diff --git a/doc/notebooks/10_tutorial_conservative_allen_cahn_two_phase.ipynb b/doc/notebooks/10_tutorial_conservative_allen_cahn_two_phase.ipynb
index 236ee1b9f3cf6c3cb4ac391289ea008693308b86..9e869b42e496afa36374616a92b1a53e47085613 100644
--- a/doc/notebooks/10_tutorial_conservative_allen_cahn_two_phase.ipynb
+++ b/doc/notebooks/10_tutorial_conservative_allen_cahn_two_phase.ipynb
@@ -216,7 +216,7 @@
        "        "
       ],
       "text/plain": [
-       "<lbmpy.phasefield_allen_cahn.parameter_calculation.AllenCahnParameters at 0x126d30cd0>"
+       "<lbmpy.phasefield_allen_cahn.parameter_calculation.AllenCahnParameters at 0x10d542d00>"
       ]
      },
      "execution_count": 6,
@@ -395,7 +395,7 @@
        "</table>"
       ],
       "text/plain": [
-       "<lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x126d44ee0>"
+       "<lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x10d5daca0>"
       ]
      },
      "execution_count": 9,
@@ -433,7 +433,7 @@
        "                </th>\n",
        "                <td>Stencil: D2Q9</td>\n",
        "                <td>Zero-Centered Storage: &#10003;</td>\n",
-       "                <td>Force Model: Guo</td>\n",
+       "                <td>Force Model: Simple</td>\n",
        "            </tr>\n",
        "        </table>\n",
        "        \n",
@@ -509,7 +509,7 @@
        "</table>"
       ],
       "text/plain": [
-       "<lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x126d22eb0>"
+       "<lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x10d56fc10>"
       ]
      },
      "execution_count": 10,
@@ -521,8 +521,8 @@
     "omega = parameters.omega(C)\n",
     "config_hydro = LBMConfig(stencil=stencil_hydro, method=Method.MRT, compressible=False,\n",
     "                         weighted=True, relaxation_rates=[omega, 1, 1, 1],\n",
-    "                         force=sp.symbols(\"F_:2\"),\n",
-    "                         output={'velocity': u}, kernel_type='collide_stream_push')\n",
+    "                         force=sp.symbols(\"F_:2\"), force_model=ForceModel.SIMPLE,\n",
+    "                         output={'velocity': u}, kernel_type='stream_pull_collide')\n",
     "\n",
     "method_hydro = create_lb_method(lbm_config=config_hydro)\n",
     "\n",
@@ -565,7 +565,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -596,16 +596,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x1417f86d0>"
+       "<matplotlib.image.AxesImage at 0x11cdd57f0>"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -673,7 +673,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -702,7 +702,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -731,7 +731,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "scrolled": false
    },
@@ -765,7 +765,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -773,7 +773,7 @@
     "periodic_BC_C = dh.synchronization_function(C.name, target=dh.default_target, optimization = {\"openmp\": True})\n",
     "\n",
     "periodic_BC_g = LBMPeriodicityHandling(stencil=stencil_hydro, data_handling=dh, pdf_field_name=g.name,\n",
-    "                                       streaming_pattern='push')\n",
+    "                                       streaming_pattern='pull')\n",
     "periodic_BC_h = LBMPeriodicityHandling(stencil=stencil_phase, data_handling=dh, pdf_field_name=h.name,\n",
     "                                       streaming_pattern='pull')\n",
     "\n",
@@ -785,7 +785,7 @@
     "# No slip boundary for the velocityfield lbm\n",
     "bh_hydro = LatticeBoltzmannBoundaryHandling(method_hydro, dh, 'g' ,\n",
     "                                            target=dh.default_target, name='boundary_handling_g',\n",
-    "                                            streaming_pattern='push')\n",
+    "                                            streaming_pattern='pull')\n",
     "\n",
     "contact_angle = BoundaryHandling(dh, C.name, stencil_hydro, target=dh.default_target)\n",
     "contact = ContactAngle(90, parameters.interface_thickness)\n",
@@ -825,29 +825,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
     "# definition of the timestep for the immiscible fluids model\n",
     "def timeloop():\n",
+    "    # solve the hydro LB step with boundary conditions\n",
+    "    periodic_BC_g()\n",
+    "    bh_hydro()\n",
+    "    dh.run_kernel(kernel_hydro_lb, **parameters.symbolic_to_numeric_map)\n",
     "    # Solve the interface tracking LB step with boundary conditions\n",
+    "    \n",
     "    periodic_BC_h()\n",
     "    bh_allen_cahn()    \n",
     "    dh.run_kernel(kernel_allen_cahn_lb, **parameters.symbolic_to_numeric_map)\n",
-    "    dh.swap(\"C\", \"C_tmp\")\n",
     "    \n",
+    "    dh.swap(\"C\", \"C_tmp\")\n",
     "    # apply the three phase-phase contact angle\n",
     "    contact_angle()\n",
     "    # periodic BC of the phase-field\n",
     "    periodic_BC_C()\n",
-    "    \n",
-    "    # solve the hydro LB step with boundary conditions\n",
-    "    dh.run_kernel(kernel_hydro_lb, **parameters.symbolic_to_numeric_map)\n",
-    "    periodic_BC_g()\n",
-    "    bh_hydro()\n",
-    "\n",
-    "    \n",
     "    # field swaps\n",
     "    dh.swap(\"h\", \"h_tmp\")\n",
     "    dh.swap(\"g\", \"g_tmp\")"
@@ -855,7 +853,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 21,
    "metadata": {
     "scrolled": false
    },
@@ -864,7 +862,7 @@
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gnf2f/AHBwAAAAX0Ga4C/AffoMJV9DEqAbJ4RefcCN4Ib3vAji2EBD3gScQBXvG0E3gRbgIvvWoDX1Yzd7+/f3DZS7epB835ywIPjcj7zwIEEMOCZoqncgRKfyQ1hEqjkEgwWXT/2d4A4GAAAAREGbAC/AKJ7Czu8CX6vARgthAveA2jwvAaz9SDiZv803X67oTLBIW9+/BbqTbkl+AEbUK3fJhqadfDoz77oT3HPfAHBwAAAAYEGbIC/AIB4Iww7u7ECGPYx19e/IEXMV4UUuexlO9qgvAiiHPSJ3iOAjz+fzu4EkWwleBGFwmK3gEe1BIKe9xon3RXHc+vnHyXgRi+rfhqK31JpzX/wzJ+vhhn3+3gDgoAAAAEZBm0AvwCAegwwAI+d3AjHnz6gRxPQhYBHH2v5xi8O5Ri2H0ST1PX+4Kl3vXghqu4AiDEHaO+uXy/wyGBz19Qnfn/1LAHBQAAAAXUGbYC/AffgkDF7sgSfBFvd8Qig/z4KN33d3/V4EjxN3d3d3Aind2dxbAim/w/sEVisTtZ9QJGBrwJJ2ED8Ajj9UJf1BHz/1PfXKBGyQ1h4Mt+w3H/+CG6i4DqAODgAAAExBm4AvwH6EECQMDLL6afELiFgRRjCIr6BL8Em93gRj+fcBHHeBHFsIF7PDGASKzw4L4aHl/HZbSwEd6mnIvkRh3PX5Zyr9DX1/gDg4AAAAQ0GboC/AKNWwo94EU7HOBIO8A/Opzr6cmnCvJPi4dwI/7nrwgcLL9uf1ThR9PwI2oIqhf3FTfhmT2j6j/f/iUHYA4KAAAAAmQZvAL8B9+QMbuAkRLLAkeWdROogSDvASHEwCRvfgRnqbvF1gDg4AAAA+QZvgL8B9+YMMV3hBDC0X008BIiIReI/yXd3Ak+gg8CKeE4EgUsAs69fJKMz/3RWQI71KzkWDVy/B8awBwkAAAABGQZoAL8AoouFLwEkd3Ajn3m//hoP0JCoU7CR+BEL//AJDzQJO5xq/w4ivvwX5SK5s6/DcVtcCcCNqIIfOps7xN3C/3wBwcAAAAFNBmiAvwCiBdhYVoaGRj/SoHQV68EV3d74VWh9jY2P6B5XgI31eAjzsY+gP2AWj0fvVXPzli4zNLir/560iB8+8/8CM9Sv3DRHfOKnR/wxuvwBwcAAAAFJBmkAvwH34sMXl79wEqLYw/eBFPCefze+H/e9VIpfvoUzLYCQ8EW93gIw7GOXwTXd3vd4CMxWBIfq/CvLr7mPc2XX65QI2qMQX4IYX++dIA4OAAAAAR0GaYC/AffoMPL4JuWjmK7u8CMFUV/mO8p/yrwIxvj/Tq/sHuxIHYP/s+xgRTYfj4WCnsWwbBu6Aff2Kl+BKL6p+pxe8AcHAAAAASkGagC/AffnDC/TGrmX1dAkHYpwIo2PyxHAEfeHBHJinGcMwy/7ES8IFr94Ean2+oaw3luQUpUPjAfUD9RfefhmS2V9UbK/8AcHAAAAAQkGaoC/AfnoET/q/6v+rwEgb4fHfEj2C5xP9gwBHvmEWputw4Xl6/wlwaXw748tKOscVTVc9Mq25EtYEbVCO94A4OAAAAGFBmsAvwChnYIHhRjaGQ6Yp+UVIfSylKCwpyN5z/yiqDY0jn3l/ghmBV74T3MdnLlOnYO/O+0cpAkDpRk7ASLwIfgH1esteC017SyfF+zO+BFftghuvW8l8bBPFEGAqADgoAAAAUkGa4C/AffmDF2JwEiGWdznJzmwrClKILOX2FaBINTHgPwZ7EgYqK+UfsGwf0BJCOBHHd0Aj3RB0N/d7nErw44vXsQ74EXVTp7nqGGff/8mAOCgAAABgQZsAL8B9+YMOcpZgSayFIDzh4q+BHO8CT6K9HVYTxuqaGuQ5nF5DsI0GPAbPnHM+7u4BHF6hyf9fID8dLpeCQ+NezC36wIz1KziFIjA3ufeQKiJH7hmbKU4vyaemAODgAAAAKUGbIC/AHll+n/f7Dz68k9fwi9tPvXR6+G2d/Ai+IzfHvOzSvL1ToAcHAAAAfEGbQC/AKKFIScZrbFxPA786iZk7xBOPSiCgyoF0KvmHl4Z7cEjA1o7mCgOx0pZ56kU/2NePDabb/gou/e7wIvq+GdyHX2Y6qmGlHF3Hso80e3iVA7V4J7ve93gCPPIOFb79C3PwkaXLhnctkoEZ6t7yXPUZesfDhmvwBwcAAAA2QZtgL8AgHlDTu8CGLZHZAEi9QIbuqPVwV09//vu6fK4cE3jsjH+HtNeqcCNr7iBDVLfmAODgAAAAiUGbgC/AffgiDGjGWhkvn18W+BEDM7g+aQ6YoxowDxeLImZ5KKsPpbSjxdBLpm9+CW77v1Ajer4Z1lHtykxyPoUhLePUJhUyASJvh/6dyiElNC4loxEJaFwCydI0oEh+/4MDFy14n5Q9CceZJ/J/OJXgkeMx3rqBFethoVu6qD8zw1nf7uW8wBwcAAAAJkGboC/AKLWgleA1/V4CR9FZAI866vfeqhIdk/J4EbXeJ6J0AcHAAAAATUGbwC/AffgrDHDUR65f3PSoBIa0d4BZ/OZfwj3HIy3QZu+VP4b42BEW/2aG+Z7rhHpmW76J/S/EBsh2/fCHT/S/9QIr1bZBLn3m8AcHAAAARUGb4C/AKN6CVQJG8CKd4EkL4Q84/lLsdW/nP80As/RzReJ74EjpCqvzDcda1X6wI2oaFcmKRGNTX/uflUzr0+DuX4A4OAAAADFBmgAvwDqVoJVAJH6PFAR3PfSHFFAiF91pTGC7j63ML46Y+QRLn6OSKI7/AivW4A4SAAAAR0GaIC/AOpeglUAkY5FxQEZ0cUcH8CfX//Y3oXz0o4RexeHM+4EO5EKqskonP6WvAjOtMKmmp8aXql3HnsO1O/al76D1gDg4AAAAXUGaQC/AOv3ARwUhCwpzpzSDQWQzYPmL4CS9coCMfWHBGGXtfyBctl6Ly24EI8M14ZBANrvw/cD4KXhBo2CLhu35wY36Zc+fpEqBF1RTP9wzyZ1DDcnj/JpArgDg4AAAAD1BmmAvwBxHRw0VOJpfgQ+jiFhjAP9dXW4cG8vXhxSn/DQi8+YZ6Phw4iSTg7+jEFAivxUQWbPiOd1wgDg4AAAAPkGagC/AKL6Cnv16AI96l8Nm476v4KtT4EPogh1yLXDZbrUwVIPkD3/qBEtd0qYa7awMhgGlFlv/TomEAcHAAAAAPUGaoC/AHB+HA1g2/bHGS+S4F4aaC9Aj6jTL8CH1rezCD535CwknE31JAi6hWF3L+oW+VQ3nr/3ISfMAcHAAAAA8QZrAL8Ao/oKegCPOkZ5fDfDjzcMo4Re5/wIj3/VHKKl1lFT5gRtQre/SC/oPw7ufvE85FHGr5/++AOCgAAAAZUGa4C/AKJ6Cnq9W/WoAjzw2bl64fi6SXAj3pdk/S9Ah3IcUcX+GeN/uXL1lhwfxnl/gieObAI78RQo6a/DPC32vj07ReNfeHPAj/AkfAkfAkfAkfAkfAkfAkfAkfAkfAkfAkfBHAAAAR0GbAC/AHB9HDS/hHkEH0s5LJ/DfGZRzlcCavuf4ER77Fc32SgiUVPWjjF8iYmEvyQIr7bPlRjT65wkHcB/4JeLhjyv+gDg4AAAAQ0GbIC/AKPfAj6wD69HDi4QtP0l3XyeYeu/o45fwrl4EPk9zCOGz5l/XzlViDKKn/AjeCLqJ0g3vhnjneUJvc1/wBwcAAABMQZtAK8AxvoKNAPs/cOGy5XLVfJtfQb6quDqNfAiPfOIUO9jyf1bmH8PNxWtgtFLJtPHwgRPQl6dLYZEPpPIFR6L/l9/wRWO84oA4OAAAAHBBm2AnwDGegg1hQlGwZDhi+xjzwY1J2x7CGIxjdDAbG8AjnRxDPDu6+TU4RXh6P/QIwhsw8y/QIdza3Uwg8P84RXG/f/PXhm/L9hEIBUZy5GPPqOGu9/8CNqFY/l/USaL+Hc79q3nr9HgP9qCDwBwUAAAAc0GbgCvAKJ0gk34JKrtvXVvwTalbmCS7QIxf9V/VoEgKK6U5n6GwmXoIA1vQcEZqDscuUUDcVy9clE9p/1Dg/jKr/CR4evgjCG3HqBEe8oITPm72tf5IESr37a5e/UNQJHwJHwJHwJHwJHwJHwJHwJHwChQAAABgQZugJ8Ao3UCMX/7gH36OGl/MFA7gNioTP+obquv8CP0N8vRwkuC9zv7ee8CGX+v9w4bhvcL4fRWvz21+UsPj3AjUUp8MhEaehLuvj4KdWnennqQ2hvq9H/AjiECGAM8gAAAAT0GbwC/AKKX/6YUqpznzVWvxU4+vqoEfy1KH5xf0rQIvq0CQX+vBD1KN1fUAsnSFRSZKH99HHL+G8+4EXun/8kCLqiS33hqbOvhvAfwBwcAAAAA5QZvgL8Axu0gs0A+1SHEdyWCvl/9XYqcb3+ATf6HnqBDube+YKHzvqBGf2CEvGly+wRS8+eHpQBwUAAAAgkGaAC/AKL5QosO4yfhKdGuYlqBGDOpziHjJa0Lj+TSkCzHSt+roE0gtzPIV6tAjLvXsMr7CzmbC+Z9qL/pYIcydWgRelaBJ6gEe8OCsQ0G1uP4ez76vo42Lw4ivv6kOMXK9n4lHoERfsRxpQJL9s5dRoJ48m/8M9U8oSfjAv/wBwcAAAABeQZogL8AomoKwoT16qsgdVr8RWtawJBf/16BF1Vqq1b6gGs6OKXOVCK7Z+u6sVOLX+G+V6gQ+M+r6DY5Ck/CZWH+14bh/2EGnwI3YZnh4PnCo1L/s9x7B8OQy/AHBwAAAAF1BmkAvwCi+gs3qrQEd3ANf0cQv49NJme9zXYqcSvCFpjf+g2KyNSXG7n38CHxC9t1zmghSDT5hcNw9fhiSC8OBO8Et0V14bbb9daHVAif1P+GfN8qjj1/3vrqAODgAAACbQZpgL8B+egRN+rQJO/4KB66rW0CM/wXVqpg7k/vUuq/QIar1Aihh1IROIWPx2YznbHag7V18rrWBHDGpz0cgugtx3Q/bCam9hDUP7CuPMJBfAjcnWrQEjtQEZ0cYuMgsoWff0J30cXGf4b5no4pfz5qBEXWzPpPw2U2/UcD+vL6i1sgfwI3Z8pBlZN+T1u/wrzZWTeWeZN/AHBwAAACEQZqAL8B/CF/QImgRfIPWSC/EV1RKqsWxyfQInoe3qtV6+gI0L/QTKxnOvL9l/ZvH/xv0LUfd+Q5cEyXgSAtkwp73omWi1/eFNfQWVvyC2ARzo4xf4biuXq9TiV4Raz/6OIXD3SfgROgSGfN5WvwRHTEufQIz+w4R318fDDDx2av+AODgAAAAi0GaoC/AffgkDWq80vgjqRQv0CKX9fMda/uq1153gRO/pe1rYJ86+tfe8CN4JOqt9fa+gRV+tvvqvqBH7gEd6Dgzd10YZZ9/0c6/wEvvfXe8n6KabHwIi/ORQ5JoSL980y/15gjw4goH0cYvjI/adwI3YZhdx3g/KWjXdwX69eTX8Ph2JoeDt0eAODgAAAB+QZrAL8AoZ2CAeQfCY2tar9K1PrgSC+/8CR0COWPqBF6XvpW1/AjG/6ft9i7Bylq3/1aAR7o4xf4PiNfnKuEemZ/eT1JAidHEL8o6RXGA5N14ZLeM4qOEt6zxH8CN4Z8P9GcDQTu3/enn/gMeraoV+CPaGVPnrOCnr63/AHBQAAAAbEGa4C/AKN6CjZf78EOtfQIvVeCHqre8CL0rfTqv8ENV2+l6BF9avdWgRfoSq91aARypDjH/mLg9EfV2Khw/Fa/w7FSejmXDLO/FvO8CI+sUTP5876OVfOu9GQGYEZ639giu/XecFKnrf4A4KAAAAGpBmwAvwCi+CQKVr34LeTNVXoEjpa9f0OaBF7gSN4EirgSfQ9oDV6OMXKiCVd8/1JeSjv9QIhPVd9UKgrrWVWGyl7+EEf1+XP9wxAi0ynwQRaP+gb8Yeo+GHz7J6quuGfL8vyo6+b91AHBQAAAAcUGbIC/AKIX/p0FPVv+Ceq1rIL1AjF/7wW1yFY0ORdvtegRfQ5q+BI/5ENaAjxGq9FtAaj6a17aHdfRyrwjOG1H6kDZnvXOSPwInQMMz7vm6nWLOwL38CLWQNxu77+9eoIg1k/EI2C2EIM5wYAKMAcFAAAAAc0GbQC/AKNrAi+gQN9AhG1q35qqT66VoEbr8I1VVXVVwI269esCLurVerQEd62vpWgIzoODH3Y5Q8Otf0ffQcLxDBf4JHzP/0cy/lwoEP0Lr6trShsQaEka+Oh63W4EbsGESw5/1XHJs4MP7V/gimzygDg4AAAB9QZtgK8B9+YMKuX1SQIfoza7W/BGNqvoEYv/XXf6GMgRd0Nb24Ej/qBF69NWgR9Vt+toEgQ+IWAjeg2MmlrjT/Xs+At7Gefo9dDz/9VXSK49BsxcHWXXA7uL+BD5NrVhe8fMbf1+GoviwPd/Aif8uvbXOL3sJcMeyZ9cAcFAAAACEQZuAJ8AonUh2HkwInRR7Wsv/f9K31Ai6gj1q30Jrrqq8FNdVWq62gRdQSVqtv1broWwgTtAi/AkiIRgSbgTICMfTRhg6y71+vXpHL3gKLs+9P+oEPqQnpf+GSS/UoM0qcX/AjP7DNvEGC8Ibn6/2GsfX6phmWMLvX0+YqYNBlOH74A4KAAAAgUGboCfAKN0gg0CP1Aj9K9erQI3r3rfoIMgSDvAjjIRWKBF5oCPfTSGZdTHnuEPH9vwS7G9b6Dhb3Xhl2OAbdR6PTXUCIlvOIVaQWg7Ot9WocF8cVeG7f8NUl85l/BvDl/wI3YMIS/2e7JJ6hBiR894+9a9cnq8n5wWqE7tL/gDgoAAAAHNBm8ArwCieC0JVqurfgmqq1VVbXf+CTqrQIu5K6rsta+8CL2rfwI/rXuSu4EfdagSPgSBTqBIPv9Wr1aBETfEHGLwjsLn9P18ldIrGvo5mH4ZGA8CIuqBJsc3lfnqHEnj/gRuwQ3z+t/Yb3etx81/6UAcFAAAAh0Gb4CfAKK/Wl7wIgthwL0DvVDW6wRa1au1aBF69KugSVX79DmgR/BMPVVqtWgRvBDrWsSov0ltAi8CBAk8CZiPErARi+gUDJpZLLnl0fdIhys6grw9X6+kZ4ETo9Y6l5jQv7hNeYTGVt/wSmvcV90CL1r2U/stuTMUwfWHWffZIR/03zgDg4AAAAHRBmgAnwCjeYIVVUdjkwIz9/qBFL//910h9focyBGqgSj61Wu0CNpwJHAgYjeI3Aaq+g4Md+v8PsB6Ez+4bipP/g2+Dj2Q5VzVA6sFXgDl9x9/fpGOYgROgnffm/g3r4EZfb8TyvUNzSS1lER8y8FPPuAODgAAAAJZBmiAnwCi+UISLo9VWdjicCJvfix61rWBG3+jVWvdfQIviarVar7BNWta6rVagRif18DF9atl/r4CN9WgI/o4xcNPhXT7hJ5hXkfQb7qv8IeP7/wbb/9kPXhxEs/6DcQ0b3TbJ718HWagRP+Dco3BH/61VBkZGcdfgj2b3O9XAjP7DlLdQxJDdUP5ESUJuG6r/JyeAODgAAACaQZpAJ8AgHsLaqBE6p+vdM6rzscmBE1gRzub92PXX0rV0tQIvStRff6gRi//q2X5H11/8BIQIr+6EefgI64Cs78Q8CIupASCkiZnWPnJXCfjLn9cFSCr/QJAhcMD1pj6Dd3zlTk34ETzmWmOi/5h16+//wyXd1A6sSH/Ai9fKC6H3vua9/lBfn/L9VhC4afjokCFvWwWn/AHBQAAAAH1BmmAnwCidgkCCmft+rfX4IuqbfoIMgRNe3/BUEVXWq1W3VQJHTrqBHf4I9a91wInA9Zf/gbsvl/AQHwEFASHAqQI7/gRujioJOJ7T++tE8V2gi3cQcY44THH23/QI7v5QIivk/OLY/hlb/9QIxh8//RK+zjm/ypmuu+AODgAAAINBmoAnwH36CzQJXkOtV9gh6q0CPpfX3Ai9q3r+rfUCM/1bL/+td5qrgRS//7/gNcXq3wLECN0cUsxaTYS/kiPbEr+l9Hsf4R4fa/S4yBE9GZVhANgkE8A/uOMaWTDPHKa+EeG9f04Ebs5lXCV75/d+ewkD5g8y/+NgvgcF3CIIwcAcFAAAAHVBmqAnwCidW/WBG717/UCNcBOIId2Kr0CNaq9k9//BFrVoEXi4EivvxHAj3wJXSK0CJ0HB0V5T/NpC/f+Lh+ZAvS7SOHu45y0MP7iDzlTs34ETo5lrMv66OJ7w0tr/z1NuOQ//gRn8rEPr5T1/MGg9FTwBwcAAAACTQZrAJ8B9+CgLVrqrsQhQnQi+ii1XAids61+/eBG8Emqq34IdVt9fStAiv4CeWWX8l9a8la9YEQWwgbtl//QRavy/A8fwI/wJH4jUCKd1W1Aj+itAjdHHLDu6lXZv9o5l4CzcPeP30c8H8cK60FX0GfDeWc+DGl/AiLvrzZf/gRuwyZ714dZ9MH8HxH4I5sJ/oA4OAAAAlUGa4CfAfwxAgC/zQI3et5PX6KEV1Ai710tQIvA8enl//VqL/+rfARECIX//X1Rf/4EjdbQEZwNF8DZiv4CAgRvR2z8CI+mjhBfImNS7C1epzMP4NWGHR4JfoOB67yi04YEV6z2PB69Ah82OAInQcM7ysrDC3f/X6CLn0cQv8JGL9GqPUMr6//4EZ/KLES7or674A4OAAAAAn0GbACfAffgiC2quQJXSPb2vsmtQInAQGX/8ENda6da+VfZPf/wU1XWta6+AlIEUv/Xv/L//Ai8DhZf/4CM4HLr+BgxL5f/4EWtHa+BmgRjxOfgReguGN3d9yMl8b65u1LfX6M6+g4dk71qQXv66o9QOMUC+NS+OBE6OZfgO7y0eX7Pd4EbsMmDas+oYkh50v39hrcn1sgywD8CPxkAZ5AAAAI1BmyAnwH6IQIFQhfwRi9VaBD4HpCH+kPb7XoEcv/696XqtQI5fgKLy8v/+X/+BIL/vwI3q0CO/6uArNfwIuEqK8CWeEYEToNhyX7Aujk1zzNsm+r6Pyz2PieIP5/1XhJxlz6VyBE6/BGJeP02Pr84pf8HUGvwIq69fYZN52r5lsMxTq+774EaoS64AzuAAAACKQZtAJ8AgHoLMgRC/+5D1X3Wq1VoEUv/62+oEgv/+X+B0/4HiBGL/+rU/gICBF9WgSOBw7gI7b/l//VvgIiBE+/gRvo8KwInQaDmOstTnx2XVzf22JklFPm87BPn9aTmD130nJBQe8G+X/wIlSX6vAjdo0/2C/H1+TK/h6fXjYMcYYYGWBH4YgDO4AAAAdUGbYCfAKJ2ghXqvfgtqutVtAjF//1/Rf+B2zarAil//Vsv69Zfr+BHL//AkcDNje6BJELAanSEOfVvok+DTJb0ccezRYO+oERdevruQOZfv4bln/qj3hhL8//AimHz/9E0xJxF5BPCXzB/XLZ67NOFZ/gDg4AAAAHdBm4ArwCib+6CVe/0tQIpf/gIZ61l/8lWy//5fgdP4EUv/ARFZP6/8v/6tr+BF6Vq9WgRrgJSrgJ7vgRervR3gRfgSTx8CNUhw45KOAr53/1oVhnYKa1OCBfnsoO/R6+DGfPwI/wIy+w4bdKVZRdL/YIpf2IA4OAAAAHFBm6AnwCia+n9ZPX+nYQWsCKX/661bJ7rv5dVy//q0CMT6/4Cay//wJG8CMv/kgSd88sBIHhGBE6OHFDkuN18wUAd6n3+jiFwPURL4di799HOsZL06b0/9HqVtn/wInJr7+oEd/Kc3fYFg2nrXfAHBwAAAAJJBm8AnwCideEgE8gg9PXNVfUBHQIpfX/L6/ARmv4EW4CQgSPq+BF4CYgSPgSK87Ctn4EY/AjdIOZfV9Bvx0xlmQknQUYnA7FSSHxtvQZ5MS74dqX/AiF/+zmWB6hIb93Ic9fNuO7H8CNyhkQK+uVMN5r9uhdhrmys0RXh6v4EfJgSPgSPgSPgSPgSPgSPgSPgFEgAAAJhBm+AvwH34JAwqqrQJHoU2+lBCPrVq4CgV+4CegRS/8Dh1wZq8CPxHX06tAir/+BI3gSPgSPgSP8TzwrAiVIGg5iOTpgzs/EITvrOZ6ntoX+y/rPnKuOB/cp/0CHquoETs5F+Jg2dbcpx/fwzbv1mEcc4COvsOG2z3F/h2WWrLmu8F+ne877v+hhZ4es4Efc4RWE35/wBnkAAAAHxBmgAvwCiF/dcwSJ/fVq3qqRS//q0CLUBIQJHq0CQX/+BMFsJE7IBG39BoTpKpi4y+ec+HtP/SNhfRywYawLePzVMH2A6T2+T89R+Z8HFGvAidfgjF4fU319HEL/DduAI/YZMjFZ3w7hmJII+uu88owoDTT6//FQI3wBnkAAAAVEGaIC/AKIX/8oSWu/Wiff/kqqwI1f0rQEbwEFl//gFn6QqD6vpf/UCJUlebL/cixwBGX2HyZZZY+qzEM32f/7DfNDFx0iMn/CGBGspznWE35/AGeQAAAIpBmkAvwCiF//y/+tL+BG0qz0EmgRxPAjF//VrL//Aj6UAjtSBoVkwmQQ0iiTH3z8hEcmvuZGwtaqc64S8cleEv1IeoHzl/8CJf9I/V0ckExFju3/8CMu2UPE5o7u+64aW9R9rh5L+mjBp69ILzMzM3v+zRYF5lYMHn/unaYQ8CN/aOcqhiP/wBncAAAAB8QZpgL8Aohf/wQhKq2y//ghqqdsv/6tr+BGL/V6tAjnddQExXAR0CLXQztn38BCQIlcAj/QaFFvVSnhmX/9HMqkr6o9tTMnDc6GK30c8GOGpxf/4Z7hd878TNcCIv+pASHe//XAjUL65bQiLXeXmwvAj+ecX4EX6efAGeQAAAAJlBmoAvwCAeCMNKu5AiF/etHfL/+aq9/A4ZP7/4EYv/XAjcDNv4HKq64H6BD+BI+BI+BIO8BIF/L8QI5fn+9cEhs/5XUhzwYaiShuX53D8cBvDc7O6P0eo/Nf8CJ1+LO7nlu95Pr68MGd3d314cW48CO+5T5SUkEIS+3Zw9MHi0r6Ct3d5+Hf2UW8dRkVr/Aj/7n1+H3b+AM7gAAABwQZqgL8Aohf+tBRsv/9cBAK8CJwN2K0vAQnfT/gRfRWgSPgSPgSPgSPo8IwIx+j8CJ0cOL5g8NPr+kTrfr+y3Pj8AifdyHr4Yl/PgRbGk13YJYaEnD2nvw13nuLgI93DjsQJjw/8m4hAj+Q0RzAGeQAAAAItBmsAvwCiF/qthJa9DQEd11wERAjVJl//gGwPCcCJ4aDhcu6wVe5/7aPcMErd78Ph2+eGovi3voLlz7Jr/fhC08EdDXut6gRKkOZaW3H+uvwQiShJsjPKBGX2G7h1wf+U5lwS9D/xmQQ/clU933YLLnaZjxv6OCSkj/QI9s6MRO1OUgvgTv9n/AGdwAAAAfkGa4C/AfZf/SBaGNVt20ol8N9VTD4q+BEL/09cBDfEI7QI6/VyAbE8JwInRw4vnLDD6/pE61rRywYaRUhhlR3/DNy4H3uooPAf8Ddzv4ETrWDgFmGxLvdcPLfeNp/L/XaEPAjY/rscVSNvuw3fWL8rmb4AR1t5yLDWff4AzyAAAAIJBmwAvwH76BQmQEfSy//wI/ARlE+v/QVYgGxPCcCIX6fw0GhtfvaHX1/k9cv6BGS96/BQP3d3d3xHv1OKxDGzH/pXIERdesMAwpCX+h5r3d3Y7t9UeqdbX/gRuUPxX5wzP3f4fJOHbcI1+2u8NcZFFwZKj4T/42CGGGvGSBG/3gDO4AAAAlkGbIC/AfghAmNkQsCPcBBd/f3wIxfr9BNutXgGvXwEB8DBAi9HEL5AmMPr/C5Lu+r9KjjpXolgNPjwf4lgjxC/QdDzu7vNl93w9PqUG8pYcD+8t8EMuDvuQUCJ0FSPehkS6/h9CVYJASS/8s5yqZ8o0j+voF/Mx5t7+NByevxDgRie/r5yLAtds3h1n37Zz1Ts///AGdwAAAHxBm0AvwCh8BFZf/0Emp/ARECR6t7orQIp3gSRE8Aj/mGXd/Bl8CBAi+GhB6PfCYdH2f/4fu4rdzw8/mWDDDwrcF/x7DtJ9a0X9a0HIPoMzYNMvh8HxrgROrqgyUnkZr4Zlj5gRuykL37/PXDU5P4Efw1bC/3SD8Os+8AZ5AAAAgUGbYC/AfZf/oEgYVVtL4IeqtAiL6R3v1aBG04Eg8TALPhgEHwIGIXXgInAidECQby1X8Pn4fL6Mgy36gj3vl+GY75uXag15f/AiVSI9dHOvz3KJekV4EZfYITaGbWFd6sgR9s9YILxrfw8in/0iwI/wJHwJHwJHwJHwJHwJHwCiQAAAAH5Bm4AvwH/4IwUKumQEUv/6DLeqt+rQGweNgNbAkAwxHr4HDEQgbAIrSA4e8BAgQIEVbBjRxXWeGkOH+dh/Ef0Gg5mhWPF0NBk/9AhjTJ2foEXpHavPdTr8v+BGL9/KGzc376HD1+38oajPP/1w5L8H8CP2r9znIvwg0//gDO4AAAB2QZugL8Aohf/4Ej0Ob4CIgSTx8Br+YKbvEcCNQHoBIYhBXOuIWBFP2fgRH0kcOKQNg12fgbsTv/Pv47zQr9r6J3f4IZcLnqBE6qpIEfsMwiWnfUcppknd/X4clYkZr8jyq8CP2ci4dZfwT/Gkf56kN8Uf/gDO4AAAAGtBm8AvwCiVATmIX4CIy//wItcCR8CR9n4CO4IIEfEc/XEQEY/PIHnv9L1rXPYT8wb/1R6gq87+LC4ESpD1h6X5/+gRiT/vrqzkWHuVcI+BHXd77wX82dztWGrN+Hl9+BH85lh1n3/7WKAM7gAAAE5Bm+AvwH96BU0CTwEhALLfd8BqPr1TyHG4fCPz/8aF++j1+IQkGpLsCL19IS3/dQIz+cEZuEquotd0sECO/U5F+B/NfqU9Qgeev/gDO4AAAABtQZoAL8B9+JDHDdMzUCXwEhiEE4BZj+fgRuCnELiF+CmAjH5EcMKNvpe+v8nly49+oEbo5Zfh22tz68k54vp1K/AjLqziF8i8zGu+BHuc5FhM4Z9/9M9UKfT/wI9cCR8CR8CR8CR8CR8CR8AokAAAAGZBmiAvwCAeUMKuBEwhQZSJcZASJ1gEdqBXxC4hcQsBGdBoPKupwqff/R6huKn4fSS+30oavWqmLFUfgRbkPX8O20+84ljh5b7/+BHXd77sUZjfTpwI/nJL8N5r77z18jmhuF+AM7gAAABmQZpAL8AooQWnXtt4BrxL5/P4jgReBp+IoVwI30+BgU4cy/JUbF/y//ghuDbZeoETrf6P2/w4S8klhm/Hv/SPnIEZ/nEKxQjxt/fAuWCPy9wBH5Q0Q/62CcbPtP/6PUjbO1z/wBncAAAAXkGaYC/AGeHfP5/PwInhoPFx7r8D/nfql74CZrUFvNDVfh6DNRzuoOs1/Ajdd1AjL71/Ajr4YDXSWCao015h0BlcPWfXeCHcvsiOPJgRvgSPgSPgSPgSPgSPgSPgFEgAAABoQZqAL8AZ+fgROiB5V/n18YCbrSu1Odh/P/gvDm73fhTDiJZMGv/nr8MDPvwIlyfQaOq6/ht1n8hOX+oEZfYm8+hHknufa6wvwvudvrdVjqXRusAjrvDJr3VEEfvn/+e8SN4qf/4AzuAAAABLQZqgL8AcIvo4cnAStOvKL+jwnv1BQEpe+99fghuWm4Ai9I+vrqQ5c58PrafAjLuziF8k5n67/FYEbzmc/DuBP9nufIA8f9X8AZ3AAAAAM0GawC/AHB+QPO/W+a97fWevyhUI8MifqlcAROq8xb39nExQx9/4CO5TjmENxUn/3AGdwAAAAEhBmuAvwBwb6yB535f/r8w3d9+/WBFqQ4hYS8u1/+q8EIl74IEUZCcapr5QTBpDrljXWX+p7NenAj+cxT/KJhF5+vqV5fgDO4AAAAA2QZsAL8Ao/GoJJ0AI9e+cUvnDuMh+a+i6rAjdfwEfynI2EPH9uLcf+z1IezfE+HBK2c9/AGdwAAAAT0GbIC/AKIIQUPkQuIXGLTIAR5dHFOYHZxf5fd3wInSKwv/qSBHX2FvIuX3O3pBSHVr/6/BPx9N2sfoEfzmKfhHvrw5F8aRuvs/Lcn/gDO4AAAA4QZtAL8Aoi+GdfE6/xCwJB+AfV/V2oaDl1qezBIJuO0H+BI6ONr8Ppfv4COfynCDjzT1rtVwgDO4AAABjQZtgL8Aoi+WuN+WBH+BI+BI+BI+BI+BI+BI+BFfXR3z9XQIQ4PNH3gROgqW95mzLr7h5Lv66DPVVhF263BmReVcCOvs9p160OJV9fwI/YaEZ/g/xv/sM9XUwzGOyjlea4AzuAAAATEGbgC/AKIaIf/0Hr+IXELiFgCPejhzo8Gfpj4sRgPXnUPwW6T5YF94QI3gjPn9q8MnP/6GKU/4CO7OEMsy0af/y/cl56hqTb/8AZ3AAAABZQZugL8AxnBb8EOIJ+C2BF+BI+BI+BI+BIO8CT8CN5w8vlqPvXr64ID1+YkGoa7Ai9fBAGxJ/1eSH/UCQ9vFm5fk8CPcWGiZ/gzLQ0z1/z1zd5/4dlxPgDO4AAABIQZvAL8B/CFgI7gz+DHEfwawIvwJHwJHwJHwJHwJHwI/kDx++q60DAuqwJHUCMurKW3W+XDnDVZs/MvDj4CP5zL/DrPvuAM7gAAAAREGb4C/AKJ6EJ1EeI8QsCKeJz+fz8A+voOVJ7u+BF6R2NfojIEfsTe35tAkWxoZNN9TK3hF4Nf8oZx2m1/ggfG9YAzuAAAAAYEGaAC/AKJ6MlX1SqI8QsBG8GPwd4jxHAi/AkfAkfAkfAkfAkLgwrOz35w4vhE98/gROg0Xn6w1b7+uoEfz1J6f6+w1ItV2Mzjz/AjrtM4hx/AmH8Z5V5Z6nXh9xv+AM7gAAAE9BmiAvwDqcFfwV4hfh+BF+BI+BI+BI+BI+BJ+uHjhxcJON8f4EZ9KGznXvX8Prad//SPUCMvv7gR+UMhC91fAQ76vH+wz44q/1hyFfgDO4AAAAU0GaQC/AMYfz+fz8CLw/8lCOBF+BI+BI+BI+BI+BI4aMHFv/Xl3eBF9H2rzEy8/+GRuf/Hwnb58BHdhwJRr2LvDrPpX4J/H3rXdnrhBv1/q/8AZ3AAAAU0GaYC/AffgkDDu95fBHd7vAah4Xz+fz8CLw78lCFgRfgSPgSPgSPgSOGGGt0tcCP0jvv73/+hNFkCN0CEZyd2uHJzRCxwI/KjV+ev4T4f34AzuAAAAATEGagC/AMYd8/n8/AinWBI4IcR4jxHALL5w4reHYbPwJHho831/Hhf7XX6E+IEbyjOEdeAJFRIcNufK8O574SvP+lqQ/O5g89P8AZ3AAAAA3QZqgL8AQ5wT4hcQuIWAWnzhxQLv7N/wI/ghHn/uQEc/lOEmeHkSz/sN8YXX5VofvdYEfjIAvSAAAADxBmsAvwDqn8/n4EU/n8/3A3wC0eC0OTYvd+UCR5x/iGLF/wEcX7lSzhJeEumJZ4ZiSa7s9cSfzHr/gDO4AAABbQZrgL8AonoIfxiiusYq+gNnlgReCH4fxC4gmBF+BI+BI+BHfkD3w8xhsrnYdgR/BEFry9qX1+hNyBG6OMX8cv/xV38NUMCMdhv5wyCC938I/fP9cuCPd+EAZ3AAAAFJBmwAvwH/6BQ8CN6C/YhWoxWqgI07E0d88sBG8FuIX4K8QsBG1wJFcCY8T4EVfSCD1WhNyAjuU4ScfwrC9f4b8/XD0rv+BHssgRjHvJ69fwBecAAAAVUGbIC/AKP6CXQGueLgRuCPELiFxHAI4/XWr2/c4UX5kQ2HbAkeh/iBGXVlGF52cCQupTCG581+GS8sl/AGAeXb8ngR6lgSPgSPgSPgSPgSPgSPgFEgAAAAyQZtAL8A6p+Ajz+fz+fgSKgWYBH+vwQjj/3ICO5ThQwu4flif7OUAX5C2a2/Aj3FwBekAAABTQZtgL8AgHoNOgIwWxYrti9XoX3gI07Ln6O8BG8CPiPEfwVwGp4gJQ77Z+i8i3/3UXwIq+q9D/EBHF/7lBIEt0u13nKqqYNfgR/6ZTlUINz/gC84AAAByQZuAL8B9+FAxy/d73e7sgSfHFd3d7ve4Ej1/QvxQEcdi7O8BG1A+9fXiOA1fCwSDv/ZmaX017fvwlmwucmYEj0NuQI726OKWd9/Aj8oZET/XM8bPf1rnKumXyeDeHLAj2xMCR8CR8CR8CR8CR8CR8AokAAAAcEGboC/AIB4kNbvd3AI4djXR+BG9Xz+fxfTICKdHzoudc/Ai3AVvf34jgRL0Fmzw3n4EZ+T5YTDmTJP34a6pdg3s/94nwI/ob4gRuvzCmqwI/aEYb7yFyLwI9xJ6/BI9s4Ej4Ej4Ej4Ej4Ej4Ej4BRIAAABkQZvAL8AongkCl7vQxRW+IVoBGi31i/2L9Yz9Ai4QwJH3wNPXAifAkcGeIfEfwVwGt5eM1a9FuQEcvlOEpfzKzTr6OXuEv68N20wI/Z6w0z1/3FrUCP8CR8CR8CR8CR8CR8AokAAAAFJBm+AvwChnfxHGILCt4BIzvAieh6dL1TqI4EU/n8/n4CMfZO98EYUd/C13lxOC4Ej0N8QEc+5dfwI9TnHLArnfX+BI+BI+BI+BI+BI+BI+AUSAAAAAhkGaAC/AfghAkcCXgeeLd3gRTwjQt7QIp3dH4EYWy6z6z6xmsUBG+hKVT+fxHAinRc651zrAi8EOK8R/D8CJ4Ig0u/QJfiizfyb+hdyBG6BGK4Wrr6BJzRuAI/Kc0YFfhpOD67uBH7P1/Duf/c56hO8/XzBw3p+BH+BI+BI+BI+BI+BI+AUSAAAAVkGaIC/AffgkDF7vQhDi4AjzsJnUI7/q8CLhDeEcAjwuNpxAj8EPcBE9/w/AirQIO+HkFIPsMy4lqH9HxYXAj+hvQEcvl33wI/Zx2GEFhtXw6z7/cAXnAAAAXUGaQC/AKJgICgo8BsHeBIFyqivFuvYvXNi/FAR1wG3XoSnQEa/4f+FYER+TXNXCgbCir9+GYpqjwGt38oW8q8ucXDcl/4Ed/hreTHwQ+Otf9SnrJfOe/hBp//AF5wAAAHBBmmAvwH8MQKHeBJGIKit4EQ70fcCOd7PwEedYCOOxtHeBG4by//1wjAi+HAoT1qMApdxouOr+wEt+6sAGsvlDhM7a/leUXAkcpyrBFufL4Aq99n3jf8py1CD70Pm//+BH+BI+BI+BI+BI+BI+AUSAAAAAaUGagC/AWx+AjhrCgr47iFxCwEefz+I4EgXr0CQfgJARGwI3E/CMCP8CRxRxynhHCf/XEcCP6J0CRyghI7v+y/fPwI/Z6w6z74Jnlv1/nKpA+PvfwR2of2vgR/gSPgSPgSPgSPgSPgFEgAAAADpBmqAvwH34oMbmEn3gJQ8ud4EfCOBFO+L7QEiLZVqA1X2SQcz3AbNe6uJgSH8vyhkqkXXXw7h34AvOAAAAZ0GawC/AfghAkLSIVwEedj6O8CKLYQd4Eo8J5/PwEaLZfZ/P4z1Aar178NDJskxYcZciP/4IYbyOp+gNVfKbn++feO0xgR7iT8T8BM/1f7/6PUJHGVP/4Ef4Ej4Ej4Ej4Ej4Ej4BRIAAAABDQZrgL8B/+gUJUBEOyuTwQhF33gRj7oQrgRTvAkYzAkHeA23gh8CJ5xSlRH38BtvvPX8auYEdcuesCa5n7A//7gC84AAAAGVBmwAvwH/5QSO/8EYt3d3gRBs4r47iFgJE74jgJA/AiinPwCQF/8pK85l+YPQdhECP19QI77QsLZ/d7gsyZ38N1z9l82gR+w1aaRCqSmErT9fAhPx8j/p4uHj1AZ6ue/M//8AXnAAAAEJBmyAvwCjCEFHAR5+xbCh+6BDOyl5TvAinYTz/6vAik/r/sQsAjvUBIHYTgSeVB6D5YEf4Ej4Ej4Ej4Ej4Ej4BRIAAAAA1QZtAL8Ao+BNmCjvgRDvneAkDu2BHO/6vId4EQv/8A2K+fXXAj1ZxUH4Ref/1nr6e/X8AXnAAAABCQZtgL8B9+CgMS+Xu9ulRfVKICOO+I4EUWy2gSjvn4CNwhgEh6PzH8Sif0cyw0tr/Aj/Akr7EeWWTwI9xqJB3wBecAAAAPUGbgC/AfvoEiVAJA8e4EfEVeBJPwCzexEv/ifLkvwGz5fNwJHKfl+QPQi99fKeoel2/huT73TgRzoPwBVkAAAA7QZugL8B9+gwmH6GJUBIFx4oPivELiFxCwEed8RwEgeWAWjpagI98uUVedoEe405MsN9rj8CQdAhgCrIAAAA4QZvAL8AoZ3gSTvAkn4Brn77+rfqUOXDjlYEj0L8QEc+xWBI5TjiC8NM/43+k4lC16BHOgQwBVkAAAABBQZvgL8B9+QMbuXwTd3fdiBIOxjgQzvILhG+d4CMFu7QJHu94BH6qXqBEXXXUBHrqWBI5TjFnE4ya/TcamuEAXnAAAAAvQZoAL8Axp+Afov/WEg5u8mYEbpHwgSeoEhVywI6u2POKX4bp/Wvn2vQI9SQBVkAAAABSQZogL8B/CECQZaAIwthEUH2bX//e8wdnUXzlc45x2fOwwuguTfodhdQI4rSAjGKw6cPsvnJ7ExP7QD99K5AjdQEhynGLwRfnH/caeundv8AXnAAAACpBmkAvwBwi3q1roPVAj9QEevl1+UsvwI6Tlj9Xqc29FHzXKJwg8/uALzgAAABpQZpgL8B/jECIuPAim//9se7vuwXkJ7sSC2PrOKmO5jv+x4CO9Xo3//xN7AtgW6FWb//4z0D0KxcCL6vYnaALJ1IvogqXL+ldAidQGzceF+f+P+XgiPzz/5T+5A+f6nWHoc1gRxCDsAVZAAAAVUGagC/AffgkDF3DDsPiEKB7sBIDY8V9hjaMdyH8p7YTC+gcqPwIwV+QWnO+gmP9neAa9+qFPAkdIbYgR3/Ajl/6yiL1AkP5Tmf/BM8ZhfKXTJmALzgAAABQQZqgL8AgHoNJ4EP0Z6vBKNd973gI4WxTvdaGvAji+2b//4Z0LQumgNV+BIwEjdIc4J4IbivqBEuvqAkS/98CPynrwS7HTP6vi4EcQg7AFWQAAAB8QZrAL8B/egRPAjHQ+gsorKKHFTHcch/MI5DOx8K4roLk3sKQSmO4Ec3//w9UhXAj14TRT4diYVkEjCth0NhUEQ6cbgQEcL8p3Y/K5xr9oCOO8BsdIIPI6pe6VyBG6/Q/5AjdQEgT+7l40ODt3hj+BH+H71puL4EfhKAKsgAAAFRBmuAvwH6MQIC49+JPkFnd7gIwKkP8gqgv8rYEu9XgRvRXgFm84Qt8qIOs++98/KHZ/f/t+sCN1+Q/LwI/gm3d7vggSPL59AkcvywI/IQIxj3AFWQAAABvQZsAL8AogTQSzlspcrjEXhKgpDbS7RXY4V5mlKZhWx8M3vTnWj2OvBhUDAjehj1ehbwJNcBtD2Ks+94DT6P/hwbr/vulit9Ya0p8wqBvxIx0MP/6gR/Q2oEWuAkbjxAQvfP+6gR6kONWE35/AFWQAAAAVkGbIC/AffgkDDu7sl8M86ZBZfFvgI0Ko58K2xkP5TxDthMKsd/IXRv5/8Xyjmxe8A+q3/lRXp+sCLyfX0cYvw3ORwEf0euHvvwJHKhDir4mBHv74AquAAAAW0GbQC/AKLXZ2CBwIwVQ9ZDspT5SucWOK4DW8l9wCP9bvkDI7denrh2HP/6CbUtaOEF8w6YkHpaP3JAj3ofYgI/qBHXynCXeGuL/PAj6wJHwJHwJHwJHwJHwCiQAAACaQZtgL8B+egQPAlm8Vj+o0EQh5Z4wkqFPQoweyiy95G720oOgiBpW9FjoSXqPp0BGroKqbJCJSnyCudj25jgEUMb0NgM7inSiDRtO4T+qoOcQmKfQDYecIV8gSw6l/EX/636/hnP+oJ29nw2zv4EUv/X9QEf0GT3r1ZF/gSFfHmEHXvr5T1Y4cW0/Aj3nKvwi99fvPVR3/gCq4AAAAHJBm4AvwCi14WhIHXgZXsU12nHXBNZDtLZhEpWgw7E05BVzTiuBHvgI83+X9lvvMLGD2cjL2gJEVLAkClgI65PpBTq8EgV4cefqvpBR4EfzhP5DF+X/Aj+QY94CP5dfonQI/ouoEj4Ej4Ej4Ej4Ej4BRIAAAABqQZugL8AQ7Wgg0CSb/+vCWxXH3R8AjvnCUVw1n3/8F3d3vqvQVbqiBKXP4IbvkNAicnchxKvI/+89Yblnzol+9CfkCL8CR/3v+BHqLQQi61KkCPc4aLDf7kTDu5+AMOr6Z/TnIv8/fAFVwAAAAF9Bm8AvwH34Ig1u94Db9CagR74BIOoEbpBCu6P6Pgqt+oaRWv2btImXP0rwI9UgnYgI9fKhTwI5P7+WP1c2U17gR/OVfgh8vv/vPXwINfv+l/wI/wJHwJHwJHwJHwCiQAAAAFVBm+AvwBnfSDU8vR6/j38CHUhxFn4fZ373zXva1+5FIUCN19nCvz4YpnwJAuPgYPccYCO7QIJa+4Ee405VgQF8NZ+BE1d//wJHwJHwJHwJHwJHwCiQAAAARUGaAC/AHCPeq6Q58v9eC8JZN3TqNlcM3zCqRY/BPobhQ8hyHgReT+A2OXf8CPcWcqwQbPtX/vPUCB/99X/8EmjP/4AquAAAADNBmiAvwBnfRw1F/UdNBeoEPraVVXoa2ta+oBHX8+l+BHuPOOWBDlofL/9560HH9r/gCq4AAABUQZpAL8AZ30cNHB4nuCF73tIl89KP4Q7YwIdSdyHEKJQlkDXrpBN+qQQw6qBFuZH6ukPsQJHwJB2NgRuyh7jVPa9Aj3G7WJz1Ag/r+//CfD+/4AquAAAAUUGaYC/AGd+LDXL8uS9Hvwi9i/Ahv0t5W9dIW3dHCCwjegNpK/8CLUlE/r/7pBWxAay+X5ShC8jIEe4s9YaXM+Av/W9H+e79PL4/Ajnh2AJkgAAAAGtBmoAvwCjegs0A+vRyMeHcCM4+Gt0l6DfGvZVH8Dbp3gQ+vwyILm9S1xoNfov/0gi/0ghlAjdf9zIMpUBGXXAk/AjrklQS/8TAj9hruFllrAmGs+Wf/9nrE9mOf/+BH+BI+BI+BI+BI+AUSAAAAExBmqAvwCiL+BL6gGs6Qaik1MEeXPSCBRQIdyfRxHfBM8ZhfMDWvpcPz5oMqX/wInRyr8N276XXAbFRMCPVnrBMuM/Xgh8f2n7ngCq4AAAAfkGawC/AffoNN+hDQJBf6+y/9YIhq1+gH0qg4THfb8IWn6S7r5Nfw3w49a4Bry5ef4EPr6q5jn/4e+/dnHY/yg4OIpqQX/T2+BE6/KJP7feGt6a0i3G4PxOYRAa/ODDL4aeOv1ywf5fijZQdYEe4tEggSPgSPgSPgSPgSPgFEgAAAERBmuAvwCi+gs1F//gH06OZf4MaWTJDITqteOd/qBEqS+jhhQ927KK1/4EWs5Vj9j/6/+DxhcAgqqh/wCPXHoMQd8AVXAAAAFNBmwArwH6IWBH9BRqX0Sq8v/1AjdK0A13RzLgm+P/uRlV83ksV+j1wdRrgoqd4EO5u+uRHmgR+jk18M273CXVQI/rFASC+J11l3uBHudGg74AquAAAAFRBmyAnwCiF/+rL/XwI4WhImpEOznERhf2Iwv/9WgGsfSRzLjDVbLz2bWKj+hH6DY7VXcPav8CIvo4iCNF16+6EkgReT6/2nwK0Aj1wiYrlp74AquAAAABMQZtAK8Ao3ghClVVoEbpWvqAazoEgjNZYsSOsRQR76gQ+T6OFlIFSDswv66Q9/zjFMDj0YsNTJQXzA9gRqkgSPgNjl7j4Ec6BHAEyQAAAAGhBm2AnwH8IWBG1u6QSaBH3gRvW1hn9F53ZkFj0P0AsnRxC8Cbrd78O4D7V5KG3+jjFwb5f4ETpCJV0cIr/CPcAjXEImP+rgoYbDHvgRvKGp1+l5wRXf/ASC6lPXyvlfAj3CJhDlzAFWQAAAGhBm4AnwCiboJN+COq7X7GVqBF9jdVVUvQIvUAs/SEPWlWScaVXhqcngTfn23o4xf9vPuBD4Q6pCJ66ME+MoNUhxxdw0rwIfwJHwJHwJH15RPNwI31cI98CL9iEHYEX4Ej4Ej4Ej4BRoAAAAFZBm6AnwCh+g83vRf/wUDarVVVoEbper1aBG6Xv1bul9ALLUhxD86UFfO/1nEgCuK8f76+jiFwbbP8CJ1XX5yZQ1FVvLPF8o6GUVHwI1zQCQXCPfAFVwAAAAHVBm8ArwH34JAwuv0CTr+MKuq16qtVl//7x1V1XVVgRvBbrVa/V4JarVcnaBG6+oEbpW/VoBHujiF/MFB5/8s4lfyL6d36Sro8wvAo9Mb4R7no4pf5aFAiU0cyhnjf+ujhOLw4l/eHFvwI/XVdRkAj1x/ywBVcAAABqQZvgJ8AgHlC1Z5gRC/96P34JNTin76/BJVVVvwRjK1ZAiDGLVoEnqAWZ+15d9Hrwj19f9FFZLJYETr8oXwR//P11QaDC3qWuYof+pIES5OqDZ1vUPW/+8j/xV923wCP3COrvgRxCDcATJAAAAJ5BmgAnwH/6DzQIoaQ8KFlMRlLQ0zNaOsvHjrzsd9LUCQFFmO2NBY1A2OpTnv+gVVzWqqtfe0TPUgewItUrV4KarWqrlFFaBG39/1aBGL//Aa/QbGcvXHnWY3fPSHouhO+kJ76OIXA3c++DfKwIlCCHNB8I/MJh5FC6QRw/OKw+HUOe9HTwItSHG9hDzb/+BIXXAbBf/l7j4EgQgzAExwAAAGRBmiAnwDGDGEFatcKKux43UQWmdj+BF7+wSVnDtvrCe7C+U7M84tubMKoYEX7CmLmb/r+BFrrqA1euxu6kObvCL2N/qBEL9V1XIevDVtP9wI3IrlXUCPWfF+yj9wBr3CPfAFVwAAAAd0GaQCfAffoLNAk+jtXgi6r2+nBDlKV6BG6Vvy11AjdK3ywI+kretdwI3q3WrdcBqVIHBm7rkCYGfn3+XdzBw/Fa8IvY3+g2I3dcezPwInRyVKmzmV/t/rqoEWpL5IEb4CQ5gSC8n4gBIuEe+BHujhNfhN+cATJAAAAAXEGaYCfAKIX3//BEEDda9AjehzQCRDIR1XrUBGdHHL/Ct9bG7VYVCBzrw8c/DkV4+oERutIZKujjV/hqi+cyhFxlxg6f8CNcRVSQJF8BrXCPfAj3nGrCb8/74AmOAAAAxEGagCfAffkC2q/QhpPBGJ1VJAi9I9fgprqq1Vat+CLM1ZaBFN9rf9UREi6Aur/IU6t4EbX8JaqtawzzoLxBlEFgaWhlHPtNAjdYjYOI4EYv/4Iq6tfStAj9LaAjeg4M3dcqIbl/y70upA3efK/gt53gROjkX1MLzCfkOFVw4+/+YVy+t1OavhmLpvLPWwIq6gwDQTmXuvwZ0v+/zhBfh239j+kcFagLv9j/wIy69XUsBrl/+dAw7uEYEe84tYcR/9rAExwAAACQQZqgJ8AolV1ghCC1tAkE+v+vtWgRRbHG7q6Q9oEfV11datAj7k6qBG9bQEfcQcYvB+ZzlgeRHl30cq8CPeNxw3n30GyXeuw7P+BE6DhH3U44H0sX/5EE+/OIXgR789/wyTd1BHs/vXF/4EZfX4re93gEfuPMY/+7gR+UND4jmRPwIr6efAkfAkfAkfAkfAKJAAAAiUGawCfAKJqgg316wI1P916tAi2o6taqutev1+rQIv/StWsCL61fAxQI3q0CQX/+BG6OMXKiH2f9z1/hxFSb9FZ9HMv4sKBDuOQnvpinN/bEHCa47p/2t9iGxl76iEL1Ah/l9a/rquBE+BI++eBF+BI+rhXvgRfq85l+ELc++BF+BI+BI+BI+AUaAAAAdkGa4CfAKL37oIN+LqtVWv0OaBH6gJAv/8COX/9DbQJIrgRuCyBG6OKX+JhP564FGgo376OVxwm8yvDgh83kKab4ETz4OUXjY3ERjIT3B5+GS3L9R0SHsrA9wYfeLwIrWBW6/vgEe5+ouBHuLDV31hjAj/vgCY4AAACMQZsAJ8B9+YLVqvQpoEfyhGq6+idSh4CPqrV19wIvSt/XUCL62r1t8C1AjCtY3tAjcDhQh4EaoFeBHayNBwY+640LUnX19cqr9b9JF76OZcDp8v8CHzIIu+c4QUd7/q4r9FcgRUowH33feesrE7/AkfAa9wj3wI95/Y13/eGSm19U7uvgIN+v+v+AJjgAAAB1QZsgJ8B/CECA2Lyi1XAi9wJHSK0BICvL/+vQI3AQEBJ+rQInXQmcV3DcVJ++jlXhGcfNeA/4Vr9IzACJyH5cJ+Mr/CHjyXvrQ3qqRCHIEXk7r5OqgRTw/ST5TBwreA17hExj/+4Ee/vOJUPu38BTe/0/AExwAAAAjUGbQCfAKGLYeHqOk8Eo9a1WrQIvX0WtfT9YEX1rL+/10rQIpP0v8XqqrVUX7/WqFsIE7IEX0EWxHiOAjxHAiprkDgxy5r/DrPu4g/7hpFevITRdzq4LjBnd76SBIFs0Xi01tQInVddyK5AjckCQv/lgNfn1/Aj3F/hnd6ggfP7X/gR/gSPgSPgSPgFEgAAAAJNBm2AnwCiLekEG+lb7fJ/qBF9ay//2dhAnAiXoI1l//VvlVvfeBR8CIT3yf6L//ASIvVoEUdq0COr4g4xjwsxeHWfdBAILXdMIquujjl0wbwVeCEaPvWvo5GH892BEaRY0ar9xBxb/wxbX/r6OROIDqmGR/w2Q7H+BGvDfGaakhFR/gSF/AbHKyXl9XxsCPf3wBMcAAABxQZuAJ8Aou8CSt0kEG+1aBF4CEy/X8CNwExT/y//q3wEB1wIf9d3wIn9cCOd/gZ7uBBWoERfRxi/lTPvYdXt/9QKpgzlY9kDgW3djmoDeCr90nomeBEWslurigQnlg/FAi1wCRdwI9wj3nr4fl1fAExwAAACOQZugJ8B9+gs0CTvAkVgjOtfvVW94EUv/+/8v/9F/rpagRl/1ARECV6CDIEeuBG4ESBGX0CQpLGffP0Jr21+tkOUovAm3n3B44Vwq0M616aNhAiUIMSWP1MhfdyIzECNcnXQ2C2G7h9wI3wEjyQI5f+WLIC7P/lC294hY18z5nwI9xsCR8CR8CR8CR8AokAAAAH1Bm8AnwCidV4JAlqrQIvASGX/9agRzvv/L/+aq+s1a5f/4EYRuA2uKRegRH00ccUXM8Yev+g3e9j/CJg2r6pD2rr6OOU2xb4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SC7Z/Ak/AkfAkfAkfAkfAkfAkfAkfAkfAkfAkfAkfBHAAAAGRBmwAvwFofgShiBMGGWYgRTsrgSTsfASB3gSMIZBbCB+8BHiITgRS//wEh4cGLepC7xrv5Jb3a7/hsqk38Bood9yhQyUYe/dq5Ai6hqTBfFTz5EYXXr7xPDNX8oTvYv/8VAHBQAAAAOkGbIC/AWx+A1z8BIH6PwEad8/n8/AjeglngR8VgI9+rGTS09b6L/CRarVcCNkkJHPfuypCP+oYgDgoAAAAtQZtAL8Ao4xBQVvARnoc8CWePcBHHeASDU4hx4aimvnCSs8vlukn4EZ13AHCQAAAASkGbYC/AffgnDG5aPb3gSRcor/jFtAkn3AI6LYQEPeU7n4BG3673XyQ2fP8X8wVLvc5V4I/jevAj6kIonTl8/8MlNR9QnfD/4A4OAAAAQEGbgC/AKMIWBJPwIp2Fnn8/iOAjTu4CR9FavV4CN4n5oEpNO8CNqGhk1M6YHW5fgN/X1/cMlHmj5xfoM9/AHBwAAAA4QZugL8AxYtgkvASh4RgRH4EDR/PvEcAsuvknFLh3Aj/uYubH+ep7MRID+UKjJW4EbJRCC94A4OAAAABXQZvAL8B9+CMMS/ZQhDAwyyGK7wIxv//QJwihfYNn9XgRjZJ6EH2Xeugn0O7EvAR53vE1eAWXi4Erff5DWiZgRtQ0RQv7rGu//DM/Rfq//wxnr94S8AcFAAAALkGb4C/AWp+A2T8BIHehbBIfvAanoJ/gJMQiwIqvJQ7LyVYASGuaTC/37rlAHBwAAABDQZoAL8AofoETwJhv//hMb2KgVAwEcfgNf0e0BseGRmkSCnGcNz+fpe56/nMjJegRuGPUNY8vIL6hXNe8T3XevgDg4AAAAF9BmiAvwH76BE8COb//6Hu5y/ffmHP+xOKwInocz9D3sn1X/AkC93xbHH7wCOegn+vV4DWfqHBgl96/wncN21uHPL11LT6rz8q30/89fDDPvwIuoamoF/udMFmnP4A4SAAAAFJBmkAvwCAeCYMbu7veBGGIoreAjvV83//wQ9jWb//TEyF5KSh293wCPei2/V4DYzSjsKq/cx73+GuaFfHSk5K4EcCM9b/DJA+fp5xQVeV/wBwcAAAAOkGaYC/AffgkDF3vAlBWV0NhMpiv8iDaRv//u8xKwbCedPnKvgSBalYvnYw/ALJ6CLwCQ6+6HHSAODgAAABjQZqAL8B/egRPAjeCEe99QJHiLu975vlgP7V6EhMH7B6B1yzf//BTQOcp6B1Akm//xoJ0IhX6BgH1fqhD+TvhVzlXhmJ94dipPhubKWKRK7Ar/Ai8dtLK+sNGd9fjEXdHwBwcAAAAI0GaoC/AKGPYIHXzQmhAFF6aE9Aj6nELD7Af/2eqtnH/AHBwAAAAO0GawC/AffnDC/Fs0MvhnkIkLu+LfAiDkUSPevWvwW3fd7vAFCP3vwSExr2Rte8CNqGhCrr8FNO+AOEgAAAAW0Ga4C/AfghAkGWQEmtBF4EcJ6dD8x/OaRfyehTwIYbcQ+tf6+vmhXDEWuilf+xpWvoB+PMK4n+SXn/uc68Eqsu0+9VBETJ+X7I4VfcCK9bcS571c9fjE1fAHBwAAAA4QZsAL8ApB2CJwI4ZhF4qEYUe/nCpRaA6CkL7oCQE6gGsuv2Me8CTqfKGOIfmf/fGwQxqhqgBwUAAAABeQZsgL8AooUQUPRDKXZZisp2yRMKsmNfEVARjsU4EzwQjXyBaoEgKqqB8Yc/YVqgvAavghO97QGwvU4SVcMQwnrcx+OyfISXH5Pvr9kJiWBFerf4Zmyk+oYZ9/4A4OAAAAJpBm0AvwH8EECAVsfTT4hYEUJsfnMnPvFTFUDiQNphY4tQbijxNoTe1BnmFcrzF2FzBZxTIUQ6CdhfVmU+Y08KMJh0IqB6/zncxw5N0CKFdaH6BmP0GUVOaRK4Or4V10MjWFyhIrXmcwTgVBAJLeA1BbGWSj3r78Bp9K/7pT4f8n8OCcslw/wRXH2ov1gRtQ0Klul0hYbnf4A4SAAAAOUGbYC/AffjAxyVxloh2KXvIN3L5b7gRa0d4Er3Hy12BSAfXhGBM6gRdQ0OU2SYUvlHxhn7yt4A4OAAAAIRBm4AvwCiVoJP3q9erwI4a1KdOXG35BocpdE4OsPUD2jCTD7wI4V1nCDmKIccd5QhY2nuyRAI8MynxhHHOUfoJheYu1usLacxGgOY7YXQ2FlOgI31/Aa/nCSwV0+/73zT/7NOdcImmM+He79P+C3Cit+Gxwx7igRtsMmfdftCQ0+uAOEgAAABNQZugL8Ax9cAsvoZbMf//hHHZv/9cEWUvu/VoCM6QyUvR7/wj3MCH1I/TORY6Co//qBEXFf5yKjGZf/uFY17ZmfPChbh47wdiJ6YA4OAAAAA4QZvAL8B+jECAQ0YgH39BP/Wrfr/9XgI7ngR/BCEhte8VbhwXy9eHu58CO9RkgrkzuCK9/d8AcFAAAAA3QZvgL8AotcA1/odb9X/W0BG9HFFTxPfL6ugQ7kOKWNe/rVC/lLXKafP0iRQIuoIstw76XvAHBwAAAGBBmgAvwCjeUJc7wJPgi5W2QI4Z1GZriYQ2PfYXamF+hHI/QCPei/r1/ARvnFYfwj3FpoLVH/cJfz8CH5xVf07O/XWbzdeYbjf5Aj6hoVyZBUcMvD+n97eev0+fWBXgDg4AAABGQZogL8AXp6HWr1tARvRhWNey+fX8O53gQ+kK78OX1l8NIr14+GFeYbx7KtcEQi6fX0iVAivzQS3X5MOm9vPUZnXlf4A4OAAAAGBBmkAvwCi+CQKcbaKgGv9H/Xr+AjfDArhx7blfw/f9aWL0G+WzTAFfwy3XAiPfOKUeBX5FH8kEY3G8cFP0ziFkHzX+BGepoa8OnnhiK1iugLw8wZgf9hn29/w3FOvgDg4AAABKQZpgL8AXp6HWr1tARvRxUX8h8tlL/tZ64It2PwIdyIVF+E5ctNnl1uYby/qC8RCj7dyfw/CbhtSYEf9I0ECLqIKfPyZ98mQBwcAAAAAvQZqAL8AXp6Hfr1/+rQGqt+36nCD4738CM9TQ15vOVDeev/dE1jYJ4OIBwUYA4KAAAABdQZqgL8AonghChzh0O0BJhXUiAh0hRWW/7h+gmG0gkEAR0n1/6PVetv1eAjOjjFxkvkuBPCH3wXpWIEPre3nEKuTf6/nGrwh0zPDiT3WuURPnL/+jSgRXq33cAcHAAAAAM0GawC/AF6egh1erwEb5hWO+y1Iexw3nrwPdLwIfUj9QkbJ5f9aJKBEtd1nLvL3xHIA4OAAAAGdBmuAvwCi+gp6gzw/zWn0u2rXgc6w14vVZ3RPW3nccgl7m6AI86OZcPRFuLeXw3zRdhhxp/wIdza6tCsrWucq/D0T2+BG1DMSwa1RhszXnCQTKvn5fLfw1V87TaphU/N9NulgV4A4OAAAAPkGbAC/AOt6C1QDWvpzkSrOfCZsPL0rwIj3wmK5uK+t/wXliGj8fX1jINIbkp/wIz1Ty/r4IeJ0/N4Q8AcFAAAAASkGbIC/AHB9HDi44LdiLPM2k6OEV4R7n+g2EMhdXcnzX4EPpCMPwze+CEfg1//Wl+CMrvnBAjahmJc6hiKk//cEvNTPnhtQh4A4KAAAAZkGbQCvAKI/oEYSIHK2rwRZiiGx7QI3gk1W31+CSrBlntAkdQDW+YRgW7gDYk2kESp+UIZcBa40BDqRCMN9Zp4ZuvMP41+T2rVf+IgQ/V61Coo8L83EmhBfKDw4z17z89R1ov/AHBwAAAEZBm2AnwDGF/74EnqAa7qSjfo4YX8K2eBDubXVmEFb30Gi5JVDc7yFFa/8CLfvyQ15sOmE2w/9wrw+Ypz/y/DeA4L+SAOCgAAAAfkGbgCfAKJ4TCFa0S116q0CO+i8K8eb6E4Ue9oqqtFfpDN/lhTQS+XwLQQB9KkDgjU5pnMiAu6nrwRXT8ybRwiAi8PR8BF/kW70Gwhqai4dXL/4EPziFpEf/8+qgMPk4TuPpfIGn2FS8viXNfmpM2ZjKBeBGere+tdbxngDgoAAAAENBm6AvwCi+CMLVq0CP1AlF+v1b6VoBHvRW+laAjepF9fUCHyfSCnx7pfnLhh5xf/FL0CK/bDPjSuVHJr/er7UZ4A4KAAAAY0GbwC/AKL5gpVYEcvs/lkzoQ5dA+oJchWrFa9oEj1aAj+oBH6kDgrNRVzKw1E69c1ahwfy9f4Jvzu7yrOOX9Hn3AiLfrziV4Zvv+vpDNQI3YZnzwfZjUv/DPC1fCEnw//AHBwAAAEtBm+AvwH6IWBIXr+CQKVW0CMX/XqtWgR+vr1gSOizL8AsZ4V+jh7vDTL/X95P0G+aBdXBa4D/AiUOCDELuye1f5MCO+8hR6r4A4OAAAABfQZoAL8AonSCjX4TyCa9VgRfX1F/XxFdc6/4IuqtAje+qreASAUiwEZ0ccv5S4B3VXxsTvU4teHEV9/1Ahk+//1v/rF+HPBK18l/gjuMFEv6vlHJv8CL3l9br/U6QBwcAAAB0QZogL8B/CFgR+kFG/FVVV59AjetV1AjBl1nOovYTBznbHAzHWF9ANf0HBWkWa5i4yz+v7yTi+/wIHq5qQ4pcJPfPyGouBDuCbX2YQ+r6DRTQ6+PA/aBW8CNTKflCHDLtNn3Zo+Da01/Z6/DOdmnGXHgDg4AAAACVQZpAL8Ao3lCir/BFWtoEXwS9TCyr+y//QSrqYdVV+TKar6NIeylQI4axHCoyGyGmCExohnOiIOOFyj/YX2FtIZhmnoOMwsxPPPZx+ccd4EjpWgSOoBHOjilw0iKqWf20L95KExfUCJ4ZCD7wfDcPX9+GiiGD+EOw5N6b1uehA/gRn9gu8aV34Mvp/nqGoktNm/gDg4AAAABkQZpgL8AonhEKVqq1Vf5fGJz7quvQ5kCN4Ix/JD2vuAjgwq41m0n/5RVBbQCzdHFPyiwy/8yIO7rsXvX6PXA3c+/gROmIfdeCQK3MTNfJr6QQ1AjP1PVTV/9hrfnhjYlL+AODgAAAAIFBmoAvwCjF/6wRhRHW34uuq6gRi//S+gSAniLEo9jk5+ZqC2iDQdzauhwI4Z3lO5x3YUxb6C6jVANIaP70BMVC2PROkRXgFl6976OReAx6tv/RREtpYERfnIoSUPtakr5rn1PfhsoT0loPaknnLv+BG7ZB/H/hntE6+HYqT+uAOCgAAACUQZqgL8B9+CQNLW0CT5j6r8RVaqqoQEfwhVCqqrVeX/61+CHVdQIy1pWpaqrQI+vvhpchSYeRFQ8z/zitoEXpWvpWgEcqQ4xeEiwz7w3FcvV0InEy8IvYuHYkj0cQv8+RgROg4R83l8ZIvjAcvnCK4aYEf10cYvyC7QSGL7fzLqBFdbKcmX4+GFyPHYsv3+Tk2AODgAAAAIBBmsAvwH/6BEmQEX0Pb9WgR/Vsv1/Xgrquta1+gSH06tAi+tr6gResM6zHWFR7BezZd2GN4yXZBf2Fsf931AI519HNrhH5/+HXG1SFfX0cy4Gdzv8CIv7X56+HulT4Ebs+CCDR2jjxHf6YamhJHlCPW1EH8/ctK+0Ph/D7jeAODgAAAGJBmuAvwCiF/6wShSqqtffmkp5ffvBJqq9r6gRevfugXarWuvtagRr1brr0OSQDV1J73koTh9FNu4ETohMkq6Q/vw0KL+obl+Wf/5kd4EV+yghEPq4vWy3fjYLYwUGBlgDgoAAAAFBBmwAvwH56BE0ngjErVUkCO/oEJ1WvoEbWBG9DnfUCVehrQEj6tAj80BG3McUuVENzuUKA+I6PvJOVeEeDav+oERr5hB87W/Ajd/lkzgDg4AAAAINBmyAvwH8MQIlaBGe+h9fgs1qqrrXoEYWxytXSHt+COtfoEi67y1VlAi7S91q1VwIvkrWq+tWgRfW2K8RwI3S2gI99CZhg77/LXr6Dhc2Ov8IXn/qQ5lxCR5XPrAiF8ik7DNyxfg+QKkVydpeoEbwzfbVTbIWODG59ruz8PlR18vAHBwAAAG9Bm0AvwCiaoKdV4JK1tAja/mzbqqXoEV9dPzv7gRuqt4EXpWveBF3XoDX6OMXMPg7kf7rV9HKvAj3jcf6DZnd69tnf4EToOebqHU7zxPYF7fShnyPUdInvF/+RDycgRewQjgl/s+QY39gi3XlAHBwAAABeQZtgK8B++gQNAjHczAEneBJ6Q9vpW9YEXpbXqrQIv3pQCOdAkGPex5Z5U/hxFSb6BIXiGDj1AidX6I8CLXuuU/ODJ47FHQ0fH2dqthrk/MAzP6sD2d58IOap+uAOCgAAAJVBm4AnwH34IgtqroEmtHtXX0TWoEbxGq6r/+CLk9v0MSQIYtzd30CEatbVy+6tAkdQI3rb1W31AI4n6DAyaWluvDwzXgb8T73LxXb+g4XL7PAj1mdrwsh61Icy/9Az7gRF+HJe+ss51vXQcE8PVF4aW6/WCY0vwlN6djrd4EU3if/oPhuEK/V/YIQ5d75P6lv++AOCgAAAAJlBm6AnwCiL3QQ7rBDqtq8FGtZv2gRfBdVetWrv7gR9r6gR91aAjheLossZkxoEgVwI3q0CMX/ka9o4yDgiGhpN/5q0jlKn+Gokde0czHC7F/gQ+RBFnysJXv8EY/DTq7hecUoyERDevg2w5fwIy7bDOvHLihiSEPDg3X9Ip+Iwylzp2evD0/tcHJhXhGC2FYLDCr/wI98AZ3AAAAB7QZvAJ8B9+CQLVq0CT4ITrXXr+IqxLWtHY5MCNrr+BF7rzD6rAjdEnEa13AjdAmrVVXqsq+lqBG6VoEkdq3wRQI/q2X/9WgRC/9NHGZdw7pstj7z9X0cq6YeRTX6/RmAERfnr5lY0L+4TXSEygR19nEL/DrPt92TdYA4OAAAAfkGb4CfAKK/f66wQhBa+zscmBE6/BQPXVV2rlgRdb7XoEX/1tAjl/3xWtVX7cCSIxeIWBGFZMv+BGGdoEfoEgx34R9Bvu6/hDxn3t+kisa94ETqvNjK6tSAhJdJ3QIz9MGHhksobX+VXj0r/gvkR5Ni5N+mqXF/vCDz++uAOCgAAAIdBmgAnwCieC0IKtdV9XatR2OTAid+vtIe31Ai/e61Ai/fj61rVa1Ajr4CAVjqAlFeBG4HD4HWBGHOrUX/+BHELAjdHGVpjWrj+QsPs+0euErTr+tAq+LOVeA6rEs8Bl6H3r0GzO+cqdc9fFXneBE8ObHN5VvGrl+X/Ak8p6+WWU/f2r98AcFAAAACUQZogJ8Aom0ghXXT+gW1rWus7HJgRNa690PaBF79a6gRt17X61l//Ws7wIpfr6VvJgJAv/8CQI4EV9IgbGS/OsTaYTQMC/6PX+GIel1wMEm+DH+jFvf0GyFofO9qTfgRF1XzoXrrOZf4dS1NLJnIoHViQ+GYdj31u8CM/sGEPj33Zu6p4dZc4ezX5QW5/nn9drAHBQAAAAIJBmkAnwCiaoId3X1Aj/XcCLqre6tWsCL0rZPX1+i//S+gRa1bL/wEdwI/BlJ6CDIETgvsRCcCL/X3AUkCL0cZl/h9nflvSPXHOI1Z9+v+jzmp9N4faMCJ6M/eCMI3KGvY/DgjjmF4bt/4Ebr5dd5zd4QuG1f97BeHvfAjcJYhYAzuAAAAAnkGaYCfAKLugg1nYQTAhi2Ueom90NavNK5cCN8CRUBRdwEpk/f/y+/61AiUv6va/gROG/gW1euBzrgISBD/4E+uDHf/XAicCErnUDB1wItSBwU75S3hSz4RDhZ9Qf/A/oe1aRxxRx/BG0fevo93z33JQIidEzmX51E4f6KcIr+HZfzSWuBGplOOUYEh4+z/feGuT1/hS/8CQIQIYAzuAAAAAokGagCfAKL3+EwhWtVoWwgmyBF02EVIuv7+oEUv9eCOtdVurfStAiv/X+X/9Wy//9cCL3Aa4jgR3yUcVlU2zDv7iDkY4J/nrX+Lh2gsqIXfJQcDEuPrwhed/9BuK3zk5Gnn6bDG4+BDvQ/tcoQDRwouEvL9f+7lyhHH6fuBF+uU4QXcO5+YP4w+r+4EX64z4QgRfgSPgSPgSPgSPgSPgSPgFGgAAAJBBmqAnwH35gstcQhRsJ4JheqqtWgRPMetfVeCSqqvoEbqBHL/X3vAiehzbyff+0+Aiu771aBE6QRa7qBF9Wq4vvViBGvq6gRvV6G94ER9NHGLMWk2EPvrn/hABA09aPX8iYHVgq+n474CJ1Xmx2n1IeoSONac/gRl9/YLyOPr7vWyAgf3p8waD0VPAkcIQBncAAACPQZrAJ8B+iFgSfBGEFVbQIxf98E/VaqtV4I5Ovb1gRS//m1Wqpa6f4CIgQy//5f/1bL/+rbX9fatAjcTASB9VwICuQI3orV6tAidAkHO/DOpDkSj+Czh9O3qkcvjHOMHlZE+989V01qJMal7ksCJXr6ML3dchRhPwIxP6vuUMkfNi+ZaVMhGvvrgR+EIAzuAAAACaQZrgJ8B/iECAL/fQtkCH0hDd4KB6r1VW+lr1gRul71BHqu1E/r/W3wEkhzwIhf/0PbrBDWut1wElk/S/4EQv/+X//J/X/l//6uBE4CIgSvVoEfgIKBIPE+McCN0cJKELT9JNy4wj3Fq7C1fomF9HLB/OLjwevT5owIlzGM7FN1VfnKvgdoSvgRi/92cmEnxud+qlskzL++AOCgAAAIhBmwAnwCiboIV6a9W4Jc2V5MqBHfXl/4CQ1eBFL+vuqr9q1PfgROAiMv/+X9YH7y//wJXoIJIETgdMv/++vrQTTICKv4CP6OMzA4XHmv/0cy8IeMqf30c+XOmB+wU88wz2NSBnlx3IFv4f/gROkZnWUI5/3JAj967yBDNuNgviDMNFoEcQsAZ3AAAAiUGbICfAKJ0CIIVX30tvpa9V9Ai6ASCv15f/9fq0CIdjjfjqCL+9L9WgReAgMv/6tl//VoEf1bEKvpWgRhH8Ddv4HSBG9Hb+BIPGwIvRw8UcxyavR/L/tPfQY8vu+DNpBf/0e482ybAidd1usIB+BHJ/X8u0wiGggGTmWQPgzvXw9PrgSKhSAM7gAAAAg0GbQCfAKH6DzvpD6+l76+lqBGv7YHzd/AiF//y//q1F//Vt/avAjE+v9smtZf/4Ea4CUviIEW/EbgI8bCtNAj9BoPY6y1D3bca3/Ymcy4Q4ZUKe99I+X0eoma/gRKkyfS/XVyHqCB9fqf8CN2GTBKv0+vCXzB6MNRPt/ly/AkcIQBncAAAAmEGbYCfAKJ39AhCGq1rdYEfgIZXp/ASECIX/9BBsv//cBYZPv/8v9+gi0CNwOyv8DxXoIMgRa4Egv//6CbwI2IoroCP6Dg531ILhuKnzBQOmA0TN9HEL/h5Et7qQ58uHOcRvZM/WeoLnnf8N59+BEX4aMdLev4dS7f+cIr/H7ndeCQRyKHHsNyL+v+HEknwIy+yiLd/cAcHAAAAAckGbgCfAf3goBAqrVVpkBG3QRb7+AgMv/8CJUBOaq/J+vq8CNXXG5f9/L/7wIn1VQI3wJHwJB3gJDo4hg2Xf/VrJo+D8cew3D/mMDf6gROt//nsf4ZvwfgRuziCNDEuxtFyEfr8N9XXBJ8Vn8CPwhAGeQAAAAF9Bm6AnwH34UCnN9Vm9ZVVRUiehjQIh3y//RAiq8vr60X/gIyAjIEV7+X/9WgSS/76tl+B6/gNf0doDV6BKO5pcfIr9SI2F9HK/9T/UkCJXXUCOvs5mOVM1/XeTdYA4OAAAAIZBm8AvwCiP/qAkrOwSJgRCfX/9/f7oJtAj3q/f3wI3AQCvAkVwIwueyvgSPgSDxudYETo4cUxID1s+c+Hs+79Bsx83Vvhgitf9rVQ4W71jJenBF5aezVUg0+gzzjxLUr2fxKPeBEub6/BJl+/c0CN2DAwrv2xOi/w7gOvz1/RxLeBHy4AzyAAAAHZBm+ArwCAeCMMLW5AiF/4CI9f1ujtneBGL//l//gI4T1wOHXALH0cQvjBcps+f6vo+DMhGAeF45IfHBf/oM8mExQ4z78Pbn8CJ0cywVoux/XUCO/RT14e0w4I+4PEHb3sF+ePZLgzwIbRn7/wI/Zwis2/P4AzyAAAAh0GaACfAKIX/9jtVl//Vsv/6tv6ViBFL/90X4HTfy/18CN6t9K0CMX//EqvpWq+BHL//AI4X9+QKiuXvV9ahLx8+VvX/9HIdP8IeMuXJvr6gRF1nr+QRjVz0cWv6G3f85l4bJZ//DMoZfi/B8J8CNyghMEKyM/H+UF+fPPPr/DsPVwI/+TAGdwAAAKBBmiAvwCiF//IEq1l//V8v/+X+vVyBE4HrL/+CbWqrtZf/ydVAiiXF2K1Ai8BAYnV8BCQIfARl+rfA4K8CJ8m8CJ8h4TgIzoNBzNJJYZz1/9HIrKwStn9NIv391IcuWEevmEvHYv/rDPU1FG7nf/AidV1+epyGv4EZfYVJll3cw0NdG1pAlmgH4odd4LeGaP3p/dcCM2sSU51hN+f4AzyAAAAAm0GaQC/AKGd6J9f7oKNl/f8vv/AjerUX/+BFqAkq4Hj4CAgROAmq/vRWgRfgSK4Eg7wJR2Ea4CDgROtb6BBhQiHfUNhjlwovzUKO0/visS4BE6+hZ3nYvfL/+ETcv3fcYQelqBFwz12FjhaW/BN12/5BeUTCqe8Eza/puCt92Hbu99blQGzjGGbcgoqx+N8wZCB5/50sCP61AGeQAAAAgUGaYC/AKGd8v+ugo2X//L+vkqvfwE1AjiMRoBGFOL7gJyl79cCN6O8Aspf3xBDjlPymeGzNf6oRDv0cOdmRhqXO8K/6PXwvfXwInX0CgTm13d3/+UQ7+qgRaDPL98th7w953/Lcz/CX8rvBFtnfwkCP5yRfpG6/c5zkFCDc/8AZ3AAAAI1BmoAvwH36DDq9DmgRjv1ASiCb9VRf/4EW/4HShHAiF//zvr+i/+/wPkCNXALL0cQsOon3/uQ5MKkr7U2YS/97BmhEEOtXDYc5YV4x0OxWE69D9BnGvWWoDNu+f/4ES6vo9Q/bT/4EZ/KGPG7u/v3LUAl91/W+voEE7fmy9+vbitajqIOxUjxcCP3AGeQAAACFQZqgL8B9+cML8VeXwt1WtUw+KvgQzv1ASnVdR+T1X387wIlfXb/gQ64Ej4Ej88JwJPUCQeeuJgRz+fgRH0kcOKGr9bTPHxXKn1/rwhzw79BwOPeslmG//QIZbkxegRV9I7fSMz9agRcX12Keu89cBHu4f4EdtbKja2pOcSRP8J3vr8AZ3AAAAHtBmsAvwH4IQKFAjnfqAkOuqgJzO8CGX//v7+tBd4Ej1eBI+BI+BGPCdH4DV6IHGrpVvoj2qWQ5e/IPmB77+CHLh8uoERdVXR6/w2t/rOW58BT2vzf8CN2GSCFjxSVnWTIvMJjTz8oL5eH3mu9OL/NuH/nAj+ci/XLwBnkAAABxQZrgL8BaH4CPO+v7uAnM7wIfATWX//GQk7Mn3/6t1wI9aK8A1r9zjnPkCYPiPbZ6nJP/DEVImh/C1rQaLtOzDaK2DQY//0evwOyfXwIvIjv+YzseBHL8vcoI/N8N8tr/rgRqZTxYmBXq+fhCMZwBnkAAAACeQZsAL8AofAQ2/9f6uvfwOnXAh/l/r0OeBH+74EX4Ej4Ej87HwGv0cOStBK98//oxN3jo01MsQ/0cRBow9fr5Sw6HN4/6DOG8sl9CAXPv/gROtYJAI1lEj9P/Dxnd3d3flXfWHbf+BHfyhjM50tB32lM+QbMFyTnCw6Ur7sMbx0wRiyNabmh+E7//2CU/4Ebvuc4KFN2mM/CN5PgDO4AAAACJQZsgL8AgHoMNAiF//yff/5f6/X8CL6Goyojy/X8CIeNgSD8AtPgiDg77t8Pw/xXn+7lY8oS6xtaVxDvPPTBecHEHa4EiChCy/Gbv+CAVy0e7vvx7Z+y/Ai9HIuy4ud+vIfhpTNzQIy7s9VnDYz311hri+D+VwbhwR64Ed+pyLBb9s8Dtv/gDPIAAAACOQZtAL8B9+CcMZqVVVaBJGI9sv8BIfl/61bXwOkCKeW9pWgRjvALRwca/gRaog5m0/4a7uvjPfhFh2q1/Ef0GQ5u8GG4rzZ/9Hr8WFwInXVHErh5b7xtP14Zgl16rjkFATv/e+f9/AjF/7lOIX/HO75bgR9s9mENhu1/94Ef4Ej4Ej4Ej4Ej4Ej4Ej4BRIAAAAI9Bm2AvwH/6BQ5+JCOpyK6wIpf/8v1/AkCYTxHANaMjn74MvgwgRXeiBkRL9SFgle+fhwinXveDEuTLx7DtXv+fy/9YaDl7sPnPjQl/wzd3qFV9f8CJUiI/1AkOmeJOWUolDkvzgti69aN/5Q1HaP+64Zvy/AjtfDU3HF64ZovgmeGev3Oci32BfoIr78AZ3AAAAF1Bm4AvwCi8BIYhcQsA+uAgPUC51+Ah8CIX9/IHnu7PD+8BDV+gyHFXXww3P4ETr8ok/v3MCQ3J+6qBFof+wzCWfs2+wWV/DtuO/RQz3fWG1rPEwyVZO+Aj/6cAZ3AAAABhQZugL8Axp+AWjkgR8BId8MQcYhfASOBEqus4ew+YK4Itr8p2H8/rASXOHFuG4dp/93LmBE8NE4r2/RS7H9fUCOX77l3oTnKuGb8H4EepQ0R71+Ame9Gz+s9UaJL/+AM7gAAAAGVBm8AvwDGHeAWjkMFN38EGIXELAi4CQ2eFYETwqHoce3d3U48Edz1/3vZ6qQU9wXHxY/Ow/n9aucOL8pYNSV+qPeG2d/8CJ0HMIXS99LLL/uuBGL9/YI/N4tfwI/ZyLDrPv8AZ5AAAAGJBm+AvwH6IQJB7ywIEtVwD64CM/FQI52COxHAiP6/Yc3dvpYEXpZVchyr8O21tEgI5f+5dfQa524T9EHl+PAj9nMsEn7z/9Ip6oU+n5XApfAj/AkfAkfAkfAkfAkfAkfAKJAAAAGBBmgAvwH8MQKFaBJrgGt4b+Efj+5IEXEbEIEsCIX6/OGlMFx9n4H/O+94SuqDe78sJPbUOJPH/rgRX1/CByrw4sn/Odfw+pX4EZfYkRm6b33y2anJ4EfzkX4H8+v7gDO4AAABqQZogL8BbH4CRvgGtO+fz+fgReDf4SrgtgRC/l/8EgYDjv4ruA/Mt9B7jlYdnduXnYdp8EyhoOZoWHw1EVOL4EXr6Kc68zYEfCPXYQKU0fpwJD9lORYLLFpfDea/2eok3mXr/08V6+AM7gAAAAF9BmkAvwBnh3+Bj+Bhz8CL1b4GBe5AyHFNT3QOvl/DDPvwIlSb4GDR33+FycuS/WGltf4EagQ9/haVj8eVTMw/Zn8v9QLlH9mmv4EflgSL4Ej4Ej4Ej4Ej4Ej4Ej4BRIAAAAENBmmAvwBnp/PwIvRA9U/1wNuIQvX0hGoEZ9aOxVyHLH+H1vvgRl9oR3yheXj9O8jMifldO8CP5zSwlaYXwzEs8AZ5AAAAATUGagC/AHCew5nhnYbz+X3XzhpflCQIfHJf93ENMCJ1+c7D8fufr8EJXd7QIy7sMiOG62vsXiUby/3dwI/giNqsHc4Z4W9vD0Xf/wBncAAAANkGaoC/AHBl/fzh5fDTtf37nqNA3+Oi/96l1WBGL99ZxP3D1v//UBH1OcVCDglbn5//apxAGdwAAAERBmsAvwBwb6yB4uPrzBHd9sM1dIc5AiXNfSFvAjL7DIh7VcIcef3y2KjtHy+TwI/ho2bj3vn8ER6fn/Z7kJvfL/wBncAAAAFxBmuAvwBwZfy/1vnDimuap0AwGXwh4/TZPvyaw1x7S1UwSAdXksf/DNy01D+6f+BF6R6/ORfrM8COvssvcv6/DXO2v8OPgI/ho2q5YIhoey//Py/AQ/tY7f/AGdwAAADpBmwAvwBwi+kHMIErr841oY+/4EbyiuELf189ZmR7X8CPyhU277vB4cRhq3ywH7/KepD2b4nx/gDO4AAAAWUGbIC/AKILQUaTKMz4xiFxncgCPS+/5hCK9l/Xy7l/8EN3yUCJyBrC251+Hpdj7krwyNe9/j4tNz4EU6CP5w1r+PJ/fLm5PAj8ocNe9f8IvfWX/reX3AGdwAAAASUGbQC/AHB9BoPG6n+sO6b+jsP/DtVSDjgCJ5ysIGNtr/9Eqv6DnV1mVyvjaXcJ/gRl9vjVOv4EfziBWmG+1//Pw/DsNdvLQBncAAAA0QZtgL8Aoh0FA6yz4lXgSRbFJtAPo/q31wIvRjzL68V5fefgI99yoRceU9R0iajtZ7gDO4AAAAERBm4AvwCiGiH/9B6/iFxC4hYAj3xIce+K9v1PU8zFjAz8CN0CM9atXUBHNqdiTinEo5DWfZkc+9HDd78obl+vj+AM7gAAAAE9Bm6AvwDGcGPw/iCfgxgRTvR+AbHyhylcCL1r/6/ONUYT/+BGXyhsVP9TryukfM7X4X3KnhRsfZ+ZadgCP5zQZQ/DTPX100fh+Mj87gDO4AAAASEGbwC/AfwhAmcBHcGPwe4hBP4MYEX5DvAifAkfAkHYVgSfgSPgSDvXBgcOYflCoPwZgNbs5GPyrQ7n8v3vhqRfrhO8x38AZ3AAAAGBBm+AvwCiehSdRHnXELAinic/n8/Ai8GPxcCP8CR8CR8CR8CR8CQ94PA4GifquHUN59+rwI3B59fRxq+H1xfgRl9iRXIu9fX8CP2cymWeCA8NJv9nr9YyXWBHEIEMAXpAAAABWQZoAL8Ao3oyVRCwEbwV/BjiF+DuBF+BI+BI+BI+BI+BHL+//BUgt3XXBUXd4EXoEJ3vc337/gRsI4EldynFZx/BZ59q7iT1OvD7u9lMHnpwI/CkAXpAAAABLQZogL8AonoyVRHAR/BDr/X/wQwIvwJHwJHwJHwJHwJP1wQQIvnCCw1b7wvF/c++vf1AR/ZxRUyVhIu8f13Z6kEcl89b/Aj8JQBekAAAAR0GaQC/AffgkDD3d4CRPCOfz+fgReCG1/Ai/AkfAkfAkfAkfAkcECCjj9cEEBHLrgSOUMkly6+V+Cfx96+UTl+XHwI/CkAXpAAAAVEGaYC/AMad6O8CLUHNnWBFqJ6iOvELALQvooci+BFX0CI7vdj8s/hRq0+gQUJmgRl1e98EgzDFM40COvlObLwEPrr/X/KevRedeE+H9+BH4SgC9IAAAAEZBmoAvwDHH4CO4J/gr+H/grgRfgSPgSPgSL4Em+uCaBGf5wsrw9LI8PradcE0FX6E7wEdyhwJPfX+Av+W9a74EeoJIAvSAAAAAWEGaoC/AEOcFvwT4hfgpgRfgSPgSPgSPgSOCY4cXxx6+Nhy/XBNAil/9yHmRXfoTNAjdCRmZcnscPVL3wTy/5PcARyfb3H6ZzP4C7ceh9NSZ6/IvHGuAM7gAAABMQZrAL8A6noUnQEg754nP+wzAi8FdCFxCwIvwJHwJHwI5f184cf8Os+/wVPqv4Ejgsr0Ed4CO5QSBI/2ma/PXCRxlT+BH47EIPwBecAAAAEtBmuAvwCi+gl/9fwIx3gJDCGBI4J/h3EfwUwIvwJHwJHwJP1w5+xSrgRuv0PmgI7sGAS5l+J0nHCVp+kLAU/HrX2G+T+6ST1/AGdwAAABHQZsAL8AonoIfsQorAknY5wIh2F8/n8/ARvBTiFxC/BTAI4/VhaHfcCZ6CO8CN0CMZydvpegR+dmve/o+v4FWhvLgR+oAvSAAAABlQZsgL8AgHgmDW7vd3gNQ7CMCR6p0j8CMd/h3X/sCTAjfAkfAkfAj+wksmf0+HH7s+olNcIF3z+BH9D5oEddXAjqriThJc9A/LH9fa9Aj2xJxKzb8/gSPgSPgSPgSPgSPgSPgFEgAAABuQZtAL8B9+CcMbu73ZfoIPAjiEFxRxCwEcd4Ek7E0IeBFOz51z+dYEXgxvgrgRfgSPgRy/r+tAwzhhQ1Fffb98FQI6r9AjcGSPl+FyVvl9YaW1uDP/Q3eAjuX7OEN3BHs7RPCHlQuBHti+zYAvOAAAABOQZtgL8AonsKO+BI9f4v1n4EbCGBIOxcBIcGPwd/Bz8GMCL8CR8CO+0DD4MP64MA0Eqrgy63/91XAj+h80BHKudBQ4PlZZ2JmQI/UAXpAAAAAU0GbgC/AMeI4CNO9H4Ea4CLs/Ain8/n8/AanhoPGoz1IWPv4EnqBJL9f66zFeeUCMPYbr7333KcES8I99cMJYlfnKubd+J/Aj3E9SnKphuf8AXnAAAAAXkGboC/AIB6DToEQWziAf+BJPwJXBmvQEedi4CO4EvELiFxSwEa9dhLd2t8uHtSX3cCP6G7wI3lFc2ASF8uvw4R71/CQYd3YEe5z1+HG68CR8CR8CR8CR8CR8CR8AokAAAB/QZvAL8B+jECYVvAj+gm+JWhiit4EXAQGBIO+fzr1A2wIuIwJB2Nz8CQfz+dYEXgtsRwIgtjrQJHZBDvfwWLh/AkcFhROESydnXBZX4ITjG/zQEcvlQSwy/L+CMvGbkUCP56wV89eGZwfUp9fm78+BH+BI+BI+BI+BI+BI+AUSAAAAGRBm+AvwFqfgI4WwSO/gIDQhD4DXPKoCPOxt1qjsCKdc/n86wIvBD8O0X/+BF4IASBYnkz39bB4C3lzcLJlsAJHobvAjrrOKWd8lfAj9nN0r8O35ff566KXL+BH7PWZe+v8AXpAAAAAiUGaAC/AffgkDF3d/AQG/BGOd94CNOwjAkYQwJAtl1nfF+sYvoEj0V4EU7E5/PwEdw38EPw/8KwIr1ggOFpfH39mPs7B3fXCn4Zqan0KrP/gRPIWFOOvPX5g9B2EIEfoN0866sccplYmWgSOVCJa/gR/6RT1Cd5+v+BH+BI+BI+BI+BI+BI+AUSAAAAAYkGaIC/AMafz+I4CNO9H4COO8CQfz+fz8CLwzYrgRC/r/wx114aDlqTMscakT/Akehs0CLhHAkr5QyEL2lzPf/a6gR6nPOLGvf/ZyvTu38MRX/4Ef4Ej4Ej4Ej4Ej4Ej4BRIAAAAV0GaQC/AIB5Q1e4EcYjit4BHRbLrF/s/jNagI47F5+BH2EdfwI+t+GQsai5y+B6pfwI/obvAR5P3+L0O6BHbfZ+sMzN4TDBnr+U5VED+f23/kTZmM/AF5wAAAGJBmmAvwCiDoUFH+BIwhgSDvn8/n4Em9BB4EQ7Cd+vQEadjbPwIvDPxede4NYEQv6+cMK0H2T/4pcKvYTd8Brruf7BEEiL08ECP39nPFBB8+9f+BH+BI+BI+BI+BI+BI+AUSAAAAFZBmoAvwCiiEFBRxC0LYSd4BZjwuoEbCGBJ4uBHWuHBge0bvUqO4+JP2t/8EM2L9Aar+c3H6d9axQI9RJ74CAa3f5/wCdX2+ON/Wesj431/Xw/tfAF5wAAAAFhBmqAvwDIHYJHAhi3EPfwhkO8CIdhHP0L7wEad8XLqhHAaj7WuVXryjKrAjLkqBI5F7XWKz/yeBHL8vLZ7D8K7nXLZfHUAEf4EiuBI+BI+BI+BI+BI+AUSAAAAVEGawC/AffmDDu8nmHO7uBF8eE3ffe7u/Jd7gRDsIF8Qx+fz8BIH4CPPLAbHq0CSvqAj+WBIqJDQoP4F9rDCbhWfglenz+s9SJ8zc/Cd614//+ALzgAAAEJBmuAvwDHiIUcCQfgI07wJR5YDZ84xfjT1Ggw4DWqcEOfxularz2HvK+BH5T3MJeLB/wJFcCR8CR8CR8CR8CR8AokAAABFQZsAL8B/CECYZ8vBGPe7vAjjlP3gI070d4COxGxct4EgQitASXgQYEDANbUScY5gTLsz8/wh4/R/We5M/V744f/4AvOAAAAAREGbIC/AffgtDG7y/SoCT4Iyu7u+IUfZRCuAjz7r1eBJOwgfgRTsfn4B918++XOZ6qUT/Aj3EnuYStP1/3nrclr/8AXnAAAARkGbQC/AIB4IQxu6UQIwhFEtAJB3xHARgthIvZnYRgRzvALV0uI+iEm+BI5IEjt5mZeBHuNORfhy/v/Z6+mnU/AjnQfgCrIAAAAwQZtgL8Axh2FHiOAkD+fgI7CGAWnkQjUCRy/cCOm4tT8vuQekLbz18BE911v/wBecAAAAP0GbgC/AffmDF3cvqxAhnYx4xBH/GLahqit4DYEbgSBXAPuuSUoi9oCPcaHMOx8pXC6LHuNC/mXvqBIOg7AFWQAAADFBm6AvwH96BQ8CP6Cb4hYCOO9HeAa1+7ES/rdbWuXd4DWVVOXe4Ejl7jTzlLSn8AXnAAAALkGbwC/AfvoEj0IVwGoLd3o8fQjcA1rrqT2Kd8CJ1Rf/qA16iT1sUNZ9/ywBecAAAABLQZvgL8B9+gwmH6HPJ5RrvgIw7Ln8/m//+H8ovgH0ug0IXdfg+Nd7/VV4Le73fhAjVoSwXSLNARy6l3z8CPcT1KcY8wjCd5//gC84AAAAP0GaAC/AKIMYUFf7GYrfOxzgQxbuyAkPV4E07n4BH6U51Ns4O/uoCO6gI/lDhDdr7w43WRXHX/uPgRxCBDAFWQAAACRBmiAvwCijIWvAEfP3YiX4EvqA1+UNdtb+CH43v/ssL/fAF5wAAABIQZpAL8AowhBZwEadiBmhDxcCT5xS+7u4CLO8BKXUCKt6t+vdQGr2UvPtdSkvTgR+w4aNexS/w/El3Fnr5RORNmf3Aj8dAFWQAAAAY0GaYC/AffgnDG7u73oIIUGAZZKvTTwIx3KohRD3Od0NhfYXOdY2FFZt+fUP/wJItij94CPPGwCyXUnoZh+CGXH6gROr6Q14EbkgJDlOOXgi2ry8J8PvNd566NJL/Aj8JQBVkAAAAGVBmoAvwH8IQIhn0QsCL7Hu/Cu/macWjI/5zswl7CAjjcV9QTfnVc5dBSGv4EYS+fzf/+gQ6B8J8gqgv2OQ6h+AbBp0TAjdfZDXlYAkckBHq7jzmX1wTPGevlPX9PF7sCPwlAFWQAAAAFBBmqAvwCjhiFGY+WLBD7RDv2H7wIwV5juc7/sfQVXmTYGghsuf8hVBYEjuBFO8As/RxiwsxeaY+9f6t+pOr+oDV6gSOU9w54Qi7mv+WALzgAAAAH1BmsAvwH35wwvxbyl8v8Ed7u8CIGEcVnO6GUV7WwpiOc6c69BNRWQIDjLjIWg9jo+MzBhXAjBjFGc0cvOd0FI21zlJ0ToCRF7TZu3/8VoC95SvALPyor0tcEQQyfh+eQvgq87+BG6+kNaAj7o4hZHmr+BHVyx/cIsRe4AvOAAAAFRBmuAvwH4IQJHAk+gi9eS74CO6gSAvK0w2FzHTnewqG8vgHTIAs3RAgTF7eTPUJfO//bWl+leBEv+oCR8p+bAI/KcQzwS+nD6/gR7yBmMe+1gCq4AAAABNQZsAL8B9+YMSqH36FPAjVwI52VwCSneA0/Cu93fUzxyc7Q+19/V+GsuP4fmJB6WjwJFyQEcvngSE3FymI99XLnrhyT1+BHJ9+X8AVZAAAAByQZsgL8B/+gQP+jugRL2Jd9er4V3HyxYIeY80MQrk5RYwq8dzhCwPAi14Z3MdznfOJXscwqYMugEgFSwGt109rWjhB8TCQJPm+J/7kRHgRuoCP5GJvUCRyoR3ynr+E3cfAj69xMCP8CR8CR8CR8CR8AokAAAANEGbQC/AfnoETwJN8AR+X3/CfdXv+gu1LXQSygRuoDYXynJLw1xf5V6BHuL7zlUINz/gCq4AAABPQZtgL8Aot5Apd+uBHrgEhETwGrcmT93+rX0GghDg0O/FjbUozmHTj5w/+jkVPn3/gRLyHm+BJXNUBIcpzYf4YSxKviz1/Ry7sCPb98AVXAAAAFNBm4AvwCjXwBH/SGJ1X5vDj1a3AjXRxinhI//z2Ybln2CUOy7egfkBCJCDGv7QI/XkwEcvn18iCEUCPpnKsNZ98IW59xsCP8CR8CR8CR8CR8AokAAAADZBm6AvwBMgthBpoBH+kEnPo9ThLEQ176+lqBG6/QTngNbly/8/Aj3FnGL8Ah18Xr+9yY+AKrgAAABZQZvAL8ATILYQaaA1+kKnl6gQ6kBEIJi7m98OT/r4aRWvw6l/Hch6qMvX+BF5PqA2HfH90CHy+KBH5TnWBud18IeX3/3Z6m7z/+v74Ef4Ej4Ej4Ej4Ej4BRIAAABUQZvgL8ATJ6CTwG55xC/hHuYEO5DiCJcYev/0e4S9j19rXXDuRQAoEbr9BVoDW5dfwI9xZxywIPw1n4dz//DJTY+nG+5//Aj/AkfAkfAkfAkfAKJAAAAAT0GaAC/AGd1Rw1F4nvgSOpOjm2A0UKsjYHsqwTYMCjwcv9QIvRxK+RXHx+aqkL2gNaonVfAjpbzjlgFPWfcv8OxPX8p6yXzmf5E0Z+vgCq4AAABYQZogL8AZ2+s4aX9S2Xo9+HHF4dzvAh1J9V1r8prp9SQIhf/Lr91ZKCd4DWuNCYQ5ef+r+BHuz1hmW9/+cMld9QINfvj5/8J8P7/gR/gSPgSPgSPgSPgFEgAAAEpBmkAvwBnfRw138N8cx98F8EfgXzVFLAiVIcR3wmYZ1+11wI3X19ILtAay+XX8CP2Gglu6wg+q+CZ4z9cCR8CR8CR8CR8CR8AokAAAAFpBmmAvwBoHRw0v4Z3PAh9HFa/DrT/4Ib7kBXSCb/nHKUUBC/MBtJX7MdBVfAi8lXRCy/Aj3wEguSX7gR+z1gLNY6T8JfP39xoIeMLvAj/AkfAkfAkfAkfAKJAAAABWQZqAL8Ao3oLNAPr0HCY2viOUsHcCMxUO8feUaq5OjjO4R6+v4EPr6OKUOxWvyBr10gm37CHND57R63+BFuSrmYXDHL+A1uXX3Aj3FnCSwk/r/74AquAAAABCQZqgL8Ao/giCkgeXaAfTpGiksZ/BHw48iZaoEOpPo4pW3r66QTfWv9QIlxH8CT8Br3HnGLBL8up/09wwCHd7wBVcAAAAU0GawC/Af/oETQIuqGtZf+uAfQv/uGCcvy5z8ORU0u6+Qv/k/R6/gxpeBE6QrruSBI8Mh27n47j4Ysz4CO6KFL18y9Ajr4kEe8rD6/gR7n74AquAAAAAbkGa4C/AKJvhSFuY1ONsDJakf/MJXHiGcA+3RzL+cXGpZKFUETC+jhB+B1cv8CHydSIR+uQ4Rbw99/w0Ou9/zhchYgvgRBbHu9XIjP3hzj3a0i3G/AkfAkL5S+VcCPy5f/BxE71pSsAR7je6gCq4AAAAWEGbAC/AfghYEqvL/9QD6dHDi4QvP9NnrybRwiVPD1DhN5jvRwgil6bdf4ES5kI/XSCPfnHYQ5z4wU/+BF5P4EhdUhLwGxyo2XcfAj/AkfAkfAkfAkfAKJAAAAB8QZsgL8B/egRNAja30CEfOSXaBF6X36tASQlYBHH0kcQuXQL+w4MaWTJ/DfLgWWS/hvAeBEX0cRUaLryg39/UiCPZP1dfQ7L4iBFuZCX6z1+G78FwkBIVeesfufwI/UCRyhne65nmnVV88CPcf3wJPwJHwJHwJHwJHwChQAAAAGRBm0AvwCia16DDQJHq36tAkVwCyde0cq41/95P0cUuFmX+BD5Pzml+FUPXjAu9oiBGkUntvvtnCC/wkeHcnpevwIvRxS/R9367lp4KgcbDYAwZVWf8BHchQ1zcBIcvcIomEAVXAAAAUUGbYC/AKJqgs36tl9/y1XAPr0cQvEzXkzTje8MT0/1AidV4JPL3Ho4QUcD/eYBRZBcED43uQPf46BE6+oBIEnEwiHLv9+d8o/5YEcQgRwBMkAAAAJVBm4AvwCia/lCkP7d/j6yjVaqxKqgRt6C2bJzJ1TBOPlPUFkFWnUOBQz8cPbxVBDI/4F5RacXaeMm000p0CKGN/KdQVhezaoLv0RoBZug2bmkxw7Lxomd5S449e1eShcXUhxS4LeA/DefcCHcR1RxClsqf66OFX/w9ZPgiCCZ8zigRev60ZglDH/4EZdVAbFx/fAFVwAAAAEtBm6AvwCibwJO6DHoEn1b9WgFk6OZfzBUef+hf8oRVV7YW8k4hf4dwI9QInWua/l/OMUwydM4v/Ai9HErDT7/uSASC4RQjLuoAquAAAABiQZvAK8Aom7Cmqr19+Ciq6qtoEX1b8Ka1Veq1WrPdegRzf//E+QMqQt2KgWBH9W+SBH9WgNfowjJaXq6Ffo9fwdjUCHwl1SEQV1Ai/9ofh+cih5bv/gEguEUIy74EfhiAJkgAAABdQZvgJ8Aom6CXfS+gR+vuBK6gRulaAR7o4hcdfwP04DylhCE9Cd9HPLw3nvgKPUZ6OIXSDO/4EI8O10GQRPuqDw7LL+b/Cn2TUnWUrvgRuqeI8Aj3Kev8N5r5YAquAAAAk0GaACfAffgkCy6tL6pIEXsEZ2l6+vwlVVDWPJlcpcCL2LrWtf1d+COtVb1VoEXkVvpWzf//D3sXwRVMV2gRRDi65lbEKoEjqA1OkMfsbvr6gROjkXyj4wLG4T+gy3cQhnfhUQ+7u+oI/m8mecErR6yejp4EXk60V3dhre6/M+R9OlwIo9B+/9NNcsBr3H6vuAKrgAAAAE5BmiAnwChnYebv9DWgH3qQ4pcoUAz8+/y7yTnXhxxv1IGzbuuH3O+F76wIjy3ORfLV6ro41eHEv5w4t8BGqIRYvziF875HwCQXH98AVXAAAABdQZpAJ8AonRgkq/pe/BHVVVoEfwTVrWtoEro1VWBF9WgJL1tARvQcFbuv8Nma6E70kXD6gROjiFOOBtDk//oEYXz+//VQI3wCQE/v+EdX8CPlKcqwJRrnn/1JAExwAAAAiUGaYCfAKJv9/X4Kwgq610Sr79DmQIYtzdN1QJR9V1VWvqBF1Vq393XUCL9dCa1VVwIxv/ynZ/Ved67QJPBFXrUCP8CK+Rr2jilwla2n/61PXhqKnw4iv3oN7u64y+d/wImpDZ4eqC7VcyCXQIvIQfKzdX9LAjrk4DX5e4+BHbfZ6wm/P9uTwBMcAAAAf0GagCfAfghAgNQnlF1VQIhf+uy+/8CLv9EKq4DY9WxOv1aBF6WoCPbUQjHFLn0D9zv+j1/hJw0vtU/o5V4CPXo6cN4M+ikmt7AiVIGSTfl+TC8wmrmML5f85KhHh2v/CPF3fvWgRrqBI6gNiovXzwI9xJzrDiP/uzkVR3/AExwAAACIQZqgJ8B++gQNAj7oe34IarVvWBH7rdWgR/VoEfsE3Va1b8EVa2xWoBHOjin/mLg9EfVv0kXu4g5FwyzvwtfWBE6C/PC7HqmH0sW5X9//Ryrwi7dfrqgzleyvCNoSDt/+BF5EN1YuHY0GEBGcwAj1wj3wI94aBFCV59c4sJ6jn/3nEKo7/gCY4AAAAItBmsAnwCidfiwgtdVX4jWtVW/zV0QEXr3+lb8VrVa4tjidoEM7m/pjVqvwR9Vb5YEU7wEj0itiFVCuAjH00ccuYdEpH9CddEC+q+g4Er3XhN53/1Ah+CIr3lvpCoO4g4RXCLm34Ecnr/4ZEvedY+EVnnAkrk4DY5e4RgR7zhBYCffX93+GU4f3wBMcAAAAwUGa4CfAffmCyrUgxCBPGgRQyQerCH5v5H+V/sfvomte0rZfv8lJcCLtgjrq3yq3p+sCL9eEtarX6BRrVV2gRRrq3v8kCNpAhqvVi/aBHFLARpf+Ro4xjkDo+z4sL0G+JYV0cVJ+n1iAuuqr36RwlF/hCMGe9SHMuFV9eXCgQ+TqRYP6J9PXNnKnHwPcGH+BE+rmBHN/3dk3uBF+uWBG/Ow/AlckCPUX3CMCPecOPgSPXXT8EHom+89f4jf0j/gCY4AAAACIQZsAJ8Ao+6CDQIude1l/r3Wv1Ai/5Pv5JNVgRvWq9bQIwzVsTwI/AqQJXq0CJ0HBhcu65h0PM1/0ev8I/P/XhMM1Wq/o4UTDqB1b1/0UzvgQ7h4EoRl/d5BdwyghD+RD+7m/OKeF4cv+BFqS64EX/lgNi4/vgR7vuzleCd+dx8Ag1+//X/AExwAAAIZBmyAnwCh+g8m/Q9oEjc1a+vrAjdX1AjE+//VusFGq1VdQEdwMl+rQIojxXiOBF6Dgx31/h1n3uf3CXzv/l//1wYfpHKlWao6CrwBf+sbw1Mcy5V5f/Ah8nq979UPqvYq5fgRbiq89YP2PwCP1FmIf/XAj3Ocqx5f+85VN3tv4IPjfT8ATHAAAAHZBm0AnwCidfSCTV1AjdwJC/VoEjWBH4HCA1y/8jSFa+lYeBAp6pGLhfEdPucy/hlgPAh8nX1obF1oQx1nqErjC/4ET6qz1I+Zj/l3aXAifAkfAkfj2H61r4Eni9fwI9xen84cUAgf/fV3/8CP8CR8CR8CR8AokAAAAjEGbYCvAffoMJrEIUoEfbY+q1rAjal6rvVvLBDVatAi9rb6NWv4JK6tARtQEdASgiVQIib4g45eFmLw6z7T7W/+q30kcveB1YKv17hsl7sdPun8CJcQerME+jDxaJ/6QvUCP5x6xOFfAlF/k84WX54XAa/KIJMv5/8sCPcacqwzLe/956iB/XX/8ATHAAAAAjEGbgCfAKL16hAIKq1Wq6+31UCLpepta+i1r9wIpf/71BDVVVoEX1tisn8BAZf/yao4Ecv/+IVQIvq2fVcC1AjH1XDa1AiL6OMX8qY+z3EHx3DTBnx6CXVdX85yr+RMDWj6+gRkd85gBE6DO91+4Dv5JO03NR6gkHzeX/gRfgSbmgNjvqJgR7j++AJjgAAAAf0GboCfAKN2gg0CNcBVdr9fUCLUMrXwEFl//Wsv/618BFQIddiOBF+q8TwIvwJIlVa4EbgROjjMuM4RZ99VoIsdat+GB3L7vXgM3zB/8Ny0fqbbqz8Dr5eBE6/QmDub6OIX4HVCT+BF+BIPD+vlgNjsWCC8rJ2c/LAj3H98ATHAAAACaQZvAJ8B+egRNJ4Ixq1sgR+ke0CKX/9W6gK7L7/ZOq9qBEL//Rf/8vv/3ATC9AkCujsKwEdwIEBGdBgPS/Pg33hhTad05bOa1Ici/h2fX8HWeE99JHHMcMr9/PMeBm9AjufM54ESq7o4mD+GFFgRzAPP/4RCItgyvpBjfuIV4Ehfr+A1+U9njPf7LiFi0BHuPXLvPXw9aj4AmOAAAAIxBm+AnwCidIIN3gnrWtVb0AlqFsIJtAh8BGZf/0Eay/l/l//XsvvwENrYgRF/T/74EgVwI4rxH+rQI9wEdl/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type=\"video/mp4\">\n",
        " Your browser does not support the video tag.\n",
        "</video>"
       ],
@@ -872,7 +870,7 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/lbmpy/phasefield_allen_cahn/kernel_equations.py b/lbmpy/phasefield_allen_cahn/kernel_equations.py
index 8a357061cb20306f3abd5e37dcb8f43be79119af..bdccb86e3e3748089dfe913eb4894ada05afb042 100644
--- a/lbmpy/phasefield_allen_cahn/kernel_equations.py
+++ b/lbmpy/phasefield_allen_cahn/kernel_equations.py
@@ -2,6 +2,7 @@ from pystencils.fd.derivation import FiniteDifferenceStencilDerivation
 from pystencils import Assignment, AssignmentCollection, Field
 
 from lbmpy import pdf_initialization_assignments
+from lbmpy.fieldaccess import StreamPullTwoFieldsAccessor as accessor
 from lbmpy.methods.abstractlbmethod import LbmCollisionRule
 from lbmpy.utils import second_order_moment_tensor
 from lbmpy.phasefield_allen_cahn.parameter_calculation import AllenCahnParameters
@@ -154,7 +155,8 @@ def viscous_force(lb_velocity_field, phi_field, lb_method, tau, density_heavy, d
 
     iso_grad = sp.Matrix(isotropic_gradient_symbolic(phi_field, fd_stencil)[:stencil.D])
 
-    f_neq = lb_velocity_field.center_vector - lb_method.get_equilibrium_terms()
+    reads = accessor.read(lb_velocity_field, stencil)
+    f_neq = sp.Matrix(reads) - lb_method.get_equilibrium_terms()
     stress_tensor = second_order_moment_tensor(f_neq, lb_method.stencil)
     normal_stress_tensor = stress_tensor * iso_grad
 
@@ -285,7 +287,8 @@ def hydrodynamic_force_assignments(lb_velocity_field, velocity_field, phi_field,
     cqc = lb_method.conserved_quantity_computation
 
     u_symp = cqc.velocity_symbols
-    cqe = cqc.equilibrium_input_equations_from_pdfs(lb_velocity_field.center_vector)
+    reads = accessor.read(lb_velocity_field, stencil)
+    cqe = cqc.equilibrium_input_equations_from_pdfs(reads)
     cqe = cqe.new_without_subexpressions()
 
     cqe_velocity = [eq.rhs for eq in cqe.main_assignments[1:]]
@@ -355,7 +358,8 @@ def add_hydrodynamic_force(update_rule: LbmCollisionRule, force, phi_field,
 
     update_rule = update_rule.subs(force_subs)
 
-    update_rule.subexpressions += [Assignment(rho, sum(hydro_pdfs.center_vector))]
+    reads = accessor.read(hydro_pdfs, method.stencil)
+    update_rule.subexpressions += [Assignment(rho, sum(reads))]
     update_rule.subexpressions += force
     update_rule.topological_sort(sort_subexpressions=True, sort_main_assignments=False)