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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..a6a9497675b5c2fb331b14289464d4488916bbec
--- /dev/null
+++ b/README.md
@@ -0,0 +1,6 @@
+pystencils
+==========
+
+
+![alt text](doc/img/logo.png)
+
diff --git a/assignment_collection/nestedscopes.py b/assignment_collection/nestedscopes.py
deleted file mode 100644
index dd33eb1a0bfbbec8ff20c29335ba2e9e02592518..0000000000000000000000000000000000000000
--- a/assignment_collection/nestedscopes.py
+++ /dev/null
@@ -1,52 +0,0 @@
-class NestedScopes:
-    """Symbol visibility model using nested scopes
-
-    - every accessed symbol that was not defined before, is added as a "free parameter"
-    - free parameters are global, i.e. they are not in scopes
-    - push/pop adds or removes a scope
-
-    >>> s = NestedScopes()
-    >>> s.access_symbol("a")
-    >>> s.is_defined("a")
-    False
-    >>> s.free_parameters
-    {'a'}
-    >>> s.define_symbol("b")
-    >>> s.is_defined("b")
-    True
-    >>> s.push()
-    >>> s.is_defined_locally("b")
-    False
-    >>> s.define_symbol("c")
-    >>> s.pop()
-    >>> s.is_defined("c")
-    False
-    """
-
-    def __init__(self):
-        self.free_parameters = set()
-        self._defined = [set()]
-
-    def access_symbol(self, symbol):
-        if not self.is_defined(symbol):
-            self.free_parameters.add(symbol)
-
-    def define_symbol(self, symbol):
-        self._defined[-1].add(symbol)
-
-    def is_defined(self, symbol):
-        return any(symbol in scopes for scopes in self._defined)
-
-    def is_defined_locally(self, symbol):
-        return symbol in self._defined[-1]
-
-    def push(self):
-        self._defined.append(set())
-
-    def pop(self):
-        self._defined.pop()
-        assert self.depth >= 1
-
-    @property
-    def depth(self):
-        return len(self._defined)
diff --git a/doc/conf.py b/doc/conf.py
new file mode 100644
index 0000000000000000000000000000000000000000..a71c41e781d07c70990ce446042ee2947f25b114
--- /dev/null
+++ b/doc/conf.py
@@ -0,0 +1,12 @@
+#!/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('../..'))
+from sphinx_doc_conf import *
+
+project = 'pystencils'
+html_logo = "img/logo.png"
diff --git a/doc/img/c_backend.svg b/doc/img/c_backend.svg
new file mode 100644
index 0000000000000000000000000000000000000000..d7d6f50821d33c02dcfd665b94d0a9f4b56210f7
--- /dev/null
+++ b/doc/img/c_backend.svg
@@ -0,0 +1,2916 @@
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diff --git a/doc/index.rst b/doc/index.rst
new file mode 100644
index 0000000000000000000000000000000000000000..a52161449e714d431cc258a06503398a986c8bf1
--- /dev/null
+++ b/doc/index.rst
@@ -0,0 +1,18 @@
+pystencils
+==========
+
+Welcome to the documentation of the pystencils code generation tool for stencil codes.
+pystencils can help you to generate blazingly fast code for image processing, numerical simulations or any other task involving numpy arrays.
+
+
+.. toctree::
+   :maxdepth: 2
+
+   sphinx/tutorials.rst
+   sphinx/api.rst
+
+
+.. image:: /img/pystencils_arch_block_diagram.svg
+    :height: 450px
+
+
diff --git a/doc/notebooks/01_tutorial_getting_started.ipynb b/doc/notebooks/01_tutorial_getting_started.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..22eba4c05d204f86e0c6d1f02245d806bd69e89e
--- /dev/null
+++ b/doc/notebooks/01_tutorial_getting_started.ipynb
@@ -0,0 +1,1831 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 01: Getting Started\n",
+    "\n",
+    "\n",
+    "## Overview\n",
+    "\n",
+    "\n",
+    "*pystencils* is a package that can speed up transformations on *numpy* arrays. All computations are carried out fully parallel on CPUs (single node with OpenMP, multiple nodes with MPI) or on GPUs.\n",
+    "\n",
+    "It is suited for applications that run the same operation on *numpy* arrays multiple times like for example:\n",
+    "- numerical simulations (finite difference, lattice Boltzmann)\n",
+    "- image processing\n",
+    "\n",
+    "As the name suggests, *pystencils* was developed for **stencil codes**, i.e. operations that update an element of a numpy array using only a local neighborhood. \n",
+    "\n",
+    "<img width=\"25%\" src='../../img/pystencils_stencil_four_points_with_arrows.svg'>\n",
+    "\n",
+    "It generates C code, compiles it behind the scenes, and lets you call the compiled C function as if it was a native Python function. \n",
+    "\n",
+    "But lets not dive too deep into the concepts of *pystencils* here, they are covered in detail in the following tutorials. Lets instead look at a simple example, that computes the average neighbor values of a *numpy* array.\n",
+    "\n",
+    "We create two rather large arrays for in- and output."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "input_arr = np.random.rand(1024, 1024)\n",
+    "output_arr = np.zeros_like(input_arr)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We first implement a version of this algorithm using pure numpy and benchmark it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def numpy_kernel():\n",
+    "    output_arr[1:-1, 1:-1] = input_arr[2:, 1:-1] + input_arr[:-2, 1:-1] + \\\n",
+    "                             input_arr[1:-1, 2:] + input_arr[1:-1, :-2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "7.13 ms ± 254 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%timeit \n",
+    "numpy_kernel()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now lets see how to run the same algorithm with *pystencils*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$${{dst}_{(0,0)}} \\leftarrow \\frac{{{src}_{(-1,0)}}}{4} + \\frac{{{src}_{(0,-1)}}}{4} + \\frac{{{src}_{(0,1)}}}{4} + \\frac{{{src}_{(1,0)}}}{4}$$"
+      ],
+      "text/plain": [
+       "         src_W   src_S   src_N   src_E\n",
+       "dst_C := ───── + ───── + ───── + ─────\n",
+       "           4       4       4       4  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "src, dst = ps.fields(src=input_arr, dst=output_arr)\n",
+    "\n",
+    "symbolic_description = ps.Assignment(dst[0,0], \n",
+    "                                     (src[1, 0] + src[-1, 0] + src[0, 1] + src[0, -1]) / 4)\n",
+    "symbolic_description"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 216x216 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(3,3))\n",
+    "ps.visualize_stencil_expression(symbolic_description.rhs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here we first have created a symbolic notation of the stencil itself. This representation is built on top of *sympy* and is explained in detail in the next section. \n",
+    "This description is then compiled and loaded as a Python function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kernel = ps.create_kernel(symbolic_description).compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This whole process might seem overly complicated. We have already spent more lines of code as for the *numpy* implementation and don't have anything running yet! However, this multi stage process of formulating the algorithm symbolically, and just in the end actually running it, is what makes *pystencils* faster and more flexible than other approaches.\n",
+    "\n",
+    "Now finally lets benchmark the *pystencils* kernel."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def pystencils_kernel():\n",
+    "    kernel(src=input_arr, dst=output_arr)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1.36 ms ± 51.5 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%timeit\n",
+    "pystencils_kernel()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This benchmark shows that *pystencils* is a lot faster than pure *numpy*, especially for large arrays. \n",
+    "If you are interested in performance details and comparison to other packages like Cython, have a look at [this page](demo_benchmark.ipynb).\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Short *sympy* introduction\n",
+    "\n",
+    "In this tutorial we continue with a short *sympy* introduction, since the symbolic kernel definition is built on top of this package. If you already know *sympy* you can skip this section. \n",
+    "You can also read the full [sympy documentation here](http://docs.sympy.org/latest/index.html)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sympy as sp\n",
+    "sp.init_printing()  # enable nice LaTeX output"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "*sympy* is a package for symbolic calculation. So first we need some symbols:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "sympy.core.symbol.Symbol"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = sp.Symbol(\"x\")\n",
+    "y = sp.Symbol(\"y\")\n",
+    "type(x)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The usual mathematical operations are defined for symbols:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$x^{2} \\left(x + y + 5\\right) + x^{2}$$"
+      ],
+      "text/plain": [
+       " 2                2\n",
+       "x â‹…(x + y + 5) + x "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expr = x**2 * ( y + x + 5) + x**2\n",
+    "expr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can do all sorts of operations on these expressions: expand them, factor them, substitute variables:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$x^{3} + x^{2} y + 6 x^{2}$$"
+      ],
+      "text/plain": [
+       " 3    2        2\n",
+       "x  + x â‹…y + 6â‹…x "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expr.expand()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$x^{2} \\left(x + y + 6\\right)$$"
+      ],
+      "text/plain": [
+       " 2            \n",
+       "x â‹…(x + y + 6)"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expr.factor()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$x^{2} \\left(x + \\cos{\\left (x \\right )} + 5\\right) + x^{2}$$"
+      ],
+      "text/plain": [
+       " 2                     2\n",
+       "x â‹…(x + cos(x) + 5) + x "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expr.subs(y, sp.cos(x))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also built equations and solve them"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$x^{2} \\left(x + y + 5\\right) + x^{2} = 1$$"
+      ],
+      "text/plain": [
+       " 2                2    \n",
+       "x â‹…(x + y + 5) + x  = 1"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eq = sp.Eq(expr, 1)\n",
+    "eq"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left [ - x - 6 + \\frac{1}{x^{2}}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡         1 ⎤\n",
+       "⎢-x - 6 + ──⎥\n",
+       "⎢          2⎥\n",
+       "⎣         x ⎦"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sp.solve(sp.Eq(expr, 1), y)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A *sympy* expression is represented by an abstract syntax tree (AST), which can be inspected and modified."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$x^{2} \\left(x + y + 5\\right) + x^{2}$$"
+      ],
+      "text/plain": [
+       " 2                2\n",
+       "x â‹…(x + y + 5) + x "
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/svg+xml": [
+       "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
+       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
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+       "<!-- Generated by graphviz version 2.38.0 (20140413.2041)\n",
+       " -->\n",
+       "<!-- Title: %3 Pages: 1 -->\n",
+       "<svg width=\"422pt\" height=\"260pt\"\n",
+       " viewBox=\"0.00 0.00 422.00 260.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
+       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 256)\">\n",
+       "<title>%3</title>\n",
+       "<polygon fill=\"white\" stroke=\"none\" points=\"-4,4 -4,-256 418,-256 418,4 -4,4\"/>\n",
+       "<!-- Add(Pow(Symbol(x), Integer(2)), Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y))))_() -->\n",
+       "<g id=\"node1\" class=\"node\"><title>Add(Pow(Symbol(x), Integer(2)), Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y))))_()</title>\n",
+       "<ellipse fill=\"none\" stroke=\"black\" cx=\"135\" cy=\"-234\" rx=\"27\" ry=\"18\"/>\n",
+       "<text text-anchor=\"middle\" x=\"135\" y=\"-230.3\" font-family=\"Times,serif\" font-size=\"14.00\">Add</text>\n",
+       "</g>\n",
+       "<!-- Pow(Symbol(x), Integer(2))_(0,) -->\n",
+       "<g id=\"node2\" class=\"node\"><title>Pow(Symbol(x), Integer(2))_(0,)</title>\n",
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+       "<text text-anchor=\"middle\" x=\"99\" y=\"-158.3\" font-family=\"Times,serif\" font-size=\"14.00\">Pow</text>\n",
+       "</g>\n",
+       "<!-- Add(Pow(Symbol(x), Integer(2)), Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y))))_()&#45;&gt;Pow(Symbol(x), Integer(2))_(0,) -->\n",
+       "<g id=\"edge1\" class=\"edge\"><title>Add(Pow(Symbol(x), Integer(2)), Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y))))_()&#45;&gt;Pow(Symbol(x), Integer(2))_(0,)</title>\n",
+       "<path fill=\"none\" stroke=\"black\" d=\"M126.65,-216.765C122.288,-208.283 116.853,-197.714 111.959,-188.197\"/>\n",
+       "<polygon fill=\"black\" stroke=\"black\" points=\"114.99,-186.439 107.304,-179.147 108.765,-189.641 114.99,-186.439\"/>\n",
+       "</g>\n",
+       "<!-- Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,) -->\n",
+       "<g id=\"node5\" class=\"node\"><title>Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)</title>\n",
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+       "<text text-anchor=\"middle\" x=\"171\" y=\"-158.3\" font-family=\"Times,serif\" font-size=\"14.00\">Mul</text>\n",
+       "</g>\n",
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+       "<g id=\"edge2\" class=\"edge\"><title>Add(Pow(Symbol(x), Integer(2)), Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y))))_()&#45;&gt;Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)</title>\n",
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+       "<text text-anchor=\"middle\" x=\"27\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\">x</text>\n",
+       "</g>\n",
+       "<!-- Pow(Symbol(x), Integer(2))_(0,)&#45;&gt;Symbol(x)_(0, 0) -->\n",
+       "<g id=\"edge3\" class=\"edge\"><title>Pow(Symbol(x), Integer(2))_(0,)&#45;&gt;Symbol(x)_(0, 0)</title>\n",
+       "<path fill=\"none\" stroke=\"black\" d=\"M84.4297,-146.834C74.2501,-136.938 60.4761,-123.546 48.9694,-112.359\"/>\n",
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+       "</g>\n",
+       "<!-- Integer(2)_(0, 1) -->\n",
+       "<g id=\"node4\" class=\"node\"><title>Integer(2)_(0, 1)</title>\n",
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+       "<text text-anchor=\"middle\" x=\"99\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\">2</text>\n",
+       "</g>\n",
+       "<!-- Pow(Symbol(x), Integer(2))_(0,)&#45;&gt;Integer(2)_(0, 1) -->\n",
+       "<g id=\"edge4\" class=\"edge\"><title>Pow(Symbol(x), Integer(2))_(0,)&#45;&gt;Integer(2)_(0, 1)</title>\n",
+       "<path fill=\"none\" stroke=\"black\" d=\"M99,-143.697C99,-135.983 99,-126.712 99,-118.112\"/>\n",
+       "<polygon fill=\"black\" stroke=\"black\" points=\"102.5,-118.104 99,-108.104 95.5001,-118.104 102.5,-118.104\"/>\n",
+       "</g>\n",
+       "<!-- Pow(Symbol(x), Integer(2))_(1, 0) -->\n",
+       "<g id=\"node6\" class=\"node\"><title>Pow(Symbol(x), Integer(2))_(1, 0)</title>\n",
+       "<ellipse fill=\"none\" stroke=\"black\" cx=\"171\" cy=\"-90\" rx=\"27\" ry=\"18\"/>\n",
+       "<text text-anchor=\"middle\" x=\"171\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\">Pow</text>\n",
+       "</g>\n",
+       "<!-- Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)&#45;&gt;Pow(Symbol(x), Integer(2))_(1, 0) -->\n",
+       "<g id=\"edge5\" class=\"edge\"><title>Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)&#45;&gt;Pow(Symbol(x), Integer(2))_(1, 0)</title>\n",
+       "<path fill=\"none\" stroke=\"black\" d=\"M171,-143.697C171,-135.983 171,-126.712 171,-118.112\"/>\n",
+       "<polygon fill=\"black\" stroke=\"black\" points=\"174.5,-118.104 171,-108.104 167.5,-118.104 174.5,-118.104\"/>\n",
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+       "</g>\n",
+       "<!-- Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)&#45;&gt;Add(Integer(5), Symbol(x), Symbol(y))_(1, 1) -->\n",
+       "<g id=\"edge6\" class=\"edge\"><title>Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)&#45;&gt;Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)</title>\n",
+       "<path fill=\"none\" stroke=\"black\" d=\"M189.812,-148.807C207.002,-137.665 232.618,-121.062 251.993,-108.504\"/>\n",
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+       "<g id=\"node7\" class=\"node\"><title>Symbol(x)_(1, 0, 0)</title>\n",
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+       "<text text-anchor=\"middle\" x=\"99\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\">x</text>\n",
+       "</g>\n",
+       "<!-- Pow(Symbol(x), Integer(2))_(1, 0)&#45;&gt;Symbol(x)_(1, 0, 0) -->\n",
+       "<g id=\"edge7\" class=\"edge\"><title>Pow(Symbol(x), Integer(2))_(1, 0)&#45;&gt;Symbol(x)_(1, 0, 0)</title>\n",
+       "<path fill=\"none\" stroke=\"black\" d=\"M156.43,-74.8345C146.25,-64.9376 132.476,-51.5462 120.969,-40.3591\"/>\n",
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+       "</g>\n",
+       "<!-- Integer(2)_(1, 0, 1) -->\n",
+       "<g id=\"node8\" class=\"node\"><title>Integer(2)_(1, 0, 1)</title>\n",
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+       "<text text-anchor=\"middle\" x=\"171\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\">2</text>\n",
+       "</g>\n",
+       "<!-- Pow(Symbol(x), Integer(2))_(1, 0)&#45;&gt;Integer(2)_(1, 0, 1) -->\n",
+       "<g id=\"edge8\" class=\"edge\"><title>Pow(Symbol(x), Integer(2))_(1, 0)&#45;&gt;Integer(2)_(1, 0, 1)</title>\n",
+       "<path fill=\"none\" stroke=\"black\" d=\"M171,-71.6966C171,-63.9827 171,-54.7125 171,-46.1124\"/>\n",
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+       "<g id=\"node10\" class=\"node\"><title>Integer(5)_(1, 1, 0)</title>\n",
+       "<ellipse fill=\"none\" stroke=\"black\" cx=\"243\" cy=\"-18\" rx=\"27\" ry=\"18\"/>\n",
+       "<text text-anchor=\"middle\" x=\"243\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\">5</text>\n",
+       "</g>\n",
+       "<!-- Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)&#45;&gt;Integer(5)_(1, 1, 0) -->\n",
+       "<g id=\"edge9\" class=\"edge\"><title>Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)&#45;&gt;Integer(5)_(1, 1, 0)</title>\n",
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+       "<g id=\"node11\" class=\"node\"><title>Symbol(x)_(1, 1, 1)</title>\n",
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+       "</g>\n",
+       "<!-- Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)&#45;&gt;Symbol(x)_(1, 1, 1) -->\n",
+       "<g id=\"edge10\" class=\"edge\"><title>Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)&#45;&gt;Symbol(x)_(1, 1, 1)</title>\n",
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+       "</g>\n",
+       "<!-- Symbol(y)_(1, 1, 2) -->\n",
+       "<g id=\"node12\" class=\"node\"><title>Symbol(y)_(1, 1, 2)</title>\n",
+       "<ellipse fill=\"none\" stroke=\"black\" cx=\"387\" cy=\"-18\" rx=\"27\" ry=\"18\"/>\n",
+       "<text text-anchor=\"middle\" x=\"387\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\">y</text>\n",
+       "</g>\n",
+       "<!-- Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)&#45;&gt;Symbol(y)_(1, 1, 2) -->\n",
+       "<g id=\"edge11\" class=\"edge\"><title>Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)&#45;&gt;Symbol(y)_(1, 1, 2)</title>\n",
+       "<path fill=\"none\" stroke=\"black\" d=\"M297.812,-76.8069C315.002,-65.6653 340.618,-49.0622 359.993,-36.5043\"/>\n",
+       "<polygon fill=\"black\" stroke=\"black\" points=\"361.916,-39.4294 368.403,-31.0533 358.108,-33.5553 361.916,-39.4294\"/>\n",
+       "</g>\n",
+       "</g>\n",
+       "</svg>\n"
+      ],
+      "text/plain": [
+       "<graphviz.files.Source at 0x7f72368cf1d0>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ps.to_dot(expr, graph_style={'size': \"9.5,12.5\"} )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Programatically the children node type is acessible as ``expr.func`` and its children as ``expr.args``.\n",
+    "With these members a tree can be traversed and modified."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "sympy.core.add.Add"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expr.func"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left ( x^{2}, \\quad x^{2} \\left(x + y + 5\\right)\\right )$$"
+      ],
+      "text/plain": [
+       "⎛ 2   2            ⎞\n",
+       "⎝x , x ⋅(x + y + 5)⎠"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "expr.args"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Using *pystencils* \n",
+    "\n",
+    "\n",
+    "### Fields\n",
+    "\n",
+    "*pystencils* is a module to generate code for stencil operations. \n",
+    "One has to specify an update rule for each element of an array, with optional dependencies to neighbors.\n",
+    "This is done use pure *sympy* with one addition: **Fields**.\n",
+    "\n",
+    "Fields represent a multidimensional array, where some dimensions are considered *spatial*, and some as *index* dimensions. Spatial coordinates are given relative (i.e. one can specify \"the current cell\" and \"the left neighbor\") whereas index dimensions are used to index multiple values per cell."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "my_field = ps.Field.create_generic('f', spatial_dimensions=2, index_shape=(3,))\n",
+    "# or equivalently:\n",
+    "my_field = ps.fields(\"f(3) : double[2D]\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Neighbors are labeled according to points on a compass where the first coordinate is west/east, second coordinate north/south and third coordinate top/bottom. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$${{f}_{(1,0)}^{1}}$$"
+      ],
+      "text/plain": [
+       "f_E__1"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "field_access = my_field[1, 0](1)\n",
+    "field_access"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The result of indexing a field is an instance of ``Field.Access``. This class is a subclass of a *sympy* Symbol and thus can be used whereever normal symbols can be used. It is just like a normal symbol with some additional information attached to it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "isinstance(field_access, sp.Symbol)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Building our first stencil kernel\n",
+    "\n",
+    "Lets start by building a simple filter kernel. We create a field representing an image, then define a edge detection filter on the third pixel component which is blue for an RGB image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "img_field = ps.Field.create_generic('img', \n",
+    "                                    spatial_dimensions=2, # 2D image \n",
+    "                                    index_dimensions=1)   # multiple values per pixel: e.g. RGB"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left(- {{img}_{(-1,-1)}^{2}} w_{1} - {{img}_{(-1,0)}^{2}} w_{2} - {{img}_{(-1,1)}^{2}} w_{1} + {{img}_{(1,-1)}^{2}} w_{1} + {{img}_{(1,0)}^{2}} w_{2} - {{img}_{(1,1)}^{2}} w_{1}\\right)^{2}$$"
+      ],
+      "text/plain": [
+       "                                                                              \n",
+       "(-img_SW__2⋅w₁ - img_W__2⋅w₂ - img_NW__2⋅w₁ + img_SE__2⋅w₁ + img_E__2⋅w₂ - img\n",
+       "\n",
+       "          2\n",
+       "_NE__2⋅w₁) "
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "w1, w2 = sp.symbols(\"w_1 w_2\")\n",
+    "color = 2\n",
+    "sobel_x = (-w2 * img_field[-1,0](color) - w1 * img_field[-1,-1](color) - w1 * img_field[-1, +1](color) \\\n",
+    "           +w2 * img_field[+1,0](color) + w1 * img_field[+1,-1](color) - w1 * img_field[+1, +1](color))**2\n",
+    "sobel_x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We have mixed some standard *sympy* symbols into this expression to possibly give the different directions different weights. The complete expression is still a valid *sympy* expression, so all features of *sympy* work on it. Lets for example now fix one weight by substituting it with a constant."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAzUAAAAsBAMAAACu84sRAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAZnbNRO8QMqsimd27VInIquLFAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAJcklEQVR4Ae1abYhcVxl+Zmf2zs73WAmCP5oxaonRxsH9YaW0zB+xoCTbFCxCbQc/ILbgDFT/FHUn8YdGC46Cgqllx0b8io1rUz+KVAeRUGN+jGIhakquKWJcxaZx2WaFur7vOffcOffecz/m7mAWMufHPe97zvs89/2Ye865dxeYtZ2YgeoPvr0T3Zr5RBn4Oz47y8MOzcAzWO7vUNdueLeexkrrhk/Cjk3AxfaOde2Gd+wpkYFM/YZPxM5JwGHHlepACG/cOZ7NPMk1ZQ5eL7rc+2cZ2UEZ2CuLYue6JHyUL7O2UzKQFTvMwy9caJNHn0/u1dpZBqRs037VnQZfSo6UMEPigkyFDTZ7YGuLrvlNA8Q8VO0vOKuheT56dNqvutPgS8mREmbIj4FJe1ayPQPEPFTqT1DIAMW0X3WnwZeSIyUskBLAwLTcdu1W+q4YJ5RahfU4m/D5ab/qToMvJUdKmCE3BqZsw7U76UoJhIpYDBMYGk2m/ao7Db6UHClhhrQEmDJLrtUhV0oglBoJjEJN5Ktu6PTEE9PgS8mREmYIMcA0XpsKr2j21qmbu6xmb8k/CSwMtSkprgVGQgeCaOdVNxThn4jzJgnfNDgMiUhyaxnOg3/5mxDe0X5kBDzqjxEGpvuVUeaKkqjPjqxnWJ3f2rKpNnWW9ZYZ6Fq0HETLV91olD4b500SvmlwGBKR5NYylDvwUJ+lB7b+S9cjclC7Gpjcv9wUVzXDXcCLrGYvv0UbHYsH8J6xMqmUk6+6yWEx3kTyVRryPtvhwO/DfI28tQdEm0e1ySN3HhUl8kySYmJ6uzIqDZVE/XOA2JoWtDFNzN/xwhlNnVB0XnWTo2K8ieRTtdkOR3htIm/tCbDcgzw/9TzDrmJiuqiqWBu4dsA14OCI9JDa0FJ3RbOeUJSvuhOAYryJ5FO12Q5HeG0ib+2JsNZD7lUe6XmGXcXEtMwl4FZriE5crP9QbVhfeM2+Lj70BHKXv77naO7Sr2noT3suCJukl+Rossw0K8EPrtvyxqnNtjhUbZKEEhZEZ4DcVc7ZkZu+A2tfAweOfWVv48DbWkDliVuHPBNonboz5AqkF2i7WrZJKLfpIGe/G9Xyr9B5E54HqsMCFW6ClhxtP49yL7cO/8e6bXnj1GZbHKo2SUIJC2LFRp4PAThDf2Su5pZgn2tYV1uVJeCfWBkYE+o+LiuqSGTG6Re1Ifm3hdEJfLrUBLHvFtsQP5oFIxkNdn0TRnTfZyRgbFmr4zeBj3Xx3hj55D1UbWIjiuBwahMXSp7uGBoEpV/Whn7wq48Xm/nRaX4E6HRM21BtRFDNAWaiVrNFR7Xg+Q//nNs73RWAhn74NVxFu9Piw8GjwH3ym6hC4WEHLjpS/iAE63bmOd0FLAO6qjD5Jktzl2yGWTjE/1MycD7WaRSUV7HCkq3RGx8f+yTdqC4u3n7P4mKPyBNwmEPBi4uLP15cvC00FAnbvx+VVkQQ7poGFDfbtYZlrXNVFoaYH4p/paEgJBMlhZmouUeA5brQ5eUaPSBcKzphv9Ti88VF4CQoefmXMbdK+1DfMX7kixqKlaKaUeMG9DFnLv9dogJuxnkBy23izYAd/FgX542Pz+OG89zw6SYyomOICMU5QxtDkbCMXenhexRMWBA1OqfxgkMf8Kvr/DuvXEFxFfMNUOLfShPKAZEUZtJqo69pOAfsbtPsPfRLbWd7bZwAfkH3tTKbKA+Az9CcbH9WAvekWD19gOQgOm8rk4qozdOotRlGrj5HiwJtjr6PdTHe+Pk8bqjaJOAID8WpjTkUASu1sIHDFFdYEOUhMhzWfBPFDdxmodhEycbBfnt3H2fpLzS2SB9ZcFKYCejYoiOh4Qjc0ZsaVQMYAKfRGdm4H/QMFpuPU7V5cfwcT4rmDwjvUjNOH0QvdJWJqI31CuZHDCv3qP68PpUaykD2Md74+GSMyg1VmwQc4aE4tTGHImCdLj6IbD88CHr3pGpQ7Si8pvVqFfM2aKM4URjRkkQPFAchHeCkMBPgPi41m1WnlUbWveg0cRyZD+BgoU6nNdq1srZtbeJLhCO40wIBvUHNOH0QXXItRG3oT0GlOgg218zdh0/Q5JprIIUYb3x8MkblhqpNAo7wUJzamEMRMNoof4S5ekQQz9Lf/K1/ozDArn7uypf5XwLpaHVnFZ3+wiYVjEId14aZnCMAC/M9vjrNurS3i1IPhVNfaNNLDnKrmKMF85td3LX/H3QaiajNecXh9EH0Y66FrM0GPygM+/6lw/vJqcDHuhhvfHwyRuWGqk0CDpkaxzlWFIc6Q5tDEbDlNp5CpRcRxMf30GLzM+D4Zfrn8yN1vBfYS2+Lr0Pu6L8onRyEdICTIphwsEWD3MpN2cdez9KGN3StJJ+jsvI+d8ooEHpsoZ4b2hHHg5joY12QT8ao+CoNoxueQYcjPBTnufGAwLsE30XA6Lk5pKdloiDKA41J7DcywWLL55tWl/ga1/K87yBHz9A5avRRTXimK56TqI9Oou8CLjC6LdwA7Te1lnYWn+BjnZFP+qTcsPo+H/yqyxERysf8INq7RSIoFAmj/WYd8pVA2E4QRJf3HbhMIimS6a/qtv7DkRr39i+1yz1ybOiOBn5sfJOwJtGfcqfFcwM+pwnf5PgEH+vMfCJbUW6492dhzJEyFAEr8Tkt1yM+2ZIHUd3gL8vgpEgHOCm5Hqm8AspmvaykqP78TU/StEVwp9FnnG+0NYXeVsKbRD/kGlSWUDiDfbywR8Fce79g5uNPS8n5xhwpQxGwuQFtERnb72ACvXJk34jMOCnSAUqKZNIqwtVL2n6iDI//8ig+WXc0VvAtNRXal9rOVOHktUb+blRP0e4YD0vMl9ANDx/5lDIUB7a21kax5eGcSHEd4KRIpgod35y2SwkJ+ls9Nlx3tzVdKUyY89hXpFk8LIwO0+BTHB7X4n3ywrKhLsZPGJiK4/t3PH5Fs5X16Upf0yp1TQkRh/r4H4WSBKajPPJQ11LySY6UoTiw3+l+TCp7HBBM8+NUzjWT03lSmdFxD+pKiOyJQTqQBBbCBkyDT3KkDEXCrEGohwkmdAckE31cdNu9rhQvyF+nwe4Ww5h/yPPrlJNJYH4aV58GX0oOHTbXdj1KIQSZ7tZYXqvJM/G6Z8CzjmUb192fmQPjDHy1P5Zh/VRTZuJ1zoD1rMeBx/RKeWZmyv89A2V5SFL3LXSVNOuvewY+Mvbgf+qq3TZRfHcjAAAAAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\left(- 0.5 {{img}_{(-1,-1)}^{2}} - {{img}_{(-1,0)}^{2}} w_{2} - 0.5 {{img}_{(-1,1)}^{2}} + 0.5 {{img}_{(1,-1)}^{2}} + {{img}_{(1,0)}^{2}} w_{2} - 0.5 {{img}_{(1,1)}^{2}}\\right)^{2}$$"
+      ],
+      "text/plain": [
+       "                                                                              \n",
+       "(-0.5â‹…img_SW__2 - img_W__2â‹…wâ‚‚ - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 + img_E__2â‹…wâ‚‚ - \n",
+       "\n",
+       "              2\n",
+       "0.5â‹…img_NE__2) "
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sobel_x = sobel_x.subs(w1, 0.5)\n",
+    "sobel_x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now lets built an executable kernel out of it, which writes the result to a second field. Assignments are created using *pystencils* `Assignment` class, that gets the left- and right hand side of the assignment."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$${{dst}_{(0,0)}} \\leftarrow \\left(- 0.5 {{img}_{(-1,-1)}^{2}} - {{img}_{(-1,0)}^{2}} w_{2} - 0.5 {{img}_{(-1,1)}^{2}} + 0.5 {{img}_{(1,-1)}^{2}} + {{img}_{(1,0)}^{2}} w_{2} - 0.5 {{img}_{(1,1)}^{2}}\\right)^{2}$$"
+      ],
+      "text/plain": [
+       "                                                                              \n",
+       "dst_C := (-0.5â‹…img_SW__2 - img_W__2â‹…wâ‚‚ - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 + img_E\n",
+       "\n",
+       "                       2\n",
+       "__2â‹…wâ‚‚ - 0.5â‹…img_NE__2) "
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dst_field = ps.fields('dst: [2D]' )\n",
+    "update_rule = ps.Assignment(dst_field[0,0], sobel_x)\n",
+    "update_rule"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next we can see *pystencils* in action which creates a kernel for us."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils import create_kernel\n",
+    "ast = create_kernel(update_rule, cpu_openmp=False)\n",
+    "compiled_kernel = ast.compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This compiled kernel is now just an ordinary Python function. \n",
+    "Now lets grab an image to apply this filter to:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import requests\n",
+    "import imageio\n",
+    "from io import BytesIO\n",
+    "\n",
+    "response = requests.get(\"https://www.python.org/static/img/python-logo.png\")\n",
+    "img = imageio.imread(BytesIO(response.content)).astype(np.double)\n",
+    "img /= img.max()\n",
+    "plt.imshow(img);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "filtered_image = np.zeros_like(img[..., 0])\n",
+    "# here we call the compiled stencil function\n",
+    "compiled_kernel(img=img, dst=filtered_image, w_2=0.5)\n",
+    "plt.imshow(filtered_image, cmap='gray');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Digging into *pystencils*\n",
+    "\n",
+    "On our way we have created an ``ast``-object. We can inspect this, to see what *pystencils* actually does."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/svg+xml": [
+       "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
+       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
+       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
+       "<!-- Generated by graphviz version 2.38.0 (20140413.2041)\n",
+       " -->\n",
+       "<!-- Title: %3 Pages: 1 -->\n",
+       "<svg width=\"684pt\" height=\"228pt\"\n",
+       " viewBox=\"0.00 0.00 684.00 227.95\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
+       "<g id=\"graph0\" class=\"graph\" transform=\"scale(0.478879 0.478879) rotate(0) translate(4 472)\">\n",
+       "<title>%3</title>\n",
+       "<polygon fill=\"white\" stroke=\"none\" points=\"-4,4 -4,-472 1424.34,-472 1424.34,4 -4,4\"/>\n",
+       "<!-- 140128518376696 -->\n",
+       "<g id=\"node1\" class=\"node\"><title>140128518376696</title>\n",
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+       "<text text-anchor=\"middle\" x=\"548.645\" y=\"-446.3\" font-family=\"Times,serif\" font-size=\"14.00\">Func: kernel (dst,img,w_2)</text>\n",
+       "</g>\n",
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+       "<g id=\"node18\" class=\"node\"><title>140128518374232</title>\n",
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+       "<text text-anchor=\"middle\" x=\"548.645\" y=\"-374.3\" font-family=\"Times,serif\" font-size=\"14.00\">Block</text>\n",
+       "</g>\n",
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+       "<g id=\"edge17\" class=\"edge\"><title>140128518376696&#45;&gt;140128518374232</title>\n",
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+       "<text text-anchor=\"middle\" x=\"52.6453\" y=\"-302.3\" font-family=\"Times,serif\" font-size=\"14.00\">fshape_dst0</text>\n",
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+       "<g id=\"node3\" class=\"node\"><title>140128518531728</title>\n",
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+       "<text text-anchor=\"middle\" x=\"175.645\" y=\"-302.3\" font-family=\"Times,serif\" font-size=\"14.00\">fshape_dst1</text>\n",
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+    "*pystencils* also builds a tree structure of the program, where each `Assignment` node internally again has a *sympy* AST which is not printed here. Out of this representation *C* code can be generated:"
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+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fshape_dst0</span> <span class=\"o\">=</span> <span class=\"n\">fshape_dst</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">];</span>\n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fshape_dst1</span> <span class=\"o\">=</span> <span class=\"n\">fshape_dst</span><span class=\"p\">[</span><span class=\"mi\">1</span><span class=\"p\">];</span>\n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_dst0</span> <span class=\"o\">=</span> <span class=\"n\">fstride_dst</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">];</span>\n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_img2</span> <span class=\"o\">=</span> <span class=\"n\">fstride_img</span><span class=\"p\">[</span><span class=\"mi\">2</span><span class=\"p\">];</span>\n",
+       "   <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_img_22</span> <span class=\"o\">=</span> <span class=\"n\">fd_img</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">fstride_img2</span><span class=\"p\">;</span>\n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_img0</span> <span class=\"o\">=</span> <span class=\"n\">fstride_img</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">];</span>\n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_img1</span> <span class=\"o\">=</span> <span class=\"n\">fstride_img</span><span class=\"p\">[</span><span class=\"mi\">1</span><span class=\"p\">];</span>\n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_dst1</span> <span class=\"o\">=</span> <span class=\"n\">fstride_dst</span><span class=\"p\">[</span><span class=\"mi\">1</span><span class=\"p\">];</span>\n",
+       "   <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">&lt;</span> <span class=\"n\">fshape_dst0</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">fd_dst_00</span> <span class=\"o\">=</span> <span class=\"n\">ctr_0</span><span class=\"o\">*</span><span class=\"n\">fstride_dst0</span> <span class=\"o\">+</span> <span class=\"n\">fd_dst</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_img_22_01</span> <span class=\"o\">=</span> <span class=\"n\">ctr_0</span><span class=\"o\">*</span><span class=\"n\">fstride_img0</span> <span class=\"o\">+</span> <span class=\"n\">fd_img_22</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_img_22_0m1</span> <span class=\"o\">=</span> <span class=\"n\">ctr_0</span><span class=\"o\">*</span><span class=\"n\">fstride_img0</span> <span class=\"o\">+</span> <span class=\"n\">fd_img_22</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">&lt;</span> <span class=\"n\">fshape_dst1</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "      <span class=\"p\">{</span>\n",
+       "         <span class=\"n\">fd_dst_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_dst1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"p\">((</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img1</span><span class=\"p\">])</span><span class=\"o\">*</span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]));</span>\n",
+       "      <span class=\"p\">}</span>\n",
+       "   <span class=\"p\">}</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * fd_dst, double * const fd_img, int64_t const * fshape_dst, int64_t const * fstride_dst, int64_t const * fstride_img, double w_2)\n",
+       "{\n",
+       "   const int64_t fshape_dst0 = fshape_dst[0];\n",
+       "   const int64_t fshape_dst1 = fshape_dst[1];\n",
+       "   const int64_t fstride_dst0 = fstride_dst[0];\n",
+       "   const int64_t fstride_img2 = fstride_img[2];\n",
+       "   double * const fd_img_22 = fd_img + 2*fstride_img2;\n",
+       "   const int64_t fstride_img0 = fstride_img[0];\n",
+       "   const int64_t fstride_img1 = fstride_img[1];\n",
+       "   const int64_t fstride_dst1 = fstride_dst[1];\n",
+       "   for (int ctr_0 = 1; ctr_0 < fshape_dst0 - 1; ctr_0 += 1)\n",
+       "   {\n",
+       "      double * fd_dst_00 = ctr_0*fstride_dst0 + fd_dst;\n",
+       "      double * const fd_img_22_01 = ctr_0*fstride_img0 + fd_img_22 + fstride_img0;\n",
+       "      double * const fd_img_22_0m1 = ctr_0*fstride_img0 + fd_img_22 - fstride_img0;\n",
+       "      for (int ctr_1 = 1; ctr_1 < fshape_dst1 - 1; ctr_1 += 1)\n",
+       "      {\n",
+       "         fd_dst_00[ctr_1*fstride_dst1] = ((w_2*fd_img_22_01[ctr_1*fstride_img1] - w_2*fd_img_22_0m1[ctr_1*fstride_img1] - 0.5*fd_img_22_01[ctr_1*fstride_img1 + fstride_img1] - 0.5*fd_img_22_0m1[ctr_1*fstride_img1 + fstride_img1] - 0.5*fd_img_22_0m1[ctr_1*fstride_img1 - fstride_img1] + 0.5*fd_img_22_01[ctr_1*fstride_img1 - fstride_img1])*(w_2*fd_img_22_01[ctr_1*fstride_img1] - w_2*fd_img_22_0m1[ctr_1*fstride_img1] - 0.5*fd_img_22_01[ctr_1*fstride_img1 + fstride_img1] - 0.5*fd_img_22_0m1[ctr_1*fstride_img1 + fstride_img1] - 0.5*fd_img_22_0m1[ctr_1*fstride_img1 - fstride_img1] + 0.5*fd_img_22_01[ctr_1*fstride_img1 - fstride_img1]));\n",
+       "      }\n",
+       "   }\n",
+       "}"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ps.show_code(ast)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Behind the scenes this code is compiled into a shared library and made available as a Python function. Before compiling this function we can modify the AST object, for example to parallelize it with OpenMP."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "<IPython.core.display.HTML object>"
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+    {
+     "data": {
+      "text/html": [
+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">fd_dst</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_img</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"o\">*</span> <span class=\"n\">fshape_dst</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"o\">*</span> <span class=\"n\">fstride_dst</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"o\">*</span> <span class=\"n\">fstride_img</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"n\">w_2</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"cp\">#pragma omp parallel num_threads(2)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fshape_dst0</span> <span class=\"o\">=</span> <span class=\"n\">fshape_dst</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">];</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fshape_dst1</span> <span class=\"o\">=</span> <span class=\"n\">fshape_dst</span><span class=\"p\">[</span><span class=\"mi\">1</span><span class=\"p\">];</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_dst0</span> <span class=\"o\">=</span> <span class=\"n\">fstride_dst</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">];</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_img2</span> <span class=\"o\">=</span> <span class=\"n\">fstride_img</span><span class=\"p\">[</span><span class=\"mi\">2</span><span class=\"p\">];</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_img_22</span> <span class=\"o\">=</span> <span class=\"n\">fd_img</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">fstride_img2</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_img0</span> <span class=\"o\">=</span> <span class=\"n\">fstride_img</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">];</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_img1</span> <span class=\"o\">=</span> <span class=\"n\">fstride_img</span><span class=\"p\">[</span><span class=\"mi\">1</span><span class=\"p\">];</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">fstride_dst1</span> <span class=\"o\">=</span> <span class=\"n\">fstride_dst</span><span class=\"p\">[</span><span class=\"mi\">1</span><span class=\"p\">];</span>\n",
+       "      <span class=\"cp\">#pragma omp for schedule(static)</span>\n",
+       "      <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">&lt;</span> <span class=\"n\">fshape_dst0</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "      <span class=\"p\">{</span>\n",
+       "         <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">fd_dst_00</span> <span class=\"o\">=</span> <span class=\"n\">ctr_0</span><span class=\"o\">*</span><span class=\"n\">fstride_dst0</span> <span class=\"o\">+</span> <span class=\"n\">fd_dst</span><span class=\"p\">;</span>\n",
+       "         <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_img_22_01</span> <span class=\"o\">=</span> <span class=\"n\">ctr_0</span><span class=\"o\">*</span><span class=\"n\">fstride_img0</span> <span class=\"o\">+</span> <span class=\"n\">fd_img_22</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img0</span><span class=\"p\">;</span>\n",
+       "         <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_img_22_0m1</span> <span class=\"o\">=</span> <span class=\"n\">ctr_0</span><span class=\"o\">*</span><span class=\"n\">fstride_img0</span> <span class=\"o\">+</span> <span class=\"n\">fd_img_22</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img0</span><span class=\"p\">;</span>\n",
+       "         <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">&lt;</span> <span class=\"n\">fshape_dst1</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "         <span class=\"p\">{</span>\n",
+       "            <span class=\"n\">fd_dst_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_dst1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"p\">((</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img1</span><span class=\"p\">])</span><span class=\"o\">*</span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">+</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">fd_img_22_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"o\">*</span><span class=\"n\">fstride_img1</span> <span class=\"o\">-</span> <span class=\"n\">fstride_img1</span><span class=\"p\">]));</span>\n",
+       "         <span class=\"p\">}</span>\n",
+       "      <span class=\"p\">}</span>\n",
+       "   <span class=\"p\">}</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * fd_dst, double * const fd_img, int64_t const * fshape_dst, int64_t const * fstride_dst, int64_t const * fstride_img, double w_2)\n",
+       "{\n",
+       "   #pragma omp parallel num_threads(2)\n",
+       "   {\n",
+       "      const int64_t fshape_dst0 = fshape_dst[0];\n",
+       "      const int64_t fshape_dst1 = fshape_dst[1];\n",
+       "      const int64_t fstride_dst0 = fstride_dst[0];\n",
+       "      const int64_t fstride_img2 = fstride_img[2];\n",
+       "      double * const fd_img_22 = fd_img + 2*fstride_img2;\n",
+       "      const int64_t fstride_img0 = fstride_img[0];\n",
+       "      const int64_t fstride_img1 = fstride_img[1];\n",
+       "      const int64_t fstride_dst1 = fstride_dst[1];\n",
+       "      #pragma omp for schedule(static)\n",
+       "      for (int ctr_0 = 1; ctr_0 < fshape_dst0 - 1; ctr_0 += 1)\n",
+       "      {\n",
+       "         double * fd_dst_00 = ctr_0*fstride_dst0 + fd_dst;\n",
+       "         double * const fd_img_22_01 = ctr_0*fstride_img0 + fd_img_22 + fstride_img0;\n",
+       "         double * const fd_img_22_0m1 = ctr_0*fstride_img0 + fd_img_22 - fstride_img0;\n",
+       "         for (int ctr_1 = 1; ctr_1 < fshape_dst1 - 1; ctr_1 += 1)\n",
+       "         {\n",
+       "            fd_dst_00[ctr_1*fstride_dst1] = ((w_2*fd_img_22_01[ctr_1*fstride_img1] - w_2*fd_img_22_0m1[ctr_1*fstride_img1] - 0.5*fd_img_22_01[ctr_1*fstride_img1 + fstride_img1] - 0.5*fd_img_22_0m1[ctr_1*fstride_img1 + fstride_img1] - 0.5*fd_img_22_0m1[ctr_1*fstride_img1 - fstride_img1] + 0.5*fd_img_22_01[ctr_1*fstride_img1 - fstride_img1])*(w_2*fd_img_22_01[ctr_1*fstride_img1] - w_2*fd_img_22_0m1[ctr_1*fstride_img1] - 0.5*fd_img_22_01[ctr_1*fstride_img1 + fstride_img1] - 0.5*fd_img_22_0m1[ctr_1*fstride_img1 + fstride_img1] - 0.5*fd_img_22_0m1[ctr_1*fstride_img1 - fstride_img1] + 0.5*fd_img_22_01[ctr_1*fstride_img1 - fstride_img1]));\n",
+       "         }\n",
+       "      }\n",
+       "   }\n",
+       "}"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ast = ps.create_kernel(update_rule)\n",
+    "ps.cpu.add_openmp(ast, num_threads=2)\n",
+    "ps.show_code(ast)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "loops = list(ast.atoms(ps.astnodes.LoopOverCoordinate))\n",
+    "l1 = loops[0]\n",
+    "l1.prefix_lines.append(\"#pragma someting\")\n",
+    "l1.is_outermost_loop"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Fixed array sizes\n",
+    "\n",
+    "Since we already know the arrays to which the kernel should be applied, we can \n",
+    "create *Field* objects with fixed size, based on a numpy array:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+    },
+    {
+     "data": {
+      "text/html": [
+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_I</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">fd_dst</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_I_21</span> <span class=\"o\">=</span> <span class=\"n\">fd_I</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+       "   <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">&lt;</span> <span class=\"mi\">81</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">fd_dst_00</span> <span class=\"o\">=</span> <span class=\"mi\">290</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">fd_dst</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_I_21_01</span> <span class=\"o\">=</span> <span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">fd_I_21</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_I_21_0m1</span> <span class=\"o\">=</span> <span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">fd_I_21</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">&lt;</span> <span class=\"mi\">289</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "      <span class=\"p\">{</span>\n",
+       "         <span class=\"n\">fd_dst_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"o\">-</span><span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">fd_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">fd_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">fd_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"n\">fd_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">4</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">fd_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">fd_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">4</span><span class=\"p\">];</span>\n",
+       "      <span class=\"p\">}</span>\n",
+       "   <span class=\"p\">}</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * const fd_I, double * fd_dst)\n",
+       "{\n",
+       "   double * const fd_I_21 = fd_I + 1;\n",
+       "   for (int ctr_0 = 1; ctr_0 < 81; ctr_0 += 1)\n",
+       "   {\n",
+       "      double * fd_dst_00 = 290*ctr_0 + fd_dst;\n",
+       "      double * const fd_I_21_01 = 1160*ctr_0 + fd_I_21 + 1160;\n",
+       "      double * const fd_I_21_0m1 = 1160*ctr_0 + fd_I_21 - 1160;\n",
+       "      for (int ctr_1 = 1; ctr_1 < 289; ctr_1 += 1)\n",
+       "      {\n",
+       "         fd_dst_00[ctr_1] = -2*fd_I_21_0m1[4*ctr_1] + 2*fd_I_21_01[4*ctr_1] - fd_I_21_01[4*ctr_1 + 4] + fd_I_21_01[4*ctr_1 - 4] - fd_I_21_0m1[4*ctr_1 + 4] - fd_I_21_0m1[4*ctr_1 - 4];\n",
+       "      }\n",
+       "   }\n",
+       "}"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "img_field = ps.Field.create_from_numpy_array('I', img.astype(np.double), index_dimensions=1)\n",
+    "dst_field = ps.Field.create_from_numpy_array('dst', filtered_image, index_dimensions=0)\n",
+    "\n",
+    "sobel_x = -2 * img_field[-1,0](1) - img_field[-1,-1](1) - img_field[-1, +1](1) \\\n",
+    "         +2 * img_field[+1,0](1) + img_field[+1,-1](1) - img_field[+1, +1](1)\n",
+    "update_rule = ps.Assignment(dst_field[0,0], sobel_x)\n",
+    "\n",
+    "ast = create_kernel([update_rule])\n",
+    "ps.show_code(ast)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Compare this code to the version above. In this code the loop bounds and array offsets are constants, which usually leads to faster kernels."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Running on GPU\n",
+    "\n",
+    "If you have a CUDA enabled graphics card and [pycuda](https://mathema.tician.de/software/pycuda/) installed, *pystencils* can run your kernel on the GPU as well. You can find more details about this in the GPU tutorial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gpu_ast = create_kernel([update_rule], target='gpu', gpu_indexing=ps.gpucuda.indexing.BlockIndexing, \n",
+    "                        gpu_indexing_params={'blockSize': (8,8,4)})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
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+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_I</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">fd_dst</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"k\">if</span> <span class=\"p\">(</span><span class=\"mi\">16</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"mi\">1</span> <span class=\"o\">&lt;</span> <span class=\"mi\">81</span> <span class=\"o\">&amp;&amp;</span> <span class=\"mi\">16</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"mi\">1</span> <span class=\"o\">&lt;</span> <span class=\"mi\">289</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">16</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">16</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">fd_dst_10</span> <span class=\"o\">=</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">fd_dst</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_I_11_21</span> <span class=\"o\">=</span> <span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">fd_I</span> <span class=\"o\">+</span> <span class=\"mi\">5</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_I_1m1_21</span> <span class=\"o\">=</span> <span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">fd_I</span> <span class=\"o\">-</span> <span class=\"mi\">3</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">fd_I_10_21</span> <span class=\"o\">=</span> <span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">fd_I</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"n\">fd_dst_10</span><span class=\"p\">[</span><span class=\"mi\">290</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"o\">-</span><span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">fd_I_10_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">fd_I_10_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">fd_I_11_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">fd_I_11_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"n\">fd_I_1m1_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">fd_I_1m1_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">];</span>\n",
+       "   <span class=\"p\">}</span> \n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * const fd_I, double * fd_dst)\n",
+       "{\n",
+       "   if (16*blockIdx.x + threadIdx.x + 1 < 81 && 16*blockIdx.y + threadIdx.y + 1 < 289)\n",
+       "   {\n",
+       "      const int64_t ctr_0 = 16*blockIdx.x + threadIdx.x + 1;\n",
+       "      const int64_t ctr_1 = 16*blockIdx.y + threadIdx.y + 1;\n",
+       "      double * fd_dst_10 = ctr_1 + fd_dst;\n",
+       "      double * const fd_I_11_21 = 4*ctr_1 + fd_I + 5;\n",
+       "      double * const fd_I_1m1_21 = 4*ctr_1 + fd_I - 3;\n",
+       "      double * const fd_I_10_21 = 4*ctr_1 + fd_I + 1;\n",
+       "      fd_dst_10[290*ctr_0] = -2*fd_I_10_21[1160*ctr_0 - 1160] + 2*fd_I_10_21[1160*ctr_0 + 1160] - fd_I_11_21[1160*ctr_0 + 1160] - fd_I_11_21[1160*ctr_0 - 1160] + fd_I_1m1_21[1160*ctr_0 + 1160] - fd_I_1m1_21[1160*ctr_0 - 1160];\n",
+       "   } \n",
+       "}"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ps.show_code(gpu_ast)"
+   ]
+  }
+ ],
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+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/02_tutorial_basic_kernels.ipynb b/doc/notebooks/02_tutorial_basic_kernels.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..400d1143e4d710cfaa295c1cf5e112db0be4ad4d
--- /dev/null
+++ b/doc/notebooks/02_tutorial_basic_kernels.ipynb
@@ -0,0 +1,744 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 02: Basic Kernel generation with *pystencils*\n",
+    "\n",
+    "Now that you have an [overview of pystencils](01_tutorial_getting_started.ipynb), \n",
+    "this tutorial shows in more detail how to formulate, optimize and run stencil kernels.\n",
+    "\n",
+    "## 1) Kernel Definition\n",
+    "\n",
+    "### a) Defining kernels with assignment lists and the  `kernel` decorator \n",
+    "\n",
+    "*pystencils* gets a symbolic formulation of the kernel. This can be either an `Assignment` or a sequence of `Assignment`s that follow a set of restrictions. \n",
+    "\n",
+    "Lets first create a kernel that consists of multiple assignments:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "src_arr = np.zeros([20, 30])\n",
+    "dst_arr = np.zeros_like(src_arr)\n",
+    "\n",
+    "dst, src = ps.fields(dst=dst_arr, src=src_arr)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\left [ grad_{x} \\leftarrow \\frac{{{src}_{E}}}{2} - \\frac{{{src}_{W}}}{2}, \\quad grad_{y} \\leftarrow \\frac{{{src}_{N}}}{2} - \\frac{{{src}_{S}}}{2}, \\quad {{dst}_{C}} \\leftarrow grad_{x} + grad_{y}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡         src_E   src_W            src_N   src_S                         ⎤\n",
+       "⎢gradₓ := ───── - ─────, grad_y := ───── - ─────, dst_C := gradₓ + grad_y⎥\n",
+       "⎣           2       2                2       2                           ⎦"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "grad_x, grad_y = sp.symbols(\"grad_x, grad_y\")\n",
+    "\n",
+    "symbolic_description = [\n",
+    "    ps.Assignment(grad_x, (src[1, 0] - src[-1, 0]) / 2),\n",
+    "    ps.Assignment(grad_y, (src[0, 1] - src[0, -1]) / 2),\n",
+    "    ps.Assignment(dst[0, 0], grad_x + grad_y),\n",
+    "]\n",
+    "kernel = ps.create_kernel(symbolic_description)\n",
+    "symbolic_description"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We created subexpressions, using standard sympy symbols on the left hand side, to split the kernel into multiple assignments. Defining a kernel using a list of `Assignment`s is quite tedious and hard to read. \n",
+    "To simplify the formulation of a kernel, *pystencils* offers the `kernel` decorator, that transforms a normal Python function with `@=` assignments into an assignment list that can be passed to `create_kernel`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\left [ grad_{x} \\leftarrow \\frac{{{src}_{E}}}{2} - \\frac{{{src}_{W}}}{2}, \\quad grad_{y} \\leftarrow \\frac{{{src}_{N}}}{2} - \\frac{{{src}_{S}}}{2}, \\quad {{dst}_{C}} \\leftarrow grad_{x} + grad_{y}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡         src_E   src_W            src_N   src_S                         ⎤\n",
+       "⎢gradₓ := ───── - ─────, grad_y := ───── - ─────, dst_C := gradₓ + grad_y⎥\n",
+       "⎣           2       2                2       2                           ⎦"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@ps.kernel\n",
+    "def symbolic_description_using_function():\n",
+    "    grad_x @= (src[1, 0] - src[-1, 0]) / 2\n",
+    "    grad_y @= (src[0, 1] - src[0, -1]) / 2\n",
+    "    dst[0, 0] @= grad_x + grad_y\n",
+    "symbolic_description_using_function"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The decorated function can contain any Python code, only the `@=` operator, and the ternary inline `if-else` operator have different meaning. \n",
+    "\n",
+    "### b) Ternary 'if' with `Piecewise`\n",
+    "\n",
+    "The ternary operator maps to `sympy.Piecewise` functions, that can be used to introduce branching into the kernel. Piecewise defined functions must give a value for every input, i.e. there must be a 'otherwise' clause in the end that is indicated by the condition `True`. Piecewise objects are standard sympy terms that can be integrated into bigger expressions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$${{src}_{E}} + \\begin{cases} 1.0 & \\text{for}\\: {{src}_{N}} > 0 \\\\0.0 & \\text{otherwise} \\end{cases}$$"
+      ],
+      "text/plain": [
+       "        ⎛⎧1.0  for src_N > 0⎞\n",
+       "src_E + ⎜⎨                  ⎟\n",
+       "        ⎝⎩0.0    otherwise  ⎠"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sp.Piecewise((1.0, src[0,1] > 0), (0.0, True)) + src[1, 0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Piecewise objects are created by the `kernel` decorator for ternary if-else statements."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\left [ grad_{x} \\leftarrow \\begin{cases} \\frac{{{src}_{E}}}{2} - \\frac{{{src}_{W}}}{2} & \\text{for}\\: {{src}_{W}} > 0 \\\\0.0 & \\text{otherwise} \\end{cases}\\right ]$$"
+      ],
+      "text/plain": [
+       "⎡         ⎧src_E   src_W               ⎤\n",
+       "⎢         ⎪───── - ─────  for src_W > 0⎥\n",
+       "⎢gradₓ := ⎨  2       2                 ⎥\n",
+       "⎢         ⎪                            ⎥\n",
+       "⎣         ⎩     0.0         otherwise  ⎦"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@ps.kernel\n",
+    "def kernel_with_piecewise():\n",
+    "    grad_x @= (src[1, 0] - src[-1, 0]) / 2 if src[-1, 0] > 0 else 0.0\n",
+    "kernel_with_piecewise"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### c) Assignment level optimizations using `AssignmentCollection`\n",
+    "\n",
+    "When the kernels get larger and more complex, it is helpful to organize the list of assignment into a more structured way. The `AssignmentCollection` offers optimizating transformation on a list of assignments. It holds two assignment lists, one for subexpressions and one for the main assignments. Main assignments are typically those that write to an array."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>Subexpressions:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$$a \\leftarrow {{src}_{N}} + {{src}_{W}}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$b \\leftarrow 2 {{src}_{E}} + {{src}_{S}}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$c \\leftarrow - {{src}_{C}} + 2 {{src}_{E}} + {{src}_{N}} + {{src}_{S}} + {{src}_{W}}$$</td>  </tr> </table><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{dst}_{C}} \\leftarrow a + b + c$$</td>  </tr> </table>"
+      ],
+      "text/plain": [
+       "Equation Collection for dst_C"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@ps.kernel\n",
+    "def somewhat_longer_dummy_kernel(s):\n",
+    "    s.a @= src[0, 1] + src[-1, 0]\n",
+    "    s.b @= 2 * src[1, 0] + src[0, -1]\n",
+    "    s.c @= src[0, 1] + 2 * src[1, 0] + src[-1, 0] + src[0, -1] - src[0,0]\n",
+    "    dst[0, 0] @= s.a + s.b + s.c\n",
+    "    \n",
+    "ac = ps.AssignmentCollection(main_assignments=somewhat_longer_dummy_kernel[-1:], \n",
+    "                             subexpressions=somewhat_longer_dummy_kernel[:-1])\n",
+    "ac"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'adds': 8, 'muls': 2, 'divs': 0}"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ac.operation_count"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `pystencils.simp` submodule offers several functions to optimize a collection of assignments.\n",
+    "It also offers functionality to group optimization into strategies and evaluate them. \n",
+    "In this example we reduce the number of operations by reusing existing subexpressions to get rid of two unnecessary floating point additions. For more information about assignment collections and simplifications see the [demo notebook](demo_assignment_collection.ipynb)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>Subexpressions:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$$a \\leftarrow {{src}_{N}} + {{src}_{W}}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$b \\leftarrow 2 {{src}_{E}} + {{src}_{S}}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$c \\leftarrow - {{src}_{C}} + a + b$$</td>  </tr> </table><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{dst}_{C}} \\leftarrow a + b + c$$</td>  </tr> </table>"
+      ],
+      "text/plain": [
+       "Equation Collection for dst_C"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "opt_ac = ps.simp.subexpression_substitution_in_existing_subexpressions(ac)\n",
+    "opt_ac"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'adds': 6, 'muls': 1, 'divs': 0}"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "opt_ac.operation_count"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### d) Ghost layers and iteration region\n",
+    "\n",
+    "When creating a kernel with neighbor accesses, *pystencils* automatically restricts the iteration region, such that all accesses are safe. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
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+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">fd_dst</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">fd_src</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">2</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">&lt;</span> <span class=\"mi\">18</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">fd_dst_C</span> <span class=\"o\">=</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">fd_dst</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">fd_src_2E</span> <span class=\"o\">=</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">fd_src</span> <span class=\"o\">+</span> <span class=\"mi\">60</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">fd_src_W</span> <span class=\"o\">=</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">fd_src</span> <span class=\"o\">-</span> <span class=\"mi\">30</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">2</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">&lt;</span> <span class=\"mi\">28</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "      <span class=\"p\">{</span>\n",
+       "         <span class=\"n\">fd_dst_C</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"n\">fd_src_2E</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"n\">fd_src_W</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">];</span>\n",
+       "      <span class=\"p\">}</span>\n",
+       "   <span class=\"p\">}</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * RESTRICT fd_dst, double * RESTRICT const fd_src)\n",
+       "{\n",
+       "   for (int ctr_0 = 2; ctr_0 < 18; ctr_0 += 1)\n",
+       "   {\n",
+       "      double * RESTRICT fd_dst_C = 30*ctr_0 + fd_dst;\n",
+       "      double * RESTRICT const fd_src_2E = 30*ctr_0 + fd_src + 60;\n",
+       "      double * RESTRICT const fd_src_W = 30*ctr_0 + fd_src - 30;\n",
+       "      for (int ctr_1 = 2; ctr_1 < 28; ctr_1 += 1)\n",
+       "      {\n",
+       "         fd_dst_C[ctr_1] = fd_src_2E[ctr_1] + fd_src_W[ctr_1];\n",
+       "      }\n",
+       "   }\n",
+       "}"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "kernel = ps.create_kernel(ps.Assignment(dst[0,0], src[2, 0] + src[-1, 0]))\n",
+    "ps.show_code(kernel)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When no additional ghost layer information is given, *pystencils* looks at all neighboring field accesses and introduces the required number of ghost layers **for all directions**. In the example above the largest neighbor accesses was ``src[2, 0]``, so theoretically we would need 2 ghost layers only the the end of the x coordinate. \n",
+    "By default *pystencils* introduces 2 ghost layers at all borders of the domain. The next cell shows how to change this behavior. Be careful with manual ghost layer specification, wrong values may lead to SEGFAULTs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
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+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">fd_dst</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">fd_src</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">0</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">&lt;</span> <span class=\"mi\">18</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">fd_dst_C</span> <span class=\"o\">=</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">fd_dst</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">fd_src_2E</span> <span class=\"o\">=</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">fd_src</span> <span class=\"o\">+</span> <span class=\"mi\">60</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">fd_src_W</span> <span class=\"o\">=</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">fd_src</span> <span class=\"o\">-</span> <span class=\"mi\">30</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">&lt;</span> <span class=\"mi\">30</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "      <span class=\"p\">{</span>\n",
+       "         <span class=\"n\">fd_dst_C</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"n\">fd_src_2E</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"n\">fd_src_W</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">];</span>\n",
+       "      <span class=\"p\">}</span>\n",
+       "   <span class=\"p\">}</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * RESTRICT fd_dst, double * RESTRICT const fd_src)\n",
+       "{\n",
+       "   for (int ctr_0 = 0; ctr_0 < 18; ctr_0 += 1)\n",
+       "   {\n",
+       "      double * RESTRICT fd_dst_C = 30*ctr_0 + fd_dst;\n",
+       "      double * RESTRICT const fd_src_2E = 30*ctr_0 + fd_src + 60;\n",
+       "      double * RESTRICT const fd_src_W = 30*ctr_0 + fd_src - 30;\n",
+       "      for (int ctr_1 = 1; ctr_1 < 30; ctr_1 += 1)\n",
+       "      {\n",
+       "         fd_dst_C[ctr_1] = fd_src_2E[ctr_1] + fd_src_W[ctr_1];\n",
+       "      }\n",
+       "   }\n",
+       "}"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gl_spec = [(0, 2),   # 0 ghost layers at the left, 2 at the right border\n",
+    "           (1, 0)]   # 1 ghost layer at the lower y, one at the upper y coordinate\n",
+    "kernel = ps.create_kernel(ps.Assignment(dst[0,0], src[2, 0] + src[-1, 0]), ghost_layers=gl_spec)\n",
+    "ps.show_code(kernel)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2 ) Restrictions\n",
+    "\n",
+    "\n",
+    "### a) Independence Restriction\n",
+    "\n",
+    "*pystencils* only works for kernels where each array element can be updated independently from all other elements. This restriction ensures that the kernels can be easily parallelized and also be run on the GPU. Trying to define kernels where the results depends on the iteration order, leads to a ValueError."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Field dst is written at two different locations\n"
+     ]
+    }
+   ],
+   "source": [
+    "invalid_description = [\n",
+    "    ps.Assignment(dst[1, 0], src[1, 0] + src[-1, 0]),\n",
+    "    ps.Assignment(dst[0, 0], src[1, 0] - src[-1, 0]),\n",
+    "]\n",
+    "try:\n",
+    "    invalid_kernel = ps.create_kernel(invalid_description)\n",
+    "    assert False, \"Should never be executed\"\n",
+    "except ValueError as e:\n",
+    "    print(e)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The independence restriction makes sure that the kernel can be safely parallelized by checking the following conditions: If a field is modified inside the kernel, it may only be modified at a single spatial position. In that case the field may also only be read at this position. Fields that are not modified may be read at multiple neighboring positions.\n",
+    "\n",
+    "Specifically, this rule allows for in-place updates that don't access neighbors."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "valid_kernel = ps.create_kernel(ps.Assignment(src[0,0], 2*src[0,0] + 42))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If a field stores multiple values per cell, as in the next example, this restriction only applies for accesses with the same index."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "v = ps.fields(\"v(2): double[2D]\")\n",
+    "valid_kernel = ps.create_kernel([ps.Assignment(v[0,0](1), 2*v[0,0](1) + 42),\n",
+    "                                 ps.Assignment(v[0,1](0), 2*v[1,0](0) + 42)])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### b) Static Single Assignment Form\n",
+    "\n",
+    "All assignments that don't write to a field must be in SSA form\n",
+    "1. Each sympy symbol may only occur once as a left-hand-side (fields can be written multiple times)\n",
+    "2. A symbol has to be defined before it is used. If it is never defined it is introduced as function parameter\n",
+    "\n",
+    "The next cell demonstrates the first SSA restriction:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Assignments not in SSA form, multiple assignments to a\n"
+     ]
+    }
+   ],
+   "source": [
+    "@ps.kernel\n",
+    "def not_allowed():\n",
+    "    a, b = sp.symbols(\"a b\")\n",
+    "    a @= src[0, 0]\n",
+    "    b @= a + 3\n",
+    "    a @= src[-1, 0]\n",
+    "    dst[0, 0] @= a + b\n",
+    "try:\n",
+    "    ps.create_kernel(not_allowed)\n",
+    "    assert False\n",
+    "except ValueError as e:\n",
+    "    print(e)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "However, for right hand sides that are Field.Accesses this is allowed:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "KernelFunction kernel([<double * RESTRICT fd_dst>, <double * RESTRICT const fd_src>])"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@ps.kernel\n",
+    "def allowed():\n",
+    "    dst[0, 0] @= src[0, 1] + src[1, 0]\n",
+    "    dst[0, 0] @= 2 * dst[0, 0]\n",
+    "ps.create_kernel(allowed)"
+   ]
+  }
+ ],
+ "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_advection_diffusion.ipynb b/doc/notebooks/03_tutorial_advection_diffusion.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e3f394266226d83590b93f680904540d6e1862e6
--- /dev/null
+++ b/doc/notebooks/03_tutorial_advection_diffusion.ipynb
@@ -0,0 +1,209 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 03: Advection Diffusion - Simple finite differences discretization\n",
+    "\n",
+    "In this tutorial we demonstrate how to use the discretization layer on top of *pystencils*, that defines how continuous differential operators are discretized. The result of this discretization layer are stencil equations which are used to generated C or CUDA code.\n",
+    "\n",
+    "We are going to discretize the [advection diffusion equation](https://en.wikipedia.org/wiki/Convection%E2%80%93diffusion_equation) without reaction terms:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\nabla \\cdot(v c) - div(D \\nabla c) + \\partial_t c_{C}$$"
+      ],
+      "text/plain": [
+       "Advection(c_C, v_C__0) - Diffusion(c_C, D) + Transient(c_C)"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "domain_size = (200, 80)\n",
+    "dim = len(domain_size)\n",
+    "\n",
+    "# create arrays\n",
+    "c_arr = np.zeros(domain_size)\n",
+    "v_arr = np.zeros(domain_size + (dim,))\n",
+    "\n",
+    "# create fields\n",
+    "c, v, c_next = ps.fields(\"c, v(2), c_next: [2d]\", c=c_arr, v=v_arr, c_next=c_arr)\n",
+    "\n",
+    "# write down advection diffusion pde\n",
+    "# the equation is represented by a single term and an implicit \"=0\" is assumed.\n",
+    "adv_diff_pde = ps.fd.transient(c) - ps.fd.diffusion(c, sp.Symbol(\"D\")) + ps.fd.advection(c, v)\n",
+    "adv_diff_pde"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It describes how the concentration $c$ of a passive substance, which does not influence the flow field, behaves in a fluid with given velocity $v$.\n",
+    "To illustrate the two effects here, image we release a constant stream of dye at some point in a river. The dye is transported with the flow (advection) but also the trace gets wider and wider normal to the flow direction due to diffusion."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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1KRJ2FdLy+jD5JmZSkinSj0r7zETGYK1AxhsvRsZljXOczmbIuvM3OLbb7ZTlP8WebZEybhny/B4y1IS/iSzB0i4TjL3zkPHN4djcXZDnmF7kuuiG3qllUpZ/FaUWaCugohSHtgIqSnFoK6CilIe2/CmK4h1tBVSU4tBWQEUpDm0FVJTy0JY/RVEURVEURVEURVEURVEURVEURVEURVEURVEURVEURVEURVEURVEURVEURVEG5f8Vts30hDCiXAAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$$0.96 {{c}_{C}} - 0.005 {{c}_{E}} {{v}_{E}^{0}} + 0.01 {{c}_{E}} - 0.005 {{c}_{N}} {{v}_{N}^{1}} + 0.01 {{c}_{N}} + 0.005 {{c}_{S}} {{v}_{S}^{1}} + 0.01 {{c}_{S}} + 0.005 {{c}_{W}} {{v}_{W}^{0}} + 0.01 {{c}_{W}}$$"
+      ],
+      "text/plain": [
+       "0.96â‹…c_C - 0.005â‹…c_Eâ‹…v_E__0 + 0.01â‹…c_E - 0.005â‹…c_Nâ‹…v_N__1 + 0.01â‹…c_N + 0.005â‹…c\n",
+       "_Sâ‹…v_S__1 + 0.01â‹…c_S + 0.005â‹…c_Wâ‹…v_W__0 + 0.01â‹…c_W"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discretize = ps.fd.Discretization2ndOrder(1, 0.01)\n",
+    "discretization = discretize(adv_diff_pde)\n",
+    "discretization.subs(sp.Symbol(\"D\"),1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ast = ps.create_kernel([ps.Assignment(c_next.center(), discretization.subs(sp.Symbol(\"D\"), 1))])\n",
+    "kernel = ast.compile()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Hw+F8UPhBlMPhcDgcDofD4XA4HxR+EOVwOBwOh8PhcDgczgeFH0T/Zr777jsMGDCAqT179gwODg6y3Uq//vorWrduzeyxys/PR/v27bF48WLmrLe3N+zt7fH48WOmPmTIEHz11VdM7cWLF3BwcJDtW1yxYgVatWrF7LYsKCiAk5MTFixYwJw9f/487O3tZTv+hg8fji+//JLZFxUdHY2GDRvK9geuXr0aLVq0YPZFFRUVoWPHjpg3bx5z9uLFi7C3t4fcsq1Ro0ahT58+TF+vXr2Co6OjbH/g2rVr0bx5c2a3ZXFxMTp37oxZs2YxZ319fWFnZyfbWTd27Fj06tWL2W0ZFxcHR0dH2Z6+DRs2oFmzZsxuy5KSEnTt2hUzZsxgzl69ehV2dnay3XATJkxAz549mb4SEhLQqFEjuLu7M2c3bdqEJk2aMLstS0tL4ezsjKlTpzJn/f39YWdnJ9sXO2nSJHTv3p3ZbZmUlITGjRvL9s5t27YNjRs3RnJyskQrKytD9+7dMXnyZOZsQEAA7OzsZLvOpk6dCmdnZ2a3ZUpKCpo0aSLb77Zz5040atQIiYmJTF89e/bEhAkTmLO3b9+GnZ2dbP/p9OnT0bVrV2a3ZXp6Opo1a4YNGzYwZ3ft2oVGjRohPj5eoqnVavTq1Qvjxo1jzt69exd2dnayPaOzZs1C586dmd2Wr1+/RvPmzbFu3Trm7N69e+Ho6IhXr15JNCJC7969MXr0aOZscHAw7O3tcfHiRaY+d+5cdOzYkdltmZmZiRYtWmDNmjXM2QMHDqBhw4bMrkYiQt++fTFixAjmbGhoKOzt7XH+/HmmvmDBAjg5OTG7LbOzs9GyZUusXLmSOevp6QkHBwfZ/uZ+/fph6NChTO3Ro0ewt7eX7c1ctGgR2rdvj4KCAomWk5OD1q1bY/ny5czZo0ePwsHBQbYTccCAARg0aBBTi4iIgL29vWw/5c8//4x27doxuy1zc3PRtm1bLFu2jDl74sQJ2Nvby3YPDhw4EAMHDmRqkZGRcHBwkO2BXLZsGdq0acPs4c7Ly0O7du3w008/MWdPnz4Ne3t72T7iQYMGoX///kwtKioKDg4Osn2Ly5cvR6tWrZjdlgUFBfjkk0+waNEi5qwmq8j1EQ8dOhT9+vVjaiqVCg0bNpTtYF65ciVatmzJ7LYsLCyEk5MT5s+fz5y9cOEC7O3tZXt/R4wYgb59+zIzQUxMjNas4ubmVmlWmTt3LnO2sqwyZswY9O7dm+krNjYWjo6O2Lt3L3N23bp1aNasGV6/fi3RNFll5syZzFk/Pz/Y2dnh7t27TH3cuHGyWSU+Ph6NGjWSzSobN25E06ZNkZaWJtE0WWX69OnM2cqyysSJE/Hpp58yM0FiYiIaN26stbuXUzl6f7eBfzNEhOjoaJSUlECtVkNHR/y6QE5ODlQqlWxpe1xcHFQqFfLz81GtWjWRVlRUhOjoaGaYAspLfFUqlWy5cHR0NPLy8lBWVgZdXV2mL1bgBsp/aKhUKhQUFKB69eoSXyqVCvXr12fOpqWlQaVSyZYLR0dHIysrC2VlZdDTE3/5VuYrISFBuF81a9Zk+lIqlX/aV2pqKkpLS6Gvry/S3rx5A5VKJVtyr/GVl5eHWrVqMX1ZWFgwZ9PT06FSqZiHWKD8gRcfH4/S0lIYGBj8aV/m5uYirbi4GCqVSnIf39VXdHS08LVvaGgo0nJzc6FSqZgHJ6D8h79KpUJubq7kvpSUlCA6OhrGxsbM2devX0OlUjEfpED5/dL4qvh1/5/4qojGV8WvDQ0ZGRnv7Kvi131eXp5WX0lJSVCpVMwXrEpLS2XL3t/F18uXL6FSqVBcXCz53DS+EhIS/rQv1kESKD+0qVQq5oskFX1V/LrPz8+HSqViHoABIDk5Wasvzc9Gbb5YgQgof1FKpVKhqKhI8nX/rr5YL/CVlZUhOjoaNWrUYM5mZWVV6is6OhqFhYWoUqWKxFd0dDTi4uKYsykpKVCpVMxDhsaX3PejxhfrRSWgPBhrfBkZGYm0goICqFSqSn2x7pdarYZKpYK+vn55fYBC8R/7UqlUKCwslHxuhYWFUKlUiI2NZc5qnr0sX5pMQER/KRMUFBTAxMTkP/KlecZp81VUVPSnfMXHxyM6OhoFBQUwNTVl+rK3t9fqS+7Zq/mZ+1ezSsXvHU2Gqlev3p/yFR0djYyMDK1ZRe7Zq/Ell1Wio6NRp04d5uy7PHuTkpL+clYxMzMTacXFxYiOjkbt2rX/tK+4uDitWUXuGfe2r4ofX+NL7mdjZZlAk1VKS0v/40zAeTd4fQuHw+FwOBwOh8PhcP4r8PoWDofD4XA4HA6Hw+H8T8IPohwOh8PhcDgcDofD+aDwgyiHw+FwOBwOh8PhcD4o/CDK4XA4HA6Hw+FwOJwPCj+I/g/A2rKpIT8/n7nO+l1mS0pKmDUBb89qW1b1/6sv1prtd/XFqi/4u32Vlpa+N18FBQV/yRerVuHv9lVWVvZefbEqVN7VV35+vqyel5f3p30VFhb+aV9qtVqrr79yv/6KLyKS3U4L/PX7xaqc+bt9FRUV/SN9adPz8vL+9LOkqKhIdrPy3+mruLj4T/uqTP8rz97i4uJKn71/hy+eVf6z2f/lTPC/6Ot9ZwJtvjiVww+i/wM0btwYvXr1YnZBXrlyBTY2NpgzZw5zrfrQoUPRrl07nDx5UvKNlJycDCsrKwwbNgwvX76UzK5btw4ODg5Yt24dM2Q0b94cPXv2xJ07dySav78/rK2tMWvWLGYFzIgRI9C2bVscP35c4istLQ1WVlYYMmQIoqOjJbMbN26Evb093NzcmA/zli1bomfPnszep4CAAFhbW2PGjBnMtepjxoxBmzZtcPToUYmv169fw9raGoMHD2ZWWmzZsgV2dnZYvXo101fbtm3Ro0cPZkdlUFAQrK2t8cMPPzDXl7u6uqJVq1Y4fPiwxFdmZiZsbGwwaNAgPH/+XDK7Y8cOfPzxx1i5ciXzofnJJ5+ge/fuuHnzpkS7d+8erKysMHXqVGYVxqRJk9CqVSscPHhQ4is7OxtKpRLffvsts6tv165daNCgAX777Tfmw6ljx45wdnbGjRs3JFpISAgsLS0xZcoUpq8pU6agRYsW2L9/v8TXmzdvYGtri4EDB+LZs2eS2b1796J+/fpYvnw501eXLl3QrVs3XL9+XaI9fPgQlpaWmDx5MrPaYfr06WjevDn27t0rCT+5ubn46KOPMGDAAGaH4IEDB1CvXj0sW7aM+dB0dnZG165dmZ2ejx8/hoWFBSZOnMisUJg1axaaNWuG3bt3S3zl5+ejbt266N+/PyIiIiSzhw8fRt26dbF06VLmgfXTTz9Fly5d4OfnJ9EiIyNhYWGBCRMmMCsU5s6di6ZNm8LDw0Piq6CgAA0aNMBXX33F7Ds+duwYPvroI/z8889MX7169ULnzp1x+fJliRYVFQULCwu4uroyqwoWLlyIJk2aYOfOnZKQUVRUhAYNGqBfv37MbsOTJ0/C1tYWixcvZh4Mv/jiC3Tq1Ak+Pj4S7cWLF7CwsMDYsWOZlQCLFy8Wumwr+iopKYGdnR369u3L7GH28vKCUqnEjz/+yAxW/fr1Q4cOHZhdoy9fvoSFhQXGjBnDrJdZunQpGjVqhK1bt0p8lZWVwd7eHn369MGDBw8ks+fPn4dSqcTChQuZlTn9+/eHk5MTzp49K/lej42NhYWFBUaNGsWscVm+fDkcHR2xefNmyQsiRAQHBwf07t0bISEhktmLFy9CqVRi/vz5zGqagQMH4pNPPoGXl5fEV0JCAiwsLDBy5EhmXcrKlSvRsGFDbNy4kflCjaOjIz7//HPcv39fovn6+qJOnTqYO3cuMxMMHjwY7du3x+nTpyW+kpKSYGVlheHDhzOr3dzc3ODg4ID169czM0GTJk3Qq1cvZhfk1atXYWNjg9mzZzMzwbBhw9C2bVtmVklJSRGyCqsn9/fff4eDgwPWrl3L9NWiRQv07NkTQUFBEu3GjRuwtrbGzJkzmZlg5MiRaNOmDTOrpKena80qmzZt0ppVWrVqhU8//ZSZVQIDA7VmgrFjx6J169ayWcXGxkY2q2zdulXIKqxM0K5dO61ZxcrKCtOnT2dWmowfP142q2RlZcHGxgbfffcdM6vs3LlTa1ZxcnKSzSr379+HpaWlbFaZPHkyWrZsqTWryGWC3bt3a80qnTp1grOzM7Pn+8GDB7CwsMD3338vW4/FqQQi+mBXmzZtiCPl7NmzlJKSwtRiY2Pp2rVrVFxczNT9/f3pxYsXTK2goIC8vLzozZs3TD0sLIxCQkJIrVYz9XPnzsn6io+Pp6tXr2r19fz5c6ZWWFhIZ86coZycHKb+8OFDCg4OprKyMllfycnJTC0hIYGuXLlCRUVFTP3GjRsUFRXF1IqKirT6evToEd2/f1/W1/nz5ykpKYmpJSUlkZ+fn6yvmzdv0rNnz5hacXExnTlzhrKzs5l6eHg43bt3T9bXhQsXKDExkaklJyeTr68vFRYWMvWAgAB6+vQpUyspKdHqKyIigu7cuSPry8fHhxISEphaamoqXb58WdbXrVu3KDIykvm1W1paSmfOnKGsrCzm7JMnT7T6unjxoqyvtLQ0unTpEhUUFDD127dv05MnT7T6yszMZM4+ffqUbt++TaWlpUz90qVLFB8fz9Rev35NFy9elPUVFBREERERTF9lZWVafT179owCAwNlfV2+fJni4uKYWkZGBvn4+Mj6unPnDoWHhzN9qdVqOnPmDGVkZDBno6Ki6NatW7K+fH19KTY2lqllZWXRhQsXKD8/n6nfvXuXHj9+LOvLy8uLXr9+zZx9/vw5BQQEyPry8/OjV69eMbXs7Gw6d+6crK979+7Ro0ePtPpKT09nzqpUKrp58yaVlJQw9StXrtDLly+Z2ps3b+js2bOUl5fH1O/fv08PHz78U76io6Ppxo0bsr6uXr1KMTExTC03N5e8vb1lfYWEhFBYWJisL29vb0pLS2POvnz5kvz9/WV9Xbt2jaKjo5laXl4eeXt7U25uLlN/8OABhYaGyj57vb29KTU1lam9evWKrl+/LvvsvXbtGqlUKqaWn5+vNROEhobSgwcPZH29r6xSWFj4l7OKXCb4K1mlskzw8OHDSjOBnK/ExEStWeXmzZuyWUWTCeR8PX78WKuvCxcuvJesUlkmCA8Pp7t37/6prJKSklJpJqgsq8hlgsqyirZMUFlW+TcDIJje4WzIe0Q5HA6Hw+FwOBwOh/NfgfeIcjgcDofD4XA4HA7nfxJ+EOVwOBwOh8PhcDgczgeFH0Q5HA6Hw+FwOBwOh/NB4QdRDofD4XA4HA6Hw+F8UHSXLl36wT6Yu7v70gkTJnywj/f/C1OnTkVUVBRq166NWrVqibTw8HAsWLAAarUatra2MDAwEOlr166Fr68vqlWrBmtraygUCkF78+YNXF1dkZ2djTp16sDY2Fg06+XlhZ07d8LAwABKpRK6uroiffr06Xj69CnTV2RkJObNmwe1Wg2lUglDQ0ORvn79ely+fBkmJiawsrIS+crLy8O4ceOEVd8mJiai2XPnzmH79u3Q09Nj+poxYwaePHkCc3NzmJmZibRnz55hzpw5KCsrY/rauHEjfHx8YGJiIrlf+fn5GDduHDIyMpi+Lly4gK1bt0JPTw+2trYSX7Nnz0Z4eDjT14sXLzBz5kxZX5s3b8b58+eZvgoLCzFu3DihXqZatWqi2UuXLmHTpk3Q1dWFUqmEnp6eSJ87dy4ePXoEMzMzmJmZid53TEwMfvjhB5SUlECpVKJKlSqi2W3btsHb2xvGxsawsbERzRYVFcHV1RVpaWlMX76+vli/fj10dXVha2sr8TV//nyEhYUxfb169QrTp09HcXExbG1tJb527NiBM2fOwNjYGNbW1tDR+b/X1IqLizFu3DikpqbCysoKpqamotmrV69i3bp1svdr4cKFePDgAWrVqgVzc3ORr7i4OEydOhXFxcXM++Xh4YFTp06hatWqsLGxEfkqKSmBq6urUFVQ0Ze/vz/WrFkDHR0d5v1atGgRgoODmb4SEhIwZcoUFBUVQalUwsjISDS7e/dunDhxgumrtLQUrq6uSEy6490uAAAgAElEQVRMhJWVFapXry6avXnzJlatWgUdHR0olUro6+uL9J9//hl3795FjRo1ULt2bZGvpKQkTJ48GYWFhUxf+/btw9GjR2FkZIQ6deqIfJWVlWH8+PFISEiApaWlxFdgYCBWrFgBhUIBW1tbia+lS5ciKCgINWrUgIWFhchXSkoKJk+ejIKCAqavAwcO4PDhwzAyMpLcr7KyMkycOBFxcXHM+xUUFITly5dDoVAw79cvv/yCwMBAVK9eXeIrLS0NEydORH5+PurUqYOqVauKZg8dOoRDhw7B0NBQcr/UajUmTJiA2NhYWFpaokaNGqLZe/fuYdmyZQDAvF/Lly9HQEAAqlevDktLS5Gv169fY8KECcjLy4NSqZT4OnLkCA4cOABDQ0MolUqRLyLC5MmTERMTw/QVEhKCJUuWAACUSqXkGbdixQr4+/szfWVmZmL8+PHIzc1l3q/jx49j7969MDAwQJ06dUQ/szW+oqOjYWFhgZo1a4pmw8LCsHjxYhAR89m7atUqXLt2DaamppJnXHZ2NlxdXfHmzRvms/fkyZPYvXu37LN3ypQpQpVPRV+PHj3Cjz/+KJsJ3NzccOXKFaavnJwcuLq6IicnBzY2NhJfp0+fhru7u6yvadOmyWaViIgILFiwAGVlZUxf69atk80qubm5GDduHLKzs5nPXm9vb+zYsQP6+vpMXz/88AOePn3KfPY+ffoUc+fOFXxVfPZu2LABFy9eRLVq1WSziqZCjZVVtm3bJutr5syZslnl+fPnmDVrlmwm2LRpEy5cuMDMBAUFBXB1dZXNKj4+Pti8eXOlWcXMzAzm5uYiTaVSYebMmSgtLWXery1btuDcuXNas0p6ejpsbGwkmeDy5cvYuHGjkO3kskqtWrX+46yyffv2SrNKamoqM6v4+flpzSoLFixAaGgo89kbGxuLqVOnoqSkhJlV/s0sW7YsaenSpe6VvuG7rNb9b128voVNnTp1yNjYmL7++mu6ffu2SPPx8SEA1KBBA5o/f76kyuDrr78mXV1dcnFxoaNHj4rWm798+ZKMjIzI3NycxowZI1md/ttvvxEAatWqFf3++++Sdd1169alqlWr0ldffUUBAQEi7fLlywSA6tevT3PnzpVUGQwcOJB0dXXJ2dmZjhw5IvIVGxtLVatWJXNzcxo9erRkdfqqVasIALVs2ZLWrl0rWYv98ccfk5GREfXr149u3rwp0q5cuUIAqF69ejRnzhxJZcCgQYNIV1eXunbtSocOHRL5SkhIIGNjYzIzM6NRo0ZJVpSvXbuWAFCLFi1ozZo1kkoKBwcHMjIyoi+//JL8/f1Fmr+/PwGgunXr0qxZsySVAcOGDSMdHR3q0qULHTx4UOQrKSmJTExMqFatWjRy5EjJivL169cTAGrevDmtWrVK4qtx48ZUpUoV6tu3L127dk2k3bp1iwDQRx99RDNnzpRUBowcOZJ0dHSoc+fOtH//ftF685SUFDI1NaWaNWvS8OHD6cmTJ6LZzZs3EwBq2rQprVixQlJJ0axZM6pSpQp98cUXdOXKFZF2+/ZtAkC2trY0Y8YMSWXA2LFjSUdHhzp16kR79+4V+UpPT6fq1atTzZo1adiwYRQRESGa3b59u+Br+fLlkuqHVq1akaGhIfXp04d8fX1F2r179wgAKZVKmj59umQ1/4QJE0ihUFDHjh1p9+7dIl8ZGRlUo0YNqlGjBg0dOpQeP34smnV3dycA1LhxY/r1118lvtq1a0eGhobUu3dvunz5skgLDg4mhUJBderUoalTp0pW4E+ePJkUCgV16NCBPDw8RNUi2dnZVLNmTapevToNGTKEHj16JJrds2cPAaBGjRrRsmXLJJUUTk5OZGBgQJ9//jn5+PiItNDQUNLR0SEbGxv6/vvvJSvwp02bRgqFgpycnMjd3V3k682bN2RmZkampqY0aNAgCgsLE83u37+fAJCjoyMtXbpUUv3QuXNnMjAwoF69etGFCxdE2qNHj0hHR4esra1p8uTJklqcGTNmkEKhoE8++YR27Ngh8pWXl0fm5uaCr9DQUNGsp6cnAaCGDRvSzz//LKlY6NatG+nr69Nnn31GZ8+eFWkRERGkq6tLVlZWNGnSJEktzpw5cwgAtW/fnrZt2yaqFiksLKTatWtTtWrVaODAgRQcHCyaPXbsGAEgBwcH+umnnyS+evToQfr6+tSzZ0/y8vIS/QyKjIwkPT09srS0pAkTJkjqZ+bPn08AqF27drRlyxaRr+LiYrKwsCATExP65ptv6N69e6LZkydPEgCyt7enRYsWSaofPvvsM9LX16dPP/2UTp8+LfIVFRVFBgYGZGlpSePHj5fUzyxatIgAUNu2bWnTpk2iCo+ysjKytLQkExMTGjBgAN29e1c06+XlRQDIzs6OfvzxR0n1Q58+fUhPT4969OhBJ0+eFPl68eIFGRoakoWFBbm6ukrqZ5YsWUIAqE2bNrRx40ZJtYi1tTUZGxtT//79KSgoSKSdO3eOANDHH39MCxYskNQu9evXj/T09MjFxYWOHz8u8hUdHU1VqlSh2rVr09ixYyU1L7/88gsBoNatWzMzga2tLVWtWpW+/vprCgwMFGkXL14Ussq8efMkWaV///5CJqiYVV69eqU1q6xYsULIKmvXrpX4qlevnmxW8fX11ZpVvv32W9LV1aVu3brR4cOHRb7i4uKoatWqZGZmRqNHj5bUqaxevVrIBG5ubpKsYmdnJ2SVGzduiLRr164JmWD27NmSrDJ48GCtWcXExEQ2q6xbt07IBKtXr5ZkgoYNG8pmlRs3bmjNKsOHDxeyyoEDB0S+kpOTqVq1alSrVi0aMWKEJKts3LiRAFCzZs1o5cqVEl9NmjSpNKvIZYLRo0fLZpXU1FStWWXLli1as0rz5s1ls0pQUJDgi5UJ/s3gHetb+EH0f4CAgADZnr3ExETZ/j+i8gAq1/9XUFCgtf/v6dOnsv1/ROXf+HK+kpKSZPv/iMr72+T6/woLC7X6evbsmWz/n8aXXM9ecnKybP+fxpdc/19RUZHWXsKoqCjZ/j8iosDAQFlfKSkpsv1/ROW9cnK+iouLKSAgQLbPLioqSrb/T+NLrmcvNTVVtv+PqPwgIdf/V1JSotXX8+fPZfv/iMoPm3K+0tLSZPv/NL7k+v9KS0u1+lKpVLL9fxpfcv1/r1+/1tr/FxYWJtv/p/El12enUqlk+/+Iyh94cj17GRkZWvv/Hj58KNv/V1ZWRjdv3pT1FR0dLdv/R1TeBSrnKzMzU2v/36NHj2R9qdVqrb5iYmJk+/80vuR69rKysrR2FT9+/Fg2UKjVagoICJDt2Xv58qVs/x9ReUepnK+cnBytncDh4eGy/X+a+yXnKzY2Vrb/j6j8RRa5/r83b95o7f8LDw+X7f/T3C+5nr24uDjZ/j+NL7n+v9zcXK39fxEREbL9f5r7JecrPj5etquYqLw7Vc5XXl4eBQUFyfp68uSJbCcwkfZMkJCQINtVTFR5JtDWVRwZGfmnfb1LVvmzmeBdsorcs/evZJWioqJKs4q2TPC+skpxcfFfziraMkFlWUVbJrh165bWTKAtq2jLBKmpqX86E1SWVV68eFFpVpHLBOnp6Vp9/Zt514Mo7xHlcDgcDofD4XA4HM5/Bd4jyuFwOBwOh8PhcDic/0kqPYgqFIoqCoXinkKheKhQKCIUCsWyP/5+n0KhiFEoFGF/XC3fv10Oh8PhcDgcDofD4fz/jl7lb4IiAN2JKFehUOgDuKVQKC7+oc0lopPvzx6Hw+FwOBwOh8PhcP5pVPob0T/+zWnuH3/U/+P6cP+w9F/A8ePH8fLlS6b26tUrnD17Fvn5+Uzd19cXDx8+BOvf+hYWFsLT0xPp6enM2ZCQENy4cQOlpaVM/cSJE4iJiWFqcXFx8Pb2Rl5eHlP38/NDWFgY01dRURE8PT2RlpbGnH3w4AH8/f1RUlLC1E+ePIno6GimlpCQAC8vL1lfV65cwYMHD5i+iouLcejQIaSmpjJnw8LCcP36dVlfp06dgkqlYmpJSUk4c+YMcnNzmfrVq1cREhLC9FVSUqLV18OHD3Ht2jVZX6dPn8aLFy+YWnJyMk6fPo03b94w9evXryM4OBhqtVqilZaW4tChQ0hJSWHOPn78GFeuXEFxcTFTP3PmDJ4/f87UUlNTcerUKVlf/v7+uH//PtNXWVkZPD09kZyczJwNDw+Hn5+frC8vLy9ERUUxtfT0dJw8eRI5OTlM/caNG7h3755WX0lJSczZJ0+ewNfXF0VFRUzd29sbz549Y2qvX7/GiRMnkJ2dzdQDAgJw9+5dpi+1Wg1PT08kJiYyZyMjI3H58mVZX2fPnsXTp0+ZX7uZmZk4fvy4rK9bt27hzp07TF9EBE9PTyQkJDBnnz17hkuXLsn6OnfuHCIjI5m+srOzcezYMWRlZTFnAwMDERQUhLKyMqavw4cPIz4+njkbFRWFixcvorCwkKlfuHABT548YfrKycnBkSNHkJmZyZwNCgrC7du3ZX0dOXJE1teLFy/g4+Oj1VdERATTV25urlZfd+7cQWBgoFZfcXFxzFmVSoULFy6goKCAqV+8eBHh4eFMX3l5eTh8+DAyMjKYs3fv3sWtW7eYzzgiwtGjRxEbG8ucjYmJwfnz52V9Xbp0CY8fP2b6ys/Px+HDh/H69Wvm7P379xEQECD77D127BhevXrF1F69eoVz587JZoLLly9XmgnkfAUHB+PmzZuyvrRlldjY2EqzSmWZ4H1klfj4+EqzSmhoqGwm0JZVQkNDtWYCbVklMTERXl5eWjOBXFYpKSmBp6en1qyiLRP8laxy7do12axSWlqq1dfDhw9x9epV2WevtqySkpKiNRO8S1aRywR/NatoywScd+BdNhoB0AUQBiAXwOo//m4fgGcAHgFYD8CwsvfDt+aycXR0FFZHL1y4UFRT4O/vTwqFQlgdvX37dtFmwxEjRgiroydPnkx+fn7C9q64uDgyMzMTai5WrVol2karWaVdo0YNGjJkCB05ckS0obJp06YEgJo0aUILFiwQ1RQEBASQjo6OUHOxbds20QbB0aNHCzUXkyZNIl9fX8FXfHw8mZubCzUXK1asEG1S27p1q+Br8ODBdPjwYZGvFi1aCDUX8+fPpwcPHghaYGAg6erqkqGhIX3++ee0detW0QZBV1dXAkB16tShiRMn0uXLlwVfSUlJZGFhIdRc/Pbbb6JNajt27CAAVL16dRo0aBAdOnRItKGyTZs2Qs3FvHnzKCQkRNDu3LlDurq6Qp3Eli1bRJv6Jk6cSADIxsaGJkyYQBcvXhR8paSkkKWlpVBzsXz5ctHW1127dhEAMjU1pe+++44OHjwo8tW+fXuh5mLOnDl0//59Qbt//z7p6emRgYEBffbZZ7R582bRpr4pU6YQALK2tqbx48eTj4+P4CstLY2srKyEOolff/1VtPV13759gq9vv/2WDhw4INpQ2bFjR6HmYs6cOaJah5CQENLX1xfqJDZt2iTa1Dd9+nQCQFZWVuTq6krnz58XfGVkZJCNjY3g65dffhFtfT148CABEGou9u/fL9oE2aVLF6HmYtasWXTnzh1BCwsLI0NDQ6FOYuPGjaJNfbNmzSIAZGlpSWPHjqVz584JvjIzM6lOnTpCncSyZctEW1+PHDlCAISai3379ol8ubi4CDUXM2fOFNU6PHr0iKpUqSLUSWzYsEG0vXfevHkiX97e3sJGz5ycHLK1tRXqJJYuXSrarnr8+HHB14ABA2jPnj2iTZA9e/YUai5mzJghqqAKDw8nIyMj0tPTo+7du9P69etFW3IXLlxIAMjCwoJGjx5NXl5egq/c3Fz66KOPhDqJJUuWiLarnj59mgAINRe7d+8WbVz8/PPPhTqJH374gW7duiVoT548IWNjY6Hm4vfffxdtyf3pp58IANWuXZtGjRpFZ86cEXzl5+dT3bp1hTqJn3/+mSIjI4VZb29vwdfXX39Nu3btEvnq27ev4Gv69OmiuomnT5+SiYmJUHOxdu1a0ZbcpUuXEgAyNzenkSNH0unTp4XNmYWFhVS/fn2h+uqnn34S1RRcuHCBAFDVqlWpX79+5OHhIdoE+dVXXwk1F9OmTRPVTTx//pxMTU2Fmou1a9eKtuQuX76cAJCZmRmNGDGCTp48KfgqLi6mBg0aCDUXixcvpvDwcGH20qVLBECouXB3dxdtYf7mm2+ESq6pU6eK6iZUKhVVr15dqLlYs2aNaEuupgqsVq1aNHz4cDpx4oTgq6ysjOzs7ISai0WLFokqlfz8/ARfffv2pZ07d4q2HX/33XdCzcWUKVPo2rVrwvd6TEwM1ahRQ6i5WL16tWgbrZubm+Br2LBhdOzYMdFGT3t7e6Hm4scffxRVKmlqPzSZYMeOHaJMMHToUKGS6/vvv6crV64Ivl69ekW1atUSai4qZgJNFVjNmjVp6NChdPToUZGvRo0aCVllwYIFoqxy48YNIav06dOHtm/fLsoEI0eOrDSraDLBypUrRVtfN23apDWrNGvWTMgq8+fPF2WVW7duCVmld+/etG3bNlEmGDNmjCirvJ0JEhMTqXbt2kImqJhVtm3bpjWrtGzZUsgq8+bNE2WVoKAgSVZ5OxOMHz9elFUuXbrEzCpOTk6SrLJz506tWaVt27ZCVpk7d66o6unu3btCJtBklbczwaRJk4SsMn78eFFWSU1NJSsrK6H6qmJW2b17tySrvJ0JPvnkE1EmeDurBAcHk76+viirvJ0Jpk6dKmQVV1dXunDhguArPT2drK2tRVnl7UygqQKTyyqdOnUSMsHs2bNFVU8PHjwgAwMDUVaR2977bwPvuDX3nZYVEVEZEbUEoATQXqFQNAWwEIAjgHYAagGYz5pVKBQTFApFsEKhCJZ7VenfjqmpKerWrQtnZ2c4OzvD0dFRpOnp6aF9+/ZwdnaGi4sLTE1NRbqZmZmgtWvXTijbNTY2hq6uLpo1aya87zp16ohmjYyM0KVLF7i4uKBr166iknONLxcXFzg7O6NRo0YiTVdXV6uvWrVqCVr79u1FvvT09NC0aVNBt7W1Fc1WqVIFnTt3lvVla2srfE4sX+3atYOLiwtcXFxEhfOmpqaoWbMm05eRkRH09PTQpEmTd/Ll7OwsKu2u6Ktx48Zafb1d7G5qaooaNWqgW7ducHZ2xieffCLyZWBggMaNGwu+PvroI9GsoaEhOnfuDGdnZ3Tr1k3iS6lUCrNNmjSR+Grbtq3g6+0CdY0vzefk5OQk+KpSpQoMDQ3RuHFjYbZu3boSX506dYKLiwu6desmKsc2NTVFnTp1hPfdtGlTrb7eLlA3NTVF9erVhfvVoUMHwZeBgQEMDQ3RqFEj4XOuV6+eaNbAwAAdO3YU7tfbJdSmpqawsbERZps1aybSdHR00KZNG8HX20XlpqamMDU1Rbdu3eDi4iLyZWhoiCpVqsDR0VGYZfnq1KmTcE8q+rK2thZ8NW/eXNaXs7OzqKjc1NQU1apVQ9euXeHs7IyOHTtCR6f8x7++vj6MjIzQsGFDwVeDBg1Es/r6+ujQoYPwsY2MjES6lZWVVl+tW7cW3nft2rWZvlxcXNCpUyfBl56eHqpWrQoHBwdh9uOPP9bqq2rVqiLd0tJSmG3ZsqXEV6tWrYR7bWFhIdJNTEyYvnR1dWFsbAx7e3vhXrN8OTk5yfqysLAQNJavli1bCrqlpaVWX5qyel1dXZiYmMDOzk74nO3s7ESzenp6cHJyEnRjY2NZX61btxa0atWqQUdHBy1atBDul5WVlWjW2NhY8NW5c2fBl46ODqpVq4YGDRoIs/b29kxfmo9tYmIi0mvXrs30ZWJiAh0dHTRv3lzQK/qqWrWq4KtLly6CL83n1aBBA+H/RwcHB4mvTz75RLhf1apVE+nm5ubCx23Tpo3wvW5iYgJdXV2RL2tra4mvt5+9enp6Ir1evXrC/WrYsKHk6+ttX6xMoPnZ+HYm0PjSZAIXF5dKM0FFX5qs4uLiIptV5J69tWrVYvrSZIJmzZoJs0qlkunL2dmZmQk++ugjwZdcVtH8/8zKBBpfb2eCqlWrCllF4+vPZhU5X9oywdu+3s4EVatWhb6+Ppo0aSLrS/Ps/bOZoF27dsLXHysTaJ5xb/uqUqUK9PX1RZmAlVXe9sXKBJrZir50dHSETODs7CybCVxcXERZxdDQUMhQ2p69b2eCir5sbGyEWblMoLlfb2cCzjvwLqdVEv92dAmAORX+zhnA+cpm+W9E2URFRcl2EKWlpcl2SRGVvyIs1yVVWFiotbMpLi5OtrOpMl/p6emyXVIaX3KdTe/T1+vXr7W+GqXNV1FRkdYuqfj4eNkuqcp8ZWRkaPUVHR0t66u4uFhr7+Vf9SXXe6nxJdfjWFJSorX3MiEhQbZfsjJfmZmZsv2SlfkqLS3V2nuZmJj4p31lZWVpLayOiYmR7XF8F19y/ZJE5b+VkuslzM7O/tO+ysrKtPZxJiUlyfZLVuYrJydHtveyMl9qtfq9+pLrvSQq7wKV65eszFdycrJsvyRReWednK83b97I9l6+qy+5r92UlBTZfsnKfOXm5mrtl3z16pVsv6Rardb6PfUuvuSecXl5eVr7Jf+Kr9TUVNl+ycp85efna+3Cjo2Nle2XJPprmUCbr4KCAq39ku/T19+VCf5KVnmXTPB3ZJX3nQkqyyraMsH78pWZmfm3ZRVtP1cryyr/ZvDf6hFVKBS1AZQQUZZCoTAC4AtgNYAQIkpSlL/ksB5AIREt0Pa+eI8oh8PhcDgcDofD4fxzedce0XfZmmsNYL9CodBF+XKj40R0XqFQXPvjkKpA+b8fnfSXHHM4HA6Hw+FwOBwO519BpQdRInoEoBXj77u/F0ccDofD4XA4HA6Hw/lH807LijjvF7mV5UB5zYBcPUFls0VFRbK1CUB55QNr1fW7vO+cnBytvtLS0pjrvYHyleh/l6/09HRZXyUlJbJ1DgCQkZHBrCd4F19v3ryRrU14F19ytQl/p6/S0tL35is3N1e2NqEyX2VlZbJ1Du/bl7av+3fxJVdPUJmvvLw82doEzaycL7VaLVvnAJRXsPwdvojovfnKz8+XrXN4F1/a3ndWVpZsbcK7+JKrTfg7fRUUFPxP+iosLJStcwC0P0uISLaWAyh/9srVObxPX5W977/iq6ioSGvNxPt+9mrz9b+YCd5nVqns2avtWfJ3ZhVtvt5nJvhf9VVZJuBUju7SpUs/2Adzd3dfOmHChA/28f5/YeTIkVi7di2Sk5OFDZSabV/p6elwdHTE3bt3UVBQgDp16og2HW7cuBHjxo3Dy5cvYWBgAKVSKWwFVKvVcHJywunTp5GZmQkLCwvR9rPAwEB07txZ6NqztbUVbVYbO3YsVq9ejaSkJImv169fw9HREXfu3EFBQQFsbGxEvrZu3YoxY8bI+urQoQNOnjyJzMxM1K5dW7T97O7du+jQoQMiIyOhVqslvlxdXbFy5UokJiaiWrVqsLa2FnxlZmbC0dERt2/fRn5+vuR+7dixAyNHjkRMTAz09fVha2sr+CIidOrUCcePH0dGRobEV3BwMNq3b48nT55ArVZDqVSKNqtNmjQJv/76q+Dr7fuVnZ0NR0dHBAYGIj8/HzY2NqLNkLt27cKwYcMQExMDPT090f0iInTr1g1HjhxBRkYGzM3NRVvZQkND0a5dO0RERKCsrAy2trYiX1OnTsXSpUuRmJgIExMT0f168+YNHB0dERAQgLy8PImvvXv3YvDgwVCpVNDT05PcLxcXF6GXrqKvx48fo3Xr1oiIiEBpaanE1w8//ICff/4ZCQkJEl+5ublo1KgRbt68iby8PFhbW4s2Vh48eBDffvut4EupVArbHYkIPXv2xIEDB/D69WuYmZmJNshGRESgVatWCA8PR0lJCZRKpWg77ezZs7Fo0SIkJCTA2NgYNjY2gq/8/Hw0btwY/v7+yM3Nlfg6cuQIvvnmG7x48QK6urqwtbUV+fr888+xb98+pKenw8zMDGZmZsL7fvbsGZo3b45Hjx6hpKQEtra2Il/z5s3DggULEB8fL/FVUFCAJk2a4Nq1a8jNzYWVlZVok+bx48fx9ddfC74q3q8vvvgCu3fvRnp6OmrVqgVzc3Phfb948QLNmjXDw4cPmfdr4cKFmDdvHuLj41G1alXY2NgIG2aLiorQpEkTXL16FTk5ORJfp06dwpdffonnz59DR0dHcr/69esHDw8PpKWloWbNmqhdu7bgKzo6Gk2bNkVYWBiKi4uhVCpF23wXL16M2bNnIy4ujumrWbNm8PPzE3y9vUnT29sbffr0kfX19ddfY+fOnUhLS0ONGjVEvl6+fIkmTZogNDSU6Wvp0qWYMWMG4uLiYGRkhDp16gi+iouL0aJFC1y+fBnZ2dkSXxcuXECvXr0QFRUFhUIBW1tb0ZbOgQMHYtu2bUhJSUGNGjVgYWEh+IqLi0Pjxo3x4MEDFBUVSXwtX74c06ZNQ2xsLKpUqSLyVVpaipYtW8LHx4fp69KlS+jZs6esr0GDBmHz5s1MX4mJiWjUqBFCQkJQVFSEOnXqiLYMr1y5ElOmTEFsbCwMDQ0lvlq1aoXz588jOzsblpaWos2jV65cQffu3YX+3Yq+hg4dio0bNyI5ORnVq1eHpaWl4Cs5ORmOjo4IDg5GYWEhlEqlyJebmxsmTZqEV69ewdDQEEqlUvBVVlaGNm3a4OzZs8jKypL4un79OpydnQVfSqVS9IwbPnw4fv/9d6av1NRUODo64t69eygsLJTcr99//x3jx4/Hq1evhGevxpdarUa7du3g5eWFrKwsSSYICAhA165d8fTpU+azd9SoUXBzc/tTWWXTpk0YO3YsYmJi/uOsEhQUhE6dOslmgrFjx2LVqlXMrJKRkYGGDRtqzSqjR4+W9dWxY0ecOHGCmVXu3dN85RwAACAASURBVLsHJycnREZGCs/et32NHz8eK1asQFJSkiSrZGVlCVmF9ex1d3fH8OHDhaxSMRN07twZx44dY2aVkJAQIauwMsHkyZNls0pOTo4oq1hbW4t87dmzB0OHDkV0dLTEl1qthrOzs5BVNM84DWFhYWjTpo2QVSpmqGnTpslmldzcXCGr5ObmSu7X/v37tWaVHj164NChQ8xMoMkq4eHhzKwyY8YM/PTTT5VmFY2vtzPBv5lly5YlLV261L3SN3yXjUb/rYtvzWWjo6NDAISrR48eQv+bpiNSc1WpUoWWLl0qbLbT9C5prkaNGtGVK1eIiOjhw4ciDQCNGTNG2PCl6YjUXLVr16Y9e/YImxMNDAxEuouLC0VERBDR/3VEai5DQ0P6+eefhQ1ymo5IzdWwYUPy9fUlovJuwYq+Ro0aJWz9/OGHH0SamZkZeXh4CL6MjIxEurOzs9D/pumI1FwGBga0aNEiwVfXrl1FuoODA126dImIyjv8KvoaMWKEsPVT0xGpuWrVqkU7d+4UNhRWq1ZNpHft2lXof9N0RL7t68cffxQ2yGk6IjWXnZ0d+fj4EFH5FsSKvoYOHSps19R0RGqumjVr0vbt2wVfNWrUEOmdO3cW+t9OnDgh0vT19Wn+/PnCBjlNR6Tm+vjjj+n8+fNEVL7xtKKvIUOGCNs1f/zxR5FWo0YN2rp1q+DL3NxcpHfs2FHof9N0RL7ta+7cucJWWU1HpOaqX78+nT17lojKNyxW9PXdd98J2zU1HZGaq3r16rR582ZhQ6GlpaVId3JyEnrWzp49K9L09PRo9uzZgi9NR6TmqlevHnl7e5NarabExESJr2+++UbYYrls2TKRZmpqShs3bhR8aTpINVf79u2FnjVNR6Tm0tXVpZkzZwpbZb/++muRXrduXTp9+jSp1WpKTU2V+Orfv7+wxVLTEam5qlWrRuvXrxc2FGo6NTVX27ZthZ61y5cvS3z98MMPwlZZTUek5rK1taVTp06RWq2mjIwMia+vvvpK2GKp6Yh829e6desEX5ruSs3VunVroXv1ypUrIk1HR4emTZsmbG8dNGiQSFcqlXT8+HFSq9WUnZ0t8fXll18KWxk1HZGay8TEhNasWSNsB3ZwcBDpLVu2pMDAQCIq742u6GvKlCnC9lZNR6TmsrGxoSNHjpBaraa8vDyJry+++ELY1KzpiNRcxsbGtHr1asGXpiNSc7Vo0ULoOL1165bE1+TJk4UtqZqOSM1lbW1Nnp6epFarqbCwUOKrd+/eFBUVRUREmzdvFmlVq1alFStWCNuBNR2RmqtZs2ZCx2lQUJBIUygUNHHiRGFL6tixY0W6lZUVHTx4kNRqNZWWlkp89erVS+jQ1XREai4jIyNavny5sIVX0xGpuZo2bSp0nN6/f1/ia/z48cI2Uk1HpOaytLSk/fv3C5s5K/rq2bOn0KHr7u4u0qpUqULLli0TfGk6IjVX48aN6dq1a0RU3nlY0dfYsWOFTDB58mSRXrt2bdq7d6/w7NXV1RXpb2cVTUfk276WLFkiZBUnJyeR7ujoKGSVR48eST7n0aNHC5lA0xGpuczNzWn37t2CL0NDQ5H+dlbRdERqLkNDQ/rpp5+ETKDpiNRcb2eVJ0+eSHy9nQlmzJgh0ipmlapVq4r0bt26CVnF09NTpFXMKt26dRPp9vb2QlZ59uyZxNfw4cOFTeCzZ88WaRWziqmpqUjv3LkzPXz4kIiIjh49KvG1cOFCIat0795dpL+dVVQqlcTXkCFDhKwyf/58kVYxq9SsWVOkd+rUScgEJ0+eFGkVs8pnn30m0t/OKi9fvpT4GjRokJAJFi1aJNIqZpXatWuL9A4dOgg98WfOnBFpenp6oqzybwbvuDWXH0T/Bxg0aBA5OzvTunXrREXyROXrrm1tbWnUqFF08uRJSV3BqlWrqFWrVvTTTz/RvXv3ROv3i4uLqVWrVvTVV1/Rrl27JHUFfn5+VL9+fZo+fTr5+vpKahSGDRsmlJdX9JWYmEi2trY0cuRIOn78uMSXm5sbtWzZkhYvXkx3794V+SopKaE2bdoIpeoVfV2/fp3q1q1LU6dOpcuXL0vqCkaMGEFdu3YlNzc3evr0qWitdnJyMn300Uc0YsQIOn78uKRGYf369UJ5+Z07d0S+SktLqV27dvTll1+Su7u7pEbh5s2bgq9Lly5JfI0ZM4a6dOlCa9asoSdPnoh8paamUt26dWn48OF09OhRSV3Bpk2bqHnz5vTjjz9SUFCQxJeTkxP17duXduzYIalRuH37tlBefvHiRUldgaurK3Xu3JlWr14t8ZWenk716tWjoUOH0pEjRyS+tm7dSk2bNqWFCxfS7du3RbUAZWVl1LFjR6FUvWKNwt27d4Xych8fH4mviRMnUqdOnWjVqlUUHh4u8pWRkUH169enoUOH0uHDhyU1Cjt37qQmTZrQggULKDAwUOKrS5cu1KdPH9q2bZukRiE4OJhsbW1p0qRJdOHCBUldwffffy+Uqj9+/FjkKysrixo0aECDBw8mT09PSV3Brl27qHHjxjR//ny6deuWxJezszP17t2btm7dKqlRCA0NJaVSSRMnTqTz589LfE2fPl0oVX/06JHIV3Z2NtnZ2dHgwYPp0KFDEl/79u2jRo0a0bx58+jmzZuiWoCysjLq0aMHff7557RlyxZJjcKjR49IqVTShAkT6Ny5c5K6gpkzZ5KTkxMtX76cHj58KPL15s0bsre3F8rLK9YoHDx4kBwdHWnu3Ll048YNkS+1Wk2fffaZUF5esUYhIiKClEoljR8/ns6ePSvxNWfOHKFUPSwsTOQrNzeXHBwchPLyinUFR44cEUrV/f39Jb569+5Nn332GW3atElSV/D06VNSKpXk6upK3t7ekrqCBQsWUPv27emXX36h0NBQka+8vDxydHSkgQMH0v79+yV1BSdOnBBK1a9fvy6qK1Cr1dS3b1/69NNPaePGjZK6gufPn5NSqaRx48aRl5eXpK5g0aJF1K5dO1q2bBk9ePBA5KugoIAaN25M33zzDe3bt09SV3D69Gmyt7enWbNm0bVr1yS+vvrqK+rRowdt2LBBUmGkUqlIqVTS2LFj6fTp0xJfS5YsobZt29LSpUspJCRE5KuwsJCaNGlCAwYMoL1790p8nT17lj7++GOaMWMGXb16VeJrwIAB1L17d1q/fr2kkufly5ekVCppzJgxdOrUKUmw/OWXX6hNmza0ZMkSCg4OFv3MLioqombNmlH//v1pz549kmql/8feeUdXUe1ffAdI6EWQJr1DEghJIIWOIgjkAiJVaYI0ESniQxGRIoQuvYiAICJFDJ3QewmRGkioCQkhvfdy7/3+/rjvHObMnLlBnj55P+9ea9ZycTzDzpBk9sw9Z38OHTpEdevWpQkTJtCJEyc0996+fftSx44daenSpfyBnSkiIoJq1KhBw4YNo19//VXja+7cueTq6kozZsygwMBATSZwcXGhXr160caNGzVopaNHj/JMcPz4cY2vAQMGvFBW2b17tyYTLFiwgJo3b15gVpFlgpMnT1Lt2rVp/PjxdOzYMc29d9CgQTyrsAd2pujoaKpRo4ZuJli8eDG5uLjoZpUWLVpQjx49pJngzJkzVrPKkCFDeFYJCQkRvndjY2OpZs2aNGjQINq5c6fG17Jly3hWkWUCDw8PMhgMtH79ek0mOH/+PNWqVYvGjRsnzSrDhw/XzSrx8fFUq1Yt+uCDD6RZZeXKldS0aVOeVZT3OKPRSN7e3rpZ5fLly1azysiRI3lWuXv3ruArMTFRyCrqTLBmzRqeVWSZoE2bNtS9e3dau3atJqtcvXpVyCrqe++YMWOodevW5Ovrq5tVBg4cKM0q/2S96INogfiWP1M2fItcaWlpwnI1pTIzM1GsWDEBwv2ic/Py8mA2m4VldOq5pUuX5ksM/lu+8vPzYTQahWVhSqWnp6NUqVL/r3xlZWXBwcFBgIO/6Fyj0Yi8vDxh+ZXNl/5ck8mEnJwcYfnVn+UrOzsbRYoUEZb3/RFf2dnZwnKiV8GX2WxGVlbWK+eLiJCRkaG7zCk9PR0lS5bkyw7/yLlzcnJQqFAhYRndn+UrIyMDJUqU+H/li+2xUy5X+1/xpXePIyKkp6frnvs/9UVEr9y9t6BM8Hfde/Py8mAymf7nMsHfmaHy8/NfuXvvq5oJjEYjcnNz/5JMUJCvf7JeFN9iexC1ySabbLLJJptssskmm2yy6U/Riz6I2lpzbbLJJptssskmm2yyySabbPqvyvYgapNNNtlkk0022WSTTTbZZNN/VTZ8yyugqVOn4s6dO5oKbgAICwvDZ599Jq0GByw4koMHD6JUqVJCBTdg2W80evRoJCYmaqquAeD48eNYuXKlpoKb6csvv8Tt27c1WA4ACA8Px6RJk6TV4IClenz//v2aqmvAsn9m9OjRSEhIkPo6deoUli1bpuvrq6++ws2bN6W+nj59iokTJ8JoNGqqwQELJsXPz0/qKy8vD6NHj0ZcXJwGywEAZ86cwdKlSzW4EKavv/4a169f11SDAxZEwfjx4zmWQ+1r8+bN+O233zRYDsCyH2TMmDGIjY2VVoOfP38eixcv1uBCmGbOnInAwEANLgSwIAo++eQTjplQ7x3asmULdu/eLfVlNBoxduxYREdHS6/XpUuXMH/+fF1fs2fPRkBAgAYXAlgQBePGjeOYCbWvn376CTt37tRgOQDLXsyPP/4Yz549Q9WqVTV7OwICAuDr66vBcjB9++23uHz5stRXQkICxo4dy3EO6r1D27dvx/bt23V9jRs3DpGRkRqMCQAEBgbi22+/1fU1b948XLx4UYMxASw4pY8//hjZ2dlSXzt27MC2bds0uBDAskf0k08+QUREhAbLAVhQALNnz5ZiOQBgwYIFOH/+vNRXcnIyxo4di8zMTKmv3bt3Y+vWrVJfRITx48cjLCxM6uvmzZv45ptvdH0tWrQIZ8+e1eBCAAtOacyYMcjIyNDgLwALVubHH3/UYEyYrwkTJiA0NFSD5QAsKICvv/4agBYXAgBLlizB6dOnNVgOwLIXafTo0UhPT9fgQgBg79692Lhxo66vSZMm4eHDh1JfwcHBmDZtmq6v7777DidPnpT6ysjIwKhRo5CWlia9Xvv378eGDRs0GBPma/LkyXjw4IEGywEA9+7dwxdffCFFiAEW7MexY8c0WA7Ass9u9OjRSE1N1eBCAAvuZv369RosB/M1ZcoU3Lt3T+rr4cOH+Ne//qXra9WqVfD399fgLwDLvrHRo0cjOTlZgwsBgCNHjmDt2rVSXwDw+eefIzg4WJoJHj9+jClTpkgxJgCwZs0aHDp0SIMLASx7tkePHo2kpCTp9Tp27BhWrVqlQZsxffHFFwgKCpL6evLkCSZPnizFcgCWrHLgwAHp9WKZQC+rnDhxAitWrNCgzZimTZuGW7duSTNBREQEJk6cqJtVNmzYgH379lnNBPHx8VJfp0+fxnfffafBhTBNnz4dN27ckPqKjIzEp59+qpsJNm7cqJtVWCbQyypnz57F0qVLNaguphkzZuDatWtWs4peJti8eTP27NmjmwnGjBmDmJgYqa8LFy5g4cKFL51Vxo0bh7y8PA3aDAC2bt2KXbt2FZhVZPdeZVaRXa85c+YUmFVYJtDbf/1PlA3f8j+ktm3bCpXmn3/+OW+2vHTpEsdvODg4UJcuXWjlypW82VKJFKlatarQIBkZGUmNGjXiNe3qBkllfXiZMmV4gyRrtlQiRViDJGu2vHLlCpUvX577Yg2SrNny888/F3yxBsnMzEyKioqixo0b83EPDw+aM2cOb5DcsWMH2dnZEWBBMrAGSdZs2alTJz6XNUiyZsurV69ShQoVeL3322+/TcuXL+fNll9++SWfW6VKFd4gmZGRQTExMeTo6MjHW7ZsSbNnz+YNkrt37xZ8sQZJ1mypRIqoGyR///13XgFub2/PGyRZs+X06dP53MqVK9Pw4cPJz8+P0tPTKS4ujpycnPi4ukHyt99+4wigUqVKaRoku3fvLlStT5o0iTdIXr9+nSpVqsRrx1mDJGu2nDlzJp9bqVIl+vDDD3mzZUJCgoBWUDZIms1m2rt3L6/7L1myJG+QZL569uwpVK1PnDiRTpw4QXl5eXTz5k2qUqUK98UaJFmz5Zw5c/jcihUr0rBhw3izZVJSEjVr1oyPqxskDxw4QEWKFOG+WIMka7bs3bs3n8uaLVmD5O3bt6lq1aoEWFAkrEGSNVv6+voKiAHWdp2WlkYpKSkC8kHdIHno0CGyt7cnwIKwYG3XrNmyX79+fG6dOnV4g2Rubi7duXOH410KFy6sabtWIkVef/11oe06LS2NXF1d+bi6QdLf35+jnEqUKKFpu1YiRWrXri00SAYHB1ONGjW4L2XbNRHR0qVLBfTB4MGDeYNkZmYmubu783F12/WxY8eoWLFiBFjQGuq268GDB/O56gbJe/fuUc2aNQmwoEhYgyRrtlyxYoWAPmANkikpKZSVlSUgMpQNkiaTiU6cOMERU8WKFSMfHx+h2fLDDz/kc9UNkg8ePOA4nEKFCmnarlevXi2gD5Rt17m5ueTh4cHH1W3Xp06dopIlS3Jf6gbJjz76iM9Vt10/fvyY6tSpw32p267Xr18voA+UDZJ5eXkCZkzddn3mzBkqVaoUARa0RteuXYW26zFjxvC51atX523X2dnZFBoayjE9dnZ2mrZrJVKkXLlyvO06KSmJTCYTeXt783F12/W5c+c45oL5Wr16NfelxJ9Vq1ZNaLsODw+n+vXrc1/e3t40d+5c3natxJ+VLVuW+vfvL7RdK/Fn6rbrixcvUtmyZYVMsGrVKt7CrcSfvfHGG7ztOisriyIiIqhBgwbcl7rtWok/K1OmjKbtWok/U7ddX7p0ieM3WCZQZhUlUkSdVZ49e6bJKnPmzOFZZfv27VazihIp0qhRIyETBAQE8KzCMoEyqyjxZ1WqVKGPPvqIZ4Lo6Gghq7BMwLLKzp07rWYVJf5M2Xadn59PgYGBHGFmb2/P265ZVlHiz1hW8fPzo4yMDIqNjRWySosWLYS26927dwuZQJ1VunbtKmSVSZMm8axy7do1nlWKFCmiySpK/BnLKiwTxMfHC1nF3d1dk1VYJpBlFSX+rH79+kLb9Y0bNzhaTZZVlPgzllX27NlD6enplJiYKGQVNzc3Iavs27dPk1WUmUCJP1O3Xd+6dUuaVdRt1/9E4QVbc21Lc18BJSQk8P9+8uQJQkJCEBISguTkZCQnJ8NoNAKwvJ0LDg7m4yaTSZgbGxvLx6KiopCbm4v09HQAABHhwYMHfDwrKwvx8fF8blpaGh97/Pixxld4eDhCQkIQHByMpKQkpKSkID8/n/ticwvy9ezZM8EXADx48IB/XVlZWcLc9PT0F/IVEhKCxMREpKamcl/5+fkv7CsyMhJ5eXlIS0uT+srMzBSul9LXo0ePQETCuSMiIgRfaWlpyMvL477u3bvHx41GozA3Li6OX+vIyEjk5+cLvh4+fMjnZmRkCL4yMjIK9MW+poSEBMGX0Wi06is+Pp6PPX36FPn5+UhNTdX1pZybmZnJxx48eKDx9fTpU+4rPj4e6enpvBFT7Ss/P1+Ym5CQwK/X06dPYTQaBV+PHj3603xlZGRwXyaT6YV9RUREwGg0Ijk5mY8/fvyYz01PTxfmZmVlWfUVGRnJx+Pi4pCRkYGcnByNr+DgYOTl5Wl8sa8pIiICJpMJKSkpUl9paWkaX8HBwQgODn4hX5mZmcjOzn4hX4mJidxXeHg4TCYTkpKS+HhoaCg/d2pqKhITEy0MMlg+6WG+7t+/r/H17NkzPjc2NhaZmZnIysoCYPlE+P79+7q+kpKS+NwnT57AbDa/sK+cnByrvqKiogRfWVlZ/HoV5Cs5OVnjKzExUeMrODgYqampSEpKgtlsFnyFhIQU6CsmJgZZWVnIzMwUfLH5ubm5wtyUlBTBFxEJvsLCwrivlJQUJCcnw2QyAbB8Msbm3r9/H2azWTh3dHQ0H4+OjkZ2djb3RUSCr5ycHOF3o9JXaGio5mtW+mL3XqUvdt579+5Z9RUVFYXs7GxkZGQIvti42ldqaqrgC4DGF/u7ZZmAzZX5iomJEXzl5OTo+srOzhbmFpQJlFnlZTNBcHAwnj17hpycnJfKKo8ePbLqKzExUfD1IpmAXWtZVlHe46xlFZmv8PBwfm6WVZSZgM0NDg7W3HvVWSU3N1c3E2RmZgpzWSYIDg6WZgJZhnrRTBAXF8e/JlmGkt172e9GZVZ5+PCh1QzFsoosE8iuV3x8PPclyyrMV3BwsObeq8wEMl/Ke5zMFzsvywQ2FSxb3/ArIG9vb7Rp0wYGgwFvvfWWsOzJ0dERzZs3xzvvvAODwYCmTZsKywKaNm2Kfv36wcfHB127dhWWWeTm5sLJyQnvv/8+DAYDWrVqJSw5aNSoETp37gyDwQAfHx/Url1b8OXp6QlPT0/uS7mMp0mTJnBxcUGXLl1gMBjQrFkzja++ffvCx8cH3bp1E3zl5eXByckJAwYMgMFgQOvWrTW+OnXqxH3VqVNH48vd3R0GgwGdOnUSfOXn56NZs2b863JxcRF8OTk54b333oPBYEC3bt1QsWJFYa6zszP69evHfSmXrzVu3BhvvfUW91W3bl3Bl4eHB5o1a8Z9KZfxEBGaNm2Kt99+GwaDAc2bNxd8OTs7o3fv3txXpUqV+JjRaISzszP69OkDg8GANm3aaHx17NgRPj4+MBgMqFevnsaXo6MjDAYD3n77bcGXnZ0dnJ2d0alTJ/j4+MDNzU1zvd59913uq3LlynzMZDKhadOm3HebNm2EZWKNGzdGu3btYDAYYDAYUL9+fcFXy5Yt0aBBA+5LuYzH3t4ezs7OePPNN7kv5XI/Jycn9OrVCwaDAd27dxd8mc1muLi48PG2bdtqfLVt25ZfrwYNGgi+WrRogTp16sBgMKBz586Cr6JFi8LJyQkdOnSAwWCAu7u74MvR0RE9e/bkvqpUqSL4at68OXr27AkfHx+0b99e8NWkSRO0atWKX6+GDRsKvtzd3VG9enXuS7m8qESJEnBycuLXu0WLFoKvxo0bo0ePHtxX1apV+RgRwdXVFT4+PtyXcplYkyZN4OXlxX01atRI8OXm5obKlStzX8oltKVLl4aTkxP//dayZUvBV5MmTfh5u3fvjjfeeEPw5ebmhm7dusFgMKBDhw4aX56envzfsVGjRsL3rpubGypUqACDwYAuXboIvsqWLQsnJye0bt0aBoMBHh4emuvFztu9e3dUq1ZN8NWiRQt07doVPj4+6NChg7Acy9HRES1btuTzGzduLPhq3rw5ypQpAx8fH7zzzjvCEtry5cvD0dERI0aM4L6Uy/0aN26M7t27c1/Vq1cXfLVs2ZL/7uvYsaPGV4sWLfj8Jk2aCL5cXV1RokQJ7ku5VDUjIwOOjo4YPnw4DAYDPD09BV+NGjXi/07du3dHjRo1BF+enp78d3rHjh2FJdpNmjSBu7s79+Xo6Ki5Xvb29tyXckloVlYWnJycMGzYMBgMBnh5eWl8sX8nHx8f1KxZE0p5e3vjzTffhMFgwJtvvin4cnR0hKurK/+6nJycBF/s3sLuvUpf2dnZcHJywpAhQ2AwGODt7a3xxe7p3bt3R61atQRfrVq14r9j3nzzTSETNGnSBK6urvzrUmeCZs2aIT8/HwaDAV27dhWWhObk5MDJyQmDBg3ivpT33oYNG6JLly78eqkzgbe3N/+ZUWeVJk2a8Kzi4+OjyQTOzs7o27cv96XOBM7OzgVmFeZLlgk8PDwKzCo+Pj6aTNC0aVN+b5VlFWdnZwwYMAA+Pj6aTNCoUSOrmcDT0xNubm7SrGI0GtGsWTOrmUAvqxiNRp79ZFmlUaNG6NixI/elzgQtW7ZE06ZNrWYV9vPq6ur6h7IKu54+Pj5o27atJquw72u9rMLuCZ06dRLuvYUKFYKzszO/3n80qzRr1gy9e/fmvv5oVqlfv75uVnFycuK/R9RZxaaCZcO3vAIiIl1+kbWxv3Kuzderc272M/qqfc02XzZfNl82XzZff+7cv/LcNl82X3+1L+DV+5n6O339k2X3gvgW2yeir4CsfRMX9A3+V821+Xp1zm3zZfNl8/XqnNvmy+brf/XcNl82XzZf/91z21SwbJ8f22STTTbZZJNNNtlkk0022fRfle1B9BXQgQMHhM34Sj19+hSnT5/W3fR89uxZXnCgVk5ODvbt28fLCdS6desWrl+/zpctqHXw4EHExcVJx549e4ZTp07p+jp37hwvOFArNzcXe/fu1fV1+/ZtXLt2TdfXoUOHEBsbKx2LiorCyZMn+WZ7tc6fP8+LBNTKy8vD3r17hXICpYKCgvD777/zwg+1Dh8+jJiYGOlYTEwMTpw4oevrwoULePjwoXQsPz8fe/fuFUoAlLp79y4CAwNfyldsbCyOHz+u6+vixYu4f/++dMxoNFr1FRwcjICAAF1fR44cQXR0tHQsPj4ex44d4yUAMl/37t2Tfo+YTCb4+fkJ5QRKhYSEWPXl7++PqKgo6VhCQgKOHj2q6+vy5csICQnR9bV3715dX/fu3cPly5d5QYpaR48exbNnz6RjSUlJ8Pf354VFal25cgXBwcFSX2azGXv37hUKi5R68OABLl26pOvr2LFjiIyMlI4lJyfjyJEjur4CAgJw9+5dqS8iwt69e4WCJ6UePnyIixcv6vo6fvw4nj59Kh1LTU3F4cOHeTGQWlevXsWdO3d0fe3bt0/X16NHj3DhwgVdXydOnEBERIR0LC0tDQcPHtT1FRgYiKCgIKu+lEVKSoWGhuL8+fO86EatkydPIjw8XDqWkZGBAwcO8IInta5du4bbt29b9aUsLFIqLCwM586d0/V16tQpXV+ZmZnYv3+/rq/rHO+FBAAAIABJREFU16/j1q1bur72798vFJEoFR4ejrNnz+r6On36NJ48eSIdy8rKwv79+3mRklo3btzAzZs3de9x1jJBREQEzpw5o3vvPXPmjG4myM7Oxr59+3R93bx5Ezdu3HgpX5GRkQVmFWuZ4O/MKgVlAj1fBWUCa1klOjq6wKxSUCbQyyp37tz5S7PKgwcPpGMFZYK7d+/i6tWrL5UJYmNjC8wEf1VW8ff3f+msYlPBsnFEXwH99NNP6NmzJ44ePYq4uDiBx+fg4IC33noLc+fOxa1bt5CXl4dq1arxUoWbN2+iVatW2L17NyIiIgQen52dHf71r39hzJgxuHjxItLS0lC5cmVe2pGVlYXmzZvj+++/579YlHy5n3/+GT169IC/vz/i4uIEHp+DgwM6d+6M2bNn4+bNm8jJyRH4ckFBQfD29sbOnTsREREhcO/s7Owwbdo0jBw5EhcvXkRqaqrAvcvOzoarqyvWrVsn9bVz5074+PjgyJEjiI2N1fjq2rUrZs6ciZs3byI3N1fwFRwcDC8vL+zcuRPh4eEaX9OnT8dHH32ECxcuIDU1FZUqVeK+8vLy4OrqirVr1+LevXsaX7t370a3bt24LyWPz97eHgaDAd988w1u3LiB7Oxswdf9+/fh4eGBX375BeHh4QKPz87ODt988w2GDx+O8+fPIyUlRbhe+fn5cHNzw+rVq/nDmZIv5+fnh3feeYfffJS+HBwc0LNnT85AZb5YqcLjx4/RsmVLbN++HU+ePEHRokVRrVo1XrwxZ84cDBs2DOfOnUNKSgoqVqzIS06MRiPc3d2xatUq/nCm9HXgwAF06dIFhw4dQkxMjMCXc3BwQO/evfHVV1/h2rVrGl9hYWFo2bIlfv75Zzx58kTD4/P19cWQIUNw7tw5JCcnC9w7s9mMFi1aYMWKFQgJCdHw+A4dOoTOnTvj4MGDiI6OFviF9vb26Nu3L7788ktcu3YNWVlZgq+IiAi4u7tj27ZtCAsL0/hauHAhBg0ahLNnzyIpKUnwxcpmli9fjuDgYI2vo0ePolOnTjhw4ACio6MFdrC9vT0GDBiAqVOnIjAwEFlZWQL3LjIyEm5ubvjpp58QFhamYfQuXboU77//Pk6fPo2kpCQN987T0xPLli3D3bt3NTy+48eP46233sL+/fsRFRUlcO/s7e0xePBgTJkyBYGBgcjMzBR8xcTEwNXVFVu3bkVoaKjG17JlyzBw4ECcPn0aiYmJgq9ChQrBy8sLS5cu5b6U/MLTp0/jzTffxL59+/Ds2TPBV5EiRTBs2DB89tlnuHr1KjIzMwXuXWxsLJo3b44tW7YgNDRUww5euXIl+vfvj5MnTyIxMVHg8RUqVAitWrXC4sWLcefOHRiNRuF6nT17Fh07dsTevXvx7NkzgXtXpEgRjBw5EhMnTkRAQAAyMjIEdnBCQgKaN2+OH3/8EY8fP9bw+NasWYO+ffvi5MmTSEhIEHh8hQsXRps2bbBw4ULuS8m9u3jxItq3bw8/Pz9ERkYKvgoXLozRo0dj4sSJuHLlCjIyMoTrlZycDBcXF2zevBmPHj3S+Pr+++/Rp08fnDhxAgkJCQKPr0iRImjXrh0WLFiAoKAg5OfnC76uXLmCtm3bYs+ePYiMjBQYvYULF8Ynn3yC8ePH48qVK0hPTxfYwSkpKXBxccHGjRvx6NEjDaN306ZN6N27N44fP474+HjBl729Pdq3bw9fX1/cvn2bcxXZvTcwMBBt2rTBr7/+iqdPnwq+ChUqhAkTJmDcuHG4fPky0tPTBX5heno6XFxc8MMPP+Dhw4caXz/++CN69eqFY8eOIT4+XsgE9vb26NixI+bNmyf1df36dbRu3Rq7d+/G06dPhUxQqFAhfPbZZxg7diwuXbqEtLQ0gdGbkZEhZAI7O5HRu23bNvTo0UOaVezt7dGpUyfMmTMHt27d4gxo5uvWrVto1aoVdu3aJc0qU6dOxahRo3Dp0iWkpqYKvrKzs9G8eXOsX79e6mv79u0wGAy6WaVLly6YNWuWNBPcuXPnpbNKbm4umjdvjnXr1vGHIKWvXbt2CVlFfe9lWeXGjRucQ8l8hYSEwMvLCzt27JBmla+//ppnFXUmKCir/Prrr7pZxcHBAT4+PpgxYwauX7+uyXYPHjzQzSqAhQXKskpycrLA6DUajVazyt69e4Wsorz3Ojg4oFevXvj666+lmSA0NFTIKup777fffothw4bh7NmzGl8mk6nArNK5c2ccOnRIkwkcHBzw3nvvYdq0adyXjB38T5SNI/o/JMZ7Uh61a9emmTNn0po1azRjjBN47Ngxgc/GjgoVKtDo0aPp1KlTmjHAwuPbsGEDffzxx5qx4sWL07vvvktBQUGcHag8atWqRTNmzBC4cexgPD5/f3+Bg8aO8uXL08iRI+n06dNSX02bNqX169fTp59+KvXVs2dPun37Nmf0KY+aNWvS9OnT6YcffpD6atOmDR0+fFjgoCl9jRgxgs6ePSv15ezsTGvXrqWJEydqxooVK0Y9evSgmzdvUunSpTXjNWrUoGnTptHmzZulvlq3bk0HDx4UmK3seO2112j48OF04cIFqS8nJydavXo1TZkyRTNWtGhR8vHxoevXr3MOrfKoXr06ffnll7R161bNmN2/eXz79+8XOGjsKFeuHA0bNowuXrwo9eXo6EgrV66kL774Quqre/fu9Pvvv3OGmvKoVq0aTZ06lbZt2yb15e3tTXv37hWYrewoW7YsDR06lK5cuSL11aRJE1q+fDl99dVXmjEHBwfq1q0bXb16lbPKlMcbb7xB//rXv2jHjh1SX15eXvTbb78JHDR2lClThgYPHkxXr16V+mrcuDF99913NGPGDKmvd955hwICAjgnVHlUrVqVpkyZQrt27ZL68vT0pN27dwscNKWvQYMG0e+//y711ahRI1qyZInAZ2OHvb09denShS5fvsy5l2pfkydPpj179kjP7eHhQTt37qT33ntPM1a6dGl6//336fr169K5DRs2pEWLFtHcuXOlvt5++226ePEi50sqjypVqtCkSZPIz89Peu6WLVvSL7/8Qv3795f6GjhwIN24cUM6t0GDBrRgwQKBJav01alTJzp//jw1bNhQM165cmWaMGEC7d+/X3pud3d32rZtm8BsZUepUqWof//+dOvWLenc+vXrk6+vr8CSZQfjBJ49e5aaNGmiGa9UqRKNHz+eDh06pOtr69atNGTIEM1YyZIlqV+/fhQUFCSdW69ePZo7d67AklX6evPNN+nMmTMC/48dFStWpHHjxtHhw4el53Z1daUtW7YIzFalr759+9Ldu3elc+vWrUtz5syh5cuXa8YKFy5MHTt2pFOnTglMYHa8/vrrNHbsWDp69Kj03M2bN6dNmzYJzFZ2lChRgt577z0KDg6Wzq1Tpw7NmjWLVq1aJfXVoUMHOnHihMC4ZQfLBMePH5ee28XFhTZu3CgwW5W+evfuTXfu3OGsReVRUFZp164dHTt2jLy8vKS+Ro0aVWBWUTJb2VG8eHHq1asXBQUFUdGiRTXjLKt8//33mjGWVY4cOUKtW7fWjJcvX54++ugj3UxgLasoM0GJEiU04yyrbNq0SeqrTZs2dOjQIWrfvr1m/LXXXqMRI0bQuXPnpL6cnZ1pzZo1NGnSJKkvg8FAN27c4Hxc5cGyipJxq/TVunVrOnDggMBsZUe5cuXoww8/tJpVVq1aJfDl2cGyyrVr1ziHVnmwrKJk3LKDZZV9+/ZR586dpb6GDRtGly5dkvpydHSkFStWCHx5pa9u3boJDHjlwbLKzz//LPXl7e1Nfn5+ZDab/+5HjL9NeEGOqO1B9BXQwIED+Tcwg1efP3+ejEYj3b17l6pXr07A81C6evVqDolW3sSV8OrMzEyKj4/nv2RZWJ47dy6HV584cYLs7e0JkMOrlUB4Bq9mUO2QkBAeQBlUe+XKlRwSrbyJq+HViYmJ1LZtW+7L09NTgGqfOnWKPwSXLl2aw6sZJHrYsGH83I0aNaIpU6ZwqPa9e/c4eN3e3p46d+4swKuVQHgGr963bx9lZGRQUlKS8Mvfw8OD5syZw+HVZ8+e5Tc8GbxaGS6U8Oq8vDx68OAB1atXj/ti8GoGiV63bh2fW7lyZRoxYgSHaqekpAgPqi1bthTg1efPn+cP5zJ49ejRo/ncBg0a0OTJk7mvhw8fcsC5El7NINHKB/tKlSrR8OHDyc/Pj9LT0yk1NZXeeustPt6iRQsBXn3x4kV+I5bBq5Xhon79+jRp0iQOr378+DEHnMvg1coHewavZlDt9PR04QFaDa++fPkylSpVioDn8OpNmzZxeLUyXNSrV48mTpzI4dWhoaE8sCvh1Q8fPiQiEm6WFStWpGHDhtGePXsoLS2NMjIyhAdoNzc3mjFjBgUGBpLJZKKAgAD+MqNEiRLUq1cv2rhxI0VHRxMR0eTJk/ncOnXq0KeffkrHjx+n3NxcevLkCQeJs1C6ZMkSDtVWAuFff/11Gjp0KO3evZtSU1MpKyuLunXrxsebN29OX3/9NV29epVMJhMFBgZS2bJlua+ePXvSDz/8wH0pgfC1a9em8ePH07Fjxyg3N5fCw8P5gwR7gbZ48WK6f/8+ERHt3LmTz61QoQINGTKEdu3aRampqZSdnS082Lu4uND06dMpICCATCaTEFyKFy9OPXr0oA0bNtCzZ8+IiIRwUatWLfrkk0/o6NGjlJOTQxEREeTi4sJ9tWvXjhYtWkT37t0jIqJff/2Vzy1fvjwNGjSIdu7cSSkpKZSbm0s9evTg482aNaOvvvqKrly5QiaTia5fv04VKlTgvgwGA33//ffclxIIX7NmTRo3bhz5+/tTTk4ORUZGkqurKw9/bdu2pYULF1JISAiZzWby8/MjOzs7wdeOHTsoOTmZ8vLyhBcOTZs2pWnTptHly5fJaDTSzZs3eaAqVqwY+fj40Lp16ygyMpKIiGbOnMnn1qhRgz7++GM6cuQIZWdnU1RUFLm7u3Nfbdq0oQULFtDdu3fJbDbT/v37ua/XXnuN3n//ffrll18oOTmZjEYj9e7dm5/b2dmZvvzyS7p06RIZjUa6desWf/nDwt/atWvp6dOnRET07bffCqF07NixdPjwYcrOzqbo6Gjy8PDgvlq3bk3z58+nO3fukNlspkOHDvEXveXKlaOBAwfS9u3bKSkpiUwmE/Xp04ef28nJib744gu6ePEiGY1GCgoKoqpVqwq+1qxZQxEREUREwguH6tWr05gxY+jQoUOUlZVFsbGx/CUxC8vz5s2joKAgMpvN5O/vzx/qypYtSwMGDKCff/6ZEhMTiYioX79+QlieOnUqXbhwgYxGI925c4e/lFJmgvDwcCIi4YVDtWrVaPTo0XTw4EHKysqiuLg4/pKYheV58+bR7du3yWw207Fjx6hIkSLcV//+/Wnbtm3cl/JFCMsqLBMEBwdTjRo1hEywatUqnlW+++473aySkJBAbdq0EbKKMhOcPHnSalZRvghp3LixkAnUWaVz585CVlmxYoXVrKJ8ec0ywc2bN8lsNtPp06etZhXlixCWVc6cOUP5+fl0//59Iau8/fbbtGLFCgoNDSUiEh7sWVZhmSA5OZk6dOggZILZs2e/cFYZOXKkbiYoKKsoP4SQZRXlg2qLFi2ErHLhwgVpVmGZQPkihGWCU6dOUV5eHj169MhqVtm4caMmq7BMkJaWRp06deLj7u7uQla5dOkSzyolS5ak3r1706ZNm7ivTz75RJMJlFmlcePGmqzCMsE/WXjBB1Fba+4roJo1a+K7776TcpWKFy/O+VlqBiQbnzlzppQBWahQITRu3BgjRozQcJUAgIgwbtw4zlpU8p4AoHr16li6dKmUq1SiRAnOeFRzlZivb775RsqALFy4MBo2bIhhw4ZpGJDM19ixY6UMSACoVq0alixZImVAlihRAh06dMCiRYs0DEgAcHBwwNdffy1lQNrb26NBgwYYPHiwhgHJfI0ePRoGgwHt2rXT+KpatSoWL14sZUCWLFkSbdu2xfz58zUMSKUvHx8fDQMyPz8f9evXx/vvv69hQDJ99NFHUgYkAFSpUgWLFi2SMiBLlSqF1q1bY+7cuRoGJLsmX331lZQBaTQaUb9+ffTv31/DgGT68MMPpQxIAKhcuTIWLlwoZUCWKlUK3t7emD17toYBCVi+h6ZNmyZlQJpMJtSrVw99+vTRMCABS8vd0KFDpQxIAKhYsSIWLFggZUCWLl0aHh4emDFjhoYBCVh+5r788kspA9JkMqFOnTpYt24dfHx8pL4Y30/NgASA119/HfPnz5cyIEuVKoWWLVti+vTp6NKli8CAZL6++OILKQPSbDajTp06WLt2rYYByeYOHDhQyoAELOxLX19fKQOydOnScHd3xxdffKFhQLKveerUqVIGJBGhdu3aWL16tZQBWbhwYc7RUzMgAeC1117DvHnzpAzIMmXKwNXVFZ9//rmGAcn0r3/9S8qAVPqSMSCLFCnC+X9qBiRgYZjOnTtXyoAsXbo0XFxcMHnyZA0DkmnKlClSBiQRoVatWli5cqWUAWlvb8/ZumoGJPP17bffSnnVpUuXRtOmTTFhwgQNA5Lps88+kzIgma8VK1bAYDBofDk4OHB+n5oByf7uOXPmSBmQjFM7btw4DQOS/d2TJk2SMiCZr+XLl0sZkEWLFuUMUTUDErD8zM2ePRs+Pj4aBiQRwdHREWPHjtUwINn4hAkTpAxIAKhVqxaWLVsGg8Gg8VWsWDHO71YzIAHLPXDmzJlSBqSdnR0aN26MkSNHahiQzNf48eOlDEjAsrzTWlZ5++23rWaVb775RsqALFy4MBo1aoThw4dbzSoyBiRgyQQvm1WKFSuGGTNmSBmQRYoUQcOGDTF06FB069ZNmgnGjBmjmwkKyirt27fHwoULrWYCWVbJz89HgwYNMGjQIGlWAYDRo0dLedWA9axSqlQptG3bFr6+vujSpYvU1/Tp06W8apYJBg4ciG7dumkyARFxRvIfzSolS5ZEq1at8O2330ozQZEiRaxmlXr16qFfv34vlVUqVapkNat4eXlh5syZ6NKliyYT2FSwbBxRm2yyySabbLLJJptssskmm/4U2b0gR9TWmmuTTTbZZJNNNtlkk0022WTTf1W2B9FXQHo12WzM2qfW1uYajUZdhEBBc22+Xh1fJpNJFyFg8/W/48tsNr+yvvTQBv+pr/z8/Jf2RUSvrK+C/i3+E196CAGbr/++r//kXvKyvgoa//94j7P5+mNzTSbTK+vrVbzH/Z2+bCpYNnzLK6Dhw4fjp59+0qANAAvewNvbGw8fPtSgDQAL3mD69OkatAFgCZjt27fH+fPnNcgFwII36NOnD6KiogR0BtPIkSOxefNmqa+4uDh4e3vj/v37Ul8rVqzAtGnTkJSUxBECTESEDh064OzZsxrkAmDhZ7377ruIiopCyZIlOXKBacyYMdi4caMGuQBY8AZeXl64d+8eihQpgho1agi+1qxZg6lTp3K0gXJPERHhzTffxOnTpzXIBQC4dOkSevbsqUEuMI0bNw7ff/+9BrkAWDiPXl5eCAkJ0aAgAGD9+vWYMmWKBrnA9Pbbb+PEiRMa5AJgYR76+Pjg2bNnHCGgnPvpp59i3bp1GuQCYMEbeHl54e7duxqEAAD88MMPmDRpkga5AFj2G3Xp0gXHjh1Dfn4+atSoIfi6du0aunbtqkEbME2aNAmrV6/WIBcAC0/R09MTd+7ckfravHkzJkyYoEEuMF9du3aFv78/8vPzBdwRYEEedenSRdfXlClTsHLlSg1yAbDgDTw9PREUFMQRAkpfW7duxSeffKJBLjD5+Pjg8OHDGuQCYEEederUSYM2YJo6dSqWLVumQS4AFp6il5cXbt26pUEbABa8wdixYzXIBaaePXviwIEDGjwUYEEevfXWWwgPD5f6+uqrr7BkyRINHgqwYBe8vLxw48YNqa+dO3di1KhRGuQCU+/evbFv3z4NQgCwII86dOigQRswff3111i0aJEGuQBYGMteXl64fv06AGh87dmzByNGjNDgoQDL91efPn3g5+enQS4AFr5p+/bt8eTJE6mvWbNmYf78+Ro8FGAJNd7e3mBbWNS+/Pz88OGHH2qQC8xX//79sXv3bun1CgsLQ9u2bREWFqZBLgAWFNO8efOQkpIioA0AywNfq1atcPXqVQ3aALDgDYYMGaJBLjBf77//Pnbt2qVBLgAWXmebNm0QGhqqwUMBFhTTnDlzNMgFwPKg0Lp1a1y5ckXq68iRI/jggw80eCjma/Dgwdi+fbsUuRAZGYnWrVvj8ePHGhQEACxYsACzZs3S4KGYrzZt2uDSpUsaDBNgYe8OHDgQ0dHRKF26tOYeN3ToUGzbtk2DhwIsrOxWrVrh0aNHsLe319zjlixZghkzZmjwUIAlkLdr1w4XLlyA2WzW3HtPnTqFfv366WaCESNGYMuWLRo8FGDJKq1atcKDBw90s8pXX30lxUOZzWZ06NAB586dk2aVM2fO8KyixDAxjRo1SjerxMfH86wiywQrV67EF198Ic1QRISOHTvizJkz0kxw4cIFvPvuuxo8FNPYsWPxww8/SLNKYmKi1Uywdu1afP755xo8FNNbb72FU6dOSTPB5cuX0aNHDw2GiemTTz7hWUXtKzk5mftSY5gAS1b57LPPdLNK586dceLECWkmCAwMRLdu3XR9TZgwAWvXrpX6Sk1NhaenJ+7evYvChQtrrtfGjRsxceLEArMKu/cqfV2/ft1qVpk8eTLPKupMkJ6ezjOBLKv8k2XDt/wPSdmQp2yRvXnzJl29epU3mOHfjXGsmS0hIUFTya9skX369Clvp4WiMY61yO7fv5+3h+LfjXGsRTYzM1ODCvDw8ODNbNeuXeMNZpA0s6kr+ZUtspGRkUI7LWuMW758OYWGhtLBgweFevEqVaoIzWzKNl9AbJG9fv06b1tlvpQtssqGPCga406dOkXPnj0Tmujs7e15M9vjx4/p8OHDvD0U/26MU7bIqlEByhbZmzdvCngEdYusupJf2SIbHR0tNNGpW2T9/f2F2nN1i6waFeDu7s5bZG/fvs3bVgGxRTY2NlZo8wXEFtnY2FihiU7dInvs2DHeHgo8b5H99ddfKS0tTYMKcHV15S2yQUFB5OzsLPhStsh+//33vKUTsCAXJkyYQMePH6e4uDihyl3dInv8+HEBHaNukVWjApQtsnfv3qVmzZrxMXWL7MaNGwVfderU4S2yCQkJ1KVLF8GXskX21KlTVKlSJcGXskV2woQJgi9li2xwcDBvgWW+WItsVFQUbdmyRcBE1a5dm7fIJiYmUteuXQVfyhbZ06dPU5UqVfh4hQoVaPDgwbxF9rPPPhN8KVtk7927x1tgAW2L7E8//SQgIWrVqsVbZJOTk6l79+58TNkiGxwcTGfOnKE33niDj5cvX54++OAD2rFjB6WkpAhtvoDYInv//n3eAgs8b5Fdv349RUZG0vbt23l7KGBpt2UtssnJyUKbr7pF9ty5cwJqR90iO23aNMGXskX24cOH1LJlS8FX9+7deYvsjh07eHsoYGm3ZS2yqampQpuvukX2woULvNUU0LbIKtt8AbFF9vHjxwIqrGjRotS1a1feIrtr1y4B96VskU1PTxfafFmLrK+vLwUFBdGlS5cEBFC5cuV4i2xSUpIGH6RskQ0LCxOwIEWLFhVaZPfs2UPFihXj48oW2YyMDKHNl7XIzp07l27fvk2XL1+m2rVr83F1i6waH6RskX3y5ImAMFO2yIaHh5Ofn5+AIVO3yCqxRuoW2YCAAAFNpG6RnT9/vuCLNd6fPXuWwsPDeTst88VaZJ88eUL79u2jkiVL8nF1i6wSa8SyCmuRDQwMpPr16wu+lFll8eLFgq9GjRrRZ599RmfOnNFkFWWLbFhYGB04cEDIKuoW2Q8++EA4t7JF9tq1awIySZ1VlG2+gCWrsBZZWVZhLbKhoaF06NAhaVbx8/OjjIwMDdZI2SJ748YN3rYKaBvvV65cKcxt0KABb5GNiooSmvSVLbLWsgrLBMOHDxfOrWyRvXXrltWsoiQPAJaswlpkY2JihCb9F80qe/bsofT0dKHNFxAb74OCgqRZZePGjRQTE6NBCrJMUFBWefDggTSrDB06lGeVsWPHCudWZxUlYoplFWWz/D9VsOFb/nck44iy0KVEbyiP8uXL09ChQ6UsM8ASBtUBkR0sdClvwsqjRo0a9Nlnn0k5oix0yXhjgCV0DRkyhNzc3KTjzs7OVn11796d+vbtq+tr8uTJUo4oC13qXxhKX4MGDRJCnvJwcnKS8jiB59X9yhcGyqN69eo0ceJE4UbJDha6ZMxWwBK6Bg0aJOXBApbQZc1X165dacCAAdLxatWq0YQJE4QbktKXt7e3UEuuPMqWLUvvv/++lAcLWEKXjAkGPEcKyJiHgCV0jR8/XvjFr/Tl5eVF48ePl84tU6YMDRgwQAhTyoOFLj1fXbp00YQWdlStWpU++eQTKTOMhS5rvvr37y9lvwGW0KXni2GG1C9Y2FGlShX6+OOPOUpCfXh4eEh5doAldPXr10/KfgMsoUv9wKb09fbbb0sZkYAl3IwdO5bjpdRHy5YtNQ/P7ChVqhT16dNHCAfKo0GDBrrXi4UuJcZJ7WvMmDFSvilgCYPWfL333ntSJh1gCV1Tp07V9fXmm29K2ZWAJXSNGjVKyjcFLGFQxioGniMFZPxcwPKCSO/fkYWuESNGSMcrVqxII0eOFB4ilIerq6uUSwhYXni8++67wgsD5VG3bl1dX+wFkTp8suP111+nESNGCGH9j/jq1asXGQwG6Xjt2rWt+mrfvr2urwoVKtCHH35Ijo6O0nEXFxcBtaQ8GA+7Z8+e0vFatWpZ9dWuXTvdTFChQgUaNmyYlLsKWDKBNV9tOnIfAAAgAElEQVQGg4Heffdd6XjNmjXp888/l3JEWVYpKBPoZZWmTZsWmFVkvGHgeVaRcURZVrGWCQYPHiy8kFIezs7OuvfeF80qMo4oyyoFZQKGJVIfBWWVrl27FphVZMzzgrIKywQyHixgySp6v7NfNKvImOcsq8hYsszXwIEDpTxYoOCs0qVLl780q9y9e/fvfsT42wTbg+j/jtgbTBm3KzMzk78FUnO7iIhOnDgh/EApuV15eXk8dKvfuBIRPX36lEqVKiVleRIRf4Mp43ZlZmbyT2DU3C4iotOnT3Nfam5XXl4eD7fsjSv7FJaIKCoqir9lVHO7iJ7zyGTcrqysLP4JjPKNK/N1/vx5AuTcrvz8fB4i1W9ciYiio6P5Q52a20VE/A2m8o0rY3lmZWXxh2A1t4uIOHBZxu3Kz8/noUj9KSwRUWxsLH/LqOZ2ET3nkcm4XdnZ2eTt7U2AlttFRBQQEECAnNtlNBp5+FB/CktEFB8fz3+Bq7ldRMRB4zJuV3Z2Nr+xqLldRES///472dnZSbldRqOR37TULE8iooSEBP6wqXzjajKZiOg5j0z9xpX5Yg+byjeuubm5RER048YNsrOz4+B79saV+WIPjOxTWPbGlYgoKSmJf/KofOPKfG3ZsoWA5yFb+cY1JyeHP2yqGaNERLdv36ZChQrx8K9keZpMJh5Q2aew7NNhIqLk5GT+EMw+HWYsTyLiQG8lyzMqKor7YkxXJWM0JyeHiIju3LlDhQsX5uFfyfI0mUw8QLBPYXft2kUpKSlERJSSksIfgtmnw4zlSUS0Y8cO7kvN8szJyeEPdWrGKBFRSEgIFSlShAoVKkTt2rUTWJ4mk4m++OILArSMUSKi1NRUqlmzJgHPPx2+fPky98UYpepPYYmIcnNz+aetjDHKWJ5ERPfv3yd7e3se/hcsWEDBwcFkNpvJbDbT9OnTCbCEbPbpcHJyMhERpaWlcW4h+3SYsTyJiPz8/Liv7t27C4zR3Nxc/vDEGKOM5UlE9OjRI3JwcBA+hWWMUbPZTDNmzOC+2KfDSUlJRESUnp7OH4KdnZ0FlicR0YEDB3iYVTNGc3Nz+QtVxhhlLE8iotDQUCpWrJjwKSxjjJrNZpo9ezax8K/8dJiIKCMjg3+S5uTkJLA8iYgOHz4shGwlYzQvL48/DFSrVo3GjBnDWZ5ERE+ePKHixYsLLE/GGCUi/mmrjDGamZnJH4LV3HEiomPHjvF7r5o7npeXxx8G3njjDRo9erSQCSIiIqhkyZICd5wxRomIFixYoMkqykzAVrGoueNERCdPnrSaVQYNGiRkAvYpLBFRZGSk1ayyZMkSIauoMwF7CFZzx4mIzpw5w++96qySn59PQ4cOFTIB444TFZxVli1bJmQVJcszKyuLPwSzFWPKrHLhwgWrWYV9qqlmeRIRxcTE8Ic6WVZhK7Bk3PGsrCz+EPwyWWXUqFFWs0r58uV1s8ratWu5LzV3vKCscvXqVSGrKLnjRqORv5DQyypslRTLKow7TkS0YcMGIRMouePZ2dn8xbgyq7B77z9ZtgfR/yGtWLFCCNlKhYaGCj9Qau3cuVMI2UplZ2eTr6+v8AOl1Pnz54UfKLVWrVolhGylwsPD+RJMmXbv3q3rKycnh3x9fYWQrdTFixf5EkyZVq9eLYRspSIiIvgSTJl+/fVXIWQrlZubS76+vnT16lWpr8uXL1tdbrFmzRo6duyY1NezZ8+E8K/Wb7/9xpdgqpWXl0fz588Xwr9SAQEBtGHDBh6y1Vq3bp0QspWKjo6mRYsW8ZCt1t69e4WQrVR+fj7Nnz9fCP9KBQYG0vr163V9rV+/nvz9/aW+YmNjhfCv1r59+4SQrZTRaKQFCxbQ5cuXeThT6tq1a0LIVmvDhg1C+FcqPj6eL8GU+Tpw4ABfginztXDhQiH8K3Xjxg0hZKu1ceNGIfwrlZCQQAsWLOAhW61Dhw4JIVspk8lEixYtEsK/Urdu3RJCtlqbNm0Swr9SSUlJNH/+fCFkK3XkyBEhZCtlNptp0aJFQshWKigoiC/BlOnHH38Uwr9SKSkpNH/+fCFkK3X06FHhhaDa1+LFi4WQrdTdu3eFkK3W1q1bhfCvVGpqKvn6+gohW6ljx44JLwTVvpYsWSKEbKVCQkKEkK3WTz/9JIR/pdLT08nX11cI2UqdOHFCCP9qX0uXLhVCtlL3798XQrZa27ZtE0K2UhkZGeTr6yuEbKVOnTolvBBU+1q2bJkQspV6+PChELLV2r59u66vrKws8vX1FUK2UmfOnBFeCKq1fPlyIWQr9fjxY+GFoFo7duwQQrZSLBMoXwgqde7cOeGFoFrWskpYWJjwQlCtXbt2FZgJlC8Elbpw4cJ/nFX0MsHu3buFF4JKsUygl1UuXbpkNRNYyyqRkZFWM8GePXt0swrLBNayivKFoFpr164VXggqFRUVRYsXL+YvBNWyllUKygQBAQHCC0G1rGWVmJgYq5mgoKyyYMECXV+///678EJQre+//578/f2l997Y2FjhhaBNz/WiD6I2jqhNNtlkk0022WSTTTbZZJNNf4r+NI6onZ1dMTs7u6t2dna37Ozs7trZ2c3695/XsbOzC7Czs3toZ2e3087OzqGgc9lkk0022WSTTTbZZJNNNtlkU4H4llmzZpkA/EJEK2bNmrUBwLxZs2bdATADwGYiGj1r1qxOAN6YOXOm1Y87bfgWub777jukpqZKa5/DwsKwYcMGTR01044dO3D37l1NHTVgQRTMmzcPDg4OmjpqwIJJ8ff316AzmJYvX47k5GSpr/DwcKxfv17X186dO3Hnzh2pr9zcXMybNw/29vZSXxcvXsThw4c1NdlMK1asQGJiotTX06dPsXbtWimiAgB2796NW7duadAZgAWdMG/ePBQpUkSDXAAs+JaDBw9q0BlMq1atQnx8vAa5AFgq91etWqXra8+ePbh586YGnQFY0Am+vr4oVKiQ1FdAQAD279+vQWcwrV69GnFxcVJfMTExWLFihRSdAQC//fYbrl27pkFBABZEwbx582BnZyf1FRgYCD8/Pw06g2nt2rWIiYmR+oqLi8OyZct0fe3duxeBgYEadAZgQRT4+voCgNTXtWvX8Ntvv2nQGUzr1q1DVFSU1FdCQgK+++47DTqDaf/+/QgICJBeL5PJhPnz53NsgtrXjRs3sHv3bg2igun7779HZGSkBgUBWFAAS5cuRZkyZaS+Dh48iMuXL2tQEIAFnTB//nyYTCYNOgMAbt26hZ07d+r6+uGHHxARESH1lZycjMWLF0tREABw+PBhXLx4UeqLiLBgwQJet6/2FRQUhF9++UWDqGDatGkTnjx5IvWVmpqKRYsW6fry9/fH+fPndX0tXLhQ19fdu3fx888/6/ravHkzwsLCNOgMwIItWrBgAUqWLCn1dfToUZw7d06DqGC+Fi1ahOzsbKmvkJAQ/PTTTxpEBdOWLVvw+PFjDaICsGCL5s+fjxIlSmgQFQBw/PhxnDlzRtfX4sWLkZWVpUFnABYMz5YtW3R9/fTTT3j48KH0emVmZmL+/PkoXry41NepU6dw8uRJDQqC+VqyZAkyMjI0KAjAguHZvHmzFJ0BANu2bcP9+/el1ysrKwu+vr4oVqyYBlEBWNBpJ06c0GC+mJYuXYq0tDTpPS40NBQ//PCDFJ0BWFBNwcHBGnQGYMEp+fr6omjRolJf586dw9GjR3XvvcuWLUNKSspLZxVrmcDX1/cvySoRERFYt26d1awSFBRkNRNYyyqHDh3S9bVy5UrdrPLs2TOsWbMG5cqV+8NZJT8/32pWuXz58l+aVW7cuCH1xTJBoUKFpNcrICAA+/bt0/W1Zs0axMbG6maV5cuX62YCPz8/q1nF19f3pbPKunXrEB0dbTWr6GWCf7L+EnwLgBIArgPwBJAAoMi//9wbwNGC5tv2iMq1adMmzUZotkfDbDbzljJZacutW7f4Bm0lOoOJNXopS1vY3pG0tDReJsNKW2TlKEp0BtujYTab+QZtWWlLUFAQL21RojOYWDukuiabyLLvh5XJuLq6cnSGuhxFjc5gYmUystKWkJAQ7kuJzmBibXSy0pbMzEyqXLkyL21h6Azma+fOndyXurSFiHitOSttUe6FuH//Pi+TUaIzmFg5irK0hfnKzs7mZTJKdIa6HEVZ2qL0xRpClegM5uvRo0dUuHBhAZ2h3KPx1Vdf6Za25OTk8DIZJTqD+dq7d6+mtEW5d6Rbt268tIWhM5iv0NBQXibD0BnKPRrffPONbmlLbm4uL5NRojPU5Siy0hYi4ogMJTqD7R0JDw/nZTLq0hYi4uUorLRFuW8zLy+Pl8ko0RnM15EjR3RLW4iIN14q0RnMV2RkJDk4OEhLW4iI5s2bx0tblOgMIsv+GoaQUqIz1OUorLRl9erVwn5S1iypRGewfZtRUVG8TEZW2iIrR2H7No1GIy+TkZW2nDp1SihtYegMJmVpCytyY75iYmJ4mYystEVdjqLct2k0Gjn+QFbacvbsWe5Lic5gslbaEhcXRyVKlNBgvpiv5cuXc19KdAaRZS8wK5ORlbawchQ15ouJtRQrS1uYr4SEBN4arsR8qctR1OgMIsu9hBXfyUpbrly5oilHUe4nZW3AaswXkWWPMiuTkZWjMDyVrLTFbDbz9ncl5ovdewMDA7kvJTqDibXbKktbmK/k5GReJqPEfKnLUWSlLWazmZfJKDFfzNf169d5JlCiM5hYK6qstCU1NZWXySiL3JivzZs3W80qrExGiflivm7fvm01q7AiNzXmi8iyR5llFVmR29atW61mFYaGqVu3riYT3Llzx2pWYc3MykygzCoMuaXEfDFf27dvt5pVGC5OiflSZhWWCWRZhRW5qTFfRJY9yqz4Ton5Yr527drFM4Esq7A2cyXmi917Hzx4YDWrfPnll7qZIDs7myO3ZFllz549mqyizATKgjl1Vnn8+LEmqygzAStyU2O+iArOKvv27ROyijoTsNZwZVaR7Sf9pwl/ZlkRgMIAbgLIALAAwOsAHinGawC4U9B5bA+icskwKSwAvfvuuwKXkB0sAClZnsqjcePGNHToUCkahrXW6aEmWACSVaKzAPTee+/p+urbt6/A8lQejRo1omHDhun66ty5s8DyVPv66KOPpPgWFoD0fLEApORjKY+GDRvShx9+KPXFApAeAoMFIBm+BbC01vXt21fqiwUgJR9LeTRo0ICGDx+u6+utt94SuF3KgwUgJedMebRo0YL69eun66t37966KID69evr+mIBiLWlqg8WgJQ8MeXh7u5O/fv3l/piAUjJ8lQe9erVoxEjRuj66tixoy6agwUgFsTUh6urKw0YMEDXV69evXQRBXXr1tX1xQKQHpqDNezKsDKAJQANHDhQ6osFID1EQZ06deijjz7S9dW+fXuBMar2NWTIEP5yRn24uLjQ+++/r+urR48e1KJFC+nc2rVrW/XVrl076t69u/Tc7GWNHu6mWbNm9MEHH0jPzQKQHjqhVq1aNHLkSKvILR8fH6kvFoD0cDdNmzalQYMGSc/NApAe5qlmzZpWfbVp04Z69Ogh9cVeiigZo8rD2dmZBg8erOure/fu/AFEfdSoUYNGjRql66t169bUs2dPqS/WZKtkeSoPJycnGjJkiPTc7KWIHtKhevXqur7Yy5pevXrp+howYIAuhsfR0VH33st86eGn2MsaPV/e3t66vtjLGiV3XHk0adKkwEzQrl076Vz2skbJsFX68vT0LDCrKFmeyqNx48YFZoKCsoqSFav29VdkFdZkq2R5Kg/2skaGbwEsmaBPnz5Ws4oeHujPyCoyfAtgyQT/SVbR88WabPVwXSwT6GUVd3f3l84q9erVKzCr6GWCgrKKm5tbgVll48aN0iKsf4Lwgg+iBe4RBQAiMhFRcwDVAXgAaCL732Rz7ezsRtnZ2f1uZ2f3e3x8/Iv8df84NW3aVPNn9erVg7e3N1q0aIHKlSsLY0WKFEHLli3h7e0Nd3d3zdxKlSrB29sbHh4eqFOnjvTvY3PVy4JKliwJLy8veHt7w8nJSTO3bt26fG6VKlU0vtzd3eHt7Q03NzfNEoWKFStyX3Xr1tWc29nZmZ9bvcylRIkS8PT0hLe3N5ydnXV9tWjRAlWrVhXGChcujBYtWnBf6mUZr7/+OvdVr149XV9ubm5/2FedOnW4rzfeeEPjS3m91EvWKlSowH3Vr19fc25HR0d+vdTLXIoXL859yb6/ateubdWXm5sb96VeUsR8eXp6Sn05OTlxX+plLgX5qlWrFvdVrVo1YaxQoULcl7u7u8ZX+fLlua8GDRpozt2kSRM+V73EtFixYtxXs2bNNHNr1qyJVq1aoUWLFqhevbrGl6urKz+3eunOa6+9xv8dGzZsaNWXeimn0peLi4tmbo0aNfj1subLzc1Nszy1XLly8PLygqenp9RX48aNuS/1ksmiRYvCw8MD3t7eaN68uWZu9erVua8aNWoIY3Z2dmjevDn3pV7WWK5cOXh7e8PLywuNGjXSnLtRo0Yv7atatWov5Mvd3V2zfLBs2bL8ejVu3PgP+XJwcICHhwdatWol9fXGG2/A29sbLVu2RM2aNa1eL/VyuDJlysDLywteXl5o0kR7a27YsCGfq15iynyxcbWqVq3KfdWqVUvjy8XFhc9VL4crXbq0VV8NGjTg16tixYrCmL29Pb/Hubq6auZWqVKF+6pdu7Zm3MXFBa1atbLqy9vbu0BflSpV0vhi9xKZr8qVK3Nfsntvs2bN4OXlBTc3N82S71KlSnFfjo6Omrn169fn55ZlAubLWiaw5ov9O6qXVit9yTJBvXr1+O9GWSZQ+lJngoKyijIT/NGsUqdOHXh5ecHd3V2TCZRZReaLZRVPT8+XyirMV0GZQJZVlJlAL6t4enpKs4ry3qvOBAVllYIygfJ66WWVl80EXl5eaNWqVYGZQO3rP80ELEO5ubnpZhUvLy/dTMB+pqxllVatWml+pmxS6UWeVpUHgG8AfA7b0tw/TbNnz5by6ogsy/Vq164tXeZA9Jxl1qxZM81yAiLLcj0Zr47IwhF1cHDgvDp1PfXcuXN1lz6y5XqypY9Ez5fryXh1RER9+vTRXfrIluvJeHVEluV6eksf8/PzqWHDhgKvTumLLdeT8eqILMv19JY+RkdHU/HixTmvTu1ryZIluksf2XI9Ga+O6DnLTMarI7Is15Px6oieL9eT8eqILCwzvaWPJpOJnJycOK9Ojaxgy/VkSx+JiIYOHSrw6pRLH9lyPRnDlsiyXE9v6aPJZCIXFxcpr47IUk/PfKmXPhJZluvJeHVERImJiVSmTBnp0kciS7W9Hq+OLdeT8eqIni/Xky19JCL+qYKaV0f0fLmejFdH9Hy5noxXZzabqWXLllJeHdHz5XqypY9EluV6Ml4dkWW53muvvSbl1RE931rAeHXKpY9suZ5s6SPR860FMl4dkWVrAXvLr176yJbryXh1RM+X68mWZLKtBcyXcukj0fPlejJeHZFluZ6MV0f0fGuBbOkj0fPlejJeHZFluZ6MV0f0fGuBbJsGkWW5nt7SR7ZcT8bWJXq+tUC2TYPIslyPMWyVSx+Jni/Xk23TILJsLWBsXfXSR7ZcT8nWVaIh2HI92TYNIqIuXbroLn1kWwvYNg01Xmv69Om6Sx/Zcr0KFSpotmkQPd9aIGPrElmW6+ktfQwLC6MiRYpIt2kQWbYW6C19zM3NpVq1aknZukREBw8eJMCyIkG99JHIsrVAb+ljREQE2dvbC5lA6WvOnDm62zTY1gK9rOLv7y9kAnVW6d27t25WYVsLZGxdIsvWAmtZpX79+jyrqDPB8ePHeSZQb9MgsmwtUGYVZSZQZhVZJli4cKFuVjEajdSoUSPdTMBY7LJtGkREAwcOFLKKMhOwrQXKbRrKTLB06VKrWcXR0ZH7UuO12NYC2TYNIqLBgwcL2zSUmSAuLo5Kliwp3aZBZNlaYC2rNG3aVLpNg8iC/bOWVYYNGyZl6xIVnFVWr14tZBV1JmjevLl0m8Y/XfizluYCqAig3L//uziA8wB8AOwGMODff74OwMcFncv2ICrXoUOHpLw6IsvDoh6vjsjC/dLj1WVnZ+vy6ogsIVCPV0dkecjV+4GKjIzU5dUxX3q8upycHKu+bt++rcurY75kvDoiC69Tj1dHZHmw0uPV5ebm0v79+6VcOCLLvlc9Xh2RZQ+fjFdHZHmI1ePVMV96vLq8vDzav3+/lAtHZOEW6vHqiCwBQI8LFxsbq8urI7L8ctfj1eXn51v1FRwcrMuwJbKwGvV8xcXF6fLqiCz8Nj1endFopP379+suhwkJCdHl1TFfery6+Ph4XV4dkeUBWY9XV5Cve/fu6XLhiCwvd/R4dYmJibq8OiILv02PV2cymWj//v1SLhyR5SFDj2FLZGFI6vHqkpKSdHl1zJcer85sNtOBAwekXDgiC+dRjwvHfOnx6lJSUnR5dUSWFwp6vLqCfD169EgTspU6efKkLq8uNTXV6v6i33//XZdXx3zJGLZEln3VegxbIstLOj1f6enpugxbIgubV4+tazab6eDBg7q+wsLCdBm2RJZArsfWzcjIEPZCq3X9+nVdti7zJWPrEhE9efJEE7KVOnPmjC5bNzMzU5etS2RhBuuxdYksD5N6mSAiIkKXrUtkeVDQY+tmZWXpsnWJLJlAj61LZMkqepngP8kqBWWCF8kq1jLBy2aV3NxcOnDgwH+UCfR8RUVFvXRWycvLs+rrzp07Vn35+/v/JVklPz+fDhw4YDWr6DFsmS9rWaWgTPBXZhW9TFBQVvkn60UfRAvkiNrZ2TUDsAWWfaKFAOwiotl2dnZ1AewAUB7ADQCDiCjX2rlsHFGbbLLJJptssskmm2yyyab/v/rTOKJEdJuIXImoGRE5E9Hsf/95KBF5EFF9Iupb0EOoTfp68uSJ7lhiYiJSU1N1x8PDw2E2m6Vjubm5iIqK0p0bFRWF3Fz9f7awsDDovahISkr6j3w9e/bMqq+cnJyX8pWcnIyUlBSrvkwmk3QsLy8PkZGRunOjo6P/I1/Jycm6cyMiInR95efn4+nTp3+Jr5SUlJf2ZTQarfqKiYlBdna27viTJ090faWmpiIpKcmqL6PRKB0zmUyIiIj4S3ylpaUhMTFRd+7Tp0+t+goPD9edGxsbi6ysrP+6L7PZXKCvzMzMl/KVnp6OhISEl/JFRFZ/N8bFxb20r4yMDFjrLIiMjER+fv5L+8rIyHgpX5mZmYiLi/tLfMXHx7+0r6ysLMTGxlr1lZeX91K+EhISkJ6erjtu7V6SlZWFmJgY3bnPnj2z6issLMyqr7S0tJfylZ2d/dK+gIIzwcv6ysnJQXR0tO7cvzMT/J1ZxVom+LuySkGZ4K/KKn9lJoiOjrZ67y3IV0GZ4FXMKjYVrAI5on+mbBxRub788ktMnjwZYWFhcHBwEBhw+fn5aNiwIY4ePYrk5GQNy++3335D165dERIS8n/snWd4FFe2tZckBCZnMMEkRXIWCASInNQwF9uM7Rn7muQI2GQwJplgMDYGTM5gcs4C1CSREQgFQIAIQhFllHPv70d9p3xO1akWA8Mde9B+nvozZ6pZLuiuVXX2Xi8sFovAzLOzs0Pv3r1VBlK5cuUENt2jR4/QqFEj3LhxA1lZWahZs6YQoDB9+nSMHj1aqis/Px8uLi7w9vZGcnIyqlSpIgStHDp0CH369MHdu3eluvr164fly5cjJiYGZcuWFRhwT58+haurK/z8/JCRkaFj082aNQsjR47EkydPYG9vL+gqKCiAq6srjh07hqSkJB2b7tixY+jZsyfu3LmDgoICgQFna2uLAQMG4LfffkN0dLSOMRgREQEXFxdcv35dqmvu3Ln48ssv8fjxY50uIkKjRo1w5MgRJCUlqQw4Vt7e3ujevbuqi2fm2dnZYdCgQVi8eDGio6NRunRp4XpFR0fD2dkZV69eRUZGho6ZN3/+fHz++ed49OgRihUrJrD8iAiNGzfGoUOHkJCQoGPm+fj4wNPTE7dv30Z+fr7uer3//vv45ZdfEBUVhdKlSwtsumfPnsHJyQlXrlxBenq6jpm3cOFCDB8+XNWlZfk1bdoUBw4cUHXxzLwzZ86gc+fOqi6eTWdra4sPP/wQP/30E6KiolCqVClBV1xcHJycnHD58mWkp6frrteiRYswdOhQPHz4EHZ2dgIDjgW07N27FwkJCTo2na+vLzw8PBAcHIy8vDyB5Wdra4uPP/4Y8+fPR2RkpKqLBVIkJibC0dERly5dQlpamo5Nt3TpUvzv//4vHj58CFtbW52uli1bYs+ePYiPj9fpunz5Mtzd3REUFIS8vDyBV2tjY4MhQ4Zg7ty5iIiI0OlKTk6Go6MjLly4gLS0NB1jcMWKFfjnP/+J0NBQ2NjYCLpY8NXOnTsRHx+vY9Ndu3YNbm5uCAoKUrmcvK4RI0Zg1qxZiIiIQMmSJQUGXEpKChwdHeHr64vU1FQdm2716tX48MMPBV0sSMrW1hZubm7Yvn074uLidLpu3LiBtm3bIjAwELm5ubrr9cUXX2DGjBkIDw/X6UpLS4ODgwPOnz+P1NRUHd93/fr1eP/99/HgwQOdLjs7O7Rv3x5bt25FXFycjpnn7++P1q1bIyAgADk5OQIzz8bGBiNHjsTUqVMRHh6Ot956S9CVkZEBR0dHnD17FikpKTpm3qZNm/Dee+/hwYMHAKDT1bFjR2zevBmxsbE6XUFBQWjRogUCAgKQnZ0t8H1tbGzwzTffYMqUKXj69KlOV2ZmJpycnHD69GmkpKTo+L5bt27F//zP/+DevXtSXZ07d8bGjRsRGxurY/ndvXsXzZo1g7+/P7Kzs3XXa/z48Zg4cSKePn2KEiVKCHzf7OxsODk5wWw24/nz57p7744dOzBw4EDcu6373CUAACAASURBVHcPRCTc44oVK4auXbti3bp1ePbsme7ee//+fTRp0gT+/v7IysrS8WonTpyIcePGISwsDCVKlBD4vrm5uXBycsKpU6eknmDPnj3w8vJCSEiITpednR26d++ONWvWSHU9fPjQqieYOnUqxowZg7CwMJ0nyM3NFbyKlqN74MABq16lT58+WLlypdQTPH78GA0bNoSfnx8yMzN112vGjBmqV7G3txfucbxXSUpK0uk6fPgwevfurXoV/t5ra2sLLy8vLFu2TOoJmFe5fv06MjMzdZ7ghx9+wNdffy31KhaLBQ0bNsTRo0f/Za9iZ2eHAQMGYOnSpYiOjkaZMmWE6xUZGQkXFxdcu3ZN6lXmzZuHL774Ao8fP9Z5AovFgkaNGuHw4cNITEzU6Tpx4gS6desm9Sq2trZ499138euvvyIqKkqnKyYmxqpXWbBgAT777DM8fvwYdnZ2Ok/QpEkTHDx4EImJiTqvYjab0aVLF0NPMHjwYPzyyy+IjIzUeZXY2FjBq2h1/fzzzxg2bBgePXok9QRNmzbF/v37pV7lTa7XwhF91aNoRlRe48aNE2Kf+eCYixcvqhxRdvDD2Js2baJixYqpazwzz9/fnwYPHiycyw9je3t7C5H92uCYiRMnCufyw9iXLl3SRePzzLwtW7YIUe98cMytW7dUhh+viwXHnDhxgurWrSvo4pl5jFPF62LMvMuXL6vMMHbwwTFbt24VcDk8M+/WrVv00UcfCecyZMyhQ4fo5MmTKueRHXxwzLRp04Q1npl35coVXQQ9Hxyzfft2IYKeBccsWbKEAgICVLYgO3hm3qlTp3SR/XxwzMyZM3W6WHDM1atXdRH0PDNv586dAi6HZ+YFBATQJ598IpzLB8f4+Pjo8EI8M2/OnDnCGs/Mu3r1qg5LwwfH7Nq1i0qXLq2u8cy8gIAAlXnIDj44xmw26yL7W7durTLzfvzxR2GND465du2aDkvDM/P27t0rYHz44JjAwEAaOnSocC4fHGM2m3V4IZ6Zt3DhQp0uFhxz7do16t27t7DOgmN8fHxo3759QjQ+z8wLDAyk4cOHC+fywTFnzpzRRfbzwTGLFi0S1vjgmOvXr+vwLzwzb//+/SpPkeliwTFBQUEqi5HXxZh5Z86c0UX288w8xtTkdbHgmOvXr6vsN3bwzLyDBw8KGB8+OCYoKIi++OIL4VwWHLNr1y46d+6cysVkB8/MY0xNdvDBMX5+fmQymYR1npl36NAhlacIQAiOCQoKUhmR7OCZeefPn6eWLVsK63xwzIoVKwQMAR8cc+PGDRo4cKBwLs/MO3z4sMpTZLpYcExQUBB9/fXXwrl8cIyvr68OL8QHx6xevVpAL7DgmJUrV9KNGzdUfi47+OCYo0ePqjxFposFxwQFBamcbXbwwTEXLlygtm3bCut8cMy6devIzs5OXWPBMStWrKCbN2/Su+++K5zLB8ccO3ZM5SkCEIJjgoOD6ZtvvtHpYnzfixcv6jA+fHDMhg0bdLpYcIy/v7/K9WUHHxxz/PhxAS/EgmOYJ5B5FRYcc+nSJR3GpzCvwnuCv//978K5L+pVAgMDadKkScK5L+pVzp8/L/UqLEwuICCAPvzwQ+FcPuTuxIkTAl6IeRXmCb777judLuZVrly5osPluLi4qJ5g27ZtAkKPD5MLCAigf/zjH8K5fMjdiRMndHghnu87ffp0Ye1FvcrZs2dpx44dOq/C+L4BAQH08ccf63QNGzaMDhw4QKdOnSJHR0dhnQ+TmzVrlrDGh9wZeRXmCbRehYXJMa/yv//7v8K5Wq+ixQuxMLmbN2/S3LlzdbqYV7l27ZrUq8jC5N60wr+TI/rvOooeROUl4xvxXyajNQCGTM0XOQo7V8ZG+r/QJWOC8cd/6noVpou/+f8ra69bl7Vr8ibqkvFx+UPGymOHtX97f2ZdRjy7f4cuGQf5/+J6Wftz/8y6rF1Pa7+5b6quwn5HXpcua9+3N1VXkSf479BV5FX+73Q1aNCAjh49+p9+zPiPFIoeRP86pd155OPPr169qnvLyL9d//3334UvCf8WOygoSLfzyMeynzp1SnjLyN6us/hz7c4jj2q5evWqDsrNo1q2bdsm3DD5+PPg4GDdziNDtXh7e5OPj4+wI6qNP//+++91uhiq5fr167q3jOzt+qVLl2jnzp2C8eHjz4ODg3U7jzyqxWw2CzuiTBeLP9fuPPJv169fv06enp7COo9q2b17t/BjyKNabt++rdt55FEtZ86cEd4yauPPZ8+eLZzLdty3bdtGfn5+Ovg1/xZ77969wg88H39++/Zt3c5jzZo16fPPP6cjR47Q2bNnhbeM2h137c4j/3bdz89PB7/mUS379u0TdkT5t+t37tyhYcOGCefyb7HPnTtHrq6ugi4e1fLTTz8J5/Jv12/evKmDX/M77gcOHBB2RHlUy507d3Q7j0zXoUOH6Pz58zqIOb/j/ssvvwhrPKrl5s2b1KdPH2Gd33E/dOiQsCPKv12/e/eubueRR7X4+vpSkyZNhHW2437r1i3dziP/Ftvf35/69esnrPOolsOHDws7ovzb9bt379KXX36p08XeYvv6+lKzZs2Edf7tunbnkUe1+Pv7k5eXl7DO77gfPXpU2BHlUS13797V7fDxO+4XL16kFi1aCOv82/WVK1cKa/yO+61bt2jAgAHCOo9qOXbsmLAjyncC3L17V7fDx++4X7x4kVq1aiWs86iWVatWCQ8a/I57YGCgbueRR7UcP35c2BHlUS0hISG6HT5+x/3y5cvUpk0bYZ3fcV+3bp1g6Pkd98DAQBo0aJBwLkO1+Pj4kLe3t7Ajyu+4h4SE0JgxY4RzeVTL5cuXyc3NTVjnUS0bNmwQdPGolqCgIN3OI49qOXHihLAjqkW1aHceeVTLlStXdF1SPKpl8+bNgjnmd9yDgoJ0O49169ZVOwFOnjwp7IhqUS2FeZUOHToI6zxWbuvWrYZeJTg4WLfzyKNaTp06RXXq1BF08agW7c4jv+N+7do1nVfhd9y3b99u1atodx75HXcfHx9hR1TrVbRdUlqvot155Hfcd+7cKbwc4r1KUFCQbueR33E3m83CjqgW1aLdeeRRLTKvwu+4F+ZVtDuP/I57YV5F2yXFdwf6+fnpdh55r7Jv3z5DrxIcHExDhgwRzuV33K15lcDAQJo/f75wLu8Jbty4ofMqfHegUSrym1AoehD969Rnn31myENMTk6matWqSXmIRApb0IiHaLFYqF27dlIeIpESbV++fHlD9tFXX31lyENMSUmht99+W8pDJFLYgtZ0dejQQcpDJFKi2suXL6+2sGjjz0eNGmXIQ0xNTaUaNWpIeYhEClvQiIdosVioU6dOgsnmdQUHB1P58uXVFhatrjFjxhjyENPT06lWrVqqydbGn2/btk0w2dpY9q5du0p5iEQKjqR8+fJSHiIR0fjx4w15iJmZmfTOO++oLSza+PNdu3YZ8hCJFLYgb7J5XQ8ePKDy5curJlura/LkyYY8xKysLKpbt65qsrWolr179xryEImI+vTpo5psLarl4cOHVL58eSkPkYho6tSphjzE7Oxsql+/vpSHSKSwBXmTrdXVr18/od2W1/XkyROqUKGClIdIpLAFeZPN68rJySEHBwe13VaLajl69KghD5FIYQsyk61FyDx9+pQqVKgg5SESKWxBZrK1qJbc3FxycnKS8hCJFLwBb7K1ugYNGmTIQ4yMjKSKFStKeYhECluQN9m8rry8PHJxcZGym4kUtqARD5FIYQuyF4JaVEt0dDRVrFhRNdlaXT/99JMhu5kx/GQ8RCIFsWLEbiZS2IJGPMRnz55RpUqVpOxmIoWDzL8Q1Opq2rSplIdIpCBDjNjNRAoH2YjdHBcXR5UrV5aym4kUtiB7IahFtTDesIyHSKTgp3iTrUW1fPrpp4Y8xISEBKpSpYqU3UykcJCN2M2MNyzjIRIRXb16VWi31aJahg0bZshDTEpKomrVqknZzUREq1atEky2VlebNm2k7GYiBQ9kzRN8/vnnhiY7OTmZqlevbuhV1q1bZ9UTtG/f/oW8ypYtW3S6vv76a6tepUaNGoZeZePGjUJbq1ZXx44dDb1KUFCQVU8wevRoQ6+SlpZGNWvWVD2B1qv8/vvvVr1K586dDb3K7du3qVy5clJ2MxHR2LFjrXqV2rVrS9nNRAoH2YjdTETUrVs31atoPQHzKqytVesJJkyYYNWr1KlTR/UEWq+ye/duq16lZ8+ehl4lNDRU8CpaTzBlypRCvYqM3fymV9GD6F+ojJhfRAof0Ig7SKQwxYx4ddnZ2YbsIyLFMBlxBwvTlZSUZFVXRESEVV1GPEQihWP1KrqMeIhE1q9XTk6OIQ/xVXUlJydb1WXteuXm5hryEIkUg2nEQ2S6jPhYz58/N+QhFqYrLy+vUF1GfL8X0WXEHWS6jDh6+fn5hjxEIoVH9rK6UlJSXkmXEQ/xVXWlpqYa8hCJlIc2I10FBQWF6jLiDhIp3ykjXWlpaYY8xMJ0WSwWQ04jkfIA8zp1Gb3JfhFdRjzEwnSlp6dbhaFHRUW9tK74+PiX1pWRkWHIQ3xVXQkJCYY8xMJ0ZWZmGvIQiZR7nNGMlsVisfqbnZCQYMgdfBFdRjzEwnQRFe4JXlZXVlbWa9X1urzKq3qCl9WVk5Pz2rzKq3qCwrxKYZ7Amq7X6Qn+27xKYZ7gTa4XfRAtlCP676wijmhRFVVRFVVRFVVRFVVRFVVRFdV/b70oR7QI3/InqKlTp+LBgwc6/ACgcJWmTJmii/lntWbNGpw6dUoXpw8o8fMjR45ESkqKgEVgZTabsXr1ah1+gNW0adMQEhIi1fX06VNMnjwZAKS61q1bhxMnTkh15eTkYOTIkXj+/LkQp8/q7NmzWLlypS7mn9WMGTNw584dHX4AUBArEydONNS1ceNGHDt2TBfzDyjx8yNHjkRycrKAH2B1/vx5LF++3FDXrFmzEBwcLNUVHR2N8ePHg4ikujZv3oyjR4+iXLlyOl15eXkYPXo0EhMTpdfr4sWLWLp0qQ4/wGr27NkIDAzUxfwDCmJl7Nixujh9Vr///jsOHTqki/kHlFj8UaNGISEhQRenDyjIkF9//VUX889q7ty5uHXrllRXXFwcxowZo8bWa3Vt27YNBw4ckOoqKCjAN998g7i4OB1+AFCQIYsWLdLF6bP68ccfcfPmTV3MP6CwBb/99lsVZaPVtXPnTuzdu1eHH2C6vv32Wzx79kx6vfz8/LBw4UIdfoDVggUL4OfnJ9WVmJiIb7/9Fnl5eUKcPqvdu3dj9+7dOvwAoMT1f/vtt4iJidHF/AMKMmT+/PmG1+vnn3/G1atXdTH/gIJ++eabb5CTkyPgB1jt3bsXO3fu1MX8A0q3ztixYxEVFSXVFRAQgHnz5unwA6wWLVqEy5cvS3WlpKRg9OjRyMnJkV6vAwcOYPv27Ya6xo0bh4iICF3MPwAEBwdjzpw5UiQRACxevBgXL17U4QcAhQc7cuRIFYHC8AOsDh06hK1bt+rwA0zXhAkTEBYWJtV19+5dzJo1S4cfYLV06VL4+vpK8QPp6ekYOXIkMjMzBSQRqyNHjmDLli2GuiZNmoQnT57o0D+AgjKZMWOGFNcAAMuWLcO5c+dQsWJFAUkEKEiakSNHIiMjQ3q9jh8/jo0bN+qQREzX5MmT8ejRI6mu0NBQTJs2TYdKYrVixQqcOXNGh0oCFCTNyJEjkZ6eLr33njhxAuvXr5fqAhSkW2hoqA7hBCgok++++85Q16pVq+Dj46NDEgEK33TkyJFIS0uT6vLx8cHatWsN73FTp07F/fv3pZ4gLCwMkydPNvQqa9euxcmTJ616AiOvcvr0adWryK7X9OnTcffuXamu8PBwTJo0CYDcE6xfvx7e3t5SXcwTGHmVc+fOWfUE1rxKVFQUJkyYYOgJrHmVvLw8jBo1CklJSVKv4uvri2XLlhl6gh9++AFBQUGFepXatWvr7nGbN2/GkSNHpLqYJ7DmVZYsWWKoa86cOQgICLDqVYw8wdatW3Hw4EFDrzJ69GjEx8dL771Xrlyx6lXmzZsHf39/q17FyBO8yVWEb/kL1YEDB4TQAYYfYG0GDH/A4wdYW8bjx4/VAAAeP8DaH1hMtzYMgUhpO2FhRTx+gLU/HD58WAgd0M5pMcwAH4bA2h/CwsLUAAAeP8B0sWF5bRiCxWKh3NxcNQCAxw8wXcePH1d18fgBputvf/ubLgyBtWpGRESoYUU8foC1ZbCYbm0YgsVioby8PBWTwochsLaMkydPSsMQWOvhe++9J4Qh8PNQUVFRajABH4bAdLFheT4Mgc1D5eXlqYP2fEASa9U8ffq0NAyB6WLhFXzoANMVExOjBgDwYQhM188//6wLQ2DzUPn5+WooED8PxXSdO3dOGobAdLGQCB4/wFr8YmNj1SRYPgyBtWouXrxYCEPg56EKCgpUHAkfkMRaNS9cuCANQ2CthyyMgQ9IYq1O8fHxaliRbE7rt99+k4YhMF0sfIcPQ2CtmleuXNGFIfDzUAwNw+MH2JxWYmIilS1blgBI57RYgI4WP2CxWMhisajYDx4/wHT5+fmputicFj8P9dlnnxEgBiSxOa3k5GQqX748ASJ+gLVqrlmzRv1s7TyUxWJR8Ro8foC1kPr7+6vn8vgBposFIfEBSWxOKyUlhSpWrKjqYvgBpmvDhg3qZ2tnt9m8GyAGN7EW0sDAQPVcHj/AWiJZ4BCPH2BzWqmpqWpYkWxOa/Pmzepna+ehLBaLGtrC4wdYq2ZwcLAaViTDD3z77beqLu2cVnp6OlWtWpWAP4Kb9u3bp+ratm2bqouf3Wbtbiy0hQ9uYrpCQkJUXbLZ7fHjx6u6tHNamZmZVL16dQKU4Cbt7PauXbtUXbLZbRaOwgc3sVbN+/fvq2FFDRo00M1uT548Wb33ame3s7KyqEaNGgT8gSTiZ7f37t2r6pLNbjNUEwtuWrt2rarr4cOHalgRj0piuqZOnarqYsFNTFd2drYaViSb3T548KBVr8KCyVhw05o1a1Sv8uTJE6teZcaMGTqvwjxBTk6OGlYkm90+cuSIzqvwnoAFgJUsWVI3u/306VOrXuWHH34QvArvCXJzc9UAQ5lX8fb2lnoVdo9jAWB8QBLzKpGRkVa9yrx58wSvws9ua72Kdnbbx8dH51V4T8CCtt566y3d7HZ0dLQaViTzKizsTxuQxDyBNa9y5swZnVfhPQEL3+S9CvMEz549k3oVdu9lYX9MFz+7nZ+fr6LTZLPb58+fF7yKdnabhVyWKFHCcHb7TSwUzYj+dYpPruWPt99+mzw9PQ3RC23atCEXFxdpfHSZMmWoZ8+eqvnUHk5OTuTm5iaN7GcGiE9n5I/q1atT165dDXW1bt2aXF1dX0qXo6MjtW/fXhqnzQxQlSpVpOdWq1aNunbtKqSp8kerVq2oYcOGUl2lS5emnj17Csmi/NGgQQOrurp27SqkRvJH1apVrepq2bIlNWrUSBoRXpiu+vXrk7u7u1QXM0B8aiR/VKlShbp162aoq0WLFtSkSROprlKlSlGvXr2s6urQoYOhri5duqhGTHtUrlzZqq7mzZsb6ipZsqRVXfXq1bOqq3PnzlSrVi3puZUqVaLu3bsb6mrWrBk1a9ZMilcoWbKk1b/HunXrkoeHhzSCnhkgPs1SpotP6+WPpk2bUvPmzaW63nrrLau66tSpY1WXh4cH1alTR4p1qFixolVdTZo0oRYtWkjxHYXpeuedd6hTp05SXcxo1K1bV6qrQoUK1KNHD0NdjRs3platWkl1lShRgnr27Kk+PGuP2rVrU+fOna3qqlevnhTrUJiuRo0avbSuWrVqUefOnaW/2eylSIMGDaS6ypcvb1WXq6srtW7dWqqrePHiVv8ea9asSV26dDHU1a5dO3JwcJDqKleunNV7iaurK7Vp08aqLqPrVaNGDUNdgJJm7ejoKL2XFKbL2dmZ2rZtK733spc1RrqYJzD6DWrbti05OTlJdZUtW/alPQF7WcNezmiP6tWrv5BXkf1mv4gnaNeuneG915pXKcwTFOZVevXqZajLwcGhUK/CXs5oj8I8QatWrahRo0avzauwlzP/qq6WLVtS48aNDT2Btb/HF/EqRrpe1atYu14v4gmseRVrnkD2suZNKhQ9iP51yhprio8sl/0gGd0YABgaavYFs7ZepUqVl9ZVqlQpAX3w79ZljdtUmC6jG9aL6DJ6EGA/SNb4btZ0lSxZ0qouPuZfe9ja2lrVValSJaucPmu63nrrLcOH/hfRZfSCBVAeUqxxCwvTZXSDB2B403iR61WxYkWrTDFrukqUKGH4MqIwXTY2NlavV4UKFaxy0grTZXSDB2D4ouJFdJUvX94qo9SaruLFi79WXUbmAIDVc4sXL271z7am2cbGxup/c7ly5QyNWmG67O3tX1pXYX8XZcuWfSVd1v5tW/tOvIguo4cyAFa/y/b29lZ/o15FV5kyZV5aV7FixV6brtKlSws4pH9Vl7V7YNWqVa1yRF/Fq1jT9Wf2KoV5Amv8SR5Rpz0K8wT/Sa/yKp7gVbyKtev1qp7gdXoVttNtLeztv7VQ9CD61ym+rUTbTpqVlSXwyLTx+o8ePVINqradNDc3V23fYF8ovp00NTVVbUcA9O2kfAss/4WKiIigrKwsgfulbdEICwtTDaqWrZWbm0sLFiwQdH300Udqi0ZaWprALdS2k546dUpd49la4eHhlJWVJbBAtS0a4eHh6pt9bTtpbm6u2moKiLxNllTYvHlzdV3bTsq3wPLtpE+fPqXs7GyBr6VtJ42IiFDf2PFsraCgIMrLy6Nff/1V0MW3k6anpwt8QG07Kd9WwthaLF4/OztbbelkNxLWTpqRkUFRUVGqsdG2k+bl5amtpoC+nTQ9PV1tnQT0bK2LFy8Kuvh4/ezsbLWlk91I+HbSmJgY1djwHNCAgADKy8sTWI2Mt8lQQOnp6QKbV9tOyrfAMg4oQwFlZ2cLbEttO2lsbKxgINzc3NR20vz8fFq9erWgi28nzcjIoI4dO6rrfDtpbm4uXb9+XTWCfDvpo0ePKCcnh0aOHKmeq439j4uLE27UfDtpfn4+rV+/Xl3TtpNmZGQIvDsW+8/aSW/evKnq4ttJHz58SDk5OWpLJ6CY7KFDh6rx+vHx8cLDVZs2bdR20vz8fNq0aZOgi28nzcjIELhy2nj9gIAA1aDy7aShoaGUk5MjsBr52P/U1FRKTEwUTBXfTpqXl0dbt25V1/h20mfPnlFGRgb17NlTp4u1kwYHB6sv0/h20gcPHlBubq7AamSIItZOmpSUJJg5vp00Pz+ftm/frq6VKlVKaCfNzMxUxzwA6FBAd+7cUY2ztp00NzdX4Epr20mTk5MFo8i3k+bn59Pu3bsFXQxRFB0dTZmZmQLTlUcB5eTk0L1791TjzLeT3rt3j3JzcwVWI0MUsXbS58+fC+xnfociPz+f9u/fr67x7aRRUVGUmZmpjnkAIm8zOzubHjx4oBpn7ehLTk6OwJXWtpOmpKQIPEXt6AvfAqsdfcnKyqJ3331XXedRQNnZ2fTw4UP1ZRo/+sI8Ac+V1qKAUlNTycXFRV3n2eD5+fl09OhRwRN4eXmp7aRZWVk0ePBgwRPwXuXx48c6r8J7Ap4rrW0nTU1NFRjLWq/Ct8DynoB5FZ5bzrPBmVdhL620oy+5ubkCV1rbTpqWlkZNmzZV17XtpHwLrLadNCsrS2CBMhQQ71XYyyFtO2leXp7AlZZ5FZ5lzLwKayc9e/aszhPwXoXng2u9SmRkpM6rsNGXvLw8gSvNexXmCVq3bq2uM6/CPIGvr6+gi0cBZWdnC3xw5lWYJ4iOjha8Co8CysvLE7jSMq/CM4NdXV0FFNClS5cEXVqvwnO4eTa4tZTyN6FQ9CD616mhQ4dK2VpEylyFh4eHlK1FRLRw4UKVraV945KdnU09e/aUsrWIlPkFI7YWEdHw4cN1M1usnj59Sh4eHlK2FhHRokWL6P3335eytXJycqhXr15SthaRMr9gxAElUlhmMrYWkTID6uHhIWVrESlMOiO2Vm5uLvXp00fK1iJS5heMOKBECnfViK0VHR1NHh4eUg4okcKkM+KA5uXlUd++faVsLSJlfqF79+5SthaRMnNmxNaKiYkhDw8PmjlzpjCzxWrlypWGbK38/Hzq37+/lK1FRHTx4kWrbK1vv/3WkAMaFxdHnTp1ohkzZuh4m0TK7KARB7SgoIAGDBgg5YASKbOWRhxQIoWxZsQBTUhIoE6dOkl5m0RE69evN+SAFhQU0MCBA6UcUCJSAef8zBZfEyZMMOSAJiYmUufOnWnatGnSNqCNGzcackAtFgsNGjSIRo0apeNtEhHdvHnTkANKpMzCsVkybbx+cnIydenSRcoBJVJYeUYcUIvFQu+++65uZotVQECAIQeUSJmFM+KAPn/+nLp06aKbL2e1fft23Xw5r2vw4MH09ddf63ibRMqspXaWjK/p06fr5stZpaamkqenp5QDSqTMNBpxQC0WC33wwQe6mS1Wd+/epU6dOkk5oETK3D4z/1oUUFpaGnl6eko5oETKTCP/QlCr6x//+IduZovVvXv3yMPDQ8oBJSKaM2eOygHVIncyMjKoW7duUg4okZK/wL8Q1NYnn3yimy9nFRoaSh4eHlIOKJEyo/fBBx8I8+WsMjMzqXv37lIOKJGSv8DMv5a3SaTwTfkXgnw9fvyYPDw8hPlyvhYsWGDIAc3KyqIePXpIOaBESv5C7969DT3BsGHDXsmrGLHBmScw8ionTpxQXwjKdI0YMcLQq4SHh6teReYJfv31V0MOaE5ODvXu3Vt4IciX2Wy26gm++OILQ68SGRlp1RMsXbrU0KswT2DkVc6ePWvIASVSuKuFeRUZb5OIaPny5YYcn8ow6wAAIABJREFU0Ly8POrfvz+NGTNG6gl8fX0NOaBECnfVyKs8e/aMPDw8dPPlrFatWmXVq3h5eQkvBPm6dOmSVa8yZsyYQr2KjA3+pteLPogW4Vv+BEVEQsLXi669znOLdP15Ppt9R/9s/81Fuop0Fekq0lWk69977uv87CJdRbpety7gz/ed+k/qepPL5gXxLbaF/R+K6vXXjRs3kJeXJ12LjY3F48ePDc8NDg5GRkaGdC0nJwf+/v7ql1Bbjx49Qnx8/EvpiouLw6NHj6zqSk9Pl67l5ubi5s2bhroeP36MuLi4l9IVHx+Phw8fGp57+/ZtpKWlSdfy8vJw48YNWCwWQ12xsbGGn33z5k3k5uZK1xISEhAaGmp47p07dwx15efn4+bNm4a6njx5gmfPnr2UrsTERDx48MCqrtTUVOlaQUGB1esVFhaGmJgYw8/29/dHTk6OdC0pKQn37983PPfu3buGuiwWi1VdT58+fWldycnJuHfvnuG/3bt37yIlJcVQl5+fn6Gu8PBwREVFGeq6deuWoa7nz58jJCTEUFdISAieP38uXSMi+Pn5oaCgwFBXZGSkVV3Z2dnStdTUVNy9e9dQ171795CcnGz42dZ0RUZGWtUVEBBgqCstLQ137tx5bboiIiKs6srKypKupaenIzg42FDX/fv3kZSUZFVXfn6+dC0qKgrh4eGG5wYGBhrqysjIQFBQkKGuBw8eIDEx8aV0xcTE4OnTp1Z1ZWZmStcyMzMRGBhoqCs0NPSVdIWFhRmeGxQUZKgrKysLAQEBVnUlJCS8lK5nz57hyZMnVnUZeYLs7GzcunXLUNfDhw9f2hO8iFex5gkK8yov6wlexavk5eUV6lUK8wRGuhISEl7aq7yIJ3hdXsWaroKCgtfmVQrzBP8pr5KcnGxVV1EVXkUc0T9BLV68GB9++CECAwORm5srcLRsbW3RrFkzbNy4ERERETrm57lz5+Du7o7Lly8jJSVF4GgVK1YMH3/8scoptdHwvRISEuDo6Ahvb2/ExcXpuGO//fYb/v73vyMgIEDl7TFdxYoVQ8uWLbF+/XqEh4fr+F4XL15Eu3btDHUNGTIEkydPlupKTk6Gg4MDjh8/jri4OJQvX17ge61cuRLvvfeeqovnVRUrVgytWrXC2rVrER4eruN7Xb16FW3btsXFixeRkpIicLTs7OwwYsQITJw4Uf1h4XWlpKTAwcEBx44dQ2xsrI6jtWbNGgwaNEg15jzfy97eHm3btsXq1avx9OlTna7r16+jTZs2uHjxIp4/f67T9eWXX2LcuHGqLp7vlZaWBgcHBxw5cgTPnj3T6Vq/fj3+9re/wd/fH9nZ2cL1sre3R/v27bFixQo8ffpU5WgxXf7+/mjZsiV8fX3x/PlzgaNla2uLUaNGYcyYMerDGc/RysjIgKOjIw4dOoRnz57p+F6bN2+GyWSCv78/srKyBL5X8eLF0aFDByxbtgxhYWE6vldgYCBatGiB8+fPIzk5WadrzJgxGD16tPpwxl+vrKwsODg44ODBg4iJidHp2rp1K7y8vHDz5k1kZWUJLNLixYujU6dOWLp0KZ48eaLTdefOHTRt2lTVxTM/bW1tMX78eIwcORIhISE6dmtOTg4cHR2xf/9+xMTE6FikO3bsQN++fXHjxg1kZmbqrpenpycWL16MJ0+e6FikISEhaNKkCc6dO4ekpCRBl42NDSZPnowvv/wSd+/eVTltjK2Zl5cHJycn7N27F9HR0ToW6Z49e9C7d2/4+fkhMzMTNWrUUJmfxYsXR/fu3fHLL7/g8ePHOhbpgwcP0KhRI5w9exZJSUkC89PGxgZTp07F559/jjt37qCgoEBgfubn58PZ2Rm7d+9GdHS0jvm5f/9+9OzZE35+fsjIyBBYpPb29ujduzcWLlyIR48e6Vikjx8/hqurK86cOYPExESdrhkzZmDEiBG4c+eOyo9jugoKCuDi4oJdu3YhKipKp+vw4cPo1q0brl+/jvT0dNSsWVNlfhYvXhz9+vXD/PnzVV08WzMsLAwuLi44ffo0EhMTBRapjY0NZs+ejSFDhuD27dvIz88X2JoWiwWurq7YsWMHoqKidMzPo0ePomvXrrh27RrS09MFFqm9vT0GDhyIuXPn4uHDhzoWaUREBJydnWE2m5GQkCCwNW1sbDBv3jx8+umnCA4ORl5ensAiJSI0atQI27ZtQ2RkJEqXLo0aNWqov0EnTpxA586dce3aNaSlpQlsTXt7ewwaNAizZ89WdfHXKzo6Gk5OTvDx8UF8fLxO108//YSPP/4YQUFBKoOX6bKxsUHjxo3x+++/IzIyUsf89PHxQadOnXD16lWkpqYKLNJixYrh73//O2bOnInQ0FAd8/PZs2dwcnLCqVOnEB8fr7v3/vLLL/joo48QFBQk9QRNmzbF5s2bpZ7g7Nmz6NChAy5fvqzqYvdee3t7fPTRR5g2bZpUV3x8PBwdHXHy5EmpJ1iyZImhV7Gzs0Pz5s0NvYqvry/c3d1x6dIlpKamonr16oIn+OSTT/Ddd99JPUFiYqLqVWJjY3XMz+XLl2Pw4MEv5FW0995Lly7Bzc0Nly5d0nkVOzs7DB06VPUqgOgJnj9/DkdHR9UTaHWtXLkS7777rqFXad26NdauXSv1BNeuXbPqVT777DNMmDDBqlc5evSo1KusXbtW8CpaT+Dm5oZVq1YhLCxMx/y8ceMGWrVqhQsXLui8iq2tLb766iuMHTsW9+/f13mC9PR0ODg44PDhw1KvsmHDBgwcONDQq7i7u2P58uWqrlq1aqm/2bdu3bLqVUaPHq16Fe29NzMzEw4ODoZeZcuWLYZexd7eHh07dsSyZcuknuBNriKO6F+oli9frg46A2Igg9lsFgITgD+CInbv3k0HDhzQxVKzQAaz2Uxjx44V1vhAhhMnTgjhO4DI9+KDaJguNitmNpuFwARADGQ4dOiQLr2PBTKYzWaV/cbrYjNZJ0+eFMJ3AJHvtWLFCmGND2Tw8fERwp2YLhbIcPjwYV1KHgtkMJvNQlAIIAYynDp1itq0aSOs83wvPoiG6WKBDD4+Piqvkx18IMORI0d0aXQskMFsNgtBIUwXm8k6deoUtWvXTljnw6PWrVsnpB3ygQxms1kIcgDEQIajR4/qUhxZIIOPj4/KpGMHH8hw6tQpIRQIEMOjNmzYIKQd2nCBDGazWQidYrpYIMOxY8d0CaKM7+Xj4yMEmDBdbCbr1KlTQigQIAYybNq0SUhmtuFCmsxmsxA6BYiBDMeOHdMlGrJABh8fH5WVxw4+kMHHx4c6d+4srPOBDFu2bBFSGG24QAaz2SwETABiIMOxY8d0yYAskMHHx0dl5fG62Py42WwmT09PYZ0Pj9q2bZsuhdHNzY1mz55NZrNZCMNiutis2LFjx3RpiC4uLjRu3Djy8fGhOXPmCGs8i9RsNgthRcAf4VEHDx6k7du361IYGYvUbDbT8OHDhTUWHrVp0yY6fvw4NWjQQFhnIU0+Pj5CCBzTxWbFzGazEFYEiMzPXbt26VIYWXjU6dOnheALQAyP8vb2FkJumK4xY8aQj4+PyhtmBx8e5ePjo/In2cGHNO3atUuXGM1YpGazmb766iudrkGDBtGGDRvI29tbCLkB/ghpOnXqlBD4wnSxWTGz2azyJ9nBQpr27dtHe/fu1SUzs/Aos9kshHQBf4RHrV+/nry9vYVAPuAPFqmPj48QTsd0sVkxs9kshCgxXWx+fN++fbpkZhYe5ePjQ6NHjxbW+JAmb29vlWXMDj48atGiRcIaC49inmDgwIHCOh8etX//fl0CMguPMpvNQngYr2vt2rV08uRJlWXMjnpceNTSpUt1urp06aJ6AsbFZAfPIj148KAuaZj3Knx4GCCGNJ08eVII32G6mFfhg2gA0RO8iFfRJvryXmXChAk6XbxX4cN3ADE8ig/N43UtWLCAzGZzoV5Fm5zbtGlTmjJlCvn4+NCkSZOENT5Q8tSpU0JQIPBHeNTx48dpzZo1Vj0B43Wy40W9io+Pz0t7lWPHjtH69esFXTZcoKTZbFbZ4uzQehVtcnjjxo1p0qRJhXoVHx8f6tChg7DOe4KNGzfqvAoLlDSbzULoFNOlZZG+iYWiGdG/TtnZ2Rm2DBRWNjY2hm0jRfXXqaK/x6Iqqn9v/Vm/U0W6/rUq0vWvVZGuoiqqP0/Z2dmhY8eOGD9+PEwm039azv9pveiMaFFr7p+gLly4IJ35cHFxQZcuXZCenq7rfbe3t0f37t1Rq1YtxMfH6+YQ3n77bfTr1w+5ubnSmaK2bduiRYsWSE5O1s25lC1bFgMGDICdnZ10LsPJyQmenp6Gurp164Z33nkHCQkJOl3Vq1dH//79DXW1adMGLVu2xPPnz3W6ypQpA5PJBHt7e+n8g6OjIzw9PZGRkaGb0ytWrBi6du2KunXrSq9XtWrVrOpq3bo1WrdujefPn+vmb8qUKQMvLy+UKFFCOv/g4OCAbt26Gery9PREvXr1kJCQoJuPqFatGry8vJCXlyeddWrVqhVat26NlJQUna7SpUvDy8sLJUuWlF6vBg0aoHv37lJddnZ28PT0RIMGDaS6qlSpYlVXy5Yt0bZtW6muUqVKoX///ihdujRiY2N15qR+/fro0aMHMjMzdXONdnZ26NKlCxwcHJCYmKib2yhMV4sWLeDm5oaUlBTdXFCpUqXQr18/lClTRqqrXr16VnV17twZTk5OUl2VK1eGyWRCfn6+VFfz5s3Rrl07pKam6nSVLFkSffv2Rfny5aW66tati549eyIrK0uny9bWFp06dYKzs7NUV6VKlazqatasGdq3b29VV4UKFRAXF6d7mVanTh306tXLUJeHhwdcXFyQlJSkm+WsWLEiBgwYYKiradOm6NChA1JTU3XzSm+99RZ69+6NihUrSnW988476N27N7Kzs3VzoLa2tujQoQMaNmxoVVdBQYF0xq9JkyaGukqUKIHevXujSpUqiIuL082Y1q5du1BdjRo1kuqqUKGCVV2NGzdGx44dkZaWJtXVq1cvVKlSBfHx8TpdtWrVQt++faW6bGxs4O7ujiZNmiApKUk3Y1q+fHkMGDAARCTV1ahRI3Tq1AlpaWm6e0nx4sXRs2dPVK9eXXq9atasaVVX+/bt0bRp05fS1bBhQ3Tq1El6jytevDh69OiB6tWrIz4+XjfLWaNGDfTt21d6L7GxsUG7du3QrFkzJCcn63SVK1cOAwcOhMVikeoqzBP06NEDNWvWNNTVr18/5OTkSO9xbm5uaN68ufTeW7ZsWQwcOBA2NjbSGVJnZ+eX9iqFeYK2bduiZcuWL+1VunbtKr3H/V94leLFixt6FSNdr9OrME/w1ltvSXW9ilepWrVqoV6lTZs2hrr69+9fqFcxuvd6enqifv36SExMfCmv4ubmJtVVmCd4Ea/y9ddfY/z48ejQoYPuz/5vr6LW3L9Q7dixQ2i/0WIlunbtqrbfsLYghm+4d++e2jLAs9tYhDRrNeXbghhWIjMzU21vZG1BjN1GRCr7jW8V5rESrP1My24jUqLvWXsjz25julj7BmsVXrt2rYpvyMrKUtsbtew2IlLZb1p2G6s+ffoIbUE8vuHRo0dqe6OW3UZEakunlt1GpOBwWHujlt1GpETyQ9MWxGMlWJsXawti7DYiorCwMFUXaxXmsRKzZs1S21x4dhuREjFfr149of2Gx0ocO3ZM1cVzZpku1vqtZbcRKdH3rL1Ry24jIrV1UsuZJVJwOKy9UctuIyI6efKkri2Ixzewdiotu41Iib5n7Y1aziwRqS2KjCnH2G1ESsS8k5OTqkuLlTCbzbq2IB7fwFqstew2IgWHw9obtZxZIgVhwHRpsRL5+fnk6uqqawtiuhj7zUbDmWW6WIu1ljNLRBQbG6u2N2rZbUSkcmq17DYiBTvDGH5aziwR0YULF1Rd7du31+EbPvnkEwL07DYiovj4eLW9UcuZJSK1FVDLbmO6WBuhljNLRHT58mVVV7t27XSoqSFDhhCg58wSKTgc1t6o5cwSkToewLcKM9SUxWJR2wi1nFkiBdMDiK3CPFZixIgRqi4tViI5OVltb9RyZokUrBHTpcVKWCwWdbRAy5klUjA9vC4tVoLxc/lWYYZveP78udre6OjoqENNMU6tljPLdLVv354APWeWSMH0MF2sVZjHSrDWXC1nlkjB4bBRDC1nloho8+bNqi6eM8t0sRZ+1sLM4xuCg4NVXTxnlv1msxZYLWeWiCg9PV1tb2StwjxWgnFqtZxZVozry3sCpuvu3btqeyPPmWW6WAusljNLpOBwWHujljNLRLRz506dV+E9Qbdu3QRdPGrq/v37Vr0KazXlW4UZaiozM5Nq1KhBgJ4zS6Tgg7RehfcEvXr1EjzBv+JVvvvuO6uewJpXOXDggHqPY16F9wSM66vlzBIpmB5rXmX69OmCrtWrV6u6cnJyrHoVxq7nW4V5T2AymVRPwHNmiRSvwkYxeK/C7nFszIP3BMyr5ObmWvUqjF3PexUeNcVav2VeJSIiQudVeE8wd+5cwRMwziyR4gkcHBwMvQpj1zOvokVNvffee4Ze5U0uFHFE/zo1e/Zsw3+4jx8/NmS3ERFt2rRJym4jUh7oxo8fL2W3ESlcTCN2G5HCSTPqcQ8LCzNktxEpN3je/POVnZ1N48ePl7LbiBQuphG7jYjoxx9/lLLbiJQHJyN2G5HCLeRNNl85OTk0YcIEKbuNSDHcDNws07VgwQIpu42IKCoqSmf++dq2bZuhLga5l7HbiBQGlhG7jUh5+JGx24iUB6cJEyZI2W1EyksSI3ZbXl4eTZo0ScpuI1J4nUY8VyKiX375RcpuI1IenCZMmCDlzBIpPMUlS5ZIObP5+fk0efJkKbuNSHkQ+OGHH6TsNiKFgStjtxEpD07jx4+X8lyJiPbs2WPIbsvPz6cpU6ZI2W1ERDdu3DBktxERLV68WMpuI1L4ptZ07d+/35DdVlBQQN99952U3UZE5O/vb8huIyL67bffpOw2IqKkpCQaN26clN1GRHTw4EFDdpvFYqGpU6dKea5ERIGBgVbZbcuWLZNyZomUByc2hyrTdfjwYUPOrMVioWnTpgkvBPkKCgoy5MwSKQ+xMs4sEVFKSgqNGzdOMNl8HT161JAza7FYaPr06YLJ5uvOnTs6k83XqlWrpJxZIoUjOm7cOClnlkgxkEacWYvFQjNmzJDyXImUl6lGnFki5eFaxpklUh7oxo0bJ+XMEikvu4w4sxaLhWbNmiWYbL4ePHhgyJklIlq3bp2UM0ukPNCNGzdOypklUljZRpxZIsXMyzizRMrLVCPOLBHRhg0bBJPNV2ZmJo0fP17KmSUiOn36tO6FIF9z5swx9CpPnjwp1KsU5gmMvMrZs2df2qs8ffrUqlfZsmWLIWeWeQJrXsWaJ5g/f76hV4mMjLTqCbZu3VqoJyjMqxh5gp9++umlvcr27dsNObPMExh5lcuXLxuy54kK9yraF4J87dy505A9X5hXuXr16it5lfHjx0t5rm96veiDaNGMaFEVVVEVVVEVVVEVVVEVVVEVVVH9W6poRvQvVOPHj8fNmzd1UemAEtf/9ddfq9HfLJKc1YoVK7B3715dVDqg4CCGDh2KmJgYISqdlY+PD3766SddVDqriRMnws/PTxdJDihswS+++EIXsc1q1apV2L17ty6SHFCYYUOHDkV0dLQQ/c3qzJkz+PHHHwFAqmvy5Mm4du2aVFdUVBQ+//xzZGVlCfgUVmvXrsXOnTuluvLy8jBs2DBERkaiWrVqOl3nz5/H3LlzDXVNnToVV65cQbly5YRIckBh0n322WcqdkOra8OGDdi2bZsuKh1QMBVDhw5FeHi4EEnO6uLFi/jhhx90Uemspk2bhkuXLumi0gGF/TZixAhkZGQIkeSsNm3ahN9//10XlQ4omIrhw4cjLCxMquvKlSuYOXOmoa4ZM2bA19dXF5UOKBiBYcOGIT09Xarr999/x+bNm6VR6QUFBRgxYgSePHkiYEpYXbt2DdOnT9dFuLP64YcfcO7cOR0+BVAwAsOGDUNaWppU17Zt27Bx40apLovFgs8++wyPHj2S6rpx4wamTp0Ki8UiYEpYzZkzB6dPn9bhUwCFsTZ06FCkpqYKmBJWO3fuxNq1a3X4FKbr888/R2hoqIApYXXr1i1MmTJFh3VhNW/ePPj4+OgwJYCCNxgyZAhSUlKkunbv3o01a9bo8CmA0q3z5Zdf4v79+1JdQUFBmDhxog7rwmr+/Pk4efKkVFdKSgqGDh2K5ORkAVPCat++fVi5cqUOn8J0ff311wgJCRHwKaxu376N8ePH67AurBYuXAhvb28dPgVQUExDhgxBUlKSgHVhdeDAASxfvlyHT2G6Ro0ahTt37qBy5cqoXLmy8NkhISEYO3asDp/C6pdffsGxY8ekujIyMjBkyBAkJiYKmBJWhw8fxtKlSw11ffPNNwgODhbwKawePHiA0aNH6/AprBYvXozDhw/r8CmAgl349NNPkZCQIGBdWB07dgyLFy/WYUqYrjFjxiAwMFCq6+HDhxg1apQOU8Jq6dKlOHjwoFRXVlYWhgwZgtjYWKkub29vLFq0SKoLAMaNG4dbt25JPcGTJ09UTyDTtWzZMuzfv1/qCbKzs1VdPKaE1alTp7Bw4UJDTzBhwgTcvHlTeu99+vQpvvrqKxVdptW1cuVK1ator1dOTg6GDBmCmJgYqa7Tp09jwYIFhromTZqE69evS3VFRERY9SqrV6+26lWGDBmCqKgoqVc5e/asVa8yZcoUXL16VXrvLcyrrFu3Djt27JB6gry8PAwdOhSRkZFSXb6+vpgzZ46hrqlTp+Ly5ctSXa/qVYYNG2boVS5dumTVq0yfPh0XLlyQeoK4uDgMHz7c0Kts3rwZW7ZsMfQE1rzK1atXMWPGDENPMHPmTJw/f97QqwwfPlxFcWl1vclVNCP6F6oTJ06osyZ8JDlrNWKzcrKZSH5WTjYT+eOPP6qfrZ0zyMvLU1EAsvkHNisHiPgUpmvw4MGGM5HR0dHqrBw/E8l0sVk5SGYi8/PzVRQAm4nkW6DYrBwg4lNYqxGblZPNRMbGxlLJkiWF+Qe+BYqPzdfORPKzcrKZSF9fX/VcHp/CdLGIb9lMJD8rx+Yf+BYoPjZfOxNZUFBATZs2NZyJZLNy0MxEMl1sVk42E5mQkKDOyvGR5EwXjx7SzkTys3L8TCTTde3aNfVc2Uwkw2vIZiL5WTnZTCSP0mEzkRcuXKC8vDyyWCxq5H7x4sWpT58+tGzZMrU1i5+V42cima4vvvhCmInkW6CeP3+uYotkM5FsVg6SmUiLxaJG2/Mzkaw169atW+q5splINivHY11YCxQ/K8fjU5iuTZs2qZ+tnYnkZ+X4mUjWmsXPyslmIr/55ht13c3NTWiBSktLU2flZDORbFYOmplIpovhbviZSNaadefOHXVW7u2339bNRPK4CO1MZEZGhoot4mciWbs2m+sH/sC68G3RbFbO3t5enYlk7dr8XD+PdWFt0TxCSjsTyc/KyWYi9+zZo57r6Oiom4lkc/38TCRr1+Zn5fiZSKaLzcpBMxNpsViEuX7ZTCSblQOUWU3tTCSbleNnIlm7Nj/Xz7AufLs2j2rSzkTys3KlS5fWzUSyuX5AmdXUzkSyuX5ZfgM/KyebiWRz/ZDMRPJz/bL8BjYrByizmtqZSDbXL8tv4Of6ZTORbFYO0M9E8rNyPOqNtWuzuX4jr8Jm5XivwjxBVFSU6lVkM5E8ekjmVZydnQ1nIk+fPm3Vq7C5ft6rME/Az/Xz+BSmi0f8aGci+bl+2UxkYV6F4UhkM5H8XL9sJpLN9fNehfcEDA/EdPHt2myu38irsLl+2UxkfHw8lSlTRvUE2plIHvvHvArzBPxcP49PYZ7gypUrUq/C7r0MBcaj3phX4ef6ZV6FR+kwr8JGuCwWC7Vs2VLVxVBvzBPwc/3Mq/CegM31M69irV37TSoUzYj+dcrDw0NgJ7GjTJky5O7urmMj8QaoSZMmOsYau6G7u7vrmIbsqFatGrVt21bHz+INUN26dQ11dejQwVCXg4MDNW3a9KV1ubm5Gepq1aoV1atXT2A6saN06dJWdTVo0ICaNWtmVVft2rWl51atWpXc3Nx0DFLeANWvX1/gT76orvr161OzZs10TDp2Q7emq0qVKlZ1tWjRghwcHKS6SpUqRR06dNDxOHldzZs3V286Wl3t27c31FW5cmVq166djoPGjubNm5Ojo6NUV8mSJcnd3d1QV7169ahFixYvpatSpUpWdTVr1owcHR0FXievq0OHDuqDgPaoW7cutWzZUqrL1ta2UF3t27fX8dnY0bRpU3J2dtbxOgHFaFjTVadOHWrZsqWOLcjr0jJG2VGxYkWrupo0aUIuLi46XueL6HrnnXeoVatWOg4yoNzQ3dzcDHVVqFDBqq7GjRsb6ipRooRVXbVr16bWrVsb6mrXrl2huqpWrSpdb9SoEbm6uuo4oryumjVrSs+tVasWtW7dWsdifJHrVb58eXJ3dzfU5erqSg0bNtRxRAHlpYg1XTVr1qQ2bdoY6mrbtq2hrnLlypG7u7uOVczratSokaEud3d3Q101atQw1AWgUF0dOnQwvF7Ozs7UuHFjqS57e3ur97i3336b2rZtq+Nsv4iusmXLUocOHQyvl5OTEzVu3Fh92fqv6KpevbpVT9CmTRuqU6eOVa9ipMvR0fG1ehUjT/A6vUphnqBVq1ZUv379P6VXadCgwSt5gpf1Ku3atbPqVV5W16t4ghf1KtY8gZEuFmBlNMP+314omhH969SrcESLqqiKqqiKqqiKqqiKqqiK6s9XdevWxUcffYQpU6boxi3+m+tFZ0SLFfZ/KKrXX0uWLMHo0aPBvxSoV68eTCYTWrZsiaNHj2IFIXVOAAAgAElEQVT//v3qmp2dHTw8PGAymVC6dGlMnz5dYHtVrlwZ/fr1Q9euXREQEIClS5cKf17z5s1hMplQr149rFmzBtevX1fXSpYsiR49esBkMiEhIQFTp04VdNWtWxcmkwmtWrWCt7c39uzZo64xNqCXlxfKlSuHGTNmCEyoSpUqqbqCg4OxePFiQVezZs1gMpnQoEEDrF27FlevXtXp8vLyQnJyMr777jvh4b1OnTowmUxo3bo1Tpw4gd27dwu6OnbsCC8vL5QvXx6zZs1CTEyMul6xYkX069cP3bt3x+3bt7Fo0SJBV9OmTVVd69evx5UrV9S1t956C927d4fJZEJqaqo6S8fqnXfegclkQtu2bXHy5Ens3LlT0OXu7g6TyYQKFSpgzpw5iIyMFHT17dsX3bt3R0hICH7++WdBV5MmTWAymeDg4ICNGzfi0qVL6lqJEiVUXRkZGZg8ebLAlatduzZMJhPc3NxgNpuxbds2nS4vLy9UqlQJc+fORXh4uLpeoUIF9O3bFz179kRISAgWLlwo6GrcuDG8vLzg7OyMzZs3w9fXV9DVrVs3mEwmZGVlYfLkyQInrVatWqquM2fOYOvWreoaYwOaTCZUrlwZP/74I8LCwtT18uXLq7pCQ0Mxf/58QVejRo1gMpng7OyM33//HefOnVPXihcvrurKzc3FpEmTBB5ZzZo1YTKZ0K5dO5w7dw5btmwRdLVr1w4mkwlVq1bF/Pnz8fjxY0FXnz590KtXLzx8+FCdKWLVsGFDeHl5wdXVFdu2bcOZM2cEXV27doXJZEJBQQEmTZokMCRr1KgBLy8vuLu7w9fXF5s2bRJ0ubm5wWQyoVq1ali4cCFCQ0PV9XLlyqFPnz7o3bs3Hj9+rM4/s3JxcYHJZELDhg2xY8cOmM1mdc3e3l7VRUSYNGmSwETkdV28eBEbNmwQPpvpevvtt/Hzzz/j/v376lrZsmVVXWFhYeqsEytnZ2eYTCY0btwYu3btwsmTJwVdnp6eMJlMsLGxwaRJkwTGX/Xq1eHl5YWOHTvi0qVLWL9+vfDZbdu2hclkQo0aNbBo0SKEhIQIunr37o2+ffsiLCwMs2fPFs51cnKCyWRCkyZNsGfPHnh7ewu6unTpApPJBDs7O0yePFngsjJmoYeHB65evYo1a8SxmjZt2sBkMqFmzZpYvHgx7ty5o66VKVNG1RUREYFZs2YJ5zo6OsJkMqFp06bYu3cvjh8/rq4VK1YMXbp0gZeXF4oXL44pU6YIHEjGLOzUqROuX7+OVatWCZ/dunVrmEwm1K5dG0uWLEFwcLC6Vrp0afTq1Qv9+/dHZGQktHkUDg4OMJlMaNasGQ4cOIAjR44Iujp37gyTyYQSJUrgu+++Ezh9VatWRf/+/dG5c2f4+flh5cqVwme3atUKJpMJ77zzDpYtW4aAgABBV8+ePdG/f3/ExMRg+vTpwrkNGjSAyWRC8+bNcfDgQRw+fFhdY7xgxmeeOnWqwDCtUqUK+vfvjy5dusDf3x/Lli0TPrtly5YwmUyoU6cOVqxYAX9/f3WtVKlS6NmzJ0wmE2JiYjBt2jTh3Pr166ue4PDhwzhw4ICgq1OnTvDy8kLp0qXx/fffC8zEypUro3///vD09MStW7fw22+/CZ/dokULmEwm1K1bF6tWrQK/YVCyZElVV1xcHL7//ntDr3Ls2DHs27dP0NWxY0eYTCaULVsW06dPF3ifvFcJDAzEkiVLBF3NmzeHl5cX6tevb9WrJCYmqvP1rArzKkxXuXLlMHPmTIEBzrxKt27dEBwcjF9//VXQ1axZM3h5eRl6AqbrZbxKhw4dVE8wa9YsREdHq+uFeRXeE2zYsAGXL18WdDFPkJaWhsmTJ0u9Sps2beDj44MdO3YIuphXqVixImbPni31Kj169MDdu3elXsXLywtOTk7YuHEjLl68qK69iFfx8vKCm5sbTp8+LXgVxjE2mUxWvUqPHj1w//59/PTTT4Iu3hNs2bIF58+fF3QxT5CdnY1JkybpvIqXlxfatWtn1auwexU/V1pUmnqRbdN/11HUmiuvefPmGTIL2cyGjFlIpMTAA3JmIRHR+++/L2UWEpE6xymbzyNSIr6NmIX5+fnk7Owsnc8jUtAwgH4+j9UHH3wgzOfxEeXPnj2jkiVLSpmFREqUtmw+j+lq2LChdD6PSIlbB+TMQiKif/7zn1JmIRFRXFwclSpVSjqfR0S0ZMkSQ2ZhQUEBNWnSRMosJCK6ePEiAXJmIRHRp59+KmUWEinojjJlykjn84gUjAWgn88j+oN5KJvPI1JizQE5s5CIaNiwYVJmIZGC7ihXrpyUWUik4CIApeVLyyy0WCzUqlUr6XweEZGfnx8B8vk8IqLPP/9cyiwkUliMFSpUkDILiYjWrl2r6tLiVCwWC7m5uUnn84gU1AkgZxYSEX311VdSZiGRgu6oVKmSlFlIRLRx40a15UvLLLRYLOTu7i6dzyNSkCKAnFlIRDR69GhDZmFaWhpVrlxZOp9HpCCRADmz0GKxUKdOnaTMQiKi27dvk42NjZRZSEQ0duxYQ2Zheno6VatWjapUqUKffPKJMJ9HpGAGADmzkIjI09NTmM/jsSUhISFka2srZRYSEU2YMMGQWcj4zDK+MtEffGYZs5CIqEePHsJ8Ho8tefDgAdna2kqZhUQKn9mIWZiVlUU1a9aUzucREe3bt48AObOQSOEzy+bziJQ5Tjs7OymzkIjo+++/l87nEf3BZ5YxC4mIDh06RMAf83labEn//v2lfGWiP/jMMmYhEdHMmTPV+bz58+cLzMKcnByqW7eudD6PSEHpAHK+MhHRwIEDpcxCImWO097eXsosJFKQbkZ8ZcZnNmIWsswJ7Xweq0GDBknn84j+yJyoVauWbj6PSMmckM3nEZGaOWHkVVjmhHY+j9XgwYNVT/CvepWFCxcKnkDrVVxcXASvwnsCNscp4ysTKZkTMr4yEamZE8yraD3BokWLhJl9rVdp1KiRoVdhmROurq40fvx4HWLt448/tupVSpcurXqVQ4cOCbpY5oSbm5vUqzRt2tTQq1y6dEn1KuPGjdN5lSFDhlj1KmXLllW9itYTsMwJGV9Z5lV4T8AyJ5gn0HqV4cOHG3oVljkhm9kn+iNzwsirtG7dWspXftMLRTOif506cuSIlFlIpEB6rfGJzp8/L2UWEik3+EOHDknZgEQKh8+IWUik3GiNvlBRUVE6k63VJWMWEik3+IMHDxrqCgoKMmQWEhEdO3ZMygYkUm5Y1nRduHBByiwkUm7wBw8elDILiZRQFiNmIZESMGGk69mzZ4bMQiLlQVTGLCRSbvAHDhyQsgGJlFAWI2YhEZG3t7eUWUik3EiNmIVEyk1HxiwkUm6kBw8eNNR19+5dQ2YhkWKYZMxCIuVGasQsJFICmGTMQqbrwIEDUmYhkfKQYcQsZLpkzEIi5UZqbd7jypUrUmYhkXKDt6br/v37hsxCIiUoRMYsJCJKTEw0ZBYSKS8UjJiFBQUFdPDgQSmzkEh5+DFiFhIpsG8Zs5BIucEbMQuJFPPAm3++LBYLHTx40BAMHhoaasgsJFJe0smYhUTKQ78Rs5BICacw4hgzXTI2IJHyUGbELCRSDLmMWUhElJqaasgsJFJewFjTdejQIUNdjx8/NuQrEymBLzJmIZHy0G/ELCRSGLhGzEKLxUKHDx+WMguJFP6kEceYSHmpKWMWEim8Tmu6/P39DZmFFouFjhw5ImUDEin8SSNmIZHyAGOkKzMzkw4fPixlFhIpwWNGzEIisqorPDzcqic4d+6coSfIysoyZCkSEQUEBBjylYkUT2DNqxhxjImse4Ls7GyrnuB1ehVfX99CvYo1T/AqXsWIr0z0al7l9u3bhXoVI0/wql7Fmid4Ea9izRO8ilex5qFCQkIK9SpGniA+Pt6qV3mT69/2IArgHQBnAYQAuAPgm///v88EEAUg4P8f/Qr7rKIHUXmFh4cb/iO2WCyGP5JEypfTyNgSKebD6MuVkZFh+OV6EV2hoaGGP8CvoiszM9PQcBMpNzwjY0tE9PDhQ0Nd8fHxhoab6TIyallZWYaG+1V1JSQkGBruwnRlZ2cbGm4i5S33y+pKTEx8aV05OTmF6jIy3C+iy8hwEynm1shA5ubmGj4IECnG5WV1JSUlGRruwnTl5eUZPggwXUaGuzBdycnJhsb2RXQZGW4ixVAZGdvCdD1//tyqrrCwMENd+fn5Unj5v0uXkeFmuoyMbUFBgVVdMTExhoabSHmQNdKVkpJi9W17YbqMHlBeRNfDhw8Nf7NTU1MNDTeR8lBnZCALu8c9e/bM0HATKdfLSFdaWpqh4X5VXbGxsYbGtjBd6enpVnWFh4f/R3RlZGQYPggwXa/LExSm63V5lfj4+EJ1Gd3jXqdXSUhIeCO9yuvyBIV5FWue4FV0vcn1og+ihXJEZ82aVRrAZSL6ftasWb8DWDdr1qzTABoD8CWiT2bOnLlq5syZoVY/CEUcUaO6ffs2mjVrBn9/f2RlZQmMJBsbG4wdOxYTJ07EkydPdIyk7OxsODo6wsfHB8nJyTpG0vbt2zFgwACEhIToGEl2dnbo0qUL1q1bh5iYGB0j6d69e2jSpAlu3ryJrKwsgZFkY2ODiRMnYty4cVJdOTk5cHJywsmTJ5GcnKzjJu7atQteXl4ICQlR+YRMV7FixdCtWzesXr0aMTExOm7igwcP0LhxY9y4cQMZGRk6PuGUKVPw7bff4smTJzpuYm5uLpydneHt7Y2kpCQdn3Dfvn3o168f7ty5o+Mm2tnZoXfv3lixYgWio6N1uh49eoSGDRvi+vXrUl3Tpk3DqFGj8PjxY52u/Px8uLi44Pjx40hKSlI5gKwOHTqE3r17q7p4bqKdnR369u2LZcuWITo6WsdNDAsLg6urK65fv66yrnhdM2fOxMiRI/Ho0SMdz7GgoACurq44evQoEhISdNzEo0ePokePHrh9+7aOm2hrawuTyYQlS5YgKipKpysiIgLOzs64evWqqosf5J8zZw6+/PJLVRfPc7RYLGjUqBEOHz6MxMREVKpUSeAment7o1u3bqounk9oZ2eHv/3tb/j1118RFRWlcgDZuVFRUXB2dsaVK1eQnp6u40zOnz8fI0aMwKNHj6TcxEaNGuHgwYOIj4/X8QlPnToFT09PBAcH63iOtra2eP/99/Hzzz8jIiJCxyd89uwZnJyccPnyZaSlpen4hAsXLsSwYcPw8OFD2NnZ6fiXTZo0wb59+6S6zpw5g06dOiEoKEjHc7S1tcUHH3yABQsWIDIyUscBjIuLg6OjIy5duoS0tDQdZ/LXX3/Fp59+itDQUJUDyHTZ2NigWbNm2LNnD+Lj43XcxPPnz6Njx44ICgrS8RxtbW3x8ccfY968eQgPD9dxExMTE+Ho6IgLFy4gNTVVxydcunQpPvnkE4SGhsLW1ha1a9dWeXu2trZo2bIldu3ahbi4OJ2uS5cuwd3dHYGBgcjNzRUYzzY2Nvj0008xZ84cqa7k5GQ4ODjA19cXqampOsbz8uXL8Y9//AMPHjwAIHIAbW1t0bp1a+zYsQNxcXE6buK1a9fg5uaGgIAAHTfRxsYGw4cPx8yZMxEeHq7jJqakpMDBwQHnz59HSkqKjk+4Zs0afPDBB+o8L6/Lzs4Obdu2xbZt2xAbG6vT5efnhzZt2iAgIEBlYvO6vvzyS0ybNg1Pnz7V6UpLS4ODgwPOnj2LlJQUHeN53bp1GDx4MO7duyfV1b59e2zZsgWxsbE6buKtW7fQqlUr3Lp1S7338rpG/j/2zjsqqmtt488UqlgRkGZFGAUsqNiwGyskpmliTDTXxBQTE1M0aoq9RI09GmONscRegooFFQSlWrEXUARRUURAkfJ+f5xv75yyZ7Dc3Guu8641a92Vfc/kyYHhPLP3+7y/Tz7ByJEjkZaWpuEm5uXlwcfHB5GRkcjJydHcr2XLluHVV1/FmTNnQESaZ2+rVq2wbNkyXL9+XaPr+PHjaNSokVlP8Pnnn2P48OFITU3VMJ4LCgrg4+ODPXv2ICcnBy4uLgpPsGLFCvTq1QunT58W6mrTpg2WLFmC69eva55xKSkpaNCgAfcEal1ffvklvv76a6Smplr0Krdv39Z4gtWrVyMsLEzoVYxGI9q3b49ff/1V6FXOnj2LgIAAJCYmcv6lXNfw4cPxxRdfmPUqPj4+iIiIEOpau3YtevbsiVOnTgl1derUiXsVJycnha7z58/D398fCQkJKCgo0Dx7R44cadarFBUVwdfXl3sCtVfZuHEjunfv/kheRf3svXTpEvcEIq/y/fffW/QqJpMJ4eHhyM7O1ujaunUrunTpYtar9OjRA3PnzhV6grS0NJhMJsTFxSE/P1/z7B07diw+/vhjXLp0SfOMY15l27ZtyM7O1niV8PBwi17lpZdewsyZM3Ht2jUNSzk9Pd2iV5kwYQI++OADs57gea2/jSMKYAuAFyCdiH71ONdaT0TFdfLkSc5bBJTcxIMHDyoYbICSkZSUlET9+vVTrNevX5+GDRtGe/bsobi4OMX4ejkjKT4+XsEZBZSMpKSkJM5bZLpYBuPgwYMKBhvwF89xxYoVlJiYSP3791ess1zm7t27KT4+XjGOXZ7BiI+PV3BGAQkRwHKZiYmJFBwcrNDFMhjR0dE8u8Ne8gxGUlISZ1GxF8tl7t69mxISEhTjxeUZjPj4eAVnFJAQASyXmZSURC1btlSsswxGdHS0gg3HdL3++uu0fPlySkpK4txM9mK5zN27d1NiYqICVcEyGLNmzaK4uDiaNWuW4lo5NzExMZFCQkIU6yyDERUVRREREYqR/CyDsWzZMkpMTOTcTPZiGYxdu3ZRQkKCYmS/PIMRFxfH86nsJc9gJCUlUbt27RTrLINx4MAB2r17t2L0vTyXmZSURIMHD1Zc6+PjQ0OHDqVdu3ZRYmKiAs/B8qIzZsyguLg4+vnnnxXXslzmxo0bKSkpiXMg2YvxHKOiomjv3r2KEfPyXGZiYiINGTJEcS3Li0ZERFBSUpICB8Dyoj/99BMdPnyYFi5cqLiW5TI3bNhASUlJnAPJXiwvun//foqMjFSMmJdzExMTE2no0KGKa1ledOfOnZSUlKRARshzmYcPH6ZFixZpdPXv35/Wr19PSUlJ1K1bN8U6y4vu37+f9u/fr8DOyHOZiYmJCp4nAJ4X3blzJyUnJ3PeolzXtGnT6NChQzw3y17yvGhSUhL17NlTsd6oUSP69ttvad++fRQVFaXAuzg6OtKLL75Iv/76KyUkJNDw4cMV17K86Pbt2ykpKYnzFpkulss8dOgQz82yl5znmJycTC+++KJineUy9+3bRwcPHlTgXeSM58TERAXPE/gLEcB0Md4ioOQmxsbGKrisgJLnmJycTC+//LJG18iRI2nfvn0UExOjwILIGc/x8fEKnifwFzcxPDyckpKSOG+R6WLcxNjYWFqzZo3iWjnjOSkpifMp2YvlMiMjIyk2NlaBuZDzHBMSEmj06NGKa1lelOlivEWmi+UyY2JieJ5XrosxnpOSkjifkr1YLjMyMpIOHTqkwEnI86IJCQk0duxYxbVybmJSUhLnLQJKxnNMTAzP87KX2hMwljZ7sVzm3r17KS4uToEmkudF4+PjaeLEiYpr5bnMxMREzltkuuReZfPmzYprWV70999/p6SkJM7SZi+WyxR5FfkMifj4eAVnFFAynpOSkqhp06YKXcyrREdHa7yK2hOY8yp79uwp06vIOaOAkvGcmJjI2dBMF/MqUVFRFB4ertHFcplJSUk0cOBAxbraq8iRI8yrzJ49m+Lj4xWcUaZL7lVatWqlWGczJKKiomjHjh1CT8C8yqBBgxTXqr2KHHuk9gSWvEpSUhK1adNGsS73Krt27VLokucyExMT6aOPPlJcy7xKREQEJSQkKHA5csZzXFycgokOKL1KYmIitW/fXrHOZkiU5VWe57wo/g58i06nqwkgCkAAgC8ADACQCyARwJdEdMfctYAV32KurPgWa1nLWtaylrWsZS1rWet/p9gE3dDQULz++uuoW7fuf1vSf6weFd+if4w3dAKwAcDnRJQLYD6AOgAaAcgEMN3MdYN0Ol2iTqdLlCNGrPVX2djYmB3tbGtra3Hss729vdl1g8Fg8VoHBweL66wF6d+tS6/XP/G1z7Iu1roiKks/46fVVdbP0ZKup7lfOp3uqe6X0Wg0u/409+u/qcvSz+JpdVn6d1vSXJausrTZ2dlZvNbS79DT3K+ydJV1vyzpelbv139Tl6X1p32WWHU9vq4n+ff+N3X9nV7lWfUE/1QP9Sx7AnP1T/UEXl5eaNy4MYKCguDt7W32//dc16McmwKwARAB4Asz6zUBnCzrfaytueIqKSlRtOGwEfhsCmZsbKym1WrKlCl8Cua7776raWliI/Czs7OpfPnyfF09Al/eoihvaUpPT+fjstm6egR+fHy8sKWJTcF8//33NS1Nq1evptu3b/Nx2WydtVqxKZjyFkX1CPzS0lJFGw4bgc+mYCYlJQlbmtgIfHn7hnoEfk5OjqINx9/fX4HFWbx4sbCl6cqVK1RaWkotWrRQtDR9+OGHfArm0aNHhS1NbArmJ598omlpYiPwc3NzFW04cixOcXExLV++XNPSNG/ePEpNTaXS0lJq3bq1oqWJtV/n5+fTiRMnhC1NbAT+559/rtAlH4Gfl5enaBlWY3HkrYCiEfjy1lw1FufUqVO8DUcnGIEvb+mUt1rdvHmT8vPzFW04rKWJTeeUtwLa2NhoRuDLW3PVWJyzZ88q2nDUI/DlLZ1sBD7D4hQUFChahllLE5vOuX79eoUu9Qj8Ll26KFqH5Fic8+fPK1qG1SPwR40aJWxpunHjBj148EDRMqwegS+PB4hG4Hfv3l3Y0nTv3j26dOmSomVYPQL/+++/N9vSVFhYqGgZZu3XbDrntm3b+Jq8/ZoNcwkLC+Pr8vbre/fuUWpqqqJlmLVfsymY8tZJNRbn4cOHipZhOa6nsLBQ0YYvb79mUzDlLbDy9uvc3Fy6evWqomWYtV+zKZgTJkxQ6GLt19evX+e4L7auxvXs2rWLr8nbr9kUTHkLbNWqVXn7dW5uLkdosPXGjRsrsDhTpkzha/L268zMTCoqKlK0DLP2azYFk+G+mC6GxWFTMN944w2+zrA4DNeTmZmpaBlm7ddsCqa8dZJhcX799VfKyMjguC+2ztqv2RTM/fv3K3Sx9ms2sfutt95S6GLt12zYlbxluGHDhgoszsyZMxW6WPv1tWvXqKSkRNEyzNqv2cRuhvtiz17Wfs0mdstbTVn7NfMEN2/eVLQMs/ZrNrFbHqeQt1+np6dTSUkJNWzYkK+rPcGhQ4cUulj7NfMq8lZTefs18yrylmE1Fmf+/PkKXcyrME8QFBSk0CXH4jDcF9Ol9iryVlN5+7XIq7D2a+ZVGO4LUHoV5gmaNWvG1+Xt1wUFBRz3xZ5xaq/y8ccf83XmVZgnuHv3rsKrqBF+S5YsUehiXiUtLY3jvti6Gotz7NgxhS41wu/TTz/l6/L26+zsbI77Yutqr/Lbb7/xNTXCr7S0VBEjUiP8GO6L6VIj/OTxEzUWJy8vT9EyrPYqDPfFdHXt2lXhCeStuWqvcvr0aaFXMTex+3kp/Bun5uoA/AZgpuqfu8v+91AAa8p6L+sXUXFt2rRJyMRk1bt3byFnikia1hUYGChkYhJJPDIRZ4pImmDWvHlzIROTiGjr1q0WP1BvvvmmkDNFJE3hDAwMFDIxiYgmTJjA8wzqCZOFhYXUokULIROTSBqJLmJisurXr5+QiUkkTdcLDAwUMjGJiKZMmSLkTBFJ01ZbtWolZGISSXgNEWeKVf/+/YVMTCJpKltgYKCQiUlENG3aNCETk0iaahoSEiJkYhJJuAgRE5PVv/71L7N5hoyMDAoMDBQyMYmIZsyYIWRiEklTTdu2bcvNv3ry5f79+4VMTFbvv/++kIlJJE3SZLpEI/DnzJkjZGIyXe3btxcyMYmkcf4iJiarDz/8UMjEJJImQwYGBgqZmEQSJ03ExCSSNqQ6duwoZGISScgac0xMIqLBgwcLmZhE0qTDBg0acCamesLkL7/8ImRiEklTJzt37ixkYhJJCBZzTEwiiVEqYmISSVOGGzZsKGRiEhEtWrRIYf7lv7ulpaXUtWtXIROTSEKKqM2/vIYOHaow//LKycmhRo0aCZmYRBLTVcTEZLq6d+8uZGISSYgMZv5FWJyvvvpKyMQkkqbmNm7cWMjEJJKYriImJtMVGhoqZGISSdisBg0aCJmYRETDhw8XMjGJpOm0QUFBQiYmkcR0FTExma6XXnpJyMQkkpAPgYGBQiYmEdHIkSOFTEwiaTptkyZNhExMIqI//vhDyMRk9fLLLwuZmEREZ86cocDAQCETk4jou+++EzIxiaRpq02bNhUyMYmI1q9fTy1bttQwMVm9/vrrQiYmkYQ1CgwMFDIxiSR2qoiJSSRNWw0ODhYyMYmINm/eLGRisurTp49Zr3Lx4kXuCUS4nvHjxz+SV1EzMYkk3I2Iicmqb9++Zr1KamoqBQQECJmYRBLnXcTEJJK8SsuWLYVMTCIJkyJiYrJ6++23hUxMIsmrBAQECJmYRBLn/VG8ipqJSSQhtyx5lQEDBphlYqanp1NAQIBiQ1Be06dPL9OryDcE5bV3716+ISjyKgMHDqRXXnlF6AkyMzMtepWZM2da9Crt2rVTbAjK68CBAxa9yqBBg+jll1/mG4LWkupRv4iWmRHV6XQhAKIBnADAgowjAbwJqS2XAKQC+ICIMi29lzUjKq6ioiI+5U9dRITi4mKz65auLWu9uLgYer3ebPvIP1FXWetWXY+vy1JbiqVrS0pKoNPpnkldgPn2JKuuf4au0tJSafT7M6irtLTUbJuZVZey/s5niSs5cdEAACAASURBVFXX460XFxdbbJP9J3qCZ1VXWetWXY+v61l8xj3Ppft3ZUSJ6CAR6YioARE1+v/XdiJ6m4gC//+fv1jWl1Brma+bN29i6tSpfJy6vHQ6HbZt24Y//vgDd+/e1Vyr0+kwadIkHD58mH+Y5HXkyBH88ssvuHbtmmbNaDRi4cKF2LlzJx48eKBZz87OxpQpU3Dq1CmhrvDwcKxZswY5OTlCXZMnT8ahQ4eEuo4dO4YFCxYgPT1dqGvRokXYsWOHUNedO3cwZcoUpKSkaHQBErpj9erVuHNHOztLr9dj8uTJiImJEeo6ceIE5s+fj6tXrwp1LVmyBNu3b8f9+/c163fv3sXkyZNx8uRJoa6IiAisWrVKqMtgMGDKlCk4ePCgUFdKSgp+/vlnXLlyRahr6dKlCA8PF+q6d+8eJk2ahBMnTgh17d69GytXrsTt27eFuqZOnYro6GgUFxdr1k+fPo158+YJdRkMBixbtgzbtm1DQUGBZj0/Px+TJk3C8ePHhbr27NmD33//HdnZ2cL/5mnTpiEqKkqo6+zZs5g7dy7S0tKEulasWGFWV0FBASZOnIhjx44Jde3btw8rVqzArVu3zOo6cOCAUNf58+cxZ84cpKamCnWtXLkSW7ZsQX5+vmb9wYMHmDhxIo4ePSrUtX//fixfvhyiLL7RaMRPP/2E/fv3o6ioSLN+8eJFzJ49G5cvXxbqWrVqFTZv3izUVVhYiIkTJ+LIkSNCXVFRURZ1zZgxA/v27RPqunz5MmbNmoWLFy9q1vR6PdasWYNNmzYhLy9Ps/7w4UNMnDgRycnJQl0HDx7E0qVLcePGDaGumTNnIjIyUqgrLS0NM2fONKtr3bp12Lhxo1BXcXExJk6ciKSkJOGQutjYWCxZsgRZWVmaNRsbG8yePRt79+7Fw4cPNetXr17FjBkzcP68lqam1+uxfv16bNiwAffu3dOsl5SUYOLEiUhISBDqOnz4MBYvXozr168Ldc2dOxd79uwR6rp27Rp++uknjqSRl06nw6ZNm7B+/Xrk5uZq1ktLSy3qiouLw6JFi8zqmjdvHnbv3o3CwkLNemZmJqZNm8aRNGpdW7Zswbp164S6iAgTJ05EXFycUFdiYiLHjYh0zZ8/H7t27RLqunHjBqZOncrRL2pd27Ztw9q1a4WeAAD3BCJdycnJWLhwITIyMjRrRqMRCxYsQEREhFDXrVu38OOPP5r1KuHh4fjjjz/MeoJJkyaZ9QRleZVff/3VrFe5ffu2Ra+yfft2s16FeYLY2FihruPHj5fpVbZv3y7UlZOTg8mTJ5v1Kjt37vxbvYo5T5Cbm/tIXsWcJ7DkVU6dOlWmV/nzzz+FuvLy8sr0KuY8waN6FXOe4Lfffntir7J3716zuqz1CPUox6b/rpe1Ndd8sUyaPGvEWgvOnDlDer2eZ43kGSgi4pk0edaItTzIM2mi1oJ169bxrJGotYBl0tRZIyLimTSj0Shsg2SYATnqgbU8yDNpojZIlklTZ41YsUwayxrJ2yBZJk2OepC3QbJMmhz1wNoN5Zk0URsky6TJUQ9yXSyTxrJG8jZIlkljGSh51oiIeCZNnjViuuSZNNYGKW83ZJk0edZI3p7Zq1cvrkvdBskyaaKsERHxTJoc9cDaIOWZNIagYFkjIuKZNAcHB541krdBskway0XL2yCvXbtGdnZ2wlw0EfFMWpUqVXgbpFwXy6QFBgZq2g337t2ryRrJ2yBZJk2dgSIinkkTZY2IiGfS5Llo1gYpz6Sps0ZExDNp9vb2wjZIlkljGajw8HCui2XSRFkjIuKZNHUumogUmTR1LpqIKDo6WpM1krdBskway0DJ2w1ZJk2UiyaS2qiZLnUbpDyTps4aERHPpMmxVPI2SIZqkmOpmC6WSRPloomIZ9LkWCrWblhaWsoxFuqsERHxTJooF01EPJMmx1KxdkOWSRPloomIZ9LkqAe5LpZJU+eiiYhn0uRYKnkbJMukyVEPTJc8kyZqg2SZNDmWirVByvPz6lw0EfFMmigXTUQ8kyZHPbA2SHl+XtQGyTJp5cuX10Qj5Jk0dS6aiOjEiROk0+mEuWgi4pk0eS6a6ZJn0lgbpLzdcOXKlQQoc9Hy9kyWSVPnoomIZ9JEuWgiqb0b0OaiiSRPUK1aNQK0uWgiqV1Z7gmWLFmiaM/s1KmTWa9y7tw57lWYJ5C3QX7zzTcar8I8wf379zVeRe4JWH5enYtm1bVrV7Ne5cKFC2QwGIS5aCLi+XlzXsXLy4t7FbUnYMgac16lR48eZr3K5cuXuVdR56KJiH744QeLXqV69ercq6ijEQxjJ/cqck/AEFLqXDQRUVpaGvcq6lw0kRT5suRVatWqpfAEcq+yY8cOi17llVdeIUDKRas9QXp6ukWvwtBDj+JV5LloIqLdu3fzZ6/Iq7z++uvcqzBPwHSx/LwoF/08F/4OfMvTlrU1V1xDhw7FyZMnsWfPHsU/r1ixIpo2bQqj0YgjR45odu5NJhPc3d1hNBqxe/duxZqtrS1atmwJnU6HrKwsnD59WrHu4eGBevXqwcHBATt37lTsIOl0OgQHB8NoNKK0tBSHDh1SXFuhQgU0a9YMRqMRR48e1ezc+/n5wcPDAzY2Nti1a5dZXTdu3MCpU6cU6+7u7vD394e9vT0iIiI0pxHBwcGwsbEBESE2Nlaoy2Aw4MSJE5qdaF9fX3h6esLW1hYRERGKNRsbG7Rq1QqAdBJ88uRJxXq1atXg7+8PBwcH7Nq1S7Pr36xZM9jZ2YGIEBMTo1grX74815WSkqLZia5bty6HZO/cuVOji90vkS43NzcEBgbCzs4Oe/bs0exiN23aFPb29kJdTk5OCA4OhsFgwOnTpzU7vj4+PqhevbpQl9Fo5PcrJycHx48fV6y7urqiQYMGsLOzQ2RkpGb3s0mTJhwcHx0drVgrV64cmjdvDr1ej7Nnz2p2fOvUqYMaNWrAzs4OO3bs0Ohq2bIlAGnX99ixY4p1FxcXNGzYELa2tti/f79m9zMoKAjlypWDTqdDVFSUWV3nzp3T7PjWrl0btWrVgp2dHbZv365YMxgM/Od47949HD16VKjLzs4OBw4c0JykNW7cGE5OTkJdjo6OaN68OQwGAy5cuKA5ba1VqxZq164Ne3t7hIeHm9WVl5eHI0eOKNarVq2KRo0awdbWFtHR0ZqTtEaNGqFChQrQ6/XYv3+/UJder8elS5c0p601a9ZEnTp1zN6vFi1aQKfToaCgAMnJyYp1Z2dnNG7cGLa2toiJidGcDDVo0ACVKlUS6nJwcECLFi2g1+tx+fJlXLp0SbFeo0YN+Pj4CO+XXq/n9+v+/ftISkpSrFepUgVBQUGwsbFBbGysUFflypWh1+uxb98+xZq9vT1/77S0NM1pa/Xq1VG3bl2zutj9KiwshPo5W7lyZTRp0gRGoxFxcXGaE5iAgAA4OzvDaDRi7969ZnVdvXpVc9rq7e0NX19f2NvbY/v27YoTA7muhw8fIiEhwayuhIQEzYmCv78/XFxcYDAYNLrs7Oy4rmvXrmlOW728vODn5wcHBweEh4crdOl0Oq6ruLgY8fHximsrVaqEJk2awMbGBomJiZruh/r168PV1RVGo1Hz3JbrysjI0Jy2enp6wmQywcHBAdu3b1ecWsp1lZSUIC4uTnFtxYoV+bNE5Anq1asHNzc32NjYCD0B+5ttzhPUr18f9vb22LFjh+K0S6fT8b8xJSUlOHz4sOJauSew5FXMeQL2eRTpknuCJ/UqBoMBx48f15yaP4pXAaST4JSUFLO6HterlC9fnj97zXkVLy8v2NjYCL2KJU9QrVo1BAQEwN7e/rG9ipOTE/+bferUKc3pdFlehf3u3rlzBydOnFCsy73K3r17NSfIzKsAUreKWldZXsXb2xt2dnZCr8Lu13/Dq4SFhSE0NBRt27Z97tp3H7U11/pF9BkoK0fUWtaylrWsZS1rWcta1vrfKy8vL8yYMQOvvvqqRdzL/1I96hdR89Aea/3H6uOPP8apU6cQGRmp+Ofly5dHkyZN+G6eOmNVt25dfiKqvtbGxgbNmzfnJ4/qXVk3NzfUq1cP9vb22LNnj6annp3EEpFmV9bJyQnNmjWDTqdDSkqK5kTUx8eH7zKqd7GNRiNatGgBQDp5VO9+urq6wt/fn++aqXcZ2S61SFe5cuXQrFkzvpun3v2sU6cOPD09LeoiIty+fVujy8XFBQEBAXzXTL3LGBQUxHcZ1bvFcl1nzpzRnIjWrl0b3t7esLGx0eyus5MhQDp5VO/KVq1aFYGBgfyET30i2rhxY77LqN4tdnR05LrOnj2r0VWrVi1+IqreXWe6iAh37961qCsqKkqzy9ioUSO+y6jeLXZwcEBwcDD0ej3Onz+v2f2sWbMmPxFV72IbDAYEBwfzk0f1rqyzszMaNGjAT/jUJ6INGzbkJ6Lq3WKmS6fT4eLFi5rdzxo1aqBWrVqwtbXV6NLr9fzzmJeXp9mVrVKlCj+pjYmJ0ZyINmjQAE5OTtDr9ZrdYnt7e/7ely9f1mRgqlevjtq1a8POzk6zu67X6/l/U0FBgeYEuXLlymjUqBFsbGxw6NAhzYloYGAgKlSoAJ1OJ9TF3js1NVWjy9vbm5+IWtJ1//59zQmyXNfhw4c1GT5/f39UqlQJBoNBc4JsZ2fH79eVK1c0J7VeXl7w8fER6mInMOzkUX2CXKlSJTRu3BhGoxHx8fGaE9H69eujSpUq0Ov1FnVdvXpVc1Lr6enJT0TVu/5yXQ8fPtScIFesWBFBQUH85FGdlatXrx6cnZ1hMBhw4MABxRo7sQKkrKf6pNbDw4OfiEZERGhOHtmzori4WHOCzHQZDAYkJydrMmkmk4mfiKpPtm1tbfn9ysjIwIULFxTr7u7uMJlM/OdoTldJSYnmBLlChQr8fh09elRzIurn58dPRNUn2+xkCJBOHtUntdWqVYPJZOInVupNaPZzLC0t1Zwgl+UJfH194ebm9kS63NzcUL9+fdjZ2WH37t2a/B97Voh0OTk5oWnTpvyET30iasmrGI1G/nO8desWzpw5Y1bXk3iVpk2bQq/X/9e8CgCLnuD06dOaE9E6derwE1G1J2D3C5DmZai7yh7Fq9ja2gp1OTo68mfvk3gV9nMsy6scOHBAcyLKvIpOp9N4AqZLp9Ph3LlzmpNa5gnMeRV2v3JzczUnyHJPIPIqzBMAT+ZV2Ilou3btYGdnB2sJ6lH6d/9dL2tG1Hx17txZky1kOQKWuzCXIxgxYoTZfv379++Th4eHIlsozxFs2LCB9+uzHIG8L75bt268X1+dLbx48SIZDAbS6/U8RyDv1//222/N9us/ePCAZzFFOYItW7YocgTqfv2ePXuazRampqaS0Wg0my0cPXo0z/CpEQuFhYVUo0YNni1kOQKWSQsPD7eYLXzppZfMZguvXLlCNjY2ihyBPFs4fvx4s9nChw8fUu3atQnQMleJiHbu3MmzcqJsIctdMOaqHLGQnp7Os5itW7fWZAsnTZpkNltYVFREPj4+ZjOPe/bssZgt7N27N8/wqRELLHfBMo/qbOHUqVN5hk+dLSwuLiY/Pz8C/uKrybOF+/bt41k5Ubawb9++PMOnzhZmZWWRg4OD2WzhTz/9pMgWMr4akZR5rF+/Ps88qrOFUVFRFrOFb7/9Ntcl56sRSVnMcuXKmc0Wzp49m2f41IiFkpISCgwM5JlHdbYwJibGYraQsYwZX02eLbx16xZnGYuyhfPmzeMZPjViQc4yFmUL4+LiLGYL33vvPZ4tVCMW5HxAUbbwl19+4brUiIXS0lJq0qSJ2WwhYxmbyxZ++OGHmmwhy/Dl5ORQpUqVFNlCOWKBsYwZC1aOXSotLaXmzZubzRYeOXKEgL+Yq2rEAmMZi7KFubm5VKVKFUW2UJ55XLZsGc/wMcSCXFerVq3MZgsZy1g+B0GeLfzss8/MZgvv3bvHWcaiOQiMZSzKFpaWllLbtm3NZgtTUlJIp9ORwWAQzkFgLGM1c5WIKD8/n1xdXXm2UD0HYfXq1TzD16tXL022kM2NEGUL2dwIc3MQhg0bZjZbKJ8bweYgyD0BmxuhZq6yeuGFFzRehT172dwIc9lCNjdCzVwlkrwKmxshmoOwceNGTbZQ7gnY3AhzXoV5grZt22qyhd99951ZryKfGyHKFm7dulWTLZR7gtDQUI1XYc9eNjfCXLZwzJgxFr0Kmxuh5sMT/TU3wpxXYXMjmFeRe4IrV67wLKZoDgKbG6HmwxMps5gBAQEaTxAREWHRq7C5EWrmKtFfcyPMzUGYPHmyRa9St25d7lXUcxDY3AhzXqVPnz4KryKfg5CZmcm9imgOwvNa+HdxRP+dL+sXUXFdu3ZN84GS1/r164UcMyLpwzV+/HghX42I6PDhw0KOGat58+YJOWZE0ofLHMeMSHowyE22WteECROEfDUiaZiHiGPGav78+QqTLa+srCyzzFUiaXiAiGNGJH1BmTBhgpBjRiSxB0UcM1a//PKLkK9GJH0RsAQx3rp1q5BjRiR9EZg4caKQY0YkGUgRx4zVwoULhcxVImkoy7hx44QcMyJpqIGIucp0TZo0ScgxI5KYiCKOGatFixYpBnjI686dOzRu3Dghx4xIepCKmKtEkoGcPHmykGNGJBlbEceM1ZIlS4R8NSLpi8C4ceOEHDMi6Uu/iLkq1yXimBFJxlbEMWO1dOlSIceMSPoiMG7cOMVgEXnt2rXLLMestLSUfvzxRyFzlUgafqIeLCKvZcuWCZmrRNIXgXHjxgmZq0TSEAgRc5Xpmjp1qpC5SkR09uxZIXOV1W+//SZkrhJJw2LGjh0rZK4SScZDbbLluqZPn67YEJTX+fPnNeZfXr///ruQuUokfREYN26ckLlKJG2SiNimrH766Schc5VIGtSm3hCU16pVq4TMVSLpi8DYsWMVJlteBw4c0GwIymvmzJlC5iqRNJRFbf7ltWbNGiFzlUjatBw3bpxiQ1Be0dHRQuYqq1mzZgmZq0SS4RYxV1n98ccfQuYqkfRFYNy4cQqTLa+YmBghc5XVnDlzhMxVImlz0JInWLdunZC5SiRtWo4bN86sJzh06JCQucpq3rx5QuYqkbQ5aMlkb9iwoUyvYs4TxMXFWfQqP//8s1mvcv36dYteZdOmTWa9CvMEIuYq0aN5FXOe4MaNGxa9ypYtW57YqyQlJZXpVUTMVSJpc9CSV9m2bdvf6lVEzFUiiSs9fvx4i17FnCcoy6scO3bskbyKyBM8qlcReYLnuR71i6g1I/oM1N/Jw3saLphV1+NdS0QoKSn5Wzh9Vl1WXUTPJj+wrPVnmTv3pNf+3Yxcq67H02VlHf9ndD2rz16rrse79ll+xv0v6npe61EzoobRo0f/B+RItXDhwtGDBg36j/37/knVvXt37N27FyUlJXz6F6vk5GSEhYUhIyMDTk5OcHd3V3yYvvzySyxYsAD5+fnw8PCAk5MTX8vNzUXr1q1x6tQp2NjYwMvLS/FHcfny5Rg6dCiys7NRtWpVODs7K3T17NmT50W8vLwUuo4dO4YePXrg2rVrQl3Dhw/HvHnzkJ+fD3d3d5QvX56v3bt3D61bt0ZKSgoMBgO8vLwUH/KVK1diyJAhyM7OhrOzM6pWrarQ9eKLL/IJel5eXjwHCQAnT55E9+7dkZ6ejnLlysHDw0Oha+TIkZgzZw7y8vLg4eGh0JWfn4/WrVvjxIkTMBgM8Pb2VuhavXo1PvnkE9y6dQvOzs5wdnZWvPcrr7yC7du3C3WdPn0aXbp0wdWrV4W6vvvuO8ycORN5eXma+1VQUICQkBAcP34cer1eo2vdunX46KOPcOvWLVSpUgVVq1ZVvPfrr7+Obdu24eHDhxpdZ8+exQsvvIArV67A0dERHh4eCmM2evRo/PTTT7h37x7c3d1RoUIFvvbgwQOEhITgyJEjQl0bN27EBx98gJs3b2p06XQ69OnTB1u2bOG6HBwc+LUXLlxAp06dzOoaN24cpk6dinv37qFatWoKXYWFhQgJCUFycrJQ15YtW/Dee+/h5s2bqFy5MlxcXBS63nzzTWzatAmFhYUaXZcvX0aHDh2QlpYGBwcHeHp6KnRNnDgRU6ZMQW5uLqpVq4aKFSvytYcPH6JNmzZITEyETqfjeRtW4eHhePfdd3Hjxg2hrrfffhvr1q0T6rpy5Qrat2+P1NRUoa4pU6Zg4sSJyM3NhZubm0JXcXEx2rZti/j4eKGunTt3on///rhx4wYqVqwIV1dXxe/XgAEDsHbtWjx48ACenp48/wsA6enpaNeuHS5fvgx7e3uNrmnTpmH8+PHIycmBm5sbKlWqpNDVvn17nmVS69qzZw/69euHrKwsVKxYEW5ubgpdAwcOxKpVq/DgwQN4eXkpdGVkZKBt27a4dOmSUNfMmTMxZswYoa7S0lJ06NCBZ4bUuiIjI9G3b19kZWWhQoUKGl2DBg3C77//LrxfWVlZaNOmDS5cuABbW1t4eXkpdM2ePRs//PAD7ty5A1dXV1SuXFmhq1OnTjh48CCIiE+4ZBUVFYU+ffogMzMTFSpUQLVq1RS6PvroIyxfvhz379+Hp6cnz0YBEu86JCQE58+fh52dHTw9PRXPkp9//hmjRo0S6iIidO7cGdHR0SAieHl5KXTFxMTgtddew/Xr11G+fHmNrk8++QRLly7F/fv34eHhodCVnZ2NNm3a4Ny5c8Jn3IIFCzBixAjcuXMHLi4uqFKlCuTVpUsX7N+/H6WlpZr7FRcXh5dffhkZGRkoX7685hk3ZMgQLF68GAUFBZr7defOHYSEhODs2bOwsbGBt7e3QteiRYswbNgw3L59W6ire/fuiIyMRGlpqebZm5iYiBdffJHrUt+vL774AgsXLkRBQQHc3d0VnuDu3bsICQnB6dOnYTQaNfdr6dKl+PLLL3H79m2hJ+jRowfPaqp1HTlyBKGhoWY9wVdffVWmV0lJSYHRaNTcr99++82iVwkNDcWuXbtQXFys8VDHjx+36FW++eabMr3KyZMn+f2SP0tWrVpl0au89NJL2LlzJ4qKijTP3pSUFHTt2tWsVxk1ahRmz54t9ATMqxw/flzoVdasWWPRq7z66qv4888/UVRUBG9vb4WuM2fOKLyKu7u74m+Q3Kuon733799H69atcezYMaG3W79+PfcqlStX1niC1157DVu3bhXer3Pnzln0KmPGjMH06dP5s/dxvMqmTZswaNAgs56gT58+2Lx5s9CrXLx4EZ06dUJaWppQ1/NaY8aMyRw9evTCMv+Pj3Js+u96WVtzzRdjUUGWw5o9ezZvu2AsKsjyTqwVk3Ez2XpwcLAi78RYVFDlnW7evKlgUUGWw9q3bx8VFRVxbiZUeSfWdsFYVEyXnPHGWFRsXZ13YtxMyPJOrO1CzqKCLIfFWjEZiwqqvBNru3j55Zf5ujqHxVhUcl3yvBNjUTFdjPGWlZWlyD/g/3NY8rwTY1ExXWruK2NRQZbDYtxXlolk6/K8U2lpKedmAlrGW3FxMedmQpbD2rNnDz18+JAiIyMVutSMN8bNhCyHxVoxr1+/Tg4ODnxdnXeaPn26QhfLYWVmZiq4mfj/HJY873TgwAG+JmK89evXj6+r806Mm8nW1dzXWbNm8TU1462kpIQCAgL4eq1atRTZ7IMHDyp0qbPZAwYM0OhirZi3bt0iJycnvq7OZs+dO5evsRwWY6nJM5GAlvt6+PBhhS51NnvgwIF8XZ13YtxMtq7OZi9YsEChS57DKi0tpaCgIL6uZrwxbiYABeON5Z0++OADhS459/XOnTs8Ewlos9mMmwlZDou1YpaWllJwcDBflzPe7t+/z7mZTFdISIiiFZNxMwFtNvvu3bs8Ewn8lc1mOaylS5cqdMnzTqWlpdSyZUu+zrivrBXz+PHjCl0sh8VaMYcMGcLX1Xmne/fucW4m8Fc2m7Virlixgq+p806lpaXUpk0bvq7OYZ08eZJ0Oh0BEGazGTeT6WLZ7Nu3b1NeXh7PRAJ/ZbOZrlWrVil0qbPZjJsJ/MV9Za2Yp0+fJr1ez3W1bNlS0Yr59ddf82vV2Ww5NxP4i0fLWjHXrl2rePaybDbTxeY3AH9ls1krJpvfwHSps9lsfgOgzWbL5zcA2mw2m9/AdLFsNmsRZfMbgL+y2UwXm9/A1tXZbDa/gemSZ7Pl8xsAiUcrz2az+Q2AMpvNvAqb3wBos9mMm8nW1dlsNr8BEHsVNr8B0GazGTeT6VJ7FTa/gekaOHAgj42w+Q1sXe1VGDcTEHsVNr+B6ZJns9n8BvbsVWez2fwGQJvNZvMb2Lo6m83mNzBd8my2fH4DoM1ms/kNTJfaq7D5DYCWUW/Jq5SUlPD5DYCWUS+f3wBos9lsfgPTpc5mv/nmmwpd8mw2m9/A1tVehc1vALSeoLi4mM9vALTZbDa/gT17mVdhnoDNbwDE2eznsWBtzf3nlJOTE0pKSjRTxFjpdDo+Re9x1h5lXa/X/xUYFhTjhj1Lulgr1fOmy9J7s903c+/9tLqe9HfEqut/QxfbGf67fu8t6WKTOq26/j0/R0vv/azqet6ecVZdj6frefUE/01dT/rez+oz7u/SZWNjg/bt2yM0NBRhYWGoVauW8D3+F0tnxbf8c+r+/fsWOaKWPliW1h5lvSx+qbkP3n9TF/1/v/7zpsvSe/+3dAGWf0esuv43dD3N7+bT6irrnlh1Ketp3vtZ1fW8PeOsuh5P1/PqCZ5VXf/EZ9zfpauoqAiJiYlwcXGBq6srPDw8rBgXVVm/iD4DdeTIESQmJmLgwIH8n1WuXBk9evRAhw4d4Ofnh0mTJmH79u18PTAwEGFhYWjUqBGqVq2Kbt26cV6Uvb09OnfujC5dusBkMmH37t2YOnUqv9bb2xthYWFo2bIlfH198eabb3JmnV6vR6tWrRAaGgo/ZcWf5gAAIABJREFUPz/k5OTg3XffVejq3r07OnToAJPJhB9//BHbtm3j6wEBAVyXm5sbunbtytmWdnZ26NSpE7p16waTyYTIyEhMnjyZX+vl5YWwsDC0atUKvr6+6NevH86fP891tWzZkuvKy8vDO++8w6+tVKkS11WvXj1Mnz4dmzdv5uv+/v4ICwtD48aN4e7uji5duvATaDs7O3Ts2JHrioqKwoQJE/i1np6e/H75+fmhf//+nMuq0+m4LpPJhPv37+Ott97i11asWBHdu3dHx44dYTKZMGvWLGzYsIGv169fH6GhoQgKCoKnpye6dOnCOVa2trYKXbGxsRg7dqxCV2hoKFq3bg0/Pz+8++67nCmm0+nQvHlzhIWFoV69enj48CHeeOMNha5u3bpxXXPnzsW6dev4er169RAWFoagoCB4eXmha9euyM/P57o6dOiA7t27w8/PD/Hx8fjhhx/4tR4eHgpd77//Pud56nQS75DpKi0txeuvv86vrVChArp164ZOnTrBZDJh/vz5WLNmDV83mUwIDQ1F06ZN4e3tjW7dunG2pa2tLdq3b891JScn49tvv+XXuru7c10mkwkffvihgk/JdNWvXx+AlKFhVb58eXTr1g2dO3eGn58fFi1ahN9//52v+/r6IiwsDE2bNkWNGjXQvXt3zpBkO6I9evSAr68vjh07hpEjR/Jrq1WrhtDQUISEhMBkMmHw4MEK3mKzZs0QFhYGf39/GAwG9OrVS6Gra9eu/H4tXboUv/32G1+vW7cuwsLC0KxZM9SsWRPdu3fnDEkbGxu0a9cOPXr0gJ+fH1JSUjBs2DB+rZubG3r27Ik2bdrAZDLhs88+Q3x8PF9v2rQp12Vra4sXX3yRrzk5OaFr1678fq1YsQJLly7l6z4+PlxX7dq10aNHD86QNBqNCl1nzpzBV199xa91dXXluurVq4cvvvhCwcht0qQJwsLCEBAQAAcHB/Ts2ZOvlStXjt+vevXqYdWqVVi0aBFfr1OnDsLCwhAcHIw6deqgZ8+enCFpNBrRtm1b9OzZE76+vrhw4QKGDh3Kr3VxcUHPnj3Rtm1bmEwmDBs2TMFWDQoKQlhYGAIDA+Ho6IiePXty81KuXDm88MILeOGFF1CvXj388ccf+OWXX/i1tWvX5rrYvWOsRoPBoNCVlpaGTz/9lF9btWpVrqtevXoYMWKEghXauHFjrqt8+fLo0aMHN2WOjo544YUX+LNkw4YN+Pnnn/m1tWrVQlhYGJo3bw4fHx/06tWLMxENBgPatGnDf47p6ekYPHiwQlePHj3Qrl07mEwmfPfddwrGZKNGjRAWFoYGDRrwv6PMDDo4OCh0bdmyBXPmzOHX1vx/fl/z5s1Rt25dvPLKK5w9aDAYEBISgp49e8LPzw+ZmZn48MMP+bXOzs7o0aMH2rdvDz8/P4wZM0bBJmzYsCHXVaVKFXTr1o2zLR0cHBTP3vDwcMycOZNfW6NGDYSFhaFFixbw9fXFq6++ynnEer0erVu3RlhYGHx9fXHjxg3IZ2pUqVKF6zKZTBg/fryCJ9ugQQOEhoZyT9C1a1fOtmSeoGvXrvDz80NERASmT5/Or61evbpCV58+fZCamsp1tWrViuu6ffv2Y3uV0NBQNG7cGC4uLujatavCq3Tq1Aldu3aFyWTCnj178OOPP/JrmVdp0aIF/Pz80LdvX86xZZ4gLCwMfn5+uHv3LgYMGKDQJfcqU6dOxdatW/l6QEAA11WWV9m3bx8mTZrEr2VehXmod955h3NZmSdguvLz8/H222/za+VexWQyYcaMGdi0aRNf9/f3557A3d0dXbt25Z5A7VWio6Mxfvx4fi3zBK1atYKfnx8GDBjAuaw6nQ4tWrRAWFgYTCYTHjx4gL59+/Jr2WeMeSi1V2GeoEmTJvDw8EDXrl05h1vuVfz8/HD48GGMGTOGX6v2BAMHDuSc0cf1KvPmzcPatWv5uslk4rq8vLzQrVs3zuEuy6swTxASEgI/Pz8MGjSIM77VXoWI8Nprr/FrmVdhun755ResXr2ar/v5+SEsLIx7WnODjqyFv77J/yde1oyo+QoNDSWTyaThChJJrCknJyfq2rWrcFz36NGjNRkRVoWFhVS7dm1q3ry5ht9HJHExRfw+Vi+99BL5+flpuIJE0uh7JycnIb+PSOJiqvOsrB4+fEg+Pj48u6Ie1x0REaHJiMjr1VdfVeRZ5eO609PTqXz58kJ+H5HEmnJzc1PkWVkVFRWRr68vNWvWTMPvI5K4mOqMiLz69Okj5PcRSTicChUqCPl9RBIX09XVVcMVJCKetVTnWVnt27dPk2eVV9++fbkuNVokKyuLKlasqMmIsJoxY4YizypHeJSUlJC/v78mz8oqKipKkWdVo0XeeecdIb+PSMLhVKpUSZNnZTV79mwhV5DpatiwoZDfR0QUGxurybPK69133xXy+4gkHE6VKlU0GRFWP//8M+cKqjMipaWl1LhxY02elVV8fDzProjQIu+//76QNUwkjZh3dnYWsoaJpHH+zs7OijyrXFezZs2ErGEiCRXg6OgoZA0TSVxMEb+PSMLhuLi4CFnDRBIXU8TvY7qaN28uZA0TSfggR0dHIWuYSOJiiljDRBIOx9XVledZ1bqWL18u5PcxXa1btxayhokkfJCjo6Mizyqvzz//XMgaJpKwM9WqVROyhokkNIyINcyqXbt2QtYwEdGpU6fI0dFRyO8jkriYItYwkcTFdHd31+RZWa1Zs0bI72PVsWNHIWuYSOJiMl0itMjw4cOFrGEiCYfj5eUlZA0TSagTEWuYVZcuXYSsYSIJ01OuXDkha5hI4mKq86ysHjx4QNWrVxeyhokkpIiINcyqe/fumjwrq0uXLlG5cuWErGEiou+//17IGib6iz/ZokULDWuYSEJ3iFjDrMLCwoSsYaK/vIqINUwkcTHNeRWWtRSxhokkRIYlr9KrVy/uVdRokatXr1L58uXNepUJEyYIWcNEf7GyRaxhIgmbJWINs3rttdeErGEiCd1nyatMmTJFyBpmuvz8/ISsYSIJTyX3KmpP8MYbbzyxV5k2bRr3KnLWMBHxrKWINUxEtH//fiFrmNVbb70lZA0Tab2K2hPMnDnToicICAgQsoaJJAyUJa/Sv39/i16lcuXKQtbw81ywckT/OVVcXGyW30ck/bES8ftYnTt3Tsh9I5JMoIgryOrSpUtCTt6j6MrIyLAYxC5Ll4gryOry5ctmdZWUlFj8oD+Nrrt37wq5gnJdIk4ekWROLenKzMwU8vseRVdubq5Zft+j6hLxrx5F1/nz583qYgMVzFVqaqqQk8d0nT171qyu69evC/l9cl0iHh2RZObN8fseRZel+5WVlSXk9z2Krvz8fLP8PiKitLQ0ISeP6bJ0v27cuCHk5LG6cOGCWV0FBQVm+X1l6SIii7pu3rz5xLru379vlt9HJG2GiTh5j6pLxO+T6xJx8oikLxnm+H1Pq+vWrVtCft+j6CosLDTL7yOSDLmI3/courKzsy3qunjxopDfRyR9ybCkKz09/Yl13b59W8gVfBRdRUVFZrmCTJeIK/iouixxBcvSZY6BTPRonsCcrjt37vxtnuBpvYolT2BJV0lJyd/mVR7FE/w3vMrTegJLv7tP6wks6UpNTX1iXU/jCf5Or5KVlWVR1/Naj/pF1Dpf+Bkog8GAixcv4ubNm8J1vV6PpKQk3majrps3b/I2GnWVK1cOCQkJvK1SXffv38fJkyeF/e0GgwGXLl0yq8tgMCAxMdGsrlu3buHy5csWdbEWCnU9ePAAJ06cEOrS6/W4fPkyb01Tl9FotKgrOzubtyKLdCUmJvJ2T3UVFhbixIkTZgPtqampyMrKEl5rY2ODhIQE3pakrtu3b/O2I5GupKQks7oePnyI48ePm9WVlpZmVpetrS3i4+Mt6rpw4YJwzdHREcnJycjNzX0iXVevXsX169eF19rZ2SE+Pp63S6nrzp07FnUdOXKEt8eqq7i4GMeOHftbdOXk5OD8+fPC310HBwccPXr0iXVdu3YNGRkZwmvt7e3L1HXu3DmhLnt7exw/fpy37aqrpKQER48eNZuTycjIsKgrLi7O7DC23NxcnD17VqjLzs4OJ06cwJ07d4TXlpaWlqmLtWSqy8HBwaKue/fu4cyZM0Jdtra2SElJMauLiHDkyBGzujIzM5Geni5cc3R0RHx8PG/HE+k6ffq0WV2nT5/mbc7mdLFWUnVdv36dt4qKdMXFxZnVlZeXZ1aXjY0Nzpw5g+zsbLO6kpOTzerKysrClStXzOqKj4/nbYLqys/Px6lTp4S6jEYjzp07Z1aXTqdDUlKSWV03btxAWlqacK1cuXKIj483++wtKChASkqKWV3nz5/nbeHqYp7Akq6n8QTmdJXlVcryBI/iVSx5AnNeRa/X49KlS2Y9wdN6lcTExCf2KqmpqWZ1MU/wJF7F0dHRoicoy6tY8gRleZXs7GyzXoXpMucJCgsLLXqCK1euWPQqZXmoJ/UqRUVFT+xVmIcy9+y1luWyckSfkdq2bRteeOEF7Nq1Czdv3kSlSpU4x8jBwQFhYWH4/vvvcezYMQ3H6PLly2jcuDHWrVuHq1evKhiCer0e48ePR//+/REbG4u7d+9q2IaNGjXC/Pnzce7cOeh0SoZgeHg4OnfujIiICA3b0MHBAb169cK3336Lo0ePatiGV69eRaNGjbB27VpcuXIFDg4OnK+k1+sxefJkvP3220JdOp0OjRs3xrx584S6IiIi0LFjR+zcuVPDNnR0dMSrr76KESNGcF1yVl9GRgYaNGiAP/74A1euXOFMPKZr2rRpeOutt3Dw4EHcvXtXwRA0GAwICgrC3LlzeU5Urmvv3r3o0KEDduzYgevXryvYhg4ODujTpw+++eYbHDlyRMM2zMrKQmBgINasWYO0tDQF21Cn02HGjBno27cvDh48qGEbGo1GNGnSBLNnz+a65Ky+ffv2oV27dkJd9vb26Nu3L4YNG4bk5GQN2/DmzZsICAjA6tWrkZaWpmAb6nQ6zJkzB3369EFUVBRycnIUDEEbGxs0a9YMs2bN4qZezuqLjo5GmzZtEB4ejuvXryvYhnZ2dujfvz++/PJLJCcna9iGt2/fhr+/P1atWoXU1FSui0Gr58+fj9dffx1RUVEatqGtrS2aN2+OGTNmcPMsv18xMTEICQlBeHi4hrloZ2eHgQMHYujQoUhKStKwDXNycuDv74+VK1fi8uXLGl0LFy7Eq6++igMHDmjYhnZ2dmjRogWmT5+O06dPc64w0xUXF4fWrVtj27ZtyMzMVLAN7ezsMGjQIHz22WdITEzUsA1zc3MREBCAFStW4PLlywq2oU6nw+LFi/HKK69g//79Grahvb09WrVqhalTp+LUqVMa3nFCQgJatmyJrVu3atiGtra2GDx4MD799FMkJCRo2Ib5+fnw9/fHb7/9hkuXLilYkDqdDsuWLUOvXr2wb98+DdvQ3t4ebdq0wZQpU5CSkqLhHR85cgQtWrTAli1bNBxmW1tbDBkyBIMHD+bGXM42LCgoQEBAAJYtW4aLFy8q2IY6nQ6///47XnzxRURGRmrYhvb29mjXrh0mT56MlJQUDdvwxIkTCA4OxubNmzVsQxsbG3zxxRf48MMPER8fr+EdFxYWwt/fH0uXLuW65Ky+1atXIzQ0FHv37kV2djaqVKnCGYIODg7o2LEjJkyYgJMnT2p4xykpKWjWrBk2bdqEa9euKdiGRqMRw4YNwwcffIC4uDgN2/Dhw4cIDAzE4sWLceHCBQ3bcO3atejRowf27t2r4R2zbOX48eNx4sQJDdvw7NmzaNq0KTZu3MiZi4xtaDQaMXLkSLz33nuIi4vT8I6Li4sRGBiIRYsWcV3y+7VhwwZ069YNe/bs0fCOHRwc0K1bN4wZMwbHjx/XsA3Pnz+PJk2aYMOGDUhPT1cwBA0GA77//nsMHDgQhw4d0vCOS0tLERgYiIULF+L8+fMatuHmzZvRtWtX7N69W8M2ZNnnH374AcePH9d4gkuXLiEoKAjr16/XeAKDwYAxY8ZgwIABiI2N1fCOiQgNGzbEggULuC4vLy/+jPvzzz+5V1F7AkdHR4teJS0tDY0aNcK6deu4J5A/eydOnIj+/fsjJiZGwzvW6XRo2LChWa+yfft27lWysrJQqVIl7gkcHBzw8ssvY9SoUUKvkp6ejoYNG3KvIn/26vV6TJkyBf369UNMTIzGq+j1eoVXAZSeYNeuXejYsSN27Ngh1GXJq2RmZnKvovYEer0e06dPN+tVjEYjgoKCMGfOHKFXiYyMRPv27bkutVd54403FF5FruvGjRvcq6SmpsLOzk7hCWbNmoU33ngD0dHRQq/StGlTzJo1i29Ayp9x+/fvR9u2bbF9+3ahV+nXrx++/vproSe4desWAgICuCeQ8451Oh3mzp37yF6lVMUVPnjwoEWvMmDAALNe5XmtR+WIWvEtz0CtXLkS+fn5+PjjjxU76LVq1UJISAjc3d2Rnp6OVatW8TU2cKFu3brw9fXFrFmzFDv/zs7O6NSpE1xdXVGuXDlMmTJF8e9s2LAhgoKCUKNGDezduxfR0dF8jQ2CcHFxgclkwogRIxQ7rzVr1kSbNm3g7u6OjIwMxdAWg8GA1q1bw9fXF3Xr1sXcuXMVO+xVqlRB586d4erqCicnJ8WwIkAauNCkSRNUr14d+/fvVwzVcHBwQKdOneDm5saHbsh3EmvUqMF1ZWVlKYa2sEEQfn5+8PHxwYIFCxQ7s1WqVOH3q2LFipg4caJCV2BgIB+QExUVhf379/M1NnDB3d0dJpMJI0eOVOzYVa9eHW3btoW7uztu3ryJZcuWKXSxwQJ169bFwoULFTuglStXRufOnfmXAvlgAkAauNCsWTN4e3sjJiYGe/fuVejq2LEjPDw8YDKZMGrUKMWOnbe3N9q1a4dq1arh9u3bWLJkiUJXy5YtYTKZ4OPjw80lq0qVKvGfY9WqVRVDlABp4EJwcDC8vLxw+PBhxbAPNnDB09MT9erVw7fffqs4ZfHy8uK67t69qxgmwwYu1K9fH3Xq1MHy5cv5Q1auy8XFBW5ublBvtNWvX5/rSkhIQEREhEJXhw4duK7vv/9eccri6emJ9u3bw83NDXl5eVi48K+/r2zggr+/P+rUqYMVK1bg9OnTfL1ixYpcV7Vq1TS66tWrh+DgYHh7eyM5OVkx7IMNXPD29obJZMLo0aMVu/MeHh7o0KEDXF1dcf/+fSxYsEChKzg4GAEBAahduzZWrVrFh0QA0sAF9ln39PTEd999p9BlMpnQvHlzeHl54dixY/jzzz8Vutq3b4/q1aujXr16GD16tGJ33t3dHR06dICbmxsKCwsVQ24AaThUYGAgateujTVr1vCBVkwXu1/e3t6KoVOANAiiRYsW8PT0xMmTJxVDSNhwqBo1asBkMmHcuHGKE+hq1apxXcXFxZg7d67ivZs1a8Z1rV+/XjHQqnz58njhhRdQtWpV1KhRA6NGjVJcW7duXbRq1Qqenp5ISUnBli1bFLratWuHmjVrwmQyYcKECYoTVTc3N3Ts2BGurq4gIsyePVvx3k2bNkWDBg1Qq1YtbNq0CcnJyXzNycmJ66pduzZGjBihuNbHx4frOnv2LDZu3MjX2HCoWrVqwc/PD5MnT1acELq6uqJjx45wc3MDAMyaNUvx3k2aNEHDhg1Rq1YtbNmyBfJnvFxXnTp1MGLECMXJUZ06ddC6dWt4eHjgwoULWL9+vUJX27ZtUbt2bfj5+eHHH39UnMS5uLjwv9lGoxE//fSTQldQUBAaNWqEGjVqYPv27YiLi+NrbDhU1apVUbduXXzzzTcKXbVr10ZISAg8PDxw6dIlxXAUo9GINm3acF3Tp09XnOC4uLjw+2Vra4tp06YpdDVu3BiNGzdGjRo1sHPnTsWgLTYcqmrVqvD19cWIESMUJzS1atXiz7grV64ohqOw4VB16tSBn58fZsyYwQdHAdJwKHa/7O3tFQMMAWlDOigoCNWrV8fu3bsRExOj0MU+jyaTCd98843Cq8g9gTmv4uPjAz8/P8yePVvRDSD3KiJP0LBhQzRp0gTe3t6IjIzUeBX2HHpcr8I8ga+vL3x9fTFv3jzFqbvcq5QvX14xrAhQepUDBw4oPEFZXqV69er8GSfyKnJPIPIq7GdRqVIlxWBFQPIqTFd0dDT27dvH18ryKnJPkJ2drRgwJ/cEdevWxa+//qo4FZV7FWdnZ4wbN06hy9/fH82aNUP16tXL9CrffvutolOF6XJzc0NOTg4WL17M19hwqHr16sHHxwdLlizhQy4BpSdwdXVVDFEC/vIE3t7eiIuLw65du/haWV6FeQJLXoUNLPL39+dYr+elHhXfYv0i+gyUwWAoc2S6taxlLWtZy1rWspa1rGWtf1bVrFkTvXv3xogRI/jp8P96PeoXUWtG9Bmo4OBgBAcHw2AwaNZsbW15K4eoypUrBzc3N94yIS+dTsdb90Tl4OAAZ2dn3pqgLtZmJNJlY2NTpi52GivS5eTkBA8PjyfW5e7u/l/TxdoVzekSjem2sbHh7cOPqwvAU+libWysJUeki512mNPF2hUfR5e9vT2qVKnyRLqMRmOZulxcXHhboGi9LF2sjdKcLtaS8yzpqlatmlCXwWBAhQoVnkqXp6enRV1Vq1a1qEvERmO6qlWrJrzW0dERLi4uvF3xcXTZ2dmhcuXKZd6vJ9FVrlw5VK1a9al0lXW/WHvn4+hydHS0qIv9zX5SXW5ubmZ1sXZrS7rkkQ+RLtGJgK2tLW/vFJWTkxPc3Nx4G6W89Hq9xWfc0+piERlRWXr2Pqouc4ZU3uL7n9b1pJ7gUbyKq6ur1as8pi7Rs/dpvQp7xj2NV/lPe4L/hFf5OzyBh4cHBg0ahDlz5uCHH354br6EPlY9ykSjf9fLOjXXfEVHRxMAAiAcB//OO+8QANLpdNSyZUuaOHEiHwd/8+ZNcnJyIgB8TL18HPycOXP4e7Nx8NHR0VRUVEQlJSXUoEEDAkC2trbUrVs3xTj42NhYfq1oHPy//vUvrouNqWfj4LOzs6l8+fIEQDgO/ueff+bvzdA1bBw8w1wwXepx8PHx8fxa0Tj4999/n+tq3rw5jR8/no+Dv3PnDlWsWJEACMfBL1y4kL+3ehx8aWkpNW3alACQjY0NdenSRTEOPjk5mV8rQtd89NFHfD04OFgxDj4nJ4cqV67MdanHwS9evJhfq0bXlJaWUosWLbgu9Tj4o0eP8mvl6Bo2EfKTTz7h62p0TW5uLjk7OxMAIbpm+fLl/Fo2pp6Ng2eYCwBkNBo14+BPnDhBOp2OAAjHwX/++ef8vdXomry8PHJxceG61OialStX8mtF4+DbtWvHdanHwZ86dUqhS42u+eqrr/h7q8fB5+fnk5ubGwEQjoNfs2YNv1Y0Dr5Tp05cl3oc/NmzZ0mv1xMAPqZ+/fr1XNfw4cP5e6vRNQUFBeTu7k4AyNHRUYOuWb9+Pb9WhK7p0qULASCDwaBB15w/f54MBgMBEKJrRo0axd9bja558OABeXp6cl1qdM2mTZv4tXJ0DZu82KNHD66LoWvOnDlDRNKkTaPRSADI2dmZ3n77bVq7di2fCPn999/z91ajawoLC6l69eoEgBwcHOjFF1+khQsX8omQ27Zt49eK0DVhYWFclxpdk5aWRjY2NgRAiK4ZO3Ysf2+Grjl06BCVlJTQw4cPqWbNmlwXQ9ewiZA7duzg14rQNS+//DIBIL1ez9E1p06dotLSUrp69SrZ2toSACG6ZsKECfy91eiaoqIiqlOnDgEge3t7Dbpm165d/FoRuua1117jutTomoyMDLK3t+e61OiaKVOm8PdWo2sYkovp6tmzpwJdExkZya8VoWveeOMNrqt169Y0adIkjq7JzMwkBwcHAiBE10yfPp2/N0PXHDx4kIqLizmSCwDZ2dlR9+7dFeiaAwcOKHSp0TX9+vXjzzg1uubGjRvk6Oio8ARydM3MmTP5e6vRNQxzIfcEcnTNwYMHNV5F7gn69++v8CpydM2tW7cUXoWha5gnmDt3rsarMHQNQ3IxXWp0zaFDhyx6lYEDB2o8gdyrVKhQQeNVmCeYP3++Ra8SFBRk1qskJCRovIrcEwwaNEihS46uuXPnDlWqVMmsV/n1118VXuXLL79UeJVmzZpxT6BG14i8ihxd8/HHHys8gdyr3L1716JXWbp0qcYTyL1Ky5YtzXqVY8eOabyKHF0zZMgQhSeQe5V79+5pvIrcE/z222/8WjW6prS0lEJCQsx6lZMnT2o8gdyrDB06lL+3OXTN81aw4lv+WfXNN98IWVBE0kj03r17C/mQRNIfIxELikgaA//OO+8I+ZBEEudR/YGS18iRI81+oDIzM6l3795C5hIR0ZIlS4QsKKZrwIABQhYUEVFMTIyQBcXqu+++ox9++EHDhySSRmn37t2bFi9eLNS1fPlyIQuKSBpP/+6779L06dOFY9cPHz5M/fv3V5h/ef3www9CPiSRhIvo3bs3LVq0SDimfsWKFUJuJZE0Bv5f//qXkA9JJD3s3nnnHQ23ktXYsWPpu+++0/AhiSQsQ+/evYXcSiKiVatW0aeffqrhQzJd7733Hk2dOpWbf3klJSVpzL+8xo8fL+RDEkmYgd69eyvMv7zWrFkj5FYSSePWBw0aJORDEklfzEXcSlYTJ07kJlutKycnh/r06aMw//Jat24dDR48WMOHZLo++OADmjJlCjf/8jpx4gS99dZbQj4kkWS4R4wYQbGxsZox9bm5udSnTx8ht5KIaMOGDfTxxx9r+JBM10cffUSTJ0/WcCuJpC/mzPyL0DVTp04V8iGJpLH5b7zxBs2fP1+Irtm8ebOQD8l0DR48WGH+5XXmzBl68803hXxIIumLwPDhw7n5l1deXh7ppv7+AAAgAElEQVS9+eabQm4lkfRFU8SHZLqGDBki5FYSSV/M1RuC8po5cybfEFTrKigooL59+9K8efOE6Jrw8HAhH5LV559/rtgQlNfFixepT58+Qj4kkcTmFbGsiSSUTt++fYXcSiKinTt3CvmQrL744gsht5JIQk306dNHyIckIpo3b56QW0kkoXTeeustmj17thCps3v3biHLmtXXX38tZFkTSRie3r17C1nWRNIXFLn5l1dhYSH169dPyIckkr4Ai1jWrIYNG0Zjx44VeoL09HTq3bu3kGVNJG2miriVRBJK5+2336aZM2cKdR04cEDIrWQ1YsQIs54gIyPDoldZvHixkGVNVLZXiY6OtuhVRo0aRaNHj9awrIkk7Iclr7J06VL6/PPPhZ6gqKiI+vfvL2RZE0mb9WV5FRHLmkhCbpXlVcx5gsfxKiJPMHr0aLNe5datWxa9yu+//05DhgzRsKyJJE8wcOBAs14lMTFRyLJmNXbsWCHLmkhCIvXp00fIsiYiWr16tVlPUJZXSU5OtuhVJkyYYNGr9OnTx6xXeV7rUb+IWjOi1rKWtaxlLWtZy1rWspa1rGWtf0s9akbUim95Rmr69OnYtWuXAnvAKi8vDwMHDkROTo4CL8Bqy5YtWLBggQJ7wIqI8Pnnn+P06dMKvACrM2fO4KuvvtLgGFjNnDkTO3bsUOAFWOXn52PgwIG4c+eOUNeff/6JefPmmdX1xRdfICUlRajr/Pnz+OKLLzQ4BlazZ89GeHi4UFdBQQEGDhyI7OxsBV6A1fbt2zFnzhwN9oDVl19+iRMnTsDZ2VmTp7p48SKGDh2qwTGwmjt3LrZu3arAHrC6f/8+3nvvPdy6dUuBY2AVERGBWbNmabAHrL7++mscO3YMzs7OHMfA6vLly/jss880eAFW8+fPx5YtW4SZqMLCQrz33nu4ceOG8H7t3r0bM2bMMKtr+PDhOHLkiAJ7wOrKlSv49NNP+Rh/ta5ffvkFGzduFGaiHj58iPfeew9ZWVkKHAOryMhITJ06VYM9YDVy5EgkJiYKdaWnp2Pw4MFmdS1atAjr1q0T6ioqKsL777+PzMxMBY6B1YEDB/Djjz9yvIBa17fffov4+HgF9oBVRkYGPvroI472UefilixZgj/++EOBPWBVXFyM999/HxkZGRpEEyChciZNmqTBHrD6/vvvcfjwYaGu69evc12enp4aXcuWLcPq1avN6ho0aBDS09MVOAZWsbGxGD9+vFldo0ePRmxsrAJ7wOrGjRv44IMPOKpGnT9bsWIFVq5cqcAesCopKcEHH3yAK1euKPACrA4fPsynQYt0jRs3DgcPHhTqunXrFgYNGoT8/HwFoonVypUr/4+98w6Pqtre/5tMEgghhLRJnTTSe6NISaOTBBRREbsighQREEEsoYv0XkUQAem999577xBCDQTS+6zfH3P39pw5eyao1+/Pq7OeJ48+bPfczz0k2e85Z73rxYIFC4RcWq0WXbt2xZ07d6BWqxVcx44d41OXRVzDhw/H3r17ZbEHrHJycvDxxx+joKBAeL1+/fVXzJs3TxbHIOXq1q0bbt68KYs9YHXy5El88803ijgGViNHjsTu3buFXM+ePcPHH3+M/Px8YezB0qVLMXfuXFkcAysiQvfu3XH9+nUh15kzZzBo0CCDXKNGjcLOnTuFZ29ubi46d+6MvLw8IdeKFSswZ84cWUSTlKtHjx64du2aLAqJ1blz5/hUXBHXmDFjuCbQP+Py8/PRuXNn5ObmCrlWr16NmTNnGuTq1asXrly5IuS6ePEi+vfvD61WKzx7x40bh82bN/8hrbJ27VpMnz6dn72/R6tcuXIF/fr1M3j2TpgwARs3bjSoVTp37oycnBwh14YNG/4yrTJ58mSsX79eyMU0gSGtsmnTJkyaNMmgVunXrx/Onj0r1Co3b940qgmmTp1qUKuUlJSgc+fOyM7OFmqVrVu3GtUE/fv3x+nTp4Va5fbt2+jVqxfKyspkEU2sZsyYgVWrVgm5pFpFdPZu374dY8eONcg1YMAAnDx50qBW6dGjh0FNMGvWLKxYseIPaZV/a71ofIupNfdvUpcuXeLeL3d3d0WLU//+/Q36G4qKisjV1ZX7G5iPgLVeLV26VOYj0G9xat68uUF/g9T75ebmxlucGNfAgQP5Z9erV0/mbyguLubeL8YlbXFauXIl38s8j9IWp1atWsn8DRMnTuT+hhs3bnDvl6urq6LF6ZtvvlH4G1iLU0lJCWk0Gu5v0Pc8rl271qC/gYgoLS2NczEfAWtxun37NudycXHhLU6MKyMjQ+FvYC1OpaWl3Psl8jxu2LDBoL+BiKhdu3Yyf4O0xSkzM5N7v0T+hmHDhsn8DczzqNVqqaysjPz8/AiQex4Z15YtW/hekRfz1Vdf5VzM88hanLKysqhatWoE/OZ5lLY4ff/99/yzmReTtTiVl5dTQEAA52KeR9bitH37dr6XeTGlLU5vvPEG9/AxzyNrcXrw4AH3pDHPo7Qde/To0fyzY2JiZC1OFRUVFBwcTMBvnkdpi9OuXbv4Xl9fX+55ZFydOnXiXMzzyFqcHj16xD1pTk5Oinbs8ePH88/W9zxWVlZSaGgo52rbtq2sHXvv3r18L/NiSlucmE9d6nlkLU7Z2dlkY2NDwG9eTGnb86RJk/hnM88ja3GS+tSZ53HWrFmcS+pT9/b2VngeP/jgA+7hY55H1o4t9amLvJhSn7rU81hZWUlarZaio6O5tzAtLU3Wji31qXt5eXHPI+NiPnWp55G1Y0t96syLKW3HlvrUmeeRtWNLfeoiz+OJEyf4Xo1Go/A8Mp868zxK27GlPnWR51HqU2eeR9aOrdVqqX79+gToPI9t2rSRcUl96lLPI+NiPnXmeRw5ciRve87LyyMHBwfOxTyPjEvqU2eeR9aOLfWpMy/m1KlTeTv2uXPn+F7RfAbmU5fOZ2BcBQUF5OTkRIDc88jasX/55Rf+2frzGYh+86lL5zMwL6bUpy71PDKuvn37ci79+QxSn7poPoPUp67veSQiSklJUWgC1o4t9amL5jMwn7rI8yj1qYu0yrJly4xqFeZTl3oeRVpFNJ/hq6++kmkVqedR6lOXeh6ZVpH61KXzGRhX69atFZ5HplWkPnWRVpH61PU9j6WlpVyriOYzSH3q+vMZiH7zqUs9j1KtwnzqUq3CNIHUp64/n0HqUxdplY0bN8q0ir4mYD516XwGplWkPnXpfAbGJfWpS+czaLVamU9dpFWkPnXRfAbmUxdplXv37im0ilQTSH3q+vMZ/q0Fk0f0f6eSkpIoISGBC0zpl6WlJTk4OJCnp6dijf0ScHd354Z26ZeZmRnVqlWL/8LQ/7K2tia1Ws0PLP0vGxsb0mg0XJD/Xi43Nzcuan4vl7Ozc5Vcxq4X++X9e7jY4VgVF7vp/71c9vb2BrlsbGzIzc2Niy39L1tbW4Nc1atXr5LL09OTD6+QfllYWPxpLm9vby6YRFxMeIj+Ljw9PfkNjIiLDYsRcbm6uvLBBIa4mGDS53JycvpDXCqVimrXrv2nuZhgEnG5u7sb5PLw8DDK5e3tbZSLiWbRZxviqlat2gtxsSEkf+R6/ZVc7Eb0914vFxeXKrmYwNTncnR05ML293LZ2dkZ5KpRowa5uLjwIV2iz/by8uIC8/dyubu786Et0i9zc/M/xWVjY0NeXl5cYEq/rKysXoiL3biLuAz9bqxRowap1WpSq9VGuZjAFHFVdfb+Ea4XOXuNcf2dNYGxs9fd3f0PawK1Wv2Hz96/q1YxdvZWpVWMaYKqtAo74/5KrWJME1TF9U/SKtIBVSLv/D+5YPKI/u+UKUfUVKYylalMZSpTmcpUpvrnlaOjIzp06ICMjAyDMVj/tHpRj6gyRMhU/+c1e/ZsVFZWok+fPigoKOB/7ujoiMaNG8PNzQ0VFRWYM2eObF90dDQCAwMREBCANWvW4Pz583zN2toaiYmJUKvV0Gg0GD58uGyvj48P4uPjodFocOXKFWzcuJGvqVQqNGrUCK6uroiIiMDo0aORl5cn5KqsrMTs2bNlnx0VFcW51q9fj7Nnz8q4EhIS4OLiAm9vbwwdOlS219vbG3Xr1oWnpyeuX7+O9evX8zVzc3M0atQIbm5uCA8Px7hx4/D8+XO+7uDggCZNmvAf8pkzZ8o+OyIiAiEhIahTpw42bdqE06dP87Xq1avz6+Xr68u9Yay8vLxQt25daDQa3LhxA+vWrZNxNWzYEO7u7ggPD8eECROQk5PD1+3t7TmXSqXC9OnTZZ8dHh6OkJAQ+Pv7Y8uWLTh58qSMi12vOnXqQN/TrdFoUK9ePXh6euL27dtYs2aNjOull16Ch4cHwsLCMHnyZDx58kTIZWlpialTp8o+OywsDGFhYfDz88P27dshfYhUrVo1fr38/f0xePBgSB9qeXp6cq6srCysXLmSr5mZmeGll16Cp6cnQkNDMW3aNDx+/Jiv165dm3NVr14dkydPlnGFhoYiLCwMderUwc6dO3H06FEZV0JCAtRqNQICAjBkyBDZQx4PDw/Ur18fnp6euH//PpYvXy7jatCgATQaDcLCwjBjxgw8ePCAr9vZ2XGuGjVqYNKkSTKukJAQhIeHw8/PD3v27MHhw4f5mpWVFb9egYGBGDJkCCorK/m6u7s7GjRoAA8PDzx8+BDLli2TcdWvXx9eXl4ICQnB7Nmzcf/+fb5eq1Yt/j1ia2uLCRMmyLiCg4MREREBX19f7N+/HwcPHpRxsesVFBSk4HJzc8NLL70Ed3d3ZGdnY8mSJTKuevXqwcfHB8HBwZg7dy7u3r3L121tbZGQkMC9POPHj5dxBQUFITIyEr6+vjh48CD279/P1ywtLZGYmAhnZ2eEhoZiyJAhKC8v5+uurq78e/vp06dYvHix7LOlXPPnz8edO3cUXC4uLnBwcMCYMWNkewMDAxEVFQUfHx8cOXIEe/fulXE1adIEarUaYWFhGDp0KMrKyvi6i4sL/12Qm5uLX375RfbZdevWha+vL4KDg7FgwQLcunWLr9WsWZNzOTk5YfTo0bK9AQEBiI6Ohre3N06cOIFdu3bxNQsLCzRp0gQuLi4ICwvDsGHDUFpaytfVajUaNWoEd3d35OXlYcGCBbLPjo+Ph5+fH4KCgrB48WJcv35dyKVWqzFq1CjZXn9/f8TExMDLywunTp3Czp07FVxqtRrh4eEYMWIEiouLFVxubm4oLCzE/PnzZZ8dGxsLf39/BAYGYsmSJbh27Rpfs7Gx4T9Trq6u+P7772V769Spg9jYWHh5eeHMmTPYvn27jKtx48ZQq9WIiIjAyJEjUVRUxNednZ05V0lJCX766SeDXMuXL8fly5f5Wo0aNZCYmAgXFxe4u7tjxIgRsr2+vr6Ii4uDl5cXzp8/j61bt/I1lUrFr1dERARGjRol0wROTk787C0tLcXcuXNlny3VBKtWrcLFixcVXGq1Gp6enkJNwLguXbqEzZs3y7gaN24MFxcXRERE4IcffkB+fj5fd3R05L8bDWmCoKCgKrWKl5cXhg0bJtvr7e2N+Ph4eHl54erVq9iwYQNfMzc3R+PGjblWGTNmDHJzc/m6g4MDv15EhFmz5Ha1yMhIBAcHw9/fHxs2bMCZM2eEXCKtUpUmkGqV8ePH49mzZzIu9vNqbm6OGTNmyD77RbWKn58fBg8eLNvLNIFGo8HNmzexdu1aGZdUq0ycOBFPnz7l61JNYGFhgWnTpsk+W6pVtm7dihMnTvA1dvYyrTJkyBCFJmBn7507d7B69WoZF/t9HhoaiqlTpyI7O5uvSzWBlZXVH9Iqzs7OCAgIUGgVqSYwplXCwsIwbdo0PHr0iK/b2dnxM86QVklPT0d6ejoaNGggzJM1FWBqzf2bFMvwCwsLE8YNtGzZUpg1RkR0/fp1UqlU5OHhQV27dlXEDQwaNEjobyHSjb739PQUZo0R6aIVALm/RcrVpk0bYdYYkW4kv4WFBbm7u/OsMSnXd999J/O3sKwxIuIZfqKsMSKi9evXcy5R3EDbtm2FWWNExDP8RP4WIqKhQ4cKvbhEutH3vr6+3HejHzfAMvxE/hYinTeC5Y9KvbhEOr+klZWV0N9CpIsUAZReXCLi3giWNaYfN7Bt2zYCxF5cIqLXXntNmDVGRDzDT5o/KuX64YcfCFBmjRHpRswHBgYK/S1Ev2X4iby4RERvvvmmMGuMSDeS39raWuhvIfotw0/fd8O4QkNDhVljRL9l+Im8uES6DD+RF5dIN5LfxsZG6MUlIpo4cSIBv2WNSeMGWIafKH+U6LcMP5EXl4jo/fffF/pbiIhn+Im8uES/Zfjpe3GJiPslRV5cIl1UACD23RDpMvxUKhUlJycr4gZycnKoVq1aQi8uEdGMGTMIUHpxGVdsbKzQi0ukiwoAxLmoRESffPKJ0ItLRDzDz9HRURiNNGfOHAJ+y0WVxg1otVqqV68ezx/Vj0ZiGX4iLy4RUffu3YVeXCKi3NxccnBwEOaiEv2W4RcVFaWIG9BqtdSwYUOZF1caN3D27FkCxPmjRLoMP5EXl4h4hp/Ii0uki6cCdB5h/WgkrVZLTZo0EXpxiX7L8GNc+tFIffr0EXpxiXQxPWq1WujFJdLFUwFKLy6r5ORk7sXVj0Zisx1EXlwiXTSMyItLRHy2gzQXVRqNxGY76HtxWTVr1kzmxZVqAuaXFOWPEulmO0i9uNJopOLiYt7aK4pGYrMd9L24rFq1aiXz4ko1wY0bN7hWEUUjff3110a1ikajEXpxiYjWrFljVKukpqbKtIpUE7DZDqL8USLdbAeRF5dIp1W8vb2FXlyi32Y7MC+uvlZp164d1yr6miAzM9OoVhk2bJhRreLn5yfMHyXSxS0Z0yqvvvqqLCtdX6tUq1bNoFYZOXKkTKtINQGb7SDy4hL9NttBPyud1euvv25QE1SlVdhsB/2sdCKdJggKCjKoVdhsB0NapVOnTpzLUDTSv61g8oj+b9XWrVsNfuPm5+cbzBoj0g3NEGWNEekO+JUrVwozvYh0RnpR/iirbdu2CTO9iHQHvKFMLyJdtqWhQN+quG7duiXMGmO1fft2YaYXEVFhYSGtXLlSmOlFpBvmcfz4cYMm8lWrVgkzvYh0N7GirDFWO3bsEGZ6EemEh6GsMSKdODVmbl+9erUw04tId2CJssZY7dy5U5jpRaQ74FesWCHM9CIiOnXqlDBrjNWaNWuE+aNEugNr69atikwvVrt27RJmehHpDnhjXKdPnxZmerFau3atwUyve/fuCbPGWO3evVuYP0qkO+CXL18uzBoj0ol5Y1zr1q0T5nwS6YYkbd68WZHzyWrPnj3C/FEi3QG/fPlyYf4okW4oiyh/9EW4Hj58KMxFZbV3715h/uiLcJ0/f16YP8pq/fr1fOCNfj1+/FiYi8pq3759wvxRIp3wWL58uTAXlUg3LEaUP8pqw4YNwvxRIt3wJlH+KKsDBw4I80eJdA8jVqxYIcwfJdLd/IjyR1lt3LhRJv6l9fTpU8UDQWkdPHhQ9kBQn2v58uXC/FEiXaarKH+U1aZNm4T5o0S6hxGG8keJiA4dOiTMHyXSnSUrVqwwyHX16lVh/iirzZs3C/NHiXSZwca8XYcPH5Y9ENTnWr58uTB/lEh3syjKH2W1ZcsW2QNBaeXl5RnVBEeOHBHmojKuFStWCPNHiXQ3i6L8UVZVaRVD+aNEOk3w/0urGOM6fvy4Ua1iTBPcvn37D2uVoqKiKrWKMU3wV2mV4uJio1wnT540qgmMaZW7d+/+pVpFlD/KqiqtYkwTvIhWMaQJ/q31X7sRBaABsAvAJQAXAHz2nz93ALANwLX//NO+qs8y3Ygartu3bxv84SkuLjb4w0OkE9WGfniIdL/ARb9giXTCxNgPjzGukpISo+G9f5bLkHBlXIaEWGlpqUFBzbgMCdequHJycoxy3blzxyBXWVmZQUFNpHua90e5nj17ZlBQV8VVXl5uUFAzLkPC9UW4DAnqP8v14MGDP8z1/Plzg8KVcRkSiBUVFQYFNeMyNpTg1q1bBrlyc3ONcmVmZhrkqqysNMr18OFDo1zGrldeXp5BQf0iXIaEPpFuErAhQU1k/Hrl5eUZFNSMy5BA1Gq1fxlXfn6+Ua67d+/+Ya7Hjx8bFNRVcRUUFBgU+i/CZejGiHEZEq6My9BZUlhYaFBQMy5DwrUqruzs7D/MVVRUZFBQE+nE65/hMiSoif6cJsjKyjJ69hr7/nry5Mkf1gR/Z61SlSao6nr9UU3wZ7TKn9EEOTk5f1gT/K9qlT+rCarSKsY0gaGHf//metEb0SpzRAcPHmwD4CARfT148OAFAOYMHjx4B4AeAC4S0RuDBw/2ANA8IyNju7HPMuWIGq5ly5YhLS0Nly5dApE870ylUqFp06aYNWsWHj58qMjvun79OkJDQ3H8+HEUFxfD3d1dlis2aNAgfP7557h9+7YiV6ysrAyBgYHYsmULcnJyFLliq1atQuvWrXHp0iVF3plKpUKrVq0wffp03L9/X5F3dvPmTYSEhODYsWM850/K9d1336FXr164deuWgquiogLBwcHYuHGjkGvt2rVo2bIlLl68qMg7Mzc3R1paGqZMmYIHDx6gZs2asut1584dBAcH4+jRoygqKlLkig0ZMgTdu3fHrVu3FHlnWq0WISEhWL9+PXJychS5Yhs2bECzZs1w8eJFRTarSqVC27ZtMWnSJNy7d0+RK3bv3j0EBgbiyJEjKCwsVHCNGDECXbt2xY0bN2BhYQGNRiPjCg0Nxdq1a/H06VMF1+bNm5GSkoILFy4o8s7Mzc3x6quvYty4cUKuBw8eIDAwEIcPH0ZhYaEi72zUqFHo0qULbt68CZVKpcg7Cw8Px+rVq/H06VNF3tn27duRmJiI8+fPK/LOzM3N8frrr2PMmDG4d++eIlfs0aNHCAgIwKFDh1BQUKDIOxs7diw++ugjXL9+XZErZmZmhoiICKxcuRJPnjxR5J3t3r0bTZo0wfnz51FRUaHgeuuttzBq1ChkZWUpuLKzsxEQEICDBw+ioKBAkXc2YcIEvP/++wa5oqOjsXz5cjx58kSRd7Zv3z40bNgQ586dU+SdmZmZ4b333sOIESOQlZWlyDvLyclBnTp1cODAAeTl5Sm4pkyZgnfeeQfXrl1TZLOam5sjNjYWS5cuRXZ2toLr0KFDqF+/Ps6ePcu5WNaomZkZPvzwQwwdOhR3795VcD179gz+/v7Yt28f8vPzFVzTp09Hp06dhFwqlQrx8fH49ddfkZ2djdq1a8syUI8ePYp69erhzJkzQq4uXbogIyMDd+/eVWSg5uXloU6dOti7dy9yc3MV2ayzZs1Cx44dcfXqVUUGqkqlQr169bBw4UI8fvxYkc164sQJxMXF4fTp0ygtLVVwdevWDd9++y0yMzNhbW0tu14FBQXw9/fH7t27hVxz587Fa6+9ZpDrpZdewoIFC/D48WPY2dnJMlBPnz6NmJgYziXNGjUzM0OvXr0waNAgZGZm8kxPxlVUVAR/f3/s3LkTubm5imzW+fPn49VXX8WVK1cAQMHVuHFjzJ8/Hw8fPlRkjZ47dw7R0dE4deoUz9iVcn3++ecYMGAA7ty5o8hmLS4uhr+/P3bs2IHnz58ruBYuXIiXX36Zc3l6esrOuMTERMydO1fIdenSJURERODkyZM8Y1fK9cUXX+CLL77AnTt3+BnHuEpKShAQEIBt27bh+fPnigzUJUuWoG3btrh8+bJQE6SkpGD27Nl4+PAhatWqJTvjrl69ivDwcJw4cQLFxcWKs3fAgAHo06dPlZrg2bNnCq7ly5cjNTWVaxX969W8eXPMnDkTDx48UHBVpVW+/vpr9O7dW6gJysvLERQUhE2bNuHZs2cKTbB69Wq0atUKly5d4mevlKt169aYNm0aHjx4oNAqt27dqlKr9OzZE7du3YKlpaXs7K2srERwcDA2bNgg1Crr1q1DixYthJrA3Nwc6enpmDx5MtdQ0uuVmZkp0ypubm4yTTB06FB0794dN2/eVGSgMk2wbt06oVbZuHEjmjZtKtQEKpUK7dq1w8SJE3H//v3frVVGjhxpUKsQkVGtsnXrViQnJ+PChQuKzFhzc3N06NDBqFYJCAjA4cOHhZpg9OjR+PjjjzmXMa3i4OAg0wQ7duxAQkKCQU3wxhtvYPTo0UKt8m+tF80R/d1Tc83MzNYAmPKfryQiemBmZuYGYDcRBRnba5qaK64rV66grKwMycnJ3DherVo1pKSkICUlBfHx8Thz5gx69+7N93h4eCAtLQ3169dHbGwsPv30Uz6EhA1dadmyJWJiYmBtbY2WLVtyg7adnR1atWqFhIQExMXFYe7cuTITf0hICNLT0xEVFYXQ0FC0aNGCG8etrKyQkpKCpk2bIi4uDhcuXEDPnj35Xnd3d84VFxeHnj17Yt++fZyrfv36aN26NaKjo2FjY4PmzZtzrlq1asm4FixYIDPLBwcHc67w8HC0bNmSG8etrKyQlJSEZs2aIS4uDlevXkW3bt34Xjc3N6SlpaFBgwaIjY3F559/jt27d3OuevXqoVWrVoiJiUGtWrXQrFkzPuSmVq1aaNmyJRITExEXF4dFixbJTOlBQUFIT09HTEwMwsPD0apVKz7kxtLSUsZ148YNfPLJJ3yvq6urjKt///6yoRpSLgcHB6SkpPBhMra2tpwrPj4eS5YskQ2qCQwMRHp6OqKjoxEZGYk2bdrg3r17nCsxMRHNmzdHXFwc7ty5g48++kjGlZqaigYNGiAuLg4DBgyQDdWIj49HmzZtEB0dDScnJ6SkpKCiogKAbriJlGvFihUYO3Ys3xsQEMCvV2RkJNLT05GZmQlAN0REypWVlYUPPviA73VxcUFqaipeeuklxMbG4ptvvpEN2oqPj+ffX66urkhKSuJDbpPXl2MAACAASURBVGrWrIkWLVogKSkJcXFxWLNmDX744Qe+19/fH2lpaYiNjUV0dDTatWvHh8lYWFggISEBLVq0QGxsLB49eoR33nmH71Wr1ZwrLi4O3333nWzQVmxsLFJTUxEVFQUPDw8kJibyITc2NjacKz4+HuvXr8fIkSP5Xj8/P6SnpyMuLg5RUVFo3749bty4wbmaNGnCuZ4+fYpOnTrxvc7OzpwrPj4eQ4YMkQ20iomJ4Vyenp5ITk5GSUkJ52revDmSk5MRGxuLLVu2yAaJ+Pn5IS0tDXFxcYiOjuY3P8BvQ1datGiBmJgY5ObmomPHjnyvk5MT2rRpg4YNGyI+Ph4jRoyQDYmIjo5GamoqoqOj4eXlhaSkJD7kpkaNGpwrLi4O27dvlw3s8PX1RVpaGuLj4xEdHY2OHTvi0qVLnKtx48b8ehUWFqJDhw4GuUaNGiUbHBUVFcW5fHx8kJSUxIfcWFtby7h2796Nb7/9lu/18fHhXDExMXjrrbf40BY2II79zi4uLsarr77K9zo4OKBNmzZo1KgR4uPjMW7cONmApsjISKSlpSEqKgp16tRBUlISH3JjbW2Npk2bIiUlBXFxcdi/fz8GDRrE93p7eyMtLQ1169ZFbGws3nnnHT60hQ1dadWqFaKjo1FeXo6XX35ZxtW6dWs0btwY8fHxmDBhAhYuXMjXIyIiOJe/vz9SUlL44Lvq1aujWbNmSE5ORnx8PA4dOoQBAwbwvV5eXkhLS0O9evUQExODDz74gA9yY0NX2PUiIqSnp/O99vb2aN26NZo0aYK4uDhMnTpVNggpPDyccwUGBqJp06Z88F316tVlZ9yxY8fwxRdf8L0ajYZzxcbGonPnzjh27Bjneumll/j1UqlUaNOmDd9bu3ZtGdeMGTNkg5DCwsKQnp6OyMhIhISEoGnTpnzwHdMEjOvUqVPo06cP3+vp6cnP3piYGHTt2pUPTGNDV9j1srKyQqtWrWRc0rN3zpw5soFDoaGh/HqFhYWhadOmMq2SnJyMZs2aITY2FufPn0evXr34Xn2t0r17dxw4cIBzSTVBVVrlp59+kg0hlGqVsLAwtGjRgg++s7KyknFdunQJPXr04HulWiU2NhafffYZH0zGNEHr1q0RExODmjVronnz5jJNIOX65ZdfZAN0goODkZaWhujoaK4JHj58yLmkmuDatWvo2rUr36uvVfr06SMbTCblsrOzQ9OmTQ1qlcWLF8uG6gUFBSEtLQ0xMTGIiIhA69at+eA7fa1y8+ZNSF8cMa3CtJ2+Vqlbty7nMqRVEhISEB8fj2XLlsmG1+lrgrS0ND74riqtItUEcXFxGDhwILZs2cLXpVrF2dkZycnJBrXKypUrZcPr/P39kZ6ejtjYWERGRqJt27Z88J1Uq8TGxuL+/ft4//33+V6mCdLT09G8eXPZjfq/pV50au7vuhE1MzPzAbAXQDiATCKqLVl7RkT2BrYCMN2IGipTfIupTGUqU5nKVKYylalM9c8q9rAmPT0d7du3N8W36JX57/jAmgBWAOhNRHlV/feSfV3MzMyOm5mZHZeOYzbVb2Vubs7bdUxlKlOZylSmMpWpTGUqU/3vl7e3N4+YkbYhm0pXL3T3Y2ZmZgndTehCImL9U4/+05KL//zzsWgvEc0iongiind2dv5vMP/jqry8HM+ePZP5CoKCgtCvXz/s3r0b5eXlsvYdS0tLNG/eHJMmTcLNmzeh1WrRsGFDvu7q6orOnTtj9erVKCgokOV4AroWiiFDhuDUqVPQarWyNhpbW1t06NAB8+fPR3Z2NvLz82WevsDAQPTt2xe7du1CWVmZLI/O0tISzZo1w8SJE3Hjxg1otVo0adKEr7u4uOCjjz7iXBcuXJD10NetWxeDBw/GyZMnodVqZW1HNWvWxKuvvop58+bh0aNHKCgogFqt5uv+/v74/PPPsXPnTpSVlcna1iwsLNC0aVNMmDAB169fBxEhOTmZr6vVanz44YdYuXIl8vPzcenSJdmDgbi4OGRkZODEiRPQarXo37+/jKt9+/b46aef8OjRIxQVFcmedtWpUwe9e/fGjh07UFZWhqVLl8q4UlJSMH78eFy7dg1EhObNm8u4PvjgA6xYsQJ5eXm4du2aLIcqNjYW3333HY4fP47KykoMHDiQr9nY2OCVV17h3ibmx2Hl5+eHzz77DNu3b0dpaamsLVKlUiE5ORnjxo3D1atXQUSyNi4nJye89957WL58OfLy8nDjxg0ZV0xMDL799lscO3YMlZWV+Oabb/hajRo18PLLL+PHH3/EgwcPUFJSAo1Gw9d9fX3Rq1cvbNu2DaWlpbI2UpVKhaSkJIwdOxZXrlwBESEtLU3BtWzZMuTm5uL27dsy/0d0dDS++eYbHD16FJWVlbJM1ho1aqBdu3Y8o7O0tBQ+Pj583cfHBz179sTWrVtRWloqy7JjPrIxY8ZwP1e7du34uqOjI9555x0sXboUubm5yMzM5N4lQNfu+fXXX+PIkSOorKyUtb9aW1sjPT0ds2bNwr1791BWVgY/Pz++7u3tjR49emDLli0oKSmRtSSZm5sjISEBo0eP5h5v/XbPt99+G0uWLMHz58+RlZXFvTiArt1z0KBBOHz4MCorK2Xtwoxr5syZuHfvHsrLyxEQEMDXvby80L17d2zevBnFxcWyFi5zc3M0adIEo0aN4h7v119/na/b29vjrbfewq+//opnz57hwYMH3IsD6No9v/rqKxw6dAgVFRWyvM3q1asjNTUVM2bMQFZWFioqKhAU9JtjRKPR4NNPP8WmTZtQXFwsa3ljmYSjRo3ChQsXoNVqZW3O9vb26NSpExYvXoxnz57h0aNH3NcJ6No9Bw4ciAMHDqCiokLWelatWjW0adMG06dPx927d1FZWYnQ0FC+7unpiW7dumHjxo0oLi6WZZey9tiRI0fi/Pnz0Gq1ePfdd/l67dq18eabb2LRokXIyclBdna2zN8WFhaGL7/8Evv370dFRYWsVa9atWrcO5eZmYnKykpERkbydQ8PD3Tt2hUbNmxAUVGRLIOWtXuOGDEC586dg1arlbXR29nZoWPHjli4cCGePn2KJ0+eyPxaoaGh+PLLL7Fv3z5UVFTIbBisdXTq1Km4c+cOtFotoqOj+bq7uzs++eQTrFu3DkVFRThy5IiMq0GDBhg+fDjOnj0LrVaLjz/+WMb1xhtv4JdffsHTp0/x7Nkzmcc2JCQEX3zxBfbu3Yvy8nJZK6iVlRVatmyJKVOm4Pbt29BqtYiP/+2Bv7u7O7p06YJ169ahsLBQlrPI2lCHDRuGM2fOQKvVyloya9Wqhddffx0LFizAkydP8Pz5c5k3Mzg4GP369cOePXtQXl6OH3/8ka9ZWlqiRYsWmDx5Mm7dugWtVov69evzdTc3N3z88cdYs2YNCgsLZbmUgK7dc+jQoTh9+jS0Wq2shdXW1havvfYa1wR5eXkyrcI0AdMq0hZokVZp1KgRX9fXBOfOnZNx6WuVzz77TMbFtMrjx49RUFAg0yoBAQG8rbWsrEyW6SvSKgkJCTKuDz/8EKtWrUJ+fj4uXrwo0yrx8fEyrdK3b1++xrQK0wSFhYVGtcqvv/7K10RaJSUlha8zTcC0yuXLl41qlS+//JKv2djYoH379pg7dy7XKm5ubnxdX6tILQkirdKiRQu+7uzsjPfff79KrcI0wVdffSXjYprg4cOH3GvNSl+rrFq1iq8xrTJ27FiuVVq3bs3X9bXKzZs3ZZpAX6tIrRRME8yZMwcPHjxAaWmpUa0izWtlWmXMmDG4cuUKrly5gjFjxiAxMZH74k0lqaqmGQEwA/AzgAl6fz4awID//PsAAD9U9VmmqbmGa9SoUZSUlKTI2CPSTQpr0KABz9jTn7S3detWnmUnGqn93nvvCTP2iHTT4kJCQqhXr160detWxQTAsWPHCjP2GFfDhg3p3XffpaVLlyq4duzYQVFRUfT1118LR2p/+OGHwow9It30s5CQEOrRo4dwpPaECROEGXtEuglmTZo0EWbsEekiMCIjIxUZe6w+/vhjYcYekW4yZGhoqDBjj4ho8uTJwow9It300MTERHr77bfp119/VUzaO3DgAEVERCgy9lh17dqV0tLSFFl2RLoJjGFhYfTpp58KYzamTZsmzNhjXMnJyTzLTp/r0KFDBjP2iHSZhyxjT3/S3tOnTyk8PFyYsUdENGvWLJ6xpx+zodVqqWnTpvTmm2/SokWLFJP2jh07RuHh4cKMPSJd5mGbNm0UubtEusl94eHhwow9IqIff/xRmLHHuFq0aCHM3SXSjbY3lAdMpMs8FGXsEemm5kZERAgz9oiI5s2bxzP29GM2tFottW7dWpixR0R05swZCgsLo/79+wtjNvr16yfM3SXSTaeNjIwUZuwREf3yyy/UoEEDRZYd40pNTRVm7BHpYmVCQ0OFGXtERAMGDBBm7BHppsBGRUUJM/aIiBYvXkz169dX5O6yatu2rTBjj0gXkxIaGkr9+vUTxmx89dVXwtxdIt201ZiYGGHGHpEuI1KUu8vqlVdeEWbsEeniSEJDQ4UZe0RE3377rTBjj0g31TQ2NlaYsUeky4gUZeyx6tChA8/Y05++e/36dQoJCRHm7hLpshibNm1KEyZMUMRslJSUUHx8PH344YfCSLA1a9bw3F1RzMYbb7xB7du3V+QBE+kmnjIuUczGsGHDKCUlhcaPH6+I2SgtLaW6devSBx98IIze2rBhA8/dleYBs+rUqZMwD5hIN4UzJCREmLtLRPT9998L84CJdFNN69evL8zdJdJF5cTExNC3334rjP945513eB6wvibIysrimkAUs/HDDz9wrWJIE7z33nuK3F0iXcSKMa3y/vvvU7t27YSa4P79+xQSEkI9e/YUapVx48ZxrSLSBI0aNeKaQJ9r586dRrXKRx99xLWKviZ4+PAhhYaGvpBW0dcETKuIcneJdLFYxrRKly5dKD09nWbOnPm7tcqUKVOoSZMmBjVBYmIivfXWW0KtcvDgQZlW0T/junXrJszdJdJNZTamVWbMmMG1in4kmFarpZSUFINa5fDhw1yriDRBjx49eO6uvlbJyckxqlVmz55NjRo1MqgJmjVrZlCr/FsLLzg1t0qPqJmZWWMA+wCcA8CMjF8BOAJgKQAvAJkAXiOiHGOfZfKIGq7S0lLZ2whpVVRUwMzMTPaE6UX3VrVeWloKKysrg9O9TFzyKisrg6Wl5R/iqqysBBHJnsiZuP73uLRaLSorKw0+2TRxKbkqKipkb4H/m1wWFhYGrQ3G9hIRysvL/xKu8vJyqFSqfxxXWVmZ0d/Zf1euP3qW/J25zM3N/1Vnr4nr963/E8/evzOXVqs1ve3Uq/+aR5SI9hORGRFFElH0f742EtFTImpKRAH/+afRm1BTGa9Vq1Zh7dq1fAKjtMrKyjBmzBicOXMGogcHR44cwc8//4wnT54IP3vWrFnYs2cPnxQmrXv37vE2I1GtWbOGt/PoV0VFBcaMGYPTp08LuY4ePYqff/4ZhrzBc+bM4e08+vXgwQNMnjwZN2/eFO5du3YtVq9eLeSqrKzEmDFjcOrUKSHX8ePHMW/ePINcP/74I3bt2iXkevjwIW8zEtX69euxatUqPrFSn2vcuHE4efKkkOvkyZP46aef+NQ//frpp5+wc+dOIdfjx48xceJEXL9+Xbh348aNWLlypZBLq9Vi3LhxOH78uHBo1unTp3k7j6jmzZvH23n06+nTp7ydR1SbN2/GihUrkJ+fr1gjIqNcZ8+e5e08ovr555+xfft2IVdOTg5vPRbVli1beDuPiGvChAk4evSokOv8+fO8nUdUCxYswLZt24Rcubm5vPVYVNu2bcOyZcuMch05ckTIdfHiRcyePdsg18KFC3nrsX7l5eVh7NixvPVYv3bs2MFbj0U1adIkHD58WMh1+fJlzJo1i09v1K9FixZh8+bNQq6CggKMHTuWR0no186dO7FkyRIhFxFh8uTJOHToEJ/uKK2rV6/y1mNRLV68GJs2beJThqVVWFiIMWPG4OLFi0Ku3bt389ZjUU2ePBkHDx4Ucl27do23HotqyZIl2Lhxo5CrqKgIY8aMwYULF4Rce/fu5a3Hopo2bRoOHDgg5Lp58yZvPRbVsmXLsGHDBj79WFolJSUYM2YMzp8/L+Tav38/Fi5cyCfI6tf06dOxf/9+Idft27cxffp0Pplbv5YvX47169cLuUpLSzFmzBicO3dOyHXw4EHe4iuqGTNm8NZj/crMzMS0adP4FE79WrlyJW891q/y8nKMHTsWZ8+eFXIdOnQICxYsEHIREWbOnIm9e/cKubKysoxqgtWrVxvUKuXl5X9Kq8yePdugVrl//z6mTJnCJ5nr19q1a6vUKoY0wbFjx3jrsah+/PFHg1qlKk2wbt26KrWKIU1w4sQJzJs3z6AmmDt3rkGt8ujRI956LKoNGzZUqVVOnDjxh7XKjh07hFzZ2dm89VhUTKuINEFVWuXMmTNGtcr8+fP/Mq0yfvx4HDt2zDR49I/Ui7w2/W99mVpzDdfhw4cJAFWvXl3Y5vjRRx8RANJoNIrWgZycHKpVqxaZm5sL2xxnzJhBAMje3p46deokax3QarUUFxdHACgsLEzR5nj8+HECQNWqVRO2OX7yyScEgDw9PXmbI+N69uwZ1a5dm8zMzIRtjnPmzCEAVLt2bd7mKOWqV68eAaDQ0FBFm+PJkyc5V+vWrRVcn376KQEgDw8PRZtjbm4uOTg4kJmZmbDN8aeffiIAZGdnp2hz1Gq19NJLLxEACgkJof79+9O+ffs419mzZwkAWVlZUatWrWjKlCmy9stevXoRAHJ3d+dtjowrPz+fnJycyMzMjBo0aEDDhw+XtTkuWLCAAFCtWrUUbY5arZaaNGlCACg4OFjR5njhwgUyMzMjKysr3uYobb/s06cPASA3NzdFm2NBQQGp1WoyMzOj+vXr07Bhw2RtjosWLeJcrM1R2n6ZnJxMACgoKEjR5njp0iUyNzcnS0tL3uYobb/84osvOBdrc2RcRUVF5OrqSgCoXr16ijbHpUuXEgCytbUVtjk2a9aMAFBgYCBvc2RcV69eJZVKxbkmTpwoa78cOHAgASBXV1dFm2NxcTG5u7sTAGGb44oVKzgXa3N8/Pgx/+xWrVoRAAoICKA+ffrI2hxv3LjBuVibo7T98uuvvyYA5OLiQh9++CGtWrWKtzmWlJSQRqMhAMI2xzVr1hAAqlmzprDNMTU1lQCQv7+/os3x9u3bZGFhQRYWFrzNUdp+mZGRQQBIrVbzNkfGVVpaSt7e3pxLv81xw4YNBIBsbGyEbY7t2rUjAFSnTh1Fm2NmZiZZWlqShYWFsM1x2LBhBICcnZ3p/fffl7U5lpWVkZ+fHwEQtjlu3ryZc4naHNu3b08AyM/Pjz777DNZm2NWVhZVq1aNVCqV0JIxcuRIAkBOTk6KNsfy8nIKCAggAMI2x+3btxMAqlGjhtCS8frrrxMA8vX1VbQ53r9/n6pXr04qlUpoyRg9ejQBIEdHR0WbY0VFBQUFBREAYZvjrl27OJfIktGpUycCQD4+Poo2x0ePHpG1tTWpVCphm+O4ceNkXNI2x8rKSgoNDSUAwjbHvXv3EgCytrYWtjm+8847BIC8vb0VbY7Z2dlkY2ND5ubm3JIhbXOcNGkSASAHBwfe5ijlioiIIADCNseDBw9yTZCWlkYzZ86UtTl+8MEHBIC8vLwUbY5PnjwhW1tbMjc3F7Y5Tp06VaYJpG2OWq2WoqOjCYCwzfHIkSMyraLf5ti5c2eDWuXZs2dkZ2fHtYq+Jpg5cybXBPptjlqtluLj4w1qlRMnThjVBF27dlVoFXb2Pn/+XKFVzp07x7l+/PFHo1qlfv36Mq0i1QSnTp3iXK1atVJYMnr06CHTKlJNkJeXJ9Mqw4cPl2mVefPmGdUqDRs2lGkVqSY4d+4c1yoiS8Znn32m0Crs7NXXKvqWjF9++cWoVklISJBplT179gi1SosWLRRapW/fvjKtItUEhYWFpFaruSbQt2QsXrzYqFZJSUnhWqVv374yrXL58mWjWqV///5cE3Tu3Floffi3Ff5brbn/zTK15oqrX79+ICLMnTuXZ5mxCgwMhIODA2rWrCkb+AHoTN5+fn5wdXXFrVu3FE+YNBoNnJyc4OXlJRv6AujM1MHBwXB0dERJSQmOHj0qW3dycoKLiwt8fX1x4MABxRNyY1w1atSAn58f3NzccPv2bcUTJo1GA0dHR3h7e2Pt2rWyJ25SrtLSUtkQCkA3+MXV1RW+vr44ePCg4gl5QEAAHBwcYGdnJ8u9BHQDVvz9/eHq6orMzEzFWyfG5ePjgzVr1gi5HBwcUF5ezvPZWDk4OMDNzQ0+Pj44cuSI4olvVVx16tSBq6sr7t27xzMPWXl6enKudevWyZ64mZub8+tVUVGBQ4cOGeQ6duyY4gmmv78/HBwcYG9vLxt0A+gGv7DrJeLy8PCAk5MTfHx8sH79etnbCMbl4OAArVYrG3IC6Aa/eHh4wMvLCydOnFA8wfT394e9vT0cHR2xefNmIZeLiwsePnyICxcuGOTasGGD7Om6mZkZv15ExPPsWNWuXRuenp7w8vLCqVOnFG8P69SpAwcHBzg5OWHTpk2ytWrVqiEgIAAuLi549OgRz4hk5e7uDicnJ/j6+mLjxo2yp8VSLkD3BkjEpdFocPr0aSGXvb091Gq1LFdVyqVWq5Gdna0YCOLq6gpnZ2f4+flh06ZNsqfFjMvBwQEqlUo2RAfQDX7RaDTQaDQ4e/as4u2hr68vHB0dhVxWVlYIDAyEWq3G06dPeXaliIsNY5JyBQUFwdHRUchVq1YteHl5wdPTE+fPn1e8PfT19YWDgwNcXV1lg6ekXM7OzsjJyRFyOTk5wc/PD9u2bVO8SWPXy9LSEnv27FFweXt7w8PDAxcvXlS8pfPx8YGjoyPc3NxkObSAbsBKUFAQnJyckJubi1OnTsnWXVxc+PXavn274o0V47KysuIZyqxsbW3h4+MDd3d3XL58WfGWjnG5u7tj3bp1v4tLrVbD2dkZderUwc6dOxVvYIKCguDg4IDq1avLhkcBusEvPj4+8PDwwJUrVxRv6by9veHo6AhPT0/ZsBBAN2AlODgYTk5OyM/Plw0OAnQDVtRqNfz8/LB7927Fmw7GZW1tjZ07d8rWbGxs4OvrC3d3d1y/fl3xNuxFuBwdHVFYWAh9TSTl2rt3r+JtflBQEOzt7WFjY4MdO3YY5Lpx44bibZiXlxccHR2h0WiEXOzvsaioiGejirj27dv3u7SKVBP8/9Aq9vb2sLW1FXKxs/fOnTuKDpmqtAq7Xsa0io+PDw4fPqx4O/1ntIpUE+hzSTWBIa3i7u4Ob29voVYxpgmkWiUrKwuXL1+WrUvPXmNapbKyUqEJmFbx9vbG8ePHf7dWYWfv/fv3cfHiRdm6u7s7nJ2d/7RWOXnypKIDi2kCQ1olJSUF6enpSE1NlQ07+jfUX5Ij+mfLdCMqLlOOqKlMZSpTmcpUpjKVqUz1z6yOHTtizJgxsqnA/+R60RtRsePXVP+n1aVLFxARj1GQlpeXF+zt7VGzZk3F2xsrKyt4e3tDrVbj3r17iqfFarUaDg4O8PT0VDwJBH57klNWVqZ46m9rawu1Ws3fDOlzaTQa2Nvbo1atWoq3N5aWlvDx8YFarcb9+/cVng5nZ2f+tHjHjh0KDwJ7u1NZWal4us64NBoNzpw5o3j6ybjs7Oywb98+IZezszMePXqkeFrs5OTEnxaLuPz8/ODg4CDkqlmzJlxdXeHp6Ylz584pnn56enrC3t4e9vb2irc3FhYW8PX1rZLLy8sLO3bsUDy08PPz42P+9Z/629jYwM3N7U9xOTk54cmTJ4o3246Ojpxr165dCn/Wi3CxN0P63hwPDw/Y29vDwcFBwaVSqeDn5wcnJyc8ffpU8RSbvbH09vbGrl27FH4jxmVmZqZ4G1GjRg24u7vDw8MDly5dUjyVZVxOTk6Kt0qMy9HREc+ePVM8xWZcXl5ePIJBWr6+vrC3t4dKpVK8jbC2toaHhwfc3d1x9epVxVNZd3d3/vnGuJ4/f654is2e5np7e2Pv3r0K/wzjsrCwULyNqIrLzc0NDg4OUKvVirdd5ubmnCsvL0/xxp1dZy8vLxw4cEDhefT19UXt2rVhZWWleBtRvXp1eHp68jdW+v5TxuXi4qJ42yXlYtEN0qpduzb//jp48KDijaiPjw/s7e0Ncmk0Gri6uuLmzZuKN8iurq78Ta0xLhZ/ZYjr0KFDijeiPj4+qF27NqpXr654S1KtWjVoNBrexaLv82Rcbm5uirdwZmZm/CwpKipSdALY2dnB2dkZXl5eOHLkiMIrx7isra0VHR3VqlWDl5cXXFxccOfOHQWXi4sLf8NjjKukpEQRY1arVi04OzvD29sbR48eVbypZWevjY2N4i0JO3tdXFxw9+5dxRtktVoNR0dHeHh4KM5eMzMzfpaUlpYquOzs7Pjf4/HjxxV+8Bfh+iOaQMol0gTserE3Q/pvajUaDRwcHGBra/unNIExrVJeXq6InpFqldOnTxvUBMa0irOzMx4+fKh4s+3k5AQnJ6cqtUpFRYWCq2bNmnBxceHdIvrdW/8XWkWr1eLkyZMGuf6MJsjOzla82X5RrUJECi4bGxu4urpCo9Hg/Pnzije1jMvBwUHRafLf0ipVaQJjWsXR0VHBpVKp0KRJE6SnpyM9PV0WcWYqSb1I/+5/68vkETVczPNoyMvUrVs3mZdJOko+NzeX7O3tDXqZ5s6dy705+l4mrVZLDRo04J4h/ZHtZ86cIQAyL5PUM9SzZ0+DXqa8vDxydHQ06GX6+eefZV4mqWdIq9VS48aNuWdI38t07tw5MjMzM+hl6t27N/cM6cfLFBQUsXHbkwAAIABJREFUkLOzs0Ev08KFC7lnSDSyPTExkXuG9L1Mly5dIjMzMzI3Nxd6mfr168c9Q/oj2wsLC8nFxcWgl2nJkiVGvUxNmzblniF9L9OVK1fI3Nxc5mWScg0YMIB7hvRHthcXF5Obm5tBL9Py5ctlXib9ke0tW7bkniF9L9P169dJpVIZ9DINGjTIoJeppKSEPD09DXqZVq9eLfM363uZ2rRpwz1D+l6mmzdvkoWFhUHf9XfffWfQy1RaWkpeXl4GvUzr1q0z6rtu27Yt9wzpe5nu3LlDlpaW3Ms0YsQImZdpyJAh3DOkHy9TVlZGvr6+Br1MmzZtkvmb9b1Mr7zyikHfdVZWFllZWcn8zVIv04gRIwx6mcrLy6lOnToGvUzbtm0z6mV67bXXDHqZmOfRkJfphx9+MOhlqqiooMDAQO5l6tevn8zLtHPnTs7FvExSz1DHjh0N+q4fPnxI1tbWBr1MY8eO5T5i/XiZiooKCgkJMei73rNnDwGQeZmk/ua3337boJfp8ePHVKNGDe5v1vddT5w4UeG7Zv7myspKCg8Pl/mbpfEy+/fv51yieJn333/foL/5yZMnVLNmTQJA8fHxCt/1lClTuL9ZP15G6nlk/map75rNZ7CwsBDGy7D5DGq1WhEvw+YzwIDvms1nsLGxofbt29PcuXNlXLGxsdzf3Lt3b5nv+tixY5xLFC/D5jOINAGbzwBAFi/DzpLZs2cb9F1L5zMwf7PUd820ikql4lpF6m9m8xmYJpD6rtl8BkNahc1nYFpF6m+WzmcQaRU2n4FpFX1NwOYzODk50bvvvivTKvn5+Ua1CpvPINUEUq3C5jNItQo7e8+fP6/QKtJ4GTafQeq7ZpqAzWeQahWpJmDzGZgm0I+cS0pKMqpVmCZISEhQaAI2n0GkVaTzGURahc1nMORvZvMZpFqFnb1Xr16VaRX9eBk2n8GQVmHzGZhWkUbOsfkM0lksUi42n4FpFakmYPMZpJpAqlXYfAaRVvm3Fl7QI2q6Ef2b1IIFCwx+4xYVFVFGRoYww5FIJ4hEuUisxowZI8xFItL9cOn/QElr4cKFBnORiouLKSMjQ5jXRES0e/dumj59uiLDkdW4ceOEGY5Euuw3UV4Tq0WLFgkzHIl0NygZGRnCDEci3XAKUYYjq/HjxwszHIl0NwL64l9av/76qzDDkUh3gzJ48GCZ+JfW/v37hRmOrCZOnCjMcCTS3QjoDzeS1tKlS4UZjkS6G5TBgwfLRLa0Dh48KMxwZDVp0iRhhiOR7kbAUIYjke4mVpThSKS7QRkyZIhBriNHjggzHFlNmTJFmOFIpLsRMJThSKQ7sEQZjkS6G4GhQ4cKMxyJiI4ePSrMcGQ1bdo0g4MMHj9+TEOGDBFmOBLpbq71hxvpc4kyHIl0wzxEGY6sZsyYIRP/0srOzqbBgwcLMxyJiNauXSvMcCTS3aAMGzZMmOFIpBO2+sONpDVz5kxhhiORLqd28ODBwgxHIt1NvyjDkXENHz5cmOFIpHsIJ8pwZDVr1ixhhiOR7kYgIyNDmOFIpBvAJMpwJNIJ2xEjRggzHIl0D+FEedOs5syZI8xwJNLdCGRkZAgzHIl0DyNEedOMa+TIkcIMRyLdkBFR3jSruXPnCjMciXQPLTMyMoQZjkREW7ZsEeY6M67vv/9emOFIpBsyIspwZDVv3jxhhiOR7gYlIyNDmOFIpHtIIspwZFw//PCDMMORSPdwUJQ3zWr+/PnCDEci3UPLjIwMYYYjkS7DW5ThyLhGjx4tzHAk0j0cNKYJ/oxW2bVrl1GtMnbsWINa5ebNm8K8aVYvolUMaYI9e/YI86ZZjR8/3qBWuX37tlFNsHjx4iq1iiFNsG/fPqNaZcKECQa1SmZmpuKBoLSWLFlSpVYR5ToT6TLPq9IqhjRBVlaWMG+a1Z/RKocOHTKqVSZPnmyQ68GDB0a1yooVK6rUKqK86X9zveiNqMkj+jepyspKg1lSlZWVMDc3N5hvZGyvVqsFERn9bENrfyUXEUGr1Zq4TFz/Kq4X+WwT17+bi7WzGcquNHGZuP6sJvg7cv1df2ebuP45XJWVlQYzSP9Krn9rvahHVJWRkfF/gKOrWbNmZXTp0uX/7H/vf6kGDBiAGTNmoKioCB4eHrCxseFr+fn5SEhIwMWLF2FlZQVPT0/ZD8TChQvRp08f5OTkwNnZGQ4ODrLPfuWVV7B161ZotVpoNBpZUPr58+eRmpqK+/fvc5+j9Idp0KBBmDp1KoqKiuDu7o6aNWvytcLCQiQkJODChQuwtLRUcP3666/o1asXcnJyuHdAWh06dMCmTZtQWVkJjUYjCwu+dOkS2rRpg3v37qFmzZpwc3OTcX377beYNGkSCgsLFVzFxcVISEjAuXPnhFzLli1Dz5498fTpUwWXmZkZ3njjDWzYsAGVlZXw9PSUcV29ehUtW7ZEVlaWkGvw4MGYMGECCgsL4ebmBltbW75WUlKCxMREnD17FhYWFvD09JT9Uly1ahW6deuGp0+fwtHREU5OTjKuN998E+vWrUNFRYXiel2/fh0tWrRAVlYWbGxs4O7uLuMaNmwYxo4di4KCAri7u8u4SktLkZSUhNOnT0OlUkGj0ci41qxZg08++QRPnjzhXgv22WZmZnj77bexevVqVFRUwNPTE9WrV+d7b926hebNmyMzM1PINXLkSIwePRoFBQWK61VeXo6kpCScOHFCyLVhwwZ07twZT5484f5IKdd7772HlStXory8XMGVmZmJlJQU3Llzh3tApMLshx9+wPfff4/8/Hy4ubmhVq1afK2iogLJyck4ceIEzM3NFVxbtmzBBx98gOzsbAUXAHz44YdYtmwZysrK4OnpCWtra76WlZWF5ORk3L59W8g1duxYjBgxAvn5+XB1dZVxVVZWIiUlBUePHhVybdu2De+99x6ys7Nhb28PZ2dnGVfnzp2xZMkSIdf9+/eRnJyMW7ducV+olGvChAkYOnQo8vLy4OrqCjs7O76m1WrRtGlTHD58GGZmZtBoNLLg7127duHtt9/G48ePhVyffPIJFi9ejNLSUgXXw4cPkZSUhJs3bwq5Jk+ejMGDByM3N1fI1bx5cxw8eFDItXfvXrz55pt4/PgxateuDbVaLeP69NNPsWDBApSWlsLDwwM1atTga48fP0ZiYiJu3LiB6tWrK7imTZuGb7/9Frm5uXBxcUHt2rVlXK1ateJ+Nn2ugwcP4vXXX8ejR49gZ2cHFxcXGVfPnj0xf/58lJSUwNPTU8b19OlTJCYm4tq1a0KuWbNmYdCgQXj+/LmCi4jQqlUr7hvT5zp8+DA6dOhgkKt3796YO3cuSkpKFNcrJycHCQkJuHr1KqpVqwZPT08Z15w5czBw4EA8e/YMarWae88ZV2pqKnbv3g0iUpxxx48fxyuvvIKHDx+iVq1aijOub9++mDNnDoqLixVn7/Pnz5GQkIArV64Iz9558+bhiy++EHIBQHp6Onbu3CnkOnXqFNq1a4cHDx4Iufr374+ZM2eiuLgY7u7uMq68vDwkJibi0qVLQq4FCxagb9++ePbsmVATtGvXDtu3bxdqgrNnzyI9PR3379+Hra2t4owbOHAgpk+fLtQqBQUFSExMxMWLF2FpaQmNRiPjWrRoEXr37m1Qq7Rv3x5btmyBVqtVnL0XLlxAamoq7t27B1tbW8X1+vrrrzFlypQqtQo7e6VcS5YsMapVXnvttSq1iiFN8N1331WpVZgm0L9ey5cvR/fu3Q1qlY4dO2L9+vVCTVCVVhkyZAjGjx8v1CqlpaVITEzE6dOnhVpl9erV6Nq1q0Gt0qlTJ6xdu1Z49t64cQMtWrTA3bt3hZpg+PDhXKvoc5WVlSEpKQmnTp0SaoK1a9eiS5cuBrXKO++8g1WrVqG8vBwajeYPaxX9s1dfq+hfr39rDR48+EFGRsasKv/DF3lt+t/6MrXmGi7m/QIgzJEcOnQoARD6maTeL0CZI8m8X5D4rKTZTCzvDgI/E/N+MS79HEnm/WJc0mym8vJy8vf35+vMz8TaKpj3C3p+JtZWwbxfjEuaI8m8X2xdP0eSeb8AZY6k1PsFKHMkWd4d42J+JtYC+uabb/J1/RxJqfcLUOZIMu8X45LmSFZUVPC8O0CZI8m8X4xLP0eSeb8g8Fk9fvyYbGxs+Hp8fLzMz8S8X4AyR1Lq/QKUOZIHDhzga6IcSeb9ApQ5klLvF6DMkWR5d9DzMz169Ejm/QKUOZLM+8W49L3XLO8OUOZISr1fEPiZmPeLcUm919JsXvzHZyX1M7FsXgDCHEnm/QKU3mup9wsCPxPL5gWUOZJS7xegzJFk3i/Gpe+97t69u4xL6r2Wer8Apfeaeb8Yl9RnJc27A5Q5ksz7xbj0vdfM+wUocyRZ3h1b1/czMe8XoPReS71fgDJHkuXdARDmSDLvF6DMkZR6vwCl95rl3QFi7zXL5gWUOZLM+8W49L3XLO8OAj+T1PsFKL3XzPvFuPRzJJn3C1DmSF67do1UKhXn0vdeM+8XoPReS71fgNJ7vXLlSr4mypFk3i9AmSPJvF/sjNPPkfzmm29kXNIcSWk2L6D0XrNsXsal771OS0vj6/rea5bNy7j0cyRZNi+g9F6XlpaSj48PX9f3XrNsXkDsvWbZvIDSe52ZmSnUBEyrsGxeQKxVWDYvoMyRZNm8jEs/R/LVV1/l6yKtUq1aNb6u771m2byMS1+rsGxeQJkjybJ52dmrr1VYNi+g9F4/ePBAplX0vdcsmxdQeq+l2byATqtIvddVaRWWzcu4PvroI1q1ahUVFBTwbF62ru+9Hj9+PF+Teq8fP34sy+YFdFpF6r1m2bzs7NXXKu+++y5fZ5qAea9ZNi9b1/des2xexqWvVVg2L6DTKlLvNcvmZVz6WoVl8zIu5r1mWsXW1pavS73XWq2Wpk2bxteYVvnxxx+FtpB/S8HUmvu/U7Vr14ZWq0VBQYFi+hmge5KjUqkU0z9ZqVQq3g4hKgsLC4N7WTuB/hQx6d7KykoT1wtysSiefxoXAKN/F/8/uF7ke8TYXnNzc6P/n01cL77X2PfuX8llZmYGc3NzE9fv4Pqjv4P+yVx/xVnyd+Vin23i+ndzmbSKkuuvOHvNzMxQr149Pjk3IiLiX9PCa8oR/R8q9g1uKlOZylSmMpWpTGUqU5nqn1GWlpZISkpCeno63nzzTVkr8z+5TDmi/0N17NgxFBQUoGXLljwrz9LSEsnJyUhKSkJERAQOHDiA77//nu9xdXVFWloaYmJiEBkZiY8++kiWp1ivXj20atUKwcHBqKiowLvvvsvXbG1t0bJlSzRs2BCRkZGYOnUqVq1axdcDAwORnp6O4OBg+Pv7o02bNjwrz9LSEomJiUhJSUFYWBiOHj2K4cOH870uLi5IS0tDbGwsoqKi0KVLF1kOX926dTkXEeHtt9/mazVr1uRcUVFRmDFjBpYvX87XAwICOFdgYCBSU1N5Jh3jSk5ORnh4OE6cOIEhQ4bwvWq1WsbVrVs3Wd5dfHw8WrZsiZCQEFhYWKBjx44yrhYtWqBRo0aIjIzEnDlzsGTJEr7u7+/PuYKDg5Gamsoz6SwsLJCQkICUlBSEh4fjzJkz+O6772RcqampiIuLQ1RUFHr06CHLb4uLi0Pr1q0RHBwMKysrvP7663zNxsYGLVq0QOPGjREREYGffvoJixcv5ut16tRBeno6QkJCEBwcjPT0dJ5JZ2FhgSZNmqBp06YIDw/H+fPn8fXXX/O9zs7OMq7evXvLcr9iY2PRqlUrhISEwNraGh06dOBrNWrU4FyRkZH4+eef8csvv/B1X19fpKenIywsDCEhIWjbti3PqVWpdLlbzZo1Q1hYGC5fvoyBAwfyvU5OTkhNTUV8fDwiIyPRr18/WeZmdHQ02rRpg+DgYNSsWRPt27eXcTVv3hxNmjRBREQEFi1ahPnz5yu4QkNDERYWhnbt2vHsN5VKhcaNG3Ou69evo3///nyvo6Mj54qKisKXX34py2qMioriXHZ2dnj55Zf5mrW1tYxr6dKlmDt3Ll/39vZGeno6wsPDERYWhldeeYVnrKlUKjRq1Ihz3b59G3379pVxtWnTBnXr1kVkZCS++uorWfZgZGQk53JwcEC7du34E19ra2s0a9YMTZo0QWRkJFasWIHZs2fzvV5eXvwJb3h4ONq3b89zV83NzdGoUSM0b94coaGhyMzMRJ8+ffheBwcHzhUVFYVvv/1WllkXERGB1NRUBAcHw9nZGenp6fxhXfXq1WVca9aswYwZM/hejUbDuSIiItChQweeb2pubo6GDRuiefPmCAsLw7179/DZZ5/xvfb29mjdujXq16+PqKgoZGRkyHJZw8PDOZeLiwvS09P50/fq1aujadOmSExMRPj/Y++8w6q4tj78OyBdREWavYECgg1b7A0bpqkxxiQmehO7iUaj0ZjYazQ2xN67xt47lmCl2wsdAREE6W19f5y7t7PP7HMgmnw394b1POd5brIz43tHcX5nZq/1NmiAY8eOwdfXlx9btWpV9O7dG56envDw8MBHH33E/aZGRkZo1aoVvL294erqiqSkJIwaNYofW758eYFr1qxZgjfT3d0dPj4+qFevHpycnODj48O5zMzMBK5Tp05h2bJlApePjw8aNmwIDw8PDBgwgPs6NRoNWrVqxX8fU1JSMHz4cH6sjY0NevTogZYtW8LT0xPz5s3D6dOn+bqbmxvnqlatGnr27MnfGpiZmaFTp06c6+zZs1iyZAk/tkqVKpzL09MTAwcO5L5OjUaDli1bolu3bqhfvz7S09OhnD9hY2OD7t27o1WrVvD09MTChQtx4sQJvu7q6gofHx+4uLigZs2a6NWrF/fnmpqaCvfeixcv4pdffuHHVq5cGT4+PmjUqBE8PT3x+eefc/+kRqNBixYt4O3tDTc3N2RmZmLIkCH82HLlyglcv/76K44ePcrX2d/TLi4uqF27Nnr27Inc3FzO1aFDB36Pu3z5MhYsWMCPZb/vLBN8+eWX3KfI3sowrtzcXHzxxRf8WGtra4Fr+fLlOHToEF+vV68e53J2dkaPHj2ErKLkCggIwNy5c/mxulnlX//6l+BYZpnA1dW12KyycuVK7N+/n6+zrFKvXj04OzsbzCo3b97ErFmz+LElySosEwDAwIED+RrLKq1bt4aHhwfWrFmDvXv38nWWCVxdXVVZpUyZMgJXUFAQpk+fzo/VzSojRoxAWFgYX2/atCm/Xn80q+hmAh8fH7x69YpztWvXDp07d4a7uztCQ0Px008/CVy9evXiXGPGjBHcqU2aNEGPHj3g6uoKExMT9O/fn6/pZpXNmzdj+/btfL127dr83uvq6orevXtzT62xsbHAdefOHSGrKDNBw4YNMXbsWMFb3rhxY85lKKt4eHhg27Zt2Lp1K18vaVZxc3PDw4cPMWnSJBWXj48PvL29hZ7S0tKpkuzf/bM+pT2i+mvevHlS7xaRdjS0i4uL1LtFpB3VrtsPpqz+/ftLvVtE2pHV1tbWUu8WkVb9IvNuEb322bE+Nd3R+xcvXpR6t1gNHDhQ6t0iIkpMTKRy5cpR+/btaeHChYJ3i0g7tlzm3SJ67bOTebeItCPR9Xm3iIgGDRok9W4RaTUWNjY2UhcnkXY8uMy7xbg8PT15n1pAQIDAFRAQQBYWFlLvFhHR4MGDuXdLd/T+ixcvqEKFClLvFhGRn5+f1LtF9Npn5+HhQT/88INq9P6NGzf0ereIiL7++mupd4tIq7GoWLGi1LtFpFVgKPvUlKP3i4qKqFmzZtSgQQOVi5NIq/0wNzeXOkKJtO5d5gjVHb2flpZGlSpV4v1gukqADRs28D413dH7zL3r7u5OEydOVCkBQkJCyNzcXNWnxmr06NFSFyeRVmNhZ2dHrVq1kioBNm/eLHWEMq42bdrwfjBdJUBYWBiZm5vzPjXd0fvffvstVa5cmYYOHarSBGVkZJCDg4PUEUqkVSewPjXZ6P327duretdZ3bt3jywsLKSOUCKte1fm4iTSaiycnJxUfWqsdu/ezfvUZKP3O3furOpdZ/XgwQOysLCQOkKJtO5d1g+mqwnKzs6mKlWq8D41XU3Qvn37uCNUpgnq1q0b713XVQI8fvyYLC0tqWvXrlJN0JQpU8jBwUHoXWeVk5ND1atX531qupqggwcPqvrBlNWzZ0+pI5RIq9ewtLSUOkKJtO5dmSOUiHhPI+tT09UEHTlyRNUPpqx3331X6ggl0s5fsLKyos6dO0s1QTNmzFD1qbFiPY2sT01XE3TixAmpi5PVBx98IDhClffe2NhYsrKyknrDibTuXZkjlIj4/AXWp6abCc6cOSN4w3W5+vXrxx2hupkgPj6eypYtq+pdZ7VgwQIhq+hmgnr16lHjxo1VLk4irWrOUFb5+OOPeVbR1QQlJCSQtbW11BtOpFW/MG+4oayi6w0n0upbDGWVTz/9lGcV3UyQlJRE5cqV473rulll6dKlBrOKh4eH1MVJpFW6GcoqX3zxhdQbTqR175YvX15vVlmxYgXPKrJM0KhRI6F3Xcl17do1g1llyJAhUm84kda9W6FCBd67rptVVq1axbOKriaIZRXWu66bVW7evClkFd1MMHToUFXvOqvU1FSytbXVm1XWrl3Ls4quJojNX5B5w//JhVKP6H9X3bt3T+8f3LS0NL3eLSKtC1Tm3SLS/kWn+4OurPj4eKl3q6Rc+rxbjEvmtyLS/uAWxyXzW7G6f/++Xq5Xr17p9W4RaQPTm3I9e/asWC59HqlXr17p9W4xLpnfqiRcCQkJUu9WSbgyMjL0ereItE7Xt+GSebdYPXjwQC9XZmamXkco45K5OEvClZiYKHVxKrlkzksi4gNO9FVkZKTUxcnKEFdSUpLUxVkSruzsbL0uTiJtIH9TrufPnxvkevjwoV6unJwcvS5OxiVzcSq5lCFIWcnJyQaHQTx8+FDqvCTSfvnR5+Ik0nr43pTrxYsXUhcnq0ePHunlysvL0+viZFwyF2dJuFJSUlQhW5dL5rwk0n750Q3ZyoqJiTHIde/ePYNcMhcnq8ePH+vlKigooPv37+v9sxsbGyt1hJaEKzU1VeriVHLpu/cWFBTodYQyLkPCe0P33pcvX74xV2FhoUGuuLi4N+b6T2YVQ5kgPT39b5tVissEb5NV3iYTGOL6T2aCt8kq+ty4RNpM8KZcWVlZBrPKP7VK+kVULpIqrf/XIiJERETw7Zy6lZqaitjYWL19pLGxsXwLoW7l5OQgOjqabzvSraSkJCQkJEgbsIkIkZGRerlevnyJ2NhYvY3hcXFxBrmioqL4tiPdev78uV4uQDtqm20peROuFy9eSNdyc3OL5Xr27JlersjISL1caWlpBrni4+P1cuXl5SEiIoJvh/qjXFFRUXxbrm6lp6cXy8W2gupWfn6+Qa7k5OS35tI3PODZs2d6uQoKChAREcG3af1/c+n7fSyO68WLFwa5oqOj+ZYl3Xr16lWxXM+fP5euFRYW4unTp8jKytLLFR8fb5CLbVnSx5Wfny9dT0hIKJbL0PUqjkvf9crIyCiWi2011q2ioqJir1dcXNwbXa/iuBITEw1yRUREFPv7qO9eEhMTo5crMzMTsbGxeu8liYmJSExMlK4REZ4+fcq3J+pWamoq4uLiDHKlpqbq5YqOjjZ4vYrjMnTvNcQVGxurlys7OxsxMTEG772GuCIiIgxeL0OZIC4uziBXVFTUG2cCQ1mF3XsNcRWXCd6EC/jrMsHbZhVDmeDly5eIi4t746wSGRn5l3G96fXKz89HZGSkwaxSHJe+e29JMpShTGCIqySZQN+9pLhMUFqGq9Qj+jcojUaDDRs24P3338elS5dU7i9zc3O0bt0aCxcuxL1791Tur9u3b6NFixY4evSoyklmYmKCUaNGYfTo0bh9+7bK/ZWVlQU3Nzds3boVERERgpNMo9Fg8+bNePfdd+Hv769yf5mbm6Nt27aYP38+7t69q+IKDg5G8+bNceTIETx79kxwf5mYmODbb7/FiBEjcPPmTZX7Kzs7G25ubti8eTMiIiJUPtBt27ahd+/euHjxosr9ZW5ujg4dOmDevHm4c+eOyv0VFhaGZs2a4fDhw9yfyhxbZcqUwXfffYdhw4bh5s2bKvdXXl4e3NzcsGnTJjx9+lTFtWvXLvTq1QsXLlxQub8sLCzQqVMnzJkzh3MpXWn37t1D06ZNcejQIZU/tUyZMpg0aRK+/vpr3LhxQ+X+ys/Ph7u7OzZs2ICnT5+q3F979+5Fjx49cO7cOZX7i/Uozpw5E+Hh4Son2YMHD9CkSRMcPHgQcXFxgmPL2NgYP/74I4YMGYLr16+rPKWFhYVo0KAB1q1bhydPnqjcX/v370e3bt1w7tw5lfvLwsIC3bp1w4wZMziX0kn25MkTNG7cGAcOHFD5U42NjfHzzz9j8ODBuHbtmspJVlRUBA8PD6xdu1bKdfjwYXTt2hVnz55VeUotLCzg4+ODadOmISwsTOVKe/r0KRo1aoT9+/cjJiZG8IEaGRlh5syZGDRoEK5du6bylBIRPD09sXr1ajx+/FjlAz169Ci6dOmCM2fOqDylFhYWeO+99zB16lSEhoaqfKDR0dFo2LAh9u3bJ+WaO3cuPv/8cwQEBKg8pRqNBo0aNYKfnx8ePXqk4jp58iQ6deqE06dPqzylFhYW+PDDDzFlyhQpV1xcHDw8PLB3717ExMQIPlAjIyMsXLgQAwcOxO+//67ylBoZGaFRo0bw9fXFw4cPVT7QM2fOoEOHDjh16pTKU2pubo5+/frhhx9+QEhIiMpTmpCQgAYNGmDPnj2Ijo4WuDQaDRYvXoxPPvkEV69eRXp6OhwcHDhXmTJl0KRJEyxfvlzKdf78ebRv3x4nT55UeUrNzc0xYMAATJw4EcHBwSrvZlJSEtzd3bEhg3r5AAAgAElEQVR7925ER0cLPlCNRoOlS5eif//+uHr1qspTWqZMGXh5eWH58uW8T0/JdenSJbRt2xYnTpxQ+UDNzMzw2WefYcKECQgKClJ5Sl+8eAE3Nzfs2rULUVFRKi5fX1989NFHuHLlispTamJigubNm2Pp0qW4f/++iuvKlSto3bq1lMvU1BSDBw/GuHHjEBgYqLpeqampcHNzw44dOxAVFSV4SjUaDVatWoW+ffvi8uXLKh+oqakpWrZsiV9//RX3798HkegDvXbtGt555x0cP35c5Sk1NTXFV199xXvWdD2laWlpcHd3x/bt2xEZGQkzMzNUqVKF33vXrVuHDz/8EP7+/iouMzMztGrVCosWLcK9e/dUXDdu3EDLli1x7NgxJCQkCPdeU1NTjBgxAmPGjOFcSk9pRkYG3NzcsG3bNkRGRqoywcaNG3lW0c0EZmZmaNOmDRYsWCDNKoGBgTyr6HpKTUxMMHr0aIwcORK3bt2SZhV3d3ds2bKFZwKld3PLli149913eSbQzSrt2rUTsory3hsaGormzZvzTKCbVcaOHas3q+Tk5AhZRddTun37dvj4+ODChQvSrNKxY0fMmTMHd+/eVWWV8PBweHl54fDhw9JMMGHCBAwdOlRvVnF3d8fGjRvx5MkTlad09+7d6NmzJ86fPy/NKp07d8bs2bOlWeX+/fto2rQpzwRKLmNjY/zwww8Gs0qDBg14VtH1bu7bt89gVvH29uZZRffe+/DhQzRp0gQHDhyQZpWpU6cKWUXJpcwqjx8/VmWCAwcOGMwqPXr0wPTp03km0PWU/hOrpB7R0qm5f4PavXs3nj9/jtGjRwv/3tXVFW3atEHlypUREhKCgwcP8jVTU1N06tQJderUgYuLC37++WfhSXblypXRtWtX2NvbIy8vD0uXLuVrbKBCkyZNUL16dezevRtBQUF8nQ1UsLe3R/Xq1YWhLIB2oELbtm1RuXJlhIWFCcMD2KCHunXrwsXFBdOnTxeegDIuOzs7FBYW4tdffxW4mjdvjqZNm6J69erYu3ev0HRerlw5dOvWDQ4ODqhRowYmTJggcNWrVw/t2rWDk5MT7t27JwwPYIMenJ2d4eLighkzZghP9JycnDgXACxatEg4t5LrwIEDuHHjBl9jAxUcHR1Rs2ZNTJgwQXiq5uLigvbt28PR0REPHz4UhgewQQ9sCMScOXOEtx2Ojo7895GFcmU1a9YMTZs2RY0aNXDo0CFhQI61tTW8vb3h6OiI2rVrY8KECcKTamdnZ3To0AEODg54/Pgxdu3aJXC1a9eOD6yaP38+H/gCaAc9eHt7w87ODiYmJpg/f77A5eXlBS8vL1SvXh1Hjx4VBuSwgQqVK1dG7dq1MX78eIGrbt26nCsyMlIYasAGKri6usLZ2RkLFizgA18A7UCFbt26wc7ODmZmZsLQDEA76KFZs2aoVq0aTp48icuXL/M1NlChSpUqqFOnDsaPHy88ea1Tpw46duwIBwcHREdHC0MN2PAnNzc31K1bF4sWLUJsbCxft7Oz41yWlpbCgC9AO1ChRYsWqFatGk6fPg1/f3+Bq2vXrqhatSrq1KmDCRMmCE9ea9euzbni4+OxadMmvsYGKri7u6NOnTpYunQpH/gCaAcqdO/eHZUqVULZsmWFYR6AdvgT4zp37hwuXLjA19jwp2rVqsHZ2Rnjx48X3krVqlWLcyUmJgoDmNjwpwYNGqBOnTpYvnw5IiIiBK5u3bqhUqVKsLGxEQaPAdrhT61atUKVKlVw8eJFYXCPpaUlunTpgurVq8PZ2Rnff/+98NagZs2a6NixIxwdHZGUlIT169cLXGwASe3atbFy5Uo8efKEr9va2qJ79+48hCgHjwHa4U+tWrVC1apVcenSJZw5c4avseFPNWrUgLOzMyZOnCg8na9RowY6deoEBwcHvHjxQhgMxYY/eXp6olatWlizZo0wnK5ixYr8z5ednR2mTp0qcHl4eOCdd95BlSpVcPXqVZw6dYqvseFPNWvWhLOzMyZNmiS8ga5evTo6d+4Me3t7vHz5EqtXrxa42CCZWrVqYf369fyLJKAd/sS4HB0dMWXKFIGrQYMGnOv69es4fvy4wNW5c2fUrFkTLi4umDx5svCGsFq1aujcuTMcHByQnp4OPz8/gatVq1Zo1KgRatSogU2bNgmDaMqXL8//3Ds5Oam43N3d0bp1a1SpUgU3b94UBgqx4U+1atWCi4sLfvzxR+HNUtWqVdGlSxfY29sjMzNTGFjFhj81atQINWvWxNatW4VBNEquqlWrCsNPAO3wJ5YJAgMDcfjwYYGL3XudnZ0xdepU4c1SlSpV+D0uNzdXGFjFhj8xrh07dghD89jwJzs7O1SrVg0TJ04UuFxdXdG2bVs4OTkhNDRUGH6omwneJKs0btwYNWrUwJ49e4SheSXNKk5OTrhz5w5+++03gUuZCXSzipOTE7/HFRUVYfHixcK5WSaoUaMG9u3bB2W2LWlWcXR0xP3794WswjIBG8A0c+ZM4S2fo6Mj59JoNMIgLSVXcVmlVq1aGD9+vCqrsAwlyyrt27fnmUCWVby9vVGpUiUYGxursoqXlxeaNWuG6tWr4/DhwwgICOBrbPiTk5OTNBM4OzvzDPXkyRNhKCMb/sS4FixYgGfPnvF1ZVYxNTUVhn4CrzNB9erVcezYMVy9elXgUmaVCRMmCJmgbt26nCsqKkoYysiyCtO21KlTB/+0KtW3/BdVqb6ltEqrtEqrtEqrtEqrtErrf6/q16+Pjz/+GOPHj+dv+f/Xq6RfREt7RP8G1bRpUzRp0kS6ZmpqivLly/MtJrpVtmxZ2Nvb8y0TyjIyMkLZsmXh4OAgPdbS0hK2trZ8a4Js3dHRUbpmZmYGGxsbvpXjTbjs7e0Ncukbd22Iy9TUtFguOzs76ZYJjUZT7PWqWLGiXi4rKyu+nedNudi2wD/CZWFhgYoVK/Jtgfq4jIzUP+4mJiawsbHR67UqCZe+34u35SpXrtwbc1lZWRV7vdi2QH1cbAvTH+GysrLibz0NnVsfV4UKFfRysWst4ypTpkyx16tSpUp/GZeDg4NBLrbTQPbrVqpUSe+N2RCXubk5KlSowLcr6uNiW6v+TC5DfweVlIttO9Xlsra2LpaLbb/7/+bS93e2lZUVbG1tDXI5OTlJ18zMzEp0j5NxGRsbvzWXoXtcSbjYttM/wlWSe+/bXi99996/iuvPyCpvw/U2meBtMpShTPCfzirF3XtlWYVlgv+1rFKSTPBXZJWqVati+PDhWLx4MSZOnPiP+RL6h6okE43+rE/p1Fz9dfjwYQJAAKTjpXv37k0AyMjISDVeOjIykkxMTAgAV04ox0tPnz6dn1t3vHReXh7VrFmTAJCZmRlXYbAJc8ePH+fHVq1alYYNGyaoMN5//30CQBqNRqXCiI6OJlNTU4FLqZyYPXs2P7ebm5ugwsjPz6c6depwrh49epCvry+fhnvq1Cl+rEyF0bdvX86lq8KIi4sjMzMzAsCVE9u2beNc8+bN4+fWVWEwlQ4AMjU1Vakwzp07x4+tXLkyff3114IKo3///pyLqTCYcuLZs2dkYWFBALhyQqnC+OWXX/i5dVUYBQUFVL9+fc7VrVs3QTlx8eJFfqxMhTFw4EDO1aJFC5o5cyYFBwdTUVERJSYmkqWlJQHgygmlCmPJkiX83LoqjMLCQnJ3dycAZGJiQl27dqVly5bxCXOXL1/mx8pUGJ9//jlf11VhPH/+nMqWLcu5+vbtK6gwli9fzo9lKgymnGAqHcalq5wICAjgx8pUGIMHD+brzZo1o+nTp3MVxosXL8ja2poASFUYfn5+/FhdFUZRURE1btyYAFCZMmWoc+fOtGTJEj4N98aNG/xYe3t7lQrj66+/5uteXl40bdo0rsJITU0lGxsbzqWrwlizZg0/lqkwzp07x7maNWvGuTp16iSoMAIDAwWuL7/8UlBODB8+nK8z5QRTYaSlpVGFChUIgFSFsWHDBn4sU06cPXuWcnNzuUqHcemqMIKDg/mxMhXG6NGjBS6lHis9PZ1sbW0JgKDCYNNwN2/ezI/V1WMxlQ4AMjY2VqkwwsLCSKPREACuwlAqJ7799lt+bqbHYiqMjIwMsrOz41y6Kozt27fzY5V6LDalt3379pxLV4Vx7949zsVUGHv27OFc48eP5+dmeiymwsjMzCQHBwcCIKgw2DTc3bt382NleqzOnTvzexxTYbDprg8ePCAjIyMCINVjTZo0iZ9bV4WRnZ1NTk5OnKt37960evVqzrVv3z5+rEyF4e3tzbl0VRiPHz8mY2NjgUupwpgyZQo/t1KFUVBQQDk5OVSlShUCQObm5uTj4yPosQ4ePChkAl0VRs+ePTkXU2GwTPD06VMqU6YMARD0WIzr559/5ufWVWHk5uZS9erVVZmATcM9cuSIkAl0s8q7776ryiosE0RFRRnMKjNmzDCYVWrVqiVwKfVYJ06cEDKBblb54IMPhKyizASxsbE8q8j0WHPmzFFlFWUmYFlFmQlYVjl9+rTBrNKvXz9VVmF6rPj4eDI3N9ebVebPn6/KKspMoMwqunqs8+fPG8wqH3/8sZBVlHqshIQEg1ll0aJFQlZRZgKm0mFcunosf39/g1nl008/VWUCllWSkpIMZpWlS5eqsgrTYzHtn76scuXKFVVWUWaCL774QsgEM2bMUGm7/mmFUn3Lf08VFRXRiBEjhB8oZT148ECvb45I+0Mv880Racddf/TRR8IPlLKOHDki9c0xrlGjRkl9c0TaUf99+/aV+uaIiH799Vepb45IO+66f//+tGTJEqkK4/jx41LfHKsxY8YI4V9ZT58+pb59+0p9c0REy5Ytk/rmiLQKjP79+0t9c0TaL8Ay3xyrsWPHSn1zRFqtR58+faS+OSIiX19f7pvT5crJyaGPP/5Y6psj0nrjZL45Vt99953UQUuk1UH06dNH6psj0n5xUoZ/ZeXm5tInn3wi9c0RaW92Mt8cqwkTJkh9c0RavUGfPn2kvjki7RcnmRuXSKvAGDhwoNQ3R6T9Yi7zzbGaNGmS1DdHpB3X36dPH6lvjoho3bp1Ut8ckVaB8emnn0p9c0Tam53MN8dq8uTJUt8ckXb8fJ8+faS+OSLtFzqZb45Iq5r47LPPpL45Iu0XcxayZVw//vij1DdHpFXS9OnTR+qbI9J+oZP55hjXoEGDpL45IqLr169LfXOsfvrpJ6lvjkirfunTp4/UjUtEtG3bNqlvjkirmvjyyy+lvjkiolu3bqlCtrKmT5+u1zeXkpJCffr0ER4IKmvnzp2qkK3kGjJkiNSNS0QUFBQkdeOymjVrltSNS6RVhvTp00cI2cravXu31I1LpL2XfPXVV1I3LhFRaGioKmQra86cOVI3LpFWGdK3b1+pg5ZI+0VTN2Qrub7++mvhgaCywsPDVSFbWfPnz5e6cYm0ao5+/fpJHbRERPv375e6cRnX8OHDadasWdJMcO/ePVXIVtbChQulblwirZqjX79+tGzZMinXoUOHpG5cxjVy5EipG5dIq0sylFUWL14sPBBUFssqMgctEdHRo0f1ZhUiolGjRunNBI8fPzaYVZYsWULjxo2TZgJlVpFlgpJkFeUDQWVFREQYzCrLly8XHggqq7iscvr06WKzivKBoLJKklUMZYIBAwbozSpnz541mFXGjx+vN6vExMTwrCLLBH5+fgYzgaGscuHCBdUDQWV9//33erNKXFwczyqG9Fj/tCrpF9HSHtHSKq3SKq3SKq3SKq3SKq3SKq3S+lOqpD2ipfqWv0FlZmZi6NChSEtLE8aVszp27BhWr14tjFFnRUQYP3487t+/L4x3Z/Xo0SN8//33ICJUrVpV1c+yYsUKnDhxQhg7zyorKwtDhw5FamqqMN6d1YkTJ+Dn56dSmLD6/vvvcefOHWGMOqunT5/yyWjK8e6sVq5ciWPHjgnj3Vnl5ORg6NChSElJkV6v06dPY/ny5Xq5Jk2ahLCwMClXZGQkxo0bp1KYsFq9ejWOHDkijHdnlZubi6FDh+LFixdwcnJS9SWdPXsWy5YtU413ZzV58mSEhIQIY9RZRUdH49tvv+UKE12utWvX4tChQ8IYdVZ5eXkYOnQonj9/Lox3Z3XhwgX8+uuvqvHurH788UcEBQVJueLi4vDNN9/wceW6XOvXr8eBAwekXPn5+Rg2bBiSkpKEMeqsLl26hF9++UWlomH1888/4/bt26hYsSIfo84qPj4eo0eP5qoQ3T6bTZs2Yd++fcJ4d1YFBQUYNmwYnj17JuW6cuUKFixYoBrvzmr69Om4efOmoFZhlZCQgFGjRiE3N1c63n3Lli3Ys2cPrKys4OTkJPSkFBQUYPjw4Xj27JmgVmEVEBCAefPmqcbhs5o5cyauX7+OChUqqLiSkpIwYsQIrjDR5dq+fTt27dolKF9YFRYWYsSIEYiNjZVyXb9+HXPmzFEpX1jNnj0bAQEBglqFVXJyMoYPH85VIbr9Pzt37sSOHTukXEVFRRg5ciSio6MF5QurW7duYebMmTAyMkLVqlVVPYhz587F1atXUb58eRVXSkoKhg8fjqysLCnX7t27sW3bNkFhouQaNWoUoqKiBOULq6CgIEyfPl2lfGE1f/58XLp0SVC+sHr58iWGDRuGzMxMKdfevXuxZcsWKRcRYcyYMYiIiJBer5CQEPz888/QaDTS67Vw4UJcvHhRypWWloZhw4YhIyNDUKuw2r9/PzZu3MgVJrpc33zzDZ48eSIoX1iFh4fjxx9/BADp9Vq8eDHOnTsnKF9YvXr1CkOHDsWrV68EFQ2rQ4cOYd26dYLyRck1duxYPHr0SMp17949TJ48GQCk994lS5bgzJkzUq6MjAwMHToU6enp0nvvkSNHsGbNGkH5ouQaP348Hjx4IM0EDx48wKRJk/Tee5ctW4ZTp05JM0FxWeX48ePw8/PTm1UmTJiAe/fuSbkeP37MJ7vLuHx9ffVmlezsbINZ5eTJk/D19ZVyAcDEiRMNZpXvvvuOq1V0ufz8/IrNKi9evJDee8+cOWMwq/zwww8ICwuT3nujoqIwduxYlfKFVUmySnJyspTr/PnzWLJkiV6uKVOmICQkhE8PV1ZMTMxbZ5WkpCQp18WLF7F48WK9WWXq1KkICgoSlC+s4uLiMGbMGL1ZZcOGDdi/f780E7CskpiYKOjpWF2+fNlgVvmnVkn1LaVbc/8mxXpcZD2N2dnZVLlyZd5XwfoX2Jav3377Tehf0N3C1K1bN95Xodu/8OTJE97jwvoXjhw5wrdW/fjjj0KfwOzZs3n/Qk5ODlWtWlXVv8C2MB06dEjoX9DdwtSrVy+9/QsRERG8x4X1Lyi3ME2bNo1ztWjRQuhfyM3NpRo1agj9C1u2bOFcR48eVfUJKLcwvffee6r+BcYVHR3Ne1ycnJz4FibGNXPmTL39C8oel3Llyqm2Vp08eVLg0t1u/eGHH+rtX1D2uDg6Oqq2MM2dO1dv/0J+fj7VrVuX91XobmE6c+YMP1a3p5GI6KOPPuJcur2Wyh4XBwcHvoWJcS1YsICf28vLS9haVVBQQPXq1SPgda/lxo0bOdeFCxf4saynUbm1asCAAbx3ULfXMjExkfe4sJ5G5RamxYsX83M3bdpU2G5dUFBAbm5uBIg9jWxr1aVLl/ixderUUW23/uyzzzhXp06dhC1MSUlJZGVlpbenUdnjwnot2RamwsJC8vDwELiU262vXr3Kj9XttSR63ePCei2VW5iSk5N536udnR3fbs24fH19+bkbN25MP/30E9/CVFRURI0aNdLb03j9+nV+rG6vJRHRv/71L709jSkpKVSuXDkCtL2WututV69ezc/Nei3ZduuioiJq2rQp52I9jWxr1a1bt/ixrNdSud162LBhApdyu/XLly+pfPnyBGh7LXW3W69bt46fu2HDhsJ266KiImrRooXQ07hmzRrOFRQUxI9lvZbK7dYjR47U29OYlpZGFStWFHoalb2WmzZt4udmvZZsu3VRURG98847nMvHx0fotQwNDeXHsl7LEydOcK5vvvlG1dPItlu/evWKKlWqxLl0t1tv3bqVn9vDw0PYbl1UVETt2rUjQNtr2atXL2G79Z07d3jfq2z+wrhx41Q9jWy7dWZmJtnb2xMg9lqye+/OnTv19jQSEXXs2JFz6fZa3r9/n/e9Mq5jx45xru+//17oaVRut87KyiJHR0eeCdh2a8a1d+9eVU+jcrt1165deSbo0aOH0Gv56NEjVSZQbrf+4YcfDGYV1veqzCpsu/X+/ftVPY3KrNK9e3eDWUU3EyizytSpU1VZhWWCnJwcqlatmpBVlNutlTM6dOcvEBH5+PgIWUWZCSIjIwUu3e3WbEaHvqzCZnQoMwHjOnbsmMGswmZ0yHotlTM6ZFll1qxZqqyizASs71U2f0E5o0M5f4Fx9enTR8gqS5cuFbIKm9EhyyrKGR0sq7BMkJ+fT87OzpxLd/7C2bNnDWYVNqODZRVla9izZ8+kWYVlgoULF6qyCtturZzRIZu/8E8tlG7N/e+pLl264OXLl4IzkxWbFpidnS04rgDtZD57e3tYWFjg6dOnqmPLly8PMzMzGBkZCV4lVpUrV4aJiQmeP3+OrKwsYc3CwgJly5aFpaWl4B0sCZeRkREcHBz0ctnY2MDc3BzGxsaCA7IkXObm5rC2toaVlRUiIyNVxzJXVE5OjuAJZVyOjo4wNzd/Iy4nJyeYmpoiOTlZ8NkxrnLlysHCwkJ6vZhvMzc31yBXREQEdH8mGVeZMmUQFxcn5TIxMcGLFy9UXGy6saWlpd7rZWJigry8PMFVBmgnzTk5OcHc3ByRkZEqxVC5cuVgbm4OExMTg1wpKSnIyMj4Q1yVKlWCqakp8vPz8fz5c71cUVFRgtcL0LrSLCwsYGpqKrg8S8JlamqKChUqwMLC4o25zMzMEBMTI7g+AfCfp+KuV2pqquAlVHJZWloKvk1Wtra2MDU1RWFhoeB2Y1yVK1eGqamplMva2hrm5uYwMzOTXi9HR0eYmJggLS1N8BIC2omBFStWfCMuQPuzzn5dpYMU0F4vCwuLN+aytbWFhYWFQa6ioiIkJib+IS4rKytYWlrC3NwcMTExernS09ORlpYmrJUpU4ZPL5b9HVSxYkWYmZkZ5DI1NUV8fDzy8vL+MFeZMmWQkZEheBxLymVqagoiMsj17NkzwdkKaCd4sk90dLTqWDapVx8Xm4Qp46pQoQJ/s6H0HP+ZXJmZmUhNTRXWSnLvZbsKDHElJCQILtk/wpWVlfWXZYKkpCTBJQtoM4GVlRWsrKz+cCYwNjaGg4NDsffevzKr/BWZoCRZ5W25DGWC4rgMZZU3yQTFcf2VmaAkWcXMzAxRUVF/elYpX758sZlAH1fLli3h4+OD3r17o0GDBtJJxf+rVeoR/S+qUo9oaZVWaZVWaZVWaZVWaZXW/165u7tj9OjR+Ne//iVVnf0vVkm/iJZuZP4blJ+fH0JCQrBy5Urh3zdo0ACtWrVC+fLlcfLkSYSFhfE1MzMzdO7cGdWqVUPFihUxd+5c4diqVauiS5cuKFu2LJ4+fYrjx4/zNY1Gg1atWsHDwwP29vZYvny58CS6fPny6NGjBywtLWFkZIS1a9cK53Zzc8M777yD8uXL4+zZswgODha4OnXqhGrVqqFSpUqYM2eOcGyVKlU4V1RUFI4ePSpwtWzZEp6enrC3t8fKlSuFJ4U2Njbo0aMHypYtC2NjY6xevVo4t6urK1q3bo3y5cvj/PnzCAwM5Gumpqbo1KkTatSogUqVKmH27NnCsZUrV0bXrl1hZWWF2NhYHD58WOBq0aIFGjZsCDs7O6xatUp48lWuXDl0794d5cqVk3LVr18fbdq0gY2NDS5evCi8+TY1NUXHjh1Rs2ZN2NnZYfbs2cJTRicnJ3h7e8PKygrx8fE4ePCgwNW8eXM0atQIdnZ2WLt2rfC2Qsllamqq+vNVr149tG3bFjY2Nrh06RJu3rzJ10xMTNCxY0fUqlUL9vb2mD17tvCwxNHRkXMlJCTgwIEDwrmbN2+Oxo0bw87ODuvWrRPeClhbW6Nbt278bcaKFSuEY11cXNCuXTuUK1cOV69exfXr1wWu9u3bo3bt2nBwcMCcOXOEN6IODg7o1q0brKys8Pz5c+zbt084d7NmzdCkSRPY2tpi8+bNwtPRsmXLolu3bqhYsSLMzc2xfPly4VhnZ2e0b98e1tbWuHbtGgICAvRyzZ07V3jzaG9vz7lSUlKwZ88e4dxeXl5o0qQJKlWqhK1btwpvtMqWLQtvb2/+hm/ZsmXCsXXr1kX79u1Rrlw53LhxA1evXuVrZcqUQbt27eDs7My5lG/4GJelpSXS0tKwa9cu4dxNmzZF06ZNYWtrix07dghP9q2srODt7c19m0uWLBGOrVOnDjp06ABra2sEBgbi0qVLAlfbtm3h4uICBwcHzJs3T3jDZ2dnh+7du8PS0hLp6enYuXOncO4mTZrAy8sLtra22LVrl/DW09LSEt7e3rC3t0fZsmWxePFi4djatWujY8eOKFu2LEJCQnDx4kW+ZmxsjLZt26JevXpwcHDA/PnzhTdplSpV4lyZmZnYvn27cO5GjRqhWbNmsLW1xd69e/HkyROBq2vXrnBwcIC1tTUWLVokHFurVi3OFRYWhgsXLghcbdq0Qf369eHg4ICFCxcKb6xsbW3Ro0cPWFhYIDs7G9u2bRPO3bBhQzRv3hwVK1bEgQMH8PDhQ75mYWGBrl278r7QhQsXCsfWqFEDnTp1grW1Ne7cuYNz584JXK1bt4arqyscHR2xcOFC4c2Qra0tv165ubnYsmWLcG5PT0+0aNECFStWxMGDB/HgwQOBq0uXLnByckL58uWxYMEC4djq1aujc+fOKFu2LO7fv48zZ87wNR8ywGoAACAASURBVCMjI7Ru3Rpubm5wcHDA4sWLhTcdFStW5NeroKAAmzZtEs7t4eGBli1bokKFCjh69Cju3r3L18zNzdGlSxdUrlwZFSpUwPz584Vjq1Wrxu9xjx49wsmTJwWud955B+7u7nBwcMCvv/4q7H6oUKEC5yIibNiwQTg3ywQVKlTA8ePHER4eLnB17twZVatWLTYTPHnyBCdOnBC4WrVqhQYNGsDe3h7Lli0T3uYrM4FGo8G6deuEc7u7u/NMcOrUKYSGhvI1llWqVq0KW1tbg1wRERE4duwYX9PNKitWrBDeTiszgUajkWaV1q1bw8bG5o2yCssEhrKKnZ0d/Pz8VFmle/fusLa2fqOs0rFjR9SoUYPfe5WZQJlV4uLicOjQIYGrRYsWnGvNmjXCzh2WCWxsbFCmTBn4+fkJXMqs4u/vD+WLI1NTU3To0AE1a9aUcimzyrNnz4RMwLJKw4YNYW9vr8oq1tbW6N69O8qXLw8TE5M/nFU6dOiA2rVrw87ODnPmzNGbVRITE7F//37h3M2aNeNZZcOGDcIbeWVWkWUCllWsra0REBCAa9euCVzt27dH79694ePjg9q1a6O09FRJ9u/+WZ/SHlH95ePjI+39IyLuCZX5DIle9yDI3EWsB0G5z185vpx5QmX76Ym0PQiy3j+i1z0Isv30RK89obq9f0TEexCUvX/K/fSsB0HW+0ek9YSy3j/d8eXMEyrr/SN63YPAev+UY9WZJ1TmMyR67QmV9f4RaXsQlJ5F5fhy5gmV9f4RvfaE6vb+ERHvQbCysuI+QyUX84TKev+ItJ5QY2NjVe8fEXFPKPMZKnv/iLQaHih6/5RczBMq6/0jeu0JlfX+EWk9ocyzqKtaYZ5Q5jPUHavOPKG6vX+My9PTU/AZKseqM0+orPePSOsJNTY25j5DpWqFeUJlvX9Erz2hur1/RMQ9ocreP6VqhXlCZZ5FIqKvvvqKexZ1VSvMEyrr/SN67Qn19PRUqVaKiorIy8uL+wx1VSvME6rs/VMqTYYPHy7t/SPS9ktWqFCBKlSoQAMHDhQ8i0SvPaG6PkPG1bJlS2nvH9FrTyjzLOqqVkaPHi3t/SMi7gmV9f4RvfaENmjQQNX7xzyhMvcy0WtPqMy9TKT1hMp6/4iIe0Jl7mWi155QWe8fkdYTKuv9IyK6e/cuaTQa7lnUVa2MHz9e2vtHRNwTyjyLuqqVXbt26e39I9J6QmXuZSLinlCZz5CIaOLEidI5BUTEPaEynyHRa0+orPePSOsJlc0pICLuCZX5DIm0nlBZ7x8R8RkKyjkFSqUJ84TKev+ItJ5QExMT8vb2VqlWmCdU5l4meu0J1e39IyLuCZX1/hG99oSy3j9dLVzv3r31ZhXmCdWXVZgnVLf3j4j4DAWZe5notSdUX1b54IMPpL1/RFrth6Gswjyhuu5lIjGryHr/mCdUX1bp16+f1L1M9HqGgr6swjyhunMKiIh7QvVlFeYJZVlFNxN8/PHHUvcyEXFPqL6swjyhuu5lxuXq6iq4l5VczBOqL6t8+umnUvcyEXFPqDKrKDMBc5o3btxYpVphnlB9WYV5QllWUbqXiYgGDRoknVNApJ2hoMwqSvfyP7lQ6hH976mMjAy9nkUiops3b0rdRUTaQLRv3z697qKIiAjVD5SyTp8+LfUZEmmDhz6nEpF2mIfMs8jqt99+k/oMibQ3LJlnkdWZM2ekPkMibfDYu3ev1GdIRHT79m2pZ5HV/v379XJFR0fTyZMnVd5AVufOnZP6DIm0wWPPnj1SnyGRNswzmbmsDhw4IPUZEmkb/GWeRSWXzGdIpA0ehriCg4OlPkNWBw8e5AM2dCsuLk7qWWR14cIFqc+QSBs89uzZI/UsEhGFhIRIfYasDh06JPUsEmm/9Ms8i6wuXrwo9RkSaYPHnj17pD5DIu1QFpnPkNXhw4elnkUi7Q1eOWBDt/z9/YWQ/Ue4wsPDpT5DVkeOHJF6Fom0N3iZZ5HVpUuXpJ5FIm3w2L17t9SzSKQdFiPzGbI6evSo1GdIpH0YoRywoVuXL1+WehaJtMFj9+7dUp8hkdbFKHMvszp27JjUvUykfRihz2dIpB0MpU9mXlhYSHv27JH6DIm0Q2xknkUll8yzSKR9GKHPZ0hE9Pvvv0s9i0Tae8mePXv0Dth48OCB1LPI6sSJE1KfIZH2YYQ+nyGR9sGQzLNYEq5Hjx5JPYtKLpnPkEj7MEKfz5CI6Nq1a1KfIePau3ev1LNIpP0SK/Mssjp16pTUZ0ikdZDqPhBU1o0bNwxy7du3T+pZJNJ+iZV5FpVcMvcyUcmyir5MUFRURL/99luxWcVQJtCXVbKysgxmglu3br1xJiguq5w9e9ZgVtHnhCbSZhWZe1nJpS8TxMTEFJsJ3jSrBAUFSd3LrIrLKoYywfnz54vNKvoywdtklfj4eIOZ4G2ySmhoqMGs8k+tP+2LKIANAJIAhCv+3TQAcQCC//3pWZJfrPSLqLySkpL0/nAQab8cyX44iLQ3LH3BlEj7RUHfD0dRUZHeH9r/Dy59AbCoqEjvFwwibTjVF0yL48rIyNAbmP+TXJmZmXoDM5H2L9E35UpOTtYbmIvjysrK0huYGZe+AFgc14sXLwxyxcTE/CVcRFQsl77AzI7Vx5WdnW1wUt6zZ8/emCslJcUgV0xMjN5Ak5OTozcwMy59wbQkXPoCc3Fcubm5egPz23KlpqYafCptiCsvL8+gmDwhIUFvMC2O6+XLl3qDaXFc+fn5b82l789ucVyxsbF6uQoKCvQG+bflSktL0xuYGZe+e1xBQYHewEyk3Q2iLzD/lVyFhYUG771vw5Wenq43ML8t138yqxR3731Trr9zJviruJKTk/+yrPK2XP+NWcUQ1z+5SvpFtFiP6PTp01P//WX0g2nTpq3897/rAOASEX0+bdq0VdOmTXtUkm3ApR5ReaWkpMDZ2Rm///47MjMzVe7C5cuX44svvsDTp09VjkCNRoOmTZti3759ePHihcqf9Pvvv6NVq1YIDw/nXic2zU+j0eDLL7/E3LlzERsbq/InvXz5EnXr1sXVq1eRkZGh8if5+fnhs88+w5MnT1RORSMjI3h5eWHPnj1ITk7mvil27uvXr6NFixZ6ub7++mvMmjVLypWWlgZnZ2dcuXIFGRkZquu1Zs0afPLJJ3jy5InKXWhsbIwWLVpg586dSE5OVrkeb9++jWbNmiEsLEzloNRoNBg+fDimT5+OmJgYlbswIyMDdevWxaVLl/Dq1Ss4OTkJTsUNGzagf//+ePTokYqL9Q5t374dz58/V3EFBwejadOmCA0N5VzMEajRaDB69GhMnTpVypWZmQlnZ2f4+/vj1atXKtfjli1b0LdvXykX65nbunUrnj9/rnI9hoWFoXHjxggNDeUOSiXX2LFjMXnyZMTExMDCwkJwBGZlZcHZ2RkXLlxAenq6yl24bds2fPjhh3j48KHKqch6Hzdv3oykpCQV171799CwYUOEhISouABg/PjxmDRpEqKjo1VcOTk5cHFxwfnz55Genq5yPe7evRvvvfeelMvY2BidOnXChg0bkJSUBBsbG8Gp+ODBA3h4eCA4OBg5OTkqp+KkSZMwYcIEREdHq1yPeXl5qFevHs6ePYuXL1+q3IV79+7Fu+++y/vsdLm8vb15b46uu/Dx48dwd3dHYGAgd3YquaZMmYJx48YhKipKxVVQUIB69erh9OnTUq4DBw6gV69euH//vorLyMgIPXv2xOrVq5GYmIhy5coJXJGRkXB1dcXt27el1+vnn3/GN998g6ioKO4IVHK5urri5MmTSE1NVbkLDx8+jO7du+P+/fsgIsERaGRkhN69e2PlypVISEhQuQujo6Ph6uqKW7duITs7W+VUnDFjBkaPHo3IyEiV67GoqAhubm44fvy4lOv48ePo2rUr7t27ByLR/2xkZIT3338fK1asQEJCgsoRGBcXh3r16uHmzZvIzs5WORXnzJmDESNGIDIyUuUIJCK4u7vj6NGjSE1NVTkVT58+jU6dOuHevXsq16ORkRH69u2LpUuXIj4+XuVUTEhIgIuLC27cuIGsrCzV9VqwYAGGDh2KiIgImJiYCI5AIoKHhwcOHz6MlJQUFde5c+fQoUMH3L17F0VFRYK70MjICAMGDMCiRYs4l/J6JSYmwsXFBdevX0dWVpbK/7xo0SJ89dVXiIiIkPqfGzZsiIMHDyIlJUXlevT390fbtm1x9+5dletRo9Fg4MCBWLhwIeLj41VOxeTkZDg7O+PatWvIzMxUORWXLl2KwYMH48mTJyqnokajQePGjbF//368ePFCxXXlyhW0adMGd+7cUfmyNRoNBg0ahHnz5iEuLk7FVVxWWbFiBQYNGsS5lFnFyMgITZs2xd69e6VZJSAggGeV/Px81b13yJAhmD17NuLi4qRZxdnZmWcVXa5Vq1bh008/xePHj6VZpXnz5ti9e7c0q9y8eRPNmzdHWFgYd1AquYYOHYoZM2bwrKL0P6enp6Nu3bo8q+jee9etW4cBAwZwLt3rpcwquv7n27dvw8vLC6GhodLrNWLECEybNg2xsbEGswq79yq5Nm7cqDerGBsbC1lF994bEhLCM4Esq4wZM0ZvVmGZwN/fX5oJtm7dajCrtGvXDlu2bMHz589V/ufw8HA0atQIISEhUq5x48bpzSrZ2dlwdnbWmwl27NiBDz74QJoJ/sn1p3pEAdSE+o3o+JIcq/yUvhGV16NHj7gjkn1YX+WlS5fo1q1b3HkIQOihCAoK4v0g7MN6KE6ePEl37tzhfiNAdCreuHGD98+wj7KHIjg4mPr166fimjZtGvn7+9Pt27fJ0tJS4GI9FEFBQbwfhH3q1q1L3377LZ04cYLu3LlD7u7uAhfrobh+/TodOHBAOFbZQxESEkIff/yxsM76Kv39/SkoKIjKli3L15Q9FEFBQbx3lX1YD8WJEyfo7t275OnpKXCxHorr168LvjHgtetx3759FBwcTAMHDhTWWV/lxYsXKSgoiLsYGRfroQgMDBT8Wfh3D8WYMWP49WrcuDFfU/ZQXLt2TfCNAaJTMTg4mD7//HNhnfVVXrx4kUJCQsjGxoavKXsoAgMDBX8W/t1DMXr0aDp+/DjduXOHvLy8BC7WQ3Ht2jXBjark2rNnDwUHB9OXX34prDds2JB+/PFHunDhAoWGhlKFChX4Guv3XLNmDQUGBgquT/y733PUqFGci7kYGRfr9wwICOB9Peyj7KsMDg7m7kr2YU7FCxcuUFhYGNna2gpcrN/z9u3bgusT/+73HDlyJB07dozu3LnDXYyA6Hr8/fff6ezZs9x5yLhYX2VwcDANHTpUOLeHhwdNnjyZzp8/T2FhYWRnZ8fXWL/nqlWr6Pbt24LrE//u9xwxYgQdPXqUwsPDqW3btgJXmzZtaN68eXT16lU6f/68wKXsqwwJCeHuSvZh/Z7nz5+n8PBwcnBwELhYX+WtW7d4Ty37MKfikSNHKDw8nLsYGRfr97x69Sr5+/tzFyPw2qm4Y8cOCg4OptGjRwvnZq7Hs2fPUnh4ODk5OfE1ZV/lrVu3aO3atcKxrN+TcXXu3JmvsX7POXPm0JUrV+jy5cvcxci4mFMxJCSExo4dK5yb9XuyLfbMxci4WF/lzZs3eU8t+zDX4+HDhyksLIx7oxlXq1ataPbs2XTlyhW6evUqdx4Cov85ODiYxo8fL5yb9XueOXOG7ty5Q9WrV+dryr7KW7du8Z5a9mH9nocOHaLQ0FDq2bOnwMX6Ki9fvkwBAQHczwxA6PcMDg6miRMnCueuX78+jR8/nk6fPk137tzhfmbGxZyKN2/epG3btgnHsn5PxtW7d29hnfVVXr58ma5du8ZdjIyLuR6DgoJo8uTJwrHM/3zq1Cm6e/cudzECov/55s2bgoMUAO/3PHjwIIWEhHBHJPuwvspLly7RjRs3uPMQEF2PwcHB3KnJPiwTnDp1iu7cuUMuLi4CF5sBcePGDdqzZ4+Ka8iQIXTgwAEKCQnhjkj2KWlWCQ4O5v5vJdfYsWN5VnF1deVryqxy/fp1wZcOqDMB81mzD+ur9Pf3p8DAQGlWYZlA6f8GXmcCxtWgQQOBS5lVWK8v+yj7KkNCQrjPmn2UWSUwMFCaVdavX09BQUG8d5V9WF8lywQNGzYUuFhWuXbtGu/1VXKxvsqQkBD69NNPhXVlVgkODuZ+ZkCdCVjvKvuwvkrG1aRJE76mzCoBAQF8Lgn76GaVQYMGCeu6WYX5mZVca9eupcDAQD5ng33YDAiWCZo1ayZwMf9zQECA4EYFRP9zSEgIDR48WFhnWeX8+fMUGhrK/cyA3P/8Tyz8mR5RjUZTE8BRImrw73+eBuALAOkAbgH4johS9RzOq1TfIq9SfUtplVZplVZplVZplVZpldb/Vnl5eaF3795477330LBhw/80zv9blVTfYvSG5/cDUAdAIwDPACzS9x9qNJqvNRrNLY1Gc0tXAF9axVdx8tu38RG9zbH/SS5Dv3ZxXGwbx5vU/yJXcfU2XGxby5uuG6r/Ra7ifh9Lr9cf+3Xf5u+gvyvX2xz7d71epfe4P1alXH+sSrPKH/u1/65cxdXf9R5nY2ODOnXqoE6dOqhateobn+d/ud7o6hJRIhEVElERgLUAmhv4b9cQkRcRednZ2b0p5/90FRQU4KOPPuL/bGNjg48//hjbtm3D8+fPER8fL/S3ubq64vvvv8fly5eRk5MjeN9MTU3RvXt3+Pr6IiIiAvn5+ahfvz5fr1y5Mr7++mscOXIEaWlpOH/+PF9jbqzZs2cjNDQUhYWF+OSTT/h6uXLl8NFHH2Hr1q1ISkpCQkKC0K9Vv359TJgwAZcuXUJ2drbg7zM1NUW3bt2wYsUKPH36FAUFBXB3d+frTk5O+Oqrr3D48GGkpaUJzkHmxpo1axZCQkJQUFCAzz77TODq168ftmzZgsTERCQlJQn9NPXq1cP48ePh7++PrKwswcNoYmICb29vLFu2jHN5enrydUdHR/zrX//CoUOH8PLlS/z+++/C713z5s0xc+ZMBAUFoaCgAF9++SVfs7a2Rt++fbF582YkJiYiOTlZ6FtxcXHBd999h4sXLyIzM1NwZ5mYmKBr165YunQpHj9+jMLCQjRu3JivOzg4YMiQITh48CBevnwpuDYBrRtrxowZCAwMREFBAb766iu+VrZsWfTp0webNm1CYmIiUlJShH4HZ2dnjBs3DhcuXEBmZqbgQCtTpgw6d+6MJUuW4NGjRygsLISX1+sHXg4ODhg8eDAOHDiAly9fCs5UQPtkcNq0abh9+zby8/MxbNgwgevDDz/Exo0bkZCQgNTUVKHXsG7duhg7dizOnTuHzMxMrF+/XsX166+/cq4WLVrwdXt7e3z55ZfYv38/Xr58iaCgIIGradOm+Pnnn3Hr1i3k5+dj1KhRfM3KygoffPABd4ylpaUJPVd16tTBt99+i7NnzyIjI0NwEpYpUwYdO3bE4sWL8fDhQxQWFqJ169Z83c7ODl988QV+++03pKSkIDQ0VLgZN2nSBD/99BNu3ryJvLw8fPPNN3zN0tIS77//PtavX4/4+Hi8evUKyr9ja9eujW+++QZnzpxBRkaG4JY0NjZGhw4dsGjRIjx48ABFRUVo164dX69UqRIGDRqEvXv3IiUlBXfv3hW4GjdujKlTp+LGjRvIy8vDd999J3C99957WLduHeLj45GRkQEHBwe+XrNmTYwePRqnT59GRkaG4Ag1NjZG+/bt8csvv+D+/fsoKipCp06d+LqtrS0+//xz7NmzBykpKbh//74QEho2bIgff/wR169fR25uLr7//nu+ZmFhgXfffRdr165FbGws7wnU5Tp16hRevXqFvXv3Clzt2rXDwoULeY9k165dBa7PPvsMu3fvxosXL/Do0SMhdHl6emLKlCm4du0acnNzMXnyZIGrd+/eWLNmDWJjY3nPKavq1atj5MiROHnyJDIyMgQ/n5GREdq2bYsFCxbwXsQePXrw9YoVK+LTTz/Frl27kJyczHv3WHl4eGDy5MkICAhAbm4ufvrpJ75mbm4OHx8frF69GjExMcjJyUH16tX5erVq1TBixAicOHEC6enpgnvZyMgIbdq0wfz58xEeHo7CwkL07t2br1eoUAEDBw7Ezp078eLFC96zyqpBgwb44Ycf8PvvvyMnJwfTp08XuHr16gU/Pz9ER0cjNzcXtWrVEriGDx+O48eP49WrV4JDm/lF582bh7CwMBQWFuL999/n6+XLl8eAAQOwY8cOJCcnIzo6mvfBAlpf5qRJk3D16lXk5OQIPmozMzP07NkTfn5+iIqKQl5eHurUqcPXq1atimHDhuHYsWNIT0/HqVOn+JpGo8E777yDuXPncq6+ffvydZYJWF9eXFwc7+sEtL7MiRMn4sqVK8jJycG8efMErh49esDX1xeRkZHIz8+Hi4sLX69SpQqGDh2Ko0ePIj09XfDEMo/nnDlzeCbo37+/wNW/f3+eVZ49e6Y3q2RnZ+OXX37ha8pMwLKKq6srX9fNKkrfrzKrhISEoLCwEAMHDuTrulklMTFRmlX8/f2RnZ0tOJBNTU3h7e2N5cuX80zQoEEDvq6bVS5fvixwtWjRAjNnzkRwcDAKCgrw+eef83Vra2shqzx//lyaVS5evIisrCzBW8kywbJly/DkyZNis4rScw1os8qMGTN4Vhk8eLDAVZKswjKB0j9qYmKCLl26CFmlSZMmfF03q9y4cUPg8vLywvTp03lWUc6RKS6rsExw/vx5ZGZmYs2a1+2IsqzSvPnrryr29vYYPHgwzwS6WaVp06ZCVhk+fLjApcwqL1++FPrWWSY4d+4cnj9/jl27dmHgwIFCbigtRZVk/y7UPaJOiv89FsCukpyntEdUXuHh4eTi4iJ1UBFpHWqsV0J3PH5GRgZ5eHhIHVRERDt37pT6Mln5+PjwXgndaZ/37t0jFxcXqS+TiGjy5MlSXyaRdoKZp6en1EFFRLR3717eK3Hr1i3VNMb3339f6qAiInr48CG5uLhIHVRERFOnTuW9Errj8bOzs6lRo0ZSXyaRVjkj82Wy6tOnD73//vsqBxUR0ZMnT8jFxUXqyyQimjZtmtSXSaSdatqkSROpL5NIqyqR+TJZ9evXT+rLJNJ6aF1cXGj06NHS8fizZs2S+jKJtFNNmzZtKvVlEmnVG6xXQjYef8CAAVJfJpF20pyLi4vUl0mkdbvJfJlE2qmmzZo1k/oyiYhOnjwp9WWyGjhwoNSXSaSdKuni4kIjR46UqnwWLFgg9WUSaaeatmjRQurLJNKO+md9nbLx+IMGDZL6Mom0U/9cXFykvkwiosWLF0t9mUTa6aGtWrWS+jKJtKPrZb5MVoMHD+Z9nbpTNRMTE6levXpSXyaR1u0m82UyrtatW/O+Tl2uy5cv6/VlEmm9qjJfJpF2wmf9+vWlvkwiohUrVkh9mUTa6aHt2rWT+jKJtHoWfb5MIqJhw4bxvk5dlU9ycjLVr19f6ssk0npoZb5MIu10xw4dOvC+Tt2pmtevX9fryyQiGjlypNSXSaSdMuzq6ir1ZRIRrV27VurLZFydOnWS+jKJtJoK1tcpU/mMGTNG6ssk0k7zdXNzk/oyibQeWtbXqavyKSoqoq5du0p9mURaTQXr65SpfMaOHSv1ZRJpp9O6u7tLfZlEWg+tzJfJuLp16yb1ZRJpPbT16tWT+jKJiCZMmCD1ZRJpp9M2aNBA6ssk0npoZW5vxtWrVy+pL5OIeH+pvqwyadIkqdubSDtt1VBW2bVrl9SXyerdd9+V+jKJtMojllVkmWDKlClSXyaRNqs0bNhQb1bZt2+f1JfJylBWefTokcGs8tNPP0l9mUTqrKKbCfbv3y/1ZbLq27ev1JdJJGYVmd5v+vTpUl8mkTYTGMoqhw8f5plAllU++uijEmUVWSaYPXu2wazi5eWlN6scP35c6vZm9cknnxSbVVgm0OWaN28en/WgT+XzTyz8WT2iGo1mJ4AOACoBSATw87//uRG0jbmRAIYS0bPivvSW9ojKKycnB2ZmZnq3JeTk5PBpaLqVm5sLExMTvVsHsrOzhSeUyiIi5OXlCU9W/wiXoXPn5eXB2NhY71YMQ/+fiAi5ubl619/mehXHVdz1ehuut7lepVxi5efnQ6PR6N2OY+jY4tb/Si5DfzbflsvQuQsKCgDo375U3PUydO63uV4FBQUgIr0TBv/K38firtfbcP1V16uwsBBFRUV/yfV6m3tJYWEhCgsLhbeHynqbP/fFcRk6d3Fc/6nrVVRUhPz8fIP33v/E9SoJ19vce8uUKfPGWeWfdo8r5fpj587Pz4eRkdHfLnP+k+tP6xElogFE5EREJkRUlYjWE9FnRORBRJ5E9G5JvoSWlv46fPgwjh8/juzsbNVadnY2VqxYgbCwMMgeGty4cQM7d+5ESkqK9NwbN27ElStXeBBVVmRkJNatW4fo6GjpsUePHsWxY8ekXDk5OVixYgVCQ0OlXDdv3uTbrmS1adMmXL58WcoVHR2NdevWISoqSnrs8ePHcfToUWRlZanWcnNzsWLFCoSEhEi5bt++jR07dujl2rJlC/z9/aVcsbGxWLt2LSIjI6XHnjhxAkeOHEFmZqZqLS8vD76+vggODpZyBQYGYvv27UhOTpaee+vWrbh48aKUKz4+HmvWrEFERIT02FOnTuHw4cNSrvz8fPj6+iIoKEjKFRISwrddyWrbtm24cOEC8vPzVWsJCQlYvXo1nj59Kj329OnTOHjwIDIyMlRrBQUFWLlyJQIDAw1yJSUlSc+9Y8cOnD9/XsqVlJSE1atX48mTJ9Jjz549iwMHDki5CgsLsXLlSty+fVvKFRYWxreDyWrnzp04d+6clCs5ORmrVq3C48ePpceeP38e+/fvx6tXr/Ry3bp1UzVXSAAAIABJREFUSzr4LDw8HJs3b0ZCQoL03Lt378bZs2eRl5enWnvx4gX8/Pzw6JHc0nXhwgX89ttvUq6ioiKsWrUKN2/elHLdvXvXINfevXtx5swZKVdqair8/Py4rka3/P39sW/fPqSnp+vlunHjhpTr/v372LRpE549k9/a9u3bh9OnTyM3N1e1lpaWhpUrV+rlunz5Mvbu3Yu0tDTVGhFhzZo1uH79upTrwYMH2LhxI+Lj46Xn3r9/P06dOiXlSk9Ph6+vL9fC6NaVK1eK5QoICEBhYaFq/dGjR9i4cSPi4uL0cp08eRI5OTmqtYyMDPj6+uLu3btSrqtXr2LPnj14+fKllGvt2rV6uZ48eYINGzYgNjZWynXo0CGcOHFCypWZmQlfX1/cuXNHyhUQEIDdu3cjNVU9p5GIsG7dOly9elXK9fTpU2zYsAExMTF6uY4fPy7lysrKgq+vL8LDw6Vc169fx65du6RcALB+/XpcuXJFyhUZGYn169frzQRHjhz5S7OKvkwQFRVlkOvo0aMGM4Gvr+8bZ5XNmzfj0qVLUq6YmJhis8qRI0ekXCwTGMoqhjKBoawSFxdnMKucPHmy2EygL6sEBQUZ5Nq2bRsuXrwovcc9e/as2Kxy6NAhKRfLBPqySnBwMNfM6ePSl1USExOxatUqvZngzJkzBrOKr6+v3qxSWiWokrw2/bM+pVtz5XXt2jU+8pnpKZRbFoYMGcJHUetuY0xJSaFy5coJegrl1oBVq1YRIOop2JaFoqIiPmab6SmUWxZu3boljKJevXq1sGWBqSSYnkK5ZSE1NZXKly8v6CmU2xjXrVvHudg2RiVX8+bNCXitpwgICODb3wIDAwnQaiBk2xiZSoLpKU6cOMG3MaalpVHFihUFPYVyG+PGjRsJEPUUbHtlUVERV28wPYVyG2NoaCjnkm1jHDNmDAGv9RTK7ZWvXr0iW1tbrqfQ3ca4detWAkQ9BdvGWFRUxNUbTE+h3MYYHh5OGo1G0FMotzGOGzeOgNd6CuX2yoyMDLK3txf0FMptjDt27OBcTE+h3F7J1Btse6VyG+O9e/fIyMhI0FMotzFOmDCBgNd6iiNHjnCurKwscnR0FPQUym2MTEGg1FMot1d26dLl/9g7z7CorvXt3/QmCCId7Kiggg27qIAUmbHGaEw3iUnUJCYmxh4TTUxMrDEmYIm9g2IvKIqigiLSB1AsgIgNLHRhvR/mv3b2mrVm8OjxjTnhua75cM46a3ufDcy+997P/fwIoMZTaLYx5uTkEAMDAwZPIW9jnDZtGgH+wlPI2xjLy8uJs7Mzg6eQtzFGRkYSgMVTyNsrg4ODCQBhG+OVK1ckXRRPIdc1c+ZMArB4CqqroqKCuLm5EQDCNsaoqChJF8VTyNsYQ0NDCQBhG+O1a9eIoaEhg6eQt1dSZIMcT0HbGCsrK0nTpk0J8BeeIikpSdJFsURyPIW8jXHIkCESBkKzjfHGjRvEyMiIwVPI2xjnzZsn6aJ4CqqrqqqKtGjRgkCGp5C3MVIsEcVT/Pnnn4wuirigeAp5G2N+fj4xMTFh8BTyNsb58+dzeAraxlhdXU3c3d0ZPIU8chEdHc3hKeTtlRRxQfEU8shFYWEhMTU1ZfAU8jZGinGS4ymoridPnpA2bdoweAp5G2NMTAyHp5C3MY4ZM4bBU8jbGIuKioiZmRmDp5C3MVKMkxxPQdsra2pqiKenJ4OnkOuKjY3l8BTyNsY333yTwVPIIxd37twhFhYWDJ5C3sa4bNkyDk9B2xhrampIhw4dGDyFvI3xzJkzki5RGyPFXlE8hTxycffuXWJpacngKeRtjCtWrODwFFRXbW0t6dixI4OnkHuC+Ph4nXiKDz74QKtXKS4uJg0bNmQ8gdyrhIWF6fQqXbp0YbyKPHKRmJgo6aKRC7lX+eijjyRPMGHCBHLw4EFJV0lJieRVRJGL1atX6/QqFBPWoUMHMm3aNCZykZSUpNOrTJw4kfEqck/w8OFDyauIIhdr167lvIrcE/Tu3VvyKpqRi9TUVJ1e5bPPPmO8yv79+yVdjx8/Jo0bN5Y8gaZXobgkbV7F19eX8QRyr5KRkaHTq0yePJnxBPLIRWlpqeRVRJELikuSexW5J/Dz85M8gWbkQqVS6fQqU6ZMYTyB3Kv8mwv/TXzLf6vqW3PFNXXqVISHh3NPMLt27YrOnTvj+vXrzGADQB2WDgwMhJmZGS5cuMA9fW/VqhUGDBiA+/fvIyIiglkzNDREv3790LRpU2RmZnKhdnt7e4SGhkoDAjSfYHbp0gVdunRBXl4eDh48KNRlbm6O8+fPc7patmwJPz8/3L9/H5GRkcwTJENDQ/j6+qJZs2ZQqVTcYCA7OzuEhobi0aNHOHHiBPcEs3PnzujatatQl4WFBQYOHAhLS0tcuHABmZmZzHqLFi3g7++P4uJiREZGMm8jDAwM0LdvX7Rs2RJZWVk4ffo0p2vQoEEoLS3FyZMnuSdynTp1go+PD/Lz85nBGYB6sMvAgQNhZWWFxMREZGRkMOvNmzdHQEAA7t+/j927dzNPsevS1bhxYwwaNAjl5eWIjY1FUVERs96xY0d069YNBQUF2L9/P6crICAA1tbWSExMRHp6OrPerFkzDBw4EMXFxdi1axenq3fv3nB3d0dOTg4zeApQD3YZNGgQKisrERsby70N8/b2Rvfu3XHz5k3s27ePWTMzM0NAQABsbGyQlJSE1NRUZr1p06YIDAzE/fv3ERUVxTwtpoNK2rRpg+zsbE5Xo0aNMGjQIFRVVeH06dPcWycvLy90794dt27dwt69ezld/v7+sLW1RVJSElJSUpj1Jk2aIDAwEMXFxdi7dy/zhk9fXx+9evVC27ZtcfnyZWYoB9UVEhKCJ0+e4PTp09xbp/bt26NXr14oLCzkdJmamsLf3x92dnZISkpCcnIys+7m5obg4GDcv38f+/btY96k6evro2fPnvDw8MCVK1cQExPD7LWxsUFISAhqa2sRFxfHvd1p164devfujaKiIkRFRXG6/Pz8YG9vj+TkZG54lKurK4KCglBSUoL9+/czb4boAJV27drhypUrzMA1QD1wJiQkBIQQnDlzhnuL4unpiT59+uD27dvYvXs3s2ZiYgI/Pz84OjoiJSWFG2Dh4uKC4OBgFBcX4+DBg8ybITpApV27drh69Soz9AVQD3ahg4TOnTvHva3w8PBA3759hbqMjY0lXampqZwuZ2dnhISEoLi4GIcPH2beKNABKh06dMDVq1cRHR3N7LWyskJwcDAMDAxw7tw57m1F27Zt4evrizt37jCDkqiuAQMGwNnZGWlpaTh//jyz7uTkhEGDBqG4uFgaTiXX1a1bN3h7eyM3N1eoKygoCEZGRjh37hzXWdGmTRv069dPq67+/fvDxcUF6enp3IAUua7o6GjurTnVdf36dRw5coRZs7S0RFBQEExMTBAfH891MLRu3Rr9+/fHvXv3uGuvkZER+vfvD1dXV2RkZHBD5hwdHREaGor79+8jJiaGewvs4+ODjh074saNG5wnsLS0RGBgIExNTZGQkMB1MLi7u0u6IiMjOV2+vr5o2rQpMjIycO7cOWbdwcEBoaGhKCkpEXqCrl27olOnTsjLy8OhQ4eYtbo8QV1ehXoCXV7l4cOHiImJEXqVzp07Iz8/X+gJAgMD0aBBA5w/fx4qlYpZb9myJfz9/aXzpelV+vbtixYtWiAzM1OnVzl58iT39rBTp07o2rUrCgoKOE/wtF7l/v372LVr13/kVRo3bozQ0FCUlZXh5MmTXOeOLl1yr3Lx4kXOEzRv3hz+/v4oKSkReoI+ffqgVatWOr1KWVkZTp8+rdUT1OVVLl68iLS0NGa9WbNmCAgIQHFxMecJqFdp3bq10BNQr1JRUYHTp09zHTJeXl7o0aOH8NpLvYpSqURoaCicnZ3xb6unbc2tvxF9CaqeI1pf9VVf9VVf9VVf9VVf9fW/V6+++ioWLlz4r0K4PO2NqMGcOXP+P8hRV3h4+Bz5aOb6UldBQQFyc3O5PEjLli0REBCAhg0bchkX+lbT09MT1dXV3JNT+kTOwcFBmBPo3LkzevbsCUNDQ+6pmLm5OUJDQ+Ho6IgHDx5wulq0aKFVF8VCeHp64smTJ5wu+uTLwcFBmKvo1KkTevbsCRMTE+4Nnrm5OQYNGgRnZ2ehrubNm2PgwIGwtrbm3s5Q/EL79u1RU1PDvX22tbWFQqGAg4MDbty4wfX6e3t7o3fv3jAxMeGe1pmZmUm6Hj58yOVn6NtDGxsboa6+ffuiffv2qK2tFeqiP0dtuvr06QNTU1OhrpCQELi6uuLRo0dcToW+pWvUqBH31ojiF7y8vITnq1GjRpKuvLw8TleHDh3Qt29foS5TU1MEBwfDzc0Njx8/FuoKCgqCjY2NUFfv3r3h7e0NQgj3BNzGxkb6Oebn53MPeNq3b4++ffvCzMyMe7ppamqKoKAgNG3aFI8fP+ZyKm5ubggKCtJ6vnr16oWOHTsCAPe23traWjpfN2/e5PJZ7dq1g6+vL8zNzTldJiYmkq7S0lJOF3172LhxY+5vimIhKPpHpEuhUMDe3h6FhYWcLk9PT/Tr1094vkxMTBAYGIjmzZujrKyMy8/Qt4fadPXs2ROdO3eGnp4e98agYcOGkq6ioiIuB+Xh4YH+/fvDwsKCe3NtbGyMgQMHokWLFigvL+eyq87OzggODoadnZ1QV48ePdClSxfo6+tzuqysrKSfo0hX27Zt0b9/fzRo0IB7c21sbIyAgAC0atVKqMvJyQkhISFadXXv3h1du3aFgYEB13VhaWkpna87d+5wOag2bdrAz89PqMvIyAj+/v5wd3dHZWUl93bQ0dERISEhsLe3F15LunXrBh8fH+jr6+vUdffuXU5X69at4efnB0tLS6EuPz8/tG7dWqjLwcEBgwYN0qrLx8cH3bp1E17jGjRoAIVCATs7O9y/f5/LILu7u8Pf31+oiyKZ2rRpg6qqKi5Ta29vr1NX165dn0pXcXExl/Vt1aoV/P39YWVlJfQE/fv3h4eHh05dujxBjx49YGxszF17LSwspO/VkpISThd9S/civAr1BCJddXmVujxBv3790K5dO61eheoSeZWOHTuiV69eWnXp8irUE/xdXsXFxUXoVWhHkcirUFRUhw4dnskTeHl5vXCvUltbq9MT6PIq2jwB9Sqia29dnqB3796YMGECli5dio8//phBz/wb6ttvvy2cM2dOeJ3/w6fp3/1vfeozouK6dOkSASBlJzQzCjRHYGNjw2EhHj58SGxtbZk8pTyjsG7dOq0ZBXmOwM3NjctTpqamEj09Pa15ykmTJmnNU9IcAbTkKTdt2kQAEBMTE2FGoV+/flJuUTNPSXME2jIKX375pdaMQmlpKXFwcJDylJoZha1bt0q6RBkFf39/KaOgiYXIysoi+vr6WjMKX3/9tZRb1MwolJWVEScnJyk7oZlR2LlzJwFAjI2NhRmFwMBAKaNA85Q0H0gzj3p6ekIsxIwZM7g8Jc0tVlRUEBcXF615yl27dkm6RHnKQYMGac1T5ubmEkNDQ615ytmzZ3N5SppbrKysJE2aNNGap9y7dy8BQIyMjKQ8pTy3qFQqmdyiHAtx/fp1YmRkpDVP+d1330m5xZEjRzJYiKqqKtKsWTMCgLRu3ZrLUx48eFDSJcJCDBs2jAAgDg4OHBYiLy+PGBsba81Tfv/990yeUo6FqK6uJi1bttSapzxy5IikS5SnfOWVVyRdmliImzdvElNTU615yp9++onLU9LcYnV1NWndujUBQFq1asXlKY8fP04AaM1Tjh49WmuesrCwkJiZmTF5SjkWYuHChVJukeYpaW7xyZMnxMPDQ2ue8sSJE5IuPz8/DgvxxhtvcHlKmlu8ffs2MTc315qnXLJkiaRLEwtRU1ND2rdvrzVPefr0aQKAGBgYkAEDBnBYiLffflvKLWrmKe/evUsaNGjA5CnlWIjly5drzVPW1NQQb29vJk8px0KcPXtW0iVCWNE5CKI85b1794iVlZXWPOXvv/8u5QM185TyOQiiPOX58+clXSIsxLhx47g8Jc0H0jkI0JKnXLlyJZenpLnF2tpa4uPjQwD1jIWJEycyMxboHARtecrx48drzVM+ePCA2NjYSHlKTYQVnYNgamrKIaxqa2tJz549uTwlvfYmJydLukR5SjoHQeRV6BwEuSeQe5X169dzXoV6gtraWtKnTx/Gq8g9AZ2DoC1P+fnnnzNeRe4JHj9+TOzs7CRPoJmnpHMQtHmV/v37S15Fc8ZCZmamTq9C5yBQr6LpCRwdHbXmKbdt28Z5FbknoHMQRHnK7OxsnV5l6tSpjFeRz1igcxCoJ9D0KhEREZxXkXuCoKAgLk9JPQGdg6DNq9A5CKIZCxUVFcTV1VXyBJpeZffu3ZxXkXsCOgeBzliQe5WrV69yXkXuCb755htJl2jGwr+18JQZ0fob0Zeg1q9fzw0toVVWVkZmzpwpZK8RojZqmiZbXgsWLBAy4QhR3wiI2Gu0Nm7cqPUPqry8nMycOVPIXiNEbdRE7DVav/zyi5AJR4h6+ImmyZbXpk2bhEw4QtRfRrNmzRKy1whRcwk1Tba8Fi5cyAwtkdeNGzeE7DVaW7ZsEbLXCFHfOM2aNUvIXiNEbSBFnFhaixcvFrLXCCGkoKBAKyeWEPUFS5uuqqoqMnv2bCEnlhC1gRRxYmktWbJEyF4jRH0jQDmxIl07duwQstcIUd+gfPPNN0L2GiHqoRkiJhytZcuWCTmxhKiHn2iaf3lFREQI2WuEqG9Q5syZI+TEEqI2tppDS+S1fPlyIXuNEPXwE03zL69du3YJ2WtyXSImHCHqYR4i9hqtFStWMENL5HX37l0ye/ZsIROOEPWgIxF7jRD1Dcp3330nZMIRoh7moYu99scffwg5sYSoB7XNmjVLyIklRP0wQnNoiVzX3LlzhUw4QtSGW8SJpRUWFibkxBKiHn5CdWnyRQlRD2AScWIJURvuefPmMeZfXqmpqUJOLK2VK1cyDwTl9eDBAzJz5kwhJ5YQ9UMSESeW6vr++++ZoSXyysjIEHJiaa1evVrIiSVEfYMya9YsISeWEEIOHz4s5MRSXT/88IOQX0uIesiIiBNL688//+SGltB6/PgxmTlzppATSwghR48eFXJiqa758+drHVqSnZ0t5MTSWrdunZBfS4j6YerMmTOFnFhCCDl27JiQE0vrp59+0uoJLl++LOTE0lq/fj1Zv3690KuUl5eTWbNmafUqMTExOr3Kzz//zAxYk9fTeJW6PIE2r3Ly5Mk6vYqIE0uI+qGlLq+yefNmISeWkL88gS6vIuLE0lq0aJGQE0uI+qGlLq+ydevWOj2BNq8SFxen06ssWbLkmb3K9u3bhUx7Qv7yBLq8ii5PsHTp0jq9ijZPsHPnzmf2Kv/metob0fqM6EtQhBCtfCJday9yb72ul+fY9brqddXrenmOTa+ZL9v/53pd/xu6XuSx63XV66rX9f/32P/mqs+I/oNq3LhxOHr0KAwMDODm5sZA569du4YRI0bg9u3bsLW1ha2tLfNLv2jRIvz+++948uQJXF1dGahuZWUlBg8ejIyMDFhYWMDZ2ZnZe/jwYXz++ed4/PgxnJycYGlpyej6+OOPcfDgQaGuGzduYPjw4SgqKkKjRo3QuHFj5thLly7F8uXLUVVVxemqqqrCkCFDkJ6eDnNzczg7OzOQ6+joaHz22Wd49OgRHB0dYWVlxeiaMGEC9u/fD319fU5Xfn4+hg0bhlu3bgl1LV++HMuWLZN0yeHI1dXVGDJkCFJTU4W6YmJiMHHiRK26Pv30U+zdu1eoq7CwEEOGDEFhYSFsbGxgZ2fH6FqxYgWWLFmCyspKTteTJ08wbNgwJCcnw8zMDC4uLoyu2NhYjB8/Hg8fPoSjoyOXQ5g0aRKioqKgp6cHNzc3GBkZSWtFRUUYPHgwbt68KdQVFhaGX375RairpqYGw4cPR1JSklBXXFwcPvzwQzx48ECoa/LkyYiMjBTqunPnDpRKJQoKCtCwYUPY29szulatWoWff/4ZFRUVcHFxgbm5ubRWW1uLV155BYmJiTA1NeV0nTt3Dh988AFKSkrg4OAAa2trRteUKVOwc+dOAOB03bt3D0qlEvn5+WjYsCEcHBwYXX/++Sfmz5+PiooKuLq6crpGjhyJCxcuCHWdP38e7777rlZd06ZNw7Zt24S67t+/D6VSiby8PFhZWXG61q9fj++//154vgghePXVV5GQkABjY2O4uroyui5evIh33nkHxcXFsLe3h42NDaNr5syZ2LJlCwghcHNzg7GxsbRWUlICpVKJa9euwcrKCo6OjoyuTZs24bvvvkN5eTlcXFxgYWHBHPu1117D2bNnJV1yWHlycjLeeOMNrbpmz56NTZs2gRACV1dXRteDBw8kXZaWlpyurVu3Ys6cOSgvL4ezszOn6/XXX0dcXByMjIw4XampqXj99ddx//592NnZoVGjRszeb7/9FuvXr0dNTQ13vh49egSFQoHc3FxYWlrCycmJ0bV9+3bMnj0bZWVlwvP15ptvIjY2VqgrIyMDr732mlZdc+fOxdq1a1FbWwtXV1eYmJhIa6WlpVAoFLh8+bLwfEVGRmLGjBkoKyuDk5MTGjRowBz77bffxsmTJ2FoaMjpysrKwqhRo3Dv3j00btwYtra2zN4ffvgBa9aska5xcl1lZWVQKBTIyclBgwYNuPMVFRWFqVOnorS0FM7OzpyusWPH4vjx4zA0NISbmxuj6/Llyxg5ciTu3r0r1PXTTz9h5cqVePLkCdzc3Bhd5eXlUCqVyMrKEurat28fpkyZgtLSUuG19/3330d0dLR0vuTXktzcXLzyyiu4c+cOGjVqxHmCX375BWFhYaiuruauvRUVFRg8eDBUKpXQExw8eBCTJ0/Go0ePhLo+/PBDHD58+Jm8yuLFi/Hbb7+huroabm5unCeQexUnJyfmO0juVUTX3vHjx0teRfN85eXlYdiwYSgqKoKNjY3Qq/z666/C80U9QVpamtATHDt2DJ9++ql07dXUNXHiRK1epaCgAEOHDsWtW7eE197ly5dj6dKlQq/y5MkTDB06tE6vos0TfPbZZ9izZw/09fXh6urKXEvkXsXa2prT9fvvv2PRokVCXTU1NZJXEV3jTp06hY8++ggPHz6Eg4MDp+vzzz/H7t27dXqVgoICWFtbc54gPDz8qbyKSNeZM2cwbtw4rV7lyy+/lLyK5vmiXiU/P1+o699c9RnRf1CdOnWKAJByVMOHD2faJt566y1pvVWrVkxe6c6dO1KuR85/o20Tv/76q7SX5qgo/62mpoZ4eXlJ6zSvRFspaa4H+Iv/Js9RjR07VlrXzCvdu3ePWFpaSroo/422TVCWGfBXjoq2UtbW1pJOnTpJ65r8t4SEBEYXzVHRVkrKMqO65Pw3yjIDIOS/hYeHS3s180q1tbWka9eu0jrNK9FWSprrAf7KUa1cuVLS9fHHH0vrzZs3l/JKlZWVpKSkRMr1UP6bPEe1Zs0aaa8m/622tpb06NFDWqd5JdpKSTPIgJhV+8knn0jrzTT4b/IMsohVSzPIAJ9Xkud6AJ5VSzPIVJcm/41mkAGeVSvPIItYtTSDTHVp8t9oBhngWbU0gwz8laOSt1LSDDLAs2rlGWRRtppmkAFxtppmkAE+W00zyFSXZl6JZpABnlVbXl4uZZBFrFqaQQbE2WqaQQZ4Vu3ly5eJgYEBl1eirZQ0gwzwOSp5BllPwKqluR6qS5NVSzPIAJ+tphlkqkszW00zyACfo5JnkPUEeSWaQQbErFqaQQb+ylHRVkp5BlmUraYZZIDPVsszyHqCbDXNIAPiHBXNIAN8tlqeQRaxan/44QdpryarVp5BBvhsNc0gU12aOaqRI0dK65qsWnkGWcSqpRlkgGfVPnnyRMogA3y2mmaQAXG2mmaQAT5bLc8gy7PVtMWTZpABNltNddEMMsBnq2kGmXqCESNGMLpoBpl6Anm2Wp5BFmWraQZZ7gloK6U8gwzwrFqaQZZ7FXkrJc0gA3y2Wp5BFrFqaQZZ7gnkXoVmkDW9Sk1NjcRil3sVeSslzSBr8yo0gyxi1VIWO9Ulz1bLM8hyr0I9Ac0gyz2BPPZBWezUE2h6FZpBFmWraQZZm1ehGeSn8Sqa2WqaQaaeQJ6tlmeQRaxamkHW5lVoBlnuVagnoBlk6gk0WbU0gyzyKvIMsihbTTPI2rwKZbHLvQqNfdAMsjavQjPI1BPIvcq/uVCfEf3nFDWumh89PT3SqlUrYmJiIlxv2LAhcXR0lEyg5qd58+bSBVzzY2xsTJo3by4ZIs2Ps7MzsbCweCZdVlZWxMnJSauuZs2aPbMuJycn6WIm+tSly9nZ+Zl0GRkZkRYtWmjV5ejoKN14/6e6LC0tX5guBwcHYmVlJX2J/ie6GjRoQFxcXLTqatq0qVZdhoaGpGXLlpKx1fzY29uThg0bPpMuCwuLF6bLzs6OWFtbP7MuV1dX6eZH89OkSZPn0mVjYyPdiGp+WrZsqVWXubk5cXNzeyZdBgYGOnU1btyYNGrUSOv5eh5dbm5uz6zL1taW2NraPpMuMzMz0qRJk2fSpa+vr1NXo0aNJBi8aL1FixZaj21mZkaaNm2qVZerq+tz6bKzs9P5+6Xt2Kamps+lq1WrVlp12djYEHt7e626WrRoofXnaGpqSpo1a6b1u9HFxUWrLnqN06bL2tq6Tl3ajm1iYvLCdDVs2JA4ODg8kycwMTGp0xPQG29tunR5FV2e4GX1KnXp0nXtfR6v8iI9Qb1XYT+GhoakRYsWL8yr0Bc4otzr/3qhPiP6zyldHFE9PT3o+hkZGhpyCIH/5N/VxDU8bf2dunT92/W6/jm69PX1n5mfW6/r5dH1PN8jz6OrrvN9drYhAAAgAElEQVRRr6te14vU9b947X2evfVe5T/7t+t18aXrb+5l1VVXWVtbIyQkBIMHD8Yrr7zCtGf/r9fTZkT16/of1NeLr8jISOY/W1tb47XXXsPmzZuRk5ODt99+m1lv164dpk6diri4OFy4cIHJRpmYmCAkJAQrVqxAdnY2fvrpJ2avi4sLPvroI+zfvx+ZmZno3r27tKanp2YO/vDDD0hNTcWePXuYvQ0bNsTo0aOxadMmZGdn491332XWPT098fXXX+PUqVO4ePEik6kxNjZGcHAwfvvtN2RlZeGXX37hdH344YfYt28fMjMz0atXL0ZXjx498P333yMlJQX79u1jevAbNmyIUaNGYePGjcjJycH777/PHNvDwwNTpkxBbGwsLl68CDs7O0ZXUFAQli9fDpVKhUWLFjF7nZ2dMW7cOOzduxcqlQp9+/bldM2bNw/Jyck4ePAgo8vKygqvvvoqNmzYgJycHHz44YfMsdu2bYsvv/wSJ0+exKVLl+Dg4MDoCgwMxK+//gqVSoVly5Yxe52cnPDBBx9gz549UKlU6NevH7PerVs3zJ07F5cuXcKRI0eYPISlpSVGjhyJ9evXIzs7G+PHj2f2tm7dGpMnT8aJEyeQnJwMJycnac3IyAgDBw7EsmXLkJmZid9++43Z6+joiPfffx+7d++GSqWCn58fs+7j44PvvvsOSUlJUi5aruuVV17BunXrkJOTg08++YTZ6+7uji+++AIxMTFITk5mwNBGRkYICAjA0qVLkZmZid9//53Z6+DggLFjx2LXrl1QqVQIDAxk1rt27Ypvv/0WFy9elDJjtBo0aIARI0Zg7dq1yMnJwaRJk5i9rVq1wueff47jx48jJSUFTZo0kdYMDQ3h7++PJUuWIDMzEytXrmT22tvbY+zYsYiMjIRKpUJwcDCz3qVLF8yZMweJiYk4ceIEk02xsLDA8OHDsWbNGuTk5GDy5MnM3pYtW2LSpEk4duwY0tLS0Lx5c0aXn58fFi9ejIyMDKxevZrZa2dnh3feeQcRERFQqVQIDQ1l1jt37oxvvvkGFy5cwMmTJ5mco4WFBYYOHYrVq1cjJycHX331FbO3RYsW+OyzzxAdHY3U1FS0atVKWjMwMMCAAQOwaNEiZGRkYO3atczexo0b4+2338bOnTuRnZ2NwYMHM+udOnXC7Nmzcf78eZw6dYrJe5mbm2Po0KFYtWoVcnJyMG3aNGZv8+bN8emnn+Lo0aNIS0tD69atGV39+/fHL7/8goyMDGzYsIHT9dZbb2HHjh3IysrCsGHDmPWOHTti1qxZSEhIQFxcHJNfMjMzw+DBg7Fy5UpkZ2djxowZzN5mzZrhk08+wZEjR5CWlgYPDw9GV79+/SRdmzdvZvba2trizTffxPbt25GVlYURI0Yw697e3pg5cybOnTuHc+fOMZlTMzMzKJVKhIeHIzs7G7Nnz2b2Nm3aFBMnTsThw4eRnp6O9u3bS2v6+vrw9fXFggULkJ6ejq1btzJ7GzVqhDfeeAPbtm1DdnY2Ro0axax7eXlhxowZOHv2LOLj45lsp6mpKRQKBcLCwpCdnY1vv/2W2dukSRNMmDABhw4dQlpaGry9vRldffr0wU8//YT09HRs376d2WtjY4PXX38dW7duRVZWFsaMGcOsd+jQAdOnT8eZM2cQHx/PZAJNTU0RGhqKP/74Azk5OZg3bx6z183NDePHj8eBAweQkZGBzp07M7p69+6NH3/8Eenp6YiIiOB0jRkzBlu2bEFOTg7eeOMNZr19+/aSJzh//jyTcTMxMcGgQYPw+++/Izs7G/Pnz2f2urq64uOPP5Z0+fj4SGvUE8yfPx9paWnYvXs3s1fTq7zzzjvMert27fD111/j9OnTSExMZHLJml5lwYIFzF7qVagn6NGjB6OrZ8+eklfZu3cvs1fuVXJycjB27FhmnXoC6lUaN24srWl6lYULFzJ75Z6gLq+yf/9+rV4lOzsbH3zwAXPstm3b4quvvkJsbCySkpJgb2/P6JJ7lSVLljB7NT2Br68vo6t79+6SVzl06BDjCahXoZ7go48+Yo7dpk0bxqs4OjpKa0ZGRjq9CvUEUVFRyMzMRP/+/Zn1p/Eq1BNMmDCB2Sv3KikpKXB2dmZ0Ua+iUqmwYsUKZq+DgwPee+89yav4+/sz63KvEh0dzXgVTU/w6aefMnvlXuX27dvYvHkzRo8e/a+6Cf2P6mlem/63PvWtueL68MMPhWw/QtQoAHt7eyHbjxBCVq1aJWQOEqIeId+9e3ch248QNTrB0tKSy5/QmjBhgpDtR4gaBeDg4CBk+xFCyNq1a4m9vT3HHKS6evfuzeVPaKWkpBBLS0suK0vr008/FbL9CFGjAJycnLisLK0NGzYI2X5Ul6+vL5eVpZWenk4sLS25rCytL774Qsj2I0SNAnBxceGysrS2bNkiZPvRGjBgAJeVpZWZmUksLS3J0KFDhdiRKVOmcPkTWmVlZcTNzY3LytLavn27kO1Ha+DAgVz+hFZOTg6xsrKSsrKa2JFp06Yx+RO5rvLyctK0aVMuK0srMjKSy5/IKzg4mMvK0rpy5QqxsrLi2H60Zs2aJbH9NLEjFRUVpHnz5sTX11eIHYmKihKy/WgpFAouK0vr2rVrxMrKisuf0JozZ47W/EllZSVp2bIll5WltX//fiHbj9aQIUO4rCytGzdukIYNG3IcYlrz5s0TcogJUaMA3N3dhWw/QtRoDlFWltaIESOEHGJCCMnPzyfW1tZCth8hhPz4449CDjEh6pH7bdu25bKytKKjo4VZWVqjRo3isrK0CgsLiY2NjZBDTIgaU0E5xJrYkSdPnhBPT08h248QNQJDxCGmNWbMGCHbjxA1tsjGxkbIISZEjYiiHGI5c5AQNe6mQ4cOQrYfIYTExsYKs7K03nrrLSGHmBA1tsjW1lbIISZEjWISsf2oro4dOwo5xIQQcubMGWFWlta7775L2rRpw3GICVHzSxs3bizkEBOinnOgTRfNDoo4xIQQkpCQoJM5+MEHHwg5xISo+aV2dnZCDjEharSQLk/QrVs3IYeYEDXmSZcn+Oijj3R6FQcHB61eZfXq1UIOMdXVo0cPrV7l0qVLki6RJ5g4caJWr/Lw4UPi6Oio1ausW7dOyCGmuvr06aPVq6SmpjKeQFPXpEmTtHqVx48fE2dnZy4rS2vjxo1avQohan6pZlaWVkZGhuQJRNiRyZMna/UqpaWlklfR5BAToka/6PIqfn5+Qg4xIWqckqWlJZeVpfX1118/lVcReYIdO3YQW1tbrV4lMDCwTq+imZWlNX36dCGHmBC1J2jatKmQQ/xvL9RnRP85pY1fRYj6Yihi+9G6du2akHtEiPoPRMTQo1VQUKAzTK2N90V1idh+tK5fv/7Mum7evFmnLhGDihA1W1DE0JPrEjHhCFGbeRHbT65LxNB7Gl3FxcXPrKuqqkrI9qNVWFj4XLpEbL+n0VVdXS1k+8l1iRh6T6OrpKREyNB7Gl1PnjwRsv1o3bp165l1PXjwQKeuGzduCFl1T6tLxNB7Wl0itt/T6KqpqdHKHCREfQPzrLoePnyoE+ydl5enVVdtbW2dukRsv6fR9ejRozp1iVh1T6Pr9u3bOnVdu3ZNq67Hjx/rzBLVpUvXd/bt27eFbL+n0VVaWqpTV35+/jPrunPnjpDtJ9el7VpSWloqZPvJdWlj+9XW1uq89t69e/eZdZWVlQk5xLQKCgp0Mgd1na+7d+8+sycoLy8Xcojlup7HE+jS9Tye4Gl0afvdfR6vUllZWadXedZr7/N4laqqqpfSq9ChZ9rqebxKSUnJP9Kr/JvraW9E698TvwRV1+t6eauCZhkYGOgcFS1vJxAd91n36unp6dSla62udT09vTp1aVt/Gl0v6v9zXT+LF6nrWf/dp9n7Is+Xrr11/e7qquc5X7r21vVv/53n6+/6/Xqen+PzHvtZzxfwfD/H5/2b0lX/q9/Zz6Pr7/i+p/tfxLH/rvNV17H19fVf6HeQrnre3/vn+R3RVXX93j+rJ3jen2Nde59H14v0BC/r3+OL8ir1VXfVc0RfgpoyZQqmTJmCGzducIyjyspKtG7dGtHR0Xjw4AHHF9y+fTsGDx6MrKwsACxf0MDAAAEBAVi1ahWKioo4xlFOTg7at2+PpKQkVFZWcnzB6dOnY/Lkybh+/Tqnq7q6Gm3atMHRo0fx4MED2NvbM7oiIiKgUCigUqmEuoKDgxEeHo6ioiKOx5ibmwtPT09cvHhR4gvKdc2aNQuTJk3C9evXYWJiwnAPq6ur4eHhgcOHDwt5jFFRUQgJCYFKpQIhLPdQX18foaGh+P3333Hr1i1O17Vr1+Dh4YHExEQh9/Dbb7/FJ598gmvXrsHExAQuLi7SF1RNTQ08PDxw8OBBlJSUwM7Ojsn27tu3D4GBgcjMzOR0GRgYYMiQIVi+fDlu3brFcfzy8/PRtm1bnD9/Xqhr3rx5mDBhAq5du8bxGAkh8PT0xP79+4V8wUOHDsHf3x+ZmZmora3lztfw4cOxbNkyFBYWcpzIwsJCtG7dGgkJCULu4Y8//oiPPvoIV69eFepq37499u7dK9R19OhRDBgwABkZGUJdo0aNwuLFi1FYWIgGDRowum7duoXWrVsjPj4eZWVlHF/w559/xrhx43D16lUhj9HLywu7d+/G/fv3Ob5gTEwM+vXrh/T0dIkTSfmC+vr6eO2117Bw4ULcvHmT4wveuXMH7u7uOHfunJB7uHjxYrz33nvIzc3ldOnp6aFjx47YtWuXkMd46tQp9OnTR9Il5zHq6enhzTffxIIFC1BQUMDpunfvHtzd3XH27Fkh9/DXX3/FO++8g9zcXI7jp6enh06dOmHnzp24d+8ebG1tmTzWmTNn0KtXL6SlpXE8Rj09Pbz77rv44YcfUFBQwHEPS0pK0KpVK8TFxeHx48dwdnZmdK1YsQJvvvkmrly5wnEP9fX10aVLF2zfvh13797luIfx8fHo3r27pEvOF9TT08MHH3yAefPmIT8/n9P14MEDuLu74/Tp00JGc3h4OMaMGYPLly9zugwMDNCtWzds3boVd+/e5VjIFy5cQLdu3ZCamspxD/X09PDxxx9jzpw5yM/P5/iCjx49gru7O2JjYyVOpDzjuHr1aowePRqXL1/muIf6+vro1asXNm3aJPEr5bqSkpLQpUsXpKSkcHxBPT09TJw4EbNnz0ZeXh6nq7S0FO7u7jh58qSQ0bxu3TqMHDkSOTk5nC4DAwP06dMHGzZswJ07dzgeY2pqKjp16oTk5GShrkmTJmHGjBnIy8vjWMjl5eVwd3dHTEyMkMe4ceNGDB8+HNnZ2Rz30NDQEL6+vli3bh1u377N6crIyIC3tzeSk5OF3MPJkydj6tSpuHHjBqeroqICrVu3xvHjx4Xcw61bt2LIkCFCXQYGBvDz88OaNWtw+/ZtzhNkZWXp9ARff/01vvrqq2fyKjt27JDYqgDvCQYOHCh5Fc1rL/UqFy9eFDKaZ8yYgS+++EKrV2nbti2OHDki9ASRkZEIDQ0VehV9fX2EhIQgLCxM6AmuXr0KT09PJCYmChnNs2fP1upVnjx5grZt2+LQoUMoKSnhWMh79uxBcHCwVq+iUCgkr6J57b1+/To8PDxw4cIFoSf47rvvJK+iee2tqamBp6cnDhw4IGQ079+/X6tX0dfXx9ChQ7F8+XKhJ9D0KpqM5u+//16nV2nXrh327duH4uJizhMcPnxYp1cZMWIEli5dips3b3KMZuoJtHmVn376SfIqRkZGDHOYepU9e/ZoZTT/W6ueI/oPqlWrVjEjn+UZs4yMDIb9BrDcw9jYWGZEOOUehoWFEZVKRaZOncrslXMPk5OTSYcOHaQ1yj386aefSEZGBsODAiBlzLZs2UIyMjLIK6+8wqzTLNeZM2fIqVOnmBHhpqamUsZMpVKR6dOnM3vl3MPk5GTSsWNHRpc8YybnQVFdY8aMIZs3byYZGRnk1VdfZdZplisuLo7ExcVJHFFAPbKeZsyysrLIrFmzmL1y7mFKSgrDDNP7P+4hzZjJ2ZUAyz3MzMwkr732GrPu6elJvv76a3L69Gly5swZic1FddGMWVZWFpkzZw6zV849TElJYZhhenp6TMZMzq4EWO5hZmYmw6QDwGTMzp49K7G5APXI+uDgYLJ8+XKSlZXFMA+Bv7iHe/fuJampqQzfVE/GY0xOTiY7duxgRqLLs1yZmZkMPxdQcw9pxiw+Pp7Y2dkxuoKCgsivv/5KVCoV+f7775m98ixXamoq6dWrF6OLZswuXbpEIiMjOV00y6VSqci7777LHFueMUtISGBwTHLuoUqlIvPnz+d0vf/++yQqKoqkpaUxLDNAzWOkWa6oqCgGF0G5h+vWrSMqlYph5QGQMmYxMTHkwoULEkeU6qJZLpVKRRYsWMDsdXR0lDJmaWlpDHcVUPMYaZZr3759zNh8OfdQpVKRcePGMXtpxuz48ePkwoULEkeU6qJZLpVKxbAYAZbHmJaWRvz8/Jj1rl27SlmuAwcOMEgROaNZpVIxXF/gLx7jsWPHSGJiosQRBVjuoUqlIosXL2b2yhnN6enpJCAggFnv0qWLlOU6fPgwgzCQj/jPysoiEyZMYPa2bNlSynJdvHhR4ohSXTR3rlKpyLJly5i9ckZzeno6CQoKYtblufMjR44wCAM5o1mlUjEMP4BlNCclJTEcUTmjWaVSMYxIAFLGbMeOHSQ9PZ3hwQIs9zA6OppBL8h5jFlZWQxvGGAZzZcuXWI4onJGs0qlIr///jun66233iLbt28nGRkZRKFQMOvy3Pnx48cZnImcx5iVlUUmT57M7G0m4x5eunSJtG3bltElZzTL2ZXAXzxG6gmGDBnCrMtz5ydPnpQ4osBfPEbqCb766itmr5zRnJycTNq1ayetaTKaRV6F5s6f1av88ccfJCsrS6dXuXTpEsM8l3uV9PR0snbtWmavPHeemZlZp1ehHFGqKzQ0VPIEcg4ywHqVlJQUrV4lLS2NbNiwgdkrz51nZmaSUaNGMevy3HlcXJzEEQVYT6BSqRgOMsB6leTkZNKlSxdpTe5VUlNTyebNmzldcq8yZswYZp16FeoJNL0KzZ2rVKo6vUq3bt0YXT179pRy59u2bWP2anqVN998k1mXM5rPnTvHeRWaO8/KyiJz585l9sq9SkpKCsM31dNgNO/cuVOnV5Hzc4G/vIpm7vzfVqjHt/xzShe+5UWOkH9ZR9vXtffvGj3+T9Wl62f1d/4cn2dUu5GREaqrq59J14scIf88uuo6X7p0/53n63nQCvW6/rN6kYiC5zn285yvF/kd9LLq+qdee19WXbq+/15WXfVeha+/C9/yInU1atQIISEhmDJlCry8vJ5J3z+19J4S31LfmvsS1PHjx3H9+nXuv/fy8oKvry9KSkrw6NEjZs3U1BTBwcFwcHBAUVER90fk5uYGpVKJ0tJSFBcXM2t0VHyHDh1w7949lJeXM+s2NjYYMWIEamtrcefOHU5X+/bt0a9fP626goKC4OjoiNu3b//Hunr16gVvb2/cvXtXqGv48OEghOD27ducrnbt2mHAgAF48OABHj58yKyZmJggKCgIzs7OuH37NmdOXF1doVQqUVZWxumiI+y9vb1x7949lJWVMevW1tYYNmwY9PT0UFRUxOny9PSEv78/SkpKhLoCAwPh6uoq1OXi4oIhQ4YIzxcdYd+pUyfcv3+f09WwYUMMGzYMBgYGuHXrFqfLw8MD/v7+wvNlbGyMgQMHwtXVFXfu3EFVVRWz7uzsjCFDhqCsrAz379/ndPXo0QOdO3cWni8rKysMGTIExsbGQl1t27bFwIED8fDhQzx48IDTFRAQADc3N6EuJycnDB06VKuu7t27o2vXrrh//z5KS0uZdUtLSwwZMgSmpqZCXW3atNGqi+JjmjZtitu3b3O6HB0dMXToUJSXl3O6APUIex8fH626Bg8eDDMzM9y6dYu76LVu3RqBgYF49OiRUJefnx9atGgh1OXg4IBhw4Zp1eXj44Nu3boJdTVo0ABKpRIWFhZCXe7u7ggODhaeL0NDQwwYMAAtW7bEnTt3UFlZyazb29tj+PDhqKiowL179zhdXbt2Rffu3bXqUigUsLS0RFFREWcgWrVqpVNX//794e7urlXXsGHDtOrq3LkzevbsieLiYjx+/JhZs7CwgEKhQMOGDYW6WrZsiZCQEDx69AglJSWcrn79+qFNmza4e/cuKioqmHU7OzsMHz4clZWVQl2dOnVCr169hLrMzc0RGhoKa2trFBUVcTerzZs3x6BBg4S6KD6mbdu2uHPnDqercePGOn+OHTt2RJ8+fbTqGjRoEBo1aoTbt29zupo1a4bQ0FA8fvxYqMvX1xceHh7C82Vra4sRI0ZoPV/e3t7o27ev8BpnZmaGQYMGwdbWVni+mjZtCoVCoVVX37594enpKbz2NmrUSKcuXZ7AzMwMISEhsLOzE157mzRpAoVCofXa26dPH7Rv316nJ3jy5Anu3r3L6erQoYNOTxAcHAx7e/sX4lV0eYL27dujf//+wmsc9SpOTk5CXa6urhg8ePAzeRXqCQBo9Sp+fn5avUpgYCBcXFy0ehVtuuryKnJP8J96Fbkn0OVVtF176/IqQ4cOhaGh4TN5lYCAADRp0uSl8yr+/v748MMP8dFHH6FNmzbc/v/1qm/N/QfVxo0buVYCOpWRIkUgayWQj4rPyMggenp6XCsBnfBF24NEI+xLS0uJvb291EqgOcKetnQaGRkJR9jTtjja9hgVFSXpUqlUUhuhaIT9lClTCKBuL9QcYV9WVia1EYpG2O/YsUPSJRphP3DgQAKo2wvff/99ZoR9Tk6O1EYoGmFPW4Zp26N8hH15ebnURigaYb9r1y5Jl2iEfUhICAEgHGF/5coVqY1QNMKetuHQtkf5CPvKykri5uZGAAhH2O/Zs4cA6jY+0Qh7pVJJAAhH2F+7dk1qIxSNsP/2228JoG7jGz58OIO1qaqqktoIRSPsDxw4IOkSjbAfOnQoASAcYX/jxg2pjVA0wp625srbC6mu6upqqY1QNML+8OHDBP/XLkfbHuUj7Gmbl2iEfUFBATExMSEAhCPsf/zxRwKw7YV0umZ1dbXURigaYX/s2DFJl2iEPW3zEuF2CgsLpTZC2vYox9r88ssvBP/Xxqc5wv7JkydSG6FohP2JEyckXaIR9q+//jqBrL1w+/bt0hTLoqIiqY2Qtj3KsTZLliyRdGnidmpqaqQ2QhFu59SpU1K7HG0vlON2aOu3CLdz584dqY3Qy8tLai+kun799VemvTAsLEyaYllTUyO1EVLcjhxrc/bsWa69UI7bGTt2rNReqInbuXfvnhR56NChg9ReSKdF0lZTeRSC6qqtrSWdOnWS2gvHjx/PYG0SEhK49kI5boe2WMvbHukUy+LiYiny0L59eykKQXWFh4dLbXyauJ3a2lopWiBvL6RTLC9evMi1F8pxO7TFmrY9yrE2Dx48kNoI5VEIqmvNmjVc2yOdrkmRItBoL6S6Ll26xLQXauJ2PvnkE6m9cPTo0QzW5uHDh1IboQi3s27dOskT0LZHuSfo06cP115Ir72pqamSJxDhdmgrM217lHuCx48fS5EHeRSCXntp/ETkVQghUgu/CGuTmZmp06t8+eWXjFeRe4LS0lIp8iDC7dCWTupVli1bxngVf39/xhNERUVJniArK4vzKnJPQFuG5VEIqqu8vFynV9m5cyfjVTQ9AW2VF+F2Ll++zHkVuSegLcPyKAT1KhUVFTq9yu7duxmvsmTJEkYXbZUXeZXc3FzOq8g9wTfffCPp0kTwVVZWSpEHkVfZu3cv41U0EXyDBw/W6lWuX7/OeRU5go/GiORRCLlXad68OeNV5J7g4MGDki4Rgo+2pOvC7fwbC/X4ln9O/fjjj1p/cXNzc4VMS1obNmwQMi0JUX9JTp8+neNE0Tpx4oSQaUlrwYIFQk4UIeo/ehHTktbGjRvJ6tWrhSPsKyoqyPTp0zlOFK3Y2Fgh05LWzz//LOREEaK+QRFxomht3rxZyIkiRP0lOWPGDI5pSev06dNCfhWthQsXCpmWhKhvUERMS1pbt24lK1euFI6Kr6qqIjNnzuSYlrTOnDkjZYtEvyOLFy8WMi0JUd+gaJp/eW3fvl3ItCREfeM0c+ZMjmlJKz4+njPZ8lq6dKmQaUmI+gZlxowZHNOS1s6dO4VMS0LUN06zZs3imJa0zp8/L2WLRLqWLVsmZFoSor5BmT59Ose0pBUZGSlkWlJds2fP5piWtBITE4VMS1rLly8XMi0JUSMddOnavXu3kGlJiPrG6ZtvvuGYlrSSkpKETEtaK1asEDItCVEjCqZPn84xLWnt2bNHyLQkRG2458yZQ/bu3SvUlZycLGRa0vrjjz+ETEtC1CP3p02bxjEtae3bt0/ItKS6vvvuO8b8yys1NVXItKQVHh4uZFoSor5xmjZtmtZs0YEDB4RMS6pr7ty5zANBeWVkZAiZlrRWrlwpZFoSosbdTJs2jWNa0jp06JCQaUl1zZs3j2Na0lKpVEKmJa3Vq1eTdevWcUxLQtQ3TtOmTeOYlrSOHj0qZFpSXd9//z3HtKSVnZ0tZFrS+vPPP8natWuFWJuysjIybdo0jmlJKzo6Wsi0pDV//nyOaUnrypUrQqYlrXXr1gmZloSoPcG0adM4piWtmJgYIdOSli6vcvXqVSHTktaGDRuETEtC/vIEdXkVTaYlrefxKps2bRIyLQn5yxNo8yqnTp3S6Ql++eUXrV4lPz+feyAory1btmj1KlVVVZJXEV174+LipBy0qBYtWsQ8EJTXzZs3dXqCrVu3CvnbhPzlCbR5lbNnzwr527R0eZVbt25JnkCka8eOHcwDQU1ds2bNIocOHRJee/8bXkX+QPkTEyYAACAASURBVLC+1PW0N6L1GdH6qq/6qq/6qq/6qq/6qq/6qq/6+q/U02ZEdQOU6uv/S0VFRQn7zwEgLy8P0dHRXN87rZiYGOTk5AjXKioqEBkZyfXU07p06RLOnz+vNYS9Z88erbry8/Nx9OhRrbpOnDiB7Oxs4VplZSUiIiK06kpOTkZCQoJWXXv37kVhYaFw7ebNmzhy5AiX7aJ18uRJaRy6ZlVVVSEiIoLr9aeVkpKC+Ph4rbr27duHmzdvCtcKCwtx+PBhrbpiY2O16qqurtapKy0tDefOndM6iGTfvn0oKCgQrhUVFeHQoUNchorWqVOnkJGRIdT15MkTREREcDkoWunp6Thz5oxWXfv370d+fr5w7fbt2zh48KBWXadPn0Z6erpQV01NDSIiIrj8DK3MzEydug4cOIC8vDzh2t27d3HgwAEuE0QrLi4OaWlpz6RLpVLh9OnTWnUdPHgQN27cEK7du3cP+/fv16rr7NmzSE1NFeqqra1FRESEMCMKqJEOp06d0jrM4dChQ8KMOwAUFxdj3759XPaG1rlz55CSkiLURQhBRESEMCsHqJEOsbGxWnUdPnxYq66SkhLs3btXq674+HgkJydr1RUZGalV1+XLl3Hy5Emtuo4cOYJr164J1x4+fIioqCgu90orISEBly5d0qlLlOsHgCtXruDEiRNah/ccPXoUV69eFa49fvwYu3fv1qrr/PnzSEpK0qpr165dWnVdvXoVMTExWnVFR0cjNzdXuFZaWopdu3Zx+VJaiYmJuHjxok5dogwfoMZ1HT9+XKuuY8eO4cqVK8K1srIynbouXryIxMRErUNOdu/eLczwAcCNGzdw7Ngxrdfe48ePa/UE5eXliIyM5HKctJKSknDhwgWt17jn9Sq6PMHzehVtnqCgoKBOr0KRMppVVVWlU1dycrJOT/CivEpdniA1NfWZvcqtW7fq9CoU3aJZ1BPo8ipnz57V6Ql0eRVdnuB5vEpGRkadnkCbV7lz545OXfVVd9UPK3oJKjIyEoMGDcLBgwc5hpaFhQWCg4MxZ84cJCUlcayqy5cvo1u3btiyZQvHqjI0NMTs2bPx3nvv4dSpUxxDq7a2Fh07dsSKFSuErKqoqCgEBwfjwIEDHEPL3NwcCoUCs2fPZniflL2Um5sLHx8fbN68meNqGhoa4rvvvsO7776L2NhYIVezU6dOWL58uZBVtW/fPgQFBWH//v0cQ8vc3BxDhgzBzJkzcfHiRY4Jdf36dfj4+GDTpk0cq8rAwAA//PAD3n77bcTGxnKsKj09PXTu3Bm//vqrkFV18OBBBAYGYt++fRxDy8LCAsOGDcOMGTOQmJjI6crLy0OXLl2wceNGjqtpYGCABQsW4M0338TJkyc5VhVlIi5dulTI1Txy5AgGDhwoXRTlXE1zc3OMHDkSU6dOxfnz5zmuZmFhITp37owNGzZwXE19fX0sXLgQb7zxBk6cOMHxKw0NDeHj44MlS5YIuZrHjx+Hv78/9uzZw3E1zc3NMWrUKEyZMgXnz5/nuJpFRUXo1KkT1q9fz3E19fX1sXTpUrz22muIiYnhdBkZGcHHxweLFy8WcjVPnDgBPz8/REVF4ebNm7CwsJB0mZmZ4Y033sBXX32FhIQEjqt57949dOzYEevWrUNubi4MDQ0lrqa+vj6WL1+O0aNH4/jx4xK/knI1jY2N0b17dyxcuFDI1Tx9+jQGDBiA3bt3c1xNMzMzvP322/jiiy8QHx/PcTWLi4vh7e2NtWvXclxNPT09/PHHHxg5ciSOHTvGcTVNTEzQs2dP/Pzzz0Ku5tmzZ9GvXz/s2rWL42qampri/fffx+eff45z585xXM2SkhJ4e3vjzz//xJUrVxhOpJ6eHlatWoVXXnkF0dHRHFfT1NQUvXv3xoIFC4RczYSEBPj6+iIyMpLjV5qamuLDDz/Ep59+inPnznFczcePH8PLywtr1qzhuJp6enpYs2YNhg8fjqNHj3JcTVNTU/Tt2xc//vgjUlJSUF1dDRcXF4kTmZiYiD59+mDnzp2cLhMTE0ycOBGffPIJzp49y3E1S0tL4eXlhdWrVyMnJ0fiRFJd69evx9ChQ3HkyBGOq2lubg5fX1/Mnz9fyPu8dOkSevfujR07dnBcTWNjY0yaNAnjx4/HmTNnOK5mRUUFvLy8sHLlSo5fqaenh02bNmHIkCE4fPgwx9U0NzfHgAEDMG/ePCFXMzU1Fb169cL27ds5rqaxsTG+/PJLfPzxx4iLi8PDhw/h4OAg6aqqqoKXlxfCwsKEurZt2walUolDhw5xXE1zc3P4+/tj7ty5uHTpEnftzcjIQM+ePbFt2zaOq2lkZISpU6di3LhxiIuL47ia1dXV8Pb2RlhYmJCruWPHDigUCskTaOoKDAzEt99+K3kCOVczKysLPXr0wNatWzmuppGREWbMmIEPPvgAp0+f5hjgtbW18Pb2xh9//CHkau7atatOr/LNN99IvE/5+bpy5YpOr/LNN99g7NixOHXqFMevJITo9CqUuUm9iua1NzQ0FLNnzxYywK9evarVqxgYGGDu3Ll45513cPLkSU4X5SRr8yr79+9nvIqcAW5ubo6hQ4dKnkCTq3njxg107dpVq1eZP38+3nrrLUmXpifo3Lkzli1bJvQqhw4dwsCBA6UbUjlX09zcHMOHD8e0adNw4cIFzqsUFBQwXkXO1dTX18fPP/8seQJNr2JgYMB5Ffm19+jRowgICMDevXslXfKf46uvvqrVq9y6dYvxKvTaS3UtWrQIY8aMQUxMDMcAp15l8eLFyMjI0OlVNFnb5ubmGD16tFav8m+upx1WVN+a+xLU6NGjsW3bNua/c3Nzg0KhQPPmzbF+/XqkpaVJa/r6+ujZsyeUSiUKCgoQFhbGPO2zsbFBSEgIevbsiR07diA2NpY5drt27aBUKmFsbIxVq1YxT8ZMTEzg7+8PhUKBo0ePYteuXcxeV1dXKBQKtGzZEhs2bEBKSoq0RiejKZVK3Lp1C2FhYcxTImtrawQHB6N3797YuXMnTp48yRzb09MTSqUSpqamWL16NfMEysTEBH5+flAqlTh27BgiIiKYvS4uLlAoFGjVqpVQV48ePaBUKnH79m2EhYUxb44aNmyI4OBg9O3bFzt27OB0eXh4QKlUwtzcHKtXr2belhkbG8PPzw8KhQKxsbHYvn07s9fZ2RkKhQJt2rTBhg0bcOnSJUZX9+7doVQqcffuXYSFhTFvaKysrBAcHAxfX19EREQgJiaGOXbbtm2hVCrRoEEDrFmzhnn7Y2xsjAEDBkChUCAuLg5bt25l9jo5OUGhUKBt27bYuHEjkpKSGF3dunWDUqnE/fv3ER4ezjzZt7KyQlBQEPr374+IiAgcP36cOXabNm2gVCphZWWFNWvWMG9/jIyM0L9/fyiVSsTHx2PTpk2crtDQUHh6emLjxo24ePEis96tWzcoFAo8ePAA4eHhzJN9S0tLBAUFYcCAAYiMjMSxY8eYva1bt4ZSqYS1tTXWrFnDvP0xMjJCv379oFQqceHCBWzYsIHZ6+joiNDQULRr1w6bN2+G5veYj4+PNCkzLCyMeYJuaWmJwMBA+Pn5YdeuXYiOjmb2uru7Q6lUwsbGRrpRlOvy9fWFUqlEUlIS1q1bx+x1cHBAaGgoOnTogE2bNnG6unTpIk2DDg8PZ54IN2jQAIGBgQgICEBkZCSnq1WrVlAqlbC1tcXatWtx+fJlac3Q0FDSlZqaijVr1jB77e3tERoaCi8vL2zZsgUJCQmcLoVCgYqKCoSHhzNviS0sLBAYGIjAwEDs2rULR44cYfa2bNkSCoUCDg4O+PPPP5m3P4aGhujbty+USiXS09OxZs0a5gm5nZ0dQkND4e3tja1btyI+Pp45dqdOnaBUKlFVVYWVK1cybz0tLCwwcOBABAUFYffu3Th8+DCzt0WLFlAoFHB0dMTatWuZtz90WqpSqURWVhZWrVrFvK1o3LgxQkND0alTJ2zduhXnzp1jjt2xY0colUo8efIEK1euZCaXmpubY+DAgQgODkZUVBQOHTrE7G3evDkUCgWcnZ2xdu1a5u2PgYEB+vTpA6VSicuXLyM8PJzRZWtri0GDBqFr167Ytm0bzpw5wxzb29sbSqUShBCEh4czbz3Nzc0REBCAkJAQ7NmzBwcPHmT2NmvWDAqFAq6urli3bh0yMzMZXb1794ZSqURubi7Cw8OZtxV16fLy8oJSqYSenh5WrlzJvF00MzNDQEAABg0ahL179+LAgQPMXjr1tkmTJli3bh0yMjKkNTrFValU4tq1awgPD2fefFNUQ/fu3bFt2zbExcUxx+7QoQOUSiX09fWxatUq5u2iqakp/P39oVQqsXfvXuzfv5/ZS6feNmvWTOgJevXqBaVSiby8PISFhTFvcqkn6NGjB3bs2IFTp04xx27fvj2USiWMjIw4T0B10RvjPXv2MHvlXmXDhg1ITU1ldPXs2RMKhQI3b95EeHg486bN2toaISEh6NWrV51eZfXq1czbMrknqMurrF+/ntH1tF6lT58+Qk9Ql1cZMGAAlEolYmJisHPnTmav3Kts3LgRycnJjK4ePXpAoVDgzp07Or3Kzp07ceLECebYHh4eUCgUsLCwwJo1a5gOGuoJlEolTp06xXnOuryK3BOEhYUx3RHUq/Tr1w87d+78j70K9QRnzpzBli1bmL26vAoASVdJSQnCwsK0ehWRJ2jTpg0UCoVWT0B1JSQkYOPGjcxeR0dHKBQKeHh4YPPmzUhMTGTWfXx8oFQqoVQq4e3tDT09Pfzb6mlbc+uHFb0EJYfUa37oBE5tHznoW/Mjh7mLPnIYt+gjB/j+N3XRSXDPqutFna+XVZeu4z6NLl3/v+QA+3+SLl3Hfl5duv5unkeXrr+np9FFJwL+p2vPq0vX78DfqevvOl91feo6X7p+h15WXc97LXkeXbq+O19WXc97LXnWf/dlPl/1XuV/X1e9J+A/TZs2JQsWLBAOu/pfL9RPzf3n1MKFC5lfXIpuOHLkCMnJyZFwJPQPtV+/ftKktiNHjjB/CLa2tuStt94i27dvJ3l5eWT8+PHMsSkiIT4+nly6dEnCWNA/RopuKCgoIEuXLuX+oCgiIScnhwQHBzO65OiG6Oho5guNohu2bdtG8vLypNH29OPl5UVmzJhBzp07R5KTkyWMBdUlRzcsX76c2UsRCYcOHSKXL18moaGhzBeQHN1w/Phx5kuHohu2bt1K8vLyyGeffcYcu0OHDhK6ISUlRcJY0C9kObrhjz/+YPZSRMLBgwfJ5cuXJUwK1SVHN5w4cULCWAB/oRu2bNlC8vPzyRdffMEcu3379hK6ISUlRcJYUF0U3ZCXl0dWrlzJ6fr444/JgQMHyJUrVyRMCtVF0Q1paWkkNjZWwlgAfyESNm/eTPLz86WR+/TTrl07Cd2QmppKOnToIK1RdAOd3vrnn38ye+XohitXrpDhw4dLa3J0Q2pqKjl9+jSxsrKS1ikiYdOmTSQ/P598/fXXzLHl6Ia0tDTi7e3N6AoJCZGmt65fv57ZK0c35ObmkpEjRzK6KLohJSWFxMXFSRgLqmvUqFFk48aNpKCgQMID0Y8c3ZCenk46d+7MXODkiASKTqAfObohNzdXwrdQXRTdkJycTM6ePUsaNWokrctxTnSis/zYcnRDRkYG6dq1K6NLjnOi6AT6kaMbrl69Sl577TVGV/fu3aXprfHx8RLGAmBxTgUFBRK2iH4ouuHEiRMkMzOTdO/eXVrTxDnt2LGDMahydMPVq1fJG2+8wRy7W7du0vTWhIQECW1FdVF0w82bNyVsEf1QdENMTAzJzMwkvXr1YnTJcU6RkZGMMZKjG65fvy5hZejHx8dHmt564cIF4ujoKK3J0Q03b94kc+fOZfbKEQkqlUrCfgA8zikqKorRZW9vT8aOHUsiIyPJ9evXybvvvsscW45zSkxMJM7Ozowuim64efOmhFOiHznOKSsrS8J+UF1ynNO+ffsYg0rRDREREeT69evkvffeY44txzklJiZKaCuARTcUFhZKOCX6keOcsrKyyIABAxhdcpzTgQMHGINK0Q07d+4kN27ckHA39ENxTufPnycXL14kTZs2ldbMzc0lzFRhYSH5+eefmb1ynFN2djYJCAiQ1ijOiU6aP3ToEPNAQ45zunHjhoS7oR+Kc0pISCBJSUkSxoLqGjJkiDS9ddGiRcxeOc4pJyeHBAYGMrqoV1GpVOTo0aNCT0C9yoQJE5hja3qVVq1aSWvUq1BPsGzZMmavpleh6DRAfY2jXiUzM5NER0czN1dynFNeXh759NNPmWM/jVehk+Z/++03Zu/TeBXqCTS9ihznlJeXJ2F46Id6lTNnzpDk5GTi4eEhrVGvQifNh4WFMXs1vQrFpFBdffr0kXBOJ06cIBYWFowuinPKz8+XkIH0Q70K9QRyr6KJc1q1ahWz19XVVfIqubm5Qq9CJ83X5VW++uor5tjUq1BPQJFbVJcc57R27Vpmr4uLS51eRdek+X9Lof5G9J9Tb7/9tpCPRgght2/fJq6urtIflCa6YdmyZaRdu3YcH40QNZbBx8eH46PRiouLk8y/nI9G67333hPy0QhR4yLc3Nwk86+JSPjtt9+Ip6cnx0cj5C8+G+WjaaIb4uPjJfMvQiSMGzdOyEcjRI2LaNKkiWT+NREJYWFhQj4a1dW7d28hH40QQi5cuEBcXFw4liut8ePHC/lohKhxEU2bNpXMvyYiYdWqVUKWK9Xl6+srZLkSosZrODs7c3w0WhMnThSyXAlR8+yaN29ORo4cyfDRaK1du1bIR6O6+vfvL2S5EqLGWDg5OXF8NFqTJk0SslwJUeMiWrRowbFcaW3YsEHIR6O6AgIChCxXQghJT08nTk5OHB+N1uTJk4UsV0L+H3vnHR5V1Ub7NwkgRZEOAQJI6NI7wicI0jOIhd4EQbqAIFUgIGAUkBKKdOkdJBASIBAIaYQ0SIH03tukJ5Py3j/i3ux99j6TgHqvXmc9z3ke4/lmvuVkMmfNPu9evzKenbm5ucBHIzp//ryUj0Y0fPhwKcsVsQxjYWpqKvDRiFatWiXloyGW4SJat24tsFyJLl++zIV/5ersqFGjcPDgwVKcU0hICJqamqry0datW0fDvxKRkJ+fj23bthVYrkTXrl2TslyJNBoNDdlKdENYWBiampoKLFei9evXS1muiGW4iPbt2wssVyIbGxtuQVDpa+zYsVKWK2IZe7dx48YCy5Vo06ZN2LVrVynOqbCwEDt06CCwXIlsbW2lLFeiL774QspyRSxDWzVu3FhguRJt2bJFynJFLMMfdOrUSWC5Et25c4eGfxnOafz48VKWK2IZ2qpJkyZ0QVCJSLCyspKyXImvLl26CCxXovv373MhW4lumDx5spTliliGtmrSpInAciXavn27lOWKWIZq6tatG7cgyMrR0VHKciWaNm2alOWKWIaLaNq0KU6ePFmaCXbt2sUtCCozQc+ePQWWK9Hjx4+lLFeiL7/8UjWrpKSkoJmZmcByJbK2tpayXImv3r1706yizASurq5SlivR7NmzuQVB1ldaWho2a9ZMYLkSHThwQMpyRSy7lvTr1w9HjBghzQQeHh5SlivR3LlzVbNKRkYGlwmUWeXw4cMVzirKTEAWhpQsV6KFCxfSrKLMBFqtFlu0aCHw3YmOHTsmZbkSXwMHDqQsV2Um8PX11ZtVFi9eLGW5Ir7KKkqWK9HJkye5rKLMBB999JGU5YpYflZZtmyZlOWKWIaQatmypcByNcjwRfRfJRkXkCgrK0vK+6rIYwsLC6XcNqKMjAy9qzV/py8ZH+2v8JWdnf3GvnQ6nV4I8Z/1pW80Q99ji4qKyvUl42pV5LlzcnL+lC8ZH+3/ta/i4mK9vrRa7Z/yJeOjsY9Ve48UFxdL+Wh/ha/c3Nw39lVSUiLlo7G+9PHRyvMl47ZVxFdpaenf5isvL+8f60vGTK2oL33PnZmZ+ca+8vPz/1ZfMjZpRX3JmKn/r30VFBS8sa/ynjsrK+tP+TJkgoo/VqfT/WN9/V2ZwJBVXt+Xvmvvf1kV/SJablmRkZHRcQCwAIBkROz4x7+rAwAXAaAFAEQCwHhElDMJGBnKigwyyCCDDDLIIIMMMsggg/7/VUXLisrFt2zatCkDAI4DwKeWlpYH/vh3mwAgEBEnbNq0qQkADLW0tHTQ9zwABnyLmn7++WdITk7m6rWJIiIiYO/evVwdOSvSLMrWfhMVFBTAxo0bwcjIiNZYs3r06BH8/vvvXL02q+3bt0NSUpLUV1RUFOzevZur/WZFmkXZ2m+iwsJC2LhxIwAArf1m9fjxY7h27Zqqr507d0JCQgJXr00UExMDv/zyC1f7zYo0eMrqtXU6HWzcuJFWiit9ubi4wJUrV7jab1a7du2CuLg4ro6cKD4+HrZv387VfrO6ePEiPHnyROqrqKgILC0taaW40pebmxtcunRJ1dfu3bshJiZG+nolJibCzz//zCFKWF2+fBlcXV05FAhRcXExWFpaUmxGpUqVuPNPnjyB8+fPcygQVnv37oWoqCgOuUGUnJwMVlZWHAqE1dWrV8HZ2ZlDgRCVlJSApaUl6HQ6irZg5enpCWfPnuWQG6z27dsHERERYGZmJvhKTU2Fbdu2QfXq1cHU1BSMjXkU8/Xr18HJyYlDgbC+Nm3aRPEUSl9eXl5w+vRpVV8HDhyAsLAw6euVlpYG27Ztg2rVqlEUCKsbN27Aw4cPORQIUWlpKWzevBny8/Olr5evry/89ttvHHKD1cGDByE0NJRDbhBlZGTAli1bOIQEq5s3b8KDBw84FAgRIsLmzZshNzeXQ0gQPX/+HI4fP67qiyA7ZL4yMzNhy5YtFNWg9GVrawsODg4cCoT1tWXLFsjJyZH68vf3h6NHj3LIDVZHjhyBly9fSn1lZWXB5s2boUqVKlJfdnZ2cPfuXdXXa+vWrZCZmSn19eLFCzh8+LCqr2PHjkFgYCCH3CDKyckBS0tLqFy5stTXnTt3wN7enkOUsL62bdsGWq1W6isoKAh+/fVXDgXC6sSJE+Dv7y/1lZubC5s2baKoBqWve/fuwe3bt1V9WVlZQXp6uvQaFxISAgcOHFD19dtvv8Hz58+lvvLy8sDS0hJMTEwoCoTV/fv34datWxwKhJWVlRWkpqZKfYWFhcG+fftUM8GpU6fAx8dHeu3Nz88HS0tLMDY2ll7jHB0dwcbGRvXaqy+rREZGwp49e/RmFS8vL9VMQLLom2SVHTt2QGJiotRXdHQ07Nq1SzUTnDt3Dp4+fao3EyCi1Jezs7PeTPDLL79AfHy89NobGxsLO3fuVM0EpNVbXyZQyyqurq5w+fJleu1V6s9klUuXLoGbm5vUV3FxMWzcuJEi0ZTXEnd3d7hw4QKHLWO1Z88evVnlp59+Us0EV65cARcXlzfKKh4eHnDu3DnVrGJtbV1uViEYrv9iO66aKopvqdBILZTd+fRnfg4CANM//tkUAIIq8jyG0Vy5Tp8+TTdIK/dNlpaW4v/+9z+6QZrsmyRjUv7+/mhkZMSVk7B7EUjJDVuaQvYi5OTk0EKO9u3bC3sRzp07hwBiaQoRKXIgeyTYvQgvXrxAY2NjWk6i3DdJNo6zpSnEV15eHi3kkO1FuHTpEvVF9k2yvkiRAylNuXHjBvUVHBxMCzlk+ybXrFlDfSn3SOTn59NCjrZt2wr7Jq9evYoAfGkKu3eDlDs1atRI2IsQFhZGCzlk+yZJmQwpTWH3IhQUFNBCDtm+yRs3blBfsn2TpDChYcOGdN8k8RUZGUkLOWT7Ji0tLRHgVWnKiRMnqK/CwkJayCHbN2lra0tLQGT7Jj/55BMEppyE3TcZHR1NCznY0hTii5S2sOUkZD+nTqfDli1bIgBfmkJ82dvbU19saQoRKSYg5STsvsnY2FhayCHbN/njjz9yvth9k0VFRbSQQ7Zv0sHBgStNUe6bHD9+PPWl3DcZHx9PCzlk+yZJOQopJ2H3TRYXF2Pbtm2F0hTiy9HRkStNUe6bnDx5slCaQsakkpKSaCEHKU1h902ScpTq1asL+yZLSkqwQ4cOXGnKnTt36JiUk5MTV5qi3Dc5bdo0oTSF+EpOTqaFHF26dKHlJMQXKUdhi9RYX6Skq0WLFrQ0hfhycXHhykmU+yZJKRBbmkJGulNTU/Gdd97hSlPYfZOkHKVatWp03yTZz1laWopdu3blSlPs7OyorydPnnDlJMp9k7Nnz6a+lPsmMzIyaEmXbN8kKUdhi9TIfs7S0lLs0aMHV5rC7pv08vLiykmU+ybnzZsnlKaQUTqtVou1atXiyknYfZPHjh2jvpT7JktLS2kZFil4s7W1pb58fHy4chLlvklSvkNKU86ePUt9ZWVl0fIw2b5JUo6iLE0hvkgZlmzfpJ+fH/Ul63gghXy1atUSOh6ys7OxXr16NBMo902eOXNGb1b58MMPuUzAZpWAgAC9WYWU3JCswmaC3NxcmlVk+ybPnz+vN6sMHjyY+lLum3z58qXerLJy5UohE7BZxdTUVDWrXL58WcgqbCYgRZSmpqZ03yTxFRISQjOBbN8kKb5ji9TYrNKkSRMEAGnHw7Vr17issmfPHm4/Jyl3UssqJBPI9k2uX7+e+lLumywsLNSbVWxsbLissnv3bi6rWFhY6M0qJBOQrMJmAlIwxxapkUxQWFiILVq0UM0qt2/fFjIBm1VIiZIsq/yXBX/lHlHJF1Gt4nxGRZ7H8EVULrbpiz06d+6MGo1GWh1NAhDb2MYezZs3x0mTJklxACQA/e9//5PWWpMAxDajsUenTp1wzJgxUl+knY1tl2UPUhqg5mvAgAE4cOBAqS8SNNRer44dO+Inn3yi6mv06NE0uCoPUrKg5qt///44aNAgab048cW2pbLH+++/j2PHjpX6Iq1xuiRSOwAAIABJREFUbJMce5BSCllFOAlAH330kdQXCRq1a9eWPneHDh3w008/VfU1cuRIrvWWPZo0aaLXV79+/XDIkCFSXyRosG2p7NG+fXtVX1WqVMERI0Zg586dpZX9jRs3xilTpqj66tu3r6ovsihSv359qa927drh559/Ln2PkKDRtWtXqS9TU1O9vvr06YNDhw5V9TVu3Dhs2LCh1Ffbtm1VfZGg0b1799f2BVAWgNR8kQDEtqWyR5s2bfCLL75Q9fXxxx9jjx49pL4aNWqEU6dOVfXVq1cvHD58uPQ9QhZFmjZtKn1s69atcdy4caq+hgwZgr169ZL6atiwoV5fPXr0wBEjRqj6+uyzz7BZs2bSx7Zq1UrVFwlAvXv3lvpq0KABTps2Ta+vkSNHSn2RRRG2xZU9zM3Ncfz48aq+PvroI+zbt6/0M7t+/fp6fZFCH9n7q0aNGjh27FiuxZU9WrZsqeqLLIp88MEHUl/16tXT66tr166qvshiDds4zx7vvfceTpgwQdXXwIEDsX///lJfZFFEzRcpZpL5Ik2yrVu3lj62RYsWqtde0nqvlgmILzXMRUWyClnMUh7NmzfXmwnKyypTpkzRm1XKywT6soq+TFCRrEIWjZRHx44dVTPB35lVyKIIWZxRHuVllZEjR/6prDJ48OC/JauMGDECO3XqJP1s/CuyClmcUR7lZRWyKKIsBfuvCCr4RZSfY/kbZGRk9LWRkZGnkZGRJwu7NuiVGjZsKPy7qlWrQrNmzaBRo0bCGAtAGQDdzMwMGjZsKIwjGRsbg5mZGTRp0kQYRwIogyKTxyrHDADKwMZmZmbSkY633noLzMzMwNTUVBjLqKivpk2bSseRatasWa6vZs2aSUc6KuqrQYMGwhiLkZERfb1kvt555x29vkxNTcHMzEzqq0qVKtSXclzkdXzJfo/lvV6mpqaqr1d5vurWrUufWznGQka91XxV9PWqX7++qq/GjRsLI6Ssrzf5Pb799ttgZmYGjRo1em1flStX1vt61alTB5o1ayZ9vQCAvl7l+VKOagKUfT6Q/2Y1X7JxJNZXgwYNpL6aNGkCTZs2lY67EV+mpqav7atSpUp6f4+1a9em7xHlqCbrS/Z61ahR441fr4r4Ir9HNV9mZmbS16tGjRr0M1vmq0GDBqrvLxMTE+pLOXILAFCrVi36eilHD4kvtd9j9erV6eulHCFlfcler7/Cl9q1pHr16vT1kn1m169fv0K+ZJ9BxFeDBg1e21e1atXo61WeL+UYHnvtlb1e7LVXOXpIfDVr1kzqq2rVqnqvcRXxpfZ6kWtJgwYNpL70ZQLi602zir5rCXm91D6zK5IJ1H6P9erVo5+NSl/sNe5Ns4paJijPF3vtlV3j9Pki1159r9ebZpW6devSz0Z9vt4kqzRq1KjcTKDv2lve69W0aVO9WUXt9dLni732yq4lxJeZmZn0d2UQo4p8WwXDaO7fKjJOxfL3yHgGGadSGxtxd3dHAJ6/x9Zak3Eq2dhIeno61qxZEytXrkzrttmxEcLFZPl7ZAyCHaeSjY14enpSX7K67blz5yKAfGwkIyMDa9WqpTpKSlhTLH+P9dW7d28EkI+NeHt7IwDP32Prtsk4lWxsJDMzE+vUqaM6NkK4mIS/x6JB2HGqnj17CqOkz58/p75kaBDCMiNjI+woKRmnUhsbIaPfsrERdvSb5e8RX2Scih1xZREcZPSbjLiyo6Rk9Jvl77EjrmScSjbiivhq9Lt79+6Uv0dGEMnoN8vfY32R0W/ZKCkZ/Wb5e+yIKxn9rlevHh1xZRv3yOg3y98jvsg4lWzEFfHV6LcMDUJGv5WsYCIyTsWygllfZPSb5e8RX2T0W8kKJiLjVCx/j4xsktFvJSuYiIx+y0ZJEV+NU7H8PeKLjH4rWcFEZPSb5e8RX2ScSm3ElYx+s6xgtu2WjH6zrGDii4x+K/l7RFu2bKF3J5RoEDL6rTbiSka/2VFS1tfnn39O75ooR1zJ6LeSFUxERr9Z/h7xVVRUhK1btxZYwcQXGf1m+XtsWyQZ/ZaNuCYkJGDVqlUFVjARGf2WoUHI6Lcaf4+MfrOsYBbBQUa/ZSOuZPSbTFIocWG7du2id02UI65k9FvJCia+yOg3u+2F9UVGv8mIKztKmpKSgjVq1FAdJSWj3zI0CBn9JhMeykzg6uqKAPJtL4ivRr9lI65k9FttlPTAgQMVzirKbS9k9Fstq8yZM4fLKspM8O677wqsYCIy+k2yijITEA6ybNsLGf1Wyypk9FuWCbRaLdauXVs1q5DRb7WsQka/ZdteyOg3m1XYTLBo0SIuE7CjpGT0W23bCxn9ZlnBbCbo378/Asi3vZDRb7WsQka/ZdtecnJyhKzCZgIy+s2ygkkmYEe/2axCPrMDAwP1ZhUy+i3b9kJGv01MTDhWMNGFCxeETMBmFTL6zbKC9bXw/lcEf/No7nYAWP3HP68GgJ8r8jyGL6JyHTlyRPWNGxERIeXvEV2/fl3K30MsC7Z79+4V+HtErq6uUv4e0dGjRwX+HlFUVJSUv0d048YNLvyzKigowL179wr8PSJ3d3cpf4/o2LFjAn+PKCYmRsrfI7KxseFCNqvCwkK0trYW+HtEHh4eUv4e0YkTJwT+HlFcXJyUv0d069YtVV86nQ6tra0F/h6Rp6enEP5Z/fbbbwJ/jyghIUHK3yOytbWV8vcQy4KttbW1wN8j8vLyEkI2q1OnTgn8PaKkpCQh/LO6ffu2lL+HWBZsra2tBf4ekY+PD7ePTKnTp08L/D2ilJQUPHjwoMDkJbK3t5fy94ivffv2Cfw9omfPnkn5e0RnzpwR+HtEqampUlYw0d27d6X8PcSyYLt//35V+Lafn5+Uv0d07tw5gb9HlJ6ejvv37xf4e0T37t2T8vcQy4LH/v37BSYvUUBAgJS/R3T+/HmBv0ek1Wr1+rp//76Uv0d8HTx4UNVXYGCglL9HdOHCBYG/R5SZmSnlAhI5OjpK+XusLyV/j+jly5dS/h7RpUuXBFYwUXZ2NlpbWwv8PaKHDx9K+XvE16+//irw94iCg4P18vcuX74ssIKJcnJy9PpycnKSsoKJr0OHDnEhm1VoaKiUFUx09epVKSsYsSzYWltbC6xgImdnZ737yA4fPiywgonCw8OlrGCia9eu6c0E1tbWAiuYyMXFRcoKJtKXVSIjI8vNKvoygbW1tWpWcXNzExYEWR07dkw1q0RHR5ebVWSsYMRXmUAtqzx58kRYEGR1/Phx1awSGxsrLAiy0pdVSCb4O7JKfHx8uVlFxgpGfJUJ9GUVGZOX6OTJk3qzSnmZQF9W2bdvn2pW8fb2/tNZ5b86fqtPFf0iWhF8y3kAGAQA9QAgCQA2AsDvAHAJAJoBQDQAjEPEdL1PBAZ8i0EGGWSQQQYZZJBBBhlk0P/Pqii+Rdw0pBAiTlI5NeS1XRlkkEEGGWSQQQYZZJBBBhn0n1e5HNG/UgaOqFyLFi0CZ2dnyiFiN85HRETAjBkzICsrS8om3LNnD5w+fZqWEbCFJAUFBTBhwgSIjIyUsgnv3LkDGzdupGwl5WbtJUuWgJOTk9RXVFQUTJ8+HTIzM6VsQmtrazh58iQtkGF9FRYWwsSJEyE8PFzKAHRwcIDvv/8edDqdlLW3bNkyePjwIVSrVk1g2sXExMC0adNAq9VKWXsHDhyAY8eOUV9sIYlOp4NJkyZBaGio1NeDBw9g7dq1oNPpoEmTJoKv5cuXw4MHD6S+4uPjYcqUKZCRkSFlEx46dAiOHj0KACD4KioqgsmTJ0NISIiUAejk5ASrVq2CgoICKdPuu+++AwcHBynLMTExESZPngzp6elS1t6RI0fg0KFDUl/FxcUwZcoUCAoKkvpycXGBFStWQEFBATRt2lTwtXr1arhz547UV3JyMkyaNAnS0tKgQYMGgq/jx4/DgQMHpL5KSkpg6tSp8OLFCykD0M3NDZYvXw75+fnS12vt2rVgZ2cHb731lsAmTE1NhYkTJ0JKSoqUAXjy5EnYt28fIKLAtCspKYHp06dDQECA1JeHhwcsWbKE+lIWf6xfvx5sbW0p+5ItZkhLS6O+6tevL/g6c+YM7NmzR+qrtLQUZsyYAX5+flLWnpeXFyxevFjVl6WlJdjY2ECVKlUEpl1GRgZMnDgRkpKSpAzAc+fOwa5du6C0tFTwhYgwc+ZM8PX1lfKKfX19YcGCBZCXlyf1tXnzZvj999+lvjIzM2HChAmQmJgo9XXx4kXYuXMn5fSxBS6ICF999RX4+PjA22+/Lbxefn5+MG/ePMjLy5Oy9rZu3QrXrl2j7EvWV1ZWFowfPx4SEhKkbMLLly/D9u3bKVNY6WvOnDng6ekpZQAGBgbCnDlzIDc3V+rrxx9/hCtXrkDlypUFXzk5OTB+/HiIi4uT+rp+/TpYWVlRfqDS19dffw1Pnz6V+goKCoLZs2dDTk6OtJDk559/hosXL4KJiYnAAMzNzYUJEyZAbGyslE1oY2MDW7dulV7jEBHmzZsHT548kbIJQ0JCYNasWZCTkyMtA9uxYwecP3+eFiexvvLy8mDChAkQHR0tZRPeunULfvjhByguLpZeexcsWACurq5SX+Hh4fDll19Cdna29Nq7a9cuOHPmjNRXfn4+TJw4EaKioqSZwM7ODjZt2kSvvUpfixcvVs0qkZGRMH36dNWssnfvXjh58qQ0q5BMEBERIfV19+5d2LBhg2om0JdVoqOjYdq0aapZZd++fXDixAmpL51OR7NKrVq1hExw//59WLdu3Rtllbi4OJg6dSpkZGRIs8rBgwdVs0pRUZHerOLo6Ahr166lzGqlrxUrVsD9+/el3GmSVdLT06W+Dh06BEeOHJH6Ki4uhsmTJ0NwcDC8++670qyycuVKKCwslF57V65cCffu3VPNKpMmTVLNKkePHoVff/0VAPRnFdm119XVFZYvX66aVdasWVNuVklNTZX6+i/rL+WI/lWHYY+oXIQHBZLilujoaMp+AxDZhKTABOBV3T3Zp5GZmUkLJoDZpE32aTx79ozWeMuKW0iBCUg2acfExNCyIvhjkzZb3PL777/Tc8rilqysLJw4cSI9ryyU8fPzo4w1WXEL4UERXyybMDY2Fnv16kXPd+3alStuuXXrFueLZRNmZ2fjlClT6HklmzAgIIDWeMuKW0iBCcCrunuydzMuLg779u1LzyuLW27fvk2rx5VswpycHFp8AX8UyrDFLYGBgZSxJitusbKyoo9VFsrEx8fTYgKQFLfcuXOH1tOT4haypzQ3Nxe//PJL+thmzZrR4paCggJ8+fIl5cHKilt27NhBH1u7dm2cMmUK3aeRkJBAS5RAUtzi4OBA69aVbMK8vDycNWsWfSxhAJI9pUFBQZSxJmMTkgIT4mvy5Mm0uCUxMREHDRpEzyuLWxwdHWmVOyluIWzC/Px8WsgBiuKW/Px8DA4Opow1lk1I9m5aW1vTx7IMwPT0dExKSqKFCSApbnn06BHna+TIkbh//36Mjo7GgoICWsgBkuKWkJAQivaQsQlJgQlIiluSk5MpKw+AZxMWFRWhs7MzrdUnhTL79u3DqKgo1Ol0uGDBAvpYJZswNDSU8mBZNiHZu3n48GH6WGVxS0pKCg4fPpyeVxa3uLq6Uh6skles0+lw8eLF9LHK4pawsDDKg2VL5khxCykwIb5YNmFqaiqOGjWKnleWzLm7u1MeLPFFSuaKi4tpUQiAWDIXHh7OITR69+7NFbecPHmSnlMWt6SlpdHSKYBXJXOOjo5YVFSEHh4eWL16dQTgecXh4eFYXFxMS82IL7a4JSIigkNVKItbzp49S88pS+bS09Np6RQwhTJk76aXlxdFe7DFLWFhYVhaWkpLzQB4NmF2djZGRkZix44dOV9scQspWyO+2OKWjIwM/PTTT+n5Vq1accUt3t7eFO0hK5lbtWoVfayyZC4qKgo7d+4sZAKyp5SwK0kmYDnKWq0Wv/jiC3qeLZnT6XTo6+tLMWSykrl169YJWYVkgujoaOzWrRuXCdjiFrWskpCQgJmZmThhwgQuq7CZ4Pnz53qzyoYNG1QzQUxMDC0rIpmAzSqkbE2WVbKzs3HSpElcVlm8eDHdU+rv708xZLKssnnzZsEX2VMaGxtLixUBxJI5NquQkjk2E0ydOpXLKmzJXHlZZevWraqZIC4uDvv166eaVezs7KRZJS4uDnNzc3H69OmqWeXFixcUQ8ZmFZIJfvrpJ84X4RVrtVpMSEhQzSrFxcV49+5dIauwmYCUdCmzSn5+Pr58+ZLyYElWYTPBzp07hUzAZhVSoiTLKv9lwV9ZVvRXHYYvonLJOFQkaLBhSXmYm5urckSNjIy4AKg8ateuzQV95fHBBx9IOVXEF2nolB0tW7ZUZXMBgF5ftWrVwoEDB6qe79u3Lw2IyqNy5cp6fbVo0UKVzQUAtA1Vdrz77rvcFxDl0atXLxrEXtdX8+bNucDzOr5q1qxJ22VlR8+ePVVZZpUqVaLgatnRrFkzLvAojyFDhqiee+edd7gvRsqje/fuqiyz8nw1bdoUu3Tp8sa+9J3v2rUrXQRRHiYmJnp9NWnShAtiykPf6/H222/r9dWlSxdVvml5vho3bswtGr2Orxo1auh9/3Xq1EmVb2piYqL3fd+oUSMuICoPfe/r6tWr6/XVsWNHGiyUh7Gxsd7P1YYNG3IBUXno+xyoVq2a3s+3Dh06qPJNy/PVoEED2rIpO/R9blarVg2HDRumer59+/aqfNPyfNWvX58Lrq/jq2rVqnp9tW3bloLmlYeRkZFeX/Xq1eOCq/LQd/1766239D53mzZt6CKIzJe+/6a6devigAEDVM/rO1eer1atWqlyRMvzVadOnXIzgYy1CFB+JjA3N1fliAKAXl+1a9fmgr7y6Nevnyp3tSJZpX379qrn/0xW6dOnD100Uh6VK1fW+5ndvHlzVV4nwJ/PKmrc1fJ8NWvW7P9ZVtH3ezQzM/vHZpXz589LC5L+CwLDF9F/j9jVdWWd+8uXL7FTp070vHL1nV3FViJeUlNTccyYMdwHAXtXwMXFhfsDU66+L1u2jPuAYuvcg4ODuS8DxNeNGzcwNzeX1nCTgyBefH19MS0tDceOHct9EIwbN46uvru6unJfBpSIlxUrVnC+2Dr3kJAQ7N69Oz2vrE1nV7HJhzK5K5Ceno6fffYZPadcfXd3d+fAxso699WrV3O+2Dr30NBQLnQrV98vXbrEwZjZuwLKVWzii6y+e3h40DuiAGKdO7uKTe4KkNX38PBwLnQrV9+vXr3KLZSwde7KVWxlbfrTp0/pHVEAsc5948aNnC+2zj0iIoK7g6ycFLh+/Trni50UUN5xV04KeHp6YuPGjel5ZZ07u4pN6tzJ6ntUVBTF8ACIkwI2NjZcWGMnBZR33JWr797e3tyXFOWkwLZt2zhfgwYNoqvv0dHRXIgkiBdyV8DW1paDbpO7Ak+ePBHuuLOIl/j4ePTx8aF3RAHESYGff/6Z88WuvsfExHBhjUwKkEZHOzs7LkR26dKFrr7n5eXhjBkzOF/s6ruvry++99579LwSPcOuYisnBWJjY7lQpLwrcOfOHW7Bq3PnznT1PT8/n7vjrpwUeP78OZqbm9PzBD1DVt/37NnD+WInBeLi4rjQpJwUuHfvHhdu2dX3goIC/Oqrrzhf7KSAn58f9yWFoGfIpMC+ffs4X+ykQEJCAhfK2bsC6enp+ODBA24hrmPHjnRSoLCwEL/++mt6jp0UiI6OxoCAAO5LihLxQjBi5BpHJgX8/f0xMTGRC6gEPUPapx8+fMiFbnZSQKfTcZMAZFKAtE8HBgZyC5fKSYEjR45wvthJgaSkJO7ONkHPkEkBJycnLnSzkwLFxcXcJACLnomMjMQXL15wXwaUiJfjx49zvthJgZSUFO7OtjITODs7Y82aNel55aQAwYgRX2xWCQoK4r4MKLPKqVOnOF/KrMLe2Sa+SPt0eVmFveOuxNEFBwdzU2XKSQH2jjsAj6NLT08Xsgo7KeDm5kbviAKIWYW94y7LBPqyCkGGkIPF0WVkZFDME8DrZxWCEWN9kUmBsLAwbqpMiaOTZRWSCbRaLY4bN47zxU4KeHh4cAuXyqzy/fff03PKSYHw8HBuIU6ZVa5duybNKp6enpiVlVVuVmEXLpU4OoIRI77YSYHIyEhuIU4NR/dfFFTwi2i5ZUUG/f3KycmBmTNngoWFBQwdOpTbixIZGQnVq1eHjRs3gkajgW7dunHz6UlJSfDpp5+CRqOBUaNGQcOGDek5nU4HOTk5sGTJEtBoNPC///2P24OVnZ0N3bp1A41GAxYWFtC6dWvOV1ZWFsyYMQM0Gg0MGzaM8xUTEwNVq1aFDRs2gEajge7duwu+xo4dS301atSInisqKoLs7Gz45ptvQKPRwIcffsj58vX1hc6dO1Nfbdq0EXxNnz6d+mL3fMTFxUGVKlVg/fr1oNFooEePHoKvTz75BCwsLGD06NFgampKzxUXF0N2djYsXryY+mL3Ovn7+8P7779PfbVt25bzpdVqYdq0aaDRaGD48OGcr4SEBKhUqRJ8//33oNFooGfPnoIv8ryjR4+Gxo0b03MlJSWQlZUFixYtAo1GAwMHDuR8vXz5Etq1awffffcd9cXuf9BqtTB16lTqi93zkZSUBMbGxrBu3TrQaDTQq1cvYf/D6NGjwcLCAiwsLARfmZmZsHDhQtBoNDBo0CDOV1hYGLRu3RqWLVsGGo0G2rVrx/nKyMiAKVOmUF/s3oqUlBQwMjKCtWvXgoWFBfTu3Zvbs5acnAyjRo2ivpo0aULPlZaWQlZWFixYsID6Yvc6RUZGQsuWLen7r3379oKvyZMng0ajgREjRnC+0tLSABFhzZo1YGFhAX369BF8DR8+nP4umzZtKviaP38+aDQa+OijjzhfsbGx0Lx5c/p6dujQgfOVnp4OkyZNor7YfaAZGRlQUlICq1evBgsLC+jbt6/ga+jQodSXmZkZPYeIkJWVBfPmzaO+2D1FiYmJ0KRJE5g7dy5oNBp4//33OV9kfyrxxe63zMzMhOLiYli1ahVYWFhAv379OF8pKSkwePBg6qtZs2aCr7lz54KFhQUMGTKE85WamgqNGjWC2bNng0ajgY4dOwq+JkyYQH2x+xqzsrKgqKgIVq5cSX2xe8NSU1Nh0KBB1Ffz5s0FX19//TX1xe4pysjIgAYNGsDMmTNBo9FAp06dOF8pKSkwfvx40Gg0MHLkSM5XTk4OFBYWwooVK0Cj0cAHH3zA+UpPT4cPP/yQ+mrRogXnKzs7G+bMmQMWFhbw8ccfc76ysrKgbt269LOzc+fOgq9x48ZRX+x+y9zcXCgoKIDly5eDRqOB/v37C7769+9Pfb333nvAKjs7G2bPnk19sft5g4ODoXbt2rB582bQaDTQpUsXwdcXX3xBfbFw+fz8fMjLy4Nvv/2W+mL3hmVkZEC/fv2or5YtW3K+cnJyYNasWaDRaODjjz/m9s2GhoZCzZo1YdOmTaDRaKBr166cr+TkZPj888+prwYNGtBzBQUFkJubSz/7BgwYwPnSarXQu3dv6svc3FzwRd4/Q4cO5XxFRETA22+/DZaWljQTKH199tlnYGFhIWSCwsJCyM3NhaVLl9JMwPrKzMyEnj17Ul+tWrUSfo9ffvkl9cVmgqioqHKzCskEo0ePFrJKdna2albx8vJ646wSGxtbblb55JNPqC9lVsnJyVHNKs+ePYNOnTqBhYUFaDSa18oq8fHxNKtYWFhIM8GYMWOoL2VWycrKUs0qAQEB8P7771Nf+rLKsGHDuEyQmJgIJiYm8P3334OFhYU0E5Dnfd2sEhQUBG3btqWfI6+TVZKTk2km0Gg00Lt3b+H1GjVqFPXFZgLia+HChWBhYSFkgrCwMDA3N6d/F6+TVVJTUwGgbB8p8cVe4wwqX+XiW/5KGfAtcpWWlnJ/UBU9V5HHGhkZcX9Qf+VzG3wZfBl8/ft9kWuAwde/3xci/m3vXYOv1/P1T/xbN/gy+DL4+r/r67+siuJbDF9EDTLIIIMMMsgggwwyyCCDDPpLVNEvooav8f8A5efn6z2nb7FA32OLioqgqKjojR77b/VVUFAApaWlb/TY4uJi0Ol0Bl8VfGxJSQkUFhb+K3296Xv37/SVl5f3xr4KCwuhpKTkjR5bWloKBQUF/zhfiKjX15/5Pf5ZX3/XZ2NhYSEUFxf/43zpdLr/L33l5eX943yVd/6feu39p/oqKCh4Y1//1GuvwdfrPfbvvPaW58ug8mXgiP4DNHv2bDhy5AjlXLFz8ampqdC9e3cIDAyUcpusra1h+fLlkJSUJGU5/u9//wMHBwcpT8rFxQVGjRoF0dHRUj7S3Llz4eDBg1JfGRkZ0L17d/D395f6OnDgACxbtkzV14cffgh3796V8qSePHkCw4cPh+joaMpMZH0tWLAA9u/fD5mZmQK3KSMjA3r06AF+fn4AIPKkDh8+DN988w0kJiZKeVIfffQR2NvbS3lST58+haFDh0JUVJSUMbl48WLYu3cvaLVawVdmZib06NEDnj17Bogiy/Ho0aOwaNEiqS8jIyP4+OOPwdbWVsoK9fHxgcGDB0NUVBRlJrK+li5dCrt37watViuwL3NycqB79+7g6+srZTn+9ttvMG/ePEhMTISaNWtyzEQjIyMYNmwY3Lx5U8qY9PPzg4EDB0JERISU5bh8+XLYuXMn3VPH+srNzYXu3buDj4+P1Nfp06dhzpw5kJCQIPU1cuRIuHHjBuTn50Pjxo05XwEBATBw4EAIDw+X+lq5ciVs374dMjIyBMZkfn4+9OjRA7y8vCjLkfV1/vx5mDVrFiQkJAjsSyMjIxg9ejRcv35dypgMCgqCAQMGQHh4uJTluHbtWrCysoL09HSB5VhQUAA9e/aEp0+fShmTly5dgi84+adIAAAgAElEQVS//BLi4+OlrNCxY8fClStXIC8vD0xNTTlfISEh0L9/fwgLC5P6Wr9+PWzduhXS09MpM5FIp9NBz5494cmTJ1LG5NWrV2HatGkQHx8vMCaNjIzgs88+g4sXL1KWI+srPDwc+vXrB6GhoVCpUiUwMzPjfFlaWsIPP/wAaWlpAmOyqKgIevbsCW5ublBcXCy8Xjdu3IDJkydDXFyc1Ne4cePg/PnzUsZkVFQU9O3bF0JCQigrlN1PuWXLFrC0tIS0tDSoU6cOx5gsLi6G3r17g4uLi5QxeevWLZg4cSLExcUJjEkjIyOYNGkSnD59WsrkjImJgT59+kBwcLCUMblt2zbYsGEDpKamCizHkpIS6NOnDzx+/BiKiorAzMyM82Vvbw/jxo2D2NhYqFGjBpiamtLPICMjI5gyZQqcPHkSsrOzBcZkfHw89OrVC4KCgqSs0J9//hnWrVsHKSkpUl99+/YFJycnKSvUwcEBPvvsM4iNjRWYiUZGRjBjxgw4fvy4lMmZmJgIPXv2hJcvX0oZkzt37oTVq1dDcnKywHJEROjXrx88fPhQyph0dHSETz75BGJiYqSMyZkzZ8LRo0chKytLuPampKRAjx494MWLF2BsbAxNmzblrnG7d++G7777TtXXgAED4MGDB1Jfjx8/BgsLC4iOjpb6mjNnDhw6dAiysrIEHnZaWhr06NEDAgICAEC89u7btw++/fZbSE5OLjerKK9xrq6uMGrUKIiKipJmlXnz5tGsorz2pqen06wi83Xw4EFYsmSJalYZNGgQ3LlzR29WUfO1cOFC2Ldvn9SXVquF7t27w/Pnz6W+Dh8+DIsXL4akpCRpVhk8eDDY2dlJM4GnpycMHToUIiMjpVnlm2++Uc0qWVlZ0K1bN9WscuzYMViwYIFqVhk6dCjY2tpKM4Gvry8MHjyY+lLysJctWwa7du0CrVYr8LBJVvHx8ZH6OnnyJMydO1c1qwwfPhxu3rwp5U77+/vrzSorVqygWUWZCUhW8fb2lmaV/7IMHNF/kZSV14Qn5e7ujo6OjpR5CCAyJtn2MwCeJxUSEsI125JGS9IceerUKa6BUdkcqazLJjwpNzc3dHJy4ho+q1WrRpsj4+LiuPYzgFfNkfb29hgWFsa12JFGS9IcefbsWaxWrRrni+VJjR49mnvuTp060ebIx48fUxYjgNgcyTa1El+kOTI8PJxrsVM2R547d45rYFTypNjWPwC+OdLFxYVrHq1atSrHmGSbWgFesS9tbW0xKiqKw28omyMvXryIb7/9Nj1PmiMJ+5JtAgYoY1+S5kh3d3cOj6BsjmSbWgFeNVreunULo6OjuSZgZXPk5cuXuQZGln2ZlpbGMW4ByhotSXOkh4cHh0d46623aHNkVFQUxxsDeNVoefPmTYHPxjZHPn/+HK9evUpZeQCv2JekOZLlxgHwzZFPnz7lGlGVzZEsGxWgrNGSNEfGxcVxrX/K5sjff/+da4ZkmyNTU1O5ZlsAvjnSy8uLsiuJL7blevfu3dxjTU1NaXNkYmIi11AMwLdc29jYYO3atTlfbMs1y2cD4JsjfXx8OMSUsuV67969XAMjy5hMSkriGooB+ObIW7ducY2VpNGSNEfOnj2beyzbHOnr68s1tSobLffv3881MLIt1ykpKQIWhLRce3l54e3bt7nGSrY5Mjk5mWtqBeCbI/38/Dj0lbLl+tdff+VamdnmyNTUVAG/wTZH2tvbc+3aSsbkwoULuceyLdcBAQFcgyxptCTNkYcPH+ZamdnmyLS0NAG/wbZc3717l2vSVLZcs2xUAL7lOjAwkMNcKBmTx44d4zBk9evXpy3XWq1WwG8Q9qWHhwc6ODhwrd/Klmu2qRWAb7lWtt0rGZMnTpzg2qKV7Esl5oLlYT948IBr/VbysFeuXMk9lm25VjbbKluuT506xbVFK1uulTgTljH58OFDvVmF5aUDvGq5tre3x9DQUC6rKFuuT58+rTerKBEaLGPSycmJywTKrMLy0gF4xmR4eDiH5FK2XJ89e5ZriyZZhWQCtqEYgG+5dnZ25pBJbFaJiYnhmloBeB52RESE3qxy/vx5aVYhmYBtAgbgediurq5cVlHysH/44QfusWzLtSwTsFnl0qVLQlZhedhsEzAA33Lt7u7OtaQrs8qPP/7IPZZtuY6OjuaagJVZ5cqVK1xWUfKw2cZdAL7lWplVlDzs/7LA0Jr775GXlxf387Nnz+g/v/vuu5CSkkJ/zs/PBwcHBwAoW+V5+vQp99jIyEi4efMmAAD06dMHQkJC6LmSkhJwdnamIwjR0dHcGEV6ejrcvn0bAAAqV64s+CIrd4gIdevWheTk5Ar7io6OBhsbG0BE+OCDDyA4OJieKy0tBRcXF+orPj6eG6Moz5efnx99bIMGDSApKYmeKygogPv371NfHh4egi/yemm1Wnj58iXny83Njf6clJTEjWhkZGSAnZ0dAABUqlRJ8OXv7099mZqaQmJiotQXAAi+YmJi4ObNm7Shk/WFiJyvtLQ0zpdWq9XrKyAggPpq2rQpJCQk0HOFhYXw4MED+vOTJ0+4x8bGxlJfOTk58OLFC86Xu7s75yM3N1fqy8TERPAVGBhIfTVv3hzi4uIq7CsuLo76ysvLo6vyxBf7v8/JyYGcnBz6c2ZmJtjZ2ZV9IEpeL/a1b9myJcTGxtKfdTodODo6Sv/7Acrey7du3QKAsr8RpS/2956fn8/5ysrKAnt7e1VfQUFB9J/Nzc1fy1dCQgL1pdPp6N0CItYXabSU+TIxMQHlvv/g4GD6N9W2bVuIjo6m54qKiuDhw4fcfz/5nQOU3YUivoqLi+lnDhH7uVJaWgqZmZn05+zsbL2+QkJCqK/27dtDVFSU4ItcGMnqNlFSUhLY2trS/1/2MxoA6P8X/lF+o9Vq6bmcnBy4e/cuAIDUV2hoKPX1/vvvc76Ki4vh0aNH9DUikwtEycnJ1Bcigq+vL/fc5D1D3kMZGRn0XG5uLvVlbGws+AoLC6O+OnfuDBEREZwvJycn6isgIIAbdU5JSaG+jI2NwcfHh3tub29v+lpXrVoV0tPTK+wrPDyc+urWrRuEh4fTcyUlJfD48WP6c1BQEDciy/oyMTEBb29v7rmJT0SEGjVqQFpaGj2Xl5cH9+7dAwD5NS4iIoJe43r27AmhoaGcL2dnZ/pzaGgoN4qamppKfcmucb6+vvS1rlmzJm3qrIivyMhI6qt3796CLxcXF+5/y/pKS0urUCYAAKhVq5ZqVgEAwVdUVBT1RSYIiEgmIIqJiRGyiq2tLSCiaiYgqlevHpcJlFlFeS1hM0F6ejr3OVtaWgqurq7054SEBG77QHlZhf2cbdSo0WtnAvLZqNVqBV/KrML6ysjIgNu3b6u+Xux1qXHjxpyvwsJCuH//Pn3/KX3FxsZSX1lZWUIm+DNZJTAwkP6zmZkZxMfHc77KywTEV05ODvdc7DWRZCw2q2RmZoK9vb2qL/a/UZlVdDodPHjwABARjIyMYPr06dwkj0ESVeTb6l91GO6IyrV+/XqOFcauohQUFKCZmZnAMCOysbER7viw8FwLCwthdYcoMjISK1euTFd3CCuMaNOmTcIdH6LCwkJs0aKFwDAjsrW1Fe74sL4++eQTgWFGFB0djVWqVMF27dpxrDCiLVu2CHd8iHQ6HbZs2VLgmhLduXMHAfg7Pqyvzz//nHJNCcOMKDY2Ft966y1s27YtxwojsrKyEu74EBUVFWHr1q0pw4ywwogcHBwQgOeasr4mTJjAMcySk5PpuYSEBKxatarACiPavn27cMeHqLi4GNu1aydwTYkcHR0RgOeasr4mT57MMcySkpLouaSkJKxevbrACiPatWsXveOze/duDA0NpedKSkqwQ4cOAiuMyMnJCQF4rinra/r06VijRg387LPP6B0fopSUFKxRo4bANSXau3evwDVlfXXu3FmVFebq6srd8fH09MSSkhJ6fubMmfROFLnjQ5SWlobvvPOOwDUlOnDgAOWa/vLLLxgcHEzPlZaWYteuXQWuKZGHhwd3x+fp06ecrzlz5mD16tVx7Nix9I4PUUZGBr777rsC15To8OHDAteU9dWzZ0/hjg+Rl5cXveNDuKasr/nz5wtcUyKtVou1a9emd3zu3r2LBQUF9PyxY8fonShyx4f11adPH+GOD5Gvry8aGRlx0ymsr0WLFglcU6KsrCysU6eOwDUlOnnyJBobG3PTKeS9W1paiv379xfu+BD5+fmhkZERN53C+lq6dKnANSXKycnBevXqCVxTojNnzgjTKezf1MCBAynX9MKFC5iRkUHPBQYGorGxMb0T5erqisXFxfT88uXLhekUotzcXGzYsKHANSW6cOGCcMeH9TV48GCBa0oUFBSExsbG3HQK62vVqlXCHR+ivLw8NDU1xaZNm9LpFPbae/nyZeGOD+tr2LBhwnQKUUhICJqYmHDTKayvtWvXCnd8iAoKCrBJkybYpEkTOp3C+rp+/bpwx4f1NXLkSMo1JdMpROHh4VipUiWBa0q0YcMGgWtKVFhYiGZmZti4cWM6ncJee2/evKk3q2g0GmE6hYhkFSXXlGjz5s2qWUWn02GLFi0ErinR7du39WaVTz/9VOCaEsXExGCVKlUErinR1q1bBQY7UVFREZqbmwtcU6K7d+/qzSpffPGFwGAniouLw7feekvgmhL99NNPerNKmzZtBK4p0f379/VmlYkTJwpcU6KEhASsVq2aalbZsWOH3qzSvn171azy8OFDLqsoM8GUKVMErilRcnKy3qyye/duYTqFqKSkBN9//33VrPJfFlTwjqjhi+g/QPfv31d948bGxgp/UKzc3d25PyhW+fn5wh8Uq4CAAO4PSqkHDx6oAnnj4+PR09NTry82ZLMqKCjA+/fvc2GWVWBgIBf+X8dXQkKCELJZPXnyhAvZrAoLC/X6evHiBRf+lXJ0dORCNqvExET08PBQ9eXh4aHqS6fTCV9KWL18+ZIL/0o9fPhQ1VdycrIQ/lk9ffqUC9msioqK0MHBgQvZrIKCgriQLfPFhmxWKSkpQvivqK/i4mK9voKDg/X6evToEReyWaWmpqKbmxsXzlh5enpyIVvmiw3ZrEJCQoSQzcrJyUnVV1pamhD+WXl7e3Mhm1VJSYleX6GhoULIZvX48WMuZLPKyMgQwr/SFxuyWZWWluK9e/e4kM0qPDxcCNlKX2zIZqXVaoXwz8rHx0d1rKq0tBQdHBxUfUVERAghm5Wzs7Oqr8zMTCFks/L19eVCtswXG7JZRUZGCiGblYuLCxf+WWVnZwshm9WzZ8+4kP06vqKiooSQzcrV1ZUL2axycnKEkM3q+fPnXMiW+WJDNqvo6GghZFfUV15enhCyWfn5+XEhW6n79++r+oqNjRUWBFm5ubm9cSbw9/fXmwn0ZZW4uLg3zioFBQXlZpU3zQQkq6hdS/RllfIyQWBgYLmZQM1XYmLiG2cVnU5XblbRlwn0ZZWkpKRyswq7IMiqvEzw8uVLbkFQqfKyyptmgvJ8VSQTvGlW+S+rol9EDfgWgwwyyCCDDDLIIIMMMsggg/4SGfAtBhlkkEEGGWSQQQYZZJBBBv0jZfgi+g/Qy5cvQe3OdGpqKldMoFRoaKgqr6ygoIArmFAqJiaG26CtVFBQkF5fbDGBzJcaF6ywsJArmPgrfaWlpen1FRYWpupLp9NBWFiY6mNjY2O5MpnX8ZWens6VO72Or6KiIq5gQuaLLZOR+VLjXGVkZHBFDjJfalyw4uJivb7i4uLe2JdWq+UKE5QKDw9X9VVSUsIVXygVHx8PWVlZqueDg4NVfWVmZnLlTjJfaryykpISrqRL5ost3/krfUVERKj6Ki0theDgYNX3bkJCwhv7ysrK4gomXscXIur9m0pISOBKgWS+1Fih2dnZXMGEUpGRkaoM0/J8JSYmcqVASoWEhKj6ysnJ4Uqn/kpfSUlJb+wrNzcXYmJiVB8bFRWlytpDRL3XuOTkZK6s6HV85eXlcWVYf7UvtqxIKX3X3vz8fK50Sqno6Gi9DFN9vlJSUt7YV0FBAURGRr6xr/IywZtmlcLCwr8tq5SXCfRlFZ1OV25WedNMkJaW9qcywT8xq5SXCf5sVnnTTFBcXKw3E8TFxb1xJigvqxhUvgwc0X+ANm3aBPPmzYOQkBCBV1ZSUgJt27aFGzduQEpKisAFu3nzJgwZMgSeP38ucMFMTExAo9HAL7/8AjExMVC9enWOoxYTEwNt2rQBV1dXKa9sy5Yt8PXXX1NfLK8MEaFdu3Zw/fp1SElJgVq1anG+7Ozs4KOPPoJnz55JfX366aewY8cOKUctPj4eWrVqBc7OzlJemZWVFXz11VcQHBwsZZh26NABrl69KuWV3bt3Dz788EPw9fUV2KomJiYwbtw4+Omnn6Rs1YSEBGjdujU4OztL2ao7duyAL7/8kvpS8t06duwIly9flvLKHjx4AAMGDKC+WC6YiYkJTJo0CbZt2yZlqyYnJ0OrVq3AyclJyivbtWsXTJ8+nbbssa+XkZERdO7cGS5cuCDllTk5OcEHH3wAPj4+AlvV2NgYpk6dCj/88IOUrZqamgrm5ubw6NEjKa/M2toapkyZQi+KLH/L2NgYunTpAufPn5fyypydnaFv377g7e0tcNSMjY1h5syZYGlpKeWVpaeng7m5OTg6OkrZqvv374dJkybRMMj6MjExge7du8OZM2ekvDJ3d3fo1asXeHt7Cxw1Y2NjmD17NmzYsAEiIyMFXllmZiaYm5vDgwcPpGzVQ4cOwfjx4+HFixcCr6xSpUrQs2dPOHXqlJSt6unpSfmnSraqkZERzJs3D9atWyflqGVnZ4O5uTk4ODhIOWpHjx6FL774AgIDAwVfJiYm0KdPHzhx4oSUrerj4wPdunUDT09Pga1qZGQEixYtgtWrV0NERITAMM3NzQVzc3O4d++elK3622+/waeffgqBgYECW7VSpUrQr18/OHbsmJSt+uzZM+jatSs8ffoUcnNzBV9Lly6FlStXSpmveXl50KpVK7hz547U15kzZ2DMmDG0aZZlq1aqVAkGDBgAR44ckbJV/f39oVOnTqq+VqxYAcuXL4ewsDCBrVpQUACtWrUCe3t7KVv1/PnzYGFhAf7+/gJbtVKlSjBo0CD49ddfpQzTly9fQseOHcHDw0NgqxoZGcGqVatg6dKl1BfLCi0sLIRWrVrB7du3ITU1lbJoyXNfvnwZRo4cSX2xrNBKlSrBkCFD4MCBA1JfISEh0L59e3B3dxfYqkZGRrBu3TpYvHgxhIaGCmzVoqIiaNOmDdy6dUvKVr169SqMGDEC/Pz8BLZqpUqVYNiwYWBtbQ2xsbHCtTc8PBzatWsHbm5uUrbqhg0bYOHChdQX+3qRTGBjYyNlq964cQOGDh0Kz58/F9iqJiYmMGrUKNizZ4+UrRoVFUUzgYytunnzZr1ZpV27dnDjxg0pw9TW1hYGDx6smlXGjBlDs4oyE5Cs4uLiIs0q27Ztgzlz5kBISIiQCRAR2rdvD9euXZP6sre3LzerbN++XcpWTUhI0JtVfvrpJ5g1axZdgJRllStXrkizioODA5dVlJlg/PjxYGVlJWWYJiYmQqtWreDx48fSTLBz506YMWOG1JeRkRF07NgRLl26JM0qjo6O0L9/f6kvY2NjmDx5MmzZskXqKyUlBczNzVWzyu7du2HatGlcJiC+SCaoaFZR+po+fTr88MMPUrYqyQQPHz6UZgJra2uYPHmyNBMYGxtD165d4dy5c6p8+v+qDBzRf5FYrhIwvDJ7e3s8efIkx42DP3hlS5cuxfj4eIE3Rloijx07hr6+vhyrDBhe2bNnz3D58uXcOfijvXLLli2Yk5PDMQ2JrzFjxqCdnR2ePXtW8NWiRQtcsmQJxsXFCWxU4uvIkSPo5+cn+CLtlb6+vrhq1SrBV5cuXXDz5s2YnZ3NsQMBXvHKbG1t8cKFC1Jf33zzDcbGxgpsVNISeejQIXzx4oXgi7RXenl5CRw0gDKO2qZNmzArK4tj4RFfFhYWaGNjg5cvX+Y4ewBlvLJFixZhdHS0wEYlvLJff/0Vg4ODObYb8TVlyhT09PTEDRs2cCxGgDKOmqWlJWZmZnLMOYBXvLLff/8dr127JvgyMzPDhQsXYlRUlMBGJe2V+/fvx9DQUMEXaa/08PDATZs2Cb7ef/993LBhA2ZmZnIMNeJr1KhReP36dbxx44bgi7RXRkZGCmxU0l65b98+jIiIEHyR9kp3d3fcsmWL4KtDhw64fv161Gq1HKsM4BWv7OrVq2hrayv4Iu2V4eHhAhuVtFfu3bsXo6Ojpb4mTpyIbm5uaGVlJfhq3749rlu3DtPT07F169aCrxEjRuClS5fQ3t5e8EXaK8PCwnDy5MmCr759++Lu3btpwyJ7nrREuri44Pbt2wVf7dq1w7Vr12J6ejq2b9+eO0faKy9evIgODg4cx5H4+vrrrzE0NFRgo5L2yl27dmFiYiLHDiS+xo0bh48fP8ZffvmFY30ClLFVV69ejampqdixY0fB17Bhw/D8+fP44MEDwRdp1QwODsYvv/xS+Fvv3bs37ty5E5OTkwVfpNH60aNHuGfPHsFXmzZtcNWqVZiSksIxlAFesVXPnj2LTk5Ogi/SqhkUFIRfffWV4KtXr164Y8cOTEtLk/r6/PPP0dHRUWCjApSxVb/77jtMTk7mWMXE18cff4ynT59GV1dXwRdpr3zx4gXOnTtX8NWzZ0/8+eefUavVCr5Ie+WDBw/w0KFDgq9WrVrhihUrMCkpiWPvArximJ46dQrd3d0FX6S9MjAwUGCjApQ1bVtZWWF2djbHqwZ4xVZ1cHDAo0ePCtcSc3NzXL58OSYmJgqMW+Lrt99+Q09PT+FaQpq2/f398ZtvvhF8de/eHX/88UfMzc2V+ho7dizevXsXT5w4Ifhq2bIlLlu2DBMSEgRmK2m0Pn78OHp7e0t9zZgxA58/f47Lli0TfHXt2hW3bt2Kubm5+M4773Dn2Kxy6tQpvVll8ODBgq+BAwfi0aNH8dmzZ6pZxdfXF1esWCH1RbIKyzkmvsaMGYO2trZ47tw51UwQFxcnsFEJW/Xw4cMYEBAgzSpTp05FHx8fXL16teCrc+fONKuwPGGAV1nl1q1beOnSJcFX8+bNcfHixRgTEyOwUUlW+fXXX8vNKuvWrRN8derUiWYVlo8LALRp28bGBq9cuaI3qyjZqCSrHDx4UJpVSCZ4+vSpNKt07NgRN27ciJmZmRyHlvgiWeX69evSrLJgwQKMiooS2KhsVgkLC1PNBB4eHrh582ZpViGZgOWqArxiq167dg1tbGz0ZpX/ssDQmvvvEfsHpMRkPH/+nELIZZiMLVu20Mcqq6eTk5MpXFiGybC1taUBoEGDBjhr1iyuepqFCysxGf7+/mhqakovkkpMhpWVFXfxZjEZKSkpFC4sw2TY29vTD2gZJoOFCysxGQEBAfSLFwtsJ614O3bs4C7eLCYjLS0N+/btSy9GSkzGvXv36AeODJMxZcoU+txKTMaLFy8oVFuGydi1axd38WYxGRkZGTT0yDAZ9+/fp2FMhsmYPn06d/Fev349bcULCgqiXwhlmAxra2vu4s1iMrRaLfbv358LFTt27KCteA8fPqQXSxaTQXzNmjWLPrcSkxEcHIwtWrTgLt4sJuPAgQPcxZvFZGRlZdEwJsNkODk50YuSDJMxZ84cLlQQYHtJSQmGhoaiubk5d/FmMRmHDx/mLt4LFy5Ee3t7zM/Px+zsbBw4cCAXKlhMhrOzMw2gMkzG/PnzuVDBYjLCwsKwVatW3MWbxWQcP35cuHgTTEZubi5d0JJhMlxdXSm0ncVkEF+LFi3iQgWLyYiIiMA2bdpwF28Wk3Hy5Enh4k185efn45AhQzhfLCbD3d2dLuLJMBlLly7lQgWLyYiMjMR27dpRX0pMxpkzZ+hjlZiMgoICGl5lmAwPDw8a2GWYDDZUKzEZ0dHR2KFDBwQAKdLr/Pnz9LEsJiMvLw91Oh0OHz6c+lJiMjw9PfHdd9+lvgjSizTlsguA7du35zAZsbGx9Iu9DJNx+fJl+lglJqOoqIiGahkmw9vbm36RkGEy2FCtxGTExcVh586dEQCkmIxr164JvgjSq6SkhFsAVGIyfHx86KKnDJOxYcMG+lglJiMhIYEuOMgwGTdu3KDBV4bJ0Gg09LmVmIxnz55h/fr1hUxAMBmbN2+mj1ViMhITE7F79+7UlxKTcevWLZoJZJiMTz/9VG9WIYuxxBeLydi2bdtrZRUWk3H79m0uqygxGePGjROyCmn1V2YVZSb46aefVLNKamoq9u7dm/oimYBklTt37ujNKhMnThSyCskEgYGB9IsXWWhgkV47d+58rayyc+fOCmeVqVOnclmFzQTKrPLJJ59wWWX37t0VziokE5Cswi4A1q1bV8gqM2bMELIKafUPCgqiXwhlWWXfvn1CViGZIDMzEwcMGEB9ffjhhxzS69GjRzQTyJBe7AJgly5duEwQEhJCF6/VkF7/VYHhi+i/R+vXr1d944aHh0tZdERHjhzB7du3S6un8/PzceHChQKLjsjBwYH7g1Jqw4YNeOjQIamvyMhIXLRoEdrb20t9HTt2TGDkERUUFODChQsFFh2Ro6Mjrl27VhWTYWlpKbDoiKKjo6WMPKITJ05IWXSIZVXtixYt4kI2q0ePHuGaNWtUMRk//PCDwKIjiouLkzLyiE6ePIlWVlZSTIZOp8PFixcLLDoiZ2dnKSOPaMuWLQKLjighIQEXLFggMPKIzpw5I2XRIZZVon/zzTcCi47I1dVVyqIj+vHHHwVuLlFSUhIuWLBAYOQRnT17VsqiQyzDpCxZskTg5hK5u7tLublEVlZWAouOKCUlBefPny+w6IguXLggZdERX0uXLhUYeUsDCAQAACAASURBVERPnz6VsuiItm/fLrDoiFJTU/X6unz5spRFh1iGb/n2228FRh6Rl5eXlEVHtHPnToFFR5Seno7z588XWHREV65ckbLoEMvwGsuXLxcYeUS+vr5SFh3Rrl27BBYdkVarxfnz5+P169elvq5fvy7l5hJf3333ncDNJSJ3ltRwFHv27BG4uUSZmZk4f/58VRbdjRs3pNxc4mvlypUCN5coICBAys0lsra2Fri5RNnZ2Th//nyBm0t069YtKTeX+Fq9erXAzSV68eKFlJtLtH//foGbS5STk4Pz588XuLlEt2/flnJzia81a9YI3Fyi4OBgKTeX6ODBg7hz504pJiM3NxcXLFggcHOJ7O3tufCv1Lp16wRuLlFYWJiUm0t06NAhgZtLlJeXhwsWLOAWBFndu3dPys0l0pdVIiIi9GaVo0ePlpsJ1LLK/fv39WaVjRs3CtxcoqioKJpVZNfeY8eOSbm5iK8ygb6soi8TbNq0STWrxMTE6M0qv/32m2pWIZlALas4OTnhmjVrVDNBRbKKra2t1NepU6ek3FzEV5lAX1aRcXOJtm7dqjerzJ8/XzUTlJdVlixZoppV3Nzc/lRWmT9/Pl0QNOiVKvpF1IBvMcgggwwyyCCDDDLIIIMMMugvkQHfYpBBBhlkkEEGGWSQQQYZZNA/UoYvogYZZJBBBhlkkEEGGWSQQQb9X5Xhi+g/QHfv3lXl9MXGxoKbm5sqR83FxUWVh1dQUAD29vaq3Dl/f38IDAxU5UndvXtXldMXHx8Prq6uqr5cXV1VeXiFhYVgZ2en6isgIAACAgJUfd27d0+Vh5eQkAAuLi6qvtzc3FR5eDqdDuzs7FS5c4GBgeDv76/XlxoPLzExEZydnVV9ubu7q/LwioqK9Pp68eIF+Pn5qfpycHBQ9ZWcnAyPHz9W5bu5u7ur8vCKi4vBzs5OlTv38uVLeP78uaqv+/fvq/LwUlJSwMnJSdWXh4eHqq+SkhK9voKCguDZs2d6fanx8NLS0uDRo0d6fanx8EpKSuD27duqPLyQkBDw8fFR9fXgwQNVHl56ejo8fPhQle/m6empysMrLS0FOzs7VV+hoaF6fTk6Oqr6ysjIAEdHR72+1Hh4iAh2dnaqPLywsDDw8vJS9fXw4UNVHl5mZiY8ePBA1Ze3t7cqD688X+Hh4eDp6anKnXv06JEquzcrKwvu37+vysPz9vZW5eEhItjb26ty+iIiIuDp06eqvpycnFR5eDk5OXDv3j1VX76+vqqMXOJLjdMXFRUFHh4eqr4eP36sysjNzc2Fu3fvqrJonz17RrFVar7Urr3R0dHw5MmTN/KVl5cHd+7cUfX1/PlzvazQO3fu6M0E7u7uqr6cnZ1V2b35+fl6ffn5+cGLFy/0+lLLBHFxceVmFX2Z4M9mFbVM8Geyik6n0+vrz2SVxMTEN84q5WWC8rKKvkyQlJT0xlmFZAJ9WUVfJnBwcFDNBOVllSdPnrxxVqlIJlDzlZqaqjerGFQBVWQj6V91GMqK5Pr8889peyzbyIZYVgr09ttvc41sbIkFaadVtscilhVMdO7cWdrIhlhWTACSRjaiCRMm0JZWtpENsawUqGbNmrT6XVkWsX37dtrItmHDBq6UITs7G7t27SptZEMsKwAASSMb0eTJk6XtsYhlBQDvvvuutD0W8VU7rbKRDbGs+KJHjx60+l1ZFuHk5MQ1sinLIqZPny5tZEMsKwCoXbu2tD0WEXHv3r20kU1ZFpGbm4u9e/fmGtlYXy4uLghMe6yyQGrmzJm0pVVZFpGQkIB169aVtscivmqn7dy5My2QIr7y8vKwb9++FFOjLLZ68uQJGhkZ0fZYOzs7ztecOXNo9buyLCIxMRHr169PMTXKsohDhw7R9lhlWUR+fj72799f2h6LWFYKZGRkJLTHEs2bN0/aHouImJycjI0aNZK2xyKWFV/AHy2tygKpgoIC/PDDDymmRlkW4e3tjcbGxti0aVOcN2+eUBaxaNEiiqlRlkWkpKRg48aNpe2xiK/aaTt06CCURRQWFuKgQYOk7bGIZaVAJiYm2KRJE5w7d65QFrF06VJpeyxiWYlS06ZNaXusskCKtNMq22MRywo5hgwZIm2PRUT08/PDSpUqURyMsixi+fLl0vZYRMS0tDRs3rw5bY9VFkhduHABAcowNWx7LGJZ8cXQoUOl7bGIZaVAlStXxsaNG3PtsUSrVq2StscilpU7vffeexRTc+rUKc4XaadVtscilpVhjRgxgmJq9u7dyxVbvXz5EqtUqYKmpqY4e/Zs2h5LRPBUyvZYRMSMjAxs1aoVxdQoC6SuX78ubY9FRNpOS9pj9+zZwxVbBQcHY9WqVbFRo0ZCeyziq3Za0h7LFkhptVps06YNxdSw7bGIiDdv3pS2xyKWlRWNGTMGK1euTBvl2WKr0NBQrFatGtcey/ratGkT1x7LFkhlZmZi+/btKaaGbY9FLCtRAkl7LNHYsWOl7bGIZaVANWrUkLbHIpYVvsAf7bEkExBfWVlZ2LFjR649lvV19+5daXss0RdffCFtj0WUZxU2E5B2WmWjPGL5WcXBwYHLKspMMHHixHKziqw9FvFVk76yPRaxLBN069ZNNas8fPiQZhWSCVhfU6ZMkbbHIiLGxsZirVq1VLMKaaclmYDNKrm5udizZ0/VrPL48WNpeyzRjBkzVLNKfHw81qlTh2YVZSYgTfrKRnnEskzQp08f1azi6upKswpplGd9zZo1S29WqVevHpcJWF8HDx6kmUCZVfLz87Ffv37SpntEPqssWLBAyCpff/21alZJSkrCBg0a0KZ7tQKp/6LA0Jr775GSB9WqVSs8cuQIlpSUcNgF+KNCfPTo0ejn54eISPEZ5GjQoAGuX78ec3Nz8fnz5wIbqVevXmhvb4+IiEuWLOHOvf322zhz5kz6wUGQDeQwNzfHQ4cOYXFxMZ46dUrwNXLkSHz27BkiosAyq1+/Pq5duxZzcnIwICBA4Mb17NkTb9++jYiI3377LXeuRo0aOGPGDPolR8kya9myJR48eBCLi4vx7Nmzgq8RI0agr68vIqLAMqtfvz6uWbMGs7OzMSgoSPDVo0cPvHXrFiIifvfdd9y56tWr4/Tp0+kHmpJl9t577+H+/fuxuLgYL168yJ0zMTHBYcOGoZeXFyKiwDKrV68erly5ErOysjA0NFTw1a1bN7SxsUFExDVr1nDnqlWrhlOmTKFfJpQssxYtWqC1tTUWFRXh1atXBV9Dhw5FT09PRESBZVa3bl387rvvMDMzEyMiIgRfXbt2xd9//x1LS0tx/fr1gq/JkyfTLxNKllnz5s1x9+7dWFRUhL///jv33jU2NsYhQ4agh4cHIqLAMqtTpw4uX74cMzMzMSYmRvDVpUsXvHr1KpaWlqKlpSV3rmrVqjhx4kT6ZULJMmvWrBnu2rULdTod3rp1S/D10Ucf4ZMnTxARBZZZ7dq1cdmyZajVajE+Pl7w1blzZ7x8+TKWlpZyKCbia8KECfTLhJJlZmZmhjt27ECdTod2dnaCr0GDBqGbmxsilgVIpa8lS5ZgRkYGJicnC746duyIFy9exNLSUvzxxx+5c2+99RaOGzeOhnaCs/k/7Z15XBVl+8avYQc5uOMGapZmpplWtv7qzV7fV7Oy1bLNFjPXNCH3TBPL1NQ0930ldwEFF1ZBRRRE3BAXFhEFEUHWw4Fz//7AmfcM88yBcK3u7+dzPgk3z3A1Z5jneuaB+5JfHh4eNG3aNDIajbRnzx6VLkmS6MUXX6T9+/cTkTqKCaiIYRk6dCjl5ORQTk6ORtejjz5Kvr6+ZDablYddlrreeecdxbTLsTHyq1mzZjR16lQyGo0UEhKi0fV///d/FBkZSUTqKCagIu5k8ODBlJ2dTXl5eRpd7dq1o3Xr1pHZbKaZM2eqag4ODvT2228r5liOZ7HU9dNPP1FJSQlFRERodL3wwgsUERFBROooJlnXwIED6erVq1RYWKjR9cgjj9CaNWvIbDYrD7ssdb355puKOe7QoYOq3rRpU/Lx8aHi4mLav3+/Rtdzzz1H4eHhRKSOYgIqYli+/vprysrKopKSEk1eYtu2bWnVqlVkNptp3rx5Gl29evVSzHGnTp1U9caNG9OkSZOouLiYoqOjNXPcs88+S6GhoURUYSAtawaDgfr370+ZmZlUVlam0dWmTRtasWIFlZeX08KFC1U1e3t7ev311+nUqVNERErciKWuiRMnUlFRER05ckSj65lnnqG9e/cSkTqKSdbVr18/ZfFVWVfr1q1p2bJlVF5eTkuXLtXoeu211+jkyZNEREqsh/xq1KgRTZgwgQoLC+no0aMaXV26dKE9e/YQEdHQoUNVNVdXV/riiy+UxVflLEZLr7JixQpVzc7Ojl599VVKSEggIlLiM+SXu7s7jR8/ngoLC+n48eOaa/epp56ioKAgIlJHMQEVnuCzzz5TvEqtWrVUdUuvsmbNGo0uS08gR2rJL0uvcvr0aatepXIWe2Wv4ubmpqq3atWK5s+fT2VlZaooJqBi7v3vf/9LR48eJSJSoqvkV4MGDWj06NGUn59PSUlJGl2dO3emgIAAIiIaOXKkqubi4kKffPKJ8uCzXr16qrqlV9m4caNGV7du3RSv8p///EejS/Yq58+fF3oVPz8/MpvNmiz2yl5FjiWSXy1btqQ5c+aQyWRSRTHJuv79738rXuXVV19V1evXr0/e3t6Ul5dHKSkpQq+ybds2MpvNqigmWZelV5Hjf+RXixYtaNasWWQymVRRTEDF3Nu1a1fFq/yTAS9E/zr07dtX+GSKqOJpS/PmzTW5RjKzZ8/W5BrJlJeXU5cuXXRzjSIjI3V30YgqzIXoyRRRxQ5MixYt6OOPPxa2Np87d65wF03W9cwzzwifTBFVtNK2fDJVuYX4V199JXwyRVSx09GyZUvhLhpRxVOz9u3bC1uum81mev7555VdtMqtzWNiYhRdohiWgQMHCnfRiCp2FB544AH68MMPha3NFy9eLNxFk3W9+OKLyi5a5dbmcXFx5OnpqeyiVW4hPnjwYOEuGlHFk/tWrVpRnz59hK3Nly9fLtxFk3X961//UnbRKrc2P3bsGHl4eAh30YgqHoTIu2iVY1hu3LhBDz74oHAXjahih0+0iybreuWVV6h79+7CGJbjx4+Th4eHsotWOe5kxIgRwl00ooon5K1bt6bevXsLY1jWrVsn3EWT+c9//qPsolWOYTl9+jR5eHgId9GIKsyFvItWOYalsLCQ2rRpo+yiVY472bBhg3AXTaZHjx7KLlrlGJYzZ86Qh4eHsotWOe5kzJgxyi5a5RiW4uJiatu2rXAXjagivsVyF61yrMjrr7+uyTqUOXfuHHl4eAh30YiIxo8fL9xFI6rYnX7kkUeEu2hERNu3b1d20UQxLL169dLkMstcuHCBPDw8NBmMMhMnTqQnn3xSGMNiNBrp0UcfFe6iEVXs8Mm7aKIYlnfeeUfJZa6sKzU1lTw8PJRdtMpxJ5MnTxbuohFV7E536NBBk8EoExQUpOyiiWJYevfuLdxFI6rYGfL09BTuohFV5E+KdtGIKnanO3bsqOyiVY5h2bt3r+5v1hAR9enTR9lFqxzDkpGRQZ6entS3b19hDMu0adOEu2hEFbvTnTt3VnbRKsewhIaGqn6zprKujz/+WLiLRlTx2yLNmzenTz/9VBjD8uuvvwp30WRdTz75pLKLVtkTREREaHKZLfnss89UXsXyGsnKyqIWLVoId9GIKmKLRLtoRFV7laioKFUuc2VdX375pa5Xyc7OphYtWuh6gt9//124i0ZUMZc8++yz9NprrwljWKKjo616lf79+ytepbInyMnJoZYtWwp/s4aIaOHChdXyKqIYlsOHD5Onp6cql9mSQYMGKV6lsieQvYroN2uIKiIDq+NVRDEsVXmVoUOHKl6lcgyL7FUq5zLLrFixQvEqIk/w8ssvU48ePYQxLAkJCVa9yvDhw+nZZ58VeoL8/Hx66KGHlFxmUTzMP5XqLkQ5vuU+IC8vD7Vr1xbWCgoK4OzsDFtb2z89trS0FOXl5XB2dhbWb9y4AYPBAEmSaqTLyckJdnZ2f3qsyWSCyWSCi4vLbddVWFgIR0fHv5WusrIyGI1G1KpV67brKioqgr29Pezt7Wukq6SkBK6urveVrvLychQXF9+XuoqKimAwGHR1ubq6wsZG/Kf71o5dXFwMW1tbODg4/OmxZrMZhYWF950uIkJ+fj7c3NyE9fz8fNSqVavGumxsbODo6Hhf6SopKYEkSVZ1ubm5Ca9dIsKNGzd0j32rugDAycnpjuhycXGp0RxnNBpBRHdE163MvUajEWazWXfutaarqmPfSU9wL3WVlZXdd3Pv/eoJTCYTSktL74gnYK9ye3X9k6lufAsvRBmGYRiGYRiGYZjbQnUXouJHHtX/JikA8gGUAyirzjdkGIZhGIZhGIZh/tnc0kL0Ji8TkTjrgGEYhmEYhmEYhmEqwTmi9wErV67UzYFMSUnB2rVrdTOMAgICdLOVSkpKsHDhQt1spUOHDiEgIEA3W2nVqlW62UppaWlYs2aNrq4dO3boZisZjUYsXLgQKSkpwrGHDx+Gv7+/rq7Vq1cjPj5eqCs9PR2rV6/WzYEMDAzUzYEsLS3FwoULdXMgjxw5Aj8/P928xbVr1+rmLWZkZGDVqlW6eYtBQUG6OZAmkwmLFi3SzYGMi4vD9u3bdXWtW7cOcXFxQl1XrlzBypUrdfMWd+3apZu3WFZWhkWLFunmQB49ehRbt27VzVtcv369bg5kVlYWVqxYoatrz549urrKy8uxaNEi3RzIY8eOYevWrbp5i76+vro5kNnZ2Vi+fLluDuTevXsRHBwszFuUdenlQB4/fhybN2/W1bVhwwbdHMhr165h2bJlujmQISEhujmQZrMZixcv1s2BPHHiBDZt2qSbA7lx40bdHMjr169j6dKlunmLoaGhujmQRIQlS5bo5kCeOnUKGzdu1M1b3LRpk24OZF5enlVd4eHhunmLRISlS5fq5kAmJiZiw4YNurq2bNmimwN548YNLF68WDcbOiIiArt27bKqSy9vMSkpCX/88YduDuTWrVt1cyALCgqwePFi3bzFyMhI3WxoIsKyZct0dZ09exa+vr66eYvbtm3TzYEsLCzEokWLdHXt378fgYGBurqWL1+um7d4/vx5rF+/XleXn5+fbg5kUVERFi1apJsDeeDAAezcuVM3b3HFihW6niA5ORnr1q3TzYH09/dHVFSUcI4rLi7GokWLdHMgo6OjsWPHDl1dK1eu1M2BTE1NrdKrWPMEixYtqrFXWb16ta5XuXjxolWvsnPnzio9gTWvYs0TrFmzRterXLp0CatXr9b1BIGBgQgPDxfqkj2BnleJjY29o15FLxta9gTWvMq2bdt0PUFVXsWaJ9i9e3eNvUp8fLxVr+Lr61ulV9HzBEw1qE5HI70XgGQAcQBiAfSv6uu5a66Yxx9/XGkJLXeFk7vo7d+/n+zs7FTZSpaddfv160cAVNlKche99PR0pe20ZVc4ueOXnMVoma1k2d3viSeeIACqrnCyrujoaLK3t1dlK50+fVoZO2DAAAKgylaSu+hlZGRQ06ZNCYCqK5ysS85ilHMgFyxYoOqi9/TTTxMAVVc4uYteTEwMOTg4qHIg5Xb7RBVZjABUeYuyritXrpCHhwcB6hxIWdfKlSsJqIiJkDvYWnbRk6N0LHMgZV1HjhwhR0dHVQ6k3G6f6H9ROnXq1FG6wsld9K5evUrNmzcnQJ0DKXf3k7MY5RzIefPmqbroyVE6ljmQche9o0ePkpOTkyoH8sSJE8pYuT29nLe4du1apYue3I0QUOdAyrrk9vSWeYuWXfTkKB3LHEhZ17Fjx8jFxUWTAykjt6d3c3NTOtjKuuSuf8D/ciAjIiIUXXIWo5y3OHfuXFUXPTlKp0mTJkoHW7mL3vHjx8nV1VXJgZw8ebISWUT0vyxGyxxIuYtebm4utWrVigB1DqTc3U/OYpTzFufMmaPq+CtH6TRu3FjpYCvrOnnypBJr1KVLF/rxxx+VeAKi/2UxWuZAyh1/5a5/wP9yIMPCwhRdfn5+ii65g61lx185SscyB1Lu+Hv69GmqXbu2EnswadIkJZ6A6H9ZjK6urkoHW7mzbmFhIbVu3ZqAivgKOW9R1rVz504ljkHuYGvZ8VeO0rHMgZR1nTlzhurUqaPomjhxoqqzrpzFaJkDKXfWLS4upocffpiAivgKOW9R7kS8a9cuRZfcwday468cpSPnQG7ZskXp+Hv27FklWsEyG1rWJedGW+ZAyrqMRiM98sgjSkyEnA0t69q7dy9JkqTKgbTsrCtH6cg5kJs3b1Y6/p4/f57q16+vxDHIHWxlXXIWo2UOpNzx12QyKZE1rVq1UjrYyh1/Q0NDSZIkVQ6kZWddOUrHMm9R1pWcnKxEPsjZ0DExMYouOTdazoFcsmSJ0vG3vLyc2rdvr8RXyB1sZV3h4eFkY2OjyoG0zKeUo3RkXRs3blQ6/qamppK7uzsB6hxIWZecxejs7ExvvPEGLV68WNXxV47SadmypdLBVtYVGRlJtra2qhxIy866cpSOZTa0rOvixYtKbJZlB1tZl5zFaJkNbekJ5CgdkVc5cOCAVa8iR+mIvMqlS5esepXFixervMrChQtVnkCO0qmOV5k6darKq8hROpbZ0LInuHz5shLnJXsVS08gx+tZZkNb6pKjdERe5fDhw+Tg4KDyBJZeRY7SEXmVzMxMjVex9ARybrRlNrSlV5GjdEReJTY2VvEEzz33nMYTyFE61fEqlT2BHK/n6OioZENbehU5SkfPqzg7O6s8gRxjSETk7e2t61Xk3GhLr7Jv3z5Flxyvp+dV5Cgd2av4+/sLvYrc1d7Sq/yTQTW75t7qr+Y+T0QZkiS5A9grSVIiEe2z/AJJkvoD6A8AzZs3v8Vv9/dE7ijZsGFD5SV34HJwcAARwcXFRanVrVtXM7ZevXpwd3eHu7u70hHPzs4ONjY2sLOzUx1b7gwmj3Vzc1Nqlp0z5XqDBg00uuT/Ojs7V6lLrlvqsrW1rVKXwWBAw4YN4e7uLtSld76Aiu6Ocq1evXqasXXr1tXosrW1VV7V0fVnzpdcszxferrc3d3RsGFDpVOfjY2NUJfc/VIe6+rqqtQsO3qKdMmfk/VVdb7q1Kmj1GVdeufrTumqX79+tXTJ58vGxkapubu7K++jfGxXV1flXFelS+5iKtccHR2t6qpdu7ZQl/wzKTpflrrkmmWnvj9zvtzd3avUJXc2lCTJqi55bK1atazqql+/vuZ8ybocHR2Vc13V+1hZlyRJyv/TndBl+T5W/lm3PF9yx0VJkmBvb6/RJXcLlY9tqatOnTp/SpeDg4NSa9CggVVdludL1iVrstQlj7WcS6zpcnd3V7rR2tvbw8bGpkpdlnOJZYdKy/Mlv+SunH9Gl/z/JeuSrw97e/tq6XJ3d9foAtQ/U9Z0VTXHWeqysbH5U7qqmuMq67KcS0Tny5ouy7lXpMtgMCjn+s96gqrOl2juFXmCqq6vms697u7u1dYlzyOWc5zlXCKa42qiSz7Xf0ZXdebemryPsuesyqtUxxPo3bNr4gmq6+30PIFojrP2PlrT5e7uLtQlmuOYalCd1Wp1XgAmAvC29jW8Iypm69atmtwsmdTUVGFulkxwcLAmN0umuLhYmD0qExcXp8nNqqyrcm6WzMWLF4W5WTIhISGajE+ZkpIS2rhxoyY3S+bo0aOa3CxLtm/frqsrPT1dmJslExYWpsnzkjEajbRx40ZNbpbMsWPHNLlZlXVVzs2SycjIEOZmyYSHh2vyvGRKS0tp48aNuvlUCQkJmoxPS/z8/DS5WTJXrlwR5mbJREREaHKzZEwmE23YsEFX1/HjxzV5Xpb4+/trMj5lMjMzhRmfMvv27dPVJYdyV874lDl58qQw41MmICBAV9fVq1eFGZ8ykZGRmozPyroqZ2nKnDp1isLDw3V17dixQ5M9KpOdnS3M+JSJiorSZHzKlJeXW9WVmJhoVdfOnTs1GZ8yOTk5woxPmf3792syPmXMZjNt3LhRk/Epc+bMGWHGp0xgYKCurtzcXGHGp8zBgwc1GZ+WujZt2qTJ+JRJSkoSZnzKBAUFaTI+ZfLy8oRZmjLR0dGajE9LXZs3b9ZkfMqcO3dOmPEps2vXLk3Gp0x+fj5t3rxZV9ehQ4c0GZ/V1XX+/HlhxqfM7t27VTuRlhQUFNDmzZs1WZoyMTExmozPyroqZ3zKJCcnCzM+Zfbs2aPJ+JQpLCwUZo/KHDlyRJPxacmWLVt0daWmpgozPmWCg4M1eeQyRUVFtGnTJl1PEBsbq8n4tMSaV0lLS7PqVW7FE1TlVbZt22bVE1TlVaryBHq64uPjq/QqlTM+ZS5dulSlV6nKE9TUq/j5+el6lcuXL1fpVSpnfMqYTKYqvYo1T1CVVwkICKixV7Gm68SJEzX2BFlZWVa9yj8Z3OkcUUmSagGwIaL8m//eC+BHItqlN4bjWxiGYRiGYRiGYf6+3I34lkYAtt3c2rYDsN7aIpRhGIZhGIZhGIZhgFtYiBLRBQAdb6MWhmEYhmEYhmEY5h8Ax7cwDMMwDMMwDMMwdxXbiRMn3rVvtnjx4on9+/e/a9/vr8KMGTOQk5MDT09PpXOZTHJyMhYsWIA6deqourXJrF+/HgkJCWjWrJnSIUympKQEkydPhp2dHZo1a6Z0LpPZt28fduzYgUaNGqm67snMnDkT2dnZQl2pqamYN2+eri5fX18cO3ZMqMtoNMLHxwc2NjZCXVFRUfD399fVNXv2bGRlZQl1Xbx4EXPnzkXt2rXRqFEjja4NGzYgLi5OqKu0tBSTJ0+GJEnw8PDQ6Dpw4AC2b9+uq2vOnDm4cuUKPD09lU5q6Dg4gQAAIABJREFUMhkZGZg9e7aurk2bNiE2NhZNmzZVumDKmEwm+Pj4AACaNWumdMGUiY6OxtatWzVd92Tmzp2Ly5cvC3VduXIFM2fOhJubGxo3bqzRtWXLFsTExKBZs2YaXWVlZZg8eTKICB4eHhpdMTEx2LRpk6a7ncy8efNw6dIloa6srCz8+uuvMBgMQl3btm1DdHS0UFd5eTl8fHxQXl4u1HXkyBFs3LgRDRo0EOqaP38+Ll68KNSVnZ2N6dOnw9XVVajLz88PBw4cQNOmTVXdOWVdU6ZMQVlZmVBXXFwcfH190aBBA2HXPTkT2NPTU+myKnPt2jWrugICAhAVFSXUZTabMWXKFJSWlgp1xcfHY926dbq6Fi9ejOTkZHh4eGh0Xb9+Hb/88gtcXFzQpEkTjS45b7hJkyaqro5ARSO9n376CSUlJfDw8FC6hsokJCRgzZo1qF+/Pho0aKDRtXTpUpw/f154vvLy8jB16lQ4OzujadOmGl1yrm/Tpk2Fun7++WcUFxcLdZ04cQKrVq1C/fr1VZ14ZZYvX46zZ8/Cw8ND6WYqc+PGDfz000+6uuRcX73zNXXqVBQWFsLT01Oj6/Tp01ixYgXq1aun6kgqs2LFCiQlJcHT01Ojq6CgAFOmTIGTkxOaNm2quTfu2bMHwcHBaNKkiarbpKzrl19+QX5+vlDXmTNnsGzZMl1dq1atQmJiIpo1a6Z0DZUpLCzElClT4OjoKNQVEhKCPXv2oHHjxkJd06dPR15enlDX2bNnsWTJEqVraWVda9aswalTp+Dh4aHRVVRUBB8fHzg4OAjnuNDQUOzatQuNGzdWdXqWmT59OnJzc4Vz3IULF7Bw4UJdXWvXrsXx48eFuoqLi+Hj4wN7e3uhroiICAQGBqJRo0ZCXb/++usteRVrnuBWvMqsWbN0vUpaWhp+//13XV1//PEHjh49Cg8PD11PYM2r+Pn51cirXLp0CXPmzIGbm5vQE2zcuBGxsbHC82UymarlVSp3CJapjlfR8wSbNm3CkSNHrHoCQN+rbNmyRVdXVV7l119/rdKriDxUWVkZfHx8YDabhXPc4cOHb8mrzJgxAwaDQTjH/ZOZNGnS5YkTJy6u8gur09Hodr24a64YOWfPxcWFvv/+e1X3LTnfCDfzj3bt2qUa++9//5sAkI2NDX3yySeqLLLTp0+Tg4ODklm3ZMkSVde50aNHK8f+17/+pck+knPjnJ2dady4cSpdmzdvVsa2bduWgoKCVGP/+9//Kro++ugjVQfAM2fOkKOjo5JZt3DhQlUXtfHjxyvHfvHFF1V5iESk5LM5OTnRmDFjVB055SxG3MxE3LFjh2psz549FV19+vRRdQA8f/68oqtBgwY0f/58la4ffvhBOfYLL7ygykMkIiUb1cnJiUaNGqXqyOnv76+Mbd26NQUEBKjGvvHGGwSAJEmi999/X9VpLyUlRdFVr149mjt3rqq72+TJk5VjP//88xQbG6s6tqenp5Ld5e3trep8GRgYSJIkEQB68MEHyc/PT9V17u2331Z0vffee6pOexcvXiQnJyclg+23335T6fr5558VXc8++ywdPnxYpUvO+nR0dKQRI0aoOkzu2rVL0dWqVSvatm2bStd7772n6HrnnXdUnfYyMjIUXXXq1KFZs2apdE2bNk3R9cwzz1BMTIxKl5yp6eDgQMOHD1d1mAwODiYbGxsl42/Lli0qXX369FF0vfXWW6pOe5mZmeTs7Kzo+vXXX1WdVWfOnKno6tKlC0VHR6t0tW3bVtH1zTffqDo5hoaGKrpatGhBmzZtUun65JNPlGP36tVLlbeZnZ2t6KpduzZNnz5dpeu3335Txj755JN04MABlS45i9He3p4GDx6s6uS4b98+srW1VTL+NmzYoNL12WefKcd+/fXXVd1kc3NzycXFRcll/eWXX1QdTOfNm6eMfeKJJ2j//v0qXR07dlR0DRgwQNUxMSoqStHl6elJvr6+Kl1yPjMA6tmzp6qb7I0bNxRdBoOBfv75Z1Wn0IULFypjO3XqRJGRkSpdcj6znZ0d9e/fX9XdOTo6muzs7JQsvXXr1ql0ff3118qxe/TooeraWlRURLVq1VLyT6dMmaLStXTpUmVsx44dKSIiQqWrS5cuiq5+/fqpuigfPnxY0dW0aVNavXq1StfgwYOVY//3v/9VdW0tKSlR6Zo8ebKqU6icz4ybGZKhoaEqXc899xwBIFtbW/ryyy9VXZTj4uLI3t6egIrc35UrV6rmODmfGQB169ZNldNYVlZGrq6uSv7ppEmTVLrWrFmjjG3fvj0FBwerdP3f//2fouuzzz5TdVE+duyYoqtx48a0fPlyla4RI0Yox37llVdUmdJEpOhycXGhCRMmqOZeOZ8ZN7Ma9+zZoxr78ssvK7r69u2r6lZ84sQJq55AzmcGQF27dlXlNBKRkr3r7Oz8p72KnM9clVdp2LAhLVq0SDX3jhkzxqpXadCggaJr7NixKk+wZcsWZezDDz9MgYGBqrHdu3dXdH344YcqT3D27FmVJ1iwYIFK1/fff2/VqzRq1EjXE2zfvt2qV5HzmWWvYtkV+MKFC4qu+vXr07x581S6Jk6caNWryNmojo6O9N1336k8QUBAgDL3PvTQQ+Tv768a26tXL2WO6927t8qrpKamKnOvyKv4+PhY9SpyBqmjoyN5eXmpdAUFBVn1Ku+8846i691331V5gvT0dKteRc5n1vMqcv63g4MDffvttyqvsnv3bmXubdWqFW3dulXYufefCKrZNZcXovcBY8aMod9//13YHvrChQvUv39/3fbQixYtoilTptCxY8c0F39xcTH179+f1qxZI4yy2Lt3L3333Xe6bavHjRtHc+fOFUZGpKSkKMG+Il1LliwhHx8fYZRFSUkJff3117R69WphZERoaCh5e3tTRESEUNf3339Pc+bMEepKS0ujr776SjfKYtmyZfTjjz8KoyyMRiMNGDCAVq1aJdQVHh5OXl5eFB4eLoxmmDhxIv3222/CyIhLly7RV199pRtlsWLFCpo0aZIwyqK0tJQGDhxIK1euFEZZREZG0ogRIygsLEyoa9KkSTR79mxhZMTly5fpq6++0o2yWL16NU2cOFEYZWEymWjQoEG0YsUKYZTFgQMHaPjw4bpRFj4+PjRr1iyhrszMTOrXrx9t3bpVGBmxdu1a+uGHH4RRFmVlZTR48GBavny5MDIiOjqahg8frhtlMWXKFJo5c6YwyuLq1avUr18/3SiL9evX04QJE4RRFmVlZTRkyBBatmyZyoTJHD58mL755hvdKIupU6fSr7/+KoyyyM7Opn79+ulGRmzYsIG+//57YZRFeXk5ffPNN7R06VKhrtjYWBo6dKhulMW0adNoxowZwiiLnJwc6tevH23cuFGoa9OmTTR+/HhhlIXZbKZhw4bR4sWLhZER8fHxNGTIEN0oixkzZtD06dMpMTFRc43k5uZSv379aMOGDcIoi61bt9K4ceOEURZms5m+/fZbWrRokVBXQkICDR48WDfKYtasWTRt2jRh7FZeXh7169eP/vjjD2FkxPbt22ns2LHCKAuz2UxeXl60cOFCYZTFyZMnadCgQbpRFrNnz6ZffvlFGGWRn59P/fr1I19fX6Euf39/GjNmjDDKwmw2k7e3Ny1YsEAYZZGYmEgDBw7UjbKYO3cuTZ06VRhlUVBQQP369aP169cLoyx27txJo0ePFkZZmM1mGjlyJM2fP18YZZGUlEQDBgzQjbKYN28e/fzzz8Ioi8LCQvrqq69o3bp1wsiIoKAgGjVqlG6UxahRo2jevHnCKIvz58/T119/rRu7tWDBApoyZYowyqKoqIj69+9Pa9euFeras2cPjRw5UtcTjB07VterJCcn09dff63rVRYvXkw+Pj5CryJ7Aj2vEhwcTN99952uJxg/fryuV0lNTa3Sq0yePFnoVWRPoOdVwsLCFE8g0jVhwgSaM2eO6sGfTHp6ulVPsHz5cl2vUlpaqngVkSeIiIiw6gmq41W2bdsm1LVy5UpdryJ7gpUrVwo9QWRkJH377be6sVs//vijVa8iewKRV1mzZs0d9yoiTyB7FWuxW/9UqrsQrXF8S03g+BaGYRiGYRiGYZi/L9WNb+FmRQzDMAzDMAzDMMxdhReiDMMwDMMwDMMwzF2FF6IMwzAMwzAMwzDMXYUXogzDMAzDMAzDMMxdhXNE7wO++eYbXLp0SZgNd/ToUfz000+ws7MTZtbNmDEDBw4cEGbp5eXlYfDgwTAajcLMui1btmD9+vWoVauWMLNu+PDhSEtLE+pKSEjA5MmTYWtrK8xgmzlzJqKiooRZejdu3MCgQYNQUlIizKzbvn071qxZo6trxIgRSElJEWbWnThxApMmTYKtra3wfM2ePRv79u1D3bp1NZl1BQUFGDRoEIqKioTny9/fH6tWrYKLi4sws87b2xsXLlwQZtadPn0aP/zwA2xsbITna+7cuQgPDxdmwxUVFWHgwIEoLCwUZsPt3LkTK1as0NU1cuRInDt3TphZl5SUhPHjx+vqmjdvHkJCQoS6iouLMXDgQBQUFAh1BQUFYenSpXB2dhZmsI0ePRpJSUlCXefOncPYsWMhSZIwg23BggXYu3evMBuupKQEAwcORH5+vlDX7t27sWTJEiWrsbKusWPHIjExUagrOTkZo0eP1tW1aNEi7N69W6jLaDRi0KBByMvLE2bDBQcHY8GCBXBychKer/Hjx+PUqVPCzLrU1FSMGjUKAIS6lixZgqCgIGGOrclkwqBBg5CbmyvM0gsNDcW8efPg6OgozKybMGECTpw4IdSVnp4Ob29vmM1mYQbb8uXLsWPHDqGusrIyDBw4ENevXxdmw0VERGDu3Lm6uiZOnIiEhARhZt2lS5fg5eWlq2vlypXw9/cXZtaVl5dj0KBBuHbtmjBLLzIyEr/99hscHByEmXU//vgj4uPjhbquXLmC4cOHo7y8XKhr9erV2L59u66uwYMH4+rVq0JdBw4cwMyZM3V1+fj4IC4uTpill5WVhWHDhqGsrEyoa926ddi6daswS89sNmPw4MHIzMwU5thGR0djxowZsLe3F+r6+eefceTIEaGu7OxsfPPNNzCZTMK8WF9fX2zevFmYR0xEGDx4MK5cuSLUdfjwYUybNk1X19SpUxETE6PMcZbk5ORgyJAhMJlMwnzdDRs2YOPGjXB1dRVmDw4ZMgQZGRlCXbGxsZg6dSrs7Ozg6emp0TV9+nRER0cLPcH169cxZMgQlJaWCs/X5s2b4evrq6vrm2++QXp6ujBfNz4+HlOmTLHqVfbv3y/0BHl5eRgyZIiSGVx57t26dSvWrVunzHF/xqscP37cqleZNWsWIiMjhTm2+fn5GDx4MIqLi3W9yurVq3XnXmte5eTJk5g0aZLu3Pvbb78hIiJCqKsqrxIQEIBVq1bpznHWvEpiYiImTJhg1auEhYXV2KssX75c1xNY8ypnz57FuHHjdOfeqrzKoEGDUFBQIMwj3rVrl+IJRLrGjBmDpKQkYb7u+fPnMXbsWADiufefTHVzRO2q+gLmzhMYGIgzZ87AaDTi888/VxnBK1euYMuWLTAajbC3t8fLL7+sGhsdHY309HSUlJTgyy+/RJMmTZRaYWEh/P39kZ+fD7PZjPfee081aZ05cwabN29GSUkJatWqhfbt26uOvWvXLpw6dQqlpaX4/PPPVcYmMzNTpatr166qsYcOHUJKSgpKSkrQr18/la6ioiL4+/vjxo0bMJvN6N27t0pXUlKSSleHDh00uo4fP67ospyos7KyFF12dnb497//rRobExODs2fPKuerWbNmSq24uBj+/v7Izc1FeXk5PvjgA5Wus2fPYtOmTSgpKYGLiws6duyoOvaePXsQHx8Po9GIL774QjUhXr16VaWrW7duqrGHDx/G6dOnFV0eHh4aXdevX1d0WU4O586dU+l6/PHHVcfeu3cv6tWrp+iynHiys7OxZcsWlJSUwNbWFv/5z39UN/AjR44gISEBRqMRtWvXhqenp1IrKSlBQEAAcnJyUFZWhg8//FCl68KFC9i8eTOMRiNcXFzQuXNnla7g4GC4ubnBaDTiyy+/VOm6du0atm7dipKSEtjY2KB79+4qXbGxsYiLi4PRaISbmxtatGih1IxGIwICApCdna3ospwckpOTlfPl7OyMJ554QqUrJCQELi4uii7LiScnJ0elq0ePHipdR48exaFDhxRdLVu2VGqlpaUICAhAVlYWTCYTPv74Y5WulJQU5Xw5OzvjqaeeUukKCwuDvb298jNluei7fv06tmzZguLiYkiShJ49e6p0HTt2DFFRUYquBx54QKPrypUrii7LhUZqaqpKV5cuXVS6wsPDIUmSostycXX9+nVs3boVxcXFsLGxwWuvvabRFR4eruhq1aqVUjOZTNixYwcyMjJQWlqKTz/9VKUrLS1N0eXk5IRnnnlGpSsiIgLl5eWKLstFTF5eHrZt26acrzfeeEOlKyEhAcHBwSgpKYHBYMBDDz2k1MrKyrBz506kp6cruiwN/cWLF1W6nn32WZWuffv2wWg0KrosFzF5eXnYvn27oqtXr14qXSdOnEBQUJCiq3Xr1krNbDZj586dSEtLg8lkwqeffqoyqOnp6YouR0dHPP/88ypdkZGRKCwsVO5BDRs2VGo3btzA9u3bUVRUBAB46623NLoCAgIUXW3atNHoSklJgclkQt++fVW6MjIyVLpeeOEFla6oqCjk5uYqutzd3ZVafn4+tm/fjsLCQhAR3n77bZWJPHXqlPLz6urqirZt2yo1IkJgYCCSk5NRWlqKzz77TGVQMzIylHu2g4MDXnzxRZWuAwcOIDs7W9HVqFEjpVZQUAA/Pz9F1zvvvKPSdfr0aWWOc3V1xSOPPKI6dmBgIM6dO6foquwJ5LEODg546aWXNLouX76s6GrcuLFSKywshJ+fHwoKChRPYKkrMTFRNfc++uijqmMHBQXhzJkzytyrp0vkVQ4dOoS0tDTlvlrZE/j5+SmewJpXcXV11XiV3bt349SpU8ocJ/IqJSUlsLOzwyuvvKLRdeHCBUVX06ZNNbry8vJQXl6O999/X+MJ5Gu3Vq1aeOyxxzS6jh8/ruiy9CqyJ5DPl8irJCUlKbpq6lVq1aql8Sp79+6t0qvInqBbt24aT3Dy5EllbGVP4O/vr3iCPn36qDzB+fPnVZ6gU6dOKl3BwcGoW7eurlfZunWr4qEqe5XY2FgcO3ZMmUuaN2+u1IxGI/z9/VWe4M96FYPBoOtVLM9XZa/CVA3Ht9wHFBYWap5eyxQVFcHJyUnzhKY6Y00mE4hI8/S6OmOrqhcXF8PR0fFvpausrAzl5eWap8R/BV0uLi66N787pau8vBwmk0nzNPZ26JIn58pP+2+HrqKiIjg7O98TXaWlpZqnsZZj78X5MpvNyiLzduuSTUNNdBERiouLNTu0MrfyPhqNRtja2mqe9rMufV02Nja6T/vvla7S0lJIklRjXUVFRVbn3nuhq6r6reoCcN/NvferJ7hfdVXlCYqKinR/3u6lrlv1Kg4ODnfEE9zJufefTHXjW3ghyjAMwzAMwzAMw9wWOEeUYRiGYRiGYRiGuS/hhSjDMAzDMAzDMAxzV+GFKMMwDMMwDMMwDHNX4YUowzAMwzAMwzAMc1fhHNH7gFdffRWZmZno1KmTplvirl27MH78eDRs2FAVBSEzdOhQREZG4vHHH9d0Sbt48SI++OAD2NjYoH379pqOYHPmzMHy5cvRpk0bTd4YALz22mu4fPkyOnfurNG1d+9ejB07Fg0aNFBFQcgMGzYMEREReOyxxzTdxjIyMvDee+8BgFDXvHnzsHTpUjz00EOqCAGZN954A+np6ejcubOmK2FoaChGjRqF+vXrC3V9++23CA0NxWOPPabJZ8vMzMS7774Ls9mMDh06aHQtWLAAixcv1tX11ltvIS0tDZ06ddLoioiIwHfffYd69eqpIipkvL29sXfvXqGuq1ev4u2334bZbMZjjz2m0bV48WIsWLAArVq1UkUbyLzzzjtISUkRnq+oqCiMGDECderUwYMPPqgZO3LkSOzevRsdOnTQ5LPl5OTgzTffRFlZGR577DFNl71ly5bh999/xwMPPKCKNpDp3bs3zp07h86dO2u6Eh48eBDDhw9H7dq1VdEZMmPGjEFgYKBQV25uLnr16gWTySTUtXLlSvz2229o2bKlKtpA5oMPPkBSUhI6deqk0RUTE4OhQ4dqojNkxo0bhx07dqB9+/aafLYbN27gjTfegNFoRMeOHTW6Vq9ejVmzZqF58+aqaAOZDz/8EKdPn0anTp00XQmPHDmCwYMHw9XVFa1bt9ZcIxMmTICfnx8effRRTQ5aQUEBXn/9dRQXFwt1rVu3Dr/++iuaN2+uijaQ+eSTT3Dy5Emhrvj4eAwYMAAuLi5o06aNRtfEiROxbds2oa7i4mL07NkTBQUF6NSpk0bXH3/8gWnTpsHDw0MVbSDTt29fHD9+XKgrISEB/fv3h7OzMx5++GGNrsmTJ2PLli1o166dJhu1pKQEPXv2RH5+Ph5//HFNt8SNGzdi6tSpaNasmSqGSebzzz9HfHw8OnXqpOnieOrUKXzxxRdwcnJC27ZtNbp++uknbNy4EY888ogmg9RkMuHVV19FXl4eOnXqpNG1detWTJkyBU2bNhXq6tevH44cOYLHH39c00H5zJkz+Oyzz+Do6IhHHnlEo+uXX36Br6+vUFdZWRl69OiB3NxcoS4/Pz9MnjwZTZo0UUVByPTv3x8xMTHo1KmTRte5c+fwySefwMHBAe3atdPomj59OtatW4e2bdtqMkjNZjO6d++OnJwcdO7cWaMrICAAkyZNQqNGjVRREDIDBgxAdHQ0OnbsqJl7k5OT8dFHH8HOzg6PPvqoRtfMmTOxevVqPPzww5oMUgDo3r07srOzhZ4gMDAQEyZMQKNGjVSxVTKDBw/G/v37hbpSU1PRp08f2NraCufe2bNnY+XKlWjTpo1QV8+ePXW9yu7du6vlVTp27KjxBOnp6Xj//fd1vcrcuXOxfPlytG7dWuhVXn/9dV2vEhwcjDFjxlj1KuHh4UJdly9ftupV5s+fb9UT9OrVS9erhIWFYdSoUbqeYMSIEQgJCamRV1m4cCEWLlyIBx98UOgJ3n77baSmpgq9yr59++Dt7Y26desKPYE1r5KdnY233noL5eXlQq+yZMkSzJ8/H61atRJ6gnfffRfJycnC87V//358++23qFOnjtATjBo1qkqvoucJli9fjrlz5+p6gqq8yrBhw+Dm5ib0BP9kqpsjCiK6a68nnniCGC2hoaFUUFAgrKWnp1NcXByZzWZhPTo6mrKysoS14uJiCgsLo9LSUmH95MmTdO7cOau68vPzhbVLly5RbGysrq5Dhw5RZmamsFZSUkKhoaG6uk6dOmVVV1hYGN24cUNYu3z5Mh05ckRXV0xMDF25ckVYMxqNFBISQkajUVg/ffo0nT17tka6rly5QocPH6by8nJdXZcvXxbWSktLrepKTEykpKQkXV3h4eGUl5cnrGVmZlJMTIyursOHD1NGRoawZjKZrOo6c+YMnTlzRldXRESErq6rV6/SoUOHdHUdOXKELl26JKyVlZVRcHAwlZSUCOtJSUl0+vRp3WskIiKCcnNzhbXs7GyKjo7W1RUbG1tjXWfPnqVTp07p6tq3bx9dv35dWLt27RodPHiQysrKhPW4uDhKT08X1srLyyk4OJiKi4uF9XPnztHJkyd1dUVGRurqun79Oh04cEBX19GjR+nixYvCmtlstqrrwoULdOLECV1dUVFRlJOTI6zl5ubS/v37repKS0uzqquoqEhYT05OpuPHj1vVde3aNWEtLy+PIiMjdXXFx8dTamqqrq6QkBBdXSkpKZSQkKCra//+/bq68vPzad++fWQymYT1hIQESklJsaqrsLBQWE9NTaVjx47p6jpw4ABlZ2cLawUFBRQREWFVV3Jyco10paWlUXx8vK6ugwcP0tWrV4W1wsJCCg8P19V14sQJunDhgrBGRBQSEqLrCS5evEhHjx61qkvPExQVFVn1BCdOnKDz58/r6rLmVS5dulSlV7HmCW7Fq4SFhel6lYyMjBp7FaPRaNWr3IonkL2KNU+g51VKS0spNDTUqlepyhPo6crMzKyxV6nKEyQmJlr1BNa8SlZWllVPUB2vYs0TJCYm6uqqyqtY8wT/ZAAcoWqsDTm+hWEYhmEYhmEYhrktcHwLwzAMwzAMwzAMc1/CC1GGYRiGYRiGYRjmrsILUYZhGIZhGIZhGOauwgtRhmEYhmEYhmEY5q7CC9F7zIoVK7B06VJhLT8/H97e3jh58qSwHhwcjIkTJ0Kv4ZSPjw+CgoKEtTNnzsDLywvXr18X1letWoXFi8VdlwsLC+Ht7Y2EhARhPTQ0FD/88IOurp9++gk7d+4U1s6dOwcvLy9cu3ZNWF+zZg0WLlworBUVFeG7775DfHy8sB4eHo7vv/8eZrNZWJ86dSoCAgKEtfPnz8PLywtXr14V1tetW4f58+cLa8XFxRg5ciSOHj0qrO/btw/jx4/X1TVt2jT4+fkJa8nJyRgxYgSysrKEdV9fX/z+++/CWklJCUaOHAm9BmJRUVEYN24cysvLhfUZM2Zg+/btwlpqaipGjBiBK1euCOsbNmzAnDlzhLXS0lKMGjUKhw8fFtYPHDiAMWPGoKysTFifOXMmtmzZIqxdvHgRI0aMQEZGhrC+adMmzJ49W1gzmUwYPXo0oqOjhfXo6GiMHj0aJpNJWJ89ezY2bdokrGVkZGDEiBFIT08X1rds2YKZM2cKa2VlZRgzZgwOHjworMfExGDUqFEoLS0V1ufMmYMNGzYIa5cvX8aIESOQlpYmrG/btg0zZswQ1srLyzF27Fi6TvmDAAAViElEQVTs379fWD9y5AhGjRoFo9EorP/+++/w9fUV1jIzMzFixAikpKQI635+fpg2bZqurnHjxmHfvn3CelxcHEaOHImSkhJhff78+Vi/fr2wdvXqVXh5eeHChQvCekBAAKZOnSqsmc1mfP/994iIiBDW4+Pj8d1336GoqEhYX7hwIdasWSOsXbt2DV5eXjh37pywvnPnTvz888/CGhFhwoQJCA0NFdYTEhLg7e2NwsJCYX3x4sVYvXq1sHb9+nV4eXkhKSlJWA8KCoKPj4+urokTJyIkJERYP3HiBLy9vZGfny+sL126FCtWrBDWcnNz4eXlhcTERGF99+7dmDx5srAGAJMmTcLevXuFtVOnTsHLyws3btwQ1pctW4Zly5YJazdu3IC3tzdOnTolrO/duxeTJk3S1TV58mTs2rVLWEtMTISXlxdyc3OF9ZUrV+p6lYKCAnh7e+PEiRPCekhIiFVPMGXKFF2vkpSUVKVXWbRokbBWWFiI7777TterhIWFYcKECXfEq6xdu7bGXiUiIqLGXuXChQtWvcr69esxb948YU32BHFxccJ6ZGSkVU8wffp0Xa+SkpKCESNGIDMzU1i35lWMRiNGjRql61X279+PsWPHWvUq27ZtE9bS0tIwYsQIXL58WVjfuHGjVa8yevRoxMTECOtMNalOa93b9eL4FjVms5maNGlCDRs2FLZ+9vPzIwA0atQo4fiePXuSJEnCtubp6elkY2NDr7zyinDsxIkTCQBt2LBBqKtZs2ZUr149Yfv5nTt3EgDy9vYWHrtXr14EQNimOyMjg2xtbemll14SjvXx8SEAtG7dOmG9RYsWVKdOHWE79V27dhEAGj58uHDsO++8QwDo5MmTmlpmZibZ2dnRCy+8IBz7888/EwBatWqVsN6qVStyc3MTti0PDg4mADR06FDh2N69exMASkhI0NSys7PJ3t6ennnmGeHY6dOnEwBavny5sN6mTRtydXUVRmCEhYURABo4cKBw7IcffkgA6OjRo5paTk4OOTg40FNPPSUcO3PmTAJAixcvFtYfeeQRcnFxEUYnREZGEgDq37+/cOwnn3xCAOjw4cOaWl5eHjk6OlKnTp2EY+fMmUMAaMGCBcJ6+/btycnJSRgFcPDgQQJAX3zxhXDs559/TgAoOjpaU8vPzycnJyfq0KGDcOz8+fMJAM2dO1dYf/zxx8nR0VHYQj4mJoYA0Keffioc+9VXXxEAioqK0tQKCwvJxcWF2rVrJxy7aNEiAkCzZs0S1p944glycHAQxrfExcURAProo4+EYwcMGEAAKCIiQlMrLi6mWrVqUZs2bYRjly1bRgBoxowZwvrTTz9N9vb2wjiSY8eOEQB6//33hWOHDBlCACgkJERTKykpIYPBQA8++KBw7MqVKwkATZ06VVh//vnnyc7OThivcfLkSQJA7777rnDssGHDCADt3r1bUystLaU6depQy5YthWPXrl1LAGjKlCnC+osvvki2trbCWIbExEQCQG+++aZwrJeXFwGgwMBATc1kMlG9evXIw8NDONbX15cA0KRJk4T1rl27ko2NjTB66OzZsyRJEr322mvCsSNHjiQA5O/vr6mVl5dTw4YNqWnTpsJYj02bNhEAmjBhgvDY3bp1IxsbG2GUTnJyMkmSRD169BCOHTt2LAGgbdu2CXU1atSIGjVqJPQE27ZtIwA0duxY4bF79OhBkiQJo2FSU1PJxsaGunXrJhw7YcIEAkCbNm3S1MxmMzVt2pQaNGggjBby9/cnADRy5EjhsV9//XWSJEkYdXLp0iWysbGhrl27CsdOmjSJAJCvr6+w7uHhoetVAgMDCQB5eXkJx7755psEQBjdcfnyZbK1taUXX3xROHbKlCkEgNauXSust2zZUter7N69mwDQsGHDhGPfffddXa+SlZVFdnZ29PzzzwvHTp06lQDQypUrhfUHH3yQDAaDMMokJCSEANCQIUOEY99//30CQMeOHdPUrl27Rvb29vT0008Lx86YMYMA0LJly4R12auI4qciIiIIAA0YMEA49qOPPiIAFBcXp6ldv36dHBwcSG/9MWvWLAJAixYtEtbbtWun61WioqIIAPXr10849p8OqhnfwgvRe0x8fLzQ6BNVTEo7duzQzXZLSUmhsLAw3WPv27dPN6ssNzeXAgICdPPqjh07JvyhJqqYlHbs2KGb7ZaamkqhoaG6uiIjI3UzwfLy8iggIEA3f+348eMUGxurq2vnzp262W5paWlCcykTFRWlmwl248YNCggIsJq/JloYyQQGBupmu128eJGCg4N1x+7fv183Eyw/P5/8/f11c7tOnjxZpS69DLVLly7R3r17dcceOHBANxOsoKCA/P39dXO7Tp06RYcOHdI9dlBQkG6G2qVLl4RmXObgwYO6mWCFhYXk7++vm015+vRp4UJSZteuXboZapcvX7aqKzo6mk6fPi2sFRcXk7+/v24GZGJiIh08eFD32Lt379bNULty5QoFBQXpjj106BCdOnVKWCspKSF/f3/drMUzZ87QgQMHdI+9Z88e3VzVzMxMq7piYmKERoyoIt/P399fNzswKSmJ9u/fr3vsvXv36uaqZmVlCRdVMocPH6YTJ04Ia6WlpRQQEKCb0Xf27FnhAwGZkJAQ3VzVq1ev0s6dO3XHxsbG0vHjx4U1k8lEAQEBull4586do8jISN1jh4aG6uaXZmdn044dO3RzGmNjY4UP2Sx16eX2nj9/nvbt26erKywsTFfXtWvXrOo6evSo0FATVWT+BgQE6ObjXrhwQfgARSY8PFw3vzQnJ4cCAgJ0cwer4wn08nGTk5MpPDxcV1dERISuJ7h+/fotewI9r5KamlqlV9HLL63KqyQkJFTpCfS8SlpaWo29iuwJrHmVI0eO6B7bmlepyhPcK6+Snp5u1RNY8yqyJ7DmVWJiYnSPHRQUZNWr7NmzR3esNa9SlSeoyqvs2rVL16v806nuQpRzRBmGYRiGYRiGYZjbAueIMgzDMAzDMAzDMPclt7QQlSSpuyRJZyRJOidJ0ujbJYphGIZhGIZhGIb5+1LjhagkSbYA5gHoAaAdgD6SJLW7XcIYhmEYhmEYhmGYvye3siPaBcA5IrpARKUA/gDQ6/bIYhiGYRiGYRiGYf6u3MpCtBmAixYfp9/8HFNNiAgvvfQSnnvuOWFe1NGjR+Hm5qabkTVs2DA0bdoU2dnZmlpeXh6aN2+Or7/+Wjh29erVMBgMutmDL7/8Mp5++mmhroSEBLi5uelmUXl5eaFJkybCbMsbN26gZcuW+PLLL4Vj169fD4PBgKioKGG9W7dueOqpp4R5USdPnkTt2rV1M59GjhyJRo0aCbMtCwoK0KpVK3z22WfCsX/88QcMBgPCw8OF9e7du6Nz587CbMvExETUqVMHs2bNEo4dO3Ys3N3dhdmWhYWFeOihh/Dxxx8Lx27evBmurq66WXo9e/ZEx44dhdmWSUlJqFOnDqZPny4cO2HCBDRs2FCYbVlcXIw2bdqgT58+wrHbtm2Dq6sr9uzZI6z36tULHTp0EGZbnj9/HnXr1tXNW5w4cSLq16+P1NRUTa2kpARt27ZF7969hWMDAgLg6uqqm1n39ttvo127dsJsy+TkZNSrV08319DHxwf16tVDcnKypmY0GtGuXTu8/fbbwrGBgYFwdXXVzYbr3bs32rZtK8y2TE1NRf369XXzA6dOnYq6devi/PnzmlppaSk6dOiAXr3EzxD37NkDV1dX3bzYDz74AG3atEFxcbGmlp6ejoYNG2LChAnCsdOnT0fdunVx9uxZTc1kMqFjx47o2bOncGxISAhcXV2xefNmYf3jjz/GQw89JMzczMjIgLu7O8aOHSscO2vWLNSpU0eYIVlWVobOnTuje/fuwrHh4eEwGAz4448/hPW+ffuiVatWKCgo0NSuXLmCRo0aYdSoUcKxc+bMQe3atYW50uXl5XjyySfRrVs34dioqCgYDAbd/NMvv/wSLVu2FGZbZmVloUmTJvDy8hKOnTdvHtzc3IRZjWazGU8//TS6du0qHHvw4EEYDAbdnNGvv/4azZs3R15enqaWnZ2Npk2bYvjw4cKxCxcuhJubmzC/2Ww247nnnsNLL70kzJCMiYmBwWDQzRkdNGgQPD09hdmWOTk58PDwwJAhQ4Rjly5dCoPBgNjYWE2NiPDCCy/ghRdeEOqKjY2Fm5sblixZIjz20KFD0axZM+Tk5Ghqubm58PT0xMCBA4VjV6xYAYPBgEOHDgl1vfTSS3j22WeFniA+Ph5ubm66uZnffvstmjRpIsy2zMvLQ4sWLdC/f3/h2DVr1sBgMODAgQPCeteuXdGlSxehruPHj6N27dq6+ZTe3t5o3LixMNsyPz8fDzzwAL744gvhWF9fXxgMBkRGRgrr3bp1w5NPPmnVq/z222/CsaNHj7bqVR588EH07dtXOHbDhg0wGAwICwsT1nv06IFOnTpZ9Sp6mdXjxo1Dw4YNcenSJU2tqKgIrVu3xkcffSQcu2XLFri6uiI4OFhYf+2113S9ytmzZ1G3bl3dbOgJEyagQYMGuHjxoqZWXFyMhx9+GB988IFw7Pbt2+Hq6ordu3cL62+++Sbat2+v61Xq1aunm8HMVA+7WxgrCT6nuXNKktQfQH8AaN68+S18u78fkiTBYDDAZDLBxkb7TMDBwQEGgwHOzs7C8a6urjAYDLCz076Ntra2cHNzg6urq3Csk5MTDAYDnJychHU3NzfY2tpCkrRvs6zLxcVFOLZWrVowGAywt7cX6jIYDFXqcnR0FNYNBgPKy8uF58ve3t7q+aqOLoPBIBzr7Oxs9XwZDAYUFxdb1aV3vlxcXGqsq6r30WAwwM3N7bbrsrGxqZYua++jwWCAra3tn9Ylv48ODg6amnzd3+r5sqarVq1awrEuLi5wc3MT6rKxsbklXa6urrekq6bvo6OjY5Xnq6bvY3V0ubm5WdVl7d6od77s7Oysni/5Z13vfbwVXdbO163okiTJ6vVV1fsony/RXCLr0rtny++j6GddnuP0/p+qmuNq1apVpa6qzpdIl/w+2tvbC+e4qt5H+R5Uk/NVnfeRiKzOvTX1BNXRpfc+urm5obS0tEZeRX4fRT/rVZ2v6swlNjY2951XcXNzQ1lZmdXzVZUua+/jrXiVwsLCGum6HZ6gqrmkJl7lVrxdda4vPQ9V1fliqkeN41skSXoWwEQi+u/Nj8cAABHpPhrg+BaGYRiGYRiGYZi/L3cjvuUwgNaSJD0gSZIDgA8A+N/C8RiGYRiGYRiGYZh/ADX+1VwiKpMkaQiA3QBsASwnIu0frzAMwzAMwzAMwzCMBbfyN6IgokAAgbdJC8MwDMMwDMMwDPMP4FZ+NZdhGIZhGIZhGIZh/jS8EGUYhmEYhmEYhmHuKrwQZRiGYRiGYRiGYe4qvBBlGIZhGIZhGIZh7iq8EGUYhmEYhmEYhmHuKrwQZRiGYRiGYRiGYe4qvBBlGIZhGIZhGIZh7iq8EGUYhmEYhmEYhmHuKrwQZRiGYRiGYRiGYe4qvBBlGIZhGIZhGIZh7ioSEd29byZJVwGk3rVv+NehAYDsey2C+dvC1xdzJ+Hri7mT8PXF3En4+mLuJP/k66sFETWs6ovu6kKUESNJ0hEievJe62D+nvD1xdxJ+Ppi7iR8fTF3Er6+mDsJX19Vw7+ayzAMwzAMwzAMw9xVeCHKMAzDMAzDMAzD3FV4IXp/sPheC2D+1vD1xdxJ+Ppi7iR8fTF3Er6+mDsJX19VwH8jyjAMwzAMwzAMw9xVeEeUYRiGYRiGYRiGuavwQvQeI0lSd0mSzkiSdE6SpNH3Wg/z10aSJE9JksIkSTotSdJJSZKG3fx8PUmS9kqSdPbmf+vea63MXxNJkmwlSToqSdKOmx8/IEnSoZvX1gZJkhzutUbmr4skSXUkSdosSVLizfvYs3z/Ym4XkiR9e3NuPCFJkq8kSU58D2NqiiRJyyVJypIk6YTF54T3K6mCOTf9foIkSZ3vnfL7B16I3kMkSbIFMA9ADwDtAPSRJKndvVXF/MUpA+BFRI8AeAbA4JvX1GgAIUTUGkDIzY8ZpiYMA3Da4uNfAMy6eW1dB/DlPVHF/F34DcAuImoLoCMqrjW+fzG3jCRJzQB8A+BJImoPwBbAB+B7GFNzVgLoXulzeverHgBa33z1B7DgLmm8r+GF6L2lC4BzRHSBiEoB/AGg1z3WxPyFIaLLRBR389/5qDBxzVBxXa26+WWrALx5bxQyf2UkSfIA0BPA0psfSwC6Ath880v42mJqjCRJbgBeBLAMAIiolIhywfcv5vZhB8BZkiQ7AC4ALoPvYUwNIaJ9AHIqfVrvftULwGqqIBpAHUmSmtwdpfcvvBC9tzQDcNHi4/Sbn2OYW0aSpJYAOgE4BKAREV0GKharANzvnTLmL8xsACMBmG9+XB9ALhGV3fyY72HMrdAKwFUAK27++vdSSZJqge9fzG2AiC4BmAEgDRUL0DwAseB7GHN70btfsecXwAvRe4sk+By3MWZuGUmSXAFsATCciG7caz3MXx9Jkl4DkEVEsZafFnwp38OYmmIHoDOABUTUCUAh+NdwmdvEzb/V6wXgAQBNAdRCxa9LVobvYcydgOdLAbwQvbekA/C0+NgDQMY90sL8TZAkyR4Vi9B1RLT15qcz5V8BufnfrHulj/nL8jyANyRJSkHFnxF0RcUOaZ2bv+YG8D2MuTXSAaQT0aGbH29GxcKU71/M7eDfAJKJ6CoRmQBsBfAc+B7G3F707lfs+QXwQvTechhA65sd2xxQ8Ufz/vdYE/MX5ubf7C0DcJqIZlqU/AH0vfnvvgD87rY25q8NEY0hIg8iaomKe1UoEX0EIAzAuze/jK8tpsYQ0RUAFyVJevjmp14BcAp8/2JuD2kAnpEkyeXmXClfX3wPY24nevcrfwCf3uye+wyAPPlXeP/JSET/+F3he4okSa+iYlfBFsByIppyjyUxf2EkSXoBQCSA4/jf3/GNRcXfiW4E0BwVk/F7RFT5D+wZplpIkvQvAN5E9JokSa1QsUNaD8BRAB8TkfFe6mP+ukiS9DgqmmE5ALgA4HNUPDTn+xdzy0iSNAnA+6joMH8UQD9U/J0e38OYP40kSb4A/gWgAYBMAD8A2A7B/ermw4/fUdFltwjA50R05F7ovp/ghSjDMAzDMAzDMAxzV+FfzWUYhmEYhmEYhmHuKrwQZRiGYRiGYRiGYe4qvBBlGIZhGIZhGIZh7iq8EGUYhmEYhmEYhmHuKrwQZRiGYRiGYRiGYe4qvBBlGIZhGIZhGIZh7iq8EGUYhmEYhmEYhmHuKrwQZRiGYRiGYRiGYe4q/w/lvM/u+ncnOwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "y = np.linspace(0, 1, v_arr.shape[1])\n",
+    "v_arr[:, :, 0] = -y * (y - 1.0) * 5\n",
+    "plt.vector_field(v_arr);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def boundary_handling(c):\n",
+    "    # No concentration at the upper, lower wall and the left inflow border\n",
+    "    c[:, 0] = 0\n",
+    "    c[:, -1] = 0\n",
+    "    c[0, :] = 0\n",
+    "    # At outflow border: neumann boundaries by copying last valid layer\n",
+    "    c[-1, :] = c[-2, :]\n",
+    "    \n",
+    "    # Some source inside the domain\n",
+    "    c[10: 15, 25:30] = 1.0\n",
+    "    c[20: 25, 60:65] = 1.0\n",
+    "\n",
+    "c_tmp_arr = np.empty_like(c_arr)\n",
+    "def timeloop(steps=100):\n",
+    "    global c_arr, c_tmp_arr\n",
+    "    for i in range(steps):\n",
+    "        boundary_handling(c_arr)\n",
+    "        kernel(c=c_arr, c_next=c_tmp_arr, v=v_arr)\n",
+    "        c_arr, c_tmp_arr = c_tmp_arr, c_arr\n",
+    "    return c_arr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<video controls width=\"80%\">\n",
+       " <source 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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' in globals():\n",
+    "    timeloop(10)\n",
+    "    result = None\n",
+    "else:\n",
+    "    ps_notebook.set_display_mode('video')\n",
+    "    ani = ps.plot2d.scalar_field_animation(timeloop, rescale=True, frames=300)\n",
+    "    result = ps_notebook.display_animation(ani)\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": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/04_tutorial_phasefield_spinodal_decomposition.ipynb b/doc/notebooks/04_tutorial_phasefield_spinodal_decomposition.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..72c458ff401a49e7e29c3223a93675177895df9d
--- /dev/null
+++ b/doc/notebooks/04_tutorial_phasefield_spinodal_decomposition.ipynb
@@ -0,0 +1,421 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 04: Phase-field simulation of spinodal decomposition\n",
+    "\n",
+    "In this series of demos, we show how to implement simple phase field models using finite differences.\n",
+    "We implement examples from the book **Programming Phase-Field Modelling** by S. Bulent Biner. \n",
+    "Specifically, the model for spinodal decomposition implemented in this notebook can be found in Section 4.4 of the book.\n",
+    "\n",
+    "First we create a DataHandling instance, that manages the numpy arrays and their corresponding symbolic *sympy* fields. We create two arrays, one for the concentration $c$ and one for the chemical potential $\\mu$, on a 2D periodic domain."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "language": "python3",
+    "language_info": {
+     "name": "python3",
+     "pygments_lexer": "python3"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "dh = ps.create_data_handling(domain_size=(256, 256), periodicity=True)\n",
+    "μ_field = dh.add_array('mu', latex_name='μ')\n",
+    "c_field = dh.add_array('c')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the next cell we build up the free energy density, consisting of a bulk and an interface component.\n",
+    "The bulk free energy is minimal in regions where only either phase 0 or phase 1 is present. Areas of mixture are penalized. The interfacial free energy penalized regions where the gradient of the phase field is large, i.e. it tends to smear out the interface. The strength of these counteracting contributions is balanced by the parameters $A$ for the bulk- and $\\kappa$ for the interface part. The ratio of these parameters determines the interface width."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$${{c}_{C}}^{2} A \\left(- {{c}_{C}} + 1\\right)^{2} + \\frac{κ}{2} {\\partial {{c}_{C}}}^{2}$$"
+      ],
+      "text/plain": [
+       "                             2\n",
+       "   2             2   κ⋅D(c_C) \n",
+       "c_C ⋅A⋅(-c_C + 1)  + ─────────\n",
+       "                         2    "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "κ, A = sp.symbols(\"κ A\")\n",
+    "\n",
+    "c = c_field.center\n",
+    "μ = μ_field.center\n",
+    "\n",
+    "def f(c):\n",
+    "    return A * c**2 * (1-c)**2\n",
+    "\n",
+    "bulk_free_energy_density = f(c)\n",
+    "interfacial_free_energy_density = κ/2 * ps.fd.Diff(c) ** 2\n",
+    "\n",
+    "free_energy_density = bulk_free_energy_density + interfacial_free_energy_density\n",
+    "free_energy_density"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In case you wonder what the index $C$ of the concentration means, it just indicates that the concentration is a field (array) and the $C$ indices indicates that we use the center value of the field when iterating over it. This gets important when we apply a finite difference discretization on the equation.\n",
+    "\n",
+    "The bulk free energy $c^2 (1-c)^2$ is just the simplest polynomial with minima at $c=0$ and $c=1$. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(7,4))\n",
+    "plt.sympy_function(bulk_free_energy_density.subs(A, 1), (-0.2, 1.2))\n",
+    "plt.xlabel(\"c\")\n",
+    "plt.title(\"Bulk free energy\");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To minimize the total free energy we use the Cahn Hilliard equation\n",
+    "\n",
+    "$$\\partial_t c = \\nabla \\cdot \\left( M \\nabla \\frac{\\delta F}{\\delta c} \\right)$$\n",
+    "\n",
+    "where the functional derivative $\\frac{\\delta F}{\\delta c}$ in this case is the chemical potential $\\mu$.\n",
+    "A functional derivative is computed as \n",
+    "$\\frac{\\delta F}{\\delta c} = \\frac{\\partial F}{\\partial c} - \\nabla \\cdot \\frac{\\partial F}{\\partial \\nabla c}$. \n",
+    "That means we treat $\\nabla c$ like a normal variable when calculating derivatives.\n",
+    "\n",
+    "We don't have to worry about that in detail, since pystencils offers a function to do just that:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$${{c}_{C}}^{2} A \\left(2 {{c}_{C}} - 2\\right) + 2 {{c}_{C}} A \\left(- {{c}_{C}} + 1\\right)^{2} - {\\partial (κ {\\partial {{c}_{C}}}) }$$"
+      ],
+      "text/plain": [
+       "   2                                   2                         \n",
+       "c_C ⋅A⋅(2⋅c_C - 2) + 2⋅c_C⋅A⋅(-c_C + 1)  - D(κ*Diff(c_C, -1, -1))"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ps.fd.functional_derivative(free_energy_density, c)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this case we could quite simply do this derivative by hand but for more complex phase field models this step is quite tedious.\n",
+    "\n",
+    "If we discretize this term using finite differences, we have a computation rule how to compute the chemical potential $\\mu$ from the free energy."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$4 {{c}_{C}}^{3} A - 6 {{c}_{C}}^{2} A + 2 {{c}_{C}} A - κ \\left(- 4 {{c}_{C}} + {{c}_{E}} + {{c}_{N}} + {{c}_{S}} + {{c}_{W}}\\right)$$"
+      ],
+      "text/plain": [
+       "     3          2                                                 \n",
+       "4⋅c_C ⋅A - 6⋅c_C ⋅A + 2⋅c_C⋅A - κ⋅(-4⋅c_C + c_E + c_N + c_S + c_W)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discretize = ps.fd.Discretization2ndOrder(dx=1, dt=0.01)\n",
+    "\n",
+    "μ_update_eq = ps.fd.functional_derivative(free_energy_density, c)\n",
+    "μ_update_eq = ps.fd.expand_diff_linear(μ_update_eq, constants=[κ])  # pull constan κ in front of the derivatives\n",
+    "μ_update_eq_discretized = discretize(μ_update_eq)\n",
+    "μ_update_eq_discretized"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "pystencils computed the finite difference approximation for us. This was only possible since all symbols occuring inside derivatives are pystencils field variables, so that neighboring values can be accessed.\n",
+    "Next we bake this formula into a kernel that writes the chemical potential to a field. Therefor we first insert the $\\kappa$ and $A$ parameters, build an assignment out of it and compile the kernel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "μ_kernel = ps.create_kernel([ps.Assignment(μ_field.center, \n",
+    "                                           μ_update_eq_discretized.subs(A, 1).subs(κ, 0.5))]\n",
+    "                           ).compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we formulate the Cahn-Hilliard equation itself, which is just a diffusion equation:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$- div(M \\nabla \\mu) + \\partial_t c_{C}$$"
+      ],
+      "text/plain": [
+       "-Diffusion(μ_C, M) + Transient(c_C)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "M = sp.Symbol(\"M\")\n",
+    "cahn_hilliard = ps.fd.transient(c) - ps.fd.diffusion(μ, M)\n",
+    "cahn_hilliard"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It can be given right away to the `discretize` function, that by default uses a simple explicit Euler scheme for temporal, and second order finite differences for spatial discretization. \n",
+    "It returns the update rule for the concentration field."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$${{c}_{C}} - 0.04 {{μ}_{C}} M + 0.01 {{μ}_{E}} M + 0.01 {{μ}_{N}} M + 0.01 {{μ}_{S}} M + 0.01 {{μ}_{W}} M$$"
+      ],
+      "text/plain": [
+       "c_C - 0.04⋅μ_C⋅M + 0.01⋅μ_E⋅M + 0.01⋅μ_N⋅M + 0.01⋅μ_S⋅M + 0.01⋅μ_W⋅M"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "c_update = discretize(cahn_hilliard)\n",
+    "c_update"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Again, we build a kernel from this update rule:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "c_kernel = ps.create_kernel([ps.Assignment(c_field.center, \n",
+    "                                           c_update.subs(M, 1))]\n",
+    "                           ).compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Before we run the simulation, the domain has to be initialized. To access a numpy array inside a data handling we have to iterate over the data handling. This somewhat complicated way is necessary to be able to switch to distributed memory parallel simulations without having to alter the code. Basically this loops says \"iterate over the portion of the domain that belongs to my process\", which in our serial case here is just the full domain. \n",
+    "\n",
+    "As suggested in the book, we initialize everything with $c=0.4$ and add some random noise on top of it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def init(value=0.4, noise=0.02):\n",
+    "    for b in dh.iterate():\n",
+    "        b['c'].fill(value)\n",
+    "        np.add(b['c'], noise*np.random.rand(*b['c'].shape), out=b['c'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The time loop of the simulation is now rather straightforward. We call the kernels to update the chemical potential and the concentration in alternating fashion. In between we have to do synchronization steps for the fields that take care of the periodic boundary condition, and in the parallel case of the communciation between processes. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def timeloop(steps=100):\n",
+    "    c_sync = dh.synchronization_function(['c'])\n",
+    "    μ_sync = dh.synchronization_function(['mu'])\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",
+    "    return dh.gather_array('c')\n",
+    "init()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can run the simulation and see how the phases separate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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byW+cHxqhhh4sYCX8Rpz8gQEAOYGBQ8PQ0W0DAsOCj2tlsYX2OUEExsNeRbDAGLLZ72uzJQLsDrA1V/bUThlVM1Eetw4m+F78bsli8fVDSb/1mmOwyYio/yaJWtBeoHX5kC9GLRt7/F9vAZHqOBF/hk/y8Y8YQlTnPunc6hnqJ7Lk71zqkzhODjLzaFE5c8lUbSVA4lMP64gHsKgQAAgJHEA8IA9Ddou0cyx52JxQAAgRpS641h4hygAzHbJmht1NSFPolhkgFRqsDbYACFlPrJnBvrgEVOfabTJ6g0GZL+sAgtVLon6vzUyIIwHeYCMe18D1A2lvY3nR7xaHFHSp+GUI0sUacgI4Il6nIw+Nuv8YUg4wgABAYAAEDANEQgACrAcEa82dg1cdc6B5yLJiGMEZAYaQnBVYoG76hZC3pysU7tz1rxPK/bjR2eGOt/se89h4T5T++uRUNFYmYVf7HvkwzJJdGTjQjI5NbipAREW2AGqyBIFW4HDNQZojTdxjYK74YtiAav0ywPhFgB6EggABAJAAEAL9CACCUnwataeAAnAcU9gS7oEwpckGfKuSlgBAAE1Pk+/MlKwGm5nJ+1GJFKuXEGOOgPtYeHSLXA2U6AbsfEbNE5ym1qZCN6JDsjcJlfmB9twDaH0oDwCASSqb7bAAgvoCwr3CjhYgt6+2MkogDfmBwgABABoAAgGAgMABxlVFKkAvhrvdB7KdMXcnZwDnmQMKhiWBhYrebAkrMJ+vE60Kr8ZMZIQX8aehzI0g0bpXVyOJh68wZZB5CqoL21abzykp+8DGQEL3UNbP6XZ/yVeEJOr/MIAAwCqAAgIggCnBgBVIZcnwe9RYxdhmCj73sh5Axd+8/H22we00EtiqcR8TQHJw+iOigtYAyqYnON268vtsbgAah9mqsbYF7ilrnqd2AZH01dmHJixm/Y0G4c/3O8Eua/YZOWreMCBAOAIADYQDDgDgAXUbTD+UwwCE6PYRK7APjy0xgbRbn7cr9A/9nBg/GGzHc1EIVKf3yAwyzADU0WDEivr0dX4nisoa/3K0AJPaV/gws9w8okC1FPCrxBjWPvBOkv0JE3QErCsiq1wczHQDZ8oygUm+NAQXvp9lpHPjCs/CQABAhcAGAwCAt54SEQtYwBATf9+P5mAjR0AOCz/fjrYPWCxrD6sqk2DUbsCO3+4NUYH0RbMmIupcyhLCosu6yhB9tM5ppiqfujpd5gEpAWTnuuqngNRKn/WybGyeQCSc+q8mmVjR8SmEosv3/td/+EBAOG0BwBOABehL+NitwsDH3ORnMyBhuQ0FgMrTF527pVsw/TuV0+BcO9D5i4XV9ZshSls6Bn2MsSFUz4ZZVsuMMX0i40Vh9nDyeQ1oeDYodgFUzT9LxrHphRkgEgJrkYrsu/uNRvKRVN2JgL5g+/TMPsc18j8/xbwABAEDoMm2yjInmPwgABAFAEGOhAALPWA874RSDqrdW2knwYJG1mHOQgAAgAQbg3DSRS2aYK390TQYF+5YmM37v9UKlXPhTz/bRJvueusyTCcGwmlfaJmWPPL78AjqZ0G2fVvgxoyReqhrN+X5t9f15rY2G825kyoIAAQCAvgAUECQPYLkh9swK2U+n7//Pmrpk2BgmqcGvg5Gm0QA19Ou972P/37nbJthZVcozrwHsnr1guC1Yq+TCW8IT2gQPE34b9EIF13vo/THrInaoFtB/LaaFBdpDFs38rk+1cMKOIkdETO/aQAm5mCYUdBQABA4GAAED0IgACASU++RRHmDvBCj+uNAvcgoCOqBJeCrGcjhq31M3wsvJV2AZjJHf5fRToYJcv8v6eYcegvlFbM5AdPOiKFjBd/c2HR52EK9D4nJE57lgxXeFTqZAE3PQQG3tkJzjVpwiXBPSZ2/zpQLXYSDvMA6C8owQABwcASLBBzjgMfTXrT1SUwMyhyuDfqlohnC/XmnLcwk7g/tcBKAfdNbCrFGWh5ZcL0Ovotkx0OvvJyh+uGIDCDK5vBUii8ydlHNVm8mE7kzp9aJiOZiio0oM/IIKlBcY0IQTC1Zaq4OKV+/Dx4H61dkk6psrwGaYykJ+SVVjwgQDAAEDIYABEEJ45bBIkB+CTYyOQBvkeAAYUejjXY+YrY5WEWo07q0zbSZAkl/6AYP5Bnbf80QMwvqBtfMmiNjUw7/6qqgcLNSHJ7A4E3wuVrYUzT84IqZIfgI3bZUMvOMD4yc8SOXdeK0IUYmNeDVzhNPWaK7t+EAQABADkDgiwBj1AUYqwEDCNvwyojyUTjFmzQEUaUFgWQelw9kXkOacIIMNczhjGpG7NzeNp2tosH2MMHfwTzbYXmvDE1SQOXIGfmE08GBvMAQj3V3YfaYzAFFzIghxx8FsQVx+HYQAECgPVCAAgikBhATMMZWJPAAQj0YCgTYNSUwzwOSLRnwbgEPZB+4N/yLA+qwsl2XfEhJcPe/z//7DdaOCNqt1xkYdre9t5sPe0s6kvF6CEyJ6W23n3gvO/TpzP//owmonq1Dddddddddddddddddddddddddddddddf+OOBhsMcABEH1QxXIwrcQ5vwbAqj3MWZw7syuHEJ1GAlONqceEJ3uhwAEMy4g6l7ieRqkmokTOQB3FANso00IRVI/cAuEdHUUoouzzRP96DmFgzPq0KE2d4/YHL4v8HHiqIVhp9iFIvAuFcge24rtKnC376HgbLvTg8vTluv/mBLAQByuHGzTNwGegLQtqLkf33g4HLgY0pzvp6fuh4ALJQYNTnTbyST98H46b/9/1D9ddddddddddddddf6Q/kCDgYAMZ0Q/jFPV4o+5mXAASmymBA9WECkfCixCAAjgcLgUJQAnyPAnIYAET6HobMBnAthtDRVicXQehqR+uhrPmYIkFdrsDpwCR67DYFLgVmOe7bpf7wi8Np0cQOdMISVZcAx+9jEjKnEILQOJemPMUaAHLMETlA47O4YcBjPcCEAAQFwo4IBdwLtEqYx1E1QKMsHhsygI3MHgBL5xWaNEg6sTh0o0WXCWfGyMnnslQ1+UMze/5DcQ8xJGa96u4eK/qAFByINxH4OPoamft/emgcGb8lFYsd5Q4zwTH9PBxQxzh4sLLdOyEAgACCQoAAQEwgCAAIAejCtNqnjI6MVngPkgXMEuhXPmfwaWeQ6cwYmE8zvAYmzyssM+C2WCA0Bl2eCKiKoqgcX+RBXN4CK+o8MoGKq41dqSqqZturfJfBUgSWWnsEo3AKuO6ORFpW24SSlQz/3wGKZBAIAAgHgBoAcCAANSi9MC5Q25MQZIDUgE+yIXEQpgBt/hnX44vH+/H5qM8DG/b+AdRbw6UIndhN7lmd2cM1IwpHQmyU3DZW4ov6j9lqp4mzg6/uESUixgrj17COs02X0wo96ShIJUyvAPqOFwOkdsEAAIEBwAiAgFu2qUow6UBdFuucdAIBqkBFLBgyswWuOpN+20VCMiVDuzhFntgC0gYJK8JI4WSN+mDN0cx1DznJqfoVtGIBwDR9UReBt/nX1gs/6Hsolw2rdxfz5Ps6CktwNJIDQlF/cAZrOEYfAwAhimGAnMs0PwhLxYB9/mJoyZZ57ADbQFDE/332Bf3IDjKlKHFKERdUvlXFiOk4xyLBWucbx5MqvDA0dbA4WFag+/etwRBB1Zb11p9z5svKd4LLzAjo50ItUDJFlPrD+8UAA1b5YfC7DyU/wSsBa2uwP5RhcDpCO0EAAVABRfw1gACAJxWjxsEWwWtzPHEpQcvCQb2Pslmp0SzZEn3PTTi2D7hHyIXtY0Ef/9zYtbFeY8Vr8MXgMoynfUVRaT4mYgfBJJlvzAg2a++lONcLX+H4QksANpcD9dAn/wkaM3mVc25o1/cspJIGWh8j8wbbAlAUeeB4N8G8wzcRgNoDVJuAJGi1AgABALAGywwAC/Ot+TEVMREAAEAlz7lRysDcKJiu3LJByiJYsHtTMdynQAySAUs2q2hx7zidr2eCRAprnF+S6zQig2y6z5YhqSit3v+ieaAaVB+y9YkYajHDIgmKoT+zf7QoyJ+qT20Fn3/aOkUCMrD0K5k1wjk20SE243NFOeCAgAVoOCABMMuAGpY0LsBcoVqdxCJsDTwLmm9YACAAEAXk+zn1br+g7LioAgAd1aa/AdsPW3Akp9+pjYmwkzoKzjV0p0npPp4TqOCvEN5/qfqYMja+wr5b0mFdAN6gsDx2jLZyr8/viTARlGG0eCAAICBYFAwgB1JqAAJgHggBe3bRZSKNjDpD0hgGCrJJH7uHIAT1g65gBBLJvWbeNO9kFYmHWRFkVmgGOOjneyyzPC9jaTNyDKGeyOvnr5zOjBzY1fozu73OwsUFOf2CQ57oKkcWMt6BHGCQFi8mgGjkvNBfRKuXq+OQqtQggfwENcHBCCyADK3JD7SIgmAFQEAAICgAAgDAEATCAxgB8UukQGAXyX+w6LsggAGRreSjaMBxEDA779kMOdGrDCS9/7HmKMaRdU7FYkYLH0VQ/IJzJT+67DSrgzk2N/yghwsJCoKZJ65U5xBncXvCFD7+Ik+mIySapM/WiJXoegwFjI4BTwHEgiWMhwygHOFo5P0hQ4utEHeA4AEBwYECIDTjK2kDzxQCtyxoZnDrdi/bMyIG3UIsg8gxDKSMB8KwFeTcrw1of1bDQu5lDNc6dnUpsSAJ+R5kPYylg1h1kClhlfMIBuX5IJctgUIeut5lCIJs5qjK+0txNOmQgKzAppRo+8MPmTxSi9YQgACCJAABBXCjYPfiiNAAzgCHfrGaMGWITN2SoqIZuaO4vtoMb6w0Nj0YP7Ig0AZAWEugaz+r7/GPMC33noItTZw0nCmphBw3gLjykOBRz3BUG9ctwIXTx2yiBxzpcHJntGEI64md0oq5i6ppAyz2C0cBStzIUIJIbKg7biChuVxTO2jFKiAfVGOMNTVcIAAQBwA5IA8JBiD8WZuxoGYQDL/qVwIhwHpQ9fvRSpG7sRgAEAHkI9nG5KhM0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kCRoile5hYrE3Fif4AaLlDcToUUgZQyp20mxDqRKXp4j+n0ZlH69iad/BkHFeTHyPtIBQWvm4CJwXNBEAAQEgMQEAAQzg74ABFigfiq7BLMHDANAMscr8fDgiTZmJooFMbi9Nvp3oJMmBTf6oH4sINtb30DpDe5vMtj24cnYkvjI4AKJbowT9Ur9aCHB+nbRzPueGEIpIwsmwU/YcQWRB742yTK3IIAAQAxQVgIQABAHBQOA5xwIJsqkL3tn3bt6AEfQPmY7AnsSCDUA1R+YPIJkwaj/NmD46xo6jOopfzyUj3pjetWJA+NgJjNoYOOyEF0qaBLx8Elgqj5OQRrI0B5l7iARbuFULV9E2qaCDDqEmngTjwMAAIFAEAAEEcIgA3DgfZEzDQCyCHr+BpjJbpgABACS1KlgQJuWO4DAmTZwd2EQiWteRNZgL7z0fAQsTA3A50TMAOyyvR1gBkvXlDcqd6XCIfiCuc5hzwbC1v9yiwyW4sexwBesE+WBUAPWioXPDjNMcm28IAAQHgAHAFg0FDQLkhedzmBL889mWMPEOIJ17BiOAAIAu8oAAgEnATu7YUFVGJaAj2nK3DDWZVTgABADvfH5maHcicwV/B34AyHbEhcqLNXBSNfVVhA9gwCmh57MP75wA/GiwYpkQE08phDkyqLswwVIFd2aiw9X4BwABAeAEMCAAWLKRbXFAsCSpwPwAapm5DHAVhWvv0LYmg5vGyOYXdi/0pj6IFVsdzDdZ/OMid1WgeNgzDqeDEVN63jemYOR+wypTV8n33f+RmqMF1F8YVG2w2sOkGNsBRgoAUBhADYAIoDEiIBQJorb22G/UX1rMGhWL/AZoUqQYR0L+9hZH9iklVB0Vf9swJhPU+Gkg4QPMK4+O40dlfShlPGtiP7uYSFd+tJk8ZO4se0oOKgsNt4QABgBQeYDAUFsgcUI8rPOgXTiF05fx03NPSMAJUi6cGGkqvFtGPU+vw/sN8B96XgFiWAL2DnB6gAGBQb+4QAIpRQFrAfjXkPMfOwZAABYAwMuYP+TMVRzPB6huuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuv/r6IGHA1l77AAHVjViRyoefLr44yyDgiV/ZMzDe9jw8WG3mOBAAEQhRYSiODoHCAAWhPuUoDL4r7/gHcdzQ5UGrLYL2qz7dQs5osXMn8SygVFk7kbW8Km7wJHfjNwYeSkhpRDgIRvH/2Ey748eG/xcf22ATJIasBBL2xCC8vHAgAQoWeCAAQB0Fd46YDSMhgAOIukJtuBaHl9gYSsgtzlMRPs2oyPAZMU/2vbNkFSEaqBg9VOGonTqiKmaClUVF5aoSiUDFfHtTw0E5V28IpNL1/aAV89QupGSaYt2DFSOAv9fEi2gJFAcGzX6HdBBAAFA5YIEAC+hWgbHGlpAgLtNiLmH5rDt4gi2ww5CcVkyXAAI4BxG7FsVXT6OMeDZWYLkOio0+TALjtWlwGkzoXPf5g12mPsolkzk40FVnEQ4eXO7lgKe2MkUywKjUvAW7TYKV5lAMbeCIBzwRYIIrRAVg8bBMLrAw3a2jmXiyE5B0gamd3FmhJO6shoJwmsEYwG0X0/pozxLKMy6rf2D7J+KVhe/GqeJsGkec+2qC/c2OEXb0Mbziz/Af21wWH12rd8n8vqkv3pslYrqBNfT1BFnthiO3UM14GQABAJBAiMs6tDnLENhgN9mAbBuKbJZ/yEABv0AoREXTr13PmxpDz1SsztngOrMnRRf3OnHpgyP+eZxrYuilJ2Os9Ew8AL0cWDONsH00GB9DnAwEDe+hLz8AHkoAI3VMwZDTfpRDCpyad9eAYVBzrmv0lV3NvABm3Y1GcfoMAAwAYAAQV4VgwBdhMxDrnL4INPatDQzRzOEDFXSi8gRcFB1crKmzMIiFHC35kkgCnK8o2TDTKo6D317shpPgXd9PJB/sJKxQLwswE7E9ddXuS4yDVgr8NXr0GWDAnkg1YDA4+9CHsgnEHHXFWTCbdS5SYZ6Ex3u7a3bVXnCLJa68IAAQEQAEBgVCQQ51O8nlkzj1b0IOOMY1Xlz7XtnlkCEUIJP6cUzFgF/fVWl4ymET6+tMH5AOGwhJSE505ykWrgFc4F8yTYkKObcBNQJwoacXRrTiLqYGXHzMC3JKdWlGpMaFHAVtzLzEFKvWk+fYwEsDhqyrTCujjAQkAcIAAQHgABAXHVDkA1Wvd2n2t4/vzA1lKBRy7OFZ0DuCFbiNF4IqxU1I8TmWfKaFDaIfl1dpeJ6XS3hUGKJGguonr+6bBhd2EGMvAuudtA8MQvvHNRgLqv2nwCOpugCSboZEAV4Z7yKiWLf4BOShlMCInwaZWgd7xr5Mfqx/Nq9gUIAA6AAgBy4QAuI3IogWFPxFBPzJ2hacrsxT9//O1JjyugSBhi3QA0vqShb3q96WD4iP/VT2/MGtt8szrBEjbi59VXE5mwlDx0CgNNSVNDDZGPTfM9QZBRXabS+l4QVb8aCDYqt18MgACASAOwgB7Cg/6agAYADTOgGN0160w5xAMD1EBZg6hzUbkb3B/ZMxdnMDM67wHe+WZjgW37wS59X7sRPtR/gEo4tI8fPgqdLz1+3Bg+JOoOWlpum6phAAEggCRcB2gLWUVeJIGD/hhijbsMAaKgIOaMZKBraUDKiSfgb4iDQCafOfZ1BW+AMbSDxKpGw8BjMhCx0lJB3fPycAW/Da6Yqge4tOQWP2/CAAIhQokDAAGRCHguPMJs/k/cB9fgAYB0pO7eZ9wLg7TZo9nxoEQ3WDgEwMmLFoHiARDbkXHu9s+tivEq9gIbyjMieB3JQHL+h1kAdIUeYlH735Ecc6VKjeCPBc2v7/78YDDhAACAaAAIAQAwHQgACE4OGDtBawc0O4nwCMJEDLiBjl41SqX5fC3eeJJhtgkl/gHX23tEABCfj72wejydU9A46wzK484Po5yNzbyh3NmgWCOM/OPicNPGQQDJZ5EeHp+DAALivhAMIFnfoAGAASZ1sxkgydxvYsDEC4QtANQdSsBlGyU+PTJ/CpC/2DFlkAKk7KpW14DoQrIjagavdCnSzN9RHq30wAt+9jNtL1Y/h/3eICjyhxqzICRABg4MECCAOwGhIAyA9y00bAAKgOOfmvcSCJSB4Al0DAoiaEk5XZjJSsGzdnb3sLIf6ejI/u/A0FHVh8xn7HIaApOWtOMeM7AvRsUxfciEQl5jPBIBXncNHIDHQmpiv0894O8ZYHn8aHeMeeSsIABAAEBwgALCkCYNugjGrC7mc4CFhBDgWqODBWfM/++/nij6MVHzG5UBJSY6/evpe7GHz92oqiBXQAh+BU/RaucEp2WsuY3wZrCrUcgApjk7ISC6S4bG8a2ep/fDWCDR33ZAJEWOOUCEAATACgWAFAggdWhcmUACFHqF2A3KprijgX1TEmYkfPDQ7k0NBcyefnvBCHC1QI2v3lRIjBmxAU5uXkUx9mLX/lrWPvmpj0/uAaLwmDpI7Ua8oSq2yMGBAYMycyJj2t9LDgMcXeicl9e4IACAAIBlASFAIaH+/76eBC20waozwAAzsKh0TbpWgYqW/fb2eZgevWai8IaNYNhFIcbMa6bBMtESmrHzcZMBr1M3XgdpjCJMeBUAG1AguqJm04bhj1Pm44FW2UcHmI+JFpOYBwACIHeECj8AINxAG+YAQCEZbkKPONbWYG4CntOIWX/MKBiVMXniIhLmT1DR0N1v/X7kiIY3fsqmnabNO/2qbgRlWqw2TDDZ3T/92FMcCBDpiH5EkadYRK0MTiegtfI6/KyEACKJXCDgnUdzJh5gBB+/CQddteYgDnG9pAIHq4Z4kTSDz2NJQZ2C9KrkfW9vPfAGP4PwBjZQ1TAOvc8IwD6dexcdpqAjeIb9wfw7H0j0/ds+2JR6CkgUF/CAAQABAmDACIYABA4CgASshaldmT4cAA2QDhUXIC9n0OmRhAMAbCNl4bic95bbAKfnN0RCzB2u8D7fD+w2XBEhxWgAwzCpE/714P8e8xGz/hAAEgx55yBCaMkNP2VFDIAAOgAoH3MHZsXUnZTnt7//2/qF666666666666666666666666666666/8dMRZLDHAJH69sBHoWA2pnuDT1StLIDoNY2C0Hd834ADP0TdPUn4Icsx2bo2js7yGPPNAwLWQiwcJSQSoyLwbCOcQB+oxkmIW8w+wDCHQwX23rTczfHXhS6VhF8AZGJ5Oyul3vo7hKO8mWIDT1yuA+o8EnAHK8kWy/77xwy39XMAAIBP+8cGMDGDOV2x3d7ozbziAAEAIjC2L/f+jipj/9WCxpMVzARkDDFfh48ok7fT8IVtEQQMdMH6Z/4e/6h+uuuuuuuuuuuuuuv/YvB9BwNQDu3sULawABzdAhDfnsef1Us2GtiF/5wjpi/gPcIAAgFuggCdUglGtgTTlQJnuloHCBmS9gdibZ9LQcO0myPRDVjvZv5uDVPQaYhyiFAePXBJmAbUQHVQ3ztOY5rJx8DOE7cSgR/BAAFgcGHQKABE8C/H5uYAisVT6B3IgMSiiMBc/m8w0iQw9+Gv+lgj4NPChekveaaZYO0/8OMcqBAarZJhIu9LA3RpwDumeIhwU1XPY/8EahRRfyjvDAGEFFjOJgGAAEA0B3BgGR29Zicx8wUeDwszwSKSjAamPeSGlUYGIsaTHzHFmY5xMRmm/MH/5/g3vU1SEJCEMgdOF1GgYyulGEsjGNATTyiHq1LZr0OlBVgIX+NSFLZNBCLy9nngg5rMUzdeprnguPwQAAgADWBYYBi/YJ5geAAEABB1ABBDm0GOAjTva8pp6BgGe5r8GLFDDUTsCGm1iE68+xeJ6x5hoo/+uuoYBkLhwf/g9iYHJjNrjCn15QeuWlPMLWKDGgQu6gX6hNjW+4dbe7A4qzCDggACAH8WGABYMA0OkGBYyAbE7SLADADykt+///54T7wJr6OcHQPsQFhygd4xb2/aasMsZTRK6rU8HINLFguKH/r+dS7Ox9Hm/d9gHKBumCvDBNprT4ASTX9za1icKPguzukv/WvGaO9ibmJvJVggABAAABhY6EBvAu8FMnMXVCaTHDnF8/KW2HWhgAEIu13JYJxzihf/3r3ssEoqn9ZszLTGC2ft/sTJROHzf9sOogcnzitbTRO5qPg7pXJbIzmeA5eVkC9neGr2F5hkHWpF1QFQPuqppMTRFqNUEAASCh5gDAEZYYUUZAEFgsOvx4VsnhKuB5aZoPXBpUOtiAu7NU2JJ40ECHhA2H9oOLn434AVNxsIg4N3MH8TDPTqC0nQZNEHf9KUA6bwg3sBgACpQm3VmegsrjNZmx56YRvBVkpnwO/0ox9iA8AnsoVqWUlGwAb7wdmt+h6gQfhCeFUk7ADdjQOj6Im076b4Jyb86Ayz5Fld79M7Le3TCkqP8CAuZAgFAUXIy0gBhSEfvhEADYBr5GYDBqNR/2HAH+BDxLnZUFaOnqiCPhW8A7D8vE/rq2KBlHOnS/sxM75/xlXLwJU8YxCs+ANVswUqQVAB3Z+jIABEAokVIAPwmVzSLfwgIAB2gEBAFT6D2jAYP8aNMAw/8AjKnQADi2DxEs1AHngAgpDWqsoJlVPx2ezMoaKDXBTK+g1Fcs410GIUkaFevdg1qpbqa2AkTCclLHiJBeE64doCAAgAUgCQMAATgPpNi8ktATwtw1e0QFqnoAAgBtb/wmlBkzOzp4B9Q7VphKj3g+KwuG3pqHe1Tl2/E/03wJp5hI4OI1eFCwkCrIrxsTIntobs/MAAQCBub/XJpkvUx4tX4Pmtb/eNNBvpszEj7dDPdMIoARACAAEBgB4QEgMJcXs3X4Asxx+uMsAAMhhE0yMs9pcOVbjQIB+BwfYMLMfbgP9MsV7DX7/DCKG0UxmLKHHvdBNlUOiqORB43V7kgh0Hus0YCTczDvE7YZs+aUyufGuBvvL1bfj6wUir4lVja92s3nx7woAAgFgCgACAsEABC9tsSypxTP5K57CWIAAIAqEbWQclF9pcvL0HdZPJwwS9/x1MsYik/3kiREyo4/7g4FdmPz4LZgP3dEATClsjbT0EYafr31MNv9z8HVnALmw2D3d4QAB8AQeWCEVgUeFdHfu9kPMZ1OHNByO3+YF5EZvtwLERQWTLwFW/9xnSWsyJ5OTHhybsAI1EHSTQBc9i0pSA7PgvftMAAQAFAyn3sIpjMNg0n4D92sTbGfYCxSK+O/gEccEUWMCAAPAAIIA6EQYBQ4Eekk8ABuAxT6o/cKgRQ7y/qCeFDAlZQjpvisa9DI45jk7BvEyE+/6SUiQ6Hen143BjzYb/nq/JMGqQfpexNInc3bgu8A3r/MXsCthnCESFKeCUH7vADJ3pGDgfYX8ojBp+U/9AjNgA90JWhMUk0hlnSnfQZcDzXsfH1eoUccsDFwEBAAEAcGgUCOAQoYJB2ydAbB75gJdqgER49AAU85eb+FhROeeDB6ihnlEYv6wcjehkTBvGLE0rncLcVf60/irzND9bTDvtw95/d7xPmBggdAdx4mFfgcHkg1CDo6Dt2VbFjDQ4uZd2MSmvuvwaNpGQLfwp4QAAgHMhggAMYSvv/+cCaPBD1UlHGEPaAACAJbtZM5k2TIz6R2PuelFMfUgOganqORajJPfPdXWMS89y3poqiAXj4edbDuUGfLUgoOovTaYVR4jmcMsAIWm2QizYgjdegRNvBAUAOA8IACAMggPwNyRkMiIJoGqEHoTXYAAQBddYv3Pu8yN4GZ++wZBHbhqj1ygYQtdlMU4zYFZr9+iqmf0G062hKSmrJUfdakQUx1d3csv43oByoGzg54GWc7MMYuOgAhy6HuWdwgAEgOAAUEAAwA7g4YwGTEAKIHIJugw6ao7ApqDJXDJIeDfYqD31xMNRDPgehUvYAPp9/Xoaex0RhEv/1z3zOP8olzVUk+89H3b2PGR4IVrgfgveC44skCcjOALpw0wAdReRcIX30EgACAYAZoQBAEIvjgNBMyBNlHSpVQFVqIAUBFVEfHGrr3A7TxSLilBEftAyDge17Akd9RPUBUwGPIOQeqxFfM7tSoAyuFYt5J/1x91KSPbf8G05ZHHCDS8VLX3hAAFgAFCRYIBB6kGs0GThqHmv+44DYQ8qYeBvCXeyIDxV/4WbDE1OtXMLoo/EIyy+nw/sNlwAOAYifhnbh8/+DrkhpEABwaXf3CAAJhxDADoD8yeRpDRUDIAAOAAgHXMC2dMjYuin79/3v89QvXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXff66666666666666666/4J8Og4FgAFcW1U7iOpb2EleWSGImbxk3ltPhAAGQIAwdCAlOaALQ0AfAcoGlgAEAAEhAELQeG2X+S0DhBZxpPD5IwYJewDGzSDF3k/xKXw+9/hN1AL8b2PG1VV1I+LbmUfEGjR4EABAFC8BAAEUooFQXAXqZQACPbs+mvWsOpiYGC3UizhlEkMEo/7atKzC7OO5C16h2Bafb5NQntOHUMuUfgLyNlMgyYwetMh+1brOo96oSz8ZyBQOWVw8HLAMWp4kg6oIjVAYx+sjNOC0t4pa9QBoRNBQABAuwAAgLhBCMeGASpD3JTwHszEcdTtcGFBjmJiPSQYILxaXVgMVw9YGL1v10Ig3///9ZNbHqelG/dOmDNwf8YltS4ilnl3xsG3hCBABomFPDpj1uARhP1IAIRdmHrSliM0Hbf8Ii74sR34SAAICoAUkICUwAEefdPruzP4Tas4AAgA1gABTRgcbRPt+Jsa3urqVwb5ow1o6nhhKusT2vMAdR43FbdBuL7/3JwSgUPBifgTEdSYKXIXWR9F5EAAbgIldm1QbLWFBjQELupus6k47mcypLUsppsGr0SYZCOLU3GWkLqCCuHtRniTqekGAAegAAgFwMFS1LIFuHaU7PY7RAenBGmE25PHtSp+CcLOa8WXmRuHQJEWllZmjAkn2qZ4njEXv1ppCXdoI2qp/cVj9tSmGitpSwPGd0r3LRnAIaWP8ga3kCa7rm6KGqBNLYNVQN/bjkjJS0WyG4px69B9LAY2SH9sFXsggunF3aOsgjF2xxjSwEKAAMQIRlXKnMDzQwAClX9id+DcUuSTxLUVmZIHmJGQ288tejI8GJ3u9rkK1iS9OVRNZjIg+TwuIM1rlJ5ehov8V0CocaS7DFpul/CAzPbQTgfjDyxo+L3n9MPdHJ7rvVVKfTyBwcmlKyKJuGV0n9BTygyDwAwAAgDgEAAEEUIAQIF4Ajsx1qUwbFGAiJD5yG4+YtEWDEznA1799UtlyAIAB/T7aSWI1pO4rMDcGeXKPDZ1+HVGve0ACpglP8TQMiFmbdiJvDkZU7fx4+JGezgA038CYKsoRLxuYIHu2ZGggnvUd/G+2N+CKDSf/rIV8pR9O3loyNRsHwgABAdAAMDARA6QD7AVRBCmspQtgSE7mSeUz6lUot+s53/ESEYbijoBqNcA++gZSp0YYyD1RKUDFjfz/ylClydbznqqxhTBOuG3loBhu+anf9GssqH3O8nJjmgGsw1/Z4eLD+oxz+bhAACAcAAICYFgYCCDNqlob6sYXU+IABCFy8NEHKUoRaDAWeBhVzPChXXeEDAAHLmEmYEqjPfaYqXc4dSdta/vNgExHWmfjXgAijTBYdKhPCsAOgkgH5IORBZ0CiXdKkDMd2Qzw32/wgACIAAgPEAAkIAgSnhl0AClHmQGPytUHFsX6Ba4oEBGd47eLg2ueAbuOEkgSt89PSZxgDj92QmdmrSFEhDABz6YJgO0cACEdCWZMNGwMVn2kO2T8YDMWPJNfT5ittHb8+7q/APeHy5tQEAAVADgpII4CHgAlZUKHAtnCugM6LssYE0Q27GObrqOzGgYXgAmS4N1zINv8CFNQI6XGL+dlT0QZi3G7XF9TQZ4axrwmBcrP5PFFZiX1EY5Pv4M3kt/gxNpj09L+1/FSAZtMajML8wQhjiQcCGxYBsgM2h5qocIE30Qhp4YBopVPjqEqqQhTChsmABnf59W+Y2lOPfMyeCCzPJbRD7CshCmFtvvLu8U2f3HvDfgBidIZIAc0BDXgMVMxK5rHYfjXii0aetcf+FGpCPBACIBAmEUCAo3AAAmQvnhwfDgQf4v3FoAF6AAIAjWTpWWmdgQp8w3ZsYf/TwWGsUUxEgVjWaiip0sH7DYNKDTQ2dxEAI/MSt2OGIvlg924/aEWqEf3++v1G80HxJzeO2pmIVckaCEAAQDQDtCAeg4FqHjE3I4YFfcAxC6MJXNyFDodTBgfIwCRApsVPp+Pz76SlMbRBeAxndgRqd/1yYVB3h8nQ6DF0kcLd/E4A0NUukGVdADdQowVGhMJuWcXAmnlMAjak//CKKhoQHJAh9BAjweEAlQHzBQZkwQsbzvnQhnHeatPwEwS5kEkUdLlFcHiySwehpgkrYD82DAxtEt+HBGP/XwCh1etPG7/btRZBCBqD+iWwKiekzlQNtS0MNqEibkHA35phBzrbHBC1DymJfA4QABJwFYEAeoIHy2yTH8OVhYcBtNqPEgUCrl2bUZbJkwwHkZ3gjmXUYNQB2vDMjnRXMLs5hwDZsbZ/nBWJxngVAM1tehMc/CtcyhQ9syFJd+sKlk313Z8lIkIArBowAA+YGCZ1MCG5zlHzwxvsvhhonrOfTH8oU/kGxvpw8IdSIGrT/UAaokF9T8+K7odJypCXmAGEdVv32RZLaYAwrAdNgZA58iqGP+KXpYXIH3sed054HxhAAHwABAYDAbCCNJ4cH3PAACo0MucXjgcVQLpUOEEbxuXkrNpG+wv7EONYBjsczwZETj9nVM3wMPn+USsrWgH8PGH+aglm+Kvi4UcI0uausFfVDKGKKiTomQTk0u5dmQAM26zXHf1CAAPgAVAAKAwMNvBTEs7K6GM3fvMKJ3OJQWTMKs+EAAQKOuX/rwXObbYpBRWZwsajdE5hQgW9CaAFck7FX/LHHxilRK4dK/AUjfX4Rfp7G89zwmtJQBjpIGL5Rw18CAAEAkBwBIBEJDDAAKtohEZiAzBCigwwAMYUmMqkExa+VYp5PyqFeN6NwAI+RIZ+QQWgbNZmIG3IHIJfyS6m3gzzMHPTwARF9ah9vwS/ldm7ElJwFNDGfioAZUKQS+v1TmGjuaLECgnhlOp5sExCTE6xggABALIQAAQCwwRjwAJ6FQ/dwGm4EbaCNih0kEBf0b9wuveDBPGPgByDqCfbAQa5nDgGMyCi+14YZ+oiJJEOHQ4gKMAFCdnb4f2Cv0lbUj8XHsdBztMETqUX/V4QBMAo0JZnTF1CLeZZBZzyAADYAUC7mwRG7sdB1f9QzXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX/CH+g4GgAh1b0tzUiBSbQCAtxQ5lAvG41TEAAJByETBmgBNijYCWCeJ9LQOEBo4XhVPAYQK7XMPv4RekCe0jKDh0C1Q2/mfbkun27/wBgmCUHNBQQdWRFZDArnPbVCIAAgLACMCABEL0CvFESoK8DfgexvkUzaQKA2UCgZAqgBCvIngjFz/r+55tmwdUwfMYcoAyEEnRRY2uusj8QcNFKNp2WuquYIJ1+zCKJP5M+FIBseKM8nNrYlAXExq8X4AWk7iYIcGQCLXPVxeBD/4ft4YABEAAoA6EQGPYJi3zicgoCWj/6/lIJkDg1397ZdQnvCEiun/B59Hv/B0T/3Wsz1wAm+voQ4vPwQffHeuxtaQbvYJ/+1gBc6YoKSIBAF5D6THdcwh2repQAMfL1nQ20BB1hbW9uPAg8fg+o6WEAAZAAIAHAJhAAGJAr+/T6ZkI1+RzgAGVoJofEE0pUkcDm5Rg+xDM6C9eIbrEhZoh+wE/cD61uYT0/ubOtVX9AfHOtMR/1G8x9Y4tnF/uufnC2WB9CJZz1lr5XHuwoAMBUBACJsZwEybIRQADL0+vK//XxVBgeKgHys2FysY2YJlLMLsUz29AiUX3qbc8zUQa7wglg4iRV1kzAAEAKivLzcHV9IEvFo0SBZ67NeYtUCutw0ljO8HRtlCo13DIXNCmr2g19ofQM4JFg1ON+EQABArEAA0IYGDXbcjAERBBT3X6ZBjNxlrYXl6yAAigPh/U2iQuwVYPPf84UhJdVAC7s62hB4tIr8smo0BorDt/3NTUNGscgi1PsfgxEwXvnMnQqENa4m1V/ahgBkHESnHKE1kHe0Am8BXLgL6owZQAg7DvWghX9QAevCAAEBMAAwKGQhAQdkRbUh+FXKAGmY48qd4NwCiAwIkjS3GqGXTA4B2+mNXeTbsJo2AHBtRA/miGhmL+64UVx019MOXEZbHFbrZD7FOTWDgaChtaJ3LyjyXtwPnb8gxgYIAAQBAOGsBAmQ+zwcHnwRXNSCmARbTsBk2YgAHdQUmDBcos0KYBSwELbRocQfqr/s12ErG9fHUyscAFLcmDnURvwLy+amCFBf4fwIAA6AopwIkb2Y9ezWAhOa/AbN9/B0rJB/2qIRz8/7/+iKuqsfvUzAZSrLD14ewi9DFH6cpz1PAHbnHRYEHHAbmLWLxX8oIAA6ADjDgSCwqyz/AwAJQrVg49iJGOR5i+wVh7Dq2bQYAQyTsMzBF54qb6xFDe7+J6IksG2/wtWHWQwsmrrK34MA3GnpgV8sIpVgP28AET/BvgxQTvoFaSr1xb3rCAIAcDTwYBHyBSeYlELog98XDzUY37BOJJFHX+eCbZcxFG/7aT3DEuLPlb0xqMr9EU43ji5WOX9QrmAB1U7bH04LL8SlkYeeR8f/+r/4AaXAuDnh2wnjQP63vBhgYHO51iWcEAAThgDhApg4FDA00jAo2hDRvTilp7XcF8imbk6AqlAoKgkmanjr/K5qLJ7a9NVMHzEJCQ7rECF2/6UnXSn3g70tMHUeqCvFjvCzKCzswYQ0zwbSi95wgsI8i0wZ0j32tBIAMKDA0JvgKgzEB0JB154CkKjLZMjNq7jRiqoBgOOQMijXrgZJ2CUReenqIfo07j6USOYb++/mIegn1HsRgekNUM6R/2Trw7JRpmHvcPYSyuCR+V2GoIAAuEBhkM414e0BmBlba4VZNlnp7BgATYwgPgmgVsB6TEO+FLNIeef0GDyMvWfb/ojCEMDjsRCm8uMW3XSmcb32eNo+rDWlrkBVr0oe4KYABAKDAt8ViAwJEYV54DybtgjjRTXeZ8gAsAVHv43gDxCu40LgT8+j0D/ZuHr7YZ6biAuer1BaC3F1/sJjpCxPrFKP741ZuyEAAeAP8gciQOWDOoPUYBvgYIV6gwdNJB4Bm4ARrT/KeNgSaeIxEsP8ltOCJW1yZt92gpfDrEA7wZouESYgtIR6huW6aE127TlVeEBI2AJaH4qohhF/7R+JZcLVRpEwuWRt7CgAGMA8NIAAQB4NkhxXA+Ci3oDEYEekDKDDJ1WjCXjJeovsVSzHQVolP/AgimPsiGz/gGwWl42C1cYW007CgrD/tN8JDNUrD+uiRG9aUsfyZuVTExYGlbwyWDlLP9y9LPf7G7SwMb/3EZa8aOuHFZxMNV/4QABMBQgsGAzkWAcWQ/8GHyzYMgdzQ/68BzXkGxhaSwOdpysA9rMtlgAc4I98KSYyVhcpSeYeIXioArdscoo44VJ8jjqIFDmAUFhMPMwxdNei/7FRxQATdkhy9ZHv5hAYAA7wiNwgWDOakhAPgOLQZQir805TugAtZwBzhAACBB9wyiQT0S88BSPNkwoXjpwLWA1oJQA7mRjZzHuOuk69fADp7W+r4ozQn3UAGHdtheap4xsqFOOq4LWrGPr8X7/bB7/37gEYFK45AIQAB0AUaXA4ABaBANtzY4TgIvDVQsiUC5I/twf10ge9OAAkr+mje8ZCfDaVZ4zGZ5EZ8Urk85whFn4Y+Ybbqz5AIBLAbgk0FN6wGoCatc89j+ADaAiVkfAHLuPhA59ALblQ4rIyCQABAqAOFiAAEqgwOTsR0KE17gAH7wH8AAQo/XFOICKpGgAGE+AwBWNk7WI5v/QL/Gkxhvld5ZpjRoQdV0/ysP/8NxhDi8ByJXhkgC2mAcLLvGX48BeuMwHwyBMwkcSmPqPel2/znkERLmDAaLtd33y/lFlft6huuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuv//4MOByvl8AIi+U2nNyCgVf8BItlB5sl+qKqr8JRI5OEHLnE8a8KNoHOga9uGMq12qKFDjUkuGvdlbRoBJvfKdz+gwHFk9AQIFNWGAAmdg/5kAHk4AJ+gwGXtO7alzB7IcACum4KKgZrYbgOXuYJ1QEK0LnGmDfGuqICxgzmvsZ1RzGnyvqTMJs8BnDPGwmPGli7AGC2yRhnwHT4jQFQ5gehLpBhAAgYB4kEBHQsYmnWDwG5yIJ0pmDA8ToAbKZJPMpEZJYAagwTdCLdPKtHvwhZ996s4cn59ObMJkqGKPuczWsuLN4zijpP9/GS2xNcvf4wxK/G0QLYny8vgwFEAxEwUA7xG58iPUENSMCaQ6N4FCAAEBEAAg0gEBgBHhgApNg0kIUAHIDwL8zE/Q2DBihvG05k2imcnsOJMJ83BaWex0oTVSU5ZArkT1RQycmjxYQkwld+QWI5i7hJaaaWHbobzxvMXmPmgTy7/8JFonHL4kPGvAEu8hIc4gga6/ICHrB8EAC4BgOCGABgKAyewUm/AAVG/W82zZgJ/2qjJQWOE4ot/poREgrWDvtBAF/iDRL7n+IfcUGrzg8R4f9Ps8pNp4Fv2wBgWiRO0ycKOsJgOkYDgB6rMg7MezjDOT02WYpO4uVrX7ahB+zGInUS751VI8nVDchmvpXT5bRBDivN3PIOJCYL/o680EZKL6vuHXCzu+sEEAqgUEQOCyMigweWCvyEFH+DCnffb1JbgwCEkqayymXABnAHLXZCuG6pGMf/sUdEbCKb0rti8fXEj/+regRrkL7vdOtY3qB1Lgk5aTYlZbuLrsMuOSlwyd5EeOeYIaoDUm+FS79YnMfTNo71KJmghRZJRoErF4eD/mgoOszQOVGH98QEFbCOBAACAkcMAJDAmBTpiNMg8pFdnYN7KAAIBcVatycDgiywdz/GKbQYkPjVV2vVuMKDseoV28AAQAqXb8KMeHTkTQ6Xf/h6ibYNBs7/LMYrU25/zayTIgvXHac6IwAgX2301Xcv0tb7hD7DBZCORrqq/IR0xV/xmnbVf6D7YSYxSAIAAQIgABAaPA0IAAuFoO1+e0wf5zq//g8igs0RBiMIDFEoJDgd3OB7rzCWqcdS3rs+u8nbsH+jl25VeZ4GhnF/75jTYZNeVBDUBYjqUel5AE6QJgKs4DCheSjt+72kiKLMIjvEF63Eoz+yy5wH4QAAgHgACAsDATDgBAVeXQVaClhQFkcUe4QAAQ2gBAZCoV0FQMoAVkKWwosoxHMXEMCjcHiYKOaIGzf32h4qjxHI4+xS9hxLXeE9hkknQccPhMHQBKwsVyDgspMDMHQWOAUMNBAACAaAAoNANBAhg8sGZTpuHwDyaTMoURBYnWI/YgnNJ1jgGNBRBn3eAC5MORh0I7iffsWcKLe+MN+24T4K814/DLXbk9Lzfckht9ptrczRUVEEpe1xI6W31ztJmpLCAAEA4EwcEAGsDMLMzNzz9dMPmWsYoAAgBEt9ZB6MGPafB55FdqcE6u+GQUxdlB6xb9EdFiBMAbEcVRo80i8wLPQgcyo40Gs/nCHojUFCWmIx1cqULnOBym6e4NsluHShr2WgHAAEAHgA4QAKADq4siPTBn/QQFCIAGxaNzS+iinfb7g8AB93AQPXECdgOxKYCKhv74rVwsKTlGQutz3q7rxgnp/VRATNmc2LjcQTl92huSdjgTOzQTGM3N4eaTDvWASleNNX1gW3SmcB+axj1kn0+/TnwEgACBXgABAICOADvPaOSB4nQIA8PjegrxFRJdBoiGCiUxs7CwVu+jPX2aIxlv2rA1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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": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "if 'is_test_run' in globals():\n",
+    "    timeloop(10)\n",
+    "    result = None\n",
+    "else:\n",
+    "    ps_notebook.set_display_mode('video')\n",
+    "    ani = ps.plot2d.scalar_field_animation(timeloop, rescale=True, frames=600)\n",
+    "    result = ps_notebook.display_animation(ani)\n",
+    "result"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now there are a lot of places one could alter and play with this model. Here a few ideas:\n",
+    "\n",
+    "- try different initial conditions and/or parameters $\\kappa, A$\n",
+    "- the model can be generalized to 3D, by altering the DataHandling and the plot commands\n",
+    "- modify the free energy formulation, make one minima lower than the other, maybe even add another phase"
+   ]
+  }
+ ],
+ "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/05_tutorial_phasefield_dentritic_growth.ipynb b/doc/notebooks/05_tutorial_phasefield_dentritic_growth.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..f3bd93a5a3726b726ba5ab0401cfde49d61f55ee
--- /dev/null
+++ b/doc/notebooks/05_tutorial_phasefield_dentritic_growth.ipynb
@@ -0,0 +1,450 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *\n",
+    "sp.init_printing()\n",
+    "frac = sp.Rational"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 05: Phase-field simulation of dentritic solidification\n",
+    "\n",
+    "This is the second tutorial on phase field methods with pystencils. Make sure to read the previous tutorial first. \n",
+    "\n",
+    "In this tutorial we again implement a model described in **Programming Phase-Field Modelling** by S. Bulent Biner.\n",
+    "This time we implement the model from chapter 4.7 that describes dentritic growth. So get ready for some beautiful snowflake pictures.\n",
+    "\n",
+    "We start again by adding all required arrays fields. This time we explicitly store the change of the phase variable φ in time, since the dynamics is calculated using an Allen-Cahn formulation where a term $\\partial_t \\phi$ occurs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh = ps.create_data_handling(domain_size=(300, 300), periodicity=True, \n",
+    "                             default_target='cpu')\n",
+    "φ_field = dh.add_array('phi', latex_name='φ')\n",
+    "φ_delta_field = dh.add_array('phidelta', latex_name='φ_D')\n",
+    "t_field = dh.add_array('T')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This model has a lot of parameters that are created here in a symbolic fashion. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\frac{{{φ}_{C}}^{4}}{4} - {{φ}_{C}}^{3} \\left(- \\frac{m}{3} + \\frac{1}{2}\\right) + {{φ}_{C}}^{2} \\left(- \\frac{m}{2} + \\frac{1}{4}\\right) + \\frac{ε^{2}}{2} \\left({\\partial_{0} {{φ}_{C}}}^{2} + {\\partial_{1} {{φ}_{C}}}^{2}\\right)$$"
+      ],
+      "text/plain": [
+       "   4                                      2 ⎛        2           2⎞\n",
+       "φ_C       3 ⎛  m   1⎞      2 ⎛  m   1⎞   ε ⋅⎝D(phi_C)  + D(phi_C) ⎠\n",
+       "──── - φ_C ⋅⎜- ─ + ─⎟ + φ_C ⋅⎜- ─ + ─⎟ + ──────────────────────────\n",
+       " 4          ⎝  3   2⎠        ⎝  2   4⎠               2             "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ε, m, δ, j, θzero, α, γ, Teq, κ, τ = sp.symbols(\"ε m δ j θ_0 α γ T_eq κ τ\")\n",
+    "εb = sp.Symbol(\"\\\\bar{\\\\epsilon}\")\n",
+    "\n",
+    "φ = φ_field.center\n",
+    "T = t_field.center\n",
+    "\n",
+    "def f(φ, m):\n",
+    "    return φ**4 / 4 - (frac(1, 2) - m/3) * φ**3 + (frac(1,4)-m/2)*φ**2\n",
+    "\n",
+    "free_energy_density = ε**2 / 2 * (ps.fd.Diff(φ,0)**2 + ps.fd.Diff(φ,1)**2 ) + f(φ, m)\n",
+    "free_energy_density"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The free energy is again composed of a bulk and interface part."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(7,4))\n",
+    "plt.sympy_function(f(φ, m=1), x_values=(-1.05, 1.5) )\n",
+    "plt.xlabel(\"φ\")\n",
+    "plt.title(\"Bulk free energy\");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Compared to last tutorial, this bulk free energy has also two minima, but at different values. \n",
+    "\n",
+    "Another complexity of the model is its anisotropy. The gradient parameter $\\epsilon$ depends on the interface normal."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\bar{\\epsilon} \\left(δ \\cos{\\left (j \\left(- θ_{0} + \\operatorname{atan_{2}}{\\left ({\\partial_{1} {{φ}_{C}}},{\\partial_{0} {{φ}_{C}}} \\right )}\\right) \\right )} + 1\\right)$$"
+      ],
+      "text/plain": [
+       "\\bar{\\epsilon}⋅(δ⋅cos(j⋅(-θ₀ + atan2(D(phi_C), D(phi_C)))) + 1)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def σ(θ):\n",
+    "    return 1 + δ * sp.cos(j * (θ - θzero))\n",
+    "\n",
+    "θ = sp.atan2(ps.fd.Diff(φ, 1), ps.fd.Diff(φ, 0))\n",
+    "\n",
+    "ε_val = εb * σ(θ)\n",
+    "ε_val"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def m_func(T):\n",
+    "    return (α / sp.pi) * sp.atan(γ * (Teq - T))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "However, we just insert these parameters into the free energy formulation before doing the functional derivative, to make the dependence of $\\epsilon$ on $\\nabla \\phi$ explicit."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$${{φ}_{C}}^{3} - \\frac{{{φ}_{C}}^{2} α}{\\pi} \\operatorname{atan}{\\left ({{T}_{C}} γ - T_{eq} γ \\right )} - \\frac{3 {{φ}_{C}}^{2}}{2} + \\frac{{{φ}_{C}} α}{\\pi} \\operatorname{atan}{\\left ({{T}_{C}} γ - T_{eq} γ \\right )} + \\frac{{{φ}_{C}}}{2} - \\bar{\\epsilon}^{2} δ^{2} \\cos^{2}{\\left (j θ_{0} - j \\operatorname{atan_{2}}{\\left ({\\partial_{1} {{φ}_{C}}},{\\partial_{0} {{φ}_{C}}} \\right )} \\right )} {\\partial_{0} {\\partial_{0} {{φ}_{C}}}} - \\bar{\\epsilon}^{2} δ^{2} \\cos^{2}{\\left (j θ_{0} - j \\operatorname{atan_{2}}{\\left ({\\partial_{1} {{φ}_{C}}},{\\partial_{0} {{φ}_{C}}} \\right )} \\right )} {\\partial_{1} {\\partial_{1} {{φ}_{C}}}} - 2 \\bar{\\epsilon}^{2} δ \\cos{\\left (j θ_{0} - j \\operatorname{atan_{2}}{\\left ({\\partial_{1} {{φ}_{C}}},{\\partial_{0} {{φ}_{C}}} \\right )} \\right )} {\\partial_{0} {\\partial_{0} {{φ}_{C}}}} - 2 \\bar{\\epsilon}^{2} δ \\cos{\\left (j θ_{0} - j \\operatorname{atan_{2}}{\\left ({\\partial_{1} {{φ}_{C}}},{\\partial_{0} {{φ}_{C}}} \\right )} \\right )} {\\partial_{1} {\\partial_{1} {{φ}_{C}}}} - \\bar{\\epsilon}^{2} {\\partial_{0} {\\partial_{0} {{φ}_{C}}}} - \\bar{\\epsilon}^{2} {\\partial_{1} {\\partial_{1} {{φ}_{C}}}}$$"
+      ],
+      "text/plain": [
+       "          2                               2                                   \n",
+       "   3   φ_C ⋅α⋅atan(T_C⋅γ - T_eq⋅γ)   3⋅φ_C    φ_C⋅α⋅atan(T_C⋅γ - T_eq⋅γ)   φ_C\n",
+       "φ_C  - ─────────────────────────── - ────── + ────────────────────────── + ───\n",
+       "                    π                  2                  π                 2 \n",
+       "\n",
+       "                                                                              \n",
+       "                 2  2    2                                                    \n",
+       " - \\bar{\\epsilon} ⋅δ ⋅cos (j⋅θ₀ - j⋅atan2(D(phi_C), D(phi_C)))⋅D(D(phi_C)) - \\\n",
+       "                                                                              \n",
+       "\n",
+       "                                                                              \n",
+       "             2  2    2                                                        \n",
+       "bar{\\epsilon} ⋅δ ⋅cos (j⋅θ₀ - j⋅atan2(D(phi_C), D(phi_C)))⋅D(D(phi_C)) - 2⋅\\ba\n",
+       "                                                                              \n",
+       "\n",
+       "                                                                              \n",
+       "           2                                                                  \n",
+       "r{\\epsilon} ⋅δ⋅cos(j⋅θ₀ - j⋅atan2(D(phi_C), D(phi_C)))⋅D(D(phi_C)) - 2⋅\\bar{\\e\n",
+       "                                                                              \n",
+       "\n",
+       "                                                                              \n",
+       "       2                                                                      \n",
+       "psilon} ⋅δ⋅cos(j⋅θ₀ - j⋅atan2(D(phi_C), D(phi_C)))⋅D(D(phi_C)) - \\bar{\\epsilon\n",
+       "                                                                              \n",
+       "\n",
+       "                                            \n",
+       " 2                             2            \n",
+       "} â‹…D(D(phi_C)) - \\bar{\\epsilon} â‹…D(D(phi_C))\n",
+       "                                            "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fe = free_energy_density.subs({\n",
+    "    m: m_func(T),\n",
+    "    ε: εb * σ(θ),\n",
+    "})\n",
+    "\n",
+    "dF_dφ = ps.fd.functional_derivative(fe, φ)\n",
+    "dF_dφ = ps.fd.expand_diff_full(dF_dφ, functions=[φ])\n",
+    "dF_dφ"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we insert all the numeric parameters and discretize:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left \\{ \\pi : 3.14159265358979, \\quad T_{eq} : 1.0, \\quad \\bar{\\epsilon} : 0.01, \\quad j : 6, \\quad α : 0.9, \\quad γ : 10, \\quad δ : 0.02, \\quad θ_{0} : 0.2, \\quad κ : 1.8, \\quad τ : 0.0003\\right \\}$$"
+      ],
+      "text/plain": [
+       "{π: 3.14159265358979, T_eq: 1.0, \\bar{\\epsilon}: 0.01, j: 6, α: 0.9, γ: 10, δ:\n",
+       " 0.02, θ₀: 0.2, κ: 1.8, τ: 0.0003}"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discretize = ps.fd.Discretization2ndOrder(dx=0.03, dt=1e-5)\n",
+    "parameters = {\n",
+    "    Ï„: 0.0003,\n",
+    "    κ: 1.8,\n",
+    "    εb: 0.01,\n",
+    "    δ: 0.02,\n",
+    "    γ: 10,\n",
+    "    j: 6,\n",
+    "    α: 0.9,\n",
+    "    Teq: 1.0,\n",
+    "    θzero: 0.2,\n",
+    "    sp.pi: sp.pi.evalf()\n",
+    "}\n",
+    "parameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dφ_dt = - dF_dφ / τ\n",
+    "φ_eqs = ps.simp.sympy_cse_on_assignment_list([ps.Assignment(φ_delta_field.center, \n",
+    "                                                            discretize(dφ_dt.subs(parameters)))])\n",
+    "φ_eqs.append(ps.Assignment(φ, discretize(ps.fd.transient(φ) - φ_delta_field.center)))\n",
+    "\n",
+    "temperature_evolution = -ps.fd.transient(T) + ps.fd.diffusion(T, 1) + κ * φ_delta_field.center\n",
+    "temperature_eqs = [\n",
+    "    ps.Assignment(T, discretize(temperature_evolution.subs(parameters)))\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When creating the kernels we pass as target (which may be 'cpu' or 'gpu') the default target of the target handling. This enables to switch to a GPU simulation just by changing the parameter of the data handling.\n",
+    "\n",
+    "The rest is similar to the previous tutorial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "φ_kernel = ps.create_kernel(φ_eqs, cpu_openmp=4, target=dh.default_target).compile()\n",
+    "temperature_kernel = ps.create_kernel(temperature_eqs, target=dh.default_target).compile()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def timeloop(steps=200):\n",
+    "    φ_sync = dh.synchronization_function(['phi'])\n",
+    "    temperature_sync = dh.synchronization_function(['T'])\n",
+    "    dh.all_to_gpu()  # this does nothing when running on CPU\n",
+    "    for t in range(steps):\n",
+    "        φ_sync()\n",
+    "        dh.run_kernel(φ_kernel)\n",
+    "        temperature_sync()\n",
+    "        dh.run_kernel(temperature_kernel)\n",
+    "    dh.all_to_cpu()\n",
+    "    return dh.gather_array('phi')\n",
+    "    \n",
+    "def init(nucleus_size=np.sqrt(5)):\n",
+    "    for b in dh.iterate():\n",
+    "        x, y = b.cell_index_arrays\n",
+    "        x, y = x-b.shape[0]//2, y-b.shape[0]//2\n",
+    "        bArr = (x**2 + y**2) < nucleus_size**2\n",
+    "        b['phi'].fill(0)\n",
+    "        b['phi'][(x**2 + y**2) < nucleus_size**2] = 1.0\n",
+    "        b['T'].fill(0.0)\n",
+    "        \n",
+    "def plot():\n",
+    "    plt.subplot(1,3,1)\n",
+    "    plt.scalar_field(dh.gather_array('phi'))\n",
+    "    plt.title(\"φ\")\n",
+    "    plt.colorbar()\n",
+    "    plt.subplot(1,3,2)\n",
+    "    plt.title(\"T\")\n",
+    "    plt.scalar_field(dh.gather_array('T'))\n",
+    "    plt.colorbar()\n",
+    "    plt.subplot(1,3,3)\n",
+    "    plt.title(\"∂φ\")\n",
+    "    plt.scalar_field(dh.gather_array('phidelta'))\n",
+    "    plt.colorbar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    Name|      Inner (min/max)|     WithGl (min/max)\n",
+      "----------------------------------------------------\n",
+      "       T|            (  0,  0)|            (  0,  0)\n",
+      "     phi|            (  0,  1)|            (  0,  1)\n",
+      "phidelta|            (nan,nan)|            (nan,nan)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "timeloop(10)\n",
+    "init()\n",
+    "plot()\n",
+    "print(dh)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<video controls width=\"80%\">\n",
+       " <source 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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": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result = None\n",
+    "if 'is_test_run' not in globals():\n",
+    "    ps_notebook.set_display_mode('video')\n",
+    "    ani = ps.plot2d.scalar_field_animation(timeloop, rescale=True, frames=300)\n",
+    "    result = ps_notebook.display_animation(ani)    \n",
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert np.isfinite(dh.max('phi'))\n",
+    "assert np.isfinite(dh.max('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": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/notebooks/06_tutorial_datahandling.ipynb b/doc/notebooks/06_tutorial_datahandling.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..b24a667b2a15dd2a6432657323d6663ec31516ed
--- /dev/null
+++ b/doc/notebooks/06_tutorial_datahandling.ipynb
@@ -0,0 +1,786 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mpl_toolkits.mplot3d import Axes3D\n",
+    "from matplotlib import pyplot, cm\n",
+    "from pystencils.session import *\n",
+    "from pystencils.boundaries import add_neumann_boundary, Neumann, Dirichlet, BoundaryHandling\n",
+    "from pystencils.slicing import slice_from_direction\n",
+    "import math\n",
+    "import time\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Test to see if pycuda is installed which is needed to run calculations on the GPU"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    import pycuda\n",
+    "except ImportError:\n",
+    "    pycuda = None\n",
+    "    print('No pycuda installed')\n",
+    "    \n",
+    "if pycuda:\n",
+    "    import pycuda.gpuarray as gpuarray"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 06: Datahandling"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a tutorial about the `DataHandling` class of pystencils. This class is an abstraction layer to\n",
+    "- link numpy arrays to pystencils fields\n",
+    "- handle CPU-GPU array transfer, such that one can write code that works on CPU and GPU\n",
+    "- makes it possible to write MPI parallel simulations to run on distributed-memory clusters using the waLBerla library\n",
+    "\n",
+    "We will look at a small and easy example to demonstrate the usage of `DataHandling` objects. We will define an averaging kernel to every cell of an array, that writes the average of the neighbor cell values to the center."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. Manual \n",
+    "\n",
+    "### 1.1. CPU kernels\n",
+    "\n",
+    "In this first part, we set up a scenario manually without a `DataHandling`. In the next sections we then repeat the same setup with the help of the data handling. \n",
+    "\n",
+    "One concept of *pystencils* that may be confusing at first, is the differences between pystencils fields and numpy arrays. Fields are used to describe the computation *symbolically* with sympy, while numpy arrays hold the actual values where the computation is executed on. \n",
+    "\n",
+    "One option to create and execute a *pystencils* kernel is listed below. For reason that become clear later we call this the **variable-field-size workflow**:\n",
+    "\n",
+    "1. define pystencils fields\n",
+    "2. use sympy and the pystencils fields to define an update rule, that describes what should be done on *every cell* \n",
+    "3. compile the update rule to a real function, that can be called from Python. For each field that was referenced in the symbolic description the function expects a numpy array, passed as named parameter\n",
+    "4. create some numpy arrays with actual data \n",
+    "5. call the kernel - usually many times\n",
+    "\n",
+    "Now, lets see how this actually looks in Python code:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 1. field definitions\n",
+    "src_field, dst_field = ps.fields(\"src, dst:[2D]\")\n",
+    "\n",
+    "# 2. define update rule\n",
+    "update_rule = [ps.Assignment(lhs=dst_field[0, 0],\n",
+    "                             rhs=(src_field[1, 0] + src_field[-1, 0] + src_field[0, 1] + src_field[0, -1]) / 4)]\n",
+    "\n",
+    "# 3. compile update rule to function\n",
+    "kernel_function = ps.create_kernel(update_rule).compile()\n",
+    "\n",
+    "# 4. create numpy arrays and call kernel\n",
+    "src_arr, dst_arr = np.random.rand(30, 30), np.zeros([30, 30])\n",
+    "\n",
+    "# 5. call kernel\n",
+    "kernel_function(src=src_arr, dst=dst_arr)  # names of arguments have to match names passed to ps.fields()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This workflow separates the symbolic and the numeric stages very cleanly. The separation also makes it possible to stop after step 3, write the C-code to a file and call the kernel from a C program. Speaking of the C-Code - lets have a look at the generated sources:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
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+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">_data_dst</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_src</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_size_dst_0</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_size_dst_1</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_dst_0</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_dst_1</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_src_0</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_src_1</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">&lt;</span> <span class=\"n\">_size_dst_0</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">_data_dst_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_dst</span> <span class=\"o\">+</span> <span class=\"n\">_stride_dst_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_src_01</span> <span class=\"o\">=</span> <span class=\"n\">_data_src</span> <span class=\"o\">+</span> <span class=\"n\">_stride_src_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">_stride_src_0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_src_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_src</span> <span class=\"o\">+</span> <span class=\"n\">_stride_src_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_src_0m1</span> <span class=\"o\">=</span> <span class=\"n\">_data_src</span> <span class=\"o\">+</span> <span class=\"n\">_stride_src_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"n\">_stride_src_0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">&lt;</span> <span class=\"n\">_size_dst_1</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "      <span class=\"p\">{</span>\n",
+       "         <span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">_stride_dst_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_src_00</span><span class=\"p\">[</span><span class=\"n\">_stride_src_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">_stride_src_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_src_00</span><span class=\"p\">[</span><span class=\"n\">_stride_src_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"n\">_stride_src_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_src_01</span><span class=\"p\">[</span><span class=\"n\">_stride_src_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_src_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_src_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">];</span>\n",
+       "      <span class=\"p\">}</span>\n",
+       "   <span class=\"p\">}</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * _data_dst, double * const _data_src, int64_t const _size_dst_0, int64_t const _size_dst_1, int64_t const _stride_dst_0, int64_t const _stride_dst_1, int64_t const _stride_src_0, int64_t const _stride_src_1)\n",
+       "{\n",
+       "   for (int ctr_0 = 1; ctr_0 < _size_dst_0 - 1; ctr_0 += 1)\n",
+       "   {\n",
+       "      double * _data_dst_00 = _data_dst + _stride_dst_0*ctr_0;\n",
+       "      double * const _data_src_01 = _data_src + _stride_src_0*ctr_0 + _stride_src_0;\n",
+       "      double * const _data_src_00 = _data_src + _stride_src_0*ctr_0;\n",
+       "      double * const _data_src_0m1 = _data_src + _stride_src_0*ctr_0 - _stride_src_0;\n",
+       "      for (int ctr_1 = 1; ctr_1 < _size_dst_1 - 1; ctr_1 += 1)\n",
+       "      {\n",
+       "         _data_dst_00[_stride_dst_1*ctr_1] = 0.25*_data_src_00[_stride_src_1*ctr_1 + _stride_src_1] + 0.25*_data_src_00[_stride_src_1*ctr_1 - _stride_src_1] + 0.25*_data_src_01[_stride_src_1*ctr_1] + 0.25*_data_src_0m1[_stride_src_1*ctr_1];\n",
+       "      }\n",
+       "   }\n",
+       "}"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ps.show_code(kernel_function.ast)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Even if it looks very ugly and low-level :) lets look at this code in a bit more detail. The code is generated in a way that is works for different array sizes. The size of the array is passed in the `_size_dst_` variables that specifiy the shape of the array for each dimension. Also, the memory layout (linearization) of the array can be different. That means the array could be stored in row-major or column-major order - if we pass in the array strides correctly the kernel does the right thing. If you're not familiar with the concept of strides check out [this stackoverflow post](https://stackoverflow.com/questions/53097952/how-to-understand-numpy-strides-for-layman) or search in the numpy documentation for strides - C vs Fortran order.\n",
+    "\n",
+    "The goal of *pystencils* is to produce the fastest possible code. On technique to do this is to use all available information already on compile time and generate code that is highly adapted to the specific problem. In our case we already know the shape and strides of the arrays we want to apply the kernel on, so we can make use of this information. This idea leads to the **fixed-field-size workflow**. The main difference there is that we define the arrays first and therefore let *pystencils* know about the array shapes and strides, so that is can generate more specific code:\n",
+    "\n",
+    "1. create numpy arrays that hold your data\n",
+    "2. define pystencils fields, this time telling pystencils already which arrays they correspond to, so that it knows about the size and strides\n",
+    "\n",
+    "in the other steps nothing has changed\n",
+    "\n",
+    "3. define the update rule \n",
+    "4. compile update rule to kernel\n",
+    "5. run the kernel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 1. create arrays first\n",
+    "src_arr, dst_arr = np.random.rand(30, 30), np.zeros([30, 30])\n",
+    "\n",
+    "# 2. define symbolic fields - note the additional parameter that link an array to each field\n",
+    "src_field, dst_field = ps.fields(\"src, dst:[2D]\", src=src_arr, dst=dst_arr)\n",
+    "\n",
+    "# 3. define update rule\n",
+    "update_rule = [ps.Assignment(lhs=dst_field[0, 0],\n",
+    "                             rhs=(src_field[1, 0] + src_field[-1, 0] + src_field[0, 1] + src_field[0, -1]) / 4)]\n",
+    "\n",
+    "# 4. compile it\n",
+    "kernel_function = ps.create_kernel(update_rule).compile()\n",
+    "\n",
+    "# 5. call kernel\n",
+    "kernel_function(src=src_arr, dst=dst_arr)  # names of arguments have to match names passed to ps.fields()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Functionally, both variants are equivalent. We see the difference only when we look at the generated code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+    },
+    {
+     "data": {
+      "text/html": [
+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">_data_dst</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_src</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">&lt;</span> <span class=\"mi\">29</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">_data_dst_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_dst</span> <span class=\"o\">+</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_src_01</span> <span class=\"o\">=</span> <span class=\"n\">_data_src</span> <span class=\"o\">+</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">30</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_src_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_src</span> <span class=\"o\">+</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_src_0m1</span> <span class=\"o\">=</span> <span class=\"n\">_data_src</span> <span class=\"o\">+</span> <span class=\"mi\">30</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">30</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">&lt;</span> <span class=\"mi\">29</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "      <span class=\"p\">{</span>\n",
+       "         <span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_src_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_src_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_src_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_src_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">];</span>\n",
+       "      <span class=\"p\">}</span>\n",
+       "   <span class=\"p\">}</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * _data_dst, double * const _data_src)\n",
+       "{\n",
+       "   for (int ctr_0 = 1; ctr_0 < 29; ctr_0 += 1)\n",
+       "   {\n",
+       "      double * _data_dst_00 = _data_dst + 30*ctr_0;\n",
+       "      double * const _data_src_01 = _data_src + 30*ctr_0 + 30;\n",
+       "      double * const _data_src_00 = _data_src + 30*ctr_0;\n",
+       "      double * const _data_src_0m1 = _data_src + 30*ctr_0 - 30;\n",
+       "      for (int ctr_1 = 1; ctr_1 < 29; ctr_1 += 1)\n",
+       "      {\n",
+       "         _data_dst_00[ctr_1] = 0.25*_data_src_00[ctr_1 + 1] + 0.25*_data_src_00[ctr_1 - 1] + 0.25*_data_src_01[ctr_1] + 0.25*_data_src_0m1[ctr_1];\n",
+       "      }\n",
+       "   }\n",
+       "}"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ps.show_code(kernel_function.ast)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Compare this to the code above! It looks much simpler. The reason is that all index computations are already simplified since the exact field sizes and strides are known. This kernel now only works on arrays of the previously specified size. \n",
+    "\n",
+    "Lets try what happens if we try to use a different array:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wrong shape of array dst. Expected (30, 30)\n"
+     ]
+    }
+   ],
+   "source": [
+    "src_arr2, dst_arr2 = np.random.rand(40, 40), np.zeros([40, 40])\n",
+    "try:\n",
+    "    kernel_function(src=src_arr2, dst=dst_arr2)\n",
+    "except ValueError as e:\n",
+    "    print(e)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1.2. GPU simulations\n",
+    "\n",
+    "Let's now jump to a seemingly unrelated topic: running kernels on the GPU. \n",
+    "To run on GPU not many changes are required: When creating the kernel an additional parameter `target='gpu'` has to be passed. Also, the compiled kernel cannot be called with numpy arrays, but has to be called with `pycuda.gpuarray`s instead. That means, we have to transfer our numpy array to GPU first. From this step we obtain a gpuarray, then we can run the kernel, hopefully multiple times so that the data transfer was worth the time. Finally we transfer the finished result back to CPU. In code this looks like this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if pycuda:\n",
+    "    kernel_function_gpu = ps.create_kernel(update_rule, target='gpu').compile()\n",
+    "    # transfer to GPU\n",
+    "    src_arr_gpu = pycuda.gpuarray.to_gpu(src_arr)\n",
+    "    dst_arr_gpu = pycuda.gpuarray.to_gpu(dst_arr)\n",
+    "    \n",
+    "    # run kernel on GPU, this is done many times in real setups\n",
+    "    kernel_function_gpu(src=src_arr_gpu, dst=dst_arr_gpu)\n",
+    "    \n",
+    "    # transfer result back to CPU\n",
+    "    dst_arr_gpu.get(dst_arr)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "###  1.3. Summary: manual way\n",
+    "\n",
+    "- Don't confuse *pystencils* fields and *numpy* arrays\n",
+    "    - fields are symbolic\n",
+    "    - arrays are numeric\n",
+    "- Use the fixed-field-size workflow whenever possible, since code might be faster. Create arrays first, then create fields from arrays\n",
+    "- if we run GPU kernels, arrays have to transferred to the GPU first\n",
+    "\n",
+    "As demonstrated in the examples above we have to define 2 or 3 corresponding objects for each grid:\n",
+    "\n",
+    "- symbolic pystencils field\n",
+    "- numpy array on CPU \n",
+    "- for GPU run also a pycuda.gpuarray to mirror the data on the GPU\n",
+    "\n",
+    "Managing these three objects manually is tedious and error-prone. We'll see in the next section how the data handling object takes care of this problem."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Introducing the data handling - serial version\n",
+    "\n",
+    "### 2.1. Example for CPU simulations\n",
+    "\n",
+    "The data handling internally keeps a mapping between symbolic fields and numpy arrays. When we create a field, automatically a corresponding array is allocated as well. Optionally we can also allocate memory on the GPU for the array as well. Lets dive right in and see how our example looks like, when implemented with a data handling."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh = ps.create_data_handling(domain_size=(30, 30))\n",
+    "\n",
+    "# fields are now created using the data handling\n",
+    "src_field = dh.add_array('src', values_per_cell=1)\n",
+    "dst_field = dh.add_array('dst', values_per_cell=1)\n",
+    "\n",
+    "# kernel is created just like before\n",
+    "update_rule = [ps.Assignment(lhs=dst_field[0, 0],\n",
+    "                             rhs=(src_field[1, 0] + src_field[-1, 0] + src_field[0, 1] + src_field[0, -1]) / 4)]\n",
+    "kernel_function = ps.create_kernel(update_rule).compile()\n",
+    "\n",
+    "# have a look at the generated code - it uses \n",
+    "# the fast version where array sizes are compiled-in\n",
+    "#  ps.show_code(kernel_function.ast)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The data handling has methods to create fields - but where are the corresponding arrays? \n",
+    "In the serial case you can access them as a member of the data handling, for example to initialize our 'src' array we can write"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "src_arr = dh.cpu_arrays['src']\n",
+    "src_arr.fill(0.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This method is nice and easy, but you should not use it if you want your simulation to run on distributed-memory clusters. We'll see why in the next section about distributed memory parallelization. So it is good habit to not access the arrays directly but use the data handling to do so. We can, for example, initialize the array also with the following code:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh.fill('src', 0.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To run the kernels with the same code as before, we would also need the arrays. We could do that accessing the `cpu_arrays`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kernel_function(src=dh.cpu_arrays['src'],\n",
+    "                dst=dh.cpu_arrays['dst'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "but to be prepared for MPI parallel simulations, again a method of the data handling should be used for this. \n",
+    "Besides, this method is also simpler to use - since it automatically detects which arrays a kernel uses and passes them in."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh.run_kernel(kernel_function)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2.2. Example for GPU simulations\n",
+    "\n",
+    "In this section we have a look at GPU simulations using the data handling. Only minimal changes are required.\n",
+    "When creating the data handling we can pass a 'default_target'. This means for every added field an array on the CPU and the GPU is allocated. This is a useful default, for more fine-grained control the `add_array` method also takes additional parameters controlling where the array should be allocated.\n",
+    "\n",
+    "Additionally we also need to compile a GPU version of the kernel."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh = ps.create_data_handling(domain_size=(30, 30), default_target='gpu')\n",
+    "\n",
+    "# fields are now created using the data handling\n",
+    "src_field = dh.add_array('src', values_per_cell=1)\n",
+    "dst_field = dh.add_array('dst', values_per_cell=1)\n",
+    "\n",
+    "# kernel is created just like before\n",
+    "update_rule = [ps.Assignment(lhs=dst_field[0, 0],\n",
+    "                             rhs=(src_field[1, 0] + src_field[-1, 0] + src_field[0, 1] + src_field[0, -1]) / 4)]\n",
+    "kernel_function = ps.create_kernel(update_rule, target=dh.default_target).compile()\n",
+    "\n",
+    "dh.fill('src', 0.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The data handling provides function to transfer data between CPU and GPU"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh.to_gpu('src')\n",
+    "dh.run_kernel(kernel_function)\n",
+    "dh.to_cpu('dst')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "usually one wants to transfer all fields that have been allocated on CPU and GPU at the same time:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dh.all_to_gpu()\n",
+    "dh.run_kernel(kernel_function)\n",
+    "dh.all_to_cpu()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can always include the `all_to_*` functions in our code, since they do nothing if there are no arrays allocated on the GPU. Thus there is only a single point in the code where we can switch between CPU and GPU version: the `default_target` of the data handling. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2.2 Ghost Layers and periodicity"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. Going (MPI) parallel - the parallel data handling"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(-1, -1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "dh = ps.create_data_handling(domain_size=(30, 30), parallel=True)\n",
+    "field = dh.add_array('field')\n",
+    "for block in dh.iterate():\n",
+    "    print(block.offset) # offset is in global coordinates, where first inner cell has coordiante (0,0) and ghost layers have negative coordinates\n",
+    "    \n",
+    "    # use offset to create a local array 'my_data' for the part of the domain\n",
+    "    #np.copyto(block[field.name], my_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "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/demo_assignment_collection.ipynb b/doc/notebooks/demo_assignment_collection.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..6a5c85a2d83a2abfbf81c513e8fbe81b43287303
--- /dev/null
+++ b/doc/notebooks/demo_assignment_collection.ipynb
@@ -0,0 +1,505 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "nbsphinx": "hidden"
+   },
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo: Assignment collections and simplification\n",
+    "\n",
+    "\n",
+    "## Assignment collections\n",
+    "\n",
+    "The assignment collection class helps to formulate and simplify assignments for numerical kernels. \n",
+    "\n",
+    "An ``AssignmentCollection`` is an ordered collection of assignments, together with an optional ordered collection of subexpressions, that are required to evaluate the main assignments. There are various simplification rules available that operate on ``AssignmentCollection``s."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We start by defining some stencil update rule. Here we also use the *pystencils* ``Field``, note however that the assignment collection module works purely on the *sympy* level."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} \\left(a^{2} - c\\right) + {{f}_{N}^{0}} \\left(a^{2} + b\\right) + {{f}_{S}^{0}} a^{2} + {{f}_{W}^{0}} \\left(a^{2} - 2 c\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{0}} \\leftarrow {{f}_{E}^{0}} \\left(c^{2} - c\\right) + {{f}_{N}^{0}} \\left(b + c^{2}\\right) + {{f}_{S}^{0}} \\left(- a^{2} + c^{2}\\right) + {{f}_{W}^{0}} \\left(c^{2} - 2 c\\right)$$</td>  </tr> </table>"
+      ],
+      "text/plain": [
+       "Equation Collection for f_C^1,f_C^0"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "a,b,c = sp.symbols(\"a b c\")\n",
+    "f = ps.fields(\"f(2) : [2D]\")\n",
+    "\n",
+    "a1 = ps.Assignment(f[0,0](1), (a**2 +b) * f[0,1] + \\\n",
+    "                  (a**2 - c) * f[1,0] + \\\n",
+    "                  (a**2 - 2*c) * f[-1,0] + \\\n",
+    "                  (a**2) * f[0, -1])\n",
+    "\n",
+    "a2 = ps.Assignment(f[0,0](0), (c**2 +b) * f[0,1] + \\\n",
+    "                  (c**2 - c) * f[1,0] + \\\n",
+    "                  (c**2 - 2*c) * f[-1,0] + \\\n",
+    "                  (c**2 - a**2) * f[0, -1])\n",
+    "\n",
+    "\n",
+    "ac = ps.AssignmentCollection([a1, a2], subexpressions=[])\n",
+    "ac"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "*sympy* operations can be applied on an assignment collection: In this example we first expand the collection, then look for common subexpressions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "expand_all = ps.simp.apply_to_all_assignments(sp.expand)\n",
+    "expandedEc = expand_all(ac)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>Subexpressions:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{0} \\leftarrow - {{f}_{E}^{0}} c + {{f}_{N}^{0}} b - 2 {{f}_{W}^{0}} c$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{1} \\leftarrow a^{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{2} \\leftarrow {{f}_{S}^{0}} \\xi_{1}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{3} \\leftarrow c^{2}$$</td>  </tr> </table><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} \\xi_{1} + {{f}_{N}^{0}} \\xi_{1} + {{f}_{W}^{0}} \\xi_{1} + \\xi_{0} + \\xi_{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{0}} \\leftarrow {{f}_{E}^{0}} \\xi_{3} + {{f}_{N}^{0}} \\xi_{3} + {{f}_{S}^{0}} \\xi_{3} + {{f}_{W}^{0}} \\xi_{3} + \\xi_{0} - \\xi_{2}$$</td>  </tr> </table>"
+      ],
+      "text/plain": [
+       "Equation Collection for f_C^1,f_C^0"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ac_cse = ps.simp.sympy_cse(expandedEc)\n",
+    "ac_cse"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Symbols occuring in assignment collections are classified into 3 categories:\n",
+    "- ``free_symbols``: symbols that occur in right-hand-sides but never on left-hand-sides\n",
+    "- ``bound_symbols``: symbols that occur on left-hand-sides\n",
+    "- ``defined_symbols``: symbols that occur on left-hand-sides of a main assignment"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left\\{{{f}_{E}^{0}}, {{f}_{N}^{0}}, {{f}_{S}^{0}}, {{f}_{W}^{0}}, a, b, c\\right\\}$$"
+      ],
+      "text/plain": [
+       "set([f_E__0, f_N__0, f_S__0, f_W__0, a, b, c])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ac_cse.free_symbols"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left\\{{{f}_{C}^{0}}, {{f}_{C}^{1}}, \\xi_{0}, \\xi_{1}, \\xi_{2}, \\xi_{3}\\right\\}$$"
+      ],
+      "text/plain": [
+       "set([f_C__0, f_C__1, ξ₀, ξ₁, ξ₂, ξ₃])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ac_cse.bound_symbols"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left\\{{{f}_{C}^{0}}, {{f}_{C}^{1}}\\right\\}$$"
+      ],
+      "text/plain": [
+       "set([f_C__0, f_C__1])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ac_cse.defined_symbols"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Assignment collections can be splitted up, and merged together. For splitting, a list of symbols that occur on the left-hand-side in the main assignments has to be passed. The returned assignment collection only contains these main assignments together with all necessary subexpressions."
+   ]
+  },
+  {
+   "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\">$$\\xi_{0} \\leftarrow - {{f}_{E}^{0}} c + {{f}_{N}^{0}} b - 2 {{f}_{W}^{0}} c$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{1} \\leftarrow a^{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{2} \\leftarrow {{f}_{S}^{0}} \\xi_{1}$$</td>  </tr> </table><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} \\xi_{1} + {{f}_{N}^{0}} \\xi_{1} + {{f}_{W}^{0}} \\xi_{1} + \\xi_{0} + \\xi_{2}$$</td>  </tr> </table>"
+      ],
+      "text/plain": [
+       "Equation Collection for f_C^1"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ac_f0 = ac_cse.new_filtered([f(0)])\n",
+    "ac_f1 = ac_cse.new_filtered([f(1)])\n",
+    "ac_f1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note here that $\\xi_4$ is no longer part of the subexpressions, since it is not used in the main assignment of $f_C^1$.\n",
+    "\n",
+    "If we merge both collections together, we end up with the original collection."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>Subexpressions:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{0} \\leftarrow - {{f}_{E}^{0}} c + {{f}_{N}^{0}} b - 2 {{f}_{W}^{0}} c$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{1} \\leftarrow a^{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{2} \\leftarrow {{f}_{S}^{0}} \\xi_{1}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{3} \\leftarrow c^{2}$$</td>  </tr> </table><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{0}} \\leftarrow {{f}_{E}^{0}} \\xi_{3} + {{f}_{N}^{0}} \\xi_{3} + {{f}_{S}^{0}} \\xi_{3} + {{f}_{W}^{0}} \\xi_{3} + \\xi_{0} - \\xi_{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} \\xi_{1} + {{f}_{N}^{0}} \\xi_{1} + {{f}_{W}^{0}} \\xi_{1} + \\xi_{0} + \\xi_{2}$$</td>  </tr> </table>"
+      ],
+      "text/plain": [
+       "Equation Collection for f_C^0,f_C^1"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ac_f0.new_merged(ac_f1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is also a method that inserts all subexpressions into the main assignments. This is the inverse operation of common subexpression elimination."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{0}} \\leftarrow {{f}_{E}^{0}} c^{2} - {{f}_{E}^{0}} c + {{f}_{N}^{0}} b + {{f}_{N}^{0}} c^{2} - {{f}_{S}^{0}} a^{2} + {{f}_{S}^{0}} c^{2} + {{f}_{W}^{0}} c^{2} - 2 {{f}_{W}^{0}} c$$</td>  </tr> </table>"
+      ],
+      "text/plain": [
+       "Equation Collection for f_C^0"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "assert sp.simplify(ac_f0.new_without_subexpressions().main_assignments[0].rhs - a2.rhs) == 0\n",
+    "ac_f0.new_without_subexpressions()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To evaluate an assignment collection, use the ``lambdify`` method. It is very similar to *sympy*s ``lambdify`` function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left \\{ {{f}_{C}^{0}} : 75, \\quad {{f}_{C}^{1}} : -17\\right \\}$$"
+      ],
+      "text/plain": [
+       "{f_C__0: 75, f_C__1: -17}"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "evalFct = ac_cse.lambdify([f[0,1], f[1,0]],  # new parameters of returned function\n",
+    "                          fixed_symbols={a:1, b:2, c:3, f[0,-1]: 4, f[-1,0]: 5}) # fix values of other symbols\n",
+    "evalFct(2,1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "lambdify is rather slow for evaluation. The intended way to evaluate an assignment collection is *pystencils* i.e. create a fast kernel, that applies the update at every site of a structured grid. The collection can be directly passed to the `create_kernel` function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "func = ps.create_kernel(ac_cse).compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simplification Strategies\n",
+    "\n",
+    "In above examples, we already applied simplification rules to assignment collections. Simplification rules are functions that take, as a single argument, an assignment collection and return an modified/simplified copy of it. The ``SimplificationStrategy`` class holds a list of simplification rules and can apply all of them in the specified order. Additionally it provides useful printing and reporting functions. \n",
+    "\n",
+    "We start by creating a simplification strategy, consisting of the expand and CSE simplifications we have already applied above:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "strategy = ps.simp.SimplificationStrategy()\n",
+    "strategy.add(ps.simp.apply_to_all_assignments(sp.expand))\n",
+    "strategy.add(ps.simp.sympy_cse)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This strategy can be applied to any assignment collection:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>Subexpressions:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{0} \\leftarrow - {{f}_{E}^{0}} c + {{f}_{N}^{0}} b - 2 {{f}_{W}^{0}} c$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{1} \\leftarrow a^{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{2} \\leftarrow {{f}_{S}^{0}} \\xi_{1}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{3} \\leftarrow c^{2}$$</td>  </tr> </table><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} \\xi_{1} + {{f}_{N}^{0}} \\xi_{1} + {{f}_{W}^{0}} \\xi_{1} + \\xi_{0} + \\xi_{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{0}} \\leftarrow {{f}_{E}^{0}} \\xi_{3} + {{f}_{N}^{0}} \\xi_{3} + {{f}_{S}^{0}} \\xi_{3} + {{f}_{W}^{0}} \\xi_{3} + \\xi_{0} - \\xi_{2}$$</td>  </tr> </table>"
+      ],
+      "text/plain": [
+       "Equation Collection for f_C^1,f_C^0"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "strategy(ac)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The strategy can also print the simplification results at each stage. \n",
+    "The report contains information about the number of operations after each simplification as well as the runtime of each simplification routine."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "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>13</td> <td>19</td> <td>0</td>  <td>32</td> </tr><tr><td>expand</td><td>0.11 ms</td> <td>13</td> <td>26</td> <td>0</td>  <td>39</td> </tr><tr><td>sympy_cse</td><td>3.25 ms</td> <td>11</td> <td>14</td> <td>0</td>  <td>25</td> </tr></table>"
+      ],
+      "text/plain": [
+       "<pystencils.simp.simplificationstrategy.SimplificationStrategy.create_simplification_report.<locals>.Report at 0x7f9be404fda0>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "strategy.create_simplification_report(ac)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The strategy can also print the full collection after each simplification..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<h5 style=\"padding-bottom:10px\">Initial Version</h5> <div style=\"padding-left:20px;\"><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} \\left(a^{2} - c\\right) + {{f}_{N}^{0}} \\left(a^{2} + b\\right) + {{f}_{S}^{0}} a^{2} + {{f}_{W}^{0}} \\left(a^{2} - 2 c\\right)$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{0}} \\leftarrow {{f}_{E}^{0}} \\left(c^{2} - c\\right) + {{f}_{N}^{0}} \\left(b + c^{2}\\right) + {{f}_{S}^{0}} \\left(- a^{2} + c^{2}\\right) + {{f}_{W}^{0}} \\left(c^{2} - 2 c\\right)$$</td>  </tr> </table></div><h5 style=\"padding-bottom:10px\">expand</h5> <div style=\"padding-left:20px;\"><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} a^{2} - {{f}_{E}^{0}} c + {{f}_{N}^{0}} a^{2} + {{f}_{N}^{0}} b + {{f}_{S}^{0}} a^{2} + {{f}_{W}^{0}} a^{2} - 2 {{f}_{W}^{0}} c$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{0}} \\leftarrow {{f}_{E}^{0}} c^{2} - {{f}_{E}^{0}} c + {{f}_{N}^{0}} b + {{f}_{N}^{0}} c^{2} - {{f}_{S}^{0}} a^{2} + {{f}_{S}^{0}} c^{2} + {{f}_{W}^{0}} c^{2} - 2 {{f}_{W}^{0}} c$$</td>  </tr> </table></div><h5 style=\"padding-bottom:10px\">sympy_cse</h5> <div style=\"padding-left:20px;\"><div>Subexpressions:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{0} \\leftarrow - {{f}_{E}^{0}} c + {{f}_{N}^{0}} b - 2 {{f}_{W}^{0}} c$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{1} \\leftarrow a^{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{2} \\leftarrow {{f}_{S}^{0}} \\xi_{1}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$$\\xi_{3} \\leftarrow c^{2}$$</td>  </tr> </table><div>Main Assignments:</div><table style=\"border:none; width: 100%; \"><tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} \\xi_{1} + {{f}_{N}^{0}} \\xi_{1} + {{f}_{W}^{0}} \\xi_{1} + \\xi_{0} + \\xi_{2}$$</td>  </tr> <tr style=\"border:none\"> <td style=\"border:none\">$${{f}_{C}^{0}} \\leftarrow {{f}_{E}^{0}} \\xi_{3} + {{f}_{N}^{0}} \\xi_{3} + {{f}_{S}^{0}} \\xi_{3} + {{f}_{W}^{0}} \\xi_{3} + \\xi_{0} - \\xi_{2}$$</td>  </tr> </table></div>"
+      ],
+      "text/plain": [
+       "<pystencils.simp.simplificationstrategy.SimplificationStrategy.show_intermediate_results.<locals>.IntermediateResults at 0x7f9bad688dd8>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "strategy.show_intermediate_results(ac)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "... or only specific assignments for better readability"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<h5 style=\"padding-bottom:10px\">Initial Version</h5> <div style=\"padding-left:20px;\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} \\left(a^{2} - c\\right) + {{f}_{N}^{0}} \\left(a^{2} + b\\right) + {{f}_{S}^{0}} a^{2} + {{f}_{W}^{0}} \\left(a^{2} - 2 c\\right)$$</div><h5 style=\"padding-bottom:10px\">expand</h5> <div style=\"padding-left:20px;\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} a^{2} - {{f}_{E}^{0}} c + {{f}_{N}^{0}} a^{2} + {{f}_{N}^{0}} b + {{f}_{S}^{0}} a^{2} + {{f}_{W}^{0}} a^{2} - 2 {{f}_{W}^{0}} c$$</div><h5 style=\"padding-bottom:10px\">sympy_cse</h5> <div style=\"padding-left:20px;\">$${{f}_{C}^{1}} \\leftarrow {{f}_{E}^{0}} \\xi_{1} + {{f}_{N}^{0}} \\xi_{1} + {{f}_{W}^{0}} \\xi_{1} + \\xi_{0} + \\xi_{2}$$</div>"
+      ],
+      "text/plain": [
+       "<pystencils.simp.simplificationstrategy.SimplificationStrategy.show_intermediate_results.<locals>.IntermediateResults at 0x7f9bad688b00>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "strategy.show_intermediate_results(ac, symbols=[f(1)])"
+   ]
+  }
+ ],
+ "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/doc/notebooks/demo_benchmark.ipynb b/doc/notebooks/demo_benchmark.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..7e56843378a40a264968e992d95f6339562e34e8
--- /dev/null
+++ b/doc/notebooks/demo_benchmark.ipynb
@@ -0,0 +1,262 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *\n",
+    "import timeit\n",
+    "%load_ext Cython"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo: Benchmark numpy, cython, pystencils\n",
+    "\n",
+    "In this benchmark we compare different ways of implementing a simple stencil kernel in Python.\n",
+    "The benchmark kernel computes the average of the four neighbors in 2D and stores in a second array. To prevent out-of-bounds accesses, we skip the cells at the border and compute values only in the range `[1:-1, 1:-1]`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Implementations\n",
+    "\n",
+    "The first implementation is a pure Python implementation:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def avg_pure_python(input_arr, output_arr):       \n",
+    "    for x in range(1, input_arr.shape[0] - 1):\n",
+    "        for y in range(1, input_arr.shape[1] - 1):\n",
+    "            output_arr[x, y] = (input_arr[x + 1, y] + input_arr[x - 1, y] +\n",
+    "                                input_arr[x, y + 1] + input_arr[x, y - 1]) / 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Obviously, this will be a rather slow version, since the loops are written directly in Python. \n",
+    "\n",
+    "Next, we use *numpy* functions to delegate the looping to numpy. The first version uses the `roll` function to shift the array by one element in each direction. This version has to allocate a new array for each accessed neighbor."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def avg_numpy_roll(input_arr, output_arr):\n",
+    "    neighbors = [np.roll(input_arr, axis=a, shift=s) for a in (0, 1) for s in (-1, 1)]\n",
+    "    np.divide(sum(neighbors), 4, out=output_arr)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Using views, we can get rid of the additional copies:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def avg_numpy_slice(input_arr, output_arr):\n",
+    "    output_arr[1:-1, 1:-1] = input_arr[2:, 1:-1] + input_arr[:-2, 1:-1] + \\\n",
+    "                             input_arr[1:-1, 2:] + input_arr[1:-1, :-2]\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To further optimize the kernel we switch to Cython, to get a compiled C version."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%cython\n",
+    "import cython\n",
+    "\n",
+    "@cython.boundscheck(False)\n",
+    "@cython.wraparound(False)\n",
+    "def avg_cython(object[double, ndim=2] input_arr, object[double, ndim=2] output_arr):\n",
+    "    cdef int xs, ys, x, y\n",
+    "    xs, ys = input_arr.shape\n",
+    "    for x in range(1, xs - 1):\n",
+    "        for y in range(1, ys - 1):\n",
+    "            output_arr[x, y] = (input_arr[x + 1, y] + input_arr[x - 1, y] +\n",
+    "                                input_arr[x, y + 1] + input_arr[x, y - 1]) / 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And finally we also create a *pystencils* version of the same stencil code:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "src, dst = ps.fields(\"src, dst: [2D]\")\n",
+    "\n",
+    "update = ps.Assignment(dst[0,0], \n",
+    "                       (src[1, 0] + src[-1, 0] + src[0, 1] + src[0, -1]) / 4)\n",
+    "kernel = ps.create_kernel(update).compile()\n",
+    "\n",
+    "def avg_pystencils(input_arr, output_arr):\n",
+    "    kernel(src=input_arr, dst=output_arr)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "all_implementations = {\n",
+    "    'pure Python': avg_pure_python,\n",
+    "    'numpy roll': avg_numpy_roll,\n",
+    "    'numpy slice': avg_numpy_slice,\n",
+    "    'Cython': None,\n",
+    "    'pystencils': avg_pystencils,\n",
+    "}\n",
+    "if 'avg_cython' in globals():\n",
+    "    all_implementations['Cython'] = avg_cython\n",
+    "else:\n",
+    "    del all_implementations['Cython']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Benchmark functions\n",
+    "\n",
+    "We implement a short function to get in- and output arrays of a given shape and to measure the runtime."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_arrays(shape):\n",
+    "    in_arr = np.random.rand(*shape)\n",
+    "    out_arr = np.empty_like(in_arr)\n",
+    "    return in_arr, out_arr\n",
+    "\n",
+    "def do_benchmark(func, shape):\n",
+    "    in_arr, out_arr = get_arrays(shape)\n",
+    "    timer = timeit.Timer('f(a, b)', globals={'f': func, 'a': in_arr, 'b': out_arr})\n",
+    "    calls, time_taken = timer.autorange()\n",
+    "    return time_taken / calls"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Comparison\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def bar_plot(*shape):\n",
+    "    names = tuple(all_implementations.keys())\n",
+    "    runtimes = tuple(do_benchmark(all_implementations[name], shape) for name in names)\n",
+    "    for runtime, name in zip(runtimes, names):\n",
+    "        assert runtime >= runtimes[names.index('pystencils')], runtimes\n",
+    "    speedups = tuple(runtime / min(runtimes) for runtime in runtimes)\n",
+    "    y_pos = np.arange(len(names))\n",
+    "    labels = tuple(f\"{name} ({round(speedup, 1)} x)\" for name, speedup in zip(names, speedups))\n",
+    "    \n",
+    "    plt.text(0.5, 0.5, f\"Size {shape}\", horizontalalignment='center', fontsize=16,\n",
+    "             verticalalignment='center', transform=plt.gca().transAxes)\n",
+    "    plt.barh(y_pos, runtimes, log=True)\n",
+    "     \n",
+    "    plt.yticks(y_pos, labels);\n",
+    "    plt.xlabel('Runtime of single iteration')\n",
+    "    \n",
+    "plt.figure(figsize=(8, 8))\n",
+    "    \n",
+    "plt.subplot(3, 1, 1)\n",
+    "bar_plot(16, 16)\n",
+    "\n",
+    "plt.subplot(3, 1, 2)\n",
+    "bar_plot(128, 128)\n",
+    "\n",
+    "plt.subplot(3, 1, 3)\n",
+    "bar_plot(1024, 1024)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "All runtimes are plotted logarithmically. Next number next to the labels shows how much slower the version is than the fastest one. For small arrays Cython produces faster code than *pystencils*. The larger the arrays, the better pystencils gets."
+   ]
+  }
+ ],
+ "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_wave_equation.ipynb b/doc/notebooks/demo_wave_equation.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..2f9f5d8d1e70e8401e97c211052eb6aa33009150
--- /dev/null
+++ b/doc/notebooks/demo_wave_equation.ipynb
@@ -0,0 +1,689 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "nbsphinx": "hidden"
+   },
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *\n",
+    "sp.init_printing()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo: Finite differences - 2D wave equation\n",
+    "\n",
+    "In this tutorial we show how to use the finite difference module of *pystencils* to solve a 2D wave equations. The time derivative is discretized by a simple forward Euler method."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "$$ \\frac{\\partial^2 u}{\\partial t^2} = \\mbox{div} \\left( q(x,y) \\nabla u \\right)$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We begin by creating three *numpy* arrays for the current, the previous and the next timestep. Actually we will see later that two fields are enough, but let's keep it simple. From these *numpy* arrays we create *pystencils* fields to formulate our update rule."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "size = (60, 70) #  domain size\n",
+    "u_arrays = [np.zeros(size), np.zeros(size), np.zeros(size)]\n",
+    "\n",
+    "u_fields = [ps.Field.create_from_numpy_array(\"u%s\" % (name,), arr)\n",
+    "            for name, arr in zip([\"0\", \"1\", \"2\"], u_arrays)]\n",
+    "\n",
+    "# Nicer display for fields\n",
+    "for i, field in enumerate(u_fields):\n",
+    "    field.latex_name = \"u^{(%d)}\" % (i,)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "*pystencils* contains already simple rules to discretize the a diffusion term. The time discretization is done manually."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\frac{{{u^{(0)}}_{(0,0)}} - 2 {{u^{(1)}}_{(0,0)}} + {{u^{(2)}}_{(0,0)}}}{dt^{2}} = \\frac{{{u^{(1)}}_{(-1,0)}} + {{u^{(1)}}_{(0,-1)}} - 4 {{u^{(1)}}_{(0,0)}} + {{u^{(1)}}_{(0,1)}} + {{u^{(1)}}_{(1,0)}}}{dx^{2}}$$"
+      ],
+      "text/plain": [
+       "u_0_C - 2â‹…u_1_C + u_2_C   u_1_W + u_1_S - 4â‹…u_1_C + u_1_N + u_1_E\n",
+       "─────────────────────── = ───────────────────────────────────────\n",
+       "            2                                 2                  \n",
+       "          dt                                dx                   "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discretize = ps.fd.Discretization2ndOrder()\n",
+    "\n",
+    "def central2nd_time_derivative(fields):\n",
+    "    f_next, f_current, f_last = fields\n",
+    "    return (f_next[0, 0] - 2 * f_current[0, 0] + f_last[0, 0]) / discretize.dt**2\n",
+    "\n",
+    "rhs = ps.fd.diffusion(u_fields[1], 1)\n",
+    "\n",
+    "wave_eq = sp.Eq(central2nd_time_derivative(u_fields), discretize(rhs))\n",
+    "\n",
+    "wave_eq = sp.simplify(wave_eq)\n",
+    "wave_eq"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The explicit Euler scheme is now obtained by solving above equation with respect to $u_C^{next}$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$${{u^{(2)}}_{(0,0)}} \\leftarrow \\frac{{{u^{(1)}}_{(-1,0)}} dt^{2} + {{u^{(1)}}_{(0,-1)}} dt^{2} - 4 {{u^{(1)}}_{(0,0)}} dt^{2} + {{u^{(1)}}_{(0,1)}} dt^{2} + {{u^{(1)}}_{(1,0)}} dt^{2} + dx^{2} \\left(- {{u^{(0)}}_{(0,0)}} + 2 {{u^{(1)}}_{(0,0)}}\\right)}{dx^{2}}$$"
+      ],
+      "text/plain": [
+       "                 2           2             2           2           2     2    \n",
+       "         u_1_Wâ‹…dt  + u_1_Sâ‹…dt  - 4â‹…u_1_Câ‹…dt  + u_1_Nâ‹…dt  + u_1_Eâ‹…dt  + dx â‹…(-u\n",
+       "u_2_C := ─────────────────────────────────────────────────────────────────────\n",
+       "                                                   2                          \n",
+       "                                                 dx                           \n",
+       "\n",
+       "               \n",
+       "_0_C + 2â‹…u_1_C)\n",
+       "───────────────\n",
+       "               \n",
+       "               "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "u_next_C = u_fields[-1][0, 0]\n",
+    "update_rule = ps.Assignment(u_next_C, sp.solve(wave_eq, u_next_C)[0])\n",
+    "update_rule"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Before creating the kernel, we substitute numeric values for $dx$ and $dt$. \n",
+    "Then a kernel is created just like in the last tutorial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+      "text/html": [
+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u0</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u1</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">_data_u2</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">&lt;</span> <span class=\"mi\">59</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">_data_u2_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_u2</span> <span class=\"o\">+</span> <span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u1_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_u1</span> <span class=\"o\">+</span> <span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u0_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_u0</span> <span class=\"o\">+</span> <span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u1_01</span> <span class=\"o\">=</span> <span class=\"n\">_data_u1</span> <span class=\"o\">+</span> <span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">70</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u1_0m1</span> <span class=\"o\">=</span> <span class=\"n\">_data_u1</span> <span class=\"o\">+</span> <span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">70</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">&lt;</span> <span class=\"mi\">69</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "      <span class=\"p\">{</span>\n",
+       "         <span class=\"n\">_data_u2_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_u1_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_u1_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_u1_01</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_u1_0m1</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_u0_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_u1_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">];</span>\n",
+       "      <span class=\"p\">}</span>\n",
+       "   <span class=\"p\">}</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * const _data_u0, double * const _data_u1, double * _data_u2)\n",
+       "{\n",
+       "   for (int ctr_0 = 1; ctr_0 < 59; ctr_0 += 1)\n",
+       "   {\n",
+       "      double * _data_u2_00 = _data_u2 + 70*ctr_0;\n",
+       "      double * const _data_u1_00 = _data_u1 + 70*ctr_0;\n",
+       "      double * const _data_u0_00 = _data_u0 + 70*ctr_0;\n",
+       "      double * const _data_u1_01 = _data_u1 + 70*ctr_0 + 70;\n",
+       "      double * const _data_u1_0m1 = _data_u1 + 70*ctr_0 - 70;\n",
+       "      for (int ctr_1 = 1; ctr_1 < 69; ctr_1 += 1)\n",
+       "      {\n",
+       "         _data_u2_00[ctr_1] = 0.25*_data_u1_00[ctr_1 + 1] + 0.25*_data_u1_00[ctr_1 - 1] + 0.25*_data_u1_01[ctr_1] + 0.25*_data_u1_0m1[ctr_1] - 1.0*_data_u0_00[ctr_1] + 1.0*_data_u1_00[ctr_1];\n",
+       "      }\n",
+       "   }\n",
+       "}"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "update_rule = update_rule.subs({discretize.dx: 0.1, discretize.dt: 0.05})\n",
+    "ast = ps.create_kernel(update_rule)\n",
+    "kernel = ast.compile()\n",
+    "\n",
+    "ps.show_code(ast)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[_data_u0, _data_u1, _data_u2]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ast.get_parameters()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{u0, u1, u2}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ast.fields_accessed"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To run simulation a suitable initial condition and boundary treatment is required. We chose an initial condition which is zero at the borders of the domain. The outermost layer is not changed by the update kernel, so we have an implicit homogenous Dirichlet boundary condition."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X,Y = np.meshgrid( np.linspace(0, 1, size[1]), np.linspace(0,1, size[0]))\n",
+    "Z = np.sin(2*X*np.pi) * np.sin(2*Y*np.pi)\n",
+    "\n",
+    "# Initialize the previous and current values with the initial function\n",
+    "np.copyto(u_arrays[0], Z)\n",
+    "np.copyto(u_arrays[1], Z)\n",
+    "# The values for the next timesteps do not matter, since they are overwritten\n",
+    "u_arrays[2][:, :] = 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "One timestep now consists of applying the kernel once, then shifting the arrays."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def run(timesteps=1):\n",
+    "    for t in range(timesteps):\n",
+    "        kernel(u0=u_arrays[0], u1=u_arrays[1], u2=u_arrays[2])\n",
+    "        u_arrays[0], u_arrays[1], u_arrays[2] = u_arrays[1], u_arrays[2], u_arrays[0]\n",
+    "    return u_arrays[2]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Lets create an animation of the solution:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<video controls width=\"80%\">\n",
+       " <source 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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": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ps_notebook.set_display_mode('video')\n",
+    "ani = plt.surface_plot_animation(run)\n",
+    "ps_notebook.display_animation(ani)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert np.isfinite(np.max(u_arrays[2]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "__LLVM backend__\n",
+    "\n",
+    "The next cell demonstrates how to run the same simulation with the LLVM backend. The only difference is that in the `create_kernel` function the `target` is set to llvm."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<video controls width=\"80%\">\n",
+       " <source 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+       " Your browser does not support the video tag.\n",
+       "</video>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "try:\n",
+    "    import llvmlite\n",
+    "except ImportError:\n",
+    "    llvmlite=None\n",
+    "    print('No llvmlite installed')\n",
+    "\n",
+    "if llvmlite:\n",
+    "    kernel = ps.create_kernel(update_rule, target='llvm').compile()\n",
+    "    \n",
+    "    X,Y = np.meshgrid( np.linspace(0, 1, size[1]), np.linspace(0,1, size[0]))\n",
+    "    Z = np.sin(2*X*np.pi) * np.sin(2*Y*np.pi)\n",
+    "\n",
+    "    # Initialize the previous and current values with the initial function\n",
+    "    np.copyto(u_arrays[0], Z)\n",
+    "    np.copyto(u_arrays[1], Z)\n",
+    "    # The values for the next timesteps do not matter, since they are overwritten\n",
+    "    u_arrays[2][:, :] = 0\n",
+    "    \n",
+    "    def run_LLVM(timesteps=1):\n",
+    "        for t in range(timesteps):\n",
+    "            kernel(u0=u_arrays[0], u1=u_arrays[1], u2=u_arrays[2])\n",
+    "            u_arrays[0], u_arrays[1], u_arrays[2] = u_arrays[1], u_arrays[2], u_arrays[0]\n",
+    "        return u_arrays[2]\n",
+    "    \n",
+    "    ani = plt.surface_plot_animation(run_LLVM)\n",
+    "    assert np.isfinite(np.max(u_arrays[2]))\n",
+    "ps_notebook.display_animation(ani)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "__Runing on GPU__\n",
+    "\n",
+    "We can also run the same kernel on the GPU, by using the ``pycuda`` package."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
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+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u0</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u1</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">_data_u2</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   <span class=\"k\">if</span> <span class=\"p\">(</span><span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">x</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"mi\">1</span> <span class=\"o\">&lt;</span> <span class=\"mi\">59</span> <span class=\"o\">&amp;&amp;</span> <span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">y</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"mi\">1</span> <span class=\"o\">&lt;</span> <span class=\"mi\">69</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">x</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">y</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">_data_u2_10</span> <span class=\"o\">=</span> <span class=\"n\">_data_u2</span> <span class=\"o\">+</span> <span class=\"n\">ctr_1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u1_10</span> <span class=\"o\">=</span> <span class=\"n\">_data_u1</span> <span class=\"o\">+</span> <span class=\"n\">ctr_1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u0_10</span> <span class=\"o\">=</span> <span class=\"n\">_data_u0</span> <span class=\"o\">+</span> <span class=\"n\">ctr_1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u1_11</span> <span class=\"o\">=</span> <span class=\"n\">_data_u1</span> <span class=\"o\">+</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"k\">const</span> <span class=\"n\">_data_u1_1m1</span> <span class=\"o\">=</span> <span class=\"n\">_data_u1</span> <span class=\"o\">+</span> <span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+       "      <span class=\"n\">_data_u2_10</span><span class=\"p\">[</span><span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_u1_10</span><span class=\"p\">[</span><span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">70</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_u1_10</span><span class=\"p\">[</span><span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">70</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_u1_11</span><span class=\"p\">[</span><span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.25</span><span class=\"o\">*</span><span class=\"n\">_data_u1_1m1</span><span class=\"p\">[</span><span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_u0_10</span><span class=\"p\">[</span><span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_u1_10</span><span class=\"p\">[</span><span class=\"mi\">70</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">];</span>\n",
+       "   <span class=\"p\">}</span> \n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * const _data_u0, double * const _data_u1, double * _data_u2)\n",
+       "{\n",
+       "   if (blockDim.x*blockIdx.x + threadIdx.x + 1 < 59 && blockDim.y*blockIdx.y + threadIdx.y + 1 < 69)\n",
+       "   {\n",
+       "      const int64_t ctr_0 = blockDim.x*blockIdx.x + threadIdx.x + 1;\n",
+       "      const int64_t ctr_1 = blockDim.y*blockIdx.y + threadIdx.y + 1;\n",
+       "      double * _data_u2_10 = _data_u2 + ctr_1;\n",
+       "      double * const _data_u1_10 = _data_u1 + ctr_1;\n",
+       "      double * const _data_u0_10 = _data_u0 + ctr_1;\n",
+       "      double * const _data_u1_11 = _data_u1 + ctr_1 + 1;\n",
+       "      double * const _data_u1_1m1 = _data_u1 + ctr_1 - 1;\n",
+       "      _data_u2_10[70*ctr_0] = 0.25*_data_u1_10[70*ctr_0 + 70] + 0.25*_data_u1_10[70*ctr_0 - 70] + 0.25*_data_u1_11[70*ctr_0] + 0.25*_data_u1_1m1[70*ctr_0] - 1.0*_data_u0_10[70*ctr_0] + 1.0*_data_u1_10[70*ctr_0];\n",
+       "   } \n",
+       "}"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "try:\n",
+    "    import pycuda\n",
+    "except ImportError:\n",
+    "    pycuda=None\n",
+    "    print('No pycuda installed')\n",
+    "\n",
+    "\n",
+    "res = None\n",
+    "if pycuda:\n",
+    "    gpu_ast = ps.create_kernel(update_rule, target='gpu')\n",
+    "    gpu_kernel = gpu_ast.compile()\n",
+    "    res = ps.show_code(gpu_ast)\n",
+    "res"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The run function has to be changed now slightly, since the data has to be transfered to the GPU first, then the kernel can be executed, and in the end the data has to be transfered back"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if pycuda:\n",
+    "    import pycuda.gpuarray as gpuarray\n",
+    "\n",
+    "    def run_on_gpu(timesteps=1):\n",
+    "        # Transfer arrays to GPU\n",
+    "        gpuArrs = [gpuarray.to_gpu(a) for a in u_arrays]\n",
+    "\n",
+    "        for t in range(timesteps):\n",
+    "            gpu_kernel(u0=gpuArrs[0], u1=gpuArrs[1], u2=gpuArrs[2])\n",
+    "            gpuArrs[0], gpuArrs[1], gpuArrs[2] = gpuArrs[1], gpuArrs[2], gpuArrs[0]\n",
+    "\n",
+    "        # Transfer arrays to CPU\n",
+    "        for gpuArr, cpuArr in zip(gpuArrs, u_arrays):\n",
+    "            gpuArr.get(cpuArr)\n",
+    "assert np.isfinite(np.max(u_arrays[2]))            "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if pycuda:\n",
+    "    run_on_gpu(400)"
+   ]
+  }
+ ],
+ "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": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/sphinx/api.rst b/doc/sphinx/api.rst
new file mode 100644
index 0000000000000000000000000000000000000000..74370adba4a1fb076ec283e1de1f3e80fcc63215
--- /dev/null
+++ b/doc/sphinx/api.rst
@@ -0,0 +1,14 @@
+API Reference
+=============
+
+.. toctree::
+   :maxdepth: 3
+
+   kernel_compile_and_call.rst
+   simplifications.rst
+   datahandling.rst
+   configuration.rst
+   field.rst
+   finite_differences.rst
+   plot.rst
+   ast.rst
diff --git a/doc/sphinx/ast.rst b/doc/sphinx/ast.rst
new file mode 100644
index 0000000000000000000000000000000000000000..6923b80ad4cc6ef5389127c0e641483cd3eda299
--- /dev/null
+++ b/doc/sphinx/ast.rst
@@ -0,0 +1,19 @@
+*********************************************
+For developers: AST Nodes and Transformations
+*********************************************
+
+
+AST Nodes
+=========
+
+.. automodule:: pystencils.astnodes
+   :members:
+
+
+
+Transformations
+===============
+
+
+.. automodule:: pystencils.transformations
+   :members:
diff --git a/doc/sphinx/configuration.rst b/doc/sphinx/configuration.rst
new file mode 100644
index 0000000000000000000000000000000000000000..e9c34d7292e6204512f7871dcd5385acd8b98ecc
--- /dev/null
+++ b/doc/sphinx/configuration.rst
@@ -0,0 +1,5 @@
+*************
+Configuration
+*************
+
+.. automodule:: pystencils.cpu.cpujit
\ No newline at end of file
diff --git a/doc/sphinx/datahandling.rst b/doc/sphinx/datahandling.rst
new file mode 100644
index 0000000000000000000000000000000000000000..6b8ed01f2479dc7bb9f86ae00c28162da841f1f5
--- /dev/null
+++ b/doc/sphinx/datahandling.rst
@@ -0,0 +1,6 @@
+************
+DataHandling
+************
+
+.. autoclass:: pystencils.datahandling.DataHandling
+   :members:
\ No newline at end of file
diff --git a/doc/sphinx/field.rst b/doc/sphinx/field.rst
new file mode 100644
index 0000000000000000000000000000000000000000..ea312ec1135cf6b05ec022a3e5eb1c148b9ca0d8
--- /dev/null
+++ b/doc/sphinx/field.rst
@@ -0,0 +1,6 @@
+*****
+Field
+*****
+
+.. automodule:: pystencils.field
+   :members:
\ No newline at end of file
diff --git a/doc/sphinx/finite_differences.rst b/doc/sphinx/finite_differences.rst
new file mode 100644
index 0000000000000000000000000000000000000000..0fe947d2f5f026a489bc8534140102f8560625ec
--- /dev/null
+++ b/doc/sphinx/finite_differences.rst
@@ -0,0 +1,7 @@
+******************
+Finite Differences
+******************
+
+.. automodule:: pystencils.fd
+   :members:
+
diff --git a/doc/sphinx/kernel_compile_and_call.rst b/doc/sphinx/kernel_compile_and_call.rst
new file mode 100644
index 0000000000000000000000000000000000000000..42468177ed77e4173db1d345109dc415085bf755
--- /dev/null
+++ b/doc/sphinx/kernel_compile_and_call.rst
@@ -0,0 +1,32 @@
+*****************************************
+Creating and calling kernels from Python
+*****************************************
+
+
+Creating kernels
+----------------
+
+.. autofunction:: pystencils.create_kernel
+
+.. autofunction:: pystencils.create_indexed_kernel
+
+.. autofunction:: pystencils.create_staggered_kernel
+
+
+Code printing
+-------------
+
+.. autofunction:: pystencils.show_code
+
+
+GPU Indexing
+-------------
+
+.. autoclass:: pystencils.gpucuda.AbstractIndexing
+   :members:
+
+.. autoclass:: pystencils.gpucuda.BlockIndexing
+   :members:
+
+.. autoclass:: pystencils.gpucuda.LineIndexing
+   :members:
diff --git a/doc/sphinx/plot.rst b/doc/sphinx/plot.rst
new file mode 100644
index 0000000000000000000000000000000000000000..d5272ea823b7fa4cf2fca05346e4c73bcb3ac3fd
--- /dev/null
+++ b/doc/sphinx/plot.rst
@@ -0,0 +1,8 @@
+**********************
+Plotting and Animation
+**********************
+
+.. automodule:: pystencils.plot2d
+   :members:
+
+
diff --git a/doc/sphinx/simplifications.rst b/doc/sphinx/simplifications.rst
new file mode 100644
index 0000000000000000000000000000000000000000..ca1508c5b3a2b458d039977c735cf17003b692b1
--- /dev/null
+++ b/doc/sphinx/simplifications.rst
@@ -0,0 +1,24 @@
+***************************************
+Assignment Collection & Simplifications
+***************************************
+
+
+AssignmentCollection
+====================
+
+.. autoclass:: pystencils.AssignmentCollection
+   :members:
+
+
+Simplifications
+===============
+
+.. automodule:: pystencils.simp
+   :members:
+
+
+
+
+
+
+
diff --git a/doc/sphinx/tutorials.rst b/doc/sphinx/tutorials.rst
new file mode 100644
index 0000000000000000000000000000000000000000..d3b0e8207435d7c1b380e71225390f074728fa0e
--- /dev/null
+++ b/doc/sphinx/tutorials.rst
@@ -0,0 +1,20 @@
+Tutorials
+=========
+
+These tutorials are a good place to start if you are new to pystencils.
+All tutorials and demos listed here are based on Jupyter notebooks that you can find in the pystencils repository.
+It is a good idea to download them and run them directly to be able to play around with the code.
+
+.. toctree::
+   :maxdepth: 1
+
+   /notebooks/01_tutorial_getting_started.ipynb
+   /notebooks/02_tutorial_basic_kernels.ipynb
+   /notebooks/03_tutorial_advection_diffusion.ipynb
+   /notebooks/04_tutorial_phasefield_spinodal_decomposition.ipynb
+   /notebooks/05_tutorial_phasefield_dentritic_growth.ipynb
+   /notebooks/06_tutorial_datahandling.ipynb
+   /notebooks/demo_assignment_collection.ipynb
+   /notebooks/demo_benchmark.ipynb
+   /notebooks/demo_wave_equation.ipynb
+
diff --git a/pacxx/benchmark.py b/pacxx/benchmark.py
deleted file mode 100644
index 2d9b8962ac2cbfba70cb57d12fa54ed4510608a2..0000000000000000000000000000000000000000
--- a/pacxx/benchmark.py
+++ /dev/null
@@ -1,170 +0,0 @@
-import os
-from time import perf_counter
-import subprocess
-from tempfile import TemporaryDirectory
-
-from pystencils import create_data_handling
-from pystencils.backends.cbackend import CBackend
-from jinja2 import Environment, FileSystemLoader
-from pystencils.backends.cbackend import generate_c
-
-script_path = os.path.dirname(os.path.realpath(__file__))
-PAXX_ROOT = '/local/bauer/code/pacxx/install'
-DEFAULT_PAXX_COMPILE_OPTIONS = ('-Ofast', '-march=native')
-
-
-def generate_benchmark_code(target_file, kernel_ast, target):
-    assert target in ('cpu', 'gpu')
-    assert hasattr(kernel_ast, 'indexing'), "AST has to be a CUDA kernel in order to create a PACXX kernel from it"
-    backend = CBackend()
-
-    function_body = kernel_ast.body
-    f_sizes = {f.shape[-1] for f in kernel_ast.fields_accessed}
-    assert len(f_sizes) == 1
-
-    env = Environment(loader=FileSystemLoader(script_path))
-    result = env.get_template("benchmark_template.cpp").render(f_size=f_sizes.pop(),
-                                                               code=backend(function_body),
-                                                               target=target)
-
-    with open(target_file, 'w') as f:
-        f.write(result)
-
-
-def pacxx_compile(source, executable, options=DEFAULT_PAXX_COMPILE_OPTIONS):
-    command = ['pacxx++', *options, source, '-o', executable, ]
-    env = os.environ.copy()
-    env['PATH'] = "{}:{}".format(env.get('PATH', ''), os.path.join(PAXX_ROOT, 'bin'))
-    env['LD_LIBRARY_PATH'] = "{}:{}".format(env.get('LD_LIBRARY_PATH', ''), os.path.join(PAXX_ROOT, 'lib'))
-    try:
-        subprocess.check_output(command, env=env, stderr=subprocess.STDOUT)
-    except subprocess.CalledProcessError as e:
-        print(" ".join(command))
-        print(e.output.decode('utf8'))
-        raise e
-
-
-def run_paxx_benchmark(executable, domain_size, iterations):
-    assert len(domain_size) == 3
-    arguments = [executable, *domain_size, iterations]
-    arguments = [str(e) for e in arguments]
-    output = subprocess.check_output(arguments)
-    return float(output) / iterations
-
-
-def paxx_benchmark(ast, domain_size, iterations, target='cpu', compile_options=DEFAULT_PAXX_COMPILE_OPTIONS):
-    """Generates,  compiles and runs the kernel with PAXX
-
-    Args:
-        ast: pystencils AST object (has to be generated for CUDA, even when run on CPU with pacxx)
-        domain_size: x, y, z extent of spatial domain
-        iterations: number of outer iterations
-        target: either 'cpu' or 'gpu' to specify where pacxx should run the kernel
-        compile_options: compile options for pacxx
-
-    Returns:
-        seconds for one outer iteration
-    """
-    with TemporaryDirectory() as base_dir:
-        code = os.path.join(base_dir, 'code.cpp')
-        executable = os.path.join(base_dir, 'bench')
-        generate_benchmark_code(code, ast, target)
-        pacxx_compile(code, executable, compile_options)
-        time_per_iteration = run_paxx_benchmark(executable, domain_size, iterations)
-    return time_per_iteration
-
-
-def lbm_performance_compare(domain_size, iterations, **lb_params):
-    """Runs benchmark with pacxx and with normal pystencils backends.
-
-    Args:
-        domain_size: 3-tuple with size of spatial domain
-        iterations: number of outer iterations
-        **lb_params: parameters passed to lbmpy to choose lattice Boltzmann algorithm & optimization options
-
-    Returns:
-        dictionary with measurements of time per iteration for different backends
-    """
-    import pycuda.driver as drv
-
-    from lbmpy.creationfunctions import create_lb_ast
-    if 'optimization' not in lb_params:
-        lb_params['optimization'] = {}
-
-    lb_params['optimization']['target'] = 'cpu'
-    cpu_ast = create_lb_ast(**lb_params)
-    lb_params['optimization']['target'] = 'gpu'
-    gpu_ast = create_lb_ast(**lb_params)
-
-    # print kernel code of CPU or GPU version - just for comparison, files are not used
-    with open("pystencils_cpu_code.c", 'w') as f:
-        print(generate_c(cpu_ast), file=f)
-    with open("pystencils_gpu_code.cu", 'w') as f:
-        print(generate_c(gpu_ast), file=f)
-
-    cpu_kernel = cpu_ast.compile()
-    gpu_kernel = gpu_ast.compile()
-    f_sizes = {f.shape[-1] for f in cpu_ast.fields_accessed}
-    assert len(f_sizes) == 1
-    f_size = f_sizes.pop()
-
-    dh = create_data_handling(domain_size, default_target='gpu', default_layout='fzyx')
-    dh.add_array('src', values_per_cell=f_size)
-    dh.add_array('dst', values_per_cell=f_size)
-    dh.fill('src', 0)
-    dh.fill('dst', 0)
-
-    # to keep it simple we run outer loop directly from Python
-    # make domain size large enough, otherwise we measure the python call overhead
-    def run_benchmark(kernel):
-        dh.all_to_gpu()
-        for i in range(10):  # warmup
-            dh.run_kernel(kernel)
-        drv.Context.synchronize()
-        start = perf_counter()
-        for i in range(iterations):
-            dh.run_kernel(kernel)
-        drv.Context.synchronize()
-        return (perf_counter() - start) / iterations
-
-    return {
-        'pystencils_cpu': run_benchmark(cpu_kernel),
-        'pystencils_gpu': run_benchmark(gpu_kernel),
-        'pacxx_cpu': paxx_benchmark(gpu_ast, domain_size, iterations, target='cpu'),
-        'pacxx_gpu': paxx_benchmark(gpu_ast, domain_size, iterations, target='gpu'),
-    }
-
-
-if __name__ == '__main__':
-    no_opt = {
-        'openmp': 8,  # number of threads - pacxx uses also HT cores
-        'split': False,
-        'vectorization': False,
-        'gpu_indexing_params': {'block_size': (64, 8, 1)},
-    }
-    only_vectorization = {
-        'openmp': 4,
-        'split': False,
-        'gpu_indexing_params': {'block_size': (64, 8, 1)},
-        'vectorization': {'instruction_set': 'avx',
-                          'assume_inner_stride_one': True,
-                          'nontemporal': False},
-    }
-    best = {
-        'openmp': 4,
-        'split': True,
-        'gpu_indexing_params': {'block_size': (64, 8, 1)},
-        'vectorization': {'instruction_set': 'avx',
-                          'assume_inner_stride_one': True,
-                          'nontemporal': True}
-    }
-    res = lbm_performance_compare(stencil='D3Q19', relaxation_rate=1.8, compressible=False,
-                                  domain_size=(512, 128, 32), iterations=500,
-                                  optimization=only_vectorization)
-    cpu_speedup = ((res['pacxx_cpu'] / res['pystencils_cpu']) - 1) * 100
-    gpu_speedup = ((res['pacxx_gpu'] / res['pystencils_gpu']) - 1) * 100
-    print("Time for one kernel call [s]")
-    for config_name, time in res.items():
-        print("  {0: <16}: {1}".format(config_name, time))
-
-    print("CPU {:.02f}%   GPU {:.02f}%".format(cpu_speedup, gpu_speedup))
diff --git a/pacxx/benchmark_template.cpp b/pacxx/benchmark_template.cpp
deleted file mode 100644
index 153d677b58026fd1b981cfbc1172f8a134ad4333..0000000000000000000000000000000000000000
--- a/pacxx/benchmark_template.cpp
+++ /dev/null
@@ -1,103 +0,0 @@
-#include <PACXX.h>
-#include <vector>
-#include <sstream>
-#include <iostream>
-#include <chrono>
-
-
-using namespace pacxx::v2;
-
-size_t division_round_up(size_t a, size_t b)
-{
-    if( a % b == 0)
-        return a / b;
-    else
-        return (a / b) + 1;
-}
-
-int main(int argc, char** argv)
-{
-    {% if target == 'cpu' %}
-    Executor::Create<NativeRuntime>(0);
-    {% elif target == 'gpu' %}
-    Executor::Create<CUDARuntime>(0);
-    {% endif %}
-
-    if( argc != 5 ) {
-        std::cout << "Usage:  ./benchmark xSize ySize zSize iterations" << std::endl;
-        return 1;
-    }
-    Dimension3 domainSize;
-    int64_t iterations;
-    auto &exec = Executor::get(0);
-
-    std::stringstream( argv[1] ) >> domainSize.x;
-    std::stringstream( argv[2] ) >> domainSize.y;
-    std::stringstream( argv[3] ) >> domainSize.z;
-    std::stringstream( argv[4] ) >> iterations;
-
-    // add ghost layers to be comparable to pystencils native backend
-    domainSize.x += 2;
-    domainSize.y += 2;
-    domainSize.z += 2;
-
-    int64_t totalSize = domainSize.x * domainSize.y * domainSize.z * {{f_size}};
-
-    std::vector<double> src( totalSize, 0.0 );
-    std::vector<double> dst( totalSize, 0.0 );
-
-    auto & dsrc = exec.allocate<double>(src.size());
-    auto & ddst = exec.allocate<double>(dst.size());
-
-    dsrc.upload(src.data(), src.size());
-    ddst.upload(dst.data(), dst.size());
-
-    double * _data_src = dsrc.get();
-    double * _data_dst = ddst.get();
-
-    const int64_t _size_src_0 = domainSize.x;
-    const int64_t _size_src_1 = domainSize.y;
-    const int64_t _size_src_2 = domainSize.z;
-
-    // fzyx layout
-    const int64_t _stride_src_0 = 1;
-    const int64_t _stride_src_1 = domainSize.x;
-    const int64_t _stride_src_2 = domainSize.x * domainSize.y;
-    const int64_t _stride_src_3 = domainSize.x * domainSize.y * domainSize.z;
-
-    auto pacxxKernel = [=]( range & config ) {
-
-        struct Vec3D {int x; int y; int z; };
-        const Vec3D blockDim  = { config.get_block_size(0), config.get_block_size(1), config.get_block_size(2) };
-        const Vec3D blockIdx  = { config.get_block(0), config.get_block(1), config.get_block(2) };
-        const Vec3D threadIdx = { config.get_local(0), config.get_local(1), config.get_local(2) };
-
-        {{ code|indent(8) }}
-    };
-
-    size_t blockSize[] = {64, 8, 1};
-
-    KernelConfiguration config( { division_round_up(domainSize.x - 2, blockSize[0]),
-                                  division_round_up(domainSize.y - 2, blockSize[1]),
-                                  division_round_up(domainSize.z  -2, blockSize[2]) },
-                                  { blockSize[0],
-                                    blockSize[1],
-                                    blockSize[2] });
-
-    // warm up
-    for( int64_t i = 0; i < 10; ++i ) {
-        exec.launch(pacxxKernel, config);
-    }
-    exec.synchronize();
-
-    auto start = std::chrono::high_resolution_clock::now();
-    for( int64_t i = 0; i < iterations; ++i ) {
-        exec.launch(pacxxKernel, config);
-    }
-    exec.synchronize();
-    auto duration = std::chrono::high_resolution_clock::now() - start;
-
-    auto ns = std::chrono::duration_cast<std::chrono::nanoseconds>(duration);
-    std::cout << ns.count() * 1e-9 << std::endl;
-
-}
diff --git a/__init__.py b/pystencils/__init__.py
similarity index 100%
rename from __init__.py
rename to pystencils/__init__.py
diff --git a/alignedarray.py b/pystencils/alignedarray.py
similarity index 100%
rename from alignedarray.py
rename to pystencils/alignedarray.py
diff --git a/assignment.py b/pystencils/assignment.py
similarity index 100%
rename from assignment.py
rename to pystencils/assignment.py
diff --git a/astnodes.py b/pystencils/astnodes.py
similarity index 100%
rename from astnodes.py
rename to pystencils/astnodes.py
diff --git a/backends/__init__.py b/pystencils/backends/__init__.py
similarity index 100%
rename from backends/__init__.py
rename to pystencils/backends/__init__.py
diff --git a/backends/cbackend.py b/pystencils/backends/cbackend.py
similarity index 100%
rename from backends/cbackend.py
rename to pystencils/backends/cbackend.py
diff --git a/backends/dot.py b/pystencils/backends/dot.py
similarity index 100%
rename from backends/dot.py
rename to pystencils/backends/dot.py
diff --git a/backends/simd_instruction_sets.py b/pystencils/backends/simd_instruction_sets.py
similarity index 100%
rename from backends/simd_instruction_sets.py
rename to pystencils/backends/simd_instruction_sets.py
diff --git a/boundaries/__init__.py b/pystencils/boundaries/__init__.py
similarity index 100%
rename from boundaries/__init__.py
rename to pystencils/boundaries/__init__.py
diff --git a/boundaries/boundaryconditions.py b/pystencils/boundaries/boundaryconditions.py
similarity index 100%
rename from boundaries/boundaryconditions.py
rename to pystencils/boundaries/boundaryconditions.py
diff --git a/boundaries/boundaryhandling.py b/pystencils/boundaries/boundaryhandling.py
similarity index 100%
rename from boundaries/boundaryhandling.py
rename to pystencils/boundaries/boundaryhandling.py
diff --git a/boundaries/createindexlist.py b/pystencils/boundaries/createindexlist.py
similarity index 100%
rename from boundaries/createindexlist.py
rename to pystencils/boundaries/createindexlist.py
diff --git a/boundaries/createindexlistcython.pyx b/pystencils/boundaries/createindexlistcython.pyx
similarity index 100%
rename from boundaries/createindexlistcython.pyx
rename to pystencils/boundaries/createindexlistcython.pyx
diff --git a/boundaries/inkernel.py b/pystencils/boundaries/inkernel.py
similarity index 100%
rename from boundaries/inkernel.py
rename to pystencils/boundaries/inkernel.py
diff --git a/cache.py b/pystencils/cache.py
similarity index 100%
rename from cache.py
rename to pystencils/cache.py
diff --git a/cpu/__init__.py b/pystencils/cpu/__init__.py
similarity index 100%
rename from cpu/__init__.py
rename to pystencils/cpu/__init__.py
diff --git a/cpu/cpujit.py b/pystencils/cpu/cpujit.py
similarity index 98%
rename from cpu/cpujit.py
rename to pystencils/cpu/cpujit.py
index 56cd2cc3a728e36a2aca585599fcc7066b226051..32dec37a92bc054499fa77425d0ee7f7ea113402 100644
--- a/cpu/cpujit.py
+++ b/pystencils/cpu/cpujit.py
@@ -35,8 +35,8 @@ Then 'cl.exe' is used to compile.
 
 - **'os'**: should be detected automatically as 'windows'
 - **'msvc_version'**:  either a version number, year number, 'auto' or 'latest' for automatic detection of latest
-                      installed version or 'setuptools' for setuptools-based detection. Alternatively path to folder
-                      where Visual Studio is installed. This path has to contain a file called 'vcvarsall.bat'
+  installed version or 'setuptools' for setuptools-based detection. Alternatively path to folder
+  where Visual Studio is installed. This path has to contain a file called 'vcvarsall.bat'
 - **'arch'**: 'x86' or 'x64'
 - **'flags'**: flags passed to 'cl.exe', make sure OpenMP is activated
 - **'restrict_qualifier'**: the restrict qualifier is not standardized across compilers.
diff --git a/cpu/kernelcreation.py b/pystencils/cpu/kernelcreation.py
similarity index 100%
rename from cpu/kernelcreation.py
rename to pystencils/cpu/kernelcreation.py
diff --git a/cpu/msvc_detection.py b/pystencils/cpu/msvc_detection.py
similarity index 100%
rename from cpu/msvc_detection.py
rename to pystencils/cpu/msvc_detection.py
diff --git a/cpu/vectorization.py b/pystencils/cpu/vectorization.py
similarity index 100%
rename from cpu/vectorization.py
rename to pystencils/cpu/vectorization.py
diff --git a/data_types.py b/pystencils/data_types.py
similarity index 100%
rename from data_types.py
rename to pystencils/data_types.py
diff --git a/datahandling/__init__.py b/pystencils/datahandling/__init__.py
similarity index 100%
rename from datahandling/__init__.py
rename to pystencils/datahandling/__init__.py
diff --git a/datahandling/blockiteration.py b/pystencils/datahandling/blockiteration.py
similarity index 100%
rename from datahandling/blockiteration.py
rename to pystencils/datahandling/blockiteration.py
diff --git a/datahandling/datahandling_interface.py b/pystencils/datahandling/datahandling_interface.py
similarity index 100%
rename from datahandling/datahandling_interface.py
rename to pystencils/datahandling/datahandling_interface.py
diff --git a/datahandling/parallel_datahandling.py b/pystencils/datahandling/parallel_datahandling.py
similarity index 100%
rename from datahandling/parallel_datahandling.py
rename to pystencils/datahandling/parallel_datahandling.py
diff --git a/datahandling/serial_datahandling.py b/pystencils/datahandling/serial_datahandling.py
similarity index 100%
rename from datahandling/serial_datahandling.py
rename to pystencils/datahandling/serial_datahandling.py
diff --git a/datahandling/vtk.py b/pystencils/datahandling/vtk.py
similarity index 100%
rename from datahandling/vtk.py
rename to pystencils/datahandling/vtk.py
diff --git a/display_utils.py b/pystencils/display_utils.py
similarity index 100%
rename from display_utils.py
rename to pystencils/display_utils.py
diff --git a/fast_approximation.py b/pystencils/fast_approximation.py
similarity index 100%
rename from fast_approximation.py
rename to pystencils/fast_approximation.py
diff --git a/fd/__init__.py b/pystencils/fd/__init__.py
similarity index 100%
rename from fd/__init__.py
rename to pystencils/fd/__init__.py
diff --git a/fd/derivation.py b/pystencils/fd/derivation.py
similarity index 100%
rename from fd/derivation.py
rename to pystencils/fd/derivation.py
diff --git a/fd/derivative.py b/pystencils/fd/derivative.py
similarity index 100%
rename from fd/derivative.py
rename to pystencils/fd/derivative.py
diff --git a/fd/finitedifferences.py b/pystencils/fd/finitedifferences.py
similarity index 100%
rename from fd/finitedifferences.py
rename to pystencils/fd/finitedifferences.py
diff --git a/fd/spatial.py b/pystencils/fd/spatial.py
similarity index 100%
rename from fd/spatial.py
rename to pystencils/fd/spatial.py
diff --git a/field.py b/pystencils/field.py
similarity index 100%
rename from field.py
rename to pystencils/field.py
diff --git a/gpucuda/__init__.py b/pystencils/gpucuda/__init__.py
similarity index 100%
rename from gpucuda/__init__.py
rename to pystencils/gpucuda/__init__.py
diff --git a/gpucuda/cudajit.py b/pystencils/gpucuda/cudajit.py
similarity index 100%
rename from gpucuda/cudajit.py
rename to pystencils/gpucuda/cudajit.py
diff --git a/gpucuda/indexing.py b/pystencils/gpucuda/indexing.py
similarity index 100%
rename from gpucuda/indexing.py
rename to pystencils/gpucuda/indexing.py
diff --git a/gpucuda/kernelcreation.py b/pystencils/gpucuda/kernelcreation.py
similarity index 100%
rename from gpucuda/kernelcreation.py
rename to pystencils/gpucuda/kernelcreation.py
diff --git a/gpucuda/periodicity.py b/pystencils/gpucuda/periodicity.py
similarity index 100%
rename from gpucuda/periodicity.py
rename to pystencils/gpucuda/periodicity.py
diff --git a/include/__init__.py b/pystencils/include/__init__.py
similarity index 100%
rename from include/__init__.py
rename to pystencils/include/__init__.py
diff --git a/include/philox_rand.h b/pystencils/include/philox_rand.h
similarity index 100%
rename from include/philox_rand.h
rename to pystencils/include/philox_rand.h
diff --git a/integer_functions.py b/pystencils/integer_functions.py
similarity index 100%
rename from integer_functions.py
rename to pystencils/integer_functions.py
diff --git a/integer_set_analysis.py b/pystencils/integer_set_analysis.py
similarity index 100%
rename from integer_set_analysis.py
rename to pystencils/integer_set_analysis.py
diff --git a/jupytersetup.py b/pystencils/jupytersetup.py
similarity index 100%
rename from jupytersetup.py
rename to pystencils/jupytersetup.py
diff --git a/kerncraft_coupling/__init__.py b/pystencils/kerncraft_coupling/__init__.py
similarity index 100%
rename from kerncraft_coupling/__init__.py
rename to pystencils/kerncraft_coupling/__init__.py
diff --git a/kerncraft_coupling/generate_benchmark.py b/pystencils/kerncraft_coupling/generate_benchmark.py
similarity index 100%
rename from kerncraft_coupling/generate_benchmark.py
rename to pystencils/kerncraft_coupling/generate_benchmark.py
diff --git a/kerncraft_coupling/kerncraft_interface.py b/pystencils/kerncraft_coupling/kerncraft_interface.py
similarity index 100%
rename from kerncraft_coupling/kerncraft_interface.py
rename to pystencils/kerncraft_coupling/kerncraft_interface.py
diff --git a/kernel_decorator.py b/pystencils/kernel_decorator.py
similarity index 100%
rename from kernel_decorator.py
rename to pystencils/kernel_decorator.py
diff --git a/kernelcreation.py b/pystencils/kernelcreation.py
similarity index 100%
rename from kernelcreation.py
rename to pystencils/kernelcreation.py
diff --git a/kernelparameters.py b/pystencils/kernelparameters.py
similarity index 100%
rename from kernelparameters.py
rename to pystencils/kernelparameters.py
diff --git a/llvm/__init__.py b/pystencils/llvm/__init__.py
similarity index 100%
rename from llvm/__init__.py
rename to pystencils/llvm/__init__.py
diff --git a/llvm/control_flow.py b/pystencils/llvm/control_flow.py
similarity index 100%
rename from llvm/control_flow.py
rename to pystencils/llvm/control_flow.py
diff --git a/llvm/kernelcreation.py b/pystencils/llvm/kernelcreation.py
similarity index 100%
rename from llvm/kernelcreation.py
rename to pystencils/llvm/kernelcreation.py
diff --git a/llvm/llvm.py b/pystencils/llvm/llvm.py
similarity index 100%
rename from llvm/llvm.py
rename to pystencils/llvm/llvm.py
diff --git a/llvm/llvmjit.py b/pystencils/llvm/llvmjit.py
similarity index 100%
rename from llvm/llvmjit.py
rename to pystencils/llvm/llvmjit.py
diff --git a/plot2d.py b/pystencils/plot2d.py
similarity index 100%
rename from plot2d.py
rename to pystencils/plot2d.py
diff --git a/rng.py b/pystencils/rng.py
similarity index 100%
rename from rng.py
rename to pystencils/rng.py
diff --git a/runhelper/__init__.py b/pystencils/runhelper/__init__.py
similarity index 100%
rename from runhelper/__init__.py
rename to pystencils/runhelper/__init__.py
diff --git a/runhelper/db.py b/pystencils/runhelper/db.py
similarity index 100%
rename from runhelper/db.py
rename to pystencils/runhelper/db.py
diff --git a/runhelper/parameterstudy.py b/pystencils/runhelper/parameterstudy.py
similarity index 100%
rename from runhelper/parameterstudy.py
rename to pystencils/runhelper/parameterstudy.py
diff --git a/session.py b/pystencils/session.py
similarity index 100%
rename from session.py
rename to pystencils/session.py
diff --git a/simp/__init__.py b/pystencils/simp/__init__.py
similarity index 100%
rename from simp/__init__.py
rename to pystencils/simp/__init__.py
diff --git a/simp/assignment_collection.py b/pystencils/simp/assignment_collection.py
similarity index 100%
rename from simp/assignment_collection.py
rename to pystencils/simp/assignment_collection.py
diff --git a/simp/liveness_opts.py b/pystencils/simp/liveness_opts.py
similarity index 100%
rename from simp/liveness_opts.py
rename to pystencils/simp/liveness_opts.py
diff --git a/simp/simplifications.py b/pystencils/simp/simplifications.py
similarity index 100%
rename from simp/simplifications.py
rename to pystencils/simp/simplifications.py
diff --git a/simp/simplificationstrategy.py b/pystencils/simp/simplificationstrategy.py
similarity index 100%
rename from simp/simplificationstrategy.py
rename to pystencils/simp/simplificationstrategy.py
diff --git a/slicing.py b/pystencils/slicing.py
similarity index 100%
rename from slicing.py
rename to pystencils/slicing.py
diff --git a/stencils.py b/pystencils/stencils.py
similarity index 100%
rename from stencils.py
rename to pystencils/stencils.py
diff --git a/sympy_gmpy_bug_workaround.py b/pystencils/sympy_gmpy_bug_workaround.py
similarity index 100%
rename from sympy_gmpy_bug_workaround.py
rename to pystencils/sympy_gmpy_bug_workaround.py
diff --git a/sympyextensions.py b/pystencils/sympyextensions.py
similarity index 100%
rename from sympyextensions.py
rename to pystencils/sympyextensions.py
diff --git a/timeloop.py b/pystencils/timeloop.py
similarity index 100%
rename from timeloop.py
rename to pystencils/timeloop.py
diff --git a/transformations.py b/pystencils/transformations.py
similarity index 97%
rename from transformations.py
rename to pystencils/transformations.py
index fa683e1d59c35073ab622a2f5b323b3d56ba20e8..e781b3bc044ad56cc50ec6644404ea93e77a4563 100644
--- a/transformations.py
+++ b/pystencils/transformations.py
@@ -8,7 +8,6 @@ import sympy as sp
 from sympy.logic.boolalg import Boolean
 from sympy.tensor import IndexedBase
 from pystencils.assignment import Assignment
-from pystencils.assignment_collection.nestedscopes import NestedScopes
 from pystencils.field import Field, FieldType
 from pystencils.data_types import TypedSymbol, PointerType, StructType, get_base_type, reinterpret_cast_func, \
     cast_func, pointer_arithmetic_func, get_type_of_expression, collate_types, create_type
@@ -17,6 +16,60 @@ from pystencils.slicing import normalize_slice
 import pystencils.astnodes as ast
 
 
+class NestedScopes:
+    """Symbol visibility model using nested scopes
+
+    - every accessed symbol that was not defined before, is added as a "free parameter"
+    - free parameters are global, i.e. they are not in scopes
+    - push/pop adds or removes a scope
+
+    >>> s = NestedScopes()
+    >>> s.access_symbol("a")
+    >>> s.is_defined("a")
+    False
+    >>> s.free_parameters
+    {'a'}
+    >>> s.define_symbol("b")
+    >>> s.is_defined("b")
+    True
+    >>> s.push()
+    >>> s.is_defined_locally("b")
+    False
+    >>> s.define_symbol("c")
+    >>> s.pop()
+    >>> s.is_defined("c")
+    False
+    """
+
+    def __init__(self):
+        self.free_parameters = set()
+        self._defined = [set()]
+
+    def access_symbol(self, symbol):
+        if not self.is_defined(symbol):
+            self.free_parameters.add(symbol)
+
+    def define_symbol(self, symbol):
+        self._defined[-1].add(symbol)
+
+    def is_defined(self, symbol):
+        return any(symbol in scopes for scopes in self._defined)
+
+    def is_defined_locally(self, symbol):
+        return symbol in self._defined[-1]
+
+    def push(self):
+        self._defined.append(set())
+
+    def pop(self):
+        self._defined.pop()
+        assert self.depth >= 1
+
+    @property
+    def depth(self):
+        return len(self._defined)
+
+
 def filtered_tree_iteration(node, node_type, stop_type=None):
     for arg in node.args:
         if isinstance(arg, node_type):
diff --git a/utils.py b/pystencils/utils.py
similarity index 100%
rename from utils.py
rename to pystencils/utils.py
diff --git a/pystencils_tests/__init__.py b/pystencils_tests/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/pystencils_tests/benchmark/SkylakeSP_Gold-5122_allinclusive.yaml b/pystencils_tests/benchmark/SkylakeSP_Gold-5122_allinclusive.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..75370ecd2951dcd91217325cb5c40126ed0664d4
--- /dev/null
+++ b/pystencils_tests/benchmark/SkylakeSP_Gold-5122_allinclusive.yaml
@@ -0,0 +1,600 @@
+# FIXME
+# FIXME performance counters might be wrong. This will only affect the Benchmark model
+# FIXME bandwidth measurements need validation
+# FIXME
+
+kerncraft version: 0.7.2
+model name: Intel(R) Xeon(R) Gold 5122 CPU @ 3.60GHz
+model type: Intel Core Skylake SP
+sockets: 2
+cores per socket: 4
+threads per core: 2
+NUMA domains per socket: 1
+cores per NUMA domain: 4
+clock: 3.6 GHz
+FLOPs per cycle:
+  SP:
+    total: 64
+    FMA: 64
+    ADD: 32
+    MUL: 32
+  DP:
+    total: 32
+    FMA: 32
+    ADD: 16
+    MUL: 16
+micro-architecture: SKX
+compiler:
+  !!omap
+  - icc: -O3 -fno-alias -xCORE-AVX512
+  - clang: -O3 -march=skylake-avx512 -D_POSIX_C_SOURCE=200112L
+  - gcc: -O3 -march=skylake-avx512
+cacheline size: 64 B
+overlapping model:
+  ports: ["0", "0DV", "1", "2", "3", "4", "5", "6", "7"]
+  performance counter metric:
+          Max(UOPS_DISPATCHED_PORT_PORT_0:PMC[0-3],
+          UOPS_DISPATCHED_PORT_PORT_1:PMC[0-3],
+          UOPS_DISPATCHED_PORT_PORT_4:PMC[0-3],
+          UOPS_DISPATCHED_PORT_PORT_5:PMC[0-3],
+          UOPS_DISPATCHED_PORT_PORT_6:PMC[0-3],
+          UOPS_DISPATCHED_PORT_PORT_7:PMC[0-3])
+non-overlapping model:
+  ports: ["2D", "3D"]
+  performance counter metric: T_OL + T_L1L2 + T_L2L3 + T_L3MEM
+memory hierarchy:
+- level: L1
+  performance counter metrics:
+    accesses:  MEM_INST_RETIRED_ALL_LOADS:PMC[0-3]
+    misses: L1D_REPLACEMENT:PMC[0-3]
+    evicts: L2_TRANS_L1D_WB:PMC[0-3]
+  cache per group:
+    sets: 64
+    ways: 8
+    cl_size: 64
+    replacement_policy: 'LRU'
+    write_allocate: True
+    write_back: True
+    load_from: L2
+    store_to: L2
+  size per group: 32.00 kB
+  groups: 8
+  cores per group: 1
+  threads per group: 2
+- level: L2
+  non-overlap upstream throughput: [64 B/cy, 'half-duplex']
+  performance counter metrics:
+    accesses: L1D_REPLACEMENT:PMC[0-3]
+    misses: L2_LINES_IN_ALL:PMC[0-3]
+    evicts: L2_TRANS_L2_WB:PMC[0-3]
+  cache per group:
+    sets: 1024
+    ways: 16
+    cl_size: 64
+    replacement_policy: 'LRU'
+    write_allocate: True
+    write_back: True
+    load_from: null  # L3 is a victim cache, thus unless a hit in L3, misses get forwarded to MEM
+    victims_to: L3  # all victims, modified or not are passed onto L3
+    store_to: L3
+  size per group: 1.00 MB
+  groups: 8
+  cores per group: 1
+  threads per group: 2
+- level: L3
+  non-overlap upstream throughput: [16 B/cy, 'full-duplex']
+  performance counter metrics:
+    accesses: L2_LINES_IN_ALL:PMC[0-3]
+    # FIXME not all misses in L2 lead to loads from L3, only the hits do
+    misses: (CAS_COUNT_RD:MBOX0C[01] + CAS_COUNT_WR:MBOX0C[01] +
+             CAS_COUNT_RD:MBOX1C[01] + CAS_COUNT_WR:MBOX1C[01] +
+             CAS_COUNT_RD:MBOX2C[01] + CAS_COUNT_WR:MBOX2C[01] +
+             CAS_COUNT_RD:MBOX3C[01] + CAS_COUNT_WR:MBOX3C[01] +
+             CAS_COUNT_RD:MBOX4C[01] + CAS_COUNT_WR:MBOX4C[01] +
+             CAS_COUNT_RD:MBOX5C[01] + CAS_COUNT_WR:MBOX5C[01])
+    evicts: L2_TRANS_L2_WB:PMC[0-3]
+  cache per group:
+    sets: 16896
+    # TODO is actuall something else, but necessary to get to 16.5 MB
+    ways: 16
+    # TODO is actually 11, but pycachesim only supports powers of two
+    cl_size: 64
+    replacement_policy: 'LRU'
+    write_allocate: False
+    write_back: True
+  size per group: 16.50 MB
+  groups: 2
+  cores per group: 4
+  threads per group: 8
+- level: MEM
+  cores per group: 4
+  threads per group: 8
+  non-overlap upstream throughput: ['full socket memory bandwidth', 'half-duplex']
+  penalty cycles per read stream: 0
+  size per group:
+benchmarks:
+  kernels:
+    load:
+      read streams:
+        streams: 1
+        bytes: 8.00 B
+      read+write streams:
+        streams: 0
+        bytes: 0.00 B
+      write streams:
+        streams: 0
+        bytes: 0.00 B
+      FLOPs per iteration: 0
+    copy:
+      read streams:
+        streams: 1
+        bytes: 8.00 B
+      read+write streams:
+        streams: 0
+        bytes: 0.00 B
+      write streams:
+        streams: 1
+        bytes: 8.00 B
+      FLOPs per iteration: 0
+    update:
+      read streams:
+        streams: 1
+        bytes: 8.00 B
+      read+write streams:
+        streams: 1
+        bytes: 8.00 B
+      write streams:
+        streams: 1
+        bytes: 8.00 B
+      FLOPs per iteration: 0
+    triad:
+      read streams:
+        streams: 3
+        bytes: 24.00 B
+      read+write streams:
+        streams: 0
+        bytes: 0.00 B
+      write streams:
+        streams: 1
+        bytes: 8.00 B
+      FLOPs per iteration: 2
+    daxpy:
+      read streams:
+        streams: 2
+        bytes: 16.00 B
+      read+write streams:
+        streams: 1
+        bytes: 8.00 B
+      write streams:
+        streams: 1
+        bytes: 8.00 B
+      FLOPs per iteration: 2
+  measurements:
+    L1:
+      1:
+        threads per core: 1
+        cores:
+        - 1
+        - 2
+        - 3
+        - 4
+        threads:
+        - 1
+        - 2
+        - 3
+        - 4
+        size per core:
+        - 21.12 kB
+        - 21.12 kB
+        - 21.12 kB
+        - 21.12 kB
+        size per thread:
+        - 21.12 kB
+        - 21.12 kB
+        - 21.12 kB
+        - 21.12 kB
+        total size:
+        - 21.12 kB
+        - 42.24 kB
+        - 63.36 kB
+        - 84.48 kB
+        results:
+          load:
+          - 42.98 GB/s
+          - 85.08 GB/s
+          - 127.45 GB/s
+          - 169.92 GB/s
+          copy:
+          - 56.07 GB/s
+          - 111.50 GB/s
+          - 164.90 GB/s
+          - 221.50 GB/s
+          update:
+          - 56.54 GB/s
+          - 112.25 GB/s
+          - 168.50 GB/s
+          - 224.75 GB/s
+          triad:
+          - 45.90 GB/s
+          - 89.81 GB/s
+          - 127.29 GB/s
+          - 169.57 GB/s
+          daxpy:
+          - 36.62 GB/s
+          - 71.30 GB/s
+          - 103.52 GB/s
+          - 135.26 GB/s
+      2:
+        threads per core: 2
+        cores:
+        - 1
+        - 2
+        - 3
+        - 4
+        threads:
+        - 2
+        - 4
+        - 6
+        - 8
+        size per core:
+        - 21.12 kB
+        - 21.12 kB
+        - 21.12 kB
+        - 21.12 kB
+        size per thread:
+        - 10.56 kB
+        - 10.56 kB
+        - 10.56 kB
+        - 10.56 kB
+        total size:
+        - 21.12 kB
+        - 42.24 kB
+        - 63.36 kB
+        - 84.48 kB
+        results:
+          load:
+          - 49.61 GB/s
+          - 98.80 GB/s
+          - 147.98 GB/s
+          - 198.22 GB/s
+          copy:
+          - 55.98 GB/s
+          - 111.56 GB/s
+          - 167.08 GB/s
+          - 220.42 GB/s
+          update:
+          - 56.53 GB/s
+          - 112.72 GB/s
+          - 168.95 GB/s
+          - 225.31 GB/s
+          triad:
+          - 54.01 GB/s
+          - 104.58 GB/s
+          - 153.02 GB/s
+          - 200.93 GB/s
+          daxpy:
+          - 41.11 GB/s
+          - 80.28 GB/s
+          - 115.71 GB/s
+          - 152.81 GB/s
+    L2:
+      1:
+        threads per core: 1
+        cores:
+        - 1
+        - 2
+        - 3
+        - 4
+        threads:
+        - 1
+        - 2
+        - 3
+        - 4
+        size per core:
+        - 660.00 kB
+        - 660.00 kB
+        - 660.00 kB
+        - 660.00 kB
+        size per thread:
+        - 660.00 kB
+        - 660.00 kB
+        - 660.00 kB
+        - 660.00 kB
+        total size:
+        - 660.00 kB
+        - 1.32 MB
+        - 1.98 MB
+        - 2.64 MB
+        results:
+          load:
+          - 27.15 GB/s
+          - 54.09 GB/s
+          - 80.61 GB/s
+          - 106.41 GB/s
+          copy:
+          - 43.53 GB/s
+          - 90.07 GB/s
+          - 127.73 GB/s
+          - 171.81 GB/s
+          update:
+          - 50.38 GB/s
+          - 98.47 GB/s
+          - 147.91 GB/s
+          - 197.20 GB/s
+          triad:
+          - 43.38 GB/s
+          - 83.72 GB/s
+          - 124.83 GB/s
+          - 166.04 GB/s
+          daxpy:
+          - 36.29 GB/s
+          - 71.29 GB/s
+          - 103.33 GB/s
+          - 136.48 GB/s
+      2:
+        threads per core: 2
+        cores:
+        - 1
+        - 2
+        - 3
+        - 4
+        threads:
+        - 2
+        - 4
+        - 6
+        - 8
+        size per core:
+        - 660.00 kB
+        - 660.00 kB
+        - 660.00 kB
+        - 660.00 kB
+        size per thread:
+        - 330.00 kB
+        - 330.00 kB
+        - 330.00 kB
+        - 330.00 kB
+        total size:
+        - 660.00 kB
+        - 1.32 MB
+        - 1.98 MB
+        - 2.64 MB
+        results:
+          load:
+          - 35.29 GB/s
+          - 70.28 GB/s
+          - 104.67 GB/s
+          - 139.63 GB/s
+          copy:
+          - 42.23 GB/s
+          - 83.70 GB/s
+          - 124.33 GB/s
+          - 167.50 GB/s
+          update:
+          - 50.09 GB/s
+          - 99.77 GB/s
+          - 149.87 GB/s
+          - 198.82 GB/s
+          triad:
+          - 52.38 GB/s
+          - 100.00 GB/s
+          - 147.40 GB/s
+          - 193.31 GB/s
+          daxpy:
+          - 41.14 GB/s
+          - 80.22 GB/s
+          - 116.23 GB/s
+          - 155.08 GB/s
+    L3:
+      1:
+        threads per core: 1
+        cores:
+        - 1
+        - 2
+        - 3
+        - 4
+        threads:
+        - 1
+        - 2
+        - 3
+        - 4
+        size per core:
+        - 10.56 MB
+        - 5.28 MB
+        - 3.52 MB
+        - 2.64 MB
+        size per thread:
+        - 10.56 MB
+        - 5.28 MB
+        - 3.52 MB
+        - 2.64 MB
+        total size:
+        - 10.56 MB
+        - 10.56 MB
+        - 10.56 MB
+        - 10.56 MB
+        results:
+          load:
+          - 22.40 GB/s
+          - 44.77 GB/s
+          - 65.71 GB/s
+          - 89.26 GB/s
+          copy:
+          - 25.32 GB/s
+          - 49.70 GB/s
+          - 72.89 GB/s
+          - 98.62 GB/s
+          update:
+          - 41.24 GB/s
+          - 81.14 GB/s
+          - 122.22 GB/s
+          - 166.44 GB/s
+          triad:
+          - 25.61 GB/s
+          - 50.02 GB/s
+          - 73.23 GB/s
+          - 98.95 GB/s
+          daxpy:
+          - 32.07 GB/s
+          - 62.65 GB/s
+          - 89.91 GB/s
+          - 120.65 GB/s
+      2:
+        threads per core: 2
+        cores:
+        - 1
+        - 2
+        - 3
+        - 4
+        threads:
+        - 2
+        - 4
+        - 6
+        - 8
+        size per core:
+        - 10.56 MB
+        - 5.28 MB
+        - 3.52 MB
+        - 2.64 MB
+        size per thread:
+        - 5.28 MB
+        - 2.64 MB
+        - 1.76 MB
+        - 1.32 MB
+        total size:
+        - 10.56 MB
+        - 10.56 MB
+        - 10.56 MB
+        - 10.56 MB
+        results:
+          load:
+          - 26.18 GB/s
+          - 51.85 GB/s
+          - 75.82 GB/s
+          - 101.39 GB/s
+          copy:
+          - 26.22 GB/s
+          - 51.83 GB/s
+          - 76.40 GB/s
+          - 102.84 GB/s
+          update:
+          - 43.51 GB/s
+          - 86.75 GB/s
+          - 129.86 GB/s
+          - 174.54 GB/s
+          triad:
+          - 26.39 GB/s
+          - 51.80 GB/s
+          - 76.27 GB/s
+          - 102.66 GB/s
+          daxpy:
+          - 37.43 GB/s
+          - 73.16 GB/s
+          - 106.53 GB/s
+          - 142.76 GB/s
+    MEM:
+      1:
+        threads per core: 1
+        cores:
+        - 1
+        - 2
+        - 3
+        - 4
+        threads:
+        - 1
+        - 2
+        - 3
+        - 4
+        size per core:
+        - 240.00 MB
+        - 120.00 MB
+        - 80.00 MB
+        - 60.00 MB
+        size per thread:
+        - 240.00 MB
+        - 120.00 MB
+        - 80.00 MB
+        - 60.00 MB
+        total size:
+        - 240.00 MB
+        - 240.00 MB
+        - 240.00 MB
+        - 240.00 MB
+        results:
+          load:
+          - 12.03 GB/s
+          - 24.38 GB/s
+          - 34.83 GB/s
+          - 45.05 GB/s
+          copy:
+          - 12.32 GB/s
+          - 24.40 GB/s
+          - 32.82 GB/s
+          - 37.00 GB/s
+          update:
+          - 20.83 GB/s
+          - 40.25 GB/s
+          - 48.81 GB/s
+          - 54.84 GB/s
+          triad:
+          - 11.64 GB/s
+          - 23.17 GB/s
+          - 34.78 GB/s
+          - 42.97 GB/s
+          daxpy:
+          - 17.69 GB/s
+          - 34.02 GB/s
+          - 48.12 GB/s
+          - 55.73 GB/s
+      2:
+        threads per core: 2
+        cores:
+        - 1
+        - 2
+        - 3
+        - 4
+        threads:
+        - 2
+        - 4
+        - 6
+        - 8
+        size per core:
+        - 240.00 MB
+        - 120.00 MB
+        - 80.00 MB
+        - 60.00 MB
+        size per thread:
+        - 120.00 MB
+        - 60.00 MB
+        - 40.00 MB
+        - 30.00 MB
+        total size:
+        - 240.00 MB
+        - 240.00 MB
+        - 240.00 MB
+        - 240.00 MB
+        results:
+          load:
+          - 15.33 GB/s
+          - 28.32 GB/s
+          - 41.34 GB/s
+          - 53.02 GB/s
+          copy:
+          - 13.96 GB/s
+          - 26.61 GB/s
+          - 34.39 GB/s
+          - 38.96 GB/s
+          update:
+          - 26.47 GB/s
+          - 47.82 GB/s
+          - 56.70 GB/s
+          - 62.78 GB/s
+          triad:
+          - 14.42 GB/s
+          - 26.66 GB/s
+          - 36.94 GB/s
+          - 44.01 GB/s
+          daxpy:
+          - 20.96 GB/s
+          - 39.12 GB/s
+          - 51.55 GB/s
+          - 58.37 GB/s
diff --git a/pystencils_tests/benchmark/benchmark.py b/pystencils_tests/benchmark/benchmark.py
new file mode 100644
index 0000000000000000000000000000000000000000..9198912ba0224714ca2b882ec2c6e6a55c44be01
--- /dev/null
+++ b/pystencils_tests/benchmark/benchmark.py
@@ -0,0 +1,189 @@
+import os
+import math
+import time
+import numpy as np
+import sympy as sp
+from influxdb import InfluxDBClient
+from git import Repo
+from kerncraft.models import ECM, Benchmark, Roofline, RooflineIACA
+from kerncraft.machinemodel import MachineModel
+from kerncraft.prefixedunit import PrefixedUnit
+from pystencils.kerncraft_coupling import KerncraftParameters, PyStencilsKerncraftKernel
+from pystencils import Field, Assignment, create_kernel
+
+
+def outputBenchmark(analysis):
+    output = {}
+    keys = ['Runtime (per repetition) [s]', 'Iterations per repetition',
+            'Runtime (per cacheline update) [cy/CL]', 'MEM volume (per repetition) [B]',
+            'Performance [MFLOP/s]', 'Performance [MLUP/s]', 'Performance [MIt/s]', 'MEM BW [MByte/s]']
+    copies = {key: analysis[key] for key in keys}
+    output.update(copies)
+
+    for cache, metrics in analysis['data transfers'].items():
+        for metric_name, metric_value in metrics.items():
+            fixed = metric_value.with_prefix('')
+            output[cache + ' ' + metric_name + ' ' + fixed.prefix + fixed.unit] = fixed.value
+
+    for level, value in analysis['ECM'].items():
+        output['Phenomenological ECM ' + level + ' cy/CL'] = value
+    return output
+
+
+def outputECM(analysis):
+    output = {}
+    keys = ['T_nOL', 'T_OL', 'cl throughput', 'uops']
+    copies = {key: analysis[key] for key in keys}
+    output.update(copies)
+
+    if 'memory bandwidth kernel' in analysis:
+        output['memory bandwidth kernel' + analysis['memory bandwidth kernel'] + analysis['memory bandwidth'].prefix +
+               analysis['memory bandwidth'].unit] = analysis['memory bandwidth'].value
+
+    output['scaling cores'] = int(analysis['scaling cores']) if not math.isinf(analysis['scaling cores']) else -1
+
+    for key, value in analysis['cycles']:
+        output[key] = value
+    return output
+
+
+def outputRoofline(analysis):
+    output = {}
+    keys = ['min performance']#'bottleneck level'
+    copies = {key: analysis[key] for key in keys}
+    output.update(copies)
+    # TODO save bottleneck information (compute it here)
+
+    #fixed = analysis['max_flops'].with_prefix('G')
+    #output['max GFlop/s'] = fixed.value
+
+    #if analysis['min performance'] > max_flops:
+    #    # CPU bound
+    #    print('CPU bound with {} cores(s)'.format(self._args.cores), file=output_file)
+    #    print('{!s} due to CPU max. FLOP/s'.format(max_flops), file=output_file)
+    #else:
+    # Memory bound
+    bottleneck = analysis['mem bottlenecks'][analysis['bottleneck level']]
+    output['bottleneck GFlop/s'] = bottleneck['performance'].with_prefix('G').value
+    output['bottleneck level'] = bottleneck['level']
+    output['bottleneck bw kernel'] = bottleneck['bw kernel']
+    output['bottleneck arithmetic intensity'] = bottleneck['arithmetic intensity']
+
+    for i, level in enumerate(analysis['mem bottlenecks']):
+        if level is None:
+            continue
+        for key, value in level.items():
+            if isinstance(value, PrefixedUnit):
+                fixed = value.with_prefix('G')
+                output['level ' + str(i) + ' ' + key + ' [' + fixed.prefix + fixed.unit + ']'] = 'inf' if isinstance(
+                    fixed.value, float) and math.isinf(fixed.value) else fixed.value
+            else:
+                output['level ' + str(i) + ' ' + key] = 'inf' if isinstance(value, float) and math.isinf(
+                    value) else value
+    return output
+
+
+def outputRooflineIACA(analysis):
+    output = {}
+    keys = ['min performance'] #'bottleneck level'
+    copies = {key: analysis[key] for key in keys}
+    #output.update(copies)
+    # TODO save bottleneck information (compute it here)
+
+    #fixed = analysis['max_flops'].with_prefix('G')
+    #output['max GFlop/s'] = fixed.value
+
+    #if analysis['min performance'] > max_flops:
+    #    # CPU bound
+    #    print('CPU bound with {} cores(s)'.format(self._args.cores), file=output_file)
+    #    print('{!s} due to CPU max. FLOP/s'.format(max_flops), file=output_file)
+    #else:
+    # Memory bound
+    bottleneck = analysis['mem bottlenecks'][analysis['bottleneck level']]
+    output['bottleneck GFlop/s'] = bottleneck['performance'].with_prefix('G').value
+    output['bottleneck level'] = bottleneck['level']
+    output['bottleneck bw kernel'] = bottleneck['bw kernel']
+    output['bottleneck arithmetic intensity'] = bottleneck['arithmetic intensity']
+
+    for i, level in enumerate(analysis['mem bottlenecks']):
+        if level is None:
+            continue
+        for key, value in level.items():
+            if isinstance(value, PrefixedUnit):
+                fixed = value.with_prefix('G')
+                output['level ' + str(i) + ' ' + key + ' [' + fixed.prefix + fixed.unit + ']'] = 'inf' if isinstance(
+                    fixed.value, float) and math.isinf(fixed.value) else fixed.value
+            else:
+                output['level ' + str(i) + ' ' + key] = 'inf' if isinstance(value, float) and math.isinf(
+                    value) else value
+    return output
+
+
+def reportAnalysis(ast, models, machine, tags, fields=None):
+    kernel = PyStencilsKerncraftKernel(ast, machine)
+    client = InfluxDBClient('i10grafana.informatik.uni-erlangen.de', 8086, 'pystencils',
+                            'roggan', 'pystencils')
+    repo = Repo(search_parent_directories=True)
+    commit = repo.head.commit
+    point_time = int(time.time())
+
+    for model in models:
+        benchmark = model(kernel, machine, KerncraftParameters())
+        benchmark.analyze()
+        analysis = benchmark.results
+        if model is Benchmark:
+            output = outputBenchmark(analysis)
+        elif model is ECM:
+            output = outputECM(analysis)
+        elif model is Roofline:
+            output = outputRoofline(analysis)
+        elif model is RooflineIACA:
+            output = outputRooflineIACA(analysis)
+        else:
+            raise ValueError('No valid model for analysis given!')
+
+        if fields is not None:
+            output.update(fields)
+
+        output['commit'] = commit.hexsha
+
+        json_body = [
+            {
+                'measurement': model.__name__,
+                'tags': tags,
+                'time': point_time,
+                'fields': output
+            }
+        ]
+        client.write_points(json_body, time_precision='s')
+
+
+def main():
+    size = [20, 200, 200]
+    arr = np.zeros(size)
+    a = Field.create_from_numpy_array('a', arr, index_dimensions=0)
+    b = Field.create_from_numpy_array('b', arr, index_dimensions=0)
+    s = sp.Symbol("s")
+    rhs = a[0, -1, 0] + a[0, 1, 0] + \
+          a[-1, 0, 0] + a[1, 0, 0] + \
+          a[0, 0, -1] + a[0, 0, 1]
+
+    updateRule = Assignment(b[0, 0, 0], s * rhs)
+    ast = create_kernel([updateRule])
+    INPUT_FOLDER = "./"
+    machineFilePath = os.path.join(INPUT_FOLDER, "SkylakeSP_Gold-5122_allinclusive.yaml")
+    machine = MachineModel(path_to_yaml=machineFilePath)
+    tags = {
+                    'host': os.uname()[1],
+                    'project': 'pystencils',
+                    'kernel': 'jacobi_3D ' + str(size)
+                }
+
+    reportAnalysis(ast, [ECM, Roofline, RooflineIACA, Benchmark], machine, tags)
+
+
+if __name__ == '__main__':
+    main()
+    while False:
+        main()
+        time.sleep(3600)
diff --git a/pystencils_tests/benchmark/generate.py b/pystencils_tests/benchmark/generate.py
new file mode 100644
index 0000000000000000000000000000000000000000..09e2769e2289525089e92649e48713cc5e9e593d
--- /dev/null
+++ b/pystencils_tests/benchmark/generate.py
@@ -0,0 +1,51 @@
+import sympy as sp
+import numpy as np
+from pystencils import Field, Assignment, create_kernel
+
+
+def meassure():
+    size = [30, 50, 3]
+    arr = np.zeros(size)
+    a = Field.create_from_numpy_array('a', arr, index_dimensions=1)
+    b = Field.create_from_numpy_array('b', arr, index_dimensions=1)
+    s = sp.Symbol("s")
+    rhs = a[0, -1](0) + a[0, 1] + a[-1, 0] + a[1, 0]
+    updateRule = Assignment(b[0, 0], s * rhs)
+    print(updateRule)
+
+    ast = create_kernel([updateRule])
+
+    # benchmark = generate_benchmark(ast)
+    # main = benchmark[0]
+    # kernel = benchmark[1]
+    # with open('src/main.cpp', 'w') as file:
+    #     file.write(main)
+    # with open('src/kernel.cpp', 'w') as file:
+    #     file.write(kernel)
+
+    func = ast.compile({'omega': 2/3})
+
+    from pystencils.kerncraft_coupling.generate_benchmark import generate_benchmark
+    from pystencils.kerncraft_coupling import BenchmarkAnalysis
+    from pystencils.kerncraft_coupling.kerncraft_interface import PyStencilsKerncraftKernel, KerncraftParameters
+    from kerncraft.machinemodel import MachineModel
+    from kerncraft.models import ECMData
+
+
+    machineFilePath = "../pystencils_tests/kerncraft_inputs/default_machine_file.yaml"
+    machine = MachineModel(path_to_yaml=machineFilePath)
+
+
+    benchmark = BenchmarkAnalysis(ast, machine)
+    #TODO what do i want to do with benchmark?
+
+    kernel = PyStencilsKerncraftKernel(ast)
+    model = ECMData(kernel, machine, KerncraftParameters())
+    model.analyze()
+    model.report()
+
+
+if __name__ == "__main__":
+    meassure()
+
+
diff --git a/pystencils_tests/benchmark/iacaMarks.h b/pystencils_tests/benchmark/iacaMarks.h
new file mode 100644
index 0000000000000000000000000000000000000000..be1973eb2ec7c9ccfe5c780d475a85e8fb09984e
--- /dev/null
+++ b/pystencils_tests/benchmark/iacaMarks.h
@@ -0,0 +1,53 @@
+/*
+* Copyright (2008-2009) Intel Corporation All Rights Reserved. 
+* The source code contained or described herein and all documents 
+* related to the source code ("Material") are owned by Intel Corporation 
+* or its suppliers or licensors. Title to the Material remains with 
+* Intel Corporation or its suppliers and licensors. The Material 
+* contains trade secrets and proprietary and confidential information 
+* of Intel or its suppliers and licensors. The Material is protected 
+* by worldwide copyright and trade secret laws and treaty provisions. 
+* No part of the Material may be used, copied, reproduced, modified, 
+* published, uploaded, posted, transmitted, distributed, or disclosed 
+* in any way without Intel(R)s prior express written permission.
+*
+* No license under any patent, copyright, trade secret or other 
+* intellectual property right is granted to or conferred upon you by 
+* disclosure or delivery of the Materials, either expressly, by implication,
+* inducement, estoppel or otherwise. Any license under such intellectual 
+* property rights must be express and approved by Intel in writing.
+*/
+
+#if defined (__GNUC__) 
+#define IACA_SSC_MARK( MARK_ID )						\
+__asm__ __volatile__ (									\
+					  "\n\t  movl $"#MARK_ID", %%ebx"	\
+					  "\n\t  .byte 0x64, 0x67, 0x90"	\
+					  : : : "memory" );
+
+#else
+#define IACA_SSC_MARK(x) {__asm  mov ebx, x\
+	__asm  _emit 0x64 \
+	__asm  _emit 0x67 \
+	__asm  _emit 0x90 }
+#endif
+
+#define IACA_START {IACA_SSC_MARK(111)}
+#define IACA_END {IACA_SSC_MARK(222)}
+
+#ifdef _WIN64
+#include <intrin.h>
+#define IACA_VC64_START __writegsbyte(111, 111);
+#define IACA_VC64_END   __writegsbyte(222, 222);
+#endif
+
+/**************** asm *****************
+;START_MARKER
+mov ebx, 111
+db 0x64, 0x67, 0x90
+
+;END_MARKER
+mov ebx, 222
+db 0x64, 0x67, 0x90
+
+**************************************/
diff --git a/pystencils_tests/benchmark/main.c b/pystencils_tests/benchmark/main.c
new file mode 100644
index 0000000000000000000000000000000000000000..6bd57f91c087842707d11291b8c34f471616672c
--- /dev/null
+++ b/pystencils_tests/benchmark/main.c
@@ -0,0 +1,11 @@
+#include "iacaMarks.h"
+
+int main(int argc, char * argv[]){
+	int a = 0;
+	for(int i = 0; i < argc+100000; i++){
+		IACA_START
+		a += i;
+	}
+	IACA_END
+	return a;
+}
diff --git a/pystencils_tests/kerncraft_inputs/2d-5pt.c b/pystencils_tests/kerncraft_inputs/2d-5pt.c
new file mode 100644
index 0000000000000000000000000000000000000000..0f2b99cf2bd7a39ed59ee7fa750f4bc495410fbd
--- /dev/null
+++ b/pystencils_tests/kerncraft_inputs/2d-5pt.c
@@ -0,0 +1,8 @@
+double a[30][50][3];
+double b[30][50][3];
+double s;
+
+for(int j=1; j<30-1; ++j)
+    for(int i=1; i<50-1; ++i)
+        b[j][i] = ( a[j][i-1] + a[j][i+1]
+                  + a[j-1][i] + a[j+1][i]) * s;
diff --git a/pystencils_tests/kerncraft_inputs/3d-7pt.c b/pystencils_tests/kerncraft_inputs/3d-7pt.c
new file mode 100644
index 0000000000000000000000000000000000000000..0e9ff901d1a9c757d945b27a3d03f48bc8e20d3b
--- /dev/null
+++ b/pystencils_tests/kerncraft_inputs/3d-7pt.c
@@ -0,0 +1,10 @@
+double a[M][N][N];
+double b[M][N][N];
+double s;
+
+for(int k=1; k<M-1; ++k)
+    for(int j=1; j<N-1; ++j)
+        for(int i=1; i<N-1; ++i)
+            b[k][j][i] = ( a[k][j][i-1] + a[k][j][i+1]
+                         + a[k][j-1][i] + a[k][j+1][i]
+                         + a[k-1][j][i] + a[k+1][j][i]) * s;
diff --git a/pystencils_tests/kerncraft_inputs/default_machine_file.yaml b/pystencils_tests/kerncraft_inputs/default_machine_file.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..edec1eef99dfcc153c7c6e933b60d1b6edca74be
--- /dev/null
+++ b/pystencils_tests/kerncraft_inputs/default_machine_file.yaml
@@ -0,0 +1,277 @@
+kerncraft version: 0.7.3
+clock: 2.7 GHz
+cores per socket: 8
+cores per NUMA domain: 8
+NUMA domains per socket: 1
+model type: Intel Core SandyBridge EP processor
+model name: Intel(R) Xeon(R) CPU E5-2680 0 @ 2.70GHz
+sockets: 2
+threads per core: 2
+cacheline size: 64 B
+compiler:
+    !!omap
+    - icc: -O3 -xAVX -fno-alias -qopenmp
+    - clang: -O3 -march=corei7-avx -mtune=corei7-avx -D_POSIX_C_SOURCE=200112L -fopenmp
+    - gcc: -O3 -march=corei7-avx -D_POSIX_C_SOURCE=200112L -fopenmp
+micro-architecture: SNB
+FLOPs per cycle:
+    SP: {total: 16, ADD: 8, MUL: 8}
+    DP: {total: 8, ADD: 4, MUL: 4}
+overlapping model:
+    ports: ["0", "0DV", "1", "2", "3", "4", "5"]
+    performance counter metric:
+        Max(UOPS_DISPATCHED_PORT_PORT_0:PMC[0-3],
+            UOPS_DISPATCHED_PORT_PORT_1:PMC[0-3],
+            UOPS_DISPATCHED_PORT_PORT_4:PMC[0-3],
+            UOPS_DISPATCHED_PORT_PORT_5:PMC[0-3])
+non-overlapping model:
+    ports: ["2D", "3D"]
+    performance counter metric: T_OL + T_L1L2 + T_L2L3 + T_L3MEM
+write-allocate: True
+memory hierarchy:
+    - level: L1
+      cache per group: {
+         'sets': 64, 'ways': 8, 'cl_size': 64, # 32 kB
+         'replacement_policy': 'LRU',
+         'write_allocate': True, 'write_back': True,
+         'load_from': 'L2', 'store_to': 'L2'}
+      cores per group: 1
+      threads per group: 2
+      groups: 16
+      performance counter metrics:
+          accesses: MEM_UOPS_RETIRED_LOADS:PMC[0-3]
+          misses: L1D_REPLACEMENT:PMC[0-3]
+          evicts: L1D_M_EVICT:PMC[0-3]
+    - level: L2
+      cache per group: {
+         'sets': 512, 'ways': 8, 'cl_size': 64, # 256 kB
+         'replacement_policy': 'LRU',
+         'write_allocate': True, 'write_back': True,
+         'load_from': 'L3', 'store_to': 'L3'}
+      cores per group: 1
+      threads per group: 2
+      groups: 16
+      non-overlap upstream throughput: [32 B/cy, 'half-duplex']
+      performance counter metrics:
+          accesses: L1D_REPLACEMENT:PMC[0-3]
+          misses: L2_LINES_IN_ALL:PMC[0-3]
+          evicts: L2_TRANS_L2_WB:PMC[0-3]
+    - level: L3
+      cache per group: {
+         'sets': 20480, 'ways': 16, 'cl_size': 64, # 20 MB
+         'replacement_policy': 'LRU',
+         'write_allocate': True, 'write_back': True}
+      cores per group: 8
+      threads per group: 16
+      groups: 2
+      non-overlap upstream throughput: [32 B/cy, 'half-duplex']
+      performance counter metrics:
+          accesses: L2_LINES_IN_ALL:PMC[0-3]
+          misses: (CAS_COUNT_RD:MBOX0C[01] + CAS_COUNT_RD:MBOX1C[01] +
+                   CAS_COUNT_RD:MBOX2C[01] + CAS_COUNT_RD:MBOX3C[01])
+          evicts: (CAS_COUNT_WR:MBOX0C[01] + CAS_COUNT_WR:MBOX1C[01] +
+                   CAS_COUNT_WR:MBOX2C[01] + CAS_COUNT_WR:MBOX3C[01])
+    - level: MEM
+      cores per group: 8
+      non-overlap upstream throughput: ['full socket memory bandwidth', 'half-duplex']
+      size per group: null
+      threads per group: 16
+benchmarks:
+  kernels:
+    copy:
+      FLOPs per iteration: 0
+      read streams: {bytes: 8.00 B, streams: 1}
+      read+write streams: {bytes: 0.00 B, streams: 0}
+      write streams: {bytes: 8.00 B, streams: 1}
+    daxpy:
+      FLOPs per iteration: 2
+      read streams: {bytes: 16.00 B, streams: 2}
+      read+write streams: {bytes: 8.00 B, streams: 1}
+      write streams: {bytes: 8.00 B, streams: 1}
+    load:
+      FLOPs per iteration: 0
+      read streams: {bytes: 8.00 B, streams: 1}
+      read+write streams: {bytes: 0.00 B, streams: 0}
+      write streams: {bytes: 0.00 B, streams: 0}
+    triad:
+      FLOPs per iteration: 2
+      read streams: {bytes: 24.00 B, streams: 3}
+      read+write streams: {bytes: 0.00 B, streams: 0}
+      write streams: {bytes: 8.00 B, streams: 1}
+    update:
+      FLOPs per iteration: 0
+      read streams: {bytes: 8.00 B, streams: 1}
+      read+write streams: {bytes: 8.00 B, streams: 1}
+      write streams: {bytes: 8.00 B, streams: 1}
+  measurements:
+    L1:
+      1:
+        cores: [1, 2, 3, 4, 5, 6, 7, 8]
+        results:
+          copy: [81.98 GB/s, 163.75 GB/s, 245.62 GB/s, 327.69 GB/s, 409.41 GB/s, 489.83
+              GB/s, 571.67 GB/s, 653.50 GB/s]
+          daxpy: [71.55 GB/s, 143.01 GB/s, 214.86 GB/s, 286.26 GB/s, 355.60 GB/s,
+            426.71 GB/s, 497.45 GB/s, 568.97 GB/s]
+          load: [61.92 GB/s, 122.79 GB/s, 183.01 GB/s, 244.30 GB/s, 306.76 GB/s, 368.46
+              GB/s, 427.41 GB/s, 490.88 GB/s]
+          triad: [81.61 GB/s, 163.25 GB/s, 244.92 GB/s, 326.65 GB/s, 406.69 GB/s,
+            487.76 GB/s, 569.10 GB/s, 650.39 GB/s]
+          update: [84.03 GB/s, 168.02 GB/s, 252.10 GB/s, 335.94 GB/s, 419.90 GB/s,
+            503.88 GB/s, 587.86 GB/s, 671.88 GB/s]
+        size per core: [16.00 kB, 16.00 kB, 16.00 kB, 16.00 kB, 16.00 kB, 16.00 kB,
+          16.00 kB, 16.00 kB]
+        size per thread: [16.00 kB, 16.00 kB, 16.00 kB, 16.00 kB, 16.00 kB, 16.00
+            kB, 16.00 kB, 16.00 kB]
+        threads: [1, 2, 3, 4, 5, 6, 7, 8]
+        threads per core: 1
+        total size: [16.00 kB, 32.00 kB, 48.00 kB, 64.00 kB, 80.00 kB, 96.00 kB, 112.00
+            kB, 128.00 kB]
+      2:
+        cores: [1, 2, 3, 4, 5, 6, 7, 8]
+        results:
+          copy: [79.53 GB/s, 158.70 GB/s, 238.20 GB/s, 317.62 GB/s, 397.09 GB/s, 476.33
+              GB/s, 555.69 GB/s, 634.96 GB/s]
+          daxpy: [70.94 GB/s, 141.90 GB/s, 212.97 GB/s, 283.91 GB/s, 354.93 GB/s,
+            425.85 GB/s, 496.74 GB/s, 567.40 GB/s]
+          load: [57.01 GB/s, 114.11 GB/s, 171.11 GB/s, 228.13 GB/s, 285.15 GB/s, 342.11
+              GB/s, 399.11 GB/s, 456.11 GB/s]
+          triad: [79.48 GB/s, 159.03 GB/s, 238.53 GB/s, 318.04 GB/s, 392.11 GB/s,
+            477.10 GB/s, 538.36 GB/s, 636.02 GB/s]
+          update: [82.75 GB/s, 165.55 GB/s, 248.50 GB/s, 331.32 GB/s, 414.06 GB/s,
+            496.82 GB/s, 579.83 GB/s, 662.36 GB/s]
+        size per core: [16.00 kB, 16.00 kB, 16.00 kB, 16.00 kB, 16.00 kB, 16.00 kB,
+          16.00 kB, 16.00 kB]
+        size per thread: [8.00 kB, 8.00 kB, 8.00 kB, 8.00 kB, 8.00 kB, 8.00 kB, 8.00
+            kB, 8.00 kB]
+        threads: [2, 4, 6, 8, 10, 12, 14, 16]
+        threads per core: 2
+        total size: [16.00 kB, 32.00 kB, 48.00 kB, 64.00 kB, 80.00 kB, 96.00 kB, 112.00
+            kB, 128.00 kB]
+    L2:
+      1:
+        cores: [1, 2, 3, 4, 5, 6, 7, 8]
+        results:
+          copy: [41.28 GB/s, 81.96 GB/s, 120.28 GB/s, 160.70 GB/s, 203.22 GB/s, 239.97
+              GB/s, 271.13 GB/s, 307.01 GB/s]
+          daxpy: [48.85 GB/s, 98.62 GB/s, 143.29 GB/s, 197.76 GB/s, 230.58 GB/s, 284.98
+              GB/s, 334.22 GB/s, 385.72 GB/s]
+          load: [38.51 GB/s, 76.67 GB/s, 114.73 GB/s, 152.90 GB/s, 188.69 GB/s, 223.64
+              GB/s, 265.21 GB/s, 289.41 GB/s]
+          triad: [40.92 GB/s, 83.49 GB/s, 124.48 GB/s, 165.24 GB/s, 206.74 GB/s, 237.90
+              GB/s, 274.96 GB/s, 329.09 GB/s]
+          update: [50.37 GB/s, 100.05 GB/s, 145.43 GB/s, 196.82 GB/s, 244.07 GB/s,
+            301.62 GB/s, 336.88 GB/s, 403.78 GB/s]
+        size per core: [128.00 kB, 128.00 kB, 128.00 kB, 128.00 kB, 128.00 kB, 128.00
+            kB, 128.00 kB, 128.00 kB]
+        size per thread: [128.00 kB, 128.00 kB, 128.00 kB, 128.00 kB, 128.00 kB, 128.00
+            kB, 128.00 kB, 128.00 kB]
+        threads: [1, 2, 3, 4, 5, 6, 7, 8]
+        threads per core: 1
+        total size: [128.00 kB, 256.00 kB, 384.00 kB, 512.00 kB, 640.00 kB, 768.00
+            kB, 0.90 MB, 1.02 MB]
+      2:
+        cores: [1, 2, 3, 4, 5, 6, 7, 8]
+        results:
+          copy: [42.17 GB/s, 83.47 GB/s, 124.57 GB/s, 163.78 GB/s, 202.56 GB/s, 242.80
+              GB/s, 276.95 GB/s, 311.36 GB/s]
+          daxpy: [50.87 GB/s, 98.72 GB/s, 152.12 GB/s, 193.48 GB/s, 251.36 GB/s, 301.72
+              GB/s, 352.55 GB/s, 365.28 GB/s]
+          load: [39.62 GB/s, 79.03 GB/s, 118.03 GB/s, 157.85 GB/s, 196.48 GB/s, 237.44
+              GB/s, 276.81 GB/s, 309.71 GB/s]
+          triad: [44.80 GB/s, 88.35 GB/s, 125.13 GB/s, 169.94 GB/s, 209.60 GB/s, 260.15
+              GB/s, 300.75 GB/s, 333.08 GB/s]
+          update: [49.80 GB/s, 100.70 GB/s, 150.56 GB/s, 196.44 GB/s, 251.90 GB/s,
+            280.93 GB/s, 352.74 GB/s, 399.27 GB/s]
+        size per core: [128.00 kB, 128.00 kB, 128.00 kB, 128.00 kB, 128.00 kB, 128.00
+            kB, 128.00 kB, 128.00 kB]
+        size per thread: [64.00 kB, 64.00 kB, 64.00 kB, 64.00 kB, 64.00 kB, 64.00
+            kB, 64.00 kB, 64.00 kB]
+        threads: [2, 4, 6, 8, 10, 12, 14, 16]
+        threads per core: 2
+        total size: [128.00 kB, 256.00 kB, 384.00 kB, 512.00 kB, 640.00 kB, 768.00
+            kB, 0.90 MB, 1.02 MB]
+    L3:
+      1:
+        cores: [1, 2, 3, 4, 5, 6, 7, 8]
+        results:
+          copy: [23.21 GB/s, 46.01 GB/s, 67.96 GB/s, 90.17 GB/s, 111.47 GB/s, 133.14
+              GB/s, 153.84 GB/s, 174.92 GB/s]
+          daxpy: [30.35 GB/s, 60.32 GB/s, 90.00 GB/s, 119.71 GB/s, 148.87 GB/s, 178.39
+              GB/s, 207.10 GB/s, 236.25 GB/s]
+          load: [23.35 GB/s, 46.52 GB/s, 69.57 GB/s, 92.60 GB/s, 115.77 GB/s, 138.89
+              GB/s, 161.82 GB/s, 184.11 GB/s]
+          triad: [25.18 GB/s, 50.08 GB/s, 74.33 GB/s, 98.78 GB/s, 122.66 GB/s, 146.78
+              GB/s, 170.52 GB/s, 194.47 GB/s]
+          update: [32.67 GB/s, 64.65 GB/s, 95.98 GB/s, 127.29 GB/s, 157.67 GB/s, 188.22
+              GB/s, 217.41 GB/s, 246.99 GB/s]
+        size per core: [1.25 MB, 1.25 MB, 1.25 MB, 1.25 MB, 1.25 MB, 1.25 MB, 1.25
+            MB, 1.25 MB]
+        size per thread: [1.25 MB, 1.25 MB, 1.25 MB, 1.25 MB, 1.25 MB, 1.25 MB, 1.25
+            MB, 1.25 MB]
+        threads: [1, 2, 3, 4, 5, 6, 7, 8]
+        threads per core: 1
+        total size: [1.25 MB, 2.50 MB, 3.75 MB, 5.00 MB, 6.25 MB, 7.50 MB, 8.75 MB,
+          10.00 MB]
+      2:
+        cores: [1, 2, 3, 4, 5, 6, 7, 8]
+        results:
+          copy: [23.83 GB/s, 47.25 GB/s, 69.84 GB/s, 92.61 GB/s, 114.31 GB/s, 136.48
+              GB/s, 157.55 GB/s, 178.99 GB/s]
+          daxpy: [31.52 GB/s, 62.72 GB/s, 93.43 GB/s, 124.29 GB/s, 154.55 GB/s, 185.18
+              GB/s, 215.10 GB/s, 245.24 GB/s]
+          load: [27.63 GB/s, 54.93 GB/s, 81.57 GB/s, 108.63 GB/s, 134.91 GB/s, 161.72
+              GB/s, 188.15 GB/s, 214.94 GB/s]
+          triad: [25.90 GB/s, 51.76 GB/s, 76.73 GB/s, 102.29 GB/s, 126.17 GB/s, 152.10
+              GB/s, 176.71 GB/s, 200.64 GB/s]
+          update: [34.10 GB/s, 67.67 GB/s, 100.62 GB/s, 133.50 GB/s, 165.61 GB/s,
+            197.74 GB/s, 228.73 GB/s, 259.05 GB/s]
+        size per core: [1.25 MB, 1.25 MB, 1.25 MB, 1.25 MB, 1.25 MB, 1.25 MB, 1.25
+            MB, 1.25 MB]
+        size per thread: [625.00 kB, 625.00 kB, 625.00 kB, 625.00 kB, 625.00 kB, 625.00
+            kB, 625.00 kB, 625.00 kB]
+        threads: [2, 4, 6, 8, 10, 12, 14, 16]
+        threads per core: 2
+        total size: [1.25 MB, 2.50 MB, 3.75 MB, 5.00 MB, 6.25 MB, 7.50 MB, 8.75 MB,
+          10.00 MB]
+    MEM:
+      1:
+        cores: [1, 2, 3, 4, 5, 6, 7, 8]
+        results:
+          copy: [11.60 GB/s, 21.29 GB/s, 25.94 GB/s, 27.28 GB/s, 27.47 GB/s, 27.36
+              GB/s, 27.21 GB/s, 27.12 GB/s]
+          daxpy: [17.33 GB/s, 31.89 GB/s, 38.65 GB/s, 40.50 GB/s, 40.81 GB/s, 40.62
+              GB/s, 40.59 GB/s, 40.26 GB/s]
+          load: [12.01 GB/s, 23.04 GB/s, 32.79 GB/s, 40.21 GB/s, 43.39 GB/s, 44.14
+              GB/s, 44.42 GB/s, 44.40 GB/s]
+          triad: [12.73 GB/s, 24.27 GB/s, 30.43 GB/s, 31.46 GB/s, 31.77 GB/s, 31.74
+              GB/s, 31.65 GB/s, 31.52 GB/s]
+          update: [18.91 GB/s, 32.43 GB/s, 37.28 GB/s, 39.98 GB/s, 40.99 GB/s, 40.92
+              GB/s, 40.61 GB/s, 40.34 GB/s]
+        size per core: [40.00 MB, 20.00 MB, 13.33 MB, 10.00 MB, 8.00 MB, 6.67 MB,
+          5.71 MB, 5.00 MB]
+        size per thread: [40.00 MB, 20.00 MB, 13.33 MB, 10.00 MB, 8.00 MB, 6.67 MB,
+          5.71 MB, 5.00 MB]
+        threads: [1, 2, 3, 4, 5, 6, 7, 8]
+        threads per core: 1
+        total size: [40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB]
+      2:
+        cores: [1, 2, 3, 4, 5, 6, 7, 8]
+        results:
+          copy: [10.92 GB/s, 20.62 GB/s, 25.34 GB/s, 26.22 GB/s, 26.32 GB/s, 26.31
+              GB/s, 26.22 GB/s, 26.16 GB/s]
+          daxpy: [17.15 GB/s, 31.96 GB/s, 38.12 GB/s, 39.19 GB/s, 39.38 GB/s, 39.16
+              GB/s, 39.06 GB/s, 38.87 GB/s]
+          load: [13.49 GB/s, 25.92 GB/s, 36.16 GB/s, 41.56 GB/s, 43.34 GB/s, 43.40
+              GB/s, 43.01 GB/s, 42.66 GB/s]
+          triad: [12.38 GB/s, 23.17 GB/s, 28.69 GB/s, 29.98 GB/s, 30.50 GB/s, 30.59
+              GB/s, 30.75 GB/s, 30.70 GB/s]
+          update: [19.67 GB/s, 34.93 GB/s, 39.93 GB/s, 40.79 GB/s, 40.43 GB/s, 40.03
+              GB/s, 39.62 GB/s, 39.33 GB/s]
+        size per core: [40.00 MB, 20.00 MB, 13.33 MB, 10.00 MB, 8.00 MB, 6.67 MB,
+          5.71 MB, 5.00 MB]
+        size per thread: [20.00 MB, 10.00 MB, 6.67 MB, 5.00 MB, 4.00 MB, 3.33 MB,
+          2.86 MB, 2.50 MB]
+        threads: [2, 4, 6, 8, 10, 12, 14, 16]
+        threads per core: 2
+        total size: [40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB, 40.00 MB]
+
diff --git a/pystencils_tests/test_aligned_array.py b/pystencils_tests/test_aligned_array.py
new file mode 100644
index 0000000000000000000000000000000000000000..f22c7682fc617aca95926c3240bca79b033f0942
--- /dev/null
+++ b/pystencils_tests/test_aligned_array.py
@@ -0,0 +1,69 @@
+from pystencils import create_data_handling
+from pystencils.alignedarray import *
+from pystencils.field import create_numpy_array_with_layout
+
+
+def is_aligned(arr, alignment, byte_offset=0):
+    address = arr.__array_interface__['data'][0]
+    rest = (address + byte_offset) % alignment
+    if rest:
+        print("Alignment rest", rest)
+    return rest == 0
+
+
+def test_1d_arrays():
+    for alignment in [8, 8*4]:
+        for shape in [17, 16, (16, 16), (17, 17), (18, 18), (19, 19)]:
+            arrays = [
+                aligned_zeros(shape, alignment),
+                aligned_ones(shape, alignment),
+                aligned_empty(shape, alignment),
+            ]
+            for arr in arrays:
+                assert is_aligned(arr, alignment)
+
+
+def test_3d_arrays():
+    for order in ('C', 'F'):
+        for alignment in [8, 8*4]:
+            for shape in [(16, 16), (17, 17), (18, 18), (19, 19)]:
+                arrays = [
+                    aligned_zeros(shape, alignment, order=order),
+                    aligned_ones(shape, alignment, order=order),
+                    aligned_empty(shape, alignment, order=order),
+                ]
+                for arr in arrays:
+                    assert is_aligned(arr, alignment)
+                    if order == 'C':
+                        assert is_aligned(arr[1], alignment)
+                        assert is_aligned(arr[5], alignment)
+                    else:
+                        assert is_aligned(arr[..., 1], alignment)
+                        assert is_aligned(arr[..., 5], alignment)
+
+
+def test_data_handling():
+    for parallel in (False, True):
+        for tries in range(16):  # try a few times, since we might get lucky and get randomly a correct alignment
+            dh = create_data_handling((6, 7), default_ghost_layers=1, parallel=parallel)
+            dh.add_array('test', alignment=8 * 4)
+            for b in dh.iterate(ghost_layers=True, inner_ghost_layers=True):
+                arr = b['test']
+                assert is_aligned(arr[1:, 3:], 8*4)
+
+
+def test_alignment_of_different_layouts():
+    offset = 1
+    byte_offset = 8
+    for tries in range(16):  # try a few times, since we might get lucky and get randomly a correct alignment
+        arr = create_numpy_array_with_layout((3, 4, 5), layout=(0, 1, 2),
+                                             alignment=True, byte_offset=byte_offset)
+        assert is_aligned(arr[offset, ...], 8*4, byte_offset)
+
+        arr = create_numpy_array_with_layout((3, 4, 5), layout=(2, 1, 0),
+                                             alignment=True, byte_offset=byte_offset)
+        assert is_aligned(arr[..., offset], 8*4, byte_offset)
+
+        arr = create_numpy_array_with_layout((3, 4, 5), layout=(2, 0, 1),
+                                             alignment=True, byte_offset=byte_offset)
+        assert is_aligned(arr[:, 0, :], 8*4, byte_offset)
diff --git a/pystencils_tests/test_assignment_collection.py b/pystencils_tests/test_assignment_collection.py
new file mode 100644
index 0000000000000000000000000000000000000000..4bf27b22e9a2a6ff7dc6f7944841bf61e8679542
--- /dev/null
+++ b/pystencils_tests/test_assignment_collection.py
@@ -0,0 +1,28 @@
+import sympy as sp
+from pystencils import Assignment, AssignmentCollection
+from pystencils.simp.assignment_collection import SymbolGen
+
+
+def test_assignment_collection():
+    x, y, z, t = sp.symbols("x y z t")
+    symbol_gen = SymbolGen("a")
+
+    ac = AssignmentCollection([Assignment(z, x + y)],
+                              [], subexpression_symbol_generator=symbol_gen)
+
+    lhs = ac.add_subexpression(t)
+    assert lhs == sp.Symbol("a_0")
+    ac.subexpressions.append(Assignment(t, 3))
+    ac.topological_sort(sort_main_assignments=False, sort_subexpressions=True)
+    assert ac.subexpressions[0].lhs == t
+
+    assert ac.new_with_inserted_subexpression(sp.Symbol("not_defined")) == ac
+    ac_inserted = ac.new_with_inserted_subexpression(t)
+    ac_inserted2 = ac.new_without_subexpressions({lhs})
+    assert all(a == b for a, b in zip(ac_inserted.all_assignments, ac_inserted2.all_assignments))
+
+    print(ac_inserted)
+    assert ac_inserted.subexpressions[0] == Assignment(lhs, 3)
+
+    assert 'a_0' in str(ac_inserted)
+    assert '<table' in ac_inserted._repr_html_()
diff --git a/pystencils_tests/test_assignment_collection_dict_conversion.py b/pystencils_tests/test_assignment_collection_dict_conversion.py
new file mode 100644
index 0000000000000000000000000000000000000000..651e0a21275c25d6af54db918ecb33397dd1d898
--- /dev/null
+++ b/pystencils_tests/test_assignment_collection_dict_conversion.py
@@ -0,0 +1,40 @@
+import pystencils
+
+
+def test_assignment_collection_dict_conversion():
+    x, y = pystencils.fields('x,y: [2D]')
+
+    collection_normal = pystencils.AssignmentCollection(
+        [pystencils.Assignment(x.center(), y[1, 0] + y[0, 0])],
+        []
+    )
+    collection_dict = pystencils.AssignmentCollection(
+        {x.center(): y[1, 0] + y[0, 0]},
+        {}
+    )
+    assert str(collection_normal) == str(collection_dict)
+    assert collection_dict.main_assignments_dict == {x.center(): y[1, 0] + y[0, 0]}
+    assert collection_dict.subexpressions_dict == {}
+
+    collection_normal = pystencils.AssignmentCollection(
+        [pystencils.Assignment(y[1, 0], x.center()),
+         pystencils.Assignment(y[0, 0], x.center())],
+        []
+    )
+    collection_dict = pystencils.AssignmentCollection(
+        {y[1, 0]: x.center(),
+         y[0, 0]: x.center()},
+        {}
+    )
+    assert str(collection_normal) == str(collection_dict)
+    assert collection_dict.main_assignments_dict == {y[1, 0]: x.center(),
+                                                     y[0, 0]: x.center()}
+    assert collection_dict.subexpressions_dict == {}
+
+
+def main():
+    test_assignment_collection_dict_conversion()
+
+
+if __name__ == '__main__':
+    main()
diff --git a/pystencils_tests/test_assignment_from_stencil.py b/pystencils_tests/test_assignment_from_stencil.py
new file mode 100644
index 0000000000000000000000000000000000000000..b3b193f8e1966e963dbf8d3815e98cfebb641e2d
--- /dev/null
+++ b/pystencils_tests/test_assignment_from_stencil.py
@@ -0,0 +1,20 @@
+import pystencils
+import numpy as np
+
+
+def test_assignment_from_stencil():
+
+    stencil = [
+        [0, 0, 4, 1, 0, 0, 0],
+        [0, 0, 0, 2, 0, 0, 0],
+        [0, 0, 0, 3, 0, 0, 0]
+    ]
+
+    x, y = pystencils.fields('x, y: [2D]')
+
+    assignment = pystencils.assignment.assignment_from_stencil(stencil, x, y)
+    assert isinstance(assignment, pystencils.Assignment)
+    assert assignment.rhs == x[0, 1] + 4 * x[-1, 1] + 2 * x[0, 0] + 3 * x[0, -1]
+
+    assignment = pystencils.assignment.assignment_from_stencil(stencil, x, y, normalization_factor=1 / np.sum(stencil))
+    assert isinstance(assignment, pystencils.Assignment)
diff --git a/pystencils_tests/test_basic_usage_llvm.ipynb b/pystencils_tests/test_basic_usage_llvm.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..30ba23683d4253135603382679dec5c4a511f25c
--- /dev/null
+++ b/pystencils_tests/test_basic_usage_llvm.ipynb
@@ -0,0 +1,398 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# pystencils - LLVM generation\n",
+    "The generation of LLVM code is simliar but not identical as seen with the C++ version. For the generation itself a python module ``llvmlite`` is used. This module provides the necessary support and bindings for LLVM. In order to generate from the AST to llvm, the AST needs to be transformed to support type conversions. This is the biggest difference to the C++ version. C++ doesn't need that since the language itself handles the casts.\n",
+    "\n",
+    "In this example a simple weighted Jacobi kernel is generated, so the focus remains on the part of LLVM generation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sympy as sp\n",
+    "import numpy as np\n",
+    "import ctypes\n",
+    "from pystencils import Field, Assignment\n",
+    "from pystencils import create_kernel\n",
+    "from pystencils.display_utils import to_dot\n",
+    "\n",
+    "sp.init_printing()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The numpy arrays (with inital values) create *Field*s for the update Rule. Later those arrays are used for the computation itself."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "src_arr = np.zeros((30, 20))\n",
+    "src_arr[0,:] = 1.0\n",
+    "src_arr[:,0] = 1.0\n",
+    "dst_arr = src_arr.copy()\n",
+    "\n",
+    "src_field = Field.create_from_numpy_array('src', src_arr)\n",
+    "dst_field = Field.create_from_numpy_array('dst', dst_arr)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Using the *Field* objects and the additional *Symbol* $\\omega$ for the weight the update rule is specified as a *sympy* equation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "                            ω⋅(src_E + src_N + src_S + src_W)\n",
+       "dst_C := src_C⋅(-ω + 1.0) + ─────────────────────────────────\n",
+       "                                            4                "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "omega = sp.symbols(\"omega\")\n",
+    "update_rule = Assignment(dst_field[0,0], omega * (src_field[0,1] + src_field[0,-1] + src_field[1,0] + src_field[-1,0]) / 4\n",
+    "                   + (1.-omega)*src_field[0,0])\n",
+    "update_rule"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "With this update rule an abstract syntax tree (AST) can be created. This AST can be used to print the LLVM code. The creation follows the same routines as the C++ version does. However at the end there are two more steps. In order to generate LLVM, type casting and pointer arithmetic had to be introduced (which C++ does for you)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "KernelFunction kernel([<double * RESTRICT fd_dst>, <double * RESTRICT const fd_src>, <double omega>])\n",
+      "\tBlock for(ctr_0=1; ctr_0<29; ctr_0+=1)\n",
+      "\t\tBlock fd_dst_C ← pointer_arithmetic_func(fd_dst, 20*ctr_0)\n",
+      "\t\tfd_src_C ← pointer_arithmetic_func(fd_src, 20*ctr_0)\n",
+      "\t\tfd_src_E ← pointer_arithmetic_func(fd_src, 20*ctr_0 + 20)\n",
+      "\t\tfd_src_W ← pointer_arithmetic_func(fd_src, 20*ctr_0 - 20)\n",
+      "\t\tfor(ctr_1=1; ctr_1<19; ctr_1+=1)\n",
+      "\t\t\tBlock fd_dst_C[ctr_1] ← omega*(fd_src_C[ctr_1 + 1] + fd_src_C[ctr_1 - 1] + fd_src_E[ctr_1] + fd_src_W[ctr_1])/4 + (omega*cast_func(-1, double) + 1.0)*fd_src_C[ctr_1]\n",
+      "\t\t\n",
+      "\t\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "ast = create_kernel([update_rule], target='llvm')\n",
+    "print(str(ast))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is possible to examine the AST further."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
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+       "<polygon fill=\"black\" stroke=\"black\" points=\"253.396,-334.104 249.896,-324.104 246.396,-334.104 253.396,-334.104\"/>\n",
+       "</g>\n",
+       "</g>\n",
+       "</svg>\n"
+      ],
+      "text/plain": [
+       "<graphviz.files.Source at 0x7f2d14f276a0>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "to_dot(ast)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "With transformed AST it is now possible to generate and compile the AST into LLVM. Notice that unlike in C++ version, no files are writen to the hard drive (although it is possible).\n",
+    "\n",
+    "There are multiple ways how to generate and compile the AST. The most simple one is simillar to the C++ version. Using the ``compile()`` function of the generated AST\n",
+    "\n",
+    "You can also manually create a python function with ``make_python_function``.\n",
+    "\n",
+    "Another option is obtaining the jit itself with ``generate_and_jit``.\n",
+    "The function ``generate_and_jit`` first generates and the compiles the AST.\n",
+    "\n",
+    "If even more controll is needed, it is possible to use the functions ``generateLLVM`` and ``compileLLVM`` to achieve the same. For further controll, instead of calling ``compileLLVM`` the jit object itself can be created and its necessary functions for the compilation have to be run manually (``parse``, (``optimize``,) ``compile``)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "kernel = ast.compile()\n",
+    "\n",
+    "#kernel = make_python_function(ast)\n",
+    "\n",
+    "# Or alternativally\n",
+    "#jit = generate_and_jit(ast)\n",
+    "# Call: jit('kernel', src_arr, dst_arr)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The compiled function(s) can be used now. Either call the function (with arguments, if not given before) or call the jit object with the function's name and its arguments. Here, numpy arrays are automatically adjusted with ctypes.\n",
+    "\n",
+    "The functions and arguments can be read as well.\n",
+    "\n",
+    "**All of the information the jit object has comes from the module which was parsed. If you parse a second module and don't run the compilation step, the module and the compiled code are not the same anymore, thus leading to false information**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#jit.print_functions()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "for i in range(100):\n",
+    "    kernel(src=src_arr, dst=dst_arr, omega=2/3)\n",
+    "    src_arr, dst_arr = dst_arr, src_arr\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The output is drawn with matplotlib."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "from matplotlib import cm\n",
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "ax.imshow(dst_arr, cmap=cm.jet)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/pystencils_tests/test_blocking.py b/pystencils_tests/test_blocking.py
new file mode 100644
index 0000000000000000000000000000000000000000..cc5ca78cbe658b96a69e0168137eb6083719a747
--- /dev/null
+++ b/pystencils_tests/test_blocking.py
@@ -0,0 +1,61 @@
+import sympy as sp
+import numpy as np
+import pystencils as ps
+
+
+def jacobi(dst, src):
+    assert dst.spatial_dimensions == src.spatial_dimensions
+    assert src.index_dimensions == 0 and dst.index_dimensions == 0
+    neighbors = []
+    for d in range(src.spatial_dimensions):
+        neighbors += [src.neighbor(d, offset) for offset in (1, -1)]
+    return ps.Assignment(dst.center, sp.Add(*neighbors) / len(neighbors))
+
+
+def check_equivalence(assignments, src_arr):
+    for openmp in (False, True):
+        for vectorization in (True, False):
+            with_blocking = ps.create_kernel(assignments, cpu_blocking=(8, 16, 4), cpu_openmp=openmp,
+                                             cpu_vectorize_info=vectorization).compile()
+            without_blocking = ps.create_kernel(assignments).compile()
+            print("  openmp {}, vectorization {}".format(openmp, vectorization))
+            dst_arr = np.zeros_like(src_arr)
+            ref_arr = np.zeros_like(src_arr)
+            np.copyto(src_arr, np.random.rand(*src_arr.shape))
+            with_blocking(src=src_arr, dst=dst_arr)
+            without_blocking(src=src_arr, dst=ref_arr)
+            np.testing.assert_almost_equal(ref_arr, dst_arr)
+
+
+def test_jacobi3d_var_size():
+    src, dst = ps.fields("src, dst: double[3D]")
+
+    print("Var Size: Smaller than block sizes")
+    arr = np.empty([4, 5, 6])
+    check_equivalence(jacobi(dst, src), arr)
+
+    print("Var Size: Large non divisible sizes")
+    arr = np.empty([100, 80, 9])
+    check_equivalence(jacobi(dst, src), arr)
+
+    print("Var Size: Multiples of block sizes")
+    arr = np.empty([8*4, 16*2, 4*3])
+    check_equivalence(jacobi(dst, src), arr)
+
+
+def test_jacobi3d_fixed_size():
+    print("Fixed Size: Large non divisible sizes")
+    arr = np.empty([10, 10, 9])
+    src, dst = ps.fields("src, dst: double[3D]", src=arr, dst=arr)
+    check_equivalence(jacobi(dst, src), arr)
+
+    print("Fixed Size: Smaller than block sizes")
+    arr = np.empty([4, 5, 6])
+    src, dst = ps.fields("src, dst: double[3D]", src=arr, dst=arr)
+    check_equivalence(jacobi(dst, src), arr)
+
+    print("Fixed Size: Multiples of block sizes")
+    arr = np.empty([8*4, 16*2, 4*3])
+    src, dst = ps.fields("src, dst: double[3D]", src=arr, dst=arr)
+    check_equivalence(jacobi(dst, src), arr)
+
diff --git a/pystencils_tests/test_blocking_staggered.py b/pystencils_tests/test_blocking_staggered.py
new file mode 100644
index 0000000000000000000000000000000000000000..d32e601736721f4a4be4cb69da582672fa3e22c1
--- /dev/null
+++ b/pystencils_tests/test_blocking_staggered.py
@@ -0,0 +1,21 @@
+import numpy as np
+import pystencils as ps
+
+
+def test_blocking_staggered():
+    f, stag = ps.fields("f, stag(3): double[3D]")
+    terms = [
+       f[0, 0, 0] - f[-1, 0, 0],
+       f[0, 0, 0] - f[0, -1, 0],
+       f[0, 0, 0] - f[0, 0, -1],
+    ]
+    kernel = ps.create_staggered_kernel(stag, terms, cpu_blocking=(3, 16, 8)).compile()
+    reference_kernel = ps.create_staggered_kernel(stag, terms).compile()
+    print(ps.show_code(kernel.ast))
+
+    f_arr = np.random.rand(80, 33, 19)
+    stag_arr = np.zeros((80, 33, 19, 3))
+    stag_ref = np.zeros((80, 33, 19, 3))
+    kernel(f=f_arr, stag=stag_arr)
+    reference_kernel(f=f_arr, stag=stag_ref)
+    np.testing.assert_almost_equal(stag_arr, stag_ref)
diff --git a/pystencils_tests/test_boundary.py b/pystencils_tests/test_boundary.py
new file mode 100644
index 0000000000000000000000000000000000000000..6aaf4e696bd27766ae0fc06186fa6521e6d9a8e7
--- /dev/null
+++ b/pystencils_tests/test_boundary.py
@@ -0,0 +1,86 @@
+from tempfile import TemporaryDirectory
+import os
+import numpy as np
+
+from pystencils import create_kernel, Assignment
+from pystencils.boundaries import add_neumann_boundary, Neumann, BoundaryHandling
+from pystencils.datahandling import SerialDataHandling
+from pystencils.slicing import slice_from_direction
+
+
+def test_kernel_vs_copy_boundary():
+    dh = SerialDataHandling(domain_size=(7, 7))
+    src = dh.add_array('src')
+    dst_builtin = dh.add_array_like('dst_builtin', 'src')
+    dst_python_copy = dh.add_array_like('dst_python_copy', 'src')
+    dst_handling = dh.add_array_like('dst_handling', 'src')
+
+    src_arr = np.arange(dh.shape[0] * dh.shape[1]).reshape(dh.shape)
+
+    def reset_src():
+        for block in dh.iterate(ghost_layers=True, inner_ghost_layers=True):
+            np.copyto(block['src'], np.random.rand(*block.shape))
+
+        for block in dh.iterate(ghost_layers=False, inner_ghost_layers=True):
+            np.copyto(block['src'], src_arr)
+
+    for b in dh.iterate(ghost_layers=False, inner_ghost_layers=True):
+        np.copyto(b['dst_builtin'], 42)
+        np.copyto(b['dst_python_copy'], 43)
+        np.copyto(b['dst_handling'], 44)
+
+    flags = dh.add_array('flags', dtype=np.uint8)
+    dh.fill(flags.name, 0)
+    borders = ['N', 'S', 'E', 'W']
+    for d in borders:
+        dh.fill(flags.name, 1, slice_obj=slice_from_direction(d, dim=2), ghost_layers=True, inner_ghost_layers=True)
+
+    rhs = sum(src.neighbors([(1, 0), (-1, 0), (0, 1), (0, -1)]))
+
+    simple_kernel = create_kernel([Assignment(dst_python_copy.center, rhs)]).compile()
+    kernel_handling = create_kernel([Assignment(dst_handling.center, rhs)]).compile()
+
+    assignments_with_boundary = add_neumann_boundary([Assignment(dst_builtin.center, rhs)],
+                                                     fields=[src], flag_field=flags, boundary_flag=1)
+    kernel_with_boundary = create_kernel(assignments_with_boundary).compile()
+
+    # ------ Method 1: Built-in boundary
+    reset_src()
+    dh.run_kernel(kernel_with_boundary)
+
+    # ------ Method 2: Using python to copy out the values (reference)
+    reset_src()
+    for b in dh.iterate():
+        arr = b['src']
+        arr[:, 0] = arr[:, 1]
+        arr[:, -1] = arr[:, -2]
+        arr[0, :] = arr[1, :]
+        arr[-1, :] = arr[-2, :]
+    dh.run_kernel(simple_kernel)
+
+    # ------ Method 3: Using boundary handling to copy out the values
+    reset_src()
+    boundary_stencil = [(1, 0), (-1, 0), (0, 1), (0, -1)]
+    boundary_handling = BoundaryHandling(dh, src.name, boundary_stencil)
+    neumann = Neumann()
+    assert neumann.name == 'Neumann'
+    neumann.name = "wall"
+    assert neumann.name == 'wall'
+    assert neumann.additional_data_init_callback is None
+    assert len(neumann.additional_data) == 0
+
+    for d in ('N', 'S', 'W', 'E'):
+        boundary_handling.set_boundary(neumann, slice_from_direction(d, dim=2))
+    boundary_handling()
+    dh.run_kernel(kernel_handling)
+
+    python_copy_result = dh.gather_array('dst_python_copy')
+    builtin_result = dh.gather_array('dst_builtin')
+    handling_result = dh.gather_array('dst_handling')
+
+    np.testing.assert_almost_equal(python_copy_result, builtin_result)
+    np.testing.assert_almost_equal(python_copy_result, handling_result)
+
+    with TemporaryDirectory() as tmp_dir:
+        boundary_handling.geometry_to_vtk(file_name=os.path.join(tmp_dir, 'test_output1'), ghost_layers=False)
+        boundary_handling.geometry_to_vtk(file_name=os.path.join(tmp_dir, 'test_output2'), ghost_layers=True)
diff --git a/pystencils_tests/test_buffer.py b/pystencils_tests/test_buffer.py
new file mode 100644
index 0000000000000000000000000000000000000000..238448c80187585bfca1ce9cd31021dc6b27856b
--- /dev/null
+++ b/pystencils_tests/test_buffer.py
@@ -0,0 +1,187 @@
+"""Tests  (un)packing (from)to buffers."""
+
+import numpy as np
+from pystencils import Field, FieldType, Assignment, create_kernel
+from pystencils.field import layout_string_to_tuple, create_numpy_array_with_layout
+from pystencils.stencils import direction_string_to_offset
+from pystencils.slicing import add_ghost_layers, get_slice_before_ghost_layer, get_ghost_region_slice
+
+
+FIELD_SIZES = [(32, 10), (10, 8, 6)]
+
+
+def _generate_fields(dt=np.uint64, num_directions=1, layout='numpy'):
+    field_sizes = FIELD_SIZES
+    if num_directions > 1:
+        field_sizes = [s + (num_directions,) for s in field_sizes]
+
+    fields = []
+    for size in field_sizes:
+        field_layout = layout_string_to_tuple(layout, len(size))
+        src_arr = create_numpy_array_with_layout(size, field_layout)
+
+        array_data = np.reshape(np.arange(1, int(np.prod(size)+1)), size)
+        # Use flat iterator to input data into the array
+        src_arr.flat = add_ghost_layers(array_data, index_dimensions=1 if num_directions > 1 else 0).astype(dt).flat
+        dst_arr = np.zeros(src_arr.shape, dtype=dt)
+        buffer_arr = np.zeros(np.prod(src_arr.shape), dtype=dt)
+        fields.append((src_arr, dst_arr, buffer_arr))
+    return fields
+
+
+def test_full_scalar_field():
+    """Tests fully (un)packing a scalar field (from)to a buffer."""
+    fields = _generate_fields()
+    for (src_arr, dst_arr, buffer_arr) in fields:
+        src_field = Field.create_from_numpy_array("src_field", src_arr)
+        dst_field = Field.create_from_numpy_array("dst_field", dst_arr)
+        buffer = Field.create_generic("buffer", spatial_dimensions=1,
+                                      field_type=FieldType.BUFFER, dtype=src_arr.dtype)
+
+        pack_eqs = [Assignment(buffer.center(), src_field.center())]
+        pack_code = create_kernel(pack_eqs, data_type={'src_field': src_arr.dtype, 'buffer': buffer.dtype})
+
+        pack_kernel = pack_code.compile()
+        pack_kernel(buffer=buffer_arr, src_field=src_arr)
+
+        unpack_eqs = [Assignment(dst_field.center(), buffer.center())]
+        unpack_code = create_kernel(unpack_eqs, data_type={'dst_field': dst_arr.dtype, 'buffer': buffer.dtype})
+
+        unpack_kernel = unpack_code.compile()
+        unpack_kernel(dst_field=dst_arr, buffer=buffer_arr)
+
+        np.testing.assert_equal(src_arr, dst_arr)
+
+
+def test_field_slice():
+    """Tests (un)packing slices of a scalar field (from)to a buffer."""
+    fields = _generate_fields()
+    for d in ['N', 'S', 'NW', 'SW', 'TNW', 'B']:
+        for (src_arr, dst_arr, bufferArr) in fields:
+            # Extract slice from N direction of the field
+            slice_dir = direction_string_to_offset(d, dim=len(src_arr.shape))
+            pack_slice = get_slice_before_ghost_layer(slice_dir)
+            unpack_slice = get_ghost_region_slice(slice_dir)
+
+            src_field = Field.create_from_numpy_array("src_field", src_arr[pack_slice])
+            dst_field = Field.create_from_numpy_array("dst_field", dst_arr[unpack_slice])
+            buffer = Field.create_generic("buffer", spatial_dimensions=1,
+                                          field_type=FieldType.BUFFER, dtype=src_arr.dtype)
+
+            pack_eqs = [Assignment(buffer.center(), src_field.center())]
+            pack_code = create_kernel(pack_eqs, data_type={'src_field': src_arr.dtype, 'buffer': buffer.dtype})
+
+            pack_kernel = pack_code.compile()
+            pack_kernel(buffer=bufferArr, src_field=src_arr[pack_slice])
+
+            # Unpack into ghost layer of dst_field in N direction
+            unpack_eqs = [Assignment(dst_field.center(), buffer.center())]
+            unpack_code = create_kernel(unpack_eqs, data_type={'dst_field': dst_arr.dtype, 'buffer': buffer.dtype})
+
+            unpack_kernel = unpack_code.compile()
+            unpack_kernel(buffer=bufferArr, dst_field=dst_arr[unpack_slice])
+
+            np.testing.assert_equal(src_arr[pack_slice], dst_arr[unpack_slice])
+
+
+def test_all_cell_values():
+    """Tests (un)packing all cell values of the a field (from)to a buffer."""
+    num_cell_values = 19
+    fields = _generate_fields(num_directions=num_cell_values)
+    for (src_arr, dst_arr, bufferArr) in fields:
+        src_field = Field.create_from_numpy_array("src_field", src_arr, index_dimensions=1)
+        dst_field = Field.create_from_numpy_array("dst_field", dst_arr, index_dimensions=1)
+        buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
+                                      field_type=FieldType.BUFFER, dtype=src_arr.dtype)
+
+        pack_eqs = []
+        # Since we are packing all cell values for all cells, then
+        # the buffer index is equivalent to the field index
+        for idx in range(num_cell_values):
+            eq = Assignment(buffer(idx), src_field(idx))
+            pack_eqs.append(eq)
+
+        pack_code = create_kernel(pack_eqs, data_type={'src_field': src_arr.dtype, 'buffer': buffer.dtype})
+        pack_kernel = pack_code.compile()
+        pack_kernel(buffer=bufferArr, src_field=src_arr)
+
+        unpack_eqs = []
+
+        for idx in range(num_cell_values):
+            eq = Assignment(dst_field(idx), buffer(idx))
+            unpack_eqs.append(eq)
+
+        unpack_code = create_kernel(unpack_eqs, data_type={'dst_field': dst_arr.dtype, 'buffer': buffer.dtype})
+        unpack_kernel = unpack_code.compile()
+        unpack_kernel(buffer=bufferArr, dst_field=dst_arr)
+
+        np.testing.assert_equal(src_arr, dst_arr)
+
+
+def test_subset_cell_values():
+    """Tests (un)packing a subset of cell values of the a field (from)to a buffer."""
+    num_cell_values = 19
+    # Cell indices of the field to be (un)packed (from)to the buffer
+    cell_indices = [1, 5, 7, 8, 10, 12, 13]
+    fields = _generate_fields(num_directions=num_cell_values)
+    for (src_arr, dst_arr, bufferArr) in fields:
+        src_field = Field.create_from_numpy_array("src_field", src_arr, index_dimensions=1)
+        dst_field = Field.create_from_numpy_array("dst_field", dst_arr, index_dimensions=1)
+        buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
+                                      field_type=FieldType.BUFFER, dtype=src_arr.dtype)
+
+        pack_eqs = []
+        # Since we are packing all cell values for all cells, then
+        # the buffer index is equivalent to the field index
+        for buffer_idx, cell_idx in enumerate(cell_indices):
+            eq = Assignment(buffer(buffer_idx), src_field(cell_idx))
+            pack_eqs.append(eq)
+
+        pack_code = create_kernel(pack_eqs, data_type={'src_field': src_arr.dtype, 'buffer': buffer.dtype})
+        pack_kernel = pack_code.compile()
+        pack_kernel(buffer=bufferArr, src_field=src_arr)
+
+        unpack_eqs = []
+
+        for buffer_idx, cell_idx in enumerate(cell_indices):
+            eq = Assignment(dst_field(cell_idx), buffer(buffer_idx))
+            unpack_eqs.append(eq)
+
+        unpack_code = create_kernel(unpack_eqs, data_type={'dst_field': dst_arr.dtype, 'buffer': buffer.dtype})
+        unpack_kernel = unpack_code.compile()
+        unpack_kernel(buffer=bufferArr, dst_field=dst_arr)
+
+        mask_arr = np.ma.masked_where((src_arr - dst_arr) != 0, src_arr)
+        np.testing.assert_equal(dst_arr, mask_arr.filled(int(0)))
+
+
+def test_field_layouts():
+    num_cell_values = 27
+    for layout_str in ['numpy', 'fzyx', 'zyxf', 'reverse_numpy']:
+        fields = _generate_fields(num_directions=num_cell_values, layout=layout_str)
+        for (src_arr, dst_arr, bufferArr) in fields:
+            src_field = Field.create_from_numpy_array("src_field", src_arr, index_dimensions=1)
+            dst_field = Field.create_from_numpy_array("dst_field", dst_arr, index_dimensions=1)
+            buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
+                                          field_type=FieldType.BUFFER, dtype=src_arr.dtype)
+
+            pack_eqs = []
+            # Since we are packing all cell values for all cells, then
+            # the buffer index is equivalent to the field index
+            for idx in range(num_cell_values):
+                eq = Assignment(buffer(idx), src_field(idx))
+                pack_eqs.append(eq)
+
+            pack_code = create_kernel(pack_eqs, data_type={'src_field': src_arr.dtype, 'buffer': buffer.dtype})
+            pack_kernel = pack_code.compile()
+            pack_kernel(buffer=bufferArr, src_field=src_arr)
+
+            unpack_eqs = []
+
+            for idx in range(num_cell_values):
+                eq = Assignment(dst_field(idx), buffer(idx))
+                unpack_eqs.append(eq)
+
+            unpack_code = create_kernel(unpack_eqs, data_type={'dst_field': dst_arr.dtype, 'buffer': buffer.dtype})
+            unpack_kernel = unpack_code.compile()
+            unpack_kernel(buffer=bufferArr, dst_field=dst_arr)
diff --git a/pystencils_tests/test_buffer_gpu.py b/pystencils_tests/test_buffer_gpu.py
new file mode 100644
index 0000000000000000000000000000000000000000..6494d69561d4fd3a40da5143b117913c1efbdd4b
--- /dev/null
+++ b/pystencils_tests/test_buffer_gpu.py
@@ -0,0 +1,222 @@
+"""Tests for the (un)packing (from)to buffers on a CUDA GPU."""
+
+import numpy as np
+from pystencils import Field, FieldType, Assignment
+from pystencils.field import layout_string_to_tuple, create_numpy_array_with_layout
+from pystencils.stencils import direction_string_to_offset
+from pystencils.gpucuda import make_python_function, create_cuda_kernel
+from pystencils.slicing import add_ghost_layers, get_slice_before_ghost_layer, get_ghost_region_slice
+import pytest
+try:
+    # noinspection PyUnresolvedReferences
+    import pycuda.autoinit
+    import pycuda.gpuarray as gpuarray
+except ImportError:
+    pass
+
+
+FIELD_SIZES = [(4, 3), (9, 3, 7)]
+
+
+def _generate_fields(dt=np.uint8, stencil_directions=1, layout='numpy'):
+    field_sizes = FIELD_SIZES
+    if stencil_directions > 1:
+        field_sizes = [s + (stencil_directions,) for s in field_sizes]
+
+    fields = []
+    for size in field_sizes:
+        field_layout = layout_string_to_tuple(layout, len(size))
+        src_arr = create_numpy_array_with_layout(size, field_layout).astype(dt)
+
+        array_data = np.reshape(np.arange(1, int(np.prod(size)+1)), size)
+        # Use flat iterator to input data into the array
+        src_arr.flat = add_ghost_layers(array_data,
+                                        index_dimensions=1 if stencil_directions > 1 else 0).astype(dt).flat
+
+        gpu_src_arr = gpuarray.to_gpu(src_arr)
+        gpu_dst_arr = gpuarray.zeros_like(gpu_src_arr)
+        gpu_buffer_arr = gpuarray.zeros(np.prod(src_arr.shape), dtype=dt)
+
+        fields.append((src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr))
+    return fields
+
+
+@pytest.mark.gpu
+def test_full_scalar_field():
+    """Tests fully (un)packing a scalar field (from)to a GPU buffer."""
+    fields = _generate_fields()
+    for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
+        src_field = Field.create_from_numpy_array("src_field", src_arr)
+        dst_field = Field.create_from_numpy_array("dst_field", src_arr)
+        buffer = Field.create_generic("buffer", spatial_dimensions=1,
+                                      field_type=FieldType.BUFFER, dtype=src_arr.dtype)
+
+        pack_eqs = [Assignment(buffer.center(), src_field.center())]
+        pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+        pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types)
+
+        pack_kernel = make_python_function(pack_code)
+        pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr)
+
+        unpack_eqs = [Assignment(dst_field.center(), buffer.center())]
+        unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+        unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types)
+
+        unpack_kernel = make_python_function(unpack_code)
+        unpack_kernel(dst_field=gpu_dst_arr, buffer=gpu_buffer_arr)
+
+        dst_arr = gpu_dst_arr.get()
+
+        np.testing.assert_equal(src_arr, dst_arr)
+
+
+@pytest.mark.gpu
+def test_field_slice():
+    """Tests (un)packing slices of a scalar field (from)to a buffer."""
+    fields = _generate_fields()
+    for d in ['N', 'S', 'NW', 'SW', 'TNW', 'B']:
+        for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
+            # Extract slice from N direction of the field
+            slice_dir = direction_string_to_offset(d, dim=len(src_arr.shape))
+            pack_slice = get_slice_before_ghost_layer(slice_dir)
+            unpack_slice = get_ghost_region_slice(slice_dir)
+
+            src_field = Field.create_from_numpy_array("src_field", src_arr[pack_slice])
+            dst_field = Field.create_from_numpy_array("dst_field", src_arr[unpack_slice])
+            buffer = Field.create_generic("buffer", spatial_dimensions=1,
+                                          field_type=FieldType.BUFFER, dtype=src_arr.dtype)
+
+            pack_eqs = [Assignment(buffer.center(), src_field.center())]
+            pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+            pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types)
+
+            pack_kernel = make_python_function(pack_code)
+            pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr[pack_slice])
+
+            # Unpack into ghost layer of dst_field in N direction
+            unpack_eqs = [Assignment(dst_field.center(), buffer.center())]
+            unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+            unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types)
+
+            unpack_kernel = make_python_function(unpack_code)
+            unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr[unpack_slice])
+
+            dst_arr = gpu_dst_arr.get()
+
+            np.testing.assert_equal(src_arr[pack_slice], dst_arr[unpack_slice])
+
+
+@pytest.mark.gpu
+def test_all_cell_values():
+    """Tests (un)packing all cell values of the a field (from)to a buffer."""
+    num_cell_values = 7
+    fields = _generate_fields(stencil_directions=num_cell_values)
+    for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
+        src_field = Field.create_from_numpy_array("src_field", gpu_src_arr, index_dimensions=1)
+        dst_field = Field.create_from_numpy_array("dst_field", gpu_src_arr, index_dimensions=1)
+        buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
+                                      field_type=FieldType.BUFFER, dtype=gpu_src_arr.dtype)
+
+        pack_eqs = []
+        # Since we are packing all cell values for all cells, then
+        # the buffer index is equivalent to the field index
+        for idx in range(num_cell_values):
+            eq = Assignment(buffer(idx), src_field(idx))
+            pack_eqs.append(eq)
+
+        pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+        pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types)
+        pack_kernel = make_python_function(pack_code)
+        pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr)
+
+        unpack_eqs = []
+
+        for idx in range(num_cell_values):
+            eq = Assignment(dst_field(idx), buffer(idx))
+            unpack_eqs.append(eq)
+
+        unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+        unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types)
+        unpack_kernel = make_python_function(unpack_code)
+        unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr)
+
+        dst_arr = gpu_dst_arr.get()
+
+        np.testing.assert_equal(src_arr, dst_arr)
+
+
+@pytest.mark.gpu
+def test_subset_cell_values():
+    """Tests (un)packing a subset of cell values of the a field (from)to a buffer."""
+    num_cell_values = 7
+    # Cell indices of the field to be (un)packed (from)to the buffer
+    cell_indices = [1, 3, 5, 6]
+    fields = _generate_fields(stencil_directions=num_cell_values)
+    for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
+        src_field = Field.create_from_numpy_array("src_field", gpu_src_arr, index_dimensions=1)
+        dst_field = Field.create_from_numpy_array("dst_field", gpu_src_arr, index_dimensions=1)
+        buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
+                                      field_type=FieldType.BUFFER, dtype=gpu_src_arr.dtype)
+
+        pack_eqs = []
+        # Since we are packing all cell values for all cells, then
+        # the buffer index is equivalent to the field index
+        for buffer_idx, cell_idx in enumerate(cell_indices):
+            eq = Assignment(buffer(buffer_idx), src_field(cell_idx))
+            pack_eqs.append(eq)
+
+        pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+        pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types)
+        pack_kernel = make_python_function(pack_code)
+        pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr)
+
+        unpack_eqs = []
+
+        for buffer_idx, cell_idx in enumerate(cell_indices):
+            eq = Assignment(dst_field(cell_idx), buffer(buffer_idx))
+            unpack_eqs.append(eq)
+
+        unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+        unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types)
+        unpack_kernel = make_python_function(unpack_code)
+        unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr)
+
+        dst_arr = gpu_dst_arr.get()
+
+        mask_arr = np.ma.masked_where((src_arr - dst_arr) != 0, src_arr)
+        np.testing.assert_equal(dst_arr, mask_arr.filled(int(0)))
+
+
+@pytest.mark.gpu
+def test_field_layouts():
+    num_cell_values = 7
+    for layout_str in ['numpy', 'fzyx', 'zyxf', 'reverse_numpy']:
+        fields = _generate_fields(stencil_directions=num_cell_values, layout=layout_str)
+        for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
+            src_field = Field.create_from_numpy_array("src_field", gpu_src_arr, index_dimensions=1)
+            dst_field = Field.create_from_numpy_array("dst_field", gpu_src_arr, index_dimensions=1)
+            buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
+                                          field_type=FieldType.BUFFER, dtype=src_arr.dtype)
+
+            pack_eqs = []
+            # Since we are packing all cell values for all cells, then
+            # the buffer index is equivalent to the field index
+            for idx in range(num_cell_values):
+                eq = Assignment(buffer(idx), src_field(idx))
+                pack_eqs.append(eq)
+
+            pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+            pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types)
+            pack_kernel = make_python_function(pack_code)
+            pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr)
+
+            unpack_eqs = []
+
+            for idx in range(num_cell_values):
+                eq = Assignment(dst_field(idx), buffer(idx))
+                unpack_eqs.append(eq)
+
+            unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
+            unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types)
+            unpack_kernel = make_python_function(unpack_code)
+            unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr)
diff --git a/pystencils_tests/test_cudagpu.py b/pystencils_tests/test_cudagpu.py
new file mode 100644
index 0000000000000000000000000000000000000000..35cd8cf9004533873330519d42e1a67b5d449f48
--- /dev/null
+++ b/pystencils_tests/test_cudagpu.py
@@ -0,0 +1,147 @@
+import numpy as np
+import sympy as sp
+from pystencils import Field, Assignment
+from pystencils.simp import sympy_cse_on_assignment_list
+from pystencils.gpucuda.indexing import LineIndexing
+from pystencils.slicing import remove_ghost_layers, add_ghost_layers, make_slice
+from pystencils.gpucuda import make_python_function, create_cuda_kernel
+import pycuda.gpuarray as gpuarray
+from scipy.ndimage import convolve
+
+
+def test_averaging_kernel():
+    size = (40, 55)
+    src_arr = np.random.rand(*size)
+    src_arr = add_ghost_layers(src_arr)
+    dst_arr = np.zeros_like(src_arr)
+    src_field = Field.create_from_numpy_array('src', src_arr)
+    dst_field = Field.create_from_numpy_array('dst', dst_arr)
+
+    update_rule = Assignment(dst_field[0, 0],
+                             (src_field[0, 1] + src_field[0, -1] + src_field[1, 0] + src_field[-1, 0]) / 4)
+
+    ast = create_cuda_kernel(sympy_cse_on_assignment_list([update_rule]))
+    kernel = make_python_function(ast)
+
+    gpu_src_arr = gpuarray.to_gpu(src_arr)
+    gpu_dst_arr = gpuarray.to_gpu(dst_arr)
+    kernel(src=gpu_src_arr, dst=gpu_dst_arr)
+    gpu_dst_arr.get(dst_arr)
+
+    stencil = np.array([[0, 1, 0], [1, 0, 1], [0, 1, 0]]) / 4.0
+    reference = convolve(remove_ghost_layers(src_arr), stencil, mode='constant', cval=0.0)
+    reference = add_ghost_layers(reference)
+    np.testing.assert_almost_equal(reference, dst_arr)
+
+
+def test_variable_sized_fields():
+    src_field = Field.create_generic('src', spatial_dimensions=2)
+    dst_field = Field.create_generic('dst', spatial_dimensions=2)
+
+    update_rule = Assignment(dst_field[0, 0],
+                             (src_field[0, 1] + src_field[0, -1] + src_field[1, 0] + src_field[-1, 0]) / 4)
+
+    ast = create_cuda_kernel(sympy_cse_on_assignment_list([update_rule]))
+    kernel = make_python_function(ast)
+
+    size = (3, 3)
+    src_arr = np.random.rand(*size)
+    src_arr = add_ghost_layers(src_arr)
+    dst_arr = np.zeros_like(src_arr)
+
+    gpu_src_arr = gpuarray.to_gpu(src_arr)
+    gpu_dst_arr = gpuarray.to_gpu(dst_arr)
+    kernel(src=gpu_src_arr, dst=gpu_dst_arr)
+    gpu_dst_arr.get(dst_arr)
+
+    stencil = np.array([[0, 1, 0], [1, 0, 1], [0, 1, 0]]) / 4.0
+    reference = convolve(remove_ghost_layers(src_arr), stencil, mode='constant', cval=0.0)
+    reference = add_ghost_layers(reference)
+    np.testing.assert_almost_equal(reference, dst_arr)
+
+
+def test_multiple_index_dimensions():
+    """Sums along the last axis of a numpy array"""
+    src_size = (7, 6, 4)
+    dst_size = src_size[:2]
+    src_arr = np.asfortranarray(np.random.rand(*src_size))
+    dst_arr = np.zeros(dst_size)
+
+    src_field = Field.create_from_numpy_array('src', src_arr, index_dimensions=1)
+    dst_field = Field.create_from_numpy_array('dst', dst_arr, index_dimensions=0)
+
+    offset = (-2, -1)
+    update_rule = Assignment(dst_field[0, 0],
+                             sum([src_field[offset[0], offset[1]](i) for i in range(src_size[-1])]))
+
+    ast = create_cuda_kernel([update_rule])
+    kernel = make_python_function(ast)
+
+    gpu_src_arr = gpuarray.to_gpu(src_arr)
+    gpu_dst_arr = gpuarray.to_gpu(dst_arr)
+    kernel(src=gpu_src_arr, dst=gpu_dst_arr)
+    gpu_dst_arr.get(dst_arr)
+
+    reference = np.zeros_like(dst_arr)
+    gl = np.max(np.abs(np.array(offset, dtype=int)))
+    for x in range(gl, src_size[0]-gl):
+        for y in range(gl, src_size[1]-gl):
+            reference[x, y] = sum([src_arr[x+offset[0], y+offset[1], i] for i in range(src_size[2])])
+
+    np.testing.assert_almost_equal(reference, dst_arr)
+
+
+def test_ghost_layer():
+    size = (6, 5)
+    src_arr = np.ones(size)
+    dst_arr = np.zeros_like(src_arr)
+    src_field = Field.create_from_numpy_array('src', src_arr, index_dimensions=0)
+    dst_field = Field.create_from_numpy_array('dst', dst_arr, index_dimensions=0)
+
+    update_rule = Assignment(dst_field[0, 0], src_field[0, 0])
+    ghost_layers = [(1, 2), (2, 1)]
+    ast = create_cuda_kernel([update_rule], ghost_layers=ghost_layers, indexing_creator=LineIndexing)
+    kernel = make_python_function(ast)
+
+    gpu_src_arr = gpuarray.to_gpu(src_arr)
+    gpu_dst_arr = gpuarray.to_gpu(dst_arr)
+    kernel(src=gpu_src_arr, dst=gpu_dst_arr)
+    gpu_dst_arr.get(dst_arr)
+
+    reference = np.zeros_like(src_arr)
+    reference[ghost_layers[0][0]:-ghost_layers[0][1], ghost_layers[1][0]:-ghost_layers[1][1]] = 1
+    np.testing.assert_equal(reference, dst_arr)
+
+
+def test_setting_value():
+    arr_cpu = np.arange(25, dtype=np.float64).reshape(5, 5)
+    arr_gpu = gpuarray.to_gpu(arr_cpu)
+
+    iteration_slice = make_slice[:, :]
+    f = Field.create_generic("f", 2)
+    update_rule = [Assignment(f(0), sp.Symbol("value"))]
+    ast = create_cuda_kernel(update_rule, iteration_slice=iteration_slice, indexing_creator=LineIndexing)
+
+    kernel = make_python_function(ast)
+    kernel(f=arr_gpu, value=np.float64(42.0))
+    np.testing.assert_equal(arr_gpu.get(), np.ones((5, 5)) * 42.0)
+
+
+def test_periodicity():
+    from pystencils.gpucuda.periodicity import get_periodic_boundary_functor as periodic_gpu
+    from pystencils.slicing import get_periodic_boundary_functor as periodic_cpu
+
+    arr_cpu = np.arange(50, dtype=np.float64).reshape(5, 5, 2)
+    arr_gpu = gpuarray.to_gpu(arr_cpu)
+
+    periodicity_stencil = [(1, 0), (-1, 0), (1, 1)]
+    periodic_gpu_kernel = periodic_gpu(periodicity_stencil, (5, 5), 1, 2)
+    periodic_cpu_kernel = periodic_cpu(periodicity_stencil)
+
+    cpu_result = np.copy(arr_cpu)
+    periodic_cpu_kernel(cpu_result)
+
+    gpu_result = np.copy(arr_cpu)
+    periodic_gpu_kernel(pdfs=arr_gpu)
+    arr_gpu.get(gpu_result)
+    np.testing.assert_equal(cpu_result, gpu_result)
diff --git a/pystencils_tests/test_datahandling.py b/pystencils_tests/test_datahandling.py
new file mode 100644
index 0000000000000000000000000000000000000000..0710fb249f71bdc0684da069922a0c7ce4601c6f
--- /dev/null
+++ b/pystencils_tests/test_datahandling.py
@@ -0,0 +1,208 @@
+import numpy as np
+import os
+from tempfile import TemporaryDirectory
+
+import pystencils as ps
+from pystencils import create_kernel, create_data_handling
+
+
+def basic_iteration(dh):
+    dh.add_array('basic_iter_test_gl_default')
+    dh.add_array('basic_iter_test_gl_3', ghost_layers=3)
+
+    for b in dh.iterate():
+        assert b.shape == b['basic_iter_test_gl_3'].shape
+        assert b.shape == b['basic_iter_test_gl_default'].shape
+
+
+def access_and_gather(dh, domain_size):
+    dh.add_array('f1', dtype=np.dtype(np.int32))
+    dh.add_array_like('f2', 'f1')
+    dh.add_array('v1', values_per_cell=3, dtype=np.int64, ghost_layers=2)
+    dh.add_array_like('v2', 'v1')
+
+    dh.swap('f1', 'f2')
+    dh.swap('v1', 'v2')
+
+    # Check symbolic field properties
+    assert dh.fields.f1.index_dimensions == 0
+    assert dh.fields.f1.spatial_dimensions == len(domain_size)
+    assert dh.fields.f1.dtype.numpy_dtype == np.int32
+
+    assert dh.fields.v1.index_dimensions == 1
+    assert dh.fields.v1.spatial_dimensions == len(domain_size)
+    assert dh.fields.v1.dtype.numpy_dtype == np.int64
+
+    for b in dh.iterate(ghost_layers=0):
+        val = sum(b.cell_index_arrays)
+        np.copyto(b['f1'], val)
+        for i, coord_arr in enumerate(b.cell_index_arrays):
+            np.copyto(b['v1'][..., i], coord_arr)
+
+    full_arr = dh.gather_array('v1')
+    if full_arr is not None:
+        expected_shape = domain_size + (3,)
+        assert full_arr.shape == expected_shape
+        for x in range(full_arr.shape[0]):
+            for y in range(full_arr.shape[1]):
+                if len(domain_size) == 3:
+                    for z in range(full_arr.shape[2]):
+                        assert full_arr[x, y, z, 0] == x
+                        assert full_arr[x, y, z, 1] == y
+                        assert full_arr[x, y, z, 2] == z
+                else:
+                    assert len(domain_size) == 2
+                    assert full_arr[x, y, 0] == x
+                    assert full_arr[x, y, 1] == y
+
+    full_arr = dh.gather_array('f1')
+    if full_arr is not None:
+        expected_shape = domain_size
+        assert full_arr.shape == expected_shape
+        for x in range(full_arr.shape[0]):
+            for y in range(full_arr.shape[1]):
+                if len(domain_size) == 3:
+                    for z in range(full_arr.shape[2]):
+                        assert full_arr[x, y, z] == x + y + z
+                else:
+                    assert len(domain_size) == 2
+                    assert full_arr[x, y] == x + y
+
+
+def synchronization(dh, test_gpu=False):
+    field_name = 'comm_field_test'
+    if test_gpu:
+        try:
+            from pycuda import driver
+            import pycuda.autoinit
+        except ImportError:
+            return
+        field_name += 'Gpu'
+
+    dh.add_array(field_name, ghost_layers=1, dtype=np.int32, cpu=True, gpu=test_gpu)
+
+    # initialize everything with 1
+    for b in dh.iterate(ghost_layers=1):
+        b[field_name].fill(1)
+    for b in dh.iterate(ghost_layers=0):
+        b[field_name].fill(42)
+
+    if test_gpu:
+        dh.to_gpu(field_name)
+
+    dh.synchronization_function(field_name, target='gpu' if test_gpu else 'cpu')()
+
+    if test_gpu:
+        dh.to_cpu(field_name)
+
+    for b in dh.iterate(ghost_layers=1):
+        np.testing.assert_equal(42, b[field_name])
+
+
+def kernel_execution_jacobi(dh, test_gpu=False):
+    if test_gpu:
+        try:
+            from pycuda import driver
+            import pycuda.autoinit
+        except ImportError:
+            print("Skipping kernel_execution_jacobi GPU version, because pycuda not available")
+            return
+
+    dh.add_array('f', gpu=test_gpu)
+    dh.add_array('tmp', gpu=test_gpu)
+    stencil_2d = [(1, 0), (-1, 0), (0, 1), (0, -1)]
+    stencil_3d = [(1, 0, 0), (-1, 0, 0), (0, 1, 0), (0, -1, 0), (0, 0, 1), (0, 0, -1)]
+    stencil = stencil_2d if dh.dim == 2 else stencil_3d
+
+    @ps.kernel
+    def jacobi():
+        dh.fields.tmp.center @= sum(dh.fields.f.neighbors(stencil)) / len(stencil)
+
+    kernel = create_kernel(jacobi, target='gpu' if test_gpu else 'cpu').compile()
+    for b in dh.iterate(ghost_layers=1):
+        b['f'].fill(42)
+    dh.run_kernel(kernel)
+    for b in dh.iterate(ghost_layers=0):
+        np.testing.assert_equal(b['f'], 42)
+
+
+def vtk_output(dh):
+    dh.add_array('scalar_field')
+    dh.add_array('vector_field', values_per_cell=dh.dim)
+    dh.add_array('multiple_scalar_field', values_per_cell=9)
+    dh.add_array('flag_field', dtype=np.uint16)
+
+    fields_names = ['scalar_field', 'vector_field', 'multiple_scalar_field', 'flag_field']
+    with TemporaryDirectory() as tmp_dir:
+        writer1 = dh.create_vtk_writer(os.path.join(tmp_dir, "out1"), fields_names, ghost_layers=True)
+        writer2 = dh.create_vtk_writer(os.path.join(tmp_dir, "out2"), fields_names, ghost_layers=False)
+        masks_to_name = {1: 'flag1', 5: 'some_mask'}
+        writer3 = dh.create_vtk_writer_for_flag_array(os.path.join(tmp_dir, "out3"), 'flag_field', masks_to_name)
+        writer1(1)
+        writer2(1)
+        writer3(1)
+
+
+def reduction(dh):
+    float_seq = [1.0, 2.0, 3.0]
+    int_seq = [1, 2, 3]
+    for op in ('min', 'max', 'sum'):
+        assert (dh.reduce_float_sequence(float_seq, op) == float_seq).all()
+        assert (dh.reduce_int_sequence(int_seq, op) == int_seq).all()
+
+
+def test_symbolic_fields():
+    dh = create_data_handling(domain_size=(5, 7))
+    dh.add_array('f1', values_per_cell=dh.dim)
+    assert dh.fields['f1'].spatial_dimensions == dh.dim
+    assert dh.fields['f1'].index_dimensions == 1
+
+    dh.add_array_like("f_tmp", "f1", latex_name=r"f_{tmp}")
+    assert dh.fields['f_tmp'].spatial_dimensions == dh.dim
+    assert dh.fields['f_tmp'].index_dimensions == 1
+
+    dh.swap('f1', 'f_tmp')
+
+
+def test_access():
+    for domain_shape in [(2, 3, 4), (2, 4)]:
+        for f_size in (1, 4):
+            dh = create_data_handling(domain_size=domain_shape)
+            dh.add_array('f1', values_per_cell=f_size)
+            assert dh.dim == len(domain_shape)
+
+            for b in dh.iterate(ghost_layers=1):
+                if f_size > 1:
+                    assert b['f1'].shape == tuple(ds+2 for ds in domain_shape) + (f_size,)
+                else:
+                    assert b['f1'].shape == tuple(ds + 2 for ds in domain_shape)
+
+            for b in dh.iterate(ghost_layers=0):
+                if f_size > 1:
+                    assert b['f1'].shape == domain_shape + (f_size,)
+                else:
+                    assert b['f1'].shape == domain_shape
+
+
+def test_access_and_gather():
+    for domain_shape in [(2, 2, 3), (2, 3)]:
+        dh = create_data_handling(domain_size=domain_shape, periodicity=True)
+        access_and_gather(dh, domain_shape)
+        synchronization(dh, test_gpu=False)
+        synchronization(dh, test_gpu=True)
+
+
+def test_kernel():
+    for domain_shape in [(4, 5), (3, 4, 5)]:
+        dh = create_data_handling(domain_size=domain_shape, periodicity=True)
+        kernel_execution_jacobi(dh, test_gpu=True)
+
+        dh = create_data_handling(domain_size=domain_shape, periodicity=True)
+        kernel_execution_jacobi(dh, test_gpu=False)
+        reduction(dh)
+
+
+def test_vtk_output():
+    for domain_shape in [(4, 5), (3, 4, 5)]:
+        dh = create_data_handling(domain_size=domain_shape, periodicity=True)
+        vtk_output(dh)
diff --git a/pystencils_tests/test_datahandling_parallel.py b/pystencils_tests/test_datahandling_parallel.py
new file mode 100644
index 0000000000000000000000000000000000000000..5111bd247eda4be951686095ecdfa94e8df54bfa
--- /dev/null
+++ b/pystencils_tests/test_datahandling_parallel.py
@@ -0,0 +1,65 @@
+import numpy as np
+from pystencils.datahandling.parallel_datahandling import ParallelDataHandling
+from pystencils_tests.test_datahandling import access_and_gather, synchronization, kernel_execution_jacobi, vtk_output, \
+    reduction
+import waLBerla as wlb
+
+
+def test_access_and_gather():
+    block_size = (4, 7, 1)
+    num_blocks = (3, 2, 1)
+    cells = tuple(a * b for a, b in zip(block_size, num_blocks))
+    blocks = wlb.createUniformBlockGrid(blocks=num_blocks, cellsPerBlock=block_size, oneBlockPerProcess=False,
+                                        periodic=(1, 1, 1))
+    dh = ParallelDataHandling(blocks, default_ghost_layers=2)
+    access_and_gather(dh, cells)
+    synchronization(dh, test_gpu=False)
+    if hasattr(wlb, 'cuda'):
+        synchronization(dh, test_gpu=True)
+
+
+def test_gpu():
+    if not hasattr(wlb, 'cuda'):
+        print("Skip GPU tests because walberla was built without CUDA")
+        return
+
+    block_size = (4, 7, 1)
+    num_blocks = (3, 2, 1)
+    blocks = wlb.createUniformBlockGrid(blocks=num_blocks, cellsPerBlock=block_size, oneBlockPerProcess=False)
+    dh = ParallelDataHandling(blocks, default_ghost_layers=2)
+    dh.add_array('v', values_per_cell=3, dtype=np.int64, ghost_layers=2, gpu=True)
+
+    for b in dh.iterate():
+        b['v'].fill(42)
+    dh.all_to_gpu()
+    for b in dh.iterate():
+        b['v'].fill(0)
+    dh.to_cpu('v')
+    for b in dh.iterate():
+        np.testing.assert_equal(b['v'], 42)
+
+
+def test_kernel():
+
+    for gpu in (True, False):
+        if gpu and not hasattr(wlb, 'cuda'):
+            print("Skipping CUDA tests because walberla was built without GPU support")
+            continue
+
+        # 3D
+        blocks = wlb.createUniformBlockGrid(blocks=(3, 2, 4), cellsPerBlock=(3, 2, 5), oneBlockPerProcess=False)
+        dh = ParallelDataHandling(blocks)
+        kernel_execution_jacobi(dh, test_gpu=gpu)
+        reduction(dh)
+
+        # 2D
+        blocks = wlb.createUniformBlockGrid(blocks=(3, 2, 1), cellsPerBlock=(3, 2, 1), oneBlockPerProcess=False)
+        dh = ParallelDataHandling(blocks, dim=2)
+        kernel_execution_jacobi(dh, test_gpu=gpu)
+        reduction(dh)
+
+
+def test_vtk_output():
+    blocks = wlb.createUniformBlockGrid(blocks=(3, 2, 4), cellsPerBlock=(3, 2, 5), oneBlockPerProcess=False)
+    dh = ParallelDataHandling(blocks)
+    vtk_output(dh)
diff --git a/pystencils_tests/test_derivative.py b/pystencils_tests/test_derivative.py
new file mode 100644
index 0000000000000000000000000000000000000000..41bfa594a32a6118bc0dff52e99369ff4f2cf112
--- /dev/null
+++ b/pystencils_tests/test_derivative.py
@@ -0,0 +1,21 @@
+import sympy as sp
+from sympy.printing.latex import LatexPrinter
+from pystencils.fd import *
+
+
+def test_derivative_basic():
+    x, y, z, t = sp.symbols("x y z t")
+    d = diff
+
+    op1, op2, op3 = DiffOperator(), DiffOperator(target=x), DiffOperator(target=x, superscript=1)
+    d1, d2, d3 = Diff(t), Diff(t, target=x), Diff(t, target=x, superscript=1)
+    printer = LatexPrinter()
+    assert all('\\partial' in l._latex(printer) for l in (op1, op2, op3, d1, d2, d3))
+
+    dx, dy = DiffOperator(target=x), DiffOperator(target=y)
+    diff_term = (dx + dy) ** 2 + 1
+    diff_term = diff_term.expand()
+    assert diff_term == dx**2 + 2 * dx * dy + dy**2 + 1
+
+    assert DiffOperator.apply(diff_term, t) == d(t, x, x) + 2 * d(t, x, y) + d(t, y, y) + t
+
diff --git a/pystencils_tests/test_dtype_check.py b/pystencils_tests/test_dtype_check.py
new file mode 100644
index 0000000000000000000000000000000000000000..fdbcb9b224b982fa974589f777e1259008204b73
--- /dev/null
+++ b/pystencils_tests/test_dtype_check.py
@@ -0,0 +1,31 @@
+import pystencils
+import numpy as np
+import pytest
+
+
+def test_dtype_check_wrong_type():
+    array = np.ones((10, 20)).astype(np.float32)
+    output = np.zeros_like(array)
+    x, y = pystencils.fields('x,y: [2D]')
+    stencil = [[1, 1, 1],
+               [1, 1, 1],
+               [1, 1, 1]]
+    assignment = pystencils.assignment.assignment_from_stencil(stencil, x, y, normalization_factor=1 / np.sum(stencil))
+    kernel = pystencils.create_kernel([assignment]).compile()
+
+    with pytest.raises(ValueError) as e:
+        kernel(x=array, y=output)
+    assert 'Wrong data type' in str(e)
+
+
+def test_dtype_check_correct_type():
+    array = np.ones((10, 20)).astype(np.float64)
+    output = np.zeros_like(array)
+    x, y = pystencils.fields('x,y: [2D]')
+    stencil = [[1, 1, 1],
+               [1, 1, 1],
+               [1, 1, 1]]
+    assignment = pystencils.assignment.assignment_from_stencil(stencil, x, y, normalization_factor=1 / np.sum(stencil))
+    kernel = pystencils.create_kernel([assignment]).compile()
+    kernel(x=array, y=output)
+    assert np.allclose(output[1:-1, 1:-1], np.ones_like(output[1:-1, 1:-1]))
diff --git a/pystencils_tests/test_fast_approximation.py b/pystencils_tests/test_fast_approximation.py
new file mode 100644
index 0000000000000000000000000000000000000000..d0cf33d8a042072caad39a8a62c111688fbe26bb
--- /dev/null
+++ b/pystencils_tests/test_fast_approximation.py
@@ -0,0 +1,30 @@
+import sympy as sp
+import pystencils as ps
+from pystencils.fast_approximation import insert_fast_divisions, insert_fast_sqrts, fast_sqrt, fast_inv_sqrt, \
+    fast_division
+
+
+def test_fast_sqrt():
+    f, g = ps.fields("f, g: double[2D]")
+    expr = sp.sqrt(f[0, 0] + f[1, 0])
+
+    assert len(insert_fast_sqrts(expr).atoms(fast_sqrt)) == 1
+    assert len(insert_fast_sqrts([expr])[0].atoms(fast_sqrt)) == 1
+
+    expr = 3 / sp.sqrt(f[0, 0] + f[1, 0])
+    assert len(insert_fast_sqrts(expr).atoms(fast_inv_sqrt)) == 1
+    ac = ps.AssignmentCollection([expr], [])
+    assert len(insert_fast_sqrts(ac).main_assignments[0].atoms(fast_inv_sqrt)) == 1
+
+
+def test_fast_divisions():
+    f, g = ps.fields("f, g: double[2D]")
+    expr = f[0, 0] / f[1, 0]
+    assert len(insert_fast_divisions(expr).atoms(fast_division)) == 1
+
+    expr = 1 / f[0, 0] * 2 / f[0, 1]
+    assert len(insert_fast_divisions(expr).atoms(fast_division)) == 1
+
+    ast = ps.create_kernel(ps.Assignment(g[0, 0], insert_fast_divisions(expr)), target='gpu')
+    code_str = str(ps.show_code(ast))
+    assert '__fdividef' in code_str
diff --git a/pystencils_tests/test_fd_derivation.ipynb b/pystencils_tests/test_fd_derivation.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..144bf19487056c2e9e363b6ec0baf828fa158227
--- /dev/null
+++ b/pystencils_tests/test_fd_derivation.ipynb
@@ -0,0 +1,250 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.session import *\n",
+    "from lbmpy.phasefield.scenarios import *\n",
+    "import pystencils as ps\n",
+    "from pystencils.fd.derivation import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 2D standard stencils\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stencil = [(-1, 0), (1, 0), (0, -1), (0, 1), (0, 0)]\n",
+    "standard_2d_00 = FiniteDifferenceStencilDerivation((0,0), stencil)\n",
+    "f = ps.fields(\"f: [2D]\")\n",
+    "standard_2d_00_res = standard_2d_00.get_stencil()\n",
+    "res = standard_2d_00_res.apply(f.center)\n",
+    "expected = f[-1, 0] - 2 * f[0, 0] + f[1, 0]\n",
+    "assert res == expected"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Finite difference stencil of accuracy 2, isotropic error: False"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "assert standard_2d_00_res.accuracy == 2\n",
+    "assert not standard_2d_00_res.is_isotropic\n",
+    "standard_2d_00_res"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}0 & 0 & 0\\\\1 & -2 & 1\\\\0 & 0 & 0\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡0  0   0⎤\n",
+       "⎢        ⎥\n",
+       "⎢1  -2  1⎥\n",
+       "⎢        ⎥\n",
+       "⎣0  0   0⎦"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "standard_2d_00.get_stencil().as_matrix()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 2D isotropic stencils\n",
+    "\n",
+    "## second x-derivative"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Finite difference stencil of accuracy 2, isotropic error: True"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stencil = get_stencil(\"D2Q9\")\n",
+    "isotropic_2d_00 = FiniteDifferenceStencilDerivation((0,0), stencil)\n",
+    "isotropic_2d_00_res = isotropic_2d_00.get_stencil(isotropic=True)\n",
+    "assert isotropic_2d_00_res.is_isotropic\n",
+    "assert isotropic_2d_00_res.accuracy == 2\n",
+    "isotropic_2d_00_res"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}\\frac{1}{12} & - \\frac{1}{6} & \\frac{1}{12}\\\\\\frac{5}{6} & - \\frac{5}{3} & \\frac{5}{6}\\\\\\frac{1}{12} & - \\frac{1}{6} & \\frac{1}{12}\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡1/12  -1/6  1/12⎤\n",
+       "⎢                ⎥\n",
+       "⎢5/6   -5/3  5/6 ⎥\n",
+       "⎢                ⎥\n",
+       "⎣1/12  -1/6  1/12⎦"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "isotropic_2d_00_res.as_matrix()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 144x144 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(2,2))\n",
+    "isotropic_2d_00_res.visualize()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "expected_result = sp.Matrix([[1, -2, 1], [10, -20, 10], [1, -2, 1]]) / 12\n",
+    "assert expected_result == isotropic_2d_00_res.as_matrix()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Isotropic laplacian"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left[\\begin{matrix}\\frac{1}{6} & \\frac{2}{3} & \\frac{1}{6}\\\\\\frac{2}{3} & - \\frac{10}{3} & \\frac{2}{3}\\\\\\frac{1}{6} & \\frac{2}{3} & \\frac{1}{6}\\end{matrix}\\right]$$"
+      ],
+      "text/plain": [
+       "⎡1/6   2/3   1/6⎤\n",
+       "⎢               ⎥\n",
+       "⎢2/3  -10/3  2/3⎥\n",
+       "⎢               ⎥\n",
+       "⎣1/6   2/3   1/6⎦"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "isotropic_2d_11 = FiniteDifferenceStencilDerivation((1,1), stencil)\n",
+    "isotropic_2d_11_res = isotropic_2d_11.get_stencil(isotropic=True)\n",
+    "iso_laplacian = isotropic_2d_00_res.as_matrix() + isotropic_2d_11_res.as_matrix()\n",
+    "iso_laplacian"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "expected_result = sp.Matrix([[1, 4, 1], [4, -20, 4], [1, 4, 1]]) / 6\n",
+    "assert iso_laplacian == expected_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": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/pystencils_tests/test_fd_derivation.py b/pystencils_tests/test_fd_derivation.py
new file mode 100644
index 0000000000000000000000000000000000000000..6de6e6a2834e2be08dbe4d7cc08fcb07fd7666cc
--- /dev/null
+++ b/pystencils_tests/test_fd_derivation.py
@@ -0,0 +1,33 @@
+import pytest
+import sympy as sp
+from pystencils.utils import LinearEquationSystem
+
+
+def test_linear_equation_system():
+    unknowns = sp.symbols("x_:3")
+    x, y, z = unknowns
+    m = LinearEquationSystem(unknowns)
+    m.add_equation(x + y - 2)
+    m.add_equation(x - y - 1)
+    assert m.solution_structure() == 'multiple'
+    m.set_unknown_zero(2)
+    assert m.solution_structure() == 'single'
+    solution = m.solution()
+    assert solution[unknowns[2]] == 0
+    assert solution[unknowns[1]] == sp.Rational(1, 2)
+    assert solution[unknowns[0]] == sp.Rational(3, 2)
+
+    m.set_unknown_zero(0)
+    assert m.solution_structure() == 'none'
+
+    # special case where less rows than unknowns, but no solution
+    m = LinearEquationSystem(unknowns)
+    m.add_equation(x - 3)
+    m.add_equation(x - 4)
+    assert m.solution_structure() == 'none'
+    m.add_equation(y - 4)
+    assert m.solution_structure() == 'none'
+
+    with pytest.raises(ValueError) as e:
+        m.add_equation(x**2 - 1)
+    assert 'Not a linear equation' in str(e)
diff --git a/pystencils_tests/test_field.py b/pystencils_tests/test_field.py
new file mode 100644
index 0000000000000000000000000000000000000000..67b34e7980d2d2b4538b768b7f956487ce54a26f
--- /dev/null
+++ b/pystencils_tests/test_field.py
@@ -0,0 +1,118 @@
+import pytest
+import numpy as np
+import sympy as sp
+import pystencils as ps
+from pystencils import Field, FieldType
+from pystencils.field import layout_string_to_tuple
+
+
+def test_field_basic():
+    f = Field.create_generic('f', spatial_dimensions=2)
+    assert FieldType.is_generic(f)
+    assert f['E'] == f[1, 0]
+    assert f['N'] == f[0, 1]
+    assert '_' in f.center._latex('dummy')
+
+    f = Field.create_fixed_size('f', (10, 10), strides=(80, 8), dtype=np.float64)
+    assert f.spatial_strides == (10, 1)
+    assert f.index_strides == ()
+    assert f.center_vector == sp.Matrix([f.center])
+
+    f = Field.create_fixed_size('f', (8, 8, 2, 2), index_dimensions=2)
+    assert f.center_vector == sp.Matrix([[f(0, 0), f(0, 1)],
+                                         [f(1, 0), f(1, 1)]])
+    field_access = f[1, 1]
+    assert field_access.nr_of_coordinates == 2
+    assert field_access.offset_name == 'NE'
+    neighbor = field_access.neighbor(coord_id=0, offset=-2)
+    assert neighbor.offsets == (-1, 1)
+    assert '_' in neighbor._latex('dummy')
+
+    f = Field.create_generic('f', spatial_dimensions=5, index_dimensions=2)
+    field_access = f[1, -1, 2, -3, 0](1, 0)
+    assert field_access.offsets == (1, -1, 2, -3, 0)
+    assert field_access.index == (1, 0)
+
+
+def test_error_handling():
+    struct_dtype = np.dtype([('a', np.int32), ('b', np.float64), ('c', np.uint32)])
+    Field.create_generic('f', spatial_dimensions=2, index_dimensions=0, dtype=struct_dtype)
+    with pytest.raises(ValueError) as e:
+        Field.create_generic('f', spatial_dimensions=2, index_dimensions=1, dtype=struct_dtype)
+    assert 'index dimension' in str(e)
+
+    arr = np.array([[1, 2.0, 3], [1, 2.0, 3]], dtype=struct_dtype)
+    Field.create_from_numpy_array('f', arr, index_dimensions=0)
+    with pytest.raises(ValueError) as e:
+        Field.create_from_numpy_array('f', arr, index_dimensions=1)
+    assert 'Structured arrays' in str(e)
+
+    arr = np.zeros([3, 3, 3])
+    Field.create_from_numpy_array('f', arr, index_dimensions=2)
+    with pytest.raises(ValueError) as e:
+        Field.create_from_numpy_array('f', arr, index_dimensions=3)
+    assert 'Too many' in str(e)
+
+    Field.create_fixed_size('f', (3, 2, 4), index_dimensions=0, dtype=struct_dtype, layout='reverse_numpy')
+    with pytest.raises(ValueError) as e:
+        Field.create_fixed_size('f', (3, 2, 4), index_dimensions=1, dtype=struct_dtype, layout='reverse_numpy')
+    assert 'Structured arrays' in str(e)
+
+    f = Field.create_fixed_size('f', (10, 10))
+    with pytest.raises(ValueError) as e:
+        f[1]
+    assert 'Wrong number of spatial indices' in str(e)
+
+    f = Field.create_generic('f', spatial_dimensions=2, index_shape=(3,))
+    with pytest.raises(ValueError) as e:
+        f(3)
+    assert 'out of bounds' in str(e)
+
+    f = Field.create_fixed_size('f', (10, 10, 3, 4), index_dimensions=2)
+    with pytest.raises(ValueError) as e:
+        f(3, 0)
+    assert 'out of bounds' in str(e)
+
+    with pytest.raises(ValueError) as e:
+        f(1, 0)(1, 0)
+    assert 'Indexing an already indexed' in str(e)
+
+    with pytest.raises(ValueError) as e:
+        f(1)
+    assert 'Wrong number of indices' in str(e)
+
+    with pytest.raises(ValueError) as e:
+        Field.create_generic('f', spatial_dimensions=2, layout='wrong')
+    assert 'Unknown layout descriptor' in str(e)
+
+    assert layout_string_to_tuple('fzyx', dim=4) == (3, 2, 1, 0)
+    with pytest.raises(ValueError) as e:
+        layout_string_to_tuple('wrong', dim=4)
+    assert 'Unknown layout descriptor' in str(e)
+
+
+def test_decorator_scoping():
+    dst = ps.fields('dst : double[2D]')
+
+    def f1():
+        a = sp.Symbol("a")
+
+        def f2():
+            b = sp.Symbol("b")
+
+            @ps.kernel
+            def decorated_func():
+                dst[0, 0] @= a + b
+
+            return decorated_func
+
+        return f2
+
+    assert f1()(), ps.Assignment(dst[0, 0], sp.Symbol("a") + sp.Symbol("b"))
+
+
+def test_string_creation():
+    x, y, z = ps.fields('  x(4),    y(3,5) z : double[  3,  47]')
+    assert x.index_shape == (4,)
+    assert y.index_shape == (3, 5)
+    assert z.spatial_shape == (3, 47)
diff --git a/pystencils_tests/test_field_equality.ipynb b/pystencils_tests/test_field_equality.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..03837702b4d4ea4b1667ea6bbe724f717a69a182
--- /dev/null
+++ b/pystencils_tests/test_field_equality.ipynb
@@ -0,0 +1,251 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *\n",
+    "from pystencils.data_types import cast_func"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Test field equality behaviour\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Fields create with same parameters are equal"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f1 = ps.Field.create_generic('f', spatial_dimensions=2, index_dimensions=0)\n",
+    "f2 = ps.Field.create_generic('f', spatial_dimensions=2, index_dimensions=0)\n",
+    "\n",
+    "assert f1 == f2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Field ids equal in accesses:  True\n",
+      "Field accesses equal:  True\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Field ids equal in accesses: \", id(f1.center._field) == id(f2.center._field))\n",
+    "print(\"Field accesses equal: \", f1.center == f2.center)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f1 = ps.Field.create_generic('f', spatial_dimensions=1, index_dimensions=0)\n",
+    "f2 = ps.Field.create_generic('f', spatial_dimensions=2, index_dimensions=0)\n",
+    "assert f1 != f2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f1 = ps.Field.create_generic('f', spatial_dimensions=1, index_dimensions=0)\n",
+    "f2 = ps.Field.create_generic('f', spatial_dimensions=1, index_dimensions=0, dtype=np.float32)\n",
+    "assert f1 != f2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Properties of fields:\n",
+    "- `field_type`: enum distinguishing normal from index or buffer fields\n",
+    "- `_dtype`: data type of field elements\n",
+    "- `_layout`: tuple indicating the memory linearization order\n",
+    "- `shape`: size of field for each dimension\n",
+    "- `strides`: number of elements to jump over to increase coordinate of this dimension by one\n",
+    "- `latex_name`: optional display name when field is printed as latex\n",
+    "\n",
+    "Equality compare of fields:\n",
+    "- field has `__eq__` and ``__hash__`` overridden\n",
+    "- all parameter but `latex_name` are considered for equality"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Test field access equality behaviour"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f1 = ps.Field.create_generic('f', spatial_dimensions=1, index_dimensions=0)\n",
+    "f2 = ps.Field.create_generic('f', spatial_dimensions=1, index_dimensions=0)\n",
+    "assert f1.center == f2.center"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f1 = ps.Field.create_generic('f', spatial_dimensions=1, index_dimensions=0)\n",
+    "f2 = ps.Field.create_generic('f', spatial_dimensions=1, index_dimensions=0, dtype=np.float32)\n",
+    "assert f1.center != f2.center"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_field_accesses_debug(expr):\n",
+    "    from pystencils import Field\n",
+    "    fas = list(expr.atoms(Field.Access))\n",
+    "    fields = list({e.field for e in fas})\n",
+    "    print(\"Field Accesses:\")\n",
+    "    for fa in fas:\n",
+    "        print(f\"   - {fa}, hash {hash(fa)}, offsets {fa._offsets}, index {fa._index}, {fa._hashable_content()}\")\n",
+    "    print(\"\")\n",
+    "    for i in range(len(fas)):\n",
+    "        for j in range(len(fas)):\n",
+    "            if not i < j: \n",
+    "                continue\n",
+    "            print( f\"   -> {i},{j}  {fas[i]} == {fas[j]}: {fas[i] == {fas[j]}}\")\n",
+    "    \n",
+    "    print(\"Fields\")\n",
+    "    for f in fields:\n",
+    "        print(f\"  - {f}, {id(f)}, shape {f.shape}, strides {f.strides}, {f._dtype}, {f.field_type}, layout {f.layout}\")\n",
+    "    print(\"\")\n",
+    "    for i in range(len(fields)):\n",
+    "        for j in range(len(fields)):\n",
+    "            if not i < j: \n",
+    "                continue\n",
+    "            print(f\"  - {fields[i]} == {fields[j]}: {fields[i] == fields[j]}, ids equal {id(fields[i])==id(fields[j])}, hash equal {hash(fields[i])==hash(fields[j])}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Field Accesses:\n",
+      "   - f[0], hash 2177071761647211096, offsets (0,), index (), (('f_C', ('commutative', True)), ((0,), (fshape_f[0],), (fstride_f[0],), -2638709558778433189, <FieldType.GENERIC: 0>, 'f'), 0)\n",
+      "   - f[0], hash -219035921004479174, offsets (0,), index (), (('f_C', ('commutative', True)), ((0,), (fshape_f[0],), (fstride_f[0],), 1379426851108887372, <FieldType.GENERIC: 0>, 'f'), 0)\n",
+      "\n",
+      "   -> 0,1  f[0] == f[0]: False\n",
+      "Fields\n",
+      "  - f, 139911303819560, shape (fshape_f[0],), strides (fstride_f[0],), double, FieldType.GENERIC, layout (0,)\n",
+      "  - f, 139911303820008, shape (fshape_f[0],), strides (fstride_f[0],), float, FieldType.GENERIC, layout (0,)\n",
+      "\n",
+      "  - f == f: False, ids equal False, hash equal False\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_field_accesses_debug(f1.center * f2.center)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Custom fields"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from lbmpy.sparse.update_rule_sparse import *"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$${{f}_{\\mathbf{{l}_{1}^{1}}}^{1}} + {{f}_{\\mathbf{{l}_{1}}}^{1}}$$"
+      ],
+      "text/plain": [
+       "f_000035D373 + f_000035D373"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "list_field = create_symbolic_list('l', 10, 2, np.float64)\n",
+    "normal_field = ps.fields(\"f: [2D]\")\n",
+    "normal_field.field_type = ps.FieldType.CUSTOM\n",
+    "\n",
+    "t1 = normal_field.absolute_access( (list_field[1](0),), (1,))\n",
+    "t2 = normal_field.absolute_access( (list_field[1](1),), (1,))\n",
+    "t1 + t2"
+   ]
+  }
+ ],
+ "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/pystencils_tests/test_finite_differences.py b/pystencils_tests/test_finite_differences.py
new file mode 100644
index 0000000000000000000000000000000000000000..5b7c504dc7d4144d32de5dfcddea69f245658a32
--- /dev/null
+++ b/pystencils_tests/test_finite_differences.py
@@ -0,0 +1,40 @@
+import sympy as sp
+import pystencils as ps
+from pystencils.stencils import stencil_coefficients
+from pystencils.fd.spatial import fd_stencils_standard, fd_stencils_isotropic, discretize_spatial
+from pystencils.fd import diff
+
+
+def test_spatial_2d_unit_sum():
+    f = ps.fields("f: double[2D]")
+    h = sp.symbols("h")
+
+    terms = [diff(f, 0),
+             diff(f, 1),
+             diff(f, 0, 1),
+             diff(f, 0, 0),
+             diff(f, 1, 1),
+             diff(f, 0, 0) + diff(f, 1, 1)]
+
+    schemes = [fd_stencils_standard, fd_stencils_isotropic]
+
+    for term in terms:
+        for scheme in schemes:
+            discretized = discretize_spatial(term, dx=h, stencil=scheme)
+            _, coefficients = stencil_coefficients(discretized)
+            assert sum(coefficients) == 0
+
+def test_spatial_1d_unit_sum():
+    f = ps.fields("f: double[1D]")
+    h = sp.symbols("h")
+
+    terms = [diff(f, 0),
+             diff(f, 0, 0)]
+
+    schemes = [fd_stencils_standard, fd_stencils_isotropic]
+
+    for term in terms:
+        for scheme in schemes:
+            discretized = discretize_spatial(term, dx=h, stencil=scheme)
+            _, coefficients = stencil_coefficients(discretized)
+            assert sum(coefficients) == 0
diff --git a/pystencils_tests/test_indexed_kernels.py b/pystencils_tests/test_indexed_kernels.py
new file mode 100644
index 0000000000000000000000000000000000000000..13dbbd4982555adb6237f3eb796302da1b979cad
--- /dev/null
+++ b/pystencils_tests/test_indexed_kernels.py
@@ -0,0 +1,55 @@
+import numpy as np
+from pystencils import Field, Assignment
+from pystencils.cpu import create_indexed_kernel, make_python_function
+
+
+def test_indexed_kernel():
+    arr = np.zeros((3, 4))
+    dtype = np.dtype([('x', int), ('y', int), ('value', arr.dtype)])
+    index_arr = np.zeros((3,), dtype=dtype)
+    index_arr[0] = (0, 2, 3.0)
+    index_arr[1] = (1, 3, 42.0)
+    index_arr[2] = (2, 1, 5.0)
+
+    indexed_field = Field.create_from_numpy_array('index', index_arr)
+    normal_field = Field.create_from_numpy_array('f', arr)
+    update_rule = Assignment(normal_field[0, 0], indexed_field('value'))
+    ast = create_indexed_kernel([update_rule], [indexed_field])
+    kernel = make_python_function(ast)
+    kernel(f=arr, index=index_arr)
+    for i in range(index_arr.shape[0]):
+        np.testing.assert_allclose(arr[index_arr[i]['x'], index_arr[i]['y']], index_arr[i]['value'], atol=1e-13)
+
+
+def test_indexed_cuda_kernel():
+    try:
+        import pycuda
+    except ImportError:
+        pycuda = None
+
+    if pycuda:
+        from pystencils.gpucuda import make_python_function
+        import pycuda.gpuarray as gpuarray
+        from pystencils.gpucuda.kernelcreation import created_indexed_cuda_kernel
+
+        arr = np.zeros((3, 4))
+        dtype = np.dtype([('x', int), ('y', int), ('value', arr.dtype)])
+        index_arr = np.zeros((3,), dtype=dtype)
+        index_arr[0] = (0, 2, 3.0)
+        index_arr[1] = (1, 3, 42.0)
+        index_arr[2] = (2, 1, 5.0)
+
+        indexed_field = Field.create_from_numpy_array('index', index_arr)
+        normal_field = Field.create_from_numpy_array('f', arr)
+        update_rule = Assignment(normal_field[0, 0], indexed_field('value'))
+        ast = created_indexed_cuda_kernel([update_rule], [indexed_field])
+        kernel = make_python_function(ast)
+
+        gpu_arr = gpuarray.to_gpu(arr)
+        gpu_index_arr = gpuarray.to_gpu(index_arr)
+        kernel(f=gpu_arr, index=gpu_index_arr)
+        gpu_arr.get(arr)
+        for i in range(index_arr.shape[0]):
+            np.testing.assert_allclose(arr[index_arr[i]['x'], index_arr[i]['y']], index_arr[i]['value'], atol=1e-13)
+    else:
+        print("Did not run test on GPU since no pycuda is available")
diff --git a/pystencils_tests/test_jacobi_cbackend.py b/pystencils_tests/test_jacobi_cbackend.py
new file mode 100644
index 0000000000000000000000000000000000000000..6fbf9d5ba1e82b637f1991aa2da2482d4951de84
--- /dev/null
+++ b/pystencils_tests/test_jacobi_cbackend.py
@@ -0,0 +1,65 @@
+import numpy as np
+from pystencils import show_code
+from pystencils.transformations import move_constants_before_loop, make_loop_over_domain, resolve_field_accesses
+from pystencils.field import Field
+from pystencils.astnodes import SympyAssignment, Block
+from pystencils.cpu import make_python_function
+
+
+def test_jacobi_fixed_field_size():
+    size = (30, 20)
+
+    src_field_c = np.random.rand(*size)
+    src_field_py = np.copy(src_field_c)
+    dst_field_c = np.zeros(size)
+    dst_field_py = np.zeros(size)
+
+    f = Field.create_from_numpy_array("f", src_field_c)
+    d = Field.create_from_numpy_array("d", dst_field_c)
+
+    jacobi = SympyAssignment(d[0, 0], (f[1, 0] + f[-1, 0] + f[0, 1] + f[0, -1]) / 4)
+    body = Block([jacobi])
+    ast_node = make_loop_over_domain(body, "kernel")
+    resolve_field_accesses(ast_node)
+    move_constants_before_loop(ast_node)
+
+    for x in range(1, size[0] - 1):
+        for y in range(1, size[1] - 1):
+            dst_field_py[x, y] = 0.25 * (src_field_py[x - 1, y] + src_field_py[x + 1, y] +
+                                         src_field_py[x, y - 1] + src_field_py[x, y + 1])
+
+    kernel = make_python_function(ast_node)
+    kernel(f=src_field_c, d=dst_field_c)
+    error = np.sum(np.abs(dst_field_py - dst_field_c))
+    np.testing.assert_allclose(error, 0.0, atol=1e-13)
+
+    code_display = show_code(ast_node)
+    assert 'for' in str(code_display)
+    assert 'for' in code_display._repr_html_()
+
+
+def test_jacobi_variable_field_size():
+    size = (3, 3, 3)
+    f = Field.create_generic("f", 3)
+    d = Field.create_generic("d", 3)
+    jacobi = SympyAssignment(d[0, 0, 0], (f[1, 0, 0] + f[-1, 0, 0] + f[0, 1, 0] + f[0, -1, 0]) / 4)
+    body = Block([jacobi])
+    ast_node = make_loop_over_domain(body, "kernel")
+    resolve_field_accesses(ast_node)
+    move_constants_before_loop(ast_node)
+
+    src_field_c = np.random.rand(*size)
+    src_field_py = np.copy(src_field_c)
+    dst_field_c = np.zeros(size)
+    dst_field_py = np.zeros(size)
+
+    for x in range(1, size[0]-1):
+        for y in range(1, size[1]-1):
+            for z in range(1, size[2]-1):
+                dst_field_py[x, y, z] = 0.25 * (src_field_py[x - 1, y, z] + src_field_py[x + 1, y, z] +
+                                                src_field_py[x, y - 1, z] + src_field_py[x, y + 1, z])
+
+    kernel = make_python_function(ast_node)
+    kernel(f=src_field_c, d=dst_field_c)
+    error = np.sum(np.abs(dst_field_py-dst_field_c))
+    np.testing.assert_allclose(error, 0.0, atol=1e-13)
diff --git a/pystencils_tests/test_jacobi_llvm.py b/pystencils_tests/test_jacobi_llvm.py
new file mode 100644
index 0000000000000000000000000000000000000000..f6e4825735cc4eedba5eabde720e601d6b20b398
--- /dev/null
+++ b/pystencils_tests/test_jacobi_llvm.py
@@ -0,0 +1,53 @@
+import numpy as np
+from pystencils import Assignment, Field
+from pystencils.llvm import create_kernel, make_python_function
+from pystencils.llvm.llvmjit import generate_and_jit
+
+
+def test_jacobi_fixed_field_size():
+    size = (30, 20)
+
+    src_field_llvm = np.random.rand(*size)
+    src_field_py = np.copy(src_field_llvm)
+    dst_field_llvm = np.zeros(size)
+    dst_field_py = np.zeros(size)
+
+    f = Field.create_from_numpy_array("f", src_field_llvm)
+    d = Field.create_from_numpy_array("d", dst_field_llvm)
+
+    jacobi = Assignment(d[0, 0], (f[1, 0] + f[-1, 0] + f[0, 1] + f[0, -1]) / 4)
+    ast = create_kernel([jacobi])
+
+    for x in range(1, size[0] - 1):
+        for y in range(1, size[1] - 1):
+            dst_field_py[x, y] = 0.25 * (src_field_py[x - 1, y] + src_field_py[x + 1, y] +
+                                         src_field_py[x, y - 1] + src_field_py[x, y + 1])
+
+    jit = generate_and_jit(ast)
+    jit('kernel', dst_field_llvm, src_field_llvm)
+    error = np.sum(np.abs(dst_field_py - dst_field_llvm))
+    np.testing.assert_almost_equal(error, 0.0)
+
+
+def test_jacobi_variable_field_size():
+    size = (3, 3, 3)
+    f = Field.create_generic("f", 3)
+    d = Field.create_generic("d", 3)
+    jacobi = Assignment(d[0, 0, 0], (f[1, 0, 0] + f[-1, 0, 0] + f[0, 1, 0] + f[0, -1, 0]) / 4)
+    ast = create_kernel([jacobi])
+
+    src_field_llvm = np.random.rand(*size)
+    src_field_py = np.copy(src_field_llvm)
+    dst_field_llvm = np.zeros(size)
+    dst_field_py = np.zeros(size)
+
+    for x in range(1, size[0] - 1):
+        for y in range(1, size[1] - 1):
+            for z in range(1, size[2] - 1):
+                dst_field_py[x, y, z] = 0.25 * (src_field_py[x - 1, y, z] + src_field_py[x + 1, y, z] +
+                                                src_field_py[x, y - 1, z] + src_field_py[x, y + 1, z])
+
+    kernel = make_python_function(ast, {'f': src_field_llvm, 'd': dst_field_llvm})
+    kernel()
+    error = np.sum(np.abs(dst_field_py - dst_field_llvm))
+    np.testing.assert_almost_equal(error, 0.0)
diff --git a/pystencils_tests/test_kerncraft_coupling.py b/pystencils_tests/test_kerncraft_coupling.py
new file mode 100644
index 0000000000000000000000000000000000000000..1ff9ab04c70d089a20f0aef0adc4802abcb78418
--- /dev/null
+++ b/pystencils_tests/test_kerncraft_coupling.py
@@ -0,0 +1,129 @@
+import os
+import numpy as np
+import sympy as sp
+from pystencils import Field, Assignment
+from pystencils.kerncraft_coupling import PyStencilsKerncraftKernel, KerncraftParameters
+from pystencils.kerncraft_coupling.generate_benchmark import generate_benchmark
+from pystencils.cpu import create_kernel
+import pytest
+
+from kerncraft.models import ECMData, ECM, Benchmark
+from kerncraft.machinemodel import MachineModel
+from kerncraft.kernel import KernelCode
+
+
+SCRIPT_FOLDER = os.path.dirname(os.path.realpath(__file__))
+INPUT_FOLDER = os.path.join(SCRIPT_FOLDER, "kerncraft_inputs")
+
+
+@pytest.mark.kernkraft
+def test_compilation():
+    kernel_file_path = os.path.join(INPUT_FOLDER, "2d-5pt.c")
+    with open(kernel_file_path) as kernel_file:
+        reference_kernel = KernelCode(kernel_file.read(), machine=None, filename=kernel_file_path)
+        reference_kernel.as_code('likwid')
+
+    size = [30, 50, 3]
+    arr = np.zeros(size)
+    a = Field.create_from_numpy_array('a', arr, index_dimensions=1)
+    b = Field.create_from_numpy_array('b', arr, index_dimensions=1)
+    s = sp.Symbol("s")
+    rhs = a[0, -1](0) + a[0, 1] + a[-1, 0] + a[1, 0]
+    update_rule = Assignment(b[0, 0], s * rhs)
+    ast = create_kernel([update_rule])
+    mine = generate_benchmark(ast, likwid=False)
+    print(mine)
+
+
+@pytest.mark.kernkraft
+def analysis(kernel, model='ecmdata'):
+    machine_file_path = os.path.join(INPUT_FOLDER, "default_machine_file.yaml")
+    machine = MachineModel(path_to_yaml=machine_file_path)
+    if model == 'ecmdata':
+        model = ECMData(kernel, machine, KerncraftParameters())
+    elif model == 'ecm':
+        model = ECM(kernel, machine, KerncraftParameters())
+        # model.analyze()
+        # model.plot()
+    elif model == 'benchmark':
+        model = Benchmark(kernel, machine, KerncraftParameters())
+    else:
+        model = ECM(kernel, machine, KerncraftParameters())
+    model.analyze()
+    return model
+
+
+@pytest.mark.kernkraft
+def test_3d_7pt_iaca():
+    # Make sure you use the intel compiler
+    size = [20, 200, 200]
+    kernel_file_path = os.path.join(INPUT_FOLDER, "3d-7pt.c")
+    machine_file_path = os.path.join(INPUT_FOLDER, "default_machine_file.yaml")
+    machine = MachineModel(path_to_yaml=machine_file_path)
+    with open(kernel_file_path) as kernel_file:
+        reference_kernel = KernelCode(kernel_file.read(), machine=machine, filename=kernel_file_path)
+    reference_kernel.set_constant('M', size[0])
+    reference_kernel.set_constant('N', size[1])
+    assert size[1] == size[2]
+    analysis(reference_kernel, model='ecm')
+
+    arr = np.zeros(size)
+    a = Field.create_from_numpy_array('a', arr, index_dimensions=0)
+    b = Field.create_from_numpy_array('b', arr, index_dimensions=0)
+    s = sp.Symbol("s")
+    rhs = a[0, -1, 0] + a[0, 1, 0] + a[-1, 0, 0] + a[1, 0, 0] + a[0, 0, -1] + a[0, 0, 1]
+
+    update_rule = Assignment(b[0, 0, 0], s * rhs)
+    ast = create_kernel([update_rule])
+    k = PyStencilsKerncraftKernel(ast, machine)
+    analysis(k, model='ecm')
+    assert reference_kernel._flops == k._flops
+    # assert reference.results['cl throughput'] == analysis.results['cl throughput']
+
+
+@pytest.mark.kernkraft
+def test_2d_5pt():
+    size = [30, 50, 3]
+    kernel_file_path = os.path.join(INPUT_FOLDER, "2d-5pt.c")
+    with open(kernel_file_path) as kernel_file:
+        reference_kernel = KernelCode(kernel_file.read(), machine=None, filename=kernel_file_path)
+    reference = analysis(reference_kernel)
+
+    arr = np.zeros(size)
+    a = Field.create_from_numpy_array('a', arr, index_dimensions=1)
+    b = Field.create_from_numpy_array('b', arr, index_dimensions=1)
+    s = sp.Symbol("s")
+    rhs = a[0, -1](0) + a[0, 1] + a[-1, 0] + a[1, 0]
+    update_rule = Assignment(b[0, 0], s * rhs)
+    ast = create_kernel([update_rule])
+    k = PyStencilsKerncraftKernel(ast)
+    result = analysis(k)
+
+    for e1, e2 in zip(reference.results['cycles'], result.results['cycles']):
+        assert e1 == e2
+
+
+@pytest.mark.kernkraft
+def test_3d_7pt():
+    size = [30, 50, 50]
+    kernel_file_path = os.path.join(INPUT_FOLDER, "3d-7pt.c")
+    with open(kernel_file_path) as kernel_file:
+        reference_kernel = KernelCode(kernel_file.read(), machine=None, filename=kernel_file_path)
+    reference_kernel.set_constant('M', size[0])
+    reference_kernel.set_constant('N', size[1])
+    assert size[1] == size[2]
+    reference = analysis(reference_kernel)
+
+    arr = np.zeros(size)
+    a = Field.create_from_numpy_array('a', arr, index_dimensions=0)
+    b = Field.create_from_numpy_array('b', arr, index_dimensions=0)
+    s = sp.Symbol("s")
+    rhs = a[0, -1, 0] + a[0, 1, 0] + a[-1, 0, 0] + a[1, 0, 0] + a[0, 0, -1] + a[0, 0, 1]
+
+    update_rule = Assignment(b[0, 0, 0], s * rhs)
+    ast = create_kernel([update_rule])
+    k = PyStencilsKerncraftKernel(ast)
+    result = analysis(k)
+
+    for e1, e2 in zip(reference.results['cycles'], result.results['cycles']):
+        assert e1 == e2
diff --git a/pystencils_tests/test_loop_cutting.py b/pystencils_tests/test_loop_cutting.py
new file mode 100644
index 0000000000000000000000000000000000000000..163b6cebb29ec98320b50ff274380bf25fc4e9f3
--- /dev/null
+++ b/pystencils_tests/test_loop_cutting.py
@@ -0,0 +1,116 @@
+import sympy as sp
+import numpy as np
+import pystencils as ps
+from pystencils import Field
+from pystencils.cpu import create_kernel, make_python_function
+from pystencils.astnodes import Conditional, LoopOverCoordinate, SympyAssignment
+from pystencils.kernelcreation import create_staggered_kernel
+from pystencils.transformations import move_constants_before_loop
+import pystencils.astnodes as ast
+from pystencils.transformations import simplify_conditionals, cleanup_blocks, cut_loop
+
+
+def offsets_in_plane(normal_plane, offset_int, dimension):
+    offset = [0] * dimension
+    offset[normal_plane] = offset_int
+    result = [tuple(offset)]
+    for i in range(dimension):
+        if i == normal_plane:
+            continue
+        lower = offset.copy()
+        upper = offset.copy()
+        lower[i] -= 1
+        upper[i] += 1
+        result.append(tuple(lower))
+        result.append(tuple(upper))
+    return result
+
+
+def test_staggered_iteration():
+    dim = 2
+    f_arr = np.arange(5**dim).reshape([5]*dim).astype(np.float64)
+    s_arr = np.ones([5]*dim + [dim]) * 1234
+    s_arr_ref = s_arr.copy()
+
+    fields_fixed = (Field.create_from_numpy_array('f', f_arr),
+                    Field.create_from_numpy_array('s', s_arr, index_dimensions=1))
+    fields_var = (Field.create_generic('f', 2),
+                  Field.create_generic('s', 2, index_dimensions=1))
+
+    for f, s in [fields_var, fields_fixed]:
+        # --- Manual
+        eqs = []
+        counters = [LoopOverCoordinate.get_loop_counter_symbol(i) for i in range(dim)]
+        conditions = [counters[i] < f.shape[i] - 1 for i in range(dim)]
+        for d in range(dim):
+            eq = SympyAssignment(s(d), sum(f[o] for o in offsets_in_plane(d, 0, dim)) -
+                                 sum(f[o] for o in offsets_in_plane(d, -1, dim)))
+            cond = sp.And(*[conditions[i] for i in range(dim) if d != i])
+            eqs.append(Conditional(cond, eq))
+        func = create_kernel(eqs, ghost_layers=[(1, 0), (1, 0), (1, 0)]).compile()
+
+        # --- Built-in optimized
+        expressions = []
+        for d in range(dim):
+            expressions.append(sum(f[o] for o in offsets_in_plane(d, 0, dim)) -
+                               sum(f[o] for o in offsets_in_plane(d, -1, dim)))
+        func_optimized = create_staggered_kernel(s, expressions).compile()
+        assert not func_optimized.ast.atoms(Conditional), "Loop cutting optimization did not work"
+
+        func(f=f_arr, s=s_arr_ref)
+        func_optimized(f=f_arr, s=s_arr)
+        np.testing.assert_almost_equal(s_arr_ref, s_arr)
+
+
+def test_staggered_iteration_manual():
+    dim = 2
+    f_arr = np.arange(5**dim).reshape([5]*dim)
+    s_arr = np.ones([5]*dim + [dim]) * 1234
+    s_arr_ref = s_arr.copy()
+
+    f = Field.create_from_numpy_array('f', f_arr)
+    s = Field.create_from_numpy_array('s', s_arr, index_dimensions=1)
+
+    eqs = []
+
+    counters = [LoopOverCoordinate.get_loop_counter_symbol(i) for i in range(dim)]
+    conditions = [counters[i] < f.shape[i] - 1 for i in range(dim)]
+
+    for d in range(dim):
+        eq = SympyAssignment(s(d), sum(f[o] for o in offsets_in_plane(d, 0, dim)) -
+                             sum(f[o] for o in offsets_in_plane(d, -1, dim)))
+        cond = sp.And(*[conditions[i] for i in range(dim) if d != i])
+        eqs.append(Conditional(cond, eq))
+
+    kernel_ast = create_kernel(eqs, ghost_layers=[(1, 0), (1, 0), (1, 0)])
+
+    func = make_python_function(kernel_ast)
+    func(f=f_arr, s=s_arr_ref)
+
+    inner_loop = [n for n in kernel_ast.atoms(ast.LoopOverCoordinate) if n.is_innermost_loop][0]
+    cut_loop(inner_loop, [4])
+    outer_loop = [n for n in kernel_ast.atoms(ast.LoopOverCoordinate) if n.is_outermost_loop][0]
+    cut_loop(outer_loop, [4])
+
+    simplify_conditionals(kernel_ast.body, loop_counter_simplification=True)
+    cleanup_blocks(kernel_ast.body)
+    move_constants_before_loop(kernel_ast.body)
+    cleanup_blocks(kernel_ast.body)
+
+    assert not kernel_ast.atoms(Conditional), "Loop cutting optimization did not work"
+
+    func_optimized = make_python_function(kernel_ast)
+    func_optimized(f=f_arr, s=s_arr)
+    np.testing.assert_almost_equal(s_arr_ref, s_arr)
+
+
+def test_staggered_gpu():
+    dim = 2
+    f, s = ps.fields("f, s({dim}): double[{dim}D]".format(dim=dim))
+    expressions = [(f[0, 0] + f[-1, 0]) / 2,
+                   (f[0, 0] + f[0, -1]) / 2]
+    kernel_ast = ps.create_staggered_kernel(s, expressions, target='gpu', gpu_exclusive_conditions=True)
+    assert len(kernel_ast.atoms(Conditional)) == 4
+
+    kernel_ast = ps.create_staggered_kernel(s, expressions, target='gpu', gpu_exclusive_conditions=False)
+    assert len(kernel_ast.atoms(Conditional)) == 3
diff --git a/pystencils_tests/test_parameterstudy.py b/pystencils_tests/test_parameterstudy.py
new file mode 100644
index 0000000000000000000000000000000000000000..2b58e756671ef91814204fc2e3f76942990733fb
--- /dev/null
+++ b/pystencils_tests/test_parameterstudy.py
@@ -0,0 +1,78 @@
+import io
+import json
+from http.server import HTTPServer, BaseHTTPRequestHandler
+from tempfile import TemporaryDirectory
+from pystencils.runhelper import ParameterStudy
+
+
+def test_http_server(monkeypatch):
+
+    result_list = []
+
+    def handle_request_mock(server):
+        handler = server.RequestHandlerClass()
+
+        def get(url, data):
+            handler.wfile = io.BytesIO()
+            handler.path = url
+            handler._read_contents = lambda *args, **kwargs: json.dumps(data)
+            handler.do_GET()
+            handler.wfile.seek(0)
+            return json.loads(handler.wfile.read().decode())
+
+        while True:
+            result = get('/next_scenario', {'client_name': 'test'})
+            if result['status'] == 'finished':
+                break
+            else:
+                assert result['status'] == 'ok'
+                result_list.append(result)
+
+                p = result['params']
+                get("/result", {'params': p,
+                                'changed_params': {},
+                                'result': {'result': p['p1'] + p['p2']},
+                                'env': {},
+                                'client_name': 'test'})
+
+    monkeypatch.setattr(HTTPServer, 'handle_request', handle_request_mock)
+    monkeypatch.setattr(BaseHTTPRequestHandler, '__init__', lambda self: None)
+    monkeypatch.setattr(BaseHTTPRequestHandler, 'send_response', lambda *args, **kwargs: None)
+    monkeypatch.setattr(BaseHTTPRequestHandler, 'send_header', lambda *args, **kwargs: None)
+    monkeypatch.setattr(BaseHTTPRequestHandler, 'end_headers', lambda *args, **kwargs: None)
+
+    with TemporaryDirectory() as tmp_dir:
+        ps = ParameterStudy(lambda p1, p2: p1 + p2, database_connector=tmp_dir)
+        ps.add_combinations([('p1', [1, 2])], constant_parameters={'p2': 3})
+        ps.run_server()
+        assert len(result_list) == 2
+
+
+def test_http_client(monkeypatch):
+    import urllib.request
+
+    call_count = 0
+
+    def simulation_dummy(p1, p2):
+        nonlocal call_count
+        call_count += 1
+
+    answers = [{"status": 'ok', "params": {'p1': 1, 'p2': 2}}, {},
+               {'status': 'finished'}, ]
+    next_answer = 0
+
+    def urlopen_mock(_, data):
+        nonlocal next_answer
+        data = data.decode()
+        assert 'client_name' in data
+        result = io.BytesIO(json.dumps(answers[next_answer]).encode())
+        next_answer += 1
+        return result
+
+    monkeypatch.setattr(urllib.request, 'urlopen', urlopen_mock)
+
+    with TemporaryDirectory() as tmp_dir:
+        ps = ParameterStudy(simulation_dummy, database_connector=tmp_dir)
+        ps.run_client('some_name')
+
+    assert call_count == 1
diff --git a/pystencils_tests/test_phasefield_dentritic_3D.ipynb b/pystencils_tests/test_phasefield_dentritic_3D.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..f3dc7fd914cd3c0a3f7f54ded12eb4652cf524c7
--- /dev/null
+++ b/pystencils_tests/test_phasefield_dentritic_3D.ipynb
@@ -0,0 +1,357 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *\n",
+    "sp.init_printing()\n",
+    "frac = sp.Rational"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Phase-field simulation of dentritic solidification in 3D\n",
+    "\n",
+    "This notebook tests the model presented in the dentritic growth tutorial in 3D. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target = 'cpu'\n",
+    "gpu = target == 'gpu'\n",
+    "domain_size = (25, 25, 25) if 'is_test_run' in globals() else (300, 300, 300)\n",
+    "\n",
+    "dh = ps.create_data_handling(domain_size=domain_size, periodicity=True)\n",
+    "φ_field = dh.add_array('phi', latex_name='φ')\n",
+    "φ_delta_field = dh.add_array('phidelta', latex_name='φ_D')\n",
+    "t_field = dh.add_array('T')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ε, m, δ, j, θzero, α, γ, Teq, κ, τ = sp.symbols(\"ε m δ j θ_0 α γ T_eq κ τ\")\n",
+    "εb = sp.Symbol(\"\\\\bar{\\\\epsilon}\")\n",
+    "discretize = ps.fd.Discretization2ndOrder(dx=0.03, dt=1e-5)\n",
+    "\n",
+    "φ = φ_field.center\n",
+    "T = t_field.center\n",
+    "d = ps.fd.Diff\n",
+    "\n",
+    "def f(φ, m):\n",
+    "    return φ**4 / 4 - (frac(1, 2) - m/3) * φ**3 + (frac(1,4)-m/2)*φ**2\n",
+    "\n",
+    "\n",
+    "\n",
+    "bulk_free_energy_density = f(φ, m)\n",
+    "interface_free_energy_density = ε ** 2 / 2 * (d(φ, 0) ** 2 + d(φ, 1) ** 2 + d(φ, 2) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here comes the major change, that has to be made for the 3D model: $\\epsilon$ depends on the interface normal, which can not be computed simply as atan() as in the 2D case"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\bar{\\epsilon} \\left(δ \\left(\\frac{{\\partial_{0} {{φ}_{C}}}^{4}}{\\left({\\partial_{0} {{φ}_{C}}}^{2} + {\\partial_{1} {{φ}_{C}}}^{2} + {\\partial_{2} {{φ}_{C}}}^{2}\\right)^{2}} + \\frac{{\\partial_{1} {{φ}_{C}}}^{4}}{\\left({\\partial_{0} {{φ}_{C}}}^{2} + {\\partial_{1} {{φ}_{C}}}^{2} + {\\partial_{2} {{φ}_{C}}}^{2}\\right)^{2}} + \\frac{{\\partial_{2} {{φ}_{C}}}^{4}}{\\left({\\partial_{0} {{φ}_{C}}}^{2} + {\\partial_{1} {{φ}_{C}}}^{2} + {\\partial_{2} {{φ}_{C}}}^{2}\\right)^{2}}\\right) + 1\\right)$$"
+      ],
+      "text/plain": [
+       "               ⎛  ⎛                     4                                     \n",
+       "               ⎜  ⎜             D(phi_C)                               D(phi_C\n",
+       "\\bar{\\epsilon}⋅⎜δ⋅⎜──────────────────────────────────── + ────────────────────\n",
+       "               ⎜  ⎜                                   2                       \n",
+       "               ⎜  ⎜⎛        2           2           2⎞    ⎛        2          \n",
+       "               ⎝  ⎝⎝D(phi_C)  + D(phi_C)  + D(phi_C) ⎠    ⎝D(phi_C)  + D(phi_C\n",
+       "\n",
+       " 4                                      4              ⎞    ⎞\n",
+       ")                               D(phi_C)               ⎟    ⎟\n",
+       "──────────────── + ────────────────────────────────────⎟ + 1⎟\n",
+       "               2                                      2⎟    ⎟\n",
+       " 2           2⎞    ⎛        2           2           2⎞ ⎟    ⎟\n",
+       ")  + D(phi_C) ⎠    ⎝D(phi_C)  + D(phi_C)  + D(phi_C) ⎠ ⎠    ⎠"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "n = sp.Matrix([d(φ, i) for i in range(3)])\n",
+    "nLen = sp.sqrt(sum(n_i**2 for n_i in n))\n",
+    "n = n / nLen\n",
+    "nVal = sum(n_i**4 for n_i in n)\n",
+    "σ = δ * nVal\n",
+    "\n",
+    "εVal = εb * (1 + σ)\n",
+    "εVal"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def m_func(temperature):\n",
+    "    return (α / sp.pi) * sp.atan(γ * (Teq - temperature))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "substitutions = {m: m_func(T),\n",
+    "                 ε: εVal}\n",
+    "\n",
+    "fe_i = interface_free_energy_density.subs(substitutions)\n",
+    "fe_b = bulk_free_energy_density.subs(substitutions)\n",
+    "\n",
+    "μ_if = ps.fd.expand_diff_full(ps.fd.functional_derivative(fe_i, φ), functions=[φ])\n",
+    "μ_b = ps.fd.expand_diff_full(ps.fd.functional_derivative(fe_b, φ), functions=[φ])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dF_dφ = μ_b + sp.Piecewise((μ_if, nLen**2 > 1e-10), (0, True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$$\\left \\{ \\pi : 3.14159265358979, \\quad T_{eq} : 1.0, \\quad \\bar{\\epsilon} : 0.01, \\quad j : 6, \\quad α : 0.9, \\quad γ : 10, \\quad δ : 0.3, \\quad θ_{0} : 0.2, \\quad κ : 1.8, \\quad τ : 0.0003\\right \\}$$"
+      ],
+      "text/plain": [
+       "{π: 3.14159265358979, T_eq: 1.0, \\bar{\\epsilon}: 0.01, j: 6, α: 0.9, γ: 10, δ:\n",
+       " 0.3, θ₀: 0.2, κ: 1.8, τ: 0.0003}"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "parameters = {\n",
+    "    Ï„: 0.0003,\n",
+    "    κ: 1.8,\n",
+    "    εb: 0.01,\n",
+    "    δ: 0.3,\n",
+    "    γ: 10,\n",
+    "    j: 6,\n",
+    "    α: 0.9,\n",
+    "    Teq: 1.0,\n",
+    "    θzero: 0.2,\n",
+    "    sp.pi: sp.pi.evalf()\n",
+    "}\n",
+    "parameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dφ_dt = - dF_dφ / τ\n",
+    "assignments = [\n",
+    "    ps.Assignment(φ_delta_field.center, discretize(dφ_dt.subs(parameters))),\n",
+    "]\n",
+    "φEqs = ps.simp.sympy_cse_on_assignment_list(assignments)\n",
+    "φEqs.append(ps.Assignment(φ, discretize(ps.fd.transient(φ) - φ_delta_field.center)))\n",
+    "\n",
+    "\n",
+    "temperatureEvolution = -ps.fd.transient(T) + ps.fd.diffusion(T, 1) + κ * φ_delta_field.center\n",
+    "temperatureEqs = [\n",
+    "    ps.Assignment(T, discretize(temperatureEvolution.subs(parameters)))\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\\left [ {{T}_{C}} \\leftarrow 0.0111111111111111 {{T}_{B}} + 0.933333333333333 {{T}_{C}} + 0.0111111111111111 {{T}_{E}} + 0.0111111111111111 {{T}_{N}} + 0.0111111111111111 {{T}_{S}} + 0.0111111111111111 {{T}_{T}} + 0.0111111111111111 {{T}_{W}} + 1.8 \\cdot 10^{-5} {{φ_D}_{C}}\\right ]$$"
+      ],
+      "text/plain": [
+       "[T_C := 0.0111111111111111â‹…T_B + 0.933333333333333â‹…T_C + 0.0111111111111111â‹…T_\n",
+       "E + 0.0111111111111111â‹…T_N + 0.0111111111111111â‹…T_S + 0.0111111111111111â‹…T_T +\n",
+       " 0.0111111111111111â‹…T_W + 1.8e-5â‹…phidelta_C]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "temperatureEqs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "φ_kernel = ps.create_kernel(φEqs, cpu_openmp=4, target=target).compile()\n",
+    "temperatureKernel = ps.create_kernel(temperatureEqs, cpu_openmp=4, target=target).compile()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def time_loop(steps):\n",
+    "    φ_sync = dh.synchronization_function(['phi'], target=target)\n",
+    "    temperature_sync = dh.synchronization_function(['T'], target=target)\n",
+    "    dh.all_to_gpu()\n",
+    "    for t in range(steps):\n",
+    "        φ_sync()\n",
+    "        dh.run_kernel(φ_kernel)\n",
+    "        temperature_sync()\n",
+    "        dh.run_kernel(temperatureKernel)\n",
+    "    dh.all_to_cpu()\n",
+    "\n",
+    "\n",
+    "def init(nucleus_size=np.sqrt(5)):\n",
+    "    for b in dh.iterate():\n",
+    "        x, y, z = b.cell_index_arrays\n",
+    "        x, y, z = x - b.shape[0] // 2, y - b.shape[1] // 2, z - b.shape[2] // 2\n",
+    "        b['phi'].fill(0)\n",
+    "        b['phi'][(x ** 2 + y ** 2 + z ** 2) < nucleus_size ** 2] = 1.0\n",
+    "        b['T'].fill(0.0)\n",
+    "\n",
+    "\n",
+    "def plot(slice_obj=ps.make_slice[:, :, 0.5]):\n",
+    "    plt.subplot(1, 3, 1)\n",
+    "    plt.scalar_field(dh.gather_array('phi', slice_obj).squeeze())\n",
+    "    plt.title(\"φ\")\n",
+    "    plt.colorbar()\n",
+    "    plt.subplot(1, 3, 2)\n",
+    "    plt.title(\"T\")\n",
+    "    plt.scalar_field(dh.gather_array('T', slice_obj).squeeze())\n",
+    "    plt.colorbar()\n",
+    "    plt.subplot(1, 3, 3)\n",
+    "    plt.title(\"∂φ\")\n",
+    "    plt.scalar_field(dh.gather_array('phidelta', slice_obj).squeeze())\n",
+    "    plt.colorbar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    Name|      Inner (min/max)|     WithGl (min/max)\n",
+      "----------------------------------------------------\n",
+      "       T|            (  0,  0)|            (  0,  0)\n",
+      "     phi|            (  0,  1)|            (  0,  1)\n",
+      "phidelta|            (inf,inf)|            (inf,inf)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "init()\n",
+    "plot()\n",
+    "print(dh)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if 'is_test_run' in globals():\n",
+    "    time_loop(2)\n",
+    "    assert np.isfinite(dh.max('phi'))\n",
+    "    assert np.isfinite(dh.max('T'))\n",
+    "    assert np.isfinite(dh.max('phidelta'))\n",
+    "else:\n",
+    "    vtk_writer = dh.create_vtk_writer('dentritic_growth_large', ['phi'])\n",
+    "    last = perf_counter()\n",
+    "    for i in range(300):\n",
+    "        time_loop(100)\n",
+    "        vtk_writer(i)\n",
+    "        print(\"Step \", i, perf_counter() - last, dh.max('phi'))\n",
+    "        last = perf_counter()"
+   ]
+  }
+ ],
+ "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/pystencils_tests/test_pickle_support.py b/pystencils_tests/test_pickle_support.py
new file mode 100644
index 0000000000000000000000000000000000000000..82d8e1f3607e21b9ab61a7ceafe0efffa7be0dee
--- /dev/null
+++ b/pystencils_tests/test_pickle_support.py
@@ -0,0 +1,16 @@
+from pystencils import Field, TypedSymbol
+from copy import copy, deepcopy
+
+
+def test_field_access():
+    field = Field.create_generic('some_field', spatial_dimensions=2, index_dimensions=0)
+    copy(field(0))
+    field_copy = deepcopy(field(0))
+    assert field_copy.field.spatial_dimensions == 2
+
+
+def test_typed_symbol():
+    ts = TypedSymbol("s", "double")
+    copy(ts)
+    ts_copy = deepcopy(ts)
+    assert str(ts_copy.dtype).strip() == "double"
diff --git a/pystencils_tests/test_random.py b/pystencils_tests/test_random.py
new file mode 100644
index 0000000000000000000000000000000000000000..2995cbdd6a81d289d020daf27d1903d0fd46b763
--- /dev/null
+++ b/pystencils_tests/test_random.py
@@ -0,0 +1,42 @@
+import numpy as np
+import pystencils as ps
+from pystencils.rng import PhiloxTwoDoubles, PhiloxFourFloats
+
+
+def test_philox_double():
+    for target in ('cpu', 'gpu'):
+        dh = ps.create_data_handling((2, 2), default_ghost_layers=0, default_target=target)
+        f = dh.add_array("f", values_per_cell=2)
+
+        dh.fill('f', 42.0)
+
+        philox_node = PhiloxTwoDoubles(dh.dim)
+        assignments = [philox_node,
+                       ps.Assignment(f(0), philox_node.result_symbols[0]),
+                       ps.Assignment(f(1), philox_node.result_symbols[1])]
+        kernel = ps.create_kernel(assignments, target=dh.default_target).compile()
+
+        dh.all_to_gpu()
+        dh.run_kernel(kernel, time_step=124)
+        dh.all_to_cpu()
+
+        arr = dh.gather_array('f')
+        assert np.logical_and(arr <= 1.0, arr >= 0).all()
+
+
+def test_philox_float():
+    for target in ('cpu', 'gpu'):
+        dh = ps.create_data_handling((2, 2), default_ghost_layers=0, default_target=target)
+        f = dh.add_array("f", values_per_cell=4)
+
+        dh.fill('f', 42.0)
+
+        philox_node = PhiloxFourFloats(dh.dim)
+        assignments = [philox_node] + [ps.Assignment(f(i), philox_node.result_symbols[i]) for i in range(4)]
+        kernel = ps.create_kernel(assignments, target=dh.default_target).compile()
+
+        dh.all_to_gpu()
+        dh.run_kernel(kernel, time_step=124)
+        dh.all_to_cpu()
+        arr = dh.gather_array('f')
+        assert np.logical_and(arr <= 1.0, arr >= 0).all()
diff --git a/pystencils_tests/test_simplification_strategy.py b/pystencils_tests/test_simplification_strategy.py
new file mode 100644
index 0000000000000000000000000000000000000000..957bee2ba7bd0ca79037b3fb8cfe8a95da702a15
--- /dev/null
+++ b/pystencils_tests/test_simplification_strategy.py
@@ -0,0 +1,43 @@
+import sympy as sp
+from pystencils import Assignment, AssignmentCollection
+from pystencils.simp import SimplificationStrategy, apply_on_all_subexpressions, \
+    subexpression_substitution_in_existing_subexpressions
+
+
+def test_simplification_strategy():
+    a, b, c, d, x, y, z = sp.symbols("a b c d x y z")
+    s0, s1, s2, s3 = sp.symbols("s_:4")
+    a0, a1, a2, a3 = sp.symbols("a_:4")
+
+    subexpressions = [
+        Assignment(s0, 2 * a + 2 * b),
+        Assignment(s1, 2 * a + 2 * b + 2 * c),
+        Assignment(s2, 2 * a + 2 * b + 2 * c + 2 * d),
+    ]
+    main = [
+        Assignment(a0, s0 + s1),
+        Assignment(a1, s0 + s2),
+        Assignment(a2, s1 + s2),
+    ]
+    ac = AssignmentCollection(main, subexpressions)
+
+    strategy = SimplificationStrategy()
+    strategy.add(subexpression_substitution_in_existing_subexpressions)
+    strategy.add(apply_on_all_subexpressions(sp.factor))
+
+    result = strategy(ac)
+    assert result.operation_count['adds'] == 7
+    assert result.operation_count['muls'] == 5
+    assert result.operation_count['divs'] == 0
+
+    # Trigger display routines, such that they are at least executed
+    report = strategy.show_intermediate_results(ac, symbols=[s0])
+    assert 's_0' in str(report)
+    report = strategy.show_intermediate_results(ac)
+    assert 's_{1}' in report._repr_html_()
+
+    report = strategy.create_simplification_report(ac)
+    assert 'Adds' in str(report)
+    assert 'Adds' in report._repr_html_()
+
+    assert 'factor' in str(strategy)
diff --git a/pystencils_tests/test_size_and_layout_checks.py b/pystencils_tests/test_size_and_layout_checks.py
new file mode 100644
index 0000000000000000000000000000000000000000..ecc454638e401004686bf41b5926ed16b3c2f8b9
--- /dev/null
+++ b/pystencils_tests/test_size_and_layout_checks.py
@@ -0,0 +1,117 @@
+import numpy as np
+import pytest
+from pystencils import Field, Assignment, fields, create_kernel
+import sympy as sp
+
+
+def test_size_check():
+    """Kernel with two fixed-sized fields creating with same size but calling with wrong size"""
+    src = np.zeros((20, 21, 9))
+    dst = np.zeros_like(src)
+
+    sym_src = Field.create_from_numpy_array("src", src, index_dimensions=1)
+    sym_dst = Field.create_from_numpy_array("dst", dst, index_dimensions=1)
+    update_rule = Assignment(sym_dst(0), sym_src[-1, 1](1) + sym_src[1, -1](2))
+    ast = create_kernel([update_rule])
+    func = ast.compile()
+
+    # change size of src field
+    new_shape = [a - 7 for a in src.shape]
+    src = np.zeros(new_shape)
+    dst = np.zeros(new_shape)
+
+    with pytest.raises(ValueError) as e:
+        func(src=src, dst=dst)
+    assert 'Wrong shape' in str(e)
+
+
+def test_fixed_size_mismatch_check():
+    """Create kernel with two differently sized but constant fields """
+    src = np.zeros((20, 21, 9))
+    dst = np.zeros((21, 21, 9))
+
+    sym_src = Field.create_from_numpy_array("src", src, index_dimensions=1)
+    sym_dst = Field.create_from_numpy_array("dst", dst, index_dimensions=1)
+    update_rule = Assignment(sym_dst(0),
+                             sym_src[-1, 1](1) + sym_src[1, -1](2))
+
+    with pytest.raises(ValueError) as e:
+        create_kernel([update_rule])
+    assert 'Differently sized field accesses' in str(e)
+
+
+def test_fixed_and_variable_field_check():
+    """Create kernel with two variable sized fields - calling them with different sizes"""
+    src = np.zeros((20, 21, 9))
+
+    sym_src = Field.create_from_numpy_array("src", src, index_dimensions=1)
+    sym_dst = Field.create_generic("dst", spatial_dimensions=2, index_dimensions=1)
+
+    update_rule = Assignment(sym_dst(0),
+                             sym_src[-1, 1](1) + sym_src[1, -1](2))
+
+    with pytest.raises(ValueError) as e:
+        create_kernel(update_rule)
+    assert 'Mixing fixed-shaped and variable-shape fields' in str(e)
+
+
+def test_two_variable_shaped_fields():
+    src = np.zeros((20, 21, 9))
+    dst = np.zeros((22, 21, 9))
+
+    sym_src = Field.create_generic("src", spatial_dimensions=2, index_dimensions=1)
+    sym_dst = Field.create_generic("dst", spatial_dimensions=2, index_dimensions=1)
+    update_rule = Assignment(sym_dst(0),
+                             sym_src[-1, 1](1) + sym_src[1, -1](2))
+
+    ast = create_kernel([update_rule])
+    func = ast.compile()
+
+    with pytest.raises(TypeError) as e:
+        func(src=src, dst=dst)
+    assert 'must have same' in str(e)
+
+
+def test_ssa_checks():
+    f, g = fields("f, g : double[2D]")
+    a, b, c = sp.symbols("a b c")
+
+    with pytest.raises(ValueError) as e:
+        create_kernel([Assignment(c, f[0, 1]),
+                       Assignment(c, f[1, 0]),
+                       Assignment(g[0, 0], c)])
+    assert 'Assignments not in SSA form' in str(e)
+
+    with pytest.raises(ValueError) as e:
+        create_kernel([Assignment(c, a + 3),
+                       Assignment(a, 42),
+                       Assignment(g[0, 0], c)])
+    assert 'Symbol a is written, after it has been read' in str(e)
+
+    with pytest.raises(ValueError) as e:
+        create_kernel([Assignment(c, c + 1),
+                       Assignment(g[0, 0], c)])
+    assert 'Symbol c is written, after it has been read' in str(e)
+
+
+def test_loop_independence_checks():
+    f, g = fields("f, g : double[2D]")
+    v = fields("v(2) : double[2D]")
+
+    with pytest.raises(ValueError) as e:
+        create_kernel([Assignment(g[0, 1], f[0, 1]),
+                       Assignment(g[0, 0], f[1, 0])])
+    assert 'Field g is written at two different locations' in str(e)
+
+    # This is allowed - because only one element of g is accessed
+    create_kernel([Assignment(g[0, 2], f[0, 1]),
+                   Assignment(g[0, 2], 2 * g[0, 2])])
+
+    create_kernel([Assignment(v[0, 2](1), f[0, 1]),
+                   Assignment(v[0, 1](0), 4),
+                   Assignment(v[0, 2](1), 2 * v[0, 2](1))])
+
+    with pytest.raises(ValueError) as e:
+        create_kernel([Assignment(g[0, 1], 3),
+                       Assignment(f[0, 1], 2 * g[0, 2])])
+    assert 'Field g is read at (0, 2) and written at (0, 1)' in str(e)
diff --git a/pystencils_tests/test_size_and_layout_checks_llvm.py b/pystencils_tests/test_size_and_layout_checks_llvm.py
new file mode 100644
index 0000000000000000000000000000000000000000..96b9bc05427aea1b34fcbf71292aa0d3a03cd809
--- /dev/null
+++ b/pystencils_tests/test_size_and_layout_checks_llvm.py
@@ -0,0 +1,80 @@
+import numpy as np
+from pystencils import Field, Assignment
+from pystencils.llvm import create_kernel, make_python_function
+
+
+def test_size_check():
+    """Kernel with two fixed-sized fields creating with same size but calling with wrong size"""
+    src = np.zeros((20, 21, 9))
+    dst = np.zeros_like(src)
+
+    sym_src = Field.create_from_numpy_array("src", src, index_dimensions=1)
+    sym_dst = Field.create_from_numpy_array("dst", dst, index_dimensions=1)
+    update_rule = Assignment(sym_dst(0),
+                             sym_src[-1, 1](1) + sym_src[1, -1](2))
+    ast = create_kernel([update_rule])
+    func = make_python_function(ast)
+
+    # change size of src field
+    new_shape = [a - 7 for a in src.shape]
+    src = np.zeros(new_shape)
+    dst = np.zeros(new_shape)
+
+    try:
+        func(src=src, dst=dst)
+        assert False, "Expected ValueError because fields with different sized where passed"
+    except ValueError:
+        pass
+
+
+def test_fixed_size_mismatch_check():
+    """Create kernel with two differently sized but constant fields """
+    src = np.zeros((20, 21, 9))
+    dst = np.zeros((21, 21, 9))
+
+    sym_src = Field.create_from_numpy_array("src", src, index_dimensions=1)
+    sym_dst = Field.create_from_numpy_array("dst", dst, index_dimensions=1)
+    update_rule = Assignment(sym_dst(0),
+                             sym_src[-1, 1](1) + sym_src[1, -1](2))
+
+    try:
+        create_kernel([update_rule])
+        assert False, "Expected ValueError because fields with different sized where passed"
+    except ValueError:
+        pass
+
+
+def test_fixed_and_variable_field_check():
+    """Create kernel with two variable sized fields - calling them with different sizes"""
+    src = np.zeros((20, 21, 9))
+
+    sym_src = Field.create_from_numpy_array("src", src, index_dimensions=1)
+    sym_dst = Field.create_generic("dst", spatial_dimensions=2, index_dimensions=1)
+
+    update_rule = Assignment(sym_dst(0),
+                             sym_src[-1, 1](1) + sym_src[1, -1](2))
+
+    try:
+        create_kernel([update_rule])
+        assert False, "Expected ValueError because fields with different sized where passed"
+    except ValueError:
+        pass
+
+
+def test_two_variable_shaped_fields():
+    src = np.zeros((20, 21, 9))
+    dst = np.zeros((22, 21, 9))
+
+    sym_src = Field.create_generic("src", spatial_dimensions=2, index_dimensions=1)
+    sym_dst = Field.create_generic("dst", spatial_dimensions=2, index_dimensions=1)
+    update_rule = Assignment(sym_dst(0),
+                             sym_src[-1, 1](1) + sym_src[1, -1](2))
+
+    ast = create_kernel([update_rule])
+    func = make_python_function(ast)
+
+    try:
+        func(src=src, dst=dst)
+        assert False, "Expected ValueError because fields with different sized where passed"
+    except ValueError:
+        pass
diff --git a/pystencils_tests/test_sliced_iteration.py b/pystencils_tests/test_sliced_iteration.py
new file mode 100644
index 0000000000000000000000000000000000000000..756937998171a56a31cb534d7f06508d1b31febc
--- /dev/null
+++ b/pystencils_tests/test_sliced_iteration.py
@@ -0,0 +1,54 @@
+import numpy as np
+import sympy as sp
+from pystencils import TypedSymbol, make_slice, Assignment, create_kernel, Field
+from pystencils.simp import sympy_cse_on_assignment_list
+
+
+def test_sliced_iteration():
+    size = (4, 4)
+    src_arr = np.ones(size)
+    dst_arr = np.zeros_like(src_arr)
+    src_field = Field.create_from_numpy_array('src', src_arr)
+    dst_field = Field.create_from_numpy_array('dst', dst_arr)
+
+    a, b = sp.symbols("a b")
+    update_rule = Assignment(dst_field[0, 0],
+                             (a * src_field[0, 1] + a * src_field[0, -1] +
+                              b * src_field[1, 0] + b * src_field[-1, 0]) / 4)
+
+    x_end = TypedSymbol("x_end", "int")
+    s = make_slice[1:x_end, 1]
+    x_end_value = size[1] - 1
+    kernel = create_kernel(sympy_cse_on_assignment_list([update_rule]), iteration_slice=s).compile()
+
+    kernel(src=src_arr, dst=dst_arr, a=1.0, b=1.0, x_end=x_end_value)
+
+    expected_result = np.zeros(size)
+    expected_result[1:x_end_value, 1] = 1
+    np.testing.assert_almost_equal(expected_result, dst_arr)
+
+
+def test_sliced_iteration_llvm():
+    size = (4, 4)
+    src_arr = np.ones(size)
+    dst_arr = np.zeros_like(src_arr)
+    src_field = Field.create_from_numpy_array('src', src_arr)
+    dst_field = Field.create_from_numpy_array('dst', dst_arr)
+
+    a, b = sp.symbols("a b")
+    update_rule = Assignment(dst_field[0, 0],
+                             (a * src_field[0, 1] + a * src_field[0, -1] +
+                              b * src_field[1, 0] + b * src_field[-1, 0]) / 4)
+
+    x_end = TypedSymbol("x_end", "int")
+    s = make_slice[1:x_end, 1]
+    x_end_value = size[1] - 1
+    import pystencils.llvm as llvm_generator
+    ast = llvm_generator.create_kernel(sympy_cse_on_assignment_list([update_rule]), iteration_slice=s)
+    kernel = llvm_generator.make_python_function(ast)
+
+    kernel(src=src_arr, dst=dst_arr, a=1.0, b=1.0, x_end=x_end_value)
+
+    expected_result = np.zeros(size)
+    expected_result[1:x_end_value, 1] = 1
+    np.testing.assert_almost_equal(expected_result, dst_arr)
diff --git a/pystencils_tests/test_small_block_benchmark.ipynb b/pystencils_tests/test_small_block_benchmark.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..b18c4bbaf893c6cc04eec8e9880eb8884c863751
--- /dev/null
+++ b/pystencils_tests/test_small_block_benchmark.ipynb
@@ -0,0 +1,184 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *\n",
+    "from time import perf_counter\n",
+    "from statistics import median\n",
+    "from functools import partial"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Benchmark for Python call overhead"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAATcAAAAUBAMAAAAaQ2ctAAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAdt3NMolEIpm7EKvvVGZvmWXoAAAACXBIWXMAAA7EAAAOxAGVKw4bAAADSElEQVRIDc2VTUhUURiG39G583Pv3NEEyZ2DFfSzUEKCXORsgqCFIzShG73UNnAoImkRA5GM2MJFUEbQ1WhlMBYVkaZDCyNRmF2BENOiVdCPU4Zi3r57zjgz95yjzLKzuHPO+33vc9859w9Nnfg/R/S4hfPA8OgdRb4zkjbZPCJpXNB6z4mVYLI/j2BmIi4WgGSzK8p81sks+r4+C5obTp/BoMUKnsMRz8pdpGHkJdFcAvQTuCkWhmFuYxrauljAIyvUQaLMh8tilhDwhoczbERyEsL3XpTMAoIu1TOmxzaBcBoTHpUWrXms4TWwLBZwD+FxQOaDsZjlE3CFh4vEYPySEDdOipI2Dj0mivBRuKGUJOOSpRfxFliIC7XAHybIfApMLGbpB6Z4uPpNVbiEFC6wYWsF4Uwc+EBSXYEua7cthwvnWLfM5yxmGbqPAR6OeusosndEU1I4LGwPeJvclftvi6dbLLkylXC1dluoNHT20nOl4jMWsxjOl0I53BDjVFMmIYfTnK7qFj6ncHqxgBWpcvWwTVrgt1jInkIkDxW/FM61DBbtcrhjIgEJRbjVC1uW1OiGc2zctqWKtkhS3YyoZzcRWlLyS+HIYr5sX9wJF0qLBDMuh4vOoJWedWG4l3UN+G4JOi2XbSAjyQ0xRNdVfH6LMMtX+LZs9p4DWiTCY8jhIin4/0qdbrgDFK4gVK4BD/PwpQWZ9rID0W0VvxTOtbwDevI8nJkGoTxjdXZ266lHAbK0nhc0DpxT7Bxdagr3EUHxNWPkaOdU/FI4slz/ARgFHo4+JPulk0J6CdPO4a7U5+5cD91zYoHs7Sl/Gj4xnJ/uuRx1S3wejllo58IpFi54KDkWozemMDboKfRIgS5EGwWNA42EvoJsh6f7G8yfuJzseyYW8AJP8tQq8TmLWS7a+MwfiHrHcWJosz1s9Dvzonb21ghELTRXpEvdNxZH3VEPIJAZtdDtOGtiAVrmOXUq+IzFLP5XOx9+zjTF7Se5Vo0TPvAf+bhrQcWv2Pk9x9ZaRS3PatW4IVH2CZNdCyp+xVsVbrKilme1asygN5Z93smuBfpM7DWqwhUUfbVqzBpVAPYuQMWvUChc08HK8r+a+dqsf+S+/F/QsHg/AAAAAElFTkSuQmCC\n",
+      "text/latex": [
+       "$$\\left [ 2, \\quad 4, \\quad 8, \\quad 16, \\quad 32, \\quad 64, \\quad 128\\right ]$$"
+      ],
+      "text/plain": [
+       "[2, 4, 8, 16, 32, 64, 128]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "inner_repeats = 100\n",
+    "outer_repeats = 5\n",
+    "sizes = [2**i for i in range(1, 8)]\n",
+    "sizes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def benchmark_pure(domain_size, extract_first=False):\n",
+    "    src = np.zeros(domain_size)\n",
+    "    dst = np.zeros_like(src)\n",
+    "    f_src, f_dst = ps.fields(\"src, dst\", src=src, dst=dst)\n",
+    "    kernel = ps.create_kernel(ps.Assignment(f_dst.center, f_src.center)).compile()\n",
+    "    if extract_first:\n",
+    "        kernel = kernel.kernel\n",
+    "        start = perf_counter()\n",
+    "        for i in range(inner_repeats):\n",
+    "            kernel(src=src, dst=dst)\n",
+    "            src, dst = dst, src\n",
+    "        end = perf_counter()\n",
+    "    else:\n",
+    "        start = perf_counter()\n",
+    "        for i in range(inner_repeats):\n",
+    "            kernel(src=src, dst=dst)\n",
+    "            src, dst = dst, src\n",
+    "        end = perf_counter()\n",
+    "    return (end - start) / inner_repeats\n",
+    "\n",
+    "def benchmark_datahandling(domain_size, parallel=False):\n",
+    "    dh = ps.create_data_handling(domain_size, parallel=parallel)\n",
+    "    f_src = dh.add_array('src')\n",
+    "    f_dst = dh.add_array('dst')\n",
+    "    kernel = ps.create_kernel(ps.Assignment(f_dst.center, f_src.center)).compile()\n",
+    "    start = perf_counter()\n",
+    "    for i in range(inner_repeats):\n",
+    "        dh.run_kernel(kernel)\n",
+    "        dh.swap('src', 'dst')\n",
+    "    end = perf_counter()\n",
+    "    return (end - start) / inner_repeats\n",
+    "   \n",
+    "    \n",
+    "name_to_func = {\n",
+    "    'pure_extract': partial(benchmark_pure, extract_first=True),\n",
+    "    'pure_no_extract': partial(benchmark_pure, extract_first=False),\n",
+    "    'dh_serial': partial(benchmark_datahandling, parallel=False),\n",
+    "    'dh_parallel': partial(benchmark_datahandling, parallel=True),\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Computing size  2\n",
+      "Computing size  4\n",
+      "Computing size  8\n",
+      "Computing size  16\n",
+      "Computing size  32\n",
+      "Computing size  64\n",
+      "Computing size  128\n"
+     ]
+    }
+   ],
+   "source": [
+    "result = {'block_size': [],\n",
+    "          'name': [],\n",
+    "          'time': []}\n",
+    "\n",
+    "for bs in sizes:\n",
+    "    print(\"Computing size \", bs)\n",
+    "    for name, func in name_to_func.items():\n",
+    "        for i in range(outer_repeats):\n",
+    "            time = func((bs, bs))\n",
+    "            result['block_size'].append(bs)\n",
+    "            result['name'].append(name)\n",
+    "            result['time'].append(time)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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ptb1yc3PZu3cvgYGBpY7t1asX7dq1AyA0NBSHw0GzZs0IDAykU6dOAIwZM4bnnnuO++67r8T43bt3s337dgYMGACcuiW5bdu2AAQFBTFq1Cji4uJITU2lcePGJcYDeHl5MXToUNf3NWvWkJycTH5+Pjk5OQQFBREdHU1WVhaDBw8GwNvbu9yfiYhIbaWCV0REpA6x1n4IfHhW24wztguAm8sYOwuYVZGYRe37ObWKc3n5RFck79rs1ILUxb83bNiQkydPAlBQUHwh6gsuuMC1ba3l2WefJTY2lopo0qSJa9vLywun0+m6hbgirLUEBQWRmppa6v5t27bRokULfvnllzJjeHt74+XlBZw6t7vuuov09HTat2/PzJkzKSgoqFROIiK1mUfd0iwiIiJSWT/88IOrgHzrrbfo27cvAQEBZGRkAPDuu++WOTY2Npa5c+dSWFgIwJ49ezhy5Eiljt+lSxccDgf79u0D4LXXXuOaa64ptW/nzp359ddfXfkWFhayY8epCfn33nuPgwcPsm7dOiZOnMhvv/0GQLNmzTh8+HCp8U4X8/7+/uTl5blmqi+88ELatWvH0qVLATh27Bj5+fnlxhIRqY00wysiIiK1grteI9S1a1deeeUVxo0bR8eOHRk/fjy9evXijjvu4LHHHiMy8uw3P/3X2LFjcTgchIWFYa2lVatWriKxory9vXn55Ze5+eabXYtP/fWvfy21b+PGjVm8eDETJ04kNzcXp9PJfffdx8UXX8yUKVNYtWoV7du35+677+bee+/llVdeISEhgRtvvJG2bdu6nuM9rUWLFtx5550EBwcTEBBARESEa99rr73GuHHjmDFjBo0aNeKdd94hJCSEhg0b0r17d+Lj4/Ucr4jUesYTb1kJDw+36el1a+2M0aNHk5WVxSWXXMKrr77q7nRE5Az6/ay79jw5u1L9Oz1Q+itljTEZ1to6uQpxbVHatXnXrl107drVTRmd4nA4uOmmm9i+fbtb8/AUteH/qYjUPb/n31oVvTbrlmYRERERERHxSLqlWUREROqtgICAKp/d3bZtG6NGjSrW1qRJEzZu3FipOIMHDy7xiqMnnniiwgtkiYiICl4RERGRKhUcHMyWLVvOO86SJUuqIBsRkfpNtzSLiIiIiIiIR1LBKyIiIiIiIh5JBa+IiIiIiIh4JBW8IiIiIiIi4pG0aJWIiIjUCsmrk6s0XuK1iZXqP3PmTJo2bcqKFSuYPXs24eHV/+rlsWPHcv/993PllVeW2Sc6OrrG8hER8TQqeEVERETc4MSJE7z00kvuTkNExKOp4HWDPU/OLtFWeOiQ6/Ps/Z0emFwjeYlI/f79TExMJDs7mzZt2pCcXLUzbSK11axZs3j11Vdp3749rVq1omfPngC888473HXXXfz222/Mnz+fq6++utTxO3bs4C9/+QvHjx/n5MmTvPvuu3Ts2JHXX3+dOXPmcPz4cSIjI3n++efx8vKiadOm3H///XzyySf8v//3/5g+fbpr9nb8+PGkpaVx9OhRhg0bxsMPP1yTPwoREY+kZ3hFRASA7OxssrKyyM7OdncqIjUiIyODhQsXsnnzZt577z3S0tJc+5xOJ5s2beKZZ54pt/B84YUXuPfee9myZQvp6em0a9eOXbt28fbbb7Nhwwa2bNmCl5cXb7zxBgBHjhyhW7dubNy4kb59+xaLNWvWLNLT09m6dSuff/45W7durZ4TFxGpRzTDKyJSD9XnmWyR09avX8/gwYPx9fUFYODAga59Q4YMAaBnz544HI4yY/Tp04dZs2aRmZnJkCFD6NixI6tWrSIjI4OIiAgAjh49SuvWrQHw8vJi6NChpcZatGgR8+bNw+l08vPPP7Nz505CQkKq4lRFROotFbwiIiJSbxljSm1v0qQJcKpAdTqdZY4fMWIEkZGRfPDBB8TGxvLSSy9hrWXMmDH8/e9/L9Hf29sbLy+vEu3fffcds2fPJi0tjYsuuoj4+HgKCgp+51mJiMhpKnhFRAQAPx+fYp8inq5fv37Ex8czZcoUnE4ny5cvZ9y4cZWKsX//fi6//HImTpzI/v372bp1KzExMQwaNIhJkybRunVrcnJyOHz4MJdddlmZcf7zn/9wwQUX0Lx5c3755Rc++ugjoqOjz/MMRURqn5q+y0wFr4iIADAxope7U5B6rrKvETpfYWFhDB8+nNDQUC677LIyF6Yqz9tvv83rr79Oo0aNaNOmDTNmzKBly5YkJSURExPDyZMnadSoEc8991y5BW/37t3p0aMHQUFBXH755URFRZ3PqYmISBEVvCIiIlJvTZs2jWnTphVrmzz5v7MJ/v7+5T7DO3XqVKZOnVqiffjw4QwfPrxEe15eXrHva9eudW2npKSUeowz+4iISOVolWYRERERERHxSJrhlRql93yKiEhd9Mknn/Dggw8WawsMDGTJkiVuykhERCpCBa/UqNPv+RQREalLYmNjiY2NdXcaIiJSSbqlWURERERERDySCl4RERERERHxSCp4RURERERExCPpGV4RkXPw8/Ep9iki1WPPk7OrNF6nByafu5OIiHg0FbxSbUr7h0vhoUOuz7P36x8mdU99WXV7YkQvd6cgIjVg5syZNG3alBUrVjB79mzCw8Pdmk98fDw33XQTw4YNIzo6+pw5VaSPiEh941EFrzEmDojr0KGDu1MR8Til/QHjx127+Hd+vv6AISLyO504cQIvLy93pyEi4rE86hlea+1ya21C8+bN3Z1Kpfn5+NDa11e3THqIxMRERo8eTWJiortTERGRcsyaNYvOnTtz/fXXs3v3blf7O++8Q69evejUqRPr168vc3xKSgqDBg3ihhtuoHPnzjz88MOufX/+85/p2bMnQUFBzJs3z9XetGlTZsyYQWRkJKmpqTzyyCNERETQrVs3EhISsNaWm/PKlSvp06cPYWFh3HzzzeTl5Z3HT0BExLN51AxvXaZbJuuu+jzzqWdbRaQuy8jIYOHChWzevBmn00lYWBg9e/YEwOl0smnTJj788EMefvhhPvvsszLjbNq0ie3bt+Pr60tERAR/+tOfCA8PZ8GCBbRs2ZKjR48SERHB0KFD8fPz48iRI3Tr1o1HHnkEgCuvvJIZM2YAMGrUKFasWEFcXFypxzpw4ABJSUl89tlnXHDBBTzxxBM89dRTrvEiIlKcCl6pUSqQPIv+UCMiddn69esZPHgwvr6+AAwcONC1b8iQIQD07NkTh8NRbpwBAwbg5+fnGvfFF18QHh7OnDlzWLJkCQA//vgje/fuxc/PDy8vL4YOHeoav2bNGpKTk8nPzycnJ4egoKAyC96vvvqKnTt3EhUVBcDx48fp06fP7/sBiIjUAyp4pUbVlwJJhb2ISN1gjCm1vUmTJgB4eXnhdDorFcMYw9q1a/nss89ITU3F19eX6OhoCgoKAPD29nY9t1tQUMBdd91Feno67du3Z+bMma5+pbHWMmDAAN56660Kn6OISH2mglekGtSXwl5EpCrV9CMf/fr1Iz4+nilTpuB0Olm+fDnjxo2rdJxPP/2UnJwcfHx8WLp0KQsWLCArK4uLLroIX19fvvnmG7766qtSx54ubv39/cnLy2Px4sUMGzaszGP17t2bCRMmsG/fPjp06EB+fj6ZmZl06tSp0nmLiNQHKnhFRESkXgoLC2P48OGEhoZy2WWXcfXVV/+uOH379mXUqFHs27ePESNGEB4eTnBwMC+88AIhISF07tyZ3r17lzq2RYsW3HnnnQQHBxMQEEBERES5x2rVqhUpKSnceuutHDt2DICkpCQVvCIiZVDBKyIiIvXWtGnTmDZtWrG2yZP/O9Ps7+9/zmd4W7duzT/+8Y9ibU2aNOGjjz4qtf/ZqyonJSWRlJRUol9KSopre+3ata7ta6+9lrS0tBL9z+wjIiKneNRriURERERERERO0wyviIiIyDl88sknPPjgg8XaAgMDWbJkCfHx8e5JSkREzkkFr4iIiLiNtbbMlZJrk9jYWGJjY92dRq1mrXV3CiIiJeiWZhEREXELb29vDh48qELJA1hrOXjwIN7e3u5ORUSkGM3wioiIiFu0a9eOzMxMfv31V3enIlXA29ubdu3auTsNEZFiVPCKiIiIWzRq1IjAwEB3pyEiIh5MtzSLiIiIiIiIR9IMr4iIiIiIiLiNn49Psc+qpIJXRERERERE3GZiRK9qi61bmkVERERERMQjqeAVERERERERj6SCV0RERERERDySCl4RERERERHxSCp4RURERERExCOp4BURERERERGPpIJXREREREREPJIKXhEREREREfFIKnhFRERERETEI6ngFREREREREY+kgldEREREREQ8kgpeERERERER8UgqeEVERERERMQjqeAVERERERERj6SCV0RERERERDySCl4RERERERHxSCp4RURERERExCOp4BURERERERGPpIJXRESkDjHG3GCM2W2M2WeMmVLK/ibGmLeL9m80xgScsW9qUftuY0zsuWIaYwKLYuwtitm4qP2vxphtxpgtxpgvjDFXVu9Zi4iI/D4qeEVEROoIY4wX8BxwI3AlcGspxeYdwCFrbQfgaeCJorFXArcAQcANwPPGGK9zxHwCeNpa2xE4VBQb4E1rbbC1NhRIBp6qlhMWERE5Typ4RUSkzktMTGT06NEkJia6O5Xq1gvYZ63db609DiwEBp3VZxDwStH2YuA6Y4wpal9orT1mrf0O2FcUr9SYRWOuLYpBUcw/A1hr/3PG8S4AbBWfp4iISJVo6O4EREREzld2djZZWVnuTqMmXAL8eMb3TCCyrD7WWqcxJhfwK2r/6qyxlxRtlxbTD/jNWusspT/GmAnA/UBjThXGJRhjEoAEgEsvvbRCJygiIlKVNMMrIiJSd5hS2s6eXS2rT1W1n9qw9jlr7RXAg8D00pK11s6z1oZba8NbtWpVWhcREZFqpRleERGpU5JXJ5doO3T0kOvzzP1/9ry/62YC7c/43g74qYw+mcaYhkBzIOccY0trPwC0MMY0LJrlLe1YcOoW6Lm/62xERESqmcf9S0BERMSDpQEdi1ZPbsypRaiWndVnGTCmaHsYsNpaa4vabylaxTkQ6AhsKitm0Zg1RTEoivk+gDGm4xnH+xOwt4rPU0REpEpohldERKSOKHom927gE8ALWGCt3WGMeQRIt9YuA+YDrxlj9nFqZveWorE7jDGLgJ2AE5hgrT0BUFrMokM+CCw0xiQBm4tiA9xtjLkeKOTU6s2nC2wRkRqRmJhIdnY2bdq0ITm55J0/Iqep4BUREalDrLUfAh+e1TbjjO0C4OYyxs4CZlUkZlH7fk6t4nx2+72VTrwO0j+oRWqverRYoZwnFbwiIlLn+TT3KfYpUhX0D2oRkbpPBa+IiNR54SPC3Z2CiIiI1EIqeEVEpNrp1lARERFxBxW8IiJS7XRrqIiIiLhDvSl4CwsLyczMpKCgwN2pUHj11ZXqv2vXrmrKpHpV53l6e3vTrl07GjVqVNm0RERERESknqg3BW9mZibNmjUjICAAY4xbcynIzq5Uf+82baopk+pVXedpreXgwYNkZmYSGBj4e1ITkVpOt0CLiIhIVWjg7gTOxRgTbYxZb4x5wRgT/XvjFBQU4Ofn5/ZiV86fMQY/P79aMVsvItXj9C3Q2ZX8w5mIiIjImaq14DXGLDDG/NsYs/2s9huMMbuNMfuMMVPOEcYCeYA3kHme+ZzPcKlF9P9SRERERETOpbpvaU4B/gG8errBGOMFPAcM4FQBm2aMWQZ4AX8/a/ztwHpr7efGmIuBp4CR1ZyziIjUoJwVD5doO3kkx/VZYr+v3rUrIiIiFVOtBa+1dp0xJuCs5l7APmvtfgBjzEJgkLX278BN5YQ7BDQpa6cxJgFIALj00kvPI2sRERERERHxBO54hvcS4MczvmcWtZXKGDPEGPMi8BqnZotLZa2dZ60Nt9aGt2rVqsqSFRERERERkbrJHas0l/bwpS2rs7X2PeC96kun9vr+xx8ZNGIEV0dH8+WXX3LJJZfw/vvv8/rrrzNv3jyOHz9Ohw4deO211/D19SU+Ph4fHx+++eYbvv/+e15++WVeeeUVUlNTiYyMJCUlBYCVK1fy0EMPceznz7XMAAAgAElEQVTYMa644gpefvllmjZt6t6TFRGPMmtxarHvOXkFrs+z9433rrG0REREpJ5xxwxvJtD+jO/tgJ/ckEedsO+775gwYQI7duygRYsWvPvuuwwZMoS0tDS+/vprunbtyvz58139Dx06xOrVq3n66aeJi4tj0qRJ7Nixg23btrFlyxYOHDhAUlISn332Gf/6178IDw/nqaeecuMZioiU1OrCJrRt4UOrC8t8kkVERETknNwxw5sGdDTGBAJZwC3ACDfkUScEXHopoaGhAPTs2ROHw8H27duZPn06v/32G3l5ecTGxrr6x8XFYYwhODiYiy++mODgYACCgoJwOBxkZmayc+dOoqKiADh+/Dh9+vSp+RMTESnH/w0NcXcKIiIi4gGqteA1xrwFRAP+xphM4CFr7XxjzN3AJ5xamXmBtXZHdeZRlzVp3Ni17eXlxdGjR4mPj2fp0qV0796dlJQU1q5d+9/+TU7NhjRo0MC1ffq70+nEy8uLAQMG8NZbb9XYOYiIiIiIiLhDtd7SbK291Vrb1lrbyFrbzlo7v6j9Q2ttJ2vtFdbaWdWZgyc6fPgwbdu2pbCwkDfeeKNSY3v37s2GDRvYt28fAPn5+ezZs6c60hQREREREXErdzzDK+fp0UcfJTIykgEDBtClS5dKjW3VqhUpKSnceuuthISE0Lt3b7755ptqylRERERERMR93PEMb7UxxsQBcR06dHB3KlXisvbtyTjjduXJkye7tsePH1+i/+lVmAECAgLYvn17qfuuvfZa0tLSqjRXERERERGR2sajZnittcuttQnNmzd3dyoiInIG72Yt8Gnuh3ezFu5ORUREROoRj5rhFRGR2qlH3F/cnYKIiIjUQx41wysiIiIiIiJymgpeERERERER8UgqeEVERERERMQjqeAVERERERERj1RvF62atTi1SuNNG9anSuPVNIfDwZdffsmIESOqJN7SpUu57KKL6Nq5c5XEExERERERqSzN8NYRTqezWuM7HA7efPPNKjv20qVL2bV37/mmJSIiIiIi8rt5VMFrjIkzxszLzc11dyqlcjgcdOnShbETJxJx7bXcOnYs+fn5dI6I4MDBgwBkbNlCzJAhACTNns2EyZOJiYlh9OjRnDhxggceeICIiAhCQkJ48cUXyz3ek08+6er70EMPAZCWlkZISAgFBQUcOXKEoKAgtm/fzpQpU1i/fj2hoaE8/fTTpKSkcPPNNxMXF0dMTAx5eXlcd911hIWFERwczPvvv+86zquvvkpISAjdu3dn1KhRfPnllyxbtoy/PfIIkddfz36Ho3p+oCIiIiIiIuXwqFuarbXLgeXh4eF3ujuXsuzevZvnk5O5qlcvxk2axIuvvFJu/81bt7Jh40Z8fHyYN28ezZs3Jy0tjWPHjhEVFUVMTAyBgYElxq1cuZK9e/eyadMmrLUMHDiQdevW0a9fPwYOHMj06dM5evQot912G926dePxxx9n9uzZrFixAoCUlBRSU1PZunUrLVu2xOl0smTJEi688EIOHDhA7969GThwIDt37mTWrFls2LABf39/cnJyaNmyJQMHDiSmb1+G3HRTtfwcRUREREREzsWjCt66oH379lzVqxcAtw4dynMvvVRu/z/FxuLj4wOcKmK3bt3K4sWLAcjNzWXv3r1lFrwrV66kR48eAOTl5bF371769evHjBkziIiIwNvbmzlz5pR57AEDBtCyZUsArLX87W9/Y926dTRo0ICsrCx++eUXVq9ezbBhw/D39wdw9RcREREREXE3Fbw1zBhT4nvDhg05aS0ABceOFdvv6+vr2rbW8uyzzxIbG3vO41hrmTp1KuPGjSuxLycnh7y8PAoLCykoKOCCCy4oNcaZ7W+88Qa//vorGRkZNGrUiICAAAoKCrDWljgnERERERGR2sCjnuGtC3744Qe+Sk8HYNGSJVwVGcll7duz+euvAVj6wQdljo2NjWXu3LkUFhYCsGfPHo4cOVJm3wULFpCXlwdAVlYW//73vwFISEjg0UcfZeTIkTz44IMANGvWjMOHD5d57NzcXFq3bk2jRo1Ys2YN33//PQDXXXcdixYt4mDRM8g5OTmueKePLSIiIiIi4g71dobXXa8R6tq1K28sWsQ9iYlcERhIwujRhIeGMv5//5fkOXOICAsrc+zYsWNxOByEhYVhraVVq1YsXbq01L4xMTHs2rWLPn1OnWfTpk15/fXX+fjjj2nYsCEjRozgxIkTXHXVVaxevZqrr76ahg0b0r17d+Lj47nooouKxRs5ciRxcXGEh4cTGhpKly5dAAgKCmLatGlcc801eHl50aNHD1JSUrjlllsY+5e/8Pz8+bz5z39yeUBA1fwARUREREREKqjeFrzu0qBBA55NTi7W1rd3b7Zt2FCi7/TJk0uMfeyxx3jssccqdKx7772Xe++9t1jbFVdcwejRowHw8vJi48aNrn2rVq0q1jc+Pt617e/vT2pq6e8uHjNmDGPGjCnWFhUVxeZ16yqUp4iIiIiISHVQwSsiIiIiIrXWnidnl2grPHTI9Xn2/k4PTC7RX+ovFbw1KCAggO3bt1OQnV1lMbdt28aoUaOKtTVp0qTYzK2IiIiIiEh9pIK3jgsODmbLli3uTkNERKRO0wySiNRGiYmJZGdn06ZNG5LPeixSKkYFr4iIiIiISC2UnZ1NVlaWu9Oo0875WiJjTCdjzCpjzPai7yHGmOnVn1rlGWPijDHzcnNz3Z2KiIhImerStVVERKQuq8gM7z+BB4AXAay1W40xbwJJ1ZnY72GtXQ4sDw8Pv9PduYiIiJSjzlxbRUSkZujRiupxzhlewNdau+msNmd1JCMiIlJP6NoqIiJSAyoyw3vAGHMFYAGMMcOAn6s1qxqQs+LhKo3X8qaHqjReXfXMM8+QkJCAr6/vecdyOBx8+eWXjBgxogoyExGpVTzy2ioiIlLbVGSGdwKnbrnqYozJAu4DxldrVlKC01k3/vD/zDPPkJ+fX+q+EydOVCqWw+HgzTffrIq0RERqG11bRUTknPx8fGjt64ufj4+7U6mzzlnwWmv3W2uvB1oBXay1fa21jmrPzAM5HA66dOnC2IkTibj2Wm4dO5b8/Hw6R0Rw4OBBADK2bCFmyBAAkmbPZsLkycTExDB69GhOnDjBAw88QEREBCEhIbz44otlHmvt2rVER0czbNgwunTpwsiRI7HWArBq1Sp69OhBcHAwt99+O8eOHSszTkZGBtdccw09e/YkNjaWn3/+GafTSUREBGvXrgVg6tSpTJs2jTlz5vDTTz/Rv39/+vfvD4D/FVfwSHIyV//xj3yVns5jTz1F1A030DM6mgmTJ7ty+va777j++uvp3r07YWFhfPvtt0yZMoX169cTGhrK008/fd4/fxGR2kLXVhERqYiJEb14uN81TIzo5e5U6qxz3tJsjGkBjAYCgIbGGACstROrNTMPtXv3bp5PTuaqXr0YN2kSL77ySrn9N2/dyoaNG/Hx8WHevHk0b96ctLQ0jh07RlRUFDExMQQGBpY+dvNmduzYwR/+8AeioqLYsGED4eHhxMfHs2rVKjp16sTo0aOZO3cu9913X4nxhYWF3HPPPbz//vu0atWKt99+m2nTprFgwQJSUlIYNmwYc+bM4eOPP2bjxo00btyYp556ijVr1uDv709BdjZH8vO5sksXZiQmAtC1Uyf+dv/9ANx+9918+Omn/CkmhvgJE/jb//0fgwcPpqCggJMnT/L4448ze/ZsVqxYcZ4/dRGR2kXXVhERkZpRkWd4PwS+ArYBJ6s3Hc/Xvn17rup16i80tw4dynMvvVRu/z/FxuJTdAvDypUr2bp1K4sXLwYgNzeXvXv3llnw9urVi3bt2gEQGhqKw+GgWbNmBAYG0qlTJwDGjBnDc889V2rBu3v3brZv386AAQOAU7ckt23bFoCgoCBGjRpFXFwcqampNG7cuNQcvLy8GPynP7m+f75hA089/zxHjx4l57ff6Nq5M/2uuoqfsrMZPHgwAN7e3uX+TEREPICurSIiIjWgIgWvt7X2/mrPpJ44/Vf8M783bNiQk0W39hacdXvxmYs/WWt59tlniY2NrdCxmjRp4tr28vLC6XS6biGuCGstQUFBpKamlrp/27ZttGjRgl9++aXMGN5NmuDl5QVAQUEB902dyhcff0z7Sy4hafZsjh07VqmcREQ8hK6tIiIiNaAii1a9Zoy50xjT1hjT8vR/1Z6Zh/rhhx/4Kj0dgEVLlnBVZCSXtW/P5q+/BmDpBx+UOTY2Npa5c+dSWFgIwJ49ezhy5Eiljt+lSxccDgf79u0D4LXXXuOaa64ptW/nzp359ddfXQVvYWEhO3bsAOC9997j4MGDrFu3jokTJ/Lbb78B0KxZMw4fPlxqvNPFvH/LluQdOcKSoluVL2zWjEvatmXp0qUAHDt2jPz8/HJjiYjUcbq2ioiI1ICKzPAeB54EplH0+oSiz8urK6ma4K7XCHXt2pU3Fi3insRErggMJGH0aMJDQxn/v/9L8pw5RISFlTl27NixOBwOwsLCsNbSqlUrV5FYUd7e3rz88svcfPPNrsWn/vrXv5bat3HjxixevJiJEyeSm5uL0+nkvvvu4+KLL2bKlCmsWrWK9u3bc/fdd3PvvffyyiuvkJCQwI033kjbtm356K23isVr0bw5fxk5kvBrr+Wy9u3pGRrq2rfg2WeZOH06M2bMoFGjRrzzzjuEhITQsGFDunfvTnx8PJMmTarUuYqI1GIeeW0VERGpbSpS8N4PdLDWHqjuZM6XMSYOiOvQoYO7UylTgwYNeDY5uVhb39692bZhQ4m+0ydPLjH2scce47HHHjvncaKjo4mOjnZ9/8c//uHavu6669i8eXOF8g0NDWXdunUl2vfs2ePanjjxv2us3HPPPdxzzz0AFGRnc+Dbb4uNmzllCjOnTCkRr8Pll7N69eoS7atWrapQniIidUydubaKiIjUZRW5pXkHUPqLVWsZa+1ya21C8+bN3Z2KiIhIeerMtVVERKQuq8gM7wlgizFmDeBaUUmvTqi8gIAAtm/fTkF2dpXF3LZtG6NGjSrW1qRJEzZu3FipOIMHD+a7774r1vbEE09UeIEsERGpFF1bRUREakBFCt6lRf9JLRQcHMyWLVvOO86SJUuqIBsREakgXVtFRERqwDkLXmvtKzWRiIiISH2ha6vUJomJiWRnZ9OmTRuSz1pnRESkriuz4DXGLLLW/o8xZhv/XUHyNGut7V69qYmIiHgWXVulNsrOziYrK8vdaYiIVIvyZnjvLfrcBTxwRrsB9Oc/ERGRytO1VUREpAaVWfBaa38u2uxgrf3+zH3GmC7VmpWIiIgH0rVVRESkZpV3S/N44C7gcmPM1jN2NQNKvjS2jkleXbV/SE+8NrFK44mIiOfx9GuriIhIbVPee3jfBOKAZUWfp//raa29rQZy82hJs2fz9Ny5xAwZQkYVrLJcEWPHjmXnzp3l9omOjiY9Pb1G8hERqYd0bRURqQJ+Pj609vXFz8fH3alILVfeLc25QC5wa82lI9XlxIkTvPTSS+5OQ0SkXtO1VUSkakyM6OXuFKSOKG+GV6rYrFmz6Ny5M3/8n/9hz7ffutrfW7GCvjfeSHBUFF989VWZ43fs2EGvXr0IDQ0lJCSEvXv3AvD666+72seNG8eJEycAaNq0KTNmzCAyMpLU1NRis7fjx48nPDycoKAgHnrooWo8axEREREREfdQwVtDMjIyWLhwIZs3b2bh/PnFbmN2Op188dFHPPnIIzz21FNlxnjhhRe499572bJlC+np6bRr145du3bx9ttvs2HDBrZs2YKXlxdvvPEGAEeOHKFbt25s3LiRvn37Fos1a9Ys0tPT2bp1K59//jlbt24t7ZAiIiIiIiJ1VnmvJZIqtH79egYPHoyvry8NmjXjTzExrn2D/vhHAHqEhPD9jz+WGaNPnz7MmjWLzMxMhgwZQseOHVm1ahUZGRlEREQAcPToUVq3bg2Al5cXQ4cOLTXWokWLmDdvHk6nk59//pmdO3cSEhJSVacrIiIiIiLidh5V8Bpj4oC4Dh06uDuVUhljSm1v0rgxAF4NGuB0OsscP2LECCIjI/nggw+IjY3lpZdewlrLmDFj+Pvf/16iv7e3N15eXiXav/vuO2bPnk1aWhoXXXQR8fHxFBQU/M6zEhGRmmSMuQH4/wAv4CVr7eNn7W8CvAr0BA4Cw621jqJ9U4E7gBPARGvtJ+XFNMYEAguBlsC/gFHW2uPGmPuBsYAT+BW4/ezXLEnttOfJ2SXaCg8dcn2evb/TA5NrJC8RkeriUQWvtXY5sDw8PPzOc/Wt6dcI9evXj/j4eKZMmUJeXh4ffvopd4waVakY+/fv5/LLL2fixIns37+frVu3EhMTw6BBg5g0aRKtW7cmJyeHw4cPc9lll5UZ5z//+Q8XXHABzZs355dffuGjjz4iOjr6PM9QRESqmzHGC3gOGABkAmnGmGXW2jOX4L8DOGSt7WCMuQV4AhhujLkSuAUIAv4AfGaM6VQ0pqyYTwBPW2sXGmNeKIo9F9gMhFtr84tetZQMDK/esxeRikhMTCQ7O5s2bdqQnFy1r+EUqYs8quCtzcLCwhg+fDihoaG0b9OGqMjISsd4++23ef3112nUqBFt2rRhxowZtGzZkqSkJGJiYjh58iSNGjXiueeeK7fg7d69Oz169CAoKIjLL7+cqKio8zk1ERGpOb2Afdba/QDGmIXAIODMgncQMLNoezHwD3PqFqNBwEJr7THgO2PMvqJ4lBbTGLMLuBYYUdTnlaK4c621a8443leAR75S6fTrTvTaE6lLsrOzycrKcncaIrWGCt4aNG3aNKZNm0ZBdrarbdL48a5tfz8/dqellTl+6tSpTJ06tUT78OHDGT685B/W8/Lyin1fu3atazslJaXUY5zZR0REap1LgDMXe8gEzv4LqquPtdZpjMkF/Iravzpr7CVF26XF9AN+s9Y6S+l/pjuAj0pL1hiTACQAXHrppeWdV62k156IiNR9KnhFRETqjtIWg7AV7FNWe2lvbCiv/38PZMxtQDhwTSl9sdbOA+YBhIeHn52niJwnPZMtcm4qeGuhT9esYfqsWa7vpmFDAgMDWbJkiRuzEhGRWiATaH/G93bAT2X0yTTGNASaAznnGFta+wGghTGmYdEsb7FjGWOuB6YB1xTdJi1Sq+nZVpH6SQVvLTSgf38G9O/v+u7dpo0bsxERkVokDehYtHpyFqcWoRpxVp9lwBggFRgGrLbWWmPMMuBNY8xTnFq0qiOwiVMzuSViFo1ZUxRjYVHM9wGMMT2AF4EbrLX/rs4TFqkq9eXZVj17LlKcCl4REZE6ouiZ3LuBTzj1CqEF1todxphHgHRr7TJgPvBa0aJUOZwqYCnqt4hTC1w5gQnW2hMApcUsOuSDwEJjTBKnVmaeX9T+JNAUeKfolXs/WGsHVvPpSzXxxAKpPt/qq2fPRYpTwSsiIlKHWGs/BD48q23GGdsFwM1ljJ0FzCqlvUTMovb9/Hcl5zPbr6904lJrqUASEU+mgldEREREPJ4nzmSLyLnV24K3tFtdzocn3QojIiIi4mk0ky1SP5X2KgKpAUmzZ/P03LnEDBlCxpYt7k6H+Ph4Fi9eDEB0dDTp6enl9q9IHxEREREREXdSwVuPnDhxwt0piIiIiIiI1BgVvDVo1qxZdO7cmT/+z/+w59tvXe3vrVhB3xtvJDgqii+++qrM8SkpKQwaNIgbbriBzp078/DDD7v2/fnPf6Znz54EBQUxb948V3vTpk2ZMWMGkZGRpKam8sgjjxAREUG3bt1ISEjAWltuzitXrqRPnz6EhYVx8803k5eXdx4/ARERERERkZqjgreGZGRksHDhQjZv3szC+fOL3cbsdDr54qOPePKRR3jsqafKjbNp0ybeeOMNtmzZwjvvvOO6rXjBggVkZGSQnp7OnDlzOHjwIABHjhyhW7dubNy4kb59+3L33XeTlpbG9u3bOXr0KCtWrCjzWAcOHCApKYnPPvuMf/3rX4SHh/PUOfITqSsSExMZPXo0iYmJ7k5FRERERKpJvV20qqatX7+ewYMH4+vrS4NmzfhTTIxr36A//hGAHiEhfP/jj+XGGTBgAH5+fgAMGTKEL774gvDwcObMmcOSJUsA+PHHH9m7dy9+fn54eXkxdOhQ1/g1a9aQnJxMfn4+OTk5BAUFERcXV+qxvvrqK3bu3ElUVBQAx48fp0+fPr//hyBSi2RnZ5OVleXuNERERESkGqngrUHGmFLbmzRuDIBXgwY4nc5KxTDGsHbtWj777DNSU1Px9fUlOjqagoICALy9vfHy8gKgoKCAu+66i/T0dNq3b8/MmTNd/UpjrWXAgAG89dZbFT5HERERERGR2qLeFrw1/Rqhfv36ER8fz5QpU8jLy+PDTz/ljlGjKh3n008/JScnBx8fH5YuXcqCBQvIysrioosuwtfXl2+++YavyngO+HRx6+/vT15eHosXL2bYsGFlHqt3795MmDCBffv20aFDB/Lz88nMzKRTp06VzltERERERKSmeVTBa4yJA+I6dOjg7lRKCAsLY/jw4YSGhtK+TRuiIiN/V5y+ffsyatQo9u3bx4gRIwgPDyc4OJgXXniBkJAQOnfuTO/evUsd26JFC+68806Cg4MJCAggIiKi3GO1atWKlJQUbr31Vo4dOwZAUlKSCl4REREREakTPKrgtdYuB5aHh4ff6e5cSjNt2jSmTZtGQXa2q23S+PGubX8/P3anpZUbo3Xr1vzjH/8o1takSRM++uijUvufvapyUlISSUlJJfqlpKS4tteuXevavvbaa0krJacz+4iIiIiIiNRGWqVZREREREREPJJHzfB6ik/XrGH6rFmu76ZhQwIDA1myZAnx8fHuS0xERERERKQOqVcFr7W2zJWSa5MB/fszoH9/13fvNm3cmE3tZK11dwoiIiIiIlLL1Ztbmr29vTl48KAKJQ9greXgwYN4e3u7OxUREREREanF6s0Mb7t27cjMzOTXX391dyoU5v6nUv0bHTpUTZlUr+o8T29vb9q1a1fZlETqncTERLKzs2nTpg3JycnuTkdERESkRtWbgrdRo0YEBga6Ow0A9jw5u1L9a/qdwVWlvpynSG2WnZ1NVlaWu9MQERERcYt6U/CKiHi65NUlZ3APHT3k+jxz/5/rzxMtIiIiUo/pXzwiIiIiIiLikTTDKyLiwXya+xT7FBEREalPVPCKiHiw8BHh7k5BRERExG10S7OIiIiIiIh4JBW8IiIiIiIi4pFU8IqIiIiIiIhHUsErIiIiIiIiHkkFr4iIiIiIiHgkFbwiIiIiIiLikVTwioiIiIiIiEfSe3hFxOMlr04u0Xbo6CHX55n7/6y/A4qIiIh4DP3LTkRERERERDySCl4RERERERHxSB5V8Bpj4owx83Jzc92dioiIiIiIiLiZRz3Da61dDiwPDw+/09251CeJiYlkZ2fTpk0bkpNLPispImWr7O+Pft9EREREKs6jCl5xj+zsbLKystydhkidVNnfH/2+iYiIiFScR93SLCIiIiIiInKaCl4RERERERHxSCp4RURERERExCPpGV4RkVoqZ8XDJdpOHslxfZbY7+tTE2mJiIiI1Bma4RURERERERGPpIJXREREREREPJJuaRYRqUNaXdik2KeIiIiIlE0Fr4hIHfJ/Q0PcnYKIiIhInaGCV0SkBs1anFrse05egevz7H3jvWssLRERERGPpIJXROoln+Y+xT7l/2/v/oMvq+v7jj9fLj92IbAbhc5WYMNmlpiiIZJ8Ra2jSbGJm4kLzEhmgFYJ/iClommNXaGOUbRMyiYTmqnohAaQViIyG6orxV8NGBKLgIGAINJQSHBXv4POrmlB+f3uH/fs+v25u1++3/s95577fMzs3HvPj895f7733v3c9/l8zudIkiT1jwmvpLE0cdZE2yFIkiRpyJylWZIkSZLUSya8kiRJkqReMuGVJEmSJPWS1/BqQbbctGXWsl0/2rXncer60zyfIkmSJI2lzZs3Mzk5ydq1a9myZXYOsVxMeCVJkiRJS2pycpIdO3a0HYYJr6TpunI2blysPGzNtEdJkiQtHRNeSdN05WzcuDhx0zlthyBJktRbJrxDZE9Zv/h+SpIkSbN1eZ4fE94hsqesX3w/JUmSpNFiwiuNsS6fjZMkSZIWy1+wkiRJkqResodX0jSrVq+a9ihJkiQtVFd+U5rwLhGHhvbLOL+fE2dNtB2CJEmSRlxXflP265e6JEmSJEkNe3i1aF0ZriBJkiRp/4zLLTdNeLVoXRmuIEmSJGn/jMstN014JUmSJEl7Nao9wr1KeJNsAjZt2LCh7VAAh/r2je+nJEmSxtWo9gj3atKqqvpcVZ27evXqtkMBBkN9X3veax3y2xO+n5K6IMnGJA8keTDJBXOsPzjJp5v1tyU5dsq6C5vlDyR5w77KTLK+KeNvmzIPapa/LsmdSZ5JcvpwayxJ0vPXq4RXGgebN2/mLW95C5s3b247lE7x76JxkGQFcBnwa8DxwJlJjp+x2duAXVW1AbgUuKTZ93jgDOClwEbgY0lW7KPMS4BLq+o4YFdTNsAjwG8CfzqMekqStFR6NaRZGgejOpxk2Py7aEycBDxYVQ8BJLkWOBX45pRtTgU+1DzfCnw0SZrl11bVk8DDSR5symOuMpPcD5wMnNVsc3VT7ser6u+abZ8bQh0lSS3becNFs5Y99/jOPY+z1h/S3Uv+THgXYFQv1NZ483Mr9cpRwLenvN4OvHK+barqmST/ALyoWf61Gfse1Tyfq8wXAT+oqmfm2H6/JDkXOBdg3bp1C9lVkqQlYcK7APYgaRT5uZV6JXMsq/3cZr7lc13etLft91tVXQ5cDjAxMbGgfSVJS+virbdOe73zsSf2PG23veYAABEhSURBVM5cd97KZQtr6MY64bXnS5I0YrYDx0x5fTTwnXm22Z7kAGA1sHMf+861/PvAmiQHNL28cx1LkjQmjjz84GmPo2KsE157vqTR1KfrSqQFugM4Lsl6YAeDSajOmrHNNuBs4FbgdOCmqqok24A/TfKHwIuB44DbGfTkziqz2efmpoxrmzI/O+wKSpK66QNvOqHtEJ4XZ2mWJGlEND2t5wNfBO4Hrquq+5J8OMkpzWZXAC9qJqV6D3BBs+99wHUMJrj6AvDOqnp2vjKbst4HvKcp60VN2SR5RZLtwG8Af5xk9/aSJHXKWPfwSpI0aqrqRuDGGct+d8rzJxgkonPtezFw8f6U2Sx/iB/P5Dx1+R0MhjhLktRp9vBKkiRJknrJHl5JvTCqEylIkiRpeEx4JfXCqE6kIEmS1IaVh62Z9thXJrySJEmSNGZO3HRO2yEsC6/hlSRJkiT1kgmvJEmSJKmXTHglSZIkSb3kNbxSj+y84aJZy557fOeex1nrD1m1HGFJkiRJrbCHV5IkSZLUSya8kiRJkqReGqshzRdvvXXa652PPbHncea695/+6mWLS5IkSZK09MYq4ZWm2rx5M5OTk6xdu5YtW7a0HY4kSZKkJWbCq7E1OTnJjh072g5DkiRJ0pCY8M7D2W4lSZIkabSZ8Ko3HKLcL76fkiRJWiwTXvXG3oYo22M/ehxyLkmSpMXytkSSJEmSpF4y4ZUkSZIk9ZJDmjWL105KkiRJ6gMTXs3itZPdcvHWW6e93vnYE3seZ647b+WyhSVJkiR1ngmvxtaRhx887VGSJElSv5jwamx94E0ntB2CJEmSpCEy4ZV6zp5sSZIkjSsT3jHn/Wn7z55sSZIkjStvSyRJkiRJ6iUTXkmSJElSL5nwSpIkSZJ6aayv4V152Jppj/syLpP/jEs91S3eb1iSJElLbawT3hM3nbOg7cdl8p9xqackSZKkfnNIsyRJkiSpl0x4JUmSJEm9ZMIrSZIkSeolE15JkiRJUi+Z8EqSJEmSesmEV5IkSZLUS2N9WyJJkiRJ3bB582YmJydZu3YtW7ZsaTsc9YQJ7xjwPw+NopWHrZn2KEmS+m1ycpIdO3a0HYZ6xoR3DPT1P4+Lt9467fXOx57Y8zhz3Xkrly0sLZETN53TdgiSJEkacSa8kiRJkrRMHH25vEx4JUmSJGkIttw0O6G9/+H7+eHOH7LrR7umrT/N+YSHovMJb5IXAB8BDge+XlVXtxySJEmSJGkEDPU0QpIrkzya5N4ZyzcmeSDJg0ku2EcxpwJHAU8D24cVqyRJkiQN26rVqzjkhYewavWqtkMZC8Pu4f0E8FHgv+5ekGQFcBnwKwwS2DuSbANWAL83Y/+3Ai8Bbq2qP06yFfjzIccsSZIkSUMxcdZE2yGMlaEmvFV1S5JjZyw+CXiwqh4CSHItcGpV/R7wxpllJNkOPNW8fHa+YyU5FzgXYN26dYuOfZQ5e7EkSePNSXHUdXNd27rrR7v2PLZ5betCvz9+37qtjWt4jwK+PeX1duCVe9n+euA/J3ktcMt8G1XV5cDlABMTE7UEcUqSJI2kvt6SUFoOC/3++H3rtjYS3syxbN4Etap+CLxteOFIkiRJ0r7tvOGiWcuee3znnsdZ6w/xOt22tTH39XbgmCmvjwa+00IckiRJkqQea6OH9w7guCTrgR3AGcBZLcQhSZIkqSN2z1q83LMXL3b+myMPP3jao7plqAlvkk8Bvwwc0Uw+9cGquiLJ+cAXGczMfGVV3TfMOCRJkqCfk8t0efKfYevj+znORnX24g+86YS2Q9BeDHuW5jPnWX4jcOMwjy311crD1kx7lCTtPyeX6Zc+vp9zncCYT99OYHSFv7X6pY0hzZIW4cRN57QdgiSNhHHu+eyjLr+f9jTPbVT/Lv7W6pdeJbxJNgGbNmzY0HYonTIuZ6nGpZ6S1Gfe/3JptHUt5HLrSj0X2tM8Lp/bPvbAa/T0KuGtqs8Bn5uYmHhH27F0ybicpRqXekpSnw37/pddSZCGbVSvhVyoUa1nHxNBb9ejrupVwitJkrQ3o5ogjYtx6fkcF85erC4w4ZUkSa1Z2O1AvjRr/3HpQRrVRHChcdvzSac/twt9P529WF1gwitJktRxo5oI7i3uUU4EF3vf1lE1qp9DjTcTXkmSpGW2t56yUU4EF2tchsCOSj3HNbFXv5jwSpKkzljojPujkjjMtNCeslGp52ITpHEZAjsu9ZS6wIRXkiR1xkJn3B+VxMFEUH3gLSA1ikx4JUmSltm4JA7Ws1+8BaRGUa8S3iSbgE0bNmxoOxRJkqR5jUviYD0lte0FbQewlKrqc1V17urVq9sORZIkSZLUsl4lvJIk9V2SjUkeSPJgkgvmWH9wkk83629LcuyUdRc2yx9I8oZ9lZlkfVPG3zZlHrSvY0iS1CUmvJIkjYgkK4DLgF8DjgfOTHL8jM3eBuyqqg3ApcAlzb7HA2cALwU2Ah9LsmIfZV4CXFpVxwG7mrLnPYYkSV1jwitJ0ug4CXiwqh6qqqeAa4FTZ2xzKnB183wr8PokaZZfW1VPVtXDwINNeXOW2exzclMGTZmn7eMYkiR1Sqqq7RiWXJLvAX+/zIc9Avj+Mh+zDdazX6xnv1jP4fmpqjpymY85S5LTgY1V9fbm9ZuBV1bV+VO2ubfZZnvz+v8ArwQ+BHytqj7ZLL8C+Hyz26wyp2y/oVl+DPD5qnrZfMeoqmnvS5JzgXObly8BHljCP8f+8DvRL9azX6xnv3S2be7VLM27tfGjJMnXq2piuY+73Kxnv1jPfrGeY2GuXtSZZ67n22a+5XON9trb9vsbB1V1OXD5HNsui3H5rFjPfrGe/WI92+eQZkmSRsd24Jgpr48GvjPfNkkOAFYDO/ey73zLvw+sacqYeaz5jiFJUqeY8EqSNDruAI5rZk8+iMEkVNtmbLMNOLt5fjpwUw2uX9oGnNHMsLweOA64fb4ym31ubsqgKfOz+ziGJEmd0sshzS1pbcjWMrOe/WI9+8V69lxVPZPkfOCLwArgyqq6L8mHga9X1TbgCuC/JXmQQa/rGc2+9yW5Dvgm8Azwzqp6FmCuMptDvg+4Nsl/AO5qyma+Y3TQuHxWrGe/WM9+sZ4t6+WkVZIkSZIkOaRZkiRJktRLJrySJEmSpF4y4V2EJMckuTnJ/UnuS/Lbbcc0TElWJLkryQ1txzIsSf5t817em+RTSVa2HdNSSXJlkkeb+2dOXf6uJA809d7SVnxLIcnKJLcnubupz0XN8muaOt7b/B0ObDvWxUqyJsnWJN9q/g969ZR1701SSY5oM8bnY67PaZLfb+p5T5L/nmRNs/zAJFcn+UbzN7iwvcjVFbbN/WPbbNs8Kmybu9k2m/AuzjPA71TVPwFeBbwzyfEtxzRMvw3c33YQw5LkKODdwERVvYzB5C1dnYjl+fgEsHHqgiT/DDgVOKGqXgr8QQtxLaUngZOr6ueBlwMbk7wKuAb4WeDngFXA29sLccn8EfCFqvpZ4OdpvptJjgF+BXikxdgW4xPM+JwCXwZeVlUnAP8b2N14/gZwcFX9HPCLwG8lOXZ5wlSH2Tb3iG2zbfOIsW3uYNtswrsIVfXdqrqzef7/GHyoj2o3quFIcjTw68CftB3LkB0ArMrgvpKHMPv+liOrqm5h9n0yzwP+Y1U92Wzz6LIHtoRq4LHm5YHNv6qqG5t1xeA2LEe3FuQSSHI48DqaGXOr6qmq+kGz+lJgMzCSMxLO9Tmtqi9V1TPNy6/x4/evgEOb7+sq4Cng/y5XrOom2+Zesm0eYbbNgG1zq22zCe8Sac5cnAjc1m4kQ/OfGHxRn2s7kGGpqh0MzqI+AnwX+Ieq+lK7UQ3dzwCvTXJbkr9I8oq2A1qsZnjf3wCPAl+uqtumrDsQeDPwhbbiWyI/DXwPuKoZyvgnSQ5Ncgqwo6rubjm+YXor8Pnm+VbgcQbf10eAP6iqmT8cNcZsm0efbbNt8wixbR7oXNtswrsEkvwE8GfAv6mq3vUuJHkj8GhV/XXbsQxTkp9kMIRoPfBiBmen/mW7UQ3dAcBPMhj29++A65Kk3ZAWp6qeraqXMzjTeFKSl01Z/THglqr6y3aiWzIHAL8AfLyqTmTQsHwIeD/wuy3GNVRJ3s9guOo1zaKTgGcZfF/XA7+T5KdbCk8dY9vcD7bNts0jxLZ5oHNtswnvIjVnpf4MuKaqrm87niF5DXBKkr8DrgVOTvLJdkMain8OPFxV36uqp4HrgX/ackzDth24vhlRdDuDXoKRm0xhLs0woq/QXHOS5IPAkcB7WgxrqWwHtk85Q76VQSO7Hri7+a4eDdyZZG07IS6tJGcDbwT+Rf34BvJnMbhW6ulmyN9XgYm2YlR32Db3im2zbfOosG0e6FzbbMK7CM3ZtiuA+6vqD9uOZ1iq6sKqOrqqjmUwUcRNVdXHs6uPAK9Kckjz3r6eHk8E0vgMcDJAkp8BDgK+32pEi5DkyCmzBK5i8EPpW0neDrwBOLOqRn7oX1VNAt9O8pJm0euBO6vqH1XVsc13dTvwC822Iy3JRuB9wClV9cMpqx5h8CM/SQ5l0BvyrTZiVHfYNveObbNt80iwbd6jc23zAW0evAdew+Cag2801yUA/PuqurHFmPQ8VdVtSbYCdzIYmnEXcHm7US2dJJ8Cfhk4Isl24IPAlcCVzTTzTwFnTzlDN4r+MXB1khUMTuhdV1U3JHkG+Hvg1mZU2PVV9eEW41wK7wKuSXIQ8BBwTsvxLIl5PqcXAgcDX27ev69V1b8CLgOuAu4FAlxVVfe0Ebc6xba5R2ybbZtHjG1zB9vmjPb3R5IkSZKkuTmkWZIkSZLUSya8kiRJkqReMuGVJEmSJPWSCa8kSZIkqZdMeCVJkiRJvWTCK0mSJEnqJRNeqaOSHNvcg2/m8q8kmXge5X0oyXsXEc8pSS54vvtLkjTqbJul0XNA2wFIGg1VtQ3Y1nYckiRpwLZZ2jd7eKVuOyDJ1UnuSbI1ySFTVyY5M8k3ktyb5JIpyzcmuTPJ3Un+fGahSd6R5PNJVs110CTvTvLN5rjXNst+M8lHm+d/M+Xfj5L8UpJDk1yZ5I4kdyU5dWn/FJIkdYJtszRC7OGVuu0lwNuq6qtJrgT+9e4VSV4MXAL8IrAL+FKS04CvAv8FeF1VPZzkhVMLTHI+8KvAaVX15DzHvQBYX1VPJlkzc2VVvbwpaxOwGfhfwEXATVX11maf25P8z6p6fDF/AEmSOsa2WRohJrxSt327qr7aPP8k8O4p614BfKWqvgeQ5BrgdcCzwC1V9TBAVe2css+bge0MGtSn93Lce4BrknwG+MxcGyQ5Dvh94OSqejrJrwKnTLkWaSWwDrh/v2srSVL32TZLI8QhzVK31V5eZ559Msd+u90LHAscvY/j/jpwGYMz1H+dZNrJsSSHAtcB76iq70w57puq6uXNv3VVZYMqSeob22ZphJjwSt22Lsmrm+dnAn81Zd1twC8lOSLJimb9XwC3NsvXA8wYNnUX8FvAtmbY1SxJXgAcU1U3MxgStQb4iRmbXQVcVVV/OWXZF4F3JUlTzokLrq0kSd1n2yyNEBNeqdvuB85Ocg/wQuDju1dU1XeBC4GbgbuBO6vqs80wqnOB65PcDXx6aoFV9VfAe4H/keSIOY65Avhkkm8waIQvraof7F6Z5KeA04G3TpkcYwL4CHAgcE8Gt2z4yNL8CSRJ6hTbZmmEpGq+0RWSJEmSJI0ue3glSZIkSb3kLM3SGEtyGfCaGYv/qKquaiMeSZLGnW2ztLQc0ixJkiRJ6iWHNEuSJEmSesmEV5IkSZLUSya8kiRJkqReMuGVJEmSJPXS/wcUgiEQ1eSf+AAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if 'is_test_run' not in globals():\n",
+    "    import pandas as pd\n",
+    "    import seaborn as sns\n",
+    "    \n",
+    "    data = pd.DataFrame.from_dict(result)\n",
+    "\n",
+    "    plt.subplot(1,2,1)\n",
+    "    sns.barplot(x='block_size', y='time', hue='name', data=data, alpha=0.6)\n",
+    "    plt.yscale('log')\n",
+    "\n",
+    "    plt.subplot(1,2,2)\n",
+    "    data = pd.DataFrame.from_dict(result)\n",
+    "    sns.barplot(x='block_size', y='time', hue='name', data=data, alpha=0.6)"
+   ]
+  }
+ ],
+ "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/pystencils_tests/test_struct_types.py b/pystencils_tests/test_struct_types.py
new file mode 100644
index 0000000000000000000000000000000000000000..0a20ca28a6a98b1f0d604ca680c4d9035cdc7877
--- /dev/null
+++ b/pystencils_tests/test_struct_types.py
@@ -0,0 +1,43 @@
+import numpy as np
+from pystencils import Field, create_kernel, Assignment
+
+
+def test_fixed_sized_field():
+    for order in ('f', 'c'):
+        for align in (True, False):
+            dt = np.dtype([('e1', np.float32), ('e2', np.double), ('e3', np.double)], align=align)
+            arr = np.zeros((3, 2), dtype=dt, order=order)
+
+            f = Field.create_from_numpy_array("f", arr)
+            d = Field.create_from_numpy_array("d", arr)
+            update_rules = [Assignment(d[0, 0]['e2'], f[0, 0]['e3'])]
+            result = arr.copy(order=order)
+            assert result.strides == arr.strides
+            arr['e2'] = 0
+            arr['e3'] = np.random.rand(3, 2)
+
+            kernel = create_kernel(update_rules).compile()
+            kernel(f=arr, d=result)
+            np.testing.assert_almost_equal(result['e2'], arr['e3'])
+            np.testing.assert_equal(arr['e2'], np.zeros((3, 2)))
+
+
+def test_variable_sized_field():
+    for order in ('f', 'c'):
+        for align in (True, False):
+            dt = np.dtype([('e1', np.float32), ('e2', np.double), ('e3', np.double)], align=align)
+
+            f = Field.create_generic("f", 2, dt, layout=order)
+            d = Field.create_generic("d", 2, dt, layout=order)
+            update_rules = [Assignment(d[0, 0]['e2'], f[0, 0]['e3'])]
+
+            arr = np.zeros((3, 2), dtype=dt, order=order)
+            result = arr.copy(order=order)
+
+            arr['e2'] = 0
+            arr['e3'] = np.random.rand(3, 2)
+
+            kernel = create_kernel(update_rules).compile()
+            kernel(f=arr, d=result)
+            np.testing.assert_almost_equal(result['e2'], arr['e3'])
+            np.testing.assert_equal(arr['e2'], np.zeros((3, 2)))
diff --git a/pystencils_tests/test_types.py b/pystencils_tests/test_types.py
new file mode 100644
index 0000000000000000000000000000000000000000..4b28c5a0b9bfe4af94d8368b2d06bcc513aface9
--- /dev/null
+++ b/pystencils_tests/test_types.py
@@ -0,0 +1,21 @@
+from pystencils import data_types
+from pystencils.data_types import *
+
+
+def test_parsing():
+    assert str(data_types.create_composite_type_from_string("const double *")) == "double const *"
+    assert str(data_types.create_composite_type_from_string("double const *")) == "double const *"
+
+    t1 = data_types.create_composite_type_from_string("const double * const * const restrict")
+    t2 = data_types.create_composite_type_from_string(str(t1))
+    assert t1 == t2
+
+
+def test_collation():
+    double_type = create_type("double")
+    float_type = create_type("float32")
+    double4_type = VectorType(double_type, 4)
+    float4_type = VectorType(float_type, 4)
+    assert collate_types([double_type, float_type]) == double_type
+    assert collate_types([double4_type, float_type]) == double4_type
+    assert collate_types([double4_type, float4_type]) == double4_type
diff --git a/pystencils_tests/test_vectorization.py b/pystencils_tests/test_vectorization.py
new file mode 100644
index 0000000000000000000000000000000000000000..2acded554db62951eb14f1005327132a3a711cc8
--- /dev/null
+++ b/pystencils_tests/test_vectorization.py
@@ -0,0 +1,139 @@
+import numpy as np
+import sympy as sp
+import pystencils as ps
+from pystencils.backends.simd_instruction_sets import get_supported_instruction_sets
+from pystencils.cpu.vectorization import vectorize
+from pystencils.transformations import replace_inner_stride_with_one
+
+
+def test_vector_type_propagation():
+    a, b, c, d, e = sp.symbols("a b c d e")
+    arr = np.ones((2 ** 2 + 2, 2 ** 3 + 2))
+    arr *= 10.0
+
+    f, g = ps.fields(f=arr, g=arr)
+    update_rule = [ps.Assignment(a, f[1, 0]),
+                   ps.Assignment(b, a),
+                   ps.Assignment(g[0, 0], b + 3 + f[0, 1])]
+
+    ast = ps.create_kernel(update_rule)
+    vectorize(ast)
+
+    func = ast.compile()
+    dst = np.zeros_like(arr)
+    func(g=dst, f=arr)
+    np.testing.assert_equal(dst[1:-1, 1:-1], 2 * 10.0 + 3)
+
+
+def test_vectorization_fixed_size():
+    configurations = []
+    # Fixed size - multiple of four
+    arr = np.ones((20 + 2, 24 + 2)) * 5.0
+    f, g = ps.fields(f=arr, g=arr)
+    configurations.append((arr, f, g))
+    # Fixed size - no multiple of four
+    arr = np.ones((21 + 2, 25 + 2)) * 5.0
+    f, g = ps.fields(f=arr, g=arr)
+    configurations.append((arr, f, g))
+    # Fixed size - different remainder
+    arr = np.ones((23 + 2, 17 + 2)) * 5.0
+    f, g = ps.fields(f=arr, g=arr)
+    configurations.append((arr, f, g))
+
+    for arr, f, g in configurations:
+        update_rule = [ps.Assignment(g[0, 0], f[0, 0] + f[-1, 0] + f[1, 0] + f[0, 1] + f[0, -1] + 42.0)]
+
+        ast = ps.create_kernel(update_rule)
+        vectorize(ast)
+
+        func = ast.compile()
+        dst = np.zeros_like(arr)
+        func(g=dst, f=arr)
+        np.testing.assert_equal(dst[1:-1, 1:-1], 5 * 5.0 + 42.0)
+
+
+def test_vectorization_variable_size():
+    f, g = ps.fields("f, g : double[2D]")
+    update_rule = [ps.Assignment(g[0, 0], f[0, 0] + f[-1, 0] + f[1, 0] + f[0, 1] + f[0, -1] + 42.0)]
+    ast = ps.create_kernel(update_rule)
+
+    replace_inner_stride_with_one(ast)
+    vectorize(ast)
+    func = ast.compile()
+
+    arr = np.ones((23 + 2, 17 + 2)) * 5.0
+    dst = np.zeros_like(arr)
+
+    func(g=dst, f=arr)
+    np.testing.assert_equal(dst[1:-1, 1:-1], 5 * 5.0 + 42.0)
+
+
+def test_piecewise1():
+    a, b, c, d, e = sp.symbols("a b c d e")
+    arr = np.ones((2 ** 3 + 2, 2 ** 4 + 2)) * 5.0
+
+    f, g = ps.fields(f=arr, g=arr)
+    update_rule = [ps.Assignment(a, f[1, 0]),
+                   ps.Assignment(b, a),
+                   ps.Assignment(c, f[0, 0] > 0.0),
+                   ps.Assignment(g[0, 0], sp.Piecewise((b + 3 + f[0, 1], c), (0.0, True)))]
+
+    ast = ps.create_kernel(update_rule)
+    vectorize(ast)
+    func = ast.compile()
+    dst = np.zeros_like(arr)
+    func(g=dst, f=arr)
+    np.testing.assert_equal(dst[1:-1, 1:-1], 5 + 3 + 5.0)
+
+
+def test_piecewise2():
+
+    arr = np.zeros((20, 20))
+
+    @ps.kernel
+    def test_kernel(s):
+        f, g = ps.fields(f=arr, g=arr)
+
+        s.condition @= f[0, 0] > 1
+        s.result    @= 0.0 if s.condition else 1.0
+        g[0, 0]     @= s.result
+
+    ast = ps.create_kernel(test_kernel)
+    vectorize(ast)
+    func = ast.compile()
+    func(f=arr, g=arr)
+    np.testing.assert_equal(arr, np.ones_like(arr))
+
+
+def test_piecewise3():
+
+    arr = np.zeros((22, 22))
+
+    @ps.kernel
+    def test_kernel(s):
+        f, g = ps.fields(f=arr, g=arr)
+        s.b     @= f[0, 1]
+        g[0, 0] @= 1.0 / (s.b + s.k) if f[0, 0] > 0.0 else 1.0
+
+    ast = ps.create_kernel(test_kernel)
+    vectorize(ast)
+    ast.compile()
+
+
+def test_logical_operators():
+    arr = np.zeros((22, 22))
+
+    @ps.kernel
+    def test_kernel(s):
+        f, g = ps.fields(f=arr, g=arr)
+        s.c @= sp.And(f[0, 1] < 0.0, f[1, 0] < 0.0)
+        g[0, 0] @= sp.Piecewise([1.0 / f[1, 0], s.c], [1.0, True])
+
+    ast = ps.create_kernel(test_kernel)
+    vectorize(ast)
+    ast.compile()
+
+
+def test_hardware_query():
+    instruction_sets = get_supported_instruction_sets()
+    assert 'sse' in instruction_sets
diff --git a/setup.py b/setup.py
new file mode 100644
index 0000000000000000000000000000000000000000..dcc5a52bfed63e23800b3bcecc5689bb7ed716bf
--- /dev/null
+++ b/setup.py
@@ -0,0 +1,32 @@
+from setuptools import setup, find_packages
+
+setup(name='pystencils',
+      description='Python Stencil Compiler based on sympy as numpy',
+      author='Martin Bauer',
+      license='AGPLv3',
+      author_email='martin.bauer@fau.de',
+      url='https://i10git.cs.fau.de/software/pystencils/',
+      packages=['pystencils'] + ['pystencils.' + s for s in find_packages('pystencils')],
+      install_requires=['sympy>=1.1', 'numpy', 'appdirs', 'joblib'],
+      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+)',
+      ],
+      extras_require={
+          'gpu': ['pycuda'],
+          'alltrafos': ['islpy', 'py-cpuinfo'],
+          'bench_db': ['blitzdb', 'pymongo', 'pandas'],
+          'interactive': ['matplotlib', 'ipy_table', 'imageio', 'jupyter', 'pyevtk'],
+          'doc': ['sphinx', 'sphinx_rtd_theme', 'nbsphinx',
+                  'sphinxcontrib-bibtex', 'sphinx_autodoc_typehints', 'pandoc'],
+      },
+      tests_require=['pytest', 'pytest-cov', 'pytest-xdist', 'flake8'],
+      python_requires=">=3.6",
+      setup_requires=['very-good-setuptools-git-version'],
+      version_format='{tag}.dev{commits}+{sha}',
+      )