getData.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import time\n",
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from io import StringIO \n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import clear_output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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UywlZKw9ne5r7uXMoPpltJxN5pK31rfAihBCi/JHkzwpl5RYwLzKWr7fFkp2n9ut7pI0fL/dqgI+LtF6VRmg9Lw7FJ7P9VJIkf0IIIcoFSf6siKIorI66yEcbjnMpJRuAdrU8eHtAE5pWl3599yKknjdfRMSwIyYJvV5Bq5XH5EIIISybJH9WIio+mXd/P8rBc8kAVHd35LW+jejbTPr13Y9WNdxxtrfhWkYuxy6lShIthLAao0ePJjk5mVWrVgHqnL0tW7Zk9uzZZo1L3J11rMdlxRJSsnlxeRSD5uzk4LlknOxteKVXAza/1Jl+zatK4nef7Gy0BNb1AmCbLPUmhLAAo0ePRqPRoNFosLe3JyAggGnTppGfn1+m5a5YsYL33nuvRMdu3boVjUZDcnJymcYkbk1a/iqo7LwCvtl2mrlbY8nKKwBgSGs/Xu3dQEalGllofS/+/Ocy208mMb5LgLnDEUIIevfuzcKFC8nJyWHdunWEhYVhZ2fH1KlTixyXm5tbZBnU++Hp6WmU84iyJy1/FYyiKKw5dJFun2zl000nycoroG1ND9ZMCGbmoy0k8SsDhUu97T97jYycsv3NWgghSkKn0+Hr60vNmjV59tln6dGjB2vWrGH06NEMGjSI//3vf1SrVo0GDRoAEB8fz6OPPoq7uzuenp4MHDiQM2fOGM5XUFDAiy++iLu7O5UrV+bVV18ttuJWly5dmDhxouFzTk4OkydPxt/fH51OR0BAAPPnz+fMmTN07doVAA8PDzQaTamWdBX3T1r+KpBD8clMCz/GgbPXAbVf35Q+Dekvj3fLVK3KTvh7OhJ/LYu9cVfp1rCKuUMSQhibokBepnnKtnOC+/w/3NHRkatXrwKwefNmXF1d2bRpEwB5eXn06tWLwMBAtm/fjq2tLe+//z69e/fm8OHD2NvbM3PmTBYtWsSCBQto1KgRM2fOZOXKlXTr1u22ZY4cOZLdu3fz+eef06JFC+Li4khKSsLf35/ffvuNIUOGcOLECVxdXXF0dLyv+onSkeSvAricms2MDSf47e/zADja2fBsl7qMC60j8/WZQOFSb0v2nmPbySRJ/oSoiPIy4YNq5in7tYtg73xPX1UUhc2bN7Nx40aee+45EhMTcXZ25rvvvjM87v3xxx/R6/V89913hoaChQsX4u7uztatW+nZsyezZ89m6tSpDB48GIB58+axcePG25Z78uRJfv75ZzZt2kSPHj0AqFOnjmF/4SNiHx8f3N3d76lu4t5J8leOZecV8N3203y1NZbMXLVf3+BW1Xm1d0N83eTxrimF1vNiyd5zbJdBH0IICxAeHk6lSpXIy8tDr9czfPhw3nnnHcLCwmjWrFmRfn6HDh0iJiYGFxeXIufIzs4mNjaWlJQULl26RIcOHQz7bG1tadu2bbFHv4WioqKwsbGhc+fOZVNBcV8k+SuHFEVh7ZFLTF93nAvJWQC0ruHOWwOa0NLf3bzBWanAul5oNRCbmMGF5Cyqu8sjDCEqFDsntQXOXGWXUteuXZk7dy729vZUq1YNW9ubt3tn56KtiOnp6bRp04affvqp2Hm8vb1LHy/IY1wLJ8lfORN9IYVpvx9j35lrAFR1c2BKn4Y82KKa9OszIzdHO1r6u/P3uWR2nErksXY1zB2SEMKYNJp7fvRqDs7OzgQElGz2gdatW7N8+XJ8fHxwdXW95TFVq1Zl7969hIaGApCfn8+BAwdo3br1LY9v1qwZer2eyMhIw2PffytseSwoKChRjMK4ZLRvOXElLZtXfjnEgC93sO/MNRzstEzsUY+Il7owsGV1SfwsQOGo320nk8wciRBClNzjjz+Ol5cXAwcOZPv27cTFxbF161aef/55zp9X+5K/8MILfPjhh6xatYrjx48zfvz4O87RV6tWLUaNGsWYMWNYtWqV4Zw///wzADVr1kSj0RAeHk5iYiLp6emmqKq4QZI/C5edV8CcLTF0/Xgrvxw4j6LAwJbViHipCxN71MfRXgZ0WIrQ+mrytyMmiQL9rfvBCCGEpXFycmLbtm3UqFGDwYMH06hRI5566imys7MNLYEvvfQSI0aMYNSoUQQGBuLi4sJDDz10x/POnTuXhx9+mPHjx9OwYUOefvppMjIyAKhevTrvvvsuU6ZMoUqVKkyYMKHM6ylu0ii3660pSiU1NRU3NzdSUlJu22x+Lz794wSfR8QA0MLfnbf6N6ZNTQ+jnV8YT36BnlbvbSItO59VYcHS/1KIciw7O5u4uDhq166Ng4MMoCvv7vTzLKv7tyWTlj8L92RwbRpUceHTR1uw8tkgSfwsmK2NluAbS71tPymjfoUQQlgmSf4snIezPRsmhjC4tR9arfTrs3Qh9W8kf6ek358QQgjLJMlfOSCDOcqP0BuDPv4+d5207DwzRyOEEEIUJ8mfEEbk7+lErcpO5OsV9py+Zu5whBBCiGIk+RPCyApH/W6Tfn9ClHsyJrJikJ9jUZL8CWFkhfP9yVJvQpRfdnZ2AGRmZpo5EmEMhT/Hwp+rtZMVPoQwso51PLHVajhzNZNzVzOpUbn0SzMJIczLxsYGd3d3rly5Aqhz4Un/6/JHURQyMzO5cuUK7u7u2NjI3LggyZ8QRufiYEfrGh7sO3ON7TGJPF65prlDEkLcA19fXwBDAijKL3d3d8PPU0jyJ0SZCKnnpSZ/J5N4vIMkf0KURxqNhqpVq+Lj40NenozeL6/s7Oykxe8/JPkTogyE1Pdm5qaT7IxNIr9Aj62NdK8VoryysbGR5EFUKHJHEqIMNKvuhruTHWnZ+Rw6n2zucIQQQggDSf6EKAM2Wg3BAepqH9tOymofQgghLIckf0KUkdB6hUu9yZQvQgghLIckf0KUkU435vuLik8mJUs6iwshhLAMkvwJUUaquztS19sZvQK7Y+XRrxBCCMsgyZ8QZahwtY9tpyT5E0IIYRkk+ROiDHX+1zq/srakEEIISyDJnxBlqEMdT+xsNJy/nsWZq7JGqBBCCPMza/I3ffp02rVrh4uLCz4+PgwaNIgTJ07c8lhFUejTpw8ajYZVq1YV2ff888/Tpk0bdDodLVu2LPbdM2fOoNFoir327NlT5LhffvmFhg0b4uDgQLNmzVi3bp2xqiqslJO9LW1regIy6lcIIYRlMGvyFxkZSVhYGHv27GHTpk3k5eXRs2dPMjIyih07e/bsOy6qPWbMGB577LE7lvfnn39y6dIlw6tNmzaGfbt27WLYsGE89dRTHDx4kEGDBjFo0CCio6PvvYJCACH1Zb4/IYQQlsOsy7tt2LChyOdFixbh4+PDgQMHCA0NNWyPiopi5syZ7N+/n6pVqxY7z+effw5AYmIihw8fvm15lStXvu3Czp999hm9e/fmlVdeAeC9995j06ZNfPnll8ybN6/UdROiUGg9b2ZsOMHu2CTyCvTYyVJvQgghzMii7kIpKSkAeHp6GrZlZmYyfPhw5syZc9vEraQefPBBfHx86NSpE2vWrCmyb/fu3fTo0aPItl69erF79+5bnisnJ4fU1NQiLyFupXFVVyo725ORW8DBc8nmDkcIIYSVs5jkT6/XM3HiRIKDg2natKlh+6RJkwgKCmLgwIH3fO5KlSoxc+ZMfvnlF9auXUunTp0YNGhQkQQwISGBKlWqFPlelSpVSEhIuOU5p0+fjpubm+Hl7+9/z/GJik2r1dCpXuGjX+n3J4QQwrzM+tj338LCwoiOjmbHjh2GbWvWrCEiIoKDBw/e17m9vLx48cUXDZ/btWvHxYsX+fjjj3nwwQfv6ZxTp04tcs7U1FRJAMVthdTzZnXURbafSuTlXg3MHY4QQggrZhEtfxMmTCA8PJwtW7bg5+dn2B4REUFsbCzu7u7Y2tpia6vmqkOGDKFLly73VWaHDh2IiYkxfPb19eXy5ctFjrl8+fJtHzXrdDpcXV2LvIS4nZAbLX+HL6RwPSPXzNEIIYSwZmZN/hRFYcKECaxcuZKIiAhq165dZP+UKVM4fPgwUVFRhhfArFmzWLhw4X2VHRUVVWTwSGBgIJs3by5yzKZNmwgMDLyvcoQAqOLqQIMqLigK7JSl3oQQQpiRWR/7hoWFsWTJElavXo2Li4uhf52bmxuOjo74+vresuWtRo0aRRLFmJgY0tPTSUhIICsry5AkNm7cGHt7exYvXoy9vT2tWrUCYMWKFSxYsIDvvvvOcI4XXniBzp07M3PmTPr168eyZcvYv38/33zzTRn+DQhrElLPixOX09h+Mon+zauZOxwhhBBWyqzJ39y5cwGKPcJduHAho0ePLvF5xo4dS2RkpOFzYZIXFxdHrVq1AHXqlrNnz2Jra0vDhg1Zvnw5Dz/8sOE7QUFBLFmyhDfeeIPXXnuNevXqsWrVqiKDT4S4HyH1vfluRxzbT6lLvd1p3kohhBCirGgUWXDUKFJTU3FzcyMlJUX6/4lbys4roPm7f5Cbr+fPF0MJ8HExd0hCCGH1rPH+bREDPoSwBg52NnSorc5hKat9CCGEMBdJ/oQwocJRv7LOrxBCCHOR5E8IEwqp5w3AntPXyMkvMHM0QgghrJEkf0KYUENfF7wq6cjKK+DA2evmDkcIIYQVkuRPCBPSaDSEGh79Sr8/IYQQpifJnxAmFlJf+v0JIYQwH0n+hDCxTgFqv7/oC6kkpeeYORohhBDWRpI/IUzM20VH46rqXFI7Y+TRrxBCCNOS5E8IMyh89Cvz/QkhhDA1Sf6EMIPQG1O+FC71JoQQQpiKJH9CmEGbmh442Gm5kpbDycvp5g5HCCGEFZHkTwgzUJd6qwzIqF8hhBCmJcmfEGYSWl999Bt5UpI/IYQQpiPJnxBmUjjZ8764a2TnyVJvQgghTEOSPyHMJMCnEr6uDuTk6/nrzDVzhyOEEMJKSPInhJloNBpCZKk3IYQQJibJnxBmFHKj39826fcnhBDCRCT5E8KMOgV4odHA8YQ0rqRmmzscIYQQVkCSPyHMyNPZnmbV3QB59CuEEMI0JPkTwsxu9vuTR79CCCHKniR/QphZyI2l3nbEJKHXy1JvQgghypYkf0KYWesaHjjZ25CUnss/CanmDkcIIUQFJ8mfEGZmb6slsE7hUm/S708IIUTZkuRPCAsg/f6EEEKYiiR/QliAwnV+/4q7TmZuvpmjEUIIUZFJ8ieEBajt5Ux1d0dyC/TsjZOl3oQQQpQdSf6EsAAajYbQ+jce/Z6Ufn9CCCHKjiR/QliIwilfpN+fEEKIsiTJnxAWIqhuZbQaOHUlnUspWeYORwghRAUlyZ8QFsLdyZ7mfu6ATPkihBCi7EjyJ4QFKRz1u+2kPPoVQghRNiT5E8KChN6Y729HTBIFstSbEEKIMiDJnxAWpIW/Oy46W5Iz8zh6McXc4QghhKiAJPkTwoLY2WgJrCtLvQkhhCg7kvwJYWFCpN+fEEKIMiTJnxAWprDf39/nrpOeI0u9CSGEMC5J/oSwMDUrO1OzshN5BQp7T181dzhCCCEqGLMmf9OnT6ddu3a4uLjg4+PDoEGDOHHixC2PVRSFPn36oNFoWLVqVZF9zz//PG3atEGn09GyZcti3926dSsDBw6katWqODs707JlS3766acixyxatAiNRlPk5eDgYKyqClEqITda/+TRrxBCCGMza/IXGRlJWFgYe/bsYdOmTeTl5dGzZ08yMjKKHTt79mw0Gs1tzzVmzBgee+yxW+7btWsXzZs357fffuPw4cM8+eSTjBw5kvDw8CLHubq6cunSJcPr7Nmz91dBIe7RzaXeZNCHEEII47I1Z+EbNmwo8nnRokX4+Phw4MABQkNDDdujoqKYOXMm+/fvp2rVqsXO8/nnnwOQmJjI4cOHi+1/7bXXinx+4YUX+OOPP1ixYgX9+/c3bNdoNPj6+pYo9pycHHJycgyfU1NTS/Q9IUoisG5lbLQaTidlEH8tE39PJ3OHJIQQooKwqD5/KSnqvGaenp6GbZmZmQwfPpw5c+aUODEraVn/LgcgPT2dmjVr4u/vz8CBAzl69Ohtvz99+nTc3NwML39/f6PFJoSrgx2t/N0BdcJnIYQQwlgsJvnT6/VMnDiR4OBgmjZtatg+adIkgoKCGDhwoNHK+vnnn/nrr7948sknDdsaNGjAggULWL16NT/++CN6vZ6goCDOnz9/y3NMnTqVlJQUwys+Pt5o8QkB/370K/3+hBBCGI9ZH/v+W1hYGNHR0ezYscOwbc2aNURERHDw4EGjlbNlyxaefPJJvv32W5o0aWLYHhgYSGBgoOFzUFAQjRo14uuvv+a9994rdh6dTodOpzNaXEL8V2h9L2b9eZIdp9Sl3my0t+/zKoQQQpSURbT8TZgwgfDwcLZs2YKfn59he0REBLGxsbi7u2Nra4utrZqrDhkyhC5dupS6nMjISAYMGMCsWbMYOXLkHY+1s7OjVatWxMTElLocIYyhuZ87rg62pGbnc+h8srnDEUIIUUGYNflTFIUJEyawcuVKIiIiqF27dpH9U6ZM4fDhw0RFRRleALNmzWLhwoWlKmvr1q3069ePjz76iHHjxt31+IKCAo4cOXLLASZCmIKNVkOnG1O+bD8p/f6EEEIYh1kf+4aFhbFkyRJWr16Ni4sLCQkJALi5ueHo6Iivr+8tB3nUqFGjSKIYExNDeno6CQkJZGVlGZLExo0bY29vz5YtW+jfvz8vvPACQ4YMMZRjb29vGPQxbdo0OnbsSEBAAMnJyXz88cecPXuWsWPHlvHfghC3F1LPm3VHEth+KpEXetQzdzhCCCEqALMmf3PnzgUo9gh34cKFjB49usTnGTt2LJGRkYbPrVq1AiAuLo5atWqxePFiMjMzmT59OtOnTzcc17lzZ7Zu3QrA9evXefrpp0lISMDDw4M2bdqwa9cuGjdufG+VE8IIOgWoLX8H45NJzc7D1cHOzBEJIYQo7zSKoijmDqIiSE1Nxc3NjZSUFFxdXc0djqhAun2yldNJGXw9og29mhhvuiMhhBDWef+2iAEfQojbK1zqTaZ8EUIIYQyS/Alh4ULrq/P9bZNBH0IIIYxAkj8hLFzHOpWxs9Fw7lomZ68WX/daCCGEKA2LmeRZVAB6PeRnQV72rf8syIWqLcHZy9yRlivOOlta1/Bgb9w1tp1KYkRlZ3OHJIQQohyT5K+iUhQ12crLgvzsUvz5n4QtP6fk3ynIvXtc9i7Q421o+xRopeG5pELre7M37hrbTyYyomNNc4cjhBCiHJPkz9JdOgRHfi1BopZd/BjMOJBbawd2jmDrAHYOYOuoxpp8Dta9DIeXw4DPoEqTu59LEFLPi483nmB37FXyCvTY2UjiLIQQ4t5I8mfpkk7Brs/v8ySafyVit/vzRoJWqj8dbn9OrU3xMPQF8Nd82DwNzv8FX4dC0HPQebL6HXFbTaq54eFkx/XMPA7FJ9O2lqe5QxJCCFFOSfJn6bwbQOCE+0jQHMHGDjQac9dETQg7jIOG/WD9q3A8HHbMgqMrof8sqNvN3BFaLHWpN29+P3SRbScTJfkTQghxz2SSZyOxxkki79vxtbD2ZUi7qH5u/hj0+kAGhNzGz/vjefXXw7T0d2dVWLC5wxFCiArBGu/f0nFImE/DfjBhH3R4BtCo/QC/bAsHf1QHrIgiCid7Pnw+meTMEgyuEUIIIW5Bkj9hXjoX6PMRjN0MVZpB1nVYHQaLB6j9HYVBVTdH6vlUQq/Artir5g5HCCFEOSXJn7AMfm1g3BZ4YJraT/HMdpgbBFs/UqebEQCE1FNX+5Cl3oQQQtwrSf6E5bCxg+AXIGwPBPRQ5w3c+gHMC4Gzu8wdnUUIqa8++t12MgnpriuEEOJeSPInLI9HLXj8VxgyH5y9IekELOwDa55XHwtbsY61K2Nvo+VCchank2SpNyGEEKUnyZ+wTBoNNHsYwvZB65Hqtr8Xw5ft1UmvrbTVy9Hehna1PQDYflIe/QohhCg9Sf6EZXPyhAe/gCfXg1d9yLgCvz0FPz0M18+YOzqzuNnvL8nMkQghhCiPJPkT5UPNIHhmB3R5DWzsIeZPmNMRdn4GBfnmjs6kCqd82X36Krn5ejNHI4QQoryR5E+UH7Y66DIZnt0FNTupawVvegu+6QIXDpg7OpNp5OuKVyV7MnML+PucdfeBFEIIUXqS/Inyx6sejA6HgXPAwR0uH4Fvu8P6yZCTZu7oypxWq6FTgNr6J1O+CCGEKC1J/kT5pNFAqydgwn5o9iigwN55MKeDumxcBRdaX/r9CSGEuDeS/InyrZI3DPkWnlihThGTegGWDYdlj0PqRXNHV2YKW/6OXEjhWoYs9SaEEKLkJPkTFUNAd3h2N3SaBFpbOB6uTguz71vQF5g7OqPzcXWgoa8LigI7YqT1TwghRMlJ8icqDnsn6PEOjIuE6m0hNw3WvQzze0JCtLmjMzrDo1+Z708IIUQpSPInKh7fpvDUH9D3E7B3gQv74ZvOsOltyM00d3RGUzjly/ZTstSbEEKIkpPkT1RMWhto/zRM2AeNBoA+H3bOhq86Qsxmc0dnFO1qeaKz1ZKQmk3MlXRzhyOEEKKckORPVGyu1eCxH2HoUnCtDsln4cfB8NtYSC/fj0sd7GzoUKcyANtk1K8QQogSkuRPWIeGfSFsL3R4FtDAkV/gy7bw9w/lep3g0BuPfrdJvz8hhBAlJMmfsB46F+jzITy9GXybQXYyrJkAi/pD0ilzR3dPCtf53Rt3ley8ijeqWQghhPFJ8iesT/U28PRWeOA9sHOCsztgbhBs/RDyc8wdXanUr1IJHxcd2Xl6DpyVpd6EEELcnSR/wjrZ2ELw8zB+DwQ8AAW5sHU6zOsEZ3aaO7oS02g0hta/bbLUmxBCiBKQ5E9YN4+a8Pgv8PACcPaBpJOwqC+sngCZ18wdXYmE1r8x5ctJGfQhhBDi7u4p+YuNjeWNN95g2LBhXLlyBYD169dz9OhRowYnhEloNNB0iDotTJvR6raDP8Cc9nD4F4sfEFK41NuxS6kkppWvx9ZCCCFMr9TJX2RkJM2aNWPv3r2sWLGC9HR1frFDhw7x9ttvGz1AIUzG0QMGfAZPbgCvBpCRCCvGwo9D4PoZc0d3W5Ur6Wha3RWAHTHy6FcIIcSdlTr5mzJlCu+//z6bNm3C3t7esL1bt27s2bPHqMEJYRY1A+GZ7dD1dbCxh9jNMKcj7JgNBXnmju6WCvv9yaNfIYQQd1Pq5O/IkSM89NBDxbb7+PiQlCQ3HlFB2Oqg86vw7G6oFQL5WfDn2/BNFzh/wNzRFVO41Ns2WepNCCHEXZQ6+XN3d+fSpUvFth88eJDq1asbJSghLIZXAIz6HQZ+pT4WvhwN33VXp4WxIG1qeuBoZ0NSeg7HE9LMHY4QQggLVurkb+jQoUyePJmEhAQ0Gg16vZ6dO3fy8ssvM3LkyFKda/r06bRr1w4XFxd8fHwYNGgQJ06cuOWxiqLQp08fNBoNq1atKrLv+eefp02bNuh0Olq2bHnL7x8+fJiQkBAcHBzw9/dnxowZxY755ZdfaNiwIQ4ODjRr1ox169aVqj6igtJooNXjMGE/NB8KKOq0MJctZ4CTztaGjnU8AdguU74IIYS4g1Infx988AENGzbE39+f9PR0GjduTGhoKEFBQbzxxhulOldkZCRhYWHs2bOHTZs2kZeXR8+ePcnIyCh27OzZs9FoNLc915gxY3jsscduuS81NZWePXtSs2ZNDhw4wMcff8w777zDN998Yzhm165dDBs2jKeeeoqDBw8yaNAgBg0aRHR0dKnqJCowZy8Y/DU0Hqh+3vaJeeP5j9D6N/r9yTq/Qggh7kCj3GMHofj4eI4cOUJ6ejqtWrWiXr169x1MYmIiPj4+REZGEhoaatgeFRVF//792b9/P1WrVmXlypUMGjSo2PffeecdVq1aRVRUVJHtc+fO5fXXXychIcEwSGXKlCmsWrWK48ePA/DYY4+RkZFBeHi44XsdO3akZcuWzJs3r1hZOTk55OTcnFYjNTUVf39/UlJScHV1vZ+/BmHpEo6ok0GjUdcL9m5g7ogAiLmSTo9PI7G31XLorZ442tuYOyQhhLB4qampuLm5WdX9+54nefb396dv3748+uijRkn8AFJSUgDw9PQ0bMvMzGT48OHMmTMHX1/fezrv7t27CQ0NLTI6uVevXpw4cYLr168bjunRo0eR7/Xq1Yvdu3ff8pzTp0/Hzc3N8PL397+n2EQ55NsMGvYHFItq/avr7Uw1Nwdy8/XsO1M+JqgWQghheqVO/oYMGcJHH31UbPuMGTN45JFH7jkQvV7PxIkTCQ4OpmnTpobtkyZNIigoiIEDB97zuRMSEqhSpUqRbYWfExIS7nhM4f7/mjp1KikpKYZXfHz8PccnyqHQV9Q/o3+Fq7HmjeWGfy/1tv2k9PsTQghxa6VO/rZt20bfvn2Lbe/Tpw/btm2750DCwsKIjo5m2bJlhm1r1qwhIiKC2bNn3/N5y4pOp8PV1bXIS1iRai2hXi9Q9LB9prmjMQgpXOpN+v0JIYS4jVInf+np6UUenxays7MjNTX1noKYMGEC4eHhbNmyBT8/P8P2iIgIYmNjcXd3x9bWFltbW0BtfezSpUuJz+/r68vly5eLbCv8XPgo+XbH3OujZmEFOr+q/nloGVyLM28sNwTX9UKjgROX07icmm3ucIQQQligUid/zZo1Y/ny5cW2L1u2jMaNG5fqXIqiMGHCBFauXElERAS1a9cusn/KlCkcPnyYqKgowwtg1qxZLFy4sMTlBAYGsm3bNvLybq7OsGnTJho0aICHh4fhmM2bNxf53qZNmwgMDCxVnYQV8WsLdbuDUgA7PjV3NAB4ONvTvLobIK1/Qgghbs22tF948803GTx4MLGxsXTr1g2AzZs3s3TpUn755ZdSnSssLIwlS5awevVqXFxcDP3r3NzccHR0xNfX95YtbzVq1CiSKMbExJCenk5CQgJZWVmGJLFx48bY29szfPhw3n33XZ566ikmT55MdHQ0n332GbNmzTKc44UXXqBz587MnDmTfv36sWzZMvbv319kOhghiuk8WV3+LWqJ2g/QvYa5IyK0vjeHzqew7WQiD7fxu/sXhBBCWBflHoSHhytBQUGKk5OTUrlyZaVr167K1q1bS30e4JavhQsX3vE7K1euLLKtc+fOtzxPXFyc4ZhDhw4pnTp1UnQ6nVK9enXlww8/LHbun3/+Walfv75ib2+vNGnSRFm7dm2J65KSkqIASkpKSom/IyqIRf0V5W1XRfl9krkjURRFUfaevqrUnByutJr2h1JQoDd3OEIIYdGs8f59z/P8iaKscZ4gccOZHbCoH9jYw/NR4GbeZQ7zCvS0fPcPMnILCH+uE01vPAYWQghRnDXev+95nj8hxA21OkHNYCjIhZ2fmTsa7Gy0BNZVR/1uk6XehBBC/EeJkj9PT0+SktTO4x4eHnh6et72JYRVKhz5e2ARpN16bkhTCi2c8uWkDPoQQghRVIkGfMyaNQsXFxcAi5xzTwizq90Z/NrD+X2w6wvo9T+zhlM42fP+s9fIzM3Hyb7UY7uEEEJUUCW6I4waNQqA/Px8NBoNvXr1KrYahhBWTaNRR/7+NAT+mg/BE6GSt9nCqVXZCX9PR+KvZbHn9FW6NZR/r0IIIVSl6vNna2vLM888Q3a2TB4rRDEB3aFaa8jPgt1fmDWUfy/1tk0e/QohhPiXUg/4aN++PQcPHiyLWIQo3wpb/wD2fQcZV80aTmi9wqXeZNCHEEKIm0rdEWj8+PG89NJLnD9/njZt2uDs7Fxkf/PmzY0WnBDlTv1e4NscEg7DnjnQ/S2zhRJY1wutBmITM7iQnEV1d0ezxSKEEMJylHqeP622eGOhRqNBURQ0Gg0FBQVGC648scZ5gsRt/PM7LH8C7F1g0hFw9DBbKIO/2snf55L5aEgzHmtn/tVHhBDC0ljj/bvULX9xcZaxgL0QFqtBP/BpAleOwp550HWq2UIJqefN3+eS2XYqSZI/IYQQQCn7/KWmpnLy5Emio6NxcnKiZs2axV5CWD2tFjq/or7fMxeyU8wWSmh9ddDHzpgkCvSymI8QQohSJH9RUVE0bNiQ3r17M2DAAAICAti4cWNZxiZE+dVoIHg3hJwU2PuN2cJo4eeGi4MtyZl5HLlgviRUCCGE5Shx8jd58mRq167Njh07OHDgAN27d2fChAllGZsQ5ZdWCyEvq+/3zIGcNLOEYWujJbhu4WofMupXCCFEKZK/AwcO8MUXXxAYGEirVq1YsGABsbGxpKamlmV8QpRfTQdD5QDIug5/fWe2MEIKl3o7JfP9CSGEKEXyd+3aNfz8/Ayf3d3dcXZ25upV885lJoTF0trcbP3b9QXkZpgljNAbkz3/fe46adl5ZolBCCGE5SjVaN9jx46RkHBz0XpFUfjnn39IS7v5SEvm+RPiX5o9ApEfwvUzsH8BBD1n8hD8PZ2oVdmJM1cz2XP6Gg80lqXehBDCmpUq+evevTv/nRawf//+Ms+fELdjYwshL8Ga52Dn59BuLNiZfrLl0PrenNl9lu2nEiX5E0IIK1fi5E/m9xPiHjUfCpEfQ8o5OLAYOj5j8hBC6nnz/e6zbJNBH0IIYfVKnPzJHH5C3CNbewiZBOGTYOdsaDMa7BxMGkLHOp7YajWcuZrJuauZ1KjsZNLyhRBCWI5STfIshLhHLR8H1+qQdgkO/mDy4l0c7GhdQ11mbnuMtP4JIYQ1k+RPCFOw1UHwRPX9jtmQn2vyEELqFc73J1O+CCGENZPkTwhTaT0SKvlC6nk4tMTkxYcULvUWm0R+gd7k5QshhLAMkvwJYSp2DhD8gvp++0woMO2ce82qu+HuZEdadj6HzstSb0IIYa1KnPxlZWWxZs2aInP6FUpNTWXNmjXk5OQYNTghKpw2o8HZG5LPweHlJi3aRqshOEB99CujfoUQwnqVOPn75ptv+Oyzz3BxcSm2z9XVlc8//5zvvjPfElZClAv2Tjcnet4+EwryTVp8aGG/v1OS/AkhhLUqcfL3008/MXHixNvunzhxIosXLzZGTEJUbG2fAkdPuHYaon8zadGdbiz1FhWfTEqWLPUmhBDWqMTJ36lTp2jRosVt9zdv3pxTp04ZJSghKjRdJQiaoL7f9jHoTbcqTnV3R+p6O6NXYHesjPoVQghrVOLkLz8/n8TE2z8qSkxMJD/ftI+whCi32j0NDu5w9RQcXWnSokNutP5tOyXJnxBCWKMSJ39NmjThzz//vO3+P/74gyZNmhglKCEqPAdXCAxT32/7BPSmm3ql840pX7adTCy2VrcQQoiKr8TJ35gxY3jvvfcIDw8vtu/333/nf//7H2PGjDFqcEJUaO3Hgc4VEv+B47+brNgOdTyxs9Fw/noWZ65mmqxcIYQQlqHEyd+4ceMYNGgQDz74II0bN+ahhx7ioYceolGjRgwaNIgBAwYwbty4soxViIrF0R06PKO+j5xhstY/J3tb2tb0BGTUrxC3lZ2qdsnISTd3JEIYXYmTv3PnzvH999+zbNky6tevz8mTJzlx4gQNGjRg6dKlLF26tCzjFKJi6vgs2FeCy9Fwcr3Jig2pXzjfn/T7E6IYRYHlj8Mvo2FeJ4jfZ+6IhDAqjVLCTj82NjZcunQJHx+fso6pXEpNTcXNzY2UlBRcXV3NHY4oT/58F3Z8ClVbwLhI0GjKvMjoCyn0/2IHzvY27HmtOy4OdmVephDlRvRv8Ou/ujFptNBpEnSeArb25otLlAlrvH+XuOVPOoYLUUYCw8DOCS4dglObTFJk46qu1PF2JiO3gC8jYkxSphDlQk46bHxDfR/0HDQfCopenZT9u+5w5R/zxieEEZRqbV+NCVokhLA6zl7Q7in1feRH6iOnMqbVanizX2MAFuyMIy4po8zLFKJc2PYxpF0Ej1rQ9Q0Y/DU8+r06MXvCYfi6M+z6wqQj9IUwthI/9tVqtYwbNw4nJ6c7Hvfpp58aJbDyxhqbjYURpV+B2c0gPxueWAEB3U1S7KgF+4g8mUiPRj58N6qdScoUwmIlnYKvAkGfB8OWQYM+N/elJcCa5+DUH+rnmp1g0FfgUdM8sQqjscb7t21pDj5y5Aj29rfv7yAtg0Lco0o+0HYM7PlKHflbt5tJ+v692b8RO2cn8ec/V9h2MpHQG3MACmF1FAXWvaImfvV6FU38AFx8YfjP8Pdi2PAanN0Bc4Ohz4fQ8nGT/HsVwlhK9dh35cqVbNmy5baviIiIUhU+ffp02rVrh4uLCz4+PgwaNIgTJ07c8lhFUejTpw8ajYZVq1YV2Xfu3Dn69euHk5MTPj4+vPLKK0VWGxk9ejQajabY69+TUr/zzjvF9jds2LBU9RHivgQ9DzY6iN8DZ7abpMgAHxdGBtYC4L3wY+QVyKMsYaX++R1ObwEbezWhuxWNBtqMhmd3gH9HyE2D1WGw7HFIl2mTRPlR4uSvLFr1IiMjCQsLY8+ePWzatIm8vDx69uxJRkbx/kezZ8++ZQwFBQX069eP3Nxcdu3axeLFi1m0aBFvvfWW4ZjPPvuMS5cuGV7x8fF4enryyCOPFDlXkyZNihy3Y8cOo9dZiNtyrQqtR6rvI2eYrNgXutfD09meU1fS+WnPWZOVK4TFyM2Eja+p74NfAM86dz7esw48uQ56vANaOzixFr7qCMfXlnmoQhiDWUf7btiwgdGjR9OkSRNatGjBokWLOHfuHAcOHChyXFRUFDNnzmTBggXFzvHHH39w7NgxfvzxR1q2bEmfPn147733mDNnDrm5uQC4ubnh6+treO3fv5/r16/z5JNPFjmXra1tkeO8vLyMXmch7qjTRPVmcmY7nNlpkiLdnOx48YH6AMz68xTXM3JNUq4QFmPHp5ASD27+0OnFkn1Ha6NO/zJuC/g0gcwkWDZcbQnMTi3beIW4TyVO/hYuXIibm1tZxkJKSgoAnp6ehm2ZmZkMHz6cOXPm4OvrW+w7u3fvplmzZlSpUsWwrVevXqSmpnL06NFbljN//nx69OhBzZpFO+qeOnWKatWqUadOHR5//HHOnTt321hzcnJITU0t8hLivrn5Qasn1PfbTNf6N6x9DRr6upCSlcesP0+arFwhzO5qLOz8TH3f6wOwv/OgxmJ8m6kJYNDzgAYO/gjzgk32y5sQ96LEyd+oUaPQ6XRcvXrVsC0+Pp633nqLV155he3b76+Pkl6vZ+LEiQQHB9O0aVPD9kmTJhEUFMTAgQNv+b2EhIQiiR9g+JyQkFDs+IsXL7J+/XrGjh1bZHuHDh1YtGgRGzZsYO7cucTFxRESEkJaWtoty50+fTpubm6Gl7+/f6nqK8RtdZoEWls4vdVkKwvYaDW8NUCd+uXHPWc5kXDr616ICmfDVCjIVQdZNRpwb+ew1UHP99RHwe41IPkcLOoHG1+HvGzjxiuEEZQ4+Tty5Ai1atXCx8eHhg0bEhUVRbt27Zg1axbffPMNXbt2LTYQozTCwsKIjo5m2bJlhm1r1qwhIiKC2bNn3/N5/2vx4sW4u7szaNCgItv79OnDI488QvPmzenVqxfr1q0jOTmZn3/++ZbnmTp1KikpKYZXfHy80WIUVs6jJrQYqr43Yd+/oLpe9G7ii16BaeFHZWJ3UfGdWA+nNqpdLfrMuP8RuzWD4Nld0GoEoMDuL+HbrnDpsFHCFcJYSpz8vfrqqzRr1oxt27bRpUsX+vfvT79+/UhJSeH69ev83//9Hx9+eJsRUncxYcIEwsPD2bJlC35+fobtERERxMbG4u7ujq2tLba26sw0Q4YMoUuXLgD4+vpy+fLlIucr/Pzfx8SKorBgwQJGjBhxxylrANzd3alfvz4xMbde/UCn0+Hq6lrkJYTRhLwEGhuI2QQXDtz9eCN5rW8j7G217Iy5yqZjl+/+BSHKq7wsWD9ZfR8YBl71jHNenQsM/FKdJ9DZG64cg2+7wbZPoCD/7t8XwgRKnPz99ddf/O9//yM4OJhPPvmEixcvMn78eLRaLVqtlueee47jx4+XqnBFUZgwYQIrV64kIiKC2rVrF9k/ZcoUDh8+TFRUlOEFMGvWLBYuXAhAYGAgR44c4cqVK4bvbdq0CVdXVxo3blzkfJGRkcTExPDUU0/dNbb09HRiY2OpWrVqqeokhFF41oHmj6rvIz82WbE1KjvxdIj67/B/6/4hJ7/AZGULYVI7P4fks+BaHUJfMf75G/SB8XugYX917sCI92BhH7WPoRBmVuLk79q1a4aWtEqVKuHs7IyHh4dhv4eHx237x91OWFgYP/74I0uWLMHFxYWEhAQSEhLIysoC1Ja7pk2bFnkB1KhRw5Ao9uzZk8aNGzNixAgOHTrExo0beeONNwgLC0On0xUpb/78+XTo0KFIn8JCL7/8MpGRkZw5c4Zdu3bx0EMPYWNjw7Bhw0pVJyGMJuQldUH5k+vVdX9NZHyXAHxcdJy9msnCnWdMVq4QJnP9jDrCF6Dn+6CrVDblOHvBYz/CoLlg7wLn98G8TrB/gUmWcRTidu5rbd/7nftv7ty5pKSk0KVLF6pWrWp4LV++vMTnsLGxITw8HBsbGwIDA3niiScYOXIk06ZNK3JcSkoKv/32221b/c6fP8+wYcNo0KABjz76KJUrV2bPnj14e8uKB8JMvOpBk8Hq+22ma/1z1tkyubc6wfkXm09xJU06rIsKZsNr6lKKtUOhyUNlW5ZGAy2Hw/hdUCsE8jIhfBL89Ii6ZJwQZlCqtX379OljaE37/fff6datG87OzoA69cmGDRsoKLDOx0TWuDagMIEr/6hrjaKoHcmrNLnrV4xBr1d4aO4uDsUn80gbPz5+pIVJyhWizJ3aBD89rI6of2Yn+JhwJSe9HvbOhT/fhYIccPSA/rPKPgEVd2SN9+9STfXi4+NjmNrkiSeeoFq1aobPPj4+jBw5sixjFcL6+DSCxjemOTJh659Wq+HtG1O//Pr3eQ6fTzZZ2UKUmfwcWP+q+r7DM6ZN/AC0WnVwyf9Fgm9zyLoOv4yG355W3wthIiVu+RN3Zo2/OQgTSYhWJ41FA2F7wbuByYqetDyKlQcv0KamB78+E1gmyzwKYTLbZ8LmaVCpCkzYDw5m/L86P1edyH37TFD04FINBn0FdbuaLyYrZY3371L1+RNCmIFvU3XEIIo6XYQJTe7dEEc7Gw6cvc6aQxdNWrYQRpUcf/PfT8/3zZv4AdjaQ7c3YMwf6uj+tIvwwyBY96q61rAQZUiSPyHKg8KpKKJ/haRbzz1ZFnzdHBjfpS4AH64/TlaudfbpFRXAH6+rgy1qBEGzR8wdzU3+7eCZHdD2xmDEfV/D16Emnd9TWB9J/oQoD6q1hPq91cdD22eatOinQ+tQ3d2RSynZzIuUOcpEORS7BY6tVidO7/vx/a/kYWz2ztD/U3jiN6jkC1dPwXcPwJbpUJBn7uhEBSTJnxDlReiNjuqHl8O1OJMV62Bnw+v9GgEwLzKWC8lZJitbiPuWn3tzkEf7p9VuFJYqoAeM361O8aQUQOSHMP8BSDxp7shEBSPJnxDlhV8bqNtdvSkUTlBrIn2a+tK+tic5+Xo+XF+6lXyEMKu9cyHppLrUWpep5o7m7pw84ZGFMGQ+OLjBxYPwdQjsmadOFSOEEUjyJ0R50vnGWqRRSyD5nMmK1WjUqV80Gvj90EX2xV0zWdlC3LPUixA5Q33f411wdDdrOKXS7GF1ebi63dQJqTdMVgeEpJw3d2SiApDkT4jypEYHqN0Z9PmwY5ZJi25SzY2h7WoAMC38KHq9zBIlLNwfb0JuOvi1gxblcKlO12rwxAro+wnYOkJcJHwVBIeWy/Jw4r5I8idEeVPY+nfwR0i5YNKiX+pZHxedLdEXUvn1gLRACAt2Zoc6Oh6Nmjxpy+ntTqNR+yo+swOqt4GcFFg5Dn4ZBZnSAi/uTTn91yCEFasVDDWDoSAXdn5m0qK9Kul4oUc9AGZsPE5atoxEFBaoIA/W3Zgeqe0YdbR8eecVoM4J2PV1dWm6Y6vhq45w8g9zRybKIUn+hCiPOt8YvXhgkckXhx8ZWIs6Xs4kpefyZYTp5hwUosT2fQtXjoGjpzqRckVhY6v+239qE3jVh/TLsOQR+P0FyEk3d3SiHJHkT4jyqHZn8O+gLg6/83OTFm1vq+WN/urULwt2xhGXlGHS8oW4o7TLsHW6+r7H2+ro2Yqmemv4v23Qcbz6+cAimNcJzu01a1ii/JDkT4jySKO52fq3fwGkJ5q0+K4NfOhc35u8AoX/rf3HpGULcUd/vg05qVCtNbQaae5oyo6dI/SeDiPXgKsfXI+Dhb3hz3fUuQ2FuANJ/oQor+p2V29w+Vmw+wuTFq3RaHizfyNstRr+/Ocy20+ZNvkUluurrTGEztjC7D9Pkpxp4iTk3B44tJRyP8ijNOp0hmd3qqOZFb06C8C33eDyUXNHJiyYFfzLEKKC0mhujvzd9x1kXDVp8QE+LowIrAnAtN+PkV8gE9Bau6j4ZD7eeIJz1zKZ/ecpgj+M4IN1/3AlNbvsC9cXwNqX1fetR6iTolsLR3d4aB48+r3az/HyEfimizogTC/rcYviJPkTojyr3wt8m0NeBuyZY/LiJ3avj4eTHaeupPPTXtNNOi0sT16Bnim/HUZRILBOZRpVdSUjt4Bvtp2m04wtvLHqCPHXMssugP0L1KTHwQ26v1125ViyxgPViaHr9VJnA9j0FizqD9fPmDsyYWEk+ROiPPt369/eb0w+75ebkx0v9WwAwKebTnI9Q/oaWatvtp3meEIaHk52fDm8Feue78SC0W1pXcOd3Hw9P+45R5dPtvLi8ihirqQZt/CMJIh4T33f7U1w9jLu+csTlyowfDkM+AzsnOHcLpgbrLaKno6EgnxzRygsgCR/QpR3DfpClaaQmwZ7vzZ58UPb+dPQ14WUrDxm/ykL0Fuj04npfLb5FABv9m9M5Uo6NBoN3RpW4bdng1g2riMh9bwo0CusOHiBB2Zt45kfDnDkfIpxAvjzHchOAd9m6rx+1k6jgTaj1b6A/h3VVU7++ha+fxA+qQerw+DkRsjPMXekwkw0iiJrxBhDamoqbm5upKSk4Orqau5whLU5uhJ+GQ06N5h049GXCe2KSWL4d3ux0WpY93wIDXxdTFq+MB9FURj27R72nL5GSD0vvh/THo1Gc8tjD8Un89XWGDYevWzYFlLPiwldA2hf2/O237uj8/vhu+7q+zF/qEsgipv0BRCzGf5ZDcfXQda/ng7Yu0D9ntDoQQjoAbpK5ovTjKzx/i3Jn5FY48UjLIheD3MDIfE4dH0DOr9i8hCe+eEAG44m0CnAix+eun0CICqW5X+dY/JvR3C0s+GPSaH4ezrd9TsnL6cxd2ssaw5dpODGGtFta3oQ1jWALg28S37t6AvUka2XoqDFcHho7n3UxAoU5KuPgY+tgePhkHbp5j5bB3UGgcYPqn2JHT3MF6eJWeP9W5I/I7HGi0dYmCO/wm9Pqf9pTzwCOtO2vp27mkmPWZHk5uv5dmRbHmhcxaTlC9O7kpZNj5mRpGbn83rfRjwdWqdU3z93NZOvt8Xyy/7z5N4YLd64qithXQPo3dQXG+1dksD9CyF8Iuhc4bkDUMnnHmtihfR6uHAA/lmjvv49KERrC7VDodEAaNi/wv+9WuP9W5I/I7HGi0dYGH0BzGkPV2OgxzvQaZLJQ5ix4ThfbY2lZmUn/pgUis7WxuQxCNMJ++lv1h65RLPqbqwcH4Stzb11I7+cms1320/z095zZOaqU5PU8XLmmS51eahVdexudd7Ma/BFa8i6Dr0/hI7P3k9VrJuiwOVo+Od39XXl2L92aqBGoJoINuoP7jXMFmZZscb7tyR/RmKNF4+wQFFLYdUz4FRZbf2zdzZp8ek5+XT7ZCtX0nKY0qchz3Sua9LyhelsOnaZp7/fj41Ww+qwYJpWv/9+ptczclm06wyLdp0hJSsPgOrujowLrcNj7fxxsPvXLxPhk9TpXXwaw/9tV9e9FcaRFHOjRfB3uPh30X3VWt1IBB8Er3rmic/IrPH+LcmfkVjjxSMsUEE+fNlGfYTT830Ies7kIfx24Dwv/XKISjpbIl7ujI+Lg8ljEGUrLTuPBz7dRkJqNv/XuQ5T+zQy6vnTc/JZsvcs326PIzFNHZHqVcmeMZ1qM6JjTVyuRcM3XQEFRq+DWsFGLV/8S3K82j/wn9/h7C7gXymDd0M1CWw0QB1pXU77+Vrj/VuSPyOxxotHWKi/f4A1E8DZB144BPZ374BvTHq9wkNzd3EoPplH2/ox4+EWJi1flL23Vkfz/e6z1PB0YuPEUBzty+bxfnZeAb8cOM/XkbGcv54FgKuDlg2V3qdaejQ0ewSGfFcmZYtbSL8CJ9apA0biIkH/rzkDPWrdbBGs3rZcLa1njfdvSf6MxBovHmGhCvLg89aQcs5sfaEOnL3OkLm70GhgTVgnmvmZduoZUXYOnL3Gw/N2oyjw09gOBAeU/YTKeQV6fj90ka+2xtLqajgf231DhuLANy1+Zlj3Dvi6SeuyyWUlq3MF/rNGnUomP+vmvkq+av/ARg9CzWCLfyRvjfdvSf6MxBovHmHB9i9Q+0S5VIXno8DO9DfHScujWHnwAm1revDLM4Ey9UsFkJNfQP/Pd3DqSjoPt/Hjk0dM26qrz7hO3uet0eVc4395w/m2oD92NhoebuPH/4XWpZaXafu4ihtyMyDmT/XR8IkN6oTzhRw9oEE/tVWwblew1Zkvztuwxvt3+WmXFUKUXMvHwbW6Oo/XwR/MEsLk3g1xtLNh/9nr/H740t2/ICzevK2nOXUlncrO9rze17j9/EpCGzkdXc41FK8GhI54k/a1PckrUFi6L55uM7fywrKDHE9INXlcVs/eWV1XeMh38GosDP8FWo0AR091NHbUj7D0MZhRF34do05Kn5Nu7qitmrT8GYk1/uYgLNy+b2Hdy2oS+PxBs/zG/cXmU8zcdJKqbg5EvNSlzPqGibIXcyWNvp/tILdAz+fDWvFgi2qmDSDhCHwdCooeRq6GOl0A+OvMNb7aEsOWE4mGQ3s0qkJY17q0qmE9ExVbpIJ8OLf7xsjhcEi7eHNf4aTSjQZAg95mnVTaGu/fkvwZiTVePMLC5WXDZy0gPQH6z4a2T5o8hOy8ArrPjORCchYTe9RjYo/6Jo9B3D+9XuHRr3ez/+x1ujbwZsHodqZ9jK8osLCPmkg0HgSPLi52SPSFFOZujWVd9CUK72rBAZUJ6xJAYN3K0u3A3PR6ddqYY6tvPal0rRB1dZEG/cDFtBPEW+P9W5I/I7HGi0eUA7u/go1T1YlZn/sbbOxMHsLaw5cIW/I3DnZaNr/UherujiaPQdyfH/ec5Y1V0TjZ27Dpxc6m/xkeWg4rx4GdE0z4C9z8bntobGI687bGsvLgBfJvLB3X0t+dsK4BdG/og/Zuq4aIsqcocPnojUml19xiUumON6aQMc2k0tZ4/5bkz0is8eIR5UBuJnzWHDISYeAcaPWEyUNQFIXHvtnDvrhrDGhRjS+GtTJ5DOLeJaRk88CnkaTl5PP2gMY8GVzbtAFkp8KXbSH9MnR/C0JeKtHXLiRn8U1kLMv+iicnX106rqGvC892qUu/ZlXveTUSUQaSYuD4jdVFLhwouq9qS/XRcOOBZTaptDXevyX5MxJrvHhEObHzc9j0JnjUhgn7zTLtwtGLKfT/YgeKAr88E0i7Wp4mj0Hcm3Hf7+ePY5dp6e/Ob88G3X29XWPb+Drs/hI868L43aXuu5qYlsOCnXH8sPss6TnqvHQ1KzvxbOe6PNS6uixBaGlSzqv9A//5Hc7tUvt4FvJuCC2GQaeJRi3SGu/f8quPEBVd2zHqcm/X4yD6V7OE0KSaG0Pb+QPw7u9H0evld87yYEP0Jf44dhlbrYYPhzQzfeJ35R/YM1d933fGPQ1a8nbRMbl3Q3ZO7sZLD9THw8mOs1czmbLiCJ1nbGX+jjgyc/PvfiJhGm5+0PEZeHItvHQSBnwGAT1AaweJx//ziFjcK2n5MxJr/M1BlCPbP4XN70LlehC2F7Smb+1ISs+h68dbScvJZ8aQ5jx6IxkUliklK48HPo3kSloOE7oG8HKvBqYNQFFg8QA4sx0a9oehPxnltJm5+SzdF88322K5nKouHefpbM+Y4FqMCKyFm6Pp+8WKEshKhlN/qE8w/NsZ9dTWeP82a8vf9OnTadeuHS4uLvj4+DBo0CBOnDhxy2MVRaFPnz5oNBpWrVpVZN+5c+fo168fTk5O+Pj48Morr5Cff/M3ua1bt6LRaIq9EhISipxnzpw51KpVCwcHBzp06MC+ffuMXmchzKL90+DgDldPqXNsmYFXJR0v9FD77MzYeIK07DyzxCFK5sP1x7mSlkMdL2cmdAswfQBHV6iJn60D9PrAaKd1srflqU612fZqV6YPbkYNTyeuZeTyyR8nCf4wgo82HDesJywsiKM7NH/U6ImftTJr8hcZGUlYWBh79uxh06ZN5OXl0bNnTzIyMoodO3v27FsO1S8oKKBfv37k5uaya9cuFi9ezKJFi3jrrbeKHXvixAkuXbpkePn4+Bj2LV++nBdffJG3336bv//+mxYtWtCrVy+uXLli3EoLYQ46FwgMU99v+1iddsEMRgbWoo6XM0npOXy5JcYsMYi723v6Kkv3nQPgg8HNcLAzcUtxTjpsfEN9H/ISeNQ0ehE6WxuGta9BxEud+WxoSxpUcSE9J5+5W2Pp9FEE76w5yoXkrLufSIhyyKIe+yYmJuLj40NkZCShoaGG7VFRUfTv35/9+/dTtWpVVq5cyaBBgwBYv349/fv35+LFi1Spos4NNG/ePCZPnkxiYiL29vZs3bqVrl27cv36ddzd3W9ZdocOHWjXrh1ffvklAHq9Hn9/f5577jmmTJly19itsdlYlDNZyTC7OeSkwCOLockgs4QRcfwyYxbtx85Gw6ZJnWVJLguTnVdA38+3czoxg2Ht/Zk+uLnpg9j0Fuz8DDxqwfi9JlmeUK9X2Hz8Cl9uieFQfDIAdjYaPh/aij7NqpZ5+cJ8rPH+bVEDPlJSUgDw9Lw5EjAzM5Phw4czZ84cfH19i31n9+7dNGvWzJD4AfTq1YvU1FSOHj1a5NiWLVtStWpVHnjgAXbu3GnYnpuby4EDB+jRo4dhm1arpUePHuzevfuWsebk5JCamlrkJYRFc3RXO1KDWVv/ujbwoXN9b/IKFP637h+zxCBub86WGE4nZuDtomNKH9Mv4UbiSXV+SoDeH5lsXWqtVsMDjauwanwQS8Z2oMONpeMm/RxF9IUUk8QghKlYTPKn1+uZOHEiwcHBNG3a1LB90qRJBAUFMXDgwFt+LyEhoUjiBxg+F/bpq1q1KvPmzeO3337jt99+w9/fny5duvD3338DkJSUREFBwS3P899+gYWmT5+Om5ub4eXvL53XRTnQ4RmwrwSXo+HkerOEoNFoeLN/I2y0GjYdu8z2U4l3/5IwiRMJaczdGgvAuw82Mf3gB0WB9a+CPg/q91aX/TIxjUZDUIAXS57uSOf63mTn6Rn3/X7pBygqFItJ/sLCwoiOjmbZsmWGbWvWrCEiIoLZs2ff17kbNGjA//3f/9GmTRuCgoJYsGABQUFBzJo1657POXXqVFJSUgyv+Pj4+4pRCJNw8oT249T3kR+BmXp9BPi4MDJQ7cc17fdj5BeYpxVS3FSgV5j822Hy9QoPNK5Cn6bFn7SUuX9+h9NbwEYHvaebvvx/sdFq+HxYK+p4OXMxJZtnfjxATn6BWWMSwlgsIvmbMGEC4eHhbNmyBT+/m8v2REREEBsbi7u7O7a2ttjaqpPTDhkyhC5dugDg6+vL5cuXi5yv8POtHhMXat++PTExaodzLy8vbGxsbnme251Dp9Ph6upa5CVEuRA4Aeyc4dIhdeoEM5nYXZ1z7dSVdH7ae85scQjVD7vPEBWfTCWdLe8NbGr6tXBzM2Hja+r74BfAs45py78FN0c7vh3VFhcHWw6cvc6bq6KxoG7yQtwzsyZ/iqIwYcIEVq5cSUREBLVrF102aMqUKRw+fJioqCjDC2DWrFksXLgQgMDAQI4cOVJkVO6mTZtwdXWlcePGty07KiqKqlXVTrz29va0adOGzZs3G/br9Xo2b95MYGCgsaorhGVwrgztnlLfb50O+blmCcPNyY4Xe6pzx3266STXM8wTh4CLyVl8vFGdZmty7wb4upmmn10R22dCSjy41YBOk0xf/m3U9a7El8Nbo9XAz/vPs2jXGXOHJMR9M2vyFxYWxo8//siSJUtwcXEhISGBhIQEsrLU4fW+vr40bdq0yAugRo0ahkSxZ8+eNG7cmBEjRnDo0CE2btzIG2+8QVhYGDqdOhv87NmzWb16NTExMURHRzNx4kQiIiIICwszxPLiiy/y7bffsnjxYv755x+effZZMjIyePLJJ038tyKECQQ9p7b+XTwIv4yCfPP0ZxrWzp+Gvi6kZOUx+8+TZonB2imKwpurosnILaBNTQ8e72D8aVXu6mos7Ppcfd/7A7B3Mn0Md9C5vjev9VUHv7wXfkz6qYpyz6zJ39y5c0lJSaFLly5UrVrV8Fq+fHmJz2FjY0N4eDg2NjYEBgbyxBNPMHLkSKZNm2Y4Jjc3l5deeolmzZrRuXNnDh06xJ9//kn37t0Nxzz22GN88sknvPXWW7Rs2ZKoqCg2bNhQbBCIEBVCJR947Ad1At0T6+DnkWZJAG1ttLzVX22h/3HvOU5eTjN5DNYu/PAlNh+/gp2Nhg8HN0Nr6iXcFAU2TIGCXKjbXV3NwwI91ak2Q1r7oVdgwpKDxCUVn49WiPLCoub5K8+scZ4gUQHEboGlQyE/G+r1hEd/MNnUGv/2fz/sZ+PRy4TU8+L7Me1N39/MSiVn5tLj00iS0nN5oXs9Jj1Q3/RBHF8Hy4apa7eO3wNeZlhNpISy8woY9u0eDp5LJsCnEivGB+HqIMvBlXfWeP+2iAEfQggzqdsVhi8HW0d18MfyJyAv2+RhvN63MfY2WrafSuLPf2RVHVP5YN0/JKXnEuBTifFd65o+gLwstdUPIGiCRSd+AA52Nnz9RBt8XR2IuZLOxGVRFOil/USUP5L8CWHt6nSBx38GOyeI2QTLhqs3ZROqUdmJsSFqP9731x6TKTVMYFdMEj/vPw/Ah4ObobM18RJuoK7ikXwWXKtD6CumL/8e+Lg68M3INuhstUQcv2IYKCNEeSLJnxACaofC47+oCWDsZlg6zOQJ4PiuAXi76Dh7NZNFO8+YtGxrk51XwNSVRwB4omMN2tbyvMs3ysD1M7DjxlyrPd8H+/KzzF9zP3dmPKwuezcvMpZVBy+YOSIhSkeSPyGEqlYnePxXdRTw6Rt9AXMzTVZ8JZ0tk3s3BOCLiBiupJn+8bO1+GzzKc5ezcTX1YFXb/ydm9yG19S+prVDoclD5onhPgxsWZ3xXdRH5a/+dtiwHrAQ5YEkf0KIm2oFwxO/qUvAnd4KSx8zaQI4uFV1Wvi5kZ6TzyfyOK1MHL2YwjfbTgMwbWAT8wxYOLUJTqwFrS30+RjK6QCfl3s2oEcjH3Lz9Yz7YT+XU+UXFlE+SPInhCiqZuCNBNAF4rbBkkch1zTTWmi1Gt4a0ASAXw6c58j5FJOUay0K9ApTVxyhQK/Qt5kvPZuYYQm3/Bx1/V5Q15r2MVPLoxFotRpmPdaSej6VuJyaw7gfDpCdJ/1VheWT5E8IUVyNjjBihZoAntkOPz0COekmKbpNTQ8GtayGosC7vx+V5bSMaOHOOA6fT8HFwZZ3biTZJrfrC7h2Gir5QufJ5onBiFwc7PhuVFvcHO04FJ/MayuOyDUrLJ4kf0KIW/NvDyNWgs4Vzu40aQI4uU9DHO1s2H/2Or8fvmSSMiu6+GuZzPxDXUXltb6N8HE1wxJuyfGw7RP1fc/3wKFizKlWs7IzXz3eGhuthhUHL/Dt9tPmDkmIO5LkTwhxe/7tYMQq0LnBuV3w4xDIKftVOKq6ORo603+47h+ycuVR2v1QFIXXV0WTlVdAh9qePNbW3zyB/PE65GdBzWBo9oh5YigjwQFehtVqpq8/zpbjMl+lsFyS/Akh7syvDYxcCQ5uEL9HTQCzU8u82KdD61Dd3ZGLKdl8vS22zMuryFZHXWTbyUTsbbVMN8cSbqCuJnNsNWhsoM+McjvI405GBtZkWHt/FAWeX3qQmCumaSkXorQk+RNC3F31NjByNTi4Q/xe+HEwZJftYAwHOxte69sIUOdSu5hs2nkHK4prGblMCz8GwPPdAqjjXcn0QeTn3hzk0f5p8G1q+hhMQKPR8O6DTWlXy4O0nHye/n4/KZl55g5LiGIk+RNClEy1VjcTwPN/wQ9lnwD2beZL+9qeZOfp+XD98TItq6J6P/wY1zJyaejrwrhQMyzhBrB3LiSdBGdv6DLVPDGYiL2tlrlPtKG6uyNxSRlMWPo3+QV6c4clRBGS/AkhSq5aSxi1Bhw94MJ++OEhyEous+I0Gg1v9W+MRgNrDl3krzPXyqysimjbyURWHLyARgPTBzfD3tYM/+WnXoStH6nve7wLju6mj8HEvCrp+GZkGxztbNh+Konp8ouLsDCS/AkhSqdqCxj1Ozh6woUD8MMgyLpeZsU1re7G0HbqAIVpvx9Dr5dpNEoiMzef124s4TYqsBataniYJ5A/3oS8DPBrDy2GmScGM2hSzY1PH20BwPwdcfy8P97MEQlxkyR/QojS822mJoBOleHiQfh+IGSWXavcSz0b4KKz5ciFFH79+3yZlVORzNp0kvPXs6ju7sjLvRqYJ4i47RD9K6CBfp+A1rpuOX2aVeWF7vUAeGNlNAfOSsu1sAzW9S9RCGE8vk1hVDg4ecGlQ2WaAHpV0vH8jZvojA0nSMuWTvR3cuR8CvN3xAHw/qCmVNLZmj6IgjxY94r6vu0YtcXYCr3QvR69m/iSW6Dn/374WwYuCYsgyZ8Q4t5VaQyjw9WO/AmH4fsHyywBHBVUi9peziSl5/DllpgyKaMiyCvQM/m3w+gVGNCiGl0b+pgnkH3fQuI/aveAbm+YJwYLoNVqmPloCxr6upCUnsO4H/bLvJXC7CT5E0LcH59Gagugsw8kHIHFAyDjqtGLsbfV8mZ/deqXhTvOcCbJNOsNlzfzd8Rx7FIq7k52vD2gsXmCSLsMW6er73u8A06e5onDQjjrbPl2ZFs8ne2JvpDKK78ekiXghFlJ8ieEuH8+DWH0WqhUBS5H30gAk4xeTNcGPoTW9ya3QM//1v1j9POXd2eSMpi1SV3C7fW+jfCqpDNPIH++DTmpUK01tBphnhgsjL+nE3Mfb42tVkP44Ut8tVUmLhfmI8mfEMI4vOvfSAB94cpRNQFMTzRqEerUL42w0WrYdOwyO04ZP8Esr9Ql3I6Qk68nOKAyD7fxM08g5/bAoaVY6yCPO+lQpzLTBqoTXH+88QR/HE0wc0TCWsm/SiGE8XjVUxNAl6pw5Rgs7g/pxl3jNMDHhZGBNQGYFn5UJtC94dcD59kZcxWdrZYPHmqGxhzLp53ZAcuGq+9bj1BXhhFFDO9Qw3D9TloexYmEsl8rW4j/kuRPCGFcXgE3EsBqkHgcFvVX+4AZ0cTu9fFwsuPk5XSW7Dtn1HOXR4lpOby/Vn0MPumB+tSs7Gz6IPYvvDHi+ypUbalO6Cxu6c3+jQmsU5mM3ALGfv8X1zNyzR2SsDKS/AkhjK9yXXUUsGt1SDqhtgCmGe8Rl5uTHS/2VOeu+3TTSZIzrfvmOS38GClZeTSu6srYTrVNW3hBHqx9GcIngj4fmg6BMRusfpDHndjZaPnq8db4ezoSfy2L8T/9TZ60YAsTkuRPCFE2DAmgn7qu66J+kHrJaKcf1s6fhr4uJGfmGQY5WKMtx6/w+6GLaDXw0ZDm2NqY8L/1zGvw42D461tAA93fgiHzwc7RdDGUUx7O9nw3sh3O9jbsPn2V98KPmTskYUUk+RNClB3POmoC6OYPV2NuJIAXjXJqWxstb/VXpzJZvPssj8zbxfojl6yqD2B6Tj6v31jC7alOtWnm52a6wq/8A992hbhtYF8Jhi6BkJfAHH0Ny6kGvi7MHtoKjQa+332Wn/aeNXdIwkpI8ieEKFuetdU+gG414FqsmgCmXDDKqYMCvAjrWhdbrYa/zlzn2Z/+pvPHW/lmWywpmRV/FZBPNp7gYko2fh6OTHqgvukKPrEBvnsArp8B95rw1CZo2Nd05VcgDzSuwss3ujC8vfooe08bf45MIf5Lo8hMk0aRmpqKm5sbKSkpuLq6mjscISxP8jk18Us+Bx61b7QIGmc6ksup2fy45yw/7T3HtRud5x3tbHi4jR+jg2tR17uSUcqxJAfPXWfw3F0oCnw/pj2h9b3LvlBFgZ2z4c93AQVqhcCj30v/vvukKArPLT1I+OFLeDrbszosGH9PJ3OHZTWs8f4tyZ+RWOPFI0SpJcffSADPgkctdWUQd3+jnT47r4DVURdYuPMMx/81hUaXBt6MCa5NSD0v80yBYmS5+Xoe/HIHxxPSGNyqOp8+1rLsC83LgjXPwZFf1M9tn4I+H4GNXdmXbQWycgt45OtdRF9IpaGvC789G4SzOdZktkLWeP+W5M9IrPHiEeKepJxXE8DrZ8C9hpoAetQ0ahGKorA79ioLdp5h8/HLFP4vV8+nEqODazG4lR+O9jZGLdOUvow4xSd/nMTT2Z4/X+yMp7N92RaYelGdv+/iQdDaqklfu7FlW6YVupicxYNf7iQpPYdeTaow9/E2aLXl/5cVS2eN929J/ozEGi8eIe5ZygV1+pdrp9W+gKONnwAWOpOUweLdZ/j5r3gycgsAcHeyY1h7dbLdqm7la2Tq6cR0en+2ndx8PbMfa8mgVtXLtsDzB9TELz0BHD3Vx7y1Q8q2TCt24Ox1hn2zh9wCPS90r2favpxWyhrv35L8GYk1XjxC3JfUi+oE0Ndi1dHAo8PVR8FlVVx2Hr/sP8/iXWc4dy0TAButhj5NfXkyuData7hb/CNhvV5h2Ld72Bt3jdD63ix+sl3ZxnxoufqotyAHfBqrI3o9TTyPoBX6eX88r/56GICvHm9N32ZVzRxRxWaN929J/ozEGi8eIe5b6iW1BfBqjDof4Ojf1elhylCBXmHzP5dZsDOOPaevGba38HdnTHAt+jStir2tZU6EsHTfOaauOIKjnQ1/TAotu0EB+gL48x3Y9bn6uUE/GPw16FzKpjxRzHvhx5i/Iw5HOxt+fTaQJtVMOI2PlbHG+7ckf0ZijRePEEaRlqC2AF49pa4IMup3dYJoEzh2MZWFO+NYHXWR3BvzA1Zx1TEysBbD2tco+750pXAlNZvun0aSlp3PG/0aMTakjJLk7FT4bSyc2qh+DnkZur4OWstMiCuq/AI9Ty76i+2nkqju7sjqCcF4VdKZO6wKyRrv35L8GYk1XjxCGE3aZVg8QF0KzqWa+gjYRAkgQFJ6Dkv2nuOHPWdJTMsBQGer5aFW1XkyuDYNfM3f4jX+pwOsO5JAcz83Vo4PxqYsBgJcjYWlw9Sfg60DDJwDzR42fjmiRFIy83joq52cTsqgXS0Pfhrb0WJbpcsza7x/S/JnJNZ48QhhVOlX1AQw8Ti4VFVbAL3qmTSEnPwC1h6+xIKdcURfSDVsDw6ozJjg2nRt4GOW0Zd/HE1g3A8HsNFq+H1CJxpXK4P/Y05vhZ9HQXaymoAPWwLVWhm/HFEqsYnpDJqzk7TsfIa282f64GYW3ze1vLHG+7ckf0ZijRePEEaXnngjAfwHKvmqCaC36Uc7KorC/rPXWbgzjg3RCehv/C9Zq7ITo4Nq8XBbfyqZaA62tOw8Hvh0Gwmp2TzbpS6Tezc0bgGKAvu+gQ1TQSkAv3bw2I/g4mvccsQ923LiCk8t+gu9Au8+2IRRQbXMHVKFYo33b0n+jMQaLx4hykRGEix+EK4chUpVbiSADcwWzvnrmfyw+yxL950jNTsfABedLY+282d0UK0yX4nhzVXR/LDnLLUqO7FhYigOdkacnzA/F9a9BH9/r35uMQz6zwY7B+OVIYzi222n+d+6f7DRavh+THuCA7zMHVKFYY33b7N2Hpg+fTrt2rXDxcUFHx8fBg0axIkTJ255rKIo9OnTB41Gw6pVq4rsO3fuHP369cPJyQkfHx9eeeUV8vPzDftXrFjBAw88gLe3N66urgQGBrJx48Yi53jnnXfQaDRFXg0bGvk3bCHE3Tl7qQlflaaQflkdDHLluNnC8fNwYmrfRuye2p33BjahjrczaTn5zN8RR+ePtzDu+/3sOX2Vsvg9ev+Za/yw5ywAHzzUzLiJX3oifP+gmvhptNDzfRg0VxI/CzU2pDaDW1enQK8w/qe/OXs1w9whiXLMrMlfZGQkYWFh7Nmzh02bNpGXl0fPnj3JyCh+Uc+ePfuW/RwKCgro168fubm57Nq1i8WLF7No0SLeeustwzHbtm3jgQceYN26dRw4cICuXbsyYMAADh48WORcTZo04dKlS4bXjh07jF9pIcTdOVdWE0DfZpBxRZ0O5vIx84aks2VEYC3+nNSZhU+2I6SeF3oF/jh2maHf7KHf5zv4ZX882XkFRikvJ7+AKSuOAPBoWz+CjNnSk3AEvu0K53aDzhWG/wxBz4H0JbNYGo2GDx5qRkt/d1Ky8hi7eD9p2XnmDkuUUxb12DcxMREfHx8iIyMJDQ01bI+KiqJ///7s37+fqlWrsnLlSgYNGgTA+vXr6d+/PxcvXqRKlSoAzJs3j8mTJ5OYmIi9/a2namjSpAmPPfaYIUl85513WLVqFVFRUSWKNScnh5ycHMPn1NRU/P39rarZWIgyl3kNvh8ICYfByQtGrYEqTcwdlcGpy2ks3HWGFX+fJztPnSrGq5I9j3eoyeMda+Djcu+taLP/PMnsP0/hVUldws3dyUjTzhxbAyv/D/IywbMuDFtmln6V4t5cSc1mwJc7uJyaQ/eGPnwzsm3ZjPy2IvLY18xSUlIA8PT0NGzLzMxk+PDhzJkzB1/f4h2Qd+/eTbNmzQyJH0CvXr1ITU3l6NGjtyxHr9eTlpZWpByAU6dOUa1aNerUqcPjjz/OuXPnbhvr9OnTcXNzM7z8/Y23OL0Q4gYnTxi5Gqq2gMwkdTBIQrS5ozKoV8WFDx5qxp6p3ZncuyFV3RxISs/ls82nCP4wghd/jiL6Qkqpz3vqchpztsQA8PaAJsZJ/PR62PoR/DxCTfzqdIWnN0viV874uDrwzYi26Gy1bD5+hZl/3LqrlBB3YjHJn16vZ+LEiQQHB9O0aVPD9kmTJhEUFMTAgQNv+b2EhIQiiR9g+JyQkHDL73zyySekp6fz6KOPGrZ16NCBRYsWsWHDBubOnUtcXBwhISGkpaXd8hxTp04lJSXF8IqPjy9VfYUQJVSYAFZrBZlXbySAR8wdVRHuTvY826Uu217typfDW9G6hjt5BQor/r5A/y928Oi83WyIvkSB/u4PWvR6hSkrjpBXoNC9oQ/9mxthaa/cDPh1NGz9QP3ccTw8/is4etz/uYXJtfB3Z8bDzQH4amssq6MumDkiUd6YZq6CEggLCyM6OrpIP7s1a9YQERFRrG/e/ViyZAnvvvsuq1evxsfHx7C9T58+hvfNmzenQ4cO1KxZk59//pmnnnqq2Hl0Oh06ncy2LoRJOHrAiFXww0Nw8W81ASxsEbQgdjZa+jevRv/m1YiKT2bhzjjWHr7EvjPX2HfmGtXdHRkdVItH2/nj5mh3y3P8tO8cB85ex9nehvcGNb3/Od2S42HZMDVh1tpB/1nQesT9nVOY3cCW1TmekMbcrbG8+uthans509zP3dxhiXLCIlr+JkyYQHh4OFu2bMHPz8+wPSIigtjYWNzd3bG1tcXWVs1VhwwZQpcuXQDw9fXl8uXLRc5X+Pm/j4mXLVvG2LFj+fnnn+nRo8cdY3J3d6d+/frExMTcb/WEEMbg6A4jV0H1tpB1XZ0O5mKUmYO6vZb+7nw2tBU7JncjrGtdPJzsuJCcxf/W/UPg9M28tTqa04npRb5zKSWLj9arI5tf6dWAau6O9xfEuT3wTRc18XP2VldOkcSvwni5ZwO6N/QhJ1/PuO8PcCU129whiXLCrMmfoihMmDCBlStXEhERQe3atYvsnzJlCocPHyYqKsrwApg1axYLFy4EIDAwkCNHjnDlyhXD9zZt2oSrqyuNGzc2bFu6dClPPvkkS5cupV+/fneNLT09ndjYWKpWNcIjFyGEcTi4wYgV6kTE2cnqVCUXjfdkoCz4ujnwSq+G7J7anQ8HN6NBFRcycwv4fvdZus2M5MmF+9h+KhFFUXhr9VHSc/JpVcOdEYG17q/gv39Qp8nJTFJHTT+9BWp0NEqdhGWw0WqYPbQlAT6VSEjNZtwPB4w22lxUbGYd7Tt+/HiWLFnC6tWradDg5iSubm5uODre+jdejUZTZLRvQUEBLVu2pFq1asyYMYOEhARGjBjB2LFj+eADtX/LkiVLGDVqFJ999hmDBw82nMvR0RE3NzcAXn75ZQYMGEDNmjW5ePEib7/9NlFRURw7dgxvb++71sUaRwsJYTbZqfDTwxC/90ZCuBKqtzF3VCWiKAq7Yq+ycGccm49fofB/YD8PR85fz8LORkP4cyH3vp5wQT788Qbsnat+bjxQnb/P3tk4FRAW50xSBgPn7CQlK48hrf345JHmsgRcKVjj/dusyd/tLs6FCxcyevTo237n38kfwNmzZ3n22WfZunUrzs7OjBo1ig8//NDwmLhLly5ERkYWO9eoUaNYtGgRAEOHDmXbtm1cvXoVb29vOnXqxP/+9z/q1i3Z4vLWePEIYVY5afDjwxC/BzQ2UDMI6veC+n3AK8Dc0ZVIXFIGi3ed4Zf98WTkqi02z3UL4KWe97iiSdZ1+OVJOL1F/dzlNej8qszfZwV2xiQxcsE+CvQKb/RrxNiQOuYOqdywxvu3Rc3zV55Z48UjhNnlpMEvoyHmz6LbPetC/d5qMlgzCGxuPbjCUqRm5/Hr/vNcz8xlQrcAdLb3sJJH4klYOhSuxYKdEzz0NTR+0PjBCou1aGcc7/x+DK0GFoxuR5cGPnf/krDK+7ckf0ZijRePEBbj2mk4+Qec3ABndoD+Xysf6FwhoLuaDAY8oK4eUtGc2gS/joGcVHCrAcOWqP38hFVRFIWpK46w7K94XBxsWRUWTF3vSuYOy+JZ4/1bkj8jscaLRwiLlJMGsVvURPDkRnXAg4EG/NvfeDzcG3wal+9HoooCu7+ETW+BoocaQfDo91Dp7v2URcWUm6/n8e/28NeZ69TxcmZlWPBtpxUSKmu8f0vyZyTWePEIYfH0enVewJMb1Nd/J4d2q3EzEazVCezufTk2k8vLhvCJcGip+rn1SOg7E2yNtAycKLeS0nN48IsdXEzJJrS+NwtHt5Ml4O7AGu/fkvwZiTVePEKUOynn4dQfcGIDxEVC/r/mRbNzUpc8q99LfbkUX07SYqQlwPIn4Pxf6mCX3tOh/bjy3YopjOroxRQenrubrLwCng6pzev9Gt/9S1bKGu/fkvwZiTVePEKUa7mZELft5uPhtItF91drdXPQiG8L0FrEnPhw4W9Y9rgar4M7PLII6nY1d1TCAq09fImwJX8DMLFHPZ7rVk9aAG/BGu/fkvwZiTVePEJUGIqiPhIufDx84UDR/ZV8oX5PNRms08V8c+Yd+RVWh6ktll4NYNhSqFyy6aiEdZr950lm/3kKgPa1PJk1tCXV73flmArGGu/fkvwZiTVePEJUWGmXIWaTmgjGboHcfy3DZqOD2qE3Hw+71yj7ePR62PI+bJ+pfq7XE4Z8p05wLcQdKIrCir8v8NbqaDJyC3BxsOWDh5oxoEU1c4dmMazx/i3Jn5FY48UjhFXIz1Gnjzm5EU6uh+RzRff7NLk5aMSvLWjvYY6+O8lJgxXj4MQ69XPwC9D9beOXIyq0s1czeGFZFFHxyQAMae3HuwObUElna97ALIA13r8l+TMSa7x4hLA6igKJJ24+Ho7fq06xUsipstoqV78X1O12/y1z1+Jg6TBI/EdtcXzwC2jx2P2dU1itvAI9n28+xZwtMegVqFnZic+GtqKlv7u5QzMra7x/S/JnJNZ48Qhh9TKvqauLnNwAp/6EnJSb+7S2N5ac662+Sts3L247/DwSsq6pfQ6HLgG/8rF+sbBs++KuMWl5FBeSs7DRapjUox7Pdgmw2sEg1nj/luTPSKzx4hFC/EtBntoSeGK9+oj46qmi+yvXu/l4uEbHOy8599d3sH4y6PPVUcdDl4Cr9NESxpOSlcfrK48QfvgSAO1rezL7sZZUs8LBINZ4/5bkz0is8eIRQtzB1dgb/QQ3wNmdaiJXSOd2c8m5eg+Ak6e6vSAP1r8K+xeon5s9oj7qtbO+G7Ioe4qi8NvfF3j7xmAQVwdbpg9uTr/mVc0dmklZ4/1bkj8jscaLRwhRQtkpN5ecO/UHZF69uU+jBf8OaqtgzGY4sx3QQI+3IXiiTNwsytyZpAxeWB7FoRuDQR5p48c7DzbB2UoGg1jj/VuSPyOxxotHCHEP9AXqPIKFk0tfji66376SOo1Lgz7miU9YpbwCPZ/9eYo5W2NQFKh1YzBICysYDGKN929J/ozEGi8eIYQRJMfDqY3qknM5aTBgNvg0MndUwkrtPX2VScujuJiSja1Ww4s96/N/oXUr9GAQa7x/S/JnJNZ48QghhKh4UjLzeG3lEdYeUQeDdKzjyazHWlLVrWL2PbXG+7eFLFYphBBCCEvg5mTHl8NbMePh5jjZ27Dn9DV6z97O+hvJoCj/JPkTQgghRBEajYZH2/qz9vkQmvu5kZKVx7M//c3kXw+TkZN/9xMIiybJnxBCCCFuqbaXM789G8T4LnXRaGD5/nj6f7GDw+eTzR2auA+S/AkhhBDituxstLzauyFLxnbE19WBuKQMBn+1i7lbY9HrZdhAeSTJnxBCCCHuKrBuZTZMDKFPU1/y9QofbTjO49/t5VJKlrlDE6UkyZ8QQgghSsTdyZ6vHm/NR0Oa4Whnw+7TV+k9ezsbomUwSHkiyZ8QQgghSkyj0fBYuxqsfb4Tzaqrg0Ge+fFvpvx2mMxcGQxSHkjyJ4QQQohSq+Ndid+eDeKZzupgkGV/xdP/8x0cOZ9i7tDEXUjyJ4QQQoh7Ym+rZUqfhvw0tgO+rg6cTspg8NydzIuUwSCWTJI/IYQQQtyXoLperH8hhN5NfMkrUPhw/XFGLNhLQkq2uUMTtyDJnxBCCCHum4ezPXOfaM2Hg9XBIDtjrtL7s21sPJpg7tDEf0jyJ4QQQgij0Gg0DG1fg/DnO9G0uivJmXn83w8HmLriiAwGsSCS/AkhhBDCqOp6V2LFs8H8X2gdAJbuO0f/L3YQfUEGg1gCSf6EEEIIYXT2tlqm9m3ET2M7UMVVx+nEDB76aiffbJPBIOYmyZ8QQgghykxwgBcbXgilZ+Mq5BUofLDuOCMX7ONyqgwGMRdJ/oQQQghRpjyc7fl6RBs+eKgZDnZadsQk0Xv2Nv6QwSBmIcmfEEIIIcqcRqNheIcahD8XQpNqrlzPzGPcDwd4beURsnILzB2eVZHkTwghhBAmE+BTiRXjgxh3YzDIkr3n6P/Fdo5elMEgpiLJnxBCCCFMSmdrw2t9G/HDU+3xcdERm5jBQ3N28d320zIYxAQk+RNCCCGEWYTU82bDxFB6NKpCboGe99f+w6iF+7gig0HKlFmTv+nTp9OuXTtcXFzw8fFh0KBBnDhx4pbHKopCnz590Gg0rFq1qsi+c+fO0a9fP5ycnPDx8eGVV14hP7/oZJJbt26ldevW6HQ6AgICWLRoUbEy5syZQ61atXBwcKBDhw7s27fPWFUVQgghxC14Otvz7cg2vD+oKQ52WrafSqL3Z9v589hlc4dWYZk1+YuMjCQsLIw9e/awadMm8vLy6NmzJxkZGcWOnT17NhqNptj2goIC+vXrR25uLrt27WLx4sUsWrSIt956y3BMXFwc/fr1o2vXrkRFRTFx4kTGjh3Lxo0bDccsX76cF198kbfffpu///6bFi1a0KtXL65cuVI2lRdCCCEEoA4GeaJjTcKf60Sjqq5cy8hl7Pf7eWOVDAYpCxpFUSzm4XpiYiI+Pj5ERkYSGhpq2B4VFUX//v3Zv38/VatWZeXKlQwaNAiA9evX079/fy5evEiVKlUAmDdvHpMnTyYxMRF7e3smT57M2rVriY6ONpxz6NChJCcns2HDBgA6dOhAu3bt+PLLLwHQ6/X4+/vz3HPPMWXKlLvGnpqaipubGykpKbi6uhrrr0QIIYSwKjn5BXy84QTf7YgD1AEinw9tReNqZXNvtcb7t0X1+UtJUUf6eHp6GrZlZmYyfPhw5syZg6+vb7Hv7N69m2bNmhkSP4BevXqRmprK0aNHDcf06NGjyPd69erF7t27AcjNzeXAgQNFjtFqtfTo0cNwzH/l5OSQmppa5CWEEEKI+6OzteGN/o35fkx7vF10xFxJZ9CcnTIYxIgsJvnT6/VMnDiR4OBgmjZtatg+adIkgoKCGDhw4C2/l5CQUCTxAwyfExIS7nhMamoqWVlZJCUlUVBQcMtjCs/xX9OnT8fNzc3w8vf3L12FhRBCCHFbofW92fBCCN0b+hgGgzz9/X5JAI3AYpK/sLAwoqOjWbZsmWHbmjVriIiIYPbs2eYL7DamTp1KSkqK4RUfH2/ukIQQQogKpXIlHd+Nast7A5ugs9XSuqYHWm3x/v+idGzNHQDAhAkTCA8PZ9u2bfj5+Rm2R0REEBsbi7u7e5HjhwwZQkhICFu3bsXX17fYqNzLl9URQoWPiX19fQ3b/n2Mq6srjo6O2NjYYGNjc8tjbvWoGUCn06HT6e6pvkIIIYQoGY1Gw4jAWoTU88bf08nc4VQIZm35UxSFCRMmsHLlSiIiIqhdu3aR/VOmTOHw4cNERUUZXgCzZs1i4cKFAAQGBnLkyJEio3I3bdqEq6srjRs3NhyzefPmIufetGkTgYGBANjb29OmTZsix+j1ejZv3mw4RgghhBDmU8vLGRtp9TMKs7b8hYWFsWTJElavXo2Li4uhf52bmxuOjo74+vresuWtRo0ahkSxZ8+eNG7cmBEjRjBjxgwSEhJ44403CAsLM7TMPfPMM3z55Ze8+uqrjBkzhoiICH7++WfWrl1rOOeLL77IqFGjaNu2Le3bt2f27NlkZGTw5JNPmuBvQgghhBDCNMya/M2dOxeALl26FNm+cOFCRo8eXaJz2NjYEB4ezrPPPktgYCDOzs6MGjWKadOmGY6pXbs2a9euZdKkSXz22Wf4+fnx3Xff0atXL8Mxjz32GImJibz11lskJCTQsmVLNmzYUGwQiBBCCCFEeWZR8/yVZ9Y4T5AQQghR3lnj/dtiRvsKIYQQQoiyJ8mfEEIIIYQVkeRPCCGEEMKKSPInhBBCCGFFJPkTQgghhLAikvwJIYQQQlgRSf6EEEIIIayIJH9CCCGEEFZEkj8hhBBCCCsiyZ8QQgghhBUx69q+FUnhKnmpqalmjkQIIYQQJVV437am1W4l+TOStLQ0APz9/c0ciRBCCCFKKy0tDTc3N3OHYRIaxZpS3TKk1+u5ePEiLi4uaDQao547NTUVf39/4uPjy/Wi01IPyyL1sCxSD8tSUeoBFacuZVUPRVFIS0ujWrVqaLXW0RtOWv6MRKvV4ufnV6ZluLq6lut/uIWkHpZF6mFZpB6WpaLUAypOXcqiHtbS4lfIOlJcIYQQQggBSPInhBBCCGFVJPkrB3Q6HW+//TY6nc7codwXqYdlkXpYFqmHZako9YCKU5eKUg9LIAM+hBBCCCGsiLT8CSGEEEJYEUn+hBBCCCGsiCR/QgghhBBWRJI/IYQQQghroliIDz74QGnbtq1SqVIlxdvbWxk4cKBy/PjxIsdkZWUp48ePVzw9PRVnZ2dl8ODBSkJCgmF/VFSUMnToUMXPz09xcHBQGjZsqMyePbvIObZv364EBQUpnp6eioODg9KgQQPl008/vWt8er1eefPNNxVfX1/FwcFB6d69u3Ly5EnD/ri4OGXMmDGKu7u7otFoFI1Gozg5OSkDBgy4Yz0cHBwUb29vxdPTU3FxcVE6duyofPXVV0Xq4e3trfj7+xf5u/npp5/uWo+ff/5ZadCggaLT6ZSmTZsqa9euLVYPPz8/pUqVKoqDg4PSqFEj5f33379jPeLi4hSg2Mve3r5IPWrWrKn4+PgoWq1WsbGxUWxsbBQvL6+71sPV1VXR6XSKm5ubMmbMGCUtLa1IPQICApTGjRsr9vb2iouLi+Li4lKm9fDz81MqV66saLVaxc7OzrC/rOpRtWpVxdvbW3F0dFR69eqlRERE3PW6OnTokNKpUyfF3t5ecXZ2VpycnIpdV/Xq1TP8PGxtbUtUD51Opzg7Oyt2dnaKt7e38vLLLyt5eXlF6lG7dm2lTp06ip2dneLh4aG4ubmVWT2cnZ0VT09PxcPDQwEUd3f3Ev/7sKSfh4ODg+H8dnZ2ik6nU3Q6Xbn7eTg6OirOzs6Kg4ODYmNjo9jZ2RliK0/1+Pf/u4GBgQqgaLVas9SjVq1aiq2traLT6Qz/RgvvhYX10Ol0SvXq1ZXAwEClUqVKio2NjWJvb6/odLpb/p9ma2urODg4FDtf4b3Q3d1d0Wq1ikajUZydne9YD3t7e6VOnTrKgw8+qPj4+BQpu1evXsrJkycN98JatWopDg4OSp06dZS33npLycnJKfLz0Ol0ip+fn/LRRx8piqIov/32m9KjRw/Fy8tLcXFxUapUqaJ4eHgo9vb2Sr169ZS1a9feMU+4evWqMnz4cMXFxaXIv/N/3wvt7e0VJycnxdbWtkjZCQkJyqhRo5SqVasafib/vr/fzu3qUqhz5863/Jn07dv3juc9e/as0rdvX8XR0bHItfVvW7ZsUVq1aqXY29srdevWVRYuXHjXeP/NYpK/Xr16KQsXLlSio6OVqKgopW/fvkqNGjWU9PR0wzHPPPOM4u/vr2zevFnZv3+/0rFjRyUoKMiwf/78+crzzz+vbN26VYmNjVV++OEHxdHRUfniiy8Mx/z999/KkiVLlOjoaCUuLk754YcfFCcnJ+Xrr7++Y3wffvih4ubmpqxatUo5dOiQ8uCDDyq1a9dWsrKyFEVRlPXr1yujR49W2rRpo3z00UfKF198oXh4eCi1a9e+Yz2GDh2q1KhRQ2nevLly8uRJZerUqYqNjY0ybNgwQz2aNWum2NvbK6+99prh78bX11dZsGDBbeuxc+dOxcbGRpkxY4Zy7Ngx5Y033lDs7OyUiRMnGuoxePBgxcnJSalatapy/Phx5euvv1a0Wq3SrVu329bj6NGjCqD8+eefysiRI5Vq1aopv/zyi/LYY48Z6jFz5kzFxsZG0Wg0yoABA5SPP/5Y8fb2VipXrnzHeoSGhio1atRQHBwclFdeeUUJCAhQevToYajHvn37FGdnZ0Wr1SojRoxQnJycFHt7e6VVq1ZlUo+xY8cqlSpVUrRarTJgwABl4sSJir29vRIQEGD0etjZ2SnVq1dXPD09lWrVqimHDh1Sxo0bp3h7eytPPPHEbetx8eJFpUqVKsrjjz+uPProo4a/47Zt2xrqsWzZMsONsW/fvsqIESMUW1tbpV69eretx6FDh5T69esrTZo0URwcHJTnnntO8fLyUkaMGGGoxx9//KHY2toqWq1WGTlypOLo6KhoNBqlVq1aZVKPX3/9VenQoYOi0WgUBwcHJSwsrET/Pizt59G/f3+lZ8+eilarVfr27av07t1bcXFxURo2bFiufh4//PCDMnjwYEWr1Sr9+/dXJkyYoGi1WqVWrVrlqh7//n/X0dFRadasmdKjR487XldlVY+NGzcqISEhyvPPP694enoqI0aMUPr27av4+/srPj4+yuOPP65ER0crPXr0UDQajdKyZUvlueeeU5o2barUrFlTsbe3V+zs7JQXX3xReeqpp5QVK1YoISEhytNPP604ODgoU6ZMMdxbd+7cqfz4449KQECAEhwcrLz//vuKTqdTKlWqdNt6rF69WnnwwQcVQKlevbrSunVrJTQ0VPHz81PGjBmj1KhRQ1m5cqUyevRoZePGjUpsbKyyevVqxcfHR3nppZeUlJQUw88jOjpaWbp0qeLo6Kh8/fXXygsvvKB89NFHys6dO5WmTZsqdevWVWxtbZXw8HBl69atSlRU1B3zhN69eystWrRQ9uzZo2zfvl0JCAhQhg0bZrgXTps2TalcubLStGlTxdbWVpkxY4bi6OiozJs3T+nYsaMSEhKi7Nu3Tzl+/Lgybty4Yvft/7pTXQpdvXpVuXTpkuEVHR2t2NjY3DFRy8/PV5o2bar06NFDOXjwoLJu3TrFy8tLmTp1quGY06dPK05OTsqLL76oHDt2TPniiy8UGxsbZcOGDXfMY/7NYpK//7py5YoCKJGRkYqiKEpycrJiZ2en/PLLL4Zj/vnnHwVQdu/efdvzjB8/Xunatesdy3rooYeUJ5544rb79Xq94uvrq3z88ceGbcnJyYpOp1OWLl162+/NmDFDqVGjRqnr0bhxY+Xdd9+9bT3++3dzq3o8+uijSr9+/Yrsb9++veLk5GSoR5MmTZTXXnutSD1at26tvP7667etx7JlyxRA2bZt223rMWTIEKVbt25F6vHiiy8qwcHBt63HsWPHFED566+/DPVYv369Aijdu3dXFEVRvvrqK8XDw0Np166doR6TJ082/Adt7HpUrlxZ+fLLL4vUY/Dgwcrjjz9u9Ho8/fTThmugsB4FBQWKt7e38u233962HpMmTVI8PDyUK1euGOoxefJkpUGDBoZ6dO/eXenXr1+RenTo0EH5v//7v9vWY926dYpWq1USEhIM9Zg7d65ia2ur9OnTR1EURXn11VeVJk2aFLmu+vbtW2b1+Pe/Dzc3N2XWrFmGc5Wnn8d//53n5+crLi4uyuLFi8vtz6PwumrVqpXyxhtvlLt65OfnK46OjsrAgQOVUaNGKQMHDrzjdWWqetSuXdtQbqVKlZScnBzDPWTgwIFKgwYNlP9v79yjorrOPvwb5iYzDDeBAS8zINd6w7uOKOKNgUqCJEbsSgEtSoy3SE21EltNRU0qaCOadNko9oIab1FXo65Q0GR5qQmogAQRb1UUYk1BYjGA8H5/+J39zQFGTatRP95nrfljzpzZ+zzn3fvsl3P2bIj+75ql1+vbHT9sXex5EN0fQ4YMGdKux9ChQyklJYW8vb0pJCSEANDZs2fFWJiTk9Ouh62L1Neku4BEJOIh8cEHH1CPHj2osbHRrouE5PKnP/1J9HOJgwcPihsQEyZMkNUtXf8WLVpEfn5+wkXCXkxseRSX1qxdu5YMBsMDk8rWMZHOibOzs6hLiokt8fHxZLVa7Zbbmmd2zt/t27cBAO7u7gCAwsJCNDU1Ydy4cWKfkJAQmEwmnDhx4oHlSGW0x+nTp3H8+HGMGjXK7j6XL19GdXW1rG4XFxcMHTr0oXUbDIbv5dHS0oJvv/22zTHberQ+N+15nDhxQlYHAAwdOhT19fVi+/Dhw/Hpp5+iX79+OH78OA4fPozz588jMjJSfGfq1KlYv3698HB1dQUAvPzyy2hqakJGRgb2798v83B0dERBQQG++eYbuLu749KlSzhw4AB+/OMfC48tW7bAy8tLeJw4cQKurq5QKpXCQzpOk8kknMLDwzFs2DDhYbVa0djYiIMHDz52j7t370Kj0cji4ejoiKNHjz52j6FDhwIANBqNaFcODg7QarU4evSoXY+KigqEh4ejpKREtCur1Yry8nIYjUaYTCYUFhZizJgxMg+r1YoTJ04Ij2XLlqFfv34yjz59+uDGjRvCw2q14t69e+jZs6esjdm2q2HDhgEAPD09H7uHbf9o/c/Xn6d4tO7n9fX1aGpqgru7+3MbDzc3N+Tl5aG8vBzh4eHPncfbb78NAG2umU/bQ2oTADB48GBoNBoxhiQnJ6O8vBw1NTUICQlB586dUV9fj/LycqxduxaxsbEoLS2VuVRXV7frYTQaxRgSFxfXrofVasVnn32G6upqjB49GgDQqVMnMRaePHmyXY+IiAhxHqW+ptFoxD5SPGpqagAA+/fvh8ViwaxZs3Du3Dl88MEHWLlyJZqbm8V3tmzZAoVCIc7N5cuX4erqikGDBol9xo0bBwcHB3H8tnVL1z+r1YrLly8LFwl7MYmIiBDvH8WlNZs2bcKUKVOg1+vFtmXLlsHX11dWrhQT23Lr6upEPNsb3yWnR+WZTP5aWlowf/58hIWFoXfv3gCA6upqaDQaMWhLGI1GVFdXt1vO8ePH8dFHHyElJaXNZ926dYNWq8WgQYMwe/ZsTJ8+3e7xSOXbBuNhdV+4cAHr1q2Dg4PD9/LIyMjAnTt3MHny5HY9Wp8bex7V1dVtjldqpNL2rKws9OzZEydPnsT69esRFRWFDRs2IDw8XHynU6dOuHHjhvAYOHAgMjMzMWfOHKjVakRERGDixIkicTIajejSpQsiIiLw9ddfY/78+fD390dERAQiIiKEh8FggF6vFx6pqam4ffu2zEOlUrWJg9FolHlILiaT6bF7mM1mLFmyBHV1dZg0aRJyc3OxZ88eXL9+/bF7SBettLQ0uLm54caNG3j33XdRWVmJqqoqux4NDQ2i7UjtSjonUj11dXUoKCiQtSuj0Yhr164JD3d3dzQ0NAiPNWvWoLi4WOYhlatUKu16hIaGAgAWLlz42D1s+4ftxdO2fzwP8WjdzxctWoQuXbpAr9c/d/FIT0/HtWvXkJqaigkTJiArK+u58ygoKMB7770HrVZr97r7NDyqqqowY8YMzJ8/H66urggMDBTlajQa+Pv7i/cA4OXlhaCgIOj1emRnZ6OlpQXDhw9HZWWlcImIiJB5VFdX49y5c7IxZN68ee16GI1G3Lx5EwAwZMgQ4VFTUwNPT08cOXKkjYePjw9cXV2RlZWF1157rd1xyTYeAHDp0iXs2rULZ86cgZOTE95++21kZmYiPT1dfMfFxQVBQUFiLFSpVOKPPgmVSgV3d3fU1NSINiDV1fq9j48PFi9ejJqaGjQ2NrYbEx8fH/EHo+15eZCLLV988QXOnj3bJtfw8PAQsXzUcu3tU1dXh7t377apu10e+R7hD8jMmTPJbDbTtWvXxLacnBzSaDRt9h08eDAtXLiwzfaSkhLy8PCg5cuXt1vHpUuXqLi4mDZu3Eju7u60detWIiL6y1/+Qnq9Xrw+//xzOnbsGAGgGzduyMp45ZVXaPLkyW3KrqysJH9/fwoJCZF56PV6MSn3tddea+MRExNDOp2OcnNz7Xq0Pjf2PJRKpZiQLHksWLBA5rF69WoKCgqisLAwioyMpKysLHJychL1P6pHQkICjRgxQnhIk6ZTU1OpuLiY9uzZQ0ajkXQ6nV2PBQsWkNlsbuOB/52wrNfrSalU0gsvvCDzkObu+fr6PnaPyMhIMXdRqVRSUFAQxcfHE4An5hEcHEwASKFQkNVqpejoaIqKirLrMX78eDFBXPKQyvrqq69o8ODBpFAoSKvVytrVW2+9RQqFwq5HfHw8WSwWmce///1vAkBqtZr0ej0pFAqaMWOGzOOTTz4hANSnT5/H7mHbP8xmM61du/ah/eNZjIetx6pVq8jNzY127dr1QI9nOR5btmyh06dPU0ZGBjk5OZGLi8tz4zFgwABydHSU9Y+kpCQaPXr0U49HcnKyqHfkyJGivWq1WnJwcJB5EBH16NGDVCqV8GhsbCR/f39KSUkRLq09ZsyYQSNGjJCNIdnZ2QSAJkyYIDw0Go14hA6A/vznP7fx8Pb2lnm0diEiGj9+PKWkpMjG2MmTJ8s8AgMDyd3dXTYWZmZmkre3N9li67JixQoKCgqi1nh6epJSqaStW7eKuomINmzYQF5eXuIc7ty5k0JDQwkAKZXKNjFpD9vyJFrHxJaUlBTq06eP3fIkZsyYQZGRkbJtUts6cOCAOEcrV66U7SO1rfr6+ofWQfQMzvmbPXs2devWjS5duiTbnpeXRwCopqZGtt1kMrX5lWtpaSl5eXlRWlraI9W5fPly0XDq6uqooqJCvOrr6+nixYsEgE6fPi37Xnh4OM2bN0+27fr16xQYGEjBwcFtPCoqKsTchNa/JPLw8CC1Wk1//etf7XrYOzfteXTt2pXS0tJkHnPnzhUe9fX1oj5bj+TkZLJard/LY/369aJjenh4kEKhoLi4OJmHs7MzqVQqam5ubtdj06ZN5OrqKvNoamoScwgrKiooNjaWYmJiZB7S/K3t27c/dg/p/Ny9e5cqKyvp7NmzpNPpyMPDw248/lOP/Px8AkD/+te/aPjw4TRjxgwiuj9Pc9asWXY9EhISaOzYsTIP27I8PDwIAE2fPl0WD71eT15eXnY9fvWrX1FoaKjM49KlSwSAfvazn1FFRQUNGjSIZs+eLfPYvHkzOTs7ExE9dg/b/mE2m2nRokUP7R/PYjwkj9WrV5OLiwt99NFHD/V41uMhtatOnTqRn5/fc+Ph6upKAGSrEgAQCc2FCxeeikdCQgLNmjVL1Ct52F6z9u/fLzy2bdtGCoVC1s+JiCIjI0mr1VJaWtpDPSQXaQ7c3LlzhUdSUhItXrxY/DG0bNky4VFbW0sWi4XmzZsnPIhI5tLc3CziERsbKxtjd+/eLTyIiEJCQsjBwUHWtg4cOEAAxJy31i62/VyiqalJrDKxdu1aUTcR0a9//Wvq27evrC1ILjdv3pTFxB625Um0Lk/izp075Ozs3Gb1kfZoHRMiEm3r1KlTREQ0cuRIeuONN2T72LatR+GZeexLRJgzZw4+/vhj5Ofnw8/PT/b5wIEDoVarkZeXJ7aVl5fj6tWrsFgsYltpaSlGjx6NpKQkrFix4pHqbmlpQUNDAwDAYDAgICBAvBwdHeHn5wdvb29Z3XV1dTh58qSs7uvXr4s5d99++20bj4CAALz44otQq9UoLi4W2zMzM3Hr1i2kp6djwoQJbTzS09MfeG7a8wgLC0NxcbHM48svv4ROp0NeXh6amprQ1NSE7777TuahVCpRX1//vTzOnDkDHx8f4eHj4yMeUUge4eHhUKlUmDt3brseFosFtbW1KCwsFB75+fkA7s9VCQgIgNVqxbFjx/DFF18Ij9zcXAD3b/E/bg8pHp06dUJtbS3GjBkDjUaD6dOn243Hf+MRHBwMpVIp5uhVVFSgoKAAYWFhdj0sFgtOnTqF6Oho4SGVtXnzZty6dQt9+/YVjwukeLi4uGDixIkP9CgpKcHNmzeFR25uLlQqFaqrqxEQEIAxY8bgs88+k7Wr3NxcWCwW1NXVPXYP2/7R2NiIDRs2PLR/PIvxSE9PR2lpKZYvX473338fc+fOfSSPZzkeUrsKCAhA9+7dnxuP2tpapKamoqioCGfOnMGuXbug1WphMplQVFSEjIyMH9QjIiICAwYMgMFgwN69e0W9kofZbBbXrOzsbAQHB+PQoUNISkoCESE5OVkcY3FxMfLy8tC7d2/cvn37oR7A/TGkrq4OKpUKFy9eFB6FhYU4cuQIRo0aBW9vb+zdu1dcaxUKBU6dOgVfX18UFBQgNjYW169fR0REBAYOHIjs7GwxR9diseDzzz+H2WwWY1NBQQGCg4Ph5uaGbdu24cKFC+jcuTOio6PFcZ4/fx4+Pj5Qq9Xtti3bfi6Rn5+PlpYWWCwW5OXlibqbmppEHKS24ObmBuD+42RPT08Rk9jYWNjDtjyJ1uVJ7Ny5Ew0NDfjpT39qtzx7MZHKdXZ2FvMwJSdbJKdH5pHTxCfM66+/Ti4uLnTkyBHZT6Ntb2HOnDmTTCYT5efnU0FBAVksFrJYLOLzkpIS8ZN52zKkTJ6IaP369bR//346f/48nT9/nj788EMyGAxtfhnamnfeeYdcXV1p3759VFxcTLGxsbKlXiorKykgIIC6du1Kzs7OtHv3bioqKqKioqIHeqSnpxMA8vPzE8d7+PBh8vDwEB5JSUlkMBho7969Yp+VK1fSzp077XocO3aMVCoVZWRkUFlZGS1dulQs9SJ5DBw4kAwGA/n4+FBZWRllZ2eL9cYkj7i4OIqJiREeGzdupK1bt1JZWRnFx8eL9bXi4uKEx4IFC0iv19OSJUvIzc2Nxo4dS2azmcxms/DYtGkT+fv7yzxGjhxJJpOJdDodJSYmUmBgII0bN054tF6SQ6/Xk0ajEeU+bo9PPvmEPvzwQ8rJySEXFxcyGo3UvXt3mjJlyhPxmDRpEoWFhVH37t1px44dZDabKTo6WtauWntUVVWR0WikhIQEmjx5Mnl4eJBWq6XY2FjhsX//flIqlTRz5kxyc3Ojvn37kkqlohdffFF4rFixgsLCwoRHWVkZBQYGUs+ePUmv19OUKVPI09NTLBOTkZFBubm5bZaycHBwoOnTpz8Rj3/84x+Um5tLGzduJIVCQT179qTc3FyKi4t7ruLx1ltvkVqtpmXLlpG7uzu9/PLLVFRUJNYoe17isXjxYtq+fTvl5OSQm5sbDRgwgJRKJVkslufKo/V1t0ePHmS1WmXX3R/KY+zYsZSYmEgajYZGjRolPMrLy8nLy4sSEhJkS71ER0eTUqkkPz8/6tKlC23bto3+/ve/0+bNm8XjYamf7969m9LS0igsLIyqqqpozZo19PHHH1NgYCCFhYXR0qVLSafTkU6ns+uxb98+ce4mTZpEmzZtonHjxpHRaCSTyUQvvfSSGAvHjh1Ls2fPpkmTJolzXFtbK+Jx9uxZ2r59u1iiLCcnh1QqFaWnp5Ner6dp06bR0aNHxZ3x9PR0kScsX76c/P39ZXlCVFQU9e/fn06ePElHjx6lwMBAsdSLSqWi5cuXU+fOncX1b/Xq1aLuHTt20OHDh+nixYu0d+9eMpvN9NJLL8lygF/+8peUkJAg3j/IpTUjRoyg+Pj4dnOLrKwsGjNmjHgvLfUSGRlJZ86coUOHDpGnp2e7S7384he/oLKyMtqwYcPzu9QL0HYhRACy9XCkxZHd3NxIp9NRXFwcVVVVic+XLl3abhlms1nss27dOurVqxfpdDpydnam/v370/vvvy9uS9tDWhzZaDSSVqulsWPHUnl5ufhcmifxfT0cHBwe+L0Hvbp27fpAjx07dlBQUBBpNBrq1auXbJFnycPHx4e8vLzEQtHSnDZ7r+TkZPrRj35EOp2ODAYDeXl5iYHzv/UwGAzk5uZGWq2WDAYDTZs2TSzGK3n4+/vLFuN1cnL6f+MhzU1SqVRkMployZIl9Ic//OGh7ar1IrbSIPM4PJydnUmtVlPnzp1pwYIFYvFXycPX11csYuvq6ioe7z9rHhwP9niePQDQb37zG7GgcJcuXWjYsGGkUqna3df28bW916uvvkq9evUiR0dHUqlUYpHnn//853Y9NBoN+fn5iYQSuP943MfHh5YsWUINDQ0PHAuJqM1i1e+88w4R2V8Q2cnJiVasWEH37t17YJy/+eYb+slPfkJOTk7k7Ows+rntWKhWq8Uiz7Z1v/fee9StWzdSq9UiJrZLuBDdnws6atQo2TZ7LracO3eOANCnn37abm6xdOlSWY5CRHTlyhWKjo4mR0dH8vDwEG3LlsOHD1O/fv3Ewtvfd5FnBRERGIZhGIZhmA7BMzPnj2EYhmEYhnnycPLHMAzDMAzTgeDkj2EYhmEYpgPByR/DMAzDMEwHgpM/hmEYhmGYDgQnfwzDMAzDMB0ITv4YhmEYhmE6EJz8MQzDMAzDdCA4+WMYhmEYhulAcPLHMEyHYerUqVAoFFAoFFCr1TAajRg/fjw2b96MlpaWRy5ny5YtcHV1fXIHyjAM8wTh5I9hmA5FVFQUqqqqcOXKFRw8eBCjR4/GG2+8gZiYGNy7d+9pHx7DMMwTh5M/hmE6FFqtFt7e3ujatSsGDBiAtLQ07Nu3DwcPHsSWLVsAAGvWrEGfPn2g1+vRvXt3zJo1C3fu3AEAHDlyBNOmTcPt27fFXcRly5YBABoaGvDmm2+ia9eu0Ov1GDp0KI4cOfJ0RBmGYezAyR/DMB2eMWPGIDQ0FHv27AEAODg4YN26dSgtLcUf//hH5OfnY+HChQCA4cOH43e/+x2cnZ1RVVWFqqoqvPnmmwCAOXPm4MSJE9i+fTuKi4vxyiuvICoqChUVFU/NjWEYpjUKIqKnfRAMwzA/BFOnTkVtbS327t3b5rMpU6aguLgYX331VZvPdu3ahZkzZ+LWrVsA7s/5mz9/Pmpra8U+V69eRY8ePXD16lV06dJFbB83bhyGDBmClStXPnYfhmGY/wTV0z4AhmGYZwEigkKhAAD87W9/w6pVq3Du3DnU1dXh3r17+O6771BfXw+dTtfu90tKStDc3IygoCDZ9oaGBnTu3PmJHz/DMMyjwskfwzAMgLKyMvj5+eHKlSuIiYnB66+/jhUrVsDd3R1Hjx5FcnIyGhsb7SZ/d+7cgVKpRGFhIZRKpewzJyenH0KBYRjmkeDkj2GYDk9+fj5KSkqQmpqKwsJCtLS0IDMzEw4O96dF79ixQ7a/RqNBc3OzbFv//v3R3NyMmzdvYuTIkT/YsTMMw3xfOPljGKZD0dDQgOrqajQ3N+Prr7/GoUOHsGrVKsTExCAxMRFnz55FU1MTsrKy8MILL+DYsWP4/e9/LyvD19cXd+7cQV5eHkJDQ6HT6RAUFIRXX30ViYmJyMzMRP/+/fHPf/4TeXl56Nu3LyZMmPCUjBmGYeTwr30ZhulQHDp0CD4+PvD19UVUVBQOHz6MdevWYd++fVAqlQgNDcWaNWvw7rvvonfv3sjJycGqVatkZQwfPhwzZ85EfHw8PD098dvf/hYAkJ2djcTERCxYsADBwcGYOHEivvzyS5hMpqehyjAM0y78a1+GYRiGYZgOBN/5YxiGYRiG6UBw8scwDMMwDNOB4OSPYRiGYRimA8HJH8MwDMMwTAeCkz+GYRiGYZgOBCd/DMMwDMMwHQhO/hiGYRiGYToQnPwxDMMwDMN0IDj5YxiGYRiG6UBw8scwDMMwDNOB4OSPYRiGYRimA/E/HZnvQfFzeRQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[6], line 18\u001b[0m\n\u001b[1;32m     16\u001b[0m plt\u001b[39m.\u001b[39mylabel(\u001b[39m\"\u001b[39m\u001b[39mBTC Price\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m     17\u001b[0m plt\u001b[39m.\u001b[39mshow()  \n\u001b[0;32m---> 18\u001b[0m time\u001b[39m.\u001b[39;49msleep(\u001b[39m60\u001b[39;49m)\n\u001b[1;32m     19\u001b[0m clear_output(wait\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m)\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "while True:\n",
    "    data_BTC = requests.get(\n",
    "            'http://localhost:9000/exp',\n",
    "            {\n",
    "                'query': \"SELECT * from 'crypto'\",\n",
    "            })\n",
    "    data_BTC_csv = StringIO(data_BTC.text)\n",
    "    df = pd.read_csv(data_BTC_csv, sep=\",\", header=0)\n",
    "    date_array = np.array(df['Date'])\n",
    "    open_array = np.array(df['Open'])\n",
    "    pred_array = np.array(df['Predict'])\n",
    "    plt.plot(date_array, open_array, label='Actuation')\n",
    "    plt.plot(date_array, pred_array, label='Predict')\n",
    "    plt.legend(loc='best')\n",
    "    plt.xlabel(\"Date\")\n",
    "    plt.ylabel(\"BTC Price\")\n",
    "    plt.show()  \n",
    "    time.sleep(60)\n",
    "    clear_output(wait=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>High</th>\n",
       "      <th>Predict</th>\n",
       "      <th>Volume BTC</th>\n",
       "      <th>Low</th>\n",
       "      <th>Vwap</th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24212.89</td>\n",
       "      <td>24117.412</td>\n",
       "      <td>29038.719</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24062.484</td>\n",
       "      <td>2023-02-22 08:58:00</td>\n",
       "      <td>24161.72</td>\n",
       "      <td>2023-02-22T03:09:01.238493Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24206.60</td>\n",
       "      <td>24118.336</td>\n",
       "      <td>28460.970</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24059.750</td>\n",
       "      <td>2023-02-22 08:59:00</td>\n",
       "      <td>24176.88</td>\n",
       "      <td>2023-02-22T03:09:01.239219Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24192.32</td>\n",
       "      <td>24101.678</td>\n",
       "      <td>28268.303</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24058.662</td>\n",
       "      <td>2023-02-22 09:00:00</td>\n",
       "      <td>24175.72</td>\n",
       "      <td>2023-02-22T03:09:01.239237Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24192.32</td>\n",
       "      <td>24047.805</td>\n",
       "      <td>27481.951</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24057.900</td>\n",
       "      <td>2023-02-22 09:01:00</td>\n",
       "      <td>24079.16</td>\n",
       "      <td>2023-02-22T03:09:01.239261Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24192.32</td>\n",
       "      <td>24021.574</td>\n",
       "      <td>26579.252</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24059.137</td>\n",
       "      <td>2023-02-22 09:02:00</td>\n",
       "      <td>24033.28</td>\n",
       "      <td>2023-02-22T03:09:01.239274Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>24192.32</td>\n",
       "      <td>24013.700</td>\n",
       "      <td>25087.746</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24061.857</td>\n",
       "      <td>2023-02-22 09:03:00</td>\n",
       "      <td>24021.74</td>\n",
       "      <td>2023-02-22T03:09:01.239286Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>24192.32</td>\n",
       "      <td>24035.457</td>\n",
       "      <td>23979.906</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24065.566</td>\n",
       "      <td>2023-02-22 09:04:00</td>\n",
       "      <td>24063.22</td>\n",
       "      <td>2023-02-22T03:09:01.239308Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>24239.81</td>\n",
       "      <td>24079.848</td>\n",
       "      <td>23809.062</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24069.902</td>\n",
       "      <td>2023-02-22 09:05:00</td>\n",
       "      <td>24050.58</td>\n",
       "      <td>2023-02-22T03:09:01.239322Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>24240.00</td>\n",
       "      <td>24061.576</td>\n",
       "      <td>23412.014</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24072.990</td>\n",
       "      <td>2023-02-22 09:06:00</td>\n",
       "      <td>24018.32</td>\n",
       "      <td>2023-02-22T03:09:01.239361Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>24242.86</td>\n",
       "      <td>24053.072</td>\n",
       "      <td>22472.246</td>\n",
       "      <td>23855.55</td>\n",
       "      <td>24077.998</td>\n",
       "      <td>2023-02-22 09:07:00</td>\n",
       "      <td>23999.39</td>\n",
       "      <td>2023-02-22T03:09:01.239374Z</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       High    Predict  Volume BTC       Low       Vwap                 Date  \\\n",
       "0  24212.89  24117.412   29038.719  23855.55  24062.484  2023-02-22 08:58:00   \n",
       "1  24206.60  24118.336   28460.970  23855.55  24059.750  2023-02-22 08:59:00   \n",
       "2  24192.32  24101.678   28268.303  23855.55  24058.662  2023-02-22 09:00:00   \n",
       "3  24192.32  24047.805   27481.951  23855.55  24057.900  2023-02-22 09:01:00   \n",
       "4  24192.32  24021.574   26579.252  23855.55  24059.137  2023-02-22 09:02:00   \n",
       "5  24192.32  24013.700   25087.746  23855.55  24061.857  2023-02-22 09:03:00   \n",
       "6  24192.32  24035.457   23979.906  23855.55  24065.566  2023-02-22 09:04:00   \n",
       "7  24239.81  24079.848   23809.062  23855.55  24069.902  2023-02-22 09:05:00   \n",
       "8  24240.00  24061.576   23412.014  23855.55  24072.990  2023-02-22 09:06:00   \n",
       "9  24242.86  24053.072   22472.246  23855.55  24077.998  2023-02-22 09:07:00   \n",
       "\n",
       "       Open                    timestamp  \n",
       "0  24161.72  2023-02-22T03:09:01.238493Z  \n",
       "1  24176.88  2023-02-22T03:09:01.239219Z  \n",
       "2  24175.72  2023-02-22T03:09:01.239237Z  \n",
       "3  24079.16  2023-02-22T03:09:01.239261Z  \n",
       "4  24033.28  2023-02-22T03:09:01.239274Z  \n",
       "5  24021.74  2023-02-22T03:09:01.239286Z  \n",
       "6  24063.22  2023-02-22T03:09:01.239308Z  \n",
       "7  24050.58  2023-02-22T03:09:01.239322Z  \n",
       "8  24018.32  2023-02-22T03:09:01.239361Z  \n",
       "9  23999.39  2023-02-22T03:09:01.239374Z  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_BTC = requests.get(\n",
    "            'http://localhost:9000/exp',\n",
    "            {\n",
    "                'query': \"SELECT * from 'crypto'\",\n",
    "            })\n",
    "data_BTC_csv = StringIO(data_BTC.text)\n",
    "df_BTC = pd.read_csv(data_BTC_csv, sep=\",\", header=0)\n",
    "df_BTC"
   ]
  }
 ],
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