技术文档.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "01744711",
   "metadata": {
    "id": "01744711"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2e4019dc",
   "metadata": {
    "id": "2e4019dc"
   },
   "outputs": [],
   "source": [
    "X = pd.read_csv(\"ENVIRON_DISCLOSURE_SCORE_x.csv\")\n",
    "Y = pd.read_csv(\"ENVIRON_DISCLOSURE_SCORE_y.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6673df37",
   "metadata": {
    "id": "6673df37"
   },
   "outputs": [],
   "source": [
    "data = pd.merge(X, Y, on=['year', 'company'],how='left')\n",
    "data = data.drop_duplicates() # remove duplicates\n",
    "target = 'ENVIRON_DISCLOSURE_SCORE'\n",
    "# print(data.dtypes)\n",
    "# data['company'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f2b514ba",
   "metadata": {
    "id": "f2b514ba"
   },
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "data['year'] = data['year'].apply(lambda x: datetime.strptime(x, 'FY %Y').date().strftime('%Y'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6a64a57",
   "metadata": {
    "id": "c6a64a57"
   },
   "source": [
    "### 数据预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "16c14d98",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 936
    },
    "id": "16c14d98",
    "outputId": "dcd6a93e-d989-42bd-ed6b-cdbda3c9bd41"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ZH2W0fyLGuIqVpaR7am1xOHAmsGOM8WYr64WSqw7Pfjvx7nA4HA6HwzFhCCEMREkV3weOiTGOaXCVHA5HByGEsBfwFfBsjPGLpLw3MC9wHTAdzQn4LYCzbFszr+TkPMMQ8b55jPHR3LWnzV0zJd4nAzYArgaOijFe1PZ37+iucPLd4XA4HJ0GltRmSxRv7/EY45e57XUT8LZ/xdAvIYRpgCOR5fsDMcYdrLx3Zl2VWDz0Br4Ebosx7t+S6zgcDofD4XA46kcIYS7gP8CeMcYb69h/vPGEw+HougghHIWSmgK8hOZfNwIvxRjfs33msrJZUcz3p2KMv1oImp2Bb2OMf7J9i0LN7AisF2N8ODfvuxpYCVgsxjg6V6/NgGXQvPHiGOPpVu5zQEdd6FV7F4fD4XA42h8hhF1RctWdUCiXL/P72MTqMUTOA9xrClghipQhs6bCzn8acAvKan+zlY8zsp3E1XAcMAqY2M4Ral3H4XA4HA6Hw9EqTAKMBUbAeOOLMmS6WAhhCmQN63A4ujBs/jUJ8nj5DngT6I+Sob4aQrjTwlGNBfYHXkZW8MuZ1/NYYFgV4r0fmmuOA6YOIUyUEO/nI8v5w1PiPYTQK4SwGkr2vBSyeD89Ob/PAR11wcl3h8PhcDQUCZG9HPAv5D5YyVo95Aj4ccDfQwh1TbpCCMcDz4UQhgLEGEegjPY3AOvlCPg+9n9TCGERlFj1YStzRcvhcDgc3Rr5heZKZQ5HWyHpX18g8m1rI7h+q2L4sD9wg1m9OhyOLgojwk9GhPqXwMzARsCSaL42i/19FrgK+ByFmLkcWDFPtufDgVpI0nmBD4FzgM0BQgjnAHsCW8cY784d0wS8AGwH7BRjvN6O8XCjjhbByXeHw+FwNBRmXT4livP+dozx+0qTe9s32/YIcDCyRl+y1nVsUvYxMA3wpzoI+N+CMABYCyV/fb31d+pwOBwOR5fCoBDCwiGEVUMIvwdffHa0D8y6tHfSv0YArwDrAOtmFqZ5/dD0x1mA5wAPO+NwdEGEEI4IISwE4wny84CbgXlQ/q8Pzdp8DSu7DBHoGyNOc25gykpkeAhh/cSo6jsUPuZ74IwQwt+AvYENYowPFBy7CDA4xvjvJOxNcOLd0VI4+e5wOByOzoJxKMkqyd/xSCZckwDrmtLzKLBkjPGmaicOIQw1V8T/A/YB5gfurIOAjyghz2HA9THG/07QHTocDofD0QUQQtgbkR8vI6+vp0IIjxsRP3Fja1c/UrLWrfZbhhDCFiGE+TvgOnsh/euhEMJOIYRZzcvxAOAX4ERg5RBC3ywcoB3XB1gXWA14xMkwh6PrIYQwJ3AIcE/myZwQ8BcACwF/DSEMijGOjDF+FGM8Jca4CXr3N0YW6bdVOP82wF+A85Kwot+hEDLfA2sDVwBP2P7pmLEtmmuWhTj1RWhHa+Dku8PhcDgaAou7l+FH4C1goxDCTEUTqETR2QK4JYQwXYzx1xjjx3a+wjEthHAWcJNZVP0I3ItC1sxDdQL+BkuuMwy4IMZ4pZ3PJ+8Oh8Ph6LYIIVwEHIosCzdBYeFORMntbgF2CCFM0qj6tQRG1k4bQpgaGNro+nQVhBBWAG4HjqiWW6cNrnMliqW8IOpf1wHHhBBmjDG+D+wKTI/CSuwXQpjUwgHOg4wprgQujzHe1V51dDgc7YqPUNLUH4D7QgjzwXgC/nzgYmBO4O4QwmQw3puZGONLMcZ7MyOsjFzP4e/Ien4TmhPwywJvoySq2wQlbo7mibMlcA1wRYzx4Xa6d0cPgpPvDofD4ShDRi63J8lshPiZIYRBADHGn5BlwQIovufgZN9eyf+TAfMB96NYoONRxeJpQWCyLKGOXeuvVCfgr0UW7/8HnBljPDWri1s7OBwOh6O7IoRwDSJCDgKOjTHeHWN8Bo2N66DwbacBG1Za9O4sCCFsE0K4DngH+B/wdAjhmEz3cFRGjPFJ4AgU5/joEMLcbX0N62tbADsAa8QYZwOuBnZBHooADwIbIO/Ic4APQgivWvneqI+OT37Y1nV0OBztgxDCsBDCSuaZ/Dgac34B7i0g4C9BoWXuCSFMFmMcGwqSMGdzveQafWKM3wB7AU+j701KwH8PLI2I/7PRHLQvsCHy/Dozxnisncu/L44JQnAOweFwOBwZQghbIfe+M2KMP7TTNfohBWc/4BTgwhjjKNt2D7AycDRwR4zxq9xxmyMXxINjjDfXuE4vs446EDgS+B3wCTKEixbLfQOk0L0FbBZjHG7HDkWWWM/HGK9Jz9dGzeBwOBwOR6dCCOEqRE5sEmN8PCkP2cJzCGFm4G6gP7BcjPGbdHtnQQjhXGA94A2UnK83yi2zAnAfcHyM8ZWGVbCTwgwvemUkVgjhEER634R0w7fb6DoXoLAyq6Z9zba9B9wZYzwiKRuIEi/OD0wOPAP8N8b4km13Hc3h6CKwsWZ3kvffCPGV0LysH7B+jPEN29YP5fnaG83l1jHL9Xqu1TvGOC6EMAWKFb8iMq46JPnODQKeR3nE7kUeN6fHGE+y7f59cUwwnHx3OBwOBzDeGn0D5BW1S4zxn+14rclQHPWjkTXd+THGUTapvxoR8Lchd79XkUX8KsgK68wY42l2nmYTfps4jk+EE0JYGVnVL5+/pwICflOzfieEMMCs5F3pcjgcDke3RghhceAF4B/A1jHGL6vsuz4i4E+LMR7fMTWsHyGEYWhs3xd4PMb4tZVPjwjcMxF5u2+M8d1G1bMzI4QwkVmkEkI4FBlNtAkBb96NL6EcPifEGK+w8n7Iwv1R1A//Y/JjjPHTKufrdIs/DoejGPZ93gzYOMb4RG5bH0TAX4QWeFMCfiLgcOAYYNtKoaZCCIcBTShfydPZd8y2DQEutWvcTnMC/kVgNuDIGOPZVu5zQEebwMl3h8PhcBBCuARZux2OklZ91gHXnAyR6UciAv7sGOMPVn4usDUwEPgKGIDcxm+KMV5qxxcqQ2a1PsKs2wOykPoQODzGeGViARFyFvAXoLiDG1cjHRwOh8Ph6G4wQnQLNBbeARwVY/yiwr5TIxf+52OM23ZYJeuAWVRuAmyJiPeY6gshhP5Iv7gUuCXGuGfjatt5YJbokwH/RJ4B36QhHEIIRwBnoFAMp7cBAT8rsj6dEiVWvMK8FX+HiPeJbNcfUaija4G3Y4z3Tch1HQ5H4xBCuBqFdNk2xvhIzqtqUIzxuzos4BeMMf67wvkPRGFqxiFjsn+hmO7XAJ/GGD8xkv1iYA001h0cleA5I+DXiZa81Yl3R1vCyXeHw+Ho4QghbIcSqR0APBRj/LUdrjEDUoTGpi7qCQF/FCLgz8ncCEMISwIzA9MB/wU+iEq+VY14P83O9TKymH8eeAxN5P4WY9wt2TedjE+MrOFuBLaKMf65rdvA4XA4HI7OhhDCzjHG6+3/fsBOiJi4HVn/VSLgH0dj+pqdhaAIIWyKyJQzY4xHV9lvMHASCn+3ZuzhyfSSdgP4ApHwj6C46k/GGN+0/fZGYRtuQgYTb7TwOrPEGD9Mfs+KEiFODhyHdL2ngHuAPwI/Ia/HVYAlgD6IGHuwVTfqcDgahhDCAWhxd88Y4zCLx56R3icCvwHnxhh/Tgj4i9F7v0mM8b+58zUbd0IICyLP6dlQcvDpULLWWYBRwF3AA2ieeKltewg4tCBefKcY1xzdB06+OxwORw9HCOEilMR0q6ikNFn54sC8wHKIvP5XOmlqwfmPQ1Zo0wHDgX1ijE8VEPCZBfyFaT0KzlfRvdhi1k8OLG71ngHF7/sN+AYlWn0YJV57N8Y4Jjl2YmB6d0F3OBwOR0+Auf/vAiyQEKw1CfgQwiKIND0rxnh1R9a5GmzR/nBgXWCnGOP/Vdl3BbQ4v2+M8coOqmKnhOl7+6DnfhXwGUquuwzSnf6HCK27UALWU1GIwCtijK/VeY0Dga2AV2KMe2XEW0LATw1MgYj9fXJW9wNQssXpY4x/m+AbdjgcHQ5bvNvffm4ZY/yPlZ8PHAisFmN8LNm/N4rPfjWa280RLUdYwblTg6p5gfuRN/NZyEtrTfQ92xSYCRlojQVmRIuNN8cY927L+3U48nDy3eFwOHooTKnphRKRfRljXDfZdhCyCJsZCMhq/UHgwBjjey24RhbX7zYUu281YCqUYOeZZL88AX9uYgHfKsuDoKz0Q4GlgG1RstZ3kdI1EfA+8CbwGooJ+EB6rFs7OLorKuVK8Ji5DkfPQQjhGmBjlGw8n/ByALADBQS8hW3ZD42pe0VLeNlIhBCWiTH+y/6fF5HD6wE7xhhvz+2bJWPvg8iZm2KMR/XEb2COsFoQxVLeEBlMPAzMbr/XARYGJkUE/LrIGvX/gANijCNrXOcSYH079sEY40Pp9UMIsyDL+/mAY2OMF9j2fjHGX/I6metoDkfXRAhhe5TvqxfK77U3cBCwRYzx/oL9ewOrA0NijLdUOOcxKDzpiYkl/fzIwn00srR/ysqnQwt9e6I57pp2mn1jjJe31X06HEVw8t3hcDh6OJI4nocB36FJ1kbIKuACFLplH5S47IAY4yV1nvcqRLxvATxhcdbXQjH8XrfyplhKdJMR8Iei+J9nxxi/reM6AxCh3w/4BPgli/eexBHcDbkXLoASfM2LSPllkMvhSTHGi+u5L4ejq8MWpmZC78LnwLdGgDih4XD0ABjxvilKMv5YhX36AztSIuAPjzF+FULYErgSkaSXdVSdK8HuZXlgxWj5WkII8wGnIAJ+hxjjnwqOWxVZXG+RkcE9HUbAnwKsDewSY7w12bYwsCgi5ucy+UO0ZKlVznk6sBuwB9IFv7Xy3igpIqazZRbwg5EBxuW2n49LDkcXR26hbwdEwE+NvJNXBJ6rZ/Ezd56ASPfngCHAhcB5OQL+b8AYZFn/eLYtOd/KQO8Y4yNtcJsOR1U4+e5wOBw9DCGEk4ChmXtdCGEhRHhvZ7uMRMlq7k7jeYYQPkUKzma1FKSgTPNnoeSl9+SI8FuA2WOMyxQcNzmyfj8MWDbG+GyN6xyCYgKuDPyCEqv+AzgmxvhTKCVXXRJ4nJxlhSlu08cYP612HYeju8AmPasiAiUi8v0fwEExxh97ovWnw9GTEJKEpDHGx3Lj87FoMS5LbJ6GoLkVLcZfDJwcYzzV9mnYNyPxrtskxvh47l7mB06mgIAPIUyKdI1lgF1jjB90fO0bhxDCXCgm8lDkBfhpFlYwhLAAard1KfYcmBhZrS4WY3zSygr7QAhhMZSg9WyU3DYfU3nSGOMPIYSJYoxjQwizIwv4SYBL3SjC4eg+yBHnOyJCfCpgrRjj6y1daAshTBFjHBlCmBJ54cyDDLzOLSDgR9v1HqtkbOILfY72Rq9GV8DhcDgcHYcQwhTIdXjbEMJZABZz7zBgBRSPc/4Y4+mxlFk+mEXSj8CrdU6yv0Mk/l4hhMFm1dTPtr0JNIUQLg4hnBxCWCqEMNTqMgo4AViuDuL9CuAQ4AOUZPVYRMDvD7wQQpgtmei9Dfxg95gd3ysKn2a/67gvh6PLIoRwHrI2mgRZNx4OfImsEl8IIcxu76q/Cw5HN0QIYX1gd+BPBcT7Bej78Hq2f4zxF+AG5Pm2I3A58hTLiPdenYV4t/qOr0tUcr7jgPuAm8xiP1t03wC1w609kHg/HRFVdyOi6kngoRDCwQAxxtcptduNuXYDeReOToj3an1gepN/xfIY7uva83s7hPAv4MAQwrRRYQ03Q7GYTzTjEIfD0Q2Qkd72/43IUv0H4K4QwoLp9loIihO/Twhh4qg8YVlo0f2AQ4PCimXjwLpI770QWMkMs5qR7E68O9obbvnucDgcPQwhhNnQxGpj4JoY46EF+6QZ6Psgy7eTkYXYA/n9k+P+CNwL3AlsiSzk/g1sG2McEZTU65/ATygJ6pR26GtoAvgA8EBCBhRaIYQQDkcxAncEnoox/mTl/YG9kEXbd8DvY4xfG/F/PzA6xrihW/c6ehosNMMGKM7l0zHGEVbez8qOpvydcQsgh6ObwawAD0Rj50FZ2Bgj3ndD1vBFcXcH2DExxniVlTXsG2HE7QbAdjHGh3PbdgbeiqUY8GUhaIBfUR6ak2OMp9k+PUInCCFchsjtU5AuNhKF7NkPWBK4OMZ4oO27IHAiarftY5XktVWutxGK8/67GOMLIYSpkO52EDICfAFZvs5pdTrTvBZnB5aKMd7W6pt1ONoAmXdGo+vRnRCah6A5CuiNFlJrWsDb938HYJUY4z8TL+cp0PdmToot4O9Boa72jzE+2J736OheaCsdoU9bVMbhcDgcnR+JtcH7IYRT0MRnNxtPDrN9+sYYf02UlelQ7M/Mzbwa8Z65st8YY/w1hPAXlKz1IuAam9zfB9wIXBhjfDOE8DtgcWAbFFe+zLK+wCUwAAOBtYCbgH+YZV62YPBzCOFyFN/vPOC2EMI6UQm7/gnsEUIYGmMcPgFN6XB0Kdg7sSFacHs2XVizd+NKtCB2HnBnCGH1GOOvjauxw+FoS2RhPWKM/w0hnIHG/0tCCN8BCyEr8EoJ73oZIXpt9l1oMPG+F7ArRrxneottuxjYHoXWAiDG+EYI4TiUOD4jc09MiPcesdAYQtgOWYDuAvw9lmIffxRCeAU4ANg/hDA6xnhsjPG1EMLxqN1uDyH0jzHe1MLLvoYMMB4LIfwD5duZCRlpXBBjfMp00weBbYGzjOR4D3jP6t0jno+j8yGEsDuwSgjhOuCRnrBA1xFIw77EGG8yp5rDgPtCCBvFGF+pdKwZkmyCQtX80843zvTZkSGETRABv5/tf26M8Tcb+zYCnqZk+OVwVEUIYcMY4z1t9e47+e5wOBzdHCGEOYCvY5K81Aj4k+3n7kbAH26keZYEaw9kvT4rcHyM8Vw7X1GcvGsQsbdujPFRu8aYEMJdtst5wPqIeN8PTeYAXogxPhdCuAGYNMb4VbV7iTFGs5xaDrjEiMMQhd/s/7EhhFuBxZCl3u+QsvUZim86GHDy3dEjEELYGnmD/DHG+LSV9Y4xjit4ZxayfVcB/t64WjscjrZCCGFjYLoQwrMxxhdt/D8NLY7faH/XzFuQ27E7ARuGEDZPF+QaTIb+BLwDnBFCeCaWYpWfj7z0to4xvpQeYAT8qfbzmRjjhXZMTyJ2l0WE9r+SBdiMAHs9hHA20o+ODCH8K8b4NyOsTrLyyVp6wRjje0F5BHZClvUjUI6hF2KMn2bXN+OI5YHJY4w/5s7RU56PoxPBvifro1xSvzrx3rYoIOB7A6cjPfSVomNCCJci4n2DGOPTOWvkLHlzNQL+9aCQpCPb+fYc3QAhhGuB7UIIc2d6xoTCY3o6HA5HN4aR4s8DT4UQDg4hrGPlfc2y6GTkhrdXCOEckAUBMDuwKCKsD6pBvJ+NLKk2jjE+atbp2LnGIAXoEOATYGZgoFkpBJTwkRjjjxnxHmrH+8sIgCF2bGopH00Z+xE4DeiPJnyghKs7xxjfqaftHI5ugjdRfN91QggnwHgrod72f/rOnIGIuEUaVVmHw9F2sPH5HGALSovexBjfR+/7pVY0R8GxWwBXAv9LrKQbhkS3uAmFKfgVeDqEMMC8+fZEYXP+VnRcVH6bP/Q04j0I/dCi6ltGTmVtMv7+Y4zvIk/FcYioz8r/i9r1UlqA5BoPIfL9d8BKMca/RMu1YwTcQGAW4Bng+9bep8PRVgjy1N0W5ZLaKsb4RGNr1D0Ry2PAXw+sXMm7JihB6z5oTHrRjslClF6LkqpmxiUjEUn/LhaKNITQ144Zafs5D+qoCONPNgLWbiviHdzy3eFwOLotQghTI1IclOX9WKBfCOF94F8hhOuBN1CC0ghsb5PRQ2KM/zN3419ijN/Z+YqI96uQu/q3aGL3pJF5vY3Ezyzg/2KHXAT8KYSwVSXLgzomw012vWVN4YoFBHwvZGH1BTCFbXo3I957yqTb0XMRQlgFxXZ/xUj3JuAQI9pPNAI+szrK3pmvkVfIYDtHj4iD7HB0R4QQLkJJ1A9B1s5lYTxijO+aJeEkwGX2vl9u+2wJ3AycGmM82coa9j0IIayIErX/18jju9FC4bkobnkAVgaeKzh866BwcxfGUq6L0BN0gOSZ/RJC+BqYN4QwSYxxdIV9nw4hPAEsZ2TVb+ZZOCp3vppIFnZjjHEsek75nEL9EEm2CXBg9NjajgYjhLAWCre5N/DX/MJj2n8dwoSMDTkL+LeqnO9+4Ak0r30jhHBHlPfz+SiPxU52vnEZAW8W8PehxdoHUQis8ddtTX0d3R9GvG8KbBpjfKwtz+3ku8PhcHRDmOLyVQhhIZTI9AvgdmQFuzOwOkqu9ilwK3KrfA7YIYTwa4zxyJiLi15AvA9DoWa2Q1nmdzcF6vhE+ckI+NGhPATNn0MIm7bG9S/G+LmR7ocBd8QY7w8l1+VsotcUQpjZDvmvHVcxlrzD0Z0QFMZpbvRefhpjfDuUwkwdHELACPimUApB0xRCWAzoBzwF5e+Mw+HoOggh7IKstnZDSczHk0V5a+cQwlmIvL40hBDRAtzNwGkJ8d7IGO8no0WEzxDBMtKI3b+gJH0HAfOgb11TqnuY9f4tKJzBePSEb1sIYUhU8uysPf6LCIWZEHk1vp2grE1+RiFmYr6dWtpuRfsnxPtSKNTMscA5Zvnqi76ORmMe9D18Mf1uhhBWBpYG1g4hvIy+qz0+aWfBd6bFSOdv9jsWfJ9GhBA2Q97UFwDfhhDWQGR8Wb6SHAG/AbBijPHfOBw1YEaFG2LEe9ovQwhHAB/GGP/U2vM7+e5wOBzdDAkR3Scqvt0qKOb5tiiEzJYhhD7IUmAJlJysCZjBTnF4COHuGOOzVa5xAxqcNo8xPhJCeAq5r+9qA9VxBQT8mBDCn1HIs+uBFYG/VLhELfwfsAbwlxDCmtFcQpMBsg+wGvAjig3rcPQI2KLYRkhx/DQrjzG+lSPgQ4zxhISkyhIZvwm83cHVdjgcbYulkJXfIzkCaV5gfhRa7vMY480xxneCkrD+Blxmu54QYzzFjmkk8X4pIoxPQbHaP0rrFEK4E+kvZwLPhhCWjTF+ZDrApihEzfh76SkIIRwJHBRCWCHGmH3PL0N622UovEMW/i/VnaZEnhD/iKWcIG1KhIcQJgJ2AI5HXozHRQtp08i+5nAY5kdGCF/Z+9ELOBolJB4MfIlCKG0RQtgzxvjXRlW00QghHI48KlcwI49Wvb85gnNd4NEY48/5/YxM3xi4G/gr8AvK8dEsUXgyB/0a+LOd278vjoqwxfrdgZMLiPcLkTHD2hNyDY915HA4HN0U2YQ7Kmv8CsgS9vIQwlpRiWdujzEeCiyMEqueiSxe969GvBtGAhvGGB+xa3yCwtf8G9glKP5qWWxp+/0jcCcwb4yxtcQ7McaXgVOBD4AHQwgHhBAWhvHkwi7A2cBVMZd4zeHorjBXyc2w/Au5bSHKpfdk5IZ7UFAivQybAH8AbowWnsLhcHQ9GLm5ANA3xvhTUn4AcC9avD4DuDGEcDOMj/d9LnAtcEAnId4PRd+l3YBrTZcpCxljE+O7UFiBH4FnQgizAKsi6/3T03vp6HtoIL4CxgB3hBDmtrIPEPG+Ygjh7yGEyaIBxvebtVDfeQaqW7qHELYKIczX0opFhaD5AuXl2c2Jd0ejEUJYM4Qw1H7eAEyFvpPnAI8CJwGvoe/RzMiYaQCwTVDopJ6Kn1BY0ztCCHPFJIZ7vcgRnPuhMWq5SvtHhcDaGOmxAZg4hDAgO1du33G53/59cVTDh6j/HRJC2CTpl+cDuyIPi6cm5ALBvbocDoejeyCEsCmydlsO+BjFc78Y+DkqLt5iwD+A94CjiywFQghTxCQZTV5RCSGshBKzfQ08FmP8Pt03hDATcAmyqL8uxnhcpXNVK69xn6mithawB7L0HY0mnP2R2/TVMcZz8sc4HN0RIYQrEPG+BfBE2t+DQlD8B7lRRyNjTgDWQ2GgXkAE1ikxxtPsGH9nHI4uihDCdYgoOgYlsVwffR/+gwil9xGBtA9wSIzxAjtucIzxW/u/IWSoESgTA39CoVKOxWKP2/apUeiUyYCvzMOvF7rfU1Dyzn7ASTHGkxp5Lx0N8xT4MsZ4qn33j0QeDZuY99PUwMHIWOI9YBhKRj8t0h8PB86IMZ5eeIHSddZAMZRvB06MrUhkH8rDA/l442gIbAFycWDNGOMn5gW4FQpVNQhZup+BvIjeS467HxHxS8UYx3R8zTsHku/Mr8jw450qc76yUDIFxPuFwB4xxmvruO4USG9dAHkl/MUMvByOFiHXDxdA7/uqwDom+yBP/wcm+Fo+zjkcDkfXRwjhEmBd4Btk3bQQMCfwFhpE7osxfhtCWBTFgH8PODJavMKQSyBUNBEKIZyNQr1MhSzkbosxfplsr0XAtzoeYMH9jlfsQggToxA2vwOmBv4FvJNZ7/eUSbej5yKEcBAi0ceTTcm2CxHRskTqBWIE/LGIrO9LDySqHI7uhmzsDiH0Bx4BlrVNXyOr5z/HGF+3fadBZPw9Mcbdi87TgVUvQ1K3S2ISMiaEsCtyC1/Kir4D9o0x3mqk/eYonMn1Mcbz7Jge8T0zz6fNgY1ijI9b2a7AEYiA3zTG+GYIYQjK+7M/0ptA4RteAW6JMV5mx1ZttxDCqYiUuB+56bcqxF8FfXMeYD7kmTkOeUx+YVavDkebIChM3ybAVjHGh3PbhqJFqfdjkgjYvjOZZfz7iCzucQlYc/Ow7DtTkYAPIUyGwoGOjjE+NCHEe3LOyREBvyD6nt3tBLxjQhFCWBBFA1gbiMAaMedNbPvtCCwZY9y33nN7zHeHw+Ho4ghKlpbFKXs2xjjclMbfISuwC5Fb3m0xxpdDCMuj8DKnmnJ0f15xLJgIXY4mdQcDT0aLu5o7JstY/7EpUpegBK59YoxHtRXxnlwrS676I/CASRlsn24/6Xb0eHyIPF02CyG8FmO8C8YT77sA68Vc+KWo+JxnIOvRB2KMV9oxPYKocji6C0IIE8UYxybEe++oeLnLhRA2R0lJn0TkZTq290VW8R/mz9kJrJDHAKOAZUIISyCPth2R6/fHyNIyotjh14QQ3osxPhtCuAN4OSqMTo/5noUQrkYegJtkxDtAjPFai8RwBKVE92+GEP4UY7wthLAs8jL4ChgVLU9ItXbLjDVijMcGJeg9wMrrJuBzhPtg9KyzbUcgT41FUViLKYBDgNtDCBfFGN+os1kcjoqwxapNyb0ztq1XjHE4Sj6dN1DqQyk80+U9iXhPxpgQk+TWue/MX0IIZQS8Ee97IEJzByjLM5ER73sCf2tJfWKMo0IImwB3AFcB/UMIN7blfNPRfRFCWBWYDo0zj0Xz/I8xvhZCOAaF2N0S5UHJH7sFcA1K/ls/YowuLi4uLm0omFdRB11rMRSHcFegt5X1SrbPjOKwf4JcI7PyhZGl0wfAzDWusY8dv3Z67ir797K/MyGLqDHA0o1+Li4u3VmQ58urKEzDyiie7mhg3Qr7Z9+LKZOymu+3i4tL5xHgUJT/ZP5ceb+Cffsk//cG9gI+A1Zt9H3k6pnpEOshy/bfUFLV74CLgMWSfdezbbsUnKfDdLEGt9dZ1gabFLWj/b8rSj7/BjB3tTaqp92AiZL/T0GLOLcAc9VxbEj+3wsZagyy35ejxZXDgUXQAtGCwHV2j48CCzW6zV26tlifGwX8Pq/3WN9bqsJxcwD7Aj8AxzT6Pjq4zfYFdgJmy5X3Tf7PvjP/zb4FaPHsYPuOH5879iB7r3dFXtqPApO2om5TAC8iy/mGt5VL5xdEmn8BjLU++AowY26fhVBugR+RR1lWvqUdd1xSVpe+4WFnHA6How2RWKC1WYiVGtfbGrgCWDZWsAYKISyCrMKfjzFumJQvjhTMK6qcvxfwRxRDff9oMd7rqFdm7TArIgXuq7H/5sDsKL7iVcCnsQ2tSXLujR5btJMhhLABMClwb719rKcjhLAmItDvT8rWQ6T7dOhdWjnG+M98nw8hbIRyQxwJjItxvCWTvxcORxdBUJ6XOxCpMQbpAo/GxD26yILZQrqsA1yKwk2d1XG1ro6CUAWLoNj0vwK3Ah/GGMckOsbiwBPAzjHGOxtR50YihHAtsLP9PAFZ4n6TWKjmQ0MciUiDzDK1Ll01KOFcX0Sq3YblEkq2nw7sB9xDlRA0OV1sX5SXaOcY440WAmRjYDuUt+Tn3LEnAUcjMuSAGOPHdTWSw5EghLA/srS+JMZ4QG7beYgQXiHG+HRS3hdZbh+IwiBdGWO80LZ1e++aEMIewJVoAfR7ZMH+dIzxNduevte7IQv4X5C30iIot8TxMcZTbZ9eaM53PXBzjPGqoNj766DFtc9a2q4hhH7pN8nhqATzesly4jyPvMb2Bd5FxghpmKkFUf6HVYFtgIDy0ZwWWxOqs9GrDi4uLi7dRVD85LuxVXvMsrSdrpVZhh2HrNIntt9FVkz9kLXYKBQHPpBYwFU6zsqnR8rWwXXWa0C+jpV+J+WXINfOkWj1+X00MaxYrwrnqbiv3fMMJjPWe06X9hdTat4xmbfR9ekKApwMvImsNmZLvzXIAv4/wEcklhrJ9i3R5PGwRt+Hi4tL6wV5tn0FjAButPf6F2SBvBIFFoSIfL0DhZo5PClvmNcLsDWKBTwgV95Mh6Lcmruv3c+7wCKNfh4NaLerUJ6fpdDCRBMi4Keq0ma72tjxbr3jLUrU22Tyg407DwDbA4sn+x2KFoFuKTp3qqMhon4csKv9vhotCqxRcFw6vp1n9dgtf04Xl3oEWa+/YjrnPkn5hda/1yo4ZhK0yHUusFpS3iO8BVH+hVEo+exf7R38xN7HmYH+uf13R142o2zfY/NthuZls2bvMDC/fc+uncC69ohn4tI6QUYKw4EVKPfgOgnxEHPY73TcXAjxO9k4eHyyrUX9rRcOh8PhmGCEEHoD8wLLABeHECaNMY6z8jZHLK2wvoMI8t9beZnlqq3G/oIshQYBk0Whaoz3BBOhCdFPdr6KuUJCCAOAlUII/XJ1zNc5PeYaZNW2HxoI10Zk/3khhCmq1Ct/ntTqYu0QwsLJtu3RZPA9ROy/GEI4JYQwRz3ndrQfQgiXopjkZ6DwKG82uEqdHpZ/YXe0oLZajPF9+9YEgBjj34CjgG+B00MIGyfHbo1IupNjjOd0eOUdDkebwMb2j5Dr9KTADcjC8BZgTeBB4P4QwoohhBntmP4o0ebEaEH97ORcDbHcDCEciYjj64CHrL7TAUSzyM6+bTkr7smBrVBy1ctjjK80oPoNQwjhRhQCYssY4/Mxxm1RAsgTgH2CkqoCpXw89v+1qM8MAhav83L/AW6y/69Fizf90FjyaAjh8RDCIcDN6DkuDxwRlDQ1q29RcsU9o2JF90UxtMcB02R6c1Ln8bp0jPEQ4AUUrqaa7upwFCLG+D9k9ToGODiEsJ15duwGbB1jfLDgsLExxutRqJlHoMfllHoPuB0teF6CxpH/obnbc8ANIYT5QgiDAGKMw5BXyxjgkJhYvMfynF0fJO/wR8A/gFVDCPPa/qGeyqX79aBn4mghQgjroNwCz8QYn4yKVNDPNv8ZefkPsbK0T/0HGT3di/rzyXa+lutOjV59cHFxcenqQmnVvj9y4/4CTUqqWsBnx7XwWhuQWDUhi6cfkFI0fZXjtkIxy2at4xpzJv/3A15GydomqlZvpIS9SZ3x+ii5MK6YlPVCrl2jMev3rLxW+9v/B1p7rGK/zwfeRi5ie1od70Ru+o9n+7l0vNjz+BhZaqfWB0XeG27JonbY39psHRJLo6L2ATZEMeDfQC6V6yCr2BO8XV1cuocAK9p4ebP9nhSYFsXhbkKLcE+iRc4+aEF9cHJ8Q78BKOFhEyJ3XkYE7L8QsTxZsl86zm+PFh8/B44u2qe7C0pauHr+GZoumFnAD8kdk+43Xx3XGJT8PytwF7IY3BAYgHIH7Qc8gyxcv0OLPr8gffMvKJlq3uL9N3KW68iy+DVkWbsTBfomylMQkOXiJ8DARj8Hl64h9j28LVc2u31zfkAGRmtZed5rdxPgMmDyRt9HB7fZnSRW6Mm3+iT7PS1awMvyMXyNFuk2So6ZN/m/5jwOWAIZfB3Zgnqm34gNgZUa3XYunVPsnT/f+uv5uW2bosWiD5Bn4IP27s+T7DPBObIa3gguLi4u3UEoJS/sbxODqgQ8miCvgLk31XmNFW3AuDSdVCE3yCbkfj2VlYVEmemHQns8BgyhygQVZe5+nlLyq4AslMaieGh9s/LccYNMOb2JnOt4hevMZ3V+juaJ4mZDFhAbozA5aZK47J565euBJnW/Ygl3UIzBr2xATQfMwcjNfTSa5Hsy2AYIstC8Od9fgLmANRA53+Pce6u0V2/k7nt5QZvNAiwLbE4SfsEmIi/Ze9CEE+8uLl1WkvEvP/5ejiaNcyRlO9u4fRfwlr3/H1I+kWw4WW26w9+sbr9D8Zbftfo+j0izgZkeACyK9KungO2T8/SI7xmwCgpxuFWuPNWT6iLgq7UbcA4KBTNjUjazPavvgW1y+89lOtitKIlvE7B3bp/drXzX9NqUiPZJkQHHVyhWdCV98zxEvk/S6Ofh0vnFdKebTOe/PLdtVuDfaNFnr6Q8+9ZuaX32iEbfRwe32dUoBMdaufK70KJnOgfdES24PYwI+CY0t5o2356Vno/97YW8su6097tmWCzK54AH2LXXbHT7uXQuyfWTGSiFL7vIyhayce0ZxLHci0j4JrQw9zfKDR9brTs1vDFcXFxcurokSlotAj6baEyGktF8T0Iu1nGdSYHDTcm5GJjaygcgN+CfUfiO+ZJjBqMEId8jF99q5x+GrJdWzt3XQDR5/xxZzw3I3U9fZIn2FbkJYY3rbYGso/4MLJBcbxUrH2P3+ooNlEsDU+Tb3f7Pxw+9EsUOXCnZJz/p3BAp47e0R39wqdw+9g58hBJepdv2QZbaWVy9H4HLGl3nRou12VBkWXhkbttuwItJm30EHJVs38DKDkjKegRR5eLSXQRZrQ/OlWU6x/I2Xl5vv3e0b8GJ9nsW5P2ya6Pvo8K9HW313c5+z4cWyJ+28peQy/dcyf3MlBzfI75niBB/HRHUl5J4BqT9wf6vSMDXea0b7PhzaE7A/xVZC2+F5RvK9dNpUMLKrCzT7dbPnrH97ldw3aoEPCJLnwDOSstdXIoEJaBfzvSnS0yHuiq3z2zIAv49kgUj+wb9Qnl8527f3xDx/jVKPJmVZfO97Sm3ft8lN9YsihZQK8430XzuZpTno8jTdRs75w72u6b3OJoDjgV2b3T7uXR+MR0iI+BvQxzJFZQb6k2B8p1cAfyhza7d6Jt3cXFx6Ypik46FKBHr2cQgmyjkCfhJrHwK4GBkoX1SndcamP4PHIbcdi/BJlXA1JQmS5+gRFxXICuFEShOIWldc9coI94Lts+N4vuNQsT/tMh9fSFKSbaOqeNe1s393tIUprtNOV4EEeIPoIWGM5GF2492bx8DC1LuPp0R75kb8/q278XkkgDlrt0bJaxtAtZrRR+YAxH4x1kdlqBEhrRbst3uIogc+BhZuW+CLJOaUJigfVAM2IfsXdmi0fXtDIJCJb1m7+NqyFNlPOGOrF3fRRZLKybHzZz83yOIKheX7iIonNp9yBLrHEqeaRkh0gdZHb4JnGrfhJOpEAKuSAfowHsJ+f+RxePrwD8L7nus3dfPNs4Po8IifHcW5Fn4NSKmpqmyX56A/8X6wtBWPJ8LrS+dRzEB/z3ShScqun7aR3Nl2yMd9S0UEulaZDmf6ckpAb8TJb16IhTr/U0s5I6LSyWxfjUKWMZ+T4e8hIoI+CwEzXvWx7awb06rEyt2RQHOtnd+c/ud9zoZgMIZ/gOR7C0aa4Cp7Lv0nclDaHFk6tx+jyFDnELvFoqNr3ZrdPu5dC5BYZG2RLzLzsA8lLzoZkWRA74G3kqO6ZM7R9/k/wnWNxreKC4uLi5dTZAlUZNNHP6OLLIHJ9uzD3s/SgT89Sgx6l5UyPxe4VrbIMuNDZKyiSkn4NOJ6K4o6dbbiCy/MlOiKl0LTWZHFE1mTAGd2/6f2hSijAj/HMX/fJU6rGpRSIwm4LxceUbA/wNN5q6kuTXVUsAe5KwpTOlqsvvOJvIzoxiEY1DokophcOy8P9GC+IJ23OHIPe0nZGHfZHW/BbPmwgn4Sm2XEUZLorBDmcX2tyg80oLJvkNs28mNrneD2yzr25tRcoXM+tx5lIeamc227VfpPC4uLl1DEEn5GbIU/D9ECKVxeLMF3+XQwnUT8qyrGf6tQfeT1Tcl3gMKpdIE7GTlmUXl0UiX2gAtNjb7rnV3QeFaPkL5UWp+wykn4P9s7bhUS5+R/X8xtQn4LUgI+Brnvszu5SEUt/8x06G+QXrtjLZfSsDvgIj3ja2PH9zoZ+LSucW+Fd+Q8y6mNgH/gm3rcWH6KBlzjEShXzLv6t65v1vZfuPs+zxxnedfjdIC2wxo/vq2nedp+45Mbtt3srFud/tdLdeYE+8uzQQtJL1l/Tmbp49AfEx/22dOZNDQBFyQHNtu73vDG8bFxcWlqwkiwJrQhPh1RBzfRxJ/NNk3s4D/BIVPaQnxfh7wPoo1tnRuW56AH5ps62Pb++eOKSLeM8uF1ex3usJ7CVo4WIAkNidabNgXxZhfj/oT6syJrPNHAufmtm2OSP0vgSWS8mZuyVbeG03+/kMp1Myyyfahdq1f0IJHxbZAsWazuG/1TGwvs2OOQlb4k9q93WXXezYZ2Lu9wl6PFLUrIlymQiTLXvY88xYHc6HJ914dUc/OKpSHeFrU3v0TrH365fZdDBEiWza63i4uLq0XRIZ8i7yDskX9QxHZMEtu3xmQZ8wnwJKNrnvBvWyPLKn/j1Ki0DQ3zZx2r1ejRfMm4CTKk66m43a3X0i09ukF/BEtvtSVzN6OTWPAr1XnMWn71kvA34VIsh1q6TvIK+NLlPx7sJX1Q7H+70Febidilv2mW72BdO0r6YEhQFxaLohM+5WcJ2/yralFwL8LHJKUdXs9HhlhfQOsjIxgPkMJk6fNt4F9q98D/gvMVuf5M8I+fb8nQiEoj0GhxZqQp/O+KAHz28A9Vc55FJp/d8pwai6NE8RfjEChy2ayfjafjTO/IMOvbJ4+K6UQNOe1e90a3TguLi4uXUVsIhRQrLCnEPG7Dlr5/9I+3I8Bh1AeKmYAJYuCQ5PyakT1BciqfEtghqJjTDnJCPiLKXArrnGNiez4r+1+0sna+Sim53r1nCtrn1rbbJC7DpGDeQJ+U0oJ4uav87wz2N8b0MR9mmRbFoqnkIC3fVZECmddYWcoWdOsjVl7ULIGmRS5X45FHhF96zlnT5Fa/cf2SftgHxR+5hNguUbXv4Pb6iBgGWD6OvZNSZI+KFTDB3RCAs7FpTsIykuyKonXWTtc4wK0IL1o7ru4EbIIXhstXC5BiZjfjnLr8U5BGiGi62OU2PA9q+OmyfZscfEEyi0qBzaivp1J0AL11xgZ2JJnSvPF7EpeiXugMHqT5MpTY4xKBPwsSO+tukCOQqW9iCxV++TrY/rT/yHL9tTTMyPhmoDDa92LS88W5CmUhd9cPynPvjH1EPCT5o/rzoIMxMpykKGQn5+h+VhGlqe65v7WzuMXUuu4zh/R/Oh4moeZmRkZtr1CKc/HM/b/NhXO9wSwf6Pbz6VzCfKQeg95y41P5mt/J0VJ3LN5epbseyZKIZeubtf6NbqBXFxcXLqCkCO2Ecn6K2ZRhOKK7UNp9f41m2QsYNv7UR6DuRopvgUizzakIHQJ5bHuBqIQKL8hq7IWJday4/dExPUzVnY6Ctmydo1j61JK80oZ1Qn4LATNHSThR2q0wTXkkgMl26ahnIAfkGybBFlhPAHMWcd9nEUF9+1kYB+IVtzHAgc2ut82Wuw9ObsVfWYIcjv9CTis0ffRwW22j/WzrxGpsQuJWy9JArrcezA5sj78icRqy8XFpe3EJm7voAXrWdvpGgujsHEjsQU4SqTR1TaevW/j/ihElPRFHmEvIaJ7kvzY26D2usbquC4wCIXFehB5DWYL2Nm9rWr7PkGOnOmpYt/1srw9Bftk7TcDsGYLz38gpTCC15IQ37a9X/J/JQK+pkU+yuHyMzkvztw+M1j//Q+JsYT15a2S392eEHVpudi3cYTpQV+iRcoNk+0h9zcj4L8mCeWV37+7CyIrV87fM8UEfLZwNpt9M56iRogzyhePb7FvyPHAVAXPZmpgTeB+pMs2AZv1xOfi0jpBi/iv5HUIyufpl9l4tFeyfUa0EHVgu9av0Q3k4uLi0tnFlITnc4rCJMg18fHcvvugifE7iIAdg8jY1IKoHtfcp2huhbQ4IpCvRPFRB1r5xMjavskmTxWTjObOF5Lj90KW7iOszssX1ROFh1mnzvPPmb9W8ntWFHfte+Ccgms0oQRyVS0LKU3sV6myT94CPovJvjVSunev415mRNZXX5C4OFJuuZUN7JOhxZMHGt13Gyko9M8DyJKtrlBLtn1P4FZEIB1R73HdRVAegs/tXXzV3oVn7TvUn9wE0v7fzt6Fz0jyF+TfOxcXl9YLcKmNAXsBC7XjdXrZOPgOsuDMXP8vtO/pFoionAq5T/+MeW+hkAsHNrqtkvb6BoWqS3WgM9DC4qwoafvgZNu1povMlLVFo++jAe2WevBNjuJQP0kNTygUG34sVRKyFhyztelQX1Py4LwTJacr0gEvsX0uIknkbdsKw8sldRsJTGe/Cw1LkDHJL5jnFjkPwp7YH1xqCzLYGUkphOYc1qffotyTIk/AT4tI+yaqzCO6oyBy/XhyHkaUW7g3I+CTbX8EDqrzWuki3q3kCHh793vljtmICkZgRd8aFxfrRw8BD1fYns3TB6M55l257ZOk52qXOja6kVxcXFw6u6AV0nFYDGVkXTYRsgL6FVuVB3ZLFIqBNqn5P1rgFmcDx62IdOuVlB1uClCTXbMJWYcNsX0mBY6jhcnIKCfg90GWIm8n5akStoVd97g6znsqSqq1Zv5aye+MgP+GnHUzig+7b41rXGXK9Sr58yOXyBWT3ykBv6ed/2cSa7JaAy0KA/IUsjjcPSlPCfjMhe1yZLnYIk+E7iYoxt6taJEljdVayf19HpTE7e8kMcsr7d8dBVljPYVItY2Abe29bEJk3HGUh2VawvZ9GNiuJ7aZi0t7C3CwjcHrkiSXrDVutOI648khFIrtfZRj5Br7jq6f239q+zacUelcDWqvDa1eDyVlmU5zGyLKhiPr/Yez+0KJuH+lwBK1JwjyPHyKZHEHxTZuIjEeSNvT/h+ECPFbqSP5KSV3/LmRi/49yE3/eJRnpQmR/tvQPL9ARlYu34L7Wt6O2bPC9l5JfZry/dzFpZIgY6jbMKI26UtzojnCm1Qn4GcAVmr0fTSg3Z627+8hlHIwFM39KhLw+TZNfp9q561Ent9OgQV8/tpJmeuzLjXF9KY77Z2fsqjfUPIevsL2m7xD69joRnJxcXHprJKb2DyLXGHTSfdsyGLofES0ZwnC0pXTNMxJtdjlqaKTJZG5CE3477NzP4PIuNmAP5jSdHGFc9Q96U6UrUmAvbEQNJQmZ31ROJhfqIN4t2OWRi6DLwBrVKqXKcePoMWGGarVL1e2K8lEjnLi/SIUxzGfpHZqZFXXRMsS36b9YBlrm4oEvP2+FhGldSdI664CzGuKdlUCHll1/x5NvgfX82y6qyTfk+3t99TIlfpOKx+Dwl8sY9tnI7GK7Ilt5uLSHoImc/0ROXmejYfpeDOtjQtrAwu31TWTa29KKQ7ujlaejvVzImKkpgdXB7fbdMjy/Wvg+qT8Qvt+7QmshBYXx6EFxOmQHvIqNRbfu6vYt38scDewiJUNAP5mes326fho2ydC3k9fAdvWcY0zkG6Z9bMD0ILHivZ7BrTI+5T1u4+Rbpgu+q7UwvuaBXlxPAXMV2W/tVGug0Ua/SxcOr+gsHyz0txDIguPUhcBn5R3e90pN35lCSgPK/iu5An4j4B7Me+VovPZ72x+1kQp/M/FKMdWqqdmudBOwMOMubRSkLf5dMk7vxfiR7KwwJWMvS5Fc/kOnac3vMFcXFxcOrNQsmTeCJHJV+a2X0DJGr2Z+16yXzXifX1TVhZIym5FltlZ4qBDgLmT7QPQBPWxepRFZIWweZXt+RA03yKSuQ+wHpoMnpDsX881F0Mu8i9RQMBTsk5Zzu5zxTqfSUDxQ/+NwrsslmzLEsWuW+HYaVG8+UPquRcKLMgQQVyRgEdE6D+BU2s9+54i1CDgTXk6wp7n8sn2HtN2lE+IBgP/Qgs4Myfl26CJ0lP2fRiLFuf6F53HxcVlwgWF0PoCOCVXvjtaYM6IhtHAbm10zfHjJLAV8IbpAjMk5QGRTx/VO352UHul8XsvNn3iMhQS5weaW+9vb+23gf3u0YlWkb75MyK6FrSyhZG+NwYtYKyA9LNlkcHGaKrEhU/OfY3tu0xSNi/yrniS8pA3+yDd9jV7Pp8Bt+b7Z8E1ZkCh+qbMlWek3OXAbEl5pgf0RSEV/4WFHXJxqSTAgtafHqAg/wYlA6KqBHxPEcp1zNSQ7F7qI+DPRQtjleZXwcaldZD3ahPKlXULpUTb7wA3okW2AbbtO3vvp210G7l0LQH2RfkBXkLzo17IgOtVtPCzsO3XO9f/J0cL3Fd1eJ0b3WguLi4unU1sgrBprmwK5Nb4BUnMc2CNRPmbrKXKHLIm+B8KIbNQbtuywMoUxD1HZMDzwIX2uxq5P51NZn7C4sJW2C9PwH+NJvt1Ee+mZD2YK1ucYgI+tSb/vdXtdy1ot95o8vkyssrKMpXXkyh2kjruZTtEGryGiM5z7Hlk7mrLUSLg90iOm8ja7g0s9mRPEpLESgXbKhHwUwAH2Xt0YqPvocHtl050jrY22c5+7561EQprtQTK/9CiUFMuLi4tE2T5/h/gcWTlvhIlL6r3kRXxvmhB+FdguTa6bt4C/j0bk7MkrNliXKdLSk1zAv5ra68sJnP6rVsbkc0r547tUeRYrv02sTa5D7MURxa+w5CnwG+m+4y0frdfcmwlvWYYlZPTX2x96ff2OwujeBwyWlgDEWpVYzzb/i8ir9BHSSzxETFyhp33VpIY2yhEwHZocaZHej24tEyAfsBmKHTl36iPgH8d2LjRdW9Qe82S+52SkX+jMgGfzteWrXL+2bI2R3PX51ButPnQ/Hg9lDPiYzTn+wTpsL+iufWZ1Eje6uKSCQob8zFajF6X8rn9bsgT7H/AErnjBiDdaQRJeNMOq3ejG87FxcWlMwmlZJ/DUVzLgZRcmRawicEdlFsNXG8ToCwpWl0TRpvsfAXsSHly0mYEJuXJynonA0tdcTGBRZB1w5hqx1Ca9A5AVk8jgMOT7ZUmdRMjgroJs4xKtqUE/Jr5+wIORRYpc9a4h8nQRH6SrC7IjfFVUxp/pmBSaftuBxxcdK8F+16GrMAeR3Hin0CWGV+isEL9bb+UgN/Nyjaze60rCVF3EWA/Solsm8VrTPZLCfhjrGx/6zdp/P2e4Pq7C8pbcCvlCzjZ96Yv8F9EvmxHKazVwGRft3h3cWlHoWSVuyolArkJWXNfACya7LuqbdurDa9fRMB/gMj+MbTQI62D2y6r+zSIdBlJEssd6TK90eLFG1QJR9LdpejZUUDAW/nyKFzPMWjhYu5q57HysyiIpZ707+lMx7kGhRnMxpuJk32rJqND5P43yLvwMjvf15Tnb5mUUgz7HxChfwcKP/glcHS1a7i45N6FiZDe/S21Cfg5rM99UbRfdxZ7H5uAv9i3YH5yhl32nfkVEfCT57b1zv3Oh428Bnn8Dsq2o/nZa8gzK/VQ7gusjizpn0bzgSZg10a3k0vXELRQM8LGv3SMSheUDgA+tTH0LMTvbGb97jvq8BRrl7o3uvFcXFxcOpOYsvA6cmP6HyK/dsNi3KEJb5mSgJJUNaF4sBWJx9x19kArtutRxVrY9k2tDmZCFrBjgKNqHHcOsGHyeyG7r1oE/CBgLvt/gaJ6VDhuCLJ6agJuz23LCPhXgJ2tbAZEQP5IbWuqPVAizveRS/bArE7IwuJhNLFfuODYLFHs6XU8l9PQosY6mMs0WoCZGy0ejLGBOyOal0UE/DtowvkT5WRIt588AktZ+75IKUxTPQT8SORG/yt1xt/vLoImQl+gBZ4PEGFRtviASKmTrW1/Jke8u7i4dKzYOHAK8j6ZB7PSo0QyL4wmdVu38XVTAn4TZE3YRB1JrBstlBPwWQia65Lt29q4Wndi+u4ipkucVO0ZUiLg/0wSL7laWxeUD0vGkd1JSPRkn4nRQnC238lF+1W6jl1jOCLVMgOF1W2cu75g/xXR4tWTKHTTWSR6aWftzy6NFRTe82tgo6SsJQT8PCTGDj1B7J7/Y+/2W2iOM9rGkeOBzZJ9/2jv/+EYOV/pu5IcM8zaPu+5lBHwryASdNGCY4egOcEGE3qfLj1DgN8hbmanCmNmypmsjQwkf0EeYz8hj6yKOdvavf6NbkAXFxeXziC5j/UpyPJ5GkRgP41IsgVQuJf7EQm8hO3fH3ibFli7IaL2FhLLVSufE5H5+1Eem7AXmvA/jBYFDi2qe1J2jSlDy+TKqxLwyLr8YGSJsGi1a1S4r6kRAf8rcFNu26KIpP4OWUK8jSydjkr2KZrUXWrP43o0cWxmkYEI+FeQG+Oi2bmQBddYEnK3St3nQgrqH0gWRChZhg1GIWhGp4O+KQL/RortUfnjurugSfseaOL9AhUIeMotEuamlDz0yJ7UZihcxUi0wNMXTT7uR2Gk+uX2nRO57z9LYt3h4uLSflJhTC0am9LQKX2RxeB7JFZ+Fc6/PS10r6ec0NiBcsKkU383aR6C5ltE2GyCJsPH5/ft7mLf/btsDKylz21pOtURufJ6cu9clYw3dyHL3z2ByQqez6JIN/x7C+/lULuPLex3qj9dicJP9C84LtOhqlrVurhkYrrjCES+bZiU10PA98n97hH9DM1R10Fz2c/QnGU34CZry9/QfOwK2/YWmmceDQypce5hpqOuXGF7b0TAv0z5/KxX+renPROX1ovpT8OL3vFkn/yYMjua48+CeWdYeYf3t4Y3oIuLi0tnkdyE4Tng/+z/lRFROBaR4mciy4GzMSI4ncjUcZ0ByEo4bx2+nyk9TYlckGy/xWTdpKwS8T6SJJ5mbvsilAj4lODPiPcm6iCr83XItd8/KQ5BMzMKszMMOJAKceCTsguQVfD6JHEIKU0WMwv0PigO78vIo2BRYGNakCgWWBNZfMxfsC2zmhliCuQjue2/xyaeta7TXcSUmCwG/gC0MDKSKgS8lQ1Ek4EZsGz0PajNLkTkx1JYciorP8S+OYva96Zfsu0U68crNbr+Li7dWVA86rXs/1qeXuli4hSIEP+RXHizguOWpuT+34yQrPeaSVlDvpvJGFzvwnxKwF+AFrGb6h2fu6MgMuAaa4fC8H42TvRDxgdvAkNbcP7rkMVfZpHaH7jHxqA9KCfgeyEC8wZEYC7Sgusciwwq/gVMbWUT29+zkdHCFSip+voV9IIeseji0nqhFJJvdjQHe4sWEvA9Sey9nN/+7wushUj1Vyh5N88NrIIs3t+xtvvAvknfAItXOf81iLxfvWDbZpRiwGcW8BkBv0ij28al6wriYD6ssU+mb8xNEiY4t60hY07DG9DFxcWllrTnBxI4FYUzmTI34VkHWaLumJTti+KL34ZI2k/zikm1uubOfydyx90JxSG7zZSd1xA5vTqabDVh8cTtuEmrXYuSxXszKwRg5uT/hUw5/RElKulHiXivGXsbuSQenPxOY9KfjSznb0ZuXn+q4zlUcrd+B4WNSYmOTAGfB8XlX8B+ZxYWLyBruha55QNboQWJWUxZDLnt2XX3sXMvVeEZdHsCAS2c/ICS3mbtMgBZ03yDPAHGL4wkx02Gkqs+TmJR00PabG3rNw8CM+W2/Qm5Uo9EpNTL2MKU9enf7HvgyahcXNpB7Lv/uo1Zq1hZPZbFOyPvrM+o4cVl5YOBvZEH2F2teaehLAxNYyaQsGSte61S72mQB1Cq2/SEMaBIX5gHkeRNJJbt+fYATrc+NrjOa02M9LRVCsr/YuNMmQW8bd/E6nIsNUIipveF4ut+jPSvGa18CbvOd0jfzYxK/m333CaJiV16jlAy+Jgdec6+TfMQNJuiedBfgdkbXecGtdM1yCJ98aSsD0qc/A4i4dNcEb0p5RU5EnkbH1Ll/IfYu5wt7KVzwEvQ/Hj+pKwXmi+8gKyWl2yL+3TpOULJIOkkG1emst/VwpyejIW67SzS8Aq4uLi4VBIUJ3yqdjz/ZIgE/x7FvtsHmMG2DUZW5o+QJKVBSTZPNeWhiTpju9oAsAOlWJhTIqI9m4yMQBauCybHzGYK5MV1XuNCG5AWzQ9GiBC/mXLr8YyA/x65H5aFZ6Ey8T6lKVbvk4udiCzaxiDr3SlQCJoyAj5V0iqcPyTnehqzpErrZH3jB2u7m4F5rbw3suJ4jjoSxeaumyXLWzetR8F+v7P9lm/0O9IoQZPqV+29qUbApwlBM+K9iSSpWk8S69NfIyJ9hqRstLXbcmjy8759H7KYm38B9mt0/V1curOgRJaPoxAfq1pZNW+peRGJ8RSwXVJea6F3MmAve+9bRMAXjUuVxqp2bKft7Tu+e0vrkIzvA5Kybk+8J/c6HTAr5Vbn81FAwCfbJ0HhY/6KEpbWisG8jPXNfhW2D6A6Af8MNeJio+SVC1Ie5m8/RMD/E1nZfo9IwLltexbu4p/IgKXNEhO7dE9BHhpLUkCiWx/8ChHwGyblEyHP15/s21y3Z3J3EErEezPvZ2QBvybyGngHI+Dz35Rq32dkrHW0XSPvBXw+mputV3DtLEfX+8AujW4nl64hNmZOlPxeAnl0nZ2UFRnwLWTj0eaNvoeyejW6Ai4uLi5FYgP7mzYJaPMkg8kEcBJEHj6KSOKnsPAOyDprRPqBT45ZDNimzmtNbpONH5CVe5akrR+yfN8FmJHmhPmsyJX30DqusRiyVBhObsECJYL9FVgzvXf7f0E0oSsjRIsGstw550IJSN/DJmkoPv4YYJ1kvyEooc8vwF11tlcva5s3gAutLI2tOweyBL4EWYN9ixKFzZftixGbdd5LRuhPY9f8N6boU0x0rIaU+gXquZ/uJCTuoqbYvGyKdDUCPmvfw2juWdEjXM1z/fcCNGm5DE2SfkDeJ1looz7IC6MJI9xJPF5cXFzaVnJj4vIoCWRVAh5ZEC+MwqhMl5QX7VsU73oQLSTgc/U8Cvhzg9prcUrxylPr9bq/59BY1+8GtNnWyFPvG7QA+xxwRrI9tYBPjSAGIm/IH4Bd67jO8YhUe5oqIWpoTsBPmj0Paid2PcnG/l9MFzrFxq2AvOI+IAk7SHPddiJglkY/E5fOLWge2IQ8Aj9EoYt2tm9vFtZoDuBztAi6cXLsRPbO9agFHqp7Pw+2v5kF/Fto4aKMgCfxqKr0fUaLgH+w78djVnYGmgOuXbB/SK5d9fvi4pKJ9bG7UELubI40NXAvWtzdK9k39bLug6IVvERBot+G3lOjK+Di4uKSF0RKfYriQ3aYdTGy0n7TlL2zkBv6RogAT5W6vIVARZenZJ9ZUKzN71AYlWbJEwsGjj+g+Hgr1XH+PsA2Nul5D5jSyi8y5aiZMpQcuww1Yq9beX80YRtov+dB1s9voUSwozGyInfclMjyv6laPQqOewZ4gOZJktZFCb4y99Mj7dxnFjybSorj9IhsnyJXfpyd6zosNEjuuUxk+zxHQrj0BEExIT/N+paVLUx9BPzhiMyqGdKouwrlBPyFyPJvLLCTlaUTntXsW7Fe7hw9gqhycelooTYBn76/g1CYtncpT0xetFh7DJoorg8snNs2BSLgf0REaEUCPle/fa1u+zewjRailDS7RQR8T/uOIcOEN5Cn4SnWJ/5jbfckJQ+neRHBmIUnuxx5JX5HOSFfSa+5DIWmORBYqo56ZQT8KOT5mU9mX9SfhyEjj6NQqJk/WX3Ptu29kIfb/1Buo2mtPNPXPMGiS01BRk6HWX/+wd6LjxC5OxzNp7ZF84vpUFijF4FNknOU5U5o9D11QJtdhnTupWm+4HUymtdmxl8pAf8GME8LrpMar+1n49eXaA64YtE7jWLAr150HheXIkEGdh+iBaXlctuWQvrXFyRe7rZtCIo0MAY4sNH30ey+Gl0BFxcXl1RQnMkvgPVILN4pn/i2esA25WM/YLGkLFXQlkLEWBMiFS+wD/+wbBLRgmutQ+IqiQj4+ygR8KkbVTqpnRpZd/yYH1QqXCdThHoji9mPkTXDVWhleP0Kx81RUFaJeN8fTbRfQpPBLM76vCh5TxNwSaXzAFNRx2Qwdz+3WF9YpKielCyqZwP+C2zZgj72kimLrwDL5LbfaPdzN+VhgKYCtkMTgT808j3paKGUWGmNgm3VCPhdrZ3ryiXQ3SX3HTsLTVauJYkBj9yCD7Q+vUij6+zi0h0FhTKYMVeWLrSmBPxqSfkgSuGzqiYmR15tWWi5X9Bi+v2IVJqN8jwiI5EXWtHCfKof7Ie89GpaQbdTu6VttDAtJOBz97IP3dwyFemOXyHyaWhSPiWyUv8BJSrN+sIMwJYo59BbwB3A9slxlXS0I5EF8LqUh4yomtzUxun77BlW9eZDBOg3iGDLrBBnQUlamzBdCi0k74/I0ucxQ4Wiuri45IXSHGBq+0Z8jxaiZkJeNxfZO9OEFo6ut745Dnl81OWV3J0EWAkZdDxXsO185C28aq68DzL0+MC+UYNb8YwmsXf9HeD1ZHuq625Bbg7g4lJNkBfFl8AGlIf+TfWPFdGCW7ZYfQKa399l/Tn15u80Cz0Nr4CLi4tLJsh64Vk0Mc1bOw8EZkYWy5O38vzrUpoIv45cgGejIKwNIs6fNcXuV7SCunELrnWFKTvnUJ7odBbKCfi+ueMORSFUPqJK8q2C66UE/JZ2f02ZEpqf9CB3zCZTZGud+wpEgt8N/IOS5clCtn0ORGL/D9izVp1rXS/Zb0Frpz9RIf4gssbfDynii9RxzmH2TK9EJPtndj9L5fa7FCn8PyOy5C4UC/jLzjqgt5dQcmNtFj8yex5UJuAnRtZx26T7N/qeGtyeRSFoUk+LrdHC20GNrquLS3cU4DQb/15CFlLTJNvS9zMl4Fe0skOpPzH53MDfEYn6CPJm+5d9T39E3l0HIN1kDxuLbgQmSc5RRLzvNiH334r22gUl2Jua5vHBFwP+TB0EfMG9NGGeP91RkO40HBFjZZ6N9ncy60+/Anfkju2PPO36JWVFFqUBhTZ8FJEPed15cmQksRDJYlPuWUxMQYzm3Hm2y/o9zfXJXZG++7tcvfZHnpiv4KEmXOoQFGrmJEqLO1PZN/JX4IZkv94oh8DB1r+yOU8TsFmj76MB7TYULcD9CPw1Kb+QKt7PyNhjPZIFvhZcM5t3Tmbv+mjg8WR7HzQf/QU4rtFt5NI1BHluvI1yyxQtHk+MGS+iELhHIu+NzxDpfi1JnPeicbOh99foCri4uLROTOloFke0Kwsi8MZiCS+T8q0QAfqrDe73krNWrvP8Q1G4kC+BJ5Cl2TfIsmhxci7fwJzIAvUNWjBJtIEhS8j6NSLg00nPLBQQ8KbAvGj3ulmyf71kdUrAb4dcst6jlBE8sxTf0hS0k+s45zXWRqsng90e9hwexBZCKCfg92pJ3YFN0ITuaDSRTy0qjkVkw00kiVeT7dsiknzfOq5zld3LqpQU+3Wtje5ESmjqjbCBPbunkPXWGZQndepUA3p7CLKY+dnezd6UT9g3o5y0Sgn45SkRDCnp0O3brM52LSLghyFC6mfg+GR7t1/gcXHpKLHv/P02Pn9of19DidQHp2OA7b8CIuB/tHf0F+oj3rPxdi5EwP8POMDKZkFh9f6KCPevKXmsNQG305xE3R/pQB1NvJ9CidT6CulOB5C4gaP8NHfbPukCfKjw/36IrG2I9X4HtduO1h4XF/UVSnrOlMjLbzTweyvrnT+m2jgAzG7H754r3wEZTGTP7zWSnDzV+m1B+fyI4P8cGaf0Seq2J1pQWiBfZ+Ql8h11eia69FxBRlYZiXYoJT19iH1zfkbhD5slEkbGOnt1529KhTabjpKuPQUK8TgWGS2djTxrKnk/D7G/6XepRTo6zUPQjCfgUai1scAJrT2/S88TFEJ3BLkFW+SlcT4KZfokCguc9f1eyCtxcO6YTtffGl4BFxeXlgtwsynUFZMpdUVBLoVjgBPt97yUQsCMQpbqt9jvx2h5GJh+yD32Q0QcLmgKyihT6m4HtrJ9s8lDfxQbvC6r90QR2RfFK3/c6nsu5UlAZ6EgBA0i7lPX5NYqQmkImpSA36ZeZQjF9GzCrJlIrPTt3t4kcZGnRMC/RZ1hWZCF+Tf2DDIyZI/kPqZHpPdPyEpwP+StsDEixkdRXyzUzFpx/fx+wG3A01XqOIDmhEynG9DbWoAFUOiT0cBcuW0XW9+aP1e+MPACig2/SqXn0V3F3rlm4Zwq7JsSLFlS5HyyvW7fz1xcOkqScWURG3v/iKySX0SLvO/ZWD137rgVKZGYLQ6fhXSZB9HC/5FJeV/k0bc90kXezX8DbL/NyFmWd2CbbW9t9ToiX/9oOsT3yHPgNBsrVkThH5qAHYra3f5viPV+A9ptebTI8w0VPAKT/riAtdvurbzWFMg78RpExi2OwnQ0WZ87zfSlL9Ei0NytvM4caPFlOLCBlS2M9LN8n00J+IUb/TxcOrck78JU1sc+QURyEQF/M2Z8Rm6RMjlft9edkAfv08CiSTtlBPwIe/+b5Syx39vZezxDpbaizrxWNCfgRyEjnF/oZMQ7JYOxHjU36UoC7ITmnVkYs8lRzoIxlCIXjLB9trN9ukx+h4ZXwMXFpWVCKWzG6o2uSxvdz9bJ/5MgEqoJEXs/IGuz60jCglBKsLl4C66TKQdz2HkvT7atgFwXM+ug+1CyyGbhbfIKTJXrLYdi4K2NXCib0OSniID/GpF2/Yvq3Io2rRQDfk9rz9SqtpLSNSkiIcZS7uo5if29HpGsU1Aef30OZLnyNbXjh15rfXkzRE4sihTu/1EeA3sqtEDxDiIof7X7eIhyN/dK99IP2BtNgu/F3OYx6xmUQPVpZIF8Apq4TtXod6MzCLL+f80UnTms7EKk9Kxb4ZhFkOK9U6Pr38FtdSPyppmzBcekBPwlmGWs/W74RMXFpTuKjVt/Q2Tk9DbGrIfI5VFIRziLxGIQkcvp76IQIPOiJHZbIausgck4kxHwn1LBBR+YEZgv+R1M1qZGWJB2bq9tELn7N6TbTIOsqv9u99OEvAr/ieIHF3oKUrJ479bEe3K/S1qbfQvsne87yfMdbPrJUVl5Hec+CliTkuHGfojs+p6Sl+gVwBLJMTvRwsT3BdedExmVfI68Mb6364R83fPviI9pLtWE8lAzT1GbgE9DMnVqwq0d2moZSnPWR9AiWPZdGYLmyd8DdyfH5L2fT6ty/quokIOkwv4pAX8QmjPUHTq1g9rsZOTlPEtP7DNdRVDuvU+QMd/tyNK9Cc3fV7Z95rdvxJsUeMJ0Zml4BVxcXOoXZNUyKvn4dOmBA7mkNQF/TMpmRZbPd9tHd1ks2UaigG2ILKdamsCzF7I0u9oUj1WTfTZBRPMtyPqtyZSHaVp4jTTExsXAW/Z/tqiQJ+BnRhPYJmqQduTiw9dZn96IuP7QrlGTeE+2T40SgjUBNyflv7P23ye3f6bYzU2NhEeI6P4RWDJXvrBdb8OCYyZBCuf6yFJs6hbcy2DkBv49skab0soXR4r8KDT5zZTZl5F729pd/T1rjVBuRbA+WlD5ChHM31E7PuyQRt9DB7fXNWjBabVWHFsU07DhExUXl+4siCBvIiFFrfx6K/8REZj3kIshXPR+Ig+t15AVcObF8l+UwyZz708J+DR3yEQF52uIJRfl5Gm6OLgT0on+QXls75lRnoprUK6a7N4PzZ13NyvvaWEhlqZEwKch+dK2XcHG1cK8KgXnnBotcH8KrGRlEwNrIaOGy1EIv0FpX0ILSGOZQOMdRMA/QinR3WQTcj4Xl0yoTcBPiQj4H9AcsVuFX21BO82EFosfsTZ6CeV1yN71KSmFoLknOa6m9zMy8vs++7a0oE7ZvHMQSQ6uovGyQW02DI3pw3ACvlMLMsr7FzKQeNX67Uy5fa5C865W5QFs2L01ugIuLi71CXAZIgdXzA8WKBnWzI2uYyvuaQiyov2KhIC3bYFiUqofcLp9jCvesykegylZnaUTnbVs0nC6/c4mhSfa+bMknjvUeR87IWJ30lz579Dke1P7fSXFBPxsVIjJl+xzKrBPSxQFygn4XWlFAhIUJ/9Eq/cVKH7taOCy/HXy7VzpOsgarAlZzi+ZlPdFCuU7KMb8PCiuaKVQMs0srXLbZ0Zk/tT2u489q+9QgrgV7F6uwqwNEbm/Pxr0m4BdGv2edLSgRar8N2YDZNk4PqZvPX2oJf21qwpaSPqOFk5UKrVVve+mi4tLbUEeX6k1eUZO9EHh6z7GFtkpJZXc1/SEM5Cr8541rnEpcuHfHVlkzYQWLf+NLL2vx8LJ2bj2ICJMjmzr+22D9poCLaDPBcye27YjIuAfI0cUI51tYmQcsVqufCCKHb9to++vHdttDmBlGytXISGkkRFJMwLetk2KdNrHyZELNa63APCs9aOVKbembxYnHiVvPR5ZCs7TBvc7j93TCJQ7py6vUBeXTFCM9vkKyvME/Meml2f9enJK3sprNPo+Gth+Z6IFuLXsvf435QR8GgP+LhSu8yeqGGGheeo3WILxVtQpP3do+Bwg9x08By0sXIsT8J1Ocs9qiEmRccIkyFjyPtMvuswzbHgFXFxcagsKi9FEYimVbLvAti3W6Hq28J7S+HQX2GD/x4LtKWk+EE2OR1Mlpjhyt/snCl/yUDLAplbpt5lCd5i130l2/kxpqSsBDSWL9i+RdfCmwLzJ9nuA55LfV9j+Z5EkYa12LWRR9iOJtVkL2rmmK3Ad58gI+F+s7pcggrbVky0UBmY4mrylIYVWtGuMtb8v2v0vnD3HOs9/PPAfSh4MxyJrsd6IgP/atl2HJqVZf8ue/0Dq9HroLoIWi/YEbkUuvfm+vBnyCBiBxYCfkD7QHQSRbk0oRumACThPxQUsFxeX1gkiCLP3c66C7RmBszlaoG5CrukDk32qWvWipN8foySUeSIjoITuvyJDgyzk2Vxo0jgcOKXR7ZTU92gUgi2zXv8ekTHLJ/ukBPyKSXkzzzzK9ai6whd0RUHGEf8xHSlru38DhyX7FBLwKKb+V7RioR8R8C9Y/1uZch031Z0ns+uMAfZvw/vOQtAMt/5fGH/bxSUv9g1sQp40Rd/mTCcfan38fcqNdSanh+YSoJRkclJk4HUGyl3yMfA8zQn4QxHp3kR1i/czyXmD0QpSk9y8k06g05IQuGje7gR8J5V8/7H/05xzfW08GwVs3+j6tvj+Gl0BFxeX2oIsqL5ECSfXS8ovtAGk1fEbG3Av6QCYfWCnpETA35psTycP66BJ8XDKE57lV9mvtg/yrTbRGY0sA2a07ZlCklm4jUVxvgdWOmeN+znEzvMsIvrfQXHKTkQTnvkRKZ9Oti62Yy5Lr1vh/NdYu9TljlzlPOMHs1YqUxkBP4ryRZIWTbYon4zvg2JkP4DCDc2JJod/QYsih1qf/x6Fufne9qlaf2uzrxCRsD9KZJd6OgxCBPwn9swGVWsbeoAlMlqseN6+M6/b36xfp3GON7T+PAJL2kYnUKwb1GbDkMX7xdY3b6cVBBPlCuZOaKGo2/c5F5f2FrTYui6KV/44zROp9rbv2ZfIQv14Eg826li0RhP5x7JxJClPidCH7FuxYlI2NzIS6BTeVcgw4Esb59dC4eouQgv/bwM7J/vuQImAX75Rde4MgkK8DAf+gMjweVEYw3et7a5J9l2GEgG/J4rZ/jPlIYgq6jcU6FuUCPiPSCzgk+2bAmfbs615nZaO55RC0HyLLGudxHKpKmgBbxE0ryv8Ntt+GQE/k30/z6xwvm6vLyGP4XRs6o08tS9GoUsnQwT8ZzQn4IfYd33HSm2GDJHGIb3/HhKDvpa807kxs8UGY23cZotgYWsLtl2IE/BdTqxfH2jPriIX1Jml4RVwcXGpT1Ds6c8QGfZ7ZDldLelhp7NAQWTquTbhmCq3bSgi4EdRTsAPQITfp6ZQ7J5syysPVyEyd7VEadsOkddXknPHBZ40xW+6rKyV93WAKSzH2/X2s3o8jazeHkdEe7pyewNwYI3zZjH+m8WRRiFV6g0dU0QopwrSUSRJuaqcZxpKIWhuSsprTtaoQGIgAv4ba6sfkSKZumv3RsT8IdQRK9aOH4WSwmXPegCy5P4JmNXKJkVE57coBvzgRr8fjRJ7Nz5F3ghzWll/pOAMR4nVNk323wARVl/QBu7rXVGAm6zvLIcmPXtb//0TLbCAz70X+9u7tWWj78/FpStLfrxBJM8Iign4Q9Cib1kCvzqv0w+F4/pz/rr2O9NDpkXk57CsTvZ3cKPbyuqxP9IvVydnwY4I42/QYnUaum47GwOeIsmf05MELUJ8hPTzPrlt0yFDgp+Ac5Py36FEhpkn4QlpX61wnd2whV2KwzGmBPwyVtYfeRJ+howYdq52HXILTy1sh7mQl+LurTnepecImvuMRos2Vb/Ntn/2DX0AeMz+7/Zke64NLrNvxV3ICK1v0i7zowW8Pez3Svatfh5YMBlr+ifnK5o7j7JzbWnXuo/yZM31JIFOx91sXtwQr3xKXuYvIcOYDYHZcvuci8b+a7G5oUvnFMTZHA28hXLr7J9s61Lfg4ZXwMXFpbrQ3Pr7M2TV+yMVEq8C6wHHUBAnq4H3kVmIZ/IKIqY3oESIDkTx2EYAtyfHzoUI9TQERl55ONbOu3q+TYCHgb8W1GkLtNJ/WAvv5TZyIYBQqJsmRP5OjiZeRyGXyiZEVk5HnYsiyFKpKVN+cv3gcjSpG1THefIk+y257bNbn/oEWKiO82UW8GOB2+q8l/xCS8jdz96mAH1MuWVgYf+tNNAmfexUSgpn9jeL6790sv9ASiFoHqaTECEdKchTZASwRlF7o3AMHyCPjjT0wLoorNNvKLdCl7E6aIM2WxFZfK6elA1Clo91E/A0J95/BXZr9P25uHR1KdAPelOB5EHE5TfIIrluq18bxyayMf7RoutmZWgB+CHgn5XO1cC26ot0sWGUCN6y/BOIxBmJLJwnT47d0caATRr9zBvUdpeY7jB5rjwjxqZD3g3DKY+Dv7T1wz8kZZX0mlVNd3k4G1eK+qk9o5dQGIr+VjYFSio/R7XrIPJtvL7ZyrYY1Ojn4dK5hYLE9JQI+OH5b3OyzxTIWOpC+92T9M05KOVbegLNJd9FRGSWq+os+zZPZ+PSSihMzyvUIL9RyJomEu9qlEA7I+AXT8qreeXk9dlfKFiMo5ULfC1ssyFoPG9CsfA/RAl6vwP+iOaKWRL0E9H4fy1Gzne2/oUWDw5sdD3a6F7Op5UGRij06fHAcklZlyLeY3Ty3cWlUwqwKLJAmo+cJRayGv8CuQGvU3Bstmp9QKPvI1evqazOPyCr0WtNMfgRWUHchmJ4zY8scT8EbkyOD0X/2+9JEPn+M5pEZBOfLNnqOSjB2bEokdpMyCpoYkT4PkcF17SC+7jK6tssyQ9KbNNk+0yZlG8PbFjhfEVW6XNYvT4FtshtO8/abIM66pq22b5okrx/bp8+KDnYS8hqauE6zjUEEdw1kx0hV8bfbP+1c9vSEER7osn9/ZTHdWyJu+NQRBR/AGxFOcG/D1K85skdM5BSrN+abdqdhFK+go0LtqXeCTvZM7w01w82AbZr9H10cJsdZO/LdAXbBlk/q0nA59pxP7QI6MS7i8sECFpkvd7ev91y2/JWlvNQIpmPsG/hinVcY9bc7+Pt+7hSjeNuQBZbLbKu74A2m9bG3mY5hbJ2s787WBttk9vejCzrCYIWVP4LXF+j3eZFxgWn57ZPnd+3wnkGotCIn6HwEoUEPFpgWtuudVSFcxXpm8Ps+Vftvy1ol05FXHVlAWZudB3a8F7OR6EiVijYlv82pxbbmY4+HNio0ffRgHbri/iAx5H31IpoTvsUmk8fiSy4/4eRkvYtWMW2VyQ6bb+FKDdKysbEugl46tRnrd7nZM+8ndttLrSo/C0ySFwfLVi8inT0UdamWyMvgfcQNzF7e9arFfeRcQ5rNroubXAvmTf/7yfgHGkEgS451jS8Ai4uLuWCLJ4/s0HvZxSKZc7cPlkImudIws7YIPIziRtrZ5DsY4lI2w9RYqqtTalYCU0sXrEB+x2T/1kb3F7nNYagsDa/oslENkFZAllpj6bk5jvGBt1tkcXAgXVeIxs4VsqVp4pHlsD1CnIubra93lAxqyM34rcxAh6RpWOoEuOfksJapAztmpRtRclqog+KFfoqVQh423dSSolLq8bzQ1aBr1t7fI3I75us/xZZX2Ux4O+tde6CY7MERFMh8v0TjBhGlo1lcVVzx05C4lXRUwS5sI6xfjV5vn/m+tAN1vcnr3CuLmd90Ir2usb68sJV9qmbgLf990fEnRPvLi4TIDbmjrRxbIS9q+fn9mlGwFv5ChQQywXXOBNZHq6QlK1p49ujwPzptZL/hyJvmfMa3U4F9zQjInWOst+F3nmIzBiOhVChZORQZiXfUwSFHHoeuK9Su5lu1RtZrD5qv5sl5a1w/qko5aMZAByHvF6bEfC5sfod4Io67+EaexdWL9jWqjjPLm3Wv860b1mriarOIpTCprxUTYdEc4Mv0SLlgcjS9Wykpx7TkXVutKC56yD7PzOSeg1Zcs9r34f9rE2ftva9If0mANNXOf9ZyHNnklx5+i2pScDTAkMSNB/8Uzu1V9GiQJYQ+nNs4Qbp6HMgi/eHbUz7mpJXfrMwrw3sA1nOty4f1s3uZSQV8tf1pDGk4RVwcXEpCbIGH4msK3dIFJYzbHuawCsLQfMsCgGxISKXT0j26XSTITQJ/cgGw00pkcVTAbMBp6GQKr/avR/agnMPQeT3WLRosRQi3a9G3gSTmHJ3BpqglFk7V/v4U4qJt3LBtiVzvzMC/jIskUsL7iFVZFan5EZ8P7JiWKvCcYtmSlQtZQiRBU3I/W6urG9Rg4BHsa0PQRb5sybl1ay2DkZE+O3IOuNb66dPWT1myO3/B3tmTwFDW9h2eQL+PWQVMtqeRbOFiYJzdLp3pj0FuBEpdxdg3hqUk0ZZm+6DJkCdyiqkA9spU4Kbvf8F+6YE/B+pkIQV2MPeQyfeXVwmQChZ726ALCXnRvpUEzmvM8oJ+EewkBwk1n9VrrOanfNxykOknWjld5ML3YFI2u2Rx+JGjW4rq1OaYL6P3c9rmAdgpTESeBnLyVNtHO2ukr9nSta8mR5VKXTM3UhXrysUpI0ft6O4yQOtrBIBn1oCDrVndGQd1zja+uyqBec5iBoLUUVtYu/fAo1+Tt1BrC2b7Bu1bDucv+7cNBN4nSwx/ZmI6HyIKp7GwMLI8Gg4Mpp5Ftg32d7tdXRgZ3v2u2BhWtAi3sqIwP4AWMTK57a+chuwU4Xz5Rf8+iGdvwk4hSTPlm2vRMBXDGFDyfitWW4uSnOvK+159mmP8YOSt3ua220Oe4dGARvRPJrAkmiR51Fgn0Y/+6ReWejZVfLPpKsJmj99SwHxTgs4kly/7DRhlVvcHo2ugIuLi4RSosjfU7Ik6o1CPYygNCnKx4D/CIUoqStxUwfez+x2LxsCy1K+cDA1soD/BFmfF8Wv/B0FrnC5fYYgl+mQO/fhKMlVFgKmf/4aKIZgXUQicJGdq5nblykwH5OzMEAE/K+I+G9mAV/jekUE/FjgrKLni6zYv6R5WJf9qBBHGjgdrfbfirmN05yAXyTZfzJEpDcBx7XgXuZBSvSN9nsW69NvIxL+ResD0yfHHALs2cp+l5HFQ1HMwyak7GcKbLdX3Gu0z97ANLmyW6hCwNvvg9EEauqOqGdnEkoeL82sT4q+S1Y+CNgLLXwVxpJGi4DbN/r+XFy6sgAXIu+R5XLl8yLdaf+CY/qghfjvkNfdJMm2Iq+si4GD7f9V7XpPkizGIUvC3xAxsi/Se9ZEIdd+oILnVQPa6yzk/j80KTvJxspjKVjEt99zoAXtvRt9D42WRM9Y2/SoJ7BQZPlvPdJJnwZOq/PcF1sf+j+MdKVEJg1AYY4yAj5NotgPhV0aTo0QBUgnvszG/Tso1yez96km4Uu5rpolDO/y4REaLcnzXsOexeO0oQU8MoTZqQPu4wa0OLUcCvO5LVokfZjqBHwv+37PD0ybb5cGPpcOiQmO8ig9YO/nzhg5TomAfxXNnxepcHw9yVEH2Xd/HDJ6q4eA/zsFXsn2rN6tNTbY8/+ZnDd/G7TX9sjz7VX71l6Yvi/IsO8Ra88NKc5vlXIUje5nV1t7j6I8WXfdOWk6i6B55Y/AIvn6Iz3kdurIt0Zzo8LDip5jV5CGV8DFxWU8IdaEwj/kV263QUT1QIrdWte3wezQpKzRA8cpwL8RYTzO/r5sdZ3K9skI+I9tYM/ut+ge80TgZshd7jNKcTAPSbZPgyx3vkXKXzZRCkVtU629kBJ0h93H9pRPds5HVtXNYu/b9qPsua5UR5v1yf1OB5pVEQH/Nkn8PqSIbWnte1Lu+C0osKqlfPHmNGujagT8/GhSlxHvxyTHV7Ly6pPeA7LWSpPhZn38IUqufs+ThD8paocW9L/s+lMihfCzXB/rshYEEyIotMLPwDPkvAooJuCz5zcdClFzTU9rP5Tc+HuSWJrJtmuoEO/Xtg+y96bTWNO4uHQnQYu5T6HJ3QpW1iv51j9u49wKmNVe8l3riyzh9qhxjavRIvaKybGrUUzA70kpyfovVq9n0m9ApXGzg9orUPIIOI5kIRYlBv0OhXvIwpBl99sHxV1+n4KYzd1dkJ51HCIt58htOw8Ze9xNcyOMiYDtkNdDPXl6zrF9N6I8sW2qD06MCPjhyFvh98j79Ujrb4Xx3guuNcjeja+BO63sDLRQVKjT5vtS8n9FQw+XVvW39Bu2JiUCfoIt4O25vw9cbL/bhdBDYVMepjy56kA0j6pIwFeqDw3WOxFR/XQHXm8yZLjxHZUJ+I/JeSnXaifKSeZBwMnUR8BvZ+PG+hXqWpFQT/rysmhcXKYN2+kya4f7UY6xv9s37Dc0lmXzzdmtz2UEfNoOgdJY1+h+Nsy+yZsiz9nPScLntdf72k73shCKMvAtMFNu23k2ZhR681fph/taP2zmYdFVpOEVcHFxGa+gv4SU6d0oJ3i3QYr9SzbYHo1ZllCK7TZzsn+jiffLkFXO/sjaYW7kjvYfUyKOwiwZKCXI/BhNbmrWHblivY4U0QtMPrSP+H2UE4aZ9fkwEpfaVtzTDGh1dgxmqWoDR0XiPTl28Rrbt0j+z68KF1nAjyfgEcE+Fjg+ff4m61NhskfLCPgP0SLDr8Cx1foZsFmFayyDVvD/j5IHx/Y2gJ6EEnq+Qh0xd1vwzPIhaD5GHgI91vLd+sVh9kyfpjIBfyElAr4vIl3eo0LS4O4o1lbzWZ98meahpbL3f6Ma50mTCveYRQsXl44QNGleGlkef0Oy0I30j9/QgmO2yPsAsu6ejZy1VdH7ScnrJSXYMyKhEgE/GcozsjIKoVBXYs0OaKtjsJA4SG8ah0jc6a1sKAr38IuNBfMn93IA0n+OaPQzb0C7XYp02uHWZiPz3320QPOjjZPbAYujfEbHUafXg/XXN5F1aDN9FVmrZwRcloTyZaQDjkE69oEt6WvIuOQMe3fet/OsUOtYmlu8e8LwCe9nmwEzAUMKtq1N2xLwDwEPtfP99Eq/sZTmZhPbO1LTAr6zCBpnzrH3sw/tTIBSmr8MojYB/x4VLOBz51zOnkl+njklMphrojYBP1cL7uEAq/PilLyCApq/n5Y/dyvb6TT7Lq9Nuffa6sCd9l06Nrn2HNbnvgQ2pkJ+kwb2s2uRvrGa/R6CuIcuScBbm28KvGX3MIOVX4jmTy3NX5eNNbs0+t4mqF0aXQEXl54sJLGAEQH/MlKC97Ky+ewD9TyaND5LaRL5Akpe2Sf5SDWaeN8FucKtSTn52gsplfeihYR9KMWrnApZJ38F7Fjj/MNsvy0pd0WcCrmcjQMeS8qHIrLxR+B6JoyAnx6Rxz8gxfV7KrjXIouPPLFZRFavb8/ypqSsHgL+v2iR4ycqhBrK/b9A/t4pJuBvxkLxIOVuRRQWpolk8ljhXjay/a5PylLLgkypGAxsbvueSCme6ZQkyeraqD+mBHxdfay7CqWkx73QYtgnVCfgL0CK3/rWzw5r9D10cHtloRc2se/K37GFNFqQ+Nil6wryoBrc6Hq4FD6b00nCQKH8Lk8hQmd+k9HIcmxTZOmWJUvNdKgVa1zjTAo810g86Cgn4Feqcb6GLb4h3amJJB49Cqc3DiW8n8bK+iNPv29t/+Emb2Jhdxp9Lw1ot5Fo4X52YD3kyTCK5lbuB9i2rH/9iHT3PyT7VPOy3BGRQrPlylez/v4siku8gZX3RiT8WkjnnKvadWzsn7ZgzJ8ChSL6DHgmKa9J8FAjwaJL3f3sVOszH6BFlMMy/YKSkVVGwP+DXIitFlwnO9cRiLQd0tbvMloUuhrNlzbBFhMon5N0RQI+m7e0ed4jZJS2C7BowbbJgAcpJuBXtG/zdxQs2iTnOMPq/gwKxboWiSUy4h/OsHf5DCoQ8MnfWotzv7fvyWi77sdo4eh66+PD8uduRZvNi+bDeyf9Op1zzoVyWjVRbuQ2G1qsb6KFIWE7oI8dT4l4z9p6KF2QgCchz9FCx/+sH1yH+JNmHhTZcyvqG3SjsabhFXBx6amCrJBGYRamVpYR8F8hV7AsUWTqGrwMcrt5lSTUSoPvJRskrkXhKQbmt9n/U6K4a59hK+FWPtTaouJqJgr/MMKUjTQxVEawDkYuwb8CVyTbp6AU/mWCMoYja/psML+AYuukLDbeenWcbxo0Af4ai4lu5XkCPlVaV0WWAzUJcSvfxfbdLF9fmhPwY9AkLE3wsxaJlVeV60xrz2g4cG1Snrn8LYkU7TcpWbxPUuFcla6xBzmX7zraOI0BX7WPdbSgCX2rF4TqvEazZJ+ULOCrEfBZTNlf6US5JDrouVwKnJj83pRSMsWb0Xe50sLbLEVt3uD72YFknHGpq832s+d9ZGd7nj1dKCXvWjpXvhQKnfKDfbcuJdFFbJ/+yFK+qqszpZirFXOcUEzAL5ds7xQENZrsjqQ42VlKwKc62eKI6DkCLawvkGzr9mOA3edViNRaJVe+lpVnJHiq4/ZDOvpqwKKU57KppNdk+vMRSMddxH4PRHrSaHtGbyLSognYvEq9izw4DgTusXONQPOMwyjFsJ4SLTZ9Dfw5Oa4iwWP1/Y0u7P7fGQTNXc5HRg7D0eLXD8hj51Xrh8tS8vL5DRljtTr8E1qMHEcNz9xWnPcKZLzxtt3LL8hYoSi8TErAP1i0T6MF6crZ+7mYvfdZ+Mw2+b4jXSMba95CC3aHIq+pbP40cfL+7gwMsvLeyCiroscwsvZ+xfrNaEph0T5GHs9bo3nyFCjf1jjEP0zeyvsZhOJ797H/V0cLk39HY2ST9e1tk2NaE150dTvPUlX2WczeoTcoN9ibE9i40f0rqc8CiKCeNVeeLSpMRRch4CmOp58R8C/Z89+5qP6U+JOlKec9/kA3Id5jdPLdxaUhYh+iXexD+ibNCfjM2vjxVCHJfYxC0f8NvKeByLr4EvtdKW7fKojkPTe7X/vbv8q5s0ROZ1Zoi2wSPCWySv+C8tXTIVTJ0t7C+5zJFJYxiNTql2zbClk7nVTHeTKFbirkgjWKKgR82kbIqmCbpLyaNdWcSLHNYshVI+CvQcrlHPl6VrtO0v5TIwJ+JHBdbp9JkPtkE1LsBlaqc4VrXGeD73yteGYZAV+xj3W02P000caJh3LXOBER6fsga4/0WfdGk+/PKCbg/2j1Oywp6/akCzAjcuPfLr1ntHiVTZAOSPZP349tkXK5SKPvo6Cfzd3ounQVQflEPrR3p82S3Lm0ybO5hgpEsm1fGi2ajCO3QFZhTC2yEB6GCKQtUZi7JpIFyKLjEdn6M7JOLqxbg9rrLETqLVxl/M4I+ONJCPgK+zZc1+ygdpvXnucrNLdEnwZZb+6IiK1BdZyvngSI8yGy8lnk1fov63sPUgo1uRIyvngNy59Ux3mvBD5FC0r72HPOCLinKJH9U1Ai4O9Kji/Kw9QfxVjer9HPqjsIMDPSi39DeWLmQV6HdyOL0SaUg+loG5d+QWTsanWcew+UuHXhpGwq6xNZCMsJ1u2Sb/N6yFBpYuAvVInxTSkJ62jr9/0mtB7t+Ix6IW+BC+33BH8L7Zx7IsI9szr/EyXPo3+iMWhxNPe8A3nH7EguL0e154hyQjyADG72RuT4BWjOPsau9ye0oHYn0oGPoYVGG2jR4Anrq3tQbKC2MpoLjiRJ+tvSPmht8DMlr63C54GM734BFqz0DBrcr46z59+EDAYmyW3PdIxOT8DbM78F+DPKu5dGdwgoVO5/0bxz5tz9bUkBf0IpJ2KnMZyb4HZqdAVcXHqqoFXhrZAC9A7lBHxf4DlEyO5O8ySsnSY5SO5+XgVuq7HfpMjq5u6kLL2fosnw6mhB4k3KV8uLCPjf2Yd6qwrXbwslczrkUpkR8P2RS+JYalgJ276DcmVDKSbg84lx9kWeEP2qXcPKJ07adhY0URpFMQGfhmf5DosbWk/fSvuk/R2ClMVfSDwQbNuSSFk6o4XtfQ2aELaa1KjVxzpSkIfIBN1PHdfYgRJZ3ITiub6AFJnUOnMfpCg/QxKb2LalYR26PfFu9zm7vcebF/SbLEzUAyTWNmgCtaX1+dMafQ9JvSb4velpgsjKL5Bl4KCkvFOMsz1ZKFm8r1ywLbVqWxpZ2H1DC61Dk7Frpey8yKOuHgJ+Ddtvs5Zcsx3b63Krz0+UCNZKRhEpAT80Ke+R/R7paRvb9/MBRLJnetIqiCz83tr2A+s3a2HhFFtxvV7JuT+2675l4/jMuX1vtmtOWsd5j7Tv2Zo09wI5zd6RVzCjBmByRAB+Cfy1xrk7LVHaFQUR8OfZO3uMlQVkuLI5Iku/tH6R6XXr1jjnxpRyXnxvz/ovaC7xC3Bpsm+r33Wr22/kwuEgT5Dh5JIAU65XZfkL9mz0M0jqdxZa+DgIzSlntvJHgVvb6Bpp4u/tkLfAmyjMzFTWJnejedv3aBHmaqSffoBI+2ZWxsn5h5Isetj36R/2zq+SPJ+VUMz3f9m5v0r6V92eEcjr4VMUQml5km8hufkDij//kN3bDi1styyEZpaIePcK+2Xf6ywE3aYT2s/boZ9dgb7PhyPr90IDMZpbwH+MJUzuLIIWeUdRit4wDpHwaT/ILODfRQT8TFa+DRX4EzTv2qnR99embdXoCri49ERJBt0+9tEpIuDTGPBlSVg7i1BOTvRB8dyGA7+rcd93ILJvfOzUOq61EiIP38WSnlp5flCfHk2Idk+vWe8zacG9ZzHgv0MKUcX460nZQWgi9zbNLcMLCXjbNpkd2wQcWkfdtkYk/e+TslmoQsDbPotbf9uojmukbuiBcqvqq5Bi/wPlIWimsfv/kjot2K1tRzGBBGJLn297CXIv/hYtRLR30qZ7rc9ciyZ1d1FyW/8nsrRayLZlSYybWdPV+452ZaGk6M1k/TazCAuUTxSzEDQPYklYKS28pYmPG9rfKCWKdOK9/jZbClnl7FDh+zgJdVi5urTLs7nYxtol8t9NRBZeTUJGUooB/xUFZH2Fa0yK3O6XzZVPT/0E/IyNbiurxzB7/49AetP3mPdfpXEHEfA/27gwTUfVtTMLiln9LQqZMAkKY/CD6TEHWd97ABliNCHL0kVaea1sjBlsulL/3PZeyAjjLkRqTFJtnLH+/ITVsX9Snhp1HGXP/EbMy9aucQ4iT6qSuy6t7le9kKfuVLnylIA/ueC4QYjYPAfYp8Y1+iNvhiHI0nkLpAs+ieZR49C8MzWyaE34j2mRFfMnlHvk9kOW7c/bu7Km7Tu44Bx9JqQObfxspkCW2c8jgrDJvqUPornbV7SxxyolAv4LRMBPZeUD7JnvZM/uXTTXbKIKaY0W3R6z/dKcE6shT9cRJHHQbdskyOPnKOCv1JEkOjn2FGuXNfPfrdx+qZX+7yl9O2suvKDQNSmROwh5KP6D6vHu10MW1UvUukYH97OTkzbLDCzTfDKTp/dFOQH/Z+sHyzf6PqxO2XxjbetHfYAb0NiSLXpk9U8J+I9QZIMxlM+fuvWcs+EVcHHpKUIpZEjeUrgPIks/sY9RGmamrykAY1BcuHoSIF2HxdNq5/s5FVkBpElbNrDBfliuPCVmp0Ur7FWznSMF9JRc2UrUIOBNuRhDBTfHCteqaUFU4bjp0Cr0eEuVfH2SsquQYnUtIu1/JGdZRHkImpuyc6HwIONy16jUbucihfp+mscqnRkpld8iwjBVZPpZH3sXIxWr3PcxaAK6eb4eVv8f0KLSJeRC0FByIav5fJAV3vhY/ZQrbsdiBGkd50mPW5caifHa8Z252O7nWUpWGc1cutvgOulE5hG0IHYQ+tbMg743WSiir5EC9LnV7d90woW+dn4uU2b9BFm+/0AuHiTlBPwm1lb327vwC50oLj6yeB2FWaFR/n28jE6SK6SzCSInRpJbGEQWY+ejUA/P082scDq7IMLzGzTRHpDbdh6yflvDfqff+iUohe6YvsY1sne70JoXEfDn2LlOrOM8DfsGIAu0MdjEHOlEL9l3rRYBf6ndY6EBRXcWtOh2AVq03grzpkBEwXfIG/UHpMvl++HiNq5OkGs8zfWpdCzvi0J0jCLxAK1yrrmR3tgssV1uTLge6YSzJWWDyS1CubRZP/sDCuv3hX3T/gIclGyfkdJi34lJeaV3tmi+sT/S8d5FnsN9cttnQXHkv0UJXtdOtrWGgF8Mkcb/pXxutjTKv5FZUn9t79GOTEDM+nZ8NvMhw5i57fdQNO/cERGej9t9nE8uPncLrjEIWWMvghZgBlh59n5/isLbFBnCzI4s8SvOfdD3/3MUzmRpcrH0Ud6wJxEBv2lSXph/qqh/5bYviAwF9873swr7p2P0cmiMrkq+W1s1Ie/6dN66HdK/r8+VZ+PwRCifyTN0koVxq9f8aEzel+Icdgvbu3Qs5ZxQRmAPpUbemg68l9Ps2Sycq2MfpLc1C8NLiYB/247tMcR7jE6+u7h0iNjH/wpsxZ/KBPynKDHIZMmxfZG7WT0rw1cj96p2tXZE8aJ3Qyuv/0fiFmsf4nFoEjNP7riJkBLzGYmyV3D+Ici6pwk4PLdtJQoIeNs2CE2QHyZxQ69xL8OQJX6rEl8iJXbl5HeRIpytCq+ZPPND0QQ5H090akoE/K1otf83apD7Vn4hUm63p0KiL2BWRMB/j2JLzmhl+9nzPKyOe54ZWa+/S3kW+Qut/61rv6dCk/k8AV/x2Sf7TIosA35FFnl9Cq6zYh3nSRW9A61P1YyT2Q7vTBZP/xY06forJffJNrGAzz3ntL0eRZbZB1JKpjsxcvfdy9pzuPWzw9uiLl1F7D0cH3sfJckbRy5hMmaRkry/G1OaUB5Z9AwadD+rWp1uo3kYofOQJUrNZNA9UVAIpm/RhLAP8jg6FS2UjkXjzhfWvns3ur49QbAJJsqR8yUKm5DlibnIxoFqusRy1AgDg3SS9cklmMu/y2ixvSYB3+D2mh3F7l0pN/atQf0EfKcjxTqg3S5Fi9CvI5f+zGNsRtu+ESJKvyGJHUwFsqmtxwFkkXqQPb9jk/Jqlu9z2/d+m6LnTYkkmZfEQrag33d7MqQD+9kVaP5zI3C6fU8+opTQPSNiZ6r0ran2zG375ciY62y0iDRRsi0/91wEzQVepUIS+SrXybwCs3Muhgx/3kDWxgvY9/k2ZKizvtXtNUq604qNfibJ/ZyIiOBfkF6cJ62zNjuFUnzuWVp4jaORN8o4pFeMQmGkMkOJiRABnxnjDcnKK5wv/66eiMbJZhbolM8PKhHw+fPVE3p0A+tDdefjonx+UnWuTkkH2Nnu7eXkPZkBhQhqQuPeUpT0g6FoQfUHYN9G96+CNvsBmL+gf2XeVV/b+3MoBQR8pWfWwfcxM/KiHk0S/gcLcYY8xo61+12Icg+sYH29Yv/rrtLwCri49ARBZPBIlMxokJUVEfA72uByNSK4+6b71LhGRvDW5WLdBvfUH1k3j0EJWma28knRpDhL5rQHIqhXpWQxfVQd558LTX7KyC3bthLFFvA7IHKkrhhybd1mRQMHUqB/tYGnF6UJz5pW/80Rwb4opcWZaRBR9oPd/7HVrmHlW6FFmnVrDWCmlNxCyZ3yM6TsHZ7sU8myPlN6ZrTj3kOWNReQEO/J/lNbfxgD/KlWexXU82hECl9sZedbu6xTx/NIyYf9EIG2R0e8HwX97DtksTIJWlQYgSzsMkuHNg9BQ7mC+zCaiB9CsdvvrMBCtZ5/dxN7/96278YsyBKprgUaFBf8wOR3wxVH+8acZX39NEruy+dTg6jsiYII99nt/+kRufYGsnLLEp/fl/UHZBX3DIq5OkOj69+dJfluTo08s3ZBE9LnkVfV9xRY9dqxMxWUFY3Ph9gz/gKR0+uRI1Qo99zLLODHAqc2uo0q3Pvkyf8p4VI3AV+pvbqjUEoUuS7SvXoh6/amTF9A+u4Gtt+D2TfDtrXrWIksWD9HFsr71/t8bCz7DrisWl3t3fqeHrbw3oB+dhwKM7EG5YkIZ0JE+VjgwVx5i741aI45HHlrTVxj32wusrD16zeBDVpwP0Wh2ZZABPz7yJjncnLEMVrUXgnYpNHPJKnTlWju/QcK4pyTeD4m7dyEvFnrsoCnFN/7NKQ7boTm+t9Z+29o+1Ui4KtalaPFtmeRkU0lK/b0HjIC/gssx1Er2+5Aq3/NcDNooa8sCkBR3ZKyIh1gBFqEz/KazYq4he+Q/vYEsoR/HH03j652jQb1t4Otrv1y5UPRPP4qZEx4HZq3HUEuEWtnEeRBcx8yXNkzKc/y72XyG1rkO5SCeUi+P3RnaXgFXFx6gtjAfbsNGmdTmYCfCFkJvEYSAyw9T4XzZ/E9ixKRzd2G97EESYwxSnHqxiCyYoZk2x8oWRB9h4if54D9kn1qTR7mtcGniVyoBMoJ+O3QxOnnegdaa7ORRW1W69h690NK7fsUxMFHStePiLweiSbEp1NStKa2Ou5WT3sha4ynkbtwOuFeErkD3mnPZO5k2/rI7W2HtH5F10ETz1MQsTezlc2AlJvfrP554r1Xci/X0YqESnbsMdYH3kCTxHos5/PE+7i0LTtKUHzOd1Aitew9n9Task0IeDTBeRCFF5guty1NzvswmhAdjHnXkFhz19PPuovk+sd6KInZlyim+/+QN8CmaFFrUzSZXdNkLXKkX6PbjOZhEDKruSPRpK8i8Y5iS3aKSUkHt9n1aAFx/uRbtTAafz+xv1uRc1dGoXs+J8nR4tLmz6ZZzgI0+d4ZjZlNWGio/HeTUvKu8c+1ynVWt3N9iCy4Mtf2/VHs35C/BrKAv4BOFJ4FWCH99lNBb6SFBHx3l+Q5rlSw7WNkuZd9G3ojwmwk8h6cowOf7ZkkHgl19Ouszlcg44+tKh2LQm0MpwXEq0uLnl9Aeuy/UDztNMxERoAPQVbLTcAVyfbp6/3WoPnZf5FXcl3vdHL9Rewa29RxzNZIP3rF3o+zEfE7IKnH22jel85fms1pi/pjA57PkWg8X5MaHtCUz62ycBvXUyN0qY0nnyLdMW+RvjXyuBlLycq7LxrHPkCeEc1C0BRcYy00p1yqBfe+uvXL35DXVN16IKV5y95ofrVE2qcqHHMmdXqNUVkHyAj4VykR8AMRX3AtIt1fQTrwesmxDZ/XJG22r7XZovk2I7dwhhZU/lurj3XwfexGeTLfZVAYzm9R+MaZES90E+IZFrNn/w9KZHyHGIp2Rml4BVxcuqug1cAFKLlABRSipRIBn/39AyIY60p4hayKx5Ik10y2nYdWtieYJEBWGy+h+IRpbMg8AZ/Gep/d2mEn5P49a7KtkgV3WcxUZL3zln2sD8vtu5IpDl+TS4ZWbaClZOnUzLoVKSN1DXKUT2qnKbomsKW120eYUkQpbMrmaNV+EIrN/ROJRTdVssUXXOfPwBu5ssMRidREKUnP36mSeKbCPVyAiO+XkKI1GyWlfXq0wDCSAvex5Hk2i8dXcJ2+1o4z0DxPwJF2jfsrHV/huTSSeF8ZvfeDCvp1m1jAo4lzpsx8haxCNyFx5aR8spcR8AeShLfq6YIWl16nFJ/0K8qtNvKyf6PrnNR9C7Rwt0Ku/NykvoWTavTtvovcok13F0qLr82SzaEkZ1PS3GIvIKu92+ydHVzrW+TSqmeTJVddOnkm2d/+wO6IyHiZEuGTfVe3RATEKXVcJ6BJ+x1oEWZZNLHPwiK8jsa+ITS3UJsJCxXQaEH6RBOy+LsILaaN1zvtbzqeZgT8SDpZEroObrfBiNwaDuyVlPdDnqjPo9jcadiO3shqdQzygBnUznUc7xmbL6vz+BXsHt8BNirY3ht5/7xDKxPFutT1HBZCBGdFwgkt6t2HLJHnTcpnqOdbg4xohpOEAa2zbpnuWXOeiBaeP0BezTfYOzLayg6m5L27uPWp/wLbJcc3nADN3c+UiKw9lZwBQ5Vj0m/pRSTej1WOuQfNOwfm293+39Da8CVsUc++QdtZ++5Y5dzZ2LevfdMHpuW5fbPvSTqHX4caodly59gy/e4hL+ivgVuL2igpmwuNrbvWcY1qOkDeAr7Zc8tfv0JbTFGrHm3YzzanPJzwTMjy/ZakrFloIWQJfzNwZkfVtY57mRvpG4+QeIkgAv4Be25NSHeaON/2yCCtXUMjd3ZpeAVcXLqjoBjvbyPlfGpKRGWegB9s5dngORCRAg9Rw2XQ9p8Oucb/QHPL6vORJfgEJ+WgZOl3DLZSm9ueJ+BnqXG+vOXDviQJDiknC89GixGPUhyCZmWk5B2QlFUj3o+z82RWX6kCdAkimWevVv/8PSCS+1lgaFEdEDn2KiKp/8/uJx9TegiKNXhJrfaqUJ997bzX2f8P2n3+C5GxcyHSYixJcpM6znsJUqw2Ixebj5LSPj2lEDSbkVOW6rkXFHrnTqQ8fgE8RnmyqekphaC5pNozTo450PZvBPGexdc+mZJ1Rn6hbYIJeGSdeTf63tyHlNEmlDj1KPRNySfb+rvtcwytzHXQVQVNCtdAlhh5C6SN0UTsN0TGT40WULMkXIsjy+hmC50NvJ9zkPfP3yiYoKOxqAl5WkyTlAf7Lv2GJb/uKYImwd9S7Ck2ae53Oj5k7uDfUmdoM5cWP5vzrb/eTHNiPSXgs8n3y5Tc2DOL9xOS81Vd5Lf/97Nr7mW/50DeMNl38i20kNUsHEG1a3Rgm51u9fzA2uRTNPFdNLdfqletRmmRYSp62CJS0pdmQx6U7yHDl6yvLWvfxu0Kju1t3866PPny428D7nVLtJj8NdKzsgTjswK7Ir3dk3C37zNYnCrh7JL+uDyJV0/BftUI1TOAd+3/WiFKZiRnfEHOQKTgmNOtH61LyUN3cqQbvWjf3uMoeVVmBPx/qEIeN/i5LGHtvUYLj2vWvpW+oUiPHI3licmNPen/Wf6htdLrAHNVqceg5P+NkfHIptXqbvveQhKOqlr/ym3fyL6LN1PKHzWI0gLwaUXnsm/mnmhBu2oiZ+rTAQoJeEqLzs08enPXOBHNkWarVpc26mNn2P3clLwbgymF503bLF3Y6YMMF9+lk+VpAtZGevBDJAv4aNy81/p7GuWgb9HzqNXfuqs0vAIuLt1NKBHVBwBLJuUpAX+HDRoXUYrJOxjFfP+eOsjCbB+0MvxPpBRlltUX0EbxfRFB9zFyhUpDWOQJ9AGUCPg7SVz1awyCsyHL5Ofz9U3uYxVgTuTeV0TAp+7W1Yj3yZEbbhNwfm7b+Vb3moMczSfuv2LJqnL7pcrH5khBHYdNdHLnmdfaudl56nxOU1v7jLD7+wzFs50nrbfV4Tkb2GtZkG+PFgw2qLQvJcJ4Brvm+yhMR0uss66wd+ZqRLAfjSxmmpCFTaboT2v98TeU7KgisYIUwpfp4Bjvdu1ZKFkcv4KsaqoR8FkImruT9mxJ++2JJj7bIEue3Sllkf8vImhnyPXHF1rb17qqoIW8zBPkO2TVOCi3z8bWZp9THqKp0ymOaMIzAhHCqcdRyD3rLATNqVgSVkTIjAWOq3aP3U3su/ENstLJW0cdhxYuiybWC6LJ8ffUmfDQpcXP5lp7L1+wseTEgu9m0eT738jq80eSheVa7yflCyvPAa/ktu+DFsRfQrpBEwofOHRC7rMN2ytriyVQvOYn7ft1l73bvyF9dMMKx68LbF3vdbqbUNLJZ7Nn/L59SxdFeudF9bRJpfYBds5fa0Ke84Qch3S4p6wPf4MWG95HCzY1c/24tP7ZISJwIfuWnGjlzeJdUwpPM4pS8tuW6IFH2js/pNaxKGRKYb6MCvvPhwyI9qZAR7Xv8bNW9w2Tb9OiKKTXZyRzkUZLUr/VkPFas/AfBccMIcmL1IJrTWbj1OnkdLO0LyCCcgRwYYU+kv99EZq3ZoTzzGj8/D8SC/uC+syMQpS22HsTLXxfgfTolEyeHxGxv1q9eiX3NQ0ikX+kxiIfE6YD1Ou50AuFExyFLLXbjYBHBpKZF+2rwK2Uoh7k2yxNXjw9Whj9kU6aiwNxQqMpJuCzEDR7JOU9kmgvbLtGV8DFpTsJSorxOZrUpGE2xhPv2V/7CH9JybX5HmT1W3Nij6zjm7AVcfvYPWfX/hMiCAoTUtKyjORTIgvk423QTZWtKZBCtmJyf70RAf+t3c8sNc6/mbXFOjaYPwusadvOQxPedZP956JEwB9TcL56LMRnRCRcE3CBlZ1r16q4WJF/hvb//ohM39V+z0mS7MzK0gn+logQ/hBYOukLvZES8QGtcMdKBuzBSNldj4IYgZQ8Jc6v87xXIuu/IXVef0a0gPApdcSOtGOOsvdgjdw7MyUiw763vp0pmNMgAv5nq1+1xZaGxchDSuP/7Hl/DJxEcyuOlIA/ESmdT9TTj9O+iJTJfyGvjUmsbBa0MPeF9fXhiOTvVBYUHfg8rkGkw5H2ftyBFNvryS1EoRiFbyKlfrwLcKPvIXc/29r3omaCZdv/POsHJ6PFml+oM0xXdxFktdUEPFCwLbO2Wqlg2xFoovYKsG9ParMOfDbXIsvcJdBC/t9sXCj6bqaT750oTW6rEu+ImD4LuC7dD43BB9s5MtJrF/t9LBqfV7M+sm9b33sbtF0fRLh/Rkkn3BAtNGUh+W6z71qhR2WlvkxurOpuQjkB/7K14U8o4V0zoqwF513B2v3+/LVaeJ50XDoi18drhqbMHT+L9ePzEIG2C4kXV3d9xg3qV8eRSyiKSNGvk3e0KDTHYmgeWNNjGfg9SegMZKT0iz3f7JtZZDQwr/XzbVtwPxsgfWmBgm3ZOzQN0kkeym1fik7qKYZCaIwDjkrKKs27TwFuaMU1ArL+fywpq/S9fRe4qo5zDkNz1uXS8yGDq3HI0KLZAiEay3ZH3lwrtPA+sufcD+WZ+gJZpw+y8kWQXt1k39Lr0Nz6YTQnPDJfn9z5J0QH+B4tJtab66APGiO/QeRxexLwe6MFngfQouctuTa709rsRXuu56KQLp/k2qzRxj5FOlUlAj6LAT8C8/hwSdqt0RVwcekOYoPrYPtgnkjzMA8ZUb0IFtLEjtkXWbt+gMj4bZNjKg3O19qAsXKufBlKoVkOrnDs1ra9rkEXuV//TM69FllE/x1ZV2UhLrIwLv2RFVoTFRYAbL+b7L4zcms9tHjwJJpIjsaI+Nxxc9rg1YTcGltsqYNI4iwe8ms2cK9edC60MDBD9syS8rJY4ihG3U8oJv4G6fOj3N07C0HzESUCfmukNB/W0ntJ+2BBWXrdvsAeSJmpmVgLJQX9CDinzutPbn9nRkr6TnW8M1Mga6wTKY+r2iepwyHWz/6UbJ+KUjiNFVvbZu0pKHnTk8jC4i/2zlYj4Ce1Prl7a549mpg3IcU6U5K3tbIrEPmSWeMvS7IQ2Oi26oBncQVafFiJ0iJOP6T0vk/JeiddKNvAvg3f0okstpL6nY3Gm0ly35pFkMXMlSgp0lTJtrOSPnBMUt4jSBf03b/c3sVhSfmFaHJUKSHtwva9caKqfZ7LptYnV0m+XROjyVutyXd/pEdtnZyvaJJ4IfIGegyRU/nE1NPbtW5DFu9Ndt1Jk31qWjs3oO2ysXJ+pH9clNt+OqWE6GPQouIOFMSXLTj3scCNmB7RXft80udmRRaXY0jiONM60nxy4DA7132tOVeuv+1rfXJf+/0nFNayprVnPX21s/Tn7iDIy/A9RDytnZSvheY47+W/P7a9L9J3X6eGzoG8HJuQh/VgK+uHdM6RKDF1puuk84A+yGjoJWDhevsFWrD/Blnmh3x/SfbLQkMuSmL93Fn6mb1HKye/p0KGK++QhO0ruL+hKJzG2S28XvZt2due14n5bcnvGdEYVdVbl1LOsqKwebNSMlC7kHLP5+nQgtuPtHKuSWn8rUTAz4TmuI8iY6D3kFX3BvlzpG2NPMMzHSAb0+rVAfpZ+9b0cqZ5WJeNaCcCPqnfvEhXPwx5og3PtdnMiAP4hz3/D+zZrZ+cq2FjL7B6tXpQIuD/TuIZghbdHrHnukCj3/3OJA2vgItLdxFkOTM6PwCgic6TlEiP12luETEw97sS8X4+mkQtUTAABRQv8ClkCbZ07tgt0UTg5Bbc09w2EFyLFg/moxS25QsUzuBytEL7GiX3sIlIQjYUnDezQl09V74eJUvd1MKnTNmzwawwdmKF6w2iuUX6zIjA+hq4t6jtkRIxfsKTlO+PCOGMeO+DlNkmpGw02UC0b9GAY8/iVdv3RHsuJ6T328Z9c2ZExI0msfCocczEyDriavtdMTa4PZ9DsFBD+f5c5bh5kKK+dv6+k349OQoPMookhi1Shpes5zodKZQTuA8jD5CAFtmGU52ATydJLbV+nwwtljxkv7fP3iNK1vArk3iS9ARBobyaSOJbYuGz0MLax1RIUIZyJXxJKxZE2vmeegN/BV7MlR+CvGqa0MJgE1pgmDnrK4iAPyw5plsSarl2ScOlTYcmQN+iCc7ZaEwtdMHHLAtz77VPItr+Gc2e/J9NvgdQ3+Q7nVAXTQ4vRuP8phSEjEnOl1m/j0MkUl3jWAe30+/R4tq2ufLByFJwBJb/h5L1/lGIlDkZ6Wk1rfcRoXEf0iUvoucQ8LMgXe49YJ9q/arKubJ+OQiFqvqZGgS89fXB+XPY/5mhxy72e5j152bGKS4N70d72LNcHYX2+ArzNkTk+gFIl/0IzXcynXlWe19HAwfVcZ1+aAFmNJqPpKEZ/4fmUQdSrlMOQXph2eJSnfe1tn1LCj0nkz6/jO23TKOfRUEdZ7S6vWDf0azO2eLvPZRb76bW4rsg3apqKFdgVWRwswXlBkVzIMvnn8mFTc1d4yNg+Srnv9j6z7I0nxdnev7cSLf5zb5jf0bz9MeQvlvVAr2OdqxqAZ+em+Z5lap5Kk+Z/J+NN/XqAOm8vWjOvZk9gzzXMgAR8CNpYwI+V6ebUHjg/mjx/6sKbdaH3IJqtTbrgHdmY3s3Tq5WH/s+jAZuzpX/ngph73qyNLwCLi7dRZCi/RladZ4eEeSX24frS+QGdqYNVO/RgvAvdv4sOcc/MXdTisPZLIvCt4wn4JEyUG8isjmBWZPfZ1Ii279FitswShO8/ojYbaI4OVV+lftiZGm+UlKWKhBr2bX+RbnVSCVXwGqD+QY20GWxLf8PLYZkA/sclOIhX5gc14eCmMi2bTXbPyPes2ewjg0+tyHC71NK7nf7kcRkTp5JFtf8uDrvp0UWWHYfe6MFmfeBQ6tdhxzBjpS29zCFpUqf2cT2mynXH2vF3M2ypm9WYXt2ngVsv51a2gc6QqyvNLsH4HdIYV/N3pMHqKBETuD1sz54BLJ+vJWS5eYknbHNOvDZLItIpG8wMiXpV7tRii/5FPrGLkz5JGCWRt9DUpdps+dtz/ZrtCC7O7LKakIhmjaz+zgETcCaTfZ6Sh9AhOOzJMnlKBHw31ibrZq1a+7YrZAr8DQ44d4ez2Zo7neqB2TftKqT7zqusbWNTRvVeob2vR6BdI9mlqmNFqSL/QdZaZ5PLrQcCivThEL/ZYYDeev9yeu4Tkoe34SsdS+hAwj49njPyBFAVfbLx4B/hyRpXJ3nyJNCgykm4NPFvMkQgXo38gZMF5PyHpZXWB9dtdH90aXZs78WGVjMY7/Xtm/JV5jlLyLgd6WU/+kjZJz1BtIVj0jOV+t7NRGab/xEOQE/h53vN5RL60iU9PHP9h09ptY1kEddmktrJjSneYxkobTguPWsr3c6b0Gr39L2PXsOGatl7+tB9r18nMQ4Dhku7WFtXKhHJfteYO37GyUyf5Fk+1KU8i5cbXXpg3S1fZFF+hFVzr+rHXsJufBhaE7+V0rf6IEoJOydSL/9DzK8SOfUteZns1bqIxQT8DdRSsJal7ECmo9fgYjvbYDpk211LcLX8cxPppTr4gFk8LYU5frGJrb9USaAgEceIvvl7xt5w3yMeSZXaLP0u98p9E00R7/S2u+kan3H3pMmKnjW1/u8eoI0vAIuLt1BkgF8H6R4jLYBeLQNLOlqemaRWrcFKrIUH4UUrY9RGItpc9fOE/DPocWAE9CgfkK+vgXXORxZa1yCJeaz8n3R4H4LmqAOyl1zA6ScNHODy53/YkrxRwfltqUDVRaC5lmS0DUtGZDQRPVVpPxegVaZP0eLB9dTsn6dhVIImgutbFMqLFYgi/BmYXsoxQx9ASmuMyHi+0Vr/8+RgrxscszWwJZ1PJdWxZlFk+cbbfBct9p1EDlxNMmiEJrE/4zI3Ky98iGVBiLF/j4S0rLO+s2BrE4vqFKvLHnqCCzxTEv6QXsLUqKb7Bn/lSTePrI0egy4NWmrjIA/gQrxdwuuMVmd+y2KFsiaEPFaGDKhpwkKT3UvItr3t7JF7PdriPT4jz3DJkS6XEgnsnZGE+g3KIX3mtLeue+tzp/bPvMmxwyyYx6jwAW8uwsiJ/5g35j7cu/D9GgCNJIkxiql73y2+Hpio++jOwoiKoajBbAFc9vKLNopn3zX9d1MznGlfXMrjk2U6x7noRBw8+W3Nbi9LrcxcAcS44jcPn3tXpuQ/jne66naPVc6l/0dhPS+NiXgkZHH/7N3lnF2VVcb/4comgS3ENyd4hbc3TUBWtyKF3cKxd1psbZUgEJbrEChLVq8RYtbAiFYEgjJfd8Pz9qcdfbdR+5kMpOE+bB/M3efc7bLWs+yLRDNcTiyZpymPcqO6jkTgTp1fQF7FzQvIUBmiRrfedAop3xAAQBvz6Yjs7g4Onp2kM1jAN4DnXpo3Xlsy9x3pTats8CjrROdJykAvjsS6B5k391la2Bt911dYDEG4IOl1tSIB/onAvg/sLNwu6o6bK0+ivjXv7l2/8zW3/lkGvtTRG05yeqcaAXWiIcdRgbAx8oY4xBd+Jj9/R8V1oJu/n+MFLEOQ7TZH6L3lkJn+Qgbyy/tjPkvzl1sydw8imj8gzGhIplF/JaJ97v7v3XXF7LQ+AbjdVNzSRqAv4H6/MplSCnuWWStMQ7F2pg3UUfLNIB91x8JnYbbGP3OyhhlY34Kis/RHyn+vY8syOZvw7oKinwN5G7lUDKXtX1sbO5zv69odcw6cI/0c//PS+bxoBCAR1Y37wPHFq2ZrmRj1dkN6EpdaVJOCADxQSJ7ocCR16JgV8uQ+RMOhPjqiLlbv2Yd1yGAIGixn4kIqdspB+BXRsRDg3wQ16JL/VLkPuZ8zGQwvrDdu5647GMX2POUaPMj8P4LBIKPsX70Kyk3APD/oMUgkQgQHYqYrgEuf2YEkI5CJps+Svy56PJ/kBrCCqRF8OMoL/iK3TKajzvcpfyhzekK0bdF8xLA3aZARzXHYioqQFjry2vIVc7KLn8aZC3wNSKuYuC9D/IrPpwKH+8l7bsKCUSCJUXKJHtxRCxv2ZY6JmRCmgsN4B5EzP0TWTRsY2O/EmKM1nfzcRcivs8p2mOu/DMQcDhHzfacaO2p7Zbph5CQJdJdiHE5BzE9V5FZEfUElkB+GR8GDu/sNkftPxox0Q9j7pYQMLYmEpyl3GnMjs7lszu7/Z04btOggFxfIGDSn4XeBc3VLn9ndEfnXJ91dl8ml4QE02+7O/ENZHUyD81m5d78vJVzcwo7a98CTrO8wm9cfQva3N9WVUcHjteBiDbbiGrQ5CAb0xsRANeKwsI8JIQUCDy+BQEF4w3AIyWPf9q9+Lm193MUoG/28Sk7qucaRNOt1OJ3YS3Mj4slUPL+OUh4ez7yIf39+JDRgP2IAHgEwh5pbTwuKnOwjcte9vtaMjcSbxMFWmyhb57GXh0L/tmVxmudXYhoWE87e1DaA/BJ92ap9Vc2d1F+DMAH5Y9utsZmo9ntZlEd1yD+8grEE76OhH7b2fNf2bq8nrxW9/SIF/iKSSDAIsUA/PJIaepWBNQegHMDkxo3MjB9NVfOlOgsHokAd6/VPC06a/ez/b8xeV/ZMagZu2551MZ5MDqPv6YgvhoOGyhaPwXf7YwCzL8d+p/6njwAfwnCKv5AiZtSe/9qxDduis7M/ogPHUvk5pE8AF+bBnDfz4vOz3dsrqZFSpB/JHNz+28kZA5a3r+jResNBL6PQRjC44gn/MTW0LyI7vnO7aU+NmbD64xZB+6NPdDe3zMawxQA79f13LZeKn3v/9BTpzegK3WlSTHZYfp7uwTeRwDxrjjGwV16sWbACciXduXBjjTYP0LaFL6cs6gHwK+NA64pJrhOt/I2xUmU48sWmcj5dkyLCK6RmEZpQfm32AUzCIEhJyOG4yzKAfiNkWuF/1LglzlRV3AnsCZRwFH729cu2W+QOVoYtzmRNl4Dk9wWjZldMu/ZBTu/y58NaUs9hzGxZEFuD0JBZW6137vX6EtZYJ120XhC1gjDEEDl3Q0Fk7/pEWg1BpnHroGIiDWQBsKX5IU7LbULEayv2zwvlnjeA2lhvEwNDbSOStE6vQ4Rw6ciou5cBCb8HRGJ9yMGLWj2TYUI6B9X1NEdAS9jEJhS6AqBbN+vYev/ZmoEY5vcEnk/m9+DH/Y7APCjgMf9OEdlTFRaKK5dByAw8VGcNZV7HgdW2wcJ+35Qfv7D3Lv/p0H+VKsA+CuQj8tvyAPvVYDnD8qioB3mJmiBfWzn4gMIOPoYCecXi/ZxuLtrnZtRXS8Cv67x3qyYdqOd24X0TAeOUzdEM95lazOpxW7v+vX+JPCML6dGXTcguuR5u8c2tfsnKCj0tzvoE8SY96pbdlTP5QgEOQZY0vbmAggI+cbmd864T20Yu0Laqeb38Z1QBHzOT2YxNcrW8EXAcol3+yEA/lukxRk0270bkO5IELwHsL3lXYfu9FXtfHoG0Z+FWqlF68n9f5jVvWJnr/NJOZFZ8/6VPC8Q++P2AHzOCrVq/sJ+qFiHSQ34OmvYPb/U9owPerkQ4r+edu9dZn0OmsS/QUDjMGq4tOng+SlzeeIB+DVqjE+Kf9rAxuJXNLsBWxfx7wuk5qNOHSjo9Z0088n/cGfO1nXKbrX+6KwpBODd+z2R8KY0RhIC3scAG0b5/ZBw8Z80u0D1gdhr0QBRX+ZHAqOR5IPeLghsgvil18iEwQ1qxtSI6jkL3W83oTv0MKRcEALPPoyU8YKArLetndo0zYRMiB57y9q4cvQsCcDbsxD4/j1c4OKuVDDOnd2ArtSVJrVkh897drgejgiWp8mkpYvZe93ISwWnIwt2U8nYkWlkTu3yfHmVAHxUXhHwPj9ylbI/juG1Zz0RUzqXywsg38ZI0ltKcCEQ/GWcpj8C7U9BAHyVBvxWmPZPjTE7nhJNfzc+fZGk+1UcUWSXy6pVY2bP9rX2/zQal3Msf3ky7aVTyYDXKanhT5bMjHHtqncryikjlvayi3Yj0hrn3mz6LOQ3voEIp68RM7Ff/H4b2jjY1vJwJMRawPIXIAsUe1hbyp6QKdqPt9i4nG6/l0fCiWE2Zg8jQUaP+NuKOnohRjy4/6mzdn6LGPyJzm/xBJ6P05EmyVZRvncfszxiZj4HDnD5TUxw2d7p4H75M+xAMgB+mVQ7UWCxPdFdU+qndHJLyHR4gUR+XxuTLxHwFQPwF9t4Najnom1qmgNjTRTrZWJOZPfkonZeHodopeWQVdoXCFC4CeciwX1f99ycAtEvdyPhbqmGr62b74BZyAfo7Wx3U3MiQG3HqvaQARQH2DqupYGG3KO9Zd+8YnPwBbrvr0buYaa1ebrB8q+gRQ14RNN8iuiNJsEwcpPxFRI2tOTCLirnbESDFQYuHJ+1m8g/OZwbNl7fofv6SiL/t8ha9nBE05TRqmFsj0WA6Lru2da0AIrFzxHoPwbYpzPX9qSebD1/Qia4upbo7iENwL9PDQ14++YXSMln+Rrr0APwBxLxVRX1BJdGTfQ8mSsu7w5ke0RrPYXchpyHo7vqngkTcG7WqnOGkAfgV3P5dQVaPRDt8C3iP2d2zzZFNMW7Nuc3IH5mOiJeu6DsKRAoPNS+7Rc9v8/m7EBMaa69xx3FD2o6a6J1PR3i29aPvk1qyiMwegyix3q6/G4IeP8taX406UKnoN39cDSe5QUA/ktcjDc31j2tvycAh7Q4Tp4XPAfxsjchYcEAxOO+af1+0vJSCpqdRm+QBYLdBsOfEn2bnyyW4RXAwkip6TB07hTGLOhKbqw7uwFdqStNSsku14+QtPt7/5R2aVyCiO6/EAWksQP9F0grxmtVFxFRByHJ4+k0m5zVAuBb6NOqiHBYL8rfBl38nyHi5Doy4HBzMkBxD/dNbC63tP1tcplBCwB81Xi55xsjTc/HyGv8pwK5bWh9SLq0KRpH8hp5v0HM5Nwurz8iVF63vpX5XS2q4yord+1E+0+mJqAWfbclUZAupMFyB9I+8wTAYsjn8dlkLnSmsDnbDAlEfkReI6dloi9q37Yo2FHD1tszSFvgf5iv9zproCNSNFZ+PwYXNKeRxUWYEQVz8oxJt9T/JfX1QoKSJgA+KmtGm59NqWEuPzklskDIwY/mnegMa9p7ZBrwX2BBWCe2RDOw69fcQWQA/NJ+LSIrkXvseamf0skt2XkVNPJuQcDVPGS+UXuSAfD30uwD/pc4ra3UmCEtqXMQA/mq1bMJ7RhAeXJNOGbT1uqNCIRcyb2zIPAvsqB1tyPz/JgOqguODEJ02cXRWen3U/CPfBe6v7u1UscEHrNZEVNbCKS79i6AgU6I9ti5RvnbIPBkIaT1/gpSEtkGAcmv2zy8j7QaD7Rz51VEP9QylUdWheNIx8vxd+hVNvf7tmUO7PtwD1T2v2pM7f+BFeO+jI3PbfZ7Y6Tl+J3N3R9sPENAzP4I4BmcWo8ub1qkEJKycqoNwNMMvH8fwLUrtXl93IqA90H2+1hbc9dRDsBvgJS1vkUWtFU8ze5W7t3UB+Bvtm+OogbIa9/tYN/chVltuPV9NqInZqXZImRKnLDS8jobeB9sfTkOc7dTNs5kAPw/qSmww/jtUDZSwhuHCe6Rq8yRVua1SLD8mbXrMwScz1pSfhj7nlb2R0hDul/03j8QvXMQGSbRFqvomdE59iMEsHoryu2Lzhp0dxxh/dqzZl29rbxPkTBiastfDZ39u1WNS1E/kVLczQhr+R/iAwaTuf9dgAyAP8/vm4L6aq9l8vfYz62Om8gC1/YDdqTYRVBnAu+b2HhtE+/xRN/mRvfXKKQgOALRA0e0Zdx+iKnTG9CVutKkkhBD8w8Efobgk93IM3Hn2CX0c2SG0wuZs71nl3AhUO3yL0VmS78iMvtx76QA+N/TBk1XpI0xyi7BGZAW4HmIkPgCSaEfsX7d6r5bC6dNFveHjGgc4vJiDc1SAL6N87Q+YoSexGkdJepe0Nq3bc1y1yQztQ4A/lo29n8hI3yC77sG0nxqyfWHtb8B3Bi3GzGwlYFtE98dbGX6SPe9EMhxf/TdIXaRNly6gsiksqiuxBhXMRd+//RFGhTnI+ZmPyr8LXZkQq555ojnlDyhGnxinoYJnWiHwJ2UAPD2fDoE8ueI4M4esw6en/uRZsmFyIS0gTSztiAKUogYrjtsP01s/t3PRMTt9FF+DMC/aX0OliJTISb9V9HZN9mvAcTYPILusk/RXf0JYoD+befaSujO2Z0ssFZfV4a3MkuBYWchLb+nETD5JyTs/RJpDk5X9O0POSE3BoFm8mt4C0xA7fKGWN4FSNnhPdvHpab1CDjYwu6MIUgQORWi0S6yMs6hOdB7iFvyGTXBgw4ct27Ild3HCNQr9duLaLjXkXBjvhrl/8r2y/z2e2FEez6DCeptv6xnY/cKeV/9DRJgeqIPM9k++YiCu4mMppoCxUx5sA3jdY3N4xCkAfwdsGtbxt39fyBSCpiz4pvfWd3e9cgARIc2EC39JHJDOGfU99RZcypyf7Sob1f0XSUATxfw3u4JxYZpisFAZnlbBcBvjrkUqrMOkWJKA/EZdQH4P+Es+2r2KwDwfyWLMbYsEhT8tE5bJ5aEQNdvkFCkDgC/ArKGfAUHrBe8ewpSPFva959MAe8KRBNcRt6yur+N8Y24oMkl9QR+swdZQNMUAB98wB+Ao2FaGKsTkeb/ODKh9x/IB+dNAfD9kRXPWNwdXlDH1uTj4/VBwt7htr5XQoL4i8djzoNXgt8i/utKpCTxDTqfg6sXD8Cf677v0da6XRkxNvM5AuAXTjyfaPYMij3wYmJtrYKEeL9DNK/3gjAv8BN0ni3j8rvo36rx7uwGdKWuNKkkYGm7lJoCpUYH6h8QoxEO+v6IMZzPvVMEvP/cLtjNyUebThHnvs4zEODwADWigCNtdw80/A1J6Z9CGg5jkFZ38Ck5G2JsRpEQCKQuESRBv93GbI+id8kD8KfHh3+NvpyKM921vA3IAPjNXL4nlDe2S3mpGnWcQEb8zoMzf0PCki+RtljQ7FvOxuqaNqyzeZHw4zvyoMQFiMBKSs2L5gMxXN9hDBcZQdcLaQN+iAjU7W3tNhDAtCsSLgSBUqWP+qgNN6ELu28r7R2fdyZkQsRJAwGel9NsReBdFXgAfpZ2bEMSgEeWC4eTCNz2Q0hu3+1PpgU0HVkgvAbyW7o/+bgGKyGAY9/O7oPvC2IcvwMOpSRQms35COTuwAe+6pt6f3JPKHD2nTbnlyAXIgfbuf2VjemDiPm9lsxVXL+onNR9FoJ474ppwtp+nBWBc9/YuVDol3s8+jXRMGltaPt5CHg80d09Xhh5O9I67GF3UAMpOIR3p8e0S0vqONv295dkroPes/N3JqRUcK2dj3cj4ctMyPrtFMYzbsmEnmdEF47FhOfuvPP3/PTozr2WfKDPIlrzOkQzrhvlL4w04F5D1kTe0q87UkI4lMjlXEmfgrXkIghseQ0H/kbnWXBBcBWiQ/tXle++vQSBhGva74VQ0NwxtADA00w7NXBuD2mmncO5uwQS5F7qnu1g83YMEs49Y+VtXqMdJ9m6/AMRjRq10QPwq8XP3XtHoTOqC3gfj4Q0hJeI5sDzYsdRA4B3ebHSUlG54WyMAXi/f/ohq9SBRfs+qmtuxKvMS3be7kwGvu6KANHLy/owMaXovLoD3fmlALzr+6pU+Cu3905Bd9ofaAbgg6D3GfIW0b0Lyor54UVIKNEhDfgrKQbgH0Zn3RG0ACIjwPpjG6PVkfLXsYheGkbeenI769e76O7ckxLXWS7vLDK3TB6A741otZG2zq6hQsBc0o8TEX22AS5mExLA32zl34MJQ4D5EAA/nMgFTTuswSIAvlIg3lkJ0WlvkeFWvdBZ9qnN3Qj7+zol8Qon9vNhYkmd3oCu1JUmlYSAmtEYs0Kz+V0gwtemBKwsOpyQ5P1lZCLVZMqLTKOnS9Vp/19EDd/oyKyogUCJaS2vFzK5fwwBCRtioCEZE3ewXWClgWKRplAINrosGaBbBcCfaO9dSD1/eN2QBtHDiFA4JHqeBODtWT8EZv8FMwUuqaenu4SGIuLnCDKXOlMhbYknybsxuBgRQ8vWXF+e6J4TaX83EKN7LuUR7XsWlJPTdELCjePINDQXQtrvIWDYMMT0Le7KmNXG8Q9l6zdqz9WIOF2v6t1JJSFC8yuk3fYJWZClpHsXe/YdIr4KzUvb0A4PwN9kc3iYtcfHXvjBgK6uzwMQI3Gf/e6BhJ87kYFyzyFCM8TUqBUIq4P70QP5+PzW5rYMgL8VAVo/uPm2/u8a/Z4Xmc5/RJ5xXBZpWP3Fzuug4dWgIrAWWSC6NaOz1gs8/mzn/cHU8ElaUM+CCEw7xeZ9RTJgYJKaX3Q/z+/G+BkSADwSWn+LtPfGIcD8e5d+UZkpxv4SO48H2/j1t3n6KxmINCsSxh2A7rjvyBj+h3HCt84cZ6TksBRSXFjS5S+OgOvRJNwiIBpldyRIb/KTn3j/AgQ6rJJaq2QA/MuIjmoCc/yZVDRmCHRenTwA/xIlALz9vgIJuWsJspAW5c8x4D3qx23U1IAnTTt54N3TzrH1Wz+kbTwMgZ/B8vN0Mhp6ShKBWEvaE4Srt1MNwD+J6NO14/eQoOkrWtSE7krJ9fyAzev20Rz4O7kQgK9RR390bs5P5O4IuaxoAuDt2XRkdOAOqXUSvX8qElg20F15A9m5GwD4IJxu8k09qSQyRQYPwMfWtofRzD+mQPr9yVzYHen25tLunR6IXxuHlLbiIKxl2vfX2Zi/imiOHWxeg9VYL7L77kaaAfgXqCEQde/vh4R2G9Ac720NpIz3Bfk4ANvYWRPo6SrgfS4ydzsv2DqLAfjH7fn+JCzkavRjFqS5/zPy9Fm4d3ohxYgxSCEn1DE3mavQdg0SSjMA/wlSaCyNPdPBe8OfX7vZOPwGWd6Gc+4hpKjYF515nwK3d3bbJ/XU6Q3oSl1pUkkIEP0W+LnLS13Q0yJgrCVtSrtoP8MFtbH8DRCz9G+7DLclAQBE35Rd8LMiCfRoxERM4571LihvaiMGHqXE/BZp+DeA66K8ugD8OdQIRht9FwD+L4hMI8kA+KfIa8APRgRnLY0oxPw+irSHjkEuDR7DfHYi89OvgQui+WwAm7RxvQ20eR9DCUCETKwfQoxdqYkxAh6/QS4Y+lneXMhH+J7IpUo8L/MgaXctjWqktfYZNVzjTEoJaTu9i5iRbZC25Qgb44cRAzxb9M1vbO5Waue2BAD+KzIgsZQIntwSkdCMjEE8xMbc+9jfmswdzWOIGfuOSGups/sU9acHYgxKAXgkCPw0fv5DSMgyp4EJBl3+3AiA/xALgOye9SRzPXMWcGBFHWdaHYfGY2//BwC+DwIWn6EN5svA0bY2R5EJ975GJtRT+7ompUQWqPsF5LLkOJq1qZ+w/h5CTR/F9u22yE3Kpqn9SxYY7Hqy+242Wzc7I5B7QGpeO2Gcgul/EAp9i+ia4P5lQ2RCH4IpLm75yyJ3YyOpcUcjpYAG8Ei8hqP3PAC/vlvnsdJJEbh3jdWzrB9bKgB4JDz7B3BGWfnuu+NpBt27Rf2oBOCpoJ0sfxYy2vkgIitTBFKMQ/EkxiKAM+kGIrXWEHi0QZR3BMUAvD+HtrX5SrpOYjwC2Hal7+naD9H5NYiERSdpAP5qagJuiLd4GNEqY5EiwWUoBlMAEgMA/1cMgCezfPyOyAq4oJ5rrS8nIj7lbjJrygAub2H13EcNVzedPDfLIhrvSAQQxi4G/0QGwHs3MH2RclMORC6oYxV7z8dsKwLgvQ/443BBWEvKn47MMuY/iAYYgYR5vwb2COUgvvBNpNHdbzzG7RbEo3ilMW81tTK6s1/0Zw/SgP8vTmBByd2J7qevbc3+z9ZfH/e8N+JNP0V8TViDdeO6LGfjtmrimbdS/7vV79fAfETWXyX1XEALsbTIA/C/oMBzwsSSkAeFwNO+iYQh80fvPIQs42vFeulKBWPd2Q3oSl1pUkh2mU5pl+wnFATztN/LIjOjWge6+24PHGiJNGlOR4T+WLuchiIiYnCq7oryffTqmRFROAYxEf7y7RZdGlMiRvVLSoJ+2bvTIw36oTgfrUibqw4AXzd411nkNZKWQSaGZQD8kygY5RaI0PxZUTtcvh+HvWwuFkaA9Nk2L5cjU89f2oW1pftmnRp9CWDAj5G7Ie8zdD67EMeRIA4R4Twa+EWU/zOb273i/iEf0aMQQdQvUaZ3CdADXcDvUUOLnYzAGDK++218vp9QCTH6o7EAaMh34BlkRPNrSIPAx0IoJbba2lcyAD5mCH4IwPu1CIhaKPFsOcS03m2/97AxOt1+T4MCO23VUe0dj37GAHzsA35KBArcSyR8+yEkOzuPs/P8d9GzuREA/wFwqstP3jFF+wZZso1D/uTXcPn+TA3ASNAYLNWkT9RxOWJyj0aC3qms/b+1vj1DgTb4xJrIGPhNEaC0I2K+h9EMwO+KuedosY7TkdZcvyjf39s3W9nJwOqp+eyEsboc0UxHI2BvHeR65xPL38feWxNpcjYQrfO6PX+BAuFQVM81iI67Pt4zlAPwLyLwv5bwB53Pw4kE8GRASBEA3wsFzPsvNehnYFHbNx/jgtPHc0kLGvBIADSWPH3p9/qM5GnnqaL2/8nm5+y642XfLo4ESe8RuVmiHID3bZto3RpMysn24seIl+hT8a4H4H9Gpk3at+K7K5BC0GlIuWMnxFOMQmDXNmT3TFDs+bOdF8E9UqUChtUzDPEcQQN4anRXfgms4t7djgJN+4kl2T570do+3Pbul7ZnPB0eNOB/hoTvPZDAIkc/l9QzOxJE/o281Y/fm0u7fO+C5kxKYn+R3ZVzIID4PXQnboJ43ecQDfKJ1XMwUgZ7jQQAT427DPHqn2ABYkve28r6sFuU7/nUorUW+rWEjduR6A4aZn89AB98wH8M7E2Bm56C8leyeV/L57v3wr4ZhIsfk3ivTIAwl43XEfa77l3oaZFV6nzTAXtmGUSPHWF/vb/2JS1Nm/iuP9KIvx4npOlKbZiDzm5AV+pKE1sqO1AQAzIKMXxrJ573sIvxJWCxFutdxC7xF4E/oqBuDUQUBcZiWbuc36GGNN2VfSqSni/h8ma2C7CJiXDvrIJM5z6jwCcqxuxEF+0I64MnUpaiBgBfoy997aL9WZRfBcC/jUD4Bo7gSF24SMN9yfgZciXybzINhLVtvu6wNfGhjenM0XdFxMlPkSR5HAJ1G8jvmgeL5iVzQXOCy9/B5s77hQ/M7b22Dr8P0EXeJ/mDto4PJXM9FPd1NqRVPxI4usa8hLX0PmKe22ReF62tdZkIGEq3tpdCDNK9OE0yG+vvyALVvgVcGX1bCzRrZT8gkG4h93uSAObGcy5WJDOJfo40AH8+EoAG89+WNBAnpkQGwH+DNOPmsvz+SHv7S2q4G5ucEtJg+95tkP3+jnIA/hSXXynktfENZ+eaVv4/cVq28V5FAFqDGnE53DcBqNwIY9DdOT4V0k4cjVk3dfbYt9AvL8R9FAFQPRAA/xEOgEe0z+uItulbt3wkSL6/YC7CGE5jZd/R2WNS0I/90J25PpHFBHKj84bt8V0sr4+tlWORJt625EGfIlrjekQbrWx75mfxniENwC+EwKAPccHWKtbzZyQUD8gDER6AD0oCWyMNycNaGL8tEe31AQ6AT7wXAPhRFLuE3Bqds0m/z+48mIkC2pnM8uoI/03NvmyNrDTfoVlwUUsDvqj/Xaltydb/E4hWr2WVQx6AP53qYKU/tfW7Lnmr5mlQsOMPkIXj+mT05PaItnmHmpaPZIoI57u8AMBvie6ZEOcr1LOd1XM/iXhfnTw3lyDh4x6IX+uNhBS3WZtvIO9C8w505p2E7p+cUlPJuIWxCK45toyelwHw1wMHVfTD8zxzIGHqG6Ee69fyiBd/guag1y0p+lmZfa2cS+x3z7hNCGCdGglgf0WkmBe3vWIf/BYB8FMiq4ChNAPwvRHvOA4XaLpGXxa2cTi8rE02tm0Kwm3fPwD8tQ3f1R6zDtgz59gYj0CCjgayOLgq8W7Ow4Lts0+BbTqr/ZNL6vQGdKWuNLElTKJbchEPJjMN89oxc9rhNJIKYst9kwuchQK+PIuYneeRVHJA9E0IkFLLVzECUIMJ+1U4oQAlADwZofYEpnmVGhcSQgAUATsHslv+UmQA/JA2zE0Yr8eAW+x/z+RXAfCjwgVdNMcI3Btt43UKeXO7NRBAcCSZadzciJENPtIawCI1+nIJ0pQ/AzHEcyPhzpNWxo3u3bnJAPjjEEE8hkiIQJrpDO2MGfuHaAbggyBlPxvHd4CjysbL8m9Al/J6iIF4BTHVTcBoxZh4IvRQxMSv0UoZEzohYvprMu33H9u8nIh8jm+NtGRLAQTM3BHt8RWAOVLj0OremNwT8oX6FJn545thnZEBbosjgG8c0lqr1KKZmBMCGkOA0EeRpuwfkYCh0wNFdvBYXGPn83IubwaqAfh3MFcWNer4jZ1pvcnunEGkAXjPYG6JwLtajCPyU90AVkw8C/X2QWf/dxigN7EmBAQ3BZNEfr/fsb/TIuHvh8iSKIA/x1Dz7rT3uyMt42dcXpMmG3IzdBsSkk9UbnusfTdbmjp+Zn9nQ8LcZ4n8ByfKKwId1kFKA+uS0ZrJPZMaI+T2YnCN/lyOXKGtFpdl59eN5BUCAgD/X3v+LXmapqg/y0a/t0B3QhUAvxACyBqkhbaL4wRnyBLxIESLxAoVM5Knnb37xieAp1tYBx7kCAFUqwD4JeuW35XanpD28ShghRa/q3QHSmZRfScCJJPuNpAS1FDgL1F+0Ew/xuWVae8OQoojn2LuidxePATxrku5toWzIri62aKz58P1ZVsEHm8W9xkBxqeSxRDr5579noxP89bPdQPUvoBA5BnJ8yuFwrGK+TgM08Z3+bPbGfAhoili91bLIxziASqs0Svqvw9p85fGlUGKgH+I12XBuz8hIbxE1uIfIgFGb3Tef0RaA37nijoOwbl/IbM4GkGJi09kFfslkZuyGn0Ke+RC4L/ttH47nF9DmMMw5GJ2PuTqaCXE6zeQ+6lAj/m7e16ECXxNDSuRrlRjLjq7AV2pK01MCZm8fi9JJs9Y+4t2BwQuNhCR/AJiIt4jTwgVMQ8LRb+/lygjjbv+NAdA6YYY15vskOxb8zKck8zfagOZMi7inscAfNC+620XvDdJiomcqxHAtRN58HAAMlUchtMEsGdLIWa4QQt+8aO5uNj606TNSjkAP2dRX8K39nc5Mn+xL5A3jT4bgcveV2wfu6B+V+dyQoF1hiPCPqd5bpfiDVb3ZdGYBrcusRZ80zpFwoYzEHH1GPLvtzB5YcVDNAPws9r7vyHvOqiIMDvExvr7PYM0dF5BmuC1AHjy++sgpM3TZsKyvZObn3mRUOACxAA0EKHvBVfTuf9TIMDpiLgeg4jBIMxrqb+psn8ICTE6I9H59CTSbPUWAD0ROP0lGRA0yY8V0pC7G4FxN+NMgYv25+SU0D01gkQ8CcQMFwHwA4F7bM2Uxl9Ad9rnONcxVADw9qw/upfuRJrFZRphIVj4f5Ag3Qc0656odypEbzzQ2XNQMTdByH8bEiT3s2ezIKHRdW6sAgB/HGKeFwC2b7HO/a3Obf3YJt67CGnvNVn3dfKYzWBj8POC54Em3BTdh4e0sZ4+uOCNbl3VBuDLxtfyF7S5eJ4IqEQBrr8m75IvtGFhMouxo+PniXp2sXd3j/K3oB4AvxiwUVW/bC8PRcKEhs3Tcv5dmgH4QEMFQVKpmwEKFGiQ9m4ZAP8JugeWLSu/K7U9ufX5U3RGT+3zC76pbY3svpmDBK8SvdONzLXMTiHP/s4Tt7mivpXQXTgCozcRzzSSyLUleQB+/jr96cD5OQfFhujn2+vHAtHo37sjcc/+hIuPUTGn8blwKhKwr2S/vfs0vzeXqyjnTHRWfoQ08RePns+OBKbvIYFckwIJeYFf6dwj2mUwwi6WsLzdEP9+PdldEytpzYkE15UKhcjSNPCnf0EBzoOV+FSIZr3Lfk+H+OCPkFJgk1Vfqk/Wnm+QMHpLl78L4qn/RaYY5WmpHkjQ8RJtt8rezOpepsXv/LpckQIr3Am8X7ZGNNDmbq7D39mRktJY4DbfboQhPI7u6MPcs8me35ig89HZDehKXWliSkgz6B9Isy4EuioC4Be1i+wa4FZEHK3lnhcxD2chUPoGpIkznX8/qs8DpT2RH7jPKTCbTdTVzS656xEDdKJdjDcCC7v3PAB/IGl/XylGJmh7Bwn2EPdsB8S4XIIDI+3Z0kgD49A2ztMQpCU1INU2MgB+OAltwdTc2Bg9SN5Vzi4IiA5+G0PwsMeAP1eMTdH8/wIxu8tE+Z7QHWjt/xoHSCC/cxcA+1f05UwkNPi3rbMHERD5JSKIZnHvPkQGwIe1OAN5typFfemBtNdiTbQetADA0wy8j2MidaVh++mPtia+QcT4NAXvptbFZYipPwRpsMyPtEWexfkmLxv3xJgtFe+xyTGREYszIeuCM1GQu9eILC3QGTMKOLez253ox4XAAS287++EEDC0CaStWicTqC89O6iea5DG3rpxfWQ+Pcs04OfFBd0uqONaEuB+NP6DSGvAD0YAXanWlr0b1vGPkD/0t/x6iOoLWmkX2XstAzwdkcg0Cu+xvfhP5BZqYwSuD7Lzck17vx/SvBsOnFw03hV1roDAiadwLhGivTE98o18RUes0xbHbEab03PjdkfvDUDKBte2WP7+iG75J1IaWCTUQ0ZrtAzAl9S3BWLg7ycLBnkeAvZSgHegeRfz+6Zs/pFbw9tsLcV+iLegBgBfVQ+Z65zBiL7ZBwEX79Ec+NoD8Ada3tyYm6CSus9HAqkrkWbzHNHzbWz/vEvzeRTA/dI4Bl1p/BMC3MbhBHwl7/4aOK3F8ueyM/AQ+120JhdDvN/J/j23j1txb7QaOqc/Qz7mv7R12N2XGZXfcj0TaD662fn1KPBHy0sGOLe9+yYC23uQBrBT/NMgYIEoL9A5/ZGyx1/cM3/fVO5NG+tPkNVsIW+EBDMBgN+KAg31sjPOnv8CuTb7xtr2sp0vPZBG+9fABYnveqAz8D3qxeC4DN0jD6Jz+D6EDeyFQPMFbC9tZu9Pg4D34bZ3Su8cZIERaIm3bGy2cc+PR5jD64juCIqEc1o/RlITc0AKhRsCs0XraTQtxPSJ9tKhSKDa4UJTBKL/mzzv79s2E+JLGjjLBSQYugYXuyy1Z7pSi/PR2Q3oSl2pKpEAgidwfash1yLfkdaAr6NdUERADUC+3BqISRmOtKXXIG96GoPJS6DgMF+Sl9iXate5/zey+hZDfoIDAB9rwF9hz46igKDxZSOf57cjreprkfnwLWQg7gXowg/ap76PMxSVH9V1js3HMYi5mg0BKWOBHaJ3vbBiKaSB0KBCUo20Hb8kE7j4sVsYScxHIHDlTLuUnyOvsdhEsCbqWdLm/E2cT9TUtzZXI3Ha7/F+SK0zRMx8iAQUXtN/bQTof4s0NLyQ4W/W/yNJBGEt6MsJCDCOhUeh/d2RG5rggmbhgnJSwPuP67ShsxJilscAd7b43e6I+NqEZh+LS6M9mTOHrTFmh9seaynGxKSSbN12J2MMwzq7Emm59EE+uQMAv7A9nxYJ+L6khq/iDuzPrAhQOc1+1w3c1EosgOWQYKdWAOvx6MvudnbOPYHrCSbkm9pvf84fbPsprAvvz/q3BeWlzs0rEBgxKPFss+j3mrb//2n/b4OYsjpBvI/BmcrbXD2CwNUkAG+/r0QA4EQlZIvOolvQPXmyrY1LEWD0ILL2eQBpxwUt0r7IciXpYzuqpwiYDi7uHiYCCJBLh92QsLMSPOuk8fuDnQdzV7z3MCbwr3MWIMu9D9Dd/pSt1+dxcX/cu5V7pqSeOAj05mSxim5GwE4SrEB0XL8or9Tvsv2/MBIqjKVZA35z6++HOEFdnTGzd68M5wB5un9P60vKRdRMZLTzsVX9IQv817Ax/wQp5Fxm9fgAgcEHfLy2W9K+7Eq11/NPEX0fzudFER1+GxZnpOC7AYgeqeVy1H03rZ2BT5B24enX/XOYO8qaZ8C86H7axP56TenVUfyN0cA/XP5EC6xFY3E78FzqWfTNb4CXqspzeUNsX/4P8X3esqAbAn8vsjNiNZfvz4rCvYmCan9IFMDa7fm5yQOkQQP+bWRp25ILRTIr650QeLyxnTfvIjB8JnQ/j0H386qIRl3W9sJIWgiEjoSKbyEf8Zsgy7Y3ESB+DqJ1fo/x/8hF0K1U8HyIN3oP01pHAYPfQRZC27n3DkE8ZwMpfj2BFNFqeSWwZ9vY9+MQ7fAiAqD3tb6dX3MsUrxth1pzh7WJhFV3VLw7t/X3lih/Sl9eR7Z/ck2d3oCu1JXKEmKcLmECBnhAgO65wEUuLwnAR4fpdEhyvZ/9rkvcH2EH+7FIK2iE/b6DZh/pPZDf8Y8Q43SQe1bEpDRp09v/3uQrtCEG4GdBDPSBNfvSD13uNyHwcENEJDyHIpYvgi72Z8lA2disrewSnBYJJ+4hC5b6NSImvkOM0pYk3PTY9ysCm1T0IantmHhvfmvH5zYfLyNwv6WAoEh6/5KNyXqpcSAjxP6MiIda5vJkWgTrujLC325Iy+a3iKDaOPr2ERvfpWvUMwXSmPnY5rdfwdzGAHyZlkcwq50oNd79PCHA97eIiE0KFQq+vRoBwl7w4ffoIshtxbckAtYl1slB9u5+rfRhUklkZqx3IPBuZvdsZlvrR9nvEGvgexc0yFLo0M7uR6JfvwMem0Bln4CYjduI4oW0cz2/sPH+N4ng4+1YT3d0d32CrJO8S6cLbH2sFH0zPWJyG8C9NeoI8TR2TDwLdYQ15YOwjkIAZ1P8jYJ6rrP9GlsKlQLwyF/qI8BZ9nuiYoDIC0P+gACdE+33qkjr6jMbxwcQ3RDupVIBke37VeNxTZyD3yAA83SkbLCNnR85hYWCOrzVWW2gtp3GLtx75+J8ukf9G4hohiNrlhmC+K5PJug4GoHVN5CgJ1rdM/bNXuge/Em0XrcgA5cPLejTLoimra0FGH2/CNUA/Ls4GqtG+SsjgOTvRL5vbQ9+gARnM+H8FNvzmZH2ZmlwRff+cTY+tyCNzZMRsDPO6rnT5u80BJy8ScJXMRMxWDqpJQQ6jkZg21rujDrG5uUkEm5O0B21N7oPS2MU2RrbDAGpofwgXD4Q55IiWu8L2hrYp2ZfTrf9NQbxSg0scKx7Z03kHmQEedeaE+WaIn9GH2d7f8f4efTueQhI7019Hn1/JJhoIHryclsb4SydF/GhsWJULDCPf8+EhKGnk3dTGdbBkog3ew2Y3T2fHdF0X9MCv4nompEISPd35/rWt0Ps94z27juWPwa5QnqR/PldZGW9a5R3MbJSvN7GfV7bH+/ZnD2GtPqn8P2P59DlhftsvSjfA/DeQnxZdDfdgniHw3DCyzrrG7l/XR7tyZuQYG2kjc8zRJYRRWvV/u90a27Ec/yXAgGiW4NX23v9OqutP4TU6Q3oSl2pKNll8D/k4mH1CVTHhYhgeggx2TO6Z4Ua8Ah4P9wO4lruA9y3syPg9gH7vQwivj+zuu63w7q/Pf8RAuBXi8tK1HEVAobvREyvl1juhQDsoBkazONiFzRNvtfcs/XiwxtJzz8jM4fsiaTEf0cM0LVImnpq6mItqSs2d5wdaYPvgQQyo639QxHT/bzN4WC7NJMBzKK8YP7XBHQitzkL+29t3gcjc7rAXFYGYiIKwIMA+JeRkCIJwNvvuxGhUqntgEzaGlQIqmwMn0MWGP2iZ1tX1ePe7YU05T+0ue5n+XFk9wDAv4TApSYNbcRYvEYnECd1xrbgu11tvA+L+1zw/tToPLsgNdfuvbXROXBi/B5pgm6ithIYj3lZCBG8DQTw3oGYxCMxX7oIsArxL3oipuIlBLosFpXX6QylO8tOQUxDy21KnBF+TVxq+/FnmN/LCdSPi9GZuxtOSyvVvnYarz5IK/Qj4AbLOwuZGG9c8O0M6M6pBMPIgLALcBrI9vvLuA6y+2AQkbZr0ZySMZBJQQW65wMAf6DL74XcXvwXZ/o7sSXyWnwhpssJmLYlur+PJG8mXmothgTeb6K7PrgxSVohIrP8O+3sHI0EIw9REiw+qqs/AgommD9WCkAGJLAYgwDY2P1IT0TzNGk/F9QRXAuGM9JbGz6Kguc1KSrY81b2zIXoPruFPLAR9uyG1o77ccIxJLjfAQmhKgMgI23Do5DF47TRs8VsraUA+M0QnTMKaSXX0RSeDVnSfI0EflO6/mxk+UNtHz+L7uBV3PdVgqSlot9n2BhdauuvL7LYvAxpQ49G53kAfb7CuUHoSu2fEAD6FuIn1rH1Oj0CEschMHcp9/6syFphNBUBsZHrp1dt7QdB5JK2xx9Gd+oQMt7ve4UlBF6+gQkiK+q53Mo60MpfHNgenaUjgSvdu8EFzQgmUsUXxC+djQR9G1veANuHj5APvu7P2P7oTrjafped/6dgVgX2e0Ybm7+QKVxdgVm+IC3uoVQIW6I6VkBnVcoF1wp2vjxl8/QUeQB+ThLKASV1rW1r7CmMprF11gMB38MRhhHWWG/r8/aIx10L5xs9NXZIWe/v6O7aJnp2ATqvridzDzsT4puSCnGkaYCLEA02yL/n2p3UgI/fK+tH9Dx5hiM+dl5EZ7yL+PKktTETIZ+G7tDvMLyBYkvCqxEv3uF+6X9IqdMb0JW6Uioh4P0TRKT7C6jdtJIQgDAcaUjNWPBOCoDvb5fWWFzQy5J6jsW0iREhNwUCj78j7yN+RjJp+0gkcT8SWDQqrwi0W5QMEH4REYO3kHeN8iBOq8nKbyCzrzjgS3xpbWXvPkQzo7MzIlC2dP3cgMyNRvAzN7CF+elFAZNoz3+LiJSVEeH0a7s0xlp921WUH4QPB4c2R2tjrB8TMsBlCqSRfw5weI1+DLF6do7ySwF4BD4+j2m7la17RFQNRhpTf8dp0BW8f5ytvwBoxC5QigCko6Mx6UVmRlkFwG+ACNhkvAJatCBoj4T2/km0XfvueSoYFiQICmvnCcTolFoyIEbsAfKA1kRH0HXA/GyELAW+RdqM+yEgfhgCiY5GhP+G9n4Pt84Gd3b7S/q1mvVptRa/82tgdfKasscj4erGOIFSfG7Ee7MNbd8OnbObUeKarB3HKmie9kHM7wcoUOlI5K6t7FwsHIfEu0Hr90IUHOxcxAwXgftBU8j7BC0D3keQFvL2df97Dfj9LW8b6+thZe2fGFJ0Xv3WxvNETGBPiWu9kjLXRQG/vsYE3RQD8D2RdddyCJidPvVeVP42ZK5GPkag6nYU0IRtHJc9iTSpo7U9JZmLvD8joc6sSCBzpPW90vQfgbe3ILDCB2sPApDbEQDfr2j86+wZ2xufIKDGWyNNgc7gQMNsQQbAB9BqO3Rmn1ijnmPJ6Mf/ISDpQPJ082xkAPyQ6PttiVwTFtSzB5lP534IgP8GuNXylkZA0oOI1rze2hJozWdwASlT/aGYDgwA/JU4Fxdu7e+H1v9HVIC7Xal9EnLz+S7SNh5keXOQ+UR+G1ldXIM0md+nwqUFugM+RdbSG6LYS58iurkPUmIK59zltuZ6I+A8CISOqtH2wQiM3IhmS9QByP/5aOBsl78yOn9G0UIsmg6ai0ttvF+xPTAOCd672/4ejfjmNaPv+iDrmmFUKyRNh+6rL0i4+USa1DdZWeMQf3gV0uSuMyfhPNwcnc3fx96wv71sXn5p9R2EaKz/kLiHqB8T5UQbu78A87r8IBhdz7evqv0FzxZHwuNviFy7IQD+c2RtNZ/llWq5R99fYu28nYSbWtIA/NbueW1aF7nYmTbRxinitiJlsg+QclChu0+0bzvVmtuN0RyIX30TU5iJ1xG6+24HLq8zP11pPOalsxvQlbpSnFBU5jftopog2ooILH4TMQcpQskftB6A3xwR6g1cZPiidiLNra/se1/m7IgZvylq01gEjB6JQKekKXzF2I1EQPQxiEn4BPmm3QdpET2IsyQgAx1KteqQ1Ho7RJR+iYjPORCzNS3SFLqVCGBHjOcHGMhdow+7IO2SpxAIeSL5wHZ97O9pwFuJNs5HgcuO6N39bQ38C6dNggiGL2hNOl+mUbEKImzHATtFz4oA+N6IyXyBmlYfiIHfDmlj/INII9XeCYDREraet2hhbS1ga+kt8oEt6wLwPUi4wSgbuwmZkPDkNUS4r9Lit90slfoSR8T0fWTEzq8QwLNAwRgFQukvCCRpIh6Ry6hvmIyBd/Jn5fpIC/ALpHkyNdK4fgOBOsF0PwBMyXXWiX3Zw/b53C5vADqnK4GhgjE5FDGiAdAKfjuPJTKvRozlIgjI6xOX1Yb+nI5AgtgCamUEFN2OmI5280lMHoC/HDF0D5CZgY+XQMHV8zNbTy/Zeku6rEDg6BqYMN3yimiACxBAsGLcVgS4XU0e8AwA/BtIeP0NeZc2EzVDRDMAPw7d4S2B2dEaXhfRA0kA3r03HQlz8KIxQ3fAf+wcOcHW1jO2Bq6mHeJoIEa9ge6ZEDCvSOvsEnSPNhB9OALRAIe6d6o09+ZEgNUX5DVcV0T05Xj5nEXAzetIGSM1B/GdFpQ27kECwm+j9VxGO+2P6I1X0T16vX0/Gmkenoc0e9eyPjfFAaqqB4Gin5B3v9gPnWFjEB3+le1V7/KqG9IuPbrOmNr4F9GBp9sYXYED8d3zqcmDZ51uxTU5pdR+JAPgXyTPf2yM+Jx/IzDr5zgBbcGeuNz28mpkNF5vsngVgy1vViRI+tbWydtkLi4Pd+WVgaGX2Zrtl+ojoj0eR3To2u75Khif2Nnz4dp0NVKQ2xJpWS+IQO8xGNCLLLpH2VxdgpQSdrF5qXQ55uqa0/b4CODSgndWRNZJwxDv0EBC22nL5iRaU6NTbbK5965orrB65qzT/qL1jO7e9zClH+Q+ayTw8/GcG38/L4YsU4sA+BEIgB9YtX7dd9egO+wa2w8XkhZExAD8k3EbatS1HBndV0lTIrpvHavvaSKLJrdWhtLBfBrF99wUtle+QLTlwtEc9kEY1Cc4Fz5daQLNU2c3oCt1pTghAv0posBiyCzrUAT6noj8YLbEiLqD+goEcPUveddrVK2GNByCFk4l8G7PeiHNli/Ia6D3RBf9GOR2JriwOC2qtyk4VqKO2E/8jghYvc7GbB4Exj/m2n9A9E0rmr8L2IUaAoceijSuVkOX/A72npcez+H+ryIc30ag+20IzP0WaZacGL27HiJQ1ywqu2xuwtjZRfSEXUZnIMKkyk98HZ9xHkxfBmk2NCgH4EPA1x0Q4VhLYOHK6oO00QIA3xTAyd7bHRGsrfgrD1rFLyEtNO+qqBSAT8xLpwJIyJTxExuHuSdE28iIx3XJzp3lbN/8xddHngia0db/6XF7kDBvsvXxXjQPNobPIBAkgG9z2lq/gmJris5eZxsjQGgsYtLeRoDkkUiT61rquSwqDdxk62IkEeOMhBRBiNtArkuCK62WAGukadbNynsqenYUOqPHkrlI+BdmWdNOYxlrwH+EhFtB6NIugBSZO7m7STC+6GxuFK256N0l7d0XiMzTEXA4Gtg88d2yCCBpkA/iOkmAbjQD8N8iS5VSi6xEOVUAvK9nOuQC7L8kmOFE2VcjAGpHnCAJ0ZVBG/kmxtMiC5jG+v4RojmbAHjyNN+CSClkPwR0l5r+W/6O5F0mzoEAvy9snS2Kzk6vDd+msxEpBbxKBIQgYdSJiO64FIEhoa+bk51Bx9Toj3eX+BPbP48hlyyzouCBDyDAbTQ6S+9DdE+TdnlJX65BwFCTKyhk4XoQUhx5D7OiIAquWLReC54vSzEd6AF4H+QxKaDvSuOfyPsLTwHwS5JpwK9KJmjtkfomtS5sHzTQOThb9GxlW7+xz+y1kbLUWei+WbqsDvdsKtsL1xY8D+1f3Oo9NXpeGFA2lN+Bc3MVAnPXj/IXsH1+HxldvRJSVvkM8TWj7HyodDnm9zOiKa8mAuCJXFMiEP1gdNecVNKHg8i7xJkJCXtfpIQ2IrO8+xUSvLW858nfKQGA/4fN+0VhLttYdkoBrQyAD54MbsIJEUvKvwXxSYOQUtmRiOa9iHIN+EHoTn+D1nzj90FKgh+hvR5oylIaGWEQ31AAVtMCrtIeCSlcbkuzJXsYn562bj9EVjdno6C42yFh1RfUFFZ1pfGcq85uQFfqSnFCBPGb7nd3BOx9RBZws2EXyWL2Tl0T5m52mb2Bmd2VHbDkmb91kHbhwS4vRWzlAosiLZqXkYR0TvfemogpfRKB5afR7Ke8W1E9ln+tjcUiUf5OVuYdSMu+G9IIPxFp1e3m+15VT9xfxFCuiEDC0If57HL8iIxRSV4CBWWfiS7ojckHpFwBaZmMJG8quTQCqHetuwbsgtksytsLaXJ9iC7SpBY0crNQN+DZETYO3sy+jPEKAPzT1sbvA9a1sr7t3VIAHvl1vQoFYOlXc9zCOumONJFfphqA7+v3wcSSkPn3W7bO2gxmkT8b1sK5h0IM9Oc0A27ToH3esL05ZfS8JxLEfQxsWlBvbJq+LBIiXWvzuj4Tkeb3eM5VDL49befAyvHz1O/OTkhgNRUS7A1G5sr3IeZurJ07S5W1mzTwvlf0zqKImL4UabkvisC3hp1DPycDrP+Hc3XShj7tZuVehMDOv9jvxxERPxsZgH1aO49nFQDfiplx2ZgfZe2/GGfdgs7p0ZQw3ImydrF2PoRZMZEFQtuw5LuVcEzs+JxVnbT2Pbj8R2rGRymbJ/IA/Iouvy8yG29Qg3m0tfMZYtaTlgtIE34c5s+/LePvyp6aTGOyFIBHYENT3J2i9Wp7u4GUFTzdFAD4Efb8srjONs7r6YjuCvRtHxur4VbPB4gmfB3YlIy23BwL8Fc2nggQyIEsyN/1/xCdGQQv3RCYNcT26QfWrgYuZkJJP4IrqLUSz0KbZ0TChtHIsrO2Gyv/XrSG6wDwl1IDpOpK47WO17WxvsXlFQHw7yHeL6z5JrcUFXWdifixM8i7Ud3K9soaRfXHa6nieW9EI90Zt9O90wPR8Y8iWqRH3IdUPUgr9gwK6NJ2npt+dn6MQOCgPyd7IH7wej/+SPt8IBJcLEzeJV+KT1+IhDAYWQYEoZwH4MPc+73cq6gOZKU52tq6pGtnUMj4PU65zj3vgZSC3qcFy8iCcfQA/AmIr3gX41XqnmGujH0xYULBGgkA/Oh4naAzukFF3BJkgfEkeWuSqRBNVgeAX49IIbGivuBurDei0T+hAoBH93mwZi605iaK3dABe+ZjpOCzKQWuZG19rYMUMkfZnIxG59ve8ftdaQLNV2c3oCt1pf/7v/+DvG/OAxFwdbMduCG45SMIAJ0LEQJfUWAeVqO+l3AuX0remxnzvWq/PXhexDwsmshbCwG7Z0f5V1vfzmlDH4IPwSbmwZ7viDTr7yBvUtuuAZuQq4NXEJhwHWJqr6eFQJaIWHoJaXukfKIuaJfDF8Ce7vmzwM0165gbaRx87+vOPdsTafG/ggsOFo3lWOCnNev6iY39vFF+GeMVAiLlAIS2XIIUAPDI9GwwYlR3qlFO0nUN0oAvA+DfRZqvhZYlnZWQ+eKfERDuidMlEfB9oY1d35IyPAH+U8T0r2q/z7U5PCIqPxCHsyDLkTGIUdrX1ve6tpe+wgVwrOjL8Ugj8FNkBvuFrdO7qeF6aVJIpMG3kUTar0xEwDty/3UxCva1UOL5LNaX/yDtqRVS7ScNvP/Yfm9P3t/4iWRg+5c2Rtdi5xliuIMPylIfqFEbTgL+7H7PC/yCLOD1RwiEXyj67jl0Z5cGIUz1teK9GIB/D2lKTVvj2yNwsUDK6iRzQXMRojm2oabLDKJzDwHwnyDT79tsjyeBd3QXxkK5TmOECtZlXZ+z/i5vCjLXljaQB+CXdfMa35tFYHVwG3hEWT8Qg32r7aOmPdxC26sAeA/k9bU9eiPS8K4C2/oiIfooRF/eg3M3gQD4KxAwfq3Lb0kgjnMhhVxADEN0xTlkQbEfQHTBdAhA+QD4XWouSvZNL3Q3BitQD8D/mMxKsckVHwLiB9VZZ0hIPRQBdXHbjiIPQvQj8wF/I+a6q0YdA6LfMQB/Fwm3ksinfMPqmq5OXV2p9YTu4JMRHebdf6bAtk1tTvYdj/qCkOxsRIcvbmdLYdDhsvOp5JuLEf88X1kZtv7+RY37GVnPvIno5ib+aALNz0AyH9WbkWlqr4HoIG+1UEt5weVdh+6P15Cb160tP8TlGIB48zh2RpG7sFQd3e08ehPdV0uR3QWHImHMvcBW7pt5kKutUdTkAWqMo+dBQlygv5IFYa17l69q6/UfwJIl/V7c1slXNMerK3WhiqyN1iDNd9YG4Guui11tr/wFKZT0tjnbHd1vHoD3d/R0Nn+PkLfoj4UvZ+Li63XQnpnb2h32TKnyI+I7l7B1Vxkfpyu141x1dgO6UldCYNUt5AMWXUNmQvqOHXbe/LYnIhyewQV4KqkjAF/d7JD9ox1QS1V8F8xl6wY9vczeP5484B20jUfjNK8RU/4NYjimqOqH+y5o7TSZy0bvBQD+j+HCrOpDC/PmGeulbR7HWf8/JdLGryhrQxubJjcobu4WsTVxLxkA81cEYNbS5kL+AB+0dsbmjHuSMXeruPWyo83RyS30Zz1EQA1KjFUZAL8rzp3B+FyC5AH4RxGzsY2Nc2lwKMs/DQGDxyLm43tf0ohJXhcRrykA/jjrf22Qb0Im1+6eNv+PRs8PtblvuHQ9CUEVzYDod5h5q+3LUcgs/y0kdGsKmoo06gaT+Rdu2HdP4LT2yuYfua1639oQNFkGIOHHWCRoajPgNTEl0uDb5zjt14klIUY1WLEcgQFXZIyXZ4ZWQgK//6DAvEV7MYDme7nvGsgs2bvM+DESWt+ELJP6RXVvbPs/KbBN1DslmRbYzS6/H9Ku35A0EzQnEoye2+LYtQTqojPuWutT0j+7+2ZGG7NXyd/BVQD8d0hrPfa9XgRq7I3upTiw4q5k2sFHpepHSgUvYZYdE0NC5/n8yHWatwKoS6vEQf/adKclzoCnkbDxEiQUKRVYY+4FkOuvx0icz4lvtiFxT7eh7UUAvNekno5Me78yiJ/7bj90Fp6MaOX7yAPwc5K5oLnC5delmfa2Nu3m8k5EZ9Y3SEP1J0Rm/ojmfIcW3SYgDdZTEI12OsUA/CouP6XhW7Q/t7X+XJF4dgGil1eP8vshpaBgsValoXwysgTy1hkpDfi7rJ8bR9+fR01Fj67UWiJ//86MhMsNSgB4pKjxGnD+eNZ9ls33DQjYvZyERnUbyw605SZIAepvZIGu4/7MgvjnSss02xPDkPubAXF9E3iuBqL78C0E/q6IQN0Lx6PM6dGd3rByP0VA/OuInlob0QpTIZ79Q1o4N+3bIFidAlm4v4to1gBa90AWO1+Tacc/gIDT/+ECKxedY+Ox5oMLmrtp0boG3U9vIOB5qaJ1YGP4MebWiBo0AALWH7bvkpZL1ADga/bjMnQ3PUum8HY5Emb3RgL6oTYf07rv/B1dKByxef898EgH7JEByOJgrmjPJAF49900JOi5jtjXXen/usD3rtT5CRGaDTsQPcC+DJKCNmnP2gX3j3Aplh0YCIA8gry530ZW5/nkTXU9UDY1kl7+iZpm+shctIHAit+SZwhXtQP9DvIS0/sQIFBXQ/BKzB9a3HekXXFk9H4A4G8DFm/nuYslqRsik7FKs9/ou50QI5cMYEnGvAYGKABax1KDSSHv/iUE0E0B8HuRMXcrW3/GUDNAWLR2PgbODONEM+MVAPiWAoS1OK4BgH8fEYBjyLuzKWJQNyMPRL+LiJUr7dlM9l4AQd6mGYBfbnzb347rdE772x1p6w1Ffnh3RQEiG4gA3snm/WQSmk40A+9eE/mXiJBfGwGTT9q4rU2e+PVlBOJ8EyTA8sRQGfB+ldW1PgkLE+vXVwgAWKbOGE3sKRq3dZBWVAMxklXC1w7R5EAE/KfozE0GyiISsiKt95cQ89fk8srWxfu4wE2ICdkfaSL9kjwA363g/z5IoPY8rcV6mB4JVj8Ffl3wjtcM6oGYl4+pEdAZAW1nuN91AXjvpqOuMGERBCS8jPO1XrZ+yDTgj61qIwIq3kB3/8aJOdjexvFB8rFKpkDgxndEfng7M9k83oIAgtG2Dn9Di8FTE+W21d94fAYEv/iVlmIYcITu4sUoOJ+jtTUtAkgObYexLALgA9Mb/NpWau8nxuJRZGWzG6INUxrw4WxK+oMuqWddJHwahgWGtPy5kTZnk3Y20mC8FxPYtTrfNu7BPVsZAN+SFi7Sjh+ABJQN8oFsL0R35sYF306PgJ8DatRzOBKI3I1ztUQzHbgSEgQ9bm1LaV13gSHtmOLxRG7STqIZgO8RvfMfarqdrKg/xJN4kfGMJ1FSx0XovP4DzYHReyH68CMiF5yJcrZHAPXmqbXZQfM10MZ+KKJ3rqGN1o7urJ3P+v8cAlPXQQKRV21uPrQxPMXO1U+Ai2qUvw+ixw73bSQD4J/GKcGhe+h4BNT+BSkBre6e16WF6rgO9TzIcWTWS6XWNbb2PUZysK2JJgA+OtueAW6v2f4rkaXUqYj/KmwTeQD+AloP5H4VuiM3Q/fUAISbjMViaSEAfggZAB8sIo6kvoXdECTwHtjqOm2hL8eQCSyGkCnbDKQEgEdChGORADCJuXSlCZs6vQFdqSv93//9H2TEzxU4AN499+BpD0SADwW2rCj3bLtQ/0tmotzNUtDUPp0IKEEM/S52SO/ZQj+WRqbK1yNi/kksmKc9D9Htd3XfBB+6pVrs9u56ZFq500TPzkeM4vqJ77a37+7DmRdNoLn0jFJd4iFYGISAo8kgU4iIaZBppk8XvxN9VwTmr0E5AP8KApsb1NN2XB9p0Xgi5WngVt8+8gTQsmTA7+AJOB99EKj8PjWD9yEC/RIEUj2MLvaLEEAYwPgbkfZ2sBh4jrSLjTrCignGYCJG+xUyE8I5EfgVAkN+jAjgxdw3M2Jmtm7uyoD3IYhxX9e9szg1AJ5WxwMRjw0SwGa0vsJZc3Ldeeis1MI54edgIyKT/cT7tc/udujD/jbXG0ftDD4lFyXz7RoD8CvZOty1oOzFE/PbB2m9fksCgI/enRYx3F8DB7XQp6CVNz26Xz4lf6bFRP1cSFP2a2qYTSPByQOICagMxJj4vjIYIWIeF8aE78jX63AqAHikGRS+WbKqbUiJ4FMEovvgl93I0y+7IWb+IbcetqemYLQD1/P5iHa6BQm9dybz5/ofalqdROt8kXjNtGHOfXmbR3NYNDe5O8DySgF4e2cTW8vJODBtGNMUAP9XZK30HS26myM7Ww5GQMoy6E7+0srt596dAwFXDWoKq9y3qyNN2s9I0CrR+u6JaIJPacFncWL/xQC8N4sPNNqzRHFVSsr/FfC4/b8wsg5qIAHTqTbPm1TM25RF7U18sw86Z/5KOQC/D1I8mb9mP7rA+DYkRG//xM6Ci5F7iX72zAPwN0ff9UGuAT+inVz5kSl3nEk7ugElf+dfj87q1xD9vzTie46npmtDJCh4hGZec1kbkysQiDd1e/WhoB0DydxbfR9QspW9gIDT+clA8YWQktwL5On2Le28eZOMBwxptZLyL0ZKSLcR3RfkAfjggmZ8/fvPjejG2uBptD7OooI+Bg4B7kfCBM9rpwB4r7g4ExIoVioSoLN3KHJZVtel11RkruaubeG7K9E9u1GUP8Dm+7FQFuKBh6A7+nkyK8jCO5r8ub62tW+pCbQnrkRComNInEsUAPDIiuswxDecPiHa1pVqzF9nN6Ar/fASCWDC/g++Dq+gwBwK+ab6CSKUf1ZRzyV2qO+euqDs8roSgWh320E7MwJ1TkMMzPGpdpfU2R1JUe8BfoQAuIcR8HkKMnm+DjHfc7o+bVFz7GZGTPG3dhlMafkBeC90M4GYstoa6XX6W/Z+2fcICFra/Z4egSH/xi75+GKzvPURQblEjfacg8DiW5D5+PzR81URwzoO2CB69hPEaP7U5RUx9iG44FcIhL4RgRX3I0B6wej9WOv1YVwgsgk0N1MDC9Toy2JuTfWyvfg2IuSnQIKv9ZHg6hUbo1HIVLJh492vRntWtjnZm3Yyuy2oJ8RFWM9+B8J7RuvHzqRdy8xl6/GUxLNDkJbEXi5vMdIukyoBnjb0KcTAOIosqG2RtvPvEahb6Q+7IxMCgpYi70u4lh/i1DopOCuusb1dW8t7PPrTAzFdN+CspNzaXpLMJdeGoc3RXKX8XFYFwJ6aDIC/gSi4sr2zObqThlFPY2cJ0kGkZkCaRsPJA/Ddrf/7Isbyf8DhLfRhcRu7EdTQLq8xF57BPBKdr29a+6a1/AUpAeCRZtDxSGhfJ87LBgio3rpgLcZm17sjGuABRGvUcmnTUQmdm5+ggIBemD4VUkr4n/V3obAGCsqJY2M8jd1DHXEGuL58fwck1p4/nz2AMB2iIf6Ks1Rsh7H1APyJZK6I6mjvn42Aj9iF4Ow2X8fZ78FI6y4G4AdQ30okBonXQAD8cGCXgjleCJ1HX1IP3DuRkhgMZAD8OOCE6Nne1udKgN/WwGd+DSBB0M3oLm9gwqREG3azfdo9te7K1qGNRQqA//7sR5YF31KPpu3u/3alegkFm3wa8YMvkQUhfsGdR7PaehyDfFavbGfC0USuGtupTcEH/Ok4q+x2KNefYYch5S/v2vApKlwburV5K+Jh/B4/CmkpN8jctzzIeFpD1ejXQGQt8CZyg9nLt7Xi2yB0DBbTHoAfjgQUm0ffTId4+BNs/+9fUv45iM7eirzg3Z8F3WkG4HN0e52+2LvHIWHE+0j40RSgu876iOc7yrsYAey/xCmNuOcegPd3eACtP43HNFHHorYvD6L1OCRTIYFZLWUSdN8+bnt5BzJt9rDWH0VWfd8rrlhfdnfrvbZwHClvfIhhCFXvt9j3U2y9bUBJbD3yAPxGiO892Prisa2JVjFrck2d3oCu9MNLSFrbp+ASCJouOQAeMfdHIm3lN6hg7u3AfIsSn1f23rTI1Gs4IsI/Rxqxj+BcThQdTkijYOHoUuqDmPrbXN4JCJB/FQXIehcBmn2j8upoO/VHWvVjgQPQJVkIvGOBaqK8mMHYwMrakQkMViE/qw0EDC5med2RBDwEtepr+V4408veeZwEUBXVsRp5jYX3bF5vQwTpLOiSXQqBmSkA3vvsL9NSHoiIuP2RwOc5W0/fIOL0eWTyvT8KVjhT9H0TYDYh5yaee5f/YxurrchL/y9FwN1NZNHbA/G6JhIC/QMRNSfVqP88BNx/bfU9QYuEV81+hrgIlWADzW4z9kOE7YYuv5vN9VDgJy20o10AePJM1e2ISTzGzUnOnY39DaaFpWusIxNiNp9E59dwLCifb3cr65gE00IGtjTNfdH6H88+zWXnS5NLAuTLfYzN2YN21mxU1JbUGCBi+w6kibtY9GwqOx/GIEZpZvdsHdtj/wD2qBpndCeNs7X/CwTi9SQLdjYDErx9jnNBg6xJzkTC7E2q6kms58XRfTCCFgD4aM0vGz0Lpswn+nVAdnYVAfD90R3xHeY2rMb8748Ej7NH+WvZ3D2L3Opt5Z7tggS2tVzadFSycRuGznZ/LoZx64XuiI+Af9acm4OsnyE2RnufAcl4OVTcAWSBD/35HMrcFZ31Q1ptT433PAD/i5p7M7jc+w4pi9yMNHaDssIh6F5dGNGgg8lcn6RcNxbVM0tRn8gA+M/IA/C9EFP/HKJx6ygtLGjt/ZSSGAwIBPs5Opc2iZ4tmio7eicEnB2UKHtxMmDu4MS3OyC65uct7qEYgP8MAfArRu/1RufDc1QIeBBvdCMZaNQFwNebiytsbx+EKeDY/jgFnWEfkmnvzoro4PcQfToSgVeV67mNbQsuaC4kwaeNR7n+bu2F+KH1kfJXqTAZ8dkhSPuxiK64EN2Jd1t7/4U0xOdF59JY2uiHvZXxJAMTXwe2wAD4im+utf2/VpQfFCM8HbBFQRn9itqL7vjXEX+Wij3Ri0zr2APwj9EGrWhbzx/ZPP1oPNbI93dn4llwzbklkXU5+fvgUITHvI3Oyq0RvTUKB1SXtCFYli3dxrXdI+5PxbczImxnKMJugjJGwAt2jctDZ/QB5AP8xmvgFFtnWyDrs96ItngauLGtc1TQh/mQkuJPa67/sGfeJKPvu4D3Tk6d3oCu9MNKSEO7YRfP7cindhzM9FR750qcTzykMX4lDmQuOjgQo/tnIt9hCGzdDgEFO5ExLgsg09rdkTZyHW23QdbO1xAA2cs9Wx4xsIdGeSGQVANp7dQOShrV3R+5AQng8tYF7+2OAl/1KynrIsQAjbGy/oMzw2uhTa2YAB6HGJLbyILQ9EaCidHI/5330T8zmR/rQg2EqI6f2hzciQiV/ZAfujFW9z+QhP5YdCF/Qxqsa+lyQi6Lprc+NhDD9AYiMsZam+5Gl3VSY7kz5sb2wAPWvi1pBuA/QlYETWsJCbGS6HyZuAABAABJREFUfqcT/Rlmc7mS7cEvqOnntoX+Br9+Ta6cEChR5I5oDmSGPhI4uuCdpC/vivZ4AH6tNqypi5Eg0RObf6IEgLffx9han6Cuplrox4UIED0cEerBiueatq5nMiArEMu1glG3c78WtHHe3X77eTrJzoBeSJsuMLC1gmqiMzyc8x9YPb9DZ9qsZMD4fojpuTHai6vj3EEVrT10bn1MFpR0KALvPkJ3yLZIc7YHAuDfBX7rvu+PMz8vOQMGkhYIL4EA+M+p51/dr4GDEYgS7pJSU2bSAPzGCOgLmkGlZ1JU/1nAV+53byRwH47u+3fQvfYuLngn0qqtFPLXfd4O6zjE+vhNWZ1kblO+Z1gpuMvIXHSFYMEXMoHPAPu/6g4Y6H7H53OIQXNsqj6X1wuZ2E8Xt6VG+0Obe1R9i0Cb/RHTPdrW1iPW3l8hDc1lkWZoOIP6orNjNKJ16jDq5yJlhCVcXpEG/IfkBW0n2T5Yp6o/7vkG1o9hlLuAmhdpi96JgNNaQXwRiNQgH8Aw7s+iZD7gD3H5O9m6PLGoXXXm1/7fD9FxD2BKHshaYQiiNUq1NxGN2rAyLqULgK87BwF43dCNWQBCe9ocv237yAut+6KzaQ0cf1p3b7fYxotICH7aodwqtyWp8yy4J/VWsreis7CBhPKHk6cnpkQKRg+2uD8Oow0a/4h+eA3RQfPUmP8RVLgLolgQH58zqTHbB93vsdByEKJD7ke0+vKhDFtXHyM6q3bQUHTuf4QEKZXneZ25j/uE7pIXEG3SpLiIaKS+7veuSLAYLCv+7c+zsj2DBMYjyHjNQmUU8vEAW1lnPcgHTZ0eCY+GoftnFcSbX1Q0TuQB/xh4nx3RDi+TuTJ9AylbPmJ7o92sQpDr4W9oIX4fWdyEBi6Ye9ncdKUJmzq9AV3ph5MQsBWCTL5lh/R3dvj+GoEJ09u7h9h7l5K/6P0hmjqouyPG9zng99GzQ8kiW4f0ZxJaQWV1uGdTI4bncTu8n7aLa2ok9TwPgcixifBq8QXVxvGcgcxS4Gjy/ky7kfmRLdTaIdMQHUKmvf0hAqlrE0bkL/NVKDZD94zmz5BW7m2Y5BsxVtciQHY4AqpuQYTdx1Qzw9sAc0d1DEOBh2a3eZkbMYr3IaDnSxuDsCZmL5t3t5ZXQSbDi5EnRoI55JzoMt7V1sTsiNg/ETHDR1TU0aFzY8/ntXEZThqA/xAxqn0tP0WcFTHCB6D9tyWZ1klfpBV66Pjshaiew2wet0z0P4D/S8djhDR47kbMWBOBUrUmarRrMUT0DSWysqj4Lvh4X91+e0KwEIC39XcXcHl7tL8d5mU3xGxsTsYA90f7+xVqaudH8/kzJMgNc3QVEmqunXj3BFoMBN1C36ZGxPc9bvw9+NLb/b+37a9aAYmBFZHW+7soiOFgdL+NROfDE8ilyob2bKyt85TrmCJAPLR5epuL120frYrusX/bGhyO9v/pCAgbBtzSwjhdjYDXx5GG4Zp+rBAA/weaBXJlvjWDVnWIv7CIjc+BlFjU0Kz59l8k4K9lkkselFnHyvg30mQOpv73IwZvSqQR9SlOyzsqr6ieg8gHupxgDBM6oy6ztp9WVie6A78kcs2VmBsfG2OCnwGW15Y7IJzPAWg6oaL/R6HzdTiiT35cp+0le6+K5uiNwPQ3bK32Rfv9bkRHn2b9eolMo29qdN7sW7MtYdx+TTkAv47V82fyWqF94n7VmL8NgH+SAOCj935n+6sW6IS0/Mais+Qh8tYvMeAUXNA0bM2uh+7Vk8Zn30Vr8scINPwauTh4BtECVTTtmrZnbrMx+AhZUnYB8OVjfzIF7oTcnpvC9scYRG/3LFq3BXOzMqLL92ACuvbrwHp2RcK6gTTzDWuTAIqRYtSTmOZ72b5332xoc1MrzkHi+3lxljcF71xpe3/NMNfu2VXAdfZ/LIh/kYpYclE9xyDedBH7PTXiL7+0Pr6DzufhwCB7pwfiHfdooZ65EV1xJO0HvO+DhOE+b2tEVy4TfbcJsux+C/Gv/tyaFrlWXBhHd1JM04T9NwSd0etWrR1El/yixb4egujUd9CZGeqZHtEMX9p6v9atg1aA/YG2NwMtubjN6ymIVn/D1sBP22vfIhrqC2S9XzW+82EeJJB7Y+/irQt478TU6Q3oSj+shMDpW5FGyUaIiD8GSeW+svR3xJw9ZBfWZUSm9jXqOQNJYX+Cgj/dZofg83bgL0nGaB8ynn2axi7El63956LALgPsojrW3utOBjL0c9+3+RC0S+RCxOAeg2keIhOwMeQZyJjhuBgJPpYn797lABuXJeq0j/zFfah9W2gOR95CILjF8AB8T5v/KxBI8wICNLYsGzOk8fk5Isw8oXW0XVa3uzrC5bQ8ElLca/NXx1TuFKSFNc7WcQP5Fd7NvdMTmbi9jwMx3PNSJrWj5qag7joA/K+o4dvdlTktInAuoNnV0v0IxHgMgYxrUOLHrqKe3mjPD7M59f4Xz6cgqBoKQvMQAoFK19n4JAQuvkLNQKBkmjuDSvZQCoDvYePweqq/HZ3QGfkbm5NYSLAZYk5WqFFODOx9i2mNIZPPBglhg627UfE4tlPfulu6GhHye5MR8jFoPCU68+6ihUBr6N78I2KKdrO8gQhwu8vW9dcIEHuXzHKsMhAa2Z0UhIYzWRlv4SyqkEbwkegODTEeQiq1xiFz2RTe/9jW9SgEeJ6PNFD7IG3+3yFgyoPgTcwRkVa15W2MBBOVVmXkfb9+YW07Mh6bxHffu+iy31MhBut5m4fXUVDI+aIx/g26E6alHkgR3BI8wwRknMi7/ZibDIA/I1Wn689rwFUFaz3WeJ/gZ4DltekOsOdLonuoNPgvAiHetXH6BQKFP6UiAHRZXwqer4pogGCh2RMx38OszgCyBwvHt5DLjGVcGa2a5u9tc38b5QD8QejeqR3wr2QemwB4t8a6ofv5TuQiphJsRmffCDJL16FIC3GdVP32exFE14Qz6qT22G/RvlkNnaH3orN7s7I60L2yH9pngea7kS4AvnRdIcWk3yF+7Dw/ngXr734k4OjbQj2no3P5cxQfZKHxbXdH1FNQR7gH90J0/yz2O+VGxfMj3dFdONSv5Rr1zYLO4TYJLKvGzfZ9w/Z8HHPrPFsXXtAX+r+APfuQCq169+26CED+GwL1H7W67wXWd++8hsDzlCVenXN5dXTX1XY1kzjjYmvBBpmlVLiLD0T004qIHpsOeQoYhejbR8kC0Z5St27LO4K8O9e5EE17s8tLnYPzIeXGWkJk++ZKdEf/Cd0dYxHOFGIuzYiUIxtIiD1lUbsLyj/e1lcDczeZGO85kPVVwGemqdv+knq3tDqDa6gyy4KTSMRGLPumK3VM6vQGdKUfXkLa4vciZndjy5segX5BYvgNYmADIbxGRZnnAie73wsh4it8PxxpPsYubj4Drh+PvoRLu4ddENfYBfke0p4J/vCW8e+779vDxUbwAT8OaWMNtjac5N6JGeONELP7mMsLIOvcSEN5FXTx9om+nSLVfjJGeO/o/QttXA5GwM6U0fMTEMHzOyIfeAjwLazf5YWgausWtPNoxIz9Ma4j9J282WkR6HI5Ao6OQhLvFRCoHbQbjo3e/y1i5nuQIPxT899Rc4MRAvGatDwPwG9B3lT3Isu/gxY0MJBmyRJR3qWIgf81Ai9fQZqxq8d9qFF+YNanRYFUhwP3W965iNjfOPFdmIvpcO5ZCtbZLkTEfKuJmi5gbM98RjqS/QzR7wDAH43O0i0RAV1qXdGRCTF22yfyV0RnZJPLp9Q8ufXsgb1pEcN9jY2DB+MuQOdL09y3sR8rI82ttaL8GRD49TbSIAtgtg/etBs6p2oJX6LyV7B5/ppIYAwsjUCme5DmVs7VQkW5TXsYabO9hZjQncgz3D2RlvCBiKnZp4U+rI7u9oeRlu3W1uaPbT5fRWfrSUijdxjOCiUqK9aqDgDlPoi26Fe1lhDgNof9vyB5EL+MqVkNATbfAdu4+Z3F5mK6xDfTI9qmlqUAEkC/RWaN87zfP2Xta3FdXY+Y0rld3tzobG4Ap7t8f4etYPO2TaLM9ezbvaL8CXYGRO+1dAf4/pEPMJu6Aw60eVmfDPxcEd3Lv4zb2UJfYguCk9F9eC95N4g9yfzRv0wmyJjN1nMy9k+N9njaYV8qAHgkMPkG56KiDXWmAPih5AXg3n/9TjXK/IW1fW2Xtz31APjFkXLQfmVrYHz6mSqzrA6kseiDtfYlDcB3ASoahzAecyOa8gucP3Iif+j2d387K2rFVELA3lDbJ8m4A3XmI1r/KSvSCV4PeUWOfRF9MlONMudCQs6RJAC+im9nQPx9S5rMdfrn8gYjnufXZEF1z6MgPhoZL78oEQ9bo/4hiOf/EtEwexCB98ii7w3a6NsfxVkZE5ebGgdEn82Zemb/H4Tu20A7ze2e9UeCgjcQj/cCOk//RKY5vgTia1+O6ylpW3DN+Jqbj+4I82kApxb0pTsSCL8MrFazrqttHa9HxufuSGbVFZQUZ0LChGH2vNbcICHLR8gF03Lxd+TPGK8geRQtAvAIVxrofg9AQoW/YZhFwfqfG9GMh7XHHutK7Zs6vQFdafJPiHiOL/xlEdM9kkSQE2SivTMCAA+tKH9GBKrGvh2nRgT9djgfuPZsCqSJ9z9aJBwS9ceE9c7IDLmBwIkPrB+ztrXMGu/3R4RFEDaUms0j4ufniLD7I3nGa1MrYygiVB5B2jdxoL9Yiv49EOLyt3Rt+sIuxL/ZZbqie29/soCoS7UyDsiCYQQVPp7t4hth/V3S5dcSiCBC810EjveKnq1q67lBHvg7A13stQOKdsTcIO3bN8KajMfA8gIAP4y8tnwvBNjU1lpJjSnamw0EwAVwfyAiym9vcf0fjswig/nfNAigGGFj9RWmhZL4dltgvRp1/ApprY4X+F5nbSPibnRoV7QGrkCE6JQ0+4AfhQQ+sfCtU13OWBuSga8RYPkFUdwK8q5aCtczEto9i4ChecgC6A1GQEwh4EaLgIWV967VPxIxJ75tSyAmbBhwNjqXuyGN2qOsLVW+xBdEmlJbI4Cvr3u2ArpTvsAFgfP9QcT+sjX6sgvS3H0JAcmX2f4LjEkA4N9Dd1rqjPBu4IoEllPYGATmNmiKPURmiTQNAs2vQSDI++Q165eOyjyUvPDlF2TA517krYPK3GydiDSYYvqkDqCxAgJGG/Hajdc7AkyHUFM72sbjMnRGz2nr5x3aGYC38f6ctF/0eUkA8PZsKhu7f1KgiYmZ+xeNSZQ/XmeA5S2PBGNTuja2cgesG+Wl9uZsyG/3ZURWJUgo/R41hKtUCBHILMwOxrmnIgMkggb8Rwjs6Zfad21YD5UAfJgXpLn9NC3QtTXGYn0kmGsg//GHI2uFr6hhlWhlzAmsmsivC8CXCl/K2t/eKdG2QN9MSxqA74u0d9steOeklJCG7iFunAaSubG8wL0X0/ynInd1lW6vEO0c/G57+ivUOYCMri4Tqvh1v7ulHh1ZDzrDLyGzoDnA9lqpVR4SDN6H+GfPc1fGLCE7w65Dls094/moKMP3p3S+0J07zuq6DtFfSZeP6GyfpqiuGm0ZYOstVi7rZvvyDkSb927lzCBT3gi832Z+HRR8cyK621OxUGL6eX8rdzX3zpIIlH4XufDbjmYw/1zbM7UsOJEC2oaId3kF46OQq5o/WBvOQ4B4aPdsyHPBKOorkwQwP1gl+jvt90hI3t/lzWh9/RDRxKVnJ6IXP0L8a10XaB6fOaVs7qLvjkB4ydXkFcMuRDT0Bdh9RbNFyj60ILDoSh2bOr0BXWnyTeiSvwSZzP0DAZEbuudLo0AdI4FNa5RXRmAsROZGpkhTzhMw3RGY+iE1gLea/fWH/NwIFB1ubRpLDXMxFKSzlvZF4tsZ7IA/tGjMEJMZNP2COdmnwB2WtwCS3t+HmJ8r7QBvIEDvWbusCv26RvXNQ+az+hIEktxj4/Elkp4fjximEMTvFiI/+SV9Du5ZVrbfvl0XEmnlkQHwTVr2Ner6FXJd07dgzn+EiMn3XXvWQNoKq9cov8PmBhH27yOXD2UA/MJW7rMUm+y2iflEQrkmn4+IEHuO+oTNzIi5egUBezEA/wrSBu6X+HY7G79jK+oIlhXtclZU1DUDGYC7Pnmi6nzrazIoFFkwz0kmqA4C3kaTd6sxGPkTjgGuQ2w/BcbhGsQA+CDc86C7YJyNRXLOEGN2BwWAYMEa+Ay5DdgEgR/jiHx4IwbsMduT3yLQ9GOkQeQFcymh6Bm2Vr8hC7L8HPJrHZhWD8Af4r5tJf7CpUib+kEkzPknOls+QszZ7G5vvWXrcScypqgyEFnFWK6H7oB/EVm1ISZ2HWvXUzRr+a+KBNreiudx4M/2/2zWj7+456mzbX6k8b1fi233Z9+KZAD8FqkxR2foATa+tQBE+24L8vTSKqQ14Nt6/gaXVoXa5raXUhrwu6LzsElDMDXWNdrS5jPA8k6yffMH8lp8AYAf7zvA3p3exm1jlxf2xEHofJilooyUBqIH3o/BgpmSFz7E6yr4gP8Q0QF9Lb+2oL9G+wIA/8ewTmyuBiO6/YDxqaugzuUQnTjUxvMh8nu9VYGpp9EKAfh4H6X2FRJC/hzRlmvSoquCdhqrIMT0APyl6Kw+FN0zlS63Jrdk+3IUmTuGcF8OJAPgL0yMY4hFdllqHUR1zGVr53jyriMDzbmk7ceHyO7Q1D0fnwEN8mffBK/H+vow4lHPQsD4YHQnzODe8fsnjNnNSIPYB1wu48/nJwo6iXix4bSgCRz156fWhtJglkgLfSwuLkyirN2QS5iWrXgKzglPs/dA5/Rn1LDccd/tTd7qaEp0h/2b7M5J0TVzIfqzCQdBtN130TisYe8PJQJq0ZmSsozsi1zI5WJ+VI2RjcUGSPv9VTIAfnHgBpunlxAGcD4Cnt/HKUimxts/Q3t9mJURrMLCOX2rjV9sOTyDzf8YSpSrbGwfRfR4S65REQB/NTVj/aHz6D2EcYS4FX4vhiC3vyRvGTcH4m1qCyy6UsenTm9AV5o8kzs4/moH3j0IUPguOkiXoQCAJ2/iWqSN7C/Qhe0Ab5D32xprOcyKtONGAUe3c79jAn4hBPBU+iojY4ZrBeIrKMMTajGz9iu78OZ149oXgbzDESE30g57r/0zIwIZzov7gYCoMTSbl/tLYoCtgRGI+ZnS5mpvBP58YvXej8Cqb9ClXqpBZmU1bM6nj56da882TrTnCJv7+6kZaR4xOh/gfOAWvLeZ1bu//V7cfleZ03fY3ITxQITYu4joSALwaA8egICWoEk63sB7yThMjwDk81opH5mKvooC0a1HxqRMh8CX4Uhj0WsP7Gjjc3xF2RcibaDSOWzncVgAASqvkmm/B7cJKZNZD8B7wG6iBt6tjXPYng9M4fb2+5zovaD58xP7fYWty5TW7vxIK+R7f4zR81BHLbNnJED8GAUdC6bqfZEFyFtk5p9h3U1t7x6NfLZuhbNOSc0LujOHIaHtorYGNrM1PRqdEeFsWJ4MgG8pcDc6Uz5G4F5gTqZCrlSCy7efYabnSBPpTevnrtQEV5HblJORsPAqdN70cWMUAPhHKfDFjzN/J2M4p8fcMLi8U2y/9CXTGv/W9sz32sKurKAZ9B9glRp9mT36XQTAB3/V3ayv+yDg91VKhOIVdXurgZVIa8BPTcLVTcV6HmprNKZZ9sFpB5J3QXMaYp6/pcKCo8U12aYzwPKClvhRJGgndHeP1x0QlTdb9Dusr/URjbNAajxI+0z3GohBQ/JeW889o/dnQL6MVyaLJdAHATvvIi3U/nX7UdHHOFDoZ+jMeBgJuj5pz/lPlYGAn5mocAVn+Wcigeu8ZO6nvM94P44egK99pyMN8+GIDvzW/j+ahA/nFvvZFgsFD8D/EgFUT9h6Or3V8ib1hHin4RRYvyIhYgqA74V4wf/hFBpK6gnKNE3rBt3JI9FZ/w66n4MyTZJmJiF86+B6eiBt4OHobD8DCW9WsfNmDkwjHJ1NM6JzqS9Ow7ts/6NzuYHO6N8joH9NBPS/TuZispX4VQdambVc3iHFgbEIkF3I5U+B4qN9A5xVp+4W1+VCNva1LXfsu0GI5nsIU8aztXqE9eP3ZPeOV4rqbuv5tXgvoHviewFENJ4rIQWM4SQ0pcnzF72QhvjnwJAafYl5Sg/Av0YGwM+KNOPvQfTNqwiA39R9WybgCXRld/vuQyQgCPELlkfn9v4F388EbFvRl8J9WXPd1gLsEc/wAaLRp3H5MabzO4RlfIoEUbcievo98nFrOt3yuStFc9zZDehKk18ic7WxUXRwrI2A6AYuCCUZAP85NQgg991UNGtFLUoagA+E+IEoyMZbqeeJOmppRRZ8G+qcqkY9AXgvdZ3SQt0xgR/8R68bv4MIqbMQAf8umY+0Hr7N5C/gbkgK/Co1tJ8QAP97uyhiAnBeRDD8EoE834PXNcr9nV2oJ2ASeAS6fY0DIeOxR8xtK76Ke1pfbyFhJkleUPQ80sDriaTdVfEKOnRu3DdTIE2pKgB+S0ScLlHWj/Fdp4io28P6ukXVd26MvP/mN2gG4IMGfABfZkBWBmOoCKqGrDUa6MyoNEmu08+Sd2YnDxAugJiTF23vfEWxFvdCGANW1p+JMdn8fI4skbZBAtoTE+t1NTJBRPDr602eY5BlPnSuNoADXX4IRu3rKGMeg2bshS4vuEnaGIFStYOgpepCmlfvoDsz3n8zo3NuNHCRy18OaaR+Q00hMrofn0WmxrkzxP7vjwK4fkEegJ0RMQNfUcPtEhIS/s/W7l/IAnQ9hgQRU9l7HoBfw32f1KwvmicE9DcwAYeN2UPW3hvI+7WdHZ0ztTSD0F3xCC6IZdwWBMDfZ2t3bcsLzPIp5P1Pt2lfun3gAfitkQb0kej+7FujnJ/gfKxG/bjQ5mP56Ju5bU6DG6CTxrc/UfktnwH2O1hwbUyBixr7HYSwn9HiHdBCH9a3sVvA5e1OWgMx53PX5Q+wNh4W5Q8hC+QXgKwQOK63PR+NC/pe0s4ATle5VPDnwtq2jh9Emt9btTJmrY4rCRCxqL22JsK4vI3OypXJ36VTRP3ZHp1nj1HghiKqI7g23BLRqwOQRe8ntGCpGvVrVwr8eNcsK+yJOdCZ3gAOL9oDk2sis0hrCvptc+VdGuZc0Nh8tuLSYjf7frZoDqZBQrNrEV96uq3F+8gHfK501Tmh60E0gAfOeyCL3jeRoLiBzpKGS9+hs/JbnEuPGuP1cyS82w+dH39DZ9enruwT4jVdsW9Cf1qKm0PmguZWjF5DtF1tWrDF+s5EvMh/aIPgHQn23rQxW9TyZkD0zLdIeWxWMq3ugWRKhd7ytZulI3HWFYlxXYUSAN7eWQrRNF+Qd22bomm3I3NhWAbAv0LCbzzNrl3LgPdT0HkaxqI7omU+RAoyayNa8Io681yyDndBFoyV1iaIzmxy+1Oj7gXJaPR4DHojIYGnMXZC58Hj6E46lYRlXleauFKnN6ArTV4JgUDPIXPV70E+93xRu/wa5E1tl0RMUQNnNlxQx0ZISv+CpUvJB2hajDQAH9wR/B7nW7TkoN0ZgbrL1+l7jbEpYh6uRYxnSsuhFW02f5FOUVR+9F7wFdkPgbyfAn90z8v8yvWkGfBbDGlrHmAX3oLu2ezIf+goRAjFgpPuSKtx1VSf4rrd/79HjOyhSOPxa5w5ZPRdE4BaUkc/P5aIQH2DkkCllv8PpLlfqeHUkXOTagvNAHxM7E9ldT9JpP3Zngnt/31t7pJuo6L3k6aqVAPwQxEoGBPcqbkJ/pAvRczI1VS4FChok5/TH5Nwb2D75Q+IWfF+MRcgC6B5PAlijgxUWnlCzc+ETIigfMf2zCjygbNT8xJcyryP3JKs5Z7Fe877gD8AAXstAW4IyPktea2hsK52RwDMs8iFytUIiC01hU7UcRECtvpH+UHDcWakdfopeVB8Ofuu0rLK3t/UxrjQBZqN2X9sbL1W1czU03QKLiO2JDtP5kL36f+QVs6uZEGk10Hn98MUaMAn6gj7I+yHhYnOfaSxdztiVF9H4PSVCJRvxZT5eMRs3k45AL8a8oH9aJh/tJcLQeE27BUPwL+NaK0biRQaKsrYBAkTPsZpeiGh9ZcUx0eY39Z3m12AlLSppTPA8qdHNOMJRH50kRBpcSwwueW1fAe02Ie1bR6CJl8Q2p0dvTeYRDBat8feRzTy4khbL7jte8/6ehoCZT4DFrfvelFDAIgsQX7ZQp/i8zQGUYrmZlm0r5cmsxRq2R1RzTYubPvgP+gsHI72/G1EwgjydGOweqjSdrwACThXjPJnt/w9o/w6VrrBBUhTsOIW+94XuWEahxPYtNe+nNgTcI6N44/iNYYs4+6ysyB2QRMUMUZTgxZw3wfN19jKtAfifad2eb9DZ1pT8FKkBJZyBzlB60EA7DMIwO9BJpjoQeZ3+1kEcO+ChKH7oNgLhyFeYZeac3O1lbe8y+uFzuEfIQHD72l2k1gIVFLi4rRmm4bY9zcjtzVxbKRYs/hqWlDSir7dHQHAaxWVn/jmKPL03ZE2t38jO+tnQmfSF+gOfwBpPT+JlAqPdt+nhJi7o7Nv6sRYr4oEkjkA3tbHPog+eB6n1JXqE6KzxyEcJihapAD4Da3NT5PRukmLpZIx62dt/tLqjQH4jxB9+as6c1BQRxi7VdG+rFQORPTmjW2oay2rY+Uof0tk/foeomHOIS9E60OkWd+Wvnaljkmd3oCuNHklRHB/Q8SkRu/8CBHKT+PALESwb1FR/pmIOHgOmRT9BUk0h+NcCFAMwE9PPthGEbH1C8SwP854uIGpMV6XIUBl5cTldCoC4yp9X5O/ZAcjTbBuCDgcbpdGTFgcae8FIKkvmZ/x37kLp67rjzA3wQyqgYiDg9w7syGmaCQihDwwEWs7VhEqXts7EI7fADsUvL8DcBMwoEZfjkNg2kCXtxki1n5X0uZZEWhVGcS3I+emoP4YgA/alPNa/oxIk2IkTnO4pLxaLnwS3y2IiKc3qcFAIoJqqO2PnRHR4ZmuRcm0eNYjYzCmQYTnUPLAW4p4vAWBG2siYOcApP1zDS0A8OT35cG2RneJ3rkEAWnXkTb5nJ8sSNEGbk0Ek9lRVLhD6og0HvM/IzrDY032IoHIZwiU2snG5BnymsUpAD4AWLU0rezZIPf/4ujcamAMMbqvviSzTHgeMUTfIa3Ki6mnidzHvr2p4HnYp/NZfedGz5uY7pIyggupmX1+/C4C+UZj9zg1A5IiwcN/0R0UmCm/BxYj03by/kzXsrF9ngohH2JQf4bAbi/cfRbTbHJ7pB86I25HNMPLiGnZrM4acO8cijRf76QcgD8ECQEGtvf+CnWRnf3rWF0xjVOHYV0bAfCfWDmnonO+SWgd9a/UBQgdcAa4Z3Pbfjg4yt+dTJEjaEMva8+mo+Yd0IY+LI3oj3A2jSF/1nRDd8kROBoFud/zruR2Q3TGSLLYOJeRD3q+i/WtidYp6gty93c3FguBCQeGn42E+Q10Vt9IpgFZm15p8d2TbMyWR2f1aegsbiDgal8Sbgwp8fFs87WIlfEyeYuLXrZmX0JA1vIIzIo1FZvoNKIAu23dM/btwugs9fEYfhCAC7rX30R3bUxTnWf7x8fGCXMxFwLGGuRdM6TOs3hvzorAvIcxOrmgbVMjuu4adL/7+T/G6t6zI+shcwV7KnnaJtzTQQP+Q6RJXOqLvWydURBPJP4G0ba/osBSPXr3ABLWQm1YN8H9SgOnCJNo2zXoDBk0HnV5i7sqS6MbEG22tG8LaQB+WmB1pEzwIALeT8QFFC8YwxCMtIHwl7uQQoZ3ibgU4sdG4FwCWf5hODd9RWvA1uU1tt6upxiA740UkkZSw2qrZOzmtr58jizaPAB/PqJzfo/dAXE7SsrdlzxGNQs6b/5O+b6cHQm4aruzc98G93X72DjOhvCocTZOdyFFuQZw8fjsha7UeanTG9CVJq+ECNGxVACciJltUBBYs+DiuBqBubuRB0UXRdrGo4BLXf4iZAB8ZTAt993FiDnbiYQ5VAvlVF22g2ysHk88O9+erdNKPWS+8LZHwGkDuK6g/AYG9pGBM32RKeNXwP0t9PVSG7N9kTbmzAiAedDquZBMY3xOpEk6ChFCdf2gbYkAzGOs/JhYusnqOo5mH/DBP/xJNes6FxGhfwprDTFb1yCm+peJb3rY2vyAClPmjpybinZ4AH5fpDX+NTJp/CdyH+UJ1CKtrusRw9tSEBr7tg8Cgyo1RBBIFwCnV20s3kJMw8Zk5pkLI1D0FVzQUhvDhcrqQYz00+QJ2T6Iaa4NwNPMcKfcDPwcnWlbkAe2YiI1uKB5FQHwPWmDFveESuMz//b9z8i7hknNyxnozPCB8nahHgAftHYPKqvDPbvW1oAPZLQEGQB/BmLMriYDsnsjQOBIpMF7SI1+T4GAnH8B91pek0WLzfcUCFT8e/hdtN5K6lvH2r97UXvs75L23vpVZUbf74HOjKZAyu6d1Wzsfhnlb0CF/3oE3r+K7poGYlKeQu7sngV+H8YiHkcb5ymjvCoBr2eCf0oCgCcPiG+IQMA2u5OoOc79EHPWIB90t6o//kxaBwHwX6OzacX4Hfu9PXBV1RqjA86A6P0FbR1cZ3tzCQRGNNAdfBrSEHwH3eVhn05HxR3QxvYvhe6jcxCTfFLBOvKAzDLW3ofJ4i9MgWjDK5BFzFLAtL4cpNE/iihOUo02Ho0A8b4TaF0GreJjEb12BxLiXUMLYH+0TpM0eLTvZkOA/1/J7vqlEA36lY3Va4g+Wyaup2wNIDdZ7yMew2ulrkreNccb6GxYh7xgsVBztx32zLQYINeea3lSSbZPHke00S6WF4D3VGycMN8LkqcjUvRG0960/F0Q3XUVLv6D25vdyeIwNFlVIBr+oI6sB8Ve+RgpEE3r3ukejUsPW8OfINp0Ov9ezTn5ufVnzZJ3/J5YiIxPP6bg/d3ICxKup0W3M1F5gymhBakRjLyd13E4N5NrEikcBAB+scT3dS2Sfo7uzDcRLXk/GR11G1IemAMpLd2JKQYWzFsRLxjW1FSIPv6IBADv1lw3q2e8FIgQAP9n0gD8hWQ+4Gfw7Sgpbykbm0fJxx7amep9uRe6D5JuQhN1rURmaT81omU/RSD7a4jv/C3mmhG5Pbsa3a1LdcQa7Urtmzq9AV1p8khkmmYhINau9ju+1MLBuwwikDaz31VA9eV2GK1FFEnc/g5EWvBfk/evtiAyMWsgTcWqenZAYN4WVPh7Lzu8o0tqY6KI4Ej7fwrEcI4GbnfPLqQgsGJFPQHg2xNdoAOQL8C3yQOoFyKGZKNUWYixvwhnXl7Rhp1szDalGfBYyOprYD5mLX9OZFo9Fml9VDHaQSAStONeIPP/nHJBczyZlDuYF58Q97WizhMR0/VnYB7Lm4vMBcWjiMGcE1kuHGlrulTrvSPnpub8eTO/pRHRfh9iYraI30t8H4iAtdupPWUAzyyIsX8backuZePxks3xF4jAOgCZ7n6C3ExsTIFWWpQXBB4zxv1FAPyB1ADgKWG4Xf7KiLDalcRZggtOab8XREzmfxARXWoy21GpPeafvPlk0TpbgMj03/J3ph4A36/OWJFpPK2dmMslbX19AzxWVB4VwciIXKvZfI4k02wqGoPfIaFApTWUvb+br8vW0MeIiSv03Y6Y9NE4YKeinnCGnI2Yjh4490nRu1MhwPRjdJ52T4xf6ruZkGZ9d3RWrWJzfytiJL9B5/IQ365UWS2uzSIAftnovT7o7Pw3Fj9jQiTr+7qIRjilak0n9oFfz+vaWhiBc8Xnnof4CCdUtKmjzoCj0XkZ7sPDbc5D0PavrS0rum/2tnd2rhqb8ZyX5aihURl9M7Xt0aHonspZZZIAh5EQ6Xh05lXuT/Ig9VY2RvO0Zd1V/L4CCd4GkbmamRIB8K+TKV9U0eB+fR6J6H4PcswTv4vOhGsQyO5j5+yF7t5fI/A8WEcuVtYOpI3pQe2t0Hn1L0S7L2Tj+DskBNsTKWp86NbA0tG8xS5AOoxumtxSNK6DkAD2ZaRt+hUFyi82d7FrtzLt3bA3HyQTjvVH5/xYZCHpY5UMtPUwihrWrx1RD1I8eA7RxCmB9MxIiBOsU3ranv0QCRJbDeQd1v+hLXxXyqcji/VtXR1jqKGY1upast9XoPtkUKodLZRb12I8BHJucj0avec14BcJba9TD/kz9WRknXgP4l2XRQpt/0FWVkMR6Hub7aWPca5gWxzboAEfA/Cer5kD0Yy1XCe671I809wUA/AXIEHVH6jhFhLRqTtZ2/+OAfDRvrwVJ2RCfP1P0Lle6T7VvgmCpQPIMIu+CMt4HOEMGxPxmzZnX1Oigd+VJt7U6Q3oSpN2QprIc7nffewQf4wMGE8dkhtQ4XvWvXsq0WUeXSaB8Z8HgcBPkPeJtwj1JZDnICZouih/WeQm5SLEgBf6/aYZeGuQl2hfbwf6tHaQH4MAvVsRePEVziw+Krt/QT0HY4Q9Ik7+aPkLIYL0PUT8n2MHdlJjikzTobafWmTO+BAFJunoQrzBxmEjlz8HuihL/aeRBVTaGRHP26DL+nmyy9Vf5gGAP9bGoxKkjMbSuzA5hQyAD+5YZkdCkxCcqGFj+izOBL6gng6dmxb2cdUcFzEoQUNkUHvUH/91z2cl2+cz2Z4Zg/nxs/zNEYH6IiIiP0HnQQMxZ3NVtCFYR3ifiW0G4O39gykwlUWaTcNojpuwLhJ8PGX7ajM39wvY2i81mU6M3wQB5ifA/E/hf9v/29h8x+4+/BlTC4CvWuvU0HhCd0FgFH8SyoRmH5UF9Z+EzgrPTG+AmJ5/klnadI/GYWakqfzzmmMaNOr+SP6ODu6Pzo/ywxz0QoLHf9Ki5Rc6bxvAChXzvC26r2oFqrX5fwTdA4ek1jOyWMnNS9V8t9CvGIAfjrRsB1nerIg+qOui6wJqBHos+X4xWgiqRSJAuPt/XTIXNNu49bwTzXdnaj1P8DPAfk+Hzt23kT/18P4uSJhzna2BvlE56yFas9KKY3zmBQFE91IzuJ5r/1RIoPApEQCfWHt9EbM+khqWNYk6Z0KCxf3aMjf2/zbA0tHzIbbvLnJ5IWbN5gj0GFBUZkE9ByOg3PsXPhO5WBjk8gKfMQ8CXa6338G9xPFklgM7U+GzGtHnYxDf4NuzFaLbn7f1dAkGJrl3ZrG53DXKD3xAcDXTLnsmsZYmawAe3U1TJfIHIXppDHCey/d7Z0d0x9a2FrG9ubvtzb+TAeOzIm3kb9Bd8CAS8DyBtIpLXah0ZD3I0uxbmoXFWyFFohG2Py/CLDaQ8PxudN6uUnOsrrE27ox4wgZR4OiK75N8Onnerl33TaKun1q7T048Owfxg31qlBOfY0MK3gtBzJueo1hbG0VlBQD+PmpY10Xf+r1wOpll9wDL64sENScjHnqkzX8D2KOinmWQNcEV6Fxch0xhbRqbtxwAb896IeH4x3XnFIc5UQ7Aj8DtdURPX4KA8Q1r1jUlOjeGoX0ZYvnMYnMx2tb835Gw4nFEnyT97pfU8UfEs+7v6uhhKUXrBndTjzABY7F1pQmXOr0BXWnSTUjzbCQCEua0vB5I8jcW+EPBd73sgH+MkqCQ7v097CC9n3wQkCbAFBG+DYqjdZcxQ73sUnsoKvsIBJB6E9NnSWgE0HzpjiEfWDYAyR6M7480uj7BAfXxxUIWLGx28gDx9xo1iAAaiSwEvInlPVbvd678GLDbFmnyTF82Tn4sbcxeBK4sG19kovs5Isr8GDUR0tF3V9p3Hqjqjhi6UeTNgD0o/Rs3Vz4qe9n8z4Q0y2PXBAGA/wsZAN8HXZqbISBgJZwEOlVPR85N3TVftH6poVFhc5MzlXTPasdJiNbDwMTz4xDgvCQZoDKD7ZmxwJ+i9/sjAuwUsuDOR9doxyJkvkAL/QHb3B9AZnqY1HJF2nANCnxUIsDia2Al1+7ge7mBtPk/QcK4Xdx3C5L3GVy055Lrub1SR8w/8nX4BgK1mgJfk2cogg/4Z2mDNiHSRByK05x0z3YnHwh6CTILmJ+0WM/eNm73k9eaORudad9b2rhnvdD5/zEVcVHcN73tmy+Qts/c7tmF1vYbyN+pM9g3X+FArxb6tgYCCq4lEdzavTfY1nkluG/r7EMkEFiBvGC9W7QGliQKjtuO693Xc4Ctyy8RIPKUrZ06LrqCdmCSRhmfdkX5ZwN3uN9lAPw6iIH8FIGr61HDpVVHnAH+ORLYv4OEqtuT3QdTFJTVG9GaL5Iw12/veSHvpqpoXqZN5E1NCQBv7+yIhLIf1VxnRyJhwiZIw3FKdK+/BpzVxrk5BAF5m0bvDELCqE8xqzw3N3sj+v0J69v5yC9735J6vlcmcXlbkblIuJu8m7oeNtdXI6AkgH+FvqsL1vO11od1Ctq1hZU/jLxVYNJtDKJVZ0NnUgDeO2TPTG4JuSq9Eyl3HUvkshT5wH4SWVns7vK7k1nwnFKjnvic7EVm0X0XeQWoJZHm8gPIKuJ48sL/Mn6jo+pZmryiwNzkfUjfibSpGwgcDcB/DxIxQArqOB+dC4Ps9wBrbwM4vA1zndqbwe3suon139Y4TLHwbAt0V7xIPhj5+daXSsFsVP4BlNCI6IxuoLgY3u/6eTi3f+Tvt8NsHJ4icU9E5fdG1oUzE52DiNf4APG18yW+XQzxtttX1HEcOtuHI4HQV7a27idzkzI1ul8/srU2P9qvP0UAdtLdUKKuFOZUBMDfa/XN7vK7Y37sW1gvU6LzYxjNLmiWQEKrexAQfjwV7qz8OiGja/og/n4UAuD7R+95vKcPUjj4ina0gO9KHZs6vQFdadJOSKPjDaRxGCSos5Ex939GoFbQFJ8FARlfUkNDzNWzKwKiHiQPxMYas8v7S6tm2f5wPsq+PwERe3fY7ycRszeQTBP/HPIXbRXzcCliHFZJtHsGpN33JXkXNIGBCYEVz4zafoS1ZU9E1I+Ixid8H0DeONBYN1d+zly6Ysx8X+9HBOHUFd/cScK/fVyey1vW2vQgkQ9hRBi8j7T2BhaUeQdwXDwWife2R1pzXyGg6nXk/3wB986pZAB8qcl2QV86ZG7s3bMR01lbM7LVRAZUbBWXjxjfMdSQyEfr6CDkTmjO6J0NEJH4L/IA/PQIgB8D3FnUV/Im61XadgsgBqQOAL+fvfdrmgU2vZCW3k5Rvrf8WBUJ9Z6zMp4mY7yCCepiyFz+vyQY/NS8lqznll0NdOb8I6J2GNL0LGw7zQD8S4hBr6XdYt+FWBkH229P7F6MGISlo28WJxPuHFy3Lvs23Gd/Iw8iXY6Yi3eRy4SVEDB6ks1nnTOgb7QOd0FCnu814JHVVbjHPkcaUL9GDMvH1AP3+iGNvd5R/rWIET+AzI+ln6M+KKbGfVZGmSXCKdaeDaihcWbfLNHWealRtu/HWojxfBBpqW2Rei8xNiOItLxIWE3UbE/R3ExDxsDf4PKrAPgHydz3nFTWHzrwDrBnQcN5DnQXv4nOOi8w9m2YDu2zkVXrYHznJX4nHmeXfyLy7bwLJnR1z6a1/BHkfcD3QHTtCMT8D66xzk5Ad8a7ZEGgX7F+voTumspAn4m5GUveqsT7A14B0UefY9aMCPj7Ap3Hd9nf0VbOK4hW6UUF7Wz5U6G78kOkXfgAjp6yd9YlU7o4GKcgUzWP6M4cQYU7C6Rw8RGyDFq/TvkYOEgH75nJJdm4fWr74jEcbxm9tyYZAL+b5W1n43pi2b4hTy93J00DfIPTTPdlxfNftB46op6ojtmQ8H0s4tM/RvfzLeT374XorJwrUUcZiBjcp8Z7cSDjAcBHZQXXHD8L4+ae/RzF+yrlP+OxQkLBo2im3TdC58x/0Z14JqKfNm6x/HCO7Zl4bz73/yHWt5sQSB4soGPXo/6sOIFqbfQjEI31rZX3HgKHl3PveL52oFuTqTWVArmvsHIPwqwYyWKTfQH8j8x941SIjn2dzFr8ZZx1RNk6i8Y1xpya6BqEswxDtGYqBlArSmllAHzRHdyqktyUyOIgAPB9E++saHM/grxS4WRt8TQ5pk5vQFea9BJi7GItsLfsMBxoeXOiQEKfIpDhERTV/BFEPFcy9/EzdAEHwKIJxLT/t0aEyyI1+3Ia8tG6vP3uiSTsgYD/GF3QC0ffvUWxZn+Tj2e7ABq46NTx4UweTLzD5YcAHyfF31r790dMTAPnN42MKY21rN+Lxn9ndEGfGH9bNP9hrOzvZUhoUGRtEOq/FUmsWwnes7f1/QbyYPi6dkl9gS7xRxFQsxgJpjIe62he/osI+cNsHB+0sfwDjkEm74ImrPPKvnTU3Ng8jECMYQDVavmdLNpzJe/83uo4kXw0+Aus3qTbpKJ6iMyyLS+YLYYAdO8hDYsiAN7vmZ5xPak14MrxxPyC1AfgD6dAiEgUMwKdX2OBX7i8nZCp4lDEQO9M5B4HnUefUKHlUnM9V7r5qrlGJuj8I6uAt5HWZp095udvV9sDO9Xpi30zGDFcb5LXcL8AnW2bFLR7KcS4HFpR/ppEGjfk7zOvxXYgYrzDHTTa1r13v1B0ng1BDPxgvw7JA/AD3LMN0bnxGDqbzwU2r1HP4YixewExYEu6Z9Ojs+wrBE7P7Z5NZ2v+Cyo005FbrqeQELw0/kpiXpasMy9tXPvxOVD62+VfQ2T15p71a6F+38+kVq89mx0xuw3y7rnKAPg1ED1UGZiYDrgDEu+nAHjvgib83Rppdw4lL4BPgQodMi+2B8OeHmvt/xeiK5Yic6G3K1mAz+ADtgcS9pVa11n+9WgvL4I0H5dD59uZCHT/H7ovf1zWv8TcjCN/P9+Azi4v3A4A/AgkkPoS3V+z2vPe1tefWf8Oj+o8DNE7MfAe4jwci7TIT0Calg/RDPpdhXiAZYv6lujrJbZmV47HFilO/Cx6f0t0xzxCSWymeL3RCXtmUk9k7kw2JHMpFZSO9kiMyZoIgH/F1sJoqgWJgTY7J/HsAnR3bonosyAECHvz+wCS8Xx3Rj2k6cxlEUj9D3Rvr0cmEAo08H723cJlfYjqOgXYsWR9DqQdAHhgfSRs+5a8Asv56Cyr41LMtysoW+xW8HxTRA9+YuVXWkMl9mWTANGe/RKdnf1c3qHWntdx8YYS35a6THV5VyCc5UJEbx2O3KI0EK3n3bG0la+9xtboBiRiECEPCB+hu2hpy+uB6JLt0D6tFSwaCZBmdr895pQD4KN5+DdwW42+LJ3qQ/SOB+AfIQvgXnv/23szI63/vZACx0D3rA8FADyZlcCT5LGECeJStCtN2NTpDehKk1ZCBPvNdmh4X2wpAL4fIrSvQUTyc0iqu5n7ro6ksxKAt2fTo4v+TiR9rXMQbm4H3b04Yh0xoesQAbkICJwNmaWdlWjfUYiA8UzKdYioegNdrvv78qLygwuaMQgs2woxEoVaG0ibaYy9dw/ONzLNTKkHeY+pU36irk9wrjaQpsRHNob9UuVYv+4BLqg77+7bfclM8/oiYOVrpHF/CrIoeN7GoIGk6d/76yxaB7Yuh6EL1fdnagQaNRAj6cfzZAQK3keNQCcdNTdkmntbIXcjyyLAbhhtN2XemhItLKQ5872GJNrbI2ldQyTF2P8GAXvBV2s3dOZUAfBJgVhBG/ax+ZyX5n2+KFmcgjIAvnuqTwX1zYnAz3eBc13+rDZnKc32aWyc77Z1WcZ01V3PS9Qdo4r+TMj5vwSd41NG7y6GGNPTiHz3kj9vCoOJlrRpW3RHvQMsTOYCqKk/UZtmqij3JFvL76Cz0t+bRQB8LxTfYk10h3qAq+gMuBDdwXfiNNrsWQzAzx33hWZQtqieqxFY+Vck9ByD7kPPSM0N3G7r4zVbG+cj7fpPqQBELX99dDe3cn75sa3U7O2ohECg74NB0gzuPU+B64qSdbe3levd8CyFBDDz2++Z0R1ZBcD3Q0z0dNTQ6nLPJ+QZsDNp/84xAP8/8lYHq1qbHiEKvttZ82L5syOa7hW033+CzuNhiGZ8Ht1HWyJLxs+QRUpKmaBoz1yLwJt1Uu+gc2Am24eFGnbRNyllkqsRsL5Oov8rIiBnFPCvkjUXx1VagUhJIVH2j6ze9RGAGPxge2Wc3TFllaJxispfk+xunDd6dq6VtXmiLZvbHL1IRTyZjtozk1sic/eRuoMfx/z722+/d9dEd3nOYpTiO20Auq/eJQ9aX4jTekb0yC7oDnuAFgJwdlQ95OlMX0dPxL/2SHzTB4H/j1PThQuim59HQqMdXX5MIw+kjQA8eVeiqyIcYSw6K06hbRrpYd/sic7k5dCZtXT0zWbWv3cxS5WyNeSef+8GNvHsamtz6twMAoG/4wQg1DjDojqORMD7+kTWguhu+sr65enNk2mNry3bl54nOszeO6Pu/CSeHYyspo4nD0anAHivdDUjsk46vaLu3a2NO9MaAP8gJa4VS/pyD7JE+9rWyQfkLfh6kwDgEW22H3mcqgt4n0RTpzegK006yQ7c1xHjMMjyijTgm4hRxs/sJwXAx0T3YMSM1dZ4tO/WtwvpAZxmqDsMPUPfHV3aQ+OLBzE1fyOvoRi0NpZBgMS/kbZWoRYjAqqPpIb5tyt/VdeP+8mblqVA3j8jJq3SvNw9G0SmufUGBswic7KDrb13WT/9ugiuD4YBW7Zx7QUA/s+I+bqCZh92ayAQtjSAq70bXACtTia5jsf2cKvzPPJBYk5DF+fmFXV0yNxY+75FwIsnfJazMraN6igqJ6VR5c1X+yKguJ/L+y0ihv9l87JWQdkrY4GbEvXEjP01aH9vELePcgA++E98oMb8n+DW8pdW3imIoQ/rYRZkrdOgZtyAkvpCO2dDhNWH5Bmj8NwTjz0RYTgCp6HTTus5Z+pfsw8dNf890Dn6YFTGTxHQ1nDpBrLAfjn/31VzhTRB48B42yHG5AsEuqxY8O22wGlF+8flXYEEk4eS1w4vEigPqpiDItDtPHQnbUte8OLP4d5kAPwfSPvWrmIsg0/k9ck0dQ9HGjlHJd7/KQK13kFM7PWUMOrRt3tbW/uWjG/YNwuVrPtalnUTKiEAfCja82uTpyfOt7VWepcU7JtYc+90ZCnwNdJy7OPqLwTgEVN3hH23RcV67qgzYGVr729JxKwgA+DnRMzrE+SFBsuTt5RLAe8dMi/RWM+OwLc3saB+iG7cG4GywxGgOwx41cq6j3oCgEts/GPBW9O9j2i24GN2XwoAeDJAKI5bNKJont383Y2AuX38PMTryrVvBvLKCSuTAAIRIP4CusN2InF2Ih7kLUosQ6IyT7Z+Xo0JJm0NjKTEfRnyw19lwdMhe2ZyS4gO+LuNz8lk51m47+9Cik37Irondk25PvVi4wQFjznQvRjii5yPaPY4vsFUCKj7CvFzlXuzo+ohO2eq6Ex/1k2JrG2+9nu1Zp/WQjzNcBzfndjjAxEAP4YEnVBQ9s/RveVdR62GrAHGWUoGdo/KSe4bJJx7yvZhoCf/FK2ZzZAQ52UsGHmqfy4/uKJMuZoJ5+baUb6fi4Pt+5upab0flTUlAncvJKPPchrZCCdpIAUnr01el6/tgQTbX9oYhn3p7xf//58Q/VfLbWBU1yX27a8wi1SKMSdv0dkb4TSfUmFNhPCKO21udqIAgCe7p6ZEYPmXtjbqukO8GPEv5wIbI7/3h6K9PQ5hF31cHf5+nrFsXXelSS91egO60qSR7DAfiojNGaNnHvA7KD4MyRilNvk1dWUXasCjS/IbEj6za5a9ASXgqP0/B9JWGkXCnYf1bwb3OwDGa5ERPfPY2FQB8DMgwmNwyTvHhPJd3oZl/XB/F0JS4QOLyk/0b2Gb238g8+X3sYC5iNg7lsy/5wkIHN2czF/xcWXl15ijva2/b5MHsoqCXRURSHtYOae5y65b6juk/fYVzW6HkqBcR88NAhneR0T24pbX09KUyORvB6TJPXP07RQFfT4YSeb3ivrzd8RM30+eob7J+noLaSJhJ0TgbhvlH5qo51qro4gZ7UkxAD8DYtIqY0mg82IYIqrvdfWORALGi5HPwNUQsN3A+SZscd3mwA/yjNHZBfOxpI3Pl1S7TRjv9VyjDx0y/6G9yBXKZ8g9we6IWW0gQnVHBEqcaXmHtGFOZrX+fAdsHT3bwdbWULJguFNEz8dQcZ4hQPNd5EO0j8tP+c4cQnaftRoQalN0n2xTUHZKEPo1MkMe2EI9J9p4BybIC4oeB35T8F1vpFk9DXlaIQWIek23nRBTsknR2nfvXgRc1kJf2qxZFq/VorGO8hezOXqJLJ7DuSR8u1bVg87n2LruSnSe7U06eFoRAD890k4bh7OwKmhDR54B/RHw+xUCCVIAfACaVrb2/7TOHHXkvBR8Myc6z4bhAp8iUGMGtI+vsjY1gBNqtCNoIl5DibAq+qaPje1YWwO9oucDkELKni7vSnRONblFQOfyou73imQ+4FsKDEfmLuQFJFCcxz1bF1nTbGq/9ySKn4Ho9JYCRiPhVQNpAF9TtgYQL1Ap5OvIPTM5JfJA113I/eepGBCLNJ9H2r5v2Dh9jO6BITRbVRS5mrkCAYnzWF7wj/6Zlblh1J7wdypbd5XruqPqSdRbh85cE1lFDqeGNZort1dUxoNUA/Bzkbl0Xaai7VORWZ4eQR6AXxMJMMfhApKWtdneOYAMeL8c0XdHIjp/EDoDP0eA7QnuOw/Ab1VSfg8re3Di2VU21+F88nOwVPTuoWQAfKt0+rxIEWtI0Z6y/09BeMly0TtVfG0A9ON9OVWiXwH3+RkCtluKSYFcZn6EguAWxu5AdMJb9u7W6B46EZ0PhTGSorYOQDHivqIEgI++35WawiokJPwM0erx2bSMzfU4YD8/1pTcz11p0k6d3oCuNPEnBB68agdbymQtNic92A7DJ3HSyHZqSwzAf4QI8doa3EXPyQPwy0bPjkLE/RvAES3U403xA7NYF4DvU/JsCqTZ3OTXkgpBgvvbt24/3HuHkYFi/0HgUgDgZ0IA81NkWvujkWuCQlc7Lc7/nlbuL3GaLrQAoCDg7VEyc68mxt69u7bVd4D9rrTe6Oi5QczGS7ZHvVBiDWt7cMfzPiJoN8ERQjQDCLEW4lX27XWIuXkfEal+7QZG8mRMAxGBqDvaGjg1avNGRNHarewvkcuc+EzZiIzAizXglyADtnun+uXyBrgx3sj68iDSkpoOmfz/Fu3zBtKC/jdZkKAjW1hncyfmNbRzdjLG6Ofumx5IiPWKzenB7lkRsNfm9VyzHx0y/9E4TYV8UwatpI+R2eliUb/fxXw6pua7ol9LIPPsb2kGOLYnc0ET/AB3t/58i7trCsqeCgFX58TzYXO/lK05r60zBN1nj1Lg87OgrqNtnfaL8ldGjOtvkDAjnNM9EYPxHdKqrdQORXvjJiRcvdLlh/gfN6Iz+TDEYCTd/hStYXt2NgIewx6Z2cbj9rLv0X36BM5PeUVfDrA15f2etgzAkz83dyLSvAxj7f5f3NbrM0jw8TWwXkHZC2CAHNXn82FoT25A8/3kv/UA/A2WFzS1SwOT04FngHve1+ZqFAUAvNuX/8aECnXmsoPmZSkE3OyNaNXpMVc0ZAB8TjM1qmsWatA4ZIz9EzZWR5EFOq4DwN9DgbUgzu0cOmcaWBwF8uDFxdb/JaLvV0Caj6OpISS19TIbmSbqCwgMuxeB40G4/CvgRffdYLKzc5VoblJ0wFYIdDwVJ3wFznB1N2mv2js7W3tKXZvRCXtmckpk/NKUyBo0gKWr2h69ESlHLGN77A5bKw2c9nJB2ZcgGu9O5NphPjLaYzakdTqMPG0W06SVLgc7oh5bEwchJYwFo2eezvQAfB+k1PAOOvdq+ZBGwUEfRRZtntZek3oA/DyUWMxE786IBGFj0ZnmAdjVyVzQbJiqKyoruD/ZE7mbfI/0fbkAOnNG4M4rpKn8b6S5vGNJPSl8ZCUyq+1YcfEiW9ezkD9PDyWz/Fq8qL5EXQshGm2PVHvIaKslEI9+bNl7UV6gz3ol9mUSgLffJ6J9WdsNIHIv9hI615vi/aDg5DO639ugM/lbBLo/TY24NVGZA6kA4BFNcjQJhaGScj1fm/Oi4P5fFN2TY7D4g26fFt7PXWnSTZ3egK408Se7uF6mORDgIDuIHkJm7xu4ZwegC/8NpPFWdjhtQQsgPXnCenciX3JFBy3SaDq/7D0y7eQ/YwAl0to7H/nJrBOMrslPqXvWEgBfUEZvX1bBO5Wa/GV50fMpyC7txZDZ36FII+k9RMDN4fuICOL17H3PwI23jzIyi4LrcablLZYxE9IuD9YcsW+8QCD3tIuzrqlkh8yNjcGK7vfutkdfQ4TcXIhB+Z29uxe63D8hA+Rjbf4mX4VkwT7XJdN6WA0xkv8mr5F2KxkjOTPa10WBgpci73NweXRevI+Z57pnF1m/vBuBAMC/hbT7SzVp7JubkfBhWpe3mdX7NOb31/JnR2fBRYgIDMKkY2qugxMQob66b3M0BoExep88yL4dIlhXc3mps2pgB6znCT7/ZMR8zvUO0pjeDGmaz5Zo2wC05k9uce97AngJxBinAPjtcAA8Os+S/UnUMZe9Ozjq22DEvIb19BR566YhiKHcuoX+XIjukendHB9LtteDC6uXsT2EiPo9cJo2NeqZHYFsnwPXRHs3CPgars5fIia9ae4K1lmDTNDRzVKwILqgYD13R1qurwBr1uzH1khT/0PaCMCTp0ECgL2Vy9sXAYRP2FwsafmLkykLHOP64cvb1eZuxajOoFn9YzdG/ZDv/V9QQne4MgIA/y06176jwqUWHXQHFLS3LxUAPLrvnsU098vmsSPmxfLORoGvv7K2B4u9UzA6mjwA74GxFNNfdM78CgEbK9rvu228j6Y+AJ+a8xQtsi+60x4nf69dgPZ7UVDqldGZt29ZO6J9vSy6p+6xtXS8jdNLyOJpGyRw9C6shiD6ZZuKOi5EQP37Ni9f4c4XpFjSQOD5vL5tSCg7jsjl2MS0ZyanRB6A/wsSMn0DXJd4twcSyA+qKPMCm5vNaQZDq6wTKwNRdmQ96D7+lIyeeAajHciD/Kk6VrT1vFTcroK6LkJ0xvVkMTL8Pl+TGgB8WV2IdvXtmcH6mALgVyMD4Ncvaz8CU/e1/3+J+KKYzwhrbV4kjH2ZvCXPpojfKHUBmag7WJd9g5Qg+lv+eejs8eemB+CDm8gNWqirt7XxT1Vzis7An9csN6bPUoKxJgAe3XF/xqwSi9ZCor5tEJ25eJS/ka3Dl22te6W+HkjYuzB53igWBiyChCl7IyGOP+MHIH4gAPBewNSXTChycs1+NPG1JAQ0lr8xErheiDCXMMa1z5yuNOmkTm9AV5p4kztAf4mI7p6YX11EDH+CCNGPELH4Pnlm9nAS5k9RHTchjc25W2ybv/RLfXtafn8EvuUOztT7iFj6FkdgIyZ/2lT90bfnI8n5RnGfcICB/fUAfC0QBDFVl+OI95J+FGry16wrSeQjjZOn7f/NEKHyDgXBOUkwsu2wNoMLmt9TETCspIwAWH6MAL6Uy451bQzXnFjmxvbjUCTYiAVRr9hcfGtrsa973htpDPyYSDOIzF+6d2UQtEV2dXsgzOU5aP8PiMq5FZ0FtxNpCBftTde2IegM+Q+ZhuCFSJNhk8Q33VBgua/i/iTeDQHimjQakSXAhwiQSfo7RMDrGmV1RO+vZuPzGHkQPQbg50AA7L/Ja3L0jL+Jyv8NJticgOt5gs8/2jOX0bxnUgCUB817IP+aH2CMV43+FGljL0U5AP9vWo+P0RvdA48gDa4Vkel5A92XZyPNy8+QxYp3g1Jpakze7Du4HboFaYfeb78ftrXdHzG1I4Dfp9ZVao1Z/o+jdTk7csP0Odqbi9l6uh5peM2A9vGlSKOvAWxX0ZdrcSbZ0bP5yO7tq6x+H3BzL8SwVFqkkGfqN0D+lodSAcBTrk0efMj6c/NydCc+amsnzMUy9nxRtHdfROdXOAumQPt2FHBmVOcQEj6eESP5LRXnX/TNrLZOvsEJE1PrmQ68A0ra25c8AN/XPZsS0QIfU+KbuyPnBWm7fmLPFkJ7Ym2yffl7MvcTHoA/q8Vx2RABT+uS16JrGYBv4Z29kBXYkzZeZ1ByP7v/KwVw7t1AH6+E9vbfbfymRq7VHiET8p1O/l4oPTvJrAQ2R+fyfAgw/Jb8Hj6ZCIAnczd2QqqPE9OemZwSeaDvDhufs8iAvl7+vbJxs3l/Dd3rRa75UsB4q3tzgtdja3kEssRYDt31oxAdO0NUR5GlZaX2vlu3Q5HgOucChDxgvDYtAPBRHSFQ9q3kQe8qAD6cq6W+ve39fkhh7NyKtbam7ceDoucDW5gfLxicEuEhYxHtdxlSjmq6s6LxXLqijg3RmXgQWQy2i20dlFnVL2xroZJuoIA+I6PDigD4nkgx4nUS90NFnXsjmnuQldMX3TWj0f5/3OaxQYG7udS6Q4LbZ6ycz8gswn/i3pmTPADfDd094VwvdGWTqD/ma4PbrCSgjlz63lenL11p0k6d3oCuNHEm8kTCIDusfo+CoDxIxrhsgfzIhsAwN5PQwEodHGTB25ImvjXaOIUvO75gEu/PS+a/+dS4nFCWHfZXIEZsjhbas5CNQdAs/jfS/JvRtTX8DRfXPIiReZ8Kn9JIMhqYjk8R+BEHpYwJ0A0QgfYwNYLTuO/Otnr+ii5276ZkNgR67W+/t0PS9rcxJosC6W5Ux3q44IBtmP9DcBrDbSzDawzvgNOsQ0B1ALMGTgxzY3tmOLBOwfodgrQAPw9lYpYLqf1h+f2R+439o2eHI6HbM6H/ZITVBTbfc8V9QxYiDZx2dapuv+fsbwgw+jHSOL4MAeabln1LxR4lChDn6vNnXADgHyeviVJbCzHx3vK2rp4kDcCHM2BFG691a5Z7LQI2mzRi2ms9d8T804Y9Y3mzI/PhkcDRNcfs57YGfo1A+wXJA9gLIwbiWyKwGBHgr2DuFkr6syTmbxsBLofZPI1GGsYjbU17a5dVrP+7JNZHkSB5Wyt7ZZd3JpmA4C0EVsYB6P6O7qQmM96Cepa18h7AtLXc+IcAvw0yrab4fBtINfMYGLt1Es/62d8Fbdy+QYzc7fb77whM9QBykRDhWgTc+KCcG5IG4P15Oh3ykT848SwFvIfzeQPX/uNtnM4lA4oWQ/vnJQT09kDaXkUar3uSDwS3rP1dydbsOiXrMqynucj26wDyllNFa61D7oAaa7Evctvwla3HLZDbppMoiMGTmP+OmJftkfB7k4K5uBoBMNeSuRmZHbkX+BS4pOZ4zI/OGG9x6EHoNgHwiXoWsTXmNd0DAP8R2pOrFHy7GZlbg5YUMMhAsBXR+fkcmXZ/b3SG/xY7N6nBCyAAcSw6p/3dP6+N1aXR+yfb+rgCWTfUAsWZSPbM5JTceuhDBvSdQqakUZcmOwPdgYU0I2SxyWxv3tbK3uyIemwdfY1oTL+WN8LFZYnGbjZXx6Ut9GUFpEiwC2m3KtOQP3vWRRjBUKKA9jXqOpjM37l3MVgGwK9O5GakpPz+SCgSaJZUf6ZAdPSrwK9T64uKcwyd72PJKwZOidwAfkuFayTqnWfnI0D3BXTmzGr5C5IFuB+c+K4HArdfp4LvpJw+6xv1LbcvkQBqFM5NbwvrIARDfw3Rbc/amN1FZnWxDBLEvks9fuYyK3N/W9Oz2Tg8amWfTXZOD7R6v0R3/BH2TqmVYGqNkOdrkwC8m+97rU+VMQy60qSdOr0BXWniSwhsOIeMaJ8GmZwOt4vjXUT8zhd9d79dBIU+h927V+EAscTzumZ3sWSzytfjAkgDqhCAt98n22E5fQvj1h8xPW8jTcDnrJ6XkFn4DOSZ9wC+zYuI9SEV5S+ICKcPyUxVA6GyFcX+3QJBtlXNfiyOzLpGIenynVbvQRhwhNx33B76gYC+wJBVCizs/Qa6qGeq065W1kGL38aAZXAdsysCz5K+Pzt6bigJRkqeEBpM5oJmcV9fSdn+e7+H9ra1+TyZy4rlEUN8WFSGJya8S5k6rpQ8obIbInwbmCZyzTJSBOrl6NxKjdlG0W8PwFcG26u5tlYgDcD7c2Ad22vL1ygvJ0iYEOu5o+a/DXumGwKT/ojO2LrCnZXJu0V5zX4/gLTPwx5ZyOoeQ+S6gArrKuSq4jFM093y+lg/gqbTUkT+1RGjOpoKrV33/i9sPv5O5GoJndtLEwV0smfTI4b4WqgOfE7mcm13pKl5H+4uRGDBZTZ/N7j8ZFCogjG7ytZ9cD/k18+1aM/0ce1fEwHvT6I79Wxg4xrr7GoEVIR6YrCiCYC3Z9ORmX7HPj5TLrqCv+hUf56wdnsz5gD0Pmff1gX3DkG0SXcEqA9D51xpQC6kLfoyzS6pSt2O0EF3QI21Pw2KyfEWYooDKHtoRV86ZF5cXf+iOf6CB6d+a2Vu5PJmR4x3ZRBNW3tjkPJCTLe2GwBvfQmuicZgQJQ928vWxGs4oM893xGBT4VaiTXqD6DhCuiceIa8a7hWfAgvYW39FBMk2P7pjZSHXkbnWTfyVmcnkt0bx7r8SWLPTE6JvAb8n5HC0hnUc7c1hc33k8BN8XwVfBNAsgEt7M0JXg+iGRooBtl8Ub2LoPNxORJ8GNLqva9OX9w32yAaIKY3NkFC+PetLR6YXIsM1FywbAxo1p4PbtxaAeBbsaz5DaI5g6Z4kcD+YaR81tI+JBP0pniOaZFixBhkIVX7DIvKuRSdZTuQUGCz+f8M0QYey5kP+bwfRYW1INX02ePo/EztyztoFli3KnhdBJ3576BzdHuioK3IBc3HVGAISHD0tq3ZmK9YlAwT8rFv5kIKp7XO/6K1bX97kQbg/X29ELK6O6SV8epKk2bq9AZ0pYkrIYb2ZUurR89mRdLG2FdaNySpfAS4hgrg3A7MBmnNzcOp6f+dPLG7Ds2uC/ohDaElyJvOz0/mAuDURLnT2GH8Z6Rx1QrDsr6VuxuS/m6GNCDGImD6fNLMShNgkuor0qQfh0CWJay8TxCD9C+kzTdP4vu56vbB3t8OgTXvIEHLPoiZeAVpjA2xfm5s709B5tpgj5p1BKDrZGDm8Viz431JkXfZsb3N3/cBacrq6Yi5QVrBX6JANDHDfRbSGPEBendHe/i/uCCsbRyb/Wzun0baDF+SD7ro92Fl4J4aa7wX0jZ4GxEqpb7ySsoLVi5NPhrJzqAFovZvQhaEasvxXVdWpgfgVydPxPZELn/+Q3UAtysQQb1m4tkB5LUg27yeO2L+27JnbF08igj7rarqSIzPizYm+9h4PIiYi69svo9FwOZDSIu8yQVRaszQXfEBEiSuUNFvz2T2RMDYq9TYo2TBuXYm7zM4pb3lAaTuyDXNp1T4Q7b3z0EgwBQIgN7N1l0KgA8uaK729dWoo5/N8TBbU34NnW/jX7j/WlhndYRVTQC8tS+YiZ8QvR+087zG+9TIP/WnuACaZJpU9yBhT0w7LYqUGRpUuIBxz/a3cetrv/+KaIvVS76ZCd23F1XNTcH3E+IMOAdnBdJCW6ZC4M5KOAWQVD0dPC890JlyTzwmfl/YnnoTcwEVyqQGiGjvLYlclb2DgLg6APyRRAKBijquQXfHUUgZ5wYbC++2aghSuHgKEyzD98FCv8EBL21NNAPwT5OPLVUpSHTvbmNtfQ93hyKhXgN3NpI/p0/GWViVrYEJvWcm19TCmHoN+PuQEGulFur5CwINS/eCravLgYXsd6292VH1IEu3T5HbVq8YEID5LxFddR9ySzIXmWZ0ZYD1qK4DbD8vgmiJ6az+kUiY9Cg6K78BTo/asnUL9XiapUoD/hsUm6FvPJ416vmxtftasjg58Rk6AAG+tWIjue8CvbF2yTvTkNEWl9Ki8hk6d99BPuhT9Gi4T5ZEAoTvbLw+tHl6Ewe8F5TRjxbos2hf3mtzd2Tcphb66HnBfkSKBbZvpkOuFv+MFB/LBDxXIuXQ/nGb7f95razvhfSWPxAB8O3Rl1gDvm8oz/p5iK252udZV5p0U6c3oCtNPAlJYochzdmcVDhxOcX+d4OGXJV/1352mI1DmpgeMDzf8pvA6UQ5/jI4FEmavWns0YjwGI203l5DvsrDZTs3GQB/pruwpkGX21dE/lXrtImMKHyfTCthWsQovmIX2reIgNi2rF/2Ow5wshIiuv5oB/YUyPftsVbup0hbaXfSQG+VBrRnOrYjc4mzEGLg90GM/mNkPjGDFHcKIlcHBXX4tXMjLthUK2Pt/q+0tKhZ5kzk/Yl6354pxr5D5gYJcBoIFOwXPTvXnjUFHEKg2f8QqDRDvLYS9UyLtFQWRJqmvqz9EaPdAH7j+92eiTzRlSJUagPwKOhpAwEJC7n8CygPEBfMJbdvx36tYH15FjM3RWaPwWd1qYYgmQbukMSz8629cSDAVtfzBJ//8dgze5AJYfpW7Rm3/pdyvw9B98A/yAc9PBBpVH+AzueP3ZjNXWONvY+ENt7/fuyCpRv5cy+A2qNxmrsl9eyOGK7Nq/YAzUzFfugOrOWrksxn6PxuXVQB8DkN+Irywx6fD90lr2L+WpFm/0gSlifk92ilWS4u6GHi2WbkBRjeBc32SPgXmxl3t7X5R/Ia76E/MyMLjg/RngyWbSvYukrSE0jotHOdNW3Pl7S2bWi/F0NM9ZPIVVDPqF09EE33HhUWVnTQHYDohgYFLktKvisV5hWss46al54ICHiqqF1kjPYfkWZ9qQZ1SV0LI3DvfaoB+DttrE+iwjrCzc0nSMARxmoWMnp5M/fuEBwAjwRZSRc9dect8U4MwD9OzTgfcf3IEukZG7dFEcg2EjivzloryOt0umlSTEiwc5D73SoAPyUFMXpKvv0FAqaX8WUl3lsV0QMrRPl1BT0TpB7yd/uZSPB9K6InFkD3/J/t2TmI3hlna/wddF9PUacv7r1ZkOLCO4h3/4+VeSeZu7P50Xn2HAk+rmDfXIj4v58gWjimmX5KFssmBuCDpnLLwlsr4w/2/flxe9E5Phjdqa2cM+HcTFnYHYuzOCXvA/4iWgDgEV1zByWCHbdHZkI09onI9eIufq0VzEtb6bNQ51QUuPFrcY7K7rRe1pfPSbjW8WUg7fyXgYvL2oPuu6+A86P86Yra1EJfigD4aSw/9KXSdVJXmjxSpzegK00cyTb/G0iaWssnrH03H5KMf40z2an4Zk5kejuSLCjReVZGpbuH6FI7yC6wvV3eFXZpnIWY6B0RQTLaLpIAAM2DgLixyIz/WkTIfEHe/KglzWpEcDeiNg1BBMsViHAYae8U+ru3OWnQDKpdZd97guQniJH8I1kwsQ+AJdqwFvz4bo0IqvcxRhkJUPZD0uRd4m/sdxWj6s28WwLgo/b9BBFpfVLP29D3mZF2bJWJcYfNDQJPLkHgya/JhB0XkgjaE43PviQ0vxN1/AxpSYxDWhIjbJ2u6d45EAmQXiTTRm5JG72V9UeeUHne9bsVS5RjbLyvRYzxOTZmRQFcQ91NwpF26NcSyCT4C8TI/AeBfT/zbUh81x2BhR8iAYwPRnUBJeemred/1VjPE3z+22HPfBy9U6bp8isECC9IHgw50Mb+H5ibHzImcyF0//3a+nhCRX/mQFqNR9CsmTMduufmp5mp3Brt54+q5t49uwT5u5wqyl8MaaaeTD5oVHcyFxiv4lwdpOY/KnM5G+ubydy+TE0xAD8bugsaJHyDxnvM/gaAeD7EsL5oc/01BbEPEFiWDOqdeDf48x4SxsM9u9TW20Lkz8oNkbDqG0r8e5I28/ZAxW9tbk+xsfwK8zFbY56LGMPA2HZHgOFQjL5AAv/trc4XEc0T/IkvjGikOn7RO+QOQC75RlCiHdheqQPmZWpkHRlcewWNzS3LyrU1+Do1FQeQ0O0XSNgXFGMWRUoQdQD4vwMH1qhnK2v/OXH7kZ/9MfG8Idr2ZTJLgZNqjFtL1nhu/S9v6/M1alrIxnNABsB/jO6Y82lRs9mVNdHQTZNSQprYbyAtXA9K1gXgC4Ngl80/AqjfQYLKcAflBLkIrDve9kztNdZR9dAMwH+GNO1HIsG51+7th6wKzwX2a+Nc9UCCtXtsjz+L7psBfs7I4upU3tGIBgoKDu+j++ku2yuLu3Hci0wDfkn3/Ux+j7Vx7O4l4/3XtDX5IyQUGknFfRmVmzs3o3m+0MpbI/pmSjIBww1E7uAK6ulvc3BOjXe7UWLlkNozjD99NjDKa3cLHqR8cCTiozyNVnZ//x2d06VjbGv8kbrj1WK7i/jaPRE2VRrIuytNXqnTG9CVJo6EQJy/4dyzWP7ydlBci5jvoM3dyy7KVy0d6r6JmYDUIT8A+B1igO5DWgJNbmgS38XAexzw7KcIpFqPPMA7FTLXfx1pAwczv9kRU/Eo0rD8NS5ITCuXhztcuyGi60X7vROZ5lFg0hbB+astKG81RJzeh/NphwCXz8iCwexu5Z+ICLxZEYjUkuZ+yThvhQiu98g0HbqTNxOsIn7PsAsz2Wcyk6+TKQHgo3YdaN8UBvVpyyVGPkhlEfPYIXNDxnT2JAPsrkdCnK8oCEZK5Buvoi9X2p45CzH5u1reWNsrO7p39yfzZTqPb2N7JvKEyq42pu9TIRhEoMoSUd6xNgcvo3MmCfogzYctcT4oi8as1fXl+jM9ElZegYJmru/eKdMQ7IVcWn2MCMmZEGjwdcmeCnWWrueOmv8O3DPXIuB93VS/0b3xFgLgl43fQczm1DX2zY/Q/RN8CIfx3g5p0n+K9ui1wI/s2YYoLspDOI2dirnvie7me6P8n1o/Gi790T0/0+qutcb8ukGB2T7AgQKUA/BzAINqlDuV/21/g4ZVAzgltbeQ4OZ9Iga2pK6Trf33Aou4/AsQ07ZpQT2borvuYJdXqClI2iR6Vhu/oWgPXdXKPqnZv78Bf3K/+6Bgoi/aOH6EBC/BVdzhZWuAjjsDzkGA51LtNRYF9UzweUEKCHfYelkDnVUr27p7nLyGoQd9ZkCugkLQvyra6QJ0dz2BtCVnds9qA/A1+7Q0UkAZTaZYEYCYEOQ6xP3xZ+qeyPr0py6v6Nw8Bd0D89bpf1weClK9f51vou9jpZLH0Pm8QXhety3/14F7ZnJNtlf+hUB4b0nULpqyBe/0QsLy4NZupuj51Oiu+RLYZzz6NkHric6TM2zNvUYeoE7SymXjhMDuKxBvvhXNWuGz4/hql98XCTf/TOTCq6CeZZDSxVj7exQSfI9DdNNTiD4eiM68cfbeMmX9IaMpSt2Duf/PJ6OhRiPa4AXM73YL62ppsnNzd5d/gZ0xRTT61EgAU0vjGd0d/8NcqJWdIYiO3ZGa7sboQPqsrYkMdH8WJ0yumiPEM39GpPgTf4/og6fqzHkb2x/ztR/YuJ7YynrrSpN+6vQGdKVOXgACUXsgsDhm7g+zi2mcHRBjkYR9fjs89rbLaz33TZmGUHfyRMOcyGddMP+qAtZSwPuPwzMkSb4HSZo98O4BzC3tIvlXVHZPG4eeVX2paqOlw5AmzJ+sf6eRmRiVaomTJyZOR+4X9nIH91RIS+BNZDHQAE6lgOhp62FOMwD/DALgB/nncX8S5QQT/qC9+ioCktci76f6ajIAPqVdmJp/rzWzm839FeSDmbVJipwat46aGyQQOhYBaIE5DBrwn6C9uEOqDKSV8gSRZmdBPYciAmADmgPx7YwYo49w5r1Im/5VBAjMV1a++2ZbWmQ23Zj2QprQpeCrjdcTCPiYhTyRfaTNxf0kXCMhIrVBiQlj9H7/Ou9F35QRyqm1tgoCa3uFd2yehiFCsoyo3xr5uG1iTDp6/jtqz9iz6yjQqsWBcUhw9xYC4INpeJMrk7L9g+7B4WTaTgsgZqthc3MrMm8ehxjTKdA9uALOnU1Rf6L1ewli7A5HPktDIKhnbO0ujYDNBnkNmiZmqmif+bYg4fA3wNnRux6A/yuJgOQFa/kQZKb+AmK054jqmxuBoq8CW/iyUFCx0cAZLe63I5GW2P3AjAikGEliz0RjME9ZX9we+DXai28iumNbMr+6s9mcj8DMnS2/1TPwArTPLkJCqeXQPXAz8M/E+92tbeci2urHVJuZH0rH3AHBVcCX0Ry3alno52qG6FlHzcvlSLP1YpsXL+AMlo9/IxJIISHJbrbW68RfuASBUdtS4JqAagC+W+r/kjoXsjH6jsxyZFnbOydH7/qzfeGqfWPPNkVn4jFVbUmt76K+tWHtbIOsqt7DQKO65XXUnpkcE+6eRQD8E7QIwEfzuHDNekOd0yLB/hcIyDzS2rEt4kNHUFOjtpPr8bz0qchtxc1k7uJq8WeujCsQPfMq4jG+RfdIU1BQ8rRJbwQkjiDhFrGkvsXJ4n5tju6u+RDvfL+1pYFoqK/ReXRrqj2uzKQyUsXYzWZn0q7AIBx/ULUOozL9ubkZmZVtlZJdbSU2e+d2RLs2KVhF7+2O7sHKYLR0IH1GG3hB9+3CwHE4d3XxHJHnnYM71gUQzfon8u4h/f01va27c1uYi/Hla/fF+PhW11tXmrRTpzegK00cyS68BnLTsI8d8IG539UOrwCM/NS+6Uke5E6BO3siqeNrSFp5LXlfywMQszQSMSVNUvVEmSEa+l5R/hxWzmD7nWI0p0KEyjgsGAz5i7iK6KsbEGcWMjPcA+t+l2oHAoheIe/reCW78Bo2d20ym63RjhQA/xYVWo7hW7ucN0JMcAMF9L0REdsNZIlwE7AxEp7ciJjz782rE+04GCd4sbzLEbH2JjJhbOC0F9rS386aGwS0fEAWxKgBHGHPepIFXrwVA4HJLvQdbGxOrNMPRHBdTV7T1++HbRDR8jCmqWb5B9h471yjnjWtD9dX7a+i+aAaRL4CaaGdgPMDGa2bo60d15EPUrWjzdfJNdu0JzqzhrTHHiuo42RECN+NC8Rqc7a+rblXcb7s3TvbWz+PrqijQ+a/I/aMlXEhOjtWINJiRC4bhpBnGgMA/zA1fYciJnEW+7+/7cHP0Hk2FO3XX+GCJpEJfpq0blJr2fLPQi4Ngp/7bmSBrBpW1/HkXRD1QwDcTW1cc368+iJG5XXM1Q/ZXgxaeyMR6Fd6ZyONtU+RxcYz6Hy6lSz+ijdxHoZj8JAQaQw1NIOQsGqBKO9oBJK+Y+srGU8G3T97/1/BeET5VyDA7rc2B9eR+cG9MbQBaVr/Fp1L57nvazNrCNy9EWnMjrX1FWipBk7TjBaUF/xY0jF3wLX27lFWzifkgya3ZEFk/x9q5YY7sEPmBYEqnyC6ZpqCth2OwKuPEAC3PlL8OAedUZUuGhHd/TZRwLuCdz0Av04ra6ygvIVtjMaQAYhXkbACoRn8KPXxjuIqXWdrudRN1YRIjAdN25F7prMSAlOblF/aody+ZDEEPD2wCi0A8DTzAs8QnftVc4/usC0Q2PYtOktHIT6lZTc4nVhPygf8r+qOh/v2WluvmyLt9qmQVc83mJvWgu+WRvTa51QIEhBPvIhfW3bO/A4n6HPPlkB0xu3oHG9QYvFCFhR6YM0+t4tVa/TNQkh7OtBpRS5aBqM7qS11HGpln4UJImimd6dFvPYfiILSJsrrEPrMnk1QXpA07xzwqiOtb79Dip9+vIIm+lBqxpGYAH3pAt5/QKnTG9CVOmniBUD/0v1e3A6RcGl8gpj/RaLv3kZMeR1TrMsRM/QH4DK7lII0+1QyTfA57EAciaS1hUGh0GX9BhHwbs9mQpLmwyraNYe9d3xVH6LvTkJM8IwV7wVN++DPbfea5V+KCIiZyUvD10cM269c3vQ2rh8Bq7VxDdQySY4uqS2RafvXiEgr0wwNLoq6I42Cx5AGyGKIONgEgQtvI4L0A0QIhKCHZyMi0Nd/AM3A+zWIcNwaAWKrkFkcFBKOFf3czI9rR82N9eVTxLzNiAIy3WV92SbMGyIyPkREUj/L35lmQqhsfma3PdfkCzIaiyCYi329Ll6zTzMhEGw0IvLbZFES/sZ9QpoQ7yEAzWv6NgEQZL6gr0MCxS1pLUDcBbaGb6WAsB7fhM7Kj5HZ8lKJ5z2Rxt3HyFTXu9XY0fpT6q+8I+a/o/aMfR98iN5Os+u0EJQ4BKj0BO/+6Nx5wdZp2X4JQo1LyQD4uZA2/92W1qRZG3cvdKbV8nOMGPbfoHPuIJwFAGLktyRtGTQH0qo8JZ7DgnrOtTavTnaG+HnfmLx12RRRG39Mhck8Os8/s7KmQmdaEEZ4d3EBlAkM3n+QsL/W3kRCt1es/9OTF7Ichc7KZzFBVtSXsGfq+MQ+0dbohmSCkR4IsPolWZyCue1Z8DX+LnBRC+t5RZvn1ez3lMgEfxACcH9lY3gnTqhDXqu0Do02we8AWwNfYj56ETj8KC0C8FF7gsu5n3TwvKxqa2xwanyjdbUd2l/BH/hoBHDsW7We7dklyLqk0MoqGpNFULyaT6gRO6lGXxdC91wD3TNt9lMezy2wNhIU/JEampkF/S3VyG2hnC2pSdPa+x1CN3VGQrT609TwKd1iudfYvrkd0dZBoBuEOashAP5NSgD4aHyDElZL7jUTa3Ep5EJuHvL+0scLDOvAejwAfzripe6gAnR131yIzsfVovw+6C5uslCxZ3ugu/0FKlyAIM3q+22PDfF7l7zGeFN8KnT3TYUTnCfG9jrEN3W4MC/R3kWRYG4c5rorer49EsT8oq3rCfG33yB+Zlb/nMwSYTgVlrx0EH3mno83L+jHIxqTMt55A+vfybYGn7V2LIxwiBOQteqxLdQ/QfnarjR5p05vQFfqhEmXhtxv7LDxprczIw3EbTFwwT3rhkyPXqGGhigC14faoee1Q1axi3Icea2j4AP+c3Q5F2rTkXYbMYW1/3U7cJvM4cN79ve/wJU+r6I/vZDG62fAA1QA8PbNSnZR3UZ1oI/5yQQf9yKNjmD6NT0SjHyKM1Um8428X91+2HsHk12mbWFWdgB2qnj/WuTrsK+bnzWQ8OI9zAdyaAMylz4HMeVfkLZsOMLyvcbIpYjYXC1q4yqI4a+rmeu/PcTqCSZrHTI3JX1ZFV3w30vYyQPwNyMgbDT1NETDhT+rtfu41Fpwdc1k6z7pZ7CqHvt/BgSCjaFFQoVyQHQmJNQ5jujMsLmZF/mX9KB8AOD/hYjgk6r6Ys/Os/HaAXc+2tou9AvdYn+ORoDQ9+5mUt+g82gDdMY+goCXHer0pyPmnw48z9z3v0Tn7SVkWjsXkg5K7EGyo6hpxYBAz1BHYHp6FrUXMalnIfcGA1voy8xIk/c7dB5Nl3jHA8zdkRu4D3E+3kvK74/upY8QHfAQAsQ8U9wT+XB9k0RAuKj+lKZbcDOyWZQ/IwJ4Lo7yg9B6XmTCnrPeKFoPSFj1AdIIWzH1Ptm+eoAs3kt3BLx/Qz2aZhbk0up4MldQ3aJ6riCL7zKVm8s/ovN59Rr1nGnj84X1aZaCtbWF1fVXLHhw0Vwkvu2oO2BWBLgNIn8frEcLADzNoNv3Luc6al7sm31sHc1R8o4Hw3oiwGIlBMr4/VV210yLNAwvrzOnZHTWooi2bVJOaUtCSjm/ROdQYWydijKOQMKKAVH+KTaP26XWVMUa2B+BLcHqoSNo2g7ZM52ZEC1zA4p/NbAd11CgBT5G5+0ndi4chrnPsH3yBALpmwRUBWfAXvb7ZGDpVvuaKLfUVUtH1NPGOvyZc6Efv5JvuiFB0gjEk+3snvVGYOWT6A5aH7ln6evWyapIwazQBYjlBYuk8xG20GTViM6tJABftW8QHzQCCawnij2F6PGm/qBzJqccU7TWyuYZWQ8FS8g7EL87i/09EdF0VZYIHUKfJdZ+u/OClPPO3wA3uL5tgQRGY8h8/f8TOGBi6EtX+mGkTm9AV+qkiZfG3pWIwbu04B3PXPdAGnwfUe3DbD4UtOJgd2B74mBuBF40yBNZc9hF0iDhx488M1V0CIfgirtE+d2i9r2JaU3VGKs+9ndaxKx/isCKOgD8L6w9ldHsEfP4T6QhcBcifFaxZwMR6PNX8u4a/oUI2t51DnNEoDSQeVmrzEqpppfLuwYJUdbyY4+IvTWs7g9IuHqwy3EhIoLAnu2J0zay915GAOT3gIr97YkAr8NRdPT5orKaCGH7/yB0kf4ken+Czk2NvvwH09Dz84YI2s9pIWgL+X30AvBg1Xdov1xeZ50UrSmb26MQQVqLUInm5mfA1dHzJUhoNaN9+mdEJH6HgMa13HfH0RrxuDES7G1VsOYLNbRK+rM9sL37Pa2tobOQto9/dxbk73lTnJYyAuDfR8xNXfccE3z+O2LPpNYaAoqGAz9H99tXODdn0XezJ/JSTMo00e9fIlDlEiwgmc1FN/L33JRIA2kkNQIEIu39Zd3vmZEG1XfoLk36b0cM9F6I+Sh1NWTvrxfGF7kCuJDMrPtB5Icy7KNdcEGtqe+aoxeZ9dHeZFZuody7kFbtzoixny76fgHymldF6/IYdJdsQrXVy89wADxyG9KK1cvy1p9BiWd+3u9Fbiymc3mzUkMbGQEVw9Bdl3IpldNqR2BGA2lYJ4OJFdTTIWeAfZcMXkxNAJ7m+zm2fOuIeQnjfhnwgv1fSDfZ3pqT6Owo6mPi+bQIAL22xrrshhRW+tnvpOJJq21w7wUXNC0D8EjLuYHcPt2JE4Jaux+xZ6HtdQT5wephiP2e4DRtYu1O0D3TmYlMILle1dprocztEMh1N7JePcLm6yt0Pz6K3I4egZQpno/2eOEZQBYravnxbWdFHyZ4PeNTB+k7r0zRI/AXP0JKdS/5/Y38039H3hr+caQk0WRRnKoL8b+fIvrZW/CF+8u77fIAfJPGeEEfLiCzeOzm+9Xi2CX5wap3K97LnZtkLlpOisehxXnzbb2SLBjqCKRw9gQVQDIdRJ/ZswnKC1KPd44FCb0R3bAJskiZc2LoS1f64aROb0BX6sDJFtgzvfs9F7rsvwAucfk9o+9mR5q1I4Gf1ahndbtkkv5V7Z1FETDzNvkAZwOoAPftvamsjB/hIqAjZuoha+uWNEvN/5+9846zq6ge+Pdt380mmwQSEmroTSB0KULoXUCQItJ/WOhFQUQpgg0RUKR3QUAFaSpVCII0UZEivUMgBNKzm2x5+/vjzN07b9697923u3fe5u75fj73s/tumzv9zJkzZ+oQ5cJbWH55S4RzFjJDPNr8Hmk6pJIKeMSy8GuI0qTsxlrmma1Nh3gyMjC9wTTo5yKzzbuZdD3G3J9DrIeOr6AMNJv4f4bMblc0WAnCNX/jFO+zsBSdzvVaQgX8hxhlE2Gn7yoxS3WETYiF8MuIH1zb/cYUk3aB//cFJj2PQlZ+jLDjYv4vGtj7yhtCVyJRcdkOy+1MkI5Web6KBEvZkfpwAbLxYOB+IfCDfo77buv3isgg8oiEcTkNEdy2xvJXbq4tZa53IytgkloYHGvy5njnnmVMObrWlO21EFdGgTB6DWLJ1YH42bTbv8lJypm5fgIi4LkuTb6EKJn/jigxv+SmX0x8TjDx+bITlzk4bSyyvPcxwkHQe4QD43pEiTgdy49wVHx85b+vOuOEZSvZbkRWACzCWDNSrNDbD5mcKVpF5dz3a8QCdaJz/gZEAf9rzEaITv5ui6z+6rOQjPoO63xghXQ1llsCSijgzfUzkAnrt4FTy5VnQmXY2RT6Xl0WsSZ90Vz/p8m3JmRC5LF+5EkLsjHsfODbhKsRNkPa48DHfx6pW5cj7bY7URoXlzFIvTuLYpllLDIoWxdY3jr/fZNWr5pwz0oQTtDfbYUopQJXMG49CdrkXcy79425Ly6cE5G2bGf3mahvsr5rHxPeE5jJoBLP7YWfPmA3ZGKn0Y0zhfUksQU8jss5X/ni3PMzpI1uiPtO695zcDanL/Pusc7vG5B2veSGkkhbNgdLji4VJv1we4IokgIXNImt6pF6GKx2PBdp73+M2asCmUyeh/TTkXsWEC2j2YqftGVaL3Wm2geFruEeQ9rWWBegCd7npsfBiNx3PWKAlQNWQ9rk+0wdfoOwT5hLsdvTQG4KLN4DX+VF440kda6CuKQezmCFUaosW/ecjExa2Qr4N5Dxx27IaoX5yN5G+yH7TlxBOEmfx7gRKxHGDsgqnIMpbP+D+rkWMiG3h3VtLRK2M4jMPxcxGPgAsYAPxpGV7Ktity9fw1mlZV0baLuZp9DiPaqtSerK007P1Uz+HIqMP1YoFYZ1LVX5zFxLfSxI5WPnROFUIy56DJ+j6h+gh6eMFpceeeB3FFoaxingaxHh6JuIIPYOZtNHc71U4/IV0wgV7Loecd+3TcMTabEVFwaiQL3b6hjyiGXrdub6ZoiV5QJEARJYW66LKBgWYCkqyqTb3xBLyp+SUAEPjEIsrjsp7b9wIsUC6rmIdd4k8/sbiAX3VMTtxa2Ia4EgTpXM2AeCVpPJ11lUOFhxwmtyrl2DDKJ3iHhuX0If8LYF/IdYkycJ8+SrVtlqINyA8g1EIfMFZEB3B2IR9i3EzUVgIdAObOK807Wm8ZY3hMJyLSKwunGZj+WiKSI/7XDi6szFiAD1jEmPYKnviohybQbw3agwECvMd0ngixup00GdnI8oin9nwuzzqY1YrLYjCoaSFjs4bgac+5oQv4WfIxawnyNC47UUuqA4Esf/KgkGKda9PwNmW78bEKX7Z+a9HyMK0leAnUrlv4lPF8WrK1ZABMi7EDcFGyDK2Lwpd2eaMviiKWdLm+fqsVbWRMXHR/7juT2Lqw/m/6uQNuBXGOW4dS3w3V5yU2JCtx55k27LONdvoFgBX4tMlrxrnvmGdX+pPvN5wjpzPYUbqUYq4E2+32vKy14Jw6kx37vIlKcJzvVJyOD7n0g9ehexRMwDh1eSH+Z9zYhrjwWIReVWJo43Adsgg7kjEBljNs5Aqcy7V8OaYLHOfx3pl3vM+/6B2VzdXP8+0vacnCTNrHsCV0olJ1OQdq6bMv5WnWeakImq3xBjLR3xjK2A/xplNhjHXx/wcyvdL8XacNL67igL+GlxeU/Yfkf1AanlS8Q79jDv+CGhoicqrPWQvmHvhO/9OaIIWdk6F8T5Ugo3n7fTbgTi5/keInygR4TzY+CBuO8u8+yayIRl2b0RzP2BO64tkH75W4gy5F3gr8F7kI0HpxOxAoFoOcCWqdOWab3UmWodiALuEDve5tu/g8g0X3TL3ADDO9TUnzso3PS+BlFUHobIBB8BxznP7oz0HcE+D4GyusjPdyVl28n/KMvW1MPxFRcrrDxmPyHCdixQwL+N9P2X4Uy+IGPbbbD60xLfcoapOyvY+WyFNc98x6MYmdlcW5sy7YyJwyzznrHIGONjRLZJrIB30itYUVMUNwbWbgYTCie46TCQMMrVyYTvSFM+S30sSD/HzpUePuKix/A6qv4BenjIZLH0vRPpUDuRAbu99DZOAb8yIvjfiNnd2pwv1+gHlu8nRXUAhALzSsjM9SHmd5LO4lfIhqtXIBYpuyEK9tnI7Peh5r7JhJuSLUQmDz5BhAF7EqGkewhEKPwDImT/nDIKeMTa62TTqMZuemga6fmIkn4F59pjyGA0SKdNkMHex4Q7eF9lviFJmkX5Cw6shRIPVpyO40QT78Cy7RTzXYGrGduK5hJEmF7bfhfS0T+LLLPfpFw8zHO7m3BuwFh6ESrgX0eU+R2m3I5wnp2AWL/t45w/HVHiBNY03vImqm4gQoQbl+akdSTinZcQbkRTZBmJ1JUXzfdfi1iMNiBCYzBZVdadhXnXxogF5quIu5HvINYv85HBxYPIYG9HQiX0xU55SboaIaijowmtEm5H/B6Oce4NNqNNVM4iwtoLaQOmIj6ZnzB5/TdkUDjalOdPgFtK1Bt3kuc04BSnXvUg7VkHMkC5FLMMGWmPAkvXosFJVPnwkf9Usc649cf6/wZC5XjQPh9Iwk2Jkcnaucgk4dPIpEESBfwkZLLRbu/KWVUfhAw4bzfpcROFFjyuAr5v5Q6FqzmSuG3IIXWuB1HAR5WJZmQS/SbCQUciRWLMu+4y6b4ImQh1J2lakUF05Iop517bDdw0kwdNyGTVbwiXyF+IWKwuRKxvV7feYbv3iUuzzZA+cmcTVhOyemYaEZN41u+NTbnZqoI0WtWkT9LN2fv2GYgIvyptgPWuYKPJmUgdn4u4B9g+Kg7m/+0QBWc3Ihe6cZqE8UnsM18i4jbGpNMHGAv6iLjUI7Lvs1iTaGXeG2xydzWFSskbzPnzKbZsb0LajZkkX5FwIaIQbooqJwmeH53gnvHW/zUmjy7AuBhDJs1+gcjkv0eUPLOBm0u80+03fci03upMtQ6kLe5CFK7fxRjCmDx7F7MvVoXv3AGRA25BVli5k6OHIvX891h9pHPPCm4eIUquYHwRbOIc/LYnpK4E7kn4rXb+H46MJeucd6Uajq+4mPPXIBNh2zrnbaX464gu4AjreqMbhvut1rlAznsE+FNEnJYnNIz4GiIz/x1rxTsl2hnEKGIe0m4E370EFSrgKZbLu4mxtmfg7WbZvT4GGkZ/DwZZPrOe8TYWDPKaQR47VysuemT/qPoH6OEpo6Wyz0KWwn6IDPSTKODHOfclsRBrQHwi/ofSG1NtbxqvRJYhhJbVe+F0zoil0TRz/atOGMchg78DsPyMl4sLoRBRgyhFSing/4ZYw5xAsRWWa/Fei7gleNB0EP+i0B/1l5DBw0nWuSbEIiBQ+n2j1Ldbz/0AmWw5AljXudaKWKLOpcxgJaLj6A6+AfGfdropX39znrsQEZR2j3onMrP+FhXM/pq8/AyxELUV8DshQtxCwkFE4Is5SkisM3n7JOESNm95U6rcIZ14QVz6+a6vIQOrLxOtlAmE1LUQ4XWuicMcZFLkNQqVw0ks+DdEFK6vEU6GrY1Yjz+CCHnTzfVgmfFl7rsJhZhYAcX6/lzc95n8OQdRwJV0MxIXT1OGzkKEr0XIBOA3KF6CeTeiVGiJiU83oQJhCUSJ8w6WT3BEQXy+SZPJhP4Ygzhug7SbX04Qj9TznyFQZ9zvsf6/ARlsXmzyayGVuRo5AxHmLzRl9TkcX/GECviLMe5pKGwvk0yQrmnCOQRRTuQRi9AoBXw7ouAcGfXNZcIJ2vhaChXw49x7rN+7E+M3v4I8aSacDD8eI1MQoTwuky8XmPpRj7TfpyH1cQ7SrixAJubtDb0PMOFGrciKC+dnyKTLp4hSLthcdx8T3lSsjebstDP3v0CEz/YS5Ww9E4cvR+WB88woSri3irjfWx9grm9uyvI9yCqE60ya9Zi6smfMd+yKpdC2ztv12Uu+xMQrSKc1Tfhv4MgtiIIi2OehoqXkhNZ11xL6rs0BtxFO9O6OTERsg6wqmkuZjfWcMI5GFN3jKvy2shM8Vv18FqdvQiZXXgFONL9HI5Nlz5vjTRPHEyPeGawACIwjfMi0XutMtQ5EBtkUqZdvmXJ7FbLC4xxTxjeo4H0XIXX/LWTF1ByTLn9B5MIgPw4hVMDbfZzb9xStTkSMwvKIPDfZuf9CkxdJZCM7/4837zzAZzi+4mLOB9biRdb1zn0bmHx/Ccv3OuXHy24bcTNS592VhxsidTcwINjJlIWbKFb6uu9c2/xd2iobwTg9sQKe4rpfUhFKyu3mQMIYjINBks/ceOJxLBjkNYM0dq52XPTI9lH1D9Aj5Qwu7GSeQpYYHWoa+XuIVsB/DlzZz/CCDm8vROl6J4VuboKGrB5RbPwTx6In5r2Xm2/+UsS7gjBXQWbRn6WE0t9NlzL3lVPAtyKC+jRCtyYlfS877z8VGRB2IYJroDS+BLHCWd75jhYiBpcx7z6UQtc8b5u0OQXLAhgZ3HyKTJYUDVZIIKggExHHmDx/1Jz7KSLMxy4nRgbFJfPKzQvz/4WIIHk9oQK+EbGGewUZAJQcZFvfEDeQTC1vEsQ18GOXKC4l3nMxssFg7JJ06/tHmzp0AqLU+jJmaWqSsuy8cxNEAPqQwk1ym5BNUr+FbID3nimbrp/zQGGWyL+snZdOORlBqAxJulzeVWo2WP+vgAxO2iKeG4tYRfw24trRFCoQgu9dBVFWvxX3fRQOPBuRdvN/OIO1oZD/adYZIqwdy8XJ/H8t4cZhJX1uBs9a+bMdYvW+D+Lu7COkz3IV8NciEyLXYixtynxf0M7WWGGdjPQvLUhbGqWAH4coM/uWjZcJ51xkpcZ2Ud+FWIr3IBNLtgI+bsKy3+4HTLz+ZNLpW1F1qMzzV5l4b2GdWwLZBPkac33D4L2EcsF2Jv8TWW0Rbnp6KI7LFHP9OMINHve3zi+NuE1YQIQSMeI9dnqPRWSI39l5EPPc95BBYKSP7Ij7L8ZzH4Ao8z4hdA+3E9IeTCN0NbArzl4KpcLxlS9l4hWUqY1NXNoRq/tvIu6MbjHfWHafh6i4Etb76yi0gP8pIr/lEYXcAmTi8ttR7ymRv2sictNXknyb844kk3vnIIr0LsS6fR3r2g9Meq3hPHMWYgCRJ2JjamSiIdi7w4tMS5XkJh+HVYbdjcTXNeX4ZZOH3aasHZywHF+IKJ++inGDh7iSOd2c/y+yOjDo7wIf8LeQfIXIFGTMsAui2H+A0H3KL5G+JfEGylb+9xlF+ArHV1zM+ctMXm7hlklktc1lTtkIXND8l+SrsQKXTEF9+yHSDhRN3EOBy7QlERdlJTelJ1wd9DUrjBrnb0UW8IQ+t2Otqc3f1NpNH2EkfMeA5LMS7/U9FhyUsfNQiIse2T2q/gF6eMjkcInyScjy//UR4XQ+xQr45QgH91sPIMwxiLC9CBmcbE1owTkREaLnk8A6CLGkyptvtX0b20JH0IHtbTrTY5x3JBk4nIL4p3RnKl0F/KfIICOYuW9BFHwfA9+znis7GDL/T0YGVz3IrOm3TPpNB8538zHJ+831EcCfEYXRHSY/7kYmV/LIMu8fmbw5HRks2+4h+gQk89td+luHKAMDIaoVEWbazbvmI8J21EB6X2DHfuRROQW87QP+FZwNmyLeF2nJm3beJKxDth+7snGJyf9XSDCRZvK61EAzThG0ssnj3ZBVJvVW+QkElXeJqefm+fWd76hFXF7sNZC0NOXgZ4hC8/tJypkpU6+b8Fcp9QzFrgaOQFZk7Ofc12rq3eFR5QwZuD+PKOBtC/g6p/61EU4knDgU8t+Ni/l/0OuMed9vcVxJVfBNt1BoeR/VJkVuEI70O0+Y/7+B+LCPUsD/Efhmgu86GumLV3DOr40oDo82v79HtAJ+As6y8ZhwAovRvCnTHyEK0D2xVo4hSrI8ogSbUO69SfMs5v7Ax+hsRNHYlvC5gs3oYupjkQ9upD/4oakHSSzRj0NWo+zixs0pT0ci7VrelPF/InX4QwplgLh28xrE73XgQqcRcW83C6v9cJ9HlPQ3INb9SfxZe2kDCFeYBW3aOshE/E3OfacRWogtNN9WdlLUV74kLIuBvLM0otR6GZF3PjN5c6B1b9wE38qIm5KiyQcKFfCrWecnIYrofZG+NdIPfJlvH4/Irz9Icn9UeiFK0y841+082BjpRxci1rOnW9fuQiz43c1lN8JsTpugPKcm0/qsM9U4EFnkt8jk11+I6PNMud4OGevMQfqOchs5b2vq2wF2Wpu/LabefoRMsthu0g4itIwfUyaM3yETXsuY37sistDdJk7zsXyHO88uh+WqrUz+px6Ox7jUIPJYUDcmO+/6pQl3L/sZ83dDRIn4IeUNmYKJT3sCrA1pG/+L2fPHfr/5vx6RD/9DGSMMRLH+BiJ/HUSogHeN8GwF/EXEt8GnErOPSMS9qbSbaYcRF/cS7+qXfGaeTX0sWMG3DHTsPGTiokc2j6p/gB4pZKoonI7Gsjox55dDhNRTze8jkQHSvRRap08iweA+wXeMQ5YwfYx08P9CBphPIR26LZSXU+4EO0n/Gkdp4dy3AjJIu77Cbw3S5lXTuMYp4GtNes3E8mGKCLX2QCmJlagbxnaIRVseWbJ3OSKE7VFJXMy7ggmXFsQdxFuYTh1Z4XAI0snORJSTwTLqwHLMHaScgLWBLLL0/7emE1rHCm8EIoi9BvzPTT/zf7DhYVkhA7EGcJei2u/6JSIoXBeUC6Sj3N7EeQZlhHrfeVPhd9SasCuOi8mL/2Issd10jLj/GIxlcsL3n2fev4jCjSmPJhwcbGLS7V0sJQvORk5unSEUpMsqmGK+7WuIO5d/UGLTY+eZVQg3UM0j/lx/iCg7+9x1RDy3OjKAmIel5HfzIi5/zd+VkQHIWxRaVAQDi32Rtu8Tkk8kpJr/Ec+n2Z7dh7RVG8blQ6n0jStn1rlgk8g/I6u2bMXWOqb87oO0i8eb30UuaMrli6kzeVOXP0EmKzezrl+KDHiDchFYe91AhH/cMuV5b0TB242sPDgHGbjmkbb+DsS9wOrIZl8LkX426Uqk/tbNYHPRPI6MEnP/1cRvRududm63ISOpwAUIMtl1uwkvcpWF8/71EYvqm81zJ1MoE8QN+q9B+qxtnPOrIsr3F+w6gtUWIv32RyTY8M48k3YfcCaFvnqD9mqkqUt9+7kA/2fy/GxE3joVkQlPLhOGl3ypsAzb8mATIjOPo1A2icv/HyFyZgeigNvfzRfClVLXkXAFX8T5n5k0OxVZrRVYI9+G2ZeEBO0ohXJgsCnhVyPus/OgDtk0/Hmkzf+7yZeDEWOcI03aJV5dQ8oyra86U60DUay9iExI/RVZPZen0LWI24cfjshEU8q8+wSk31oh5nodopjvAi50rh2Js7lqxPPXmO9wDXZ2JdwI8tioeJgy9ypO/4n0467Fe+rh+IqLOR8YvB1KaMC2njl3IdI37hyR3kGfsxkJLN/Ntz+HTNZsas41IEryGab+rUfhKtI2pH+eTxljEkL5e7SJ/zTzbNAmuAr4sYgblc+BayPel0Pk6WMirqXebnoKw4t8Zp5JfSzYj3j0a+w8FOOiR/aOqn+AHoOcoeEMdCcy+LkBWArjSgGx7n4F2fSoGbHWnItYpLRFvG9AjQUidC2LzEDfgyjez8Xq8OPCoFgQDCwBL8ERdp1O6Dngjn5868aIQPo/SivgG5Dlrjcl+e6EYQfCw/KIIu8dQlcJ9+FYClX47hHIUqjPEGViiznfYo7DTJoGipmznOf3MuePMr8vRgY1f0GsJZdx4jDKlMN5wGNOWdjfdGqxm9Fa93/DhLsHpRXwFyIC3LmEnWMtIhAePAh1alDzptLyUUlcMBsjWb+DDZZWKhU2MiP/MQlcQJn7L0UGt0cjljVrIQrv1xGlwm8IBf+NCQWVkktLnTBuQdql/tSnMYjVwhrWuXIrRUYhCskPkI2ugg0A3zTxWcYpdw3IoPM/Jt7lLKsPJdpdgquAf5PCza62IPT5e0iZMLzkv686QziYWhZpcx9yw0jyLTiDM+f6RkhbNQ9Rfk5FJg8PIZzQu49wUBQo4N9EFKXLueGV+Jb9CC1CbzXhvISs3pmEbDb5Dwrd45xk0u1PJBhAUOjqIdgHYz7iAiCHWIVejlilLTDx/qOVBmdj+og06qZ5vpkEfuQRVzILMcpTCuvf1Sb9i74VmXg4n8omq1Yw6VFu+Xufy7QSZSpOprnalDFX8R68c3tEHnsLmQgJwlgd6VPbiZngs97lqw84hXAiaRfrfNCebYr09ccjqy3yWCsGzT2xVsM+8yXqPf0s1+WMSAK/yz9FFDBPIbL63u7zFCrgV67k+5CJ5HuQ9uVzU6bmIIYjHYgCa3S5NHG+J3BpYfdN55t3TsaaCLPyYgIygfguojC7AFHI30PoHqo//ftgy7RDot9M80Bk779acVoHace7MT6MrXttFz2fAr+IeWdQ138LPBekVVR6IRbJDyL93ZiYe6LO/RppY6bEXA/azAcotDatMXHuAH7qPHOUyf//8xmOr7iY8+ci8mSgoD7Y3Pd7RDE9nwjFu7l3Eo7BSLn8QhSd/0Ta6i+ac6MIVwt+gozVdkb0Dlcg9TeRiy6MYpPkCvglEBklzqVMVHxSbzc9heFFPjP3pj4WTFI+Yu6vSA/gMy56DO+j6h+gxyBlpAg8dchA5z/IIO0HyDK/d5HB/WRE0fAixtrBdGSHE25WVdKPKGKdlcjqMPiuMr+TDIbsmcNYBby5vhGiPEvqp25NZCnvBub3xqbzK6eAvwWx2orckGQQ8nNJRDnTnbRhN/m7h+k4vmbeEQgsIxCLo08Qy6sohcUkLCsrQiFmN8zg2qT754gVaNHGMIQD31HITHyfAh7ZLKyTBBseWnnzKDK4KaeA/535rhWiylqScpZW3iBK22WwFGeVfo8Tl7iB4D6Iwsa2pD0IEYZvJtycrsZ5XwsiqP8lKk8jwjkUEaZ3xmkLkBUgDyIKs/MI3SpsgGxKMw34ToIwrjb5WbRJYoJno5QuSRW1gaL7W4griO0Q37oLzfdcRqEV5feR1RclLSsRq5/A8miFiOu2C5pXkAGqvXx0A6wBfkwYXvLfR51x8xNZzXIKosA/rb91p8Q9RyLWWVMRn/qnmvx+ChnY7Ics6bYnjU9ELNUOqPB7voK0g5ea9x6ATGb+x9SdJ01aNVvPnIE1uVPi3Vch+w7YirDtkb5qflA2CNvpnU2Z+TdiUZ2nzOa3A6mbcfkbc36ESd/ZiB9hd8J1Ns4SXmSwtRMyMfIPChWF5SbfVkOsZgMfx6U2PW016dpY6p3OM4FCL2rj190xrh0QGeZVU1dmm7LxHtIunFwqPvjrA+pNfPKmvE7DbKpOuMS6DVEoBMYgtqu+knKh53wZcP+cMJzLTTymEMpW6yNuUZ4xeeC61DnapN1NWCsry4TTipnUMHnRhshwJyPjgOcJ96cINtYrtynh8RS7tNiQ0DLwM0RhuCeObIlMUq+ATPC9T+gP96IEcZlM+jLtkO03B6nctZjycyVwsXNtVUR27sYZMyF1eBwywfnTqDJi3XsGIutHutWw0v1oU/aWTfjtF5uy8lv3Xc59u5j39imtkdWCncCZdpzM37OAr/sMx1dczLk6pH7PxijCzflAAV/Kuv4gZB+Fdd1vc8LYEWffDgoV8IGs0YqMpe9CJh57TPz+hKUUddMCka92IML6Gpm8eY3yCvjGqDjGxCf1dtNTGF7kM3PtUFIcC+Jp7OwjLnroYR9V/wA9BikjTQeILBk6HLE0fAFRgv4fYrkXDIBmIMtqgoFQKyIUfatMGLcg1vSJN74zzxVYHiboBA80DdxviBDmKFTAr2Cdb0aUJk+TbDO6s5BBz3TgO0EDjwgKgQJ+U/d7TZr+GbOcrVx8+pGXdmexbtT5iGd+jijs5iGCTx5RpnyXcNMze7ByNka5Q8SES1QHh1gTvYNsKGV/Y6DICTadWtJKp2ORAec7yATPWaXCcMpyDhkcPGLKbJQCPhC6Jpq4B/6SB31CpD95g0yA/RMRhh7E8Qfen3Bjrv8CUTg9AGzsXPutKQ+XU2yl24wI2zNJ4PvQPPMbU45GOeeDcjACEd6nY5agmvMbIgrGw8u8P7AO3CbmelL/tpVaSeQQRcHdiPXDWuZ8E6IkCTYS7UYE5b3M9dpyYSLKqgNNvO4iWgEfDBjWMXXl9KTx8pn/Aym7SeqMubY31qDRnFsWUSK/QIL2PSLsg7GWNyPWVxtav7+JtPnPIpbGK5v6+xky0Msj7llsy92y34G4WrvcOXegKUt/RBRTTYgF2x9NOO8QM9FdooxdjbSB20TEfXscqzTn2XGIK5BISzjrvkGpmxWUnQkmLd4jXE79C2I28jbXl0BcXqxS7rucNBqB9Pv3JUjrk5EJi7Kb65r7Tzf5GizJt/eLuASxdF+dsA1YClFs/BiZaDgQYyAQFx88twGmPn6CKB8fNP/v6tzzdcJ9C+rj0rOK+TIo/XOCcE7AsrR2rp0PvBAXL0S5ksea4C0RzjcR2XS2KT+tEfe0mDL3MWIBG6yKrWhTQmRV05NI23gXYvSSRzYqPSGqnCJWsHeb+8opXnzItEO23xzEsrc24UbH10VcXxVRzi/C2cCX0Kp6TecZt2/e19z3Q0rsy2Lq50wcd2Ex916DKCL/jLN6ISYvdzHl5K/IGDGRoY+PcHzFxXnHCohF9a+c84Hbz7sptq7fz4R1Xpl3n4dMCj+J1c+aa0UKeOvaKoh8uwxW2+TGBxmP5xEjwo8QuegExC96oJQeixgSTkdkuwIFvPO+cuOn1NtNT2H4ls9SGwviaezsIy566OEeVf8APQYhE8Ua82bC5TCNiKL0c0S5HCjZjwDuRAay72MpDigcDEZ1XleZRn3HNOJghfMb07h9jAgB8zEbWNkdB4UK+MBf2gHmG5NYI19hwjkGSwFjXbcV8F/CzKAjExWHm7RNZaBmwnFnXkvNPl+CKKcPRwTtUYgFUmB1diPG/YbpQO5DBitnkmCQSjhx8jvEh+pY9zuRGeB2RBA4hXAiYxRiwfAplsVqXHwQJcV/MRsDkUABb+XXLIz1XcplNFHeEFog3IBYHQV+SBP563XT3/wfFfdfmfd+nULraLtO32ny5hlkZn9VZMXHeYiA/oOo8CLCakEE3htLpY15/2zMcmWrDJW0ECNsZ4r2nEAsRBL5MXTSbAXKr+ix7z/M1JsTnHM9SPt0gfnGPDEKwJgwAr+n8yivgH8M+HOp8lWN/O/vkbTOmGvfNGn7LHC2c20bZPLj/ARhutZBtj/MG0werkFhv3Ikogj9J6HVWRvSVv4OY+Xufn9cfKzyHOVXdX+kj7vHybddou4vE9dIdybOPdubNF1AqASuI8JNQFR8fNVNnOXOiAL+fWSwfw8iE0QqIjED+7jwnPNTkEHwuKCMmnRsN+WgJup5ZLXglYg7kLIW1oj/818gyq3fOtcCl2m7W+fK1fco+cxLG0DYjteasnORqReHEBoyuAr4BxEFZ0upd1chX3z1zzWIBec7Jo3WgYLNaY8z6XOr+ZZdcazcSTbJdymyyvVaRGm6VES+BQqqZkSp/LFJr5Ex7wxcC0UqmJEVYnlkw83lTFyCFTT/QSzKV3SeWQXYqExcUpVpfdaZah+mrG2CtP2fIOMZt+6sgkyi/d0pz2vguMpDViHlsRT1Vlp9hsjoQTmz+9YWU+b+RMQqD+ddNyB9zWbAiua5PJY8EPW8yaPAV/Pppe71FY6vuDjP1iDt85WIHO4qwQML+D4FPKHi3bauj+prfmPK0VHEbO5J4WT/plHvI74db0LaldcQVx8XImPC2eZ9jyCK+BWRduF/iFuQQ4jwuZ0grVJvNz2F4XXsRIpjQTz1zT7iooceUUfVP0CPAWZgaO22tfkdNAYNiMJohmlUghnUpYEvkNCfl3mmYDaV4s6yYmsm89tVyAQbq+1vGv0dkI52AdG+kgMF/K8QJfoikg0gT0csQXZyOxansd4YsbyZBvwEUQr9Ghksn5Ekzh7yfz9kMmW3qPgig5i8+e5gWXsLMgM/E7EuKulGCBHex5rO8Dhzzha01kasOC9FBkGLEOukseZ6G4UTPaWE7jMQC6qHCTcGilLAN1nPNCLKtdeJmEipUr5cjQgLOxAuUdvFnLu6gvfY5fE0xBrLtrQ+FBHqdovKR+fe8xDXBXlEqG1HXKp8y7qnnOKnBRGq73Tfb78DUTg9ifHR7ZbNmLL6I/NtUZa7FyPKi7JL753nvoMs61/WuWcTk3aHxTw3FXjT/H8A4UaBwSTcJPoxEUkJBTyWIIcM9n+a4H1e89/HgbgXmI8oA15DXL9sTegH8yITh1gFtZOXxyHtk7vh2XbWPVEK+GcJ+9VaKl/xVdIKydwTKODvImKZd5L8wGprIq7tSeG+B9sRKuCDjTCTbOzlpW4iirBu4JfOcxMQn/954Ccx7zsIUf7Gprd177mmbD1A4Ubp4xFF/9uItXmB/3DEevtgRPmQePLdvPeHiCLvJnPufEpY8Fvlrpyy2ksbQLQ18Z6IEnITxAIsUPDtan1/sGfB0eXKs698wV//fLOJfw2wFSKrPUe4cfRkkwcfmHjPN2k1Ddl871vO++Ly5iJCxecY9/sodL8QpF0Tokj7HNnrxJWFRyAyXdGKWOu9Ywg38Wwz5yYhqyOnI7LgdJMGRfUyKj74kWkz12+WiW8dUkdfId6l5rLEKESd+9ZAJj86nTSYbMr2J0hdHO+UpcA46tAy3/pVxPDJduW3MmIwlURpvSuW67QSdSb1cHzFpURa7oTlqo/CiaVAAX8nMpYuuzIZGWd9ZOqNvXlqVD3diQplDUKXUmMI2/M/mrK5GtKH3o/ICMFKgqA9+A+ysiZxGuGh3fQUhrexk3U9lbEgnvpmH3HRQ4+4o+ofoMcAMi9UVsctMWpEhMzpyOZqRTOo5Toq0wHMJGK3e0RJUrELCKKXvV+BbDyyrXN+W0Rg29c6ZwvGpxL6sLM3VosTuMYhvmDPxlLglvjuZRDFyHuEs+6pC91JG3FkoPE4lmIIx5IRmW1vB7ayzrUgA4jIzWgiwmlCZuJ/7n4nomj/qXXuTyY/ijY5SZJeiFXD+yatJ1vhrIpsOvk5MtmyFDJJcywyKPLic61c3pj0yGNm6SncvOpaRJlYZJlXqiMn3Mn+WOeeXyPWYM3O/V9AlFE/Bo60zi9BaFm4Psafaam8ifiuX5rytEHU/dZ9tyPCd0mrc+v+CxDl1E8pVIZeaOrergne4Spdeyi20PoR4ppgNjKwXj3iPUcjg5H7TbqfS7iyqKyVcJlvdBXwq1rXWhA3YdOBPRK8K/X891Fn3PARxfU7yKDrTsTdzFXI5PFKiBLhEaInZV2Ld3tZ7rXEWwfZg6AjEEvrZ4Et+xGXK4hRvONYbRMq4P8ErF1hurptjT24/g0yWbmGkybbIW1QN7BFwnB81c2lkXbjA+AC59p4RGH2LqKgCxRF9mZ0JZfLW+nyCVLHbTdIwcB3fUT5+YmJbxvS/6yNKBEX0I/Jd0T2ONPk15tI/d8uqjwhystEZQE/fcC5yITkxlhWe+babcCjiKJ9R8Tt3ycYAw9k4n42jl/iauULnvpnxGKvAzNJa741UMA/YcrsfGTl6krmnuUQhd3vTPk4NkF89kYU9/s53xRYUq5hyojtYsJW8txI/KaEkRsvO+H8DGlL9rLOHY7U7xuQ1SqBjF6k9I14d+oyLYtJv9mfw+TpFogl8NqEbjoCBXzsnlal4kNh37Iy4nqvrw1H2uEtEev5HqRNOAlRfAUT0UmMo8bguDIx51ciodI64bXUw/EYF9sYyd2b4GakzVzGfY8p60HdjLWuN/WvHumbL8GxMEfara2Q/Ww2t87vREJZA+kbf0UoZ49G9BfzEEMM203N6oic/AjiJz2IQ+L9d/DQbvoIw/zvSz5LdSyI37Gzl3GtHnpEHVX/AD36mXGh9V6UtdsUQouQBkIF/ItWx1Z2CZJpjPJEW75caK6V3JTF3OsqQz6l0H/pasjg7BUcRRgycHsDsTpfgwhfgcimhydbv0sJKRuaTiWR0sF6bpI5xsaFYzq+Iyt5b4L0ivWNiAhDUwndU0S6dkB8c75NOKsbdPyJlqGZe5uQpX+PEAoWttVZHaHQsCEySC5rgRj1veb/E8w3PxKUMUQAXJ7QL/JniJL+Qwpd2kQNKLzkDSL4noMojx4n3FwncP30S5NnlyD+L3eJ+d4oQegI555aZHPFqc75kwitRIPjd5RYkhn1DRH3BEvv9kKsHe8mVBrknPybgExy/TjBey9DdpUfa9IuD/zMXAvcMpSyDs25cbDS7Ejn3isJ3U2tV+KdbYR+vo8j4VL2CspRHaJ8mYNYUvwfoY/ndqyJxFL5kWb++6ozzr3ByoIlkP7qJ+b3UYR+pXc09Wgu8E27bDrvOh4Z9AWK94uRgdwmFCtzLgS+TaGwHyjgn8RRwJeJwwUmzYtWl5lwZgArO+f3RwZJ95Yql266IvuWBG3NeCecuRS6M7Hju6Mp3yVdtHmum0H7shTiJ38axQr4wAXNu8iAtpZwA9uzrPvilCEnm/TalRKu9pCJ3n8iE3CLTJgfIyvhTkwQziREwTLeOR8o4D8C/u7G3fwf+OQ9JUEZSL0PQNrK4B3vIBOG/0fY3++BTCasb/1+CumX9zLnVigTD1/54qV/Jtxc151oCxTwQd78kcI9JOxyUOQTOCZOFyATHku78UdksXYT1k1YEzo4qwfKlIGi8kwoR44x6fkX8zvw8/9DQllxB4zLrzJxSV2mxbPc5PNALDOfQFaBtiP18irMhBmhAv5/SP+aqF9DZL6jKRy32Qr4vr2WEKXpT5HxwhxETv8jJTbXDMo70e5q7LpWsdK6GuH4iou5/2dI3d7bOR/U70C2OB2jmHe+4+skGD8jMsAHOC7/kLH5f6w60wmcal0vK2uYOvk4Ihv9iFBPMQrRX8xC5L/REc+ugkxYHhL3/pgwfbSbqYaBR/nMzS/zdy8GaSyIx7Fz2nHRQ49yR9U/QI9+ZJoItXmM4EThYOVSxLJhktWwBgr4j5BOMNKHWEQ4gbuFezHLxsz5i5CBfVl/xxENYZ7ijZvqTUM6zTSua1qdzzaI4DAf6dSnITPFeyMCTiLfu9b1L5n3bOx+n/vNiHBZZKUf9RwyqH7INPQHDiBv3aVSb2Ap/CPu/wvwz7jvstL3LuDfSeIScT0QFg4z+fc9+5rzzSOQ2euHiLBKjXh3s/PbXsr4GLK7+CM4CilgH8Tn3REUWlpECfVe8oZwo9hgqf2HiOIuOL+RKcvzkAmoQFh9GlEKbxoRTiA8FFk/IILBJYhgeobJn2DVwb8QoXtTxLo7jyVgJ4zvV5FNb87BbD5qXbvIvPNmLLcWQR4iVlcfUcYHP+HgYyvzewJiZZlHNtacQ/zGijsSWvOUTTOk3fwEx90UYVuztHP/t4mZfBysA2mPXkVWFy1Elm0fV6o8+8h/X3XGypcLnXP1iPL8CYy/UsQK/gJk8uRKpB1/hehJsMAXcaB43938/ktEPgfK8l3cNDdp+r7Jo4mUbytHIEr+vImvbb1ZcjCErCSLVNqXCC9oaz4A/mHOnUeMOxMnP5Yv825vdTPi+YmIwqaUAv4txFIuyXL5HGLlehcyiGt0vmsiYi3aZ3GODPynIKvrzkFkjnXK1U1kQuS/Jg+exEwQOd8fWMDfbJ0PJuQ6gR8mrV+k2AeYMLZElOn/QlYC/Rjpwx7CKLwRS7A/WM/sYu5fhChKA5kqyqLSV7546Z8Rd0K2fB4V560QBeh/KHTJV4klcg3S174IXBbxbaua+PwSUVbkgVvstIprG5KWZ0Lf/+cj7cENJpw+BVrS+FjXU5Vp8VBnqnEgfc9/EJeNwUTY2yaef8BY65v82hiROX6X4L3nI0r8xyiWw4sU8Na10UhbNxbHMjsijKuRCbQzKd7vwB1j2ErrRO2kz3B8xcU8P9LUuQWE+8fsh7PpLaIw/I9TBxK3NeZaLdIP/BNpf3c0eZ835eM4ZMXL4zj7IRHjuiT4FvO3EanT003di1LA30+4n1jkRFupOFh5kGq76SkMn2OnVMeCeBw7px0XPfRIclT9A/SoMMNE4XwjYil+tXPtQtM47WGdsxXwRyAd9EEVhBco4P+MCAq/QBQIkQoC4mf5j6fEbKrprHZBOt6/IwLbBoRLzo5BBgF/Mp1KHpklL7lxU0Q4G5pnD3W/N+Le7yDCRR1llC7m/jWRJdiVpnGRn0XTcSyizLJj843dwD4x6R7k/68QxVdjkrjEhDWJcJByQsT1RmQZ4+dYfgpLvO8nphMMhCnb6usXJu+vRpZpFyngS5U933mDDObsJZO1yOTAB8jy2+1NfK7FbPKIKDWORhQXXW6a4fiqdq4F+dqEKCi7Tb58ggwo17LuXcqk4e1uXErE+xJTv2YQ+jrd3bnnSnPtfybfJyNC+VkmriWtt4lxAWK+9yxkgu/OmGcD61BXsRWZZqbs/gPxbWkPBAPF+zrmm/9iXdsYEbTuIWb5/WAcyHL5yUh7t1zC8pxq/vuoM+b8EshAtQcRtnckbA8mIr7v/+A88xVEOJ5n4uxafNUgLiwOcc5fasrzVYSKiIuR/mxn51532eqhFcR/LDKo6iH0tfpLE07J5b9YLogqSOegrfnQ5H8HsHlU+UF8dB/snIsa2HmpmyaPv4RY3+2HKJACv69LU1oBP82Ec6qbJjHftQRSn13XaUchbXAwoOt20yiu/kWcDzYKuwJxn/EeIqu5q5ZsFzQ3m3N7k9CC3/4GUmwDrOc3N2G8bNJrOaT9f8ec+4uJ9xbWM3uSzP+6j3zx0j8jbUsesWi82jpf5zxr+4D/JwlXu8TE7QlkIsRVuO2OGEIEloOHm28r65qpH+V5faTdySPt5UjrWqVlLTWZ1med8XmY8nwBsudSoLC6DWkjf4v0PbdSaAG/JuV9cP8aGZMdjLVai8Jx3iqECvhIl5xEyATBb2BJU4/ypj7ORpSvWzv32qvSVkL68zxOuxGX72mH4ysu1nN7E64UnIxMRr6NtD3/QtrfVc31PZC+pV8TSVb+bYrIGUGbPMuUu8nWvZuaayfF1b+o8mv+NiLGfuUU8KMHoc6k1m6mHQZ+x06pjgXxOHZOOy566JH0qPoH6NGPTJOB58VIx36NOfdzyli7IRZGa5Z59yRECbQi4SA48Av3EaL43i7m2Z2QmcE6CgWvuBnIIqt1RAE/A/HjNs80hK519DqI4HFogrT6NpbCAxG6p5q4rG6nj/PcREThm8Rthj0wWANRGJRUWCEWC5vEvCNuWf4kZJAznkJhaJ6J08bWvbZwtwQilF8eF98Kyt4myPK/PLLkbRuks/wSokifSzK/jjWIUrMLcTGzpHXtIlOWtze/TyRUwK9TSRx85A0yQO0gtEBwlWLvmfQKNtpzl1I346wSQGbn824ZcO4JFMcNyAZIX8XyRWrdtywiSJyTJO0I95I4EFGy7IMoCOYDKzr3noJYa+cR5eoCc689MRGlBPyFScfIyTNkr4VgGaW7zPUAxEr8h875XePSDFHqLsJYUUeU6TnIqqDpwB+ta4HrrRWjvnOgR1TaJC3fKea/r/ZsJ/N3HDL4eNmUsWsJrVwnm7CPcZ5dzpTPQ8ulK4WTepcig5ZfIYqyecRPJC8XcS5puzMGace6EeucOcRsEIu0nW69Srq83W5rvoMoo14hXLJrx31/pL0tuTeGr7qJtOvB6opgMP8K0mcHkyPlFPCHuGlRJk9eRCw4tzXpfp0J923zPccjk0B5rP40YV5chVhlbU+oFNkcaf9/H5QfQnksUMAvQtrQDhIq3q17UmkDYsLa3KTNe5g9eBDr1t8gyp5XsVahJS3PHvLFS/9M6ApyX0L5/DrruvvewAL+LcSyvKSv2RLxuwbpt1azy0QQV6u8TTTp/LVBLs9Bev4cae+K9tMoEcYkPMu0eKwzvg6TDz8mXIlyNeKaKygTfzXl9TaKN5+P24TwCJPXe1DGnQ/ig/t6pC0va3hjf7f5ewbS999EaNE7H7Hq3gozBqRQrljZ3H/iUAjHV1zM/fua916HNT5G5LAzCNvKl5H+dFPz/11Imz2QMeByiKvX0xAL7iYn/msj44dDK3xvEgX8IYh+4G9Ym5f2Mx6ptJtph4HHsRMpjwXxOHZOOy566FHJUfUP0KPCDAsb66UQq4TZyIB1PjI7F6Xo2hlnwBJz3zmIsJlHBrvXEc7MBrOl/wY2jHh2fyJcNCADJ3eQsm7ct5gOaWfEZ+EcIjYiiQg7ToG1ugn7CawBASKMzEOUyKu67zYN/xHIwG+nSvLF/F9SYYUIESebb9iCQgVJ3ETFj5DOORCojif0KXgYoUuFKc5zTYjVynQsS6L+ljvz/3qEluk9pgzOQaxUj7HuK6cMqUcEzkUYS3rClRW7OmGehAxSn7DLRLXzBunQZxG/6XEdYuHwNqKEWzKIe1QaUTgATbLhZpSv6zon/G8jk007JnjfZSY/t6KwXu5N4YSInS5jzPfuiliLL+vGxwnjcsLJvAPi7kXauGAZ5c+RAWbgluGsqOdwJgYJ28tvIIqEJexnEEvb55G2blkTzieEPme3oB9Ct69jsPPfR50x528237RCEJ55z3WIpeUsxK/0eMSi62liFHtx6RB33ZTxhSY+B7vxNb/3R/qHos14K0jD0Yg/1jxifTgi4p6g3xyIax93wPIBMvgO2prAnUmBe5aYd3mpm4jC9l1EYbQ1ooQ7kHBztgsx7oEodEETaRnofl9ceUY2OG0ntE6cjShKbV/GO5oyW2S5V+L9J5n3HWLlRZAvv0DamKLVMyYdf4QMQGM3vEtatq1zA24DYsLazJStd7GUbIisVXb/nyrki5f+GZHF52D2YELarUA+L6eAn2KeTbxZoPOOyYhC6iE7HArb8EbEIv1pEshP/SnPiGughcikY8n22NxfNZnWZ51J+yBUWtaZtNkIUVrtQ6gY/TrSr84nuXXtlUi72+ScX8O8+7tYshGyd9c1Jt9OrDAO2yMTV1eY39tRKAs8gEz8THCeaxtq4XgKY6R55wcmze3VnDlzHInIMD2IsvpVkzf9Ls9EG6rZslUdIgu+g2WMEfHMiVHXKVbAf4K4JQzK8QhCK/E9B1hvJjPI7WbaYeB37JTqWBCPY+e046KHHpUeVf8APfqRaYUK+EsQpVJB4279H1i7fbvMO69BBrdnIrOjf0EE6ZsJrV6CGcW/YM26IoPmhTgDe9NwvUfhIO2niDBwnbneZsfJ/F+PKOCnI9Yvq7txT5BGe5m/+5h4/R1L6EAG9+2Ij8RNCTv9lRBFXTvWJp4R79+eYn9+tvAeqbAiVFTlsSzEzbUTEQWJq6gK8ub7Jg+eRXzermfdE+zo/R7izmUrxDri54g1+hmDVe6CMoYI24eb+GyL5TIhrnNCXGws5bzrFpPefzffun3UexDLzjmYndCrnTeU3vR4Iyx3OhQqxca59TSNA7EaPQIRLmLLsnX/+ohlwEsYv9xWvVgCmfw4GPHhG7sPQVR5iUiz75py/BqFA7g4IXIRMpBoJ0J4pLxl1g4mX/d3zteYchxY1wS+ZD/G8tddqkzHxXWAeTfg91WS/77qjFMGdrDO2e3BV5BNj/LA7YgC+y5kZU1TqXwoE0e7X7wIUURcifF9GXwH4UTzWf0JxwlzSUJLpdOx/CAj/WzHIIUTp4Afh/SlZd2Z+KqbVji74/iFRqxRg7w/m1A+mIC4Tfgc40O1H2kUyE2TEcXfuchmZe4G4usjg8JKXC2dhPi9fZ5ws67AwvE8xIrqehPu/hiZylyfSOGqkUEb2FFhH5DwnV80ZettCt1MRPp1r1a+4LF/RtqmjZxzE0iugF86QRj7I/L5+cjqz0Ah1Yosic8jFs6ui4MRyOrVuVj7iQxieT7QysNbTFkrKR8wRGRaX3XG54FMXMzHbI5rytcZyJjrW0nKNaIQfBK4yzl/ArK6Km8d11vXV0P8yx+fIAy3P7ne1JWgvI0yZfdlE04n4obiG0EdtZ4t5eM/9XB8xcVcD1ZutCKrBD9GFJlN9nXz/xLISqK/IQrxPCU2n+xHWcs5YR2CyAGxm4UDK5j6+wIRymbCMUcTIld8ijUBZ+K9RgXfmHq76SkMb2MnUh4L4rdvTn1cq4celR5V/wA9+plxobAbJ+BXau32KeJCJFC0tyJ+3udQuKFlYKn3F9NI7u2GYTXqIyi0XJqAzGAGQtvnyOZAU9xGz3x/4AP+b5Rxl+M8+1tk4LCi+f1VQl/yO1n3nY0I/F3IYGKqaaDfooQfWWTAkEdm5Y/H8nfn3LcmocJqf0SYCBRVZzj3bmXOu77LLjcdxzaEboCWwfJ1bJWFPRHXLB3IwKEdEfAi/TBa547BbFhSQRpXrIhEhIZHEUHjHuDr1rXrTJyuwvHnR6ECPjKtfecNMhjMY6wFKBR4L0cEo2UoVoq9gyxfGz8Y7UCJdPgecCdioZjUJ3IbYiE1HamXtiugHZAJttnm73vIwHs3ZHBXUvlt3nGjKcvbmt/bIu4KXqe8EBlsfnZGkrhEhL060sbdB6xS4r4RyFLhy3DcZ0XceyqWxXJcuU/wbfYApqwSZrDz31edMeevoYS1i3XfKOCbpiy+Z8rcDOALA0yXKBc0VxFaWR9o4nfmQPPVej5wQdNj8mUk0icl8u+dNHyi25p3Tbglw/FVN5HJjnkU+yrNUdjO348Mzmyl9ARTf2NdcSVNoxJlot7U6zeofD+Z/0PkjhcxygFERppn0vZdQh/TLwO/p3ivgcFUvFfUB1RSzilUwJfcPLca+YKn/hmRUU9G2s3xbnwoXKEaq4BPkDe/IfRV2420iUcQKnmWRBQ/CxGF+beBLyAy4QVIO1fWHeAAyvNryCrGkyizUgwPMq2vOlOtA5FTzkVklYtNXgdpuaXJl2C/kXWRsc93y5U/J4wbTbn5NiIX/t7k0X/N7y0ROSmPpWzHMVqIeO9m1v81Vl3Z2uTxdYTWrfuY938PkTdfM78jN5L0HY6vuJQIP7CAdxXwQZhBPRqFWO9Gur6z3tdfGfYoUxY/pHAFV5QBTs6UndeRtqrI3RahcrTVvPOamHDLrXhLvd30FIbXsRMpjgXxPHZOMy566NHfo+ofoMcAMi/aBc215tyXSWbtFizhutA6Fyjg90aE3i854e2PDOhfJV7xHjeI+K4J73REIfGR+f0oYgXQaL2jEbHam4O4uxmdIE2CDaJ2oFCpZSvgd7bOb2G+6XZkQuEECmfZ3c6skVBRHGw8Mw0RQlemeCnuWojCqh2xCOmksKMN4ro0jj9qk6d5CjeeqjH5/QrScd+C+KUOrFyWQPz1b4N08OPi4mLOXWc6nQEptRLky1XI7PVvEWFlFiIwHm6uNyDWIgsRi9kxzvORS8yqkTeIUvZuU84upFBJcCEyufDliPfUIgqE+cBXU0zrOlPOb8esAClTJ1cnHLi1Em6a+4g5ty4y4L4PUTT8FFk6227S+F2Mj+4S3zQSsfzY0Tm/PcmEyOUo9P9a8WCYUFH8Cwo3Ng3atVrEauwdnE08nffkEIVqHpmo28t9VwXf5PpGv50I/7Np5b+vOmPO/Rqp95u76YS4HymaAET88V9ifVtia+QS6ROlgL8c2cCpYAVXf8pZTJiBAn4hcAcV+vcmoaUPxW3NDCwf7zFlwEvdRCzeArkhbn+AYNC9BtJf/9Y53xz17gHkix32WMQCqp0KNqaz44soId5E5JW9kL7gGsyEH+Ky7SDE1/1cymyoPoB4VdQHRKVHgjC+aML4cLDjMZB8wVP/jMhdLyLKgmOA5aPiQIUK+IhwggnLfZH2dyNkxea7WJO1SBtzEIWb1HaYsnakG98UyvMsyu/1krpM67vO+D4QGe01RPZ43dS/eabsTkDa8+sRo6Jp5vgX5ZVi2yGunYJ0b0HcgAVl6VPEYOkL1jNLYzYxj3hflBLxVxQr64P610Bood2IWFHnEWVYsOpiRRLsjeAjHF9xMfeugPTHxyCTYuOs94wiWgEf9JlR+VDKqKQSq+IaxO/7Kya+kXICxZPrtcjY+23KK+D/iLg0zZX67ojnU283PYXhbexEymNBPI6d046LHnoM5Kj6B+hRInOSWae4Av4MxCIpkRIBEWgfNM8dbt+LKKIXYHx5UjggCizgE/kpJexIRyDW5Q+a38shG7e8iwiLU5HlW6OsZ/ckwSY+hH43p0SlITEW8HHf76a/lS4rIlZ5tyKDj78iHemniHXIRlhKK6RT/oNJr+/HhRfxPYFwdyaWQg6xdMkjFjpPmw7pLUpYzUaVJcKlX5Eb6A5iOb7ShLM9ocC4KTIYfYxwKZjtA/4kKthQx1feIFbCX0QUAjcjAu+F5trPiN/0uG+JH8kGDysjVnXLR+VduXxGhJWxCeJzKmJRsSuhtUwgqMxChLv5iHJypPPseoiFx6Flvmldt2xSWC+3I1qITLTEt4I0qUMUuT2mTNoKwGUQRUMH8L2E75uETB6+geUKKWl+OWkQLLH/P1/576vOmGvfMvdfSLEP2QvMte3deJj/xyADtUQ+kZOkF4VC/68JLTiLJhIG60B8wF9IZVbi10R9c5lwItuamDLgtW4iFoGfIe3+pnHvQ+SEx4B/9DePK8ybI5CJmGlOma5o1YH5/yiTXnnCjSldVyM1RGzo69zjqw84hwp9NFvPbo7Ic4cNZn70N1/w1z9fisjM++NsYBmTF7Z8/tsK4n8ZopDY0jm/PtJGR+4VgbSX2yKTWBUrq/tZnpdP8N60ZVovdaaaB2I88KjJ21ZEdrnapN+p5p5JyITVrxFL68BVSdy+WeeaPH6C4g0M9we+hmWNal1b3uTT9xN892rm3kD5aI8dAyXZFGQc+BCh67HWmPfFtWeph+MrLubaKcjqj05kXJ9HDJlOBSaZe0oq4BPkTb9kDev+pSl03xeVZsH+cUFZrEHaqXeIV8C3IavgrjK/k/bHqbebnsLwJp+R8lgQT32zj7joocdAj6p/gB4RmZKwgbHutwX8y5EO/zTrerkB8WbIjN8s4Chzbn3TGLp+fHNWeCuWC4NiFyJ1hMug9rPeNRaxOMkjytd3EIFw06i4RoQTCPU3RDSmcQr4SN/iMe//AWKFWYsoia806bwmxr2O+f73zfffhNnMzzy/KoUbziUdBP3SxOssE3awIeneVqdylPmWO0gubF1u8nvKAMtqOf+EP8DxM0gofF2EKGLsjUzqTNrNR3y8L5HgG7zkDSLczsQobZHlhLciCtj/mPoyJSpNzHnXEjgunNORQVAeESLKpkEleeLcuyYyiPgfMmh1BZVXEWuBZYN3l/juqHifjkwG3gpMLFEv44TISixdkihdRxMue5wB/AlRMD+BLDlM1G5aZXgS4q6lpAKecJCcc68Tbkp6pK/891Vn7PRCXHvNQNzJBOXsYqSul1wO7bwrarO8pZFJgcSrBihUwF+FpYAsUca3AnYigW/ImOfHU6h0jgsn8DufBy4vFfeY50tOJFvlzEvddN49Bel7/k5pBfwfTLh1Scp0fw9TluciCg57P4NKJ/lsheU3kTb1ZWBlc67kRmEReZN6H4C0SZ8B/8CS5yoMa0ArdQYrX/DXPx+JGIvsliSdKZTPAzcd25d7BrHcyyNuPjZxri2PWKTvhfgYrgvKV4nwK12VNWjl2bmelkzrTW6KSd9UFfVIv3w00meeFHH9GpOOkdaacemIrET9xOTxOtb5KF/QtouIWsSFxoc4bsRKxOEmZPwVbBz5PetaDtn/4klz7adEbFI9VMLxFMZvELn0bGSic0lgD8RaN48o2oP6OJLQB/wVOEYOJcIYkKyR4P1HmrT6APHzfpeJSzBBYCvgv2i1ASMQJehnwL4Jw0q93fQRhjnnVT4jxbEgnvpmH3HRQ4/BOKr+AXo4GSJWSE/347mgEV8a2No6n1TJuyWigJ+JKL3nIh140dI1t8Mo0WhdAPw64nywVPFW69zBiPXhOYjgHWy6dmiCb7/GfO/vEeuAH1K8WWKUAv5RIjb8iHh/YFVibzK7qzl3nnPvxeb8dESh9nfEitsOv2yeUKgYusikzbOIZf/27nuQZXnPENPJO+/+Ec7SX+vaz4mZsY8rc+b/fYDdIu75ISKcP0ToNzRwa3QporR0Z/brkI45T3kf717yhnCVwPZ23BEh4hZk0HN3TP4daK4fkiBNr0Cs/H6ICKhFbhZIIAyUuwdx87GX+X8VRHB7nUJBZRQiqHyGLCmtSOGIKBo+QgYeG5f7TkIh8n9Y+wEkDKuhwvt3N2n9FOJH8GwKN2SOVF463xu0jZMooYA36XiGSd/lnXcEivfA4j31/PdVZ8y1euv/OpO/M5HNRn9t6kVRu2HuHxn3Xue+UxEr6XcQZUDiQS7Rivy4NuBHiNB+H9bm0v09yqTbvsiS2PuRgcn1pb45SRmgsE3yVjdj3j2FEgp4ZPD0AqElZ7/dOSW8fxKW5W6ZvClVt+w++RuEPrMDNx1JfC176QOs+wI3gieWi3upcAbzmyrNFzz1z+b+65BJ2/6szJuIJZ8neG4vkzcPAF+0zm+FyLpdhEqgGxDlVUWTKGmX55g0H2yZ1mudse4fi6wUW7KS5/pzIMrxQEl6snU+kEOWM2nwi6R5g7h4/AiZSGqwzkcpwez8m4AoRtuxfOOXK0fIhNrbyAqwQGl9qnPv1835b1WaJz7C8RiXq5E2bVecjTrN9WvMu39JuBFlK2JI8DnS7iUpA6nJGoic8QHSXv4IMegI9vD5GaZtN3X2DcKJhsMR2XMB/dhYGT/tZmph4HfslOpYEL99c+rjWj30GIyj6h+gh5Mhonz+BFlu1a9BUNxvc25FZOn3rsgu6K3Wta2QDrgDeNw6X7FFB6FvxwVYs7aEnfJPzfWNEUVMHlH62w3vOgnCudk0olNMo/pz0yGeSWkF/D7I4P95Si8bDmZsiyw7gNsQpdQy5vfBJh4nmbQ91lxP5A8VEWiXwSinnWs/M+++BWdjL0Tg+gsidNVE5bt1fwPiTqgTsXa18+ZCRCjaMcG32ml5IiJo7BZz/RREqHokyFPElcVCYpa7I9a4Jb/DV94gk0iLcKzVrLIcCBHTEIHRdnOyv4nnOQnC+THi6mMnrMEjobA/htBtT6k8ttN+L2Ap5/pahK5XgnevgvgRdQUV21fegyS0JkME6A+QdqYoLk75tb93W0TpNh1YLWFYv7HTvdIDx8LL/UZzzl2BU2s/S7wCfgziT7AT+LHzDtfiPfX8x2979gNkQtR2WVOH+A8O+oa9ouKDDAgvpoxSg1Dp8gMqUGq56UVYZ+OUe4F14LHAev0Jp1y+Rdx7H+LS4xxTfhIvC3fKwNbONW91s8w3TiFaAd+IbGD5X2CLhO/5P1PPtupPWif83rUS3ue67HgVaVvLppmPNsAuQ6bs1yFy1EJgw8Eqzx7zxUv/bJ4Za9qBpPfb8nUiC3HgUGSFTPCdeyPt5UOIW5UvIAqJexDZ63uIbDXb3Dcb4ypyCJRnHzKttzrj3N+AKN7+TYKxyiCU82WQiea5SN/Q5lxvQyagL07wrhzSzt5p6kS9E/9lEIvkPXDaBMRN6B9IvpFzkA815htvRiy010I2ksw771kSWYnzOhVMavgIx2NcrkTkI7dNc32n/87ct611rhWR5RJvhE0KsgahLmNnLEMKYG2kXucRN5ATzPlJiP7hQ2RS5zHg2+XKl3U99XbTUxhn42/slOpYEL99c+rjWj30GKyj6h+gh5MhsjFLF2YpWT+ej7VKR5Tb/0U618DH7dMULrefgnTEsyh0FVKJ+4drTAdwNTKjXuQLEpkAaEeWsXYhrmhGlIuD847tTMO6k3VuNLKzeBIF/EEYNzsx7/85MhGxrpOOOev5PKJc/gbhhjojrHuLBh0xYf0AWX71OeKeYVM3LUxH1oN0zrZC7WBkJcF+CcNqRpavdpo8qkEU7/OBXZOWMfP/8Sb/itLRSbPvIAr4+5CVB3OBK6LeWeo9vvMGUe7lEQuXrSPCCTr5YBndNMSqq4aEmx6b8xub/P8GhUt7A+XuOsDjiCK0yf6GEnlznPn2IpceiKXOHAqtClclXlA5EKnLz5ZLN2BZpF05xb3XvGsFnMGqk4c7k9y/9zUmHlslub9EmKXKX7BM/jbEd3mrcz3w8TmJUAH/ZWRwdjyOj29z79fM+UDxnnr+47c9q0OsnKYjdchVwD+BaTco9gEfLIMuafGEDO6mI0qXRN8V856iVV3O9e8QDobq4+4tVYYiwplEjKWhlee7I8uOD0EUTHngauu+ODcCUWVgM/PbW91MmPZTCBXwG5tzQf9wQoLnL0KUQB8h/Vces3dNf8oAMTIHoiy4h4TWzk6afQsxECi5WTCe+gBkleOS9nciGy2+j1gojksYRzuc/bEmSjzmS+r9sxPPJRE55jzzO9Yqm3AD70os5K8z8VndiUeg5HnG1I3LcKxhkdUiR5FA6eapPKcu0/qqMxH31yO+gR/AuG+rtGz350CU4j9Exm+/wXLriSj+3iehpTCyaedHwE+c80chVrSBlX0HcLS51oy01ffibJob8f7jECMbt5zuavJ8E2Qz3RsoVloHEzNlJwN9hOMrLub+CYiBxIdEtGl2eiMrKd8B7nXKfV3UcxHvSUXWQOSbpxHZqd59ByID/hqRAY903rkioshe0o1viTRLvd30FIZ3+YyUxoJ4Gjv7iIseegz2UfUP0MNkRNgJrm0aj0PN7375PMbakd78vgxRVByHKF/WQSzO30Fmzm1fb18i9AFf0YAJUYbNRgbVuyFC4rbu95nfgXX8jysJw3p+JKGVph33NhIq4OPOEfrmXIjxwU/xJlM5pKNcYOL5Qwpn+PtmpqPCtO67GhG2LkeEt3dNXk12y4DpnILBygTgK6aTOj3u/TFhNgHHIMLPG4jQULTZSZkyVuAyI+Z++9u/iwwOuoE/lEuXEu/0kjfIAHUmMrB7F1klsQ2h0BAnRLyPWEIkFh4QoXcGsKab1ojQv8DE+RPzPUUDyYi8iRJsg2/dFKnfl1EoFJcSVI4g2cbHG5g0/7Jzfj/Eh+tsk3e3ES477bM+jis/MfnzGQn9jfbnQAYJ15q070La5tdNWqxl3Rfk1SSk7r4OXG+eK9rEE/EZaVvIp5r/+G3PgntakLbtY5NXrgI+cEHzDUJXVAdiXIdFxcs6tzqidDmeBG4Jyn2r+f9QxFLJVg6NQJRUP0csBe37l0KWEu9KmeXEznPfRdw3LGedi5qgnoAsI/6pSftgr4LYQXFEGejGagPwVDcrzIMpSFv0KKKwK5v/5vxPEOXRPkjbu4nJq5kksPyNSbONIq5fjSiQt6kwXnbfF+mH2bk/9T4A2fQsj1gVu4P4X5m0/2q5/HXCOcE8t6fnfPHSP7t5BzyMGI20lHnuEES2SjqZESzPt61Y7VU5exLuVTLFuifSt3OJ70q9PONJpsWT3OSEGexf8gaitGlw4zQYB6LoPhgZp33BOr804i+/GxmnfQ+xiH8SMa6K3FQ14v0NiNX+E4SbQAYKxrcQy91vIUrFnqC8IBMPJRWj5vvyiGLrMozcSFgX/wT80bxrNUJZKXAzNgrLf3WJOKQejq+4OGGuR4k2zcnDe4HnY94T1W+nLmsgOoQuSsjmyGTFQ0hfEdtGRsXBuZ56u+kjDHPem3xGimNBPI6d046LHnqkcVT9A4b7AWxoGoCgMWhCBJ9LrXvKKigp7AiPR4TOwMf2YaZR24ViFwsrAH9GrBt+ap3fAvFl2I619KvMN1xtGr5A2b4asuToW1Hfisy2z0KElUQCo3nuK4hi6CSsjTgonO1vo4QCPkE8ZiIC7bOI0LWRuRY08sGyqX0Ry547KomDFVaw8em21ru3M2XgLkQQcpeXXWTS9W6kIz7LulbJZE0j4kdyLuL7zF76W07gCYStIsW7+w0UDrRORiw6pmIGTBV+s5e8QZbCzbbK8rrmu5+nvBDxR4qtX8oJDxcDr0ecXxpR1P0GWT79nInTMcRbziaZFKlFViG8EeS7lW72Ur2dCdumWGsa590bI8vAz0GE+kmEGyLPRAbjdyNt1D2V1hkTRmBNlGi1R4n3uJaVUULsQSY+lyED3adM2B+Y32s5969o8igPfNctA1FlIc38x2N7Zn1DUGZaCDcBu5p4BfxRiKJhEckUYjshfVMi1wml8t78H6xQ2M+5ZxyiuDnXOf9/VjkIrAP3jipDEXnTCRxjnbvIvONMrFVc5toBSDu0AbKqK9YqLaYMuJNvqdfNfubFVqZc5rGUbiXyfzukLT6YwnZpV6RPLNrPJEEZONGEv551Luifv9TPeLl9Yal282JS7AOQ/v5cZALxBUQ5cpoT338hPr1jFYoR4XRjVr55zBcv/TPwW8Qib4x17jsmLucTKnPdfB6JrJi6nQSyJ6Lc6ZOdS9y3h/n2B3A2+kuYrqmXZzzKtHiWm8x9DYhl6kykLn0pafpXkM6tSD38xOT3axS2i0sjY6C55vrPkb6hyMrYee9pWBNgyArk6YT92GxkFez61j1bmWtF7uZi8r8NUaR9YL7/alOHHkOUcc1Iv/YWxj0GYhkc+DA/p1SZ8xmOr7jYeUZYZ9ajRJtmPXc9ojhvKFcOSVnWIGxvv4r056vbz0V8zzfMs/0yoMFDu+kjDOte7/IZgzwWxPPYOc246KFHWkfVP2A4H4ilR940TA+bzu5QRBF6B9aSQnN/XOcbNRiyB12XIb7U3PcFjdLyiHXDx1jWMIgC/kngmwnicp3pHOznJ5lG+JwSz/0VmRhIuvz1N4RCb6AAOzrm3jZCBfwZJBsEXWE6ti+Z39sjA9J5mGWDFCqTV0EEr2dJaOFkPfsDE4eiZWLI7vCPRuUzMtN9MQkUFeU6LsSy89uELmhK+rk0zxyD5TLDnDsHOCkuXCfNAhc0jxAq4JMIQV7yBtkU7WYcn/PAZFPenqe0EDGOQldIpQTuQAA4ExlIretcXwJZ1jjKOjcdWfpbZPGL+KSOHEBa3xnU+00RBUyRlSliKfA/xGrhy0nyxwnrTmQQ/Rpi2bIQUWRsYa6PJbQo2r7CdweW6HlECT+xkufduJr/i6yBnHv/gbSRgYX2NxFfgYuQ9vtak2Zt5vpKWKuG4spA2vmP3/ZsVawJPOt8CzJAjLOAf8bKT7sslqo3h5s4xPpRtcryGm4ZcfL+eFMPourMkqYMP4goITa3yt87SFv2HUS500mxNbEbToFCHHH3EbjleBWxQrwPGYSNRZQwTwTpgmyq92PzvdfHxLukEokU6+ZADsQC3k6bUvn/DcTKLNj4McjrBkTpVnbTwYi8WYRlAYXIDnnguKhnKoiXK6+5FoQ++4CVgFdM3L5q/v8rcLy5vjciW11RLi5WebZlTR/54qV/xtkozjrfgtTJdkQB2uxcb0Q2WpwBHJygfFyGKHe2dL8H2ZT+O048AjcH92EZnyQIJ/XyjAeZ1nediQm/FZkw7jBlcUKl6VgqbU2+34e48NgYMVZ5H8tFDOKi4nvmG86zno2cNEf69k+RfstetbcyMhb9AbKirNn5lnWRcVzijRyRMeVliPx4M9Jv3YJMKLyCKHrbgeusZ1ZHfMmfNJTC8RiXqPHbZEorLlcD/kkoH5Sa3PUmayATBwspXPWZc+OKrB5cRMINNZ0wUm83fYQREWbq8hkpjQXxOHZOOy566JHmUfUPGM4H4qPvK4jVwp8RwSiwQmhHNnD5IWKdMJZiP2IFy42IsHZDBgqvAVfFfEPQ6K2LCHFnO9fLCpXIsuL3cWaGEeuWl4Db7bCccHc28d0uQTjXIh3hvojF/qYm3Lcxg72IZ9oIN3f9KaV9dK6ELOea4qTrDhQrrGqtBv0I8/7dK8j7OmSiZR4y27tscN78PRNxq3CR+e51KFYg2Vb/UYLbacjS75JuGQhd0HQiA84iBZpV3sYgy8KOsM4vj1iBzqVwkFxKAf9dRMn3OI6LpCGQNzU4dc26th6lhQhXsRJruev8/hJSd39gpXWRgsKU5z9iLMOctPguxZMihwLrY/yUUzjYXQKx0niJiD0mEMF+OgkE46j4IxZU9yLKnW1wFKWIpUwHZil6wry5Epl82wCZiMsDv8C4n6rgPXa6fce8p+gdhALd/jguZMz5XyGTnR1I+30njvumqDLgI//xW2eC5eovm/zYG2lXAgvaEcjk3gzz1/YjX4dY4ha55ykRXuCfPtKFjnPvmUF6RaRZklUieyBt40Jz7xzEZdqGzj0F1oFJwjH5+RMT/+cRhej9SNv4sCnnFyHWdqPNMxMRmaGo30RWFrkygJe6OZhHgvwfT4TbDETx+QJwZZnny1mJX2Pyex7SR30x6tkE8bDD2cn97dybSh8QpCdhXxWU1Y2RVTo/Q+Sqm5G24m5EORNb/0uU51TzxYpL2v1zSWtHxDL0eVNH7kA2exuLyMLfN+XmjKh4Oe/ZzuTFrTiyNmI53xHkA9FuDp4imcGEj/LsQ6b1VmcSpEUrhXJz2Xyo4N0XYE1gIIZMd+H4aEcU8GebNLgwKu7WvfVI3/8C0r9ErhqjsJ+oR+Sjt4lw/eQ8dziFK0SWRyb/52FWjpl4XIsortsRowbb/droBGmTeji+4mLu2wfpzx9H2oEzsTbTJV4B34BMGr1Igj2PSFHWQFbXb0TYPo1HZMGXMHu5uPXO/N4GmRDYvML6kXq76SMMO01If+x0KCmPBfHQN/uKix56pHlU/QOG2+F2Ps61iYgVQrBRxd+QAUCX6aCeRmZbzzD328rMuIFKC6JoudP8LrKKQITmOkR4eABRxCReLm2uxylsHwOeiLm2EbAXJTY2su4NOrv1KRScNzZptatzv92RjUYUdcfFvNt+32jrfzt9oxRWtp/+mW7aJ4hTA+LjeD7iN3Alc34DE9cZ5gisQl9ELBH2dt4TNUgZQ2jlUrBRYMy3BAr4dmRpW6w1MZZgaJ3bDBEWZmOtlIgoR3aanmLi/pUk9SXtvEEEgpUSpG1JISJBOAeY/LQHUSMR64Y8oc/dnPO3FhkUvEqxZcFYxK+u7c5iR0JflQ8g/qnHOM8Fm1seGJNfRXkdkWaTnHPuRkFRS5NbEEu8Z900LxHWtUhbuL11LvBl/gtg6YTvcRU8C5HVH6VWFC1j0v1pjEBNqKT+EWIRfT2imI1sZ3zlP57bM6StecV8+//Ms7ORAeMNJr5jzL1XIAP56yi0gC+yirKv4QjoSF/5ATIRWOA6x3l2JaTdPDYinOOJcJ2FWLtPcNJ+C0RJ+XNk0nyE/a1IPzQH2D/iG05ErLts5e6GhAPcUUi7/hHwR3NuJ8Rybj5Sd/OIb+0g/kvjWFaZ73oR4+YNj3Uz7l2DdbjvNmWilsL8DPLqMeBm5/7VY8panOL9c5PnmyPWz09iKQiSxDUinDzGHyz++oCTcZThiNzxG+BRU45qEFnsVaQPvwtpZ68kuv/rW/nmOV989c9XYvn3db7rm4Quu0YiBjKfEvazc5BVMMeW+kb7GtKudCGKsWCp/IVI3S/ah8dKzwNItilx6uXZKVtpybRe6kxEuCOA0004P8Maa1CogE+0crREOC2mfB1hym6g2Ava/OWQuvkhZsNfc3484YqDn0S8dyNgrPm/Dln99j8iFPBOHo9FfOq3AyeX+faNCC1+26zzyyF9/nzg19b5zZDVIZFuA+PKo49wfMXFXLsEGaM9jfT3ryAyyduIAUOgXJxMqIDf2pTpfRGDpxPL5E2qsgahcv4+xIgveG43pA3/A4V7FgTtcT3iCvE5YoznSsTJR7uZahj4HTulOhbEU9/sIy566OHjqPoHDLcDUQSvgSx/Wc65FjREWyCd457m/i+ZTupmxO/cyc5zJ1O4uV4dhYqNSxEl/op2OBHf9mdEAZ94A7u4RpOwA/4d4mOrzbn+NRyleYnv2gJRkL2I6cQR4aMBUZS8giiTVsFZAmy9o6FEHGoQAbYRa4NBOx7m/yKFlXVtcj/LQz1ixTkfWZa7K+Im4grEmqoRsRA6FRks5zH+VRO8e0VCK5fdovKVQmG7kdC/apKVCEdROIDbDJmpn01pBXwbobuZdcqE4SVvCAcvHyBL52PdR5jfgRDxHJZv04T5sgaybPUzrM2GEWHkWfMdR2Bt1mPS4DBkIPTdmPeOtv4fZ/4uiyio30IUgPdilg9TqBR5lZgJtLi6mSDN+gQrChW/LVaZj3QZFfMNXyNaIZJYAU8JBQ8l2mZz/VATzvaE1qPnYLU5lNl400f+U4X2DGlrnjXl7OtI33UxMsjPI/3W70yaP46sxroWq5+KqmfW+WAQGljSNyNWWp3I6oNg4qDejqspl//DLBu2rn3TfJet3NsX8VccKIieQNrDoC7ZaWeX5wZk+f/rGEt869oXTTj2iqAjzbnDMW4RkEHxuUg/fYcVn91M/B7HUVBF1LMWwn1evNRNpA/YtFz+JXiPXS/boso2ZeQm6/dfCY0N6gllDVeB8B2KNyQ9xdy7jXVuC0KF5WZR31wmPlErEn30AVsgypkexDrW9vW8swnHVhK3IhbJfyJUjn7Bef9EZLPWwz3ni5f+GTjahHNQRD7+CplY3IhQvq1HVmEeiNTnrbD6gLhwcVZZEbqEOR1pgyKVO+beJSneuymu3fRSnp17U5Fp8VBnIq6NRKz1X0D897+CtPOnOPXmGGRy4XYSutB0wmlF+qnZpox1m/LmumVYDukferD20kL8Q5+KtfGsOX8VYuV5BKFLvJIKeHPPEYhc9RGFboDiytlI88znSPvQZl1b1uT9HKyVL06ZSjoxlno4HuPyc5M3XwaWsMrB/ogrvpnI5Efg6nA9RAH/L0RWWAScWSpcUpY1EBnrIqR+dSDW3uta9wW6ifuxjKwQdzOHIm3E8RXUk9TbTU9heBs7kfJYMEFcBnPsnPq4Vg89fBxV/4DhdCDLUZ9ABKduQoHUtUyaZDqsIl/rOLtnI4P7jwmt3Q5DlkndA2xtzu2GdOR/I7TadJf4TECE8XMrjFM5i/jTTDxXs87tj3TUP6ognBMRn6GPUbjx1tam4V9EaElzBWKJWNYVBbJs725EEPkE8Z93MJa/YwqVLtubTmMW1qYq1vVEPsooFNaCgWjgx/5mHKVU8G7KuAFCBs8rWb8nIcuv3kY2uI2cWEEEzonm//USxGFV862PYC1HNeXxL8ggwh4cBMLEKGSZ75sUum2IUu56yRvE6v8mE59p5u/7iFC5As6matbfdRDh+V3MEuuk9QWZKPqdSaefW9d3QpaABpYk5yJC353m25IMhH6ETKLZm/6sigzO3jTvfhTZsLgBsfqeQ7hhZOzS5X6kmSt4bY34J/2cBMvyy3yDnfeXUsYFDdEKhEDxHtc2b2s9sxYy8J6PKH3PJbSAduMZV9ZSzX88tmdEtzWvIYP6Xc25ZmBLE4/nkbqSt44iFxVOGP9nytl7iOLjT5iBDzKJdz8y8Psdha5slkEGnO0Yv5xO+v8Cyx8zMsB60aT9eciy//+asvCXoExRbNU7xqTvAiL8uyJtvauQb0Msdj4339hmzo9E6u5niKIyGHSPwFgulmtXfNZNCvuADcrdn/Dbj0VWuY20ziWpm/YA9X7MZmSIUnQBxRvmroUM3L7tnN8AYw3unA8shp+ijMUw0e1MlBug1PoA6/oWhL60/4NluGHe+xlWe4ko5tZF2tPTY94ZWAB6yRc89c+E1qSvI23Vyta1C5FJyt2i4lauXDvnf4QouDZyzgdKnjzwtZhnv27KQSI3az7Kc3APKcm0vuuMdV8z4iP+b4QudP6K9P8fULiZ+ghkrPNYuXIRkwZnme9eD5kYu8Gks63kD8r1JKTvLemmAekDg/L0FoUK2DrErcbL5traVh1YA5ETH8FMQiUs7yOQ8edsk06jrWvLIorLgv0k6Mem7j7CSTsMxBr9BUTJH0zk9f1FVh8+hshw61nPrYNMiOSB75XLG1KWNczvryDy2fdNefo3ZqLXlLPDCWXm55B+4EkSTuxY11NvNz2F4W3sRMpjwQriMhhj59THtXro4euo+gcMlwPprD9GLCV3QpYl/dI0GG9S6EO73nRS1wS/zd8aQiE0+LsModuASxFB6hZkxnys9c5fEVpmLOV8W73pOD4mgZ9fxDroCOc74nYzP9TEcT3ze3+kEz7LuqeUgsdWFJ1gGuvHEQusFZFO/Q7EWupEZDA4j3BZUqwlqsmTj5DlosciHezT5tlbiFEOI0LrC+a+8SQQ5sulmcmD/RBh6B6sDSCj0ifm3JVEW5JNQoSiSAU8ohA/AxE0lysVhvPcTojS7mEK/frZCnh7ED0G6Rjzdv5XO2/Mc6ub7/0tMnHzMDKhMw0RLtbFWhJIKERsgFV3y4ThClMrmvh1YCkhgDVNnF8l3AfiWgotR0rVmdNM2b8LR6GKCCsHmjTqMH9PQFaW3JUkHgNIs8NNvvwDy9KtTFzK1Zs4BXysBTxijdNJqHivpG3+kTn/86g8rWb+47c9K9fWvIdM+rqTxZsjVuePUWYjb8Sy5UPg98ig42bz3jyiHG9BLG9vM+X3XUQxc615/wckm6y62qTzfna5QfrbKxHr4UcJJ66Dcngosmz8Y+D75cJxwhyJDEJnEz0o/hQZFAeW/nVJ3+2rbprrdh9gl6+k3+kq3vMUKqorqZuB8uIv5tgNMWI4y42PKTe2QcAhJqx/4qwWccpuSYUl0YrK/4u6nkYbYF1zre92RpQiXSZt1kUGqPciZbuUr+iipeG+8mUA5bni/tncX49Yar+NtIkjkf5kAY5rw/4eFPbPtuFCDtnjKY+0dxOda/shkxxFrkUiwki9PONBpvVZZyLCPRJRQAeuc+5C+pS9kYmsuVgTroiyPldJOIRK3tsoNFZZiXBFn62AdxXuJTcuRsZ9DyMrA+aSQAFvri1HBWOBiPjMJl5p/Rlw9QDrUOrhpBkGMg6eTYmVv0j9/NCUQVtem4y1+W25vCElWYPCtuEBZFPgrUxZes6OG+Km5odIHXoEmWyqdGNNH+1m6mGYZ3zJZ6mPBfsRl/72zV7GtXro4eOo+gcMhwPxLfsh4quqwbm2HaIweR/js9Ccvx54rYIwLkQEgd0xwpU5n3Pe2YFY9hyAWFlshSwbmoelQCgRTrDRXR4ZSJ2Is2wTCnz0Bv7zDjJhJla8R91jGtR3kKV3CxGrrjbreguypO27wKEl3nkGMnjcgUK3EcsSbsB0N9YyTictd8HaEGmgaWbua0SshQJ/mStUkP/XIKsbprh5Yf5OIlTA70E4oTMaUUYuwlrKW0G4O5qyU0oBf5Q5Fyje7Vn7qEGYl7wxZSmwaGpB6sdCxLpqJLKh7z1I/VyA+Knet8T7Yi1EnbphD1CvM3ViHvAz57lWZEDnug5JUmeOQWb97yFioyzz7gOAB025Ccrn+mmmGaJ4WTdJXEje1tRZvwMF/EVEu47ZFKlfwUqhpG1z4DtwWeAN4G8V1JHU8x+/7VmStiZYbbOHm67mnlFl4nMOYvW1E4UW7Rsgm532IFa2OcKl2rchg76XEMvAslaqiPJ8JmKdb5ejoH3MIUrFRYgypNmcXxOxqn+UBANhItoGkg2K7yEcFJcbDHupm1jtvPlt9wGxCnhEmRHn5z9Q7NlK24rlJnPtapNfnVir68qUgbcQw4TTKdHvUqiw3KzEfUFfF7gC9NIHIPVgIqGbJttgY2XESuwjxK3S+chE2J8pMxHmhOErX7z0zxH31Zu68K7JkwVY+4w49x6IVf8rSMPY/pnQh/KPCfeeCIxWflguPp7Ksw+Z1rvc5Ny/DnCO+f98pD/b2Pz+kinLb+Ao3JKWMyevp1G8AnoFpM/pIWJVVcL374fU9e2Qiel5xCvgX8dxM1VpfMz9pZTWyyDtQNlVb0MhnMEOg1DxeDbSbtXb5517awkV/JNKva9cfjHIsob13sBifg9kcndHZNPuj5CJv3Upbz1dyYRYau1m2mHgceyUND7mesVjwYHGJUmZ9RUXPfSoxlH1D8j6gQx+bjeNT9/OzFi+vBAF+HzEWm95c+6biKVCkt2yd0IEp/1iGn1baD2F0D9iHlEgPEfyDaK+ahrZVxEBP7B0+hYR7koQdzbzkQHeQhIo3hHrS9c621aMnIBYoEwDvmilaeSyPzcc8/5HEQGoIeaeY5GZ7POC99t/S71/IGmGLOP6GiIk3UsyH9JXI9aH20Zcs/1fTiJUiu2C+Kc73nzPDxLmf5SwF6eA3xQZmAWWT53lwvGVN8jAKg/cYp37ijl3pnPvJeb8DBPuAyTYsMc8ex4yiN8x4tpFJt2ORCwEZgM/ta7Xl4tHxDvtZ44jFFQ2jLrHKp9XUsaH4ADT7BGKXTyUE4IrqTcN1v+BVfaWEe9cHuMig8rb5mWQ+nkVMvAuO+Dykf94bM+orK0pWm0T8V1R4U9CLPZPIbTCsvuwscggqAer3wrSjGJr+7g24GRTTn4Rda8T5p8RS0rbGnBlLGVSiXAa3fdZ1+xB8WEYhREyiDgLqb9/L5UnPuumyZPPKXY7EamAt66PQizHnjNxs9M5ykK80rq5rPXsb0z8TkiQNxeadPgyxu9uuQNRWH5s4rJVxPXVEZ+93zS/vfQBSP3PI1ZfNyNWaO4ESAMyIXcfMrn1mfm2e7FcU5UIw1e+eOmfS8SzHmm3nkZkzUkR93zVhPujSt7rlPtySp7zkP5uEclk59TLsxX3NGVar3KTW8at/2sRRf4/ESOlwI3Cqkg7+CbwR/rhNs8K4wqTfrfjrNhD5JWgfB9YwTvt8dK9iOJ4KaQfm02xAn5bZCJhJuXdjqxFjPtK655SSuvlSSY7pR6Or7hY9wdy1/5In/flmPuC1UJTkFVCmyd8f6qyBmKIcB6W1bo5Px4ZW15uffeHiK5hXefeAhdVCeOVaruZdhh4HjuVic+AxoIDjEu/+ua04qKHHtU6qv4BWT8Q5fNs4NSY60FnfIhppPYyvzc2v4sGshHvOAXxhxvrO5FCYawO8R+2E+J7zh4glbXcQxSqryNKkG8gy83yyEDuHKdBXAoR0vMU+kiMC+caRKi9mGLLSlvBdjwinD+GWd6WpEMy962LKIJLzcQ2EVpqrZvkvQNMM3uJW71VHnYrE8aVpiPa1k1XZCD2ByfvJxEuM70WEQDLKt6xBkFR9xAqXx6i0EfhxkiHm6fQBURcOL7yZpRJu8+wLH4Rn30fEfq1Pdh8+0nIxl4nIwOUpJvdBJsFPwPsbJ2/GLEI2M38XhlRmMym8n0XtkEGAUWTT8hE1RxkAFZgleqUFVtxGpc3A02zY1KoN3acbGXplAThTDRpk7Rt/or5vQYJ6qbH/PdVZ/rT1rxk8u/LJNzIG7Eq7KLEps+mvN9vysFK/YzPOki/+TJmA8mIeAWD4A1MnkcukyVeWX0mYlXW5pZR656RVlx2sM63IhaXSTYj9FU3JyMKt5fdtKBQAW/3Z6NNeJ1YSjJz7Rgcxbs5X2nd3Mu6thqW+zzi27M9kD0KCowW4vLSeXZLZDC5X8S1OmAV63fqbYCVt10mP98z//8W2D/m/sDqPTDE+GKCMFLPl0Eqz0k2Cy7poxmx2t4NmUB8EaM0RvrOwNrxBwnCSdo/u0qen1h5U3K1oK/yjAeZ1medccKsRfrJic751UxdOt7K/60RS/K1CSedBqKAv9GkzTk4k2CIC5q+iegS79gLMXgpmOg2deQlZKVzMyKjz6ZYAb8zZVZxmHzOm7DKfY+ttL6X6JURcWU59XB8xcVc24dCBeL6iCx2M6U3hPy6Ke+rlPo+c2+qsgbinz5v6sK/kXHdpoTu+PZGxu5bmd9TkBVQT5JgH7GI8FJvN32EYc77ks9SHwsOQlySjp29jGv10KMaR9U/IOsHYmX0cdBAE6GAMA3GCkjH+Stzbi1KKFOcZ28H/mF+lxIAcpReglrOEjUQ6r5MsTL9YEIB8lVk09eVEaHuBKzBWokOqpHQp++7iHByPZbPRuf+E819j1BB545YZrUTKpHi/NXvjigGEluclAgzSZrdZtKszVxfvcw710YEoecQRZc9MLoQEdqKdmU3Ze1lE26SfNnL3HteqXuRyZx5wO+c81uQfNCdWt4QKgaCQckqps7dR7iLeiBgHg8cZf7/EYXuEpoThhe4qNjUxOmfiBumXyKWgbs5969qykM7cHHCMC423/g6shfCUcBmTlk4xoR3L47LiKGWZtb9/Wlriiy2ypS18Yg1c6VtcysRSx6rkf9p1xnr2YG0NYFF3aQyYeyDDHL3QNr+NUvlIbIZaw9mY/Gk5Tk4zO91kQ1iX6fQ5YlroT/OfFNi9xxW3fgMUd61xeUPsgrpGcRq2R482JMZrhWzl7pZIs1eo7QCfj1koHYiziDV3Hu0OX94RJj9qpsR95Sq/z825Xli3D1l0qXI2CEij7y0AVa+vIwoV/YDfka44eWfEeVnq/PMcogv1e8mDCO1fPFVns09P0HccZUr+4ELmkABvxJi5ZfIfSID7J8R91nfKReOr/LsXBt0mdZ3nbHeMRLZW+QFxGL3NhN+sJLsblMW90Xk4SeAPyfJFyecRmRyeX/E8Gmsde1WYhTw1j1xq3uDcvYCYp29DrCkudaATDLfZH6PQBSns5F9SwIFfK5cfExaP2DSYs8S3xPU5Vak3Vloyn+RC7pqheMxLlubvLmGQgX82ciE16lEuIo1ZeWnSF86jvLj81RlDWQvjIdN/L+PbET8KjLptjMyofAAxsiK0Mhvurkv0Uocpzyn1m6mHQb+x5sDik+Zd2cmLnroMRSOqn9AFg/EomiK9ftJ4HliXAJY970E/DbifKw1ujluBV61z5f4ttNJuIQtKi7m3FLIIO8/FG5QF/iF/AeibOlAlrGNTxCXWiu82YggfDai1OlGOvq9KN4s9iTE/cx/gCXi4o4IPmea/5dDBILrotLM6mBqEWHmjKh3lkizDRGLhS0IlwEmTbN2k2ZLuN8TEU4LsrRqpumAApdFwSClSBlmPbsShXsMlBrUrYb4HsxTuMFVlEDzf+a+PWPeFfWMl7whYhd6Qt+lx5nfDYSbaXUh1iQj7fBxBJGId+6GDIRvCPIaWQHQbt47l+Jlm8E7V0U2lPlWgvjUIsv/88jy538idWcR4obkIswmWsig+HPEOqESoctLmplrA2lrFiD1ZsmEdXNzRLHyGIPcNvvIfzy2Z+bZJgbW1pSzqDvU5Of6yMRzgXLLLffm73iTlt+oIB415rkRhG4z1jJl7A0iNoo0/29rylisX2QnnG8Bm5r/D0AGKv8jYlBs5f0BiLJ0CzcPY8Lw1Z4lTjNzLVDAP4JMzOSJWF1l6oS94mAgdfPGCspAnakLzwTPxb07osxFWWFVpQ2I+c6fm7TfyPzexOT5/0w+vGTKSKQSNCYuvvLFV3nOIcrUbuDbJFfAv470od1Yy+tLhNPf/nmTmPfFheOjPKcu01K9OjMCUU4/DpwLfA9p1z7CtE/m2x4z8frUxK3e/oYE4YxExoIfmvd0IuMce1XpLciE8lmUWMkckf9BOXvSfNuniFHWQeaerwD/xawmQyZF/4yM0b5FedcrGyGug7ZA2v77TXndM6oMRdS3b+K4zqhWOL7iYj0zHpng7EBWHwbt5rLI6okuU+6/YD0z2nzjXMpvTJ+6rBG8B7FG/ifSFq6JjMmvR9q06xD58i3CiZ8csg9R5IrBEuGk2m56CsPn2CnVsWCW4qKHHkPhqPoHZOkwHc1qptGYStixnUrYwcb5vl3JNDRlLeuwNhg1vw8zYdobv0X50t0S8df7pX7EZXPn+v7m2qHON5yGuNpZDfGNfFyFabgJIpzebhrrtZAB5RuIEP5fxEJyNeuZU4mwnrOuB36KtzG/GxCB61PE93mk/2NE8J+JZbWd4Pt/YjqLOYif5aWs9ydJsyvLpRmFPgfrEaXYXMTtw9WIMmznmGcn4FhDuGUxJpwVCTezjFXAm/d/SGgZV06B5CVvCP2AH0Ghn+alkY3AZmF8hBP6J/2Dm1YJwvkFMiB9BRE+NiBUNm2AKEbexdrALSIN2xKEc6z5Ox6xEuhCBJGtEaHoYcSn7yJEUD4WGTx+gAy6krgY8JVmg9HWJKk3dt08HnGh8H2TRoPVNqee/3hsz5znm0mvrZlgvv9K8/s/Jh1jXeQgA8F5JLR8N3l+r3lmBmIhdhQysbAioiyMUiaPJLRAKxqElCjLj2M2ekI2ZowdFJvfX0YG6GU3h8Jf3exvmu2A9Nd54DQ3/yPKfOp1MyJufzVhjixzXwvil7mkL2Trfi99gHN/oBBdCVlpeR+FbvqONWn5FqI8/tCka7n+2Uu+eCzPQb85Fmm/OhELunIK+DpEAfsm8L24fIsIJ7X+2WN59iHTeq8z5pmcCftprAkpRMGap9CtwrLIJOwO1reVVNZazzYjfdpUpI/eFKlPHYjC3I7Xb03YRyZ4b1DOxiEbkS8y5eubJo+7kbHUZSb8k6xnRyGK+nIT/UH+z0VWKy2F1O+HKKG0BtqQ1SXuxstxBlKph+MrLhHPjyHUA1xjlZ9VCX3+B65AL0LavBkUujSJskZPXdawn0fG5FMIN+hd15zfCTHEeAVRwEfqGMqlF37GNZkZO/mIT5biooceQ+Wo+gdk8UCWYC1CBK31EMHrH8hg9Hs4y9UQwf4I4B0iNjxy7j0c2bjKttCbjCyL/S+FFvf2MrIGRHh4HFi5H3F5BEsphnT6L5vzpxMul4wU/IkXuDY0YexhnTsXERqDyYtgGWpgeRIsr/w5jnWIGw4ywPoMS7g151dHBJSnTcMebOzXJ1QjwvGLJPSRjFiHf4psBLVGxPWVB5pmVv4faZ2rQ5aZf2reeVjM+w4xZaxs/lvh2JvgxSngbcuKFZBBUhJFpc+8uZvQaul6CjcP2xMZWF6NKNpWQ9wfPUllSyUvRwTmrxPjYgP4IuEmx7bPxai8jqszV5m4BLP/SyHLrjswvgGRJattiFXMdYhC5iPC+lNWAesjzZzwgrbmUQa5rSGmbppvfwYZ3A+0bU49/z3Xme0RC6mDrHONDH5bk0P6yGsRwX11YDuTJ3ch7WaNE596ZDD7HLBqwrr5EVJ3voH0HVNNHO5FXOlMIvRRf4QTl+lxcS1Tlh8j3ODXHhSPdu5vQVZ6PRdXdnzXzYGkmXl+JywfssQrKlOvm+b+AlkD2UBxUblnkTo7hwSrHvDXBwR182vO+QZkE8p5hJNzwRLwsxEl3eHISsKTE8Ql9XzxWJ7dfnMc0uYUKeDtdEesUIM6vHyC8uyrf/ZVntOWab3UmRJx/Btwq/X768j4I3Cf0Ua0j+/EyiWkrr6DGdNY5/dA3HjcQqGxy5mUt8KOK2ftyArUFlNGbgaeMvc+hSjdg8mTchbvsflv8t5WWtsuVdoI3Y2dWSoMX+H4iotVhn6GrErfFFFaj0Jklk6k3enbKwBxZ3QP0o++ZfJ2X+t9pSyFU5E1TDoUtRGECvgXEaXnZHO+GVGabltJ/UtQnget3fQRhnmHl7GTpzTLTFz00GOoHFX/gKwcpkPq2+wBGXh2I8ru1ZCO9wVE0LoNmfEehfjSPR5Z0n5amTAuRgS4u3A6RcIlQE9R7BNxFCIMzCPhxh1BnMzfXU1cpmIJ9kgHHjR636HQb11ZH4jIYP51ZHYzjyiOlkIEoZnIhk5t5t4DzD3fRRQBT5rfRRtEWe8/P6pBtuK1J6LIetnkQaDkXx4RXudTZoBqvfMkxJpsZ0oI5YhQ3a80K5P/9cjS0s8RIW6SdS2HWCi1Az9LEJdS4dgK+POca03ITPQHmJnwaucN4SDjS8AdiGLiSkRhdCfh8sjzTBnf3vw+3nzfDuXCMPefYOW/7UcxsAxcg9CH9WYmL/6Fo0RNEM41pm5s45wfjyzX7jJ54Pr2XcmkwW8p46bDV5oF+U10u/ko1kCVAbQ1xNRNQgX1ksggpZ3+t82p5z9+27MLEXdenSbMZwg31mphkNoaJ8wvYrkoQQa8HcigeC/C5doTEQvL+cAJCd77fURI35FC/5OtyGA4jyiPJpi8fxnxUXo4MiheCHzfrR8VlGV3UDwdsRALNgpfElGQtmM29at23exnmr1GzAo04hWVqddN8x5X1ngQ6cteQGS0SJcYyGDvB4jsU27Vg68+wK2bT1Po2m8VZEB8HrIJXqAQHWHd01YmDF/54qs8x/WbSyH9ZqQFvInTKSasLdzvriCcQeufPZZnHzKtlzoTEW4LodLwReBS8//XTTy+F3wHYjWeqN8sEd53zLcvZ37bdepERHm6XsRzcX7IS5WzG837gg1iWxCr/TOwJtKj6mGS/KdwYqpAaW3OjUA2V8xj9ZuVlrPBDMdXXMwzv0EUkM8j7fTnGJkNmfD7LqEFvG0g14jID43O+6JcmqQqa1hxbkfamq2d64ELmv8i472osptoH4QE5fkGBmdck7WxU6rxyVJc9NBjqB1V/4CsHaZTChqtnU2j9AQyIGpFrBCCTbDmIBYfr2IJd0QLQhcgHek+WNbeFHbeRyEKic/M/XsjSoqrEAHgB6XCiIlPIARvgvgivBPTESNL6f6JdO4lfS1HvPcaE59jkKWcPzbp8ZS5HrhWGE84sdA3gESEmNjNm8zzQRqfZz1nC141puF+09z7EfAsokh4l8Ll8qX86DcjS55+7XYO7vOI8PO0yfPITZVino/Lf3dgFbiFuBejFEMsVTtJ5qc0Lhw73VZGBMw80hmvibi0OBlRlpVTVHrLG+uekcjyztsQv9JTEGXR/4DjEPdGfzXnmpBOfQEJfBWa/L/XpInt4y5QVKxLODhdz5zbzOTTC8CuFdSZWcRYliADhetNXh+NpWyJub/cwDi1NIsIK6rdfBSzfJV+tjWUqZtWHi2BWCnNovK2OfX8x297FgjC30I2c/0RYpH+pHVP4O5qDhW2NTFpGOT99YiFzSqIFe9h5vcik1Z3IxMBH2IsE0vFB3Ev8QjSvzTGfM+xJr0uMr/XM2HNNOfPSlpnSpRle1C8jynHC5FJ5GdMHMsq+H3UzQGm2Tsk9IeLh7pplWdX1liAWP4dY/L5AZNGdn/aisgecyjvmsFnHxBVN/9h3dOCyJl5pN4UKN4T1EUv+eKxPFfSb/Yp4BHF+8nIwP+HgxxOv/tnj+U5bZnWS52JCLcWmTS+x/y+xNShk5C22h4nTUba7rITSRHhNGKMlZB+rNv+ZkJXHluaOO6Z8L2VlLNjsSZPk9bJJPlv3Ru4bfkMMZL6DtYkepmynHo4vuLi5M0uiJHAKGTV+/PWPUsgbpm6KfQBX5skjIiyPKiyBqLU/zGhK5x2pH25FxnnBUYYwYaqLyGTDYlWVA6wPPer3fQRhnM91bGTz/hkKS566DFUjqp/wOJ+IFbAf0eWXG5IseXMbqZD/IdppGpM4/QNRNjbg8KNVqI6jl1NJ7gv0buX1zv33mYav7nm713AIaXCMOddVwa2MHAOonzvwXILgQjOCzGbBpFsoHUlItxsQyhojyC0oNnHpNUcxHogj2xAFDcIcBUDwft3RGZsP0V8/Y2Mub8NsQy9BNkA6QQKLfzLdbSrmY4h0qrEubeB0L3CTknSLEH+1zrv38/k/V1I57iIBAqkBOHYEz2TEEuaBSYus5HOt9wO817yxsRlWedcsDHlL6xzvzHl+Xmkg/8E+Im5NjlhG7B6XP4jS04XID65/2vSabK5tjmOX9EEdWZbt8wgdTOw1BpPsqX0UUoXn2mWtN2cSuh+qj9tTdm6SdgGNQFfQNyMnEyCttlH/uOxPaOwbQ6UAyOAHyITuLb7CXuy7y4StjXAWs5vu/3az+TxKda5ichg8HZTHs6mcJO6UvH5AqI8+2rENbs+XGbyaW3ruQ+c74jL/6Rl+XFgQ3NuKURx+nuTl7uVCge/dbO/abYOMuFzcMJwfNTNOFnjLKTunYIoWGYh/ddZiKHBgYiF+SwSGC3gtw+Iq5u2z+o9zHv/hEyUJXbF4SlfvJRn+tdvfgupnyeaNDwjQXxS7589l+dUZVpfdaZE2L9BJopGmfL7innn+cH3I8r/p5A+p9K9BUaacjvVpP0IZFL8cYpdZe6B9DVJ3AD1t5zZq14GRW5y7l+D0D1FgZV4XJ3xFY7HuBTkjXX+J8geHCsh46ZAbvseIhdcQRn3P9a7Upc1zPlWpP14GPHtfQ3S9rYjE/NfIZyk/CLSPk8PwqygnvgY12Rt7JRqfLIUFz30GKpH1T9gcT4QZUjQQb9LuAT4l8hO6kuY+75EOCO9RYn3xQnC30Fml8c45zdHloDfbhqmFcz5OqTDXcM0mk3WM3Gd7W7m+89270M2gFmACPE7WnFZyzSKc4FbEqbZDiacm61zwUByU6Rz/yqi2LnH3HsBEdYbMe//A+JeJ1gCVYsohgKFVasdP8oI1XHp5dyzvkmD3YL0L3P/AYiS6uZy764g/69y8n9fkw6JBo8VhHM1hZuurIj4UNwDa/OeqHB85Q2h4uFJLJ/D5tpeyEDO3khrW0J/c0FdXi5pGUCE4LmYjScpnKS4GrFCbEGsYZ5FFFurmevjS707qs5QKGxchKw22M46FwgqC5AlgGXrjs80o3/t5jpU2NZUUjeRwfZIYgbAlBDq0sx/PLZnbjmz34dYHH6O9AHu0s/9kBVXZdsaQr/AN2D5NHXuuQ9RVJQdkJaKj7m+qfm2Xcrk//bIxLK9x8WYcuH0oyxPpYRLrpg0892eDSTNxpbLM+veVOtmmfK8KTLJszuiPNwOMZCYZ/JpAeL27nDr2VJ1x2sf4MTFrpu2BfFNSDuxdNI88ZQvXsqzm2aU7zfHIX5k2xErzy6SWe+m3j9XoTynKtP6qDMxYQb95CREWXS2+X0UYk0/B5nc/R2ykuBfhKt/EyngEUV74Ad/a8I+em9E4f8EouCahKxeecbcW65d9lLOKs1/pA3YElkBez9wapIy5iscT2GUyps7TLn6zOSRvTnqd81zt1BGcYgHWSMo54iR4LkmjG2QMeVKyATeC+b8XxADwjrzbS+SYJNgn+XZUxg+x06pxidLcdFDj6F8VP0DFucDcYVwLiLg/hHZ6fl2ZCA0H3jfNCKbIQqKHqQj3q7CcC4wjdp487sRsTr+3DRewfL4tzD+EZ3nc/bfmDDakE68CzjHOn+RiYu9XNJ2C7Ed4mPwxArS7BcmnDPNucCC5wBzPnA1sbUJ50cVpNWWhNY3gaBdTwmFlZNGNaXSKSbMJRBB/kb3fRH3/hARvu+oIM2S5v+bhP4xm0x6Jhps9TecmPfExd1L3iDLTHc33zkPmcRZERmUtiAD7D8AKznPBZtilfS7HBHeOMQq4Do3rc0327P0p5pvWtuNW8I6c7ZTN+cRsfzafNNNJr/KLgf1mWb0r928CxmEJ25r+lE3T0cGLCUVDT7zH4/tGaXb5r2R+v8W4mv4bsT6KfBhuy9wqBv/iDBWQ9zmBAPRqabc2S6uvoJYuJw0kPg4eROZ/87/swg32cuRrN/srwywfdQ3VLtu+kgzX3WzTHkukDWsZ9YyebUi1kRCXHmOSDMffUC5unmPOXcBMlj+QYXplna+eCnP9L/fvAbpN223VlXtn6tQnlOVaX3UmRLh5kw5+yvwjHV+S+BXiHu7O+16U2H5Ph+x1l/VOd+MKLDeQPq3DuBtRNFVXy4+vspZP/L/+4iFdD2V7/uVejiewiiVN/ORVTQbmffPRBTYE5Bx95nAsQnSKnVZwwlvQ2Qi8jrnfOCS5l3z9wUTbtmN732XZ09h+B47pRafLMVFDz2G8lH1D1jcD9N5/tw0Bscjs8atwMGI9cZ75tpUQuXlg1RgjUTo+/D3yA7qD5vfjyIWFKMQ5ccM4O4BxGUkMmDLI0uIL0BmGW3FeyAc72jFaz3relL/nkE455hzGyACxHnBe0xjfyciXKzWzzgFwnNZhdUA0q0JEXI+p3CHenc511hkY5Bf2PlfLs0qzP973LxKGk9f5cxX3iAbTf4cEbw/RPwsLoEIlR9glIUUWlzZSsCkSstmq5zuY52vjbjvHFNWxiZ9f0Sdiaybzv0NJr8Sb3rjOc36027+icLVFUnamkrr5uVuvg2F/PdYZ+La5nmI9eEVSLvwAaFP6dspXA2TpK2ZhCg3XkaUEM8jG7WOQxQvzyPWgIFSol/LSU2a/8mUoVL5v765Z/d+hJG6DNDrt26mnmbmeR91s6ysYc5FuVmrZCLBdx9Qqm5+iPQNHfTDPYePfPFVnulfvzmGCtwODiCc/vTPvspzqjKtrzpjnh+BuBJa3Tm/lUnHw5zzLc7vStucB4Hby8T7IMRN21cIVy+UVfB7LGeV5v+VREz+D4VwPMYlKm/mI2Mn+33B6r8dgu9LGhaeZA0rvAuQFTWBC5tDzTtPQtw1fRWR1Y6rNL18lWePdcaXfOYjzTITFz30GIpH1T8gC4dpDC40Dci5zrUVkCVhVyPKhDwVWqKZ90wxnWk3Yi3xbWAV555HTEeYyH9cibj8ErHMyGOsLq3rtnXblwfQ6Y6yGt2rkWWBVxIql4IwjjX3xC6fSxBWINymqYBfy8Th30RPVtQhgsvHwN6VplmF+d8wgHh4KWe+8gaZwFkfcWXRiVgkrQX8FBHGJwb545bzCsNZG1GCxOV/PSIgT8faf6HCMErWTeu+w5EJk2b3O4ZYmvW73awkrArq5kd23Rxq+W+9M+06Y7fNVxG2zbYbllaTZldg9QEVhlODrK45DfFjmkeWLn8b8euYB/YfSFysvCmX/8cgG0hNHkCapSoDmHf5bM9STTPzHh91M5GsMUjlzEcfkKRuHon0Ff2tm6nni6/yjL9+02c4PspzqjKtuddHnTnBpNUbiMXw+piNYREXIH80aRqkX8UTSVZYDYhs/Keo9ABGE7EnRiVheixnvtoAH32Ar7jE5g2h3LY1otDeZgBhpC5rmPftbL71fEKZ7BzKbFw7WGk2WOXZY53xOXZKO80yExc99BhqR9U/ICsHhQLx2db5QIkcCHbrutcqCGMc4vt4pHM+h1jrPIRsfFGx6xTnfW3I8rZuzPLWiHvcTf76Y8U50nTq7cjStUjf9PTTss4Jy1VYTTNhjxzou60wdkIsHV5HNr4K8n41ZBKhHWvznn6831f+ewnHZ96Y959sylknYuHyGeLbs+Tu6f3M/5Ot82sgy04XUOgTuz91pmTdRKyHO7A2xhniaZZ6uxmRN4NeN33lv/VsqnWG0m1zpKKg0vhQqJQYgWy0/TeThrNNmXgAGD0I8Qny5g1kb4tg0L08sjntAqzNVYdyWbae9dWepZZmTjhp1s3Y8jyYh482IGnddOpXf9xzpJ4vvsoznvpNj+FUozwvtv0mstLqDGRPoxmIq5ftkU0DZ1Ghy4wS4dSaMvsxsHXE9W2QPm6z/sbFcznz0gZUoZylGZfYvEHktdOBV3FWYlQYhjdZA1kFlzfx+T6F+4pUvEKgWuXZV52x3pe2fOYtPlmKix56DIWj6h+QpcPpEM9yrgXKkn77KnTeV2+/GzjMNIiRm9gNZlwGOc1GIzOpUWnmKvgHmmZ9yzuRzWK6iNksbABhbIYoK3qQ2eHXEN94r1I4sBjS+V+FcFLLGwoFxC+YTj6YZZ8DfGGQ8/8t8+4ZwCvIUtBXKPRh3e/8j6ubRkDptIUX+i9w+0wzL+2mj7rpI/8j0iaV9ozSbfNgWVe6S7/HIxtH3osoXb49iPEJ8j/Im5dN3r8HnDYYcfNRlqvQnqWaZk44adbN2PI8mIePNsBH3fSYL17Kc1zdZBD7Tc/h+CzPWeo3/w+4FVHm/JdwFcmAV3Ka96+LKHIfwlLAI1aj/0B8zQ9GPHyVM19jGl/lzEdc4vLmAGSlR79WJCUJw1wbsKxBONm+DeJ65EFS3OTSR3n2FEbVx06DFZ8sxUUPPYbSUfUPyNrhNCA/9BDeysgy/fkMohWSz7j4TDMKLUYHbFEfE8bSyK7hP0M2cDoI4zPPXB+0pVJp5r/vcNLMG7ezRtzrPAEck1L+f8WU6cuArw92/rt1BvG92OkILQMdQPhMM19tTep100f+W+9KtT3z3Z/ZaQSsYf0eLGV/kDcXA9eaNm1LO9zFIc2q1J6llmZWOGnXTZ/tjNc+IOW4pJ0vXsqzm2ak0G9WM5zFvAykWmciytjmyObfryAuFkdF3dfPsHZBFPDTgT8jG5S/irg9Kbu56hAsZ17GNB7LmY+4JMmbgU5a+5A1lkT2FHkTsw76T2oAAK8ASURBVLfPYNSRAaTZYE6MZG7sNNjxyVJc9NBjqBxV/4AsHqYBOd80ID9LMZwfA88wyLP2VYqLl3BMWK6PMm+N+WAKLT7y32c4vvKG0BpkTJrheMh/u84UCN8plIHU08xnG5B23vgMI+064ztf3O/PQN1Muz/LRHuWxbzRuPT/nWmVZ1/9ZpXCyUQZ8BkGYlgyH/juIL93HcQ94z8RBfxPCN2BlN1ctZ/5n6ocWK389xXOYIfhI2981H9gB/P+Yz3kge80y9rYKc2+JjNx0UOPah51KINOb2/v3Fwudx6y8dW0FIN6EPHP/cfe3t6HAHK5XE1vb29+sALwFRePaUZvb2+383vQ0isgl8vlent7eyPCLjo3AFLPf8/heMmbIA96e3tnQV9eDWo4PvLf1JkfI+6A3uzt7b3chD3oeeMjzXy1AT7yxlP9D96Zap3x2Tab8PKlfg8Uj3XTV3+WifbMVzhZameyFBf3nWmVZ1/9pudwMlEGfJYzi0+RjaNXH8yX9vb2vpjL5Y5EFEZ9fXQul6t1++wBhuOlnGWpD/AVFx9546n+/xNxC5VmPQS8plnWxk4++prMxEVRqklukPsaxSKXyzX09vZ2phxGfW9vb5f5P1KgGKRwUo+Lz3Cygsf89xKOUjm5XK6xt7d3kfl/sRdQtA0Ymmi+VI6m2dAlS3mTpbj4wle/6TEcLQP9IJfL1QOPIz7mv9bb29tT5U/qF1mTA7OEj7xJu/7ncrklent7P0/r/RHh+UizTNWZLMUnS3FRFBdVviuKoiiKoiiKoijDglwul0P2sDgP2Kq3t/elKn+Sogxp1PhKURRlYKjyXVEURVEURVEURRk25HK5ZYGG3t7et6v9LYqiKIqiZBtVviuKoiiKoiiKoiiKoiiKoijKIFNT7Q8YKLlcbt9cLndJLpd7PJfLzc3lcr25XO7man+XoiiKoiiKoiiKoiiKoiiKMnypq/YHDAI/ANYD5gMfAmtU93MURVEURVEURVEURVEURVGU4c5ib/kOnASsBoxCNs5RFEVRFEVRFEVRFEVRFEVRlKqy2Fu+9/b2Phr8LxvXK4qiKIqiKIqiKIqiKIqiKEp1yYLlu6IoiqIoiqIoiqIoiqIoiqIMKVT5riiKoiiKoiiKoiiKoiiKoiiDzGLvdmaQ6K32ByiKoiiKoiiKoijC888/z4knnpja+y+++GKAVMPIWjhZiouvcIIwJk+enFoYvvFVN32kWdpxAa2b/WXq1KlZ9Cudiu7xmmuu4dZbb+Wvf/0rjY2NaQQxVFlsyogq3xVFURRFURRFURRFURRFURYzRowYQT6fZ4899mC11VZj/Pjx1NXV0dzczOGHH87o0aOr/YnDHlW+K4qiKIqiKIqiKIqipMSUKVNSfb9vy2cf+EozRVnc2W+//VhxxRW55JJLePnll3n55Zf7rt1zzz1stNFG1NbWljzq6urKnqupqYm9r6mpiQ033JD6+voqpsTQRZXvpN+ogzTsvpZNQfpLmnwtm/OxDGzq1Kmpvt83WVo6l5Vy5jMuvtA0qxxdPj/0wsliOVMqR9uzoUlW5JkgHHWf0L9wFCUr+Bpz+ggn0DkoijI0qK2t5Ytf/CJNTU2cdNJJBddWXHFFZs6cSXd3N11dXX1Hd3c3nZ2ddHV1Deq3jBgxgra2Ntra2hg1ahS77747W2655aCGsTiiyndFUZQM4WvgPXny5MxMXPlUVihKFvDZzihDE1+TiYqiKIqiKFnmb3/7G+edd15q73/nnXdSe3cUCxYsYMGCBUybNg2AZ555hkceeYRcbrFxz54KqnzPGMFANW2lmCr4hje+ypkvslTOshQXX/hMMx/hZCkuPsNRkpO1diZr8fGBrzTTdqYystafqXWtogxvtJ1RhgNtbW2ph/GNb3yD2tpacrkcuVyu7/+amhpqamr6/i91Lep3qWvd3d3MnTuXFVZYYdgr3iEDyvdcLrcXsJf5OcH83SyXy91g/v+st7f3O54/S1EURVEURVEURVEURVEUJZKNNtqIRx99tF/P9vb2ks/n+9zIBK5lenp66Orq4gc/+AHLLrssBx544CB/tVIpi73yHZgMHOqcW8kcAO8BqnxXFEVRFEVRFEVRFEVRFGWxJ7BUr62tjbze2Njo+YuUOBZ75Xtvb+/ZwNlV/gxFURRFURRFURRFURRFUZSq0dPTQ0dHB9OnT+eNN97goIMOoq2tjVVWWYVjjjlGlfJVYLFXviuKoiwO6AaFijI00bqpKIqiKIqiKMriyvPPP89JJ50Ue33atGlMmzaNV155hXfeeYe99tqLxsZGGhoaCg77XPB/4ANeGRiqfFf6hW5ONrwJNqZJU2GVNWVV1upM2grLiy++GEi3jAXh+CpnPtIsS3XGF1mrm4qiKIqiKIqiDB9GjRqV+N6XXnqJl156KfH9NTU1RUr6rbfemiOPPDLW3Y1SjCrfPeLDui5rCgRNM8UHqhRVfKBKXiUrZG21gPYBQ5OslTMf+Eoz8DM5rijK8GbKlCmpvl/bGSUrrLTSSmU3be3q6mLhwoUsXLiQjo4OOjs76ezsZNGiRQV/g/+7urqKznV2dnLfffdx6623cs8997D00kvT2trKyJEjGTlyJK2trX2/R48ezTrrrMPYsWM9pcLQRpXviuIJnwMiZfii5axysqKsyOJqAUVRFEVRFEVRFGVg1NfXU19fz8iRIwf0nqOPPppnn32W559/nhkzZjBv3jzee+895s+fz7x58+js7Cy4f/z48dx6663U1NQMKNzFHVW+K4onfFm9Bi5hFEVRFEVR0sCX6zFFURRFURRl6NDa2sq2227LtttuW3Stt7eXG2+8kRtvvLHv3Oqrr64+41Hlu6IoiqIoiqIoQwx11aUoiqIoilKe9vZ2rr/+enp6elhqqaVoaWmhp6eHfD7fdwS/7fNR/0c9l+Rd+Xyejz/+mBkzZhR82+OPP862227LCiuswA033FCdBBoCqPIdvz6/dRBRGTrwqhyfaZaVvMlSOcta/mcpLr7CyUpZVoYuWWozIXvx8YGm2dAkazKAruZUlOGNtjOKkoypU6dy++23V/RMLpejpqaGmpoaamtrqa2t7fsdd67UvTU1NSy//PI0NjYyc+ZM2tvbC8Jbf/31BzPKix2qfFcUZdijm+0piqIoirK4o5vUKoqiKMrwY5dddmGJJZbg/fffZ/r06dxzzz2MHTuWK6+8MlZxrq5g/KLKd0VRFEVRFEVRFEVRFEVRlCFAb28v3d3ddHd309XVVfJvsMnpxIkTGTduHM8//zz19fW0tbVVORZKgCrfFUVRFEVRFEVRFEVRFEVRPHLnnXfy+9//vkChHvw/EDbddNNB+kJlMMj19vZW+xuGApoIiqIoiqIoiqIoQwQfbgEBddWjKIpSAT5cnAFMnTo1i35RinSPZ599Ns899xzbbrstdXV11NfXJ/5b6tr48eNpaGioRhx9stiUEbV8VxRFURRFURRFURRFURRF8cyiRYt44YUXaGho6FOqB//bf6POBX9XWGEF1lprrWpHRYlBle/AlClTUg/Dl8VDsFt3VjaP9DGr6mMXdUXRTdAU3dh3aKJ1U1Hr2qGJ1k1FURRFUbLOHnvsQUNDA52dnXR1ddHZ2UlnZyfz58/vOxect6/n8/mC9zQ1NXHfffdVKRZKOVT5riiKoiiKoiiKoiiKoiiK4pENN9yQDTfcsOLnenp6+hTxN910E3fccQfHHHMMo0ePpra2lkWLFlFbW8sJJ5zAUkstlcKXK5WgyndFUYYsavWmKIqiKIqiKMriTtqr7XWVlaIML2pra2lubqa5uZldd92VOXPm8PDDDxfdt+yyy3L00UdX4QsVG91wVdBEUJQKyJp7oyyhExaKoiiKomSBLLmEyko4WYqLr3CCMLIkO/uqm77c9mapnGUhLgHDZcPVweTll1/m2GOP7fvd1NTEjjvuyDLLLMM222zDuHHj0gy+Giw2ZUQt35Uhjfp8V3ygvrgVRVEURVEURVEURVlcWXvttXn00Ud56qmnuO+++/j444/529/+xoIFC/jzn//MmWeeyYQJE2htba32pw47VPmuKIqiKIqiKIqiKIqiKIqymLPZZpux2WabAdDb28uhhx7KBx98wFFHHQXAyJEjOeyww9hzzz2pra2t5qcOG1T5riiKoiiKogxbdPWTolSGTzcNiqIoiqL0n1wux1VXXcV7773HJ598wttvv81vf/tbLrnkEi655BIOOOAAVl99dRobG2lsbKSpqanvf/tcfX09udxi4+VlyKHKd0VRFA/49MWurpQUJTm6T4Ki7aaiVIavOhPsMaQoWSBLG64qirJ40dTUxOqrr87qq6/O1ltvzd57782DDz7I5Zdfzm233ZboHblcjsbGRhoaGlhuueXYYIMN+PKXv8ySSy6Z8tdnA1W+ZwzdCFPxQZD/qqxITtaUO1naBM1Xe5alNPMVjo+80bpZGVnLf8iW5XuWJpOyFJesoZbvilI5vmSNLE2M+ZqwUJThxujRo9lvv/3YddddmTt3LosWLWLRokUsXLiQzs5OFi5cWHTulVde4YknnmDhwoW8/PLLvPzyy3R1dfHNb36z2tFZLFDlu6IoiqIoipKYrE1YZAnNG0VRFEVRFCUJra2tiTdf/e53v9v3/+jRo9lggw3Ybrvt0vq0zKHKd0VRFGVYoxZ8iqIoiqIoiqIoihLNXnvtRUdHB6+88gobb7wx3//+96v9SYsVqnxXFEVRFEVRFEVRFEVRFEXJGL29vfT09BQd+Xw+8nzU0dTUxCGHHMJpp53GQw89xEMPPVQQRktLCy0tLWyxxRYcd9xx1NbWVim2QxNVvntErSuHN+q7VFEUZfiSJRlA+zNFURRFURRFGTp0dHRw6aWX9rkfdJXsadPe3k57ezt33303X/3qV1lmmWVSD3NxQpXvHvHphzMr/j6z5Ls0S3HJGj7yJmvKKl/lOWttpqbZ8CVrMkCW8l/756GJ5svQxVfe+NrUUVGUoYm2M4qSjEceeYRzzz237/dSSy1FU1MTzc3NtLS0FPy1j8bGRurq6qitrR3QUVNTQ21tLfl8nsbGRsaMGVPF1BiaqPJdURTFA6pEUBRFURRFURRFURRlMJk3b17B7+nTpyd6LpfL0dDQQGNjY9/mq62trYwcObLg7+TJk1l77bXT+PRhgyrfgSlTpqQehi+L1GDmNk0L22BZe5aseLOET9cGaZczzX8lS6RdN7XOKKDlrD9omlWOjzQDlTWHKllyo6UoytAlbT2NtjPKUOCDDz7g6aef7vO/bv8NDtt9TNy5jTbaiAULFtDR0cHChQtZuHAhHR0dLFq0KDbs3t5eFi1axKJFi5g7d27sfSuttBLXXnttGtEfNuR6e3ur/Q1DAU0ERVEURVEURVGUIYJO8iiKogw9fEzAAkydOjWXeiD+KdI9nnvuuTzyyCORN9fU1PS5dCn1f7nrA7m3u7ubTTbZhK233jr1xOkHi00ZUct3RVEURVEURVEURVEURVEUj/T09LDccstxxRVXFCnBc7nFRreslEGV74qiKIqiKIqiKIqiKIqiKJ6pqamhpaWl2p+hpIgq3xVFURRFURRFURRFURRFUTwwY8YMjj32WD799FMAnn32WUaMGEFLS0vBUVtbW+UvVQYDVb4riqIoiqIoiqIoiqIoilKSyZMnM3Xq1Gp/xmLPk08+2ad4BzjttNMi72tsbKSurq7PFU3gmsZ2TxPlt70/vyt5xvUR39jYyM4776wW/DGo8p30d9EGfxvtPP/880C6Gwf53JwoK+FkbaMlX+UsS2mWNXxsgpa1/M9SmvnYaClrZcBXmkF2ZICslOcsxQX8yrRZiUvW8NmeZQXtA4ZvOEEYWWprsrQZclbCyVJcArKu4N9zzz2ZMmUKHR0dtLe3s2DBgsj/29vb6enp6Tvy+Xzf4f6OOhf87u7uprOzM/I9pZ4rFZbLv/71Lw466CAmTpzI6NGj1We9hSrfFUVRFEVRFEVRFEVRFEVRPNHW1kZbW1u1P6Nf9Pb29inl586dy9e+9jWefPJJnnzySQCampqYOHFi37Huuuuy1VZbVfmrq4cq3xXFE1mxeLHDURRlaKHWiJWjaaYoiqIoiqIoipKcXC7X5/5mySWX5J577uHjjz+OPP71r39x991389BDD1X7s6uGKt8VRRn2ZMnlgKIowxsffjgD12OKoiiKoiiKoihNTU2suOKKTJo0ifb2dmbNmtV33H///Tz99NPV/sSqosp3RVEURVEURVEURVEURVGUYUh7ezs/+clPePPNNxkxYgStra20tLQwYsQIent76erqorOzM/Jv8H9nZyeLFi2iu7u76P1LL710FWI1dFDle8YIrGt9bE7hIwwf1nWaZoovS9EsbRynu9wPTXzmi+b/8CVr9T9L8clSXJShi69ypjKtoijK0ENljWzy/vvv849//CPx/autthrLLrss9fX11NfX09DQQH19PY2NjbS1tTF69GjGjBnDmDFjGD16NGPHjk3x64c+qnxX+oX6yFWU4Y0PVz3gZ/8CdQmkZAl1o6UoiqIoiqKkhQ9dEKihj2/WWGMN7r33XubMmcOcOXOYOXMms2fPZvbs2cyYMaPPf/v06dPp6uri9ddfZ/fdd2ePPfao9qcvFqjyPWMEFiI+lGKKoiRHLQQUZWiiFpyKoiiKoqTNlClTUn2/T8MVRVGySWtrK62trSyzzDKx9/T09PDQQw9xwQUX8P7773v8usUbVb4riqIoQxKdsFCyhCr5hy66WkBRKkNXwCqKoijK8OSss87qc08zYcKEKn/N4oMq3xVFURRFUVJGlVWKoiiKMnzJ0p48OtGvKEOL6dOn8+CDD9LV1UVPTw89PT10d3dH/rWP/lybO3duX7ijRo2qYqwXL1T5TrZ8SWVt81Cf4WQF3XBR8YFapVeOptnwRtvmoYvWzaGJ5svQRVfyKIriA21nFCUZf/nLX7jpppsAqKuro66ujtra2oIjOBd3rbGxseCempqayGdyuRzvvvsuHR0drLXWWlWO+eKDKt8VRVEURVEURVEURVEURVEWM/L5PDU1Nfztb3+r9qcoMajyXVEURVEURVEURVEURVEUZTGjpqaGfD7PzjvvTF1dHQ0NDdTX11NXV0d9fT0NDQ2R/8cdyy23HDvttFO1o5UpVPmeMYJlU1nZOMyHj1xd0qwolaMbFFaOjzSDdNv/IJys5U2W0LpZOZpmQxNf+yRo3lSO7mGhKIoPpkyZkur7tZ1RssKuu+4KQGdnJ11dXUVHd3d337WOjo6+/7u7u+nq6qKzs7Pv/4ULFwJwxRVXsOSSSzJ69GjGjBnDmDFj2HLLLVlnnXWqGdXFFlW+K4qiZAgdECs+UKVY5WjdVBRFURRFURRlsJkwYQJHHHHEoLxrxowZ3HPPPcycOZNZs2Yxa9YsPvjgA6ZPn84f/vAHGhsb+yzro/6WulZfX09raysTJ07sO0aOHEkulxuUbx/KqPKd9GdUwa9Fog9UiTB08Zk3WbEUzJJFcpZQBW/l6CZ4laP9meIDbc8URVEURVGUoc64ceM48sgji86/+OKLPPvss32W8oH1vPu3o6ODOXPmFJy3r7lMmjSJb3/72zQ3N9PU1ERTU1Pf/83NzdTW1vqIduqo8l1RFEWpGB9K3iwpeJX+4WtiLEv4qpuqSK4MXxNjvtC6qSiKoiiKMnxYZ511BuRypru7mz/96U9cfvnlBeffffddTjvttJLPbrLJJpx33nnU19f3O/xqo8p3Zdjjy09+2mHY4ShK2qjiZWiiVtyK1k1FURRFGXr48l+ucqCiKEONxx9/nDPPPLPfzz/77LPMmTOHJZdcchC/yi+qfPeIWooOb9QdhKIMTbKksNZ2RvFB1qy4sxYfH6hMqyiKoiiKoiRhrbXWYpllluGjjz4qed+qq67Kqquuyvjx41lqqaWYMGEC48aNY9y4cTQ0NHj62nRQ5buiKIqiZIQsTSQoijJ00RUWiqIoiqIoCkBvby/XXHMNU6dO5Qtf+AJNTU309PTQ1dVFd3c33d3drLDCCiyzzDJ0dXUVXHvnnXfo7u4G4I033uCNN96IDOOOO+5g7NixPqM1qKjyPWME/lF9WHBlxbrSZ5opwxe1SK4cn9aomjeVkaXynKW4KP0jS5tu+/KTr5bviqIolaEyraIoWaWrq4tbbrkFgGnTpvWdX3LJJWlqaqK2tpb6+nrq6uqoq6ujvr6ehoYG6uvrmTBhQt/52tpauru7mTdvHvPnz2f+/PnMmzePTTfdlJEjR1YreoOCKt8VxRNqkaooSlbQ9kxRFEVRFEVRFEVpaGjgwQcf5JVXXuHf//43TzzxBG+99Rbnn38+K664YrU/b0igyveM4WvzUF+WVYqiKMrQQ63FFUVRFEVRFEVRFID6+nrWXXdd1l13XVZaaSXOOuss8vl8tT9ryKDKd0VRFEVRFEVRFEVRFEVRFKVient76e3tJZ/P9/lwV0JU+a4oiqIoiqIoiqIoiqIoiuKRN998k6OOOqrsfTU1NeRyOWpqagqOcufs/2tra2loaCCfzxccgdI87neSc729vUXfXFtbm0aSLZbkohJoGKKJoCiKoiiKoiiKMkTQzZAVRVGGHj72fgKYOnVqLvVA/FOke7zjjjv4zW9+4/UjNttss5LK+tra2gGfGzVqFLvtths1NTVpRmWxKSNq+a4MaXw07L52ns8SurfA0MXXRpiaN5XjQ4mg+TJ00bqpKIoyfPG5UXlWJiyyEk4QRpb6Z18TYz7STOtm/8JRBo999tmHffbZB4Cenp6+o7u7m+7u7r7/S51Lcn9PTw+XXnopkydPZoMNNmDkyJG0trYycuTIvv/b2tpoaGiocopkE1W+Z4ysKUV9beqnVEaQ/2nnjSqrFEVRFEVRFEVRFEXJOrW1tam6annooYd4/vnn+/SGLiNGjOC2226jtbU1tW8YrqjyXVEURVEygk5YKYqiVEaW2s0sxUVRFGXKlCmpvl+tuJXhxpVXXklPTw/z588vOObNm8ezzz7Lfffdx0033cSECRP6LOJHjBhBS0sLzc3NLLXUUmm7kcksqnxXFEVRFEVRFEVRFEVRFEVZzPjwww+5++676ezsLHA347qfiTvf09PDtGnTAPjDH/4QG84+++zDscce6ytamUKV7xnDlzsQRfGBuh2qHE2zoYuvvNH8H5po3VSUoUmW6maW4qIoiuKjPYtzv6EoixMPPPAAt99+O21tbdTV1VFXV0dtbW3B//X19dTV1VFfX09zc3PRfeuuuy51dXX09vaycOFCOjo66Ojo6Pu/q6uLXXfdtdpRXWxR5buiKIqiKIqiKIqiKIqiKMpiRm9vLzU1Ndxxxx2p+oxX+o8q3xVFURRFURRFURRFURRFURYzamtryefzbL/99n2W7U1NTX1/7aO5uZnm5mZGjBjR59Pd9uve0tLC0ksvTXNzc7WjlSlU+Z4xgmVTaW62pBstKYqS9qZuWWxnNM0URVGSo5uHKoqiVIavdtMXuuGqMhx46aWXeOSRR+jp6ek78vl8wd+4c8HvGTNm9L2vq6uLrq4u5s6dO6DvevTRRwcaNcUi19vbW+1vGApoIiiKoiiKoiiKogwRfExaQ7pGS0E4OsmjKEpW8DHJAzB16tRc6oH4p0j3ePbZZ/P444/T1tZGTU0NtbW1sX+Do9T1pPfW1NT0+XNvb28vOPbdd1922223aqRPpSw2ZUQt3xVFURRFURRFURRFURRFUTyz3HLLccMNN1T7M5QUqan2ByiKoiiKoiiKoiiKoiiKogxH1CtJtlHLd0VRFEVRFEVRFEVRFEVRFI/U1tby3nvvscsuuzBmzBhGjx7NmDFjaGtrY7fddmPNNdektra22p+pDBBVviuKMuzRjTAVRVGGL9oHKEplZG1TR0VRFEWpFocddhirrLIKs2fPZtasWcyePZvPPvuMp556ivvvvx+A+vp6mpubaWpqKjiCc83Nzay22mrsvffeVY6NEocq3xVFGfZMnjyZqVOnVvszFEVRlCqgfYCiVIavOvP888+nHoYvfE5YZGWT2qyEE4SRpUlYX5sh+0gzrZv9C0cZPJZbbjkOPPDAovP/+te/eOutt+jo6GDhwoV9m6Pa/8+aNYuFCxfy/vvvc//99zN//vwC6/kxY8aw5JJL0tDQUIWYKTaqfFcURVEURVEURVEURVEURRkCbLjhhmy44YaJ7n3sscc4//zzue666yKvL7HEEkycOJEJEyaw3377seqqqw7mpyoJUOU7MGXKlNTD8LXkOLAQycqsapYsBHzhY/ZeLQQVpXLUtYWiKIqiKIqiKIoymGy99dZsvfXWdHZ2FrivmTVrFp9++ikff/wxH3/8MQ8//DAPP/wwLS0tfdbxo0ePZty4cXzzm9+kqamp2lHJLKp8V4Y0qkhWlKGJKpIVRVGUNPHlCkD7GkVRFEVRskBDQwPjx49n/Pjxkdf/+c9/8vrrrzN79mxmzpzJ7NmzefLJJ+nt7eWuu+5i+eWXZ+LEiay00kocfPDBNDU1kcvlPMcim6jyXRnSqB9WJStkTYmgdVPJClnx9RmEo4pEJStoP6MoSpZIe7W9+vxWFKUcG2+8MRtvvHHBua6uLh588EE++OADpk2bxuOPP84zzzzDrbfeSk1NDc3NzbS0tPQdI0aMoLm5mREjRrDXXnux+uqrVyk2ixeqfFeGNGr5riiVkRVFoioRFUVRhjdZm7RWFEVRKsPXhIWiDGfq6+vZbbfd+n7PmzePRx99lAULFtDe3s6CBQvo6Oigvb2975gxYwbvvfce999/PxtssAEnnngiyy23XBVjMfRR5XvGCAYQaSuUA9/yyvDE194COiCuHF+Wgj7aAFW8KErlZMklVJbagCzFRVEURakcXwZfWRkHKIpSHUaOHMmXv/zlovNPP/00p59+etH5f//73zzzzDOqfC+DKt8VRVEURRm2ZGnCKmtkye1IluKiKIqiKIqiDC/efPPN2Gt//vOfef3111lrrbXYYIMNWH755T1+2eKBKt8zhi+LZEVRFGXooda1lePTVZOiKEoW0HZTURRFUYYXX//61znooIOYNWsWH3/8ccHx4Ycf8tBDD/HQQw8BcNJJJ7HZZpsxbty4Kn/10EGV74qiKIqiKMqwJUuuerKErhZQFEVRFEUZOuRyOcaOHcvYsWNZe+21yefz9PT0sGjRIvbYY4+++y666CIuuugi6urq2HXXXTnxxBPJ5XJV/PLqo8p3RVGGPT4UL4qSJbK0sa+iKIqiKIqiKMriynvvvcdhhx0We72+vp6mpiaam5tZaqml+pTmPT09ff/n8/mC/+3rcefL0d3dzT333MNRRx1Fa2vrIMZ48UOV7/jb/MQHvjZc9RWGz3Cygk9Lsazkja80y0p6gaZZf8hammUpnCzFxWc4WUEtrBWlMnSvDEVRfKDtjKIk47PPPit5vauri66uLubNm8enn37ad37cuHGsttpq1NTUUFNTQ21tLbW1tX3/D+R88HfcuHHDXvEOqnxXFEVRhjnqJ11RhjfqdqZyNM2GN+rzXVEUH0yZMiXV92s7o2SF0aNHs8MOO7Bw4UI6OjqYM2cOs2bNYubMmSUt1GfMmMFPfvITVlllFY9fOzxR5buiKIoyrFGrV0UZ3mgbUDmaZsMbtXxXFMUH2s4oSjIeffTRvs1OK6GhoYGnnnqK5557rshqPcqKvdw95X7n83kmTpxIU1NTCqkwtFHlu6IoiqIoiqIoiqIoiqIoymLGWmutxcSJEyN9uEf9DqzhOzs7ue6667x+62qrrcaVV17pNcyhgCrfSX85E/jZOM5XOFmKC2TPN26WNkL0teTc14arWcgXX+H4jIuWs8rDyZI7iKy0mb7CyVr+g7pQGaqoS7Chi7qdURTFB+p2RlGSsfnmm7P55psnvr+3t7dIGV9KYZ9UqR/8fu2117j22muLwh0zZgzHHnvsYEZ9sUGV74qiKB7QJdqKMjTRulk5qhQdumjeKIqiKIqiKKXI5XJ9m6WmwQYbbEB3dzcvvvgiuVyOf/3rXwDstddefPLJJ+RyOVZYYQVGjhyZSvhDEVW+K4on1EpI8YEqEitH6+bQJUsWyVo3FR+oL3ZFURRFURSlmtTW1nLYYYf1/X766af55S9/yfXXX993LpfLseqqq7L//vuz7bbbVuEr/aLKd0VRFEVRlJTRSR5FURRFGb74cqGisoaiDD/y+TwfffQR3d3dRe5khsqx5ZZbsnDhQqZNm8a0adP47LPPeP311zn33HM599xz+fWvf80666xT7aRMDVW+K4qiKIqiKIqiLOboJJ+iKIqiDD9uv/12Lr/88mp/BgA1NTWJjvHjx/Ppp5/2Pff5559X8avTR5Xv+N1w01dYPsLJUlx84HMpeNbCSRtdpl85vtIsa2U5S2nmgyzVzaz1AVnJF8hWOcsSmi+Vk7V2Rt1oKVlC62blZCkuipImyy23XMHv8ePHM2rUKEaNGkVbW1vB3+D/1tZWampq+vy/J1WalzuUaFT5riiKoiiKoiiKoiRCLewVRVEUZeiw2Wab8fDDD3PjjTfy0EMPMX/+fGbMmEFvb2/sM7W1tbS2ttLa2srIkSP7/m9qaqK5uZnm5maampoKDvf8EkssQVtbG7lczmNsF09U+U76/tfA76ZuWcKHcJ81qyqfA6KsbISoKIqiDF+ytLGvUjm+5CYfZUCV4oqiZAlffvIVJQvU1tZyxBFHcMQRRwDiB769vZ158+Yxf/585s2b1/d/3O/p06ezcOHCvqOrq6tsuLlcjvHjxzNu3DhGjx7NyJEjGTVqFCNHjmTkyJGsv/76RZb5wxFVvmeMYNmUDiKVLKATCUqW8KHgA38bbWVFWeWLLCn4FMUHqkhWFEVRFEXpHzU1NX3W7H/84x957rnnqK2tpaenp+Do7u7u+7+2tpampibq6+tpaWlh0aJFLFiwoKQSvre3l+nTpzN9+vTYex555JFhbx2vyneyZfkcDLqzEif191k5WfP3qb7+lKygfvKHN9qfKUplZE2eURRFUSpDx4GKMjjccccdkcrxESNG0NraSmNjI42NjTQ1NfX9HxwNDQ3U1dVRW1sbe9jXARYsWNBnWb/55psPe8U7qPJdGeKo25mhSdZWWKhSTFEURVEURVEURVGUrHHuuecydepUnn/+eT744APmzZsHiJJ8wYIFZZ+vq6vrU7AH/9uHe762tpb6+nrq6up48MEHefzxx2lpaSl5LLHEEowdOzazm7aq8h1/Pt8hG+4AdFl7/8iKCxU7nLTJSpplsc6oj+TKyZLbmazlTZbQcqb4QMuZoiiKkjbq811RBodVV12VVVddte/3/Pnz+fjjj5k+fTqdnZ10d3cXHYFLmkquBee7urro6Ojo+7+9vZ329nY6OjrI5/Mlv7WpqYlx48ax6qqrss0227DlllumnTxeUOW70i/UD6eiVEZWJhLscLKCtmfDG62biqIoiqJkAZVpFUVJQmtra5FCvj/09vZy2WWX8dZbb1FbW9unbO/p6aGrq6tPKV9TU0NTUxO1tbXMnz+/pAJ+4cKFfPDBB3zwwQc88sgjXHHFFay++uoD+s6hgCrf8ed2JEv+xHy56dA06x9ZCUfzv39o3ayMLLVn6kKpcrKU/4ric2PfrMgAWdoMWdszRRneaBugKIoPent7yefzdHZ2cvvtt1f0bC6Xo7W1lR122IG2trYCdzX19fV9Lmva29tpbGxklVVWSSkWflHlO37dzmQFnVWvnCxaV/pYcq4MTVTJO7zJkrIqa2RtY1+lMrLUNqsSSVEURVEUpTxvvvkmRx11lJewcrkcvb29/X6+t7e3z+3N8ccfP4hfNrRR5Tt+B5BZsnzNUlx8kDXLZ1/hZCkuyvBGlWLDG02zoYvmzfBG879ydGJEURQfaDujKMno6OjwFlZvby8HHHAAzc3N1NTUUFtbS01NDTU1NeRyuYLfgXX8okWL6OzsLDgOOeQQb988FFDle8YIOo+sbITow7rSp9uhrFiK+ipnaYfhKxy14FVANygc7mSpD8gauoH08EbrZuXoClhFUXygG64qSjLWWWcdHn300bL3Be5iuru7aW9v59BDD2XevHkVh5fL5Yad8nygqPI9YwSCfVYseLJkjZS1uEB2LN/V4kHJCllqZxRFGbpkacJC201FURRFUYYDgWV6bW0tCxcuLKt4b25uZtSoUbS2tjJq1ChaWlpob29nrbXW4rnnnmP99dentrbW09cv3qjyXVGUYY+vjePUsm54owqeoUmWNqj0hbZnQxctz8MbtUhXFCVLqBGWoqRHQ0NDpP/2xsZGFi1aBIg7m46ODqZPn15wz3/+8x8ADjjgAA4++GAaGxtVCV8GVb7jb8NVHURWTpbczvgiKxu7Zsm9kQ5UFUXJEqp4Hbr49MWtbrQURVGS48uFik7AKYqShObmZh555JHIa729vXR1dRX5ae/s7CzY2PW2227jtttuA0SZ39TURHNzc8HfESNGMGHCBCZMmMDEiRNZc801GTt2rJc4DiVU+e4RVSQPb9QaSckSqngZmqhFsqIoiqIoipIF1Oe7olSHXC5HQ0MDDQ0NRdd+97vf8eabb7Jw4cK+I7CQt88F56dNm8a///3vvk1hW1pauP3222lubvYdraqiyndFURRlWKMKa0WpDK0ziqIoiqIoijL8WHrppVl66aVL3pPP58nn8/T09PT9nTlzJmeeeSbvvfceu+66KwCjRo1iiSWWoK2tjVGjRjFy5Eja2tpYccUV2W677cjlcj6i5AVVvmeMwGdZVixSFSUrZMUVAPirmz7TzAfq3mh4kyWXYIqiKIqiVIavFepZkp0VRUmPzs5O9t9/f2bPnl323lwu1+dKpqampkCxHvxvK9qTMnfuXObOnRt5raWlhc033zzxu4Y6qnzHr6uWLHW6WYqLD3z6yM1KOFnaOC5LcQnQulk5WWqblcrIUjnL2qA7Sz7ss9bXZCVfskbWJscVRVEUZbiRz+cTKd5BfMAHrmWi2HjjjVl55ZWpra2lpqaG2travv+D3/b/9n3BeYD58+czZ84cWltb2XTTTQcrqkMCVb6TrQ1Xs2j5rn7yK0OtKytHLZIVH/goZ+qmo3KytipFy0DlZKluZmkiQRm6ZGmVnaIoiqIMR5qamnj00UcLzvX09LBgwYK+Y/78+bS3t/f9v2DBAq699tqid40dO5YVV1yxz23MyiuvTGNjo6+oLBao8l1RFEVRFCVlVCmqKIqiKIqSHF1hoyh+qa2tZdSoUYwaNarkfa4C/oEHHuCBBx7o+11fX88GG2zAWWedNew2Vo1Dle+K4gm1ElKyRJYsRRXFB2r5riiVoXVGURRleJO2hwIdOytKaVyf7j09Pey+++7ssssufb87OzuZM2cOs2fPZvbs2Xz66ac89dRTPPPMM0ybNo2VV1652tEYEqjyXekX6uuxcjTNKkfTrHKyNMmjihfFl0uorNQZX6gVf+Voe6b4QOUmRVEURVGmTp3KOeecU+3PUKt3C1W+ky2f38GgK0txUiojS5v6+SJrG8dlKZyslDFQhWV/0Lqp+CBr5SwraJs5dFElv6IoiqIMXXp6egbtXfvuuy9jxoyhrq6uYMPUckdbWxtLL730oH3H4o4q39ENVytFLauGNj6s63QwXDlq9aioq57KyZLle9byRqkM7QMURVEUpTJ0kk9R+sd2223HdtttV/Kenp4eurq66OrqorOzk/fee49TTjml6L7bb7+d5uZmJk6cyPjx4xk9ejRjxoxhzJgxff+3tLTQ2NhYcDQ1NdHb20sul0srmosVqnxXFEXxgFrwKT7KgE+3Q74UiWqRrKSNr4mxLJUznRgb3mTJxZ2i+MKX//Is1U31+a4o6RFYqDc1NQGwxBJL8OijjwLQ0dHBxx9/XHR89tlnvPnmm8ycOZN8Pj+g8I877ji+8pWvDDgeiwuqfPeICqrDG83/oYsqESonS2nmKxxV8AxNsmaRnKW6qXVGURRFURRFUfzS3NzMSiutxEorrVR07cYbb+SGG24YcBgDVd4vbqjy3SO+rB6VoUmW/GNmzb1RluqmT0ViliySfdVNH0pRH2TNijdLZKk984WW58rRclY5WXI9liWZVlF8kTWZVlGU4cmTTz6Z+N66ujrq6+sjj4cffpjHHnuMLbfckv322y/z7mlU+e6RLFk+ZykuvtA0G7pkyeVAVpT8WbR8V4YmWVO8ZmmSxxdZUooqig9UplWUylG3M4qiZIEf//jHvPfee3R2dtLd3d3nMz74v5LjmWee4aWXXuLOO+/k6KOPZquttqp29FJDle+KoiiKolRE1ly1KIqiKIqiKIqiKKVZcsklWXLJJQflXa+99ho//vGP+eCDD3j66adV+a4oiqIoiqIoiqIoiqIoiqIMDh0dHfzhD38gn89TV1cXe9TU1NDb20tvby/5fH5I/427FhzB7xdeeAGApZdems0337zKOZEuqnxXFEVRFEVJGXXToCiKoijDF/X5rihKFDfeeCO///3vqxJ2Lpcjl8tRU1Pj/W9NTQ3rr78+W2yxBfvss09V4u8TVb7jryP0GZZuhDj08OlXOGvhpE2WfD5nrZxlKS6+wslSXLKE1s2hS5b6gCyRtXzJUnyyto+NoihDE21nlOHA4YcfzujRo1m0aBFdXV10d3fHHj09PXR1dfX9Dc6/++67LFq0iD/96U+JFeDBofhBle+KoiiKoiiKoiiKoiiKoigeaWxs5IADDhjQO6655hpuu+02xowZM0hfpQw2qnxXFEVRFEVRFEVRFEVRFEVZDOnp6eH73/8+ra2ttLa2MnLkSEaOHNn3f1NTEw0NDTQ0NFBfX099fX3f//Z5tYZPB1W+K4oyZPHlI3ny5MmphqEokH551rI8tNH2TFGGJlo3FUVRFEVZnPniF7/I//73P2bMmMHbb7/N/PnzWbBgQb/eFaWYD85NnDiR9ddfn2222Ya2trZBjkW2UeW7R3xutpYVBY+PNMuK/80s4tOnaFbqjC80zYY3qqwaumjdrBwfaQbpymZBOFnKG5/tjMqClaEbSCuK4oMpU6ak+n5tZ5Ss8IUvfIELL7yw4FxPTw8LFixg3rx5zJ8/n4ULF9LV1UVnZ2ffX/v/uL/2/6+99hp///vfufTSSznhhBNYZpllaGlpKTiamprUev7/2/vzOLnKOu//f5/aq7uquyt7B0ICJoSwhghBUEMTiSCKiEEFbpxRgRl/4wwDDuoM35EBvMdbEARxQdmFGZYBZRVBMIDsQZIAGsISJCzp7N3praprO78/kqrpTneSPknXVaeuej0fj/OoqnNO1bmus1XV51zncw2D4DsAwJcI8AIAAAAA4E0wGFRTU5OamppG7TNd19X111+vRx55RFdcccWw8wQCAcXj8XIwfs8999TFF1+sYDA4auWoRQTfAcAAAsn+RQu++sb2BwAAlWaqFTe/aQBUiuM4Ovvss3XWWWfpvffe08aNG9XX17fdYeXKlXrmmWe0YcMGTZw4sdrFryqC7wAAWIJAMuCdibQjy5Ytq+jnAwAAACY4jqO99tpLe+21V3nc4sWL9dJLLymZTCocDisQCOjtt9+WJJ166qk65JBD6vp/JMF3ADDAlvz1EsFX2MXksQl/MpUnn7ziAFC/TH0H8JsGqD/pdFrLli1TLpdToVBQsVgc9Fgath3vdb7tTc9kMnr11VeHlCuRSKinp0eStPfee5teLb5C8N0gk3+8bPmDx59VmGDTfmbbecamuphajk11sYltx6ZNbPoOsAnbxb+4aAnABM4zwMj8+te/1g033LDL7w8EAgoEAgoGg0MeS8P2ppceY7GYMplM+TP33HNP3XDDDYpEIqNRxZpH8B0ADCDnO+BPHJsAAKDSyPkOoFLmzJmjRx99VGvWrFE2m93ufAcccICam5uHDBMmTNCcOXPkOI7BUtcXgu+q/BehZN8fb4IV/mVi29ASDahvfAcAAAAAQPXtv//++tWvfjVonOu6ymQy2rx5s2688Ua98cYbeuedd9Tb2zvsZ1x33XWaPn26ieLWJYLvgGW4TRsAAAAAAKB+PPnkk7rooovKryORyA5bwpfMnj1bkyZNqmDJQPBdtOLdFTZ1Hsn2hwlcFIFNbNqfbaoLYBPusAFgE5v6fSFPOuAvixcv1ne+850h408++WTFYrFBQzweVzweVywWU0NDg6ZNm6ZQiNBwpbGG4WsERQAAAOoPvwEBAAB27u233x52/K9//Wslk0klEgl99atf1THHHGO4ZCgh+C67cr6XrkJXsqWQyc5caI3kHXcLAAAAAAAA2O8LX/iCDj30UHV3d6unp6f8WHr+yCOPaNGiRdp///01btw4BYPBahe57hB8BwAAAAAAAIAaEwwGNXPmzO1Of+WVV/T000/r6aefViAQUCKRUCKRKLeKnzdvnk488UQ5jmOw1PWF4DsAz0zdYWHTnQ/krkWl9wG2/67h2AQAAABgi3Xr1umFF15Qe3u72tvblcvlytOKxaK6urrU1dVVHvfSSy/pyCOP1Pjx46tR3LpA8N0ypT/3JtKCkHrEn0zkSKWTHe/IXQv2AX9iuwAAAACoVel0Wtdff73WrVsn13X1zDPPSJJCoZAmTZqkyZMn68ADDxzU2r30GAgENHHiRALvFUbwXQSRAa9MXuQBAAAAAADAUIsWLdJvfvObIeOvvfZa7bHHHopEIlUoFQYi+A4ABpDaAvAnjk0AAAAAteqEE07Q+PHjtXnzZq1fv17XXXedJOlrX/uaJCmVSumQQw7Rscceq3A4rFAopHA4POj59h6DwSC54EcBwXcAAAAAAIAKaWtrq+jnX3XVVZIq2yfXwOUA8A/HcTR37tzy64ULF+rNN99Ue3u7Vq9erZtvvllPPPHEqGcu+MEPfqAjjjhiVD/TVgTfVfkvQslcqzdTHWFWehkml2Nb6hQTrThtW2eACXS4CvgTxybgjak7hgDUN1MXLADbRKNRHXjggTrwwAMlbQnGr1u3TrlcTvl8fkSPixYt0muvvbbD5bS0tBiojR0IvgOAAXTqCPgTxyYAAAAAWyUSCSUSCU/vWbNmzaDg+8yZM7X//vtrn3320RFHHEEHrR4RfMcuMRWsKLXkh7+YusOCloLekb8aJrCf1TeTrV5N7WeV/k1j4zqrNM4z/sX/AMA7Uxf6OTYBjIb58+dr3bp16ujoUGdnp15//XW9/vrrkqSxY8fq3//93xWNRhWJRMqPA58Hg8Eq18BfCL4DgEVoxQsAAAAAAHbV/vvvr0suuaT8+tJLL9XDDz8sSdq4caPOO+88T583c+ZM/eIXvxjVMtYSgu8GkR8RgC3IkexPfM/AxLEJAAC8ocNVALXsm9/8pj7/+c/LdV1ls1lls1n19/crm82qr69Pl1122Q7fP336dEMl9SeC74AhBMUAAAAAoP6QdgZALQuHw5oxY8aw0wqFgh599FEtXbq0PO6QQw7RIYccogMOOEBz5841VUzfIvgOAKhrXBgD6pupO3kIiMAWfG8CAOAfXV1dev7555XL5VQsFlUoFAY9lp7vaPy247Z9z0jet+eee+r999+XJL388st6+eWXJUkPPPCA5w5fbUPwXeauQptcli05n23KX22yLrYtB/7DsblrTCzHprrAO1P7s237mS37M+dmmMDFJAAmcJ4BRubee+/VTTfdtNufEwgEyp2mRqNRhcNhBYNBBQKBQY+l54FAQNFotDx+7NixmjZtWnl6Pp9Xa2urGhsbR6GWtY3gOwAYYKqVGHnSAW84NgEAAADUqqOOOkovvfSSVq1apc2bN+/y5xSLRWUyGWUymfK4UgB+4LhvfetbOuGEE3arzPWG4Dt8zURQhFZV3pVaCNjS4aZtKQdM3Qpuy/Y3xVRHmASSvbGtdS2dIXvHselPXBjzL9LOADDBVCe1QK2bPn26fvzjH5dfd3d3q6urS/l8vjzkcrlBrweOLxQKw04fOO2uu+4qf/69996rTCajtrY2jRkzphpVrjkE31X5k7r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      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import missingno as msno\n",
    "\n",
    "# Visualize missing values\n",
    "msno.matrix(data)\n",
    "\n",
    "# Check the type of missing values\n",
    "msno.dendrogram(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "df352b87",
   "metadata": {
    "id": "df352b87"
   },
   "outputs": [],
   "source": [
    "data = data.dropna(subset=[target]).query(target+'!=0').reset_index(drop=True)\n",
    "data_proc = data.drop(['year', 'company'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2d527e6c",
   "metadata": {
    "id": "2d527e6c"
   },
   "outputs": [],
   "source": [
    "def preprocessing(df, thrsh_var=0.1, thrsh_missing=0.5, imputation={'numeric':'mean','categorical':'mode'}):\n",
    "    \n",
    "    \n",
    "    # remove columns with percentage of missing values above a certain threshold\n",
    "    # thrsh_missing = df.isnull().sum().sum()/np.product(df.shape)\n",
    "    pct_col_missing = df.isnull().sum() / len(df)\n",
    "    col_selected = pct_col_missing[pct_col_missing < thrsh_missing].index\n",
    "    df = df[col_selected]\n",
    "    \n",
    "    bool_cols = list(df.nunique()[df.nunique() == 2].index)\n",
    "    numeric_cols = [col for col in df.columns if col not in bool_cols]\n",
    "        \n",
    "    # OHE\n",
    "    # df = pd.get_dummies(df)\n",
    "    \n",
    "    # scale variables\n",
    "    \n",
    "    \n",
    "    # fill in missing values using imputation\n",
    "    def Imputation(type_, df):\n",
    "        from sklearn.impute import SimpleImputer\n",
    "\n",
    "        if type_ == 'mean':\n",
    "\n",
    "            df_imputed = df.fillna(df.mean()).reset_index(drop=True)\n",
    "\n",
    "        elif type_ == 'median':\n",
    "\n",
    "            df_imputed = df.fillna(df.median()).reset_index(drop=True)\n",
    "\n",
    "        elif type_ == 'mode':\n",
    "\n",
    "            imputer_mode = SimpleImputer(strategy='most_frequent')\n",
    "            df_imputed = pd.DataFrame(imputer_mode.fit_transform(df), columns=df.columns).astype('int').reset_index(drop=True)\n",
    "\n",
    "        elif type_ == 'KNN':\n",
    "\n",
    "            # pip install --upgrade scikit-learn\n",
    "            from sklearn.impute import KNNImputer\n",
    "\n",
    "            imputer_KNN = KNNImputer(n_neighbors=5)\n",
    "            df_imputed = pd.DataFrame(imputer_KNN.fit_transform(df), columns=df.columns).reset_index(drop=True)\n",
    "\n",
    "        elif 'Regression' in type_:\n",
    "\n",
    "            df_missing = df[df.isnull().any(axis=1)]\n",
    "            df_notmissing = df[~df.isnull().any(axis=1)]\n",
    "\n",
    "            if type_ == 'RFRegression':\n",
    "\n",
    "                from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "                reg = RandomForestRegressor()\n",
    "\n",
    "            elif type_ == 'HGBRegression':\n",
    "\n",
    "                from sklearn.experimental import enable_hist_gradient_boosting  # Enable HistGradientBoostingRegressor\n",
    "                from sklearn.ensemble import HistGradientBoostingRegressor\n",
    "\n",
    "                reg = RandomForestRegressor()\n",
    "\n",
    "            reg.fit(data_notmissing.drop(target, axis=1), data_notmissing[target])\n",
    "\n",
    "            imputer = SimpleImputer()\n",
    "            df_missing_imputed = pd.DataFrame(imputer.fit_transform(df_missing.drop(target, axis=1)))\n",
    "            df_missing_imputed.columns = df_missing.drop(target, axis=1).columns\n",
    "            df_missing_imputed[target] = reg.predict(df_missing_imputed)\n",
    "\n",
    "            df_imputed = pd.concat([df_notmissing, df_missing_imputed], axis=0)\n",
    "\n",
    "        elif type_ == 'MI': # multiple imputation\n",
    "\n",
    "            from sklearn.experimental import enable_iterative_imputer\n",
    "            from sklearn.impute import IterativeImputer\n",
    "\n",
    "            imputer_multiple = IterativeImputer(max_iter=50)\n",
    "            df_imputed = pd.DataFrame(imputer_multiple.fit_transform(df), columns=df.columns).reset_index(drop=True)\n",
    "            \n",
    "        return df_imputed\n",
    "    \n",
    "    \n",
    "\n",
    "    numeric_imputed = Imputation(imputation['numeric'], df[numeric_cols])\n",
    "    categorical_imputed = Imputation(imputation['categorical'], df[bool_cols])\n",
    "    df_imputed = pd.concat([numeric_imputed, categorical_imputed], axis=1)\n",
    "    \n",
    "    \n",
    "    # Scaling\n",
    "    # Min-max scaling, Standardization, Robust scaling, Log transformation\n",
    "\n",
    "    # Outliers\n",
    "    # Z-score method, the interquartile range (IQR) method, and the Tukey method\n",
    "    '''\n",
    "    threshold = 2\n",
    "    scaler = StandardScaler()\n",
    "    df_scaled = pd.DataFrame(scaler.fit_transform(df_imputed), columns=df_imputed.columns)\n",
    "    df_no_outliers = df_scaled[(np.abs(zscore(df_scaled)) < threshold).all(axis=1)]\n",
    "    '''\n",
    "\n",
    "    from sklearn.preprocessing import RobustScaler\n",
    "    \n",
    "    # Scale the selected columns using RobustScaler\n",
    "    scaler = RobustScaler()\n",
    "    df_imputed[numeric_cols] = pd.DataFrame(scaler.fit_transform(df_imputed[numeric_cols]), columns=numeric_cols)\n",
    "        \n",
    "\n",
    "        \n",
    "    # Eliminate semi-constant features\n",
    "    \n",
    "    from sklearn.feature_selection import VarianceThreshold\n",
    "    \n",
    "    selector = VarianceThreshold(threshold=thrsh_var)\n",
    "    df_numeric = selector.fit_transform(df_imputed[numeric_cols])\n",
    "    selected_cols = df_imputed[numeric_cols].columns[selector.get_support(indices=True)]\n",
    "    df_numeric_new = pd.DataFrame(df_numeric, columns=selected_cols)\n",
    "    bool_counts = df_imputed[bool_cols].apply(pd.Series.value_counts)\n",
    "    bool_thrsh = thrsh_var*df_imputed[bool_cols].shape[0]\n",
    "    df_categorical_new = df_imputed[bool_cols].drop(columns=bool_counts.columns[(bool_counts < bool_thrsh).any()])\n",
    "    df_new = pd.concat([df_numeric_new, df_categorical_new], axis=1)\n",
    "\n",
    "    # Transformation (Categorical)\n",
    "\n",
    "    return df_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a24ded30",
   "metadata": {
    "id": "a24ded30"
   },
   "outputs": [],
   "source": [
    "data_preprocessed = preprocessing(data_proc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ecb60432",
   "metadata": {
    "id": "ecb60432"
   },
   "outputs": [],
   "source": [
    "data_new = data_preprocessed.copy()\n",
    "data_new['company'] = data['company']\n",
    "data_new['year'] = data['year']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3ce523c6",
   "metadata": {
    "id": "3ce523c6"
   },
   "outputs": [],
   "source": [
    "# data_new.dropna(inplace=True)\n",
    "df = data_preprocessed"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e935269",
   "metadata": {
    "id": "6e935269"
   },
   "source": [
    "### 特征工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4512af23",
   "metadata": {
    "id": "4512af23"
   },
   "outputs": [],
   "source": [
    "X_new = df.drop([target], axis=1)\n",
    "Y_new = df[target]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e68967cc",
   "metadata": {
    "id": "e68967cc"
   },
   "source": [
    "### 特征选择"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1a52e257",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1a52e257",
    "outputId": "1e5e6fa7-258a-4542-8198-e9aef9547b65"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "向前选择法得到的因子有:\n",
      "\n",
      "['SULPHUR_DIOXIDE_SULPHUR_OXIDE_EM', 'TOTAL_WATER_DISCHARGED', 'ENERGY_CONSUMPTION', 'CLIMATE_RISKS', 'WATER_POLICY'] \n",
      "\n",
      "\n",
      "向后选择法得到的因子有:\n",
      "\n",
      "['HAZARDOUS_WASTE', 'TOTAL_WATER_WITHDRAWAL', 'GHG_SCOPE_2_LOCATION_BASED', 'NOX_EMISSIONS', 'WASTE_REDUCTION', 'GHG_SCOPE_1', 'NAT_GAS_USED', 'BIODIVERSITY_POLICY', 'TOTAL_WASTE', 'CLIMATE_CHG_OPPORTUNITIES', 'ELECTRICITY_USED', 'CLIMATE_CHG_POLICY', 'ENVIRON_SUPPLY_MGT'] \n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Backward and forward elimination\n",
    "import statsmodels.api as sm\n",
    "\n",
    "def backward_elimination(X, Y, corr_threshold=0.3, significance=0.05):\n",
    "    num_features = X.shape[1]\n",
    "    X_selected = X.copy()\n",
    "    regressor_OLS = sm.OLS(Y, X_selected).fit()\n",
    "    while max(regressor_OLS.pvalues) > significance:\n",
    "        regressor_OLS = sm.OLS(Y, X_selected).fit()\n",
    "        corr_matrix = np.corrcoef(X_selected, rowvar=False)\n",
    "        max_corr = np.abs(corr_matrix - np.identity(X_selected.shape[1]))\n",
    "        max_corr = np.max(max_corr, axis=1)\n",
    "        if np.max(max_corr) > corr_threshold:\n",
    "            j = np.argmax(max_corr)\n",
    "            X_selected = X_selected.drop(X_selected.columns[j], axis=1)\n",
    "        else:\n",
    "            break\n",
    "    return X_selected\n",
    "\n",
    "def forward_elimination(X, Y, corr_threshold=0.3, significance=0.05):\n",
    "    num_features = X.shape[1]\n",
    "    X_selected = pd.DataFrame()\n",
    "    remaning_features = X[[col for col in X.columns if col not in X_selected.columns]]\n",
    "    regressor_OLS = sm.OLS(Y, remaning_features).fit()\n",
    "    while min(regressor_OLS.pvalues) < significance:\n",
    "        remaning_features = X[[col for col in X.columns if col not in X_selected.columns]]\n",
    "        regressor_OLS = sm.OLS(Y, remaning_features).fit()\n",
    "        corr_matrix = np.corrcoef(remaning_features, rowvar=False)\n",
    "        max_corr = np.abs(corr_matrix - np.identity(remaning_features.shape[1]))\n",
    "        max_corr = np.max(max_corr, axis=1)\n",
    "        if np.max(max_corr) > corr_threshold:\n",
    "            j = np.argmax(max_corr)\n",
    "            X_selected = pd.concat([X_selected, remaning_features[remaning_features.columns[j]]], axis=1)\n",
    "        else:\n",
    "            break\n",
    "    return X_selected\n",
    "\n",
    "\n",
    "Xslct_backward = backward_elimination(X_new, Y_new)\n",
    "Xslct_forward = forward_elimination(X_new, Y_new)\n",
    "\n",
    "print('向前选择法得到的因子有:\\n')\n",
    "print(list(Xslct_backward.columns), '\\n\\n')\n",
    "print('向后选择法得到的因子有:\\n')\n",
    "print(list(Xslct_forward.columns), '\\n\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5aRn7ABmYSOa",
   "metadata": {
    "id": "5aRn7ABmYSOa"
   },
   "source": [
    "结构方程模型构建因子相关图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1a1b309d",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 377
    },
    "id": "1a1b309d",
    "outputId": "7d86514b-48df-4e5f-9f69-85693811c6e7"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:Fisher Information Matrix is not PD.Moore-Penrose inverse will be used instead of Cholesky decomposition. See 10.1109/TSP.2012.2208105.\n"
     ]
    },
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       "<title>climate_change&#45;&gt;CLIMATE_CHG_OPPORTUNITIES</title>\n",
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       "<title>climate_change&#45;&gt;ENVIRON_DISCLOSURE_SCORE</title>\n",
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       "</g>\n",
       "<!-- GHG_SCOPE_1 -->\n",
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       "<title>GHG_SCOPE_1</title>\n",
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       "<!-- GHG_SCOPE_2_LOCATION_BASED -->\n",
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       "<!-- climate_change&#45;&gt;GHG_SCOPE_2_LOCATION_BASED -->\n",
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       "</g>\n",
       "<!-- biodiversity -->\n",
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       "<title>biodiversity</title>\n",
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       "</g>\n",
       "<!-- BIODIVERSITY_POLICY -->\n",
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       "<title>biodiversity&#45;&gt;BIODIVERSITY_POLICY</title>\n",
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       "<title>supply_chain</title>\n",
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       "<title>supply_chain&#45;&gt;ENVIRON_SUPPLY_MGT</title>\n",
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      ],
      "text/plain": [
       "<graphviz.graphs.Digraph at 0x2412695cfa0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pip install graphviz\n",
    "from semopy import semplot\n",
    "import semopy as sem\n",
    "from semopy import Model\n",
    "import os\n",
    "\n",
    "# Define the model\n",
    "model_spec_SEM = '''\n",
    "    # Measurement model\n",
    "    air_quality =~ NOX_EMISSIONS \n",
    "    waste =~ HAZARDOUS_WASTE + WASTE_REDUCTION + TOTAL_WASTE\n",
    "    water =~ TOTAL_WATER_WITHDRAWAL\n",
    "    energy =~ NAT_GAS_USED + ELECTRICITY_USED\n",
    "    climate_change =~ GHG_SCOPE_1 + GHG_SCOPE_2_LOCATION_BASED + CLIMATE_CHG_OPPORTUNITIES\n",
    "    biodiversity =~ BIODIVERSITY_POLICY\n",
    "    supply_chain =~ ENVIRON_SUPPLY_MGT\n",
    "    \n",
    "    # Structural model\n",
    "    ENVIRON_DISCLOSURE_SCORE ~ air_quality + waste + water + energy + climate_change + biodiversity + supply_chain\n",
    "'''\n",
    "\n",
    "# Fit the model\n",
    "model_SEM = Model(model_spec_SEM)\n",
    "model_SEM.fit(df)\n",
    "\n",
    "# print(model_SEM.inspect())\n",
    "# print(sem.calc_stats(model_SEM))\n",
    "semplot(model_SEM, filename='my_sem_plot.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ro2aW0lyYcxX",
   "metadata": {
    "id": "ro2aW0lyYcxX"
   },
   "source": [
    "# 机器学习部分模型选择"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "rMT7jonjSmNW",
   "metadata": {
    "id": "rMT7jonjSmNW"
   },
   "source": [
    "## Logistic 回归模型搭建"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "tQGvjUz6SEpV",
   "metadata": {
    "id": "tQGvjUz6SEpV"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import tensorflow as tf\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import train_test_split, cross_val_score, cross_val_predict\n",
    "from sklearn.metrics import accuracy_score, f1_score, roc_auc_score, confusion_matrix\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "sX0YeJHgTvxe",
   "metadata": {
    "id": "sX0YeJHgTvxe"
   },
   "outputs": [],
   "source": [
    "def generate(y):\n",
    "    mean_y = np.mean(y)  # 计算Y的均值\n",
    "    x = np.zeros_like(y)  # 初始化X向量为0\n",
    "    x[y > mean_y] = 1  # 将Y向量大于均值的位置设置为1\n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6m6KzlGrT1u9",
   "metadata": {
    "id": "6m6KzlGrT1u9"
   },
   "outputs": [],
   "source": [
    "Y_new = generate(Y_new)\n",
    "X_selected = X_new.loc[:, ['SULPHUR_DIOXIDE_SULPHUR_OXIDE_EM', 'TOTAL_WATER_DISCHARGED', 'ENERGY_CONSUMPTION', 'CLIMATE_RISKS', 'WATER_POLICY'] \n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ZIr5j-qWSxng",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ZIr5j-qWSxng",
    "outputId": "a201e8b2-4a5f-48d7-b605-98116b399d76"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "交叉验证:\n",
      "正确度: 0.6838905775075989\n",
      "AUC: 0.675\n"
     ]
    }
   ],
   "source": [
    "# Create a logistic regression object\n",
    "logistic = LogisticRegression()\n",
    "logistic.fit(X_selected, Y_new)\n",
    "\n",
    "# Evaluate the performance using cross-validation\n",
    "scores = cross_val_score(logistic, X_selected, Y_new, cv=3)\n",
    "y_pred_cv = cross_val_predict(logistic, X_selected, Y_new, cv=3)\n",
    "\n",
    "# Compute the metrics using cross-validation\n",
    "accuracy_cv = accuracy_score(Y_new, y_pred_cv)\n",
    "f1_score_cv = f1_score(Y_new, y_pred_cv, average=None)\n",
    "auc_cv = roc_auc_score(Y_new, logistic.predict(X_selected))\n",
    "\n",
    "# Print the results\n",
    "print(\"交叉验证:\")\n",
    "print(\"正确度:\", scores.mean())\n",
    "print(\"AUC:\", auc_cv)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "J2rwQFnQYub9",
   "metadata": {
    "id": "J2rwQFnQYub9"
   },
   "source": [
    "## 神经网络-Keras回归预测模型搭建"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "j8guIV4oVVIL",
   "metadata": {
    "id": "j8guIV4oVVIL"
   },
   "outputs": [],
   "source": [
    "# import the modules\n",
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.metrics import roc_curve, roc_auc_score, classification_report, accuracy_score, precision_score, f1_score, recall_score\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "iYqTdKZPVfqD",
   "metadata": {
    "id": "iYqTdKZPVfqD"
   },
   "outputs": [],
   "source": [
    "cb = tf.keras.callbacks.EarlyStopping(monitor='val_loss', patience=2)\n",
    "\n",
    "keras_model = keras.models.Sequential([\n",
    "    keras.layers.Dense(120, input_shape=(5,), activation=\"tanh\"),\n",
    "    keras.layers.Dropout(0.5),\n",
    "    keras.layers.Dense(60, activation=\"tanh\"),\n",
    "    keras.layers.Dropout(0.5),\n",
    "    keras.layers.Dense(30, activation=\"tanh\"),\n",
    "    keras.layers.Dropout(0.5),\n",
    "    keras.layers.Dense(1, activation=\"sigmoid\")\n",
    "])\n",
    "keras_model.compile(loss=\"binary_crossentropy\",\n",
    "              optimizer=\"Adam\",\n",
    "              metrics=[\"Recall\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "bUuDfA91VkWR",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "bUuDfA91VkWR",
    "outputId": "37ed5e95-9fd8-467b-94ef-08433cc6e3b3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "8/8 [==============================] - 1s 36ms/step - loss: 0.7873 - recall: 0.5055 - val_loss: 0.6539 - val_recall: 0.9907\n",
      "Epoch 2/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.7151 - recall: 0.7506 - val_loss: 0.6529 - val_recall: 0.9439\n",
      "Epoch 3/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.6752 - recall: 0.8168 - val_loss: 0.6396 - val_recall: 0.9252\n",
      "Epoch 4/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.6929 - recall: 0.7373 - val_loss: 0.6249 - val_recall: 0.9439\n",
      "Epoch 5/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.6601 - recall: 0.7660 - val_loss: 0.6083 - val_recall: 0.9065\n",
      "Epoch 6/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.6415 - recall: 0.7351 - val_loss: 0.5974 - val_recall: 0.9065\n",
      "Epoch 7/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.6567 - recall: 0.7417 - val_loss: 0.5885 - val_recall: 0.8785\n",
      "Epoch 8/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.6268 - recall: 0.7550 - val_loss: 0.5796 - val_recall: 0.8879\n",
      "Epoch 9/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.6168 - recall: 0.7572 - val_loss: 0.5709 - val_recall: 0.8785\n",
      "Epoch 10/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.6175 - recall: 0.7748 - val_loss: 0.5666 - val_recall: 0.8692\n",
      "7/7 [==============================] - 0s 1ms/step\n",
      "AUC: 0.7815 +/- 0.0000\n",
      "正确度: 0.7273 +/- 0.0000\n",
      "Epoch 1/10\n",
      "8/8 [==============================] - 0s 12ms/step - loss: 0.6161 - recall: 0.7494 - val_loss: 0.5364 - val_recall: 0.9027\n",
      "Epoch 2/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.6007 - recall: 0.7562 - val_loss: 0.5274 - val_recall: 0.8761\n",
      "Epoch 3/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5944 - recall: 0.7606 - val_loss: 0.5224 - val_recall: 0.8850\n",
      "Epoch 4/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5945 - recall: 0.7562 - val_loss: 0.5164 - val_recall: 0.8584\n",
      "Epoch 5/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5866 - recall: 0.7517 - val_loss: 0.5075 - val_recall: 0.8850\n",
      "Epoch 6/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5788 - recall: 0.7718 - val_loss: 0.4993 - val_recall: 0.9115\n",
      "Epoch 7/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5676 - recall: 0.7696 - val_loss: 0.4932 - val_recall: 0.8850\n",
      "Epoch 8/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5952 - recall: 0.6980 - val_loss: 0.4879 - val_recall: 0.9027\n",
      "Epoch 9/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5697 - recall: 0.7562 - val_loss: 0.4794 - val_recall: 0.8850\n",
      "Epoch 10/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5771 - recall: 0.7338 - val_loss: 0.4739 - val_recall: 0.8938\n",
      "7/7 [==============================] - 0s 1ms/step\n",
      "AUC: 0.8128 +/- 0.0313\n",
      "正确度: 0.7475 +/- 0.0202\n",
      "Epoch 1/10\n",
      "8/8 [==============================] - 0s 17ms/step - loss: 0.5623 - recall: 0.7785 - val_loss: 0.4794 - val_recall: 0.8053\n",
      "Epoch 2/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5536 - recall: 0.7494 - val_loss: 0.4746 - val_recall: 0.8053\n",
      "Epoch 3/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5379 - recall: 0.8031 - val_loss: 0.4784 - val_recall: 0.7965\n",
      "Epoch 4/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5714 - recall: 0.7584 - val_loss: 0.4811 - val_recall: 0.7699\n",
      "7/7 [==============================] - 0s 1ms/step\n",
      "AUC: 0.8204 +/- 0.0278\n",
      "正确度: 0.7369 +/- 0.0223\n",
      "Epoch 1/10\n",
      "8/8 [==============================] - 0s 12ms/step - loss: 0.5488 - recall: 0.7220 - val_loss: 0.4742 - val_recall: 0.9035\n",
      "Epoch 2/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5210 - recall: 0.7578 - val_loss: 0.4791 - val_recall: 0.9123\n",
      "Epoch 3/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5156 - recall: 0.8139 - val_loss: 0.4813 - val_recall: 0.9298\n",
      "7/7 [==============================] - 0s 1ms/step\n",
      "AUC: 0.8278 +/- 0.0272\n",
      "正确度: 0.7405 +/- 0.0203\n",
      "Epoch 1/10\n",
      "8/8 [==============================] - 0s 11ms/step - loss: 0.5473 - recall: 0.8031 - val_loss: 0.4258 - val_recall: 0.8584\n",
      "Epoch 2/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5569 - recall: 0.7740 - val_loss: 0.4220 - val_recall: 0.8319\n",
      "Epoch 3/10\n",
      "8/8 [==============================] - 0s 9ms/step - loss: 0.5203 - recall: 0.7696 - val_loss: 0.4182 - val_recall: 0.8319\n",
      "Epoch 4/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5407 - recall: 0.7606 - val_loss: 0.4167 - val_recall: 0.8407\n",
      "Epoch 5/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5333 - recall: 0.7740 - val_loss: 0.4158 - val_recall: 0.8761\n",
      "Epoch 6/10\n",
      "8/8 [==============================] - 0s 6ms/step - loss: 0.5346 - recall: 0.8009 - val_loss: 0.4128 - val_recall: 0.8761\n",
      "Epoch 7/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5111 - recall: 0.7987 - val_loss: 0.4119 - val_recall: 0.8584\n",
      "Epoch 8/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5162 - recall: 0.7718 - val_loss: 0.4117 - val_recall: 0.8584\n",
      "Epoch 9/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.4963 - recall: 0.8166 - val_loss: 0.4095 - val_recall: 0.8407\n",
      "Epoch 10/10\n",
      "8/8 [==============================] - 0s 7ms/step - loss: 0.5152 - recall: 0.7897 - val_loss: 0.4063 - val_recall: 0.8407\n",
      "7/7 [==============================] - 0s 1ms/step\n",
      "AUC: 0.8412 +/- 0.0362\n",
      "正确度: 0.7548 +/- 0.0339\n"
     ]
    }
   ],
   "source": [
    "# Perform k-fold cross-validation\n",
    "k = 5\n",
    "kf = KFold(n_splits=k, shuffle=True, random_state=42)\n",
    "f1_scores_0 = []\n",
    "f1_scores_1 = []\n",
    "auc_scores = []\n",
    "acc_scores = []\n",
    "for train_idx, valid_idx in kf.split(X_selected):\n",
    "  X_true_train, Y_true_train = X_selected.iloc[train_idx], Y_new[train_idx]\n",
    "  X_valid, Y_valid = X_selected.iloc[valid_idx], Y_new[valid_idx]\n",
    "\n",
    "  # Train the model\n",
    "  cb = tf.keras.callbacks.EarlyStopping(monitor='val_loss', patience=2)\n",
    "  keras_model.fit(X_true_train, Y_true_train, validation_data=(X_valid, Y_valid), epochs=10, batch_size=100, callbacks=[cb])\n",
    "\n",
    "  # Make predictions on validation set\n",
    "  Y_valid_pred = keras_model.predict(X_valid)\n",
    "  Y_valid_pred_bool = np.round(Y_valid_pred)\n",
    "\n",
    "  # Compute performance metrics for each class\n",
    "  f1_scores_0.append(f1_score(Y_valid, Y_valid_pred_bool, pos_label=0))\n",
    "  f1_scores_1.append(f1_score(Y_valid, Y_valid_pred_bool, pos_label=1))\n",
    "  auc_scores.append(roc_auc_score(Y_valid, Y_valid_pred))\n",
    "  acc_scores.append(accuracy_score(Y_valid, Y_valid_pred_bool))\n",
    "\n",
    "  # Report the performance metrics\n",
    "  print(\"AUC: {:.4f} +/- {:.4f}\".format(np.mean(auc_scores), np.std(auc_scores)))\n",
    "  print(\"正确度: {:.4f} +/- {:.4f}\".format(np.mean(acc_scores), np.std(acc_scores)))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sbk2jX5dZMbe",
   "metadata": {
    "id": "sbk2jX5dZMbe"
   },
   "source": [
    "# 支持向量机"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "kF466nVCWa6o",
   "metadata": {
    "id": "kF466nVCWa6o"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn import svm\n",
    "from sklearn.metrics import accuracy_score, f1_score, roc_auc_score\n",
    "from sklearn.model_selection import cross_val_predict, StratifiedKFold\n",
    "from sklearn.datasets import make_classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2IL6yXoAWjO2",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "2IL6yXoAWjO2",
    "outputId": "d5cb0a03-71f4-4271-b00e-9de4299dede4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "正确度: 0.7082066869300911\n",
      "AUC: 0.675\n"
     ]
    }
   ],
   "source": [
    "# Create an SVM classifier object\n",
    "svm_classifier = svm.SVC(kernel='linear', probability=True, random_state=42)\n",
    "\n",
    "# Use cross-validation to make predictions on the dataset\n",
    "cv = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)\n",
    "y_pred = cross_val_predict(svm_classifier, X_selected, Y_new, cv=cv)\n",
    "\n",
    "# Calculate the accuracy, F1-score, and AUC for both classes\n",
    "accuracy = accuracy_score(Y_new, y_pred)\n",
    "f1_0 = f1_score(Y_new, y_pred, pos_label=0)\n",
    "f1_1 = f1_score(Y_new, y_pred, pos_label=1)\n",
    "auc = roc_auc_score(Y_new, y_pred)\n",
    "\n",
    "# Print the results\n",
    "print('正确度:', accuracy)\n",
    "print('AUC:', auc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ONaX3sa2ZYnH",
   "metadata": {
    "id": "ONaX3sa2ZYnH"
   },
   "source": [
    "对所有的模型的表现进行比较之后，我们觉得使用AUC和正确度都最大的DNN-keras神经网络模型来对pdf中涉及的公司表现进行预测。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4qm-BDLNcMwD",
   "metadata": {
    "id": "4qm-BDLNcMwD"
   },
   "source": [
    "# 自然语言处理部分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "blQWCx69XDsp",
   "metadata": {
    "id": "blQWCx69XDsp"
   },
   "outputs": [],
   "source": [
    "import io\n",
    "import pdfminer\n",
    "from pdfminer.converter import TextConverter\n",
    "from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter\n",
    "from pdfminer.pdfpage import PDFPage\n",
    "import openai\n",
    "import re\n",
    "import textwrap3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "Q9oc3ulGc3Ui",
   "metadata": {
    "id": "Q9oc3ulGc3Ui"
   },
   "outputs": [],
   "source": [
    "openai.api_key = \"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\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bqQ0qIYRc6HZ",
   "metadata": {
    "id": "bqQ0qIYRc6HZ"
   },
   "outputs": [],
   "source": [
    "import chardet\n",
    "def convert_pdf_to_txt(path):\n",
    "    resource_manager = PDFResourceManager()\n",
    "    fake_file_handle = io.StringIO()\n",
    "    converter = TextConverter(resource_manager, fake_file_handle)\n",
    "    page_interpreter = PDFPageInterpreter(resource_manager, converter)\n",
    "\n",
    "    with open(path,'rb') as fh:\n",
    "        for page in PDFPage.get_pages(fh, caching=True, check_extractable=True):\n",
    "            page_interpreter.process_page(page)\n",
    "\n",
    "        text = fake_file_handle.getvalue()\n",
    "\n",
    "    converter.close()\n",
    "    fake_file_handle.close()\n",
    "\n",
    "    return text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1af5b95c",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "esg_report = convert_pdf_to_txt('test3.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "XP6J_YMedKhb",
   "metadata": {
    "id": "XP6J_YMedKhb"
   },
   "outputs": [],
   "source": [
    "def generate_summary(esg_reports):\n",
    "    # 使用ChatGPT生成ESG报告的摘要\n",
    "    response = openai.Completion.create(\n",
    "        engine=\"text-davinci-002\",\n",
    "        prompt=f\"Please summarize the following ESG report: {esg_reports}\",\n",
    "        max_tokens=1024,\n",
    "        n=1,\n",
    "        stop=None,\n",
    "        temperature=0.5,\n",
    "    )\n",
    "\n",
    "    summary = response.choices[0].text\n",
    "    return summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "-EJIUH7OdOpZ",
   "metadata": {
    "id": "-EJIUH7OdOpZ"
   },
   "outputs": [],
   "source": [
    "def generate_text(esg_reports):\n",
    "    response = openai.Completion.create(\n",
    "        engine=\"text-davinci-002\",\n",
    "        prompt=f\"Please classify and extract named entities from the following ESG report: {esg_reports}\",\n",
    "        max_tokens=1024,\n",
    "        n=1,\n",
    "        stop=None,\n",
    "        temperature=0.5,\n",
    "    )\n",
    "    entities = response.choices[0].text\n",
    "    return entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "Mf_JMpBCdXij",
   "metadata": {
    "id": "Mf_JMpBCdXij"
   },
   "outputs": [],
   "source": [
    "def company_name(entities):\n",
    "        response=openai.Completion.create(\n",
    "                engine=\"text-davinci-002\",\n",
    "                prompt=f\"Please search out all the company name in the following entities in a list: {entities}\",\n",
    "                max_tokens=1024,\n",
    "                n=1,\n",
    "                stop=None,\n",
    "                temperature=0.5,\n",
    "        )\n",
    "        companies= response.choices[0].text\n",
    "        companies= companies.split('\\n')\n",
    "        return companies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "IBDLM823dcWW",
   "metadata": {
    "id": "IBDLM823dcWW"
   },
   "outputs": [],
   "source": [
    "def esg_indicators(entities):\n",
    "        response=openai.Completion.create(\n",
    "                engine=\"text-davinci-002\",\n",
    "                prompt=f\"Please search out all the ESG indicator name in the following entities in a list: {entities}\",\n",
    "                max_tokens=1024,\n",
    "                n=1,\n",
    "                stop=None,\n",
    "                temperature=0.5,\n",
    "        )\n",
    "        esg_indicators= response.choices[0].text\n",
    "        esg_indicators= esg_indicators.split('\\n')\n",
    "        return esg_indicators\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "qw_0ug9bdgUO",
   "metadata": {
    "id": "qw_0ug9bdgUO"
   },
   "outputs": [],
   "source": [
    "def find_indicators(esg_reports,esg_indicators):\n",
    "        response=openai.Completion.create(\n",
    "                engine=\"text-davinci-002\",\n",
    "                prompt=f\"In the folling report:{esg_reports}, please search out all the values of the ESG indicators in the following list: {esg_indicators}, and give out the value following this template:-ESG indicator: , - year: ,- value:. - company name: \",\n",
    "                max_tokens=1024,\n",
    "                n=1,\n",
    "                stop=None,\n",
    "                temperature=0.5,\n",
    "        )\n",
    "        indicators= response.choices[0].text\n",
    "        return indicators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "xc9cj7SidjTX",
   "metadata": {
    "id": "xc9cj7SidjTX"
   },
   "outputs": [],
   "source": [
    "def process_text(text):\n",
    "    # 将文本分割成多个块\n",
    "    chunks = re.findall(r\"\\A.{1,4000}\\b\", text, re.DOTALL)\n",
    "    \n",
    "    results = []\n",
    "    result2 = \"\"\n",
    "    for chunk in chunks:\n",
    "        prompt = chunk + \"\\n\\nQ:\"\n",
    "        summary=generate_summary(prompt)\n",
    "        entities=generate_text(summary)\n",
    "        company=company_name(entities)\n",
    "        entities = ['SULPHUR_DIOXIDE_SULPHUR_OXIDE_EM', 'TOTAL_WATER_DISCHARGED', 'ENERGY_CONSUMPTION', 'CLIMATE_RISKS', 'WATER_POLICY'] \n",
    "        esg_data = []\n",
    "        for indicator in entities:\n",
    "            response =find_indicators(prompt,indicator)\n",
    "            print(response)\n",
    "            # 提取年份\n",
    "            year = re.search(r\"year:\\s*(\\d{4})\", response).group(1)\n",
    "            # 提取数值\n",
    "            value = re.search(r\"value:\\s*([\\d.]+)\", response).group(1)\n",
    "            # 提取公司名称\n",
    "            company = re.search(r\"company name:\\s*(.+)\", response).group(1)\n",
    "            esg_data.append({\n",
    "                    'ESG indicator': indicator,\n",
    "                    'Year': year,\n",
    "                    'Value': value,\n",
    "                    'Company': company\n",
    "                }) \n",
    "        results += esg_data\n",
    "    # 将提取的数据转换成DataFrame\n",
    "    df = pd.DataFrame(results, columns=['ESG indicator', 'Year', 'Value', 'Company'])\n",
    "    return df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "bd5c6222",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "SULPHUR_DIOXIDE_SULPHUR_OXIDE_EM\n",
      "\n",
      "-ESG indicator: SULPHUR_DIOXIDE_SULPHUR_OXIDE_EM\n",
      "- year: 2021\n",
      "- value: 0.12\n",
      "- company name: PwC\n",
      "\n",
      "\n",
      "A:\n",
      "\n",
      "ESG indicator: TOTAL_WATER_DISCHARGED\n",
      "\n",
      "- year: 2016\n",
      "\n",
      "- value: 1,727,806\n",
      "\n",
      "- company name: PwC\n",
      "\n",
      "\n",
      "ENERGY_CONSUMPTION\n",
      "\n",
      "-ESG indicator: ENERGY_CONSUMPTION\n",
      "- year: 2010\n",
      "- value: 2.4\n",
      "- company name: PwC\n",
      "\n",
      "\n",
      "CLIMATE_RISKS\n",
      "\n",
      "-ESG indicator: CLIMATE_RISKS\n",
      "- year: 2021\n",
      "- value: 0.1\n",
      "- company name: PwC\n",
      "\n",
      "\n",
      "Water_Policy\n",
      "\n",
      "-ESG indicator: Water_Policy\n",
      "- year: 2021\n",
      "- value: 0.7\n",
      "- company name: PwC\n"
     ]
    }
   ],
   "source": [
    "data = process_text(esg_report)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "E0zjX2yqfEek",
   "metadata": {
    "id": "E0zjX2yqfEek"
   },
   "source": [
    "因为chatGPT表现不稳定，需要反复运行。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "2uQi5lTnpM8H",
   "metadata": {
    "id": "2uQi5lTnpM8H"
   },
   "outputs": [],
   "source": [
    "def generate(y): \n",
    "    x = 'ESG发展前景不看好，不可投资'\n",
    "    decision = \"ESG performance is not good, we shouldn't invest in this company\"\n",
    "    if y > 0.75:\n",
    "        x = 'ESG发展前景看好，可投资'\n",
    "        decision = \"ESG performance is good, we should invest in this company\" \n",
    "    return x,decision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "zKjJ3-GJjKDi",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "zKjJ3-GJjKDi",
    "outputId": "5de06a2e-6ac6-4099-e3a7-ac217f54bb19"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "ESG indicator: SULPHUR_DIOXIDE_SULPHUR_OXIDE_EM, \n",
      "- year: 2021, \n",
      "- value: 2, \n",
      "- company name: PwC.\n",
      "\n",
      "\n",
      "Total water discharged\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2009\n",
      "- value: 2,812,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2010\n",
      "- value: 2,650,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2011\n",
      "- value: 2,512,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2012\n",
      "- value: 2,650,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2013\n",
      "- value: 3,040,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2014\n",
      "- value: 3,040,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2015\n",
      "- value: 3,040,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2016\n",
      "- value: 3,040,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2017\n",
      "- value: 3,040,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "-ESG indicator: Total water discharged\n",
      "- year: 2018\n",
      "- value: 3,040,000\n",
      "- company name: Coca-Cola\n",
      "\n",
      "\n",
      "ENERGY_CONSUMPTION\n",
      "\n",
      "-ESG indicator: ENERGY_CONSUMPTION\n",
      "- year: 2021\n",
      "- value: 1.5\n",
      "- company name: PwC\n",
      "\n",
      "\n",
      "CLIMATE_RISKS\n",
      "\n",
      "-ESG indicator: Carbon emissions, - year: 2021, - value: 12%, - company name: PwC.\n",
      "\n",
      "\n",
      "ESG indicator: WATER_POLICY, \n",
      "- year: 2016, \n",
      "- value: 1, \n",
      "- company name: PwC.\n",
      "1/1 [==============================] - 0s 19ms/step\n",
      "ESG发展前景看好，可投资\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'ESG发展前景看好，可投资'"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "esg_reports= convert_pdf_to_txt('test3.pdf')\n",
    "data = process_text(esg_reports)\n",
    "index_name = ['SULPHUR_DIOXIDE_SULPHUR_OXIDE_EM', 'TOTAL_WATER_DISCHARGED', 'ENERGY_CONSUMPTION', 'CLIMATE_RISKS', 'WATER_POLICY'] \n",
    "new_df = data\n",
    "esg_indicators = new_df['ESG indicator'].unique()\n",
    "global_vars = globals()\n",
    "X_test = []\n",
    "for name in index_name:\n",
    "    if name in esg_indicators:\n",
    "        name_df = new_df.loc[new_df['ESG indicator'] == name,:]  \n",
    "        global_vars[name] = float(name_df['Value'].values[0]) \n",
    "    else: \n",
    "        global_vars[name] = 0 \n",
    "    X_test.append(global_vars[name])\n",
    "X_test = np.array(X_test)\n",
    "X_test = X_test[np.newaxis, :]\n",
    "Y_test = keras_model.predict(X_test)\n",
    "decision, decision1 = generate(Y_test)\n",
    "print(decision)\n",
    "decision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "5XlbjHDoqHRU",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 305
    },
    "id": "5XlbjHDoqHRU",
    "outputId": "fb776160-db9b-4210-8776-a3b6df6746dd"
   },
   "outputs": [],
   "source": [
    "import PyPDF2\n",
    "from reportlab.pdfgen import canvas\n",
    "from reportlab.lib.pagesizes import letter\n",
    "from reportlab.lib.units import inch\n",
    "from reportlab.lib import colors\n",
    "from reportlab.platypus import Table, TableStyle\n",
    "\n",
    "# 创建一个PdfFileWriter对象\n",
    "pdf = PyPDF2.PdfFileWriter()\n",
    "\n",
    "    \n",
    "# 添加一个空白页\n",
    "pdf.addBlankPage(width=letter[0], height=letter[1])\n",
    "\n",
    "\n",
    "# 在第二页上添加一些文本和表格\n",
    "canvas_obj = canvas.Canvas(\"temp.pdf\", pagesize=letter)\n",
    "canvas_obj.drawString(2*inch, 10.5*inch, \"Table:\")\n",
    "\n",
    "# 创建表格数据\n",
    "table_data = []\n",
    "for row in range(data.shape[0]):\n",
    "    table_data.append(list(data.iloc[row,:]))\n",
    "    \n",
    "# 创建Table对象并设置样式\n",
    "table = Table(table_data)\n",
    "table.setStyle(TableStyle([\n",
    "    ('BACKGROUND', (0,0), (-1,0), colors.beige),\n",
    "    ('TEXTCOLOR',(0,0),(-1,0),colors.black),\n",
    "    ('FONTNAME', (0,0), (-1,0), 'Helvetica'),\n",
    "    ('FONTSIZE', (0,0), (-1,0), 12),\n",
    "    ('BOTTOMPADDING', (0,0), (-1,0), 6),\n",
    "    ('BACKGROUND', (0,1), (-1,-1), colors.beige),\n",
    "    ('TEXTCOLOR',(0,1),(-1,-1),colors.black),\n",
    "    ('FONTNAME', (0,1), (-1,-1), 'Helvetica'),\n",
    "    ('FONTSIZE', (0,1), (-1,-1), 12),\n",
    "    ('BOTTOMPADDING', (0,1), (-1,-1), 6),\n",
    "    ('GRID', (0,0), (-1,-1), 1, colors.black)\n",
    "]))\n",
    "\n",
    "# 绘制表格并保存\n",
    "table.wrapOn(canvas_obj, 0, 0)\n",
    "table.drawOn(canvas_obj, 2*inch, 9*inch)\n",
    "canvas_obj.save()\n",
    "\n",
    "with open(\"temp.pdf\", \"rb\") as temp_file:\n",
    "    temp_pdf = PyPDF2.PdfFileReader(temp_file)\n",
    "    pdf.getPage(0).mergePage(temp_pdf.getPage(0))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db4b404b",
   "metadata": {},
   "source": [
    "# 生成对应的pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "de4759ed",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "import PyPDF2\n",
    "from reportlab.pdfgen import canvas\n",
    "from reportlab.lib.pagesizes import letter\n",
    "from reportlab.lib.units import inch\n",
    "from reportlab.lib import colors\n",
    "from reportlab.platypus import Table, TableStyle, Image\n",
    "\n",
    "# 创建一个PdfFileWriter对象\n",
    "pdf = PyPDF2.PdfFileWriter()\n",
    "\n",
    "    \n",
    "# 添加一个空白页\n",
    "pdf.addBlankPage(width=letter[0], height=letter[1])\n",
    "\n",
    "\n",
    "# 在第二页上添加一些文本和表格\n",
    "canvas_obj = canvas.Canvas(\"temp.pdf\", pagesize=letter)\n",
    "canvas_obj.drawString(2*inch, 10.5*inch, \"Table:\")\n",
    "\n",
    "# 创建表格数据\n",
    "table_data = []\n",
    "for row in range(data.shape[0]):\n",
    "    table_data.append(list(data.iloc[row,:]))\n",
    "    \n",
    "# 创建Table对象并设置样式\n",
    "table = Table(table_data)\n",
    "table.setStyle(TableStyle([\n",
    "    ('BACKGROUND', (0,0), (-1,0), colors.beige),\n",
    "    ('TEXTCOLOR',(0,0),(-1,0),colors.black),\n",
    "    ('FONTNAME', (0,0), (-1,0), 'Helvetica'),\n",
    "    ('FONTSIZE', (0,0), (-1,0), 12),\n",
    "    ('BOTTOMPADDING', (0,0), (-1,0), 6),\n",
    "    ('BACKGROUND', (0,1), (-1,-1), colors.beige),\n",
    "    ('TEXTCOLOR',(0,1),(-1,-1),colors.black),\n",
    "    ('FONTNAME', (0,1), (-1,-1), 'Helvetica'),\n",
    "    ('FONTSIZE', (0,1), (-1,-1), 12),\n",
    "    ('BOTTOMPADDING', (0,1), (-1,-1), 6),\n",
    "    ('GRID', (0,0), (-1,-1), 1, colors.black)\n",
    "]))\n",
    "\n",
    "# 绘制表格并保存\n",
    "table.wrapOn(canvas_obj, 0, 0)\n",
    "table.drawOn(canvas_obj, 2*inch, 9*inch)\n",
    "\n",
    "# 添加图片和说明文字\n",
    "img = Image(\"my_sem_plot.png\", width=6*inch, height=4*inch)\n",
    "img.drawOn(canvas_obj, 2*inch, 2*inch)\n",
    "canvas_obj.drawString(2*inch, 1.5*inch, \"ESG Structure Plot\")\n",
    "\n",
    "# 添加字符串 decision\n",
    "canvas_obj.drawString(2*inch, 1*inch, decision1)\n",
    "\n",
    "canvas_obj.save()\n",
    "\n",
    "with open(\"final.pdf\", \"rb\") as temp_file:\n",
    "    temp_pdf = PyPDF2.PdfFileReader(temp_file)\n",
    "    pdf.getPage(0).mergePage(temp_pdf.getPage(0))\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c109b5a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
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