{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Example 3: Urban climate adaption" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from pyclmuapp import usp_clmu\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we use the `RUN_TYPE= \"branch\"` to avoid the repeated spinup phases.\n", "\n", "The case (`usp_spinup`) is run for 10 years to spinup the model.\n", "\n", "How to get `usp_spinup` ?\n", "\n", "```python\n", "usp_spinup = usp.run(\n", " case_name = \"usp_spinup\", \n", " SURF=\"surfdata.nc\",\n", " FORCING=\"forcing.nc\",\n", " RUN_STARTDATE = \"2002-01-01\",\n", " STOP_OPTION = \"nyears\", \n", " STOP_N = \"10\",\n", " RUN_TYPE= \"coldstart\",\n", " )\n", "usp_spinup\n", "```" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Copying the file forcing.nc to the /Users/user/Documents/GitHub/pyclmuapp/docs/notebooks/usp/workdir/inputfolder/usp\n", "CPU times: user 1.04 s, sys: 268 ms, total: 1.31 s\n", "Wall time: 2min 37s\n" ] }, { "data": { "text/plain": [ "['/Users/user/Documents/GitHub/pyclmuapp/docs/notebooks/usp/workdir/outputfolder/lnd/hist/example3_clm0_2024-11-23_15-31-18_clm.nc']" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", "# initialize\n", "usp = usp_clmu()\n", "usp_or = usp.run(\n", " case_name = \"example3\", \n", " SURF=\"surfdata.nc\",\n", " FORCING=\"forcing.nc\",\n", " RUN_STARTDATE = \"2012-01-01\",\n", " STOP_OPTION = \"nyears\", \n", " STOP_N = \"2\",\n", " RUN_TYPE= \"branch\",\n", " RUN_REFCASE= \"usp_spinup\", # the case name of the spinup run\n", " RUN_REFDATE= \"2012-01-01\",\n", " )\n", "usp_or" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2 explore the urban adaptation to urban climate\n", "\n", "workflow:\n", "\n", "1. case2: modify the urban roof albedo --> simulate the white/cooling roof for urban adaptation\n", " \n", "2. case3: modify the forcing --> simulate global warming\n", " \n", "3. case4: modify forcing and urban roof albedo --> white roof effect under global warming" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**how to change the surface data?**\n", "\n", "```python\n", "# change the surface data\n", "usp_clmu.modify_surf(\n", " action=action, # dict like result of usp_clmu.check_surf_data() \n", " #or usp_clmu.surfdata_dict\n", " mode=\"replace\", # optional; the default is \"replace\"\n", " usr_surfdata=None, # optional; the path to the new surfdata file, \n", " #the default is \"surfdata.nc\" provided by pyclmuapp\n", " surfata_name=\"surface_replaced.nc\" # optional; output file name, \n", " # the default is \"surfdata.nc\"\n", ")\n", "```\n", "\n", "Args:\n", "- usr_surfdata (str): The path to the user-defined surface data file. The default is None.\n", "- action (dict): The dictionary of the revised surface data for the urban surface parameters. The default is None, which means no action.\n", "- mode (str): The mode for the revision. The default is \"replace\".\n", "- surfata_name (str): The name of the revised surface data file. The default is \"surfdata.nc\".\n", "- urban_type (int): The type of the urban surface. The default is 2. 0 is for TBD urban, 1 is for HD urban, and 2 is for MD urban." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 1.47 s, sys: 351 ms, total: 1.82 s\n", "Wall time: 4min 38s\n" ] } ], "source": [ "%%time\n", "\n", "# we have run a simulation using the `usp` object, \n", "# the forcing data path is stored in the `usp.usr_forcing_file` attribute\n", "# the surface data path is stored in the `usp.surfdata` attribute\n", "# we can modify the forcing data by calling the `usp.modify_forcing` method \n", "# and run the simulation again using the `usp.run` method\n", "\n", "# if there is no forcing data path provided or have not run a simulation using the `usp` object,\n", "# check the forcing, by calling `usp.check_forcing(usr_forcing=\"forcing.nc\")` method\n", "\n", "# if there is no surface data path provided or have not run a simulation using the `usp` object,\n", "# check the surface, by calling `usp.check_surf(usr_surf=\"sufdata.nc\")` method\n", "\n", "# modify the surface\n", "usp.modify_surf(action={\"ALB_ROOF_DIR\":0.2}, surfata_name=\"surface_modfied.nc\", mode=\"add\")\n", "usp.modify_surf(action={\"ALB_ROOF_DIF\":0.2}, surfata_name=\"surface_modfied.nc\", mode=\"add\")\n", "usp_surf = usp.run(\n", " case_name = \"example3\", \n", " RUN_STARTDATE = \"2012-01-01\",\n", " STOP_OPTION = \"nyears\", \n", " STOP_N = \"2\",\n", " RUN_TYPE= \"branch\",\n", " RUN_REFCASE= \"usp_spinup\", # the case name of the spinup run\n", " RUN_REFDATE= \"2012-01-01\",\n", " )\n", "\n", "# modify the forcing\n", "usp.modify_forcing(action={\"Tair\": 1}, mode=\"add\", forcing_name=\"forcing_replaced.nc\")\n", "usp_warming_surf = usp.run(\n", " case_name = \"example3\", \n", " RUN_STARTDATE = \"2012-01-01\",\n", " STOP_OPTION = \"nyears\", \n", " STOP_N = \"2\",\n", " RUN_TYPE= \"branch\",\n", " RUN_REFCASE= \"usp_spinup\", # the case name of the spinup run\n", " RUN_REFDATE= \"2012-01-01\",\n", " )\n", "\n", "# recover the surface\n", "usp.modify_surf(action={\"ALB_ROOF_DIR\":-0.2}, surfata_name=\"surface_modfied.nc\", mode=\"add\")\n", "usp.modify_surf(action={\"ALB_ROOF_DIF\":-0.2}, surfata_name=\"surface_modfied.nc\", mode=\"add\")\n", "usp_warming = usp.run(\n", " case_name = \"example3\", \n", " RUN_STARTDATE = \"2012-01-01\",\n", " STOP_OPTION = \"nyears\", \n", " STOP_N = \"2\",\n", " RUN_TYPE= \"branch\",\n", " RUN_REFCASE= \"usp_spinup\", # the case name of the spinup run\n", " RUN_REFDATE= \"2012-01-01\",\n", " )\n", "# recover the forcing\n", "usp.modify_forcing(action={\"Tair\": -1}, mode=\"add\", forcing_name=\"forcing_replaced.nc\")" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['/Users/user/Documents/GitHub/pyclmuapp/docs/notebooks/usp/workdir/outputfolder/lnd/hist/example3_clm0_2024-11-23_15-31-18_clm.nc']\n", "['/Users/user/Documents/GitHub/pyclmuapp/docs/notebooks/usp/workdir/outputfolder/lnd/hist/example3_clm0_2024-11-23_15-35-55_clm.nc']\n", "['/Users/user/Documents/GitHub/pyclmuapp/docs/notebooks/usp/workdir/outputfolder/lnd/hist/example3_clm0_2024-11-23_15-32-50_clm.nc']\n", "['/Users/user/Documents/GitHub/pyclmuapp/docs/notebooks/usp/workdir/outputfolder/lnd/hist/example3_clm0_2024-11-23_15-34-23_clm.nc']\n" ] } ], "source": [ "print(usp_or)\n", "print(usp_warming)\n", "print(usp_surf)\n", "print(usp_warming_surf)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**use `usp_clmu.nc_view()` to read the output files**" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "ds_or_usp = usp.nc_view(usp_or[0])\n", "ds_warming_usp = usp.nc_view(usp_warming[0])\n", "ds_surf_usp = usp.nc_view(usp_surf[0])\n", "ds_warming_surf_usp = usp.nc_view(usp_warming_surf[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3 Plotting\n", "\n", "Note: ploting with time will need the `nc-time-axis` package, which can be installed by `pip install nc-time-axis` or `conda install nc-time-axis`" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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vZefOnbz44ot917a0tLBixQoaGxu57777aGlpoaWlpe/+8ePHDyj7dCoFfCpzJ3mZPdE+LX1KVixG6u23Sb/zNulNm8nu3IF1lMZ3JRRCHzfeCZSKCtHHl6MVFKDlRFALCtHCIacnKRxGOQ2ZudNJURQCl3wIs7mZrh/9EGPfXrr/56coX7mV/EWLuXhpkPaoxVOvxdi6L0NOSEPXVZbN9lGQMyb+ExVCiDFjzLwrP/bYY9x2223cfvvtfUeuPPzww0ccuWKaJqZpcniizePxsHr1ar72ta9xyy23kEgkWLBgAatWreqbGg6wbds29u3bB8ANN9xwxBruuOMO7rzzzlPzAk+AMyZg6LMztm1jVFeTWvcW6Xc3kq7airF//5EjAFQVraQUvbQUrawU1/gK1NIS9Lw8tOLivlLbcDRtDxfF5SJ03ccxmpqJPbCSzMaNRP/vPhRNp3L+fD58doCOqMlrG5O8vilJJKCiqbBsjp/c0PtnS4UQQpxeY6JUNxqNxMnh72UZBul160itW+scTbJzB1Zn5xGPUwIB9PHj0UpK0EvL0CsqUXNz0IuK0AoKUMMRZ1bSGXCW3/EYLc103n0XiWefBcB/xRWEPvVplBlzWbc9xYPPdrNlbwaXDtcsDzF7ooez5/oI+SV4EkKc2WJJk9XrE9Q0ZvjS3+Sha0OXIDjjSnVi6Jjd3SRWv0hy9WpS69djx3r6P0BR0IpL0MrK0EtK0MrGoZeVokYi6MUlaLk5qJEcp+Q2Qna3jSR6UTE5X7oFs62d9NvrSTzzDGowTEBRmTdlFld+IEhPooeaRmdMgdetUJyvM2+KBE5CiDOPYdps2ZPmqdd6eHNLkp6EhabC9ZdEKMkbns8Y+WQ7w9m2jVFbS+K5VSTWvEKmaitks333Kx4PekWl07RdWopr3DjU3Fy03Fy04hLUnBy0SAQlGBy1zdunmz5pEpF/+mc6v/3/yO7eTfyJx1ACfgIfVlkwbRrdCZvfvxCltcvk2bfiFOboTC134/OM7B2EQggxFGzbpqnd4Jk3Y7y4Ps7+pkNjanwehVkT3RjG8BXLJHA6A1mGQebdd0m88ALJN17HqN7X7341koNr2lT0ygm4Jk1CzYmgFxajFRY42SQpu50URVHwzp9P5Mv/ROfd38NsbCT+pz+i+HwUXKixaOoEorEAf1rTQ0unyVtVSRbP9Mp8JyHEmJZImby+Kckzb8bYuCtFpjdeUhSYMt7F9AoP44t0SvJ1CnOGLwsvgdMZwozFSL32KonVL5Jauw6rvf+RJdq4cbgmT0avnIBeXoGWn+cMmSwsdA7AdclcoaGkuFz4zjkH8+//ge4f/wirs5P4Y39CdbuZcJ7KwukV1DRlefXdJHvqMuxvzFJR7JLz7IQQY4ph2Oyuy/Dn13t4dWOS9u5Dm43ywypzJnuYWOoiN+wESxUlLkrydTzu4cvAS+A0Rtm2jdHYSPLFF0m+8jLpjRuxk4dNFNc0XJMn45o4EX3CRPSSYrT8QvTycufg25ycET9ccrRTg0H8F16I1dFB9Fe/wqyvJ/7nP4PLxawlCk1zSnhtY5LmDpNdBzLMnuSR8QRCiFHPtm3auk1eXBfj+XUJdtVm+uYhu3SYNdHDtHI3RbkakaATLJUW6OSHtRHx5VHehccYo6mJ2OOPkXjxBbK7dvUbFaD4/bimTUOfMAF3ZSVqXoFzxtu4cagFBU5Dt/QpnVZ6UTGBSz6E1dFJzyMPkd25g+Tq1fg0jXPmLKOyxEdNo8H26rTMdRJCjGqJlMW7u5L8+fUY67enSKQO9SmVF+vMmehhfLGLkF+lKE9zzlTN0/GOsP5OeRceY9q/dRupN97o+1ktKMA9bbrT4D1+PFokgj5+nLMDrrAQNRAYxtUKcJrF/ZdeihntIvH006TXr0PNieDTNC6cuITfNLrY25CltinLtHL3iHsTEUKIY2lozfLYmh5eeTdBfeuhRu+gT2HeFC+Tx7nICWlEgs4B9GWFLnJD6oj9Ii+B0xjjv/iDmM0taMVFuKZPRyssRsuJoJdXoBcXoRUUjrnJ3KOdoih45s7F6unBikZJrVlD8oUXUMMRlpdr/FZZSmunSU1jlqYOQ5rEhRCjgmnZPPx8N/c93U0642SXVAWmVbiZOcFDcb5zwHxpvk55sYuiPO20nHhxsiRwGmOC138C18xZGA31uMp7m7vzpLl7pFNcLryLF2PGerB6YmQ2vE38ySfI/ZiLaZHZ7OgKsLc+Q22zNIkLIUa+pvYs3/1NGxt2pAEoiGjMn+ZhYokLv08lJ6hSWeqiJN9FTnDkZpeORgKnMUZRFDzz5uGZO1eau0cZNRjEt3QpdiyGHY+R3bGD1FNP8MEPTmMH57CnLkNTu0Fnj0l+RP7TFUKMPJZl8+L6OD96pIPumIWiwPnzfcye5Cbk1yg5mF3K1XuPBxt95N13DFIUxRl8IUYdvagY35Kl2LE4PT09mPX1nFX3PHrwbNq7LRpbszS0GRI4CSFGnGjc5MePdPDc2ji2DbkhlQ8tCzCu0MWMSjcVJS7CgdF/CoK8+woxwuiTJuHpiZLZtpVEfT3u+n1MXxqjqivE/maD/Y1Ok/hwzjERQoiDbNvm3V0p7v5tO3UtTvP3gqkelsz0Ma5QZ94UD6UFY6ddRN55hRhhFEXBM3sOvos+CIDd0sxyZSsAO2oydMdMmjrMYz2FEEKcFsmUyf8+2cmtP26mrsXA41a46oIgH5jvZ+ZENx+Y7x/SoMlsbyfx+uvYthy5IoQ4jOJy4b9wOd0VFRi1tSzr/Cu/0s6mK2bR1m1S25SholgfVQ2VQoixZV99hv96oI0tezMATCjVWbHYT35EZ/ZED5PHu9G1oXmPytbVEf3N/cSffgpF1yl7ZhVaJGdInvtESeAkxAilBoJ4zz2PWG0t3qZqZs3oZlNXDjWNWcYVuujsscgLj/5+ASHE6JLJ2vzljR5++XgXPQkLVYELF/uZXummJE9n/hQvRXknH17Ytk12zx6i9/2axAvPHzr9IhTCqKuTwEkIcSTf8guJPfIwVm0N58zbxyYWsa06w+IZXhpasxI4CSFOq6b2LD99tJNX3klgA/kRjY+eGyAS1Jgy3s3sSR783pPrArJNk/TWLUTv+zXJV1+FjJPRUgsL8Z59Np55C3BNmHDyL2aQJHASYgTzLF2KEgph9/SwLP42v9EX0JOArh6L2qYsU6VJXAhxGhiGzZtbEvzk9x00tjs9loune1g6y0c4oDJ3speJZSc3Y87OZEi9vZ7offeRWre278gwbdw4vOeeiz6+HC0vH/fMGSj+4Tv1QgInIUYwze/HM28+qTdex9dSy8yyTt7tzmdPXYa8sEZzh0lFiQROQohTpyNq8Ju/dPPEKz0YJvg8Ch89L0hxnkZpvs68Kd6TOkfTSiRIvv4a0d/cT2bTJg6e+KtPmoz3nHPQSorR8gtwT5uGq3LCsB8VJoGTECOc7/zzSb3xOkrtPs6aWMu75LN1X5plc7zsb8pQLk3iQohTwLRsqval+fEjHezY75TLJpW5+PDZfly6yrRyN7MmegZ9fqYVjRJ/8QV6HniA7M4dfbe7Zs3Cc9Yy9IJ81PwCPNNnoFdUoPr9Q/K6TpYETkKMcN4LLoDv34PV0cESczsPuOaTSKl0Ri3cuilN4kKIIRdPWjz2SpQHnukmlrRRVbhkaYAp5S5Cfo15UzyDPv7JaGsj/ueniT36e4yaGudGRcG9YAGeJUvRIhG0wsLeA+orUH2+oX1xJ0kCJyFGOFdpGa6Jk8ju2U2ws57ZoTbWdxexvSZDJKjR2CZN4kKIoZNIWXz3N62secfZxVYQ0bh6eRCPS2FcoYv5U73khk7sPce2LIymJmJ/+iPxJx7HbGx07tA0PEuX4lm0GDUQQCsoxD1jOq6KyhF7IL0ETkKMcIrHg2fxYrJ7dqPV1bB0/n7WU0TVvjQXLfazvynLlHL3qDhVXAgxslmWzV2/besLmpbO8nLOHB+KAjMqPcyYcOLvNUZjI9H77yf+zF+wOtqdG91uvOecg2f+AhSPG62oBPf06bgqKlDc7qF+WUNKAichRgHfhSuI/f4RzP3VzF1cT8i9iJ6MRlOHQSSo0dJhUl4sgZMQ4uT84aUoq9cnAPjYihClBTphv8rcKV7GF51YP6VtmsSffprOe/4Lq6sTAMXnw3v+Bbhnz0Z1uVCLi50epvHjR3zAdJAETkKMAu6ZM1Dz87Ha2wnHm5nta+GtTCmb96RZ0Zt1OtE3NSGEONym3Sl+8VgXAOfM8VKSr1NepDN/qveED+c1e3ro+v49xP70R7BtlFAY34UX4p42DTQdvaQE9/Rp6OPLUVyj6xw7CZyEGAW0nFzcM2eRev01XI21LK7Yz1uUsq06zUfPDdLcYUiTuBBi0Nq7DP7ffa1ksjaVJU6wNHuSm9kTvbj0E/tCltm+jbZvfpPs9m0AuBcuwr9iBbhc6GVluKdOQx83btQFTAdJ4CTEKKC43XjPPofU669h7dnJ9Knnkusx6Ezr1DRlyQ1Jk7gQYnCyhs2372+jqd0k4FNYsSTAxDIXsyacWNBkZzLEnn6Krh98H6u7G3SdwJVXoU+cgF5RiXv6DPSyMhR9dIceo3v1QpxBvOecDR4PdixGhBhzvM28lh7Hpt0prvhAiFppEhdCnCDbtvn1U52s25ZCAT56bpCyfJ25k724XQMPmozODrp++EPijz8GloVaUEjwur9BDUfwzJqFZ978EbtL7kTJO6wQo4ReUIhr0iQAvC11LNSqAdhRk8GjQ1fMoqXDHM4lCiFGmVfeTfDQ81HAOai3tEBn7hQvOQMcN2DbNunNm2n54heI/+mPYFm4Fywk9JnPoBeV4Dv3XDyLl4yZoAkkcBJi1FBzcnDPmQOAsmc7Ezw9FPqymBbsqM2gqXCgOYvde1yBEEIcS01DhnsebMc0YVqFmxmVLqaVu6koHlgxykom6Xn097T8/d+R3bYNNI3ANdfiu+gi9LJxTjP41Gko6tgKNcbWqxFiDFNcLnznnQeAWV9HJKgwx+0Mkdu4O01OSKOx3aArZg3nMoUQo0AsYfLt+9vo6rHICalcsMBHeZGbWZM8A9qdm21uouO736HzO9/G6u5Czc8n8g8345o8Gfe06fiXL0cvLj4Nr+T0kx4nIUYR16QpaGVlmA0N+DvqWaD6eZkKdh/IYNuQSts0tmVPeKqvEOLMkTVs/ucPnWyvcTLVV3wgSEFEY95U73F7JG3TJLVxI113f49MVRUA7nnz8H34UlRdxz1vHp5Zs0ftjrmBkIyTEKOIlpuLa+o0APS9OxjnjVMWSGNZsGVvmlBAZX9jlkxWynVCiCPZts3Tr/fw5zdiAHz47AC5IY05k73H3ZVr9fTQ8+jvafunLztBk6oSuOYafB++FC0cxnf++U4T+BgOmkACJyFGFTUSwTNvHgDG7p34c4PMdTUAzvC6SECls8ekpdMYzmUKIUaozXtS/PKxTiwb5k3xMKHExdTxbiaUHjvYydTW0vFfd9H5ve9idXai5uYS/tKXcU2ajKtsHP4LV+CaMPGMGMIrpTohRhFF13EvXIQSCmH39BBJtDIXg+eYyL76LPGUha4pHGjOMq5QJokLIQ5p6shy92/biSVtinI1zpvro7RAZ9YkD6p69PcKO5Mh+c4Guv/7v8lUbQXAPWcO/iuvQjEMXNOm41m4ENXnO50vZVhJxkmIUcZVVIRr4kQA3DU7KPKmqQimsIEte5wm8YY2g25pEhdC9IonLX7y+w72Nxm4dLjy/CChgMq8qV58nqOHAmZHBz2/f4T2f/tXJ2hSVfxXXYX/iitRNR3PWcvwLlt2RgVNIIGTEKOOmpuLa8YMAKwdVbhzI8xz1wHO7jq/VyWVsWlszw7nMoUQI4Rh2Dz6YjevvJME4KoLgvg8KrMneSnMOXrhKVtXR+d/f5/O79+D1dGBmpND5Mtfxj11Glokgu+CC/DMmoWinXkbUSRwEmKUUcNhPHPng65jtbeT60oxx65BwWZ/U5bOqEnQ5zSJZw1pEhfiTGbbNm9sTvDbZ50hl2fP9lKc62LSODeTxh29r8loaabt379O/PHHwTBwzZxF5JZ/QnG7cU2YiG/5hejjxp3OlzGiSOAkxCijaBquygr08nIAfPt3EHGZTAo73yY37UkRCap09lg0d0iTuBBnsr11GX78+w7SGZvxRTpLZ3kpzNWYM9mDdpS+Jjudpv2bt5F5ZwMoCv4rriD48Y9jZzN45i/A94EPoEUiw/BKRg4JnIQYhbSCAlyTJgOg7KxCz4sw31UPwKbdaXRNQVWcSeJCiDNTe7fBT37fQXOHic+jcNX5QdwulXlTvAS8R37825ZF96/+l9Trr4OiEPrCF3HPno2iqvjO/QCeRYtR3O5heCUjiwROQoxCak4u7lmzATCq95EbcTHLqkZVbOpbDVq7jL5J4t0xOb9OiDNNImXxwKpuNuxMA/A3K0IoisLsiW5K8o/e15R8/XW6f/1rAHwXfxAtEkYrLHKOTpkyRXbp9pLASYhRSA2H0Ssq0AoLwbII1u/G74Zp4TgAm3enCfhUEilnkrgQ4sxhGDbPr4vx+Cs9AKxY7CcSVJlY5mJK+dEP283W19Hxn3dCJo0+aRLueXNxT52G/4Ll6IVFp2/xo8CA5ji9+uqrJ/2LJkyYQEVFxUk/jxACFFVFLytDnzgJs7UVfW8V6rwrmN9exw5msHF3iouXBgj5FfY3GUweb+PS5duiEGOdbdts2p3k1092kTVg8jgX86d4CAdU5k72omtHvg9Y8Tgd//n/MBsaUAIBAh/9KHpxCZ6Fi1ADgWF4FSPbgAKnCy+88KRTdHfccQe33377ST2HEOIQLS8P16SJpNetxdi+jfCF1zOjpQZNnU5zh0lTu0FBjkZTu0FLp8G4wrF9DIIQAmqbsvz8T110RC1CfpUrzw+BAnOneAn6j9LXZBhE7/8/Uq+9BkDwb65DDUecoCkYPN3LHxUGPDl8+fLlLF++/IR/gW3b/Od//ucJXyeEODbn3LqpKD4fdjxOTncdHW6dWeEetnSF2bg7xaVnB1Ggd5K4BE5CjGUdUZPfPNPNjv0ZVAWu/2CItGGzcKrnff/7T77+GtH7evuaVqxAKyzAPXs2rvHjT+fSR5UBB04XXnjhoDNGEjgJMfSUUAg1Jxd98mSyW7fi3rcNteICFnQeYAuz2bQ7zYeXBZwm8TaDaNwkHDjzhtUJcSawLJvn3urhhXVOn+OlZwfwuhXKi3WmVRy9rylTU0PH976LnU6jV07AvXgxenklnt6NJ+LoBtQcft55551Uf9LJXi+EOJKiKOhlZbgqKgFnirgvJ8A0+wAu1aa926SuxTisSVxmOgkxVu2uy7DymSiWBbMnuZk50U1OUGP+VO9R+xvNri46/+suzLo6FJ+PwLXXooXCeBculJEDxzGgjNNrvbXPwTrZ64UQR6fl5aNPnAiKgllfTz7dxHQ3cyLdvNuZw6Y9acqLXQR8CjWNWSaPc6NLk7gQY4ph2vziT51E4xZ5YZXLzw2Szjp9TUfLMtuZDNEHHiD1yisABD7+cRTdhWf+fLSCgtO9/FFnwOMIUqnUCT/5U089dcLXCCEGTsvNRS8oRO/N6PpqtmOHIixy1wKweXcKy7bJCWl09pi0dErWSYixZuOuFG9vdz6jr10RIpaymF7pZnzRkbkR27ZJvPIKPb/5PwC851+AXlCIe9o0XJOnnNZ1j1YDDpw+9rGPYZoDH6T39NNP8/GPf3xQixqMWCzGv/zLv1BWVobX62XBggU88sgjA76+paWFG2+8kYKCAvx+P+eccw6rV68+5jXJZJJp06ahKAo/+MEPTvYlCHHClEAANRJBPzhFfHcVvrCPKXYDHt2iK2ZR25RF1xSnSbxFZjoJMZZkDZuVz3Rh2TBlvAufW2V8kYuZEzxH3Q2f3b2bzh/cg51Moo8fj/fcc9GKivDMn39GHtg7GAMOnFatWsVnP/vZAT32mWee4brrrkPXB9x7ftKuvfZaVq5cyR133MGqVatYunQpn/zkJ3nooYeOe206nebiiy9m9erV/OQnP+HJJ5+kuLiYSy+9lFd6U5lH861vfYt4PD6UL0OIE6IoCtq4cbh6M07ZnTvJ85sYuof54U4ANu5yJgdHDmsSF0KMDW9vT/JO73TwZbN9BHzOkSpu11H6mlpb6fzRDzEPHEDxeAh+4pMomoZnwUIZPXACBhw4XX311TzyyCN86UtfOubjVq1axbXXXoumaTz99NMnvcCBeOaZZ3jhhRe49957+fu//3tWrFjBr371Ky655BK++tWvHjdTdt9997F161YeffRRPv3pT3PJJZfwxz/+kWnTpvG1r33tqNesW7eOn/3sZ/zkJz85FS9JiAHT83JRi4pRc3IgmyXYuBcjEGGxq7dctyeFadkEvArxlEVTu5TrhBgL0hnnWBXbhmnlLnJDGrMnecgNHZk5shIJog8/ROqVNQAEr/8EYOOeNRtdRg+ckAEHTo888ggrVqzgl7/8Jd/85jeP+pjnnnuOa6+9FlVVeeqpp1ixYsWQLfRYHn/8cYLBINddd12/22+66SYaGhpYu3btca+fPn0655xzTt9tuq5zww03sG7dOurr6/s9PpPJ8LnPfY4vfelLLFmyZOheiBCDoObkoAUDuKZPB0Dfuw2P38MkpQm/yyKWtNlXn0VRFPxelf2NWQzTHuZVCyFO1rptKTbtdrJNZ832kR/Rjt7XZJokX3mFnt+uBMB77nlopSXO6IE5c+QMuhM04MDJ7Xbz5JNPsnTpUu666y5+9KMf9bv/hRde4OqrrwbgySef5OKLLx7ShR7L1q1bmTlz5hGlwXnz5vXdf7zrDz72aNdXVVX1u/0///M/icfjfPvb3z6ZZQsxJNRAEC03D33CBACMbVvJCaqkdT8LQu0AbNrtNI7mBDXae0xau6RcJ8RolkxbPLCqCxuYXukmHNSYMt6Nx3Xkx3p6+za6fvpj7EQCrbQU30UXofoDMnpgkE7okN9AIMCqVauYOXMm//Zv/8ZvfvMbwAmarrrqKmzb5vHHH+eSSy45FWt9X+3t7eTl5R1x+8Hb2tvbh+z6jRs3cs899/DLX/6SwAmc4ZNOp4lGo/3+CDFUtLJS9JJScLmwOjrITbaQ8YZZ4t4PwNa9aQzTOa/OtqBemsSFGNX+uiVB1b4MAMtmeSkIq0fNNhn19UR/8QuM/fvB7SZ4w2ew02kZPXASTihwAsjNzeX555+nsrKSv/u7v+O2227jqquuwrIs/vSnP3HppZee1ILWrFmDoigD+rNx48a+646VahxIGnIg1xuGwec+9zmuv/56PvzhDw/8RQF33XUXkUik7095efkJXS/EsWg5uSheL66pUwFw79uG2+9mgtpGyG2SSNvsPuC8yeYEVepbs8QS1nAuWQgxSLGExUPPRbGBWRPdhAMaU8o9eNz9P9KtaJSeP/2R5JqXAQhe93EUy5LRAydpUNveysrKePHFFzn//PO5++67cblc/PGPf+SjH/3oSS9o+vTp/OpXvxrQYw9OI8/Pzz9qVqmjowPgqNmkww30+h//+Mfs27ePRx99lK6uLoC+zFEqlaKrq4tQKIR2lC2d3/jGN7j11lv7fo5GoxI8iSGj5uSg+gO4p0wlu20b1o6tBKdfSMIdYFGolVfaS9i0O83MCR6CfpXapizNHQZBv6TphRht3tgcZ1uN80XorFk+ckIq4wv7f5zbmYwzr+nBB8C28Zx1FnplJVokgmf+Ahk9cBIGHDjdc889R9x20UUX8bvf/Y7zzjuPbdu2sW3btiMe83670t5PaWkpX/jCF07omrlz5/Lwww9jGEa/PqctW7YAMGfOnONef/Cxh3vv9Vu3bqW7u5upvd/qD/etb32Lb33rW7z77rssWLDgiPs9Hg8ez9HPCxLiZKl+P1p+HlqFE4wb+/aR50rR7gqxxL2fVyihal+arOGU63xelZrGDBPKXGiqNIYKMVpE4yaPvNADOEerBLwKk8e78XoOZZts2ya1eTPd/98vsGMxtKIiAh+93CnRyeiBk6bYtj2g7TWqqqIoCgN8uPPkinJCQzMHa9WqVXzkIx/hkUce4frrr++7/bLLLmPz5s3U1tYeNQt00C9+8Qv+8R//kbfeeotly5YBTlluwYIFBINB3nrrLQB27NhBU1NTv2ubmpr45Cc/yT/8wz9w/fXXs2TJEoID+EsZjUaJRCJ0d3cTDocH87KF6CezbRvJt/5Kz0O/w2xowPXJG6kKzyXSdYA7Wz9IV1rnM5eFmTvZSyZr09plcOGiAMV5p2/emhDi5Pz59SjfW+lUQz53RYTSfJ2LlgTwHRY4Zav30fmD/yb58mrQdXJu/VcwTTwLF+FZuFB20R3FiXwmD/gd8/777z/phZ0ql112GZdccgk333wz0WiUKVOm8PDDD/Pss8/y4IMP9guaPv/5z7Ny5Ur27t1LZaVzOOrnPvc5fv7zn3Pddddx9913U1RUxL333svOnTt58cUX+66dMWMGM2bM6Pe7a2pqAJg8eTIXXnjhKX+tQrwfNTcXdA33zFkkGxpQdlfhP28eKU+IxaEWVqfL2LgrzdzJznA8y4KG1qwETkKMEh1Rkz+85GSb5k3x4HMrTB7n6hc0me3txJ54guQrvX1Nf/M3oCjoFZV4Zs+WoGkIDPgd82//9m9P5TpO2mOPPcZtt93G7bffTkdHBzNmzODhhx/mE5/4RL/HmaaJaZr9Mmcej4fVq1fzta99jVtuuYVEIsGCBQtYtWoVy5cvP90vRYhBUXNzUf0B9EmTYDVkt28j78MKNT1BznJVs5oyttekSWUsvG6VcEDlQEuWaZUeAt4T3icihDiNbNvmlXfi7D6QRQGWzfYSCWqUlxzqU7SSSRKvvUrP7x8By8KzaBGumbNQbBvvggUo0i4yJMbMV81gMMhPfvKT407y/s1vftM3RuFwxcXFrFy58oR/74QJE06ofCnEqaJ6vWiFhVjJJIrfjx2PE2qvRdXGUeqOUezP0JxwU7UvzeIZPkIBlQPNBs3tBpPGSZO4ECNZW5fJY2ucbNP8qR7cLoVJ41z9vvSkq7bS83//hx2NohYUELj2Y9jRKJ5zzkUrLByupY858jVTiDFELy6BrIF71izn5z1VeN0KKU+YJQGnP+/d3rPrVEXB61aobcpiWRL8CzFSWZbNyxvi7K3PoijOmXQhv0blYdkms6OD2MMPkd2zGzSN0E03YXV24poyBdcUGT0wlAYUOJWVlfHDH/5w0L/kZK8XQgyMmpuLomu4ZswEnCniuSGNuBZgqbsGgD0HMvT0znDKCaq0dpm0R2WSuBAjVXOnyROvxgBYOM2Dpjm9TQGf8xFu2zbxF54n8fzzAASuuQbV42SgPQsWyuiBITagwKmpqYlYLDboX3Ky1wshBkbLzUUJBNErK0FRMBsaiBjdWLZKoTtNRTCFZTsH/wJ43CpZw6KhVQ7+FWIkMi2bl9bHqGnMovZmm8J+pV+2yWhppuf++8E0cc+dh2fxEqfHSUYPnBID7nF64okn+naQnSjp4hfi9FDcbrSiIuyaavSJkzD27cVTvQ1P0VmklDBLAw3UxiaxcVea8+b5AQgHNQ40Z5lW4e63O0cIMfwa2wyefsNJPCya7kVVFCaOcxP092abLIv4k09i1O4HXSdw7bVY7W14FixClyHLp8SAA6eNGzf2O+JECDEy6cVFZPfsxjN3Dsa+vdg7qwhPOJvOHj9LXPt5jInsb8rSETXJC2uE/Sp1LQbNHQYTSqVJXIiRwjBsXlwXp7bJQFVh2RwvQZ9CZYnr0GMaGog9+igAvvM+gJ1KoZdXyOiBU2hAgVN1dfVJ/6KcnJyTfg4hxPE5fU46rmnTAcjs3EnuVSatXVDgMZmak2RXl5+Nu1JctCSAqiq4dIXa5iyVJS55sxVihKhvM3jmr062ackML7atMKHUOZsOwDZNYo//CbOhHlwuPMuWofp8eBcslNEDp9CAAqeDgyKFECOfFslBCQbBslBzc7E6O/E37kF3TSWjhVjiq2dX19S+wAkgN6zS0mHSETXJj4yZKSVCjFpZw+aFdTHqWgw01elt8nkUJpQeyjZl6+qIP/YYAL4LloNl4pk7T0YPnGLS0CDEGKO43c5Ygngcd+85i+ruKgJehbjqZ5G+H021aeowaWxzmsK9bpVM1u77WQgxvA40Z3nurTgAS2f5sG2byhIXkWBvtimbJfbo7zGbm1E8HjyLFqEVFKJPnDicyz4jSOAkxBikFRZiG0Zf4JTZupX8sEo6Cz43zM5x3pA37k71XRPyq9Q2ZUlnrWFZsxDCkc5YPL82Rn1rb7ZplhefR2VC2aEexGxNDfGnnwLAu2IF2Bbu6TNQvd7hWvYZQwInIcYgLTcXxe3GVTkBXC6szk6CPc2oqkLWF2GJ7wAAG3el+ibfh4MqXXGL5naZ6STEcNrflOWFdQnAKdGZlpNtyg31ZpsyGXp+/whWWxuKz4dn/nwn2yRtNaeFBE5CjEFqJIISCmFns7inO03irj1V+D0KCdXLPO0AHt2ms8dif5NTntNUBV2D2uasHCMkxDBJpJxsU2O7ga45Z9J53P2zTZm9e0g88xcAfBdf7MxvkmzTaSOBkxBjkOJyoRcXY8ViuGc75brstiryIjqprILLpTI/Nwo4WaeDcoIazR0GXTEp1wkxHGoa06x+28k2nT3HR9aEyhIXeWEn22Qlk/Q89Dusri6UYBDP3LmSbTrNJHASYozSC4ucb6K9fU5G9T7CStL5Z3+EJZ5aADbtSWGaTobJ71VJpW0a27LDs2ghzmCxhMXzaxM0d5i4dKdM53EpTCw7tJMus3NH39Eq/g9e4mSVZ0i26XQaksCpo6ODAwcODMVTCSGGiJqbi+Lxovr9aGVlYNt492/H51FIaD5mqfUE3RbxpM2eukzfdaGAyv6mLJmslOuEOJ321qdZ846TbTpnjo9M1qa86LBsUyxGz0MPYff0oEYiuGfNcrJNFZJtOp0GHTh1d3fzz//8zxQXF1NYWMjEw7ZArl27lo985CNs2LBhSBYphDhxaiSCGg5hHTaWwNxeRV5II5UGxe1iYV43ABt3pfuuiwRUunosWjplNIEQp0t3zOSFdXFaOnuzTXN8uHSFieMODaVNb99G8uWXAPB96EPYmYxkm4bBoAKnjo4Oli1bxs9+9jPKy8uZOXNmv2bSefPm8cYbb/C73/1uyBYqhDgxiqahl5RgxeN4evucMtu2EQmABZj+MGe59wOwZV+arOH8N6xpCqrizJERQpweew6keXWjU0o/b56fVNpmfJFOQcTJNpldXfQ89DvseBw1Lw/3tOloBQWSbRoGgwqc7rzzTnbt2sXDDz/M22+/zXXXXdfvfp/Px/Lly3nppZeGZJFCiMHRCgrANNEmTEDx+7ETCXwt+/G5FZKqj8k0kue3yGRtttccyjrlhDSa2g26YzKaQIhTrSNq8sL6BG1dJm6XwlmzveiawqQy96Fs05bNpF59FQD/hy/FTqcl2zRMBhU4PfXUU1x++eVcf/317/uYyspK6urqBr0wIcTJU3NzUX0+yGZxz5oNgL2zikhQJZkB2+1mUW4nAO8etrsu4FNJpGya2qVcJ8SpZNs2u2rTvLnZyTZ9YJ6vL9tUmNubbWpvJ/bII9jJJFphIfqUyWgFBc6cNnHaDSpwamxsZNasWcd8jNfrJR6PD2pRQoihoYZ75zkd1ueU2bqV3JCGaYHlD3OWyznEe0dNhmT60BiCgE+hpjGLYUiTuBCnSluXyUsbErR1m3h6s02qojCxN9tk2zapd98l9eYbAPgu+wgkU7hnzJCDfIfJoAKn/Pz84+6i27FjB6WlpYNalBBiaCiqil5ahpWI4541CxQFs6GBQKYLj1shpfspt9soCZuYFmzd279c1xE1pUlciFNod12aNzc7O+k+sMBHMmUzrlCn6GC2qaWF2KOPYKfTaKWl6JWVaIWFkm0aRoMKnC644AKeeuop6uvrj3r/tm3bePbZZ/ngBz94UosTQpw8LT8fLBvF70efOAkAddc2wn6VRAYsl4slOe1A/3KdrikoQF2LBE5CnArRuMkr7yToiFp43QrLZnlBgUnj3aiqgm1ZpN5+m9S6dQD4P/IRSCYl2zTMBhU43XbbbRiGwXnnncdDDz1EW1sbANu3b+e+++7joosuwuPx8NWvfnVIFyuEOHFqTg6qz4edTOKZ4/Q5Zaq2khfRMAwLKxhhqV4DwN66LNH4oYbwnJBGQ1v/24QQQ6OxzeD1TU5v0/kL/CRSNmUFOsUHs02NDcT++AfIZNDLy9HGjXeyTbKTblgNKnCaO3cuv//97+nq6uIzn/kM9957L7ZtM2fOHL74xS+STCZ59NFHmTp16lCvVwhxgtRwGCUUxo7FDvU57dxJ0GXgcqmkNR9FZgcT8kxsYNPuQ+W6gE8hnrRo7pDASYihZFo2f3mzh84eC5/HyTbZwORxvdkm0yS5di3pDW8D4P/IRyGRkGzTCKAP9sIrr7ySffv2sXLlStauXUtHRwfhcJhly5Zx0003UVBQMJTrFEIMkqKq6OPKSL/7LnplJWpODlZXF67aPYR8U4glbXwuF0vCrdR0lLBxV4rzF/idaxUFv1elpiHDxDIXuqYM86sRYmxo7zJ5rXdu0wUL/MRSFiX5OsX5zseyceAAsccfA8NAnzgRtbgYLRCQbNMIMOjACSAvL4+vfOUrQ7UWIcQpouXlowDYNu45c0i9/jqZqq3kXzSdjmgWKxhhcayax5QSDrQYtHYZFOY4bw85IY2WToO2LpOS/JN6yxBC9Nq4O0Vzh4mqwKLpXuIpi8nj3Giqgp3NkvzrX8ls3AiA/6O92abFiyXbNALIIb9CnAG0nBxnAGYyiXvOXMAZSxD0qei6Qkb3ETG6mVroNIIfXq5z6QqWBfUtMklciKGQzli8uN4Z1zO13E0qY1OSr1Na0Jttqq0l/uTjYJq4pk1Dy8tHKyySbNMIMajA6Yc//CEFBQU0NDQc9f6GhgYKCwv56U9/elKLE0IMDSUUQo1EsGIx3NOng8uF1dGBN9pMwKs4wzB1N0vDLQC8uzPV7xilnKBKXWuWeNJ6v18hhBigpnaDzXucLyfzpngwLftQtimdJvHaq2S2bAGc3iY7kcA9Y7pkm0aIQQVOf/jDH5g3bx5lZWVHvb+srIwFCxbwyCOPnNTihBBDQ1EUtNIySKZQ3G7cU6cBYGzdSn5EI52xsYJhFijV6Bq0dpk0tB0aQxDwq8SSFk0dMppAiJNh2zZvbE4SjVu4XQol+TpFeVpftilbU0P8z087ZfVZs1HDYck2jTCDCpx27drFnN7dOe9n9uzZ7N69e1CLEkIMPS0/HxuwLavfFPFwQENVwXD58Wd7mF3slOTe3XWoXKcqCl63yv7GDKYlk8SFGKxo3OL1Tc7Ay9kT3dg2TCpzo2sKViJBYs3LZLdtB5y5TbbMbRpxBhU4JRIJAoHAMR/j9XqJxWKDWpQQYuhpuTmoAX+/41ey1fvw2yn8XoVkxsZ2uVkSbAJg0+4U1mHlutyQRmuXSXuXjCYQYrDqW7Ps2J8BYOYEN0G/QlFub7apeh+JVc8ANu7581H8frSCQlwVFcO4YvFegwqcKisrefPNN4/5mL/+9a+MHz9+UIsSQgw9NRBEy8vHisfQ8vPRSkrBsjB3biM/opPM2FiBMHPtarwu6I5Z1DQcagh3uxRMy3njF0KcOMO0eentBKmMTdCvkh/WKMlz4feqWD09JF56ieyuXaAo+C+TbNNINajA6fLLL+f111/n//7v/456/69//Wtef/11rrjiipNanBBiaGllpdgp51gV98Ep4lu3EglqqAoYbj/uTJz5pc434sOPYAGIBFQOtBgkUtIkLsSJau82eXu7M7tp/hQPKAplhU62KbNnD4nnngPAs3gxitst2aYRalCB09e//nVKS0v54he/yEUXXcRdd93Fb3/7W+666y5WrFjB3//931NWVsY3vvGNoV6vEOIkaDm5oGrYpnmoz2lbFQGPjc+jkMrY2G4PS/zOjtkte9IY5qFyXSigEk1YNEuTuBAnbG99mr31TsZ2eoWboE+lIKJhdnWSfPkljH17nWzTpZdJtmkEG9Q0u8LCQl5++WVuuOEG1qxZw5o1a1AUpW/78llnncWDDz5IYWHhkC5WCHFy1Nxc1EAAOxbDNWkyis+HHY+j1O0nNzSehjaDYDDCjFgNId8EepI2u2ozzJrovHmrioLXpbC/MUtliQtVlUniQgxEMm3x8tsJTAuKcjUCPoWyAh2vRyW5cReJF54HwLvsbFBVtKIiXJWyk24kGvQY4KlTp7J27Vrefvtt1q1bR1dXFzk5OZx11lksWbJkKNcohBgiqs+HVlCAUV+PHongnjWL9IYNZKq2knNBJXUtWSy3D1emlYWlaV7d52HjrlRf4ASQE1KdJvGo2TddXAhxbM0dBpt6ZzfNn+pBURRKCnTM1lYn27R/P6gqvg9/CDuewL14CYrbPcyrFkdz0u96S5YskUBJiFFELyklu28fAO7Zc5zAaetWQpdegc+jkszY6G43S111vMpkqqrTZLI2bpeTXfK6VQzToLHNkMBJiAGwbZuqfWnqWpwS95TxvWW6HI30ul0kX1oNgPfc88AGrbhYsk0jmBy5IsQZRs3NRdFd2Nks7lmzQFEw6urQYl3khFSSaRsrGGFi9gD5IcgaUFWd7vccQb/GgeYs6aw0iQtxPF0xi9d6ZzdNKHUOyx5XqONKxUm9sgajrg50Hd8llzi9TdNnSLZpBBv018XW1lbuv/9+1q9fT1dXF6Z55GwXRVFYvXr1SS1QCDG0tNxclGAQKx5Hy8lBnzABo7qaTFUVubPPobHNxPL4cXW0sLg0xfM9XjbuSrFwmrfvOcJ+lcZ25+DfcYXy/UuIY2luz7Kt2tmpOn+qU/YuydfJNuwn8eILAPjOvwBM0+ltkp10I9qgAqfNmzdz0UUX0dnZ2e88q/dSFGkcFWKkUdxu9OIip1yXk4N79hwncNq6ldDS8/C4FdJZG93tZYnnAM8zlZ21GeJJi4DPCZI0TQEbGtsMxhW6hvkVCTFyGYbN+u0p2rpMNBUmlLgIBVTyQirx3/wZs6kJ3G58F1+M1d2Ne8lSyTaNcIP6qviv//qvdHR0cNttt1FdXU02m8WyrCP+HC0LJYQYflpRMXbW2RbdN5Zg5w48qkE4oJJMOeW6cel6xuWBZcGWvf3LdeGgSkNblmRaynVCvJ/WbpP12515aDMq3Zg2jC9yoXW3kezdSedbfiF2Oi3ZplFiUIHTX//6V66++mr+8z//k8rKSjRNG+p1CSFOIS03F8Xtxk6n0cePR41EIJMhu3s3eWENw7SwPT6UdIpFxc7AvvcOwwz6VWIJm5ZO+YIkxPupb8mwo8b50jFvqhdNhaJcnfS7GzEO1IKi4P3AB7BTKeltGiUGFTi53W4mT5481GsRQpwmaiSCEgphxeMoivKeQ39V3C6VtGFje7wsce8HoKYhS1fPoSBJVRR0DRrkCBYhjiqRsnhra4pY0sbrdhrCwwGVfE+W+F+eBsA1bRoYBlpRsWSbRolBBU4XXXQRb7/99lCvRQhxmiguF3pJKVbcOYjbPdsJnNJVW/G6FYK+g7vrwhQkm5hUrGADm3a/t1yn0dxh0JOQrJMQ79XSabBxt5OpnTvFQzpjUV7kwm5tIr1hAwCeJUt6s03TJds0SgwqcPr+979PVVUVP/jBD4Z6PUKI00QvLATDxLZt3NOng65jtbVhtTSTn6ORzdq95boki4viALy7u3+5LuBViKcsWqVcJ0Q/tm2zrz7D3jonIztvsgdVVSjK1Um+8gpWZye43ejjxku2aZQZ1K66b3/728yePZuvf/3r/PKXv2T+/PlEIpEjHqcoCvfdd99JL1IIMfTU3FwUrxc7lUL1+XBNnUp2+3YyW7cQPvdidF0ha9hoHh+L9Br+pM6iodWgucOgOM9561AUBY9L5UBzlollLtlJK0Svzh6LtVUp0lmbSFAlP6Li82hE7CidLztjejzz5oNl4Z42TbJNo8igAqff/OY3ff+8b98+9vVOIX4vCZyEGLnUcBg1HMaOx8Hnwz17Tm/gtJXIxZcQ9Ckk0zbuYJhwrIXpZbPZXmezcXeKDy8L9j1PJKjS1m3SFbPIDclGESEAmjuyVO1zStsLp3lJpGBahQ71+8hs2QKAe+5c1FAIvax0OJcqTtCgAqfq6uqhXocQ4jRTNA29tIz01s1oFOCZM4f4H/9Adu9e7FSS/IjO3rosdsCH0tHM4sIY2+sCbNyV5kNnBfqySz6PSkuHSWunIYGTEDizm3buz7C/ySnTzZnkwaUrFIQg/ugqJ8sbiaAWFqKXlaEGgsd5RjGSDCpwqpQzdIQYE7T8fLBsbNtGKyxEKy7GbG4mu307oWkL0FQD0wTN7WO+Us3v9Tm0d5vUtRiUFx8afOn3KtQ2Z5k83o2mSrlOnNlauwze3p7CtKA0X8fnVQh6VSLpdtrfehMAz+LFqLaNPm78MK9WnKghOSuho6ODAwcODMVTDVosFuNf/uVfKCsrw+v1smDBAh555JEBX9/S0sKNN95IQUEBfr+fc845532Pi4nH49x+++1MmzYNj8dDfn4+K1asYPfu3UP1coQ4LdTcXFS/DzvpzGrq2123dStBv0rAp5BIW1jBCP5YG3PGO0HRe2c6RYIanVGLjqg0iQtR32qwY79zxMrC6R4SKZvyYh1z1y6ye/YA4Jo1GyUcRisuHs6likEYdODU3d3NP//zP1NcXExhYSETJ07su2/t2rV85CMfYUPvdsvT4dprr2XlypXccccdrFq1iqVLl/LJT36Shx566LjXptNpLr74YlavXs1PfvITnnzySYqLi7n00kt55ZVX+j02Fotx4YUXct9993HLLbfw/PPPc//997Ns2TISicSpenlCnBJqOIwSjmDFescSzO2d57StChWLvIhGKuPMc3J21/UAzlgCyzp03JLbpZA1LFo6jNP/IoQYQeIpi23VKRraDBRg5gQ3bpdCgTdD/NlVznl048ahBvzo48tRfb7hXrI4QYMq1XV0dHDuueeya9cuFi1aRGFhIdu3b++7f968ebzxxhv87ne/Y/HixUO22PfzzDPP8MILL/DQQw/xyU9+EoAVK1awf/9+vvrVr3L99dcfc7r5fffdx9atW3nzzTc555xz+q6fP38+X/va11i7dm3fY7/5zW+yfft2Nm/ezKRJk/puv/LKK0/RqxPi1FEUBb2sjExTEwCuyVOcnXY9PRi1tYTzK1CVLKYFmsfHLGMffs98ehIWe+uzTC0/tBMo4NOoazGYXmGj61KuE2emlg6Dd3c5TeGTxzs7TfNDKqFYM63vHJrdhK2gjxs3nEsVgzSojNOdd97Jrl27ePjhh3n77be57rrr+t3v8/lYvnw5L7300pAs8ngef/xxgsHgEeu46aabaGho6Bf4vN/106dP7wuaAHRd54YbbmDdunXU19cDkEgk+PWvf811113XL2gSYjTT8vKxUbAtC0XTcM2cCThTxEM+FZ9HIdlbrvP0tDOvd9zMxiPKdSqdMZO2binXiTOTZdnsb8yw+0BvmW6al1TaZnyhTmbDesz6elAU3FOnoeZE0IuKhnnFYjAGFTg99dRTXH755Vx//fXv+5jKykrq6uoGvbATsXXrVmbOnImu90+gzZs3r+/+411/8LFHu76qqgqADRs2EI/HmTp1KjfffDO5ubm43W6WLFnCX/7yl6F4KUKcdlpuLmrAj91bavb09jllqrai65AX1kile8t1mTSLC6IAbN2XxjAPlet0TcG2oLFdjmARZ6aumEVVdYaOqIWuwdQKFx63Qp4dJfGyk0hwzZiBoqi4KipldtMoNajAqbGxkVmzZh3zMV6vl3g8PqhFnaj29nby8vKOuP3gbe3t7UNy/cHM03/913+xZcsWfvvb3/L4448TDoe54ooreO655973d6TTaaLRaL8/QowEajCIlpt3qM9p9mwAjNpazO5uIkGnzG3ZYHt9TM3sIxxwjmTZWZvp91whv0p9i0E6a53eFyHECNDYlmVr7+ymWRM9pDOQF1bxdzeR2bwZcHbToanopTK7abQaVOCUn59/3F10O3bsoHQQfzHWrFmDoigD+rNx48a+6441sXgg04wHcr1lOR8GbrebVatWccUVV/DRj36UP//5z5SWlvLtb3/7fZ/jrrvuIhKJ9P0pLy8/7pqEOF20stK+nXVqOIzeO3IkU7WVsF/F61ZIpS2sYBhXtIMF5U6madN7ynWhgEpPQo5gEWeerGFT05hhT93B3XReUhmL8jyF9KtrsLq6wO3BVVGJmpuHVlg4vAsWgzao5vALLriAp556ivr6esYdpblt27ZtPPvss9x0000n/NzTp0/nV7/61YAeW9F7tk9+fv5Rs0odHR0AR80mHW6g1+fn5wNw7rnnEgqF+h7n9/tZvnw5TzzxxPv+jm984xvceuutfT9Ho1EJnsSIoeXmgaZhmyaKpuGePQdj/34yW7fiO/c8ckLOYb7+iBclk2LR+C5eJUJVdZpM1sbtcr5caKqCAjS0Gowvch37lwoxhrR0GlTtyxBP2vg9CuVFOsm0TV6mjdRf/wqAZ+EC7EwGfcIEFH1QH79iBBjUv7nbbruNJ598kvPOO4/vfe97tLW1AbB9+3befPNNbrvtNjweD1/96ldP+LlLS0v5whe+cELXzJ07l4cffhjDMPr1OW3pHWs/Z86c415/8LGHe+/1R+uDOsi2bVT1/RN4Ho8Hj8dzzHUIMVzU3FzUQAA7FkOJRHDPmUPimb+Q3bEDO5slN6TR2GZg22B7/UxKVpMXXkRH1GJbTZoFU719zxUJqjS1Z4mnPAS8QzIqTogRr77l0Oym+VO9JFI2hTkansZqYjucXeeeBQtR3G70EpndNJoN6l1t7ty5/P73v6erq4vPfOYz3Hvvvdi2zZw5c/jiF79IMpnk0UcfZerUqUO93qO65ppriMVi/OlPf+p3+8qVKykrK2PZsmXHvX7Hjh39dt8ZhsGDDz7IsmXLKCsrA5yg7pxzzuGNN97o16OUSCR45ZVXOPvss4fwVQlx+qg+H1p+AVZvX6JeXu6cY5dOk927l1BAxetRSGdsrGAYvaeDhRW95brd/ct1Ab9KLGnT2ikzncSZIZ602N+UYV+9szFiwTQP6azF+GCa1CtrnCNWcnJQCwtR8/PR8guGecXiZAw6V3jllVeyb98+Vq5cydq1a+no6CAcDrNs2TJuuukmCgpO31+Myy67jEsuuYSbb76ZaDTKlClTePjhh3n22Wd58MEH+81w+vznP8/KlSvZu3dv39Exn/vc5/j5z3/Oddddx913301RURH33nsvO3fu5MUXX+z3u37wgx+wYsUKPvzhD/P1r38dRVH47//+b9ra2o7Z4yTESKeXlpKtdg7sVlQV9+zZpP76VzJbtxKcMYNIwDnM1xv2QibDopIuVhNhR02GZNrC53G+h6mKgq475boJpbJrSIx9TR1OmS5j2OSFVQpzNKdMl2wiueFtADxLl0IyhXvhRJRjVCfEyDeowOm3v/0txcXFfPjDH+YrX/nKUK9pUB577DFuu+02br/9djo6OpgxYwYPP/wwn/jEJ/o9zjRNTNPEtg9to/Z4PKxevZqvfe1r3HLLLSQSCRYsWMCqVatYvnx5v+vPPfdcVq9ezTe/+U0+/elPA3D22WezZs2afnOghBht1NxcFF3HzmZRXC7cc+Y4gVPVVvibvyE3rNHcYULv7rqK+D6K85bQ3GFStS/NkpmHJiBHAhotnQbRuEk4IAf/irHLsmwONGXZfVhTeE/CpiRXRd9TRXaf82XEPW8+qt8nR6yMAYp9eAQxQC6Xi1tuuYUf/vCHp2JNZ4RoNEokEqG7u5twODzcyxECO5Mh9uc/gwJaTg5WKkX7174KpknuHXeSCReweXcaj0fBY2fQu9p5KnAxz26GaRVuvnBlzqHnsm1qm7KcPdfP5HGSdRJjV1uXwV/ejPGrJ7qwbPi3T+WSTMO542IE/u8eks89h15eTuizf4teXILv4osHtNNbnF4n8pk8qHxhaWkpmUzm+A8UQowaituNXlyE3TvPSfV6cU2ZAjhTxH0elaBfJZGywe0BM8vicCsAew5kiCUPzW5SFAWvR+VAU7bfmXZCjDVN7Qbbq9NYNowv0vH7NAI+hUi8icxmZ4ORZ+lZ2Ok0emWFBE1jwKACp6uvvpoXXniBdDo91OsRQgwjragIO3uoqdvdu6M0s3ULigL5EQ3DcAIkyxektKea8YUalg1b9vRvEg8HVNqjJl0xGYYpxqZM1uZAc5Y9dU5T+KLpXqJxk6KAibp1A2Zjg3PEyqxZqIEAWpGU6caCQQVO3/72twkGg1xzzTV9x5EIIUY/LScXxe3C7s0ou3uPX8nu2YOVShEKqLhcKlnDxgpFUKPdLCxzHrtxd/8vUj6PSioju+vE2NXSaVDTmKWhzUBVYO4UD4YBZbT3zW5yz5wFpolWUoIWiQzzisVQGFRz+MKFC0mn02zcuJHnnnsOr9dLUVHRESlIRVHYu3fvkCxUCHHqqTk5KKEQViyGlpeHXlyMVliI2dpKdsd2AvMXEvQpxJM2kaAO2Cz2N/I046luyNIVM8kJHmoG93sVapuyTCl3o6lSohBjS31rll29xw5NLXejKgoBn0K4o5b4tm2As5vONgxc5RXDuVQxhAaVcbIsC7fbTUVFBRUVFRT1nvBs23a/PwePKBFCjA6Ky4VeUtJ3bh2Ae85cwOlzUhTn0N9M1ulbsgIhCqK1TCxxgqXN78k6RQIanT0WHd1yBIsYW3oSJg2tWXYdOLSbLho3KXXHYeN6rO5uFK8X16RJznmQxUXDvGIxVAaVcaqpqRniZQghRgq9oJCMta3vZ/ecOSRffolMVRW2ZREOaOiagWGCHgijt9SxqCRJdZObjbtTXLDQf+hal4JhWjR3GBTmyhETYuxo6TDZV5+ls8fC7VKYNcFNS6dJsdlOesMGwJkUbiWTuKdMRQ0Eh3nFYqjIFC4hRD9qbi6Kx4OVcpq9XVOmOD9Hoxh1dQR8Kn6vQjJtgaqCorLIfQBVgboWg7au/j1NQb/GgZYsWUN214mxwbJs9jdl2Ns7KXzOJDcZwybotQg17SG7aycA7iVLUCwL/ShnuorR66QDp23btvHYY4/xwAMPDMV6hBDDTI1EUEPhvrEEiq7jmjEDcMp1mgp5EY10xinFm6EccqL1TCl13k42vadcFw6odMcs2qRcJ8aI9qhJS6fZ19+0cJqXnrjFOKULa8Na7HQaNTcXrbgYJRRCK5Iy3Vgy6MBp/fr1LFiwgLlz53Lddddx44039t336quv4vf7eeqpp4ZijUKI00jRNPSyUqxEvO+2Q2MJtgJO75KiKJgm2L4AajLOomLn8Rvfc3adrinYNjS1ZU/TKxDi1GpqN9hblyGRtgn6FCaOc2HZUJhuIrNlM9A7uynWg6u8AtXnO84zitFkUIFTVVUVF110EdXV1XzlK1/hsssu63f/+eefT0FBAX/4wx+GZJFCiNNLyy8Ay+47mujgWAJjfw1WNErIrxL0qSTSFigKltvDAqUaTYXmDpOm9v7lulBApb7V6MtSCTFapbMWB5qy7Gs4eKCvl2TKJqSm8R/YSba6GgDP4sVgK+jjyoZzueIUGFTgdMcddwCwYcMGfvCDH7B06dJ+9yuKwjnnnMP69etPfoVCiNNOzc1F9fmwk0kAtEgEvbwcgExVFZrWv1xnhXIIxVqYUeaMHNi4q3/WKeRX6UlYtHZJuU6Mbq2dJq1dJrsPHFamS1iMpw3r3fVgWegVTpZJzYmgFUqZbqwZVOD0yiuv8LGPfYwpvccxHE1FRQWNjY2DXpgQYvio4TBKJPKesQRO1ild5ZTrcg4v13l8KOkkiwujgFOuO/wYTE1VUBVoaJVhmGJ0a2g12FefwTChMEejNF8D2yY/Vk/m4Oyms5Zh98RwVU5AcctZjWPNoAKnnp6evtlN7yeVSmGa8u1SiNFIURT0sjJIJPpuOzjPKbt9O7ZpEgwcVq7D6XWaZ+7FpUNH1OJAS/8gKRzUaGzPEk9KuU6MTvGkRWN7lj31h45YiSVtImYUb802zMZGUFU88+aBpqKXlg7zisWpMKjAqby8nK29TaLvZ8OGDUyePHlQixJCDD8tLx8bsHsH2eoVFSihEHYqRXbvHjTVObsu1Rs4mcEI/ng7c3p3Xm96T7ku4FOIJW1auyTrJEanlk6D5g6TmsP6m3oSFuPsVsxN7wLgnjULLAs1Nw+toGA4lytOkUEFTpdffjnPP/88L7300lHvf/TRR3nrrbe4+uqrT2ZtQohhpOXmogYC2L1ZJ0VVcc+aDRy2uy6ooakqhgm43GAaLM7tBGDTnjTWYeU6VVFw6wp1LUa/Mp4Qo4Ft29S1ZNlXn8EGJpS6iARVVMsgt6uG7I7tgFOms2Ix9AkTUHQZ+joWDSpw+o//+A9KS0u57LLL+Lu/+zvefvttAO69914+85nP8KlPfYoJEyZw6623DulihRCnjxIIoObm9utz8rxnLEHQrxLw9w7DBCx/kNnZ3fjcCtG4RXVD/xEEkaBKa6dBT0LKdWJ06Y5Zzuymw45Y6Ylb5GXa8Oza2nfEinvaVBS3G1dJyTCvWJwqgwqcCgsLWbNmDUuWLOHXv/41f/nLX7Btmy9/+cv87ne/Y+nSpbz00ktE5CRoIUYtRVHQS8uwU4dKbq6ZM0FVMZubMdva0FQoiGik0r1n1wXDeJLdzB3n9De+dximz6OQSDkfQEKMJi2dBo2tBk3tJqoK8yZ7iCUtyrLNmNudLxKeRYuxEkm0ggLU/PxhXrE4VQadR5w8eTJvvPEGGzdu5K233qKjo4NwOMyyZcuOGE8ghBidtNxcUFVs00TRNFSfD9fkyWR37yazdQu+C1cQDmpoau/ZdZoOts3icAvrKGHznhRXnR9E05wxBYqi4PWo1DZnmFTmQlWVYX6FQhyfadnUNmepaXKyTdPK3bhdCq50jEhHDdlduwDwnHUWdjyBa/4CFFVONBurBhQ4XXTRRdx444189rOfBZzJ4BMmTKCiooIFCxawYMGCU7lGIcQwUQ/2OcXjKOEw4IwlyO7eTXrTZnwXrnCGYfqdTFI4oGIFw8zI7CXoLSWWstlTl2F6pafvOSNBlY5ui66YRV5YG66XJsSAdXSbtHeZ7Krt3xSel27FvXMzyXQaNT8frbQUYjG04uJhXrE4lQYUEq9Zs4aampq+n1esWMFvfvObU7QkIcRIofr9aHn5/fucFi4CILt7F2ZXF6oCBTka6Uxvuc4fwpXsYX6Z8+1843vKdV63Sjpr09IhR7CI0aGpw6CpI0tbt4muwayJbuLxLKXJerI7dwDgXXoWdjSKVliEmps7zCsWp9KAAqe8vDza29v7fpYdMUKcOfTSUuz0oeBHy89HnzQZbJt078aQcEBD1xRnd52qYms6SwLOANyqfWmyRv/3DL9XobbZwDDlvUSMbJmszYHmLDUNzhiNmRM8aKqCJ9FFuH0/RvU+ADxLl2Kn0+iVFSiKlKDHsgGV6ubNm8cDDzzA+PHjKe5NQW7cuJHf/va3x732YHlPCDE6qXl5KLqOnc2iuFwAeJcuJbZvL+m31+P/4Aed3XW+w8t1EaakasgJVNAVt9m5P8OcyYfKdTlBjZZOg86oSWGubNkWI1drl0F3zGRHrZNBXTDNQzRukp9oRtu1BcOy0CdMQA0GsVUVrUjKdGPdgN6x7rrrLq644gq+/vWv90XSTz75JE8++eT7XmPbNoqiSOAkxCin5eSgBIJY8ThaTg4AnkWLiP3hUYwDBzAaG9FLSynI0dhbl4WAM0Vc72pjYUmal/d62Lg71S9wcukKpmnT1GFI4CRGtMY2g8Y2k+6YhcelMKPSQ2NTghmpOoydOwHwnrUMq6sLvaICTXaTj3kDesdatmwZe/bsYf369dTX13PjjTdy1VVXcdVVV53q9Qkhhpni8aAVFWHUVENv4KQGg7hnzyazZQvp9evQr7yKSEBD1wyyho1LV7DdXha7a3mZqWyvSZPKWHjdh7oDgn6NuuYs0ys8uF1S2hAjTyJl0dCWpbrRyTbNmeTBtiEQbSXQtA+zsQFUFffChVgdHbjKK4Z5xeJ0GPBXvXA4zMUXXwzAjTfeyIIFC/jbv/3bU7YwIcTIoZcUk929u99tnqVLyWzZQurtt/FfcSXB3t11yZSNK6hghXKYEK2jIDSVth7YXp1h4XRv3/XhgEpjm0F7t0Fpget0vyQhjqul0yAas9ixv3+ZriBeh753OybOLlPFtlGDIbTiY5/hKsaGATWHT5o0iZ/+9Kd9P99///1ynIoQZxAtJxfF7cLOZPpu88ydh+L1YrW3Y+zbh3Jwd13Wafi2PV7UbJpFxc6RLRt39z+7Tu+d7dTYJmfXiZHHOWLFGXgZT9oEvApTxrtJdfZQlGomu30b4JTpzGg3+rhxqIHgMK9anA4DCpxqamro6urq+/lzn/scTzzxxClakhBipFFzclCCwX5jCRS3G/f8BQCk1q8DcMp1utK3i87y+Vmi1wCwqzZDItX/qJVwQKW+1eg7KFiIkSIat2jpNNjX4HxZmDfFi2lBoKcFf/1OrGgUxefDNXMmimWjjxs3zCsWp8uAAqeioiLq6+v7fpZxBEKcWRSXC72kpF/gBM7uOoD0O+9gGwYBn0rIr5BIHTyCJcL4TD2lOTamBVv29p/pFPKr9CQtWrvkCBYxsrR0mvQkzL4y3fypHqIxg7yeetR9vZPCFy/GTqVQQmEZenkGGXBz+AMPPICu633jCNasWXPc6xRF4Vvf+tZJLVAIMTLohUVktm3rd5tr+nTUcBgrGiWzfRueufMoiGh0RnuHW7rcYFksKujhL11hNu1OsWy2r+96VVXQFKhvzVJeLH1OYmQwLZvapgxN7SapjE0kqDKhzEXj3lYKU42Hhl6etQyruxvP7NmoXu9xnlWMFQMKnL7//e9z9dVX84tf/AJwAqI1a9YcN3iSwEmIsUPNzXV6mlKpvg8JRVXxLFlC8qWXSK9fj2fuPGcYpn5od50VCLHU2MdfWMDe+iw9cZNQ4NBRK+GgRkuHQSJl4ffK+V5i+HVETTqiljNeA5g/xYNhQKCnDX/NNsxMBrWgAK2iArOxEb2sbJhXLE6nAQVO06ZNY+vWrVRXV1NfX8+FF17IjTfeKLvqhDiDqJEIaiiMHYvBYd+uPUvPcgKnzZuxkkkCPh8hv0I8aRMJKliBMEWtDVTkWdR2qGzek+a8+f6+6wNehbqoRUfUlMBJjAjN7QbxlMnOWqe0vGCal2hPhqJoLUq1U6bznuUcsaLm5KAVym66M8mAxxGoqsrkyZOZPHkylZWVLFiwgOXLl5/KtQkhRhBF09BLS0hXVXH40bx6eTlacTFmczOZTZvwnn02BTk6ndHeHXiaBgoszu2itiOPjbv7B06qqqAoCm3dJuOLpFwnhlfWsDnQkqWxzSRrQH5EY1yhTvOuRgoSDRjV1YDzhcGK9uBZtBDF7R7mVYvTaVBf76qrq/mnf/qnoV6LEGKE0woKwLL6bRBRFAVPb5P4wd114YCKy6WQ6R1NYAXCLFb3ogD7m7J0Rvs3gwd8Ko1tWQxDNp6I4dXaadDVY7HrwKHZTVkDfN3N+Gp3gGU5E8JzclB0Hb2kdJhXLE43yYsLIQZMzclF9fmwk8l+t3uXngVAdudOrO5uAl6VkE8hkT4YOIXIy7YzqcAJmDbt6T/TKeRX6YnbdMZkd50YXk3tBqmMxe6DgdNULz3dKfJidSjVewBnN53V3Y2al+t8mRBnlAGV6i666CIURWHlypWMHz+eiy66aEBPrigKq1evPqkFCiFGDjUcRolEsKJRVP+hcptWUIA+cSJGdTWpDRvwX3QR+Tk6HdE0oIKiYms6S8Kt7G0rYePuNBcuCvRd79IVDMumI2pSmCNn14nhkUxb1LUa1LcaWBaUFugU5+k0b2sgP96AWbsfAM8iJ3DyzpqNosvf1zPNgP6Nr1mzBkVRSCQSfT8PxMEDgYUQY4OiquilpWSamo64z7v0LGLV1aTXr8N/0UW95TqVTNbG7XKOYFkU28cflBIaWg1aOg2KDjvg1+tWaGw1mFbulvcOMSxaOk1iicOOWJnqIZO18XU14TuwC8u20SdNQvX7sVMpdJnddEYaUKnOsixM02TatGl9Pw/kj2lK2l2IsUbLL8AGbKv/tG/PokWgqhi1tRjNzb3lOrWvXGd7/YSy3UwvdLZ4b9rdfxhm0KfS2WPSk5Ap4mJ41LdkSWUtqut7xxBM9RLripMbqz9Uplu0GLO7Gy0/HzU/fziXK4aJ9DgJIU6IlpuL6g9g92agD1JDIdyzZgGQXr+u7+y6bLY3EFIUbI+PxYFGADbuSvVrMvd5FJJpp1wnxOkWjZs0dxgcaDKwgcoSnbywhtHU5JTp6g6AouBZtAg7kcA1YSKKKh+hZyL5ty6EOCFKIICam3PE8SvAYbvr1mPbdl+57uDBv1YowkKlGl2D1i6z3wG/iqKgadDSIYGTOP1aOk0SKYttNb2zm6Z6yWRt/J2N+Or3AuCaMgXF7Ub1+dCKZHbTmWpAPU6//e1vB/0LPvvZzw76WiHEyKMoCnrZOIzDzq88yDN3Hj1uD1ZbG0Z1Nf6Jkwj7VbrjFh6Xgu324rOamVWQZnOzh42705QVHprdFPSpNHcYpDMWHrd8rxOnh9V7xEo6a3Og2UBRYN4UD/H2bgoTzSjVuwHwLF6CdbBMl5MzvIsWw2ZAgdONN97Yr1nTtu3jNm8efIwETkKMPVpBAYqmY2cy/Yb/KR4PnvnzSa9fR2r9ekKTJlEQ0WjvNsBWQQHLF2AJdWxmMpt2p7jsnEDf+0nQp9LQZtDRY1GaL4GTOD06e0zauy2qG53epsnjXIQCGq27m8mPNWA21IOq4lm4ELOlFdfCSinTncEGFDjdf//9R9z2xz/+kb/85S9cfPHFnH/++RQXF9Pc3Myrr77KSy+9xOWXX87HPvaxIV+wEGL4aQUFqPl5WF1dR5QsvGedRXr9OtLvbCD4N39DOKjidqmkDRuPS8EKRpiXrMGjT6Kzx6K2yaCy1Mk6aZqCDbR3GZTmyzZvcXo0tRtkDJuqfYeOWMlkLAId9Xgb9mEBrukzQNNQvF60wsLhXbAYVgN6Z3rvmXRPPPEEL7zwAs8//zwf/OAHj3j8888/z5VXXskXvvCFoVmlEGJEUXQdV+UEUuvW9jt+BcA1fTpKKITd00Nm+3Z8s+cQDqh0xZxyHboLNwZzC5O83ehn4+5UX+AEztl1DW0GMyfaaKqMJRCnlmHY1LUYJNMWTe0mmgpzJnlItHZQmGyDfTsB8C5ejBWNOmW63NxhXrUYToPKNX7ve9/j4x//+FGDJoAPfehDXHfddXznO985qcUJIUYuvbgYxePFes8UcUXT8C5eDBzaXZcf0TAMC3o30VmBEEvczjDBTXvSWNah3XVBn9MT1R2TsQTi1GvtNumMmezrHUEwrcKN36tiNjWRF6vHam4GXcc9f76zm65SynRnukH926+qqqK8vPyYjykvL6eqqmpQixJCjHxqfj5aQQFWd9cR93l6j2BJb96MnUoRDqh4est14JxdN4ta/G6bWMJib++HFoDHrZLJWkecZyfEqdDUlsUybTb3HgO0YJqXbMbE31aLt8k50Nc9cxaoKopHynRikIFTKBTi1VdfPeZjXn31VUKh0KAWJYQY+RRVxTVhAnai/zwmAL2y0ul9ymRIb96Ez6MSDqgkUr2P0zR0TWV+fg8Am3b3P7vO43KaxIU4lVJpi7oWg3jKpiNq4dJh9kQPiaZWwuku2OOU6Q4/m07NyxveRYthN6jA6eqrr+bNN9/k5ptvpqWlpd99LS0t/MM//AN//etfueaaa4ZkkUKIkUkrLkYN+o8YhqkoCp4lh2Y6KQrkRTQMw+4r15nBMEtcTrlu6773lOv8Ku3dBvGklOvEqXPwiJWDB/rOmujB7VIwGxrIizditbWCy4Vn7lzsRAJ35QQp04nBBU533XUXs2fP5v/7//4/KisrmTt3LhdffDFz586lsrKS//3f/2X27NncddddQ73e9xWLxfiXf/kXysrK8Hq9LFiwgEceeWTA17e0tHDjjTdSUFCA3+/nnHPOOeoBxel0mu9///vMmTOHQCBAcXExl112GW+++eZQvhwhRgU1EkErKsHq6jziPm/vMMzs9u1Y0ahTrnMrfcMwbX+QaUoDPpdNImVT23yoXOf3KiRSMkVcnFr1rVkUxWbznkNDL7OpDP6OOrxNNQC458wBQHG7pUwngEEGTrm5uaxdu5bbb7+dsrIyqqqqePnll6mqqqKsrIzbb7+dt956i5zTOCDs2muvZeXKldxxxx2sWrWKpUuX8slPfpKHHnrouNem02kuvvhiVq9ezU9+8hOefPJJiouLufTSS3nllVf6PfaLX/wi//7v/87VV1/N008/zc9//nNaW1tZvnw569atO1UvT4gRSVEUXBUV2JnsEWfXaUVF6JUTwLZJbdiA3/uecp2iorp0ZoWjAGyrzvRdqyoKqgJtXVKuE6fGwSNWuuIW0biFz6MwvdJNsqGFUKYbdm8DwLt4CWY0ipqfL2U6AQxwHMHR+Hw+7rzzTu68805isRjd3d2Ew+Fh6Wt65plneOGFF3jooYf45Cc/CcCKFSvYv38/X/3qV7n++uvRtPdumj7kvvvuY+vWrbz55pucc845fdfPnz+fr33ta6xduxZwAqyHHnqIT33qU/12DJ533nmUlZXxu9/9jrPOOusUvlIhRh6tuBi1d/yAEon0u8971lJi+2tIr1+Pf8UK8iMarZ2mU65TcGY6xevZQITtNWk+cm6w79qAX6Wx3WCOYePSZSyBGFqtnSbxpMXO/U7APmeSB11TMBvryY03YnV2ong8uGfPxqivxzVnDsoxPkfEmWNIirXBYJBx48YNWzP4448/TjAY5Lrrrut3+0033URDQ0Nf4HOs66dPn94XNAHous4NN9zAunXrqO89WkJVVVRVJfKeD4dwOIyqqni93iF6RUKMHmowiD5uPGa0+4j7PIuXgKpi7K/BaGk5slznCzBbq0dVbJo7zH6luaBPpSchu+vE0LMsmwPNWVwuhS17Dw29NBJJAh31+Jqc3jv3vHlg206ZTs6mE73GRJfb1q1bmTlzJrreP4E2b968vvuPd/3Bxx7t+oNjFVwuF//4j//IypUreeKJJ4hGo9TU1PDFL36RSCTCF7/4xaF4OUKMOvq4cWBa2Gb/IEcNhXDNmAE4M518HpVI8LByHeDzu5gUiAOwrTrdd7tLVzBNaI9KuU4Mrc4ek7Zuk7Yuk0TKJuhTmDTORbK+mWA2ir3Lec8/eDadmpuHlpc/zKsWI8WYCJza29vJO0rt+eBt7e3tQ3b9j370I2699VY+9rGPEYlEmDhxIm+88QYvvfQSU6ZMed/fkU6niUaj/f4IMVZoxcWokRyso/y9Ptgknl6/Htu2yQ9rGKZ92DDMMHO9TQBsr0n3v9aj0Nhm9NtxJ8TJauk0SGftvkB93hQvmqpgNRwgJ9GMHY2i+Hy4Z87EisedoZdSphO9RlzgtGbNGhRFGdCfjRs39l13rEOHj3cg8Ylc/93vfpcf/OAH3Hnnnbz88ss8+eSTTJ8+nUsuuYR33333fZ/jrrvuIhKJ9P053gBRIUYT1evFVVGO3X1k4OSZNx/cbszWVoz9+wkHNDxuhdTBcp3HyzxPIwD76rOkMoeazEN+lc4ei56EjCUQQ8MwbGqbDDwu2LrP6W9aMM2L0dODr7MJX6Mz9NKzYAFYForLhVYku+nEISPuFM3p06fzq1/9akCPraioACA/P/+oWaWOjg6Ao2aTDjfQ67dv387tt9/OPffcw7/927/1Pe6yyy5j1qxZ3Hrrrbz88stH/R3f+MY3uPXWW/t+jkajEjyJMUUvLSO9rQo7m0VxHTp7TvF68cybT/rt9aTXrSP48QnkBFXauk28bg0UhWJPikJfltaki921GeZOcfoFvW6F1k5nLEEkKN/4xclr6zbpipm0dJhksja5IZXKEp34zmbyjB7snc5uur6hl7m5UqYT/Yy4wKm0tPSEDweeO3cuDz/8MIZh9Otz2rJlCwBzeudwHOv6g4893Huv37RpE7Zts7S39HCQy+Vi/vz5R4wuOJzH48Hj8QzsBQkxCmlFRWg5uVjd3WgFBf3u8yxdSvrt9aTe2UDgYx8jL6zR3GFi26AoYPkCzPG38XKylG01hwInRVHQdWjuMJhY5h6OlyXGmMb2LJZFX1P4/KleFMCuqyEn2YIdj6EEg7imTcc4cADPjJko+oj7qBTDaMSV6gbjmmuuIRaL8ac//anf7StXrqSsrIxly5Yd9/odO3b0231nGAYPPvggy5Yto6ysDKDvf996661+16fTad555x3Gjx8/FC9HiFFJcbnQKydg9fQccZ975kyUYBC7p4fsjh2Eg065Lp3pPbvOF+gr1+2o6T9FPORTaek0SaalXCdOTjpjUd9i4HLBjv0Hh156MLu68Ebb8DbsA8CzYCGYJoqmoxcXD+eSxQh0UmF0U1MTjz32GDt27CCRSPDrX/8agNbWVqqrq5k7dy4+n29IFnosl112GZdccgk333wz0WiUKVOm8PDDD/Pss8/y4IMP9pvh9PnPf56VK1eyd+9eKisrAfjc5z7Hz3/+c6677jruvvtuioqKuPfee9m5cycvvvhi37Uf+MAHWLp0KXfeeSeJRIILLriA7u5ufvazn1FdXc0DDzxwyl+rECOZXlpCxu3GTqdRDsuwKpqGZ/FiUq+8Qmr9esKzZ5MbUmntNPF6NHC5maLX4tVt4ik40GxQWeqU+/w+lcY2g86oia9wTHzXE8OkpdMkmrBobjcwTCjK1Sgt0ElsayLXSsDO3t10SxZjRaNOmS5fynSiv0G/C917771MnDiRL3/5y/zP//wP999/f999LS0tnHPOOTz44INDssiBeOyxx/jMZz7D7bffzqWXXsratWt5+OGH+fSnP93vcaZpYppmv0NJPR4Pq1evZsWKFdxyyy1cccUVNDY2smrVKpYvX973OFVVeeGFF/jXf/1X/vCHP3DllVdy8803A84QzhtuuOH0vFghRigtvwA1Px+zq+uI+7xLneGw6U2bsNNp8sI6pgUH/1NU3S5mRXqniB+2u05TFWzb6U0R4mTUt2bRFPqOWJk/1Yti21BX4+ymSyZRIxFck6dgxeLoFRVSphNHUOz3Hms+AE8//TRXXXUVS5Ys4fbbb2fVqlX88pe/xDxshsvChQspKyvjL3/5y5AueKyIRqNEIpG+ietCjBWZ7dtJvvkmrkkT+91u2zYdd96J1dZK6MabYP4SNu1OoWsKPo+CEu/h7fYcVtZPoyRP49ZPHfqm3xE18bgULl4aQNdkirg4cbGExYvrY5gW/OjhDiwbvvrpPPLNTqw1zzNp98vYm9/Bt2IFgauuxmxqwv+hD6OXlAz30sVpcCKfyYPKOH3/+9+noqKCl19+mcsvv5yio0xUnTt3Ltu2bRvM0wshRjGtuBjV78NKJPrdrijKYTOd1uF1K+SGVBIpp3fJ9vmZo9WhKDZNR5kiHo1bdMck6yQGp6XTIJ6y2FufwbJhXKFOYa5Oqr6RgJ3C3vmeoZc5OVKmE0c1qMBp48aNfPSjHyUQCLzvY8aNG0dzc/OgFyaEGJ3U3Fy0wiKso5TrPL2BU2b7dqyeHnJDOtbBcp2qEVCzTMzJAv2HYbpdClnDpiMqDeLixNm2c8SKx6WyaffBpnAvGFmUuhoiiWZIp1Hz8tAnTMA+WKY7bKyGEAcNKnCyLAvXcf5Ctba2yvZ7Ic5AiqKgV1Zip9O8txNALy5Gr6gAyyK9YQPhgIrPo5Dq3TFne33M9bcCsL0m0+9aj1uhoTV7xHMKcTydPRatXSZgU9PgBObzp3qw2lpxxbvwHtgNOLObMAxsTUEvlhKdOLpBBU7Tp0/n9ddff9/7DcPglVdeYe7cuYNemBBi9NKLi1EDQexY7Ij7PL1N4qm31+NxK+SEVBLpg2MJgszTnUO199Zl+k0RD/pUOntMYknJOokT09SeJZ212VmbxQYmlrnICWmk6xoIkMbe1Tv0cpGzm06L5Bwxi0yIgwYVOH3605/mnXfe4Tvf+c4R95mmyb/927+xb98+PvvZz570AoUQo48aDqOVlh61XOddvBgUBaO6GrO1lbywjt1brrM9XkroID9gYVqw+8ChrJPPq5BI2XRKuU6cgKxhU9uUJehT2bgrBTjZJjJplIZachLNkM2iFRWhl5djx2LoFZVSphPva1CB0y233MLy5cu54447mD59et/gyY9//ONMnTqVn/70p1xyySV8/vOfH9LFCiFGD1dFObZpYlv9Ax01EsE1YwbgZJ2CfhWPp3cYpqKgaBpzcp1M1eHlOlVR0FSnyVeIgWrpNOiKWWQNi/pWA1VxDvW1W5txJaN49u8CnGwThoGtKjL0UhzToAInl8vFc889x7//+7/T1tbG1q1bsW2bP/7xj3R0dPD1r3+dp556akCH6wohxiatqBg1FMKKHnnwb9/uunXr8LggHFBJpg+bIu5yynU7atJYh/U0BfwqTe0G6axkncTA1LcYYB860HdKuZugTyV7oA6fksXevR3oPZsuGkUNR6RMJ45p0AMw3W433/3ud2lra2Pbtm28/vrrbN68mfb2du666y7cbjlXSogzmer3o5eXHzVwcs9fAC4XZksLRm0tuSENw3SCIcsXYKrSiNcFsaRNXfOhDFPQpxJLWVKuEwMST1o0tmcJBw+V6RZM9aAk41iN9eTEm8A00UpL0cvKsHtiuMorUOTzSxzDoAKnSZMm8eUvfxlwdtDMmDGDc889lzlz5vQ73kQIcWbTy8YBYJv95y+pXi+eefMBSK9fT8iv4nKpZLI2uNzoVpoZhU6G4PAp4rqmYFs2HVEp14nja+owiCUtehIWLZ0mugazJ3mwW5pxp2N4qw9mm5ZgHyzTycBLcRyDCpza2toIhUJDvRYhxBijFxejRiLHnOmU3vA2PpdN0KeQ6i3X2bqHOf52ALZX9x9L4PWo1Lca/Q4CFuK9LMumtimD131odtOMSg8+t0L2QC0+zcTe29vf1FemC6MVFg7nssUoMKjAacGCBezatWuo1yKEGGMUtxtXRSV2z5FjCdyzZqEEAljRKMbuneSFNdLZ3j4nf5A5ai2KAo3tBp09hzJWIX/vFPG4lOvE++uImrR1WYQCCpt295bppnlQ41Hs5iZyovVgWejl5ehFRVg9PbjKy6VMJ45rUIHT17/+dZ5++mlefvnloV6PEGKM0cvKQFOxM/0zR4qm4Vm0CIDU+vWE/BqqCqbpHL8SznZTme8EUodPEfe6VVIZq9+RLEK8V1O7QdawaG436eyxcLsUZlQ6ZTo9m8Szr3d20+IlTilZUdBKSod51WI0GNSxz+3t7XzoQx/ikksu4ZprrmHp0qUUFxcfdRedzHIS4symFRSg5uVhdXWhvedcS++SpaRee43M5s3kfMLG71FIpi2Cfg1smzl5cWragmyvyXDuXH/fdW7d2V03eZxkB8SR0lmL2uYsIb/GSxviAMyb7MGt2WT31+DXTOzqPQB4Fi3CinajhsLoUqYTAzCowOnGG29EURRs2+ZPf/pT3xynwwMn27ZRFEUCJyHOcIqu45owkdS6tbx364g+aRJKIIAdj2PX1ZAXqeBAc5ag3zl+ZZ56gD8zk711GTJZG7fLeY8J+VXaugwSKQu/d9Cbg8UY1dpp0h2zKMzR2LzHyVYumuFFjXZgtbWS210Hto0+cSJafj7Z2v14Zs1GkWPCxAAMKnC6//77h3odQogxTC8uRvF4sVIpVK+373ZFVXHPmEF6wwYy27YRPn8C4EwRt3xByuIt5AVn0hGDXQcyzJnkfLD5vQqdPTYdUVMCJ3GEupYsquJMnk+mbSIBlUllLuw9zehmBs+erdg4TeG2aYItZToxcIMKnP72b/92qNchhBjD1Px8tIICzI421Pd8QLlnzuoLnEIfvhyv2zn01+fxonW2MLs4y2sxF9tr0n2Bk6o6mafWLoPxRXI0hjgkGjdpajeIhDRefNsp0y2c7kW1Tcz91Xg1E3v/PlAUPAsXYfX0oIZCsptODJh8VRNCnHKKquKaMAE7kcK2+48RcM2aBYBRW4ueipET6p0iriigqswJdgDO8SuHTxEP+lSa2gwMQ8YSiENaOk3iSQuw2dF7ZM+i6V60rjbMjg5yO/cD4JoyBS0nBysaRR8/vl8mVIhjGVTGqba2dsCPraioGMyvEEKMMVpxMWrAj51IoAQCh26PRNDGjcesryOzYwc5kxfS2GZCb7luurkfj6uYWMKirsWgotjJMAX9Ki2dBp0xk8KcQb2ViTHGtGz2N2bweVW27EljWlBWoFOSr2Nva0CzLTy7Nvcv01k2eqmU6cTADerdZsKECQM6h05RFAxDJvwKIZzDfbXiEoz6A6iHBU7gzHRK1teR2b6N4NzFuF0KacPG4wvg7mxjeilsrnXGEhwMnFy6gmE683okcBIAHd0m7d0WBTka7+x0ZjctnO6FTBpjfy0ezcCuPwCqimfBQqdMFw4dsdtTiGMZ1LvNZz/72aMGTt3d3WzatInq6mqWL1/OhP+/vfsOj6M6Fz/+nbK9qXdZ7r13mktowUASGwgll9BJSCUFEuCC4eYSAgnt8ku4oQQcioEQyg2hY5tmMDbu3bKt3tuuVto6M78/VlprLVuWZVmypfN5Hj2gs7MzZ1ay9t1z3vOeoUOPtX+CIAwQkiRhGjKEyP59GLqOJB/IFDCPH0/gg/cJb9+B0xSbhmsO6FicZtDCTEhpYXOJgx37w5w758A5bRaJitoIo/PNYlNxgcr6KFHdwNeiUVwVRZJg2mgLSmMFEW8TKU37ATCNGYPschEpKcE8ZoyYphOOSo8Cp2efffawjxmGwYMPPsgDDzzA008/3dN+CYIwACmZmcguF4bfj+R2x9tNw4cjWSwYzT60inJSPVnxApeGamaiqRKJkVTURWnyayQ5Y4UNnDaZxubYXmRuh9gnczALhXVKqiK47TJrd8RGm0blmWO/F7vLkCQZ865NAFhnzIwF74aBmp3Tn90WTkK9nhwuSRK//vWvmTBhArfccktvn14QhJOY7HSi5uaheZsS2iVVxTR6DACR7dtw2hVUJTYVp9udeFqqGZIR+3O1o+hABXKbRSIQMkQVcYHqBg1fi47TLsWn6aaPtSK1+omWl+NQIlBVAYqCecoU9OZmJKdTrKYTjtpxW1U3c+ZMVqxYcbxOLwjCSUrNzUXSjVhibgfmttV14e3bcdhk7NZYFXHD5kAOtDAhMwLAjv0Htl+RJAlVgeoGkUs5mBmGQVlNBFWB8hqNeq+G2SQxcbgFpb4azecjuWYPEPs9k+12dJ8XNTcX2W4/wtkFIdFxC5z27t0rEsMFQehEycxEcrnRfb6E9vbAKbJvH1IoQIpHIRg2QI5tvzLJ3QRAYVsV8XZOm0xNg0YoLDb9Hax8LTpVDVE8zgNJ4ROHmzGrQHkxmKyYdmwEwDJ9RmyaTtPFNJ3QI70aOOm6TmlpKb/73e948803OeWUU3rz9IIgDACy1YqpYAiGNzFwUtLSYqubdJ3Irl247TISoOtgWKzkBkpJdslENdhTdmC6zmmT8QfEpr+DWXVDlGDIwGKW2LSnbZpujBXZ10ikqgqHHIC6GjCZME+ejNHcjOQSq+mEnulRcrgsy12uYDEMg6SkJP74xz/2uGOCIAxcanYOoe3bMCIRJNOByt/m8eMJ1NTEyhJMnILNIhEM6yh2J0qLl/G5Ep/vjE3XTRgWqyKuKLG/RXVejew0UUV8sIlqBsWVEWxWiV3FYVpDBi67zMg8M8r+vYRbg6Q07ATAPGEistVKpLYW88hRYppO6JEeBU7z5s07ZOAkyzLJycnMnDmTa665hszMzGPuoCAIA4+SkYGSlIzu9aKkpcXbTeMnEFi1ivD27TgVSHIpVNVHsbttSI21TMxr5XMs8SrictvfIbtVoqIuyvhhBoosyhIMJnVNGg3NGhnJKu9+0bbFymgLsh7FKN0PdiemzzZiANYZsWk6NA01RxS9FHqmR4HTqlWrerkbgiAMJpLJhFowlNDX6xICJ/OoUaCq6A0NaNXVJDnTqaiNYhDbfmWUWo3ZVEBzq055TZT89iriNpmGZh2vXyfFLcoSDCaVdRF0HSJRg+1tCwfat1iJ1DXgkkIYjfVIFgvmiRMx/H5kpwslXUzTCT3ToxynkpISfAcldh6subn5qLZmEQRhcFGzs5DMZoxQh1VyZjOmkSOB2Oo6l13GYpYIRwx0qwNrQyWj82Kf93YUHXiexSwTiYiyBINNIBTbhsftkNmyN7bFSlaKQnaailJbQTSikVyyFQDzlClIZjOa14uak92per0gdFePAqdhw4bxyCOPdHnMX/7yF4YNG9aT0wuCMAgoqWnIqaloTU0J7ebxE4BY4GS1SLjsMq0hA93uRG7xMyErtlq3Yz0nALNJoqIu0id9F04M1Q1Rmlt1XHY5oXaTHA5ilJXE6jRtWw+Addbstmk6HTVHrKYTeq5HgdPBu5v39BhBEAYvSVEwDx2G0dKa0B4vS1C4ByMcJsWtEI0aYGrbfsXtRQLKa6N4/QdGmJx2mQavRktAlCUYDAzDoLQ6gkmVaPLr7K+IIAFTR1tRGmoIN3hJaq2FFj+S04lpzBiMlhZkp0NM0wnH5LjVcSorK8Plch2v0wuCMAAomZnIdht664HgScnKQk5OhkiEyJ49uOwyqioRiRoYqpmk5iryM9un6w6MOtmtEoGgmK4bLJr8OjWNGkkumQ1to00j8kwkORWUqlIiyHj2bwDAMmMGkqKgNzWhZGYhO5392XXhJNft5PD/+q//Svj+cAnimqZRVlbGSy+9xJw5cw55jCAIAoCcnIySnkG0uiq+NFySJMzjxxP8/HPCO3bgGD8BhzW2tYrZ7kRuqmV8vkxJdSzPae5EW+xckoQkQW3jgaRxYeCqro8QDBtkJEt8vatD7Sa/F62qEsXpQN6xGTgwTWdEo5jy8vqz28IA0O3A6e67747/vyRJrFq1qsvVdTk5Odx///3H0jdBEAY4SZJQCwqIlBRhGEa8zEk8cNq+DefFF5PqUdhfEcZwOVBqK5iQ38q7qOwpjVURN5tiz3PaZSrrowltwsATjRoUV0Vx2iTKaqLUNWmYVJg4woJSWUrI6ydFa4JwGDktDXXo0LbVdE5R9FI4Zt0OnFauXAnE5pW/8Y1vcPXVV3PVVVd1Ok5RFFJSUhg7diyyfNxmAgVBGCCU9HRkmwMjEEBqG3UyjRkLsoxWXY1WX4/LnowkSWiSgmoY5EqNJLkyaWrWKSwLM76tGKbTLlNVH6XeGxXFMAew2qYojc0aWakqn23yAzBhmAWrCkpFMRHVhmtn7D3LOnNW7HfH60UdUiCm6YRj1u3Aaf78+fH/X7p0KQsXLmTevHnHpVOCIAwesseDnJyM1tQYn66TbTZMw4YT2VsYK4Z5yhmxKuIhHbPFilpXwbiCfL7YGmRHUSgeOKmKhGFAZZ0InAayitoohgESsHFPh9V03nqidXWY7BakPdsBsMyaiWEYGJGImKYTekWPhoSWLl0qgiZBEHqFJEmo+XkYgcTVdabx4wAI79iOqkKySyHYVpZA8XsZnxVLAt9RFE5Yxet2yJTXRgmGxOq6gaglqFNeG8HjlNlVEqYlYOC0SYzKN6PWVRFqCZJWswt0HTUvDzUrOzZN53CipKf3d/eFAaBHlcM7Ki0tpaKiglCHInYdiQBLEIQjUVLTQFES9q4zj59A67/+RWTXLoxolCSXQlltFN1sQ2msY7TTh9lkx9eiU14bJS8j9jyXXaasJkptk0Z+pkgXGGhqGqI0BwzyMxU27I6NNk0dbUXRoyjlRUSsThyb2lbTzZoFgO71og4Zgux291u/hYGjx4HTv/71L2655Rb27NnT5XGaJpYGC4LQNSUlBdnlRvc3oySnAKDm5SE5nRh+P5H9+3AUjMJqlghFwCRLWJrrGJU/gm37wuwoCscDJ1mWUBQor42I1XUDjK4blFRFsJgkQmGDbfs6bLHSUEOkoRGL2QZFhSBJWGbMjK2mi0Qw5Q/p594LA0WPPo6tWrWKxYsX4/f7+clPfoJhGMybN48bb7yR8ePHYxgG559/PnfddVdv91cQhAFIMptRc3LR/f4DbbKMeVysGGZ4+w6sZgm3QyYQim2/otZVMn5ILDDquP0KgMcZ2xzY3yqm6waSxmaN2qZY7aate0NENchIVshNV1FqywlGDDLKY1usmEaORElOjhW9dLnEajqh1/QocPrDH/6A0+nk66+/5tFHHwVg4cKFPP7442zevJl7772Xjz76iG9/+9u92llBEAYuNTMDND0hXyleRXxHLNE32aUQ1fT49ivjU2N5UWU1iVXEHVaJ1qBBTWO0D+9AON6q6qOEIgZWs5xYuynYilJZRtThwbortsVKfJquqQk1O1usphN6TY8Cp7Vr1/Kd73yHzMzMeJuuxz7ZSZLEbbfdxrRp08SIkyAI3aakpCLb7RgtLfE287hxIElES0vRvV5cdhmTSSaMCaJhkiJN8SriO4sPVBGXJAmzSaK0JiK2fxogIlGDkuoILrtMY7PGvvLYvoTTRltRGqoJe304tBaoLAdFwTJ1WmyaTtNRc3P7uffCQNKjwKm1tZXcDr+IFosFn8+XcMzcuXP5/PPPj613giAMGpLLhZKSiu5vjrfJLhdqfj4A4Z07sFtlnDaJYMjAUE0o9dWMHxorRdB5uk6mrkmjyS+m6waCmsYoXr+O2yGzsS0pfHiOiWSXjFpVSlA3kVYSqxRunjAB2eHAaG4WRS+FXtejwCkrK4va2tr497m5uWzbti3hmPr6epEYLghCt0mShJqXhxFMDIDap+vC27cjSZDiVghFYmUJ5MZaxuXGRpT2lIaJRA+MLtksMsGQQa2YrhsQymuiYIAiw/pdHWo3NTch1VUTdbgx72ibppsZm6bTfD7UnGxkh5imE3pPjwKnKVOmsHXr1vj3CxcuZOXKlbz00ku0tLTw3nvv8fLLLzN58uRe66ggCAOfnJqCpKoY4QPTbvEE8R07MHQdl11BliFqciAHWskzNZPklIlEobAsnHA+u1WipDqCpovpupOZv1Wnoi5CkkuhvDZKdYOGqsCkERaU+mrCzS24A7XQWI9ksWCZNAlD10GLouaKopdC7+pR4PStb32LjRs3UlxcDMDtt9+O0+nke9/7Hm63m0WLFqFpGv/93//dq50VBGFgU5JTkNxu9OYD03XqsGFINhtGSwvRkhKcNhm7RSIQlcDQUHwNjItP1yUGTh6nQoNXp8EnRr9PZtWNUVqCOg6bFB9tGj/Mgk3VUSuKaJVspBZtAsA8dSqS2Yze3IzscotpOqHX9Shwuvbaa2ltbaWgoACAYcOGsXbtWn74wx9yzjnncMMNN7BmzRpR/FIQhKMimUyYcnPROySIS4oS27uOWBVxRYEUj0owbGBYbCi1FYwtOFCWIGFVnkkiqulU14vpupOVrhsUV4WxmmV0Azbu6VC7qakeo7Ee3eHGtCNW9NI6s0PRy9zc+DY+gtBbjrlyeLsRI0bw5z//ubdOJwjCIKWkZyDpWzB0Halto3Dz+PGEN24gvH07jvMW4XbE2jWrA8XvZdTYECYVvH6dyrooOekHCl867QqlNRHGFFgwqVK/3JPQc/U+jfomnRS3TGFpGH+rjsMqMWaIGaWwklAgSopWDC1+JJcL05gxGJqGZBioOWI1ndD7ejTipCgK3/ve93q7L8fE7/dz8803k5OTg9VqZerUqbz00kvdem5ZWRk333wz8+fPJykpCUmSePbZZw97/Icffsgpp5yC3W4nLS2Nq6++mpqaml66E0EY3JTUVCSHI7EsQdu+ddH9+9FbW3HZZaxmiYBkRQq2Yg14GZ1vBmD7QdN1boeM169T1yRGnU5GVfVRIlEdS4faTVNGWVG0MGpVCa0mJ8n720abps9AUhT05ubYKk0xTSccBz0KnNxuN/ltS4RPFEuWLGHZsmUsXbqUd955h1mzZnH55Zfz4osvHvG5hYWFvPDCC5jNZhYtWtTlsR9//DHnnXcemZmZvPnmmzz66KN8+OGHnHnmmYfdr08QhO6TnU6UtNSEPCclOQUlOxsMg8jOnZhNEh6nTCAMSDJyUy1jD1OWQFUkDCP2BiycXEIRndKqCC67QjCsH9hiZawVtaEavakJyWZD2RkrQxAveunzoeblI9ts/dZ3YeDq0VTd7Nmz2bRpU2/3pcfefvttPvjgA1588UUuv/xyILbSr7i4mFtuuYVLL70URVEO+/x58+bFyyusW7eO5cuXH/bYW265hdGjR/Pqq6+iqrGXb9iwYZx22mn87W9/46abburFOxOEwUnNzSdSVJzQZh4/nkBlJeHt27BMn06yS6GqXotvvzJuyiQkoLQ6SmOzRrLrwL95tyO28e+4oTpWi9j492RR26jhbdHJSVPZuCdIJAppHoX8DBVlcznBqERazS4Ih5HT0lCHDsXQNDBAzcnp7+4LA1SP/oLcc889rFixgmXLlvV2f3rk9ddfx+l0cskllyS0X3PNNVRUVLBmzZouny/L3XsZysvLWbt2LVdeeWU8aAI49dRTGT16NK+//vrRd14QhE6UlBQksxmjwyjugX3rtmMYBk67jNkkETTbkVv8JOnNDMuJ5TZt2hNMOJ/LLtMc0KltEqvrTial1RFkCRRFSqzdFPCj1FXQanbjKTyQFC5JErrPh+x2o4ppOuE46dGI0/vvv8+CBQu49tpreeyxx5g9ezaZmZlIUmLipSRJ3Hnnnb3S0a5s3bqVcePGJQQzQLyO1NatWzn11FN75Todz3vwtUSldEHoHXJyMrLHg97cjGKJTcGZRo4Ekwnd60WrqMCWk4vTJtMcMGOPhFGaG5k2Jpd9FRE27A6xYLrjwPlkCUWC8toI+Zmmw11WOIH4WjSqG6IkuRS8fo3C0tgWK9PHWFHqi9B8zai2VOTC2D6Gllkzgdg0nWXCBKS23xtB6G09Cpzuvvvu+P+vX7+e9evXH/K4vgqc6uvrGT58eKf2lJSU+OO9dZ2O5z34Wl1dJxQKJeRAHbxFjSAIB0iqipqbR2jTRpS0tFibyYR59GjC27YR3rEde24uqR6ZBp+GYTKh1FUxadxw3vi4mcq6KFX1UbJSD/yJ8zgVquqj+Ft1nHYxXXei21sepiVokOqR+HhDAAMYmm0ixSmh7iyixbCQXr4VdB01Px81Kzs2TYeEki2m6YTjp0eB08qVK3u7H3GrVq1i4cKF3Tp2w4YNTJ06FaDTaFdHXT3WE4c7X1fXue+++7jnnnt6tR+CMJAp6emA1LkswbZthLdvx37W2TjtCqoSJSI7UBtrcchhxhSY2b4/zMbdQb55yoGtNhw2iQafQU1jFKfd3E93JXRHY7NGcWWEFLeCJHWYphtjRfY1ojTWErS6ce1p32KlbbTJ60VO8ohpOuG46lHgNH/+/N7uR9yYMWN48sknu3XskCFDAEhNTT3kaE9DQwNw6BGinkhNTQUOPYLV0NDQ5XVuu+02fvnLX8a/9/l8J9zKREE4kSipqchOJ4bfj+R2A2AaPwH4B5G9ezGCQRw2K3arREvITnJLNbKvkWmjk9m+P8yG3UHOneuIf6CRJAmzSaKsNsKwHFOvf6ASes/esjCtQZ20JLVt9FBDkWHySAtK+X4iLSFsFjNS8V6QJCwzYoGT4WvGPHkyklkExsLx02sFMHtLdnY2119//VE9Z9KkSSxfvpxoNJqQ57RlyxYAJk6c2Ct9az/Pli1bOpUt2LJlS5fXsVgsWMScuyB0m2y3o2SkEy0tRW4LnJT0dOS0NPS6OsJ79mCZNIkUj0JRpQ6GhuxtZNzQLMwmicZmneKqKEOzD+Q0uR0ytY0aTX49YdWdcOKoa4pSXBUh1RP7W95eu2ncUAt2VUOtKKJZsZNeshGI5b4pyckYkQiGIqFmZfVX14VBoscT/dFolIcffpjZs2fjdrsTApaNGzfyox/9iN27d/dKJ49k8eLF+P1+/vnPfya0L1u2jJycHObMmdMr18nNzWX27Nk8//zzaNqB1Tlffvklu3btYsmSJb1yHUEQYtScHIzQgYKWkiRhHn9gdR2A2y4jAZrJhlJbjlmFScNjH1I27k5cXWe3ygRDBrWNoqbTicgwDArLwoQjBg6bjK4b8Z/h9LFWlMZaZF8jQYsbx+7YarqOtZtkT1LbFK8gHD89GnEKBAKcc845rF69mrS0NNxuNy0dqvwOGzaMZ555hpSUlD7Z6Pe8887j7LPP5qabbsLn8zFy5EiWL1/Ou+++y/PPP59Qw+m6665j2bJl7N27N77XHsCrr74KwL59+4BYPSenM5YfcfHFF8ePu//++zn77LO55JJL+NGPfkRNTQ2//e1vmThxItdcc81xv1dBGEyU1DQkqxU9GES2WoFYWYLgJ5/EAyenXcZmkQhgx+H3IrX6mTrawte7gmzaE+TC050oyoFpOZtVorQ6wog8M4osputOJDWNGqXVUdKSYn+zC8si+Fp0bBaJsQVmlF0VRMIaTrkBqaocFAXL1GkAGM1+zFOmiGk64bjr0YjT73//ez7//HPuu+8+qqqqOk2teTwe5s+fz3vvvdcrneyO1157jSuvvJK77rqLb37zm6xZs4bly5d32hpG0zQ0TUvYCBTgkksu4ZJLLuE3v/kNAH/+85/jbR0tWLCAt99+m8rKSi688EJ++tOfsnDhQj766CMxFScIvUxOSkJO8mB0qCJuGj0aFAW9rhatpgaTKpHkUmjBghRsRfE1MjLfjNMm0RI02FOWuAVLklOhwafT4BM1nU4kum6wpzSMrhvY2oqUbuiwxYopEkStLsOvukgrio02mSdMQHY4xDSd0Kd6FDi9/PLLLFiwgFtvvRVJkg6ZZDl8+HBKSkqOuYPd5XQ6efTRR6msrCQUCrFp0yYuu+yyTsc9++yzGIbB0KFDE9oNwzjs18HOPvtsvvjiCwKBAPX19SxbtowMsYpDEHqdJMuoeXkYLa3xNtlqxTRiBADhHTuAWDCkGzKGJCM31aHIElNGxUao2t9825lNEpGoTk2DmK47kVTWRymvjcRHm8IRgy3tW6yMsaI0VCM1+wibndh2tq+ma5um83pRkpLFNJ3QJ3oUOJWUlDCrbV75cNxuN16vt0edEgRBaKempWFIUluNnpgDeU7bgFhlcItZIqTaUesqQYsydXQscNq2P5Yz05HTrlBSHSES7fzBSOh7US022iRJYDHH3pa27gsRjhikehQKslTU6lKChoLHWwpNDUgWC5ZJkwDQ/S2oBQVIJlHcVDj+ehQ4uVyu+N5uh7N3717SRfQvCMIxklPTkJ0OdL8/3hYPnHbvxohEsFokXHYZv+xA9vtQvA0MyVRJccuEIwbb9ydu/Ot2yHhbdOq8YrruRFBRGytYmp50IO22vXbTtNEWlBYfSn01fpOb1OKNAJinTo1tyxMOIykKaqaYphP6Ro8Cp7lz5/Kvf/3rsCNKZWVlvP3228ybN++YOicIgiBbrajZ2Ql5TkpOLrLHA+Ewkb17AUhxK0QkE2hRlNoKJEliWtuo04aDVtepioShQ1VdpO9uRDikSNRgT2kIVZEwqbG0j6ZmjT2lsdy0aWOsKPXV0OJHUy1Ydm4EYnvTQVvRy+TkeIV5QTjeehQ43XLLLTQ0NHDWWWexevVqotFYrkBraysfffQR55xzDpFIJKHgoyAIQk8pmVmxBOC2nENJkhI2/YXYdJ2qSoQtTtSqUgiH4tN1u0rCtAT0hHO6HDLltVGCocR2oW+V1USoadDiuU0AK75uxTBgRK6JdLeMWllMQLaSUlsIrX4klwvTmDEA6H4/6pAhSOoJV5ZQGKB6FDjNmzePP//5z2zatIkzzjiD3//+90BsCu+cc86hsLCQv/zlL8yYMaNXOysIwuCkpKUi22wYwQMjR6bx4wAI74gFTg6bjMMq4VddyP4mlMYaMlNUctJVdB02702crnPZZXytOrVNYrquv4QiOrtLwlgsEmpbyYgGn8ba7QEAzp7tQG6qR2mso9nkIaVoIwDW6TOQFCU2TWcyoWaLaTqh7/S4AOYPf/hDNm3axE9+8hNmzZrFiBEjmDZtGj/84Q/ZsGHDUVf/FgRBOBzZ7UFKSkLvMF1nHjMWJAmtogKtsRFJglSPQliXQJJRa8oBmNa2uu7gYpiKLKFIUF4rpuv6S2l1lDqvRqqnw2jTuhY0HUbmmRiea0atr0SPRJAkMO3eDHQoetnUhJySipIqpumEvnNMY5vjxo3j0Ucf7a2+CIIgHFKsLEE+oXVr422y04k6dCjR/fsJ79iB7dRTcdljm8JG7B6UmgqkVj9TRtt4e7Wf/RURGpu1hK1WPE6Fqvoo/lYdp73HnyOFHgiEdHaXhHDa5Hgh0nqvxrqdsQD3nDkOiIRRK4tpVRykVu6AcBg5LQ21rZyM3tKCdcJEJEVsnyP0HfGXQhCEk4KalgayjBE9UH+pPc8p0iHPyW6RaJFtKK3NKA01JDkVhuXGlql32oKlrUhmbZOo6dTXiivDNPg0kl0H3oY+WteCrsPoIWaGZptRGmqQm734TU6S98WKXlpnzkKSJIxQCMlsRskUNfSEvnVMgdPnn3/OjTfeyOzZsxkzZgyzZ8/mxhtv5LPPPuut/gmCIACgpKQgO12HLkuwcweGpqEokJasEoyAbrKgVhaDYcRX123cnZjnJEsSFpNEaU3kkMVuheOjJaCzpzSCx6kgt4021TVFWd8+2jTbAYBaW4FmgBINo+yNFTu1zJoJgNbUhJyaipKS2g93IAxmPQqcDMPgpptuYt68eTz11FOsW7eOvXv3sm7dOp566inmz5/PTTfdJP4QCYLQaySLBTUnG93ni7epBQVIDgdGIEC0uAiAJEf7dF1SbFPY5iYmjbCgyLHq1FX1iaNLbodMbaOG1y9W1/WVfRVhvC06Sc4Oo01rW9ENGFtgZkiWCanVj1JTjl91kV6+BXQdNT8fNSsbAKO1FdOQIWKaTuhzPQqcHnzwQf76178yceJE/vGPf1BVVUU0GqWqqopXXnmFCRMm8MQTT/DQQw/1dn8FQRjE1Mws6LDXpCTLmMe2ra5r3/TXIeO0y/ixIIUCKHWV2K0yYwtim78eXNPJbpUJhQ1qGsV0XV/wtWjsKw+T7JLj23XVNEZZ3/ZzObt9tKmyBLnFR6viwFMYm6azzIyNNunBIJLFKopeCv2iR4HTE088wbBhw/jiiy+46KKL4vu0ZWRkcPHFF7N69WoKCgr461//2qudFQRhcJNTU5HtdoxAIN52YPuVWOCkyJCepBAKGxg2B2plCWhRpo05sLru4NFwq0WitDqCpotR8uNtb1mY5lYDt+PA28+Ha1swDBg/zEx+pgmptRlT8S7CVjfWoA+5ZC9IEpYZbYFTUxNKaipySkp/3YYwiPUocCotLWXJkiXY7fZDPu50OlmyZAmlpaXH1DlBEISOZLcbOSUlYbrONC424hQtKYmXK/A4FFRVImhzo3jrUZrqGDfUgtkk0disU1yVWIIgyanQ4NNp8ImaTsdTg09jf2WENI8SH22qboiyqS33rH20yVS6F7nFR7PJQ1rJxljbyJEoyckAGK0BTAUFSLJY3yT0vR791uXl5REMBrs8JhQKkZeX16NOCYIgHIokSah5eQmFMBWPByU3DwyD8M6dADjtMi67RGvUBLqOUleJSZWYNNwCwIaDksTNJolIVKemQUzXHS+GYbC3LEwwlFj64cO1LRjAxOEWctNNyM1NqGV70d3JhKPg2rMe6FC7KRBAsllRMsRqOqF/9Chwuvbaa3nllVeorq4+5OOVlZW8/PLLogimIAi9TklNi1WNjhwYNYpP17VVEZckSEtSCUd0dIcLtbIEKRxk2phY4LR5TxBNS5yWc9gUSqsjRKNiuu54qGvSKK6KkNZhI9+q+iib9ySONqkle1Ba/QQtbhzNVUjVFaAoWKZNB0D3NqGkpSG3jT4JQl/rUeB02WWXMWfOHKZNm8b999/P559/zp49e/j888/5wx/+wIwZMzjllFP47ne/S0lJScKXIAjCsVCSk5FcrsQq4vE8px0Yemx1nMchYzLJBC0u5BYfSkMNI/LMONtqN+1u20S2nccp09SiU+sV03W9TdcNCsvCRKIGduuBt50PvoqNNk0aYSE7TUVuqsNUvp9oUhrNrTrpxRsBME+YgNyWGmIEQpiGiGk6of/0qHL4iBEjYgXIDIPbb7+90+OGYfDWW2/x1ltvJbRLkhTfEFgQBKEnJLMZNSeX8M4dKG3Jwabhw5EsFoxmH9Hyckz5+ditMm67jLcF7LKMUl2OkjWEKaOsfL45wMbdQcYNtcTPqyoShg5VdRGyU8WGsb2pulGjtDpKevKB0gEVdRG27A0h0TbaZBiYSvYghUOEPRkQ1rDvapumm9k2TdfaimyzoWRm9sdtCALQw8Dp+9//fjyxTxAEoa+pmZmEt2/D0HUkWUZSVUxjxhDevJnI9m2Y8vPbpusU6r1RNIcHpa4CqbWZaaNjgdO2/WHCEQOz6cDfMpdDprw2yvhhOhazGNHoDZpuUFgawjAMrObE0SaAyaMsZKWqKPXVmCqL0ZLTaG7RyfSXQlMDksWCZdIkILaaTs3MQk5K6o9bEQSgh4HTs88+28vdEARB6D6lvSxBayuS0wnEpuvCmzcT3r4d+7nfBGLTbxazTFB14PTWo9TXkJ83nFSPQr1XY9v+ULyqOMS2bKmojVLTqJGfKQKn3lBZF6W8LkpG8oG3m7KaCNv2hZGAs2Y5QNcxleyGaJSIyY4R0kjZvwEDME+dimQ2YxgGRiiIOiRffHAX+pX4yyAIwklHdrlQ0tIS85za963bty/ebrPIJDllWkIGujm2BYtkGEwd3ba6blfi6mBFlpCl2DSScOyimkFhaRhFkhJG9tpHm6aOtpCZoqLUV6FWlaKlpONr0Uh2ANva9qZrW01ntLYi2x0oGWKaTuhfInASBOGkpOYeVJYgLQ11yBDQdYLr1sXbU9wKmgaaMzm2BYuvMT7KtLs0TEsgcasVt1Ohqj7aqV04euW1USrro6QlHchtKq2OsKMojCS1jzZpmIp2ARBRrBgGZJVuwPD7kd1uTKPHAKB7vSgZ6cgeT7/ciyC063HgtHr1ahYvXszw4cOxWCwoitLpS1VFgqUgCMeHnJqCZDJhhA+sjrPOmQtA6Ks18Ta3U8FmkQhgRoqEUOqryUhWyU1X0XXYvDexppPDJuEPiC1YjlUkarCnNITZJGFSO482TR9jJT1ZRa0pR62tIJqcTnOLTpIdpFXvAmA786xY6Yn2abr8AjFNJ/S7HkU2zz//PFdddRWGYTB8+HBmz54tgiRBEPqUkpSM7HajNzejpKYCsb3M/K/9k2hJCdGKCtScHKxmiSSXQnVDFIfNgVpZRKRgFFNHWymv9bNhV5BTJtri55UlCbMqUVYTYWi2SbxR91BpdYSaBo2c9APvDcVVEXYWh5ElOGuWHaIR1OLdGLKCJpvRDY2skvXo9fVILhe2efMAMFpakB1OUfRSOCH0KNr53e9+R3JyMu+88w6z2uafBUEQ+pJkMqHm5hLatjUeOMlOJ+aJEwlv2kTwqzU4v7MYgFRPbPot6vBgbqxGaapj6qgM3v7cT1FlhEafRrL7wHSSxylT06jh9eskuZRDXl84vFBYZ09pGJtFQlU6jDatiY02zRhrJdWjopbvj402pefia9Xx2HTkj99DB+xnn4Nkjm3MrHubUHPzUcQ0nXAC6NFUXUlJCZdddpkImgRB6FdKRiaSbsSLXgJY58wBIPTVV/F2t0OOTddpSmwLltoKPE6F4bkmADbuSUwSt1tlgmGd2iZRDLMnSqqj1DVppHgOBJ1FlWF2l4aRZThzlgMiYUxFuzDMVjRZJRrVyS5ej95Qj+RyYzvjDCBWF9AIR1Dz8/vrdgQhQY8Cp6FDhxIOh498oCAIwnGkpKYgOZ0YLS3xNvOEiUgOB7rXS6Rt7zqTKpHqUQgEDXSHG7WqFCkUYGpbkviG3Z333rRZZEqqwui62ILlaLQGdfaUhHDaZRT5wGjT+22jTTPHWklxK5gqi1Eaa9DaqoQn2Q3kT94HwH7OgdEmw+9HdjhRRdFL4QTRo8Dphz/8IW+99RYNDQ293R9BEIRukx1OlNTEsgSSqmKZOROA4JoDSeLJLgVJgojNHd+CZdIIC4oMVfUalXWJyeAeh0y9V6emUYw6HY2iijCNzRrJ7gNvL/vKwxSWRVBkOHOmAykUQC3ahW61o0kKkYhBdvHX6I0NyB4PttNPjz9X93pRsrKQXa7+uB1B6KRHgdPPf/5zLrroIk477TReeOEFtm7d2mlPOrE3nSAIfUHNy8UIJa6Mi6+u27QRPRAAwO1QsFskAmEwFBW1uhS7VWbs0NjIxsaDRp1ilcMNthcFCUfEqFN3NLdqFJZH8DgV5A5J9e+3raSbPd5GsltBrShC8daje1Lxt+p4rDrKp7HRJluH3CZD1zGiUUximk44gfS4HMHUqVOpqqri+9//PlOmTGHYsGGdvoYPH96bfRUEQehESUmN7VPXIXhShwxBycqCSITQhth+Z4oCackqgZCO7vSg1FUh+X3xmk4b9wTRjcQAKSNFpbJWY195YmAmdBaOGGzeE8LXouNxHnhrKSwLs688Ntq0cKYdqdWPqXg3usONjkw4YpBdsg69sbHTaJPh9yM7xWo64cTSo1V1jz32GDfffDMmk4mFCxeSnZ0tyhEIgtAv5ORkZLcnVpbAEqsILkkS1jlzaXnzDUJr1mA79TQAkhwKsiwRNTuwNNWhNlQzbuhILCaJxmad4soIw3LM8XOrioTHJbOzOExGiokUt1hhdyiabrClMMj+yjC56QdKOBiGEc9tmjPBRpJTwbRnP7KviWjOEPwtOm5LbLTJAOznnItkMh04r9eLefhw5LZtdQThRNCjaOfhhx8mNzeX1atXk5eX19t9EgRB6DZJUVDz8ghv3AhpafF2y+zZtPzfm0QKC9Hq6lDS0nA6ZJx2mdawgdliQ6ksxpQ3gokjLHy9M8jG3aGEwAkgyanEql3vDzFnoi1heb0QC452FYXYVRomM0VNKHZZWBahqDKCqsDCGXYkvw+1tBDdnYSOTCiiMax6LUZTE3JSEtbTTjtwXl0HTUPNze2P2xKEw+rRVF1VVRUXXXSRCJoEQTghKOnpGIChHUjkVpKSMI2JbdfRniSuyJDmUQiGDHSXB7WpDtnXEJ+u21QYRNM65zNlpqiUVEcoqRJ72B2suCrC1n1hkp0yNsuBt5TYaJMfgLkTbXicCqbSQuTWZnSnB3+rjsscRfn0A6DzaJPu88X2JBR70wknmB4FTiNHjqSpqamXuyIIgtAzSkoKssuJ4fcntLcniQe/WoPRlr+U5FRQFYmwbEEKh1FrKxmRZ4qNRAUNdpd2LrViNknYLBI7ikI0t4pVdu2q6qNs3B3EYpZwORKnMXeXhCmuimJSYeF0O7KvEVP5PjR3CgYSobBBTvE6DG/baNOppyY8X29owDR8BLLD0Ze3JAhH1KPA6Re/+AVvvvkmxcXFvd0fQRCEoybb7SjpGej+5oR2y5QpSBYLel0d0b17AXDaZVwOidaggWZ3oFSVoOhRpoyM5UcdqqYTxKqPNzbr7CwKx4OwwayxWWP9rgCRaOy16cgwjPhKulMm2nA5FEwle5CCAQyHC39Ax2GKon7eNtp07jc7jzY5nZiGD+u7GxKEbupRjtOIESOYP38+M2fO5Oc//zlTp07F7XYf8th5bXsNCYIgHE9qTg6RvXsS2iSLBcu06QS//ILgV2swjRyJJMWm6xp9EXRXEmpdFUpjLdPGpPP55gDb9oUIhfW2cgQdziVJZKYo7KsIk52mkpdhYrBqCeqs3xnA69fJy+j8NrKzOExpdWy0acF0B3JjLWpFEVpSKoYBwZDO6PKvMLxe5ORkrKeckvB8raEBy8SJKEnJfXVLgtBtPQqcFixYgCRJGIbBXXfd1eUmmJomhrUFQTj+lNRUJKsNPRBAth3YtNcydw7BL78g9PXXOC++BMlsxu1UMJmihA0ZFQOlppz88dmkehTqvRrb94eZNsba6Ro2i4wi62zfHyLNo2C19Liiy0krHDHYuCtIZb1Gfqba6e9/x5V0p02247RJmPbsQYqEMWwOWlp1nCYN0+oPYyvpDh5t8vuRrTZMw0f05W0JQrf1KHA6UrAkCILQ1+SkJGRPEkZzM3QInEwjRiKnpKA3NBDavBnrzJk4rDJuu4y3RcfqdKNWlxEZMZFpoy18uLaVDbuDhwycANKTFcqqI+wuDTN55KGPGajayw4UtZUd6LilSrvtRWHKa6OYTRLzp9lR6qswVRSjJadhGBAI6YwuW4Ph8yGnpHQabdLr6jCNHRvfuFkQTjQ9CpzuvvvuXu6GIAjCsZFkOVaWYP36Tu3WOXNofecdQmvWYJ05MzZdl6RQ742iu12oNaUoDdVMHZ3Hh2tb2V0apiWg47B1HlFSZIlUj8qe0jBZKSoZKYOjhl3HsgMZB5Ud6HjMB22jTadPtuGwgGn7HjB0DIuNloCOXdEwrf4oNtr0zW8idagBqLe2gtmCaeTIvrotQThqg2+cWRCEAUtNS8OQpISyBADW2XMACO/Yjub1AuB2yFjMMiFNim/BkpGkkJuuouuwufDQSeIQSzCPRg22F4WIRAdHonhxVYQt+0Kdyg50tG1fmIq6KBaTxLxpdpTaCtSaUqLJ6WDENgDO3f8lRnPbaFPbqsd2Wl0tpqEFKGnpfXFLgtAjxxQ4bdiwgVtvvZVvfetbnHXWWfH24uJiXnnlFbEJsCAIfUpJS0NO8qC3BUfx9owM1OHDwTAIrf0KALtVJskp0xLU0V1JKPXVyC0HtmDZsLvrbVYyU1XKa6Psq+hcvmCgaS87YDXLncoOtNMNg/e/ipWDOH2qDbtJx1S8GwMJzBZaQjoOOYr5y48AsH/zvMTRpkAASVExjRgpUkGEE1qPA6dbb72VmTNn8qc//Ym33nqLlStXxh8zDIMrrriC5557rlc6KQiC0B2SxYJp6FB0X3Onx+I1ndYcqOmU4lbQNNAtdqRAK0p9NVNGWZCAosoIDb7DL25RFQm3Q2ZnUYjG5oG7CKarsgMdfboxQFW9htUsccYUO2pNOWptOVpKRmy0KWCQs/9LjOZm5NRUrHMPGm2qrUXNz0fJFAUvhRNbjwKnZ555hj/96U9ccMEFbN68mdtuuy3h8aFDhzJ79mz+7//+r1c6KQiC0F1qTg6SSU3Y9BfAMn06qCpaRQXRsjIA3E4Fq0UiGDYwLFbUymI8dokRebFVXpv2HH66DiDZpdASNNixP4SmD7wpu45lB7JSDx807SoO8fbq2GjTN09xYFc1TEW7MFQTqCZaQzo2OYyl42iTcuB8RjCIJMmYR44So03CCa9HgdNf/vIXxo0bxz//+U8mTpyI2WzudMzYsWPZs2fPIZ4tCIJw/Chp6ShpaWiNjQntst2OZfJkAEJtW7BYzRLJLoXWkIHmSkJprENuqmdq+3Tdrq4DJ4CsFJXiqgil1QNrO5aOZQdy0juXHWhX2xTlxfd9GAbMGm/llIk21MoSlPoqtLbcppaAQe6+LzH8fuS0NKxz5iScI1pXh5qXi5Kd3Re3JgjHpEeB0/bt2zn77LNR1cOvJsnMzKSmpqbHHRMEQegJSZYxDRuO0draqcK3pX26bu1X8QTyVI+CYYBusoAWQa2vZNIIC4oMVQ0au0u6zmEymySsFont+0O0BPTjc1N9LLHsgHrIsgMAwbDOsn97CYQMCrJMLJ7vQo6EMBXvwrDYQFEJhHSsUhjzlysAcBw82hQOg6FjGjUaSRbrlYQTX49+S1VVJRzu+o9JRUUFTqezR50SBEE4FkpWFrKz89515nHjkFxuDL+f8PZtALjtMlazRDCko9tdqJXF2OQocyfGakG9tspHONL1NFyqR6HRp7OzKHTSb8fSnbIDEEsGX/6+j5pGDY9D5vvnuVEVCbWyBLWxFi0pVofJHzDI3fsFtPhR0tOxzJ6dcB6ttgY1Oxc1J+e435sg9IYeBU6TJk1i5cqV6PqhP121trby4YcfMmPGjGPqnCAIQk8oHg9qbi7aQZuRS4qCddYsIJYkDmAySaQlKbQGDXSnG9nvQ2ms5dy5DjxOmQafzkdrW7q8nixJpCcr7C2PUFkXPS731FeKKo9cdgDggzUt7CgKoyrw/UUeXA4FKdiKqWgXmt0JskIwZGCVwli+ii0esp930GhTJIIR1TGPGpXQLggnsh4FTtdeey27du3ipptu6jTy5PP5uPrqq6mqquKGG27olU4KgiAcLTV/CJKud67p1JZfE96yBb0lFhAlOWNv2pqkgmGg1JZjNct8Z54LgI83th4xILJbZSQJtu2P7XV3Mqqsj7JpT9dlByBW4+qjda0AXPwNN/mZJtA1zIVbkb0N6J4UAJpbNXIKV8dGmzIysMyclXAerbYWNSsLNTf3+N2UIPSybgdOiqLwu9/9DogFTpdffjlPPvkkaWlpPP300wDMnj2b3NxcXn31Va666iouvvji49NrQRCEI1CzspCSkjrVdFLz8lBy8yAaJfT11wC4HQp2q0QgqKM73ajV5UiBFiYMtzBxuAVdh3+u9KEfYRouI0WhpiHKntKTr7ZTY7PGhm6UHaiojfDyhz4A5k2zM71taxpT0S5MRTvR0rJAkgmFDcxGGOtXsdymTivpolEIhzGPGZ2wV50gnOi6HTgZhpEwd//CCy/w17/+lWHDhlFeXo5hGKxbt44hQ4bw+OOP87e//e24dPhw/H4/N998Mzk5OVitVqZOncpLL73UreeWlZVx8803M3/+fJKSkpAkiWeffbbTcT6fj3vvvZcFCxaQlZWF0+lk0qRJ3H///QSDR159IwhC35EsFkxDCtC9vk6PWefGRp2CX8Wm61QV0pJUAmED3eFCbm1GaagG4NvznFhMEiXVUb7cGujymooskeJW2FUSprbp5Jmy627ZAX9AZ9nbXiJRGJ1vZtEpDgDUqhIsezaju5IwLLFAyteqk1e4Glpb20abZiacS6urQ87IRM3NO343JgjHwTEtYbjhhhvYtGkTfr+fsrIyfD4f27Zt4wc/+EFv9a/blixZwrJly1i6dCnvvPMOs2bN4vLLL+fFF1884nMLCwt54YUXMJvNLFq06LDHlZSU8MgjjzB9+nSeeOIJ/u///o+LL76Yu+++mwsuuOCkTwoVhIFGzc09ZE0n68xZIMtE9+8nWh0LkJKcCrIEmi5jqCbUqlIwDDxOhfPaAoR3Vrfg9Xdd7NLlUIhEDbbvDxE9CbZj6W7ZAU0zeP4dL43NOqkehSvOdSPLEnJTPeYd6zEkGd3pASAUMbDoIaxr23ObFiWONmkaRiCAecwYpEOUsxGEE1mv7E5ps9mwddiNvK+9/fbbfPDBB7z44otcfvnlACxcuJDi4mJuueUWLr30UpQuEg/nzZtHbW0tAOvWrWP58uWHPG7YsGEUFRXhcDjibd/4xjdwOBzccsstfP7555x++um9eGeCIBwLJS0NOS0NrakJtUNFatntxjx+POGtWwl9tQb1wm/hcsg4bTKtIR21fQuW5iZ0dzJzJ9pYvytISXWUNz/x8/1Fni6vm5miUl4TZX9lhFH5J2ZgYBhGrNxCcYiymgi56abDlh0A+NdnfvZVRLCYJK4+3xPL6Qq2YtnxNXKrn2jmgZGj5hadoXs+h0ArSmZm59Gm+nqU9HRM+fnH7f4E4Xg5qhGnE7Wi6+uvv47T6eSSSy5JaL/mmmuoqKhgTdvqmcORu1k7xOFwJARN7Wa3La8tLS3tZo8FQegLkqJgHj4Co6VzTacDW7B8haHrKDKkJcVWghlWO1IogNIQq0UnyxIXLXQjy7B1X4ht+7rex86kSjjtMjuKgkccoeoPDT6NNdsCfLqhleqGKDnppsOWHQBYsy3A6i0BJODyc9xkpqgQjWDeuQGlrpJoRg60vT+EIwamaBDbulUA2BctSqjPZOg6Ros/NtpksRzP2xSE4+KoRpwefvhhnnnmmW4fL0kSe/fuPepOHa2tW7cybty4TgU5J7dVCd66dSunnnrqcbv+ihWx5McJEyYct2sIgtAzSmYmstOB0dKC1KG2nHnSJCSbDb2xgciePZjHjMHjVFCVKJGogWK1o1YUERkyEmSF7DSV+VPtrFzfyhufNDMiz4TVfPgPXckumdLqCDuKQsweb0PuYjSnr/hbdfaWh9lbHiYYNkhPUrosOQCwvyLMGx/H9v47Z66D8cMsYBiY927DXFpIJC0b5AMj+r4WnYLCttGmrCws0xPL0ugNDcgpqaj5Q3r/BgWhDxxV4NTU1ETTQXVRTgT19fUMHz68U3tKSkr88eNl8+bNPPDAAyxevDgeqB1KKBQi1CHPwufrnLAqCELvU5KSULJziBTtR+4QOEkmE5YZMwh+9hnBNWswjxmDyy7jtEu0Bg1MriTUhhrU6nKi2bE3+bNmO9hUGKTBp/Pely18u61cwaFIkkRGikpRZYTsNBMFWf23ciwU1imqjLC7JIyvVSfVrZCRfOSR9qZmjefe8aLpMHmkhW/MsAOglu/HvG8b0aQ0MB8YNQpHDEyRIPb20abzOo826c0+rHNPRe7H9A5BOBZHNVV39913o+v6UX0drVWrViFJUre+Nm7cGH9eV9OIx2uKsaioiAsuuID8/HyeeuqpLo+977778Hg88a98MbcvCH3GNGQIkqYdtqZTaMOGto1mIT1JiVUKN5kxVBPm3ZuQ/LEPOiZVYskCNwCrNwcoOcL+dFazjNkksWN/kJZg39d2imoGRZVhVm1o5eudsZW/QzJVnPYj/+kPRwyWve3FHzDITlP57pluJElCqa/GsnM9utmGYT8QiBoGeP06OYWfQjCAkpUd21i5A72xETkpBVNBQe/eqCD0oV5JDu9NY8aM4cknn+zWsUOGxD4FpqamHnJUqaGhATgw8tSbiouLWbhwIaqq8tFHHx3xGrfddhu//OUv49/7fD4RPAlCH1GyspA8Seg+L0rygX+r6rDhKBkZaDU1hDZtxDpnLm6ngskUJRwxMKdkoFaVYtm9keDkU0A1MXqImeljLKzfFeKfK5v52SXJKMrhP5ylJSmUVkfZXRxi6mhrn+SKdkz8rqiLYjFL5GYcfs+5Qz3/1ZU+ymujOKwSVy3yYDZJSC3NmLd/DdEIenriFimNPo0kUwj7158Ah85t0r0+rHPmIB8iV1QQThYnXOCUnZ3N9ddff1TPmTRpEsuXLycajSbkOW3ZsgWAiRMn9mofi4uLWbBgAYZhsGrVKvLyjlyHxGKxYBGJkILQL2SrFdPQoYQ3bYIOgZMkSVhmz6H1rX8RXLMG65y5OKwybruMt0XH7JKJpmWhVhRhdiUTHjUJgAtOd7GzKExlXZRPN7WyYPrhAwFZkkjzKOwpjWAAKW4Ft0PBZZe7TMjuqQafxu6SECVVUcAgK/Xw+80dzscbWtm4O4Qsw3+c5yHFrUA4hGXnehRvPdGsxL95/lYdVZXI2/0ZejCAkpODZdq0hGN0rxfZ48Y0dOgx3qEg9K8BsRX14sWL8fv9/POf/0xoX7ZsGTk5OcxpG47vDSUlJSxYsABN01ixYgUFYshZEE4Kam4uqArGQdtEWdtWxUZ270ZrbECSYqNE0agOBmAyo7mTMe3bjlJbAYDTJnPB6bFpqg++aqHB1/XKOYdNxmGT2F0cZvXmAB+tbeH9NX6+2NLKntIwVfVRWoP6MdWC87fqbNoTZNX6FvZVREh2y0dcLXcoO4pCvLM6thXNt85wMiLXDLqOec8m1PL9RNNzQDrw1hGOGIQiBkPdYYzPY3WbHAfnNhkGelMTplGjEvLMBOFkdMKNOPXEeeedx9lnn81NN92Ez+dj5MiRLF++nHfffZfnn38+oYbTddddx7Jly9i7d29C0PPqq68CsG/fPiBWz8nZ9g+8feuYmpoaFi5cSGVlJU8//TQ1NTXU1NTEz5GXl9et0SdBEPpevKZTY2NCTSclNRXTqFFE9uwhuOYrHN/8Jm6HjMUkxwo5miUMhxtaWzDv3EjQ4cawO5kx1srXO4PsLY/w2qpmrrvQ0+U0nMep4GnbEy8cMQiEdMraaj3JEljNEm6HTHqySpJTwe2QcdrlI06v9TTx+1BqGqMsf9+HAcweb+WUibEEblPxLsz7d6KlZsXKrLfRdPD6NfLSFaxvvUAkGETJzcU8dWrCeXWvF9nlwjR0WI/6JQgnkm4HTj1J9O5Lr732GnfccQd33XUXDQ0NjB07luXLl3PZZZclHKdpGpqmdfpkd3ANqD//+c/8+c9/Bogfu3379nhg9R//8R+d+rB06VLuvvvu3rolQRB6kaQomIcNJ7B6NYZhJAQ51jlziezZQ+irNdjPPRe7Vcbjkmnw6ljMseO0tExMlSWYd28iNGkOkqKyZIGLh19qYHdJmI17Qkwbbe1WX8wmCbNJwdM2+KLpBsGQgdevU9UQAgMsZgm7VSLNo5LiUXDb5VhA11YCIaoZlNVE2FUSpr5Jw2WXGZJ5+MrfRxII6Sz7t5dg2GBotonvzHfFksGryzDv2YLu9GBYO6yEM2J5TSkelYytKwlu3QqqiuvK7yeMNkGsBIFl6jQUT9eFQwXhZCAZYp+QfuHz+fB4PHi9Xtxud393RxAGBa2pidb33kGyOxKmjPRgkPrbfgvhMEm/vgXTsGHUNETZURQmLUkhHouEQ6j1VYQmzCIybBwAH61t4b01LThtEr/+Xip267FnQBhGbPorEIyNTEU1UBSwWWSSnDJpSQq1jVo88TvVo3Q78ftQdN3g2X972VkcxuOU+dl3U3DZZWRfI9b1nyKFg2ipmQnP8fl1FAVGR4sIP/H/wDBwfu972E49LfHcPh9GMIj9nHNRkpN73EdBOJ6O5j15QOQ4CYIgdEesplMuemNjQrtstWKZMhU4sPGv26lgs0gEQh1G280WdKcHc+FWlPrYHnfzp9vJTFHwBwz+vdrfK/2UJAmrWSbZrZCTbmJIlonMFBWTArVNGhv3hKhpjJKVqpKR3P3Vcofz3pct7CwOoypw1SIPLruMFAxg3vE1st+LlpKRcHwwZBDVYKijlcgLz4BhYD3llE5BE4DW0IA6dJgImoQBQwROgiAMKqYhQzC06OFrOq1bhxGJYDVLZKWq+AM6HTMVdFdSbLuRXRuQgq2oisRFC2OFMNduD7KvPDH5vLeoioTLoZCZojIk00R22tEnfh/Kht1BVq5vBeCSb7jJyzDF70+tKSeakQsdpv80DXytOvnpEuqrz2D4/ah5eTi/e2mnc+t+P7LVhnnEiGPupyCcKETgJAjCoKJkZSG7YzWdOjKNGYOclITR2kp461YAstNUkl0KXn9ijqeWlo1SX415zxbQdYZmm5kzIZbf9M+VzUS1kyMDYvv+EK+uiBX3XDDdzrQx1th2Kvt3YCotJJqWHZsjbGMY0OCLkpWikLz6LaL79iHZbLivvwHJ3HkzY72uDrWgACUtrc/uSRCONxE4CYIwqLTXdDK8zQntkixjaStNEGzbGNykSuRnmDAMCEU6BEOyjJaahalkN6ay2H6ci0514rLL1DZprFjX0jc300MtAZ2XPvDy7L+9RKIwZoiZb86N1aJSK/ZjLtyG5k5J2E4FoKlZx+1QyK3eQmhVbI9O1/evQklP73QNvbUVzBZMo0Ye/xsShD4kAidBEAYdNTcXlEPUdGqbrgtv24reHAuskt0K2akKPr9Ox6U0hsWKbnNi2rMZubEWm0Xm2/NiCecrv26lpjHaNzdzlLYUBnnwxXrW7wohSTBvqo3vL/IgyxJKQw3mnRvRzWYMR+I+fC1BHUmGArWB0MsvAGA75xwsh9mjU6urxVQwBCWtc1AlCCczETgJgjDoKOnpyOmxmk4dqVnZqAUFoOsE160FYuk9uRkmHDaJ5tbEKTvdk4IcCsb2swsFmDTCwtgCM5oem7LTT6BFy82tOs+94+W5d334AwaZKQo/viiZC053YVIlpNZmzDvWI4eD6EmJU2uRaGyFX0GyBi8+jREKYRo9GscFFx7yWnoggKSomEaO6pMtZgShL4nASRCEQUdSFMxDh2G0tHaq6WadMxeAUNt0HYDVIpGXYSIcia0m6yialo1aU46pcCuSYbB4vguTCvsrIqzdHjzu93IkhmGwfleQB1+oZ8ve2DYqZ8608/NLUxiSZYodFAlj2bEetaE6ltfUga7HpuiyUxWc77+CVlWJ7PHgvuZapA75Tx1pdbWo+fkoGRmHfFwQTmYicBIEYVBSsrOQHXaMlsR8JMuMGaAoREtLiVZUxNvTk1XSkhQamw+KnBQFLSUDc/Fu1Moikt0K586NTdm9vdrfaZSqLzX5NZ55y8tLH/hoDRnkpKv87JJkzp3rRG3fmFjXMRduQa0oIpKRCwcVr2xs1kh2y2QVfkH463Ugy7ivvQ75MLVujGAQCQnzyFGdCmEKwkAgfqsFQRiUZE8SSnY2elNTYrvTibltY/Dgmi/j7YoMQzJNWEwSrcHEYMiw2tHNFsy7NiH7Gjltso3cdJVAyOBfnyYmofcFwzBYsy3AQy82sLM4jCLDN+c6+OnFyeSkmw4cGI1g3rsN874dsVpNqinhPM2tOhaTREG4nOAbsb1AHYsXYxp5+IRvra4ONS8PJTv7sMcIwslMBE6CIAxKkiRhKijAiEYxDtpSKl7Tae3ahHpPTrtMbppKy0G1nQD0pDTkVj/mnRtQtAgXLXQhSbBxT4hdxaHjfj/tGnwaT77ZxD9XNhMMGwzJVLn5shS+MdOBohzIN5Jam7FuXYN51wY0VxKG1Z5wnlDYIBwxGOoOEn3hadA0zNOmYVv4jcNe2wiHMXQd06jRYrRJGLDEb7YgCIOWkpmF7PagexNrOpknTERyOtG9Xlre+lfCY1lpKkmHqO2EJBFNz0GtLsW8bxt56SqnT4nt7fbaqmbCkeObKK4bBp9vauXBF+spLItgUuGC05386KJkMlMStyVVaiuwrv8UU+leomnZnVbQaRr4WjTy0hTMbzyH3tSEkpGB63v/0WWyd7SqElNeHmpOznG5R0E4EYjASRCEQUu22TAVDME4KHCSVBXXpbENwgPvv09oy5b4Y4et7QSgqmhJaZj37UStKuWc2Q6SXDKNzToffHX8ajvVNkb539eaePNTP5EoDM8x8YvLUpg31Y7ccTsWLYpp33asGz5D9nuJZA8BU2LhyvYil+lJKmnrPyCycyeYzbhvuBHZZuNwtLo6ZLsTy5Sph00aF4SBQD3yIYIgCAOXmptHePt2jHA4ofq1Zfp0bIULCHy8iua/L0P97W0oqanAgdpOZbXRxE2AAcPuxAi2Yt69CX2Gh8XzXTzzlpdPNrSyfX+ItCSFNI8S+2+SSppHweOSkXuwbF/TDT7d2Mr7a1qIamA2SZx/mpM5E6ydzicFWjDv3oSptBDd6YltHXMITX4dp00mz7ub4HtvA+C6/IouR5H0QAC9pRXbaaeJKuHCgCcCJ0EQBjUlPR05NQ2tqQn1oOXzjiVLiBQVES0uwvf00yT98pdIqhqr7ZRpotGv0dyq43YkDt5ryemoVaWYd21k3JRTOWWijS+2Bqht0qhtOmhVHqAqkOpRSPW0B1VqPMByOw8dVFXWRfnHCh9lNbFCm6OHmLlooYtkV+fRHqW+OpZ71V5u4KCK4O3ak94LbM2En/k7ANZ587C2VVQ/FEPT0CorMY8fj0nsSScMAiJwEgRhUJNUFfPw4QRWr4aMzo+5r7uOxj/cR7S4iJbXX8N5yXcBsJol8jNN7CwKEbXKqB3jFUkimp6NqaII3Z3C4gWTWDDDTl2TRl1TlDqvRl2TRr039hXVoLpBo7qhc1BlUiHVfSCYSvUoNDVrrFrfiqaDzSJx4elOZoy1ds4/0jVMpXsx79mMFAkTzRrSqdxAu0jUoCVgMCJLQnnub0RbWlALhuJcclGXr1+0shIlOzs2RScSwoVBQAROgiAMeu01nfSWFmSHI/Gx1FRcV12F7/HHCaxahWnESCzTpwOx2k4N3tgoUlrSQSM9qomoJxXTvu1onhSSM3JJdimMyk/MKdJ1gya/HguomrR4UFXXpNHQrBGJQlWDRtUhgqoJw8wsXuDC7eg8yiQFA5j3bMZUvAvd4UZLPvzWJ7oRK3KZlarg/vg1QiUlSA4H7uuvRzKZDvs8rbER2WTCOn0Gst1+2OMEYSARgZMgCIOe7ElCycwiWlbaKXACsEychO2ccwi8/z7NLzyPkpuLmpmJLEF+pglvi05rUMduTRxxMRwuCPgx79pI0OnGsLs6nVuWJVLcCiluhdFDEh/TdIOm5gOBVHtQFYoYnDrJxpRRlkOucpMba7Hs3IBSW4mWloVhsXZ5/40+DY9TJqdsA8HPPgVJwn31NSgpKYd9jhEKoXubsM6Zi5qV1eX5BWEgEYGTIAiDniRJmIYWECnaj6Hrh5xyclxwIdF9+4gUFuJ7+imSf30Lktkcq+2UrrKvPIzVLHeaCdNSMzFVlmDZvYngxDmdikx2RZElUj0qqR6VMQXdeIKuYyrfh2n3JuRQkGh2Pshdr3Dz+XVMqkSBVEvwH8sBsJ+3CPP48Yd9jqHrRMsrMI8ehXn0mG7fjyAMBGJCWhAEgfaaTm50n++Qj0uKguuaa5FcLrTycvz/eCX+WFZqrLZTk7/zdBqSTCQtG7V0L/bV72Le9hVq2T5kbwNo0V7rvxQOYt6xDsuWNYBENDOvy6BJ16HeqyHLMCJVw3jxaYhEMI0bj/2887q8llZVhZKehmXqNCRVfP4WBhcROAmCIACy3R6rJN7kPewxSlIS7quvAUkiuHo1wS9jW7KYVIkhmSYkpM61nQDMFqIZubHq28W7sW78DPuX72P//J1YIFV+bIGU3FSPZcNnmPdtR/Okoieldnl8OGJQ743iccqMLTBjfutFtJoa5OQU3Fdf3WWSd3tgaZk2HdnVeepREAY68VFBEAShjZqTS2j7tk41nToyjx2L/fzzaX3rLZpfWo46ZAhqTg5JLoWsVIWyms61nWInN6G7k9HdybHvwyHkYCvm4t2wfxeYTOg2B9HUTPSkNHRnErrTDUoXf6YNA7Vif2yPvEAL0cwhcITik/5WnVDEIC/dxJAsE5GPP6Jl40ZQVdw3XI/sdB7+cpEIWn0dlhkzMeXnd3kdQRioROAkCILQRsnIQDlMTaeO7Od+k8jevUR27MD31JMk3fobZKuV3AwTjc2Hru3UidmCbrYkBlKBFszFu5H27cQwm9HtTqIpmehJqZ0DqXAotkFv0Q50szU2NddFEU1dh8ZmDbNJYlS+mcwUlcj2bbS8+QYAzosuxlQw9LDPNwwDrbwc09BhWMYdPv9JEAY6ETgJgiC0kVQV07BhBL/4slNNp4TjZBn3VVfT+If70Kqr8b/4Iq5rrsFqjk3Z7SwOE9VIrO10JO2BlKdtJVs8kNqFtE9PDKTcKahVJahVJWjJ6Ri2zisBOwpHDLx+nSSXzLAcM26HTGjDBnzP/A10Hcus2VjPOKPLc2i1tUhuD5Zp0w87GicIg4HIcRL63Zdffskll1xCdnY2ZrOZrKwsLr74Yr744otun+Puu+/ucvPRrqxatQpJkli1alWPnt9dCxYsYMGCBcf1GsKxU7NzkO2xmk5dkV0u3NddB7JM6Ot1BD/9FIC0ZJWM5FiRymPSFkRFM/OJ5BQQdadAJBLLkdq0GrW2gmhG3hGDJn+rjq9FJzddZdxQC26HTPDLL/E9/RRoGpZp03H9R9eb9+otLRihENZp01CSk4/tvgThJCcCJ6FfPfbYY5x22mmUlZXxwAMP8OGHH/KnP/2J8vJyTj/9dP7f//t/3TrP9ddff1SBVkfTp0/niy++YHpbUUNhcJOTklCystCbGo94rGn4CBzf/g4A/n++SqS4GFmCvAwTZpMU38KkV8QDqTyi2UNiU3NdrGjTjdiqOd2A0flmRuSZMZskAqtW0vzc38EwsJ5yCq5rr+1yZZyhaWjVNVjGjUMdNqz37kcQTlKSYRiHWAIiHG8+nw+Px4PX68Xtdvd3d/rF559/zrx581i0aBGvv/46aoc/3tFolMWLF/P222/zySefcNpppx3yHK2trdhPkorF7aNNx3tkSzh2kX37aP14FeqQIUfcRsQwDHxP/JXw5s3Iqakk//Y2ZLudspoIe8sipHqUw+1yctxEogaNzTrJLpmhOWY8DhnDMGh9711a//UvAGwLv4FjyZIj3l+ktBQ1Mwvb/PnI1q4LaQrCyepo3pPFiJPQb+677z4kSeLxxx9PCJoAVFXlL3/5C5Ik8Yc//AE4MB23fv16Lr74YpKTkxnRtqnooabqQqEQv/rVr8jKysJutzNv3jy+/vprhg4dytVXXx0/7lBTdVdffTVOp5PCwkIWLVqE0+kkPz+fX/3qV4RCoYTr3HPPPcyZM4eUlBTcbjfTp0/n6aefRnwmOXkpWV3XdOpIkiRcV34fOTUVvb6e5uf+jmEYZKWYSHbLeA9V2+k48gd0mpq1+NRce9DU8sbr8aDJvmgRjosuOmLQpNXXI1utWKdPF0GTILQRgZPQLzRNY+XKlcycOZO8vLxDHpOfn8+MGTNYsWIFmnbgzWfJkiWMHDmSf/zjH/zv//7vYa9xzTXX8Mgjj3DNNdfw5ptvctFFF7F48WKampq61cdIJMK3vvUtzjzzTN58802uvfZaHn74Ye6///6E44qKivjBD37AK6+8wmuvvcaSJUv46U9/yu9+97tuXUc48ch2O6YhQ7qs6XTw8e7rbwBVJbx5M4GPPkJVIT/TDEiEwsc/iDYMaPBq6DqMGmKJT80Zuo7/peUEPvwQAMdFF+E4/4Ij5gTqgQB6sx/L1Kko6Yff504QBhuxqu4kYxgGwT74I3w0rGbpqBOz6+rqaG1tZdgRciaGDRvGV199RX19fbztqquu4p577unyedu3b2f58uX85je/4b777gPg7LPPJjMzk8svv7xbfQyHw9xzzz1ccsklAJx55pmsW7eOF198kbvuuit+3DPPPBP/f13XWbBgAYZh8Oijj3LnnXf2OGld6F9qbh6hHdu7rOnUkWnIEJwXXYz/5ZdoefMNTMOGkTR8BFlpCmXVUdJMh6jt1Evap+aSnDLDss14XLHPxIam0fz3ZYTWrQNJwnnFFdhOPfS0d0eGrqNVVmIeNx7TiJHHp9OCcJISgdNJJhg2OPMnJf3djQQf/b8h2CzH5x2hfbqrY/Bx0UUXHfF5H3/8MQDf/e53E9ovvvhirrzyym5dW5IkLrzwwoS2yZMns2LFioS2FStW8Pvf/561a9fiO2hqp6amhszMzG5dTzixKBkZqNm5aGVlKAVDuhUAW884g8jeQkLr1uH729Mk//Y2ctOdNPo0mlt03M7eH+RvCei0hgxy0lQKskxYzLF+GuEwvqefIrx1K8gyrquvwTpjRrfOqVVWomRlY5kyBekIBTUFYbARU3VCv0hLS8Nut7N///4ujysqKsJut5PSYZf27OzsI56/fYTq4KBFVVVSU7vejqKd3W7HelBeh8ViIRgMxr//6quvOOeccwB48skn+fzzz1m7di133HEHAIFAoFvXEk48kqpinTEDyeNBq6np3nMkCdflV6BkZqI3NeFb9iwW1WBIpomIZuBv1WkN6oTCBuGIQVQDTY9Nsx0tw4BGn0ZUg5F5Jkbmm+NBkx4M4n38L7GgyWTC/YMfdj9oampCUlSs06YhO7oudSAIg5EYcTrJWM0SH/2/If3djQRW89GPNimKwsKFC3n33XcpKys7ZJ5TWVkZX3/9Needdx5Kh0+93fnk3x4cVVdXk5ubG2+PRqMJ037H6qWXXsJkMvHWW28lBFlvvPFGr11D6D9KSgrW6dMJfPYpus+H3I0VsJLVivv6G2h84H4iO3bQ+u67pJ23CF+LjtcfKw8QjhoYOmiGga4b6B0CJ4nYSKuEhCSDLLX/t+1Ljh3jDxi426bmklwHPgPrLS14//xnosVFsb788IeYR43u1v0a4TB6YyPW2XNQc3KO8tUShMFBBE4nGUmSjtu0WF+77bbbeOedd/jRj37E66+/nhAcaZrGTTfdhGEY3HbbbUd97nnz5gHw8ssvJ9RnevXVV4lGe3FHeklCVdWEvgcCAZ577rleu4bQv0xDh6J5vYTWf41ksSBZLEd8jpqTg+uyy2l+7u+0vv1vTMOHM3LsWAwjtvWJrhtoOmi6ga5z0P8b8ccjUYOobhCNQlSLjVC1P5aVqlCQbU744KJ7vTT9v8fQKiqQHA48P/5xl9uodGToOtGKCkwjRmAeM6anL5cgDHgicBL6zWmnncYjjzzCzTffzOmnn85PfvIThgwZQklJCX/+859Zs2YNjzzyCKeeeupRn3vChAlcfvnlPPjggyiKwje+8Q22bdvGgw8+iMfjQe6lwjrnn38+Dz30EFdccQU33ngj9fX1/OlPf8LSjTdX4eRhGT8ew+clvGc3asHQIy7jB7DOnUtkbyHB1avxPfsMyb+9DSUpCUUBRZEwAbGxo6OjtQVeqiIlJJtr9fV4H/sftNpaZI8Hz09+elSjRlpNNXJKCpap05BMpqPulyAMFiJwEvrVT3/6U2bNmsWDDz7Ir371K+rr60lJSeH000/ns88+45RTTunxuZ955hmys7N5+umnefjhh5k6dSqvvPIK3/zmN0lKSuqV/n/jG9/gb3/7G/fffz8XXnghubm53HDDDWRkZHDdddf1yjWE/ieZTFimT0fzNRMtL8eUn9+t5zkv+S6R4mK08nJ8Tz+N8+KLUPPyjynhWpFBkRMDrmh1Nd7/eRS9qQk5NZWkn/7sqEoI6M3NoOlYp05D8Xh63DdBGAxE5fB+IiqH94/Vq1dz2mmn8cILL3DFFVf0d3eEk0y0pprAqlUgSShpad18Tg1N9/8Bo31RgdmCacRwTCNGYho5EtPQocc0whMtLaXp/z2G4fejZGXh+enPUI7ig4ERiRAtK8UydTqWadNE+QxhUDqa92QROPUTETgdfx988AFffPEFM2bMwGazsWnTJv7whz/g8XjYvHlzpxVzgtAd4T17CHzxOUpKardXnUX27aX1/feJ7N2L0dqa+KCqYioYimlULJBShw3vdpXuyL69eP/yF4xAADU/H8+Pf4LscnX7XgxdJ1pcgqlgCLYz5nWrXpUgDERH854spuqEAcvtdvP+++/zyCOP0NzcTFpaGueddx733XefCJqEHjONGIHubSK0aRNSfn63RotMw0fg+eFN8cKSkcJCIoV7iBQWovt8RPYWEtlbGDtYllHz8w+MSI0Ygex0djpneMcOvE/8FcJh1BEj8Nz0I2Sbrdv3YRgG0fJylIx0LDNmiqBJELpJjDj1EzHiJAgnLyMcJvDZp0SKilELjrwR8GHPYxhotbVtQdReIoV70A9RLkPJyYkFUSNHYhoxkmhREb5n/gbRKKZx4/HceONRBz7Rigokux376WeILVWEQU9M1Z0EROAkCCc3zesl8PEq9ObmXq15pDU2xIOoSGEhWlXVYY81T52G++qrjzpHSqutBcPAdvoZqB3qnAnCYCWm6gRBEI4zxePBOmMGgU8+QWtqOqqE7C7Pm5yCMisF66xZQGzFW2RvYTyYipaVgWFgmTsX1xXfO+oVelpTE0Y4jO3U00TQJAg9IAInQRCEHlJz8zBPmUJozRp0i+Wocoy6S3a5sEydhmXqNAD0QAC9oR4lJ/eoV8Dpfj+6z4d11ixMw4f3el8FYTAQe9UJgiAcA/OYsZjGjEWrrMLQtON+PdlmQ83NO/qgKRBAq6vDMmky5rHjjlPvBGHgE4GTIAjCMZAUBcu0aah5eUTLyzgR00aNcBitqhLzuHFYJk/ucTK7IAgicBIEQThmss2GdeZMZIcTraamv7uTwNA0omVlmEaMxDp9BpIqMjQE4ViIwEkQBKEXKKmpWGfOhEgktoXJCcDQdaIlpahDhmCdOUvUahKEXiACJ0EQhF6iFgzFPGkSWl0dRjjcr32JF7jMzMA6e063q5wLgtA1ETgJfe7VV19FkiRefvnlTo9NmTIFSZJ47733Oj02YsQIpk+f3hdd7JahQ4dy9dVX98u133rrLb7//e8zadIkTCbTUScKS5LET37yk07tS5cuRZIkbrrpJnRd763uDhqSJGGZMDFWpLKsDKMfX0OtshLZ5cI2e47YuFcQetGACZz8fj8333wzOTk5WK1Wpk6dyksvvdSt55aVlXHzzTczf/58kpKSkCSJZ5999ojPCwQCjB49GkmS+NOf/nSMdzB4LFiwAEmSWLlyZUJ7Q0MDW7ZsweFwdHqsrKyMffv2sXDhwr7sapdef/117rzzzn679pdffsn48eOZMmXKMZ/PMAx+9rOf8V//9V/89re/5fHHH0cWCcQ9IplMWGfMQMnKQquo6Jc+aDU1SKopFjSJquCC0KsGzF/GJUuWsGzZMpYuXco777zDrFmzuPzyy3nxxReP+NzCwkJeeOEFzGYzixYt6vY177zzTlpaWo6l24NSWloaEydOZNWqVQntH3/8Maqqct1113UKnNq/743AKRAIHPM5AKZNm8aIESN65VxH68knn2T37t28/PLLzJ0795jOFY1Gueqqq3jsscf44x//yH333ddLvRy8ZKcTa9v+b9ohtlA5nrSmJoxIBOusWaLApSAcBwMicHr77bf54IMP+Mtf/sIPfvADFi5cyJNPPsnZZ5/NLbfcgnaE2irz5s2jtraWDz74gF/+8pfduuZXX33FY489xqOPPtobtzDoLFy4kF27dlFZWRlvW7VqFbNmzWLRokV8/fXXNHdIsF21ahWKonDGGWcAcM899zBnzhxSUlJwu91Mnz6dp59+utNS8KFDh3LBBRfw2muvMW3aNKxWK/fccw+rVq1CkiRefPFFfvOb35CdnY3T6eTCCy+kurqa5uZmbrzxRtLS0khLS+Oaa67B7/d3OnfHqbr2cy5fvpw77riDnJwc3G43Z511Frt27Up4rmEY/P73v6egoACr1crMmTP54IMPWLBgAQsWLDji69dbo0HBYJCLLrqIF198kaeeeopf//rXvXJeAdSsLCzTp6O3tKC3tvbJNfXmZnSfD8v0GaLApSAcJwNiXerrr7+O0+nkkksuSWi/5ppruOKKK1izZg2nnnrqYZ9/tG9C4XCYa6+9lh//+MfMnDmzR33uKcMwMHppxKS3SDbbUefYLFy4kP/5n/9h1apVXH755UBsVOmCCy7gtNNOQ5IkPv300/gI4MqVK5k+fTqetlyNoqIifvCDHzBkyBAAvvzyS376059SXl7OXXfdlXCt9evXs2PHDv7zP/+TYcOG4XA44iOFt99+OwsXLuTZZ5+lqKiIX//611x++eWoqsqUKVNYvnw5GzZs4Pbbb8flcvE///M/R7y322+/ndNOO42nnnoKn8/Hb37zGy688EJ27NiB0rY9xh133MF9993HjTfeyJIlSygtLeX6668nEokwevToo3ote6q5uZnzzjuP1atX8/LLL3PRRRf1yXUHE9OIkehNTYQ2b0bKzz/qPeWOhh4IoNXXY5k2DfPYscftOoIw2A2IwGnr1q2MGzcO9aD6JJMnT44/3lXgdLT+67/+i5aWFn73u99RW1vba+ftDiMQoHTmiZMgDZC/bj2S3X5Uz5k/fz6yLMcDp/r6erZu3cof//hHnE4n06dPZ+XKlSxatIjS0lL279+fEBg/88wz8f/XdZ0FCxZgGAaPPvood955Z0IgV1NTw/bt2xMCkvZpwsmTJyeca+fOnTzyyCP87Gc/449//CMAZ599Nl988QUvvPBCtwKn8ePH8/zzz8e/VxSF7373u6xdu5a5c+fS2NjIQw89xKWXXspf//rX+HETJ07klFNO6bPA6e9//zsATzzxhAiajhNJlrFMnoLu8xEtLkEZWnDUHzK6wwiH0SorMU+YgGXiJFHgUhCOowHxr6u+vp6UlJRO7e1t9b2YY7Bx40YeeOAB/vd//xfHUSzvDYVC+Hy+hK/BLDk5mSlTpsQDmI8//hhFUTjttNOAWGDVntd0qPymFStWcNZZZ+HxeFAUBZPJxF133UV9fT01BxUgnDx58mGDkQsuuCDh+3HjYltRnH/++Z3aGxoaOk3XHcq3vvWtTtcHKC4uBmKjY6FQiO9+97sJx82dO5ehQ4ce8fy95YwzziApKYl77rmHwsLCPrvuYCNZLFhmzEBOTSFaXEykpAStrg69tbVXqowbmka0vBzTyFGiwKUg9IET7l/YqlWrup0AvGHDBqZOnQrQ5ae43vqEF41Gufbaa7n00ks599xzj+q59913H/fcc88x90Gy2chft/6Yz9ObpB5ubLpw4UIeeughKioqWLlyJTNmzMDpdAKxwOnBBx/E6/WycuVKVFXl9NNPB2L5Zeeccw4LFizgySefJC8vD7PZzBtvvMG9997bKfk7Ozv7sH04OOA2txUIPFx7MBiM9/FwUlNTE763WCzAgaT09kA+MzOz03MP1Xa8TJ48mYcffpizzz47Hqj21WjXYKMkJWNbsBC9rg6toZ5odTWGrxm9Pci32ZDtdiS7HaltOrc74gUu84dgnSUKXApCXzjhAqcxY8bw5JNPduvY9vyW1NTUQ44qNTQ0AJ3fBHvqkUceYd++fbzyyis0NTUBxEeOgsEgTU1NuFyueB5LR7fddltC4rnP5yM/P/+o+yBJ0lFPi52o2gOnVatWsWrVqoQVje1B0ieffBJPGm8PWF566SVMJhNvvfUWVqs1/pw33njjkNc5HlMjx6I9sKquru70WFVVVZ+OOs2YMYMPP/yQs88+m4ULF7JixQrGjBnTZ9cfTBSPB8XjwTRiBIauo/t86D4fWlMTWlUluteL1tgImoZkNiM5HLFg6jDBkGEYRMvKUDIzsc6ejTxA/i4IwonuhAucsrOzuf7664/qOZMmTWL58uVEo9GEPKctW7YAsdyR3rB161a8Xi+jRo3q9Nidd97JnXfemTAK1pHFYomPPAgx8+bNQ1EUXn31VbZt28YDDzwQf8zj8TB16lSWLVtGUVERV1xxRfwxSZJQVTUhQA0EAjz33HN92v+emjNnDhaLhZdffpklS5bE27/88kuKi4v7NHACmD59Oh999BFnnXVWPHgaK5KLjytJllGSklCSkjANGQKTJ8dW33m96F4v0ZpqtPoGtJoajGgUZBnZ4YiNSFmtSJKEVlGB7PFgmyMKXApCXzrhAqeeWLx4MU8++ST//Oc/ufTSS+Pty5YtIycnhzlz5vTKdX772992qhRdVVXF5Zdfzg9/+EMuvfRSRo4c2SvXGgzaywi88cYbyLIcz29qN3/+fB555BEgMb/p/PPP56GHHuKKK67gxhtvpL6+nj/96U8nTWCakpLCL3/5S+677z6Sk5NZvHgxZWVl3HPPPWRnZ3drlWdxcTFr164FYO/evUCsIjvEyiQc7WrPqVOn8tFHH3HmmWfGg6f2fC+hb8gOR2xblJwczOPGYYTDsVEorxetvh6tugrD60WrrsbQNBSXO1bgMi2tv7suCIPKgAiczjvvPM4++2xuuukmfD4fI0eOZPny5bz77rs8//zzCSMT1113HcuWLWPv3r0UFBTE29vfdPbt2wfAunXr4lNDF198MQBjx47t9Em8qKgIiG0H0p36O0KihQsXsnbtWqZNm4bb7U54bP78+Tz88MOYzeaEVZHf+MY3+Nvf/sb999/PhRdeSG5uLjfccAMZGRlcd911fX0LPXLvvfficDj43//9X5555hnGjh3L448/zh133EFSUtIRn79y5UquueaahLb2VYdXXXVVtyrfH2zKlCmsWLEiIXgaP378UZ9H6B2S2YySnh6r/D1yJIamoTf70Ju8aN4mlNQ01Jyc/u6mIAw6ktEbyzpOAH6/nzvuuINXXnmFhoYGxo4dy2233cZll12WcNzVV1/NsmXL2L9/f8KUSFd5MF29REVFRQwbNow//vGPR1U80Ofz4fF48Hq9nQIGYXDav38/Y8eOZenSpdx+++393R1BEIRB42jekwdM4HSyEYHT4LZp0yaWL1/OqaeeitvtZteuXTzwwAP4fD62bt3ap6vrBEEQBrujeU8eEFN1gnCycTgcrFu3jqeffpqmpiY8Hg8LFizg3nvvFUGTIAjCCUwEToLQD0aOHMmHH37Y390QBEEQjtKAqBwuCIIgCILQF0TgJAiCIAiC0E0icBIEQRAEQegmETgJgiAIgiB0kwicBEEQBEEQukkEToIgCIIgCN0kAidBEARBEIRuEoGTIAiCIAhCN4nASRAEQRAEoZtE4CQIgiAIgtBNInASBEEQBEHoJhE4CYIgCIIgdJMInARBEARBELpJ7e8ODFaGYQDg8/n6uSeCIAiCMLi1vxe3vzd3RQRO/aS5uRmA/Pz8fu6JIAiCIAgQe2/2eDxdHiMZ3QmvhF6n6zoVFRW4XC4kSeq18/p8PvLz8yktLcXtdvfaeYXuEa9//xKvf/8Sr3//Eq9/zxmGQXNzMzk5Ochy11lMYsSpn8iyTF5e3nE7v9vtFv9w+pF4/fuXeP37l3j9+5d4/XvmSCNN7URyuCAIgiAIQjeJwEkQBEEQBKGbROA0wFgsFpYuXYrFYunvrgxK4vXvX+L171/i9e9f4vXvGyI5XBAEQRAEoZvEiJMgCIIgCEI3icBJEARBEAShm0TgNED4/X5uvvlmcnJysFqtTJ06lZdeeqm/uzUorFq1CkmSDvn15Zdf9nf3BpTm5mZuvfVWzjnnHNLT05EkibvvvvuQx65fv56zzjoLp9NJUlISS5YsYd++fX3b4QGmu6//1Vdffch/D2PHju37Tg8QK1as4Nprr2Xs2LE4HA5yc3P59re/zddff93pWPG7f3yJwGmAWLJkCcuWLWPp0qW88847zJo1i8svv5wXX3yxv7s2aPz+97/niy++SPiaOHFif3drQKmvr+eJJ54gFArxne9857DH7dy5kwULFhAOh3nllVf429/+xu7duznjjDOora3tuw4PMN19/QFsNlunfw8vv/xy33R0AHr88ccpKiri5z//OW+//TaPPvooNTU1zJ07lxUrVsSPE7/7fcAQTnr//ve/DcB48cUXE9rPPvtsIycnx4hGo/3Us8Fh5cqVBmD84x//6O+uDHi6rhu6rhuGYRi1tbUGYCxdurTTcZdccomRlpZmeL3eeFtRUZFhMpmMW2+9ta+6O+B09/W/6qqrDIfD0ce9G9iqq6s7tTU3NxuZmZnGmWeeGW8Tv/vHnxhxGgBef/11nE4nl1xySUL7NddcQ0VFBWvWrOmnnglC72qf8ulKNBrlrbfe4qKLLkqonlxQUMDChQt5/fXXj3c3B6zuvP7C8ZGRkdGpzel0Mn78eEpLSwHxu99XROA0AGzdupVx48ahqok76EyePDn+uHD8/fjHP0ZVVdxuN+eeey6fffZZf3dpUNq7dy+BQCD++9/R5MmTKSwsJBgM9kPPBpdAIEBWVhaKopCXl8dPfvITGhoa+rtbA4rX62X9+vVMmDABEL/7fUXsVTcA1NfXM3z48E7tKSkp8ceF48fj8fDzn/+cBQsWkJqaSmFhIX/84x9ZsGAB//73vzn33HP7u4uDSvvve/vvf0cpKSkYhkFjYyPZ2dl93bVBY8qUKUyZMiWe4/fxxx/z8MMP89FHH7F27VqcTmc/93Bg+PGPf0xLSwt33HEHIH73+4oInAaIrobPxdD68TVt2jSmTZsW//6MM85g8eLFTJo0iVtvvVUETv1E/JvoP7/4xS8Svj/77LOZNm0aF198MU8++WSnx4Wjd+edd/LCCy/w2GOPMWPGjITHxO/+8SWm6gaA1NTUQ44qtQ+LH+rTh3B8JSUlccEFF7B582YCgUB/d2dQSU1NBQ490trQ0IAkSSQlJfVxr4TFixfjcDhEiY5ecM899/Df//3f3HvvvfzkJz+Jt4vf/b4hAqcBYNKkSezYsYNoNJrQvmXLFgCxJL6fGG27GYlPeH1rxIgR2Gy2+O9/R1u2bGHkyJFYrdZ+6JlgGAayLN52jsU999zD3Xffzd13383tt9+e8Jj43e8b4jd4AFi8eDF+v59//vOfCe3Lli0jJyeHOXPm9FPPBq/Gxkbeeustpk6dKv5Q9TFVVbnwwgt57bXXaG5ujreXlJSwcuVKlixZ0o+9G7xeffVVWltbmTt3bn935aT1u9/9jrvvvpv//M//ZOnSpZ0eF7/7fUPkOA0A5513HmeffTY33XQTPp+PkSNHsnz5ct59912ef/55FEXp7y4OaFdccQVDhgxh5syZpKWlsWfPHh588EGqq6t59tln+7t7A84777xDS0tL/I1h+/btvPrqqwAsWrQIu93OPffcw6xZs7jgggv47W9/SzAY5K677iItLY1f/epX/dn9k96RXv/a2lquuOIKLrvsMkaOHIkkSXz88cc88sgjTJgwgeuvv74/u3/SevDBB7nrrrv45je/yfnnn99pyrM9IBW/+32gf8tICb2lubnZ+NnPfmZkZWUZZrPZmDx5srF8+fL+7tagcN999xlTp041PB6PoSiKkZ6ebixevNj46quv+rtrA1JBQYEBHPJr//798ePWrVtnnHnmmYbdbjfcbrfxne98xygsLOy/jg8QR3r9GxoajMWLFxtDhw41bDabYTabjVGjRhm33nqr0dTU1N/dP2nNnz//sK/7wW/l4nf/+JIMoy0RQxAEQRAEQeiSyHESBEEQBEHoJhE4CYIgCIIgdJMInARBEARBELpJBE6CIAiCIAjdJAInQRAEQRCEbhKBkyAIgiAIQjeJwEkQBEEQBKGbROAkCIIgCILQTSJwEgThpFFUVIQkSVx99dXdOv7qq69GkiSKioqOa79OVO+++y5z587F4/Ec1et2KAsWLBAbVgsCYq86QRi0ioqKGDZsGOeeey7vvvtuf3dH6GX79+/nO9/5DikpKVx//fW4XC6mTp3a390ShJOeCJwEQRAGoI8++ohQKMRDDz3EZZdd1t/dEYQBQ0zVCYIgDEAVFRUAZGVl9XNPBGFgEYGTIAjdsm3bNi699FIyMjKwWCwMGzaMX/ziFzQ0NBzy+JqaGn79618zZswYrFYrKSkpzJ07lwcffDDhuL/97W98+9vfZujQofHjzj33XFauXNmr/f/LX/7CuHHjsFqtFBQUcM8996DreqfjotEoDz/8MFOmTMFms+HxeFi4cCH//ve/Ox179913I0kSq1at6vTYs88+iyRJPPvss/G2jjlaO3fuZMmSJaSlpXU7D6s7P4P2ayxduhSAhQsXIklSt6/x2WefMX/+fBwOB6mpqVx66aWUlpYe8tiKigqWLl3K3Llz430aOnQoP/rRj6ipqUk49qqrrkKSJNauXXvIc916661IksTrr79+xD4KQn8SU3WCIBzR6tWrOeeccwiFQlx88cUMHTqUL7/8kkceeYR///vffPHFF6SmpsaP37NnDwsXLqS8vJzTTz+d73znO7S0tLB161buvfdefvWrX8WP/fGPf8yUKVM466yzSE9Pp7y8nDfeeIOzzjqL1157jW9/+9vH3P9bbrmFVatWccEFF3DOOefwxhtvcPfddxMOh7n33nvjxxmGwaWXXsprr73G6NGj+fGPf0xLSwuvvPIKF1xwAY8++ig/+9nPjrk/hYWFzJ07lwkTJnDVVVfR0NCA2Wzu8jnd/RkkJSWxdOlSVq1axccff8xVV13F0KFDAUhKSuryGh999BHnnXcesixz6aWXkpOTw0cffcRpp51GcnJyp+M/+eQTHnzwQc4880zmzJmDyWRiw4YNPP7447z33nusX78ej8cDwA9+8AP+/ve/8+STTzJr1qyE80QiEf7+97+TlZXFhRde2P0XUhD6gyEIwqC0f/9+AzDOPffcLo/TNM0YNWqUARjvvvtuwmO33XabARjXXXddQvvs2bMNwHjiiSc6na+0tDTh+3379nU6pqKiwsjJyTFGjRp1yD5fddVVXfa53VVXXWUAxrBhw4yKiop4e21trZGUlGS4XC4jFArF2//+978bgDF//vyE9tLSUiMjI8MwmUwJ/V26dKkBGCtXrux07WeeecYAjGeeeaZT/wHjzjvv7NY9GEbPfgZd9e1w1xg+fLghSZLx6aefxtt1XTeuuOKKeL87qq6uNpqbmzuda9myZQZg/Pd//3dC+8SJEw2Xy2X4/f6E9tdee80AjN/85jfd6qsg9CcxVScIQpc+//xz9uzZw3nnnce5556b8Ngdd9xBamoqL774IuFwGIC1a9fy1VdfMW/ePG644YZO58vLy0v4ftiwYZ2Oyc7O5qKLLmLPnj0UFxcf8z3ceeedZGdnx79PS0vj29/+Ns3NzezatSve3j6t9sADDySMAOXl5fGLX/yCSCTCCy+8cMz9ycrK4j//8z+7ffzR/gx64rPPPmPfvn1ccMEFnH766fF2SZL4/e9/j6IonZ6TkZGB0+ns1H7llVfidrv58MMPE9pvvPFGmpubefnllxPan3rqKSRJ4vrrr+9x/wWhr4jASRCELm3YsAGI1fE5mMPhYObMmQQCAXbv3g3AV199BcA555zTrfPv27ePG264gREjRmC1WuP5OI899hhwIMn5WEyfPr1TW3sA19TUFG/bsGEDNpuN2bNndzq+/f43btx4zP2ZMmXKEafmOjran0FPbNq0CYAzzjij02MFBQXk5+cf8nmvvfYa5557Lunp6aiqiiRJyLKMz+fr9LO78sorsdlsPPXUU/G28vJy3nvvPebPn8/IkSN73H9B6Csix0kQhC75fD4AMjMzD/l4+6otr9cLHAhEcnNzj3juwsJCZs+ejc/nY+HChVx44YW43W5kWY7n6IRCoWO+h/Y8m45UNfbnT9O0eJvP5ztsgHDwfR6Lw72Wh3O0P4OeaH9uRkbGIR/PzMzslFz+4IMP8utf/5r09HTOOecc8vLysNlsADzyyCOdfnZJSUl897vfZdmyZWzfvp3x48fzzDPPoGnaIUcnBeFEJAInQRC65Ha7Aaiurj7k4+3t7ce1JyCXl5cf8dwPP/wwjY2NPP/883zve99LeOyHP/whH3/8cU+73SNut7vb9wkgy7FB+2g02un4roKYo63AfbQ/g55oDy4PXg138DXaRaNRfve735GTk8PGjRtJT0+PP2YYBg888MAhz/ODH/yAZcuW8dRTT/Hggw/yzDPPkJKSwpIlS3rcd0HoS2KqThCELk2bNg3gkEvuW1tbWbduHTabjTFjxgDEp7nef//9I5577969AHzrW99KaNd1nc8///xYut0j06ZNIxAIxKcbO2oP4jpW325faXaoILF9eq23+gXd/xn0xJQpUwD49NNPOz1WXFzcqSRBXV0dXq+XuXPnJgRNAOvWrSMQCBzyOqeccgqTJk3iueee45133mHfvn38x3/8B1artcd9F4S+JAInQRC6dNpppzFixAjeeeedTsm+9913H3V1dVx++eXxnJ1Zs2Yxe/ZsPvnkE5588slO5+sYZBQUFACxxOSO7r//frZu3drbt3JEV111FQC33XYbkUgk3l5eXs5DDz2EqqoJI2MzZ84E4O9//3tCTagvvviiV5LI2x3tz6AnTj/9dIYNG8Zbb72V8PMwDIPbb789YUoTYlN6NpuN9evX09raGm9vbGzkpz/9aZfXuvHGG6mrq4tPz4mkcOFkIqbqBGGQ27Jly2E3f50+fTo/+9nPePbZZzn33HNZtGgRl1xyCQUFBaxZs4YVK1YwYsQI/vCHPyQ87/nnn2fBggXceOONPPfcc5xyyikEg0G2bdvGhg0bqK+vB2LTcc888wxLlizh0ksvJTU1lS+//JL169dz/vnnH7Lo5PF05ZVX8tprr/Hmm28yefJkLrjggngdp/r6eh588EGGDx8eP37u3LmccsoprFixglNOOYV58+ZRXFzM//3f/3HhhRf2WjFHWZaP+mfQk2s88cQTLFq0iLPOOitex2nFihVUVlYyefJkNm/enHD8j370Ix588EGmTJnChRdeiM/n45133qGgoICcnJzDXuvKK6/kN7/5DRUVFcyZM4dJkyYdU98FoU/1dz0EQRD6R8eaQof7+va3vx0/fvPmzcbFF19spKWlGSaTySgoKDB+9rOfGbW1tYc8f1VVlfHzn//cGD58uGE2m42UlBRjzpw5xkMPPZRw3MqVK43TTjvNcLlcRlJSkrFo0SLj66+/PmQdop7Wcdq/f3+nxw5X5ygSiRh/+tOfjEmTJhkWi8VwuVzG/PnzjTfffPOQ16itrTWuvPJKIyUlxbDZbMbcuXON9957r8s6Tt3t/8GO5mdwtHWc2n3yySfGvHnzDJvNZqSkpBiXXHKJUVxcbMyfP79THadwOGzce++9xqhRowyLxWIMGTLE+OUvf2k0NzcbBQUFRkFBwWGvc/nllxuA8dRTTx1V/wShv0mGYRh9Hq0JgiAIg9qECRMoKSmhsrLykLWgBOFEJXKcBEEQhD719ttvs337dq688koRNAknHTHiJAiCIPSJxx9/nNLSUp588klaWlrYvn17fB89QThZiMBJEARB6BNDhw6lrKyMMWPGcP/993PBBRf0d5cE4aiJwEkQBEEQBKGbRI6TIAiCIAhCN4nASRAEQRAEoZtE4CQIgiAIgtBNInASBEEQBEHoJhE4CYIgCIIgdJMInARBEARBELpJBE6CIAiCIAjdJAInQRAEQRCEbhKBkyAIgiAIQjf9f4vDCdTpEkgKAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(6, 5))\n", "ax = fig.add_subplot(111)\n", "\n", "# plot the original\n", "dd = (ds_surf_usp['TSA']-ds_or_usp['TSA']).isel(gridcell=0).groupby('time.hour')\n", "mean = dd.mean('time')\n", "var = dd.var('time')\n", "mean.plot(ax=ax, label='Original', color='#3964DF')\n", "ax.fill_between(mean['hour'].values, mean - var, mean + var, alpha=0.3, color='#3964DF')\n", "\n", "# plot the warming\n", "dd = (ds_warming_surf_usp['TSA']-ds_warming_usp['TSA']).isel(gridcell=0).groupby('time.hour')\n", "mean = dd.mean('time')\n", "var = dd.var('time')\n", "mean.plot(ax=ax, label='Warming 1 K', color='#E02927')\n", "ax.fill_between(mean['hour'].values, mean - var, mean + var, alpha=0.3, color='#E02927')\n", "\n", "ax.set_xlabel('Local hour of day', fontsize=14)\n", "ax.set_ylabel('Temperature difference [K]', fontsize=14)\n", "ax.tick_params(axis='both', which='major', labelsize=12)\n", "ax.set_title('')\n", "ax.legend(frameon=False, fontsize=12)\n", "\n", "plt.tight_layout()\n", "plt.savefig('figs/example3_usp.pdf', dpi=300)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**clean up the case files**" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "usp.case_clean(case_name=\"example3\")\n", "\n", "# when you using ups.run(crun_type='usp-exec') --> see warmup section\n", "# the case files in ./workdir/ouptutfolder/your_case, ./workdir/logfolder/your_case, \n", "# and ./workdir/inputfoler/usp will be removed.\n", "\n", "# when you using ups.run(crun_type='run') or ups.run(), the default crun_type is 'run'\n", "# only ./workdir/inputfoler/usp will be removed." ] } ], "metadata": { "kernelspec": { "display_name": "pymet", "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": "3.11.8" } }, "nbformat": 4, "nbformat_minor": 2 }