60TuteqmlerjUfu5qGInqEL8NYhfiKv7+4mCP0d/ZfZYjBHQjvkq5L9W71i6pe76rN3dctCkR4xbHxvcIVU2KX5/k6+urqS+CrWIvVjvV8US2N5le9qblrngm+L7+0KY6v7+7ELiFWIX7+5arGKrwWfWb/Pm/xXyYPv8+CrBP/gn0Jgrmzb+J+b5cFWCz4j4n5vgx+I+J+b4+AAAAECEGbAC/AK0vnQJGIZEIJyerQovljNqtJDHy/Efq83L8vzeC31Lfq9cRDL/Q2o3lRuvnRnvlvvGK9fLJyX6/6qQUrq4++VXhocgi5UmXy16tG/3ghGO+9cvcI1z/LXE3v+jd+vdwhVRXh3fEovVcKr3cqv3r/wcrwe/B78Cfxi+o7DsL+glVcqtCV/z/F/EyCFvLQzvm+I/rD/wzp/o/deMX3WvfPv+susHOHvQmKKFL8kno2Z4KGvY7mcYxFNfvA51LjoBMrwIJF7L/G/0B79gMUTq/Qhjw/8Nvw265vZOgf/BPq4dRX664IF7EKr6Ru+BQQ6KG9Ca9B3/Wv/1fviMJqudCu6tfVgs45ENQ3xiJf4hZTE96/voGYlD66tW8b8b1r44hrSpfRe8Ke9Ecr17x3X6M/wIEJjEL1Nyq/9cI16E1+jV1y58tdcknUmTr7k2P+PQjvte+Ve8T+X5fL8TXq4inh73wcQry9RPcN//D6G9eOrFXrl+u0Z6Cn/l+W8CF8HwxF6uW7C4z54qoN+tC+8LVezuT1/8PQpwhpQEFpCTp+iPJyR3LeCLjEMNR9eBh+CH7OCG77HR/U3S9Ur/r/01esRrkk5flXvMLRevCQ7x7lfw1CNwh3Jr/X+v8YQ/3xiv8JSYpL3cVVaLGRLwni+oR+J6pCGOgLojoEnqvQ76+ShxLoL43pvGhdEf4R8JZO79f0NiSxI3idYvK/4T5PiEZ6T8YilSTYj2bvil/WJ9Qh8Z4If5jar0KV/dkVVkqIV/DYQ9Bb2EARCVrfL/X+nNV2vde8I5O17HE+p/wlURiF/Wr++7r3XP1ovb/m8Em92/ChN33d3d3d3bw3VvDf9X6yGVflN3E3evfOv+wyOV8cSTX8P1fHEu3yK/6v4W/KjvdBv+ryF//BJu75dDfkr1+v/17f8Neiv90v0eq50R/EpE7XkZ5Dibr+f0Ke2vq/31OvVyr3TxA5F2l5egKYY6+q2l95Mj/hFfEI7ET9ClxitRKliR695Pk/gh3d04peK68KKruVVcqGdVS1Q1ViqP3iK9WEuv0Vy6hPwzRH1t/grDXX2Dtd68q2FKsXhByv9Dnhd/1yekgi9cvoQhL161KX/Df81GzGvhCtFQrMfKr65QPRcv/6PfwUQQ3fi7CT+RYq9E660XviEV/CX5sQiPGKbGPhz2b4hf/E1ev7FKH8irV5cEQRhr0V8cqvEr/wrqtDH6m6uS9F7vL3ct8nq/cUr9zqx+r/q9Vq/6vFcXDPMjv8sJ390hDHeqVe+5e5etFfv7kRHu5e9X6ifl119av1L11WjvBtf88vPiF+eS7+77gwriP8EH+bHfedeBA4hZ8EWDP5/iPlwRYNPn+I+Dn5/iPj4AAAA+tBmyAvwCnr4qhCxeBz36BQ8Fpf+XQ1jHKK2+dGf5a5Zebr657iZMCnhvlxyCP9v9ehLl/Q7u5V6vl5IniaEEPVAWdVq9iFLkQvxEI8tXwxcqvXL8/xKJ4+X4mX/J+TqK7hD5q/rRexC169pf1/4KfgRdrrzsNwzyoIPCHL9IQ/yr1iCewGiEfBy/hH4lE75cYt79ffSJ3cJfr3zL3QFf81cXO/BTR+14KAQwjyxeNxr46vkv0W/wnnVfFresHZvBX8H7X1f+veDUeveHfh/4b3h3fCPUP+CYMfCV4r8CAglFDfLXoNt+tqrRqiMfVuwbl7/lRu3X+Cx/FLf4rdgQ8FWrhK1i+I+asHLy/6FV0BNKhdddUDn40nj/jaEdry0XzHE83QP/g6/DBLvxxP3UQidQ4k5F+oCKhfiPiaqEUL7/9ev16Ifh3/Wi9y93166ly/LV/xPyoKd3G3y1z16FlWdIWpU9hHx+/Xr5Vi9uq/DH0kXvCOFuGV6tr/7rDBegYBNHavWL9Z4i7Q55al6pEehxL3xBJ88vUnR9cvUV1q3X1aL7Vcviyr3i69Q4n3xfxa9JpIX1eveGwd/DULcd1CHzeFNXUWvmBF1V/0IeTtXrAhk8F6V/l8Ke4zv8CYFPAnBTXzzeid89baL1cnyovda6hz7+WzhZH/+udPiQyCIirVOrwwDTqo1Ge1x2jv1oj+EPsKInfSvVwp5aKxjJRdOPBWGZKDNCn7D/q16u1/XPLpoT0nD8Ld3ZKE+7ljPMTd1ur9jjezfEIU9bXyK8lWr4pV4KgceE/QCTBmhLZPVL/RHPCFE8XXQxTZ/4n1QnpOfoEuTgnhZfyDl1b/8mi/+Jq82GZu7/VzwvITdyZ6I93F/Or3syvr9WK5eo/GI5MfqbxnxmTVG79evCWV/oY8M5fWgu8l5ht79Cb8WFHf3cnRe7m5UT8vPrFfxtF6n/Q4nehCkIxxLo/7X8uE0i5/C4Q8EVE6XdF7f8J+rRXGI/++V+ahRnrf9prlv0bK60J7yfEV75ewIP4Rv1zlDFPSvBaZct/dYT+Ex3xVYa1sQry4LAIMI+itM/4rm+TqRCO8MCEdq9Xy//o1/lRH/XMVyo+Srggq50CgX3c2CD4PuX/+xC9QwrHxXzRVSISdcOpf669bV6t4lqWteqFd7XyfN8QjRVgu/ovfLV6vWSv65fkV7uMk4mCugvQt9/08XdX/RP/Kr36J0myL+vX9X9c1xCI/cnXJYELLlzXaEvBH89y98l98vUvX19xPxM3y993Nd0uJBVXKCr5sOb+e+XBx/nwVYK/lw5k+f5/lwVYLPifn+f4Mfifn+f4+AAAD80GbQC/AKzgInjECS8GNcvPJ6E/9kV69Xpc38nyU/nW58vy/Lrk/Am5hCw0/0LqE+0Mf9a6i67V/nRHkqRHevV/Rqul6T1e+J8CH18tCFSBfyr1dyYCJ+AiS1S1tVtVuvX/y3SL19fXVgLnR2HYVGIJXJPVoT4muL+L8DubqL6X5a9CvfMvfr30iN9L3h/1HIsXhfrqb9ekwrxhChnI/gcQt3+Dnv9BB4KObf/zII9fqe+EQSF3c78arpVwE2GVM3Wt+te6HeiJE919JdX1P1P1+J6/X3hHWCU2l+hCLv4hX+K+J8OafwcQ3yor36/iMEZLL/3aN79feP1h6ja+IWOdQksXUOfWT6r7rsGYruXp17wVPL/+hvdix3d9hM9ckuCnWi3hzWDgCJDL+L/RXSXrUUIQYafL7ovWupd/HfMiV8T39yyXob3gVF2I3hH4/569dgpBvdBEQhOuhOuDqGeRFroIYQf6Cz16vW8mB+GUv0d+gOAMOvoIV8d2vV699+35Pjf69LsIoXXidZj/C0Jei5VgkrU1whGdBIla1rwm6sE4nvpfKhz+D2iv4KfQGfrmsxN358thP2EdUEdeveWi9+vviaxf2JxqGrHhz1eJ9YyflRKrRVeri65vQpEbyDNd0YirvH6XcQj/8JghBHrV3gv7v0bu/1+Wu175a5f0Xv0f/hciN3xa9WWj+8lE6uE4Y5v0e82Srz8qs6iur6+vELjiChd/ZFfWC8LX1/KiP116/+I8CTR33glBD07n+z6uupbyUd+gkDOTE5OH4a51/eEKL3/kqnXuYvigq/HLF8gKDO7u7u/vBOgiTd3fd/0Tu9elVaI8vKr1xFYj4W1g0DnlLWlv9H36CevRHrte89X8cvhD9F6zvDnJ2TWGaEsp789V81XOgk8nLdgSxnjcj+T5L4uhRDuqAjhBe6/hBYvhDXb+WvScCXDApFl9HbwQ969l/XE0aPMuS9L/y1zixW77vTcbE9/S/aF94n3+JE1ZgYdhj4a/CYI+75zFL4I/QCdBB1S/8MhZe/X92Bd/on4df9eht5bCFEiq+X0S/gmrl4Mt8oIxG75jXEwwi+7ASA1Y7wJ1ZdyV3V8ghX1MrYxbGuM1i9NeqkEZhCzcXDl9fWXfrHvktcVJ3ojnf36q1u5V6uX5e+u7GLfELiF6+9X6tX+J+JkvoYh5seHshER6rky/Cde+QFBtV1V/VfGIWJp/tGf7V757uSanRX7lu9Xr1frV6vR3xiEWh/e675UKaL/u+/5fv71/8+IX58Qvz/P884hfuCL6yf47/CX+bD2/lwIXELBN8nwh8R8/y4IsEHyfCHxHz/BL8nwh8R8/x8AAAA5FBm2AvwCtr50CRiDCvf8XtdxX0j/m5a5f6wKeXkhmgQ0LeF7i5vQj++T+u4pXnqNVyTAr5OIgs5V72JX1XFojGOW5iF+Joco91V9XN8iLF8nhv80ldcvQGPVAa/X4O9HYdgp9BrrfxP/yr1cTr/4nXer4xfvtE76rHr5K6XviJOfrR6vCVFe+E0FKgn9DfVxX6K2OJ6rFfv2F0XMY1R/8vAp1Oo7AbIUVzwYpcvBX8FOv90b3QGkM9fhs/hOveE6xeCOveCP4NfxK9l//RXxu+fuChSo60HQor3wdQ36K1+i2iatGbwV/BP8Efwz6iUbqXCUQrPwRXfc+KUqfLqsF/wRvxJqsBRifHLwz8JnuwO4R71fsRRe8RrClF6hRIdMJ6i/k8OfiEIf4PIe9Deivrlq56XLZAldflrr7k7/RflcsuTeLUnLb/hL0LvLsI11for165RS7v9BAq4ivV+rnVK9YQ+1XL6f69+vSZ/i9cK/DPcFvctv+EvQRirDlevCGP8fmzaa1VV4dPXLKvBz8FvEIIH3g6or1hjrwaJXNeEAhS/RHr18fa9fPv9F728cSL9r+uHu6Re/XvY79e3/CXJG+hOdP481aqqrWvBUI8d+a1x34JR3kGfFAjEaq/YRgi3v/r+IV/Q7wcjsbEvoM3xaI/xNejf6k6v575UXvnV5Okf3QJ9Cifj4R5K5Fehy4pPR/TerRPaM/gg/J8iM99T4kLL81g5/gxFo76//Qh+ohXk9f1hZ/SL3UO9KvSUBN/BbCPyLitF6X0W0X4IhUvu34KBd7vd3PxRN3d3y/X6I3jUTu5qCLrRUbqf/vrn8US/Ef0d9NBXHIrHho3QVNebJx6Nltr/jF6FfiOIvk1/Xoa6Jr70EmOtWJK9tz9cnyXjOOIdXuvrsUTT/8JrwyEkV+wEyBARIoX9Hf7k9bRa4rr0a9L+X72XwWC17ww/lRWPtfedondAlfYNfx6K9YNgh4OvzyWAgwp3/EXlo35uG4Xf+IRX1otRfq9YNBC9XKhWYxilyvlXMfKtKq4uM8HD8hK5Kr765kf91DylTCHX+3EKvjleu8Yif2OW0ODltO//F4vk8GVE74qI7V5By3xSyer/EwVaIgi8Zyoc/yxF3ffyK8nwb9/aM9civdy9/y/euK8Qv3L8l39/fd/cF/zYQ/xXyYMuIWfBVgr+I+J+b5cFWCz4j4n5vgx+I+J+b4+AAADtEGbgC/AKGvnjV8RQhdfMgTPBxfl/+JQ2Vc8Rydd1JNgRfy9ISsXy1Usnq8FvLVS2MQhJr/5f0X/cIXWv5LibqX2JReoQsP+hLwlxKGd1E/Er2IX7V/idf10vfr3yfX69k+v30XquaxCycq/1/2Ao/fR2G4JfQc6uTX69L69XEr3x698Tv+Sg+TqvIRe8EZ9cn/XEX9r0EUXvBD6Bd69r8E/NeH/hf+vUvA7UWGY3PnKoyU1lmfA4hBE7wKYYWJlwc/ByI8Hb8G/ry//ojnm+q+6Bj8P/C9e8I1bX69X1g7CPg7BxdE/BlCPrUb6F/icDSO+dCOy+CP39Bn5qxeF/y0uENGY1cIeq5JeWuLQtugIfoT6E+vr6/DPwR1fwTqsPV7X92GwUfBhDXorx/dXF9SkCW7rlk6pfL8tc3yfaE91L2DH2vf3r1ctiifYvbXoT3WvdaN3wNEFPKhD1ejPXL8pC7vqLvBR6G6yZuXuXudHbxde8f8Tvh2rQI8cQT7oQs7wlwx3CiK5eC7Zf/43NNrXh0/venQxDjZ48PvXUuu/f9UCIR4NBnggJEXr3z+yfL42vfCqP2/0X5fJCnOvRvosZPz63tCn8JKvV/VXpYbCAT/GY4hA35KqwSBOFFd4Rqx1q/UJfHeHKEo77CKJ36vJyS5Pwii94FQPqx0xNY0JeX5/w/CVRKxTritFzxvavVKiPdTIj3hUwJeqrXW/0Z/1euKXur6BD+ORX1gR/4KQn4OwQyci/71/VFCfQSCKO3WvdiQz7XxCtJwTwxyLHmXwzEGZigMPDwSn3fjfxBTbvwXmIZV/JfN1Eoj1cX8RXKvdav8+v6xWahr8Ja2eI4MYRrsUhM/J8mX/yCO/sL0JZVaEVP0hDH0ryVq/X3rzp4T+l0Cc3xNbEor/r+8JDaFEvFEvHExihd4dCi94TGfCFevVjP6K+/g7hrkWo7lQpy/BR3fd8/VLl1Xhz6X2hfeJS9LUZ0GPhL0wjdAXTLl4M/hOvUv64nwrsYrsU/4Xf+vlitpE76p+DgQCM77kdeAjv2hhkxilxKuAwgQ+xPtXui99r3yL/21/b+64j4W9gkRf4xTUelXERF/fiF+NhjkV5H/EYv4V1ciERz5F67XfNzafYX9/X88VS0MQlpKgRej2/VpcbXx7cQT7X/70Kyl5d/E+Cz8kl/xcV6vLywRfFcnydUhjzd/f3iFgz+K+TCX+bD3X8+BC6/gq+K+f5viPlwRYJPivn+b4j4Kfivn+b4j4+AAAA0hBm6AvwCoiFg650HPyc6I/y/LXLNVK/zUORXa+WXlgx5f7uVcsYiPWIVz+i/6mV/mvlu4R+Ve9F7hWC3mV7+TlriZeT6RO8tevBjRYruWr5OEfi7Ow7BZc/z/PilrifAm0Gu6AR9Yqf1WCd+zfIid8yxfGfEb/181V/EoveDv4J/g5gkLu/Y4lnl4EH8MoJZ4KOboEvwT/Db8P0Pe/Qm+EkU15dtv+Bboz+ksvSXvCCWLwY/Bn8Zr0b3hl+Ckb0BH9CPX1rF4Kd1BCi97D2IW+DKHvR2mxGTB2rza0kK75PmXXxCJ3xy99r3QXMvfr14f1hMehPfonT0BP+CPJzY4l3+Byhr0Na/Xou7q4u/BKEN33fqCRIwzRqv2245Ej+fJVT/LJno8Vb+XePfiaL1VKvVld744hctfwUYIPsvdIY5Nz/L4aq+/1fsIBrtKX0f3jT64/vnukDdeoTE0KJxxOoT4hFOn6sQph0939T3g9Mhz+BBN4v4ED2Lovdwh0Cqr9Kr44hHrwopKkU6oygN+FOSM9Dc6Iw0FPCiQh+r8Fj+b4j3RX8KLw0feBUBH3cZ8TjcL2X/Hgh6Apgl+VCH6H6qv18e0rGIWsvxfGxaxPJQUEdfwWwlywt/UnVycyEPrhTv0R65vgo+CzwShf00J7oIeh/HEEX66rRf3YSAm1sTXoT30je6r4L4J/BWXd3u93dMq6BzMZy0+SEe7u+7/oEXd2K1kz65ugW1/+v/LX/UJfFq9ejv19D/R/XjiW7eKr++fSUFMEJu76ji93JwXw5UlLBBr6R3RP1qgk8/Ii/PCv4le8K6r1+vX2iueFvrXLWGwp4VHb8WMm4I4cvjLublKbd3j98L9gQ0jv2HH2CAnWXu5cJrwmOk50R4df8g5DR5fETYoQidXoleCyuasDIWqAKoD/wtW+v1v4eqW7i16flxyJbwXDuoerkVvAr+wMoW61eCZ/xXJXWv/l8P79E7r677rlsctKvEK/yYxb4gmriUX/f39urz8SvQU4JqIx3yev+uOFIrm5YLv1yfUiFOX9cvy4he5fv7+4Qu4K/l+sPb+TEf58HHELPgmwVfL/iMnzCECeI+XBNgr+K+f5/gw+K+f5/j4AAANKQZvAL8Aoy+JhRfEoEjGv/ATfwEjgy7vll5O4j5KqSXAi/lu/4jrr0JeC/nROpfE2MUQ5Yu+tLy5qib9FfHE+6A91fXxOv4MRxL36hHEL8SidiFZxCsGn9S1HeCHv+rq6iUfu4I+u6A39r+dhuCZ/Ig968CL8N5eEfiVz/E1gT+uJ6rXq5EX5W1fN4NSa6+qXu/HIvsn3x36v4EOveGPhHv8EgUe/UE3EfNiEEfBHrJ/Vv19rBt0f3gYgiu58IqZPAt1roBS1d5gl4WS9WDPjESVZ+veCcSveHaxVQN94W1yL1cXjZWWXw18EHxG/gqgl5P1b51atb4n50b3hCvZf/11jiTV72FJPROy//+DWjxV6K2vG+nRu6fsDOJ7++uT4m/R+/XqL/4OsOvw3R6jF912gt1+i9T/vlXvv79175Z82zsT8L+Ea9VBEEfhpoTX69v+GfX8I8snaCH/1/+r9y9A6NVg4BF4yi94UUj/Xvtdr5642fGUJ7f8FXyYGMyEP4NavVR/goZCu+muFuOJm0no369e/Xx8TXIit5mvViROInAszpcwiR/w/6PGT9giNWr+GDX1Jsd5KEP4EgEZa1+KvhD4exsWaCd8eEb9Cn0uL9cTl2/4Ji/Q76Ftr++TvtYZyBI2qqvWFw4fXoz9av8RfBMis8J0X/hsP+CEM9fhb0Loz/r+hyL/JhXfGU/4KcM3q/hXvkTVj7VKlhtIQ+8/V5sTRX+IriPFrsEvz/nV+wT/LR+mx2TBcH4cHI8ir5VZXmNe4jWruTlQrqL/8civ5RXnfiSr3ui9XCd1Fq519Ur3i/hMZ4bHL3hX4IQgva/gl4hS04xCBEjnrwUd33d+qtfOvXhER4nXovXgwDiO+sIZASXe7nWW93Q4hHfFEu+bfxF1H+Ex1ilNnj4Xf8noTciVhL/ghu/nvlQrLf65eAihK5XzAiu+RZX36/rdX7lX53XxfydQ1iEV4hROnhL0OlFIz64IK9/yY0sRxHxGvl+aT67VzqJ6+pOvvkrxS0KWetXsYhJs/Dvovi1zKty7G1Ym9Dv9asTfNXiib5Ym36nu+DEQhTkvk58Qv39/cH3zYjVc2DD/B18/xHy4LsGnz/EfBz8/xHx8AAAMDQZvgL8AqYhZV8XBpgwoNP9rUmnLyInSer9xVeryctctcvQGHBj39r+qnX/Sq8q4qu47q+vr7A05l1E+DHfLBhc/yr1iF8BJ1qapLt+/oFeTj0X8lwzr4mjsNwR+g96hxL9XN3IvS+i6+NXvlxC1gRPgx+DffEVlIsX0vXhmsUvrV0Bp9fwUwSevv19YhVjlv83xC90Cf4/XOj1jcf8LYrxil13i0veFN4P9f4X639eEevvw20Ii8I/BT8M/D/3xSL8L/DDK7/n8Foj4JIKPRG8M/Z+rX3jcnFeDUk1gJH396EvPiaEdJTCPxdl/gSPglzS3vLy1yycqEP8i/vak5fl+JQlvjV942vz9EKnuvVi/j/j8laF1QthZ6hn0GWhK55V/V9UKN09PvQ7q9e+Sti69e8bsUT43BWX/4SQ9hy0IfsCOL7+gQu/Qp/tHfwJYrwv8Hh/Bd8KOsEQhFYxxCF9vtX6CJPFV8Vt/fy6/X369KNQ3FXMidBD6PnT9lM9/iKwsPRnuo3XCUO+Ck3hzvH8JVrqq+WuEPGVf4S+Gkd/hf50I/jidXyL4l5+jA7xrEhv0peBHQU6CfVBF/n+Sr8QvQdE+CASr+LHEMq/jvPl9Ff9Xpf36v8tYMtao/6y0bq4vxWuBHgm8w3d+5TbuujGd/yE7u+YEVV3rCwRRu+SuI+SeqBGPVfn8d+JkwkGccQzQpuoLbwl/Xv174P4fukLdP1JXJ6CX6r+Sl4Vo/dA59UvdfQ75ReOJvXE+SveM3oN+CEEnxXxEvBHBT2hDy+i1V6O7xv7Xt76J6+kf/UV4OgTUKJLjHEhxGgv4LQ14fESYT/olfr+hC6/hd/x+GKKdR+CS99KlgSPyoQxrnhzCCKM+zH9vwPQZW/gbAz0M/IvenMIX4pX+IoQuIVdASwhjFvfL89ckED8EOMXJ1g62v5rnq7+fqREY6+7mFEwZ1IvKi/XqxLyy3Mr9d1wcCF+XqXr6+vr+/v7iLvv7++Dr6wTYz4OvjvvBNg3+O+Dr4742AAAADe0GaAC/AKeIXELQhaXxUHXOg5+udEefk6k60XupKuZX775dfrXy/Kr9SotVg7XywVckRxOv6rmr3cRoj96vKIX5V/VRqv4OavdAIPBNUR2CD3XyfJ8nzS1q9c+vl6nxC16J3XJTFVyXyory62dh2CPHYhfNJxKDXYhfAsk8CGSlxv0Al9NdV6vXqthhe7/pe+axivXxcvBjDvNPXJU1dL3tVhf5aL3gwr2N5kRQkiypp/8J1yksC/8CHxi3Kw78L6wv8FZ9foR2v9f3xuMjQoLIXXYEsETM7/a+HIIPX0nyCFS4XL4LT9gTRNrFfX6N1cng3IsvHrf2vd0vd6J79F90Bh1QEkT166CvX8qw3Cf9C/S8CxBNlocxjER7169Jy6/KVV0uJv7VIvJfOid3L3dej+8FY+sWLrK6xtXrN8K/CP4vFRpb0BR0dhGFvQQ9eLx3oIPWCz86ufq/cf8vy/Kr44nTJYEr3FIvdx3gIA34Irvv0CHrl/nX3z/f38suJ0Ni09ehPX8FcE2a7v7C50Z75ZfRH9ly/3E6I/USjseN/orHh4dfdUcyEd1LJhgbJidP/pUJ7rXsWxyeoJ8OQQhFaq97Xz1zeBdBB+jP+CfqtVVL8IAhIq79TfEVzIr+EwRI6deCMEda2Pibr+W+LxyNBP1hnrsHFH6auCfBdsYjFx7X4I+qv8wJeqrW/6InXVX61eXBf8GIV8Jj/tXkpPr+JRf/CPcCXNwIcFHghqu5+rn56+22mnwqa6ZddWjPXV4X1bAldrXoS/4IT1q/V9D/hQny+qI/TDPhT4r5xKN2k4M4GEx934rfBLD9aO6K++kEH61fq1/e2vVidcTjiCy9/FEV65PBL61/4n4R1yq/QnWGQh4bCQIrv90BPCG/17yV/+v4KvMM3fVrl70r4VWKf0fqsFfqCJH7F5vMrwR93ckxK8SvQS+Tu0Z+tehx/wjgRKL3gXnjEZ74xS5mOwDAARUU6joB+Al8EFY/arF4jdBn99avJUOYxHH/MeGgh8dr9GY9KQUTBXhH8iJ3yVtr3p1y6uJuavq6rq678UuMR7GIXwMW67pYLe/0I6SgIZkV/TXOXcsghT08/z/q8nJXUGXX0hj+ya/V+q+pe/uL7+/uDH58If5sGXX839g498+CbBV8T84hApiPlwQYK/ifiPn+DD4n4j5/j4AAAA1RBmiAvwCol/60CZ4MfQReN5fvufvn5OwL/HIl1ery1E9av1+BB+BNq8E2bWXJyS9ojyL4lYsYrsYhaXN/3xFYJferyiiZF/BcKJd3Kr44m/xK9+vVxPy39ev9/9SaviLEK7+RcT/E52H4fxGJGIOe/XsUTTeEuuehhLviifififl+JXsQvsv0v/kXvCJL4r4jw/v5X/BD2i9WbPQFH0EPhevY4mzoL64XRWP0UyKuBVrl4FEJIjb8GNfeCV+Cn4Mfkqx4MT+yfN8RWCkXeC3/Vwz4PNLAo/f8EPonSejt0vdEJVVWClVV9Cv6J68MhxYuwKoIFixC1QOWvvCIq6BjrBaFUfvC43WeWhHeevuwNPv7N7/DHx1C62nULr3f6EYxRLhEh7CFer19Fd6Tqfq/nYQ3fy33Edr0voT3ba92X2fXr1Yj1D9YKeLYQKxUJDEGy48vreNyZatDiryev9yq/6vJ6vY5cbv7iF7vk1Xq7VvlXq5UXr3XvE17xvxGhCG1wJMJcXr9X+LvCtehDCcEIrVbvl3/1lEbv5b5Vf5fZVfXy+OfxlYMhGOIJ11l6r5SEd/0v69eruuRerCuSqhXqua+dCfRD5NHiiFyRfgiFeCpVqhj34g6rqvwJYKPGhUEhqqrPDEENVVU6XE/r1DZQakyPPjZRWmXj0Z/nm5awQ/16uGPYy+BThP4T9Hf57qZCH+bqb4jX/hAUr+UJS8y/8FP4YVzwqEfQn4nFE9AhP8vYIdc/iAj0CYF/V9fxPhT4X7/hP/khPW/J3dWBTNXOif9vuEV6vX/0veHa98T4Qq+KIUuV/WCML9WivNiPk3QLAcgjvfl5a9WCoFME/oYlRue6v5EWugfiLX/iaE9fa/icE4IPBGEPhBa+fx+uH4KOoh0Dwf1mojnma/JcEQJkd8v/6uUORLXgQQ4v/CJvhL7X/6/lqJX8J+j5pX/CP1gIrrv1zz+0hF/CCBDd+nXSloM1eSope6/AlBxFixC4hfAj5PQh79Fe7iIKBiEWupUWLqXpHiK1frRf91+jP3q/zyL+7ie+C7kk2WK58QvXP8t/XBZ98k4hfnkX/zzehTX3Bh8+bfyYIM/+Drr+fBNgq+bNk+O+XD2Cv4r474MPivjvj4AAAANeQZpAL8Arq+JQJGKEIigxqeI9C/3zIreC3jlt8l8t4O8nLBRck/LdRKN3zzXMiv1r+rjpRSv4n4mSwETgg9Cek5pOS/Qju4hemr6lX9cvy9ReMRvX6vdRlc1+j9XE/Er3xa/7/QR1752HYex2fqvQIO+aubFEL+vXcJ/L8X8b89cXfrLy8cTf2b9ermUqeG/gxNJYEn19Uj5fBTBDky9V18l0C/4b+P0uJ0V8XnszIuD0SCPu+SrQCnEL3gQwp4OydgJ1okvBnV6/z0T3glEr86An+p0TuvrvBf/QkqXxXwl8OQ3zL0R69fZKrxiKcl4+VGboCuXr6nVroNnXviV6+EL5kTrwY/BafsDHQlutEbo/oTRO8EWuJ8VRe+bwV0XvBOtda94J/xK9BX6Hd912i9Xa98+v/6r1X377uyfv/o/dSr0nLr9e+16XBSPhPmk4r4yX0J9E+CEU7vtXIY2qk7loFATxxOP8uvtX8CMugwSSgQ69F7rXv19ebEcCvCYhC8UtcOr17r0Jbfz3g10OQ6gn4OBfQVXh2hfOqXXw5L1Xz/oz6rk+e+17GKfIr5L5UfoZ4ta+KVon0fKJ2Tf+viPk+XqE0RvhVXPGjqJ98M4EL9diifh74eBFVd/hv5aqM60IeuWYbGi5V+WidbwzgzhHniNpWj+lfwRHqv4r4c+UEhFXfw9BT1VVVVXTr2CUiqtV06XVev/iqXCf4XH369rr+VemuBJQnK8IBFep/A7wT0EMmPgjNaVUqWfJ0jPLQbo76r/i8cS7VZA8hLq7Qjt//MryYn8TjYk9eQa/+RGbwTAtgm8m7PrIKd8lfYfor1n1trlfovVnS9XBPI6f6Yvwp7B6EZc4Y8SIrH64uCf5MG/TXPXgkM93z9ggDPggPRf//lR26BHXuvwh6hTwgI+E93/py48d4f/EfPDj/hDRKwcV75Vv4HLjFcyjVQiHwkTu9VxakWZfhD+q0Toi4MkV/BgGMQuIXwYk6AR4hX6eetXhQQjwr98klToU/f3avVa/tP9erFcfjlsUKXoBrcQr6YhX65hhDr+Cd/IqVIchD1PXNWrzVES198RywUVzCF+/v7+/vu+/EL9/f3P6FNfcF3zf4e/zYIOv4hfwY/E/H/Bh8T8f8GHxPx/x8AAAA3VBmmAvwCjr4uNELiFmXxfYDHwUegt0WOIZ6u4nwKX5ZOT5Fi8E/9X+SZfE/L4FPjicbwMP5YJM2vRekqq5EZ57lvnv5eTqZemoDDrm6hFHfwf4I8TXvHfmk5P65upr2JXunROrl+dE7qde617575PiEV+plKlVETV9cnCOdh2CLm+f9Bz0vV4X0OJ3+WuJxRPyrl0BlJXOr1QZVciv5NccsXxHhHJ69I/4IPR/Vm3zVcV839Z6J1Y30CftTX34JvwyCQ+7sYxW52sHMK64roDyl7qZE7wIK7AynQlj5kMc+vDpfDJfD+sIm1zT+H/v8Si5fCtv+F+ZeiMRR+r0Rqza2boCOK+XELl/4mVW7AS/oHJ/tevLocQzOvhp3f8ISUY/xvQb9UhrdfX19PeJ3YXfYeBX4zT/BOFnve+oT6Q3puKR6ifRek7Q7KXv5flVvterlXvn8cleVfL4Q169XE+XWEQr5wj5/j3eTZ3hMYhNqqGIT6v0b9cqM/UbNh719RCO+qufqOWLzaX38npfr6f0XvD/rha4bqruh+P7Rn8Jzd3fr+8GK+TXgSKv0CQT4jk/S//CQa8SGfCIR8dV5O64z9F9+vuignVuh9erAygTunxRCv4NYS4tXIVXHX6q94d/G+z9Qnk9cCP/rA1AxVKuF4ITKu/Z691qlXi1ahpBJs+eBNBv7Eoz9DhXYHEL1y1UqJ1ctV+DqhrfHVYHvDGCfCWqM9YHknYHELd/g4fgg/Nde/6HEJTrQMwcfov64R+EFe6BD7m6nXq9ekwTAhrg3Q7oJq0FXqrBIIVd7wMjEcuPu7q65qoI6awh9AT/hTus2tqvQn/YM/f1oR++JR3lx68bRO3/CQhZ+JhH5KPpfoRFdA1OhPddYkTYom7+g8/EVeXE+gIYS6deocQi98fBVdycn4JO7seTfa91r3z3jso4n1YTGI761/Yr2OvCuuLhL1eZ/wngcj+BeEoz7/W+vhDw6EgRXfidcJE8dXqx1E8daLyp3q/d9dYMgkivjOwjO54PxEnL3P1PVRdcVCYhHhXpCHvyd34U1xaN+9v9f+6K/YJgmvd/U+OJepbjF/iFitKCy+61f7V+/HEu9adckT9csl2rwXiF7iMQvyy9V3Erm/v7++774M/vJiF/N/gQOIWDX6wQYS+XBNgv+FPg0+FPj4AAAAPLQZqAL8AqXoEz4hZ18fJYD/98O+greK9CHi+Wb1/JyL3UR8nUxu7vxE+Pu/FK35fluwNCgn5PmupJ+dE/fOr/PLxHUqvEXG/Ki9V31EdcEFjM390vSVEXtL0i+J+VEOnyrl9gi6rlr9a6iUTKn/8v18nlVXCG3+76qEe/r6/i87BHDt82O1aWKIHn8nXJYNffdwv6Oi98++J/DvsBQ17oDn6+h/VcSv3ydCAkvdCa91rF1giu/Xh/0BB9f2vXz/CPw6YY94Z5or0P90q++XuvkV+vwL9e8GPwVtdffX2L+evV4JC3ub42Vmm8DyHETvBGGPGVy06nfbMuXYivddcn6FdviuZ//o/fr1LgSIQR3+GoY5pH8LLFG1ozFUFV4Q3nE6/XXzomvAgiFf4mtCJaAwietCe6vwcgh6AvhvqJ6+q6+vwU+gKLWutX+JROhO4S716QYvq564Sxk/MSevfalVeq2PJRmK6QzLX1v76lvu0vo/eMxPLdeLZZd0/guyHdPV9aL3XCohbES/r2vDvx68J+wv769dp+pKtjEktXE16/38qv1Fr3V0MUfZN19daq9evS8R19fiM53hIWwvSJHWrAu+//v8VrIZCteKr0Tl/oz1XXd+hH/lviy9V4Q/Fdjgx4NBmuJ0Jf42akTpmrkXvkXvkvBiDzFEwlx8trebeOxnEaX65/nvhNXPhfwKQLwR9VY/RH6PX9+r+JBEjvjZXTvxM4pby/jUTvhjwv8PiVeFe0T3zy2sICF+M9E+b5NcKDJiqv4IgSkVdV06rDGVe6/E747xte8FeuJrEV701/+r/q9ZK95PhwJ+CYvwivXwdoZ3XCusIXoJva4nQh69WIj1+fEO7/k8f+Ze8R+foHY/oEJULe8Zr0b/m3l1QPQ1XBbC3xfr07+kIe+ukWfk8L0J7oF9W6+vHEq/iPn1UR2CMsg4n2OJdMtAZQTfFUt7rhWFvR3l4mbX9Ga/Rum+186tr5VjdCgiuX6O/sy94VUtP8OK3x/dddDiX+VhkKVxP38/yq8MiFhXAqCQSXfY1xIGsFGuLBDWOfCQIiPuReuCD8KVl4yvfLXr+tl+ZXvBsKrwQnd9qoBU/k+Jrlh34SwRP+lwrfdoVH7IVXrN/rllvVj9Uq1EK9fXEK9iEWS9Xhr48Ytrq5PX/2qVLvFE1Wsfq+wQH+f4v4lEfFL8nyUKV3yy31yQx8JdIR313X1XLJ3fcTz/f39/eIXEL9/cM/4c/wh8+b/Ngqz/4EDiOfD2G/j/mw1v4/5cGGHPj/ifj/gh+P+J+P+PgAAAOKQZqgL8AsPlDTvgk5Ipcur1yoz1yzcnU3Wj/+ZenqJq4R8Cj8HfoCXgrwS5+euXqLxiN/Q5FRvLzfIvY4nU16K0j/gn5Pk+auaUcSz/foj0MJd/lxSIlEKe1yr16SP3xGuqoYr1V8nNv/Ow3BBmoMd2Ky9XVVxCN3YOcn/G+hvgS14EP4O8nr6uT2q5UXvmWLwT7+7gx3+hlQrzTcRXN6oJ9XN5c/oR12B3P+veL9An9G+Wit8TjUJ14GH4n8iN3yVQGXW6l70I+ORovD7+EFKnwgpUxxO+v/D/+7rGxoo6VB/EVeTSl7RLfKjN6E9/Yz4R01hcdp/N81cRXonVRfRfX1oT3gTwv4Iwj7onvBiGfBrvG6oM/Feof+H4VqEuuPo2fv5b2X5fnrmRnr1/XL9r2l5epasDPrPrFry5eGPgzhPhJBFIohb4Yi/Xr9CLk/cvL8qEP0B/1YMOk+O6AhBZF7oJ1fr2vfYsMdDhH1E4h+J4mLhU8vYHsK3QNcIUBPF39Vodzp7oj16sdhAJoSx3fhAXfIv/BiGas4QREq2v3XPXIvS+hrfCPwQwncXXo3Qj6s1zXVTVQMRqM9bE9aO50CENqnXhfCGOti+3+B6BGiO717rxRPyfHeDWhL+gnd/ehne69+vfr3z1xKL1DENFypv4mCniUZ9L5Na+J/36XzeBHN4E56wqHtWNYFzd3oV+qBeOrivi0VyWqX/X1q/USr9RN4SC/hP5/QP+18E5lrWvu+FOeWtC+jKEUWsn6//gwEYxCjY+t4r5PEqqOJv0Tvk+EPk6iKy0d/CX4dV+wLbqievr6+tXlz64jfwTw5U6EvE+iP9SdeEXdaFdfS94EMMfJ1GoT3hcT2BZ9/ggav8P9B3QxXc8lX8KZnn1JgwCsEfonpOsQthBGIRc7bfwgodI+/b45T0GDy7BEH0fLf/ivV9X1r3Wv64xHfwYBBXy//q5hLfiX+nk51bwyOriviF70rsWPgm6X18nhwngQNcSjPjFEOGUYxREjkq48UsW/BF1zcVoRjom3QFeCG77VwgjPO7r7iIKVyev177BF3ftfKid8TdOvKvr+ccvrHIt+uuIRHsct6T/YxWkqVREFdaJ3Tr+TZUV4nkkwEB8EB0WvniL4LekEn6iEV7uWO7xinILYhcQuIWDL5P8EH+bCH+K+DH5/n+J+TBVgt+f5/ifgx+f5/ifjoAAADhUGawC/AKUviYxfFS4HXVAIHeBpwYcqDUf9EKljFLjfLe1dxSL36v8ivQxXcgp9H/JYQycnyfJ7oV01fU698q/vlVzELLcciv316vYhfQle+J+JV7wT4IdUXoimqqb9G75pa175VesD6TX/gXcnXVr3cVWCHfMisX6v4N/6uVwjnYZhrCWXNiuI/Qa6hRPgl9hvXKvVxvUT1r3U3X4EfWCt1yL3s3glr3gn9ASy9UsXU9v+sv4IYcua+KrkRemHL5q4hEc917y/BSdXkf/goMj9jOZxjF8269ddFay6MM8IaxtEq6Ak0SLrVyXm8EpvdH682FhC/SJ0gpZMRrjrzd/zUBlE3Qs6+rR175OgQDaHIjO/cLK5k/f/XuyBTXyT4n0Dv5fuvXgnoT0K8dLUVXr1cVI/hOtL5ZV9Sf5HJ6Ed7eOJF+13Er1XOsSrxKsdxaIx9r14nLl+X7+J4ogteN1y+E8JcLSCia2vgi/8frpH9W695SxVyfdVP8/3dQqhz1YG/pKJn8DwvBE/tFfxmvROl9F9EHiYUFxtMGurAj0K1XG9gt/r0nr0RYn3gkNWr1h9/P6IhD3iC/Kv6FE/Or3QVVYPA1jol03hjJ2jd+vv19+vVxd4mi9jZyeXhv8OwpUSvfP2FcmVx2hHUQjP6JLz/Pv4ZV/aV5MEYpexylxzwyDIER1Xc8EAZXvQlG79X8tX8Z+VX60TL9e/Xry7oMAzhLiflRe616FV/0DIfV/YCXCGIV/EfMYqr6ASAEFX+kZ/pf/Jfr/2K8J/E/COauS4Enoob6C+uGsew7Va/CHoLdilrmROlwKP54QW6gjqu/kN4teCkVVxPf+hD/Jr4jwiKrjPHryZOJQ95KG/i6xGhRPQZrn+T4fhm+EOp+MQz94JxHhP4lec6E9XJJxF+i/8IV+ViPl+Fwh40vUEnxENCEUtxSEOfX9epfU/L8qFPS/8OoWXd934EIM1koTKXnqohX6pU647QxT0as+l4I6v4V/HfL19Pk/b/4JfRPVoyufIvSLuIV8YorrXEw1r/XCzay3xcR0vWidJ6/ochPx0xHyXwgr/CEopCH12n/4Sgpwhk4v4n55bnV+/vVvi5biEdjELIORHfELQxWkqiF3+vd8FW1fIid8vstctXFqx1wneivBeIXuXv7+uI5flxCwffNgo6/nwXcQsHXz/Ag/P8CD8/wvAAAAPqQZrgL8ApK+JixCxGBfy+CENbu0EuD7fJXJNYCC1cTPbFfJ3Gd/0ry4E/XP8vgTfg//EwRYQdclcklSdfX6UvLfPJdd693Sv9dxnyXyrVr/pFt/PDmMy6ovTcl9I3fJVNL3c1jib/E4pfi657wQ60qqI6fqfpKq8Qsr/zsOwkMQW9PQJv8TmyjkI++SQcTf5rHELf5175/i9c/8X8WvScl9eCMWvfy4niCSZqDlCuhHpD+sUsnNVcRkr38vNW14Kz9AST44hveL9gQQj31wQoT2NVnXgQau8CSEl7wcil7oDWIXulX3Xe0hHvDrWLwQusT/Re7An++RLAhAowt0vXxFfWHPYczfEf1+LKvMtj6J3evu2v/iFjn6kWfJJ691XhHVgPMPoSzwmL1v1QOfWhHdfV4oh+wJPs1F7wz+COGekbqzjsZF8/ZA7EUIoV1dfIgh18v2QTu+/uUt39yr369XE+C/KvDi0v2/0Xvl/RWmxS7H4Y4q8J7oMqI9bl+jNWlddVq/X3L3avXKr/r/9f+DSr+HsmasV9/SL79Sq+1988uN+XC9A79LCOCNq/ht/12iZfavJgr0ucHneC71Ud4JByFs3hKOqx+if/BJ1X9Yj8v6N36++WTtH9jiRfoZx+fniXcIL83YJghdaIx5KK/hD8T3C/xOMV21gZYDOBirKqE65/dX8FNX8EoM/hf0JvCHrvn+VE6udH6FeJkELdOvRvVcf4Wq+IURzsngmNr/wRhDoEXwaO60Ke+bfm0vSrED0L743oJkq4Qqv9E8ehdehPQpUXiFl+Xte8bWtbkSL+IXeCMyr9WGEiP9Akqu9YJV4Z+J1YZ30hD+Fx1YdIi90BF+hd8PL3hP9mG1rrRnqj8UQjrn8KDccytFSTgnhTnv5vR3/X9r1Rmm6k9CukvXvkrCGqAmmloP0L7o1Xp1zL+TPV/JV/kV/F/E1y+El7wmIXq4bhf7FLfq/ofJ65vLpe19S1aGPfm7vf9eCQ+75b/9kRSp8yJ0laL3jvXa/8F9X+JzkieJeEzfCC/+el/Cg5eUvzf8svft12vSYW+BQL4CYHq/gQBK0d1x8YTu/hYEJLvj+DMLK5vwt71OnYRr0uBCHo7neiP3r3fjkLH/RsQiNRCIXNgIMKdp1oQjfxC2MX0M/fLfxuTXQi7u7v8MVi7n+5PBH3d5elfuJ6iV7rlrV5fQvsUsM/N6vFbozl/JV/L3PXaM/6vLz1U8lTYxF1iFn2SGPm+N/5MYh1vmoQr6vrxC/P8/z/P9/f3EffcN/4Sy/G/Lf338mCjr+J+CT435a5Pm+I+CT434n5viPgk+N+J+b4j4+AAAADtkGbAC/AKsIWCj0Ev36veqI8Z4i01tNa5a5aqWaoj6RH/V/k3ydDldqwIPqJ66wd4fWtIT+favkk5EMee4nvV6EKQivX9Vr+hyLyb5KfWv5a9ehNUB9wnzQjjP69XJXN3EWKJ8fWN5a91NXEr1cXXG67/A80brr/Re+Rer0Xvpe+S3/3E1Wr9/wjnYZhXmQY/OtURF6Iwl+b+/Qju4W7+o6t16QQvxPyot+gMpOgQevsBb63RO+Re+IXuoS6/BKXW+veF6L2vmV8QrriV6GX/G2KzevMu0vVj/hOid4Vr3novvL38MouWNRdKuDuidWghJg9fyI0vmVyqBj8X+SsbXpPXvDNH6GhC1ck1zfr6u6XES0IRiZGKTGMQr6Arn9i0XvCf5UT32raq4TXvKJ1xFa2OAgL4Y+IRO+IXr7/XugL5/0Nd4MwneWhXfJ0D319CqP3X1ovdC+1+Fl9L3cMX69XSxrs2WhPt0bpOT5f/tCOrtevH7wX/nk5f17rVqX6EtWq+8/r7Bn6/BRka/C1AQ8mE/YKX4uivXEzZOvDutqy/NXoY9dor3y3cEP2iPWC6iv3EavjlfV6r3YNgYdiff+ie6BDRfV6+k9fSneFDx/SybaJ70lqMxe8Mv7Q686/+fqG/0Jesv47wl8otYx4JSq/2iMdfy+n8vQJxN5WveJa94v4TwpxdcM1hPd9YQ+E8baCHnV4TFor+Nq9c/x6I3gRgr4IKv3DdaavWDUyL3gxCCKdZ8SiP869WqJ0nE1y/L8+NjZU8wIUTvgrhHnr69E9J3eL3ujvFPwLmSo4EIp32PiOvw4/AhBWrXx7RO61f5qxzrDr8u+W9tF/fov+wmDnb/58JiFafE/PP6P0T2CHqt73BGZV3xiIJ4x0BtGfMK7u7WuTwt+Twh674jwzp/44m8lX5Ncvk+T5KE/3eG/UPeDsGHgRQYb/hG4m68QiP54nEa9el6l7ttxMT8iM9WJz+hPVjvt/JFcI+DP4EQOwj1ilhDVS4KxNCOn+33rnq1VjoEWsVrterjfFUV6zBLp65ZMtFc8fXvCJvHmrJRnri4T6rmjOX7Vr6RxXq5EZz5F68OcYoMv1KoxQ0yxkVfW/xgJbvu+RHXdYpKte61/+v6pFRXJMFXEK62K+K+aCjf9E6+WXBF/V68Rd3d33UvVyVS9Q5dTjldoNPu+/V/tEeSvrm5FrELXc3PBb8R8Zd98GfxHy4JOv58GHELPg2wV/EfP8R8uDbBZ8R8/xHwY/EfP8R8fAAAADr0GbIC/AK8vidfwU8iDjyPk1KkRy/PJ6/rk7jPk7jO+bBjgh9C3vCHx2bSQzqul7uS+l7uSX1ef+6Rau6kEL4Pci9fiYY6R/zYQ//rXfJyesnVckxf/i//l18vxPQCh9T192CdIj+zfNr9X+bwbvELiF6iZDsMw79YvVpfoNdWMLL100vr6X3gl4om+N+X5+wFTWOeBgIvVxN3onvk+Re8pvZEWKsEOsnuEV6Feb5pBSzXo/qwn8+ZfonV68y+id/VApS90f8/k647Ra8I6GzzMrnJZ7BDVPfoneCur+DUvsvhYvxXxnxHxXYHX+iNfCG/f5YS4heviLf8+KxghfBKf9Fa+WuJRO8L/k+REciaA2hvqVF7r7DY3oEVE91r7rpbl9A/aGxdBsJ7X4YuI+K8HuvRTpEXz0qCXVy3m1y44lPr5FfXUWr6/rSk9Ce8Il8nyVivE5H/CXFfFUMRb1wkvpdtFbsK4nLrk+ZBB/S+1/1Kry8tcvy9zr3UR4LhXgsGeSi//XpO175by16sX8texxK94V7/hI7FqTBj7Az1bHdiu16MxfwzrZUKrwRu7tX+1f0WqhH5V77X/hYI9h7a8GX2F0V8coh4tlpfF+nVV9InVuvvK/l8TXvloWxnoR4+hCCN11xM3PEL4iXiURjsCKL9OTi/ArAp8cJRX60R7474WRXxk4wzznwYojvhGt0R75f175fbVvm8tey//0/4Uq6rlx+LuGLoCdR29FRH+I6BZBFvdj0EPhD4Q8KfiOvwh3etclcR4Vr/wzV64/5621fqulX9aav7P4SCfiCIvU/4Sv60br1l4m/Qu0XgYOvA7m+IqgIK+JQx5OEPjPBiFPk+I8bRe/Xv1fsDfxRL91fGS+b9G/0EfQn1/q/jNF//Re9r2t/wrzxFxt5q1+rAj+gR1VVYrpDHrVf45b+mrxHovVhleLo/dAx9a9Lhv1q51E+HAj4rYonwmIXvRqwcBOFq8cjtemvpZv5aEd+vUvpfklyd6FOfXyG7uhipZfa5UvCIlH6vXMdCqO/zL6+NrmXqxWXpXLwj8LmoYqPK+eCLJ++wideRLpSqkxj8OdfrfXExRt7wgpCOW2kl9cTBEiRzwehjwIx1i8E4QvHbvkrugIPwSivmgxy/ClevCn2eNsCN6+pMUriOLgp0lf6V6tKr1/XderTV1XVe/0XpPgwzOcQs3fd/cT8GPxHzYKOv4gQs+DbBV8T8/yiIZv5cG2Cv4n5/iPgw+J+f4j4+AAAAPgQZtAL8AqohaELN6BM0i+Jgp5Inln6Ql69HfqIxxOvk8HdbL5+gPf7rlV/4JvXp9qXAqfAvaEIxciF+XXzr1ZEr/J9VU1UxHXJUIovdfX6L8sLeivL6P1ev4r0O75lf5F7EL8i9iifk9E+asDP2v165/ibwMNe8DC+uLrR/1cNr1HYZhH0FumHL/H1o3TZUvdQhXNfF+B3r3xKLljifeC34Jv6J3QCBL110vfS90wl+vexCL3gnyfXCMFL+kRvivilc8tW6HivLX3hGreF/hmj94er1DEfLwLKRO8bXL0b4joMJfHYV9aJ6sL0Rzwr+MRO6Aj/i0X1YL/gr+Dn8IdevhwEW7vvCYwn18ci1iFute+OxCKrzfmkyZ8Hp/DJ+wKI/vRO+N+J+J8TxxPvCAS+T5EbvJX3QRr3YT9n969396G+7nQju9e7v9fS4Ofgn/BnDHNNhLfo/S+hV/r6rqqlfd969L698TT/xCnz2vfKvfonV69+vfKj+vJ8tfVlyYR7/hHpe+KrisYhd+wFulel7+CP4ZUmsX1XYsZquqnXev/C+sC8Nqvwh8JfHfGfFZNLW+i9432Btr3d9rb/hIYxPkTwe7oEPv8IYwv0EeGcvfkL5aFf8I5OXwUD/j/F6soe8OBz4bQlK1xdbaFd91z/L8sx3hXesJY/hLxNDWOlrcEQpV3vI6wi/noYtKuFAnXEr+uF/Y7wiHvBODNCXVyeqN+tFvl1/eE1+hPQtTy0E93Hxnq9ddAWi4xEEA9H/GMzvriOgbAn+Iqm/Givm8MmrGdfoveP12vT9r46gp8MfL+GYRq0Xvibvia0W3j6IxP2J1VVXa4nxiIDpY/iRAJCKu/y3xHUyv1+Zddcy94f1nzZtL+60dzx2tBXwQgiha+EfRHrkv6HENi9NeuqV/Rt//IjzeGxVWBR9139m9+KJdDEUmZMvq94Yr15w17PXPCvr0b0pVVQmjP9b+r6qwJHwVH+W8I1y/BH3d/1rfEf6++177XpMzR2qnVOkOQlmmRMK/YQrifnq4fhW+bnQrpfXpctfVQKfgh3hL4NirlriQ5XPrhcDWCBexiJY1wwDgMu7/DwoEN34uwJoQr16ItetDc3cKfDHglFfEXU8M/F5qEfvv0/uvrDFe/X1dIz5f/1i8IVivdXk9XxxN+p8Qvy/LJxavjlsXerYpCYa+Jydfr16r/2pPRq8EmffqWGC//wr8T8V8lzT9TXeIXu8QhTOIX7+/vu/v77vv+1eF/vCH+X4v58+vlxnyZ8EHELPYMsLfE/ngnivmz7+f4j5b4X+FPifn+I+HPhT4n5/iPj4AAAAP9QZtgL8ArC+KiMCDhcYgsTPx3r+N5a5a5cQslxHeif7m7+r7VXlwI/0JV/n1/88EmO3tVyfJjkTeI5cYvKl8qL1CFkvVjv61/pfvlV/QnqJX/yQpxEtTRmiUv75pMG/5u4QlL/F+uXxKJ3y3xK9v/Xy45dd31a91J1EdfWjt8QrGuuTCr8FLX/wjnYZhn0FOvHVqbEfHauZEl89cmMRL9xy919xC91C3X8R2C/1F1xPxPxPQE+i36/lriOn60bvu1/WC0Rr+Fea/R+j9Vefm/Vugcn1U/jifeF9jibdQnjJ3MyvQCrqZvAg18egwvfoneDkR4N638P1r9ZVYCbCOr/4r4rwUiUbrwR9f3hDCHNiEeb17EL1HVxK94rNnorVtrlMIRCfsT4Iq94R/Oje8IuueuT0Gl79e+Vekwy/CO8/oC+GeubCqhzgwl9C2l9Gv+LJRu5aI7e/kRmK5ETK9v5Snd9dr750X3xPxOv+gOZuv4mXNRmkytDfeEKJ1evSYr438DbCS5oUQ3phxCXjF/fJXXU1dmGO+n9onfKvT4Eb3EeCihLeGK1JiPQK31at0698/lq0z/hMQhMZui+ny/COqwUDq1VVV7rupUR69f+G/xPz+Fh6Fu3ifWQIeKq/hEP9ArCOq9G75eqXuqXupbwjk20Xs7wzj8cvquO11J4J6I9L40tV+GRtjFV/hHwSUVOnf8QidiCV4RD2NizRyd8Fmi/f8y/QrvCvy6xIf+H4R9ehXhSQYjim/tq/hL4SCysYxGtiiRHrCnwh89Xrk+Iy//r3iRC9WGaK9+r9Bd3zIn/R/AjcQqvh7f8MVOi9JxdXo7RC4uLra+jVXr5EIv4EMV4fL4Ziu7tNb5vPvJRudLDYrwr6B/8Vva8L0Nc8LUR/1/+v7wR5X/DFd4Vy+va9JeiOSKxHw+MRO+ZH95aplzevoR6/TVz5LGYVqlS9Xrhn2E6xOn8fCPLCGnr8EVSFPLotGik9CPnyd+MUhHPIuwESQEZd3fHEjvk78/if4KDvd93z+GPyeV+J1Wr1X0EEhPfq1LitETJ5fYG33CXdr3er3guOhnQ9moW/oT/foR7widH7w+et16+boCM0fvAoPXGgg4xEfL4QRL/CHxS06v5Hd/yrlVSr36/6dX7nX/f1P3or+DJdpI+b4jEL8V0BPFdX19clRKHPDfLN6Evf0KQhS96rW7te+Vf16v+iv3Eq/VK9ev/nkELJVyiFh3l+RFeJX/ok1dVdVdcvQf1f2vUTIKIYeZMQi4hcQs1avV+X/+Cu+T77QSeXv7sQq+5O/v7+4MPkr8R/mwXdfz4LvYEHPguwWfP8/xAiC2XBdgt+f5/ifgx+f5/ifjoAAABBlBm4AvwCrCFnsBg++CbwSBJV2L5JPQx/kn5a5e4mbkk5viLv+TuTvV/l6iYU9FeXDm8VQm5Pit8lcknJ8nyTfYhcQt+hX/dX7A80Vj5L5F6hC1fiieonuEUI/DJf/0P/FZqN3peq91Xt/XU3yfyeje+aQYrmX86vr5VfuFfn+JROu9F75P0fr5Fe6jars7DMMDkEpU3+rk3qdIj0Kf5cYtyuT5PpXPqXi/nuwET717oDX61i7dZV69+vfS9WCP/4Ce1fC4pFjfRWl9fVxXy5f+aKRu1/4ZfheveCEevdgT/f4vk9X/0evhkEnd8vAg/Aj1y+GKr6L6+uuKQhvhD4QVz4QlS9IvdAbcPYrJ6L09xEi+XWLhn7EyZx/iH0AgwUYhap0KfoK+h/p+volFbrR26vqVGbr6iUTuvqpCel/6F9tfQUlCVx1+gj0vFVXvBFtDWi+X77m+vk//QU9JpVgjHUlvXvvpe45e7RARXf7vWLSfrF1KsbrRXOtFbpV7wbDl6uXwj7A1+9e8K9/wmMRdfFXYE8VT30fqx/54jJq6BOO3d36rqro3VelXmu++WXAwBFX8DF8CEX4613PJyr68temfwEHCotBOlXAg73Qjqsbuj/0W8+NmEO/8Efd/f1gzF3/Us+Dkar+N1l4vGUEdXon94OQmq9Nyr3xNYnb/hPi7v70V+9Ff017FE9QjF8JEM7/OFepa4jwz+VEY8Ilv1f9X+1foHQLfC3x1XxxL9XMr+GwtjYs0TvPAi9foQ/yr+uZf9BP1onSc/yovfH53hHif5r65OuMxPX9ZfgQ/Xl8FlDwQdF++EAQkd7t83zdav1q/690P9aN3t/N4VN4uhL+F/QI/ivYCTBTVfXJ2idVQQ9weoT3wYwj61XJPz3n/orxHRCLX5PRDEVf19GqvGKOM0q4EsZTxfk5kIfr7CdX8X+ZFi8P17y6xXOQq7O+y8Yiq519hv39r3onVhYTQonX8NevVz3jqEvT60bGS5d0jS8s3J4RN4n9L3yr1er3hHWGPiF91jKvWf4fCXQHPDF6vYpcYti/RXxbI7X4IdVX0j+0Mc+5LA6NYsYpcyk8WXd93+CPu+Sr6mRVwJwRR3+S/Rv/r3QZEyVSE106pkn/4IX5/i/QPTQ7ev4vDJ/D5fpfVT9a+vD3wM1YvBFBJvcZXjEZ8x4GUECxvAR4IvECFi3+vXl9Ahq/gl9d83sYhb+Cc1CFiOVDuhz0JefvqW+0I6bl8EmlxfdxKK8g5bdcl0r9eKRaFL8QjPdaFsYha4n4hCHhz0d5+465av+/0Kf5bpZ6+pp7kRXgk5LXJ/f33c/0MQQtXav9931wafJm/xHzYIuv58EH+dbg+wS/ebfxHz/EfLg0wTfN8R8/xHwV/N8R8/xHx8AAAA9JBm6AvwCmL4uIXxkXgIHBJ6Cn4jki+VDn+X5b5K5OojricP4d9BHxa/vEV69KXk+kM76XvarkvArcQr7ie/5VfELYhZbhCZXxPgp1xKuQ5hjCFxndd6xXzXX1Fr1L/4nqNXvl/ksN0eLv7/mVjvven/DPJ0Fv9ehP4pc2hHX6J3ydd8i9iiegQ7X+KXHE+6Au/Bf8K+gO/rocSJ/3UIeKEr1a6/Re1/QhbfwjC/N9fS9In3Ql69fTYWzdSYV3QK9eCjd7vkTFKz4Eer/DSI3ixElAbfgn+6Ed7r3ia9+vzwj1/2B3yP+FBCKvipfvCuNGKI57GLi8Go/sDSF+5OxBe/oeL8P17X+v64iupcv2gSCdVd4bF+CMI+6Gd5a9QonoGPrp/mFLWFKjq4SoQgjX68FvOhsRk0/qTBLq9BRqu+9fdLL/6+PtWP16vWKuXz5Mf8J9efVBn4R+EeLYr0KdoLuSYTq1YTx2lWHvX3L3L4QaHPVfU/X1q/xOv/n7DnwWfBcEvAmBrwll5fhFFf43x9X61b9fUOff4HtDuhQQgy87E3YIffXHVideiciPiesK+/7+5ep+5+rQS75JLEgp9j/DlC37+tYq9f7wIIMY/X/QMzo3dav1yVE9T9dCidfwrgQfXddYS1QvXobHnoLAw8MhOsEH4iqDCQxjr6CHxlX1xP1CPUT2BmDfg+F9avY4lXrAitHyr1cvBIIk5ZFg7wjC/Pd3H7EezqzX6vjFJ28GQQ8EzJveEMGX5Mv22+QV1BB0CAR3VehD93fCHQFP4IvhJ+Evwhr9FSolBvVLa4R/glhXifmutF6f1/EY/WDJq+MUPR5a+vBOTW1OjMXydH/EU+nrDIisiRX8h1fxHFP0Hw2i/riZl+v74EWGRSmwqwa8WLVdVWTwRhBVVSpN9+hD/r01a98lYNQxXL4n56GyoW51L44kTxGK0/6sxC1mzcVDIxFxzGIkyi/V5/RveJ/qVZdySd+BdfzlNu/Qn56S8Lo7ZfIN4YjvBCFq7ri5BcSb5IPA5Ay+ZEfHEK7YghDd6XnGfNfHw5s/xMRl+F30BB9BbdaLl4MvgI4Sva4+OX2uFQO6Rsx4GEESJc8BHgkXLwQYiom60LehCI8v//gxN5TQ56vNXXE369b09E6vRuvJ60Lva6/i64uqDuXl70R8Qp719P1r/v+WuSe54Jq7fJV+rycqvr5VTrQSr3yxFdXLKKWblXqOw7BJ90Czdcfd/fc+IWX4K/m+XCH+bBN1/FfLguwTfWFsnz/P8T8mC7BP83z/P8T8FfzfP8/xPx0AAAAPuQZvAL8ArAhYgQuvi4I/QScr0b93Jq/v0b8q/rl7iS938qJ09xHUZ19x3eCQXe7u55MC38Cz8F/e/D6/r0d5r5vQzvkl+WpZKfrq9HfHE7dTXy+TeDChDQrzSvm0P6OvQjq4hX7ivmV/Wi/Edev0Tr/qXEKeni1756X/gZddddcqP+b64lf9wSwrzL+IHEPRdJ6J79fWubxxMd1dV6M83r3j/hfXGqdK5/BOvDpflXLoCX7ATen7KvXj/zK/xHxHQO9cTDg5H+v0fNXq8T9c14JS9A5XXVAh0/0bqGynszK+BZrl4bCC94JRnivlVWAoX31hOhiZcI/BP8N6x3wZeo6GeZCenxRf0X3m/NE9/KjN2B1aL7y+jnXvCZZefXC01ehXpfXuzaoDKEUJyugI49COl3+CSEeKrhKJ9BHKR9KidJ5d6fEUbq6rkQzxb+XqXqf7R/V2rfE1hmr65/w/+eReFPQI/X19WilToE/ovouqBrhcQj2MRddRWT0v/7BDsv99r3YT/PO72vtjNz4TLk5aoPjZcQJqgRC/DXoLBCep17qJ+WY7wlxMmDH2Bb4oguS1rEYjCMxHvrwehnqIRHK3BITVXksIetek7XvnrDgnv6K+oaxsW3pX4RWLX/ujPrrXpFXr3yonVxKL3i3XDcIruGcQtcfXz0fXoXmnX9YnfIhj9AXQqr9KCHu7eQvz3xPovgkGo73ehD5f/6GRIyveCsEiua/v0T9OuKk9e917434MUM6FLj6+auK4QQRaRfeIU1NAiCHg0GLfWGhMYrtdPiiEVYU+qv6NfCF7Ni2Xf3V/dXxipJl76jpeVG7EK10E4X+X0fv4pcWw+CIq1V/IQEZFVbvk+vAjcYiGx/AjjOgJfWGyyrl4Jfzq/0iPXq9Ve+bXq4lH6s+TC+rBv/X/3+v/M1esFPwT/grhQYt6ELN6L36K96aN2XyfpWlsEjN3cnNV/Xr/ohepfkQp9/VJb6wYhT5UJ74noF+tCL5Ku6wpr0X9CyEv4MQSQlzxPPr/+T16vBFqv0noV1fJy6+eXZfwUC3d3d3cyKvEAhu7u/iK9JUT19Dvkz40KeJEefCvP+rzjFvVP3o/Xy/oR33S+197ovvDbrdEboL9provd14aoreBA+DASCQl7mRVGIjmTwEyCRErwFiCbwEmCpe8IazVfq1e60V+tel5UNYxiFK5WP3XdRME9zyLq+5ETq9Y9VfV7X5RRN9q82Cr1NV/fBJiv6K/tzejfrdXqrXP3zfKIU+a1eqvvyfv/oW/fXszvl9EeDD5uIxCy9xHf39wZXxnzYKuIWfBhgu+M+I+XBhgv+M+I+DT4z4j4+AAAA/xBm+AvwClr4mMELBjUkUv5bie+X0Gn+Tf6vfNYhEd4MfxMI+hb16I8Y/4u4jv762oivrRv9avjF9J6K/6sfN/Ngx1UIwp0jvH0IxF6Fd1r/3XqHEr/4ibA469e1+sVWDPX30j/+T4hXuolevhOEeauZXhCtXieTFEIuwMPv6hbwv1/dQ2uVUN9fgu+J1QCTrHKHEif7wivkra6hD9FKlf6E/EwlzSevT+hMeSpETq9WiKhL6RO7F+/v70Su4usM6XBDoSxWCgixrzpe+l7oOV7rROrH/BOfwq0bvDPyiPBb8KUXuojy4JuSuIXpcGusZrFa49W+dW9ifv4i8frtE75174v9CXvG/pCG/UqvjF6uEUJ9XBMgh0L31QGXWPoM9J69PYQ9SGCRbLfrRsx9SVL9+n4T+VoX79fef8+/1eRfF9R3Ul56N3y+Fwihb+epUZcNj/D4X8K5B7GCPbe/hHpC2+OoQhdCF+b4qsX9KI1kvu5vk3+hj9fy/OiP8t9r1adXCfg0FdAgXgQO74hHf9EKn2pU19r/9e9te+e+F/LrnRezvCqwe+v8L/6xGMwQtXPy3v3qzy/bBQTVdVfru9f9Sq+OVp69X+1fw/8CV17d4T+JD6Ev6fy+XXoR75F9MX//4FGEhiE+l+I9Hjz0IBFk9eBb9Vf4tGf5fkRGN1sZXYJO794h3sT7PWDAI9h4GdYSqx1q/ixPg1or+gdfD8mKojH6+LGIhKdJwYwl6H/xiFWkFLE+hLzcRXEIz/V19/hqKu7u734TCTvf4jqO8LG6tXK5KrriOmC5e+BRqg7V69E/Xr/9f1VyP+GPiNKbUFgvVVXWqvVBP1gkIq7/KrMYok4lV8d/FSZtcR8l4LxCN3hPWFuLf3X4zVaP/p1Y8d+eTnp/wmIWhi+sYur9F/N4Iiar0R1EcqEdJWsuwESHEJrul68TV/EUXvJxxCbUO7l6or44m3Qbr17CW/4X5a6ROk9Ff217zUTq9G9T8sEfVY5+pVnjc9/2Um718Tr9fmv1fXXr4spd34Xrn9Dlr5eze5V7v71fvV+/v8lHaTDfqDe8oi33CMM/E+hHeiydL7w78Lq34OPgWhPgeKO+uLC4QxC64Yn1w5fhQQjP+vjy16W/vR/1cdVJ0IX5vHmlf8M4NM+b6f9d/aN3p1WuXYW1iKL2//CHXJ9aJH6tWImo5X6ra9dRFikWSgEvkdLo7+DDDmarlYiv/0R7r+RXiK7qW+W8KUZ69Xupe9X6n61eW1lv6eH/V76vqfeuT6+qX/y0IX4jX+v+r+7rgq+s+L+QZEe8Hevv6wj/nwRf58GGH/zwTxnz/fyfEfLgywW/P9/J8R8GXz/fyfEfHwAAAPGQZoAL8AqohZBC6vhCd4IOw0ldwV1J19PIv/ll5USP9zcnURVfyXg1+Bb/P8sK+hLxT/n0ruIkqq5Jria76nQh7EKluK/kHEO9upl6/rlRPwrywn6L36+rm9r/5Pkrk31o3ScT+r+B/XgWfYBAaxeBR0MV71Uy9dRXxHgx9d1G/GwlzSr4qfVDekX9ZK9K/0IeqruK+Ve9k+qy17wzXviF6qhdct8a/U692Dz2EvfJ3uqhBcvkqo5ek4nfzQvzd83oXmu6Xvbifrmrk+EPE0O6l4Tova/9tF1jUc+UccYqnTr6L7rvQju9cvBuvBmXwZnV/DdE7oCSVYtdRS+9kXq4lek4xehMYQvrELCn1QGkf0HKK/X0IfRvVdaENWF98yvVjzL3gYqJ3YRr1clL9D3Ogz6i53/CvNQhbsDLkeM8XUkl/X2H6Hd3+CjXaL3UK/LrrV/Akm71elUqr3h7VgvCnp/LLt+Ir1v9CuhJfCXcJIJ994xF1XMvVhP0sdyIIPOkp+W4IbwEcEegbfBdQt+yhpapVhGjd9gk6r1P+Jf8I+idi2PJh0+PmrjS/+DGyPevROrO1etUZ+v9fyer/L5fsX4IAv8Shr/EIj+T0EAx8EaKVbwSfCn5a9Cu/XpRxD/Y4n74EuExCy1orVX8T3H36Lmn4jxIdVnjdVIhDHyeBHCvhcvhMSsXhHJz9gUgf1VyYs3wUeGQR1zq58/iq/81E79e8jXqy6wa/g3hWp0XptYz1f2/O/i/1e8GDFb3vfwoCW7u73fx8dVw30CJ9311XWEc44lO3jPQfr/rRPEM1c/0X/fQ3lWxOIzFEa1VfnV8iEPri5DVX4EkV0BDFdfV/P1P3o3/hCq96xCueDUIXl3iHWcMyVq94Wwm/0JYjcvo1H+X4JBWquS5cleOQr2IV4hbr6uTBGEvN8uTECJs+rB+/aQTfz/CYURugj1BDVfkRcmJ5fzG3fmXgQQkCQr3djeCEMRyxfKspN1f0N+RF/5OtdFe6hFU6Zf19E6uMgiqde/V3k3iWieOhde8tek5F98yLF5n+CTe9/AwCVvjFFdfGI1/AY4JPipOX4nuNXqrrZKv8CgbsDHQlqwv8/w3h7llrk9CveqtfaJ18qE94YfhLS/rv7RP92r16/qvrV5OWu0LyVMYiO3ySCF6i8QjnIgloKUK7q4u9Eft0V/n7B/VjuV3ffq8TfNpwUfXf3ECEEH8td4hfv7+/v7+/Bw4MvrGf4n5cNdfz4KOv4Lv8Zk+f5/iPlwdYLfn+f4j4Mvn+f4j4+AAAAD+kGaIC/AKcvjdfzr4yhCwX+gx0nJEeKtNe7xiM7fLikR/LXLJyI/da983ydAX/ySYEnr/wZ/lhV9aE9+r16/nf83r17SEfrkRH7iu7qwYBCnxGsV8qK93GouVcuvlveqiJ64KfXrpJG75etX6+q+b+X1fv6+u8H/oBc/lu4U6jPZEd+oQut3fC969XNGWbEiFk9G7XxC9r/45areuJ8EK8FuvR/dARPX11yeWid9L6uZe6+vvRap/w56P36x5fXorX5kZzoCKfr6Eeievwql7wRjfkRe3+i38HYJESLwShhfSV9fV1QENoR3xWOJ9r4SXute8EWuJ3/CPEI/RHCS1JisT6K9XGIUVPmvvr6fwRap179feVr16GLFVRKvXJ7XX1a+7BGttehL9gWz9xfc6EN399Yyi9T/QzoR4hDejO4zr6Qpj68n9F9+vv1b7+1751a/XvhGTte+XwgSMf4oQta1hb0GWqgvk2/ar0Tonq/Qx629c8kvrypcbQ5WrH2ipVweGRe61fwSb9Curtfa4nRe+L89elO8JdoX14I+efwKOT0T369FYR65ANPX6FMVnku/p5e0Z+ouu1/WCoJ/F/CPxfQW+QKY2PN9BL8M+FNUBFH9aGd8lc8nF/Alo3Qj6E9jEL9dATcg4n03osed+Bm+Bmsju9Vd4dKhD+Csb5zq1d/q/xeMWkXj/BIEfJrPXvkX+IX4LPD9Hf2Pqg18mSolCOvm+C2FfRYojtF6JXwtW/URXFq5r9X6mV/DUm96wuHQiEPa8Vri0RzyauE/m+bwRmmrV/tXrkV74lE7GLKn2vZf/4TEIS6+uSrnm4iIxK6BC74hCHxCjnaApivn/d37/V65K9f/r/9E74jwRiKoF/rRerEL5L7V9fyYTJ4J6P2dhBwjzoJxSfIOWmQh9Zq1U3xNI8lRfgie/0bvBOKRekqboR67EKlq6xh/GfL8aF4W9exCLF5Pz5f/tE7y0ZvL8I1r6RIpfXqXc6v1Kr4xRactfG68M/A+g48La7XpsNLyUPTNCkZ2chRed0+cUr/NDHP883PNyoUx4lorafiUXLwUnrtE77XrzNHy6AwJdeBmOuzXCICbDyJFjER68BsgsX50DkFHhGvVSrl1qdK7V5a8QhPU/zYhfir7hn437u+p6q0IyRLJRe1yaJ3stYPK+PBJ8DgGdc8uufrkkrV8ctjulfvV+pUV5auHF11lq8Xup0vku3XP2yIjy1LKOJV7Xxt4EjEfDvxnXVTUCxo3d2vVyfJIn/EL1/LfL8vUvX9zd/L9w3/hrF/LiMv0I/E+uT6wTdfxXy4JsEnyYjN8nyfJ8T8mDDBL8V8nyfJ8T8FPxXyfJ8nxPx0AAAPYQZpAL8AqAxAqsTiFil8SgixBR6v8klzIj9yq8Rge/6tXLJyVSEIv/m1zT/JJy1cIozw16CLyv+I9COiOkI6a42rif16WpkXu4q/RekEIz6hHr64V9De/V/1eJ9e/Xouojr60M7HErr9Sp8yxdAjy8vxK98q/6A++uhyl28nSOVPrVci9d8Ffr11onY4n3Uy9pf9k861v9A52MJd/BXxRPX1ovdg1r3f3o3dsSvd/tfJWX0D/JwjDvofmr1aOoG57sCq8n7f/19fhlUOISZPCPwiKq/uI71y7FexgjwYiUZ/H17XJN8Z8VpeToI/DPwnXoZqIhG4zvWL9Xqp0VvDIV9i1b3ROqj+j177xxM1l/iv+RXK5kbu/vXu/v8Tp+oJB+qplwRj/BKFUK7wah3Xiul9e617on4eRqhTiEJ6WgrrD7Q+pPWxEdIJd+jPdRC99fdej9+vvbX1c9cf8SvfJ+r4hT5sCF8BAHpfP+id5y6//Q33iS3QR9BP0Ee19DuhTipa//Jjd0XKS4iTlrlXrL//8b89YKvX4eHdQh19axT1o/dCa9i3Xv0M9CYxBXU1/hSrRuEeuYC3Qh9cgJPpa6nV/spNV11dS7av+r/Eor+DALo/SjcO+K3wQ/fyoR3k3yVyL30veBB/Aowz2hfVuvSei5k/EeEPYLvZtciHJV5CVXXZru7r1f5ZNFR/+T3Cd5At4Ja94f/Cd9L/sHpO++J90bv174L4eHMWtv1/PwhVe/65fBTrFfQoEpHd3d3fkXhCn4c+Iav+r1f4RoQ9c3hei9QtlGky6TlvRUR6rXvnhP0Xo2wziHmhEJgiKqrv4RXzBMRu+76iOgZVbwISxiqlXBmI8Wf56oX67wyEpLA7hCtLxFXxbu09BP19V8v4JDPfXiMOX42G4AIIa0p8VscQNSJQ5VeTIWuT6X9PP5aDoR7Aj56CbvGfEfPzsYfhP0F/0IWKyVe/BPMxVardLX390h3dSL3WvddcoIy7u1L4vX+v9eN+BhBAhPfrXsQiddCvQz2GM2X9IS57VcML3n/EQz6EP1orxPfp+Ezr1YMyrVddhWvav17oXXukkV9YwWBA+B4Ku3gVDAlu93d3IjqMRC4ZRrgmhHwP4JOv0X9G7qdTpNX1MhffEdzdTVzfNBB6/n6Rurte7W6BEkRuglX3Usi/91euXqfqfu17rV4q/rgtqly60TLrRcpL1fu/krlrZ/knGIpyL3f2sg5bXfXLXJBP/fXd3Xff/L8v3B3/hD/MI6+bBB1/Pgw4hZ8HGCv58E2I+I+XBtgs+I+f4j4MfiPn+I+PgAAAD4EGaYC/AKGvkil8bGr4jwETvAQOC/kiLi65fl+WTarmr0Gn+T5JcC3quHn/F+vquZE7v6perm+S717/5VeQQsnor9x3fb65eWCfSlqq5P65ARXfe7q6ja4v4te9Cdf1f3Iid1VdI/TcIoQ8KcyFvDHy8R4V6/3smjdXE1z+CmvdgLcV3ovvAg+gPv4/6Ru6r5F7qEl79Sp4f63G4e5qodi3xPb/vLVvhCsTXvLXugS0Xuu8CT8MkR8vjpMQ/B313+/hl+H9clYJ/hP80Jeiem5EcqSWFqtFl/+RGe+T+sEYnwufw+P7Avhfz656wqvivhb2S+SfE/iP0b3i9YV/C0MYO8i8E+/Q/p/Qy8l0hDyUn+j+71audem27qZX1Xr3y/o3fL4Ro/vn8PifDI/9F7z79CvQlxCC8ViFqwIfw9hG0uqQSe/X/VK/y1yoj3YKw33or99cqLGOwRfBh+bwVVf4kEfVe+Ul36/ROvZfiLwj90fs3w/9hwVIz71lhLDwmMQT1Vg91/whHYK2Yjv/Ibd1hnb398uiPL6veU/kJ4Ng2hb9wurnSPVa9WCCr/r+Tn+WvRmrCffwZoR0P+gvHT8QjP8TvtavriPDouvQpySoT+1foCACnwx8Jb4rw6TwW/CITkoEe+W+Jy/+DrCPHxueh7xO5SLXuGPiER91/y1yeb44gKrvd3d3e7exldq/Wr9DKv5f6M/zfFfEeX5Phyj/82uIxikIudfWvda/vnrB1Qjodz0E68ziNH8IjPlryit3+iJV4hU64s3hNV2rnhR/J2L9dc3koneD0IeFaE9JiPiuv1f7RX8oX6+tE/4z+v+wW16n8H0Jc8RzyYj0IoSxXgnMtda+lzQlVcpGci18xHtNCal+kR7rXr5EJ6vUqvlROvI0V6oHfoI1foG4eRc51a/v1/4Q+EO/4VELJ6vL3L4IxSr95d8qI/38/zojnX4E7pb8cijvrGMV8ryl8sxd34GEGC94GcFW//k878fV75/hZCX8U179X8gc+1a86y///HfGIj7/hUQiy88mtZvyyYORK3/vEaWuuvAmid+EOX8EXiPAgSXfjEQKPr+DsNIkXgJ0FC98/UvhH4bq96eKVSVFUv8chOugP+i//12hD4xbw76E/rX9f1pqlZNObHNG6nUkngg+6JF4LvcSvX6/7jevHE3/V8Utdq/Vqx1yXwRYa1yxHd1r3XIlk5Ln71fHK1bq757wL3rgr+TVXL+8EXu5fmEL3Gy9/fVxHf3BD9Z8v3jv8t+I/Bf/mwWdfz4Jv8E34iH5vrCWK+I+I+XBVgn+M+I+I+Cz4z4j4j4+AAAADsUGagC/AKyIWYQgWPELBZ6HvJ0vSeit86M/z1y2MW8lRXV9x3ft/3xHXaK3gedcqI3fDz/iuRXiy//or92vVy/Or/LS+JxC/q/zLl3/PMIXwMOG/Q28Ieh3sQtevfr1+vvC/w//Xu/uJqovrXLrr1vfLVRF2AgcnEwW+vviOoQXuh//9eocQvfrV65fBTXKsGPwdm6A8+vq79e9qsE/w/3+vVXCvovROlF4Ka9dRnv83sVXHeE94fa9Q1TYlXDJ0VjoDCOXLy+mEOmI6rpepep+voR60KeuauaCniPiF7qI67wyEfDIT8Il6BSE6HEr77XrHEKamXUZ8UhHVWvdX1r3UvUvX19fX5/jev0XvBP6guhUQhMuCXGrr7so4tlv3/P1qx1/KvTYVo/fEr1UBD/J9r/dcTjFaj+BoXn+L0lb+rZN30Lovuu9V7z/de38C1CN0vR2KoXUX8voIdfLXLWhVVCvgQD+Poa3n1iNZP2QU779CfVififj3v9DO8RhIQgn4O8J+CsVu7vu+3g1lu/wQ1c3/S+WS5ETupV/6r/5Vf4n4nwJAZ6AgAh8cHd5ehfVsMLXRGi/+E0Tt9Rfy33+hHfa98Tb8SBbzsPwl2gh0u69P65T3DH4Ib394W9Dt4Z6wchd+gJYXrn1y/zy4zT4zrhDwmEEZ976//X+IX5UR65d/LfP8vg2DsJcTXaOVISbXoj7/vG+/GIou9YhIj7zVBPd3d3v9vgkZGR71QsyvWM1ze0veBLBVWCcy9WET+Nor+Efh38IxHCcMYby+hPV6vPs4jVVVV8Km1/WIXgXn8Qhz+CUR4IVfEdfgmf6/+RXkw+IkFELWFfh032iv+v5eWE/X83r0ev5q7uNQp6rXvCHxGny6LmOtHl4Z3xdaCi9QombEccTrwV/gQoc4lel50TMa/RcxN8nL4OnXaEX8DLW+MJCtaL6wUiFzHgZwRIuXgTwQdAL0HHWvecR99AlS9Ect4n8d+i9Dvov79Xv0K6vRWpfOve6J6/R83uvtcy/MveBAa94HisXwgCW77vkWYxGfP4DxBRLWry3q+ORcVZNcnzK3hk2uFv7V654b0W9Uf9+v60v0M6X16quTlrBNrn61/Jqr1y9S9djkL5ir65r50KeCXHfCFCa1ovJWhHVbSK8Ry/F/EozGv1f4vHLaUcTfvgt+Z/f34Nn938ghcQvcX39/fiF+8Qgguu/iO/vXEAqwRfGfiIuPv8E3ELPgqwR/D/y4KsEnw/8FPw/8fAAAA7RBmqAvwCsCFrAt518TBSMQa9XIiMVydyRFxNcvyrFJyVyY4hdVqry88ED/jKpG79eu4ifiV75V/8qK9cstRCv83cd3ycSrw56F+hLkupOtDO6175likrV75VfXy6/V/Ag1euREnrSr0JfqO+ZWKqT24U5in3c/NCHonihC1yXujdWH/j9V/E+CvjiFu7AW5F75l6sHf2N6AQYnoFmqiviPHpe+K19/J88K82IWEfW/cSvdAQfXQxWurde6Aliel67y17wzrhlHy8C3UzfDXhYV8VP6N8+lKrwUi+wNPuL70SKGvQnsQtL4pCXil4MKI11GeB79wghDnc/YCrH9Wjv4a9deiRfr3n/CK94Yr3xHoMfE1pyZaJ7xtF9WCE6y8v4mTggzsMwjxUZtod0Xc1X+ioJdV/UqL3y/r7wi6xf4pfeGdYrWR/LLyonVz+WhPeN+P+f5+/gQs7DMI8Rr4pBBrGISO+Mk2LUZUnX1XdILP+v7q16vRPfL9r3yr3y36OlXBgEe/so7v8FQpX8Mhc3Vfgj6r1cyN1UBTFyj3E/79azsEcK4NcuLSHX81a/XomsEgi7u2/BDRHJF6Tu/2Wu5/RP/P86K/gkDKE91SJ3X4Wr/474MVe+75b5fCPfg+BjClQv1NLaF36P0Uv1rw576GIQLv8yI/h06K9+jPLUP+CwM+T031yY0CgCIXWrPhOTmRH+1757599QIMMVOhPX69Fv4WzyBMeVx+1/895pDO/fDh4Ib3t+r1hQnQwRawtVXrIasZrHdfz86veD5wzzoS1evScyt8k23XJ0hHX44RjEKEHH8LpX8EPw+qwhrFDete+K7Ba+whXvhjwiI7Au5Mb8IOhCPdCydfXVcN3yXo7HyRF/ciCD9gm9guMrHU0gpXeEvxXhLXCXuhfdjq94wMondgVff3orycJfor9audF9g3Hq52/ft+BIhXlm9G6n8ehuUvoV6/Ruv0Qqdh/11XVa5eDZ/PWAjwp55u78DeCRH7wNILPAuhzyap0TvipRcXeTzd30H/VL3X1w5a16O83aHOKw+dUVjXWizV0hHfaL7sI+y+xXwVV94MO/BJ8DMfHKzv8Vr+8OUbveqHZeEeur7L//DoxCb38Rt32hXX69VP0GH10sHjLRXxyisid6/6HC1frV+m1fqXrV+vri+SHuWv7DWI5F8d8la9dcTXXIry4cwcfE8319UIXELiFg5+xH43/NrL94IPfPggwW/L8X8vy4IMF3y/F/L8Gfy/F/L8fAAAAOTQZrAL8Ao4hYpfFwf1oPPNcTXLfc2G/hsnzfEWKXwIPuEYWfzIW0S/4/avkk5UKf++9fEr3yr1+v6+TkkvVoU9DedBrm9pCu9198lYX333H/PfL4P/QCR36vKvqr+tWhL0d4b5K5vrHEEf+CXWP7/Xrwz8CiK8EuTB//vk+a6Am/joJ+JRW9iV68CjsYt/aVysI9fonfJ+veEdehPfouvAknWtdQReCcYvfN4mjdeCl/Fr1ciJ7wYj/BOe1+vdQlC/ESL4S/Q1oqgedVLIjOfIjJ0uRX8Cb8Hf5v0VugfiUVuhL6+lvDL+JRO61K3w9fLJloxVdAXaL3XJ6+8T1/8PQtxSLF8TJj9+hNRS70Enpf3Ve2vffc/Yf/P8Sit8q9aX163Xr1UNFdfVdR3gQMuWvXwKEJ+hb2T9KL/vF/+k4/k7r5UMeXkBJ1ViXi/if1fwOQIe4nuFPAoDr4T+WTl+JRes3w/9hwRQvf7e/hQYQKudPi5P/V/17rWovwSDnfbwUwR3fc1yAj+Hyq/z/avjlc6BTHYJyfNjYsT/SL9Cuk5f19869v4F1GaFvQV6+vJ7es9aiX4v+id4JvXWHBCM/xHhchKr7ASoI+/9CH+1frRe7Axhn4mbm+LxyLy8HYW8SGay1eXmRu6i16n8LwzQ2hvViq1GZqv6IiPfMr/E1m+bvrCZHd3d3umascSsmvRO+I8HNFy98W/V8cv/lluIXqfx8M+hL1WvTehDy6OhL+C0IVcR0l4a/EIY+IXwulf5sQp6a62b5levX/k9Bf4Iwx+hPvCCXscycvCSX8mUTfL2DPVRG/gVIT58QhLlHKtVV07ePqtXK9E79EFcwlXPzikZdavXJNkouY9hD5ZMnxwrOy36EvM/4SX2jfia16vQnrya8gita+gUE1XVeZV53ekjN4WP3/L8vyr3cRIMUuPrln+yl3fgQQt4EsNIveBLBN4rE4mjpk6Ai1e9hKn/DOGt86tNdoR1+CI+q9Rf/BzRoP175bqasIUXLwInfxi3xCIJacBpgmkoI7sMD6rV5b+/qEkfsv9fWGfgr1QLjwzzr02bWkvdCMumh3Vhai5IlslYY1y3er9RM1zRNxCO+IWH/RXlzYn7X/ehCVfRHmvV/i/iZBS4xbVXV8Vc0FH0u/X/jCzr/ufvj+vr6gr+YRzfWGOv58EX+fBdgr+L+T4j5cCRgs+L+T4j4Mfi/k+I+PgAAADv0Ga4C/AKMvkhVfGa/l9BpoSGI+PD3oZ+a4v5fb3z/yyer/Ii90BB9Uiv1q8ohf0ZoKuS+l67iK9erlRe71eSwN5bELXJdyK/zYol75Nf2IX4mCvk+17tiPpe91bVcZqv6D/rRO670W9CV7sBp/Bv8Cn3+iVJYEWhJU6iuv5oLBRIyyKOROl6/nkr617b1aL1YZEr2KJ7/CesOfH/Ahnvkrm1/4f6/hT16FOLVtfF9RfU8ldevvCvwvWOSP+hqOr+BnyaV4ORqJlRf347oC2L6T8TRuvkgoqElTrxyv8ngb/QHP8mX6+N8E4/wiPQt/EhFE79e6BeP8I/Q2uWsC5+I1/J6NGrB6dHjVWvdfX1onde14KITEIXiFxCwp/2gk+u/qW+ZHb5K5V6xxJN7wXk+P8E+ttXrCVe8ILsPggXu/v8lXOtXqj+tF7rX3WvfAwIRF1wmq4UQXjTYvHP9BRy9qXul/YonXxNcT86P3YaH9DqP3UPeDIMV2hBU8SCFe+JRPdGEdfUqE94c+Mr74XxbFL6E+F5cK+vqqvQVqK8eI3fd3fWDH4K34Ky36EPjiXBfdfbJ3dcvSCP6vXov+of6BgJ7+q2sKfy/CqLFWmid6qx6Iidfovq4n4OUI8dcL6y+gn0SX8I/V+whRK79UVfcvy1hv4kSiPWR9XLguHr3QNgj1/CnV/NWCv4EkL+EEr/r+8p17oN/C30WuEUIyhj0PqOWOiQUVUhiXvwwEER+4S7/i7yfSVvM1fzVfrV+vwUCay1eqCdE6+dH7xus3zb21frXry4Z3lx4Sr0JefRza141e2hWWn77Xw0ZX6jkR8YpMfw6TyiPDpOojr65Mle66zvXX8K44hbzVeOJ18nQ0kNfO9dDWImtDnkrRH/X/yL0lav11idZJS7vwhR6vSRO95Mu6+v5Uf/QT/r/f8Kc8ghaGLjTvyfwzVpVX59piC//oId1dLwTe7RcvA7fia5tc34HcEyL3gRw0i5eBbBMveERERl1kyYrb/hz0JeT18X6Fd7ovqwT6XgSaJmPpfdD6L86+4om9+MXzK/go+AphCkWYxEe/wkiRVy3UTOOR8Y+I+I7/QWxi37AZ5Ff4r5Pilff8OZMTuvWv/BA5KBU/tE66iFixCvuVXqpetX7j+on5auWW2I7fqIV6EL13YMsFNclavLf0QTpb1f9XsctK1z9qr9/fQ5FV5ebqTv64Kq4wQvxMcv/ngs+YR+CH/NgTuv58FXELPgywV/P8R8R8uDrBZ8/xHxHwY/P8R8R8fAAADREGbAC/AMd6D3dyX6vJy9RNcq18s7+a6iOuuWuJV4Lul75leqmm5aXyq+MRfeAkavJSEK/WiPVSVywZb+/v8nxEv0vjUXtcbr3gVfYDRq539y7f0IerjpPQn98TBQOJSeXAm6wm/mrdE94f+G/xFcq9XEovehPY74CQyOv2v/onfJ8Qr/EL3h/4bwVLwItH7EL1F+BB3hdeEfhHJQM/Q3XGorGMWdZ2DcEnxniaIxfr6qAQYRVvdE7wWjdf+CkXfCEK83cRH6FoT3hD+CPe71xCFFWYhT4agci0JfpfHvxtEckX9J470txC99oneiUOJXvTWNVSo7dd+veE2r6/+FkIihHqTu8H+PsOV6RfSw+vsO6ydV2i9EYMRWv1/riQQ6r1X/PWmje+16fgqX0K/CvJXJ1osX2rH3Xa9XonvlXvlXvifiboHAb7CnwYDvBEugfAy0vBP86L0R6INd1wivglv5fQVevXovxg7d93d931gv+Cd+CN1X8teiPXPXr3y16K/wj4Lgz5B3l1wQY2JGlFX6B2EZMtCu+65fjVr4K0TKFPQR7+EfVu4tf1ggz1/fX8qFf+J+J+fwVBGuRX8lf36P3glJr/4r5ugJoZvSRuriPwSZF5F+zsOwvWglUI8nySZn5vmfitU/hD3DPYz1F9aFf7D/4Y+TwukXvFV7x2qBnql9O8hIcHEPcjNHJVe8E+q36k8JE8CkRCnxiq/h8iv4dNrhC/m6iOvr7kV+q61/2E9YR1kF/KvVjvQjXo7/L8v0v7qaH/R3IrIWvQQ/XNNX8yvJyfNXLXJl//Q/sU/VdaJ1DZffq8FfoZFXICK77ycmOU1gvKuDDr4nGKUl2ElZ/P2+OJPROuD0YuWuX1if0BlDVdy4Jgmj919PVwTY5FSaReHaI/wQQQvn1lN6J6qBL6LrlXrwovAwcYorrGKkZLoCCO6u+1eI5pcaqf8E/L1anUda90TL+v/nr+tfyVFr0m6vV97PPg4wSF+/0XK6uuqtyXfJX8iN12y96v3q9VIr+qv+r3fVavJfBP6vN/34FgvaLL81z9/fiF+/v7++r6v7+8QsF3+CjOI/E4n5sE265cHGDr4n5MFmDv4n4P/ifjoAAADbEGbIC/AKgvjaELH+w1u4KrkrkvpG/Ly3y/L4HH8uMRcf5bV8VXMvfETj2Ha+tYL+af8cgxTpctYHFS1oj3yfSvQxXb4mC319WVL3ydRC90/ghu79f3cJ4hX1CPz/Er3zq/YDD+BD3cUveWr9RnX8isb/XoKPW/xNq+Jl5q3XpF/T+Lrn+XwiXvvAm1i8DD3xPW0vfJ81YIcJ9I/QljfhndQj4E38vgZ0rYxeerB3rmRnOgY1clX/gl/F/Eo5k8DyEkVjwlRG8LfiF7z179feCasVYIzoz+WveC8brk/BSfxNYsv/NonQSehfSL8ht38iuVgce+wa/64nptCW+NXp6tEi+Fl7XCH1GVz1zo3fKvVhWhMXzy8Nd8FPIh3ffQa+EqPVd36L6vX3xK98SvVhlfH+C/ST7XvBMZe6FiNV/kozLoCHRYqy9eJ0/zGWvXCYhBOS4qE75+X7QQ6T1/7a/qoZ8Hz8u8Ofn8eEfjeghXq5/l+0fsNsw4g+tfrX2WEsK13wz6CbR2BDmCDv8CLLd/XXor6v/tEe6pcvVexyryp7r/9f/Kiv+i/7hn4lXvtF79G66FnROl9e34KAR9cEq+EKwI3wbK667BKVV9VTrQFcLojZPSTv5b5b5+gSAp6JR37uq/pE747wQhD9F6q5OS8FA3OwvDXoJdF81/XNJpV4Ixmqv0LXU/p9Qv1oS/w5VVXETiF8Iegz6pEfolehh/o+UvPGYtG1XoEYrrrCC8CFQp/jPilf4rwjV91J+b1F1ydwmiv5PR65dBDWP1wn5lv+137/V7rV/SgieloslEyXtGfu3VeOJIRIkvOCEirvQ5Va6CFXunXq9HMirnDH69NitiUNl4EiCj0EHKrZHfeCRUu43wZcYilypMHYW6ARIMkfuuvRul7rCVCXeOdYIqvie8X+HoIvWFNgQaJX18t6XQKq+rAncYSK+8CiGlixiIaneC0IVuvV6//XquVXq++bFEPYhTXwT4IcSdF6bN1y/p199oV331dr/XFfy1xP2r/Kv5b0V8Uvf3SI/cTN8EfoW/QzT118S0FKFHUWv0V6uRE70l6+T56q/n+eXwRl1V4lcZq8j/gk9Cnl0+0+/uX7nEL8+IWP+3/BJ8vz4nEfPgmzfWDDBL83y4nFfGf4MME3zfH/Bn83x/wvAAAA1ZBm0AvwCoiECh0IXXxMSr4Qgx5I3Ao5uZDe+RWVxF8lXFq5BauWl6ukTrfEdv4n5bwPP5UJ/0Ax/X13UlUhVr+Cnb+WewIPtURzpiP8cSzfXxHhfrrvi76vAo/A8/lRu/l5uwc4JeWt6pCfAn9/4hCRpq7+tevE5MM65flkxlcvmqgEOJRu6eTa+RF7wrgn9XlX6Evr3xC3uhHfr3hGr1iaxSPlhPGI5cOquMkwhXroBAhPx/xvxtG6sN+4JIJsDQF/oQd33frhqKBCZ3yrPAYxAS3fd9zwMAhXPmp8vW32BjE96Et2Xeeje9198EKL3g2Dfy/FU/5PQjvnrAghH5NeGX4+sVccvQs/4SXE4JLRbvr7+WsE0FFo2Zb8Wt7LLZb+iV691L8vyr7xPxf4RrjvibGIrX/BB81e7Hgs769GasgvoCCNQtzr6JQh/g6RCqgpv6mV71RXvVfEnPfE/E/F9wT9/S+Gvh6hPeEgh8EKN0j+esNfEic3w/9hwnQ95780JoTsEMEq+EQRBTlxyRdAS1VZDO/5YnEiLGdvAsUfrxY7yV/8FK1XLWqFe+175F75l75d+C4H6JlBNxCCL78Jbqbq+16ivBG0RzwIoV+67Qj9+r4xWurQ++MXrw+J+VCX/VyvRP1QsYvdOvfdP4dRNQTfrsNBEovVVV1UJdP86vfC3h4cCYQta1uuvqJvryGV/17oDiCLp/ifkRe+DBf+Hqv4SVev/1/9q9v+Fn/CGmCI9VVy+jClX47XN8KIjnx1YZGq/xHkNrr6YtH6Tk8VXug37Cft6zZhxOvm+an/DnOhbxvL3oIP1q/evY5dfF9x3z3y9V1m7u8sEZd3y81HrwRhjt0TqoN17rRX669X3+rzPeBEgp9iHffLWFu//xfd93QxXy18b4GMKa4oI+gE6DDr65fRf/r+sIOIf8Pc8+4JxOqqv6qwSG1Vv17+qaX3RSK3UR8V4Kq94OvxAIrvvjFevA6hK665LHI23cf8T2xNVEVxEmE/hE2/4J1z9evVk1dyDldzf/XCPo7SYPsEq0Xku+ib5buIQjrHLboD8Eev0LV/iZb+3q7gzsEBe/v77GIw+yaW/v74PhC0I4lfz4NuIWfB9g6+I+XBdg7+I+BA+I+PgAAAzZBm2AvwCnr42NwEHgz5KuZAgr5JKurAQA1X+X5a5cQs1odt66fMqO8GPVXSN1cRLyq/y6/8D+pbmq9FfvV+v7XvlV74lfwQ6otT3LLpV1e6M/hP4f3v10v/Bv7AZvv8CH8CTur91/1GdfXBJi3fP4dyYEHQhZKiuv5PperC+/qgPvFEL3yYP30BlCvQCRCPyfSJ14I+/4IvQmpF8X8Xr+hikIv8SuXQCF2ORL3hP5a+8TxxKt4LRPgt/ovfa33gfei5KuCEES+OoS6CVG6fk+RE7oCaLrBEOgj9HeuJy/JehCEsa8V+K/QQv8iv1FK50T4FsT3CSK58Tr/wQj/17wmNvNrnRe11+ByEdTVwjS+J+0IKn2vvlX3gQRKEua9VhHWid43rX+CBGigq9GY+9PJo7HgwNfaLki9q3y1hH8tYj8TWFfTr2MVp6w1+X5a5UTviV6sKb4EYEdVWVGQJMuW9XJctXk5F75VaVf16K94xUKlfnCfy3xMg9ijMM3v4KTD//0NPpV+tfbbTT4KfhH80/q8uWr/E/oS8nBd4ar03d8EKGMQVd+FX8//hmCISq7+D8L+CkfJzoz9R/z1gkCPQEQHcmJHeHd8IfEeFPjdacFlQt1XX8pheq6A7ghX54WfQKaM+u4YBDWqvfKv/J6hNF7oZl5qwlRO1qf0LBD19RFcTdBlQUPDMGYYKfVeCcUjP89dVo3wx4XGVgrXVeIq/hYnx1U69LhHXCN+r/BAj98q9K/giQ54ffwggmxEYIHHY/VZh278bBJ3fLwRQRiXd3vJlr0/ov/1/+iP+r7/gmy77Qh65boNevwdfA/PGK9VgcwlWC8IeDUECL3w1Iv1/JhBI/UJy/UJbr6G51Ox4uqdX8FkEy+L1uBPSJlOl68d8G32I+IV5cn5/tGebkqwR/CGqhjw+q9Fff8EeTd/xH3XIid99tr3ZSdfgm12r9av8/TyVKrzVy34xHEuN1Ndg4EQTrvqr/Rv+6v2qL3TLfJfPrv+fqe+1f5YoUsl8FH1y/LWD7YhdfPr+7vELXWIWDj5hkZfrnxW/lwWcQs+DjBX8tfXFfP8uDjBZ8IfP8GPwh8/x8AAAAN0QZuAL8AqQhbwOOagCe4NdK+ruX5f0CBvlRarAm9fq1ct+r/J+r9wh3q0nPDXoW0R6JURyz3EVYNd8SiP1LXLdSyeifrkt83BTy3UtCiZeSsv5JeX5V6+J+X0J+JXqHLq+qw7gj9Fqa0J6lXu4muJoYjYrHEL72bx/5tfr7wvXvDen+vfeIJav5cUT4L/gv+C/4JxOX/+tJE75Pde+K6Aj/iFeCP0d5LiZOJRfHxanTsB464isK62ORo5r4QXv19+veG9VDaOxjc2C3FPwZ/BKOXvCIQ8WEvDYjwm+wFiEe/v7BUI7+/46FBCwkT9f9Hc8KDPhRCCrPjkZzGK74xbHcR3P3KixfP4JxPQJRPX0NfhN+J+NH1grotfrf4jwWfAhErTQjv16WmEe/wKGuCBbwtyz+gj0Ym5p0EmW+SqqK6LkyUfoheF9DFxeHCK+6w+uvrRosUSLqohF7oGgQ8Vp7wLCNHOuCL0J8TjEZ27jJqeTdfVy+P+P+P9hwFNUL1m2/191E9T9MR8RT/RPZ2CWCnB+0Gn8E568l3+SC27+qpVHEMfLdav+r9v7f68qiFOR8qv8vxPxKPFrwLAM0d+huqqhOPY6DfoX1o2W24SrtfJriET2/h/rgnwtQl69Ecq58You/hteCkN/PpeVX60R+tX/X/cKq9c/gyCKP1cnl+lVASwkvdCaL3SAgrr4/5vD9GesmuXf8E7w8H4tCW7lp/+Xfre1gpD8KAiNqrOtGfr8xeonwga+Iky0fvE5Oetv5bf8E+CMyO/hFV7GO/uEOkO+IXsUvgpN+r1iqv5vSyL9Xk3QvugYq8IUT/hX5KK9eiPXL+v/BYFoJ/lqXuIQpiUQQpCPsvd9a9XOr3gjEIuY66rvEKt7y0L/JUBHQT9y9IId1EdL4Yova8EHwPBlqhCmuOJHeTvgVQx4Pwsi94Lwt8IIkXQEkNT8cjvNl+XneCfvXy+Ga9+o7vCKviPhCl9Y5T0rELJWjPXKveIz8d8R39w54bN8kE/orV9/Jf1/aM8gpbqeu/1eql6+tXgw7rrrXKX1euf5+v9Ef5f0V7uLV5L+r7+tXlvkf8E65vwKVGfvrvwVP7+/AwbX+IXq+v5YSWDAQDDBTXMv/CP+X/Ahdfz4Jv8+DDBUJglmwhr4j4j5cGGCz5/iPiPgx+f4j4j4+AAAANfQZugL8AowhY0Qs9gCAcmBx6/h/0ErS+to7kQz1ev5OVXvQlXqwCN5+RF7f6/1yfbLBRy+Efy9yzdWvpE/PcI1cT39/ei/71e6m916rk8CJq5IJMT8J4u4j3Xqyrx/5tvFTLFIMV37B8J717HL+dh4R3Ea7nxC/LVIZWSvVgxw/6PUt81xeORvYonqJscpuz5F75F79E7uHF79erDff9DiXfEIq8CnV65qwJNe8Cf8H/wIIlG6TlriIexeX5bi64tCe8BEhjL/+rnQCd4peoisJpEc8J/CfwzkT/XDqP1YLwQSY74h+J+FxMvHQ3oSvRGTarBBR3HkITd3yVou+We2vE9gSRPevePE+JoR2OJXvG74kER7378Et33fidSe1wh/VRSEdXOsWOJD5k6y//+CMIycFCxOgs/hGK9C6i1fJrqJQ5jr8DISrXwIlH79ffL569Xa90DX4R+G/hfVDR9YEheFxXhGsXqid898YjxVuvb/BIIWsuhrEOEeRX+J7tF/V6x+111r3y12vV698tY3eBMG+EdY4JTY/b/BEZayzQU8ng/L4Y9ASDIW96cnomf5flrlvhHsYDGrBfov/gINoW/oN+OydoZ1v4d74JfMNVfiPyYxGV7p7xbV/D43oC6G5OX4n0fyn6BMDPw58RV/GperCPWC9pzdr4t/cE3orMv+Ftor3xXYTDHf4JAsiNjJ1QQpYYMhT+GQz4eGFItfnqpEV6wlRX+le8KegbjryqvV531wTbLWEV8l0LP8f8V4OfzUIXprxwjwk/kRO/V7fuvdTrlpInR+9EXvVE6TFV67BzugVAghrJRXn8+ql/N3z1937fehGXUSiPQ5Us+OJSvQ4m9fKviegEiDjaXGeDLXaP18ZJydaPVafwUQU3fd0k/Qzr5r4n50XPr9X8DKGPAhhhF7wfhxev0btfq97aK946juVhTje5Zf/8v/8FVCGveEqJ1Y+id0F/y1gUvwh4FEMVxKveF/gt9wjjlo3QxT4x39y9aK/xXd9cvCEFNWhHda919f6L461/WyVWsXXV/Uqv7r+qie3X9W81oV30MQuxBfX1c12gg/Wr9/Wiv2UfjlaY3/iibvu9Fe74M8CA/uM+767+4EL5KBV658FGCq+Evkr65sFGD34Ej4VgAAAOAQZvAL8AqghYlfFVQDBwYcl80/LXLWBR9gPX32MQev7Xv9fJBB6GtGcs1Td9bJ8nyScvcb34gmfqTiEI6CTE5+J1fcvr1evSYX3Wr/FfLv+vXugKNe679GeXdHeCegR7EL8TQxE9iFkuFOx/5PHkxxO/i+vCOuXEL4F3dDKL3X16qL17wIovsBGja4j4hG74j5l6CD0JqJHElzJVXxPwqp1GOVffCf656oF9X+EVikwrrJ8K643GIvL8FG7vd9KnS+BU6/r0bt/LXIvfEIkXxUP+hd5lqGv6Kw+qdLAgUOixiiXL4xFmX8MbwYniPBH3gnPEdavS8M/DIuTGi/DdFr4d+XwzRHPB1+I9iEbpdUXq5EV9c0NL2uI0TvhBEizsEMOXxWna5P76mQIulu0fvnrF/nXvlv175/n+eqBB83x34n00ZvJXqfcEvgnBOhveDEEPwbAkGVqVULcTWFN4jG8t/Jp+q+Kr+WTmqgKPr+LR//ov+r6/CXxixxMF5V4lE6u0bpA25m/Wv18xlhetQxxCCb1iK/jO5cFO/BGM1V/l+J1XEL3TUSNiUTH6/vhjG87T8tHYVhn0FOjeIV7rqgK5K4hEfX4iq618GYVqr+frk517sEQEfwZBP4TXq5PQhe8Ov4K65utXrEnV/k8V3/DOyfo/Ruz/OjPWGRVYwVr/45Ff0OVjobRn8OVfwbBpXdC/uv67X/UJ9aK/mPRP619E76XvC9F9eg1jiXt8IL/4yuf9f+LozHgmCENboS8asbNWvBaEERj2XxvqkZ+pPn6v49X+GKX6seGDdDX8niNcdfoveEV5lXGL3iN+j2+OV+4U/RP/r/4ahr4t/f3Xdrq1Y9FvBBxyELTTcqvXEr3gYQZIvdgNUCAi94xVm1QORF4iveIWLIV2xk8yAW3/DXx1y9Mt8/X4SdcRrwKAnHIYelsYuvn8CWEvAmhrwehTwtXu55hivSIlgUfgxV5O/gRoa+OwR6xj8d7CpvdYv17xul/jlZ1jFWvYQWMVy3kz8X891+SjtVAR+/4a+Ov+STl8S6rQju0ShS9aI/2rz1PJa1z1fI/4a+P/u5Lb6n7l7pXvn7vFIsohcYitMRmCzDXx/1d9gw9hYv3Nz2MQQviFie/v7h/4/59ZPuvrnwQcQs+CzDfx4mCmbWX7r64n5cFmHPhD4r434IfhD4r434+AAAANzQZvgL8AqHiASbvu5l8XMIVQaVJJ6O8nEq9c/UT8vc/xU3J3GfJBTyxWXdRE3q9VFyCFSQhauruEIIvR6n5bufu8QsnN8n9+jd8l1fy1xfxfxfxKvr9b14I+7zf/IvdRHX7EbeEOCriUXq4tekqq6RO+K8M/mrDe+TwMIjwfpF7wIoroD7XuvpfAl/Al0SLwYiZOSCD0JvPcSid392r/J8T85T7vwOIjL8TgQcLr3xdZS/IhHdA13QOd4b1x6Pl8eteWuXglBEvdB0NeCoR5qJ3iNcap07AXIb7C1Ey7vv+OXob5ULqXE179alsEXwxV/ikRzwIT+EkZ/mV/BiqsBo/Bz+IR3Or11COv17oSJVugyG+rrH969Lgw1fwR/ieuhRPitXEIjnYl9RvgegpXBMiRQjyzv4VmL//P6O5p/RCrNOHvVB8hZbLeVVVdBX8vqvvk/RfdOrdBQnTzcR+r45Wir8MV7qCBe6E0TqXmrl0Kr3Qnbx+BQMSRdWLzsEcL4Q9hDGZaDj/fqY2765a+wZ0V+rrCG917pk+X5+ofXute6HvrqwYAj6L6pCX6174X8dkxun+CIYrF/uuEeT9BPLwIGSvrXutXjsBAQSClXfGKKg0qVARX19G+DaqVLtEebtE6StC/+CoOq/gm1b+wx+hPdQ/4Q7XDHxFDO/Xq9E7euuYhTAjZq47C34qq6T/XFIS/g7Da17LJzyaF+BGCaK1L9CHriPQufGaf8E/HyUYIdwxvBcI98dkEqtYpXrCH8PveCMKhYVdfjvUI+FsuPFfF+Iy7onfr/4msGQQgnXrL98R8yM/0r/JJYNRsRxEnoS98XWT8MQU33X1J19UhT0OJ0d6kV5H/fopk8GIIPikWOfonXYE+j99+FKveK32v/gwgs2aqE0buvwRVy8OLwVfnXKsC+O8H4zoBIgm8G4Ytfqx9r3U9cbfoS8nov/ZER/gTIJcMVyl9feNojeE9clUMCHxHxnwt8RVVWHqI8lfVRFnEIS18JQTbSEdWq+/X1vttfFbav9r/sJaHL74mcUT199L4lXg3q1f5ftEfv+W6v5+p+vFEKfPPI/6v71eI5FeC3l+XuJ1cniEEniFxC/f3J394hfuq+uI7gu+65PvAsdfz4MOIQmfBhgqEwTyH6rl+UQsR8uDLBt83z/B383z/HwAAAA5JBmgAvwCkr4iMELBP6CXo/nQQea5KuIm5fl+X5e4378BA5PR3/V/1fuEPiPkgp5f4m6/XpOXuWTn8BA6wEDrk+bwjV+/vrkXoIMbmwT8UT1EzYEDLtL3UUvdgR/h/JcTXP89V9fxPgIst8ivfovQ+/79XrHCV67QlE6uJXvlXq4te+J+JxC3zL0uH/hHdS1z9fX0vX2BR+BBq5fIr/N83xEN6Eo/T4mvSf3Go3sYrpV5650LzHgIFeBRNrA7++vaQjuwKKVyTH/D/oHeuEfAg0fJVE477hb4Y9/jqM1YM/gpGr3yojFevfELqF+Lmwj8S0N6T0S83glu+7u7PArL4QQhzqElj/Ir1y+D99Qh8/hsT0Cn4sWi9LVovfrqlwQfWQzv8CBrC3xHx4RRO85fE0fvAjhNFirBSP+Hs7C8KcT9S4KqCXVqiv43G+gx2OV2NfL3Ed13cnob3i/ia943VgTV4KV89Jf8CB14Z+EOv/DwxGi8levDun8GR/36zQnYIYU7QUyrbvCGsR82P0RDH7TV/AmJe7tFf9f3698prv/RO9H+WTC/50JfsGoR/Re8Tl50MevX1P4N1zEKYED8IVwlXofXer1lrUdg79gIF9hkt06FJV8EN33ute+Vf32idLQaBHJgvDGNjSZl8TJxNYKFCnEXz+GPv8X4vF8STqpBiMr4hXiFN+PE0Iwxlq42GnWv38qIxXf3Xr/7X/UP9AQgRoW1v1Ru9fmxbOTnvH6yUT9Ln1j+I1wkhHQpV/PCdRO1v/Mfd9ARR3QpK/nFeGPwoiuVjRHg5BL3HdTIz9G/q/hb19BB1Qb9fUd83iaL1CiZ+FkK6GPhDDYjwUiP0d/rqu1VL1Xy/PdRHX47JWveTXEIvVifx/69EcLQo/5Pju/lEEVdV6/m5aVfvfVvZerRHMYSXKmwXhjoBAggvkR+k4joEvr60JfwWfC/4FqGPivRr/ohF+I/rVejc69b6l+X2fq+vrR+9usGXfxa5UOVn/HEmtOuBdC3g5HIveC8cvTar/05K+vPEm8R+DHi2FnaGPjNKavr6+vr6iqrochsi8Qp6cDZX+IWW4/w0leIX8OfCVUrXf3Xh2r9T+CYTNd3fNXr57rkuEoY6hO7RHq9X61eJ5ftXja4b+E1/4KD0uX8DcWI76nmvgj+FrG+xOIX8+CbiFnwYYb+F/iBCD8R8uDDDnwv8T8/wQ/C/xPz/HwAAAA4JBmiAvwCvYCFwbl/5tB55qievr+WXAz/m+Srjvk+RXgjxOTlV5OWXkV75J7ievqJrAj/lk3rq+SE/Q0q45/1hP4Rycvy//Lr+W4j+1fGdApyX1zdgLk/yfFoU/gV+v68pN3W6O8Ol//mxO/xROOJ2v/iUTonkxxPvkWKrAn1rV/q/q+rB+u/vRe7J+I6BX8Cj8CWN8DSPrm6hb5odwjiMM5OVexCpeJBIXd7/Erl4GH4GfiERqMW51HUvDvwvVyXCPf69Q2cP5YW40skKK/gaAxVRHX19RPX1E+X8iGd8ZDmCf1xWHjyXBAsTrxFctctYfE+EQihrG//CYR8I/CPwjROrDOvXvAviLHENfwI2XBuHUfL45Gi18dCnE0+N5KBQ0L6jy99eiXr1qTPruXk3uv31SFPqu1yrL6Yhe+ZFiriVaTv49e+PXqEKe+DIT5fhIR61iOv0bqsDeNx7hWmOP3vZWQUXUMofWX/+8Nf/CuKy0IeTlk+sCwKRHvuuW+XX69+vu4OV75vYvwz+PkzfHUfoZwIG6Age+reOwQegYLXLHdAc0jPWCs/QMy+I36vfLJ2vjv1+v/iUf/gQAV+Sv75l7wwCH4/9e6H+gj8IaeP8L19/dR2GdYGyr36tWCX8Z4dgiqtU64OQz0BPD/aCHaoz/P9q9CFrCgRQl+4I9f/JXEL3uveXNn7+Es7C8I8nyS1x9Rtc6Dj1ghEeEBDK7/CX5OoURX8EvpUZ/BB7sEdaq/mXT9fWr+FNYyr9v4VBt4n4kR4nL6K/6/+esGAYzsLwuOIGLz4rEb1gvEfzqoY0Z6GKXG6mV+voT8b9ia4i9iELbzub1/dQhCr/l+I9Xm2/G9fKhz9aLXX19SdV1+DL8TeBKS9Ng/BMi94XFVka97S95NP4eR/zPWI+C6FOSXJj/vqq+voj7Cg5CMvA2BBXxys6RU3cJ1xa/8E9e1vor+DcMfqxJqicqIMRT5GJBctyFOWIELE8l+pF390CMiJ32vfr11r368q+r4xT0bEK/hL4Qr0Z79fy3yVo79/wsr9gJv8IQUfJiP93/P81CFxCEO7tFeqievrxC/Pjif4JMmN+SuXkrlvlV9L2r9avVasXxN4GbqueC9d8R3iF+XELiFxCCC+/vufrlvgz+fEZv8CJr5sFX+fBdgr+XEYoQgWxPyYLsFnwh8R8GHwh8R8dAAAADoEGaQC/AK6IWhC4hdfMCENaq8GPSJ4p83LcTfLXL+rfLLyfEfEq/cdBHhHXPJcTPtVcnur1cV3cnPQgmqibELXq9VIivXr0EWJf83LdxtXEoz4hXJ9VJ1rF8nhfv+ri/iaqJ1X/F+BB7+L6AWfrquqiOvSfGQ0X/+auf6+uWsDv+Lv60SuRevCPf9CEWsL/D6RcpV/XoQ6uvmhXiYvqr0Lee4dXvQ1Eyxi2McQvvA2/As9cmrn/y9A7P4X+E9Ynr/X6J1YV1xeNnZ94dDHxXxSN0mD/r9X39I3fX0vQtyoS9iFl9Hq+kT3azYW64Jv4hGjnyiCO+79cIVWqL3tqVXg1/+HvhET0D0I9aLV0C30bXDK9WPr1V/E1iKERe6tWz+BZDfoUiu+EIVELN6G1Xq9WLz4nXKgk/2vb7vq1eu6V3EeKyr/xLQvvLvDe1xPqvV+tf9fjvhD4z4zfr9j2KMx7e9ahPA3YrEYn0V79GeSvwJhuqvv9F77XpeWsb96xtD3qvFyYrxVCO+VWrhT9EnQl6H1l//qgNGXiLyVqMGIQL3xC1X4XL0Srng0FY4kPslqwt+1/Xonj5V/8t8svC1DYRF+p/yLk/hSExiNqe4qM4mYYoWfI2tAQ/gSXWDuCWq6rv4Mw/8v6EP8t1Fq/yq9ZAij9fr/qIWVYMRWsJ/2JRe8TRO8Ff9f3wxCPFfEL0vET5MQvy3vXOr/LVgcQ14E5awp+ojXX8IVgzDfgsCCu6mocQl+vxQnphHw9/RXqgdjvBSIrHOI4WhH16I4her1qMuugJYWvPlwSNGc+S6L6iUdjwh6jfHfiK4isKfGegT6oGO8R+b5fFVffwQQlxFP+L5Ueq9EqWwiVEfzNX/RI/y1fVsR2BVq/y3zr1YEL1q9CibXg/DHgQw8j90B/BFdVEv+CDO17y5Nul/JUvWjd1MvfKveK+EqL2/JBJ3fteDKr45WdsYu14Nx3g3DFYNq//RP/KvVWi/qo2SgT+qR3MTE0/4eX8vJ+hz13e6L7rVvGOuTolG6QcuvhD4jwM4j4i7lr1eqn68Yr1EbNv+Gb43kVpPXokciX1+r3ei/7lXqtiVehy2kFE3lEK8r/gm9evzXu5Lv76l6ruTqvl6+pfnk08cS7WMVX+WJfyK6Cb5F/3f3r/q+r8DgWhC/LdX19fX39/3VcU/4JvrFf58DDi/kwYcQs+DjBP/itCYdmx2M+b5cGGCz4R+b4MfhH5vj4AAAPwQZpgL8AwPoJNJ6Jb9EtQha5YumpRCI/l7je5Pl+Wa4zv+aHsK4nn+dF75a5cQuIWIqSVf7/+VG71RXrlV/l1/r9e8B16v7qril7vV4IqCOS5KEEm65auE75a2qrWL2l75iXf1EL3hfLqr1xMmxK96EonYxdyXiIaL//fEoX0ToTJf8Wp0+J9l+XELdUjdWEa9eH/QL+q+vov//sI+BBNrBP/Anm8CX1sT9AaR/WvfIsvk+SEhCy8st6PVWJy8st6NfqFdfCNYHlI7+BXEK/gUfgVfgIXXX0id7XQLa94usUmF/QI/xPQCBFmPu/BiDDwYqRawr0EfQI6N20uJ+kSXyQny1UT/XG/F2IQur+7Xp7wQnd/pFwTZBjv+IRr/EK5+ivXP8TuvRX6BDqnk5ZMFS8Dx8C1+IrT+X5+vqJRPdRNcII0UJcTJ/xt8TJoRNl1lzJ5un3+n5OvlR/FcvU6+k9e6C4XRevi/i/BDqq6iur+LriK4xEl8MonoSwH0kN6uEV7sBAfja5fL8Jdeb0EMI397FO/vWu67+7V/171Vvl+f7Xupr9e8P7oKULfFkmzvBl8QDdf+I3yb+Et/odlCQiEauTvrgg34U3z7/jO0If6V/pX8GNX/Ld/jviP4q7668EAil31TojxOCb45I/5H8PouXiBHhr8UhXfJXCUJ34xCf8UTeEPxFcRS/WKLxn5FrEKu9U7jFB48bwT/H0R+tX13DiK54GEE/xKEMeEKsda91q8vP4UDKE94iv75PYzwmSbtCGPhiFdCPiq+XCIiM4msFIQL3fQRCHX44RS8KDvICDwz6AVIEkEha1Z0a7v6/tXrCXwg/L7gp7fL8n698vzycKVgq0OJe+v4V9e+evrm+bxdHeKy7wShCvQh+vxe61cxxL2pcRq/gmm7vx3xmuJRWJdL5PmXqxXHE+vEaf8KCFxCyfPyo/dFxP67l8ItDH6nV7pn6+vS8J44ltKj7fgrDCP3QHkFS946ien9HeTgohgUtilrF5fBFd++vGeiZalp313oR3c3ar3f6E+Et8T4GFor45T0Hf4Escr+DMLeCcKV6J0nL+ivBD94V1hOj9Xolzy79arwQ3fv9oj+iq/dVX19F9p9kNJUECKVFUYp8rGL6/Rnv1/Lcslujv19RENiF3/E8k1KiHSr+mRe6+hFXqv9fyV/der33JX+ry3w71IvWLX6I91av1asfL3L1q/y/L39/d/q+vlxS16vdxME/x1g8L8vgk9y9y9y/L8uv9f4hfn+758Qvc/XiFxC93964ngj+E/8R/mwMHX8+Cb/Pgow78aJghifnEcR8uCjD3wt8R8/wR/C3xHz/HwAAAD+EGagC/AKWIWLELiEChTiFxCwSl/+VBVi+WqnQjoj1f5PpX6krklGKzal8SsV8snN8lc2OW0EOJ/o7VhHEr4vuWTqT0b/YEHXEr/4lf/rVcSv/l+WX+pFfp16ubuEIa9HqEF8XXLQhCnf30veFdUCf8QixUv9/3QKxPX1r3Ui/6pE75aoL0V+h9X+KhcQslgtoS9L+J0JQjqw3xi+6i69XrlXLX/6I+IV3onyVQR9BH1+L1xaL1UH/QL/zSYEn4L/y75Z/lhfiZqieul/LoT+i9XFyDlsYhF8DjXtcT+BR6/rr6QhvCvxeVf+q9Q1CQ/lqxvOmsCPh7wYhToDaK+XzURv19rrXvnrmhTlia0d79Eq9FvBB8MJFZ4a/FAiM79/136ikaOb4oGASWL45ZVy0+J/ZEJ7oF9ev17XhH+vY4le8PtYvC/qGV11ELF8Zdfz9Ar/E+2je8nwLoJUdnwxCfF3ffLWCT+j1F2GzVdoJdfa98uquX00WL5dffcnUqL75/177X3iWi94mvvia4usNH1/3Cax+9YugbVi6+4MPEUK68fhP0PruEe6Xvjbw16BNqgxXpMfr1qbu7lQSe7Wriu+rVHfrr177Vr9e/Xr2eiel/6GueBSfj2id0OqVPHV7whvP+GIT4Q3/i4+nBYa3uhnfE+Eq93ERPdl/+K1+jP4Mf/Qz4NCeHhXgVFjiE13LNz12veX8qO9Zd1BVnnCHHnVE6XhaEqhTELjF1XFXX39faxmuuI6X+vigSb3bXgUfj/grJ8cCKq764Vh5X+JQh9f16v8tc9VD9VaFveCUMfN4V6wR0rfEd8MQnySfJfF8J+98qEP86ueCU/yVyK9UBb9fgWwY+FkrHT1XXLVwV3Wsq9H74cXr3XugW+uuCJDHhf4nlQ15uKViai60VCP9xCviie9XOoR+N8EF1r5qL3Q19DxPRfWv/CVXvEfHhRH6t0Tvil6WtXrgohf5fR2upZi/yhHZ7j3zae/r6k7+y0M/2DKr44m/h//iFIRjiXTLX4KqvWhK5eDcPeBHD3yIsXhGvfL7KvTUuMQ25r+F/iM77E7yUO6T0ar7ur6iUf3WvdfgiXxHSotY5T0t8T4GM3QC1BN0FBXQFII9a91o3fJNUI1itUMUM/dctyTYWSPlLQb+P/9UvdV4QSJ0vEfFSL4rHLrrX8ToR1FfBn8E8MfdRSK8/N8lUL9cv1yIR1dr3y9aO/2r9xHy9yd919djkS09cOffoS0+sTf31cslcg5DL9Wr/P4GzVT9/Wivd/f34xCWDeHfhSvv7+/v+fXN4hflvvq+vu/uCX/Df+Fv8Mb+TAxa+bBB74O/n+f4Ovn+f4Ovn+f4+AAAAEFUGaoC/AKkvjaXxsavmYa1UGHIrElxEvcnEq/lEq8/N+r9x0EVBHLYNavXLiF+VCH+VX+Wb0Xqv75uJ/V65uov5aELVx1Xq8LCkJk5Yr1esT/RnrBLxi/ScqJ2v6fE8lRXy1QKevC9F6+JRf0MVn/qP+JV6sBkrtTd34EvQ5CLwvxMTSEoX02Lr36J03fy12v6+Sm6qM9iPLqgX+vr7hHrrBjXpaARPr6n6n6X45GeGRCP8T699v+/Rfd6v3dXE3Voj1xK5Yhccjlz3YBU14FE2/hHELXFV0hHvCOs2fB2Cr4URe8+sdr1i+Jp9Q0hTIR4vuJQt4gQvtr36L0RX4azF+GIyLv5759dv4OaN3yK7oH43qVFTImfJghXgRAur+DBInY4m2MVLKrA16xX50Tq9Ce38LQjy2IWuEUTqEL3CMl6G14+vT+hnv69CPfci75Mc2fd/r14Rq58taaL3ia94lr3xK9XG/Pl+aIn/iutYugn8IfNRq+e3whwj/yoX1etdQjS/1//Qt+vhDwxUqRPe/+5UEHmrBCd3+pvFdcv691Wr7X3y/r3yr2/noUTr/4R6gj+G0NboPVt4KPiPQf+GN8ngQgwgh0I+tXUGFC4TmRfBh7BxRO7f5JM2I9Ee+QEXVU6jFV/B3RHKwQ1c7/AoDvBUbXWr/az/LVSfLfr0mFhaE98RVdLBl/CCvP+RDO+GIR4YkHITf4Q7hKqrrRejMQN8TqgOlXxiII5/5qGKJe3gp+CfQRRTTOgZa+38H4d+XqSUQv6Ef7BIBTvVF7oO175pa/iK4QhPk/Wqv7167kjOEd/16v4J9UBHC3XrC3oUT4EoGnwQeBPBrv5UR5eXxxa1Re6KJ8GYIF7rrKr9X+I+SuFIU4pev/iF6+IXqwhrnnXxHUJIvei+ejPVur9/hFq5JwiiP0B3C/XvwaE8ONFfoX8Y1Y8Rrl+Ze+RE74rxCvJkwlvhaEeIm1q46TiK56XlaExfohkkoT+le7nQh75/llwhxxCtvLj6vXYI+75eD0FnYCNBBWKovV6P/5l/VARwh1+EvxsMfL8vEIV36PcrJrRfkv0K6uSTJQnvEH8V8n1W14EcIeBDC3h0JIveCcOS5t4MKvfGeZ0LYWdoW5KtUFW+T5KuT05NGXvkrpX8GAjsDZVjwfcv3/JhEknr3sR4wR1CHUQpVHw0sYk9Ef9f1gj794vhSF+T0S7nitCPAl5OSTJV75fdEfvxC/E4hfnr1fFE9x9c8RWivV/zKxC9dvukd5vVvPiPRmkXVq/dq/fdX1yp5f55MBDVfGKrwQ1L19fX9/cb/39+n90v+5flmu+/EL1fX19cR33ffBV8+Ev82KzfWCb/PgqwV/LhLfxfyfLgqwWfEfF/J8GPxHxfyfHwAAAP1QZrAL8Arq+IkL/xGg08EPoS0Ty/LPyfJNy/P8T1E3y/OhTJC///q/zL32r9RUPCiC3Jia9E8tct8ndVWhT1UR1KvX6vVdXCK98s9gYavVfXDPoTa/W14+sUmNzDEM9Q5b4xbdRvxOMW/z7/v7x/oG+q0d71rl+X41e1/2A4dP9E7r61fuFoS9CWjMuJ9GfEK74uudexi++f5d9/yrLFEr0T5F72kTute69VXfF+BBo/eBbr3gxWOJ9iiV2K96t3rF4E37EonVxkJ8TIIX4mcUQXFF/+NxRDP5/jUXMY5T07oBorrVvAo9fa5U/0T54Vq58csc6Cfw1XrwR/DeuNxk6WY+HlFH8GZ170P8ZRu8JPwlRe8JegW64Qh6wjv1vWi0/WvR3pfKhD/ghu/S/CiI58iJHxympl1+CFovdA91xX6P3QE0I9P1r3Wve694TC/690C2uLHE8vAwDV1r/w3vJRu14KK9VKvdcLiFk4n4n4RxkfrqEu+T1qI2Xf/ego9LvpfKinTqIrb+XwS0WNfE1xNYbfhHWFeIRWtav4MhFUEPYK/Z/koV74IoTGIfv3DdcT8I9AgJVBTVfwiuXxC9Nl+ehB1y/LcUiP2qv+r3yeHKsfa97r02P1wyhb+Ffi/wSSX1w5CfCHgcNddSfDHX4Y9Ra9F4l3gs/IhD+D34My+CktYrJ1J2vq5P16uVfyV1wxiYsabiYn8NIIdClwh3ob3X19cvNGPwWaqI8C0ZXYxXc8XvbV/A0gpRr+BpBPJyy+hP7rvHiPhnFE1xVcMQpXilkuGPCeQcTf9Wn4lGfxOtFqvsDKGO0T47pjv1f9Xrj9eBBBX5BCvtuELVzqb9f9Sq9UIDPwt5O+pt9a9e/vfJjEX2v0M6E60futeiNkQlopfEE7u8E5r5Pl+JQp66V6XCU6v8OfXRBaK/jv6K/6v+r3n1yeGwp5GreXe/6/pfwt8VYTxVhPfKhD16vLQVq83JeCMKeBTD15Nc16dYni2Ke0Kckd4IQi7u9700Z7wQ9/YJO7v9gkJu71X1SP3VdfhD2JCXYW+B6C3gu4xFHfGViF8N/BiM8IrwRhC+RG/W1IORzY1CuTEYR5L9WrknHE3q+6ZMn1WCLxXjtjEZ6VfWvDxUd6qqq0TvCOXiKFKviFf3X8nE9a/6WS+tiEXqrhcQsfyS1zVoj9clclav3PdavOIWG/nyUJeb0apv6spHv19a91SsXf3r3y98lT9fX8/XGVEwv/d9/33ff3xvy2CwTp/0/4hCniFxC4hcQjLEL913EXcO/WCH/CHz58Qv58EHrnwVYX+T4Q+XPihEF8R8uCrDHyfCHwh8/w78nwh8IfP8fAAAAP0QZrgL8Aqa+NjRiBUrwZVoe97S98m+ufAo9fq0q+ZXq4Q7/k/RHgk5/nrn7iV6hCv5fnoUpd1LL6L+aon4nuEbuEaVcarF80nEQ36F12GffPdo3d6J3/a9a98uIXEL8WidXrf7WprBGqoEOS/qIu4R6DZegyXwIPoBN/ARInHLvXS9CtxPfNgh9dYV3iaE9JYY9699InfIr+i4pXYhfifZ9eirV3CHzL1citl//6BvRO6+u+L+IvCNCe+bwImi//+C0tc0N33jaL019c1Xoz16v865j4RVjfxqPn8DeTwKYjfwj4EvX/SEd4T+F8i/XvBTvhFHYxOz8JVp+K+viPjRPzo2XxkN8TXE16PUuvhtSYeeuFvXDVY5CjUMnxixzwR64nwhRe6AUYR9rwnQlvFhlTq8S+gIYbXN4v4TFyYGoMr30S79f/JXKhHeI1z/EdAccLcXdQrPif6E3lzqW/ya5K7Q7vl+Uhd3VDfTL8qL3iS+69MOJ10PDN1SK/T9av4jJwTQl61fF3hz4a9Ag9BffrUT9X0KQxX/cnciO/ev+9f/LPyyP+sEVC++kR6xCr0TvBQEPE0bvioS4YQ+ugG1tfDHhLeXeK+I/rU/Xd1UiEPjFF6xCl/BP/BRly5c3i6CXoR8CsqwQJX+5RiNimGx6SVFwSNeqvwUYU9Erq7wZbvvde+evQmNPzoQnS5eqxiIL3rDHXCYTBB8Z144n3g1BgCIqruegyCMmqor1xIO/6I9ctcq/r1fqF1f4vwIAJ/QZ8J7y74v4RRe+JX/xUI8R1X6vd83dU6EtEc/uU277f5+4Xpc39eFKM9cIUOIU/94dfg3D6vNU3hA/cGPY7dB3L6K/gpq/yq8L/dl3xC/isWEPBaOrBSM8EIjXWhD3zfXy0/166jlfpifHadf1E9/Yuv5K0Jbxh5c/oC3+aFr5l+i1Jy/ghI7u9wXiapOfl+J6jOhXrqtCnscQora8MjF/rFQ2KXvBSHorLhLml+IsFPxO3l5ivvslEz9iNaoz3yq/kKuXV3jy+J/oX66AlJX2sXm7vGK9fKr+BFIr6x/6Azjl6V/yXC90COiv5t4zCtclxFcQv71+I8u3ySV2jXxiIK74xWn+dcvBkfuWtqs35OwSjPkQn/SE0IRHiFXxU+DQq/ggELVcnEIryckvozyXJ2VL3Sy7KvfP1P11y1X4HXLcfJb98oxbEMDEc9vJgxz6r0TfXoU/Vyilum8Qter4olzLWLq+Hq4UtPv7+/7+75fluonrd39fX99333gSHBB8+T/Pk/z4W9d1z/Jgg38EHxHy5N/LhDL9CIIZfn+TBhhz4j4j4r5/n+CD4j4j4r5/n+OgAAA/9BmwAvwClL5otfG2vjZhC4hYLuVAgee5kV65J7OPrlrB/kqReq4Q6iviF+hgQhMdy3yycs2173yTCFtfLQhcQt3JCfLXojRuXWXFVFoQ/cb8tDlvf9TfN1NXEd8mAgaPl4E1fPWBB1g52ORHquaEeWP4lC+k9EeWoRRuxS/F1gJPjF92AIB9/eseqWvXt/N9K0ldfeH8mBH9AdRPXS74UELGcahPWOJV5HvF/SJ1865a+NRXxivll+G/1z9AE69Au64R6/oEfXhv4Z6/QjsUTrmhhe8JiPD//4RR+xmXMld/+BTBRjF94Z1kr10B7CO14UhHiY9fo7163lqVW6/DX4jXDFfEIY58V8Usc6AhvqXrXupUX37K9/npeEa956xeCmr+FRat43JwyryfjiCNUvCG3/CPGovV6LXxMVYRo9W/jb9EKqSv5JNid8mgh151b+dC++JVvFiV7fwnJi9cI9Q/1k7v0LqgJ4jw1sUQyp/ohpYS4V+NQTa+EegKHwh8NUXr4yERC9VEcsnOh3fOvfFq91/OhdeGfQzr9e8Idf3gQg5CVgGG4hC64QQh+u90T0b2EOqqqqtdfZhDvtcs30r4xQK0zXF3hHrwj8KutVfXz+qv6q/YPc269eEaEv4dq/zIn6qsZEhT7Ur5IahXioR9mqvU6K/X4cojVjyK+X/wxy/wnGQUeG/iyV6vhFRnyCVfb/OjJUqiF/6a90l+v+4VVySwPwCJ7r9F/eNMj94nK/gghOoquSL9Wm4+uIvlKM1XQMxSK3ya4Y/mrDJtZw9+Dd+DcFfQEAMdfR+KJfcy98vm+M3xFYlo/efVA1H9a9b+HIR5FviERyDibxGGAh8v6K02LDQIa794KwhJ/cT4n4VoQ5v+qiscS93iNDFLiZcdsn9fUGN5/n30j9+vVQz19avb/hUQjOaojqRCX/k8E974y0bzy8WjPWEaM/YIav/1Ov+qX/YT96v3r3cnxtF//8Zvl18uOJdrXgrCHghC26r3yd2D8/Ud11m0/++EOTGITf4i7kmHLquLqoYRO+Kl79ubpfdyr3ZPiPiPUQi94YrlarhtWPl8CCENYIer+CkJTDiS2WdFoN6oEdFfO8LfPerXUI9dWxFUCQQCLLTfwIREbvRaoDXUy/CWagnvisUuMXWIXGL79f/r/rV6FIjrllrquuJhf4mvru5ar68Yir75LvX3XJWvfq90AqBEm/y3Usl9VSvDl91x9fQQ9aIxVyr18/UvUiv3/aI+KWuShS96K83PEDFORfueFvhX67++pepeonr65hC4hfv77uuu6+vrEIYob+sI4T+XHYv5MMf58GWF/hX5MdjPm+XBlhj4V+EPm+HfhX4Q+b4+AAAAQnQZsgL8Apq+KisDzil8VDj/1+gl03rbwY0R43k+SukIeuleS+uXwPNXqwFbRXJuTuEO+H8f/Qm1+tTd1zycstRFXIhT96vNxK/rm7/ifl8Dbu/vggwnvF0fuolenGKO+fELiFxC4xCtdROIU9FWr/r3WivW/cZ3KsUohXr4lXvnV/n8HvwIPwJ7riYT5cYvou9CamrW8wpfia4tCurivhH4nf9744lfVUV3Dyxd6181jlv0hPVdTSWBr6v/AivoBHhPX8I8sq+Jk4tH74tF72Jm7W/ia9fq8lSrquLU6j5wR93yVRikz3gXa+6AU4jrRHOwFqE62IXvF16sFI+sL/DPoG/pd/1geQuvY2c9MvhDwz19+I9y9mff8kI3E9+IXEL8ShHS/jkX0ILhT1wRf4JRDvu+/xTu+uJ8mn4S+ERfYF8ShfSLf6DPHE/7okfXuvw1vJ8K0IcrBFu/b+hzwlxqCPYhZOFa4V+L7hHGRfP8i1k+l/6uKil89doJRUufrH1eu0WLqIUqda9fo/X2r/a9WKr3QN6vJQj4IhUuDIFEKd/E31+hNeEN4QrFEZ9aoJP8v69Xr+8F/uqVej94FAd9K9UEfr8vyr6TeqE174/uC/x1CemxP4chQ6P8ILXwRdQTdKid4JPhj8Z7oku1p/xG3QxEBKsgqWhij338Pv7+XwIRNPJq96VaonSdr369XF+ei98I1wtXN83hoK/Ki98lcdCVxi13ItfrVf8I1cLL3evXi9ehOefiyGVVlXGBn8RrC2EtcJhP59YXCBNaxuaaDN4GME/qhCVRxLVnyyev/lX/cHNYJPh7XovQzfXJ+r4pZrtF6K5fEhTx/XDf8qEPWTrYn8I/Zlf6X/zfDGuHvoBRgQfi7w8TX9UxfUN+Oo/eXdBuvScZCvLN8cv/BCT2l9eERV1oQ91FfH06uO+FvCCRX+XwiJrNqlV/VevEfJhvkqgIGvn4n569ZgWu/Qh/ECfFH9FkzOuLR3+JV5eVXxxKTdav5/h8MeBHBEi9dgQ698suKq9HYZhDkn9Biqv60Wq5q4YvwWku73vffkyehWefFF6CaQs6eI+T5uvBNWLXg4WvhP5/b8HYQ8P6wyGF79f+6J+/RXocrTQvyIrxFa9VyemtvPl2qwUDEbvwRld+vBwkTL9EviFfyrmPBkesZqhHrmEIuIVm9BBf16J1jltJX1or3Vq8NiEXGEq/zdzViavJsiN369W69JaN8lZa9dfcq9V691onXxC/+Iq5+/vV8QT9q9XPOKXqL64ZEIT3/Kr96K/l1i0r1l/ojxPzd98nE9X4OD1XXoz1fMIXEL+rw7y/cl9cvyz+hD/131fX19fXpqT1X6r5e+7+4xcTw38uTF/LhjFfLgg/wR/IeCeM+TDGL+f4IvhD4/5/gi+EPj/n+PgAAABA5Bm0AvwCmCFihCxfsNaqHa0J6M577+VDHiqiL5fiVeTv5UWsQTfJfJCXo7QtyoQ/98s9Bmr1cV8n8nyL5e4+uWXB76ju4IF1CopHr1aEPROk+qjcQTXE4hb+SwK9YtX8lRKvfGr8+XoDz6+v5UR6df1r0MCENLkcq9G+iVX1/yo3Xwj/XE0/perkV/k+RE6l+va/3gh9cuIR/i/Qv4R6/DgjrV75UTt/GQjyyaEycsuJ3lLNoSj9I/iVzHgWK3xyK98YprLvAziPAi1y+JRGPYmuvKI6B361i8P0R/Cutm8N79HrGy+ADwK4LqzC+vr8unvwiuouIGIRypf1xNP+I9Heu0Tt/JRf5LpEfwMozwMYhXrBzXvAx194E+vviEV/a10HxaO7sCKEbx/wuEd7j9YJ+v9PD910hHWqnF/D2y/+DwCZCnovRS/iepH8tVOhn8Yr1a8JawjRW+Wr0e/Zvj6xdAjP5smJ2MV66+vHblfrx3WvWDwFkI+jX+L+Nrib4RrCHxHxG3yaGvPkoV/0utG7u/kutXpfOiv9KlWiCFfwYJX+SS/u+7vLXrzD/YvwQUNrrRO6+u+IQiL4QhWtDTJXCHhCtZf/1r+V/z+Ccmq1W9WDva6iNfEeFX4ERFEbvwIhvBhrJV65Xd947+vpOf428MUJ6hRJs8LL3gyo/Vyfod3xEI8MXwgj9eCDX9fXjiHtZPVf9FwjKAl+g58OG+GQRjBW7u5Sv/hjGzh0+d4ZDKIlfBaGfHfPk7RnrtFerAgAYZMOqsbRevn6joR4hEelxXQhXX3TxgtxKRY8X6Ce8f0tAvHK5+77+I8UI+auOXtcF3rBuEz/A0g5VvWQUT1F1SDvQQ9dWBnEeIo/S8kMfHrDIJoYV/BOOV8v/z0sCGI+q+pK0K/86/qg/V+utmRXPP+XxbRXqwcj175F/4j5/WjPdgU2i9WIq98sMXxT28Efd9S1Hq3QR3yyVaEdVfYEH39hD4IMlQrNhERu4iEdaWj9Wb+j/sUTr1XoXHImpaiEV5/BJveJa9CMlXBBX0lzomc7vvXtXevdS9aO3iN4iveOr3hzSaiYZxCvFEmpwVm8PjEXvDIQ8eEPiP0I/+v/kh8Qt32X/+uIQnviF/53XJXIuVjEIe/65fSKx3ovfJ19aN73XugjXv1/3/dDFdsYuLEL+tviK9f/r/wV1fHE3K9Xq+qtDf3l/Kgo6GPriEN68TV5MuRcn1J19S/JT/quq0Z/tX67GKzrEL1EXo/6viifuIqocriMuM9X+lY7nVirl+1f7V/lupZrj7uLu+vV759/wx8R8bd933fd98R3933OMRGb2v/BQZCXhn4Y+bAmdfz4Jv8+CjBn84hBuI+XBRg0+I+f4OfiPn+PgAAAP2QZtgL8ArvoFDwQ+gvUXzoIPfOrxFUi/61f5Pkn5fBz6icUTL6/+I+I+IhnBDiPQ1qx9emEIIOuXqJ6f59ffyy/S/R+7mkuJ7iZLhHwd6sBW6+FBiP6QYietfLNjaF9r9Eit/xNcvOh3X1+ilSTm3/JUSivXEq/hOr6//XpO4UELGej94zXrV+t5+65/i/i0K6hiv+hxK9jifvkXvk9petfEXxPqi9Q4l+xxL9Wf4EX4P2vb/hPia5YX42uCEEhd3Oo/UyKuBVrmPBzXugEK+gWCV7qT5qxNfdgX/hf4ZXQO/X1F99cevfCKLl4F8HC1v/4i8mF6i/llX8mJa9VTrFNWrky4NvXD2hleDkIVhivfL6XydARaGp1wn10Nr3YGEX3F9/f4pq+l/wgt/9aNHoQqSzUTv16+BAhbjZ+EEPf4heiMXif+q3+wQhDd+9D+1+J/R+7LXu/v716XiETvDPrQnvIt+GPiN8FCCXQtwj8TeEPhD4Q16Cv+gillF9oJPLV/Lk/S/+gRBBCXrvvvliKgx60L/QonL++M1qhHVwwhTwpwwgunUcja7Ape6rCFeq/v+Jon1/hDO9QqwR11sfaEOX2r4xROj64mCDwVl/8Ch7MI0+Bq6rA3BJXNVxC939iav+viWguEfu8J/AlB2ukXpeT4iFOIl3q+L4TBEVVqnW2J+PRH8SXGKJ9Gq4RC6v+r78GAhX1hIeBHBFWK+Hfwwr41UuddBX2Plrvl9BNFf2CJer168I4WqI+8UvWjd8/cVV8mIxPJ8NfFVxKv7av4KR1UJ9CvharHUMYxf3wornx3gjBT4Qq/Yf12r16/6hPwRe4Ie0roEPxnHEvULjl1QwnfvXr9F6/rifiV6fF/ByM8H6+J3ydWCPVS/oQ/ghEUX//FE44l7eFfgmEfaEvdgjCfZ9clYcL4KAur+Ft+vUKJ7ASOFH/8kvyi4ksS5vz68Egh76/BGTd7EnXZstBd+E/V9d8T+r/q5Xomcu/FEvx2qA1gs6n0sVy+hL3ft/hT5Ri6iFn+vEwS3ffcreoIzPd6VPTxiEJZdSq/6KVLXL+BAFovd2rfF1iviPUcj94YMr+Cb8T4JvpeCkVrBnG/BmCBZXWhHXn9BejvJdd8K/iFsQi0MRPXxCEvLyVyfoz1gIDJhapPdfxETgXS4hev3Rv4xdvngiFLM/4RvRHr0Xvl6froUvUZ1L8V7Ivfr2KWxxPqvV4h8/DF8uEd5cUuXV+5ZKdEf5Zb/lupcUitG5f1er1fqfqrf6vDHwuv+pevrQxuvEL9/eIV/Lff3GYJsM/Dn1iOI58E3+fBNhv4b+QRBTEfLgmw58N/L8/wQ/Dfy/P8fAAAEBUGbgC/AKeIWIXxNr4udfMg08Jdwxy1y1yozxHJNyy1LNzL0E+3Jyq+IV/L/NoiK/tL369Xq89gL2rnf3q94GHQxfV65Q2v4nCNF6vW/yr1XE/y8vxqEdXPeq9VRHX1dWBF3xN8T8T2AyaO53N4E/2AufcqI/evfEL+Ci+rlrl6iUXP1E131FonUMV7/a98lYR9QgveCX0Ffza/Rer16sCmas4Q+KRX9CF7vV+6RO74U5ZuWTiUJ6NvRnrhNcsaQofyyVRC+D0SCO7u5k8CuEvApm8FotcvAj6y0ZugMoXXtVWveN1l44n/w78J/BTV+oRxqO0lUbLzPaRuxykzvDHv70TvBz3+gg8Iv+bhVBHv+4RXq4n9C3qwjquvX5l//V5MI+wQ/G+/fw0hT+GKxz9Ef4r5vn+esIfBr9UNfxi9PXnomXtUv17sC6rq17VevexavjkTVUQIeAgOOIQ2dWDgCFCNxMhf/7v+LQnvWuH0JufEK3hfOlz6+r+/61y+v9fMgp46uTT6iPHO/QuKuVffPv7kxS8P6wx7BmCLx2sI/gwhHhm+Nk5/0dz5K4iLwJFDHPudf9fccr9SVWvXWvYxTZG+Vel9e+f50fqHT498q9VAQV8LQnwgiv8IVUMVw8jd2IC1ckcvCYlCHpckZ4MVrqfwzLVf6veDAR4NOlvXv1/4rEZ9DY3Frrlr6iITL/+jP+pU+P+IXu/r7fvkvjKCJfbV9eBT9RXhha4dBiCZEbxMEhNVYqo79CfMb03gaQ+iPrX/RH+lf3X8vovdQX/DyPqfiF6uWFRRPX1+QIycZFVCPhOiP/1GK9X1zVxFeif+EPhhXpfDPgQwT1QR/LJcHaE14YBWvVhHv+sb+L+Ze/X+KJ+GYY+OwmEvBOEFc+33dcR83p/LLUiFPiia5N8QBASK/jOv0V/1/Jwtrx/wj/BH3evCHz16tO8Gff8J1JIv+uWkEKxNHfxKQiU3CKvV3Ivlrl6/lvPviK4lE/LhsYvef4R9cvaE//X/k53hj5sI/llza7ly65axSrnpf+BkBMveBaCCuVU6M2v6wVhDw6aXkX989CEWzsJH4T5Jfu5Oute9Bfvn87rk6DAzfgyMiWPVEvQxEe+MXmNcoEyi94PhPer9fyL8l5lf4jqEli+ElsYhT34YVi6GiK5II75a5q/H173+SuSvRO+er18fr3cq9b/RXocuP1E9ff1/oz44hbng69dVyV9Fw794T39XUnq8j5OvXx1Ubc+KW67qW8DpVpRC/Ewx3N83zrk8YhjtXeMUfZN993q4j7v7+8Qv3Bf9YjJ8mEMv3hjfyYY/z4ED/BN833hDN9YYyfN8R8uCjBB83xPzfN8R8EvzfE/N83xHx8AAABDtBm6AvwCsCECZo3oj/q8FPOgi8nLenJci9XIvfIidXN818qudxPf8vgc6L/5Vr5ZeZE6vV4IsTQv94T3U6FdL65/tf/Lvfk9X+X9f9avS/u+XlRXOomTBj/RH/X8MLqJpfzZcnoTV1UnEo3fEondxNc/yqxQxXvfSL3uvSc1VyaL6Er1YEH4EX/fEQsIR5ByPef0S94nP1XLiEIfxq98TrifwEjvkXvpe+l6tqqhLoHasQtL/wKI68T6Ak+va8kJiFvllXxMf6Oz9X8CAl749csSp74E2uXgaQ8sTvh7+vvAg8Yuqxfwj8K1i6B78M0TqX69jidXg0DPuhb+DcEH6NV0b4EJb/BIFHvN4TXUTrroQgqXFwij9EX1xaJ7oTXpeX3RPfKvfXgQD64IIz4oEQh3+/Xvi/0XvnrBzrC49C29te6CPwiJ8Mi/H/CInwzRO8P/DPX3+vY4lexCvHIjlqHE3rBsDiEvWvja41H6cXO0xGdyc+uevi/arDCrCFBLpKi6y7z63QnvH8USTYonwRifQjxfxO+C6EuNvl+Ee4b7/DVC2PCnsEWNrQSeq16X/BNr0X+vBEvFegY16agdperG/tevR5Mm+FoSuCZD370ROvGfBB8ElYQzbERD8EbBTtKrVVqqvWGXa+KQp/AWJAR1XfwT/0R/l8Z6ECvBIavRXl7Xx+id9ovfr30vfKi95RqvWFvrJhjCiWv4rvq16eTCfq0d/kieLEa1VVX6I58t0BxHK/QMn0O+FoJDO7v7zwQ3d3Z8yvWh2/0JR3yhlEY+JqkKQh/J9lRf9S0IUv8fWBaBn4NgX9EBDWEaE9eFf6J+EuIXsQuKXrXutW7i7rl9Cbn61OX6/riP/lQxysEoSBHqt64hX7BCK9JX+T5/1fwJIRV/BCNR3+J1roz3691L5d4V9gU69Jk3hv8EMI8RXPG8qEvNjwgTe/ByugIIgd3fd3f19fRF1y3CFr/5EIfwYnV/DA6sZ8R6CdCX8jV/iKv8X8JCbxWQWwpqEe0E3JhCz1/o7V4IjbveWm+w97vuXvugv6/lqwQ7pjqFE1kOiP8nUT1/IvVjTaz4aXvBiGl74he/Xtfr0LfKKRYuz0SKTJFzkTkc5E5HM/sxt3quLVzoMCepUfvHfM9cv2DuvSK9hnV/iF6/CIQ9BTwyFEV/EhBE6uLhp/o7JhCy8l4mr/L3SJ3ff9A8gj7vmPA4a7Rs/63qxlHnd6++XsE67ur+/qRXrhD9YxjF9EcsRxsK3q1/eGdYV/+qvVfXeP64rkyLwx6qyfa1/8tev/iaFL3oQ/UTNU/XQhfiYf+sCPrWJ+uSKuWriK5KvkFL1wSfIX5P4n5++r6/l+XuX5bEL8s3f39xOB+w382b/J95clcmGP82EOIWfBl/gi+L+f7wtv5xCBDEfLguw58X8/zfEfP8EPxfz/N8R8/x8AAAPTQZvAL8ApwhaXzIFDwfbPEcn6F91IvRfP+rK2SuSCvlXvl/rlxiJym+IqJ6+vr18Tr9H/8TJsi98RCgpDXNywhct8TiFoYggXMtfFyfVx3d9yzDEe8uBF+Dn4P8Fnd8+KV4xV72f517wKv9GqvuorrWLr8L/G9NSzWMR2fYol9gKv80mD8q9CXLLyyehdX61E5PzddehHVz/BCp0RVxELouXgca5KtALOrHoIL7oFvp0SL9X39L3QXGeGVfS98RfMvSL3Raxipf8I656O8I3Fr3eidLy3cavqXxKO0lCUvonZ75vgqIId/w0iRfC1V9glrXf3eT9/v9HqgbievXhXiiHJnDovw2N7A3/Bb8E/wW5MV+dE75/g4hG50XL9XoYQvPXLJcevfCaP30rm8CDyl3cUEEFglug0v+2v6te9RHd93JyUqltfGuWN7lBL3fd5zuXw/1/+hPupehOtpe/Xv16V/EyDiXv8CF88Jcsn/PXoSnWxH4ajruxSCS+fqcl31XWB2DXj34zru0dj8FHVdV7L/1Sv+vv199r6bn6Am0d8bOsXh/0E+OJ1Qogov8NQnxGOQnWX/9ahLBSfoHb8Oq8E9Cn8G5vzd34GCLqut+gIC6MIRXn1+WvRmvBGI8J6GR4SpUuVEwdh7HSJZdAXxEJr4QoQsJP4Z7BAYENa3JdE6MKRn8EExHd/EwQ3d7GvHfpXrh5C2eUMgjrVX+dCH+1eXiVeSgPQGnqvH5MXrR9/wmIJhTjPCnvKfd/N8T5zfJrk6za9CH8FfXBt+BBBChbeC8PonXX312v/TXvDgTvifQler16R/woIJ+SxyLqbNiM8Em928F8FF3u7/eE14Toj+N11W2hH69XkwhRX8X+O6ivN35/iNZKP14nWHg2uXyy7q+/4T5K7Wogv/8vomdJ/yeFt3E3iaNnv0XvG/J83yHp/Kr4xFGWWc8M16tFvBiCbwTgg8G4IPjJzvCfxAwh5UrCAQl8ERHfv+CQj3mXrxFYvGZF3PfOjS9F6T8tCe8bXviV74lcqob69LEgs7/+E1c8Hvwn14d+CcYi9Vd5c7/hmoiq4niETvDRl71V6GIQfL/rW/1MngQj+D4/hJXm9fyS5Qgj9a4ShChi3qvqeuWfBUE4YELIv6sI5eq7XvBbRutcVJ1VdorHTfT9fhKr98u3Nyq9erxXEr+Ga4vln9f1eif7ll2XFL+r9av+r2IVoVfYhYJfnXX3zct8/zy9/fc/33c4haXLwSfJm/z7/zYIOv58CFxHBZ95t/EfPXEfBX83xHz/EfBX83xHz/EfHwAAABABBm+AvwCs4GnEeUNaqDPa+T5Pkrk+T9Xupe4le+J+fuLrst7y8QvQU8/y3UTfPv9GeSpEd6quvr/X8l/6/0tfoSveD2vTL9EeE+VCXIZrri0I7EL8q9XLTr69evqrmv/mrVHfqP6/Ag/B/XvB38DHhhXwiitFWL969E19f9cXT55/n7i8QtP2bseFPpCu/Xv16uIk7qwEvrmQnq3Xqf6CEEKcsKCELkwskJbXYEL8LrmMYqUscTOrwJYQ8F6W9P4nEL0gojOeF/hn4ZqmWgINYutYuvFE+CH3rFXCeNY3y9AewYfFVkaGdvwp3j+ghqG3/+g29jncqojBj6BTrC/uJQrvte+TXBVrr5EQqfJ8usFf+IrCdHiqgII/r7Byde717wxvEvwTi+gJOqCnwS/lkwdAQISXwrKKX9Hr9ar0WsX0qF7VXPWiScTN6CHT4+ivdRvX1EeGK13DPQ/4qhPeFF4mhFfBhCfCNcN3wj4Q9CNYQoa56FL0Tp7+5PQWeTtFeq5O/v7rlrG0UqfqVPPXqr67bXSE9WOovYvHKHtf/BFCXCF8IL2//hjwxuxGLfglgt1qur+HMoxDAv8/gQ/ghLv/w30uI9fWrGOJPltVhn1FdS/a9SqJ/jfl/X3hknzVgTgIPwTI/dXC1xXUy9T/xC9698fd9YlxWIq9Y79K9eqVaAjiPChPhDX4IRG7s+I+b5vhYER61fGyjm9EV+jcqVdc/XVRfxPUNq/QEoFPWj/8EHwWHve+GYY9em9FYiKhGfCoyfhbwTvsBvgQfBqCe+XvQzrw5rVe8MbzZH/CXJfJfzE9f/iMJrw+va+gRF3diulff/yoU98q9dAzXX47S8FtCX60XqoK+vr6/KNRP1nHVxEvovb/hK4ib5OM8PZHl4JN7wIzUqEPLZBKv39RPVL3yVQU9BSi9144lUEOsL9XxRP6/617rXuh/oI6wYgw8LhbwIIKq4mZ/wxfLhH0Ed3FSjEQFS4kIy/sWTd93r8vd3ebu+9cuvr+Wa0CDqkNy0twzfq5WFxHzL1bSN33P6K+/0EHhH0FWnrkfhH/d9Yl/IhHX2imTGIwrIv7W/638BRBnwU0fvDNe7kXuhFelrV+lq4YVj4QVjEKfPCWIV9gcwhE+r99er7/Qh4XXJ1QCP1YKd3y0JybJiFaWD70BlDHhSi5dy1Tr/5S93Xr/vV+vrql76q6uWQUrlvV6GK08OfV81Ui94R+COjd8iMx3y33cqKxV2r9y/E1Wr0KJ71fu1fEL0BEoTHutEfqVEer5+WG/iPvlmr6+/v+WVf/Ey9/P3P3wS/EfGf4a/zYY6/nwQf4I/iPk1i/n+I+XBRh34j4/5/iPgi+I+P+f4j4+AAADykGaAC/AK0viYNeeJ5P0Hn+STlvBf6ifBvkXxn6vCvoS0MXEoV1XF9T4xRXeM5aqJ+JR3r1el8Tr+hi3xCwly4hYb4u+J+JRuluEO/vXu/vRYtX9fiFdaq9cSvfE0v/B3riIRL//E+hreCGvQj6FP/8/z44n2X//4RX3xN7XQ/4S3xKJ3o19y4EERdAa+18wh7wq/6XxO//yhXd2KJjObqZG7rt1gQAv8SCQu758auvAy1y8H/oDnW/X1onVVq5WG6/McSL+6A0hle6+n6+vrxxPrwPYOPk8f82n8CNDAhf0WqXwjG7Er3hleP/E3yIQz6RK8HYirAv/DFe6+gN4n7Q93gQwv4KRaI0QsLr391V1iNUCf4EICBC9QjT+FUXrwzrCObdTDy/8vl/P8TvqVDrlaW/pern+Xq175PkQnviPivivNrkV7wkvG5Md8NfjPg0hLjaL//dfXVhD3/oWx4REfraLqVBJ79XugJfHKcilXBt6AkBLqkV+tX6uTlrjPiFaS0BftVf19filXBBCNQUK91BAh8Wqggi+4JO+V05PQhxWF3/XMgg/guLWBNXUSr/Re77+rBCfVX7m0+D74CADnz1qjP9r/9erte+W+KRe7PV/hW8SKrdCe9tE6HuKiS//Fl1rX6vNgqN4KvSCHUIdfSVDen8HofVz2N+VCH9V7qTv+dXkuFvl+EkJ6vXpONXoV9a67HEKvV69IOfaKprr79XgrSFP8SbqugIYa0oMwh9RvVdX8WvmKJ8CoDjX6P3QCPBmrfP1ozHXXr+qiflrBRvSk7Re+CuEeSXiPiJ39fo9T4ZCSv+Cgju7u70y+FO77u7vd9vwQ93aep0I6hS+heOJv8T1+Cl9BChLvDXwkZX6voIi/CHy+gnRP9G/P+hN/Rr5UbtfCvwdwsIU+diIhf69uvF3f3cvVVyYkvcehD9S9UvdNdUj9Wb4j4Q+fjCXbxvqJ8NZMLhLXl+PDU3CsNVxC4jXvwXF3d3veX0KeqtXpfLWBSH16E91fRn40vnKvXgcAVL+hys7YhTEngtCy/8JjpOfxOWor4bhuwEfRXiVguNS8ivm10tehT1gIwbS0WO+ZHrxC+Sq5OVf9xXx6J2IVpCEXwsEFt8VJU8+18MQR4lXUnXfEXcsvL3Ljib9z1X8mvu+XweOq5a0R+uxi31/C/oW0Xicv/Ih3e6+PlquIqVX65OSS+S7RX+fv77X3BRf3zd/ev+p+vVV4hfliO/v7mwE5gs+fCGN+sCBxCz4IsFWCDNhDHfJ8uCLBZ8J/J8GPwn8nx8AAAO+QZogL8ApohYPuVBx6Xz2KWTkrk7iJOSuVXqpawc1fX/QGH19drwPf5FeCzZ65b5b2S6kX/Tq/cRPuvRFREKVKhLzLl4Q5auJ9KuJQrv/l1/f169Zf/6uaT5cCD8HfwIOFV8TP6G1CPOjOfPXE/E+BJr1YEHfo3dRlYRJ1CnX4I+/17Xgx1UfWCAI/F+LycShWYhXiUP6xCPCXojdIy9WEq9riwL1FvjUfSrgaRqMZxVA9q/pK3gRa7eC8SjdVBfXMrza5f/9V/QOg/4MgojxfCF4j8CNBRhlb2gR/Df4lG79deFj/EAiu/8xiI9/hJe+OX3pr3qvv1aqA1h/oCCP6+rR26+vrXqz16Svwb7HEn3+9eGvQmsYilzKqwQ3frrifQQ6u7p/r7RO6iwQ3fuZfupf5boP/CWK9Ce8I+gc/F5KCvpBrrWtfwjwrdwyj9XCNXCMW9y5cH3X6HfHtX6+51fvV++hSteXwIgi9tfHYEuIK77v7vuy3f3LE42ixY2LzF4WwrwxCfmIqqvFusHO60OfwYiPBeTwXvr8PER2+K7BkCLwhV/ifE5O0TumJXq5fib4ZxsepVyL/yBmFqtYoR4kEpF1VdzxF1Wr4nXX4KQh0ERXWCQRqr6xUeHPQxX8Tvh5Cf+HQuqcPEzZKFdeLovYiU+RqhvxV+Sven1F9gR0it3dcOwp7u/T8iv+tRA59RFR/cJFI7/iFerkL3d5xEunfCCufq/wnr6/Qh5OL6Y3ofQt+u6i+ole7+7p/wjyL18R3r0RcMI75P3/9rCPvl5kuCGTe8nv/gxKURu/DIkt3+HVvqQEV32P0Rjr6lRH61el/W6v8lY7XCCL3gSBCKlfHKTJu4NaqGVMvqK7+5V68EwPYUFLL6K0vgkF3uQH8TX31bfToMP1q8uP3k3yYxCdeFvUI9Da914onwqFqxvr6te6lkf8Mv4hF7uIlsT+STJlf6HZSUHhPVdNIX7xD/XpBb+8EmtnrAgm0vq/xyufDFeif+dX61fwtquTBMC+G/Qtps7kXcQiN0CJfo1YxEFd8QvzrmPAWQf8GUEIl34/2sXRF1onfr3YFMKd6v0ffCGIV9QwisYhdYG3XxSJ2MW/V4pauJ7BFX8/CKI0EFlXnob14nYhDn1N1axdPJevddXE96P36v1q/X8vyL/9E/I1+/6mV4KPv0LiiKW7+urlQp+76lRX+Wrm+JiPnGKr/L8sEHxfJ8knPfPiFxCxXwafLhj/Nhb5sQI4M/n+f4j4Mvn+f4j4Mvn+f4j4+AAAA5xBmkAvwCwL4qDHZZNq6iOpUHu65bjVf9Wq41FfwU1eDNfFo0VL4tYsYrvjFepNrsG7RenEKK4pflkEL4JfQCN3xEI8qOxDXoj9xfc/91CPz4hbur3RO+TqaTieoRXuvrkwb/BDgu6RevnoUT0Am/XiFu4aRH+b9erDPXn0l9e7/AihDwS0d8cTfw//BIV3d768N/DZt/oKVBN6HteEfhvfo+WucCx+FVyVRhPMeBP/EL7oEFfulX511gvPl//RO6AgtSp0q9W69VgW/hn8aveDoX8I+SCE7v3xiM7fCF4OgbQoMU9I9cSvXyxuCURf1zqe/XvFdfJ8ciP4CBFK/xHy1QQ9X4tI/eVFEu73xPhX4V+bQ4gj3h2veFevlxxP3z0OJFb7+OhtfMhPV69GZaC3fa9NxMtP8vkclAlaG9Jie9+hxPqX/YkJ4yc6mLwh9rf8MYEhI7dx9+scjdq+RBbq7V6wJmsCoM8CcK1/WUvy/ovVWvSjiFXqziV7zBH5UfpX/CnkFu+lhr/LWxl4hIR3kxKwhivBCJ7nvToYhg4rHg5Xg37wXwI3xtFfwye+NpfKifrlsQv6++VH7wv9Cbw80V+mNkf8L8n6L0diQyiXNccGBz6qUYoYyznhj4a/DSEP4Knfqxjp141CN0si74uuX5UIfqSuXEKcj5V6uT5fYSQmuk8nr/95Avv+F9fDuOuf4rzfSV7wkEawUhKq+l+b6Qh/BHV9cPaK/hsL+6O/hr19fX3oz0OW8tVWf5/k+CQFsKv4ifk/Q1sv/hbEYZCC+HLQhvcXd93+E77vL/++78Mr1+TX6FdfEq94yiv6avfo7+FKvaWvxn9XrIS64IF8Qj9JhHEdTVPVRv6HHSXifHKuIrmlz/BGEkfvBGO8HIIF6Y7wtei1E0J16JVZIIdN7EnoQZK8vd14I+7vVWXu+4vsPiuq84nx/4tH6QcQv/Vq3z1gRQx4Rr3h8IeGRVL+YcoXq/xyvDfItRBf//r5FcvtGf7RHxiuZR4CQCq9rn9VEgSvgu9zdyIvfJLUQi91EUMU9pF4hbeDvMKIZyXyerwquI0d6X+IWhiPeJsTk5L5Onl7mqJQzvmV6GE3xSvEL8RIKJ18fiFgpvQmKSpO5Kte3Qju9Trn5Fe7rvV5Oa/V7FKpL0d4L6iOtDnoQo+y99y98TU/X9/cG/y/Lh7r+fAgeufBJgu+X5/iPlwSYL/l+f4j4NPl+f4j4+AAAAOAQZpgL8Ap4haXxWvqDgYgw5kRE50Z/lXvlnqRernrkvlqonsD/6jUV/l8GOq4LuVXv75Ubscr2JcENFyiL65fl8C3xxN4NOJXq2JxiN69krdFi+q4hXk+TiUV/iVfsBR1fv79v8FAhcYt5eLxyvWviV74nwJte8Cv1+iPfVdL3j/690DX069/4FDLgzyF/8GQKYJ+ai//+F/xHfWBQ42LPZmxBLfAp+gb/DFWrBX6A/6wr8I/CO8KfHeuu174v49Wxyhwef4a+EsUT8GkKcsvLHYENL3hsqt2C9+34IevZEZrXCH8RuuOZHfffy6/8Lnl5PP+kJ6sR8FfoHJ/17X690v694KeX/+CfI5ufqJQqPJ+liJZa/iUJ74T8We91+a/9OqCNX8I16XgXocrQlyKX6HN99Bj99zoj12r3cI3gu+HF1N4yj9Wvi69Xa9+pVnhOpVnQfDPUvxt2CUGPwjehdHeGNqPL/9VYfe7/5bwJpvAg/n8I6uGEV+8EmteVeVEYvNviau1983yXko79YISrX+QbjuEqCvJCXQJar1VX8OLsCI0Z65a4z2I8EHwYgo8UwQmWt1tf8lHfWCJgR6K/grDvyoR/9fxOkhOXsGS5dsFuOJ+uwEj+F4dX8Xvpeboxuut0R5OSq0Z/FCfBd19I/eCcO/F1jaM/zL+nxPVQz0FaF90CwNrF1/BR4X0/6f8JCFnwxlJ+v/EeCQ+73HwVm3d3d3d3jnnmNe/BDqgrkxvtC6qJ6k6iFfxzxxKVeE6v4JTq/Wj/rEfCxvEa0W6FnRjp2NBfWbeC4CDDfoTXyUEY2DeVP/fghCF7uD0oIRDvsfSx+wn71/r5+olW6JrlrCaXqf14j4Zorns6viiVfFr+VeHV4IRnwgvTP+CL0WphiFA+z5NV3noT1clq/q9cuoTVysPjMcSa3PDYYRX8JjPjKr65n/DnJeJovXiaFdIvhDoCB6lRM/oq18q5fKpk1xMII/dAYAr4YyVLLgSKtjFd+oLFY+TwM6vkriER7qdelf8LckT6O0tC/X1JdRXgSl4Ejv5ftGYux+7u7+oiXll4n9He76EL8TBDYmrzcqGPLyyX3y96K/U/xPz1dyVdiFgv6+kKc+sQuvrELQhbqXr69VN/LXdCF+XEL8v38sGIhfBHn/w9kviPvBxxHB58R8vy4KMG3xHy/B38R8vx8AAAAMMQZqAL8AqGAgcWIWhCwX8sVciD3VcZXJT4qrELLQFf4LcGZf/1f4n5ZLq/X/0r/S9JxfxK9XFov+nvBjgx4le/pf/Eo3YhViFuoruEJKBzvieuTJ8L9aE8Fno/pN64lcscS/fE1gSaxa/p/EL1YJy/EdD6J3WpU61666wIPwb6xdCeocSev/huCXmRHv17wZ/DPwz+RflLXxsXMxXjF5eAiaJ7wKYc8ZXugY+kvif0b2vjl9r9Yq9YrwT/De8DNrAhUdtf+COid4O/wIEE/orb618SYXXxN8QhTlc/X4EjWDH4Let/oCaEetF7sDOJvde8b8EfwU7wW5OB0gpqX5ep/ZK4n50Z9csl8qvN6EtWJ/aJ6sT8T9Os+TGfa38DhDHob+EepLhFBLr5avV+tFeXJ+Wtv51b55eP8fxMIyP+CboEt9dVesJuTtBB/sEnVX+dWOgNfrBJ1V/AhawxR+8GArHEI7eJOr/Krydxr/gn5ke/k6+Eqyawfhzwsb8xqqvDzBDVVVytVf2M+Tw2ChCe9BXwqFfia5EI/LYKQT1YF8E6O+/0Xpn/Dq/ieJV6xy7+/sv5fmQh/DYSV+pAQkVVVOnUi/vm8Fvxvx4v7V4nm+L8msR+I8GAM4eL//EdII+HzG3f4KDPe96ZLBWIrb8x1j1UsRyq/hV4RiSUyb+n2Ccnf81ev/GfGb7BITd89+vQvyIS0RyRuslaCT3QJSeE10DfWieTden+uLQl6HEJbz/E16sNhi90dKvr0FdIv2UZu7S8SvfYIy3d6uiaoxOvoV8GAa8CYC7wePwJ3EI78FesKk8M0XvhD4QRmKHLqt7y/i4c5J+uwoI7lR3vwRCN3sdOiV+t/lBQW7u7u6VeYEJbu994Mher3v0t+v6p5BCuhC/FdAIfYpYdELQhZH/Ev+7iEK7wULdcyLF1xFz9fcnuv+uavv6n64LbBT7kv1evV7u+9Xr1fvutX7/kiL/lgx9CHrTl79P76v7rlifgy+ewlnwhiRHPgqwVfNf19cIfLgqwV/DHwYfDHx8AAADckGaoC/AKuvj9f+AVHiFgzwQOXlKHt3LyVUlckvL8vy/E/L2AgffBfy9y6+JXvnXv65ZKm6quRenuPuw/7+pup4L7vq6FLiF+VbHy0MV79699L3v0hC93CHf8RJX+i/6ievr0vr3WvdfxMEvr79fSYf6/k4tX+X51v8f8avdAI+sc+JxiIvVzVVdV4Rfgn+DX1Hdf6/rApm6+tCe8MBjrXLa+CQKPfsgm5qqMQ9/mXrf9P4/50Jf49b+B39AJdeBBHVYCfS13+34v4X2qwIOhRPhv1CXg9NXH43EPMo+I+L6/gogl9W/VpPrN+dG7012a4a11jkQLPqVeFvlu77tF7vRWrpfeEatJhH4+vVWit4U3xWMIS/QQ/AgQ5hXHeghFW2j98v0Tu75vkV77Xu016l8qL3xPsb48/i9v/O/6L1Z8Efo/4zl/QQfqe+9f/Wq4/wIArwfCvBEZHf6BH1V9fr1cntr75Vb26ynXvFvHE+l7Qvq9egooE56oHomXA0iPB6IrA5fCq8I0R5cIlv0K6+f59fo/fr3698OgkPqveBWBXDl8dxISqu9/HBR9VXV1f0r+EhHhTvB2DAJBfxtCnqohFb4zGShSy47jdJq5byZfRO+NxsSWEXpy8F8FNaM/yfJuv+jdV4IwlRfk/BCZV3ute+f4r4LvBD8JhGvX9VXUT13goDMmIPdQMcPF//sv/eitN5T7ug4iAz6/6SXb+Ve22mmTkkL/+hHdAQfQL6L1cSv+igw+LkwhkxmsTXvE/A0gQumL8nxH4nrgq9EevV7wi+4v9F919fX6VbPJxfjRN432AlwXL3gQwYIvVgl+GK94z8RTq+HBiOfGkWJ/yI3RP/oVn1yX8vh4ei5dAoPXoT72frRu+Gewf+/oEwIqqJ8tFysv/gj1hUd0GeIRCZ4lf3xCL+uI3XwtyT0LzXIurrV+ghXP9oj4xS4ZFUIKUgvt6afw8JUyKq54YXvBVBDd+LwUVjnQjEileIXFIqxCs9gMkOd6vVpYhftG/LXT/V4Yf8j/icL0fquSlxVXXVfXJSyXCHfQpfk7i6EKXGIXuEcUhK75H/BItE0K724r4nAh5PRH/V++b1frt/ovQS/FXxIhZOeIvkL9+CbBL8V/hD/NhLL8RfeCbBN8b8V8R9YJsE/xvxXxHwU/G/FfEfGQAAAA2lBmsAvwCjL4mNELEYGHiFgz5UHn+XGK7UOW0vr/5F7uK7+++X51f4n56pCfBLpYHP1yQXUAgCSVEzXr3er0/+5LEL6ddovUKJ8GOqAXeCb19XJQ5fYglyNr8v/6J3xK9/S+/nkrrlV7qIRXsQp6L1f4n0J1/6wTevX6J7EKv0X1YJ9+r/Gq1cT8/z/Fr2vmV98Trqn9r2OJaf6XvpE69kk9erAqm9vwn8bQlj4IUFHgn5vkrdBPvpe8/eE+sVL9axqKe8+MU3LvArhboBBhLp+gSeotE7p190BB+F/gjrHPBD8M0TscTfwR0XvBLXugJvrvBgGUXtcHEEi97CXn/BBBEsR1q1gu6vQhRzLgI0QiP4N6v0Cn9r3QI3XPeB9EIz/KvdX1a91+EK+0vovVgjCfQPRNYfCOv19569Jgj+GRevf4Xt/wUCFu4m+dE7X2rZfn/+Sq0R9PNGyF/90Xq5fkR+8yrdE7xf9e95a/FUN7f4JAw99QT7VcqGv1fVoz9x99q9aJ4CKornQCACHX0P/KrH2vdwt3L8tr5r00XpuajvBNVGF6r8EIjVX6BiJrCmT0bP4OzK9YPBau8a/PQlqrxRDF/i/kXvtX/Xr9ffr1DiFEnPfG/LdAhJ1/r0E//Lrr8PSXfIuHvx/xXfgkDoI9VV6WL9cV8Ur5f+GoFlHf9Gf5/ieojr13MjP8SvYhfn+0Xq1Re/Xqoft/oJdBP6CL1a/J83zVzK+/BRBCSqq/i9Vq/xHtr+sMl+L8U/i+0FF/3P3Eyc8lTr3hr4z4qi9vvh4v/8R4Jxe73d6YPX2Yc796J+NRO7msEuuZermXqxm8N0dnU694QHq9ev/JV/GOf16sFAbhzkjVz8vLW0hXVgnN49+EdjiCRf9Cia5/RK9X86rHm8MhL4Qr16C1fL9lFbv83d3gwF9B2hbvKIvnRO8J16l/+j28OURzwJ1FaTCozxI74iC7BQl9fLXKU17rBBUiOncqnSXnXvZ5OkVsQvi1Pc+IWHBCyYIaO9r+vWp1UZ+xCHd8R4OqxV3Xa92Ky9ovdS3xF/1EfLBjyI3i+WTtF/1r1dq9er9WrycsnrFBv9dIQ58lXL39/f36+JxC/f3J+IV4hYNflxOS+8OYkRz4JsFnyYnL8b8uCDBb8T8b8GXxPxvx8AAAANbQZrgL8AqK+Zgm1UaIWDDlibiPuSojrQvpuJV/l+y934McEI4gv36/judCuqomrie/GI2r9FfXXJ6/65uVFfFEvXz5f//Ao4JMRkxWhSz8SvdaM98Tr/5fl/ra+T9F79f7616QQsw4m5r4Rgm5levRO+bwY/mRX3/J3XE7/rlWXQCB9RK9Q4le8eTxpOoS61fwT+wN/wY69X8ENF/Jg//BjBF69NcZ+vt8miN5fYEUf4V0X8HHBhxaEx/xinqXHgQasawW/wc1981UCbiFqge+gIubBb+br8IcZiuqwj+CCChdat2BLP3L4VG9jNL3rAgfiPByEkKy+K+SSgKvwVj0P9SX+tDOk2L/R38T90Xvv5+uuC4wUe8FXfyffUShPfa98/zq/6/vluuTivEfFuTavC+9CIcxeL6k9XugZ/1f9e+1/jiE1ilf6LyonLJxPyr1cvl3wj5RNVwzxsKd/LfL0Bv+BNFYhT3wUe4hCX8FwzoCcCTwUJEr2Jl5fuufxhV68J8bElhKQWwgmfIJn8N+Gh3xFL/5PiPjkEe/BCRV061BAiPk9fVQIRS31Jl+xWNRxPH+G+gM4K4tYJ6DXjtv9XzsJJgmfhUP/E9hKgi9/WqI+vwSFVdjwRERn+RXk5McTfwmCD9Fe/X/p/f2iP+v/1/dQR1i/l1movfBzD2bEehPfizbvd3dAYRCI/TSv2DOrHSPLyfoj1hURiiFclaE/8LG6DfzfNlxPXgVwQIkW8MVrP+C+Cf7rQpjtLrvbrl11HdA3yYEQCN8Wjv7F/L11mov750R/DYUriFeXh+Cf6CCEEI5/b/4I+7va+dX8K/BkNuojzUfpMj6pHudyK5eeiOdgIMlYIQgjv+v7qeCt4MBG5LJeqBh6iUIzHQN6mUYQUQ4lXb/uCy7u7u7u/fwXQSld3d3ff5QQkd+P8t1r3Wv+tf1T9xWIX5lbGIp6W9h5Uq4P1dfUSrFejfh5/xy/nvkrX/yL/HEq/2r9fX6av1EK/X10MW98VjiFv88E6/nr60aLpvq7vRc8nOyO+StF7v6/Qnv+6rscrtJxMGX9yWIQ5/P8/zyr/EL14hX9Wub1zeIWDP63v5cEnX8+DDiJZ8FmC76xO/n+I+XBZgv+X5/iPg0+X5/iPj4AAAAzpBmwAvwCpK+KgQOWuWuS/Qefv+Sbl8Cn+64lHeDKpUbup17ql75df0vnk9X71SpL5JRC7+fqf9F/S/8E/sBZ16EvRU6H6r1vm982idLyfonTV9RK9iFXxK9S/vkqoiuIqwL+uWqiaoGfrt78EObS/kwfbFE1zXV0OW/xPxKLl4PWvVxK9X/JWP1f4f+Gc/FgkLu9Y7gpHw7Dq5tF6KuOriPmRvnlojeWveF/69/+hOzFoXSqsDPCesnwU/BTpddUBxCP6CXuwJYR8XrF9deuv5kXu+sRxiOO+MirwZfDUES829VaSgIJURutW8NnqgnRCp4b0uEqV/wRXfv5Ax8V8V4ZEInvDPwa+gNOsLqs+sbkwW/BGvK/0J7L//+itD+Ir0X3fftsZu7wlWLXfXS/koj6Z+vrlxvHEL9WXiidfr2KJ8oZR+7A0iYdofRWI7tDHv0T98t19fcIdjhHcnf1y8tY2jt4l/a95flr3gR+KQseXYbOidCnCvwRr1VDsIVSKyrApjfv5aw8v0EH/V/n6AVY7HLbSxv4Jnfo7HiVS31y+/tE75YjkQvrvXoYwnhDmZVrrr8CMS7Aj7wqsJEFBxi2P9P7Iqr8Sr1QfDnwgi98PIv8bpIu+JX9cs+HV8eid7HyXcFYxVeuvkrkBLqqqq3Nf6wj6qN+Jr1fwX1c8M/pFfxj+W+RE79X9HV+oRrJ8f8X2pdI8VcH8E3gkLy5XiKN3UqM5fT7us7V6sFvt9b6vfJ83hl1m0NiyVQX6jKoI+n6+wfhn9E/6yYr4n8F8FFVdz9cy9iqxpK43yVfyZal8La9E/WGw0veCEQvS8fBZ9blJu6ogtFyksCHqvr0nej5UOUVtiCcYQyv8/jaK/gjHL/x4SrtG6q1f2IV74+CjCGsBAVf9b4QUuZjb/7rfGKIHgHKt6xeyL3QISdaJ1Xovd/f3CHxHoIIrGMU91jO3gRx3g7J8VJyw8IWLxNenXdox0kte7/V/1f5Vf9X71fv71fv+PnrV5RCLV8ES/vkRf3UiFeImvrviYu5fBhg5/uWbv7+/vEL94hZe4N75sFHX8+I4jnwUYM/n+I+XBRg0+f4j4Ofn+I+PgAAADdUGbIC/AKoIWDzl+X5flnFE66tBx/kV/klsB71fwIP5/wSF3dugED61eCn0bq5J+1618snIr/N8nWrz/Xo7eDGrwWDkb1c3zSl//vl+JRO1+sVP9cute+q9H/XNIvlr5KhlX+LggrqhW7Hb4jrv19IOJ3xi3+N7Af/uO7iP1vQha2Re9m9k8FJ/jPBD7Av5KAo6wz8GNF74fghzaoR7+vuZe/7kRHKL/+it8crnhn4V+GdYFyj7MapqZeBrrl3SJO8BbJe8dV+gNNe68n6//siM79feF2sUmJ+CD4U1xaL2/1frQmvhrEL8ZDfFfr6/Rukq7WYgCFDCK+X4S4bhXwKZegO/J+l+vQPzyL++O6+lQrviar6+k+r7A7ie/sdl2J+TxGtiPtCXhgQsdqjMfomVLl9f+BmP8vy6/+d93+vY4kn+fa9Va8qa+f5Sd3VfUnWj91q3v5/nyevSYMeLYSELF4VEIMmvxXx36tGZKN36I01cnP0CoLoj44m+OWRXf4Q9ghETWE6L3U/QzEYmjxeDA/gpwnxaFtfo3dgYV332vRtUCwmqrVVWt78ojd/q/UtDF+P1f9X/V6oIejyCXfjiS0bwJAe8Q65UZ/18Vy9gSa93KvVzr18vt76/BP8uGdC0JqENpGen+CG77Hl1cO+5DqusK/BoG/jK9CH/V/gixsWL/fCdDiCi5XUUr9X2zr47ter16ThpC38lE6ueFeeTiY/iew9V9Py0MRr9SfEfgkKqqrGvmV/RGRV1U94XFb+CDf6K/hV1xNWi92iPY5f6wQewiDO6QZQnq4N4J6DGuXoCWiCN39lnz8fqgoEVeSuuI/Xt/1xN4rEci9WBVBQhPdevr4IYJq5a0K6/V5NUXv17z+wKa7fr68US+wL/GLt19g5JLlfiUi14kRXJ7Iid8XBN6EP8mMW8uXVBYfJsT3XQIPWhb9fQo3sM+ghfN2AyQTVjxHxFDER6grzpFY/VisFi+0SsYpcMiquLBYHMYqWY8EyV6qvNvFVfuJriUXuo/qZWOtWMQt4RV1wyIRYUHI3vk7m7rwQE1xGiZdzrH9llzZOX2JlqqGEu5No6O+IWCjSXqu/nr63Rnk8Rd93zXLVfWr9cHH2v9f4hZrvEL9xNA2cGXz/NYEr3z0TEYKsFfxHy19fXNX1zYKsFnxHwIHxHw9AAAA7RBm0AvwCp4HHOvjfBDgn9BZ43uK5Ebvk+T5K5K7kwI/wZ69WgkxG+T9eriK5IiolEf5V7EK75Oqrk7jO++XEIvy7/V5MEuCfRMcT7HE2pfJdzX611Eq/WiP1eIVn4n4lcsYvvl616W4zv6pHebDul8T8IwoIRYvmWvNiuZGfFE/MsXYL98XWB9Xg3+Dei94Je/Ap/Ax/n/r0TvOl61/rq6FIt5/gnr1cEcMc0RmxGxC9/4JfYE+rmr/sf8focQvsXns6IpfhH9cx4IUvVl+J/Er47A/+wJ/w/8M/BC0KfoHLVzoT6+ovr9C+otH74nt0Wqw6GPgghYQt8IYhZMV/r1OqVYEj1YGH+pVnsqxXm/Eo3fEr5S4YiOoW60TvFiPiPiL5ZfXpMvoEvxXw16CtC4vj9/AgQz0vfCW/7/z5sRup/l399RPWh3eIVdkLu6wY4nl8IiUfWv17X695RaJ3tr7z5c/9Hqn/4rCHCH0vUKX5qEdP3R/dB/11hHE1Xtb/u8E4xJL1XvtEeIrqopld+q1V9V/Udr7+/l3/8q++EV6tte8ilwgI34uhlQnxeMhflCW9YJxPyzc+KIOWvnV/B4J7D3wQULY8OBCuPk9G6uRWvTvuhsaSMehRMJ8X801Bv5aN0bhgd4JhHyfJVCQn4Y+2iy8FMEQhV060EQR+BoBT4wI1hD/Q2JFPgt8WG0R/i/kk5JRym5F42UXleD+jd+CMVqvQl/yS88fk1g+1oV8IfFUusFovVVXfwSAkRHP1/v+qBKOrC/wz8FNF7w3+Ve/V/pEeqrrV7rR+6QV6E5PBCOWvoU50L6uJ+/ZoS/7Vvp938XdT9e8Mf9E74m834tFfwtV6q0JRXVgxJ33isvFVwTwz8I13V/J+h3dfhysXhUIeG10DUR6H1kxA4gs/9dgIMMK3ix3xC9Jx8M+tQj1S+fX+qqE0IiZdJWOl+EEJ7w2gR3v90/T9fwgid19fxoIy7u2OJSRjW3eEyYvT/0BD1xPuhHfPfFwj6FvEfCOB6OhHeDou/1Miqu4U84QWObvwQ3fjlYuveReX5fX1Kv/BZ7hDvxiK9IoyU92xklvhpUq8cr/HIj9dev6HLarjauKhIQhc/wiv0My+YEV3u/7vd+GhPUSr33XdjEf+70R+ohf1xWKXEL2D7Xq/cSr9d8Urw38f63uiqq5MuvV5OREe6VX1/LUTiFcl8OfCXz9/fyx19dw6IWEvlxH+EflwYYLPkxG/hD5MGGC35/hD4Mfn+EPjoAAAOeQZtgL8ArIxAqdrwED1/S+dFaCX0EfxeBOohV/KiR/lvlscuLtm7175LuIRX765flxS44l6q/wKfwKdX8ENEaCipJNqT1eQQr13LJ9ev/1er5KiUXvkV++SgKdX2vwUXIjdiF6m1V6L6T16vWu4ZRO+derlk9e+kXviFfuM+IrkuuZr8N4QxdRHXXJfN4/JUK1y/F/Gr3xfxK9VAT/VWX/5l75F75F75vmXrwX7wl3/CvNPzT3EXXXJfJ+vvCfx/sO65UJvjVZzeBnEK7wI4e8COEugNYQWLogR665UIfwvVzwvXvDNe8EPwz8I6wYeovr7QIcnqmv/WhNb/hLmmupamXonZ0dvb8BFrwFb7A9n7ClCIuxzWL4lE6UcrO9U/mE3hz4ItYLQjr1Xtcla/8I9fr3YHcfNgg+CDCQxF9jF18dIIW6hra/N6P1aolV0hTFCF6A4Pr6lRpfJ5aP3y/a98SveCHWC6iPJ3eNovrxQj5dfev+xPvvG4V4iTjkNisRLFa36CD1k1WvS3C9P5/tEeq1Y60djwTVYv0TuoqqiPTR++Re+Tf/evd/id4fo/VwYwkLY2lXvEL4EHeE/bDNL54zesFZa5EFnvnkwsLV/Cwn4QQlMuT1DROqxxIcfUb+JRn7A+htXuhPr6ZV9XdXEq0mCEEFcCDCPEr13F6v/jfi6r6/lrnjF8dXEq/nLVQqhNfH/CPgSAS/J13wt8GCv+r9wn1oR3uv+l6XqW+RfVzr3jA/4JQTdwIPoMQv9cVXGVnoX0cMQi/xGIX45X6hbwwEPhARVVqu60R/1f5qz6yhnyuq+v5V/8qK/Uq9jlx/lum+x7p4T5Bi1hHniByCOpO0V4tXE0CQyrvjERWKWBD77vwj8I1fwhV+4VRH7/H1/8nyeLMi941L2tH16TIPqvrV+uqfqXoWP+LRevOGMv/694eBPCQ5f5anhHqvquegIoiXCSV/HcUSbEMVX6fxn9XxROKJdbEeFxFer1wnBP1f9OYVu5OwTF1Xd+vHmrlk4cQl6zaGEiWlYol9gJUKVi6uewt48RBZ6nS7AqfB5RItfCGuJ17CCuv0/gnDCxOr3jlKs7XrkqVXsQtXDCL4vDvwc+oY+L7qbiIKX8l8J2uf7kQjx8i9Mnu8Qt7NPywYev/uueT+uS+xSwc/9fSGPN+IXuX5e5Ypf4hYMfivkw51/PYED3z4ewVfFfN81ffNgwwV/FfN8HHxXzfC8AAAANlQZuAL8Ao4xAkdosYo4yeJrRGgv5IjlQuL5YjBD+auTqaTlrBnrBD8CHgl5I31f5a51fELLzV8nLWDv/XwSc2/0fpKBF+aua+b5rqJXr5dLLfX8TJ6J18iK/0pU1199P+Z/wQ9fP+ieqvrVpfXv6wvr16uLrRfnXL4nwJfoBC6/sLhLsK+79kpf+Cf1opU68Qrp/+N+CAFcNevfNXNXN/896r67DYheoYvvY5U68R8Z4/WFdcaYu7xax94HGuY8CSHPByEqsCn7dYq/rQiOegn8WsXQLwksXhlL064T0NfGYrp0FRC3wsjVKKJV/MvB2Ok09fP0BPCPjRPhX7onfF0OJNTLL/+tfEdcnfgv+Gzy4Xdevfr36L1ei92EwYr3gnwo//m+K6/nXpRnesd+Verpev1yn9Durlk4mu16VdS3yoveyovfG/E+J+Jf695f6+zkp89e+GYVEI/6J2OXV2BPxPovRWqFPJoiJ1cuX5/1/jiddqr9aKx4Q68VV/Cy82u16fG/j17FE44hdvgnhU8XQpfnROrH16sbvdejt0Mcpd6/vnpfdYk3cMeCAZr00J/XLNxfyo3XhXXBPjY3Ey8I6/hPj4V475K/274R+EUMfXDYFwEaKw8YCGqrc6hFEYocTb5vhzHRZc5/j0Z/0R5NKuVe+J+J/XuoK/YLEN7wU8UTCoxEtP2vRuYXXP3J8V8Z8R4YHeIGIydKu+IRHrDPwR0dzwVhlFt8I+Hx6M9aUvL1XWj98Wid3Ah14JBi19Ct3COkgn0i+q50KYqwgG+rRH6PV6J6r/1xHgn2KIesb+VCX8GAaV10G3JT2N51Hh/8F8JDlOReFeST0M/fr/7V+q+I+I3yBX+j95clIG3zTYz4jiiW+PHePFeGxF8IwRevVl/U312YVu6Xz/lPu6y0fugW69CO8o1XrkR+xcuc8GwIOvwTGXKsJ7x4YV75PBTgm7rwRUkv1clYW9AZPgIoSjFTXE+ufxir3xAJbvu/XsRXondcvIivXeOR2ovhARd933sVXLfPBbU/2hHYxRA8bl18T8TLX3ffJ6J+I7urguvV+te3f99ej/70R67V+/vV6u8QtcTJ6kXileIWe9Xg2/7lXJ/PN394he7+4N/kw91/ECFnw9g0+O+XD2DX474Ovjvj4AAAOpQZugL8AqohZsB40Ch6wED1/QhYc9Be8T6N0dyoQ9CCcQrv0V+4jv7+9X7kscjhcfVeCH39/fXPBNUl3J3xPPNdW6fRH6mVtr98Sr/L4Ty8TBHonU0nN1J8y98369P9YHH1EgjNu7+Aq1jFZxVy9hkyP3Veha919XfEq8vFw5hDfo/S1y/3FXzdwt4/v+n8X9+BbaN3698y94Ur6sG/sBAl6k7iPKRe8frH/Bj7A26qJXvBl8P/DvXPwrzS80vNPU1c0mWvdghEeJS94mvVj/g4o/fKuSrhci/y//r7oEv9fdArq02L+NyYqidVaxdfUNo/QnzIjS1S9NyxGb8yO/6udSojdaM3yq3gpL8T8tbP4nWJ/IsXoZa/RPSqqvoCuJ8K/H16TeF+MR3xC4hYqwXYhcSTXoUdRXr3yr1erVt/fYeBCi6xxJP2vi9fS5a5JFauXxz+0Tq7Xr4nwvQtz42TH/PXuwMNeoUSoS4SripOkXvF6sE+sM4iyURyI0zEfVctXaJ0nN4FL4EIJTWBLovvBJXv197a+7A05c/X/gVwIEJfnYVkwc8dGaq5fCP/vWorE7wSlQp/TrwR1Xz/q9VKv+ovoN/lVi8TqgYBpC0q8M/KhH/1/+vKvKvdBmvfa++79fX6P3l1wVwqMX0n1fF9KytOTiVYy/L8L3xOuEwPAEHw8NRHSP47wU17EzjmPCvsb8vS9dct8/zoR1DY2VN/FL3kwkviZKiZPhDDxUR65PiPiPKI/BP1VVVX8GH6Qj9ZtYdHXxyLl5d4719d6Eq9u+Bh/XuobhSp5ueTbRei34Y6+9foz6/BHVd/wRd3Y8NkVjw6I+vm+Xo/5vkrnV/GVi8wmTaqvr7Bn7jZRxLt5gvXBfDPzYihf/0I6bwUVXXdKl6EPW1Q4lSJJWr9DvQF0PddYihPeWvVQbJ5slfUI9fYV1inWUd4kVfHwzuhPXo83oQ3uidfX6Ed8nySL57rKfd9Td/Rki9v9ekr6CAQ+He9XPspd3JQPw5XEeE/Toj/Pb/hneJ05PVq5PlX1L9Er4lFv9rfXCsIdAMMCApE+OUjd/WidVavVBv2vWjvjkSx3DGsD0I/hhHSqMVXPQjwT56nRv9fgwwz8fvI/iFeTnva+Wr1fFL+trFK8YqviF+I+IiL0Xoa+P1iOvk/up0Ie+THE6l7nvhz4/4oQvU/z93Er/ELL39w58IfFfGiFnwYYb+P+K+O+XBxhz4/4r474Ifj/ivjvj4AAAA7hBm8AvwCkr4uKELiFiMDzlXywYctdxHoOf7jO+q1f9FTp8uuusE/wI/wIOCPHfDGqkrkk5Pa+SRfE6/sQt9I379FfuSrhDqSxBOIJXcJ1XBDjs1E91N1XJY4m+v8QvUI5PVKu78CXk5Peurqa+JV64tf3wjDnNS+abEV6amIXvk+l6uT5r4v56ycUT4Nfg11/0vY4kU//N830vVgn3/lEXwRwReit+vf1y16N3xH69r475FboFtSp1+Gfj9cKoTn+EVMirgU0uXQHfWqvWDeuXQHEqtWG0hHvBGXw/8K16rAy17v8N64tF6q0JbvBEFnvqFPQvpBCxXoT1VzYEkarHgvF9g1H96JXx/y+xq99rr4IARXfc+FkT58IV1M/0L7xovW/4Vy4R1ivhbCfESc18VXFdMUrY1FDTLMVyy7ohVTd96Hd22vd9WBBr3yUOJv8/zXpKVJfRfXnF/r3n+8i//RehOoqxC9gK3WL3ui98vQ/8T5Mu6Jl0lWRIQ91fcqv0CT1fcSr/SvVw73JiiaoGHx3oFAY6fo/qTrXpcg1F79ffKveN1p+F/hnCvoeVXfXonY5d71/Xq5F6KwStCn/7usCES+0R75+oXR/uxAvr8KDLw2F/CeXpe8L174lfVh34Rr18NQlfFb+JxXEX/TIrHcSuY8r8a65/nxCtcCQCPoUbvXsUTeCcQiv8E9WAjwS9zIz1y/a92BtHyL/4vf/sKw58XxFaoXfL4PP/QDoEoz9fxysa4Wv4pWPjvAjAh8/wjRu6de+audX8ghFfwgpOfy1/Loq9jFaj+FKL3hjjiXc8FeEueK+NfWsf8xKqsYtKlj36ft+J3xCM/URWhC94f+x9ZNrhOuoQvlrVC/1l1wvVQMMK86/m9em9eiqllf17N8R8R4TIveXJiPk44l0uOJt1CavJQK9CiEfghr3j/QFcJL1cfCPaO9v9XnqVem00Il+i9ErqXTzyoU/3VgSAU9ot4TJWJo/fr10Ewt1+Cn8T9SYsII/eGa9814INc6GPCXoe8T6vE+jerC/6XrwUUXsYoUFQXjFRiJvrj4MF9q4TgowgoaYjLb/3DgIb3xSpKfrEH70V/lrkxCK8UiLEL4IzVhWiPiFSdcPVxGnNgmr1rYi0TvYRuuq5OWuf9X71f7go+OvVjrV77V/lpYIv3q/2r9T9avKOJV4schN7y0R4K77EL8vyxHdiF+8QsG3yfWCL/Ngm6/nwccQs+HsFfyf4It/P8R8uHsFnxHz/EfBj8R8/xHx8AAADvUGb4C/AKiIWOwOeDEv/zoMdjiRLl/lrAgZdr5Ebvk+SuT5LuWuVHfwJ9X6L/V/BX7iYKOSriK9G6fi8Qvyr/ELfq+rqkX9cnyfL+rycvzfq/XXEwkOX0nNL6E9XNGclcyFdVTL3WvXz/1yqdPlXvA917wLui/1G/WvV6v9ovOpfjv17uOXvmVj6V79eriFen/C44hXff139qv7sVr195q9ViKJ369LySddRHxCJ3hHvfxRPy1xPxK5dBn19fQGfjFd69e9pe+St17wy9eF9fJgqD8K80vNXo/RPr18nyI3fIvfovvCde1+jdr9ekXF5ht7xuexc2LJPSm6iER+vo3sGfr6+tWdfWjRzr6CHsDTrNRe9+vwcawSAhR/wpehXfNE2EMnMhMVep1W+KdHr6RmPnxiITIx8vgxP8q+8ole8f8f8T8I1ipcV3Toz9fWvda919UhPfF9fV9G/PPQM8JdK19WIX9HOlXFRXnvyavl6pfaCDfYIe7tJz9Qj8X8qv8WrFVJq5de3U9aWoV0vL1L19S9aE+/X01gZ9ZDQqIRfmrhTx/rRfeLxeXJdX2IGJJaWq5ZeVEf564hFfwMhPAwBjwXDF/4EAQiRX6L1DlFxVFtc/id4nDVAQcfid6q/3Xq9ctcvy/Kr/Or/F6wj0d64pX8ERF5VHKX8W16N1evSL/4nwzkGxstr+EeP7hn7QjvhO8P4/iKL83/cd81Y09Y0TXL8Jr3gmDK96oj/q/x3l/JjJyEe8HYpfmuE9X/RP1y9Al1y1y/E/E/Cf6F9v7hTnq4/HEEWm24rhCs1F9rB8Tkfwl5BnkFeBACatfJ9IV+8E+q+g+DfoMBCWv5UV7wyJ7Egx7++FP+Ixi+hHoEIla71/6M9Yfoj+CFfdr/of60R6wQhCsN/J83qF+v9Cf+E+X/Bp0V/jUbvlX/y3m9BHjiXljifugLNHzwqKWeter0Xv16K+e4RkfXWf7oR1HcuRbt/lwp6DebKvFm7HUSULCFj8teu5JF9yL5fAgBlcq2kdjy+h56z600R4rYU+I+OX+MJvXDHx6ENC28Tmoe8ndaS8ieWjdJ4JN738GlSL+IUiOvGLH38YiR/ill19SLmL55aMbSwp3gzo7nglEK5YhcQsNfCnrFS4qrq0Z+569f9aL/oZV+9XqnV5xRLxCzK/RXhn4XX6Fd7KQrvq9XvtXq9X7/1fFEq1+sfHImu5LELNfDHwxUvfJ1d33xXw79Y76w+v4n5sF2F/gj+I+XBhhj4I/iPh34I/iPj4AAAA3hBmgAvwClL4uMEIFC18dXq8uBx2X/ieHfQX/fq8nJfNdSRFSxHJ8iEd8R3r/5V75JOX78EuCTHYgQtckuDDVfzoj1y6+eT0VirmvBWXuRXrl6l9Hkf8M80uKxFxFclVEUOJXvmqwT5ONRO+devQn51yp/1yfJ9ITH+lfql/111VQj4M/UI/CMI9L0RXGX96J3114xEX0nJ83hf818/z/Oi5fP0BT1gx01k62vm+IvDZNfUEnNWb5vc13yDFv4VSueEfhfeE69u/8GFHZ+t/Am/Ak174WX3jiL14P6J74leb9E98it+vMvFL8+KWLX948nyb9YT5kfsQTiFnHL7uKq4Y7qI50J79CHPlRI1YCBfQPS+PP5T/KvviV90CcT6Prjf4pX+EER74jxe8GOsG4ZR/eC8I+DkEPYCbBX49+NL4X+CH4J6L3YCRE+Clw//xP69P92i1poU/y/L1PLWr/Ir13ei6/pfovqyaxZ5BbKL9YthRPUK8V+gr0uE/2j9HdoIP1z+r1yeBOfgo+CZeCY0vr7oGva/JxvYGvefCXr7GR7SVEwJISiMTiMTV5O/0OfxVX616xCv9f/E/EorG/CORfBl4eor+2v/TVKvonj5fkXuuXJvhWGce5MX70fon16TW6BONsYjXxC+DgN+DgN9Wr2KJ18L42JNF3sIq/xPSGRQnDD3hX4K4SHI3oYGIog4/2r/ICK73bEIjxShyPzfor/E9fX48tcyN/4he6Ar5OPxRL6iJ7g5QnLt/16CiusHDBJVe+IRl0BJFbWXiOkSL5li7AyhDsT7NReky5tVeqD4/wkDTzCvCNF1BE9dfS4r9Uu6Qp+vwOwv6r1/WL9R9ei9WF94Q+EKO/YKQbVj30Ckd4IvRfmr/oN75vBKHPBeChe8GYNPnhYcqtFWbXr73RnL6m7Rn/N3evi16s9FYug+vNv1eqDLyemn/9hDY5H/+lTqOJeqyjvDJpS//oU8EPL+i+koPvrvCn9Cb7wKEBdBlXxiIFHxl62LgqWOYhEe+IiFqqmqp4i0CBC+VahDq/A9iqwnlqeCP0TopcVXyVyo0e6FV6Tn+fu0V+67/n7hPsCCPRa6lRGOuJGKqVAw8EnVc9fEjiE1OIVyc/ejvBn8nf39/d3f3iFxCwd/Ngo6/nwIHELB18/xHy4PMGnz/EfBz8/xHx8AAAP3QZogL8AqohYiuCH0ErQpYD81y/FoU/3EbXzVyVgQdWAhfYLaK/SE+BJ9aENBJhTXJNzeiT8svJ1N3Hd6O9/dRN098TCPET+hL1ev65pMVrkl2SuS+sv8v/N8k2BX/EoZ3gx/KvfL8ndSL9Cep9avdLWtP+Fhir+7m+Ijn/Vx3ejdiifkXroFOsHX4v4R+J36EouVUBbXX19f6J36+6hBe616l8R4d1f894EYIwjzSiEXEL3r0nERlxStXJS+OXugY+vwTi9L2uXh0I0Nn5Yz94EME3hUd4gklfUnsV42hj/EfEfEeCn2Bto/dKsVcXRf/wRGe94Y9CevqK9HzVp/L8qFN8ateBBP2BJG/For+MP5lWM1xSJF8QsVWDEy9fonv196aL1rwT1Y8HYf8G4f/ROr17wpxRBPYEP4W7/hLmxCy8ldSPEbiuRBDrqXrteieK3zoTG7AbYr5f18ar16udEKn3Xr7yhn6Qt/ECqxvxLmf+8IeEOZG7qSTju4IKu0Efdgj1t/OiZRXJfIh3Vg2JPxdYCCLiEXoKLquojr6+utqXnVq4u34Rwj+LiyZ1+ilVT3+wf/J83wu5PXp6Cbrl/KO1Umar9Sq8nLXCPQRC9Y4UjsUvBhXx8vg1GyL9G79fVl/r15NP+EeWUQj1evR3GdhETXEfSEPWDUbNgoDfggDfk9xl8yPH8CSVFfw6CFXP0TqsCTXuoxX+J6/VG6uesn9CexqKSEW/4RqJQjrELJcT3y7oT0Xgg1g/+BUoj+Cgyt8JaoHe/Cn51f5qwk/jkIeubw6IR36gik4mvX/UQif6nr1fqE/l8nwR4Sr65Oe/uon9C+vaXpugTa1Vd14Ii/aEP4LyK/gxJXEq/6v56N/of8SI7Ahivjqwua6Xw00d/Nuv1V/EewZ/HaoK7w2EKHsN1Wvwx9bL1oIfvEfRP0bBSR/+nJ1NmSFP8R3+X+j94RIi+8/oGfo9e6ehxLb+T82MUmP9K8g57+T8LVz/Hwlz4pFm3sct5/Qr3l+Wvy7ktfozmEFdKttv2OIUOIxtC/ff54I+75KtgagzeJr3Td1E9fhoKIW/aBF1ojkuLq9cQvdav8+MRnrX8M/6oT+J9CveFRKL2uTZ9VfIiNeCii+8HhdcTCyxYhEJcv/4Ibu++uGPXCFycvV+H/YMff8Lovdav1q/cKdyIsXwx8V4b1yfPDvoQ9eivPp+t8svaN3XjlE6Dc6L1eyVgXAjOIXrV/df4he9eh//0V9/q8/JXJXJL8/3yoQ8VcvXBD/3Fck+1P/1XLHXff3w4v595Pn+f5cJfWfDHELBF8V8/z/P8R8uCjDnxXz/P8/xHwQ/FfP8/z/EfHwAAAA6ZBmkAvwCu4CB2viYe9BD8TyVyfJXJPy/LNUnyfJ3CHyVSESYCB9/a3UTCghYr1eqFavukq5L+fnQzrEL3G98lyK9jkWm6pX7CxpPRHvBD9CV6Caya5frrXquKr19jiVesL75ZOJ8DTqtEy8vqIRe6rVei99rW//kXu9eq4leuwEyb4+F65MIZvXrtNWrTrqTmxRPULdev/il6QcTf4lcuwFL8F3wINE7wclvKSuT6XvkRe7A7+4nr1cTq98TDdAoxOOq8lzfFIidLZPCeXC4nHEP79FfEK/AohJe6BSFFqtUTvpfVg3LXoR3yL72KWOfGKVNcR/N39v39RPU8NCEeuX9H67NX1XIuXpqkQjsEJlXbGKn/oHo3q1foIeu32q9f1sl5qN6sPvfhv4Kz+D8EPg3BD4LwvDYhHk5tdSWIj6x2fN1yaCWY+quRCMxd6O/VdGr3Wvdf698tc/sysVy0viUTq5V6TiJliOhPWd9YzwjxCE9jF1Llr03yvyWZ71urkl9Vo0W0/+VX+l5Vq+4R70R6uCHqE/tXrB0ZC+7jvCz+X9COr16vR/S8sK8I0MQmkT9e6BbnobjuQEY5V8vn6usCoRXvnrAkULdeMWNzfd8I6769G7fhj4YVc/y1y3wjCYxCyYdPi64ToUT8b0F8vr+I4Q8tWSYXoY/hMSisdBEvjt0UM+BODfg2CvV9gpdcqv4KQl8NY2cvc1/4sSjP9168qfLeJr18CCgh0JXH11dBWgn02ei9E8KfEWMUXesMG31DAIru7saqFtiHd7wIFFa6++qBaEugS1fxB9/q83L7ctMFOvfe/CVfzVxFeva/Xp6EqfY9FfsWvRKXxWIXx66BuVCGN4dxnUiv4QrF+if+b5Ff9f+F18ni82HQj1xT/hPv5oT9Y/pfyV4okYZ65cHYYrE64uI5kNfoO+iC7FE+Sr1gwPCPL/8k9aI98ej14r+iftbiECHqp1TVyiEMS89F/8P/0XKqe+7xQV+TwwEEL6xSnouToGYKFYxb+6AiiFfxYxEeFfRcopVz+qvFUF2idW2vfS9T8Gnww9cTq+uWIxiJfWAQEHH4DHB54RCy9+vjsL1/2y3yyc2MQ85Bb5kTxJXXcnFwQ0bfLN82Ceh3eG/y9/fVssnaL2u9WJL/iZ6Bxh3VHeO9CEq069N2r3yK81ffYhayqDT4gQv31fX1/cV3Bj8T9YKOv58F3ELBp8T8nxHy4LMF3xPyfEfBn8T8nxHx8AAADx0GaYC/AK/gcdL5QQhrd2g14nELLUR8ncd396tN34P/xKvV8EOI1RsSvpE6I5aEKXIpUbrV5akR+mFE/KrwQWbJYr3y82IWqm+qwvk4lG75/l+JXKly+MXF2BZq99L3tfSE91FLrwS9/3cI3xsKcciVFXzZK9dAs1Ui9XEV0vYonXvjif79f4pX8Ir3gR/xK5dgKU3QZ9fX1Oid19fcPVl0v6ddWvzEe8PWT2Wgn79E9OOJb6TiEZ/dfeGfQJ/V9I/Qz1ovfPjiF5YonXWsv195hHSonda+617sGZO16bRu665Ky/BP8J/mR+hkYSL9OqwpmsKZOS8CCX5fdW6+l6GJE7rrmJ3eOJ5dgMkMdxKJ1evItH9fWvuhFF7qJQn3hqrOvo3onr6usI0bvBP8F9F79BboV4qbpBvq2LvnVorS6/l+/0EPVy169vn16biao1YvBhXuu6+l6+vrrCOvQroT9BfvhKubGLrw73/WN/cVdIRcrRK1W/2r/q82F6J3xPcNq9VE9/gwXU3UQiv1N4QokXYPgYdIV2BD9fX0xHS9dZKP1HeFDxOLi6VaBru/+MwnMOd7yftxH4I73fmTGIQJ9BT6d9ycTVQuvfHoT14WN6aK9cahD6/XpK+vr669erj8Wwg94Wru+r0F+rRInyEd/hkL1zK/xl48/nLdwQ1jgyrHgmFq/V/GWMVf+BHor/G1qjP61qidXr3WvdfWi9Rf/4XvReu3Xqt43Lp/1hj4OK95wgiMfHfN4UEeSr+KHdaI9P/5vBCI9DvG/H/bQn+MUuUyNc9VH0/BHXXwQwtYEvEej/iNRxFWq1qq+FSIne3QxROlHfiAQ9VTrgjNXE+J1l1XS+I8HYS89e6BzXvFcUS8cTbFvr9f+CsEKKxQohldzdz+M+GKP3nwuIWIFyljJU/BcatVWvS2Ky3VDiCtS13QE0Z4UoX75UTpNBmbl3vyYZBEit4JwhDHxXo3q3WOeWrnnrF9S8t/86J1LwR8n9fCcJeEqEzvHil6ny9cqI/Q8b4Sor1ivjs/HeEd8fC+sTcSven6dVanV+vvb6D7Xq9WrCHwJDRfa4mXXEyIl9cX/HIz/HLH35iL32vRWzeCahtf1gj+HSTcTC/3cvbcnozzV1y/onXX869S/6lRP3UTNVzVzDEN+L5/mhf79EfpZs2S+K2/ib9GeS5bvgl+O+1/91f83U3XPy339wTf4c6/jPvEb+QZEe8EH+bBN1/Pgm/z4OMN/F/WIyfZ4J5Pn+I+XBxhz4v5vn+f4j4Ifi/m+f5/iPj4AAAO9QZqAL8Aqy+IxC+Anc2BjwS+gs8RckIcmuuT0R+4r5LwIOsGeHsVQmo65EM7v76ub9euwOXuLX+MV8qXxNctfVx3UyK/cIdyS/a/+VGeExyF2IT9E79e7iLrV/kXu4rr+b5pbhtE6udepf2+pK0q6kuWTnhXmQl4jVH6XNmuqGId69kk4he/Xq9FviF+J16E+DleD2vdAafXXr3uveJr3QE0/T9fgpy8SQz3hR//PXNHWO3yVUiL1cV4T+CU+v8cTzHhvv+uG/BCLQux2A2wwsuwRa5ET14K2tVxHU3TN1J+jd+vda911kwqIRfiPkxBMJXJVAIN9XeTeN6/r5uVG6l16+XwUhGvXv179e/XuheFeIriELfqojpCzpPkoQVVYQoV3cnXfaNmNfouXy1z+Pr0n2IUKvlQsR4jWf73QPWj9Xr3uvSv+FPvmr0Ll4fUnr0TX3yZPUvt1z/dPniaHIILE2r49XOvpUdjuGFfvRH75fX15a+lf8JehrUM/Z2JiKE4nF/G+pPcwSqq+XwQnqv5bEIQfPOr1x/koXmPQxX7+4IvBs0VjwbgQV7wQUZitV/J2vfE6/xxPv16rByBP3/nYbhIQuKXuE4RwwCjwmCFBR+5a4jHEEGxItZNK9bUter+6/8ov4tX8FATRWeCwX0SiPeLE+GDIr+GaLzrhcFKueLCPhjVAhy6P8TXCed4R57uq5YQrrZPuhC9y6oEUHlXYQkFH7+2347qbwTaxmqk9Ub/jwhWL/SP++dX+f9E/XLLxPZgJaF18PwQerzL4+rmRmr1fEKF/tAdQh4I6M8mK16/rRF+fFeV0/Nrkk9Hf9Xk5VcrFUXsUTneFRiL6IGZ8qs2/BGK1UqTX98RjqM/ia90J7XiKx+sT7Aj+yrFsXZXq+OJtWSrSevXlCi9DIxFxS+vTehXvLV/LXq9CCp+pU77u9LxNVFor779/6x+EwSF3fLXg2HdAnDHkr3y/a93q/er+BUH5f/0J14rfE1QMdUDEMLXRKxfHQQ2Ky9+Ez7/RMvC9XOgf/DO9LwefAxVi1QfCIFsECxYxS0yxiMMsjKPhAEN37nwp1yXr+rKJReu5tv9cLdQorGX//5leUciXhMYhtyLvvSRnk3ROkw1qwQOTpSp8v2qVeVX+Wtuxy271eSuuIRXxC96t8kgwm/c8EmK0v5dpc+/u70IqTkk9X+WKvxSLiFu0bvgn+TuYQs/Vd/fdwZ/eT/Pn/zYe6/nsEGC76wtk+TPr4j5r++C35vm+I+DT5vm+I+F4AAADqEGaoC/AKYvi9fwf1J3oPf/X8nZS7v7+axCjbR5ZPX/Ui+OtX6kxRM+CX2Aoe3+GBBCqT0Xq0t78lBB1qjdMvpG6qmrkv16xCxHNXN4N+2o5b5fQletv6ugk9Ce7KRXrk/Rukppe+T5K5OwT75flXLqNXqwJffzr3QCr1ySclYN93E+H9P4Vgj9F9dsyvjidXyfXcIXxX0jd4b+xHh8t4FE1ZPhDWDmsXXfNeCf4b+G9UTWBCCcJ1FRWOxnJr4UQk6fJ7fYFn3ojnhfS/81eri/AkhFCTP/U6fIvviET30p68FZ/Agn+kb3xiudgeX39/hPr6qvvhb0XpOS6mkeboTNL6x+tbHxCNF/XFkMq7qfsIie77EfbXvLrjPhD5q5V6bpC3eDsX4rb/vEaeG+YKLWFeWXpBXvBe+qR2iS//y2xCC2VL6q4nufxvy0f3zr3l36I9+viu16l5tUH95cmJ0LZsoV5a5UFen9FtFbX4Igg771VSd/o3fr3y3h/4Mgj4PCoT/sw7wRdfr3QEIFHTokVU9ei+8te8terKevX3je/0O6El8GKBCSefH43E/CdDnJ8I+kdCO+VXscTf4/wkEbrQlj4exsre7wZgzV/ifn1/6oR3hD4hr3tr339r3hX4v97/QroJqCAKsn6/9ctYffYCPDPhkShvX6I9cT+j/6BsCvrRIr5Ff4Q3vBx4MQXoS6SwIvWvWTM/4b4mL46uSifv/qyuI8GlX3xUIePEXggzcRWNoj53+X5/iVbyCfl7Buu9E6u1fqEf0XuwVAZ0WvHA7hMQsRl1i9dK86+CHwqJ3v+6s8DEX6Rn8PiPBn7Amm7+hAtX65ebw+I6Ag5MmsO5Km66r6/DIiEu0XxH6r2X0vqbuxxBSUfEEoHEIiloJUV5KAlhaqrr8SXxPf6H1fEVQtq2dxmnVX9V/R2R9B2uXgpBtC/q8ohZd0TvX8EWq/S8qFOWMUuPIIVKrwUhfyv9HOr51zGuNhjVfXr1Lide8tF7oSEV7rRX8UHJsXVysfXpOeG+efTtYX6xfojW1BP/0Xqwp8C5xiiu/gaqJf4rwXh72JZHf7r1+v/H1eq6suuK+MQt8YhJyC2IXoBh/kgi50MabRfluom7q/k4mXlRn+dX+eT1e6pHe9YLbur5PQh5K75JhRPg299Dke8v3gXvywUfN8ncveIX7k7nELBZ9YUyfYj8Rr4n4j5MCBgn/wpl+b4n4j7wcYLvm+J+I+DH5vifiPjYAAAA7tBmsAvwCrCFsQsQvi0GmIMvBLaa2muKuWI0T5v1f4j5F7qSTAo+gKuGq0f8vo70/5+kK6rm70I75Pa+Sl8kQIRz0KOUlsfJXq92B5LjFtdfgr+D/8XD3ERd9clZKJ1VEL3yfJdwjiEU9OB5+BX9AJH19fUvV9oYvdzd9X99iFev9//EwS+i+k6ocQR66jvkWL4r5Fi8L6fxvxaEvVfQ72F/f396EPtv+gl6CPt+9F7t/BD1/V8KClhH0frrXpF83ye17SJ7wzRO8J/Cde9Py/BKPR/Y4mZedR73a6/B4lfx2tV6+W+f4n5K3hpX1PiM/o+aX0K9iFXg1Kit8f8WveJFr3QLR/X5CfJS4r+Il7iML0Ivr+F+KvmuqQvrFoTyiPRny//oz119IIP9fddoT369XLVaLKsL9f6+WqAgboEapfE/PXr6XNk9CuhmtBfUta1G8kUX/+n4Mvgk+Cw2uX8IZPQQ6uTzP2f5/E0J7xNe8r38CzC+EfhPHF/8FP8FF3u77eG5b7/d33b3yIz12r/av8TW2i/8HwtF701ciPQjvuTm9Ca9H9v4GeEeE5cHPta542oaV/EwQlfdjoToYjBX5KuG9LqLLVfhUX491U/z4xWiqPAnB3uCvxNerkXqw+O8G4OUd/hf4vproI0Z5qC4R+XHEi/fB3C3xPoT36vNX2J5PdL/sYiC+VUl4YCQJbvd3d2PhDVQh9TeGvn9aN3WvSYJ95vju/m1/7avPwnCtz1vCHQKReq6qq71hFV0jPjFC58lX0R/C4gvd+Fat8TWYRI/17f/QEEIVQf9a9e6O/j6v86v1N0xF8v6nXWCnCt9XzX9BviUNv0MaReK79b9DOrqhi3xRKn5vBCI8IJDfniPiC9fRqLqvRv/Sv+r9gjyeiv0G8M/IMRtSc6O9ZNF/8cgQkVfMb8/z/CNGfGIgtZ5Rig3+zzL4n3BIfd7/YKCu7u7vMirscCHe8c89ffJ8TLw5i5ZMv1Trky82MRvQv6vPaEoT15qI/y1y690Tx9r6sMuvX2uT+QER3vc8E3wIjWLL8fGoIQTYhELnmRiL6A4gkV+nqomq1/LyXcKIS/g2NjEW3s3xiM/xHzQ16/J/n/u0br7Xq1kwYZKlquhRLk7V+p1Ylrlrhn5cFGtGQt/Ha9Ee9tfHeiZTXrl+ry6fcteqVdlViXBE/1fFErvxyLeT4d+K9GeM7+/v7+4jvu+uf/uHPrCGFPl+bBR1/E/Dvwt83z/EfLgwwx8LfN8/xHw78LfN8/xHx8AAAEFUGa4C/AKWviYwQvgW8ERfr9BL8Wvm7kkqSuStL5JeWu65ZtrtBCuI8Ff5L9CmrAj/iYIrEUJ6l2t3SN03onVpfJJUtd4xffEr/HLylvR3xxOuoqWkJ8CLrlhjmR2juSqmk2qqZCukvk4levn+JROk2RF76XuterL+ZF6/3/8sPYrEiiaXJ1zdMyJ3cIdhf8i98nhv4X7/ocrv8T8T8X4K/gl+BB+BNrHKHEm/fJ7XsR+pUrC9e1/8TVRsM+j9CXonzoEf4RrCevXvLsahYnl8YoX8WRcCiKRO8I1y+GljnhdXQHHv7r0IGKvBuFV7w7+l7wjXq26dT8OUv6G+pf08z5K1zTbE+D8I+Hz+NFojeER6t9o3vLXugSvr+L+KriKyE/Ruqp+voV6/Qn9F97S+r16sZ8MLf6EdCNRUwhC5H73is9CqlTrBRRzkjkkaN5J5LK+upEIY9m7v5b5UfvbX18X4L+v179ZUMUeXlVVwRa7j/J+WSgZ+vr6FZHhXwjWrfDU1gpLpfrCeq0PKr4leisFPpq7+lQSfrXxJzy4PhNY0RVASgZdSosVLSluvr6Xq5H+h3Qj/y4hB/GLSrg9qx0DmqVLCw6v8Z6iUbqxGIw3/kwI4tDMvlXL77f9X+70vde1+r+DYP/H+L1wx4IwJKFseHQz+jflr6+teqgY6wcAYelhHj+uTXpazZMU4h+I+KC6Esrlrk+fwtQhj2JrlvR/BIEVfq/pX616sMm+EsbEk+Rd+vfGI379fF1y8GvXCfxHo/RXN4r7EIz79fBt8CMlfqK6HfBMwT3e7vu8KhB3d35RSI/oV4QP9or3X4v8QjdWWj9v9erCTr1f9Xr0R+rk4mFPR+/ii/X8R1XL8he71xVqzL/8yM/gURHzdAjJ1m7vxGqie43v+bwRhD2asuhbpveK1nHo/XX1onXjqP36DFQp82hMR4Iwmq7kt8QKIYhFcvk9Iy9Zf/0L94+ve3+vS4v4f4QlJj/0+h6V+hvHEu2OJ10JS2xT4tm1CopY3XXykrqW/uu5LsBNLwMx8YhT5fLr4n5UXq51z60F4a6qTQu+HEL6+S6/Bjkf8LDES+IWdfo9da9dz99ehDef1r1WCtr3hMT6Ki+pJ8LIvsn6++idrhGlc1wiLNjEYZ8x4KQx0AxwYV2vfr3yVz9hwb19RHf3or96v0DQ3yI7Pky///JLcMwvX89cngjo3d/XJVXYk93E+ldWS764muXqTwR0bugS1/1r+tlkpb1V5FxGj95OIV9xEOfVTK9V1zT/Lhj9/LV6Ef6lrl386K89fX3wS/fJ8RE1y/L1IIWTuCn/CH+L+TDH+YRyfJgk6/nwTcQs+DDDfxX3m38T83xHy4MMOfFfN8T83xHwQ/FfN8T83xHx8AAAAPgQZsAL8ArQhZcBA8Qv7DW7gm9XrkqpER65JuWqvqf5a5bEL8nUR4for44nVVFX34CBwp6O8NXEX0hXT8tL5/nkrvm7iPBft/1f3/Fr0I8iE9Cg4lXJbq6m+T5EIi+ZX+Rek5a3V64le8Cr8DjrqTBf+IR3viev54S5q9XjcRiPXrELNyeE/hnX/E44n2KJ8Eole8dXqw3ROv17seGqwj8F/77n7+4mGeIvCW60P6/RvX6tEcVVA19fT1jdUH9YGfl/BR/wShrxWsYl6sLvw6+wnRpz9feP3mwvzYpYmhWI9C4/6/rm+S1/r9EboLn6CIlW6FjZMPC0bqqGliriawnROkzd/X0hLefWWhHV0i9rxde89e3/CggmbBzl0ZDfRFyAjCSMt/ZPf+8WRGW8tlviFa9fIva/9JHhdSr7p19+vvl8b+J+17yv7Xq9eVLCVf0vCFW+eTCdH97r2ute8S69Sr/X2/zDlrCdwl33wsgrFe3dCaKVP1qMqbpOuqqe/QU6+LxxCv/oGgI+oQ8ECQnu4Y8ZpfFoRl8tVrL4355h7Fe3v4S9BU6QphkpNaXDLFmd7u/wTvxv6N1X34FceiJ0SrV65a5Vf2LuxuuHMbFm6f4uSj+rrlrE/PRu8J/gWYc9CeisIIhHfrl+iZFxfVAYw7a70b/p9QrVg0Bz4z1r+uRXxir8+CjwQ8v//xfxPnor9UvfP93l1wIME1wTKz1rmrYm8NdYbCsKL48gz9X6/jun8RrBKHkbq4roCf8JayO8IZL+onGK13xvwqrw9Q+h9r8EYqYmu8r8OwSi61Vdz61xH8qEPQxQjRUPr5kR/BmZW8EpfEiXd/k+ib+dXrClf/rzq8ZqsM+wLNF7v8RrkV/LRe8Trl9NG75bX/gnedhJwzxMQ9cEQX1X6XVX9KqkutDH68QqSHIoYZEFPyq6+l75N9dWI+BQxm2hv6O+d4R9ehD0I785fZNt/W9I3z9Spd6N0lX8TIMUu9S+LMXd/go7vu5k8PhQFp3vd33+K6AqhBE6r17v7ia4WR38R3vorlDkQudeVeSr+wkrwt6vFVotTehniqBWfVei+OgSterS+XzUXvGfBJ1xOtYxQorf4URiLPAvhzwESCrwFeCBcpN1euWr/nuojqM+OxC/HfP5cEWaj9Nyy1/Iidrmtf3yI38cr26lX/goFyVP12KWxxBP+IWW5JF88N0CE8uqvEejORS5fS+v/lV/1frkHLfr6++/61fFIvUsFq5PXQPPYEB96EOfcQIWM7vv7xCwX/E/eCrr+IELPguwWfE/L8R8uC7Bb8T8vxHwZfE/L8R8fAAAAOEQZsgL8ArAhfA84L1fETckTy+iz0BP9PVxm3+XBr+NQIHgo9F6qkvRKsH/wzu5V6xCv5aGLeSteqvr6+nuutCYa9Dfwnuh3dwh+vv6yr5F1JUX8q91CPWuXxP2r1XVfWixdfzfNJUTC3ovX0i9ClRHToV3h/+ve692BXF9/Yjfor+CnWC34J65eDH/8vy1y9fX0vV+HdCFcKjF9FehdXcRM/5K/L8M0Kcnx+hqKt/BjU6eGfhUV40V0BJN0SreGF4xInVy9MnR/YMaN1Y/4Ia9r9e64S5oriLzZ/Q+r5P0Mf9YvBmJ1j9o7yZXXqVZ4R6rhGuEEI6uZe6/BkfqVfa/8Z8KKsOUXvL83HEi/eP3w1DK+pvQu8QX+ugSDkZb3v6rXvD2uWspfH/lvnsQrSxle+WsuvUqfLLj+v/g+Qj0JF+q9BmKewINavH66Xou4qbv8EIQ3fvu+dX+1/eDDVwx0IFeGF8v690EgwsckxB0XvG/E7OxguF7BrhBeBV6w7Cu3/VaK/Xffyq9v4tF70P8LB28d8MULi/X/xNehHj5f17oJr5/1778XrgXYUEIfCeBMghI77+j2viqWNP+WCQU+7Vy+XVwT/E+DoMo7eFvYTo379f+CEJIv/BjRX+H5OX065UI7GLrxrXvl+CGCeuuRHYrvoCLVqeaEvsIAlit3d7ukXKIrJ8OVZI3+sJiETvLXpahO6GmV+urnXofsJ7pUJ6d4o4Tav0DEV5BLEbvX9er4hWfBGSShPr67oJ0Tqx4j2qOy0Ld2sYi3KpV660R61Re/QyuuFxiG3k0eq+qR/xXUmT8stBFoIPVZSvf5ay657xn4m6rwp8IULfHE28dXVnfwhhDnWv16NrROm6+rrQ7uqvl11EosWKUd9XxeOJHfOa+EawM4KEJ7fzVujd8t+jvS9fHaFE7/pVsCrfEeFa9DAhZr59nBF1U6j1Xt/St4f+Hfmr2//l+bwVfAsUXtcOyK+MRnY8DSCgEJHffwO4IvBT+16rCInvm5Ovqbv6hT5K5ob54nMq9e+16+1yqtcu/wQUU6X6J3Vr4+NWP9K/ev69X/V+/v7++xxN7f8F13Jdfovda93+GNejftcT+B8DPjx823Kvlgqwln/w9m6ruvxC9ROIX4n7i+oL75hk3p/34Kuv58FHELPgswVfG/4GjXxHy4LMFfwh8R8GHwh8R8fAAAAEB0GbQC/AK2IWZfEwWbU4xBwV2xiI7Yxbl8vUsuCX+hL65vqI+T5KrRGv0RutAhSQxhrCZf/0HipXJPxN3PQhaGKk/yVgj9gfcvE/E/Er3UIwlzISx+r16L0nraEFzdXEVv7oZ3h2r44k1O+ZYr4lexyvXxP3VgOH1CPz+B/3d10jlX9L3UV1fzL1r+EuaNfzRd6M9clc3xnxVYb/r1XCNYK9r/oDiTr66uu/v8Iq8E9Ff5vm+cxL3CPNF2GNegj0TQR3fXEoV2X/9feFf0iJloH4+8X6BLRe8Pn+F1yxk/3QGtIh06CQroSFF7wVJW6EivB3Xv6uRG6sfWLx+8FP4iEvxSLfNfNH+r/EIhVnXJghL4fE9fQn0ZdRfhX8vX8NfN1EL3VeG65a+Ve+16TR6sDX1f/EfFVherfDUI8VjEfViFkf1flGrWN76/TvlqtBQquonq+v9Wp9d4FDWBOFfr3QkIY4hjZ1ej/Pibxvw2G+gIYnwyf4FLrhLmQ9vpemsXjfQ5ugW6r9Veqr77uSpetWK7V9fq/UXJhhfrF5/jK9r1XugQ179e+Jl9G9vCHhA7Ei65UJOkJrwUgrBLe77u2/woI3fd3fd9vBDVzwaia7V/1fqXpe67tEf9f1Wr/E/E9DAR+CINoX3Wv/EfYW+CLG6u8EX4m60bvl+WThH4FuE+PiKF4u4a+NQtvD27jPD7Qh+wN4X2tZu78WfyHRH7i+2L+ZXrBEN1+jv472z/NeBT+Pr/0F8YqVzqJV+v5Vf5ZeF4TqJQvoq8EWtX90R4htfjpAh1c0/xnzK9Vgiqu/zq/iDK/hDrBCG8f3fd73VdYx+GhfRT9fWhD/PdA752dPv9q/Qfr3U/X+v64vqdE6uKXvhGEfR+mELJ6L0uRTbEkqv8ExFX1V9+HX419Pl//1+hD+CdeH9WEQh39idV9fWvVj/no/Vi9aSv+r+cI1jPmq/z/a/qvwto7DMIVOgo/XKKWbtH6tNaZCF11UqCT9+OJV4jN6+uu0LlXondA7L1yZa/8IhDpB7xVCe/V/XoNvoMrro7CcPZNl8yfv8EYcWqxpflHIg74y/A3ZMX8D6CLx1HOo8C+Grzflvkr0J70E7S1/S86JsRCXaxicQuIRFNxN9+mhEqW8+v0fvDfyySX16+8Wb0RF7xXwSfAVwlb4xRA0rwIoWQivl+f7Xo3BgZCYx83hEd2AgR3doR+Ci/5L9fVy1l3zSdyYIKviCXKMR79/xSN/7lv61eCLNRXm+Iv7fqJZnf19eu4nuPv1euW71eavrq1gpr+/tEf7+4gQhDxCzX9/3J33ff3wWf2bOIl8GP+T6wxk+TBhxCwa/J8nzfN8uDbBf8nyfN83wafJ8nzfN8fAAAAD5UGbYC/AKavi0Chil8fAgdIX/6V5PRWvl+X5ZeRE7sCzR+8HfuENv/yScvcI96EOQV8lWhV4/Jz19YCjWr7RWMQslcvr0txcL+hb16/hG5EK6r/r5vde+l79e18V2DHXKvUMW9V+Bbr2v/lr+vxVX+SuSSoR6lhf0f8uEMeIWqArl6+h3r8O5X8I/H9fiqJ3Qd+FPg9//LWn0D+veEBngtL4J694Iev16uJRH8ZhSpuuT0N6I9eiRSMqqfr6uXD/X+//jUdKvIr/FT4c10hXXia9XEQT3EAhF7u53oz3cId6JFVfX594vNxUmNonVia97aP3hvXMvzxOqBvV+mJ6/hyEuVF6YQr8C3rhiM9CK+kR60RevvX/38vhXXo/vif17HEi47vBSqHKN+v+sXcMdhX2f4j4jfKj97q3X1oznV9e19CO74V4KkGYr9WXtq1etRnSCn70pF/+vfLXEr46EhlX+L+fvR37rsIfArd/OvfLfN5fRRPUT2BB9+LdWzfD/2HBUjO/bLCWFa74RGIJzpNi6L3i8dghoc54O/ghxHLjES9cqviiV7eX+9UJ8eCYqLUmNBar1yoz/E+Evida9fX3r3c+39Cu64R9BHrFLT/j+M8MJX1gm9XVYJfgxH1ylFPu6i65/0V/B0Gfn+ehxNOuCUIL3hsFHQGEFSPlPYK6Fd11ft+C+Ernm+e2kPeJ/4r0vl9H9G8nxhgRCru7ZfhLCIU/FDuhpvGfDx5cEYS8K5thGW9exyr3evfFwxXWEfz3nxGogTWqqq8WqrQhtLy+Car4hRJpwybwqSn8bfon5PXvBGFry5fQtKvCPot6oz1xX4IzbvUJjkP8iL6J48lem9H6vBIZar78EhNVKpL8tRVXV9Ij/S/l5kL79E7219XOvfDKK+OfOXhHiFdUCfJn53hj8Ut3Fq0uT+vqeWN3fJ9YID9AIShV8YorMmEFr2/4fq+/wSd3foB4gwX+ql/A7goRfdo6y2r3+idVgVav+ivWbrW0JfxVX6hyX0RuwMvs+GhC2ORV/Kv7W+je1htt+CtrXt+Gf2vvCfx/xX5EWLwXBHwKiV/hREidcCCHESLr67xHq+vFEt7/dF/3LVzfCC9WC6i5eC/S/gg9elWbqlXEZP6n+6q5eI6i0Kj45du7X/erHer/a/6k71fFEr9X6R+urv0JxC2IV9+2vhv0JeLzV/9rl2GvfJSozHVK/X1ku/76v7vnd30uJ6HLRViiV4L+r56ubr71eW+bkgm+rHe/5a7mEL80v18R8Fn1itfKI/BbuuVfxXy4KME/+K38T83xPyYKMFnxPzfE/Bh8T83xPx0AAAO/QZuAL8AqGB5xIhdfGQZVJFcqBA3y/LXLMuTkfN1xKvBlYK89xOIX4lFexi3q4hX71fpk61fquuTQn4n5YZ9DbRGI+bF7X19IY3xHzfNdyr3yL/XWr1zr3xa98TWAgdVr3k1cIVzScIw6v5PR2jLBIFq5EbpBxN/D+R8T+DkR4L/QGf19OvukJRO+cvd3yfNXN4bwtU0J4V/F1ehNfE1lr36I3QFkI9T9RK913h3XDKOx4E3rw2FljfCC9JQT9a+6+tGi61foIepen8f8M175oX5q4quaM5THd/xHxCFfO4QRY5JYHMShL+DgVXSJ1evXxOuCr+pM34meqvC/4JkKqEuWT0N6qhLXF1CHPW0hTHcZ8ldovU+f8TXvCNYvlVvPlSXP8/2vfonV3+pVfLRPqn7+wY5OBW6EYRXwlLgQfWgj2OnmZG/RHr16J2RBD/tK8nq8nPfa988tAwFo79/hh61te1joeS3+f1QjpbrxNH7xL9/0K7xGEsDrrB7/rBVQVqPwTnMKd/h9+Ccqv4IX0zfaIxVfXfLJhH6OjsXXXovdB8Pq/6J3yr4kvRu7175flp+JAo52H4SXf/889txT8EHoME6ltLwl8iDj9ARQn7PJ2r/LWQf5vXehHx3w8jv7ovW+o1CO/XuhIrsIZOfwVB+EaiV6716fiUJ6LWIQkPVcZd+MUU38Z83xUwp36z4eBDe/zxHr60V/DR1esIP4quS8f6BaLk5V7penXurhgQsVvEcSCI6rv4RmJqvVGY6iPCBPBR+lfwIYjwiK8P6r8EX4tXrmV5MFYzxdH95dCn8Rm4lE/I/zGe8Jc9/L6G/n8EutVrYFvIRV+SCPtNP13yXcnt1zIzlcR5teuYqgJIS+IRXPlv0dpNtX8OfHd/r/HE28Xo7wqKXELXLL6K9+hHX55wFALYnreKsu79Gc++2i2msnr3S+HH4InXgk7vljlNYKbwN4aXLwJYIPAlhpF7wNIJl7XGXeP/KvdQj4QN4SEfo7WIVnqCOjuvOIhn5ueuJ/Xx+id+id7a+1+itf/LdB/WGO6mAtfAkQRXfrHKKnXg1DQISO/FfP8ler16v+r/Eyc3c3g4MjuVmC3h3DIha+IzVeTv1v65UIYq/79fBFpcRr1c8lx/er/q/xMV8Oa15Beqm9e81f+bN8m4IhDvvV/dXV9yu775d9caOR/Q58T89d1LJ8ghfAlC8Qvz4hfi/v7xCCSivhv/CGP/oIZvxnfwV4hfz4OMv3gqwV/H/F/WDDBZ8f8X8F3x/xfxkAAAPCQZugL8Aoy+TEIFDihCuEF8XBZyXydySehbSXE0IWTk119RHWjv1+Wr3cb/BXciM/evXdL3yr3gh/Jv++JV+4RxC9xK5dRPYBV/fdSXcZ1UvwtzSeh/4SELJzVyZf/lrL+bv60O7uLvidcst5NVNv5kXu4Y+bX6v8ytD+KceIWqZK5ETvH1ixxK94X0OJv8IdfxPg3+C/4M6Ll0B7N1r3xOMRF9LxCxWv+tehf0J6EKBj+ff659eBj3cJeWid7S9+vvH/mX2vCfXX4T0NiTYZwjNeRcEYU8EIrqM7AnpG7qTrVvB2XW/6a98yudgJELonav/iFKnxCxQU+CI7vvr5EIc1wxrF8ngd/g11uhLeCcX4XCfhEIq3sIonfrF8b6H/CPwhS7+r6+wn6vz0broDqE+3QtuxPvRu71fv8E/4Whf0N6XqMvQQeRffVfKviuIRe+IXpc/wX9c/0qvjFPkVYEjqpQuI8IL5ZLdHfu+/tezcn7/6Gd4QwhxVYGXQggR38JVYO9UFfXHegg92F/pIr1yq/UtcqN0uJo71QG4P5f/+vqEvHbXz/LVv3r3gYNdIvYtihPzZ2CWFcO0Of/sMao3r8T+16vfVT+YRd3WD0vl1eYmq7sFHVdVfvRn+1e71yk2ZX8I0V/BQGfDgTQnqwnqsEnVe6YOVf0Pn4hCurL8GgK0ToWv75H/4jF84IQi979dctUDFIQ/0CGq79gYwvXoj36/xS/E/KhL+DQM9fhLWLN48IfB4r/BDNiaN3zL18Lw7icVSo73hfTwp/k8Ubxz1lwQAhI93a8JfML8cvS8Ph6sEIW8Sbwr8VXrxX4qsm1+vXwjCNTxa+eK52JrXh0ZWEV6MhD+ON8R8Qr+GSVys2q8QaTRa5P16sK4jEH84/ybpG+Ih+vqaflq+QUqSrvkV7y7x4xC/vG16+E/GfGVeStFfwt8ZrJr0GKh7DHo2KuutCeuq+Wl8XiF+fwj8H4W6AQ4JELY6IatubjPCVFfL6/q54ar/7V7xIYXvLp43wp2iPFL9HjHnzeCXdVR1+/RvdA/9PWi/r7rX2/BJXvBRXvArH+EAS3fd8i8Yr14C/BF8lciN32vVVr+6l+65EJ74j4j4QV/hjoDaMlf8O6ovXmS9LqhHsQtYEKjdfL9o/b/rBVRO+TFK9VL9S9av1q9VxXq/z33eDDBTXF1av7q81ff3xN8FffafgSn2ixHP1Ey933J39/L9yP9FaCn5hHL94e6/nwTcQs+DDBX8V8vxHy4MMFnxXy/EfBj8V8vxHx8AAAOlQZvAL8Apy+EZF8TFCFgzqp+VAifuJ+JV6uJm5Efu4zwz+T5JeJV4McL9f1sver1yfq/yr/X6sa/v1fv75H1r0lQjDHoW8LbSGd+vdRFr9e+K6mrnrBbRe6i9fEr/5+wGC76+SuleGOaEttX3/W2rE3N9S4f6/+qoDyL9vX/gVQx5BXar3gQX4Env+ul75vZPBLXvmWLwvgn4u7ASNFOneuYvmqgY65v0b369fo/UNnFwUyGtwek8EYURO8ZXvCG/RO9f1nfMidr4he8Ou18Rv9E6Frmk46K5f/kriEUqysD6b5F7wflqp/CItCW/X3iT+EcmGSr2vwRXf1+CEjvxdAQw9foR18T4yi94EMIo/dAbwz19DqN3teJrFT+DaG17X5QrWo65JKu+Xxr+dBTvCOaole3e11/r3y3lonXRPRfWi91r2T9fwsBC8IYTL/+hrRG6K0a/kl7QS7q69fFVCvxN4nWD4Si9l//V+9HfuGPBsGPEhPwUgj8Z+VDOqwLft+q6+tF7a4RgnELWtfoUEIJqhbKrE/JF4P34M/g9E2uS7uSQUvugh1YUCOuJ0JY/V64WobKF+NK/aJ3Q03zfaN119fVL3XtXgXc7DsL3FxyxPrBx0/oLP3/Lr4S8FL+UENaq/lE12hD/a/kqCFFfoCICO6TX/xPhc2/0Xq4y9NEfqun8dvApBlGqGRxB/vdF6+SJqGEKZnlCWo514L6sdQh8R66+eqCPq0Z/wQ3d39+r9BP5Py/ov+5e/p0IeuM8P7wh8NF8JawlRX6+tX6Vf98NZcuJfk/ET86Es88pNV4ZN4XlNu/nr1fEKTOU3yK+/BqboQbq+vr7rqEu18v4rw78VsUTWMoS/yK8tlFd6N1HYbhrdBD8nNEVsUq8n9f83y19ydaI/xwJO7v3gjLd3MirVosvZ69E7xNe6DIXR+xxN8W/vbV6EqbND/iPp2/gXIaELNk35jLVSeifN/f6vXSJ30vfN3rl4FTjEV6vApjvBRXLWN0j94EsOInVWvV2r9At/EyYSoW8Q/4Iu5C//giNqvfaJ1YTosXYNTeNL2HRC+vBRXvAQFXxiiuvhSuSe5epZObqbyhZFfEL8R8ZeDDBJ6N1ct1onSVfggycvy/a/7i69Xl9Xxy+VOvr64K/Xtd8tL3/q9Vr++XFKu5e5e7779Xxy3/V++hiGheyeDD++P/6g3/zf5hHEiFnwx/nwYYK/j/iPlwYYLPj/iPgx+P+I+PgAAADZEGb4C/AK2IWVfHwbcvy/oEDfEov6ELEUxE49h2k+SEkIL8E+cQtcSg4/xKvQhXY5eXcd1XVY4nUlwnBb698nTEdf17WOJV5uJtf64vXL4le6AUPpievqqL/39wt1FXcIwl6O8KPie18TJ1fMhXfFeCn4f+HfhfXFovffgQ694Nfgt+CffNTX5bAs17x+Cm4T+XqEepkfr2rwj8Tkwz+de+P8HqRe8E4Q8MhDwViOwEyEO9E+eFfhP4Mwn9o07wu/BOLvLX2/4Y6Qn0eriYwEPd/nxlcmX/9CH7Ac/uJ7A3CPCr7AohGs2t198ei9a4IojvWJ0tUI7qI65cFIuXCvf4ryLyL4Kq1eul6q+5F6ifv3H/6O3i8q+174jf6v1F+Gh/QQ2vnRulfno/vP8T38CR4QwjxU9glwjqjP7q8tf2ve2vvlVvl18i9XF/E6/8FAX7Yjwp8MfFCZdEvloNuvyPkf8j5H+3vWoTx4i8Hu1i/G+C0bd3u9u8KCN33d33fb8Xd93+DFq54XLfKXqqsK6qvlVKjLCfy+Dj39aK9+vfBGi66CFE6+0bpeJ+DuFqDusyrDOP9HeuVWen0BPfQOwQ+3132iP0wnLYKfy1yL3iRngpB2hOr0RGfx1ev175/iETt/BLC1foSh7whjtehT+Gav0NCVDEc2MeiViN+jPWCAWitJURXNEL1ROkrX2/0boSEITFbaF+K9fxGQ6v4doQ/xHyXxGuOpEfw2lj+FyeFeuO0Z/IbzUX/zVkJ81cKfIj9439r1WBP+Mr1jF/K1kf8JCFifRbe691cvoRuCaesEnrL6kRn61euSK50XL9FeqBbXpMmbbRX9f1/T+BGxLCsO8shf+XQW6a+60M7r6EV7r6i1yoQqV/0vA3h7wLIJNYF8Fn8JdgSdVovKtXeGqE/8nOyuUXq74Yp/wR8qNnSbq0lCXVfiK14OvgID8LLHxC9AO8FCN3Tr13y89aERGGaK9P+GvR/xdgoo3X3JQ/9r4kqKxS9wj7r/3RH7++qlV+4uKELJguwS2qL14KGjHSq0V69X6bV5uJRH+JlHLqKvlf8FNy+DA/U+q/sCYWYQuIXEL8vywi/yHe8Fv0I/BX/l/wJHf8+Cb/PguwVXyfJ8R8R8uCbBf8nxHxHwafJ8R8R8fAAAAOuQZoAL8ArQhYMORB5iIvV75eotXov/9cSv6ELfq9cnxHyI/dxW3/5ERq0J/BJd3doLel7sFfvqgY/H5hi8r55V1xHLBdX1rF7NeCHJxKv1CPxeMU3y6AVPqTVf89eid/Xo/Q1xEJcvxPUSvdasSevda9iibXhH4/4Xr1YIdc/S9TL3QSJ1IveBB+BX/LjiGXq6Xvm+RF7w38EOFOkXoR9Xt/9RKsfIr1UIqx2An9WBHNS/RO6BfvmreuG0c6fCK1tIHekXLpevsGPX9YO/g5Eo3Vhf4f9A7G3whBMqQRCG+RGf4hXPAQNSrOvrVpKtH6sX8Ivz/PrhrwJIY9nROq0KXpMrrBmE/dH56x/5kbq4IPCGFRCPCT+iCrs2dcmjd9otd6v4Fb2BFfkordKvda+/X2/tFcrLVz9e8I/16QQvh7r/x350aLX6nv1LW/0L6sT8Mhf4FxDIoR4r5fisQQM3xUvojxghZKP70EOVKgnXx1SJ3tyei9Xr36/+1ftAj/Qn94qv/nRO+VE74n5Vb7Xvtey//ovfOvUPYgR/ssKL9cI91gcevu+4Q5Cld/g/dUJ9fyqxpLn7+tf1y9I65fKv/nV64n4RRW8CN7D3wl+M6wSF1Uq8bKb6vJrkQzq9et+C4G/XCK4R6+J9D+jMGXwlriJOUoQ1U1wZ+HP6G/qrriviN4Z82ejePtevBdhTkiOJi14Qo7/gi3u/sRWN12r1mJ5fmgjFaq/QZor+O+CAncIL16Sv1q9YIxHzK3jdYWov/IK+ZXPj9d9ar+F/msN69CbkV4JyKvWreJX9cR6EIU/gWjYxVTrhteF/hc3guM61+a+OV6yF6E/E/Cf0/iV6fkrlt/Dmdh2E/QUqew3R2VzxdXV6CT9av3EK/UISDkUYZuTdl7vrW95a98/xvxFYr+jt+r42ewKdhZwoOQ/0TzoX0nKhTgX6Ed8muWfHKzF11/Fq5jFU6fOufwM4c8HIQR+8CWHvAggirlRO8Rqg76+tH/dgvSO+0kCrxymtuoL6y0R64IIc05V895WvpaBOutfdTdfyL6sIfhIEV34sYoWVH/GI3LoBzgo+6wuI+IX9DiaL6rXps2hiFj/m8FpvBSbwuZG7HE6h/nkzZRCzLn1/eBAozy4Z9xK94Yq+KJlr65K4IcNYjtCe13S9GfdxPzoQx17rXrV5Kn9C6v65L/kg0+xC/F/E9RMtyd/fB59/eCDv+fBdxCwc/fy/EfLgSMGf38vxHwcffy/EfHwAAADqEGaIC/AKivi8QseviWGt3BX0qVE0SIuPRH+quJl9Xu4zv9UV/BTkxmCTZYS6r1zVxa/1+iMTer1zZf9++WCXQnuWJ5v17HEr/5F75t/r1P++WTAj9f2ubXvmXvdFf9f9wt0DHBJly1E16vL6tl//9iPEkRO6BPXr5r7pc8I/H+CneBR+BX9gLEWr44k375Lof69r8E1Ki930IVLUX8SinTX3fonVj9YZ+Ga94fE+Ga941b7/hPsAgJEJM/wcggXpMd70Z+18CWE1yrC79lvDQiCbxQnd3f+II77v8ChBKId9345jER7/CClWfHeDn+iv0BnosVY8fWJEr3QMT+LFyYR64JP4iuI+T9CIvdY58X3JWDEI1hUqO+v9frl8JQjVd8RxUIrvQjL5Ogo/0Xq5/l+WqBT6/C/wn+f2XptWKGI7RV+HKI+uX6hTXxPhwR8qtMX3wX1RuzsEcKcVCi+RAgy+RXPTjMTXvBCSsCYFbwprh+8lfXy2/wT1rWtu+Eq4TL/8Koa8mHy+CFoz/XghPJyI35H/jl19or0vBxR3k4e8G1Fi8GlE11FK/komV8yN1ctYLgQ98IcJzYvW6CPRq+EPEb+6hDWHeCUQq6rp1wIYfVt/dP9G/1q/xPxPxvg2CvQJAIPX5dCiF8E4Q8E4YrD3r2tddyPliYexLQtojmBMIe99X3/eG9pLgjRXqhgS8EG66xVEfws/i1f5kTqxvz/DJrwll2kX/cEVv+FueEF6Eo7+HSF6rwmuwXhDv7HfDBPk+kMfXCH83yK6qvq/MRF/1DK91J8i9+veP/SP6UUTWM1Yn1Hon/kX/QTSJ3gu52HYUris2I1m5UCD/y/Kr2IJS19fcEPYR12Cg93d7vkq4RHIs95FWnR3/X94Swryr0UIWvQmqzUR78EpKquq5gX5sJfCml8brv+fwJIr5PHJcugPYLl7qkbug017rXutf9ev1f6V5uIkwnR3+CiHa0JfHErS/PMugfiURjX+u/sCzQipH/eCT4HYmMUV18csXtXX6JJh/1C/xqsSVFK/XNzQtzorEV6K98tYEQRXJXoZ4lpkX/Wr3XdaL/5UR/lV/ZfZVfwEUGe+r6vR2LvgrsGnwWL6QhzwVbv7VHeTAqavRnxy27vvV9Pc/er9y9eOX1+r1ayikVwVfWDh/ev+0X5fl1/r+ar7n7vu7tvEL9xHf39wT/WEv8ev57BRiMF2Cf/CW/lxmKEQ7Nf3zYLsFnwh8HHwh8LQAAAA21BmkAvwCnr42QQsUIWDG5O+uSaom+JqpeuQQvg1/Ig13gv+G/gp3xMFl/y/VWyfJ1Nbr6L//1E6X+o2xC1ydxCvr+eoRRHgnXxKxfEr1csnNXycklXfP8T8Sr/Fr3gfz1T9g91mdWBZwTP4nrq/9F7/5V6X199eyVxXxWv+gU69f4xS5XxPhEvgpXgp3stctejdeE8J+j9CHotXxNejda6A9jtePEo7+D3iFriPC/9G94Rr3hGsc8E4X+JxxPLwUjaGo48yfGYyzzHgRQ14Kwl4Ix3h1eLXjSef7VqlBr9pCIuwJYj4UhfiI/DD+EELjngZqJ3xiN0mBpL8RVgXxff4XFyZdej9WBTCC9Nyo3vK6xdCa+f50TvCRPEfhBG7xGEV8RF+gq0ZpoLP9K9Wl3lKWy38RBHVfu6Vupayr5EWL4pYugU+vr6+jetEf9X2t34IvggEa/Xtd69IvpF70I8vw2GfgVkIigp371y6Che7q1Rf92vKic90N+OEdBn8IeBGDvcPo//BBkxFYviboEuR/giELX6GPQT6P8cK0kr3d3q8EZHfc1xMIdur3UWuVdzdr2v69f9gUgQoW/X4RLWIDGNw77VZKEduuK6DK+X73y/2idv4O1ZBPzfaO++gMDxC9Azq/XdgJUE9ehD/avNgVgT/Gd6P1+vePC3ghP6ovfr+vRP9B1L+uXr8GyhLi0WKM9FeJwgG1b5/iKwz8VldArBLMhD9fTq/WvOuGvguE3Uer3xS94uvSZdVP1V0EVBRjxnhd+CPLxC/+I+Il5ZFhat0Dmi9W6J1ZqK/mr1cuT9f9f3hT8RBP9X3XXOhj0OJV+u6hNFf6V7xNFy8CeDK66oFPzZa66R3p/wmIWN25+dDu7BAJ6lRXOtSrPlqtfdfWr7/+LximvtcsbjiQs+TvgQwp4Owt4KQpS4nutFf4mapsQhfjdY/v+GeeWtcnRsPnrD7vkRuugjVyqXoZ8GVcvhLGKelYhfiEI74heiK7qSsJKuMkf8EPoT0tpoR1XSnRE+ReruapetXiL4gchLtI/4ItOSvVc1VoV/pVfq+gt7ur/lrl+6f3PXV/gSMo4hbyF/8GBoJ75ql+dDG+5r+/v766lvV4l/se74J/8d/hD5sFnyZ8GGCoTDcIVxF8uDbBZ8f8R8GPx/xHx8AAADJUGaYC/AKMIWFRC6+Mg15OpOuUQgRHo+JR3n3X/yVzQVcsRuvdh/Xq/dScvxPy/1gQ/y+BZybr+TdfwWcuv5eSSplKnWsXWCK78X1fP1G6/ugEn6iUTutek5PRvCfsC/gjy74lF9r+/pVxqxSdVyezfLeURXL88hf/5F/XXyfN2epU71ih/0Jq/RLziF/V/pX8Cr8CX39Vv8nYFX3o3d/f3+G/gj+CfT9ULv4M6+8eI86rLuwFiFe/5uwq/B5rjIKC//oj/MjOfFK5rBOK0Xq5fAnlXu5N3P9EE9X0I9c3EfESc/iv6J6rDuXh6EuSE/RXJuTXr4KCU/k6l6vp+perWL4/2Vevidfr1ev+kbw9835+zgwRougQ+vrRerPRYv0TvgVkaKCvJiO5sfvBt8dQR7qCDqq7Qrr5flrdW/BIZax3QTYYof4LmrDfwRnrlBCId96HEIJ5X6/qv9f/r/oF9ek4msI/H0Jf0qwRC/hG8T+Wu/0bvhdcxBRjvtScRWD8EPz+Gu0pvr+fuF+4vGIv/UFPQjLiwhvV0d96wkvQXP0GPwR9Ve+IQh9/1XjYtU66oz+er+C8FIJNauNTSXq3cIq/QzVDRKJ3oTXLVgczXhCi9fL9r1Prgm8h6qvCPoE4quXww+4Q7mQz/x3xyufFXVdh8/Wit0J9Air/r+uqXvkvG+wh7/Eb55H8OZ2G4JrrJ6/yy6flQe5Url+J6rrXLHKt11J19/XpLietX8X8G4JKza2VF7sX7dHeQXt9WSvW/gWIJ+60q5e4jv8ETQrvkVjHKaxuVRynpWOWZV7+DEJI/eDMNfJdBMqN3Q/Jwx8PWKQ+Q7CzgnddSYS/L+hveWvXUEBLvxiyJiFIR8NIkV8ljl03Ty3HyDkLt2AnxiI/gnXhurwS+vpPr0TvlXu/5+9f9a9pqI9NfQpfl/X9WQI9/X1y10ub76wUYLLutrta5Ffv7+/roUtVE9XjltVfWr1acQX/+Tkgo/u+/wcPu+5/iZu++Iu9XH+IQxdgHQcGv0I5fvBJ1/PXELwKGCq+T5/lEQUzV9c2BQwX/P83wd/P83wtAAAANoQZqAL8AqC+PkELByOQc2rdX/X83Or4xXauLV+41XPly//q3y/LJgv/J6IvVUR4P8P+hbS+iVWEcd6EdNXFXFd6v3+Hu8N+CPE0fvCNexxNzxOuXwQ6uJrnl2vmRHxxLN/H/muqrnV/n1yz+B5S92A0ff89Dkbfpn6pHcgm9XmuLXrEKlHE+8Dj8B88YrvXIvY4n7wvWLX/xS98Qva/6m2v1zr3gnqdPBJq9e7J7/B2X5UTutevE/D/46CGvzZRCE/PjFS74R8BA/m/VrwzXpMM0SLX690BB+E9l//Id3+BJovvKO+MRO8IfTXqylXqX90C/T+Ogk9Xvyd34IC/N8QhHyuf4nWBLt6+/fyO84m6BTR+8L16qwRXfIngSggsW/69COxxKveXWDMM9fX17XgkWKCddd8tK/Xx4FgRv7+X68I0fr9ffr7xOuXw+vl/ROq/peiG8Zv177XutHfrWXh7v4FoOClrX6zQBXgevX91k/L6fpr32i+PlXvlXvlXpKghV+ojGIS1GPBJRXpL6J3jjr3hDdBX0J1nPhtjmL61+tZYrvXBTzfQsS77v8Ebvld332iPEYVo8XgXAQ9wT/F+L1mgjErr3hgX88j/viQRDlr6CdeEPjnXL91zYhHGe5UCGur15Sar7V6574vX6K/YPAMPi/WvVlLWCPJX474RwVcehLW/pCO6hLr8EQ7GsX/l/9wSG1V6fQNwRq7w0MKIWt8v6O/hrJgnBRWXdgYfwp8ZVDf6/viIJ8FNHseGxEnF0uK0Kfwe99xFDEQWnP0V/k/V5M9e3mvXJJwt8JX34Q9gS6K/er/CEE2n4coj3WuY/V+qtf/E1guq5fSveWCTu+XQCpAkdfyL369LiHJX196PzrwUQV9IZ0mn4c1xKK+MU197Ov/AnhhX6AUYKkfvB6Gl6Tl+e/V+oRV6X9dXiu/4KNpe+l90C1eP+WvvFl7DIysFle8Fla+GlixC4xE5T8snGq+OR8YqtX6/BgsQtv4Sgl1X0lJ/d5KN0uB0rFikReUuKXq77kGIpsSpVq/f8tX9clA2EQU9XevVy9SWKJ3992jPv/uJR2xS3ur03v71br8HWDLl1v/L8sYIX4mIEIJL7gv+fBLifmwTb+XBtgqEwXzYjFCOJ+TBtgs+EPiPgw+EPiPjoAAANRQZqgL8Av3oJWhT0M/NyyXGy8kmD/WCnBTy671eIuI71eriJ7n7nRcvAw+onHKXTrrm+bsYEPiOwNNf4onwRvwIOCkv/9CFlv6+tf/MiPEV3zb+L13+BxE0++3+ivBSOJvXol8QtvieX176XvaxRPxHxC9r++Nk4jsDT7+7WLtCewIhKz16CnQn4lexC/CKK2/ASJUfL41cqsAgNWxSIqx/wRnqwK/v8L/CNE7oE/wzRe+XXG+NlXO8tTL+KRO7CIS7Hill3IvdjC9/WrVhn8n0jd8cuoaFIXN67y6E9B59A4P1EfCyFOa4IJeoYWOfCFP4jwc+gX/N+J8TrFhPoEYb8Xqodvhherj/DH5198q9Xr3gtHoS3o65fJXDEOPDHQnor0EIpP7+spFX91WitJtovSUDX0DP8Wid8X8esVDEceZRVgoMr9hkEnjvUEHiKEdT/+kL94TH7+DxDCzQS5aO8ulJVr+8muy9VXEInSYZ+GfxHxcmCL8P/E/r2uJ5H+iF7rhf0E6hLswp3+Cs/6uUvl6kvNvl+dEf51eXkQvvWuGMcyhx4yVs1ehnfr3oy9SwaBcGlboJqEfjkNY+bsCE7oDX6k+X3BERdX8CaHUZvAmh+qkv1/89YeDPm1k1xnj6P3htrlWhGMRPfq/itZ++aJRugnsEALasD7R3PHiPCq39K/6KlUXOFffqvVBjXgiGdF/Ohj1Wr9IL9wr3ovfIr1snhM1Dn66Dq8Ja3V5S/+DqhWoJ+ZBFzsLhRGY8KuSoj4rwKfwZaXyozHX1E+EtZ8lBtI/X6+l9Ff6X8j+GvCGCBeq4SLwjsn7/8oxDv/mV/0V7wI1XYxbyebu6wQhLX/Qz6U1gX9+h6e34RwU9oc/zr3X11WvuvwXa8Ehd3Y+JrAvhbwIoY8GoSkqRE6+eS++HEPbHMnsX7/BVBBzxPo1dh8yL3WvVmVUECL3hj4KBC98QIu+7/hi6qT0I/Ec1c14NzwVL/vX0tWr9d8Til+Wq1f3V+p4zngtv7/lVjvV67rdf/OiVfL8vUT1yDFvEXwXr/qXoHHrxiIF1k2IRnjFabGLfEL9/P9139wIn0uwLnEI8+CriFnwbYKhME8Z8gjiL5cG2Df5fn+Dz5fn+PgAAADYEGawC/AKkvjbELECF8BA4J+WM9B566Xp+XuLp8TL8v3JcZ8R8nxFXq8P2EcuL1yydq83S9dRFPm75f/l/X/6vJgfcnV4J8N+htpb4sQT8qHdiCcQsvNXq9P6t3xqE/vQle/V+wCApe8FmsHvELXfuvOlzL/sDDV4ftZ3+iPfLTqf6lV/ifibqS/XvG9fr3zb/Xq/GLfX/f3EL3jNZfgV+v9bxKJ1bXh91UKQQehdRPCKIdMYi/HxPgWa+PlV/AS5lcxC1tdgSevhjHEEe8M/BD8M/C+n7oTXwz4HEESseCAZJhT4Uq1cvsl8YhXQxyz4lRPkF7vwITBKZ3e78WMUuGXjFdKq4Si+kvhXf/pVYZGlEvfsX762NRO8Irwj8GNX+FfkW/wtVQlJxPxKJ3g9G+caisXw4hUUJcahPRHF16G1+r36M8X0gg/34LvYCOBAj69Oq1bJ7af/396L03E0vnV/CwRrCle8MfCWTBDRNVhEvwVBwi1lRleWHhni43b+VXJak/X8vL3LJYPQz39/QP/X19B6gi3iv0idXOsXiMlAv/Mjdi2ISMohnr4iEcG+u6XyxPfWhP/BZ8lCf+FPfWgtnwppeCLLfdV/KhnoLBiFmpH8Nk+XpjvDZgRVXc8DOCmJ9e8lX8KaqEEbq4rwV5qnriIef6FtFcXT8H4jwl12HvQdEVgzN4Igj4PQS7wzBUHrr6tCOq4L/Dm8E4YrE6XiPxHjKK9+id19fwhBPtguFqvVb+HxFriKrl+dDk6WcV8Ob+K6mddfJWI/SK/T1olcnto/ryOvV/FaqJ8GmuEoJ+6ru9DH+XuO758jqjy934LQx4PQ4hOvtXrl9krN8260V8ZLa+GIIvQipe0Kclquq6vsQJ8HArwEcEPAtfifAk9fOhMXgxCHQHkGHhcR+v4rk6BeAi0d/GfLRXrg4gpX6Ed+vvCfrXuvx34he1/8/sUCK78fGIr2OoaQh7w5rdX8tXu+Ta8UT4jTX4xCbHzVw1BR6FdXr3dL3euVX99ClxxN/kuqrdX/V5fV5auW4Sgs/50VjuXv67uTq5BS0KRHQxCZEVK+KuLgsu/ucQuIXEIKM9fX14hcQver/fXLdwY/JQYxv1gu+s+CzBb91x3yUsuCzBd8I/J8Gfwj8nx8AAAA4tBmuAvwCkr4iExCw96Clq9fRXKjd7cQKX5K5JuXGIg/6vi0R6sBH0Vvl+X5VZYxbXcId/xHzQT8tctClU33QN8tROKV1y3Ut1q/zXT36ugltCa0W+eauvXv19jiXv8R8i9YhXiF9F+NRevAp174tG75VevXvDNF6Cm9eoUS+4/9eriV79XribuFviF7473rk1/4Z1xPxNCifB38/wI5PAk/YmsO666Bv+aCX++XAQIz4vsA0IY1+rH6K9b+CUT4+ie8M/C/XX4+sV6o/UNlPeY8EYQXvivCus3wc/BGJRu6AvhFeqq6pCPnxEEfobevRTp4yr+DCvawfdG7XFaI94CDfxav4CXE+AkxvxHQKfxt2BbDPf4l+fXova4Y17XP0MRiYdKHEJeWgKYf+EUfuwd/h5CIoJMv4hCSq8KiK2vky/L+CEzvvilqgQCK5+vv1/86P77Vu4js/v8cGV7wz6As+vfP+Wv6V4LdcTWI3cILHOgkGVfa8GwJxHIvIvIvKG+Golb6E1YhCj4TmV+67v4n5Ud+xq9JXr19d6+7l+a6de8CYP8FQlC/+C74UHdBIH2OkS15tcTVggo3eC7j2QMsgDQS9vXnYI4TwbZF4U9fzRy+K1+g49XfQIPX1gj1q/hqr9d9K/6+Nc/Q5EN9X6O/6K8vovfonS3oV1PwYYYwhr47/lrtC83gSV4IKv4Y9gSwwSq/BuHy1XruI+0Ieq/1/86viF9i/hHsFwEn5JcJv7Qnug2EfBR/RH3fPWnv8Egh76hrWsQ6f6HvGeY276B+EPBII6hjqscju+v8cQgrbwIoKQSa1fo/xX7RO1+r/L4Y9n96vXovfEbwz/E5Md+I6179XrBcFIJ9NCW376wRivoXl4hDu+ZXxxL27AWIn9X1xf0PCKK8l6/8QJriPG/FUfreaKyer+K1wxBP9Z+uX7/lQzuq+dX+dfzaq/19K9Lw38G4eky+wJYtC/96vW3forL4EiCTJ+5PQ7psnw0bXz+DriFfxPg7Nr/wchBCe8Mhhe+IRO6ibyV7sLe9F7t5MMK8vfwIEEnq8v9BndfxXhAt4OhGIV4hfA0hKq4gYrUSqMWxVIRNgqwU+jdLyX1Ecsl8RfBZ32tXq8TV931Lilru7+9WO+ueDD65e5fBoXX/V9fX19fyyiFlwOGDP5qfzYr5aBBiMFGCv4Q+WvrmwUYLPhD4OPhD4WgAAADq0GbAC/AKiMQLHaDL0G2n5a5Z/Qx+5v1ebA9/lrlm5vkrkgkxOrlvRa5Yi4i+abia9F/3G0IREn6/+vkRX7iquKglwjl5awEr+fEIzl2T6/V6wyUpa1v9Yr/0WqBCJ61y7AaPwKehCM/ZauIQnupuvrRnQQYvfo95RC/F9wjWBxJ8Xe6+/X17SJ3xnyLFJzr1cT4+i5/dcrwKNfdAJH2B/H9gIkI9gI8M9/f1ND9i/itYmi9WhNL+6j0TsYvMYxFNfa/Wtd/gZ/gIGiOV0vfFfNWFS+P+L9A3+Gfgqr2MRXrG495/Aqgo+K+IrCGTEjas3qOhcQtetS33xd4Ry4W/giM77/EKnXilcrn+L8DaLqgfj+vp6zfO6wjR4/oMrrw9WOb/kw1+JxxBQXsu/XvEbv+CZSLhi4VQnquEfidfxunXPSaklQjtN8vUmvZ17r6tF7wQfLrllx+6ifBobwhriFir0Tq0TpjtrwZAkrWKdCvG1ddaH5dPiyF14QoneMxfoIPX3d931or1Wr9Kvfr1Vr77Xvl/Xvu8K7oEG82uJrntr6J7whhOwEBkwxQR6ERiFC766Az+/u1fwKHwLwjCS8iT+vjiS5RtV472H1fLXP8/ur16L3ggCPYI/cvwh8PeCII3jUid+idbWgjXKFOK8FW94RXEWjv6N8TS/rivBqFQQlVd/Y/4/p/iZdCUTr9X6Cnwjr0XvCeqia9E/4eEL3WjdtfXZCXEI/TfVPI/0donHBP9X+dCH8CR8FgjwbDPhD5paCXob66pCfCGWvxAnXv0Df0LIi/8KfiPD260R/hqGPvky/3JxfoW9ciEPWJ1a9dcYiP8RQxUoqqJ6F+n9KTKbp/FCfJkxrl4QhjW9kkxeKf2TV/lV6q9td/KrljiSEaO1ernyqnTrvAmgs8CqCRCfdyo3dSdKvq9Cepfc3B9DAhZ8SpMm+/u6/luhIrwkkI75rXxtcq5/CPwVhhF7wbhin+jd+vSc/Vyu1pDXt/wz83EL/y5fRKdLTxiJY6De6CJFivn+bwWfA1cYr1iF+EKqIqsEN73vtf/P89ctcvVddc1YKsM/HevdfXL6/pv/QTESCl/RHlpD+tX8DwZF/dvd986tDf1lx1dbon/1Sp1ftq83Pq/+X55Biq8VxMNfCH9S9fX8/y+BKL4CAPMIXEL9/fV9f3Xf33f3BB8IfMI/Ak/51/Pgu4hZ8FWG/j8EmI+IEQ/EcRLgqw58IfP8T8/wQ/CHz/E/P8fAAAAztBmyAvwCp4D52IWIEL4CB0vimGtVByIW7jUR65ZBC/q/UR19av1wSUEc/LQ5E3k5EV6qI65eJX98vy0lwPOhCuTmgmvQmuu+euJxRPUTN0jd5dVrzLo2vpe8L74nqW8CnriVfoBF+tEqT0WKCDln9bzCFxi++L+JXvYm+16ulKnl1h/4b6//Xrf6vJX19fgTS1698nyfJDmNy+ivXre9CV9XE1xPxa14CBouboB3ivAn9/E+BhF1QP319dZ90DvYxXy8E9cugN4IPiP0b3hSveK+cSi94EET0AgQuhHdfuvfEQ2/42tCb1wgCEjvlWfGVy/KvfKrF4ay5dei+8FP4n5/ApcUTXEoV03OhLH0jd8ILGh7CfX6FxRq/18iHMV1VVfL9/L4l+N3sfv9H66+vwhWLXiOOIRb+I+qt8i9Xons7BLCQxBAZZVr4ZkwtWLwxXroZVqw1iL0EHq5ZcN+wub9X615Vq/uJy+4M/0J/8qO/yeHM3Kgh0K4EDeBA99Vx+CahL/SI/gX6vWCPVA6EeBIHK/jvyq98vUt8t3aL3d98g2LF+9BGHOvJm9EqJ4msIcv/9CFDiOMRLVhPWDeCUqrqqqnXBWF/BSF5OVCnqg2E649CWO9X70R/kXrw3RdeF1fEXsR8RCvolfxFQgjtEcI3iBNYKRHxFYz8R8nwjWDYPIQ/U1UX8TdX11k16P3jshf//JhXiJPhJYJ2tr/rRv3yoj1wpXIr9fRX0f0Jo79fUb19d+i9fCC9JxC94wfCi/k+L9by411c6FPJXXLVfgqJr+SonoI+gj6i/BKCxH7L/xfviNY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type=\"video/mp4\">\n",
+       " Your browser does not support the video tag.\n",
+       "</video>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "if 'is_test_run' not in globals():\n",
+    "    scenario1.run(30000)  # initial steps\n",
+    "\n",
+    "    def run():\n",
+    "        scenario1.run(100)\n",
+    "        return scenario1.velocity[:, :]\n",
+    "\n",
+    "    animation = plt.vector_field_magnitude_animation(run, frames=600, rescale=True)\n",
+    "    set_display_mode('video')\n",
+    "    res = display_animation(animation)\n",
+    "else:\n",
+    "    scenario1.run(10)\n",
+    "    res = None\n",
+    "res"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/05_tutorial_modifying_method_smagorinsky.ipynb b/doc/notebooks/05_tutorial_modifying_method_smagorinsky.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..ce37facedffb1f5b366071de79bcf83ff694a5ce
--- /dev/null
+++ b/doc/notebooks/05_tutorial_modifying_method_smagorinsky.ipynb
@@ -0,0 +1,482 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'lbmpy.session'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-4-e8cce828271f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mlbmpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msession\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mlbmpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrelaxationrates\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'lbmpy.session'"
+     ]
+    }
+   ],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.relaxationrates import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 05: Modifying a LBM method: Smagorinsky model\n",
+    "\n",
+    "In this demo, we show how to modify a lattice Boltzmann method. As example we are going to add a simple turbulence model, by introducing a rule that locally computes the relaxation parameter dependent on the local strain rate tensor. The Smagorinsky model is implemented directly in *lbmpy* as well, however here we take the manual approach to demonstrate how a LB method can be changed in *lbmpy*.\n",
+    "\n",
+    "## 1) Theoretical background\n",
+    "\n",
+    "Since we have *sympy* available, we want to start out with the basic model equations and derive the concrete equations ourselves. This approach is less error prone, since the calculations are done by the computer algebra system, and oftentimes this approach is also more general and easier to understand. \n",
+    "\n",
+    "### a) Smagorinsky model \n",
+    "\n",
+    "The basic idea of the Smagorinsky turbulence model is to safe compute time, by not resolving the smallest eddies of the flow on the grid, but model them by an artifical dissipation term. \n",
+    "The energy dissipation of small scale vortices is taken into account by introducing a \"turbulent viscosity\". This additional viscosity depends on local flow properties, namely the local shear rates. The larger the local shear rates the higher the turbulent viscosity and the more artifical dissipation is added. \n",
+    "\n",
+    "The total viscosity is \n",
+    "\n",
+    "$$\\nu_{total} = \\nu_0 + \\underbrace{(C_S \\Delta)^2 |S|}_{\\nu_{t}}$$\n",
+    "\n",
+    "where $\\nu_0$ is the normal viscosity, $C_S$ is the Smagorinsky constant, not to be confused with the speed of sound! Typical values of the Smagorinsky constant are between 0.1 - 0.2. The filter length $\\Delta$ is chosen as 1 in lattice coordinates.\n",
+    "\n",
+    "The quantity $|S|$ is computed from the local strain rate tensor $S$ that is given by\n",
+    "\n",
+    "$$S_{ij} = \\frac{1}{2} \\left( \\partial_i u_j + \\partial_j u_i \\right)$$\n",
+    "\n",
+    "and \n",
+    "\n",
+    "$$|S| = \\sqrt{2 S_{ij} S_{ij}}$$\n",
+    "\n",
+    "\n",
+    "### b) LBM implementation of Smagorinsky model\n",
+    "\n",
+    "To add the Smagorinsky model to a LB scheme one has to first compute the strain rate tensor $S_{ij}$ in each cell, and compute the turbulent viscosity $\\nu_t$ from it. Then the local relaxation rate has to be adapted to match the total viscosity $\\nu_{total}$ instead of the standard viscosity $\\nu_0$.\n",
+    "\n",
+    "A fortunate property of LB methods is, that the strain rate tensor can be computed locally from the non-equilibrium part of the distribution function. This is somewhat surprising, since the strain rate tensor contains first order derivatives. The strain rate tensor can be obtained by\n",
+    "\n",
+    "$$S_{ij} = - \\frac{3 \\omega_s}{2 \\rho_{(0)}} \\Pi_{ij}^{(neq)}$$\n",
+    "\n",
+    "where $\\omega_s$ is the relaxation rate that determines the viscosity, $\\rho_{(0)}$ is $\\rho$ in compressible models and $1$ for incompressible schemes.\n",
+    "$\\Pi_{ij}^{(neq)}$ is the second order moment tensor of the non-equilibrium part of the distribution functions $f^{(neq)} = f - f^{(eq)}$ and can be computed as \n",
+    "\n",
+    "$$\\Pi_{ij}^{(neq)} = \\sum_q c_{qi} c_{qj} \\; f_q^{(neq)}$$\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We first have to find a closed form for $S_{ij}$ since in the formula above, it depends on $\\omega$, which should be adapated according to $S_{ij}$. \n",
+    "So we compute $\\omega$ and insert it into the formula for $S$:\n",
+    " "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "τ_0, ρ, ω, ω_total, ω_0 = sp.symbols(\"tau_0 rho omega omega_total omega_0\", positive=True, real=True)\n",
+    "ν_0, C_S, S, Π = sp.symbols(\"nu_0, C_S, |S|, Pi\", positive=True, real=True)\n",
+    "\n",
+    "Seq = sp.Eq(S, 3 * ω / 2 * Π)\n",
+    "Seq"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note that we left of the minus, since we took the absolute value of both tensor. The absolute value is defined as above, with the factor of two inside the square root. The $\\rho_{(0)}$ has been left out, remembering that $\\Pi^{(neq)}$ has to be divided by $\\rho$ in case of compressible models|.\n",
+    "\n",
+    "Next, we compute $\\omega$ from the total viscosity as given by the Smagorinsky equation:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "relaxation_rate_from_lattice_viscosity(ν_0 + C_S ** 2 * S)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "and insert it into the equation for $|S|$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Seq2 = Seq.subs(ω, relaxation_rate_from_lattice_viscosity(ν_0 + C_S **2 * S ))\n",
+    "Seq2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This equation contains only known quantities, such that we can solve it for $|S|$.\n",
+    "Additionally we substitute the lattice viscosity $\\nu_0$ by the original relaxation time $\\tau_0$. The resulting equations get simpler using relaxation times instead of rates."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "solveRes = sp.solve(Seq2, S)\n",
+    "assert len(solveRes) == 1\n",
+    "SVal = solveRes[0]\n",
+    "SVal = SVal.subs(ν_0, lattice_viscosity_from_relaxation_rate(1 / τ_0)).expand()\n",
+    "SVal"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Knowning $|S|$ we can compute the total relaxation time using\n",
+    "\n",
+    "$$\\nu_{total} = \\nu_0 +C_S^2 |S|$$\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Ï„_val = 1 / (relaxation_rate_from_lattice_viscosity(lattice_viscosity_from_relaxation_rate(1/Ï„_0) + C_S**2 * SVal)).cancel()\n",
+    "Ï„_val"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To compute $\\Pi^{(neq)}$ we use the following functions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def second_order_moment_tensor(function_values, stencil):\n",
+    "    assert len(function_values) == len(stencil)\n",
+    "    dim = len(stencil[0])\n",
+    "    return sp.Matrix(dim, dim, lambda i, j: sum(c[i] * c[j] * f for f, c in zip(function_values, stencil)))\n",
+    "\n",
+    "\n",
+    "def frobenius_norm(matrix, factor=1):\n",
+    "    return sp.sqrt(sum(i*i for i in matrix) * factor)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the next cell we construct equations that take an standard relaxation rate $\\omega_0$ and compute a new relaxation rate $\\omega_{total}$ according to the Smagorinksy model, using `Ï„_val` computed above"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def smagorinsky_equations(ω_0, ω_total, method):\n",
+    "    f_neq = sp.Matrix(method.pre_collision_pdf_symbols) - method.get_equilibrium_terms()\n",
+    "    return [sp.Eq(τ_0, 1 / ω_0),\n",
+    "            sp.Eq(Π, frobenius_norm(second_order_moment_tensor(f_neq, method.stencil), factor=2)),\n",
+    "            sp.Eq(ω_total, 1 / τ_val)]\n",
+    "\n",
+    "\n",
+    "smagorinsky_equations(ω_0, ω_total, create_lb_method())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2) Application: Channel flow\n",
+    "\n",
+    "Next we modify a *lbmpy* scenario to use the Smagorinsky model. \n",
+    "We create a MRT method, where we fix all relaxation rates except the relaxation rate that controls the viscosity."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'create_lb_method' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-2-f0f088c69f93>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m method = create_lb_method(method='mrt', stencil='D2Q9', force=(1e-6, 0),\n\u001b[0m\u001b[1;32m      2\u001b[0m                           relaxation_rates=[0, 0, ω, 1.9, 1.9])\n\u001b[1;32m      3\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'create_lb_method' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "method = create_lb_method(method='mrt', stencil='D2Q9', force=(1e-6, 0),\n",
+    "                          relaxation_rates=[0, 0, ω, 1.9, 1.9])\n",
+    "method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Only the collision rule has to be changed. Thus we first construct the collision rule, add the Smagorinsky equations and create a normal scenario from the modified collision rule."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "collision_rule = create_lb_collision_rule(lb_method=method)\n",
+    "collision_rule = collision_rule.new_with_substitutions({ω: ω_total})\n",
+    "\n",
+    "collision_rule.subexpressions += smagorinsky_equations(ω, ω_total, method)\n",
+    "collision_rule.topological_sort(sort_subexpressions=True, sort_main_assignments=False)\n",
+    "collision_rule"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the next cell the collision rule is simplified by extracting common subexpressions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.simp import sympy_cse\n",
+    "#collision_rule = sympy_cse(collision_rule)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A channel scenario can be created from a modified collision rule:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ch = create_channel((300, 100), force=1e-6, collision_rule=collision_rule,\n",
+    "                    kernel_params={\"C_S\": 0.12, \"omega\": 1.999})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#show_code(ch.ast)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ch.run(5000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.vector_field(ch.velocity[:, :])\n",
+    "np.max(ch.velocity[:, :])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Appendix: Strain rate tensor formula from Chapman Enskog\n",
+    "\n",
+    "The connection between $S_{ij}$ and $\\Pi_{ij}^{(neq)}$ can be seen using a Chapman Enskog expansion. Since *lbmpy* has a module that automatically does this expansions we can have a look at it:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.chapman_enskog import ChapmanEnskogAnalysis, CeMoment\n",
+    "from lbmpy.chapman_enskog.chapman_enskog import remove_higher_order_u\n",
+    "compressible_model = create_lb_method(stencil=\"D2Q9\", compressible=True)\n",
+    "incompressible_model = create_lb_method(stencil=\"D2Q9\", compressible=False)\n",
+    "\n",
+    "ce_compressible = ChapmanEnskogAnalysis(compressible_model)\n",
+    "ce_incompressible = ChapmanEnskogAnalysis(incompressible_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The Chapman Enskog analysis yields expresssions for the moment  \n",
+    "\n",
+    "$\\Pi = \\Pi^{(eq)} + \\epsilon \\Pi^{(1)} +  \\epsilon^2 \\Pi^{(2)} \\cdots$\n",
+    "and the strain rate tensor is related to $\\Pi^{(1)}$. However the best approximation we have for $\\Pi^{(1)}$ is \n",
+    "$\\Pi^{(neq)}$. For details, see the paper \"Shear stress in lattice Boltzmann simulations\" by Krüger, Varnik and Raabe from 2009.\n",
+    "\n",
+    "Lets look at the values of $\\Pi^{(1)}$ obtained from the Chapman enskog expansion:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Π_1_xy = CeMoment(\"\\\\Pi\", moment_tuple=(1,1), superscript=1)\n",
+    "Π_1_xx = CeMoment(\"\\\\Pi\", moment_tuple=(2,0), superscript=1)\n",
+    "Π_1_yy = CeMoment(\"\\\\Pi\", moment_tuple=(0,2), superscript=1)\n",
+    "components = (Π_1_xx, Π_1_yy, Π_1_xy)\n",
+    "\n",
+    "Π_1_xy_val = ce_compressible.higher_order_moments[Π_1_xy]\n",
+    "Π_1_xy_val"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This term has lots of higher order error terms in it. We assume that $u$ is small in lattice coordinates, so if we neglect all terms in $u$ that are quadratic or higher we get:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "remove_higher_order_u(Π_1_xy_val.expand())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Putting these steps together into a function, we can display them for the different cases quickly:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_Π_1(ce_analysis, component):\n",
+    "    val = ce_analysis.higher_order_moments[component]\n",
+    "    return remove_higher_order_u(val.expand())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Compressible case:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tuple(get_Π_1(ce_compressible, Pi) for Pi in components) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Incompressible case:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tuple(get_Π_1(ce_incompressible, Pi) for Pi in components) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the incompressible case has some terms $\\partial \\rho$ which are zero, since $\\rho$ is assumed constant.\n",
+    "\n",
+    "Leaving out the error terms we finally obtain:\n",
+    "\n",
+    "\n",
+    "$$\\Pi_{ij}^{(neq)} \\approx \\Pi_{ij}^{(1)} = -\\frac{2 \\rho_{(0)}}{3 \\omega_s} \\left( \\partial_i u_j + \\partial_j u_i \\right)$$"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/06_tutorial_thermal_lbm.ipynb b/doc/notebooks/06_tutorial_thermal_lbm.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..8ee2ead09e8614457b6e6005c8dd7cf0f2e69657
--- /dev/null
+++ b/doc/notebooks/06_tutorial_thermal_lbm.ipynb
@@ -0,0 +1,211 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from pystencils.jupytersetup import *\n",
+    "from pystencils.timeloop import TimeLoop\n",
+    "from pystencils.datahandling import SerialDataHandling"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 06: Coupling two LBM simulations for thermal simulations\n",
+    "\n",
+    "In this notebook we demonstrate how to run a thermal lattice Boltzmann simulation.\n",
+    "We use a separate set of distribution functions to solve the advection-diffusion equation for the temperature.\n",
+    "The zeroth moment of these additional pdfs corresponds to temperature. \n",
+    "\n",
+    "The thermal LB step is coupled to the normal hydrodynamic LB scheme using the Boussinesq approximation. The force on the liquid is proportional to the relative temperature. The hydrodynamic LB method computes the fluid velocity which in turn enters the thermal scheme, completing the two-way coupling.\n",
+    "\n",
+    "To set this up in *lbmpy* we create first a `data handling` object and create an array to store the temperature."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "domain_size = (100, 50)\n",
+    "\n",
+    "gpu = False\n",
+    "dh = SerialDataHandling(domain_size)\n",
+    "temperature_field = dh.add_array(\"T\", gpu=gpu)\n",
+    "dh.fill('T', val=1.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we define how to compute the local force from the temperature field:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gravity = sp.Matrix([0, -1e-2])\n",
+    "force = -gravity * (temperature_field(0) - 1.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we can create both LB steps. \n",
+    "\n",
+    "The coupling is created by passing the following parameters to the hydrodynamic step,\n",
+    "\n",
+    "- `compute_velocity_in_every_step`: usually the velocity is not computed/stored in every time step, only for output and plotting reasons. In the coupled algorithm we have to make sure that after every time step the current velocity is stored in an array, since it enters the thermal LB scheme.\n",
+    "- `force`: we can simply pass our sympy expression for the force here, as long as the `LatticeBoltzmannStep` operates on a data handling that stores the fields that are referenced in the expression. This is why we have to create the data handling first and pass it to both Step objects\n",
+    "\n",
+    "and to the thermal step\n",
+    "- `compute_density_in_every_step`: density corresponds to the temperature here, which we need to be computed in every time step, since it enters the force expression for the hydrodynamic scheme\n",
+    "- `equilibrium_order`: for the thermal LB method a first order accurate equilibrium is sufficient. This is slightly faster to compute than the normal equilibrium of order 2\n",
+    "- `velocity_input_array_name`: the velocity entering the thermal equilibrium equation is not computed as first moment of the thermal pdfs. Instead, the hydrodynamic velocity is used here."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "optimization = {'target': 'cpu' if gpu else 'cpu', 'openmp': 2}\n",
+    "\n",
+    "hydro_step   = LatticeBoltzmannStep(data_handling=dh, name='hydro', optimization=optimization,\n",
+    "                                    relaxation_rate=1.8,\n",
+    "                                    compute_velocity_in_every_step=True,\n",
+    "                                    force=force)\n",
+    "thermal_step = LatticeBoltzmannStep(data_handling=dh, name='thermal', optimization=optimization,\n",
+    "                                    relaxation_rate=1.8, density_data_name=\"T\",\n",
+    "                                    compute_density_in_every_step=True,\n",
+    "                                    equilibrium_order=1,\n",
+    "                                    velocity_input_array_name=hydro_step.velocity_data_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We add `NoSlip` boundary conditions on all four walls for both schemes with the exception of the left wall of the thermal scheme. Here we set a heated wall, where the temperature is fixed to `1.01`. This kind of Dirichlet boundary condition can be set using a `FixedDensity` LB boundary."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x360 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "add_box_boundary(hydro_step.boundary_handling)\n",
+    "add_box_boundary(thermal_step.boundary_handling)\n",
+    "thermal_step.boundary_handling.set_boundary(FixedDensity(1.01), slice_from_direction('W', dh.dim))\n",
+    "\n",
+    "plt.figure(figsize=(20, 5))\n",
+    "plt.subplot(1, 2, 1)\n",
+    "plt.title(\"Hydrodynamic\")\n",
+    "plt.boundary_handling(hydro_step.boundary_handling)\n",
+    "plt.subplot(1, 2, 2)\n",
+    "plt.title(\"Thermal\")\n",
+    "plt.boundary_handling(thermal_step.boundary_handling)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run(time_steps):\n",
+    "    hydro_step.pre_run()\n",
+    "    thermal_step.pre_run()\n",
+    "    for t in range(time_steps):\n",
+    "        hydro_step.time_step()\n",
+    "        thermal_step.time_step()\n",
+    "    hydro_step.post_run()\n",
+    "    thermal_step.post_run()\n",
+    "    hydro_step.time_steps_run += time_steps\n",
+    "    thermal_step.time_steps_run += time_steps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x360 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "run(5000)\n",
+    "assert dh.max('T') < 2\n",
+    "\n",
+    "plt.figure(figsize=(16, 5))\n",
+    "plt.subplot(1, 2, 1)\n",
+    "plt.scalar_field(thermal_step.density[:, :])\n",
+    "plt.subplot(1, 2, 2)\n",
+    "plt.vector_field(hydro_step.velocity[:, :]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert np.isfinite(hydro_step.velocity[:, :].max())\n",
+    "assert np.isfinite(thermal_step.density[:, :].max())"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/demo_automatic_chapman_enskog_analysis.ipynb b/doc/notebooks/demo_automatic_chapman_enskog_analysis.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e0dcbed8a02dadb9027b88536267f79b1e94cbbf
--- /dev/null
+++ b/doc/notebooks/demo_automatic_chapman_enskog_analysis.ipynb
@@ -0,0 +1,366 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sympy as sp\n",
+    "from lbmpy.chapman_enskog import ChapmanEnskogAnalysis\n",
+    "from lbmpy.creationfunctions import create_lb_method\n",
+    "sp.init_printing()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo: Automatic Chapman Enskog Analysis \n",
+    "\n",
+    "\n",
+    "First, we create a SRT lattice Boltzmann method. It is defined as the set of moments, together with one relaxation rate per moment."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$z$</td>\n",
+       "                            <td style=\"border:none\">$u_{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{0}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{2}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x z$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y z$</td>\n",
+       "                            <td style=\"border:none\">$u_{1} u_{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} z$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2} z$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{1}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{2}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2} z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{1}^{2}}{3} + \\frac{u_{2}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f9bbc455a90>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "method = create_lb_method(method='trt', stencil='D3Q19', compressible=False)\n",
+    "method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, the Chapman Enskog analysis object is created. This may take a while..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "analysis = ChapmanEnskogAnalysis(method)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This object now information about the method, e.g. the relation of relaxation rate to viscosities, if the method approximates the compressible or incompressible continuity equation ..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "analysis.compressible"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ \\frac{\\rho}{3}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡ρ⎤\n",
+       "⎢─⎥\n",
+       "⎣3⎦"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "analysis.pressure_equation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$- \\frac{\\omega_{0} - 2}{6 \\omega_{0}}$$"
+      ],
+      "text/plain": [
+       "-(ω₀ - 2) \n",
+       "──────────\n",
+       "   6⋅ω₀   "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "analysis.get_kinematic_viscosity()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$- \\frac{1}{9} + \\frac{2}{9 \\omega_{0}}$$"
+      ],
+      "text/plain": [
+       "  1    2  \n",
+       "- ─ + ────\n",
+       "  9   9⋅ω₀"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "analysis.get_bulk_viscosity()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "But also details of the analysis are available:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\left[\\begin{matrix}{\\partial_{t} \\rho} + {\\partial_{0} u_{0}} + {\\partial_{1} u_{1}} + {\\partial_{2} u_{2}}\\\\- \\frac{\\epsilon \\omega_{0}}{2} {\\partial_{2} {\\Pi_{02}^{(1)}}} - \\frac{\\epsilon \\omega_{0}}{2} {\\partial_{1} {\\Pi_{01}^{(1)}}} - \\frac{\\epsilon \\omega_{0}}{2} {\\partial_{0} {\\Pi_{00}^{(1)}}} + \\epsilon {\\partial_{2} {\\Pi_{02}^{(1)}}} + \\epsilon {\\partial_{1} {\\Pi_{01}^{(1)}}} + \\epsilon {\\partial_{0} {\\Pi_{00}^{(1)}}} + \\frac{{\\partial_{0} \\rho}}{3} + {\\partial_{t} u_{0}} + {\\partial_{0} (u_{0}^{2}) } + {\\partial_{1} (u_{0} u_{1}) } + {\\partial_{2} (u_{0} u_{2}) }\\\\- \\frac{\\epsilon \\omega_{0}}{2} {\\partial_{2} {\\Pi_{12}^{(1)}}} - \\frac{\\epsilon \\omega_{0}}{2} {\\partial_{1} {\\Pi_{11}^{(1)}}} - \\frac{\\epsilon \\omega_{0}}{2} {\\partial_{0} {\\Pi_{01}^{(1)}}} + \\epsilon {\\partial_{2} {\\Pi_{12}^{(1)}}} + \\epsilon {\\partial_{1} {\\Pi_{11}^{(1)}}} + \\epsilon {\\partial_{0} {\\Pi_{01}^{(1)}}} + \\frac{{\\partial_{1} \\rho}}{3} + {\\partial_{t} u_{1}} + {\\partial_{1} (u_{1}^{2}) } + {\\partial_{0} (u_{0} u_{1}) } + {\\partial_{2} (u_{1} u_{2}) }\\\\- \\frac{\\epsilon \\omega_{0}}{2} {\\partial_{2} {\\Pi_{22}^{(1)}}} - \\frac{\\epsilon \\omega_{0}}{2} {\\partial_{1} {\\Pi_{12}^{(1)}}} - \\frac{\\epsilon \\omega_{0}}{2} {\\partial_{0} {\\Pi_{02}^{(1)}}} + \\epsilon {\\partial_{2} {\\Pi_{22}^{(1)}}} + \\epsilon {\\partial_{1} {\\Pi_{12}^{(1)}}} + \\epsilon {\\partial_{0} {\\Pi_{02}^{(1)}}} + \\frac{{\\partial_{2} \\rho}}{3} + {\\partial_{t} u_{2}} + {\\partial_{2} (u_{2}^{2}) } + {\\partial_{0} (u_{0} u_{2}) } + {\\partial_{1} (u_{1} u_{2}) }\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡                                                                             \n",
+       "⎢                                                                             \n",
+       "⎢  ε⋅ω₀⋅D(\\Pi_(1)_(1, 0, 1))   ε⋅ω₀⋅D(\\Pi_(1)_(1, 1, 0))   ε⋅ω₀⋅D(\\Pi_(1)_(2, \n",
+       "⎢- ───────────────────────── - ───────────────────────── - ───────────────────\n",
+       "⎢              2                           2                           2      \n",
+       "⎢                                                                             \n",
+       "⎢  ε⋅ω₀⋅D(\\Pi_(1)_(0, 1, 1))   ε⋅ω₀⋅D(\\Pi_(1)_(0, 2, 0))   ε⋅ω₀⋅D(\\Pi_(1)_(1, \n",
+       "⎢- ───────────────────────── - ───────────────────────── - ───────────────────\n",
+       "⎢              2                           2                           2      \n",
+       "⎢                                                                             \n",
+       "⎢  ε⋅ω₀⋅D(\\Pi_(1)_(0, 0, 2))   ε⋅ω₀⋅D(\\Pi_(1)_(0, 1, 1))   ε⋅ω₀⋅D(\\Pi_(1)_(1, \n",
+       "⎢- ───────────────────────── - ───────────────────────── - ───────────────────\n",
+       "⎣              2                           2                           2      \n",
+       "\n",
+       "             D(rho) + D(u_0) + D(u_1) + D(u_2)                                \n",
+       "                                                                              \n",
+       "0, 0))                                                                        \n",
+       "────── + ε⋅D(\\Pi_(1)_(1, 0, 1)) + ε⋅D(\\Pi_(1)_(1, 1, 0)) + ε⋅D(\\Pi_(1)_(2, 0, \n",
+       "                                                                              \n",
+       "                                                                              \n",
+       "1, 0))                                                                        \n",
+       "────── + ε⋅D(\\Pi_(1)_(0, 1, 1)) + ε⋅D(\\Pi_(1)_(0, 2, 0)) + ε⋅D(\\Pi_(1)_(1, 1, \n",
+       "                                                                              \n",
+       "                                                                              \n",
+       "0, 1))                                                                        \n",
+       "────── + ε⋅D(\\Pi_(1)_(0, 0, 2)) + ε⋅D(\\Pi_(1)_(0, 1, 1)) + ε⋅D(\\Pi_(1)_(1, 0, \n",
+       "                                                                              \n",
+       "\n",
+       "                                                           ⎤\n",
+       "                                                           ⎥\n",
+       "      D(rho)                                               ⎥\n",
+       "0)) + ────── + D(u_0) + D(u_0**2) + D(u_0*u_1) + D(u_0*u_2)⎥\n",
+       "        3                                                  ⎥\n",
+       "                                                           ⎥\n",
+       "      D(rho)                                               ⎥\n",
+       "0)) + ────── + D(u_1) + D(u_1**2) + D(u_0*u_1) + D(u_1*u_2)⎥\n",
+       "        3                                                  ⎥\n",
+       "                                                           ⎥\n",
+       "      D(rho)                                               ⎥\n",
+       "1)) + ────── + D(u_2) + D(u_2**2) + D(u_0*u_2) + D(u_1*u_2)⎥\n",
+       "        3                                                  ⎦"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sp.Matrix(analysis.get_macroscopic_equations())"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/demo_create_method_from_scratch.ipynb b/doc/notebooks/demo_create_method_from_scratch.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..a39c844801d6ee439d98f30e09f8f6e56d80669a
--- /dev/null
+++ b/doc/notebooks/demo_create_method_from_scratch.ipynb
@@ -0,0 +1,414 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "nbsphinx": "hidden"
+   },
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "import pystencils as ps\n",
+    "from pystencils.stencils import visualize_stencil"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo: Create lbmpy Method from Scratch\n",
+    "\n",
+    "<img src='../../img/collision_space.svg' width=\"90%\">\n",
+    "\n",
+    "\n",
+    "### Defining transformation to collision space"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA20AAAAUBAMAAADsGchtAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAdt3NMolEIma7mVTvEKvunM/GAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAFf0lEQVRoBe2az4scVRDHvzuzvTP7o+Oai5CDDkHZQ1AXET0IZs9eskEjshcH/4Esufjj4oJIIAjuQdBcpEFyMIdl8SKIkEXEk+KoeJGQXURQRIka9RCJa1W915np6qoHb4nx4jtkuqvep771Y6en0zM4/DDwAtzVXzddvQ3TzMZ8AmfNYAkNh0gVYmvcWiK/9IMR/YeGeBrobQLfPPNUq3li+75lZsOLNiF7s4jexfMrOGT+cZCGtcoLr3oEF+ItW8MhElkRIV6tk27WS+++oYFw7jbLIsTGRCFz61LbHsOXreaJ7StT71GbwIcjIIu4guJPlMuWCGlIPOXrbpdLDsGFzH+m9tMp22wNh0hkRYR4tUqyWeUenh1qItksiwg2bm+Y2zm6uO2g0M0LtmKxpUfbK5Mof7w6oqAZBH4GPgVO2hohnvK9BjxpE6BCrmzdUPtrm6XhEX5WTARvUybdrEMjLOw0AaSbZRHBxu0Nc1sCZvcwrwsOtlLrsXxn3SSAe2huWcRHwNUVXFY1RY0QT/neBi6NTAJUCKZ0GbXN0vAIPysmgreZVrpZCwMc+r0J0FmqWRYRbNxemVtvANyxh5m/VOBoe0SZ+fSMTcQ+5xDHRzy37pCCqkUa5tz+Bk5vozskr1pciD+37pC8anmEnxUTwdsMlW5W94Y3NzjNsohoI6Lgz7epCtitMPNrM5PatqbMfHrEJmKfswjgwRGKioKqRRrW3MrrNLdFFBV51eJC/LkV7FXLJdyshBBvM9RuaKBTOu3ttK8D/H5DFiFRiJC5zW4AL69i+o9mJrXtFWXm07dsIvY5i8AM6faX2yKkYc2tR9tPrJoEF+LPzdJwCTcrIcTL6Y1XbKBTOu07vTreHI9kblmERCFC5tbZpilUxtyC7b2WHnDMJmKfswh09uiGb9AWIQ1zbtdlbhbBhfhzyyLcrERDvM2MYwOd0mnvA839fCZzyyIkChEyt4WhfdXbDW/9E21BfGITMZUsAhcp/vQvbRHSsOYWr5MWwYX4c8si3KxEQ7yc3nilmwXMVeO99ZHMzWmWTUgUIm7OjT5W5437ErY5gS0iPTebkA8Mq6fO3ED3JZe2zUkvDKkj7v2kpeETFYXyCfY2VyzOaZbcETQBOkvP7Uhrf4xCGjI3fuvPbqKvPzij7TmDp2uYRcRUsogP0FvHzKAt4lwncR54fWQS6eukpeESblZCiLeZcbpZmK/wfBOgM5mb0yyTCFGIkLnxR21/B3PLKnC0OR+cFhFTySGmK0ytm3cZzn0J6P/d79h3Mu5dhrwHc+5L/KxYI3ib3Uo3C08AdzUBOpO5Oc0yiRCFCJlbUVGMY7i8Ul6jg4nFNuACWbRnjWwWEVLJIc6cWvuWruWrtgbH09qd7fLjQGC3+adWVJQWz0jZw7WTNbTHI8ZZWYR4tUayWb37Tm0NdCHJZlmE2GQgMje5gHx953fA0RGVNl5iA31f0PLwm9sitj5/fANZxPH9/d+A7oqtIfFUVuXJu2m3EJ37CRsvLmTup2s/QNnFlkVMZKVisYZ4lT20wyu9u7+/P9DtTTbLIoKNNWRu8rBHqp9fHzehPupRonSj3vTQc66wlF2M+QQ/f8nTCATeD1nU/y7VB8ouZtH4l4n80g9GFPJ9wLm63KI+mHgNT4mVp1/FHcou1nwiPFdWsZIa8Un06kSidHizEGWXXeG5svLcYiK/9IMRYW6z9bvni2Yb5Cx8K6M9b8ad2s7mfCJ8x6JjpTQCUS7GNOJLXYi2s/t2EAcoPb9ZTIS59TZj3RvxdfIldE976u80tZ3JfCL0W8dKaQSiz3ITqy5E23nL7SAOUHp+s5iguR2+9//fKUyMfuLw7MTxxOF//KMO/mXD1NHhPwrjTLx3gTLSAAAAAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\left [ \\left ( 0, \\quad 0\\right ), \\quad \\left ( 0, \\quad 1\\right ), \\quad \\left ( 0, \\quad 2\\right ), \\quad \\left ( 1, \\quad 0\\right ), \\quad \\left ( 1, \\quad 1\\right ), \\quad \\left ( 1, \\quad 2\\right ), \\quad \\left ( 2, \\quad 0\\right ), \\quad \\left ( 2, \\quad 1\\right ), \\quad \\left ( 2, \\quad 2\\right )\\right ]$$"
+      ],
+      "text/plain": [
+       "[(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2)]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.moments import moment_matrix, moments_up_to_component_order, exponents_to_polynomial_representations\n",
+    "moment_exponents = list(moments_up_to_component_order(2, 2))\n",
+    "moment_exponents"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left ( 1, \\quad y, \\quad y^{2}, \\quad x, \\quad x y, \\quad x y^{2}, \\quad x^{2}, \\quad x^{2} y, \\quad x^{2} y^{2}\\right )$$"
+      ],
+      "text/plain": [
+       "⎛       2             2   2   2     2  2⎞\n",
+       "⎝1, y, y , x, x⋅y, x⋅y , x , x ⋅y, x ⋅y ⎠"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "moments = exponents_to_polynomial_representations(moment_exponents)\n",
+    "moments"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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uauX9VB4xxs286bLzgfpDsW3LLNY8uJgQIlfe8FwDoXqFEJ4FPBpC+EwI4fA2vGVbPnfTPbvpA6/ah3948lLOeMLBnPv0g/j2Z+a3661DCL0hhH8BVgDfAV4MzAZ2a9fPUAnMmb+dfZfcDYwNxfqBLj75r3D+8TM55/Al3PDVeWMCse+Su+melubIlT/7AdOBVwM/CSHcFUJ41cgcWfv99Y/T+dv9DuEDr9pnssXS3YrPuvARFj/xYWbMitz3uxlcdMYBHHLkVg49elszbzeyq3YS8FbgBVRm7GePWmSo5TGrfLq6Kh/6D917CCuXL2XRgX/hoxfuzbTp8JEbt/How6v5wCv3Z4+9A/strSzrkU01ZwjopnIm0mHAMuATIYSrgWUxxrva9pM+8Y6FLHnq1qkWS3dP4uAjtjNjVmV3PIRICPDgvQ3vItXYa5jJ2EBIzauGAmD5H5by8xvncdrrYFYPHHp05IgTAj/5LgZCbTaXSjDau3fxvWvm0bPbEIc/c/NUi6Z/Md1/vHlvTt//EN544kHsvmCQ40/dWM9q4+YaVgAXA/sy+TUYUvOqoXj4fujqgoWLIQ53sebBxRxwcGTVXzcZCHXI+L2LNU3PXWxc18XXrujl/EvX1LN4+gdNL1y2mguuXM1vfjSbO2+bzfSZU070jew1XEBlfmEO9UehCzgphHBQ8wNWqbz7i4dx1Ilj/2rrnjbA7LmVK7KHBqcTQmR+7zq2bOxhy8ady/73x48Np1yxR6LjVZ4dXedyc0f+fTVwdgjhXuCKGOMX61r7qn/r5blnrmefJ9R1oXL6kQDongZHnbiFm76xG9d+anfOvGDdFGtcRmW+odE9oTnAfzY1RpXTT2+AxU8a+9rQIGzZtPPrGAPr1+7BzNmwdtX+O17/5S0fSWiUKo5Gzoar7l08Bfg88MUp1/jTHTO56/YePnnr8np/SDYiUTU8CCuX1zMncTjwT8A5VGIxd/LFd9gAPCPG+KcmR6iSCf0D5wLvHPPi3N1nMzx0AA8/AAsPqLy28r4NPOEpj7P/wQM7lrvyhlfEvt6fJjhc5VgI4e+Bz1K5TqEeG4DtwCeAz9S1xq9u7WHgoem84oilAGzb0sXwMLzhhJl86raJ7hyQ4pzE2lXdfO+aeWzeEBgahB9f38Pt1+/GkSdMOZESY/xtjPF8YAHwJuAuYDPgfZ7UWdu2zGLjugN42knwnc/C0OPbuOdOuOOWeZx8Zl3zaVILtgFbgZuBs4CFMcb3xRgfrGvt0163js/99F4+fstyPn7Lcp739+s48oRNXPLfK2qtkt6eRAjQ/6Xd+fS7FhKHYa9Fg7zq3as58Yy6f9FGror9MvDlEMJhNLd3IdVn9HUQb/3YX7js/IO54AUzmTt/kLPfMY2eeYsZGryH7mnDaQ9VhTNmr6HuKIw3e05k9pydlwLMmjPM9JnD7Lmw5uUB6UViz4VDXHnDA+16uxjjb4HzQwgXAn8HvB1YSuXKwWwdVlP+jL9QLgR402XsuMHf8HAYuY7iYBYdaCjUDtuozFHcDlwB3BBjbO+1XuddvHaqRdI/BbbNYoybY4xfjjEeARwDXEXlUNRGKtdOSI2ZKBDjjb6OYuXygxkaLNzvlhIxk8pew1oqJ+gcHGM8OcZ4fdsDUaekNuRW7l/T9LoTzF18C1jZwlhUNr++9cApA1E1PhR//EW9E5ASwB1ULgZufK5hYm353E0qEq1M6LU8GThq7+IfYoyPtfp+KocQwtFc/6X31hWIqtGh+Mg/3xhC2KvDw1RBxBjviTG+rI17DZumXmTqdZOKxO1NrjdE5aEtUqJ2PFHujz/f3PCtNrq6IosO+hkr7gYYMBRKSbOfuytiX++O02ETiUTs630Q+FijqwEfjH296zswJKmmUY8c3cTAyrmE8NEG32KQ7u73MDxcfWa2oVDiYl/vH6lcZNeIrcD7Rr+Q2DOuAUL/wAFUHgM51bHa9cBtsa93VedHJe00JhAwr/o8iAm33Y++9bPMnvMAr/vA+0deiVQmHG+Nfb2PjLzf6Eeh9sYYpzybRGqn0D9wIJWn1M2ZZLEIrAZ+EPt6xxySTzQSUpbVCsQky0fgzhjjpI+INBTKM0/Tk2g8EI0Y88xsDz0pZ4yESq+TgagyFMorI6FSSyIQVYZCeWQkVFpJBqLKUChvjIRKKY1AVBkK5YmRUOmkGYgqQ6G8MBIqlSwEospQKA+MhEojS4GoMhTKOiOhUshiIKoMhbLMSKjwshyIKkOhrDISKrQ8BKLKUCiLjIQKK0+BqDIUyhojoULKYyCqDIWyxEiocPIciCpDoawwEiqUIgSiylAoC4yECqNIgagyFEqbkVAhFDEQVYZCaTISyr0iB6LKUCgtRkK5VoZAVBkKpcFIKLfKFIgqQ6GkGQnlUhkDUWUolCQjodwpcyCqDIWSYiSUKwZiJ0OhJBgJ5YaB2JWhUKcZCeWCgajNUKiTjIQyz0BMzVCoU4yEMs1A1M9QqBOMhDLLQDTOUKjdjIQyyUA0z1ConYyEMsdAtM5QqF2MhDLFQLSPoVA7GAllhoFoP0OhVhkJZYKB6BxDoVYYCaXOQHSeoVCzjIRSZSCSYyjUDCOh1BiI5BkKNcpIKBUGIj2GQo0wEkqcgUifoVC9jIQSZSCyw1CoHkZCiTEQ2WMoNBUjoUQYiOwyFJqMkVDHGYjsMxSqxUioowxEfhgKTcRIqGMMRP4YCo1nJNQRBiK/DIVGMxJqOwORf4ZCVUZCbWUgisNQCIyE2shAFI+hkJFQWxiI4jIU5WYk1DIDUXyGoryMhFpiIMrDUJSTkVDTDET5GIryMRJqioEoL0NRLkZCDTMQMhTlYSTUEAOhKkNRDkZCdTMQGs9QFJ+RUF0MhGoxFMVmJDQlA6GpGIriMhKalIFQvQxFMRkJ1WQg1ChDUTxGQhMyEGqWoSgWI6FdGAi1ylAUh5HQGAZC7WIoisFIaAcDoXYzFPlnJAQYCHWOocg3IyEDoY4zFPllJErOQCgphiKfjESJGQglzVDkj5EoKQOhtBiKfDESJWQglDZDkR9GomQMhLLCUOSDkSgRA6GsMRTZZyRKwkAoqwxFthmJEjAQyjpDkV1GouAMhPLCUGSTkSgwA6G8MRTZYyQKykAorwxFthiJAjIQyjtDkR1GomAMhIrCUGSDkSgQA6GiMRTpMxIFYSBUVIYiXUaiAAyEis5QpMdI5JyBUFkYinQYiRwzECobQ5E8I5FTBkJlZSiSZSRyyECo7AxFcoxEzhgIqcJQJMNI5IiBkMYyFJ1nJHLCQEgTMxSdZSRywEBIkzMUnWMkMs5ASPUxFJ1hJDLMQEiNMRTtZyQyykBIzTEU7WUkMshASK0xFO1jJDLGQEjtYSjaw0hkiIGQ2stQtM5IZISBkDrDULTGSGSAgZA6y1A0z0ikzEBIyTAUzTESKTIQUrIMReOMREoMhJQOQ9EYI5ECAyGly1DUz0gkzEBI2WAo6mMkEmQgpGwxFFMzEgkxEFI2GYrJGYkEGAgp2wxFbUaiwwyElA+GYmJGooMMhJQvhmJXRqJDDISUT4ZiLCPRAQZCyjdDsZORaDMDIRWDoagwEm1kIKRiMRRGom0MhFRMZQ+FkWgDAyEVW5lDYSRaZCCkcihrKIxECwyEVC5lDIWRaJKBkMqpbKEwEk0wEFK5lSkURqJBBkISlCcURqIBBkLSaGUIhZGok4GQNJGih8JI1MFASJpMkUNhJKZgICTVo6ihMBKTMBCSGlHEUBiJGgyEpGYULRRGYgIGQlIrihQKIzGOgZDUDkUJhZEYxUBIaqcihMJIjDAQkjoh76EwEhgISZ2V51CUPhIGQlIS8hqKUkfCQEhKUh5DUdhIhBCWhhAeCCG8sMb3DYSkxNUbihDC20IIfwghzExudLsqbCSAtwKLgG+ND4WBkJSmqUIRQngb8H5gMfCyhIc3Riji52MIYS7wMNAz8tJm4IwY4w0GQu0SQojAnTHGI9Mei/IphNBD5bMIoDfGuHZUIKqfX3+IMR6aygAp7p7EK4DRH/49VPYo/hUDISkjJtij+DfGBgJgcQjhmMQHN6JwexIhhAD8FThgksW6DITqFUJ4HvB1IIz71h4j/z467vXtwDExxr92emwqhnF7FOMNA9+JMb4kwSHtMC2NH9phJ7Pzl3cim4EXADckMxwVwGNU/rKbVeP747e37cD6jo5IRfMGKp9NPRN8rwt4UQhhUYxxZbLDKubhpv8LzJ3k+9VDTxOe9SRN4OfAQ3UuOwxcG2Nc18HxqEAmmIOYcDHgTcmMaKxCRSKEsAQ4ro5FDYXqNnJo8gpqHw4YbQvwkc6OSEVRZyAAZgL/FEKY0flRjVWoSFA57bW7zmV7gOtCCPt2cDwqjqupb9taTeXkCGlSIYSTgcuZOhBV3aRwOmxhIjFy2uurgel1LL4RWAf8O7Cmk+NSMcQY1wPfonI4qZbNwJWeFKE6/Qb4PJW9z811LD8XeFdHRzSBwkSCXU97HW+YyuGC3wOvBxbGGN8TY3w8icGpED5K5Re6li7gKwmNRTkXY1wTY3wNlYt+3wOsAjZMsVrip8MW4hTYKU573Try7/XAZTHGnyU2MBXKyHZ2D7Bkgm8PA9+MMZ6V7KhUFCGELqCPyt7CkVSOiow/AzUC307ydNii7ElMdNrrRiqnIX4YOCjG+FIDoVZMMYHthLVaEmMcjjH+vxjjM4GnAV9i10NRgZHTYZMaV1H2JG4GnkPlr7mtwHLgUip/2W1PcWgqmBDCfCqHBcZfM3EfsNT5CLXTyPZ2HvAvVK7MngtsAz4cY3x3ImPI+zYdQjgIuBd4HLiOyiElzy5Rx4QQrgbOYuee+GbgnTHGZemNSkUWQuimcijqIuBYKnMXC5KYUy1CJKYDrwH+N42rEVU+IzeJvJmd99zZCizyAjolIYTwFOAZwFeS2HPNfSSkpI2bwHbCWoVWlIlrKTHjJrCdsFahuSchNWFkQnE18CBOWKvAjIQkqSYPN0mSakrseRKhf2AucDZwPJPfyhsqF8HdBlwT+3q3TrGs1FGhf2B3Ktvusew8o6mWR4HvA1+Lfb2DHR6aNKnQP7AI+EcqF+fNnGLxCbfdRCIR+ge6gM8BRzWw2jOp3Pb7tR0ZlFSH0D8wHfgy8KQGVnsWlW39wo4MSqpD6B/YE/galXtD1WuXbTepw01Po7FAVD079A8c3O7BSA14Fo0FouqUkb/ipLScQmOB2LHe6G03qUg8JaV1pVY1u/0FmouL1C5PbnK9MHrdpCJRzzMeakn8SUzSKK1su62sK7WqLdtuYhPXu3jJ4kPGfL19W+D5Z63jnz+6OqURSfXZvjVw5Vv25rc/nsPGx7pZeMB2znnnAMe/uJ7Hm0rpevDeaSx720LuuXM206ZHjnnhBt58xWqmTdyU9CJx7f137/j/zRsDZx96MM8+faoHbkjpGxyE3n0H+fdv38+iJwzyo+vm8OE37cuBh97Hfks8o0nZtuxtC5m/1xBX/+4vbHi0i4vOOIBvfXJ3zrxgwnuPZeM6iVu+OY95ew5y1ImTPfVLyoaeuZHzLl7LfksG6eqGE07bxIJ9t/OnO8bfPlzKnjUrpvPs0zYwc3akd98hjnz2Ju7/U83TY7MRiZu/uRsnnv4YIRvDkRqydmU3q+6fwUGH+uwSZd+pr36UH1w7jy2bAg8/MI1f3zqHp59c81Bp+p/KK5dP44939PDCcx5LeyhSwx7fDh987SKefdpjHPRUI6HsO/KELTxw90xetvQQzn3aEpYctpWTXrKx1uLpR+KGr+7GE4/cwv5LO/7wDKmthofg0vMWMW165IKPPJz2cKQpDQ/Be8/an2NftIFvLb+ba35/DxvXd/GpixbUWiX9SPzg2vk892Xr0x6G1JA4DB86fx/WD0zj4qsfYrpnaisH1q/t5pGHp3HGG9cxY1Zk9wXDPP+sx/jVD2rebibdSNx52yweXT2N557pWU3KlyvevJAVf5nBB76xglk93kpZ+bDH3kP07vc4//vp3Rl8HB57pIubvrEbi5+0rdYq6Z0CC3Dj1+bzjOdtYM5u/pIpPx66bxo3f2M+02ZEzn7qztvGvP6SVbzoHP/gUba966qH+PS79ubbn9mTrq4wIRNOAAABC0lEQVTIU47ewhsvq3l9WrqRePsnPY6r/Nn3oEGuX/PntIchNeVJT9/Gf3z3gXoXT39OQpKUWUlFopXDSR6KUprcdpVXbdl2k4pEK9dAeP2E0tTKHIPbrtLUlm03qUj8iOaq9jjw0zaPRWrEbU2utxH4dTsHIjXoh02utwn4VfWLRCIR+3pXAR8EhhpYbRB4T+zr9WwRpSb29d4DfAwYbmC17cBFsa/XK7CVpluBrze4znbgnaO33RBjcodNQ//AXsAxVJ5xHWosFqk84/rHsa/X3XVlQugfWEBl2+1h8m13HXB77OuteZsDKUmhf+AAKk8HnewGlDW33UQjIUnKF0+BlSTVZCQkSTX9f3sA4pkyxlNTAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from lbmpy.stencils import get_stencil\n",
+    "d2q9 = get_stencil(\"D2Q9\", ordering='walberla')\n",
+    "visualize_stencil(d2q9)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1\\\\0 & 1 & -1 & 0 & 0 & 1 & 1 & -1 & -1\\\\0 & 1 & 1 & 0 & 0 & 1 & 1 & 1 & 1\\\\0 & 0 & 0 & -1 & 1 & -1 & 1 & -1 & 1\\\\0 & 0 & 0 & 0 & 0 & -1 & 1 & 1 & -1\\\\0 & 0 & 0 & 0 & 0 & -1 & 1 & -1 & 1\\\\0 & 0 & 0 & 1 & 1 & 1 & 1 & 1 & 1\\\\0 & 0 & 0 & 0 & 0 & 1 & 1 & -1 & -1\\\\0 & 0 & 0 & 0 & 0 & 1 & 1 & 1 & 1\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡1  1  1   1   1  1   1  1   1 ⎤\n",
+       "⎢                              ⎥\n",
+       "⎢0  1  -1  0   0  1   1  -1  -1⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  1  1   0   0  1   1  1   1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   -1  1  -1  1  -1  1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   0   0  -1  1  1   -1⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   0   0  -1  1  -1  1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   1   1  1   1  1   1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   0   0  1   1  -1  -1⎥\n",
+       "⎢                              ⎥\n",
+       "⎣0  0  0   0   0  1   1  1   1 ⎦"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "M = moment_matrix(moments, stencil=d2q9)\n",
+    "M"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ \\left ( 1, \\quad \\rho, \\quad \\omega\\right ), \\quad \\left ( y, \\quad \\rho u_{1}, \\quad \\omega\\right ), \\quad \\left ( y^{2}, \\quad \\rho u_{1}^{2} + \\frac{\\rho}{3}, \\quad \\omega\\right ), \\quad \\left ( x, \\quad \\rho u_{0}, \\quad \\omega\\right ), \\quad \\left ( x y, \\quad \\rho u_{0} u_{1}, \\quad \\omega\\right ), \\quad \\left ( x y^{2}, \\quad \\frac{\\rho u_{0}}{3}, \\quad \\omega\\right ), \\quad \\left ( x^{2}, \\quad \\rho u_{0}^{2} + \\frac{\\rho}{3}, \\quad \\omega\\right ), \\quad \\left ( x^{2} y, \\quad \\frac{\\rho u_{1}}{3}, \\quad \\omega\\right ), \\quad \\left ( x^{2} y^{2}, \\quad \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}, \\quad \\omega\\right )\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡                                                                             \n",
+       "⎢                         ⎛ 2      2   ρ   ⎞                                  \n",
+       "⎢(1, ρ, ω), (y, ρ⋅u₁, ω), ⎜y , ρ⋅u₁  + ─, ω⎟, (x, ρ⋅u₀, ω), (x⋅y, ρ⋅u₀⋅u₁, ω),\n",
+       "⎣                         ⎝            3   ⎠                                  \n",
+       "\n",
+       "                                                       ⎛           2       2  \n",
+       " ⎛   2  ρ⋅u₀   ⎞  ⎛ 2      2   ρ   ⎞  ⎛ 2    ρ⋅u₁   ⎞  ⎜ 2  2  ρ⋅u₀    ρ⋅u₁   \n",
+       " ⎜x⋅y , ────, ω⎟, ⎜x , ρ⋅u₀  + ─, ω⎟, ⎜x ⋅y, ────, ω⎟, ⎜x ⋅y , ───── + ───── +\n",
+       " ⎝       3     ⎠  ⎝            3   ⎠  ⎝       3     ⎠  ⎝         3       3    \n",
+       "\n",
+       "     ⎞⎤\n",
+       " ρ   ⎟⎥\n",
+       " ─, ω⎟⎥\n",
+       " 9   ⎠⎦"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.maxwellian_equilibrium import get_moments_of_continuous_maxwellian_equilibrium\n",
+    "\n",
+    "eq_moments = get_moments_of_continuous_maxwellian_equilibrium(moments, order=2, dim=2, \n",
+    "                                                              c_s_sq=sp.Rational(1, 3))\n",
+    "omega = sp.symbols(\"omega\")\n",
+    "relaxation_info = [(moment, eq_value, omega) for moment, eq_value in zip(moments, eq_moments)]\n",
+    "relaxation_info"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$\\omega$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$\\rho u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\rho u_{1}^{2} + \\frac{\\rho}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$\\rho u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$\\rho u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\rho u_{0}^{2} + \\frac{\\rho}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7fd077d75828>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.methods.creationfunctions import create_generic_mrt\n",
+    "\n",
+    "force_model = forcemodels.Guo(sp.symbols(\"F_:2\"))\n",
+    "method = create_generic_mrt(d2q9, relaxation_info, compressible=False, force_model=force_model, cumulant=False)\n",
+    "method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example of a update equation without simplifications"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>Subexpressions:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$$vel0Term \\leftarrow f_{4} + f_{6} + f_{8}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$vel1Term \\leftarrow f_{1} + f_{5}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\rho \\leftarrow f_{0} + f_{2} + f_{3} + f_{7} + vel0Term + vel1Term$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$u_{0} \\leftarrow \\frac{F_{0}}{2} - f_{3} - f_{5} - f_{7} + vel0Term$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$u_{1} \\leftarrow \\frac{F_{1}}{2} - f_{2} + f_{6} - f_{7} - f_{8} + vel1Term$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$forceTerm_{0} \\leftarrow \\left(- \\frac{\\omega}{2} + 1\\right) \\left(- \\frac{4 F_{0} u_{0}}{3} - \\frac{4 F_{1} u_{1}}{3}\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$forceTerm_{1} \\leftarrow \\left(- \\frac{\\omega}{2} + 1\\right) \\left(- \\frac{F_{0} u_{0}}{3} + \\frac{F_{1} \\left(2 u_{1} + 1\\right)}{3}\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$forceTerm_{2} \\leftarrow \\left(- \\frac{\\omega}{2} + 1\\right) \\left(- \\frac{F_{0} u_{0}}{3} + \\frac{F_{1} \\left(2 u_{1} - 1\\right)}{3}\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$forceTerm_{3} \\leftarrow \\left(- \\frac{\\omega}{2} + 1\\right) \\left(\\frac{F_{0} \\left(2 u_{0} - 1\\right)}{3} - \\frac{F_{1} u_{1}}{3}\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$forceTerm_{4} \\leftarrow \\left(- \\frac{\\omega}{2} + 1\\right) \\left(\\frac{F_{0} \\left(2 u_{0} + 1\\right)}{3} - \\frac{F_{1} u_{1}}{3}\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$forceTerm_{5} \\leftarrow \\left(- \\frac{\\omega}{2} + 1\\right) \\left(\\frac{F_{0} \\left(2 u_{0} - 3 u_{1} - 1\\right)}{12} + \\frac{F_{1} \\left(- 3 u_{0} + 2 u_{1} + 1\\right)}{12}\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$forceTerm_{6} \\leftarrow \\left(- \\frac{\\omega}{2} + 1\\right) \\left(\\frac{F_{0} \\left(2 u_{0} + 3 u_{1} + 1\\right)}{12} + \\frac{F_{1} \\left(3 u_{0} + 2 u_{1} + 1\\right)}{12}\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$forceTerm_{7} \\leftarrow \\left(- \\frac{\\omega}{2} + 1\\right) \\left(\\frac{F_{0} \\left(2 u_{0} + 3 u_{1} - 1\\right)}{12} + \\frac{F_{1} \\left(3 u_{0} + 2 u_{1} - 1\\right)}{12}\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$forceTerm_{8} \\leftarrow \\left(- \\frac{\\omega}{2} + 1\\right) \\left(\\frac{F_{0} \\left(2 u_{0} - 3 u_{1} + 1\\right)}{12} + \\frac{F_{1} \\left(- 3 u_{0} + 2 u_{1} - 1\\right)}{12}\\right)$$</td>  </tr> </table><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$$d_{0} \\leftarrow f_{0} + forceTerm_{0} + \\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right) - \\omega \\left(- f_{1} - f_{2} - f_{5} - f_{6} - f_{7} - f_{8} + \\rho u_{1}^{2} + \\frac{\\rho}{3}\\right) - \\omega \\left(- f_{3} - f_{4} - f_{5} - f_{6} - f_{7} - f_{8} + \\rho u_{0}^{2} + \\frac{\\rho}{3}\\right) + \\omega \\left(- f_{0} - f_{1} - f_{2} - f_{3} - f_{4} - f_{5} - f_{6} - f_{7} - f_{8} + \\rho\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$d_{1} \\leftarrow f_{1} + forceTerm_{1} - \\frac{\\omega \\left(- f_{5} - f_{6} + f_{7} + f_{8} + \\frac{\\rho u_{1}}{3}\\right)}{2} + \\frac{\\omega \\left(- f_{1} + f_{2} - f_{5} - f_{6} + f_{7} + f_{8} + \\rho u_{1}\\right)}{2} - \\frac{\\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right)}{2} + \\frac{\\omega \\left(- f_{1} - f_{2} - f_{5} - f_{6} - f_{7} - f_{8} + \\rho u_{1}^{2} + \\frac{\\rho}{3}\\right)}{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$d_{2} \\leftarrow f_{2} + forceTerm_{2} + \\frac{\\omega \\left(- f_{5} - f_{6} + f_{7} + f_{8} + \\frac{\\rho u_{1}}{3}\\right)}{2} - \\frac{\\omega \\left(- f_{1} + f_{2} - f_{5} - f_{6} + f_{7} + f_{8} + \\rho u_{1}\\right)}{2} - \\frac{\\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right)}{2} + \\frac{\\omega \\left(- f_{1} - f_{2} - f_{5} - f_{6} - f_{7} - f_{8} + \\rho u_{1}^{2} + \\frac{\\rho}{3}\\right)}{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$d_{3} \\leftarrow f_{3} + forceTerm_{3} + \\frac{\\omega \\left(f_{5} - f_{6} + f_{7} - f_{8} + \\frac{\\rho u_{0}}{3}\\right)}{2} - \\frac{\\omega \\left(f_{3} - f_{4} + f_{5} - f_{6} + f_{7} - f_{8} + \\rho u_{0}\\right)}{2} - \\frac{\\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right)}{2} + \\frac{\\omega \\left(- f_{3} - f_{4} - f_{5} - f_{6} - f_{7} - f_{8} + \\rho u_{0}^{2} + \\frac{\\rho}{3}\\right)}{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$d_{4} \\leftarrow f_{4} + forceTerm_{4} - \\frac{\\omega \\left(f_{5} - f_{6} + f_{7} - f_{8} + \\frac{\\rho u_{0}}{3}\\right)}{2} + \\frac{\\omega \\left(f_{3} - f_{4} + f_{5} - f_{6} + f_{7} - f_{8} + \\rho u_{0}\\right)}{2} - \\frac{\\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right)}{2} + \\frac{\\omega \\left(- f_{3} - f_{4} - f_{5} - f_{6} - f_{7} - f_{8} + \\rho u_{0}^{2} + \\frac{\\rho}{3}\\right)}{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$d_{5} \\leftarrow f_{5} + forceTerm_{5} + \\frac{\\omega \\left(- f_{5} - f_{6} + f_{7} + f_{8} + \\frac{\\rho u_{1}}{3}\\right)}{4} - \\frac{\\omega \\left(f_{5} - f_{6} - f_{7} + f_{8} + \\rho u_{0} u_{1}\\right)}{4} - \\frac{\\omega \\left(f_{5} - f_{6} + f_{7} - f_{8} + \\frac{\\rho u_{0}}{3}\\right)}{4} + \\frac{\\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right)}{4}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$d_{6} \\leftarrow f_{6} + forceTerm_{6} + \\frac{\\omega \\left(- f_{5} - f_{6} + f_{7} + f_{8} + \\frac{\\rho u_{1}}{3}\\right)}{4} + \\frac{\\omega \\left(f_{5} - f_{6} - f_{7} + f_{8} + \\rho u_{0} u_{1}\\right)}{4} + \\frac{\\omega \\left(f_{5} - f_{6} + f_{7} - f_{8} + \\frac{\\rho u_{0}}{3}\\right)}{4} + \\frac{\\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right)}{4}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} - \\frac{\\omega \\left(- f_{5} - f_{6} + f_{7} + f_{8} + \\frac{\\rho u_{1}}{3}\\right)}{4} + \\frac{\\omega \\left(f_{5} - f_{6} - f_{7} + f_{8} + \\rho u_{0} u_{1}\\right)}{4} - \\frac{\\omega \\left(f_{5} - f_{6} + f_{7} - f_{8} + \\frac{\\rho u_{0}}{3}\\right)}{4} + \\frac{\\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right)}{4}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$d_{8} \\leftarrow f_{8} + forceTerm_{8} - \\frac{\\omega \\left(- f_{5} - f_{6} + f_{7} + f_{8} + \\frac{\\rho u_{1}}{3}\\right)}{4} - \\frac{\\omega \\left(f_{5} - f_{6} - f_{7} + f_{8} + \\rho u_{0} u_{1}\\right)}{4} + \\frac{\\omega \\left(f_{5} - f_{6} + f_{7} - f_{8} + \\frac{\\rho u_{0}}{3}\\right)}{4} + \\frac{\\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right)}{4}$$</td>  </tr> </table>"
+      ],
+      "text/plain": [
+       "Equation Collection for d_0,d_1,d_2,d_3,d_4,d_5,d_6,d_7,d_8"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "collision_rule = method.get_collision_rule()\n",
+    "collision_rule"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Generic simplification strategy - common subexpresssion elimination"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table style=\"border:none\"><tr><th>Name</th><th>Runtime</th><th>Adds</th><th>Muls</th><th>Divs</th><th>Total</th></tr><tr><td>OriginalTerm</td><td>-</td> <td>293</td> <td>261</td> <td>0</td>  <td>554</td> </tr><tr><td>sympy_cse</td><td>61.27 ms</td> <td>114</td> <td>67</td> <td>0</td>  <td>181</td> </tr></table>"
+      ],
+      "text/plain": [
+       "<pystencils.simp.simplificationstrategy.SimplificationStrategy.create_simplification_report.<locals>.Report at 0x7fd077bef438>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "generic_strategy = ps.simp.SimplificationStrategy()\n",
+    "generic_strategy.add(ps.simp.sympy_cse)\n",
+    "generic_strategy.create_simplification_report(collision_rule)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### A custom simplification strategy for moment-based methods"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table style=\"border:none\"><tr><th>Name</th><th>Runtime</th><th>Adds</th><th>Muls</th><th>Divs</th><th>Total</th></tr><tr><td>OriginalTerm</td><td>-</td> <td>293</td> <td>261</td> <td>0</td>  <td>554</td> </tr><tr><td>expand</td><td>32.60 ms</td> <td>116</td> <td>227</td> <td>0</td>  <td>343</td> </tr><tr><td>replace_second_order_velocity_products</td><td>14.12 ms</td> <td>126</td> <td>235</td> <td>0</td>  <td>361</td> </tr><tr><td>expand</td><td>10.95 ms</td> <td>118</td> <td>227</td> <td>0</td>  <td>345</td> </tr><tr><td>factor_relaxation_rates</td><td>15.49 ms</td> <td>118</td> <td>184</td> <td>0</td>  <td>302</td> </tr><tr><td>replace_density_and_velocity</td><td>5.22 ms</td> <td>118</td> <td>184</td> <td>0</td>  <td>302</td> </tr><tr><td>replace_common_quadratic_and_constant_term</td><td>21.72 ms</td> <td>106</td> <td>148</td> <td>0</td>  <td>254</td> </tr><tr><td>factor_density_after_factoring_relaxation_times</td><td>15.14 ms</td> <td>106</td> <td>136</td> <td>0</td>  <td>242</td> </tr><tr><td>subexpression_substitution_in_main_assignments</td><td>12.94 ms</td> <td>102</td> <td>132</td> <td>0</td>  <td>234</td> </tr><tr><td>add_subexpressions_for_divisions</td><td>4.48 ms</td> <td>102</td> <td>132</td> <td>0</td>  <td>234</td> </tr><tr><td>cse_in_opposing_directions</td><td>12.80 ms</td> <td>102</td> <td>116</td> <td>0</td>  <td>218</td> </tr><tr><td>sympy_cse</td><td>42.44 ms</td> <td>86</td> <td>73</td> <td>0</td>  <td>159</td> </tr></table>"
+      ],
+      "text/plain": [
+       "<pystencils.simp.simplificationstrategy.SimplificationStrategy.create_simplification_report.<locals>.Report at 0x7fd077c7d080>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simplification_strategy = create_simplification_strategy(method, cse_pdfs=True, cse_global=True)\n",
+    "simplification_strategy.create_simplification_report(collision_rule)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Seeing the simplification in action"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<h5 style=\"padding-bottom:10px\">Initial Version</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} - \\frac{\\omega \\left(- f_{5} - f_{6} + f_{7} + f_{8} + \\frac{\\rho u_{1}}{3}\\right)}{4} + \\frac{\\omega \\left(f_{5} - f_{6} - f_{7} + f_{8} + \\rho u_{0} u_{1}\\right)}{4} - \\frac{\\omega \\left(f_{5} - f_{6} + f_{7} - f_{8} + \\frac{\\rho u_{0}}{3}\\right)}{4} + \\frac{\\omega \\left(- f_{5} - f_{6} - f_{7} - f_{8} + \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right)}{4}$$</div><h5 style=\"padding-bottom:10px\">expand</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow - f_{7} \\omega + f_{7} + forceTerm_{7} + \\frac{\\omega \\rho u_{0}^{2}}{12} + \\frac{\\omega \\rho u_{0} u_{1}}{4} - \\frac{\\omega \\rho u_{0}}{12} + \\frac{\\omega \\rho u_{1}^{2}}{12} - \\frac{\\omega \\rho u_{1}}{12} + \\frac{\\omega \\rho}{36}$$</div><h5 style=\"padding-bottom:10px\">replace_second_order_velocity_products</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow - f_{7} \\omega + f_{7} + forceTerm_{7} + \\frac{\\omega \\rho u_{0}^{2}}{12} - \\frac{\\omega \\rho u_{0}}{12} + \\frac{\\omega \\rho u_{1}^{2}}{12} - \\frac{\\omega \\rho u_{1}}{12} + \\frac{\\omega \\rho \\left(u0Pu1^{2} - u_{0}^{2} - u_{1}^{2}\\right)}{8} + \\frac{\\omega \\rho}{36}$$</div><h5 style=\"padding-bottom:10px\">expand</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow - f_{7} \\omega + f_{7} + forceTerm_{7} + \\frac{\\omega \\rho u0Pu1^{2}}{8} - \\frac{\\omega \\rho u_{0}^{2}}{24} - \\frac{\\omega \\rho u_{0}}{12} - \\frac{\\omega \\rho u_{1}^{2}}{24} - \\frac{\\omega \\rho u_{1}}{12} + \\frac{\\omega \\rho}{36}$$</div><h5 style=\"padding-bottom:10px\">factor_relaxation_rates</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} + \\omega \\left(- f_{7} + \\frac{\\rho u0Pu1^{2}}{8} - \\frac{\\rho u_{0}^{2}}{24} - \\frac{\\rho u_{0}}{12} - \\frac{\\rho u_{1}^{2}}{24} - \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\right)$$</div><h5 style=\"padding-bottom:10px\">replace_density_and_velocity</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} + \\omega \\left(- f_{7} + \\frac{\\rho u0Pu1^{2}}{8} - \\frac{\\rho u_{0}^{2}}{24} - \\frac{\\rho u_{0}}{12} - \\frac{\\rho u_{1}^{2}}{24} - \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\right)$$</div><h5 style=\"padding-bottom:10px\">replace_common_quadratic_and_constant_term</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} + \\omega \\left(- f_{7} + \\frac{f_{eq common}}{36} + \\frac{\\rho u0Pu1^{2}}{8} - \\frac{\\rho u_{0}}{12} - \\frac{\\rho u_{1}}{12}\\right)$$</div><h5 style=\"padding-bottom:10px\">factor_density_after_factoring_relaxation_times</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} + \\omega \\left(- f_{7} + \\frac{f_{eq common}}{36} + \\rho \\left(\\frac{u0Pu1^{2}}{8} - \\frac{u_{0}}{12} - \\frac{u_{1}}{12}\\right)\\right)$$</div><h5 style=\"padding-bottom:10px\">subexpression_substitution_in_main_assignments</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} + \\omega \\left(- f_{7} + \\frac{f_{eq common}}{36} + \\rho \\left(\\frac{u0Pu1^{2}}{8} - \\frac{u0Pu1}{12}\\right)\\right)$$</div><h5 style=\"padding-bottom:10px\">add_subexpressions_for_divisions</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} + \\omega \\left(- f_{7} + \\frac{f_{eq common}}{36} + \\rho \\left(\\frac{u0Pu1^{2}}{8} - \\frac{u0Pu1}{12}\\right)\\right)$$</div><h5 style=\"padding-bottom:10px\">cse_in_opposing_directions</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} + \\omega \\left(- f_{7} + \\rho \\left(- \\xi_{72} + \\xi_{73}\\right) + \\xi_{71}\\right)$$</div><h5 style=\"padding-bottom:10px\">sympy_cse</h5> <div style=\"padding-left:20px;\">$$d_{7} \\leftarrow f_{7} + forceTerm_{7} + \\omega \\left(\\rho \\left(- \\xi_{72} + \\xi_{73}\\right) + \\xi_{71} + \\xi_{76}\\right)$$</div>"
+      ],
+      "text/plain": [
+       "<pystencils.simp.simplificationstrategy.SimplificationStrategy.show_intermediate_results.<locals>.IntermediateResults at 0x7fd077d6cef0>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simplification_strategy.show_intermediate_results(collision_rule, symbols=[sp.Symbol(\"d_7\")])"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/doc/notebooks/demo_moments_cumulants_and_maxwellian_equilibrium.ipynb b/doc/notebooks/demo_moments_cumulants_and_maxwellian_equilibrium.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..d5c0d83c2da0584c52bcd3efb2b6a3dec1087a47
--- /dev/null
+++ b/doc/notebooks/demo_moments_cumulants_and_maxwellian_equilibrium.ipynb
@@ -0,0 +1,811 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "nbsphinx": "hidden"
+   },
+   "outputs": [],
+   "source": [
+    "from lbmpy.cumulants import *\n",
+    "from lbmpy.moments import *\n",
+    "from lbmpy.continuous_distribution_measures import continuous_moment\n",
+    "from lbmpy.stencils import get_stencil\n",
+    "from pystencils.stencils import visualize_stencil_2d\n",
+    "import sympy as sp\n",
+    "sp.init_printing()\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo: Moments, Cumulants and Maxwellian Equilibrium\n",
+    "\n",
+    "## 1) Moments & Cumulants\n",
+    "\n",
+    "\n",
+    "### Moments\n",
+    "\n",
+    "The *moments* and *cumulants* modules contain functions to calculate moments and cumulants of functions on a discrete velocity space defined by a stencil. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left ( f_{0}, \\quad f_{1}, \\quad f_{2}, \\quad f_{3}, \\quad f_{4}, \\quad f_{5}, \\quad f_{6}, \\quad f_{7}, \\quad f_{8}\\right )$$"
+      ],
+      "text/plain": [
+       "(f₀, f₁, f₂, f₃, f₄, f₅, f₆, f₇, f₈)"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stencil = get_stencil(\"D2Q9\")\n",
+    "pdfs = sp.symbols(\"f:9\")\n",
+    "pdfs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Discrete moments are computed by following formula:\n",
+    "\n",
+    "$$ \\sum_{d \\in S} d_1^{m_1} d_2^{m_2} \\; f_d  $$ \n",
+    "\n",
+    "with $S$ being the stencil, $d_i$ the direction components, $f_d$ the function values for each direction and $m_j$ the components of the moment tuple.\n",
+    "\n",
+    "Lets compute the first moment in the first direction, i.e. $(m_1, m_2) = (1,0)$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "visualize_stencil_2d(stencil)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$- f_{3} + f_{4} - f_{5} + f_{6} - f_{7} + f_{8}$$"
+      ],
+      "text/plain": [
+       "-f₃ + f₄ - f₅ + f₆ - f₇ + f₈"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discrete_moment(pdfs, (1, 0), stencil)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We get contributions of all directions that have a non-zero x-component, weighted with the sign of the direction. \n",
+    "\n",
+    "For the second order moment, the direction components are squared, so all contributions come in with a positive sign."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$f_{3} + f_{4} + f_{5} + f_{6} + f_{7} + f_{8}$$"
+      ],
+      "text/plain": [
+       "f₃ + f₄ + f₅ + f₆ + f₇ + f₈"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discrete_moment(pdfs, (2, 0), stencil)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can specify the moments not only as exponent tuples but also as polynomials in the $d_i$'s. \n",
+    "The symbols for the $d_i$ are provided by the *moments* module as ``MOMENT_SYMBOLS``"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$- f_{3} + f_{4} - f_{5} + f_{6} - f_{7} + f_{8}$$"
+      ],
+      "text/plain": [
+       "-f₃ + f₄ - f₅ + f₆ - f₇ + f₈"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x, y, z = MOMENT_SYMBOLS\n",
+    "discrete_moment(pdfs, x, stencil)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The same works also for sums:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$f_{1} + f_{2} + 2 f_{5} + 2 f_{6}$$"
+      ],
+      "text/plain": [
+       "f₁ + f₂ + 2⋅f₅ + 2⋅f₆"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discrete_moment(pdfs, x**2 * y + y**2, stencil)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here the advantage of the polynomial representation becomes visible. \n",
+    "To compute the same moment with exponent tuples takes two calls:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$f_{1} + f_{2} + 2 f_{5} + 2 f_{6}$$"
+      ],
+      "text/plain": [
+       "f₁ + f₂ + 2⋅f₅ + 2⋅f₆"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discrete_moment(pdfs, (2, 1), stencil) + discrete_moment(pdfs, (0, 2), stencil)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Cumulants\n",
+    "\n",
+    "Cumulants are an alternative to the moment represenation, see the [Wikipedia article](https://en.wikipedia.org/wiki/Cumulant). Cumulants can be calculated directly using the cumulant generating function, or can be calculated by moments."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{f_{3} + f_{4} + f_{5} + f_{6} + f_{7} + f_{8} - \\frac{\\left(f_{3} - f_{4} + f_{5} - f_{6} + f_{7} - f_{8}\\right)^{2}}{f_{0} + f_{1} + f_{2} + f_{3} + f_{4} + f_{5} + f_{6} + f_{7} + f_{8}}}{f_{0} + f_{1} + f_{2} + f_{3} + f_{4} + f_{5} + f_{6} + f_{7} + f_{8}}$$"
+      ],
+      "text/plain": [
+       "                                                                 2      \n",
+       "                                    (f₃ - f₄ + f₅ - f₆ + f₇ - f₈)       \n",
+       "f₃ + f₄ + f₅ + f₆ + f₇ + f₈ - ──────────────────────────────────────────\n",
+       "                              f₀ + f₁ + f₂ + f₃ + f₄ + f₅ + f₆ + f₇ + f₈\n",
+       "────────────────────────────────────────────────────────────────────────\n",
+       "               f₀ + f₁ + f₂ + f₃ + f₄ + f₅ + f₆ + f₇ + f₈               "
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discrete_cumulant(pdfs, (2, 0), stencil)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{m_{2 0}}{m_{0 0}} - \\frac{m_{1 0}^{2}}{m_{0 0}^{2}}$$"
+      ],
+      "text/plain": [
+       "           2\n",
+       "m₂ ₀   m₁ ₀ \n",
+       "──── - ─────\n",
+       "mâ‚€ â‚€       2\n",
+       "       mâ‚€ â‚€ "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cumulant_as_function_of_raw_moments((2,0))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$c_{1 0}^{2} e^{c_{0 0}} + c_{2 0} e^{c_{0 0}}$$"
+      ],
+      "text/plain": [
+       "    2  câ‚€ â‚€         câ‚€ â‚€\n",
+       "c₁ ₀ ⋅ℯ     + c₂ ₀⋅ℯ    "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_moment_as_function_of_cumulants((2,0))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2) Using Moments to derive discrete LBM equilibrium\n",
+    "\n",
+    "For full stencils i.e. *D2Q9* and *D3Q27* a LBM equilibrium can be derived using the following strategy:\n",
+    "\n",
+    "- calculate all moments or cumulants up to second order of the continuous Maxwell-Boltzmann distribution\n",
+    "- for full stencils there are as many moments/cumulants as stencil directions, so we can determine the pdf values from them"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First we obtain the continuous Maxwellian equilibrium as *sympy* expression. We fix the speed of sound to $\\frac{1}{3}$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{3 \\rho e^{- \\frac{3 \\left(- u_{0} + v_{0}\\right)^{2}}{2} - \\frac{3 \\left(- u_{1} + v_{1}\\right)^{2}}{2}}}{2 \\pi}$$"
+      ],
+      "text/plain": [
+       "                   2               2\n",
+       "       3⋅(-u₀ + v₀)    3⋅(-u₁ + v₁) \n",
+       "     - ───────────── - ─────────────\n",
+       "             2               2      \n",
+       "3⋅ρ⋅ℯ                               \n",
+       "────────────────────────────────────\n",
+       "                2â‹…Ï€                 "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.maxwellian_equilibrium import continuous_maxwellian_equilibrium, discrete_maxwellian_equilibrium\n",
+    "\n",
+    "dim = len(stencil[0])\n",
+    "maxwellian = continuous_maxwellian_equilibrium(dim=dim, c_s_sq=sp.Rational(1,3))\n",
+    "maxwellian"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we get all moment exponent tuples up to order 2 and calculate these moments of the continuous Maxwellian equilibrium:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left ( \\left ( 0, \\quad 0\\right ), \\quad \\left ( 0, \\quad 1\\right ), \\quad \\left ( 0, \\quad 2\\right ), \\quad \\left ( 1, \\quad 0\\right ), \\quad \\left ( 1, \\quad 1\\right ), \\quad \\left ( 1, \\quad 2\\right ), \\quad \\left ( 2, \\quad 0\\right ), \\quad \\left ( 2, \\quad 1\\right ), \\quad \\left ( 2, \\quad 2\\right )\\right )$$"
+      ],
+      "text/plain": [
+       "((0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2))"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "moments = moments_up_to_component_order(2, dim=dim)\n",
+    "moments"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ \\rho, \\quad \\rho u_{1}, \\quad \\frac{\\rho \\left(9 u_{1}^{2} + 3\\right)}{9}, \\quad \\rho u_{0}, \\quad \\rho u_{0} u_{1}, \\quad \\frac{\\rho u_{0} \\left(9 u_{1}^{2} + 3\\right)}{9}, \\quad \\frac{\\rho \\left(9 u_{0}^{2} + 3\\right)}{9}, \\quad \\frac{\\rho u_{1} \\left(9 u_{0}^{2} + 3\\right)}{9}, \\quad \\frac{\\rho \\left(9 u_{0}^{2} + 3\\right) \\left(9 u_{1}^{2} + 3\\right)}{81}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡           ⎛    2    ⎞                      ⎛    2    ⎞    ⎛    2    ⎞       \n",
+       "⎢         ρ⋅⎝9⋅u₁  + 3⎠                 ρ⋅u₀⋅⎝9⋅u₁  + 3⎠  ρ⋅⎝9⋅u₀  + 3⎠  ρ⋅u₁⋅\n",
+       "⎢ρ, ρ⋅u₁, ─────────────, ρ⋅u₀, ρ⋅u₀⋅u₁, ────────────────, ─────────────, ─────\n",
+       "⎣               9                              9                9             \n",
+       "\n",
+       "⎛    2    ⎞    ⎛    2    ⎞ ⎛    2    ⎞⎤\n",
+       "⎝9⋅u₀  + 3⎠  ρ⋅⎝9⋅u₀  + 3⎠⋅⎝9⋅u₁  + 3⎠⎥\n",
+       "───────────, ─────────────────────────⎥\n",
+       "  9                      81           ⎦"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cont_eq_moments = [continuous_moment(maxwellian, m, sp.symbols(\"v_:2\")[:dim]) for m in moments]\n",
+    "cont_eq_moments"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To obtain the same equilibrium as in the LBM literature, we have to drop all terms that have order 3 or higher:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ \\rho, \\quad \\rho u_{1}, \\quad \\rho u_{1}^{2} + \\frac{\\rho}{3}, \\quad \\rho u_{0}, \\quad \\rho u_{0} u_{1}, \\quad \\rho u_{0} u_{1}^{2} + \\frac{\\rho u_{0}}{3}, \\quad \\rho u_{0}^{2} + \\frac{\\rho}{3}, \\quad \\rho u_{0}^{2} u_{1} + \\frac{\\rho u_{1}}{3}, \\quad \\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho}{9}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡                                                                             \n",
+       "⎢             2   ρ                        2   ρ⋅u₀      2   ρ      2      ρ⋅u\n",
+       "⎢ρ, ρ⋅u₁, ρ⋅u₁  + ─, ρ⋅u₀, ρ⋅u₀⋅u₁, ρ⋅u₀⋅u₁  + ────, ρ⋅u₀  + ─, ρ⋅u₀ ⋅u₁ + ───\n",
+       "⎣                 3                             3            3              3 \n",
+       "\n",
+       "       2       2    ⎤\n",
+       "₁  ρ⋅u₀    ρ⋅u₁    ρ⎥\n",
+       "─, ───── + ───── + ─⎥\n",
+       "     3       3     9⎦"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cont_eq_moments = [remove_higher_order_terms(m, order=3, symbols=sp.symbols(\"u_:3\")) \n",
+    "                   for m in cont_eq_moments]\n",
+    "cont_eq_moments"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we take these equilibrium moments and determine pdf values, which would lead to these moment values.\n",
+    "The moment matrix transforms pdfs into moment space. To obtain the equilibrium pdfs we only have to transform the equilibrium moments with the inverse of this matrix:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWQAAADgCAMAAAADk+xoAAAAP1BMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADFBd4eAAAAFHRSTlMAMquZdlQQQO0wRO/NZondIrt8bFiOv0QAAAAJcEhZcwAADsQAAA7EAZUrDhsAAA0ZSURBVHgB7Z1tW9vYDkXDa2daoO29+f+/dXxsdiIlsvfWE6XJDOLDHGMtbx0vQmCCCruH/fz2uOu3cgM/F7e73cP+6Xl6eynv0IG792H2cT8kP7SOaxp4b8nX1Ltkn0p++fG61ZSUcamIJXE1VeRqsa17cZJfH58e9+uSSRltRCyJq6kiV4uRe3GSJ/Z5QzIvoxlJAYZVxEWM3cOVun7GRptsyXC+tkbW1tjpfIS35A1hcymytnFNhLfkDWEteV1O9GAK6FoMDaLUfiTDztoaWVtjp/MR3pI3hM2lyNrGNRHekjeEteR1OdGDKaBrMTSIUvuRDDtra2RtjZ3OR7iX/PT4Y//2+L6WQcq4TMSSuJoqcrXY9r14yWB7LTXQkkt1xmEtOfZSerYll+qMw1py7KX0bEsu1RmHteTYS+nZllyqMw5rybGX0rMtuVRnHNaSYy+lZ73k16eP948/PU4kNhWxUjtFYV7y2zQP9/rz13q2OBCCAAmnTZc0EZtgqauMpe4FsE93kt9/DOjj7Yi6I3EgBNeIOGmKNBHbiV1FDN0vw53k3/P07MvGfEv0aik2EqwKzpvOwSI2WKWrjs3dL8Od5P0s+ft+fYhW3H9mY7zpnCZigxU3KWKZewF7sgkr+XX/NKjv+2cD+8P6jQlNxxZEbN6tuEkRg4ALcCv51/5jJD4sC8LdekEnl3N8R2g6YBGbc8VNihi2egHuJc+P5D8tmTZdJEvY/UsWPiW3Ppyvbz8Pb2/LN9tb+OcjRGg6SBGrkpy8F4KPR/K3/bfljpcvLi+3+MK31XTeHN/bcg/Tf4UP7WBFDLEX4P+z/5zh9++R+P6Hv4WjTefb5HuDDdXeBdYOrdYPbLp9Tt4t3/A/rf3PyJRoL11vcKgoOG86x4nYYJWuOjZ3vwx3knc/x/9W/9h48ULcf2pjtOmSJmK6jmvcC27cf6S95NeP6R+drTsWB0LQScRJU6SJ2E7sKmLofhHuJSOy11IDLblUZxzWkmMvpWdbcqnOOKwlx15Kz7bkUp1xWEuOvZSeHZJfn9f/PXVps68a9mt6gb5/38WVP/r9dHFlwSO+Jf9xyTcZIBGbitgfcJZu4R/JdIDkGnMjtOlyUyI2wbWbFNNgPsKdZDJAIk54iBh2RZomseLhluS9rOBOMh8gEV+DFbFZIG+awQYrdq/F5k2uNHeS+QDJFTbGm877F7HB1m5STJs3udLcShZ+Iix2FLGxMaFpAhvofUsWBkhEeyI2jAhNE9hA710yHSAR7YnYYo82TWADvW/JwmeuaE/EhhGhaQIb6H1Krh9uSUjeiVMrInaXkq8z3JKRLE6tiNhdSrbfXdQNt2Qki1MrInb/ksuGWzKSedMhbqdiEyl2r8XmPa40d4/kHRkgESc8RAzbIk2TWPFwS/JeYtxLxg31WmqgJZfqjMNacuyl9GxLLtUZh7Xk2Evp2ZZcqjMOa8mxl9KzQ3IPt5QqPQ/r4ZZzJ+Vn+umiXOl5YEs+d1J+xksmAySkjM2JGPD//uolkwESUoYtEQN+XKPBkGNVHVo5XFEbR9LQNcKcZDJnQspoI2LAsa4MhohlYIe1No6koesK5iSTORNSRicRA25W8govKZug5ZDwpHwaJ+IR5iSTARJSxq5EDLhZow3qZUMuh7VxJA3dI8xKJj84JmV0ETHgdo02aOqkbMjlkPCkfBon4hFmJZM5E1LGpkQMuF2jDZo6KRtyOSQ8KZ/GiXiEecmbcya/ll9RtPWLXcbGROz0Hsb70QYNR8qGXA4JT8qncSIeYVYy+UQnZWxKxHbkt50gzqzR/g/l2rh8GjYSbXJIVodbxPkSEcOuzBptUC8bcjmsjSNp6B5hmeEWcb5ExLArs0Yb1MuGXA5r40gaukeYfbpgwy3ifImIYVdmjTaolw25HNbGkTR0jzAnmQ2QiL88RcSwreMabfBYZV8XDbkc1saRNHSPMC+ZzJmQMvqIGHCs8WAIqurQisqTboeYzwMRjzEv+TS63y8x0JJLNG6HtORtPyXVllyicTukJW/7Kam25BKN2yEtedtPSXVIPrx2UZLYIWcG3GsXZ9U+UWKgny5KNG6HtORtPyVVL5mMpZAyNiRiSTyZivR7WL1kMpZCyrgfEUviydQpPZozQVNeBklSgJ2u9jInmYylkDLaiFgST6ay3+CyMoaCTWEVMeBYTy5zkslYCimjg4gl8WTqSI9e2kVXXgZJUoCdrvYyJ5mMpZAy2ohYEk+mjnR7n+hmVlIGKWLAsdrLrGTyc2ZSRrqIJfFk6pxu7xPtzErKIEUMOFZ7mZVMxlJIGekilsSTqXO6vU+0MyspgxQx4FjtZV7yDYZbxFkYEcMtzqu9T1dY3iFlXCFiwLHay4Zk/MMc8ilJykgXsSROU/PjKFYDdhOsCkaau3+Ys3xxWf0LQaSMDYpYEk+mjnSih5SxPxEDjtVeZp8udmQshZQRL2JJPJk60u19optZSRmkiAHHai9zkpdv+Ff/LBEpI17EkngydaTb+0Q3s5IySBEDjtVe5iTfZrhFnIURMdzktNr7NKdxSMpJDDhWm+4lk7EUUka+iCXxZCobhonHULCnwypiB/7zwF/mJZ+y/X6JgZZconE7pCVv+ymptuQSjdshLXnbT0m1JZdo3A5pydt+SqpDcg+3lKhcD+nhlnU3ZZV+uihTuR7UktfdlFW8ZDJAQsrYlIgl8WQq0u9h9ZLJAAkp435ELIknU6d0O1+CZmYlZUPOhyIeYU7y8prtx9qfuSdl7ErEkngytWi4BZs8mVbB6dN1BXOSyQAJKaOjiCXxZOpIty/poptZSdmQ86GIR5iTvPwc7fv+5bTB8j4p4yIRS+LJ1JEe3S+68rIh50OSBjzCrGTyE2FSRhcRS+LJVEVLpAO7ClYRjzArmQyQkDL2JWJJPJk6p0f3i7bTSsqGVNKAR6lecg+3wNX5Gtk7p8IP3ZDcwy1nssi0yhl/PBF9LHq45ehn+yiyF1wRYfbpoodbAmmHU5G9Q/F4EGFO8vINfw+3HJWZo8ieKeMwwpzkHm6BqmCN7ImYl0wGSEgZLUUsiSdTi4ZbsEk/rYKzZ2uMeclnF/WJCgMtucIiyWjJRFBFuSVXWCQZLZkIqii35AqLJKMlE0EV5SG5h1sqTG5k9HDLhpyqUj9dVJncyGnJG3KqSl4yGSAhZexJxID/91cvmQyQkDJsiRhwOoUCMJobQc2uIleLYQNRqpNMBkhIGW1EDPjKQAjKWEWMDbUk49Sun7EruJNMBkhIGfsXMeDTesFLtSblcFgbJ6ahe4Q7yWSAhJTRRsSAT2u0MVPGoYgVx6ldP3cZ4VYyGSAhZagQMeBjjTZm65/HIlYcp3bd2KSVTAZISBlWRAz4WMX7ELHiOLXr5w1FuJd8g+GWryL5psMtX0Hy7YdbvtjTxW2GW76a5JsMt3w1ybcZbvla311M850fz8+PD+NrUfhGyrhGxIDHAyGoHlYRY0MtyBPjRGw71X4LB7LXYgMtuVhoFNeSIyvF51pysdAoriVHVorPteRioVFcS46sFJ8bknu4pVjqaVwPt5waucL7/XRxBamnkS351MgV3veSyVgKKWN7IpbEk6lIv4fVSyZjKaSM+xGxJK6nRvMlaGZWEcMVF+BOMhlLIWXsRsSSuJq6Ml+CblhFrAZ3kslYCiljQyKWxBOp0Q+M0c2sIoYrLsCdZDKWQsrYjYgl8USqqEPEsM8LcCuZjKWQMjYjYkk8kyrqEDFs9ALcSiZjKaSMzYhYEs+kijpEDBu9APeSbzDcIv69IRGbjYg6RKxI8re//p6TyKckKWMzIpbEM6mivS0s+ZtbCP7/v3a7h/3nz06XLy7/+j9LtGUPH9tpFTFccQFuny5uM9wi/r0hERtKRB0iVi15+Yb/X/+bW0R7IlYt+TbDLeLfGxKxu38k32a4RZyFEbHi4RY8ji8acnHPyUjstdZAS671Gaa15FBL7cmWXOszTGvJoZbaky251meY1pJDLbUnW3KtzzCtJYdaak+25FqfYVpLDrXUnvSSyQAJKWNnIpbEk6lIv4fVSyYDJKSM+xGxJK6nimMotRjuJkp1kskACSmjjYglcTVVnFqpxXAvK6lOMhkgIWV0ErEknkgVX42vxXA7UaqTTAZISBltRCyJJ1Kj+0Q3s9ZiCI5SrWTyE2FSRhcRS+KZ1Og+0c6stRiCo1QrmQyQkDK6iFgSz6RG94l2Zq3FEBylesk93AJXxzWydqyeHUW4lUw+JUkZ7UQsiWdSo/tEO7PWYgiOUq3k3fLFpYdbIGxeI2sO8O9EuJNMBkhIGc1ELIknUqP7RDez1mIIjlKd5OUb/h5ugbB5jaw5wL8T4U5yD7d4YdeRTAZISBk7FLEkrqaKYyi1GO4lTvWPZLC9lhpoyaU647CWHHspPduSS3XGYS059lJ6dpG8H2+PpcEdNhv4Oaud/6Ty83j73l7qDbzPap93/wAdke0u6RSmcAAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1\\\\0 & 1 & -1 & 0 & 0 & 1 & 1 & -1 & -1\\\\0 & 1 & 1 & 0 & 0 & 1 & 1 & 1 & 1\\\\0 & 0 & 0 & -1 & 1 & -1 & 1 & -1 & 1\\\\0 & 0 & 0 & 0 & 0 & -1 & 1 & 1 & -1\\\\0 & 0 & 0 & 0 & 0 & -1 & 1 & -1 & 1\\\\0 & 0 & 0 & 1 & 1 & 1 & 1 & 1 & 1\\\\0 & 0 & 0 & 0 & 0 & 1 & 1 & -1 & -1\\\\0 & 0 & 0 & 0 & 0 & 1 & 1 & 1 & 1\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡1  1  1   1   1  1   1  1   1 ⎤\n",
+       "⎢                              ⎥\n",
+       "⎢0  1  -1  0   0  1   1  -1  -1⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  1  1   0   0  1   1  1   1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   -1  1  -1  1  -1  1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   0   0  -1  1  1   -1⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   0   0  -1  1  -1  1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   1   1  1   1  1   1 ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢0  0  0   0   0  1   1  -1  -1⎥\n",
+       "⎢                              ⎥\n",
+       "⎣0  0  0   0   0  1   1  1   1 ⎦"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "M = moment_matrix(moments, stencil)\n",
+    "M"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}- \\frac{2 \\rho u_{0}^{2}}{3} - \\frac{2 \\rho u_{1}^{2}}{3} + \\frac{4 \\rho}{9}\\\\- \\frac{\\rho u_{0}^{2} u_{1}}{2} - \\frac{\\rho u_{0}^{2}}{6} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho u_{1}}{3} + \\frac{\\rho}{9}\\\\\\frac{\\rho u_{0}^{2} u_{1}}{2} - \\frac{\\rho u_{0}^{2}}{6} + \\frac{\\rho u_{1}^{2}}{3} - \\frac{\\rho u_{1}}{3} + \\frac{\\rho}{9}\\\\\\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{0} u_{1}^{2}}{2} - \\frac{\\rho u_{0}}{3} - \\frac{\\rho u_{1}^{2}}{6} + \\frac{\\rho}{9}\\\\\\frac{\\rho u_{0}^{2}}{3} - \\frac{\\rho u_{0} u_{1}^{2}}{2} + \\frac{\\rho u_{0}}{3} - \\frac{\\rho u_{1}^{2}}{6} + \\frac{\\rho}{9}\\\\\\frac{\\rho u_{0}^{2} u_{1}}{4} + \\frac{\\rho u_{0}^{2}}{12} - \\frac{\\rho u_{0} u_{1}^{2}}{4} - \\frac{\\rho u_{0} u_{1}}{4} - \\frac{\\rho u_{0}}{12} + \\frac{\\rho u_{1}^{2}}{12} + \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\\\\\frac{\\rho u_{0}^{2} u_{1}}{4} + \\frac{\\rho u_{0}^{2}}{12} + \\frac{\\rho u_{0} u_{1}^{2}}{4} + \\frac{\\rho u_{0} u_{1}}{4} + \\frac{\\rho u_{0}}{12} + \\frac{\\rho u_{1}^{2}}{12} + \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\\\- \\frac{\\rho u_{0}^{2} u_{1}}{4} + \\frac{\\rho u_{0}^{2}}{12} - \\frac{\\rho u_{0} u_{1}^{2}}{4} + \\frac{\\rho u_{0} u_{1}}{4} - \\frac{\\rho u_{0}}{12} + \\frac{\\rho u_{1}^{2}}{12} - \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\\\- \\frac{\\rho u_{0}^{2} u_{1}}{4} + \\frac{\\rho u_{0}^{2}}{12} + \\frac{\\rho u_{0} u_{1}^{2}}{4} - \\frac{\\rho u_{0} u_{1}}{4} + \\frac{\\rho u_{0}}{12} + \\frac{\\rho u_{1}^{2}}{12} - \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡                            2         2                           ⎤\n",
+       "⎢                      2⋅ρ⋅u₀    2⋅ρ⋅u₁    4⋅ρ                     ⎥\n",
+       "⎢                    - ─────── - ─────── + ───                     ⎥\n",
+       "⎢                         3         3       9                      ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢                    2          2       2                          ⎥\n",
+       "⎢                ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₁    ρ⋅u₁   ρ               ⎥\n",
+       "⎢              - ──────── - ───── + ───── + ──── + ─               ⎥\n",
+       "⎢                   2         6       3      3     9               ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢                   2          2       2                           ⎥\n",
+       "⎢               ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₁    ρ⋅u₁   ρ                ⎥\n",
+       "⎢               ──────── - ───── + ───── - ──── + ─                ⎥\n",
+       "⎢                  2         6       3      3     9                ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢                   2          2              2                    ⎥\n",
+       "⎢               ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀   ρ⋅u₁    ρ                ⎥\n",
+       "⎢               ───── + ──────── - ──── - ───── + ─                ⎥\n",
+       "⎢                 3        2        3       6     9                ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢                   2          2              2                    ⎥\n",
+       "⎢               ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀   ρ⋅u₁    ρ                ⎥\n",
+       "⎢               ───── - ──────── + ──── - ───── + ─                ⎥\n",
+       "⎢                 3        2        3       6     9                ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢     2          2          2                        2             ⎥\n",
+       "⎢ ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀⋅u₁   ρ⋅u₀   ρ⋅u₁    ρ⋅u₁   ρ  ⎥\n",
+       "⎢ ──────── + ───── - ──────── - ─────── - ──── + ───── + ──── + ── ⎥\n",
+       "⎢    4         12       4          4       12      12     12    36 ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢     2          2          2                        2             ⎥\n",
+       "⎢ ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀⋅u₁   ρ⋅u₀   ρ⋅u₁    ρ⋅u₁   ρ  ⎥\n",
+       "⎢ ──────── + ───── + ──────── + ─────── + ──── + ───── + ──── + ── ⎥\n",
+       "⎢    4         12       4          4       12      12     12    36 ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢      2          2          2                        2            ⎥\n",
+       "⎢  ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀⋅u₁   ρ⋅u₀   ρ⋅u₁    ρ⋅u₁   ρ ⎥\n",
+       "⎢- ──────── + ───── - ──────── + ─────── - ──── + ───── - ──── + ──⎥\n",
+       "⎢     4         12       4          4       12      12     12    36⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢      2          2          2                        2            ⎥\n",
+       "⎢  ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀⋅u₁   ρ⋅u₀   ρ⋅u₁    ρ⋅u₁   ρ ⎥\n",
+       "⎢- ──────── + ───── + ──────── - ─────── + ──── + ───── - ──── + ──⎥\n",
+       "⎣     4         12       4          4       12      12     12    36⎦"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "derived_eq = M.inv() * sp.Matrix(cont_eq_moments)\n",
+    "derived_eq"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the same as the standard discrete equilibrium found in LBM literature."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}- \\frac{2 \\rho u_{0}^{2}}{3} - \\frac{2 \\rho u_{1}^{2}}{3} + \\frac{4 \\rho}{9}\\\\- \\frac{\\rho u_{0}^{2} u_{1}}{2} - \\frac{\\rho u_{0}^{2}}{6} + \\frac{\\rho u_{1}^{2}}{3} + \\frac{\\rho u_{1}}{3} + \\frac{\\rho}{9}\\\\\\frac{\\rho u_{0}^{2} u_{1}}{2} - \\frac{\\rho u_{0}^{2}}{6} + \\frac{\\rho u_{1}^{2}}{3} - \\frac{\\rho u_{1}}{3} + \\frac{\\rho}{9}\\\\\\frac{\\rho u_{0}^{2}}{3} + \\frac{\\rho u_{0} u_{1}^{2}}{2} - \\frac{\\rho u_{0}}{3} - \\frac{\\rho u_{1}^{2}}{6} + \\frac{\\rho}{9}\\\\\\frac{\\rho u_{0}^{2}}{3} - \\frac{\\rho u_{0} u_{1}^{2}}{2} + \\frac{\\rho u_{0}}{3} - \\frac{\\rho u_{1}^{2}}{6} + \\frac{\\rho}{9}\\\\\\frac{\\rho u_{0}^{2} u_{1}}{4} + \\frac{\\rho u_{0}^{2}}{12} - \\frac{\\rho u_{0} u_{1}^{2}}{4} - \\frac{\\rho u_{0} u_{1}}{4} - \\frac{\\rho u_{0}}{12} + \\frac{\\rho u_{1}^{2}}{12} + \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\\\\\frac{\\rho u_{0}^{2} u_{1}}{4} + \\frac{\\rho u_{0}^{2}}{12} + \\frac{\\rho u_{0} u_{1}^{2}}{4} + \\frac{\\rho u_{0} u_{1}}{4} + \\frac{\\rho u_{0}}{12} + \\frac{\\rho u_{1}^{2}}{12} + \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\\\- \\frac{\\rho u_{0}^{2} u_{1}}{4} + \\frac{\\rho u_{0}^{2}}{12} - \\frac{\\rho u_{0} u_{1}^{2}}{4} + \\frac{\\rho u_{0} u_{1}}{4} - \\frac{\\rho u_{0}}{12} + \\frac{\\rho u_{1}^{2}}{12} - \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\\\- \\frac{\\rho u_{0}^{2} u_{1}}{4} + \\frac{\\rho u_{0}^{2}}{12} + \\frac{\\rho u_{0} u_{1}^{2}}{4} - \\frac{\\rho u_{0} u_{1}}{4} + \\frac{\\rho u_{0}}{12} + \\frac{\\rho u_{1}^{2}}{12} - \\frac{\\rho u_{1}}{12} + \\frac{\\rho}{36}\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡                            2         2                           ⎤\n",
+       "⎢                      2⋅ρ⋅u₀    2⋅ρ⋅u₁    4⋅ρ                     ⎥\n",
+       "⎢                    - ─────── - ─────── + ───                     ⎥\n",
+       "⎢                         3         3       9                      ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢                    2          2       2                          ⎥\n",
+       "⎢                ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₁    ρ⋅u₁   ρ               ⎥\n",
+       "⎢              - ──────── - ───── + ───── + ──── + ─               ⎥\n",
+       "⎢                   2         6       3      3     9               ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢                   2          2       2                           ⎥\n",
+       "⎢               ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₁    ρ⋅u₁   ρ                ⎥\n",
+       "⎢               ──────── - ───── + ───── - ──── + ─                ⎥\n",
+       "⎢                  2         6       3      3     9                ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢                   2          2              2                    ⎥\n",
+       "⎢               ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀   ρ⋅u₁    ρ                ⎥\n",
+       "⎢               ───── + ──────── - ──── - ───── + ─                ⎥\n",
+       "⎢                 3        2        3       6     9                ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢                   2          2              2                    ⎥\n",
+       "⎢               ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀   ρ⋅u₁    ρ                ⎥\n",
+       "⎢               ───── - ──────── + ──── - ───── + ─                ⎥\n",
+       "⎢                 3        2        3       6     9                ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢     2          2          2                        2             ⎥\n",
+       "⎢ ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀⋅u₁   ρ⋅u₀   ρ⋅u₁    ρ⋅u₁   ρ  ⎥\n",
+       "⎢ ──────── + ───── - ──────── - ─────── - ──── + ───── + ──── + ── ⎥\n",
+       "⎢    4         12       4          4       12      12     12    36 ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢     2          2          2                        2             ⎥\n",
+       "⎢ ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀⋅u₁   ρ⋅u₀   ρ⋅u₁    ρ⋅u₁   ρ  ⎥\n",
+       "⎢ ──────── + ───── + ──────── + ─────── + ──── + ───── + ──── + ── ⎥\n",
+       "⎢    4         12       4          4       12      12     12    36 ⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢      2          2          2                        2            ⎥\n",
+       "⎢  ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀⋅u₁   ρ⋅u₀   ρ⋅u₁    ρ⋅u₁   ρ ⎥\n",
+       "⎢- ──────── + ───── - ──────── + ─────── - ──── + ───── - ──── + ──⎥\n",
+       "⎢     4         12       4          4       12      12     12    36⎥\n",
+       "⎢                                                                  ⎥\n",
+       "⎢      2          2          2                        2            ⎥\n",
+       "⎢  ρ⋅u₀ ⋅u₁   ρ⋅u₀    ρ⋅u₀⋅u₁    ρ⋅u₀⋅u₁   ρ⋅u₀   ρ⋅u₁    ρ⋅u₁   ρ ⎥\n",
+       "⎢- ──────── + ───── + ──────── - ─────── + ──── + ───── - ──── + ──⎥\n",
+       "⎣     4         12       4          4       12      12     12    36⎦"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "literatureVersion = sp.Matrix(discrete_maxwellian_equilibrium(stencil, c_s_sq=sp.Rational(1,3), order=3))\n",
+    "literatureVersion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3) Reduced Stencils\n",
+    "\n",
+    "This method for deriving a discrete equilibrium works well for \"full stencils\" i.e. with $3^d$ directions, where $d$ is the dimension."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Matched moments 13 - non matched moments 2 - total 15\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table border=\"1\" cellpadding=\"3\" cellspacing=\"0\"  style=\"border:black; border-collapse:collapse;\"><tr><td  style=\"background-color:#ddd;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">order</td><td  style=\"background-color:#ddd;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"background-color:#ddd;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"background-color:#ddd;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">0</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(0,&nbsp;0)&nbsp;&nbsp;x&nbsp;1</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">1</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(1,&nbsp;0)&nbsp;&nbsp;x&nbsp;2</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">2</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(1,&nbsp;1)&nbsp;&nbsp;x&nbsp;1</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(2,&nbsp;0)&nbsp;&nbsp;x&nbsp;2</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">3</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(2,&nbsp;1)&nbsp;&nbsp;x&nbsp;2</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(3,&nbsp;0)&nbsp;&nbsp;x&nbsp;2</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">4</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(2,&nbsp;2)&nbsp;&nbsp;x&nbsp;1</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(3,&nbsp;1)&nbsp;&nbsp;x&nbsp;2</td><td  style=\"background-color:Orange;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(4,&nbsp;0)&nbsp;&nbsp;x&nbsp;2</td></tr></table>"
+      ],
+      "text/plain": [
+       "<ipy_table.ipy_table.IpyTable at 0x7fd36422eb70>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "moment_equality_table(get_stencil(\"D2Q9\"), truncate_order=2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Matched moments 32 - non matched moments 3 - total 35\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<ipy_table.ipy_table.IpyTable at 0x7fd3642dd7b8>"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "moment_equality_table(get_stencil(\"D3Q27\"), truncate_order=2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Matched moments 26 - non matched moments 9 - total 35\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table border=\"1\" cellpadding=\"3\" cellspacing=\"0\"  style=\"border:black; border-collapse:collapse;\"><tr><td  style=\"background-color:#ddd;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">order</td><td  style=\"background-color:#ddd;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"background-color:#ddd;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"background-color:#ddd;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"background-color:#ddd;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">0</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(0,&nbsp;0,&nbsp;0)&nbsp;&nbsp;x&nbsp;1</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">1</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(1,&nbsp;0,&nbsp;0)&nbsp;&nbsp;x&nbsp;3</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">2</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(1,&nbsp;1,&nbsp;0)&nbsp;&nbsp;x&nbsp;3</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(2,&nbsp;0,&nbsp;0)&nbsp;&nbsp;x&nbsp;3</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">3</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(1,&nbsp;1,&nbsp;1)&nbsp;&nbsp;x&nbsp;1</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(2,&nbsp;1,&nbsp;0)&nbsp;&nbsp;x&nbsp;6</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(3,&nbsp;0,&nbsp;0)&nbsp;&nbsp;x&nbsp;3</td><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">&nbsp;</td></tr><tr><td  style=\"border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">4</td><td  style=\"background-color:Orange;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(2,&nbsp;1,&nbsp;1)&nbsp;&nbsp;x&nbsp;3</td><td  style=\"background-color:Orange;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(2,&nbsp;2,&nbsp;0)&nbsp;&nbsp;x&nbsp;3</td><td  style=\"background-color:lightGreen;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(3,&nbsp;1,&nbsp;0)&nbsp;&nbsp;x&nbsp;6</td><td  style=\"background-color:Orange;border-left: 1px solid;border-right: 1px solid;border-top: 1px solid;border-bottom: 1px solid;\">(4,&nbsp;0,&nbsp;0)&nbsp;&nbsp;x&nbsp;3</td></tr></table>"
+      ],
+      "text/plain": [
+       "<ipy_table.ipy_table.IpyTable at 0x7fd3a3ba82e8>"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "moment_equality_table(get_stencil(\"D3Q19\"), truncate_order=2)"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/doc/notebooks/demo_stencils.ipynb b/doc/notebooks/demo_stencils.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..b61461bfc565e48f22ea9e833a1075c024629e11
--- /dev/null
+++ b/doc/notebooks/demo_stencils.ipynb
@@ -0,0 +1,189 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "nbsphinx": "hidden"
+   },
+   "outputs": [],
+   "source": [
+    "from lbmpy.stencils import *\n",
+    "from pystencils.stencils import *\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo: Stencils\n",
+    "\n",
+    "A stencils is a tuple of directions, where each direction is again a tuple with as many entries as there are dimensions. Technically a stencil is only a nested tuple.\n",
+    "The *stencils* submodule already has a predefined set of commonly used stencils.\n",
+    "A common notation for stencils in the lattice Boltzmann literature is the *DxQy* notation, where *x* is the dimension of the space, and *y* the number of directions. For example *D2Q9* is a two-dimensional stencil with 9 directions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((0, 0), (0, 1), (0, -1), (-1, 0), (1, 0), (-1, 1), (1, 1), (-1, -1), (1, -1))"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stencil = get_stencil(\"D2Q9\")\n",
+    "stencil"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "visualize_stencil_2d(stencil)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the literature there is no agreement or convention of the direction ordering. \n",
+    "Thus the ``getStencil`` function takes an optional parameter defining the ordering."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "stencil = get_stencil(\"D2Q9\", ordering='counterclockwise')\n",
+    "visualize_stencil_2d(stencil)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Compare this to the visualization above and note that only the direction order has changed.\n",
+    "The LBM method is independent of the stencil ordering, as long as one order is consistently used everywhere."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The visualization routines take an optional ``data`` parameter, which has to be a sequence of information to attach to each direction. This info is then shown as labels instead of the direction index.\n",
+    "\n",
+    "There are two ways to visualize 3D stencils - either as a 3D plot, or as three 2D plots:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "nbsphinx": "hidden"
+   },
+   "outputs": [],
+   "source": [
+    "plt.rcParams['figure.figsize'] = (11.0, 9.0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 792x648 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "visualize_stencil_3d(get_stencil(\"D3Q19\"), data=list(range(19)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 792x648 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "visualize_stencil_3d_by_slicing(get_stencil(\"D3Q19\"), sliceAxis=2)"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/doc/notebooks/demo_theoretical_background_generic_equilibrium_construction.ipynb b/doc/notebooks/demo_theoretical_background_generic_equilibrium_construction.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..cd92dff4129b8755ba50cdbe881eff349347f7c7
--- /dev/null
+++ b/doc/notebooks/demo_theoretical_background_generic_equilibrium_construction.ipynb
@@ -0,0 +1,616 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import sympy as sp\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from pystencils.sympyextensions import prod\n",
+    "from pystencils.stencils import visualize_stencil\n",
+    "from lbmpy.stencils import get_stencil\n",
+    "from lbmpy.moments import get_default_moment_set_for_stencil, moments_up_to_order\n",
+    "from lbmpy.creationfunctions import create_lb_method, create_generic_mrt\n",
+    "from lbmpy.quadratic_equilibrium_construction import *\n",
+    "from lbmpy.chapman_enskog import ChapmanEnskogAnalysis\n",
+    "from lbmpy.moments import exponent_to_polynomial_representation\n",
+    "\n",
+    "%matplotlib inline\n",
+    "sp.init_printing()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo: Theoretical Background - LB Equilibrium Construction using quadratic Ansatz\n",
+    "\n",
+    "According to book by Wolf-Gladrow _\"Lattice-Gas Cellular Automata and Lattice Boltzmann Methods\"_ (2005)\n",
+    "\n",
+    "Through the Chapman Enskog analysis the following necessary conditions can be found in order for a lattice Boltzmann Method to approximate the Navier Stokes mass and momentum conservation equations. In the Chapman Enskog analysis only the moments of the equilibrium distribution functions are used, thus all conditions are formulated with regard to the moments $\\Pi$ of the equilibrium distribution function $f^{(eq)}$\n",
+    "\n",
+    "The conditions are:\n",
+    "- zeroth moment is the density: $\\Pi_0 = \\sum_q f^{(eq)}_q = \\rho$\n",
+    "- first moment is the momentum density, or for incompressible models the velocity:\n",
+    "    - compressible: $\\Pi_\\alpha = \\sum_q c_{q\\alpha} f^{(eq)}_q = \\rho u_\\alpha$\n",
+    "    - incompressible: $\\Pi_\\alpha = \\sum_q c_{q\\alpha} f^{(eq)}_q = u_\\alpha$\n",
+    "- second moment is related to the pressure tensor and has to be: \n",
+    "   $\\Pi_{\\alpha\\beta} = \\sum_q c_{q\\alpha} c_{q\\beta} f^{(eq)}_q =  \\rho u_\\alpha u_\\beta + p \\delta_{\\alpha\\beta}$\n",
+    "- third order moments are also used in the Chapman Enskog expansion. The conditions on these moments are harder to formulate and are investigated later. A commonly used, but overly restrictive choice is \n",
+    "  $\\Pi_{\\alpha\\beta\\gamma} = p ( \\delta_{\\alpha\\beta} u_\\gamma + \\delta_{\\alpha\\gamma} u_\\beta + \\delta_{\\beta\\gamma} u_\\alpha )$. In Wolf-Gladrows book these conditions on the third order moment are not used but implicitly fulfilled by choosing fixed fractions of the coefficients $\\frac{A_1}{A_2}$ etc.\n",
+    "\n",
+    "Now the following generic quadratic ansatz is used for the equilibrium distribution. \n",
+    "\n",
+    "$$f^{(eq)}_q = A_{|q|} + B_{|q|} (\\mathbf{c}_q \\cdot \\mathbf{u}^2 ) + D_{|q|} \\mathbf{u}^2$$\n",
+    "\n",
+    "\n",
+    "The free parameters $A_{|q|}, B_{|q|}, C_{|q|}$ and $D_{|q|}$ are chosen such that above conditions are fulfilled.\n",
+    "The subscript $|q|$ is an integer and defined as the sum of the absolute values of the corresponding stencil direction. For example: for center $|q|=0$, for direct neighbors like north, east, top $|q|=1$ for 2D diagonals like north-west its 2 and for 3D diagnoals like bottom-north-west its 3.\n",
+    "\n",
+    "_lbmpy_ can create this quadratic ansatz for use for a given stencil:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Create Stencil\n",
+    "stencil_name = \"D2Q9\"\n",
+    "stencil = get_stencil(stencil_name)\n",
+    "\n",
+    "# Create quadratic equilibrium ansatz\n",
+    "ansatz = generic_equilibrium_ansatz(stencil)\n",
+    "\n",
+    "# Show equilibrium for each stencil direction\n",
+    "plt.figure(figsize=(16, 10))\n",
+    "visualize_stencil(stencil, data=ansatz, textsize=9, slice=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next we define the restrictions obtained through the Chapman Enskog analysis, in the book listed as equations (5.4.2) and following:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left \\{ \\left ( 0, \\quad 0\\right ) : \\rho, \\quad \\left ( 0, \\quad 1\\right ) : \\rho u_{1}, \\quad \\left ( 0, \\quad 2\\right ) : p + \\rho u_{1}^{2}, \\quad \\left ( 1, \\quad 0\\right ) : \\rho u_{0}, \\quad \\left ( 1, \\quad 1\\right ) : \\rho u_{0} u_{1}, \\quad \\left ( 2, \\quad 0\\right ) : p + \\rho u_{0}^{2}\\right \\}$$"
+      ],
+      "text/plain": [
+       "⎧                                         2                                   \n",
+       "⎨(0, 0): ρ, (0, 1): ρ⋅u₁, (0, 2): p + ρ⋅u₁ , (1, 0): ρ⋅u₀, (1, 1): ρ⋅u₀⋅u₁, (2\n",
+       "⎩                                                                             \n",
+       "\n",
+       "              2⎫\n",
+       ", 0): p + ρ⋅u₀ ⎬\n",
+       "               ⎭"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "moment_restrictions = hydrodynamic_moment_values(dim=len(stencil[0]), compressible=True, up_to_order=2)\n",
+    "moment_restrictions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The parameter `up_to_order` can be modified to 3. Then the third order restrictions are included as well (see discussion above). Using these moment restrictions, the necessary conditions on the parameter $A$ to $D$ can be found."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}2 C_{1} + 4 C_{2} + 2 D_{1} + 4 D_{2} - \\rho\\\\8 C_{2} - \\rho\\\\2 C_{1} + 4 C_{2} + D_{0} + 4 D_{1} + 4 D_{2}\\\\4 C_{2} + 2 D_{1} + 4 D_{2}\\\\2 A_{1} + 4 A_{2} - p\\\\A_{0} + 4 A_{1} + 4 A_{2} - \\rho\\\\2 B_{1} + 4 B_{2} - \\rho\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡2⋅C₁ + 4⋅C₂ + 2⋅D₁ + 4⋅D₂ - ρ ⎤\n",
+       "⎢                              ⎥\n",
+       "⎢           8⋅C₂ - ρ           ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢2⋅C₁ + 4⋅C₂ + D₀ + 4⋅D₁ + 4⋅D₂⎥\n",
+       "⎢                              ⎥\n",
+       "⎢      4⋅C₂ + 2⋅D₁ + 4⋅D₂      ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢       2⋅A₁ + 4⋅A₂ - p        ⎥\n",
+       "⎢                              ⎥\n",
+       "⎢     A₀ + 4⋅A₁ + 4⋅A₂ - ρ     ⎥\n",
+       "⎢                              ⎥\n",
+       "⎣       2⋅B₁ + 4⋅B₂ - ρ        ⎦"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "equations = moment_constraint_equations(stencil, ansatz, moment_restrictions)\n",
+    "\n",
+    "sp.Matrix(equations)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Since we have still more unknowns than equations, some additional restrictions have to be imposed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ A_{0}, \\quad A_{1}, \\quad A_{2}, \\quad B_{0}, \\quad B_{1}, \\quad B_{2}, \\quad C_{0}, \\quad C_{1}, \\quad C_{2}, \\quad D_{0}, \\quad D_{1}, \\quad D_{2}, \\quad p\\right ]$$"
+      ],
+      "text/plain": [
+       "[A₀, A₁, A₂, B₀, B₁, B₂, C₀, C₁, C₂, D₀, D₁, D₂, p]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dofs = generic_equilibrium_ansatz_parameters(stencil)\n",
+    "dofs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In Wolf-Gladrows book the following arbitrary restrictions are added to the necessary constraints:\n",
+    "\n",
+    "$$ \\frac{A_0}{A_1} =  \\frac{A_1}{A_2}  =  \\frac{B_1}{B_2} =  \\frac{D_0}{D_1} =: r$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ \\frac{A_{0}}{A_{1}} - r, \\quad \\frac{A_{1}}{A_{2}} - r, \\quad \\frac{B_{1}}{B_{2}} - r, \\quad \\frac{D_{0}}{D_{1}} - r, \\quad \\frac{D_{1}}{D_{2}} - r\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡A₀      A₁      B₁      D₀      D₁    ⎤\n",
+       "⎢── - r, ── - r, ── - r, ── - r, ── - r⎥\n",
+       "⎣A₁      A₂      B₂      D₁      D₂    ⎦"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "additional_restrictions = [\n",
+    "    \"A_0 / A_1 - r\",\n",
+    "    \"A_1 / A_2 - r\",\n",
+    "    \"B_1 / B_2 - r\",\n",
+    "    \"D_0 / D_1 - r\",\n",
+    "    \"D_1 / D_2 - r\", # comment out this line to get solution dependent on r\n",
+    "]\n",
+    "additional_restrictions = [sp.sympify(e) for e in additional_restrictions]\n",
+    "additional_restrictions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ \\left \\{ A_{0} : \\frac{4 \\rho}{9}, \\quad A_{1} : \\frac{\\rho}{9}, \\quad A_{2} : \\frac{\\rho}{36}, \\quad B_{1} : \\frac{\\rho}{3}, \\quad B_{2} : \\frac{\\rho}{12}, \\quad C_{1} : \\frac{\\rho}{2}, \\quad C_{2} : \\frac{\\rho}{8}, \\quad D_{0} : - \\frac{2 \\rho}{3}, \\quad D_{1} : - \\frac{\\rho}{6}, \\quad D_{2} : - \\frac{\\rho}{24}, \\quad p : \\frac{\\rho}{3}, \\quad r : 4\\right \\}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡⎧    4⋅ρ      ρ      ρ       ρ      ρ       ρ      ρ      -2⋅ρ       -ρ      \n",
+       "⎢⎨A₀: ───, A₁: ─, A₂: ──, B₁: ─, B₂: ──, C₁: ─, C₂: ─, D₀: ─────, D₁: ───, D₂:\n",
+       "⎣⎩     9       9      36      3      12      2      8        3         6      \n",
+       "\n",
+       " -ρ      ρ      ⎫⎤\n",
+       " ───, p: ─, r: 4⎬⎥\n",
+       "  24     3      ⎭⎦"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "solveResult = sp.solve(equations + additional_restrictions, dofs + [sp.Symbol(\"r\")], dict=True)\n",
+    "solveResult"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The equilibrium we found here is the same as obtained with the usual _lbmpy_ construction technique:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "constructed_equilibrium = sp.Matrix(ansatz).subs(solveResult[0]).expand()\n",
+    "normal_lbmpy_equilibrium = create_lb_method(stencil=stencil_name, compressible=True).get_equilibrium_terms()\n",
+    "assert constructed_equilibrium == normal_lbmpy_equilibrium"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Generalization of above technique\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generic_polynomial(u, coeff_prefix, order=2):\n",
+    "    dim = len(u)\n",
+    "    result = 0\n",
+    "    for idx in moments_up_to_order(order, dim=dim):\n",
+    "        u_prod = prod(u[i] ** exp for i, exp in enumerate(idx))\n",
+    "        coeff = sp.Symbol((\"%s_\" + (\"%d\" * dim)) % ((coeff_prefix,) + idx))\n",
+    "        result += coeff * u_prod\n",
+    "    return result\n",
+    "\n",
+    "\n",
+    "def generic_polynomial_coeffs(dim, coeff_prefix, order=2):\n",
+    "    result = []\n",
+    "    for idx in moments_up_to_order(order, dim=dim):\n",
+    "        result.append(sp.Symbol((\"%s_\" + (\"%d\" * dim)) % ((coeff_prefix,) + idx)))\n",
+    "    return result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ 1, \\quad x, \\quad y, \\quad x^{2}, \\quad y^{2}, \\quad x y, \\quad x^{2} y, \\quad x y^{2}, \\quad x^{2} y^{2}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡          2   2        2       2   2  2⎤\n",
+       "⎣1, x, y, x , y , x⋅y, x ⋅y, x⋅y , x ⋅y ⎦"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "allMoments = get_default_moment_set_for_stencil(stencil)\n",
+    "allMoments"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We use, as before, all constraints for moments up order 2. This time we do not use a quadratic ansatz for the equilibrium distribution or the additional constraints (i.e. the ratios of coefficients being some constant $r$).\n",
+    "Instead an arbitrary second order polynomial $u$ is used for the third order moments. The forth order moment does not appear at all in the Chapman Enskog expansion and is thus set to a constant.\n",
+    "\n",
+    "So we end up with the following moments"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAACHsAAAAnBAMAAABnZsuFAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAZrsyIt1EEO+Zq1TNdomYxc4EAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAT1ElEQVR4Ae1cfWxkV3U/Y8947B1/VQoikRBxQ9UCRcJ/9B8qpJ1QIjWVyhqJUBIUsFQiwj/siDZiiaDebEtC00SZbhXRpCQZRGmo1O1abaoEUGSrECLColiiqrJUyQ6lSF2JDaHZZEW+tufj3nfPO+/eN2N7HHucedK8uffcc3/nnN8977yP8TMAQOVtuBttIwZGDIwY6JeByj84zeo1y/3OGR69ifu+NjzOjjzdAQZGGbADpCrIMx3pHFlQwv3SPAs37pdQRnFsiYFRBmyJtr4nVe8Q1QdafU8ZGsXKEhxaHhpvR44OnoFRBgye0zzi2ir3j+Wl+6I3OQ+HJbp9Ec4oiE0zMMqATVO2yQlzbZ5w+yan7T31s++wF1CHW3Cmufcc3aMezR7/8q54NjC7EaC9mAERN1833ovHyHZNT3YYYejLx2zzwLrh4m6Ax4xo1E0y8D/wT8mxnRwYmN0I0F7MgIibO0mvxo4cI3p4K+39Uj5qzfHzJv5rYfx5Ixp1kwx8CA42k4M7ODAwuxGgvZgBETd3kN0cdOQYyY1vobNvysdy9cV8+PX/g5vm86JRL83Ah3fpOfPA7BaB9mQGFN1Mr8mAR2qFY2TbBnLlo5o+3CrNnqZKZsMlPWcrha0BNS4oCGw2zj/9N3mJ9ErQ+whSIQ4MSGFeqdqmuSkKzdy+umv24VFfs7avFLG7NWotUCoDSkjeXAZsLXbr5tZQtjTLHiMEUsJG75TLlY/3AXzuJz8tOMayvy+IrSAxm9UONK12SR+B6ve/ddFqVO+5YhHSQLWN/ISp9Xzf9xA9tvUZpJqaAGKN3mwpoNCsLoS2ahUj/8wX1XCumR4JavW3L4VO1ro+a3Fj60B5HNXryy7pI7VXH3+bminNHmtkAoBEBiDJTGgBngRbXLgoVkJo3Uyo7YTYHiNoI8FGMeWgcvJl8unMsdXgWq58fBfgB3BTM4xKi2Wft9JCPzEbGrdhOVgvqKcFCDS9Wv+QVbgZZl8sATpr9CdNOfHDiA6PtHwv++4zyEwfIAHE4L3ZUkChOd3Eqyaky2yRyJ8wKqGbHgk6053Q9q3Ztm+5760CGRjd7csuTvgu1Dvwi2U9ldrla1QIIJEBSDITatG3s3AFrLSg4GZadeAj9hhBAwk2IikHB15D/fGTy8otXT4qbagchdl1NUxNkc0mjsZMOTEbbr6X7irOZXo9GwgElwL83Co+CPClNBDN4u1R931o0TXyX6hX/8eTrbyw7yDVtASQgPdkSwGp5mXg6FIybEYi5xOB1mpsuF5hRGl5buZWldA10TZv2wZyOPrLY5bZVfpI7YEWTB5VImr2SEQfAPgoExmAekJoHr6/hfPY+bmm58M1YukW3IxqeWEplFdS36X62TGiJiTYiKQcXEm/z1ZOqsngysdLJKs1YawDhfsjkdWP6mmRdmI2wAyVjyORGQkRAsE7AQq3iF8EOLmYBPo0/LHg+QW+IQ5P6HCmUD76DFJhJoAEvCdbCkg16YqL6VIybBYjnzAPevCixZWP4ojC8tzgH0TYbaI7sciy7QJZYOp7zDK7ah5SO7kEB+zvZuVrlAWQlY9EBiDJQqiyyE3Kil4L5xm0c3N9H25O6DpFN2NamawMKlNSjVL97BhRExJsFFMO4JJ34bw3H1OTffn4FcmuApjrwIQ9fTnZ9/S0SDsx2x0P08uRKXERAgGWs8OrZvjJFpWPBND4D779W6LfY4EJPVI++gxSuZQAcuC92FJAoVldwnakfBQjnyXN3Obzpjii1Dw3P1My13zvt/8Fjx7ctgvk8HJfHrPMrpqA1E5fKJaP8jXKAsjKh0JUTSJZCFVCbvJJpcfCeQbt3Fzfh5sTuk6/bjr1MqgYfJl+OEbCzBQbxZQDaP8tPir5xKthMi7TAvUaXDJOA6y0YSI3joNOJvdN15E6QORVxsRsdzzMtmlarYM73D7148X66Q34fUlYkWV7BKpjOTu8kUmyxsdbkACavHjxOVHrscCIHisfqSC/cB9Ub8vs60YCyIEX2ApA6chniKRI+UBpFjnwCkyfOL2qnQlHfW4kGBVlz80TT/9dmC1Kd128KCKfgDkg63MJEKFYdY9ZZjc4BEwt1OwVVm6Nah2eQIloAuhRPphkJlRZ5CaXD71wV599qmWUfOC5oVS41fvvU7mTcjOnlYKCnMGwrv3pi1Y4RkJQaTZCytU6ot8+g9lZyV0TzvIa1RZI4dcBDnVhnB6Q6M3J3kKy+h0yEnmVMTHbHQ+VdZp4hPdYAiaOTjWOAroT2RCoij4c7BbGJlDcE8gvcGG2CBA9Vj5SQbYfgRlXlwxgAsiBF9gKQOnIx+bRRrR8hMhlBVYer5/P++OP0NxIMCrKjpv6K62VZjbdKEWBrM89gKy6wyy1m/nDiYi9w10loqZeI59KlIgmgB7lg0kGItRuXD7Uwk38BTxpdVzg+aFEuHBjc1rlTsrNnFYKKm8wQPWnb7VCVGk2Qsq5o7Y6v7YIDx9QEWE9uB2hqv/OeB/FFWpHyofI/i3YhNirjInZ7nhoLKnpb4Lqi1dOrcMV+CB3XcmliUBVvPqIlI9aB8+yCaAMxi1w1jcNRI+Wj3iQn5j/CowtwMy5roEBSAA5cMuWAkpHXltFK9HyUevkI19rwWvwzDPAH3bNH/XZCDJbFe/hvayBO8cNPt6a61JM9AKGV/I6OSBaHjLjfKYmbxqI4dGEAyJcG6LDZLtkk3SsXYdMX0ytXGYpqU/OBLVBszwDmGSodYK+b3H5UOhH5uG4hJ/F7RkMQ8RQItz6LTAluRPj2UOJFpGomMsM+tUQg2QsrKvSpwHe8vr0kotaPqejv9Js1Dr5lINK89BqfXVygbPGv7pz1YP4OyalLcCt2Y0Kd/3OXTMe9H38jr3KmJjtjofx59T0W/ABS2tyA+6E8Xt1NRAVBErcvNyDCgkgh/7zU6c+curUE8qWbSJ6rHwkgnwYfURH3wrfsjjEVgzIySxbCigd+eQyQkbLh438K1B/rdJtdOiDc2ZPnXrsjlOnqOlHiNm6eP+er6Mcf8rKuMHKvdKlmOgFDKfEKhaIQNiE+OysGSCCp48DItxciME5tks2SSdnV6z7PVM71fZd/12+Rk4rOOenmW8mGYhQu3H5UAv3QAuu5/Bd3IrBbIgTOBXuBcA/tIjyrKCmWIsIDMwVl5UNkjG1rkGfvcilAevTSy5q+Wy81E+zYVMOpmBuYwYObXDWZK/uPNWEz/wGI+OqzXXccxBlyskUr3A48jJrYnakfOCPAzPnEYNeScldTIhRSp6X8JcXqWnKkRlKKF0+NND4utP0556LtD2npkuTU/NMy8pTQaKJg4vwYZgrzEgARcoHs6WAkpEny0ch8u9jAa4twwX6SCj+tONHmFkxCtkZ1XEz3cYH0xQTv4DhlPwligYiEDHBPgdrGojhyUQ6RIfJdskm8ynqdAq1260kOG2lPjkLiWiByjNASKZUshtnhUI/BvXnOfwQt79kyIYkgc2KunDxRL0iuRPj2UOJFpHIrBii/WqwQTZGR0xPpkEcxBfB1PKFS9UQeZKNQsph+ZhsPwSXLwJFwxEhTONa3F2+TIB4zYgX6hX7xMrJbiAVt90deZk1MduVjwkM2m9TSzC9BHfzQwUiw2x06Yq3NZe3jBy+CdUmJIBc/cUpPnnsbNfnC+Ni+UgFib6eoSyaXLV4CSBXPgpsKaBk5Mmbl0Lkv4SpC5iaf0UfccznmR/hVGOjUCgfc/PwwGcpJn4BQ5TcJQomxIYAEhCBiAn2OVhzJBNQKysf6RAdJqujzU8yn2KXTqF2I2obbXi/kZeuEZ+7ZUJ5BjDJTKiBl9/jwsLVX4PGcxx+iNtlVxiS8mFW1IW70oU1yZ0Yzz5RWYvWSLLMEO2gxGBWPnoyLfr0kotaPn8RpeNOslFIOfzr9unH5+EklblDyxwRAj21iDtMFNzwYWDlaPFPfZ3sLaTittirjInZrnzIE0+ZXmvTGf2dWKveLOx7WPmmZ5KX0lW42cbbMNOEnkDlyUNBxu45UkGOdeCKyp+ch9q88SYF5MALbCmgZOSpR6fFyF+EI/MHm/BB+ohj/qj3I8wsG5Xjm7UcN3PL9VvwBWWKaa0FRkkDEYiYYJ+DNQUk1YmuPtIhOkyyi3prwqfYjV3Y0Rq9B+A/2OewK12jVgByzoWJuRaRLITmxNjhk0pYuPrLMLb+EMUc4vblIxuSBDYr6sJdWYV3NX4vxXNWPkirieVDVsQQ7aDEFzZGJ9yeTDt9/CMu8Z1R1UVUFnqKjWLK4XtrU3cCXtbghlkjf5c18Uvq1l+l/Vn8fBSOLNZfoV7YSAZwPwnkub+8yriyHlSwlZotN/NTXVI+sk77lYU65vxxuLHdJUKsOQKqrdb/HIyBq549+3WsdF2CiALRQOHqI4ZOiWLliSCnFib+cnacbk/tBHIzBiRZWGArAIXIbYT8ozQ9+yiJXFbgq/AOOIi35vQhP8JFgx/hVGOjxauPA/NjbY4JaLZR8uWDgAhETPBqBWuPilECCuUjGqJ2TtTherHN6nzKjVBb/diz9y5ZuVojyQBJxAAkXjnnpFMgk0jmVDIku/KhFu6H8KZON8+yP+azIaZZragOd3qjcp3kToxnD8VaRKKwYoj2q8EG2RiVj55Mg+hj2qrl4wsRE3WKjeLBBksw8zyMv0oRYtZI3o2hM7j9inY34OfPnv4awDUt6mYby+A73L+O9vIqY+2PMg1qpGZPfeOVr+LflyySTq2DO1j7w9PYu/ncv55YZEKMOQKqn/vxIhgDT168+EI5EIH7VeE27SLo9971xLyVJ4Ks//N//e6P8LyAz0/7BGLwIlsKKERuIqQbM6bLyHXk8oPE507P02XBnfSRSH2e+RFmlo0Wy0f9vr+mcx3GRNljlDQQgYgJ9jlYe1SMElAoH9EQWdFhivpsW2x7dbwIKlI7jQ+ulqxcr1Gtg8iSiAqIrTnnuI07QyaRzIQaORQW7uZnfufEMsUc4vbZlQ0xzSqX2agP98RP/+A/kzx7qDppcfngFTFE+9Vgg2yMyoePGFcwJJM2DaKP53Tx3aN+sF82dMrVOgT9jRc2GhuNt7/wID6ixayhDz55XaA93E67WpP2uDWa/JXb8V9EOgk+QaftId77Xels+ovWbNO3JUSGMZcBGQMyvwyINUzyJNGNVZ4bCZLkeIqcWx4cEJuSvMtTiA+l3GbkLNWRkwBPJnRn6/7Nic8zPyL4PJEfTnBLcSMxXSYKtKfbD9o0EIEEE6qpgEL54OmCy83gQg7zMscn68gp16xFlgFGzjMSa+Supkgl5xz2DZmlJGt0NpdnOYfNzFACuy1r6nCTPOegiETFXOBcQ+Ha0NHiDSr9IMzr40suAcpdR26GDZtyLlDKGskc984Llw80Jtus+9Zf+iUwLHq0dXnvd6Wzc6/MufMlTyQyjLkMyBgQQ+e8Pfy2QDz0p16h+ux/r2I7hW7kPCsSJMv5vtpMyNw08t5ArCEr3pW232dHs5HzuI6cBHQrG25n601W4h1LszQLlQEyblCNYgovYAQlDUROBhOqqYG48Pji434/EF8yFzQm2QzPKdzJOfhOra1QK0CMkzn3gWd/mwRdlma7UpJ1BvCMPMs5Bi3N0XCTPOegmP7ASuBcM2fKByO7qOKmAV9yCVDuQqSbEcGNUjZsyslUWkGXOZMdFnH5APn9FuALopbbf171Di1Spy5FJJOXza6vZ2pQ1X/22jhaNOeBrAGCSANhHcpvV0ODHuzYYDy6ldPkYpACeZp+HrATtgwkmBS5jXCsKWNWTlIdOWvNtBsd+nAnt2Mp4bvtEd/Q3xRTeAEjlA+tAwiiTKim1iL4YIK5kmHlQtAnm0FHTqEDoFafi52xahvW5jdHci4DGIZiTsTNYhWjaoZw8QfoPnhmAgMrCYO0HPwR+KCvhMoy0EsuCoovRGxqjTVlhpWTtJByokor6DInVz7eJ8OAnBc2f7DQwA08WjE6ZbPHmkFZ//RavfuljYI5D2QNEMRYE3du00B0njTbmVXAZyVJ9P6CFMzZ+788QCDG5MhthNUFsWflJB1r4i63nT3bAvoUN5Qyvoxc/fETRRWgmO7yL7rgeLh+CMoMokyoZlAieGWCueJR5ULQZptBR06hdi18Blg5wRQTUcDDudsbm3kZ5pbwWsb33XcZyTl00aeYo3HjrwU5muPh9sUz/nckJFGxEjdIFpSVoK+EOlh+ySVA8YXIZtgYa2q0rE1Z4zInVz6qseWSWZU4UgaJjZLZr8M/KyyW/huX7ZN79rbEzT6CVAEPDEhhXqnapnmJ6Q+6G64fBo1ciqdOoUFvK9QWgSZutT9hiYUSkjeXAcHhTbR2iWf0UF2IKH9L2OidcrnyoUCHrRmtv3zzMmyR7JK/6vrhdfUgnEK3aTYKRDcve2vbLZ6JhXAhMihO9kv5iPJxUzcqHgnfKAzUP/ZGiXSX4tzP5eMD17Z2idWR2T3BQPVn+MhqtO0gA/u5fMDsrTvI3Ah6CBj43+UhcHKIXXTl47EhDqHE9S+NLj9K2HkDDE3e9gYIchdDXOmy8cuXd9GHHTL9foB3r+4Q9gh2CBioNmHs5SHwc4hd/EWTnT+wD2m+2BqVjyHOzO27PndhVD62z2IZwqwvG5c+XqY2lGPH8P/hNofS85HTA2FgcgFq5weCNAKJMjB+zaKXP+wb++b716Dx6r4JZhTI5hmozMPaxuanjWb0y8B4Vj36nTFEehP3HF8eIndHrg6cgU/d85sDxxwBWgb+H4nJQxEXCg9lAAAAAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\left \\{ \\left ( 0, \\quad 0\\right ) : \\rho, \\quad \\left ( 0, \\quad 1\\right ) : \\rho u_{1}, \\quad \\left ( 0, \\quad 2\\right ) : \\rho u_{1}^{2} + \\frac{\\rho}{3}, \\quad \\left ( 1, \\quad 0\\right ) : \\rho u_{0}, \\quad \\left ( 1, \\quad 1\\right ) : \\rho u_{0} u_{1}, \\quad \\left ( 1, \\quad 2\\right ) : b_{00} + b_{01} u_{1} + b_{02} u_{1}^{2} + b_{10} u_{0} + b_{11} u_{0} u_{1} + b_{20} u_{0}^{2}, \\quad \\left ( 2, \\quad 0\\right ) : \\rho u_{0}^{2} + \\frac{\\rho}{3}, \\quad \\left ( 2, \\quad 1\\right ) : a_{00} + a_{01} u_{1} + a_{02} u_{1}^{2} + a_{10} u_{0} + a_{11} u_{0} u_{1} + a_{20} u_{0}^{2}, \\quad \\left ( 2, \\quad 2\\right ) : M_{22}\\right \\}$$"
+      ],
+      "text/plain": [
+       "⎧                                     2   ρ                                   \n",
+       "⎨(0, 0): ρ, (0, 1): ρ⋅u₁, (0, 2): ρ⋅u₁  + ─, (1, 0): ρ⋅u₀, (1, 1): ρ⋅u₀⋅u₁, (1\n",
+       "⎩                                         3                                   \n",
+       "\n",
+       "                           2                              2              2   ρ\n",
+       ", 2): b₀₀ + b₀₁⋅u₁ + b₀₂⋅u₁  + b₁₀⋅u₀ + b₁₁⋅u₀⋅u₁ + b₂₀⋅u₀ , (2, 0): ρ⋅u₀  + ─\n",
+       "                                                                             3\n",
+       "\n",
+       "                               2                              2             ⎫\n",
+       ", (2, 1): a₀₀ + a₀₁⋅u₁ + a₀₂⋅u₁  + a₁₀⋅u₀ + a₁₁⋅u₀⋅u₁ + a₂₀⋅u₀ , (2, 2): M₂₂⎬\n",
+       "                                                                            ⎭"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dim = len(stencil[0])\n",
+    "u = sp.symbols(\"u_:3\")[:len(stencil[0])]\n",
+    "moment_restrictions = hydrodynamic_moment_values(dim=len(stencil[0]), compressible=True, up_to_order=2)\n",
+    "moment_restrictions[(2, 1)] = generic_polynomial(u, \"a\")\n",
+    "moment_restrictions[(1, 2)] = generic_polynomial(u, \"b\")\n",
+    "moment_restrictions[(2, 2)] = sp.Symbol(\"M_22\")\n",
+    "moment_restrictions = {m: v.subs(sp.Symbol(\"p\"), sp.Symbol(\"rho\") / 3) for m, v in moment_restrictions.items()}\n",
+    "moment_restrictions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next all parameters are collected.."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ a_{00}, \\quad a_{01}, \\quad a_{10}, \\quad a_{02}, \\quad a_{11}, \\quad a_{20}, \\quad b_{00}, \\quad b_{01}, \\quad b_{10}, \\quad b_{02}, \\quad b_{11}, \\quad b_{20}, \\quad p\\right ]$$"
+      ],
+      "text/plain": [
+       "[a₀₀, a₀₁, a₁₀, a₀₂, a₁₁, a₂₀, b₀₀, b₀₁, b₁₀, b₀₂, b₁₁, b₂₀, p]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "parameters = generic_polynomial_coeffs(dim, \"a\") + generic_polynomial_coeffs(dim, \"b\") + [sp.Symbol(\"p\")]\n",
+    "parameters"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "... and a _lbmpy_ LB method is created. On this method an automatic Chapman Enskog analysis can be conducted to find \n",
+    "constraints for the free parameters above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ \\left ( 1, \\quad \\rho, \\quad \\omega\\right ), \\quad \\left ( y, \\quad \\rho u_{1}, \\quad \\omega\\right ), \\quad \\left ( x, \\quad \\rho u_{0}, \\quad \\omega\\right ), \\quad \\left ( y^{2}, \\quad \\rho u_{1}^{2} + \\frac{\\rho}{3}, \\quad \\omega\\right ), \\quad \\left ( x y, \\quad \\rho u_{0} u_{1}, \\quad \\omega\\right ), \\quad \\left ( x^{2}, \\quad \\rho u_{0}^{2} + \\frac{\\rho}{3}, \\quad \\omega\\right ), \\quad \\left ( x^{2} y, \\quad a_{00} + a_{01} u_{1} + a_{02} u_{1}^{2} + a_{10} u_{0} + a_{11} u_{0} u_{1} + a_{20} u_{0}^{2}, \\quad \\omega\\right ), \\quad \\left ( x y^{2}, \\quad b_{00} + b_{01} u_{1} + b_{02} u_{1}^{2} + b_{10} u_{0} + b_{11} u_{0} u_{1} + b_{20} u_{0}^{2}, \\quad \\omega\\right ), \\quad \\left ( x^{2} y^{2}, \\quad M_{22}, \\quad \\omega\\right )\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡                                       ⎛ 2      2   ρ   ⎞                    \n",
+       "⎢(1, ρ, ω), (y, ρ⋅u₁, ω), (x, ρ⋅u₀, ω), ⎜y , ρ⋅u₁  + ─, ω⎟, (x⋅y, ρ⋅u₀⋅u₁, ω),\n",
+       "⎣                                       ⎝            3   ⎠                    \n",
+       "\n",
+       " ⎛ 2      2   ρ   ⎞  ⎛ 2                         2                            \n",
+       " ⎜x , ρ⋅u₀  + ─, ω⎟, ⎝x ⋅y, a₀₀ + a₀₁⋅u₁ + a₀₂⋅u₁  + a₁₀⋅u₀ + a₁₁⋅u₀⋅u₁ + a₂₀⋅\n",
+       " ⎝            3   ⎠                                                           \n",
+       "\n",
+       "  2   ⎞  ⎛   2                       2                              2   ⎞  ⎛ 2\n",
+       "u₀ , ω⎠, ⎝x⋅y , b₀₀ + b₀₁⋅u₁ + b₀₂⋅u₁  + b₁₀⋅u₀ + b₁₁⋅u₀⋅u₁ + b₂₀⋅u₀ , ω⎠, ⎝x \n",
+       "                                                                              \n",
+       "\n",
+       "  2        ⎞⎤\n",
+       "⋅y , M₂₂, ω⎠⎥\n",
+       "            ⎦"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rr = sp.symbols(\"omega\")\n",
+    "collision_table = [( exponent_to_polynomial_representation(m), v, rr) for m, v in  moment_restrictions.items()]\n",
+    "collision_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "method = create_generic_mrt(stencil, collision_table, compressible=True)\n",
+    "analysis = ChapmanEnskogAnalysis(method, constants=set(parameters))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left\\{0, - \\frac{b_{10}}{2} + \\frac{b_{10}}{\\omega}, \\frac{a_{01}}{2} - \\frac{a_{01}}{\\omega} - \\frac{b_{10}}{2} + \\frac{b_{10}}{\\omega}, \\frac{a_{01}}{2} - \\frac{a_{01}}{\\omega} - \\frac{a_{10}}{2} + \\frac{a_{10}}{\\omega} - \\frac{\\rho}{6} + \\frac{\\rho}{3 \\omega}, \\frac{a_{01}}{2} - \\frac{a_{01}}{\\omega} - \\frac{b_{01}}{2} + \\frac{b_{01}}{\\omega} - \\frac{\\rho}{6} + \\frac{\\rho}{3 \\omega}, \\frac{a_{01}}{2} - \\frac{a_{01}}{\\omega} + b_{10} - \\frac{2 b_{10}}{\\omega} - \\frac{\\rho}{2} + \\frac{\\rho}{\\omega}\\right\\}$$"
+      ],
+      "text/plain": [
+       "⎧     b₁₀   b₁₀  a₀₁   a₀₁   b₁₀   b₁₀  a₀₁   a₀₁   a₁₀   a₁₀   ρ    ρ   a₀₁  \n",
+       "⎨0, - ─── + ───, ─── - ─── - ─── + ───, ─── - ─── - ─── + ─── - ─ + ───, ─── -\n",
+       "⎩      2     ω    2     ω     2     ω    2     ω     2     ω    6   3⋅ω   2   \n",
+       "\n",
+       " a₀₁   b₀₁   b₀₁   ρ    ρ   a₀₁   a₀₁         2⋅b₁₀   ρ   ρ⎫\n",
+       " ─── - ─── + ─── - ─ + ───, ─── - ─── + b₁₀ - ───── - ─ + ─⎬\n",
+       "  ω     2     ω    6   3⋅ω   2     ω            ω     2   ω⎭"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "analysis.does_approximate_navier_stokes()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These constraints can be solved for the free parameters:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAAgAAAAUBAMAAABCNWFYAAAAG1BMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB4Gco9AAAACHRSTlMAdt3NMolEZgN4ymIAAAAJcEhZcwAADsQAAA7EAZUrDhsAAAAXSURBVAgdYxAyKVZjCGMAIpoQQipCagCy4Q1mVUJFwQAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$$\\left [ \\right ]$$"
+      ],
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "solveRes = sp.solve(analysis.does_approximate_navier_stokes(), parameters)\n",
+    "solveRes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/latex": [
+       "$$\\left \\{ \\left ( 0, \\quad 0\\right ) : \\rho, \\quad \\left ( 0, \\quad 1\\right ) : \\rho u_{1}, \\quad \\left ( 0, \\quad 2\\right ) : \\rho u_{1}^{2} + \\frac{\\rho}{3}, \\quad \\left ( 1, \\quad 0\\right ) : \\rho u_{0}, \\quad \\left ( 1, \\quad 1\\right ) : \\rho u_{0} u_{1}, \\quad \\left ( 1, \\quad 2\\right ) : b_{00} + b_{01} u_{1} + b_{02} u_{1}^{2} + b_{10} u_{0} + b_{11} u_{0} u_{1} + b_{20} u_{0}^{2}, \\quad \\left ( 2, \\quad 0\\right ) : \\rho u_{0}^{2} + \\frac{\\rho}{3}, \\quad \\left ( 2, \\quad 1\\right ) : a_{00} + a_{01} u_{1} + a_{02} u_{1}^{2} + a_{10} u_{0} + a_{11} u_{0} u_{1} + a_{20} u_{0}^{2}, \\quad \\left ( 2, \\quad 2\\right ) : M_{22}\\right \\}$$"
+      ],
+      "text/plain": [
+       "⎧                                     2   ρ                                   \n",
+       "⎨(0, 0): ρ, (0, 1): ρ⋅u₁, (0, 2): ρ⋅u₁  + ─, (1, 0): ρ⋅u₀, (1, 1): ρ⋅u₀⋅u₁, (1\n",
+       "⎩                                         3                                   \n",
+       "\n",
+       "                           2                              2              2   ρ\n",
+       ", 2): b₀₀ + b₀₁⋅u₁ + b₀₂⋅u₁  + b₁₀⋅u₀ + b₁₁⋅u₀⋅u₁ + b₂₀⋅u₀ , (2, 0): ρ⋅u₀  + ─\n",
+       "                                                                             3\n",
+       "\n",
+       "                               2                              2             ⎫\n",
+       ", (2, 1): a₀₀ + a₀₁⋅u₁ + a₀₂⋅u₁  + a₁₀⋅u₀ + a₁₁⋅u₀⋅u₁ + a₂₀⋅u₀ , (2, 2): M₂₂⎬\n",
+       "                                                                            ⎭"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_moment_restrictions = {a : b.subs(solveRes) for a, b in moment_restrictions.items()}\n",
+    "new_moment_restrictions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "All methods constructed with these constraints should theoretically approximate Navier Stokes. "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/demo_thermalized_lbm.ipynb b/doc/notebooks/demo_thermalized_lbm.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..5466eb597b327d529b8dd6e853dad52312f2492a
--- /dev/null
+++ b/doc/notebooks/demo_thermalized_lbm.ipynb
@@ -0,0 +1,377 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pystencils as ps\n",
+    "from lbmpy.session import *\n",
+    "from lbmpy.moments import is_shear_moment, get_order"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo: Thermalized (Randomized) LBM\n",
+    "\n",
+    "This demo notebook shows how to modify the LB collision operator to account for microscopic fluctuations. This technique is also called thermalized or randomized LBM. In these methods a random fluctuation is added to the equilibrium moments. In this simple example we implement a thermalized model by writing our own simple linear congruent random number generator, the draws indepedent random numbers on each cell. A seed is stored for each cell since all cells are processed in parallel."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1) Creating the method definition\n",
+    "\n",
+    "We begin with a standard SRT method..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{0}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f85c7558eb8>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "random_number_symbols = sp.symbols(\"rand_:3\")\n",
+    "method = create_lb_method(method='srt', relaxation_rate=1.8)\n",
+    "method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "...and modify its collision table. The `create_lb_method_from_existing` function provides a convenient way to do this. \n",
+    "We pass a custom function that receives a row of the collision table and returns a modified version of it.\n",
+    "Our modification rule adds symbols that stand for random numbers to some of the moments."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{0}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$0.001 rand_{0} + u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$0.001 rand_{1} + \\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$0.001 rand_{1} + \\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$0.001 rand_{1} + \\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$1.8$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f8600a022b0>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def modification_func(moment, equilibrium, relaxation_rate):\n",
+    "    if is_shear_moment(moment):\n",
+    "        equilibrium += random_number_symbols[0] * 0.001\n",
+    "    elif get_order(moment) > 2:\n",
+    "        equilibrium += random_number_symbols[1] * 0.001\n",
+    "    return moment, equilibrium, relaxation_rate\n",
+    "\n",
+    "\n",
+    "thermalized_method = create_lb_method_from_existing(method, modification_func)\n",
+    "thermalized_method.override_weights(method.weights)\n",
+    "thermalized_method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2) Creating the kernel equations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next we have to define rules how to compute the quantities $rand_0$ and $rand_1$. \n",
+    "We do this using a linear congruent RNG on each cell. We pass in a seed array, and in each time step this seed array is updated with the new random numbers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\left [ {{seed}_{C}^{0}} \\leftarrow 1664525 {{seed}_{C}^{0}} + 1013904223, \\quad {{seed}_{C}^{1}} \\leftarrow 1664525 {{seed}_{C}^{1}} + 1013904223, \\quad {{seed}_{C}^{2}} \\leftarrow 1664525 {{seed}_{C}^{2}} + 1013904223, \\quad rand_{0} \\leftarrow \\frac{{{seed}_{C}^{0}}}{4294967295}, \\quad rand_{1} \\leftarrow \\frac{{{seed}_{C}^{1}}}{4294967295}, \\quad rand_{2} \\leftarrow \\frac{{{seed}_{C}^{2}}}{4294967295}, \\quad {{dbg}_{C}} \\leftarrow \\frac{{{seed}_{C}^{0}}}{4294967295}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡                                                                             \n",
+       "⎢seed_C__0 := 1664525⋅seed_C__0 + 1013904223, seed_C__1 := 1664525⋅seed_C__1 +\n",
+       "⎣                                                                             \n",
+       "\n",
+       "                                                                   seed_C__0  \n",
+       " 1013904223, seed_C__2 := 1664525⋅seed_C__2 + 1013904223, rand₀ := ──────────,\n",
+       "                                                                   4294967295 \n",
+       "\n",
+       "          seed_C__1            seed_C__2            seed_C__0 ⎤\n",
+       " rand₁ := ──────────, rand₂ := ──────────, dbg_C := ──────────⎥\n",
+       "          4294967295           4294967295           4294967295⎦"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dh = ps.create_data_handling(domain_size=(80, 80))\n",
+    "\n",
+    "seed_type = np.uint32\n",
+    "max_seed_type = np.iinfo(seed_type).max\n",
+    "\n",
+    "# Initialize the seed array\n",
+    "seedField = dh.add_array('seed', dtype=seed_type, values_per_cell=len(random_number_symbols))\n",
+    "for b in dh.iterate():\n",
+    "    random_field = np.random.randint(0, high=max_seed_type, dtype=seed_type, size=b['seed'].shape)\n",
+    "    np.copyto(b['seed'], random_field)\n",
+    "    \n",
+    "debug_output = dh.add_array('dbg')\n",
+    "\n",
+    "linear_congruent_rng_eqs = [ps.Assignment(seedField(i), seedField(i) * 1664525 + 1013904223) \n",
+    "                            for i, _ in enumerate(random_number_symbols)]\n",
+    "floatEqs = [ps.Assignment(ps.TypedSymbol(s.name, np.float), seedField(i) / max_seed_type)\n",
+    "            for i, s in enumerate(random_number_symbols)]\n",
+    "                      \n",
+    "rng_eqs = linear_congruent_rng_eqs + floatEqs + [ps.Assignment(debug_output.center, seedField(0) / max_seed_type)]\n",
+    "rng_eqs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These assignments are then added to the LB collision rule."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "collision_rule = create_lb_collision_rule(lb_method=thermalized_method)\n",
+    "collision_rule.subexpressions += rng_eqs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, lets test our method by running a lid-driven-cavity with it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ldc = create_lid_driven_cavity(data_handling=dh, collision_rule=collision_rule, lid_velocity=0.05,\n",
+    "                               kernel_params={'rand_0': 0, 'rand_1': 0})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#show_code(ldc.ast)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ldc.run(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.vector_field(ldc.velocity[:, :]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert np.isfinite(dh.max('ldc_velocity'))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/sphinx/api.rst b/doc/sphinx/api.rst
new file mode 100644
index 0000000000000000000000000000000000000000..3c2052ed7c02490d7099ec5d796aa95ed1807033
--- /dev/null
+++ b/doc/sphinx/api.rst
@@ -0,0 +1,17 @@
+API Reference
+-------------
+
+.. toctree::
+   :maxdepth: 1
+
+   scenarios.rst
+   kernelcreation.rst
+   methodcreation.rst
+   stencils.rst
+   methods.rst
+   maxwellian_equilibrium.rst
+   continuous_distribution_measures.rst
+   moments.rst
+   cumulants.rst
+   forcemodels.rst
+   zbibliography.rst
diff --git a/doc/sphinx/continuous_distribution_measures.rst b/doc/sphinx/continuous_distribution_measures.rst
new file mode 100644
index 0000000000000000000000000000000000000000..bb2d8eda0d99305a5e3bd7d4381133d0cecc6904
--- /dev/null
+++ b/doc/sphinx/continuous_distribution_measures.rst
@@ -0,0 +1,8 @@
+******************************************************
+Continuous Distribution Measures (Moments & Cumulants)
+******************************************************
+
+This module provides functions to compute moments and cumulants from continuous probability distribution functions.
+
+.. automodule:: lbmpy.continuous_distribution_measures
+    :members:
diff --git a/doc/sphinx/cumulants.rst b/doc/sphinx/cumulants.rst
new file mode 100644
index 0000000000000000000000000000000000000000..4131a6ae06a7bf08835d8a63addba38b5d1ea818
--- /dev/null
+++ b/doc/sphinx/cumulants.rst
@@ -0,0 +1,6 @@
+*********
+Cumulants
+*********
+
+.. automodule:: lbmpy.cumulants
+   :members:
diff --git a/doc/sphinx/forcemodels.rst b/doc/sphinx/forcemodels.rst
new file mode 100644
index 0000000000000000000000000000000000000000..f9993f081e4981ef6cf4269b08a0962dbb674099
--- /dev/null
+++ b/doc/sphinx/forcemodels.rst
@@ -0,0 +1,6 @@
+************
+Force models
+************
+
+.. automodule:: lbmpy.forcemodels
+   :members:
diff --git a/doc/sphinx/kernelcreation.rst b/doc/sphinx/kernelcreation.rst
new file mode 100644
index 0000000000000000000000000000000000000000..8abd99a461ebc3f835ce922f1d124ea507edb9f5
--- /dev/null
+++ b/doc/sphinx/kernelcreation.rst
@@ -0,0 +1,3 @@
+
+.. automodule:: lbmpy.creationfunctions
+   :members:
diff --git a/doc/sphinx/lbmpy.bib b/doc/sphinx/lbmpy.bib
new file mode 100644
index 0000000000000000000000000000000000000000..9620dc345ce71d66b4fca4719f64ea83f654732b
--- /dev/null
+++ b/doc/sphinx/lbmpy.bib
@@ -0,0 +1,71 @@
+@article{karlin2015entropic,
+  title={Entropic multirelaxation lattice Boltzmann models for turbulent flows},
+  author={B{\"o}sch, Fabian and Chikatamarla, Shyam S and Karlin, Ilya V},
+  journal={Physical Review E},
+  volume={92},
+  number={4},
+  pages={043309},
+  year={2015},
+  publisher={APS}
+}
+
+@PHDTHESIS{luo1993lattice,
+   author = {{Luo}, L.-S.},
+    title = "{Lattice-Gas Automata and Lattice Boltzmann Equations for Two-Dimensional Hydrodynamics}",
+ keywords = {HYDRODYNAMICS},
+   school = {GEORGIA INSTITUTE OF TECHNOLOGY.},
+     year = 1993,
+   adsurl = {http://adsabs.harvard.edu/abs/1993PhDT.......233L},
+  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+
+@Article{guo2002discrete,
+  author    = {Guo, Zhaoli and Zheng, Chuguang and Shi, Baochang},
+  title     = {Discrete lattice effects on the forcing term in the lattice Boltzmann method},
+  journal   = {Physical Review E},
+  year      = {2002},
+  volume    = {65},
+  number    = {4},
+  pages     = {046308},
+  publisher = {APS},
+}
+
+@article{buick2000gravity,
+  title={Gravity in a lattice Boltzmann model},
+  author={Buick, JM and Greated, CA},
+  journal={Physical Review E},
+  volume={61},
+  number={5},
+  pages={5307},
+  year={2000},
+  publisher={APS}
+}
+
+
+@article{Wohrwag2018,
+archivePrefix = {arXiv},
+arxivId = {1710.07486},
+author = {W{\"{o}}hrwag, M. and Semprebon, C. and {Mazloomi Moqaddam}, A. and Karlin, I. and Kusumaatmaja, H.},
+doi = {10.1103/PhysRevLett.120.234501},
+eprint = {1710.07486},
+isbn = {9783642121425},
+issn = {10797114},
+journal = {Physical Review Letters},
+number = {23},
+pmid = {23347591},
+title = {{Ternary Free-Energy Entropic Lattice Boltzmann Model with a High Density Ratio}},
+volume = {120},
+year = {2018}
+}
+
+
+@article{Semprebon2016,
+author = {Semprebon, Ciro and Kusumaatmaja, Halim},
+doi = {10.1103/PhysRevE.93.033305},
+keywords = {lbm,multiphase,phasefield},
+mendeley-tags = {lbm,multiphase,phasefield},
+pages = {1--11},
+title = {{Ternary free-energy lattice Boltzmann model with tunable surface tensions and contact angles}},
+volume = {033305},
+year = {2016}
+}
\ No newline at end of file
diff --git a/doc/sphinx/maxwellian_equilibrium.rst b/doc/sphinx/maxwellian_equilibrium.rst
new file mode 100644
index 0000000000000000000000000000000000000000..b2656cb6eb62b11eafa6e60ce82a617904a15d2d
--- /dev/null
+++ b/doc/sphinx/maxwellian_equilibrium.rst
@@ -0,0 +1,17 @@
+**********************
+Maxwellian Equilibrium
+**********************
+
+.. automodule:: lbmpy.maxwellian_equilibrium
+    :members:
+
+    .. autofunction:: lbmpy.maxwellian_equilibrium.discrete_maxwellian_equilibrium
+
+    .. autofunction:: lbmpy.maxwellian_equilibrium.generate_equilibrium_by_matching_moments
+
+    .. autofunction:: lbmpy.maxwellian_equilibrium.continuous_maxwellian_equilibrium
+
+    .. autofunction:: lbmpy.maxwellian_equilibrium.get_moments_of_continuous_maxwellian_equilibrium
+
+    .. autofunction:: lbmpy.maxwellian_equilibrium.get_moments_of_discrete_maxwellian_equilibrium
+
diff --git a/doc/sphinx/methodcreation.rst b/doc/sphinx/methodcreation.rst
new file mode 100644
index 0000000000000000000000000000000000000000..54f7ebb9716994452d714819776c7eef0e66461d
--- /dev/null
+++ b/doc/sphinx/methodcreation.rst
@@ -0,0 +1,8 @@
+Creating LBM methods
+====================
+
+This module is a lower level API to construct methods.
+When possible use the high level API.
+
+.. automodule:: lbmpy.methods.creationfunctions
+    :members:
diff --git a/doc/sphinx/methods.rst b/doc/sphinx/methods.rst
new file mode 100644
index 0000000000000000000000000000000000000000..63227e3a9f15d0bee400105c2f7cdf2f75924419
--- /dev/null
+++ b/doc/sphinx/methods.rst
@@ -0,0 +1,51 @@
+***********************
+Methods (lbmpy.methods)
+***********************
+
+
+LBM Method Interfaces
+=====================
+
+.. autoclass:: lbmpy.methods.AbstractLbMethod
+    :members:
+
+.. autoclass:: lbmpy.methods.AbstractConservedQuantityComputation
+    :members:
+
+
+
+
+LBM with conserved zeroth and first order
+=========================================
+
+.. autoclass:: lbmpy.methods.DensityVelocityComputation
+    :members:
+
+
+
+
+Moment-based methods
+====================
+
+Creation Functions
+------------------
+
+.. autofunction:: lbmpy.methods.create_srt
+
+.. autofunction:: lbmpy.methods.create_trt
+
+.. autofunction:: lbmpy.methods.create_trt_with_magic_number
+
+.. autofunction:: lbmpy.methods.create_mrt_orthogonal
+
+.. autofunction:: lbmpy.methods.create_with_continuous_maxwellian_eq_moments
+
+.. autofunction:: lbmpy.methods.create_with_discrete_maxwellian_eq_moments
+
+
+Class
+-----
+
+.. autoclass:: lbmpy.methods.MomentBasedLbMethod
+    :members:
+
diff --git a/doc/sphinx/moments.rst b/doc/sphinx/moments.rst
new file mode 100644
index 0000000000000000000000000000000000000000..976a9d76e5492b5c256d8432e27683253815d861
--- /dev/null
+++ b/doc/sphinx/moments.rst
@@ -0,0 +1,6 @@
+*******
+Moments
+*******
+
+.. automodule:: lbmpy.moments
+   :members:
diff --git a/doc/sphinx/scenarios.rst b/doc/sphinx/scenarios.rst
new file mode 100644
index 0000000000000000000000000000000000000000..c04148c9ef90856e6bb091481eddfd2b1e876fef
--- /dev/null
+++ b/doc/sphinx/scenarios.rst
@@ -0,0 +1,3 @@
+
+.. automodule:: lbmpy.scenarios
+   :members:
\ No newline at end of file
diff --git a/doc/sphinx/stencils.rst b/doc/sphinx/stencils.rst
new file mode 100644
index 0000000000000000000000000000000000000000..3c0b247922d2d9eac3b53cb608ce2035d0770f3b
--- /dev/null
+++ b/doc/sphinx/stencils.rst
@@ -0,0 +1,7 @@
+********
+Stencils
+********
+
+.. automodule:: lbmpy.stencils
+    :members:
+
diff --git a/doc/sphinx/tutorials.rst b/doc/sphinx/tutorials.rst
new file mode 100644
index 0000000000000000000000000000000000000000..e66e1b5b182db3f3cdc88c50c8798c9b715c4720
--- /dev/null
+++ b/doc/sphinx/tutorials.rst
@@ -0,0 +1,22 @@
+Tutorials
+---------
+
+All tutorials are automatically created by Jupyter Notebooks.
+You can open the notebooks directly to play around with the code examples.
+
+.. toctree::
+    :maxdepth: 1
+
+    /notebooks/00_tutorial_lbmpy_walberla_overview.ipynb
+    /notebooks/01_tutorial_predefinedScenarios.ipynb
+    /notebooks/02_tutorial_boundary_setup.ipynb
+    /notebooks/03_tutorial_lbm_formulation.ipynb
+    /notebooks/04_tutorial_nondimensionalization_and_scaling.ipynb
+    /notebooks/05_tutorial_modifying_method_smagorinsky.ipynb
+    /notebooks/06_tutorial_thermal_lbm.ipynb
+    /notebooks/demo_stencils.ipynb
+    /notebooks/demo_create_method_from_scratch.ipynb
+    /notebooks/demo_moments_cumulants_and_maxwellian_equilibrium.ipynb
+    /notebooks/demo_automatic_chapman_enskog_analysis.ipynb
+    /notebooks/demo_thermalized_lbm.ipynb
+    /notebooks/demo_theoretical_background_generic_equilibrium_construction.ipynb
\ No newline at end of file
diff --git a/doc/sphinx/zbibliography.rst b/doc/sphinx/zbibliography.rst
new file mode 100644
index 0000000000000000000000000000000000000000..76fc5b3cdd64f84301ba8d4340b70d790403d454
--- /dev/null
+++ b/doc/sphinx/zbibliography.rst
@@ -0,0 +1,5 @@
+Bibliography
+------------
+
+.. bibliography:: lbmpy.bib
+   :cited:
\ No newline at end of file
diff --git a/__init__.py b/lbmpy/__init__.py
similarity index 100%
rename from __init__.py
rename to lbmpy/__init__.py
diff --git a/boundaries/__init__.py b/lbmpy/boundaries/__init__.py
similarity index 100%
rename from boundaries/__init__.py
rename to lbmpy/boundaries/__init__.py
diff --git a/boundaries/boundaryconditions.py b/lbmpy/boundaries/boundaryconditions.py
similarity index 100%
rename from boundaries/boundaryconditions.py
rename to lbmpy/boundaries/boundaryconditions.py
diff --git a/boundaries/boundaryhandling.py b/lbmpy/boundaries/boundaryhandling.py
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rename from boundaries/boundaryhandling.py
rename to lbmpy/boundaries/boundaryhandling.py
diff --git a/boundaries/createindexlistcython.pyx b/lbmpy/boundaries/createindexlistcython.pyx
similarity index 100%
rename from boundaries/createindexlistcython.pyx
rename to lbmpy/boundaries/createindexlistcython.pyx
diff --git a/chapman_enskog/__init__.py b/lbmpy/chapman_enskog/__init__.py
similarity index 100%
rename from chapman_enskog/__init__.py
rename to lbmpy/chapman_enskog/__init__.py
diff --git a/chapman_enskog/chapman_enskog.py b/lbmpy/chapman_enskog/chapman_enskog.py
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rename from chapman_enskog/chapman_enskog.py
rename to lbmpy/chapman_enskog/chapman_enskog.py
diff --git a/chapman_enskog/chapman_enskog_higher_order.py b/lbmpy/chapman_enskog/chapman_enskog_higher_order.py
similarity index 100%
rename from chapman_enskog/chapman_enskog_higher_order.py
rename to lbmpy/chapman_enskog/chapman_enskog_higher_order.py
diff --git a/chapman_enskog/chapman_enskog_steady_state.py b/lbmpy/chapman_enskog/chapman_enskog_steady_state.py
similarity index 100%
rename from chapman_enskog/chapman_enskog_steady_state.py
rename to lbmpy/chapman_enskog/chapman_enskog_steady_state.py
diff --git a/chapman_enskog/derivative.py b/lbmpy/chapman_enskog/derivative.py
similarity index 100%
rename from chapman_enskog/derivative.py
rename to lbmpy/chapman_enskog/derivative.py
diff --git a/continuous_distribution_measures.py b/lbmpy/continuous_distribution_measures.py
similarity index 100%
rename from continuous_distribution_measures.py
rename to lbmpy/continuous_distribution_measures.py
diff --git a/creationfunctions.py b/lbmpy/creationfunctions.py
similarity index 100%
rename from creationfunctions.py
rename to lbmpy/creationfunctions.py
diff --git a/cumulants.py b/lbmpy/cumulants.py
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rename from cumulants.py
rename to lbmpy/cumulants.py
diff --git a/fieldaccess.py b/lbmpy/fieldaccess.py
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rename from fieldaccess.py
rename to lbmpy/fieldaccess.py
diff --git a/forcemodels.py b/lbmpy/forcemodels.py
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rename from forcemodels.py
rename to lbmpy/forcemodels.py
diff --git a/geometry.py b/lbmpy/geometry.py
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rename from geometry.py
rename to lbmpy/geometry.py
diff --git a/innerloopsplit.py b/lbmpy/innerloopsplit.py
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rename from innerloopsplit.py
rename to lbmpy/innerloopsplit.py
diff --git a/lbstep.py b/lbmpy/lbstep.py
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rename from lbstep.py
rename to lbmpy/lbstep.py
diff --git a/macroscopic_value_kernels.py b/lbmpy/macroscopic_value_kernels.py
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rename from macroscopic_value_kernels.py
rename to lbmpy/macroscopic_value_kernels.py
diff --git a/max_domain_size_info.py b/lbmpy/max_domain_size_info.py
similarity index 100%
rename from max_domain_size_info.py
rename to lbmpy/max_domain_size_info.py
diff --git a/maxwellian_equilibrium.py b/lbmpy/maxwellian_equilibrium.py
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rename from maxwellian_equilibrium.py
rename to lbmpy/maxwellian_equilibrium.py
diff --git a/methods/__init__.py b/lbmpy/methods/__init__.py
similarity index 100%
rename from methods/__init__.py
rename to lbmpy/methods/__init__.py
diff --git a/methods/abstractlbmethod.py b/lbmpy/methods/abstractlbmethod.py
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rename from methods/abstractlbmethod.py
rename to lbmpy/methods/abstractlbmethod.py
diff --git a/methods/conservedquantitycomputation.py b/lbmpy/methods/conservedquantitycomputation.py
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rename from methods/conservedquantitycomputation.py
rename to lbmpy/methods/conservedquantitycomputation.py
diff --git a/methods/creationfunctions.py b/lbmpy/methods/creationfunctions.py
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rename from methods/creationfunctions.py
rename to lbmpy/methods/creationfunctions.py
diff --git a/methods/cumulantbased.py b/lbmpy/methods/cumulantbased.py
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rename from methods/cumulantbased.py
rename to lbmpy/methods/cumulantbased.py
diff --git a/methods/entropic.py b/lbmpy/methods/entropic.py
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rename from methods/entropic.py
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diff --git a/methods/entropic_eq_srt.py b/lbmpy/methods/entropic_eq_srt.py
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rename from methods/entropic_eq_srt.py
rename to lbmpy/methods/entropic_eq_srt.py
diff --git a/methods/momentbased.py b/lbmpy/methods/momentbased.py
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diff --git a/methods/momentbasedsimplifications.py b/lbmpy/methods/momentbasedsimplifications.py
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rename from methods/momentbasedsimplifications.py
rename to lbmpy/methods/momentbasedsimplifications.py
diff --git a/moments.py b/lbmpy/moments.py
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rename from moments.py
rename to lbmpy/moments.py
diff --git a/parameterization.py b/lbmpy/parameterization.py
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rename from parameterization.py
rename to lbmpy/parameterization.py
diff --git a/phasefield/__init__.py b/lbmpy/phasefield/__init__.py
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rename to lbmpy/phasefield/__init__.py
diff --git a/phasefield/analytical.py b/lbmpy/phasefield/analytical.py
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rename from phasefield/analytical.py
rename to lbmpy/phasefield/analytical.py
diff --git a/phasefield/cahn_hilliard_lbm.py b/lbmpy/phasefield/cahn_hilliard_lbm.py
similarity index 100%
rename from phasefield/cahn_hilliard_lbm.py
rename to lbmpy/phasefield/cahn_hilliard_lbm.py
diff --git a/phasefield/contact_angle_circle_fitting.py b/lbmpy/phasefield/contact_angle_circle_fitting.py
similarity index 100%
rename from phasefield/contact_angle_circle_fitting.py
rename to lbmpy/phasefield/contact_angle_circle_fitting.py
diff --git a/phasefield/eos.py b/lbmpy/phasefield/eos.py
similarity index 100%
rename from phasefield/eos.py
rename to lbmpy/phasefield/eos.py
diff --git a/phasefield/experiments1D.py b/lbmpy/phasefield/experiments1D.py
similarity index 100%
rename from phasefield/experiments1D.py
rename to lbmpy/phasefield/experiments1D.py
diff --git a/phasefield/experiments2D.py b/lbmpy/phasefield/experiments2D.py
similarity index 100%
rename from phasefield/experiments2D.py
rename to lbmpy/phasefield/experiments2D.py
diff --git a/phasefield/high_density_ratio_model.py b/lbmpy/phasefield/high_density_ratio_model.py
similarity index 100%
rename from phasefield/high_density_ratio_model.py
rename to lbmpy/phasefield/high_density_ratio_model.py
diff --git a/phasefield/kerneleqs.py b/lbmpy/phasefield/kerneleqs.py
similarity index 100%
rename from phasefield/kerneleqs.py
rename to lbmpy/phasefield/kerneleqs.py
diff --git a/phasefield/n_phase_boyer.py b/lbmpy/phasefield/n_phase_boyer.py
similarity index 100%
rename from phasefield/n_phase_boyer.py
rename to lbmpy/phasefield/n_phase_boyer.py
diff --git a/phasefield/nphase_nestler.py b/lbmpy/phasefield/nphase_nestler.py
similarity index 100%
rename from phasefield/nphase_nestler.py
rename to lbmpy/phasefield/nphase_nestler.py
diff --git a/phasefield/phasefieldstep.py b/lbmpy/phasefield/phasefieldstep.py
similarity index 100%
rename from phasefield/phasefieldstep.py
rename to lbmpy/phasefield/phasefieldstep.py
diff --git a/phasefield/phasefieldstep_direct.py b/lbmpy/phasefield/phasefieldstep_direct.py
similarity index 100%
rename from phasefield/phasefieldstep_direct.py
rename to lbmpy/phasefield/phasefieldstep_direct.py
diff --git a/phasefield/post_processing.py b/lbmpy/phasefield/post_processing.py
similarity index 100%
rename from phasefield/post_processing.py
rename to lbmpy/phasefield/post_processing.py
diff --git a/phasefield/scenarios.py b/lbmpy/phasefield/scenarios.py
similarity index 100%
rename from phasefield/scenarios.py
rename to lbmpy/phasefield/scenarios.py
diff --git a/phasefield/simplex_projection.pyx b/lbmpy/phasefield/simplex_projection.pyx
similarity index 100%
rename from phasefield/simplex_projection.pyx
rename to lbmpy/phasefield/simplex_projection.pyx
diff --git a/plot2d.py b/lbmpy/plot2d.py
similarity index 100%
rename from plot2d.py
rename to lbmpy/plot2d.py
diff --git a/postprocessing.py b/lbmpy/postprocessing.py
similarity index 100%
rename from postprocessing.py
rename to lbmpy/postprocessing.py
diff --git a/quadratic_equilibrium_construction.py b/lbmpy/quadratic_equilibrium_construction.py
similarity index 100%
rename from quadratic_equilibrium_construction.py
rename to lbmpy/quadratic_equilibrium_construction.py
diff --git a/relaxationrates.py b/lbmpy/relaxationrates.py
similarity index 100%
rename from relaxationrates.py
rename to lbmpy/relaxationrates.py
diff --git a/scenarios.py b/lbmpy/scenarios.py
similarity index 100%
rename from scenarios.py
rename to lbmpy/scenarios.py
diff --git a/session.py b/lbmpy/session.py
similarity index 100%
rename from session.py
rename to lbmpy/session.py
diff --git a/simplificationfactory.py b/lbmpy/simplificationfactory.py
similarity index 100%
rename from simplificationfactory.py
rename to lbmpy/simplificationfactory.py
diff --git a/sparse/__init__.py b/lbmpy/sparse/__init__.py
similarity index 100%
rename from sparse/__init__.py
rename to lbmpy/sparse/__init__.py
diff --git a/sparse/mapping.py b/lbmpy/sparse/mapping.py
similarity index 100%
rename from sparse/mapping.py
rename to lbmpy/sparse/mapping.py
diff --git a/sparse/update_rule_sparse.py b/lbmpy/sparse/update_rule_sparse.py
similarity index 100%
rename from sparse/update_rule_sparse.py
rename to lbmpy/sparse/update_rule_sparse.py
diff --git a/stencils.py b/lbmpy/stencils.py
similarity index 100%
rename from stencils.py
rename to lbmpy/stencils.py
diff --git a/turbulence_models.py b/lbmpy/turbulence_models.py
similarity index 100%
rename from turbulence_models.py
rename to lbmpy/turbulence_models.py
diff --git a/updatekernels.py b/lbmpy/updatekernels.py
similarity index 100%
rename from updatekernels.py
rename to lbmpy/updatekernels.py
diff --git a/lbmpy_tests/benchmark/benchmark_evaluation.ipynb b/lbmpy_tests/benchmark/benchmark_evaluation.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..bbe4178fa1e6e8696f41c963d40093a4de538283
--- /dev/null
+++ b/lbmpy_tests/benchmark/benchmark_evaluation.ipynb
@@ -0,0 +1,812 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div class=\"bk-root\">\n",
+       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
+       "        <span id=\"90aa376d-22ca-4c8d-8b4d-d162db330c7f\">Loading BokehJS ...</span>\n",
+       "    </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "\n",
+       "(function(root) {\n",
+       "  function now() {\n",
+       "    return new Date();\n",
+       "  }\n",
+       "\n",
+       "  var force = true;\n",
+       "\n",
+       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
+       "    root._bokeh_onload_callbacks = [];\n",
+       "    root._bokeh_is_loading = undefined;\n",
+       "  }\n",
+       "\n",
+       "  var JS_MIME_TYPE = 'application/javascript';\n",
+       "  var HTML_MIME_TYPE = 'text/html';\n",
+       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
+       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
+       "\n",
+       "  /**\n",
+       "   * Render data to the DOM node\n",
+       "   */\n",
+       "  function render(props, node) {\n",
+       "    var script = document.createElement(\"script\");\n",
+       "    node.appendChild(script);\n",
+       "  }\n",
+       "\n",
+       "  /**\n",
+       "   * Handle when an output is cleared or removed\n",
+       "   */\n",
+       "  function handleClearOutput(event, handle) {\n",
+       "    var cell = handle.cell;\n",
+       "\n",
+       "    var id = cell.output_area._bokeh_element_id;\n",
+       "    var server_id = cell.output_area._bokeh_server_id;\n",
+       "    // Clean up Bokeh references\n",
+       "    if (id !== undefined) {\n",
+       "      Bokeh.index[id].model.document.clear();\n",
+       "      delete Bokeh.index[id];\n",
+       "    }\n",
+       "\n",
+       "    if (server_id !== undefined) {\n",
+       "      // Clean up Bokeh references\n",
+       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
+       "      cell.notebook.kernel.execute(cmd, {\n",
+       "        iopub: {\n",
+       "          output: function(msg) {\n",
+       "            var element_id = msg.content.text.trim();\n",
+       "            Bokeh.index[element_id].model.document.clear();\n",
+       "            delete Bokeh.index[element_id];\n",
+       "          }\n",
+       "        }\n",
+       "      });\n",
+       "      // Destroy server and session\n",
+       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
+       "      cell.notebook.kernel.execute(cmd);\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  /**\n",
+       "   * Handle when a new output is added\n",
+       "   */\n",
+       "  function handleAddOutput(event, handle) {\n",
+       "    var output_area = handle.output_area;\n",
+       "    var output = handle.output;\n",
+       "\n",
+       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
+       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
+       "      return\n",
+       "    }\n",
+       "\n",
+       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
+       "\n",
+       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
+       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
+       "      // store reference to embed id on output_area\n",
+       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
+       "    }\n",
+       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
+       "      var bk_div = document.createElement(\"div\");\n",
+       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "      var script_attrs = bk_div.children[0].attributes;\n",
+       "      for (var i = 0; i < script_attrs.length; i++) {\n",
+       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
+       "      }\n",
+       "      // store reference to server id on output_area\n",
+       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  function register_renderer(events, OutputArea) {\n",
+       "\n",
+       "    function append_mime(data, metadata, element) {\n",
+       "      // create a DOM node to render to\n",
+       "      var toinsert = this.create_output_subarea(\n",
+       "        metadata,\n",
+       "        CLASS_NAME,\n",
+       "        EXEC_MIME_TYPE\n",
+       "      );\n",
+       "      this.keyboard_manager.register_events(toinsert);\n",
+       "      // Render to node\n",
+       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
+       "      render(props, toinsert[toinsert.length - 1]);\n",
+       "      element.append(toinsert);\n",
+       "      return toinsert\n",
+       "    }\n",
+       "\n",
+       "    /* Handle when an output is cleared or removed */\n",
+       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
+       "    events.on('delete.Cell', handleClearOutput);\n",
+       "\n",
+       "    /* Handle when a new output is added */\n",
+       "    events.on('output_added.OutputArea', handleAddOutput);\n",
+       "\n",
+       "    /**\n",
+       "     * Register the mime type and append_mime function with output_area\n",
+       "     */\n",
+       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
+       "      /* Is output safe? */\n",
+       "      safe: true,\n",
+       "      /* Index of renderer in `output_area.display_order` */\n",
+       "      index: 0\n",
+       "    });\n",
+       "  }\n",
+       "\n",
+       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
+       "  if (root.Jupyter !== undefined) {\n",
+       "    var events = require('base/js/events');\n",
+       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
+       "\n",
+       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
+       "      register_renderer(events, OutputArea);\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  \n",
+       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
+       "    root._bokeh_timeout = Date.now() + 5000;\n",
+       "    root._bokeh_failed_load = false;\n",
+       "  }\n",
+       "\n",
+       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
+       "     \"<div style='background-color: #fdd'>\\n\"+\n",
+       "     \"<p>\\n\"+\n",
+       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
+       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
+       "     \"</p>\\n\"+\n",
+       "     \"<ul>\\n\"+\n",
+       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
+       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
+       "     \"</ul>\\n\"+\n",
+       "     \"<code>\\n\"+\n",
+       "     \"from bokeh.resources import INLINE\\n\"+\n",
+       "     \"output_notebook(resources=INLINE)\\n\"+\n",
+       "     \"</code>\\n\"+\n",
+       "     \"</div>\"}};\n",
+       "\n",
+       "  function display_loaded() {\n",
+       "    var el = document.getElementById(\"90aa376d-22ca-4c8d-8b4d-d162db330c7f\");\n",
+       "    if (el != null) {\n",
+       "      el.textContent = \"BokehJS is loading...\";\n",
+       "    }\n",
+       "    if (root.Bokeh !== undefined) {\n",
+       "      if (el != null) {\n",
+       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
+       "      }\n",
+       "    } else if (Date.now() < root._bokeh_timeout) {\n",
+       "      setTimeout(display_loaded, 100)\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "\n",
+       "  function run_callbacks() {\n",
+       "    try {\n",
+       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
+       "    }\n",
+       "    finally {\n",
+       "      delete root._bokeh_onload_callbacks\n",
+       "    }\n",
+       "    console.info(\"Bokeh: all callbacks have finished\");\n",
+       "  }\n",
+       "\n",
+       "  function load_libs(js_urls, callback) {\n",
+       "    root._bokeh_onload_callbacks.push(callback);\n",
+       "    if (root._bokeh_is_loading > 0) {\n",
+       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
+       "      return null;\n",
+       "    }\n",
+       "    if (js_urls == null || js_urls.length === 0) {\n",
+       "      run_callbacks();\n",
+       "      return null;\n",
+       "    }\n",
+       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
+       "    root._bokeh_is_loading = js_urls.length;\n",
+       "    for (var i = 0; i < js_urls.length; i++) {\n",
+       "      var url = js_urls[i];\n",
+       "      var s = document.createElement('script');\n",
+       "      s.src = url;\n",
+       "      s.async = false;\n",
+       "      s.onreadystatechange = s.onload = function() {\n",
+       "        root._bokeh_is_loading--;\n",
+       "        if (root._bokeh_is_loading === 0) {\n",
+       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
+       "          run_callbacks()\n",
+       "        }\n",
+       "      };\n",
+       "      s.onerror = function() {\n",
+       "        console.warn(\"failed to load library \" + url);\n",
+       "      };\n",
+       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
+       "    }\n",
+       "  };var element = document.getElementById(\"90aa376d-22ca-4c8d-8b4d-d162db330c7f\");\n",
+       "  if (element == null) {\n",
+       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '90aa376d-22ca-4c8d-8b4d-d162db330c7f' but no matching script tag was found. \")\n",
+       "    return false;\n",
+       "  }\n",
+       "\n",
+       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.16.min.js\"];\n",
+       "\n",
+       "  var inline_js = [\n",
+       "    function(Bokeh) {\n",
+       "      Bokeh.set_log_level(\"info\");\n",
+       "    },\n",
+       "    \n",
+       "    function(Bokeh) {\n",
+       "      \n",
+       "    },\n",
+       "    function(Bokeh) {\n",
+       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n",
+       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n",
+       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n",
+       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n",
+       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n",
+       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n",
+       "    }\n",
+       "  ];\n",
+       "\n",
+       "  function run_inline_js() {\n",
+       "    \n",
+       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
+       "      for (var i = 0; i < inline_js.length; i++) {\n",
+       "        inline_js[i].call(root, root.Bokeh);\n",
+       "      }if (force === true) {\n",
+       "        display_loaded();\n",
+       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
+       "      setTimeout(run_inline_js, 100);\n",
+       "    } else if (!root._bokeh_failed_load) {\n",
+       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
+       "      root._bokeh_failed_load = true;\n",
+       "    } else if (force !== true) {\n",
+       "      var cell = $(document.getElementById(\"90aa376d-22ca-4c8d-8b4d-d162db330c7f\")).parents('.cell').data().cell;\n",
+       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
+       "    }\n",
+       "\n",
+       "  }\n",
+       "\n",
+       "  if (root._bokeh_is_loading === 0) {\n",
+       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
+       "    run_inline_js();\n",
+       "  } else {\n",
+       "    load_libs(js_urls, function() {\n",
+       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
+       "      run_inline_js();\n",
+       "    });\n",
+       "  }\n",
+       "}(window));"
+      ],
+      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"90aa376d-22ca-4c8d-8b4d-d162db330c7f\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };var element = document.getElementById(\"90aa376d-22ca-4c8d-8b4d-d162db330c7f\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '90aa376d-22ca-4c8d-8b4d-d162db330c7f' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.16.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"90aa376d-22ca-4c8d-8b4d-d162db330c7f\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from lbmpy_tests.benchmark.evaluation import *\n",
+    "import seaborn as sns\n",
+    "from bokeh.io import output_notebook, save, show\n",
+    "from bokeh.layouts import gridplot\n",
+    "from bokeh.resources import Resources\n",
+    "output_notebook()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = get_categorical({'study_name': 'vectorization_flags'})\n",
+    "df = df.query('openmp==4 and stencil==\"D3Q19\" and method==\"mrt_raw\"')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>compiler_flags</th>\n",
+       "      <th>method</th>\n",
+       "      <th>openmp</th>\n",
+       "      <th>split</th>\n",
+       "      <th>instruction_set</th>\n",
+       "      <th>stencil</th>\n",
+       "      <th>mlups_max</th>\n",
+       "      <th>mlups_median</th>\n",
+       "      <th>fixed</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-march=native -mavx512vl</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>no-split</td>\n",
+       "      <td>avx512</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>105.689198</td>\n",
+       "      <td>105.668004</td>\n",
+       "      <td>generic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-march=native -mavx512vl -mno-fma</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>no-split</td>\n",
+       "      <td>avx512</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>105.549041</td>\n",
+       "      <td>104.331998</td>\n",
+       "      <td>generic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-mavx2</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>no-split</td>\n",
+       "      <td>avx</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>9.313466</td>\n",
+       "      <td>9.303262</td>\n",
+       "      <td>generic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-mavx2 -mno-fma</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>no-split</td>\n",
+       "      <td>avx</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>9.260901</td>\n",
+       "      <td>9.218732</td>\n",
+       "      <td>generic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-march=native -mavx512vl</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>split</td>\n",
+       "      <td>avx512</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>103.796639</td>\n",
+       "      <td>103.735438</td>\n",
+       "      <td>generic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>-march=native -mavx512vl -mno-fma</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>split</td>\n",
+       "      <td>avx512</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>104.085830</td>\n",
+       "      <td>102.983059</td>\n",
+       "      <td>generic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>-mavx2</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>split</td>\n",
+       "      <td>avx</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>79.212026</td>\n",
+       "      <td>78.240678</td>\n",
+       "      <td>generic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>-mavx2 -mno-fma</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>split</td>\n",
+       "      <td>avx</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>77.784685</td>\n",
+       "      <td>77.739951</td>\n",
+       "      <td>generic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>-march=native -mavx512vl</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>no-split</td>\n",
+       "      <td>avx512</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>105.555956</td>\n",
+       "      <td>105.546385</td>\n",
+       "      <td>all fixed</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>-march=native -mavx512vl -mno-fma</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>no-split</td>\n",
+       "      <td>avx512</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>106.581461</td>\n",
+       "      <td>105.378463</td>\n",
+       "      <td>all fixed</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>-mavx2</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>no-split</td>\n",
+       "      <td>avx</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>8.774606</td>\n",
+       "      <td>8.748501</td>\n",
+       "      <td>all fixed</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>-mavx2 -mno-fma</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>no-split</td>\n",
+       "      <td>avx</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>8.714489</td>\n",
+       "      <td>8.682320</td>\n",
+       "      <td>all fixed</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>-march=native -mavx512vl</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>split</td>\n",
+       "      <td>avx512</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>105.372216</td>\n",
+       "      <td>105.337044</td>\n",
+       "      <td>all fixed</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>-march=native -mavx512vl -mno-fma</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>split</td>\n",
+       "      <td>avx512</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>105.397390</td>\n",
+       "      <td>105.273621</td>\n",
+       "      <td>all fixed</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>-mavx2</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>split</td>\n",
+       "      <td>avx</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>81.811473</td>\n",
+       "      <td>80.867429</td>\n",
+       "      <td>all fixed</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>-mavx2 -mno-fma</td>\n",
+       "      <td>mrt_raw</td>\n",
+       "      <td>4</td>\n",
+       "      <td>split</td>\n",
+       "      <td>avx</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>81.527082</td>\n",
+       "      <td>80.370593</td>\n",
+       "      <td>all fixed</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       compiler_flags   method  openmp     split  \\\n",
+       "0            -march=native -mavx512vl  mrt_raw       4  no-split   \n",
+       "1   -march=native -mavx512vl -mno-fma  mrt_raw       4  no-split   \n",
+       "2                              -mavx2  mrt_raw       4  no-split   \n",
+       "3                     -mavx2 -mno-fma  mrt_raw       4  no-split   \n",
+       "4            -march=native -mavx512vl  mrt_raw       4     split   \n",
+       "5   -march=native -mavx512vl -mno-fma  mrt_raw       4     split   \n",
+       "6                              -mavx2  mrt_raw       4     split   \n",
+       "7                     -mavx2 -mno-fma  mrt_raw       4     split   \n",
+       "8            -march=native -mavx512vl  mrt_raw       4  no-split   \n",
+       "9   -march=native -mavx512vl -mno-fma  mrt_raw       4  no-split   \n",
+       "10                             -mavx2  mrt_raw       4  no-split   \n",
+       "11                    -mavx2 -mno-fma  mrt_raw       4  no-split   \n",
+       "12           -march=native -mavx512vl  mrt_raw       4     split   \n",
+       "13  -march=native -mavx512vl -mno-fma  mrt_raw       4     split   \n",
+       "14                             -mavx2  mrt_raw       4     split   \n",
+       "15                    -mavx2 -mno-fma  mrt_raw       4     split   \n",
+       "\n",
+       "   instruction_set stencil   mlups_max  mlups_median      fixed  \n",
+       "0           avx512   D3Q19  105.689198    105.668004    generic  \n",
+       "1           avx512   D3Q19  105.549041    104.331998    generic  \n",
+       "2              avx   D3Q19    9.313466      9.303262    generic  \n",
+       "3              avx   D3Q19    9.260901      9.218732    generic  \n",
+       "4           avx512   D3Q19  103.796639    103.735438    generic  \n",
+       "5           avx512   D3Q19  104.085830    102.983059    generic  \n",
+       "6              avx   D3Q19   79.212026     78.240678    generic  \n",
+       "7              avx   D3Q19   77.784685     77.739951    generic  \n",
+       "8           avx512   D3Q19  105.555956    105.546385  all fixed  \n",
+       "9           avx512   D3Q19  106.581461    105.378463  all fixed  \n",
+       "10             avx   D3Q19    8.774606      8.748501  all fixed  \n",
+       "11             avx   D3Q19    8.714489      8.682320  all fixed  \n",
+       "12          avx512   D3Q19  105.372216    105.337044  all fixed  \n",
+       "13          avx512   D3Q19  105.397390    105.273621  all fixed  \n",
+       "14             avx   D3Q19   81.811473     80.867429  all fixed  \n",
+       "15             avx   D3Q19   81.527082     80.370593  all fixed  "
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "out = df.sort_values(['fixed', 'method', 'split'])\n",
+    "out = out.reset_index()\n",
+    "del out['pk']\n",
+    "out"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Evaluation of optimization study\n",
+    "\n",
+    "study compares different optimization options for two domain sizes of a 2D domain $1024^2$ and a 3D domain $128^3$ on a single socket of the benchmark machine using AVX and AVX512 parallelization."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "opt_study_3d = get_categorical({'study_name': 'optimization_options',\n",
+    "                                'domain_size':[128, 128, 128]}).query('stable==True')\n",
+    "opt_study_2d = get_categorical({'study_name': 'optimization_options',\n",
+    "                                'domain_size':[1024, 1024]})#.query('stable==True')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#opt_study_3d.query(\"method=='srt-cumulant'\")['stencil']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### All D3Q27 single core results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = opt_study_3d.query(\"openmp == 1 and stencil=='D3Q19'\")\n",
+    "#df = opt_study_2d.query(\"openmp == 1 and method=='mrt_raw'\")\n",
+    "\n",
+    "ps = (980, 150)\n",
+    "res_col = 'mlups_max'\n",
+    "p1, src = bokeh_scatter_plot(df, 'vec', res_col, color_column='split', plot_size=ps)\n",
+    "p2, src = bokeh_scatter_plot(df, 'fixed', res_col, color_column='cse', source=src, plot_size=ps)\n",
+    "p3, src = bokeh_scatter_plot(df, 'cse', res_col, color_column='field_layout', source=src, plot_size=ps)\n",
+    "p4, src = bokeh_scatter_plot(df, 'method', res_col, color_column='cse', source=src, plot_size=ps)\n",
+    "\n",
+    "p1.legend.label_text_font_size=\"6pt\"\n",
+    "p1.legend.padding=1\n",
+    "p1.legend.margin=1\n",
+    "pl = gridplot([[p1], [p2], [p3], [p4]])\n",
+    "\n",
+    "save(pl, filename=\"plot.html\", title=\"lbmpy Benchmark\", resources=Resources('inline'))\n",
+    "show(pl)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Speedup plots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from bokeh.models import Span\n",
+    "\n",
+    "df = opt_study_3d.query(\"openmp == 4 and stencil=='D3Q27'\")\n",
+    "speedup = speedup_table_categorical(df, 'fixed', ['generic', \"loops only\"])\n",
+    "\n",
+    "ps = (450, 300)\n",
+    "p1, src = bokeh_scatter_plot(speedup, 'vec', 'speedup', color_column='split', \n",
+    "                             plot_size=ps, log=True)\n",
+    "p2, src = bokeh_scatter_plot(speedup, 'method', 'speedup', color_column='cse', \n",
+    "                             plot_size=ps, source=src, log=True)\n",
+    "\n",
+    "# Vertical line at 1\n",
+    "p1.renderers.extend([Span(location=1, dimension='height', line_color='black', line_width=1)])\n",
+    "\n",
+    "pl = gridplot([[p1, p2]])\n",
+    "show(pl)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Best runs for each method"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "res_col = 'mlups_median'\n",
+    "df = opt_study_3d.query(\"openmp == 4 and stencil=='D3Q19'\")\n",
+    "#df = opt_study_2d.query(\"openmp == 1\")\n",
+    "\n",
+    "r = df.groupby(['method'])[[res_col]].max().reset_index()\n",
+    "r = r.sort_values(by=res_col, ascending=False)\n",
+    "sns.barplot(y = 'method', x=res_col, data=r)\n",
+    "r"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Seaborn - tests"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = opt_study_3d.query(\"openmp == 4 and stencil=='D3Q27'\")\n",
+    "speedup = speedup_table_categorical(df, 'fixed', ['generic', \"loops only\"])\n",
+    "\n",
+    "ax = sns.stripplot(y='speedup', x='cse', jitter=True, hue='split', data=speedup)\n",
+    "ax = sns.violinplot(y='speedup', x='cse', data=speedup, inner=None, color=\".8\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "data = opt_study_3d.query(\"stencil=='D3Q27'\")\n",
+    "fig = plt.gcf()\n",
+    "ax = sns.stripplot(y='mlups_max', x='openmp', jitter=True, hue='split', data=data)\n",
+    "ax = sns.violinplot(y='mlups_max', x='openmp', data=data, inner=None, color=\".8\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sns.stripplot(y='mlups_max', x='openmp', jitter=True, hue='cse', data=data)\n",
+    "sns.violinplot(y='mlups_max', x='openmp', data=data, inner=None, color=\".8\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sns.violinplot(data=speedup.query(\"speedup<1.5\")['speedup'], orient='h')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/benchmark/evaluation.py b/lbmpy_tests/benchmark/evaluation.py
new file mode 100644
index 0000000000000000000000000000000000000000..305e6508db078900acac90b6bbf8dff256d22efa
--- /dev/null
+++ b/lbmpy_tests/benchmark/evaluation.py
@@ -0,0 +1,282 @@
+"""Function to process benchmark results in pandas."""
+from pystencils.runhelper.db import remove_constant_columns, Database
+
+db = None
+
+def get_categorical(query):
+    global db
+    if db is None:
+        db = Database('mongo://lbmpy_bench')
+    res = basic_clean_up(db.to_pandas(query))
+    res = make_categorical(res)
+    return res
+
+
+def get(query, **kwargs):
+    global db
+    if db is None:
+        db = Database('mongo://lbmpy_bench')
+    return basic_clean_up(db.to_pandas(query, **kwargs))
+
+
+def remove_all_column_prefixes(df, inplace=False):
+    """Strips everything left of a dots in pandas data frame column names: 'abc.def.value' is renamed to 'value'
+
+    Similar to remove_prefix_in_column_name, that removes everything before the FIRST dot
+    """
+    if not inplace:
+        df = df.copy()
+
+    new_column_names = []
+    for column_name in df.columns:
+        if '.' in column_name:
+            new_column_names.append(column_name[-column_name[::-1].index('.'):])
+        else:
+            new_column_names.append(column_name)
+    df.columns = new_column_names
+    return df
+
+
+def basic_clean_up(df):
+    """Cleans up a data frame that was loaded from the benchmark database.
+
+    - fills default values for vectorization options
+    - replaces columns that have stored lists with tuples
+    - removes constant columns
+    """
+    if df is None or len(df) == 0:
+        return df
+    df = df.applymap(lambda e: tuple(e) if isinstance(e, list) else e)
+
+    fill_default = {
+        'optimization.vectorization.nontemporal': False,
+        'optimization.vectorization.instruction_set': 'auto',
+        'smagorinsky': False,
+        'entropic': False,
+        'cumulant': False,
+        'stable': True,
+    }
+    categorical_columns = []  # ['optimization.vectorization.instruction_set']
+
+    for col, default in fill_default.items():
+        if col in df:
+            df[col] = df[col].fillna(default)
+
+    for col in categorical_columns:
+        if col in df:
+            df[col] = df[col].astype('category')
+
+    df, constants = remove_constant_columns(df)
+    remove_all_column_prefixes(df, inplace=True)
+    return df
+
+
+def make_categorical(df):
+    """Summarizes boolean columns into categorical columns, such that plotting is simpler afterwards.
+
+    - fixed_loop_sizes and fixed_relaxation_rates are summarized into single column with four values
+    - same for 'cse_global' and 'cse_pdfs' columns
+    """
+    from pandas.api.types import CategoricalDtype
+
+    def bool_to_category(col):
+        df[col] = df.apply(lambda e: 'True' if e[col] else 'False', axis=1).astype('category')
+
+    if all(c in df for c in ['instruction_set', 'assume_aligned', 'nontemporal']):
+        def vec_column(row):
+            if row['instruction_set'] == 'auto':
+                return 'auto'
+            else:
+                result = str(row['instruction_set'])
+                if row['assume_aligned']:
+                    result += "-align"
+                if row['nontemporal']:
+                    result += "-nt"
+                return result
+
+        df['vec'] = df.apply(vec_column, axis=1)
+        del df['instruction_set']
+        del df['assume_aligned']
+        del df['nontemporal']
+        df['vec'] = df['vec'].astype('category')
+
+    if all(c in df for c in ['method']):
+        def method_category(row):
+            method = row['method']
+            if 'smagorinsky' in row and row['smagorinsky']:
+                method += '-smag'
+            if 'entropic' in row and row['entropic']:
+                method += '-entr'
+                if method.startswith('mrt3') and 'relaxation_rates' in row:
+                    num_free_relaxation_rates = sum(1 for e in row['relaxation_rates'] if e == 'rr_free')
+                    method += '-free{}'.format(num_free_relaxation_rates)
+            if 'cumulant' in row and row['cumulant']:
+                method += '-cumulant'
+            return method
+        df['method'] = df.apply(method_category, axis=1)
+        for col in ['smagorinsky', 'entropic', 'cumulant', 'relaxation_rates']:
+            if col in df:
+                del df[col]
+
+    if all(c in df for c in ['fixed_loop_sizes', 'fixed_relaxation_rates']):
+        def fixed_column(row):
+            mapping = {
+                (False, False): 'generic',
+                (True, False): 'loops only',
+                (False, True): "ω's only",
+                (True, True): "all fixed",
+            }
+            return mapping[(row['fixed_loop_sizes'], row['fixed_relaxation_rates'])]
+
+        cat_type = CategoricalDtype(categories=['generic', "ω's only", "loops only", "all fixed"], ordered=True)
+        df['fixed'] = df.apply(fixed_column, axis=1).astype(cat_type)
+        del df['fixed_loop_sizes']
+        del df['fixed_relaxation_rates']
+
+    if 'fixed_loop_sizes' in df:
+        bool_to_category('fixed_loop_sizes')
+    if 'fixed_relaxation_rates' in df:
+        bool_to_category('fixed_relaxation_rates')
+
+    if all(c in df for c in ['cse_global', 'cse_pdfs']):
+        def cse_column(row):
+            mapping = {
+                (False, False): 'none',
+                (True, False): 'global only',
+                (False, True): "pdfs only",
+                (True, True): "full cse",
+            }
+            return mapping[(row['cse_global'], row['cse_pdfs'])]
+
+        cat_type = CategoricalDtype(categories=["full cse", 'global only', 'none', "pdfs only", ], ordered=True)
+        df['cse'] = df.apply(cse_column, axis=1).astype(cat_type)
+        del df['cse_global']
+        del df['cse_pdfs']
+
+    if 'cse_global' in df:
+        bool_to_category('cse_global')
+
+    if 'cse_pdfs' in df:
+        bool_to_category('cse_pdfs')
+
+    if 'all_measurements' in df:
+        del df['all_measurements']
+
+    if 'split' in df:
+        df['split'] = df.apply(lambda e: 'split' if e['split'] else 'no-split', axis=1).astype('category')
+
+    if 'method' in df:
+        df['method'] = df['method'].astype('category')
+
+    return df
+
+
+def speedup_table(df, column_name):
+    import pandas as pd
+    """Computes the speed up that a boolean optimization (column) causes."""
+    result_columns = ['mlups_max', 'mlups_median', 'all_measurements']
+    param_columns = list(set(df.columns) - set(result_columns + [column_name]))
+    param_columns.insert(0, column_name)
+    df = df.set_index(param_columns)
+    result = pd.DataFrame(df.loc[True][['mlups_median']] / df.loc[False][['mlups_median']])
+    return result.rename(columns={'mlups_median': 'speedup'})
+
+
+def category_columns_to_string_columns(df):
+    category_columns = []
+    for c in df.columns:
+        if df[c].dtype.name == 'category':
+            category_columns.append(c)
+            df[c] = df[c].astype(str)
+    return category_columns
+
+def speedup_table_categorical(df, column_name, slow_values):
+    df = df.copy()
+    df['_tmp_'] = df.apply(lambda row: False if row[column_name] in slow_values else True, axis=1)
+    category_columns = category_columns_to_string_columns(df)
+    del df[column_name]
+    result = speedup_table(df, '_tmp_').reset_index()
+    for c in category_columns:
+        if c == column_name:
+            continue
+        result[c] = result[c].astype('category')
+    return result
+
+
+def flatten_index(df, keep=[], remove=[]):
+    """See reset_index - pass index names to keep or to remove"""
+    flatten_indices = []
+    if remove:
+        assert not keep
+        for i, cn in enumerate(df.index.names):
+            if cn in remove:
+                flatten_indices.append(i)
+    else:
+        for i, cn in enumerate(df.index.names):
+            if cn not in keep:
+                flatten_indices.append(i)
+    return df.reset_index(level=flatten_indices)
+
+
+def bokeh_scatter_plot(df, category_column, dof_column, color_column=None, enable_hover=True, plot_size=(400, 300),
+                       source=None, log=False):
+    """Interactive bokeh scatter plot.
+
+    Args:
+        df: pandas data frame with data
+        category_column: column name for data that is plotted on y axis (has to be categorical column)
+        dof_column: column name plotted on the x axis (numeric)
+        color_column: categorical column used to color the data points
+        enable_hover: switch for tooltips on hover
+        plot_size: (width, height) of plot
+        source: use this parameter to link multiple bokeh plots together, pass the source here that was returned
+                by the first plot, make sure to use the same data frame for all plots
+
+    Returns:
+        (plot, source to pass to next plot to link them together)
+    """
+    from bokeh.plotting import figure, ColumnDataSource
+    from bokeh.models import HoverTool, WheelZoomTool
+    from bokeh.transform import jitter, factor_cmap
+    from bokeh.palettes import d3
+
+    if source is None:
+        source = ColumnDataSource(df)
+
+    if df[category_column].dtype.name == 'category':
+        figure_kwargs = {'y_range': [str(e) for e in df[category_column].unique()]}
+    else:
+        figure_kwargs = {}
+
+    if log:
+        figure_kwargs['x_axis_type'] = 'log'
+
+    p = figure(plot_width=plot_size[0], plot_height=plot_size[1],
+               tools="reset,pan,box_select,wheel_zoom", toolbar_location="right", **figure_kwargs)
+    p.toolbar.active_scroll = p.select_one(WheelZoomTool)
+
+    kwargs = {}
+    if color_column:
+        color_column_values = [str(e) for e in df[color_column].unique()]
+        palette = d3['Category10'][min(max(len(color_column_values), 3), 10)]
+        kwargs['color'] = factor_cmap(color_column, palette=palette, factors=color_column_values)
+        kwargs['legend'] = color_column
+
+    use_jitter = True
+    y = jitter(category_column, width=0.05, range=p.y_range, distribution='normal') if use_jitter else category_column
+
+    p.circle(source=source, x=dof_column, y=y, alpha=0.5, **kwargs)
+
+    p.legend.location = 'bottom_center'
+    p.legend.orientation = "horizontal"
+    p.legend.label_text_font_size = "6pt"
+    p.legend.padding = 0
+    p.legend.margin = 0
+
+    if enable_hover:
+        columns_to_hide = ['all_measurements', color_column, category_column, dof_column]
+        hover = HoverTool()
+        hover.tooltips = [(c, '@' + c) for c in df.columns if str(c) not in columns_to_hide]
+        # hover.tooltips.append(('index', '$index'))
+        p.add_tools(hover)
+    return p, source
diff --git a/lbmpy_tests/benchmark/i10staff14_benchmark b/lbmpy_tests/benchmark/i10staff14_benchmark
new file mode 100644
index 0000000000000000000000000000000000000000..3da1f5ec379d12c9fe1c4dddf6b84e1f77920b88
--- /dev/null
+++ b/lbmpy_tests/benchmark/i10staff14_benchmark
@@ -0,0 +1,23 @@
+#nvidia-docker run --privileged=true -it --name "benchmark_martin" i10git.cs.fau.de:5005/software/pystencils/benchmark /bin/bash
+#docker exec -it benchmark_martin /bin/bash
+
+apt-get update; apt-get install -y vim htop
+pip install blitzdb
+
+export PATH=$PATH:/usr/local/likwid/bin
+
+likwid-setFrequencies -t 0
+likwid-setFrequencies -g performance
+likwid-setFrequencies -x 3.3 -y 3.3 # set frequency to 3.3
+
+git clone https://i10git.cs.fau.de/software/pystencils.git 
+cd pystencils; python install_all.py
+
+# Socket 1
+cd lbmpy_tests/benchmark
+export OMP_PLACES="{0}, {1}, {2}, {3}"  # pin to first socket
+taskset -c 0,1,2,3 python3 test_benchmark.py client -n i10swarm14_freq3.3 -H i10staff41
+
+# Socket 2
+export OMP_PLACES="{4}, {5}, {6}, {7}"  # pin to first socket
+taskset -c 4,5,6,7 python3 test_benchmark.py client -n i10swarm14_freq3.3 -H i10staff41
diff --git a/lbmpy_tests/benchmark/test_benchmark.py b/lbmpy_tests/benchmark/test_benchmark.py
new file mode 100644
index 0000000000000000000000000000000000000000..b8192dcca9fb40375455a2eb83db7040156bceb3
--- /dev/null
+++ b/lbmpy_tests/benchmark/test_benchmark.py
@@ -0,0 +1,280 @@
+import pytest
+import numpy as np
+import sympy as sp
+from lbmpy.scenarios import create_lid_driven_cavity
+from pystencils.runhelper import ParameterStudy
+from statistics import median
+from pystencils.cpu.cpujit import add_or_change_compiler_flags
+
+
+def parameter_filter(parameters):
+    """Returns false for parameter combinations which are invalid or not implemented yet."""
+    is_entropic_kbc = parameters['method'].startswith('trt-kbc-') and parameters.get("entropic", False)
+    if is_entropic_kbc and parameters['stencil'] == 'D3Q19':
+        return False
+    if is_entropic_kbc and not parameters['compressible']:
+        return False
+    return True
+
+
+def optimization_options_cpu(all_vectorization_options=False, all_cse_options=False, cores=(1,), with_split=False,
+                             instruction_set='avx'):
+    """Generator of different CPU optimization options.
+
+    Args:
+        all_vectorization_options: if true, explore all different vectorization possibilities (x6 more options)
+        all_cse_options: if true, explore all cse options
+        cores: sequence of core numbers
+        with_split: if true, yield configurations with and without split, otherwise only without split
+        instruction_set: 'sse', 'avx' or 'avx2'
+    """
+
+    if all_vectorization_options:
+        vectorization_options = [
+            {'instruction_set': instruction_set,
+             'assume_aligned': assume_aligned,
+             'nontemporal': nontemporal,
+             'assume_inner_stride_one': True,
+             'assume_sufficient_line_padding': lp}
+            for assume_aligned in (False, True)
+            for nontemporal in ((False, True) if assume_aligned else (False,))
+            for lp in (False, True)
+        ]
+        vectorization_options.append(False)
+    else:
+        vectorization_options = [{'instruction_set': instruction_set, 'assume_aligned': True,
+                                  'nontemporal': True, 'assume_inner_stride_one': True}]
+
+    if all_cse_options:
+        cse_options = [
+            {'cse_pdfs': cse_pdfs, 'cse_global': cse_global}
+            for cse_pdfs in (False, True) for cse_global in (False, True)
+        ]
+    else:
+        cse_options = [{'cse_pdfs': False, 'cse_global': True}]
+
+    for vectorization_option in vectorization_options:
+        for cse_option in cse_options:
+            for split in (False, True) if with_split else (False,):
+                for openmp in cores:
+                    for field_layout in ('fzyx', 'zyxf'):
+                        if field_layout == 'zyxf' and vectorization_option is not False:
+                            continue
+                        opt_option = cse_option.copy()
+                        opt_option['vectorization'] = vectorization_option
+                        opt_option['split'] = split
+                        opt_option['openmp'] = openmp
+                        opt_option['field_layout'] = field_layout
+                        yield opt_option
+
+
+def method_options(dim=2, with_srt=False, with_mrt=False,
+                   with_entropic=False, with_cumulant=False, with_smagorinsky=False, with_d3q27=True):
+    """Generator for different lbmpy method parameters
+
+    Args:
+        dim: 2D or 3D
+        with_srt: include single relaxation time models (by default only TRT are included)
+        with_mrt: include multi-relaxation time models
+        with_entropic: include entropic models
+        with_cumulant: include cumulant models
+        with_smagorinsky: include methods with Smagorinsky turbulence model
+    """
+    relaxation_rates = tuple(np.linspace(1.1, 1.9, 27))
+    rr_free = "rr_free"
+    methods = [{'method': 'trt'}]
+    if with_mrt:
+        methods += [{'method': 'mrt3'}, {'method': 'mrt_raw'}]
+
+    if with_srt:
+        methods += [{'method': 'srt'}]
+
+    if with_entropic:
+        methods += [{'entropic': True, 'method': 'mrt3', 'relaxation_rates': [1.5, 1.5, rr_free]},
+                    {'entropic': True, 'method': 'mrt3', 'relaxation_rates': [1.5, rr_free, rr_free]},
+                    {'entropic': True, 'method': 'trt-kbc-n1'},
+                    {'entropic': True, 'method': 'trt-kbc-n2'},
+                    {'entropic': True, 'method': 'trt-kbc-n3'},
+                    {'entropic': True, 'method': 'trt-kbc-n4'},
+                    {'method': 'entropic-srt'}]
+
+    if with_cumulant:
+        methods += [{'cumulant': True, 'method': 'srt'},
+                    {'cumulant': True, 'method': 'trt'},
+                    {'cumulant': True, 'method': 'mrt3'},
+                    {'cumulant': True, 'method': 'mrt_raw'}]
+
+    if with_smagorinsky:
+        methods += [{'smagorinsky': True, 'method': 'srt'},
+                    {'smagorinsky': True, 'method': 'mrt3'}]
+
+    stencils3d = ('D3Q19', 'D3Q27') if with_d3q27 else ("D3Q19",)
+    for stencil in ("D2Q9",) if dim == 2 else stencils3d:
+        for method in methods:
+            options = {'compressible': True, 'stencil': stencil, 'relaxation_rates': relaxation_rates}
+            options.update(method)
+            if parameter_filter(options):
+                yield options
+
+
+def benchmark_scenarios(domain_size, method_option_params={}, optimization_option_params={},
+                        fixed_loop_sizes=True, fixed_relaxation_rates=True):
+
+    method_option_params['dim'] = len(domain_size)
+    for method_option in method_options(**method_option_params):
+        for optimization in optimization_options_cpu(**optimization_option_params):
+            result = method_option.copy()
+            result.update({
+                'domain_size': domain_size,
+                'optimization': optimization,
+                'fixed_loop_sizes': fixed_loop_sizes,
+                'fixed_relaxation_rates': fixed_relaxation_rates,
+            })
+            yield result
+
+
+def run(domain_size, **kwargs):
+    color = {'yellow': '\033[93m',
+             'blue': '\033[94m',
+             'green': '\033[92m',
+             'bold': '\033[1m',
+             'cend': '\033[0m',
+             }
+    study_name = kwargs.get('study_name', 'study')
+    del kwargs['study_name']
+
+    if 'relaxation_rates' in kwargs:
+        kwargs['relaxation_rates'] = [sp.sympify(e) for e in kwargs['relaxation_rates']]
+
+    if 'compiler_flags' in kwargs:
+        add_or_change_compiler_flags(kwargs['compiler_flags'].split())
+        del kwargs['compiler_flags']
+    else:
+        add_or_change_compiler_flags("-march=native")
+
+    opt_str = str(kwargs['optimization']).replace("'", "").replace("False", "0").replace("True", "1")
+    opt_str = opt_str.replace("assume_aligend", 'align').replace("instruction_set", "is").replace("nontemporal", "nt")
+    param_str = "{bold}{domain_size}{cend} {blue}method: {method: <5}, stencil: {stencil}, {cend} " \
+                "comp: {compressible:d}, const_loop: {fixed_loop_sizes:d}, const_rr: {fixed_relaxation_rates:d}, " \
+                "{green}opt: {opt_str}{cend}"
+    param_str = param_str.format(opt_str=opt_str, domain_size=domain_size, **kwargs, **color)
+    sc = create_lid_driven_cavity(domain_size, **kwargs)
+
+    mlups = [sc.benchmark(time_for_benchmark=2) for _ in range(5)]
+    if not np.isfinite(sc.data_handling.max(sc.velocity_data_name)):
+        print("-> ", param_str, " got unstable", flush=True)
+        return {'mlups_max': None,
+                'mlups_median': None,
+                'all_measurements': [],
+                'stable': False,
+                'study_name': study_name}
+
+    result_str = "  {yellow}{bold}{mlups:.0f}±{diff:.2f} MLUPS {cend}".format(mlups=median(mlups),
+                                                                              diff=max(mlups) - min(mlups),
+                                                                              **color)
+    print("-> ", param_str, result_str, flush=True)
+    return {'mlups_max': max(mlups),
+            'mlups_median': median(mlups),
+            'all_measurements': mlups,
+            'stable': True}
+
+
+def study_optimization_options(study, domain_sizes=((1024, 1024), (256, 256, 128)),
+                               with_srt=False, with_mrt=False, with_entropic=False, with_cumulant=False,
+                               with_smagorinsky=False,
+                               all_vectorization_options=False, all_cse_options=False, cores=(1,), with_split=False,
+                               with_symbols=False, overwrite_params={}):
+    mp = {'with_mrt': with_mrt, 'with_entropic': with_entropic, 'with_cumulant': with_cumulant,
+          'with_smagorinsky': with_smagorinsky, 'with_srt': with_srt}
+    op = {'all_vectorization_options': all_vectorization_options, 'all_cse_options': all_cse_options,
+          'cores': cores, 'with_split': with_split}
+
+    for ds in domain_sizes:
+        for const_ls in (True, False) if with_symbols else (True,):
+            for const_rr in (True, False) if with_symbols else (True,):
+                for params in benchmark_scenarios(ds, mp, op,
+                                                  fixed_loop_sizes=const_ls, fixed_relaxation_rates=const_rr):
+                    params.update(overwrite_params)
+                    params['study_name'] = 'optimization_options'
+                    study.add_run(params, weight=ds[0] // domain_sizes[0][0])
+    return study
+
+
+def study_block_sizes_trt(study):
+    mp = {'with_mrt': False, 'with_entropic': False, 'with_smagorinsky': False, 'with_srt': False, 'with_d3q27': False}
+    op = {'all_vectorization_options': True, 'all_cse_options': False,
+          'cores': (1, 2, 3, 4), 'with_split': True}
+
+    domain_sizes = [
+        # 3D
+        (8, 8, 8), (12, 12, 12), (16, 16, 16),
+        (32, 32, 32), (64, 64, 64), (128, 128, 128), (256, 256, 256),
+        (257, 257, 257), (258, 258, 258), (259, 259, 259), (260, 260, 260),
+        (261, 261, 261), (262, 262, 262), (263, 263, 263), (264, 264, 264),
+        # 2D
+        (32, 32), (64, 64), (70, 70), (80, 80), (84, 84), (90, 90),  # L2 boundary
+        (128, 128), (256, 256), (300, 300), (320, 320), (340, 340), (350, 350),  # L3 boundary
+        (400, 400), (512, 512), (1024, 1024), (2048, 2048), (8192, 8192),
+    ]
+
+    for ds in domain_sizes:
+        for fixed in (True, False):
+            for params in benchmark_scenarios(ds, mp, op, fixed_loop_sizes=fixed, fixed_relaxation_rates=fixed):
+                params['study_name'] = 'block_sizes_trt'
+                study.add_run(params, weight=ds[0] // domain_sizes[0][0])
+
+
+@pytest.mark.longrun
+def test_run():
+    """Called by test suite - ensures that benchmark can be run"""
+    s = ParameterStudy(run)
+    study_optimization_options(s, domain_sizes=((17, 23), (19, 17, 18))).run()
+
+
+def study_compiler_flags(study):
+    mp = {'with_mrt': True, 'with_entropic': False, 'with_cumulant': False,
+          'with_smagorinsky': False, 'with_srt': False}
+    op = {'all_vectorization_options': False, 'all_cse_options': False,
+          'cores': (1, 2, 3, 4), 'with_split': True}
+
+    vector_configs = [
+        ('-march=native -mavx512vl',          "avx512"),
+        ('-march=native -mavx512vl -mno-fma', "avx512"),
+        ('-mavx2',            "avx"),
+        ('-mavx2 -mno-fma',   "avx"),
+    ]
+
+    for fixed in (False, True):
+        for flags, instruction_set in vector_configs:
+            for params in benchmark_scenarios((128, 128, 128), mp, op,
+                                              fixed_loop_sizes=fixed, fixed_relaxation_rates=fixed):
+                    params['study_name'] = 'vectorization_flags'
+                    if 'vectorization' in params['optimization'] and isinstance(params['optimization']['vectorization'], dict):
+                        params['optimization']['vectorization']['instruction_set'] = instruction_set
+                        params['compiler_flags'] = flags
+                    study.add_run(params)
+
+
+def main():
+    s = ParameterStudy(run)
+
+    study_compiler_flags(s)
+
+    #study_block_sizes_trt(s)
+    #
+    #study_optimization_options(s, domain_sizes=((128, 128, 128), (1024, 1024)),
+    #                           with_mrt=True, all_vectorization_options=True, with_smagorinsky=True,
+    #                           with_entropic=True, with_srt=True, with_cumulant=True,
+    #                           all_cse_options=True, with_split=False, with_symbols=False,
+    #                           cores=(1, 2, 3, 4))
+    #
+    #study_optimization_options(s, domain_sizes=((128, 128, 128), (1024, 1024)),
+    #                           with_mrt=True, all_vectorization_options=True, with_smagorinsky=True, with_srt=True,
+    #                           all_cse_options=True, with_split=True, with_symbols=True,
+    #                           cores=(1, 2, 3, 4))
+
+    s.run_from_command_line()
+
+
+if __name__ == '__main__':
+    main()
diff --git a/lbmpy_tests/full_scenarios/kida_vortex_flow/Evaluation.ipynb b/lbmpy_tests/full_scenarios/kida_vortex_flow/Evaluation.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..56a5a50f8b11067f42291a43c45f1e2a7ccc857f
--- /dev/null
+++ b/lbmpy_tests/full_scenarios/kida_vortex_flow/Evaluation.ipynb
@@ -0,0 +1,2176 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "import pandas as pd\n",
+    "import matplotlib\n",
+    "from pystencils.runhelper.db import Database, remove_constant_columns\n",
+    "matplotlib.style.use('ggplot')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Kida Vortex Flow evaluation\n",
+    "\n",
+    "This notebook assumes that all scenarios have been run, for example by calling\n",
+    "`python3 kida_vortex_flow.py local`\n",
+    "\n",
+    "This creates a `db` folder containing a database with all results. This notebook reads these results and analyses them."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The next cell reads the complete database into a pandas dataframe and does some basic clean up of the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "db = Database('./db')\n",
+    "all_res = db.to_pandas({}) # load all\n",
+    "\n",
+    "\n",
+    "def clean_up(df):\n",
+    "    # Convert cells that are lists to tuples - so that the remove_columns works\n",
+    "    df = df.applymap(lambda e: tuple(e) if isinstance(e, list) else e)\n",
+    "    \n",
+    "    # fill defaults correctly\n",
+    "    df['compressible'] = df['compressible'].fillna(False)\n",
+    "    df['stencil'] = df['stencil'].fillna('D3Q27')\n",
+    "    df['entropic'] = df['entropic'].fillna(False)\n",
+    "    \n",
+    "    # add max_enstrophy column\n",
+    "    df['max_enstrophy'] = df.apply(lambda row: max(row['enstrophy']), axis=1)\n",
+    "    \n",
+    "    # sort of too high enstrophy (from unstable simulations)\n",
+    "    df['stable'] = df.apply(lambda row: row['stable'] and row['max_enstrophy'] < 4.0, axis=1)\n",
+    "\n",
+    "    # Show only columns that are not constant\n",
+    "    df, constants = remove_constant_columns(df)\n",
+    "        \n",
+    "    return df\n",
+    "    \n",
+    "all_res = clean_up(all_res)\n",
+    "\n",
+    "# get only the stable simulations\n",
+    "all_stable = all_res[all_res['stable']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "interesting_columns = ['domain_size', 'method', 'compressible', 'smagorinsky', 'entropic', 'stencil',\n",
+    "                       'relaxation_rates', 'max_enstrophy', 'mlups']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "    <tr>\n",
+       "      <th>52322db137434ea7bb3cf237ca630352</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.702458</td>\n",
+       "      <td>63.725894</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>384568510ab34724b00c26fa1df6f347</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.701027</td>\n",
+       "      <td>66.652911</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dd4576af37e848f593d979ccdbaad7d6</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.123308</td>\n",
+       "      <td>79.039199</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>c34ad8ddcbf142658ce751e76c8617c7</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.123279</td>\n",
+       "      <td>84.097401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7dc31fddd07b49858c989f2c2eb72539</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.123677</td>\n",
+       "      <td>64.524588</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12545acc11e64d098753c3cf19a57298</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.123647</td>\n",
+       "      <td>67.710659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>beacfae2f81a403f83137e0914b9360d</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt-kbc-n1</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.779498</td>\n",
+       "      <td>32.201492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8bf5ddecca204b46b850e8b637948a5b</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt-kbc-n2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.814222</td>\n",
+       "      <td>35.735995</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>bf5974695ac84c4096628d96bf02ff7e</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt-kbc-n3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.779788</td>\n",
+       "      <td>31.725340</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>054dd85fe3214bcd99433be4781de499</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt-kbc-n4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.823226</td>\n",
+       "      <td>34.204170</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>79890f8f5f28420d94f6ab3bec665778</th>\n",
+       "      <td>100</td>\n",
+       "      <td>mrt3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, 1, 1)</td>\n",
+       "      <td>1.231109</td>\n",
+       "      <td>177.615262</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7a85f103f8354452a0bdea2cea65daf8</th>\n",
+       "      <td>100</td>\n",
+       "      <td>mrt3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, 1, 1)</td>\n",
+       "      <td>1.163564</td>\n",
+       "      <td>92.973482</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>300a0e8eedf84e9ebc1fc34a6c139e4d</th>\n",
+       "      <td>200</td>\n",
+       "      <td>mrt3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, 1, 1)</td>\n",
+       "      <td>2.265399</td>\n",
+       "      <td>225.758547</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>70b832ddfb9045f79c4ddfaa9e31f387</th>\n",
+       "      <td>200</td>\n",
+       "      <td>mrt3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, 1, 1)</td>\n",
+       "      <td>2.060101</td>\n",
+       "      <td>109.428139</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30b7ae4bbc724415ac99226bfebb4c0d</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>2.252673</td>\n",
+       "      <td>155.374599</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>e54833ea17ce48c09e7116f54d32e77f</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>2.244981</td>\n",
+       "      <td>159.846572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0ef7443522e9470caf2f0a2cf5bbc271</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>2.022619</td>\n",
+       "      <td>155.381936</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>bb56332b268645368eca14330c3a2a11</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>2.017195</td>\n",
+       "      <td>160.029627</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7c68fe423ec342af9c1c25bf2a0c389d</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>0.408900</td>\n",
+       "      <td>265.738974</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5c91a59bff78466397994022c2a7a58d</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>0.408704</td>\n",
+       "      <td>295.351243</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ea080bdf8fc04959984c74943cdf90f4</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>0.408126</td>\n",
+       "      <td>155.603733</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2e79ebf52a0d42358ab780476555ce2a</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>0.407897</td>\n",
+       "      <td>160.453408</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4173f7ab1e654c76b79a906f1413d671</th>\n",
+       "      <td>200</td>\n",
+       "      <td>mrt3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, free, free)</td>\n",
+       "      <td>2.570421</td>\n",
+       "      <td>107.601627</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7179028f5f704ecb8641f38a0efb8ed2</th>\n",
+       "      <td>200</td>\n",
+       "      <td>mrt3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, free, free)</td>\n",
+       "      <td>2.528398</td>\n",
+       "      <td>66.452264</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>bb35e1c1a0234f0080034b22a9d31921</th>\n",
+       "      <td>200</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.860364</td>\n",
+       "      <td>298.702238</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2a1cb2664cfc4622b02beb1d56882f29</th>\n",
+       "      <td>200</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.859388</td>\n",
+       "      <td>354.128765</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2afef18786af4505adb0262ae316a8d5</th>\n",
+       "      <td>200</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.861403</td>\n",
+       "      <td>186.981246</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7659d7eeda4548cdbb24d1bf8f41a468</th>\n",
+       "      <td>200</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.860424</td>\n",
+       "      <td>201.240652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f1a6d53ead594d93a7f5dd0205c8e8a5</th>\n",
+       "      <td>200</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2.425819</td>\n",
+       "      <td>300.992072</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>99 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                  domain_size      method  compressible  \\\n",
+       "pk                                                                        \n",
+       "ececd102bb704556ba259a90cf08d6ef          100        mrt3         False   \n",
+       "12a60c0f482041468d426f060d591ea0          100        mrt3         False   \n",
+       "e5030ef8146943bd9548e40a1ac0deba          100         srt          True   \n",
+       "4083027c83e144a3a916d7f205268ff8          100         srt         False   \n",
+       "a07245bd0f9740a7bb1d2a5401643a67          100         srt          True   \n",
+       "04df0909d67443f98cef2fa12ea15358          100         srt         False   \n",
+       "5f19fe8bf62947b09b002888a9288a2b          100         srt          True   \n",
+       "d3d08944480e49ffa2e50a6f7c8fab83          100         srt         False   \n",
+       "ad585c4f6bed4d60bbdb0ee9bfde51bb          100         srt          True   \n",
+       "b8640f253f804e07b23b4bd76d9db1b9          100         trt          True   \n",
+       "d18644c1a06242d9a983387c12a8a366          100         trt         False   \n",
+       "cbab3f56c547415b9027c17c2aabce05          100         trt          True   \n",
+       "1aa8d35d14dd494491bf2de363a681a8          100         trt         False   \n",
+       "f8e9b66b166041eaa54ba33b91ea1154          100         trt          True   \n",
+       "17b9c19fa8ab4e15b065be47a272791f          100         trt         False   \n",
+       "c215c771ee01445c8e59b28840551da6          100         trt          True   \n",
+       "977d154e4e364ef7a60fd3803ef1a8f8          100         trt         False   \n",
+       "ca9a8ab2b76048da89a96b6d585d4eaf          100         trt          True   \n",
+       "cc31eaa857644f67952a6355a28e355f          100         trt         False   \n",
+       "4cc8a67feaeb411c8dca020a23afa8b1          100         trt          True   \n",
+       "9be977cff94a415c82d44d26b297a597          100         trt         False   \n",
+       "0fcd700f7d89473c83f9cd2333322ed1          100        mrt3          True   \n",
+       "df99b7731c354d8683312b8a6bf89ce7          100        mrt3          True   \n",
+       "dd47321e01cb42ffbbac2010f94e5920          100         srt         False   \n",
+       "0f9c09a178d74ee2a17527c788f4705f          100         srt          True   \n",
+       "c6c0f1a886314232aba2fe10cd8d8e91          100         srt         False   \n",
+       "e40fb0b053e948858c5151d2bdd61413          100         srt          True   \n",
+       "a0fa320af37f41d0a6bd597a1bda172d          100         srt         False   \n",
+       "14e0a62f8e534991897b2c1757686e80          100         srt          True   \n",
+       "f34d4a9e58474c5098c777e42b0a7b7e          100         srt         False   \n",
+       "...                                       ...         ...           ...   \n",
+       "3d4b70ee58f94b3cab0adcb33c9273d2           50         srt         False   \n",
+       "52322db137434ea7bb3cf237ca630352           50         srt          True   \n",
+       "384568510ab34724b00c26fa1df6f347           50         srt         False   \n",
+       "dd4576af37e848f593d979ccdbaad7d6           50         srt          True   \n",
+       "c34ad8ddcbf142658ce751e76c8617c7           50         srt         False   \n",
+       "7dc31fddd07b49858c989f2c2eb72539           50         srt          True   \n",
+       "12545acc11e64d098753c3cf19a57298           50         srt         False   \n",
+       "beacfae2f81a403f83137e0914b9360d           50  trt-kbc-n1          True   \n",
+       "8bf5ddecca204b46b850e8b637948a5b           50  trt-kbc-n2          True   \n",
+       "bf5974695ac84c4096628d96bf02ff7e           50  trt-kbc-n3          True   \n",
+       "054dd85fe3214bcd99433be4781de499           50  trt-kbc-n4          True   \n",
+       "79890f8f5f28420d94f6ab3bec665778          100        mrt3         False   \n",
+       "7a85f103f8354452a0bdea2cea65daf8          100        mrt3         False   \n",
+       "300a0e8eedf84e9ebc1fc34a6c139e4d          200        mrt3         False   \n",
+       "70b832ddfb9045f79c4ddfaa9e31f387          200        mrt3         False   \n",
+       "30b7ae4bbc724415ac99226bfebb4c0d          200         trt          True   \n",
+       "e54833ea17ce48c09e7116f54d32e77f          200         trt         False   \n",
+       "0ef7443522e9470caf2f0a2cf5bbc271          200         trt          True   \n",
+       "bb56332b268645368eca14330c3a2a11          200         trt         False   \n",
+       "7c68fe423ec342af9c1c25bf2a0c389d          200         trt          True   \n",
+       "5c91a59bff78466397994022c2a7a58d          200         trt         False   \n",
+       "ea080bdf8fc04959984c74943cdf90f4          200         trt          True   \n",
+       "2e79ebf52a0d42358ab780476555ce2a          200         trt         False   \n",
+       "4173f7ab1e654c76b79a906f1413d671          200        mrt3          True   \n",
+       "7179028f5f704ecb8641f38a0efb8ed2          200        mrt3          True   \n",
+       "bb35e1c1a0234f0080034b22a9d31921          200         srt          True   \n",
+       "2a1cb2664cfc4622b02beb1d56882f29          200         srt         False   \n",
+       "2afef18786af4505adb0262ae316a8d5          200         srt          True   \n",
+       "7659d7eeda4548cdbb24d1bf8f41a468          200         srt         False   \n",
+       "f1a6d53ead594d93a7f5dd0205c8e8a5          200         srt          True   \n",
+       "\n",
+       "                                  smagorinsky  entropic stencil  \\\n",
+       "pk                                                                \n",
+       "ececd102bb704556ba259a90cf08d6ef          NaN     False   D3Q19   \n",
+       "12a60c0f482041468d426f060d591ea0          NaN     False   D3Q27   \n",
+       "e5030ef8146943bd9548e40a1ac0deba         0.80     False   D3Q19   \n",
+       "4083027c83e144a3a916d7f205268ff8         0.80     False   D3Q19   \n",
+       "a07245bd0f9740a7bb1d2a5401643a67         0.80     False   D3Q27   \n",
+       "04df0909d67443f98cef2fa12ea15358         0.80     False   D3Q27   \n",
+       "5f19fe8bf62947b09b002888a9288a2b         0.10     False   D3Q19   \n",
+       "d3d08944480e49ffa2e50a6f7c8fab83         0.10     False   D3Q19   \n",
+       "ad585c4f6bed4d60bbdb0ee9bfde51bb         0.10     False   D3Q27   \n",
+       "b8640f253f804e07b23b4bd76d9db1b9         0.12     False   D3Q19   \n",
+       "d18644c1a06242d9a983387c12a8a366         0.12     False   D3Q19   \n",
+       "cbab3f56c547415b9027c17c2aabce05         0.12     False   D3Q27   \n",
+       "1aa8d35d14dd494491bf2de363a681a8         0.12     False   D3Q27   \n",
+       "f8e9b66b166041eaa54ba33b91ea1154         0.16     False   D3Q19   \n",
+       "17b9c19fa8ab4e15b065be47a272791f         0.16     False   D3Q19   \n",
+       "c215c771ee01445c8e59b28840551da6         0.16     False   D3Q27   \n",
+       "977d154e4e364ef7a60fd3803ef1a8f8         0.16     False   D3Q27   \n",
+       "ca9a8ab2b76048da89a96b6d585d4eaf         2.00     False   D3Q19   \n",
+       "cc31eaa857644f67952a6355a28e355f         2.00     False   D3Q19   \n",
+       "4cc8a67feaeb411c8dca020a23afa8b1         2.00     False   D3Q27   \n",
+       "9be977cff94a415c82d44d26b297a597         2.00     False   D3Q27   \n",
+       "0fcd700f7d89473c83f9cd2333322ed1          NaN      True   D3Q19   \n",
+       "df99b7731c354d8683312b8a6bf89ce7          NaN      True   D3Q27   \n",
+       "dd47321e01cb42ffbbac2010f94e5920         0.10     False   D3Q27   \n",
+       "0f9c09a178d74ee2a17527c788f4705f         0.12     False   D3Q19   \n",
+       "c6c0f1a886314232aba2fe10cd8d8e91         0.12     False   D3Q19   \n",
+       "e40fb0b053e948858c5151d2bdd61413         0.12     False   D3Q27   \n",
+       "a0fa320af37f41d0a6bd597a1bda172d         0.12     False   D3Q27   \n",
+       "14e0a62f8e534991897b2c1757686e80         0.16     False   D3Q19   \n",
+       "f34d4a9e58474c5098c777e42b0a7b7e         0.16     False   D3Q19   \n",
+       "...                                       ...       ...     ...   \n",
+       "3d4b70ee58f94b3cab0adcb33c9273d2         0.16     False   D3Q19   \n",
+       "52322db137434ea7bb3cf237ca630352         0.16     False   D3Q27   \n",
+       "384568510ab34724b00c26fa1df6f347         0.16     False   D3Q27   \n",
+       "dd4576af37e848f593d979ccdbaad7d6         2.00     False   D3Q19   \n",
+       "c34ad8ddcbf142658ce751e76c8617c7         2.00     False   D3Q19   \n",
+       "7dc31fddd07b49858c989f2c2eb72539         2.00     False   D3Q27   \n",
+       "12545acc11e64d098753c3cf19a57298         2.00     False   D3Q27   \n",
+       "beacfae2f81a403f83137e0914b9360d          NaN      True   D3Q27   \n",
+       "8bf5ddecca204b46b850e8b637948a5b          NaN      True   D3Q27   \n",
+       "bf5974695ac84c4096628d96bf02ff7e          NaN      True   D3Q27   \n",
+       "054dd85fe3214bcd99433be4781de499          NaN      True   D3Q27   \n",
+       "79890f8f5f28420d94f6ab3bec665778          NaN     False   D3Q19   \n",
+       "7a85f103f8354452a0bdea2cea65daf8          NaN     False   D3Q27   \n",
+       "300a0e8eedf84e9ebc1fc34a6c139e4d          NaN     False   D3Q19   \n",
+       "70b832ddfb9045f79c4ddfaa9e31f387          NaN     False   D3Q27   \n",
+       "30b7ae4bbc724415ac99226bfebb4c0d         0.12     False   D3Q27   \n",
+       "e54833ea17ce48c09e7116f54d32e77f         0.12     False   D3Q27   \n",
+       "0ef7443522e9470caf2f0a2cf5bbc271         0.16     False   D3Q27   \n",
+       "bb56332b268645368eca14330c3a2a11         0.16     False   D3Q27   \n",
+       "7c68fe423ec342af9c1c25bf2a0c389d         2.00     False   D3Q19   \n",
+       "5c91a59bff78466397994022c2a7a58d         2.00     False   D3Q19   \n",
+       "ea080bdf8fc04959984c74943cdf90f4         2.00     False   D3Q27   \n",
+       "2e79ebf52a0d42358ab780476555ce2a         2.00     False   D3Q27   \n",
+       "4173f7ab1e654c76b79a906f1413d671          NaN      True   D3Q19   \n",
+       "7179028f5f704ecb8641f38a0efb8ed2          NaN      True   D3Q27   \n",
+       "bb35e1c1a0234f0080034b22a9d31921         0.80     False   D3Q19   \n",
+       "2a1cb2664cfc4622b02beb1d56882f29         0.80     False   D3Q19   \n",
+       "2afef18786af4505adb0262ae316a8d5         0.80     False   D3Q27   \n",
+       "7659d7eeda4548cdbb24d1bf8f41a468         0.80     False   D3Q27   \n",
+       "f1a6d53ead594d93a7f5dd0205c8e8a5         0.10     False   D3Q19   \n",
+       "\n",
+       "                                         relaxation_rates  max_enstrophy  \\\n",
+       "pk                                                                         \n",
+       "ececd102bb704556ba259a90cf08d6ef             (None, 1, 1)       1.231109   \n",
+       "12a60c0f482041468d426f060d591ea0             (None, 1, 1)       1.163564   \n",
+       "e5030ef8146943bd9548e40a1ac0deba                      NaN       0.494621   \n",
+       "4083027c83e144a3a916d7f205268ff8                      NaN       0.493650   \n",
+       "a07245bd0f9740a7bb1d2a5401643a67                      NaN       0.494792   \n",
+       "04df0909d67443f98cef2fa12ea15358                      NaN       0.493823   \n",
+       "5f19fe8bf62947b09b002888a9288a2b                      NaN       1.438728   \n",
+       "d3d08944480e49ffa2e50a6f7c8fab83                      NaN       1.434357   \n",
+       "ad585c4f6bed4d60bbdb0ee9bfde51bb                      NaN       1.459617   \n",
+       "b8640f253f804e07b23b4bd76d9db1b9   (viscosity, trt_magic)       3.286732   \n",
+       "d18644c1a06242d9a983387c12a8a366   (viscosity, trt_magic)       3.377183   \n",
+       "cbab3f56c547415b9027c17c2aabce05   (viscosity, trt_magic)       1.163212   \n",
+       "1aa8d35d14dd494491bf2de363a681a8   (viscosity, trt_magic)       1.161721   \n",
+       "f8e9b66b166041eaa54ba33b91ea1154   (viscosity, trt_magic)       1.643292   \n",
+       "17b9c19fa8ab4e15b065be47a272791f   (viscosity, trt_magic)       1.645383   \n",
+       "c215c771ee01445c8e59b28840551da6   (viscosity, trt_magic)       1.008890   \n",
+       "977d154e4e364ef7a60fd3803ef1a8f8   (viscosity, trt_magic)       1.007901   \n",
+       "ca9a8ab2b76048da89a96b6d585d4eaf   (viscosity, trt_magic)       0.299495   \n",
+       "cc31eaa857644f67952a6355a28e355f   (viscosity, trt_magic)       0.299547   \n",
+       "4cc8a67feaeb411c8dca020a23afa8b1   (viscosity, trt_magic)       0.297157   \n",
+       "9be977cff94a415c82d44d26b297a597   (viscosity, trt_magic)       0.297208   \n",
+       "0fcd700f7d89473c83f9cd2333322ed1  (viscosity, free, free)       1.559682   \n",
+       "df99b7731c354d8683312b8a6bf89ce7  (viscosity, free, free)       1.516528   \n",
+       "dd47321e01cb42ffbbac2010f94e5920                      NaN       1.454686   \n",
+       "0f9c09a178d74ee2a17527c788f4705f                      NaN       1.369640   \n",
+       "c6c0f1a886314232aba2fe10cd8d8e91                      NaN       1.365130   \n",
+       "e40fb0b053e948858c5151d2bdd61413                      NaN       1.393093   \n",
+       "a0fa320af37f41d0a6bd597a1bda172d                      NaN       1.388213   \n",
+       "14e0a62f8e534991897b2c1757686e80                      NaN       1.248994   \n",
+       "f34d4a9e58474c5098c777e42b0a7b7e                      NaN       1.247721   \n",
+       "...                                                   ...            ...   \n",
+       "3d4b70ee58f94b3cab0adcb33c9273d2                      NaN       0.694096   \n",
+       "52322db137434ea7bb3cf237ca630352                      NaN       0.702458   \n",
+       "384568510ab34724b00c26fa1df6f347                      NaN       0.701027   \n",
+       "dd4576af37e848f593d979ccdbaad7d6                      NaN       0.123308   \n",
+       "c34ad8ddcbf142658ce751e76c8617c7                      NaN       0.123279   \n",
+       "7dc31fddd07b49858c989f2c2eb72539                      NaN       0.123677   \n",
+       "12545acc11e64d098753c3cf19a57298                      NaN       0.123647   \n",
+       "beacfae2f81a403f83137e0914b9360d                      NaN       0.779498   \n",
+       "8bf5ddecca204b46b850e8b637948a5b                      NaN       0.814222   \n",
+       "bf5974695ac84c4096628d96bf02ff7e                      NaN       0.779788   \n",
+       "054dd85fe3214bcd99433be4781de499                      NaN       0.823226   \n",
+       "79890f8f5f28420d94f6ab3bec665778        (viscosity, 1, 1)       1.231109   \n",
+       "7a85f103f8354452a0bdea2cea65daf8        (viscosity, 1, 1)       1.163564   \n",
+       "300a0e8eedf84e9ebc1fc34a6c139e4d        (viscosity, 1, 1)       2.265399   \n",
+       "70b832ddfb9045f79c4ddfaa9e31f387        (viscosity, 1, 1)       2.060101   \n",
+       "30b7ae4bbc724415ac99226bfebb4c0d   (viscosity, trt_magic)       2.252673   \n",
+       "e54833ea17ce48c09e7116f54d32e77f   (viscosity, trt_magic)       2.244981   \n",
+       "0ef7443522e9470caf2f0a2cf5bbc271   (viscosity, trt_magic)       2.022619   \n",
+       "bb56332b268645368eca14330c3a2a11   (viscosity, trt_magic)       2.017195   \n",
+       "7c68fe423ec342af9c1c25bf2a0c389d   (viscosity, trt_magic)       0.408900   \n",
+       "5c91a59bff78466397994022c2a7a58d   (viscosity, trt_magic)       0.408704   \n",
+       "ea080bdf8fc04959984c74943cdf90f4   (viscosity, trt_magic)       0.408126   \n",
+       "2e79ebf52a0d42358ab780476555ce2a   (viscosity, trt_magic)       0.407897   \n",
+       "4173f7ab1e654c76b79a906f1413d671  (viscosity, free, free)       2.570421   \n",
+       "7179028f5f704ecb8641f38a0efb8ed2  (viscosity, free, free)       2.528398   \n",
+       "bb35e1c1a0234f0080034b22a9d31921                      NaN       0.860364   \n",
+       "2a1cb2664cfc4622b02beb1d56882f29                      NaN       0.859388   \n",
+       "2afef18786af4505adb0262ae316a8d5                      NaN       0.861403   \n",
+       "7659d7eeda4548cdbb24d1bf8f41a468                      NaN       0.860424   \n",
+       "f1a6d53ead594d93a7f5dd0205c8e8a5                      NaN       2.425819   \n",
+       "\n",
+       "                                       mlups  \n",
+       "pk                                            \n",
+       "ececd102bb704556ba259a90cf08d6ef  176.596129  \n",
+       "12a60c0f482041468d426f060d591ea0   91.106972  \n",
+       "e5030ef8146943bd9548e40a1ac0deba  217.031768  \n",
+       "4083027c83e144a3a916d7f205268ff8  239.673111  \n",
+       "a07245bd0f9740a7bb1d2a5401643a67  141.128573  \n",
+       "04df0909d67443f98cef2fa12ea15358  152.456265  \n",
+       "5f19fe8bf62947b09b002888a9288a2b  207.926447  \n",
+       "d3d08944480e49ffa2e50a6f7c8fab83  237.441128  \n",
+       "ad585c4f6bed4d60bbdb0ee9bfde51bb  143.931989  \n",
+       "b8640f253f804e07b23b4bd76d9db1b9  200.702268  \n",
+       "d18644c1a06242d9a983387c12a8a366  214.121774  \n",
+       "cbab3f56c547415b9027c17c2aabce05  125.385181  \n",
+       "1aa8d35d14dd494491bf2de363a681a8  128.222002  \n",
+       "f8e9b66b166041eaa54ba33b91ea1154  196.540572  \n",
+       "17b9c19fa8ab4e15b065be47a272791f  211.561366  \n",
+       "c215c771ee01445c8e59b28840551da6  123.841753  \n",
+       "977d154e4e364ef7a60fd3803ef1a8f8  126.989943  \n",
+       "ca9a8ab2b76048da89a96b6d585d4eaf  195.848303  \n",
+       "cc31eaa857644f67952a6355a28e355f  210.540766  \n",
+       "4cc8a67feaeb411c8dca020a23afa8b1  123.325867  \n",
+       "9be977cff94a415c82d44d26b297a597  125.820542  \n",
+       "0fcd700f7d89473c83f9cd2333322ed1   91.205269  \n",
+       "df99b7731c354d8683312b8a6bf89ce7   56.677409  \n",
+       "dd47321e01cb42ffbbac2010f94e5920  155.110713  \n",
+       "0f9c09a178d74ee2a17527c788f4705f  216.245445  \n",
+       "c6c0f1a886314232aba2fe10cd8d8e91  242.824977  \n",
+       "e40fb0b053e948858c5151d2bdd61413  145.293881  \n",
+       "a0fa320af37f41d0a6bd597a1bda172d  153.774930  \n",
+       "14e0a62f8e534991897b2c1757686e80  214.444867  \n",
+       "f34d4a9e58474c5098c777e42b0a7b7e  241.014936  \n",
+       "...                                      ...  \n",
+       "3d4b70ee58f94b3cab0adcb33c9273d2   82.627730  \n",
+       "52322db137434ea7bb3cf237ca630352   63.725894  \n",
+       "384568510ab34724b00c26fa1df6f347   66.652911  \n",
+       "dd4576af37e848f593d979ccdbaad7d6   79.039199  \n",
+       "c34ad8ddcbf142658ce751e76c8617c7   84.097401  \n",
+       "7dc31fddd07b49858c989f2c2eb72539   64.524588  \n",
+       "12545acc11e64d098753c3cf19a57298   67.710659  \n",
+       "beacfae2f81a403f83137e0914b9360d   32.201492  \n",
+       "8bf5ddecca204b46b850e8b637948a5b   35.735995  \n",
+       "bf5974695ac84c4096628d96bf02ff7e   31.725340  \n",
+       "054dd85fe3214bcd99433be4781de499   34.204170  \n",
+       "79890f8f5f28420d94f6ab3bec665778  177.615262  \n",
+       "7a85f103f8354452a0bdea2cea65daf8   92.973482  \n",
+       "300a0e8eedf84e9ebc1fc34a6c139e4d  225.758547  \n",
+       "70b832ddfb9045f79c4ddfaa9e31f387  109.428139  \n",
+       "30b7ae4bbc724415ac99226bfebb4c0d  155.374599  \n",
+       "e54833ea17ce48c09e7116f54d32e77f  159.846572  \n",
+       "0ef7443522e9470caf2f0a2cf5bbc271  155.381936  \n",
+       "bb56332b268645368eca14330c3a2a11  160.029627  \n",
+       "7c68fe423ec342af9c1c25bf2a0c389d  265.738974  \n",
+       "5c91a59bff78466397994022c2a7a58d  295.351243  \n",
+       "ea080bdf8fc04959984c74943cdf90f4  155.603733  \n",
+       "2e79ebf52a0d42358ab780476555ce2a  160.453408  \n",
+       "4173f7ab1e654c76b79a906f1413d671  107.601627  \n",
+       "7179028f5f704ecb8641f38a0efb8ed2   66.452264  \n",
+       "bb35e1c1a0234f0080034b22a9d31921  298.702238  \n",
+       "2a1cb2664cfc4622b02beb1d56882f29  354.128765  \n",
+       "2afef18786af4505adb0262ae316a8d5  186.981246  \n",
+       "7659d7eeda4548cdbb24d1bf8f41a468  201.240652  \n",
+       "f1a6d53ead594d93a7f5dd0205c8e8a5  300.992072  \n",
+       "\n",
+       "[99 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all_stable[interesting_columns]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The next cells shows the simulations with the maximum enstrophy:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>domain_size</th>\n",
+       "      <th>method</th>\n",
+       "      <th>compressible</th>\n",
+       "      <th>smagorinsky</th>\n",
+       "      <th>entropic</th>\n",
+       "      <th>stencil</th>\n",
+       "      <th>relaxation_rates</th>\n",
+       "      <th>max_enstrophy</th>\n",
+       "      <th>mlups</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>pk</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>88563608773741bdb3b0fa324fa8efcf</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.826669</td>\n",
+       "      <td>80.106425</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>d1be6b688fae439684bba3944dbd0a88</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.825455</td>\n",
+       "      <td>83.918875</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>054dd85fe3214bcd99433be4781de499</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt-kbc-n4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.823226</td>\n",
+       "      <td>34.204170</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>e22d730605f945428515b45158f7db5b</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.819374</td>\n",
+       "      <td>64.945927</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>b69c4cbaf91c4d61bf1c4b93ebcfc7eb</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.817902</td>\n",
+       "      <td>67.821583</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8bf5ddecca204b46b850e8b637948a5b</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt-kbc-n2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.814222</td>\n",
+       "      <td>35.735995</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3642e846bd3948d68497d94bf744b04b</th>\n",
+       "      <td>50</td>\n",
+       "      <td>mrt3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, free, free)</td>\n",
+       "      <td>0.803124</td>\n",
+       "      <td>48.392167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>bf5974695ac84c4096628d96bf02ff7e</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt-kbc-n3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.779788</td>\n",
+       "      <td>31.725340</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>beacfae2f81a403f83137e0914b9360d</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt-kbc-n1</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.779498</td>\n",
+       "      <td>32.201492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0e6f3ad628ae44e19da5168aa41194bb</th>\n",
+       "      <td>50</td>\n",
+       "      <td>mrt3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>D3Q27</td>\n",
+       "      <td>(viscosity, free, free)</td>\n",
+       "      <td>0.779498</td>\n",
+       "      <td>35.004117</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                  domain_size      method  compressible  \\\n",
+       "pk                                                                        \n",
+       "88563608773741bdb3b0fa324fa8efcf           50         srt          True   \n",
+       "d1be6b688fae439684bba3944dbd0a88           50         srt         False   \n",
+       "054dd85fe3214bcd99433be4781de499           50  trt-kbc-n4          True   \n",
+       "e22d730605f945428515b45158f7db5b           50         srt          True   \n",
+       "b69c4cbaf91c4d61bf1c4b93ebcfc7eb           50         srt         False   \n",
+       "8bf5ddecca204b46b850e8b637948a5b           50  trt-kbc-n2          True   \n",
+       "3642e846bd3948d68497d94bf744b04b           50        mrt3          True   \n",
+       "bf5974695ac84c4096628d96bf02ff7e           50  trt-kbc-n3          True   \n",
+       "beacfae2f81a403f83137e0914b9360d           50  trt-kbc-n1          True   \n",
+       "0e6f3ad628ae44e19da5168aa41194bb           50        mrt3          True   \n",
+       "\n",
+       "                                  smagorinsky  entropic stencil  \\\n",
+       "pk                                                                \n",
+       "88563608773741bdb3b0fa324fa8efcf          0.1     False   D3Q19   \n",
+       "d1be6b688fae439684bba3944dbd0a88          0.1     False   D3Q19   \n",
+       "054dd85fe3214bcd99433be4781de499          NaN      True   D3Q27   \n",
+       "e22d730605f945428515b45158f7db5b          0.1     False   D3Q27   \n",
+       "b69c4cbaf91c4d61bf1c4b93ebcfc7eb          0.1     False   D3Q27   \n",
+       "8bf5ddecca204b46b850e8b637948a5b          NaN      True   D3Q27   \n",
+       "3642e846bd3948d68497d94bf744b04b          NaN      True   D3Q19   \n",
+       "bf5974695ac84c4096628d96bf02ff7e          NaN      True   D3Q27   \n",
+       "beacfae2f81a403f83137e0914b9360d          NaN      True   D3Q27   \n",
+       "0e6f3ad628ae44e19da5168aa41194bb          NaN      True   D3Q27   \n",
+       "\n",
+       "                                         relaxation_rates  max_enstrophy  \\\n",
+       "pk                                                                         \n",
+       "88563608773741bdb3b0fa324fa8efcf                      NaN       0.826669   \n",
+       "d1be6b688fae439684bba3944dbd0a88                      NaN       0.825455   \n",
+       "054dd85fe3214bcd99433be4781de499                      NaN       0.823226   \n",
+       "e22d730605f945428515b45158f7db5b                      NaN       0.819374   \n",
+       "b69c4cbaf91c4d61bf1c4b93ebcfc7eb                      NaN       0.817902   \n",
+       "8bf5ddecca204b46b850e8b637948a5b                      NaN       0.814222   \n",
+       "3642e846bd3948d68497d94bf744b04b  (viscosity, free, free)       0.803124   \n",
+       "bf5974695ac84c4096628d96bf02ff7e                      NaN       0.779788   \n",
+       "beacfae2f81a403f83137e0914b9360d                      NaN       0.779498   \n",
+       "0e6f3ad628ae44e19da5168aa41194bb  (viscosity, free, free)       0.779498   \n",
+       "\n",
+       "                                      mlups  \n",
+       "pk                                           \n",
+       "88563608773741bdb3b0fa324fa8efcf  80.106425  \n",
+       "d1be6b688fae439684bba3944dbd0a88  83.918875  \n",
+       "054dd85fe3214bcd99433be4781de499  34.204170  \n",
+       "e22d730605f945428515b45158f7db5b  64.945927  \n",
+       "b69c4cbaf91c4d61bf1c4b93ebcfc7eb  67.821583  \n",
+       "8bf5ddecca204b46b850e8b637948a5b  35.735995  \n",
+       "3642e846bd3948d68497d94bf744b04b  48.392167  \n",
+       "bf5974695ac84c4096628d96bf02ff7e  31.725340  \n",
+       "beacfae2f81a403f83137e0914b9360d  32.201492  \n",
+       "0e6f3ad628ae44e19da5168aa41194bb  35.004117  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all_stable.sort_values('max_enstrophy', ascending=False).query(\"domain_size==50\").head(10)[interesting_columns]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plotting\n",
+    "\n",
+    "rows can be accessed by their key:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_scenarios(rows):\n",
+    "    if not hasattr(rows, '__len__'):\n",
+    "        rows = [rows]\n",
+    "            \n",
+    "    lines = []\n",
+    "    \n",
+    "    fig, axes = plt.subplots(1, 3, figsize=(16, 8))\n",
+    "    for row in rows:\n",
+    "        l, = axes[0].plot(row['time'], row['enstrophy'])\n",
+    "        lines.append(l)\n",
+    "        axes[0].set_title(\"Enstrophy\")\n",
+    "        axes[0].set_xlabel(\"time\")\n",
+    "\n",
+    "        axes[1].plot(row['time'], row['kinetic_energy'])\n",
+    "        axes[1].set_title(\"Kinetic energy\")\n",
+    "        axes[1].set_xlabel(\"time\");\n",
+    "\n",
+    "        axes[2].loglog(row['energy_spectrum'])\n",
+    "        axes[2].set_title(\"Energy Spectrum\");\n",
+    "\n",
+    "    descriptions = [\n",
+    "        \"{size} {c} {method}{ent}{rr}{smag}\".format(\n",
+    "            c=\"comp\" if row.compressible else \"incomp\",\n",
+    "            size=row.domain_size,\n",
+    "            smag=\"Smagorinsky({})\".format(row.smagorinsky) if not pd.isnull(row.smagorinsky)else \"\",\n",
+    "            rr=row.relaxation_rates if not pd.isnull(row.relaxation_rates) else \"\",\n",
+    "            method=row.method,\n",
+    "            ent=\"entropic \" if row.entropic else \"\")\n",
+    "        for row in rows]\n",
+    "        \n",
+    "    plt.figlegend(lines, descriptions, loc = 'lower center')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "domain_size                  100\n",
+      "method                      mrt3\n",
+      "smagorinsky                  NaN\n",
+      "entropic                   False\n",
+      "stencil                    D3Q27\n",
+      "relaxation_rates    (None, 1, 1)\n",
+      "max_enstrophy            1.16356\n",
+      "mlups                     91.107\n",
+      "Name: 12a60c0f482041468d426f060d591ea0, dtype: object\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x576 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#row = all_stable.loc['d18644c1a06242d9a983387c12a8a366']\n",
+    "row = all_stable.iloc[1]\n",
+    "plot_scenarios([row])\n",
+    "print(row[interesting_columns])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x576 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# or multiple rows\n",
+    "best = all_stable.query(\"compressible==True\").sort_values('max_enstrophy', ascending=False).head(7)\n",
+    "plot_scenarios([r[1] for r in best.iterrows()])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "r = [r[1] for r in best.iterrows()][-1]\n",
+    "np.isfinite(r.relaxation_rates)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Filtering\n",
+    "\n",
+    "Example: get all simulations with Smagorinsky model and D3Q19 stencil"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>domain_size</th>\n",
+       "      <th>method</th>\n",
+       "      <th>smagorinsky</th>\n",
+       "      <th>entropic</th>\n",
+       "      <th>stencil</th>\n",
+       "      <th>relaxation_rates</th>\n",
+       "      <th>max_enstrophy</th>\n",
+       "      <th>mlups</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>pk</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>e5030ef8146943bd9548e40a1ac0deba</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4.946206e-01</td>\n",
+       "      <td>217.031768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4083027c83e144a3a916d7f205268ff8</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4.936496e-01</td>\n",
+       "      <td>239.673111</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5f19fe8bf62947b09b002888a9288a2b</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.438728e+00</td>\n",
+       "      <td>207.926447</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>d3d08944480e49ffa2e50a6f7c8fab83</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.434357e+00</td>\n",
+       "      <td>237.441128</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>b8640f253f804e07b23b4bd76d9db1b9</th>\n",
+       "      <td>100</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>3.286732e+00</td>\n",
+       "      <td>200.702268</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>d18644c1a06242d9a983387c12a8a366</th>\n",
+       "      <td>100</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>3.377183e+00</td>\n",
+       "      <td>214.121774</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f8e9b66b166041eaa54ba33b91ea1154</th>\n",
+       "      <td>100</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>1.643292e+00</td>\n",
+       "      <td>196.540572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17b9c19fa8ab4e15b065be47a272791f</th>\n",
+       "      <td>100</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>1.645383e+00</td>\n",
+       "      <td>211.561366</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ca9a8ab2b76048da89a96b6d585d4eaf</th>\n",
+       "      <td>100</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>2.994949e-01</td>\n",
+       "      <td>195.848303</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cc31eaa857644f67952a6355a28e355f</th>\n",
+       "      <td>100</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>2.995467e-01</td>\n",
+       "      <td>210.540766</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0f9c09a178d74ee2a17527c788f4705f</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.369640e+00</td>\n",
+       "      <td>216.245445</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>c6c0f1a886314232aba2fe10cd8d8e91</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.365130e+00</td>\n",
+       "      <td>242.824977</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14e0a62f8e534991897b2c1757686e80</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.248994e+00</td>\n",
+       "      <td>214.444867</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f34d4a9e58474c5098c777e42b0a7b7e</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.247721e+00</td>\n",
+       "      <td>241.014936</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>210c215c3d734a6c9aae0a227ad2e9d5</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2.934254e-01</td>\n",
+       "      <td>215.424204</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f5ce3448c4054659babb4b1d015a802e</th>\n",
+       "      <td>100</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2.933446e-01</td>\n",
+       "      <td>238.884413</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95104ee8f9424d9aab86f0758bdb24ac</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>4.939280e+00</td>\n",
+       "      <td>74.624124</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ecdddae784ac45e2ab94cb357ba8f32c</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>1.775981e+158</td>\n",
+       "      <td>78.517568</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9962f4f31787473aad403ecb1e8102de</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>6.648575e-01</td>\n",
+       "      <td>78.000648</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f73590a979344c16a0612562a88991b6</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>6.641643e-01</td>\n",
+       "      <td>81.162636</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9c530a487456455fb093a7917f3334ec</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>2.128982e-01</td>\n",
+       "      <td>75.682983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cc78595f224745f0b645721441c805d0</th>\n",
+       "      <td>50</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>2.129308e-01</td>\n",
+       "      <td>80.018191</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8376cd3ba1a54554a2a90d3033a05d63</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3.157733e-01</td>\n",
+       "      <td>78.404292</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f52609ca532844299d1a40677e2be7ee</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3.157016e-01</td>\n",
+       "      <td>83.833210</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>88563608773741bdb3b0fa324fa8efcf</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.266686e-01</td>\n",
+       "      <td>80.106425</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>d1be6b688fae439684bba3944dbd0a88</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.254547e-01</td>\n",
+       "      <td>83.918875</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>81e3433734054cd6b0f5fb7c99c6e6e9</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7.767943e-01</td>\n",
+       "      <td>77.892873</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2779869090cb40a5963e324e20d0185e</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7.755419e-01</td>\n",
+       "      <td>81.929208</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>a6ee0b3a362f43788a1ba1b0e9abbfff</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>6.953403e-01</td>\n",
+       "      <td>77.632133</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3d4b70ee58f94b3cab0adcb33c9273d2</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>6.940956e-01</td>\n",
+       "      <td>82.627730</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dd4576af37e848f593d979ccdbaad7d6</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.233076e-01</td>\n",
+       "      <td>79.039199</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>c34ad8ddcbf142658ce751e76c8617c7</th>\n",
+       "      <td>50</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.232795e-01</td>\n",
+       "      <td>84.097401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18a5b6e56bf74d00b9fc633e5cf78ccd</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>1.175117e+01</td>\n",
+       "      <td>265.340308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>467a8338b04e4d19bc90b951da57553f</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>1.189589e+01</td>\n",
+       "      <td>295.063290</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3d798e0998ba4b5d8d0d450d770aab62</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>6.026859e+00</td>\n",
+       "      <td>265.581777</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f8bb882352fa48d3bd8eb1fad8f07322</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>6.034221e+00</td>\n",
+       "      <td>295.238134</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7c68fe423ec342af9c1c25bf2a0c389d</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>4.089003e-01</td>\n",
+       "      <td>265.738974</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5c91a59bff78466397994022c2a7a58d</th>\n",
+       "      <td>200</td>\n",
+       "      <td>trt</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>(viscosity, trt_magic)</td>\n",
+       "      <td>4.087039e-01</td>\n",
+       "      <td>295.351243</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>bb35e1c1a0234f0080034b22a9d31921</th>\n",
+       "      <td>200</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.603643e-01</td>\n",
+       "      <td>298.702238</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2a1cb2664cfc4622b02beb1d56882f29</th>\n",
+       "      <td>200</td>\n",
+       "      <td>srt</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>False</td>\n",
+       "      <td>D3Q19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.593883e-01</td>\n",
+       "      <td>354.128765</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                  domain_size method  smagorinsky  entropic  \\\n",
+       "pk                                                                            \n",
+       "e5030ef8146943bd9548e40a1ac0deba          100    srt         0.80     False   \n",
+       "4083027c83e144a3a916d7f205268ff8          100    srt         0.80     False   \n",
+       "5f19fe8bf62947b09b002888a9288a2b          100    srt         0.10     False   \n",
+       "d3d08944480e49ffa2e50a6f7c8fab83          100    srt         0.10     False   \n",
+       "b8640f253f804e07b23b4bd76d9db1b9          100    trt         0.12     False   \n",
+       "d18644c1a06242d9a983387c12a8a366          100    trt         0.12     False   \n",
+       "f8e9b66b166041eaa54ba33b91ea1154          100    trt         0.16     False   \n",
+       "17b9c19fa8ab4e15b065be47a272791f          100    trt         0.16     False   \n",
+       "ca9a8ab2b76048da89a96b6d585d4eaf          100    trt         2.00     False   \n",
+       "cc31eaa857644f67952a6355a28e355f          100    trt         2.00     False   \n",
+       "0f9c09a178d74ee2a17527c788f4705f          100    srt         0.12     False   \n",
+       "c6c0f1a886314232aba2fe10cd8d8e91          100    srt         0.12     False   \n",
+       "14e0a62f8e534991897b2c1757686e80          100    srt         0.16     False   \n",
+       "f34d4a9e58474c5098c777e42b0a7b7e          100    srt         0.16     False   \n",
+       "210c215c3d734a6c9aae0a227ad2e9d5          100    srt         2.00     False   \n",
+       "f5ce3448c4054659babb4b1d015a802e          100    srt         2.00     False   \n",
+       "95104ee8f9424d9aab86f0758bdb24ac           50    trt         0.12     False   \n",
+       "ecdddae784ac45e2ab94cb357ba8f32c           50    trt         0.12     False   \n",
+       "9962f4f31787473aad403ecb1e8102de           50    trt         0.16     False   \n",
+       "f73590a979344c16a0612562a88991b6           50    trt         0.16     False   \n",
+       "9c530a487456455fb093a7917f3334ec           50    trt         2.00     False   \n",
+       "cc78595f224745f0b645721441c805d0           50    trt         2.00     False   \n",
+       "8376cd3ba1a54554a2a90d3033a05d63           50    srt         0.80     False   \n",
+       "f52609ca532844299d1a40677e2be7ee           50    srt         0.80     False   \n",
+       "88563608773741bdb3b0fa324fa8efcf           50    srt         0.10     False   \n",
+       "d1be6b688fae439684bba3944dbd0a88           50    srt         0.10     False   \n",
+       "81e3433734054cd6b0f5fb7c99c6e6e9           50    srt         0.12     False   \n",
+       "2779869090cb40a5963e324e20d0185e           50    srt         0.12     False   \n",
+       "a6ee0b3a362f43788a1ba1b0e9abbfff           50    srt         0.16     False   \n",
+       "3d4b70ee58f94b3cab0adcb33c9273d2           50    srt         0.16     False   \n",
+       "dd4576af37e848f593d979ccdbaad7d6           50    srt         2.00     False   \n",
+       "c34ad8ddcbf142658ce751e76c8617c7           50    srt         2.00     False   \n",
+       "18a5b6e56bf74d00b9fc633e5cf78ccd          200    trt         0.12     False   \n",
+       "467a8338b04e4d19bc90b951da57553f          200    trt         0.12     False   \n",
+       "3d798e0998ba4b5d8d0d450d770aab62          200    trt         0.16     False   \n",
+       "f8bb882352fa48d3bd8eb1fad8f07322          200    trt         0.16     False   \n",
+       "7c68fe423ec342af9c1c25bf2a0c389d          200    trt         2.00     False   \n",
+       "5c91a59bff78466397994022c2a7a58d          200    trt         2.00     False   \n",
+       "bb35e1c1a0234f0080034b22a9d31921          200    srt         0.80     False   \n",
+       "2a1cb2664cfc4622b02beb1d56882f29          200    srt         0.80     False   \n",
+       "\n",
+       "                                 stencil        relaxation_rates  \\\n",
+       "pk                                                                 \n",
+       "e5030ef8146943bd9548e40a1ac0deba   D3Q19                     NaN   \n",
+       "4083027c83e144a3a916d7f205268ff8   D3Q19                     NaN   \n",
+       "5f19fe8bf62947b09b002888a9288a2b   D3Q19                     NaN   \n",
+       "d3d08944480e49ffa2e50a6f7c8fab83   D3Q19                     NaN   \n",
+       "b8640f253f804e07b23b4bd76d9db1b9   D3Q19  (viscosity, trt_magic)   \n",
+       "d18644c1a06242d9a983387c12a8a366   D3Q19  (viscosity, trt_magic)   \n",
+       "f8e9b66b166041eaa54ba33b91ea1154   D3Q19  (viscosity, trt_magic)   \n",
+       "17b9c19fa8ab4e15b065be47a272791f   D3Q19  (viscosity, trt_magic)   \n",
+       "ca9a8ab2b76048da89a96b6d585d4eaf   D3Q19  (viscosity, trt_magic)   \n",
+       "cc31eaa857644f67952a6355a28e355f   D3Q19  (viscosity, trt_magic)   \n",
+       "0f9c09a178d74ee2a17527c788f4705f   D3Q19                     NaN   \n",
+       "c6c0f1a886314232aba2fe10cd8d8e91   D3Q19                     NaN   \n",
+       "14e0a62f8e534991897b2c1757686e80   D3Q19                     NaN   \n",
+       "f34d4a9e58474c5098c777e42b0a7b7e   D3Q19                     NaN   \n",
+       "210c215c3d734a6c9aae0a227ad2e9d5   D3Q19                     NaN   \n",
+       "f5ce3448c4054659babb4b1d015a802e   D3Q19                     NaN   \n",
+       "95104ee8f9424d9aab86f0758bdb24ac   D3Q19  (viscosity, trt_magic)   \n",
+       "ecdddae784ac45e2ab94cb357ba8f32c   D3Q19  (viscosity, trt_magic)   \n",
+       "9962f4f31787473aad403ecb1e8102de   D3Q19  (viscosity, trt_magic)   \n",
+       "f73590a979344c16a0612562a88991b6   D3Q19  (viscosity, trt_magic)   \n",
+       "9c530a487456455fb093a7917f3334ec   D3Q19  (viscosity, trt_magic)   \n",
+       "cc78595f224745f0b645721441c805d0   D3Q19  (viscosity, trt_magic)   \n",
+       "8376cd3ba1a54554a2a90d3033a05d63   D3Q19                     NaN   \n",
+       "f52609ca532844299d1a40677e2be7ee   D3Q19                     NaN   \n",
+       "88563608773741bdb3b0fa324fa8efcf   D3Q19                     NaN   \n",
+       "d1be6b688fae439684bba3944dbd0a88   D3Q19                     NaN   \n",
+       "81e3433734054cd6b0f5fb7c99c6e6e9   D3Q19                     NaN   \n",
+       "2779869090cb40a5963e324e20d0185e   D3Q19                     NaN   \n",
+       "a6ee0b3a362f43788a1ba1b0e9abbfff   D3Q19                     NaN   \n",
+       "3d4b70ee58f94b3cab0adcb33c9273d2   D3Q19                     NaN   \n",
+       "dd4576af37e848f593d979ccdbaad7d6   D3Q19                     NaN   \n",
+       "c34ad8ddcbf142658ce751e76c8617c7   D3Q19                     NaN   \n",
+       "18a5b6e56bf74d00b9fc633e5cf78ccd   D3Q19  (viscosity, trt_magic)   \n",
+       "467a8338b04e4d19bc90b951da57553f   D3Q19  (viscosity, trt_magic)   \n",
+       "3d798e0998ba4b5d8d0d450d770aab62   D3Q19  (viscosity, trt_magic)   \n",
+       "f8bb882352fa48d3bd8eb1fad8f07322   D3Q19  (viscosity, trt_magic)   \n",
+       "7c68fe423ec342af9c1c25bf2a0c389d   D3Q19  (viscosity, trt_magic)   \n",
+       "5c91a59bff78466397994022c2a7a58d   D3Q19  (viscosity, trt_magic)   \n",
+       "bb35e1c1a0234f0080034b22a9d31921   D3Q19                     NaN   \n",
+       "2a1cb2664cfc4622b02beb1d56882f29   D3Q19                     NaN   \n",
+       "\n",
+       "                                  max_enstrophy       mlups  \n",
+       "pk                                                           \n",
+       "e5030ef8146943bd9548e40a1ac0deba   4.946206e-01  217.031768  \n",
+       "4083027c83e144a3a916d7f205268ff8   4.936496e-01  239.673111  \n",
+       "5f19fe8bf62947b09b002888a9288a2b   1.438728e+00  207.926447  \n",
+       "d3d08944480e49ffa2e50a6f7c8fab83   1.434357e+00  237.441128  \n",
+       "b8640f253f804e07b23b4bd76d9db1b9   3.286732e+00  200.702268  \n",
+       "d18644c1a06242d9a983387c12a8a366   3.377183e+00  214.121774  \n",
+       "f8e9b66b166041eaa54ba33b91ea1154   1.643292e+00  196.540572  \n",
+       "17b9c19fa8ab4e15b065be47a272791f   1.645383e+00  211.561366  \n",
+       "ca9a8ab2b76048da89a96b6d585d4eaf   2.994949e-01  195.848303  \n",
+       "cc31eaa857644f67952a6355a28e355f   2.995467e-01  210.540766  \n",
+       "0f9c09a178d74ee2a17527c788f4705f   1.369640e+00  216.245445  \n",
+       "c6c0f1a886314232aba2fe10cd8d8e91   1.365130e+00  242.824977  \n",
+       "14e0a62f8e534991897b2c1757686e80   1.248994e+00  214.444867  \n",
+       "f34d4a9e58474c5098c777e42b0a7b7e   1.247721e+00  241.014936  \n",
+       "210c215c3d734a6c9aae0a227ad2e9d5   2.934254e-01  215.424204  \n",
+       "f5ce3448c4054659babb4b1d015a802e   2.933446e-01  238.884413  \n",
+       "95104ee8f9424d9aab86f0758bdb24ac   4.939280e+00   74.624124  \n",
+       "ecdddae784ac45e2ab94cb357ba8f32c  1.775981e+158   78.517568  \n",
+       "9962f4f31787473aad403ecb1e8102de   6.648575e-01   78.000648  \n",
+       "f73590a979344c16a0612562a88991b6   6.641643e-01   81.162636  \n",
+       "9c530a487456455fb093a7917f3334ec   2.128982e-01   75.682983  \n",
+       "cc78595f224745f0b645721441c805d0   2.129308e-01   80.018191  \n",
+       "8376cd3ba1a54554a2a90d3033a05d63   3.157733e-01   78.404292  \n",
+       "f52609ca532844299d1a40677e2be7ee   3.157016e-01   83.833210  \n",
+       "88563608773741bdb3b0fa324fa8efcf   8.266686e-01   80.106425  \n",
+       "d1be6b688fae439684bba3944dbd0a88   8.254547e-01   83.918875  \n",
+       "81e3433734054cd6b0f5fb7c99c6e6e9   7.767943e-01   77.892873  \n",
+       "2779869090cb40a5963e324e20d0185e   7.755419e-01   81.929208  \n",
+       "a6ee0b3a362f43788a1ba1b0e9abbfff   6.953403e-01   77.632133  \n",
+       "3d4b70ee58f94b3cab0adcb33c9273d2   6.940956e-01   82.627730  \n",
+       "dd4576af37e848f593d979ccdbaad7d6   1.233076e-01   79.039199  \n",
+       "c34ad8ddcbf142658ce751e76c8617c7   1.232795e-01   84.097401  \n",
+       "18a5b6e56bf74d00b9fc633e5cf78ccd   1.175117e+01  265.340308  \n",
+       "467a8338b04e4d19bc90b951da57553f   1.189589e+01  295.063290  \n",
+       "3d798e0998ba4b5d8d0d450d770aab62   6.026859e+00  265.581777  \n",
+       "f8bb882352fa48d3bd8eb1fad8f07322   6.034221e+00  295.238134  \n",
+       "7c68fe423ec342af9c1c25bf2a0c389d   4.089003e-01  265.738974  \n",
+       "5c91a59bff78466397994022c2a7a58d   4.087039e-01  295.351243  \n",
+       "bb35e1c1a0234f0080034b22a9d31921   8.603643e-01  298.702238  \n",
+       "2a1cb2664cfc4622b02beb1d56882f29   8.593883e-01  354.128765  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "smag_d3q19 = all_res.query(\"(smagorinsky > 0) and (stencil =='D3Q19')\")\n",
+    "smag_d3q19[interesting_columns]"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/lbmpy_tests/full_scenarios/kida_vortex_flow/scenario_kida_vortex_flow.py b/lbmpy_tests/full_scenarios/kida_vortex_flow/scenario_kida_vortex_flow.py
new file mode 100644
index 0000000000000000000000000000000000000000..beeaa58c63f930f7898460e66f26c0ba6dbacded
--- /dev/null
+++ b/lbmpy_tests/full_scenarios/kida_vortex_flow/scenario_kida_vortex_flow.py
@@ -0,0 +1,291 @@
+"""
+Testcase as in
+Boesch, Chikatamarla, Karlin: Entropic multirelaxation lattice Boltzmann models for turbulent flows (2015)
+"""
+import numpy as np
+import sympy as sp
+import pystencils as ps
+from lbmpy.lbstep import LatticeBoltzmannStep
+from lbmpy.relaxationrates import relaxation_rate_from_lattice_viscosity, relaxation_rate_from_magic_number
+from pystencils.runhelper import ParameterStudy
+
+
+# --------------------------------------------- Setup ------------------------------------------------------------------
+
+
+def set_initial_velocity(lb_step: LatticeBoltzmannStep, u_0: float) -> None:
+    """Initializes velocity field of a fully periodic scenario with eddies.
+
+    Args:
+        lb_step: fully periodic 3D scenario
+        u_0: maximum velocity
+    """
+    from numpy import cos, sin
+
+    assert lb_step.dim == 3, "Works only for 3D scenarios"
+    assert tuple(lb_step.data_handling.periodicity) == (True, True, True), "Scenario has to be fully periodic"
+
+    for b in lb_step.data_handling.iterate(ghost_layers=False, inner_ghost_layers=False):
+        velocity = b[lb_step.velocity_data_name]
+        coordinates = b.midpoint_arrays
+        x, y, z = [c / s * 2 * np.pi for c, s in zip(coordinates, lb_step.data_handling.shape)]
+
+        velocity[..., 0] = u_0 * sin(x) * (cos(3 * y) * cos(z) - cos(y) * cos(3 * z))
+        velocity[..., 1] = u_0 * sin(y) * (cos(3 * z) * cos(x) - cos(z) * cos(3 * x))
+        velocity[..., 2] = u_0 * sin(z) * (cos(3 * x) * cos(y) - cos(x) * cos(3 * y))
+
+    lb_step.set_pdf_fields_from_macroscopic_values()
+
+
+def relaxation_rate_from_reynolds_number(re, u_0, domain_size):
+    nu = u_0 * domain_size / re
+    return relaxation_rate_from_lattice_viscosity(nu)
+
+
+def time_step_to_normalized_time(time_step, domain_size, u_0):
+    return time_step / (domain_size / u_0)
+
+
+def normalized_time_to_time_step(normalized_time, domain_size, u_0):
+    return int(normalized_time * domain_size / u_0)
+
+# --------------------------------------------- Analysis ---------------------------------------------------------------
+
+
+def energy_density_spectrum(velocity):
+    """Computes energy density for different wave lengths.
+
+    Fourier transformation gives again a 3D field, which is then summed up radially.
+
+    Args:
+        velocity: numpy array indexed as [x, y, z, velocity_component]
+
+    Returns:
+        1D array where entries correspond to energy at different wave lengths
+    """
+    def radial_profile(data):
+        """Sums up given multidimensional field at constant r (integrating over φ and θ) in spherical coordinates."""
+        z, y, x = np.indices(data.shape)
+        center = tuple(c // 2 for c in data.shape)
+        r = np.sqrt((x - center[0]) ** 2 + (y - center[1]) ** 2 + (z - center[2]) ** 2)
+        np.round(r, out=r)
+        r = r.astype(np.int)
+        binned_data = np.bincount(r.ravel(), data.ravel())
+        normalization = np.bincount(r.ravel())
+        return binned_data / normalization
+
+    kinetic_energy = np.sum(velocity * velocity, axis=3) / 2
+    energy_fft_result = np.fft.fftn(kinetic_energy)
+    energy_fft_result = np.abs(np.fft.fftshift(energy_fft_result))
+    # cut off the zero freq energy
+    return radial_profile(energy_fft_result)[1:]
+
+
+def curl(vector_field):
+    """Computes curl (rotation) of a 2D or 3D vector field."""
+    dim = len(vector_field.shape) - 1
+
+    def grad(diff_coord, idx):
+        return np.gradient(vector_field[..., idx], axis=diff_coord)
+
+    if dim == 2:
+        return grad(0, 1) - grad(1, 0)
+    elif dim == 3:
+        result = np.zeros_like(vector_field)
+        result[..., 0] = grad(1, 2) - grad(2, 1)
+        result[..., 1] = grad(2, 0) - grad(0, 2)
+        result[..., 2] = grad(0, 1) - grad(1, 0)
+        return result
+    else:
+        raise NotImplementedError("curl only implemented for 2D and 3D")
+
+
+def mean_kinetic_energy(velocity_arr):
+    """Computes average kinetic energy in the given 3D velocity array as :math:`1/2 * v^2`. """
+    energy_density = np.sum(velocity_arr * velocity_arr, axis=3)
+    return 0.5 * np.mean(energy_density)
+
+
+def mean_enstrophy(velocity_arr):
+    """Computes average enstrophy of given 3D velocity array.
+
+    Enstrophy is computed as spatial average of :math:`1/2 (∇ x u)^2`
+    """
+    w = curl(velocity_arr)
+    w_dot_w = np.sum(w*w, axis=3)
+    return 0.5 * np.mean(w_dot_w)
+
+
+def parallel_mean(lb_step, velocity_post_processor, all_reduce=True):
+    num_local_blocks = 0
+    for b in lb_step.data_handling.iterate(ghost_layers=False, inner_ghost_layers=False):
+        num_local_blocks += 1
+        velocity = b[lb_step.velocity_data_name]
+        local_result = velocity_post_processor(velocity)
+    assert num_local_blocks == 1
+    reduce_result = lb_step.data_handling.reduce_float_sequence([local_result, 1.0],
+                                                                operation='sum', all_reduce=all_reduce)
+    if reduce_result is not None:
+        return reduce_result[0] / reduce_result[1]
+    else:
+        return None
+
+
+def plot_energy_spectrum(velocity_arr):
+    import matplotlib.pyplot as plt
+    spectrum = energy_density_spectrum(velocity_arr)
+    plt.loglog(spectrum)
+    plt.title("Energy Spectrum")
+    plt.show()
+
+
+# --------------------------------------------- Main -------------------------------------------------------------------
+
+def run(re=6000, eval_interval=0.05, total_time=3.0, domain_size=100, u_0=0.05,
+        initialization_relaxation_rate=None, vtk_output=False, parallel=False, **kwargs):
+    """Runs the kida vortex simulation.
+
+    Args:
+        re: Reynolds number
+        eval_interval: interval in non-dimensional time to evaluate flow properties
+        total_time: non-dimensional time of complete simulation
+        domain_size: integer (not tuple) since domain is cubic
+        u_0: maximum lattice velocity
+        initialization_relaxation_rate: if not None, an advanced initialization scheme is run to initialize higher
+                                        order moments correctly
+        vtk_output: if vtk files are written out
+        parallel: MPI parallelization with walberla
+        **kwargs: passed to LbStep
+
+    Returns:
+        dictionary with simulation results
+    """
+    domain_shape = (domain_size, domain_size, domain_size)
+    relaxation_rate = relaxation_rate_from_reynolds_number(re, u_0, domain_size)
+    dh = ps.create_data_handling(domain_shape, periodicity=True, parallel=parallel)
+    rr_subs = {'viscosity': relaxation_rate,
+               'trt_magic': relaxation_rate_from_magic_number(relaxation_rate),
+               'free': sp.Symbol("rr_f")}
+
+    if 'relaxation_rates' in kwargs:
+        kwargs['relaxation_rates'] = [rr_subs[r] if isinstance(r, str) else r for r in kwargs['relaxation_rates']]
+    else:
+        kwargs['relaxation_rates'] = [relaxation_rate]
+
+    dh.log_on_root("Running kida vortex scenario of size {} with {}".format(domain_size, kwargs))
+    dh.log_on_root("Compiling method")
+
+    lb_step = LatticeBoltzmannStep(data_handling=dh, name="kida_vortex", **kwargs)
+
+    set_initial_velocity(lb_step, u_0)
+    residuum, init_steps = np.nan, 0
+    if initialization_relaxation_rate is not None:
+        dh.log_on_root("Running iterative initialization", level='PROGRESS')
+        residuum, init_steps = lb_step.run_iterative_initialization(initialization_relaxation_rate,
+                                                                    convergence_threshold=1e-12, max_steps=100000,
+                                                                    check_residuum_after=2 * domain_size)
+        dh.log_on_root("Iterative initialization finished after {} steps at residuum {}".format(init_steps, residuum))
+
+    total_time_steps = normalized_time_to_time_step(total_time, domain_size, u_0)
+    eval_time_steps = normalized_time_to_time_step(eval_interval, domain_size, u_0)
+
+    initial_energy = parallel_mean(lb_step, mean_kinetic_energy, all_reduce=False)
+    times = []
+    energy_list = []
+    enstrophy_list = []
+    mlups_list = []
+    energy_spectrum_arr = None
+
+    while lb_step.time_steps_run < total_time_steps:
+        mlups = lb_step.benchmark_run(eval_time_steps, number_of_cells=domain_size**3)
+        if vtk_output:
+            lb_step.write_vtk()
+
+        current_time = time_step_to_normalized_time(lb_step.time_steps_run, domain_size, u_0)
+        current_kinetic_energy = parallel_mean(lb_step, mean_kinetic_energy)
+        current_enstrophy = parallel_mean(lb_step, mean_enstrophy)
+
+        is_stable = np.isfinite(lb_step.data_handling.max(lb_step.velocity_data_name)) and current_enstrophy < 1e4
+        if not is_stable:
+            dh.log_on_root("Simulation got unstable - stopping", level='WARNING')
+            break
+
+        if current_time >= 0.5 and energy_spectrum_arr is None and domain_size <= 600:
+            dh.log_on_root("Calculating energy spectrum")
+            gathered_velocity = lb_step.velocity[:, :, :, :]
+
+            if gathered_velocity is not None:
+                energy_spectrum_arr = energy_density_spectrum(gathered_velocity)
+            else:
+                energy_spectrum_arr = False
+
+        if dh.is_root:
+            current_kinetic_energy /= initial_energy
+            current_enstrophy *= domain_size ** 2
+
+            times.append(current_time)
+            energy_list.append(current_kinetic_energy)
+            enstrophy_list.append(current_enstrophy)
+            mlups_list.append(mlups)
+
+            dh.log_on_root("Progress: {current_time:.02f} / {total_time} at {mlups:.01f} MLUPS\t"
+                           "Enstrophy {current_enstrophy:.04f}\t"
+                           "KinEnergy {current_kinetic_energy:.06f}".format(**locals()))
+
+    if dh.is_root:
+        return {
+            'initialization_residuum': residuum,
+            'initialization_steps': init_steps,
+            'time': times,
+            'kinetic_energy': energy_list,
+            'enstrophy': enstrophy_list,
+            'mlups': np.average(mlups_list),
+            'energy_spectrum': list(energy_spectrum_arr),
+            'stable': bool(np.isfinite(lb_step.data_handling.max(lb_step.velocity_data_name)))
+        }
+    else:
+        return None
+
+
+def create_full_parameter_study(gpu=False):
+    """Creates a parameter study that can run the Kida vortex flow with entropic, KBC, Smagorinsky and MRT methods."""
+    opt_cpu = {'target': 'cpu', 'openmp': 4}
+    opt_gpu = {'target': 'gpu'}
+
+    mrt_one = [{'method': 'mrt3', 'relaxation_rates': ['viscosity', 1, 1], 'stencil': stencil}
+               for stencil in ('D3Q19', 'D3Q27')]
+    smagorinsky_srt = [{'method': 'srt', 'smagorinsky': cs, 'stencil': stencil, 'compressible': compressible}
+                       for cs in (0.8, 0.1, 0.12, 0.16, 2.0)
+                       for stencil in ('D3Q19', 'D3Q27')
+                       for compressible in (True, False)]
+    smagorinsky_trt = [{'method': 'trt', 'smagorinsky': cs, 'stencil': stencil, 'compressible': compressible,
+                        'relaxation_rates': ['viscosity', 'trt_magic']}
+                       for cs in (0.12, 0.16, 2.0)
+                       for stencil in ('D3Q19', 'D3Q27')
+                       for compressible in (True, False)]
+    entropic_kbc = [{'method': 'trt-kbc-n{}'.format(kbc_nr), 'entropic': True, 'compressible': True}
+                    for kbc_nr in (1, 2, 3, 4)]
+    entropic_kbc_d3q19 = [{'method': 'mrt3', 'entropic': True, 'compressible': True,
+                           'relaxation_rates': ['viscosity', 'free', 'free'], 'stencil': stencil}
+                          for stencil in ('D3Q19', 'D3Q27')]
+    entropic_pure = [{'method': 'entropic-srt',  'compressible': True, 'stencil': stencil}
+                     for stencil in ('D3Q19', 'D3Q27')]
+
+    all_scenarios = mrt_one + smagorinsky_trt + entropic_kbc_d3q19 + smagorinsky_srt + entropic_kbc + entropic_pure
+    study = ParameterStudy(run)
+    domain_sizes = (50, 100, 200)
+    for domain_size in domain_sizes:
+        for re in (6000,):
+            for scenario in all_scenarios:
+                scenario = scenario.copy()
+                scenario['re'] = re
+                scenario['optimization'] = opt_gpu if gpu else opt_cpu
+                scenario['domain_size'] = domain_size
+                study.add_run(scenario, weight=(domain_size / min(domain_sizes)) ** 4)
+    return study
+
+
+if __name__ == '__main__':
+    parameter_study = create_full_parameter_study(gpu=True)
+    parameter_study.run_from_command_line()
+
diff --git a/lbmpy_tests/full_scenarios/rod/scenario_rod.py b/lbmpy_tests/full_scenarios/rod/scenario_rod.py
new file mode 100644
index 0000000000000000000000000000000000000000..fe87bac3438a495317d64fbb04cac987fa35eda4
--- /dev/null
+++ b/lbmpy_tests/full_scenarios/rod/scenario_rod.py
@@ -0,0 +1,136 @@
+"""Scenario that simulates a channel with a narrow area to analyse the rotational symmetry of the flow field.
+
+This setup is used to illustrate the difference of D3Q19 and D3Q27 for high Reynolds number flows as shown in
+    "Rotational invariance in the three-dimensional lattice Boltzmann method is dependent on the choice of lattice" by
+    Alexander Thomas White, Chuh Khiun Chong (2011)
+
+The deficiencies of the D3Q19 model can be resolved by choosing a better equilibrium (D3Q19_new)
+"""
+import os
+import sys
+import numpy as np
+import sympy as sp
+from lbmpy.boundaries import FixedDensity, NoSlip
+from lbmpy.geometry import add_pipe_inflow_boundary, add_pipe_walls
+from lbmpy.lbstep import LatticeBoltzmannStep
+from lbmpy.relaxationrates import relaxation_rate_from_lattice_viscosity
+from pystencils import create_data_handling
+from pystencils.slicing import make_slice, slice_from_direction
+
+
+def rod_simulation(stencil_name, diameter, parallel=False, entropic=False, re=150,
+                   time_to_simulate=17.0, eval_interval=0.5, write_vtk=True, write_numpy=True,
+                   optimization_params=None):
+    if optimization_params is None:
+        optimization_params = {}
+
+    if stencil_name == 'D3Q19_new':
+        stencil = 'D3Q19'
+        maxwellian_moments = True
+    elif stencil_name == 'D3Q19_old':
+        stencil = 'D3Q19'
+        maxwellian_moments = False
+    elif stencil_name == 'D3Q27':
+        stencil = 'D3Q27'
+        maxwellian_moments = False
+    else:
+        raise ValueError("Unknown stencil name " + stencil_name)
+    d = diameter
+    length = 16 * d
+
+    u_max_at_throat = 0.07
+    u_max_at_inflow = 0.07 / (3 ** 2)
+
+    # Geometry parameters
+    inflow_area = int(1.5 * d)
+    constriction_length = int(1.8904 * d)
+    throat_length = int(10 / 3 * d)
+    constriction_diameter = int(d / 3)
+
+    u_mean_at_throat = u_max_at_throat / 2
+    lattice_viscosity = u_mean_at_throat * constriction_diameter / re
+    omega = relaxation_rate_from_lattice_viscosity(lattice_viscosity)
+
+    method_parameters = {'stencil': stencil,
+                         'compressible': True,
+                         'method': 'srt',
+                         'relaxation_rates': [omega],
+                         'entropic': entropic,
+                         'maxwellian_moments': maxwellian_moments, }
+    kernel_params = {}
+    if entropic:
+        method_parameters['method'] = 'mrt3'
+        method_parameters['relaxation_rates'] = sp.symbols("omega_fix omega_fix omega_free")
+        kernel_params['omega_fix'] = omega
+
+    print("ω=", omega)
+
+    dh = create_data_handling(domain_size=(length, d, d), parallel=parallel)
+    sc = LatticeBoltzmannStep(data_handling=dh, kernel_params=kernel_params, optimization=optimization_params,
+                              name=stencil_name, **method_parameters)
+
+    # -----------------   Boundary Setup   --------------------------------
+
+    def pipe_geometry(x, *_):
+        # initialize with full diameter everywhere
+        result = np.ones_like(x) * d
+
+        # constriction
+        constriction_begin = inflow_area
+        constriction_end = constriction_begin + constriction_length
+        c_x = np.linspace(0, 1, constriction_length)
+        result[constriction_begin: constriction_end] = d * (1 - c_x) + constriction_diameter * c_x
+
+        # throat
+        throat_start = constriction_end
+        throat_end = throat_start + throat_length
+        result[throat_start: throat_end] = constriction_diameter
+
+        return result
+
+    bh = sc.boundary_handling
+    add_pipe_inflow_boundary(bh, u_max_at_inflow, make_slice[0, :, :])
+    outflow = FixedDensity(1.0)
+    bh.set_boundary(outflow, slice_from_direction('E', 3))
+    wall = NoSlip()
+    add_pipe_walls(bh, pipe_geometry, wall)
+
+    # -----------------   Run  --------------------------------------------
+
+    scenario_name = stencil_name
+    if entropic:
+        scenario_name += "_entropic"
+
+    if not os.path.exists(scenario_name):
+        os.mkdir(scenario_name)
+
+    def to_time_steps(non_dimensional_time):
+        return int(diameter / (u_max_at_inflow / 2) * non_dimensional_time)
+
+    time_steps = to_time_steps(time_to_simulate)
+    eval_interval = to_time_steps(eval_interval)
+
+    print("Total number of time steps", time_steps)
+
+    for i in range(time_steps // eval_interval):
+        sc.run(eval_interval)
+        if write_vtk:
+            sc.write_vtk()
+        vel = sc.velocity[:, :, :, :]
+        max_vel = np.max(vel)
+        print("Time steps:", sc.time_steps_run,  "/",  time_steps, "Max velocity: ", max_vel)
+        if np.isnan(max_vel):
+            raise ValueError("Simulation went unstable")
+        if write_numpy:
+            np.save(scenario_name + '/velocity_%06d' % (sc.time_steps_run,), sc.velocity_slice().filled(0.0))
+
+
+def test_rod_scenario_simple():
+    rod_simulation("D3Q19_new", re=100, diameter=20, parallel=False, entropic=False,
+                   time_to_simulate=0.2, eval_interval=0.1, write_vtk=False, write_numpy=False)
+
+
+if __name__ == '__main__':
+    # High Re (Entropic method)
+    rod_simulation(stencil_name=sys.argv[1], re=500, diameter=80, entropic=True, time_to_simulate=17,
+                   parallel=False, optimization_params={'target': 'gpu'})
diff --git a/lbmpy_tests/full_scenarios/schaefer_turek/scenario_schaefer_turek.py b/lbmpy_tests/full_scenarios/schaefer_turek/scenario_schaefer_turek.py
new file mode 100644
index 0000000000000000000000000000000000000000..4df34327b428d4b95651991112d52c38bc0dcce2
--- /dev/null
+++ b/lbmpy_tests/full_scenarios/schaefer_turek/scenario_schaefer_turek.py
@@ -0,0 +1,158 @@
+"""
+2D Benchmarks described in the paper
+Schäfer, M., Turek, S., Durst, F., Krause, E., & Rannacher, R. (1996). Benchmark computations of laminar flow around 
+a cylinder. In Flow simulation with high-performance computers II (pp. 547-566). Vieweg+ Teubner Verlag.
+
+- boundaries are not set correctly yet (halfway-bounce back is not considered)
+"""
+import numpy as np
+import warnings
+from lbmpy.boundaries.boundaryconditions import NoSlip
+from lbmpy.geometry import get_pipe_velocity_field
+from lbmpy.relaxationrates import relaxation_rate_from_lattice_viscosity
+from lbmpy.scenarios import create_channel
+
+
+def geometry_2d(dx):
+    """Geometry setup for the Schaefer Turek benchmark as described in the paper.
+    Returns the domain size in cells, a callback function that sets the obstacle and a dict with parameter information
+    """
+    cylinder_offset_bottom = 0.15
+    cylinder_offset_top = 0.16
+    cylinder_offset_inflow = 0.15
+    cylinder_diameter = 0.1
+    channel_length = 2.2
+
+    cylinder_midpoint = np.array([cylinder_offset_inflow + cylinder_diameter / 2,
+                                 cylinder_offset_bottom + cylinder_diameter / 2])
+
+    channel_height = cylinder_offset_bottom + cylinder_diameter + cylinder_offset_top
+
+    def to_lattice_units(x):
+        result = x / dx
+        if abs(round(result) - result) > 1e-10:
+            warnings.warn("dx does not divide on of the lengths. Geometry might be slightly inaccurate")
+        return round(result)
+
+    domain_size_l = [to_lattice_units(channel_length), to_lattice_units(channel_height)]
+    to_lattice_units(cylinder_diameter)
+    cylinder_midpoint_l = [i / dx for i in cylinder_midpoint]
+    cylinder_radius_l = cylinder_diameter / 2 / dx
+
+    def sphere_geometry_callback(x, y):
+        return (x - cylinder_midpoint_l[0]) ** 2 + (y - cylinder_midpoint_l[1]) ** 2 < cylinder_radius_l ** 2
+
+    parameter_info = {
+        'cylinder_diameter_l': cylinder_radius_l * 2,
+        'cylinder_midpoint_l': cylinder_midpoint_l,
+        'dx': dx,
+    }
+    return domain_size_l, sphere_geometry_callback, parameter_info
+
+
+def compute_delta_t(max_lattice_velocity, max_velocity, dx):
+    """Computes length of a time step given a physical and a lattice velocity"""
+    # latticeVelocity * dx / dt = velocity  -> dt = latticeVelocity / velocity * dx
+    return max_lattice_velocity / max_velocity * dx
+
+
+def evaluate_static_quantities(scenario):
+    """
+    Evaluates drag coefficient, lift coefficient, pressure drop over obstacle and the (approximate) recirculation length
+    given a Schaefer Turek scenario object
+    :return: a dictionary with the results
+    """
+    force_on_cylinder = scenario.boundary_handling.force_on_boundary(NoSlip("obstacle"))
+    pi = scenario.parameterInfo
+    drag_coefficient = force_on_cylinder[0] * 2 / (pi['u_bar_l'] ** 2 * pi['cylinder_diameter_l'])
+    lift_coefficient = force_on_cylinder[1] * 2 / (pi['u_bar_l'] ** 2 * pi['cylinder_diameter_l'])
+
+    obstacle_midpoint_height = int(round(pi['cylinder_midpoint_l'][1]))
+    density_slice = scenario.density[:, obstacle_midpoint_height]
+    last_cell_x_before_obstacle = np.argmax(density_slice.mask) - 1
+    obstacle_width = np.argmin(density_slice.mask[last_cell_x_before_obstacle + 1:])
+    first_cell_x_after_obstacle = obstacle_width + last_cell_x_before_obstacle + 1
+
+    pressures = [density_slice[x] / 3
+                 for x in [last_cell_x_before_obstacle, first_cell_x_after_obstacle]]
+    pressure_difference = pressures[0] - pressures[1]
+    pressure_difference *= pi['dx'] ** 2 / (pi['dt'] ** 2)
+
+    # Velocity in a line starting directly after the obstacle
+    # recirculation is (somewhat inaccurately) determined as the number of cells behind
+    # obstacle with x velocity smaller than zero
+    vel_slice = scenario.velocity[first_cell_x_after_obstacle:, obstacle_midpoint_height, 0]
+    recirculation_length = np.argmax(vel_slice > 0) * pi['dx']
+    return {
+        'c_D': drag_coefficient,
+        'c_L': lift_coefficient,
+        'DeltaP': pressure_difference,
+        'L_a': recirculation_length,
+    }
+
+
+def schaefer_turek_2d(cells_per_diameter, u_max=0.3, max_lattice_velocity=0.05, **kwargs):
+    """Creates a 2D Schaefer Turek Benchmark.
+
+    Args:
+        cells_per_diameter: how many lattice cells are used to resolve the obstacle diameter
+        u_max: called U_m in the paper: the maximum inflow velocity in physical units, for the first setup
+                  it is 0.3, for the second setup 1.5
+        max_lattice_velocity: maximum lattice velocity, the lower the more accurate is the simulation
+                              should not be larger than 0.1, if chosen too small the relaxation rate gets near 2 and
+                              simulation might also get unstable
+        kwargs: parameters forwarded to the lattice boltzmann method
+
+    Returns:
+        scenario object
+    """
+    dx = 0.1 / cells_per_diameter
+    viscosity = 1e-3
+
+    dt = compute_delta_t(max_lattice_velocity, u_max, dx)
+    lattice_viscosity = viscosity / dx / dx * dt
+    omega = relaxation_rate_from_lattice_viscosity(lattice_viscosity)
+    domain_size, geometry_callback, parameter_info = geometry_2d(dx)
+    cylinder_diameter_l = parameter_info['cylinder_diameter_l']
+    u_bar_l = 2 / 3 * max_lattice_velocity
+    re_lattice = u_bar_l * cylinder_diameter_l / lattice_viscosity
+    print("Schaefer-Turek 2D: U_m = %.2f m/s  cells=%s, dx=%f,  dt=%f,  omega=%f, Re=%.1f" %
+          (u_max, domain_size, dx, dt, omega, re_lattice))
+
+    initial_velocity = get_pipe_velocity_field(domain_size, max_lattice_velocity)
+    scenario = create_channel(domain_size=domain_size, u_max=max_lattice_velocity, kernel_params={'omega_0': omega},
+                              initial_velocity=initial_velocity, **kwargs)
+    scenario.boundary_handling.set_boundary(NoSlip('obstacle'), mask_callback=geometry_callback)
+    parameter_info['u_bar_l'] = u_bar_l
+    parameter_info['dt'] = dt
+    scenario.parameterInfo = parameter_info
+    return scenario
+
+
+def long_run(steady=True, **kwargs):
+    if steady:  # scenario 2D-1 in the paper
+        sc = schaefer_turek_2d(60, max_lattice_velocity=0.05, **kwargs)
+    else:  # Scenario 2D-2 (unsteady)
+        sc = schaefer_turek_2d(40, u_max=1.5, max_lattice_velocity=0.01)
+
+    for i in range(100):
+        sc.run(10000)
+        res = evaluate_static_quantities(sc)
+        print(res)
+    import lbmpy.plot2d as plt
+    plt.vector_field_magnitude(sc.velocity[:, :])
+    plt.show()
+
+
+def test_schaefer_turek():
+    opt = {'vectorization': {'instruction_set': 'avx', 'assume_aligned': True}, 'openmp': 2}
+    sc_2d_1 = schaefer_turek_2d(30, max_lattice_velocity=0.08, optimization=opt)
+    sc_2d_1.run(30000)
+    result = evaluate_static_quantities(sc_2d_1)
+    assert 5.5 < result['c_D'] < 5.8
+    assert 0.117 < result['DeltaP'] < 0.118
+
+
+if __name__ == '__main__':
+    long_run(entropic=True, method='trt-kbc-n1', compressible=True,
+             optimization={'target': 'gpu', 'gpuIndexingParams': {'blockSize': (16, 8, 2)}})
diff --git a/lbmpy_tests/full_scenarios/shear_wave/Equilibrium Construction - ReducedStencils.ipynb b/lbmpy_tests/full_scenarios/shear_wave/Equilibrium Construction - ReducedStencils.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..b45f0b9c6e34281ef73357bda642870c10e4ee0d
--- /dev/null
+++ b/lbmpy_tests/full_scenarios/shear_wave/Equilibrium Construction - ReducedStencils.ipynb	
@@ -0,0 +1,2620 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from lbmpy.methods.creationfunctions import createSRT\n",
+    "from lbmpy.methods.momentbasedsimplifications import *\n",
+    "from lbmpy.stencils import getStencil, visualizeStencil3DBySlicing\n",
+    "import sympy as sp\n",
+    "import numpy as np\n",
+    "\n",
+    "from sympy.abc import x, y, z\n",
+    "from functools import partial\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "sp.init_printing()\n",
+    "\n",
+    "%matplotlib inline\n",
+    "\n",
+    "def plotSympyFunction(f, bounds, **kwargs):\n",
+    "    xArr = np.linspace(bounds[0], bounds[1], 101)\n",
+    "    yArr = sp.lambdify(x, f)(xArr)\n",
+    "    plt.plot(xArr, yArr, **kwargs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "$$\n",
+    "\\newcommand{\\bTens}[2]{ \\pmb{#1}^{(#2)} }\n",
+    "\\newcommand{\\bTensS}[3]{ \\pmb{#1}^{(#2)}_{\\pmb{#3}} }\n",
+    "\\newcommand{\\bx}[0]{\\textbf{x}}\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Construction by cont. Maxwell Boltzmann Distribution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Vp67Cnq4IIeYDF0kpLTBRV9Eb8Ww8LYQ4FfhXLHE1S9wV8SO09SpCQLaU0qgx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\nNEMJu0KhUKQZ/w+2JZw+Ggzl+gAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8d3189da20>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "stencil = getStencil(\"D3Q19\")\n",
+    "visualizeStencil3DBySlicing(stencil)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "params = { 'compressible': False,\n",
+    "           'equilibriumAccuracyOrder': 2,\n",
+    "           'relaxationRate': sp.Symbol(\"omega\")\n",
+    "         }\n",
+    "sym = sp.Symbol(\"c_s2\")\n",
+    "val13 = sp.Rational(1,3)\n",
+    "old = createSRT(stencil,useContinuousMaxwellianEquilibrium=False, c_s_sq=val13, **params)\n",
+    "new = createSRT(stencil,useContinuousMaxwellianEquilibrium=True, c_s_sq=val13, **params)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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0GgaUR1hJx3wSG68pU0Iugm01I/t0vWFN2WXCkeFHpgRnMvWouUQNc3tB1FAO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\ngg==\n",
+      "text/latex": [
+       "$$\\left[\\begin{array}{ccccccccccccccccccc}\\left ( 0, \\quad 0, \\quad 0\\right ) & \\left ( 0, \\quad 1, \\quad 0\\right ) & \\left ( 0, \\quad -1, \\quad 0\\right ) & \\left ( -1, \\quad 0, \\quad 0\\right ) & \\left ( 1, \\quad 0, \\quad 0\\right ) & \\left ( 0, \\quad 0, \\quad 1\\right ) & \\left ( 0, \\quad 0, \\quad -1\\right ) & \\left ( -1, \\quad 1, \\quad 0\\right ) & \\left ( 1, \\quad 1, \\quad 0\\right ) & \\left ( -1, \\quad -1, \\quad 0\\right ) & \\left ( 1, \\quad -1, \\quad 0\\right ) & \\left ( 0, \\quad 1, \\quad 1\\right ) & \\left ( 0, \\quad -1, \\quad 1\\right ) & \\left ( -1, \\quad 0, \\quad 1\\right ) & \\left ( 1, \\quad 0, \\quad 1\\right ) & \\left ( 0, \\quad 1, \\quad -1\\right ) & \\left ( 0, \\quad -1, \\quad -1\\right ) & \\left ( -1, \\quad 0, \\quad -1\\right ) & \\left ( 1, \\quad 0, \\quad -1\\right )\\\\\\rho - \\frac{3 u_{0}^{2}}{2} - \\frac{3 u_{1}^{2}}{2} - \\frac{3 u_{2}^{2}}{2} & \\rho - \\frac{3 u_{0}^{2}}{2} + 3 u_{1}^{2} + 3 u_{1} - \\frac{3 u_{2}^{2}}{2} & \\rho - \\frac{3 u_{0}^{2}}{2} + 3 u_{1}^{2} - 3 u_{1} - \\frac{3 u_{2}^{2}}{2} & \\rho + 3 u_{0}^{2} - 3 u_{0} - \\frac{3 u_{1}^{2}}{2} - \\frac{3 u_{2}^{2}}{2} & \\rho + 3 u_{0}^{2} + 3 u_{0} - \\frac{3 u_{1}^{2}}{2} - \\frac{3 u_{2}^{2}}{2} & \\rho - \\frac{3 u_{0}^{2}}{2} - \\frac{3 u_{1}^{2}}{2} + 3 u_{2}^{2} + 3 u_{2} & \\rho - \\frac{3 u_{0}^{2}}{2} - \\frac{3 u_{1}^{2}}{2} + 3 u_{2}^{2} - 3 u_{2} & \\rho + 3 u_{0}^{2} - 9 u_{0} u_{1} - 3 u_{0} + 3 u_{1}^{2} + 3 u_{1} - \\frac{3 u_{2}^{2}}{2} & \\rho + 3 u_{0}^{2} + 9 u_{0} u_{1} + 3 u_{0} + 3 u_{1}^{2} + 3 u_{1} - \\frac{3 u_{2}^{2}}{2} & \\rho + 3 u_{0}^{2} + 9 u_{0} u_{1} - 3 u_{0} + 3 u_{1}^{2} - 3 u_{1} - \\frac{3 u_{2}^{2}}{2} & \\rho + 3 u_{0}^{2} - 9 u_{0} u_{1} + 3 u_{0} + 3 u_{1}^{2} - 3 u_{1} - \\frac{3 u_{2}^{2}}{2} & \\rho - \\frac{3 u_{0}^{2}}{2} + 3 u_{1}^{2} + 9 u_{1} u_{2} + 3 u_{1} + 3 u_{2}^{2} + 3 u_{2} & \\rho - \\frac{3 u_{0}^{2}}{2} + 3 u_{1}^{2} - 9 u_{1} u_{2} - 3 u_{1} + 3 u_{2}^{2} + 3 u_{2} & \\rho + 3 u_{0}^{2} - 9 u_{0} u_{2} - 3 u_{0} - \\frac{3 u_{1}^{2}}{2} + 3 u_{2}^{2} + 3 u_{2} & \\rho + 3 u_{0}^{2} + 9 u_{0} u_{2} + 3 u_{0} - \\frac{3 u_{1}^{2}}{2} + 3 u_{2}^{2} + 3 u_{2} & \\rho - \\frac{3 u_{0}^{2}}{2} + 3 u_{1}^{2} - 9 u_{1} u_{2} + 3 u_{1} + 3 u_{2}^{2} - 3 u_{2} & \\rho - \\frac{3 u_{0}^{2}}{2} + 3 u_{1}^{2} + 9 u_{1} u_{2} - 3 u_{1} + 3 u_{2}^{2} - 3 u_{2} & \\rho + 3 u_{0}^{2} + 9 u_{0} u_{2} - 3 u_{0} - \\frac{3 u_{1}^{2}}{2} + 3 u_{2}^{2} - 3 u_{2} & \\rho + 3 u_{0}^{2} - 9 u_{0} u_{2} + 3 u_{0} - \\frac{3 u_{1}^{2}}{2} + 3 u_{2}^{2} - 3 u_{2}\\\\\\rho - u_{0}^{2} - u_{1}^{2} - u_{2}^{2} & \\rho - 3 u_{0}^{2} + 3 u_{1}^{2} + 3 u_{1} - 3 u_{2}^{2} & \\rho - 3 u_{0}^{2} + 3 u_{1}^{2} - 3 u_{1} - 3 u_{2}^{2} & \\rho + 3 u_{0}^{2} - 3 u_{0} - 3 u_{1}^{2} - 3 u_{2}^{2} & \\rho + 3 u_{0}^{2} + 3 u_{0} - 3 u_{1}^{2} - 3 u_{2}^{2} & \\rho - 3 u_{0}^{2} - 3 u_{1}^{2} + 3 u_{2}^{2} + 3 u_{2} & \\rho - 3 u_{0}^{2} - 3 u_{1}^{2} + 3 u_{2}^{2} - 3 u_{2} & \\rho + 3 u_{0}^{2} - 9 u_{0} u_{1} - 3 u_{0} + 3 u_{1}^{2} + 3 u_{1} & \\rho + 3 u_{0}^{2} + 9 u_{0} u_{1} + 3 u_{0} + 3 u_{1}^{2} + 3 u_{1} & \\rho + 3 u_{0}^{2} + 9 u_{0} u_{1} - 3 u_{0} + 3 u_{1}^{2} - 3 u_{1} & \\rho + 3 u_{0}^{2} - 9 u_{0} u_{1} + 3 u_{0} + 3 u_{1}^{2} - 3 u_{1} & \\rho + 3 u_{1}^{2} + 9 u_{1} u_{2} + 3 u_{1} + 3 u_{2}^{2} + 3 u_{2} & \\rho + 3 u_{1}^{2} - 9 u_{1} u_{2} - 3 u_{1} + 3 u_{2}^{2} + 3 u_{2} & \\rho + 3 u_{0}^{2} - 9 u_{0} u_{2} - 3 u_{0} + 3 u_{2}^{2} + 3 u_{2} & \\rho + 3 u_{0}^{2} + 9 u_{0} u_{2} + 3 u_{0} + 3 u_{2}^{2} + 3 u_{2} & \\rho + 3 u_{1}^{2} - 9 u_{1} u_{2} + 3 u_{1} + 3 u_{2}^{2} - 3 u_{2} & \\rho + 3 u_{1}^{2} + 9 u_{1} u_{2} - 3 u_{1} + 3 u_{2}^{2} - 3 u_{2} & \\rho + 3 u_{0}^{2} + 9 u_{0} u_{2} - 3 u_{0} + 3 u_{2}^{2} - 3 u_{2} & \\rho + 3 u_{0}^{2} - 9 u_{0} u_{2} + 3 u_{0} + 3 u_{2}^{2} - 3 u_{2}\\\\- \\frac{u_{0}^{2}}{2} - \\frac{u_{1}^{2}}{2} - \\frac{u_{2}^{2}}{2} & \\frac{3 u_{0}^{2}}{2} + \\frac{3 u_{2}^{2}}{2} & \\frac{3 u_{0}^{2}}{2} + \\frac{3 u_{2}^{2}}{2} & \\frac{3 u_{1}^{2}}{2} + \\frac{3 u_{2}^{2}}{2} & \\frac{3 u_{1}^{2}}{2} + \\frac{3 u_{2}^{2}}{2} & \\frac{3 u_{0}^{2}}{2} + \\frac{3 u_{1}^{2}}{2} & \\frac{3 u_{0}^{2}}{2} + \\frac{3 u_{1}^{2}}{2} & - \\frac{3 u_{2}^{2}}{2} & - \\frac{3 u_{2}^{2}}{2} & - \\frac{3 u_{2}^{2}}{2} & - \\frac{3 u_{2}^{2}}{2} & - \\frac{3 u_{0}^{2}}{2} & - \\frac{3 u_{0}^{2}}{2} & - \\frac{3 u_{1}^{2}}{2} & - \\frac{3 u_{1}^{2}}{2} & - \\frac{3 u_{0}^{2}}{2} & - \\frac{3 u_{0}^{2}}{2} & - \\frac{3 u_{1}^{2}}{2} & - \\frac{3 u_{1}^{2}}{2}\\end{array}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡        (0, 0, 0)                     (0, 1, 0)                         (0, -\n",
+       "⎢                                                                             \n",
+       "⎢        2       2       2          2                      2          2       \n",
+       "⎢    3⋅u₀    3⋅u₁    3⋅u₂       3⋅u₀        2          3⋅u₂       3⋅u₀        \n",
+       "⎢ρ - ───── - ───── - ─────  ρ - ───── + 3⋅u₁  + 3⋅u₁ - ─────  ρ - ───── + 3⋅u₁\n",
+       "⎢      2       2       2          2                      2          2         \n",
+       "⎢                                                                             \n",
+       "⎢         2     2     2             2       2              2          2       \n",
+       "⎢   ρ - u₀  - u₁  - u₂      ρ - 3⋅u₀  + 3⋅u₁  + 3⋅u₁ - 3⋅u₂   ρ - 3⋅u₀  + 3⋅u₁\n",
+       "⎢                                                                             \n",
+       "⎢        2     2     2                   2       2                         2  \n",
+       "⎢      u₀    u₁    u₂                3⋅u₀    3⋅u₂                      3⋅u₀   \n",
+       "⎢    - ─── - ─── - ───               ───── + ─────                     ───── +\n",
+       "⎣       2     2     2                  2       2                         2    \n",
+       "\n",
+       "1, 0)                        (-1, 0, 0)                        (1, 0, 0)      \n",
+       "                                                                              \n",
+       "               2                         2       2                         2  \n",
+       "2          3⋅u₂           2          3⋅u₁    3⋅u₂           2          3⋅u₁   \n",
+       "  - 3⋅u₁ - ─────  ρ + 3⋅u₀  - 3⋅u₀ - ───── - ─────  ρ + 3⋅u₀  + 3⋅u₀ - ───── -\n",
+       "             2                         2       2                         2    \n",
+       "                                                                              \n",
+       "2              2          2              2       2          2              2  \n",
+       "  - 3⋅u₁ - 3⋅u₂   ρ + 3⋅u₀  - 3⋅u₀ - 3⋅u₁  - 3⋅u₂   ρ + 3⋅u₀  + 3⋅u₀ - 3⋅u₁  -\n",
+       "                                                                              \n",
+       "     2                         2       2                         2       2    \n",
+       " 3⋅u₂                      3⋅u₁    3⋅u₂                      3⋅u₁    3⋅u₂     \n",
+       " ─────                     ───── + ─────                     ───── + ─────    \n",
+       "   2                         2       2                         2       2      \n",
+       "\n",
+       "                   (0, 0, 1)                         (0, 0, -1)               \n",
+       "                                                                              \n",
+       "     2          2       2                         2       2                   \n",
+       " 3⋅u₂       3⋅u₀    3⋅u₁        2             3⋅u₀    3⋅u₁        2           \n",
+       " ─────  ρ - ───── - ───── + 3⋅u₂  + 3⋅u₂  ρ - ───── - ───── + 3⋅u₂  - 3⋅u₂  ρ \n",
+       "   2          2       2                         2       2                     \n",
+       "                                                                              \n",
+       "     2          2       2       2                 2       2       2           \n",
+       " 3⋅u₂   ρ - 3⋅u₀  - 3⋅u₁  + 3⋅u₂  + 3⋅u₂  ρ - 3⋅u₀  - 3⋅u₁  + 3⋅u₂  - 3⋅u₂    \n",
+       "                                                                              \n",
+       "                     2       2                         2       2              \n",
+       "                 3⋅u₀    3⋅u₁                      3⋅u₀    3⋅u₁               \n",
+       "                 ───── + ─────                     ───── + ─────              \n",
+       "                   2       2                         2       2                \n",
+       "\n",
+       "                 (-1, 1, 0)                                          (1, 1, 0)\n",
+       "                                                                              \n",
+       "                                              2                               \n",
+       "      2                        2          3â‹…uâ‚‚           2                    \n",
+       "+ 3⋅u₀  - 9⋅u₀⋅u₁ - 3⋅u₀ + 3⋅u₁  + 3⋅u₁ - ─────  ρ + 3⋅u₀  + 9⋅u₀⋅u₁ + 3⋅u₀ + \n",
+       "                                            2                                 \n",
+       "                                                                              \n",
+       "          2                        2                         2                \n",
+       "  ρ + 3⋅u₀  - 9⋅u₀⋅u₁ - 3⋅u₀ + 3⋅u₁  + 3⋅u₁          ρ + 3⋅u₀  + 9⋅u₀⋅u₁ + 3⋅u\n",
+       "                                                                              \n",
+       "                        2                                                  2  \n",
+       "                   -3â‹…uâ‚‚                                              -3â‹…uâ‚‚   \n",
+       "                   ───────                                            ─────── \n",
+       "                      2                                                  2    \n",
+       "\n",
+       "                                         (-1, -1, 0)                          \n",
+       "                                                                              \n",
+       "                   2                                                  2       \n",
+       "    2          3â‹…uâ‚‚           2                        2          3â‹…uâ‚‚        \n",
+       "3⋅u₁  + 3⋅u₁ - ─────  ρ + 3⋅u₀  + 9⋅u₀⋅u₁ - 3⋅u₀ + 3⋅u₁  - 3⋅u₁ - ─────  ρ + 3\n",
+       "                 2                                                  2         \n",
+       "                                                                              \n",
+       "        2                         2                        2                  \n",
+       "₀ + 3⋅u₁  + 3⋅u₁          ρ + 3⋅u₀  + 9⋅u₀⋅u₁ - 3⋅u₀ + 3⋅u₁  - 3⋅u₁          ρ\n",
+       "                                                                              \n",
+       "                                                2                             \n",
+       "                                           -3â‹…uâ‚‚                              \n",
+       "                                           ───────                            \n",
+       "                                              2                               \n",
+       "\n",
+       "              (1, -1, 0)                                          (0, 1, 1)   \n",
+       "                                                                              \n",
+       "                                           2          2                       \n",
+       "   2                        2          3â‹…uâ‚‚       3â‹…uâ‚€        2               \n",
+       "⋅u₀  - 9⋅u₀⋅u₁ + 3⋅u₀ + 3⋅u₁  - 3⋅u₁ - ─────  ρ - ───── + 3⋅u₁  + 9⋅u₁⋅u₂ + 3⋅\n",
+       "                                         2          2                         \n",
+       "                                                                              \n",
+       "       2                        2                         2                   \n",
+       " + 3⋅u₀  - 9⋅u₀⋅u₁ + 3⋅u₀ + 3⋅u₁  - 3⋅u₁          ρ + 3⋅u₁  + 9⋅u₁⋅u₂ + 3⋅u₁ +\n",
+       "                                                                              \n",
+       "                     2                                                  2     \n",
+       "                -3â‹…uâ‚‚                                              -3â‹…uâ‚€      \n",
+       "                ───────                                            ───────    \n",
+       "                   2                                                  2       \n",
+       "\n",
+       "                                      (0, -1, 1)                              \n",
+       "                                                                              \n",
+       "                           2                                                  \n",
+       "         2             3â‹…uâ‚€        2                        2                 \n",
+       "u₁ + 3⋅u₂  + 3⋅u₂  ρ - ───── + 3⋅u₁  - 9⋅u₁⋅u₂ - 3⋅u₁ + 3⋅u₂  + 3⋅u₂  ρ + 3⋅u₀\n",
+       "                         2                                                    \n",
+       "                                                                              \n",
+       "     2                         2                        2                     \n",
+       " 3⋅u₂  + 3⋅u₂          ρ + 3⋅u₁  - 9⋅u₁⋅u₂ - 3⋅u₁ + 3⋅u₂  + 3⋅u₂          ρ + \n",
+       "                                                                              \n",
+       "                                             2                                \n",
+       "                                        -3â‹…uâ‚€                                 \n",
+       "                                        ───────                               \n",
+       "                                           2                                  \n",
+       "\n",
+       "           (-1, 0, 1)                                          (1, 0, 1)      \n",
+       "                                                                              \n",
+       "                         2                                                  2 \n",
+       "2                    3⋅u₁        2                 2                    3⋅u₁  \n",
+       "  - 9⋅u₀⋅u₂ - 3⋅u₀ - ───── + 3⋅u₂  + 3⋅u₂  ρ + 3⋅u₀  + 9⋅u₀⋅u₂ + 3⋅u₀ - ───── \n",
+       "                       2                                                  2   \n",
+       "                                                                              \n",
+       "    2                        2                         2                      \n",
+       "3⋅u₀  - 9⋅u₀⋅u₂ - 3⋅u₀ + 3⋅u₂  + 3⋅u₂          ρ + 3⋅u₀  + 9⋅u₀⋅u₂ + 3⋅u₀ + 3⋅\n",
+       "                                                                              \n",
+       "                  2                                                  2        \n",
+       "             -3⋅u₁                                              -3⋅u₁         \n",
+       "             ───────                                            ───────       \n",
+       "                2                                                  2          \n",
+       "\n",
+       "                                   (0, 1, -1)                                 \n",
+       "                                                                              \n",
+       "                        2                                                  2  \n",
+       "      2             3â‹…uâ‚€        2                        2             3â‹…uâ‚€   \n",
+       "+ 3⋅u₂  + 3⋅u₂  ρ - ───── + 3⋅u₁  - 9⋅u₁⋅u₂ + 3⋅u₁ + 3⋅u₂  - 3⋅u₂  ρ - ───── +\n",
+       "                      2                                                  2    \n",
+       "                                                                              \n",
+       "  2                         2                        2                        \n",
+       "u₂  + 3⋅u₂          ρ + 3⋅u₁  - 9⋅u₁⋅u₂ + 3⋅u₁ + 3⋅u₂  - 3⋅u₂          ρ + 3⋅u\n",
+       "                                                                              \n",
+       "                                          2                                   \n",
+       "                                     -3â‹…uâ‚€                                    \n",
+       "                                     ───────                                  \n",
+       "                                        2                                     \n",
+       "\n",
+       "        (0, -1, -1)                                        (-1, 0, -1)        \n",
+       "                                                                              \n",
+       "                                                                         2    \n",
+       "     2                        2                 2                    3⋅u₁     \n",
+       " 3⋅u₁  + 9⋅u₁⋅u₂ - 3⋅u₁ + 3⋅u₂  - 3⋅u₂  ρ + 3⋅u₀  + 9⋅u₀⋅u₂ - 3⋅u₀ - ───── + 3\n",
+       "                                                                       2      \n",
+       "                                                                              \n",
+       " 2                        2                         2                        2\n",
+       "₁  + 9⋅u₁⋅u₂ - 3⋅u₁ + 3⋅u₂  - 3⋅u₂          ρ + 3⋅u₀  + 9⋅u₀⋅u₂ - 3⋅u₀ + 3⋅u₂ \n",
+       "                                                                              \n",
+       "               2                                                  2           \n",
+       "          -3⋅u₀                                              -3⋅u₁            \n",
+       "          ───────                                            ───────          \n",
+       "             2                                                  2             \n",
+       "\n",
+       "                                (1, 0, -1)                    ⎤\n",
+       "                                                              ⎥\n",
+       "                                              2               ⎥\n",
+       "   2                 2                    3⋅u₁        2       ⎥\n",
+       "⋅u₂  - 3⋅u₂  ρ + 3⋅u₀  - 9⋅u₀⋅u₂ + 3⋅u₀ - ───── + 3⋅u₂  - 3⋅u₂⎥\n",
+       "                                            2                 ⎥\n",
+       "                                                              ⎥\n",
+       "                         2                        2           ⎥\n",
+       " - 3⋅u₂          ρ + 3⋅u₀  - 9⋅u₀⋅u₂ + 3⋅u₀ + 3⋅u₂  - 3⋅u₂    ⎥\n",
+       "                                                              ⎥\n",
+       "                                       2                      ⎥\n",
+       "                                  -3⋅u₁                       ⎥\n",
+       "                                  ───────                     ⎥\n",
+       "                                     2                        ⎦"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights = old.weights\n",
+    "oldEq = [sp.expand(e.rhs / w ) for e, w in zip(old.getEquilibrium().mainEquations, weights)]\n",
+    "newEq = [sp.expand(e.rhs / w ) for e, w in zip(new.getEquilibrium().mainEquations, weights)]\n",
+    "diff = [sp.expand(a - b).collect(sp.Symbol(\"u_0\")) for a, b in zip(oldEq, newEq)]\n",
+    "sp.Matrix([stencil, oldEq, newEq, diff])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Direct Neighbors:\n",
+    "$$ \\rho w_i ( 1 - u_\\alpha u_\\alpha )$$\n",
+    "\n",
+    "Next Neighbors:\n",
+    "$$ \\rho w_i \\left( 1 + 3 u_\\alpha c_\\alpha - 3 u_\\alpha u_\\alpha + 6 (u_\\alpha c_\\alpha )^2 \\right)$$\n",
+    "\n",
+    "Diagonals:\n",
+    "$$ \\rho w_i \\left( 1 + 3 u_\\alpha c_\\alpha + 3 u_\\alpha^2 c_\\alpha \n",
+    "                  + \\frac{9}{2} (c_\\alpha u_\\alpha)^2 - \\frac{9}{2} u_\\alpha^2 c_\\alpha      \\right) = $$\n",
+    "                  \n",
+    "$$ \\rho w_i \\left( 1 + 3 u_\\alpha c_\\alpha - \\frac{3}{2} u_\\alpha^2 c_\\alpha^2\n",
+    "                    + \\frac{9}{2} (c_\\alpha u_\\alpha)^2       \\right) $$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "AssertionError",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-16-118770e16d0f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     19\u001b[0m \u001b[0mtest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtestFormula\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgetStencil\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"D3Q19\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m \u001b[0mdiff\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0msp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnewEq\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 21\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdiff\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mdiff\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mAssertionError\u001b[0m: "
+     ]
+    }
+   ],
+   "source": [
+    "def testFormula(stencil):\n",
+    "    result = []\n",
+    "    u = sp.symbols(\"u_:3\")\n",
+    "    ua_ua = sum(e**2 for e in u)\n",
+    "    \n",
+    "    for d in stencil:\n",
+    "        entry = 1 # sp.Symbol(\"rho\") * sp.Symbol(\"w_i\")\n",
+    "        ua_ca = sum(u_i * c_i for u_i, c_i in zip(u, d))\n",
+    "        ua2_ca = sum(u_i**2 * c_i**2 for u_i, c_i in zip(u, d))\n",
+    "        dSum = sum(abs(a) for a in d)\n",
+    "        if dSum == 0:\n",
+    "            entry *= 1 - ua_ua\n",
+    "        elif dSum == 1:\n",
+    "            entry *= (1 + 3 * ua_ca - 3 * ua_ua + 6 * ua_ca**2)\n",
+    "        elif dSum == 2:\n",
+    "            entry *= ( 1 + 3 * ua_ca - sp.Rational(3,2) * ua2_ca + sp.Rational(9,2) * ua_ca**2 )\n",
+    "        result.append(entry.expand())\n",
+    "    return result\n",
+    "test = testFormula(getStencil(\"D3Q19\"))\n",
+    "diff = sp.Matrix(test) - sp.Matrix(newEq)\n",
+    "assert (diff.T * diff)[0] == 0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from lbmpy.creationfunctions import createLatticeBoltzmannMethod"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "compressible=False\n",
+    "eao = 3\n",
+    "mOld = createLatticeBoltzmannMethod(method='srt', stencil='D3Q19', compressible=compressible, \n",
+    "                                    useContinuousMaxwellianEquilibrium=False, equilibriumAccuracyOrder=eao)\n",
+    "mNew = createLatticeBoltzmannMethod(method='srt', stencil='D3Q19', compressible=compressible, \n",
+    "                                    useContinuousMaxwellianEquilibrium=True, equilibriumAccuracyOrder=eao)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table border=\"1\" cellpadding=\"3\" cellspacing=\"0\"  style=\"border:1px solid black;border-collapse:collapse;\"><tr><td  style=\"background-color:#bbbbbb;\">Shared&nbspMoment</td><td  style=\"background-color:#bbbbbb;\">ref</td><td  style=\"background-color:#bbbbbb;\">other</td><td  style=\"background-color:#bbbbbb;\">difference</td></tr><tr><td>$x^{2}&nbspy^{2}$</td><td>$\\frac{\\rho}{9}&nbsp+&nbsp\\frac{u_{0}^{2}}{3}&nbsp+&nbsp\\frac{u_{1}^{2}}{3}&nbsp-&nbsp\\frac{u_{2}^{2}}{6}$</td><td>$\\frac{\\rho}{9}&nbsp+&nbsp\\frac{u_{0}^{2}}{3}&nbsp+&nbsp\\frac{u_{1}^{2}}{3}$</td><td>$-&nbsp\\frac{u_{2}^{2}}{6}$</td></tr><tr><td>$x^{2}&nbspy$</td><td>$u_{0}^{2}&nbspu_{1}&nbsp-&nbsp\\frac{u_{1}&nbspu_{2}^{2}}{2}&nbsp+&nbsp\\frac{u_{1}}{3}$</td><td>$u_{0}^{2}&nbspu_{1}&nbsp+&nbsp\\frac{u_{1}}{3}$</td><td>$-&nbsp\\frac{u_{1}&nbspu_{2}^{2}}{2}$</td></tr><tr><td>$y^{2}&nbspz$</td><td>$-&nbsp\\frac{u_{0}^{2}&nbspu_{2}}{2}&nbsp+&nbspu_{1}^{2}&nbspu_{2}&nbsp+&nbsp\\frac{u_{2}}{3}$</td><td>$u_{1}^{2}&nbspu_{2}&nbsp+&nbsp\\frac{u_{2}}{3}$</td><td>$-&nbsp\\frac{u_{0}^{2}&nbspu_{2}}{2}$</td></tr><tr><td>$y^{2}&nbspz^{2}$</td><td>$\\frac{\\rho}{9}&nbsp-&nbsp\\frac{u_{0}^{2}}{6}&nbsp+&nbsp\\frac{u_{1}^{2}}{3}&nbsp+&nbsp\\frac{u_{2}^{2}}{3}$</td><td>$\\frac{\\rho}{9}&nbsp+&nbsp\\frac{u_{1}^{2}}{3}&nbsp+&nbsp\\frac{u_{2}^{2}}{3}$</td><td>$-&nbsp\\frac{u_{0}^{2}}{6}$</td></tr><tr><td>$x&nbspz^{2}$</td><td>$-&nbsp\\frac{u_{0}&nbspu_{1}^{2}}{2}&nbsp+&nbspu_{0}&nbspu_{2}^{2}&nbsp+&nbsp\\frac{u_{0}}{3}$</td><td>$u_{0}&nbspu_{2}^{2}&nbsp+&nbsp\\frac{u_{0}}{3}$</td><td>$-&nbsp\\frac{u_{0}&nbspu_{1}^{2}}{2}$</td></tr><tr><td>$x^{2}&nbspz^{2}$</td><td>$\\frac{\\rho}{9}&nbsp+&nbsp\\frac{u_{0}^{2}}{3}&nbsp-&nbsp\\frac{u_{1}^{2}}{6}&nbsp+&nbsp\\frac{u_{2}^{2}}{3}$</td><td>$\\frac{\\rho}{9}&nbsp+&nbsp\\frac{u_{0}^{2}}{3}&nbsp+&nbsp\\frac{u_{2}^{2}}{3}$</td><td>$-&nbsp\\frac{u_{1}^{2}}{6}$</td></tr><tr><td>$x^{2}&nbspz$</td><td>$u_{0}^{2}&nbspu_{2}&nbsp-&nbsp\\frac{u_{1}^{2}&nbspu_{2}}{2}&nbsp+&nbsp\\frac{u_{2}}{3}$</td><td>$u_{0}^{2}&nbspu_{2}&nbsp+&nbsp\\frac{u_{2}}{3}$</td><td>$-&nbsp\\frac{u_{1}^{2}&nbspu_{2}}{2}$</td></tr><tr><td>$y&nbspz^{2}$</td><td>$-&nbsp\\frac{u_{0}^{2}&nbspu_{1}}{2}&nbsp+&nbspu_{1}&nbspu_{2}^{2}&nbsp+&nbsp\\frac{u_{1}}{3}$</td><td>$u_{1}&nbspu_{2}^{2}&nbsp+&nbsp\\frac{u_{1}}{3}$</td><td>$-&nbsp\\frac{u_{0}^{2}&nbspu_{1}}{2}$</td></tr><tr><td>$x&nbspy^{2}$</td><td>$u_{0}&nbspu_{1}^{2}&nbsp-&nbsp\\frac{u_{0}&nbspu_{2}^{2}}{2}&nbsp+&nbsp\\frac{u_{0}}{3}$</td><td>$u_{0}&nbspu_{1}^{2}&nbsp+&nbsp\\frac{u_{0}}{3}$</td><td>$-&nbsp\\frac{u_{0}&nbspu_{2}^{2}}{2}$</td></tr></table>"
+      ],
+      "text/plain": [
+       "<ipy_table.IpyTable at 0x7f8d31898080>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.methods.creationfunctions import compareMomentBasedLbMethods\n",
+    "compareMomentBasedLbMethods(mOld, mNew, True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from lbmpy.moments import *\n",
+    "from lbmpy.maxwellian_equilibrium import *\n",
+    "from lbmpy.stencils import getStencil"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/local/bauer/code/lbmpy/lbmpy/maxwellian_equilibrium.py:19: UserWarning: Weigths of discrete equilibrium are only valid if c_s^2 = 1/3\n",
+      "  warnings.warn(\"Weigths of discrete equilibrium are only valid if c_s^2 = 1/3\")\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYEAAAA1BAMAAABVW0rAAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAiUSZq1TvELvdZiIy\nds1Wk1T5AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAHiElEQVRoBdWZbahURRjHn7N7d8++3l25X8K4\n3Y1AkKK7vlAa6t0Sgyy7G/mSvXBvahiKuaAgErYLFhp9aFEKrMwVA0tQFwKhoNzIoE/eNfObl7sf\nDDFquQm+oOb2zJlz5sy5M7MzhQnOhz1znvk9z3+e8zJnZhbAtFjzHtehBkjfzpIuih4x0JGJ3A/P\ny8y8TY9Y9Z4W7yGpGyB6HUlcgE9hrC5t8I16JF5P3fR5ac0AEXWsnDRW0LgHTuowPRLPJS8Hwwpn\nBoirs9X37fOr3Woj2kcY9EjkWjcJp80AcXRCLS+UVfBq3Y/7uzeTVj0Sb2qjGCBU55gXaqX+2hLU\nynsOyqMBYnC/9YirE8vSnthrlD0KNBwKnElP9EhCfxkMEFfHfoP2IqYPSsBQNtSgDspfA+RBeETp\n7jboEaazkrro3z6HO73ipZJGXI+kfluxSxPEAGE6cfoY7aUhQwufk8Qm1h0LIbkeNnc6knY0GSAP\n/dqwzzbhRCna6UzKo+gRiU7E+bgk3E9MH8yQxCbW/EpIK3SJhx6x8qHRcGQUJiQCrskAkek4Vz9e\ncYIkqrIvFrE+XFsEMQq5coGDAfIVJC9/G27B7oBj4ESPSHWOkwd7LOeEitZgsBgISk6IdRVsgmgT\n0v1ZoXkKAqelBGyA0JUShtiEN2wn0RQLh5w5IzajheuKr1NuYstjlB8swURdcHWsoWsw1oCDsFxo\nJgYO+fEZKYH+6ZvIpW6BatrGIYlspCALI9XpbSG6juLzAS6Jjo41XCVP8B7ISC8fh8BqMQJa0L+3\nCvPJy6SatvFIDqQTD6kOXhlI3aCqewEvkVAca6wAuxPbbkG0KLSjwUdKigzieXIP38WX6bBq2sYh\n5Qa4H6qgmlQnib0nWWCxr8P2mlPjf6g1XAmttXBWHBcBz9FBQJFBuWJ/AjAPZuSzAPJpG4fgHB5p\noXBd4XXwCYqNOnDk5vgCwQuo1X7y3KnzqWsgnXFxCB+ZjzXy3dkGwNb+V5fhQRoEOGSsJJ0fKnTe\nx1e84ojhWCcpnBXvAY4mYuEQVQaLeC/5tI1D8B7gmCUUhc4AQDnvwNLe8X22b0EmJ8TFK8CnJX+T\n+Q4ppm0cgu+BbBGk0DmegzHag5MNSe+AtyrGIh6RvwdJfoTgp20RljyPxPmx6DXWK4UOdn+k6EAz\nGcpXeOtZ+feAR8CdK/IhcN5U9c8D0zY/Ax5J57nvgZ+BQgcfoeMNP37XmjVLu9vy9YFlXUPgM8fP\n7PwMAl59fSV27mfATFjhdDIF2YeYh//PuiIDXlKeAUdkKjBQ587vbvVOZBBtwZB/y+5u//Hj1tQq\nau9BtArDNEqHlEms25f2Yfm8gdWMYwz+EOQdQuz7A2sQbKRnaOaCqBCr3b70VrtdQFql80C7/XG7\nfQEJJQLxUS8Dgt3tcifuAWZwjz9F8eq/eZNVqxP/3hlsKnOI8h7EWETle+Ah+CZPNBiuqahWJ5yb\nwaYyhygz8HdPlBl4CE7rcGJhWFSrE85d3FTmGmmVQ1QZ2ANsfFRlwJBMHkZyNPKWac8Kao7BHu+j\niGp1ArDjzGzqq968liHBDJgOpMuKDCRIOevN7OwNcKIupBBZj2tEgCVug2x1QjZd89BTdBHv7vKh\nVIjNBIM6P/kZvM3iKBCc2eFtIKVnFHpojfngomQurlhfBvjetYmrE3vxcAkiNUi2XGS/e/QPBsgU\nnayfAQujQnBiGm85VKYF1iTjvUoaM7gPYLt7LludTJTAqoBdpYglXAW065GATqIuyQAUCE6KwrTf\n5Qqk+Xk87RBxG9wF0+mZdHWC3QtdL1k1ihyih+CvHgno7ABVBqwrPoJTigR2EguOq5a4NCKRezoH\na/jnwfh54FcnjhP5we7B8A2SY/94g20qs2YzJKDz4pyhJwL+zokCeRN3W644AD5CvTcEP+IGA7dL\nkPwI2oHVCUNJBlbnIsA3xd4W21RmzaSiRwI6ACcx5tQiR5J/I7eOsn/CCzQX3pW4RZ46sAaiWVgS\nWJ0winRv+cyrOXgdByT5/rYeCehA4kNv8GMquCvEd4Uhzl7REMUS4z/I34MvIH21NCS5KtQPu5co\nwMT6MLld8qJHSPc0OnIkVkXJwZyr2yP2gbhtxM3hIj5uioLdi9bxWXR3bWSUHjHQkSPOzi9u+NHS\nWxDk0c2exJf58F9Ck2fA7pWxvhQ/jqqiRwx05AiG9gajxEbZX/Zu4rE6vuQReQfpBYYPMjWA4n9F\nDHTkCH2J1xLd9EX7d1GfuD1agqMwF+wFOKJKuogZhC5CohkuwJYG9J8Tg5CxSIMY6EgR+i+U+z98\n35ycIB5++vZSSC3GmZ01/SjA7FRFQOZuvlCDU7NwZjftSBPCuZ8FAvSIgY4c6c07cu5BlJ5q2b2K\nPHXdSuy9bd2aSZsBotcBF3H/y+e3/Lrqn+o0urbj53FYHJGnuBggeh2gCPsvf/UUEcVppN7TVDR5\n5ldAt2kHesRAx0Vi9CHCFUDB60HXY7wRbnQFAD6DBRrCADHQcZEvmZj2wjlk4sgvzENROXI0p2hh\nZj1ioEORUItFDedY9V6qbHUGln8AkntCd9Y9SY8AAAAASUVORK5CYII=\n",
+      "text/latex": [
+       "$$\\left ( \\frac{\\rho}{9} - \\frac{\\rho u_{0}^{2}}{18 c_{s}^{2}} - \\frac{\\rho u_{1}^{2}}{18 c_{s}^{2}} - \\frac{\\rho u_{2}^{2}}{18 c_{s}^{2}} + \\frac{\\rho u_{0}^{2}}{18 c_{s}^{4}} + \\frac{\\rho u_{1}^{2}}{18 c_{s}^{4}}\\right )$$"
+      ],
+      "text/plain": [
+       "⎛        2        2        2        2        2  ⎞\n",
+       "⎜ρ   ρ⋅u₀     ρ⋅u₁     ρ⋅u₂     ρ⋅u₀     ρ⋅u₁   ⎟\n",
+       "⎜─ - ────── - ────── - ────── + ────── + ──────,⎟\n",
+       "⎜9        2        2        2        4        4 ⎟\n",
+       "⎝    18⋅cₛ    18⋅cₛ    18⋅cₛ    18⋅cₛ    18⋅cₛ  ⎠"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stencil = getStencil(\"D3Q19\")\n",
+    "getMomentsOfDiscreteMaxwellianEquilibrium(stencil, [(2,2,0)], compressible=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQIAAAAcBAMAAAB4yqw8AAAAMFBMVEX///8AAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAu90iRJl2qzKJ72ZU\nEM0DZc8xAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAESUlEQVRIDb1XS4gcVRQ907+p/mU6grhRaMb4\nXzgIQdBFN640m+kZSDSLSG8STIikcRF0o51FCGSRaZAeEEFmoQHBT4soxCC0ih9CxEZRcRHSZKEb\nbZQomU0Y733vvndvzdR63qLeqXPuO3Xq1qvqGSBrNDLI8sqRwA7vnASos9ENVB0wdKaDqa3dNicB\nvo5XBZaX5qeB1Vl1GKg6DJ1yuGNxKVYlbQ9/y0pwL9akMreU3IxrIlAdBkaZgNLOoURUYfEhNE3N\nGcEvZiXYh1bb67l2/l+zSqDqMNDWKe0cCj0WH08l+MvXJ99nJQB+mAS/zMdkdAvDGp7TDm8ylUpQ\n7DJFO6aeneB+L9Mx143QANVhoCkwNDvk+I5SCVpyjx9nJyh3otkwIgOMbqApgKHZocSGqQTiW+9m\nJ/gkmlU1S+QA1S00BYZ2Dvm/tyd4z1fXDh78b+ThN2Z9YVDoy+kzeNqjWlcYmoyu0BrYCu/wCC2z\nPUji088HZA0uXP1i4q+X/Hn1Ho9sAtWh0BoYWhxWtiWobnhb4KNbYw+twYdbW6JXtra4fzRsAtWh\n0BoYWhxOkIXvQeHQy4SLUzpg/VifJz+igbD1o108IZ3gipggrPrlEPLvy2KexEDplMMyWfkEQxyg\n6rkGHR4b75nSJCMkCGyxtoFTQaQ5JAg6OldQkv64MjFQOuWw1pcE1ab73O3p0aJ3MT92a90hJAjs\nk9SnvSrHBEHPj573NxJqvIGhUw6ttiSojLA8pg9Eh55E2INk8dZs9vBs9gehyE4qXVwEjh8nEuXZ\n7MYHsxnljnqdVCrBBdbVQOjS+gDikEy5oDWWBPQ4Ti0B3INKg5U4pAfKLk+STVQHNSrlIU9B9cJt\nUGvPvuTluA88fQnfAs4hebbJFbEHq8ANOucE1wesxCEJlF3lx5xrQ1olCVQvNt0++TI4iIGn92Fh\nAueAWpMr+MfW7cT7QDcGzDeAhREwZtEPMVD2LnrMn1/vI3y8uq5O9bke9lYn2J7A0dc2URnDOUiC\n8C7U/8GPdGGUNuiJ9vBzH+snnXFsorIrONAZUHT+mtGQHqhebBTeKWNHAkfTHxW5EZyDJPiMLLgH\ntZvHnmM7eljAG5e7KLbP8DkN6YGyv65/d7q/Ngk/cpJA9forJ8+9sDOBo+mbS7+IzkEShG8ivWF+\nvC3z3N3XBIUEfKos9eCiLwgJ0vrOBK6aesDviRt+H/xOmHsQ6cMiJ6/xtuDxk5/cUVnaB/I3Up22\nUhiqmwTWoL6JhbZUuwTuJ5gTtPpCn5f5K5wWZCdlc/FdyNZNAltAf7zRu+CHS1Dt0QkneCqUzY89\nehBuXwRaZmVLnfA9sCWqA1esEPFR/h74UdugOdenAyeIoz718PKn7cgpMOxwGO5FZRh9/6NZTUT5\n8BGpz6/e6gKX+CyVAF9Lwe5M+YZPsGj+X6i1d+fa/ipFamRh8YHdvGT2tf4HlkVccLJf3ecAAAAA\nSUVORK5CYII=\n",
+      "text/latex": [
+       "$$\\left [ \\rho \\left(c_{s}^{4} + c_{s}^{2} u_{0}^{2} + c_{s}^{2} u_{1}^{2} + u_{0}^{2} u_{1}^{2}\\right)\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡  ⎛  4     2   2     2   2     2   2⎞⎤\n",
+       "⎣ρ⋅⎝cₛ  + cₛ ⋅u₀  + cₛ ⋅u₁  + u₀ ⋅u₁ ⎠⎦"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "getMomentsOfContinuousMaxwellianEquilibrium([(2,2,0)],3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Equilibrium Construction with Hermite Polynomials\n",
+    "\n",
+    "\n",
+    "##  What are Hermite polynomials? - Introduction in 1D\n",
+    "\n",
+    "To get startet we look at Hermite polynomials in 1D first. The n'th hermite polynomial is defined as\n",
+    "\n",
+    "$$ H^{(n)} = (-1)^n \\frac{1}{W(x)} \\frac{d^n}{dx^n} W(x)  $$\n",
+    "with a weight function $W$, that not coincidentally looks very similar to the Maxwellian distribution.\n",
+    "$$ W(x) = \\frac{1}{\\sqrt{2\\pi}} e ^{-\\frac{x^2}{2}}$$\n",
+    "\n",
+    "Lets compute the first few Hermite polynomials using this definition. For this the derivative of the weight function is helpful : $\\frac{d}{dx} W(x) = -x W(x)$ i.e. differentiating the weight function yields\n",
+    "a factor of $-x$\n",
+    "\n",
+    "$$ H^{(0)} = (-1)^0 \\frac{1}{W(x)} \\frac{d^0}{dx^0} W(x) =  \\frac{1}{W(x)} W(x)= 1 $$\n",
+    "$$ H^{(1)} = (-1)^1 \\frac{1}{W(x)} \\frac{d}{dx} W(x)  = -\\frac{1}{W(x)} (-x W(x)) = x$$\n",
+    "$$ H^{(2)} = (-1)^2 \\frac{1}{W(x)} \\frac{d}{dx} (-x W(x) ) = x^2 - 1 $$\n",
+    "\n",
+    "This get tedious really quick, so we implement this definition in *sympy*:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAKIAAACWCAMAAABqx6OSAAAANlBMVEX///8AAAAAAAAAAAAAAAAA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\nRU5ErkJggg==\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}1\\\\x\\\\x^{2} - 1\\\\x^{3} - 3 x\\\\x^{4} - 6 x^{2} + 3\\\\x^{5} - 10 x^{3} + 15 x\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡        1        ⎤\n",
+       "⎢                 ⎥\n",
+       "⎢        x        ⎥\n",
+       "⎢                 ⎥\n",
+       "⎢      2          ⎥\n",
+       "⎢     x  - 1      ⎥\n",
+       "⎢                 ⎥\n",
+       "⎢     3           ⎥\n",
+       "⎢    x  - 3⋅x     ⎥\n",
+       "⎢                 ⎥\n",
+       "⎢   4      2      ⎥\n",
+       "⎢  x  - 6⋅x  + 3  ⎥\n",
+       "⎢                 ⎥\n",
+       "⎢ 5       3       ⎥\n",
+       "⎣x  - 10⋅x  + 15⋅x⎦"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hermiteWeightFunction1D = sp.exp(- x*x / 2) / sp.sqrt(2 * sp.pi)\n",
+    "\n",
+    "def hermite1D(n):\n",
+    "    if n == 0: return 1\n",
+    "    W = hermiteWeightFunction1D\n",
+    "    result = (-1)**n * sp.diff(W, *[x] * n) / W\n",
+    "    return result.expand()\n",
+    "\n",
+    "# Print the first 6 Hermite polynomials\n",
+    "sp.Matrix([hermite1D(i) for i in range(6)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from lbmpy.cumulants import cumulantAsFunctionOfRawMoments\n",
+    "\n",
+    "#sp.integrate(hermiteWeightFunction1D * x**2, (x, -sp.oo, sp.oo))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Hermite polynomials have an interesting property: they form an ortogonal basis for the space of polynomials with respect to the weighted scalar product\n",
+    "\n",
+    "$$ <f, g>_W = \\int_{R} f(x) g(x) \\; W(x) \\; dx .$$\n",
+    "\n",
+    "The orthogonality property \n",
+    "$$ <H^{(n)}, H^{(m)}>_W  = \\delta_{nm} \\, n! $$\n",
+    "is automatically fulfilled when the polynomials are constructed according to above rule, but can also be used as defining property of the Hermite polynomials.\n",
+    "\n",
+    "Note that Hermite polynomials, when defined as above, are not orthonormal. The scalar product of a Hermite polynomial with itself is not equal to one, but to the factorial of its order.\n",
+    "\n",
+    "Since Hermite polynomials form a basis, every element of the function space can be expressed as a linear combination of Hermite polynomials. This is analogous to a Taylor or Fourier expansion, where in a Taylor expansion the monomials ($1, x, x^2, x^3, ...$) are used as basis elements and in a Fourier expansion the complex exponentials. We will see that Hermite polynomials are particularly well suited to expand equilibrium distribution functions compared to other bases.\n",
+    "\n",
+    "The expanded form of a function $f$ with expansion coefficients $b_i$ is\n",
+    "$$ f(x) = \\sum_{n=0}^\\infty b_n H^{(n)} $$\n",
+    "\n",
+    "Multiplying both sides such that we can reformulate everything as scalar products gives\n",
+    "$$ \\int f(x) H^{(m)} W(x) \\; dx =  \\sum_{n=0}^\\infty \\int b_n H^{(n)} H^{(m)} W(x) \\; dx  \\; \\Rightarrow \\;\n",
+    " \\left<f, H^{(m)} \\right>_W  =  \\sum_{n=0}^\\infty b_n \\underbrace{ \\left< H^{(n)}, H^{(m)} \\right>_W }_{\\delta_{nm} n!}   $$\n",
+    "\n",
+    "The coefficients can then be determined with\n",
+    "$$ b_n = \\frac{1}{n!} \\left<f, H^{(n)} \\right>_W $$\n",
+    "\n",
+    "and the Hermite expansion for an arbitrary function $f$ reads\n",
+    "$$ f(x) = \\sum_{n=0}^\\infty \\frac{1}{n!} \\left<f, H^{(n)}\\right>_W \\, H^{(n)} $$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Adapted expansion\n",
+    "\n",
+    "In the lattice Boltzmann literature a slightly different expansion is used. There the weight function and normalization factor is moved into the expansion, such that the coefficients are simply the integral over the product of basis function with $f$.\n",
+    "\n",
+    "With the expansion formula:\n",
+    "\n",
+    "$$ f(x) = W(x) \\sum_{n=0}^\\infty \\frac{1}{n!} a_n H^{(n)} (x) $$\n",
+    "\n",
+    "the coefficients simplify to\n",
+    "\n",
+    "$$ a_n = \\int H^{(n)} f \\; dx $$\n",
+    "\n",
+    "Since $H^{(n)}$ is a polynomial (i.e. a sum of monomials), the $a_n$ are a linear combination of moments of $f$."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Testing expansion\n",
+    "\n",
+    "To illustrate the expansion we implemented above formulas for coefficient calculation and for the expansion itself."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def hermiteCoefficient(f, n):\n",
+    "    return sp.integrate( hermite1D(n) * f, (x,-sp.oo, sp.oo) )\n",
+    "\n",
+    "def hermiteApproximation(f, N):\n",
+    "    W = hermiteWeightFunction1D\n",
+    "    return W * sum(hermiteCoefficient(f, n) / sp.factorial(n) * hermite1D(n)\n",
+    "                   for n in range(N))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To compute expansion coefficients the integral has to be evaluated from $-\\infty$ to $\\infty$. Thus only functions where this integral has a definite value can be approximated.\n",
+    "\n",
+    "For demonstration, lets approximate the hat function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQwAAABYCAMAAAA3Ojn0AAAAPFBMVEX///8AAAAAAAAAAAAAAAAA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\njQAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$$\\begin{cases} x + 1 & \\text{for}\\: x > -1 \\wedge x < 0 \\\\- x + 1 & \\text{for}\\: x \\geq 0 \\wedge x < 1 \\\\0 & \\text{otherwise} \\end{cases}$$"
+      ],
+      "text/plain": [
+       "⎧x + 1   for x > -1 ∧ x < 0\n",
+       "⎪                          \n",
+       "⎨-x + 1  for x ≥ 0 ∧ x < 1 \n",
+       "⎪                          \n",
+       "⎩  0         otherwise     "
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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rkt/jSIAp3CVrRKIxCguMb67JzZIwr+rDNfQ72BRVmZiMncJdskJPXz+bW4/mdEmYVwNl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\nIpKDFO4iIjno/wH0uboq24IYjQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8d352deb38>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "hat = sp.Piecewise((x+1, sp.And(x < 0 , x > -1) ), \n",
+    "                   (-x+1, sp.And(x >= 0 , x < 1) ), \n",
+    "                   (0, True))\n",
+    "plotSympyFunction(hat, (-2, 2))\n",
+    "hat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "646903f2fd074b9384204011c15dad3d"
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from ipywidgets import interact, IntSlider, FloatSlider\n",
+    "from IPython.display import display\n",
+    "\n",
+    "def approximateHat(n):\n",
+    "    approximation = hermiteApproximation(hat, n)\n",
+    "    display(approximation)\n",
+    "    plotSympyFunction(hat, (-2, 2), label='original')\n",
+    "    plotSympyFunction(approximation, (-2, 2), label='approx. n=%d' % (n,))\n",
+    "    plt.legend()\n",
+    "    plt.show()\n",
+    "    \n",
+    "interact(approximateHat, n=IntSlider(min=1,max=16,step=1,value=4));"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "One can see that indeed the function is approximated, however not particularly well. \n",
+    "Lets try another example with a Gaussian, a function the Hermite expansion was designed for"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "147bddacf1554ee4b60e6c5d6ca61d7d"
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def approximateGaussian(variance=2, mean=0, n=4):\n",
+    "    gaussian = sp.exp(-(x-mean)**2 / variance)\n",
+    "    approximation = hermiteApproximation(gaussian, n)\n",
+    "    #display(approximation)\n",
+    "    plotSympyFunction(gaussian, (-5, 5), label='original')\n",
+    "    plotSympyFunction(approximation, (-5, 5), label='approx')\n",
+    "    plt.legend()\n",
+    "    plt.show()\n",
+    "\n",
+    "interact(approximateGaussian, variance=FloatSlider(min=1, max=3, step=0.25),\n",
+    "                              mean = FloatSlider(min=-1, max=1, step=0.2),\n",
+    "                              n=IntSlider(min=1,max=16,step=1,value=4));"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Important property of Hermite expansion: Moment conservation\n",
+    "\n",
+    "The moments of an order $N$ Hermite approximation has the same first $N$ moments as the original function. \n",
+    "The approximation conserves the first moments.\n",
+    "\n",
+    "For any polynomial $P(x)$ with a degree not greater than $N$ holds:\n",
+    "$$ \\int P(x) W \\sum_{n=0}^{N} \\frac{1}{n!} \\left( \\int H^{(n)} f \\, dx \\right) H^{(n)} \\, dx = \n",
+    "   \\int P(x) \\, f(x) \\, dx$$\n",
+    "On the left hand side is the moment of the Hermite expansion, which is equal to the moment of approximated function $f$.\n",
+    "\n",
+    "Proof:\n",
+    "\n",
+    "The polynomial can be represented in the Hermite basis as $P(x) = \\sum_k c_k H^{(k)}(x)$\n",
+    "Inserting this in the left hand side gives\n",
+    "$$ \\int W \\sum_{n=0}^{N} \\frac{1}{n!} \\left( \\int H^{(n)} f \\, dx \\right) H^{(n)} \\sum_k c_k H^{(k)} \\, dx $$\n",
+    "After regrouping:\n",
+    "\n",
+    "$$ \\sum_{n=0}^{N} \\sum_k c_k \\left( \\int H^{(n)} f \\, dx \\right) \\frac{1}{n!} \\int   W H^{(n)}   H^{(k)} \\, dx $$\n",
+    "\n",
+    "$$ \\sum_{n=0}^{N} \\sum_k c_k \\left( \\int H^{(n)} f \\, dx \\right) \\delta_{kn} $$\n",
+    "\n",
+    "$$  \\int f \\sum_{n=0}^{N} c_n H^{(n)}  \\, dx = \\int f \\; P \\, dx  $$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "## Multidimensional Hermite polynomials\n",
+    "\n",
+    "The weight function for $D$ dimensions is:\n",
+    "$$ \\omega(\\bx) = \\frac{1}{(2\\pi)^{D/2} } e ^{-\\frac{\\bx^2}{2}}$$\n",
+    "\n",
+    "$$  \\bTens{H}{n}(\\bx) = (-1)^n \\frac{1}{\\omega(\\bx)} \\bTens{\\nabla}{n} \\; \\omega(\\bx)  $$\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Main points\n",
+    "\n",
+    "- Boltzmann equation is projected onto hermite subspace\n",
+    "- knowing velocities at stencil = knowing exact expansion coefficients up to order 2\n",
+    "- also the continuous Maxwellian is projected onto Hermite subspace (why?) in paper: \"because feq has hermite coefficients up to arbitrary order, and thus the conservation of rho and u don't hold exactly\"\n",
+    "- moments up to third order of projected and original Maxwellian agree"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "# Construction with Hermite Expansion\n",
+    "\n",
+    "According to \n",
+    "\n",
+    "*Kinetic theory representation of hydrodynamics:\n",
+    "a way beyond the Navier–Stokes equation, Shan, Yuan, Chen 2005*\n",
+    "[link](https://www.cambridge.org/core/services/aop-cambridge-core/content/view/57B640BEE52716398F6C015BC66D189C/S0022112005008153a.pdf/kinetic_theory_representation_of_hydrodynamics_a_way_beyond_the_navierstokes_equation.pdf)\n",
+    "\n",
+    "## Hermite Polynomials\n",
+    "\n",
+    "A popular way to construct the discrete lattice Boltzmann equilibrium, is by expanding the Maxwell-Boltzmann distribution in a series of Hermite Polynomials. Hermite Polynomials form an orthogonal polynomial basis for the space of square integrable functions w.r.t to the following weighted scalar product:\n",
+    "\n",
+    "$$ \\int \\omega(\\xi) H^{(n)} H^{(k)} \\; d\\xi = \\delta_{nk} n! $$\n",
+    "\n",
+    "with the weight function.\n",
+    "\n",
+    "$$ \\omega(\\xi) = \\frac{1}{\\sqrt{2\\pi}} e ^{-\\frac{\\xi^2}{2}}$$\n",
+    "\n",
+    "They can be constructed using the weight function:\n",
+    "\n",
+    "$$ H^{(n)} = (-1)^n \\frac{1}{\\omega(\\xi)} \\frac{d^n}{d\\xi^n} \\omega(\\xi)  $$\n",
+    "\n",
+    "In the next cell the hermite polynomials are defined in *sympy* and a few examples are calculated:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def weightFunction(x):\n",
+    "    if hasattr(x, \"__len__\"):\n",
+    "        dim = len(x)\n",
+    "        xSq = sum(v**2 for v in x)\n",
+    "    else:\n",
+    "        dim = 1\n",
+    "        xSq = x**2\n",
+    "    \n",
+    "    return sp.exp(-xSq / 2) / ( (2 * sp.pi) ** (sp.Rational(dim,2)) )\n",
+    "\n",
+    "def hermite(index, variables):\n",
+    "    \"\"\"Multidimensional Hermite polynomial.\"\"\"\n",
+    "    order = len(index)\n",
+    "    if order==0 : return sp.Rational(1,1)\n",
+    "    w = weightFunction(variables)\n",
+    "    diffArgs = [variables[i] for i in index]\n",
+    "    result = (-1) ** order / w * sp.diff(w, *diffArgs)\n",
+    "    return result.expand()\n",
+    "\n",
+    "def hermite1D(order, var):\n",
+    "    return hermite([0]*order, [var])\n",
+    "\n",
+    "def weightedScalarProd(f1, f2, w, x):\n",
+    "    return sp.integrate(f1 * f2 * w, (x, -sp.oo, sp.oo))\n",
+    "\n",
+    "def scalarProd(f1, f2):\n",
+    "    return weightedScalarProd(f1, f2, weightFunction(x), x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAADYAAAAYBAMAAABDzROoAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAEHaZIu+JVM27RDKr\nZt2dj8xZAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVQoFWNgAAM2S0MIAwuZwnACiyhE6AnD\nfgdckq8Y/BfgkmNgqBfALfcItxSbAW65y+hS7IEwEa4Erg0wNpiWsfkI4+8or0RzCxNcLv7/f5gy\nKA2SY1RWYHBF0wOSBsmxsQcw6KPpgcm5MzcwzMQhJ8CqwPAJJifxDgS6YfoY1gtw/4bJIdFgd1ow\nMAUgicGYYLk5DJwHYAJINFjOkmH9BSQxGBMsJ5Nk7wATQNDMR3+cBfEsEEKoLJ4Gxl+oIgge3wVO\nBQQPlcWlZI0qgOABAEK+LUb2w94IAAAAAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$y^{2} - 1$$"
+      ],
+      "text/plain": [
+       " 2    \n",
+       "y  - 1"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hermite((1,1), sp.symbols(\"x y\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Examples:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAE4AAAAWBAMAAACcWbe0AAAAMFBMVEX///8AAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAZqvNmRDdRHYyiVS7\nIu/EmopNAAAACXBIWXMAAA7EAAAOxAGVKw4bAAABPElEQVQoFX2QsUvDYBDFH5rGJpGmOHbS7opo\nV6kIUnAKRTqLg67iXDCCzgZcHQqCuFldXPsfpJP/gXux1lqt6N1l+XpJfNDL3Xu/fvlygKE+95Fh\nZLcuivcdPGeHhruKCp5gyamGrVung2P4QWFZB2qeiwoTlLrYUr4ebTg/sMs414GaX+CMYId0xWwt\n/dZAv6DN55VCtLMxYEjBB3AKup9/gusU572ytfAJOO/ADeR7iVdq7ozYcSdA8RtoARd8uYrCKBVu\nfgAsUmcHcPd2gUYO5/cA/4D+1U2A9RzubKNajbcp7AngleVxu8mqSZ+89yECrvisRzH3pc6UhKuT\nFwdUvD6nl1xmlXBTMnmF+RJO1veVgu6OWIfiCyfrG6c40xDOHiTrMwPVM9esv4VWPA1VZI7W2nDF\nnP/r/wBQHkyDk66GAgAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$$H^{(0)} = 1$$"
+      ],
+      "text/plain": [
+       "H__{(0)} = 1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFAAAAAVBAMAAAAjqnRBAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAZqvNmRDdRHYyiVS7\nIu/EmopNAAAACXBIWXMAAA7EAAAOxAGVKw4bAAABRklEQVQoFX2QO0sDURCFPzTvRBItLKwkhaQJ\niKZUYme7iFhYiYKtYGUhGMGAnQEtLQRR7KKCWin5B5tC/B2Lb01AZ26C3OxuPDCvc87OXgYsNLWv\nWUSfNgWHcNdHtegiRxMQMXstOtAmT+AWouMBxUcMyOvEyKyPD4wxYdS4G1B8xFPXeO3j/8aRnxIS\nznbXqDUcL0K/w6YU/bWcKBzxT0i+wrHIatQPQpH6gkQLlkR9kBgLdQk56EHmDWIOjxsFmO9nzDYg\nuyJbLzuOSb8xul/cuhByZyqfd+ekaUhAOmfK6bSipP0yo5U1qfUaHOi2K2VZNNlOZ9SdeyHKEq4j\nKd1UuaqpBw4zZm5L1lP+AzkgmDN+B1zn64pVwyflgGDO+BEwWsRNwtMHxbzOGS2lt423Mt5QjoXy\ncyXitiu9oj1FC9W9YX4BUv9IFpEidJcAAAAASUVORK5CYII=\n",
+      "text/latex": [
+       "$$H^{(1)} = x$$"
+      ],
+      "text/plain": [
+       "H__{(1)} = x"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHwAAAAWBAMAAADwX+WxAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAZqvNmRDdRHYyiVS7\nIu/EmopNAAAACXBIWXMAAA7EAAAOxAGVKw4bAAABrklEQVQ4EZWRv0tCURTHv5S/NbSIhqaypcWI\nkqZCCaKl4SHR0BQJ1hJEU0OQQUJbQmuQEEVLWEE0VOR/oFNrU3OS/Vawc87Tp0+vgl94957z/XyP\n98oF6pTjOllndFS64FqYw12LGWZtFcAlRmCROzQHmbWTM4UNnOSsQ+oQMzXR3a4k1vCyiRl1SJga\niWvj9UnDXqsMsTZ6ZrYO3LTKEFOorxwEfdoOMVcY4F0lZioVyPwCtmjrp+9IlakwE3K/cmv/AZwf\nwDGVKXtSfsYU0xth9X5k9pNb1y/gKAJLdPD9g4bB+kytFlZrqXLIeHce8FBl0/BWLgPzpozRCDM6\nLvRxbwbwrlB3xR4wrm+11XoQ2L6otUalj+9O+P3ZMJkZAW6fbKeTrCDXyxiIR8U0L/p4Ogkc8snX\nQhfNGerOkNYem9zq5UNEshot7hxnEryYpGHa6K1TMVKUTqyOl6jip28jelqF5PLy7H9N9JxPia2K\n76SnVUjG5dm/FdSwbh15xV+qXN6W15/dSDcW9qIn3+NrdKnn0yOh97glW4orcMWyjib2exXYMlYY\nVtidWP8w92q7vqHKUQAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$$H^{(2)} = x^{2} - 1$$"
+      ],
+      "text/plain": [
+       "            2    \n",
+       "H__{(2)} = x  - 1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAIgAAAAVBAMAAABvbLv8AAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\nQmCC\n",
+      "text/latex": [
+       "$$H^{(3)} = x^{3} - 3 x$$"
+      ],
+      "text/plain": [
+       "            3      \n",
+       "H__{(3)} = x  - 3â‹…x"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALcAAAAXBAMAAAC7XMNCAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\n",
+      "text/latex": [
+       "$$H^{(4)} = x^{4} - 6 x^{2} + 3$$"
+      ],
+      "text/plain": [
+       "            4      2    \n",
+       "H__{(4)} = x  - 6â‹…x  + 3"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAANYAAAAXBAMAAACFeawMAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\n/hwAAAAASUVORK5CYII=\n",
+      "text/latex": [
+       "$$H^{(5)} = x^{5} - 10 x^{3} + 15 x$$"
+      ],
+      "text/plain": [
+       "            5       3       \n",
+       "H__{(5)} = x  - 10â‹…x  + 15â‹…x"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from IPython.display import display\n",
+    "\n",
+    "for i in range(6):\n",
+    "    display( sp.Eq(sp.Symbol(\"H^{(%d)}\" % (i,)),\n",
+    "                  hermite1D(i, x)) )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Orthogonality:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAKEAAAB9CAMAAAD9c/PQAAAAP1BMVEX///8AAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADFBd4eAAAAFHRS\nTlMAMquZdlQQQO0wRO/NZondIrt8bFiOv0QAAAAJcEhZcwAADsQAAA7EAZUrDhsAAAWMSURBVHgB\n7ZzrgqJIDIVLQHq2VdTZev9nXaoCMwk5VZHOsOPsVv9QMLePgLSHoOEU818X3u3vTmAhnGI/zH/n\ndwMMt4TVxUR4eju4n0C3PYRjP92m8tb4zMSkc2wJz5fxJ/526TofCOP9sX15XfeZKYvOIQjHru9i\nmfB2SVmm60q0efaZKRnIIQhnr6FC+Mzv9nPJw2cmQpBjD2HMhJ+x8Kb3mYkQ5NhBOMY+pfmMA2Xb\nPPrMlAzl2EH4iFPKc6KnDV8IPjOlQzl2EeYelgk95pVQ59hBiHYB66TPTIlQjh2EgQ7jc/2d8lUz\nIYISewifz5TmVjzbuMxECErsIaTTaV8/Y3/VTISgxB7CcE//9S7Ff8w+MyHqHJKw7y7x2t3IWT+O\n0/xhqAgYfGYqp3NIQg31+19phP590HrYeujvgD9DOw5bD/0d8GeQx6HW03sqGNGGmSppJ0mo9fSG\n8EDBT5U0gSAEepoTHir4qRAgEIRAT3PCefk4wU+FAIEgBHp6B6ERbZipEHDihEhpvU5oRBtmqoOc\nOCHS068TGtGGmeogJ0mo9fQewmr0g66plK4HrIQ6BydEPX6d0Ig2zFQHOSXCj/hBDnScFjX57FR7\nLxvRhrlI8J1fJQZ6mgJ/PNYIjWjDTCWAE9/LAejpH2y0UCM0og0z5QdOgtCS7PW9bEVrsb7Z/LSq\nnSSh1tMiyaGCnyppAkkoeN5kpRH6d0TrYeuhvwP+DOk4HIfyLM9fwZvhMQ+Y/kPzZW87vhT/p51t\ntJ4Wm22YH33/fFYuxNcn/FRJl5A91HpaENbNYxruTvFThLCVevTiqJ0EIX06++oQvstnhEse5DOw\nddFITm7ASRACPb3mT8+G+XJPTl3pxhMjOsXCEoIQ6GkKpEfDfM0DvyKhEV0swQmR0mKEhnnxvBcG\nky9FIydOiPQ0IzTM5PlZmOBbI3yKRiUkodbTgrBqJs976e6xf0PRo13ANiAv9nkjtq+m9VeioVPq\n4auK3tbkQxEwWBN+2ipQYo+iB3JbduucAB+Fu67M6JQLOPHj0FL0QG4LwlPu4FAgtKJzKuAkCIGe\nFghabnPz4z5NU9/l8zZ/fV2uRy9e2kkSaj29ps/PdfOV7rgsEtajl0LaSRIKnjdZaYT+HdF62Hro\n74A/QzoOm6L39bG9l339S9Gyh1pPiwo+8yymp6Fy034upUtIQq2nBaHPPF5nsV+8gXIppEsIQqCn\nOaHPHJ7p4yN9ROVZxTIoIQgN0e0zf8bCR1uOCEoIQkN0+8zP0uUSTghKcEJDjvnMIV5P09AXrztl\nTlSCEyI9zTbQZx7jNd1feyl87YHqoBKSMEuh0hjd0OSGeYz5cklf+4bOfGFCE3BC1GPWQ585xCxg\nbuXri3MpVCIRfnz7i0CAnmaEliY3ou/5TvNbLN5LnUqBHH9/Y7MAoKc5oc/c5fdyvYcHK3qgxvn2\nnZbjkL+mlkEOfhyiCbnIoeX2HnM3fwFnrL+XEYEk1HpaIPjMYer7yj37VEmXkISC501WGqF/R7Qe\nth76O+DP0I7D1kN/B/wZ5HGo9bSocKg5yBE/jT7m8pJQ62lBeKh5M+K/5+94bgmBnuaEh5qDHPEP\nF0gI9DQnPNQcxIj/cbtCQqCnOeGh5iBG/FOAhEhpMcJDzWsdGvHfHpgQ6ek1cn4+1LzUoRH/ON/q\nBXuI9LQg1HL7l5mXRDTiT78oAAkP3Y1GciKkEf853fcECZGeXrYtPwG5/evMKRON+Mf8owyY0CfZ\nfdEz4DLiP3fpL146+mUL8T8F6GnepEPN86WPfJivI358xvbN6J3RmxF/hGds5zfhtRrne8BKLkb8\n0zPG5fv8Yi+LhO+y0gj9e6L18P/Tw3f/Vbcx/XjaMNSHMf7dtT9D/lW3YQj/AOMMZ08FpXc5AAAA\nAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}1 & 0 & 0 & 0 & 0\\\\0 & 1 & 0 & 0 & 0\\\\0 & 0 & 2 & 0 & 0\\\\0 & 0 & 0 & 6 & 0\\\\0 & 0 & 0 & 0 & 24\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡1  0  0  0  0 ⎤\n",
+       "⎢              ⎥\n",
+       "⎢0  1  0  0  0 ⎥\n",
+       "⎢              ⎥\n",
+       "⎢0  0  2  0  0 ⎥\n",
+       "⎢              ⎥\n",
+       "⎢0  0  0  6  0 ⎥\n",
+       "⎢              ⎥\n",
+       "⎣0  0  0  0  24⎦"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sp.Matrix(5, 5,\n",
+    "          lambda i,j: scalarProd(hermite1D(i, x), hermite1D(j, x)) )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Hermite expansion:\n",
+    "\n",
+    "A function $f(x)$ can be expanded in Hermite polynomials:\n",
+    "\n",
+    "$$ f(\\xi) = \\omega(\\xi) \\sum\\limits_{n=0}^{\\infty} \\frac{1}{n!} a^{(n)} H^{(n)}(\\xi) $$\n",
+    "\n",
+    "with \n",
+    "\n",
+    "$$ a^{(n)} = \\int f(\\xi) H^{(n)}(\\xi) \\; d\\xi$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from pystencils.cache import memorycache\n",
+    "\n",
+    "@memorycache(maxsize=64)\n",
+    "def hermiteCoeff(f, index, variables):\n",
+    "    intArgs = [(v, -sp.oo, sp.oo) for v in variables]\n",
+    "    result = sp.integrate(hermite(index, variables) * f, *intArgs)\n",
+    "    return result.expand()\n",
+    "\n",
+    "@memorycache(maxsize=8)\n",
+    "def hermiteExpansion(order, f, variables):\n",
+    "    from itertools import product\n",
+    "    nrVariables = len(variables)\n",
+    "    \n",
+    "    result = 0\n",
+    "    for currentOrder in range(order):\n",
+    "        termsForOrder = 0\n",
+    "        for index in product(*[range(nrVariables)]*currentOrder):\n",
+    "            termsForOrder += hermiteCoeff(f, index, variables)  * hermite(index, variables)\n",
+    "            print(\"Order/Index\", currentOrder, index, hermiteCoeff(f, index, variables), \"   Poly\", hermite(index, variables) )\n",
+    "\n",
+    "        result += termsForOrder / sp.factorial(currentOrder)\n",
+    "    return result #* weightFunction(variables)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Order/Index 0 () rho    Poly 1\n",
+      "Order/Index 1 (0,) rho*u_0    Poly v_0\n",
+      "Order/Index 1 (1,) rho*u_1    Poly v_1\n",
+      "Order/Index 1 (2,) rho*u_2    Poly v_2\n",
+      "Order/Index 2 (0, 0) rho*theta + rho*u_0**2 - rho    Poly v_0**2 - 1\n",
+      "Order/Index 2 (0, 1) rho*u_0*u_1    Poly v_0*v_1\n",
+      "Order/Index 2 (0, 2) rho*u_0*u_2    Poly v_0*v_2\n",
+      "Order/Index 2 (1, 0) rho*u_0*u_1    Poly v_0*v_1\n",
+      "Order/Index 2 (1, 1) rho*theta + rho*u_1**2 - rho    Poly v_1**2 - 1\n",
+      "Order/Index 2 (1, 2) rho*u_1*u_2    Poly v_1*v_2\n",
+      "Order/Index 2 (2, 0) rho*u_0*u_2    Poly v_0*v_2\n",
+      "Order/Index 2 (2, 1) rho*u_1*u_2    Poly v_1*v_2\n",
+      "Order/Index 2 (2, 2) rho*theta + rho*u_2**2 - rho    Poly v_2**2 - 1\n"
+     ]
+    }
+   ],
+   "source": [
+    "from lbmpy.maxwellian_equilibrium import continuousMaxwellianEquilibrium\n",
+    "\n",
+    "variables = sp.symbols(\"v_:3\")\n",
+    "theta = sp.Symbol(\"theta\" ,real=True, positive=True)\n",
+    "mb = continuousMaxwellianEquilibrium(dim=3).subs(sp.Symbol(\"c_s\")**2, theta)\n",
+    "\n",
+    "maxwellBoltzmannHermiteApprox = hermiteExpansion(3, mb, variables)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+      "text/latex": [
+       "$$\\rho u_{0} u_{1} v_{0} v_{1} + \\rho u_{0} u_{2} v_{0} v_{2} + \\rho u_{0} v_{0} + \\rho u_{1} u_{2} v_{1} v_{2} + \\rho u_{1} v_{1} + \\rho u_{2} v_{2} + \\rho + \\frac{1}{2} \\left(v_{0}^{2} - 1\\right) \\left(\\rho \\theta + \\rho u_{0}^{2} - \\rho\\right) + \\frac{1}{2} \\left(v_{1}^{2} - 1\\right) \\left(\\rho \\theta + \\rho u_{1}^{2} - \\rho\\right) + \\frac{1}{2} \\left(v_{2}^{2} - 1\\right) \\left(\\rho \\theta + \\rho u_{2}^{2} - \\rho\\right)$$"
+      ],
+      "text/plain": [
+       "                                                                              \n",
+       "                                                                              \n",
+       "ρ⋅u₀⋅u₁⋅v₀⋅v₁ + ρ⋅u₀⋅u₂⋅v₀⋅v₂ + ρ⋅u₀⋅v₀ + ρ⋅u₁⋅u₂⋅v₁⋅v₂ + ρ⋅u₁⋅v₁ + ρ⋅u₂⋅v₂ + \n",
+       "                                                                              \n",
+       "\n",
+       "    ⎛  2    ⎞ ⎛          2    ⎞   ⎛  2    ⎞ ⎛          2    ⎞   ⎛  2    ⎞ ⎛   \n",
+       "    ⎝v₀  - 1⎠⋅⎝ρ⋅θ + ρ⋅u₀  - ρ⎠   ⎝v₁  - 1⎠⋅⎝ρ⋅θ + ρ⋅u₁  - ρ⎠   ⎝v₂  - 1⎠⋅⎝ρ⋅θ\n",
+       "ρ + ─────────────────────────── + ─────────────────────────── + ──────────────\n",
+       "                 2                             2                             2\n",
+       "\n",
+       "       2    ⎞\n",
+       " + ρ⋅u₂  - ρ⎠\n",
+       "─────────────\n",
+       "             "
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAw8AAAAvBAMAAABXtutOAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAEHaZIu9UZs27RDLd\nq4n9ARY7AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAJM0lEQVR4Ac1bS4hkRRa9WZ/XdlV1diIuBG0t\naHEjdKe6saGVAn+bgWkVxcVANzNUg7QzlrhwJ72SAhUVV40ItdGNYBf0xo30QxRF/JS6mYVoYg2M\nK62CWY2f8sa9EXFvREa8zvfqZWbFIt+N+zsnIrLyc/IVAI/tN3pDlnWYS/fUnWp2IMypM5Y9EUvt\nTNKp4mmzu3LkIkfE0pn/gX/r6QGwhadYmtb4GQuCWIpB0qniaXNpZfF/HBFLZ34EV1f0fPq28BRL\nsxo/Y0EQSzFIOlU8bS5tzP2fI2LpzM/grxt6Pn1beIqlWY2fsSCIpRgknSqeM4tdFxHLecz1Gfce\nop1TtYWnWJrQ+BkLgliKQdKp4mlzadn5xXIec/1QTw6ELTzF0sTGz1gQxFIMkk4VT5vb3i2Wd+HH\npr6aHAxTeIqlmI2fsSCItW8Ch/xGi6WawnN6ciBs4SmWJjZ+xoIglmKQdKp42nwP3rUBsVTmwmBh\nU00Pgik8xVK8xs9YEMTaB4HO8WV4sLf44vnX4fq74OY1slQ/dM49Au+ff+rAvFlPn7HsCXLpfBLv\njoTVPl7TnC3OwEmY39vbgcEqLG2Rpar6qzCzA2f39pRvuub0GcuedHH3voh3R8J1Nurh2YtwiQrm\nzp2GYhDVzq3dA4dfi5zTnU6dsdqTh2ZL+Fe0HSocRSqnvflleJQyOnhdOBclGydmHKQxdcZqTwyX\nd6LNUeEoUj293Fv8FeDECYCFXZiBmR8HQT46r24OeYOUSU+Y8eJFyxjeDwkw49gb5uxvxgik6l3u\nwTKI/kh9VbgOzmnzHnBoUGwB/pl14QX4Z1CNzpMw5A1SJj0hxov3lsCMr3wXEmDGsTfM2d+MEUjV\nOw0wiFVHFa6D8xa+Bzy7tAG7cHgLLsBncDT4fITOS4d6sbcOQOu5xBiKEpgxPB0iMOPYG+bsb8YI\npOq9BcVmrDqqcB2cU/B2f3DrJjwB3YudQedXmD+ny2dfW3isO+TVGRO3iTEUJX7fR8YQbzkxHvJC\ni4MRSNX7CW6BWHVU4Tqgx3688M0mityfAHz/PKAavrSmyzvf3/7BHUNenTFxmxhDUSIwMh7acmI8\n5MW81oZFMELokf+a3QpVRxWuDXm1Z1W9xV1ISGhpb22UVguK0rWLXpqsO+11Na1cvaqX2DIE8OEa\nYPgXwZ9h8bmf+LSa9tboP4bUonRN01ue9rqaNq7dvuvSnuqI7xH8wxC+GxzdcP39Ne314akYRelg\n01ue9rqaNq5e1du36rjqPx/RpyYil/585LzFcs0V1C74ewVA0KwoXWZ6y603qHEVVdeqgiAmUl+1\n6njNFXW+/cEfxEwfv0fQOB59jwi9AZOq5bhY7YJr0vadzzhr1RnB1XprE6gqCGJeCI11UqbhwyOs\n6KQ/CNjetnb3vtSNM84bMAnWnZnULhiBNkHNnf59mTHv/+qbBLjz1iZQVRDEvBAa66TMxodHWJE6\niMRSUi5iwjo0hZVJIrpxsjRsq+MClojDNF9p3EQ7lYWxYB9M8ggjJtCE8c1rFqgJgVFW1PAgWIcm\necqaRvchEd0oVSwNGxcOoq4KWCI2Mg2nGY2LKt39WHQQnCXNTJZrRtboD5qA4WS5GHmIcI0mxVSs\nYhQX+KyGBPgg4nVrMICGB8E6NMlTbBrdh0V0o1SRNExSkKMuBVYiNjINpZkmXOnuxzIHYbN8M4Jy\nzfBaZ9C+Ck1g08hDjGs0KaLiFKOoQLIQlWJ10E2uWpFfdwDGB7GXGtB5+XMcn27CUQnvdNfXX35y\nfX2LdWj6oGUl6aIEFtHNpyuWhtEFwwVWIjYyDaWZJlxJys1P6+sfr6+/YrN8M4JyzUAYKWsUxmA4\nWfJ4Qx3jGoGEqZh77BwIZ5kCyXIxvSfCYAduNFv2+Us6vAPhimTdGqzxXwSQDk3yFJuGMInorEld\nNtKwceHg55AUsERMMo1Joybom0GxkW9ho5cmypJmDOWaUd+RHxQBKEosIy4kDxEuKVWGilOM4gLJ\nakaAX5poRbzIYbCmL01AOjTLU2TSClH87bImZaRhcuGyeVlSgFmoqtP9aiaNmphKduEjHQRlSTOG\ncs1M+ehDEYCixDpmbOQhxjXfN4ixVYziAslqRkCtCJGe6SXAGh8E6dAsT4WSNGtSRhqGokRYR10K\nDpOqTjqMSaMm6LuAqR9SAR0EZd1EspfP8s0obeQH3lehCWwaRY1xzUEQYyuyxQWS5VYzMjYnyorw\nGwIuchis8UGQDs3yVChJsyZlpGEoSqLBy5ICq1F3+wAmjZqwmG1cOIg2ZUkzhmq2D4oAFCUCMGNA\neUhEdGJsXDjiAslyMUob/UFWhJB23RCANT4I0qFZngoladakSBouSqLKy5ICKxEbmcakcRMSs61y\nQ7QpS5pxVrN9UASgKBGWGZM85EV0YmwVo6ECn9WMAD+1onVDAHbv2VfWkJkd959605nRVUWYJcVF\nnkKCJblA/b5nXekCL9NIE+eig+BuTuDCX17w90McqpmZKl5mqoaK6Jqi9DkiD1lNCsC60gWcpWPY\nSsH4xmzM3X1p07nUitwik2A2v7MFv2y42uCqI50VHxJ5CnfojHWLUmVd6QKvw0gT57rBA4Bv5rJU\nM8zSvKTIWDqiazxNUPLQqq11rnQBZ+lYCBMSgGPQtf/mAKBW5Bbp8cOG1ORID+bddoZdcxEvT4Ho\nPk6TUi5pJgVn/f1q3icuX+CbiRLmY2jkeGUjQpNvqKNmTpNSLg8iBT7LxyoJwNcAj+tUa/tFpuUp\nypov4QjeVpMY+UgieYKuPK98pFV6FTB/A/jBvzbVA71uN3cQ+Ug9hLaz87zykVY5VMC82mt8EEhx\nyf/TUMw3H4kzJzvP88pHWmVYAfNVrzHS5UGuNB/JVUzGn+eVj7TKLA+z8EdzoC+ypflItmQigTyv\nfKRVYnmYpa3GQLP9XGk+kquYjD/PKx9plVkFzN3NgY5nS/ORbMlEAnle+UirxPIwM9ln9TUJFH14\nIJ2Uj6TzJ+XN88pHWuVWAfMPmFtpiHUF4LZ0aT6Szp+UN88rH2mVWx5msQ8zK82w5r782dzonhj5\nSCJ5gq48r3ykVXoVMH/5efu7hljX4a9+ZbI2H0mmT8yZ55WPtEquAubVvb3f6mH9CSGSEnGAimf+\nAAAAAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\frac{u_{0}^{2} v_{0}^{2}}{2} - \\frac{u_{0}^{2}}{2} + u_{0} u_{1} v_{0} v_{1} + u_{0} u_{2} v_{0} v_{2} + u_{0} v_{0} + \\frac{u_{1}^{2} v_{1}^{2}}{2} - \\frac{u_{1}^{2}}{2} + u_{1} u_{2} v_{1} v_{2} + u_{1} v_{1} + \\frac{u_{2}^{2} v_{2}^{2}}{2} - \\frac{u_{2}^{2}}{2} + u_{2} v_{2} + 1$$"
+      ],
+      "text/plain": [
+       "  2   2     2                                         2   2     2             \n",
+       "u₀ ⋅v₀    u₀                                        u₁ ⋅v₁    u₁              \n",
+       "─────── - ─── + u₀⋅u₁⋅v₀⋅v₁ + u₀⋅u₂⋅v₀⋅v₂ + u₀⋅v₀ + ─────── - ─── + u₁⋅u₂⋅v₁⋅v\n",
+       "   2       2                                           2       2              \n",
+       "\n",
+       "              2   2     2            \n",
+       "            uâ‚‚ â‹…vâ‚‚    uâ‚‚             \n",
+       "₂ + u₁⋅v₁ + ─────── - ─── + u₂⋅v₂ + 1\n",
+       "               2       2             "
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simpl = sp.simplify( maxwellBoltzmannHermiteApprox / sp.Symbol(\"rho\") ).expand().collect(variables)\n",
+    "simpl.subs(theta, 1).expand()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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JmOfJzYAdFAKeB5MRD4Yj+87HDMs6c84xhMJNWPK7cHxg3t9HFW3g7SDbVcD1LxqRCLAS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\n+YAAAAAASUVORK5CYII=\n",
+      "text/latex": [
+       "$$\\left ( \\frac{4 \\rho}{9} \\left(1 - \\frac{u_{0}^{2} + u_{1}^{2}}{2 c_{s}^{2}}\\right), \\quad \\frac{\\rho}{9} \\left(1 + \\frac{u_{1}}{c_{s}^{2}} - \\frac{u_{0}^{2} + u_{1}^{2}}{2 c_{s}^{2}} + \\frac{u_{1}^{2}}{2 c_{s}^{4}}\\right), \\quad \\frac{\\rho}{9} \\left(1 - \\frac{u_{1}}{c_{s}^{2}} - \\frac{u_{0}^{2} + u_{1}^{2}}{2 c_{s}^{2}} + \\frac{u_{1}^{2}}{2 c_{s}^{4}}\\right), \\quad \\frac{\\rho}{9} \\left(1 - \\frac{u_{0}}{c_{s}^{2}} - \\frac{u_{0}^{2} + u_{1}^{2}}{2 c_{s}^{2}} + \\frac{u_{0}^{2}}{2 c_{s}^{4}}\\right), \\quad \\frac{\\rho}{9} \\left(1 + \\frac{u_{0}}{c_{s}^{2}} - \\frac{u_{0}^{2} + u_{1}^{2}}{2 c_{s}^{2}} + \\frac{u_{0}^{2}}{2 c_{s}^{4}}\\right), \\quad \\frac{\\rho}{36} \\left(1 + \\frac{1}{c_{s}^{2}} \\left(- u_{0} + u_{1}\\right) - \\frac{u_{0}^{2} + u_{1}^{2}}{2 c_{s}^{2}} + \\frac{\\left(- u_{0} + u_{1}\\right)^{2}}{2 c_{s}^{4}}\\right), \\quad \\frac{\\rho}{36} \\left(1 + \\frac{1}{c_{s}^{2}} \\left(u_{0} + u_{1}\\right) - \\frac{u_{0}^{2} + u_{1}^{2}}{2 c_{s}^{2}} + \\frac{\\left(u_{0} + u_{1}\\right)^{2}}{2 c_{s}^{4}}\\right), \\quad \\frac{\\rho}{36} \\left(1 + \\frac{1}{c_{s}^{2}} \\left(- u_{0} - u_{1}\\right) - \\frac{u_{0}^{2} + u_{1}^{2}}{2 c_{s}^{2}} + \\frac{\\left(- u_{0} - u_{1}\\right)^{2}}{2 c_{s}^{4}}\\right), \\quad \\frac{\\rho}{36} \\left(1 + \\frac{1}{c_{s}^{2}} \\left(u_{0} - u_{1}\\right) - \\frac{u_{0}^{2} + u_{1}^{2}}{2 c_{s}^{2}} + \\frac{\\left(u_{0} - u_{1}\\right)^{2}}{2 c_{s}^{4}}\\right)\\right )$$"
+      ],
+      "text/plain": [
+       "⎛    ⎛      2     2⎞    ⎛            2     2      2 ⎞    ⎛            2     2 \n",
+       "⎜    ⎜    u₀  + u₁ ⎟    ⎜     u₁   u₀  + u₁     u₁  ⎟    ⎜     u₁   u₀  + u₁  \n",
+       "⎜4⋅ρ⋅⎜1 - ─────────⎟  ρ⋅⎜1 + ─── - ───────── + ─────⎟  ρ⋅⎜1 - ─── - ───────── \n",
+       "⎜    ⎜          2  ⎟    ⎜      2         2         4⎟    ⎜      2         2   \n",
+       "⎜    ⎝      2⋅cₛ   ⎠    ⎝    cₛ      2⋅cₛ      2⋅cₛ ⎠    ⎝    cₛ      2⋅cₛ    \n",
+       "⎜───────────────────, ───────────────────────────────, ───────────────────────\n",
+       "⎝         9                          9                                9       \n",
+       "\n",
+       "     2 ⎞    ⎛            2     2      2 ⎞    ⎛            2     2      2 ⎞    \n",
+       "   u₁  ⎟    ⎜     u₀   u₀  + u₁     u₀  ⎟    ⎜     u₀   u₀  + u₁     u₀  ⎟    \n",
+       "+ ─────⎟  ρ⋅⎜1 - ─── - ───────── + ─────⎟  ρ⋅⎜1 + ─── - ───────── + ─────⎟  ρ⋅\n",
+       "      4⎟    ⎜      2         2         4⎟    ⎜      2         2         4⎟    \n",
+       "  2⋅cₛ ⎠    ⎝    cₛ      2⋅cₛ      2⋅cₛ ⎠    ⎝    cₛ      2⋅cₛ      2⋅cₛ ⎠    \n",
+       "────────, ───────────────────────────────, ───────────────────────────────, ──\n",
+       "                         9                                9                   \n",
+       "\n",
+       "⎛                 2     2             2⎞    ⎛                2     2          \n",
+       "⎜    -u₀ + u₁   u₀  + u₁    (-u₀ + u₁) ⎟    ⎜    u₀ + u₁   u₀  + u₁    (u₀ + u\n",
+       "⎜1 + ──────── - ───────── + ───────────⎟  ρ⋅⎜1 + ─────── - ───────── + ───────\n",
+       "⎜        2            2            4   ⎟    ⎜        2           2           4\n",
+       "⎝      cₛ         2⋅cₛ         2⋅cₛ    ⎠    ⎝      cₛ        2⋅cₛ        2⋅cₛ \n",
+       "────────────────────────────────────────, ────────────────────────────────────\n",
+       "                  36                                         36               \n",
+       "\n",
+       "  2⎞    ⎛                 2     2             2⎞    ⎛                2     2  \n",
+       "₁) ⎟    ⎜    -u₀ - u₁   u₀  + u₁    (-u₀ - u₁) ⎟    ⎜    u₀ - u₁   u₀  + u₁   \n",
+       "───⎟  ρ⋅⎜1 + ──────── - ───────── + ───────────⎟  ρ⋅⎜1 + ─────── - ───────── +\n",
+       "   ⎟    ⎜        2            2            4   ⎟    ⎜        2           2    \n",
+       "   ⎠    ⎝      cₛ         2⋅cₛ         2⋅cₛ    ⎠    ⎝      cₛ        2⋅cₛ     \n",
+       "────, ──────────────────────────────────────────, ────────────────────────────\n",
+       "                          36                                         36       \n",
+       "\n",
+       "          2⎞⎞\n",
+       " (u₀ - u₁) ⎟⎟\n",
+       " ──────────⎟⎟\n",
+       "       4   ⎟⎟\n",
+       "   2⋅cₛ    ⎠⎟\n",
+       "────────────⎟\n",
+       "            ⎠"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.maxwellian_equilibrium import discreteMaxwellianEquilibrium\n",
+    "from lbmpy.stencils import getStencil\n",
+    "discreteMaxwellianEquilibrium(getStencil('D2Q9'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <table style=\"border:none; width: 100%\">\n",
+       "            <tr style=\"border:none\">\n",
+       "                <th style=\"border:none\" >Moment</th>\n",
+       "                <th style=\"border:none\" >Eq. Value </th>\n",
+       "                <th style=\"border:none\" >Relaxation Rate</th>\n",
+       "            </tr>\n",
+       "            <tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$1$</td>\n",
+       "                            <td style=\"border:none\">$\\rho$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x$</td>\n",
+       "                            <td style=\"border:none\">$u_{0}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y$</td>\n",
+       "                            <td style=\"border:none\">$u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$z$</td>\n",
+       "                            <td style=\"border:none\">$u_{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{0}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{1}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{3} + u_{2}^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{1}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x z$</td>\n",
+       "                            <td style=\"border:none\">$u_{0} u_{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y z$</td>\n",
+       "                            <td style=\"border:none\">$u_{1} u_{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} z$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{0}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2} z$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{u_{1}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} y^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{1}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$x^{2} z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{0}^{2}}{3} + \\frac{u_{2}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "<tr style=\"border:none\">\n",
+       "                            <td style=\"border:none\">$y^{2} z^{2}$</td>\n",
+       "                            <td style=\"border:none\">$\\frac{\\rho}{9} + \\frac{u_{1}^{2}}{3} + \\frac{u_{2}^{2}}{3}$</td>\n",
+       "                            <td style=\"border:none\">$\\omega_{0}$</td>\n",
+       "                         </tr>\n",
+       "\n",
+       "        </table>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<lbmpy.methods.momentbased.MomentBasedLbMethod at 0x7f8d351deda0>"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lbmpy.creationfunctions import createLatticeBoltzmannMethod\n",
+    "createLatticeBoltzmannMethod(stencil='D3Q19')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Own Subspace construction"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAAcBAMAAAB/iHIpAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\nEkT3kSxYvC71rovCxf/rjbdu3X8oCkYq6UhcpwAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$$\\left\\{1, x, y, z, x y, x z, y z, x^{2} - 1, y^{2} - 1, z^{2} - 1\\right\\}$$"
+      ],
+      "text/plain": [
+       "   ⎛⎡                            2       2       2    ⎤⎞\n",
+       "set⎝⎣1, x, y, z, x⋅y, x⋅z, y⋅z, x  - 1, y  - 1, z  - 1⎦⎠"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from itertools import product\n",
+    "dim = 3\n",
+    "basis = set()\n",
+    "x, y, z = sp.symbols(\"x y z\")\n",
+    "for order in range(3):\n",
+    "    for index in product(*[range(dim)] * order):\n",
+    "        basis.add(hermite(index, [x,y,z]))\n",
+    "basis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjIAAAAbBAMAAACU3ni9AAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\neHnp8QAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$$\\left [ x^{2} y, \\quad x^{2} z, \\quad x y^{2}, \\quad y^{2} z, \\quad x z^{2}, \\quad y z^{2}, \\quad x^{2} y^{2}, \\quad x^{2} z^{2}, \\quad y^{2} z^{2}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡ 2     2       2   2       2     2   2  2   2  2   2  2⎤\n",
+       "⎣x ⋅y, x ⋅z, x⋅y , y ⋅z, x⋅z , y⋅z , x ⋅y , x ⋅z , y ⋅z ⎦"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "additionalVectors = [x**2 * y, x**2 * z, \n",
+    "                     y**2 * x, y**2 * z,\n",
+    "                     z**2 * x, z**2 * y,\n",
+    "                     x**2 * y**2, x**2 * z**2, y**2 * z**2]\n",
+    "additionalVectors"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "@memorycache(maxsize=50)\n",
+    "def hermiteScalarProduct3D(f, g):\n",
+    "    weight = weightFunction(x) * weightFunction(y) * weightFunction(z)\n",
+    "    return sp.integrate(weight * f * g, \n",
+    "                        (x, -sp.oo, sp.oo),\n",
+    "                        (y, -sp.oo, sp.oo),\n",
+    "                        (z, -sp.oo, sp.oo),)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#basisList = list(basis) + additionalVectors\n",
+    "#sp.Matrix(len(basisList), len(basisList), \n",
+    "#          lambda i, j: hermiteScalarProduct3D(basisList[i], basisList[j]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def gramSchmidt(vectors, scalarProduct):\n",
+    "    vecLen = lambda v: sp.sqrt(scalarProduct(v,v))\n",
+    "    projection = lambda u, v: (scalarProduct(u,v) / scalarProduct(u,u)) * u\n",
+    "    result = []\n",
+    "    result.append(vectors[0] / vecLen(vectors[0]))\n",
+    "    \n",
+    "    for newElement in vectors[1:]:\n",
+    "        for r in result:\n",
+    "            newElement -= projection(r, newElement)\n",
+    "        result.append(newElement / vecLen(newElement))\n",
+    "    return result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAABHQAAAAbBAMAAADvz8UZAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\nAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\left [ 1, \\quad x, \\quad y, \\quad y^{2} - 1, \\quad y z, \\quad x^{2} - 1, \\quad x z, \\quad x y, \\quad z, \\quad z^{2} - 1, \\quad x^{2} y, \\quad x^{2} z, \\quad x y^{2}, \\quad y^{2} z, \\quad x z^{2}, \\quad y z^{2}, \\quad x^{2} y^{2}, \\quad x^{2} z^{2}, \\quad y^{2} z^{2}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡          2            2                    2       2     2       2   2      \n",
+       "⎣1, x, y, y  - 1, y⋅z, x  - 1, x⋅z, x⋅y, z, z  - 1, x ⋅y, x ⋅z, x⋅y , y ⋅z, x⋅\n",
+       "\n",
+       " 2     2   2  2   2  2   2  2⎤\n",
+       "z , y⋅z , x ⋅y , x ⋅z , y ⋅z ⎦"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "allVectors = list(basis) + additionalVectors\n",
+    "allVectors"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result = gramSchmidt(allVectors, hermiteScalarProduct3D)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Q3wJ/L0qC6Q1aqoBGULhG/cfz5z96/rx+ZkWDholuZDLlQUOyLDQmlav0l7VvRUTMSdDP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\nhdicmwJNgabAKAWW9vbe9L+ZPINAvwZ+sAAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$$\\left [ 1, \\quad x, \\quad y, \\quad \\frac{\\sqrt{2}}{2} \\left(y^{2} - 1\\right), \\quad y z, \\quad \\frac{\\sqrt{2}}{2} \\left(x^{2} - 1\\right), \\quad x z, \\quad x y, \\quad z, \\quad \\frac{\\sqrt{2}}{2} \\left(z^{2} - 1\\right), \\quad \\frac{\\sqrt{2}}{2} \\left(x^{2} y - y\\right), \\quad \\frac{\\sqrt{2}}{2} \\left(x^{2} z - z\\right), \\quad \\frac{\\sqrt{2}}{2} \\left(x y^{2} - x\\right), \\quad \\frac{\\sqrt{2}}{2} \\left(y^{2} z - z\\right), \\quad \\frac{\\sqrt{2}}{2} \\left(x z^{2} - x\\right), \\quad \\frac{\\sqrt{2}}{2} \\left(y z^{2} - y\\right), \\quad \\frac{x^{2} y^{2}}{2} - \\frac{x^{2}}{2} - \\frac{y^{2}}{2} + \\frac{1}{2}, \\quad \\frac{x^{2} z^{2}}{2} - \\frac{x^{2}}{2} - \\frac{z^{2}}{2} + \\frac{1}{2}, \\quad \\frac{y^{2} z^{2}}{2} - \\frac{y^{2}}{2} - \\frac{z^{2}}{2} + \\frac{1}{2}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡            ⎛ 2    ⎞          ⎛ 2    ⎞                  ⎛ 2    ⎞     ⎛ 2     \n",
+       "⎢         √2⋅⎝y  - 1⎠       √2⋅⎝x  - 1⎠               √2⋅⎝z  - 1⎠  √2⋅⎝x ⋅y - \n",
+       "⎢1, x, y, ───────────, y⋅z, ───────────, x⋅z, x⋅y, z, ───────────, ───────────\n",
+       "⎣              2                 2                         2             2    \n",
+       "\n",
+       " ⎞     ⎛ 2      ⎞     ⎛   2    ⎞     ⎛ 2      ⎞     ⎛   2    ⎞     ⎛   2    ⎞ \n",
+       "y⎠  √2⋅⎝x ⋅z - z⎠  √2⋅⎝x⋅y  - x⎠  √2⋅⎝y ⋅z - z⎠  √2⋅⎝x⋅z  - x⎠  √2⋅⎝y⋅z  - y⎠ \n",
+       "──, ─────────────, ─────────────, ─────────────, ─────────────, ─────────────,\n",
+       "          2              2              2              2              2       \n",
+       "\n",
+       "  2  2    2    2       2  2    2    2       2  2    2    2    ⎤\n",
+       " x ⋅y    x    y    1  x ⋅z    x    z    1  y ⋅z    y    z    1⎥\n",
+       " ───── - ── - ── + ─, ───── - ── - ── + ─, ───── - ── - ── + ─⎥\n",
+       "   2     2    2    2    2     2    2    2    2     2    2    2⎦"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#sp.Matrix(len(result), len(result), \n",
+    "#          lambda i, j: hermiteScalarProduct3D(result[i], result[j]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.maxwellian_equilibrium import getMomentsOfContinuousMaxwellianEquilibrium\n",
+    "\n",
+    "mb = continuousMaxwellianEquilibrium(dim=3).subs(sp.Symbol(\"c_s\")**2, theta)\n",
+    "v = sp.symbols(\"v_:3\")\n",
+    "mbX = mb.subs({v[0]: x, v[1]: y, v[2]: z})\n",
+    "\n",
+    "\n",
+    "def unweightedScalarProd3D(f, g):\n",
+    "    return sp.integrate(f * g, \n",
+    "                        (x, -sp.oo, sp.oo),\n",
+    "                        (y, -sp.oo, sp.oo),\n",
+    "                        (z, -sp.oo, sp.oo),)\n",
+    "\n",
+    "mbX\n",
+    "\n",
+    "myBasis = result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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1KTIoK/9b+b4FLbHpiLJxUC6dRYmbS4PjxQEncKbGkerQHbC63cWRcgh3xNhI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\n5/8BCi553zEkRw8AAAAASUVORK5CYII=\n",
+      "text/latex": [
+       "$$\\left [ \\rho, \\quad \\rho u_{0}, \\quad \\rho u_{1}, \\quad \\frac{\\sqrt{2} \\rho}{2} \\left(u_{1}^{2} + 1\\right) - \\frac{\\sqrt{2} \\rho}{2}, \\quad \\rho u_{1} u_{2}, \\quad \\frac{\\sqrt{2} \\rho}{2} \\left(u_{0}^{2} + 1\\right) - \\frac{\\sqrt{2} \\rho}{2}, \\quad \\rho u_{0} u_{2}, \\quad \\rho u_{0} u_{1}, \\quad \\rho u_{2}, \\quad \\frac{\\sqrt{2} \\rho}{2} \\left(u_{2}^{2} + 1\\right) - \\frac{\\sqrt{2} \\rho}{2}, \\quad \\frac{\\rho u_{1}}{2} \\sqrt{2} \\left(u_{0}^{2} + 1\\right) - \\frac{\\rho u_{1}}{2} \\sqrt{2}, \\quad \\frac{\\rho u_{2}}{2} \\sqrt{2} \\left(u_{0}^{2} + 1\\right) - \\frac{\\rho u_{2}}{2} \\sqrt{2}, \\quad \\frac{\\rho u_{0}}{2} \\sqrt{2} \\left(u_{1}^{2} + 1\\right) - \\frac{\\rho u_{0}}{2} \\sqrt{2}, \\quad \\frac{\\rho u_{2}}{2} \\sqrt{2} \\left(u_{1}^{2} + 1\\right) - \\frac{\\rho u_{2}}{2} \\sqrt{2}, \\quad \\frac{\\rho u_{0}}{2} \\sqrt{2} \\left(u_{2}^{2} + 1\\right) - \\frac{\\rho u_{0}}{2} \\sqrt{2}, \\quad \\frac{\\rho u_{1}}{2} \\sqrt{2} \\left(u_{2}^{2} + 1\\right) - \\frac{\\rho u_{1}}{2} \\sqrt{2}, \\quad - \\frac{\\rho}{2} \\left(u_{0}^{2} + 1\\right) - \\frac{\\rho}{2} \\left(u_{1}^{2} + 1\\right) + \\frac{\\rho}{2} \\left(u_{0}^{2} u_{1}^{2} + u_{0}^{2} + u_{1}^{2} + 1\\right) + \\frac{\\rho}{2}, \\quad - \\frac{\\rho}{2} \\left(u_{0}^{2} + 1\\right) - \\frac{\\rho}{2} \\left(u_{2}^{2} + 1\\right) + \\frac{\\rho}{2} \\left(u_{0}^{2} u_{2}^{2} + u_{0}^{2} + u_{2}^{2} + 1\\right) + \\frac{\\rho}{2}, \\quad - \\frac{\\rho}{2} \\left(u_{1}^{2} + 1\\right) - \\frac{\\rho}{2} \\left(u_{2}^{2} + 1\\right) + \\frac{\\rho}{2} \\left(u_{1}^{2} u_{2}^{2} + u_{1}^{2} + u_{2}^{2} + 1\\right) + \\frac{\\rho}{2}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡                    ⎛  2    ⎞                       ⎛  2    ⎞                \n",
+       "⎢               √2⋅ρ⋅⎝u₁  + 1⎠   √2⋅ρ           √2⋅ρ⋅⎝u₀  + 1⎠   √2⋅ρ         \n",
+       "⎢ρ, ρ⋅u₀, ρ⋅u₁, ────────────── - ────, ρ⋅u₁⋅u₂, ────────────── - ────, ρ⋅u₀⋅u₂\n",
+       "⎣                     2           2                   2           2           \n",
+       "\n",
+       "                      ⎛  2    ⎞                 ⎛  2    ⎞                    ⎛\n",
+       "                 √2⋅ρ⋅⎝u₂  + 1⎠   √2⋅ρ  √2⋅ρ⋅u₁⋅⎝u₀  + 1⎠   √2⋅ρ⋅u₁  √2⋅ρ⋅u₂⋅⎝\n",
+       ", ρ⋅u₀⋅u₁, ρ⋅u₂, ────────────── - ────, ───────────────── - ───────, ─────────\n",
+       "                       2           2            2              2             2\n",
+       "\n",
+       "  2    ⎞                    ⎛  2    ⎞                    ⎛  2    ⎞            \n",
+       "u₀  + 1⎠   √2⋅ρ⋅u₂  √2⋅ρ⋅u₀⋅⎝u₁  + 1⎠   √2⋅ρ⋅u₀  √2⋅ρ⋅u₂⋅⎝u₁  + 1⎠   √2⋅ρ⋅u₂  \n",
+       "──────── - ───────, ───────────────── - ───────, ───────────────── - ───────, \n",
+       "              2             2              2             2              2     \n",
+       "\n",
+       "        ⎛  2    ⎞                    ⎛  2    ⎞                ⎛  2    ⎞     ⎛ \n",
+       "√2⋅ρ⋅u₀⋅⎝u₂  + 1⎠   √2⋅ρ⋅u₀  √2⋅ρ⋅u₁⋅⎝u₂  + 1⎠   √2⋅ρ⋅u₁    ρ⋅⎝u₀  + 1⎠   ρ⋅⎝u\n",
+       "───────────────── - ───────, ───────────────── - ───────, - ─────────── - ────\n",
+       "        2              2             2              2            2            \n",
+       "\n",
+       " 2    ⎞     ⎛  2   2     2     2    ⎞          ⎛  2    ⎞     ⎛  2    ⎞     ⎛  \n",
+       "₁  + 1⎠   ρ⋅⎝u₀ ⋅u₁  + u₀  + u₁  + 1⎠   ρ    ρ⋅⎝u₀  + 1⎠   ρ⋅⎝u₂  + 1⎠   ρ⋅⎝u₀\n",
+       "─────── + ─────────────────────────── + ─, - ─────────── - ─────────── + ─────\n",
+       " 2                     2                2         2             2             \n",
+       "\n",
+       "2   2     2     2    ⎞          ⎛  2    ⎞     ⎛  2    ⎞     ⎛  2   2     2    \n",
+       " ⋅u₂  + u₀  + u₂  + 1⎠   ρ    ρ⋅⎝u₁  + 1⎠   ρ⋅⎝u₂  + 1⎠   ρ⋅⎝u₁ ⋅u₂  + u₁  + u\n",
+       "────────────────────── + ─, - ─────────── - ─────────── + ────────────────────\n",
+       "        2                2         2             2                     2      \n",
+       "\n",
+       " 2    ⎞    ⎤\n",
+       "₂  + 1⎠   ρ⎥\n",
+       "─────── + ─⎥\n",
+       "          2⎦"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expansionCoefficients = getMomentsOfContinuousMaxwellianEquilibrium(myBasis, dim=3)\n",
+    "expansionCoefficients = [c.subs(sp.Symbol(\"c_s\"), 1) for c in expansionCoefficients]\n",
+    "expansionCoefficients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/latex": [
+       "$$\\frac{\\rho}{4} \\left(u_{0}^{2} u_{1}^{2} \\left(x^{2} y^{2} - x^{2} - y^{2} + 1\\right) + 2 u_{0}^{2} u_{1} y \\left(x^{2} - 1\\right) + u_{0}^{2} u_{2}^{2} \\left(x^{2} z^{2} - x^{2} - z^{2} + 1\\right) + 2 u_{0}^{2} u_{2} z \\left(x^{2} - 1\\right) + 2 u_{0}^{2} \\left(x^{2} - 1\\right) + 2 u_{0} u_{1}^{2} x \\left(y^{2} - 1\\right) + 4 u_{0} u_{1} x y + 2 u_{0} u_{2}^{2} x \\left(z^{2} - 1\\right) + 4 u_{0} u_{2} x z + 4 u_{0} x + u_{1}^{2} u_{2}^{2} \\left(y^{2} z^{2} - y^{2} - z^{2} + 1\\right) + 2 u_{1}^{2} u_{2} z \\left(y^{2} - 1\\right) + 2 u_{1}^{2} \\left(y^{2} - 1\\right) + 2 u_{1} u_{2}^{2} y \\left(z^{2} - 1\\right) + 4 u_{1} u_{2} y z + 4 u_{1} y + 2 u_{2}^{2} \\left(z^{2} - 1\\right) + 4 u_{2} z + 4\\right)$$"
+      ],
+      "text/plain": [
+       "  ⎛  2   2 ⎛ 2  2    2    2    ⎞       2      ⎛ 2    ⎞     2   2 ⎛ 2  2    2  \n",
+       "ρ⋅⎝u₀ ⋅u₁ ⋅⎝x ⋅y  - x  - y  + 1⎠ + 2⋅u₀ ⋅u₁⋅y⋅⎝x  - 1⎠ + u₀ ⋅u₂ ⋅⎝x ⋅z  - x  -\n",
+       "──────────────────────────────────────────────────────────────────────────────\n",
+       "                                                                              \n",
+       "\n",
+       "  2    ⎞       2      ⎛ 2    ⎞       2 ⎛ 2    ⎞          2   ⎛ 2    ⎞         \n",
+       " z  + 1⎠ + 2⋅u₀ ⋅u₂⋅z⋅⎝x  - 1⎠ + 2⋅u₀ ⋅⎝x  - 1⎠ + 2⋅u₀⋅u₁ ⋅x⋅⎝y  - 1⎠ + 4⋅u₀⋅u\n",
+       "──────────────────────────────────────────────────────────────────────────────\n",
+       "                                                                              \n",
+       "\n",
+       "               2   ⎛ 2    ⎞                            2   2 ⎛ 2  2    2    2 \n",
+       "₁⋅x⋅y + 2⋅u₀⋅u₂ ⋅x⋅⎝z  - 1⎠ + 4⋅u₀⋅u₂⋅x⋅z + 4⋅u₀⋅x + u₁ ⋅u₂ ⋅⎝y ⋅z  - y  - z  \n",
+       "──────────────────────────────────────────────────────────────────────────────\n",
+       "                    4                                                         \n",
+       "\n",
+       "   ⎞       2      ⎛ 2    ⎞       2 ⎛ 2    ⎞          2   ⎛ 2    ⎞             \n",
+       "+ 1⎠ + 2⋅u₁ ⋅u₂⋅z⋅⎝y  - 1⎠ + 2⋅u₁ ⋅⎝y  - 1⎠ + 2⋅u₁⋅u₂ ⋅y⋅⎝z  - 1⎠ + 4⋅u₁⋅u₂⋅y⋅\n",
+       "──────────────────────────────────────────────────────────────────────────────\n",
+       "                                                                              \n",
+       "\n",
+       "                 2 ⎛ 2    ⎞             ⎞\n",
+       "z + 4⋅u₁⋅y + 2⋅u₂ ⋅⎝z  - 1⎠ + 4⋅u₂⋅z + 4⎠\n",
+       "─────────────────────────────────────────\n",
+       "                                         "
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expandedResult = sp.simplify( sum(a* b for a,b in zip(myBasis, expansionCoefficients)) )\n",
+    "expandedResult"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 154,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def expandedToVector(expansion, truncate2ndOrder=True, addWeights=True):\n",
+    "    d3q19 = getStencil(\"D3Q19\")\n",
+    "    d3q19Weights = getWeights(d3q19, c_s_sq=sp.Rational(1,3))\n",
+    "    expansion = expansion.subs(sp.Symbol(\"c_s\"), 1).subs(theta, 1)\n",
+    "    \n",
+    "    rescaledSymbols = [x,y,z] + list(sp.symbols(\"u_:3\"))\n",
+    "    expansion = expansion.subs({s: s * sp.sqrt(3) for s in rescaledSymbols} )\n",
+    "    \n",
+    "    #expansion = expansion.subs{}\n",
+    "    res = []\n",
+    "    for i in range(len(d3q19)):\n",
+    "        factor = sp.Rational(1,1)\n",
+    "        term = expansion.subs(x,d3q19[i][0]).subs(y,d3q19[i][1]).subs(z,d3q19[i][2])\n",
+    "        if addWeights:\n",
+    "            term *= d3q19Weights[i]\n",
+    "        if truncate2ndOrder:\n",
+    "            term = removeHigherOrderTerms(term.expand())\n",
+    "        res.append(term)\n",
+    "    return sp.Matrix(res)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 155,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "normalEq = createLatticeBoltzmannMethod(stencil='D3Q19', compressible=True, useContinuousMaxwellianEquilibrium=False).getEquilibriumTerms()\n",
+    "betterEq = createLatticeBoltzmannMethod(stencil='D3Q19', compressible=True, useContinuousMaxwellianEquilibrium=True).getEquilibriumTerms()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Hermite expansion = normal LB equilibrium:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 156,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAABoAAAHaCAMAAAApC6n8AAAANlBMVEX///8AAAAAAAAAAAAAAAAA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\nAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\\\0\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡0⎤\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎢0⎥\n",
+       "⎢ ⎥\n",
+       "⎣0⎦"
+      ]
+     },
+     "execution_count": 156,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expandedToVector(maxwellBoltzmannHermiteApprox.subs({v[0]: x, v[1]: y, v[2]: z}), truncate2ndOrder=False)- normalEq"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 158,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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8fnart06nY46wCOs1DFdSlhtzdbv34Ndhj8HX6PEzpl0Pxh3D8Pfy4b8nVpU8\njcZwg/w0AhY+s4qtXUi4k5t0ytfGG8FikI5jtHS0tRU1tvgfynKtUP6zY/etLCfW6I0JNOLr+xiG\nJsIiT6Mx3JMGLHwe7CsQt5ObdMpVPk0IovV4I2ts8Iez4HtquZU8j/Dryb3DI/6WZdel+1CW61ij\nZ/QWeH03yvDDigjL9GmU8TEwXOWYy/QkMG5PyfzriWaeJzQborEaD2U52lpXS6fbUH6VuAtluY41\nekZg4fXdKNN5+AEl3dxzGvlwdUcjALSe4A7WeCjL9QT14nnuWlkur/ibD9OO63uz0oeUdINOTTcC\nRGsGNR4cq9FPzrzvz2P8ejqU5e67Fx7sjQgcynJGgP7V4fCg4lCWWx/uam3OSviLAXeQhHVDYweY\nezT4M6f7NlJwroYe+v8sz2Pc0+jhOpTl9NjYR/isa7tEZ46LAXfUD+uGxg4wMTG9p0zIM1RjPd2q\nu45byuhHmv+d/3dLlCa5HMpyk4FrFENrcxrZ+w9dDLiDAqwbGjvAxMT0njIhz1CNh7Jcd1wvn/FQ\nllsfY/+rlC3JWlPJxYA76MG6obEDLMxMnArRWI2HslxPY/yTPIey3IWkx9iSrHWNeTHgDoqwbmjs\nAOOr1nqKbHkGajyU5frDetmch7Jcb3xV0TsMwNfm4FzeeingQ1nOBdfPmbrrz6M8ET6U5cxuaIne\nYYA0KRIfDdZLAR/Kcj68h7Jco+td4dChLNcOehFq26ssx+pZB1wvLyy4h7JcCPmhLMd63pV2D2W5\nP09G6OPrXpYLwKX30+wFrkca50wkrKjpIW8ZxKEsh4J0Jduj/Ho6lOXcq8Dan/QmrLPP2fdfRt/a\nnEXAbJjIIw1W04O+1hCHshwM0pWMDzLSwDX1/21lOdGh4oCwXAAu3XvsBa6HCUc/EQ6eHMpy9WsZ\nRfPeuuFBRhqqhJFD/t9WlsthSIl84i4WgCsjwj7g5kgj1fSSVE5yz28ZxKEsR4Nz5fSDjDQwiuGl\n+PBIPjmgylouMigh5sul03kfMDtjCK6vQ6iseaP9aVLLQi6rfe4HFk4nwt414XPGpY5ziENZjkbn\nuukHGGk2OTnynSL6X1WWU1Tv4ok7JAB3ojeLCm4aXYeAq+WFUFatjNquPaWanp9iS94aqkAcynLp\nZLj61o80h7LcIyrLia4VR5oRAbgO2TRXzQQwWl7Ib0gSrq8hTlsrUnCdyjM+CIeynI/C1T+Hspxr\nAv/yeaoyVi6XxFpeqd9qtO2swypr9O3dBBgstRMnXTnrupXlBMsWNSrkQqjt91kBBj7zhyx5BHMk\n/EDz9UUbieIWT2Xc3LFDWa4E6IqpB/j1dCjLnf1Umk3qttGVqluPYjMkJAAAIABJREFU0487cYtA\nGhVyKVYH1vOS3AlgtLxQDBMR94TU9Cjh4jODOJTlSmiunnqIkeZQlnP9yJxDGk/chpoeEIAbGGnG\ngN0gxv62ZcNEvqdpqOlxRRsGcSjLXX18KQQeYaQ5lOX8pD1jJWQWaturLFf6zpaaBJaE2TCRcQ9l\nuUNZjne66+0fynInfn0fawz2V04u3HNPkzOjhAbMBHNcUTbSIDBig7idENipjrWkpP6SxGjluJ4S\nNbb4H8pyeiD/4ZFDWe60Sd3OxlwTcpk/jSITDZgL5ri/QN2To/4PxO2EgE5JQp1kIFpPWVljgz+c\nBd9Ty63keYRfT4eyXPmzbLpfKUIu06dRJoKBx2TVMhhJYFySQU8ip+YJITS97nJkrMZDWa5E7oqp\ndBvKrxKHstzeRpmUTbOq7Vu6aaHMHgdO7SAE0HqIDdZ4KMv1BPXieQ5luY+L6HRMy6ZZLT4mq2ah\njR2HTk0Tgmg9hMZqPJTlemJ6+TyHstzlY3zUcMUIHMpyVww+rTr8ETGrLFctwcmo2JoPdyQwArZ2\nwJUsCyAK2LwyWsHAhLC1lOpILYAgtSxAWwBBCPUnL3LH2l/9ipyP8US4IxKqxBxaguPeFOX+CHn+\n7MBVs2AEbFVB0IEFEAR2ARqGwFZSs51cAEEqWYC2AIIQ6kg+gKJc8tKPNI+hLJc8wtunH2x3E8jc\nmLKtoqE5sJXmsNIYAVstrOr4AgiCtwANQ2ArqdlOLoAglSxAWwBBCHUkH0BRLnn5f26keQrrZpLl\n3rdQy/L0qb770v/yktJg2DoSG4yArSO481pmsJaLEboYMHSjw3hzhDo4d76FtQfp2nke79cT1LJ8\nad+G8iU4W6tg60iLYQRsHcEVa4aGCovMFyN0MWDhQqfh5giZvO9eUS55+HAjDdSy/NoW872/fHw8\no5moeM0QtqbIka0qqYYRsJXg5eQgcC6nJT4+Xj+AhMLFCF0MWHMw23d7qsrZ9fukQmSWrcS2gj2/\nmqeV9S6OPdxIg7Qs4xqbd/9n+Nf2JqiqcdLEv8ooF+bUh92eJak2izsJLPgxw/un+6EIXuOOaVaF\n/3Oevj87/z/ACo/+YKkQVWTVnUdRlEsOPtpIA7Us47tbnr+9189CdpTPLN5ig60pbm6ZzvNLeJub\nG3DCWtsv8U8VRsDWgjsNTCBw8sd7Ll/jfjFCFwPG7hFrt6dsSWNpU03ODvhUY9gQhGdK1hDB+vod\n/8Mw3waSQG58+2gjDdSy3F6bdBoRGjv1rEqJb3xRJNUwArayXjIDzCDk7p8z+uHY5Wh65d/DeSpP\n8Rh6Rc4OtZ7AaEPIhkHL2L9+P+NI86L+a4qQbtf2aCMN0rI8/YabmRGhMfem7re3N0usLXapP1Cr\nDSNgK+8fE8AcQu7/hChw+8UIXQyYeyD3+z0Vo0QaU7GcHfRJYMTWwxCSrbMIiNPHKY00r7DZIMxN\nGx9tpEFalunZxHf4feN/fL+/hj+jvr7df99l/Qm2NpovdiksqbYDN3X3EeAGzXjo/Pn08fril30P\nOzpDqPjfojYRwhbcdqzfU3mKJ0IBicvZQZ8ERhMCshcQv195pAlvaYel7sv4YCMNfotHfDZhCI2d\nXtyTWNd6r26KUd8ndykoqZYxhnHzie2eSZ7DTCAMUVmtifLv50//PMm/brgql2m2Eo/qqTjFS+hd\nOKScHYqRwMjBghConTjEu5uUke5pHmW224ONNFSeqPSKJDHXFBo7jWuqpS61T0au8MypCWBzovz7\nOfzV//L9Pu5oPv8ezVN+iueXF4emEHJ2uYFoQmCk1vOZBARsJw7x4UqmkUbOKqWV30/6gUYaoi23\nJXMrJIm5ExQaS7Kr/peUn+AXX5NJBq0pSbUTxq0uaQuBq4nyEPf81wfk9/yndjTRDNGCBd2RePJg\n8Tg3y3z7360GXuApBJ72NKEFTxUpuuSpzyPl7NhyVAWDjDQSomLv/kj/9J+/32Hj/1n3nzc/56mM\nNP492ff/8SPNoyrL5dZJ9zTBwIXGiOxqES5zyh/P4cTMGCgRuxTUajthXHhJE9gTwPZc+79hOPg9\nu99QxFFCU9AohiYhEisCvMBTDDzrKUHLjvGbiTymuhxSzg6vuxUYZaQBEJB9DbG9FLuMNP7R2v1/\nHkFZLrXCx9u7+7i96mrq9quRhguN+aaPsqujmmpbl9orI5fok+0EsC/dnmu/TSdy9zRUoY2q3REC\nPNkk5CpOozKJILt4c8S4PwHsS854SmhmMvUp7s0bIV+FlLPDq3EFRhPC1yHY1xBvz/5z/n4OS2jk\n6l8PcX+fB/r1pCrMnZ63KQlQaIzKro5qqsUuFWcd11ptCi68pIluMwHsMdoT5bdZRS/+oXdxlNIU\nNIqhRcjlyiNNAe5cCDoB7FlNeEppeojwqU9xb4qEoJwd9klgNCF8HYK9gHCZ0sy9478nH7Lb+jwr\nCnOnOCUBCo1R2VU/SerP94ubzOA++ezRnYxdqiGptk3wrHDBJU3UMAdsTZR/dn69B6nLQoi6L2gU\nQ4uQy5VjVYBDWXHxLogxNQc84ymlmWnIUzwSgnJ2oZjwSWBYEJK9gHA1neOMvW0yWGZ8t4lHuqfR\nFOa2xxKuiT5eXsJ8Er+U4OP17en59cm9MsP/3tquMsXqTPns0do2S59BrTYVN1WmwbrfNs/f50+v\nFT4GDCbKszqc/89hgWVxlNJkuctum5DLl2NVgENpcfEumCE1CTzlKaWZafBTPBOCcnahmPCJYZgQ\ngD2DcPV8/JzPoQuc/OD9CJ9HGmlce2CFudO3/lBtu6gDWbZ89sw1s4rbsXKzWaMGjCbKN4HCQQ3N\nLklzKLGSF29aqCcNgec8ddVJNHmKW6ykT4MYiH0L4t4V5VJAH2ykwQpzp5fweyj5XG23BxVg0a7s\nllU5a0fFBZc0C6s6rgDDifJVQbijoMG8uhHHaq+nrj4EPOkpRGtIuWFvgU9jGJB9AwLPRcXkbtr6\nWCNNfocnu/I8NdaOkP+eqpZCnbzKYOwouOiSZiCxwxgYTpRnJdEuRkM5GzYYq/2e4pFm1lOM1vAK\nHNrv0yj7u1eUS1F8rJEmDTDiytOQmIOyqy48k4JhKbBhOsZbmouVrfCSlo92JTTCXYVFpiVoKFYL\nPN3fCLW7iGadw9hb4pNRBzt894pyyZ/HGmk0hbnTu3h5TAqAf04MZNmmBcMM3NFLWoErKUi4HB5M\n7UfDsVrgKQYe9C9nX4C2wKdMpy9x/4pyyc/HGmlUhbltHlZy+tgeEbiPCDyAolwK9GONNOGhA3kP\nRPLSbd/Uv5/4jOKtELYSQDOJEbDVBKMZFkAQuAVoGAJbSc12cgEEqWQB2gIIQshOPoCiXHLysUaa\n5BXYHspyICjO1Lc8CZeNVgyBrU0gfnABBIFcgLYAghDqSLYlPToAbieLH2kOZbltVgltlb5VO7QE\nT2MEbOVlm/sLIAj+AjQMga2kZju5AIJUsgBtAQQh1JE8lOU6gnStLIey3FDk/Q/Ona9AwRDY+q+5\nkfpujhDhpiY/wtvw1cN3dODxfj0dynLD3U8s5RlGkMuTA8TFgMcJbiVujpDpyKEsZ4boShkOZblG\n4HfrrQ1K3Yk1Qiq3QWAVJx3Y7akqC9fvkwqRSDa3h7JcMzzXP3goy6ltcCjLpZmdaoj8XEG/4tYt\nwXVfh7JcI1Cjhx7t19M9Ksux9XVFm2xMss5s+m69NYY0S0jM1OZqI7PAjJ/c7fZUDf2AslxdffFJ\ng6jzhz1Gw9sOZTkQp1sy3aOynOxn8Q0nQ0JuZivcgLLczXmqEhpQlhOBj62nQIjsziBpHMpyKE63\nZLtHZTnZz2JfHZGssxuhX29NYk0QQmuEbs5TlRCWhUM+qcHCEDK7s0gah7IcDNQNGe9RWU72s3hi\nP5yy3M15qhMKfbpLWU70/tR6EELk9gZB41CWg3G6ISN+m8eNK8uJfpZfZvtoynI352mDkOvVfcpy\novvTkUZCoAUNnMahLCeCemsGItJEqCVthBtVluP9rLw2e0DIzZwofwvKcjfnqU7Idx8hC0f6VCNJ\nRxoBAduJ0ziU5Rrhvf6hO1SWg7piLpKxrypCbkkLrhJyqybKQ4G4qyrLzXmatODWeJrQQlc1CPk8\nUhaO6fvAMOfWwxBVO7k/0v9TynIPv+4p3dOELnZ7ynL8ipb76ohknT3X/gaU5QY9JVpwRLJu1lOC\nFjqC/1IJuWNAFg7ekGSwlCj3NAACsq9pPKay3P+5FZaPojF+r8pydT/z/XXrq0OSdb5Ye679DSjL\nDXrqPAKSdbOeEjQPET4aIXewW1kuQpVNHmkQhM8m2qmmcSjLlVjeZuo5/H76kS9CuHFlubqf+djG\nvjoiWeeLtSfK34Cy3JinzqM80hDJuklPKZqHCB+V0ICyXMLK2zTSbOsJXr+okl/IJNpJ0jiU5XI4\nbzBxr8pysp/FvjooWWfNtb++styYp66L5ZGmlqyb8ZSi5c6rEhpQlstgKRFbT4WQ7CWNQ1kuRfMW\nt/eqLMf7WdYmezhluTFPXR/LI00lWSeXOfDuCDT0KFrOrhIaUJbLYFsit54GAdhzGu5J8aEsx+J6\nY7t3qSwn+1krqpoW3JxAiIbWYiCP5QGhPiQu3mOeOjAIPOcpRBsmtFcX0E3ScX9h/wlKoiVYLRqH\nslyJ0w2l7lJZrqErBkKraMH1TZQXeAqayNc2wAHhJC/eY566OhHwpKcQbZiQ9KkdGXEUsm/QwHNR\nBeztGx5rLfehLDfc4/y/rqegTT5ctBRAAwK8eJcifSkEPC+FgtD6eKRc6IYkHevbjrI/lOX64vqP\nc6XbdXHlOZTltJY4lOW0yAA7vCEB+RaaDmW5hcFcB3Uoy43H8lCW64/Z6A1JP7KW81CW0yJzXfuh\nLHfd+B+1L47AoSzXHVC0ctX9h/fys1czC0KEhw6jynK1LxD3YoTruuf2MOM5rH9S6jYIYxbYOhSW\nBRC5vuosWQmca+hM7K/bPxF+fw2vTu2ss2RTxdpKFrxQBFtLqY7UAghYC8bFVgigGRdAYOiLAePq\n9ltvgzBmga1DPi+AwPVdDBhXV1mH6sZyeF/OPLnuKf/RU3Gqd9jK1XgQW+uSxt4CCFgDxsVWCKAZ\nF0Bg6IsB4+r2W2+DMGaBrUM+L4DA9V0MGFdXWYfqxnJ45r/cWKjN0/jsuBOCK1dP2Fq5Zu0sgIBV\nYFxshQCacQEEhr4YMK5uv/U2CGMW2Drk8wIIXN/FgHF1lXWsbiiHZ440UKjNs3jBN0kVwbAjVq42\nrLJ0w4KBGwU6D2FcbO2E3LItgMD1XQwYV7ffehuEMQtsHfJ5AQSu72LAuLrKOlA3ksOzRhoo1OYJ\nfG2zvb4+Pj5+/IIj9xlS8xLrWTeM/D0NnBGsxKCYmUW4VKcqilkQHT6XWmjqYsC0kmZaDSYuZREu\npdRglixWSuWGWWArqkTl1g+hckP1Wav1SRmVGsmjJYfO4xqkIYdnjTRQqM2jb5Pkvl5c8u3sxYPH\ndMvSHDsPhT7TwAistkXtsJOnfgJT+jA1bK2Q94qSdfhc1Zd3LG7TwLkGNWEFExe0CLtSVjAxcGW1\nuGEW2IqAF6jPqZ2wqi/v2Nz2h23sPM7UtsTfn7D9cv8z8Y8x0mChNg/yHW5kXs9+E94b2a3m5UuL\nSbz87WezwB689SnCX2OybSbhAqwpikkIRtT2mRWIuxcDFtWxlYDFZy2YAiEYTMIFWAsmBibWAqFx\nwyykVXVa4yYhCC+ftLmxAnFXAtfcCq5GDeNW1u7zuK47YLTk8IyRBgq1edDttUqnP99u2cz7+dO/\nR9698Ud+8EIRYGW8J4ElAWmJrw8Zkm2zCbt6IrCiKAYgGDfTZ5Y/7l4MWFbHGsllaAdTIniLTbgA\nK8HEwMza5oZZAKvqtMINQDBixT2lE8r83gKABbd2H8S4lbX/PBZ1n5pyeMZIA4XaPLPf78Iv/Hoa\n0S1Dy0ck7/izbAS4cGqkYmOMyLb1EY7AWFEMQSCSjWCi7G7M/3x7e/ux/wccBgbVyUZqBhMgOFMf\n4WYwMTC3NrlhFsiqOr2noZvcuCPbfhe33WHrP91kXJpyeMZIA4XavOMv7jYmft7/etGI8+fTx+uL\nXxj8/hr+lvryUuploQi2Jgw3qsi/ssaBC1wjFRtjRLatuFFwJeEEHPLMiZKdWj6Xuq1glpw5NQ6c\ni5aE7rN7s+pv+HOTUisFqRUFs+RMqWYwU6b2NkFAboWFxU13OlQ/19BNbsWtYW4JF1IruHrKOo9L\nSRGXthxee6TRX44Rxdrcf1Aff/2UafcLyj8W9k9vXtzTPJd8rZ8KYWuD9xwwFnwq1QRi8Qbg43wO\nc4IwNWwtSCLQ6ZdEyCIVxUpJPWX4nORXlBDruFYrKcAimA2fYTAV3AbRfIieMjKYGTjnB4kMAbnl\nAtdo6NJXMLcU+WFu2WfnngxbpUOTA0AT5nlcMvPOYMjhtUea5HCBTykqbPLhHtZYumVfv9ttUB6h\nElDact7ePgyMhDZSBXmbGmNAti2XJQlJOAH7TEJRjJRsJhs++3W9b8+utBlMVMMwMAim7jMM5h7C\nzWBmYORotiUIyC3nMoOpO+0xJhu6yS1HfpxbwoXUMm52XiSs85gU4HEx5PDwSCNE2pIhV/Q3/Ecc\nd7/dDyVDt8z/kvK/j8KX/62ekbC41nZ4HJi+7Kgt/DUi21avsIRqYI4waWUgSlZdhhVq3mvdZz9R\nM7y0qhHMpcAkmIbPOJgK4Wq1nka4GcwM7APm5lf8zR830TR/IgTmlvtgHcyKm+G0rwg0dNW5J7nF\nyI9za4bNXaiSqo3nDrkp57Edlzcf+c/tX2432y7OsfP1bB8/0swoy8V7mq/wh9OPwzV1y4g2GBpb\n2Qg5B8xCmZyst7ExRmTb0AIzRtjVUVoZKIp1XIYNn7cXcW6zC4xg1g6f5oBBMFWfYTAVwiiYjLAR\nTAosS2ZLs6FJHyTBRNxUpz3LeMElEAQ4M5GJJjcSeQLcxa3ZBwmuZBQt+Dy26zbl8FRluXLXEYep\nU9oGSnGkOYeZwn6kMXXLXvxwmh7eVGNrAGTtuQ44RrBstsYYkm1DC8wY4eCcuwb5D1IUqy/DWz72\nbfi8vVz8r38cdjKCeSlgzWccTIUwCiYj7HbzKQOCSYFlyWxpNjQ560gwETfNaVcP4Oat9MYhs6kT\nl+LWClsXNeU8dncUW9SLG3VcTDk8/OvJ6Wo9p3Cl5Q5pu1UVxdq+w/Dz182lMXXLKm0w2Rg179M6\n4BKamIqNMSLb5oeJr7P/8VI+jLA7kFoZKYr1XIYNn7cIbxPdjWAWliG1DFj1GQZTIYyCyQgbwaTA\nsmS2tBraZcp9kAQTcVOdxupzBDgzkYlLcWv1QeqzZBQt8DyGa6JlXNxP/3g7Em7F6jqUkaaE6/1j\nW+CUtrH46zaf5tdfYd/O/gmMpVtWaYPlVs5sGO91wLmGlIiNMSjbJiROGWGHHoGholjPZbjL5+1B\nlxHM5GrcLgNWfW4EExD2XSbe/jGmZdcOZnzkV4rwVKuhXd7cB6tgSm6q07ChKTAnRPYvxa0Vtj5q\n6DwOxHmbybi4p4hxpKHT7aLX5kjzGv/pTttYLg1af15eXn62iz1Q86IXn0obLLdyhHPty+bTLAPO\nNWyJLPw1JtsmF7dxwhkYKorRSDBGZbft83ZbtN1ZGcEskFtqFbDqMwymSlgGkxNuB5MC85J5P0NA\nbi5b7oNVMCU31WnY0BQ4c+GJS3HLuPPU/IrGl+fwXH0wLq5kSw7PGmme3raRJm1zzPwyBPOzXcnB\nxSe3cobg7ZkPwMQAMCyvGVXcuKKUlFtEmCBaSe1RjwymhcSOdwOP+RzuuaHCi71SkDFkuxphlq29\nq4RNcBt0mgxh7fpbRy/FTcFtUUnHhuIC5PCskebDzZTxN7ppm+o9vfi/z62PevGRHjfEtUAtOjBZ\nJQHKWSYVVy5uW0TYYkSOa4IpMpikUE9SBebBHPM5/DMTJgAxEjKYLIO1qxG2ylXHcdgkt0Gn14w0\nPPKB+X5uYU5tFYXenaG60YxfY6RxE4xDqbQtvJ5gLMrxLaVdfHAr89KNfQz89fL3/Mx+hjVAwCGM\nixa3gcItkwLcKiKOKYIpu4Ppbtg+qndjh5r3BxPjLgimAiwC1jTAsIFVjE0QdBACo4yaTYn8bm4K\nrkaD2sfqRnJ47ZHGTzD2I03a0rrBm13o4S2tXXzmx9ZYhwYsKYxZMC5a3DaGq17fB2FQ9t3BRKCX\nsy0I5hJyKGxLuCHgBYyXcJvkMVg3ksNrjzRv7nnvy/nlN20pz3cyzZfa6/SlrpZLrmo11W0PEi7L\n8VCRPhsE7ivazLXjQtXEvdjBFcHcTw6HbQE3DLyfMFmtvABsEGIsLn6WqvjoI036dRRf45le51kQ\nwrSlsnukjggcETgi4GaeVXN8U0SUkaYMzL8/5/A7KW1TQbd96/n7ieQ/kkcEjgg8fgTkIz/vsx9p\nLqgs537kILVKbB1qgwUQsD6Mi60QQDMugMDQFwPG1e233gZhzAJbh3xeAIHruxgwrq6yjtSN/5K5\nsLIcWpnl/jJ3qyieux7zVN7SnQUQFC6nMS625kI9iQUQuJqLAePq9ltvgzBmga1DPi+AwPVdDBhX\nV1mH6r6OshxYmeVmYUJr5Zq1swACVoFxsRUCaMYFEBj6YsC4uv3W2yCMWWDrkM8LIHB9FwPG1VXW\nsbqvoSznZ5HwpYlupIHWyjVrZwEErALjYisE0IwLIDD0xYBxdfutt0EYs8DWIZ8XQOD6LgaMq6us\ng3VfSVmOr8zaXMDW4l6HypoFUcBgShX1wrjYipBVVS8LosNnVJ97Nm8sWJwGxtUBqxpMkNeZLMKl\nlBrMksVKqdwwC2xFlajc+iFUbqi+gbip1DBuZVWU5Xqcuqqy3AkL+mFr9rhHDM2AyFgsYQmOzRF2\nlZiqXgbhHp+ZL3H3YsC4OmI1g0nykqRB2OU0g0nQlKTJDbPAVlqHya0bYlBZTumahJtJjeTFSU1Z\nzq7b4V1TWc79+4Q8Ela2jq1DZU1AoHq4rYhvaYJjk4QLsKrqJQiP+8zd2fYvBoyry9bisxrMnLdK\nWIQLsBrMCg/sFAiVm2ARYISVtVIBVrkJCMavQKjcWIm4K4BrbgVXpYZxqVVRlpOnRV13gLimshxQ\nq/Sc5HotxttWWZMQNF6NdHyFhybqhXGllRF2FUZgRXBshc/YK5ObHUwM3GE1gokRTMKumBFMDFxb\nDW6ShS8urQsauubl9wxusoC3dHDbHTZFWa6n7qsqyymr6cB6Ldme/lepe9EWlrpSgHEL1dbYGFhZ\nTsHtIhyBseAYAh71ufYj7XVxawczQY1v28HEeF2E28HEwMza5gZYuPLAKlupzQ1AMGJut81N5vcW\nACy4talh3Mraf7qJut0LH9Iby+OL8iiyMkc4ZdmrLFdWZlGNrGJN9bgTQc73aYmhFQgKXOAaqdgY\nWFkO4xZrwZWEE3DIwwXH+iAmlOUuBlxcbaSSz1C9rZSjjdRHOAHDYBbgVipBQG6FxWJuBXiaWyk4\nzC35HCB4Hyy4egoryyGnxAlwVWW5sjKLamQVa/FY8G6rrBUICpylNQquTOXGQKJeGLdYC5wgnK5T\nIYtQ9eqCaPt8ykIu1OeLAe8P5g7C7WAW4NIeMnU7DT3IrUR+uKGzz65K0QcLriQULYqyXE8nO5Tl\neFRTY1xfcEwOVm7+tC7Tl4VcxgXHXAyGgclb63kIy34zmHsIJ2BflVBvy8CFCEgliOs3tCTX5JYj\nP97QCdfXKMKWcSWfZDmU5X7Pf2qZrXR9r63l5bAudFA5K/9EVgTHMG617GNOcCwBhzbVINzBfcpy\nS4HJK52UWKZbDxxMP98LSOHtD2YGDsGc4pav73UH2s8tA+/hFiM/zo2MNEj0jrSocn4cynL+4TCR\n2SJXNWJ1j3uSeExoZ/gVGwOKoZ0wLlr2IW9ISiv792n5D6FGgLdj7ptBzAnAoQvVEuDdwdxelSqk\n8PYHkwLnYMpEs6FJ2Egr7edGBYwkpWxpciORH+XW7IMENxPhiUNZzmsCUAmwdLmsrD2hjJdhLIZG\nX7JNawMLtdjZ7FostzISHKsvw1v7Moh1ynIXA+b9shlMqjyzNJgUWDAqhq09lIYmXWUpN1d9x9Wu\nGTcKMcqt2Qd7qB3Kcv7FXEUCjF7VipU2kUsrn9gYUAxNwUXLPtjZ7CpLrdytLMcglgnA8ZuldcAi\npK1gUuUZ0kj7g0mBBaNiaHFzufKAsJQbBS5UROpS3Fp9sIvaFtuX+nSDKxVZ7w0uHspytKVjYzTE\n0KIirXt12J/vFzdLIHz4sg8Z6AgMBcfgZZhBLBOA4yPNOmAax5C2g9mlLMci4aDtYAJxn5pei5vL\nmUeaQ1mOxu1QlnPRKFJX9KpWrLT70ODRdBbfgoJjKq57ks8m/PCTIwNDVS8KnOlwiFUCcHykOS0D\nztS3RPYZBnO7QQRSeHuDSYEZo7Lb5uby5ZGm6kB7uVHgQoalLsUt48I+2EXN/Ul5KMuR5lIV4HL3\nIZkHkipu17KPRkUQmI80jfL+EHrU4+3S54sB++r6PxrhvcFUI9FPzeWUYQvFjbVFHVUowB0lcxYF\nYjc3BTfX20gM1X0oyzUiGQ6pV0u55GRMcAwCj0GoQi6y+6wCTm+tt8KmHMeSNmj9ziLCCg9slmHz\n+fY2tIPAwJiEYsVCLvu5YVyFRGUeqvtQlqtiB3eUyzBYcgKL60YFWC8AjihCLvt7NgQub60HVPpM\nEBet3+mDK7kwcDnek4Jh29/QC0YaJfK7uSm4PcEaq/tQlrNjii/DaNmHjVXlwMBVltmd+QvVbI27\nyi0I5q76U2EUtiXcEHCqdMd2CbfJ+gfrPpTlOuIMr5Zo2UcHVpUFAlc55nZ2XKjmKtxbakUw93Jw\n75yFwsoLuGHg/YQPZbkFMTwgjggcEXiYCBzKcg/TlIcjRwTPRLq3AAAgAElEQVRuOAKHslxX41RL\n7HIJbM2HexILIHA1FwPG1e233gZhzAJbh3xeAIHruxgwrq6yjtTNJp5FnENZrgqoInqHFt7V5cy9\nBRC4josB4+r2W2+DMGaBrUM+L4DA9V0MGFdXWYfqPpTlqtgpO1hCC1sVCGxeAPGPgXF1+60Xi8QQ\nNcwCWxcAD0HgzAu4YeAO61jdh7JcT0ih6J2fDCMF8jrgSpYFEAWMpi4GTCtZmb4NwpgFtg55vwAC\n13cxYFxdZR2s+1CWq6KninrxtZRbKWytEOOOquplQUwLwF0MGLkHbWowYe5DWS6F5VJxU/tgqrix\nPZTleHD4mkd+XNm/WcGxQ1mOtNh+ibQkTqert+EOhK2EWgJ+f3bGj20FKT0sF2nWR/2e2QllEW8x\nue0P28Mry7HI/ieU5cZ9ZiXirrX4rSOYGJhb2crNomS2VyGNVVSApyXSCoTKTYQtsBBW1WmVWz+E\nyo0FJO4K4Dpb8VmlVhdAew+vLMectsXQ5JIvBqHtxteW3ICyHGNo+8wKxF0ZCXZyzAKL6hiuO24E\nUyAEgyQs80VgTaZPFpAWgxtmIa2q0xq3AQitE0pnvEUCi3y7w/b4ynIiZs7w6Mpyoz6j/O5tXe5V\nXX+eqmPy5GgHsyrc2JG4sWcrMn0YChCWGSOwItMn8wNLmxtmAayq0wq3EYjlcdsdtsdXlgM95eGV\n5QZ9LtmHBcfcW8T++ncHYt0wDFysOaWedFimL5c7WYRLzpSKp8y2OyORlu+3MLeyZtDipjsdyHFu\nBTi54kZ5MZktuQdV70pBi1vJGVMJN+xyaiI3MOAe0uXUnSjLCafbKmtlKRwV36oVMATkZsiNcXVl\nOUGw7XPRU6M+l0gUONGzZ4BBMAVu+vXkn4yeP51oiHv8GpYyv549m6w8Q62IcKGeUrmVnEFKpGXg\nlB1tMwTiVlhY3BpOI24FuHBqQCBuJfIWt1JFTGWfEbWCK8olw39AWS65SrcNMbScrRLfItIaOYNI\npMa4RcGxCQE44Z8zyJ49AQyCKXGbwczKM1UjIcLSloD9ESGRloFlOWJJENdv6MG45ciPxy35DMOW\ncUmQWPKhleU0YTAXA11lLV8ua/Gt6n1nCnBsDCyGpuBWyz409TbSykDVq7oMK9R8s+s+++lTQKjt\n9PTpy20fjZs7Og5M3hWl4TaDqRCugqlFohnMDBycNiCUhk5hqztQxc1w2lcOGjoBB24GhMYtRr7B\nTXG6GTZ3CaJyaBDi8ZXlQruUL0NlTVGAY6EscDQVG+MGlOUoK5c2fN5eECqE2tCFil1D54BBMBmu\n49wKpkK4bw1NOWWkTB8FZjGkuy1uVABuVL0tOe3dlxKCHe1hxM0dziOCwY26G9KtsFFcUTAZHl9Z\nLnkat4bKGn1nNRHfIk3E8Mju1hiK4Bi5WhJctOxDPescCd///OlNIdINCWHCkobPVMiFACOfGbdl\nwAzX8W8FUyGMgskikYFdAgSTAsuS2dLi5oHT9Z0EE3HTnMbcKHBmokEonbCfW64hJfJIA8IGqaWC\nafv4ynLJ07g1xNDoVY0Ig5EmYnhkNzbGDSjLEVI+afhMhVwMn1nPXgbMcB3nVjAVwn4wtxeRpVMG\nyfRRYBZDutvi5vLlkYYEE3FTnXb3Rb66V3dJIRAEOJNRIWAnHOCWa0iJVtgobsovtltsH1lZjrnc\nJYYGFOBy92F4ZDc2xg0oyxFSPtnlMxBqkz6znr0MmOE6znYwAWF3Mp79/1StTwRuyPTdkbLcWNxc\nWHKTGqp3IoKtsFFcUTAbHl5ZLnsaE20xNHpVq4TBchNxvLSfxbegGJqKK5ec8N6TgaGqFwVOVMS2\n7fN2HweE2qTPnNsqYI6bfYbBVAnLYPJQZGAYTArMS+b9DAG5uWw5bFUHktxUpyE3Cpy5qBB7ueUa\ntkT2uZ8aQ3C7j64sJz1uWaBQmy+Qu0+rtH5Mxd0rhqYD62T4EfIMqTokfeY9u8oud7qBF+HKYEpO\nTYtGuFmIH5RhCznE2qJBp1EfXACBuXGfrH3FZ6uYPz4Ul1tWlutxtuRRr2o7FTBUXLnkZEwMTQUu\nPpkpTchFdp8xbrpkHVeWW4Qrg2n6XmfQIlHnMvZk2HwByW3QaTTSjEPwyAdfJDfDRXF4/vSQdTec\nOpTlROSFQblagrUsomjboAC3C7GjipALPmVY2eYuBF4gJwJx0UKtJjtwEAODjA0TDNv+hkYjTYMF\nOqREfjc3BRdR4Laxug9lOR4/uY+vlmjZhyzbtGDgZpHeg/MXqt4aluZbEMwlfFDYlnBDwAsYL+E2\nyWOw7kNZriPO8GqJ1rJ0YFVZIHCVY25nx4VqrsK9pVYEcy8H9z/7oSw3EMSxNvOLRcTn162EezrX\n7xwImfLA/BX/kEzbDBHmBuW9I3FE4IjAEQEXgUNZ7ugGRwSOCFw+AuuV5Xo4VyvWcgFszYd7Egsg\nYDUYF1shgGZcAIGhLwaMq9tvvQ3CmAW2Dvm8AALXdzFgXF1l3V/3DmW505NfytP+4NV02NpGYkcX\nQDDEbRfjYisE0IwLIDD0xYBxdfutt0EYs8DWIZ8XQOD6LgaMq6usQ3WL134FKPU5Taro/eP1GTzG\ncYefflIefYtWrLlZmG6lyDaVTS9pHFkAAWvAuNgKATTjAggMfTFgXN1+620QxiywdcjnBRC4vosB\n4+oq61DdkxqWn0+nLziN6BResVbxkTt+FolcTYetsnTDsgAComNcbIUAmnEBBIa+GDCubr/1Nghj\nFtg65PMCCFzfxYBxdZV1rO4pDctXp2mDZvy5NyKEm6QOMTS8mg5bi3vTwAXCSKmiXpgatqI6VFUv\nC6LDZ1SfmytmLFicBsbVAasaTJDXmSzCpZQazJLFSqncMAtsRZWo3PohVG6ovoG4qdQwbmXdryw3\no2H5982/xrUisu1sf3r3iKFhNSxszRXNA2cILWGKemFq2EorMVW9DIgen2l9JX0x4FKFkjKDicsZ\nhF0hM5gYmFpNbpgFtgLgQ1mOBiWk/25PVPw0Vf4xntOE25kXr9XHP9uCqw7NMrEyKyBha6lkGrhA\nwFQR31JFvTA1YWWr5gqwquplQXT4DH2Si99YtmlghsN3i89qMHmRbd+KRAFWg4mBi7VAqNwEi1Ba\nWNc3dAe34ghNCW70oPvx8fzyvN3dTofNvWrHjxI/8hmsqJvFxVN53d6E5B6Y1MT8njHSvPmJfehe\n6BTfMvntHsS496n7Gx/3mBd85MosnwlbSXFbDM2EIGhVMr7CQxP1wrjSKgMdgacFx2yfKz/yjuSW\nD22JWWAGg3aNYKIiqPWHg4mBa6vBDYdNWoe5DUBonbB2JO1J4HQkb40+mPOpif7zWMbl6/czjlDb\nm6OqSoyR5uX59RVOxNnet7JBjQvAda7XGgeufFN2YmMool6YGrDKQEfgPYJj/pf4r7uk4Gfw2CHA\nDWUcB0Yo3NYOJs+97QPCo8HEwMza5gZYuPLAOsptBELphMyRuAuARcZ2HxTZpUHpeqBuGZePUxpp\n/Au82McYafxjGvj5LedCS7OsrMwa1shqi6FhYEiVG2Nj3KTg2IQAXIkEd7Tab7VSyUhbqVgbqWYw\nSzmKiwjLXpuAA8aMRFp+H+BNNnRy70GV5V7L8JA6QXukwf86+bIvSfmjrVlWVmYNa2TNALufeolX\nclBuUyNDMbR+wu2TQ4ihFeDCSEC0fc4KMZV8GwIuVcTUDPD+YPYTFpFIrw0N/EUwC7DwlBhuuKGL\ne4+pLBckHUhTuGR7pNHPW/rIaFgArqag7w0DIwUMAZ864C0Kjk0IwAn/FEMjmFmorVIy2x9MjIv4\ntUeaQ1lO/hhBUXS21Ln9YRG2jhZdpCwHFm23RxrFHWf+pP9H6ZplGaDWyMpmn4ACV1uOcWD6eiMF\nODaGJuoVuTUIG2phHgAJjkXgsNEg3EHdZz99CinLUWDFZ59lHJgEU8NtBrOHsBYJcsrIYGbg4PoU\ntxy06zR0M27uad2mENPgpjjdDFvG3ZyHEIqyXA6XT8A2e/MrCdJzGjlbN9zT/O/8vwrIdWftk/P9\n3f4xNzTL3Bj78RpfVkE0sjruy2eBycmRubJEbAysLKcQBgvMWpfhNJ+A+lwikfkwCMPn7QWhQllu\nfzBV4J3B1HB3B5MC52DKRLuhyw9t2kq7uTka8pcAa2iXx+CWI29wE06XkQb1wTSCiWLFgJXl3ESK\nH/7PUO3UezjNy0gjHvD+n/Z+mlI3TMV7GkOzjEpNEv2ujru4OWA2aEPmsZEVUa98w1/JwqEFZnWg\nfVW5lZGqFwHOtBiE4fO2Uiwqz/hr3muYtbA/mArw7mAquPuDSYFzMGViaw+loUnYSM/cz42KY2ZK\nrKFD27n7FTc/ZMvy7P5vJCxI5IkVccs1pESzDxLclF9ssbIcqrt26u3Zf87fz9vSgU3Cg6Krv57K\nwJx+I6ZtKB5HGkOzjEpNGuJblJRLXww4DwhY1IvclxPCaIFZHWhPP7UyFBwjwNlVBmH4TIVcCLeO\n7nMx4OwzDKZCeH8wKXAOpkzE9oDcXO5830CCuZ8bBc6UWEM7+yJuuYaUaPZB4nPKL7ZbbIWyHFgT\nLZ1Kp627rZOz65SRhoz4aQ1H2m7cnrdxx9Aso7e5lUZWbmXhaTRcDDg3MlSWUwj7YYL/9JSBjq0M\nxdAocPaZQRg+b60HhNr2BnMeuB1MBXd/MClwDqZMxPaADe1y57CRnrmfGwXOlFhDO/sibrmGlGj1\nQZcn+5zyyy1UluuLi3vsEm9Hwo++GlsZaQqn949tfnPaxuLpD/O2ZtnWJbYb/kq/y/b4UsBZfAuK\neqmEXUDYKkbeezIwVPWiwLkFOETb522w6lKWyzXExKWAs88wmCrhvcGkwNzVvN/m5rLlPlj1zL3c\nKHDmwht6Gbdcw5bIuLAPQmoMwe1qynLWCeBK/pzP/oeg+0t7YD5NaofXOKcmbSMzMGjFI3Sj3uYm\ndJp5JH0pYBXXljZs04fAvAO2IehP0Srn3mBeDNhfCcOfZRVdv8NXMS6KhKinZdDCtpMbGcJy7YPu\nIYgNi3PLNXQmNJ97ivO6W06NzBGOnJ7etpEmbTMlv+DJ/Ki3uXs89rXqwHIwNVmSDCquXMXYENYi\ngCkJgccgdAG47S/RVNX4VlOIyW+tH4cMJTTcvcFUIzHEU+mDYiXhYCuhYWIcAndjwW3IYZd5R4uK\nultOPbyGJZbWGGgO9b68Y3FbsxoVuFmKHVSEXJRThhVu7ULg3cH0N+If/L9RT2NvMFXglo/iGA7b\nfm7lZ5mostOgRX4vNw23h9ZQ3WhtgfGc5vdrew9W2hZOT3jULRlCSrt/xq3MCrd2NeBWmZ5jCi5Y\nYNaDRvIowCTHdHJ3MKdrniu4P5hz9bJSMGwruEFgVvnM7gpuM/X6MmN1HxqWdpzxDT9aFGhjVTkw\ncJVldmfHLfFslXvKLQjmnupzWRS2JdwQcK51PrGE22T1g3UfGpYdcYY3/F2rGA1wCGyU6Tm855a4\nB395nhXB3E8Kh20BNwy8n/BpAbdpFmN1+1mq4qP/ekq/jpJ2ZdpmiEPDMofiSBwROCKQIqBrWL6/\n+pnR1acMzL8/52e/hiFtSba3nr+fYn6wbsIdwVZShZ1cAAErwbjYCgE04wIIAr0ADUNgK6nZTi6A\ngJVcCndJf4SMb8N4ubjV/qE/AdzMV7dMASzxrouyvQ5FOVbihNZNuIZ1c5yf7RfKcDC6vwCCwuU0\nxsXWXKgnsQCCVLMADUNgK6nZTi6AgJVcCndJf4SMb8N4ubgp/tUKc+qvp32KcrxutJ7kUJjjURrf\nx3EdwsEQ2LoAeAgCZl5ADeIu6Y8K8i2YLxc3xbtaYU4dafYpyvG6/X+8fOGQa1lo5WWb+wsgID7G\nxVYIoBkXQBDoBWgYAltJzXZyAQSs5FK4S/ojZHwbxsvFTfOvUpjTRhpLUU4DdyvhX18/XtATHL5u\nYoPAVgQ/CIwgoG0Q93qEJxW/OmTlsE/YWmI4DVwgjJSqj2ZRO3Vww3UbyNO4uDZkVZ1GmbFNhTC8\nI2gqBMmjJ7fXGZyoqoo20hiKcqCOS+t4uZfnuk94Os1q5wsy2GFt984Iv3+64Tu/vpk4Zbjfo1eH\nIbA11zwPnCG0hCkrZ1A79XDDlbeR53FxbdRqOk0z47QJ0fbOg5oQuGZmBQpzykgTphM3FOUYMNG0\n2qvjxZCLWNYgMMPhu9O4YvkHQ54GZjhit1vx61QvfeuQlcM+CWuN61584P+TDG+D7Ocm3PKGGrhE\nUNVHE9QYRA83yESsyKqpzeOK2hhwh9MLIKy4zbDgofc0kcKcMtJYinLC6/zGDU0rC6+bwNYaPb5y\nYwy4hoB7U7hXI9yv+MWa3paVwz5JKzs5ZoFlYzDg3Jf6NfqYzyebm2ThLcJpRm0WV9bGgF2G2B81\npxdACO/4ID/DgofeYUCFOWWk6VKUq32PgVK0svC6CWytcVMLDAEzCLh7X4T7Fb9A0zf16nAjAKs8\nOVxPbQjhAQjYEJJwbJp+jT4J4WpqccNEJONRnzEusErgttMLIKR3+kijhB6wAKGHCnPKSNOjKMdq\njYHaq+PFUN3uBLAEAZYJ3L7lHxPAgB4znT+fPl7Dk3ZLpQ00fUtWrvhkAcuToymEh4GZW2FXAKcI\nhqNcVq7gEiwB0RYmLCUNp5fgltpKSgI3nS4FS2oQoi9uwyxkd3PLsdOby9ML8xxpPNKgVd+bh+iR\n5HYkU0RaWWXdxLDCXB5pBpTgSms0UndF2Gmf+5eZeWUEM4K8B7Zl5fqbhuO6P3j++vmgJjfKGDWI\nAM5N43ILWblCmGAJiDa3UpJyA8hLcEttJSWASz93mYTTpWBJDUIA7/R7mlBLFwsx0ry7GXtppCEv\nzMMjTXldefFrS1FFufpY6h07BdtqUL83Bax7kCuYws2lG4kZYGum+IDil2h6R7UhK5cdqWTlspUk\nZM+eAQaeCuAUQV+50EcjjEpSQLhDTadjB7GcXoPb43Pu594p4LTs0ZLbgri1IYAjorv55ZVppCHL\nD/BI453Fn6iJAESpIsV5wTaAGThMAJMXrjsIBXgCt46Jgpu6zEgk6pniCLhH8QtLfgXSuqxc9qkh\nYwalxLaCo8C1pwow6e5SVi4T3hIKhD+oc8sdRHd6IW6Xz6nbeOLS6UzYH1bbeUHcmhC1I5iGpjDn\nR5qiLKcJykVZGudjVJQL/tZfkeKQYBsQ4apB/d4UcMfbiGZw0ZguGE8A2zPFFcUvoFfHLjKGXp1j\nn6+WhowZu4bOASNPGXBuct/4m4Kh+znhxoR0hcyES+gZhM0tdxCKLJt3CW6Xz6mfa05nwtlpxs0X\nzG/VR3GT3jV/PQEI5AjrbqrC3KiyXKWSm332ic1LRSuL6KoRrax6oK7QyM4EsIug/W7dCVw2phOS\nNDkBbM8Ux4pfJK6FQd0DDb06qoRGmgZ5WuM6oVN38p9+3KwazI20LgFGnjLg1JccOtLoI7iazyY3\n0kEIN+A0o2b5jHG7fC7DBHKaAGenGTdn33qeEjfgnUOtl0EaEMgRBqEqzIlfT+V6kZTk0jZ4aI00\nJ6zj5SnGt+QTHS8UvlBL9RXDtxx4AheO6RVZvzMB7Iu1Z4pv4gpC8avE1UNsn7r3GLJyrkgelUnT\nIE9rXFP8DwN7itxTBpwj6EZBn/3VLfkn1AiuP7p9GMQyp5fgeoqmz6nb9DvNuLlK0kgD44aalA0T\nFgRyREK4XFv8k7KAL8b/eyLXixSatA3ZT1FRbtupvqOXUMdre1/3JilNdLxgn6lA/c6lgCdw4Zi+\nhrD7YcovLzUwUvyicS256x5o6NW5YnmkIU2DPK1xT3PAnib3lAHnJocafZSwB9s+DGKOG3B6Ca6n\naPqc+nm/04ybqyR2aQwBvHNtzztdEwI5IiFcLqAwJ+5pUrdLSnJp6ytxH/IH+WaI31nTCmqMbRok\nUwpzlwKexJUXpyoMbmcWWM4UZ8hA8YvGteRmvactK+eKpSZ3a0o+Xt+enl+fNqz6GiN75Syw8JQR\nzhEc0EdjEKdZbvzeYxWu5XPpNv1Oc25m3EDnZRg2hHAEjDRQYU4daZKSXNrGjkz+IC9d20xBXTVf\nKndyEwJnuBSwiisvTpiYZlWBwUxxDaPYMRrrPSW7ktIawb4MK4DJjIGlpwsIj0KoPY85vQh3v8+A\n8DA30HlHMaQjYKRJ7e8uu+XRizbSJCW5tM2FuxTlcu6YgLpq/hjui7y4vn8pYBVXLMHTucEjGjCa\nKQ4BKiNGa0l+VcXjjtII4uo1iotbF3g6CgwIj0Jgbu7/4/hfV4rTGtwFPgPCw9yEd24GiHsGNvAB\njjQhiMKcNtJ8bDpPp7TNbF7Qe8/zUSWh6qqBPqNAYLMOnF64jstZVhUXjOkWVnVcAYYzxauCcEdB\ng3l1I26EvZ66+hDwpKcVe4RbZejYwVIp+51GuCt83iM/mcKx27tRR+haA2WkSUpyaZu4uqfJU6ew\nfxqFFJp39xkMXF64XoiPpTDuoMAWqhIDw5niqDizYTSWydqFjYCuXhYQP46AZz2l2AiXHrfTSgfZ\n7TTGXeAzBrYdpTl2ezcsBEMV5vBI45cu+PEobSlf9C4qehymNV01dAWAAJpRA9by99ox7uiYDmrD\nwCBjl2kJGmqEBZ66e5qpq5Lt+KVwlzht079Sjit4RxXm8Ejz9uI+55fftKWxeZ8SM4C6aisGaghM\n+U6mIe6Ci5P7rQy1qlfSHMLCjbDAUww8xA1mvhSumwUS5sjDSh/A+O+9qxTm5EiTrkNJSS5tc6wP\nRbkciiNxROCIgBaBWmHOjzRl3ZN7/+rf83OYzJOU5NKWwI0oyqViaM2Ff9L/g2WoUjF7uwACVoJx\nsRUCaMYFEAR6ARqGwFZSs51cAAEruRTukv4IGd+G8XJxw/7Vp/bouiePeSjL4ch2WeHqk66SKNMC\nNAyBrYiCalsAAbEvhesGmv1Kh5DxbRj/uXf19GPx6ylF5VCWc0uH+WQDuHQkRaxvuwCCVLQADUNg\nK6nZTi6AgJVcCtfNa3PtLRsdkrhD4z/37lCW6+kl/u/jO5DCwzR7HMx5MAS25kI9iQUQsJpL4bqR\nBjY6JHGHxn/v3YWV5dQ24MtotozYqoKgAwsgECxfAhPzLKhtAQQhvAANQ2ArqdlOLoCAlVwK1/0z\nn1/xAiu+c+M/9u4yynKpDVRJSLaiJObH1gRGt4PAtGgzPYh7PcKKhqVFqEN2EUNga4nlNHCBMFKq\nkKJFbV7D0kDu8NnwyTysOm2WzBlUCMO7DOBu6F9efn7iUlti7kxGDUs/3St9lOc0o8pyDi6K36lS\nk3xFycYAWxO7sJ0DriDgzhzu1QhrGpYWoQ7ZRQyBrSWU08AFQktZQooWtXkNSwO5w2fNJ9NuOW0C\n5HPw/dnl/Tj7efn1x/DOZ17AwqFEDcuv8rJO/n6aRGxUWa6I32lSk3jNhbSyxaWzwMkRbTuLKwmz\nGmaBGYzcVXQiAaE6hLbUJIBw1UtrjetehmJpWEoI6Za31MAlgpqGpY1rc8NMLORZXFwbsdpOk8wx\nWYeN6MgOxK3GmGHBWi9wSxqWp+1FMcGm3NPMK8spUpN4zQWw1q57jvHdPEPAwTfjawYXEJa1zABL\nFGZRNCwRoTqEpuwignA6IG4l7Z/67rnGtXUiAQRzKu4y4NzkipxjB67pNCZiIk/i4tqYNXYbxWmW\n2e+KsKVTRYFA3gmMYRaARtGwbL01YvNoXlkOS03iNRfIKlxP4RsBBs0iTTGmI7iI8BJgCcItWMMS\nEpIhdM85nVrUAIR7i/nb29uPf1Fw+QDcceACV1ICODYNFlJE1AoWSTWcJrlIshN5GJdU0Ug2nUbl\nRNjSqTIQN4ExzAKMNEXDkrw4D9/T0NXetY+2stzz+fwb/t6i6oBlzQW2lkqE6yl8WBwTAxe4RirG\ndAS31NbAvQxhrGEJCckQtjQsC8R40zQ1LDEwCpwgnJomZOYalgUXYRVby2mS6/XFzzD7+vZ6LF3r\nnsZxS22tVNNpVFCELfe8kLsrbgJjmIUcaYiGJXlxHh5pymvLuYe2shyUmiwwVDOwWEtKuF7Ch8Qx\nS8EaWPcgl8gxHcHNpRuJGWBrpriiEwlZ8BDOyDkiYI5raFgWiKppgKcCOEfQYfQJKZbKYspyOnWQ\niptAkYYpXOCzRDacToRLQRG2cqq4TH1xExhtFsgRDkE1LJNujuPjR5r31/ouufgiU6Y2wmmnhiXn\nnX+0jwCTF69LF5IlxXQn4QRXthPA5kzxh9GwRJ6KNk8R9DEFco4l1M1UQ8MydxBLwxJVMIyLfJbA\nTaczYVJOhK0aafriJjCaLKAjHIJqWJLJr1/u1rEMPN3KckBlMVJUlBuTApq/R/V3q+HLVU1eQaGJ\nBk4B05clAbK+vWZwqzFdwZ0BrmeKI2BFwzLFdeuAWghdvN2vAwUiNULdNJWnOu4wcO2pAky6u5Rz\nrHuNplDqA9JyOnYQ3WnUCFuUh3FrnzVgw2nao5WwpZ7naYK4VU2KBSjzWYEhakcwBNOw9P9Phg/+\n9ZSOyq15T4M1LIkCGtEMHBqoR4Ddc/leZbkoUPXk/7Il1DBhOKaLIMUuM0LYnimONSwJzUKjvshY\nco6kEYj/yNMa9zQHjDxlwLS7p7lfhBohXHxmKYsb6SAEGTldA8/hIp9rXL9XRhrgNCGcS4qwtSGg\ndwKjyQI6UkNwDcs8qUeMNOUuI73WPG2Dh9ZIo2hYeorx7Z5EM3AkfLuBcwOlxBbTIVw2picktp0A\n9gjtmeJYJ5LEtZCom35SdhEsNqxxJ3UikacMmJx0vXKOxfkttc7pGnkOF/lc4/q9fI73Oi3C1oaA\nnVdgGCxAN60hag1Lsl6VjTTkepE6ftpuoTGV5aDU5PZm7U1ZzlAjrHmTFtgLvPEn3zGmI7hwTCeQ\nW3IC2BdszxTfBFeYhiWNa6FRh3BSzhEsNqxxd2hYcrzToKgAACAASURBVE8ZcDnpoBYjuj4V57fU\nOqdr5Dlcj8F9rnH9XjrHu50WYWtDwM4rMAwWwBEB4XxJGpbhhnFzlY00pRWTolzabtlVZbkcKKhh\nuQ1t24RBIpRYaovobiN5R9/3ApcqkivbWroxXEfQXII3RRgoZNSMkYYljWvJXYdwTs7Ro3FPa9x5\nDUsxJ54B576EtRhRrynOb6l1TtfI07jC5xrX78Vu0++0CJsFIZtUnm4GC9BNJY2iYfmb3uAp1HJL\nKyZFubSNkSGDVBWrLH6naFj6f7e2Yb0SSpSPUzjvZcAVXVtqUiGcvGBoZHeSsDUP3r8Q7uU5TNot\nEexSlpuWc+SXYd40k8DSUwacI9gv50jivyUnuZnNO4krfeaMJ5xmYbNlMIF3DMNkARxhEM6xomHZ\nmiMcz/2kKJe2OTCXVpaTvHPVILFd1OMfWfS4HMLoUTOt4oIx3QSjGTRgNFOclsNpjDYWwnJxYXWI\ny/AoLn4sDzwdBd7ZuMFPBUM4zYJi7kJc4LMJxDNI4NGw+YuVQK1fjMcP833kSIvGLSvLjYnqqdJq\nO4U6VFwwpvPWaO4rwJ3z4Dk0RhsLoTbSSE9HceFIgzwdBZYnHQ+MvY87iHTaRqpzIFzkc12qY08C\nj4YNLJptClBKUtCRBg261kB5TpMU5dK2VHooy7F1hyU0XSn4b1HnPHhZAUaT+ZoWeOKiq1cTBRxE\nwH0z/gEYMSFccrgjWd7MX2Xe7TTGXeAzBq7Imzu7vRvupoeynNkoJyzZBsd0G4zmwMA0x0h6CZq8\nWvrJcXKF5QixkBcBD4OAApfCXeI04Hsbpit4dyjLdTQ9FIBbcHFyv5UPZbmO+OtZVlzeMfqK5sXI\nt2D9994dynK30O4HhyMCDx6B/4SyXL3EY6ZF9yMotR7ASmCuZMbtga1DFBdAkPoWoC2AIITs5H9B\nWQ4u8bBDQ3LsRyBgNHkA02hcP43bA1uH2C6AIPUtQFsAQQh1JOs/0MV/TwnhrpXl4BKP5FnXdj+C\nUs0BrATmSmbcHtg6RHEBBKlvAdoCCEKoI/lfUJaDSzw6YlOy7EcoWFXqAK7CcfUd3B7YOkR2AQSp\nbwHaAghCqCf5H1GW46t2ekJT59mPUOPlvQM4h+ImErg9sHWI8AIIUt8CtAUQhJCZvCtluQ4pL74+\nZwsAtubgTONmBDOhinMZ1AiwqnpH8pCkBdzhNEEjSQN4GpdUYSTVYBrlyGE1mNg7bCV4OTkInMtp\niUkJwQKnBqvfJxWi1NJI3aGyXIeUl1zM4UOArTk407gZQU9Y4lwGNQ8cIVSZPly5Bdzh9BTwNC6u\nrbJawawy4x0rmDhs2FrVMAdcQYCdWQlBB2UFq98nVZwOEAamO1SWs6W88FIVaa0Xgs3iyqjWuGv1\nvTSZPsnCW6TPLJ/tNCsQdy3gWVxcG7FOKZ2R8i5ZILRgYu+wlWDPAhMInOyWELxkz9PE6QBlRsPn\nuEdlOVPKCy/mANY6IJO4XYGOr/hYoO+lqOkBFs4EfGYZTadZ/rhrAk/i4tqYtR1MlhnvRgglmNg7\nbGX4M8AMQu72SwjWPdojtYOFfBIYbQhJ191I1f9muyz3qiznfLmQLtowbl+gY2Mt0PfCqneIRf9K\npYbTu4CHcXFt3NoMJs+M9yMEDiZeDYStHH4CmEPI/X79P3mKN4MFfRIYTQjJ1lkExOleleUm5MvQ\nEg8ZkJZEWEGgemso0hI3NtaWeZ++F5TpKywot8K4HAepltMl+zjwOG6prZVqBrNVsBxLEDCYJWzj\nPk8AF1Zaql9C8KI9L9DjnRdyFjTuVVnOkvJK3lsSYTwgU7hgQjfHzfewgdhefS+oepelVyyfU2zy\n1nB6GngKFwQzE82JdDZ7gwxmJpzzg0SGgMHMBYaDmX6suL8fzudP/5JGDFFZLacHJAQv2/OcOzLe\niD2ncb/Kcq4h3Yv+LGk1UyKMB8RFchgXTeiWuLlnuyp26ntB1bssvWL67AiIT8PpXcDDuCiYgm05\nm90hEcxMWJYjltQeMJg530QwJ4BNp61+nvminy2JkM8kgkVKlqTovU0IyJ5D3K+ynAtLQyIsXdV0\niTAsgBWCPYpbT+ie0/dKhLfWVjBie2OZPj/ZM0ja1D4nhbgArMmXuYO60wpwdSHTgUdx62BquKTn\nS7G0TLjpczOYWaeuDmaXzxPAldPQZ0P/L3iq9Bo6LMtguYkfP2TRo4LRjnetzQMh7lVZzpLyIlc1\nQyKsHnrncNGE7hrXd4TSWEAijBAOnSZ8CYwIAcXptld6bpI2xGcioFOA65ThtAIML2QV8BwuCmYF\nG3ZawaSEZclsaQXzRMJGgmn77NEngG2nsYQgoZn9Er0mEfLU4huDLZ8ERiveJ8i+hrhbZTlLysv7\nLiXrqitHbJk6IHO4HopP6K5xfY7cWEgijBD2ebePwNggsOrd9pryKGnjpTpfnba6/5gvvTScVoBR\nMLcK0/ccbqDcK2njvPPnjh/TijQhJZy4gG0rmC57DlsBPtk++3omgH0x3oO8rXywhCChmbOKXmP0\nvPqGZIMRGM3O68sI9jXE3SrLGVJe9KpGJOvQ2FsHZA7XR5pP6K5xfY7UWEgijBL2ebePwIgQUPWO\nSq8Qn1FfTPhxazitAKNg1sBzuB6DB7PG9XutYFLCsmS2tILpMuWRhgTT9tmjTwD7Ym2nN6eYhKAr\nlWl6iPARvSYRcjdqPsOrG1osnwRGK96hVsFeQLhsW4+I+tOh2Em8NSI5lBTl0nbL/s+V5QwpL3pV\nqyTr5NhbB2QaV0zornF9mGJjQYkwSjiG1G0ERoRoqN5tyjOVz6npCi5LdTkNgGUwa+BpXBHMGtfv\n2cEEGjw1TCuYLmcOWxVMy2fCDbaSDmw5jSQEKZqvOXxEr2kGayvC7yEFRiveHkKyFxAu1zlKbN+T\nslxbyote1YrgWggqH3tZQCZx5SR1hmvoe1HCgWb4YhhZ3wvK9G23RWf/s9HNtf94fXt6fg2Kc/mU\nKcAs1XZaBbYuw6dJXBlMxtcIJiXMS+b9djBdthy2Kpimz4UbbCUV2HYaSAhStOwZ6zWFkKbIB3xi\nGDlYGgRgzyAcvf+Uspwce2VAcpPJxHbrIa+WYEL3EO4JA49hwEc9zod8ykh/+iwasAxmH17KpeCC\nYKYSnVsFuLN0zKaETV68x2CV9ph2WtIc6zWevfRpEAOxb0H8B5Tl5NjbEMCSXUi5WqIJ3UO4blqQ\nv/3YbkhKtWMYmvSK7Iulhq6UBiyD2QWXM2FcFMxcpC+BgfvK5lw4bHt9dvAIeN5piTbWaxwh4NMY\nBmTfgHh8ZbmO1Ya5o+EEvlqWqeu4VIcVA3cUJFkUIRfZF0mZriQGRheyLricCeIuCKa7SO+XtIFh\n2+8zHmnmnYY0c4R7Evt9GmX/+MpycOztaYycZ8nVMqORxMWAXc/+JvWsS+4P5joul0BCYVviMwKe\nd2A32hKfxvg/vrLc6NgL4rfiaglg/W/l/ZdhBHwxwbUFwUR8b8SGw7bAZww86/UCtAU+DbL3s1Tz\nR/7LnS6MX/EPsbTNRcIUqrx3JI4IHBE4IgAicCjLgaBIU71IRB6fthzA06G7SEHcHtg6RGABBKlv\nAdoCCELITpJFVi7z/7mZ7E/h/xC7ZMrxFKZypL2uLV5Hgq1dgCkThsDWVKZnux9BqeUAVgJzJTNu\nD2wdorgAgtS3AG0BBCHUkazfxSd+PdkIT3H+n52z5MDrSLC1lOpIYQhs7YDLWfYjZKg6cQDX8bj2\nHm4PbB3iugCC1LcAbQEEIdSR7FSW0zUswzt/OiqiWfx/u198FgleGkqL2elLAWNcm4+Z4wA2Q/RP\nM+D2wNYhYgsgSH0L0BZAEEI9yS5ludPn0+krPRyuUF/qm6LqWHNHLAINubG1CcQPYghs5WVb+/sR\nFPQDWAnMlcy4PbB1iOICCFLfArQFEISQmexRlnt9dotq+HIsjyz+iuLVDcps8eVJHK5DtAxDYGuG\nn8bNCGZCFecyqBFgNZgkD0lawB1OEzSSNICncUkVRlINplGOHFaDib3DVoKXk4PAuZyW+C8py53+\nvvkl3yAUculEzDQns6XCRdQO0TIMga3ZoWncjKAn1ul7Hcpyplia3gz5yGV6poOfA868lMR/S1ku\n3M68uPsa8dne9cbNszJbciUGW69li5ZJCE9OWmvgWVzuuOtu9a/JEglNnEtSY6AFQhNDYwXirgRm\n3Gyn54BncWVtjHCJhBZMCcEsBUILpgybh8BWAj4LTCBw8r+lLPfm//ymv7JSULa3HqQ9uo0vttir\n38X6milahhdzAGsNPIlLHY7pGtcbYyQGlOUEbDuYInswmD6fTKcngSdxQW2jwQQQ0tQOJgibg8BW\nhj0DzCDk7n9MWe7l+fW1nngTQ0JebcOCFMO+V79L9jV32/DoynIslHmwwsEUuYMBLWsZDOYu4EYj\nYVxklYRjt8IyfQhC2hb1zCXAEoRb/lvKcuExDQ9B2H/5hGZnjO152qnfJfvaf0BZTsS0GcyS2xJD\nGwzmHuA1ynKScIpE4NaldFa8iKkEsbNnCtyZLi9BuOW/pSwH/3UKIflRp+2l9hyR2eJRdvuirxmi\nZRmi0u/K1pLgwFO4YEI3xy1jrq9binMVRo1UO5hZyGXU55Ph9DTwFO6CYGbCjVjmAWFnz5RVtFsp\n569aCTidM/rEf0xZ7km9c/lET4lDqFLYd+p3yRPXLX9+dGW5qq/5nWYws5CLKYY2GMxdwI1Gwrho\ndrwknCLhoyLE0jKwP6p+EsTOninxJ4CR0xXwoSwXw/F305EBmlgx7FgM7ZQuPrV+VyWGBnWqtmp1\n0TIFuLpy6MCjuPWEbg03dUDHHeh7pUhsnoFA+gPNYPrJnpaynMbNldSdVoB3BxPjLghmBvYxOymx\nbAfzUJb7dJ9y/9DsvHWTYcnGQ1muvlwaYmgncrUk4ly+Z/NFFTWu7/Glsfxrr/yHQBDg7Rj8jhB7\nleUYN8Pp7c2jQrIOXYZr4Dnc/cGkhGEYN2MrmIeyHAtcs/OiJmPPOw5lORYQQwwtLMmSinW+VfiE\n7vqk8zlyYwExNArs8yqfDWK3shzjZjhNFWIMlbUaeA7Xu74vmJSwEkhvbgXTc/DqfP5j+Lxlot8T\nwL44d5pCnk6HstwWj2friTAUQ6MXH6J1RVo5R7vuw1Gi6u/5y73bwv3yOjHFLQUYjb01sCGGpuB6\nlnySeo3rc6SRBul7UWCfV/lECBhMKuSyNJgK8O5gKrje9X3BpMBKIL25FUx3OI80JJjIZ1nDBLAH\n4U7XwJtTrJ+7LJlmzj7W8/B6ZoHR6ryhZsFeQLhsh7JcbqUuMbSoSOsG1z/fL6ftVYVilYMMdGys\nAWW5TCslIgTULKNCLpUYmtkXu5zuUparnZ7GXRJMqZWTohi3rWC6LDlsVTCdHS37q6DngIXTFaa7\nqXEd7T38hq0IZZo5e90I3tzqeaGY8ElgWBCSvYBwNR3KciHc4asthkavlpXgmJykzgPdFueiwIUM\nS2UIqFm23RZ1Kctxbm2nVWB5GWbAk7h7g0kJsxCW3XYwXb58ClcNLX0ukFtqElg6zYEPZbkQEfeH\n8/iHXoar0rmVs5X14WzHCRVYimgNAWu4YJL6EK6iLIed06z+1j4+Q6qy7A2m/gxJXMjGnFYI7w6m\nTriKi7EjwxYKCJ8NGHkYAgOnZUlkkWhjjeAxpU+DGIh9C+JQlkNNSW3K1RLN+G8Ia1HEmFaAQU7d\npAm5yL44xu2kAcvL8Bgwxt0fTJWwHjtwRIbNZ5I+g6JtEwJGTrdR0lGJNtYIDgf4NIYB2Tcg6Axg\n8XbPzaHfr+3tNGmb3HWzD+DrscpxnFKuauXOFRezrQowGnttMJID4y4QssDApOaOpCLkIvtiB1aV\nBQPvDiZWnlkQTAxcuWTvwLDt95n8LCMc5p2GNAmyndzv0yj7Q1nObhV8GbbLmTkuBux69tRFwGQM\nL2RmqfvJgMK2xGcEPB+W3WhLfBrjfyjLdcQLX947ClpZLgW8QHsMUx+9kGGUW7XisC3wGQPPhmEB\n2gKfBtn7War5I389pQtjeo1n2uYih7JcDsWROCJwRECLwH9CWU5zvt9eLfbJxbA1H+5JLIAg1SxA\nwxDYSmq2kwsgYCWXwvX/zfzAtzJBGndn/Nfe1aF8TGW5/Z0ALfZxPfHLTaxS17l31boAgtSzAA1D\nYCup2U4ugICVXAp3SfNCxrdhvFzcFP/q196KX09KKWK+A2U5wnYyyVatRhRsHapiAQSpbwEahsBW\nUrOdXAABK7kUrpur5y4k20wqWPGdG/+5d/8FZbn9fcL/Gc1XbbuuCK1DtS2AIPUtQMMQ2EpqtpML\nIGAll8Jd0ryQ8W0YLxc3zb//iLKc5n6/XSwSCUWxtR/V5VwAQepbgIYhsJXUbCcXQMBKLoW7um0g\n+SsaLxc36BTVPNB+Pd2MslzxYLV+V0IexBVrWROO2A4Ci/LcMCk41iH7hn3C1sJqGrhAGClVTs6i\n5l5j+vHx4zTL/EeJ23aQfxvI07i8Hn1fdVovwo+oEIZ3BEeFIHn05PYagzCHO2XSRppbUZZzPC+j\n3zWLK5eOpFDm7WUIzwqOTWvoWZ5OA+dAqYkYwXf/KrgPIefubPENYypABzdc1kCexsW1VVbL6Soz\n3rEgDO88qAWBK+bWv9vLZb6INqUy0lxPWY5xvpR+1yyuXDrCFpjNAjO/5W634Bh755ct+yZ98rVj\nK+E1C0wgYrIOYYmgJicHqNUQ7vUJ/n7m7N9xpcRNsvAWgFxlnMWtQMIOI2w7vQDC8u40w4J1t0Dz\nNb2fZnvvSrApI831lOVkQOMbM4Yk6ySKtMzggqUjrMu4emaAJT1m6RccY01vyr4Bn1zd2EpJTQJT\niJgWIYwRHNDmYxAmN8DCmUynJ3FBbYywy9F2egGE6Z2vY5gF624e4+v3M74wz79hJ36UkeZ6ynKJ\nWNlG37HK2o7FHBO4qDa1y6wl3C84BprePYP+dVf3NP27xNalkE+atSoYdoaBJYS7Y69nXuTujuXk\nIGEB4eppcEMsup0exkW1ScKxP2KnF0DAuAncYRay9dw749JI81q6nDLS+Mc08HNxZTlZa/R9RLJO\nggDLBC5aOqJ2mbWE+wXHQNO3ZN+KT5ZOHYjhODAAkYRT04TMXE6uECZYshWagoSl5LjTLZ8xbrGW\nlCTcdLoULKlBCBi3ghZTwyxk67kXQKSRJryqf0PGIw19r0TN5eLKcnV1fi/7/nE+f4Z3CW+rll/J\n4yaXrdLvquRdJGSwTOFKrEZ7DxC2ZooPCI6Jpjdk37JLdQSzWU9MAQNPRQhz07i6+7T5BITFLUma\njTo9hdvjc+nn2OlEuDSH8NmCKEX1VDv0wBHR3d7dHWoaaZ7OT6kqP9K8v/rzl36kV+koUYZJprhN\nFG9Bv+vp5Tm98J6xJLuLCOvtPRAJc6b4gOCYaHrnc0P2LUfE1KnLOUliGBh5KkKYmsZXJOTkSO0l\nKSDcoQa33EFmnB7G7fK5GiaE05lwcRm083jcCNyWbEIgRwQNv4A7jTRk8uuXG4DKwHPWPpnQBZXl\n5oTBklAbk6yj7w1SgGNMh6TwqjFdU2+bAK5niiPC4X+U0+/5T+1ocn9rII1RS07OP54IpWvgylNE\nKHYJXacOA9eeKoRJdwfafImw5XNDQ889xNkuRbrTkz4j3C6f6UiDnKY9WgmbAVE1qabD1wx97cid\nK8vFDkw20XeosqYowOWORGBEcgIXjenyajoBbM8U/xuGg1//ZNfSqasZGbJv89Jqc8DI05qwa6jS\n3f2Lw/yH+Iwu7/zCanEjHYQgo+bdqk/fc7hdPredJoQTF+6zszfjZnvnkZsQyBFG436U5XIcc2Lz\nHaus0XdWE2Ew1C4ZLyUmcNmYHpDEaRIba5Cwo9xU/cCCY77pxcvLa0aG7Jsrn6+WJILI0xS4uJ0D\n9oW5pzVhlyF3d6TNRwhHJh6y/vtqjpvt9Byup2n6PO4089lV0oyb7Z3n2YTwGbgjLPRvz/5z/n4O\nDULWq7InwuR6kRDT1tfi3plQ/iDfDPk7UoRiaNt7ujcdVqLfBftMBkyJSwFP4KIxXW3vsUi4BxL1\nyZLcj1soOEbjWvLXjAwNPVcsjzSkaZCnpYaQmgP2RbmnNWGXIXV3pM3nDmfCHmz7MIg5brbTc7ie\nounzuNPMZ1dJM262d55nE8Jn4I6wkcZnuQ9luY0p/Y6+N1TWgAIc6IwU06encOWYrrb3GGFzhj0S\nHNsuGWQiZvCxZmTIvrkSOVaVkpn0NICXr2lgMSe+JuxqiE0Dtfko4UKGQUxzk5fsUodLTePaPo87\nzXx29Iy4mU3aASEcgSPNPSjLVQ3rdtr6XVSorRIGy2cPx0v7k7hyTOftPQlszhR3Q9HLc/jPsDhK\n3U+Oue5U3xy1Zd9csRyrAhzAxNWrVBFSk8DSU0Y4R/Bz+4PCP7utqGXChRCDOE1yk81bqrioz6Wf\n9zvNfTbjZnpns5CNx7ubC9PHz/n87B4ourO3/ARiv55yt3t62+bUpG0Is/+6tLJcrqgroSnAlbOn\nC0ZkUnHlrQdvb4FVGTTgrpniFZLfwWhjjHKTc3R59eI5rH0wIsAZ/wsIj0JoHWS305fyGRAe9ll2\nXqsF+XHUTVs0bllZjvvW3leF2nZqVqi4ckxvCGsB7gpw30xxgYfRxhhpI430VFRvGdBZhzxdQHgU\nQpGs2e806ngrfAaEh33e7R1y5NSgQWcAK/c0SVEubUufugtluf2aFf7xmfhTB16QS2i6Uhi4b6a4\nrACjyXxNCxoQ7MWGTcjtIAKe9ZRWh3DpcTutdBB0ybbBSA6Mu8BnDExq7kju9u406sjjK8t1hN3I\nggXg4JhuILHDGJhl6t5dgtZ7Ge5mlTIi4HRsz/ZSuAuad49bFy57Be8eX1luQZtBAbjRMR3xgMAo\nY5dtPxq+Wi7wFAN3edXMdClc9wwyPIFuVn7HB/+9d4ey3B13l4P6EYF7icB1lOXuJToHzyMCRwTW\nROAqynLu/zWkDoitQ34ugID1YVxshQCacQEEgV6AhiGwldRsJxdAwEouhevfT4x6KSRxh8Z/7V09\nrUv892RHcEZZDq/uwlabAcmxAIKglSTGxdZSqiO1AILUsgANQ2ArqdlOLoCAlVwK1w00+yVKIePb\nMP5z766jLAfVAfvWfDXbaQEExMe42AoBNOMCCAK9AA1DYCup2U4ugICVXArXzaCFvRSSuEPjv/fu\nGspyeHUXtg414gIIWB/GxVYIoBkXQBDoBWgYAltJzXZyAQSs5FK4bqTZL1EKGd+G8QreXUlZrl4U\nnqKPreko3apCbf0QFC6nB3H7axsEzoS0hKKQZhHqEEPDENha2E0DFwgjpcqbWdTmleUM5A6fDZ/M\nw6rTZsmcQYUwvMsATt/g5eXnJ7+akxzoSl5VWU4uNw+crWV8brL8t3sxmvuEdyI9g1ep2xChPP+a\nxLVrmwTm/Ni+piynxDWX7hFDwz5h6wLgDKElTHkzg5o7Txx00DBw75Zzdyr6i/Y5hTbyPC6vR+6b\nTssi3GJCtL3zcCYErxPuX1NZTlndJVa0sfVaRevqLSwO/dreREndExD0oJaexhW1/SPCqkKaIMQW\n13aIoUkIHzZsLQGdBi4QMVWHsDSNpixnUnOvT5hTlhPINbV5XOEzM3Q4zUq4QaH+c6cDwmrSDgjB\ngtPwGa6pLKeoA8o1Xyx8nvb2LjpFWU4BlgERlincqxFWlOWQ+3UIbTE06ZOPFbaSKM4CE4iYrAk7\nY2waRVnOpnayuUkW3iKcZtRmcXFttdVwus7s9xg3ZzEghHcS04IAJSSNayrLKQv2wJovyTuGDwu1\nKcAgIMI0g3s9wlgWDrovQ7j9kBiA6F5L2lJZA8ESjRAMgnBsGkVkrRe3xQ0TkciCmis4jotrY9a2\n0yyz35Xc2hDSOwDahgAFAI1rKsuV1V1UyatYiwdq+LBQW4GgwAWukYoxHcEttRXcf0QYK8shQqDp\nW2JoBYJGsFiLpyA1DgxAJOHUNCEzV5brpDahLAeQZetO4CKfpa3ptMzeGGm2zHNxG2YhW++qynJl\ndRdV8irWEkjZtNl3JNRWIChwFgApuDI1gVtqK3BrCFvzNxVlOURINH1bDK1A0AgWa/FUpGaA3ZMQ\nMQ9XhDA3jatSKMt1UXN/Pv31s+GVuJUOYjgtqM3gIp9FMNPvlnBAOF0Il4KCWxuiL27N0ENHOI17\nUZbjvPOPz9OAUBt58XppGJ5KMR3A5RB+fwlhc/7moSzn/wrQFVRRywwrwAEQ2bruUbl776TSHrnj\nVYp1ZuuGilN/9DuHstzpgspyhlzWkAJc9S5ERSMstuwQbnVBXki4nr+JCB/Kcu4E/N7+bakkVlGw\nwpnrsrv5EUrcUgfRleW01vU0BnHt1vWEyUhzKMs5Gczn2IpiEwM1IgCXrwAETF5EJoDdnUa3Wu4I\nYXRxWkLYnr95KMv51yb7qWSo15AOFJJzCnCgeVnrzuHaretJl5EGyOmhHs24WRDAuxCr+qvJAjpS\n07gfZbmat4/C5vugUFv3SDOEW1+ctiZaRNh1pUNZLnX63N27leVSybidU4ADzctadw7Xk2q3rs8x\n7DTjZkEA73y17GOwAI7UNO5HWa7m7cMQfR8TauseaU4juGhMX0TYUsg4lOXCY5pfP1/cbtw5BTjQ\nvKx153B9L7Zn56ZzvFtOj3Erp4q77fNVvroFo2NigRaERxWOSBru92VUXwlSxL6Um6p0Tjel235u\nxfeP7RKbtvHw63dMiE0M1Jiemuwzkvci4DWE5Zi+iLCYncr5Hspyf75fTh8+LLLX8GBNK8Dxew/W\nutO41uxc50Ds5/1yeoybDSE7L4+byQJ0U0nDves/jjS/ZbhQR5rXqKCQtpETGaQqllnV6vT0/PLx\n4pUFiBoYVUAzNMI472XAFd1pxTo5pi8ibM/fXbUTOgAAETlJREFUPJTlnp5fw5o/e6RZpizHW3dS\nsc5u3dzPD2W5eKZeWlmONy0bINgullZzmTo6I4OqdlVcOaavIdw1f7Oi6HcwzTFGaqw6LsOCUG2A\njQA8XUS4rtzYg9zkYq9RarjjAZ8NevKwJDzMTXZeWU3bghxp0bhlZbmGThUIApZWcxl3CnWouPLi\ntIQwmJ0KvBUmTHOMkTbSSE9F9ZZBnhxucPx8e3v72Vbnp/JrCCe0vi3uIMLpUWqw4yGf+1iSXJLw\nMDfhHYHvSkJHGjQOZTk7rP7h4KEsN/1+ki3AaKTpm6nabiCE2y7BjypKLuiSzYs29zHuAp8xcJOL\nOLjbu2GZmkNZTjSCMGDJNjimi7JNAwZuFmkcXIImr5b41qPBAx9CwDjnmPVSuAuad8yRf5r7Ct4d\nynIdLQwl2xZcnNxv5Y9anqKDjJ5lPxq+Wi7wFAPrrvQeuRSu+2/2UJbrbYSufIeyXFeYjkxHBI4I\n7InAoSy3J3pH2SMCRwT6IlDfuv8fn7nXAfIUZst0ZCRZqqWJ2Y6t+XBPAkNgaw9eyrMfISGx7QHM\nAnLlXdwe2DpEdQEEqW8B2gIIQshO1i8fFTP3bIA7UJbrW0zWcnU/goJ+ACuBuZIZtwe2DlFcAEHq\nW4C2AIIQ6kj+F5Tl+haTtYK1H0FBP4CVwFzJjNsDW4coLoAg9S1AWwBBCPUk/wPKcmCpXE9kSJ79\nCASMJg9gGo3rp3F7YOsQ2wUQpL4FaAsgCKGu5F0py3VIeeEF+diaAzSNmxHMhCrOZVAjwKo4HclD\nkhZwh9MEjSQN4GlcUoWRVINplCOH1WBi77CV4OXkIHAupyUmJQQLnBqsfp9UiFJLI3WHynI9Ul5i\nHXsIAbam6MzjJgR9a4pztal54Aihq+nh2g3gHqdngOdxcW3UagaTZsZpM5g4bNhKq5gEphAgrUrh\ndRN696+r+ziDP24WQADG0nSHynIdEmF4JSC25phM42aElGALzDrEuSS1GqNAqGp6qfJ6K4Hr4x1O\n1wXSngCuCU/jJnxtWyKhisxpRZO9QKjBFN6FssJa++zeVPDyvL1YZRA4MdO2P/7lMuCNyf2E1GAJ\nCMah+KRCsBJul8XFZ7hHZTlbygsvG8PWEqZZ3IKQUjLQ8UUjA7poAiNCaGp6qe56a/m8Tm+N9S47\nmDXRkT0jmD1QRjBx2KRVNFJ6o4zWShKih22/hKBKaKDnCUbj8ZY07lVZzo2aZ6eUewFdtHFc0TBo\nSI+NNaCLJhorQihqeoCFM3UuoGs53Q0sCLcbCeN2WdvBHIFQgonDBqzS53YrAYgeuv39XCU00PME\no/F4Sxr3qizXlPIqy8bGddEuJIuWLnVbI3bpe4nGiu2NVe9K7xj3uRnMfmBBeAK31NZKpUiEPDyY\nrYLlWIJ4Pp9/wx+vOGzYWmCkzxPABU5L9UsI6oQCNg9WOVW0qr09+QQhYEFB416V5dpSXmVRnCER\nJoI0g+uWR9qyaFVjCYmwQpgwEo2V2xup6Z1eP17DWy7dA+OwrPnVTfTuWx7YdrofmBOewUXBJDGJ\nyRwJty+CWQjLgsWSIVAwS3tYweQ+k7OyH9h0WpHCKzSLXw1CKFgIooClVA4WgoDsOY2Gstz//t//\nl+qJ20pQpzpmqrCMCMBVyHGH8/bmhpRXhqikvLK1nRjGRdMsJWHaWEIiDDISGAkCqt75JbJv/u+F\nGZ9bwewHFoSbjYRxUTBldFIk/BERzAz8/7d3tcuRo0iwzx5fbFx4Ztaxfv9nXQoEFFVZxYfw3NiD\nfrgRglRWQoOsRkpdj+VkCChmKdcVU8e8ANwN2rCsKzRZwiZEhZRYrKaTzDFBCMhe0qBJ8PV6j/D3\n+gPYP3/xN5bHp+bRn0Lt/+AsF87tWHnl+d22CHvY3mOzuO0yS8t7jDUWsAjLhJOkBsYFgV3vaAlW\nfEtXG3N4nV1pJidmR0wDuLmQMwi7jYRxWzGtRnLFLMAx8A4EFpNexZNqh25GT+ok97qhmN1WwsBN\n0JCwZYXHW9dqBFcscUECT86u08KrtulHsKaPNezD5PJK288f8SMbwb3Q69PqSPMSxQ1/Zp976l7T\nzBi1IY8wMUL2rLzYrBZfpp7Mx+DYm0OOn2u41LPZMB2RBOGQV9sbWIQxwpWQwrggoJjplZ4/YhOy\nmJGY9Qwx1QnaAEZitoTXcJGYgnDY9cTkhHXNkuOJyX3qmJj9mAl9AbgfNLYQRK3bNgIjRNSiDwv9\nwxmGitEvRRcCsm9pfFpnuZ6VF8V+vYXzmWwr4y2Lhxh7SUGxreESiFxm2QpNJcqXA/miMcJUNm0K\nI0Fg17v0mvKf4ee4MO3UmAOznm9nJ2gDGInZEl7DJf5STMprN09MTrit1ex5YoaCRTYmZj9mOsMC\nMFXzg36KxiVv9G8HI8RoEkTc2kagLE+sgS9FF4IKKPYtjU/rLNex8uKz2pSJ1houKS2XWbZCU4nc\n3sjfixOmsmlTGBcEdL3jljYsZtQXM/712QnaAEYTWUt4DZdISTEF4bDrickJ65olxxMzFCojDROz\nHzOhLwBTNT/oFNQzjTeMEKNJEHFrG4GyPLEeKKYExP+6EFRQsdc0wr+gn89ZrmPlxWe15xBdMR8D\nYy/X87GMq5ZZaqGvxoIWYZxwJaQwLgjHpi/dTmhiLl+ZCtymhoIGwFrMlvAyrhKz5Ut7fTETYV2z\n5HhihkJFtkbMXsyEvgbcCxpZCHKadOa4tY1AWZ5YqYrryDwCodlrGp/TWc638uKzWmNZB8beKHX5\ns4ir131KoX2LME64cBFLbh8FAtr0pcuidFO/ibl8ZSqwSPlBm8BaTBH0Iq4WU/CtSkC/NU5Y1iz7\nvpihWJGtEbMbc+UGW8kE7gcNLAQ5WolMNEIlBMWK1dQFSQFLiSKWBQHYSxrhTvHf7+9P6b/769om\noKs7wpfu/3lJXi35szD6JM5y4UZ7obyQSJceerYE6z610N75MPAcBrzVE05avjIeAe+YBazF3EIY\niOmxA8dMwqCsmWXIpjrQXMzhdBB4OWiNNk1It6MpinEAsfdo/AHOcmDsNcSD2cZsiZZZOsZaABoD\nz2FY1iu6LwICXpYFrMXcQRiJ6bEDxyzCoKidhWW7G3M4HwJeD1qjzTVCIKRjslWBRyB7h8bXd5Yb\nfQYIyhkz8Ww5tszSRg1HMLBbRR00rFd0X1Q1OxkYGE1kHSBxGOJuEDNM0vctbaBs92PGI8160JCm\n0NnfvR/TLPuv7ywHx16/GcTRLbOlwIy7HwYcenb8fRSd9FbefTFvnf7DKyPZtsSMgNejuY22JaY5\n/l/fWW527AX67ZgtAWy4XbZhGkbAH2a4tkFMxPc3ycOybYgZA69GvQFtQ0yT7GmVatn0HeE8MX6/\nfhDLn6VKXI9W9k7iKHAUOAoABbSzXFqsHIvWofPt7/cnWvCePxnSC63LPdtR4ChwFHAUaJ3l1DWN\nUzMfOs5yWYmVz+bZvRUAq87nA7Yi+aX5WDacO0VsAwQ73wa0DRCMUD95nOX6GoW7Kd8fjyf2bPRI\nnaEyB3hIpl9WCLcHzp0itQGCnW8D2gYIRmggeZzlBkQafBxtBEmUQc/uiSJru58PeC3OzbWwbDh3\n6tQbINj5NqBtgGCERpLHWW5AJVr2It8PMVCtX+QA9zX6lSVwe+DcKV4bINj5NqBtgGCEhpLHWS7I\nNGCGpp6PH1K3FjLNucaBTc+yehae6gEPBM3haroDvIxbz9BLmWL2Ktbjppg4Opxb4WpqErhWNFLH\nWY6EUY+DZLUWbbY6z3yNmJZhCJyb2a7jZgT7s2uG5lMj4K6Y+Owd4JGgV4DXcfHZeG5XTF4Yp7ti\nYtlwLj/FIjCHAOnjLJdESe96kwJVS6pJmy01cInntQZMyxREJIdzC+9l3IKQE4JwVcI05+pQG/Es\nyydvPxWw4DYQdAuY9xRwPpA+l3FbmLAnCA+IqSBERoXY3DOXgQVBtXuc5aIk6a0HSp2Qcb0bY85m\nSz/zJfpa37RMQxA7nFt5r+JWhJwShEP2pcQGfy9LzHzu9lPHLLj1g24B854GzkfS5ypui0J7gnDI\n6YipIXTOx/TMys1qpZ5sminlHGe5pMtbXkKsZLrac79/V+h/X91ZblJMVTxmgAfo9BfXF3MYGBT0\nGgkUx1ma8NWtDLM0jCJyP6xnrgALbnr3OMslTZ7NNSaX7NgMrT7dNe/f5ZqWjQPrNv19nOUUN1fM\nWnqzmOPAtWROeWLmMuFN+9+eaT3X9x/hPdpoM0eaVFiapSEIneeKOd6BbG4TlnWancw5znJJEeBM\nfkmV2/MxbrOFnvlS7embllWInjGYbNEV3HA//EOc5SS3/D9DuAH//v5K30oeXfVT47lViYo2KeY4\ncD1FSvliYtwNYlZgSYjvf1TP9FuptgdvJRQ05/r40s5y7LmnK2juLdPo8Oi6sBxnudoBg3Q3/b2g\nGVoxclkwQwtjV3hromFfNg7cdoq4N42L1qyqodEXsxAGfGpWHmmgmKXYgpgLwCjoQoESRtM0Za6d\nSbEQhM7LMdER1Xkhe0nDcJabfe7pOMul93NSQ0BjrZDPGkubc4lp2Pf3wmZotASr5yxncQs1bTs9\nA7i5kDMIL+C2a1Ytwq6YhXA4ffiSvv4s2yv5m13bBYHFxAZw7aVHh9sMcBM0JPxnOMsh+8qYlxut\nf00DzdAebPJhXlcDdlkd0zIDGI69JQZKrOGiZZZySOcjDb32ijYWM1MiHYN/ry8HFDO9IHTIWU5w\n6wRtAN8W08C9LyYHhjKmTE/M4ywnhKsjO+i8qMnE74XHWU4I2jFD4y/hbPy96Leb9m6m+DaH85TG\nGnaWE+QyxG1nOcGtEzR3iGFBN9OwYkoZa7hU856YnDChGVtqDyxmqFJem9mJWYgZai4AE0UZNOXV\n7TjLJS2eqq1CFSemru8XNEPjk8+cXVbHtMwAhmNvw3cNlyDk0lGrA4bL8nhF8y08FV5j5oQbQu2O\nJyY3cqnAoX75yhQswa0TtAF8W0wDl1jeE5MDl5h1whMzlC6yMTFRzELMUHMBmNjJoCmvbimo4yz3\nrbueJv5U8ka/ZVanLj751NxQpLRyUVq055Bp2eUc+3md5Ur0OXH14bvOcitiDjnLZZ7pc6iREK5a\neywIB/hLCcemT3vltOwyBBQzFC19sOmZIX/04nUSWAUt6B5nuShIvOMgpKHdYkkFbbb45NP4d5VW\nLpCyr/mmZSZwb+Z4LOLqdZ+ScFECmnNxwiVmmSgQUMx0WTTkLCe5+UGbwDfFNHHvismBpYZl3xcz\nFCt9sOmZOmYp5iKwDrpQvRLHWS4KcZzl/sd+1qCO2r5aTHYbsZ+u7rrTsKjV7tKlffztqc2uX5mS\nP8eN35wqEDHRm4bb0mrPIDy4qFnB1QwDuBYYSZWRpi2sYp4Ukw1hHBgEzQ/baU1zmlD4Rc3GHzqC\n2Hs0jrNcT1ZjtqwLSiuAY6xVC5WUAVyOjyQsIxfdF+e4PSzg/jTs08a498U0Cft0xFEtGxXQMU+K\niUcaFLTgY+xqmtOEdEzGuaxsyN6hcZzlLCVrPp4t67rPWnIyhYHnQAwjF90X52DplSDIqA1NZHPI\nEHeDmAbhOXJQtvsx45FmPWhIcyrS+zHNsj/Ocv0GwtNwv163xIcBh55t3q3vsvIKwInMq/DJjiHZ\ntsSMgNe1uY22JaY5/tpZLq7Oe4ooceh8eQ7b+/Nb/uT4/zWfseSlZBrOatXzRRYf34fAs2MvOB3E\nBeWmsz4KeIeYMJgNYkLc3yMTy7YhZgy8GvQGtA0xTbKnVaq0/UwrgukB27glF6cydGZHufyZKoW/\nx1muSHESR4GjgKVAcZZ7SwNMU64OndlRLn+yYsdZjolxkkeBowBUoHWWg0VO5lHgKHAU2K3Av/JI\neb8Jt4YoAAAAAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}\\frac{\\rho}{12} \\left(9 u_{0}^{2} u_{1}^{2} + 9 u_{0}^{2} u_{2}^{2} - 6 u_{0}^{2} + 9 u_{1}^{2} u_{2}^{2} - 6 u_{1}^{2} - 6 u_{2}^{2} + 4\\right)\\\\\\frac{\\rho}{72} \\left(- 18 u_{0}^{2} u_{1}^{2} - 18 u_{0}^{2} u_{1} + 9 u_{0}^{2} u_{2}^{2} - 6 u_{0}^{2} - 18 u_{1}^{2} u_{2}^{2} + 12 u_{1}^{2} - 18 u_{1} u_{2}^{2} + 12 u_{1} - 6 u_{2}^{2} + 4\\right)\\\\\\frac{\\rho}{72} \\left(- 18 u_{0}^{2} u_{1}^{2} + 18 u_{0}^{2} u_{1} + 9 u_{0}^{2} u_{2}^{2} - 6 u_{0}^{2} - 18 u_{1}^{2} u_{2}^{2} + 12 u_{1}^{2} + 18 u_{1} u_{2}^{2} - 12 u_{1} - 6 u_{2}^{2} + 4\\right)\\\\\\frac{\\rho}{72} \\left(- 18 u_{0}^{2} u_{1}^{2} - 18 u_{0}^{2} u_{2}^{2} + 12 u_{0}^{2} + 18 u_{0} u_{1}^{2} + 18 u_{0} u_{2}^{2} - 12 u_{0} + 9 u_{1}^{2} u_{2}^{2} - 6 u_{1}^{2} - 6 u_{2}^{2} + 4\\right)\\\\\\frac{\\rho}{72} \\left(- 18 u_{0}^{2} u_{1}^{2} - 18 u_{0}^{2} u_{2}^{2} + 12 u_{0}^{2} - 18 u_{0} u_{1}^{2} - 18 u_{0} u_{2}^{2} + 12 u_{0} + 9 u_{1}^{2} u_{2}^{2} - 6 u_{1}^{2} - 6 u_{2}^{2} + 4\\right)\\\\\\frac{\\rho}{72} \\left(9 u_{0}^{2} u_{1}^{2} - 18 u_{0}^{2} u_{2}^{2} - 18 u_{0}^{2} u_{2} - 6 u_{0}^{2} - 18 u_{1}^{2} u_{2}^{2} - 18 u_{1}^{2} u_{2} - 6 u_{1}^{2} + 12 u_{2}^{2} + 12 u_{2} + 4\\right)\\\\\\frac{\\rho}{72} \\left(9 u_{0}^{2} u_{1}^{2} - 18 u_{0}^{2} u_{2}^{2} + 18 u_{0}^{2} u_{2} - 6 u_{0}^{2} - 18 u_{1}^{2} u_{2}^{2} + 18 u_{1}^{2} u_{2} - 6 u_{1}^{2} + 12 u_{2}^{2} - 12 u_{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(36 u_{0}^{2} u_{1}^{2} + 36 u_{0}^{2} u_{1} - 18 u_{0}^{2} u_{2}^{2} + 12 u_{0}^{2} - 36 u_{0} u_{1}^{2} - 36 u_{0} u_{1} + 18 u_{0} u_{2}^{2} - 12 u_{0} - 18 u_{1}^{2} u_{2}^{2} + 12 u_{1}^{2} - 18 u_{1} u_{2}^{2} + 12 u_{1} - 6 u_{2}^{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(36 u_{0}^{2} u_{1}^{2} + 36 u_{0}^{2} u_{1} - 18 u_{0}^{2} u_{2}^{2} + 12 u_{0}^{2} + 36 u_{0} u_{1}^{2} + 36 u_{0} u_{1} - 18 u_{0} u_{2}^{2} + 12 u_{0} - 18 u_{1}^{2} u_{2}^{2} + 12 u_{1}^{2} - 18 u_{1} u_{2}^{2} + 12 u_{1} - 6 u_{2}^{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(36 u_{0}^{2} u_{1}^{2} - 36 u_{0}^{2} u_{1} - 18 u_{0}^{2} u_{2}^{2} + 12 u_{0}^{2} - 36 u_{0} u_{1}^{2} + 36 u_{0} u_{1} + 18 u_{0} u_{2}^{2} - 12 u_{0} - 18 u_{1}^{2} u_{2}^{2} + 12 u_{1}^{2} + 18 u_{1} u_{2}^{2} - 12 u_{1} - 6 u_{2}^{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(36 u_{0}^{2} u_{1}^{2} - 36 u_{0}^{2} u_{1} - 18 u_{0}^{2} u_{2}^{2} + 12 u_{0}^{2} + 36 u_{0} u_{1}^{2} - 36 u_{0} u_{1} - 18 u_{0} u_{2}^{2} + 12 u_{0} - 18 u_{1}^{2} u_{2}^{2} + 12 u_{1}^{2} + 18 u_{1} u_{2}^{2} - 12 u_{1} - 6 u_{2}^{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(- 18 u_{0}^{2} u_{1}^{2} - 18 u_{0}^{2} u_{1} - 18 u_{0}^{2} u_{2}^{2} - 18 u_{0}^{2} u_{2} - 6 u_{0}^{2} + 36 u_{1}^{2} u_{2}^{2} + 36 u_{1}^{2} u_{2} + 12 u_{1}^{2} + 36 u_{1} u_{2}^{2} + 36 u_{1} u_{2} + 12 u_{1} + 12 u_{2}^{2} + 12 u_{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(- 18 u_{0}^{2} u_{1}^{2} + 18 u_{0}^{2} u_{1} - 18 u_{0}^{2} u_{2}^{2} - 18 u_{0}^{2} u_{2} - 6 u_{0}^{2} + 36 u_{1}^{2} u_{2}^{2} + 36 u_{1}^{2} u_{2} + 12 u_{1}^{2} - 36 u_{1} u_{2}^{2} - 36 u_{1} u_{2} - 12 u_{1} + 12 u_{2}^{2} + 12 u_{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(- 18 u_{0}^{2} u_{1}^{2} + 36 u_{0}^{2} u_{2}^{2} + 36 u_{0}^{2} u_{2} + 12 u_{0}^{2} + 18 u_{0} u_{1}^{2} - 36 u_{0} u_{2}^{2} - 36 u_{0} u_{2} - 12 u_{0} - 18 u_{1}^{2} u_{2}^{2} - 18 u_{1}^{2} u_{2} - 6 u_{1}^{2} + 12 u_{2}^{2} + 12 u_{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(- 18 u_{0}^{2} u_{1}^{2} + 36 u_{0}^{2} u_{2}^{2} + 36 u_{0}^{2} u_{2} + 12 u_{0}^{2} - 18 u_{0} u_{1}^{2} + 36 u_{0} u_{2}^{2} + 36 u_{0} u_{2} + 12 u_{0} - 18 u_{1}^{2} u_{2}^{2} - 18 u_{1}^{2} u_{2} - 6 u_{1}^{2} + 12 u_{2}^{2} + 12 u_{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(- 18 u_{0}^{2} u_{1}^{2} - 18 u_{0}^{2} u_{1} - 18 u_{0}^{2} u_{2}^{2} + 18 u_{0}^{2} u_{2} - 6 u_{0}^{2} + 36 u_{1}^{2} u_{2}^{2} - 36 u_{1}^{2} u_{2} + 12 u_{1}^{2} + 36 u_{1} u_{2}^{2} - 36 u_{1} u_{2} + 12 u_{1} + 12 u_{2}^{2} - 12 u_{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(- 18 u_{0}^{2} u_{1}^{2} + 18 u_{0}^{2} u_{1} - 18 u_{0}^{2} u_{2}^{2} + 18 u_{0}^{2} u_{2} - 6 u_{0}^{2} + 36 u_{1}^{2} u_{2}^{2} - 36 u_{1}^{2} u_{2} + 12 u_{1}^{2} - 36 u_{1} u_{2}^{2} + 36 u_{1} u_{2} - 12 u_{1} + 12 u_{2}^{2} - 12 u_{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(- 18 u_{0}^{2} u_{1}^{2} + 36 u_{0}^{2} u_{2}^{2} - 36 u_{0}^{2} u_{2} + 12 u_{0}^{2} + 18 u_{0} u_{1}^{2} - 36 u_{0} u_{2}^{2} + 36 u_{0} u_{2} - 12 u_{0} - 18 u_{1}^{2} u_{2}^{2} + 18 u_{1}^{2} u_{2} - 6 u_{1}^{2} + 12 u_{2}^{2} - 12 u_{2} + 4\\right)\\\\\\frac{\\rho}{144} \\left(- 18 u_{0}^{2} u_{1}^{2} + 36 u_{0}^{2} u_{2}^{2} - 36 u_{0}^{2} u_{2} + 12 u_{0}^{2} - 18 u_{0} u_{1}^{2} + 36 u_{0} u_{2}^{2} - 36 u_{0} u_{2} + 12 u_{0} - 18 u_{1}^{2} u_{2}^{2} + 18 u_{1}^{2} u_{2} - 6 u_{1}^{2} + 12 u_{2}^{2} - 12 u_{2} + 4\\right)\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡                                           ⎛    2   2       2   2       2    \n",
+       "⎢                                         ρ⋅⎝9⋅u₀ ⋅u₁  + 9⋅u₀ ⋅u₂  - 6⋅u₀  + 9\n",
+       "⎢                                         ────────────────────────────────────\n",
+       "⎢                                                                         12  \n",
+       "⎢                                                                             \n",
+       "⎢                        ⎛       2   2        2          2   2       2        \n",
+       "⎢                      ρ⋅⎝- 18⋅u₀ ⋅u₁  - 18⋅u₀ ⋅u₁ + 9⋅u₀ ⋅u₂  - 6⋅u₀  - 18⋅u₁\n",
+       "⎢                      ───────────────────────────────────────────────────────\n",
+       "⎢                                                                        72   \n",
+       "⎢                                                                             \n",
+       "⎢                        ⎛       2   2        2          2   2       2        \n",
+       "⎢                      ρ⋅⎝- 18⋅u₀ ⋅u₁  + 18⋅u₀ ⋅u₁ + 9⋅u₀ ⋅u₂  - 6⋅u₀  - 18⋅u₁\n",
+       "⎢                      ───────────────────────────────────────────────────────\n",
+       "⎢                                                                        72   \n",
+       "⎢                                                                             \n",
+       "⎢                        ⎛       2   2        2   2        2           2      \n",
+       "⎢                      ρ⋅⎝- 18⋅u₀ ⋅u₁  - 18⋅u₀ ⋅u₂  + 12⋅u₀  + 18⋅u₀⋅u₁  + 18⋅\n",
+       "⎢                      ───────────────────────────────────────────────────────\n",
+       "⎢                                                                        72   \n",
+       "⎢                                                                             \n",
+       "⎢                        ⎛       2   2        2   2        2           2      \n",
+       "⎢                      ρ⋅⎝- 18⋅u₀ ⋅u₁  - 18⋅u₀ ⋅u₂  + 12⋅u₀  - 18⋅u₀⋅u₁  - 18⋅\n",
+       "⎢                      ───────────────────────────────────────────────────────\n",
+       "⎢                                                                        72   \n",
+       "⎢                                                                             \n",
+       "⎢                         ⎛    2   2        2   2        2          2        2\n",
+       "⎢                       ρ⋅⎝9⋅u₀ ⋅u₁  - 18⋅u₀ ⋅u₂  - 18⋅u₀ ⋅u₂ - 6⋅u₀  - 18⋅u₁ \n",
+       "⎢                       ──────────────────────────────────────────────────────\n",
+       "⎢                                                                        72   \n",
+       "⎢                                                                             \n",
+       "⎢                         ⎛    2   2        2   2        2          2        2\n",
+       "⎢                       ρ⋅⎝9⋅u₀ ⋅u₁  - 18⋅u₀ ⋅u₂  + 18⋅u₀ ⋅u₂ - 6⋅u₀  - 18⋅u₁ \n",
+       "⎢                       ──────────────────────────────────────────────────────\n",
+       "⎢                                                                        72   \n",
+       "⎢                                                                             \n",
+       "⎢   ⎛     2   2        2           2   2        2           2                 \n",
+       "⎢ ρ⋅⎝36⋅u₀ ⋅u₁  + 36⋅u₀ ⋅u₁ - 18⋅u₀ ⋅u₂  + 12⋅u₀  - 36⋅u₀⋅u₁  - 36⋅u₀⋅u₁ + 18⋅\n",
+       "⎢ ────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢   ⎛     2   2        2           2   2        2           2                 \n",
+       "⎢ ρ⋅⎝36⋅u₀ ⋅u₁  + 36⋅u₀ ⋅u₁ - 18⋅u₀ ⋅u₂  + 12⋅u₀  + 36⋅u₀⋅u₁  + 36⋅u₀⋅u₁ - 18⋅\n",
+       "⎢ ────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢   ⎛     2   2        2           2   2        2           2                 \n",
+       "⎢ ρ⋅⎝36⋅u₀ ⋅u₁  - 36⋅u₀ ⋅u₁ - 18⋅u₀ ⋅u₂  + 12⋅u₀  - 36⋅u₀⋅u₁  + 36⋅u₀⋅u₁ + 18⋅\n",
+       "⎢ ────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢   ⎛     2   2        2           2   2        2           2                 \n",
+       "⎢ ρ⋅⎝36⋅u₀ ⋅u₁  - 36⋅u₀ ⋅u₁ - 18⋅u₀ ⋅u₂  + 12⋅u₀  + 36⋅u₀⋅u₁  - 36⋅u₀⋅u₁ - 18⋅\n",
+       "⎢ ────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢  ⎛       2   2        2           2   2        2          2        2   2    \n",
+       "⎢ρ⋅⎝- 18⋅u₀ ⋅u₁  - 18⋅u₀ ⋅u₁ - 18⋅u₀ ⋅u₂  - 18⋅u₀ ⋅u₂ - 6⋅u₀  + 36⋅u₁ ⋅u₂  + 3\n",
+       "⎢─────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢  ⎛       2   2        2           2   2        2          2        2   2    \n",
+       "⎢ρ⋅⎝- 18⋅u₀ ⋅u₁  + 18⋅u₀ ⋅u₁ - 18⋅u₀ ⋅u₂  - 18⋅u₀ ⋅u₂ - 6⋅u₀  + 36⋅u₁ ⋅u₂  + 3\n",
+       "⎢─────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢  ⎛       2   2        2   2        2           2           2           2    \n",
+       "⎢ρ⋅⎝- 18⋅u₀ ⋅u₁  + 36⋅u₀ ⋅u₂  + 36⋅u₀ ⋅u₂ + 12⋅u₀  + 18⋅u₀⋅u₁  - 36⋅u₀⋅u₂  - 3\n",
+       "⎢─────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢  ⎛       2   2        2   2        2           2           2           2    \n",
+       "⎢ρ⋅⎝- 18⋅u₀ ⋅u₁  + 36⋅u₀ ⋅u₂  + 36⋅u₀ ⋅u₂ + 12⋅u₀  - 18⋅u₀⋅u₁  + 36⋅u₀⋅u₂  + 3\n",
+       "⎢─────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢  ⎛       2   2        2           2   2        2          2        2   2    \n",
+       "⎢ρ⋅⎝- 18⋅u₀ ⋅u₁  - 18⋅u₀ ⋅u₁ - 18⋅u₀ ⋅u₂  + 18⋅u₀ ⋅u₂ - 6⋅u₀  + 36⋅u₁ ⋅u₂  - 3\n",
+       "⎢─────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢  ⎛       2   2        2           2   2        2          2        2   2    \n",
+       "⎢ρ⋅⎝- 18⋅u₀ ⋅u₁  + 18⋅u₀ ⋅u₁ - 18⋅u₀ ⋅u₂  + 18⋅u₀ ⋅u₂ - 6⋅u₀  + 36⋅u₁ ⋅u₂  - 3\n",
+       "⎢─────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢  ⎛       2   2        2   2        2           2           2           2    \n",
+       "⎢ρ⋅⎝- 18⋅u₀ ⋅u₁  + 36⋅u₀ ⋅u₂  - 36⋅u₀ ⋅u₂ + 12⋅u₀  + 18⋅u₀⋅u₁  - 36⋅u₀⋅u₂  + 3\n",
+       "⎢─────────────────────────────────────────────────────────────────────────────\n",
+       "⎢                                                                        144  \n",
+       "⎢                                                                             \n",
+       "⎢  ⎛       2   2        2   2        2           2           2           2    \n",
+       "⎢ρ⋅⎝- 18⋅u₀ ⋅u₁  + 36⋅u₀ ⋅u₂  - 36⋅u₀ ⋅u₂ + 12⋅u₀  - 18⋅u₀⋅u₁  + 36⋅u₀⋅u₂  - 3\n",
+       "⎢─────────────────────────────────────────────────────────────────────────────\n",
+       "⎣                                                                        144  \n",
+       "\n",
+       "   2   2       2       2    ⎞                                         ⎤\n",
+       "⋅u₁ ⋅u₂  - 6⋅u₁  - 6⋅u₂  + 4⎠                                         ⎥\n",
+       "─────────────────────────────                                         ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "2   2        2           2               2    ⎞                       ⎥\n",
+       " ⋅u₂  + 12⋅u₁  - 18⋅u₁⋅u₂  + 12⋅u₁ - 6⋅u₂  + 4⎠                       ⎥\n",
+       "───────────────────────────────────────────────                       ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "2   2        2           2               2    ⎞                       ⎥\n",
+       " ⋅u₂  + 12⋅u₁  + 18⋅u₁⋅u₂  - 12⋅u₁ - 6⋅u₂  + 4⎠                       ⎥\n",
+       "───────────────────────────────────────────────                       ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "     2               2   2       2       2    ⎞                       ⎥\n",
+       "u₀⋅u₂  - 12⋅u₀ + 9⋅u₁ ⋅u₂  - 6⋅u₁  - 6⋅u₂  + 4⎠                       ⎥\n",
+       "───────────────────────────────────────────────                       ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "     2               2   2       2       2    ⎞                       ⎥\n",
+       "u₀⋅u₂  + 12⋅u₀ + 9⋅u₁ ⋅u₂  - 6⋅u₁  - 6⋅u₂  + 4⎠                       ⎥\n",
+       "───────────────────────────────────────────────                       ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "   2        2          2        2            ⎞                        ⎥\n",
+       "⋅u₂  - 18⋅u₁ ⋅u₂ - 6⋅u₁  + 12⋅u₂  + 12⋅u₂ + 4⎠                        ⎥\n",
+       "──────────────────────────────────────────────                        ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "   2        2          2        2            ⎞                        ⎥\n",
+       "⋅u₂  + 18⋅u₁ ⋅u₂ - 6⋅u₁  + 12⋅u₂  - 12⋅u₂ + 4⎠                        ⎥\n",
+       "──────────────────────────────────────────────                        ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "     2                2   2        2           2               2    ⎞ ⎥\n",
+       "u₀⋅u₂  - 12⋅u₀ - 18⋅u₁ ⋅u₂  + 12⋅u₁  - 18⋅u₁⋅u₂  + 12⋅u₁ - 6⋅u₂  + 4⎠ ⎥\n",
+       "───────────────────────────────────────────────────────────────────── ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "     2                2   2        2           2               2    ⎞ ⎥\n",
+       "u₀⋅u₂  + 12⋅u₀ - 18⋅u₁ ⋅u₂  + 12⋅u₁  - 18⋅u₁⋅u₂  + 12⋅u₁ - 6⋅u₂  + 4⎠ ⎥\n",
+       "───────────────────────────────────────────────────────────────────── ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "     2                2   2        2           2               2    ⎞ ⎥\n",
+       "u₀⋅u₂  - 12⋅u₀ - 18⋅u₁ ⋅u₂  + 12⋅u₁  + 18⋅u₁⋅u₂  - 12⋅u₁ - 6⋅u₂  + 4⎠ ⎥\n",
+       "───────────────────────────────────────────────────────────────────── ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "     2                2   2        2           2               2    ⎞ ⎥\n",
+       "u₀⋅u₂  + 12⋅u₀ - 18⋅u₁ ⋅u₂  + 12⋅u₁  + 18⋅u₁⋅u₂  - 12⋅u₁ - 6⋅u₂  + 4⎠ ⎥\n",
+       "───────────────────────────────────────────────────────────────────── ⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "    2           2           2                           2            ⎞⎥\n",
+       "6⋅u₁ ⋅u₂ + 12⋅u₁  + 36⋅u₁⋅u₂  + 36⋅u₁⋅u₂ + 12⋅u₁ + 12⋅u₂  + 12⋅u₂ + 4⎠⎥\n",
+       "──────────────────────────────────────────────────────────────────────⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "    2           2           2                           2            ⎞⎥\n",
+       "6⋅u₁ ⋅u₂ + 12⋅u₁  - 36⋅u₁⋅u₂  - 36⋅u₁⋅u₂ - 12⋅u₁ + 12⋅u₂  + 12⋅u₂ + 4⎠⎥\n",
+       "──────────────────────────────────────────────────────────────────────⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "                       2   2        2          2        2            ⎞⎥\n",
+       "6⋅u₀⋅u₂ - 12⋅u₀ - 18⋅u₁ ⋅u₂  - 18⋅u₁ ⋅u₂ - 6⋅u₁  + 12⋅u₂  + 12⋅u₂ + 4⎠⎥\n",
+       "──────────────────────────────────────────────────────────────────────⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "                       2   2        2          2        2            ⎞⎥\n",
+       "6⋅u₀⋅u₂ + 12⋅u₀ - 18⋅u₁ ⋅u₂  - 18⋅u₁ ⋅u₂ - 6⋅u₁  + 12⋅u₂  + 12⋅u₂ + 4⎠⎥\n",
+       "──────────────────────────────────────────────────────────────────────⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "    2           2           2                           2            ⎞⎥\n",
+       "6⋅u₁ ⋅u₂ + 12⋅u₁  + 36⋅u₁⋅u₂  - 36⋅u₁⋅u₂ + 12⋅u₁ + 12⋅u₂  - 12⋅u₂ + 4⎠⎥\n",
+       "──────────────────────────────────────────────────────────────────────⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "    2           2           2                           2            ⎞⎥\n",
+       "6⋅u₁ ⋅u₂ + 12⋅u₁  - 36⋅u₁⋅u₂  + 36⋅u₁⋅u₂ - 12⋅u₁ + 12⋅u₂  - 12⋅u₂ + 4⎠⎥\n",
+       "──────────────────────────────────────────────────────────────────────⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "                       2   2        2          2        2            ⎞⎥\n",
+       "6⋅u₀⋅u₂ - 12⋅u₀ - 18⋅u₁ ⋅u₂  + 18⋅u₁ ⋅u₂ - 6⋅u₁  + 12⋅u₂  - 12⋅u₂ + 4⎠⎥\n",
+       "──────────────────────────────────────────────────────────────────────⎥\n",
+       "                                                                      ⎥\n",
+       "                                                                      ⎥\n",
+       "                       2   2        2          2        2            ⎞⎥\n",
+       "6⋅u₀⋅u₂ + 12⋅u₀ - 18⋅u₁ ⋅u₂  + 18⋅u₁ ⋅u₂ - 6⋅u₁  + 12⋅u₂  - 12⋅u₂ + 4⎠⎥\n",
+       "──────────────────────────────────────────────────────────────────────⎥\n",
+       "                                                                      ⎦"
+      ]
+     },
+     "execution_count": 158,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expandedToVector(expandedResult, truncate2ndOrder=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Pointwise evaluation property"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 176,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from lbmpy.maxwellian_equilibrium import continuousMaxwellianEquilibrium"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 168,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "uVals = (sp.Rational(1,2), sp.Rational(1,3), sp.Rational(1,4))\n",
+    "rhoVal = 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 171,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "approx = maxwellBoltzmannHermiteApprox.subs({a:b for a,b in zip(sp.symbols(\"u_:3\"), uVals)}) \\\n",
+    "                                      .subs(sp.Symbol(\"rho\"), rhoVal)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 172,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+tWCrCwcOHLyrYet04eC0jgV5WN6JwSen7dbN6TCh6Sn+przDSoUemq5HJ68DBHho8ikp\n6ID4G64hG3Z4J4oPEnQJLj0NcJ6rwzxr3+osTHTjGM6jr4qri33b0iz8bRtSORZkBZ+JTJHyW2kj\nTHFWOTYF/EpgpcsUi3Rk0jjJCAAhHuLlJSUFszYPDfuTD/1BglkE5fLle7c3HR3Lsvb96d75BzyQ\n/vTABGt9M2cXXgyMlCxIqcX/OmTK3wW203jOqKP99ZYynTgavUiZfyjVOIIRIL6rIh1x8ikpSCfs\nnN/2YzPryOqDBEc/hb9eaDo6zNJy/itrazjtiCX96YEB5Z86MWdkAczCAXZ8z2B++zIrqH8HbbkZ\nlTHDBHppfluPeTH+j2aUUxM3AwR4gCCfkoIZ7T0sl30Le3Z9A//zYxuNyB2mqyFkFPiropC5Tz+c\nx3pQ8EV9r+gCK81G9XAd/F2nQnOYiyPDwITYUB7rQSFhPU6LWaYzKuwXRhkkwbcPMcr1h4BJoaE8\n1oVC0pqcDjvvSrNRkcrAyKQWS41w0UfD0BjIEB7rQ2GMupxy0wzNLcJhN9XD2BhIeAsgum8MN2HT\nITzeDYX/AbkJ0YZIroJcAAAAAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\frac{v_{0} v_{1}}{6} + \\frac{v_{0} v_{2}}{8} + \\frac{v_{0}}{2} + \\frac{v_{1} v_{2}}{12} + \\frac{v_{1}}{3} + \\frac{v_{2}}{4} + \\frac{1}{2} \\left(\\theta - \\frac{15}{16}\\right) \\left(v_{2}^{2} - 1\\right) + \\frac{1}{2} \\left(\\theta - \\frac{8}{9}\\right) \\left(v_{1}^{2} - 1\\right) + \\frac{1}{2} \\left(\\theta - \\frac{3}{4}\\right) \\left(v_{0}^{2} - 1\\right) + 1$$"
+      ],
+      "text/plain": [
+       "                                       ⎛    15⎞ ⎛  2    ⎞                     \n",
+       "                                       ⎜θ - ──⎟⋅⎝v₂  - 1⎠             ⎛  2    \n",
+       "v₀⋅v₁   v₀⋅v₂   v₀   v₁⋅v₂   v₁   v₂   ⎝    16⎠             (θ - 8/9)⋅⎝v₁  - 1\n",
+       "───── + ───── + ── + ───── + ── + ── + ────────────────── + ──────────────────\n",
+       "  6       8     2      12    3    4            2                     2        \n",
+       "\n",
+       "                           \n",
+       "⎞             ⎛  2    ⎞    \n",
+       "⎠   (θ - 3/4)⋅⎝v₀  - 1⎠    \n",
+       "─ + ─────────────────── + 1\n",
+       "             2             "
+      ]
+     },
+     "execution_count": 172,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "approx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 177,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAVgAAAAzBAMAAAAgBg1eAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\n",
+      "text/latex": [
+       "$$\\frac{\\sqrt{2} \\rho}{4 \\pi^{\\frac{3}{2}} \\theta^{\\frac{3}{2}}} e^{\\frac{1}{2 \\theta} \\left(- \\left(v_{0} - \\frac{1}{2}\\right)^{2} - \\left(v_{1} - \\frac{1}{3}\\right)^{2} - \\left(v_{2} - \\frac{1}{4}\\right)^{2}\\right)}$$"
+      ],
+      "text/plain": [
+       "                  2             2             2\n",
+       "      - (v₀ - 1/2)  - (v₁ - 1/3)  - (v₂ - 1/4) \n",
+       "      ─────────────────────────────────────────\n",
+       "                         2⋅θ                   \n",
+       "√2⋅ρ⋅ℯ                                         \n",
+       "───────────────────────────────────────────────\n",
+       "                     3/2  3/2                  \n",
+       "                  4⋅π   ⋅θ                     "
+      ]
+     },
+     "execution_count": 177,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "continuousMaxwellianEquilibrium(dim=3, c_s_sq=theta, u = uVals)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "MB Approximation again:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import itertools\n",
+    "from math import factorial\n",
+    "from lbmpy.moments import momentsUpToOrder, momentMultiplicity, MOMENT_SYMBOLS\n",
+    "from lbmpy.maxwellian_equilibrium import *\n",
+    "from lbmpy.stencils import getStencil\n",
+    "from lbmpy.moments import getDefaultMomentSetForStencil, discreteMoment\n",
+    "\n",
+    "dim = 3\n",
+    "order = 4\n",
+    "theta = sp.Symbol(\"theta\")\n",
+    "stencil = getStencil(\"D3Q27\")\n",
+    "\n",
+    "variables = MOMENT_SYMBOLS[:dim]\n",
+    "x, y, z = MOMENT_SYMBOLS\n",
+    "result = 0\n",
+    "for order_i in range(order+1):\n",
+    "    for index in itertools.product(*[range(dim)]*order_i):\n",
+    "        hermP = hermite(index, variables)\n",
+    "        a_i = getMomentsOfContinuousMaxwellianEquilibrium([hermP], dim=dim,c_s_sq=1)[0]\n",
+    "        result += hermP * a_i / factorial(order_i)\n",
+    "\n",
+    "cSym = sp.symbols(\"c_:3\")[:dim]\n",
+    "factorC = sp.sqrt(3)\n",
+    "factorU = sp.sqrt(3)\n",
+    "substitutions = { a: b*factorC for a, b in zip(variables, cSym) } \n",
+    "substitutions.update( { s: s*factorU for s in sp.symbols(\"u_:3\")} )\n",
+    "substitutions\n",
+    "eq = result.subs(substitutions).expand() \n",
+    "#( eq / sp.Symbol(\"rho\") ).expand()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def expandEq(eq, stencil):\n",
+    "    result = []\n",
+    "    weights = getWeights(stencil, c_s_sq=sp.Rational(1,3))\n",
+    "    for w_i, d in zip(weights, stencil):\n",
+    "        result.append( eq.subs( {a: b for a,b in zip(cSym, d)}) * w_i)\n",
+    "    return result\n",
+    "\n",
+    "generated = sp.Matrix(expandEq(eq, stencil)).expand()\n",
+    "ref = sp.Matrix(discreteMaxwellianEquilibrium(stencil, c_s_sq=sp.Rational(1,3), order=order)).expand()\n",
+    "diff = generated - ref"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mom = getDefaultMomentSetForStencil(stencil)\n",
+    "contMom = sp.Matrix(getMomentsOfContinuousMaxwellianEquilibrium(mom, dim=dim, c_s_sq=sp.Rational(1,3), order=order))\n",
+    "discMom = sp.Matrix([discreteMoment(tuple(generated), m, stencil) for m in mom])\n",
+    "(contMom - discMom).expand()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d2q9 = getStencil(\"D2Q9\")\n",
+    "getWeights(d2q9, c_s_sq=sp.Rational(1,3))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Gauss Quadrature\n",
+    "\n",
+    "Gaussian quadrature approximates an integral by:\n",
+    "\n",
+    "$$ \\int w(x) f(x) \\; dx \\approx \\sum\\limits_{a=1}^{n} W_a f(x_a) $$\n",
+    "\n",
+    "Where $w(x)$ is the weight function of a scalar product, and the function to integrate is evaluated at the zeros of corresponding orthogonal polynomials. The integration weights $W_a$ are defined as:\n",
+    "\n",
+    "$$ W_a = \\frac{\\left< H^{(n-1)}, H^{(n-1)} \\right>_w }  \n",
+    "              {H^{(n-1)}(x_a) \\;  \\frac{d}{dx} H^{(n)} \\rvert_{x_a} }  $$\n",
+    "\n",
+    "\n",
+    "This approximation is exact if $f$ is a polynomial of degree $(2n-1)$ or less."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Example: \n",
+    "\n",
+    "To approximate the integral $\\int w(x) \\; x^3 \\; dx$, four evaluation points are required i.e. the zeros of the fourth Hermite polynomial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hermite4zeros = sp.solve(hermite(4, x))\n",
+    "hermite4zeros"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def gaussIntegrationWeights(polynomial, weightFunction, x, order):\n",
+    "    p_n_minus_1 = polynomial(order-1, x)\n",
+    "    p_n = polynomial(order, x)\n",
+    "    numerator = weightedScalarProd(p_n_minus_1, p_n_minus_1, \n",
+    "                                   weightFunction(x), x)\n",
+    "    \n",
+    "    evalPoints = sp.solve(p_n)\n",
+    "    weights = [numerator / p_n_minus_1.subs(x, z) / sp.diff(p_n, x).subs(x, z)\n",
+    "               for z in evalPoints]\n",
+    "    weights = [sp.simplify(w) for w in weights]\n",
+    "    return evalPoints, weights\n",
+    "\n",
+    "def gaussHermiteQuadrature(f, x, order):\n",
+    "    zeros, intWeights = gaussIntegrationWeights(hermite, weightFunction, x, order)\n",
+    "    return sum([f.subs(x, z) * w\n",
+    "                for w, z in zip(intWeights,zeros)])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "List of evaluation points $x_a$ and their weights $W_a$:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for o in range(1, 4):\n",
+    "    xa, wa = gaussIntegrationWeights(hermite, weightFunction, x, o)\n",
+    "    display([o, xa, wa])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sp.sqrt(3).evalf()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Construction via low Mach number expansion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from lbmpy.maxwellian_equilibrium import continuousMaxwellianEquilibrium"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "mb1d = continuousMaxwellianEquilibrium(1)\n",
+    "mb1d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "cite2c": {
+   "citations": {
+    "4426775/NAVD9HT7": {
+     "id": "4426775/NAVD9HT7",
+     "title": "Seeger - Unknown - The cumulant method applied to a mixture of Maxwell gases",
+     "type": "article"
+    },
+    "4426775/WKNQD5EE": {
+     "author": [
+      {
+       "family": "der",
+       "given": "Von"
+      },
+      {
+       "family": "Dr-Ing habil Manfred Krafczyk Dr-Ing habil Marcus Magnor",
+       "given": "Berichterstatter"
+      }
+     ],
+     "id": "4426775/WKNQD5EE",
+     "issued": {
+      "year": "2011"
+     },
+     "title": "Ein integrierter Softwareansatz zur interaktiven Exploration und Steuerung von Strömungssimulationen auf Many-Core-Architekturen",
+     "type": "article-journal"
+    }
+   }
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/full_scenarios/shear_wave/Evaluation.ipynb b/lbmpy_tests/full_scenarios/shear_wave/Evaluation.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..32c88b82be53ee3023cd5adb20feecdf772a8d5b
--- /dev/null
+++ b/lbmpy_tests/full_scenarios/shear_wave/Evaluation.ipynb
@@ -0,0 +1,820 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "from pystencils.runhelper.db import removeConstantColumns\n",
+    "from pystencils.runhelper import Database\n",
+    "\n",
+    "%matplotlib inline\n",
+    "\n",
+    "db = Database(\"./shear_wave_db\")\n",
+    "db.pandasColumnsToIgnore = ['changedParams.', 'params.optimizationParams.',\n",
+    "                            'env.cpuCompilerConfig', 'env.timestamp']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def cleanupDb():\n",
+    "    allData = db.filter({})\n",
+    "    for d in allData:\n",
+    "        params = d.params\n",
+    "        if 'optimizationParams' not in params:\n",
+    "            params['optimizationParams'] = {}\n",
+    "        newParams, newOptParams = updateWithDefaultParameters(params, params['optimizationParams'], False)\n",
+    "        d.params = newParams\n",
+    "        d.params['optimizationParams'] = newOptParams\n",
+    "        if d.params['stencil'] == 'D2Q9':\n",
+    "            d.params['stencil'] = 'D3Q27'\n",
+    "        d.save()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def cleanupMethodColumn(df):\n",
+    "    df = df.copy()\n",
+    "    df.insert(0, 'tmp', np.nan)\n",
+    "    df.loc[(df.method=='mrt3') & (df.cumulant==True), 'tmp'] = 'cumulant'        \n",
+    "    df.loc[(df.method=='mrt3') & (df.cumulant==False), 'tmp'] = 'mrt'\n",
+    "    df.loc[(df.method=='trt-kbc-n4') & (df.cumulant==False) & (df.entropic==True), 'tmp'] = 'entropic'\n",
+    "    df.loc[(df.method=='trt-kbc-n4') & (df.cumulant==True)  & (df.entropic==True), 'tmp'] = 'entropic-cumulant'\n",
+    "\n",
+    "    df.loc[df.method=='srt', 'tmp'] = 'srt'\n",
+    "    \n",
+    "    rr = df['relaxationRates'].apply(pd.Series)\n",
+    "    df.loc[(df.method=='trt') & (rr[1] == 1), 'tmp'] = 'trt_one'\n",
+    "    df.loc[(df.method=='trt') & (rr[1] == \"(-2*omega + 4)/(-omega/4 + 2)\"), 'tmp'] = 'trt_magic'\n",
+    "    \n",
+    "    del df['method']\n",
+    "    del df['relaxationRates']\n",
+    "    del df['force']\n",
+    "    del df['entropic']\n",
+    "    if 'cumulant' in df.columns:\n",
+    "        del df['cumulant']\n",
+    "    df = df.rename(columns = {'tmp' :'method'})\n",
+    "    \n",
+    "    categories = ['srt', 'trt_one', 'trt_magic', 'mrt', 'cumulant', 'entropic', 'entropic-cumulant']\n",
+    "    df = df.assign(method=lambda x: pd.Categorical(x['method'], categories=categories, ordered=True))\n",
+    "    df, constantCols = removeConstantColumns(df)\n",
+    "    print(constantCols)\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Checking results given in Fig2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "params = {'useContinuousMaxwellianEquilibrium': False,\n",
+    "          'compressible': True,\n",
+    "          'forceModel': 'silva',\n",
+    "          'stencil': \"D3Q27\",\n",
+    "          'equilibriumAccuracyOrder': 2,\n",
+    "          'ySize': 1,\n",
+    "          'cumulant': False,\n",
+    "          'en'\n",
+    "         }\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Reproducing results from Geiers Paper"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "L_0                                      32\n",
+      "compressible                           True\n",
+      "entropicNewtonIterations               None\n",
+      "equilibriumAccuracyOrder                  3\n",
+      "forceModel                             none\n",
+      "initialVelocity                        None\n",
+      "omegaOutputField                       None\n",
+      "periodicityInKernel                    True\n",
+      "stencil                               D3Q27\n",
+      "u_0                                   0.096\n",
+      "useContinuousMaxwellianEquilibrium     True\n",
+      "v_0                                     0.1\n",
+      "ySize                                     1\n",
+      "Name: 00303806ec3d4733a72a61334f172bb8, dtype: object\n"
+     ]
+    }
+   ],
+   "source": [
+    "params = {'useContinuousMaxwellianEquilibrium': True,\n",
+    "          'compressible': True,\n",
+    "          'stencil': \"D3Q27\",\n",
+    "          'equilibriumAccuracyOrder': 3,\n",
+    "          'ySize': 1,\n",
+    "         }\n",
+    "\n",
+    "df = db.toPandas(params, dropConstantColumns=False)\n",
+    "df = cleanupMethodColumn(df)\n",
+    "del df['hostname']\n",
+    "del df['mlups']\n",
+    "df = df.set_index(['nu', 'method', 'L']).sort_index()\n",
+    "df = df.sort_index(level=[0,1,2])\n",
+    "df = df.assign(phaseError = lambda x: np.abs(x.phaseError) )\n",
+    "#df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3rd Order Equilibrium"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>phaseError</th>\n",
+       "      <th>viscosityError</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>L</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>6.930304e-07</td>\n",
+       "      <td>0.006271</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>64</th>\n",
+       "      <td>1.090044e-08</td>\n",
+       "      <td>0.001237</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>1.703872e-10</td>\n",
+       "      <td>0.000292</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>256</th>\n",
+       "      <td>2.468612e-12</td>\n",
+       "      <td>0.000072</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       phaseError  viscosityError\n",
+       "L                                \n",
+       "32   6.930304e-07        0.006271\n",
+       "64   1.090044e-08        0.001237\n",
+       "128  1.703872e-10        0.000292\n",
+       "256  2.468612e-12        0.000072"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.loc[(1e-3, 'cumulant')]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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T56spx1cQEREpO7fby7bwW9kWfivnE2c53H+QI+ce5sXTX+Znp7/K1pZb6O7Y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\nAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc7a8968898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pltDf = df.reset_index()\n",
+    "g = sns.FacetGrid(pltDf, col=\"nu\", hue=\"method\", \n",
+    "                  col_wrap=2, col_order=pltDf['nu'].unique()[::-1],\n",
+    "                  size=4, aspect=1.4, legend_out=True, hue_kws=dict(marker=[\"^\", \"v\", '<', 'P', 'o', '>']))\n",
+    "g.map(plt.plot, \"L\", 'viscosityError').add_legend()\n",
+    "g.set(xscale=\"log\", yscale=\"log\");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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1kDYn2e+JcfKEj795fYa5hJeGnH6/rd0U5dmHc3Q+5ruftxEVZCfm6a+98vSm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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc7a8d15a90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pltDf = df.reset_index()\n",
+    "g = sns.FacetGrid(pltDf, col=\"nu\", hue=\"method\", \n",
+    "                  col_wrap=2, col_order=pltDf['nu'].unique()[::-1],\n",
+    "                  size=4, aspect=1.4, legend_out=True)\n",
+    "g.map(plt.plot, \"L\", 'phaseError', marker='o').add_legend()\n",
+    "g.set(xscale=\"log\", yscale=\"log\");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plotting only a single graph:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>method</th>\n",
+       "      <th>srt</th>\n",
+       "      <th>trt_magic</th>\n",
+       "      <th>mrt</th>\n",
+       "      <th>cumulant</th>\n",
+       "      <th>entropic</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>L</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>7.132551e-07</td>\n",
+       "      <td>0.000147</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7.062766e-07</td>\n",
+       "      <td>7.128203e-07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>64</th>\n",
+       "      <td>1.114986e-08</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.110863e-08</td>\n",
+       "      <td>1.114825e-08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>1.738588e-10</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.738305e-10</td>\n",
+       "      <td>1.741583e-10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>256</th>\n",
+       "      <td>2.333423e-12</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2.843368e-11</td>\n",
+       "      <td>2.733735e-12</td>\n",
+       "      <td>2.871477e-12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>512</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.574884e-12</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "method           srt  trt_magic           mrt      cumulant      entropic\n",
+       "L                                                                        \n",
+       "32      7.132551e-07   0.000147           NaN  7.062766e-07  7.128203e-07\n",
+       "64      1.114986e-08        NaN           NaN  1.110863e-08  1.114825e-08\n",
+       "128     1.738588e-10        NaN           NaN  1.738305e-10  1.741583e-10\n",
+       "256     2.333423e-12        NaN  2.843368e-11  2.733735e-12  2.871477e-12\n",
+       "512              NaN        NaN  1.574884e-12           NaN           NaN"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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GYeRdsjwGOGia5mEAwzBeB24xTXMB56ZllzEMIweoNE1Tf0L70LNPDrm97iN/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\nrkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc7a8dbe9b0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "selectViscosity = 1e-4\n",
+    "data = df.loc[(selectViscosity)]['phaseError'].unstack(level=0)\n",
+    "data.plot(logx=True, logy=True, marker='o', figsize=(10,8))\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Reduced stencils"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "method                        srt\n",
+      "L_0                            32\n",
+      "compressible                 True\n",
+      "entropicNewtonIterations     None\n",
+      "forceModel                   none\n",
+      "initialVelocity              None\n",
+      "omegaOutputField             None\n",
+      "periodicityInKernel          True\n",
+      "u_0                         0.096\n",
+      "v_0                           0.1\n",
+      "ySize                           1\n",
+      "Name: 861493f9c4f04ccda2e05b13ec77d229, dtype: object\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>useContinuousMaxwellianEquilibrium</th>\n",
+       "      <th>phaseError</th>\n",
+       "      <th>viscosityError</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>equilibriumAccuracyOrder</th>\n",
+       "      <th>L</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"8\" valign=\"top\">1</th>\n",
+       "      <th>32</th>\n",
+       "      <td>False</td>\n",
+       "      <td>1.554623e-19</td>\n",
+       "      <td>0.000813</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>True</td>\n",
+       "      <td>2.487397e-19</td>\n",
+       "      <td>0.000813</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>64</th>\n",
+       "      <td>True</td>\n",
+       "      <td>2.254204e-19</td>\n",
+       "      <td>0.000163</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>64</th>\n",
+       "      <td>False</td>\n",
+       "      <td>2.254204e-19</td>\n",
+       "      <td>0.000163</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>False</td>\n",
+       "      <td>1.787817e-19</td>\n",
+       "      <td>0.000043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>True</td>\n",
+       "      <td>1.787817e-19</td>\n",
+       "      <td>0.000043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>256</th>\n",
+       "      <td>True</td>\n",
+       "      <td>6.801476e-21</td>\n",
+       "      <td>0.000011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>256</th>\n",
+       "      <td>False</td>\n",
+       "      <td>2.720591e-20</td>\n",
+       "      <td>0.000011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"8\" valign=\"top\">2</th>\n",
+       "      <th>32</th>\n",
+       "      <td>True</td>\n",
+       "      <td>2.592976e-05</td>\n",
+       "      <td>0.055683</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>64</th>\n",
+       "      <td>True</td>\n",
+       "      <td>1.666409e-06</td>\n",
+       "      <td>0.004814</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>64</th>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>True</td>\n",
+       "      <td>1.048924e-07</td>\n",
+       "      <td>0.001153</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>256</th>\n",
+       "      <td>True</td>\n",
+       "      <td>6.568541e-09</td>\n",
+       "      <td>0.000288</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>256</th>\n",
+       "      <td>False</td>\n",
+       "      <td>3.018647e-06</td>\n",
+       "      <td>327.819809</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"8\" valign=\"top\">3</th>\n",
+       "      <th>32</th>\n",
+       "      <td>True</td>\n",
+       "      <td>2.759086e-05</td>\n",
+       "      <td>0.100255</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>64</th>\n",
+       "      <td>True</td>\n",
+       "      <td>1.692622e-06</td>\n",
+       "      <td>0.000238</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>64</th>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>True</td>\n",
+       "      <td>1.053012e-07</td>\n",
+       "      <td>0.000043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>256</th>\n",
+       "      <td>True</td>\n",
+       "      <td>6.574926e-09</td>\n",
+       "      <td>0.000011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>256</th>\n",
+       "      <td>False</td>\n",
+       "      <td>3.081155e-06</td>\n",
+       "      <td>295.992995</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             useContinuousMaxwellianEquilibrium    phaseError  \\\n",
+       "equilibriumAccuracyOrder L                                                      \n",
+       "1                        32                               False  1.554623e-19   \n",
+       "                         32                                True  2.487397e-19   \n",
+       "                         64                                True  2.254204e-19   \n",
+       "                         64                               False  2.254204e-19   \n",
+       "                         128                              False  1.787817e-19   \n",
+       "                         128                               True  1.787817e-19   \n",
+       "                         256                               True  6.801476e-21   \n",
+       "                         256                              False  2.720591e-20   \n",
+       "2                        32                                True  2.592976e-05   \n",
+       "                         32                               False           NaN   \n",
+       "                         64                                True  1.666409e-06   \n",
+       "                         64                               False           NaN   \n",
+       "                         128                              False           NaN   \n",
+       "                         128                               True  1.048924e-07   \n",
+       "                         256                               True  6.568541e-09   \n",
+       "                         256                              False  3.018647e-06   \n",
+       "3                        32                                True  2.759086e-05   \n",
+       "                         32                               False           NaN   \n",
+       "                         64                                True  1.692622e-06   \n",
+       "                         64                               False           NaN   \n",
+       "                         128                              False           NaN   \n",
+       "                         128                               True  1.053012e-07   \n",
+       "                         256                               True  6.574926e-09   \n",
+       "                         256                              False  3.081155e-06   \n",
+       "\n",
+       "                              viscosityError  \n",
+       "equilibriumAccuracyOrder L                    \n",
+       "1                        32         0.000813  \n",
+       "                         32         0.000813  \n",
+       "                         64         0.000163  \n",
+       "                         64         0.000163  \n",
+       "                         128        0.000043  \n",
+       "                         128        0.000043  \n",
+       "                         256        0.000011  \n",
+       "                         256        0.000011  \n",
+       "2                        32         0.055683  \n",
+       "                         32              NaN  \n",
+       "                         64         0.004814  \n",
+       "                         64              NaN  \n",
+       "                         128             NaN  \n",
+       "                         128        0.001153  \n",
+       "                         256        0.000288  \n",
+       "                         256      327.819809  \n",
+       "3                        32         0.100255  \n",
+       "                         32              NaN  \n",
+       "                         64         0.000238  \n",
+       "                         64              NaN  \n",
+       "                         128             NaN  \n",
+       "                         128        0.000043  \n",
+       "                         256        0.000011  \n",
+       "                         256      295.992995  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "params = {'method': 'srt',\n",
+    "          'compressible': True,\n",
+    "          'ySize': 1,}\n",
+    "\n",
+    "df = db.toPandas(params, dropConstantColumns=False)\n",
+    "df = cleanupMethodColumn(df)\n",
+    "del df['hostname']\n",
+    "del df['mlups']\n",
+    "df = df.set_index(['stencil', 'nu', 'equilibriumAccuracyOrder', 'L']).sort_index()\n",
+    "df = df.sort_index(level=[0,1,2])\n",
+    "df = df.assign(phaseError = lambda x: np.abs(x.phaseError) )\n",
+    "df.loc[('D3Q19',1e-5)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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0OY+77rqDHTuiAPjww3fp1q0TGzduACAuLo5Bg67k/vtH8tlnH3PRRf1SkkVx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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc7a8b14c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.set_context(\"poster\")\n",
+    "pltDf = df.loc['D3Q19'].reset_index()\n",
+    "\n",
+    "pltDf = pltDf[pltDf['equilibriumAccuracyOrder'] > 1]\n",
+    "g = sns.FacetGrid(pltDf, col=\"nu\", row='equilibriumAccuracyOrder',\n",
+    "                  hue=\"useContinuousMaxwellianEquilibrium\",  hue_kws=dict(marker=[\"o\", \"v\"]),\n",
+    "                  col_order=pltDf['nu'].unique()[::-1],\n",
+    "                  size=4, aspect=1.4,  legend_out=False)\n",
+    "g.map(plt.plot, \"L\", 'viscosityError', marker='o').add_legend()\n",
+    "g.set(xscale=\"log\", yscale=\"log\");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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uN6I/MMCv7SHeqtpDs/fsqNxew/0r1lw1t8eiPBdxT8VPiScqfoq4pM6ViHu6\nWZZIudDezpbyHRxuPkhf0kVnY38ixb4lfHTJBm6es2BoX+W5iHvKc3HrQnsrL5Tv5HDzwRGL2xX7\nDPctWc9Nw3J7LMpzEfdU/JR4ouKniEvqXIm4p5tlmQwHqs7w2okdnB84AQm9APh7ZlGWdRMPl25g\n6fxC5bmIS8pzmUj7zp3m9ZM7qRmwwxZJmsXKrJvYXLqB7PSrL26n/rmIeyp+SjxR8VPEJXWuRNzT\nzbJMpu6+Xl45sofdde/R4a9xFtsIeMlhAXfOXsumJWUkeH3RbqbIlKQ8l0jo6u3llSPv8m79vhG5\nnR2Yz6Z5t/GBUYvbqX8u4p6KnxJPVPwUcUmdKxH3dLMs0VJ5oZEtR7ZxsrOcYGIHAJ7eVBallLJ5\nxUbm5+RHuYUiU4vyXCKtoqmerUe3c6pz5OJ2i1JXsHm5k9vqn4u4p+KnxBMVP0VcUudKxD3dLEu0\nBQIB9tWd4sXyX3PBcxaPb4BgEFL7ClmXv5oHVqwjJTH8xTZEpivluUyW/sAAb58s59dnd1+xuN2m\nktv54IKbldsiLqj4KfFExU8Rl1T8FHFPN8sSCwbzvLmjnS3luzh08QB9SRecL/b7KfQ6iyTdOndh\ndBsqEsOU5xINF9rb2Vq+g/dHLG7np8hn+Oji9dyi3Ba5bip+SjxR8VPEJRU/RdzTzbLEgqvl+cHq\ns7x2YgfV/ceHFklK6MmidOYqHi7bQG56ZjSaKhKzlOcSbQeqzvDLineo7D42IrfLZq7iY2UbyFZu\ni4RFxU+JJyp+irik4qeIe7pZllhwrTzv6evjtaN72VW7l3Z/DR5PkGDAS9bAPO6cu467zSotkiSC\n8lxiQ25uBlU1F3jlyF521+0dsUhSVqCETXPW8gHltsg1qfgp8UTFTxGXVPwUcU83yxILws3zcxeb\n2HpkOyc6DhNIbAfA05fCguQVPLRsI4vyCiPdVJGYpTyXWDA6zysvNLL1yHZOdh4mMGxxu4UpK3ho\n+UYW5hZEq6kiMUvFT4knKn6KuKTip4h7ulmWWHC9eR4IBNh++ghvVuymyXNm2CJJBazOvZWHytaR\nmpgcwRaLxB7lucSCsfI8EAjw9qlyfnV2Nxc8FSMWt1ubdysPlt6mRZJEQlT8lHii4qeISyp+irin\nm2WJBW7yvKWrgy2Hd3HwwgF6k5qcjf1+8r2LuHfhetbOXzK075P7v0dPoJfclGzyUnLITc0hNyWH\nvNQc0vxvJV8IAAAgAElEQVSpE/FWRKJGeS6xIJw8b+7oYEv5zisWtyvwLuaji9ezet7iSWipSOxS\n8VPiiYqfIi6p+Cninm6WJRZMVJ6Xn6/kZbuDqr7j4O8BIKFnJstnrOTh0o0caXmf506+dMVxy7MN\nX1z1mOvri0ST8lxiwfXm+fvVZ3nlisXtZrJixio+tnKjFreTaUnFT4knKn6KuKTip4h7ulmWWDDR\ned7b38drR/exq2YvbQnVeLxBggEPmQOzafefJ0hgaF+vx8vX1v4pBWl5E3Z9kWhQnkssuNE8H1zc\n7p3a92jznx+xuN3GOev40FItkiTTh4qfEk9U/BRxScVPEfd0syyxIJJ5Xn3pIlvLt3G8/TCBxCuv\ncdfs9XxyyeaIXFtkMinPJRZMRJ6Ptbjd/KTlbF5+J4vyCvUYE4lrKn5KPFHxU8QlFT9F3NPNssSC\nycjzQCDAzjPHec6+Sl9Kw9B2f88sbp51Kw+V3kFWWlpE2yASScpziQUTmeeBQIAdp4/xRsWuEYvb\npfTlU5g5i4ruY1cco8eYSDxQ8VPiSUK0GyAiIiIyXXi9Xm6fv5TnXmsiuOTnePx9BLpS6Uu5yJ6O\nX/Lurl8xK1DCXfPW8YElZZpeKSISZV6vlzsXr+DOxStGLG7XnVRPRXc9BIFhJSKvx8sjix6MWntF\nRORKKn6KiIiITKK9xxpo7ejHf6EI74wmeg6vx5vcw6LSNqoHjtOceJotNafZWulMr7x/6XqWFsyO\ndrNFRKa9GSlp/M7ae/gd7rm8uF3wMHguP8M521dEEpryLiISS2J+2rsxZgHwNWCGtfYToW1pwL8C\nvcBb1tr/e61zaFqNRJKmvYu4p2mSEgsmK8+/+cx7VNS24kltxePvIdCSC0DZgmz+2yfKePtUOb8+\n++7Q9EqApJ5cVs26SdPiJeYpzyUWTGb//N/e+iWHA78EIBgEjweCAz5yWciHF6zn9vkGr9c7KW0R\nmUia9i7xJKLFT2PM08ADQIO1tnTY9nuBJwEf8H1r7bfDONfPhhU/Pwtcsta+ZIz5ibX2U9c6Vp0r\niSQVP0Xc082yxIJYy/PWri5eLN/FgaaDdCfVA84NtabFSyxTnkssmKw87x8I8JV/3UHvkl/g8ffS\nW7WIWZnJdKSeJujvAsDXO4OyGTfz8bI7yU5Pj3ibRCaKip8STyI97f0HwHeAHw5uMMb4gO8C9wDV\nwF5jzIs4hdAnRh3/eWttA1eaDRwO/XtggtssIiIiEnWZKSn81pq7+S3u5mR9DS8f38np3iOaFi8i\nEiMuP8akEO+MJgZqF3Cx3sfXP/cw7zdYtle/S6u/ioNdb3Fg9zayAwu4Z8F6NixYptGgIiKTKKLF\nT2vtNmNMyajNa4FT1tozAMaYZ4HN1toncEaJhqMapwB6ENBvDREREYlri/OL+HL+bxAIPHJ5Wrz3\nDGcC+/iXo/tIOpDLquybeGiFpsWLiEyWN/ZVA9DfVIynJQfwMhAI8rO3KvjyJ9dwf+kazl1s4oXy\ntznZeZiLiaf4yblT/OxUJsszbuKRVXeSm54Z3TchIjINRPyZn6Hi58uD096NMZ8A7rXWfiH0+rPA\nOmvtl8Y4Phv4Fs5I0e9ba58IPfPzO0A3sGO8Z3729w8EExI0LUxEJIaFNa1GeS5yWUtHBz/e8zbv\nnN9Ll78OcKbF53kX8BGznvtWribBp/9fZNIpz0Wuon9ggJcO7OG1E9to9lTi8QYJBrzksIAHl2/i\n3rKbNRpUYo2mvUvciPni50TQM4UkkmLtGXEiU5GeESexYCrn+dC0+K4jBBM7AfD0aVq8TD7lucSC\nWM/zmksXef7w29iO9wkkdgDg7c1gWfpKPl52JwUzsqLcQhE981PiS6Sf+Xk154E5w17PDm0TERER\nkRugafEiIlNH0cxZfGnjxwgENvOrE+/z68p3aE44y5HenZTv3UXWQAmb5t3O3UtWajSoiMgEiMbI\nzwTgBHA3TtFzL/CotfZIpNqgT5YlkmL9k2WRqUAjhSQWxFuej7VafHawhDvnarV4iQzlucSCqZjn\ndS3NvHB4O0fbDxFIdNru7U3DpK3k42V3UTRzVpRbKNONRn5KPIlo8dMY82NgE5AD1AOPW2ufMsbc\nB/wTzgrvT1trvxWxRqDOlUTWVOxcicQa3SxLLIjnPNe0eJksynOJBVM5zwOBAG+fOsKbFbu46KvA\n4w0QDHiYMTCXu+bczoeWrtIHVzIpVPyUeBLxkZ+xQJ0riaSp3LkSiRW6WZZYMB3y3LmpDk2L95zB\n4xsAIKlH0+JlYijPJRbES543trfy/PvbONJ6kIHEVgA8vaksTi3jkdK7mD0rJ8otlHim4qfEExU/\nRVyKl86VSDTpZlliwXTLc02Ll0hQnkssiLc8DwQC7DhzjDfO7KLJe3poNGhm/2w2zr6Njyy7hQSf\n8lomloqfEk9U/BRxKd46VyLRoJtliQXTOc81LV4mivJcYkE85/mF9naeP7yNwy0HGEhsAZy8Xphc\nysdLNzEvOzfKLZR4oeKnxBMVP0VciufOlchk0c2yxALluabFi3vKc4kF0yHPA4EAu8+e4Oend9DI\naTy+AYJByOibzR3Fa7l/+RqNBhVXVPyUeKLip4hL06FzJRJpulmWWKA8H0nT4uVGKM8lFky3PG/u\n6OCFw9s51HyA/qRmZ2NfMguSVvDwirtYmFsQ3QbKlKTip8QTFT9FXJpunSuRSNDNssQC5fnYNC1e\nwqU8l1gwnfP83YoTvH5qB/WcwuPrJxiEtL4i1heu5b4Va0hM8Ee7iTJFqPgp8UTFTxGXpnPnSmSi\n6GZZYoHyfHyaFi/jUZ5LLFCeQ0tXB1ve38WBi/voS7robOxLoiRxOZuX38WS/KLoNlBinoqfEk9U\n/BRxSZ0rEfd0syyxQHl+fTQtXq5GeS6xQHk+0r5zp3n1xHbqgicgNBo0ta+Q2/LX8GDpOpL8Gg0q\nV1LxU+KJip8iLqlzJeKebpYlFijPb5ymxcsg5bnEAuX51bV1d7Hl8E72N+2nN6nJ2diXxBz/UjYv\nv5NlBXOi20CJKSp+SjxR8VPEJXWuRNzTzbLEAuW5e5oWL8pziQXK8/EdrDrDyye2UztwAhL6AEju\nyWdd/hoeLL2NlMTEKLdQok3FT4knKn6KuKTOlYh7ulmWWKA8n1iaFj89Kc8lFijPw9fZ282W99/h\nvcb36ElqdDb2JzI7YSkPLb2TFUVzo9tAiRoVPyWeqPgp4pI6VyLu6WZZYoHyPHI0LX76UJ5LLFCe\n35jD5yt52W6jut9CQi/gjNxfk7uazStvJzUxOcotlMmk4qfEExU/RVxS50rEPd0sSyxQnkeepsXH\nP+W5xALluTtdvb28WP4Oe+rfGxq5T7+fIp/hfnMnN80uiWr7ZHKo+CnxRMVPEZfUuRJxTzfLEguU\n55NL0+Ljk/JcYoHyfOIcq6ti69FtVPUfGxoNmtiTwy05t/KxsvWkJ2s0aLxS8VPiiYqfIi6pcyXi\nnm6WJRYoz6NH0+Ljh/JcYoHyfOJ19/XycvkedtfvoSuxztnY76fAu5j7l2zklrkLo9tAmXAqfko8\nCav4aYz5A2vtv01CeyJCnSuJJHWuRNzTzbLEAuV59F3PtPgn93+PnkAvuSnZ5KXkkJuaQ25KDnmp\nOaT5U6P5NqY15bnEAuV5ZJ2or2Hr0bc523sU/D0A+HuyuXnWLXxs5QYyU1Ki3EKZCCp+SjwJt/hZ\nbq0tnYT2RIQ6VxJJ6lyJuKebZYkFyvPYMt60eE9KCy+cfuWK45ZnG7646rHJbq6EKM8lFijPJ0dP\nXx+vHN3LO7V76PDX4PEAAwnks4h7F29kbcniaDdRXFDxU+JJuMXP14Ak4F2ga3C7tfbvIte0iaPO\nlUSSOlci7ulmWWKB8jx2XW1aPH3JoRFHl2PB6/HytbV/SkFaXnQaKspziQnK88l3qqGWrUe3cabn\nCPi7AUjoyWJV1i18rGyDFrObglT8lHiSEOZ+u4f9W/8DiIiIiMikWZxfxJfzf4NA4JHL0+K9Z/Aw\nsn62JGUV3r4MgsEgHo+6rCIik2VRXiF/lvcpevv7eO3YPnaef5f2xPPs63yT93a9RR4L+cjCDawr\nWYLX6412c0Vkmgl7wSNjTC6wDqdg+o61tj6SDZtI+mRZIkmfLIu4p5FCEguU51NLa1cX//PX/4/m\nZAtAsN9P96GNMJBIeoqfksIMFhRmUlKYyfzCTGakJUa5xdOD8lxigfI8NlQ01bPlyDZOd5cT9DsT\nSBN6ZlI28yY+VnYn2enpgJ7hHKs08lPiSbjT3j8CPI0zAtQL3AE8Zq19ObLNmxjqXEkkqXMl4p5u\nliUWKM+nlv6BAF/51x30LvkFHn8vvZXLmJ+wkqyMJCpqW2lq6R6xf3Zm0lAhdH5hJiUFGaQkhTsJ\nSsKlPJdYoDyPLf0DA/z82H62V++m1V+NxxMkOOAjJ7iAexasp9ffxPOnrywt6BnO0aXip8STcHt8\n3wI2WGsrAIwxC4DngSlR/BQRERGR+LL3WAOtHf34LxTindHEQP0cKryt/O59aynMTqOts5eK2jbO\n1rZSEfqzzzayzzYCznOcCrJTLxdDCzOYm5eOP8EX3TcmIhJnEnw+7i9dw/2lazh3sYkXyt/mZO9h\nLiSe5NlzJ/H2puNJ9BAc9QznRxY9GMVWi0g8Cbf46R8sfAJYa88YY/SgDhERERGJijf2VQPQ31SM\npyUH8DIQCPLsm6f48idXkZGayMqF2axcmA1AMBjkYmvPUCG0oraVs3Vt1F6oY1d5HQA+r4fZeemh\ngmgG8wszKcpOw+vV4BcRkYkwd1YO/+3OR+gPPMwbxw/ydtVuWhLOXfEM57KcZWQkpkeplSISb8Kd\n9v4S8CbwVGjTF4APWmunxEcxmlYjkaRpNSLuaZqkxALl+fQTCAapu9DpFEJr2zhT20pVQxv9A5ej\nJsnvY15BxlAxdH5hJjkzkrWg0hiU5xILlOdTS/Wli/zzzmfpSDl7xddmJs1gdnohxelFFKcXMju9\nkNzUHLwejcWKNE17l3gS7sjPx4B/Ab6GM0voV8DvR6pRIiIiIiKR5vV4KMpJoygnjfVlhYDzLNHq\nxnYqalqpqG2joq6Vk1WXOFF1aei49BT/0OhQLagkIuJOQcZMes+UElxSg8ffS39jEfOyc5mR2835\ntlrKLxyn/MLxof0TvX4K0wtGFEWL0wtISUiJ4rsQkVgWbvHzj621n4poS0REREREoizB56WkIJOS\ngkw+ENrW3dtPZV2bUwwNTZk/fOYCh89cGDpOCyqJiNyY0c9w7qsopaLSx9895jzDub23g+r2Gs63\n13K+vZbq9hqq22qobK0acZ7s5KwRI0SL04vITsnSKFERCXva+yHgJmttVKanhBZY+howw1r7idC2\nh4H7gUzgKWvtL8Y6XtNqJJI0rUbEPU2TlFigPJfrcbUFlVo7+4a+PnpBpfmFmczJS8efEN834cpz\niQXK86nlm8+8R0VtK57UVjz+HgItuQCULcjmy59cddVj+gP91Hc2DhVDz7c5hdG2vvYR+yX5EkMj\nQy8XRYvSC0nyabT+eDTtXeJJuMXPXwHFwH6ga3C7tfbzYRz7NPAA0GCtLR22/V7gScAHfN9a++0w\nzvWzweLnsG1ZwN9bax8b6zh1riSS1LkScU83yxILlOfixlgLKnX3DgztM7ig0oLQ6vLxuKCS8lxi\ngfJ8+mrpaeN8aJTo4GjR+s5GAsHA0D4ePOSmZFM0NELUKY7OSp6p5zkPo+KnxJNw5+I84+IaPwC+\nA/xwcIMxxgd8F7gHqAb2GmNexCmEPjHq+M9baxuucf6/Dp1LRERERCQqPB4P2TOSyZ6RzOqlecDI\nBZWcP21UNbRRWdcGB5zjtKCSiMjEmZGUwYwkw/JsM7Stb6CP2s76odGhg0XRg42HOdh4eGi/lIQU\nitMLKE4vGiqKFqYVkOjzR+OtiMgECrf4+Rlr7Ydv5ALW2m3GmJJRm9cCp6y1ZwCMMc8Cm621T+CM\nEh2XMcYDfBt4zVq7/0baJiIiIiISKVpQSUQk+vw+P3MzZjM3Y/bQtmAwyKWellAxtHZotOjpS2c5\ndaliaD8PHvJTc0NT5osoSi9gdkYRMxIz9SGVyBQSbvEz2Rgzx1pbNf6uYSkGhp+rGlg31s7GmGzg\nW8DNxpi/DBVJ/wj4EDDDGLPIWvtvYx2flZVKQoJvYlouchW5uRnRboLItKA8l0hTnstkKCyYwZqy\n4qHXXT39nK6+xIlzlzhZ1czJqktXLKiUm5XC4jkzWTIni8VzZ7Jo9kxSk6fuaCTluUSa8lzGk0cm\nS5gzYltPfy9VLTWcvVRN5eCflvPUNTSwr+HQ0H4ZiWnMmzk79KeYkpmzKc4swK9RoiIxKdxnfh4D\nlgANOM/89ABBa+2CcC4SGvn58uAzP40xnwDutdZ+IfT6s8A6a+2XbuRNjEfPFJJI0jOFRNzTM+Ik\nFijPJZa0dvZyNrSg0pnaVs5OkQWVlOcSC5TnMpGCwSAXups5314TGiVay/m2Gpq6L47Yz+vxUpCa\n50ybzygcGi2akZgepZa7o2d+SjwJd+TnvRN83fMw4iOW2aFtIiIiIiLTXmZqIisXZrNyYTYw9oJK\ntRfq2FVeBzgLKs3JS2d+aEGlBYWZFMbZgkoiIpPN4/GQkzKLnJRZrModWsOZrv5uajvqqG67PG3+\nfEcdNR117K2/fHxmYkZoUaXLBdH81Fx8Xo1+F5ks1yx+GmM2W2u3WmsrjTFZ1trmYV/7c+B/3uB1\n9wKLjTHzcYqenwYevcFziYiIiIjEtetZUOns8AWVEn3My88YscL81RZUOl3TQkdX/1CxVUREri0l\nIZkFM0pYMKNkaFsgGKCp68LlEaLtNVS31XLs4gmOXTwxtF+Cx0dhWj7F6UUUZwyuOl9Emj81Cu9E\nJP6NN/LzcWBr6N9vArcM+9qnCaP4aYz5MbAJyDHGVAOPW2ufMsZ8Cfg5zgrvT1trj1xn20VERERE\npq2xFlSqamjnbKgYWlF77QWVBqfMv/leNZX1bayYn4XPG92p8yIiU5XX4yUvNZe81FxuyVs5tL2z\nr3PY4kpOUbSmo56q9hqou3z8zKQZw0aIOgXRvNQcvJ7xc/nJ/d+jJ9BLbko2eSk55KbmkJuSQ15q\njoqqMu2NV/z0jPHvq72+Kmvtb46x/VXg1XDOISIiIiIi40vweYcKmh8Ibevu7aeyrm2oGFpR23rF\ngkqDfrG3io+umze5jRYRiXOp/lQWZy1kcdbCoW0DgQEau5qGCqLV7TWcb6vlyIXjHLlwfGg/v9dP\nUVqBUxTNcKbNF6cXkJKQMuIaZbnLee7kS1S2jlynenm24YurHovsGxSJceE+8xNg9EPJ9ZByERER\nEZEYl5yYgJmbhZmbNbRt+IJKu47U0dDcBcAruyrZuLKI9BStWCwiEkk+r4+CtHwK0vJZnX/T0Pb2\n3g6nEDqsKFrdXkNlWxXUXj4+OznLmTYfGik6P3MePo+PgeDA0D5ej5dHFj04mW9LJCaNV/xUgVNE\nREREJM4MLqi0vCSLXx+4vO5oZ08/W3dU8Jl7lkSxdSIi01d6YhpLZy1m6azFQ9v6A/3UdzZS3Xa5\nKHq+vZb3m47wftPlJwh6R03Q3Vh8OwVpeZPWdpFYNV7xc7Ex5ldX+bcHWBS5ZomIiIiISKTtPdZA\nS0fviG1vHTjPB28ppjA7LUqtEhGR4RK8CUMjPIdr6WkbWmm+ur2G05cqaO5pASDZl8z98++JRnNF\nYs54xc8HJqUVIiIiIiIy6d7YV33FtoFAkGffPMWXP7kqCi0SEZFwzUjKYEaSYXm2AZzniP7Vzv9B\ne18HDy74iBY6Egm5ZvHTWvv24L+NMSXACuB1YK61tiKyTRMRERERkUj6m99ZHe0miIjIBPF5fazJ\nv5ljF0+wsfi2aDdHJGZ4w9nJGPMp4CXgn4Fs4B1jzG9FsmEiIiIiIiIiIhK+dYWr+fjiB/B5fdFu\nikjMCKv4CfwFcAfQaq1tAG4G/jJirRIRERERERERkesyJ6OIFdlLo90MkZgSbvFzwFrbNvjCWlsL\nBCLTJBERERERERERERH3xlvwaNARY8yXAL8x5ibgD4GDkWuWiIiIiIiIiIiIiDvhjvz8IlAMdAFP\nAy04BVARERERERERERGRmBRW8dNa2wE8bq1dA3wKeAvoiGC7RERERERERERERFwJd7X3rwPfN8bM\nBd4G/gT4XiQbJiIiIiIiIiIiIuJGuNPeHwJ+D3gU+JG19h6cFd9FREREREREREREYlK4xU+ftbYH\neAB41RjjBdIi1ywRERERERERERERd8Itfr5pjCkHEoFtOFPfX4pYq0RERERERERERERcCnfBo68A\n9wG3W2sDwB9Za/88oi0TERERERERERERcSEhnJ2MMQb4QyDdGOMBfMaY+dbaOyPaOhERERERERER\nEZEbFO60958Al3AWOToI5AHlkWqUiIiIiIiIiIiIiFvhFj+91trHgdeB/cDDwLqItUpERERERERE\nRETEpXCLn53GmCTgBHBraOX35Mg1S0RERERERERERMSdsJ75CfwIZ3X3zwDvGGPuBc5HrFUiIiIi\nIiIiIiIiLoW72vt3gEestY3AJuDfcaa+i4iIiIiIiIiIiMSkcFd7zwI+bYzJATyhzWXA30WqYSIi\nIiIiIiIiIiJuhDvtfQvQABwBgpFrjoiIiIiIiIiIiMjECLf4Octae1dEWyIiIiIiIiIiIiIygcJd\n7b3cGHNrRFsyBmPMAmPMU8aYn43anmaMec8Y80A02iUiIiIiIiIiIiKx7ZojP40xFTjT3FOB3zDG\n1AD9g1+31i4Y5/ingQeABmtt6bDt9wJPAj7g+9bab491DmvtGeCx0cVP4C+An17r+iIiIiIiIiIi\nIjJ9jTftfVPo7yTgfuCDOMXPV4E3wzj/D4DvAD8c3GCM8QHfBe4BqoG9xpgXcQqhT4w6/vPW2obR\nJzXG3AMcBZLDaIOIiIiIiIiIiIhMQ9csflprKwGMMc/gFBr/HWeq/G8DK4A/Gef4bcaYklGb1wKn\nQiM6McY8C2y21j6BM0o0HJuANGA50GWMedVaGxhr56ysVBISfGGe+kq28iJtnX2sXpZ/w+eQ+Jab\nmxHtJohMC27zXGQ8ynORyaE8l0hTnouIyKBwFzxaZ61dOvjCGPMSUH6D1ywGqoa9rgbWjbWzMSYb\n+BZwszHmL621T1hrvxb62ueApmsVPgGamztvsKmOn/7SUtXQzuxZa/F5w31MqkwXubkZNDa2RbsZ\nIlNauDcobvNc5FqU5yLuKc8lFijPRdzTBwgST8ItflYZYxZZa0+FXucD5yPUphGstReAPxjjaz+I\n5LWf3P89Ovq6qewJEExO5Sv/rxKTX4zJL2ZpcR75s1LxejyRbIKIiIiIiIiIiIjcoHCLn37gkDFm\nG84zPzcAtcaYXwFYaz94Hdc8D8wZ9no2k1RIvV5luct57uRLJOQ4r3uBw+zj4Kkcel9dTUqSj3n5\nGcwvzGR+YSYlhRlkZybjUUFUREREREREREQk6sItfj4+6vXfu7jmXmCxMWY+TtHz08CjLs4XMbfk\nrOI5+zJ4g5c3Bj3cO/temhITqKhtxZ67xPFzl4a+nJHqdwqhBZeLoplpiVFovYiIiIiIiIiIyPQW\nVvHTWvv2jZzcGPNjnMWJcowx1cDj1tqnjDFfAn6Os8L709baIzdy/kg7drqTgZYcfFmNQ9uCAz4q\nvXtZsHw2N6/JZ1biHDpakqiq66CitpWK2jbeP32B909fGDomOzOJksJMFhRmUhIqjKYkhVt3FhER\nERERERERkRvhCQaD4+81xTU2tt3Qm/zmM+9R2XWSpCUHAAgGPDDgw+PvH7Gfz+MjPzWXovQCitIK\nmJmQQ197Kk2NXs7WtXG2tpXWzr6h/T1AQXYqJQWZzC90RojOzU/HrxUvpyQ9UF3EvdzcjLCeF3Kj\neS4SDuW5iHvKc4kFynMR98LNc5GpQMMPr+Fvfmc1A4Gb+audJ2jv6+CT5iHumn0Hrb3t1HbUUdNe\nS01HPTUdddS211HTUTfi+CRfIoXzC1hdms9MXw6BrnTaLiZRUzfA2bpW3jlSxztHnGN8Xg/FuWmX\nnx9akEFxbppWlxcREREREREREblBKn6Ow+f1sSb/Zo5dPMHG4tvweDzMSMpgRlIGS2ctHtovEAxw\nsbuZmlARtKa9jtqOes61VXO29dyIc6bPTmOxKWBmQjbenkw6L6XQWJdAVV0n5+rbeftgDQCJCV7m\n5mdQEhoduqAwk7ysFC2oNE09uf979AR6yU3JJi8lh9zUHHJTcshLzSHNnxrt5omIiIiIiIiIxBwV\nP8OwrnA1y7KX4POOPS3d6/GSk5JNTko2K3NXDG3vD/TT0Nk0VBAdHCV68tJp4LSzkw8ohvwFM5np\nz8Xfn0lfWxoXGxI5U9vMqfMtQ+dLTUoYKoYOTpvPykhSQXQaKMtdznMnX6KytWrE9uXZhi+ueixK\nrRIRERERERERiV0qfoZhTkYRUHRDxyZ4E5xngaYXQP7l7d39PdR11lPTXk9NRy217c70+TPtJ50d\n/EAxpBR7mZk4i+TATAY60mm9kMSx2haOnk3FeXoozEhLdIqhhZdXmE9P8bt6zxJ71uTfzJZTrzIQ\nHBja5vV4eWTRg1FslYiIiIiIiIhI7FLxM0qSE5IoyZxLSebcEdvbetupDT1H1Jk6X0dNez0XB5og\nCSiC5CJI8CSQShaengw6mlN4vzGZg5UZ0JcEeMiZkTxUCJ1fmMG8ggySE/Xjnio6e7upudRMXVsz\nTe2XuNDVSktPK76BFAa87UP7FQSW8d6hTtJTzpOe4h/6kxb625+gZ8aKiIiIiIiIyPSlaliMyUhM\nJyMxnSVZC4e2BYNBmnsuDT1H9HyoKFrX2UB/YiPk///s3XmYVPd95/t3VXX13kDT3eyrWA6r0AaI\nVehHgnoAACAASURBVLIlOVqNFHuSjBNPMpYzk2ecO8msd2Y8ufGNx1e+M89M4sT2jOPYsZ3J2J7r\nRZstyZZkCRCLQAgJEPqxColm3+lu6K3q/lEFahCrDk1VV79fz6NH1KHqnG810off+Z7fOT+oyM8q\nLaOCss4BtJ2oZt2RGl7bXUvmVB2JTJoRDTXnzA4d1VRrc+w66ujqZN+J4+w7foQDrcc43HacY6dP\ncLKzhbauVk5nWulMnCKTOg2prgvv5Lw/rvda3uOdHcvpPjIMsh/8s6xIp6itKjvbDD3bGK0893Vd\n9fvbqypSPkZBkiRJkiSVhEQ2my10Db3u4MGTJfkluzPdHDx1+NxZoq37ONh2mCznfuVUdxVdrbV0\ntdaQPVVHpq2WZEcdoxsHnnPL/IiGGpJJG19XqivTTbY8y6ad77K/5RiHW49z9PQJTnScpLWzldPZ\nVjpoozt5mmyqg8v2FLvKSWUqSVNFVbKGmrJaBpTXMqhyAPWVA/j58r1kxq8ike7M/RlWtUACKpPV\njCmbzpDuiK72ClpPddKS/yf36y7aO7svc/CcVDJBTeUFGqY9X1emqa0qy72uLqemsoyylI10fXhN\nTXVXFDylmucqDk1NdRw8eLLQZUh9mnmuYmCeS/FdaZ5LfYEzP/uwVDLFsJohDKsZwi1Dbjy7vaO7\nk31t+9nbsp/mHs8TPZY6SHrAwfd3kIV97dXsOVnHsgO1ZFbWke4cwJhBQxk/fNDZW+abBvWvFeYz\nmQzHT7Wx98RR9p88yqHW4xw5dZwT7Sdp6WyhLdNKR/YUXclTZFPtJJIXGbufeexqdxnJ7krS3QOp\nSFZTk8rN7h1UOYCG6gE01dQzbEA9wwYMoiJ98We1rty4j7ZjJ0gfHkFy4CHaN84nVXWaxR/t5I2j\n69nSsYZtide4cfh0PjpqPpMGTT/nz62zK9OjGZr/5/R5r9ty21pOdXGyrZN9R9q40usjVRWpfFP0\nwk3TmjPN0vwM05qqNJXlzjKVJEmSJEm9x5mf/UhbZxt7WvfnnyO67+yM0bauU+e8L5tJkD1VS+ZU\nLdlTdZR3DWT0gBFMHDKMG0bkbpkfVFtRoG/x4V3sOZotHS20dbdyOttGV+IUmbLTJJKZS+4rm0mS\n7KqkLFtFVaqGykQ1telaBlXWUV81kKaaQQyrG8TwgYOpray8JvV/8btr2bn3BInqEyTS7WSONwEw\n84YGPveJqazdv56Xd69gd8seAIbXDGXxyPnMGXYLlWUf7s8rk83Sdrrr3AbpmQZqvkn6gYbqqU46\nuy798zujLJV4v0FaeZmGaY9b9q/F7OTte47TeqqLGyc0xN6X4nOmkIqBM4Wk+MxzFQPzXIrPmZ8q\nJTY/+7lsNsvxjhNnZ4fuadlHc8te9rbupyt77nMns90pMm11ZE/VUpmpZ3jNUCY1jmbKiKGMG15H\nTeWFZy1+Zd03aM900FTVwJCqRpqqG2mqamRIdSM16epY9eeeo3mMfcePfvjnaJ75fpkEie4KyjKV\nlCeqqUrWUJuuZWB5HfXVA2isHsjQunpGDBzMwKpqksncbd7FNLjKZrPsOL6Lpc0rWHfgTTLZDJWp\nSuYOv5U7Rs5jaM2Q61JHe2f3hRump3o0TE+f+3utpy/959PTB27LPzvjtOzCt+lXpalIp87Zx18/\nuYld+0/yZ4/OIZX0lv1C82RZxaCY8lzqq8xzFQPzXIrP5qdKic1PXVAmm+HQqSNnV5t/98Qe3jux\nh2OdRz7wPNFsRzmZU3VUZgYxtGoo4wePZOaIsUwc3kBFOsWL7y3jx1uf+sAxpjVEfG7Wox/Y3p3p\n5lDLSfYeP9KLz9GsY1BlHQ3VgxhaN4jhA+pprBtAWTJ1mZ19ULEOro63n+CVPatZ3rya4x0nAJhS\nP4nFo+Yzs3EqyURxNfwymew5DdH3G6NdH2ygnn7/dVf3lf3vnS5Lnm2UVpan2N58nCzwqbsncfdt\no3v3y+myPFlWMSjWPJf6EvNcxcA8l+Kz+alSYvNTV6Uz08WBtoPsadnHjqPN7DzazMHTBzjNBwcX\n2dNVlHcPor6inoNlm89pmiZIMKn8Vjo6u6/uOZpnnHmOZrYq1nM0r4ViH1x1Z7p549AmXt79CtuO\n7QRgcGU9i0bezvzhc6gtrylwhR9eNpulvbP7A03SC8847Tw74/RU+/uLP9VUlvHYP51HbVXv/nei\nS/NkWcWg2PNc6gvMcxUD81yKz+anSonNT10Tp7tOs6dlH+Hge2w7vJu9rfs5mTlMJtV+xfvo+RzN\nikQ11aka6sprGVgxgMFVA2jshedoXgt9aXDV3LKXpbtX8Oq+dXRkOilLlnHrkFncMWo+Ywf0j9mP\nXd0Z/vXXV3CitePstrtuHcVv3zO5gFXJk2UVg76U51KxMs9VDMxzKT6bnyolNj/Vq46dPsGGPbv4\n+dsrOFG5Hcg1OaeUz2Z43RAaqgdc8DmafUlfHFy1dZ5i9b7XWLp7BQdOHQJg7IDR3DFyPrcMuZF0\nqnRnQa7cuI9vPv3WOdtSyQR/9ugchjf03VmwfZ0nyyoGfTHPpWJjnqsYmOdSfDY/VUrKCl2AStug\nygHMGzudH//sKNnJ75FId9D5XkTDqJn8g8XOtCuU6nQVHxm9kDtGzScc2cbLza+w8dDbfO/ED/nJ\ntqeZP2IOi0bezuDK+kKXes09/9ruD2zrzmT5wQvb+Be/MasAFUmSJEmSpN5i81O9bs3mA5xo7SJ9\neDjJgYfo3j+alw4289FbRjrTrsCSiSRTGyYztWEyh04dYXnzKlbseZVf7PoVv9z1Ejc2TWfxyHlE\n9RNJXHZlqb7hT373tkKXIEmSJEmSrhObn+p1Z2badR0aSeJ4I5B0pl0RaqwazMMT7+f+8ffw2v71\nvNy8gjcObuSNgxsZVj2ExaPmM2fYLVSVFc/zViVJkiRJki7FZ35KMZXqM4Wy2SzvnHiXl3evYN2B\nN+nOdlORKmfusNu4Y9Q8htUMLXSJKiE+I07FoFTzXLqezHMVA/Ncis9nfqqUOPNT0gUlEgnGDxzL\n+IFj+fVJD7Jiz6ssa17F0uYVLG1eweT6idwxaj4zG6aSSqYKXa4kSZIkSdIH2PyUdFkDyuu4d9xd\n3DPmTjYceouXd69gy9FtbDm6jfqKQSwceTsLRsyhrry20KVKkiRJkiSdZfNT0hVLJVPcNGQmNw2Z\nyZ6WfSxrXsmqfa/x1I5neWbnL7l5yCzuGDWfcQNGl8wCSZIkSZIkqe+y+SnpQxlRO4zfjB7h4xPu\nZfXedSxtXsGa/etYs38dY+pGsXjUfG4dMovyVLrQpUqSJEmSpH7KBY+kmHygek42myUc3cbS3St4\n89BbZMlSk65m/vA5LBp5Ow1VgwtdooqYC2SoGJjnUnzmuYqBeS7F54JHKiXO/JR0TSQSCaYMnsSU\nwZM4fOooy/esYsWeV/nluy/x/LsvM6NxKneMmk9UP5FkIlnociVJkiRJUj9g81PSNddQVc+SCfdx\n/7i7WXfgTV5uXsGGQ2+x4dBbDKluZPHI+dw+/FaqyqoKXaokSZIkSSphRd/8jKLoBuDzwMAQwifz\n25LAF4EBwNoQwncLWKKki0in0swdfitzh9/KOyfeZenulby2fz0/2vokT+54ljnDbuGOkfMZUTus\n0KVKkiRJkqQS1KvNzyiKvg08CBwIIczosf1e4CtACvibEMKXL7aPEMIO4NEoin7UY/MSYBRwGNjd\nG7VLurbGDRjDuGljeGTiA6zcs4alzStZ3ryK5c2rmDToBhaPms+sxumkkqlClypJkiRJkkpEb8/8\n/A7wVeB7ZzZEUZQCvgbcQ65xuSaKoifJNUIfO+/znwkhHLjAfiNgRQjhG/mm6Au9ULukXlBXXsvH\nxn2Eu8YsZuPhzSzdvZK3j25l67EdDKoYyMIRt7Ng5BwGlNcVulRJkiRJktTH9WrzM4SwNIqicedt\nngNsy8/oJIqiHwBLQgiPkZsleiV2Ax35X2cu9+b6+mrKypxNpt7T1GSj7sMYNnQed0+bR/OJfTy3\n7WVe3rmKp3c+xzO7nmfeqFu4d9KdTGoYTyLhQoPKMc/V28xz6fowz9XbzHNJ0hmFeObnSOC9Hq93\nA3Mv9uYoihqALwE3R1H07/NN0p8AfxVF0SLg5csd8OjRtngVS5fQ1FTHwYMnC11Gn1ZODQ+Nvp97\nhn+UV/et4+XdK1j+7hqWv7uG0bUjWDxqAbcNvYnyVLrQpSrvK+u+QXumg6aqBoZUNdJU3UhTVSND\nqhupSVdf9f6u9ATFPFdvMs+l+MxzFQPzXIrPCwgqJUW/4FEI4TDwB+dtawMeLUxFknpLZVkli0fN\nZ9HIeWw9tp2Xd6/gzUNv8fdv/3/8dNvTzBsxm8Uj59FY1VDoUvu9mU3T+PHWp9h14r1ztk9riPjc\nLONZkiRJklQcCtH8bAZG93g9Kr9NkgBIJBJMrp/I5PqJHD19LLcw0p7VvPDuUl58dxnTGyIWj1rA\n1MGTSCaShS6338lkM0wbHPHTxM/IZN9/8kgykeQTEx8qYGWSJEmSJJ2rEM3PNcCkKIrGk2t6/hbw\nqQLUIakPqK8cxEMT7uXe8Xfz+oE3Wbp7BRsPv83Gw2/TVNXA4pHzuH34bKrTVYUutU/r6O7kZMdJ\nTna2cLKjhZMdree8bulo5UT+dUtHK1myH9jHopHzGFYzpADVS5IkSZJ0Yb3a/Iyi6PvAnUBjFEW7\ngT8NIXwriqI/BJ4jt8L7t0MIm3qzDkl9XzpZxpxhtzBn2C28e2I3LzevYO3+9fx429M8teM5Zg+7\nhTtGzWdk7fBCl1oUMtkMrZ1tucZlZwsnOs40MVs4mX/dkt92srOF9u6Oy+6zqqySunQtTQMbGVBe\nS3t3B5uPbAGguqyaB8bf09tfS5IkSZKkq5LIZj84e6fUHDx4svS/pArGB6oXTktnKyv3rGFZ80oO\nnz4KwISB47lj1HxuappBKllaq8h2dHecbVae7OjxzwVeX2x2Zk/JRJK6dC0DymupLa+lrryWunT+\n3+e9ri2vJZ0893pZd6ab//DKf6Kls5V/MGkJd45e8KG/W1NTXeJK3meeqzeZ51J85rmKgXkuxXel\neS71BUW/4JEkXUxtuoZ7xt7JXWMWs+nw27y8ewWbj2xh+/GdDCyvY8HI21k4Yi4DKwYUutQL6jk7\ns2cTs6UjP1Oz8/3ZmSc6W+i40tmZ5bUMqWo827Qc0KOBeabZWVdeS1VZFYnEhx/TpJIpZg+9mc1H\ntrBo5O0fej+SJEmSJPUWm5+S+rxkIsnMxmnMbJzG/raDLNu9kpV71/Lznb/k2Xde4OammSweNZ8J\nA8fxl6//Ne2ZDpqqGhhS1UhTdSNNVY0MqW6kJl0du5aO7o73bzHPNzNP9LjdvOcMzZbOy8/OTCVS\n1JXXMrSq8f3ZmReZoXmh2Zm9be7w25jaMLnkZtlKkiRJkkqDt71LMXlbTXE63dXOmv2vs3T3Cva0\n7gNgZO1whlY1se7gmx94/7SGiM/NevQD2y82O/OCr694dmYVdeU1+QZmXb55WZNvZJ77Ou7szL7C\n2yRVDMxzKT7zXMXAPJfi87Z3lRJnfkoqSZVlFSzK3/a+7dhOXm5ewRsHN9LcsvcD702QYEhVEz/a\n8mR+RfPWs7ebX+3szDPNy9p8c3NAeV1+xmZNwWZnSpIkSZLUX3kGLqmkJRIJJtXfwKT6GzjWfpzl\nzav55a5f0ZXtPvueLFle2r38nM+dmZ05pLqpx63lNe/PzOzxuqqssl/MzpQkSZIkqa+x+Smp3xhU\nMZAHb/gYI2qG8a1N/xOAdDLNr098gIaqBurKa3IzNdM1lDk7U5IkSZKkPs+ze0n9zqym6dSma2jp\nbOXhCfezeNT8QpckSZIkSZJ6QbLQBUjS9ZZKppg99GaGVQ9h0cjbC12OJEmSJEnqJc78lNQvzR1+\nG1MbJpNKpgpdiiRJkiRJ6iU2PyX1S6PrRgAjCl2GJEmSJEnqRd72LkmSJEmSJKkk2fyUJEmSJEmS\nVJJsfkqSJEmSJEkqSTY/JUmSJEmSJJUkm5+SJEmSJEmSSpLNT0mSJEmSJEklyeanJEmSJEmSpJJk\n81OSJEmSJElSSbL5KUmSJEmSJKkk2fyUJEmSJEmSVJJsfkqSJEmSJEkqSTY/JUmSJEmSJJUkm5+S\nJEmSJEmSSpLNT0mSJEmSJEklyeanJEmSJEmSpJJUVugCLieKohuAzwMDQwifzG8bA/wlcATYEkL4\ncgFLlCRJkiRJklSEenXmZxRF346i6EAURRvP235vFEUhiqJtURT9u0vtI4SwI4Tw6HmbZwI/CiF8\nBrj5GpctSZIkSZIkqQT09szP7wBfBb53ZkMURSnga8A9wG5gTRRFTwIp4LHzPv+ZEMKBC+x3FfCj\nKIo+A/xdL9QtSZIkSZIkqY/r1eZnCGFpFEXjzts8B9gWQtgBEEXRD4AlIYTHgAevcNf/GPjT/P5/\nBPztpd5cX19NWVnq6oqXrkJTU12hS5D6BfNcvc08l64P81y9zTyXJJ1RiGd+jgTe6/F6NzD3Ym+O\noqgB+BJwcxRF/z7fJH0W+EIURZ8C3rncAY8ebYtVsHQpTU11HDx4stBlSH3alZ6gmOfqTea5FJ95\nrmJgnkvxeQFBpaToFzwKIRwG/uC8bRuBTxamIkmSJEmSJEl9Qa8ueHQRzcDoHq9H5bdJkiRJkiRJ\n0jVTiJmfa4BJURSNJ9f0/C3gUwWoQ5IkSZIkSVIJ69WZn1EUfR9YmftltDuKokdDCF3AHwLPAZuB\n/x1C2NSbdUiSJEmSJEnqf3p7tfd/eJHtPwd+3pvHliRJkiRJktS/FeKZn5IkSZIkSZLU62x+SpIk\nSZIkSSpJNj8lSZIkSZIklSSbn5IkSZIkSZJKks1PSZIkSZIkSSXJ5qckSZIkSZKkkmTzU5IkSZIk\nSVJJsvkpSZIkSZIkqSTZ/JQkSZIkSZJUkmx+SpIkSZIkSSpJNj8lSZIkSZIklSSbn5IkSZIkSZJK\nks1PSZIkSZIkSSXJ5qckSZIkSZKkkmTzU5IkSZIkSVJJsvkpSZIkSZIkqSTZ/JQkSZIkSZJUkmx+\nSpIkSZIkSSpJNj8lSZIkSZIklSSbn5IkSZIkSZJKks1PSZIkSZIkSSXJ5qckSZIkSZKkkmTzU5Ik\nSZIkSVJJsvkpSZIkSZIkqSTZ/JQkSZIkSZJUkmx+SpIkSZIkSSpJiWw2W+gaJEmSJEmSJOmac+an\nJEmSJEmSpJJk81OSJEmSJElSSbL5KUmSJEmSJKkk2fyUJEmSJEmSVJJsfkqSJEmSJEkqSTY/JUmS\nJEmSJJUkm5+SJEmSJEmSSpLNT0mSJEmSJEklyeanJEmSJEmSpJJk81OSJEmSJElSSSordAHq36Io\nKge+BdwGnAI+FUJ4+wLv+1fA75Nr2P+7EMJP8ts/BfxHoBz48xDC13p8Jg08C3wxhPDSBfb5EvB7\nIYR3ru23Orv/vwH+B1ALfCGEcOeFtl1mH7cBfxBC+Ow1qulB4CngthDCa9din70tiqI/Bv4p0A10\nAX8dQvj6FXxuHPBSCGFcrxaYO9ZIYG0IYXhvH0sqVua5eX45xZznURSlgK8Ci4AE8M0Qwl/01vGk\nYmaem+eXU+R5XgZ8HVgAZIDHQgj/q7eOJ6lvcOanCu2fA60hhKnAHwPfPf8NURTNBn4HuAlYCPyX\nKIoG5xtOX8pvmwX8kyiKpuU/EwEvAfOvx5e4kBDCZ0MIay+37TL7WHutBlZ5/xj4EfAH13CfvSaK\noi8AHwfuDCHMAO4BfjuKoj8paGE9RFF0P/ArYFiha5EKzDy/9D7M8+LO838MNAA3AnPI/Td4S2FL\nkgrGPL/0Pszz4s7z3wYGAjOAjwB/FUVRXWFLklRozvzURUVRdCfwH4A2YCqwAfgUMIIeV+zyfwES\nQvhCj8+OJncF83yLQggne7x+APi/8p9fGkVRYxRFY0II7/Z4z/3AT0IIp4HT+SvCD5KbmfFiCOFI\n/pg/Aj4J/BnwKPBfyA3YrvZ7/6P855LAa8DnQgin89s/D5wAVgF1IYTfi6LoHXJ/+b+T/5mduYr8\nEvCF8/bdc1tjFEXPAiOB1fnjtEdRdDB/3GHAvwE+33N/IYSXel41jaLoO0AruUHmoHztnyY34Hw8\nhPCv8sduBO4iN0hdH0XRvwohnMj/3pkr9FlgDbmr+HXkrvpPAdqBfxlCeDGKomwIIZH/3O/lv/uZ\nn8Pq/P4XAX+UP95g4BDw6yGEfRc41j8FAvCxEMKWKIpqgLeBKP/9p4cQ9gOEEA5GUfT7wOooiv4r\n8G+B24Ex5GbsrMzXDPBGj5/7UOAbwGhyV4D/fQjh+fx/u2c/3/OKdRRFzwFDOde/CCH86rxtjwK/\nTu7/D6komefmOeb55fJ8I7AyhJABWqMo2pE/xjqkImKem+eY55fM8xDCd6Mo+vsQQjbfjO8AOpHU\nrznzU5czH/hDcoOrMcCvXcmHQgjvhRBuusA/J8976whgb4/Xe4FRV/iei342hPBvQwiPX0mtPUVR\nNJ3cwGJ+COEm4ADwr6MoGkVusHYHuZ9JdLX7voDxwP9BbpZJHe9f7W0Evpw//pX+RT0ihDCL3ED1\nb/P7ugn4/SiKBubf89vAL0LuNqK15K7Wn7ll+8/JDW6mAylyg94vAtvyV/0/Te4q/uU8E0KIgAHk\nBmXzQwiTgW3krghf6Fj3kZtR8Dv5fXwCeBqYTm7WwTs9DxBCeIvcYG9KflNlCGFafmD0PeDfhhBu\nAXb0+NhXgG+HEG4ld6X6Gz2uAPf8fM/j/NoF/vs9v/FJCOETIYSNV/CzkQrNPDfPzfOL5HkIYVUI\nYVP+5zif3OzPpVfwc5IKwTw3z83zS4/Pu6Lc4wzWkLsl//QV/JwklTBnfupyNoYQdgNEUbSZ3FXC\ny7qKK8uJC7wnc97ri73nQs378z97tT4CTAJW5e7MoZzcrI95wCshhH0A+au5H4t5rKUhhK35/f09\nuVtevpL/vdVXua9n8v/eRe7P7EB+v0eAeuB4fv//d/59PyQ3aP4673+33QAhhE/nP/ufyM0kIISw\nIf++y1mdf/+2KPccqM9GuR/kPGD7JY61Hnie3ODwd8nNaMhy8YxKn3/M/JXzESGE5/Pbv0NuhgHA\n3cCUKIr+rMfnJ/T8/PmuYuan1FeY5+a5ef6+C+Z5FEV3AD8AfjuEcPQiNUuFZp6b5+b5+y6Y5yGE\nz0ZR9H8CL0dR9EoI4RcXqVtSP2DzU5fT8ypZltxA58y/z0hz3hXQEMJ75K5sXk4zudtHtuVfDwf2\nXOQ99HjPy/kaFp23/fzPXq0U8L9DCP8cIIqiWnL/nyzk3O/c8/v2/Hn0/Ev/crp6/DrRc58hhFMX\neP+ljtNxkf0CEEXRzcBM4CtRFP05ue85IoqieZz3ZxdFUVP+l+dvnwJsyf86EULIXqCOU/nfvxX4\nPvDfyD3DqPv879jzWCF3S9KuKIp+HRgaQlgdRVE1kI6iKAohhB6fmU5uYP02uavEZ35W5/932fPn\nkAI+Gt6/BWsEsB94uMfnzxFCuKJZFFIfYp6b52e2m+cXkK/5vwO/GS6wEItURMxz8/zMdvP8PPnv\neSKEsDWEcDiKomfIzeS1+Sn1Y972rg/jGFAfRVFTFEUVwL0x9vVz4B8BRFG0EDgdzn2eEOSumn4i\niqLq/F/GdwEvkLsSeVe+jmpyt2M8G6MWyD2E/ZEoioZEUZQgdxL0x+SeIXRrFEWjoyhKAr/V4zOH\nyN0CArDkKo61MIqiMfn9/S6573MpPY/z8FUcB3JXlf86hDAmhDAuhDAa+Dtyz/NZA8yNoujMAPbP\nyX2PpeS/Z35g9Sy5AcwhYHr+5/PxixzvDnLPPPofwFvkrsKnLnEsgG8Df5mvixBCG7lbeb4VRdGQ\nfB1DgG8C/zn/+2eFEA4Du6IoeiC/6VM9fvtF4J/l9zENeBOovtwPTeoHzHPz3Dzn7OIt/x24x8an\n+ijz3Dw3z3PmAv85iqJklLuN/teAV67BfiX1YTY/ddVCCMfJPV9nDbkBwasxdvdXQEUURZvI/cV6\n5jaL26Io+nn+eK8C/zN/vOXAn4QQmkMIzeQecP4rYD3wv/Lv/dBCCG+Qu/XkRWATuf9HvhxCOAT8\nE3LPulnDuVdU/5TcFds15AaeV2oTuQHFBnJXz7916bfzn4F/FkXROqDqKo5TTm6g8fXztv834DfI\nXVn9I+C5KIo25l//LbnvNSmKojeAvwc+nb+a/O/I/RxWknsQ+oX8EJgVRdGb5H6WbwLjQwh7LnIs\ngJ+QW2n3787sJITwZXJ/9s/n3/8C8PchhC9e5Li/A/xpFEWv8/5tM5B7dtPt+Xp+mP8u5z/fSup3\nzHPzHPP8jP9IbibZ96IoWp//52INBKnomOfmOeb5Gd8gN4N0A7mm59dCCCuvwX4l9WGJbDZb6Bqk\ngohyqzP+Xjjvgd1X+NnfI7+K4rWtqn/KX6W+D/iDEIInm5KuinlePMxzSXGY58XDPJdUSnzmp6Ri\n8OfAQ+QGWJKkvss8l6TSYJ5LKhnO/JQkSZIkSZJUknzmpyRJkiRJkqSSZPNTkiRJkiRJUknqF8/8\nPHjwpPf2q9fU11dz9GhbocuQ+rSmprrElbzPPFdvMs+l+MxzFQPzXIrvSvNc6guc+SnFVFaWKnQJ\nkqRrwDyXpNJgnkuSerL5KUmSJEmSJKkk2fyUJEmSJEmSVJJsfkqSJEmSJEkqSTY/JUmSJEmSJJUk\nm5+SJEmSJEmSSpLNT0mSJEmSJEklqazQBXwYURQlgS8CA4C1IYTvFrgkSVIR+8q6b9Ce6aCpqoEh\nVY00VTfSVNXIkOpGatLVhS5PkiRJktRLrnvzM4qibwMPAgdCCDN6bL8X+AqQAv4mhPDlS+xmCTAK\nOAzs7sVyJUklYGbTNH689Sl2nXjvnO3TGiI+N+vRAlUlSZIkSepthZj5+R3gq8D3zmyIoigFW5Sm\nXwAAIABJREFUfA24h1wzc00URU+Sa4Q+dt7nPwNEwIoQwjeiKPoR8MJ1qFuS1EfNHnozj2/7Od3Z\n7rPbkokkn5j4UAGrkiRdLWfyS5Kkq3Xdm58hhKVRFI07b/McYFsIYQdAFEU/AJaEEB4jN0v0HFEU\n7QY68i8zvViuJKkE1JXXMnngJDYfe/vstjlDbmNYzZACViVJulrO5JckSVerWJ75ORLoOYLZDcy9\nxPt/AvxVFEWLgJcvt/P6+mrKylLxKpQuoamprtAlSP1CnDyv65gIvN/8XLlnLdv3HeX+KYu578Zb\nSCZdA1DmuXS9fNg8v69uEY9v/zndmfdn8qcSSX5/zm/RNMD/f/U+81ySdEaxND+vSgihDbjiS7tH\nj7b1YjXq75qa6jh48GShy5D6tCs9Qfmwed7VneH1NZCdXE4i3UH30SZS1a0crNjKd8NWvrfhB0yq\nnsHD0xcztqHpQx1DfZ95LsXX23kOMHnAuTP5F46cR3l7jf//6izzXIrPCwgqJcXS/GwGRvd4PSq/\nTZKk2NZsPsCJ1i7Sh4eTHHiIjq03k0omue+uWtYdXseRsnfY0rWa/3f9amo6R3D7sNk8MH02leny\nQpcuSTpP+cmxnJnJn83C2h07qe5Yzb1Tb6Ms5d1ekiTpXMXS/FwDTIqiaDy5pudvAZ8qbEmSpFLx\n/Gu7Aeg6NJLE8UYgSXcGdm2v4D/9xh9wuKWFn25cxsaj62mr2MOLR57gxV89w6iyiPsmL+KmUeMK\nWr8kKaerO8Nbb6bJTk6TSHeS7SyntXwPzxz4Mc80/4yx5VN5aOpCpg4bffmdSZKkfiGRzWav6wGj\nKPo+cCfQCOwH/jSE8K0oiu4H/oLcCu/fDiF86Vod8+DBk9f3S6pf8bYaKb6mprrElbzveuT5une3\n88zWV9jTHaCsE4B0ewM31t/EIzMXUF9T29slqEDMcym+3s7zlRv38c2n3yI9ZjPJgYdo3zCfVE0r\nwyYd4khqB6S6AKhob+LmxltYMmM+A6qqPsyh1IeZ51J8V5rnUl9w3ZufhWDzU73JwZUUXzE1P884\n1dHBzzatZtX+tbSl95JIQLY7RUN2HB8dN487Js5wkaQSY55L8fV2nn/xu2vZufcEieoTJNLtZI7n\nntM884YGPvvxyTy1cRWvHVzH6Yr9AGS7yxjCDdw1fj4LbphibvcT5rkUn81PlRKbn1JMDq6k+Iqx\n+dnTzkP7eeKtZWxr20i2PLdIR7KjhknVM1kyfZGLJJUI81yKr1jyfMv+PTy1eRk7298imz4FQLKj\njim1N7JkxiJGDRrcm4dXgZnnUnw2P1VKbH5KMTm4kuIrlpPly+nKdPPSlg289O4qjiTfIZHMkM1C\nbedI5g67zUWS+jjzXIqv2PK8q7ubX779Ost2v8qx1C4SySzZTIK6rlHMHzGb+6bdSnlZ+nqUouvI\nPJfis/mpUmLzU4rJwZUUX7GdLF+Jwy0n+OnGV9h4dD2dFUdzG7vKXSSpDzPPpfiKOc8PnDjOTzcu\nY9OJN+guP57b2FnB6PQUHowWMmPk2OtdknqJeS7FZ/NTpcTmpxSTgyspvmI+Wb4SLpJUGsxzKb6+\nkuev7tzCc9tXsC+z9Wxul7c3ctPgm3n4xvkMrKopZHmKyTyX4rP5qVJi81OKycGVFF9fOVm+HBdJ\n6tvMcym+vpbnbR2neXLDatYefI229L6zud2YvYG7xt/OognTze0+yDyX4rP5qVJi81OKycGVFF9f\nO1m+EjsP7eeJTcvYdspFkvoK81yKry/n+bYDe3ly83J2nNrUI7drmVyTy+0xgxsLXKGulHkuxWfz\nU6XE5qcUk4MrKb6+fLJ8OV2Zbn61ZQMvX2SRpAenz6Ei7WIbxcA8l+IrhTzvynTzQniDpe+u5mhq\nVz63E9R2juD24bN5YNpsc7vImedSfDY/VUpsfkoxObiS4iuFk+Ur4SJJxc08l+IrtTw/2HKCJzYs\nZ8OxN+g6J7encN/kheZ2kTLPpfhsfqqU2PyUYnJwJcVXaifLV+JiiyTNGnwzD8+Y7yJJBWCeS/GV\ncp6v3bWVZ7etYG/3Fhe3K3LmuRSfzU+VEpufUkwOrqT4Svlk+XIuvkjSeD467nYXSbqOzHMpvv6Q\n55da3O4jY2/nzkkzze0CM8+l+Gx+qpTY/JRicnAlxdcfTpavhIskFZZ5LsXX3/J856H9PPHWMra1\nvZ/biY4aJlXP4OHpi83tAjHPpfhsfqqU2PyUYnJwJcXX306WL+fCiyTlFttwkaTeY55L8fXXPO/K\ndPPSlg28tGs1R1I7zy5uV9M5grlDb+PBGXOoTJcXusx+wzyX4rP5qVJi81OKycGVFF9/PVm+EmcW\nSdpwdP15i21EPDB5ETe62MY1Y55L8ZnncLilhSc2LufNo+vprDiS29hVzojUZO6fvJCbR99Q2AL7\nAfNcis/mp0qJzU8pJgdXUnyeLF+Z197dzrMuktRrzHMpPvP8XK+/t4NntrxCc3eAsg4A0u31zKi/\niUdmLKChdkCBKyxN5rkUn81PlRKbn1JMDq6k+DxZvjouktQ7zHMpPvP8wk53dvCzTWtYvW8tLenm\nXG5nkgzOjOOOMbfzkckzKUumCl1myTDPpfhsfqqU2PyUYnJwJcXnyfKHd6lFkh6esZgxgxsLXGHf\nYZ5L8Znnl7fr8EGe2LSMrW0byJS3ApDoqGZC1XQ+Pm0RE5qGFbjCvs88l+Kz+alSYvNTisnBlRSf\nJ8vxXWqRpNuHz+aBabNdJOkyzHMpPvP8ymUyGV7etokX31nJ4cROEqluslmo7hzOnCG38tCM26kq\nd5GkD8M8l+Kz+alSYvNTisnBlRSfJ8vX1sUXSZrCA5MXukjSRZjnUnzm+YdztLWVJza+whtHXqej\n4nBuY1eaYclJ3DdpAbeNnVTYAvsY81yKz+anSonNTykmB1dSfJ4s955LL5K0gPqamgJXWDzMcyk+\n8zy+Dc27eDosY3dngHQ7AGXtg5g+cBaP3LiIJhdJuizzXIrP5qdKic1PKSYHV1J8niz3PhdJujzz\nXIrPPL922js7eWbzWlbuWcPJdDOJRJZsJkl991gWjZ7L3VNmuUjSRZjnUnw2P1VKbH5KMTm4kuLz\nZPn6cpGkCzPPpfjM896x+8ghHt+0jNC6kUx5LqcSnVWMr5jGx6cuYtLQEQWusLiY51J8Nj9VSmx+\nSjE5uJLi82S5MFwk6VzmuRSfed67MpkMy3ds5oWdKznIdhKpbgAq24dy25BbeWj67dRWVha4ysIz\nz6X4bH6qlNj8lGJycCXF58ly4V3JIklfWfcN2jMdNFU1MKSqkabqRpqqGhlS3UhNurqwX+AaMM+l\n+Mzz6+f4qVae2LCS9Ydfp73iYG5jV5qhyYl8bMJ85oyd1G8fZ2KeS/HZ/FQpsfkpxeTgSorPk+Xi\n8tq723lm63L2dm85Z5GkYXUNvNex5QPvn9YQ8blZj17vMq8581yKzzwvjE173uVnYTm7OjafXSQp\n1TGQaXWzeGTmIoYOGFjgCq8v81yKz+anSklZoQuQJEnF5dYxE7h1zAROdXTw9KbVrN6/lrbyvbzX\ncZhsFhI9hsLJRJJPTHyocMVKkpg+YgzTR3yKjq5Ontu8jlea13Ci7D02tC/lzVeXMbB7DAtHzuHX\npt5CWSpV8jP5JUnqqU/O/IyiaAzwl8ARYEsI4cuXer9XltWbvLIsxedMoeJ3ZpGkrZ2vQbL77PZB\niWH8kxs/zdiGpgJWd22Y51J85nnx2HPsCE9sXM7mljfpLj+R29hZybjyaYweWsuyfUs/8Bln8ks6\nw5mfKiXXvfkZRdG3gQeBAyGEGT223wt8BUgBf3OphmYURQ8A9SGE/xlF0Q9DCL95qWM6uFJvcnAl\nxefJct/xjZee583MLwDOzgLNZqG2cyRzh93GA9NnU5kuL3CVH455LsVnnhefTCbDyp2B53es4ADb\nIdWV+40scN5M/s/P+ZcMqxlSkDqvJfNcis/mp0pJIW57/w7wVeB7ZzZEUZQCvgbcA+wG1kRR9CS5\nRuhj533+M8Aq4EdRFH0G+LvrULMkSf1eV3eGzRvKyU4uJ5HuoPO9yQwdOICWyu20VjTz4pFmXvzV\nM4xMRdw/eQE3jb6h0CVLUr+XTCZZMGEqCyZM5eTpUzyxYQXrDr1Oe8WBc943sTZiSFVjgaqUJKn3\nXPfmZwhhaRRF487bPAfYFkLYARBF0Q+AJSGEx8jNEj1HFEX/GvjT/L5+BPxtL5ctSVK/t2bzAU60\ndpE+PJzkwEN07xvH/gMp/uzRB9jbuo9nt75CM1toTmzgm1s3kN44mBvrb2LJjIU01NYWunxJ6vfq\nKqv4ndl38TvcxX/95ePsSK04+3tbTm7mj3/x/zC19kaWzFzEiIH1BaxUkqRrp1gWPBoJvNfj9W5g\n7iXe/yzwhSiKPgW8c7md19dXU1aWilWgdClNTXWFLkHqF8zzwnr5zXUAdB0aSeJ4I5CkO5PlJ8t2\n8oXfn8ev3XoTpzo6+OGry1i6ayUny5t5re1F1q56iSGJCdw3ZRH333gryWSysF/kEsxz6fowzwur\nsytD85YGshPzM/n3j6a6JkNH9R42dixnw5pXGJQdw90TFvDILbdTnk4XuuSrZp5Lks4oyIJH+Zmf\nT5955mcURZ8E7g0hfDb/+tPA3BDCH16L4/lMIfUmnykkxecz4krTrsMHeXzTUra2bSRb3gpAoqOG\nidXTWTJtEeMbhxa4wnOZ51J85nnfsHLjPr759Fukx2wmOfAQ7RsWkEqm+Oe/GfHK7td46+Qb5yyS\nNLZ8Cg9OWcS04aMLW/gVMs+l+Hzmp0pJscz8bAZ6/k06Kr9NkiT1UWMbmvijxZ8gk3mEl7Zu4Fe7\nVnE49Q5bu17lv7zxKjWdI5g79FYemD6XqvK+uUiSJPVFz7+2G/jgTP7nVx/kX/zGQ2QyD/Dqrq38\nYvsK9ie3siu7nq9tXk/F+iZubryZJTMWMKCqqrBfQpKkK1QsMz/LgC3AXeSanmuAT4UQNl2L43ll\nWb3JK8tSfM4U6j+Otrbw0w2v8ObR9XRWHM5t7EozPDWZ+yYt5NYxEwpWm3kuxWeel56W06d5auNK\n1h5cx+mK/QBku8to4gbuHj+fBTdMKbrHmZjnUnzO/FQpue7NzyiKvg/cCTQC+8ktXPStKIruB/6C\n3Arv3w4hfOlaHdPBlXqTgyspPk+W+6f1u9/hmS3L2N0VoKwDgLL2emYOmsUjMxfSUDvgutZjnkvx\nmeelbcv+PTy1eRk7298imz4FQLKjjim1M1kyYzGjBg0ucIU55rkUn81PlZKCzPy83hxcqTc5uJLi\n82S5f2vv7ORnb61h1d41tKT3kEhkyWaS1HeP5c4xc/lINIuyZO8vjGKeS/GZ5/1DV3c3z4f1LH1v\nNcdSu0gks2QzCeq6RjF/xGzum3Yr5WWFWyTJPJfis/mpUmLzU4rJwZUUnyfLOmPX4YM8+dZytrRu\nIFPeAkCio5obqnKLJE1oGtZrxzbPpfjM8/7nwInjPL5xOZuOv0FXxbHcxs4KRqen8GC0kBkjx173\nmsxzKT6bnyolNj+lmBxcSfF5sqzzZTIZXt62iV+9s4pDiR0kUt1ks1DdOYzZQ27loRlzqS6vvKbH\nNM+l+Mzz/u3VnVt4bvsK9mW2QlknAOXtjdzUcDMPz5zPwKqa61KHeS7FZ/NTpcTmpxSTgyspPk+W\ndSlHW1t5cuMK1h9ZR0ePRZKGJSdx78QFzB436ZocxzyX4jPPBdDWcZonN6xm7cHXaEvvI5GAbHeK\nxuwN3DX+dhZNmN6riySZ51J8Nj9VSmx+SjE5uJLi82RZV2pD8y5+FpbzXufbkG4HoKx9ENMHzuLh\nGQsZMmDgh963eS7FZ57rfNsO7OXJzcvZcWoT2fI2AJIdtUyumckj0xcxanDjNT+meS7FZ/NTpcTm\npxSTgyspPk+WdbXaOzt5ZvNaVu5Zw8l089lFkgZ1j2Hx6LncPeWmq14kyTyX4jPPdTFdmW5eCG+w\n9N3VHE3tIpHMkM0mqO0cwfzhs7lv2mwq0tdmkSTzXIrP5qdKic1PKSYHV1J8niw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WMVostr2mirbWFD85V88fl76eiZOLvVlY2Bd157zyV7T5I0ny1b2MCyhQ3ADWNtwyMjPLe/k80H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\nJ4CHO3qMgwdPdHZZ0hm1tf3Yu/doocuQurWOXqCY58on81xKzjxXMTDPp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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc7a9179ef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pltDf = df.loc['D3Q27'].reset_index()\n",
+    "\n",
+    "g = sns.FacetGrid(pltDf, row=\"nu\", col='equilibriumAccuracyOrder',\n",
+    "                  hue=\"useContinuousMaxwellianEquilibrium\",  hue_kws=dict(marker=[\"^\", \"v\"]),\n",
+    "                  row_order=pltDf['nu'].unique()[::-1],\n",
+    "                  size=4, aspect=1.4, legend_out=True)\n",
+    "\n",
+    "\n",
+    "#g = sns.FacetGrid(pltDf, col=\"nu\", hue=\"useContinuousMaxwellianEquilibrium\", \n",
+    "#                  col_wrap=2, col_order=pltDf['nu'].unique()[::-1],\n",
+    "#                  size=4, aspect=1.4, legend_out=True)\n",
+    "g.map(plt.plot, \"L\", 'phaseError', marker='o').add_legend()\n",
+    "g.set(xscale=\"log\", yscale=\"log\");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/full_scenarios/shear_wave/scenario_shear_wave.py b/lbmpy_tests/full_scenarios/shear_wave/scenario_shear_wave.py
new file mode 100644
index 0000000000000000000000000000000000000000..22a8f03dfe58801090ec62b596b3c73b22f2244e
--- /dev/null
+++ b/lbmpy_tests/full_scenarios/shear_wave/scenario_shear_wave.py
@@ -0,0 +1,223 @@
+"""Shear wave scenario from
+    The cumulant lattice Boltzmann equation in three dimensions: Theory and validation
+    by  Geier, Martin; Schönherr, Martin; Pasquali, Andrea; Krafczyk, Manfred (2015)
+
+    Chapter 5.1
+"""
+import numpy as np
+import sympy as sp
+from lbmpy.scenarios import create_fully_periodic_flow
+from lbmpy.relaxationrates import relaxation_rate_from_lattice_viscosity, relaxation_rate_from_magic_number
+from lbmpy.creationfunctions import update_with_default_parameters
+
+
+def get_exponent_term(l, **kwargs):
+    pi = np.pi
+    return (2 * pi / l) ** 2 + (4 * pi / (3 * l)) ** 2
+
+
+def get_initial_velocity_field(l, l_0, u_0, v_0, y_size, **kwargs):
+    pi = np.pi
+    domain_size = (l, y_size, 3 * l // 2)
+    vel = np.zeros(domain_size + (3,))
+    ranges = [np.arange(n, dtype=float) for n in vel.shape[:-1]]
+    x, y, z = np.meshgrid(*ranges, indexing='ij')
+
+    vel[..., 0] = u_0 * l_0 / l
+    vel[..., 1] = v_0 * l_0 / l * np.sin(2 * pi * x / l) * np.cos(4 * pi * z / (3 * l))
+    vel[..., 2] = 0
+
+    return vel
+
+
+def get_analytical_solution(l, l_0, u_0, v_0, nu, t):
+    pi = np.pi
+    domain_size = (l, 3, 3 * l // 2)
+    vel = np.zeros(domain_size + (3,))
+    ranges = [np.arange(n, dtype=float) for n in vel.shape[:-1]]
+    x, y, z = np.meshgrid(*ranges, indexing='ij')
+
+    exponent_term = (2 * pi / l) ** 2 + (4 * pi / (3 * l)) ** 2
+    vel[..., 0] = u_0 * l_0 / l
+    vel[..., 1] = v_0 * l_0 / l * np.sin(2 * pi * (x + u_0 * t) / l) * \
+                  np.cos(4 * pi * z / (3 * l)) * np.exp(-nu * t * exponent_term)
+    vel[..., 2] = 0
+
+    return vel
+
+
+def plot_y_velocity(vel, **kwargs):
+    import matplotlib.pyplot as plt
+    from matplotlib import cm
+    vel = vel[:, vel.shape[1]//2, :, 1]
+    ranges = [np.arange(n, dtype=float) for n in vel.shape]
+    x, y = np.meshgrid(*ranges, indexing='ij')
+    fig = plt.gcf()
+    ax = fig.gca(projection='3d')
+
+    ax.plot_surface(x, y, vel, cmap=cm.coolwarm, rstride=2, cstride=2,
+                    linewidth=0, antialiased=True, **kwargs)
+
+
+def fit_and_get_slope(x_values, y_values):
+    matrix = np.vstack([x_values, np.ones(len(x_values))]).T
+    m, _ = np.linalg.lstsq(matrix, y_values, rcond=None)[0]
+    return m
+
+
+def get_phase_error(phases, evaluation_interval):
+    xValues = np.arange(len(phases) * evaluation_interval, step=evaluation_interval)
+    phaseError = fit_and_get_slope(xValues, phases)
+    return phaseError
+
+
+def get_viscosity(abs_values, evaluation_interval, l):
+    y_values = [np.log(v) for v in abs_values]
+    x_values = np.arange(0, evaluation_interval * len(y_values), evaluation_interval)
+    m = fit_and_get_slope(x_values, y_values)
+    exp_term = get_exponent_term(l)
+    return - m / exp_term
+
+
+def get_amplitude_and_phase(vel_slice):
+    fft = np.fft.rfft2(vel_slice)
+    fft_abs = np.abs(fft)
+    fft_phase = np.angle(fft)
+    max_index = np.unravel_index(fft_abs.argmax(), fft_abs.shape)
+    return fft_abs[max_index], fft_phase[max_index]
+
+
+def run(l, l_0, u_0, v_0, nu, y_size, periodicity_in_kernel, **kwargs):
+    inv_result = {
+        'viscosity_error': np.nan,
+        'phase_error': np.nan,
+        'mlups': np.nan,
+    }
+    if 'initial_velocity' in kwargs:
+        del kwargs['initial_velocity']
+
+    print("Running size l=%d nu=%f " % (l, nu), kwargs)
+    initial_vel_arr = get_initial_velocity_field(l, l_0, u_0, v_0, y_size)
+    omega = relaxation_rate_from_lattice_viscosity(nu)
+
+    kwargs['relaxation_rates'] = [sp.sympify(r) for r in kwargs['relaxation_rates']]
+    if 'entropic' not in kwargs or not kwargs['entropic']:
+        kwargs['relaxation_rates'] = [r.subs(sp.Symbol("omega"), omega) for r in kwargs['relaxation_rates']]
+
+    scenario = create_fully_periodic_flow(initial_vel_arr, periodicity_in_kernel=periodicity_in_kernel, **kwargs)
+
+    if 'entropic' in kwargs and kwargs['entropic']:
+        scenario.kernelParams['omega'] = kwargs['relaxation_rates'][0].subs(sp.Symbol("omega"), omega)
+
+    total_time_steps = 20000 * (l // l_0) ** 2
+    initial_time_steps = 11000 * (l // l_0) ** 2
+    eval_interval = 1000 * (l // l_0) ** 2
+    scenario.run(initial_time_steps)
+    if np.isnan(scenario.velocity_slice()).any():
+        return inv_result
+
+    magnitudes = []
+    phases = []
+    mlups = []
+    while scenario.time_steps_run < total_time_steps:
+        mlup_current_run = scenario.benchmark_run(eval_interval)
+        if np.isnan(scenario.velocity_slice()).any():
+            return inv_result
+        magnitude, phase = get_amplitude_and_phase(scenario.velocity[:, y_size // 2, :, 1])
+        magnitudes.append(magnitude)
+        phases.append(abs(phase))
+        mlups.append(mlup_current_run)
+
+    assert scenario.time_steps_run == total_time_steps
+    estimated_viscosity = get_viscosity(magnitudes, eval_interval, l)
+    viscosity_error = abs(estimated_viscosity - nu) / nu  # called ER_\nu in the paper
+
+    result = {
+        'viscosity_error': viscosity_error,
+        'phaseError': get_phase_error(phases, eval_interval),
+        'mlups': max(mlups),
+    }
+    print("   Result", result)
+    return result
+
+
+def create_full_parameter_study():
+    from pystencils.runhelper import ParameterStudy
+
+    params = {
+        'l_0': 32,
+        'u_0': 0.096,
+        'v_0': 0.1,
+        'ySize': 1,
+        'periodicityInKernel': True,
+        'stencil': 'D3Q27',
+        'compressible': True,
+    }
+    ls = [32 * 2 ** i for i in range(0, 5)]
+    nus = [1e-2, 1e-3, 1e-4, 1e-5]
+
+    srt_and_trt_methods = [{'method': method,
+                            'stencil': stencil,
+                            'compressible': comp,
+                            'relaxation_rates': ["omega", str(relaxation_rate_from_magic_number(sp.Symbol("omega")))],
+                            'equilibrium_order': eqOrder,
+                            'maxwellian_moments': mbEq,
+                            'optimization': {'target': 'cpu', 'split': True, 'cse_pdfs': True}}
+                           for method in ('srt', 'trt')
+                           for stencil in ('D3Q19', 'D3Q27')
+                           for comp in (True, False)
+                           for eqOrder in (1, 2, 3)
+                           for mbEq in (True, False)]
+
+    methods = [{'method': 'trt', 'relaxation_rates': ["omega", 1]},
+               {'method': 'mrt3', 'relaxation_rates': ["omega", 1, 1], 'equilibrium_order': 2},
+               {'method': 'mrt3', 'relaxation_rates': ["omega", 1, 1], 'equilibrium_order': 3},
+               {'method': 'mrt3', 'cumulant': True, 'relaxation_rates': ["omega", 1, 1],  # cumulant
+                'maxwellian_moments': True, 'equilibrium_order': 3,
+                'optimization': {'cse_global': True}},
+               {'method': 'trt-kbc-n4', 'relaxation_rates': ["omega", "omega_f"], 'entropic': True,  # entropic order 2
+                'maxwellian_moments': True, 'equilibrium_order': 2},
+               {'method': 'trt-kbc-n4', 'relaxation_rates': ["omega", "omega_f"], 'entropic': True,  # entropic order 3
+                'maxwellian_moments': True, 'equilibrium_order': 3},
+
+               # entropic cumulant:
+               {'method': 'trt-kbc-n4', 'relaxation_rates': ["omega", "omega_f"], 'entropic': True,
+                'cumulant': True, 'maxwellian_moments': True, 'equilibrium_order': 3},
+               {'method': 'trt-kbc-n2', 'relaxation_rates': ["omega", "omega_f"], 'entropic': True,
+                'cumulant': True, 'maxwellian_moments': True, 'equilibrium_order': 3},
+               {'method': 'mrt3', 'relaxation_rates': ["omega", "omega_f", "omega_f"], 'entropic': True,
+                'cumulant': True, 'maxwellian_moments': True, 'equilibrium_order': 3},
+               ]
+
+    parameter_study = ParameterStudy(run, database_connector="shear_wave_db")
+    for L in ls:
+        for nu in nus:
+            for methodParams in methods + srt_and_trt_methods:
+                simulation_params = params.copy()
+                simulation_params.update(methodParams)
+                if 'optimization' not in simulation_params:
+                    simulation_params['optimization'] = {}
+                new_params, new_opt_params = update_with_default_parameters(simulation_params,
+                                                                            simulation_params['optimization'], False)
+                simulation_params = new_params
+                simulation_params['optimization'] = new_opt_params
+
+                simulation_params['L'] = L
+                simulation_params['nu'] = nu
+                l_0 = simulation_params['l_0']
+                parameter_study.add_run(simulation_params.copy(), weight=(L / l_0) ** 4)
+    return parameter_study
+
+
+def test_shear_wave():
+    params = {
+        'l_0': 32,
+        'u_0': 0.096,
+        'v_0': 0.1,
+
+        'stencil': 'D3Q19',
+        'compressible': True,
+        "optimization": {"target": "gpu"}
+    }
+    run(32, nu=1e-2, equilibrium_order=2, method='srt', y_size=1, periodicity_in_kernel=True,
+        relaxation_rates=[sp.Symbol("omega"), 5, 5], maxwellian_moments=True, **params)
diff --git a/lbmpy_tests/full_scenarios/square_channel/scenario_square_channel.py b/lbmpy_tests/full_scenarios/square_channel/scenario_square_channel.py
new file mode 100644
index 0000000000000000000000000000000000000000..71d0aa57db0d354d12fef384d82e9602489d5aaa
--- /dev/null
+++ b/lbmpy_tests/full_scenarios/square_channel/scenario_square_channel.py
@@ -0,0 +1,344 @@
+"""
+Square channel - test of spurious currents normal to flow direction in reduced stencils (D3Q19, D3Q15)
+Test case described in:
+Truncation errors and the rotational invariance of three-dimensional lattice models in the lattice Boltzmann method
+Silva, Semiao
+
+
+python3 scenario_square_channel.py server
+python3 scenario_square_channel.py client --host i10staff41 -P '{ "optimization" : { "target" : "gpu"} }'
+"""
+
+import numpy as np
+import sympy as sp
+
+from pystencils import make_slice
+from lbmpy.scenarios import create_channel
+from lbmpy.methods.creationfunctions import relaxation_rate_from_magic_number
+
+
+defaultParameters = {
+    'stencil': 'D3Q19',
+    'method': 'srt',
+
+    'lambda_plus_sq': 4 / 25,
+    'square_size': 15,
+    'quadratic': True,
+    're': 10,
+    'compressible': True,
+    'cumulant': False,
+    'maxwellian_moments': False,
+    'equilibrium_order': 2,
+    'force_model': 'guo',
+    'c_s_sq': 1 / 3,
+
+    'analytic_initial_velocity': False,
+    'convergence_check_interval': 10000,
+    'convergence_threshold': 1e-10,
+
+    'reynolds_nr_accuracy': 1e-8,
+    'use_mean_for_reynolds': False,
+}
+
+
+def fit_and_get_slope(x_values, y_values):
+    matrix = np.vstack([x_values, np.ones(len(x_values))]).T
+    m, _ = np.linalg.lstsq(matrix, y_values)[0]
+    return m
+
+
+def get_convergence_order(series):
+    return fit_and_get_slope(np.log10(series.index.values), np.log10(series))
+
+
+def lambda_plus_sq_to_relaxation_rate(l):
+    lambda_plus = np.sqrt(l)
+    return 1.0 / (lambda_plus + 0.5)
+
+
+def viscosity(relaxation_rate, viscosity_factor):
+    return viscosity_factor * (1 / relaxation_rate - 0.5)
+
+
+def x_vorticity(velocity_field, dx):
+    grad_y_of_z = np.gradient(velocity_field[:, :, :, 2], dx, axis=1, edge_order=2)
+    grad_z_of_y = np.gradient(velocity_field[:, :, :, 1], dx, axis=2, edge_order=2)
+    return grad_y_of_z - grad_z_of_y
+
+
+def x_vorticity_rms(velocity_field, dx):
+    x_vort = x_vorticity(velocity_field, dx)
+    return np.sqrt(np.sum(x_vort * x_vort) / x_vort.size)
+
+
+def reynolds_number(max_velocity, relaxation_rate, length, viscosity_factor):
+    return max_velocity * length / viscosity(relaxation_rate, viscosity_factor)
+
+
+def force_from_reynolds_number(re, length, relaxation_rate, viscosity_factor, max_velocity_factor=1):
+    nu = viscosity(relaxation_rate, viscosity_factor)
+    max_velocity = re * nu / length * max_velocity_factor
+    force = max_velocity * 4 * nu / ((length / 2) ** 2 * 11815 / 10032)
+    return force
+
+
+def analytical_vel_max(force, relaxation_rate, width, viscosity_factor):
+    return force / (4 * viscosity(relaxation_rate, viscosity_factor)) * (width / 2) ** 2 * 11815 / 10032
+
+
+def create_initial_velocity_field(force, relaxation_rate, domain_size, viscosity_factor):
+    y_half = domain_size[1] / 2
+    z_half = domain_size[2] / 2
+
+    x_grid, y_grid = np.meshgrid(np.arange(domain_size[1]), np.arange(domain_size[2]), indexing='ij')
+    x = (x_grid - y_half) / y_half
+    y = (y_grid - z_half) / z_half
+
+    x_velocity = -(x ** 12 - 66 * x ** 10 * y ** 2 + 495 * x ** 8 * y ** 4 - 33 * x ** 8 - 924 * x ** 6 * y ** 6
+                   + 924 * x ** 6 * y ** 2 + 495 * x ** 4 * y ** 8 - 2310 * x ** 4 * y ** 4 + 1815 * x ** 4
+                   - 66 * x ** 2 * y ** 10 + 924 * x ** 2 * y ** 6 - 10890 * x ** 2 * y ** 2
+                   + 10032 * x ** 2 + y ** 12 - 33 * y ** 8 + 1815 * y ** 4 + 10032 * y ** 2 - 11815) / 10032
+
+    x_velocity *= force / (4 * viscosity(relaxation_rate, viscosity_factor)) * (domain_size[1] / 2) ** 2
+    x_velocity = np.repeat(x_velocity[np.newaxis, :, :], axis=0, repeats=domain_size[0])
+    velocity = np.zeros(tuple(domain_size) + (3,))
+    velocity[:, :, :, 0] = x_velocity
+    return velocity
+
+
+def run(convergence_check_interval=1000, convergence_threshold=1e-12, plot_result=False, lambda_plus_sq=4 / 25, re=10,
+        square_size=15, quadratic=True, analytic_initial_velocity=False, reynolds_nr_accuracy=1e-8,
+        use_mean_for_reynolds=True, **params):
+    """
+    3D Channel benchmark with rectangular cross-section
+    :return: tuple containing
+        - size of spurious velocity normal to flow direction normalized to maximum flow velocity
+        - number of iterations until convergence
+        - the computed reynolds number
+    """
+    omega = lambda_plus_sq_to_relaxation_rate(lambda_plus_sq)
+    params['relaxation_rates'] = [omega, relaxation_rate_from_magic_number(omega, 3 / 16)]
+
+    stencil = params['stencil']
+    viscosity_factor = 1 / 2 if stencil == 'D3Q15' and params['maxwellian_moments'] else 1 / 3
+
+    print("Running size %d quadratic %d analyticInit %d " %
+          (square_size, quadratic, analytic_initial_velocity) + str(params))
+    domain_size = [3, square_size, square_size]
+    if not quadratic:
+        domain_size[2] //= 2
+        if domain_size[2] % 2 == 0:
+            domain_size[2] -= 1
+
+    params['domain_size'] = domain_size
+    initial_force_value = force_from_reynolds_number(re, domain_size[1], omega,
+                                                     viscosity_factor, 2 if use_mean_for_reynolds else 1)
+    if not quadratic:
+        initial_force_value *= 2  # analytical solution for force is invalid if not quadratic - a good guess is doubled
+
+    if analytic_initial_velocity:
+        initial_field = create_initial_velocity_field(initial_force_value, omega, domain_size, viscosity_factor)
+        params['initial_velocity'] = initial_field
+
+    scenario = create_channel(force=sp.Symbol('Force'), kernel_params={'Force': initial_force_value}, **params)
+
+    last_vel_field = None
+    iterations = 0
+
+    while True:
+        scenario.run(convergence_check_interval)
+        iterations += convergence_check_interval
+        vel = scenario.velocity_slice(make_slice[:, :, :])
+        if last_vel_field is not None:
+            change_in_time = float(np.ma.average(np.abs(vel - last_vel_field)))
+
+            max_vel = np.array([np.max(scenario.velocity_slice(make_slice[:, :, :])[..., i]) for i in range(3)])
+
+            vel_for_reynolds = np.mean(
+                scenario.velocity_slice(make_slice[1, :, :, ])[..., 0]) if use_mean_for_reynolds else max_vel[0]
+            computed_re = reynolds_number(vel_for_reynolds, omega, domain_size[1], viscosity_factor)
+
+            reynolds_number_wrong = False
+            if reynolds_nr_accuracy is not None and change_in_time < 1e-5:
+                reynolds_number_wrong = abs(computed_re / re - 1) > reynolds_nr_accuracy
+                if reynolds_number_wrong:
+                    old_force = scenario.kernel_params['Force']
+                    scenario.kernel_params['Force'] = old_force * re / computed_re
+
+            ref_square_size = 15
+            scale_factor = square_size / ref_square_size
+            scaled_velocity = scenario.velocity_slice(make_slice[:, :, :]) * scale_factor
+            scaled_vorticity_rms = x_vorticity_rms(scaled_velocity, 1 / scale_factor)
+
+            print("    ", iterations, "ReErr", computed_re / re - 1, " spuriousVel ", max_vel[1] / max_vel[0],
+                  " Vort ", scaled_vorticity_rms, " Change ", change_in_time)
+
+            if np.isnan(max_vel).any():
+                break
+
+            if change_in_time < convergence_threshold and not reynolds_number_wrong:
+                break
+        last_vel_field = np.copy(vel)
+
+    if plot_result:
+        import lbmpy.plot2d as plt
+        vel_profile = vel[1, params['domain_size'][1] // 2, :, 0]
+        plt.subplot(1, 2, 1)
+        plt.plot(vel_profile)
+
+        vel_cross_section = vel[1, :, :, 1:]
+        plt.subplot(1, 2, 2)
+        plt.vector_field(vel_cross_section, step=1)
+
+        print(max_vel)
+        print(max_vel / max_vel[0])
+
+        plt.show()
+
+    velocity_profile = list(scenario.velocity[1, :, 0.5, 0].data)
+
+    return {
+        'normalized_spurious_vel_max': max_vel[1] / max_vel[0],
+        'scaled_vorticity_rms': scaled_vorticity_rms,
+        'x_vorticity_rms': x_vorticity_rms(scenario.velocity[:, :, :], 1),
+        'iterations': iterations,
+        'computed_re': computed_re,
+        'velocity_profile': velocity_profile,
+    }
+
+
+def parameter_filter(p):
+    if p.cumulant and p.compressible:
+        return None
+    if p.cumulant and not p.maxwellian_moments:
+        return None
+    if p.cumulant and p.stencil == 'D3Q15':
+        return None
+    if not p.quadratic and not p.reynolds_nr_accuracy:
+        # analytical formula not valid for rectangular channel
+        # -> rectangular setup should be run with adaptive force only
+        return None
+    return p
+
+
+def weight(p):
+    return int((p.square_size / 15) ** 4)
+
+
+def small_study():
+    from pystencils.runhelper import ParameterStudy
+
+    parameter_study = ParameterStudy(run, database_connector="square_channel_db")
+
+    common_degrees_of_freedom = [
+        ('reynolds_nr_accuracy', [1e-8, None]),
+        ('analytic_initial_velocity', [True]),
+        ('force_model', ['luo']),
+        ('cumulant', [False]),
+        ('method', ['srt']),
+        ('equilibrium_order', [2]),
+        ('stencil', ['D3Q19']),
+        ('compressible', [True]),
+        ('quadratic', [True, False]),
+        ('maxwellian_moments', [False, True]),
+    ]
+    convergence_study = common_degrees_of_freedom.copy()
+    convergence_study += [('square_size', [15, 25, 35, 45, 53])]
+    convergence_study += [('lambda_plus_sq', [4 / 25])]
+    parameter_study.add_combinations(convergence_study, defaultParameters, parameter_filter, weight)
+    return parameter_study
+
+
+def create_full_parameter_study():
+    from pystencils.runhelper import ParameterStudy
+
+    parameter_study = ParameterStudy(run, database_connector="mongo://square_channel")
+
+    common_degrees_of_freedom = [
+        ('cumulant', [False, True]),
+        ('cumulant', [False]),
+        ('compressible', [False, True]),
+        ('reynolds_nr_accuracy', [None, 1e-8]),
+        ('stencil', ['D3Q19', 'D3Q15']),
+        ('analytic_initial_velocity', [False]),
+        ('force_model', ['guo', 'simple', 'silva', 'luo']),
+        ('method', ['srt', 'trt']),
+        ('equilibrium_order', [2, 3]),
+        ('quadratic', [True, False]),
+        ('maxwellian_moments', [False, True]),
+        ('use_mean_for_reynolds', [True, False]),
+    ]
+
+    convergence_study = common_degrees_of_freedom.copy()
+    convergence_study += [('square_size', [15, 25, 35, 45, 53, 85, 135])]
+
+    convergence_study += [('lambda_plus_sq', [4 / 25, 1 / 12])]
+    parameter_study.add_combinations(convergence_study, defaultParameters, parameter_filter, weight)
+
+    relaxation_rate_study = common_degrees_of_freedom.copy()
+    relaxation_rate_study += [('square_size', [53])]
+    values_from_silva_paper = [0.01, 0.04, 0.09, 0.167, 0.18, 0.25, 0.36]
+    additional_values_near_004 = [0.02, 0.03, 0.035, 0.045, 0.05, 0.06, 0.07, 0.08]
+    relaxation_rate_study += [('lambda_plus_sq', values_from_silva_paper + additional_values_near_004)]
+    parameter_study.add_combinations(relaxation_rate_study, defaultParameters, parameter_filter, weight)
+
+    return parameter_study
+
+
+def d3q15_cs_sq_half_study():
+    from pystencils.runhelper import ParameterStudy
+    parameter_study = ParameterStudy(run, database_connector="square_channel_db_d3q15study_otherMoments")
+
+    dofs = [
+        ('compressible', [False, True]),
+        ('reynolds_nr_accuracy', [None, ]),
+        ('analytic_initial_velocity', [False]),
+        ('force_model', ['guo', 'silva']),
+        ('method', ['srt', 'trt']),
+        ('equilibrium_order', [2, 3]),
+        ('stencil', ['D3Q15']),
+        ('quadratic', [True, ]),
+        ('maxwellian_moments', [True, ]),
+        ('c_s_sq', [1 / 3]),
+        ('square_size', [45, 85]),
+    ]
+    parameter_study.add_combinations(dofs, defaultParameters, parameter_filter, weight)
+    return parameter_study
+
+
+def d3q27_study():
+    from pystencils.runhelper import ParameterStudy
+    parameter_study = ParameterStudy(run, database_connector="mongo://square_channel")
+
+    dofs = [
+        ('compressible', [False]),
+        ('reynolds_nr_accuracy', [None, ]),
+        ('analytic_initial_velocity', [False]),
+        ('force_model', ['guo', 'silva']),
+        ('method', ['srt']),
+        ('equilibrium_order', [2]),
+        ('stencil', ['D3Q27']),
+        ('maxwellian_moments', [True, ]),
+        ('c_s_sq', [1 / 3]),
+        ('square_size', [15, 25, 35, 45, 53, 85, 135]),
+        ('use_mean_for_reynolds', [False]),
+    ]
+    parameter_study.add_combinations(dofs, defaultParameters, parameter_filter, weight)
+    return parameter_study
+
+
+def test_square_channel():
+    res = run(convergence_check_interval=1000, convergence_threshold=1e-5, plot_result=False, lambda_plus_sq=4 / 25,
+              re=10, square_size=53, quadratic=True, analytic_initial_velocity=False, reynolds_nr_accuracy=None,
+              force_model='buick', stencil='D3Q19', maxwellian_moments=False, equilibrium_order=2, compressible=True)
+
+    assert 1e-5 < res['normalized_spurious_vel_max'] < 1.2e-5
+
+    res = run(convergence_check_interval=1000, convergence_threshold=1e-5, plot_result=False, lambda_plus_sq=4 / 25,
+              re=10, square_size=53, quadratic=True, analytic_initial_velocity=False, reynolds_nr_accuracy=None,
+              force_model='buick', stencil='D3Q19', maxwellian_moments=True, equilibrium_order=2, compressible=True)
+    assert res['normalized_spurious_vel_max'] < 1e-14
+
+
+if __name__ == '__main__':
+    create_full_parameter_study().run_from_command_line()
diff --git a/lbmpy_tests/lattice_tensors.py b/lbmpy_tests/lattice_tensors.py
new file mode 100644
index 0000000000000000000000000000000000000000..d58fc7512258fa335b2f44d576a87b5963140ecb
--- /dev/null
+++ b/lbmpy_tests/lattice_tensors.py
@@ -0,0 +1,35 @@
+import itertools
+from pystencils.sympyextensions import kronecker_delta as kd
+
+
+def delta4(i, j, k, l):
+    """See Silva: Truncation error paper, Eq13.a"""
+    return kd(i, j) * kd(k, l) + kd(i, k) * kd(j, l) + kd(i, l) * kd(j, k)
+
+
+def delta42(*args):
+    """See Silva: Truncation error paper, Eq13.b"""
+    assert len(args) == 6
+    res = 0
+    for selected in itertools.combinations(args, 2):
+        rest = list(args)
+        del rest[rest.index(selected[0])]
+        del rest[rest.index(selected[1])]
+        res += kd(*selected) * kd(*rest)
+    return res
+
+
+def delta6(i, j, k, l, m, n):
+    """See Silva: Truncation error paper, Eq13.c"""
+    return kd(i, j) * delta4(k, l, m, n) + \
+           kd(i, k) * delta4(j, l, m, n) + \
+           kd(i, l) * delta4(j, k, m, n) + \
+           kd(i, m) * delta4(j, k, l, n) + \
+           kd(i, n) * delta4(j, k, l, m)
+
+
+def test_rudimentary():
+    from pystencils.sympyextensions import multidimensional_sum as s
+    assert sum(delta4(*t) for t in s(4, dim=3)) == 27
+    assert sum(delta42(*t) for t in s(6, dim=2)) == 60
+    assert sum(delta6(*t) for t in s(6, dim=2)) == 120
diff --git a/lbmpy_tests/phasefield/test_analytical_3phase_model.ipynb b/lbmpy_tests/phasefield/test_analytical_3phase_model.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e7e6cc4dec966bb7d73bd37804d7014a7786e69f
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_analytical_3phase_model.ipynb
@@ -0,0 +1,303 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.analytical import *\n",
+    "from pystencils.fd import evaluate_diffs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Analytical checks for 3-Phase model\n",
+    "\n",
+    "Here you can inspect the components of the free energy. View only bulk or interface contributions, before and after transformation from $U \\rightarrow (\\rho, \\phi,\\psi)$:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\frac{\\alpha^{2} \\kappa_{0}}{2} {\\partial (\\frac{\\phi}{2} - \\frac{\\psi}{2} + \\frac{\\rho}{2}) }^{2} + \\frac{\\alpha^{2} \\kappa_{1}}{2} {\\partial (- \\frac{\\phi}{2} - \\frac{\\psi}{2} + \\frac{\\rho}{2}) }^{2} + \\frac{\\alpha^{2} \\kappa_{2}}{2} {\\partial \\psi}^{2} + \\frac{\\kappa_{0}}{2} \\left(\\frac{\\phi}{2} - \\frac{\\psi}{2} + \\frac{\\rho}{2}\\right)^{2} \\left(- \\frac{\\phi}{2} + \\frac{\\psi}{2} - \\frac{\\rho}{2} + 1\\right)^{2} + \\frac{\\kappa_{1}}{2} \\left(- \\frac{\\phi}{2} - \\frac{\\psi}{2} + \\frac{\\rho}{2}\\right)^{2} \\left(\\frac{\\phi}{2} + \\frac{\\psi}{2} - \\frac{\\rho}{2} + 1\\right)^{2} + \\frac{\\kappa_{2} \\psi^{2}}{2} \\left(- \\psi + 1\\right)^{2}$$"
+      ],
+      "text/plain": [
+       "                                                                              \n",
+       "                                                                              \n",
+       " 2                            2    2                             2    2       \n",
+       "α ⋅κ₀⋅D(phi/2 - psi/2 + rho/2)    α ⋅κ₁⋅D(-phi/2 - psi/2 + rho/2)    α ⋅κ₂⋅D(p\n",
+       "─────────────────────────────── + ──────────────────────────────── + ─────────\n",
+       "               2                                 2                         2  \n",
+       "\n",
+       "                     2                  2                   2                2\n",
+       "          ⎛φ   ψ   ρ⎞  ⎛  φ   ψ   ρ    ⎞       ⎛  φ   ψ   ρ⎞  ⎛φ   ψ   ρ    ⎞ \n",
+       "   2   κ₀⋅⎜─ - ─ + ─⎟ ⋅⎜- ─ + ─ - ─ + 1⎟    κ₁⋅⎜- ─ - ─ + ─⎟ ⋅⎜─ + ─ - ─ + 1⎟ \n",
+       "si)       ⎝2   2   2⎠  ⎝  2   2   2    ⎠       ⎝  2   2   2⎠  ⎝2   2   2    ⎠ \n",
+       "──── + ────────────────────────────────── + ──────────────────────────────────\n",
+       "                       2                                    2                 \n",
+       "\n",
+       "                  \n",
+       "                  \n",
+       "       2         2\n",
+       "   κ₂⋅ψ ⋅(-ψ + 1) \n",
+       " + ───────────────\n",
+       "          2       "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "order_parameters = sp.symbols(\"rho phi psi\")\n",
+    "rho, phi, psi = order_parameters\n",
+    "F, _ = free_energy_functional_3_phases(include_bulk=True,\n",
+    "                                       include_interface=True,\n",
+    "                                       transformed=True,\n",
+    "                                       expand_derivatives=False)\n",
+    "F"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Analytically checking the phase transition profile\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Automatically deriving chemical potential as functional derivative of free energy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$- \\frac{\\alpha^{2} \\kappa_{0}}{4} {\\partial {\\partial \\phi}} + \\frac{\\alpha^{2} \\kappa_{0}}{4} {\\partial {\\partial \\psi}} - \\frac{\\alpha^{2} \\kappa_{0}}{4} {\\partial {\\partial \\rho}} + \\frac{\\alpha^{2} \\kappa_{1}}{4} {\\partial {\\partial \\phi}} + \\frac{\\alpha^{2} \\kappa_{1}}{4} {\\partial {\\partial \\psi}} - \\frac{\\alpha^{2} \\kappa_{1}}{4} {\\partial {\\partial \\rho}} + \\frac{\\kappa_{0} \\phi^{3}}{8} - \\frac{3 \\kappa_{0}}{8} \\phi^{2} \\psi + \\frac{3 \\kappa_{0}}{8} \\phi^{2} \\rho - \\frac{3 \\kappa_{0}}{8} \\phi^{2} + \\frac{3 \\kappa_{0}}{8} \\phi \\psi^{2} - \\frac{3 \\kappa_{0}}{4} \\phi \\psi \\rho + \\frac{3 \\kappa_{0}}{4} \\phi \\psi + \\frac{3 \\kappa_{0}}{8} \\phi \\rho^{2} - \\frac{3 \\kappa_{0}}{4} \\phi \\rho + \\frac{\\kappa_{0} \\phi}{4} - \\frac{\\kappa_{0} \\psi^{3}}{8} + \\frac{3 \\kappa_{0}}{8} \\psi^{2} \\rho - \\frac{3 \\kappa_{0}}{8} \\psi^{2} - \\frac{3 \\kappa_{0}}{8} \\psi \\rho^{2} + \\frac{3 \\kappa_{0}}{4} \\psi \\rho - \\frac{\\kappa_{0} \\psi}{4} + \\frac{\\kappa_{0} \\rho^{3}}{8} - \\frac{3 \\kappa_{0}}{8} \\rho^{2} + \\frac{\\kappa_{0} \\rho}{4} - \\frac{\\kappa_{1} \\phi^{3}}{8} - \\frac{3 \\kappa_{1}}{8} \\phi^{2} \\psi + \\frac{3 \\kappa_{1}}{8} \\phi^{2} \\rho - \\frac{3 \\kappa_{1}}{8} \\phi^{2} - \\frac{3 \\kappa_{1}}{8} \\phi \\psi^{2} + \\frac{3 \\kappa_{1}}{4} \\phi \\psi \\rho - \\frac{3 \\kappa_{1}}{4} \\phi \\psi - \\frac{3 \\kappa_{1}}{8} \\phi \\rho^{2} + \\frac{3 \\kappa_{1}}{4} \\phi \\rho - \\frac{\\kappa_{1} \\phi}{4} - \\frac{\\kappa_{1} \\psi^{3}}{8} + \\frac{3 \\kappa_{1}}{8} \\psi^{2} \\rho - \\frac{3 \\kappa_{1}}{8} \\psi^{2} - \\frac{3 \\kappa_{1}}{8} \\psi \\rho^{2} + \\frac{3 \\kappa_{1}}{4} \\psi \\rho - \\frac{\\kappa_{1} \\psi}{4} + \\frac{\\kappa_{1} \\rho^{3}}{8} - \\frac{3 \\kappa_{1}}{8} \\rho^{2} + \\frac{\\kappa_{1} \\rho}{4}$$"
+      ],
+      "text/plain": [
+       "   2                 2                 2                 2                 2  \n",
+       "  α ⋅κ₀⋅D(D(phi))   α ⋅κ₀⋅D(D(psi))   α ⋅κ₀⋅D(D(rho))   α ⋅κ₁⋅D(D(phi))   α ⋅κ\n",
+       "- ─────────────── + ─────────────── - ─────────────── + ─────────────── + ────\n",
+       "         4                 4                 4                 4              \n",
+       "\n",
+       "               2                    3         2           2           2       \n",
+       "₁⋅D(D(psi))   α ⋅κ₁⋅D(D(rho))   κ₀⋅φ    3⋅κ₀⋅φ ⋅ψ   3⋅κ₀⋅φ ⋅ρ   3⋅κ₀⋅φ    3⋅κ₀\n",
+       "─────────── - ─────────────── + ───── - ───────── + ───────── - ─────── + ────\n",
+       "   4                 4            8         8           8          8          \n",
+       "\n",
+       "    2                                   2                         3         2 \n",
+       "⋅φ⋅ψ    3⋅κ₀⋅φ⋅ψ⋅ρ   3⋅κ₀⋅φ⋅ψ   3⋅κ₀⋅φ⋅ρ    3⋅κ₀⋅φ⋅ρ   κ₀⋅φ   κ₀⋅ψ    3⋅κ₀⋅ψ ⋅\n",
+       "───── - ────────── + ──────── + ───────── - ──────── + ──── - ───── + ────────\n",
+       "8           4           4           8          4        4       8         8   \n",
+       "\n",
+       "          2           2                         3         2              3    \n",
+       "ρ   3⋅κ₀⋅ψ    3⋅κ₀⋅ψ⋅ρ    3⋅κ₀⋅ψ⋅ρ   κ₀⋅ψ   κ₀⋅ρ    3⋅κ₀⋅ρ    κ₀⋅ρ   κ₁⋅φ    3\n",
+       "─ - ─────── - ───────── + ──────── - ──── + ───── - ─────── + ──── - ───── - ─\n",
+       "       8          8          4        4       8        8       4       8      \n",
+       "\n",
+       "     2           2           2           2                                   2\n",
+       "⋅κ₁⋅φ ⋅ψ   3⋅κ₁⋅φ ⋅ρ   3⋅κ₁⋅φ    3⋅κ₁⋅φ⋅ψ    3⋅κ₁⋅φ⋅ψ⋅ρ   3⋅κ₁⋅φ⋅ψ   3⋅κ₁⋅φ⋅ρ \n",
+       "──────── + ───────── - ─────── - ───────── + ────────── - ──────── - ─────────\n",
+       "   8           8          8          8           4           4           8    \n",
+       "\n",
+       "                         3         2           2           2                  \n",
+       "   3⋅κ₁⋅φ⋅ρ   κ₁⋅φ   κ₁⋅ψ    3⋅κ₁⋅ψ ⋅ρ   3⋅κ₁⋅ψ    3⋅κ₁⋅ψ⋅ρ    3⋅κ₁⋅ψ⋅ρ   κ₁⋅ψ\n",
+       " + ──────── - ──── - ───── + ───────── - ─────── - ───────── + ──────── - ────\n",
+       "      4        4       8         8          8          8          4        4  \n",
+       "\n",
+       "       3         2       \n",
+       "   κ₁⋅ρ    3⋅κ₁⋅ρ    κ₁⋅ρ\n",
+       " + ───── - ─────── + ────\n",
+       "     8        8       4  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F, _ = free_energy_functional_3_phases(order_parameters)\n",
+    "\n",
+    "mu_diff_eq = chemical_potentials_from_free_energy(F, order_parameters)\n",
+    "mu_diff_eq[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Checking if expected profile is a solution of the differential equation:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{1}{2} \\tanh{\\left (\\frac{x}{2 \\alpha} \\right )} + \\frac{1}{2}$$"
+      ],
+      "text/plain": [
+       "    ⎛ x ⎞    \n",
+       "tanh⎜───⎟    \n",
+       "    ⎝2⋅α⎠   1\n",
+       "───────── + ─\n",
+       "    2       2"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = sp.symbols(\"x\")\n",
+    "expectedProfile = analytic_interface_profile(x)\n",
+    "expectedProfile\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Checking a phase transition from $C_0$ to $C_2$. This means that $\\rho=1$ while $phi$ and $psi$ are the analytical profile or 1-analytical profile"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for eq in mu_diff_eq:\n",
+    "    eq = eq.subs({rho: 1,\n",
+    "                  phi: 1 - expectedProfile,\n",
+    "                  psi: expectedProfile})\n",
+    "    eq = evaluate_diffs(eq, x).expand()\n",
+    "    assert eq == 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Checking the surface tensions parameters\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{\\kappa_{0} + \\kappa_{2}}{16 \\cosh^{4}{\\left (\\frac{x}{2 \\alpha} \\right )}}$$"
+      ],
+      "text/plain": [
+       "   κ₀ + κ₂   \n",
+       "─────────────\n",
+       "       4⎛ x ⎞\n",
+       "16⋅cosh ⎜───⎟\n",
+       "        ⎝2⋅α⎠"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F, _ = free_energy_functional_3_phases(order_parameters)\n",
+    "F = expand_diff_linear(F, functions=order_parameters)  # expand derivatives using product rule\n",
+    "two_phase_free_energy = F.subs({rho: 1,\n",
+    "                                phi: 1 - expectedProfile,\n",
+    "                                psi: expectedProfile})\n",
+    "\n",
+    "two_phase_free_energy = sp.simplify(evaluate_diffs(two_phase_free_energy, x))\n",
+    "two_phase_free_energy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{\\alpha}{6} \\left(\\kappa_{0} + \\kappa_{2}\\right)$$"
+      ],
+      "text/plain": [
+       "α⋅(κ₀ + κ₂)\n",
+       "───────────\n",
+       "     6     "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gamma = cosh_integral(two_phase_free_energy, x)\n",
+    "gamma"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "alpha, k0, k2 = sp.symbols(\"alpha, kappa_0, kappa_2\")\n",
+    "assert gamma == alpha/6 * (k0 + k2)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_analytical_n_phase.ipynb b/lbmpy_tests/phasefield/test_analytical_n_phase.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..464c278b5bb6995882314bbaa98b3d4d2191fbc3
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_analytical_n_phase.ipynb
@@ -0,0 +1,529 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.analytical import *\n",
+    "from functools import partial"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Analytical checks for N-Phase model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Formulation of free energy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the next cell you can inspect the formulation of the free energy functional. \n",
+    "Bulk and interface terms can be viewed separately."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/latex": [
+       "$$\\frac{3}{2 \\alpha} \\left(\\tau_{0 1} \\left(\\phi_{0}^{2} \\left(- \\phi_{0} + 1\\right)^{2} + \\phi_{1}^{2} \\left(- \\phi_{1} + 1\\right)^{2} - \\begin{cases} - \\left(\\phi_{0} + \\phi_{1}\\right)^{2} & \\text{for}\\: \\phi_{0} + \\phi_{1} < 0 \\\\- \\left(- \\phi_{0} - \\phi_{1} + 1\\right)^{2} & \\text{for}\\: \\phi_{0} + \\phi_{1} > 1 \\\\\\left(\\phi_{0} + \\phi_{1}\\right)^{2} \\left(- \\phi_{0} - \\phi_{1} + 1\\right)^{2} & \\text{otherwise} \\end{cases}\\right) + \\tau_{0 2} \\left(\\phi_{0}^{2} \\left(- \\phi_{0} + 1\\right)^{2} + \\left(\\phi_{0} + \\phi_{1}\\right)^{2} \\left(- \\phi_{0} - \\phi_{1} + 1\\right)^{2} - \\begin{cases} - \\left(- \\phi_{1} + 1\\right)^{2} & \\text{for}\\: - \\phi_{1} + 1 < 0 \\\\- \\phi_{1}^{2} & \\text{for}\\: - \\phi_{1} + 1 > 1 \\\\\\phi_{1}^{2} \\left(- \\phi_{1} + 1\\right)^{2} & \\text{otherwise} \\end{cases}\\right) + \\tau_{1 2} \\left(\\phi_{1}^{2} \\left(- \\phi_{1} + 1\\right)^{2} + \\left(\\phi_{0} + \\phi_{1}\\right)^{2} \\left(- \\phi_{0} - \\phi_{1} + 1\\right)^{2} - \\begin{cases} - \\left(- \\phi_{0} + 1\\right)^{2} & \\text{for}\\: - \\phi_{0} + 1 < 0 \\\\- \\phi_{0}^{2} & \\text{for}\\: - \\phi_{0} + 1 > 1 \\\\\\phi_{0}^{2} \\left(- \\phi_{0} + 1\\right)^{2} & \\text{otherwise} \\end{cases}\\right)\\right)$$"
+      ],
+      "text/plain": [
+       "  ⎛     ⎛                                  ⎛⎧                 2               \n",
+       "  ⎜     ⎜                                  ⎜⎪       -(φ₀ + φ₁)           for φ\n",
+       "  ⎜     ⎜                                  ⎜⎪                                 \n",
+       "  ⎜     ⎜  2          2     2          2   ⎜⎪                    2            \n",
+       "3⋅⎜τ₀ ₁⋅⎜φ₀ ⋅(-φ₀ + 1)  + φ₁ ⋅(-φ₁ + 1)  - ⎜⎨     -(-φ₀ - φ₁ + 1)        for φ\n",
+       "  ⎜     ⎜                                  ⎜⎪                                 \n",
+       "  ⎜     ⎜                                  ⎜⎪         2               2       \n",
+       "  ⎜     ⎜                                  ⎜⎪(φ₀ + φ₁) ⋅(-φ₀ - φ₁ + 1)      ot\n",
+       "  ⎝     ⎝                                  ⎝⎩                                 \n",
+       "──────────────────────────────────────────────────────────────────────────────\n",
+       "                                                                              \n",
+       "\n",
+       "          ⎞⎞        ⎛                                              ⎛⎧         \n",
+       "₀ + φ₁ < 0⎟⎟        ⎜                                              ⎜⎪ -(-φ₁ + \n",
+       "          ⎟⎟        ⎜                                              ⎜⎪         \n",
+       "          ⎟⎟        ⎜  2          2            2               2   ⎜⎪        2\n",
+       "₀ + φ₁ > 1⎟⎟ + τ₀ ₂⋅⎜φ₀ ⋅(-φ₀ + 1)  + (φ₀ + φ₁) ⋅(-φ₀ - φ₁ + 1)  - ⎜⎨     -φ₁ \n",
+       "          ⎟⎟        ⎜                                              ⎜⎪         \n",
+       "          ⎟⎟        ⎜                                              ⎜⎪  2      \n",
+       "herwise   ⎟⎟        ⎜                                              ⎜⎪φ₁ ⋅(-φ₁ \n",
+       "          ⎠⎠        ⎝                                              ⎝⎩         \n",
+       "──────────────────────────────────────────────────────────────────────────────\n",
+       "                                                        2⋅α                   \n",
+       "\n",
+       "  2                   ⎞⎞        ⎛                                             \n",
+       "1)     for -φ₁ + 1 < 0⎟⎟        ⎜                                             \n",
+       "                      ⎟⎟        ⎜                                             \n",
+       "                      ⎟⎟        ⎜  2          2            2               2  \n",
+       "       for -φ₁ + 1 > 1⎟⎟ + τ₁ ₂⋅⎜φ₁ ⋅(-φ₁ + 1)  + (φ₀ + φ₁) ⋅(-φ₀ - φ₁ + 1)  -\n",
+       "                      ⎟⎟        ⎜                                             \n",
+       "    2                 ⎟⎟        ⎜                                             \n",
+       "+ 1)      otherwise   ⎟⎟        ⎜                                             \n",
+       "                      ⎠⎠        ⎝                                             \n",
+       "──────────────────────────────────────────────────────────────────────────────\n",
+       "                                                                              \n",
+       "\n",
+       " ⎛⎧           2                   ⎞⎞⎞\n",
+       " ⎜⎪ -(-φ₀ + 1)     for -φ₀ + 1 < 0⎟⎟⎟\n",
+       " ⎜⎪                               ⎟⎟⎟\n",
+       " ⎜⎪        2                      ⎟⎟⎟\n",
+       " ⎜⎨     -φ₀        for -φ₀ + 1 > 1⎟⎟⎟\n",
+       " ⎜⎪                               ⎟⎟⎟\n",
+       " ⎜⎪  2          2                 ⎟⎟⎟\n",
+       " ⎜⎪φ₀ ⋅(-φ₀ + 1)      otherwise   ⎟⎟⎟\n",
+       " ⎝⎩                               ⎠⎠⎠\n",
+       "─────────────────────────────────────\n",
+       "                                     "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_phases = 3\n",
+    "order_params = symbolic_order_parameters(num_symbols=num_phases-1)\n",
+    "f2 = partial(n_phases_correction_function, beta=1)\n",
+    "F = free_energy_functional_n_phases(order_parameters=order_params, \n",
+    "                                    include_interface=False, f2=f2,\n",
+    "                                    include_bulk=True )\n",
+    "F"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Analytically checking the phase transition profile\n",
+    "\n",
+    "First we define the order parameters and free energy, including bulk and interface terms:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "F = free_energy_functional_n_phases(order_parameters=symbolic_order_parameters(num_symbols=num_phases-1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we automatically derive the differential equations for the chemial potential $\\mu$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$3 \\alpha \\tau_{0 1} {\\partial {\\partial \\phi_{1}}} - 6 \\alpha \\tau_{0 2} {\\partial {\\partial \\phi_{0}}} - 3 \\alpha \\tau_{0 2} {\\partial {\\partial \\phi_{1}}} - 3 \\alpha \\tau_{1 2} {\\partial {\\partial \\phi_{1}}} + \\frac{12 \\phi_{0}^{3}}{\\alpha} \\tau_{0 2} - \\frac{18 \\phi_{1}}{\\alpha} \\phi_{0}^{2} \\tau_{0 1} + \\frac{18 \\phi_{1}}{\\alpha} \\phi_{0}^{2} \\tau_{0 2} + \\frac{18 \\phi_{1}}{\\alpha} \\phi_{0}^{2} \\tau_{1 2} - \\frac{18 \\phi_{0}^{2}}{\\alpha} \\tau_{0 2} - \\frac{18 \\phi_{0}}{\\alpha} \\phi_{1}^{2} \\tau_{0 1} + \\frac{18 \\phi_{0}}{\\alpha} \\phi_{1}^{2} \\tau_{0 2} + \\frac{18 \\phi_{0}}{\\alpha} \\phi_{1}^{2} \\tau_{1 2} + \\frac{18 \\phi_{0}}{\\alpha} \\phi_{1} \\tau_{0 1} - \\frac{18 \\phi_{0}}{\\alpha} \\phi_{1} \\tau_{0 2} - \\frac{18 \\phi_{0}}{\\alpha} \\phi_{1} \\tau_{1 2} + \\frac{6 \\phi_{0}}{\\alpha} \\tau_{0 2} - \\frac{6 \\phi_{1}^{3}}{\\alpha} \\tau_{0 1} + \\frac{6 \\phi_{1}^{3}}{\\alpha} \\tau_{0 2} + \\frac{6 \\phi_{1}^{3}}{\\alpha} \\tau_{1 2} + \\frac{9 \\phi_{1}^{2}}{\\alpha} \\tau_{0 1} - \\frac{9 \\phi_{1}^{2}}{\\alpha} \\tau_{0 2} - \\frac{9 \\phi_{1}^{2}}{\\alpha} \\tau_{1 2} - \\frac{3 \\phi_{1}}{\\alpha} \\tau_{0 1} + \\frac{3 \\phi_{1}}{\\alpha} \\tau_{0 2} + \\frac{3 \\phi_{1}}{\\alpha} \\tau_{1 2}$$"
+      ],
+      "text/plain": [
+       "                                                                              \n",
+       "                                                                              \n",
+       "3⋅α⋅τ₀ ₁⋅D(D(phi_1)) - 6⋅α⋅τ₀ ₂⋅D(D(phi_0)) - 3⋅α⋅τ₀ ₂⋅D(D(phi_1)) - 3⋅α⋅τ₁ ₂⋅\n",
+       "                                                                              \n",
+       "\n",
+       "                   3             2                2                2          \n",
+       "              12⋅φ₀ ⋅τ₀ ₂   18⋅φ₀ ⋅φ₁⋅τ₀ ₁   18⋅φ₀ ⋅φ₁⋅τ₀ ₂   18⋅φ₀ ⋅φ₁⋅τ₁ ₂  \n",
+       "D(D(phi_1)) + ─────────── - ────────────── + ────────────── + ────────────── -\n",
+       "                   α              α                α                α         \n",
+       "\n",
+       "      2                2                2                2                    \n",
+       " 18⋅φ₀ ⋅τ₀ ₂   18⋅φ₀⋅φ₁ ⋅τ₀ ₁   18⋅φ₀⋅φ₁ ⋅τ₀ ₂   18⋅φ₀⋅φ₁ ⋅τ₁ ₂   18⋅φ₀⋅φ₁⋅τ₀ \n",
+       " ─────────── - ────────────── + ────────────── + ────────────── + ────────────\n",
+       "      α              α                α                α                α     \n",
+       "\n",
+       "                                                    3            3            \n",
+       "₁   18⋅φ₀⋅φ₁⋅τ₀ ₂   18⋅φ₀⋅φ₁⋅τ₁ ₂   6⋅φ₀⋅τ₀ ₂   6⋅φ₁ ⋅τ₀ ₁   6⋅φ₁ ⋅τ₀ ₂   6⋅φ₁\n",
+       "─ - ───────────── - ───────────── + ───────── - ────────── + ────────── + ────\n",
+       "          α               α             α           α            α            \n",
+       "\n",
+       "3            2            2            2                                      \n",
+       " ⋅τ₁ ₂   9⋅φ₁ ⋅τ₀ ₁   9⋅φ₁ ⋅τ₀ ₂   9⋅φ₁ ⋅τ₁ ₂   3⋅φ₁⋅τ₀ ₁   3⋅φ₁⋅τ₀ ₂   3⋅φ₁⋅τ\n",
+       "────── + ────────── - ────────── - ────────── - ───────── + ───────── + ──────\n",
+       "α            α            α            α            α           α           α \n",
+       "\n",
+       "   \n",
+       "₁ ₂\n",
+       "───\n",
+       "   "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mu_diff_eq = chemical_potentials_from_free_energy(F, order_params)\n",
+    "\n",
+    "# there is one equation less than phases\n",
+    "assert len(mu_diff_eq) == num_phases - 1\n",
+    "\n",
+    "# show the first one\n",
+    "mu_diff_eq[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next we check, that the $tanh$ is indeed a solution of this equation..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{1}{2} \\tanh{\\left (\\frac{x}{2 \\alpha} \\right )} + \\frac{1}{2}$$"
+      ],
+      "text/plain": [
+       "    ⎛ x ⎞    \n",
+       "tanh⎜───⎟    \n",
+       "    ⎝2⋅α⎠   1\n",
+       "───────── + ─\n",
+       "    2       2"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = sp.symbols(\"x\")\n",
+    "expected_profile = analytic_interface_profile(x)\n",
+    "expected_profile"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "... by inserting it for $\\phi_0$, and setting all other order parameters to zero"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$- \\frac{3 \\tau_{0 2}}{2 \\alpha} \\left(4 \\alpha^{2} {\\partial {\\partial (\\frac{1}{2} \\tanh{\\left (\\frac{x}{2 \\alpha} \\right )} + \\frac{1}{2}) }} - \\tanh^{3}{\\left (\\frac{x}{2 \\alpha} \\right )} + \\tanh{\\left (\\frac{x}{2 \\alpha} \\right )}\\right)$$"
+      ],
+      "text/plain": [
+       "        ⎛   2                                       3⎛ x ⎞       ⎛ x ⎞⎞ \n",
+       "-3⋅τ₀ ₂⋅⎜4⋅α ⋅D(D(tanh(x/(2*alpha))/2 + 1/2)) - tanh ⎜───⎟ + tanh⎜───⎟⎟ \n",
+       "        ⎝                                            ⎝2⋅α⎠       ⎝2⋅α⎠⎠ \n",
+       "────────────────────────────────────────────────────────────────────────\n",
+       "                                  2⋅α                                   "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# zero other parameters\n",
+    "diff_eq = mu_diff_eq[0].subs({p: 0 for p in order_params[1:]})\n",
+    "\n",
+    "# insert analytical solution\n",
+    "diff_eq = diff_eq.subs(order_params[0], expected_profile)\n",
+    "diff_eq.factor()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "finally the differentials have to be evaluated..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{12}{\\alpha} \\tau_{0 2} \\left(\\frac{1}{2} \\tanh{\\left (\\frac{x}{2 \\alpha} \\right )} + \\frac{1}{2}\\right)^{3} - \\frac{18}{\\alpha} \\tau_{0 2} \\left(\\frac{1}{2} \\tanh{\\left (\\frac{x}{2 \\alpha} \\right )} + \\frac{1}{2}\\right)^{2} + \\frac{6}{\\alpha} \\tau_{0 2} \\left(\\frac{1}{2} \\tanh{\\left (\\frac{x}{2 \\alpha} \\right )} + \\frac{1}{2}\\right) + \\frac{3 \\tau_{0 2}}{2 \\alpha} \\left(- \\tanh^{2}{\\left (\\frac{x}{2 \\alpha} \\right )} + 1\\right) \\tanh{\\left (\\frac{x}{2 \\alpha} \\right )}$$"
+      ],
+      "text/plain": [
+       "                       3                          2                           \n",
+       "        ⎛    ⎛ x ⎞    ⎞            ⎛    ⎛ x ⎞    ⎞           ⎛    ⎛ x ⎞    ⎞  \n",
+       "        ⎜tanh⎜───⎟    ⎟            ⎜tanh⎜───⎟    ⎟           ⎜tanh⎜───⎟    ⎟  \n",
+       "        ⎜    ⎝2⋅α⎠   1⎟            ⎜    ⎝2⋅α⎠   1⎟           ⎜    ⎝2⋅α⎠   1⎟  \n",
+       "12⋅τ₀ ₂⋅⎜───────── + ─⎟    18⋅τ₀ ₂⋅⎜───────── + ─⎟    6⋅τ₀ ₂⋅⎜───────── + ─⎟  \n",
+       "        ⎝    2       2⎠            ⎝    2       2⎠           ⎝    2       2⎠  \n",
+       "──────────────────────── - ──────────────────────── + ────────────────────── +\n",
+       "           α                          α                         α             \n",
+       "\n",
+       "                                    \n",
+       "                                    \n",
+       "                                    \n",
+       "        ⎛      2⎛ x ⎞    ⎞     ⎛ x ⎞\n",
+       " 3⋅τ₀ ₂⋅⎜- tanh ⎜───⎟ + 1⎟⋅tanh⎜───⎟\n",
+       "        ⎝       ⎝2⋅α⎠    ⎠     ⎝2⋅α⎠\n",
+       " ───────────────────────────────────\n",
+       "                 2⋅α                "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from pystencils.fd import evaluate_diffs\n",
+    "diff_eq = evaluate_diffs(diff_eq, x)\n",
+    "diff_eq"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    ".. and the result simplified..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAOBAMAAADkjZCYAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAEJmJZjLNVN0i77urRHZ72Yd1AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAVElEQVQIHWNgEDIxZWBgSGeQmMDAsoCBOYGB+wAD+0cG/gMMvN8Z5BUYeP8xzDdgYP3MMF8BREJEgLLs3xm4NzCwfATpYkpgYGhnkApgYBB+d5QBAPogE3QldevOAAAAAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$0$$"
+      ],
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "assert diff_eq.expand() == 0\n",
+    "diff_eq.expand()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "...and indeed the expected tanh profile satisfies this differential equation.\n",
+    "\n",
+    "Next lets check for the interface between phase 0 and phase 1:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for diff_eq in mu_diff_eq:\n",
+    "    eq = diff_eq.subs({order_params[0]: expected_profile,\n",
+    "                       order_params[1]: 1 - expected_profile})\n",
+    "    assert evaluate_diffs(eq, x).expand() == 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Checking the surface tensions parameters\n",
+    "\n",
+    "Computing the excess free energy per unit area of an interface between two phases.\n",
+    "This should be exactly the surface tension parameter."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "order_params = symbolic_order_parameters(num_symbols=num_phases-1)\n",
+    "F = free_energy_functional_n_phases(order_parameters=order_params)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "two_phase_free_energy = F.subs({order_params[0]: expected_profile,\n",
+    "                                order_params[1]: 1 - expected_profile})\n",
+    "\n",
+    "# Evaluate differentials and simplification\n",
+    "two_phase_free_energy = sp.simplify(evaluate_diffs(two_phase_free_energy, x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\int \\frac{3 \\tau_{0 1}}{8 \\alpha \\cosh^{4}{\\left (\\frac{x}{2 \\alpha} \\right )}}\\, dx$$"
+      ],
+      "text/plain": [
+       "⌠                  \n",
+       "⎮     3⋅τ₀ ₁       \n",
+       "⎮ ────────────── dx\n",
+       "⎮         4⎛ x ⎞   \n",
+       "⎮ 8⋅α⋅cosh ⎜───⎟   \n",
+       "⎮          ⎝2⋅α⎠   \n",
+       "⌡                  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "excess_free_energy = sp.Integral(two_phase_free_energy, x)\n",
+    "excess_free_energy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Sympy cannot integrate this automatically - help with a manual substitution $\\frac{x}{2\\alpha} \\rightarrow u$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\int \\frac{3 \\tau_{0 1}}{4 \\cosh^{4}{\\left (u \\right )}}\\, du$$"
+      ],
+      "text/plain": [
+       "⌠              \n",
+       "⎮   3⋅τ₀ ₁     \n",
+       "⎮ ────────── du\n",
+       "⎮       4      \n",
+       "⎮ 4⋅cosh (u)   \n",
+       "⌡              "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "coshTerm = list(excess_free_energy.atoms(sp.cosh))[0]\n",
+    "transformed_int = excess_free_energy.transform(coshTerm.args[0], sp.Symbol(\"u\", real=True))\n",
+    "transformed_int"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now the integral can be done:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAABgAAAAMBAMAAACKHmBGAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAdokyIqtUu2bdRBDvmc2dyWZjAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAd0lEQVQIHWNgkP///78AAwQwKbuauDAqKjAw2DEwmDGwMzA0MaQy2EaCZE0ZGGYx8G9gyARxNBi4PzPwJEA4kxmYvzBwNoA5LB8YmH8zcAqAOYwTQDI8EA6rAEgP/wKIHqAZCNOAHFmgPQw5IKOBgOnSbQbf+YEAtswY/wTjD9AAAAAASUVORK5CYII=\n",
+      "text/latex": [
+       "$$\\tau_{0 1}$$"
+      ],
+      "text/plain": [
+       "τ₀ ₁"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result = sp.integrate(transformed_int.args[0], (transformed_int.args[1][0], -sp.oo, sp.oo))\n",
+    "assert result == symmetric_symbolic_surface_tension(0,1)\n",
+    "result"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_analytical_n_phase_full.ipynb b/lbmpy_tests/phasefield/test_analytical_n_phase_full.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..937d6062ae665e39919e47c48f57376474c0303f
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_analytical_n_phase_full.ipynb
@@ -0,0 +1,121 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.analytical import *\n",
+    "import pystencils as ps"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Full analytical checks for N phase model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = sp.symbols(\"x\")\n",
+    "c_a = analytic_interface_profile(x)\n",
+    "\n",
+    "\n",
+    "def gamma(i, j):\n",
+    "    if i == j:\n",
+    "        return 0\n",
+    "    elif i < j:\n",
+    "        return sp.Symbol(\"gamma_%d%d\" % (i, j))\n",
+    "    else:\n",
+    "        return sp.Symbol(\"gamma_%d%d\" % (j, i))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The following checks if the 'tanh' shaped profile is a solution to $\\mu_i = 0$ and if the excess free energy is the surface tension parameter."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Checking N = 3\n",
+      "  -> Testing interface between 0 and 1\n",
+      "  -> Testing interface between 0 and 2\n",
+      "  -> Testing interface between 1 and 0\n",
+      "  -> Testing interface between 1 and 2\n",
+      "  -> Testing interface between 2 and 0\n",
+      "  -> Testing interface between 2 and 1\n"
+     ]
+    }
+   ],
+   "source": [
+    "numPhases = 3\n",
+    "\n",
+    "print(\"Checking N =\", numPhases)\n",
+    "c = sp.symbols(\"c_:%d\" % (numPhases - 1,))\n",
+    "F = free_energy_functional_n_phases(order_parameters=c, surface_tensions=gamma)\n",
+    "\n",
+    "μ = chemical_potentials_from_free_energy(F, c)\n",
+    "\n",
+    "lastPhaseIdx = numPhases - 1\n",
+    "\n",
+    "# Check all permutations of phases\n",
+    "for i in range(numPhases):\n",
+    "    for j in range(numPhases):\n",
+    "        if i == j:\n",
+    "            continue\n",
+    "        print(\"  -> Testing interface between\", i, \"and\", j)\n",
+    "        substitutions = {c_i: 0 for c_i in c}\n",
+    "        if i != lastPhaseIdx:\n",
+    "            substitutions[c[i]] = c_a\n",
+    "        if j != lastPhaseIdx:\n",
+    "            substitutions[c[j]] = 1 - c_a\n",
+    "\n",
+    "        for μ_i in μ:\n",
+    "            res = ps.fd.evaluate_diffs(μ_i.subs(substitutions), x).expand()\n",
+    "            assert res == 0, \"Analytic interface profile wrong for phase between %d and %d\" % (i, j)\n",
+    "\n",
+    "        two_phase_free_energy = F.subs(substitutions)\n",
+    "        two_phase_free_energy = sp.simplify(ps.fd.evaluate_diffs(two_phase_free_energy, x))\n",
+    "        result = cosh_integral(two_phase_free_energy, x)\n",
+    "        assert result == gamma(i, j)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_analytical_paper_comparison.ipynb b/lbmpy_tests/phasefield/test_analytical_paper_comparison.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..03902bb30f43e85b8d75f2e5603f6001bc074986
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_analytical_paper_comparison.ipynb
@@ -0,0 +1,152 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.analytical import *\n",
+    "\n",
+    "\n",
+    "def laplacian(f):\n",
+    "    return Diff(Diff(f))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Comparison of 3-phase model equations with paper\n",
+    "\n",
+    "[Semprebon, Krüger, Kusumaatmaja] 2016 "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Free Energy Function F\n",
+    "First we compare the transformed free energy function (23):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "order_parameters = sp.symbols(\"rho phi psi\")\n",
+    "κ = sp.symbols(\"kappa_:3\")\n",
+    "α = sp.symbols(\"alpha\")\n",
+    "ρ, φ, ψ = order_parameters\n",
+    "F, _ = free_energy_functional_3_phases(order_parameters, kappa=κ, interface_width=α)\n",
+    "\n",
+    "eq_23 = κ[0] / 32 * (ρ + φ - ψ) ** 2 * (2 + ψ - ρ - φ) ** 2 \\\n",
+    "        + α ** 2 * κ[0] / 8 * (Diff(ρ) + Diff(φ) - Diff(ψ)) ** 2 \\\n",
+    "        + κ[1] / 32 * (ρ - φ - ψ) ** 2 * (2 + ψ - ρ + φ) ** 2 \\\n",
+    "        + α ** 2 * κ[1] / 8 * (Diff(ρ) - Diff(φ) - Diff(ψ)) ** 2 \\\n",
+    "        + κ[2] / 2 * ψ ** 2 * (1 - ψ) ** 2 + α ** 2 * κ[2] / 2 * (Diff(ψ)) ** 2\n",
+    "\n",
+    "assert F - eq_23.expand() == 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Chemical Potentials\n",
+    "\n",
+    "This compares formulas (38), (39) and (40) from the paper, as typed in the next cell, to the automatically derived version which starts from the potential formulation above. \n",
+    "\n",
+    "For equation (38) the automatically derived version is different than the version reported in the paper.\n",
+    "See the code in the next cell for our correction."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def chemical_potential_formulas_from_paper(order_parameters=sp.symbols(\"rho phi psi\"),\n",
+    "                                           κ=sp.symbols(\"kappa_:3\"),\n",
+    "                                           α=sp.symbols(\"alpha\")):\n",
+    "    ρ, φ, ψ = order_parameters\n",
+    "\n",
+    "    # --------------------- μ_ρ formulas ---------------------------------------------\n",
+    "\n",
+    "    # possibly wrong version in paper?\n",
+    "    μ_ρ_paper = κ[0] / 8 * (ρ + φ - ψ) * (ρ + φ - ψ - 2) * (ρ + φ - ψ - 1) \\\n",
+    "                - κ[1] / 8 * (ρ - φ - ψ) * (ρ - φ - ψ - 2) * (ρ - φ - ψ - 1) \\\n",
+    "                + α ** 2 / 4 * ((κ[0] + κ[1]) * (laplacian(ψ) - laplacian(φ)) +\n",
+    "                                (κ[1] - κ[0]) * laplacian(ρ))\n",
+    "    # corrections from paper: sign of kappa[1] term + different interface term\n",
+    "    μ_ρ = κ[0] / 8 * (ρ + φ - ψ) * (ρ + φ - ψ - 2) * (ρ + φ - ψ - 1) \\\n",
+    "          + κ[1] / 8 * (ρ - φ - ψ) * (ρ - φ - ψ - 2) * (ρ - φ - ψ - 1) \\\n",
+    "          - α ** 2 / 4 * ((κ[0] + κ[1]) * (laplacian(ρ) - laplacian(ψ)) +\n",
+    "                          (κ[0] - κ[1]) * laplacian(φ))\n",
+    "\n",
+    "    # --------------------- μ_φ formulas ---------------------------------------------\n",
+    "    μ_φ = κ[0] / 8 * (ρ + φ - ψ) * (ρ + φ - ψ - 2) * (ρ + φ - ψ - 1) \\\n",
+    "          - κ[1] / 8 * (ρ - φ - ψ) * (ρ - φ - ψ - 2) * (ρ - φ - ψ - 1) \\\n",
+    "          + α ** 2 / 4 * ((κ[1] - κ[0]) * (laplacian(ρ) - laplacian(ψ)) -\n",
+    "                          (κ[0] + κ[1]) * laplacian(φ))\n",
+    "\n",
+    "    # --------------------- μ_ψ formulas ---------------------------------------------\n",
+    "\n",
+    "    μ_ψ = -κ[0] / 8 * (ρ + φ - ψ) * (ρ + φ - ψ - 2) * (ρ + φ - ψ - 1) \\\n",
+    "          - κ[1] / 8 * (ρ - φ - ψ) * (ρ - φ - ψ - 2) * (ρ - φ - ψ - 1) \\\n",
+    "          + κ[2] * ψ * (ψ - 1) * (2 * ψ - 1) + α ** 2 / 4 * ((κ[0] + κ[1]) * laplacian(ρ)\n",
+    "                                                             - (κ[1] - κ[0]) * laplacian(φ) - (\n",
+    "                                                                     κ[1] + κ[0] + 4 * κ[2]) * laplacian(ψ))\n",
+    "\n",
+    "    return μ_ρ, μ_φ, μ_ψ\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "F, _ = free_energy_functional_3_phases(order_parameters)\n",
+    "μ_derived = chemical_potentials_from_free_energy(F, order_parameters)\n",
+    "μ_paper = chemical_potential_formulas_from_paper()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert (μ_derived[0] - μ_paper[0]).expand() == 0\n",
+    "assert (μ_derived[1] - μ_paper[1]).expand() == 0\n",
+    "assert (μ_derived[2] - μ_paper[2]).expand() == 0"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_entropic_model.ipynb b/lbmpy_tests/phasefield/test_entropic_model.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..da23daf4156c676ae0b1c002016b14296ca69815
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_entropic_model.ipynb
@@ -0,0 +1,769 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.analytical import *\n",
+    "from lbmpy.phasefield.eos import *\n",
+    "from lbmpy.phasefield.high_density_ratio_model import *\n",
+    "from pystencils.fd.derivative import replace_generic_laplacian\n",
+    "from pystencils.fd.spatial import discretize_spatial, \\\n",
+    "        fd_stencils_standard, fd_stencils_isotropic, fd_stencils_isotropic_high_density_code\n",
+    "from lbmpy.phasefield.cahn_hilliard_lbm import cahn_hilliard_lb_method\n",
+    "from lbmpy.forcemodels import EDM\n",
+    "from lbmpy.macroscopic_value_kernels import pdf_initialization_assignments\n",
+    "from scipy.ndimage.filters import gaussian_filter"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Implementation of high density difference model\n",
+    "\n",
+    "According to *\"Ternary free-energy entropic lattice Boltzmann model with high density ratio\" by Wöhrwag, Semprebon, Mazloomi, Karlin and Kusumaatmaja*\n",
+    "\n",
+    "Up front we define all necessary parameters in one place:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "a = 0.037\n",
+    "b = 0.2\n",
+    "reduced_temperature = 0.61\n",
+    "gas_constant = 1\n",
+    "κ = (0.01, 1, 1)\n",
+    "λ = (0.6, 1, 1)\n",
+    "χ = 5\n",
+    "φ_relaxation_rate = 1\n",
+    "ρ_relaxation_rate = 1\n",
+    "external_force = (0, 0)\n",
+    "clipping = False\n",
+    "\n",
+    "domain_size = (100, 100)\n",
+    "stencil = get_stencil('D2Q9', ordering='uk')\n",
+    "\n",
+    "fd_discretization = fd_stencils_isotropic_high_density_code\n",
+    "target = 'cpu'\n",
+    "threads = 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part 1: Free Energy\n",
+    "\n",
+    "The free energy of this model contains a term that is derived from an equation of state. The equation of state and its parametrization determines the density of the liquid and gas phase. \n",
+    "\n",
+    "Here we use the Carnahan-Starling EOS, with the parametrization from the paper"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$- 0.037 \\rho^{2} + \\frac{0.042578305 \\rho \\left(- 0.000125 \\rho^{3} + 0.0025 \\rho^{2} + 0.05 \\rho + 1\\right)}{\\left(- 0.05 \\rho + 1\\right)^{3}}$$"
+      ],
+      "text/plain": [
+       "                           ⎛            3           2             ⎞\n",
+       "         2   0.042578305⋅ρ⋅⎝- 0.000125⋅ρ  + 0.0025⋅ρ  + 0.05⋅ρ + 1⎠\n",
+       "- 0.037⋅ρ  + ──────────────────────────────────────────────────────\n",
+       "                                              3                    \n",
+       "                                 (-0.05⋅ρ + 1)                     "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ρ, φ, c_l1, c_l2 = sp.symbols(\"rho, phi, c_l1, c_l2\")\n",
+    "\n",
+    "critical_temperature = carnahan_starling_critical_temperature(a, b, gas_constant)\n",
+    "temperature = reduced_temperature * critical_temperature\n",
+    "\n",
+    "eos = carnahan_starling_eos(ρ, gas_constant, temperature, a, b)\n",
+    "eos"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we use a function that determines the gas and liquid density, using the Maxwell construction rule. This function uses an iterative procedure, that terminates when the equal-area condition is fulfilled with a certain tolerance. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left ( 0.0695273860315274, \\quad 8.02904149705209, \\quad 115.480272671423\\right )$$"
+      ],
+      "text/plain": [
+       "(0.0695273860315274, 8.02904149705209, 115.480272671423)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ρ_g, ρ_l = maxwell_construction(eos, tolerance=1e-3)\n",
+    "(ρ_g, ρ_l, ρ_l / ρ_g)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "With this information we call a function that assembles the full free energy density:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$0.5 c_{l1}^{2} \\left(- c_{l1} + 1\\right)^{2} + 0.5 c_{l2}^{2} \\left(- c_{l2} + 1\\right)^{2} + 0.3 \\rho \\left(- 0.037 \\rho - \\frac{1.0 \\left(1.7031322 \\rho - 51.0939660000001\\right)}{1.0 \\rho^{2} - 40.0 \\rho + 400.0} + 0.042578305 \\log{\\left (1.0 \\rho \\right )} - 0.0530922164415325\\right) + 0.5 {\\partial c_{l1}}^{2} + 0.5 {\\partial c_{l2}}^{2} + 0.005 {\\partial \\rho}^{2} + 0.00085206629489322$$"
+      ],
+      "text/plain": [
+       "       2           2          2           2         ⎛           1.0⋅(1.7031322\n",
+       "0.5⋅cₗ₁ ⋅(-cₗ₁ + 1)  + 0.5⋅cₗ₂ ⋅(-cₗ₂ + 1)  + 0.3⋅ρ⋅⎜-0.037⋅ρ - ──────────────\n",
+       "                                                    ⎜                      2  \n",
+       "                                                    ⎝                 1.0⋅ρ  -\n",
+       "\n",
+       "⋅ρ - 51.0939660000001)                                              ⎞         \n",
+       "────────────────────── + 0.042578305⋅log(1.0⋅ρ) - 0.0530922164415325⎟ + 0.5⋅D(\n",
+       "                                                                    ⎟         \n",
+       " 40.0⋅ρ + 400.0                                                     ⎠         \n",
+       "\n",
+       "     2              2               2                      \n",
+       "c_l1)  + 0.5â‹…D(c_l2)  + 0.005â‹…D(rho)  + 0.00085206629489322\n",
+       "                                                           \n",
+       "                                                           "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "free_energy = free_energy_high_density_ratio(eos, ρ, ρ_g, ρ_l, c_l1, c_l2, λ, κ)\n",
+    "free_energy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the free energy expressed in the order parameters $\\rho, c_{l1}, c_{l2}$. Next we have to transform it into coordinates $\\rho, \\phi$. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "transformation_eqs = [ c_l1 - (1 + φ/χ - (ρ - ρ_l)/(ρ_g - ρ_l)) / 2,\n",
+    "                       c_l2 - (1 - φ/χ - (ρ - ρ_l)/(ρ_g - ρ_l)) / 2]\n",
+    "transform_forward_substitutions = sp.solve(transformation_eqs, [c_l1, c_l2])\n",
+    "transform_backward_substitutions = sp.solve(transformation_eqs, [ρ, φ])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To do the transformation, we use the substitutions dict.\n",
+    "After the substitutions the differentials have to be expanded again."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left\\{\\phi, \\rho\\right\\}$$"
+      ],
+      "text/plain": [
+       "{φ, ρ}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "free_energy_transformed = free_energy.subs(transform_forward_substitutions)\n",
+    "free_energy_transformed = expand_diff_full(free_energy_transformed, functions=(ρ, φ))\n",
+    "free_energy_transformed.atoms(sp.Symbol)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now the free energy depends only on ρ and φ. This transformed form is later used to derive expressions for the chemical potential, pressure tensor and force computations."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part 2: Data setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh = create_data_handling(domain_size, periodicity=True, default_target=target)\n",
+    "\n",
+    "# Fields for order parameters\n",
+    "ρ_field = dh.add_array(\"rho\")\n",
+    "φ_field = dh.add_array(\"phi\")\n",
+    "c_field = dh.add_array(\"c\", values_per_cell=2)\n",
+    "\n",
+    "# Chemical potential, pressure tensor, forces and velocities\n",
+    "μ_phi_field = dh.add_array(\"mu_phi\", latex_name=r\"\\mu_{\\phi}\")\n",
+    "pbs_field = dh.add_array(\"pbs\")\n",
+    "pressure_tensor_field = dh.add_array(\"p\", len(symmetric_tensor_linearization(dh.dim)))\n",
+    "force_field = dh.add_array(\"force\", values_per_cell=dh.dim, latex_name=\"F\")\n",
+    "vel_field = dh.add_array(\"velocity\", values_per_cell=dh.dim)\n",
+    "\n",
+    "# PDF fields for lattice Boltzmann schemes\n",
+    "pdf_src_rho = dh.add_array(\"pdf_src_rho\", values_per_cell=len(stencil))\n",
+    "pdf_dst_rho = dh.add_array_like(\"pdf_dst_rho\", \"pdf_src_rho\")\n",
+    "\n",
+    "pdf_src_phi = dh.add_array(\"pdf_src_phi\", values_per_cell=len(stencil))\n",
+    "pdf_dst_phi = dh.add_array_like(\"pdf_dst_phi\", \"pdf_src_phi\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part 3a: Compute kernels and time loop\n",
+    "\n",
+    "We define one function that takes an expression with derivative objects in it, substitutes the spatial derivatives with finite differences using the strategy defined in the `fd_discretization` function and compiles a kernel from it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def make_kernel(assignments):\n",
+    "    # assignments may be using the symbols ρ and φ\n",
+    "    # these is substituted with the access to the corresponding fields here\n",
+    "    field_substitutions = {\n",
+    "        ρ: ρ_field.center,\n",
+    "        φ: φ_field.center\n",
+    "    }\n",
+    "    \n",
+    "    processed_assignments = []\n",
+    "    for a in assignments:\n",
+    "        new_rhs = a.rhs.subs(field_substitutions)\n",
+    "        \n",
+    "        # ∂∂f representing the laplacian of f is replaced by the explicit carteisan form\n",
+    "        # ∂_0 ∂_0 f + ∂_1 ∂_1 f     (example for 2D)\n",
+    "        # otherwise the discretization would not do the correct thing\n",
+    "        new_rhs = replace_generic_laplacian(new_rhs)\n",
+    "        \n",
+    "        # Next the \"∂\" objects are replaced using finite differences\n",
+    "        new_rhs = discretize_spatial(new_rhs, dx=1, stencil=fd_discretization)\n",
+    "        processed_assignments.append(Assignment(a.lhs, new_rhs))\n",
+    "        \n",
+    "    return create_kernel(processed_assignments, target=target, cpu_openmp=threads).compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Chemical Potential\n",
+    "\n",
+    "In the next cell the kernel to compute the chemical potential is created. First an analytic expression for μ is obtained using the free energy, which is then passed to the discretization function above to create a kernel from it. We only have to store the chemical potential of the φ coordinate explicitly, which enters the Cahn-Hilliard lattice Boltzmann for φ."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$${{\\mu_{\\phi}}_{(0,0)}} \\leftarrow 0.0004 \\phi^{3} + 0.000473530700220886 \\phi \\rho^{2} - 0.00760399528440326 \\phi \\rho + 0.0205263968409311 \\phi - 0.02 {\\partial {\\partial \\phi}}$$"
+      ],
+      "text/plain": [
+       "                 3                           2                                \n",
+       "μ_φ_C := 0.0004⋅φ  + 0.000473530700220886⋅φ⋅ρ  - 0.00760399528440326⋅φ⋅ρ + 0.0\n",
+       "\n",
+       "                                  \n",
+       "205263968409311⋅φ - 0.02⋅D(D(phi))"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "μ_ρ, μ_φ = chemical_potentials_from_free_energy(free_energy_transformed, \n",
+    "                                                order_parameters=(ρ, φ))\n",
+    "μ_phi_assignment = Assignment(μ_phi_field.center, μ_φ)\n",
+    "μ_kernel = make_kernel([μ_phi_assignment])\n",
+    "μ_phi_assignment"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Pressure tensor and force computation\n",
+    "\n",
+    "For the pressure tensor a trick for enhancing numerical stability is used: the bulk component is not stored directly in the pressure tensor field, but the related quantity called `pbs` is stored in a separate field.\n",
+    "\n",
+    "$ pbs = \\sqrt{|ρ  c_s^2 - p_{bulk} |} $\n",
+    "\n",
+    "The force is then calculated as $ \\nabla \\cdot  P_{if} + 2  (\\nabla pbs) pbs$\n",
+    "\n",
+    "In the following kernel the pressure tensor field is filled with $P_{if}$ and the pbs field with above expression."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Bulk part\n",
+    "pressure_assignments = [\n",
+    "    Assignment(pbs_field.center, \n",
+    "               pressure_tensor_bulk_sqrt_term(free_energy_transformed, (ρ, φ), ρ)),\n",
+    "]\n",
+    "\n",
+    "# Interface part\n",
+    "P_if = pressure_tensor_from_free_energy(free_energy_transformed, (ρ, φ), \n",
+    "                                        dim=dh.dim, include_bulk=False)\n",
+    "index_map = symmetric_tensor_linearization(dh.dim)\n",
+    "\n",
+    "pressure_assignments += [\n",
+    "    Assignment(pressure_tensor_field(index_1d), P_if[index_2d])\n",
+    "    for index_2d, index_1d in index_map.items()\n",
+    "]\n",
+    "pressure_kernel = make_kernel(pressure_assignments)\n",
+    "\n",
+    "\n",
+    "# Force kernel\n",
+    "pressure_tensor_sym = sp.Matrix(dh.dim, dh.dim, \n",
+    "                                lambda i, j: pressure_tensor_field(index_map[i, j] \n",
+    "                                                                   if i < j else index_map[j, i]))\n",
+    "force_term = force_from_pressure_tensor(pressure_tensor_sym, \n",
+    "                                        functions=[ρ, φ], \n",
+    "                                        pbs=pbs_field.center)\n",
+    "force_assignments = [\n",
+    "    Assignment(force_field(i), \n",
+    "               force_term[i] + external_force[i] *  ρ_field.center / ρ_l)\n",
+    "    for i in range(dh.dim)\n",
+    "]\n",
+    "force_kernel = make_kernel(force_assignments)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Lattice Boltzmann schemes for time evolution of ρ and φ\n",
+    "\n",
+    "- ρ is handled by a normal LB method (compressible, entropic equilibrium)\n",
+    "- stream and collide are splitted into separate kernels\n",
+    "- macroscopic values are computed after the stream, but inside the stream kernel\n",
+    "- velocity field stores the velocity which was not corrected for the forces yet\n",
+    "- the φ collision kernel corrects the velocity itself, because then the updated forces are used for the correction. When u is computed, the updated forces are not computed yet\n",
+    "- when ρ and φ are updated, they are clipped to a valid region, this clipping should be only necessary during equilibration of the system\n",
+    "- exact difference method is used to couple the force into the ρ-LBM"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The following cell handles the clipping of the order parameters:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if clipping:\n",
+    "    def clip(ac, symbol, min_value, max_value):\n",
+    "        \"\"\"Function to clip the value of a symbol which is on one of lhs of the assignments \n",
+    "        in an assignment collection\"\"\"\n",
+    "        assert symbol in ac.bound_symbols\n",
+    "        for i in range(len(ac.subexpressions)):\n",
+    "            a = ac.subexpressions[i]\n",
+    "            if a.lhs == symbol:\n",
+    "                new_assignment = Assignment(symbol, sp.Piecewise((max_value, a.rhs > max_value), \n",
+    "                                                                 (min_value, a.rhs < min_value), \n",
+    "                                                                 (a.rhs, True)))\n",
+    "                ac.subexpressions[i] = new_assignment\n",
+    "                break\n",
+    "\n",
+    "    # TODO: how can this 'densgin' be derived automatically?            \n",
+    "    tred = reduced_temperature\n",
+    "    densgin = -67.098 \\\n",
+    "              + 549.69 * tred \\\n",
+    "              - 1850.6 * tred * tred \\\n",
+    "              + 3281 * tred * tred * tred \\\n",
+    "              - 3237.3 * tred * tred * tred * tred \\\n",
+    "              + 1687.6 * tred * tred * tred * tred * tred \\\n",
+    "              - 361.51 * tred * tred * tred * tred * tred * tred\n",
+    "    ρ_clip_min, ρ_clip_max = densgin * 0.5, 1.2 * ρ_l \n",
+    "    φ_clip_min, φ_clip_max = -χ * 1.5, χ * 1.5          "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, the collide and stream kernels for the ρ lattice Boltzmann are created"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "force_model = EDM(force_field.center_vector)\n",
+    "\n",
+    "ρ_lbm_params = {\n",
+    "    'stencil': stencil,\n",
+    "    'method' : 'trt-kbc-n2',\n",
+    "    'compressible': True,\n",
+    "    'relaxation_rate': ρ_relaxation_rate,\n",
+    "    'optimization': {\n",
+    "        'symbolic_field': pdf_src_rho,\n",
+    "        'symbolic_temporary_field': pdf_dst_rho,\n",
+    "        'openmp': threads, \n",
+    "        'target': target\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "# Standard collision step, that does not compute ρ and u from pdfs, but reads\n",
+    "# them from fields - this is necessary because ρ may have been clipped before\n",
+    "# the velocity field is not force corrected, which is the correct for the EDM model\n",
+    "# but might be wrong for other force models\n",
+    "ρ_collide = create_lb_function(kernel_type='collide_only',\n",
+    "                               density_input=ρ_field,\n",
+    "                               force_model=force_model,\n",
+    "                               velocity_input=vel_field,\n",
+    "                               **ρ_lbm_params)\n",
+    "\n",
+    "\n",
+    "# First the assignments are created, then the density is clipped\n",
+    "# then a kernel is created from the clipped assignments\n",
+    "ρ_stream_ur = create_lb_update_rule(kernel_type='stream_pull_only',\n",
+    "                                    force_model=None, #save uncorrected velocity\n",
+    "                                    output={'density': ρ_field, \n",
+    "                                            'velocity': vel_field},\n",
+    "                                    **ρ_lbm_params)\n",
+    "\n",
+    "if clipping:\n",
+    "    clip(ρ_stream_ur, sp.Symbol(\"rho\"), ρ_clip_min, ρ_clip_max)\n",
+    "ρ_stream = create_lb_function(update_rule=ρ_stream_ur, **ρ_lbm_params)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The φ lattice Boltzmann solve the Cahn-Hilliard equation. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "φ_lb_method = cahn_hilliard_lb_method(stencil=stencil, \n",
+    "                                      mu=μ_phi_field.center, \n",
+    "                                      relaxation_rate=φ_relaxation_rate, \n",
+    "                                      gamma=1)\n",
+    "φ_lbm_params = {\n",
+    "    'lb_method' : φ_lb_method,\n",
+    "    'compressible': True,\n",
+    "    'optimization': {\n",
+    "        'symbolic_field': pdf_src_phi,\n",
+    "        'symbolic_temporary_field': pdf_dst_phi,\n",
+    "        'openmp': threads, \n",
+    "        'target': target\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "ch_method = cahn_hilliard_lb_method(stencil=stencil, \n",
+    "                                    mu=μ_phi_field.center, \n",
+    "                                    relaxation_rate=φ_relaxation_rate, \n",
+    "                                    gamma=1)\n",
+    "\n",
+    "corrected_vel = vel_field.center_vector + sp.Matrix(force_model.macroscopic_velocity_shift(ρ_field.center))\n",
+    "φ_collide = create_lb_function(kernel_type='collide_only',\n",
+    "                               density_input=φ_field,\n",
+    "                               velocity_input=corrected_vel,\n",
+    "                               **φ_lbm_params)\n",
+    "\n",
+    "φ_stream_ur = create_lb_update_rule(kernel_type='stream_pull_only',\n",
+    "                                    output={'density': φ_field},\n",
+    "                                    **φ_lbm_params)\n",
+    "if clipping:\n",
+    "    clip(φ_stream_ur, sp.Symbol(\"rho\"), φ_clip_min, φ_clip_max)\n",
+    "φ_stream = create_lb_function(update_rule=φ_stream_ur, **φ_lbm_params)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Time loop\n",
+    "\n",
+    "Now we can put all kernels together into a time loop function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "op_sync = dh.synchronization_function([ρ_field.name, φ_field.name])\n",
+    "p_sync = dh.synchronization_function([pbs_field.name, pressure_tensor_field.name])\n",
+    "pdf_sync = dh.synchronization_function([pdf_src_phi.name, pdf_src_rho.name])\n",
+    "\n",
+    "def time_loop(steps):\n",
+    "    for t in range(steps):\n",
+    "        op_sync()\n",
+    "        dh.run_kernel(μ_kernel)\n",
+    "        dh.run_kernel(pressure_kernel)\n",
+    "        \n",
+    "        p_sync()\n",
+    "        dh.run_kernel(force_kernel)\n",
+    "        \n",
+    "        dh.run_kernel(ρ_collide)\n",
+    "        dh.run_kernel(φ_collide)\n",
+    "        \n",
+    "        pdf_sync()\n",
+    "        dh.run_kernel(ρ_stream)\n",
+    "        dh.run_kernel(φ_stream)\n",
+    "        dh.swap(pdf_dst_phi.name, pdf_src_phi.name)\n",
+    "        dh.swap(pdf_dst_rho.name, pdf_src_rho.name)\n",
+    "    return dh.cpu_arrays[φ_field.name][1:-1, 1:-1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part 3b: Compiling getter & setter kernels"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The setter kernel computes ρ, φ from C and sets the pdfs to equilibrium using the values in the order parameter and velocity fields."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "init_assignments = [ \n",
+    "    Assignment( φ_field.center, transform_backward_substitutions[φ].subs({ c_l1: c_field(0), c_l2: c_field(1)} )),\n",
+    "    Assignment( ρ_field.center, transform_backward_substitutions[ρ].subs({ c_l1: c_field(0), c_l2: c_field(1)} )),\n",
+    "]\n",
+    "\n",
+    "init_rho = pdf_initialization_assignments(ρ_collide.method, \n",
+    "                                          density=ρ_field.center, \n",
+    "                                          velocity=vel_field.center_vector, \n",
+    "                                          pdfs=pdf_src_rho.center_vector)\n",
+    "init_rho = init_rho.new_without_subexpressions()\n",
+    "init_assignments += init_rho.all_assignments\n",
+    "\n",
+    "init_phi = pdf_initialization_assignments(φ_collide.method,\n",
+    "                                          density=φ_field.center,\n",
+    "                                          velocity=(0,0,0), \n",
+    "                                          pdfs=pdf_src_phi.center_vector)\n",
+    "init_phi = init_phi.new_without_subexpressions().new_with_substitutions({μ_phi_field.center: 0})\n",
+    "init_assignments += init_phi.all_assignments\n",
+    "\n",
+    "init_pdfs_assignments = init_rho.all_assignments + init_phi.all_assignments\n",
+    "\n",
+    "init_pdfs_kernel = create_kernel(init_pdfs_assignments).compile()\n",
+    "init_kernel = create_kernel(init_assignments).compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part 4: Geometry initialization & plotting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_status():\n",
+    "    plt.figure(figsize=(25, 6))\n",
+    "    plt.subplot(1, 4, 1)\n",
+    "    ρ_arr = dh.cpu_arrays[ρ_field.name][1:-1, 1:-1]\n",
+    "    plt.scalar_field(ρ_arr)\n",
+    "    plt.title(\"ρ ({:.2f}, {:.2f})\".format(np.min(ρ_arr), np.max(ρ_arr)))\n",
+    "    plt.colorbar()\n",
+    "    \n",
+    "    plt.subplot(1, 4, 2)\n",
+    "    φ_arr = dh.cpu_arrays[φ_field.name][1:-1, 1:-1]\n",
+    "    plt.scalar_field(φ_arr)\n",
+    "    plt.title(\"φ ({:.2f}, {:.2f})\".format(np.min(φ_arr), np.max(φ_arr)))\n",
+    "    plt.colorbar()\n",
+    "\n",
+    "    plt.subplot(1, 4, 3)\n",
+    "    f_arr = dh.cpu_arrays[force_field.name][1:-1, 1:-1]\n",
+    "    plt.vector_field_magnitude(f_arr)\n",
+    "    plt.title(\"F ({:.2f}, {:.2f})\".format(np.min(f_arr), np.max(f_arr)))\n",
+    "    plt.colorbar()\n",
+    "    \n",
+    "    plt.subplot(1, 4, 4)\n",
+    "    μ_arr = dh.cpu_arrays[μ_phi_field.name][1:-1, 1:-1]\n",
+    "    plt.scalar_field(μ_arr)\n",
+    "    plt.title(\"μ_φ ({:.2f}, {:.2f})\".format(np.min(μ_arr), np.max(μ_arr)))\n",
+    "    plt.colorbar()\n",
+    "\n",
+    "def init_drop():\n",
+    "    radius = dh.shape[0] // 5\n",
+    "    mid1 = [dh.shape[0] // 2, dh.shape[1] // 2]\n",
+    "\n",
+    "    for block in dh.iterate(ghost_layers=True):\n",
+    "        x, y = block.midpoint_arrays\n",
+    "        mask1 = (x - mid1[0]) ** 2 + (y - mid1[1])**2 < radius ** 2\n",
+    "\n",
+    "        block[force_field.name].fill(0)\n",
+    "        block[vel_field.name].fill(0)\n",
+    "        block[μ_phi_field.name].fill(0)\n",
+    "\n",
+    "        c_arr = block[c_field.name]\n",
+    "        c_arr[:, :].fill(0.0)\n",
+    "        c_arr[mask1, 0] = 1.0\n",
+    "\n",
+    "        gaussian_filter(c_arr[..., 0], sigma=3, output=c_arr[..., 0])\n",
+    "        gaussian_filter(c_arr[..., 1], sigma=3, output=c_arr[..., 1])\n",
+    "\n",
+    "    dh.run_kernel(init_kernel)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Part 5: Putting it all together"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1800x432 with 8 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "init_drop()\n",
+    "time_loop(1000)\n",
+    "plot_status()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ρ_arr = dh.gather_array(ρ_field.name)\n",
+    "assert not np.isnan(np.min(ρ_arr))\n",
+    "assert not np.isnan(np.max(ρ_arr))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_eos.py b/lbmpy_tests/phasefield/test_eos.py
new file mode 100644
index 0000000000000000000000000000000000000000..07821a0ae99fcbdb5ab29111082147d37a8d7257
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_eos.py
@@ -0,0 +1,44 @@
+from lbmpy.phasefield.eos import *
+
+
+def test_eos_to_free_energy_conversion():
+    rho, r, t, a, b, c = sp.symbols("rho, r, t, a, b, c")
+    eos = carnahan_starling_eos(rho, r, t, a, b)
+    f = free_energy_from_eos(eos, rho, c)
+
+    assert sp.simplify(eos_from_free_energy(f, rho) - eos) == 0
+
+
+def test_maxwell_construction_cs():
+    """Test of Maxwell construction routine with parameters from paper
+    Ternary free-energy entropic lattice Boltzmann model with high density ratio
+    """
+    rho = sp.Symbol("rho")
+    a = 0.037
+    b = 0.2
+    reduced_temperature = 0.69
+
+    eos = carnahan_starling_eos(rho,
+                                gas_constant=1,
+                                temperature=carnahan_starling_critical_temperature(a, b, 1) * reduced_temperature,
+                                a=a, b=b)
+    r = maxwell_construction(eos, tolerance=1e-3)
+    assert abs(r[0] - 0.17) < 0.01
+    assert abs(r[1] - 7.26) < 0.01
+
+
+def test_maxwell_construction_vw():
+    """Test of Maxwell construction routine with parameters from paper
+    Ternary free-energy entropic lattice Boltzmann model with high density ratio
+    """
+    rho = sp.Symbol("rho")
+    a = 2. / 49.0
+    b = 2.0 / 21.0
+    reduced_temperature = 0.69
+
+    eos = van_der_walls_eos(rho, gas_constant=1,
+                            temperature=van_der_walls_critical_temperature(a, b, 1) * reduced_temperature,
+                            a=a, b=b)
+    r = maxwell_construction(eos, tolerance=1e-3)
+    assert abs(r[0] - 0.419) < 0.01
+    assert abs(r[1] - 7.556) < 0.01
diff --git a/lbmpy_tests/phasefield/test_force_computation_equivalence.py b/lbmpy_tests/phasefield/test_force_computation_equivalence.py
new file mode 100644
index 0000000000000000000000000000000000000000..8a07e3c3348536d507ee4abcdadfad01ebc90583
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_force_computation_equivalence.py
@@ -0,0 +1,37 @@
+# -*- coding: utf-8 -*-
+"""Force can be computed from pressure tensor or directly from φ and μ. The pressure tensor version is numerically
+more stable. Mathematically they should be equivalent.
+This test ensures that the complicated pressure tensor formulation yields the same force as computed directly."""
+
+import sympy as sp
+from lbmpy.phasefield.analytical import chemical_potentials_from_free_energy, substitute_laplacian_by_sum, \
+    pressure_tensor_interface_component_new, force_from_pressure_tensor, force_from_phi_and_mu
+from pystencils.fd import Diff, expand_diff_full, normalize_diff_order
+
+
+def force_computation_equivalence(dim=3, num_phases=4):
+
+    def Λ(i, j):
+        if i > j:
+            i, j = j, i
+        return sp.Symbol("Lambda_{}{}".format(i, j))
+
+    φ = sp.symbols("φ_:{}".format(num_phases))
+    f_if = sum(Λ(α, β) / 2 * Diff(φ[α]) * Diff(φ[β])
+               for α in range(num_phases) for β in range(num_phases))
+    μ = chemical_potentials_from_free_energy(f_if, order_parameters=φ)
+    μ = substitute_laplacian_by_sum(μ, dim=dim)
+
+    p = sp.Matrix(dim, dim,
+                  lambda i, j: pressure_tensor_interface_component_new(f_if, φ, dim, i, j))
+    force_from_p = force_from_pressure_tensor(p, functions=φ)
+
+    for d in range(dim):
+        t1 = normalize_diff_order(force_from_p[d])
+        t2 = expand_diff_full(force_from_phi_and_mu(φ, dim=dim, mu=μ)[d], functions=φ).expand()
+        assert t1 - t2 == 0
+    print("Success")
+
+
+if __name__ == '__main__':
+    force_computation_equivalence()
\ No newline at end of file
diff --git a/lbmpy_tests/phasefield/test_liquid_lens_angles.ipynb b/lbmpy_tests/phasefield/test_liquid_lens_angles.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..b9c6b106c3e821b929de051c4a080fb76883e1fe
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_liquid_lens_angles.ipynb
@@ -0,0 +1,198 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.phasefield.experiments2D import *\n",
+    "import lbmpy.plot2d as plt\n",
+    "from lbmpy.phasefield.post_processing import *\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Liquid lens setup - 3 phase model\n",
+    "\n",
+    "rudimentary test for liquid lens setup - angles are not yet validated with Neumann relation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sc = liquid_lens_setup(domain_size=(150, 75), optimization={'target': 'cpu', 'openmp': 2}, \n",
+    "                       kappas=(0.01, 0.02, 0.001), cahn_hilliard_relaxation_rates=[np.nan, 1, 3/2])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#for i in range(10000):\n",
+    "#    sc.run(20_000)\n",
+    "#    phi = sc.concentration[:, :].copy()\n",
+    "#    tps = get_triple_points(phi, phase_indices=[0,1,2], contour_line_eps=0.01, threshold=5.5)\n",
+    "#    print(tps[0].angles)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sc.run(5000)\n",
+    "\n",
+    "plt.figure(figsize=(16, 8))\n",
+    "phi = sc.concentration[:, :].copy()\n",
+    "plot_contour_lines(phi, alpha=0.5)\n",
+    "tps = get_triple_points(phi, phase_indices=[0,1,2], contour_line_eps=0.009, threshold=1.5)\n",
+    "plot_triple_points(tps, line_length=40)\n",
+    "\n",
+    "assert len(tps) == 2\n",
+    "for tp in tps:\n",
+    "    np.testing.assert_allclose(sum(tp.angles), 360.0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[151.4964898829199, 165.52435158031807, 42.97915853676206]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "analytic_neumann_angles([0.01, 0.02, 0.001])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Liquid lens setup - n phase model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sc = create_two_drops_between_phases(domain_size=(200, 75))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sc.run(1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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l8/EHNPJpKwpWMb8XnBdCUM6LZLNkWXx2HbzIHC8KXmRSuulysZm8EAJkVPFiKI4YzQsxjhcKFysvpsWmKHwp5R3AjSW3XroZ9GE4e/l6fToGjBf+0dSyTSoxFC/7Ictr4eJbR9fYg5jjcrNuXgiRCRND//OCSzzOHYGQmencIi0++R04+2+VFwkvhgiMn81ZnqL0egvIRfpt5fDI8m1bRlJeDCn3Uakvx8XEi2mx5ZZWyNZxwzVtHJaPM21Y0aoZhBXjDX/o4nNknsj/z9f72S6ljHIsSWuZ1brZvEDEHjwpFKQQSJHcEyJR8vSPQNwPkVKTMrkGISOEJBNWnBY+ihd5jj6evHj85WKzeVGmmrYrL7afXEyLLafwi8yTpQwdrtmmDRvGpFUzBtTKnh1+Z/E4rPAnIf/sOnlRsFhTBR4pAikUIiVW9qEQRIogyoRJMXhPmg4hI5CgJMpdjSLU5FyJIpQoShR/7FoQmeGQ/Qri8eLFOsKGcbHJRUTFi4JcSDlUHhjx3KiwYWxdXkyDLafwi5juI6yPYhb5XvFsc2taDDfoss8PfHnDH3caalmqk5/OI1KUzE8QqhqRohAqCr6q4qsqoaIQqCqhUIgySn9g2YMWRQgZoUURWhiiJz81UfhqGKJEYVIBkFH643mR5mnYghnPi5gLlVwU07d5qHiRpZh/98XDizJsQYVfTH5Zdsrr5yxGKZHxb5uu7p6UtmLjaz0pyYvC4P+45/q8EKl7RiFU1f4vUFVcTcPVdTxNx9E1PFXD1TR8JT73FSVW+orSf6WCRJGxRa9FIXoYYAUBRhhgBj5mEGD6PkYQYPh+XCEEQcbyF/3hqZN4kR1pLEq/QyUXo+mLQVC/st3GvMgi4YcU24EXk7EFFf502EiD6mLBwPItWhMFFKbZSyGIFIVA0wg0jVDTcHQdV9fpGgYdw6RjmHQ1g55u4qgarmrgqjoBKoGiEQml/15FRihE6FGAJkPM0MMMfezAo+Z71HyXuu9R8zxqnhsrf99HCwK0IEANw1z64kTmFbukOFdB9vO/Hrtp8PyU98eMY7+oIUShgh0T9cKnZsug3+oc8d23Cy+2oMIv+uRiiNzdsobMcNhw46ns2TJXyWRa40KH4wzTLzYDZe5/PrfZPv3sG9P8pL75VNH7hk5PN+iYFmuWxZpps2bEv5ZWo63aHHUC7jh9hEdWTrPcXcENHILQJ+p31MZpVoSCpmpYusW8Pctl87t5+q4DHGio1MMes36Hpucw63Zoui5N16Huuli+j+55fcWvRFFCt6yDa8CTdAyyMqT4t69cTKJf8aLixbTYcgq/mDExZAFOj/Le8+FYRbfJtD65snj9N0o5/EDhrfnn0qnSxUbj4C05Xog4NFIUQjVW9J6u0zNNOpbJql1n2ayxZNVZNhqcETb/dvIYXz/5DZY65wijAE21qFm7qTeewg7rIKaxD03bgaJYAESyi++fxfeO0XWOsNx7lGMP38lnD38FVdHY2VjkGXsu5zt272On3WHebbPgdph3ujR7PeqqiuF5mInVr0ThoCGas/TT/4MKT+byPNzg3rBc9DvxRn+LQegFkItJydsA/Yu2jExM2/rpT+RF0pFb/r6LmxfTQMgJiumxxI1CyK8IhY3UqOcTNl39vM6wTMflpPQXXTgDJT/Guui7b1R83cAzTVqWxapd40ytzhlrhjPmLHf14B8e+CrHV44ihMZM4wrmZl9Cvf5dhNFOPN/CDyyCQCcMNaRMhm5KgRARihKhqT6a5qNrDobeQ1VO0W7/b5ZX/o21zkNIGXLJ/AG+74obuM4I2eWuscNps6PbYqbnUHNdDNdF9z3UMERICvwpcn/YzRMfN0EuRBlfR6XjAsjFutNfhgm0MsNpNyetFzEvyuKsQwYuFl4oMrxdSlk2FyqHLajwVQYZHGR0PFvGMWSY1jQNvTL6RQrkQrNPyORyOP35kPi/zDwnMlTyTyTHpGM2VNXYqu8repsztSan7SYnzQW+0vb5x/tuYaW3RN3ey75dr8eyX0nHmcXzari+ReCbBKFGGOpEkYKUClIKZDJURwiZ/CJUNUBVg0Txu5hGD8tsUzNX6Hb/jqMnP0zXOc1ifZHXXPVMnmGr7HWW2dlrsaPTYbbXwXY9DM8buHj64/jLuJmtBOP/wzzZgFyIvAw85nIxIv1FucjTHU7j2DKSdlRO4kVp7p5gvBhKS+ZuqaV/cfJiWoW/5Vw6o1D8xHFY2WctMixrF+bjl7FueArEwN7Oxi/7/BKRm6yUT3+Wbqq+hitbQVFE0htJChLL3td1PNOka9ucqzc4WWtw1F7gzsDkA3d8kaXOGWbqV3Ht5b+HF97IWm+Ok0tNXLdGEGhEkTr07mmRWv667mKZPeq1gxzY9wY09cscPf57vOeOT7K7sYv/eO0zub5p4ak6Uleh3UEKgeG56H48AijuZBzkNzv9JcuBcofXBuQimYUpxWMsF6N4OUYu1jvE8HEpI4UZ2OmQwiytKPf28bxIv3NaxadczY2tnwJT8SJdlkKIzeFFP9bWkosstrTCL2P+4ONlQ4dR9OUVpzKnrBumlyqb4Xvj3jeKbjEvcihHg7SNW8lOIpBJx6xn6LQsm5V6nVO1Jsdq8zysz/OXD97D3afuoWbu4ror300QfRtrvTm63Rk8P3XbqH0L/nwgpSAIDBwUwlCj5zSo15oc2P801OhLPHDkt/md2z7BDXuu4fUHr+CQvsQ+bY1dnRYzvS4110X3/djFE4Z9nuUmffULfzkvs1x8IslFGS9G0318eAGyP9Ur/UJROskvmdEdCfoxQGSuCzmQ+VCRWSZCSRS8ItM3F1vBOUqVXEzAFnTp5H34+aZSNnSYRRsLK3/DVJiKd8M97IMmX/75oc+eFJDscMueadK2bc40mpyszfCIvcjN7YiP3nszQRhycO9bMewfptXZQac3i+PU8H0jcdVcmD3rhYgQQmJZXWyrTb22SrN2ml7nfTx8/M8xVIPXX/NcXmBLDnaX2NFtsdDp0Oj1MH0P3Q9yM3SzC4LF3Brm06bKRalP9zzkYiqMlotivElhuZSO6RvZOH8GoZJYsWePoRBEmZ/MHGFQEchRnaXpLG3ILNchUWSs8Ae/CEUSz/Qmmf2NRKSmkhw1PXEd+RbFMnJxyMVF7MMfjAMfNJ7yVyLDlGzqh6+Hm2DDKKNf9lmLM+IGglqkkn1Xmt5iavLpHPF5RVybh5qGr+u4lsm5WmzVP1Jf4LC2wPsf/BYPnjtMs34N+/f+P3TdK+h05+g5DTzPyln0F1LhA3EHrxZg6A71+ip1e4W6cTcPH/0lWt2HuW7HFbz50BVc5i5zSWeFvd02DaeH6bi5cfvF3apSKzINVUq+0HnJxUhfbpH+lHJRoJ9NwyS5GKdI8vIzooz0F7zbvDIihUwUu0IoBIGi9H+REPiqSiTi5TtCRSUSglAR/eU6ov4aTqMU/kDBkyh3IeNrNYqSX7yshxZFKFKiRRF6FKFGIUrSQlByC8htUC7StI7gxVaVC/XiVfjjfcvT1tWl984jr5OaZuunN9yYGyj6gVUfqipdw6Bt25yr1Tlen+VRa4FbXI0P3vNv+KHPof0/iWb+IO3uIp3uLK5rZ9w3F0bJj4KihChKhGG4WFaHRm2JmfpZnO5f8ODRP8PSTN547fN4juZzsLvEzu4ai50ONcfBzIzZl1KWfOdRDeDzlItxmDBBa7PlYl3vGCHPm8ILEavJMFl3KVAU/GRJDleLl+XwNBVP0/A1lVBV8FWFUFUSuVViZa/ERzIW/9CrktnY6YJ8SpSu0yTRwgg1jJf00MIIPQgxghAjCNDDCD0MMcMwnuWdrvNEIiPZ1V7PkxfrxWMtFxexha/mas1xRbsYb7ihW7Cc0w67MfTLauyy+GXvLsYfRbdIYyjFmVE4rmmyXKtxptbgkdo8h/VF/vLYEb5x+lvY5n4u2f8uHO86Wp1FHKeO55nJiJsLa9WPQmrtCyFR1RDL7FKrrdGoLWPrX+fBR99Ozz3Ns/Zcxw/v2cPl7jKHOsvMdbs0HQfTdft+/XG83lS5GBdfDNNkTPwLKhfF+CMU2mbwIhTxua+quOnSHJqKo+s4hoara7iGjmdoeIZGoKuEmkKgK0SqQqQKpJL8BEhF6b8q7UISKXOkBAlKlCj9KEKEEjWUKEGEGkRofojhBeh+iOn5mF6A5QdYno/lBxhhiBnER1XG/WEx/U2QC1E+SLpIkzH0L7RcXLwKH+W8aseNWnUXskYebu6VvDH1iyaK3td11iyLZcvmaH2Oo/YCt/oGH7zvC3T9Lvt3vZZG86foODvpdGfp9Rq5Ttlxil6Izfnm4zp/U7++rvsYhotttWnUlqhbp1lZ+QOOnv4nmkaDN131LJ6t9NjfW2Vvt8V8oUM3nqHLSGtt6rSOeXZLy8WINFwoXkQi9rn7ioKrqvT0eO2lrmnQsQy6tkHPNnBsHd/W8C2N0NIIDcGJXo/7zrQ4ttplqePSdn0cL8QLQsJIEkYSKWWuYSIEqIqCqgg0VWDqKjVDY9Y22NG0uHyhwRXzTRqoqE6A5obovQCz52P1fGo9j5rjYbseddfD8gPMjNUfdwCPd4dcELk4j6U7+nKR083j5UIhulgVftwgGyBfLOJMltXN0xaLsnqSkrCN0BpPf9jWGFgP6fLFnmHgJC6cU7U6x+1ZDls7+euTJ7n12NfR1CaHDvwOkXgO7e48vV4T17PxvNEds5ul4MehTPmn1r6qhui6h211sO0WzdpZRPQ5Dh/5DYKwy3fsfyo/sHOeQ+4SB7przHc71HtOZoZuNOgvGTGh7QknF1OelaV1o7yIRNwB66kKPU2na+i0LZOObdCqW3TrJt2midfQ6ZiCm4+e5quPLHFsqUPH8ZESDF2hXtNo1HQaDY2arWHbKqahoBsCTVVQhOibr2Ek8YMI141w3ZBuL6TTCWh3fNrdgJ4TEkUSTRUsNC0u3z3Diy/fzTX1Okbbx2x71Noe9Y5Ls+vQcFxqrkctsfr1MERFIuQTWy7UKRX+lhuWWd4ZNUD2bj5sWqtnuBE33TCn87fzyigISNw38YzZrmWxUqtxotbkEXuBb9Hkz+66haXuOXYtvJSFxbfT6R2g5zRx3NiFEwTapgy13HzE3I0iBd83EALCSCMMNWr2TVx7xXWcPP3bfPbYl7hreZEfv/oZtIwaB8wV9uktar0eluehJ4pfRNG2kotRYReijERIfEXtW/Uty6Rtm6w2bFozFp1ZE3fO4svLy3zs8/dy7FwHXVe4dH+dl71kN897zjzXXV3H0EAVUbzSqohIh1EK5GAwVCFBUiQGg4AoSvqvpCBEIYwUzq2GfOW2Fb5y+zL3PbDCLfeeQtcUnnZokR946mXsnrforLj0VnWclkazqxL2XGw/oAaIMCQeCiKKr35CycVUNLeqhZ+vv8hdlVkvUJbxyTXq6Nq+nPYkv99UFoGgv+tU6r7pGTptu8bZepOTtSZHrEU+frbFxw9/CUUxufySdyKVF9N15uj2ZvA8C983CEOVKIqHspZb2Y/t951k6atqiGG4mGYX22rRtM8ig09y/5HfRcqA77vy2bxizuZgb5kdnRbz3Q4Nx8H0XHR/sPRyrCmK9s5FLhcTnhud2/MrI5EQBELQ1XU6hsGabbBWr7EyY7O2UMNZMPns2SU+8uWH6Dg+1145y4/84KU87ckNTDXAEAG6CNEIUWWEStRX9grJMEtB7igZWPmIWImmC+dFKEQyVvwBKiEKgVTxpIYXaay5gr/525N8/FPHWVn1uGLvLG99zpXscwX1pR6zqz3m17o0ey5Nx6Xme+iRREs6hp+IcjGthb8FFX7qkshmvGxBpCwTxgn3+uKVNaiG4w43vAa1fznN7H+UweqWrmniWSbLdp2z9TpHagvcK2b443tu48TaCRbnXsCuHe+k3TtAz41nyvq+kcyWTTtnk7dtWYWfpkH2O3N13U9m6naoWas07Ic5cerXObtyO5fO7eOnr34yVwUt9ndX2dFpx2P2HQfd9xI3jwQZPaHkYjg12aeHU70ZZUQiCRSBo+m0TJOWpbPcrLM8X2dt0eZ4Q+X3P/tNTi33eP6zd/LTP3aQXTOSmuJhCQ9DBugiQI1+//a6AAAgAElEQVRCNJFsgiNk4juXfc4J5ER9J2XcyYskWaY7Vv6hUAlR8YWKj4YjDRx0uqHJF29v8//+yYOcPtfjZU/ex+uvvIT62R7zZzvMtXrMt7s03Hg5bzOMMkM3n1hycRH78LM7x2cxTvjz94ZZWmTtMK3hsPy9wcy74XTlZ+UVx9uLZJx3uoyxINB0fF2jY5q07DpL9Ton63Mct+b4+Lk2/3TvF1AUi8sP/jKhvImuM0vPaeJ5g9myWWU/vvP08fm+oxW/RFHipRlSa1/XHer2Ko3aOQj+mfsf+T2k9HnNtc/l5bMW+3rL7Oy0me+0aPacvpsn3WkrNhHzcyIuCrkYSb+Ynjzd9dwbxwspJIFQ6GkqHcNkuW6x0qxxbrFJa5fNv7ZWef/N97N7h8VvvvNJXLZH0FBcatLFEi66DNBlgCaD2KqXiVUvI0gt+v7bxiCTtP7eyiTj+Im34QwTxR8IFR8dV+j0MOlIk3Zo8jf/cI73/sVhFmcs3vHi69m3EjB7rsvicpv5do8Zx6XueWjJZj4io2eeCHJxESv8gcUao1hXpmGTmkbThk1Lv4zKFPRT6yVZs95LrPqubbNUq3O2McOJ2iwPqLP88Tdv5fjqcXYvvJSFxV+j1d1Dtzsbr2iZcd9Mo+gvJKapREalrczaV9UQQ4/H7dfsFWbrRzl56jc4tfRFDs7v52euexoH/TX2dVZY6HSY6XawnR6m7/dn6fbXMBpK2haVixL65dQ3M62DsLSD1lEV2obJmm1yZrbB8mKd1T11PvToST7+tUf57pv28TNvPcCM6tCkS106GNLHjDw0AlQZxopeJgvtIXOjS4aU/SgWJuG55Q2SdZZyir9v7Wu4ikFPWHQxWZU1HjoteNsvfYvVVY9ffflTubInWDjVYiFR+rOOix0EGFGUuJqeOHJRKfypw86H/qQ78Y3YfaPjahpdy2K1VmOl3uBkY57jtXk+fmaN/33P59G0Oldc8ls44Qtpd+dxnTquZxNFCmEYT0jLjsK5uBU+pEpfCJnM0vUxDId6bZWGvYyhfJJ7H/4vyMjjtdc9l1fM2ezqrLC7s8Zsp8VMt0vNceORGGHY33C9kBK2pFxMQT9VEpOn2q8vremEKk9RaBs6q7bNuZkaZ3Y2Wd1T570PHuXmu07yU2+9iu+9aZZ5pUND9qjJHpb00KWPFsbe9dRtk1Psyav7ir8suROSWpyklVYEEhErfaESJErfESZtUWNV1ljyTH72Hfdw+OEWv3TTk3myo7BwusXicocdrQ4Nz8cOArRkmYbJ24pcHHLxhFf4m7UOybgadbgRPP1H7S9jLMDXNLqmRatWY61W50xjhlP1OQ6rs/zRnV/i5NpJ9u18Gc2ZX6fd3UW7O5ebLQuMHVd/saM4WcswXAyjx0zjLLP145w9+06On/0Ch+b38xNPejqXeWvs7Cyz2Gkx3+5guy41142b6lGiGs57TZkLJBdj6G9crqenJYEI8FSVnqqyapucm6lzbr7BuQNNPnrmLH972xF+8Wev4RUvqDGvdJmRbWqRgyk99MiPu1Fl7MJJXx8vS7COrJdlqZiFwv2+u0eIuGNXKARCw0eno9l0sFmlzlnf5j//yn3ce7jFb7/iKRxaDlg83WHXUovZnkvTdbHCAFWmy3RMStjWl4vHXOELIVTgNuCYlPJ7hBCXAR8CFoCvAj8spfTG0ch32l48KP20SrzuiJvsQrVaq7PUaHKmMcvxxiL/utbjI9+4GVW1ufzg79FzX8jSyh48z8b39YyFnAj5lhx2uTnIunmy16bpULPXWJg7iaV9knse/A2QPm966gt4oaWwu73CrtYKs90OzW4X2/PQgwA1s3H644lpivdjiXQ9ohDo6jptw+Bcw+LsQoNzuxt8UfP5b/9yLz/yHy7lR79/gUXRpkmXRtTFjFz0yEchKkwIIlb4F6KvqMBAGft8cmGpm8dVTBzFpCVqLNPgjGvzpp/6Fp12wLte9hR2nuiy+9QaC60e8z2Hmu/Ha/FQtPIvPC6EXEyr8DdTu/4McHfm+neBd0kprwKWgTdv4ru2FHIfL1kp0FVV2qYZd8g2Zzgyv8iD87u5Z/YAf3D/A3zo659hcf5Grr7iH1lt38TSyh4cp47v60SRmmxGkt+Q5ImKNI9pnuP8CzzPpNOd5ezSAVrOK7n+mo8wN3Mt7/naZ/nDR09w3+xeHp7fybGZec40Z1i1bXqGgZ8s6vW45CXzl7/KhpPcfazTRn9dHFdV6ZgarbrF6pzNqRmFP/q3+3n6U+Z442sWmaPDTNShHvWwAgc9HCj7rBtnyJ2z3gRlj0UUPmG/nyCTBkVGaDLAjFzs0KEZdZmVHXaYDu/6zWtxg4j/fudDtHdYrMxYrNVMOrqGq6qEiZwML8B9YTFOMi+0XGzKxCshxAHgu4HfBH5OxMNSXgL8YBLl/cA7gT+aTCz+N6gFp/OZDVbnZmy8Mn+YUqDfjzFhavPAWTkIj5B4mh4veGZZnGs0WKrPcqy5g3u1Gf7HLZ+k43a4+rJfIBKv49ipvbTbc/i+McSK7YCsZZit2KRUCMN4rX3HqeG4NTq9GXbv+f9YnHsftz38Xh5aPsnbbngulyk6oaIQimQpXimTxbXC5NOIlGhKndJvmVkad+AnpRBWLJBFWnGMsqXfRE6iBw3/sjj5sPIleyUMOqv77y5PlxQDhe8pCj1do2MatBoG3Tmd//blB9FUwTvfdpAFpcMsHRqyixm6GHgUO2NzKDJlkkZL4+QbsZNREj9Nl0bQHyUk1XgUzMHFGf6vHzvE77/7QT5/6QIvmzWx3ICa62EGQWzhSxnPdpfDPBskeNh/PiwrZRkdJUHFLInM9QZdkFPWEps10/YPgF8Amsn1IrAipQyS66PA/klE4uZmRgGI4S8sC9eDeGrmfjZ2lpnkljROw6SM8tf98/xia6kPNH06W2QF8eQVX1XpmCZrls1SvcGJmQVONRb5t57gg1/5GIY+y/XXfIDl1o20O3P0eo2+n77CaPi+Qau1CFJhduYneNp1T+db9/8Cv3LrJ3nrDS/m2bO78JJhexKouS41z4vXU+l/t2GTMn82uIqS+DIZDw4ko0WGz4EpWhRlhV2S9YTE8ikL55mNNeSg6zKNE/Ut7LSiGdAaVC2xWROSrJGjaXRMnVbdpD1n8aVuh4fOdPiFn7ycvXWPJj3qsocVOWgkexUUBb+IMb73ofowS6PsuUn+/LLXy3hmrxF58Rh+AY7Q+a4XNvj7jzf4n7c+wtNfch1Gz6TW8zD9ED1dcplsWc9Wx9nEZJMmyfI6p9ILOis/6qjMoZKXgWwvQF5L5fOapmO97djzVvhCiO8BTkspbxdCvKg0hTFK6yAhxFuAtwBcQuxbzFs+SdYy61T3Va0Ybkzme/fLClRhs4UkTCAyu+skBaqwRG96PWQnCkEo444wxzTjjcTrTU425zna2MXfn1ni0w98iZ3zz2TnrndxduUAK6s7kwlUeglPhln1RHfrwGhrHyAIdIIg3nvX8038mRfzlGs/yEOP/Bzv/uqnOH3t83l5cwdBIhNzioKUEtv3UaOIdPmWPv20QGb2uB3s1CSSYxyvv6FHEj97Lslv8CHJy2BRd2XHpqc7PY2Tw6JM9jf9SAgriYWfWoopfZlRGpJk6QSh4CkKHV2jY5u0GxbdOZ0PfPp+Dh6wefkLasyIVqLsXTQ5sJpzlk/e4inPKCOup7m3AVFPKyVVCTEjFxSYERqeovL2nz7If/rZu/i7o2f5kZ076HR8bC9eZlkPQ0gMPpFpTcU8S7JdsOalGHC8/+0ZfPeysKJcjMxDhqkDmRk2UofguZNYBGyOhf984P8QQnwXYAEzxBb/nBBCS6z8A8DxsoellO8B3gPwVFWVq6bVb37m4mULUdaFUhy+lbnONkH7BSNbyGRxR53BTjqDTRhkJv6gAEIqDIIIga+p9AyDlmlxrlbnRHOeY/Vd/MXRY3zl0a9x6d4fQjPezpFjl+A49dwSxhWmh+/rhOEs3W6Tbq/Jnj1/Tt3+FT58z6dpX/Esvm9hB1oUEQFSxssGGEGAFoXxol1yYOvL/u5M9C357I5NUbIWfH83JyV/b/Ab3tWpzBjJKndySr1EDjObgKQ7PWXvD54dxE/DUtlO35nmwVPivRW6pkG7ZtKdNfnccouOE/Db/+flNFW3r+z1yM+Nwskp+myGys7LfRzT3y/Gm2TxZ406KVGJlb4tdJroXLXX4Nu/bQefuuUUr75sD/W6geX4mMkCa1EYQmYjlZSkFCCT/TmycpFeF42A4bAkaakslMhEGbLykeZp6H4/PLl6rBS+lPIdwDsAEgv/bVLKHxJCfAR4LfFInTcAH5tEy9dUjs43od+UTjKUdKz0rXxB/zpmZFrjDrtwyFhN/QIUhahSIKIQVZLsphMOdtiRJEurRihRXODUqKQSILYCA0XD1eN9Zpdr9diyr+/mA48+yu1Hv87ll/w8UryRcyt7cZx66cYkj9eM2K2KIj+y6/tHEUSRQqs9TxQp7Fr8DS7TFvinwx9G8mxeO78z6ZSLXWy262D6qbWaWG+Jko8ESeedQqQkoz4UQaCoBEqs5AMlDgsVJfklFYGSbFIjQCYdgDFdQWldnizVKzJKHinRIomQEWoUy59I5FBLNwFJZE9JZDOW0VgmBzI6kOGBnMbzEtK1chzdoGUZrDVs1mbqdOds/vZf7+fqKxo89UqDOi0s6WFIH1XGu4/1rftRKFPKk5T5tHaOKByz7yuJl6rTtKIyIh9bcampHj/2pv187paz/OPRc7xubhHDlehBzHPD9wnCeHSXkBFSUZOduuLJXvFuXmq/Yo+UJEzE3z7t/I2UdHKYJFLUvtLPVxayxBjIW/U5r0Siv8h5Jkr6K1trU7H0Qq6W+XbgQ0KI/wJ8DXjvpAc8TeXRnTM55T5Q9gOGkSlYkG829T9+auFkLfko/sVbpiWFKowLkh7GBUgL4y3V9DBEjSR6GCGiEC0iLlCRjIf9ERfeSAg8PV7SeMWus1yb5URjJ3938kyi7N9Gx/1xWu1Fut1mP6/nM3lpOyLv7ollw3FqOE6NMNRYnP9FrtgPHz/8Yeav+3Ze2phHEBEqgoamYrkuahT2Lad4G76BAo+UZMcmRcFXBaGqJdeCINnNKVAVAlUkP5VIFf1KId7eL14LZiCbsawmiYaMshdRanzEsqhEEWooUSPQwnBwDOPt/AbHWBa1RD7jiiGW4VR2FRlXFGmFEldOKo6h06pZtOp1OjM2X+30WGq5/P7vPIm60sPGw4z82JVDxFgUrf7zFdUyRT5tS6AAQVz5GcLHwqcuPHbP13nJC3bzz188zne/Yj9GV6L7Mb9NT8VLDAJFyuQbpopdDCp7NdnWMSM3Qd8QSBS/ohAoJHHie/HOX4PWYCoTxU3es96D/g5gfa/EQOlnPRV9HDk2FW82VeFLKT8LfDY5fxB49nqed0yVe6+Yi2ml5SRrMSXHIIpwgxAvDPHCiCCUhFIS9f2jAi3ZUMHSNGq6hqEocSFIdtJJf3oQoQURWiDRkms9CHNHLYxQgwAjlKhJQUu3Wg8VFU836ZkWy/UZztlzfHq5y80P3sqle3+QiDew1tqB75uleU4nGwF9N0+l6GOkM3CFkEgpRnZud3szCLGPvTt/hv07j/Khe75A/ekv5rlzO/AMjZleB8tzUIOAtAM3SCwzX1NjRa7F5/EvPRf4uoqnCYJkNydfE/HOTppgxfU43e6x1HZotTy6jhdv+OGHBGFEFGZkUoCiKGiqgq4pmIaKbWrULYO5msX8rMHOmo2tqKghiUxGaCGoQZTIo0RNtvlLZVULI7Qg3v4v3QJQ6RsqyZh5oRBq8S5V7Xqd9myds02T933qTi7d3+DAHgNTaWNEftxJW3Q8THKpjMO0z5b1CxSv11MBiNhA05UAkwBLCXnd6w7y6c+d4sOHj/P6Sw9CpBKqKqbjYvo+Ikr2VE6MgXjLxrhyD9R4u1FfU/oVfmoAhKqCrymEKkk8QaTGFUX/qJAxBhKXj4zwo0HFqqKgiHhDmFThA/2tH9Pz7LGP26djy5ZaD9+1BO/8m1syo+eS3uipHV/51mWZE1VRBKqqYBgqlqXTqBnMz1jsmW1wcEeTPbaNHoDhp9uqxQXK8EO0pOBpYYQWgZCCSNMJNBPHtFi2ZvnkybN88p47mJu5CsP+Wc6c202v1yhPcqLQVDXsK/nspuPbDdl8Z5dcUJSoXxnGS0Hn4XkmglnOrhzgkj2/xErrh3n/nTfjPfVZPH9hjl7PwPC6iDAAGfStsVixKwS6iqcpBIaKpyt4hkqgC5Z8n8NnVjl2us25lS5rbRen5+P7IVGYFEBFoGgCVVfRDAXVUFF1BUVXUEwBapKnCGQYEQYBUSciXIkIvZDQjwj9iCiSfXlVVIGmq1imRs02mGmYLDZt9s7XuWSxzoJeRw0She9H6H6IHki0IIwrBz9M9oKNW6woGlJR8Q0Tt17jjKnxh5//GjsWGjzpyTPoGuhRvLSxQjRQ+FkFO85/n/uI5BX0uLjF54qY9p3F96bRhUSV8bLNuojYtcuk2TD4+tGzGMLk+/bvx9U0DNdB9T0kcQswTFtySaUfalpiEAgCXY0rf03gawquiDi+1uXEaodz7R6rbZdOz6XnBHheSBCEhNnKf6OeW5HJnsgP3v13r3vq1GS2lML3LcnT3nYdUoCiKgiduOBYCoqpoFoKiqEgTIFI98hM/Pm5LcX6taFASBEXtNUA54yHe9rDPe3gnPbonXVYWfY4/WiHb9x7itCPa1tNV6nXDebnbPYuxBXBwZ01agh0T8aVQQRKKFBUnVC1WIo0PnznNzjd6mBbc+zb9wZOndlDr9csyWmMeP2YAFUN+wqt8uUPkCp9VY03Rk9RZukHoUarvcBaby+HDr6S5eXP8dG7v849e3fzqmsO0cRARh4RAaEq8VWBbyh4WqzYHzzb4tETLU6f67C25uAmOzgpmoJR17DnTRpXNdi1v0bjkE3t8hr6Lh00QaRKpApSkURCggJSyCG5jC21uCdPRCAigZL8RCjAkzjHXbqP9Ogd7dE75dA763J8pc3Dx5cJ3EFFo+kqdk1npmmyMFtj31ydSxYa7LYtzFDGLVY/aSFIFSE00G2+udbmo1+8gxuuu5RID5hfUNGE7G9aMnKsfRbj3C9lHbmT3DVllUQ2PFtxjLLyRSG+SNwhxGvya4pEUwTzczYv//an87FPfI1T7R6vvuZy5hQLJXQJZUigREQa+HpsDLgKnHQ8ji61OHm6w9Jqj1bbpdf18b2gvyWDqiloloZR1zAaOtbeGrPzBsasjjGvY8ybaDMq2qyGWlNQbQ2hk6ykm8mylEgfZBARuhGRFyHdiMiTyEAS+XHlQSiRiSy4V1vwv8o+1DC2lMIPjAi+R890rElCQMalIw4VaQ+6HCh78oyTBYUfb4wsEJFAjyzMqMZsKFADgRIqqL6CEghUX+AccVi6c5XV+9dYPt7l+D1r3NKLP6yiCExLo9EwmZuxWGjaGKrByTNtjpxY4oYnPYkXvuz7+cBH3o9h7SaS40fipBZr6rKo3Dl5pPzIWveT+CkRmLUdiDWNH/r3r+eLt/4rv/4vn+OKS3YwP2/RdT2WWl1W1xy6HQ/PCyFR7FZTp77L5sAzdjP/1Dma1zeRNoR6RKRLAi0k0iSRGtFTQzqqT6hGSEXGPyGTDbvjyqmY1MEKEgIlUvoVgIhiORSRQDkg0G+0MMMaC6GCGigoASiBghoKFAe6D/dYvbtF6+E27RM9Hji2xF33DQwWRU3ktG4y17SYaViISOHR4yv4QcRNL3oWNzz9Mj79uVuIkHEnpcwMKY27qNZn3Y8T20m++Y26e0bFS93BpKPrRbLhkEIkobbY4Eff+Eo+c/PX+K3Pfon9u+fZvbOO43ustBxWWw6drofnBv0KVtXjit+aM2lc3WDPJXVmrmjQuLKOOqMSqpJQi4hUGcuIEiFV4qMSy0WgSHwRJO5pt6/LSrORkRXIuHJQ+/dSO3+F6UbowFZT+HrIuX3L/etsgZHZTrvkXE6whlOFD6AkzrPYolKSCiApRKGCGqhx4TqgUH/2DDP+HJqvxhWBJ/BPe6x9s8XafS3ax3qcXO7wyLEVAi9kfucMz73pmVx99fUQGtj1GXre/RiGi6oGI2fRFt0TlbIfRqrosyuGliHeMN1DNzza3Yepzcwidtjc+IpnYX/D4q6vHubuh05i1nXMWR3rEpsdBxeZvX6GxnUNaAhCXRLqUfzTIpb0NqEWEWohkRqHRYokUkOiRMlHShQr+r7CHy+bol+AB8ZIrgKIlFhGQzU5xrKqhokshgrKQYXaC2ZoBnMogYgrgyCuDJwjDmv3tmk92KZ30uHEUoeHj68gA8mBK3fzohfcwMFL9+MZglrTZmllhVAo8WJkyUaA6dwDGIx8yX8UJivhce6caSuHDRaH7Mqa8agZJdk1S2F1zcGcrSMtixu/6xno+2y+8ZX7eOhrZ9BtDbOpY+4y2LN/hsbldWaua2LsNZAGhJok0qLBUY1YVntEWkSkRkRKekxlQyJT+SgYAmX6DAbyMfp6YzxJsaUUfqiGtGc6Q+HFwlNWmNKwUQwbFDCRUf5x4YoVvxIXtlT59ysCBSVQUPYo6E+qsctvsNdX0AIVzVMR5xSWv7zK3V96kFs+ewfXPvOpXP30Z/L1L76PSw/dRBipOE6tJLfJaJGC1Vop/QHKLftyDaNpHvOLJ6jP3cOdt/8z3/GqV/KZL36Kw3fcx+7rd3LND1/JzDPqhM2IQA8JtIhIjwvvqt5LrLMoc4yVfKRGiRWfKPvEYusr+lTJi3JDRIrhddezMimRBdlU+lZ//zoayKqSyKkaxrIa/8TguF/BenaDmt9E9RU0T8VwdYIjEWc+f46///BnWNw7z8te+Wx2XbrAZz/xED15gJ4wsIWBJ/RkKGA04PI0FvmoOOOs8oILZiy9UfdK4qVulkAk6+aj0xM6jx4PCCOJumBw61fu5pZP3oExo3PJTQd4yvNmkPMS3wgIjChW6HpEVw1oaz5SjQjVuHUnFTkkF32ZSK9T2VDyRsC0xmoRw2v3bwxbanlk9RmqtD5vld6bxKBRCj8bli1YQL9wIUkKlNIvYGqoJkdl0OQOkxZBoKIFKqqvYDgmpmNi9yyCeyUPfewIx+88hmXNYugH2LHzv3Lq+HXxKpielWw4fvGtCHqhMG527SSoaoCqBZhGj8bMWXbtv4OH7v95NDOgvbrEpS84yCWv3oc8EOLUHVzDJTBDAi3oK/aBdZYW5rggZxX7oFleoujJF+T0emyes53TI2SzWAGkMlpWCYj+MTFegkEloPoqRk9Hdw3snoW1YnPmn09x98fu5WnPv4I7v3CY3/39G3nmvi47ohXmwzVqYQ9Dev15C7lOXJhOEY8LGxc+ClPETxeZSC37nmLRUussqXMcVxb5k788x733dVht+7S7Dte//jrMZ1r07B5uzcMzPHzTJ9Jlv7KPtKJCz7fq0vP0mFb8ZTKSPRbPx2EaZd+tdy++9fDFM4XUbp2+0TGOYeOaRmUFq1jAlEjJVQT95nY4aBGooYrqaZiOgdEzsVs17LU6wTcF937oXs4ePk6tsY99l/wBndVrWV3ZjdNrli6nsF1xPgrfNLvYtRYLOx6lNnsbD9z9S3jOGvueeYjLf+By5JUeTrNDr+Hi2j0CPSDQQyI17PveIzXejq+v2DNWWVG5jyvIxfOp8j5C8RePY39RUX4FpJVBYvVrro7h6hg9g9qaTaNTw3xEcOcf30X7VJsnXT/Pr/7nS9ktV9kRrtKIetiRgy79/h61Qygq4PUq8PQZGN8Zuw76UeKOCoWKL3Taao1Vpc4pZY7D3QY/8Z++TCTh6u+8jL2v2Ut73qUz08OxXbyai28EhHqIzBkAg+8dKVGpQh8lF6Os+fXKyTQI9OAiVPg3Cql8eTrrV06YATiuVpxkYY36pZXAwLqK3T26r6M7OlbHwmrZWMt17HOzrHy+xzf/6ksErsfeS19Ls/FjdFu7cHpNXKee26O2svrHQ1GSrRANJ/6ZHerNJazGSZbOvYtTj34Ga7bBU978bKxnCHrzLXpzHZyGg2c7eJaf+F3DgVWmTleAJ1lqKXJhUyioUTI6Sflnz0fJLxGD1mqgojkahqNjdUzsls3sco25NYvDf36Yuz57lB/9yat5zUvr7I5azMsujbCHxWA9nXRNHZEZATMyr5NaAuvFGF6mfQ6REERSiefFCB1HMVlR6iyJOidEg7e/4z4eun+NF/30DWjPqrM806Uz26PbdPBsD8/2iPSBLz7tiIdy+ciGl53n0vgYjLyL1OnWw99SPnyASEyY4TclxjJZpIfxFtbYgpZYVmqk4oYuqq3i2A56o0ut1qPb6FJrNHne027iob86zKO3foTT6j+w99LXsmPPG+is7abTnqfXbeL75oTx98PhF7uvv3z46XBYGk/TfQzdod5YoTFzDrt5nOWVP+Xhb3wCiLji5Tew5/t24+5c49xii16zi9t08CyPwAjiwqxERCJvtU1beKWQfcUjsy6OSe6KscpqhNEi8rIJoyuBUfdyv1CgGiquqeLqLq7uEggPX7G54o0HQEb86X+/D9O8klc9rxbnUYVICgzpY6S7XJGO0x90jKbpzeV1PS6fURg3SigTZbDJuUqgaPiKRk+YtIXFkrA5GZn8+m89wOF7Vrjp/76B6EkaZ+aXWZvt0ZtxcBouoRkSmMHAoldGV/BTuWjkCP0zpVxsqLU0Jbacwp/KDzitr3Baxsn8BxRSlPYJDFUAEkIZokRK7BdWQ3zDJ1ADTNPFN10s22H/W/dw6Xdfyf0f/CZH7/4AQnyI3QdezP5Db6HbuoROewGn20y2NRxsVp7PSD8VU2ToYkK5khdComk+uu5i2R3s2ir15jJm/SFOHv9jHie64u8AACAASURBVHzgSwgBe595FYdedwX+7jZrC6fpzXdwZnp4totnlyj7KTpZBykrKOQi66epn4sFPHssY8Uo5ZZUOFKJj8Xx2yMrAAlCEYRKiKqoRCR8iCSSECFDrnzTAcIg4N3/9QFOnryEN71mEVdozEqdmvSwhIcuAzQZosoQNXWeZFaV7RtRoxQdIJURLRpked4TPsm4BkzKabpKbuq+UfqbmntCo6eYtLBYFSYP9wx+9Zfv49GHu7zk559EeL3C0kyb1dku3VkXt+7h1TxCIyTSIqS6PnfdSKPyMZSL/v0pseVcOnylEHgBa7tJGGVlZa+HLKlARfM0dEfH6JpYbQuzVaO23MBabqKervHIRx/k6O13I8OI+Z3PYPe+n8F3rqbbmsdxGniJ4o8iNTdCJX8cpOVisfZHbWWYKvjBzGMfVQ2w7DZ2bY1a8xya+S2OHXk3y2fuQtV1Ln3+dRz43kvwdrbpzbZw5juxVV9z8Wtx51uoh0mnW6Lo03kcUzS5H+tdkJKXrkvW+/JZ8txQBRAlY/m9xL3T1bHXLJorFnPLNjvaFo984Djf+tQprn5yk19+x+UcsAOaeNQjDwsPgwC9oPSVKBp8xwzPyiZwjVseWETDrZ38MtOZ/bWSFWpDoeInyt4VOo7QaWGygsmt97n87q/fh+9LXvwL1xA+WefcbI/WnEN73sGte/i2T2AFsbLXJrvscml7LOVjGrlQuDh9+EMK/0KjzHju+ymnK33FUT+KHw/t1FwNwzEwnFjxWy0bq13DWm5iLDc48YkTPPSZb+J1uzTmLmfvgZ9CyGfRa8/j9Jr4vkXgG4ShllP++UlaF89krexm5cWlE2IfvY+uexhmB9NuUZ85Ryi+wLGH/oT2yqNYMw0u+3fXs+M7F3DnO7gzHXqzHZxaD7fu4tsevuHjW37cPFflkLKfFrlyMU0zfCqiJbTW0QodUurrTIwIY9lUAgW9q2P0NOxVi/qqyeyqzY6WTe9Lbb7wngdRVcGP/vhl3PTts8ziUcfHIsDCR48CNAZLMfRH7yeWft/iH2e9Tkp63zsyUPKprz5EJRQKgVRxFQ0Xja4waKFzxlN597uPcOvNZ5jfZ/Oct11JZ59kecZhdb5Lr+nhzLixsjdDQiOMW03TdqH10yW3llw84RX+NM2cx0gPpgUvq/iJ6Fv7WqBh9Ax0z8DqWJhtC7tVw1xpYKw0WL2lw/3/cAedc0uYtR3sOfAD2Par8XpzuN1ZPM/C9y3CxN0TVwBKyWJrW0v5Fy36dCG0dP0gRQlRNR9N9dGNHobZxbTXsOrnWGv/DaeO/C1ub4Xm7h1c9ZqnUn+WgTfbwZlNrPl6D9d28axY0QdGQKiFhFo4WN6gaM3L9Sn+ixqZMtCX0XBg6auuitHRsVctaq1Y6c+1TZpnVO7404c5cucKc4smP/imQ7zo+bM0RIhNgEmIQYAmIzRCFJLlm0W65236Tjmclmncs6SKvtApSzKBSij4qHioOGh00TjrwF+87yif+/QpAJ72vfvZ/d2LrDQ8VmYcWjM9urMuXs3HayRuHD2eGYvyBJCLJ7zC36LIWl39IZ1hPK5f8zV0X8dwDUzXxGxbWO14VI9xroF3D9z/V3ex/PBRVNVkx56XMzf3Znx3D67TxHNrGcWvJcpfLUxMyrt/JqZ3AyMIpqFdpuyzil7TfTTV6yt6q7aKZh3j3Nk/5eyJzyBDn8WrLuGK11+DelWIt9ChN5co+ZqLa7l4poev+/HIm8R10x8PzePkltniEAiIZDyZ0FfQHA29p2O2dew1k0bbYnbNZq5rojwScMdfHOH4vasYpsr1T5vnO1++m6ff0KCmSgxCNCSajFATS38wVzfv219PJ2V2I8dIJmvSIwiEQoCCLxVcobLSifjUJ8/whZvP8uiDLTRD4dqX7OGy793D2qzPWt1lbcah23Rwmh5u3SOwAkJz4LNPl1+/6PGEUfhp8jbSfJrSmtgQrREo8/unQzrj6fEKWpBY/Ym7x+yaWGs25pqNcbaBPGrz0Efu4/Q3DiOjiLmdN7Jzz1v///bOPUaS477vn9+8eh67e3t7d7w73kM8kRQpilZi8swYia1YkByTgiI6TiwxCWwKNkALkYDIhgFJJhAICQTLMWLE8SMyEwmxFUWSA1vWQX5RVhLJcUSRFM03RfJInnjHe+7tPXZ33jOVP7p7pqenu6fntdN78/sAg5mprq76zberf/Xr6ppqTPMW6pUlatUFmo089UaeZiNLq5Vx/tAlnnH+eNeo03P43eGbdNqeUpnJNMhk6mRzNXK5Mllrg3zpMm15gfNnHuLyhadJpdPsu+MmDn/gBjhQob5SprqjQm3BdvR1q07dqndukreyrcA/Q0GEw59Buxi5vDjlD3GOdNqnz+lnqhmszRzWZpbihu34F8sWC7UchavC8a+d5cRjq1xdrQJQWsqy+7o8Bw6WOHi4wPUHi+zbZ7FzZ5ZCMU0qZT9IfOCjfv0/pTNkAs2m4cqVBqurDc6eqXHq9TKnT5U5+0aZtYs16tUWmVyK3YcWuPWe/SwfXWLDarKer7GxUKNcqlFZrFEt1WgUmjQLzZ4btK5xobOutlO72LYO/1H6hdrqG7dB9Y2RZj/lqPtKt9Kk2o7jb9lRf7aexSpbWJcLWJcK5FZLpE4vcuZPT3Pqb56l3WyysHwr113/IVLmjo7jd6N++5mvGd/0zsFDPJN2+OKZVutG9JlMg0y27syfL2Plr2IVr9BoP8q5Nz7LxuVXSOeyHHrnbex97x5a+zap79mktlS1X4WaPTafaXQcvRvN94zRT5sJt4up1zkAMd1x/XTdvueU7Tj+HIVyjkIlR7Gao1jLUmhkserC+stlTj+xxsXvb7CxWqW62aTpruIYWeGA3xm2m9gLwuXyGQpLWXbsLbDnLUscuGsF2Z2lkmlSzjUo5+uUC3UqhTrVUp1asU4j36RRaNByx+vT9ho3U3XG46aNUue2dfizGNKZcocSFvW7jj/dSpNpZkg301gVyx7y2chjXSqQvVAidWqR1b9Y5eQ3n6HdaFJcvJF9Bz+CtO+kVl6mVl2gVi3RaFgdxx830p+Ww3eXfs5m6+Q6wzZXsQqXacojnHn9M1TWT5K2shz68bex++5lGgc2aLiOvljrOPpWptXn6GNH8+MwwxliW4H9FCWDtOz/laTr6R7Hn61lsMo5crUMVtX5t24jTa6RIddKk22lyLRSpI2QNkLKCNKGVr1Nq9Ki1WzTbraRNjhPWwxub67GKUHEeb5APk3asp8r0AZa0qaVMrRShkaqTSPdop5pUc+1qOca1Kwm9XyDWr5Bw2pSLzRoWnZE70b17Yz7R7sxhUtiu7jmHH7QJQ2MJ3xUjxtUvv9u+jD1e8p151B7h3tcx59upck2s2QaGfJX82TXc1gXi1irC6TeWOLiX6xy8lu24y8t38L+A7+Iad5OtbxMrbJAtVbqrNnjri4Z5fSHdfhhzt4/hJPJNLCsClZ+k3zhKlbpEmSe5I3v/xblK6+RzmU5+O63sXL3DpoH1qmv2MM3tR3O2Lxl/5+hlW71/Du2Z5405ppqF2NHfyNqIYbO8uHuME+67kw4cDqATMPz7q4l1equNptylnUQ0528MOqCXz1/gHPe287qk+20oZlu0cq0aWZa9kJ4uSbNXMt5Ne3ZN1lnuC9rO3r7vxcycLpltGEkt11ccw7fJe60pbj5/PmH3TZKvgAE6VnALd1Kk21kybQy5Go5e4z/fAHr7CKpk0tc/NOLnPrrZzDNFjv3/hi7Vn6JWuUg1fIy1coCtXqBRj3nW4lzOss3eIdx0ukW2WydfN6eWlksXSJbOMH5c/+Ry+cfIZVNc/Ddt7Py3iUah65Su26T2t4KtXz4sE2sIZtrtF2MxIhaiLE/uwsFplpCqpF2ll9OkWqmSbWEdCPtrNVj//ckZVLdx1W4zr4dUHGUs/V1Du6yBojdsRtn1lV3tUpjr2jqLlmdtTsBN5I3aY+jT8ngWTjbvV1cEw4/7g2rKOEh+ECG9biDDnyc+gaViy+fcS6vJTjqd9fqyW1Y5K/kyV8pYp1ZInViidN/cpKz330BkQwHjvwCVvafUd3cTaW8g2plwRnmcW/oTs/hixiyuTpWrkK+sEFxYQ2rdIHNyhc5/ep/x9Dm+r//Vvb+1F6ah9apXbdBdblMfbFGdalKK9PqzrgJi+b9WkZxjbSLwH3i1juMbU7bs+s1nYhf3NVim753Z/aZPSzU9eWBjn5Mumva0F3czl3BMu0497Tpvrvr4DhRvf0zzVBabLt2cU04fJjMJfqsGbIn987r9zv+XCNHrpqjcKFI/nwJ68wy5vkir3zhKdZPn6WwcJgDb/p3NKu3sbm+2472a0WazUxnuYZJOX43sneHcAqFDfLFK5QWV0lZT3PylX9LtXyWpcP7OfLBW+HWMtXrr1LdvUl12V7npp6t90X0tmQxInpbrO3LpCK8KWjRnc3jRv7S6QSAns/u92nTcfye9/7PjpOXGG0oqYzSLra1w49qwP4e1d9LhvWaw15mxRmTC4sAwvKFjcf57O1EWs52d5aPe3M328iSK+ewNvMUrxQpnF0kd2YH6/+rxfE/foRWo8H+Qz9DsfjzVDb2sOks2dBo5Jw5+5Nx+KmU/axZK18mn9+gtHiR4tJZLl/5Pc69/idk8nlu/hd3UviHQvXAZSq77HVuqqUqjXyjE9G30i37pwbdhPXq4+o3D+0iygZ/uVG2jqhF6L94PWsbuh3BVtMZ7ukY0TG6Nx9mftpFejs7/CjCnOa442mDmOR4m79c7yEI8MX+iN91/LlGDqtsUbhUIL9WpPDGTjLf38GJz7/M+eePky/u59CRT9Gs/gAb67uplhep1wvODd3R180TaTtj9TVyVpVi6RKlxVXS+Sc48dInqVfW2HvHzRz84CEah65S2X+V6kqZyqL9z9hmptmJ6o2Y4BVSgxw9DHect3O7GKeOKWsR2hnMQIvY93YGpcXZNgxbrcW2j/CjxsVcgnrvcfMH9dhB+cMihzjl+qM043mlPNud/OI+WNpTZmdGTyOLVbfI1/IULhYonlskf2qZ6rczvPD5/0ezUmXvoQ9QKv4rZ0nmFWrVIvV68JPF4pBKtbCsCoXiOsWFNUo7znD58m9x7uTXsBZL3PrAUTI/VKdy+DLllTLV5QpVq9o3fOP+psDZNm4f4GrkdoTz0i4GRYozPEe6Y/0Bv22LtfAuWz3X7SKmw0/c8shu9BBrsSt/1BfnIAbth2e/oG1x0oK2ecsO2haUL+DS0KuFq09nrNu5sdlKt2i1W/ZURqtJvrjE0Zvfyckvv86px7+IlX+Ywzd9kuLCXVQ2dlIpL9mPXezc1I0e5kmlWva8+lwVyypTWrhEYXEV0t/m1Rd/lWZtncPveBvX37ef6qHLbOxZp7xrw360YL5GI2vPvnGXKXZ/YydC8zZqg+3ww6L6BLUL92Z7ZN1hdke0i9DINQFadIbeZnGOBNkYJ2+YPdusXYQR937F2BG+iBwC/gDYh32aPmSM+U0RWQG+DNwAnADeb4y5FFnWUTHy2AD1Aw7Qtln4aFBP3valpQLyexBjz5Loi/YreQprRYrnFymc2knzuTzPf+7blNfW2LHydvYdfJB6+UbKm/bc/VqtSLvdfeqWO5VT7EnVCIZMpo6VL1MoXqVQukSm+D3eOPGrrK+9xMK+Pbz1Q3fArWUq11+hsneT8mKZaqEb1Tczzd7hmyAtvL+/N3oZfHyjtJ0Aw65MORQxbY/dzqesxVSJa3vc3zMlLabaHlyG0MKkzdYM6YjIfmC/MeYJEVkEvgv8JPBBYM0Y82kR+Tiw0xjzsciyjoqRRzuhbGxiTbkK3rH/8mpWeKN7/7vr8Hz2ecf2xUh3jR53bH+9SPFiicKFRazTO7n8zU1eOvYojUqFndfdyd7rP0y7cTO18hINZ0VOdxlmcB8r6ET1+Q1yhXUk+xxnXv89Ll94FmuxxFt++k4W3pGlsu8y1d2blHduUilV7Bk4uXrPH6fsnxTQ3gy9v7/7A7uvcY7RBNrFlpzgA+i7kT0jLRLFjLToi+BnjEltkcPvK1Dkq8BvO68fM8accTqF/2OMuSVyX2+EH3Ywwno9QvL3ZAtxNlH7+cueZqTk1uW/h2noj3I9l6OuM/L+WzdXz5Fr5Miv5ylcKVJYXaBwYZHc+WXOfWOV177xt9TLm1iFFXbsupOdK3eTzb4V087Rdv6hm0o3SaVr1BtPsbb6MFcuPkm9egVrcZE3v+fvsOudS9Suu0Jl9zqV3Zv2TdlijVque2M2dPVKb6cW1ATDLpen0C76q5ZktQtvnZ46QiP+CWoRWl5U2TPQYt7bxZZF+D2FidwAfAu4HXjdGLPs2XbJGLMzcv+oIZ2wca2ovP5LYr9nCcoX1hiCDqT/e1gkFHbjJaqRumPYYYfHE/36n83rn8mTq+UobBbIXylQWCthrZXIri1SfaHF619/mUuvnaZeKQNCOmORyuQAaDdrtJp1wJArlVi5cT+H77mR7C1QX9mgumuD6q4yFWfJ4nq23hmrb6VbPWP19s8yvY7eO04fNCYa56SZQLvw01kSIGntwrcttD0H2RlUzqj5EqhFqN1Bdobl3cbtIm6EP7GbtiKyAPwR8FFjzFX/Mzcj9nsAeACAw1EZA9KiDnhAet9luTdacpWPMtsfYQfZ4XfSfhvDPvvrGWKqvOtIxVkrxH9Dty1tWqkWjUyDeqFGvlTB2rFJdleRm95+I+nN22Ejw/pLV1l/4zL19TIA1o4iC4eXWbppifZCjeZimcbSOutLFWo7KlQXq9RKVXvtm1yjP6p3tOho6+/EvL/R6+Dj6hS2bch20d0UcEIPa8M024Vvm70AsQncFlpPSFlx6ou134y0iLVtgv5iaBumrUVMJhLhi0gW+Brwl8aY33DSXmScIZ0ZEuuO9ziXaqOMHQZ9Ft97z6bgRdmyjSzZSpZsNYe1aZEpZ8mWLTLVLOlallQzhftnGpNu22uUWA2a+Yb9rNhijXqpTr1gL3Dmrn3TmYETtfaN8b3H+B1byUTG6beyXRCzrc6KLdZikkz8ns2UtdiyCF/sUP6zwAuus3c4BtwPfNp5/+q4dSWKsB572H29+4eV4+/lY57j3jVpXGfcTDepZ+pkrTq1YpVsNessi5uxF8pqpTqXriZlaGeclQetFk2rYUfy2SatbHfJ4p71b+IYF+XgB2mRdLayXSQd1aJLQrSYxCydHwH+GniG7u3GXwG+A/wh9kDN68BPG2PWIssaJsKf4oE3YQ9hnmglEywzoizvw1f8q3GmW2l7HfRGuvM0LmlLr8NP2x2Fu9RsK2U796CHkNimjNCetkiLQQyM6vztIQHtIlLvaTrHBGoxybKGivAToMWWRfjGmP8bYcq7xi0/lGn28v4IdFBdoxzgSdo/yE95Vp5sp9qIEVrpVrcTyKV6nsgVtK/Xsfvfe3cY4bdtoRYTKfsaaRcTKVu12FZaJO6fttuSqIMRdzbElDCYTrTiOm8x0nl3O4AgZ+/u4923J5oPWuwswVpsOapFF9Wiywy1SK7D36qxOl89geu6jMMkyhnTnr7Lfuk6a//TibxOv8ehRzn5uCRAi7HqSVi72LJ/mG8DLSbdLryB0sB6kqZFBNN5IsYkCLo5aQLSvNuIsT0uYTNjwj7HKWdQvrC8U9SiZ8hG+sfm22K/Og8juYa1iMWctItYqBbB+WetRQTJjfCh09vFGi7w7ROYHtQTD5oV4/8+7PjcMDdxovLEsTtmeT0rDAbk7xmXv8a18NrkvWIJ/B/JjLUIvKKakhYD889Buwi8ghL3TfrSAr/PSosQkhvhQ7cXC+qNR+mB4wo0Qs/ZIehyL6qOoKgkLL9q0U1XLbrpqkU3XbWIJHERfuQ/B729n78nHHRwhukNw3pZb5p/+7D5g+wflD/MRtVi4lqERtOesjtR3gS16Lv6SoAWoXnnsF10zfb5qVlrEZPEOfweBl1e+sWJEtH49gmry9tA/AxqXMPkH1RGVGOIyq9abJkWgUONc6pFLFtVi/Dvg/LHLWMAyRzSiSO2l6he27stSqC4Pf8goi6xTMT2QemqhWoRlK5aqBZDkEyH7+2J4zKiABMnKGKI2h6Edx/Voj+/aqFaqBbh+0SQTIc/qMcet1edJIPEjtsYJSSPatFfvmqhWgSVr1oMJJkOf5QDNKindNPiiBQ3X1C9UfkG5Q26TFQthi8/qBwX1aKLatHlWtFiAMlz+IOEGzTm5RI2PhdHnLj5BtkwzLag7arF6PnDtqkWXVSLLteCFjFInsMf8VJlbIzvfdj93M9xL8mCtru/3fi+bzWqRRfVootq0SWJWsQgeQ4f4t0dH3Zb3DqHLSPs0jLoQHrTosYbvY1YtVAt3DyqRTePatHNs62HdGD0yxzje41S5yhjdlH1+XvhqIPn32+QPapFb72DbFQtVIsgG68FLWKSTIcf9AP9vXnYJY73FVZG0PdBPbb/APh730GRhLf8uI0kzB7VInybaqFaBG271rWISTIdfhB+gUbp9eKWEXSggw6wN32YKGOY6CXONtViuPJGLUO16KJadEmCFjFJnsMPEiKqpx02LU6dcQ+0BHz2X+qNYtcw+6oW0WWpFsOnRdXtolp0SYoWMUjeWjp+sYLGsIIEjZsWp85x8Pfs40QWqoVqEVWGi2rRZZ61iEHyInw/kxQ3CON5edPGLdP/OWj8b9C+flSLePtNAtWit27Volv3dtEigOQ7/DAmdZkjnpc3bRyCyppm9KBadFEtuqgWXVQLIIFDOoHPkQzOON72awnVootq0UW16HKNaxH3+dKJc/h9uL/Dc5MjdqeQULwPCldGo+cxjLMsN2jMeCwDfOXFKd93jkyqfW3XdjqNtrEt20UAyXL4BtKt9MSKm0WDHbbOcWzcDifkJE++Ycoatt5pdSCzIm7bGJQvTjlb1Q7jHKNBeUY5ztuhbTRpxso3dYcvIncDvwmkgf9qjPl0WN6USZGr50ava4sd4CROqiSdULNi2ifyJMrfLozqwIPSh8kbt/5hGeW4h+0zbhsZJ/+0SYTDF5E08DvAjwOngMdE5Jgx5vmg/Kl2itJGKZEOrt+mgAM+5skU7wTrrzeJerlEnxgSmWeY9MC8PWnRdQ3aNk7ecRg3qLDTfbb68nr39ZfT/91XwQidQlxCNfal+6vy7zfoe1CZTuLIx3mrO4Qy5Vj5ph3h3wUcN8a8CiAiXwLuBYIdfivFwpXSRA2YRMOLLCPQcfu+Iz3nnP87CBgzRH7PLY2gths2uDfpNhhaTXBF0v8zOmX4HwrdfV6s5+aNf1vQd3yHJGbnYAI6h7C8syTQgTPYUdPj1D35PG2rZ5+AtO5n4ysvLHgZR7t+Z9t3LKQ7kO3d5n424jlPIsrqM3+EK4Rx8k6CC1yIlW/aDv8AcNLz/RTw90KNqWfYc3Jlyib1MvyQiudABp5kpm8fMZ77aiEnXo8P6zuZouoMsjfgR3gZtxOMNUQSIy3kpDO9Hikyj3jSu/v5nIUn3V++97OMeMURaGwsosuLDjTC8/a0mYD2FuXYOz8xMt0OUHoCkSC54/4Wt4jAjthbSPe97wHybpqI8967T6eNdLaZTjDhzW886WE/Js7ps9UO/zVOxMo3bYcfJE1vbCvyAPAAQH53jsXV/MQrDK3c3Sf0CPY7b/t7bw5v5BPt6E3P/uEnnvdkDe5Auvv1dghBkdW0h3yCG7c/QpMYDr6bJ+hE73fo9rsQVF53W3B9vc49KF+gfSHEnRbnJ3zGmf+Y+vYLDCKC219gIGK6eXrfpW9bT9sMcfSd/RGM92p1BFm8P1dcB24X3ulvut+DnbzxbBfptsVucOCpsK99+Wzw56c/f09BA/PNjmk7/FPAIc/3g8BpbwZjzEPAQwBHjx41f/X+v5mySYqiKNcW8oF4Qd20/2n7GHCziBwRkRxwH3BsynUqiqIoAUw1wjfGNEXkI8BfYk/L/Jwx5rlp1qkoiqIEM/V5+MaYPwP+bNr1KIqiKNFs38XTFEVRlKFQh68oijInqMNXFEWZE9ThK4qizAnq8BVFUeYEdfiKoihzgjp8RVGUOUEdvqIoypygDl9RFGVOUIevKIoyJ6jDVxRFmRPU4SuKoswJ6vAVRVHmBHX4iqIoc4I6fEVRlDlBHb6iKMqcoA5fURRlTlCHryiKMieow1cURZkT1OEriqLMCerwFUVR5gR1+IqiKHOCOnxFUZQ5QR2+oijKnKAOX1EUZU4Yy+GLyK+LyPdE5GkR+YqILHu2fUJEjovIiyLyE+ObqiiKoozDuBH+14HbjTFvB14CPgEgIrcB9wFvA+4GfldE0mPWpSiKoozBWA7fGPOwMabpfH0EOOh8vhf4kjGmZox5DTgO3DVOXYqiKMp4THIM/+eAP3c+HwBOeradctL6EJEHRORxEXn8woULEzRHURRF8ZIZlEFE/grYF7DpQWPMV508DwJN4AvubgH5TVD5xpiHgIcAjh49GphHURRFGZ+BDt8Y8+6o7SJyP/Be4F3GGNdhnwIOebIdBE6PaqSiKIoyPuPO0rkb+BjwPmNM2bPpGHCfiFgicgS4GXh0nLoURVGU8RgY4Q/gtwEL+LqIADxijPmQMeY5EflD4HnsoZ4PG2NaY9alKIqijMFYDt8Yc1PEtk8BnxqnfEVRFGVy6D9tFUVR5gR1+IqiKHOCOnxFUZQ5QR2+oijKnKAOX1EUZU5Qh68oijInqMNXFEWZE9ThK4qizAnSXf5m9ojIBWATWJ21LTHYjdo5SbaDndvBRlA7J812sPNNxpg9gzIlyuEDiMjjxpijs7ZjEGrnZNkOdm4HG0HtnDTbxc446JCOoijKnKAOX1EUZU5IosN/aNYGxETtnCzbwc7tYCOonZNmu9g5kMSN4SuKoijTIYkRvqIoijIFEuXwReRuEXlRGqpyMQAABDdJREFURI6LyMdnbQ+AiBwSkf8tIi+IyHMi8q+d9E+KyBsi8qTzek8CbD0hIs849jzupK2IyNdF5GXnfeeMbbzFo9mTInJVRD6aBD1F5HMicl5EnvWkBeonNv/JaatPi8gdM7bz10Xke44tXxGRZSf9BhGpeHT9zIztDD3OIvIJR88XReQnZmznlz02nhCRJ530mek5EYwxiXgBaeAV4M1ADngKuC0Bdu0H7nA+LwIvAbcBnwR+edb2+Ww9Aez2pf174OPO548DvzZrO33H/CzwpiToCbwDuAN4dpB+wHuAPwcE+GHgOzO28x8BGefzr3nsvMGbLwF6Bh5n55x6CvsJekccX5CelZ2+7f8B+Dez1nMSryRF+HcBx40xrxpj6sCXgHtnbBPGmDPGmCecz+vAC8CB2Vo1FPcCv+98/n3gJ2doi593Aa8YY74/a0MAjDHfAtZ8yWH63Qv8gbF5BFgWkf2zstMY87Axpul8fQQ4uBW2RBGiZxj3Al8yxtSMMa8Bx7F9wtSJslPsZ7e+H/jiVtgybZLk8A8AJz3fT5EwxyoiNwA/CHzHSfqIcwn9uVkPlTgY4GER+a6IPOCk7TXGnAG78wKum5l1/dxH74mUND0hXL8kt9efw776cDkiIn8rIt8UkR+dlVEego5zUvX8UeCcMeZlT1rS9IxNkhy+BKQlZgqRiCwAfwR81BhzFfjPwI3A3wXOYF/2zZp/YIy5A7gH+LCIvGPWBoUhIjngfcD/dJKSqGcUiWyvIvIg0AS+4CSdAQ4bY34Q+CXgf4jI0qzsI/w4J1JP4J/TG5QkTc+hSJLDPwUc8nw/CJyekS09iEgW29l/wRjzxwDGmHPGmJYxpg38F7bo8jMKY8xp5/088BVsm865Qw3O+/nZWdjDPcATxphzkEw9HcL0S1x7FZH7gfcC/9I4A87OEMlF5/N3scfG3zIrGyOOcxL1zAA/BXzZTUuansOSJIf/GHCziBxxor/7gGMztskdw/ss8IIx5jc86d7x2n8CPOvfdysRkZKILLqfsW/iPYut4f1OtvuBr87Gwj56Iqek6ekhTL9jwM86s3V+GLjiDv3MAhG5G/gY8D5jTNmTvkdE0s7nNwM3A6/OxsrI43wMuE9ELBE5gm3no1ttn493A98zxpxyE5Km59DM+q6x94U98+El7F7zwVnb49j0I9iXlk8DTzqv9wCfB55x0o8B+2ds55uxZzk8BTzn6gfsAr4BvOy8ryRA0yJwEdjhSZu5ntgd0BmggR1x/nyYfthDEL/jtNVngKMztvM49hi420Y/4+T9p057eAp4AvjHM7Yz9DgDDzp6vgjcM0s7nfT/BnzIl3dmek7ipf+0VRRFmROSNKSjKIqiTBF1+IqiKHOCOnxFUZQ5QR2+oijKnKAOX1EUZU5Qh68oijInqMNXFEWZE9ThK4qizAn/H96JozhMyQPSAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.phase_plot_for_step(sc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(16, 8))\n",
+    "phi = sc.concentration[:, :].copy()\n",
+    "plot_contour_lines(phi, alpha=0.5)\n",
+    "tps = get_triple_points(phi, phase_indices=[0,1,2], contour_line_eps=0.01, threshold=2.5)\n",
+    "plot_triple_points(tps, line_length=20)\n",
+    "\n",
+    "assert len(tps) == 2\n",
+    "for tp in tps:\n",
+    "    np.testing.assert_allclose(sum(tp.angles), 360.0)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_n_phase_boyer_analytical.ipynb b/lbmpy_tests/phasefield/test_n_phase_boyer_analytical.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..ce532291c7393c4d25aa336d07729a5130d86716
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_n_phase_boyer_analytical.ipynb
@@ -0,0 +1,437 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.n_phase_boyer import *\n",
+    "from lbmpy.phasefield.analytical import *\n",
+    "from itertools import permutations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# A) Homogenous surface tensions case (3.1)\n",
+    "\n",
+    "Equation numbers refer to paper *\"Hierarchy of consistent n-component Cahn-Hilliard systems\"* by Franck Boyer, Sebastian Minjeaud\n",
+    "\n",
+    "\n",
+    "## 1) Testing properties of $\\bar{\\alpha}$\n",
+    "\n",
+    "testing if equation (3.1) is indeed fulfilled"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for n in [2, 3, 4, 5, 9]:  # test for various number of phases\n",
+    "    σ_sym = sp.symbols(\"sigma\")\n",
+    "    σ = sp.ImmutableDenseMatrix(n, n, lambda i, j: σ_sym if i != j else 0)\n",
+    "    α_bar, _ = diffusion_coefficients(σ)\n",
+    "    for i in range(n):\n",
+    "        for j in range(n):\n",
+    "            if i != j:\n",
+    "                assert α_bar[i, j] == 1 / (n * σ_sym)\n",
+    "            else:\n",
+    "                assert α_bar[i, j] == -(n-1) / (n * σ_sym)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2) Testing properties of $\\Psi_k^{[n]}$\n",
+    "\n",
+    "Proposition (3.1) in the paper"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for n in [2, 3, 7]:\n",
+    "    c = sp.symbols(\"c_:{n}\".format(n=n-1))\n",
+    "    f = lambda c: c**2 * (1-c)**2\n",
+    "    for k in range(1, n):\n",
+    "        assert sp.expand( psi(k, c + (0,), f) - psi(k, c, f) ) == 0  # Proposition 3.1 (i)\n",
+    "    assert psi(n, c + (0,), f) == 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3) Assemble free energy and check necessary properties"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "n = 5\n",
+    "c = sp.symbols(\"c_:{n}\".format(n=n))\n",
+    "f = lambda c: c**2 * (1-c)**2\n",
+    "\n",
+    "sigma = sp.symbols(\"sigma\")\n",
+    "\n",
+    "f_bulk = capital_f_bulk_equal_surface_tension(c, f, sigma, 1)\n",
+    "\n",
+    "σ_mag = sp.ImmutableDenseMatrix(n, n, lambda i, j: sigma if i != j else 0)\n",
+    "lb = l_bar(f_bulk, diffusion_coefficients(σ_mag)[0], c)\n",
+    "\n",
+    "for i, lb_i in enumerate(lb):\n",
+    "    if i != n-1:\n",
+    "        term = lb_i.subs(c[-1], 1 - sum(c[:-1])).subs(c[i], 0) \n",
+    "    else:\n",
+    "        term = lb_i.subs(c[-1], 0).subs(c[-2], 1 - sum(c[:-2]))\n",
+    "    assert sp.expand(term) == 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Testing Proposition 3.3\n",
+    "\n",
+    "first line of Proposition 3.3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for n in [2, 3, 4, 5, 6, 10]:\n",
+    "    f = lambda c: c**2 * (1-c)**2\n",
+    "    c = sp.symbols(\"c_:{n}\".format(n=n-1))\n",
+    "    c = c + (1 - sum(c),)\n",
+    "\n",
+    "    result = psi(1, c, f) + psi(2, c, f)\n",
+    "    if n in (2, 3):\n",
+    "        assert result == 0\n",
+    "    else:\n",
+    "        expected = 24 * sum(c[i[0]] * c[i[1]] * c[i[2]] * c[i[3]] \n",
+    "                            for i in capital_i(4, n))\n",
+    "        assert sp.expand(result - expected) == 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "last line"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Testing n = 2:  ok\n",
+      "Testing n = 3:  ok\n",
+      "Testing n = 4:  ok\n",
+      "Testing n = 5:  ok\n",
+      "Testing n = 6:  ok\n"
+     ]
+    }
+   ],
+   "source": [
+    "def compare_f_bulk(n):\n",
+    "    sigma = sp.symbols(\"sigma\")\n",
+    "    f = lambda c: c**2 * (1-c)**2\n",
+    "    c = sp.symbols(\"c_:{n}\".format(n=n-1))\n",
+    "    c = c + (1 - sum(c),)\n",
+    "    own = capital_f_bulk_equal_surface_tension(c, f, sigma, 1)\n",
+    "    if n == 2:\n",
+    "        ref = sigma * f(c[0])\n",
+    "    if n == 3:\n",
+    "        ref = sigma / 2 * ( f(c[0]) + f(c[1]) + f(c[2]) )\n",
+    "    else:\n",
+    "        ref = ( sigma / 2 * sum(f(c_k) for c_k in c) + \n",
+    "                2 * sigma * sum(c[i[0]] * c[i[1]] * c[i[2]] * c[i[3]] for i in capital_i(4, n) ) )\n",
+    "    \n",
+    "    assert sp.expand(ref - own) == 0\n",
+    "\n",
+    "for n in range(2, 7):\n",
+    "    print(\"Testing n =\", n, end=':')\n",
+    "    compare_f_bulk(n)\n",
+    "    print(\"  ok\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# B) Arbitrary surface tension case (3.2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def numeric_surface_tensions(n):\n",
+    "    \"\"\"Some numeric values for surface tensions - symbolic values take too long\"\"\"\n",
+    "    return sp.ImmutableDenseMatrix(n, n, lambda i, j: 0 if i == j else (i+1) * (j+1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Checking consistency with 2-phase system\n",
+    "\n",
+    "Makes sure (C2) and (C3) are satisfied if $|I|=n-2$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "n = 3\n",
+      "  Testing 0 1 : OK\n",
+      "  Testing 0 2 : OK\n",
+      "  Testing 1 2 : OK\n",
+      "n = 4\n",
+      "  Testing 0 1 : OK\n",
+      "  Testing 0 2 : OK\n",
+      "  Testing 0 3 : OK\n",
+      "  Testing 1 2 : OK\n",
+      "  Testing 1 3 : OK\n",
+      "  Testing 2 3 : OK\n",
+      "n = 5\n",
+      "  Testing 0 4 : OK\n",
+      "  Testing 1 3 : OK\n",
+      "  Testing 1 4 : OK\n",
+      "n = 8\n",
+      "  Testing 0 7 : OK\n",
+      "  Testing 1 3 : OK\n",
+      "  Testing 1 4 : OK\n"
+     ]
+    }
+   ],
+   "source": [
+    "for n in [3, 4, 5, 8]:\n",
+    "    print(\"n =\", n)\n",
+    "    c = sp.symbols(f\"c_:{n}\")\n",
+    "    σ = numeric_surface_tensions(n)\n",
+    "    α, γ = diffusion_coefficients(σ)\n",
+    "    f0 = capital_f0(c, σ, lambda c: c**2 * (1-c)**2)\n",
+    "    \n",
+    "    pairs_to_test = combinations(range(n), 2) if n < 5 else [(0, n-1), (1, 3), (1, 4)]\n",
+    "    for i0, j0 in pairs_to_test:\n",
+    "        print(\"  Testing\", i0, j0, end=' : ')\n",
+    "\n",
+    "        substitutions = {c[i]: 0 for i in range(n) if i not in (i0, j0)}\n",
+    "        substitutions[c[j0]] = 1 - c[i0]\n",
+    "        l = sp.expand(l_bar(f0, α, c).subs(substitutions))\n",
+    "        for i in range(n):\n",
+    "            if i not in (i0, j0):\n",
+    "                assert l[i] == 0\n",
+    "        print(\"OK\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Checking consistency with 3-phase system"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "n= 4\n",
+      "  Testing (0, 1, 2) : OK\n",
+      "  Testing (0, 1, 3) : OK\n",
+      "  Testing (0, 2, 3) : OK\n",
+      "  Testing (1, 2, 3) : OK\n",
+      "n= 6\n",
+      "  Testing (0, 4, 5) : OK\n",
+      "  Testing (1, 2, 3) : OK\n",
+      "  Testing (0, 1, 4) : OK\n"
+     ]
+    }
+   ],
+   "source": [
+    "for n in [4, 6]:\n",
+    "    print(\"n=\", n)\n",
+    "    c = sp.symbols(f\"c_:{n}\", real=True)\n",
+    "    σ = numeric_surface_tensions(n)\n",
+    "    α, γ = diffusion_coefficients(σ)\n",
+    "    f0 = capital_f0(c, σ, lambda c: c**2 * (1-c)**2) + correction_g(c, σ)\n",
+    "    \n",
+    "    triples_to_test = combinations(range(n), 3) if n < 5 else [(0, n-2, n-1), (1,2, 3), (0, 1, 4)]\n",
+    "    for ind in triples_to_test:\n",
+    "        print(\"  Testing\", ind, end=' : ')\n",
+    "\n",
+    "        substitutions = {c[i]: 0 for i in range(n) if i not in ind}\n",
+    "        substitutions[c[ind[2]]] = 1 - c[ind[0]] - c[ind[1]]\n",
+    "\n",
+    "        l = l_bar(f0, α, c).subs(substitutions)\n",
+    "        for i in range(n):\n",
+    "            if i not in ind:\n",
+    "                back_substitutions = { 1 - c[ind[0]] - c[ind[1]]: c[ind[2]] }\n",
+    "                for c_i in c:\n",
+    "                    back_substitutions[c_i] = sp.Symbol(c_i.name, positive=True)\n",
+    "                l_i = sp.simplify(l[i]).subs(back_substitutions)\n",
+    "                assert l_i == 0\n",
+    "        print(\"OK\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Check explicit formula for $\\Theta$ in case of $n=4$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def theta4(alpha, ind):\n",
+    "    assert len(ind) == 4\n",
+    "    assert alpha.rows == 4\n",
+    "    k, l = ind[2], ind[3]\n",
+    "    return 2 * alpha[k, l] / alpha[k, k]\n",
+    "\n",
+    "n = 4\n",
+    "c = sp.symbols(f\"c_:{n}\")\n",
+    "σ = numeric_surface_tensions(n)\n",
+    "α, γ = diffusion_coefficients(σ)\n",
+    "\n",
+    "for ind in permutations(range(4)):\n",
+    "    assert capital_theta(α, ind) == theta4(α, ind), \"Check failed for \" + str(ind)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# C) Interface width and surface tension check on binary interface"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.phasefield.n_phase_boyer import free_energy as free_energy_boyer\n",
+    "import pystencils as ps\n",
+    "num_phases = 3\n",
+    "\n",
+    "epsilon = 5\n",
+    "x = sp.symbols(\"x\")\n",
+    "# Interface width is defined differently in this paper: i.e. (usual eps) = (their eps) / 4\n",
+    "c_a = analytic_interface_profile(x, interface_width= epsilon * sp.Rational(1,4))\n",
+    "c = sp.symbols(\"c_:{}\".format(num_phases))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sigma = symbolic_surface_tensions(num_phases)\n",
+    "F = free_energy_boyer(c, epsilon=epsilon, surface_tensions=sigma, stabilization_factor=0)\n",
+    "mu = chemical_potentials_from_free_energy(F, c)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  -> Testing interface between 0 and 1\n",
+      "  -> Testing interface between 0 and 2\n",
+      "  -> Testing interface between 1 and 0\n",
+      "  -> Testing interface between 1 and 2\n",
+      "  -> Testing interface between 2 and 0\n",
+      "  -> Testing interface between 2 and 1\n",
+      "Done\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Check all permutations of phases\n",
+    "for i in range(num_phases):\n",
+    "    for j in range(num_phases):\n",
+    "        if i == j:\n",
+    "            continue\n",
+    "        print(\"  -> Testing interface between\", i, \"and\", j)\n",
+    "        substitutions = {c_i: 0 for c_i in c}\n",
+    "        substitutions[c[i]] = c_a\n",
+    "        substitutions[c[j]] = 1 - c_a\n",
+    "\n",
+    "        for μ_i in mu:\n",
+    "            res = ps.fd.evaluate_diffs(μ_i.subs(substitutions), x).expand()\n",
+    "            assert res == 0, \"Analytic interface profile wrong for phase between %d and %d\" % (i, j)\n",
+    "\n",
+    "        two_phase_free_energy = F.subs(substitutions)\n",
+    "        two_phase_free_energy = sp.simplify(ps.fd.evaluate_diffs(two_phase_free_energy, x))\n",
+    "        result = cosh_integral(two_phase_free_energy, x)\n",
+    "        assert result == sigma[i, j]\n",
+    "print(\"Done\")        "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_n_phase_paper_boyer_lbm.ipynb b/lbmpy_tests/phasefield/test_n_phase_paper_boyer_lbm.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..c3f57e8887dd88221d47cfa1081a522f8a2cb9c2
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_n_phase_paper_boyer_lbm.ipynb
@@ -0,0 +1,363 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.analytical import *\n",
+    "from lbmpy.phasefield.n_phase_boyer import *\n",
+    "from lbmpy.phasefield.kerneleqs import *\n",
+    "\n",
+    "from pystencils.fd.spatial import discretize_spatial\n",
+    "from pystencils.simp import sympy_cse_on_assignment_list\n",
+    "from lbmpy.phasefield.cahn_hilliard_lbm import *\n",
+    "from pystencils.fd.derivation import *\n",
+    "\n",
+    "one = sp.sympify(1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Chemical potential\n",
+    "\n",
+    "Current state:\n",
+    "\n",
+    "- not stable (yet)\n",
+    "- without LB coupling the model is stable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "domain_size = (100, 100)\n",
+    "\n",
+    "n = 4\n",
+    "c = sp.symbols(f\"c_:{n}\")\n",
+    "simple_potential = False\n",
+    "omega_h = 1.3\n",
+    "\n",
+    "if simple_potential:\n",
+    "    f = free_energy_functional_n_phases_penalty_term(c, interface_width=1, kappa=(0.05, 0.05/2, 0.05/4))\n",
+    "else:\n",
+    "    ε = one * 4\n",
+    "    mobility = one * 2 / 1000\n",
+    "    κ = (one,  one/2, one/3, one/4)\n",
+    "    sigma_factor = one / 15\n",
+    "    σ = sp.ImmutableDenseMatrix(n, n, lambda i,j: sigma_factor* (κ[i] + κ[j]) if i != j else 0 )\n",
+    "    \n",
+    "    α, _ = diffusion_coefficients(σ)\n",
+    "    f_b, f_if, mu_b, mu_if = chemical_potential_n_phase_boyer(c, ε, σ, one, \n",
+    "                                                              assume_nonnegative=True, zero_threshold=1e-10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Data Setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh = create_data_handling(domain_size, periodicity=True, default_ghost_layers=2)\n",
+    "p_linearization = symmetric_tensor_linearization(dh.dim)\n",
+    "\n",
+    "c_field = dh.add_array(\"c\", values_per_cell=n)\n",
+    "rho_field = dh.add_array(\"rho\")\n",
+    "mu_field = dh.add_array(\"mu\", values_per_cell=n, latex_name=\"\\\\mu\")\n",
+    "pressure_field = dh.add_array(\"P\", values_per_cell=len(p_linearization))\n",
+    "force_field = dh.add_array(\"F\", values_per_cell=dh.dim)\n",
+    "u_field = dh.add_array(\"u\", values_per_cell=dh.dim)\n",
+    "\n",
+    "# Distribution functions for each order parameter\n",
+    "pdf_field = []\n",
+    "pdf_dst_field = []\n",
+    "for i in range(n):\n",
+    "    pdf_field_local = dh.add_array(\"f%d\" % i, values_per_cell=9) # 9 for D2Q9\n",
+    "    pdf_dst_field_local = dh.add_array(\"f%d_dst\"%i, values_per_cell=9, latex_name=\"f%d_{dst}\" % i)\n",
+    "    pdf_field.append(pdf_field_local)\n",
+    "    pdf_dst_field.append(pdf_dst_field_local)\n",
+    "\n",
+    "# Distribution functions for the hydrodynamics\n",
+    "pdf_hydro_field = dh.add_array(\"fh\", values_per_cell=9)\n",
+    "pdf_hydro_dst_field = dh.add_array(\"fh_dst\", values_per_cell=9, latex_name=\"fh_{dst}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### μ-Kernel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if simple_potential:\n",
+    "    mu_assignments = mu_kernel(f, c, c_field, mu_field, discretization='isotropic')\n",
+    "else:\n",
+    "    mu_subs = {a: b for a, b in zip(c, c_field.center_vector)}\n",
+    "    mu_if_discrete = [discretize_spatial(e.subs(mu_subs), dx=1, stencil='isotropic') for e in mu_if]\n",
+    "    mu_b_discrete = [e.subs(mu_subs) for e in mu_b]\n",
+    "\n",
+    "    mu_assignments = [Assignment(mu_field(i),\n",
+    "                                 mu_if_discrete[i] + mu_b_discrete[i]) for i in range(n)]\n",
+    "\n",
+    "    mu_assignments = sympy_cse_on_assignment_list(mu_assignments)\n",
+    "    \n",
+    "μ_kernel = create_kernel(mu_assignments).compile()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "second_neighbor_stencil = [(i, j) \n",
+    "                           for i in (-2, -1, 0, 1, 2)\n",
+    "                           for j in (-2, -1, 0, 1, 2)\n",
+    "                          ]\n",
+    "x_diff = FiniteDifferenceStencilDerivation((0,), second_neighbor_stencil)\n",
+    "x_diff.set_weight((2, 0), sp.Rational(1, 10))\n",
+    "x_diff.assume_symmetric(0, anti_symmetric=True)\n",
+    "x_diff.assume_symmetric(1)\n",
+    "x_diff_stencil = x_diff.get_stencil(isotropic=True)\n",
+    "\n",
+    "y_diff = FiniteDifferenceStencilDerivation((1,), second_neighbor_stencil)\n",
+    "y_diff.set_weight((0, 2), sp.Rational(1, 10))\n",
+    "y_diff.assume_symmetric(1, anti_symmetric=True)\n",
+    "y_diff.assume_symmetric(0)\n",
+    "y_diff_stencil = y_diff.get_stencil(isotropic=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "μ = mu_field\n",
+    "μ_discretization = {}\n",
+    "\n",
+    "for i in range(n):\n",
+    "    μ_discretization.update({Diff(μ(i), 0): x_diff_stencil.apply(μ(i)),\n",
+    "                             Diff(μ(i), 1): y_diff_stencil.apply(μ(i))})\n",
+    "force_rhs = force_from_phi_and_mu(order_parameters=c_field.center_vector, dim=dh.dim, mu=mu_field.center_vector)\n",
+    "force_rhs = force_rhs.subs(μ_discretization)\n",
+    "force_assignments = [Assignment(force_field(i), force_rhs[i]) for i in range(dh.dim)]\n",
+    "\n",
+    "force_kernel = create_kernel(force_assignments).compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Lattice Boltzmann kernels\n",
+    "\n",
+    "For each order parameter a Cahn-Hilliard LB method computes the time evolution."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if simple_potential:\n",
+    "    mu_alpha = mu_field.center_vector\n",
+    "else:\n",
+    "    mu_alpha = mobility * α * mu_field.center_vector "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Defining the Cahn-Hilliard Collision assignments\n",
+    "ch_kernels = []\n",
+    "\n",
+    "for i in range(n):\n",
+    "    ch_method = cahn_hilliard_lb_method(get_stencil(\"D2Q9\"), mu_alpha[i],\n",
+    "                                        relaxation_rate=1.0, gamma=1.0)\n",
+    "    kernel = create_lb_function(lb_method=ch_method, \n",
+    "                                velocity_input=u_field.center_vector, \n",
+    "                                compressible=True,\n",
+    "                                output={'density': c_field(i)},\n",
+    "                                optimization={\"symbolic_field\":pdf_field[i],\n",
+    "                                              \"symbolic_temporary_field\": pdf_dst_field[i]})\n",
+    "    \n",
+    "    ch_kernels.append(kernel)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hydro_lbm = create_lb_function(relaxation_rate=omega_h, force=force_field, \n",
+    "                               compressible=True,  \n",
+    "                               optimization={\"symbolic_field\": pdf_hydro_field,\n",
+    "                                             \"symbolic_temporary_field\": pdf_hydro_dst_field},\n",
+    "                               output={'velocity': u_field}\n",
+    "                               )\n",
+    "#hydro_lbm.update_rule"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Initialization"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def set_c(slice_obj, values):\n",
+    "    for block in dh.iterate(slice_obj):\n",
+    "        arr = block[c_field.name]\n",
+    "        arr[..., : ] = values\n",
+    "        \n",
+    "def init():\n",
+    "    dh.fill(u_field.name, 0)\n",
+    "    dh.fill(mu_field.name, 0)\n",
+    "    dh.fill(force_field.name, 0)\n",
+    "    \n",
+    "    set_c(make_slice[:, :], [0, 0, 0, 0])\n",
+    "    set_c(make_slice[:, 0.5:], [1, 0, 0, 0])\n",
+    "    set_c(make_slice[:, :0.5], [0, 1, 0, 0])\n",
+    "    set_c(make_slice[0.3:0.7, 0.3:0.7], [0, 0, 1, 0])\n",
+    "    \n",
+    "pdf_sync_fns = dh.synchronization_function([f.name for f in pdf_field])  \n",
+    "hydro_sync_fn=dh.synchronization_function([pdf_hydro_field.name])\n",
+    "c_sync_fn = dh.synchronization_function([c_field.name])\n",
+    "mu_sync_fn = dh.synchronization_function([mu_field.name])\n",
+    "\n",
+    "def time_loop(steps):\n",
+    "    for i in range(steps):\n",
+    "        c_sync_fn()\n",
+    "        dh.run_kernel(μ_kernel)\n",
+    "\n",
+    "        mu_sync_fn()\n",
+    "        dh.run_kernel(force_kernel)\n",
+    "\n",
+    "        hydro_sync_fn()\n",
+    "        dh.run_kernel(hydro_lbm)\n",
+    "        dh.swap(pdf_hydro_field.name, pdf_hydro_dst_field.name)\n",
+    "\n",
+    "        pdf_sync_fns()\n",
+    "        for i in range(n):\n",
+    "            dh.run_kernel(ch_kernels[i])\n",
+    "            dh.swap(pdf_field[i].name,pdf_dst_field[i].name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/local/bauer/miniconda3/envs/pystencils_dev/lib/python3.7/site-packages/matplotlib/contour.py:1243: UserWarning: No contour levels were found within the data range.\n",
+      "  warnings.warn(\"No contour levels were found\"\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "init()\n",
+    "plt.phase_plot(dh.gather_array(c_field.name))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "time_loop(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#plt.scalar_field(dh.cpu_arrays[mu_field.name][..., 0])\n",
+    "plt.scalar_field(dh.cpu_arrays[u_field.name][..., 0])\n",
+    "plt.colorbar();"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_n_phase_penaltyterm_model.ipynb b/lbmpy_tests/phasefield/test_n_phase_penaltyterm_model.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..a3578d55e11468a344e62a640c1021f3a5d0b6db
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_n_phase_penaltyterm_model.ipynb
@@ -0,0 +1,140 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.analytical import *\n",
+    "from lbmpy.phasefield.phasefieldstep import PhaseFieldStep\n",
+    "from lbmpy.phasefield.experiments1D import *\n",
+    "from lbmpy.chapman_enskog.derivative import *\n",
+    "from pystencils.datahandling import SerialDataHandling"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Testing N-phase model with penalty term"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "c = sp.symbols(\"c_:4\")\n",
+    "α = 1\n",
+    "F = free_energy_functional_n_phases_penalty_term(c, kappa=0.05, interface_width=α, penalty_term_factor=0.01)\n",
+    "sc = PhaseFieldStep(F, c, domain_size=(100, 1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Contour lines of bulk free energy:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure()\n",
+    "plot_free_energy_bulk_contours(F, c, phase0=0, phase1=3, levels=np.linspace(0, 0.02, 100))\n",
+    "plt.colorbar();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure()\n",
+    "error = tanh_test(sc, 0, 1, expected_interface_width=α)\n",
+    "assert error < 0.002"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Velocity: 0.01  Time steps for round: 10025\n",
+      "Running 5000 initial time steps\n",
+      "Running round 1/2\n",
+      "Running round 2/2\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "error = galilean_invariance_test(sc, velocity=0.01, phase0=0, phase1=1, expected_interface_width=α, rounds=2)\n",
+    "assert error < 1e-12"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_nestler_model.py b/lbmpy_tests/phasefield/test_nestler_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..078f1a4f9b043d6e2c56be11c55f0de2ea331af3
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_nestler_model.py
@@ -0,0 +1,47 @@
+import sympy as sp
+import numpy as np
+from collections import defaultdict
+from lbmpy.phasefield.nphase_nestler import create_model
+
+
+def get_parameters(num_phases, sigma, alpha=1):
+    res_a = {}
+    res_eps = {}
+    for i in range(num_phases):
+        for j in range(i):
+            res_a[(i, j)] = alpha / (72 * sigma[(j, i)])
+            res_eps[(i, j)] = sp.sqrt(alpha * sigma[(j, i)])
+    return res_a, res_eps
+
+
+def test_main():
+    num_phases = 3
+    alpha = 2
+    sigma = defaultdict(lambda: 0.001)
+    sigma[(1, 0)] = 0.005 / 4
+    sigma[(0, 1)] = 0.005 / 4
+    sigma[(0, 2)] = 0.0083 / 4
+    sigma[(2, 0)] = 0.0083 / 4
+    sigma[(1, 2)] = 0.01 / 4
+    sigma[(2, 1)] = 0.01 / 4
+
+    a_dict, epsilon_dict = get_parameters(num_phases, sigma, alpha)
+    dh, init, run = create_model([50, 50], num_phases, a_dict,
+                                 epsilon_dict, 0.0005, alpha, penalty_factor=0.0,
+                                 simplex_projection=True)
+
+    c_arr = dh.cpu_arrays['c']
+    nx, ny = dh.shape
+
+    c_arr[:, :int(0.5 * nx), 0] = 1
+    c_arr[:, int(0.5 * nx):, 1] = 1
+
+    c_arr[int(0.3 * nx):int(0.7 * nx), int(0.3 * ny):int(0.7 * ny), 0] = 0
+    c_arr[int(0.3 * nx):int(0.7 * nx), int(0.3 * ny):int(0.7 * ny), 1] = 0
+    c_arr[int(0.3 * nx):int(0.7 * nx), int(0.3 * ny):int(0.7 * ny), 2] = 1
+
+    init()
+
+    res = run(100)
+    assert np.isfinite(np.max(res))
+
diff --git a/lbmpy_tests/phasefield/test_neumann_evaluation_circle_fitting.ipynb b/lbmpy_tests/phasefield/test_neumann_evaluation_circle_fitting.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..bf78f7690873d579ce819daf1362747cb5568b02
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_neumann_evaluation_circle_fitting.ipynb
@@ -0,0 +1,153 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.experiments2D import *\n",
+    "from lbmpy.phasefield.post_processing import *\n",
+    "from lbmpy.phasefield.contact_angle_circle_fitting import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Testing Neumann angle evaluation based on circle fitting\n",
+    "\n",
+    "Set up a 3 phase model to have example data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kappa3 = 0.03\n",
+    "alpha = 1\n",
+    "\n",
+    "sc = liquid_lens_setup(domain_size=(150, 60), optimization={'target': 'cpu'}, \n",
+    "                       kappas=(0.01, 0.02, kappa3), \n",
+    "                       cahn_hilliard_relaxation_rates=[np.nan, 1, 3/2], \n",
+    "                       cahn_hilliard_gammas=[1, 1, 1/3],\n",
+    "                       alpha=alpha)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sc.run(10000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.phase_plot_for_step(sc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ 97.07526088311518, \\quad 120.64387551875555, \\quad 142.2808635981293\\right ]$$"
+      ],
+      "text/plain": [
+       "[97.07526088311518, 120.64387551875555, 142.2808635981293]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "angles = liquid_lens_neumann_angles(sc.concentration[:, :, :])\n",
+    "assert sum(angles) == 360\n",
+    "angles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ 89.99999999999999, \\quad 126.86989764584402, \\quad 143.13010235415598\\right ]$$"
+      ],
+      "text/plain": [
+       "[89.99999999999999, 126.86989764584402, 143.13010235415598]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "analytic_angles = analytic_neumann_angles([0.01, 0.02, kappa3])\n",
+    "analytic_angles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for ref, simulated in zip(analytic_angles, angles):\n",
+    "    assert np.abs(ref - simulated) < 8"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_nphase_1D.py b/lbmpy_tests/phasefield/test_nphase_1D.py
new file mode 100644
index 0000000000000000000000000000000000000000..f0722f645138d6195d8337ce8212742cec41e1fe
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_nphase_1D.py
@@ -0,0 +1,113 @@
+import numpy as np
+from functools import partial
+from lbmpy.phasefield.analytical import n_phases_correction_function, analytic_interface_profile, \
+    n_phases_correction_function_sign_switch
+from lbmpy.phasefield.experiments1D import init_sharp_interface
+from lbmpy.phasefield.scenarios import create_n_phase_model
+from pystencils import create_data_handling, make_slice
+from pystencils.runhelper import ParameterStudy
+
+
+def extract_profile(sc, width, phase_idx=1):
+    width //= 2
+    interface_x = sc.data_handling.shape[0] // 4
+    extraction_slice = make_slice[interface_x - width:interface_x + width, 0, phase_idx]
+    return sc.phi_slice(extraction_slice).copy()
+
+
+def analytic_profile(width, alpha):
+    x = np.arange(width) - (width // 2)
+    return np.array([analytic_interface_profile(x_i - 0.5, alpha) for x_i in x], dtype=np.float64)
+
+
+def error(profile1, profile2):
+    return np.sum(np.abs(profile1 - profile2)) / profile1.shape[0]
+
+
+def run_n_phase_1d(num_phases, interface_width=1, correction_factor=0.5,
+                   correction_power=2, surface_tension=0.0025, domain_width=100,
+                   initialization='step', interface_with='last', evaluation_steps=5000, time_steps=50000):
+
+    assert num_phases > 3
+
+    dh = create_data_handling((domain_width, 1), periodicity=True)
+    if correction_power is not None and correction_factor is not None:
+        if correction_power == 'sign_switch':
+            f2 = partial(n_phases_correction_function_sign_switch, beta=correction_factor)
+        else:
+            f2 = partial(n_phases_correction_function, beta=correction_factor, power=correction_power)
+    else:
+        f2 = lambda c: c ** 2 * (1 - c) ** 2
+
+    sc = create_n_phase_model(data_handling=dh, f2=f2, surface_tensions=surface_tension,
+                              num_phases=num_phases, alpha=interface_width)
+
+    if initialization == 'step':
+        if interface_with == 'last':
+            init_sharp_interface(sc, phase_idx=1, inverse=False)
+        elif interface_with == 'two':
+            init_sharp_interface(sc, phase_idx=1, inverse=False)
+            init_sharp_interface(sc, phase_idx=0, inverse=True)
+        else:
+            raise ValueError("Parameter 'interface_with' has to be either 'last' or 'two'")
+    else:
+        raise ValueError("Unsupported value for 'initialization parameter")
+
+    sc.set_pdf_fields_from_macroscopic_values()
+
+    outer_steps = time_steps // evaluation_steps
+    eval_results = []
+    stable = True
+    for os in range(outer_steps):
+        eval_result = {}
+        sc.run(evaluation_steps)
+        phi_slice = sc.phi[:, 0, 1]
+        eval_result['phi_min'], eval_result['phi_max'] = np.min(phi_slice), np.max(phi_slice)
+        if np.isnan(eval_result['phi_max']):
+            stable = False
+            break
+
+        simulated = extract_profile(sc, 50 * interface_width)
+        analytic = analytic_profile(50 * interface_width, interface_width)
+        eval_result['error'] = error(simulated, analytic)
+        eval_result['other_min'], eval_result['other_max'] = np.min(sc.phi[:, 0, 2:]), np.max(sc.phi[:, 0, 2:])
+
+        eval_results.append(eval_result)
+
+    result = {'stable': stable, 'eval_results': eval_results}
+    print("α={interface_width}, p={correction_power}, β={correction_factor}, ".format(**locals()) +
+          "st={surface_tension}, init={initialization}".format(**locals()), end="")
+
+    if stable:
+        result.update(eval_results[-1])
+        result['profile'] = list(extract_profile(sc, 50 * interface_width))
+        print(" -> err={result['error']:.4f}, "
+              "min/max={result['other_min']:.4f}/{result['other_max']:.4f}".format(**locals()))
+    else:
+        print("  -> unstable")
+    return result
+
+
+def study_1d(study):
+    for num_phases in (4, ):
+        for alpha in (1, 2, 8):
+            for st in (0.005, 0.005 / 2, 0.005 / 4, 0.005 / 8, 0.005 / 16):
+                for beta in (0.0001, 0.001, 0.01, 0.1, 1, 10, 100):
+                    for correction_power in (2, 4, 'sign_switch'):
+                        for if_type in ('last', 'two'):
+                            params = {
+                                'num_phases': num_phases,
+                                'interface_width': alpha,
+                                'correction_factor': beta,
+                                'correction_power': correction_power,
+                                'surface_tension': st,
+                                'domain_width': alpha * 100,
+                                'interface_with': if_type,
+                            }
+                            study.add_run(params)
+
+
+if __name__ == '__main__':
+    s = ParameterStudy(run_n_phase_1d)
+    study_1d(s)
+    s.run_from_command_line()
diff --git a/lbmpy_tests/phasefield/test_nphase_2D.py b/lbmpy_tests/phasefield/test_nphase_2D.py
new file mode 100644
index 0000000000000000000000000000000000000000..018feeaf788280151b8f3c5c2a76e7b29a175180
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_nphase_2D.py
@@ -0,0 +1,219 @@
+import numpy as np
+from functools import partial
+from lbmpy.phasefield.analytical import n_phases_correction_function, n_phases_correction_function_sign_switch
+from lbmpy.phasefield.contact_angle_circle_fitting import liquid_lens_neumann_angles
+from lbmpy.phasefield.post_processing import analytic_neumann_angles
+from lbmpy.phasefield.scenarios import create_n_phase_model, create_three_phase_model
+from pystencils import create_data_handling, make_slice
+from pystencils.runhelper import ParameterStudy
+from time import time
+
+from pystencils.utils import boolean_array_bounding_box
+
+color = {'yellow': '\033[93m',
+         'blue': '\033[94m',
+         'green': '\033[92m',
+         'bold': '\033[1m',
+         'cend': '\033[0m',
+         }
+
+
+def random_string(length):
+    import random
+    import string
+    return ''.join(random.SystemRandom().choice(string.ascii_letters + string.digits) for _ in range(length))
+
+
+def run_n_phase_2d(num_phases, interface_width=1, correction_factor=0.5,
+                   correction_power=4, domain_width=100, domain_aspect_ratio=2,
+                   kappas=(0.005, 0.005, 0.005),
+                   initialization='step', interface_with='two', evaluation_steps=10000, time_steps=10000000,
+                   angle_convergence_threshold=0.001, return_scenario=False,
+                   f2=None, **kwargs):
+    start_time = time()
+
+    expected_angles = analytic_neumann_angles(kappas)
+    angle_format = ", ".join(["{:.1f}".format(a) for a in expected_angles])
+    print("{num_phases} phases at {domain_width} domain, {blue}corr: {correction_factor}**{correction_power},"
+          "{green} angles: {expected_angles}:{cend}".format(num_phases=num_phases, domain_width=domain_width,
+                                                            correction_factor=correction_factor,
+                                                            correction_power=correction_power,
+                                                            expected_angles=angle_format,
+                                                            **color)
+          )
+
+    dh = create_data_handling((domain_width, domain_width // domain_aspect_ratio), periodicity=True)
+    if f2 is None:
+        if correction_power is not None and correction_factor is not None:
+            if correction_power == 'sign_switch':
+                f2 = partial(n_phases_correction_function_sign_switch, beta=correction_factor)
+            else:
+                f2 = partial(n_phases_correction_function, beta=correction_factor, power=correction_power)
+        else:
+            f2 = lambda c: c ** 2 * (1 - c) ** 2
+
+    full_kappas = [sum(kappas) / 3] * num_phases
+    if interface_with == 'last':
+        full_kappas[0], full_kappas[1], full_kappas[-1] = kappas
+    else:
+        full_kappas[0], full_kappas[1], full_kappas[2] = kappas
+
+    def surface_tensions(i, j):
+        if i == j:
+            return 0
+        return (full_kappas[i] + full_kappas[j]) / 6 * interface_width
+
+    if num_phases > 3:
+        sc = create_n_phase_model(data_handling=dh, f2=f2, surface_tensions=surface_tensions,
+                                  num_phases=num_phases, alpha=interface_width,
+                                  **kwargs)
+    elif num_phases == 3:
+        sc = create_three_phase_model(data_handling=dh, kappa=full_kappas, alpha=interface_width,
+                                      **kwargs)
+
+    if initialization == 'step':
+        if interface_with == 'last':
+            drop_phase_idx = num_phases - 1
+        elif interface_with == 'two':
+            drop_phase_idx = 2
+        else:
+            raise ValueError("Parameter 'interface_with' has to be either 'last' or 'two'")
+        sc.set_single_concentration(make_slice[:, 0.5:], 0, value=1)
+        sc.set_single_concentration(make_slice[:, :0.5], 1, value=1)
+        sc.set_single_concentration(make_slice[0.3:0.7, 0.3:0.7], drop_phase_idx, value=1)
+    else:
+        raise ValueError("Unsupported value for 'initialization parameter")
+
+    sc.set_pdf_fields_from_macroscopic_values()
+    print("   - {yellow}{time}s{cend} Compiled".format(time=int(time() - start_time), **color))
+
+    if return_scenario:
+        return sc
+
+    outer_steps = time_steps // evaluation_steps
+    eval_results = []
+    last_angles = None
+    stable = True
+    converged = False
+    abort_reason = ''
+    for os in range(outer_steps):
+        sc.run(evaluation_steps)
+        max_phi = sc.data_handling.max(sc.phi_field_name)
+        if np.isnan(max_phi):
+            stable = False
+            print("   {yellow}-unstable{cend}".format(**color))
+            abort_reason = 'nan'
+            break
+        try:
+            angles = liquid_lens_neumann_angles(sc.concentration[:, :, :], drop_phase_idx=drop_phase_idx)
+        except (ValueError, AssertionError):
+            stable = False
+            print("   {yellow}-problem detecting angle{cend}".format(**color))
+            abort_reason = 'angle detection failed'
+            break
+
+        drop_bb = boolean_array_bounding_box(sc.concentration[:, :, drop_phase_idx] > 0.5)
+        domain_too_small = False
+        min_distance = 2
+        for bounds, shape in zip(drop_bb, sc.shape):
+            if bounds[0] < min_distance or bounds[1] > shape - 1 - min_distance:
+                domain_too_small = True
+        if domain_too_small:
+            print("   {yellow}-domain too small - drop touched boundary{cend}".format(**color))
+            abort_reason = 'domain too small'
+            break
+
+        angle_format = ", ".join(["{:.1f}".format(a) for a in angles])
+        print("   - {yellow}{time}s{cend}, {step}: {green}{angles}{cend}".format(time=int(time() - start_time),
+                                                                                 step=sc.time_steps_run,
+                                                                                 angles=angle_format,
+                                                                                 **color))
+        eval_results.append({'theta{}'.format(i): value for i, value in enumerate(angles)})
+        if last_angles is not None:
+            max_diff = max(abs(a - b) for a, b in zip(last_angles, angles))
+            if max_diff < angle_convergence_threshold:
+                converged = True
+                print("   {green}-converged{cend}".format(**color))
+                break
+        last_angles = angles
+
+    result = {'stable': stable, 'converged': converged, 'eval_results': eval_results, 'abort_reason': abort_reason}
+    if stable:
+        data_file_name = random_string(20)
+        result['data_file_name'] = data_file_name
+        print("   - writing result to {}".format(data_file_name))
+        result.update(eval_results[-1])
+        sc.data_handling.save_all(data_file_name)
+
+    return result
+
+
+def study_3phase(study, **kwargs):
+    kappas = [(0.01, 0.02, k3) for k3 in (0.02, 0.01, 0.005, 0.001, 0.0005, 0.0001)]
+    for k in kappas:
+        for d in ['standard', 'isotropic', 'isotropic_hd']:
+            params = {'num_phases': 3,
+                      'domain_width': 300,
+                      'kappas': k,
+                      'discretization': d}
+            params.update(kwargs)
+            study.add_run(params)
+
+
+def study_2d(study, **kwargs):
+    kb = 0.05 / 4
+    kappas = [
+        (kb, kb / 2, kb / 2),
+        (kb, kb / 2, kb / 4),
+        (kb, kb / 2, kb / 8),
+        (kb, kb / 2, kb / 16),
+        (kb, kb / 2, kb / 32),
+        (kb, kb / 2, kb / 64),
+        (kb, kb / 2, kb / 128),
+        (kb, kb / 2, kb / 256),
+    ]
+
+    for domain_width in (100, 260, 500):
+        for num_phases in (4, 5):
+            for interface_with in ['two', 'last']:
+                for d in ['standard', 'isotropic']:
+                    for kappa in kappas:
+                        for triple_point_factor in (np.average(kappa) * 0.8,
+                                                    np.average(kappa) * 1,
+                                                    np.average(kappa) * 1.2,
+                                                    0.5 * np.min(kappa),
+                                                    np.min(kappa),
+                                                    np.max(kappa)):
+                            aspect = 2
+                            if kappa[0] / kappa[2] >= 64:
+                                aspect = 3
+                            if kappa[0] / kappa[2] >= 128:
+                                aspect = 4
+
+                            params = {
+                                'num_phases': num_phases,
+                                'correction_power': 'sign_switch',
+                                'correction_factor': 1,
+                                'kappas': kappa,
+                                'domain_width': domain_width,
+                                'discretization': d,
+                                'angle_convergence_threshold': 0.01,
+                                'interface_with': interface_with,
+                                'triple_point_energy': triple_point_factor,
+                                'domain_aspect_ratio': aspect,
+                            }
+                            params.update(kwargs)
+                            study.add_run(params)
+
+
+def main():
+    s = ParameterStudy(run_n_phase_2d)
+    # study_3phase(s)
+    study_2d(s)
+    s.run_from_command_line()
+
+
+if __name__ == '__main__':
+    main()
+
+
diff --git a/lbmpy_tests/phasefield/test_numerical_1D_3phase_model.ipynb b/lbmpy_tests/phasefield/test_numerical_1D_3phase_model.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..638b67a503970807387f6f67ca047ae3ab69376e
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_numerical_1D_3phase_model.ipynb
@@ -0,0 +1,407 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.scenarios import create_three_phase_model\n",
+    "from pystencils.datahandling import SerialDataHandling\n",
+    "from lbmpy.phasefield.experiments1D import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 1D Numerical tests for 3-phase model\n",
+    "\n",
+    "\n",
+    "## 1) Interface validation (check for tanh shape)\n",
+    "\n",
+    "This test ensures that an initialized sharp step function interface relaxes to the expected $\\tanh$ form. \n",
+    "Therefore a periodic 1D domain is set up. Due to the periodicity actually two interfaces have to be initialized."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "alpha = 6\n",
+    "width = 100 * alpha\n",
+    "x_step1 = width // 4            # location of first interface\n",
+    "x_step2 = (width // 4) * 3      # location of second interface\n",
+    "include_rho = True\n",
+    "\n",
+    "phaseIdx = 1 if include_rho else 0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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R+0wYOabrvpFjavv76Mknn2Tvvffu3J43bx7nnHNOn4/XjDOlJRQN16qYcKEjSWqJqfvB9SfCB78K0w+tJaQbtgfJ3nvvzb/9279xyimnDNo5JQ1zt5zVfCZ0g1dfgfWvdt23/tXac656b/PnvPGtcNR5rYuxD0xKS8oZtWqyXyWpl7b0wQtgwhT42gdqt79fBpP3gDvPr12a6cUHryeffJL3ve99nb9VOm/ePFavXt10VmDPPffszSuRpMEzagy8bgdY/Ttqnzyjtt199rRkTEolSdLQ1LZdLSFdtRQm7lzblqQq682M5u+fhQvfBq+ugVFj4ZS7YcKOfT7lqFGjWL9+fef2mjVr+nysHs/R8iOq3yztrD77WJK2oDcfvDaU7B76OVh8Bcw6s1bKK0nD2YQ3wr4fhZ9eVbvtR0IKsOOOO/Lcc8+xYsUKttlmG2688UaOPPLIFgVbY1JaShZ5SpK0WY3fIZ1+KEw/pOt2P2Ru/P/hdevW9etYklSId34Olj8C7zyz34caPXo0X/ziF9l///2ZPn06e+yxRwsC7MqkVJIkDT1P/6xrAjr90Nr20z/rd1L61FNPsXz5ciZNmsTdd9/NjBkz+h2uJA2qCW+Eube07HCnn346p59+esuO150/CVNCQXSu0qqK2bD6rv0rSf3zZ5/aNPmcfmhtfz9NmjSJE044gXe84x3svffeLFiwgMcff3yTdt/5zndob2/nxz/+Me9973t597vf3e9zS9Jw5ExpSVnAW032qySV34QJE7jllo0zDF/+8pebtvvABz7ABz7wgcEKS5Iqy5lSSZIkSVJhnCmVJEmqmzZtWudvlG5w6qmncs8993TZd8YZZzB37tzBDE3SMJaZpf76V+MCcX1hUlpSlnlWk/0qSUPP/Pnziw5B0jDW1tbGihUrmDRpUikT08xkxYoVtLW19fkYJqWSJEmSVFLt7e10dHSwfPnyokPpUVtbG+3t7X1+vklpCZXv7x9qHVfflSRJUu+NHj2a6dOnFx3GgHKho5JKk5ZKSgt4JUmSpC5MSiUNOxFxZEQ8GhFLIuKsJo+PjYhv1R+/LyKmdXt8l4hYHRGfGayYJWlrOdZJGipMSkvIOdIqq5fv2suFiYiRwHzgKGAv4MMRsVe3Zh8HXsjM3YB/Ac7v9vi/ALcgqTBXPngli5Yt6rJv0bJFXPnglYMWw2c/+1n22GMP9tlnHz7wgQ/w4osvDtq5t8SxTtJQYlJaUhZ5VpP9WgozgSWZ+URmvgJcCxzbrc2xwNX1+zcAh0X9i8AR8X7gCeChQYpXUhN7T9qbz9z1mc7EdNGyRXzmrs+w96S9By2G2bNn8+CDD/LAAw/w5je/mX/6p38atHP3gmOdpCHDhY4kDTdTgaUN2x3A/j21ycxXI2IVMCki/gicCcwGeixni4iTgZMBdtlll9ZFLg0j5y86n1+v/PVm20weP5lTbj+FyeMns/zl5bxpuzdx8S8v5uJfXty0/R5v2IMzZ5652WM++eSTvO997+v8rdJ58+axevVqzjnnnE3aHnHEEZ33DzjgAG644YYtvKpB5VgnachwprSELOyssNhwYy8XqNmb330Su6c2/wD8S2au3twJMvPSzJyRmTMmT57cxzAlbcm2Y7Zl8vjJLPvDMiaPn8y2Y7YtLJYrr7ySo446qrDzN+FYJ2nIcKa0pCzzlAZMB7Bzw3Y78EwPbToiYhQwEVhJbZbhuIj4Z2A7YH1ErMnMiwY+bGl42dKMJmws2T1ln1O47tHr+OTbPsnMKTMHIbqu/vEf/5FRo0bx0Y9+dNDPvRmOdZKGDJNSScPN/cDuETEdeBo4HvhItzYLgTnAj4HjgB9kZgKHbGgQEecAq/2QJhVjQ0I6753zmDllJjPfOLPLdn/U/nOvWbdu3WbbXn311dx4443ccccdZfsNasc6SUOG5bslVCvtLNX/sall6qvvluuDy7CSma8CpwG3Ao8A12XmQxFxbkQcU292BbXvVS0BPg1s8lMKkor14IoHuySgM6fMZN475/Hgigf7feynnnqK5cuXs379eu6++25ee+21pu3+4z/+g/PPP5+FCxcyfvz4fp+3lRzrJA0lzpRKg8iy7HLIzJuBm7vt+2LD/TXAB7dwjHMGJDhJvfKxvT+2yb6ZU2a2pHx30qRJnHDCCTz77LMcfvjhLFiwgBNPPJFdd921S7vTTjuNtWvXMnv2bKC22NEll1zS7/O3imOdpKHCpFSSJKnBhAkTuOWWjT/P+eUvf7lpuyVLlgxWSJJUaZbvllB0XqmqXH1XkiRJqnGmtKQs86wm+1WSym3atGmdv1G6wamnnso999zTZd8ZZ5zB3LlzBzM0Saosk9LSciatmuxXSdqczCzdYnDz58/v83MbV/KVJDVn+a4kSSqFtrY2VqxYUZlELjNZsWIFbW1tRYciSaXmTGlJVeP/jtWd/SpJPWtvb6ejo4Ply5cXHUrLtLW10d7eXnQYklRqJqUlVK6iJbVUvXPLVpomSWUwevRopk+fXnQYkqRBZvluSTmjVk32qyRJktSVSakkSZIkqTAmpSUUDdeqJn+nVJIkSaoxKS0pyzyryX6VJEmSujIplSRJkiQVxqS0hKLzSpXj6ruSJElSFyalkiRJkqTCmJRKkiRJkgpjUlpCrsxaZRvWVraPJUmSJDApLal0ldaKsl8lSZKkrkxKJUmSJEmFMSktJUs7q87yXUmSJKnGpLSkLPOsJvtVkiRJ6qpXSWlEHBkRj0bEkog4q8nju0TEDyPi5xHxQES8p/WhSpIkSZKqZotJaUSMBOYDRwF7AR+OiL26NfsfwHWZ+XbgeOD/a3Wgw0k0XKtqosuNJEmSNNz1ZqZ0JrAkM5/IzFeAa4Fju7VJYNv6/YnAM60LcXiyzLOa7FdJkiSpq1G9aDMVWNqw3QHs363NOcBtEfF/Aa8DDm9JdJIkSZKkSuvNTGmzQsPuEz4fBr6ame3Ae4CvRcQmx46IkyNicUQsXr58+dZHO0xE55Uqp7N61w6WJEmSoHdJaQewc8N2O5uW534cuA4gM38MtAHbdz9QZl6amTMyc8bkyZP7FvEwYZlnNdmvkiRJUle9SUrvB3aPiOkRMYbaQkYLu7X5LXAYQETsSS0pdSpUkiRJkrRZW0xKM/NV4DTgVuARaqvsPhQR50bEMfVmfwecFBG/BL4JnJiZTgr1kYWd1Wf5riRJklTTm4WOyMybgZu77ftiw/2HgYNbG9rwZkZfTfarJEmS1FVvynclSZIkSRoQJqUlFA3Xqpp674b9K0mSJIFJqSRJkiSpQCalJeQcWvW50JEkSZJUY1IqSZIkSSqMSWlJuUprNdmvkiRJUlcmpWVldWeludCRJEmSVGNSWlLOqFWT/SpJkiR1ZVIqSZIkSSqMSWkJ+TulVWa/SpIkSY1MSkvKMs9qsl8lSZKkrkxKJUmSJEmFMSktIQs8KywgnC6VJEmSOpmUlpR5SzXZr5IkSVJXJqWSJEmSpMKYlJaQ5bvVZv9KkiRJG5mUlpRlntVkv0qSJEldmZRKkiRJkgpjUlpCARAWeVZTWL4rSZIkNTAplSRJkiQVxqRUkiRJklQYk9ISsryz2uzf4kXEkRHxaEQsiYizmjw+NiK+VX/8voiYVt8/OyJ+GhG/qt++a7Bjl6TecqyTNFSYlJaUq7RWk/1avIgYCcwHjgL2Aj4cEXt1a/Zx4IXM3A34F+D8+v7ngaMz863AHOBrgxO1JG0dxzpJQ4lJqaThZiawJDOfyMxXgGuBY7u1ORa4un7/BuCwiIjM/HlmPlPf/xDQFhFjByVqSdo6jnWShgyT0lKywLOy7NoymAosbdjuqO9r2iYzXwVWAZO6tfkL4OeZubb7CSLi5IhYHBGLly9f3rLAJWkrONZJGjJMSssoLfOsKvu1FJr9aaB712y2TUS8hVqZ2ynNTpCZl2bmjMycMXny5D4HKkn94FgnacgwKZU03HQAOzdstwPP9NQmIkYBE4GV9e124DvACZn5+IBHK0l941gnacgwKS2haLhW9dizhbsf2D0ipkfEGOB4YGG3NgupLe4BcBzwg8zMiNgOuAn4fGbeM2gRS9LWc6yTNGSYlJaUZZ7VZL8Wr/69qdOAW4FHgOsy86GIODcijqk3uwKYFBFLgE8DG35K4TRgN+DvI+IX9csOg/wSJGmLHOskDSWjig5AkgZbZt4M3Nxt3xcb7q8BPtjkeV8CvjTgAUpSCzjWSRoqnCktIcs7q83+lSRJkjYyKS2pDAs9q8helSRJkroyKS0hFzqqsrBnJUmSpAYmpZIkSZKkwpiUSpIkSZIKY1JaQpZ3VljYv5IkSVIjk9KSckGcarJfJUmSpK5MSiVJkiRJhTEplQaZ5buSJEnSRialJWWZZzXZr5IkSVJXJqWSJEmSpMKYlJZQNFyrauxXSZIkqZFJaSklaaFnJdmvkiRJUlcmpZIkSZKkwowqOgBtKizxrDB7V5IkSWrkTGkpWeRZVfarJEmS1JVJqSRJkiSpMCalJRSEi7RWmF0rSZIkbWRSWkqW71aV/SpJkiR1ZVIqSZIkSSqMSWkJuT5rtdm7kiRJ0ka9Skoj4siIeDQilkTEWT20+cuIeDgiHoqIb7Q2zOHGIk9JkiRJw8MWf6c0IkYC84HZQAdwf0QszMyHG9rsDnweODgzX4iIHQYqYEmSJElSdfRmpnQmsCQzn8jMV4BrgWO7tTkJmJ+ZLwBk5nOtDXN4sXy3wsLelSRJkhr1JimdCixt2O6o72v0ZuDNEXFPRPwkIo5sdqCIODkiFkfE4uXLl/ct4mHB1Xeryp6VJEmSuupNUtpsYqf7J+tRwO7ALODDwOURsd0mT8q8NDNnZOaMyZMnb22skiRJkqSK6U1S2gHs3LDdDjzTpM33MnNdZv4GeJRakqo+s8izmsJ1rCRJkqQGvUlK7wd2j4jpETEGOB5Y2K3Nd4H/DhAR21Mr532ilYEON+Yt1WS/SpIkSV1tcfXdzHw1Ik4DbgVGAldm5kMRcS6wODMX1h87IiIeBl4DPpuZKwYy8CpzjrTa+tK/69ato6OjgzVr1rQ8nqK0tbXR3t7O6NGjiw5FkiRJBdpiUgqQmTcDN3fb98WG+wl8un6R1GIdHR1MmDCBadOmETH0/2yRmaxYsYKOjg6mT59edDiSJEkqUG/Kd1UAyzyrqa/9umbNGiZNmlSJhBQgIpg0aVKlZn4lSZLUNyalJVSNtEM96Wv/ViUh3aBqr0eSJEl9Y1IqSZIkSSqMSWlJWb5bTfarJEmS1JVJaQlF55WqaKC79pK7Hufex5/vsu/ex5/nkrseH+Az12Qmp59+Orvtthv77LMPP/vZzwblvJIkSRqaTErLKJ1Rq6rB6Nd92idy2jd+3pmY3vv485z2jZ+zT/vEQTg73HLLLTz22GM89thjXHrppXzyk58clPNKkiRpaOrVT8JIKo9/+PeHePiZlzbbZocJYznhikXsuO1YfvfSWnbbYRsu/P5jXPj9x5q232unbTn76Lds9phnnnkmO+20E5dddhnjxo1jwYIF7Lnnnpu0+973vscJJ5xARHDAAQfw4osvsmzZMqZMmdL7FylJkqRhw5nSErJyt8piUPp34rjR7LjtWJ5+cQ07bjuWieNG9+t49957L7fddhv77rsvU6dO5eyzz+aMM85o2vbpp59m55137txub2/n6aef7tf5JUmSVF3OlEqDKulvEe+WZjRhY8nu6e/ajWvu+y1nHL47B+26fZ/PuWjRIo4++mgyk9GjR3PkkUcyZ86cpm0zN319/vyLJEmSeuJMqVQxGxLSiz7ydj59xH/joo+8vct3TPuiWVI5cuTIpm3b29tZunRp53ZHRwc77bRTn88tSZKkajMpLaFouFbFxMCX7z7QsYqLPvL2zpnRg3bdnos+8nYe6FjV52Mecsgh3HTTTaxbtw6Ab3/72xxyyCFN2x5zzDEsWLCAzOQnP/kJEydO9PukkiRJ6pHluyXl6rvVlIPQs3/zzl032XfQrtv3q3x3v/3247jjjuOkk05i5cqVrFq1imuuuaZp2/e85z3cfPPN7LbbbowfP56rrrqqz+eVJElS9ZmUSuqVz3/+8xx44IHMmzePG2+8scdcZSE3AAAdk0lEQVR2EcH8+fMHMTJJkiQNZZbvSoPKsmxJkiSpkTOlJWX5bjUN9X6dNWsWs2bNAuCqq67iwgsv7PL4wQcf7CypJEmStopJqaQ+mTt3LnPnzi06DEmSJA1xlu+WkAWe1Wb/SpIkSRuZlJbUUC/zVHODsfquJEmSNJSYlEqSJEmSCmNSWkKWd1ZZ2L+SJElSA5PSkrLIs5oGpV9/dAH85u6u+35zd23/IPj1r3/NgQceyNixY5k3b96gnHNrRcSREfFoRCyJiLOaPD42Ir5Vf/y+iJjW8Njn6/sfjYh3D2bckrQ1HOskDRWuvitVzdT94PoT4YNfhemH1hLSDduD4A1veANf+cpX+O53vzso59taETESmA/MBjqA+yNiYWY+3NDs48ALmblbRBwPnA98KCL2Ao4H3gLsBHw/It6cma/1J6Zzrj6eu9b9igDWRTI6gz+OgJdj0z9kJLVqimi4P5Rumxnqr6nKr62Kr6mVr20kMDaT8evhlYAxWdv/ztH7cM6ca3s4y+Ao41j3/LyZbL/60f4cQlKJrGUMY89Z3pJjmZSWUHReqYqiv9Olt5wFz/5q820mTIGvfaB2+/tlMHkPuPP82qWZN74Vjjpvs4c888wz2WmnnbjssssYN24cCxYsYM8999yk3Q477MAOO+zATTfd1NtXNNhmAksy8wmAiLgWOBZo/KB2LHBO/f4NwEUREfX912bmWuA3EbGkfrwf9yegPXc6gIVLH2DdiBH05j/+ZOOH6qF225Oh/Jqq/Np6MpRfUytf26vAqxH8oaHubEzW/psugdKNdet2mkE++ijhZxxpyMuE1dvszNgWHc/yXamK2rarJaSrltZu27br1+HuvfdebrvtNvbdd1+mTp3K2WefzRlnnNGiYAfdVGBpw3ZHfV/TNpn5KrAKmNTL5261D83+FGfufDIjsr9/sZBUpDEJn2v/BB+a/amiQ4ESjnVTjv4i68P5EKkSAib99YKWHc6RQRpqtjCjCWws2T30c7D4Cph1Zq2Ut48WLVrE0UcfTWYyevRojjzySObMmdPn4xWs2d/ou2eDPbXpzXOJiJOBkwF22WWXXgX1odmf4tpLr2TJWBNTaag6Yv30siSkUMaxbsIbGTljDrn4CgvCpCEsgZi8B7xx75Yd05nSEnKgrrYB79/G75C+6wu12+tP3HTxo60QTWqtRo4c2efjFawD2Llhux14pqc2ETEKmAis7OVzycxLM3NGZs6YPHlyr4L61u0X8NSoV2v1MF68eBmSl9viCb51++AsKtcLpRzr7v+TT7A2/fgpDWkJN0w/p6WHdFQopdzid140NA1Kvz79s42LHEHt9oNfre3vo0MOOYSbbrqJdevWAfDtb3+bQw45pP+xFuN+YPeImB4RY6gt5rGwW5uFwJz6/eOAH2Rm1vcfX1+xcjqwO7CovwF96/YLOH/ppfXvlEoaql4J+OeOy8uSmJZurLv38ef56LVPcv1r7yr67wdevHjpx+XRnMpn7l7PZf/5eH+HhU6W75aSc6WVNRhd+2dNSsemH9qv8t399tuP4447jpNOOomVK1eyatUqrrnmmqZtn332WWbMmMFLL73EiBEjuOCCC3j44YfZdttt+3z+VsrMVyPiNOBWaotnXpmZD0XEucDizFwIXAF8rb64x0pqH+aot7uO2kIhrwKn9nc1SoBHnvkJE9cHsT5dfXcI31bxtVXxNQ3G6ruPPPOTHs4weMo41j3QsYpJ24zlW3k8M1/5NbvSwSuMYky+Wrtl8G8DWFvQuX1Nvrah9JrGxqusZTTJSL4Yn2LXya/jniUrOOmQXfs7NAAQtT+IDb4ZM2bk4sWLCzl32c356jsYFSO4Ys79RYeiFjv72iP40cvPcMfHHtyq5z3yyCNNV7odbHfeeSfz5s3jxhtvbMnxmr2uiPhpZs5oyQlKwLFOUjOOdZKGg96OddaKlVFavltVBf0NSJIkSSoty3dLyOLdahvK/Ttr1ixmzZoFwFVXXcWFF17Y5fGDDz6Y+fPnFxCZJEmShiqTUkl9MnfuXObOnVt0GJIkSRriLN8tKas8qykbriVJkiSZlJbSUC7v1BaE/StJkiQ1MiktKefSqsl+lSRJkroyKZUkSZIkFcaktISi4VpVEwPes1c+eCWLli3qsm/RskVc+eCVA3zmmq9//evss88+7LPPPhx00EH88pe/HJTzSpIkaWgyKS0pf6m0mgajX/eetDefuesznYnpomWL+Mxdn2HvSXsP+LkBpk+fzl133cUDDzzA3//933PyyScPynklSZI0NPmTMNIQc/6i8/n1yl9vts3k8ZM55fZTmDx+MstfXs6btnsTF//yYi7+5cVN2+/xhj04c+aZmz3mmWeeyU477cRll13GuHHjWLBgAXvuuecm7Q466KDO+wcccAAdHR29eFWSJEkarpwpLSHLd6ts4Mt3AbYdsy2Tx09m2R+WMXn8ZLYds22/jnfvvfdy2223se+++zJ16lTOPvtszjjjjC0+74orruCoo47q17klSZJUbc6USoOq/+W7W5rRhI0lu6fscwrXPXodn3zbJ5k5ZWafz7lo0SKOPvpoMpPRo0dz5JFHMmfOnM0+54c//CFXXHEFP/rRj/p8XkmSJFWfSalUMRsS0nnvnMfMKTOZ+caZXbb7ImLT+d2RI0f22P6BBx7gE5/4BLfccguTJk3q0zklSZI0PFi+W0IW7lZZEAO81tGDKx7skoDOnDKTee+cx4MrHuzzMQ855BBuuukm1q1bB8C3v/1tDjnkkKZtf/vb3/Lnf/7nfO1rX+PNb35zn88pSZKk4cGZ0lJy7d2qGox+/djeH9tk38wpM/tVvrvffvtx3HHHcdJJJ7Fy5UpWrVrFNddc07Ttueeey4oVK/jbv/1bAEaNGsXixYv7fG5JkiRVm0mppF75/Oc/z4EHHsi8efO48cYbe2x3+eWXc/nllw9iZJIkSRrKLN8tJQt4JUmSJA0PzpSWUVq+W1VDvV9nzZrFrFmzALjqqqu48MILuzx+8MEHM3/+/AIikyRJ0lBlUioNEZnZdBXcosydO5e5c+f2+fmZQz1FlyRJUitYvltC5Uk7NBD60r9tbW2sWLGiMolcZrJixQra2tqKDkWSJEkFc6a0pKqReqi7bLjeGu3t7XR0dLB8+fJWh1SYtrY22tvbiw5DkiRJBetVUhoRRwIXAiOByzPzvB7aHQdcD/xpZvobEFKLjB49munTpxcdhiRJktRyWyzfjYiRwHzgKGAv4MMRsVeTdhOA04H7Wh3kcBOdV6oiu1aSJEnaqDffKZ0JLMnMJzLzFeBa4Ngm7f4n8M/AmhbGN2xZvltN9qskSZLUVW+S0qnA0obtjvq+ThHxdmDnzLxxcweKiJMjYnFELK7Sd+MkSZIkSX3Tm6S0WbVh54RPRIwA/gX4uy0dKDMvzcwZmTlj8uTJvY9ymLG8s9rsX0mSJGmj3iSlHcDODdvtwDMN2xOAvYE7I+JJ4ABgYUTMaFWQUlVYvitJkiR11Zuk9H5g94iYHhFjgOOBhRsezMxVmbl9Zk7LzGnAT4BjXH2375xJq7CwfyVJkqRGW0xKM/NV4DTgVuAR4LrMfCgizo2IYwY6QEmSJElSdfXqd0oz82bg5m77vthD21n9D0uWeVaUHStJkiR10ZvyXUktFCamkiRJUieTUkmSJElSYUxKSymt8qwo+1WSJEnqyqS0hML1WavLrpUkSZK6MCkto3SmtKrsV0mSJKkrk1JJkiRJUmFMSkvICs9qC+dLJUmSpE4mpSVl2lJN9qskSZLUlUmpJEmSJKkwJqUlZPlutdm/kiRJ0kYmpSVlmWc12a+SJElSVyalkiRJkqTCmJSWkOWd1Wb/SpIkSRuZlJaSRZ6SJEmShgeTUkmSJElSYUxKSygs8Kw0e1eSJEnayKS0lNIC3orKzitJkiRJYFIqSZIkSSqQSWkZOZNWcXawJEmStIFJaUmZtlST/SpJkiR1ZVIqSZIkSSqMSWkJuTprtdm/xYmIN0TE7RHxWP329T20m1Nv81hEzKnvGx8RN0XEryPioYg4b3Cjl6TecayTNNSYlJaUZZ7VZL8W7izgjszcHbijvt1FRLwBOBvYH5gJnN3wgW5eZu4BvB04OCKOGpywJWmrONZJGlJMSiUNJ8cCV9fvXw28v0mbdwO3Z+bKzHwBuB04MjNfzswfAmTmK8DPgPZBiFmStpZjnaQhxaS0hCzvrDb7t1A7ZuYygPrtDk3aTAWWNmx31Pd1iojtgKOpzUBsIiJOjojFEbF4+fLlLQlckraCY52kIWVU0QGombTMs6Ls14EXEd8H3tjkoS/09hBN9nV2XUSMAr4JfCUzn2h2gMy8FLgUYMaMGXa7pJZzrJNUJSalJeRMWrXZvwMrMw/v6bGI+F1ETMnMZRExBXiuSbMOYFbDdjtwZ8P2pcBjmXlBC8KVpD5xrJNUJZbvShpOFgJz6vfnAN9r0uZW4IiIeH190Y8j6vuIiC8BE4FPDUKsktRXjnWShhST0pKyBqaasuFahTgPmB0RjwGz69tExIyIuBwgM1cC/xO4v345NzNXRkQ7tbK4vYCfRcQvIuITRbwISdoCxzpJQ4rluyVkeWe1hTlpYTJzBXBYk/2LgU80bF8JXNmtTQf+5ylpCHCskzTUOFMqSZIkSSqMSakkSZIkqTAmpSUUnVeqIrtWkiRJ2siktIzS3ymtKvtVkiRJ6sqkVJIkSZJUGJNSSZIkSVJhTEpLKq3zrCS7VZIkSerKpFSSJEmSVBiT0hJy9d1qC+dLJUmSpE4mpSVl2lJN9qskSZLUlUmpJEmSJKkwJqUlZOVutdm/kiRJ0kYmpSVlmWc15YaedXllSZIkCTAplSRJkiQVyKS0hCzvrLKwfyVJkqQGJqVllJ1XqhjLdyVJkqSuTEolSZIkSYUxKS2haLhW1QThJKkkSZLUyaS0lHJjmacqJrvdSpIkScObSakkSZIkqTC9Skoj4siIeDQilkTEWU0e/3REPBwRD0TEHRHxJ60PdbixfLeaXH1XkiRJarTFpDQiRgLzgaOAvYAPR8Re3Zr9HJiRmfsANwD/3OpAhxvLd6vJ1XclSZKkrnozUzoTWJKZT2TmK8C1wLGNDTLzh5n5cn3zJ0B7a8OUJEmSJFVRb5LSqcDShu2O+r6efBy4pT9BDXeWd0qSJEkaLkb1ok2zHKlp7WFE/BUwA3hnD4+fDJwMsMsuu/QyxOHI4t2qyib3JEmSpOGsNzOlHcDODdvtwDPdG0XE4cAXgGMyc22zA2XmpZk5IzNnTJ48uS/xDgvOlFab/StJkiRt1Juk9H5g94iYHhFjgOOBhY0NIuLtwL9SS0ifa32YkiRJkqQq2mJSmpmvAqcBtwKPANdl5kMRcW5EHFNv9mVgG+D6iPhFRCzs4XDqjbS4s6o6+9XVdyVJkiSgd98pJTNvBm7utu+LDfcPb3Fcw5rlndVm/0qSJEkb9aZ8V5IkSZKkAWFSWlIWd1aTq+9KkiRJXZmUlpDlnRUWECakkiRJUieT0lIyaamsDV3rQkeSJEkSYFIqSZIkSSqQSWkJWb5bbfavJEmStJFJaUlZ3FlNubF+t9A4JEmSpLIwKZUkSZIkFcakVBpUFu9KkiRJjUxKyygbyzxVJZ396uq7kiRJEmBSKkmSJEkqkElpCQWJZZ5VFYSTpJIkSVInk9KSsny3mlx9V5IkSerKpFSSJEmSVBiT0hKycLfa7F9JkiRpI5PSkrK4s5o6+9XVdyVJkiTApFSSJEmSVCCT0hKyvLPa7F9JkiRpI5PSUnLt3arKJvckSZKk4cykVJIkSZJUGJPSErK8s9rsX0mSJGkjk9IysrKz+lx9txAR8YaIuD0iHqvfvr6HdnPqbR6LiDlNHl8YEQ8OfMSStPUc6yQNNSalkoaTs4A7MnN34I76dhcR8QbgbGB/YCZwduMHuoj4c2D14IQrSX3iWCdpSDEpLSHLO6vN/i3UscDV9ftXA+9v0ubdwO2ZuTIzXwBuB44EiIhtgE8DXxqEWCWprxzrJA0pJqWl5Oq7VeXqu4XbMTOXAdRvd2jSZiqwtGG7o74P4H8C/wt4eXMniYiTI2JxRCxevnx5/6OWpK3jWCdpSBlVdACS1EoR8X3gjU0e+kJvD9FkX0bEvsBumfl/R8S0zR0gMy8FLgWYMWOGf4GQ1HKOdZKqxKRUUqVk5uE9PRYRv4uIKZm5LCKmAM81adYBzGrYbgfuBA4E3hERT1IbO3eIiDszcxaSNMgc6yRVieW7JeWfG6upszDb1XeLshDYsMLkHOB7TdrcChwREa+vL/pxBHBrZl6cmTtl5jTgz4D/8kOapJJyrJM0pJiUllCYr1RYEP7JoUjnAbMj4jFgdn2biJgREZcDZOZKat+nur9+Obe+T5KGCsc6SUOK5buSho3MXAEc1mT/YuATDdtXAldu5jhPAnsPQIiS1G+OdZKGGmdKSylJyzsraeO6yvavJEmSBCalpRSdV6oiu1aSJEnayKS0pJworabObrWDJUmSJMCkVJIkSZJUIJPSErK8s9pcXVmSJEnayKRUkiRJklQYk1JJkiRJUmFMSkvI8t1qs38lSZKkjUxKyyjTX7GsKFfflSRJkroyKZUkSZIkFcakVJIkSZJUGJPSkrKAt5o29qv9K0mSJIFJqSRJkiSpQCalJRQN16qasGclSZKkBialJWX5bjV19qur70qSJEmASakkSZIkqUAmpSUUzpJWmuW7kiRJ0kYmpSVlWlpN2eSeJEmSNJyZlEqSJEmSCmNSWkLhJFqlWb4rSZIkbWRSWkquvVtVnf3q6ruSJEkSAKN60ygijgQuBEYCl2fmed0eHwssAN4BrAA+lJlP9ju6a46DF56CP66EUW3w6hpYvw7W/r72eCZEDMzt5t+QATnnldtN5JsTXsdL48fy8mtrmX3lW1gdsGbEKF4jCYLsx20zGx7v77GLvi37a4P1jH8NXo71LBk7hkOv/+9MXA/t69Zx8XPPl+bfYMtuR4yC0eNg7La1/25HtQEJM0+GP/vU5l+bJEmShpUtJqURMRKYD8wGOoD7I2JhZj7c0OzjwAuZuVtEHA+cD3yo39G9aRbc9oXNt9nw4b3VtwWcc+81f2TFtq9j3YjaBPaznXWe62vN6slXX297fDn1/7XiHEXdDoXXtnpEAsH6CF4AXhgBH3zpZcj19WCL/zfYstv162DtOlj70saYR7XB1P22/NokSZI0rPSmfHcmsCQzn8jMV4BrgWO7tTkWuLp+/wbgsIjo/1fnDjoNjvjHfh9mqJi5Zi2XPPc8IxqTkha8jSqJbn352ZUvcMJLqwsKZpCNaoOPXg/TDy06EkmSJJVMb5LSqcDShu2O+r6mbTLzVWAVMKn7gSLi5IhYHBGLly9f3rsIDzoNJuzUu7YVMHPNWt77h5drCYwJafXU+3W/NWuHT0IKcNDpJqSSJElqqjdJabPMqHt9YW/akJmXZuaMzJwxefLk3sQH914Ev3+md20rYFHbWP5j/LhaGaSL4VRPvV9/1jaWBdtuU3Q0g+fer8Bv7i46CkmSJJVQb5LSDmDnhu12oHuW2NkmIkYBE4GV/Y7u3ou2/J3SClnUNpa/2WH7zu+UAiamVdKtL7/8htcPn8T01TXw9Q+amEqSJGkTvVl9935g94iYDjwNHA98pFubhcAc4MfAccAPMluQTT1xJ0x687BZfffBtnFMSmB9shYYC7XVd2Okq+8O8dcG6xm/PhjNa4wheIVk4nr48bjxnPD7l0vzb3DAV999+meW8UqSJKmLLSalmflqRJwG3ErtJ2GuzMyHIuJcYHFmLgSuAL4WEUuozZAe35Lo/uqGlhxmqPhY/SJJkiRJw0Wvfqc0M28Gbu6274sN99cAH2xtaJIkSZKkquvNd0olSZIkSRoQJqWSJEmSpMKYlEqSJEmSCmNSKkmSJEkqjEmpJEmSJKkwJqWSJEmSpMKYlEqSJEmSCmNSKkmSJEkqjEmpJEmSJKkwkZnFnDhiOfDUVjxle+D5AQqnFYyvf8ocX5ljg+rF9yeZOXmgghlsjnWDzvj6p8zxlTk2cKxzrBtcxtc/ZY6vzLHBAI11hSWlWysiFmfmjKLj6Inx9U+Z4ytzbGB8VVP298v4+sf4+q7MsUH54yubsr9fxtc/xtd3ZY4NBi4+y3clSZIkSYUxKZUkSZIkFWYoJaWXFh3AFhhf/5Q5vjLHBsZXNWV/v4yvf4yv78ocG5Q/vrIp+/tlfP1jfH1X5thggOIbMt8plSRJkiRVz1CaKZUkSZIkVcyQSEoj4siIeDQilkTEWQXFcGVEPBcRDzbse0NE3B4Rj9VvX1/fHxHxlXq8D0TEfgMc284R8cOIeCQiHoqIM0oWX1tELIqIX9bj+4f6/ukRcV89vm9FxJj6/rH17SX1x6cNZHz1c46MiJ9HxI1li61+3icj4lcR8YuIWFzfV5b+3S4iboiIX9f/DR5YltiGGse6LcbmWNeaOEs73pV5rKuf0/GuBRzrthibY11r4nSs63t8gz/WZWapL8BI4HHgTcAY4JfAXgXEcSiwH/Bgw75/Bs6q3z8LOL9+/z3ALUAABwD3DXBsU4D96vcnAP8F7FWi+ALYpn5/NHBf/bzXAcfX918CfLJ+/2+BS+r3jwe+NQj9+2ngG8CN9e3SxFY/15PA9t32laV/rwY+Ub8/BtiuLLENpYtjXa9ic6xrTZylHe/KPNbVz+l41//30LFuy7E51rUmTse6vsc36GPdgP+DaMGbciBwa8P254HPFxTLtG6D16PAlPr9KcCj9fv/Cny4WbtBivN7wOwyxgeMB34G7E/th3dHde9n4FbgwPr9UfV2MYAxtQN3AO8Cbqz/R1WK2BpibDZ4Fd6/wLbAb7q/B2WIbahdHOv6FKdj3dbHVerxrqxjXf34jneteR8d67Y+Tse6rY/Lsa7vsRUy1g2F8t2pwNKG7Y76vjLYMTOXAdRvd6jvLyzmesnB26n91ao08dVLKH4BPAfcTu2vpC9m5qtNYuiMr/74KmDSAIZ3AfA5YH19e1KJYtsggdsi4qcRcXJ9Xxn6903AcuCqeonM5RHxupLENtSU+b0pXX861vVZ2ce7so514HjXKmV+X0rXl451feZY13eFjHVDISmNJvty0KPYOoXEHBHbAN8GPpWZL22uaZN9AxpfZr6WmftS+8vVTGDPzcQwaPFFxPuA5zLzp427N3P+ov49HpyZ+wFHAadGxKGbaTuYMY6iVv50cWa+HfgDtZKOngzF/54Hy1B8bxzruh+8pGMdDJnxrqxjHTjetcpQfF8c67of3LGuvxzruhkKSWkHsHPDdjvwTEGxdPe7iJgCUL99rr5/0GOOiNHUBq6vZ+a/lS2+DTLzReBOajXn20XEqCYxdMZXf3wisHKAQjoYOCYingSupVbmcUFJYuuUmc/Ub58DvkPt/wDK0L8dQEdm3lffvoHaQFaG2IaaMr83pelPx7p+Kf14V+KxbsP5HO/6r8zvS2n60rGuXxzr+qeQsW4oJKX3A7vXV8waQ+0LyAsLjmmDhcCc+v051Gr+N+w/ob4a1QHAqg3T3QMhIgK4AngkM/93CeObHBHb1e+PAw4HHgF+CBzXQ3wb4j4O+EHWi9RbLTM/n5ntmTmN2r+tH2TmR8sQ2wYR8bqImLDhPnAE8CAl6N/MfBZYGhH/rb7rMODhMsQ2BDnWbYFjXf+Ufbwr81gHjnct5Fi3BY51/eNY1z+FjXVb+yXUIi7UVnX6L2r16l8oKIZvAsuAddT+IvBxavXmdwCP1W/fUG8bwPx6vL8CZgxwbH9GbZr8AeAX9ct7/v927tgEYSiKAui10tYVMoA4gpO5kI1ziCCCdhnG5omdgoT8r5wDKZJAcsknFx6EdJRvk+RS+W5J9nV8SHJKMiY5JFnW8VXtj3V+mGmNd3n9oa2bbJXlWtv9+Q50tL7bJOda32OSdS/Zfm3TdR+z6brpsnbXd713Xd1T303zHHXd+2y6brqsuu67jLN33aIuBgAAALP7hc93AQAA+FOGUgAAAJoxlAIAANCMoRQAAIBmDKUAAAA0YygFAACgGUMpAAAAzRhKAQAAaOYBAD8wlUxn4BgAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "test_sc1 = create_three_phase_model(data_handling=SerialDataHandling((width, 1), periodicity=True),\n",
+    "                                    alpha=alpha,  # interface width\n",
+    "                                    kappa=(0.015/alpha, 0.015/alpha, 0.015/alpha),  # interface energy,  determines surface tension\n",
+    "                                    cahn_hilliard_relaxation_rates=1.0,  # relaxation rate = 1/tau, determines mobilities\n",
+    "                                    hydro_dynamic_relaxation_rate=1.0,  # relaxation rate = 1/tau, determines viscosity\n",
+    "                                    cahn_hilliard_gammas=[1, 1, 1/3],\n",
+    "                                    include_rho=include_rho,\n",
+    "                                    hydro_lbm_parameters={'force_model': 'guo'},\n",
+    "                                    )\n",
+    "\n",
+    "vis_width = 25\n",
+    "init_sharp_interface(test_sc1, phase_idx=phaseIdx, inverse=False, x1=x_step1, x2=x_step2)\n",
+    "init_sharp_interface(test_sc1, phase_idx=phaseIdx + 1, inverse=True, x1=x_step1, x2=x_step2)\n",
+    "plot_status(test_sc1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the plot above, $(\\phi_0, \\phi_1, \\phi_2) = (\\rho, \\phi, \\psi)$. Similarly for the chemical potential.\n",
+    "\n",
+    "Now we collect and visualize the profile of $φ_1$ over time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#test_sc1.run(10000)\n",
+    "#plot_status(test_sc1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1\n",
+      "100\n",
+      "20000\n",
+      "30000\n",
+      "50000\n",
+      "100000\n"
+     ]
+    }
+   ],
+   "source": [
+    "time_steps = [1, 100, 20_000, 30_000, 50_000, 100_000]\n",
+    "visSlice = make_slice[x_step1 - vis_width:x_step1 + vis_width, 0, phaseIdx]\n",
+    "\n",
+    "phiProfiles = {}\n",
+    "maxVelocity = {}\n",
+    "avgVelocity = {}\n",
+    "\n",
+    "for steps in time_steps:\n",
+    "    test_sc1.run(steps - test_sc1.time_steps_run)\n",
+    "    print(test_sc1.time_steps_run)\n",
+    "    phiProfiles[test_sc1.time_steps_run] = test_sc1.phi_slice(visSlice).copy()\n",
+    "    maxVelocity[test_sc1.time_steps_run] = np.max(test_sc1.velocity[:, 0, 0])\n",
+    "    avgVelocity[test_sc1.time_steps_run] = np.average(np.abs(test_sc1.velocity[:, 0, 0]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Calculate values of analytic solution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.phasefield.analytical import analytic_interface_profile\n",
+    "x = np.arange(2 * vis_width) - vis_width\n",
+    "analytic = np.array([analytic_interface_profile(x_i-0.5, alpha) for x_i in x], dtype=np.float64)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "and plot them together with the simulated profiles for different times. \n",
+    "The deviation is measured as $avg(|\\phi_{ref} - \\phi_{analytic}|)$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Deviation at t=      1: 0.16254748219467496\n",
+      "Deviation at t=    100: 0.14368367993309505\n",
+      "Deviation at t=  20000: 0.09427408255750361\n",
+      "Deviation at t=  30000: 0.0861887811110137\n",
+      "Deviation at t=  50000: 0.07382637928550817\n",
+      "Deviation at t= 100000: 0.05507983756095572\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def deviation(profile):\n",
+    "    return np.average(np.abs(profile - analytic))\n",
+    "\n",
+    "\n",
+    "plt.plot(analytic, label='analytic', marker='o')\n",
+    "for t, profile in phiProfiles.items():\n",
+    "    plt.plot(profile, label=\"t=%d\" % (t,), marker='x')\n",
+    "    print(\"Deviation at t={0:>7}: {1}\".format(t, deviation(profile)))\n",
+    "plt.legend()\n",
+    "\n",
+    "# assert against a measured threshold, to make sure code changes do not decrease accuracy\n",
+    "assert deviation(phiProfiles[time_steps[-1]]) < 0.06"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "avg_vels = np.array([avgVelocity[t] for t in time_steps])\n",
+    "max_vels = np.array([maxVelocity[t] for t in time_steps])\n",
+    "plt.semilogy(time_steps, avg_vels, label='avg(|vel|)', marker='x')\n",
+    "plt.semilogy(time_steps, max_vels, label='maximum vel', marker='o')\n",
+    "plt.legend()\n",
+    "plt.xlabel(\"time steps\")\n",
+    "assert maxVelocity[time_steps[-1]] < 1e-6"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2) Advection of 1D interface\n",
+    "\n",
+    "In this test, a constant velocity $u_x$ is initialized. Again, the scenario is fully periodic, so the interface should be advected with constant velocity and because of Galilean invariance the average velocity in the domain should remain constant."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_sc2 = create_three_phase_model(data_handling=SerialDataHandling((width, 1), periodicity=True),\n",
+    "                                    alpha=1,  # interface width\n",
+    "                                    kappa=(0.015, 0.015, 0.015),  # interface energy,  determines surface tension\n",
+    "                                    cahn_hilliard_relaxation_rates=1.0,  # relaxation rate = 1/tau, determines mobilities\n",
+    "                                    hydro_dynamic_relaxation_rate=1.0,  # relaxation rate = 1/tau, determines viscosity\n",
+    "                                    include_rho=include_rho,\n",
+    "                                    solve_cahn_hilliard_with_finite_differences=False,\n",
+    "                                    hydro_lbm_parameters={'force_model': 'edm', 'compressible': True},\n",
+    "                                    dx=1,\n",
+    "                                    dt=1,  # only used if CahnHilliard is solved with finite differences\n",
+    "                                    )\n",
+    "ux = 0.05  # we choose a high velocity here, because then the error is visible faster, with u=0.001 the same\n",
+    "# momentum loss effect is visible, however after more time steps\n",
+    "init_sharp_interface(test_sc2, phase_idx=phaseIdx, inverse=False, x1=x_step1, x2=x_step2)\n",
+    "init_sharp_interface(test_sc2, phase_idx=phaseIdx + 1, inverse=True, x1=x_step1, x2=x_step2)\n",
+    "\n",
+    "test_sc2.data_handling.fill(test_sc2.vel_field_name, ux, value_idx=0)\n",
+    "test_sc2.set_pdf_fields_from_macroscopic_values()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "time_steps = 6_000\n",
+    "t = []\n",
+    "avg_velocity = []\n",
+    "test_sc2.run(1)\n",
+    "while test_sc2.time_steps_run < time_steps:\n",
+    "    avg_velocity.append(np.average(test_sc2.velocity[:, 0, 0]))\n",
+    "    t.append(test_sc2.time_steps_run)\n",
+    "    test_sc2.run(500)\n",
+    "\n",
+    "plt.plot(t, avg_velocity, marker='x')\n",
+    "plt.xlabel(\"time steps\")\n",
+    "plt.ylabel(\"average velocity\");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert (np.abs(np.array(avg_velocity)-ux) < 1e-7).all()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Further test: Disable hydrodynamic LBM i.e. velocity field is unchanged.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_sc3 = create_three_phase_model(data_handling=SerialDataHandling((width, 1), periodicity=True),\n",
+    "                                    alpha=1,  # interface width\n",
+    "                                    kappa=(0.015, 0.015, 0.015),  # interface energy,  determines surface tension\n",
+    "                                    cahn_hilliard_relaxation_rates=1.0,  # relaxation rate = 1/tau, determines mobilities\n",
+    "                                    hydro_dynamic_relaxation_rate=1.0,  # relaxation rate = 1/tau, determines viscosity\n",
+    "                                    include_rho=include_rho,\n",
+    "                                    hydro_lbm_parameters={'force_model': 'edm', 'compressible': True},\n",
+    "                                    )\n",
+    "ux = 0.05\n",
+    "\n",
+    "init_sharp_interface(test_sc3, phase_idx=phaseIdx, inverse=False, x1=x_step1, x2=x_step2)\n",
+    "init_sharp_interface(test_sc3, phase_idx=phaseIdx + 1, inverse=True, x1=x_step1, x2=x_step2)\n",
+    "test_sc3.data_handling.fill(test_sc3.vel_field_name, ux, value_idx=0)\n",
+    "test_sc3.set_pdf_fields_from_macroscopic_values()\n",
+    "\n",
+    "test_sc3.run_hydro_lbm = False  # hydrodynamic LBM is disabled!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sums_over_force = []\n",
+    "while test_sc3.time_steps_run < 5_000:\n",
+    "    sums_over_force.append(np.sum(test_sc3.force[:, 0, 0]))\n",
+    "    test_sc3.run(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.subplot(1, 3, 1)\n",
+    "\n",
+    "plt.plot(sums_over_force)\n",
+    "plt.xlabel(\"t\")\n",
+    "plt.ylabel(\"sum(F)\")\n",
+    "\n",
+    "plt.subplot(1, 3, 2)\n",
+    "plt.plot(test_sc2.force[:, 0, 0])\n",
+    "plt.xlabel('x')\n",
+    "plt.ylabel('F')\n",
+    "\n",
+    "plt.subplot(1, 3, 3)\n",
+    "plt.plot(test_sc2.phi[:, 0, 1]);\n",
+    "plt.xlabel('x')\n",
+    "plt.ylabel('φ_1');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert (np.abs(sums_over_force) < 2e-18).all()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_numerical_1D_nphase_model.ipynb b/lbmpy_tests/phasefield/test_numerical_1D_nphase_model.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..8d6e99606d80de82bd3230d58501f4eaac1727a0
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_numerical_1D_nphase_model.ipynb
@@ -0,0 +1,424 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.scenarios import create_n_phase_model\n",
+    "from pystencils.datahandling import SerialDataHandling\n",
+    "from lbmpy.phasefield.analytical import *\n",
+    "from lbmpy.phasefield.experiments1D import *\n",
+    "from lbmpy.phasefield.analytical import analytic_interface_profile\n",
+    "from functools import partial"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Tanh test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\begin{cases} - c^{2} \\left(- c + 1\\right)^{2} & \\text{for}\\: c > 1 \\vee c < 0 \\\\c^{2} \\left(- c + 1\\right)^{2} & \\text{otherwise} \\end{cases}$$"
+      ],
+      "text/plain": [
+       "⎧  2         2                   \n",
+       "⎪-c ⋅(-c + 1)   for c > 1 ∨ c < 0\n",
+       "⎨                                \n",
+       "⎪ 2         2                    \n",
+       "⎩c ⋅(-c + 1)        otherwise    "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "width = 100\n",
+    "f2 = partial(n_phases_correction_function_sign_switch, beta=1)\n",
+    "\n",
+    "\n",
+    "sc1 = create_n_phase_model(data_handling=SerialDataHandling((width, 1), \n",
+    "                                                            periodicity=True),\n",
+    "                           f2=f2,\n",
+    "                           num_phases=4, alpha=1)\n",
+    "\n",
+    "phaseIdx = 1\n",
+    "init_sharp_interface(sc1, phase_idx=1, inverse=False)\n",
+    "#init_sharp_interface(sc1, phase_idx=0, inverse=True)\n",
+    "\n",
+    "sc1.set_pdf_fields_from_macroscopic_values()\n",
+    "\n",
+    "f2(sp.Symbol(\"c\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAADsAAAAPBAMAAACo4Ko7AAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAVO8Qq5l2zWaJMt0iu0SCRuA9AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAlUlEQVQYGWNgAAHmyM4FWAkGBkZlBgZ2AeY9WAkGk5DPDAxNDAzTsRIMDGxA6SsMDPIG2AiI9BcGhvcC2AiwNPNXoHQyFiIBLM3zk4Fh/RwsxASINFDj+jlYCIg0AcMZgK6SBzkNg4C4/C4DQ78BNgIiDQyWcFCwYBAQaW4BZi0GbAQDq9N3DwbmaSnAKMFCgCMMNwEAUtl2XU+SFbMAAAAASUVORK5CYII=\n",
+      "text/latex": [
+       "$$100000$$"
+      ],
+      "text/plain": [
+       "100000"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if 'is_test_run' in globals():\n",
+    "    sc1.run(1000)\n",
+    "else:\n",
+    "    sc1.run(100_000)\n",
+    "plot_status(sc1)\n",
+    "sc1.time_steps_run"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "alpha = 1\n",
+    "visWidth = 25\n",
+    "x = np.arange(2 * visWidth) - visWidth\n",
+    "analytic = np.array([analytic_interface_profile(x_i - 0.5, alpha) for x_i in x], dtype=np.float64)\n",
+    "\n",
+    "visSlice = make_slice[25 - visWidth:25 + visWidth, 0, phaseIdx]\n",
+    "simulated = sc1.phi_slice(visSlice).copy()\n",
+    "\n",
+    "plt.plot(analytic, label='analytic', marker='o')\n",
+    "plt.plot(simulated, label='simulated', marker='x')\n",
+    "plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert not np.isnan(np.max(simulated))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Phase separation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_phases = 3\n",
+    "f2 = partial(n_phases_correction_function, power=2, beta=0.001)\n",
+    "ll = create_n_phase_model(data_handling=SerialDataHandling((200, 200), \n",
+    "                                                            periodicity=True),\n",
+    "                          f2=f2,\n",
+    "                          surface_tensions=lambda i, j: 0.0025/2 if i != j else 0,\n",
+    "                          num_phases=num_phases, alpha=1,\n",
+    "                          cahn_hilliard_relaxation_rates=1.2,\n",
+    "                          optimization={'target': 'gpu'})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ll.set_concentration(make_slice[:, :], [1/num_phases] * ll.num_order_parameters)\n",
+    "φ_arr = ll.data_handling.cpu_arrays['pf_phi']\n",
+    "φ_arr += (np.random.rand(*φ_arr.shape)-0.5) * 0.2\n",
+    "ll.set_pdf_fields_from_macroscopic_values()\n",
+    "#plt.phase_plot_for_step(ll)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f_bulk, f_if = separate_into_bulk_and_interface(ll.free_energy)\n",
+    "φ = sp.symbols(\"phi_:{}\".format(num_phases))\n",
+    "hessian = sp.hessian(f_bulk, φ)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left ( \\left[\\begin{matrix}-0.0025 & -0.00125 & 0\\\\-0.00125 & -0.0025 & 0\\\\0 & 0 & 0\\end{matrix}\\right], \\quad \\left [ -0.00125, \\quad -0.00375, \\quad 0\\right ]\\right )$$"
+      ],
+      "text/plain": [
+       "⎛⎡-0.0025   -0.00125  0⎤                         ⎞\n",
+       "⎜⎢                     ⎥                         ⎟\n",
+       "⎜⎢-0.00125  -0.0025   0⎥, [-0.00125, -0.00375, 0]⎟\n",
+       "⎜⎢                     ⎥                         ⎟\n",
+       "⎝⎣   0         0      0⎦                         ⎠"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "evaluated_hessian = hessian.subs({ f: 1/num_phases for f in φ})\n",
+    "eigenvalues = [a.evalf()  for a,b in evaluated_hessian.eigenvals().items()]\n",
+    "assert any(a < 0 for a in eigenvalues)\n",
+    "evaluated_hessian, eigenvalues"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ -0.00125, \\quad -0.00375, \\quad 0\\right ]$$"
+      ],
+      "text/plain": [
+       "[-0.00125, -0.00375, 0]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eigenvalues"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 0.28610655901737136 0.38574533140705647\n",
+      "1 0.283708971182857 0.38542379366226814\n",
+      "2 0.27737525687493003 0.3875834110336176\n",
+      "3 0.26743667524125925 0.39169417290369996\n",
+      "4 0.2546379859119067 0.3971101679812658\n",
+      "5 0.23876111373228687 0.4035147117655119\n",
+      "6 0.21954225718115644 0.41081546554212317\n",
+      "7 0.1971502541085478 0.4189466180723286\n",
+      "8 0.17255739304169496 0.4278436664439243\n",
+      "9 0.14760771909058418 0.43743508856384516\n",
+      "10 0.12354706683387104 0.45060517746073125\n",
+      "11 0.10208515792533701 0.4653737116964212\n",
+      "12 0.0845978411284506 0.48178183362228577\n",
+      "13 0.07088806627123448 0.5034911266012848\n",
+      "14 0.060327351687933226 0.5246314660509649\n",
+      "15 0.05218965145635607 0.5443720200667833\n",
+      "16 0.04580494814810558 0.5624163207448445\n",
+      "17 0.04070144973803341 0.5793441950185287\n",
+      "18 0.036188599078823845 0.5963215158797522\n",
+      "19 0.032713912036045 0.6122861731926151\n"
+     ]
+    }
+   ],
+   "source": [
+    "if 'is_test_run' in globals():\n",
+    "    ll.run(1000)\n",
+    "else:\n",
+    "    for i in range(24):\n",
+    "        ll.run(2_000)\n",
+    "        min_φ, max_φ = np.min(ll.phi[:, :]), np.max(ll.phi[:, :])\n",
+    "        print(i, min_φ, max_φ)\n",
+    "        if max_φ > 0.6:\n",
+    "            break\n",
+    "    assert max_φ > 0.6\n",
+    "    ll.time_steps_run"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left ( 0.028002448257740176, \\quad 0.641502234020855\\right )$$"
+      ],
+      "text/plain": [
+       "(0.028002448257740176, 0.641502234020855)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ll.run(4_000)\n",
+    "np.min(ll.phi[:, :]), np.max(ll.phi[:, :])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if 'is_test_run' not in globals():\n",
+    "    plt.phase_plot_for_step(ll)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2) Advection Test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sc2 = create_n_phase_model(data_handling=SerialDataHandling((width, 1), periodicity=True),\n",
+    "                           num_phases=3, alpha=alpha)\n",
+    "\n",
+    "ux = 0.05\n",
+    "phase_idx =1 \n",
+    "sc2.data_handling.fill(sc2.vel_field_name, ux, value_idx=0)\n",
+    "init_sharp_interface(sc2, phase_idx=phase_idx, inverse=False)\n",
+    "\n",
+    "sc2.set_pdf_fields_from_macroscopic_values()\n",
+    "plot_status(sc2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if 'is_test_run' in globals():\n",
+    "    sc2.run(1000)\n",
+    "else:\n",
+    "    sc2.run(10_000)\n",
+    "    assert abs(np.average(sc2.velocity[:, :, 0]) - 0.05) < 1e-10\n",
+    "plot_status(sc2)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_phasefieldstep_direct.ipynb b/lbmpy_tests/phasefield/test_phasefieldstep_direct.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..199495a8075629af5b51a82a79273fdfeb6bf2f8
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_phasefieldstep_direct.ipynb
@@ -0,0 +1,181 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.phasefieldstep_direct import PhaseFieldStepDirect\n",
+    "from lbmpy.phasefield.contact_angle_circle_fitting import liquid_lens_neumann_angles\n",
+    "from pystencils.fd import Diff"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Test of phase field with 4th order FD"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Free energy definition:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_phases = 3\n",
+    "kappa = [0.01, 0.01, 0.01]\n",
+    "penalty_factor = 0.01\n",
+    "domain_size = (40, 40)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$0.005 c_{0}^{2} \\left(- c_{0} + 1\\right)^{2} + 0.005 c_{1}^{2} \\left(- c_{1} + 1\\right)^{2} + 0.005 c_{2}^{2} \\left(- c_{2} + 1\\right)^{2} + 0.01 \\left(- c_{0} - c_{1} - c_{2} + 1\\right)^{2} + 0.005 {\\partial c_{0}}^{2} + 0.005 {\\partial c_{1}}^{2} + 0.005 {\\partial c_{2}}^{2}$$"
+      ],
+      "text/plain": [
+       "        2          2           2          2           2          2            \n",
+       "0.005⋅c₀ ⋅(-c₀ + 1)  + 0.005⋅c₁ ⋅(-c₁ + 1)  + 0.005⋅c₂ ⋅(-c₂ + 1)  + 0.01⋅(-c₀\n",
+       "\n",
+       "               2               2               2               2\n",
+       " - c₁ - c₂ + 1)  + 0.005⋅D(c_0)  + 0.005⋅D(c_1)  + 0.005⋅D(c_2) "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "c = sp.symbols(\"c_:{}\".format(num_phases))\n",
+    "\n",
+    "def f(c):\n",
+    "    return c**2 * (1 - c)**2\n",
+    "\n",
+    "free_energy = sum((kappa[i] / 2) * f( c[i] ) + kappa[i]/2 * (Diff(c[i]))**2 \n",
+    "                  for i in range(num_phases))\n",
+    "free_energy += penalty_factor*(1-sum(c[i] for i in range(num_phases)))**2\n",
+    "\n",
+    "free_energy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Simulation:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "step = PhaseFieldStepDirect(free_energy, c, domain_size)\n",
+    "\n",
+    "# geometric setup\n",
+    "step.set_concentration(make_slice[:, :], [0, 0, 0])\n",
+    "step.set_single_concentration(make_slice[:, 0.5:], phase_idx=0)\n",
+    "step.set_single_concentration(make_slice[:, :0.5], phase_idx=1)\n",
+    "step.set_single_concentration(make_slice[0.25:0.75, 0.25:0.75], phase_idx=2)\n",
+    "\n",
+    "step.set_pdf_fields_from_macroscopic_values()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in range(1000):\n",
+    "    step.time_step()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.phase_plot(step.phi[:, :])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ 107.7400812901783, \\quad 99.91508694115207, \\quad 152.34483176866968\\right ]$$"
+      ],
+      "text/plain": [
+       "[107.7400812901783, 99.91508694115207, 152.34483176866968]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "angles = liquid_lens_neumann_angles(step.phi[:, :])\n",
+    "assert angles[0] > 107\n",
+    "angles"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/phasefield/test_phasefieldstep_direct_boyer.ipynb b/lbmpy_tests/phasefield/test_phasefieldstep_direct_boyer.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..d2f60c97707a64b4d72546c5c199b0af82607ed3
--- /dev/null
+++ b/lbmpy_tests/phasefield/test_phasefieldstep_direct_boyer.ipynb
@@ -0,0 +1,272 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.phasefieldstep_direct import PhaseFieldStepDirect\n",
+    "from lbmpy.phasefield.n_phase_boyer import *\n",
+    "\n",
+    "from lbmpy.phasefield.contact_angle_circle_fitting import liquid_lens_neumann_angles\n",
+    "from pystencils.fd import Diff\n",
+    "\n",
+    "one = sp.sympify(1)\n",
+    "\n",
+    "import pyximport\n",
+    "pyximport.install(language_level=3)\n",
+    "from lbmpy.phasefield.simplex_projection import simplex_projection_2d  # NOQA"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Test of phase field with 4th order FD"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Free energy definition:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "n = 3\n",
+    "domain_size = (150, 150)\n",
+    "\n",
+    "ε = one * 4\n",
+    "penalty_factor = 0.01\n",
+    "stabilization_factor = 10\n",
+    "\n",
+    "#κ = (one,  one/2, one/3, one/4)\n",
+    "κ = (one, one, one, one)\n",
+    "sigma_factor = one / 4 * 67 * 100\n",
+    "σ = sp.ImmutableDenseMatrix(n, n, lambda i,j: sigma_factor* (κ[i] + κ[j]) if i != j else 0 )\n",
+    "c = sp.symbols(\"c_:{}\".format(n))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "α, _ = diffusion_coefficients(σ)\n",
+    "\n",
+    "f = lambda c: c**2 * ( 1 - c ) **2\n",
+    "a, b = compute_ab(f)\n",
+    "\n",
+    "capital_f = capital_f0(c, σ) + correction_g(c, σ) + stabilization_factor * stabilization_term(c, α)\n",
+    "\n",
+    "f_bulk = free_energy_bulk(capital_f, b, ε) \n",
+    "f_if = free_energy_interfacial(c, σ, a, ε)\n",
+    "free_energy = (f_bulk + f_if) / 20000 / 100 + penalty_factor * (one - sum(c))**2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$1.5 \\cdot 10^{-5} c_{0}^{2} c_{1}^{2} c_{2}^{2} + 0.005025 c_{0}^{2} \\left(- c_{0} + 1.0\\right)^{2} + 0.005025 c_{1}^{2} \\left(- c_{1} + 1.0\\right)^{2} + 0.005025 c_{2}^{2} \\left(- c_{2} + 1.0\\right)^{2} - 0.0025125 \\left(c_{0} + c_{1}\\right)^{2} \\left(- c_{0} - c_{1} + 1.0\\right)^{2} - 0.0025125 \\left(c_{0} + c_{2}\\right)^{2} \\left(- c_{0} - c_{2} + 1.0\\right)^{2} - 0.0025125 \\left(c_{1} + c_{2}\\right)^{2} \\left(- c_{1} - c_{2} + 1.0\\right)^{2} + 0.01 \\left(- c_{0} - c_{1} - c_{2} + 1.0\\right)^{2} - 0.005025 {\\partial c_{0}} {\\partial c_{1}} - 0.005025 {\\partial c_{0}} {\\partial c_{2}} - 0.005025 {\\partial c_{1}} {\\partial c_{2}}$$"
+      ],
+      "text/plain": [
+       "         2   2   2              2            2              2            2    \n",
+       "1.5e-5⋅c₀ ⋅c₁ ⋅c₂  + 0.005025⋅c₀ ⋅(-c₀ + 1.0)  + 0.005025⋅c₁ ⋅(-c₁ + 1.0)  + 0\n",
+       "\n",
+       "          2            2                      2                 2             \n",
+       ".005025⋅c₂ ⋅(-c₂ + 1.0)  - 0.0025125⋅(c₀ + c₁) ⋅(-c₀ - c₁ + 1.0)  - 0.0025125⋅\n",
+       "\n",
+       "         2                 2                      2                 2         \n",
+       "(c₀ + c₂) ⋅(-c₀ - c₂ + 1.0)  - 0.0025125⋅(c₁ + c₂) ⋅(-c₁ - c₂ + 1.0)  + 0.01⋅(\n",
+       "\n",
+       "                    2                                                         \n",
+       "-c₀ - c₁ - c₂ + 1.0)  - 0.005025⋅D(c_0)⋅D(c_1) - 0.005025⋅D(c_0)⋅D(c_2) - 0.00\n",
+       "\n",
+       "                  \n",
+       "5025â‹…D(c_1)â‹…D(c_2)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "free_energy.evalf()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Simulation:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "step = PhaseFieldStepDirect(free_energy, c, domain_size)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# geometric setup\n",
+    "step.set_concentration(make_slice[:, :], [0, 0, 0])\n",
+    "step.set_single_concentration(make_slice[:, :], phase_idx=0)\n",
+    "step.set_single_concentration(make_slice[:, :0.5], phase_idx=1)\n",
+    "step.set_single_concentration(make_slice[0.25:0.75, 0.25:0.75], phase_idx=2)\n",
+    "#step.smooth(4)\n",
+    "step.set_pdf_fields_from_macroscopic_values()\n",
+    "\n",
+    "plt.phase_plot(step.phi[:, :])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in range(10):\n",
+    "    step.time_step()\n",
+    "    #simplex_projection_2d(step.data_handling.cpu_arrays[step.phi_field.name])\n",
+    "plt.phase_plot(step.phi[:, :])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f1106c0eda0>,\n",
+       " <matplotlib.lines.Line2D at 0x7f1106c0eef0>,\n",
+       " <matplotlib.lines.Line2D at 0x7f1106b98080>]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(step.phi[25, :])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f1106c3bef0>,\n",
+       " <matplotlib.lines.Line2D at 0x7f11077832e8>,\n",
+       " <matplotlib.lines.Line2D at 0x7f1106c27048>]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(step.phi[15, :])"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
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diff --git a/lbmpy_tests/testImage.png b/lbmpy_tests/testImage.png
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diff --git a/lbmpy_tests/test_boundary_handling.py b/lbmpy_tests/test_boundary_handling.py
new file mode 100644
index 0000000000000000000000000000000000000000..9af8e404fa1d7a3ad03dd4f42524dbf4fc7a3b42
--- /dev/null
+++ b/lbmpy_tests/test_boundary_handling.py
@@ -0,0 +1,33 @@
+import numpy as np
+from pystencils import make_slice, create_data_handling
+from lbmpy.creationfunctions import create_lb_function
+from lbmpy.boundaries.boundaryhandling import LatticeBoltzmannBoundaryHandling
+from lbmpy.boundaries import NoSlip, UBB, StreamInConstant, NeumannByCopy
+from lbmpy.lbstep import LatticeBoltzmannStep
+from lbmpy.geometry import add_box_boundary
+
+
+def test_simple():
+    dh = create_data_handling((10, 5), parallel=False)
+    dh.add_array('pdfs', values_per_cell=9, cpu=True, gpu=True)
+    lb_func = create_lb_function(stencil='D2Q9', compressible=False, relaxation_rate=1.8)
+
+    bh = LatticeBoltzmannBoundaryHandling(lb_func.method, dh, 'pdfs')
+
+    wall = NoSlip()
+    moving_wall = UBB((0.001, 0))
+    bh.set_boundary(wall, make_slice[0, :])
+    bh.set_boundary(wall, make_slice[-1, :])
+    bh.set_boundary(wall, make_slice[:, 0])
+    bh.set_boundary(moving_wall, make_slice[:, -1])
+
+    bh.prepare()
+    bh()
+
+
+def test_exotic_boundaries():
+    step = LatticeBoltzmannStep((50, 50), relaxation_rate=1.8, compressible=False, periodicity=False)
+    add_box_boundary(step.boundary_handling, NeumannByCopy())
+    step.boundary_handling.set_boundary(StreamInConstant(0), make_slice[0, :])
+    step.run(100)
+    assert np.max(step.velocity[:, :, :]) < 1e-13
diff --git a/lbmpy_tests/test_boundary_indexlist_creation.py b/lbmpy_tests/test_boundary_indexlist_creation.py
new file mode 100644
index 0000000000000000000000000000000000000000..f680c474977a9f6ec3fe03596d4a6ef8c208f8e7
--- /dev/null
+++ b/lbmpy_tests/test_boundary_indexlist_creation.py
@@ -0,0 +1,39 @@
+import numpy as np
+import pystencils.boundaries.createindexlist as cil
+from lbmpy.stencils import get_stencil
+
+
+def test_equivalence_cython_python_version():
+    if not cil.cython_funcs_available:
+        return
+
+    stencil_2d = get_stencil("D2Q9")
+    stencil_3d = get_stencil("D3Q19")
+
+    for dtype in [int, np.int16, np.uint32]:
+        fluid_mask = dtype(1)
+        mask = dtype(2)
+        flag_field_2d = np.ones([15, 16], dtype=dtype) * fluid_mask
+        flag_field_3d = np.ones([15, 16, 17], dtype=dtype) * fluid_mask
+
+        flag_field_2d[0, :] = mask
+        flag_field_2d[-1, :] = mask
+        flag_field_2d[7, 7] = mask
+
+        flag_field_3d[0, :, :] = mask
+        flag_field_3d[-1, :, :] = mask
+        flag_field_3d[7, 7, 7] = mask
+
+        result_python_2d = cil._create_boundary_neighbor_index_list_python(flag_field_2d, 1, mask, fluid_mask,
+                                                                           stencil_2d, False)
+
+        result_python_3d = cil._create_boundary_neighbor_index_list_python(flag_field_3d, 1, mask, fluid_mask,
+                                                                           stencil_3d, False)
+
+        result_cython_2d = cil.create_boundary_index_list(flag_field_2d, stencil_2d, mask,
+                                                          fluid_mask, 1, True, False)
+        result_cython_3d = cil.create_boundary_index_list(flag_field_3d, stencil_3d, mask,
+                                                          fluid_mask, 1, True, False)
+
+        np.testing.assert_equal(result_python_2d, result_cython_2d)
+        np.testing.assert_equal(result_python_3d, result_cython_3d)
diff --git a/lbmpy_tests/test_builtin_periodicity.py b/lbmpy_tests/test_builtin_periodicity.py
new file mode 100644
index 0000000000000000000000000000000000000000..cc1eca2fc51015a366dce8cb7dab053e67a34b58
--- /dev/null
+++ b/lbmpy_tests/test_builtin_periodicity.py
@@ -0,0 +1,15 @@
+import numpy as np
+from lbmpy.geometry import get_shear_flow_velocity_field
+from lbmpy.scenarios import create_fully_periodic_flow
+
+
+def test_builtin_periodicity():
+    shape = (16, 16)
+    initial_vel = get_shear_flow_velocity_field(shape, 0.05, 0.1)
+
+    sc_ref = create_fully_periodic_flow(initial_velocity=initial_vel, relaxation_rate=1.8)
+    sc_test = create_fully_periodic_flow(initial_velocity=initial_vel, relaxation_rate=1.8,
+                                         optimization={'builtin_periodicity': (True, True)})
+    sc_ref.run(20)
+    sc_test.run(20)
+    np.testing.assert_almost_equal(sc_ref.velocity[:, :], sc_test.velocity[:, :])
diff --git a/lbmpy_tests/test_chapman_enskog.py b/lbmpy_tests/test_chapman_enskog.py
new file mode 100644
index 0000000000000000000000000000000000000000..47b2cb37e6fbd297f5888f276bee83a2a16c5937
--- /dev/null
+++ b/lbmpy_tests/test_chapman_enskog.py
@@ -0,0 +1,215 @@
+import pytest
+import sympy as sp
+import functools
+from sympy.abc import a, b, x, y, z
+from pystencils.fd import expand_diff_products, combine_diff_products, Diff, \
+    expand_diff_linear, normalize_diff_order
+from pystencils.sympyextensions import multidimensional_sum
+from lbmpy.chapman_enskog.chapman_enskog_higher_order import determine_higher_order_moments, get_solvability_conditions
+from lbmpy.chapman_enskog.chapman_enskog_steady_state import SteadyStateChapmanEnskogAnalysisSRT, \
+    SteadyStateChapmanEnskogAnalysis
+from lbmpy.chapman_enskog.chapman_enskog import ChapmanEnskogAnalysis, LbMethodEqMoments, take_moments, \
+    get_taylor_expanded_lb_equation, chapman_enskog_ansatz
+from lbmpy.relaxationrates import lattice_viscosity_from_relaxation_rate
+from lbmpy.creationfunctions import create_lb_method
+from lbmpy.forcemodels import Guo
+
+
+def test_derivative_expand_collect():
+    original = Diff(x*y*z)
+    result = combine_diff_products(combine_diff_products(expand_diff_products(original))).expand()
+    assert original == result
+
+    original = -3 * y * z * Diff(x) + 2 * x * z * Diff(y)
+    result = expand_diff_products(combine_diff_products(original)).expand()
+    assert original == result
+
+    original = a + b * Diff(x ** 2 * y * z)
+    expanded = expand_diff_products(original)
+    collect_res = combine_diff_products(combine_diff_products(combine_diff_products(expanded)))
+    assert collect_res == original
+
+
+def test_diff_expand_using_linearity():
+    eps = sp.symbols("epsilon")
+    funcs = [a, b]
+    test = Diff(eps * Diff(a+b))
+    result = expand_diff_linear(test, functions=funcs)
+    assert result == eps * Diff(Diff(a)) + eps * Diff(Diff(b))
+
+
+def test_srt():
+    for stencil in ['D2Q9', 'D3Q19', 'D3Q27']:
+        for continuous_eq in (False, True):
+            omega = sp.Symbol("omega")
+            print("Analysing %s, ContMaxwellianConstruction %d" % (stencil, continuous_eq))
+            method = create_lb_method(method='srt', stencil=stencil, compressible=True,
+                                      relaxation_rate=omega, maxwellian_moments=continuous_eq)
+            analysis = ChapmanEnskogAnalysis(method)
+            omega_value = analysis.relaxation_rate_from_kinematic_viscosity(1)[omega]
+            assert omega_value, sp.Rational(2 == 7)
+
+
+@pytest.mark.longrun
+def test_steady_state_silva_paper_comparison():
+    eps, tau, lambda_plus, f = sp.symbols("epsilon tau Lambda f")
+
+    method = create_lb_method(stencil="D3Q19", compressible=False, relaxation_rate=1 / tau,
+                              maxwellian_moments=False)
+    analysis = SteadyStateChapmanEnskogAnalysis(method)
+
+    dim = 3
+    dt = 1
+    expanded_pdf_symbols = analysis.f_syms
+    feq = expanded_pdf_symbols[0]
+    c = analysis.velocity_syms
+    lamb = sp.Symbol("Lambda")
+
+    r = sp.Rational
+
+    def d(arg, *args):
+        """Shortcut to create nested derivatives"""
+        assert arg is not None
+        args = sorted(args, reverse=True, key=lambda e: e.name if isinstance(e, sp.Symbol) else e)
+        res = arg
+        for i in args:
+            res = Diff(res, i)
+        return res
+
+    s = functools.partial(multidimensional_sum, dim=dim)
+
+    rho = sp.Symbol("rho")
+    u = sp.symbols("u_:3")[:dim]
+
+    ref_fs = [
+        # f^0, Eq.17a
+        feq,
+        # f_1 Eq.17b
+        - tau * dt * sum(c[i] * d(feq, i) for i, in s(1)),
+        # f_2 Eq.17c
+        tau * lambda_plus * dt ** 2 * sum(c[i] * c[j] * d(feq, i, j) for i, j in s(2)),
+        # f_3 Eq.17d
+        -tau * (lambda_plus ** 2 - r(1, 12)) * dt ** 3 * \
+        sum(c[i] * c[j] * c[k] * d(feq, i, j, k) for i, j, k in s(3)),
+        # f_4 Eq.17e
+        tau * lambda_plus * (lambda_plus ** 2 - r(1, 6)) * dt ** 4 * \
+        sum(c[i] * c[j] * c[k] * c[l] * d(feq, i, j, k, l) for i, j, k, l in s(4)),
+    ]
+
+    def reference_cont_eq(a1=0, a2=1, order_range=(0, 4)):
+        by_order = {
+            0: sum(d(u[i], i) for i, in s(1)),
+            1: - dt * lambda_plus * (
+                sum(d(u[i] * u[j], i, j) for i, j in s(2)) + sum(d(rho, i, i) / 3 for i, in s(1))),
+            2: dt ** 2 * (lambda_plus ** 2 - r(1, 12)) * sum(d(u[i], i, j, j) for i, j in s(2)),
+            3: -dt ** 3 * lambda_plus * (lambda_plus ** 2 - r(1, 6)) * (
+                sum(d(rho, i, i, j, j) / 3 for i, j in s(2)) +
+                a1 * sum(d(u[k] * u[k], i, i, j, j) for i, j, k in s(3)) +
+                a2 * sum(d(u[j] * u[k], i, i, j, k) for i, j, k in s(3)))
+
+        }
+        return sum(by_order[i] for i in range(*order_range))
+
+    def reference_mom_eq(h=0, stencil_name="D3Q19", order_range=(0, 4)):
+        coefficients = {
+            "D3Q15": (0, 7, -6, r(1, 3), r(8, 3), r(-8, 3)),
+            "D3Q19": (0, -r(7, 2), r(9, 2), r(1, 3), -r(4, 3), r(5, 3)),
+            "D3Q27": (0, 0, 1, r(1, 3), 0, r(1, 3)),
+        }
+        b1, b2, b3, c1, c2, c3 = coefficients[stencil_name]
+        by_order = {
+            0: d(rho, h) / 3 + sum(d(u[i] * u[h], i) for i, in s(1)),
+            1: -r(1, 3) * dt * lamb * (sum(d(u[h], i, i) for i, in s(1)) + 2 * sum(d(u[i], i, h) for i, in s(1))),
+            2: dt ** 2 * (lamb ** 2 - r(1, 12)) * (sum(d(rho, i, i, h) / 3 for i, h in s(2)) +
+                                                   b1 * sum(d(u[k] * u[k], i, i, h) for i, k in s(2)) +
+                                                   b2 * sum(d(u[j] * u[h], i, i, j) for i, j in s(2)) +
+                                                   b3 * sum(d(u[i] * u[j], i, j, h) for i, j in s(2))),
+            3: -dt ** 3 * lamb * (lamb ** 2 - r(1, 6)) * (c1 * sum(d(u[h], i, i, j, j) for i, j in s(2)) +
+                                                          c1 * sum(d(u[k], k, j, j, h) for j, k in s(2)) +
+                                                          c2 * sum(d(u[j], i, i, j, h) for i, j in s(2)) +
+                                                          c3 * sum(d(u[i], i, j, j, h) for i, j in s(2)))
+
+        }
+        result = sum(by_order[i] for i in range(*order_range))
+        return result
+
+    # Check scale hierarchy - Eq.17 in Silva Paper
+    for f_idx in range(1, 5):
+        print("Checking f_idx", f_idx)
+        ref = ref_fs[f_idx].subs(lamb, tau - r(1, 2))
+        diff = analysis.pdf_hierarchy[f_idx].subs(analysis.collision_op_sym, 1 / tau) - ref
+        diff = diff.expand().subs(analysis.force_sym, 0)
+        diff = normalize_diff_order(diff)
+        assert diff == 0
+
+    # Check continuity equation
+    for order in range(0, 3):
+        print("Checking continuity order", order)
+        reference = reference_cont_eq(order_range=(order, order + 1)).subs(lamb, tau - r(1, 2))
+        diff = reference + analysis.get_continuity_equation(order) / tau
+        diff = normalize_diff_order(diff)
+        assert diff.expand() == 0
+
+    # Check momentum transport equation
+    for order in range(0, 2):
+        print("Checking momentum order", order)
+        coord = 0
+        reference = reference_mom_eq(coord, order_range=(order, order + 1)).subs(lamb, tau - r(1, 2))
+        diff = reference + analysis.get_momentum_equation(only_order=order)[coord] / tau
+        diff = normalize_diff_order(diff)
+        assert diff.expand() == 0
+
+
+def test_higher_order_moment_computation():
+    """In chapman_enskog_higher_order.py there are some functions to generalize the std Chapman Enskog expansion
+    These are not used by the Chapman Enskog class yet."""
+    method = create_lb_method(stencil='D2Q9', method='trt', maxwellian_moments=False)
+    mom_comp = LbMethodEqMoments(method)
+    dim = method.dim
+    order = 2
+
+    taylored_lb_eq = get_taylor_expanded_lb_equation(taylor_order=order, dim=dim, shift=True)
+    eps_dict = chapman_enskog_ansatz(taylored_lb_eq,
+                                     time_derivative_orders=(1, 3),
+                                     spatial_derivative_orders=(1, 2),
+                                     pdfs=(['f', 0, order + 1], ['\\Omega f', 1, order + 1]))
+    higher_order_moments = determine_higher_order_moments(eps_dict, method.relaxation_rates, mom_comp,
+                                                          dim, order=order)[2]
+    solvability_conditions = get_solvability_conditions(dim=method.dim, order=order)
+    continuity_eq = mom_comp.substitute(take_moments(eps_dict[1])).subs(solvability_conditions)
+
+    u = sp.symbols("u_:2")
+    rho, t = sp.symbols("rho t")
+    assert continuity_eq == Diff(rho, t, 1) + Diff(u[0], 0, 1) + Diff(u[1], 1, 1)
+
+    std_ce_analysis = ChapmanEnskogAnalysis(method)
+    for k, v in std_ce_analysis.higher_order_moments.items():
+        assert sp.expand(higher_order_moments[k] - v) == 0
+
+
+def test_steady_state():
+    rr = sp.symbols("omega")
+    method = create_lb_method(stencil='D2Q9', method='srt', relaxation_rate=rr)
+    a1 = SteadyStateChapmanEnskogAnalysis(method, order=2)
+    a2 = SteadyStateChapmanEnskogAnalysisSRT(method, order=2)
+
+    a1.get_pdf_hierarchy(0)
+
+    def compare(eq1, eq2):
+        eq1 = (eq1 * -rr).subs(sp.symbols("epsilon"), 1)
+        assert sp.expand(eq1 - eq2) == 0
+
+    compare(a1.get_continuity_equation(), a2.get_continuity_equation(0) + a2.get_continuity_equation(1))
+    for d in range(2):
+        compare(a1.get_momentum_equation()[d],
+                a2.get_momentum_equation(d, 0) + a2.get_momentum_equation(d, 1))
+
+    viscosities = a2.determine_viscosities(0)
+    print("viscosities", viscosities)
+    nu = sp.symbols("nu")
+    assert sp.cancel(viscosities[nu] - lattice_viscosity_from_relaxation_rate(rr)) == 0
+
+    with_force = SteadyStateChapmanEnskogAnalysis(method, order=2, force_model_class=Guo)
+    momentum_eq_with_force = sp.expand(with_force.get_momentum_equation(0)[0] * rr)
+    momentum_eq_without_force = sp.expand(a1.get_momentum_equation(0)[0] * rr)
+    assert momentum_eq_with_force - sp.symbols("a_0", commutative=False) == momentum_eq_without_force
diff --git a/lbmpy_tests/test_code_hashequivalence.py b/lbmpy_tests/test_code_hashequivalence.py
new file mode 100644
index 0000000000000000000000000000000000000000..39ba4d7871bcadcdb58815f026526e9f0410cb1b
--- /dev/null
+++ b/lbmpy_tests/test_code_hashequivalence.py
@@ -0,0 +1,25 @@
+from hashlib import sha256
+from pystencils.backends.cbackend import generate_c
+from pystencils.llvm.llvmjit import generate_llvm
+from lbmpy.creationfunctions import create_lb_ast
+
+
+def test_hash_equivalence():
+    """
+    This test should ensure that if the Python interpreter is called multiple times to generated the same method
+    exactly the same code (not only functionally equivalent code) should be produced.
+    Due to undefined order in sets and dicts this may no be the case.
+    """
+    ref_value = "461f0ced7afa3d0499d5bd90d87fcdb0cfc6a5f56ee9fa4f13386c15b8484ca2"
+    ast = create_lb_ast(stencil='D3Q19', method='srt', optimization={'openmp': False})
+    code = generate_c(ast)
+    hash_value = sha256(code.encode()).hexdigest()
+    assert hash_value == ref_value
+
+
+def test_hash_equivalence_llvm():
+    ref_value = "52dad2fb2c144062b524ab0b514115a1a1b22d7e7f1c8e3d0f3169e08954f8ea"
+    ast = create_lb_ast(stencil='D3Q19', method='srt', optimization={'target': 'llvm'})
+    code = generate_llvm(ast)
+    hash_value = sha256(str(code).encode()).hexdigest()
+    assert hash_value == ref_value
diff --git a/lbmpy_tests/test_conserved_quantity_relaxation_invariance.py b/lbmpy_tests/test_conserved_quantity_relaxation_invariance.py
new file mode 100644
index 0000000000000000000000000000000000000000..d5b6763901a0ce17f351fef7300f46da1e99deed
--- /dev/null
+++ b/lbmpy_tests/test_conserved_quantity_relaxation_invariance.py
@@ -0,0 +1,106 @@
+"""
+The update equations should not change if a relaxation rate of a conserved quantity (density/velocity)
+changes. This test checks that for moment-based methods
+"""
+import pytest
+import sympy as sp
+from copy import copy
+from lbmpy.methods.creationfunctions import create_srt, create_trt, create_trt_kbc, RelaxationInfo
+from lbmpy.methods.cumulantbased import CumulantBasedLbMethod
+from lbmpy.methods.momentbased import MomentBasedLbMethod
+from lbmpy.simplificationfactory import create_simplification_strategy
+from lbmpy.stencils import get_stencil
+from lbmpy.moments import MOMENT_SYMBOLS
+
+
+def __change_relaxation_rate_of_conserved_moments(method, new_relaxation_rate=sp.Symbol("test_omega")):
+    conserved_moments = (sp.Rational(1, 1),) + MOMENT_SYMBOLS[:method.dim]
+
+    rr_dict = copy(method.relaxation_info_dict)
+    for conserved_moment in conserved_moments:
+        prev = rr_dict[conserved_moment]
+        rr_dict[conserved_moment] = RelaxationInfo(prev.equilibrium_value, new_relaxation_rate)
+
+    if isinstance(method, MomentBasedLbMethod):
+        changed_method = MomentBasedLbMethod(method.stencil, rr_dict, method.conserved_quantity_computation,
+                                             force_model=method.force_model)
+    elif isinstance(method, CumulantBasedLbMethod):
+        changed_method = CumulantBasedLbMethod(method.stencil, rr_dict, method.conserved_quantity_computation,
+                                               force_model=method.force_model)
+    else:
+        raise ValueError("Not a moment or cumulant-based method")
+
+    return changed_method
+
+
+def check_for_collision_rule_equivalence(collision_rule1, collision_rule2):
+    collision_rule1 = collision_rule1.new_without_subexpressions()
+    collision_rule2 = collision_rule2.new_without_subexpressions()
+    for eq1, eq2 in zip(collision_rule1.main_assignments, collision_rule2.main_assignments):
+        diff = sp.cancel(sp.expand(eq1.rhs - eq2.rhs))
+        assert diff == 0
+
+
+def check_method_equivalence(m1, m2, do_simplifications):
+    cr1 = m1.get_collision_rule()
+    cr2 = m2.get_collision_rule()
+    if do_simplifications:
+        cr1 = create_simplification_strategy(m1)(cr1)
+        cr2 = create_simplification_strategy(m2)(cr2)
+    check_for_collision_rule_equivalence(cr1, cr2)
+
+
+@pytest.mark.longrun
+def test_srt():
+    for stencil_name in ('D2Q9',):
+        for cumulant in (False, True):
+            stencil = get_stencil(stencil_name)
+            original_method = create_srt(stencil, sp.Symbol("omega"), cumulant=cumulant, compressible=True,
+                                         maxwellian_moments=True)
+            changed_method = __change_relaxation_rate_of_conserved_moments(original_method)
+
+            check_method_equivalence(original_method, changed_method, True)
+            check_method_equivalence(original_method, changed_method, False)
+
+
+def test_srt_short():
+    stencil = get_stencil("D2Q9")
+    original_method = create_srt(stencil, sp.Symbol("omega"), compressible=True,
+                                 maxwellian_moments=True)
+    changed_method = __change_relaxation_rate_of_conserved_moments(original_method)
+
+    check_method_equivalence(original_method, changed_method, True)
+    check_method_equivalence(original_method, changed_method, False)
+
+
+@pytest.mark.longrun
+def test_trt():
+    for stencil_name in ("D2Q9", "D3Q19", "D3Q27"):
+        for continuous_moments in (False, True):
+            stencil = get_stencil(stencil_name)
+            original_method = create_trt(stencil, sp.Symbol("omega1"), sp.Symbol("omega2"),
+                                         maxwellian_moments=continuous_moments)
+            changed_method = __change_relaxation_rate_of_conserved_moments(original_method)
+
+            check_method_equivalence(original_method, changed_method, True)
+            check_method_equivalence(original_method, changed_method, False)
+
+
+@pytest.mark.longrun
+def test_trt_kbc_long():
+    for dim in (2, 3):
+        for method_name in ("KBC-N1", "KBC-N2", "KBC-N3", "KBC-N4"):
+            original_method = create_trt_kbc(dim, sp.Symbol("omega1"), sp.Symbol("omega2"), method_name=method_name,
+                                             maxwellian_moments=False)
+            changed_method = __change_relaxation_rate_of_conserved_moments(original_method)
+            check_method_equivalence(original_method, changed_method, True)
+            check_method_equivalence(original_method, changed_method, False)
+
+
+def test_trt_kbc_short():
+    for dim, method_name in [(2, "KBC-N2")]:
+        original_method = create_trt_kbc(dim, sp.Symbol("omega1"), sp.Symbol("omega2"), method_name=method_name,
+                                         maxwellian_moments=False)
+        changed_method = __change_relaxation_rate_of_conserved_moments(original_method)
+        check_method_equivalence(original_method, changed_method, True)
+        check_method_equivalence(original_method, changed_method, False)
diff --git a/lbmpy_tests/test_cpu_gpu_equivalence.py b/lbmpy_tests/test_cpu_gpu_equivalence.py
new file mode 100644
index 0000000000000000000000000000000000000000..f1749c9f20800e9a8942cf004a16dc50f7efbd57
--- /dev/null
+++ b/lbmpy_tests/test_cpu_gpu_equivalence.py
@@ -0,0 +1,114 @@
+import pytest
+import numpy as np
+from copy import deepcopy
+from lbmpy.scenarios import create_channel
+
+
+def run_equivalence_test(scenario_creator, time_steps=13, **params):
+    print("Scenario", params)
+    params['optimization']['target'] = 'cpu'
+    cpu_scenario = scenario_creator(**params)
+    params['optimization']['target'] = 'gpu'
+    gpu_scenario = scenario_creator(**params)
+
+    cpu_scenario.run(time_steps)
+    gpu_scenario.run(time_steps)
+
+    max_vel_error = np.max(np.abs(cpu_scenario.velocity_slice() - gpu_scenario.velocity_slice()))
+    max_rho_error = np.max(np.abs(cpu_scenario.density_slice() - gpu_scenario.density_slice()))
+
+    np.testing.assert_allclose(max_vel_error, 0, atol=1e-14)
+    np.testing.assert_allclose(max_rho_error, 0, atol=1e-14)
+
+
+def test_force_driven_channel_short():
+    default = {
+        'scenario_creator': create_channel,
+        'domain_size': (32, 32),
+        'relaxation_rates': [1.95, 1.9, 1.92],
+        'method': 'mrt3',
+        'pressure_difference': 0.001,
+        'optimization': {},
+    }
+    scenarios = []
+
+    # Different methods
+    for ds, method, compressible, block_size, field_layout in [((17, 12), 'srt', False, (12, 4), 'reverse_numpy'),
+                                                               ((18, 20), 'mrt3', True, (4, 2), 'zyxf'),
+                                                               ((7, 11, 18), 'trt', False, False, 'numpy')]:
+        params = deepcopy(default)
+        if block_size is not False:
+            params['optimization'].update({
+                'gpu_indexing_params': {'block_size': block_size}
+            })
+        else:
+            params['optimization']['gpu_indexing'] = 'line'
+
+        params['domain_size'] = ds
+        params['method'] = method
+        params['compressible'] = compressible
+        params['optimization']['field_layout'] = field_layout
+        scenarios.append(params)
+
+    for scenario in scenarios:
+        run_equivalence_test(**scenario)
+
+
+@pytest.mark.longrun
+def test_force_driven_channel():
+    default = {
+        'scenario_creator': create_channel,
+        'domain_size': (32, 32),
+        'relaxation_rates': [1.95, 1.9, 1.92],
+        'method': 'mrt3',
+        'pressure_difference': 0.001,
+        'optimization': {},
+    }
+
+    scenarios = []
+
+    # Different methods
+    for method in ('srt', 'mrt3'):
+        for compressible in (True, False):
+            params = deepcopy(default)
+            params['optimization'].update({
+                'gpu_indexing_params': {'block_size': (16, 16)}
+            })
+            params['method'] = method
+            params['compressible'] = compressible
+            scenarios.append(params)
+
+    # Blocked indexing with different block sizes
+    for block_size in ((16, 16), (8, 16), (4, 2)):
+        params = deepcopy(default)
+        params['method'] = 'mrt3'
+        params['compressible'] = True
+        params['optimization'].update({
+            'gpu_indexing': 'block',
+            'gpu_indexing_params': {'block_size': block_size}
+        })
+        scenarios.append(params)
+
+    # Line wise indexing
+    params = deepcopy(default)
+    params['optimization']['gpu_indexing'] = 'line'
+    scenarios.append(params)
+
+    # Different field layouts
+    for field_layout in ('numpy', 'reverse_numpy', 'zyxf'):
+        for fixed_size in (False, True):
+            params = deepcopy(default)
+            params['optimization'].update({
+                'gpu_indexing_params': {'block_size': (16, 16)}
+            })
+            if fixed_size:
+                params['optimization']['field_size'] = params['domain_size']
+            else:
+                params['optimization']['field_size'] = None
+
+            params['optimization']['field_layout'] = field_layout
+            scenarios.append(params)
+
+    print("Testing %d scenarios" % (len(scenarios),))
+    for scenario in scenarios:
+        run_equivalence_test(**scenario)
diff --git a/lbmpy_tests/test_cumulant_methods.py b/lbmpy_tests/test_cumulant_methods.py
new file mode 100644
index 0000000000000000000000000000000000000000..8a700d5f97a248b912ab0ceeeb35818db2167c75
--- /dev/null
+++ b/lbmpy_tests/test_cumulant_methods.py
@@ -0,0 +1,28 @@
+from lbmpy.methods import create_srt
+from lbmpy.stencils import get_stencil
+from pystencils.sympyextensions import remove_higher_order_terms
+
+
+def test_weights():
+    for stencil_name in ('D2Q9', 'D3Q19', 'D3Q27'):
+        stencil = get_stencil(stencil_name)
+        cumulant_method = create_srt(stencil, 1, cumulant=True, compressible=True,
+                                     maxwellian_moments=True)
+        moment_method = create_srt(stencil, 1, cumulant=False, compressible=True,
+                                   maxwellian_moments=True)
+        assert cumulant_method.weights == moment_method.weights
+
+
+def test_equilibrium_equivalence():
+    for stencil_name in ('D2Q9', 'D3Q19', 'D3Q27'):
+        stencil = get_stencil(stencil_name)
+        cumulant_method = create_srt(stencil, 1, cumulant=True, compressible=True,
+                                     maxwellian_moments=True)
+        moment_method = create_srt(stencil, 1, cumulant=False, compressible=True,
+                                   maxwellian_moments=True)
+        moment_eq = moment_method.get_equilibrium()
+        cumulant_eq = cumulant_method.get_equilibrium()
+        u = moment_method.first_order_equilibrium_moment_symbols
+        for mom_eq, cum_eq in zip(moment_eq.main_assignments, cumulant_eq.main_assignments):
+            diff = cum_eq.rhs - mom_eq.rhs
+            assert remove_higher_order_terms(diff.expand(), order=2, symbols=u) == 0
diff --git a/lbmpy_tests/test_cumulants.py b/lbmpy_tests/test_cumulants.py
new file mode 100644
index 0000000000000000000000000000000000000000..8fa17c1cfbd46b4e02c70b91093111ee056d3c1e
--- /dev/null
+++ b/lbmpy_tests/test_cumulants.py
@@ -0,0 +1,93 @@
+from lbmpy.creationfunctions import create_lb_method
+from lbmpy.moments import discrete_moment, exponents_to_polynomial_representations, \
+    exponent_to_polynomial_representation
+from lbmpy.stencils import get_stencil
+from lbmpy.cumulants import *
+
+
+def test_cumulants_from_pdfs():
+    """
+    Tests if the following transformations are equivalent:
+      - directly pdfs to cumulant
+      - indirect pdfs -> raw moments -> cumulants
+    """
+    stencil = get_stencil("D2Q9")
+    dim = len(stencil[0])
+    indices = moments_up_to_component_order(2, dim=dim)
+
+    pdf_symbols = sp.symbols("f_:%d" % (len(stencil),))
+    direct_version = cumulants_from_pdfs(stencil, pdf_symbols=pdf_symbols, cumulant_indices=indices)
+    polynomial_moment_indices = exponents_to_polynomial_representations(indices)
+    direct_version2 = cumulants_from_pdfs(stencil, pdf_symbols=pdf_symbols, cumulant_indices=polynomial_moment_indices)
+    for idx, value in direct_version.items():
+        poly = exponent_to_polynomial_representation(idx)
+        assert direct_version2[poly] == value
+
+    moment_dict = {idx: discrete_moment(pdf_symbols, idx, stencil) for idx in indices}
+    indirect_version = {idx: cumulant_as_function_of_raw_moments(idx, moment_dict) for idx in indices}
+
+    for idx in indices:
+        assert sp.simplify(direct_version[idx] - indirect_version[idx]) == 0
+
+
+def test_raw_moment_to_cumulant_transformation():
+    """Transforms from raw moments to cumulants and back, then checks for identity"""
+    for stencil in [get_stencil("D2Q9"), get_stencil("D3Q27")]:
+        dim = len(stencil[0])
+        indices = moments_up_to_component_order(2, dim=dim)
+
+        symbol_format = "m_%d_%d_%d" if dim == 3 else "m_%d_%d"
+        moment_symbols = {idx: sp.Symbol(symbol_format % idx) for idx in indices}
+
+        forward = {idx: cumulant_as_function_of_raw_moments(idx, moments_dict=moment_symbols)
+                   for idx in indices}
+        backward = {idx: sp.simplify(raw_moment_as_function_of_cumulants(idx, cumulants_dict=forward))
+                    for idx in indices}
+        assert backward == moment_symbols
+
+
+def test_central_moment_to_cumulant_transformation():
+    """Transforms from central moments to cumulants and back, then checks for identity"""
+    for stencil in [get_stencil("D2Q9"), get_stencil("D3Q27")]:
+        dim = len(stencil[0])
+        indices = moments_up_to_component_order(2, dim=dim)
+
+        symbol_format = "m_%d_%d_%d" if dim == 3 else "m_%d_%d"
+        moment_symbols = {idx: sp.Symbol(symbol_format % idx) for idx in indices}
+
+        forward = {idx: cumulant_as_function_of_central_moments(idx, moments_dict=moment_symbols)
+                   for idx in indices}
+        backward = {idx: sp.simplify(central_moment_as_function_of_cumulants(idx, cumulants_dict=forward))
+                    for idx in indices}
+        for idx in indices:
+            if sum(idx) == 1:
+                continue
+            assert backward[idx] == moment_symbols[idx]
+
+
+def test_collision_rule():
+    cumulant_method = create_lb_method(stencil='D2Q9', compressible=True, cumulant=True, relaxation_rate=1.5)
+    cumulant_method.set_first_moment_relaxation_rate(1.5)
+    assert cumulant_method.force_model is None
+    assert cumulant_method.zeroth_order_equilibrium_moment_symbol == sp.symbols("rho")
+    assert cumulant_method.first_order_equilibrium_moment_symbols == sp.symbols("u_:2")
+    assert all(e.relaxation_rate == 1.5 for e in cumulant_method.relaxation_info_dict.values())
+    cumulant_method.get_equilibrium_terms()
+
+    cr1 = cumulant_method.get_collision_rule(moment_subexpressions=True, post_collision_subexpressions=True,
+                                             pre_collision_subexpressions=True)
+    cr2 = cumulant_method.get_collision_rule(moment_subexpressions=False, post_collision_subexpressions=False,
+                                             pre_collision_subexpressions=False)
+    cr1_inserted = cr1.new_without_subexpressions()
+    cr2_inserted = cr2.new_without_subexpressions()
+
+    t = cr1_inserted.main_assignments[8].rhs - cr2_inserted.main_assignments[8].rhs
+    assert t == 0
+
+    html = cumulant_method._repr_html_()
+    assert 'Cumulant' in html
+
+
+def test_cumulants_from_pdf():
+    res = cumulants_from_pdfs(get_stencil("D2Q9"))
+    assert res[(0, 0)] == sp.log(sum(sp.symbols("f_:9")))
diff --git a/lbmpy_tests/test_entropic.py b/lbmpy_tests/test_entropic.py
new file mode 100644
index 0000000000000000000000000000000000000000..b08b49af129d93edf449ecbc9d25a8a77e2f2398
--- /dev/null
+++ b/lbmpy_tests/test_entropic.py
@@ -0,0 +1,32 @@
+import numpy as np
+import sympy as sp
+from lbmpy.forcemodels import Guo
+from lbmpy.methods.entropic_eq_srt import create_srt_entropic
+from lbmpy.scenarios import create_lid_driven_cavity
+from lbmpy.stencils import get_stencil
+
+
+def test_entropic_methods():
+    sc_kbc = create_lid_driven_cavity((20, 20), method='trt-kbc-n4', relaxation_rate=1.9999,
+                                      entropic_newton_iterations=3, entropic=True, compressible=True,
+                                      force=(-1e-10, 0))
+
+    sc_srt = create_lid_driven_cavity((40, 40), relaxation_rate=1.9999, lid_velocity=0.05, compressible=True,
+                                      force=(-1e-10, 0))
+
+    sc_entropic = create_lid_driven_cavity((40, 40), method='entropic-srt', relaxation_rate=1.9999,
+                                           lid_velocity=0.05, compressible=True, force=(-1e-10, 0))
+
+    sc_srt.run(1000)
+    sc_kbc.run(1000)
+    sc_entropic.run(1000)
+    assert np.isnan(np.max(sc_srt.velocity[:, :]))
+    assert np.isfinite(np.max(sc_kbc.velocity[:, :]))
+    assert np.isfinite(np.max(sc_entropic.velocity[:, :]))
+
+
+def test_entropic_srt():
+    stencil = get_stencil("D2Q9")
+    method = create_srt_entropic(stencil, 1.8, Guo((0, 1e-6)), True)
+    assert method.zeroth_order_equilibrium_moment_symbol == sp.symbols("rho")
+    assert method.first_order_equilibrium_moment_symbols == sp.symbols("u_:2")
diff --git a/lbmpy_tests/test_esotwist_visualization.ipynb b/lbmpy_tests/test_esotwist_visualization.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..c55a894d071e519451964b94f60a5b833aab4819
--- /dev/null
+++ b/lbmpy_tests/test_esotwist_visualization.ipynb
@@ -0,0 +1,135 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.fieldaccess import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Esoteric Twist\n",
+    "\n",
+    "*\"Esoteric Twist: An Efficient in-Place Streaming Algorithmus for the Lattice Boltzmann Method on Massively Parallel Hardware\" (2017) Geier Schönherr*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "eso_odd = EsoTwistOddTimeStepAccessor()\n",
+    "visualize_pdf_field_accessor(eso_odd)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "eso_even = EsoTwistEvenTimeStepAccessor()\n",
+    "visualize_pdf_field_accessor(eso_even)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# AA Pattern\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "aa_odd = AAOddTimeStepAccessor()\n",
+    "visualize_pdf_field_accessor(aa_odd)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "aa_even = AAEvenTimeStepAccessor()\n",
+    "visualize_pdf_field_accessor(aa_even)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/test_field_access_pattern_visualization.ipynb b/lbmpy_tests/test_field_access_pattern_visualization.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..a934222b5981d03f50cd716be80ed291d34e04a6
--- /dev/null
+++ b/lbmpy_tests/test_field_access_pattern_visualization.ipynb
@@ -0,0 +1,109 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.fieldaccess import *\n",
+    "from lbmpy.session import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2-field stream pull"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f568e420940>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "visualize_pdf_field_accessor(StreamPullTwoFieldsAccessor)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## AA-Pattern"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f568e7e71d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "visualize_pdf_field_accessor(AAOddTimeStepAccessor)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f568e640e48>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "visualize_pdf_field_accessor(AAEvenTimeStepAccessor)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/test_float_kernel.py b/lbmpy_tests/test_float_kernel.py
new file mode 100644
index 0000000000000000000000000000000000000000..0099f7876442c64e9e7defc71c1b48621fe998a0
--- /dev/null
+++ b/lbmpy_tests/test_float_kernel.py
@@ -0,0 +1,20 @@
+from pystencils import show_code
+from lbmpy.scenarios import create_lid_driven_cavity
+from lbmpy.creationfunctions import create_lb_function
+
+
+def test_creation():
+    """Simple test that makes sure that only float variables are created"""
+
+    func = create_lb_function(method='srt', relaxation_rate=1.5,
+                              optimization={'double_precision': False})
+    code = str(show_code(func.ast))
+    assert 'double' not in code
+
+
+def test_scenario():
+    sc = create_lid_driven_cavity((16, 16, 8), relaxation_rate=1.5,
+                                  optimization={'double_precision': False})
+    sc.run(1)
+    code_str = str(show_code(sc.ast))
+    assert 'double' not in code_str
diff --git a/lbmpy_tests/test_force_on_boundary.py b/lbmpy_tests/test_force_on_boundary.py
new file mode 100644
index 0000000000000000000000000000000000000000..13e9b589a0e186a5ac98bb60814beb902ebac98d
--- /dev/null
+++ b/lbmpy_tests/test_force_on_boundary.py
@@ -0,0 +1,35 @@
+import numpy as np
+from pystencils import make_slice
+from lbmpy.boundaries import NoSlip, UBB
+from lbmpy.scenarios import create_channel
+
+try:
+    import waLBerla as wLB
+except ImportError:
+    wLB = None
+
+
+def calculate_force(step, obstacle):
+    bh = step.boundary_handling
+    bh.set_boundary(obstacle, make_slice[0.3:0.4, 0:0.5])
+    step.run(100)
+    return bh.force_on_boundary(obstacle)
+
+
+def test_force_on_boundary():
+    results = []
+    domain_size = (80, 30)
+
+    boundaries = [NoSlip('obstacle_noslip'),
+                  UBB((0,) * len(domain_size), name='obstacle_UBB')]
+
+    for parallel in (False, True) if wLB else (False,):
+        for boundary_obj in boundaries:
+            print("Testing parallel %d, boundary %s" % (parallel, boundary_obj.name))
+            step = create_channel(domain_size, force=1e-5, relaxation_rate=1.5, parallel=parallel, force_model='buick')
+            force = calculate_force(step, boundary_obj)
+            print("  -> force = ", force)
+            results.append(force)
+
+    for res in results[1:]:
+        np.testing.assert_almost_equal(results[0], res)
diff --git a/lbmpy_tests/test_geometry_setup_serial.py b/lbmpy_tests/test_geometry_setup_serial.py
new file mode 100644
index 0000000000000000000000000000000000000000..28bcff8192bfd20bf5112dd5d7a3b7dfe3a05f0b
--- /dev/null
+++ b/lbmpy_tests/test_geometry_setup_serial.py
@@ -0,0 +1,67 @@
+import numpy as np
+import os
+
+from lbmpy.lbstep import LatticeBoltzmannStep
+from pystencils.slicing import make_slice
+from lbmpy.geometry import add_pipe_walls, add_black_and_white_image
+from lbmpy.boundaries import NoSlip
+
+
+def test_pipe():
+    """Ensures that pipe can be set up in 2D, 3D, with constant and callback diameter
+    No tests are done that geometry is indeed correct"""
+
+    def diameter_callback(x, domain_shape):
+        d = domain_shape[1]
+        y = np.ones_like(x) * d
+
+        y[x > 0.5 * domain_shape[0]] = int(0.3 * d)
+        return y
+
+    plot = False
+    for domain_size in [(30, 10, 10), (30, 10)]:
+        for diameter in [5, 10, diameter_callback]:
+            sc = LatticeBoltzmannStep(domain_size=domain_size, method='srt', relaxation_rate=1.9,
+                                      optimization={})
+            add_pipe_walls(sc.boundary_handling, diameter)
+            if plot:
+                import lbmpy.plot2d as plt
+                from pystencils.slicing import make_slice
+                if len(domain_size) == 2:
+                    plt.boundary_handling(sc.boundary_handling)
+                    plt.title("2D, diameter=%s" % (str(diameter,)))
+                    plt.show()
+                elif len(domain_size) == 3:
+                    plt.subplot(1, 2, 1)
+                    plt.boundary_handling(sc.boundary_handling, make_slice[0.5, :, :])
+                    plt.title("3D, diameter=%s" % (str(diameter,)))
+                    plt.subplot(1, 2, 2)
+                    plt.boundary_handling(sc.boundary_handling, make_slice[:, 0.5, :])
+                    plt.title("3D, diameter=%s" % (str(diameter, )))
+                    plt.show()
+
+
+def get_test_image_path():
+    script_file = os.path.realpath(__file__)
+    script_dir = os.path.dirname(script_file)
+    return os.path.join(script_dir, 'testImage.png')
+
+
+def test_image():
+    sc = LatticeBoltzmannStep(domain_size=(50, 40), method='srt', relaxation_rate=1.9,
+                              optimization={})
+    add_black_and_white_image(sc.boundary_handling, get_test_image_path(), keep_aspect_ratio=True)
+
+
+def test_slice_mask_combination():
+    sc = LatticeBoltzmannStep(domain_size=(30, 30), method='srt', relaxation_rate=1.9,
+                              optimization={})
+
+    def callback(*coordinates):
+        x = coordinates[0]
+        print("x", coordinates[0][:, 0])
+        print("y", coordinates[1][0, :])
+        print(x.shape)
+        return np.ones_like(x, dtype=np.bool)
+
+    sc.boundary_handling.set_boundary(NoSlip(), make_slice[6:7, -1], callback)
diff --git a/lbmpy_tests/test_gpu_block_size_limiting.py b/lbmpy_tests/test_gpu_block_size_limiting.py
new file mode 100644
index 0000000000000000000000000000000000000000..d91189eaa8831acc74543f6823f276c297cd60a3
--- /dev/null
+++ b/lbmpy_tests/test_gpu_block_size_limiting.py
@@ -0,0 +1,14 @@
+from lbmpy.creationfunctions import create_lb_ast
+
+
+def test_gpu_block_size_limiting():
+    too_large = 2048*2048
+    opt = {'target': 'gpu', 'gpu_indexing_params': {'block_size': (too_large, too_large, too_large)}}
+    ast = create_lb_ast(stencil='D3Q19', cumulant=True, relaxation_rate=1.8, optimization=opt,
+                        compressible=True, force_model='guo')
+    limited_block_size = ast.indexing.call_parameters((1024, 1024, 1024))
+    kernel = ast.compile()
+    assert all(b < too_large for b in limited_block_size['block'])
+    bs = [too_large, too_large, too_large]
+    ast.indexing.limit_block_size_by_register_restriction(bs, kernel.num_regs)
+    assert all(b < too_large for b in bs)
diff --git a/lbmpy_tests/test_html_output.py b/lbmpy_tests/test_html_output.py
new file mode 100644
index 0000000000000000000000000000000000000000..a5c481a1c34fcf4e0f8f8243f08a46a64209f9ea
--- /dev/null
+++ b/lbmpy_tests/test_html_output.py
@@ -0,0 +1,34 @@
+from lbmpy.creationfunctions import create_lb_method
+from lbmpy.methods.creationfunctions import compare_moment_based_lb_methods
+from lbmpy.moments import moment_equality_table_by_stencil, moment_equality_table, moments_up_to_component_order
+from lbmpy.stencils import get_stencil
+
+
+def test_moment_comparison_table():
+    new = create_lb_method(stencil='D3Q19', maxwellian_moments=True)
+    old = create_lb_method(stencil='D3Q19', maxwellian_moments=False)
+
+    assert old.zeroth_order_equilibrium_moment_symbol == new.zeroth_order_equilibrium_moment_symbol
+
+    assert '<td' in new._repr_html_()
+
+    res_deviations_only = compare_moment_based_lb_methods(old, new, show_deviations_only=True)
+    assert len(res_deviations_only.array) == 4
+
+    res_all = compare_moment_based_lb_methods(old, new, show_deviations_only=False)
+    assert len(res_all.array) == 20
+
+    d3q27 = create_lb_method(stencil='D3Q27')
+    compare_moment_based_lb_methods(d3q27, new, show_deviations_only=False)
+    compare_moment_based_lb_methods(new, d3q27, show_deviations_only=False)
+
+
+def test_moment_equality_table():
+    d3q19 = get_stencil('D3Q19')
+    table1 = moment_equality_table(d3q19, max_order=3)
+    assert len(table1.array) == 5
+
+    table2 = moment_equality_table_by_stencil({'D3Q19': d3q19, 'D3Q27': get_stencil("D3Q27")},
+                                              moments_up_to_component_order(2, dim=3))
+    assert len(table2.array) == 11
+    assert len(table2.array[0]) == 2 + 2
diff --git a/lbmpy_tests/test_lbstep.py b/lbmpy_tests/test_lbstep.py
new file mode 100644
index 0000000000000000000000000000000000000000..447b8643e963ad38dccf8af5107004c68fb6425e
--- /dev/null
+++ b/lbmpy_tests/test_lbstep.py
@@ -0,0 +1,97 @@
+import pytest
+import numpy as np
+from lbmpy.scenarios import create_lid_driven_cavity, create_fully_periodic_flow
+
+try:
+    import pycuda.driver
+    gpu_available = True
+except ImportError:
+    gpu_available = False
+
+try:
+    import waLBerla as wLB
+    parallel_available = wLB.cpp_available
+except ImportError:
+    parallel_available = False
+    wLB = None
+
+
+def ldc_setup(**kwargs):
+    ldc = create_lid_driven_cavity(relaxation_rate=1.7, **kwargs)
+    ldc.run(50)
+    return ldc.density_slice()
+
+
+def test_data_handling_3d():
+    print("--- LDC 3D test ---")
+    results = []
+    for parallel in [False, True] if parallel_available else [False]:
+        for gpu in [False, True] if gpu_available else [False]:
+            if parallel and gpu and not hasattr(wLB, 'cuda'):
+                continue
+            print("Testing parallel: %s\tgpu: %s" % (parallel, gpu))
+            opt_params = {'target': 'gpu' if gpu else 'cpu',
+                          'gpu_indexing_params': {'block_size': (8, 4, 2)}}
+            if parallel:
+                from pystencils.datahandling import ParallelDataHandling
+                blocks = wLB.createUniformBlockGrid(blocks=(2, 3, 4), cellsPerBlock=(5, 5, 5),
+                                                    oneBlockPerProcess=False)
+                dh = ParallelDataHandling(blocks, dim=3)
+                rho = ldc_setup(data_handling=dh, optimization=opt_params)
+                results.append(rho)
+            else:
+                rho = ldc_setup(domain_size=(10, 15, 20), parallel=False, optimization=opt_params)
+                results.append(rho)
+    for i, arr in enumerate(results[1:]):
+        print("Testing equivalence version 0 with version %d" % (i + 1,))
+        np.testing.assert_almost_equal(results[0], arr)
+
+
+def test_data_handling_2d():
+    print("--- LDC 2D test ---")
+    results = []
+    for parallel in [True, False] if parallel_available else [False]:
+        for gpu in [True, False] if gpu_available else [False]:
+            if parallel and gpu and not hasattr(wLB, 'cuda'):
+                continue
+
+            print("Testing parallel: %s\tgpu: %s" % (parallel, gpu))
+            opt_params = {'target': 'gpu' if gpu else 'cpu',
+                          'gpu_indexing_params': {'block_size': (8, 4, 2)}}
+            if parallel:
+                from pystencils.datahandling import ParallelDataHandling
+                blocks = wLB.createUniformBlockGrid(blocks=(2, 3, 1), cellsPerBlock=(5, 5, 1),
+                                                    oneBlockPerProcess=False)
+                dh = ParallelDataHandling(blocks, dim=2)
+                rho = ldc_setup(data_handling=dh, optimization=opt_params)
+                results.append(rho)
+            else:
+                rho = ldc_setup(domain_size=(10, 15), parallel=False, optimization=opt_params)
+                results.append(rho)
+    for i, arr in enumerate(results[1:]):
+        print("Testing equivalence version 0 with version %d" % (i + 1,))
+        np.testing.assert_almost_equal(results[0], arr)
+
+
+def test_smagorinsky_setup():
+    step = create_lid_driven_cavity((30, 30), smagorinsky=0.16, relaxation_rate=1.99)
+    step.run(10)
+
+
+def test_advanced_initialization():
+    width, height = 100, 50
+    velocity_magnitude = 0.05
+    init_vel = np.zeros((width, height, 2))
+    # fluid moving to the right everywhere...
+    init_vel[:, :, 0] = velocity_magnitude
+    # ...except at a stripe in the middle, where it moves left
+    init_vel[:, height // 3: height // 3 * 2, 0] = -velocity_magnitude
+    # small random y velocity component
+    init_vel[:, :, 1] = 0.1 * velocity_magnitude * np.random.rand(width, height)
+    shear_flow_scenario = create_fully_periodic_flow(initial_velocity=init_vel, relaxation_rate=1.95)
+    with pytest.raises(ValueError) as e:
+        shear_flow_scenario.run_iterative_initialization(max_steps=20000, check_residuum_after=500)
+    assert 'did not converge' in str(e)
+
+    shear_flow_scenario = create_fully_periodic_flow(initial_velocity=init_vel, relaxation_rate=1.6)
+    shear_flow_scenario.run_iterative_initialization(max_steps=20000, check_residuum_after=500)
diff --git a/lbmpy_tests/test_macroscopic_value_kernels.py b/lbmpy_tests/test_macroscopic_value_kernels.py
new file mode 100644
index 0000000000000000000000000000000000000000..c143ee6c8e6c54acdecec8e2ca11fc4ba4ffff59
--- /dev/null
+++ b/lbmpy_tests/test_macroscopic_value_kernels.py
@@ -0,0 +1,54 @@
+import numpy as np
+from lbmpy.creationfunctions import create_lb_method
+from lbmpy.macroscopic_value_kernels import compile_macroscopic_values_getter, compile_macroscopic_values_setter
+
+
+def test_set_get_density_velocity_with_fields():
+    for stencil in ['D2Q9', 'D3Q19']:
+        for force_model in ['guo', 'luo', 'none']:
+            for compressible in [True, False]:
+                force = (0.1, 0.12, -0.17)
+                method = create_lb_method(stencil=stencil, force_model=force_model, method='trt',
+                                          compressible=compressible, force=force)
+                size = (3, 7, 4)[:method.dim]
+                pdf_arr = np.zeros(size + (len(method.stencil),))
+                density_input_field = 1 + 0.2 * (np.random.random_sample(size) - 0.5)
+                velocity_input_field = 0.1 * (np.random.random_sample(size + (method.dim, )) - 0.5)
+                setter = compile_macroscopic_values_setter(method, pdf_arr=pdf_arr,
+                                                           quantities_to_set={'density': density_input_field,
+                                                                              'velocity': velocity_input_field}, )
+                setter(pdf_arr)
+
+                getter = compile_macroscopic_values_getter(method, ['density', 'velocity'], pdf_arr=pdf_arr)
+                density_output_field = np.empty_like(density_input_field)
+                velocity_output_field = np.empty_like(velocity_input_field)
+                getter(pdfs=pdf_arr, density=density_output_field, velocity=velocity_output_field)
+                np.testing.assert_almost_equal(density_input_field, density_output_field)
+                np.testing.assert_almost_equal(velocity_input_field, velocity_output_field)
+
+
+def test_set_get_constant_velocity():
+    for stencil in ['D2Q9', 'D3Q19']:
+        for force_model in ['guo', 'luo', 'none']:
+            for compressible in [True, False]:
+                ref_velocity = [0.01, -0.2, 0.1]
+
+                force = (0.1, 0.12, -0.17)
+                method = create_lb_method(stencil=stencil, force_model=force_model, method='trt',
+                                          compressible=compressible, force=force)
+                size = (1, 1, 1)[:method.dim]
+                pdf_arr = np.zeros(size + (len(method.stencil),))
+                setter = compile_macroscopic_values_setter(method, pdf_arr=pdf_arr,
+                                                           quantities_to_set={'velocity': ref_velocity[:method.dim]}, )
+                setter(pdf_arr)
+
+                getter = compile_macroscopic_values_getter(method, ['velocity'], pdf_arr=pdf_arr)
+                velocity_output_field = np.zeros(size + (method.dim, ))
+                getter(pdfs=pdf_arr, velocity=velocity_output_field)
+                if method.dim == 2:
+                    computed_velocity = velocity_output_field[0, 0, :]
+                else:
+                    computed_velocity = velocity_output_field[0, 0, 0, :]
+
+                np.testing.assert_almost_equal(np.array(ref_velocity[:method.dim]), computed_velocity)
+
diff --git a/lbmpy_tests/test_maxwellian_equilibrium.py b/lbmpy_tests/test_maxwellian_equilibrium.py
new file mode 100644
index 0000000000000000000000000000000000000000..202e37a657e58adcb11da9cdd88df8858fccde74
--- /dev/null
+++ b/lbmpy_tests/test_maxwellian_equilibrium.py
@@ -0,0 +1,100 @@
+from lbmpy.maxwellian_equilibrium import *
+from lbmpy.moments import MOMENT_SYMBOLS, moments_up_to_order, moments_up_to_component_order, moment_matrix, \
+    exponents_to_polynomial_representations
+from lbmpy.stencils import get_stencil
+from lbmpy.cumulants import raw_moment_as_function_of_cumulants
+from pystencils.sympyextensions import remove_higher_order_terms
+
+
+def test_maxwellian_moments():
+    """Check moments of continuous Maxwellian"""
+    rho = sp.Symbol("rho")
+    u = sp.symbols("u_0 u_1 u_2")
+    c_s = sp.Symbol("c_s")
+    eq_moments = get_moments_of_continuous_maxwellian_equilibrium(((0, 0, 0), (0, 0, 1)),
+                                                                  dim=3, rho=rho, u=u, c_s_sq=c_s ** 2)
+    assert eq_moments[0] == rho
+    assert eq_moments[1] == rho * u[2]
+
+    x, y, z = MOMENT_SYMBOLS
+    one = sp.Rational(1, 1)
+    eq_moments = get_moments_of_continuous_maxwellian_equilibrium((one, x, x ** 2, x * y),
+                                                                  dim=2, rho=rho, u=u[:2], c_s_sq=c_s ** 2)
+    assert eq_moments[0] == rho
+    assert eq_moments[1] == rho * u[0]
+    assert eq_moments[2] == rho * (c_s ** 2 + u[0] ** 2)
+    assert eq_moments[3] == rho * u[0] * u[1]
+
+
+def test_continuous_discrete_moment_equivalence():
+    """Check that moments up to order 3 agree with moments of the continuous Maxwellian"""
+    for stencil in [get_stencil(n) for n in ["D2Q9", "D3Q15", "D3Q19", "D3Q27"]]:
+        dim = len(stencil[0])
+        c_s_sq = sp.Rational(1, 3)
+        moments = tuple(moments_up_to_order(3, dim=dim, include_permutations=False))
+        cm = sp.Matrix(get_moments_of_continuous_maxwellian_equilibrium(moments, order=2, dim=dim, c_s_sq=c_s_sq))
+        dm = sp.Matrix(get_moments_of_discrete_maxwellian_equilibrium(stencil, moments, order=2,
+                                                                      compressible=True, c_s_sq=c_s_sq))
+
+        diff = sp.simplify(cm - dm)
+        for d in diff:
+            assert d == 0
+
+
+def test_moment_cumulant_continuous_equivalence():
+    """Test that discrete equilibrium is the same up to order 3 when obtained with following methods
+
+    * eq1: take moments of continuous Maxwellian and transform back to pdf space
+    * eq2: take cumulants of continuous Maxwellian, transform to moments then transform to pdf space
+    * eq3: take discrete equilibrium from LBM literature
+    * eq4: same as eq1 but with built-in function
+    """
+    for stencil in [get_stencil('D2Q9'), get_stencil('D3Q27')]:
+        dim = len(stencil[0])
+        u = sp.symbols("u_:{dim}".format(dim=dim))
+        indices = tuple(moments_up_to_component_order(2, dim=dim))
+        c_s_sq = sp.Rational(1, 3)
+        eq_moments1 = get_moments_of_continuous_maxwellian_equilibrium(indices, dim=dim, u=u, c_s_sq=c_s_sq)
+        eq_cumulants = get_cumulants_of_continuous_maxwellian_equilibrium(indices, dim=dim, u=u, c_s_sq=c_s_sq)
+        eq_cumulants = {idx: c for idx, c in zip(indices, eq_cumulants)}
+        eq_moments2 = [raw_moment_as_function_of_cumulants(idx, eq_cumulants) for idx in indices]
+        pdfs_to_moments = moment_matrix(indices, stencil)
+
+        def normalize(expressions):
+            return [remove_higher_order_terms(e.expand(), symbols=u, order=3) for e in expressions]
+
+        eq1 = normalize(pdfs_to_moments.inv() * sp.Matrix(eq_moments1))
+        eq2 = normalize(pdfs_to_moments.inv() * sp.Matrix(eq_moments2))
+        eq3 = normalize(discrete_maxwellian_equilibrium(stencil, order=3, c_s_sq=c_s_sq, compressible=True))
+        eq4 = normalize(generate_equilibrium_by_matching_moments(stencil, indices, c_s_sq=c_s_sq))
+
+        assert eq1 == eq2
+        assert eq2 == eq3
+        assert eq3 == eq4
+
+
+def test_moment_cumulant_continuous_equivalence_polynomial_formulation():
+    """Same as test above, but instead of index tuples, the polynomial formulation is used."""
+    for stencil in [get_stencil('D2Q9'), get_stencil('D3Q27')]:
+        dim = len(stencil[0])
+        u = sp.symbols(f"u_:{dim}")
+        index_tuples = tuple(moments_up_to_component_order(2, dim=dim))
+        indices = exponents_to_polynomial_representations(index_tuples)
+        c_s_sq = sp.Rational(1, 3)
+        eq_moments1 = get_moments_of_continuous_maxwellian_equilibrium(indices, dim=dim, u=u, c_s_sq=c_s_sq)
+        eq_cumulants = get_cumulants_of_continuous_maxwellian_equilibrium(indices, dim=dim, u=u, c_s_sq=c_s_sq)
+        eq_cumulants = {idx: c for idx, c in zip(index_tuples, eq_cumulants)}
+        eq_moments2 = [raw_moment_as_function_of_cumulants(idx, eq_cumulants) for idx in index_tuples]
+        pdfs_to_moments = moment_matrix(indices, stencil)
+
+        def normalize(expressions):
+            return [remove_higher_order_terms(e.expand(), symbols=u, order=3) for e in expressions]
+
+        eq1 = normalize(pdfs_to_moments.inv() * sp.Matrix(eq_moments1))
+        eq2 = normalize(pdfs_to_moments.inv() * sp.Matrix(eq_moments2))
+        eq3 = normalize(discrete_maxwellian_equilibrium(stencil, order=3, c_s_sq=c_s_sq, compressible=True))
+        eq4 = normalize(generate_equilibrium_by_matching_moments(stencil, indices, c_s_sq=c_s_sq))
+
+        assert eq1 == eq2
+        assert eq2 == eq3
+        assert eq3 == eq4
diff --git a/lbmpy_tests/test_momentbased_methods_equilibrium.py b/lbmpy_tests/test_momentbased_methods_equilibrium.py
new file mode 100644
index 0000000000000000000000000000000000000000..b69f020b68003faf7a05ee1f2f34db67c719f5bf
--- /dev/null
+++ b/lbmpy_tests/test_momentbased_methods_equilibrium.py
@@ -0,0 +1,75 @@
+"""
+Moment-based methods are created by specifying moments and their equilibrium value.
+This test checks if the equilibrium formula obtained by this method is the same as the explicitly
+given discrete_maxwellian_equilibrium
+"""
+import sympy as sp
+from lbmpy.methods import create_srt, create_trt, create_mrt_orthogonal
+from lbmpy.maxwellian_equilibrium import discrete_maxwellian_equilibrium
+from lbmpy.relaxationrates import get_shear_relaxation_rate
+from lbmpy.stencils import get_stencil
+from lbmpy.creationfunctions import create_lb_method
+
+
+def check_for_matching_equilibrium(method_name, stencil, compressibility):
+    omega = sp.Symbol("omega")
+    if method_name == 'srt':
+        method = create_srt(stencil, omega, compressible=compressibility, equilibrium_order=2)
+    elif method_name == 'trt':
+        method = create_trt(stencil, omega, omega, compressible=compressibility, equilibrium_order=2)
+    elif method_name == 'mrt':
+        method = create_mrt_orthogonal(stencil, lambda v: omega, compressible=compressibility, equilibrium_order=2)
+    else:
+        raise ValueError("Unknown method")
+
+    reference_equilibrium = discrete_maxwellian_equilibrium(stencil, order=2,
+                                                            c_s_sq=sp.Rational(1, 3), compressible=compressibility)
+    equilibrium = method.get_equilibrium()
+    equilibrium = equilibrium.new_without_subexpressions(subexpressions_to_keep=sp.symbols("rho u_0 u_1 u_2"))
+
+    diff = sp.Matrix(reference_equilibrium) - sp.Matrix([eq.rhs for eq in equilibrium.main_assignments])
+    diff = sp.simplify(diff)
+    assert diff.is_zero
+
+
+def check_for_matching_equilibrium_for_stencil(stencil_name):
+    stencil = get_stencil(stencil_name)
+    for method in ['srt', 'trt', 'mrt']:
+        check_for_matching_equilibrium(method, stencil, True)
+        check_for_matching_equilibrium(method, stencil, False)
+
+
+def test_d2_q9():
+    check_for_matching_equilibrium_for_stencil('D2Q9')
+
+
+def test_d3_q27():
+    check_for_matching_equilibrium_for_stencil('D3Q27')
+
+
+def test_d3_q19():
+    check_for_matching_equilibrium_for_stencil('D3Q19')
+
+
+def test_d3_q15():
+    check_for_matching_equilibrium_for_stencil('D3Q15')
+
+
+def test_relaxation_rate_setter():
+    o1, o2, o3 = sp.symbols("o1 o2 o3")
+    method = create_lb_method(method='srt', stencil='D2Q9', relaxation_rates=[o3])
+    method2 = create_lb_method(method='mrt3', stencil='D2Q9', relaxation_rates=[o3, o3, o3])
+    method.set_zeroth_moment_relaxation_rate(o1)
+    method.set_first_moment_relaxation_rate(o2)
+    assert get_shear_relaxation_rate(method) == o3
+    method.set_zeroth_moment_relaxation_rate(o3)
+    method.set_first_moment_relaxation_rate(o3)
+    assert method.collision_matrix == method2.collision_matrix
+
+
+def test_mrt_orthogonal():
+    m = create_mrt_orthogonal(get_stencil("D2Q9"), maxwellian_moments=True)
+    assert (m.moment_matrix * m.moment_matrix.T).is_diagonal()
+
+    m = create_mrt_orthogonal(get_stencil("D3Q27"), maxwellian_moments=True)
+    assert (m.moment_matrix * m.moment_matrix.T).is_diagonal()
diff --git a/lbmpy_tests/test_moments.py b/lbmpy_tests/test_moments.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e0b1c0a6d9fd4ff6c1661b7f9380fe9cc87c1de
--- /dev/null
+++ b/lbmpy_tests/test_moments.py
@@ -0,0 +1,75 @@
+from lbmpy.stencils import get_stencil
+from lbmpy.moments import *
+
+
+def test_moment_permutation_multiplicity():
+    test_moments = [(2, 0, 0),
+                    (1, 2, 0),
+                    (1, 0, 2, 0)]
+
+    for m in test_moments:
+        assert moment_multiplicity(m) == len(list(moment_permutations(m)))
+
+
+def test_moment_order():
+    r = moments_of_order(2, dim=3, include_permutations=True)
+    assert len(list(r)) == 6
+
+    r = moments_of_order(2, dim=3, include_permutations=False)
+    assert len(list(r)) == 2
+
+    r = moments_up_to_order(2, dim=3, include_permutations=True)
+    assert len(list(r)) == 10
+
+    r = moments_up_to_order(2, dim=3, include_permutations=False)
+    assert len(r) == 4
+
+    r = moments_up_to_component_order(2, dim=3)
+    assert len(r) == 3**3
+
+    r = moments_up_to_component_order(2, dim=2)
+    assert len(r) == 3**2
+
+
+def test_extend_moments_with_permutations():
+    no_perm = moments_of_order(2, dim=3, include_permutations=False)
+    with_perm = moments_of_order(2, dim=3, include_permutations=True)
+
+    assert set(extend_moments_with_permutations(no_perm)) == set(with_perm)
+
+
+def test_representation_conversion():
+    x, y, z = MOMENT_SYMBOLS
+    e = exponents_to_polynomial_representations([(2, 1, 0), (0, 0, 0)])
+    ref = 5 * x**2 * y + 3
+    assert sp.simplify(5 * e[0] + 3 * e[1] - ref) == 0
+
+    e = polynomial_to_exponent_representation(x ** 4 * z ** 2)[0][1]
+    assert e, (4, 0 == 2)
+
+    e = polynomial_to_exponent_representation(x ** 4 * y ** 2, dim=2)[0][1]
+    assert e, (4 == 2)
+
+
+def test_moment_properties():
+    x, y, z = MOMENT_SYMBOLS
+    # even - odd
+    assert is_even((2, 0, 0))
+    assert not is_even((2, 1, 0))
+    assert is_even(x ** 2 + y ** 2)
+    assert not is_even(z)
+
+    # order
+    assert get_order(x ** 4 * z ** 2) == 6
+    assert get_order((2, 2, 3)) == 7
+    assert get_order(sp.sympify(1)) == 0
+
+
+def test_gram_schmidt_orthogonalization():
+    moments = moments_up_to_component_order(2, 2)
+    assert len(moments) == 9
+
+    stencil = get_stencil("D2Q9")
+    orthogonal_moments = gram_schmidt(moments, stencil)
+    pdfs_to_moments = moment_matrix(orthogonal_moments, stencil)
+    assert (pdfs_to_moments * pdfs_to_moments.T).is_diagonal()
diff --git a/lbmpy_tests/test_n_phase_boyer_noncoupled.ipynb b/lbmpy_tests/test_n_phase_boyer_noncoupled.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..20779d9530c41ebf871e70b2e01867f430ea8fe2
--- /dev/null
+++ b/lbmpy_tests/test_n_phase_boyer_noncoupled.ipynb
@@ -0,0 +1,374 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.n_phase_boyer import *\n",
+    "from lbmpy.phasefield.kerneleqs import *\n",
+    "from lbmpy.phasefield.contact_angle_circle_fitting import *\n",
+    "from scipy.ndimage.filters import gaussian_filter\n",
+    "from pystencils.simp import sympy_cse_on_assignment_list\n",
+    "one = sp.sympify(1)\n",
+    "\n",
+    "import pyximport\n",
+    "pyximport.install(language_level=3)\n",
+    "from lbmpy.phasefield.simplex_projection import simplex_projection_2d  # NOQA"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Simulation arbitrary surface tension case"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "n = 4\n",
+    "dx, dt = 1, 1\n",
+    "mobility = 2e-3\n",
+    "domain_size = (150, 150)\n",
+    "ε = one * 4\n",
+    "penalty_factor = 0\n",
+    "stabilization_factor = 10\n",
+    "\n",
+    "κ = (one,  one/2, one/3, one/4)\n",
+    "sigma_factor = one / 15\n",
+    "σ = sp.ImmutableDenseMatrix(n, n, lambda i,j: sigma_factor* (κ[i] + κ[j]) if i != j else 0 )\n",
+    "#σ"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh = create_data_handling(domain_size, periodicity=True, default_target='gpu')\n",
+    "c = dh.add_array('c', values_per_cell=n)\n",
+    "c_tmp = dh.add_array_like('c_tmp', 'c')\n",
+    "\n",
+    "μ = dh.add_array('mu', values_per_cell=n)\n",
+    "\n",
+    "cvec = c.center_vector\n",
+    "μvec = μ.center_vector"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "α, _ = diffusion_coefficients(σ)\n",
+    "\n",
+    "f = lambda c: c**2 * ( 1 - c ) **2\n",
+    "a, b = compute_ab(f)\n",
+    "\n",
+    "capital_f = capital_f0(cvec, σ) + correction_g(cvec, σ) + stabilization_factor * stabilization_term(cvec, α)\n",
+    "\n",
+    "f_bulk = free_energy_bulk(capital_f, b, ε) + penalty_factor * (one - sum(cvec))\n",
+    "f_if = free_energy_interfacial(cvec, σ, a, ε)\n",
+    "f = f_bulk + f_if"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#f_bulk"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "μ_assignments = mu_kernel(f, cvec, c, μ)\n",
+    "μ_assignments = [Assignment(a.lhs, a.rhs.doit()) for a in μ_assignments]\n",
+    "μ_assignments = sympy_cse_on_assignment_list(μ_assignments)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "discretize = fd.Discretization2ndOrder(dx=dx, dt=dt)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rhs = α * μvec\n",
+    "discretized_rhs = [discretize(fd.expand_diff_full( Diff(Diff(mobility * rhs_i)) + fd.transient(cvec[i], idx=i), functions=μvec))\n",
+    "                   for i, rhs_i in enumerate(rhs)]\n",
+    "c_assignments = [Assignment(lhs, rhs) \n",
+    "                 for lhs, rhs in zip(c_tmp.center_vector, discretized_rhs)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#c_assignments"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "μ_sync = dh.synchronization_function(μ.name)\n",
+    "c_sync = dh.synchronization_function(c.name)\n",
+    "optimization = {'cpu_openmp': 4, 'cpu_vectorize_info': None}\n",
+    "μ_kernel = create_kernel(μ_assignments, target=dh.default_target, **optimization).compile()\n",
+    "c_kernel = create_kernel(c_assignments, target=dh.default_target, **optimization).compile()\n",
+    "\n",
+    "def set_c(slice_obj, values):\n",
+    "    for block in dh.iterate(slice_obj):\n",
+    "        arr = block[c.name]\n",
+    "        arr[..., : ] = values\n",
+    "\n",
+    "def smooth():\n",
+    "    for block in dh.iterate(ghost_layers=True):\n",
+    "        c_arr = block[c.name]\n",
+    "        for i in range(n):\n",
+    "            gaussian_filter(c_arr[..., i], sigma=2, output=c_arr[..., i])\n",
+    "        \n",
+    "def time_loop(steps):\n",
+    "    dh.all_to_gpu()\n",
+    "    for t in range(steps):\n",
+    "        c_sync()\n",
+    "        dh.run_kernel(μ_kernel)\n",
+    "        μ_sync()\n",
+    "        dh.run_kernel(c_kernel)\n",
+    "        dh.swap(c.name, c_tmp.name)\n",
+    "        #simplex_projection_2d(dh.cpu_arrays[c.name])\n",
+    "    dh.all_to_cpu()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "set_c(make_slice[:, :], [0, 0, 0, 0])\n",
+    "set_c(make_slice[:, 0.5:], [1, 0, 0, 0])\n",
+    "set_c(make_slice[:, :0.5], [0, 1, 0, 0])\n",
+    "set_c(make_slice[0.3:0.7, 0.3:0.7], [0, 0, 1, 0])\n",
+    "smooth()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#dh.load_all('n_phases_state_size200_stab10.npz')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/local/bauer/miniconda3/envs/pystencils_dev/lib/python3.7/site-packages/matplotlib/contour.py:1243: UserWarning: No contour levels were found within the data range.\n",
+      "  warnings.warn(\"No contour levels were found\"\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.phase_plot(dh.gather_array(c.name))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ 146.44269023807928, \\quad 117.81813928465394, \\quad 95.73917047726678\\right ]$$"
+      ],
+      "text/plain": [
+       "[146.44269023807928, 117.81813928465394, 95.73917047726678]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "neumann_angles_from_surface_tensions(lambda i, j: float(σ[i, j]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 0.4948967100003756 [83.97834853343086, 100.48843351167487, 175.53321795489427]\n",
+      "1 0.46325071699993714 [83.73089000952169, 100.65861489552344, 175.6104950949548]\n",
+      "2 0.4162677360000089 [83.49917147819785, 100.82171580037817, 175.679112721424]\n",
+      "3 0.4208440130000781 [83.31522725116703, 100.94465624438456, 175.74011650444845]\n",
+      "4 0.4054762699997809 [83.14244042613915, 101.06096493509406, 175.79659463876686]\n",
+      "5 0.4099374320003335 [82.98452286961921, 101.16728073593467, 175.84819639444606]\n",
+      "6 0.4051740560003054 [82.84784900062101, 101.25699289301976, 175.89515810635933]\n",
+      "7 0.38569620899988877 [82.74572683273676, 101.31684772333017, 175.93742544393302]\n",
+      "8 0.3827051820003362 [82.67014193290147, 101.35096921023188, 175.9788888568664]\n",
+      "9 0.4393134040001314 [75.9000636413822, 108.96518552940361, 175.13475082921425]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import time\n",
+    "for i in range(10):\n",
+    "    start = time.perf_counter()\n",
+    "    time_loop(1_000)\n",
+    "    end = time.perf_counter()\n",
+    "\n",
+    "    try:\n",
+    "        print(i, end - start, liquid_lens_neumann_angles(dh.gather_array(c.name)))\n",
+    "    except Exception:\n",
+    "        print(i, end - start, \"none found\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/local/bauer/miniconda3/envs/pystencils_dev/lib/python3.7/site-packages/matplotlib/contour.py:1243: UserWarning: No contour levels were found within the data range.\n",
+      "  warnings.warn(\"No contour levels were found\"\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.subplot(1,3,1)\n",
+    "t = dh.gather_array(c.name, make_slice[25, :]).squeeze()\n",
+    "plt.plot(t);\n",
+    "\n",
+    "plt.subplot(1,3,2)\n",
+    "plt.phase_plot(dh.gather_array(c.name), linewidth=1)\n",
+    "\n",
+    "plt.subplot(1,3,3)\n",
+    "plt.scalar_field(dh.gather_array(μ.name)[:, :, 2])\n",
+    "plt.colorbar();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert not np.isnan(dh.max(c.name))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "t = dh.gather_array(c.name, make_slice[25, 55:90]).squeeze()\n",
+    "plt.hlines(0.5, 0, 30)\n",
+    "plt.plot(t);"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/test_phase_field_scenarios.py b/lbmpy_tests/test_phase_field_scenarios.py
new file mode 100644
index 0000000000000000000000000000000000000000..d20f29752e7bc14983427055b87d847562e458e9
--- /dev/null
+++ b/lbmpy_tests/test_phase_field_scenarios.py
@@ -0,0 +1,46 @@
+import os
+import warnings
+from tempfile import TemporaryDirectory
+import numpy as np
+import sympy as sp
+from lbmpy.phasefield.phasefieldstep import PhaseFieldStep
+from lbmpy.phasefield.analytical import free_energy_functional_n_phases_penalty_term
+from pystencils import make_slice
+from lbmpy.boundaries import NoSlip
+from lbmpy.phasefield.experiments2D import create_two_drops_between_phases, write_phase_field_picture_sequence, \
+    write_phase_velocity_picture_sequence
+
+
+def create_falling_drop(domain_size=(160, 200), omega=1.9, kappas=(0.001, 0.001, 0.0005), **kwargs):
+    c = sp.symbols("c_:3")
+    free_energy = free_energy_functional_n_phases_penalty_term(c, 1, kappas)
+    gravity = -0.1e-5
+    if 'optimization' not in kwargs:
+        kwargs['optimization'] = {'openmp': 4}
+    sc = PhaseFieldStep(free_energy, c, domain_size=domain_size, hydro_dynamic_relaxation_rate=omega,
+                        order_parameter_force={2: (0, gravity), 1: (0, 0), 0: (0, 0)}, **kwargs)
+    sc.set_concentration(make_slice[:, 0.4:], [1, 0, 0])
+    sc.set_concentration(make_slice[:, :0.4], [0, 1, 0])
+    sc.set_concentration(make_slice[0.45:0.55, 0.8:0.9], [0, 0, 1])
+    sc.hydro_lbm_step.boundary_handling.set_boundary(NoSlip(), make_slice[:, 0])
+
+    sc.set_pdf_fields_from_macroscopic_values()
+    return sc
+
+
+def test_drops_between_phases():
+    sc = create_two_drops_between_phases()
+    with TemporaryDirectory() as tmp_dir:
+        file_pattern = os.path.join(tmp_dir, "output_%d.png")
+        write_phase_field_picture_sequence(sc, file_pattern, total_steps=200)
+    assert np.isfinite(np.max(sc.phi[:, :, :]))
+
+
+def test_falling_drop():
+    sc = create_falling_drop()
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore")
+        with TemporaryDirectory() as tmp_dir:
+            file_pattern = os.path.join(tmp_dir, "output_%d.png")
+            write_phase_velocity_picture_sequence(sc, file_pattern, total_steps=200)
+        assert np.isfinite(np.max(sc.phi[:, :, :]))
diff --git a/lbmpy_tests/test_phasefield.py b/lbmpy_tests/test_phasefield.py
new file mode 100644
index 0000000000000000000000000000000000000000..d7377abdce945771580cc0108a049d5b93ea8851
--- /dev/null
+++ b/lbmpy_tests/test_phasefield.py
@@ -0,0 +1,68 @@
+import sympy as sp
+
+from pystencils.fd import evaluate_diffs, expand_diff_full
+from lbmpy.phasefield.analytical import free_energy_functional_n_phases, symbolic_order_parameters, \
+    analytic_interface_profile, symmetric_symbolic_surface_tension, chemical_potentials_from_free_energy, \
+    cosh_integral, pressure_tensor_from_free_energy, force_from_pressure_tensor, force_from_phi_and_mu, \
+    substitute_laplacian_by_sum
+
+
+def test_analytic_interface_solution():
+    """Ensures that the tanh is an analytical solution for the prescribed free energy / chemical potential
+    """
+    num_phases = 4
+    phi = symbolic_order_parameters(num_phases - 1)
+    free_energy = free_energy_functional_n_phases(num_phases, order_parameters=phi).subs({p: 0 for p in phi[1:]})
+    mu_diff_eq = chemical_potentials_from_free_energy(free_energy, [phi[0]])[0]
+
+    x = sp.Symbol("x")
+    sol = analytic_interface_profile(x)
+
+    inserted = mu_diff_eq.subs(phi[0], sol)
+    assert sp.expand(evaluate_diffs(inserted, x)) == 0
+
+
+def test_surface_tension_derivation():
+    """Computes the excess free energy per unit area of an interface transition between two phases
+    which should give exactly the surface tension parameter"""
+    num_phases = 4
+    eta = sp.Symbol("eta")
+
+    free_energy = free_energy_functional_n_phases(num_phases, interface_width=eta)
+    phi = symbolic_order_parameters(num_phases)
+
+    x = sp.Symbol("x")
+    sol = analytic_interface_profile(x, interface_width=eta)
+
+    for a, b in [(1, 3), (0, 1)]:
+        substitutions = {phi[a]: sol}
+        if b < len(phi) - 1:
+            substitutions[phi[b]] = 1 - sol
+        for i, phi_i in enumerate(phi[:-1]):
+            if i not in (a, b):
+                substitutions[phi_i] = 0
+
+        free_energy_2_phase = sp.simplify(evaluate_diffs(free_energy.subs(substitutions), x))
+        result = cosh_integral(free_energy_2_phase, x)
+        assert result == symmetric_symbolic_surface_tension(a, b)
+
+
+def test_pressure_tensor():
+    """
+    Checks that the following ways are equivalent:
+    1) phi -> mu -> force
+    2) phi -> pressure tensor -> force
+    """
+    dim = 3
+    c = symbolic_order_parameters(3)
+    f = free_energy_functional_n_phases(order_parameters=c)
+
+    mu = chemical_potentials_from_free_energy(f, c)
+    mu = substitute_laplacian_by_sum(mu, dim)
+    force_chem_pot = expand_diff_full(force_from_phi_and_mu(c, dim, mu), functions=c)
+
+    p = pressure_tensor_from_free_energy(f, c, dim)
+    force_pressure_tensor = force_from_pressure_tensor(p, functions=c)
+
+    for f1_i, f2_i in zip(force_chem_pot, force_pressure_tensor):
+        assert sp.expand(f1_i - f2_i) == 0
diff --git a/lbmpy_tests/test_phasefield_scenarios.py b/lbmpy_tests/test_phasefield_scenarios.py
new file mode 100644
index 0000000000000000000000000000000000000000..a45d8e7e0baf68dd7281e05e6d1ebad0d121159c
--- /dev/null
+++ b/lbmpy_tests/test_phasefield_scenarios.py
@@ -0,0 +1,30 @@
+from pystencils import make_slice
+from lbmpy.phasefield.scenarios import *
+
+
+def test_setup():
+    domain_size = (30, 15)
+
+    scenarios = [
+        create_three_phase_model(domain_size=domain_size, include_rho=True),
+        #create_three_phase_model(domain_size=domain_size, include_rho=False),
+        create_n_phase_model_penalty_term(domain_size=domain_size, num_phases=4),
+    ]
+    for i, sc in enumerate(scenarios):
+        print("Testing scenario", i)
+        sc.set_concentration(make_slice[:, :0.5], [1, 0, 0])
+        sc.set_concentration(make_slice[:, 0.5:], [0, 1, 0])
+        sc.set_concentration(make_slice[0.4:0.6, 0.4:0.6], [0, 0, 1])
+        sc.set_pdf_fields_from_macroscopic_values()
+        sc.run(10)
+
+
+def test_fd_cahn_hilliard():
+    sc = create_n_phase_model_penalty_term(domain_size=(100, 50), num_phases=3,
+                                           solve_cahn_hilliard_with_finite_differences=True)
+    sc.set_concentration(make_slice[:, 0.5:], [1, 0, 0])
+    sc.set_concentration(make_slice[:, :0.5], [0, 1, 0])
+    sc.set_concentration(make_slice[0.3:0.7, 0.3:0.7], [0, 0, 1])
+    sc.set_pdf_fields_from_macroscopic_values()
+    sc.run(100)
+    assert np.isfinite(np.max(sc.concentration[:, :]))
diff --git a/lbmpy_tests/test_plot.py b/lbmpy_tests/test_plot.py
new file mode 100644
index 0000000000000000000000000000000000000000..803eb9a77daf2a2b8e6c0534d5d7b13428e22a10
--- /dev/null
+++ b/lbmpy_tests/test_plot.py
@@ -0,0 +1,46 @@
+import os
+import numpy as np
+from tempfile import TemporaryDirectory
+from lbmpy.scenarios import create_lid_driven_cavity
+import lbmpy.plot2d as plt
+
+
+def test_animation():
+
+    ldc = create_lid_driven_cavity((10, 10), relaxation_rate=1.8)
+
+    def run_vec():
+        ldc.run(100)
+        return ldc.velocity[:, :, :]
+
+    def run_scalar():
+        ldc.run(100)
+        return ldc.density[:, :]
+
+    plt.clf()
+    plt.cla()
+
+    with TemporaryDirectory() as tmp_dir:
+        ani = plt.vector_field_magnitude_animation(run_vec, interval=1, frames=30)
+        ani.save(os.path.join(tmp_dir, "animation1.avi"))
+
+        ani = plt.vector_field_animation(run_vec, interval=1, frames=30, rescale=True)
+        ani.save(os.path.join(tmp_dir, "animation2.avi"))
+
+        ani = plt.vector_field_animation(run_vec, interval=1, frames=30, rescale=False)
+        ani.save(os.path.join(tmp_dir, "animation3.avi"))
+
+        ani = plt.scalar_field_animation(run_scalar, interval=1, frames=30, rescale=True)
+        ani.save(os.path.join(tmp_dir, "animation4.avi"))
+
+        ani = plt.scalar_field_animation(run_scalar, interval=1, frames=30, rescale=False)
+        ani.save(os.path.join(tmp_dir, "animation5.avi"))
+
+        ani = plt.surface_plot_animation(run_scalar, frames=30)
+        ani.save(os.path.join(tmp_dir, "animation6.avi"))
+
+
+def test_plot():
+    arr = np.ones([3, 3, 2])
+    plt.multiple_scalar_fields(arr)
+    plt.show()
diff --git a/lbmpy_tests/test_postprocessing.py b/lbmpy_tests/test_postprocessing.py
new file mode 100644
index 0000000000000000000000000000000000000000..52608237186af7ba09be5bddf93da58a3c33d12d
--- /dev/null
+++ b/lbmpy_tests/test_postprocessing.py
@@ -0,0 +1,12 @@
+import numpy as np
+from lbmpy.postprocessing import scalar_field_interpolator, vector_field_interpolator
+
+
+def test_interpolation():
+    scalar_arr = np.arange(0, 3*3).reshape(3, 3)
+    scalar_ip = scalar_field_interpolator(scalar_arr)
+    np.testing.assert_equal(scalar_ip([[1, 1.5], [0.5, 1]]), [2.5, 0.5])
+
+    vector_arr = np.arange(0, 3 * 3 * 2).reshape(3, 3, 2)
+    vector_ip = vector_field_interpolator(vector_arr)
+    np.testing.assert_equal(vector_ip([[1, 1.5], [0.5, 1]]), [[5., 6.], [1., 2.]])
diff --git a/lbmpy_tests/test_relaxation_rate.py b/lbmpy_tests/test_relaxation_rate.py
new file mode 100644
index 0000000000000000000000000000000000000000..25fbe4208b9c31733d33730388b38e16c7fa43ba
--- /dev/null
+++ b/lbmpy_tests/test_relaxation_rate.py
@@ -0,0 +1,15 @@
+import pytest
+from lbmpy.creationfunctions import create_lb_method
+from lbmpy.relaxationrates import get_shear_relaxation_rate
+
+
+def test_relaxation_rate():
+    method = create_lb_method(stencil="D3Q19", method='mrt_raw',
+                              relaxation_rates=[1 + i / 10 for i in range(19)])
+    with pytest.raises(ValueError) as e:
+        get_shear_relaxation_rate(method)
+    assert 'Shear moments are relaxed with different relaxation' in str(e)
+
+    method = create_lb_method(stencil="D2Q9", method='mrt_raw',
+                              relaxation_rates=[1 + i / 10 for i in range(9)])
+    assert get_shear_relaxation_rate(method) == 1.5
diff --git a/lbmpy_tests/test_scaling_widget.py b/lbmpy_tests/test_scaling_widget.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee79981a0ec9e6907457afd1ce340167d44758cb
--- /dev/null
+++ b/lbmpy_tests/test_scaling_widget.py
@@ -0,0 +1,47 @@
+from lbmpy.parameterization import ScalingWidget, Scaling
+
+
+def test_scaling_widget():
+    w = ScalingWidget()
+    s = Scaling(physical_length=16, physical_velocity=0.001, kinematic_viscosity=1e-6, cells_per_length=8192)
+
+    w.scaling_type.value = 'diffusive (fixed relaxation rate)'
+    w.physical_length.value = 16
+    w.max_physical_velocity.value = 0.001
+    w.cells_per_length.value = 8192
+    w.kinematic_viscosity.value = 1
+    w.omega.value = 1.9
+
+    scaling_result = s.diffusive_scaling(1.9)
+
+    assert w.dx.value == 16 / 8192 and s.dx == w.dx.value
+    assert round(w.dt.value, 5) == 0.03346 and scaling_result.dt == w.dt.value
+    assert round(w.max_lattice_velocity.value, 5) == 0.01713
+    assert scaling_result.lattice_velocity == w.max_lattice_velocity.value
+    assert w.re.value == 16000 and s.reynolds_number == w.re.value
+
+    s = Scaling(physical_length=1, physical_velocity=0.001, kinematic_viscosity=2e-6, cells_per_length=4096)
+    w.scaling_type.value = 'fixed lattice velocity'
+    w.physical_length.value = 1
+    w.max_physical_velocity.value = 0.001
+    w.cells_per_length.value = 4096
+    w.kinematic_viscosity.value = 2
+    w.max_lattice_velocity.value = 0.1
+    scaling_result = s.fixed_lattice_velocity_scaling(lattice_velocity=0.1)
+
+    assert round(w.omega.value, 2) == 0.34 and scaling_result.relaxation_rate == w.omega.value
+    assert round(w.dt.value, 4) == 0.0244 and scaling_result.dt == w.dt.value
+    assert round(w.re.value) == 500 and s.reynolds_number == w.re.value
+
+    s = Scaling(physical_length=2, physical_velocity=0.002, kinematic_viscosity=4e-6, cells_per_length=2048)
+    w.scaling_type.value = 'acoustic (fixed dt)'
+    w.physical_length.value = 2
+    w.max_physical_velocity.value = 0.002
+    w.cells_per_length.value = 2048
+    w.kinematic_viscosity.value = 4
+    w.dt.value = 0.01
+    scaling_result = s.acoustic_scaling(dt=0.01)
+
+    assert round(w.omega.value, 2) == 1.60 and scaling_result.relaxation_rate == w.omega.value
+    assert w.max_lattice_velocity.value == 0.02048 and scaling_result.lattice_velocity == w.max_lattice_velocity.value
+    assert round(w.re.value) == 1000 and s.reynolds_number == w.re.value
diff --git a/lbmpy_tests/test_serial_scenarios.py b/lbmpy_tests/test_serial_scenarios.py
new file mode 100644
index 0000000000000000000000000000000000000000..05c057bac53f8767e16025b51b037b164b74aa32
--- /dev/null
+++ b/lbmpy_tests/test_serial_scenarios.py
@@ -0,0 +1,217 @@
+import os
+import numpy as np
+from lbmpy.scenarios import create_lid_driven_cavity as run_ldc_lbmpy
+from pystencils import make_slice
+from types import MappingProxyType
+
+
+def create_force_driven_channel(force=1e-6, domain_size=None, dim=2, radius=None, length=None,
+                                optimization=MappingProxyType({}), lbm_kernel=None, kernel_params=MappingProxyType({}),
+                                **kwargs):
+    from lbmpy.lbstep import LatticeBoltzmannStep
+    from lbmpy.boundaries import NoSlip
+    from pystencils.slicing import slice_from_direction
+    wall_boundary = NoSlip()
+
+    if domain_size is not None:
+        dim = len(domain_size)
+    else:
+        if dim is None or radius is None or length is None:
+            raise ValueError("Pass either 'domain_size' or 'dim', 'radius' and 'length'")
+
+    assert dim in (2, 3)
+    kwargs['force'] = tuple([force, 0, 0][:dim])
+
+    round_channel = False
+    if radius is not None:
+        assert length is not None
+        if dim == 3:
+            domain_size = (length, 2 * radius + 1, 2 * radius + 1)
+            round_channel = True
+        else:
+            if domain_size is None:
+                domain_size = (length, 2 * radius)
+
+    if 'force_model' not in kwargs:
+        kwargs['force_model'] = 'guo'
+
+    lb_step = LatticeBoltzmannStep(domain_size, optimization=optimization, lbm_kernel=lbm_kernel,
+                                   kernel_params=kernel_params, periodicity=(True, False, False), **kwargs)
+
+    boundary_handling = lb_step.boundary_handling
+    if dim == 2:
+        for direction in ('N', 'S'):
+            boundary_handling.set_boundary(wall_boundary, slice_from_direction(direction, dim))
+    elif dim == 3:
+        if round_channel:
+            def circle_mask_cb(_, y, z):
+                y_mid = np.max(y) // 2
+                z_mid = np.max(z) // 2
+                return (y - y_mid) ** 2 + (z - z_mid) ** 2 > radius ** 2
+
+            boundary_handling.set_boundary(wall_boundary, mask_callback=circle_mask_cb)
+        else:
+            for direction in ('N', 'S', 'T', 'B'):
+                boundary_handling.set_boundary(wall_boundary, slice_from_direction(direction, dim))
+
+    assert domain_size is not None
+    if 'force_model' not in kwargs:
+        kwargs['force_model'] = 'guo'
+
+    return lb_step
+
+
+def plot_velocity_fields(vel1, vel2):
+    import lbmpy.plot2d as plt
+    diff = np.average(np.abs(vel2 - vel1))
+    has_diff = diff > 1e-12
+    num_plots = 3 if has_diff else 2
+    plt.subplot(1, num_plots, 1)
+    plt.title("lbmpy")
+    plt.vector_field(vel1)
+    plt.subplot(1, num_plots, 2)
+    plt.title("walberla ref")
+    plt.vector_field(vel2)
+    if has_diff:
+        plt.title("Difference (%f)" % diff)
+        plt.subplot(1, num_plots, 3)
+        plt.vector_field(vel2 - vel1)
+    plt.show()
+
+
+def compare_scenario(lbmpy_scenario_creator, walberla_scenario_creator, optimization=MappingProxyType({}),
+                     action='Testing', name='ss', plot="off", **kwargs):
+    if 'time_steps' in kwargs:
+        time_steps = kwargs['time_steps']
+        del kwargs['time_steps']
+    else:
+        time_steps = 100
+
+    ref_file_path = get_directory_reference_files()
+
+    if action == 'Testing':
+        reference = np.load(os.path.join(ref_file_path, name + ".npz"))
+
+        lbmpy_version = lbmpy_scenario_creator(optimization=optimization, **kwargs)
+        lbmpy_version.run(time_steps)
+
+        rho_lbmpy = lbmpy_version.density_slice(make_slice[:, :] if lbmpy_version.dim == 2 else make_slice[:, :, :])
+        vel_lbmpy = lbmpy_version.velocity_slice(make_slice[:, :] if lbmpy_version.dim == 2 else make_slice[:, :, :])
+
+        if plot == "on":
+            plot_velocity_fields(vel_lbmpy, reference['vel'])
+
+        np.testing.assert_almost_equal(reference['rho'], rho_lbmpy, err_msg="Density fields are different")
+        np.testing.assert_almost_equal(reference['vel'], vel_lbmpy, err_msg="Velocity fields are different")
+
+    else:
+
+        wlb_time_loop = walberla_scenario_creator(**kwargs)
+        pdfs_wlb, rho_wlb, vel_wlb = wlb_time_loop(time_steps)
+
+        if os.path.exists(ref_file_path + name + ".npz"):
+            os.remove(ref_file_path + name + ".npz")
+        np.savez_compressed(ref_file_path + name, pdfs=pdfs_wlb, rho=rho_wlb, vel=vel_wlb)
+
+
+def get_directory_reference_files():
+    script_file = os.path.realpath(__file__)
+    script_dir = os.path.dirname(script_file)
+    return os.path.join(script_dir, "reference_files")
+
+
+def compare_lid_driven_cavity(optimization=MappingProxyType({}), action='Testing', plot="off", **kwargs):
+    if kwargs['method'] == 'MRT':
+        name = "LidDrivenCavity_" + kwargs['method']
+    else:
+        name = "LidDrivenCavity_" + kwargs['method'] + "_" + kwargs['force_model']
+    if kwargs['compressible']:
+        name = name + "_compressible"
+    else:
+        name = name + "_incompressible"
+
+    try:
+        from lbmpy_tests.walberla_scenario_setup import create_lid_driven_cavity as run_lid_driven_cavity_walberla
+    except ImportError:
+        run_lid_driven_cavity_walberla = None
+
+    return compare_scenario(run_ldc_lbmpy, run_lid_driven_cavity_walberla, optimization, action, name, plot, **kwargs)
+
+
+def compare_force_driven_channel(optimization=MappingProxyType({}), action='Testing', plot="off", **kwargs):
+    from functools import partial
+    lbmpy_func = partial(create_force_driven_channel, dim=2)
+
+    name = "ForceDrivenChannel_" + kwargs['force_model']
+    if kwargs['compressible']:
+        name = name + "_compressible"
+    else:
+        name = name + "_incompressible"
+
+    try:
+        from lbmpy_tests.walberla_scenario_setup import create_lid_driven_cavity as run_force_driven_channel_walberla
+    except ImportError:
+        run_force_driven_channel_walberla = None
+
+    return compare_scenario(lbmpy_func, run_force_driven_channel_walberla, optimization, action, name, plot, **kwargs)
+
+
+def test_channel_srt(action='Testing', plot="off"):
+    params = {'force': 0.0001,
+              'radius': 40,
+              'length': 40,
+              'method': 'SRT',
+              'stencil': 'D2Q9',
+              'time_steps': 500,
+              'maxwellian_moments': False,
+              'relaxation_rates': [1.8]}
+
+    if action == 'Testing' or action == 'Regenerate':
+        for force_model_name in ('simple', 'luo', 'guo'):
+            for compressible in (False, True):
+                print("%s Channel SRT, Force Model %s, compressible %d" % (action, force_model_name, compressible))
+                compare_force_driven_channel(compressible=compressible, force_model=force_model_name,
+                                             action=action, plot=plot, **params)
+    else:
+        print("Possible Actions: Regenerate or Testing")
+
+
+def test_ldc_srt(action='Testing', plot="off"):
+    force = (0.0001, -0.00002)
+    if action == 'Testing' or action == 'Regenerate':
+        for force_model_name in ('simple', 'luo', 'guo'):
+            for compressible in (False, True):
+                print("%s LidDrivenCavity SRT, Force Model %s, compressible %d" % (action, force_model_name,
+                                                                                   compressible))
+                compare_lid_driven_cavity(domain_size=(16, 19), lid_velocity=0.005, stencil='D2Q9',
+                                          method='SRT', relaxation_rates=[1.8], compressible=compressible,
+                                          maxwellian_moments=False,
+                                          force=force, force_model=force_model_name, action=action, plot=plot)
+    else:
+        print("Possible Actions: Regenerate or Testing")
+
+
+def test_ldc_trt(action='Testing', plot="off"):
+    f = (0.0001, -0.00002, 0.0000124)
+    if action == 'Testing' or action == 'Regenerate':
+        for force_modelName in ('luo',):  # guo for multiple relaxation rates has to be implemented...
+            for compressible in (True, False):
+                print("%s LidDrivenCavity TRT, Force Model %s, compressible %d" % (action, force_modelName,
+                                                                                   compressible))
+                # print("testing", force_modelName, compressible)
+                compare_lid_driven_cavity(domain_size=(16, 17, 18), lid_velocity=0.005, stencil='D3Q19',
+                                          method='TRT', relaxation_rates=[1.8, 1.3], compressible=compressible,
+                                          maxwellian_moments=False,
+                                          force=f, force_model=force_modelName, action=action, plot=plot)
+    else:
+        print("Possible Actions: Regenerate or Testing")
+
+
+def test_ldc_mrt(action='Testing', plot="off"):
+    if action == 'Testing' or action == 'Regenerate':
+        print("%s LidDrivenCavity MRT, compressible 0" % action)
+        compare_lid_driven_cavity(domain_size=(16, 17, 18), lid_velocity=0.005, stencil='D3Q19',
+                                  method='MRT', compressible=False, maxwellian_moments=False,
+                                  relaxation_rates=[1, 1.3, 1.4, 1.5, 1.25, 1.36, 1.12], action=action, plot=plot)
+    else:
+        print("Possible Actions: Regenerate or Testing")
diff --git a/lbmpy_tests/test_simple_equilibrium_conservation.py b/lbmpy_tests/test_simple_equilibrium_conservation.py
new file mode 100644
index 0000000000000000000000000000000000000000..3adb861fad4cc62a95ba242cd1c5d674906ecd63
--- /dev/null
+++ b/lbmpy_tests/test_simple_equilibrium_conservation.py
@@ -0,0 +1,22 @@
+import numpy as np
+from lbmpy.creationfunctions import create_lb_function
+
+
+def test_srt():
+    src = np.zeros((3, 3, 9))
+    dst = np.zeros_like(src)
+    cuda = False
+    opt_params = {} if not cuda else {'target': 'gpu'}
+    func = create_lb_function(method='srt', stencil='D2Q9', relaxation_rates=[1.8], compressible=False,
+                              optimization=opt_params)
+
+    if cuda:
+        import pycuda.gpuarray as gpuarray
+        gpu_src, gpu_dst = gpuarray.to_gpu(src), gpuarray.to_gpu(dst)
+        func(src=gpu_src, dst=gpu_dst)
+        gpu_src.get(src)
+        gpu_dst.get(dst)
+    else:
+        func(src=src, dst=dst)
+
+    np.testing.assert_allclose(np.sum(np.abs(dst)), 0.0, atol=1e-13)
diff --git a/lbmpy_tests/test_sparse_lbm.ipynb b/lbmpy_tests/test_sparse_lbm.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..855bb151c25525f7079fc40d4aa0651d4d73b923
--- /dev/null
+++ b/lbmpy_tests/test_sparse_lbm.ipynb
@@ -0,0 +1,369 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.sparse import *\n",
+    "from pystencils.field import FieldType\n",
+    "import pycuda.gpuarray as gpuarray\n",
+    "\n",
+    "import pystencils as ps"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Sparse (list based) LBM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "domain_size = (20, 20)\n",
+    "omega = 1.8\n",
+    "target = 'cpu'\n",
+    "\n",
+    "ghost_layers = 1\n",
+    "arr_size = tuple(ds + 2 * ghost_layers for ds in domain_size)\n",
+    "lid_velocity = 0.01\n",
+    "force = 1e-6\n",
+    "\n",
+    "channel = False\n",
+    "if channel:\n",
+    "    kwargs={'force': (force, 0)}\n",
+    "else:\n",
+    "    kwargs = {}\n",
+    "\n",
+    "method = create_lb_method(stencil='D2Q9', relaxation_rate=omega, compressible=False, **kwargs)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ubb = UBB( (lid_velocity, 0) )\n",
+    "noslip = NoSlip()\n",
+    "flags = {\n",
+    "    'fluid': 1, \n",
+    "    noslip: 2,\n",
+    "    ubb: 4,\n",
+    "}\n",
+    "flag_arr = np.zeros(arr_size, dtype=np.uint16)\n",
+    "flag_arr.fill(flags['fluid'])\n",
+    "\n",
+    "if channel:\n",
+    "    flag_arr[0, :] = 0\n",
+    "    flag_arr[-1, :] = 0   \n",
+    "    flag_arr[:, 0] = flags[noslip]\n",
+    "    flag_arr[:, -1] = flags[noslip]\n",
+    "else:\n",
+    "    flag_arr[:, -1] = flags[ubb]\n",
+    "    flag_arr[:, 0] = flags[noslip]\n",
+    "    flag_arr[0, :] = flags[noslip]\n",
+    "    flag_arr[-1, :] = flags[noslip]\n",
+    "\n",
+    "plt.scalar_field(flag_arr)\n",
+    "plt.colorbar();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Mappings"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mapping = SparseLbMapper(method.stencil, flag_arr, flags['fluid'], flags[noslip], flags[ubb])\n",
+    "index_arr = mapping.create_index_array(ghost_layers)\n",
+    "\n",
+    "# Arrays\n",
+    "#index_arr = index_arr_linear.reshape([len(method.stencil), mapping.num_fluid_cells])\n",
+    "#index_arr = index_arr.swapaxes(0, 1)\n",
+    "\n",
+    "pdf_arr = np.empty((len(mapping), len(method.stencil)), order='f')\n",
+    "pdf_arr_tmp = np.empty_like(pdf_arr)\n",
+    "\n",
+    "vel_arr = np.ones([mapping.num_fluid_cells, method.dim], order='f')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pdf_field, pdf_field_tmp, vel_field = ps.fields(\"f(9), d(9), u(2): [1D]\",\n",
+    "                                                #f=pdf_arr[:mapping.num_fluid_cells],\n",
+    "                                                #d=pdf_arr_tmp[:mapping.num_fluid_cells],\n",
+    "                                                #u=vel_arr\n",
+    "                                               )\n",
+    "pdf_field.field_type = FieldType.CUSTOM\n",
+    "pdf_field.pdf_field_tmp = FieldType.CUSTOM"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Macroscopic quantities"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cqc = method.conserved_quantity_computation\n",
+    "inp_eqs = cqc.equilibrium_input_equations_from_init_values()\n",
+    "setter_eqs = method.get_equilibrium(conserved_quantity_equations=inp_eqs)\n",
+    "setter_eqs = setter_eqs.new_with_substitutions({sym: pdf_field(i)\n",
+    "                                                for i, sym in enumerate(method.post_collision_pdf_symbols)})\n",
+    "kernel_initialize = ps.create_kernel(setter_eqs, ghost_layers=((0, 0),), ).compile()\n",
+    "\n",
+    "def init():\n",
+    "    kernel_initialize(f=pdf_arr[:mapping.num_fluid_cells])\n",
+    "init()\n",
+    "\n",
+    "\n",
+    "getter_eqs = cqc.output_equations_from_pdfs(pdf_field.center_vector,\n",
+    "                                            {'velocity': vel_field})\n",
+    "kernel_compute_u = ps.create_kernel(getter_eqs, ghost_layers=((0,0),) ).compile()\n",
+    "\n",
+    "def get_velocity(arr=pdf_arr):\n",
+    "    fluid_cell_arr = mapping.coordinates\n",
+    "    kernel_compute_u(f=pdf_arr[:mapping.num_fluid_cells], u=vel_arr)\n",
+    "    full_velocity_arr = np.zeros(flag_arr.shape + (2,), dtype=np.float64)\n",
+    "    full_velocity_arr.fill(np.nan)\n",
+    "    arr = fluid_cell_arr[:mapping.num_fluid_cells]\n",
+    "    full_velocity_arr[arr['x'], arr['y']] = vel_arr\n",
+    "    return full_velocity_arr[1:-1, 1:-1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Stream Collide Kernel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/latex": [
+       "$$\\left \\{ d_{0} : {{d}_{0}}, \\quad d_{1} : {{d}_{0}^{1}}, \\quad d_{2} : {{d}_{0}^{2}}, \\quad d_{3} : {{d}_{0}^{3}}, \\quad d_{4} : {{d}_{0}^{4}}, \\quad d_{5} : {{d}_{0}^{5}}, \\quad d_{6} : {{d}_{0}^{6}}, \\quad d_{7} : {{d}_{0}^{7}}, \\quad d_{8} : {{d}_{0}^{8}}, \\quad f_{0} : {{f}_{0}}, \\quad f_{1} : {{f}_{\\mathbf{{idx}_{0}}}}, \\quad f_{2} : {{f}_{\\mathbf{{idx}_{0}^{1}}}}, \\quad f_{3} : {{f}_{\\mathbf{{idx}_{0}^{2}}}}, \\quad f_{4} : {{f}_{\\mathbf{{idx}_{0}^{3}}}}, \\quad f_{5} : {{f}_{\\mathbf{{idx}_{0}^{4}}}}, \\quad f_{6} : {{f}_{\\mathbf{{idx}_{0}^{5}}}}, \\quad f_{7} : {{f}_{\\mathbf{{idx}_{0}^{6}}}}, \\quad f_{8} : {{f}_{\\mathbf{{idx}_{0}^{7}}}}\\right \\}$$"
+      ],
+      "text/plain": [
+       "{d₀: d_C__0, d₁: d_C__1, d₂: d_C__2, d₃: d_C__3, d₄: d_C__4, d₅: d_C__5, d₆: d\n",
+       "_C__6, d₇: d_C__7, d₈: d_C__8, f₀: f_C__0, f₁: f_000035D373, f₂: f_000035D373,\n",
+       " f₃: f_000035D373, f₄: f_000035D373, f₅: f_000035D373, f₆: f_000035D373, f₇: f\n",
+       "_000035D373, f₈: f_000035D373}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#index_field = ps.Field.create_from_numpy_array(\"idx\", index_arr, index_dimensions=1)\n",
+    "index_field = ps.Field.create_generic(\"idx\", spatial_dimensions=1, index_dimensions=1, dtype=index_arr.dtype)\n",
+    "\n",
+    "collision_rule = method.get_collision_rule()\n",
+    "\n",
+    "Q = len(method.stencil)\n",
+    "symbol_subs = {sym: pdf_field.absolute_access((index_field(i-1),),()) \n",
+    "               for i, sym in enumerate(method.pre_collision_pdf_symbols)}\n",
+    "\n",
+    "symbol_subs.update({sym: pdf_field_tmp(i) for i, sym in enumerate(method.post_collision_pdf_symbols)})\n",
+    "\n",
+    "symbol_subs[method.pre_collision_pdf_symbols[0]] = pdf_field(0) # special case for center\n",
+    "symbol_subs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "collision_rule = method.get_collision_rule()\n",
+    "update_rule = collision_rule.new_with_substitutions(symbol_subs)\n",
+    "kernel_stream_collide = ps.create_kernel(update_rule, ghost_layers=[(0,0)], target=target).compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Boundary Kernels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if not channel:\n",
+    "    if target == 'gpu':\n",
+    "        raise NotImplementedError(\"UBB on GPU not working yet\")\n",
+    "        \n",
+    "    ubb_mapper = SparseLbBoundaryMapper(ubb, method, pdf_field)\n",
+    "    ubb_kernel = ps.create_kernel(ubb_mapper.assignments(), ghost_layers=0).compile()\n",
+    "    ubb_idx_arr = ubb_mapper.create_index_arr(mapping, flags[ubb])\n",
+    "    ps.show_code(ubb_kernel.ast)\n",
+    "    def handle_ubb():\n",
+    "        ubb_kernel(indexField=ubb_idx_arr, f=pdf_arr[:mapping.num_fluid_cells])\n",
+    "else:\n",
+    "    def handle_ubb():\n",
+    "        pass"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Time Loop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def time_step():\n",
+    "    global pdf_arr, pdf_arr_tmp, index_arr\n",
+    "    handle_ubb()\n",
+    "    if target == 'gpu':\n",
+    "        gpu_pdf_arr = gpuarray.to_gpu(pdf_arr)\n",
+    "        gpu_pdf_arr_tmp = gpuarray.to_gpu(pdf_arr_tmp)\n",
+    "        gpu_index_arr = gpuarray.to_gpu(index_arr)\n",
+    "    \n",
+    "        kernel_stream_collide(f=gpu_pdf_arr[:mapping.num_fluid_cells], \n",
+    "                          d=gpu_pdf_arr_tmp[:mapping.num_fluid_cells], \n",
+    "                          idx=gpu_index_arr)\n",
+    "    \n",
+    "        pdf_arr = gpu_pdf_arr.get()\n",
+    "        pdf_arr_tmp = gpu_pdf_arr_tmp.get()\n",
+    "        index_arr = gpu_index_arr.get()\n",
+    "    else:\n",
+    "        kernel_stream_collide(f=pdf_arr[:mapping.num_fluid_cells], \n",
+    "                              d=pdf_arr_tmp[:mapping.num_fluid_cells], \n",
+    "                              idx=index_arr)\n",
+    "    pdf_arr_tmp, pdf_arr = pdf_arr, pdf_arr_tmp\n",
+    "\n",
+    "def run(steps=100):\n",
+    "    for t in range(steps):\n",
+    "        time_step()\n",
+    "    return get_velocity()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "init()\n",
+    "result = run(100)\n",
+    "plt.vector_field(result, step=1);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Check against reference"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if channel:\n",
+    "    reference = create_channel(domain_size, force=force, lb_method=method)\n",
+    "else:\n",
+    "    reference = create_lid_driven_cavity(domain_size, relaxation_rate=omega, lid_velocity=lid_velocity,\n",
+    "                                         compressible=False)\n",
+    "reference.run(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "np.testing.assert_almost_equal(reference.velocity[:, :], result)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/test_split_optimization.py b/lbmpy_tests/test_split_optimization.py
new file mode 100644
index 0000000000000000000000000000000000000000..76342617ed941b2fee819c39b063aeb292860338
--- /dev/null
+++ b/lbmpy_tests/test_split_optimization.py
@@ -0,0 +1,66 @@
+import pytest
+import numpy as np
+from pystencils.sympyextensions import count_operations_in_ast
+from lbmpy.creationfunctions import create_lb_ast
+from lbmpy.scenarios import create_lid_driven_cavity
+
+
+def test_split_number_of_operations():
+    # For the following configurations the number of operations for splitted and un-splitted version are
+    # exactly equal. This is not true for D3Q15 and D3Q27 because some sub-expressions are computed in multiple
+    # splitted, inner loops.
+    for stencil in ['D2Q9', 'D3Q19']:
+        for compressible in (True, False):
+            for method in ('srt', 'trt'):
+                common_params = {'stencil': stencil,
+                                 'method': method,
+                                 'compressible': compressible,
+                                 'force': (1e-6, 1e-5, 1e-7)
+                                 }
+                ast_with_splitting = create_lb_ast(optimization={'split': True}, **common_params)
+                ast_without_splitting = create_lb_ast(optimization={'split': False}, **common_params)
+
+                op_with_splitting = count_operations_in_ast(ast_with_splitting)
+                op_without_splitting = count_operations_in_ast(ast_without_splitting)
+                assert op_without_splitting['muls'] == op_with_splitting['muls']
+                assert op_without_splitting['adds'] == op_with_splitting['adds']
+                assert op_without_splitting['divs'] == op_with_splitting['divs']
+
+
+@pytest.mark.longrun
+def test_equivalence():
+    relaxation_rates = [1.8, 1.7, 1.0]
+    for stencil in ['D2Q9', 'D3Q15', 'D3Q19', 'D3Q27']:
+        for compressible in (True, False):
+            for method in ('srt', 'mrt3'):
+                for force in ((0, 0, 0), (1e-6, 1e-7, 2e-6)):
+                    common_params = {'domain_size': (20, 30) if stencil.startswith('D2') else (10, 13, 7),
+                                     'stencil': stencil,
+                                     'method': method,
+                                     'compressible': compressible,
+                                     'force': force,
+                                     'relaxation_rates': relaxation_rates}
+                    print("Running Scenario", common_params)
+                    with_split = create_lid_driven_cavity(optimization={'split': True}, **common_params)
+                    without_split = create_lid_driven_cavity(optimization={'split': False}, **common_params)
+                    with_split.run(100)
+                    without_split.run(100)
+                    np.testing.assert_almost_equal(with_split.velocity_slice(), without_split.velocity_slice())
+
+
+def test_equivalence_short():
+    relaxation_rates = [1.8, 1.7, 1.0]
+    for stencil, compressible, method, force in [('D2Q9', True, 'srt', 1e-7), ('D3Q19', False, 'mrt3', 0)]:
+        dim = int(stencil[1])
+        common_params = {'domain_size': (20, 30) if stencil.startswith('D2') else (10, 13, 7),
+                         'stencil': stencil,
+                         'method': method,
+                         'compressible': compressible,
+                         'force': (force, 0, 0)[:dim],
+                         'relaxation_rates': relaxation_rates}
+        print("Running Scenario", common_params)
+        with_split = create_lid_driven_cavity(optimization={'split': True}, **common_params)
+        without_split = create_lid_driven_cavity(optimization={'split': False}, **common_params)
+        with_split.run(100)
+        without_split.run(100)
+        np.testing.assert_almost_equal(with_split.velocity_slice(), without_split.velocity_slice())
diff --git a/lbmpy_tests/test_srt_trt_simplifications.py b/lbmpy_tests/test_srt_trt_simplifications.py
new file mode 100644
index 0000000000000000000000000000000000000000..a95247de0250722f297c05ffa4fba5119ae7cb3b
--- /dev/null
+++ b/lbmpy_tests/test_srt_trt_simplifications.py
@@ -0,0 +1,66 @@
+"""
+This unittest checks the simplification quality of SRT and TRT (compressible and incompressible) against
+known acceptable values.
+"""
+import sympy as sp
+
+from lbmpy.forcemodels import Guo
+from lbmpy.simplificationfactory import create_simplification_strategy
+from lbmpy.methods import create_srt, create_trt, create_trt_with_magic_number
+from lbmpy.stencils import get_stencil
+
+
+def check_method(method, limits_default, limits_cse):
+    strategy = create_simplification_strategy(method, cse_pdfs=False)
+    strategy_with_cse = create_simplification_strategy(method, cse_pdfs=True)
+
+    collision_rule = method.get_collision_rule()
+
+    ops_default = strategy(collision_rule).operation_count
+    ops_cse = strategy_with_cse(collision_rule).operation_count
+
+    assert ops_default['adds'] <= limits_default[0]
+    assert ops_default['muls'] <= limits_default[1]
+    assert ops_default['divs'] <= limits_default[2]
+
+    assert ops_cse['adds'] <= limits_cse[0]
+    assert ops_cse['muls'] <= limits_cse[1]
+    assert ops_cse['divs'] <= limits_cse[2]
+
+
+def test_simplifications_srt_d2q9_incompressible():
+    omega = sp.symbols('omega')
+    method = create_srt(get_stencil("D2Q9"), omega, compressible=False, equilibrium_order=2)
+    check_method(method, [53, 46, 0], [49, 30, 0])
+
+
+def test_simplifications_srt_d2q9_compressible():
+    omega = sp.symbols('omega')
+    method = create_srt(get_stencil("D2Q9"), omega, compressible=True, equilibrium_order=2)
+    check_method(method, [53, 57, 1], [53, 41, 1])
+
+
+def test_simplifications_trt_d2q9_incompressible():
+    o1, o2 = sp.symbols("omega_1 omega_2")
+    method = create_trt(get_stencil("D2Q9"), o1, o2, compressible=False)
+    check_method(method, [77, 86, 0], [65, 38, 0])
+
+
+def test_simplifications_trt_d2q9_compressible():
+    o1, o2 = sp.symbols("omega_1 omega_2")
+    method = create_trt(get_stencil("D2Q9"), o1, o2, compressible=True)
+    check_method(method, [77, 105, 1], [65, 55, 1])
+
+
+def test_simplifications_trt_d3q19_force_incompressible():
+    o1, o2 = sp.symbols("omega_1 omega_2")
+    force_model = Guo([sp.Rational(1, 3), sp.Rational(1, 2), sp.Rational(1, 5)])
+    method = create_trt(get_stencil("D3Q19"), o1, o2, compressible=False, force_model=force_model)
+    check_method(method, [268, 281, 0], [241, 175, 1])
+
+
+def test_simplifications_trt_d3q19_force_compressible():
+    o1, o2 = sp.symbols("omega_1 omega_2")
+    force_model = Guo([sp.Rational(1, 3), sp.Rational(1, 2), sp.Rational(1, 5)])
+    method = create_trt_with_magic_number(get_stencil("D3Q19"), o1, compressible=False, force_model=force_model)
+    check_method(method, [269, 282, 1], [242, 176, 1])
diff --git a/lbmpy_tests/test_stencils.py b/lbmpy_tests/test_stencils.py
new file mode 100644
index 0000000000000000000000000000000000000000..563db970fddf71b62bc72726ffb54b4b18d90573
--- /dev/null
+++ b/lbmpy_tests/test_stencils.py
@@ -0,0 +1,82 @@
+import pytest
+import itertools
+import warnings
+import sympy as sp
+import lbmpy.stencils as s
+import pystencils.stencils
+from lbmpy.stencils import get_stencil
+from pystencils.stencils import is_valid_stencil, is_symmetric_stencil, visualize_stencil
+
+
+def get_3d_stencils():
+    return s.get_stencil('D3Q15'), s.get_stencil('D3Q19'), s.get_stencil('D3Q27')
+
+
+def get_all_stencils():
+    return [
+        s.get_stencil('D2Q9', 'walberla'),
+        s.get_stencil('D3Q15', 'walberla'),
+        s.get_stencil('D3Q19', 'walberla'),
+        s.get_stencil('D3Q27', 'walberla'),
+
+        s.get_stencil('D2Q9', 'counterclockwise'),
+
+        s.get_stencil('D2Q9', 'braunschweig'),
+        s.get_stencil('D3Q19', 'braunschweig'),
+
+        s.get_stencil('D3Q27', 'premnath'),
+    ]
+
+
+def test_sizes():
+    assert len(s.get_stencil('D2Q9')) == 9
+    assert len(s.get_stencil('D3Q15')) == 15
+    assert len(s.get_stencil('D3Q19')) == 19
+    assert len(s.get_stencil('D3Q27')) == 27
+
+
+def test_dimensionality():
+    for d in s.get_stencil('D2Q9'):
+        assert len(d) == 2
+
+    for d in itertools.chain(*get_3d_stencils()):
+        assert len(d) == 3
+
+
+def test_uniqueness():
+    for stencil in get_3d_stencils():
+        direction_set = set(stencil)
+        assert len(direction_set) == len(stencil)
+
+
+def test_run_self_check():
+    for st in get_all_stencils():
+        assert pystencils.stencils.is_valid_stencil(st, max_neighborhood=1)
+        assert pystencils.stencils.is_symmetric_stencil(st)
+
+
+def test_inverse_direction():
+    assert pystencils.stencils.inverse_direction((1, 0, -1)), (-1, 0 == 1)
+
+
+def test_free_functions():
+    assert not is_symmetric_stencil([(1, 0), (0, 1)])
+    assert not is_valid_stencil([(1, 0), (1, 1, 0)])
+    assert not is_valid_stencil([(2, 0), (0, 1)], max_neighborhood=1)
+
+    with pytest.raises(ValueError) as e:
+        get_stencil("name_that_does_not_exist")
+    assert "No such stencil" in str(e)
+
+
+def test_visualize():
+    import matplotlib.pyplot as plt
+    plt.clf()
+    plt.cla()
+
+    d2q9, d3q19 = get_stencil("D2Q9"), get_stencil("D3Q19")
+    figure = plt.gcf()
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore")
+        visualize_stencil(d2q9, figure=figure, data=[str(i) for i in range(9)])
+        visualize_stencil(d3q19, figure=figure, data=sp.symbols("a_:19"))
diff --git a/lbmpy_tests/test_stokes_setup.ipynb b/lbmpy_tests/test_stokes_setup.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..d3496b50dbf0a3315a40529a8860834a6551fe0e
--- /dev/null
+++ b/lbmpy_tests/test_stokes_setup.ipynb
@@ -0,0 +1,782 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from pystencils.jupytersetup import *\n",
+    "from pystencils.slicing import add_ghost_layers, remove_ghost_layers\n",
+    "from lbmpy.relaxationrates import lattice_viscosity_from_relaxation_rate, relaxation_rate_from_lattice_viscosity\n",
+    "\n",
+    "\n",
+    "def discrete_l2_norm_by_number_of_nodes(field):\n",
+    "    squared_sum = np.sqrt(np.sum(field ** 2, axis=-1))\n",
+    "    return np.linalg.norm(squared_sum) / np.sqrt(squared_sum.size)\n",
+    "\n",
+    "\n",
+    "def discrete_linf_norm(field):\n",
+    "    return np.max(np.abs(field))\n",
+    "\n",
+    "\n",
+    "def add_flipped_on_top(field):\n",
+    "    flipped = np.copy(field)\n",
+    "    flipped[:, :, 1] *= -1\n",
+    "    flipped = np.flipud(flipped)\n",
+    "    return np.concatenate([field, flipped], axis=1)\n",
+    "\n",
+    "\n",
+    "def get_lower_half(field):\n",
+    "    assert field.shape[1] % 2 == 0\n",
+    "    return field[:, :field.shape[1]//2, :]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Stokes flow - comparison to an analytical solution\n",
+    "\n",
+    "This notebook sets up a periodic scenario with a given force field where the analytical (Stokes) solution is known. The simualted results are compared to the analytical solution.\n",
+    "\n",
+    "### Analytic part"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sym_x, sym_y, sym_mu = sp.symbols(\"x y mu\")\n",
+    "sym_k = sp.symbols(\"k\", integer=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Definition of stream function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\sin{\\left (y \\right )} \\sin{\\left (k x \\right )}$$"
+      ],
+      "text/plain": [
+       "sin(y)â‹…sin(kâ‹…x)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "potential = sp.sin(sym_k * sym_x) * sp.sin(sym_y)\n",
+    "potential"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Velocity field as curl of stream function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}\\sin{\\left (k x \\right )} \\cos{\\left (y \\right )}\\\\- k \\sin{\\left (y \\right )} \\cos{\\left (k x \\right )}\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡ sin(k⋅x)⋅cos(y)  ⎤\n",
+       "⎢                  ⎥\n",
+       "⎣-k⋅sin(y)⋅cos(k⋅x)⎦"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sym_vel = sp.Matrix([sp.diff(potential, sym_y), -sp.diff(potential, sym_x)])\n",
+    "sym_vel"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Definition of pressure field"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{1}{k} \\left(k^{2} + 1\\right) \\cos{\\left (y \\right )} \\cos{\\left (k x \\right )}$$"
+      ],
+      "text/plain": [
+       "⎛ 2    ⎞                \n",
+       "⎝k  + 1⎠⋅cos(y)⋅cos(k⋅x)\n",
+       "────────────────────────\n",
+       "           k            "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "p = (sym_k ** 2 + 1) * sp.cos(sym_k * sym_x) * sp.cos(sym_y) / sym_k\n",
+    "p"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Compute force field (for variable viscosities)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}\\left(k^{2} + 1\\right) \\left(\\mu - 1\\right) \\sin{\\left (k x \\right )} \\cos{\\left (y \\right )}\\\\- \\frac{1}{k} \\left(k^{2} + 1\\right) \\left(k^{2} \\mu + 1\\right) \\sin{\\left (y \\right )} \\cos{\\left (k x \\right )}\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡  ⎛ 2    ⎞                           ⎤\n",
+       "⎢  ⎝k  + 1⎠⋅(μ - 1)⋅sin(k⋅x)⋅cos(y)   ⎥\n",
+       "⎢                                     ⎥\n",
+       "⎢ ⎛ 2    ⎞ ⎛ 2      ⎞                 ⎥\n",
+       "⎢-⎝k  + 1⎠⋅⎝k ⋅μ + 1⎠⋅sin(y)⋅cos(k⋅x) ⎥\n",
+       "⎢─────────────────────────────────────⎥\n",
+       "⎣                  k                  ⎦"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def laplacian(term):\n",
+    "    return sp.diff(term, sym_x, sym_x) + sp.diff(term, sym_y, sym_y)    \n",
+    "\n",
+    "\n",
+    "symForce = sp.Matrix([- sym_mu * laplacian(sym_vel[0]) + sp.diff(p, sym_x),\n",
+    "                      - sym_mu * laplacian(sym_vel[1]) + sp.diff(p, sym_y)])\n",
+    "symForce = sp.simplify(symForce)\n",
+    "symForce"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_field_from_term(start, end, points, term):\n",
+    "    \"\"\"Get a numpy array from a symbolic description.\"\"\"\n",
+    "    xc, yc = np.meshgrid(np.linspace(start[0], end[0], points[0]),\n",
+    "                         np.linspace(start[1], end[1], points[1]), indexing='ij')    \n",
+    "    result = np.zeros(tuple(points) + (2,))\n",
+    "    result[:, :, 0] = sp.lambdify([sym_x, sym_y], term[0], 'numpy')(xc, yc)\n",
+    "    result[:, :, 1] = sp.lambdify([sym_x, sym_y], term[1], 'numpy')(xc, yc)\n",
+    "    return result"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Non-dimensionalization\n",
+    "\n",
+    "Parameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cells = 100\n",
+    "domain_size = np.pi\n",
+    "k = 2\n",
+    "mu = 1\n",
+    "density = 0.1\n",
+    "relaxation_rate = 1.2\n",
+    "method = 'srt'\n",
+    "force_model = 'guo'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Force factor 3.827935392629609e-08\n",
+      "VelFactor    0.000349065850398866\n",
+      "dx           0.031415926535897934\n",
+      "dt           1.0966227112321513e-05\n",
+      "Re           0.3141592653589793\n"
+     ]
+    }
+   ],
+   "source": [
+    "replacements = {sym_mu: mu, sym_k: k}\n",
+    "\n",
+    "dx = domain_size / cells\n",
+    "dm = dx**3 * density\n",
+    "nu_l = lattice_viscosity_from_relaxation_rate(relaxation_rate)\n",
+    "nu_phy = mu / density\n",
+    "dt = nu_l / nu_phy * dx**2\n",
+    "forceFactor = dt**2 * dx**2 / dm\n",
+    "vel_factor = dt / dx\n",
+    "Re = vel_factor * cells / nu_l\n",
+    "\n",
+    "print(\"Force factor\", forceFactor)\n",
+    "print(\"VelFactor   \", vel_factor)\n",
+    "print(\"dx          \", dx)\n",
+    "print(\"dt          \", dt)\n",
+    "print(\"Re          \", Re)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Setting up velocity field:|"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}\\sin{\\left (k x \\right )} \\cos{\\left (y \\right )}\\\\- k \\sin{\\left (y \\right )} \\cos{\\left (k x \\right )}\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡ sin(k⋅x)⋅cos(y)  ⎤\n",
+       "⎢                  ⎥\n",
+       "⎣-k⋅sin(y)⋅cos(k⋅x)⎦"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sym_vel"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Setting up force field:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$4.781968159653842e-07$$"
+      ],
+      "text/plain": [
+       "4.781968159653842e-07"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def get_force_field(start, end, points):\n",
+    "    x, y = np.meshgrid(np.linspace(start[0], end[0], points[0]),\n",
+    "                       np.linspace(start[1], end[1], points[1]), indexing='ij')\n",
+    "    force_val = np.zeros(tuple(points) + (2,))\n",
+    "    force_val[:, :, 1] = -(np.cos(k * x) * np.sin(y) * (k ** 4 + 2 * k * k + 1)) / k\n",
+    "    return force_val\n",
+    "\n",
+    "\n",
+    "force = get_field_from_term((dx / 2, dx / 2), (np.pi - dx / 2, np.pi - dx / 2), [cells, cells],\n",
+    "                            symForce.subs(replacements)) * forceFactor\n",
+    "\n",
+    "plt.vector_field(force, step=8)\n",
+    "np.max(force)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "offset = dx / 2\n",
+    "analytical_solution = get_field_from_term(start=(offset, offset),\n",
+    "                                          end=(np.pi - offset, np.pi - offset),\n",
+    "                                          points=[cells, cells],\n",
+    "                                          term=sym_vel.subs(replacements))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Scenario set up:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "force = force.copy(order='F')\n",
+    "forceWithGl = add_ghost_layers(force, index_dimensions=1)\n",
+    "forceField = Field.create_from_numpy_array('forceArr', forceWithGl, index_dimensions=1)\n",
+    "initialVelocity = analytical_solution / dx * dt\n",
+    "\n",
+    "sc = create_fully_periodic_flow(initial_velocity=initialVelocity, method=method,\n",
+    "                                force=(0, forceField(1)), force_model=force_model,\n",
+    "                                kernel_params={'forceArr': forceWithGl},\n",
+    "                                relaxation_rate=relaxation_rate,\n",
+    "                                compressible=False, equilibrium_order=1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# View generated code\n",
+    "#show_code(sc.ast)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Boundary set up:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pi = np.pi\n",
+    "repl_sym_vel = sym_vel.subs(replacements)\n",
+    "vel_x_lambda = sp.lambdify([sym_x, sym_y], repl_sym_vel[0], 'numpy')\n",
+    "vel_y_lambda = sp.lambdify([sym_x, sym_y], repl_sym_vel[1], 'numpy')\n",
+    "\n",
+    "offset = 0  # 0.5*dx\n",
+    "\n",
+    "ubb_arr = np.zeros((cells + 2, cells + 2, 2))\n",
+    "# Left Border\n",
+    "ubb_arr[0, 1:-1, 0] = vel_x_lambda(offset, np.arange(0.5 * dx, pi, dx))\n",
+    "ubb_arr[0, 1:-1, 1] = vel_y_lambda(offset, np.arange(0.5 * dx, pi, dx))\n",
+    "# Right Border\n",
+    "ubb_arr[-1, 1:-1, 0] = vel_x_lambda(pi - offset, np.arange(0.5 * dx, pi, dx))\n",
+    "ubb_arr[-1, 1:-1, 1] = vel_y_lambda(pi - offset, np.arange(0.5 * dx, pi, dx))\n",
+    "# Lower Border\n",
+    "ubb_arr[1:-1, 0, 0] = vel_x_lambda(np.arange(0.5 * dx, pi, dx), offset)\n",
+    "ubb_arr[1:-1, 0, 1] = vel_y_lambda(np.arange(0.5 * dx, pi, dx), offset)\n",
+    "# Upper Border\n",
+    "ubb_arr[1:-1, -1, 0] = vel_x_lambda(np.arange(0.5 * dx, pi, dx), pi - offset)\n",
+    "ubb_arr[1:-1, -1, 1] = vel_y_lambda(np.arange(0.5 * dx, pi, dx), pi - offset)\n",
+    "\n",
+    "\n",
+    "ubb_arr[0, 0, 0] = vel_x_lambda(offset, offset)\n",
+    "ubb_arr[0, 0, 1] = vel_y_lambda(offset, offset)\n",
+    "\n",
+    "ubb_arr[0, -1, 0] = vel_x_lambda(offset, pi - offset)\n",
+    "ubb_arr[0, -1, 1] = vel_y_lambda(offset, pi - offset)\n",
+    "\n",
+    "ubb_arr[-1, 0, 0] = vel_x_lambda(pi - offset, offset)\n",
+    "ubb_arr[-1, 0, 1] = vel_y_lambda(pi - offset, offset)\n",
+    "\n",
+    "ubb_arr[-1, -1, 0] = vel_x_lambda(pi - offset, pi - offset)\n",
+    "ubb_arr[-1, -1, 1] = vel_y_lambda(pi - offset, pi - offset)\n",
+    "\n",
+    "ubb_arr *= vel_factor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from lbmpy.boundaries import UBB, NoSlip\n",
+    "from pystencils.slicing import slice_from_direction\n",
+    "\n",
+    "velField = Field.create_from_numpy_array('ubbField', ubb_arr, index_dimensions=1)\n",
+    "myUbb = UBB(velocity=(velField(0), velField(1)), adapt_velocity_to_force=True)\n",
+    "\n",
+    "for direction in ('W', 'E', 'S', 'N'):\n",
+    "    sc.boundary_handling.set_boundary(myUbb, slice_from_direction(direction, dim=2))\n",
+    "\n",
+    "plt.boundary_handling(sc.boundary_handling)\n",
+    "\n",
+    "sc.kernel_params['ubbField'] = ubb_arr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Run"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$0.0007012618474408325$$"
+      ],
+      "text/plain": [
+       "0.0007012618474408325"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sc.run(20000)\n",
+    "plt.vector_field(sc.velocity[:, :], step=4);\n",
+    "np.max(sc.velocity[:, :])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "L2  Error 0.007035092839391688\n",
+      "Inf Error 0.010440166565635706\n"
+     ]
+    }
+   ],
+   "source": [
+    "simulated_solution = sc.velocity[:, :] * dx / dt\n",
+    "l2_norm = discrete_l2_norm_by_number_of_nodes(simulated_solution - analytical_solution)\n",
+    "inf_norm = discrete_linf_norm(simulated_solution - analytical_solution)\n",
+    "assert l2_norm < 0.008\n",
+    "assert inf_norm < 0.11\n",
+    "print(\"L2  Error\", l2_norm)\n",
+    "print(\"Inf Error\", inf_norm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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gQQMOHjyo4ioiIvmcZcGvn5C5YTo+x7dyxgpjjnMIZ6r2Y0zbOtQrG2J3QrlKxhhaVilGyyrtiD3YmPs+G0z5/csZe2AtRQ/cRmbZZvhETYXKN2slYhHxLP8wM3q9VKtWja1bt7J27Vruv/9+2rdv/6fXfXx8MFmflw6HAz8/v4v3nU4nAN7e3rjd7ovvSUtL+9t+NmzYwPr169m8eTOBgYFERUVdctwfXenw3//lAPDy8rqYJSfpHFcREfEcv28hc15bWNaPE8cO80DmSKZXW87tk55i5rBWKq15WGTFMOaMjKLL+Gd5LGI5j2QO5czhvfBGTzIXdIKjP9gdUUTEdseOHSMwMJBBgwYxZcoUfvjh2j8bK1asyLZt23C73Rw+fJjvvvvub2Pi4+MJDQ0lMDCQPXv2sGXLlouv+fj4kJmZ+bf3tG7dmhUrVuByuTh9+jQbN26kadOm15zv39KMq4iI2O/MXpyfPor3rx9y1grlFddoXPX6M7ZNdSqFB9mdTnJQ3bJFeHVoC349WZfnPx9E0M6l3Pn7KopGt8FVqydebR+BsAi7Y4qI2GLHjh3cc889OBwOfHx8mD17NlOmTLmmbbRs2ZKIiAjq1q1LnTp1aNSo0d/GdOjQgTlz5lCvXj2qV69Os2bNLr42ZswY6tWrR6NGjVi6dOnF53v06MHmzZupX78+xhimT59OyZIl2bNnz7//ha+BLocjIiL2STyJa8PTmB+WkGL5MjuzC8dqDOPOjg2IKKZrgBYEe08m8srarVT9bRFjvNfia1yYpqNx3DQVAnUes4jknoJwORw7ZfdyOJpxFRGR3JeehLXpVVxfzwBXOq87b+HrUiOY0KUZjcqH2p1OclHVEsHMHB7Ft/vrMuGDnrQ7tYB+384l84c38G79X0yzceATYHdMERGxmYqriIjkHrcbfnqTzE8fxSf1DJ+4mvJW4REM6nQz0TWLX1xwQgqeGyoVpemkLqzd0YQRH33K4KSFtP3sMTK2zMW3w5NQp5cWcBIRKcC0OJOIiOSOEzvJiLkV3r+D7cmhjPCaRkKX+cy/ux/tapVQaRWMMXSqV4ro/w7maMdFjHY8xi+JfvDOSDIWdoEze+2OKCIiNtGMq4iIXF/pibi/eBq+nUOyO5BH3WMJv3EEM6OqEOir/w3J3/l6OxjaoiI9G03ktc/bs3JTNP/9fQVes5phWk7G0XoK+AbaHVNE8iHLsvQPqddBTqyrpMWZRETk+rAs2PUuGWvvwzvlFMudbfi6wh3c27M5FYpq4SW5entPJvL8qq9of+w1enl9RUZQWXy7PA/VO9odTUTykQMHDhAcHEzRokVVXnOQZVnExcWRmJhIRMSfV42/lsWZVFxFRCTnndlHxpq78T30JTvdFXnZbxy9u3Xn1tol9WVA/hXLslj90zE+XLOSKZlzqeY4SmblW/Hp/ByEVrA7nojkA5mZmRw5coS0tDS7o+Q7/v7+lC1bFh8fnz89r+IqIiL2cGbg/uoFrI0vkGJ586KzH/4txjCpbXUdFiw5IiEtk5c/2Y3393O4y3sVvg7wuvl+TPOJ4KX/xkRE8hIVVxERyX3Ht5O+cix+cbt539WCD0tN5J5eralaItjuZJIP7Twaz8urvqDPqVe51SuW9BIN8es9F8Kr2x1NRESu0rUUV60qLCIi2ePMwP3F07jntSH+zDHuZCrO7tHMHX+bSqtcN3XKFGHeHd2I67SAKdZdpJzYh2t2K9xfvQxul93xREQkh2nGVURE/r0TO0h/ewx+cbt519WSDRFTeLB3C4oX9rc7mRQgR8+nMu2tL+l8+Hk6en1PeolGWbOv1eyOJiIiV6AZVxERub5cmRdmWedGkXDmKJOZiukZzcvD26i0Sq4rExLAzNG3cr7zfO6xJpNyYi+u2S1xf/2KZl9FRPIJzbiKiMi1ObGT9JVj8DuzS7Os4nH+N/va5fDzdNDsq4iIR9OMq4iI5DzLwr1pFq65USScPsJd3KNZVvE4f559vZPUE7/inH0jVuzCC9cWFhGRPEkzriIi8s+STpP+zlj8DnzGOldjPox4kAf6tKR4sAqreK6j51N5+q0N9D38FK29dpBRtRO+PWZCYJjd0UREBM24iohITtr3Gekzm8GBjTzuHsGpTgt4afjNKq3i8cqEBDBjVAd+bbeIZ1wDMXs/IX1mczj4jd3RRETkGuVIcTXGLDDGnDLG7LzM61HGmHhjzLas2yM5sV8REbmOnBk4P34A3ujJwRR/Jge/yIA7nmBgs4oYY+xOJ3JVHA7DqNZV6DzuaSYFPsOxJAv3os64PnsSXE6744mIyFXKkUOFjTGtgSRgiWVZdS7xehQwxbKszteyXR0qLCJikzP7SFsxDP/TO3jd2ZZDkQ8ypVN9/H287E4m8q+lZDh55r1Y6u14it5eG0kv1QS/vvMhtILd0URECqRcP1TYsqyNwNmc2JaIiNjL+nEpmbNbkXbqAHc7plJ64Gs81L2RSqvkeYG+3jzRtxkBfeZxL3eSeWwnmbNaws5VdkcTEZF/kJvnuDY3xvxkjPnIGFM7F/crIiJXIzOVjFUTMO9PYGtmRR4pNZf77vovt9QsYXcykRzVqV4pJk2+n6nFZrEzowSsHE7mB1PAmWF3NBERuYwcW1XYGFMR+OAyhwoXBtyWZSUZY24DXrEsq+pltjMGGANQvnz5xocOHcqRfCIicgXnDpK2dBD+Z3Ywy9Udr5sfZMxNVXE4dC6r5F9Ol5tZ6/dQ6KsnGOX9EWklI/Ef8DoULm13NBGRAsHjVhW2LCvBsqykrPtrAR9jTLHLjJ1nWVakZVmR4eHhuRFPRKRg+/VTMl67kYzTv3G31300GfES49pUU2mVfM/by8HkW2tRbcirTDX/wX18B+mzWsGBjXZHExGRv8iV4mqMKWmylqA0xjTN2m9cbuxbREQuw+3C9dlTuN/sy770UB4sPpP77voPTSN0jUspWFpXC2fy5HuZGvoyh1P9cC/uhuurl8CDr3UvIlLQeOfERowxy4AooJgx5gjwKOADYFnWHKA3MN4Y4wRSgdutnDpGWURErl3KWdJWjMD/0BesdLVm/w1P8GLH+vh46fLeUjCVCQnghYn9ePb9yjTa9jCdP3uMtN+/x7/XHPAvbHc8EZECL8fOcb0edDkcEZHr4NiPpC0diCP5JNOsEdzQ6z90rKdz+kT+Z9XWw/zy/rPc41iKs3B5/AcugxK17I4lIpLveNw5riIi4hncP76JM7o9cUnp/KfQswye+KhKq8hf9Gxcju7jp/Ef//8jIf48mXPbYO16z+5YIiIFmoqriEhB4HaR+fFDON4fz7fOqsysEsP0O4dROTzI7mQiHqlmqcI8OXks0yvMY7uzHObtoWR+/rTOexURsYmKq4hIfpeWQNrrffHZ8iqvu9rx8y0LmTYoikJ+ObLMgUi+VSTAh+nD2rO51WLecd2Iz8ZnSFs2BDJS7I4mIlLgqLiKiORnZw+QOudmvA98zpPWSMoOeo1RUdXJWuhdRP6Bw2GY2L42gX3mMd09CN9f15A6rx3EH7U7mohIgaLiKiKSXx34ivTZUaSfO8YU/8e4/Y7HaVO9uN2pRPKkjvVKc9vYaUz1vh/X6d9Im30THNECkiIiuUXFVUQkH3J/vxDXkm4cTg/k8ZKv8uik8VQpHmx3LJE8rU6ZIkydPJkHi77IyRSDc35H3NuW2x1LRKRAUHEVEclPXE4y1kzB8eFdbHTWYUWDhUwf04PQQr52JxPJF4oH+zN9Qj/m14jhe2cVHO+NJfOTh8HtsjuaiEi+puIqIpJfpCeSurg3vlujiXF14thti3iwZzN8vPRRL5KT/Ly9eLx/a3bdsoilrlvw2TyDtDcHQWaq3dFERPItfZsREckPEo6TMrc9Pr9/yRNmLLWGzWBg80p2pxLJt4wxjIqqTukBs3nGGorvvo9Iib4Nks/YHU1EJF9ScRURyetO/Uzq7DZYcb9xv9+DDJrwCC0qF7M7lUiB0KZmCbqNe5IHvafgOLmD1Nk3Q9xvdscSEcl3VFxFRPKy/V+SMa8tiSmpPBz6HPdOmkSl8CC7U4kUKDVLFebOSf/l/uBppCbGkTb3Fjj8nd2xRETyFRVXEZE8yr1tOa7Xe3Iwowgvln+NpyYMoliQn92xRAqkUkUCeGLicKaVepXjab44F3bG2v2+3bFERPINFVcRkbzGssj8YjqO98bynbMaqxos4KnhtxHg62V3MpECLdjfh6dHd2dJrWi2O8thvTUU56bX7I4lIpIvqLiKiOQlrkzSVk3E58uneM/Vkj3tFnFfz2Z4OYzdyUQE8PFy8Ei/1mxutYhPXZF4f3o/6R9M1eVyRESyScVVRCSvyEghZUk//He8wWx3D/z6xDC8dXW7U4nIXxhjuKN9XZK7zWehqwN+sXNJXTYEnOl2RxMRybNUXEVE8oKUsyTP74z/oc950oyh6ciX6FivtN2pROQKekVWoPrQWTzHEAL2fkDKwp6Qnmh3LBGRPEnFVUTE0yUcI3nerfic+ImHfaYwYMKjNK4QancqEbkKLaoUo/PYp3jUaxK+RzeRrGu9ioj8KyquIiKeLO43Uua0xTr3Ow8VepRJE6focjcieUzNUoUZOeEBHva7D6/TP5Mytx2cP2x3LBGRPEXFVUTEUx3/ibS5bUlNTuCxsGd4YOI4ShbxtzuViPwL5YsG8p+Jk3mo8JM440+QOrctnP7F7lgiInmGiquIiAeyDmwkI6YjZ9IdTC/9Ck+MH0xIoK/dsUQkG4oH+/PIHSN5Ivx5ElPSSJ/XDo7E2h1LRCRPUHEVEfEw7t1rcC3pxcHMEOZVfo3/G9mDQF9vu2OJSA4o7O/Dk2Nv58Vyr3Ii3Y+MBZ2x9n1mdywREY+n4ioi4kGcW5fAW0PY7irPuw1ieGxQe3y99VEtkp/4+3jx5PDOLK4xl33O4riW9sW94x27Y4mIeDR9GxIR8RCZm17De80kvnbVZkurhUzt0RyHw9gdS0SuA28vBw/3b8PHkTFsdVWBd0Ze+IcrERG5JBVXEREPkLHheXw+vZ+PXU043HEhE9rXwxiVVpH8zBjD3V2bsiNqPl+76uC9ZhKZm+bYHUtExCOpuIqI2MmySP/0CXw3/B+rXS1I6RrNwBZV7U4lIrlo1M11ONxhAetcjfH59F4yv3zJ7kgiIh5HxVVExC6WRdqH9+O36QXecrXBq3c0PZtE2J1KRGwwsGU14rvEsMbVDJ8vHiN93ZNgWXbHEhHxGCquIiJ2cLtJfW8y/rGzWeLuQNH+s+lUv6zdqUTERr2bVoJeMax03YTfN8+RtvZBlVcRkSwqriIiuc3lJGXlWAJ+Wky0uxuVB8/kllql7E4lIh6gS4NyhNw+l6Wu9vh/P4vU9/8DbrfdsUREbJcjxdUYs8AYc8oYs/MyrxtjzAxjzD5jzHZjTKOc2K+ISJ7jyiR52XACd7/FTKsvDYa/RMuq4XanEhEP0rZ2KcoPnsV8d2cCti0kZeV4cLvsjiUiYqucmnFdBHS4wusdgapZtzHA7Bzar4hI3uFMJ+n1ARTat5oXzBBaj36OJhFF7U4lIh7oxmrFqTtsBq9ZvQncvZzk5SPA5bQ7loiIbXKkuFqWtRE4e4Uh3YAl1gVbgBBjjI6LE5GCIzONpCW3E3TwU55xjKLT2KeoVzbE7lQi4sGaVipKi1Ev8DIDKfTreyQvGwauTLtjiYjYIrfOcS0DHP7D4yNZz4mI5H//K62/f840r7H0Gf84NUoWtjuViOQBDcqF0H7MM7xohlBo3xqS3xym8ioiBVJuFVdziecuuUyeMWaMMSbWGBN7+vTp6xxLROQ6y0wjaUk/gg5/wTSvcfQf/yiVw4PsTiUieUit0oW5bexTvGCGUui3D0h6c4jKq4gUOLlVXI8A5f7wuCxw7FIDLcuaZ1lWpGVZkeHhWrBERPKwzDSSFvcl6PAGpnmNp//4R4goVsjuVCKSB9UoWZjOWeU16Le1JC1VeRWRgiW3iutqYEjW6sLNgHjLso7n0r5FRHJfZipJi/sQeGQj07wnMGD8wyqtIpIt1UsG02XcUzzvGE7Q/rUkvTEYnBl2xxIRyRU5dTmcZcBmoLox5ogxZqQxZpwxZlzWkLX/S2iDAAAgAElEQVTAfmAfEA1MyIn9ioh4pMxUkhb1IfDIVzztPYGB4x+iokqriOSAaiWC6Tb2/3jOMYKgAx+RtHSQyquIFAjGsi55qqlHiIyMtGJjY+2OISJy9TJSLsy0Hv2Gp70nMnj8A5QvGmh3KhHJZ/adSmTVnEeZ6p5PUsStBA18A7x97Y4lInJNjDFbLcuKvJqxuXWosIhI/peRQtKi3gQe/YZpPhMZMkGlVUSujyrFg+k57gmmO0YRdOATkl4foJlXEcnXVFxFRHJC1kJMgcc2Mc1nIkPHP0C5MJVWEbl+qhQPotf4x3nWMZqgQ+suHDasBZtEJJ9ScRURyS5nBomvDyDo6Fc84z1BpVVEck3l8CD6jH+M5xwjL8y8LhsOLqfdsUREcpyKq4hIdrgySVo6iODfP+NZ77EMGv+QSquI5KpK4UH0GPc4L5vBBO1bQ9JbY8DtsjuWiEiOUnEVEfm3XE6Slg0n6MAnPO8YSd9xj+qcVhGxRZXiwXQYO41XTX+CfnmH5JV3gNttdywRkRyj4ioi8m+4XSS9NYagfWt42TGY7uMe13VaRcRWNUoWps2oZ5lDbwrtXkbye3eBB189QkTkWqi4iohcK7ebpJV3EPTLO8w0t9NhzDSqFA+2O5WICHXKFKH5iOeZb3Wj0PbFpKy+R+VVRPIFFVcRkWthWSS/O5mg3cuYQ2+iRk2nRsnCdqcSEbmofvlQGgx/iSXWbQT+GE3K2gdVXkUkz1NxFRG5WpZFyuopFNqxhPlWN5qPeJ46ZYrYnUpE5G8aVyxK9SGv8qa7PYHfzyL10yfsjiQiki0qriIiV8OySPnoYQJ/jGGJdRsNhr9M/fKhdqcSEbmsGyoXo8LgWbzlvpmAzS+S9tl0uyOJiPxrKq4iIlch9fPpBH73Ksvd7ag+5FUaVwyzO5KIyD9qWbU4JQbO4X13K/y/eor0b16zO5KIyL+i4ioi8g/Sv55FwFfTeN/dirKDXuOGysXsjiQictVuql6CwD5z+dQdid+6+8mMXWJ3JBGRa6biKiJyBZmxS/Bb/wCfuJsQ2GcuraoVtzuSiMg1a1e3LOndYvjKXRevDyaTuX2V3ZFERK6JiquIyGVkbl+F1weT2eiuS0a3aNrVLWt3JBGRf61L4wiO3RpDrLsqjlWjcO352O5IIiJXTcVVROQSXHs+xrFqFLHuqpzoEEOXxhF2RxIRybZ+LWvwc5todrnL414xGPf+jXZHEhG5KiquIiJ/4d6/EfeKwex2l+PnNtH0bVHD7kgiIjlmaJv6bGo+jwOucDLf6It1+Hu7I4mI/CMVVxGRP7AOf0/mG3054ApnU/MYhrapb3ckEZEcN7ZDEz5qOJvjzsKkLeoJJ3baHUlE5IpUXEVE/ufETtIW9eSEM5iPG81hTIdIuxOJiFwXxhju7N6at2rP5LzTm5T5XeDMPrtjiYhcloqriAhA3G+kzO/Keac3b9eayaRuN2KMsTuViMh1Y4xhSp92LKz0EikZTpJiOkP8EbtjiYhckoqriEjCcZJiOpOWkc6iSi9xd9/2Kq0iUiA4HIapg7ryWtnpuFPPkxjdBZLj7I4lIvI3Kq4iUrClnCUhujOknGVW6WeYMqgrDodKq4gUHN5eDqYO68tLxf4Pn8TDJMR0hfREu2OJiPyJiquIFFwZycTP74F/wkFeKPoY94wYgI+XPhZFpODx9/Hiv2OG81zh+wk8u5v4hX0gM83uWCIiF+kbmogUTM504hf1I+jMTzwbfC//GTMKfx8vu1OJiNgmyM+bO8ZN4rmAyRQ5sZn4pUPB5bQ7logIoOIqIgWR20XCmyMocuwrnvefyPhxkyns72N3KhER24UV8mXouHt5yWskRQ5+TOLbE8Cy7I4lIqLiKiIFjGWR+M4kCu//gBleQxk47gGKBfnZnUpExGOUDgmg67gnmGf6ELxnBUkf3KfyKiK2U3EVkQIlee3DBO9aynx6cNvYpygbGmh3JBERj1M5PIgWI59nqdWBoK1zSPn8ObsjiUgBp+IqIgVG6oaXKPT9q6yw2hI54iWqFA+2O5KIiMeqUzaEykNmssbdksCvniJtS4zdkUSkAFNxFZECIT32dQI2PMZadzPKDXyN+uVD7Y4kIuLxmlUOJ7DvPL5wN8D34ylk7njX7kgiUkDlSHE1xnQwxvxijNlnjLnvEq8PM8acNsZsy7qNyon9iohcDeeej/D+4E6+cdfGq9c8WlQrYXckEZE845Y6ZUnoHMOP7iqwajSu/RvtjiQiBVC2i6sxxguYBXQEagH9jTG1LjF0hWVZDbJuOtZERHKF+9AW3CuGsstdgWMd5nNr/Qp2RxIRyXO6Na3KrpuiOeAqTuYbt2Md/8nuSCJSwOTEjGtTYJ9lWfsty8oAlgPdcmC7IiLZYp3cTfqS3hxxhfJ9i7n0aVHT7kgiInnWkFsa8mmj2cS5/ElZ0B3O7rc7kogUIDlRXMsAh//w+EjWc3/Vyxiz3Riz0hhTLgf2KyJyefFHSF7QnUSnF6vrzmTErU3tTiQikufd0a01S6u+REZGBokxXSHplN2RRKSAyIniai7x3F8v9rUGqGhZVj1gPbD4shszZowxJtYYE3v69OkciCciBU7KWRKiO+NOS2BBxee5s1dbjLnUR5WIiFwLYwx39+/Ca6Wm4ZV8iviYbpCWYHcsESkAcqK4HgH+OINaFjj2xwGWZcVZlpWe9TAaaHy5jVmWNc+yrEjLsiLDw8NzIJ6IFCgZycTHdMcv8Qgziv8fdw/uhcOh0ioiklO8vRzcPWIQL4U+SOC5Xzi/qC840//5jSIi2ZATxfV7oKoxJsIY4wvcDqz+4wBjTKk/POwK/JwD+xUR+TNXJucXDyAobjvPF76Xu0YNx9dbV/0SEclpAb5eTBwzgRcD7yTkxGbilw4Dt8vuWCKSj2X7G51lWU5gIvAJFwrpW5Zl7TLGPGGM6Zo17E5jzC5jzE/AncCw7O5XRORP3G7iV4wl5OgGXvKfwLixdxLk5213KhGRfKtIoA9Dx93HDO9hFDmwloRV/wHrr2eLiYjkDGN58AdMZGSkFRsba3cMEckDEtc8QPDWWczx6k/niS9SNjTQ7kgiIgXCb6eT+Oq1CQyz3iep5X0Etbvf7kgikkcYY7ZalhV5NWN1DJ2I5HkpX84geOssltOeqFHPqrSKiOSiyuFBNBz+Cu+7byTom2dI/XaR3ZFEJB9ScRWRPC1j29sEfvEwn7ibEjFoFjVKFbE7kohIgVO/fCgh/eey0V0P34/+Q+bPH9kdSUTyGRVXEcmzXPs2YN4bz3fuGphe0dxQpbjdkURECqybapYhrlMMu9wVsN4aivv37+2OJCL5iIqriORJ1vHtZL7Zn/3uEhxoG037+hXtjiQiUuD1uKE6W1vN5ZgrhLQlveDMXrsjiUg+oeIqInnPuUMkL+jBWZc/X0TOpl/renYnEhGRLMPaNeX9uq+SkmmRGNMVEk/YHUlE8gEVVxHJW1LOEh/TFVdGCsuqvsTYLjfanUhERP7AGMPEXu2ZX346jtQ44qO7QlqC3bFEJI9TcRWRvCMjhfMxPfBPOsprpZ5icv+uGGPsTiUiIn/h5TBMHtKXV4o+TGD8Ps4t6gfOdLtjiUgepuIqInmDy8n5JQMJjvuJF4vcy+QRQ/D20keYiIin8vfxYuKYcbxc6E5CT2zi/LJR4HbbHUtE8ih96xMRz2dZxK+cRMiRz3nVfyxjx04m0Nfb7lQiIvIPCvv7MGTcfbzmPZiQ31aTsOZ+uyOJSB6l4ioiHi/x06cp8vObLHD0pNfYRwkr5Gt3JBERuUolCvvTfvTTLKMDhX+cQ/KXM+yOJCJ5kIqriHi01O8WE7z5Wd63WtN0xEuUCwu0O5KIiFyjKiWCqTpkJp+4mxLwxSOk//SO3ZFEJI9RcRURj5W55xN8197FV+56FB0wlzplQ+yOJCIi/1JkpXBMr2i2uqvieHcszv1f2R1JRPIQFVcR8UjuIz/gXjGEn93lOdc5hlbVS9sdSUREsql9/Yr8dksMh9zhZC69HevkbrsjiUgeoeIqIp7n7AFSF/XktDuI71vMoWvT6nYnEhGRHHL7TfVZ12gWiU5vkuZ3h4RjdkcSkTxAxVVEPEtyHPExXcnIzOSdmjMYdmszuxOJiEgOG9etDUsqPQ/pCZyP7gpp8XZHEhEPp+IqIp4jI4Vz83vgl3ycuWWmMbHvbRhj7E4lIiI5zBjDnQN7MSv8EQol7Ofcgr7gTLc7loh4MBVXEfEMLifnXh9MkbjtvBJyL3cNH4SXQ6VVRCS/8vV2cMeo0bxSaDKhp7ZwbtkocLvtjiUiHkrFVUTsZ1mcX/UfQg+v51X/0YwZMxl/Hy+7U4mIyHUW7O/DkHH3Mtt7EKG/rSb+gwfsjiQiHkrFVURsl/jZc4TsWsJiR3d6jn2c0EK+dkcSEZFcUrywP+1GP8MKbqXID7NJ/uo1uyOJiAdScRURW6XGLiX466f4wGpJ4xEvUy4s0O5IIiKSy6qUCKbykFmsd0cS8NkDpO943+5IIuJhVFxFxDaZe7/A54M72eyuReHb51GnbKjdkURExCaRlcJx9YjmJ3dlzKpRuA59a3ckEfEgKq4iYgvrxE6cywayz12Kkx1jaF2zrN2RRETEZrc2rMTPbeZx1BVK2pI+WGf22h1JRDyEiquI5L74oyQt6MF5lx+bms2me/PadicSEREPMaBNYz5uMJM0p5uEmO6QdNruSCLiAVRcRSR3pcVzProrVnoiK6q+wPCOrexOJCIiHmZs93YsKP8MvqmnOBfTAzKS7Y4kIjZTcRWR3OPM4OyCvhRKPMCcEo8xsX93jNG1WkVE5M8cDsOdQ/vzatj9FD63k7OLB4HLaXcsEbGRiquI5A63m7PLRhN2aguvBt/FHSNH4e2ljyAREbk0P28vxo6ZxMyAcYQd/ZxzK+8Ey7I7lojYRN8aRSRXxH/4MGG/vcdcn0EMHnsvhfy87Y4kIiIerkiAD33GPcoiR09Cf15Kwrpn7Y4kIjZRcRWR6y7p6zkU2TqTlbSj3ehnCA/2szuSiIjkEaVDArhh1Mt8YLWi8KanSY1danckEbFBjhRXY0wHY8wvxph9xpj7LvG6nzFmRdbr3xpjKubEfkXE86Xv/ICA9ffzubsREUNnU6l4sN2RREQkj6lZughhA6LZ5K6NzweTyNz7hd2RRCSXZbu4GmO8gFlAR6AW0N8YU+svw0YC5yzLqgK8BOg4D5ECwHU4Ft4ZwU53RVw959M4ItzuSCIikke1qF6aM53ms89dGueygVgndtgdSURyUU7MuDYF9lmWtd+yrAxgOdDtL2O6AYuz7q8EbjFaSlQkX7Pi9pO6uBcnXEXY0yaGdg0q2R1JRETyuK431OTb5nM47/IjaUEPiD9qdyQRySU5UVzLAIf/8PhI1nOXHGNZlhOIB4rmwL5FxBMlnyEhpisZmU4+rj+Tfm0a251IRETyiSEdWvJ29RchPYlz0V0hLd7uSCKSC3KiuF5q5vSva5VfzZgLA40ZY4yJNcbEnj59OtvhRCSXZaRwNqYnfiknWFThGUb3aG93IhERyUeMMUzo1425JR8nKPEAZxf0BWeG3bFE5DrLieJ6BCj3h8dlgWOXG2OM8QaKAGcvtTHLsuZZlhVpWVZkeLjOhxPJU9wu4l4fQsjZ7cwMu487hgzA4dBZASIikrO8vRxMGDmSV4PvIuzUFs4uG6NrvIrkczlRXL8HqhpjIowxvsDtwOq/jFkNDM263xv43LL06SKSr1gW51bdTdHD63gtYDSjR0/Gz9vL7lQiIpJPBfp6M3jsvUT7DCTst3eJ//ARuyOJyHWU7eKadc7qROAT4GfgLcuydhljnjDGdM0aNh8oaozZB9wN/O2SOSKStyV8/hKhOxfxhqMrPcY9QZFAH7sjiYhIPhce7Mcto5/lHW6hSOwMkr6ZZ3ckEblOjCdPfEZGRlqxsbF2xxCRf5D6wwoCVo/hI6s55ccso3aZULsjiYhIAbL1wCkSF/blRsdPOPssxa/2bXZHEpGrYIzZallW5NWMzYlDhUWkAMvctxHv1XfwnbsGQbfHqLSKiEiuaxxRnMye89nprggrh1+4jriI5CsqriLyr1knd+N8sz8H3cU53nEBN9Ysa3ckEREpoNo1qMyeNjGcdAWTurgXVtx+uyOJSA5ScRWRfyfhGInzu5Po8uabG+bQrXltuxOJiEgB169NYz6qP5PMTCfxMV0h+YzdkUQkh6i4isi1S0vgXHQ3HOnxLK/2AkNvu9HuRCIiIgCM7nEriyo8g3/KCc7G9ISMFLsjiUgOUHEVkWvjzCBuYT+CEn5jbsnHmHB7T4zRtVpFRMQzOByGCUMGMCvsXkLObiduyWBwu+yOJSLZpOIqIlfPsji7bCxFT25iVvAkxo8cjbeXPkZERMSz+Hl7MWrMXcwOGE3RI+s5u/Iu8OAraYjIP9M3ThG5auc/fJSw31YR49OfgWMfINDX2+5IIiIil1QkwIce457gDUc3wnYvIeGz5+2OJCLZoOIqIlcl6Zt5hMS+wipu4ebRzxEe7Gd3JBERkSsqHRJA5OgZfGS1oPDXT5KydZndkUTkX1JxFZF/lL7rAwLW3csGd0MqDptLpeLBdkcSERG5KjVKhRAyIIZv3TXxXTORjL1f2B1JRP4FFVcRuSLn79/ByhHsdlfA2Ws+jSqG2x1JRETkmjSvXoa4zgv4zV0S17KBuI/vsDuSiFwjFVcRuSzrzD7SFvfmhKsIv9yygLb1K9sdSURE5F+5rWktvms5j3iXL0kLekD8Ebsjicg1UHEVkUtLOkV8TFcynC7WNZpF75sa2Z1IREQkWwa1b8G7NV+BjCTOzusKqefsjiQiV0nFVUT+Lj2Js9Hd8Us9zesR0xnZrZ3diURERLLNGMOYvl2ZX+ZJgpIOEje/N2Sm2R1LRK6CiquI/JnLSdyiARQ5v5s54Q8yYXB/jDF2pxIREckRXg7D+OHDeS1kCkXPxBL3xghwu+2OJSL/QMVVRP4/yyJuxQSKHv+S2UETGD16Ij5e+pgQEZH8xd/Hi2FjpzDXbzhFD33I2fem2h1JRP6BvpGKyEXnP/o/iv66gsXevek77hGC/LztjiQiInJdhAT60nncNJY7biNsezQJX7xsdyQRuQIVVxEBIHHzAkK+e4HV3ESrMS9TPNjf7kgiIiLXVZnQQOqNeI1PrRso/OWjpPzwtt2RROQyVFxFhLTdHxH4yX/52qpH2WExVC4ebHckERGRXFGrbChBAxbyvbs6PqvHk7HvS7sjicglqLiKFHDO37/DvD2M3e7ypPdYSKOKxe2OJCIikqtaVC/D6c4LOegujuvN/riP77A7koj8hYqrSAFmndlL+uLenHAVZm/bhdzSoIrdkURERGxxW9PafN8qmvMuP5IWdMc6/7vdkUTkD1RcRQqqxJPER3ch1WnxeeRserZuZHciERERWw1o35L368yAjBTOz+sCKWftjiQiWVRcRQqitATi5nXBN+0sK6o+z7Aut9idSERExCOM6dWZheWnEZh8lLjoHpCRYnckEUHFVaTgcWZwZn5fCifsY27Jxxjbvw/GGLtTiYiIeASHwzBu6BBmF72X0LM/cWbxIHA57Y4lUuCpuIoUJG43Z94YQbHTm5lTZDLjRo7F20sfAyIiIn/k5+3FyDF3MSdwDMWOfkbcW5PAsuyOJVKg6RurSAFy9r2pFDu4hhi/IQwedz8Bvl52RxIREfFIwf4+9J7wBK9796LoL29y7qP/szuSSIGm4ipSQMR/9iJh26N5y9GRjuOeJSTQ1+5IIiIiHq14sD8tx7zCahNF6HcvkPBNtN2RRAosFVeRAiA5dhlFvnqcT2lGvVGzKRMaaHckERGRPKFS8WDKD4tho9WAQuumkrr9fbsjiRRIKq4i+Vzank/x++AOvnXXpMjAhdQoHWp3JBERkTylQYVw6L2Ine4IvFaNImP/13ZHEilwslVcjTFhxph1xpi9WT8v+Y3YGOMyxmzLuq3Ozj5F5Oo5f/8eVgzmV3dZEnss4Yaqpe2OJCIikie1rhvB7x0WcdhdFOcbfXEd32l3JJECJbszrvcBn1mWVRX4LOvxpaRaltUg69Y1m/sUkavgPvUraYt7ccoVzJ5bFtK2YTW7I4mIiORpXVrU49uW0SS4fEme3xXr3EG7I4kUGNktrt2AxVn3FwPds7k9EckJCcdIjOlCmtPii6bz6HlTY7sTiYiI5AsDbr2RNXVnYmWmcn5eF0g+Y3ckkQIhu8W1hGVZxwGyfha/zDh/Y0ysMWaLMUblVuR6Sj1H3NwueKWf5+0aLzGkUxu7E4mIiOQrI3t2YknEswSkHOfMvG6QnmR3JJF87x+LqzFmvTFm5yVu3a5hP+Uty4oEBgAvG2MqX2F/Y7JKbuzp06evYRciQmYqZ+b1ICjpIAvKPcmYfr0wxtidSkREJF9xOAzjBg9iXomHCTm/m9Pz+4Izw+5YIvnaPxZXy7LaWpZV5xK394GTxphSAFk/T11mG8eyfu4HNgANr7C/eZZlRVqWFRkeHv4vfiWRAsrl5PTCAYSd3cacovcydtgIvBwqrSIiIteDj5eD0aMmMqfwnYSf+obTb4wAt9vuWCL5VnYPFV4NDM26PxT424WtjDGhxhi/rPvFgJbA7mzuV0T+yLI4s3w84cc+Z27QOEaOvRs/by+7U4mIiORrAb5eDBr/IDF+Qwg/uIYzq/4LlmV3LJF8KbvF9RmgnTFmL9Au6zHGmEhjTEzWmJpArDHmJ+AL4BnLslRcRXLQ2dUPUmzvWyzx6Uvf8Y8T5OdtdyQREZECISTQl07jn2WFVyeK7VzAuU+esTuSSL5kLA/+V6HIyEgrNjbW7hgiHu38+hcI+foJVjna0+SORZQrWsjuSCIiIgXOvpMJ/Dq7P7fxNQltn6NwqzF2RxLxeMaYrVlrIf2j7M64ioiNEjYtIOTrJ/iE5tQeFa3SKiIiYpMqJQpTevgivrQaErR+Ksk/vGV3JJF8RcVVJI9K3vYuhT79L19b9QgfspjqpUPsjiQiIlKgNagQjm//1/nBXQ3f1eNJ2/Op3ZFE8g0VV5E8KP2Xz/F9bxTb3ZWh3xs0qlTC7kgiIiICNK9RjvPd32CvuwxmxSAyDm62O5JIvqDiKpLHZP4ei3v5AH5zl+J019dpVauC3ZFERETkD9o2qsbeWxdzzBVC5pI+uE7ssjuSSJ6n4iqSh7hO7iF9cQ9Ou4L4ue1i2kfWtDuSiIiIXEK3lg35ttUCEl3eJMd0wTp7wO5IInmaiqtIHmGd/52kmC6kOB181TyGHq0b2x1JREREruD29q1Y2+A1XJnpnJ/bGRJP2h1JJM9ScRXJC5JOc25OJ8hIYnW9VxnYMcruRCIiInIVhnfvyPKqL+CbdpozcztD6nm7I4nkSSquIp4uLZ4zczsTkHqCNys/x8ieXf5fe3ceXlV1qH/8u3KSEDJBRkgIoyCKKIOMIjLKJIgoiqBVUYuKOGFbB3731lvtbXtbZ2kVFUVkLOKAIAiIIqDMKPMghClkAEIICZnOWb8/krbWggwhWSc57+d58sDebLJfHxcrvKy1d1wnEhERkbNkjGHUiGG8k/Ic0bk/kDVhMBTluY4lUuWouIr4s6I8st4YTPTxnbyV/DtG3X4bxhjXqUREROQceIIMo0beyxsJ44g9+h1Zbw2F4gLXsUSqFBVXEX9VXEDWmzcRe3QDbySM47577sMTpNIqIiJSFYUGB3HvqEd5vfZYEjJXkPnOCPAWu44lUmWouIr4I28xme+MICHrG16vPZZ7Rz1KaLD+uIqIiFRlNUM93PHAU7wR8QCJaYvJmnw3+HyuY4lUCfqbsIi/8fnImnw3iWmLeSPiAe544ClqhnpcpxIREZELICoshFtG/463a9xBQuonZM14EKx1HUvE76m4ivgTa8ma8SAJqZ/wdo07uGX074gKC3GdSkRERC6gmIhQBo35M1NChpKwfSqHZ/9G5VXkDFRcRfyFtRye/RsStk9lSshQBo35MzERoa5TiYiISAVIjAqj++hXmeUZQPzGCRyZ96zrSCJ+TcVVxE8cmfcs8RsnMMszgO6jXyUxKsx1JBEREalA9WLCufL+CXxiehC3+nmyF7/oOpKI31JxFfED2YteJG7188wx3bny/gnUiwl3HUlEREQqQeOEKJr/8h0W0omYr58hZ9mbriOJ+CUVVxHHcpa+TsyyZ1hIRy7+5bs0TohyHUlEREQqUfPkGOrcNZmltg1Ri35N7srJriOJ+B0VVxGHclZMpNYXT/ClbUudu96neXKM60giIiLiwBWNEql5+1RW2ssI/+xhTqyd4TqSiF9RcRVx5PjK94n6fCzL7RVE3zGVKxoluo4kIiIiDrVvlgzDp7HOXkzNOfeTt+Ej15FE/IaKq4gDJ9bOJOKzh1hlWxBy23TaXpTkOpKIiIj4gc6XNKDwlul877uI0I/uIX/TXNeRRPyCiqtIJcv77iNqzrmP9bYZDJ9Oh4vruY4kIiIifuTqyxpz/KZpbPPVJ3jWnZzcutB1JBHnVFxFKlH+prmEfngPG31NKLhlOp0uaeA6koiIiPihbq2akXnDdHb5kvHMGEHBzi9dRxJxSsVVpJKc3LqQ4Fl3ss1Xn5ybpnP1ZU1cRxIRERE/1qvtJewfOJVUXwJMHUbh7uWuI4k4o+IqUgkKdn6JZ8YIfvAlkXnDdLq1auY6koiIiFQBfTu0ZFf/KaR5Y/BNHkph6krXkUScUHEVqWCFu5bB1GGk+hLYP2gavdpe4jqSiIiIVCEDOrdh87Xvk+mNxDtpCMX71rqOJFLpVFxFKlDhrq+xU27igDeWXf2n0Kd9S9eRREREpAoa1LUd63q8xxFvOEXvXk/RvtWuI4lUKhVXkQpSsPOrf5bWHf2nMqBzG9eRREREpAob0qMzq9kU1QgAABwcSURBVHtM5khJTUreGUzR3lWuI4lUGhVXkQpQsPNLmHoz+73x7Ow/TaVVRERELogbe3Rmbc/3OewNp+TdwRSmqrxKYChXcTXG3GyM2WyM8Rlj2v3Mdf2MMduNMbuMMU+W554i/q60tN7CPm88PwyYRv/OrV1HEhERkWpkSPdOrOs5lSxvJN5Jg/XCJgkI5V1x3QTcCCw93QXGGA8wHugPtACGG2NalPO+In7p5I4lmCmlpXXPddPp16mV60giIiJSDd3QvQPf9ZpCpjcK76QbKEz91nUkkQpVruJqrd1qrd1+hss6ALustbuttUXAdGBwee4r4o9Obv+CoKnD2OtLYM/AGfTteIXrSCIiIlKNXd+tAxt7TyHTF4Vv0hAK93zjOpJIhamMZ1zrAft/dHyg7JxItXFy+2KCpg0j1ZdI6sDp9O1wuetIIiIiEgAGXdOejb2nkO6NwvfejRTuWeE6kkiFOGNxNcYsMsZsOsXH2a6amlOcsz9zv1HGmDXGmDVZWVlneQsRd05uW0jQtFvZ46vD/utn0EelVURERCrRoK7t2dxnGune6NLy+sNy15FELrgzFldrbW9rbctTfHx8lvc4ANT/0XEKkPYz95tgrW1nrW2XkJBwlrcQcSPv+zkET7+V3b66HLx+Br3bXeY6koiIiASggVdfyda+UznkrY19fwgnty92HUnkgqqMrcKrgWbGmMbGmFDgVuCTSrivSIU6vmYmNWbfyVZfQ9KHzKKXSquIiIg4NKDLlewYMIO93kQ804aRt3Gu60giF0x5vx3OEGPMAaAzMNcYs6DsfLIxZh6AtbYEGAMsALYCM621m8sXW8StnG8mEfHpfWywTTlx6yx6tGnuOpKIiIgI/Tq1Iu2Gv7PdV5/QD+4gd90s15FELghj7WkfN3WuXbt2ds2aNa5jiPybo1/9jdglT7LCXk7IiGm0b17/zL9JREREpBIt27Sb8L8Po5XZxYl+r1Kr0+2uI4n8B2PMWmttu7O5tjK2CotUG0cWvUjskif5irZE3DVLpVVERET80tUtm1Ay4gNW2xZEzR9D9tcTXEcSKRcVV5GzlDX398Qte4ZFdCLhnr/TqnFd15FERERETqtD8wbUuHMWy2lNzOJfc2Txy64jiZw3FVeRM7GWrI+eJmH1/zEvqBuN7p9Oi/rxrlOJiIiInFGbJknE3TOTL+hA3Nf/TdZnf3AdSeS8qLiK/Byfj8yZj5CwYTwfefpw2egpNK0b4zqViIiIyFlrUT+R+vfNZL7pSsLKP5L10dPgx++5ETkVFVeR0/EWkz7pDhK3TmJmyGA6jJlEw/go16lEREREzlmzpBgueWAqH3n6kLBhPBlTHwCf13UskbOm4ipyKkV5pL8xhLp75/Bu+J30fHgCyTHhrlOJiIiInLdGidF0fGgSU0Nvps7OaaRPHA4lha5jiZwVFVeRn8o/Ssb4fiRkLOPNWo9w08PPEx8V5jqViIiISLkl1Q6n/yN/ZWLkL6l7YAHpfxsEhbmuY4mckYqryI/Y42lkvdqb2se28Fbd3/KLMb8lKizEdSwRERGRCyYmIpRbH/4jb8T+hvjDq8l8rQ8277DrWCI/S8VVpIw3axfZr/WkZv5B3mvyF+6971HCQjyuY4mIiIhccOGhwYwc/RQTU54j+vhOjrzaA1/2PtexRE5LxVUEKDqwnrzXe2MLTzD7ite594678AQZ17FEREREKkxocBD33jOaKRe/ROjJwxwf35Pi9K2uY4mckoqrBLz8nV9R8vYAjpd4WHLVZO64aQjGqLSKiIhI9RcUZLh7xG182vYtioqLKZjQh8LUVa5jifwHFVcJaDmrpxEy5UYO+mLY2GcGQ/v2cB1JREREpFIZYxgx+DqWd5vKUW8Y9t2BnPhujutYIv9GxVUCk7Vkzf8/as29n+9sU9Jv/Ij+Xdq5TiUiIiLizJCeXdg5cDY7bT1qfngHR778q+tIIv+k4iqBx1tC+rQxJHz7ez43XQgb+QldW13sOpWIiIiIc73bX07x7XNYRhvivnyKjA9+Az6f61giKq4SYIryOPTmUOrueJ/poTfS4qGZtGxUx3UqEREREb/RtlkK9R+YzYfB/aiz8Q0OvXMbFBe4jiUBTsVVAobNzSDj1WtJPPQlE2uNpv+jE0iJjXQdS0RERMTvNKlTm66PTGJSxEiS9s8jffwAyD/qOpYEMBVXCQglGdvJfrUb0cd3MjHlOW576DlqhYe4jiUiIiLit+Kjwrjlked5M3EcMdnfcfiV7viO7HEdSwKUiqtUe/m7llHwRi98hXl8cPkb3Hvvg9QI9riOJSIiIuL3aoZ6uPv+XzP14pcJOZlF7l97ULh3jetYEoBUXKVay/7mPULeH0ymN5IVPaZz+9Ab9T1aRURERM6BJ8gw8rbbWXjV++SWeLDvDCBn7SzXsSTAqLhK9eTzkv7BE8QseIj1tjkHb/qY67t3cZ1KREREpMoa2rcXOwZ9yDbbgFpz7iFjzu/AWtexJECouEr1U5hL2hs3Unfj63wc3I+Y+z6l6xXNXacSERERqfJ6truCkLvn8llQN+qsfZ60t0dAUb7rWBIAVFylWvEe2UPmS91ITF/KxFoPcs1jk2mWHOs6loiIiEi1cVnDOlz56AzeixhJ3f2fkfFKT2zOQdexpJpTcZVqI3/HV+SPv4Ya+YeY3PR5fvHwc8REhLqOJSIiIlLtJEbX5JZHn+edBr8nIncPOa90pSB1letYUo2puEq1cGTpBEKnDiHTG8mSrtMY+Yu7CfFoeIuIiIhUlLAQD3ffPZrPOk4ityQI8+51ZH871XUsqab0N3up2rwlpE1/hLgvfs0qWnJ42Fxu6N3ddSoRERGRgGCM4eYB/UgdMoeN9iJi5j9A+uynwedzHU2qGRVXqbJsbgaHXutL8rZ3mR06iOTRc+jYoonrWCIiIiIBp2vrS6l131w+9fSm7vfjSfvbQGz+UdexpBpRcZUq6eQPK8h56Spijn7H2/FP0HvsOzRKrOU6loiIiEjAapYcR5fHpvJuzEPEZ35L9oudKdy3znUsqSZUXKVqsZasRS8TMnkgx0o8fNz+PUaOforosBDXyUREREQCXkxkDX7x0LPMuuJNCoqKMBP7cGTpW65jSTVQruJqjLnZGLPZGOMzxrT7metSjTEbjTEbjDFrynNPCWCFJzj49m0kLPtvltOG9GHzGTZwAEFBxnUyERERESnjCTKMuOkmfhgyj7VcQtwXj3Nw0j1QXOA6mlRh5V1x3QTcCCw9i2t7WGtbW2tPW3BFTqc4cweZL3al7v55vB9xJxc/+gmd9DyriIiIiN/q2vpSUsZ8xoywW6i3ZxbpL3XDezTVdSypospVXK21W6212y9UGJFTObZ2NsV/uwbPySymNHuJWx57iaTaEa5jiYiIiMgZ1I+PYvDjr/Nug/8l/MQ+8l+7mtxNn7mOJVVQZT3jaoHPjTFrjTGjKumeUtWVFJI24zFqzxnJLl8ya/t+yB2330VosB7NFhEREakqwkI83HX3g3zd4+8c9MYQMWs4h2Y/Dd5i19GkCjljAzDGLDLGbDrFx+BzuE8Xa21boD/woDHmmp+53yhjzBpjzJqsrKxzuIVUJ8UZ28l4oSvJWyfyUcgAwkZ9Tp+r2ruOJSIiIiLn6bruV1MyciHzPD1J+n48h17qqa3DctaMtbb8n8SYL4FfWWvP+OIlY8wzwAlr7V/OdG27du3smjV6l1NAsZbDyyYSufgp8m0IcxqN4+bbRhEeGuw6mYiIiIhcAMcLipn93ivcePDPBAcZCvq9QGzH4a5jiQPGmLVn+w6kCt9zaYyJMMZE/ePnQB9KX+ok8u8Kctj/1nDiF4/le5qy/rq53DlytEqriIiISDUSHRbCnb8cy/LeH7HDV4/Yz+7nwLt3Q1Ge62jix8r77XCGGGMOAJ2BucaYBWXnk40x88ouqwMsM8Z8B6wC5lpr55fnvlL95P2wgiPPdyDpwAKmRt5JvYc/p1eH1q5jiYiIiEgFMMbQv2snao9exIyaw0jeM5usv3SkYN9619HET12QrcIVRVuFA4DPy6G5/0vC2hc4ZONY3upPDB08hGCPXsAkIiIiEgiKSnz8fdZUem39f8SaXI52HkfdPo+BMa6jSQXzq63CIqdTkrWLgy/1ImntX1gSdBVZty3i1htvUmkVERERCSChwUHcduvtpN68kBWmDXW/+R8OvNoPb/Y+19HEj6ghSOXz+chY+DLe8VcRlbOdyXWeoMPjH9L24kauk4mIiIiII51aNuPysZ8yOe5RYo6sp/CVDmR9NQH8eIeoVB5tFZZKVXJ4NxmT76FezjqW0Yai/i/Ss2Mb17FERERExE9Ya1mwbCWxi8fSgc3sj72K5F9MwBNT33U0ucC0VVj8j89HxqJXKXmtE1HHtvJ+nV9z6ePzVVpFRERE5N8YY+jXtRONHlvE+3EPEXdkLQWvdCDrq7e0+hrAtOIqFa7k8B7SJ99DSs5aVtCagv4v0rNjW9exRERERMTPla6+fkvc4rG0Zwv747qUrr7WTnEdTS4ArbiKf/B5yVj0KsWvdaLWsS1MqfMrmj++QKVVRERERM5K6eprZxo+tpgpcWOIO7yGgpc7kPXVm+DzuY4nlUgrrlIhTqauJvvvD5Gct5VvuYL8/i/Rs+OVrmOJiIiISBVlreXzZd8Qt3gs7djKwahWxA97jRopV7iOJudJK67ijM3PZu97D1Dj3WsJPnGIqSm/5eJfLVJpFREREZFyMcbQt+tVNBj7BVPrPkHY8d143urG3qmPQmGu63hSwbTiKheGtWQtf4/QL/6bSG8Oc8IG0nDo72nTrKHrZCIiIiJSDa3aspPMD8cxsHgB2Z44fH3/QFz7W8AY19HkLJ3LiquKq5RbYdomsqaPIeX4er6zzUjt9CzX9elLsEcL+iIiIiJScYpKfHw692MuWfcMLUwqe2M6kzT8NUITm7qOJmdBW4WlUtiTx9g7/Vd4JlxDZM4Optd9nKSxSxncv79Kq4iIiIhUuNDgIG4cPIRajyxjetyDxB7dAH/txL5Z46DwhOt4cgFpxVXOXUkRaYvHE7XyBaJ8x5kf3JPYG/5Ih5bNXScTERERkQC2fP0m8j99kmu9X3PME0tBl99Qt9svwRPsOpqcgrYKS8WwlsOrZmIXPUNCcRqruIz0juPod21/QoO1wioiIiIi7hUUe5n/2cc0XPdH2rCdjBoNCen7LLFtrtfzr35GxVUuuNwdS8n5+ElS8jazw6bw/aVj6TP4F0TXDHUdTURERETkP2SfKGTRh2/TbtfLNDbp7ItuS+yQPxLZuKPraFJGxVUumML0baTNepLGh5eQYWuztN4orr75YZJiolxHExERERE5o/1ZOXw76wV6pE8k3hxnd51+pAz9A6EJTVxHC3gqrlJuhYe2cmDO72mYNpcCG8rntYdx2dCnaV6/rutoIiIiIiLnbPPuA+z48Dn6Hf+AYONjX/0bqH/9OBVYh1Rc5bydPPA9aZ88S+PMhRTaEBaF96fugKdpf/klrqOJiIiIiJSLtZZvNmwke/4f6F3wOR7jY2/ydaQMGkeNpEtdxws4Kq5yzk7sWUXmp8/R5MhXnLBhLI4aTHK/sbS7rDlGD7GLiIiISDVirWXFhk0cXfg8vfPmUsMUsyexN0mD/ovw+q1cxwsYKq5y1o7vWMaRec/R+Ng35NhwltS+iUbXjaX1xdoyISIiIiLVm7WWtVt2kDb/eXoe/5hIU8APcd2oc904IpvoJU4VTcVVfl5JIYe+mU7xN2/QIH8zR2wUS+OH0XzgY7RonOI6nYiIiIhIpft+5x72zH2B7tmzqGXySY1sTc2r7qNOx5vBE+I6XrWk4iqnVJy9n9T5r5Gwczq1fcfYbZP4ru7NXD5oDE1T6riOJyIiIiLi3LbUg2yb+wpXZs6mvsnkqCeOo5eMoHHfMXii9aLSC0nFVf7FWrI3L+bwkvE0PvIlQday3NOOnMvv4qprhxIbGeY6oYiIiIiI38nKyefbz2cQv2USne16iglmT2IvEnuNofbFXUHvgSk3FVehJOcQe5dOJnzj+yQV7SXbRrKi1gBqd72PTldeiSdIf9BERERERM6kxOtjxapV5C1/nS65C4g2+Ryo0ZSiVrfTqOvtBEUluI5YZam4Bih78hh7V8zEu2EmjXLX4sHHJi5iT+PhtOo3kgZ14l1HFBERERGpsn44mMmWBW/SbO8MLjF7KSGI1OiO1Gh7Kymdb8LUiHIdsUpRcQ0kJYWkrf6Y3NXTaHT0a2pQzD6byMbYvkS3v5X27TsTFuJxnVJEREREpNo4WeRl5bdfk79uOq2yF1LPHOYkNdgb351aHYeT1HagXuh0FlRcqzlfXjYH1nxK3ub51M9cQiR5HLbRrIvqQXDrW2nXpTfRNUNdxxQRERERqfZy8gpZ/fVnsHEmV574ihhzghwTzcE6PYhs2Z/6V/bH1KztOqZfUnGtbnw+ju1ZS9rqTwjbu4SGJzfjwccxG8GGmh0pbjGU1t1uIKFWhOukIiIiIiIBKyP7OBu+nE3Yttm0KVhNtMmnBA97wy+nsHFPUtpfT3TD1nqxUxkV16rOWgoP7+HA919RsG0hyYeXE2OPAbCFJuyP60JYi75c1r4n8dEqqyIiIiIi/iYzO5fNqxZTvG0BDbKXcwl7ATgSFMehhKsJv7Q3yS27ERbXIGCLbKUVV2PMn4FBQBHwAzDS2rKG9e/X9QNeBjzAW9baP57N5w+U4uo9mUPalhUc27Gc4EPrqJu7+Z9F9ZiNYFNYO/Ib9qBeu4Fc2rQpQXojsIiIiIhIleH1Wbbs2E7amk+J3LeEywvXEW3yATgSFEtGVEu8SW2Jbd6FpEs7ExQWGC95qszi2gf4wlpbYoz5E4C19omfXOMBdgDXAgeA1cBwa+2WM33+6lZcbVE+Rw5s5+i+rZxM34k5vJ3YYxtJLt5PkCn9/7CHZPaHX0ZhnTZEXtSJS1t3pnZkuOPkIiIiIiJyoRw9nse2DcvJ272SsIz1NMjfTEOTDoAXw8GQRmTXvhzimxGedDGxDS4ltl5zTEiY4+QXlpOtwsaYIcBQa+1tPznfGXjGWtu37PgpAGvtH870OatMcbWW4vxjHM/OIv9YJidzsijMPUpxziE4spuauanEFuwjwXf4nwUVIMvWYm9oM47HtSKkYUdSWnahYb16WlEVEREREQkgXp8ldf9+0jYvo3jvKmod/Y7GRTuJNbn/usYasjyJHA2rT0FUI4i7iJDoOtSIjqNmdCIRMQlExyQQXLNWldl6fC7FNfgC3vduYMYpztcD9v/o+ADQ8QLe14mVk54iae8cIn3HibInCDFe4oC4n1yXYyNI8ySzO/wKtkY3xpPQlIik5iQ0bEFSnUQSPEEu4ouIiIiIiJ/wBBkuatiAixqOAEYAUOz1se/QIbL2bSHv0A58WbsIO76HmIJ9NMvbTFTGyVN+rmLr4biJ4oQnmsymt9B++H9V4n9JxTljcTXGLALqnuKXxllrPy67ZhxQAkw51ac4xbnTLvMaY0YBowAaNGhwpnjOeGvUJiOsMQdDa+ENi8HWjCUoIobgyHhqRMVTs1Y8UbF1qVMnmUtVTkVERERE5ByEeIJokFKPBin1KH3q8l9KSrwcTD9IbnYGJ3MOU5SbhffEEbx52ZiCo3gKsgkuysFbo5ab8BWg3FuFjTF3AvcDvay1+af49eq/VVhERERERETOyblsFS7XUmDZ24KfAK4/VWktsxpoZoxpbIwJBW4FPinPfUVERERERCRwlHcP62tAFLDQGLPBGPM6gDEm2RgzD8BaWwKMARYAW4GZ1trN5byviIiIiIiIBIhyvZzJWtv0NOfTgAE/Op4HzCvPvURERERERCQw6a1BIiIiIiIi4tdUXEVERERERMSvqbiKiIiIiIiIX1NxFREREREREb+m4ioiIiIiIiJ+TcVVRERERERE/JqKq4iIiIiIiPg1FVcRERERERHxayquIiIiIiIi4tdUXEVERERERMSvGWut6wynZYzJAva6zvEz4oHDrkOIlNF4FH+i8Sj+RONR/InGo/gT1+OxobU24Wwu9Ovi6u+MMWuste1c5xABjUfxLxqP4k80HsWfaDyKP6lK41FbhUVERERERMSvqbiKiIiIiIiIX1NxLZ8JrgOI/IjGo/gTjUfxJxqP4k80HsWfVJnxqGdcRURERERExK9pxVVERERERET8morreTLG9DPGbDfG7DLGPOk6jwQWY0x9Y8wSY8xWY8xmY8wjZedjjTELjTE7y36McZ1VAoMxxmOMWW+M+bTsuLExZmXZWJxhjAl1nVECgzGmtjFmljFmW9kc2Vlzo7hijHms7Ov0JmPMNGNMmOZHqUzGmInGmExjzKYfnTvlnGhKvVLWb743xrR1l/w/qbieB2OMBxgP9AdaAMONMS3cppIAUwI8bq29FOgEPFg2Bp8EFltrmwGLy45FKsMjwNYfHf8JeLFsLGYD9zhJJYHoZWC+tfYSoBWl41Jzo1Q6Y0w94GGgnbW2JeABbkXzo1Sud4F+Pzl3ujmxP9Cs7GMU8LdKynhWVFzPTwdgl7V2t7W2CJgODHacSQKItfaQtXZd2c9zKf2LWT1Kx+GksssmATe4SSiBxBiTAlwHvFV2bICewKyySzQWpVIYY6KBa4C3Aay1RdbaY2huFHeCgZrGmGAgHDiE5kepRNbapcDRn5w+3Zw4GHjPlvoWqG2MSaqcpGem4np+6gH7f3R8oOycSKUzxjQC2gArgTrW2kNQWm6BRHfJJIC8BPwG8JUdxwHHrLUlZceaI6WyNAGygHfKtq6/ZYyJQHOjOGCtPQj8BdhHaWHNAdai+VHcO92c6NcdR8X1/JhTnNPrmaXSGWMigQ+AR621x13nkcBjjBkIZFpr1/749Cku1RwplSEYaAv8zVrbBshD24LFkbLnBgcDjYFkIILSrZg/pflR/IVff/1WcT0/B4D6PzpOAdIcZZEAZYwJobS0TrHWzi47nfGPLR1lP2a6yicBowtwvTEmldLHJnpSugJbu2xrHGiOlMpzADhgrV1ZdjyL0iKruVFc6A3ssdZmWWuLgdnAVWh+FPdONyf6dcdRcT0/q4FmZW+FC6X0QftPHGeSAFL2DOHbwFZr7Qs/+qVPgDvLfn4n8HFlZ5PAYq19ylqbYq1tROlc+IW19jZgCTC07DKNRakU1tp0YL8xpnnZqV7AFjQ3ihv7gE7GmPCyr9v/GI+aH8W1082JnwB3lL1duBOQ848txf7AWOs3q79VijFmAKWrCh5gorX2944jSQAxxlwNfA1s5F/PFT5N6XOuM4EGlH7BvNla+9MH8kUqhDGmO/Ara+1AY0wTSldgY4H1wO3W2kKX+SQwGGNaU/qisFBgNzCS0n+o19wolc4Y8z/AMEq/G8B64F5KnxnU/CiVwhgzDegOxAMZwG+BjzjFnFj2DyyvUfoW4nxgpLV2jYvcp6LiKiIiIiIiIn5NW4VFRERERETEr6m4ioiIiIiIiF9TcRURERERERG/puIqIiIiIiIifk3FVURERERERPyaiquIiIiIiIj4NRVXERERERER8WsqriIiIiIiIuLX/j+M7Po42zfargAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(analytical_solution[:, cells // 2, 1], label='analytical')\n",
+    "plt.plot(simulated_solution[:, cells // 2, 1], label='simulation')\n",
+    "plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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TXddx8iVjzAprbcz5rsvpiC7yudCgQL17W1OlZXr0wGerlOXxnx98AAAAAL5id9IpPfHlWjWpXEIPd6jtOo7fo+hCNcoU1b+6NNDSHUka+VOC6zgAAACAX8nI8uj+z1ZJVnq3T1MFB1LDLjd+hyFJ6tm8kro2qah3fozXku1HXMcBAAAA/MZ/vo/Xql3H9HKPhqpcsrDrOAUCRReSJGOMXuwWrSqliui+T1fp0PFU15EAAACAfG/exoP64Ndt6hNbWZ0bV3Qdp8Cg6OL/FAsL1qh+zXQiNUP3frpKmVke15EAAACAfGvXkVN6aOpqRUcW17OdG7iOU6BQdPFf6pYvrpe6NdSyHUl6/fstruMAAAAA+VJqRpbu/niFjKRRfZsrLDjQdaQChaKL/3Fz80rqExul0b9u1/cbDriOAwAAAOQ7z83aoA37juut3k24L9cBii6y9Wzn+oqOLK6Hp63R70dSXMcBAAAA8o1pcbv12fLdGn5lDV1Tr5zrOAUSRRfZCgsO1Ki+zRVgjO76aKVSM7JcRwIAAAB83sZ9x/WPGevVunopPXQd++W6QtHFOVUuWVhv9W6sTfuP69mZG1zHAQAAAHza8dQMDf94hcILBWtEn6YKYr9cZ/idx1+6um453XNVDX0et1tT43a7jgMAAAD4JGutHpu2VruPntZ7fZupTLFQ15EKNIouzuuh6+qoTY1S+ueM9dqwL9l1HAAAAMDnjFuwQ99tOKAnO9VVi6olXccp8Ci6OK/AAKMRfZqqROFgDf94pZJPZ7iOBAAAAPiMZTuS9Op3m9UpuryGtKvmOg5E0cUFKl00VO/d1kx7j57WQ5+vlsdjXUcCAAAAnDuQnKp7PlmpqJKF9VrPRjLGuI4EUXRxEWKqltQznevrx82H9Oa8eNdxAAAAAKdSM7I0bEqcTqVlanT/5ioWFuw6EryCXAdA/tK/VRVt2HtcI39OUP2KxXVDwwquIwEAAAB5zlqrp79arzV7kjWmf3PVLlfMdSSchRFdXBRjjJ7v1kDNokro4alrtGn/cdeRAAAAgDw3YeFOfbFyjx68tpY6NCjvOg7+hKKLixYaFKgP+jVX8UJBGjolTkdT0l1HAgAAAPLMwoTDevmbTepQv5zuv7qW6zjIBkUXl6Rs8TCN7h+jg8fTdM8nK5WZ5XEdCQAAALjsdh05pXs+WakaZYrozd5NFBDA4lO+iKKLS9akcgm93L2hFm07ope+2eQ6DgAAAHBZpaRlauiUOFkrjR0Qo6KhLHnkq/iTQY70bF5JG/Yl68OFO9WgYrh6Nq/kOhIAAACQ66y1enT6GsUfPKFJg2NVpVQR15HwFxjRRY49fUM9talRSk99tU6rdx9zHQcAAADIde/9nKBv1h3Qk53qqX2tMq7j4DwousixoMAAjbytmcoWC9WwKXE6dDzVdSQAAAAg1/yw8aDe+D5e3ZtG6o721VzHwQWg6CJXlCwSorEDYnT8dKaGTlmh1Iws15EAAACAHNty4IQe/Hy1GkaG65UeDWUMi0/lBxRd5Jp6FYrrrd5NtGbPMT0ybY08Hus6EgAAAHDJEk+kafDE5SocEqgxA5orLDjQdSRcIIouclXH6PJ6vGNdzV67X2//EO86DgAAAHBJUjOydOfkOCWlpGv8wBaqEF7IdSRcBFZdRq4bdkV1bU88qRE/JahamSLq3pSVmAEAAJB/eDxWj0xbozV7jmlU3+ZqWCncdSRcJEZ0keuMMXqxW0O1rl5Kj09fp+U7k1xHAgAAAC7Y2z/Ea/ba/Xq8Y111jC7vOg4uAUUXl0VIUIBG9WumShGFNHRynH4/kuI6EgAAAHBeX67coxE/Jah3TGUNu6K66zi4RBRdXDYlCodowqAWspIGT1yu5NMZriMBAAAA57R8Z5Ke+GKdWlcvpRe6RbPCcj5G0cVlVbV0EY3u11y7kk5p+McrlJHlcR0JAAAA+B+/H0nR0MlxqhRRSB/0a66QIKpSfsafHi67ltVL6ZUejbQw4Yiemble1rLtEAAAAHxH8qkMDZ64XFbShEEtFF442HUk5BCrLiNP9GxeSdsTT+r9X7apeumiupP7HQAAAOADMrI8Gv7JCu1KOqWPhrRU1dJFXEdCLqDoIs880qGOdh5J0cvfblLFEoV0Y6MKriMBAACgALPW6vEv1mphwhG90auxWlYv5ToScglTl5FnAgKM3ryliZpHRejvn6/Wku1HXEcCAABAAfaf7+P15cq9+vu1tdWzeSXXcZCLKLrIU2HBgRo3MEaVS57Zdij+4AnXkQAAAFAAfbTkd438OUF9Yivr/mtquo6DXEbRRZ4rUThEkwbHKiw4UAMnLNOB5FTXkQAAAFCAfL/hgJ6ZuV5X1y2rF7qyjZA/oujCiUoRhfXh7S10IjVTgz5cpuOp7LELAACAy2/lrqO6/7NValiphEbe1lRBgVQif8SfKpxpUDFco/o1U8Khkxo2eYXSMrNcRwIAAIAf2554UkMmLle54mEaPzBGhUNYm9dfUXThVPtaZfRaz0ZavP2IHp22Vh4Pe+wCAAAg9x06kaqBHy5TgDGadHusShcNdR0JlxE/woBzPZpV0oHjqXrtuy2qEB6mJ2+o5zoSAAAA/EhKWqaGTIzT4RPp+mxoK/bKLQAouvAJd/+thvYfS9Xo+dtVPjxMt7et5joSAAAA/EBGlkfDP16pjfuPa+yA5mpcuYTrSMgDFF34BGOMnuvSQAePp+r52RtVskiIujaJdB0LAAAA+ZjHY/X49LX6NT5Rr/ZoqKvrlnMdCXmEe3ThMwIDjEb0aarYqiX18NQ1+nnLIdeRAAAAkE9Za/X87I36ctVePdKhtm6NjXIdCXmIogufEhYcqLEDY1SnfDHd/dEKxe1Mch0JAAAA+dCIHxM0cdFODWlXTfdcVdN1HOQxii58TvGwYE0aHKuK4YU0eOJybdp/3HUkAAAA5COTFu3UWz/E6+ZmlfT0DfVkjHEdCXmMogufVLpoqCYPiVWR0CD1H79Mvx9JcR0JAAAA+cDM1Xv17KwNuq5+Of375oYKCKDkFkQUXfisShGFNWVIrLI8HvUbv1QHj6e6jgQAAAAf9vPmQ3p46hq1ql5S7/ZpqqBA6k5BxZ88fFrNssU08fZYJZ1M14Dxy3TsVLrrSAAAAPBBy3cm6a6PVqheheIaOyBGYcGBriPBIYoufF7jyiU0ZkCMdhxO0eCJy3UqPdN1JAAAAPiQjfuOa/DE5YqMKKSJt7dQsbBg15HgGEUX+ULbmqU1ok9Trd59TMOmrFB6psd1JAAAAPiAnYdTNGDCMhUNDdKUIS1Vqmio60jwATkqusaYksaYecaYrd6PEee4bqD3mq3GmIFnnW9ujFlnjEkwxowwf1oOzRjziDHGGmNK5yQn/EPH6PJ6tUcjLdh6WPd/ukqZWZRdAACAgmzP0VPqO26pPNZqypCWiixRyHUk+Iicjug+IelHa20tST96j/+LMaakpGcltZQUK+nZswrxKElDJdXyPjqe9brKkq6TtCuHGeFHbmlRWc92rq/vNhzQQ1PXKMtjXUcCAACAAweSU9V33FKdSM3Q5MGxqlm2qOtI8CE5LbpdJU3yPp8kqVs211wvaZ61Nslae1TSPEkdjTEVJBW31i621lpJk//0+rckPSaJJoP/cnvbanq8Y13NWrNPT3yxVh7KLgAAQIFy+GSa+o5boiMn0zVpcKyiI8NdR4KPCcrh68tZa/dLkrV2vzGmbDbXRErafdbxHu+5SO/zP5+XMaaLpL3W2jVs7ozs3H1lDaVmZOmdH7cqLDhQz3dtwEbgAAAABcCxU+nqN26p9h47rcmDW6ppVLZ3T6KAO2/RNcb8IKl8Np96+gK/Rnbtw57rvDGmsPe9O1zQmxszVGemPysqKuoCI8EfPHhtLaVmZGn0/O0KCw7QUzfUo+wCAAD4seOpGeo/fpm2H07RhIEtFFutpOtI8FHnLbrW2mvP9TljzEFjTAXvaG4FSYeyuWyPpCvPOq4k6Rfv+Up/Or9PUg1J1ST9MZpbSdJKY0ystfZANvnGSBojSTExMcxhLUCMMXqiU12lZXo0dsEOhQUH6uEOdVzHAgAAwGWQkpap2z9crs0Hjmt0/+ZqV4v1anFuOb1Hd5akP1ZRHihpZjbXzJXUwRgT4V2EqoOkud4pzyeMMa28qy0PkDTTWrvOWlvWWlvVWltVZwpxs+xKLmCM0TM31detLSrr3Z8S9N7PCa4jAQAAIJedTs/SkEnLtXr3MY24tamurlvOdST4uJzeo/uqpKnGmCE6szpyL0kyxsRIustae4e1NskY84Kk5d7XPG+tTfI+v1vSREmFJH3rfQAXJSDA6KXuDZWW6dHrc7coNChAd7Sv7joWAAAAckFaZpaGTonT0h1Jert3E3VqWMF1JOQDOSq61tojkq7J5nycpDvOOp4gacI5ros+z9eompOMKBgCA4xe79lIaZlZenHOJoUEBWhA66quYwEAACAH0jM9uufjVVqw9bBeu7mRujaJdB0J+UROR3QBnxEUGKC3ezdVeuZKPTNzg4yk/pRdAACAfCk906PhH6/UD5sO6vmuDXRLi8quIyEfyek9uoBPCQkK0Pt9m+naemX1z5kbNGXxTteRAAAAcJH+XHKZqYeLRdGF3zlTdptTdgEAAPIhSi5yA0UXfomyCwAAkP9QcpFbKLrwW5RdAACA/IOSi9xE0YVfo+wCAAD4PkouchtFF36PsgsAAOC7KLm4HCi6KBD+XHYnL97pOhIAAECBl5aZRcnFZUHRRYHx/8tuOT0zc4PGLdjuOhIAAECBlZqRpWFTVlBycVlQdFGg/LHP7g0Ny+vFOZv03s8JriMBAAAUOKfSMzV44nL9Gp+oV3s0pOQi1wW5DgDktZCgAI24talCg9bq9blblJaRpb9fV1vGGNfRAAAA/N6J1AwNnrhcK34/qjdvaazuTSu5jgQ/RNFFgRQUGKA3ejVWSGCARvyUoNRMj57sVJeyCwAAcBkln8rQgA+XacPeZL3bp5lubFTBdST4KYouCqzAAKNXejRUSFCAxszfrrSMLD3buYECAii7AAAAuS0pJV39xy/V1oMn9X7fZurQoLzrSPBjFF0UaAEBRs93baCw4ACNXbBDaZkevdS9oQIpuwAAALkm8USa+o1bqp1HUjRmQHNdWaes60jwcxRdFHjGGD11Qz2FBQfq3Z8SlJbp0es9GykokLXaAAAAcupAcqpuG7dE+4+l6sNBLdSmZmnXkVAAUHQBnSm7D3eoo9CgAL3xfbzSMrP0du+mCgmi7AIAAFyq3Umn1HfcUiWlpGvKkFjFVC3pOhIKCIoucJZ7r66lsOBAvThnk1LS4vRBv+YqFBLoOhYAAEC+k3DohPqNW6bTGVn66I6WalK5hOtIKEAYrgL+5I721fVqj4aavzVRAyYs1fHUDNeRAAAA8pW1e46p1weLlWWtpg5rTclFnqPoAtm4NTZK7/ZpqtW7j6nPmCU6cjLNdSQAAIB8Ycn2I7pt7FIVCQ3S9Ltaq075Yq4joQCi6ALncFOjihozIEbbEk+q1+jF2nfstOtIAAAAPu2nzQc1cMIylQ8P0/S72qhKqSKuI6GAougCf+GqOmU1eXBLJR5PU68PFmvH4RTXkQAAAHzSrDX7NHTyCtUuV0xTh7VW+fAw15FQgFF0gfOIrVZSnw5tpdMZWer1wWJt2n/cdSQAAACf8vHS3/XAZ6vUvEqEPrmzpUoWCXEdCQUcRRe4ANGR4Zo6rLWCA416j16sFb8fdR0JAADAJ3zw6zY9/dV6XVWnrCYNjlWxsGDXkQCKLnChapYtqml3tVbJIiHqN26pftlyyHUkAAAAZ6y1euXbTXr1283q0riiRvdvrrBgtmWEb6DoAhehUkRhTburjaqVLqI7JsVpxqq9riMBAADkucwsjx6dvlajf92ufq2i9FbvJgoOpFrAd/BfI3CRyhQL1WfDWimmaoQe/Hy1xv+2w3UkAACAPHM6PUvDpqzQ9BV79OC1tfRC12gFBhjXsYD/QtEFLkHxsGBNvD1WHRuU1wuzN+rf322WtdZ1LAAAgMsq+VSG+o9fqp+2HNKL3aL14LW1ZQwlF76HogtcorDgQL3Xt5luaxmlUb+OVf52AAAgAElEQVRs0+NfrFVmlsd1LAAAgMviQHKqeo1epLV7kvXebc3Ur1UV15GAcwpyHQDIzwIDjF7qFq3SRUM14setSkrJ0MjbmrIQAwAA8CsJh05q4IRlSj6doYm3t1CbmqVdRwL+EiO6QA4ZY/TQdbX1fNcG+nHzQfUfv1TJpzJcxwIAAMgVq3cfU68PFiktM0ufDW1FyUW+QNEFcsmA1lX1bp+mWr37mG4ZvVgHklNdRwIAAMiRX+MTddvYJSoaFqTpd7VRdGS460jABaHoArnopkYV9eGgWO05eko93l+o+IMnXEcCAAC4JNPidmvIxOWqUqqIvrirjaqWLuI6EnDBKLpALmtXq7Sm3tVaGR6rnqMWacn2I64jAQAAXDBrrd79casenb5WraqX0tRhrVS2eJjrWMBFoegCl0GDiuH6angblSkWqgHjl2n22n2uIwEAAJxXZpZHT321Xv+ZF68eTSM1YVALFQsLdh0LuGgUXeAyqRRRWF/c3UaNK4fr3k9WadyC7a4jAQAAnNOp9EwNm7JCny7bpeFX1tB/bmmskCDqAvIn/ssFLqMShUM0ZUhLdYourxfnbNLzX2+Ux2NdxwIAAPgvh0+mqc/Ypfp5yyG90C1aj3WsK2OM61jAJaPoApdZWHCgRt7WTIPaVNWEhTt036erlJqR5ToWAACAJGnn4RTdPGqRthw4rg/6NVf/VlVcRwJyLMh1AKAgCAwwerZzfUWWKKSXvtmkxBNpGjsgRuGFuecFAAC4s3r3MQ2ZuFwea/XJna3ULCrCdSQgVzCiC+QRY4zuvKK6Rnj32u0xaqF2J51yHQsAABRQczcc0K1jFqtwaKC+uLsNJRd+haIL5LEujStq8pBYHT6Zru7vL9SqXUddRwIAAAWItVbjf9uhuz5aobrli+ur4W1VvUxR17GAXEXRBRxoVb2UvhzeRoVDgnTrmCX6bv1+15EAAEABkOWxem7WBr0we6Our19en97ZSqWLhrqOBeQ6ii7gSI0yRfXV8DaqX7G47v54pcYt2C5rWZEZAABcHilpmRo6OU6TFv+uO9tX0/t9m6lQSKDrWMBlQdEFHCpVNFSf3tlKHRuc2X7omZkblJnlcR0LAAD4mUPHU9V7zOIz2wd1baCnb6yvgAC2D4L/ougCjoUFB+q925pp2BXVNWXJ7xo6ZYVS0jJdxwIAAH5i84Hj6vbeQm1PTNHYATHq37qq60jAZUfRBXxAQIDRkzfU04vdovXLlkO6ZfRiHTye6joWAADI5xZsTVSvUYuV6bGaOqy1rqlXznUkIE9QdAEf0q9VFY0f1EI7D6eo23sLtWFfsutIAAAgn/pk6S4N+nC5IiMKacY9bRUdGe46EpBnKLqAj7mqTllNu6uNJKnXB4s1b+NBx4kAAEB+kuWxemH2Rj311Tq1q1la0+5qrYolCrmOBeQpii7gg+pXLK6Z97RVrbJFNXRKnMbM38aKzAAA4LxOeldWHv/bDg1qU1XjB8aoWFiw61hAnqPoAj6qbPEwfTa0tTpFl9fL32zWk1+uUwYrMgMAgHPYd+y0en2wWL/EJ+r5rg30XJcGCgrkn/somIJcBwBwboVCAjWyTzO9WTpeI39O0K6kUxrVt7nCC/OTWQAA8P+t3n1Md06OU2p6liYMaqG/1S7jOhLgFD/iAXxcQIDRI9fX0X96NdbynUnq/v5C7Tic4joWAADwEXPW7lfv0YsVGhSgL4a3oeQCougC+cbNzSvp4zta6eipdHV/f6GWbD/iOhIAAHDIWquRP23VPZ+sVHRkuGbe01a1yxVzHQvwCTkqusaYksaYecaYrd6PEee4bqD3mq3GmIFnnW9ujFlnjEkwxowwxpizPnefMWaLMWaDMea1nOQE/EVstZKacU9blSoSon7jlurTZbtcRwIAAA6kZmTpwc9X643v49WtSUV9fEdLlSoa6joW4DNyOqL7hKQfrbW1JP3oPf4vxpiSkp6V1FJSrKRnzyrEoyQNlVTL++jofc1VkrpKamStbSDpjRzmBPxGlVJF9OXwtmpTs7Se/HKdnpu1QZksUgUAQIFx6Hiqeo9Zopmr9+nR6+vord5NFBYc6DoW4FNyWnS7SprkfT5JUrdsrrle0jxrbZK19qikeZI6GmMqSCpurV1sz+ybMvms198t6VVrbZokWWsP5TAn4FfCCwVrwsAYDWlXTRMX7dTtE5cr+VSG61gAAOAyW7cnWV1GLtTWgyc0un9z3XNVTZ01KRKAV06Lbjlr7X5J8n4sm801kZJ2n3W8x3su0vv8z+clqbak9saYpcaYX40xLXKYE/A7QYEB+udN9fXvmxtqyfYj6v7+Qm1PPOk6FgAAuEy+XrNPvUYvUmCA0fS72uj6BuVdRwJ81nmLrjHmB2PM+mweXS/wa2T3Iyb7F+elM9seRUhqJelRSVPNOX5UZYwZaoyJM8bEJSYmXmAkwH/0bhGlj+9opWOnM9TtvYWaH8/fAwAA/InHY/Xm91t036er1DAyXDPvbav6FYu7jgX4tPMWXWvttdba6GweMyUd9E5BlvdjdlOM90iqfNZxJUn7vOcrZXP+j9d8ac9YJskjqfQ58o2x1sZYa2PKlGEpdRRMsdVKauY9bVWxRCEN+nCZPly4Q2fuCAAAAPnZqfRMDf94pUb8lKBezSvpoztaqjSLTgHnldOpy7Mk/bGK8kBJM7O5Zq6kDsaYCO8iVB0kzfVOdT5hjGnlHa0dcNbrZ0i6WpKMMbUlhUg6nMOsgF+rXLKwpt/dRlfXLad/fb1RT321TumZLFIFAEB+tffYafUctVjfbzygf9xYT6/1bKTQIBadAi5ETovuq5KuM8ZslXSd91jGmBhjzDhJstYmSXpB0nLv43nvOenMolPjJCVI2ibpW+/5CZKqG2PWS/pM0kDL8BRwXkVDgzSmf3MNv7KGPl22W7eNXaLEE2muYwEAgIu0dPsRdXn3N+1OOqXxg1rojvbVWXQKuAjGn/pjTEyMjYuLcx0D8Amz1uzTY9PXKKJwiEb3b65GlUq4jgQAAC7AR0t+13OzNiiqVGGNHRCjGmWKuo4E+AxjzAprbcz5rsvpiC4AH9WlcUVNv6uNAoxRrw8Wa8aqva4jAQCAv5Ce6dGTX67TP2asV/tapTXjnraUXOASUXQBPxbtXZmxceUSevDz1Xr5m03K8vjPLA4AAPxF4ok03TZ2iT5dtkvDr6yhcQNbqHhYsOtYQL5F0QX8XOmiofr4jpbq36qKxszfrtsnLlfyqQzXsQAAgNfaPcfUZeRvWr8vWe/2aarHOtZVYAD34wI5QdEFCoDgwAC90C1ar/RoqMXbDqvre79p68ETrmMBAFDgzVi1V70+WKwAYzT9rjbq3Lii60iAX6DoAgVIn9gofXpnK51My1T39xdp7oYDriMBAFAgZWZ59NKcjXrw89VqXLmEZt3bVtGR4a5jAX6DogsUMDFVS2rWve1UvUwRDZuyQm9+v0Ue7tsFACDPJKWka8CEZRq7YIf6t6qij+9oqVJFQ13HAvwKRRcogCqWKKSpw1qrV/NKGvFTgoZMWq7k09y3CwDA5bZ+b7I6v/ub4n4/qtd7NtIL3aIVHMg/yYHcxt8qoIAKCw7Ua97/wS7YelhdR/6meO7bBQDgsvly5R7dPGqRPNZq+l2t1SumsutIgN+i6AIFmDFG/VtV0adDWyklPUvd3luob9btdx0LAAC/kpHl0XOzNuihqWvUpHIJfX1fOzWqVMJ1LMCvUXQBqEXVkpp9XzvVLV9Mwz9eqX9/t5n9dgEAyAWJJ9LUd9xSTVy0U4PbVtNHd7RUae7HBS47ii4ASVK54mH6dGgr3dYySqN+2aZBHy7T0ZR017EAAMi3Vu8+sz/u2j3H9HbvJnqmc33uxwXyCH/TAPyf0KBAvdy9oV7t0VBLtyep88jftH5vsutYAADkK9ZafbJ0l245a3/cbk0jXccCChSKLoD/cWtslKbe1Voej1WPUYs0NW6360gAAOQLqRlZemz6Wj311Tq1qlFKs+9rx/64gAMUXQDZ+mOxjBZVI/TY9LV68su1Ss3Ich0LAACftTvplG4etUjTVuzR/VfX1IeDWiiiSIjrWECBFOQ6AADfVapoqCYPbqn/fL9F7/+yTRv2Hdf7fZupUkRh19EAAPApP285pAc/Wy2PtRo/MEbX1CvnOhJQoDGiC+AvBQYYPdaxrsb0b64diSnq/O5vWrA10XUsAAB8gsdj9fYP8Ro8cbkqliik2fe1o+QCPoCiC+CCdGhQXjPvbasyxUI1YMIyvfdzgjxsQQQAKMCOnUrXkEnL9fYPW9W9SaS+vLuNqpQq4joWAFF0AVyE6mWKasY9bdW5UUW9PneLhk6JU/KpDNexAADIc+v3JqvzyN/0W8JhvdAtWv+5pbEKhQS6jgXAi6IL4KIUDgnSO7c20XOd6+vX+ETdNHIBWxABAAqMP7YO6jFqkTKzrD4f1lr9W1WRMcZ1NABnoegCuGjGGA1qW02fD2utrKwzWxB9snSXrGUqMwDAf51Kz9TDU9foqa/WqWW1kppzf3s1i4pwHQtANii6AC5Zs6gIzb6/vVpWK6mnvlqnh6eu0an0TNexAADIddsST6r7e4v01eq9+vu1tTXx9liVZOsgwGdRdAHkSMkiIZp4e6z+fm1tfbV6r7q/t0jbEk+6jgUAQK6ZvXafurz7mxJPpmny4Fg9cG0tBQYwVRnwZRRdADkWGGD0wLW1NHlwrBJPpqnLu79p9tp9rmMBAJAj6ZkePTdrg+79ZJXqlC+mOfe3U/taZVzHAnABKLoAck37WmU05/52qlO+mO79ZJWem7VB6Zke17EAALhoe4+dVu8xizVx0U4NaXdmXYoK4YVcxwJwgYJcBwDgXyqEF9Lnw1rrlW82a8LCHVq166hG3tZMlUsWdh0NAIAL8tPmg3po6hplZlm937eZbmhYwXUkABeJEV0AuS44MEDPdK6vD/o11/bDKbpxxALN3XDAdSwAAP5SRpZHr3y7SYMnxqlieCHNvq8dJRfIpyi6AC6bjtHl9c397VW1dBENm7JCL8zeyFRmAIBP2nfstG4ds0Sjf92ufq2i9OXwNqpauojrWAAuEVOXAVxWlUsW1rS7zkxlHv/bDq34/ahG3tZUlSKYygwA8A0/bz6kh6auVnqmRyP6NFWXxhVdRwKQQ4zoArjsQoMC9VyXBhrVt5m2HTqpG95ZoHkbD7qOBQAo4DKzPHr12826feJylQ8vpNn3t6fkAn6Cogsgz3RqWEGz72+nqFKFdefkOL3IVGYAgCP7k0+rz9gl+uDXbeoTG6WvhrdRNaYqA36DqcsA8lSVUkX0xd1t9NKcTRr32w4t//2o3r21qaJKMZUZAJA3ftx0UI9MW6O0TI/eubWJujaJdB0JQC5jRBdAngsNCtTzXaM1qm8zbU88qRtHLNCctftdxwIA+Lm0zCw9//VGDZkUpwreVZUpuYB/YkQXgDOdGlZQdGS47v9sle75ZKV+S4jSs53rKyw40HU0AICf2Xk4Rfd9ukrr9iZrUJuqevKGugoN4v83gL+i6AJwqnLJwpo6rLX+8328Pvh1m1Z6V2WuVa6Y62gAAD8xc/VePf3VegUGGI3u31zXNyjvOhKAy4ypywCcCw4M0BOd6mrS4FgdPpmmziN/0+fLd8la6zoaACAfO5Weqcemr9EDn61WnfLF9M0D7Sm5QAFB0QXgM/5Wu4y+faC9mkVF6PEv1umBz1brRGqG61gAgHxo84Hj6jJyoaat2KN7rqqhz4a2UmSJQq5jAcgjFF0APqVs8TBNGdJSD19XW7PX7tMNIxZo5a6jrmMBAPIJa60mL96pLiMX6tipdE0eHKtHr6+r4ED+2QsUJPyNB+BzAgOM7rumlqYOay2PR+r1wWK993OCsjxMZQYAnFtSSrrunLxCz8zcoNbVS+nbB65Q+1plXMcC4ABFF4DPiqlaUt880F4do8vr9blb1G/cUh1ITnUdCwDggxYlHFand+Zrfnyi/nlTfX04qIXKFAt1HQuAIxRdAD4tvFCwRvZpqtdubqTVu4+p4zvz9f2GA65jAQB8REaWR//+brP6jl+qIqFB+nJ4Gw1pV00BAcZ1NAAOUXQB+DxjjG5pUVmz72+nShGFNHTKCv1jxjqlZmS5jgYAcOj3Iynq+cFijfplm3rHVNbs+9opOjLcdSwAPoB9dAHkGzXKFNUXd7fRG3O3aOyCHVq2I0kj+jRV3fLFXUcDAOQha62+WrVXz8zcoAAjvd+3mW5oWMF1LAA+hBFdAPlKaFCgnr6xviYNjlVSSoa6vLtQ4xZsl4eFqgCgQEg+laH7Pl2lh6auUb0KxfTtg1dQcgH8D4ougHzpb7XL6LsH2+uK2qX14pxNGvjhMh08zkJVAODPFm87ok7vzNd36w/o0evr6LOhrdkbF0C2KLoA8q3SRUM1dkCMXuoereU7k3T92/P13fr9rmMBAHJZeqZHr3y7SbeNW6LQ4EB9cXcb3XNVTQWy4BSAc6DoAsjXjDHq27KK5tzfXpUjCuuuj1bqselrlJKW6ToaACAXJBw6oe7vL9ToX7fr1hZRmnN/OzWuXMJ1LAA+jsWoAPiFPxaqevuHeI36dZuW7kjS272bqGlUhOtoAIBLYK3VR0t+14tzNqlwSKDG9G+uDg3Ku44FIJ9gRBeA3wgJCtBjHevq86GtlZll1fODxXprXrwysjyuowEALsKhE6kaPHG5/jlzg1pVL6W5D15ByQVwUSi6APxObLWS+vbB9urcqILe+XGreo5apIRDJ13HAgBcgG/W7df1b83Xom1H9Fzn+pp4ewuVLR7mOhaAfIaiC8AvFQ8L1tu3NtV7tzXT70mndOOIBZq4cAfbEAGAj0o+naG/f75awz9eqUoRhTXn/nYa1LaajGHBKQAXj3t0Afi1GxtVUIuqEXrsi7V67uuN+mHTIb3eq5EqhLMdBQD4ioUJh/XotDU6eCJND1xTS/deXVPBgYzHALh0OfoOYowpaYyZZ4zZ6v2Y7aovxpiB3mu2GmMGnnW+uTFmnTEmwRgzwnh/ZGeMaWKMWWKMWW2MiTPGxOYkJ4CCrWzxMH04qIVe6h6tFb8fVYe35mvGqr2yltFdAHApNSNL//p6g/qOW6ow77ZBf7+uNiUXQI7l9LvIE5J+tNbWkvSj9/i/GGNKSnpWUktJsZKePasQj5I0VFIt76Oj9/xrkv5lrW0i6RnvMQBcsj+2Ifr2gfaqXa6YHvx8te79ZJWOpqS7jgYABdLaPcd044gF+nDhTg1qU1Vz7m+vJmwbBCCX5LTodpU0yft8kqRu2VxzvaR51toka+1RSfMkdTTGVJBU3Fq72J4ZVpl81uutpOLe5+GS9uUwJwBIkqqWLqKpw1rr0evr6PuNB9Th7fn6YeNB17EAoMBIz/TozXnx6vH+IqWkZWnKkFg916WBCoUEuo4GwI/k9B7dctba/ZJkrd1vjCmbzTWRknafdbzHey7S+/zP5yXpQUlzjTFv6EwZb5PDnADwfwIDjO65qqaurFNGD09dozsmx+nmZpX0TOf6Ci8U7DoeAPitjfuO6+Fpa7Rp/3H1aBqpZzs3UHhhvu8CyH3nLbrGmB8kZbdx2dMX+DWyWyrP/sV5Sbpb0t+ttV8YY26RNF7StefIN1Rnpj8rKirqAiMBgNSgYrhm3dtOI3/aqvd+2abfEhL16s2NdFWd7H5mBwC4VBlZHo36ZZtG/LhVJQqHaEz/5uyLC+CyMjlZjMUYs0XSld7R3AqSfrHW1vnTNX281wzzHo+W9Iv38bO1tu6frzPGJEsqYa213gWqkq21xXUeMTExNi4u7pJ/PQAKrnV7kvXwtNWKP3hSvWMq6+mb6ql4GKMMAJBTWw6c0CPT1mjd3mR1aVxR/+rSQBFFQlzHApBPGWNWWGtjznddTu/RnSXpj1WUB0qamc01cyV1MMZEeBeh6iBprnfK8wljTCtvmR1w1uv3Sfqb9/nVkrbmMCcA/KWGlcL19X3tdPeVNTRtxW51fGu+FmxNdB0LAPKtzCyP3v8lQZ3f/U17j53WqL7NNKJPU0ougDyR0xHdUpKmSoqStEtSL2ttkjEmRtJd1to7vNcNlvSU92UvWWs/9J6PkTRRUiFJ30q6zzuK207SOzoztTpV0nBr7Yrz5WFEF0BuWLXrqB6ZtkbbElN0W8soPdmprooxugsAFyzh0Ak9PG2t1uw+pk7R5fVCt2iVLhrqOhYAP3ChI7o5Krq+hqILILekZmTpP99v0fjfdqh88TC93KOhruTeXQD4SxlZHo3+dZtG/JigwqGBer5rtDo3qqAzk/cAIOcougCQC1buOqrHpq9VwqGTurlZJf3zpnoqUZhpdwDwZ+v3Juux6Wu1cf9x3diogv7VpQGjuABy3YUW3ZxuLwQAfq1ZVITm3N9OI39K0Pu/bNOv8Yl6sVu0OkazWigASFJaZpbe/TFBo37dpojCIfqgX3O+RwJwjhFdALhA/zVa0bCCnuvSQGWKMVoBoOBi1guAvMaILgDksujIcM28t63GzN+ud37YqoXbDuvZzvXVrUkk958BKFBOp2fpje+3aMLCHapQPEwTb2/BOgYAfAojugBwCRIOndCj09dq1a5jurJOGb3QNVqVSxZ2HQsALrv58Yl6esY67U46rX6tovR4R1amB5B3WIwKAC6zLI/V5MU79frcLbJWerhDbQ1qU1VBgTndohwAfM+Rk2l6cc4mfbVqr6qXLqKXezRUq+qlXMcCUMBQdAEgj+w9dlrPzFivHzcfUsPIcL3So6GiI8NdxwKAXGGt1Rcr9+rFORuVkpapu/9WQ8Ovqqmw4EDX0QAUQBRdAMhD1lp9s+6Anp21QUdPpWtIu2p68NpaKhzCUggA8q+dh1P09Ix1WphwRM2rROiVHg1Vu1wx17EAFGAsRgUAecgYoxsbVVC7mqX16nebNGb+dn27fr9e7NZQf6tdxnU8ALgoGVkejV1wZuG9kMAAvdAtWn1joxQQwMJ7APIHRnQB4DJYuv2InvxqnbYnpqhz44r65431VLZ4mOtYAHBecTuT9I8Z67X5wAld36Cc/tUlWuXD+f4FwDcwdRkAHEvLzNL7P2/TqF+2KTQoQA93qK3+rasqkBERAD4oKSVd//52sz6P260K4WF6tnMDdYwu7zoWAPwXii4A+Igdh1P0zMz1WrD1sKIji+ulbg3VuHIJ17EAQJLk8VhNW7Fbr367WSdSMzWkXTXdf00tFQnlDjcAvoeiCwA+xFqrOev26/mvNyrxZJr6tozSox3qKrwwe08CcGfT/uP6x4z1WvH7UbWoGqEXuzVUnfIsNgXAd7EYFQD4EGOMbmpUUX+rXUZvzovXpEU79d36A3rqhnrq3jRSxjCdGUDeOZmWqbfnxevDRTtVPCxIr/VspJ7NKrHYFAC/wYguADiwfm+y/jFjvVbvPqbYaiX1ry4NVK9CcdexAPg5a62+XrtfL8/ZpAPHU9UntrIeu76uIoqEuI4GABeEqcsA4OM8HqvPlu/W63M3K/l0hvq3qqKHrqvDdGYAl8Wm/cf13KwNWrojSQ0qFtfzXaPVvEqE61gAcFEougD+X3t3Hh11ee9x/P1k38hO9hUIhC0CAu5sUhZL1WoVtVWPt6221m6nvZX29p7rPbf2WGvb660ebxVr1bYuR3sK1lZcWC2LgAUEQ0gICZkkZN/INsnMc/+YkUspGCowM5n5vM7JSX6/PEm+6HOeySfP8pNRorPPyc/ePMTvdtSSHBfFvy6dxM2z83U6s4icF119Q/z8rQqe315LUmwk3106iVvmFGiMEZFRSUFXRGSU+bDBM9vyXk0703OTeODaqZptEZFPzOW2vLyrjp+uq6Czz8nnLynkO0smkhynZcoiMnop6IqIjELWWtbubeDHfy6nqXuQG2blsmp5KRljYvxdmoiMIrtrO3hg7QE+qO9iblEqD1w7lSk5OgdAREY/nbosIjIKGWO4bkYuiydn8sv1VTz9bjXr9h/j3oUT+OKVxcREhvu7RBEJYPWd/Tz8xkHW7GkgMzGaR2+ZwbUX5ehkdxEJOZrRFREJYEdae3nw9XLeLm8iNzmWVctLWVGWrV9aReTv9A4O87+bDvPk5mos8OWrirl3wQTiozWnISLBRUuXRUSCyNaqVv7r9XLKG7u5uDCFf18xhRn5yf4uS0T8zO22vPK+g0fWVdDcM8hnLsrh/mWTyEuJ83dpIiIXhIKuiEiQcbktr+yu46frDtF6fJDrZ+TwvWWl5CTH+rs0EfGDbYfb+NHrH3KgoZuZBcn88NNTdICdiAQ9BV0RkSB1fHCYJzZW8dSWIxjg7nnjuGf+eBK0RFEkJFS3HOcnbxxk3YEmcpJiuH95qfbhikjIUNAVEQlyjo4+Hn6jgrV7G0iLj+LriyZw2yWFREWE+bs0EbkAmrsHePSdSl7cWUd0RBj3LhjPl64ap0PqRCSkKOiKiISIvXWdPPSXg2yrbqMgNY7vLJnIZ8pyCAvT7I5IMOgZGOLJzdWs3nKEIZeb2y4p4OuLShg7JtrfpYmI+JyCrohICLHWsrmylYf+cpDyxm6m5SayatlkrixJ93dpIvIJDQ67+P2Oo/xyfRXtvU5WlGXz3SWTKEqP93dpIiJ+o6ArIhKC3G7Lmr31PLLuEPWd/VxVks79y0qZlpvk79JE5Cy53ZbX9jXwyJsV1LX3c/n4NFYtL6UsTyeti4go6IqIhLDBYRfPb6vlsQ1VdPYNcc30LL69eCIlmWP8XZqInIG1lrc+bOLnbx3i4LEepmQnsmp5KVeVpOugKRERLwVdERGhe2CI1ZurefrdI/QNubjuohy+uXgixVr6KBIwrLVsPNTCL946xD5HF8Xp8XxrcYn22ouInIaCroiInNDe6+RXmw/z3NZanC43N8zM5RtXl5CfGufv0kRC2taqVh55s4L3jwh0/+0AABDrSURBVHaSlxLLN64u4YaZuUSE6/R0EZHTUdAVEZF/0NIzyBMbD/PbHbW43ZaVc/K5b9EEspNi/V2aSEjZWdPOz96sYHt1O9lJMdy3aAI3XZyvx4OJiIxAQVdERM7oWNcAj2+o4sWdRzEYVs7J557548hL0QyvyIW0o7qNxzZUsaWylfSEaL62cDy3zi3Qs3BFRM6Sgq6IiIzI0dHH4xuqeGW3A2vhhlm5fHXBBO3hFTmPPnr81+Prq3ivpp30hGjunlfM7ZcWERulgCsi8s9Q0BURkbPW0NnPk5ureeG9owy53Kwoy+FrCycwKUunNIt8Um635e3yJh7bUMU+RxfZSTF8Zf54Vs7J1wyuiMgnpKArIiL/tJaeQVa/W81vt9XS63SxdGom9y0sYXqensMrcrZcbsvrHzTy+PoqKpp6KEyL46vzx3PDrDztwRUROUcKuiIi8ol19Dp5ZmsNv/nrEboHhrmqJJ27543jygl6nqfImfQ7Xbz6voPVW6qpaetjQkYC9y2cwIqybJ2iLCJynijoiojIOesZGOL57bU889caWnoGKc0aw93zxrGiLEczUyJerccHeX5bLc9vr6W918lFeUncM388y6Zm6Tm4IiLnmYKuiIicN4PDLtbsaeCpzdVUNh8nKzGGu64o4tZLCkiMifR3eSJ+cbjlOE+/e4RXdzsYHHazeHIGX75qHHOLU7XyQUTkAlHQFRGR885ay8ZDLTy1uZqth9tIiI5g5Zx87rqiSI8mkpBgrWVnTQdPbanm7fImIsPDuHFWHl+8spgJGQn+Lk9EJOgp6IqIyAW1v76L1VuqeW1fI9ZaPjUlkzsuK+Ly8WmazZKg0+90sXZvPc9ureXDxm5S4iK5/bIi7riskPSEaH+XJyISMhR0RUTEJ+o7+/nd9lpe3FlHe6+TCRkJ3HFZITfMyiMhOsLf5Ymck6NtfTy/vYaXdzno6h+iNGsMt19WyA0z8/QMXBERP1DQFRERnxoYcvH6vkae3VbDPkcXCdER3Dgrl9svK9KSThlV3G7L5soWnttWy4aKZsKMYdm0LO64tFD7b0VE/ExBV0RE/GZPXSfPba3hT/sacbrcXDEhjZVzClgyJZOYSM2CSWBq7hngD+/X8+J7R6lp6yM9IZrbLingtrkFZCXF+Ls8ERFBQVdERAJA6/FBXtpZx+93HKW+s5+k2Eg+OzOXlXPymZyd6O/yRBh2udl0qIUXd9ax/mAzLrdlTlEKX7i0kOXTsvUYLRGRAKOgKyIiAcPttvz1cCsv7azjzQNNOF1uyvKSuHl2PtfOyNEjisTnalp7eXlXHa/sdtDcM0h6QhQ3zsrjptn5WmovIhLAFHRFRCQgdfQ6+eOeel7aWcfBYz3ERIZxzfRsPjszl8vHpxMepv2PcmF0Dwyxbv8xXn3fwfbqdsIMLJyUwc1z8llUmkFkuGZvRUQCnYKuiIgENGst+xxdvLSrjtf2NNAzOMzYMdGsKMvm+hm5lOUl6dAfOWeDwy42HGxh7d563i5vxjnspjAtjptn53PjrDztvRURGWUUdEVEZNQYGHKx4WAza/Y0sP5gM06Xm6K0OK6dkcv1M3IYN1ZLSeXsudyWHdVtrNnTwJ/3N9IzMEx6QhQrynK4bkYOM/KT9UcUEZFRSkFXRERGpa5+z/LSNXvr2Xq4DWthem4S10zPZunUTIVeOS2X27Kzpp11B47x5w8aaeoeJD4qnKXTsrhuRi5XjE8jQkuTRURGPQVdEREZ9Zq6B3htbwOv7W1gr6MLgJKMBJZOzWLZtCym5iRqZi6EDQy52Hq4lXX7m3irvIn2XidREWHMKxnL9TNzuLo0k9goPc5KRCSYKOiKiEhQqe/s580Dx1h34BjvHWnHbSE3OZYlUzNZOjWLOUWpOsgqBPQMDLGxooU3Dhxj48Fmep0uxkRHsLA0g6VTs5g/aSwJ0RH+LlNERC4QnwRdY0wq8BJQBNQAN1trO07T7k7gh97LH1lrn/XefxC4A0ix1iac1D4aeA64GGgDVlpra0aqR0FXRCQ0tPc6ebu8iTcPHGNzZSvOYTdJsZFcWZLO/IljmT9xLJmJOmQoGFhrKW/sYdOhFjYdamZXTQfDbkt6QhSfmpLJkqlZXD4+jegIzdyKiIQCXwXdh4F2a+1DxphVeALr/ae0SQV2AbMBC+wGLrbWdhhjLgVqgcpTgu69QJm19ivGmFuAz1prV45Uj4KuiEjoOT44zKaKFjZWNLPpUAvNPYMAlGaNORF6Ly5KURAaRTp6nWypamVTRQubK1to8f4/nZydyPyJY1lUmsHFhSmawRcRCUG+CroVwAJrbaMxJhvYaK2ddEqbW71t7vFe/8rb7oWT2hw/JeiuAx6w1m4zxkQAx4CxdoRiFXRFREKbtZaKph42VbSw6VALO2vaGXJZ4qLCuaQ4lbnFacwtTmV6bhJRETqYKFB09Q2xq7ad9460s/1IO/scnVgLyXGRXFXi+WPFvJJ0MjRLLyIS8s426J7rJpZMa20jgDfsZpymTS5Qd9K1w3vv45z4GmvtsDGmC0gDWs+xXhERCWLGGEqzEinNSuSe+ePpHRxme3UbGyta2FbdxoaKgwDERIYxqyCFucWpzC1OZWZ+ig4t8qGWnkF21niC7Y4j7Rw81o21EBUexkX5SXzr6onMm5hOWV6yZm1FROQTGTHoGmPeBrJO86l/O8ufcbpXqJGmkc/6a4wxdwN3AxQUFJxlSSIiEgrioyO4enImV0/OBKD1+CC7ajzh6r0j7Tz6TiXWQmS4YWpOEjPyk5mem0RZXhLjxiYoZJ0H/U4XHzZ2sc/RxQeOLvbUdVLd2gtAbGQ4Fxem8O3FE5lbnMqM/GRiIvUHBxEROXcjBl1r7eIzfc4Y02SMyT5p6XLzaZo5gAUnXecBG0f4sQ4gH3B4ly4nAe1nqO9J4EnwLF0e4fuKiEgIS0+IZtm0bJZNywage2CI3TUd7DjSzvu1Hby8q47fbK0BIC4qnGk5SUzP8wTfablJFKbG6VmsH6Pf6aKiqYcPHJ2eYFvfxaGmHtzeV+exY6K5KC+JlXPymVucyrTcJCL131NERC6Ac126vBa4E3jI+37NadqsA35sjEnxXi8Bvn+W33cb8Dlg/Uj7c0VERP5ZiTGRLCzNYGGpZ+eNy22pbjl+IqTtc3Ty2+21DA67AYiKCGNcejwTMhIoyRhDSWYCJRkJFKbFh9Se356BIaqaj1PZfJwq71tlcw+Ojn4+erVOjY+iLC+JJVMymZ6XTFlekk7CFhERnznXw6jSgJeBAuAocJO1tt0YMxv4irX2S952/wL8wPtlD1prn/Hefxi4DcgBGoDV1toHjDExwPPATDwzubdYa6tHqkeHUYmIyPk27HJT2Xyc/fVdJ8JdZXMPde39J9pEhBkK0+IoTIsnNzmWvJRYclNiyUuJIy8llrT4KIwZPcugh11uGrsGcHT0U9/Zj6Ojj/qOfhwd/dS09dLYNXCibVR4GOPGxlOSOYaSjAQmZiYwPS+ZnKSYUfVvFhGR0cEnpy4HGgVdERHxlT7nMNUtvVQ291DZ5JnVrOvop76jj+6B4b9rGxMZRm5yLBljYkhNiCItPorU+I/eR3s+TogiKTaS2Khw4iLDz9sSaWstg8NuBoZc9DldtPc6T7y19Tpp7x30fHzcc6+xa4Bj3QO43H//+0HGmGjyUmIpSI07EWpLMseQnxKr5dwiIuIzvjp1WUREJCTFRUUwLdezd/dU3QNDJ2ZA6zv6TsyMtvQMUt7QTVuvk67+oY/9/pHhhtjIcE/wjYogJjKc6IgwPm6S1G1hwOmib2iYfqebfucw/UMu3B/zN+3wMENK3P+H77nFqZ4Z6WTPjHRuSizZSTE6JEpEREYVBV0REZHzLDEmksTsSCZnJ56xzZDLTceJWVXP++7+oRMzr/1DLvqdnrc+78eDw66P/bnGGLISo08E49jIcOKiPGH5o9CcEhd5YhY5PSGKxJhIwnS6tIiIBBkFXRERET+IDA8jIzGGDB3QJCIict5pU42IiIiIiIgEFQVdERERERERCSoKuiIiIiIiIhJUFHRFREREREQkqCjoioiIiIiISFBR0BUREREREZGgoqArIiIiIiIiQUVBV0RERERERIKKgq6IiIiIiIgEFQVdERERERERCSoKuiIiIiIiIhJUFHRFREREREQkqCjoioiIiIiISFAx1lp/13DeGGNagFp/1zGCdKDV30WIoL4ogUX9UQKJ+qMEEvVHCSSB0B8LrbVjR2oUVEF3NDDG7LLWzvZ3HSLqixJI1B8lkKg/SiBRf5RAMpr6o5Yui4iIiIiISFBR0BUREREREZGgoqDre0/6uwARL/VFCSTqjxJI1B8lkKg/SiAZNf1Re3RFREREREQkqGhGV0RERERERIKKgq6PGGOWGWMqjDFVxphV/q5HQosxJt8Ys8EYU26MOWCM+ab3fqox5i1jTKX3fYq/a5XQYYwJN8b8zRjzJ+91sTFmh7c/vmSMifJ3jRIajDHJxphXjDEHvePkZRofxV+MMd/2vlbvN8a8YIyJ0fgovmKM+bUxptkYs/+ke6cdD43H/3jzzT5jzCz/Vf6PFHR9wBgTDjwOLAemALcaY6b4tyoJMcPAd6y1k4FLga95++Aq4B1rbQnwjvdaxFe+CZSfdP0T4Bfe/tgBfNEvVUkoehR4w1pbClyEp19qfBSfM8bkAt8AZltrpwHhwC1ofBTf+Q2w7JR7ZxoPlwMl3re7gSd8VONZUdD1jblAlbW22lrrBF4ErvNzTRJCrLWN1tr3vR/34PklLhdPP3zW2+xZ4Hr/VCihxhiTB3waWO29NsAi4BVvE/VH8QljTCIwD3gawFrrtNZ2ovFR/CcCiDXGRABxQCMaH8VHrLWbgfZTbp9pPLwOeM56bAeSjTHZvql0ZAq6vpEL1J107fDeE/E5Y0wRMBPYAWRaaxvBE4aBDP9VJiHmv4HvAW7vdRrQaa0d9l5rnBRfGQe0AM94l9KvNsbEo/FR/MBaWw88AhzFE3C7gN1ofBT/OtN4GNAZR0HXN8xp7um4a/E5Y0wC8CrwLWttt7/rkdBkjFkBNFtrd598+zRNNU6KL0QAs4AnrLUzgV60TFn8xLv38TqgGMgB4vEsDz2VxkcJBAH92q2g6xsOIP+k6zygwU+1SIgyxkTiCbm/s9b+wXu76aMlJt73zf6qT0LKFcC1xpgaPFs5FuGZ4U32LtUDjZPiOw7AYa3d4b1+BU/w1fgo/rAYOGKtbbHWDgF/AC5H46P415nGw4DOOAq6vrETKPGemBeF51CBtX6uSUKId//j00C5tfbnJ31qLXCn9+M7gTW+rk1Cj7X2+9baPGttEZ7xcL219vPABuBz3mbqj+IT1tpjQJ0xZpL31tXAh2h8FP84ClxqjInzvnZ/1B81Poo/nWk8XAvc4T19+VKg66MlzoHAWBsws8tBzRhzDZ4Zi3Dg19baB/1ckoQQY8yVwBbgA/5/T+QP8OzTfRkowPPiepO19tQDCEQuGGPMAuC71toVxphxeGZ4U4G/AV+w1g76sz4JDcaYGXgORosCqoG78EwGaHwUnzPG/CewEs8TE/4GfAnPvkeNj3LBGWNeABYA6UAT8B/AHznNeOj9Y8xjeE5p7gPustbu8kfdp6OgKyIiIiIiIkFFS5dFREREREQkqCjoioiIiIiISFBR0BUREREREZGgoqArIiIiIiIiQUVBV0RERERERIKKgq6IiIiIiIgEFQVdERERERERCSoKuiIiIiIiIhJU/g/bpkPwPiOi4QAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "diff = analytical_solution - simulated_solution\n",
+    "plt.plot(diff[:, cells//2, 1]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.vector_field_magnitude(simulated_solution - analytical_solution)\n",
+    "plt.colorbar();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Periodic version"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "force_p = add_flipped_on_top(force)\n",
+    "\n",
+    "analytical_solution_p = get_field_from_term((0, 0), (pi - dx, pi - dx), [cells, cells], sym_vel.subs(replacements))\n",
+    "analytical_solution_p = add_flipped_on_top(analytical_solution_p)\n",
+    "\n",
+    "force_with_gl_p = add_ghost_layers(force_p, index_dimensions=1)\n",
+    "forceField = Field.create_from_numpy_array('forceArr', force_with_gl_p, index_dimensions=1)\n",
+    "initial_velocity_p = analytical_solution_p / dx * dt\n",
+    "\n",
+    "sc_p = create_fully_periodic_flow(initial_velocity=initial_velocity_p, method=method,\n",
+    "                                  force=(0, forceField(1)), force_model=force_model,\n",
+    "                                  kernel_params={'forceArr': force_with_gl_p},\n",
+    "                                  relaxation_rate=relaxation_rate,\n",
+    "                                  equilibrium_order=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.vector_field(analytical_solution_p, step=8);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sc_p.run(50_000)\n",
+    "plt.vector_field(get_lower_half(sc_p.velocity[:, :]), step=6);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "simulated_solution = get_lower_half(sc_p.velocity[:, :]) * dx / dt\n",
+    "plt.vector_field(simulated_solution, step=4);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "L2  Error 0.00036617543711501665\n",
+      "Inf Error 0.0006321865458609466\n"
+     ]
+    }
+   ],
+   "source": [
+    "l2_norm = discrete_l2_norm_by_number_of_nodes(simulated_solution - analytical_solution)\n",
+    "inf_norm = discrete_linf_norm(simulated_solution - analytical_solution)\n",
+    "assert l2_norm < 4e-4\n",
+    "assert inf_norm < 7e-4\n",
+    "print(\"L2  Error\", l2_norm)\n",
+    "print(\"Inf Error\", inf_norm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.vector_field_magnitude(simulated_solution - analytical_solution)\n",
+    "plt.colorbar();"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/lbmpy_tests/test_vectorization.py b/lbmpy_tests/test_vectorization.py
new file mode 100644
index 0000000000000000000000000000000000000000..ce92f54ff59abccd0d3106bada92e2c5f9e2882a
--- /dev/null
+++ b/lbmpy_tests/test_vectorization.py
@@ -0,0 +1,70 @@
+import pytest
+import numpy as np
+from lbmpy.scenarios import create_lid_driven_cavity
+
+
+def test_lbm_vectorization_short():
+    print("Computing reference solutions")
+    size1 = (64, 32)
+    relaxation_rate = 1.8
+
+    ldc1_ref = create_lid_driven_cavity(size1, relaxation_rate=relaxation_rate)
+    ldc1_ref.run(10)
+
+    ldc1 = create_lid_driven_cavity(size1, relaxation_rate=relaxation_rate,
+                                    optimization={'vectorization': {'instruction_set': 'avx',
+                                                                    'assume_aligned': True,
+                                                                    'nontemporal': True,
+                                                                    'assume_inner_stride_one': False,
+                                                                    'assume_sufficient_line_padding': False,
+                                                                    }},
+                                    fixed_loop_sizes=False)
+    ldc1.run(10)
+
+
+@pytest.mark.longrun
+def test_lbm_vectorization():
+    vectorization_options = [{'instruction_set': instruction_set,
+                              'assume_aligned': aa,
+                              'nontemporal': nt,
+                              'assume_inner_stride_one': True,
+                              'assume_sufficient_line_padding': lp,
+                              }
+                             for instruction_set in ('sse', 'avx')
+                             for aa, lp in ([False, False], [True, False], [True, True],)
+                             for nt in (False, True)
+                             ]
+    time_steps = 100
+    size1 = (64, 32)
+    size2 = (666, 34)
+    relaxation_rate = 1.8
+
+    print("Computing reference solutions")
+    ldc1_ref = create_lid_driven_cavity(size1, relaxation_rate=relaxation_rate)
+    ldc1_ref.run(time_steps)
+    ldc2_ref = create_lid_driven_cavity(size2, relaxation_rate=relaxation_rate)
+    ldc2_ref.run(time_steps)
+
+    for double_precision in (False, True):
+        for vec_opt in vectorization_options:
+            for fixed_loop_sizes in (True, False):
+                optimization = {'double_precision': double_precision,
+                                'vectorization': vec_opt,
+                                'cse_global': True,
+                                }
+                print("Vectorization test, double precision {}, vectorization {}, fixed loop sizes {}".format(
+                    double_precision, vec_opt, fixed_loop_sizes))
+                ldc1 = create_lid_driven_cavity(size1, relaxation_rate=relaxation_rate, optimization=optimization,
+                                                fixed_loop_sizes=fixed_loop_sizes)
+                ldc1.run(time_steps)
+                np.testing.assert_almost_equal(ldc1_ref.velocity[:, :], ldc1.velocity[:, :])
+
+                optimization['split'] = True
+                ldc2 = create_lid_driven_cavity(size2, relaxation_rate=relaxation_rate, optimization=optimization,
+                                                fixed_loop_sizes=fixed_loop_sizes)
+                ldc2.run(time_steps)
+                np.testing.assert_almost_equal(ldc2_ref.velocity[:, :], ldc2.velocity[:, :])
+
+
+if __name__ == '__main__':
+    test_lbm_vectorization()
diff --git a/lbmpy_tests/walberla_scenario_setup.py b/lbmpy_tests/walberla_scenario_setup.py
new file mode 100644
index 0000000000000000000000000000000000000000..a9624b25db8eefde15bf3d3e88e3ff5b905584d6
--- /dev/null
+++ b/lbmpy_tests/walberla_scenario_setup.py
@@ -0,0 +1,149 @@
+import waLBerla.field as field
+from waLBerla import makeSlice, createUniformBufferedScheme, createUniformBlockGrid
+
+
+def create_walberla_lattice_model(stencil, method, relaxation_rates, compressible=False, order=2,
+                                  force_model='none', force=(0, 0, 0), **_):
+    from waLBerla import lbm
+
+    if method.lower() == 'srt':
+        collision_model = lbm.collisionModels.SRT(relaxation_rates[0])
+    elif method.lower() == 'trt':
+        collision_model = lbm.collisionModels.TRT(relaxation_rates[0], relaxation_rates[1])
+    elif method.lower() == 'mrt':
+        if stencil != 'D3Q19':
+            raise ValueError("MRT is available for D3Q19 only in walberla")
+        collision_model = lbm.collisionModels.D3Q19MRT(*relaxation_rates[1:7])
+    else:
+        raise ValueError("Unknown method: " + str(method))
+
+    if len(force) == 2:
+        force = (force[0], force[1], 0)
+
+    if force_model is None or force_model.lower() == 'none':
+        force_model = lbm.forceModels.NoForce()
+    elif force_model.lower() == 'simple':
+        force_model = lbm.forceModels.SimpleConstant(force)
+    elif force_model.lower() == 'luo':
+        force_model = lbm.forceModels.LuoConstant(force)
+    elif force_model.lower() == 'guo':
+        force_model = lbm.forceModels.GuoConstant(force)
+    else:
+        raise ValueError("Unknown force model")
+    return lbm.makeLatticeModel(stencil, collision_model, force_model, compressible, order)
+
+
+def create_force_driven_channel_2d(force, radius, length, **kwargs):
+    from waLBerla import lbm
+
+    kwargs['force'] = tuple([force, 0, 0])
+
+    domain_size = (length, 2 * radius, 1)
+
+    lattice_model = create_walberla_lattice_model(**kwargs)
+    blocks = createUniformBlockGrid(cells=domain_size, periodic=(1, 0, 1))
+
+    # Adding fields
+    lbm.addPdfFieldToStorage(blocks, "pdfs", lattice_model, velocityAdaptor="vel", densityAdaptor="rho",
+                             initialDensity=1.0)
+    field.addFlagFieldToStorage(blocks, 'flags')
+    lbm.addBoundaryHandlingToStorage(blocks, 'boundary', 'pdfs', 'flags')
+
+    # Communication
+    communication = createUniformBufferedScheme(blocks, lattice_model.communicationStencilName)
+    communication.addDataToCommunicate(field.createPackInfo(blocks, 'pdfs'))
+
+    # Setting boundaries
+    for block in blocks:
+        b = block['boundary']
+        if block.atDomainMaxBorder[1]:  # N
+            b.forceBoundary('NoSlip', makeSlice[:, -1, :, 'g'])
+        if block.atDomainMinBorder[1]:  # S
+            b.forceBoundary('NoSlip', makeSlice[:, 0, :, 'g'])
+
+        b.fillWithDomain()
+
+    sweep = lbm.makeCellwiseSweep(blocks, "pdfs", flagFieldID='flags', flagList=['fluid']).streamCollide
+
+    def time_loop(time_steps):
+        for t in range(time_steps):
+            communication()
+            for B in blocks:
+                B['boundary']()
+            for B in blocks:
+                sweep(B)
+        full_pdf_field = field.toArray(field.gather(blocks, 'pdfs', makeSlice[:, :, :]), withGhostLayers=False)
+        density = field.toArray(field.gather(blocks, 'rho', makeSlice[:, :, :]), withGhostLayers=False)
+        velocity = field.toArray(field.gather(blocks, 'vel', makeSlice[:, :, :]), withGhostLayers=False)
+        full_pdf_field = full_pdf_field[:, :, 0, :]
+        density = density[:, :, 0, 0]
+        velocity = velocity[:, :, 0, :2]
+        return full_pdf_field, density, velocity
+
+    return time_loop
+
+
+def create_lid_driven_cavity(domain_size, lid_velocity=0.005, **kwargs):
+    from waLBerla import lbm
+
+    d = len(domain_size)
+
+    if 'stencil' not in kwargs:
+        kwargs['stencil'] = 'D2Q9' if d == 2 else 'D3Q27'
+
+    if d == 2:
+        domain_size = (domain_size[0], domain_size[1], 1)
+
+    lattice_model = create_walberla_lattice_model(**kwargs)
+    blocks = createUniformBlockGrid(cells=domain_size, periodic=(1, 1, 1))
+
+    # Adding fields
+    lbm.addPdfFieldToStorage(blocks, "pdfs", lattice_model, velocityAdaptor="vel", densityAdaptor="rho",
+                             initialDensity=1.0)
+    field.addFlagFieldToStorage(blocks, 'flags')
+    lbm.addBoundaryHandlingToStorage(blocks, 'boundary', 'pdfs', 'flags')
+
+    # Communication
+    communication = createUniformBufferedScheme(blocks, lattice_model.communicationStencilName)
+    communication.addDataToCommunicate(field.createPackInfo(blocks, 'pdfs'))
+
+    # Setting boundaries
+    for block in blocks:
+        b = block['boundary']
+        if block.atDomainMaxBorder[1]:  # N
+            b.forceBoundary('UBB', makeSlice[:, -1, :, 'g'], {'x': lid_velocity})
+        if block.atDomainMinBorder[1]:  # S
+            b.forceBoundary('NoSlip', makeSlice[:, 0, :, 'g'])
+        if block.atDomainMinBorder[0]:  # W
+            b.forceBoundary('NoSlip', makeSlice[0, :, :, 'g'])
+        if block.atDomainMaxBorder[0]:  # E
+            b.forceBoundary('NoSlip', makeSlice[-1, :, :, 'g'])
+        if block.atDomainMinBorder[2] and d == 3:  # T
+            b.forceBoundary('NoSlip', makeSlice[:, :, 0, 'g'])
+        if block.atDomainMaxBorder[2] and d == 3:  # B
+            b.forceBoundary('NoSlip', makeSlice[:, :, -1, 'g'])
+
+        b.fillWithDomain()
+
+    sweep = lbm.makeCellwiseSweep(blocks, "pdfs", flagFieldID='flags', flagList=['fluid']).streamCollide
+
+    def time_loop(time_steps):
+        for t in range(time_steps):
+            communication()
+            for B in blocks:
+                B['boundary']()
+            for B in blocks:
+                sweep(B)
+        full_pdf_field = field.toArray(field.gather(blocks, 'pdfs', makeSlice[:, :, :]), withGhostLayers=False)
+        density = field.toArray(field.gather(blocks, 'rho', makeSlice[:, :, :]), withGhostLayers=False)
+        velocity = field.toArray(field.gather(blocks, 'vel', makeSlice[:, :, :]), withGhostLayers=False)
+        if d == 2:
+            full_pdf_field = full_pdf_field[:, :, 0, :]
+            density = density[:, :, 0, 0]
+            velocity = velocity[:, :, 0, :2]
+        elif d == 3:
+            density = density[:, :, :, 0]
+
+        return full_pdf_field, density, velocity
+
+    return time_loop
diff --git a/setup.py b/setup.py
new file mode 100644
index 0000000000000000000000000000000000000000..a612d86e0e4d623a7accdee5555688c0a60c23b2
--- /dev/null
+++ b/setup.py
@@ -0,0 +1,28 @@
+from setuptools import setup, find_packages
+
+setup(name='lbmpy',
+      description='Code Generation for Lattice Boltzmann Methods',
+      author='Martin Bauer',
+      license='AGPLv3',
+      author_email='martin.bauer@fau.de',
+      url='https://i10git.cs.fau.de/software/pystencils/',
+      packages=['lbmpy'] + ['lbmpy.' + s for s in find_packages('lbmpy')],
+      install_requires=['pystencils'],
+      classifiers=[
+            'Development Status :: 4 - Beta',
+            'Framework :: Jupyter',
+            'Topic :: Software Development :: Code Generators',
+            'Topic :: Scientific/Engineering :: Physics',
+            'Intended Audience :: Developers',
+            'Intended Audience :: Science/Research',
+            'License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)',
+      ],
+      python_requires=">=3.6",
+      extras_require={
+            'gpu': ['pystencils[gpu]'],
+            'alltrafos': ['pystencils[alltrafos]'],
+            'interactive': ['pystencils[interactive]', 'scipy', 'scikit-image', 'cython'],
+            'doc': ['pystencils[doc]'],
+      },
+      version_format='{tag}.dev{commits}+{sha}',
+      )