calculate_travel_cards.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                   0\n",
      "ZVV 3 Zonen              2792.394976\n",
      "ZVV 9-Pass Zürich        2876.794976\n",
      "GA                       2900.000000\n",
      "ZVV 1-2 Zone             2901.994976\n",
      "ZVV 9-Pass (alle Zonen)  3012.594976\n",
      "ZVV 4 Zonen              3050.594976\n",
      "Half-Fare                3795.394976\n"
     ]
    },
    {
     "data": {
      "image/png": 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QUBD29vZ3bEP08vKiS5cuLF68uME1T58+zdatW41jv2bYsGE4Ozvz/fff8/3339OrV68GLW7u7u4MGjSIL774gqysrJvul5eXd9ux/JxrRV9T3gc/9cQTT5CRkXHTxsQAVVVVxpbJuzFy5EgcHBx45513brnm7tpzvzYD99PX+qfvDyGEuFcysyWEEI0UFBTEkiVLmDp1KuHh4cycOZMOHTpQW1vLwYMHWb58OU8//bTx/Oeee453332X5557jh49erB3717OnTvX7OOKiIigT58+zJs3j8LCQpydnVm6dCn19fU/+9ixY8fy4YcfMmrUKKZPn05ubi7//ve/CQ4OJiEhocG53bt3Z/v27Xz44Yd4e3sTEBBA7969b3vtMWPGYG9vzyuvvIKZmRmTJ09u8P2goCD++te/Mm/ePC5fvszEiROxt7cnJSWF1atX86tf/YpXXnnlttdvyuvRuXNnZs2axX/+8x+Ki4uJiooiPj6exYsXM3HiRAYPHgzA4sWL+fTTT3nssccICgqirKyM//73vzg4OBiLHhsbG7RaLd9//z2hoaE4OzvToUMH6uvrGTp0KE888QRarRZzc3NWr15NTk5Og3j5W/nggw8YPXo0kZGR/OIXv6CqqopPPvkER0dH5s+f3+BcCwsLJk2axNKlS6moqOBvf/vbTdf797//Tf/+/enYsSO//OUvCQwMJCcnh0OHDpGens7JkyfvOJ47/cydnJz4/PPPsbe3x87Ojt69ezdpPVNMTAzLli3j+eefZ9euXfTr1w+dTkdycjLLli1jy5Yt9OjR467G5+DgwGeffUZMTAzdunVj2rRpuLm5kZqaSlxcHP369eNf//oXDg4OxjV1dXV1+Pj4sHXrVlJSUu7qvkIIcVumCUEUQogH17lz55Rf/vKXSrt27RRLS0vF3t5e6devn/LJJ580iNqurKxUfvGLXyiOjo6Kvb298sQTTyi5ubm3jX7Py8trcJ9Zs2YpdnZ2N93/2uaxN7p48aIybNgw4+asf/7zn5Vt27Y1Kvr9f//7nxISEqJYWVkpYWFhyqJFi4xjulFycrIycOBAxcbG5o6bGt/oqaeeUgBl2LBht/15rly5Uunfv79iZ2en2NnZKWFhYcqcOXOUs2fP3vYxN2rs61FXV6csWLBACQgIUCwsLBQ/P7+bNjX+8ccflSeffFLx9/dXrKysFHd3d2XcuHHK0aNHG9zz4MGDSvfu3RVLS0vj65mfn6/MmTNHCQsLU+zs7BRHR0eld+/eyrJlyxr1PLZv367069dPsbGxURwcHJTo6OgGmxrf6Nprq1KplLS0tFuec/HiRWXmzJmKp6enYmFhofj4+Cjjxo1TVqxYYTzn2mt3p6j7n1q7dq2i1WoVc3PzW25q/FO3es/V1tYq7733nhIREaFYWVkpbdq0Ubp3764sWLBAKSkpafRYAGXOnDk3Hd+1a5cycuRIxdHRUbG2tlaCgoKUp59+usHrmJ6erjz22GOKk5OT4ujoqDz++ONKZmZmo//7FEKIxlApyi127hNCCCGEEEIIcU9kzZYQQgghhBBCtAAptoQQQgghhBCiBUixJYQQQgghhBAtQIotIYQQQgghhGgBUmwJIYQQQgghRAuQYksIIYQQQgghWoBsatwIer2ezMxM7O3tUalUph6OEEIIIYQQwkQURaGsrAxvb2/U6jvPXUmx1QiZmZn4+fmZehhCCCGEEEKIViItLQ1fX987niPFViPY29sDhh+og4ODiUcjhBBCCCGEMJXS0lL8/PyMNcKdSLHVCNdaBx0cHKTYEkIIIYQQQjRqeZEEZAghhBBCCCFEC5BiSwghhBBCCCFagBRbQgghhBBCCNECpNgSQgghhBBCiBYgxZYQQgghhBBCtAAptoQQQgghhBCiBUixJYQQQgghhBAtQIotIYQQQgghhGgBUmwJIYQQQgghRAuQYksIIYQQQgghWoAUW0IIIYQQQgjRAqTYEkIIIYQQQogWIMWWEEIIIYQQQrQAKbaEEEIIIYQQogVIsSWEEEIIIYQQLUCKLSGEEEIIIYRoAVJsCSGEEEIIIVq1tMJKvtx3ydTDaDJzUw9ACCGEEEIIIW6lsraez3Zf5Iu9l6it16P1dqBvkKuph9VoUmwJIYQQQgghWhVFUVh3MpN3NyWTVVINQN8gF9w0ViYeWdNIsSWEEEIIIYRoNU5nlDB/XSJHrxQB4NvGhtfGhjMywhOVSmXi0TWNFFtCCCGEEEIIk8svr+FvW87y/dE0FAVsLMz4zaAgfjkwEGsLM1MP765IsSWEEEIIIYQwmTqdnq8OXeGj7ecoq64HYHxnb+aNCcPL0cbEo7s3UmwJIYQQQgghTGLvuTze2pDEhdxyACK8HZg/PoKe7ZxNPLLmIcWWEEIIIYQQ4r66UlDBXzacYfuZHACc7Sx5dWR7nujhh5n6wVqXdSdSbAkhhBBCCCHui4qaev616wL/25dCrU6PuVrFzMh2/GFYCI42FqYeXrOTYksIIYQQQgjRovR6hTUnMnh3UzK5ZTUADAhx5c1oLcHu9iYeXcuRYksIIYQQQgjRYk6mFTN/fSLHU4sB8He25fVxWoaFuz9wUe5NJcWWEEIIIYQQotnlllXzweazLD+WDoCtpRm/HRLML/oHYGX+YEa5N5UUW0IIIYQQQohmU1uvJ/ZgCv/ccYHyGkOU+6SuPswdHYaHg7WJR3d/SbElhBBCCCGEaBa7knP5y4YkLuVXANDJ15E3oyPo3raNiUdmGlJsCSGEEEIIIe7Jpbxy/rIhiV1n8wBw1Vjyx1FhTOnmi/ohinJvKim2hBBCCCGEEHelrLqOT3ZeYNGBFOp0CuZqFc/0a8fvhobgYP3wRbk3lRRbQgghhBBCiCbR6xVW/pjOe5vPkl9uiHIf1N6N18dpCXLTmHh0rYcUW0IIIYQQQohGO55axPz1SZxMKwYgwNWON8ZpGRzmbtqBtUJSbAkhhBBCCCF+Vk5pNe9tSmbV8QwANFbm/H5oME/3DcDSXG3i0bVOUmwJIYQQQgghbqumXsf/7b/Mv3aep6JWB8CU7r78cVR73O0frSj3ppJiSwghhBBCCHETRVHYcSaXv8YlcbmgEoAufk7MHx9BFz8n0w7uASHFlhBCCCGEEKKBC7nlvLUhib3nDFHubvZW/GlUGI919Xmko9ybSootIYQQQgghBAAlVXX8c8d5Fh+8TL1ewdJMzbP9A/jtkGA0VlI6NJX8xIQQQgghhHjE6fQKy4+m8cGWsxRU1AIwLNyd18ZqaedqZ+LRPbik2BJCCCGEEOIRdvRyIfPXJ3I6oxSAIDc73oiOICrUzcQje/BJsSWEEEIIIcQjKKukinc3JbP2RCYA9lbm/GFYCLP6tsPCTKLcm4MUW0IIIYQQQjxCqut0fLnvEv/edZGqOh0qFUzt4ccrI9vjqrEy9fAeKlJsCSGEEEII8QhQFIUtiTm8vTGJtMIqALq3bcP86Ag6+jqaeHQPJym2hBBCCCGEeMidyyljwfpEDlwoAMDTwZp5Y8IY39kblUqi3FuKFFtCCCGEEEI8pEoq6/jH9nN8ffgKOr2CpbmaXw0IZPagIOwkyr3FyU9YCCGEEEKIh4xOr7D0SCp/23KWoso6AEZGePD/xmjxd7E18egeHVJsCSGEEEII8RD54VIBC9YnkZRliHIP9dDwxrgI+oe4mnhkjx4ptoQQQgghhHgIZBRX8c7GM8QlZAHgYG3OS8NDmdGnLeYS5W4SJv2pf/bZZ3Tq1AkHBwccHByIjIxk06ZNxu8PGjQIlUrV4M/zzz/f4BqpqamMHTsWW1tb3N3defXVV6mvr29wzu7du+nWrRtWVlYEBwcTGxt7P56eEEIIIYQQLa66TsdH288x9O+7iUvIQq2Cp3r7s/vVwTzdL0AKLRMy6cyWr68v7777LiEhISiKwuLFi5kwYQLHjx8nIiICgF/+8pe89dZbxsfY2l7vMdXpdIwdOxZPT08OHjxIVlYWM2fOxMLCgnfeeQeAlJQUxo4dy/PPP8+3337Ljh07eO655/Dy8mLkyJH39wkLIYQQQgjRTBRFYdPpbN6OO0NGsSHKvVeAM29Ga4nwlij31kClKIpi6kHcyNnZmQ8++IBf/OIXDBo0iC5duvDRRx/d8txNmzYxbtw4MjMz8fDwAODzzz9n7ty55OXlYWlpydy5c4mLi+P06dPGx02bNo3i4mI2b97cqDGVlpbi6OhISUkJDg4O9/wchRBCCCGEuBdnskpZsD6Rw5cKAfB2tGbemHDGdfKSKPcW1pTaoNXMKep0OpYuXUpFRQWRkZHG499++y2urq506NCBefPmUVlZafzeoUOH6Nixo7HQAhg5ciSlpaUkJiYazxk2bFiDe40cOZJDhw7ddiw1NTWUlpY2+COEEEIIIYSpFVXU8vqa04z95z4OXyrEylzN74eGsOPlQUTLnlmtjskDMk6dOkVkZCTV1dVoNBpWr16NVqsFYPr06bRt2xZvb28SEhKYO3cuZ8+eZdWqVQBkZ2c3KLQA49fZ2dl3PKe0tJSqqipsbGxuGtPChQtZsGBBsz9XIYQQQggh7ka9Ts+S+FT+vvUcJVWGKPexHb2YNyYM3zYS5d5ambzYat++PSdOnKCkpIQVK1Ywa9Ys9uzZg1ar5Ve/+pXxvI4dO+Ll5cXQoUO5ePEiQUFBLTamefPm8dJLLxm/Li0txc/Pr8XuJ4QQQgghxO0cvJjPW+uTSM4uAyDM0543oyOIDHIx8cjEzzF5sWVpaUlwcDAA3bt358iRI3z88cd88cUXN53bu3dvAC5cuEBQUBCenp7Ex8c3OCcnJwcAT09P4z+vHbvxHAcHh1vOagFYWVlhZWV1b09MCCGEEEKIe5BWWMk7G8+w6bShY8vJ1oKXh4fyZC9/SRh8QJi82PopvV5PTU3NLb934sQJALy8vACIjIzk7bffJjc3F3d3dwC2bduGg4ODsRUxMjKSjRs3NrjOtm3bGqwLE0IIIYQQorWorK3n890X+WLvJWrq9ahVMKNPW14aHoqTraWphyeawKTF1rx58xg9ejT+/v6UlZWxZMkSdu/ezZYtW7h48SJLlixhzJgxuLi4kJCQwIsvvsjAgQPp1KkTACNGjECr1RITE8P7779PdnY2r732GnPmzDHOTD3//PP861//4o9//CPPPvssO3fuZNmyZcTFxZnyqQshhBBCCNGAoiisT8hi4cYzZJVUAxAZ6MKb47WEeUoi9oPIpMVWbm4uM2fOJCsrC0dHRzp16sSWLVsYPnw4aWlpbN++nY8++oiKigr8/PyYPHkyr732mvHxZmZmbNiwgdmzZxMZGYmdnR2zZs1qsC9XQEAAcXFxvPjii3z88cf4+vry5Zdfyh5bQgghhBCi1TidUcJb65OIv2yIcvdxsuG1seGM6uApCYMPsFa3z1ZrJPtsCSGEEEKIllBQXsPftp5j6ZFUFAWsLdT8ZlAwvxoYiLWFmamHJ26hKbVBq1uzJYQQQgghxMOuTqfn60NX+Gj7OUqr6wGI7uzNvNFheDvdOsRNPHik2BJCCCGEEOI+2nc+j7fWJ3E+txwArZcD88dH0CvA2cQjE81Nii0hhBBCCCHug9SCSv4Sl8S2JMO2RM52lrwyoj1Te/phppZ1WQ8jKbaEEEIIIYRoQRU19fx71wW+3JdCrU6PmVrFzMi2vDA0FEdbC1MPT7QgKbaEEEIIIYRoAYqisOZEBu9uSian1LCP7IAQV94YpyXEw97EoxP3gxRbQgghhBBCNLOE9GLmr0vkx9RiAPydbXltbDjDtR4S5f4IkWJLCCGEEEKIZpJXVsMHW5JZfiwdRQFbSzPmDA7mF/0DJMr9ESTFlhBCCCGEEPeotl7PV4cu8/H285TVGKLcH+vqw9xRYXg6Wpt4dMJUpNgSQgghhBDiHuw6m8tfNiRxKa8CgI4+jswfr6V7W4lyf9RJsSWEEEIIIcRdSMmv4C8bktiZnAuAq8aSP44MY0p3X9QS5S6QYksIIYQQQogmKauu4187L/B/B1Ko0ymYq1U83bcdvx8WgoO1RLmL66TYEkIIIYQQohH0eoVVxzN4b3MyeWWGKPeoUDdeH6cl2F1j4tGJ1kiKLSGEEEIIIX7G8dQi5q9P4mRaMQDtXGx5fZyWIWHuEuUubkuKLSGEEEIIIW4jt7Sa9zafZeWP6QDYWZrxu6EhPNOvHVbmEuUu7kyKLSGEEEIIIX6ipl7HogOX+WTHeSpqdQBM7ubL3FHtcXeQKHfROFJsCSGEEEIIcZWiKOxMNkS5Xy6oBKCznxPzo7V09W9j4tGJB40UW0IIIYQQQgAXcsv5y4Yk9pzLA8DN3oq5o8KY1NVHotzFXZFiSwghhBBCPNJKq+v45/bzxB68TL1ewcJMxbP9A/jdkBA0VvJxWdw9efcIIYQQQohHkl6vsPxYGh9sOUt+eS0AQ8PceW2clgBXOxOPTjwMpNgSQgghhBCPnGNXCpm/LolTGSUABLrZ8cY4LYPau5t4ZOJhIsWWEEIIIYR4ZGSXVPPupjOsOZEJgL2VOX8YFsLMyHZYmqtNPDrxsJFiSwghhBBCPPSq63T8b38K/951gcpaHSoVPNHdj1dGtsfN3srUwxMPKSm2hBBCCCHEQ0tRFLYm5fB23BlSCw1R7t38nZg/PoJOvk6mHZx46EmxJYQQQgghHkrnc8pYsD6J/RfyAfBwsGLe6HAmdPFGpZIod9HypNgSQgghhBAPlZLKOv6x/RxfH76CTq9gaabmlwMD+M2gYOwkyl3cR/JuE0IIIYQQDwWdXmHpkVT+vvUchRWGKPcRWg9eG6vF38XWxKMTjyIptoQQQgghxAMvPqWQ+esSScoqBSDYXcOb0VoGhLiZeGTiUSbFlhBCCCGEeGBlFlfxzsYzbEjIAsDe2pwXh4USE9kWCzOJchemJcWWEEIIIYR44FTX6fhizyU+23OB6jo9KhU82cufl4eH4qKRKHfROkixJYQQQgghHhiKorDpdDZvx50ho7gKgJ7t2vBmdAQdfBxNPDohGpJiSwghhBBCPBCSs0tZsC6JQ5cKAPBytGbemHCiO3lJlLtolaTYEkIIIYQQrVpRRS3/2H6Obw5fQa+AlbmaXw8M5PlBQdhaysdZ0XrJu1MIIYQQQrRK9To938Wn8vdt5yiurANgdAdP/jwmHD9niXIXrZ8UW0IIIYQQotU5dLGABesTSc4uA6C9hz1vRmvpG+xq4pEJ0XhSbAkhhBBCiFYjvaiSdzaeYeOpbAAcbSx4eUQo03v5Yy5R7uIBI8WWEEIIIYQwuapaHZ/tvsAXey9RU69HrYKnerflpeGhtLGzNPXwhLgrUmwJIYQQQgiTURSFDQlZLNx4hsySagD6BDrzZnQE4V4OJh6dEPdGii0hhBBCCGESiZklLFifRHxKIQA+Tjb8v7HhjO7gKVHu4qEgxZYQQgghhLivCitq+dvWsyyNT0WvgLWFmtlRwfw6KhBrCzNTD0+IZiPFlhBCCCGEuC/qdHq+OXyFf2w7R2l1PQDjOnkxb0w4Pk42Jh6dEM1Pii0hhBBCCNHi9p/PZ8H6RM7nlgMQ7uXA/GgtvQNdTDwyIVqOFFtCCCGEEKLFpBZU8te4JLYm5QDQxtaCV0a2Z1pPf8zUsi5LPNyk2BJCCCGEEM2uoqaeT3df4L/7Uqit12OmVhHTpy0vDgvF0dbC1MMT4r6QYksIIYQQQjQbRVFYeyKThZvOkFNaA0D/YFfeiNYS6mFv4tEJcX9JsSWEEEIIIZrFqfQS5q9P5NiVIgD8nG14bayWEVoPiXIXd03R67lw7AfOHz7A6DkvoVKrTT2kRpNiSwghhBBC3JP88ho+2HyWZcfSUBSwsTDjt0OC+UX/AIlyF3dNV1/HmX27ObJuJYWZ6QCE9ulPcM8+ph1YE0ixJYQQQggh7kptvZ6vDl3m4+3nKasxRLlP7OLNn0aH4+lobeLRiQdVbXUVp3Zs4WjcGsoL8gGwsrWjy8ixeIW0N/HomkaKLSGEEEII0WS7z+by1oYkLuVVANDBx4H50RH0aOds4pGJB1VlaQnHN2/gxOb1VFcYtgiwa+NM9zET6DRsNFa2tiYeYdOZtOHxs88+o1OnTjg4OODg4EBkZCSbNm0yfr+6upo5c+bg4uKCRqNh8uTJ5OTkNLhGamoqY8eOxdbWFnd3d1599VXq6+sbnLN79266deuGlZUVwcHBxMbG3o+nJ4QQQgjx0LmcX8EvYo/w9KIjXMqrwMXOkvcmd2TtnP5SaIm7UpqXy85FX/DfOc9yeOV3VFeU08bLm+G/+h3PffI/eo6fjKW1DbWZ5aYeapOZdGbL19eXd999l5CQEBRFYfHixUyYMIHjx48TERHBiy++SFxcHMuXL8fR0ZHf/va3TJo0iQMHDgCg0+kYO3Ysnp6eHDx4kKysLGbOnImFhQXvvPMOACkpKYwdO5bnn3+eb7/9lh07dvDcc8/h5eXFyJEjTfn0hRBCCCEeGOU19Xyy8zz/tz+FOp2CuVrF033b8fthIThYS5S7aLr81MscWbeSMwf2oOj1AHgEBtNrwhSCe0WiVpuh1OupOJZD2d506vOq8PxjT8ydrEw88sZTKYqimHoQN3J2duaDDz5gypQpuLm5sWTJEqZMmQJAcnIy4eHhHDp0iD59+rBp0ybGjRtHZmYmHh4eAHz++efMnTuXvLw8LC0tmTt3LnFxcZw+fdp4j2nTplFcXMzmzZtvOYaamhpqamqMX5eWluLn50dJSQkODg4t+OyFEEIIIVoXvV5h1fEM3tucTF6Z4fNRVKgbr4/TEuyuMfHoxIMoIzmJ+HUruHQs3njMv2MXek2Ygn+HzqhUKvQ19VT8kE35/gx0pbUAqKzMcJ7aHhuti6mGDhhqA0dHx0bVBq1mzZZOp2P58uVUVFQQGRnJsWPHqKurY9iwYcZzwsLC8Pf3NxZbhw4domPHjsZCC2DkyJHMnj2bxMREunbtyqFDhxpc49o5L7zwwm3HsnDhQhYsWNDsz1EIIYQQ4kFyIq2Y+esSOZFWDEBbF1veGKdlSJi7RLmLJlEUhZTjR4lfu5yM5CTDQZWK0F596TlhCp5BIQDoymopP5BJ+eFMlGodAGp7CzT9fND09kJt02rKl0Yx+WhPnTpFZGQk1dXVaDQaVq9ejVar5cSJE1haWuLk5NTgfA8PD7KzswHIzs5uUGhd+/61793pnNLSUqqqqrCxsblpTPPmzeOll14yfn1tZksIIYQQ4lGQW1bN+5vPsuKYIW7bztKM3w4J4dn+7bAylyh30Xi6+nrOHtrHkbUryE+7AoCZuTnagUPoET0ZZ28fAOryKinfl0HFsRzQGRrvzN1ssB/oi21Xd1TmD87eWjcyebHVvn17Tpw4QUlJCStWrGDWrFns2bPHpGOysrLCyurB6QUVQgghhGgOtfV6Fh1I4ZOdFyi/GuU+qZsPfxoVhruDRLmLxqurqeb0rm0c3bCa0rxcACysbeg8fDTdx0xA42xoBaxJLaV8TzpVSQVwdXGTpb899lG+WIe7oFI/2DOoJi+2LC0tCQ4OBqB79+4cOXKEjz/+mKlTp1JbW0txcXGD2a2cnBw8PT0B8PT0JD4+vsH1rqUV3njOTxMMc3JycHBwuOWslhBCCCHEo2hncg5/2XCGlHxDlHtnPyfmR2vp6t/GxCMTD5Kq8jJObNnA8U3rqSorBcDW0Yluo8fTefgYrDUaFEWhKrmQsj3p1KaUGB9rHeaMfZQvlu0cHpo2VZMXWz+l1+upqamhe/fuWFhYsGPHDiZPngzA2bNnSU1NJTIyEoDIyEjefvttcnNzcXd3B2Dbtm04ODig1WqN52zcuLHBPbZt22a8hhBCCCHEo+xiXjl/2ZDE7rN5ALhqrPjT6DAmdfVB/YDPKoj7p6wgn2Nxa0jYvpm6mmoAHN096BE9mYhBQ7GwtELR3ZAsmFNpeKBahW0XN+yjfLHwsDPhM2gZJi225s2bx+jRo/H396esrIwlS5awe/dutmzZgqOjI7/4xS946aWXcHZ2xsHBgd/97ndERkbSp08fAEaMGIFWqyUmJob333+f7OxsXnvtNebMmWNsA3z++ef517/+xR//+EeeffZZdu7cybJly4iLizPlUxdCCCGEMKnS6jo+2XGeRQcuU69XsDBT8Wy/AH47JBh7iXIXjVSQkcbR9atI2rsLvc7QeurWNoCeE6bQvk9/1GZm6GvqKduXYUgWLDEkWqoszbDr7Ymmvw/mjg/v8h2TFlu5ubnMnDmTrKwsHB0d6dSpE1u2bGH48OEA/OMf/0CtVjN58mRqamoYOXIkn376qfHxZmZmbNiwgdmzZxMZGYmdnR2zZs3irbfeMp4TEBBAXFwcL774Ih9//DG+vr58+eWXsseWEEIIIR5Jer3CimPpvL8lmfxyQ6T2kDB3XhsbTqCbRLmLxsm6cJb4NSu4cPQwXN1JylfbgV4THqdd526oVCp0ZbWUHEyj/FAWSrWhEFNrriYL9nnwkgXvRqvbZ6s1akqWvhBCCCFEa3XsShEL1ieSkG5YJxPoasfr0VoGt3c38cjEg0BRFK4kHCd+7QrSEhOMx4N69KHXhMl4h4YDUJ9fRdm+dEOyYP3VZEFXGzQDfbDr6oHK4sFMFrzmgdxnSwghhBBCtIyc0mre3ZTM6uMZAGiszPnD0BBm9W2H5QMaqS3uH71ex7nDBziydiW5ly8CoDYzI7z/YHqOn4SLrz8AtWlllO1Np+p0vjFZ0MLPHocoX6y1D36y4N2QYksIIYQQ4iFVXafjf/tT+PeuC1TW6lCp4PHuvrw6Mgw3+4d3nYxoHvW1tSTu2cHR9asozskCwNzKik5DR9F97EQcXN1QFIXqs4ZkwZpLNyQLtm+DfZQflgEPT7Lg3ZBi60GjKFBXaepRCCGEEKIVUxSFncm5vLf5LGlFhs8NkX5O/HlMOB19HIF6qK037SBFq1VTWcmJHVv5cctGKksMBZS1xp5uI0bRZdhIbOztUXQKFUdSKd+fQ12OIX0QNdh2csa+nwcWHle3WGqmz62KolB7JRWrkHB4gIo3WbPVCK1qzVZtBbzjbdoxCCGEEEKIh055nQU/FvlwssiLWr1hTsbevJoeLhl0dMrGQq1Hr1hToRtBef1EdBjW+qmows5sCxrztZir8pp1TIoeSlNtKDxrR3WJBcHbtmDh07ZZ79FUsmZLCCGEEEII0ShFtdYcLfAlscQDnWJYw+diVUEvl3TaO+RhplLQKY6U1I2jXDcOBXsA1BShMV+HxmwjalVFs45JV6ui6KIdRefsqK8yA0Blpqf69GmTF1tNIcXWg8bCFv6caepRCCGEEKKV0F2Ncv94x3mKKq9Huc8dFYa/s62JRydas5zLl4jfsI7z8Ye51uzmHRJKr3ETCezSFZVaTX1hDUUHcqg4XgC6q8mCzlZo+rlj16ULKouhwMfNNqba1DQKv/2O4o3rUKoN7Ylmri60mfYEhSO6Yh/Sv9nudT9IsfWgUanA8uHbXVsIIYQQTXfkciHz1yWSmFkKqAl2d+XNaC0DQtxMPTTRSimKQlpiAvFrV3Al4bjxeGC3nvScMAXfsAgAatPLKNubStWpG5IFfTXYR/lhE9G8yYKKolB17BgFsbGU79hp3LfLqn177GdOZ1+YwtcXlnL58CI2+WzC086z2e7d0qTYEkIIIYR4wGQWV7FwUzLrTxq6XeytzXlxWCgxkW2xMJMod3EzRa/nwpHDxK9dTvbF8wCo1GrC+g6k5/jJuLUNMCQLniuibE8aNRcbJgtqBvpiFejYrMmCSl0dpVu2UhgbS/Xp08bjdlEDMX/yMVY5nGfZuX9RdLQIABtzG84UnJFiSwghhBBCNL/qOh3/2XuJz3ZfpKrOEOU+rac/r4wIxUUjUe7iZvV1dZzZv4sj61ZRlJkOgLmFJR2GjKDHuMdwdPdA0SlUnsilbE86dVlX116pwbazO5qBvlh6NW9Xla60lOLlyyn8+hvqs7MBUFlZ4ThhAiUTB/BF5S42pfyZOn0dAF52XjwV/hSPhTyGg6WJw+qaSIotIYQQQohWTlEUtiRm89e4M6QXVQHQs10b3oyOoIOPo4lHJ1qj2qpKErZv5ljcGsqLCgGwsrOj68hxdB0Vja2jE/paHeUHMijbl4GuuAYAlaUau56eaPr7YN7GunnHlJZG4VdfU7xyJUqlIRLezMUFp+lPcmagPx9kriH+1IvG8zu7dSZGG8NQ/6GYqx/MsuXBHLUQQgghxCMiObuUt9YncfBiAQBejtbMGxNOdCevR3qzWHFrlSXF/LhpPSe2bqCmwjBLpWnjTPexE+k0bBSWNrboymsp2XaFikOZ6CsN+62p7SzQ9PVGE+mF2tai2cajKApVx49TuCiWsu3br6/HCglBEzOdnWF1fHPxe678eAUAM5UZw9sOJ0YbQye3Ts02DlORYksIIYQQohUqrqzlw23n+ObwFfQKWJqr+fXAQGYPCsLWUj7CiYZKcrM5umE1p3duo77OkErZxtuXnuMnEd5/MOYWFtQXVFG09QKVR3NQ6vQAmDlbYz/QB7vuHqgszJptPEp9PWVbt1IQu5jqhATjcbuBA1BNHc9yx7OsOP9Pyo6XAWBvYc+U0Ck8GfYkXhqvZhuHqcl/qUIIIYQQrUi9Ts938an8fds5iisNa1ZGd/Dkz2PC8ZMod/ETeVdSOLJuJckH96LoDQWUZ1AIvSY+TnCPPqjUamozyinYe5GqhLzryYI+GuyjfLHp4NqsyYKG9VgrKPz2G+ozswBQWVriOGEC+dGR/KtqF1uvvIYuXQeAv70/T4U/xcTgidhaPHzvbym2hBBCCCFaiUMXC1iwPpHkbMNv+9t72PNmtJa+wa4mHploTRRFISM5kfi1K0g5ftR4vG2nrvSa8Dh+ER0BqLlQTNmedGouFBvPsQptg/1AX6yCmjdZsDY9ncKvvqJkxUr0N6zHcnxyKqf6e/N25hpOnFltPL+nZ09iwmMY6DsQM3Xzzai1NlJsCSGEEEKYWHpRJQs3JhN3yjAT4GhjwcsjQpneyx9ziXIXVyl6PZeOHyF+zQoyz50BQKVSE9KnH73GT8YjMBhFp1CVkGdIFsy8nixo08kN+4G+WHprmm88ikLV8RMUxl5dj3V1Zs0qJBjbGdPYGlrNtxeXkXl1iwJztTljAsYwI3wG4S7hzTaO1kyKLSGEEEIIE6mq1fH5not8vuciNfV61CqY3tufl4e3p42dpamHJ1oJXX09yQf2cGTdSgrSUwEwMzcnYtAwekRPoo2ntyFZ8FCmIVmwsBoAlcUNyYLOzZcsqNTXU7ZtGwWxsVSfvGE9Vv/+6KaOYZnDWVZd+CeVCYYZrjZWbXi8/eNMaz8NN9u723Bbr1fIvVKKZ8CDlb4pxZYQQgghxH2mKApxp7J4J+4MmSWGD8Z9Ap15MzqCcK8Hax8h0XLqqqs5tWsrRzespiw/DwBLG1s6jxhDt9Hj0bRxRldRR+n2K5QfvDFZ0BxNpDd2kd6Y2TVfsqCurIziFSsp/PqrBuuxHKKjyR7Xgy+qd7Mz9U2UTMPCsCDHIGZoZzAucBzW5ndX7FVX1HHmQBan9qRTXljNjL9G4uBi02zPqaVJsSWEEEIIcR8lZpawYH0S8SmGvY98nGz4f2PDGd3BU6LcBQBVZaWc2BLHj5vXU11WCoCtoxPdxkygy4gxWNnaUV9YTfG6i1QcyW6YLDjAB9vuHqgtm28dVG16BkVff03xihXor8bJmzk74zDtCY73cyc2aw1J59Yaz+/n3Y8YbQx9vfve9Xu6IKOchN3pnDucTf3V52dlZ05RVqUUW0IIIYQQoqHCilr+vvUs38WnolfA2kLN7Khgfh0ViHUzRm6LB1dpfh7H4taQsGMz9TWGTYYdPTzpGT2ZiKihmFtaUptZTsHaZKpO5YGhBsHC2w77KD9DsqBZ8xXsVSdOUBC7mLKtW43rsSyDgrB56gk2hZaz5NJKck/nAmBlZsW4wHHEaGMIcgq6q/vp9QqXE/JJ2JVGxtli43EXXw2dBvsS2tMD82YsIu8HKbaEEEIIIVpQvU7PN4ev8OG2c5RWG9q8xnby4s9jwvFxenB+Qy9aTkF6KkfWreTM/t3odYZIdPd2QfScMJnQ3v1QqdXUXCymaM9Zas4XGx9nFeJkSBYMdmq2WVGlvp6y7TsojI2l6sQJ43G7vn2pfWIk3zqcYf2lT6hONLS/utq4Mq39NJ5o/wRtrNvc1T2rK+pIOpDJ6T0ZlBVcXW+mVhHYxZVOg33xasbnd79JsSWEEEII0UIOXMhnwfpEzuWUAxDu5cCb0Vr6BLqYeGSiNcg8l0z82hVcPHrYeMwvohO9JkyhbaeuoIeqxHxDsmCG4T2E6oZkQZ/mSxbUlZdTsnIlhV99TV1GhuFWFhY4RI8jdUwX/lm9i/0Zf4Ecw/lhzmHEaGMY1W4UlmZ3F+ZSkFFOwq50zv1wvVXQ2s4CbX9vOkT5YN+MoR6mIsWWEEIIIUQzSyus5K9xSWxJNHwybWNrwcsj2vNkL3/MmnEDWfHgURSFyyeOEb9uBelJpw0HVSpCekbSc8JkvILbo9TpqDicdVOyoG0PD+wH+DZrsmBdRgaFX39jWI9VbijozNq0wX7q48T3dSY2aw0XLq43jAEVg/wGEaONoYdHj7uabdLrFS6fzCdh98PTKngnUmwJIYQQQjSTytp6Pt11kf/su0RtvR4ztYqYPm15cVgojrbNlwonHjx6nY6zh/dzZO0K8q6kAKA2M0c7cDA9oifh4uNnSBbckWpIFqyoM5xja46mb/MnC1adPElBbCxlW7fB1dZFy8BALJ+azIaQMpamrKLwjCHExcbchseCH+Op8Kfwd/C/q/sZWwV3Z1BW+NNWQT+8gpt3k+XWQootIYQQQoh7pCgK605msnBjMtmlhg+S/YJdeGNcBO097U08OmFKdbU1JO7ewdH1KynJNcx0WlhZ02n4aLqPmYC9iyv1RdUUr79IRfwNyYJtrLAf4Ittj+ZLFlR0uuvrsY4fNx636xtJ5eRhLLJPZOOVf1F3xlDoedl5MT1sOpNCJ+FgeXdbEty2VXCANx0GPhytgncixZYQQgghxD04nVHC/HWJHL1SBICfsw3/b4yWkREeD+Vv6kXjVFeUc3LrRn7ctI7KkmIAbOwd6DZ6PJ1HjsVGY09tVgWFS5OpTLghWdDLDvtBvth0cGu2ZEFdeQUlq66ux0pPv3ojCxzGjSVlVAf+Xr2LH7IXQr7hW53cOhGjjWGY/zDM1U0vF/Q6PZcTCgypgueKjccf1lbBO5FiSwghhBDiLuSX1/C3LWf5/mgaigI2FmbMGRzEcwMkyv1RVl5YwLGNa0nYvonaqioAHNzc6THuMToMHo65pRU1l0rIW3aamnNFxsdZBTthH9W8yYJ1mZkUfvMtxcuWXV+P5eSE5onJHOzjyOKcdVy+vMFwXGXGsLbDiNHG0Nmt813dr7qijqT9mVc3IDZE1z8KrYJ3IsWWEEIIIUQT1On0LD54mY93nKfsapT7hC7e/Gl0GF6OEuX+qCrMzODo+pUk7d2Jrt7wvnD1a0uvCVMIjRyAWm1GVWI+hXvOUJd+Q7JgR1dDsqBv87WbVp06ReGiWEq3bLm+HisgAPMnJ7ImuIRlV1ZTet6wWbK9hT2TQyczPWw6Xhqvu7pffno5p3alcS4+55FsFbwTKbaEEEIIIRppz7k83lqfyMW8CgA6+DgwPzqCHu2cTTwyYSrZF89zZO0KzsUfBEUBwCdMS68JjxPQtQfU66k4mkvZvnR0V/eQwlyNXU8P7Pv7YO7SPAW6otNRtnMnhbGLqTp2zHjctk8fyh4bxBcOp9ma9im684biy8/ej6fCn2Ji8ETsLOyafD+9Tk9KQj6ndqU3aBV09TO0Cob0eHRaBe9Eii0hhBBCiJ9xOb+Cv8Ylsf1MLgAudpa8OrI9j/fwkyj3R5CiKKSeOkn82uWknj5pPB7YvRe9xk/BJ0yLvrKOsl1phmTB8uvJgnaR3mgivTDT3N3eVD+lr6igeNVqCr/6irq0NMNBCwvsx4zm/Ij2/F/NLk7k/Q2KDd/q4dGDGG0MUb5RmKmbXgxVlxtSBW9uFXSj0xBfvIIevVbBO5FiSwghhBDiNspr6vnXzgv83/4UanV6zNUqZvVtx++HhuBoI1Hujxq9XseF+EPEr11BzqULAKjUasL7RdFz/GRc/dtRX3w1WfBINkrt1WRBJys0A3yw6+nZbMmCddnZFH3zDUXfL0NfVma4j6Mjto8/xt7ednyVu4GM9I0AmKvNGd1uNDHaGMJdwu/qftdaBc/G56C7oVUwYoA3EY94q+CdSLElhBBCCPETer3C6uMZvLc5mdwyw2/vB4a68ca4cILdJcr9UVNfV0fS3h0cXb+KoqxMAMwtreg4dAQ9xj6Gg5s7ddkVFH5/lsqTeaA3tBNaeNlhH+WLTUdXVGbqZhlL1anTFC5eTOnmzXB1bZhl27aopo1nVXAhK9JWU3HJ0ObqZOXE46GP82TYk7jZujX5XtdaBRN2ppN5vth4XFoFG0+KLSGEEEKIG5xMK+bNdYmcSCsGoK2LLa+P1TI03F3aox4xNZWVJGzfxLGNa6koMmzwa22nocuoaLqOGoeNvQO1KSXkbzhN9dkbkgWDHLGP8sMqpHmSBRWdjvJduyiIjaXq6A3rsXr3pmhCP75wPM2ujC/QXzLMOAU6BjJDO4PowGiszZs+42RsFdydTnmRtAreCym2hBBCCCGA3LJq3t98lhXHDPsQ2Vma8dshITzbvx1W5vLb+0dJRXERP25ax8mtG6mpNMwSaVxc6TH2MToOHYGFpTXVSQXk7jlJXZqhhQ8V2HRwxT6q+ZIF9RUVFK9eY1iPlZpqOGhujv2YUSQND+b/anaRWPBPuDqEft79mKGdQT/vfndVDOWnlxk2IL6xVVBjQUR/bzpE+aBpI62CTSXFlhBCCCEeabX1ehYdSOGTnRcorzG0ZU3q5sPcUWF4OMiHy0dJcU42R9ev4vTubejqDKEWzt6+9JwwhfD+UagVMyp+zKFwXwb1+YY9tDBXY9fjarKga/MkC9ZlZ1P07beG9Vilhoh2taMjtpMnsKuXNYtzN5CbuRkAKzMrxgWOY0b4DILbBDf5XnqdnpST+STsulWroB8hPd0xl33j7poUW0IIIYR4ZO1MzuEvG86Qkm+Yvejs68ib4yPo5t/GxCMT91Pu5UscWbeSswf3oSiGGR2v4Pb0nDiF4O69Uap1lO/LpvxAhjFZUGVjjibSC01f72ZLFqxKTKQwdjGlmzYZ12NZtPVHeWIcy4PyWZ2+iuorhvh4VxtXprWfxuPtH8fZuulbD1SV15K0P5PTezIatAoGdXWj42BpFWwuUmwJIYQQ4pFzMa+cv2xIYvfZPABcNVbMHdWeyd18UUuU+yNBURTSz5wmfu0KLp+4vg6qXZfu9JowBd/wDuhKainZeJmK+GyUWsP+VGZOVmj6X00WtLr3GR9Fr6d8924KF8VSeeSI8bhNz57kje/DIsdT7Mv6D1wxHA9zDiNGG8OodqOwNGt6kZeXVsapXemcO/KTVsGrGxBLq2DzkmJLCCGEEI+Msuo6Ptl5gUUHUqjTKViYqXi2XwC/HRKMvbVEuT8KFL2ei8fiiV+7nKzzZwFQqdSERvan14QpuLcLpC67gqLl56g8cUOyoKctmig/bDs1T7KgvrKS4jVrKFr8FbVXrlZS5uZoRo3g1NAAvqzbyfmiz6ASVKiI8otipnYmPTx6NHnGSVoFTUeKLSGEEEI89PR6hRXH0nl/SzL55bUADAlz57Wx4QS6aUw8OnE/6OrrOLN/D0fWraQww7D5r5mFBR0GDafHuMdw9PCkNqWU/NhEqpMLjY+zCnTEPsoXq9A2zdJWV5eTQ9E331K0bBn6khIA1A4OWE2KZkdPS77Kj6MwdysANuY2TAyeyFPhT9HWoW2T73WnVsFOg33xlFbBFifFlhBCCCEeaseuFLFgfSIJ6YYPtoGudrwerWVwe3cTj0zcD7XVVZzasZWjcaspL8gHwNLGli4jx9Jt9HhsHZyoTiogb9VJalN/kiw40BdLv+ZJFqxOSqIgNpbSjTesx/L3p37KKJYG5bI2cxV16Yb1YJ52nkwPm86kkEk4Wjk2+V7SKth6SLElhBBCiIdSTmk1725KZvXxDAA0Vub8YWgIs/q2w9K8eTaYFa1XZWkJxzdv4MTm9VRXlANg59SG7mMn0mnYaCwtrKk8nkvO3mM3JAuqsOvugWaALxbNkCxoWI+1h8LYWCrj443Hbbp3J3t8L/7neJLDOf8Hht0G6OTaiRhtDEPbDsVC3bS2Vr1Oz6UT+STsSiPrQonxuJu/PZ0G+xLcQ1oFTUGKLSGEEEI8VGrqdfxvfwr/2nmByquhBk/08OXVkWG42VuZeHSipZXm5XI0bjWndmylvtbQOtfGy5se0ZPQDhiCWqem/IcsCg5koC+7mixofUOyoP29Jwvqq6ooWbOGwsVfUXv5suGgmRm2I4Zxcog//63fxeXS/0I1mKnMGNZ2GDHaGDq7dW7yvW7bKtjNjU6D/fAMdJBWQROSYksIIYQQDwVFUdh+Jpe/xiVxpaASgK7+TsyPjqCzn5NpBydaXH7qZY6sW0nywb3odYYi2yMwmF4TphDcKxKlrJ6y7elU/JCNUnM1WdDREk1/X+x6eaC2uvePxXU5uRQtWULx0qXorq3HsrfHYtJYtnRX803BZkoLdwBgb2HP5NDJPBn2JN4a7ybfy9gqGJ+Drt7QKmhjb4G2v7QKtiZSbAkhhBDigXcht4wF65PYd96wJsfd3op5Y8KY0NlHotwfchlnzxC/djmXjl1v0/Pv0JleEx7Hv2Nn6nMrKV55kcoTuaAzJAuae9hiH+WLbWe3ZkkWrD5zhsLYxZRs3AhXN0O28POjZvJwvg7MYlP2GuqzDOu0/Oz9eCr8KSYGT8TOwq5J95FWwQePFFtCCCGEeGCVVNXx0fZzfHXoCjq9gqWZmucGBDBncDB2zTBTIVonRVFIOX6U+LUryEhONBxUqQjt1ZeeE6bgGRRCzeUSCr5KovrM9WRBywBDsqB1+3tPFlT0esr37qUwdjGVhw8bj9t060bauK586XiSH/O/gizD8R4ePYjRxhDlG4WZumkF0a1aBdVqFYHSKtjqyd9CQgghhHjg6PQKy46m8cGWsxRWGKLch4V78Pq4cNq6NG22QDw49DodZw/uJX7dSvJTLwOgNjMnImoIPaIn08bTm+ozheR+dpLaK6WGB6nARuuCJsoXK3+Hex9DVRUla9dRuHgxtSkphoNmZtgOH8rRQV78V7ebjPLFkA/manNGtxvNDO0MtC7aJt8rL7WMhN3pnP9Jq2DEAB8iBvigaSNrEFs7KbaEEEII8UA5crmQ+esSScw0fJgOdtfwxjgtA0PdTDwy0VLqaqo5vXs7R9evpjQvBwALaxs6Dx9NtzHj0Tg4G5IFvztGfd7VZEGza8mCPli42d7zGOrz8ihcsoTi75aiKy4GQK3RYDZxNBu7KSwp3kZFSQUATlZOPB76ONPCpuFu27QtBnQ6PSnSKvjQkGJLCCGEEA+ErJIqFm5MZt3JTADsrc15YVgoMyPbYtEM625E61NdXs6JLRv4cdM6qsoMxbWNgyPdx0yg8/AxWJpbU/FDFln7j6AvM8xwqqzN0PTxRtOveZIFq8+epTB2MaUbNqBcW4/l40PFpCF8G5jFlry16PMMs06BjoHM0M5gXOA4bMybFh1fVVZL4v5MEvc2bBUM6uZGpyF+eARIq+CDSIotIYQQQrRq1XU6/rv3Ep/uvkhVnQ6VCqb19OOVEe1x0Ugb1cOorCCfY3FrSNixhbpqw0yVg5sHPaIfo8Pg4airoWxfJgWHs64nCzpYounvg11vz3tOFlT0eir27aMgNpbKQ9fXY1l37cKV0Z34wukEp4u+g1zD8b7efYnRxtDXuy9qVdMK/zu1CnYY6IOdk7zHH2QmLbYWLlzIqlWrSE5OxsbGhr59+/Lee+/Rvn174zmDBg1iz549DR7361//ms8//9z4dWpqKrNnz2bXrl1oNBpmzZrFwoULMTe//vR2797NSy+9RGJiIn5+frz22ms8/fTTLf4chRBCCHF3FEVhS2I2f407Q3qR4QN3j7ZtmD8+gg4+jiYenWgJBRlpHF2/iqS9u9DrDOl9bv7t6Dnxcdr36Y+uoIaydVeoPH5DsqD7DcmC97hZtb66+vp6rEuXDAfVaqyHDeaHKHf+q99DbuUSKAJLtSXRQdHMCJ9BcJvgJt3njq2CQ3wJ7i6tgg8LkxZbe/bsYc6cOfTs2ZP6+nr+/Oc/M2LECJKSkrCzu7649Ze//CVvvfWW8Wtb2+t9tzqdjrFjx+Lp6cnBgwfJyspi5syZWFhY8M477wCQkpLC2LFjef755/n222/ZsWMHzz33HF5eXowcOfL+PWEhhBBCNMrZ7DIWrE/k4MUCADwdrPnz2HCiO3lJK9VDKOvCWY6sXcn5I4dAMRRRvuEd6DVhCu26dKc2tYzCb89SnVRgfIxlO4eryYLOqO4x3r8+L4+i776j6Lul6IqKAFDb2aGaMIINXfUsLd1JVbmh4HexdmFa2DSeaP8EztbOTbrPtVbB03syqCiWVsFHgUpRrr6jW4G8vDzc3d3Zs2cPAwcOBAwzW126dOGjjz665WM2bdrEuHHjyMzMxMPDA4DPP/+cuXPnkpeXh6WlJXPnziUuLo7Tp08bHzdt2jSKi4vZvHnzTdesqamhpqbG+HVpaSl+fn6UlJTg4HDvKTZCCCGEuLXiylr+se0c3/yQaohyN1fz64GBzB4UhK2lrH54mCiKwpWE48SvXUFaYoLxeFCPPvSaMBmv4DCqkwsp25PeIFnQWuuC/UBfrNre+2ey6rPnKFy8mNL1643rscy9vSmbOJCvAjPZUXDQeG77Nu2J0cYwOmA0lmZNWwuWl1pGwq40zh/JlVbBh0BpaSmOjo6Nqg1a1d9aJVd32nZ2bvhbgm+//ZZvvvkGT09PoqOjef31142zW4cOHaJjx47GQgtg5MiRzJ49m8TERLp27cqhQ4cYNmxYg2uOHDmSF1544ZbjWLhwIQsWLGjGZyaEEEKIO9HpFZbEp/Lh1rMUVRo+9I6K8OT/jQ3Hz/nek+RE66HX6zj/w0Hi16wg9/JFANRmZoT3H0TP8ZNx9vSl8kQuOR8doz73hmTBbleTBd3v7f2gKAoV+/dTuCiWioPXiymrLp24NDKCz52Oc7Z0BRSAChVRflHM1M6kh0ePJs066XR6Lh3P49Tu9JtaBTsP8SW4uwdmFhLs8rBrNcWWXq/nhRdeoF+/fnTo0MF4fPr06bRt2xZvb28SEhKYO3cuZ8+eZdWqVQBkZ2c3KLQA49fZ2dl3PKe0tJSqqipsbBqmxcybN4+XXnrJ+PW1mS0hhBBCNL/DlwqYvy6R5OwyANp72PNmtJa+wa4mHploTvW1tSTu2cHR9asozjHs9GtuZUWnoaPoPnYCGo0zFfHZZH11BH3p1WRBKzM0fbzQ9PPBzOHekgX11dWUrF9vWI91wVDkoVZjNTSKgwNc+K+yl8LqJCgFG3MbJgZP5Knwp2jr0LZJ96kqqyVxXyan9/6kVbC7O50G+0qr4COm1RRbc+bM4fTp0+zfv7/B8V/96lfGf+/YsSNeXl4MHTqUixcvEhQU1CJjsbKywspKpnOFEEKIlpReVMnCjcnEnTJ88Ha0seCl4aE81dsfc4lyf2jUVFZwctsmjsWtobKkGABrjT1dR0XTddQ4LBVryg9kkHX4gjFZUO1giX1/H+x6eaK2vrePq/X5+RQt+Y6ipUvRFRYarm9nhxI9lDVd61hWupu6KsNsqqedJ9PDpjMpZBKOVk0LYbltq+BAHzoMkFbBR1WrKLZ++9vfsmHDBvbu3Yuvr+8dz+3duzcAFy5cICgoCE9PT+Lj4xuck5Nj2OzO09PT+M9rx248x8HB4aZZLSGEEEK0rKpaHZ/vucjney5SU69HrYLpvf15aXh7nO3ufV8k0TpUFBdxbONaTm7dSG1VJQD2Lm70GDeRjkNGQpme8q0ZFPyYcz1Z0M3GkCzYxf2ekwWrz11dj7XuhvVYXl4UT+jHooA09hVvhGLDuZ1cOxGjjWFo26FYqC0afQ9jq+CudLIuXm8VdG97dQNiaRV85Jm02FIUhd/97nesXr2a3bt3ExAQ8LOPOXHiBABeXl4AREZG8vbbb5Obm4u7u2GH7m3btuHg4IBWqzWes3HjxgbX2bZtG5GRkc34bIQQQghxJ4qiEHcqi4Ubk8koNqzF6R3gzJvREWi9JYDqYVGUncnR9atI3LMD3dUix8XXn57jJxPWL4r6zEpKll8yJAtejWmzbHs1WTDs3pIFDeuxDlAYG0vFgQPG45YdIzg/MpzPnI5zqWINFINapWaY/zBitDF0ce/SpPtIq6BoLJOmEf7mN79hyZIlrF27tsHeWo6OjtjY2HDx4kWWLFnCmDFjcHFxISEhgRdffBFfX1/j3ls6nY4uXbrg7e3N+++/T3Z2NjExMTz33HMNot87dOjAnDlzePbZZ9m5cye///3viYuLa1T0e1MSR4QQQghxs6TMUhasT+SHFEMbl4+TDX8eE86Yjp7yofQhkXPpAvHrVnL+8AEUxdBG5xUaRq8JjxPYpQc154sNyYKXS42PsQ53xj7KF6t297Zvmr6mhtKr67Fqzl8wHFSrsRjcn/392/BfZS+ldYY1gRoLDZNDJjM9fDreGu8m3ScvtYyEnWmcPyqtgo+yptQGJi22bveX66JFi3j66adJS0tjxowZnD59moqKCvz8/Hjsscd47bXXGjyxK1euMHv2bHbv3o2dnR2zZs3i3XffvWlT4xdffJGkpCR8fX15/fXXG72psRRbQgghxN0prKjlw21nWfJDKnoFrMzVzB4UxK8HBmFjKZu2PugURSEt8RTxa5dzJeG48XhA1x70mjAF7+BwqhLyKdubTn2OoZUQMxW2Xd2xH+h7z8mC9QUFFH23lKIlS66vx7K1RTd2MCu7VLOq4gD1imFzZF+NLzO0M5gYPBE7C7s7XbaBO7YKDvEjuJu7tAo+Yh6YYutBIcWWEEII0TT1Oj3fHL7CP7afp+Rq+MDYTl78eUw4Pk6yXvpBp+j1XDhymPh1K8i+cA4AlVpNWN+B9Bw/GRdPPyrisynfn4Gu5HqyoF1vL+z7eWPmeG8zQDUXLlC4eDEla9eh1Bqub+7pScG4PvxfYCqHyq7v29Xdozsx2hgG+Q7CTN34Ar+ytJak/RmGDYivPgdjq+AQXzwD7m02Tjy4Hth9toQQQgjx4Dt4IZ8F65M4m2No2wr3cuDNaC19Al1MPDJxr3T1dSTt28WRdasoykwHwNzCkg5DhtNj3GNobJwpP5BJ1qJ4lOqryYL2ltj398aut9c9JQsqikLFwYMUxi6mYt8+43GLiHCSR4byqdNx0qo2QBmYq8wZFTCKGG0MWhdtk+6Te6WUU7vSOXc0B329YU7CxsGSiAHe0ioomkyKLSGEEEI0i7TCSt6OO8PmRMM+l21sLXh5RHue7OWP2T2EHgjTq62qJGHHFo7FraG8sAAAKzs7uowYR7fR0VjUWlK+L4OsHy9A/Q3JggN9se16b8mC+poaSjfEURgbS83584aDKhXmg/qxp58DX6r2U1F/HqrA0cqRJ0KfYFrYNNxt3Rt9j2utggk708m+JK2CovlIsSWEEEKIe1JZW89nuy/yxd5L1NbrMVOriOnTlheGheBkK1HuD7LK0hKOb1rH8S0bqKmoAEDTxpnuYyfSadgoyNdRti6NwhuTBf3tDcmC4S73lCxYX1hI0XffUbTkO3QFhgJPZWtD3eiBrOhSxZqqw+h1hpCKAMcAZoTPIDooGhvzxrep3rJV0ExFUDdpFRTNQ4otIYQQQtwVRVFYdzKTdzclk1VSDUDfIBfejI6gvae9iUcn7kVJbg5HN6zi9K7t1Ncaos3bePkY4tv7D6L+UjnFX12gNuX6LNC1ZEHLtvcWe15z8SKFsYspWbcOpcZwb3NPD3LH9OTLdpc5WrUDrmZt9PXuS4w2hr7efVGrGj/zlHullIRd6Zz/SatghwHeRAz0we4e15QJcY0UW0IIIYRostMZJSxYn8iRy0UA+Lax4bWxWkZGeEiU+wMsL/UyR9auIPngXhS9YdbIMyjEEN/erSfVpwop+PephsmCXdyxH+iDhUfjE/5+SlEUKg8doiA2loq9N6zH0oZxengg/25znOyazVAFlmpLooOimRE+g+A2wY2+h06n59KPeSTs+kmrYDsHwwbE0iooWoAUW0IIIYRotILyGv629SxLj6ShKGBjYcacwUE8NyAQawuJcn9QpScncmTtCi79eMR4rG2nrvSaMAWf4Agqj+aQ+7fj6EoMM00qSzPsenui6e+D+T3MAulra6+vxzpnSDVEpUI9sA87+2pYZHaIKt0FqAEXaxemhk1lavupOFs7N/oet2sVDO7uTsfB0iooWpYUW0IIIYT4WXU6PV8dusJH289RVm3Yt2hCF2/+NDoML0eJcn8QKXo9l44fIX7NCjLPnQFApVIT0qcfvcZPxtXNn/KDmWSvPIJSZXjN1RoLNP190PT2Qm1z9x8j64uKKF66lMJvl6DLzzfc28aG6lF9WdapgvW1V4s+HbRv054YbQyjA0Zjadb4NYC3bRUc6EPEAG9pFRT3hRRbQgghhLijvefyeGtDEhdyywGI8HZg/vgIerZr/OyCaD109fWcPbiX+LUrKEhPBcDM3JyIqGH0iH4Mewtnyvalk3Us/nqyoKsNmoE+2HX1QHUPrXY1ly5RuPgrStasMa7HMnN3I2t0N/4TcJmEmj1QCypURPlGEaONoadnz0a3pl5vFUwj+1Kp8bhHgAMdB/kS3N0ds3tIRhSiqaTYEkIIIcQtXSmo4C8bzrD9TA4AznaWvDqyPU/08JMo9wdQXXU1p3Zt5eiG1ZTl5wFgaWND5xFj6TZ6PJblFpTtTCf79KXryYJ+V5MFtXefLKgoCpU//EDholjK9+wxHjcPDyVhaDv+3eY4efU7oAZszG2YEDSBGdoZtHVo2+h7VJbWkrgvg8S90iooWhcptoQQQgjRQEVNPf/adYH/7UuhVqfHXK1iZmQ7/jAsBEcbC1MPTzRRVVkpJ7bE8ePm9VSXGWZ7bB2d6DZmAp2GjUKVUUfZ8nSKbwiNsA5zxn6gL5YBd58sqNTWUrJxI4Wxi6lJTjYcVKlgQC+297Eh1vwHapVLUA8eth5MD5/O5JDJOFo1vjC6VaugrYMlEdIqKFoJKbaEEEIIAYBer7DmRAbvbkomt8zQ4jUgxJU3o7UEu0uU+4OmND+PY3FrSNixmfqrLXuOHp70jJ6Mtv9g6pJLKf3yPHXZhv2zUKuw7eKG/UBfLDzvPlmwvqiI4u+XUfTtt9TnGWbQVDY2VI7ozXcdy9isO2Y4UYGOrh2J0cYwrO0wLNSNK+Tv1CrYabAvQd2kVVC0HlJsCSGEEIKTacXMX5/I8dRiANq62PLaWC3Dwt0lyv0BU5CexpF1Kzmzfxd6nQ4At3aB9JowheCufag6lkf+xwnoiq8lC6qx6+VlSBZ0uvuZoJpLKRR+tZiSNWtRqg37rpm5u5ExsjOftbvImfr9oAO1Ss1Q/6HM1M6ks1vnRr+/rrUKnt6bQeWNrYI93Ok0yA+PAIe7HrsQLUWKLSGEEOIRlldWwwdbkll+LB1FAVtLM347JJhf9A/Aylyi3B8kmeeSiV+7gotHDxuP+UV0oteEKfgGRlBxKIvcD46hr7whWbCftyFZ0Pbu2kMN67HiKYyNpXz3buNxs/bBnBjqz7+dT1Co2w31oLHQMClkEtPDp+Oj8Wn0PXKvlJKwM53zxxq2CnaI8kHbX1oFResmxZYQQgjxCKqt1xN7MIV/7rhAeY3hw/ekrj7MHR2Gh4O1iUcnGktRFC6f/JH4tctJTzptOKhSEdyjD70mTMHN2Z+yfRlkLz8K9YZNis1drNEM9MWu290nCyq1tZRu2kRB7GJqzpy5frxfD7ZEWvGVxVHquQw68NX4MkM7g4nBE7GzaFx7oq5ez8XjuZzalS6tguKBdk/FVk1NDVZW8tsEIYQQ4kGyKzmXv2xI4lK+Ya1OJ19H3oyOoHvbNiYemWgsvU7H2cP7ObJ2BXlXUgBQm5mjHTiYHtGTsFecKNubTvapo8ZkQQtfDfZRfthE3H2yoK64mKLvl1H0zTfX12NZW1M2rAdLOpawnRPGc7t7dCdGG8Mg30GYqRs3S3q7VsGQHh50HOyLRztpFRQPliYVW5s2bWLp0qXs27ePtLQ09Ho9dnZ2dO3alREjRvDMM8/g7e3dUmMVQgghxD1Iya/gLxuS2JmcC4Crxoo/jmrPlG6+qCXK/YFQV1tD4u4dHF2/kpJcQyS/hZU1nYaNotuYCVgWmlO2KZ3cC5eNj7Fu3wbNQF+sAh3vev1d7eXLFH71FcWr16BUVQGgdnMldXgEnwVc5Lze0LporjJnVMAoZmhnEOES0ejr51wu5dQuaRUUDx+VoijKz520evVq5s6dS1lZGWPGjKFXr154e3tjY2NDYWEhp0+fZt++fRw6dIinn36av/zlL7i5ud2P8d8XpaWlODo6UlJSgoOD/EZFCCHEg6Wsuo5/7bzA/x1IoU6nYGGm4pl+AfxuSDD21hLl/iCorijn5NaN/LhpHZUlxQDY2DvQdXQ0nYePhUvVlO1Jpy7rWrIg2HZ2RzPQF0uvu0sWVBSFyiNHKIxdTPmuXXD1I6M6NIhjg7351DWBEr3hfo5WjjwR+gTTwqbhbuveqOtfaxVM2JlOTspPWgWH+BLUVVoFRevUlNqgUcVWZGQkr732GqNHj0atvv2bPiMjg08++QQPDw9efPHFpo+8lZJiSwghxINIr1dY+WM6720+S365IXlucHs3Xh+nJdBNY+LRicYoLyzg2Ma1JGzfRO3VGSUHN3d6jHuMiH5DqE0opmx/BrqiG5IFe3oakgXb3N3aO6WujtLNmylcFEt1UpLxuK5vVzb1tuAb6+Por/YmBjgGMCN8BtFB0diY2zTq+sZWwT0ZVJZKq6B48DR7sfWok2JLCCHEg+Z4ahHz1ydxMq0YgABXO94Yp2VwWONmHYRpFWZmcHT9SpL27kRXbwgwcfVrS8/xkwnpHEllfC4VhzKvJwvaWaDp640m8u6TBXUlJRQtW0bRN99Sn2NoUVRZWVEytBtfdyhij9kF47mRXpHEaGPo59MPtapxs085l0tJ2JXGhaO56HVXWwUdLekw0IeIAT7YOlje1biFuN+aUhs0es2WXq+/46yWEEIIIUwvt7Sadzcns+rHDAA0Vub8fmgwT/cNwFJaslq97IvnObJ2BefiDxrb9nzCtPSa8Dh+bTtQvj+D3L/9iFJnSBY0c7bGfqAPdt09UFncXVR/7ZUrFH71NcWrVl1fj+XqQsqwcD5rd4FLqiMAWKotGRc0jhnhMwhpE9Koa+vq9Vz8MZeEXQ1bBT0DHeg4WFoFxcOv0cWWhYUFWVlZuLsbfiP26quvMm/ePJydnVtscEIIIYRonJp6Hf+3/zL/2nmeilrDRraPd/fl1VHtcbeXKPfWTFEUUk+dJH7dClJPnTAeD+zei17jp+Bm70/Z3nRylt+QLOijwT7KF5sOrneVLKgoClXHjlEQG0v5jp3Gwk4VHED8IE8+dztFGYbQCxdrF6aGTeWJ0CdwsXFp1PUrSmpI3JdJ4t4bWgXNVYR0l1ZB8WhpdLH1027DL774gtmzZ0uxJYQQQpiQoijsOJPLX+OSuFxQCUBXfyfmR0fQ2c/JtIMTd6TX67gQf4j4tSvIuWRo0VOp1YT3izLEt9ca4ttzzx83PsYqxAn7KD+sgu4uWdCwHmsLhbGxVCcmGo/X9e7Exl5mfGuXAKo0AELbhBKjjWFMwBgszRrX4peTUkrCbmkVFOKau95nS5Z6CSGEEKZ1IbectzYksfecYb8jN3sr/jQqjMe6+kiUeytWX1dH0t6dHF2/kqKsTADMLa3oOGQE3cdMxCJbRdnadPIz0w0PUINNJzfsB/pi6X13wSa6khKKly+n8Jtvqc/OBgzrsYoGd2ZxRAEHLK8FYaiI8o0iRhtDL89ejSro7tQq2GmwH4Fd3aRVUDyy7mlTYyGEEELcf6XVdXy8/TyLD16mXq9gaabm2f4B/HZIMBor+V97a1VTWUnC9k0c27iWiqJCAKztNHQZFU2XoWNQzlVRtjgVXWE1ACqLG5IFne+uFbQ2NfX6eqxKw8ynyrkNl4a159N2F7li9iMANuY2jA8az4zwGbRzbNeoa9+2VbCHB50G++LeVloFhWjS38hvvPEGtra2ANTW1vL222/j6OjY4JwPP/yw+UYnhBBCCCOdXmH50TQ+2HKWggrDh9th4R68Njacdq53t5eSaHkVxUUc37yeE1viqKk07EulcXYxxLdHDqX2x0JKPk1GX3EtWdAcTaQ3dpHemNk1PVlQURSqfvyRwthYyrbvMK7HIrAtP0S587n7aSrURwHwsPVgevh0JodMxtHK8Q5XvS4n5Wqq4LGGrYIdo3zQ9pdWQSFu1Ohia+DAgZw9e9b4dd++fbl06VKDc+52V3IhhBBC3NnRy4UsWJ/EqYwSAILc7HgjOoKoUDcTj0zcTnFONkfXr+L07m3o6uoAcPb2peeEKYRE9KbqUC4F/0homCw4wAfb7h6oLZueLKjU1VG6dSuFsYupPnXKeLymVwfW91BY5pAMKkNKZUfXjsRoYxjWdhgW6p8v6HT1ei4cy+XU7p+2CjrSabAvgd3cMDOTVkEhfqrRxdbu3btbcBhCCCGEuJXskmoWbjrD2hOGtT32Vub8YVgIs/q2w0I+3LZKuZcvcWTdSs4e3IeiGAopr+D29Jw4BX+vCMr3Z5K39QQYvoWFtx32UX6GZEGzpv/iWldaSvHyFRR+8w31WVmGg5aWFA7qyKKIPH6wTgZArTJjqP9QZmpn0tmtc6N+SS6tgkLcG2nsFkIIIVqh6jodX+67xL93XaSqTodKBVN7+PHKyPa4aqxMPTzxE4qikH7mNPFrV3D5xDHj8XZdutNr/GTcrPwo25NO3sqTxu9ZhThhP9AXq2Cnu+oOqk1Pp/CrryhZsRL9Deuxzg8J4tN2F0m3MNxLY6FhUsgkpodPx0fj06hrZ6eUcGpXeoNWQTtHSzpIq6AQTdLoYuull15q1HmyZksIIYS4e4qisCUxh7c3JpFWaNhgtkfbNrwZHUFH38atqRH3j6LXc/FYPPFrl5N13rDcQqVSExrZn57Rk7Evd6BsZzr5GacND1DdkCzo0/RkQUVRqDp+4up6rO2gN0yPKQF+HBzown88zlBldgIAH40PM8JnMDF4IhrLn7/XtVbBhF3p5F7+SavgEF9DqqDMpgrRJI0uto4fP97g6/3799O9e3dsbGyMx2TNlhBCCHH3zuWUsWB9IgcuFADg6WDNvDFhjO/sLf+PbWV09XWc2b+HI+tWUphh2JfKzMKCDoOG033UBCzSVJStyKCw0ND+qbJQY9vDA/sBvneVLKjU11O2bRsFsbFUn0wwHq/uHs6aHnpWtbkAKkMLYTf3bszUzmSQ3yDM1D+/9quipIbEvRkk7sts0CoY2sOwAbG0Cgpx91TKXW6YZW9vz8mTJwkMDGzuMbU6paWlODo6UlJSgoOD/IUjhBCieZVU1vGP7ef4+vAVdHoFS3M1vxoQyOxBQdhJlHurUltdxakdWzkat5rygnwALG1s6TJyLF0GjUFJqqL8YCb6CkMghtrWHLtIbzR97y5ZUFdWRvGKlRR+/RX1mdfXY+UPCOf/IvI4apcLgLnKnJEBI4nRxhDhEtGoa2enlJCwM52LP/60VdAXbX9vaRUU4jaaUhvI3+BCCCGEiej0CkuPpPK3LWcpqjR8OB8Z4cH/G6PF38XWxKMTN6osLeH45g2c2LKB6vIyAOyc2tBtzAQ69BxC7bEiSj89dz1ZsI0V9gN8se1xd8mCtenpFH39NcUrVqKvMMTFq9o4cTaqHZ8GXiLTKhEARytHHg99nGntp+Fh5/Gz19XV6bnw482tgl5BjnQcLK2CQjQ3KbaEEEIIE/jhUgEL1ieRlGX4wBvqoeHN6Aj6BbuaeGTiRqV5uRyNW82pHVupr60BwMnTi57jJxMS0oeqg9kU/ivxerKglx32Ub7YdHS7q2TByuPHKYxdTNm2bcb1WPp2Puwf0Ib/ep2lxsyw9qudQztitDFEB0VjY25zp0sC11sFT+/LpEpaBYW4b6TYEkIIIe6jjOIq3tl4hrgEQ0uYg7U5Lw0PZUaftpjLjEKrkZ96mSPrVpJ8cC96nQ4Aj8BgekZPxt8tgvJ9mRRsu76XlVWwE/ZRd5csqNTXU7Z9O4WLYqk6eT2tsKpbe1Z1r2ety2VQ5QDQx6sPMdoY+vv0R636+feLtAoKYVqNLrYSEhIafK0oCsnJyZSXlzc43qlTp+YZmRBCCPEQqa7T8cWeS3y25wLVdXrUKniylz8vj2iPs5184G0tMs6eIX7tci4dizce8+/QmV7RU3BT+1K2N52CdEMLHyqw6ehqSBb0tW/yvXTl5RSvWEHRV19Tl2kI0sDCgtwBYXwZnsMJh4sAWKqtGBs4lhnaGYS2Cf35615rFdyZRu6VMuNxaRUU4v5rdECGWq1GpVJxq9OvHVepVOiu/vbnYSIBGUIIIe6WoihsOp3N23FnyCg2RLn3CnDmzWgtEd4S5d4aKIpCyvGjxK9dQUbytUJKRWivvvQYOxn7InvK9qWjK6g2fM9cjV0PD+wH+GDu8vMtfD9Vl5FB4dffULx8uXE9Fk6OnIny59PAS+RYG9oVna2dmRY2jSdCn8DFxuVnr1tRUsPpvRkk7s2gquxqQIe5itCeHnQa7Iebf9MLQiHEzVokICMlJeWeByaEEEI8Ss5klbJgfSKHLxUC4O1ozZ/HhjO2o5dEubcCep2Oswf3Er9uJfmplwFQm5kTETWE7sMnYnEZypdnUlxuaOEzJgtGemGmafpsZNXJkxTExlK2dRtc/eW0zt+Lvf2d+J/3eWotzgAQ2iaUGG0MYwLGYGl25/soikJOSikJu9K5eCwXvf5qq6CTFR0G+kiroBAm1uhiq23bti05DiGEEOKhUVRRy4fbzvHtD1fQK2BlrubXUUHMjgrC5i6S6UTzqqup5vTu7Rxdv5rSPEMhZWFtQ+fho+nSfzTKqUoqYtOoqr2aLOhkhWaAD3Y9PZucLKjodJRt30FhbCxVN+xZWtElmJXdaolzz0BR5QEQ5RtFjDaGXp69frYY19XpuXAsx5AqeGOrYLAjHQdJq6AQrUWji63z58/zxhtv8MUXX9w0XVZSUsLs2bP561//+kjsuyWEEELcSr1Oz5L4VP6+9RwlVYY2rrEdvZg3JgzfNhLlbmrV5eWc2LKBHzevp6q0BAAbB0e6j5lAROfB1B4ppOw/F+Hq7ND1ZEFXVE0sXHTlFZSsWknhV19Tl55uOGhhQVbfYP6nzSHB6bLh/ua2jA8az4zwGbRzbPez171Vq6CZuZqQnu7SKihEK9ToYuuDDz7Az8/vln2Jjo6O+Pn58cEHH/DZZ5816wCFEEKIB8HBi/m8tT6J5GzDLEOYpz1vRkcQGfTza21EyyorzOdY3FoStm+mrtqwbs7BzYOe4yYREtCLqoM5FP8n2Xi+VZAj9lF+WIU0PVmwLjOTwm++pXjZMvTXQsQc7Tk90I/PAlPIsz0PgLutO9PDpjMldAqOVndeu3fHVsEoHyL6e2NjL62CQrRGjS629uzZwzfffHPb7z/xxBNMnz69WQYlhBBCPCjSCit5Z+MZNp3OBsDJ1oKXR7TnyZ5+EuVuYgUZaRxdv4qkvbvQ6+oBcPNvR88Jj+PvEE75vkyKdl8tslRg08EV+6i7SxasSkigMHYxpVu2GNdj1ft5sLuvPbF+KdRanAOgg0sHYrQxDG83HAu1xR2veadWwU6D/Qjo4iqtgkK0co0utlJTU3F3d7/t911dXUlLS2uWQQkhhBCtXWVtPZ/vvsgXey9RU2+Icp/Rpy0vDQ/FyVZmGUwp68JZjqxdyfkjh+BqirJveAd6jZuMm86X8n0ZFOWfNZx8LVmwvw/mrk1LFlR0Osp27KAwdjFVP/5oPF7eKZBl3arZ4pmDoipArTJjuP9QYrQxdHHr8rOzZRXFV1sF9/2kVbCXB50G+UqroBAPkEYXW46Ojly8ePG2QRkXLlyQWHQhhBAPPUVRWJ+QxcKNZ8gqMUSBRwa68OZ4LWGe8v9BU1EUhSsJx4lfu4K0xOt7gwb16EPPUY9hn+9A+eYMissvAKCyMUcT6YWmr3eTkwUN67FWUfj119Rd+0WzuTmZfYP4UpvD6TapANhZaJgUMonpYdPxtff92fFLq6AQD59GF1sDBw7kk08+YciQIbf8/j//+U8GDBjQbAMTQgghWpvTGSW8tT6J+MuGKHcfJxteGxvOqA6eEuVuInq9jvM/HCR+zQpyLxs2AVabmRHefxDdB0/A4iJULM+mtNbwmpk53pAsaNW0ZMG6rCwKv/mG4mXL0ZcZ2voUBw2n+nvzefAV8u0M9/fR+PBU+FM8FvwYGkvNHa+pq9Nz/lgOp6RVUIiHUqOLrXnz5hEZGcmUKVP44x//SPv27QFITk7m/fffZ8uWLRw8eLDFBiqEEEKYSkF5DX/beo6lR1JRFLC2UPObQcH8amAg1hYS5W4K9bW1JO7ZwdH1qyjOyQLA3MqKTkNH0aXXKJRTlVR+nUnNtWRBT1s0UX7Ydmp6smDVqdMUxsZSunnz9fVYvu7siLTl67Zp1FpcAqCbezditDEM9huMmfrO7wtpFRTi0dDoYqtr166sWLGCZ599ltWrVzf4nouLC8uWLaNbt27NPkAhhBDCVOp0er4+dIWPtp+jtNoQsBDd2Zt5o8Pwdmra+h7RPGoqKzi5bRPH4tZQWVIMgLXGnq4jo+kQMYjaI0VULL5sPN8q0BFNlC/WoW2aNPuo6HSU79pFQWwsVUePGY+XdWjL912r2OZTgKIqxFxlwZh2I5ipnUmEa8Sdr3mtVXBnGhd/zDO2CmraGFoFtf29sbmLzZKFEK2XSlGurhxtpKqqKjZv3syFCxdQFIXQ0FBGjBiBre3Du39IaWkpjo6OlJSUyLo0IYR4ROw7n8db65M4n2uI79Z6OTB/fAS9ApxNPLJHU0VxEcc2ruXk1o3UVlUCYO/iRo+xEwnx7kXVoRxqU6+24anAJsIF+yg/LP2aNkOkr6igePUaCr/6irpUw9orzMxI7xPAl9psklwN6/QcLB14PPRxngx7Eg87jzte81qrYMLOdPJSb24VDOziilpaBYV4YDSlNmhysdWcFi5cyKpVq0hOTsbGxoa+ffvy3nvvGVsUAaqrq3n55ZdZunQpNTU1jBw5kk8//RQPj+t/saWmpjJ79mx27dqFRqNh1qxZLFy4EHPz6xN3u3fv5qWXXiIxMRE/Pz9ee+01nn766UaNU4otIYR4dKQWVPKXuCS2JeUA4GxnySsj2jO1px9malmXdb8VZWdydP0qEvfsQFdnaLdz8fWn59jJ+NuGUbE/i/p8w95ZmKuw6+6BZoAvFk1MFqzLzqbo228p+n4Z+tJSABR7O0728+SLkFQKNIaPS+0c2jEjfAbRQdHYWtz5F83lRTUk7ru5VTC0lwcdB/vi1sRCUAjROjSlNmhUG+HSpUuZNm1ao26elpZGamoq/fr1+9lz9+zZw5w5c+jZsyf19fX8+c9/ZsSIESQlJWFnZwfAiy++SFxcHMuXL8fR0ZHf/va3TJo0iQMHDgCg0+kYO3Ysnp6eHDx4kKysLGbOnImFhQXvvPMOACkpKYwdO5bnn3+eb7/9lh07dvDcc8/h5eXFyJEjG/W8hBBCPNwqaur5964LfLkvhVqdHjO1ipmRbXlhaCiOtnfeD0k0v5xLF4hft5Lzhw+gKHoAvELD6DV6Cu413pQfzKSkzLBWSmV9Q7JgExP7qk4nUrh4MaWbNkG9oVW0zseNbX2s+a5dJjWWVwDo49WHGG0M/X36o1bdfhZKURSyL5Vyape0CgohGjmzFRUVRW5uLs888wzR0dGEh4c3+H5JSQkHDhzgm2++Ydu2bfzvf/9j/PjxTR5MXl4e7u7u7Nmzh4EDB1JSUoKbmxtLlixhypQpgCGQIzw8nEOHDtGnTx82bdrEuHHjyMzMNM52ff7558ydO5e8vDwsLS2ZO3cucXFxnD592nivadOmUVxczObNm392XDKzJYQQDy9FUVh7IpOFm86QU1oDwIAQV94YpyXEQ2Ye7idFUUhLPEX82uVcSThuPB7QtQe9hk1Ck6OhIj4bpcYQUmHmaImmvy92vTxQWzV6GTqKXk/57t0ULoql8sgR4/GSCD++71rJDt9iFJUKS7UlYwPHMkM7g9A2oXe8prQKCvHoaPaZrT179rBu3To++eQT5s2bh52dHR4eHlhbW1NUVER2djaurq48/fTTnD59ukGLX1OUlJQA4Oxs6Ic/duwYdXV1DBs2zHhOWFgY/v7+xmLr0KFDdOzYscE9R44cyezZs0lMTKRr164cOnSowTWunfPCCy/cchw1NTXU1NQYvy692k4ghBDi4XIqvYT56xM5dqUIAH9nW14bG85wrYdEud9Hil7PhSOHiV+3guwL5wBQqdWE9R1I9/7jsbgAlatzKdcZPieYe9hiP9AX285uqMwbX8DoKyspXrOGwsWLqbtyfT1Wai9/vozIIdnNkGrobO3CtPbTeKL9E7jYuNzxmrdsFbRQE9pTWgWFEE1IIxw/fjzjx48nPz+f/fv3c+XKFaqqqnB1daVr16507doVtfruf2Oj1+t54YUX6NevHx06dAAgOzsbS0tLnJycGpzr4eFBdna28ZyfFnfXvv65c0pLS6mqqsLGpmFf98KFC1mwYMFdPxchhBCtW355DR9sPsuyY2koCthamjFncDC/6B8gUe73ka6+jqR9uziybhVFmekAmFtY0mHIcLp0HYWSUEn19znUXT3fMsAR+yhfrNs3LVmwLieHom++pWjZMvRXf7GraGw53ted/4SmU2hv2Jg4pE0IMeExjAkcg5WZ1W2vd61VMGFXGpekVVAIcQeNn3O/ytXVlYkTJzb7QObMmcPp06fZv39/s1+7qebNm8dLL71k/Lq0tBQ/Pz8TjkgIIURzqK3X89Why3y8/TxlNYb1OY919WHuqDA8Ha1NPLpHR21VJQk7tnAsbg3lhQUAWNnZ0WX4ODoER1F7tIiq7w3FFyqw0bqgifLFyr9prfxViVfXY228vh6r1suFrb0t+T4olxpLwz0G+g4kRhtDb8/edyzi6ut0XDiaS8Kuhq2C3iFOdBzkK62CQoibNLnYagm//e1v2bBhA3v37sXX19d43NPTk9raWoqLixvMbuXk5ODp6Wk8Jz4+vsH1cnJyjN+79s9rx248x8HB4aZZLQArKyusrG7/Gy0hhBAPnt1nc3lrQxKX8ioA6OjjyPzxWrq3lSj3+6WytITjm9ZxfMsGaioMr4OmjTPdR08kxLUHVYdzKT9pCKTA7FqyoA8Wbo3fXsawHmsPhbGxVN7w+aA43IelXSrY5V+MolZhbWbD1OAJPBX+FAGOAXe8ZnlRDaf3ppO0P7Nhq2AvDzoN9sXVV1oFhRC3ZtJiS1EUfve737F69Wp2795NQEDDv+y6d++OhYUFO3bsYPLkyQCcPXuW1NRUIiMjAYiMjOTtt98mNzcXd3d3ALZt24aDgwNardZ4zsaNGxtce9u2bcZrCCGEeHil5Ffw1w1J7EjOBcBVY8kfR4Yxpbsvaolyvy9KcnM4umEVp3dtp77WsCa6jZcPPUdPxs+iPZWHsikrMxRZKmszNH280fRrWrKgvrKSkrVrKYxdTO2VawWbGVd6+vA/bS7JHoZfurrbevBk2JM8Hvo4jlaOt72eoihkXywhYVc6l45Lq6AQ4u6YdJ+t3/zmNyxZsoS1a9c22FvL0dHROOM0e/ZsNm7cSGxsLA4ODvzud78D4ODBg4Ah+r1Lly54e3vz/vvvk52dTUxMDM8991yD6PcOHTowZ84cnn32WXbu3Mnvf/974uLiGhX9LmmEQgjx4CmvqeeTnef5v/0p1OkUzNUqnunXjt8NDcHBWqLc74e81MscWbuC5IN7UfSG+HaPwBB6j5yCW6UnFT/kXE8WdLBE098Hu96eTUoWrMvJpWjJEoqXLkV3dT2W3s6GHyNd+F/7LAocDAV1hEsEMdoYRrQbgYX69q//nVoFOw32JaCztAoK8ah7YDY1vl1f9KJFi4wbDl/b1Pi7775rsKnxtRZBgCtXrjB79mx2796NnZ0ds2bN4t13371pU+MXX3yRpKQkfH19ef3112VTYyGEeAjp9Qqrjmfw3uZk8soMsyhRoW68Pk5LsLvGxKN7NKQnJ3Jk7Qou/Xg9Vr1tp670GvQYmiwNlcdzQWf4+GHubot9VNOTBavPnKEwdjElGzfC1c2Oaz3bsLmnOctDC6mxVKFWqRniN4QYbQxd3bvecT3WtVbBxH2ZVJdLq6AQ4vZatNh66623eOWVV7C1bdg/XVVVxQcffMAbb7zR9BG3clJsCSHEg+FEWjFvrkvkZFoxAO1cbHl9nJYhYe4S5d7CFL2eS8ePEL9mBZnnzhgOqlSE9ulPj17RWFyA6qQC4/mW7RyuJgs6o2pkO6ei11O+dy+FsYupPHzYeLyovSffdalgT7tKFLUKOws7Hgt+jKfCn8LX3vf217uhVfDi8TyUG1oFOw7yRdvPG2uNzIIKIRpq0WLLzMyMrKws4/qoawoKCnB3d0en0zV9xK2cFFtCCNG65ZZW897ms6z80ZAuZ2dpxu+GhvBMv3ZYmUuUe0vS1ddz9uBe4teuoCDdsHeVmbk5EQOH0aXDCJSEKmqvXN2vUgXW4S7YR/li1bbx/z/VV1UZ1mMt/oralBQAFDM1l7t787+IXM55GloUfTQ+TA+bzqSQSWgsbz+LWV+n4/yRXBJ2pZGfVm487h3iRKchvgR0klZBIcTtNfumxjdSFOWWvx08efKkcTNiIYQQ4n6oqdex6MBlPtlxnopawy/7JnfzZe6o9rg7SJR7S6qrrubUrq0c3bCasvw8ACxtbOg8dAwR/gOpO1ZEzfqrScBmKuy6XU0WdG98smBd7tX1WN81XI91pLcTsWG5FDga9tPs6t6VGG0MQ/yGYKa+fXFdXlTN6T0ZJO6XVkEhxP3R6GKrTRvDBoIqlYrQ0NAGBZdOp6O8vJznn3++RQYphBBC3EhRFHYm5/KXDUlcLqgEoLOfE/OjtXT1b2Pi0T3cqspKObEljh83r6e6zDBjZevoRPcREwl26kp1fD5ViZkAqKzM0PTxMiQLOjR+S5Xq5GTDeqy4OON6rBoPJzb2VLM6tIRqqzzMVRaMbjecmdqZdHDtcNtrKYpC1sUSTv20VdDZio5R0ioohGhZjS62PvroIxRF4dlnn2XBggU4Ol6PS7W0tKRdu3YSpS6EEKLFXcwr5631Sew5Z5hNcbO3Yu6oMCZ19ZEo9xZUmp/Hsbg1nNqxhbqaagAcPTzpNWIyvqoQqo7kUlltKLLUDpbY97uaLGjduI8ail5Pxb59FMTGUnno+nqswlAPvutczt7AMhS1CgdLR6aHTuHJsCfxtPO87fWkVVAI0Ro0utiaNWsWAAEBAfTr169B0p8QQgjR0kqr6/jn9vPEHrxMvV7BwkzFs/0D+N2QEDRNiAoXTVOQnsaRdSs5s38X+qvrst3aBdJ7yGTcyjypPJRHpS4LAHM3G0OyYBf3RicL6qurKVm7jsLFi6m9dAkwrMe61NWDRRH5nPM2hGq0cwhgRvgMooOisbW4fSvi7VoF2/fyoONgP1x9JZFSCHH/NPn/Tvb29pw5c4aOHTsCsHbtWhYtWoRWq2X+/PlYWsoGf0IIIZqPXq+w/FgaH2w5S355LQBDw9x5bZyWAFc7E4/u4ZV5Lpn4tSu4ePT6LJOftiO9+hni26t3F1CpGDaKtmx7NVkwrPHJgvV5eRR99x1F3y1FV1QEgN7Wmh96OvB1RAH5joaZy95evZmpnUl/n/6oVbcu4K61CibsTOfSCWkVFEK0Hk0utn7961/zpz/9iY4dO3Lp0iWmTp3KpEmTWL58OZWVlXz00UctMEwhhBCPomNXCpm/LolTGYZwhEA3O14fp2Vwe/efeaS4G4qicPnkj8SvXU560mnj8eAekfTsFo35BYXa7aVUY9i/zDrc2ZAs2M7xdpe8SfXZcxQuXsz/Z+++w6Mq0z6Of2cmvfdeCOkJhJLQS0KRJiCKoghBhFdXXVldy7ooSrEra1l1bQsEC7LSS+gldAi9JQECBEhIAuk9mcyc94+DA5GOYCj357q8LnPmzDnPRGHmnuf33E/ZokUo59Zj1Xg4siQOFkRUUG1ZhLnWgkFN72d45HDCXcIvey01KpjPvrXZDaKCvmFOxHTzp0mMq0QFhRCN6rqLrcOHD9OyZUsAZs2aRXx8PDNmzGDTpk089thjUmwJIYT4w/JKa/hgaTrz96hrgOwtzXihZygjOjTB4jo2vhXXxmgwcGjrRrYvmM3ZE2prda3OjKjO3WgZ1gtlfxX1K0upA9BpsGnlgX1Xv2vuLKgYjVRu3EhRUhKVm7eYjheGuDOjRTmbQiowajW4WLkyMvxRhoQPwc3a7bLXKy+q4cD6HNJ+HxVs50XzBD+JCgohbhs31PrdaFT3s1i1ahX9+/cHwN/fn4KCgps7OiGEEPeUGr2BKRuP89XaTKrqDGg0MCTWn1d6h+Nuf+3d7MS10dfVcjBlNTsWzaH0jNqm3dzSihbd+hLt3Rn97hL0q9T3do2lDtt23th38kHneG3/LYw1NZQuXKjuj3X0KACKVsPRlu4kRRdy2E+ND4Y4hTIiagT9mvbDUnfpayuKQm6mugGxRAWFEHeK6y624uLieOedd+jZsyfr1q3j66+/BuD48eN4enre9AEKIYS4+ymKwoq0fN5NTudkkdrKvXWAExMGRhPj59S4g7sL1VRWsHfFEnYtXUhVaQkAVvYOxPV8gBDbVtTsLKTmkLoeS2tvjl0nX+zae19zZ8H6ggKKZ/xC8S+/mNZjGawt2RZnx8/NSjjrVARo6OLbhcSoRNp7t7/kHp4A9XUGjuyQqKAQ4s503cXWZ599xrBhw5g/fz5vvPEGISEhAMyePZuOHTve9AEKIYS4ux3JL2fS4jQ2HFFnUDwdLBnbN5IHWvpc9gO4uDEVRYXsXLKAfauWUlddDYC9mzvtuj+MnzGY6r0FVNerM1xm7tbYd/XDptW1dxasOXxuPdbCC9ZjuduzOBYWRVVRbVmKlc6aIcEDGRY1jKaOTS97LVNUcMNpairVa5n9tgFxd39cfSUqKIS4/WkURVFuxoVqamrQ6XSYm999U/hlZWU4OjpSWlqKg4NDYw9HCCHuCqVVej5ddZgft57AYFSw0Gl5qmsQzyWEYCut3G+qotM57Fg0h7T1azDU1wPg6hdA+4RHcCvxoCatCM59GrAIsFc7C0a6XlNnQUVRqNy4SV2PtWmT6XhhUxdmtKxkU2g9Rq0GD2sPhkYO5eHQh3GycrrstdSo4CmO7SloGBVMOBcVtL37PmcIIe4s11Mb3PC72c6dO0lPTwcgKiqK1q1b3+ilhBBC3EMMRoX/bT/F5BWHKKpUW7n3ivJk3P1RBLheW8MFcW3yjh5h+4LZHE7dDOe+W/UJi6J9uwexzbGhblMZNRQBYBWhdha0aOJwTTOKxtpayhYtomj6dGqPZALqeqwjMa5Mb17MEb8yAKJdm5EYlUivJr0w1166UKqvM3B4ez77U34XFQx3IiZBooJCiDvXdRdbZ86c4dFHH2XdunU4OTkBUFJSQrdu3Zg5cybu7u43e4xCCCHuEqnHi5i46CAHT6sfxEM87Bg/IIouofLecbMoisLJ/XtJXTibk/v3mI4Ht2pLXPP+mB9R0G+soo4y0GqwaemOfbwf5p7XtmdZfWEhxb/MpHjGDAxFaqFmsLZgS2sbfokp56xTCVqNjp7+3UmMSqSVR6vLFm/lReoGxGkbfxcVbOdFTDc/iQoKIe54111sjRkzhoqKCg4ePEhkZCQAaWlpPPHEE/ztb3/jl19+uemDFEIIcWc7XVLN+0szWLT3XCt3KzP+3jOMxA6BmMuMxU1hNBrITN1C6oLZ5B9TZ5o0Wi1RHbrRIqgnHKjGsKESPaCx0GHbzgu7zr6YXWNnwdojRyj64QdKFyxEqVNnJKtd7Vgca2RxdC3VVhXYmtsxPORBHo98HH97/0teR40KlqgbEO89HxW0d7GiWYKvRAWFEHeV616z5ejoyKpVq2jTpk2D46mpqfTq1YuSkpKbOb7bgqzZEkKIG1OjN/Dd+mP8JyWTGr0RjQaGtg3g5fvCcLWTVu43Q71eT9r6NexYNIfiXLWYNbOwpEWXPkS5d0S/rwylWl2npbW7oLOg9dW/b1UUhcpNmymaPp3KDRtMxwuaODOjVQWbw4wYtRp87Xx5POJxHgx9EHsL+0uP81xUcN/abAqzfxcV7OZPkxg3tNewRkwIIRrbLV2zZTQaL9kEw9zc3LT/lhBCiHuboigsO5DHO8np5JSoXe/aNnFh/MAoon0cG3l0d4faqir2rVrKziULqCw+t+7K1o64hEE0tWxO7f4S6o6px83crLHr6ottK0805lefSTTW1lK2eDFFSdOpPXIEAEWj4XBzZ35qUcoh3zLQaGjl0ZrEqES6+XfDTHvpjxSXjQq29yImQaKCQoi723UXW927d+eFF17gl19+wcfHB4CcnBz+/ve/06NHj5s+QCGEEHeWjLwyJi5MY8uxQgC8Ha14vV8k/WO8pZX7TVBZUszuZYvYszyZ2qpKAOxcXGnX9WF89UHUphdTq6hFlrm/PQ7xflhFXVtnwfqiIop/+YXiGb9gKFT/+xmszNnUyppZLSrJdy7DTGNO3yb3MSJqBM3cml3yOg2ignvO/tabQ6KCQoh7znUXW19++SUDBw6kSZMm+PureexTp07RrFkzfvrpp5s+QCGEEHeGkqo6Pll5mJ+2nsCogKWZlr90bcozCcHYWEgr9z+qJD+PHYvmciBlJYZze1g5+/jRseMjuBS5Ube3jFrUDYStwp2xj/fHIujaOgvWZmZSNP0HShcsOL8ey8WWRa2NLGleR5VVFQ4WjowKe5ihEUPxsvW65HVMUcE12RTmXBgVdCamm59EBYUQ95zrfvfz9/dn165drFq1ioyMDAAiIyPp2bPnTR+cEEKI21+9wcgvqSf518rDlFSpRUDfZl683i8Sfxdp5f5Hnck6xvaFczi0eQOKosb1vYPDad/6QWyyranf+bvOgl39MPe6emdBRVGo2rKFwqQkKtefX491NtCRmS0r2Rxeg0GnIdChCcMjhzMweCA25pf+76lGBbM5uPE0tZXq+jCJCgohxE3c1PhuJg0yhBDi0rYcLWTiooNk5JUDEO5pz/iBUXQMdmvkkd3ZFEUhO/0AqQtmk7Vnp+l405g4YsPvxzxTwVBSC4DGQottW2/sOvtg5mR11Wsb6+ooW5xMUVIStYcPq/fTaDjUzIEZLSrI8AM0Gtp5tyMxMpEufl3Qai5e56UoCqePlLBvbTbHfxcVbJ7gR2Qnb4kKCiHuSrekQcaaNWt4/vnn2bp160UXLS0tpWPHjnzzzTd06dLlxkYthBDijpFdXMV7S9JZsj8PAEdrc17uFcbjbQMwk1buN0wxGjm6M5XUBbPIPXIIAI1GS2TbeFr4dYeMGow7ajBwrrNgRx+1s6DN1Yua+uJiSmbOpOjnGRgKCgB1PdbGlpbMblFNvksl5loLBjW9n+GRwwl3Cb/kdfR1Bo6knusqKFFBIYS4omsutj777DOeeuqpS1Zvjo6O/OUvf+GTTz6RYksIIe5i1XUGvl53lG/XHaW23ohWA8PaBfLSfWE421o09vDuWIZ6Pekb17F94RyKck4BoDM3p1WnfkQ4tkOfVo7xjFrYmLlaYdfVD9vWHmjMdVe9du2xY+p6rPnzUWrV2bBqZxsWtq5nWXMDldY1uFi58mz4owwJH4Kb9aVnJS8XFQxv70VziQoKIcQlXXOxtXfvXj788MPLPt6rVy8mT558UwYlhBDi9qIoCov35fL+knROl9YA0L6pC+MHRBPpLfHqG1VXU83+1SvYkTyPikJ1tsnC2oa2nQfRxLwZ+oxS9EopAOZ+dtjH+2Ed7XbVzoKKolC1dau6HmvdetPxM/72zGxVxZaIWgw6DSFOoYyIGkG/pv2w1F2875miKJw+XMK+lN9FBV3PRQU7SlRQCCGu5JqLrfz8/Evur2W6kJkZZ8+evSmDEkIIcfs4eLqUiYvSSD2uthP3dbLmjfsj6dvMS1q536CqslL2LF/M7mWLqalQ17vZOjnToeMjeNUEoM8sR49aZFmGOWMf74dlU8er/r6NdXWUJS9R12MdUmOIikZDRpQ9M1tWku5fBRoNXXy7kBiVSHvv9pe85vmo4CkKcypNx/0inGmeIFFBIYS4VtdcbPn6+nLgwAFCQkIu+fi+ffvw9va+aQMTQgjRuIoq65i84hAzU09iVMDKXMuz8SH8Jb4pVtcQXxMXKys4w47F89i/ZgX15yJ9zp4+dGz7CE4FLtSnV6GnHLRg08IDu65+WHhfvbNgfXExJf/7H0U//4zh7Ln1WJZmbGhhwdxWteS5VGGls2ZI8ECGRQ2jqWPTS4+vsFrdgHjTBVFBCy3h7SQqKIQQN+Kai61+/frx5ptv0qdPH6ysGnY7qq6uZvz48fTv3/+mD1AIIcSfS28w8tPWE3y68jBlNeoH7v4x3oztF4mvk3Ujj+7OVHDqBNsXziFj0zqMBgMAXk3CaB/zIDbZlhgO1FJPFRpzLbZtvbDr7IuZ89U7C9YeO07RD9Mpnb8ApUaNd1Y5WbOoVT3LWhiptK7Dw9qTFyKH8nDowzhZOV10DVNUcG02x/dKVFAIIW6ma279np+fT+vWrdHpdDz//POEh6tdijIyMvjqq68wGAzs2rULT0/PWzrgxiCt34UQ94qNRwqYuOggR841Y4j0dmDCgCjaNXVt5JHdmXIOpZO6YBbHdqaajjWNjiW2aV/MjikYq9RiVmurdha0be+N7iqFjaIoVG1LpSgpiYqUFNPxM352/K9VFZsjNRh0GqJco0iMSqR3YG/MdRdfU19n4PC2PPanZF8UFYzp5kdgc4kKCiHEpdyS1u+enp5s3ryZZ599lrFjx/JbjabRaOjduzdfffXVXVloCSHEveBkYRXvJKexIi0fAGcbc17pHc5jbQLQyQfu66IoCsf37CB1/mxyMg6qBzUaolsn0NwrHo7UohzQYwR0LlbYd/XFNtbzqp0Flbo6ypYupTBpOrXp6abjaZG2/NqqmrSAajQaHd0DupMYlUhrj9aXXI9VVnBBVLDqgqhge2+aJ/ji6iNRQSGEuFluaFPj4uJiMjMzURSF0NBQnJ2db8XYbhsysyWEuFtV1tbzn5RMvt9wnLp6IzqthsT2gfy9ZxiO17B3kzjPaDBwaMsGUhfMpuBkFgBanRmt291PmH0shiOVcO4d19z3XGfBZlfvLGgoKaH4f79S/NNP1J9rRGWwMGNDjBnzWuvJddVgY2bDQ6EP8Xjk4/jb+190DUVRyDlcwv7fRQUd3NSoYEQHiQoKIcS1uiUzWxdydnamTZs2NzQ4IYQQjU9RFBbsOc37S9PJL1MbNXQOceOtAVGEedo38ujuLPraGg6krGLHonmUnVVnBs2trGnX/iECNeHUZ1ViyFVjepZhzth39cMy+OqdBWuPH6fohx8onTf//HosRysWtaxneUuFCpt6fGx9eSXycR4KfQh7i4v/u/0WFdy3Npui0xIVFEKIP9sNFVtCCCHuXPuzS5mw6CA7TxQD4O9izbj7o+gV5Smt3K9DTUUFe1Yks2vpQqrL1DbtNg5OdGz7CB6VvhhOVFNPJWjBOsYd+65+WFwloqcoClWp28+vxzo3BZXva8OvrWrYHKXHoNPQyqM1wyOH0z2gO2bai9/KJSoohBC3Bym2hBDiHlFQUcvHyw7x685TKApYm+t4vnsIozsHSSv361BeVMDO5AXsW7UMfU01AE7uPnRs9TBOBU4YjtZioFrtLNjmXGdBlyt3FlTq6ihbtozCpCRq086vxzoYYc3s1rUcDKhFpzWnV5NeJEYm0ty9+cXXOBcV3LfmFFn7CiQqKIQQtwEptoQQ4i5XV2/khy1ZfL7qCOW16izHoJY+/LNvJF6OV28vLlRFp7PZvnAuaevXYDSov0evgDDaRz6AdbYFxiP1GKhFa2uGXQcfbDv4XLWzoKGkhOJfZ6nrsc6cUY9Z6FjfXMf8WAO5rnrsLRwZFfYIQyOG4mXrddE19LUGDqdeJirY3Z/AZq4SFRRCiEYixZYQQtzFUg6dYdLiNI6dVT+EN/d1ZMLAKGIDXRp5ZHeOvMzDpC6czZHULaZYX9PwOFoH9sIsS0E5bMRIvdpZsIsvNrGeaC2uPFNYl5VF0Q8/UjJvHkq1OjtW5WDJolb1rGgJ5TZGAh2a8EbkcAYGD8TG3Oaia5QVVLN/XQ7pv4sKRrT3pnmCHy4+V98MWQghxK0lxZYQQtyFsgoqeSc5jVXp6myJq60F/+gTzsOx/tLK/RooisKJ/XvYvmAWJw/sMx1v1rIH0a6dIKsWjhhQAHMfW+zj/dXOgrrL/24VRaF6xw4Kk6ZTsWbN+fVY3mpUcFNUPfVmGtp5tSMxKpEufl3QarQXXSPnUDH71mZfMioY2dEbS+kiKYQQtw0ptoQQ4i5SUVvPF2uOMHXjcfQGBTOthpEdm/C3nqE4WMmH8KsxGg0c2baF1AWzOHP8KABanY7Y2P6EWLXEeKoGStXujZahTmpnwRCnKzYWUfR6ypYtpygpiZqDB03HD4ZZMSe2jgOBdZjrLLk/qB+JUYmEu4RfdA19rYFD5zYglqigEELcOaTYEkKIu4DRqDB3dw4fLsvgbLlaDMSHufNm/yhCPKTz3NXU19WRtn4N2xfNoSQvFwAzSys6xA3GzxCMMb8WIzWguaCzoO+Vf6+G0lJKZs2i6MefqM9XW8IbzHWsb65lYayRHLd6XKzceCZ8CI+GP4qbtdtF15CooBBC3Nmk2BJCiDvcnlMlTFh4kD2nSgBo4mrDm/2j6B7hIa3cr6K2qoq9K5ewa8kCKkvUVvg2dk50in0EtzIvjKfrMFKLxlyLTZwn9l38rtpZsO7kSXU91ty5KFVVAFQ5WLCoZT0rWkG5jUKIUygToxK5v+n9WOosGzxfooJCCHH3kGJLCCHuUGfKa/ho2SFm78wGwNZCx5geoTzZqQmWZtLK/UoqS4rZtXQhe1csobZKjeU5u/rQsflg7M86oJysx0gdWhszbDv4YNfBG52dxWWvpygK1bt2UZSURPmq1ab1WHlealRwU5SBejMtnX07kxiVSAfvDhcVwpeLCvpHOhPTzZ8AiQoKIcQdR4otIYS4w9TVG5m26ThfrMmk4lwr94da+/LPPhF4OEgr9yspyctlx+K5HEhZhUGvB8DHN5y2oQOwyjVHOWFEoR6dk6XaWbCN1xU7Cyp6PWXLV1A0fTo1+/ebjh8MtWRurJ79TfRYmdnwYPAAhkcOp6lT04uuUVZQzf6UbNI3556PClrqiGjvpUYFvSUqKIQQdyoptoQQ4g6yJiOftxenc7xAnflo4e/EhAFRtApwbuSR3d7OZB0jdcFsDm/ZiKIYAQgJaUNL3x7oshU4AQpGzL1tsY/3w7q5+xU7CxrKys6vx8rLU4+ZadX1WHEKOW4G3K09+VvEUB4JewQnK6cGz1cUhexDxexfm83xfQUgUUEhhLgrSbElhBB3gKNnK3h7cRoph84C4G5vyWt9Iniola9Eyy5DURSy0/aTumA2WXt3mY7HNOtJpGM7OF0PJ9UqxzLkXGfB0Ct3Fqw7dUpdjzVnzvn1WPbmLGppYGUrDWW2EOkSxV+jEunTpA/muoYF02WjglEuxCT4SVRQCCHuMlJsCSHEbaysRs8Xq48wbVMW9UYFc52GUZ2CeL57CPbSyv2SFKORzJ3b2D5/NrmZhwDQanS0aTWQILNolLN6qKxXOws2d1M7C/rZX/56ikL17t0UTUuifPVqMKozY3meFsyLrWdjtJF6Mx3dA7qTGJVIa4/WFxVsEhUUQoh7kxRbQghxGzIaFWbvzOaj5RkUVNQB0D3Cg3H3R9LUXVq5X4qhXk/6hhS2L5xD0Wm1aYiFuTUdWg/Gu64JSrEeBT2YabGN88S+iy9mrtaXvZ5SX0/5ihUUJk2nZt/5jY0PhJgzL87A/iYGbMzteDT0IR6PfBx/e/+Gzz8XFdy3Jpus/Q2jgjHd/Ino6I2ltbwNCyHE3Uz+lhdCiNvMzhPFTFx0kH3ZpQA0dbPlzQFRdAv3aOSR3Z7qaqrZv3o5O5LnU1FYAICdrQsdYwbjUuaOcsaAgh6NtRl2Hbyx6+hzxc6ChvJySmbNpuinH6k/re65ZTDTsq6ZhsVxkO2u4GPrxyuRj/NQ6EPYWzScFfstKrhvbTbFub+LCnbzIzDaFY1EBYUQ4p4gxZYQQtwm8stq+GBpBvN25wBgb2nG33qE8kTHJliYaRt5dLefqrJSdi9bxJ5li6mprADA1cWf9hGDsCuwgzwjCgZ0TpbYdfbFto0XWsvLdxasy86m+McfKZk1G+O59ViVdmYktzSyorWGMlsNLd1b8veoRLoHdMdM2/At9HJRwcj2XjTv5oezl0QFhRDiXiPFlhBCNLIavYEpG4/z1dpMquoMaDTwSKwfr/aOwN3e8uoXuMeUnT3DjsXz2L9mBfV1tQD4+0QR26QvlvnmkKsARsy9znUWjHFDo7t8sVq1ezdFSdMpX7ny/HosDzUquDFawWhuTq/AXiRGJdLcvXmD5142KuhuTUyCn0QFhRDiHteo7wDr16/n448/ZufOneTm5jJv3jwGDRpkenzkyJFMnz69wXN69+7NsmXLTD8XFRUxZswYFi1ahFarZfDgwXz++efY2Z1f07Bv3z7++te/sn37dtzd3RkzZgz/+Mc/bvnrE0KIK1EUhZVp+byTnM7JInUmpXWAExMGRhPj59S4g7sNFZzMYvvCOaRvWodyrigKC2pPjGc8unwgF0DBsqkj9vF+WIY5X7azoFJfT/mqVRRNS6J6717T8QPBZiyIM7I3yIi9pSPDwx7m8YjH8bL1avD8y0UFA6JcaC5RQSGEEOc0arFVWVlJixYtGDVqFA899NAlz+nTpw/Tpk0z/Wxp2fBb3mHDhpGbm8vKlSvR6/U8+eSTPP3008yYMQOAsrIyevXqRc+ePfnmm2/Yv38/o0aNwsnJiaeffvrWvTghhLiCI/nlTFqcxoYj6hojTwdL/tk3gkEtfa/YevxelJORRuqCWRzbtR0ADRpaRvYizDYWTaER8lE7CzY711nQ//KdBQ0VFZTMnk3xDz+iP31aPWamZX00LG6j4ZQ7BDoE8XrkMB4IfgAbc5sGzy89W83+ddmkb8qlrlqNCpr/1lVQooJCCCF+p1GLrb59+9K3b98rnmNpaYmXl9clH0tPT2fZsmVs376duLg4AL744gv69evH5MmT8fHx4eeff6auro6pU6diYWFBdHQ0e/bs4ZNPPpFiSwjxpyut1vPZqsP8sOUEBqOChU7L/3UJ4q/dQrC1lLjZbxRF4fjuHaQumEVORhoAWq0Z7ZoNJEATAWUGqDGCmQbbWE/suvhh7nb5zoJ12TkU//QTJbNmYaxUZ6Iqbc1Y0tLAilgNpbYa2nq15R9RiXT164pWcz52qCgK2RnF7FsrUUEhhBDX57Z/d0hJScHDwwNnZ2e6d+/OO++8g6urKwBbtmzBycnJVGgB9OzZE61Wy7Zt23jwwQfZsmULXbt2xcLifOep3r178+GHH1JcXIyzs/NF96ytraW2ttb0c1lZ2S18hUKIe4HBqPC/7aeYvOIQRZVqK/f7ojwZd38kga4yG/IbQ309h7ZsYPuC2RScOgGAlbkt7Zs/hGetP5QbAAMaqws6C9pfvrNg9Z49FCZNp3zFivPrsdzVqOD6aAUsregb1JfEqEQiXCIaPLeupp7D2/LYl5IjUUEhhBA35LYutvr06cNDDz1EUFAQR48e5fXXX6dv375s2bIFnU5HXl4eHh4NWyGbmZnh4uJCXl4eAHl5eQQFBTU4x9PT0/TYpYqt999/n4kTJ96iVyWEuNdszypiwsKDHDytfnET4mHH+AFRdAl1b+SR3T70tTUcWLuSHYvnUXb2DAAOtu50iHwQpzJXKDYCBnSOFmpnwbZeaC8zE6iux1pNUVIS1Xv2mI4fCNKxsI3C3qYKTlaujAofwmMRj+Fm7dbg+ZeNCnbwpnmCr0QFhRBCXLPbuth67LHHTP/evHlzYmJiCA4OJiUlhR49etyy+44dO5aXXnrJ9HNZWRn+/v5XeIYQQlzsdEk17y/NYNFedW2QvZUZf+8ZRmKHQMyv0B3vXlJdUc6e5YvZvXQR1eVqMerhEkTb4P7YFtlAIYARM08b7OP9sGnhftnOgoaKCkrnzKHohx/R56jt8w1mGtZHQXIbLSc9NIQ4hTIhKpF+Qf2wMrMyPfdyUUFHd2uaS1RQCCHEDbqj3jmaNm2Km5sbmZmZ9OjRAy8vL86cOdPgnPr6eoqKikzrvLy8vMjPz29wzm8/X24tmKWl5UWNOIQQ4lrV6A18t/4YX6ccpVqvtnJ/rE0Ar/QKw9VO/m4BKC8sYGfyfPatWoa+tgaAJl7NaeXXC4tCM1D7hmARpHYWtAq/fGdB/enTFP14bj1WhbrfVqWNjqWtjCxvraXUTkNn3868EZVIB+8ODa5jigquzaY4r8p0PCDaheYJEhUUQgjxx9xRxVZ2djaFhYV4e3sD0KFDB0pKSti5cyexsbEArFmzBqPRSLt27UznvPHGG+j1eszNzQFYuXIl4eHhl4wQCiHEjVIUhWUH8nh3STrZxdUAtGnizPgB0TTzdWzk0d0eCnNOqe3bN6RgNKgRvcjAzkS7dkRXrFFnsjRgHe2KXVc/LAMcLnut6n37KEpKomz5CjAYAMhz07EgTmF9M9BZ2TIgeADDI4fT1Klpg+eWnq1if0oO6ZslKiiEEOLWadRiq6KigszMTNPPx48fZ8+ePbi4uODi4sLEiRMZPHgwXl5eHD16lH/84x+EhITQu3dvACIjI+nTpw9PPfUU33zzDXq9nueff57HHnsMHx8fAB5//HEmTpzI6NGjee211zhw4ACff/45n376aaO8ZiHE3Skjr4yJC9PYcqwQAG9HK8b2i2RAjLe0cgdyjxwidcFsMndsBUVBi47YsL4EW7VAU65AMWpnwdae2HXxxdzd5pLXUQwGylevpihpOtW7dpmOH2iiZVEb2BMMbjaePBsxlEfCHsHJyun8cxWF7PRi9qVcIirYzY/IDt5YSFRQCCHETaRRFEVprJunpKTQrVu3i44/8cQTfP311wwaNIjdu3dTUlKCj48PvXr14u233zY1uAB1U+Pnn3++wabG//73vy+7qbGbmxtjxozhtddeu+ZxlpWV4ejoSGlpKQ4Ol/+WVQhx7ympquOTlYf5aesJjApYmGl5pmtTnkkIxsbi3v7grigKJ/buInXBbE6l7QfAXGtJ28iB+CkhUK12B9RY6bBr74Ndp8t3FjRUVFI6dy5FP/6I/tQp9ZhOw4Zz67FOeGqIdIkkMSqRPk36YK4zNz23rqaeQ1vz2J9ycVQwpps/AVEuEhUUQghxza6nNmjUYutOIcWWEOL36g1Gfkk9yb9WHqakSg9A32ZevN4vEn+XS8/K3CuMBgOHt20idcFszmYdA8DGwpH2EYNwr/EGvfq2o3OwwK7LlTsL6nNzKfrpJ0p+nYWxvByAKhstS1sqLI/VUmqnpZt/NxKjEon1jG0wi3jZqGBHb5rHS1RQCCHEjbme2uDe/tpVCCFuwJajhUxcdJCMPPXDf7inPeMHRNExxO0qz7y71dfVcXDdKnYsmkdJfi4ALrY+tAsbgEOZE5QDKJh5XNBZ0OzSnQWr9++nKGk6ZcuWnV+P5apjUZzCuuYazKzteDD0QYZFDMPf4Xy3WFNUcO0psg4Uno8KelgT082PiPYSFRRCCPHnkXccIYS4RtnFVby3JJ0l+9V9/BytzXnpvjCGtQvA7B5u5V5bVcmeFUvYtWQBVaUlAPg4hxEX2AfrUmtQD2HRxAH7BH+swpwvGdtTDAbK16xR12Pt3Gk6fqCJlsVxsDsEvOx8+VvkMB4KfQh7C3vTOZePCroS081PooJCCCEahRRbQghxFdV1Br5Zd5Rv1h2ltt6IVgOPtwvg5fvCcba99Bqje0FFcRG7li5k74ol1FWrBU6wVywxnglYlJlBKaABqyhX7Lv6YRl46aiFsbKSkrnzKPrhhwbrsTZGwuK26nqsFu4t+DgqkR4BPTDTnn/rKj1bxf61OaRvPk1djToDZm6ldhWMSfDDyfPejnQKIYRoXFJsCSHEZSiKQvL+XN5LTud0qboXVPumLowfEE2k9727frM47zQ7Fs7l4LpVGOrr0aKjuX8C4Y5t0VVqoAzQness2PXynQX1eXkU//QTxb/OwlimbmhcZa1lWSuF5a21lDmYcV/gfbwXlUiMe4zpeYqicCq9iP1rsxtEBZ08bWie4CtRQSGEELcNeTcSQohLOHi6lImL0kg9XgSAr5M1b9wfSd9mXvdsK/f8Y5mkLpjNkW2bURQj5hoLYoMH0MQiCk0NUAkaSx127b2x6+SLzuHSs37VBw6q+2MtWwb1auOKPBe1dfv6ZhosbB15OOxhhkYMxdvO2/S8K0YFu/sREClRQSGEELcXKbaEEOICRZV1TF5xiJmpJzEqYGWu5Zn4YP7SNRhrC11jD+9PpygKpw7uI3XBbE7s2w2Alc6OtqH98TY2UTsL1oDWwQL7zuc6C1pd/NaiGAxUpKRQNC2Jqh07TMcPBmhY3FbDrhAN/g6BvBw1nAeCH8DG/PxsWMmZKg6kXBwVjOzgTXOJCgoBgNFopK6urrGHIcRdw8LCAq32j6/HlmJLCCFQW7n/tPUEn6w8TFmNOttyf4w3r/eLxNfJupFH9+czGg0c3b6N1AWzyDt6BAAHCzfahQ7ApcYDakHtLGiNfVc/bFp6XLKzoLGqipJ559ZjnTgJgEELmyI1JLfVctxLQ1uvtvw7KpGufl3RatRr/BYV3Lc2mxMSFRTiiurq6jh+/DhGo7GxhyLEXUOr1RIUFISFxR9bmy3vVEKIe96mzAImLjrI4fwKACK9HRg/IIr2TV0beWR/vnq9nvQNa9m+cA7FuTkAeNgGEhfUD/tKBziX3rMIdMA+3g+riEtH9/T5+RT/9DPFv/6KsbQUgCorDctbwbJYLeWO5vQL6sdHUYlEuESYnne5qGBgM1ead5OooBC/pygKubm56HQ6/P39b8o38ULc64xGI6dPnyY3N5eAgIA/tHxAii0hxD3rVFEV7ySnsfxgPgDONua83CucoW0D0N1jH+jrqqvYt2oZO5PnU1GsrlMLdI6mpW9PrCqtoFI9T+0s6ItlE8dLXqf64EGKpk+nbMnSBuuxkuMgpbkGG3sXhoQP4bGIx3CzPr8vmUQFhbgx9fX1VFVV4ePjg42N/DkR4mZxd3fn9OnT1NfXY25ufsPXkWJLCHHPqayt5+uUo3y34Rh19UZ0Wg2J7QN5sWcoTjb3Viv3qtISdi1dxJ4Vi6mtrESLlgjPdkS5dca8ykwtsnQabFp5YN/VD3OPiz/MKUbj+fVY27ebjpvWYwVraOocwtioRO5vej9WZlbnnqdwKuNyUUE/Ijp4YXGJ9V9CiPMM5zb9/qNRJyFEQ7/9mTIYDFJsCSHEtVAUhYV7T/P+kgzyytRW7p1CXHmrfzThXvZXefbdpfRMHjsWz+PAmpXU6+sw01jQ0v8+Qm1boa3VQJXaWdC2vTf2nXzQOVhedA1jVRUl8+dTPP0H6k6cANT1WJsjNSxuo+W4t4ZOvp34JnIEHXw6mGIYv0UF963NpiS/YVQwppsf/hIVFOK63atdUoW4VW7WnykptoQQ94QDOaVMWHiQHSeKAfB3seaNflH0jva8pz6knD1xnNQFszm0ZQOK0YiVzpY2Qf3wNw9HowdqQWt/rrNgu0t3FtTnn6H4558p/t//GqzHWtFSXY9V6WzFgOABfBo5nGCnYNPzSs5UsT8lm4zNuQ2jgh29aR4vUUEhhBB3Hym2hBB3tYKKWiYvP8T/dpxCUcDaXMdfuwXzf12aYmV+b7RyVxSFnIyDpC6YzfHdatt1e3MXYkP64mHwQ2ME9GDmfq6zYKtLdxasSU+nKCmJ0iVLQa8HIN9Zw+I4DSkxGhwcPRgW8RiPhD2Cs5Wzem/jBV0FD0pUUAhx8yUkJNCyZUs+++wzAKqqqkhMTGTlypWUl5dTXFyMk5NTo45R3LvkHU4IcVfSG4xM35zF56uPUH6ulfsDLX34Z98IvB3vjVbuitHI0V3bSV0wi9zDGQC4WvkS16QvTrWuoNZLWATYYx/vj9Ul4nuK0UjFunUUJU2nats20/E0f0huq2VHiIYItyjGRyXSp0kfzHVqrr2upp6MLWpXwQZRweauxCRIVFAIASNHjqSkpIT58+c3OJ6SkkK3bt1uuEiaPn06GzZsYPPmzbi5ueHoeHFDn5EjRzJ9+vSLjh85coSQkJDrvqcQlyPFlhDirrPu8FkmLTrI0bNqC71mvg5MGBBNXBOXRh7Zn8NQX0/GpnVsXziHwmx1bytf+zBa+d2HbY3duT2ywCrSBft4v0t2FjRWV1O6YAFFSdOpy8pSr6uFLREakttoOeajJcE/gSlRicR5xpmimCX5alQwfUsu+nNRQQsrHRESFRRC/EmOHj1KZGQkzZo1u+J5ffr0Ydq0aQ2Oubu7X/f9DAYDGo1G2u6LS5JiSwhx18gqqOSd5DRWpZ8BwNXWgld7h/NInP890cpdX1PD/jXL2bF4PuWFZ9GiJdi5NTGe8VjUWkANamfBlh7Yd/XF3NP24mucOUPxjBmU/DITwwXrsVa2gGVxWqpcbHgw5EH+HTmMAIcAQI0KnkwrPN9V8BwnTxtiuvkR3l6igkKIG1NYWMjzzz/P+vXrKS4uJjg4mNdff52hQ4de8vyEhATWrVsHqA0O4uPjSUlJueS5lpaWeHl5XXT8k08+Ydq0aRw7dgwXFxcGDBjARx99hJ2dHQBJSUm8+OKL/PDDD/zzn//k8OHDZGZm4u3tzRtvvMEvv/xCSUkJzZo148MPPyQhIeGm/C7EnUne/YQQd7yK2nq+XJPJ1I3HqTMYMdNqeKJjE/7WIxRH6xtv13qnqC4vY/eyxexevpia8jLMNBY08+xChFM7dHU6qD3XWbCdF/adfNE5XtxZsCYjg6Kk6ZQmJ59fj+WkIbmNhpTmGpxdfBgZ8TgPhT2Eg4UDcJmooOaCroKX2fBYCHHrKIpCtd7QKPe2Ntfd9IZDNTU1xMbG8tprr+Hg4EBycjKJiYkEBwfTtm3bi86fO3cu//znPzlw4ABz5869oZb4Wq2Wf//73wQFBXHs2DGee+45/vGPf/Cf//zHdE5VVRUffvgh//3vf3F1dcXDw4Pnn3+etLQ0Zs6ciY+PD/PmzaNPnz7s37+f0NDQP/R7EHcuKbaEEHcso1Fh3u4cPlyWwZlyNRvXNcydt/pHEuJx97dyLys4y87k+exbvYz62lostTbE+fUlyLo52noN1IHW3hy7Tr7YtfNGa93wr3zFaKRywwYKk5Ko2rLVdDzdDxa31bIjVENzzxa8HZVIz4CemGnV518uKhjZ0YdmCb44XWIvLiHEn6NabyDqreWNcu+0Sb2xsbi+j5aLFy82zRj95re9wwB8fX155ZVXTD+PGTOG5cuX8+uvv16y2HJxccHGxgYLC4tLzlpd6d59+/Zl1qxZvPjii6ZjTZo04Z133uGZZ55pUGzp9Xr+85//0KJFCwBOnjzJtGnTOHnyJD4+PgC88sorLFu2jGnTpvHee+9dw29D3I2k2BJC3JH2nCphwsKD7DlVAkCgqw1v3h9Fj0iPu76Ve2H2SbYvnEP6xhSMBgN2Zs60bDIQH11TtbNgPZi5XdBZ0LzhOgJjTQ2lCxZSNH06dceOAep6rK3hGha31ZLla0bPwJ78GJVIC3f1g4RiVDhxsJB9a7I5eVCigkKIm6Nbt258/fXXDY5t27aN4cOHA2rh9d577/Hrr7+Sk5NDXV0dtbW12Nhc25c6GzZsoG/fvqafv/32W4YNG3bJe9vaqtHqVatW8f7775ORkUFZWRn19fXU1NRQVVVluq+FhQUxMTGm5+7fvx+DwUBYWFiD+9fW1uLq6nqtvw5xF5J3RiHEHeVMeQ0fLTvE7J3ZANha6Hi+eyijOjfB0uzubuV++nA6qQvmcHSHOgvlYuFN66BeuBi80AAYwcLfHvt4P6yiXC+K8NWfPUvRb+uxSkoAqLKEVS01LI3VUufmwMNhD/N1xFC87bwBqKuuJ2NrLvtTciQqKMQdwNpcR9qk3o127+tla2t7Ufe/7Oxs079//PHHfP7553z22Wc0b94cW1tbXnzxRerq6q7p+nFxcezZs8f0s6en5xXvnZWVRf/+/Xn22Wd59913cXFxYePGjYwePZq6ujpTsWVtbd3gi72Kigp0Oh07d+5Ep2v4e/j9zJ24t0ixJYS4I9TVG5m26ThfrMmkolZt5f5Qa19e6xOBp4NVI4/u1lEUhaw9O0ldMJvs9AMAeNk0pbXffdjrneBc2sYqQu0saNHE4aKZvZpDhyhKmk7Z4sUo59ZjnXGE5DZa1sZo8HAL5OnIYQwKGYSNufpBQqKCQtyZNBrNdUf5bmebNm3igQceMM10GY1GDh8+TFRU1DU939ra+rpaue/cuROj0ci//vUvU3fBX3/99arPa9WqFQaDgTNnztClS5drvp+4+909fxqFEHetNRn5vL04neMFaiv3GD9HJgyMpnWAcyOP7NYxGgwc2rKB7Qtmc/ZkFhq0NLFvTgvvbljprdU9srQabFq6Y9/VD3Ovhp0FFaORyo0bKUpKonLzFtPxDF91f6ztYRpifdryUWQiXf26otPq1KjgAbWr4IVRQWcvdQNiiQoKIf5soaGhzJ49m82bN+Ps7Mwnn3xCfn7+NRdb1yskJAS9Xs8XX3zBgAED2LRpE998881VnxcWFsawYcMYMWIE//rXv2jVqhVnz55l9erVxMTEcP/999+S8Yrbn7xrCiFuW0fPVvD24jRSDp0FwM3Okn/0Cefh1n5o79Lomr6uloNrV7Fj8VxKz+RjpjEnwqUDUW4dMNebgx40Fjps23ph19kXM6eGnQWNNTWULlxI0fQfqDt6VD2mga3n9sc67m9Ov6B+zIwcTqRrJKBGBQ9uPcW+tdmUnqlWL6SBJs1cienmj1+k812/Dk4IcXsaN24cx44do3fv3tjY2PD0008zaNAgSs9tTXGztWjRgk8++YQPP/yQsWPH0rVrV95//31GjBhx1edOmzaNd955h5dffpmcnBzc3Nxo3749/fv3vyVjFXcGjaIoSmMP4nZXVlaGo6MjpaWlODg4NPZwhLjrldfo+ffqI0zblEW9UcFcp2FUpyCe7x6CvdXd2cq9prKCvSuWsHPJAqrLSrHU2hDp3oFQ+9ZoDWqURWv3W2dBL7Q2DX8P9QUFFM/4heJffsFQXAxAtYW6HmtZrBa9pzNDwofwWPhjuNuom3aW5FexLyWbjN9HBTv50DzBF0d3iQoKcburqanh+PHjBAUFYWV190aqhfizXenP1vXUBjKzJYS4bRiNCrN3ZvPR8gwKKtTFz93C3XmzfxRN3e/OBcYVRYXsXLKAfauWUlddjZ2ZEx38HsDfMhyNUQMGtbOgXRdfbFt7XtRZsObwYYqmT6ds4aIG67GWxmlZ00KDj0cIz0UNp3/T/liZWV0QFTzFyYNFpus4e6ldBcPaSVRQCCGEuFnkHVUIcVvYeaKYiYsOsi9bjYY0dbPlzf5RdIvwaOSR3RpFp3PYsWgOaevXYKivx9nCi46Bg/DQ+qNBA0Yw97fH4RKdBRVFoXLjJnU91qZNpuOHfdT9sVLDNXTw68ynUYl09OmIRqOhrrqevetPsT/ld1HB5m7EJPhJVFAIIYS4BaTYEkI0qvyyGj5YmsG83TkA2Fma8bceIYzsGISFmfYqz77z5GUeJnXhbI6kbgFFwcs6iBYB3XFS3EznWIU7q50FgxwbFEDG2lrKFi2iMCmJuszz67G2hWtY3EbLyUAr+jftz9yoRIKdgoELooKbc9HXnosKWpsR2dFbooJCCCHELSbFlhCiUdTWG5iy8Thfrsmkqk4tAh6J9ePVPuF42N9d6w4UReHk/r2kLpjFyQN70aAl0DaSGO9u2BjsQEHtLNjCHfv4izsL1hcWUvzLTIpnzMBQpEb/qi1gdQsNS+O0KN7uPBb+GEPCh+Bs5SxRQSGEEOI2Ie+2Qog/laIorEo/wzvJaZwoVDfJbRXgxIQB0bTwd2rcwd1kRqOBI9u2kLpgFmeOH0WnMSfMMY5o985YGCzBABoLLbZtvbHr7IOZU8Mis/bIEYp++IHSBQtRzm3gedZBXY+1uoWGQJ9IXoxKpE+TPljoLNSo4JrLRAW7+eEXIVFBIYQQ4s8kxZYQ4k+TeaaciYvS2HCkAAAPe0v+2TeCQS1976pW7vV6PWnrV7N94RxK8nKx1FoT4xZPmGMcOqMZGEBra45dJx/s2ns36CyoKAqVmzZTNH06lRs2mI4f8YbF7bSkhmvpEpjAV1EjiPOMQ6PRUJxXydaULLWr4IVRwU7eNI+XqKAQQgjRWKTYEkLccqXVej5bdZgftpzAYFSw0GkZ3SWIv3YLwc7y7vlrqLaqir0rl7Br6UIqi4uwNXOkrVc/Am2i0SpaMILO1Qr7Ln7YxnqgMdeZnmusraVs8WKKkqZTe+SIekwDqWEaFrfVcirQmkGhDzIucjgBDgGmqOD+lGyJCgohhBC3KXknFkLcMgajwq87TvHx8kMUVaoxuJ6Rnoy7P5ImbrZXefado7KkmF1LF7J3xRJqqypxtvCktd8jeJsHqZ0FFTD3s8M+3g/raLcGnQXri4oo/uUXimf8gqGwEFDXY62JUddjaf28eTzicQaHDcbBwuF8VHBtNqVnJSoohBBC3M6k2BJC3BLbs4qYsPAgB0+XARDiYcdb/aPoGubeyCO7eUryctmxeC4HUlZh0OvxtGpC88CHcdV6mc6xDFM7C1o2bdhZsDYzk6LpP1C6YIFpPVbBBeuxQvxb8GpUIj0DemKmNaM4r5L1KYcvExX0w9Hd+s998UIIIYS4Kim2hBA3VW5pNe8vyWDh3tMA2FuZ8WLPMEZ0CMRcd3e0cj+TdYzUBbM5vGUjKAr+thE09+uKHU7qCVqwiXHHrqsfFj7nN2NWFIWqLVsoTEqicv359ViZXup6rB0RZnRreh/fRSXSwr2FGhU8WMj+tdmcTPtdVLC7P2FtPSUqKIQQQtzG5F1aCHFT1OgNfL/+GP9JOUq13oBGA4+18eflXuG42Vk29vD+MEVRyE7bT+qC2WTt3YVOY06wXUui3TtjpaizShpzLbZtvbDr7IuZ8/nOgsa6OsoWJ1OUlETt4cPqMWD7ufVYp4PsGRz+MBMiHsfbzpva6nr2rj7XVfD3UcHufviFS1RQCHF3yMvL4/333yc5OZns7GwcHR0JCQlh+PDhPPHEE9jYnG/w8/777zNu3Dg++OADXn311UYctRDXTootIcQfoigKyw/m8U5yOtnFamEQF+jMhIHRNPN1bOTR/XGK0Ujmzm1snz+b3MxDWGitaebcmXCXtpgZzUEBra0Zdh19sW3vjc72fGfB+uJiSmbOpOjnGRgK1A6MNeawNkbDkjZaLAICGBY5jEEhg7A1t1WjgosOkbE1r0FUMKqTN80kKiiEuMscO3aMTp064eTkxHvvvUfz5s2xtLRk//79fPfdd/j6+jJw4EDT+VOnTuUf//gHU6dOlWJL3DGk2BJC3LBDeeVMXHSQzUfVxg5eDlaM7RfBwBY+d/zMi6FeT/qGFLYvnEPR6WxszRyJde9FU/sW5zsLulhh39UXm9aeaC3OdxasPXZMXY81fz5KbS0ABfbqeqw1LTRENmnD61GJxPvFo0XLiYOFrFl7pGFU0NtW7SooUUEhxF3queeew8zMjB07dmBre75pUtOmTXnggQdQFMV0bN26dVRXVzNp0iR++OEHNm/eTMeOHRtj2EJcF3kHF0Jct5KqOj5deZiftp1UW7mbaflL16Y8mxCMjcWd/ddKXU01+1cvZ0fyfCoKC3Cy8KCT94P4WoWe7yzoe0FnQZ1aVCqKQtW2bRRNS6Ji3TrT9Y56weK2WnZEmdMruB9To4YT5RpFbXU9B9aelqigEOLmUhTQVzXOvc1t4Br/3iosLGTFihW89957DQqtC134d+CUKVMYOnQo5ubmDB06lClTpkixJe4Id/anIiHEn8pgVJiRepJPVhyiuEoPQJ9oL964PxJ/lzt749yqslJ2L1vMnmWLqKmswNMqkLZ+vXE39zOdYxnqpHYWDHYyfQhQ6uooXbJE3R8rIwNQ12PtOLceKy/YiUfCh/B2xFDcbdzVqOAvh0jfmke9RAWFEDebvgre82mce79+GiyubVuPzMxMFEUhPDy8wXE3NzdqamoA+Otf/8qHH35IWVkZs2fPZsuWLQAMHz6cLl268Pnnn2NnZ3fRtYW4nUixJYS4JluPFTJh4UEy8soBCPO0Y/yAaDqFuDXyyP6YsrNn2LF4HvvXrMBQV4efbTjNAjvjoHVVT9CCdXN37OMbdhasLy6m5H//o/jnGdSfPQtcsB4rTottUDDDo4YzoOkALLWWnDhYyJa1ezh1iahgeDsvzC11CCHEvS41NRWj0ciwYcOoPRfD/uWXXwgODqZFixYAtGzZksDAQP73v/8xevToxhyuEFclxZYQ4oqyi6t4f0kGyftzAXC0Nuel+8IY1i4Aszu4lXvBySy2L5xD+qZ1aBUtQXbNifLthDXqt7Iacy22bc51FnQ531mw9thxin6YTun8BSjnvn0tslPXY61qqaFlcGcmRA2nk08n6moMZKzLZV9KNmUXRAWDYtQNiH0lKiiEuNnMbdQZpsa69zUKCQlBo9Fw6NChBsebNm0KgLX1+Vn+KVOmcPDgQczMzn9sNRqNTJ06VYotcduTYksIcUnVdQa+WXeUb9YdpbbeiFYDj7cL4KX7wnGxtWjs4d2wnIw0UhfM4tiu7VhorYh0aE+EczvMUV+T1sYMu44+2HbwMXUWVNdjpVKUlERFSorpWse8YHEbLbuaWdE3dAA/RQ4nxDlEjQrOPEzGBVFBSxszIjv50DzeFwc3iQoKIW4Rjeaao3yNydXVlfvuu48vv/ySMWPGXHbd1v79+9mxYwcpKSm4uLiYjhcVFZGQkEBGRgYRERF/1rCFuG5SbAkhGlAUheT9uby/JIOcEnU2pm2QCxMGRBPl49DIo7sxiqJwfPcOUhfMIicjDRszB1q59iTYoSU61PieztkS+65+2MSe7yyo1NVRtnQphUnTqU1PB9T1WDtD1fVYZ8PceCxiKO+GP4KzhTMnDhSy8MeGUUEXH1uaJ0hUUAghfu8///kPnTp1Ii4ujgkTJhATE4NWq2X79u1kZGQQGxvLlClTaNu2LV27dr3o+W3atGHKlCl8/PHHjTB6Ia6NFFtCCJO002VMXHSQbcfVYsHH0YrX74/k/ubed2TczVBfz6EtG9i+YDYFp07gZOFBB4+B+NtGqJ0FAXMfW7WzYDN3U2dBQ0kJxf/7leKffjKtx6o1g5Rz67EcQyNJjEqkT5M+KHVaMjblkpxySKKCQghxHYKDg9m9ezfvvfceY8eOJTs7G0tLS6KionjllVd4+umnadq0Ka+99tolnz948GD+9a9/8d5772Fubn7Jc4RobBrlwk0MxCWVlZXh6OhIaWkpDg535jf7QlxJUWUdn6w8xIxtJzEqYGmm5dmEYP7SNRhriztvNkZfW8OBtSvZsXgeZWfP4GEVQJRLRzwtA03nWIac6ywYcr6zYO3x4xT/+CMl8+ahVJ9fj7UsVsuqVlriwhIYETWCOM84ivOq2J+SLVFBIUSjqqmp4fjx4wQFBWFlZXX1JwghrsmV/mxdT20gM1tC3MPqDUZ+2nqCT1cdobRabeV+f4w3r/eLxNfpzisWqivK2bN8MbuXLqKmvBw/23A6+PfHycxdPUED1jHu2Hf1w8JX7SyoKAqVqakUJU2nYu1adY8a4Linuh5rd4wNA8IfZGbkMALsAjhxoJBF/9vDqfRi031dfH7bgFiigkIIIYQ4T4otIe5RmzILmLjoIIfzKwCI8LJnwsBo2jd1beSRXb/ywgJ2Js9n36plGOvqaWLXjKjADtho1W+bNOZabOI8se/si5mrWkQqdXWULV9O0bQkatLSTNfaEaIhua2GwkhvHo8cxvuhD2FlsCF9cy7r1201RQU1GmgiUUEhhBBCXIEUW0LcY04VVfFucjrLDuYB4GRjzsu9whnaxv+Oa+VemHNKbd++IQUzxYxQh1aEe7fFQqNO92ttzLDt4INdB290dmq3QUNpKcW//krxTz9Tn58PnFuP1VzDkjZa3MNbMDIqkR6BPSjPr2PPnGwytjWMCkZ18qGZRAWFEEIIcRWNWmytX7+ejz/+mJ07d5Kbm8u8efMYNGiQ6XFFURg/fjzff/89JSUldOrUia+//prQ0FDTOUVFRYwZM4ZFixah1WoZPHjwRTuK79u3j7/+9a9s374dd3d3xowZwz/+8Y8/86UK0eiq6ur5OuUo364/Rl29EZ1Ww/B2Afz9vjCcbO6sVu65Rw6RumA2mTu2YqOzp4VjPMGOLdGd+ytN52SJfRdfbNp4mToL1p04QdEPP1Iyd45pPVaxLSyL07K6lY72EffxUVQiMW4tOHGgkKVfHJCooBBCCCH+kEYttiorK2nRogWjRo3ioYceuujxjz76iH//+99Mnz6doKAg3nzzTXr37k1aWpppodqwYcPIzc1l5cqV6PV6nnzySZ5++mlmzJgBqAvYevXqRc+ePfnmm2/Yv38/o0aNwsnJiaeffvpPfb1CNAZFUVi49zQfLM0gt1QtMjoGuzJ+QDThXvaNPLprpygKJ/buInXhHE4d3IejuTvt3PoRaBd9vrOg97nOgs3VzoKKolC1fTuF06dTsXqNaT1Wlgcsbqtlf4wDD0Q9zKyIobhq3UnfnMvPKVsoK1B/T6aoYHd/fMOcJCoohBBCiOty23Qj1Gg0DWa2FEXBx8eHl19+mVdeeQWA0tJSPD09SUpK4rHHHiM9PZ2oqCi2b99OXFwcAMuWLaNfv35kZ2fj4+PD119/zRtvvEFeXh4WFuq39//85z+ZP38+GRkZ1zQ26UYo7lQHckqZsPAgO06oMzR+ztaMuz+K3tGed0zhYDQYOLxtE6kLZnM26xjuVv5EOnXA2zrIdI5lsCP28f5YhqoFkaLXU7ZsOUVJSdQcPGg6b2ewhsVtNZQ1C2BY1HAGhQyi9ixqV0GJCgoh7kDSjVCIW+Ou70Z4/Phx8vLy6Nmzp+mYo6Mj7dq1Y8uWLTz22GNs2bIFJycnU6EF0LNnT7RaLdu2bePBBx9ky5YtdO3a1VRoAfTu3ZsPP/yQ4uJinJ2dL7p3bW0ttbW1pp/Lyspu0asU4tYorKhl8opDzNx+CkUBa3MdzyUE81TXpliZ3xkRuPq6Og6uW8WORfMozc/D1yaM+3yfwMXCSz1BA9bN3dTOgn7qDJ2htJSSWbMo+vEn03qsOjNY11xDchstPlFteDoqkS4+XclOK2HVV4fJzrhEVLCdF+Z3YMt7IYQQQtxebttiKy9PXbzv6enZ4Linp6fpsby8PDw8PBo8bmZmhouLS4NzgoKCLrrGb49dqth6//33mThx4s15IUL8ifQGIz9sOcFnqw5TXlMPwMAWPoztF4G3450xQ1NbVcmeFUvYtWQBtWUVNLGLplPAQOx0TuoJZlpsYz2w7+KH2blZp7qTJ9X1WHPmoFSr3QJLbNX9sdbGmtM5qh+fRg0n2DqU9M25zPwutUFUMKiFO827+UlUUAghhBA31W1bbDWmsWPH8tJLL5l+Lisrw9/fvxFHJMTVrT98lkmL08g8o7Zyj/ZxYMLAaNo0cWnkkV2biuIidi1dyN4VS1BqDYTYtyY8oA2WWrWg0libYdfBG7uOPujsLNT1WDt3UpSURPmq1ab1WCfc1fVYB1s582DUEGZHPIZZiS37lmezYesm6uuMgEQFhRBCCHHr3bbFlpeXGhXKz8/H29vbdDw/P5+WLVuazjlz5kyD59XX11NUVGR6vpeXF/nn4kQXXuPCe/yepaUllpaWN+V1CHGrnSis5O3F6axKV/+/drG14NXe4QyJ80envf1naYrzTrNj4VwOrluFhWJNlGN7gj1bYqYxB9TOgnadfbFt44XWUoei11OanExR0nRq9u83XWdXU3V/rMoWwQyPTuTDJvdzJr2SLd9lN4gKuvra0jxBooJCCCHuHSNHjqSkpIT58+fj5OTEZ599xsiRI6/4nKysLIKCgti9e7fps/e13kOcd9sWW0FBQXh5ebF69WrTf+CysjK2bdvGs88+C0CHDh0oKSlh586dxMbGArBmzRqMRiPt2rUznfPGG2+g1+sxN1c/vK1cuZLw8PBLRgiFuFNU1tbz5dpMpmw4Tp3BiJlWw4gOTXihZyiO1uaNPbyryj+WSerCORzZugkHMxdinXoRaB+NFnWvL3MvG+zi/bGJcUOj02IoK6Pwp9kU/fgj9ediwnU6WH9uPVZgTCeei0ok1qkNh7bkM/eHPRdFBWO6+eEjUUEhhGhUKSkpdOvW7bKPJyQkMHnyZOLi4tiyZQvt27e/6JwePXrg6OiIXq9Hr9ezbNmyi87ZsGEDXbt2Ze/evcTExFz0eH5+Pq+99horVqygpKSErl278sUXXzTYYuhSLnwPcXBwoFmzZrz99tt07979is+72UaOHMn06dMv+3hSUhJPPPEEAJ9//jm/9cQ7fPgw9vZX70bs7+9Pbm4ubm5uN2fA96hGLbYqKirIzMw0/Xz8+HH27NmDi4sLAQEBvPjii7zzzjuEhoaaWr/7+PiYOhZGRkbSp08fnnrqKb755hv0ej3PP/88jz32GD4+PgA8/vjjTJw4kdGjR/Paa69x4MABPv/8cz799NPGeMlC/GFGo8L8PTl8sDSDM+VqI5cuoW6MHxBFiMft3cpdURROHdxH6oLZnNi3G3crfzp7PISPTbDpHMumjtjH+2EZ5oxGo6Hu1CmKfvyRktlzUKqqACixgeWxWlJiLUmIGciXkcNxqfZmX0o2P2zd0jAq2PlcVNBVooJCCHE76NixI7m5uRcdX7hwIc888wzPPfccsbGxtGjRgqlTp15UbGVlZbF27VoWLVqEXq9n8ODBZGdn4+fn1+C8adOmERcXd8lCS1EUBg0ahLm5OQsWLMDBwYFPPvmEnj17kpaWhq2t7RVfw7Rp0+jTpw8FBQW88cYb9O/fnwMHDtC0adMb+I3cmM8//5wPPvjgouOJiYlkZmZy//33m445Ojqa/v33/Q4upa6uDgsLi8umwMR1UBrR2rVrFeCif5544glFURTFaDQqb775puLp6alYWloqPXr0UA4dOtTgGoWFhcrQoUMVOzs7xcHBQXnyySeV8vLyBufs3btX6dy5s2Jpaan4+voqH3zwwXWNs7S0VAGU0tLSP/R6hfij9pwsVh78aqMS+NpiJfC1xUrXj9YoKw7mKUajsbGHdkUGQ71yeOsm5aexLyr/GtJf+WXk35U9L85UTr22Xv3nn+uVgp/SlNqTZYqiqH/2K3fuUk6N+ZuSFhmlpIVHKGnhEcqyThHKmL9HKT1+7Kp8vedr5WxlgXJszxll/qe7lC//str0zy+TtioHN+QodbX1jfzKhRDi1qqurlbS0tKU6urqxh7KH5KWlqbY29srb7zxhunYv//9b8XBwUGprKxscO748eMVHx8fpb6+XtHr9Yqnp6fy9ttvNzinvLxcsbOzU77++utL3u/QoUMKoBw4cMB0zGAwKO7u7sr3339/xbECyrx580w/5+TkKIDyzTffKAUFBcpjjz2m+Pj4KNbW1kqzZs2UGTNmNHj+rFmzlGbNmilWVlaKi4uL0qNHD6WiokJRFPWzcZs2bRQbGxvF0dFR6dixo5KVlXXF8VzonXfeUWxtbZU9e/aYjsXHxysvvPBCg/MeeOAB0+dtRVGUwMBAZdKkSUpiYqJib2+vPPHEE8rx48cVQNm9e7fpvAMHDij333+/Ym9vr9jZ2SmdO3dWMjMzFUVRlCeeeEJ54IEHlI8//ljx8vJSXFxclOeee06pq6u75vHfTq70Z+t6aoNGndlKSEgwTWleikajYdKkSUyaNOmy57i4uJg2ML6cmJgYNmzYcMPjFKKxnS2v5aNlGczamQ2AjYWO57uHMLpzEJZmt++6o3q9nvQNa9m+cA6leXk0sWtGX7//w978XNMOMw22sZ6mzoJKfT1lS5ZQmJREzb7z67F2N1X3x6prFUFi9Aje9byPzK0FLJ11qGFUsKU7MQkSFRRC3LsURaG6vrpR7m1tZn1Df/eWlJTwwAMPkJCQwNtvv206PmzYMF599VVmz57NiBEjAPX1TZ8+nZEjR6LTqe9/I0aMICkpiTfeeMN0/1mzZmEwGBg6dOgl7/nbFj8X7p+k1WqxtLRk48aN/N///d81j9/a+lxn3Lo6ampqiI2N5bXXXsPBwYHk5GQSExMJDg6mbdu25ObmMnToUD766CMefPBBysvL2bBhA4qiUF9fz6BBg3jqqaf45ZdfqKurIzU19Zp/p4sXL+att95i5syZtGjR4prH/5vJkyfz1ltvMX78+Es+npOTQ9euXUlISGDNmjU4ODiwadMm6uvrTeesXbsWb29v1q5dS2ZmJo8++igtW7bkqaeeuu7x3C1u2zVbQgioqzeStPk4/16dSUWt+pfZQ618ea1vBJ4Ot+/mlXXVVexbtYydyfOpLa0kxL4VXf0fxEqnxjI0Vhd0FrS3wFBeTuHUaep6rHPRkjodbGimYUkbHcGtE3gxMpFgJYr9KTnM2Jp6Pipoe0FXQYkKCiHucdX11bSb0a5R7r3t8W3YmNtc13OMRiOPP/44ZmZm/Pzzzw0KCxcXFx588EGmTp1qKrbWrl1LVlYWTz75pOm8UaNG8fHHH7Nu3ToSEhIANeY3ePDgBvG5C0VERBAQEMDYsWP59ttvsbW15dNPPyU7O/uSEcfLqaqqYty4ceh0OuLj4/H19eWVV14xPT5mzBiWL1/Or7/+aiq26uvreeihhwgMDASgefPmABQVFVFaWkr//v0JDlbj9ZGRkdc0joyMDIYNG8bYsWN55JFHrnn8F+revTsvv/yy6eesrKwGj3/11Vc4Ojoyc+ZMUx+EsLCwBuc4Ozvz5ZdfotPpiIiI4P7772f16tVSbAkhbj9rM87w9uI0jhVUAhDj58j4AdHEBt6+jV2qSkvYtXQRe1YsRlujJcwxjpCAlphp1E3FdY6W2HXxxbaNJ1pLM+qysyn48keKZ81CqVK/iS21geWttaxva02PFg/xn/DHMWbZsv9/2WzPSDXdy9XXjphufoS29ZSugkIIcYd6/fXX2bJlC6mpqZds2jBq1Ch69+7N0aNHCQ4OZurUqcTHxxMSEmI6JyIigo4dOzJ16lQSEhLIzMxkw4YNV0xGmZubM3fuXEaPHo2Liws6nY6ePXvSt29fU+rqmWee4aeffjI9p6KiwvTvQ4cORafTUV1djbu7O1OmTCEmJgaDwcB7773Hr7/+Sk5ODnV1ddTW1mJjoxahLVq0oEePHjRv3pzevXvTq1cvHn74YZydnXFxcWHkyJH07t2b++67j549ezJkyJAGXbkvpbS0lEGDBhEfH99gZvB6xcXFXfHxPXv20KVLF1OhdSnR0dGmGUcAb29v9l/QOfheJMWWELeZY2creHtxGmsPnQXAzc6Sf/QJ5+HWfmhv01bupWfy2LF4HgfWrMQGB1o4xhPoHo1Wo3YWNPO0wT7eD5sW7mh0Wqp276YoaTrlK1eCUZ2hOuWm7o91pI03Q5oP4xffgeTsqGT9x9mUF0pUUAghroW1mTXbHt/WaPe+HjNnzmTy5MkkJydftgNgjx49CAgIICkpiVdffZW5c+fy7bffXnTe6NGjGTNmDF999RXTpk0jODiY+Pj4K94/NjaWPXv2UFpaSl1dHe7u7rRr185UdEyaNKnBLNWFPv30U3r27ImjoyPu7u6m4x9//DGff/45n332Gc2bN8fW1pYXX3yRuro6AHQ6HStXrmTz5s2sWLGCL774gjfeeINt27YRFBTEtGnT+Nvf/sayZcv43//+x7hx41i5cuUlOzLC+ZlBrVZ70czgb7Ra7UXLdvR6/UXnXa0pyG9xySv5fSGm0Wgwnnufv1dJsSXEbaK8Rs+XazKZuuk4eoOCuU7Dk52CGNM9BHur27OV+9kTx9m+cA4Zm9fjau5De5cB+Nqc/7bRIkjtLGgV7gwGA+UrV1A4LYmavXtN5+wJUvfHUtq0IDF6BK3M25O+Lo953+1vEBWM7uxDdFeJCgohxJVoNJrrjvI1hj179jB69Gg++OADevfufdnztFotTz75JFOmTMHX1xcLCwsefvjhi84bMmQIL7zwAjNmzOCHH37g2WefveYv5H6LGh45coQdO3aYZoc8PDwu27nPy8urwezabzZt2sQDDzzA8OHDAbUYOnz4MFFRUaZzNBoNnTp1olOnTrz11lsEBgYyb948XnrpJQBatWpFq1atGDt2LB06dGDGjBmXLbbGjRvH5s2bLzszCODu7t4gGmkwGDhw4MAV2+9fSkxMDNOnT2+wnZK4Oim2hGhkRqPCnF3ZfLjsEAUV6oLdbuHuvNk/iqbudo08uospikJOxkFSF8zm+O4d+NqE0t3zcdysfNUTNGAd7YpdVz8sAxwwVFRQNH06hT/8gOG0+pe9XgcbojUsaasjIq4XL0cMxzHPj33zs5l9aJfpXq6+dsR09yO0jUQFhRDiblFQUMCgQYNISEhg+PDh5J3bO/E3Op2uwWzRk08+yaRJk3j99dcZOnToJWdY7OzsePTRRxk7dixlZWVX3bAX1CYa7u7uBAQEsH//fl544QUGDRpEr169bvi1hYaGMnv2bDZv3oyzszOffPIJ+fn5pmJr27ZtrF69ml69euHh4cG2bds4e/YskZGRHD9+nO+++46BAwfi4+PDoUOHOHLkiGm92u/9+uuvfPDBB0ybNg17e/uLfo92dnbY2dnRvXt3XnrpJZKTkwkODuaTTz6hpKTkul/b888/zxdffMFjjz3G2LFjcXR0ZOvWrbRt25bw8PDrvt69QootIRrR7pPFTFiUxt5TJQAEudnyVv8oukVcfQ+MP5tiNHJs93ZS588m7/BhmthF09fv/3Awd1VPMNNg29oTuy6+mLvbUJedQ/4HX1M061eoVPfHKrOG5a01bGpnz32tHuGrwEcp3qOw/4tsygvVTLdGA01butO8mx8+oRIVFEKIu01ycjInTpzgxIkTl1yPFBgY2KA5Q0BAAD179mTFihWMGjXqstcdPXo0U6ZMoV+/fqb9Vq8kNzeXl156ifz8fLy9vRkxYgRvvvnmDb2m34wbN45jx47Ru3dvbGxsePrppxk0aBClpaWAugny+vXr+eyzzygrKyMwMJB//etf9O3bl/z8fDIyMpg+fTqFhYV4e3vz17/+lb/85S+XvNfXX3+NoiiXLSzHjx/PhAkTGDVqFHv37mXEiBGYmZnx97///bpntQBcXV1Zs2YNr776KvHx8eh0Olq2bEmnTp2u+1r3Eo1ypd7rAoCysjIcHR0pLS3FwcGhsYcj7gL5ZTV8uDSDubtzALCzNONvPUIY2TEICzNtI4+uIUN9PRmb1rF94RzKcvIIdmhFmGMc1jp11k1jpcOuvQ92ndTOgtV79lCYNJ2yFSvQnMtpZ7tCclstx9r58WiLEcTb9OLIxkIOb8uTqKAQQvwBNTU1HD9+nKCgoAZtzIUQf8yV/mxdT20gM1tC/Ilq6w1M3ZjFl2uOUFlnAOCRWD9e7ROOh/3t9Sapr6lh/9oV7Fg8j/riakId4ogPGIy59lxnQQcLtbNgWy80OihftZrCpGnU7FHXY2mAvU3U/bHM2scxPGoETYqacWDZaRYcOt+Z6LeoYFgbT8wkKiiEEEKIu4gUW0L8CRRFYXX6Gd5JTiOrUI3UtfR3YsLAaFr6OzXu4H6nuryM3csWs3v5YsxrzIlwbEsT/2i0GrUQMvM431nQWFNFycyfKZj+A4bTpwF1PdbGaA3L2poT3a4frwYNw5jmwP7vszlUeBA4HxWM6e6Hd4hEBYUQQghxd5JiS4hbLPNMBZMWp7H+sNrK3d3ekn/2ieDBVr63VSv3soKz7Eyez77Vy3DCjTjHnvi6nW/Fa9HEAfsEf6zCnKnPy+XMvyZT9Ov/GqzHWtFaw5b2TvSJfYx/OQ4ie2sVW3/No15/BvgtKuhLs3hf7F1ur5k8IYQQQoibTYotIW6Rsho9n686wvTNWdQbFSx0WkZ1DuL57iHYWd4+f/QKs0+yfeEc0jem4GUZRLzLw7hZ+akPasAqyhX7rn5YBjpQvW8fOS+/Q9mK5WgMF6zHaqPlZKcgHm02gkeqOpGxLp8VhzJN93D1UzcglqigEEIIIe4lt88nPiHuEgajwqwdp/h4+SEKK9VNDHtGejDu/iiauF15w8A/0+nDGWr79h3bCbSLorfXkzhYnOssqDvXWbCrL2YulpSvXs3psUnU7NoNqOux9jXRkNxGg3XnTjzWdDgOxwI4+ONpVhcdUs+RqKAQQggh7nFSbAlxE+3IKmLCooMcyCkDINjdlrcGRBMf5n6VZ/45FEUha89OUhfOJj/9ME0dWnK//1+wMVM3QtRY6rBr741dJ1/Q6imdO4eC6UkYctT1WPVadX+sle0sadHxAf7uPISSnVoOL86jXn8MkKigEEIIIcRvpNgS4ibILa3mg6UZLNijFiX2lma80DOUJzo2wVzX+K3cjQYDh7ZuZPuC2ZRnnyHMIY62Ac9hrrUEQOtggX1ntbOgoegMBd98rq7HqqgE1PVYK1tpSO3oSt/YYUzQ9+L4phI2Hzq/gaJEBYUQQgghGpJiS4g/oEZv4L8bjvHV2qNU6w1oNPBonD+v9A7Hzc6ysYeHvq6Wgymr2bFoDsZiPRGObQn0fwidRv2jb+ZhjX1XP2xaelCTfpDTr39K2bJlpv2xclzU/bHyOoczJPwJeuc0J31WHhuLsgDQaDU0belGTDd/vEMcJSoohBBCCHEBKbaEuAGKorD8YD7vLknjVFE1ALGBzkwYEE1zP8dGHh3UVFawd8USdi1diHWNDc0cO+LrG2oqhiwCHbCP98My1JGKlLVkjZjWYD3W/kANyW21OHRNYLD7MJQDThz+Lp/T+iwArGzNiersI1FBIYQQQogrkGJLiOt0OL+ciYsOsimzEAAvByvG9otgYAufRp/ZqSgqZOeSBexbtRRXfGjv1A93F3/T42pnQV/M3c0omTuPk3+bhjH7/HqsTVEaVnWwplWHh3iWQeRtreXg4RJALSglKiiEEEIIce0afzGJEHeI0io9ExYepO/nG9iUWYiFmZbnu4Ww+uV4Hmjp26iFVtHpHFZ8+2+mjHmKgrWH6e7yOF29Hsbdyh90GmziPPF8KRbHXi6Uzv6eQ/Hx5L/7Lsbs05RbwdyOGsa/7IX5P//BS5Ez8FucwM4f8sk5XIJGqyG4tTsPvtyaR99oQ1QnHym0hBBC3LCUlBQ0Gs1l/+nWrRs7d+5Eo9GwdevWS16jR48ePPTQQwwYMIA+ffpc8pwNGzag0WjYt2/fJR+fO3cuvXr1wtXVFY1Gw549e6469qysLEaPHk1QUBDW1tYEBwczfvx46urqLvucCRMmXPH1Tpw48ar3FXcumdkS4ioMRoWZ208yefkhiqv0APSO9uSNflEEuNo06tjyjh5h+4LZHNu+g2C7GPp6/1+DzoK27b2x7+RD3Ykj5H/0FmVLl5r2xzrtrK7HKoxvxoO+T9L+cACZ08+wW58DnIsKdvGhWVeJCgohhLh5OnbsSG5u7kXHFy5cyDPPPMNzzz1HbGwsLVq0YOrUqbRv377BeVlZWaxdu5ZFixah1+sZPHgw2dnZ+Pn5NThv2rRpxMXFERMTc8lxVFZW0rlzZ4YMGcJTTz11TWPPyMjAaDTy7bffEhISwoEDB3jqqaeorKxk8uTJl3zOK6+8wjPPPHPR8bFjxzJ//nwef/zxa7q3uDNJsSXEFWw7VsjERWmk5aqt3MM87XirfzSdQ90abUyKonBy/15SF8ziTHomoQ6xDPB7BgudWhBp7S2w7+yDTZwHVVs3cuK5cdTu2AWo67EOBGhY0k6Hc/x93G/2GGW7zMhZUQKonQXd/NWoYGicRAWFEELcfBYWFnh5eTU4lp6eziuvvMLrr7/OI488AsDo0aMZN24cn332GTY257/cTEpKwtvbmz59+qAoCu7u7iQlJTFu3DjTORUVFcyaNYuPP/74suNITEwE1OLtWvXp06fBTFrTpk05dOgQX3/99WWLLTs7O+zs7Boc+/nnn/nxxx9JTk4mNDTUdPy365w6dYqgoCDGjRtnGieARqPh+++/Jzk5meXLl+Pr68u//vUvBg4caDrnwIEDvPrqq2zYsAFbW1t69erFp59+iptb4312uZdJsSXEJeSUVPPeknSS96nfvDlYmfHSfWEMbx+IWSO1cjcaDWSmbiF1wWwqTxYS4diWtv49z3cWdFc7C1qF21G6aAGZ70zDeEqdpfptPdbaDrbEtR3KEyU9ObGmnIyiCuC3roLuxHTzk66CQghxB1MUBaW6ulHurbG2vqH3j5KSEh544AESEhJ4++23TceHDRvGq6++yuzZsxkxYgSgvr7p06czcuRIdDr1C8ERI0aQlJTEG2+8Ybr/rFmzMBgMDB069Ca8sisrLS3FxcXlms/fuXMnTz31FB988AG9e/c2HZ83bx4vvPACn332GT179mTx4sU8+eST+Pn50a1bN9N5EydO5KOPPuLjjz/miy++YNiwYZw4cQIXFxdKSkro3r07//d//8enn35KdXU1r732GkOGDGHNmjU39XWLa6NRFEVp7EHc7srKynB0dKS0tBQHB4fGHo64hWr0Br5dd4yv12VSozei1cDQtgG83CscF1uLRhlTvV5P2vrV7Fg0F02RQoRjO/xsws53Fgywxz7eH52rnpKfZ1Aw8xc05WoRVWGl7o+1t4sP/UL+D+/j0RzbUYhBr0YJJSoohBB3tpqaGo4fP05QUBBWVlYYq6o41Dq2UcYSvmsnWpvri9cbjUb69+9PVlYW27Ztw97evsHjQ4cOJTc3l5SUFADWrFlDjx49OHLkCCEhIYAa7YuMjGTt2rUkJCQA0LVrVwIDA/nxxx+vOoasrCyCgoLYvXs3LVu2vK7xZ2ZmEhsby+TJk68pinjmzBni4uKIj4+/aGydOnUiOjqa7777znRsyJAhVFZWkpycDKgzW+PGjTMVpZWVldjZ2bF06VL69OnDO++8w4YNG1i+fLnpGtnZ2fj7+3Po0CHCwsKu6/Xdy37/Z+tC11MbyMyWEKjflC09kMe7yenklKjfCLYNcmH8gCiifRqnlXttVRX7Vi1l55IFONQ40dIxHg+fANPjVpEu2Mf7YazMpnDa+6b1WBog1xmS22gp6xbL/bZPELHfidwZpRzhLCBRQSGEELeH119/nS1btpCamnpRoQUwatQoevfuzdGjRwkODmbq1KnEx8ebCi2AiIgIOnbsyNSpU0lISCAzM5MNGzYwadKkPzS2Z555hp9++sn0c0VFRYPHc3Jy6NOnD4888sg1FVp6vZ6HH34YT09Pvv/++4seT09P5+mnn25wrFOnTnz++ecNjl24Bs3W1hYHBwfOnDkDwN69e1m7du1FsUWAo0ePSrHVCKTYEve89NwyJi46yNZjRQD4OFoxtl8k/WO8GyVOV1lSzK6lC9m3Yhle2gA6Ow7CycldfVCrwaaVB3adfahNTyVn3HsN1mMdDIClbc3x7voAPSsHcGa7npyiWqD0fFSwux/ewRIVFEKIu5HG2prwXTsb7d7XY+bMmUyePPmidUsX6tGjBwEBASQlJfHqq68yd+5cvv3224vOGz16NGPGjOGrr75i2rRpBAcHEx8ff0Ov4zeTJk3ilVdeueRjp0+fplu3bnTs2LHBTNSV/O1vf+PIkSNs3779opmS62Fubt7gZ41Gg9GoJlYqKioYMGAAH3744UXP8/b2vuF7ihsnxZa4ZxVX1vHJysP8vO0ERgUszbT8JT6YZ+ODsW6E2Z6S/Dx2LJpLxroUAq2iuM91ODZm6tS0xlKHbTsvbFu7UL5mCcefmIrx5Pn1WFsiNaR0cqB981EMzm7DyUWlHNOr38BZ2ZoT3cWHaIkKCiHEXU+j0aC5zihfY9izZw+jR4++aN3S72m1Wp588kmmTJmCr68vFhYWPPzwwxedN2TIEF544QVmzJjBDz/8wLPPPvuHv1T08PDAw8PjouM5OTl069aN2NhYpk2bhlZ79bXc3333HVOnTmXt2rUXdU38TWRkJJs2beKJJ54wHdu0aRNRUVHXPObWrVszZ84cmjRpgpmZfMy/Hch/BXHPqTcYmZF6kn+tOExptdrK/f7m3oztF4Gf85//BnUm6xipC2ZzYtsuQh1a0c/rqfOdBe3Msevsi2WQGaVzfuH0+BloyisBdT3WqpYa0hKa0MvtaQZn+JE3p4zjFAO/RQX9CW3jgZm5RAWFEELcHgoKChg0aBAJCQkMHz6cvLy8Bo/rdDrc3d1NPz/55JNMmjSJ119/naFDh2J9iRk0Ozs7Hn30UcaOHUtZWRkjR4686jiKioo4efIkp0+fBuDQoUMAeHl5XdQt8Tc5OTkkJCQQGBjI5MmTOXv2rOmxyz1n06ZNjBkzhrfeeoumTZte9Hqtra1xdHTk1VdfZciQIbRq1YqePXuyaNEi5s6dy6pVq676Wn7z17/+le+//56hQ4fyj3/8AxcXFzIzM5k5cyb//e9/TU1FxJ9Hii1xT9l8tIBJi9LIyCsHIMLLnvEDoukQ7PqnjkNRFLLTD5C6YDYFB44R7tiG/n5/Qac911nQTe0sqLUupPDHf1O2ZCmaegMaIM8JlrTRUpvQlXjDo/jsNqdsay1llKkbELdyp3k3iQoKIYS4PSUnJ3PixAlOnDhxyWhbYGBgg3bsAQEB9OzZkxUrVjBq1KjLXnf06NFMmTKFfv364ePjc9VxLFy4kCeffNL082OPPQbA+PHjmTBhwiWfs3LlSjIzM8nMzLxohupyPef++9//UldXx7hx4xq0p//NE088QVJSEoMGDeLzzz9n8uTJvPDCCwQFBTFt2jRT049r4ePjw6ZNm3jttdfo1asXtbW1BAYG0qdPn2uagRM3n3QjvAbSjfDOd6qoiveWpLP0gPptkpONOS/fF8bQtgF/ait3xWgkc+c2ti+YTe2JUiKc2jfsLOhvj11XX+rPHuDstCnUbT+fu0/zh+XtLPBvN5Tm+d3I21t9vqugnTnRnX1oFu+LnbNEBYUQ4l5xpY5pQogbJ90IhbgGVXX1fJNylG/XH6O2Xm3lPrx9IC/dF4aTzZ/Xyt1Qryd94zq2L5iNRbEFEY5t8fQNND1uFeGCbXt3qnet5uTLr6CcW49l0KjrsTZ2cqVd0NP0PBrG2eRKclCjhBIVFEIIIYS4fUmxJe5KiqKwaF8u7y9JJ7e0BoAOTV0ZPzCKCK8/b3ayrqaa/atXsDN5Pi417rRxug8nr3OLbbVg09ID62gbylfM5tiIn9GWqUVUpaW6Huto12Z0tRpJtwOOVB6p5SyVpq6CLbr74SVRQSGEEEKI25YUW+KucyCnlEmL0kjNUlu5+zpZM+7+SPo08/rTCpOqslJ2L1vM/uXL8NUGE+/4MLbnppk1Flps23pj7lVF0a9TyJu0BE29AS3n12NpOwygdVk/nPYYKdMbgVo1KnhuA2KJCgohhBBC3P6k2BJ3jcKKWiavOMzM7SdRFLAy1/JcQghPd22K1Z8UsSs7e4YdyfM4vHYDQVbNuc8lEUud2jVJa2uGXScfMBznzI9voU9V12NpgHQ/WNnehibRo2h9shVF62sooB6QqKAQQgghxJ1Kii1xx9MbjPy09QSfrjxMWY1aoAxo4cPYvhH4OF3fBos3quBkFtsXzuFU6j7C7GLp4zkKM6266aDO1Qq7Dp7oT24h54M34YL1WFsjNGzr6E+c+1O0zfCkap2eImrUroKt3YlJkKigEEIIIcSdSootcUfbeKSAiYsOcuSMuoFvlLcDEwZG0zbI5U+5f05GGqkLZ1O8/yQRju2I9h6FVqN2NzT3s8O2lQOVqYs4+dJPpvVYVefWY51u34XWxsHEpptTf1ShHj3W9uZEdZaooBBCCCHE3UCKLXFHOllYxdvJaaxMywfAxdaCV3qF82gbf3TaWzsLpCgKx3fvIHX+LAwnq4lwbEcb326mx63CnbFsqlCy9EcKvlmC9tx6rDOOsDTOHKvWjxN8piN2e+tRS0QF9wB7Yrr5ERInUUEhhBBCiLuFFFvijlJZW89/UjL5fsNx6uqN6LQaRnQI5MUeYTjamN/SexsNBg5tXs/2hXOxKbSmmWO7Bp0FrVu4Y2Z7hjOzPqD+w52/HSbDF1Lau9GkyVOEZTahens9ZdSfjwp288erqYNEBYUQQggh7jJSbIk7gqIoLNhzmveXppNfVgtAl1A33uofRain/S29t762hgNrV7J78SLcar1p59AbWw9H9UFzDbaxHhjL95E/dSKaE+p6LOO59Vj72sYQbTuciMO2GHcqVFOPtb050V18ie7ii52z5S0duxBCCCGEaDxSbInb3v7sUiYsOsjOE8UA+LtYM+7+KHpFed7S2aCaigr2LF/MgWUr8NeGEe/wMJZ2asMNjY0Ztq2cqMlcTc7709GVVqABqixgdUsdJa0HEFLZk7ATGvSAKSrY3Y+QWIkKCiGEEELcC6TYEretgopaPl52iF93nkJRwMZCx1+7hTC6c9AtbeVeXljAzuT5ZKZsIdgqhp7Ow893FnSxxCrcgvItM8kZuxhtvQEd6nqslXGO2EWMwC07CtsMI9WA9lxUsLlEBYUQQggAUlJS6Nat22UfT0hIYPLkycTFxbFlyxbat29/0Tk9evTA0dERvV6PXq9n2bJlF52zYcMGunbtyt69e4mJibno8QkTJjBz5kxOnTqFhYUFsbGxvPvuu7Rr1+6Gx7127drLPi7uTVJsidtOXb2RH7Zk8fmqI5TXqq3cH2zly2t9IvByvHUd+gpzTrFj0VxObzlIuH0cvdxHnO8s6GOLuVclBclfUDJ1B6CuxzrsA5vahuHvnojvcVeMBxVqMUpUUAghhLiMjh07kpube9HxhQsX8swzz/Dcc88RGxtLixYtmDp16kXFVlZWFmvXrmXRokXo9XoGDx5MdnY2fn5+Dc6bNm0acXFxlyy0AMLCwvjyyy9p2rQp1dXVfPrpp/Tq1YvMzEzc3d1vaNxC/J5GURSlsQdxuysrK8PR0ZHS0lIcHBwaezh3tZRDZ5i0OI1jZ9U26c19HZkwMIrYwFvXyj038xCp82ZTfjCXCMd2eFk3MT1mGeyARptF/qwv0GZdsB4rXMeR1gkEMYD60+cbc0hUUAghxJ+ppqaG48ePExQUhJWVFYqiUF9nbJSxmFlobzjBkZ6eTrt27fjb3/7GO++8A8AXX3zBuHHjyM3NxcbGxnTuhAkT+P777zl58iSKouDn58fzzz/PuHHjTOdUVFTg7e3Nxx9/zDPPPHNNY/jt896qVavo0aPHDY8bYN26dbz66qvs3bsXFxcXnnjiCd555x3MzNR5joSEBGJiYrCysuK///0vFhYWPPPMM0yYMMF0jZKSEl555RUWLFhAbW0tcXFxfPrpp7Ro0cL0e5g/fz4vv/wyb775JsXFxfTt25fvv/8ee/tbu579XvD7P1sXup7aQGa2xG3heEEl7yxOY3XGGQDc7Cz4R+8IHo71Q3sLWrkrisKJfbtJnT8HzYk6Ihzb4ezVVX1QA1YRjugLtpL/3+/RlVagRV2PtaaFPTXRj+BZGIv/aajnfFQwprs/nkESFRRCCNF46uuMfPfCuka599Ofx2Nuef1fNJaUlPDAAw+QkJDA22+/bTo+bNgwXn31VWbPns2IESMA9f17+vTpjBw5Ep1OvdeIESNISkrijTfeML0Hz5o1C4PBwNChQ69pDHV1dXz33Xc4OjqaipkbHXdOTg79+vVj5MiR/PDDD2RkZPDUU09hZWXVoJiaPn06L730Etu2bWPLli2MHDmSTp06cd999wHwyCOPYG1tzdKlS3F0dOTbb7+lR48eHD58GBcX9Uvoo0ePMn/+fBYvXkxxcTFDhgzhgw8+4N13372m1yBuPSm2RKOqqK3nizVHmLrxOHqDgplWw8iOTfhbz1AcrG5+K3ej0cDhrZvYuWA+doV2xDi2x87DSX3QTIN1mDUVaQvJnzwHrV5dj3XWAda0aYKD3+PY5fhikwV6MEUFm3X1xdZJooJCCCHE9TIajTz++OOYmZnx888/N/jC0sXFhQcffJCpU6eaiq21a9eSlZXFk08+aTpv1KhRfPzxx6xbt46EhARAjRAOHjwYR0fHK95/8eLFPPbYY1RVVeHt7c3KlStxc3P7Q+P+z3/+g7+/P19++SUajYaIiAhOnz7Na6+9xltvvYVWqy5RiImJYfz48QCEhoby5Zdfsnr1au677z42btxIamoqZ86cwdJS/YwxefJk5s+fz+zZs3n66adN40hKSjLNZCUmJrJ69Woptm4jUmyJRmE0KszdncOHyzI4W662co8Pc+fN/lGEeNjd9PvV19VxcN1q9i5KxqPWl/YOvbF0UyMJGmsdlv5GCjdMo3z2ZuDceixvLTviOuBlMwj3fBs4AUbUqGCL7n6ExHqiM9fe9LEKIYQQN8rMQsvTn8c32r2v1+uvv86WLVtITU29ZPRt1KhR9O7dm6NHjxIcHMzUqVOJj48nJCTEdE5ERAQdO3Zk6tSpJCQkkJmZyYYNG5g0adJV79+tWzf27NlDQUEB33//PUOGDGHbtm14eHjc8LjT09Pp0KFDgwKsU6dOVFRUkJ2dTUBAAMBFa8m8vb05c0ZN+Ozdu5eKigpcXV0bnFNdXc3Ro0dNPzdp0qTB/S+8hrg9SLEl/nS7TxYzYVEae0+VANDE1YY3+0fRPcLjpkfwaqsq2btyKWlLVxOoCaer/UOYndv8WOtojpljIWcWfYHulxOAuh5rW4Q9p5r1w6O6M17lWig/FxWM9SCmm59EBYUQQty2NBrNDUX5GsPMmTOZPHkyycnJhIaGXvKcHj16EBAQQFJSEq+++ipz587l22+/vei80aNHM2bMGL766iumTZtGcHAw8fFXLzptbW0JCQkhJCSE9u3bExoaypQpUxg7duwfGve1MDdvmODRaDQYjep6u9/WnKWkpFz0PCcnp2u6hrg9SLEl/jRnymr4cNkh5uzKBsDWQseYHqE82akJlmY3942hsqSYnUsWkLUmlWCrFnR3fMzUWVDnboFSf4jC+V9hVlyGDqi2gLUt/TE0fQS7s8G4nVVnsaztzYnu6kuzLhIVFEIIIW6WPXv2MHr0aD744AN69+592fO0Wi1PPvkkU6ZMwdfXFwsLCx5++OGLzhsyZAgvvPACM2bM4IcffuDZZ5+9oS9GjUYjtbW1f2jckZGRzJkzB0VRTGPYtGkT9vb2F3VMvJzWrVuTl5eHmZkZTZo0ue7XIW4fUmyJW6623sC0TVl8sfoIlXUGAAa39uO1PuF4ONzcVu7FeafZsXAuZ7cdIcwulu5u5xfGmvlYUHt6HaVJP6DVGzADzjpo2RgXh53zIKwKHSEPFMAj0J6YbhIVFEIIIW62goICBg0aREJCAsOHDycvL6/B4zqdrkHr9SeffJJJkybx+uuvM3ToUKytrS+6pp2dHY8++ihjx46lrKyMkSNHXnEMlZWVvPvuuwwcOBBvb28KCgr46quvyMnJ4ZFHHvlD437uuef47LPPGDNmDM8//zyHDh1i/PjxvPTSS6b1WlfTs2dPOnTowKBBg/joo48ICwvj9OnTJCcn8+CDDxIXF3dN1xGNT4otccsoisKajDO8vTiNrMIqAFr4OzFhQBStApxv6r3yj2WSumAONQcKiXBoQ6S72klIASx8oHTfLAzzVwLqeqxDvnYcaNETZ003HCvNoFCigkIIIcSfITk5mRMnTnDixAm8vb0vejwwMJCsrCzTzwEBAfTs2ZMVK1YwatSoy1539OjRTJkyhX79+uHj43PFMeh0OjIyMpg+fToFBQW4urrSpk0bNmzYQHR09B8at6+vL0uWLOHVV1+lRYsWuLi4MHr06Aat6a9Go9GwZMkS3njjDZ588knOnj2Ll5cXXbt2xdPT85qvIxrfbb3P1oQJE5g4cWKDY+Hh4WRkZABq//uXX36ZmTNnUltbS+/evfnPf/7T4H/CkydP8uyzz7J27Vrs7Ox44okneP/99037HFwL2Wfr+mWeqeDtxWmsO3wWAHd7S17rE8FDrXxvWit3RVE4dXAfO+bPRZdlJNyxLXbmTupjOjB3raJw3fdoDx0E1Fjg1mh/CkIHYF8ehWJQxyFRQSGEEHeqK+0FJIS4cffMPlvR0dGsWrXK9POFRdLf//53kpOTmTVrFo6Ojjz//PM89NBDbNq0CQCDwcD999+Pl5cXmzdvJjc3lxEjRmBubs577733p7+We0FZjZ5/rzpC0uYs6o0K5joNozoHMaZ7KHaWN+d/N8VoJHP7VnbNX4BDkSMxDh2xOtdZEEsNGsvTFC/9D2Zn88/tj6VlQ+vWKJ79sSh1x67kgqhgd39CWntIVFAIIYQQQtx0t32xZWZmhpeX10XHS0tLmTJlCjNmzKB79+6AuqdCZGQkW7dupX379qxYsYK0tDRWrVqFp6cnLVu25O233+a1115jwoQJWFhY/Nkv565lNCrM2nmKj5cfoqCiDoAeER6M6x9FkJvtTblHvV5P+sa17F+4HK8aP9rZ98LM+dx/Qxuor95Pxfzv0dXWYAbkOduxvVU8NpY9MK+2hNILooLd/fAKuvLeG0IIIYQQQvwRt32xdeTIEXx8fLCysqJDhw68//77BAQEsHPnTvR6PT179jSdGxERQUBAAFu2bKF9+/Zs2bKF5s2bN4gV9u7dm2effZaDBw/SqlWrS96ztra2QSeasrKyW/cC7wI7TxQxYWEa+3NKAWjqbstb/aNICL/yHhXXqq66in2rlnFk2XoCNBF0th2I1lKdidLYG6k8tRrDgjmgGNEBaYH+HI3sjW1dS2yNGqgGawcLmnXxIbqrL7aOEhUUQgghhBC33m1dbLVr146kpCTCw8PJzc1l4sSJdOnShQMHDpCXl4eFhUWDvQYAPD09Td1h8vLyLlpE+NvPv+8gc6H333//orVi4mJ5pTV8sDSd+XtOA2BvacYLPUMZ0aEJFmZ/PJZXVVbK7iULObV2N8GWLeliP9j0mMaultJ9v6LZtwGAeo2WbTGxlPv1xaLKG9sa9TyJCgohhBBCiMZyWxdbffv2Nf17TEwM7dq1IzAwkF9//fWSbT9vlrFjx/LSSy+Zfi4rK8Pf3/+W3e9OU6M3MGXjcb5am0lVnQGNBobE+vNK73Dc7f/4rFHpmXx2LJpL8bYThNm2prPzgwAoKGBdTNnGJLSnMtAAZTZ2bGvRBY1DD7S11lhUgVanIbi1RAWFEEIIIUTjuq2Lrd9zcnIiLCyMzMxM7rvvPurq6igpKWkwu5Wfn29a4+Xl5UVqamqDa+Tn55seuxxLS0ssLSVq9nuKorAiLZ93k9M5WaS2cm8d4MTEgc1o7vfHi5qzJ7PYMX8OdftLCXeII9ylmXpfrYLBeJyqtdPQlKpNL7I9/Nkf3QMLTSw6oxZqJSoohBBCCCFuL3dUsVVRUcHRo0dJTEwkNjYWc3NzVq9ezeDBarzs0KFDnDx5kg4dOgDQoUMH3n33Xc6cOYOHh7p+aOXKlTg4OBAVFdVor+NOdCS/nEmL09hwpAAATwdLxvaN5IGWPn9oPypFUcjJOMjOefOxOKEh1CEWK1e1oYaiM1BTuhvD+hkodRUoGi37Q2M53eQ+LPT+WCqAAp5BDjRP8CMk1gPdTYgvCiGEEEIIcTPc1sXWK6+8woABAwgMDOT06dOMHz8enU7H0KFDcXR0ZPTo0bz00ku4uLjg4ODAmDFj6NChA+3btwegV69eREVFkZiYyEcffUReXh7jxo3jr3/9q8xcXaPSKj2frjrMj1tPYDAqWOi0PNU1iOcSQrD9A63cFaORY7u3s3deMk6FzsTYd8D8XGdBo1kd1SdWYdy1BAx11JjbsaN1H6pduqGrt8NCr0YFQ2I9aN5NooJCCCGEEOL2dFsXW9nZ2QwdOpTCwkLc3d3p3LkzW7duxd3dHYBPP/0UrVbL4MGDG2xq/BudTsfixYt59tln6dChA7a2tjzxxBNMmjSpsV7SHcNgVJi5/ST/WnGYokq1lXuvKE/G3R9FgKvNjV+3vp6MTetIX7gar1p/4mx7oHVUZ6MMugqqDsyDw5tAMVLo6M/uZt3QWMShUXTo6s9FBbv6Et3FR6KCQgghhBDitqZRFEVp7EHc7q5nl+i7QerxIiYsPEhartryPtTDjvEDoukc6nbD19TX1LB/zQqOLdtCIBF42zQ9/5hyhprtM+H0AYwaLcf9WnE0uDtmNDGd4xnkQEw3P4JbS1RQCCGE+E1NTQ3Hjx8nKCgIKyurxh6OEHeNK/3Zup7a4Lae2RJ/rtMl1by/NINFe8+1crcy4+89w0jsEIi57sYKnOryMvYsSyZ37UGCLZvT3qYfoHYWrK3JxLD1V4wlJ6gzt+dAdB8KPRPQGe0x41xUMM6DmAR/PIPu/iJXCCGEuBekpKTQrVu3yz6ekJDA5MmTiYuLM+2d+ns9evTA0dERvV6PXq9n2bJlF52zYcMGunbtyt69e4mJibnimJ555hm+/fZbPv30U1588cUbHvfatWuveB9x75FiS1CjN/Dd+mP8JyWTGr0RjQaGtg3g5fvCcLW7saheWcFZdi1aQNm2bEJtW+Hv0BsAIwZqCndh3DUfpfIsZfYB7G0zgjq7c1FBI9g4WBAtUUEhhBDirtSxY0dyc3MvOr5w4UKeeeYZnnvuOWJjY2nRogVTp069qNjKyspi7dq1LFq0CL1ez+DBg8nOzsbPz6/BedOmTSMuLu6qhda8efPYunUrPj4+f3jcQvyeFFv3MEVRWHogj3eT08kpqQagbRMXxg+MItrnxppOFGafYuf8+RgOlBP6/+3deVyVZf7/8ddhXwQUQxblKCIpKpqGOcn8AhPDddRcinFDyGrGdUrGPbPFzKVsNXMUbNKcNDNLJ3UcNDUXzLBMUkTFXHEDRGSRc35/OJ5vBCKWcELez8fjPB6e677u+/7c5xI9H67Pfd1ubXGq3RSAYgrJz0jC/MMGiouucMq7DQfbDsVgGwCAwaxSQRERkd/KbDZzraDAKue2c3Ss0ArFDg4OpR7Bk5qayrhx45g0aRL9+/cHIC4ujilTpjBv3jxcXP7vfvHExER8fX3p0qULZrMZLy8vEhMTmTJliqVPbm4uK1asYPbs2eXGcvLkSUaNGsX69evp3r37HYkbYMuWLcTHx7Nv3z48PT0ZOnQoL730EnZ21796R0RE0KpVK5ycnPjHP/6Bg4MDTz/9NM8//7zlGFlZWYwbN47PPvuMgoICQkNDef3112ndujUAzz//PKtXr+bZZ59l6tSpXLp0ia5du7Jw4ULc3NzKvRapOkq2aqgfz+Qwfc0Bdhy5AICvhxOTugXTo5Xvr1rK/dShH/l21ec4ZdgS5NYa+9rXVxa8Zr5CQepaTOlbKbRxIL1hGCcbhGODOwZUKigiInInXSso4M2h/axy7tFLVmL/K+4by8rKolevXkRERPDiiy9a2gcOHEh8fDwrV65kyJAhwPVkcsmSJcTExGBrawvAkCFDSExMZPLkyZbvMCtWrKC4uJjo6OibntdkMjF48GDi4+Np0aLFHYv75MmTdOvWjZiYGD744AN+/PFHhg8fjpOTU4lkasmSJTzzzDPs2rWLHTt2EBMTQ1hYGJ07dwagf//+ODs78+9//xsPDw8WLFhAp06dOHToEJ6engCkp6ezevVqvvjiCy5dusSAAQOYOXMmL7/88m1fj1QOJVs1TFZeIa9tPMSHOzMwmcHRzoanHmrM0xGBuDjc3l8Hs9nMsZRv2L/6S2qf9ySkVjtsPK7/w1dQdB7Td59x7cQecmrV58eQx7hc+34M2GHD9VLBluH1af5HlQqKiIjUVCaTiT//1b5wBwAAIZ1JREFU+c/Y2dmxdOnSEr/w9fT0pE+fPixevNiSbCUlJXHs2DGGDRtm6RcbG8vs2bPZsmULERERwPUSwr59++LhcfNKnVdffRU7OztGjx59R+N+99138ff35+2338ZgMNCsWTNOnTrF+PHjee6557CxuV6906pVK6ZNmwZAUFAQb7/9Nps2baJz585s27aN3bt3k5mZaXlc0Zw5c1i9ejUrV67kySeftMSRmJhomckaPHgwmzZtUrL1O6Jkq4a4Vmzio93HmbvxEFl5RQB0benDpG7B+Hve3lLupuJiDu7YRtqaLfjkG2njEg7/m62+mnsU83drKDr3I5le93HwD2Mpdry+8qABlQqKiIhUJjtHR0YvWWm1c9+uSZMmsWPHDnbv3l1m6VtsbCxRUVGkp6cTGBjI4sWLCQ8Pp0mTJpY+zZo1o0OHDixevJiIiAgOHz7M1q1by33UzzfffMMbb7zB3r17f1VFT3lxp6am8uCDD5Y4blhYGLm5uZw4cQKj0QhQ6l4yX19fMjMzAdi3bx+5ubnUrVu3RJ+rV6+Snp5ued+oUaMS5//5MeT3QclWDbAj/QLTP/+BH89cBqCptxvT/tScDoG3t5R7UWEBPyRt4qd/J2OkGW2dOoLL9Rmuqxe+w7x/LflXLnC8wR853mwg2Fz/bZKNrYGgUG9COjbAu5FKBUVERCqLwWD4VaV81rB8+XLmzJnD2rVrCQoKKrNPp06dMBqNJCYmEh8fz6pVq1iwYEGpfnFxcYwaNYp33nmHhIQEAgMDCQ8Pv+m5t27dSmZmpiXxASguLubZZ59l3rx5HDt27DfFXRH29vYl3hsMBkwmE3D9njNfX182b95car/atWtX6Bjy+6Bk6y524lIeM9alsu77MwDUdrHn2c73Ev2AEbvbWMo9/0ou+75cx/nNhwiwb0kbp4cBMJmvkf/TDkwH15Nt40R6wwgu3nO9VBBUKigiIiJlS0lJIS4ujpkzZxIVFXXTfjY2NgwbNoxFixZRv359HBwc6Nev9D1pAwYMYMyYMSxbtowPPviAv/zlL+XOWA0ePJjIyMgSbVFRUQwePLhEieKviTs4OJhPPvkEs9lsiWH79u24ubmVWjHxZtq2bcuZM2ews7OjUaNGFdpHfp+UbN2FrhYWM39LOgu2pFNwzYSNAQa2b8gzne+ljqtDhY+Te/EC337+OXm7z9LYuRX1Xa//huiaKZ+iw/+l6MhmzroHkt5iMAUuvygVfLgBgW1UKigiIiIlnT9/nt69exMREcGgQYM4c+ZMie22trZ4eXlZ3g8bNowXXniBSZMmER0djbOzc6lj1qpVi8cee4yJEyeSk5NDTExMuTHUrVu3VImevb09Pj4+NG3a9DfF/de//pV58+YxatQoRo4cycGDB5k2bRrPPPOM5X6tW4mMjOTBBx+kd+/ezJo1i3vvvZdTp06xdu1a+vTpQ2hoaIWOI9anZOsuYjab+eK707yyLpVT2fkA/KGxJ9N6tiDYt+LlexdPnSTl0zXwQz4BtUKwdwsEoLAom+If15N3MoWT3u041u7vmG1VKigiIiIVt3btWjIyMsjIyMDX17fU9oYNG5Yo4zMajURGRrJhwwZiY2Nvety4uDgWLVpEt27dbvnMrMqMu379+qxbt474+Hhat26Np6enZRn7ijIYDKxbt47JkyczbNgwzp07h4+PDw899BDe3t538rKkkhnMZrPZ2kH83uXk5ODh4UF2djbu7r/PROKHU9lM//wAu49eBKB+bWcmdw+ma0ufCt/4eSY9je8/WYfTcXsaujbHxnB9ZcH8vDOYU9dxMfsMGQ3COefVFgz/KxX0cKDlQ/Vp8f/q4+Je8VkzERER+e3y8/M5evQoAQEBOFWTe7VEqoPyfrZuJzfQzFY1d/FKIXM2HGT57uOYzOBkb8NfwpvwVHhjnOxtb7m/2Wzm+HcppK7eRJ0LdQl2aQu1rm+7mnUYU+qXnDI7kGEM50pgY8t+Po3dCemoUkERERERkZtRslVNFRWb+HBnBq9vPERO/jUAerTyZWK3YOrXLl3L/EsmUzGHd33Nkc924JNvpKVTe8vKgvln91GQ/hXHXYwcb/I4xfb/KxW0MxB0v0oFRUREREQqQslWNbQt7TzTP/+BtMxcAIJ93Xm+Z3PaN657iz3hWlERBzZv4vSX3+FvvpeWDg+CE5hM1yg4sZOcE99z1LMVZ5sPV6mgiIiIiMhvoGSrmpmz/iBvJx0GoI6LPeOimvJ4OyO2NuXfl1WQl8f3X37JpS1HaGTfnBb2DwJwrfgqhUe+4kxWJse823O5+ROWfXwau9Oqoz+N23ipVFBERERE5DYp2apmOgXXY8FX6Qxs35C/Rd6Lh4t9uf2vZF1i35q1FCRfoJFzC3yc2wNQWJBN/pEtHC+0IcP3D1zz+lmpYKg3rTo2oF5DlQqKiIiIiPxaSraqmTbGOmwb/zDe7uWvOJR19gzffbIWQ2ohRpdgbF0bApB/5QxXju3msN09nPHuDDb/VyoYEl6f5n9UqaCIiIiIyJ2gZKsaKi/Ryjx2hB9WrsfluCONXe4F1+vteVnpXDp9iEOugeTU72rp79PYg1YdG9C4rRe2tioVFBERERG5U5Rs3QXMZjMnDnzPoU+24HnxHoKcWlpWFrxy/gdOX7xAWp0WFPlGAv97AHE7lQqKiIiIiFQmJVvVmNlkIn33LjLW7MYn30hTh/ssKwvmnP2eY1fNHK8djNm7KaBSQRERERGRqqS6sWqo+FoR+//zH5L+/jamlZdoamqLh8M9XLuWz7lT37Lj1HG2OLckwzMEs40dPo3deeSJFgyZ0YHQbgFKtERERETuEosWLeKRRx65rX0MBgOrV68G4NixYxgMBlJSUu58cL9TX375Jffddx8mk6nSz6Vkq5r58T+b2Rq/AJcNcK9dG1zs3CgszOHEqe9IuniFr11acr6WPza2Bpr9wYf+E0Pp+/dQgkK9dU+WiIiIWN3mzZsxGAw3fXXs2JFvvvkGg8HAzp07yzxGp06dePTRR+nZsyddunQps8/WrVsxGAx89913ZW4/e/YsMTEx+Pn54eLiQpcuXUhLS7tl/D+P1cPDg7CwMP773/9W/AO4g/Lz85k6dSrTpk2zyvlvaNSoUbljmpGRYdX4fqlLly7Y29uzdOnSSj+XygirGdsfr9HEsTUAeVfPcyrrAqmORkwuwQA4e9jTKtyf5n/00wyWiIiI/O506NCB06dPl2pfs2YNTz/9NH/961+5//77ad26NYsXL+YPf/hDiX7Hjh0jKSmJzz//nKKiIvr27cuJEydo0KBBiX4JCQmEhobSqlWrUucym8307t0be3t7PvvsM9zd3XnttdeIjIzkwIEDuLq6lnsNCQkJdOnShfPnzzN58mR69OjB/v37ady48a/4RH69lStX4u7uTlhYWJWe95eSk5MpLi4u0ZaVlUWnTp24//77MRqNVors5mJiYnjzzTcZPHhwpZ5HUx3VzLG0j8i+fIJ9mSfYWODBD86NMdnY4RN4vVRw6IwwQrs1UqIlIiJSA5nNZkyFxVZ5mc3mCsXo4OCAj49PidelS5cYN24ckyZNon///gDExcXxr3/9i7y8vBL7JyYm4uvrS5cuXejRowdeXl4kJiaW6JObm8uKFSuIi4srM4a0tDR27tzJ/PnzadeuHU2bNmX+/PlcvXqVjz766JbXULt2bXx8fGjZsqVlv40bN3LhwgWio6OpX78+Li4uhISElDreypUrCQkJwdnZmbp16xIZGcmVK1eA67N+DzzwAK6urtSuXZuwsLByZ4WWL19Oz549S7QlJyfTuXNn7rnnHjw8PAgPD2fv3r23vKaf279/P127dqVWrVp4e3szePBgzp8/f9P+Xl5eJcazXr16jB07Fg8PD5YuXYrBYADg0qVLDBkyhDp16uDi4kLXrl1LzCYmJiZSu3Zt1q9fT3BwMLVq1aJLly6lkvN//OMfBAcH4+TkRLNmzXj33Xct226URa5atYqOHTvi4uJC69at2bFjR4lj9OzZkz179pCenn5bn83t0sxWNZMTNIBD++3BAQy20LSdDyFaVVBEREQAc5GJU899bZVz+73QAYOD7W3vl5WVRa9evYiIiODFF1+0tA8cOJD4+HhWrlzJkCFDgOvJ5JIlS4iJicHW9vq5hgwZQmJiIpMnT7Z8qV+xYgXFxcVER0eXec6CggIAnJz+73E6NjY2ODo6sm3bNp544okKx+/s7AxAYWEh+fn53H///YwfPx53d3fWrl3L4MGDCQwM5IEHHuD06dNER0cza9Ys+vTpw+XLl9m6dStms5lr167Ru3dvhg8fzkcffURhYSG7d++2XFNZtm3bVmpm5vLlywwdOpS33noLs9nM3Llz6datG2lpabi5ud3yerKysnj44Yd54okneP3117l69Srjx49nwIABFS6XnDBhArt27WL37t0lzhkTE0NaWhpr1qzB3d2d8ePH061bNw4cOIC9vT0AeXl5zJkzh3/+85/Y2NgwaNAgxo0bZyn5W7p0Kc899xxvv/02bdq04dtvv2X48OG4uroydOhQy7kmT57MnDlzCAoKYvLkyURHR3P48GHs7K6nP0ajEW9vb7Zu3UpgYGCFruvXULJVzYT37sCan76lVbhRpYIiIiJSrZlMJv785z9jZ2dXYgYEwNPTkz59+rB48WJLspWUlMSxY8cYNmyYpV9sbCyzZ89my5YtREREANfL/Pr27YuHh0eZ523WrBlGo5GJEyeyYMECXF1def311zlx4kSZJY43k5eXx5QpU7C1tSU8PJz69eszbtw4y/ZRo0axfv16Pv74Y0uyde3aNR599FEaNmwIQEhICAAXL14kOzubHj16WL78BwcH3/TcWVlZZGdn4+fnV6L94YcfLvH+/fffp3bt2mzZsoUePXrc8ppuJDEzZsywtC1evBh/f38OHTrEvffeW+7+H330Ea+99hpr164lKCjI0n4jydq+fTsdOnQAridO/v7+rF692jKjWVRUxHvvvWf5DEaOHMkLL7xgOc60adOYO3cujz76KAABAQEcOHCABQsWlEi2xo0bR/fu3QGYPn06LVq04PDhwzRr1szSx8/Pr9LvJ1OyVc3c08CNmFf+HzY2N/8th4iIiNRMBnsb/F7oYLVz365JkyaxY8eOUjMgN8TGxhIVFUV6ejqBgYEsXryY8PBwmjRpYunTrFkzOnTowOLFi4mIiODw4cNs3bq1xBf0X7K3t2fVqlXExcXh6emJra0tkZGRdO3a1VIO+fTTT/Phhx9a9snNzbX8OTo6GltbW65evYqXlxeLFi2iVatWFBcXM2PGDD7++GNOnjxJYWEhBQUFuLi4ANC6dWs6depESEgIUVFRPPLII/Tr1486derg6elJTEwMUVFRdO7cmcjISAYMGICvr2+Z13D16lWg5OwcXF/4Y8qUKWzevJnMzEyKi4vJy8vj+PHjtxoOAPbt20dSUhK1atUqtS09Pb3cZGvv3r3ExcUxc+ZMoqKiSmxLTU3Fzs6O9u3bW9rq1q1L06ZNSU1NtbS5uLiUmGny9fUlMzMTgCtXrpCenk5cXBzDhw+39Ll27VqpxPrn9+rd+AwzMzNLJFvOzs6lylTvNCVb1ZASLRERESmLwWD4VaV81rB8+XLmzJlTagbk5zp16oTRaCQxMZH4+HhWrVrFggULSvWLi4tj1KhRvPPOOyQkJBAYGEh4eHi557///vtJSUkhOzubwsJCvLy8aN++PaGhoQC88MILJWapfu71118nMjISDw8PvLy8LO2zZ8/mjTfeYN68eYSEhODq6srYsWMpLCwEwNbWlo0bN/L111+zYcMG3nrrLSZPnsyuXbsICAggISGB0aNH8+WXX/Kvf/2LKVOmsHHjxlKLhMD1RMVgMHDp0qUS7UOHDuXChQu88cYbNGzYEEdHRx588EFLDLeSm5tLz549efXVV0ttu1niB3Du3Dn69OlD3759b/q5VcSNcsIbDAaDJQG+kfAuXLiwRNIGWMpKyzrOjRnTXy71fvHixRLjVxm0QIaIiIiIVKmUlJSbzoD8nI2NDcOGDWPJkiUsW7YMBwcH+vXrV6rfgAEDsLGxYdmyZXzwwQfExsaWe6/Tz91ImNLS0tizZw+9evUCoF69ejRp0sTy+jkfHx+aNGlS6ov69u3b6dWrF4MGDaJ169Y0btyYQ4cOlehjMBgICwtj+vTpfPvttzg4OPDpp59atrdp04aJEyfy9ddf07JlS5YtW1Zm3A4ODjRv3pwDBw6UimH06NF069aNFi1a4OjoWO7iFr/Utm1bfvjhBxo1alTi+ps0aXLTVRqLioro168f9erVY+HChWX2CQ4O5tq1a+zatcvSduHCBQ4ePEjz5s0rFJu3tzd+fn4cOXKkVGwBAQEVvka4vmx+eno6bdq0ua39bpeSLRERERGpMufPn6d3795EREQwaNAgzpw5U+J17ty5Ev2HDRvGyZMnmTRpEtHR0ZYFKX6uVq1aPPbYY0ycOJHTp08TExNzyzhWrFjB5s2bOXLkCJ999hmdO3emd+/et/2A4J8LCgqyzFylpqby1FNPcfbsWcv2Xbt2MWPGDPbs2cPx48dZtWoV586dIzg4mKNHjzJx4kR27NhBRkYGGzZsIC0trdz7tqKioti2bVupGP75z3+SmprKrl27GDhwYJmf2c2MGDGCixcvEh0dTXJyMunp6axfv55hw4aVWt79hrFjx7Jv3z7mz59PVlZWqTEtLCwkKCiIXr16MXz4cLZt28a+ffsYNGgQ9evXtyS4FTF9+nReeeUV3nzzTQ4dOsT3339PQkICr732WoWPAbBz507LrF9lUhmhiIiIiFSZtWvXkpGRQUZGRpllaQ0bNuTYsWOW90ajkcjISDZs2EBsbOxNjxsXF8eiRYvo1q1bqUUjynL69GmeeeYZzp49i6+vL0OGDGHq1Km/6ppumDJlCkeOHCEqKgoXFxeefPJJevfuTXZ2NgDu7u589dVXzJs3j5ycHBo2bMjcuXPp2rUrZ8+e5ccff2TJkiVcuHABX19fRowYwVNPPVXuNYeGhpKdnW25Z2nRokU8+eSTtG3bFn9/f2bMmHFbZX1+fn5s376d8ePH88gjj1BQUEDDhg3p0qULNjZlz9PcWHq9Xbt2ZW5PSkoiIiKChIQExowZQ48ePSgsLOShhx5i3bp1pUoHy/PEE0/g4uLC7NmziY+Px9XVlZCQEMaOHVvhY8D1hTwGDhxouZ+ushjMFX0oQg2Wk5ODh4cH2dnZuLtriXURERH5fcjPz+fo0aMEBASUWihBaob+/fvTtm1bJk6caO1Qqo3z58/TtGlT9uzZc9Pyw/J+tm4nN1AZoYiIiIhINTV79uwyVw6Umzt27Bjvvvvubd/n9WuojFBEREREpJpq1KgRo0aNsnYY1UpoaKhl1cnKppktERERERGRSqBkS0REREREpBIo2RIRERGp5rTemciddad+ppRsiYiIiFRTtra2ABQWFlo5EpG7y42fqRs/Y7+WFsgQERERqabs7OxwcXHh3Llz2Nvb3/Q5SCJScSaTiXPnzuHi4oKd3W9Ll5RsiYiIiFRTBoMBX19fjh49SkZGhrXDEblr2NjYYDQaMRgMv+k4SrZEREREqjEHBweCgoJUSihyBzk4ONyRmWIlWyIiIiLVnI2NDU5OTtYOQ0R+QYW9IiIiIiIilUDJloiIiIiISCVQsiUiIiIiIlIJdM9WBdx4qFlOTo6VIxEREREREWu6kRNU5MHHSrYq4PLlywD4+/tbORIREREREfk9uHz5Mh4eHuX2MZgrkpLVcCaTiVOnTuHm5vab19qX3y4nJwd/f39++ukn3N3drR2OVDGNf82m8a/ZNP41m8a/Zvs9jb/ZbOby5cv4+fndcnl4zWxVgI2NDQ0aNLB2GPIL7u7uVv9hE+vR+NdsGv+aTeNfs2n8a7bfy/jfakbrBi2QISIiIiIiUgmUbImIiIiIiFQCJVtS7Tg6OjJt2jQcHR2tHYpYgca/ZtP412wa/5pN41+zVdfx1wIZIiIiIiIilUAzWyIiIiIiIpVAyZaIiIiIiEglULIlIiIiIiJSCZRsiYiIiIiIVAIlW1ItvPLKK7Rr1w43Nzfq1atH7969OXjwoLXDEiuZOXMmBoOBsWPHWjsUqSInT55k0KBB1K1bF2dnZ0JCQtizZ4+1w5IqUlxczNSpUwkICMDZ2ZnAwEBefPFFtMbX3emrr76iZ8+e+Pn5YTAYWL16dYntZrOZ5557Dl9fX5ydnYmMjCQtLc06wcodV974FxUVMX78eEJCQnB1dcXPz48hQ4Zw6tQp6wV8C0q2pFrYsmULI0aMYOfOnWzcuJGioiIeeeQRrly5Yu3QpIolJyezYMECWrVqZe1QpIpcunSJsLAw7O3t+fe//82BAweYO3cuderUsXZoUkVeffVV5s+fz9tvv01qaiqvvvoqs2bN4q233rJ2aFIJrly5QuvWrXnnnXfK3D5r1izefPNN3nvvPXbt2oWrqytRUVHk5+dXcaRSGcob/7y8PPbu3cvUqVPZu3cvq1at4uDBg/zpT3+yQqQVo6XfpVo6d+4c9erVY8uWLTz00EPWDkeqSG5uLm3btuXdd9/lpZde4r777mPevHnWDksq2YQJE9i+fTtbt261dihiJT169MDb25tFixZZ2vr27YuzszMffvihFSOTymYwGPj000/p3bs3cH1Wy8/Pj2effZZx48YBkJ2djbe3N4mJiTz++ONWjFbutF+Of1mSk5N54IEHyMjIwGg0Vl1wFaSZLamWsrOzAfD09LRyJFKVRowYQffu3YmMjLR2KFKF1qxZQ2hoKP3796devXq0adOGhQsXWjssqUIdOnRg06ZNHDp0CIB9+/axbds2unbtauXIpKodPXqUM2fOlPh/wMPDg/bt27Njxw4rRibWkp2djcFgoHbt2tYOpUx21g5A5HaZTCbGjh1LWFgYLVu2tHY4UkWWL1/O3r17SU5OtnYoUsWOHDnC/PnzeeaZZ5g0aRLJycmMHj0aBwcHhg4dau3wpApMmDCBnJwcmjVrhq2tLcXFxbz88ssMHDjQ2qFJFTtz5gwA3t7eJdq9vb0t26TmyM/PZ/z48URHR+Pu7m7tcMqkZEuqnREjRrB//362bdtm7VCkivz000+MGTOGjRs34uTkZO1wpIqZTCZCQ0OZMWMGAG3atGH//v289957SrZqiI8//pilS5eybNkyWrRoQUpKCmPHjsXPz09/B0RqqKKiIgYMGIDZbGb+/PnWDuemVEYo1crIkSP54osvSEpKokGDBtYOR6rIN998Q2ZmJm3btsXOzg47Ozu2bNnCm2++iZ2dHcXFxdYOUSqRr68vzZs3L9EWHBzM8ePHrRSRVLX4+HgmTJjA448/TkhICIMHD+Zvf/sbr7zyirVDkyrm4+MDwNmzZ0u0nz171rJN7n43Eq2MjAw2btz4u53VAiVbUk2YzWZGjhzJp59+yn//+18CAgKsHZJUoU6dOvH999+TkpJieYWGhjJw4EBSUlKwtbW1dohSicLCwko96uHQoUM0bNjQShFJVcvLy8PGpuRXFltbW0wmk5UiEmsJCAjAx8eHTZs2WdpycnLYtWsXDz74oBUjk6pyI9FKS0vjP//5D3Xr1rV2SOVSGaFUCyNGjGDZsmV89tlnuLm5WeqyPTw8cHZ2tnJ0Utnc3NxK3Z/n6upK3bp1dd9eDfC3v/2NDh06MGPGDAYMGMDu3bt5//33ef/9960dmlSRnj178vLLL2M0GmnRogXffvstr732GrGxsdYOTSpBbm4uhw8ftrw/evQoKSkpeHp6YjQaGTt2LC+99BJBQUEEBAQwdepU/Pz8yl2xTqqP8sbf19eXfv36sXfvXr744guKi4st3wk9PT1xcHCwVtg3ZxapBoAyXwkJCdYOTawkPDzcPGbMGGuHIVXk888/N7ds2dLs6Ohobtasmfn999+3dkhShXJycsxjxowxG41Gs5OTk7lx48bmyZMnmwsKCqwdmlSCpKSkMv/PHzp0qNlsNptNJpN56tSpZm9vb7Ojo6O5U6dO5oMHD1o3aLljyhv/o0eP3vQ7YVJSkrVDL5OesyUiIiIiIlIJdM+WiIiIiIhIJVCyJSIiIiIiUgmUbImIiIiIiFQCJVsiIiIiIiKVQMmWiIiIiIhIJVCyJSIiIiIiUgmUbImIiIiIiFQCJVsiIiIiIiKVQMmWiIhIFTAYDKxevdraYYiISBVSsiUiIne1mJgYDAYDTz/9dKltI0aMwGAwEBMTc8fO9/zzz3PffffdseOJiEj1pWRLRETuev7+/ixfvpyrV69a2vLz81m2bBlGo9GKkYmIyN1MyZaIiNz12rZti7+/P6tWrbK0rVq1CqPRSJs2bSxtBQUFjB49mnr16uHk5MQf//hHkpOTLds3b96MwWBg06ZNhIaG4uLiQocOHTh48CAAiYmJTJ8+nX379mEwGDAYDCQmJlr2P3/+PH369MHFxYWgoCDWrFlT+RcvIiJWo2RLRERqhNjYWBISEizvFy9ezLBhw0r0+fvf/84nn3zCkiVL2Lt3L02aNCEqKoqLFy+W6Dd58mTmzp3Lnj17sLOzIzY2FoDHHnuMZ599lhYtWnD69GlOnz7NY489Ztlv+vTpDBgwgO+++45u3boxcODAUscWEZG7h5ItERGpEQYNGsS2bdvIyMggIyOD7du3M2jQIMv2K1euMH/+fGbPnk3Xrl1p3rw5CxcuxNnZmUWLFpU41ssvv0x4eDjNmzdnwoQJfP311+Tn5+Ps7EytWrWws7PDx8cHHx8fnJ2dLfvFxMQQHR1NkyZNmDFjBrm5uezevbvKPgMREaladtYOQEREpCp4eXnRvXt3EhMTMZvNdO/enXvuuceyPT09naKiIsLCwixt9vb2PPDAA6SmppY4VqtWrSx/9vX1BSAzM/OW93/9fD9XV1fc3d3JzMz8TdclIiK/X0q2RESkxoiNjWXkyJEAvPPOO7/6OPb29pY/GwwGAEwm023td2PfiuwnIiLVk8oIRUSkxujSpQuFhYUUFRURFRVVYltgYCAODg5s377d0lZUVERycjLNmzev8DkcHBwoLi6+YzGLiEj1pZktERGpMWxtbS0lgba2tiW2ubq68pe//IX4+Hg8PT0xGo3MmjWLvLw84uLiKnyORo0acfToUVJSUmjQoAFubm44Ojre0esQEZHqQcmWiIjUKO7u7jfdNnPmTEwmE4MHD+by5cuEhoayfv166tSpU+Hj9+3bl1WrVtGxY0eysrJISEi4ow9NFhGR6sNgNpvN1g5CRERERETkbqN7tkRERERERCqBki0REREREZFKoGRLRERERESkEijZEhERERERqQRKtkRERERERCqBki0REREREZFKoGRLRERERESkEijZEhERERERqQRKtkRERERERCqBki0REREREZFKoGRLRERERESkEvx/ErcaZ0shUYcAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Reload the data\n",
    "df_travel_cards = pd.read_csv('Travel_Cards.csv')\n",
    "df_travel_routes = pd.read_csv('Travel_routes.csv')\n",
    "\n",
    "def convert_to_dict(costs):\n",
    "    # Split the string into pairs of key-value\n",
    "    items = costs.strip(\"[]\").split(\"; \")\n",
    "    # For each pair, split into key and value and strip the unnecessary characters\n",
    "    items = [item.split(\": \") for item in items]\n",
    "    items = [(k.strip(\"'\"), float(v)) for k, v in items]\n",
    "    return dict(items)\n",
    "\n",
    "# Convert 'Costs' only\n",
    "df_travel_routes['Costs'] = df_travel_routes['Costs'].apply(convert_to_dict)\n",
    "\n",
    "# Initialize a dictionary to store the monthly costs for each travel card\n",
    "monthly_costs = {card: [0]*12 for card in df_travel_cards['Travel Card']}\n",
    "\n",
    "# Iterate over each row in the travel routes dataframe\n",
    "for i, row in df_travel_routes.iterrows():\n",
    "    route_costs = row['Costs']\n",
    "    times_per_month = row['How many times per month']\n",
    "    included_cards = row['Included in Travel Card']\n",
    "\n",
    "    # Calculate the monthly cost for each travel card\n",
    "    for card in monthly_costs.keys():\n",
    "        # The cost for the route is 0 if the travel card is included in the route\n",
    "        if card in included_cards:\n",
    "            cost = 0\n",
    "        # Use the cost associated with the 'Half-Fare' card if 'GA' is the only included card\n",
    "        elif included_cards == '[GA]':\n",
    "            cost = route_costs.get('Half-Fare', 0)\n",
    "        # Use the cost associated with the travel card, if it exists, or the cost associated with the 'Half-Fare' card, if it doesn't\n",
    "        else:\n",
    "            cost = route_costs.get(card, route_costs.get('Half-Fare', 0))\n",
    "\n",
    "        # Add the cost for the route multiplied by the number of times it's taken per month to the monthly costs\n",
    "        monthly_costs[card] = [x + cost * times_per_month for x in monthly_costs[card]]\n",
    "\n",
    "# Add the cost of each travel card divided by 12 to the monthly costs for that card\n",
    "for i, row in df_travel_cards.iterrows():\n",
    "    card = row['Travel Card']\n",
    "    cost = row['Cost (CHF)'] / 12  # Divide by 12 to get the monthly cost\n",
    "    monthly_costs[card] = [x + cost for x in monthly_costs[card]]\n",
    "\n",
    "# Calculate the cumulative costs\n",
    "cumulative_costs = {card: np.cumsum(monthly_costs[card]) for card in monthly_costs.keys()}\n",
    "\n",
    "# Get the total annual cost for each travel card as a dataframe\n",
    "df_total_costs = pd.DataFrame({card: [cumulative_costs[card][-1]] for card in cumulative_costs.keys()})\n",
    "\n",
    "# Sort the dataframe by the total annual cost\n",
    "df_total_costs = df_total_costs.sort_values(by=0, axis=1)\n",
    "\n",
    "# Flip the dataframe so that the travel cards are in the rows\n",
    "df_total_costs = df_total_costs.transpose()\n",
    "\n",
    "# Print the dataframe\n",
    "print(df_total_costs)\n",
    "\n",
    "# Adjust the cumulative costs for the GA card to reflect the total annual cost at the beginning of the year\n",
    "cumulative_costs['GA'] = [df_travel_cards[df_travel_cards['Travel Card'] == 'GA']['Cost (CHF)'].values[0]] * 12\n",
    "\n",
    "# Create a new figure\n",
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# Plot the cumulative costs for each travel card\n",
    "for card in cumulative_costs.keys():\n",
    "    plt.plot(range(1, 13), cumulative_costs[card], label=card)\n",
    "\n",
    "# Set the title and labels\n",
    "plt.title('Cumulative Costs over the Year')\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('Cost (CHF)')\n",
    "plt.legend()\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
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       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
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   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "# Initialize a dictionary to store the route costs for each travel card\n",
    "route_costs = {card: {destination: 0 for destination in df_travel_routes['Destination']} for card in df_travel_cards['Travel Card']}\n",
    "\n",
    "# Iterate over each row in the travel routes dataframe\n",
    "for i, row in df_travel_routes.iterrows():\n",
    "    destination = row['Destination']\n",
    "    route_costs_row = row['Costs']\n",
    "    times_per_month = row['How many times per month']\n",
    "    included_cards = row['Included in Travel Card']\n",
    "\n",
    "    # Calculate the route cost for each travel card\n",
    "    for card in route_costs.keys():\n",
    "        if card in included_cards:\n",
    "            cost = 0\n",
    "        elif included_cards == '[GA]':\n",
    "            cost = route_costs_row.get('Half-Fare', 0)\n",
    "        else:\n",
    "            cost = route_costs_row.get(card, route_costs_row.get('Half-Fare', 0))\n",
    "        route_costs[card][destination] += cost * times_per_month * 12\n",
    "\n",
    "# All the costs from the route_costs dictionary can be made a bit cheaper due to a new offer: Half-fare plus. There are three options: you pay 800 and get 1000, 1500 get 2000 or pay 2100 and get 3000. We can make a switch case with the best fitting option for each card.\n",
    "def half_fare_plus(cost):\n",
    "    if cost < 1000:\n",
    "        return cost * 800 / 1000\n",
    "    elif cost < 2000:\n",
    "        return cost * 1500 / 2000\n",
    "    else:\n",
    "        return cost * 2100 / 3000\n",
    "    \n",
    "# Apply the half_fare_plus function to all the costs in the route_costs dictionary\n",
    "route_costs = {card: {destination: half_fare_plus(cost) for destination, cost in costs.items()} for card, costs in route_costs.items()}\n",
    "\n",
    "# Get the card costs\n",
    "card_costs = df_travel_cards.set_index('Travel Card')['Cost (CHF)'].to_dict()\n",
    "\n",
    "# Calculate the total cost for each card\n",
    "total_costs = {card: sum(route_costs[card].values()) + card_costs[card] for card in route_costs.keys()}\n",
    "\n",
    "# Sort the travel cards by total cost\n",
    "sorted_cards = sorted(total_costs.items(), key=lambda x: x[1])\n",
    "\n",
    "# Get the cost of the cheapest card\n",
    "cheapest_card_cost = sorted_cards[0][1]\n",
    "\n",
    "# Plotting\n",
    "fig = go.Figure()\n",
    "\n",
    "for idx, destination in enumerate(df_travel_routes['Destination'].unique()):\n",
    "    # create a list of costs per route for each sorted card\n",
    "    costs_per_route = [route_costs[card][destination] for card, _ in sorted_cards]\n",
    "    fig.add_trace(go.Bar(\n",
    "        x=[card for card, _ in sorted_cards],\n",
    "        y=costs_per_route,\n",
    "        name=destination\n",
    "    ))\n",
    "\n",
    "# Add the costs of the cards themselves\n",
    "fig.add_trace(go.Bar(\n",
    "    x=[card for card, _ in sorted_cards],\n",
    "    y=[card_costs[card] for card, _ in sorted_cards],\n",
    "    name='Card Cost'\n",
    "))\n",
    "\n",
    "# Add the total costs of the cards as text annotations to the plot\n",
    "for i, (card, total_cost) in enumerate(sorted_cards):\n",
    "    fig.add_annotation(\n",
    "        x=i,  # this is the index of the card in the sorted list\n",
    "        y=total_cost + 100,  # this is the total cost of the card\n",
    "        text=str(round(total_cost, 2)),\n",
    "        showarrow=False\n",
    "    )\n",
    "\n",
    "    # Calculate the total route costs without the card cost for each card\n",
    "    total_route_costs = {card: sum(route_costs[card].values()) for card in route_costs.keys()}\n",
    "\n",
    "    # Add a red dot for the total route costs without the card cost\n",
    "    fig.add_trace(go.Scatter(\n",
    "        x=[card for card, _ in sorted_cards],\n",
    "        y=[total_route_costs[card] for card, _ in sorted_cards],\n",
    "        mode='markers',\n",
    "        line=dict(color='red', width=2),\n",
    "        showlegend=False  # Remove the legend for this trace\n",
    "    ))\n",
    "\n",
    "# Modify x-axis labels to include the difference to the cheapest card\n",
    "xaxis_labels = [f\"{card}<br>(+{round(total_cost - cheapest_card_cost, 2)}, CHF)\" for card, total_cost in sorted_cards]\n",
    "\n",
    "# Add the layout details\n",
    "fig.update_layout(\n",
    "    title='Annual Costs Breakdown for Each Travel Card',\n",
    "    xaxis=dict(title=\"Travel Card\", tickmode='array', tickvals=list(range(len(sorted_cards))), ticktext=xaxis_labels),\n",
    "    yaxis_title=\"Cost (CHF)\",\n",
    "    barmode='stack'\n",
    ")\n",
    "\n",
    "fig.show()\n",
    "\n",
    "# save the plot as a png with high resolution, 5000 by 2000 pixels\n",
    "fig.write_image(\"annual_costs_breakdown.png\", width=1000, height=500, scale=3)"
   ]
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