advent2020_leaderboard_full.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "requesting day 2\n",
      "requesting day 3\n",
      "requesting day 4\n",
      "requesting day 5\n",
      "requesting day 6\n",
      "requesting day 7\n",
      "requesting day 8\n",
      "requesting day 9\n",
      "requesting day 10\n",
      "requesting day 11\n",
      "requesting day 12\n",
      "requesting day 13\n",
      "requesting day 14\n",
      "requesting day 15\n",
      "requesting day 16\n",
      "requesting day 17\n",
      "requesting day 18\n",
      "requesting day 19\n",
      "requesting day 20\n",
      "requesting day 21\n",
      "requesting day 22\n",
      "requesting day 23\n",
      "requesting day 24\n",
      "requesting day 25\n"
     ]
    }
   ],
   "source": [
    "all_names = []\n",
    "for day in range(2, 26):\n",
    "    print(\"requesting day \" + str(day))\n",
    "    r = requests.get('https://adventofcode.com/2020/leaderboard/day/' + str(day))\n",
    "    soup = BeautifulSoup(r.text, 'html.parser')\n",
    "    entries = soup.find_all('div', attrs={\"class\": 'leaderboard-entry'})\n",
    "    names = [' '.join(e.text.split('Dec')[1].split(' ')[4:]) for e in entries]\n",
    "    all_names += names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "cache = {}\n",
    "for idx in range(len(all_names)):\n",
    "    if all_names[idx] not in cache:\n",
    "        cache[all_names[idx]] = 0\n",
    "    cache[all_names[idx]] += (100 - (idx % 100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = sorted(cache.items(), key=lambda x: x[1], reverse=True)\n",
    "nums = np.array([i[1] for i in s])\n",
    "# nums = nums[nums >= 200]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot(nums, binwidth=50):\n",
    "    fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(20, 20))\n",
    "    ax1.plot(nums)\n",
    "    ax1.grid()\n",
    "    ax1.set_xlabel(\"ranking\")\n",
    "    ax1.set_ylabel(\"points\")\n",
    "    ax1.set_title(\"Day \" + str(int(len(all_names)/200) + 1))\n",
    "\n",
    "\n",
    "    plt.hist(nums, bins=np.arange(min(nums), max(nums) + binwidth, binwidth))\n",
    "    plt.grid()\n",
    "    plt.xlabel(\"points\")\n",
    "    plt.ylabel(\"number of people\")\n",
    "    plt.title(\"Day \" + str(int(len(all_names)/200) + 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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pg82yggkAAABoAwJTB9t3iZwVTAAAAECzBKYONnu0P+u27EittelRAAAAgClMYOpgx08fyuqNO/KTf3xdtu3c0/Q4AAAAwBQlMHWwX1p6Wn7xBafktlUbsmLN5qbHAQAAAKYogamDjQz05aXnHZ8kWbPZZt8AAABAMwSmDjd3bDBJsmbTjoYnAQAAAKYqganDzR0bSJKs2SwwAQAAAM2YsMBUShkqpdxYSvl2KeU7pZT/0Tp+Sinl66WUu0spf11KGWgdH2w9Xt56/uQDftZvtI7fVUp56UTN3InGBvsy2NcjMAEAAACNmcgVTDuSvKjW+swkz0ryslLKRUl+L8n7aq1nJFmf5M2t1785yfpa6+lJ3td6XUop5yR5TZJzk7wsyZ+WUnoncO6OUkrJ3LFBezABAAAAjZmwwFT32X9rs/7WV03yoiR/0zp+ZZLLWt+/qvU4recvKaWU1vFP1lp31FrvTbI8yXMnau5ONHfaoBVMAAAAQGMmdA+mUkpvKeVbSR5Nck2Se5I8Xmvd3XrJyiQLW98vTPJgkrSe35BkzoHHD/Iekhw3NpDHbPINAAAANKRvIn94rXVPkmeVUmYm+UySsw/2staf5RDPHer49ymlXJHkiiSZP39+li1b9lRGbjubN29+0s+yc9OOPLRuT9d8Zugk4zlHgWY5T6G9OUehvTlHGa8JDUz71VofL6UsS3JRkpmllL7WKqUTkzzUetnKJCclWVlK6UsyI8m6A47vd+B7DvwdH0jygSRZsmRJXbp06cR8mEm2bNmyPNlnuWnHXfnaquW5+IU/mt6eg/U4YKKM5xwFmuU8hfbmHIX25hxlvCbyLnLHtVYupZQynOTFSe5Mcm2SV7dednmSq1vff7b1OK3nv1xrra3jr2ndZe6UJGckuXGi5u5Ec8cGsrcm67fa6BsAAACYfBO5gmlBkitbd3zrSfKpWuvnSil3JPlkKeU9SW5J8qHW6z+U5COllOXZt3LpNUlSa/1OKeVTSe5IsjvJr7QuvaNl7rTBJMmazTsyd2yw4WkAAACAqWbCAlOt9dYk5x/k+Ioc5C5wtdbtSX7mED/rd5P87rGesVvsj0prNu1Mjm94GAAAAGDKmdC7yDE5Zo0MJEk2bNvV8CQAAADAVCQwdYFpQ/sWom3aLjABAAAAk09g6gJjTwSm3Q1PAgAAAExFAlMXGBvoSylWMAEAAADNEJi6QE9PydhAXzbtsIIJAAAAmHwCU5eYNtTnEjkAAACgEQJTlxgb6nOJHAAAANAIgalLTBvqt4IJAAAAaITA1CWmDfVlsz2YAAAAgAYITF1ibNAeTAAAAEAzBKYuse8SOXswAQAAAJNPYOoS04f6stEKJgAAAKABAlOXmDbUl52792bH7j1NjwIAAABMMQJTlxgb7EuSbLaKCQAAAJhkAlOXmDbUnyQ2+gYAAAAmncDUJaYN7VvBJDABAAAAk01g6hJPrGDa4U5yAAAAwOQSmLqEFUwAAABAUwSmLiEwAQAAAE0RmLrE/kvkNm93iRwAAAAwuQSmLjE62Jsk2bzDCiYAAABgcglMXWKgtyc9Jdm+a2/TowAAAABTjMDUJUopGe7vzbZde5oeBQAAAJhiBKYuMtTfm+0CEwAAADDJBKYuMmQFEwAAANAAgamLDA9YwQQAAABMPoGpiwz199jkGwAAAJh0AlMXGe7vzbadVjABAAAAk0tg6iL2YAIAAACaIDB1kWF3kQMAAAAaIDB1kSGBCQAAAGiAwNRFhl0iBwAAADRAYOoiwwM2+QYAAAAmn8DURYb6e7N9996mxwAAAACmGIGpiwz192Tn7r3Zs7c2PQoAAAAwhQhMXWS4vzdJbPQNAAAATCqBqYsMD+wLTDb6BgAAACaTwNRFhvqsYAIAAAAmn8DURYYGBCYAAABg8glMXWT/HkzbdrqTHAAAADB5BKYu8sQm37utYAIAAAAmj8DURYb69/11btspMAEAAACTR2DqIkP97iIHAAAATD6BqYsM2+QbAAAAaIDA1EX2r2ASmAAAAIDJJDB1kX+7i5zABAAAAEwegamLPBGYdu1teBIAAABgKhGYushg376/TpfIAQAAAJNJYOoiPT0lg309AhMAAAAwqQSmLjM80JttAhMAAAAwiQSmLjPc35vN23c3PQYAAAAwhQhMXebcE6bnhhVrs3dvbXoUAAAAYIoQmLrMTzx9QR7asD3fXvl406MAAAAAU4TA1GUuOXt++ntLPn/7I02PAgAAAEwRAlOXmTHcnwtPmZPrlq9pehQAAABgihCYutBJs0eyeuP2pscAAAAApgiBqQvNmzaYNZt3ZteevU2PAgAAAEwBAlMXmj99KEmyZvOOhicBAAAApgKBqQvNmzaYJFm9UWACAAAAJp7A1IX2r2CyDxMAAAAwGQSmLjRv+r4VTI9usoIJAAAAmHgCUxeaMzqQnpI8agUTAAAAMAkEpi7U19uTOWODedQeTAAAAMAkEJi61Pzpg1m9yQomAAAAYOIJTF1q3rQhK5gAAACASSEwdan50wdz75oted8138uO3XuaHgcAAADoYgJTl3rx2fOzYOZQ/vBLd+c9n7uz6XEAAACALiYwdalLzp6fL//XpXnLxafkIzfcn2V3Pdr0SAAAAECXEpi63H972VlZOHM4f/zl5U2PAgAAAHQpganL9ff25C0Xn5Kb7l+ff71nTdPjAAAAAF1IYJoCfu45i7Jw5nB+7a+/ndUbtzc9DgAAANBlBKYpYHigNx+8fEk2bt+Vt1x1U7btdFc5AAAA4NgRmKaIsxdMzx++5vzctmpD/vtnv9P0OAAAAEAXEZimkB8/Z35e85xFufrbq7J9l1VMAAAAwLEhME0xLzlnfrbv2psb713X9CgAAABAlxCYppiLTp2Tgb6eLLvrsaZHAQAAALqEwDTFDA/05qJT52TZ9x5tehQAAACgSwhMU9CSxbOy4rEt9mECAAAAjgmBaQpaNHskSbJy/daGJwEAAAC6wREHplJKTyll+kQMw+Q4qRWYHlgnMAEAAABHb1yBqZTy8VLK9FLKaJI7ktxVSvn1iR2NiXLS7OEkyYPrtjU8CQAAANANxruC6Zxa68YklyX5xySLkrxhwqZiQh03Npih/h4rmAAAAIBjYryBqb+U0p99genqWuuuCZyJCVZKyaLZI3lQYAIAAACOgfEGpvcnuS/JaJKvlFIWJ9kwUUMx8U6aNWIFEwAAAHBMjDcw/X2tdWGt9SdqrTXJA0n+/QTOxQQ7afZIVq7fln1/nQAAAABP3XgD098e+KAVmT557Mdhspw0eySbd+zOui07mx4FAAAA6HB9h3uylHJWknOTzCil/PQBT01PMjSRgzGxTpk7kiS5b+2WzBkbbHgaAAAAoJMdNjAlOTPJK5LMTPLKA45vSvKWiRqKiXf6cdOSJMsf3ZwLFs9ueBoAAACgkx02MNVar05ydSnlebXW6ydpJibBwlnDGejryT2PbWl6FAAAAKDDPdkKpv2Wl1LemeTkA99Ta7XRd4fq7Sk5de5olj+6uelRAAAAgA433sB0dZKvJvlikj0TNw6T6bR5Y7l91YamxwAAAAA63HgD00it9e0TOgmT7rTjxvL52x7O9l17MtTf2/Q4AAAAQIfqGefrPldK+YkJnYRJd9pxo9lb991JDgAAAOCpGm9g+tXsi0zbSikbSymbSikbJ3IwJt5Zx09Pkty20mVyAAAAwFM3rsBUa51Wa+2ptQ7XWqe3Hk+f6OGYWGfMG8vcsYF8bfmapkcBAAAAOthh92AqpZxVa/1uKeXZB3u+1nrzxIzFZOjpKXnB6XPz1bvXZO/emp6e0vRIAAAAQAd6sk2+fy3JFUn+10Geq0ledMwnYlJdfMZx+btvPZQ7H9mYc0+Y0fQ4AAAAQAc6bGCqtV7R+vPHJmccJtvFZ8xNKcknbnwg77ns6U2PAwAAAHSgce3BVErpL6W8rZTyN62v/1hK6Z/o4Zh486YP5U0/cko+esMDufa7jzY9DgAAANCBxnsXuT9LckGSP219XdA6dkillJNKKdeWUu4spXynlPKrreOzSynXlFLubv05q3W8lFL+bylleSnl1gP3fSqlXN56/d2llMufygfl0N5+6ZmZN20wn75lVdOjAAAAAB3oyfZg2u85tdZnHvD4y6WUbz/Je3Yn+a+11ptLKdOSfLOUck2SX0jypVrre0sp70jyjiRvT3JpkjNaXxdmX8C6sJQyO8nvJFmSffs+fbOU8tla6/pxzs6TGOzrzaLZI1mzaUfTowAAAAAdaLwrmPaUUk7b/6CUcmqSPYd7Q6314f13mau1bkpyZ5KFSV6V5MrWy65Mclnr+1cluaruc0OSmaWUBUlemuSaWuu6VlS6JsnLxjk34zRnbCBrNgtMAAAAwJEb7wqmX09ybSllRevxyUneNN5fUko5Ocn5Sb6eZH6t9eFkX4QqpcxrvWxhkgcPeNvK1rFDHf/B33FF9t3xLvPnz8+yZcvGO15b27x586R8lp0bd+Th9bu75n83mCyTdY4CT53zFNqbcxTam3OU8RpvYLouyfuTXNJ6/P4k14/njaWUsSR/m+Q/11o3llIO+dKDHKuHOf79B2r9QJIPJMmSJUvq0qVLxzNe21u2bFkm47Pcsut7ufbBu/OCi1+Yvt7xLmwDJuscBZ465ym0N+cotDfnKOM13pJwVZJTkry79XVKko882Ztad5r72yQfq7V+unV4devSt7T+3H/rspVJTjrg7ScmeegwxzmG5k4bTJKs27Kz4UkAAACATjPewHRmrfUXa63Xtr6uSPK0w72h7Fuq9KEkd9Za//cBT302yf47wV2e5OoDjr+xdTe5i5JsaF1K94UkLymlzGrdce4lrWMcQ8eNDSRJHrMPEwAAAHCExnuJ3C2llItam2+nlHJh9l02dzjPT/KGJLeVUr7VOvbOJO9N8qlSypuTPJDkZ1rP/WOSn0iyPMnWtPZ4qrWuK6W8O8k3Wq97V6113TjnZpzmju1bwbRmsxVMAAAAwJEZb2C6MPtWFz3QerwoyZ2llNuS1FrrM37wDbXWr+Xg+ycl/7aX04Gvr0l+5WAvrrV+OMmHxzkrT8GcVmBaawUTAAAAcITGG5heNqFT0Li5rUvk1ghMAAAAwBEaV2Cqtd4/0YPQrLHBvgz29bhEDgAAADhi7kdPkqSUkrljg1mzyQomAAAA4MgITDxh7rRBd5EDAAAAjpjAxBPOPn5arr9nbb54x+qmRwEAAAA6iMDEE37zFefk3IUz8taP35zrlq9pehwAAACgQwhMPGFssC9Xvuk5OWXOaN5y1U357iMbmx4JAAAA6AACE99n5shAPvLm52Z0sC+/9JFvZtP2XU2PBAAAALQ5gYkfMm/6UP74tefnvrVb8/5/WdH0OAAAAECbE5g4qAtPnZOXP2NBPnzdvVnrznIAAADAYQhMHNJ/efHTsnXnnnzmllVNjwIAAAC0MYGJQzp93ljmjA7knse2ND0KAAAA0MYEJg5r8ZyR3L9WYAIAAAAOTWDisBbPGc39a7c2PQYAAADQxgQmDmvxnJE8tGFbduze0/QoAAAAQJsSmDisk+eMptbkwXXbmh4FAAAAaFMCE4e1aM5IktiHCQAAADgkgYnDOnnOaJLkPvswAQAAAIcgMHFYs0b6M22ozwomAAAA4JAEJg6rlJLjpw/l0Y07mh4FAAAAaFMCE09qzthA1m4RmAAAAICDE5h4UnNGB7N2y86mxwAAAADalMDEk5ozNpC1mwUmAAAA4OAEJp7UnNHBbNi2K7v27G16FAAAAKANCUw8qdljA0mS9S6TAwAAAA5CYOJJzR3dF5jWuEwOAAAAOAiBiSc1uxWY1lnBBAAAAByEwMSTmjM2mCRZu2VHw5MAAAAA7Uhg4knNHXOJHAAAAHBoAhNPavpQf3p7StZZwQQAAAAchMDEk+rpKZk9OpC1VjABAAAAByEwMS5zRgey1ibfAAAAwEEITIzLnLGBPLrJJXIAAADADxOYGJcz5k3L3as3Zc/e2vQoAAAAQJsRmBiX8xbOyNade3Lvmi1NjwIAAAC0GYGJcTlv4fQkye2rNjQ8CQAAANBuBCbG5fTjxjLU3yMwAQAAAD9EYGJc+np7comR0fcAACAASURBVPaC6blNYAIAAAB+gMDEuJ1/0qzceN+6/MJf3pgdu/c0PQ4AAADQJvqaHoDO8V9+/Ixs2bE7f33Tg1nx2JacvWB60yMBAAAAbcAKJsZt2lB/XnvhoiTJQ49va3gaAAAAoF0ITByRE2YOJRGYAAAAgH8jMHFE5o4OZqC3JysFJgAAAKBFYOKI9PSULJg5lIce3970KAAAAECbEJg4YifMGHaJHAAAAPAEgYkjtnDWcFatF5gAAACAfQQmjtgJM4ezetP27Nqzt+lRAAAAgDYgMHHEFs4cSq3JIxvswwQAAAAITDwFJ8wcTpL8+t98O5+/7eHUWhueCAAAAGiSwMQRu2DxrPzckpOy6vFt+eWP3Zz/+PFbXC4HAAAAU1hf0wPQeUYG+vJ7r35Gdu/Zm/d/ZUX+5xfuypyxgbzrVec1PRoAAADQACuYeMr6envyKz92ei497/h86c5Hmx4HAAAAaIjAxFE7Z8H0rHp8W7bu3N30KAAAAEADBCaO2mnzxpIkKx7b0vAkAAAAQBMEJo7aacftC0z3PLa54UkAAACAJghMHLXFc0bSU5J7rGACAACAKUlg4qgN9ffmxFkjVjABAADAFCUwcUycdtyoPZgAAABgihKYOCbOWjA9d6/elAfXbW16FAAAAGCSCUwcE2983uL09pT872u+1/QoAAAAwCQTmDgmFswYzr9/wSn5u2+tygNrrWICAACAqURg4ph53YWLUmvyj7c/3PQoAAAAwCQSmDhmTpw1kmeeOCOfv01gAgAAgKlEYOKYuvTpC/LtlRvyxTtWp9ba9DgAAADAJBCYOKZ+6vyFWThzOL941U35u2+tanocAAAAYBIITBxT86cP5dr/Z2lmjw7k+nvWNj0OAAAAMAkEJo65gb6enHX8tNz1yKamRwEAAAAmgcDEhDjr+Om5a/Wm7NlrHyYAAADodgITE+KsBdOyfdfePLBua9OjAAAAABNMYGJCnHX8tCTJdx/e2PAkAAAAwEQTmJgQZ8yblp6SXL9ibWp1mRwAAAB0M4GJCTE80JulZ87LVdffn5//i6/nkQ3bmx4JAAAAmCACExPmA2+4IO+57Lx8e+Xj+dn3X28lEwAAAHQpgYkJ09fbk9dftDi/+fJz8sC6rVmxZkvTIwEAAAATQGBiwj33lNlJkpvuW9fwJAAAAMBEEJiYcKcdN5pZI/256b71TY8CAAAATACBiQlXSskFi2flm/cLTAAAANCNBCYmxXNOnp0Va7bkd66+Pdt37Wl6HAAAAOAY6mt6AKaG1120OPc8tjlXXn9/Tpg5nP/wo6c1PRIAAABwjFjBxKQYG+zL77/6mXn+6XPyl9fdl5279zY9EgAAAHCMCExMqrdcfGoe2bg97/rcd7Jtp0vlAAAAoBsITEyqH33acXnDRYvz0RseyFs/9s3UWpseCQAAADhKAhOTqpSSd192Xn77Fefk2rsey5/9yz02/QYAAIAOJzDRiF/4kZPzwqcdl9//p7vy6j//VyuZAAAAoIMJTDSip6fkL3/hOfnlpafl9lUbs2bzzqZHAgAAAJ4igYnG9PaUvOD0uUmSux7Z1PA0AAAAwFMlMNGoM4+fliT57iMbG54EAAAAeKoEJho1d2wwc8cGrGACAACADiYw0bgzj5+Wu1YLTAAAANCpBCYad+b86fne6k3Zs9ed5AAAAKATCUw07tmLZ2b7rr35zb+7PXtFJgAAAOg4AhONe/nTF+SKF56aT9z4QK67Z03T4wAAAABHSGCicaWUvOXiU5Mk9zy6ueFpAAAAgCMlMNEW5o4NZGSgN/ev29r0KAAAAMAREphoC6WULJo9kgcFJgAAAOg4AhNtY9Hskdy/VmACAACATiMw0TYWzxnJA+u2upMcAAAAdBiBibaxaM5oduzem0c37Wh6FAAAAOAITFhgKqV8uJTyaCnl9gOOzS6lXFNKubv156zW8VJK+b+llOWllFtLKc8+4D2Xt15/dynl8omal+Ytnj2SJHnAPkwAAADQUSZyBdNfJXnZDxx7R5Iv1VrPSPKl1uMkuTTJGa2vK5L8WbIvSCX5nSQXJnlukt/ZH6XoPotagenK6+/Lx75+f+54aGOzAwEAAADjMmGBqdb6lSTrfuDwq5Jc2fr+yiSXHXD8qrrPDUlmllIWJHlpkmtqretqreuTXJMfjlZ0iZNmj+TFZ8/LF25/JP/vZ27Pf/joTanVfkwAAADQ7vom+ffNr7U+nCS11odLKfNaxxcmefCA161sHTvU8R9SSrki+1Y/Zf78+Vm2bNmxnbwhmzdv7prPMh6vX5z8zMLhfHXV7nz0zm358NVfzmkze5seCw5pqp2j0Imcp9DenKPQ3pyjjNdkB6ZDKQc5Vg9z/IcP1vqBJB9IkiVLltSlS5ces+GatGzZsnTLZzkSF23blU+954tZ1bsgb156TtPjwCFN1XMUOonzFNqbcxTam3OU8Zrsu8itbl36ltafj7aOr0xy0gGvOzHJQ4c5TpebMdyfpWcel8/d+lD27HWZHAAAALSzyQ5Mn02y/05wlye5+oDjb2zdTe6iJBtal9J9IclLSimzWpt7v6R1jCnglc88IY9u2pEb7/3BrbwAAACAdjJhgamU8okk1yc5s5SyspTy5iTvTfLjpZS7k/x463GS/GOSFUmWJ/mLJG9NklrruiTvTvKN1te7WseYAi45e15GBnrz97datAYAAADtbML2YKq1vvYQT11ykNfWJL9yiJ/z4SQfPoaj0SFGBvry4rPn5/O3PZzffsU5Geq32TcAAAC0o8m+RA6OyGufuyjrt+7K+774vaZHAQAAAA6hXe4iBwf1vNPm5LXPPSkf+MqK7Ny9Nz91/sKcd8KM9PQc7AaDAAAAQBMEJtreb778nOzcXfOR6+/PX153X15/0aK857KnNz0WAAAA0OISOdre6GBf/tfPPjM3vPOSvOY5J+VjX38gt63c0PRYAAAAQIvARMeYOzaYd7787MweGcib/uob+d//fFdWPb6t6bEAAABgynOJHB1l+lB/Pnj5kvzhl+7OH127PH907fK84PS5OXvB9Fz+Iydn4czhpkcEAACAKUdgouOcv2hW/upNz83K9VvzqW88mH+47eHcsGJtvnTn6nzkzRdmwYyhlGITcAAAAJgsLpGjY504ayS/9pIz86X/ujQfffOFeWDd1vzIe7+cN/3VN1JrbXo8AAAAmDIEJrrChafOyWfe+vz8++efkmV3PZZP37yq6ZEAAABgynCJHF3jvIUzcs6C6fnWg+vzzs/clrtWb8o7XnZWenpcLgcAAAATyQomukpPT8mfvu6CvOTc4/OBr6zIV5evaXokAAAA6HoCE13n+BlD+YOfeUZmjfTnr7/xQNPjAAAAQNcTmOhKg329+elnn5hr7lidj3/9gWzavqvpkQAAAKBrCUx0rTdctDizRwfyzs/clp99/w25d82WpkcCAACAriQw0bVOnjuaG37jknz4F5bkvjVb8mN/sCyv+pPr8o+3PZy7V29KrbXpEQEAAKAruIscXa2UkhedNT/X/NoL84XvrM6Hvroib/3YzUmSM+aN5d2XnZeLTp3T8JQAAADQ2QQmpoQTZ43kzS84Ja+7cFHueHhj7nx4Yz741Xvz839xQ1501ry89Nzjc+nTF2Rs0CkBAAAAR8q/pplShvp78+xFs/LsRbNy2bMW5v9++e587tsP54t3PppP37wqn7jioqZHBAAAgI5jDyamrNHBvvzGpWfna2//sbztkjNy/Yq1eWDt1qbHAgAAgI4jMDHllVLys0tOTJL8/a0PNTwNAAAAdB6BCbJvj6bnnjw7n7lllbvLAQAAwBESmKDl1UtOzPJHN+f6FWubHgUAAAA6isAELT/5zBMye3QgH/zqvdm8Y3fT4wAAAEDHEJigZai/N6+/cFG+/N1H86z/8c/51DcebHokAAAA6Ah9TQ8A7eRtl5yRM4+fno/feH/e/ulbs27rzlxx8anp6SlNjwYAAABtywomOEBfb09e/owF+dDlz8ml5x2f937+u1nyu1/Mu/7+juzda/NvAAAAOBgrmOAghvp78yc//+z8/a0P5wu3P5IPX3dv7nx4Y55x0oz850ueluGB3qZHBAAAgLYhMMEhlFLyk888Ia98xoKc+y/T84kbH8gN967NrQ9uyBuftziL54zmzOOnpdflcwAAAExxAhM8iVJK3rr09Lx16en59M0r8/a/vTXXr1ibJHnzC07Jb73inIYnBAAAgGbZgwmOwE8/+8Tc/Fs/ns/9pxfk+afPyT/c+rC9mQAAAJjyBCY4QtOG+nPewhn5d88+MY9s3J7bVm1oeiQAAABolMAET9GLzpqX3p6Sf/rOI02PAgAAAI2yBxM8RTNHBvLCM+bm/f9yT+59bEtOnzeWt11yRgb6dFsAAACmFv8ShqPwh689P6+/aHFuW7Uhf3zt8rz7c3fYkwkAAIApxwomOArTh/rzrledl3e9KnnP5+7IB792b/725pUZHezLpecdn3f+xNkZ6u9tekwAAACYUAITHCPvuPSsnLtwem5buTGrN23PVdffn5vuW58/fd2zc/Lc0abHAwAAgAkjMMEx0tfbk586/8T81Pn7Hv/0+avza5/6dl75R1/L77/6Gbn06QuaHRAAAAAmiD2YYIJccvb8/MPbXpBT543llz92c37n6tvz7Qcfz8r1W7N+y057NQEAANA1rGCCCXTirJH8f//heXnv57+bD193b668/v4nnjvtuNH89ivPzY+cNif9vVovAAAAnUtgggk20NeT337lOXnT80/Odx7amI3bdmXDtl35q3+9L5d/+MZMG+zLhafOzilzR7NgxnBOmDmcE2YO5bTjxjI66BQFAACg/fnXK0ySk2aP5KTZI088fv1Fi7PsrkfzlbvX5MZ71+ard6/Jjt17n3h+1kh//uKNS7Lk5NlNjAsAAADjJjBBQ4YHenPp0xc8sfl3rTXrtuzMwxu258F1W/P7X7grP//Br+cPfuaZedm5x2egz2V0AAAAtCeBCdpEKSVzxgYzZ2ww5y2ckQtPnZO3XHVT3vaJW5IkQ/09mTbUn8G+nowN9uXsBdNz3sIZedWzTsjcscGGpwcAAGAqE5igTc0eHcjHfvHCXP2tVXls045s3L47G7ftys7de7Nu685cf8/afOaWVfm9f/puLj59bhbOGs45C6bn1RecmD6bhgMAADCJBCZoY0P9vfm55yw65PP3PLY5H7n+/nzle4/lG/ety1XX35+/+OqKvOPSs/Pis+ellDKJ0wIAADBVCUzQwU47biz//SfPTbJvD6dr7lid937+u3nLVTflgsWzcv5JM/PzFy7KqceNNTwpAAAA3Uxggi5RSslLzj0+P3bWvHzyxgdy5fX356ob7s/Hb3wgr77gxFx4ypxccva8DPX3Nj0qAAAAXUZggi7T39uTNzzv5LzheSfnkQ3b85t/d3v+9psrc9X19ydJTpw1nP/4Y6fnZ5eclJ4el9ABAABw9AQm6GLHzxjKBy9fkj17a/71njW5+f7H8y/fezTv+PRt+YfbHs6bnn9yLjp1TkYG/KcAAACAp86/KmEK6O0pufiM43LxGcflbZecno99/YG8+3N35Kt3r8ncscH89LMXZtHskVyweFaeNn9aeq1sAgAA4AgITDDFlFLy+osW51XPOiHfevDx/Mm1y/OX192bXXtqkmS4vzczhvszMtibk2aN5OwF03POCdNz6tzRDPT1ZMGMoUwb6m/4UwAAANBOBCaYoqYN9T+xqqnWmgfXbctN96/L7as2ZvOOXdm8Y3fuXbM1/3rPiifi035zxwbypuefkrcuPS2lWO0EAAAw1QlMQEopWTRnJIvmjOSnn/39z+3cvTf3PLY596/dmp179mbl+q258d51+Z9fuCvffvDxXPr04zN9qD8zRwZy/kkzbRwOAAAwBQlMwGEN9PXk7AXTc/aC6U8c+6UX1vzRl5fnw9fdm3++Y/UTx59x4oxc9qyFuWDxrJxzwvT09/Y0MTIAAACTTGACjlhPT8mvvviM/P/s3Xu8pXddH/rPd6+1L7PnnkwyhFwJhHCTawRUtAN4VwrniBaPF7S21Na2WO05xZ7ao7WcY1/VckpVPLSoSNHoi+ILFK9VphYVkBAkJBEJISEhCblMJnPfl7V+54+19p49ySRk5tkze+/M+/16rdd61vM861nfNckvK/nk+/s9P7jnytyx70iOzA9y890H8ra9n82/+Z2bkiRTvYm87Kpd+fevfW7O3zK9xhUDAABwJgmYgNM23e/laRduTZI895Id+TtfflnufuhoPnbbg/mrO/bnXR++PS//mb15+u6tee2LLsm3vegSXU0AAABPQAImYFVdtH1TXvW8TXnV856c17zg4vzKn9+WT33hobzpvTfkV/78tnzrcy/KdL+X6cmJXLxjU17xjAstFA4AALDBCZiAM+Y5F2/Pz3z789Jayx/e9MX85PtvzM/84d+ccM6rnvfkvOiyHUmSC7bO5MoLNucpuzZnZrK3FiUDAABwGgRMwBlXVfmGZz8pX/+s3VkctswtDjO3MMi7Pnx73vrHn8lv/9VdDzs/eeoFW/LdL7ks3/ici7J727QuJwAAgHVMwAScNVWVyV5lsjeRLdP9/PDXPj1/76uvzMLiMMPWcs+BY/nsfYdz632HsvfT9+Unfvum/MRv35RNk7085+JtuXLXllQlOzdP5fu/8opcuG1mrb8SAAAAETABa2zLdD8Z32Tu/C3TefaTtydJ3vjKq/LX9xzMn3/2gdz54JFcd/uD2fs39yZJHjg0n3f8z8/lil2zufz8zXndl1+aVz5z91p9BQAAgHOegAlYl6oqz7xoW5550bZHHLv9gcP5tY98Prfefzg33XUgP/DOj+VVz3ty9jz9gvTHHVIvunxndutwAgAAOCsETMCGc/n5m/Nj3/zMJMnc4iBv+aPP5N0fuf0Razl963Mvymuef3Gu2DWbS8+bzXTfwuEAAABngoAJ2NCm+7286ZuekR/+2qty1/6jSZKDxxbzBzfek1/6s8/ldz559/i8ibzgsh25ZOdsvubpF+QVz7hwND0PAACAzvzXFfCEMDPZy5UXbFl+/bxLd+QH9zw1n733UG5/4Eg+ccf+/NWd+/Mnf31v3nPdnZnqT+QVV1+Yr3/27jz/0h15yq7N7lQHAABwmgRMwBPWtpnJvOCynXnBZTvzmhdcnCQZDFuuu/3B/O4Nd+d3PnlXfv/Ge5Ik2zdN5prLd+affd3T85yLt69l2QAAABuOgAk4p/QmKi9+ynl58VPOy49/67PymXsP5hOf359P3LE///3me/Oqn/tQZvq9PH33llx5wZZUki0z/bz8GRfmq566K1P9ibX+CgAAAOuOgAk4Z/UmKs940rY840nb8roXX5aHjizkXR++LfsOL+STd+7Px27flyR54NB8fvUvbs/WmX5e9rRdedL2mbziGRfmq6+6YI2/AQAAwPogYAIY2z47mX/8iqsesf/YwiB//tn78wef+mI+dMv9+eCn782v/sXt+fFveWZmDg8zHLZMTFi/CQAAOHcJmAC+hJnJXl7xjN15xTN2J0kOzy3m+3/5L/MTv31TkuTNH/3DfN2zd+dJ22by7Cdvz56rL8hmd6gDAADOIf4LCOAUbZ7u59f+/kty890H8969H83B6Qvzhzfek8PzgwyGLdP9iXztM3fn+77qirzwsp3p6W4CAACe4ARMAKeh35vIl12yPQ9cMpk9e56XfPvzMhi2/OVt+/L7n7on7/34nfnADXdn5+xkvvKpu/KUXZuz5+oLcs0V56116QAAAKtOwASwSnoTlZdeeX5eeuX5+effcHX++OYv5k//5v58+NYH8vs33pOf++AtedK2mVyxazaX7pzNBVunc8HW6ezacuLztpl+qnQ9AQAAG4eACeAM2DLdz6uff3Fe/fyLkyRH5wd5z8fvzPW3P5jb9x3Jn37mvjxwaD6Lw/aI9071JsaB09RJA6iLd2zKcy/ZLoQCAADWDQETwFmwaaqX73np5fmel16+vG84bHno6ELuOzSX+w/O5b5Dc7lvxfP9h+bzhf3H8ok7Hsq+w3NZmUVddeGWXHbebJJk15bpXLxzU2anenn2k7fnpVeeJ3wCAADOKgETwBqZmKjs3DyVnZun8vTdWx/z3MGwZd/h+dx/aC433PlQ3vPxO/PFg8fSWnL9Hfuz7/D88rkve9qu7Ln6gtEUvC3T2TV+3r5pMhMWHAcAAM4AARPABtCbqOU1m5550bZ8x5dfunystZbBsOXgscW8/6/uys/+4afzoVvuf8Q1+hOVXVums2vrVC7YMp0vu2RHvv1Fl+TScScUAADA6RIwAWxwVZV+b9QN9fqvvCLf+xWX58DRxRVT7R75/MUDc9n7J5/JL/6Pz+a7X3J5dm2dyiU7Z3P5ebPZPN074fqTvYlcunNW9xMAAPCoBEwATzBVle2zk9k+O5mnXbjlUc/7wv6jefMHbsov/dnnvuQ1t2+azAsv25HzNk/n4h0zefFTzs8LL9+R2Sk/IwAAgIAJ4Jx18Y5N+YXvelEWB8PMD4a5Y9/RfH7fkRxbGJxw3uG5xXzijv25/vP78zdfPJS7Hzqa4Z/ckv5E5VlP3pYLt05nx+xUds5OZsfsVHbMTmbbzGRmJnuZ7k9kZrKXS8/blCdtm7H4OAAAPEEJmADOcf3eRPq9iVz9pK25+kknX2z8dS++bHn74LGFfOz2B/PRz+3LJ+/cny/sP5Yb7zqQB4/M59jC8FE/pyrZPNXPtpl+nrxjUy7ZuSkX79yUp124JRdt35TNU/1snu5lx+xUts300+9NrPp3BQAAzgwBEwCnZOvMZF5+9YV5+dUXPuLYsYVBHjwyn4PHFjO3MMz8YJAj84N87v7Duf/gXA7PD7L/yEK+sP9IPnb7g/ntT96dwbA9yuf0s33TZLbOTGZ2qpetM/3RIuVbppcXPN+1ZSoXbh3t275pUocUAACsEQETAKtmZrKXi7ZvykXbT9z/1VddcNLzFwbD3Hrf4TxwaBQ+HTy2kIeOjh77j4yeD80t5sj8Yu4/NJe/vvtg7j80l8WThFJTvYns2jKVXVunc8E4iLrygs150eU7R11Rm/rZNjOZ6f6EIAoAAFaZgAmANTM5npqXnHxq3skMhy0PHV0Y3RVv+c548yfcKe+eA8dywxceym98bO6k15juT2S6P5FNU71sm5nM1pl+tm2azKbxulHT/V7O2zKVL79iFE5tnupn26Z+dmyaysykgAoAAB5OwATAhjIxUdm5eSo7N0/lqt2PHUzde2C0PtSBYws5cGwxB44uZG5hkLnFYeYWhzk6P8jBuYUcOLqYfYfnc2zp2MIwDxyey9v2nrxTavvsZLbN9DPV72WqV5nsTWSytxRY9bN1HFpN93uZ7FcmJyYy2ats2zSZq5+0NVdduDVTfWtMAQDwxCFgAuAJ68JtM7lw28xpvffI/GJuuutADs4t5vDcYg4eW8z+IwvZf3Q+B46OQqn5wTALS4/FlnsPHstn7xsFWQePLZ50Kl+S9CcqT7twS3bMTi6HU5O9ytaZybzo8p05f/NUplfchW/zVC8zk71M9ibS740Cq36vlrcnJnRUAQCwtgRMAHASs1P9XHPFeZ2uMRy2LAyHWRi0LCyOuqJuvvtgbr77QD59z8EcGodXC4OWhcEw9x+ay3uuu/OUPmOikh2zU9kxO5nzZkedXTtnJ7Nz81S2zUxmZnna30S2TI+6q7Zt6mfzdP+EY5un+oIqAABOm4AJAM6QiYnK9EQv0/0k08nOzVN52oVb86rnPfmk57fWcvsDR3JobnE8jW+Qo/OjO/EdnR9kcdiyOA6sFgfDLA5bjs6P7ty3/8hC9h2ezx37juSTd87nwcMLmR8MH3etVcm2mcnsmJ3M9k2T2TYzman+qLNqsjeRqd5EZqd7yyHWeePHztnj2zOTvVX6kwMAYKMRMAHAOlFVuWLX5lW5Vmttea2pucVB5haGOTSe6ndgfHe++aVji8McOLaYh47MZ//4Dn4Hji3koaOjzqr5wTDzi8McGYdZ7eQz/0adUNP9zE71smN2Mjtnp7J90+h55+xktm063lE11Z/I1pl+tm8adV/t2DQ6PtmzNhUAwEYkYAKAJ6Cqysxkb9xVNLlq1x0MWw4cXcgDh+fz4JH57Ds8nwcPz2ffkfk8dGQhR+YHOTy3mP1HF/Lgkfnc+eDRPHhkPg8dXXjUYGqlqf5ENk/1sn3T5Lgzajrnb57K+VtGXVKj5xP3Tfd1TgEArDUBEwDwuPVW3MXvVAyGbTz1b9RNNbc4yMFji3no6EIeGndNPXR0IYfnF3NkbpD9Rxey7/Bc7nzwSD555/7sOzz/qIumz071MtWfSH+i0puo9Ccm0lvergznjuaXb/1otm2azKbJifR7E5mcqPTHi6b3JyqbJnvZNNXPzOTSdVZeb/Q8OV6ranaql1qxXNV5m6fypG0zqbKGFQBw7hIwAQBnXG+isn3TZE63m6q1lgNHF/PA4bnsOzyf+w+Nuqf2HZ7Lg0cWsjAYZjBsGQxbFlc8LywOc8c9R7L/yHxuf+Bwji0MszgcrV+1OF5cfen8LiZ7x8Otico44JpIbyLp1Sic2jrTz7aZyWyd6WfT+K6Ak/3R+lZT/YlsmuxldqqX2el+Nk/1MjvVz+bp3vK5vYlavpNgf7y9eaqf2ele+hMl4AIA1pSACQBY96oq22cns312MldecGrv3bt3b/bsedljnjO/OMzR+UGOLgwyaC2DwWhB9WFry2HU3PicI/OLWYqjWkvuPXgsd+0/Njp30DJsxwOu4bBl0FrmF4c5eGwhB48t5nP3j4OuwTDz45BrfnGYowuD0/vDyWiR9qXF2JcWZl9aD2u0WPujHxvtHz/6tdylNdUfd4LVODzrHe/smpnsZfN0L9P9RBSWBgAAIABJREFUUbg1Cr1G1+/3RmFZz10JAeCcImACAM55U+OFx7ev4npVp2o4bDmyMAqwjswNcnh+MUfnBzk8P1i+a+DiOPhaHLTMD0YLrx+ZW8z8YHR3wYXBMAuDYeYWhqNrLR8bBVgHji0dG117bnE4fk/3Lq6Vlu5KuH3T6M6E22Ym05uo5e6uqhO3e+PXE1WZmKhM9iqzU6NOr35vHHL1joddKx+jzq9+psfTG1cGXf2JyubpfrbOjB7W6wKAM0fABACwDkxMVLZM97Nlup9sPfufPxi28d0CF3NkfjCeOng82Frqyloch1VH5geZWxyMQ6/R/oVxAHZovL7W/vEaWweOLmTQRiHasLUMV2wPWktrWe78ai3jbrHFHF0YZBVzr+XpiEudXJO9iUxPjqYabpoa3eFwut/L9OSoC2vzVC/T426sk4VbvVoRhk31xlMlR1MjJ2o8ZXIiy+uCLd1pcao/kdnJ3imvZQYA65mACQCAUTfQVC+bpno5f62LWWFpmuFgHEgtTz0cB17HFgY5NLeY+cVRGLa0HtfSGltH5gc5cGwUch2aGyx3eS0MhplbHD2OzI1CtUNzi3ng0HyOLQ5ybNw9dmxhsBx+rWbYlSQ7ZydH0wl7lcmJieVpiEt3U5yd6i2HVBN1PNSaWPk8kUz3R2HYzFTvEUHYKOg63hm2aXK0ttfK9cJWdpRNVKVWbI/2T2R2/PfGVO/4AvjW/QJgJQETAADr1sREZSKVyXUwu62Nu68Wh8MMh8mgjRaSX5qOuPDwNbjG2yvDsCPzi+M1uRZz6/2HM784CsQWBsPlbrC5xUGOzg/y4JGFDIbD5c6u5aBtOXQbdX7NLYzCsLNtcrz2Vr9XowXqp/qZ6k2klqc7jp9XToEcB1hLgVlVcuihY/mte67PdH9ifHzl+Rm/Hu+bOP7+pXMme8cDsN7SuSebkjm+9tJ0zdF6ZL3MjBfSXwrjjq85Ngr+Zqd74+8lUAN4LAImAAB4HEbrRSW9iRVp13Syc+1KWjYcjtblGiyFT4PR8/Bhd1ZcWqh+YdCWA7NBG09dHHdprdweBVmjTrCldbsGS1MiV0yNHK0Xtri80P2wjQK5wYrt0XVH11wcDjM/GE3NfOBoy7479mduYZiWlecfr2VpGuXSvuOvV7+z7GSOd4QllePBV1VSyXKItfSc5XNGIdjSOUvdYbPjxfSXrrkyeEtOfL3yvSvPrfGxpYBtdqp3vLvtcYZzvYlaniI62avluk/4/BXf65H1HP+eU71eZsd3vlzqgDvedZeT7BPYwRPNhgmYquobk/zHJL0k/6W19tNrXBIAAKwLExOVmYl10OZ1GkZ3etxz2u9fmgq5cjrjynW9VgZWS1MtR2t9jdYSOzI/GAdwwxPuALk05fLIOJRbHLbkhIAraRltL11/6fUo9BoFasdDs9F5i8M2XsdsHMgNk0GGJ9TZMtpuDwvUkpwQ4LWWLAxHd7g8PDcYr2l2YhC3Xk31R8HYVG/i+JTMiSyHTxNVK7aT/nga7+xUP5O9GgV9Ew8L0ZZDv5U3DlgRAKaWP3dmsrciSBsdWxncnRAYLu878fysCN36veNh3coppiu/y8ruvaVjS11yK4O5ld13sJFsiICpqnpJfj7J1yW5M8lfVtX7W2s3rW1lAADAWprsTWT7pols37R2d4Fcr1p7ZPfXyu3FwTjsmltcntbZxmHYsLW0LAVVx4Oz4+ccD9WGLcs3CTg6P1junht11D1sLbXx9rGFYQ7PLS6vm7a04P/x7aUppicGc/cePPaITrmTdbid0AW3oqNuaVrreg7fVnr4VM+lsGqqP5GtM/1s2zSZrTP9k66rtjxF9SSdcr1aCux66fcmHtadd2KX2q2fm89nJm59zABuaRrqpqlRWDY5nvLae1jQdrLQrd8b3RF0aZ23SqUmTuy2G/1ZPCxIFMCtOxsiYEry4iS3tNZuTZKqujbJq5MImAAAAE5iOSSI/xBfqbWWucVhkhM7xFqSNlzZiXY8ZMu4s+yE88ch1bC15amiR+YXTwjLhg/bfnjQNz++a+aR+cEj3rfyjpsPn746tzjIwWOLOXBsIQePLWZxsPiIQO3hHX0rr3G8k27UwfclffrmM/WXo5OVQdrK7rSlNd5ODKVq+S6fD1/rbTTVdNSB1n+U9648f+KEbrPRjRmWutcezdc8/YI89YItZ/FP5+zbKAHTxUnuWPH6ziQvWXlCVb0hyRuSZPfu3dm7d+9ZK+5MOnTo0BPmu8ATkTEK659xCuubMcoTXeUU/sO7MloU5oxUsfI5WVlVWwrYlqZortg+dOhwZjdvPn5sKVjL6MThOH0btGR+kMwNxp1rK85f2l7uMltx/cVhMj9oOTZIhsPxdfPwaagn1jU8yevBsOXYYJD5weLyZy0fH44/f/F4HYMVHXiLw2RuXPvK9514nXbC91hZ/+BxZHQ/+NzpvPTJGyWCOT0b5dudLAY84S9ha+3tSd6eJNdcc03rMo97Pek6Jx04s4xRWP+MU1jfjFFY34zRL21+cZijC4O0x5h7uWmql+n+xlwr7/HaKAHTnUkuXfH6kiR3rVEtAAAAAElGi9ZP9SfWuow1t1H+BP4yyVVV9ZSqmkryuiTvX+OaAAAAAMgG6WBqrS1W1T9O8gcZzUj9pdbajWtcFgAAAADZIAFTkrTWfjfJ7651HQAAAACcaKNMkQMAAABgnRIwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQAAAIBOBEwAAAAAdCJgAgAAAKATARMAAAAAnQiYAAAAAOhEwAQAAABAJwImAAAAADqp1tpa17Dqquq+JLevdR2rZFeS+9e6COBRGaOw/hmnsL4Zo7C+GaOsdHlr7YKTHXhCBkxPJFX1sdbaNWtdB3Byxiisf8YprG/GKKxvxiiPlylyAAAAAHQiYAIAAACgEwHT+vf2tS4AeEzGKKx/ximsb8YorG/GKI+LNZgAAAAA6EQHEwAAAACdCJjWsar6xqr6dFXdUlVvWut64FxUVZdW1Qer6uaqurGq3jjef15V/VFVfWb8vHO8v6rqreNx+8mqeuHafgM4N1RVr6qur6rfGb9+SlV9ZDxGf6Oqpsb7p8evbxkfv2It64ZzQVXtqKr3VNVfj39Pv8LvKKwfVfXPxv+e+6mq+vWqmvE7yukQMK1TVdVL8vNJvinJs5J8Z1U9a22rgnPSYpIfba09M8lLk/zQeCy+Kckft9auSvLH49fJaMxeNX68Icnbzn7JcE56Y5KbV7z+d0neMh6jDyb5gfH+H0jyYGvtaUneMj4POLP+Y5Lfb609I8nzMhqrfkdhHaiqi5P80yTXtNaek6SX5HXxO8ppEDCtXy9Ocktr7dbW2nySa5O8eo1rgnNOa+3u1trHx9sHM/qX4oszGo/vHJ/2ziSvGW+/OsmvtpEPJ9lRVRed5bLhnFJVlyT5liT/Zfy6krwiyXvGpzx8jC6N3fckeeX4fOAMqKptSb4myTuSpLU231rbH7+jsJ70k2yqqn6S2SR3x+8op0HAtH5dnOSOFa/vHO8D1si4BfgFST6SZHdr7e5kFEIluXB8mrELZ9//m+T/SDIcvz4/yf7W2uL49cpxuDxGx8cfGp8PnBlXJrkvyS+Pp7H+l6raHL+jsC601r6Q5GeSfD6jYOmhJNfF7yinQcC0fp0sBXbLP1gjVbUlyX9L8sOttQOPdepJ9hm7cIZU1bcmube1dt3K3Sc5tT2OY8Dq6yd5YZK3tdZekORwjk+HOxljFM6i8fpnr07ylCRPTrI5o6mqD+d3lC9JwLR+3Znk0hWvL0ly1xrVAue0qprMKFx6d2vtvePdX1xq2R8/3zveb+zC2fVVSf52Vd2W0XTyV2TU0bRj3OqfnDgOl8fo+Pj2JPvOZsFwjrkzyZ2ttY+MX78no8DJ7yisD1+b5HOttftaawtJ3pvkK+N3lNMgYFq//jLJVePV+6cyWmjt/WtcE5xzxnPK35Hk5tbaf1hx6P1JXj/efn2S963Y/73ju+C8NMlDS1MAgNXXWvux1tolrbUrMvqt/JPW2ncl+WCS145Pe/gYXRq7rx2f7/+8whnSWrsnyR1VdfV41yuT3BS/o7BefD7JS6tqdvzvvUtj1O8op6z8vbB+VdU3Z/R/YXtJfqm19uY1LgnOOVX1siT/M8kNOb6+y7/MaB2m30xyWUY/zN/eWts3/mH+uSTfmORIku9vrX3srBcO56Cq2pPkn7fWvrWqrsyoo+m8JNcn+e7W2lxVzSR5V0brqe1L8rrW2q1rVTOcC6rq+Rktwj+V5NYk35/R/+j2OwrrQFX9ZJK/k9Hdk69P8vcyWmvJ7yinRMAEAAAAQCemyAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAANZAVf1EVf3zk+z/N1X1tWtREwDA6eqvdQEAABtdVVWSaq0Nu16rtfavV6EkAICzSgcTAMBpqKorqurmqvqFJB9P8o6q+lhV3VhVP7nivNuq6ier6uNVdUNVPeMk1/r7VfV7VbWpqn6lql77WO+tqguq6o/G+/+/qrq9qnadre8OAPBwAiYAgNN3dZJfba29IMmPttauSfLcJH+rqp674rz7W2svTPK2JCdMi6uqf5zkVUle01o7epLPONl7/68kfzLe/1tJLlvNLwUAcKoETAAAp+/21tqHx9vfUVUfT3J9kmcnedaK8947fr4uyRUr9n9Pkm9K8m2ttblH+YyTvfdlSa5Nktba7yd58PS/AgBAdwImAIDTdzhJquopGXUXvbK19twkH0gys+K8pfBokBPXwPxURqHRJY/xGSd7b3WqGgBglQmYAAC625ZR2PRQVe3OqCvp8bg+yT9I8v6qevIpfN6HknxHklTV1yfZeQrvBQBYdQImAICOWmt/lVFYdGOSX0ryZ6fw3g9l1P30gVNYqPsnk3z9eEreNyW5O8nBUyoaAGAVVWttrWsAAOAUVNV0kkFrbbGqviLJ21prz1/rugCAc1f/S58CAMA6c1mS36yqiSTzSf7+GtcDAJzjdDABAAAA0Ik1mAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQAAAIBOBEwAAAAAdCJgAgAAAKATARMAAAAAnQiYAAAAAOhEwAQAAABAJwImAAAAADoRMAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQAAAIBOBEwAAAAAdCJgAgAAAKATARMAAAAAnQiYAAAAAOhEwAQAAABAJwImAAAAADoRMAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQDgFFTVbVV1tKoOVtX+qvrzqvrBqlr1f6+qqqdX1fuq6r6q2ldVf1BVV684/n1VNaiqQysee1a7DgCAL0XABABw6l7VWtua5PIkP53kXyR5xxn4nB1J3p/k6iS7k3w0yfseds5ftNa2rHjsPQN1AAA8JgETAMBpaq091Fp7f5K/k+T1VfWcJKmqb6mq66vqQFXdUVU/sfSeqvpAVf2Tldepqk9W1WtOcv2Pttbe0Vrb11pbSPKWJFdX1fln9IsBAJwiARMAQEettY8muTPJV493HU7yvRl1IH1Lkn+4IkB6Z5LvXnpvVT0vycVJfvdxfNTXJLmntfbAin0vqKr7q+pvqurHq6rf7dsAAJw6ARMAwOq4K8l5SdJa29tau6G1NmytfTLJryf5W+Pz3pfkqqq6avz6e5L8Rmtt/rEuXlWXJPn5JD+yYvefJnlOkguTfFuS70zyv6/S9wEAeNwETAAAq+PiJPuSpKpeUlUfHC/O/VCSH0yyK0laa3NJfjPJd48XBv/OJO96rAtX1QVJ/jDJL7TWfn1pf2vt1tba58ZB1g1J/k2S156B7wYA8JgETAAAHVXVl2cUMH1ovOvXMlqc+9LW2vYkv5ikVrzlnUm+K8krkxxprf3FY1x7Z0bh0vtba2/+EqW0h30OAMBZIWACADhNVbWtqr41ybVJ/uu4iyhJtibZ11o7VlUvTvK/rXzfOFAaJvnZPEb3UlVtS/IHSf6stfamkxz/pqraPd5+RpIfzyPvMgcAcMZVa22tawAA2DCq6rYku5MsZhQS3ZTkvyb5xdbaYHzOazMKj85L8j+S3JZkR2tt5eLe/yrJTyV5amvt1kf5rNcn+ZUkRzLqTlryrNba56vqZzJaw2lLki+O6/ip8R3nAADOGgETAMAaqKrvTfKG1trL1roWAICuTJEDADjLqmo2yT9K8va1rgUAYDUImAAAzqKq+oYk92U0pe3X1rgcAIBVYYocAAAAAJ3oYAIAAACgEwETAAAAAJ3017qAM2HXrl3tiiuuWOsyVsXhw4ezefPmtS4DOE3GMGx8xjFsbMYwbHzG8fpx3XXX3d9au+Bkx56QAdMVV1yRj33sY2tdxqrYu3dv9uzZs9ZlAKfJGIaNzziGjc0Yho3POF4/qur2RztmihwAAAAAnQiYAAAAAOhEwAQAAABAJwImAAAAADoRMAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0El/rQvgsd3whYfyfW/6wOM+/7af/pYzWA0AAADAI+lgAgAAAKATARMAAAAAnQiYAAAAAOhEwAQAAABAJwImAAAAADoRMAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQAAAIBOBEwAAAAAdCJgAgAAAKATARMAAAAAnQiYAAAAAOjkrAdMVTVTVR+tqr+qqhur6ifH+59SVR+pqs9U1W9U1dR4//T49S3j41ec7ZoBAAAAeHRr0cE0l+QVrbXnJXl+km+sqpcm+XdJ3tJauyrJg0l+YHz+DyR5sLX2tCRvGZ8HAAAAwDpx1gOmNnJo/HJy/GhJXpHkPeP970zymvH2q8evMz7+yqqqs1QuAAAAAF9CtdbO/odW9ZJcl+RpSX4+yb9P8uFxl1Kq6tIkv9dae05VfSrJN7bW7hwf+2ySl7TW7n/YNd+Q5A1Jsnv37hdde+21Z+37nEn37nsoXzz6+M//sou3n7ligFN26NChbNmyZa3LADowjmFjM4Zh4zOO14+Xv/zl17XWrjnZsf7ZLiZJWmuDJM+vqh1JfivJM0922vj5ZN1Kj0jFWmtvT/L2JLnmmmvanj17VqfYNfaf3v2+/OwNj/8v023ftefMFQOcsr179+aJ8s8jOFcZx7CxGcOw8RnHG8Oa3kWutbY/yd4kL02yo6qWkpRLktw13r4zyaVJMj6+Pcm+s1spAAAAAI9mLe4id8G4cylVtSnJ1ya5OckHk7x2fNrrk7xvvP3+8euMj/9JW4t5fQAAAACc1FpMkbsoyTvH6zBNJPnN1trvVNVNSa6tqn+b5Pok7xif/44k76qqWzLqXHrdGtQMAAAAwKM46wFTa+2TSV5wkv23JnnxSfYfS/LtZ6E0AAAAAE7Dmq7BBAAAAMDGJ2ACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQAAAIBOBEwAAAAAdCJgAgAAAKATARMAAAAAnQiYAAAAAOhEwAQAAABAJwImAAAAADoRMAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQAAAIBOBEwAAAAAdCJgAgAAAKATARMAAAAAnQiYAAAAAOhEwAQAAABAJwImAAAAADoRMAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQAAAIBOznrAVFWXVtUHq+rmqrqxqt443v8TVfWFqvrE+PHNK97zY1V1S1V9uqq+4WzXDAAAAMCj66/BZy4m+dHW2seramuS66rqj8bH3tJa+5mVJ1fVs5K8Lsmzkzw5yX+vqqe31gZntWoAAAAATuqsdzC11u5urX18vH0wyc1JLn6Mt7w6ybWttbnW2ueS3JLkxWe+UgAAAAAej2qtrd2HV12R5E+TPCfJjyT5viQHknwsoy6nB6vq55J8uLX2X8fveUeS32utvedh13pDkjckye7du1907bXXnqVvcWbdu++hfPHo4z//yy7efuaKAU7ZoUOHsmXLlrUuA+jAOIaNzRiGjc84Xj9e/vKXX9dau+Zkx9ZiilySpKq2JPlvSX64tXagqt6W5KeStPHzzyb5u0nqJG9/RCrWWnt7krcnyTXXXNP27Nlzhio/u/7Tu9+Xn73h8f9luu279py5YoBTtnfv3jxR/nkE5yrjGDY2Yxg2PuN4Y1iTu8hV1WRG4dK7W2vvTZLW2hdba4PW2jDJf87xaXB3Jrl0xdsvSXLX2awXAAAAgEe3FneRqyTvSHJza+0/rNh/0YrT/pcknxpvvz/J66pquqqekuSqJB89W/UCAAAA8NjWYorcVyX5niQ3VNUnxvv+ZZLvrKrnZzT97bYk/yBJWms3VtVvJrkpozvQ/ZA7yAEAAACsH2c9YGqtfSgnX1fpdx/jPW9O8uYzVhQAAAAAp21N1mACAAAA4IlDwAQAAABAJwImAAAAADoRMAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQAAAIBOBEwAAAAAdCJgAgAAAKATARMAAAAAnQiYAAAAAOhEwAQAAABAJwImAAAAADoRMAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ0ImAAAAADoRMAEAAAAQCcCJgAAAAA6ETABAAAA0ImACQAAAIBOBEwAAAAAdCJgAgAAAKATARMAAAAAnQiYAAAAAOhEwAQAAABAJwImAAAAADoRMAEAAADQiYAJAAAAgE4ETAAAAAB0ImACAAAAoBMBEwAAAACdCJgAAAAA6ETABAAAAEAnAiYAAAAAOhEwAQAAANCJgAkAAACATgRMAAAAAHQiYAIAAACgEwETAAAAAJ2c9YCpqi6tqg9W1c1VdWNVvXG8/7yq+qOq+sz4eed4f1XVW6vqlqr6ZFW98GzXDAAAAMCjW4sOpsUkP9pae2aSlyb5oap6VpI3Jfnj1tpVSf54/DpJvinJVePHG5K87eyXDAAAAMCjOesBU2vt7tbax8fbB5PcnOTiJK9O8s7xae9M8prx9quT/Gob+XCSHVV10VkuGwAAAIBHsaZrMFXVFUlekOQjSXa31u5ORiFUkgvHp12c5I4Vb7tzvA8AAACAdaC/Vh9cVVuS/LckP9xaO1BVj3rqSfa1k1zvDRlNocvu3buzd+/eVap0be3elPzoly0+7vOfKN8bnigOHTpkXMIGZxzDxmYMw8ZnHG8MaxIwVdVkRuHSu1tr7x3v/mJVXdRau3s8Be7e8f47k1y64u2XJLnr4ddsrb09yduT5Jprrml79uw5U+WfVf/p3e/Lz97w+P8y3fZde85cMcAp27t3b54o/zyCc5VxDBubMQwbn3G8MazFXeQqyTuS3Nxa+w8rDr0/yevH269P8r4V+793fDe5lyZ5aGkqHQAAAABr77QDpqraXVXvqKrfG79+VlX9wON461cl+Z4kr6iqT4wf35zkp5N8XVV9JsnXjV8nye8muTXJLUn+c5J/dLo1AwAAALD6ukyR+5Ukv5zk/xy//pskv5FRd9Kjaq19KCdfVylJXnmS81uSHzrtKgEAAAA4o7pMkdvVWvvNJMMkaa0tJhmsSlUAAAAAbBhdAqbDVXV+xnd0W1ofaVWqAgAAAGDD6DJF7kcyWoD7qVX1Z0kuSPLaVakKAAAAgA3jtAOm1trHq+pvJbk6ozWVPt1aW1i1ygAAAADYEE45YKqq//VRDj29qtJae2/HmgAAAADYQE6ng+lVj3GsJREwAQAAAJxDTjlgaq19/5koBAAAAICN6bTvIldV51fVW6vq41V1XVX9x/GAvNriAAAZWUlEQVRd5QAAAAA4h5x2wJTk2iT3Jfm2jO4ed1+S31iNogAAAADYOE77LnJJzmut/dSK1/+2ql7TtSAAAAAANpYuHUwfrKrXVdXE+PEdST6wWoUBAAAAsDF0CZj+QZJfSzI/flyb5Eeq6mBVHViN4gAAAABY/057ilxrbetqFgIAAADAxtRlDaZU1d9O8jXjl3tba7/TvSQAAAAANpLTniJXVT+d5I1Jbho/3jjeBwAAAMA5pEsH0zcneX5rbZgkVfXOJNcnedNqFAYAAADAxtBlke8k2bFie3vHawEAAACwAXXpYPp/klxfVR9MUhmtxfRjq1IVAAAAABtGl7vI/XpV7U3y5RkFTP+itXbPahUGAAAAwMbQZZHvSvLKjNZhel+Sqap68apVBgAAAMCG0GUNpl9I8hVJvnP8+mCSn+9cEQAAAAAbSpc1mF7SWnthVV2fJK21B6tqapXqAgAAAGCD6NLBtFBVvSQtSarqgiTDVakKAAAAgA2jS8D01iS/lWR3Vb05yYeS/N+rUhUAAAAAG0aXu8i9u6quy2ih7yR5TWvt5tUpCwAAAICNossaTEkym2Rpmtym7uUAAAAAsNGc9hS5qvrXSd6Z5Lwku5L8clX9q9UqDAAAAICNoUsH03cmeUFr7ViSVNVPJ/l4kn+7GoUBAAAAsDF0WeT7tiQzK15PJ/lsp2oAAAAA2HC6dDDNJbmxqv4oozWYvi7Jh6rqrUnSWvunq1AfAAAAAOtcl4Dpt8aPJXu7lQIAAADARnTaAVNr7Z2rWQgAAAAAG1OXNZgAAAAAQMAEAAAAQDenHDBV1bvGz29c/XIAAAAA2GhOp4PpRVV1eZK/W1U7q+q8lY/VLhAAAACA9e10Fvn+xSS/n+TKJNclqRXH2ng/AAAAAOeIU+5gaq29tbX2zCS/1Fq7srX2lBUP4RIAAADAOeZ0OpiSJK21f1hVz0vy1eNdf9pa++TqlAUAAADARnHad5Grqn+a5N1JLhw/3l1V/2S1CgMAgP+/vfsP1vQs6wP+vUgUKDCEiOykSezSkjqCgYjbSAvT2UALwVhDp6KhFCJG0h9gdGC0i/6BlTITxiKOlFJTiVmUElNamkySkQmRLW2RHw3BhICUSLawhiFVQmClDd1w9Y/zrHlZNz/Ouc857/vsfj4zZ87z3O/zPnu9593r/PjOfT8PADAPG57BlOQnk/xAd/9ZklTVm5L8fpK3bkZhAAAAAMzDhmcwZe3i3vct7N+Xb73gNwAAAADHgZEZTL+Z5CNV9d5p/0VJ3jFeEgAAAABzMnKR71+pqn1JnpO1mUuv6O6bN6swAAAAAOZhZAZTuvvjST6+SbUAAAAAMEMj12ACAAAAAAETAAAAAGM2FDBV1QlV9f7NLgYAAACA+dlQwNTd9yX5elU9fpPrAQAAAGBmRi7y/X+T3FpVNyT5s8OD3X3JcFUAAAAAzMZIwHTd9AEAAADAcWzDAVN3762qRyf5ru7+zCbWBAAAAMCMbPguclX195J8IsnvTvtnVdU1m1UYAAAAAPOw4YApyS8mOTvJV5Kkuz+R5MmbUBMAAAAAMzISMB3q7nuOGOuRYgAAAACYn5GLfH+yqv5hkhOq6owklyT50OaUBQAAAMBcjMxg+qkkT0tyb5J3J/lqkp/ZjKIAAAAAmI+Ru8h9PckvVNWb1nb7a5tXFgAAAABzseGAqar+RpLLkzxu2r8nyU90902bVBsbsHPPdes6fv+l521RJQAAAMDxYuQaTO9I8s+6+78mSVU9J8lvJnn6ZhQGAAAAwDyMXIPpa4fDpSTp7v+WxDI5AAAAgOPMumcwVdUzp82PVtWvZ+0C353kx5Ls27zSAAAAAJiDjSyRe/MR+69f2O6BWgAAAACYoXUHTN19zlYUAgAAAMA8jdxF7qQkL0+yc/E83X3JQzzv8iQ/lOSu7v7eaewXk7wyyf+eDvv57r5+eux1SS5Kcl+SS7r7fRutGQAAAIDNN3IXueuTfDjJrUm+uY7nXZHkXyd55xHjb+nuf7U4UFVPTXJBkqcl+ctJ3l9Vf72779to0QAAAABsrpGA6VHd/Zr1Pqm7P1hVOx/m4ecnubK7701yR1XdnuTsJL+/3n8XAAAAgK3xiIHn/lZVvbKqTqmqkw9/DJzv1VV1S1VdXlVPmMZOTfKFhWMOTGMAAAAArIiRGUzfSPLLSX4h9989rpP81Q2c6+1J3jA9/w1Zu1PdTySpoxx71DvVVdXFSS5Okh07dmTfvn0bKGP17Hh08tozD23Z+Y+VrxOsqoMHD+ozmDl9DPOmh2H+9PE8jARMr0nylO7+k9EiuvtLh7er6t8luXbaPZDk9IVDT0ty5wOc47IklyXJrl27evfu3aNlrYS3vuvqvPnWkbfpwe1/6e4tOzewFuIeK9+P4Hilj2He9DDMnz6eh5Elcrcl+fpmFFFVpyzs/v0kn5y2r0lyQVU9sqqenOSMJB/djH8TAAAAgM0xMjXmviSfqKoPJLn38GB3X/JgT6qqdyfZneSJVXUgyeuT7K6qs7K2/G1/kn88neu2qroqyaeSHEryKneQAwAAAFgtIwHTf54+1qW7X3KU4Xc8yPFvTPLG9f47AAAAAGyPDQdM3b13MwsBAAAAYJ42HDBV1R05yh3dunsjd5EDAAAAYKZGlsjtWth+VJIXJzl5rBwAAAAA5mbDd5Hr7j9d+Pjj7v7VJM/dxNoAAAAAmIGRJXLPXNh9RNZmND1uuCIAAAAAZmVkidybF7YPJdmf5EeHqgEAAABgdkbuInfOZhYCAAAAwDyNLJF7ZJJ/kGTn4nm6+5fGywIAAABgLkaWyF2d5J4kNyW5d3PKAQAAAGBuRgKm07r73E2rBAAAAIBZesTAcz9UVWduWiUAAAAAzNLIDKbnJPnxqroja0vkKkl399M3pTIAAAAAZmEkYHrhplUBAAAAwGxtOGDq7v+1mYUAAAAAME8j12ACAAAAAAETAAAAAGMETAAAAAAMETABAAAAMETABAAAAMAQARMAAAAAQwRMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMETABAAAAMETABAAAAMAQARMAAAAAQwRMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMETABAAAAMETABAAAAMAQARMAAAAAQwRMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMETABAAAAMETABAAAAMAQARMAAAAAQwRMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMWUrAVFWXV9VdVfXJhbGTq+qGqvrs9PkJ03hV1a9V1e1VdUtVPXMZNQMAAABwdMuawXRFknOPGNuT5MbuPiPJjdN+krwwyRnTx8VJ3r5NNQIAAADwMCwlYOruDyb58hHD5yfZO23vTfKihfF39poPJzmpqk7ZnkoBAAAAeCgnLruABTu6+4tJ0t1frKonTeOnJvnCwnEHprEvLj65qi7O2gyn7NixI/v27dvygrfDjkcnrz3z0Jad/1j5OsGqOnjwoD6DmdPHMG96GOZPH8/DKgVMD6SOMtZ/YaD7siSXJcmuXbt69+7dW1zW9njru67Om2/durdp/0t3b9m5gbUQ91j5fgTHK30M86aHYf708Tys0l3kvnR46dv0+a5p/ECS0xeOOy3JndtcGwAAAAAPYJUCpmuSXDhtX5jk6oXxl093k3tWknsOL6UDAAAAYPmWskSuqt6dZHeSJ1bVgSSvT3Jpkquq6qIkn0/y4unw65P8YJLbk3w9ySu2vWAAAAAAHtBSAqbufskDPPS8oxzbSV61tRUBAAAAsFGrtEQOAAAAgBkSMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMETABAAAAMETABAAAAMAQARMAAAAAQwRMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMETABAAAAMETABAAAAMAQARMAAAAAQwRMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAENOXHYBLNfOPdet6/j9l563RZUAAAAAc2UGEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMETABAAAAMETABAAAAMAQARMAAAAAQwRMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADDlx2QUwLzv3XLeu4/dfet4WVQIAAACsCjOYAAAAABgiYAIAAABgiIAJAAAAgCECJgAAAACGCJgAAAAAGCJgAgAAAGCIgAkAAACAIQImAAAAAIYImAAAAAAYImACAAAAYIiACQAAAIAhAiYAAAAAhgiYAAAAABgiYAIAAABgiIAJAAAAgCECJgAAAACGnLjsAo5UVfuTfC3JfUkOdfeuqjo5ye8k2Zlkf5If7e67l1UjAAAAAPdb1RlM53T3Wd29a9rfk+TG7j4jyY3TPgAAAAArYFUDpiOdn2TvtL03yYuWWAsAAAAAC6q7l13Dt6iqO5LcnaST/Hp3X1ZVX+nukxaOubu7n3DE8y5OcnGS7Nix4/uvvPLK7Sx7y9z15Xvypf+z7Co27sxTH7/sEmCpDh48mMc+9rHLLgMYoI9h3vQwzJ8+Xh3nnHPOTQurzb7Fyl2DKcmzu/vOqnpSkhuq6g8fzpO6+7IklyXJrl27evfu3VtY4vZ567uuzptvXcW36eHZ/9Ldyy4Blmrfvn05Vr4fwfFKH8O86WGYP308Dyu3RK6775w+35XkvUnOTvKlqjolSabPdy2vQgAAAAAWrVTAVFWPqarHHd5O8vwkn0xyTZILp8MuTHL1cioEAAAA4EirtvZqR5L3VlWyVtu/7+7fraqPJbmqqi5K8vkkL15ijQAAAAAsWKmAqbs/l+QZRxn/0yTP2/6KAAAAAHgoK7VEDgAAAID5ETABAAAAMETABAAAAMAQARMAAAAAQwRMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMETABAAAAMETABAAAAMAQARMAAAAAQwRMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMOXHZBXBs27nnunUdv//S87aoEgAAAGCrmMEEAAAAwBABEwAAAABDLJFjpax3SV1iWR0AAAAsmxlMAAAAAAwRMAEAAAAwRMAEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMOXHZBcB227nnunUdv//S87aoEgAAADg2mMEEAAAAwBABEwAAAABDBEwAAAAADBEwAQAAADDERb6ZvfVetHvVzr9eLjoOAADAqjGDCQAAAIAhAiYAAAAAhgiYAAAAABgiYAIAAABgiIAJAAAAgCHuIgczs9672rnrHAAAAFvNDCYAAAAAhgiYAAAAABgiYAIAAABgiIAJAAAAgCECJgAAAACGCJgAAAAAGHLisgsAttbOPdet6/j9l563RZVsj+Pt9QIAAKwCM5gAAAAAGCJgAgAAAGCIJXLASlvvkjcAAAC2n4AJ+BbHW6Czkdfruk0AAADfyhI5AAAAAIaYwQRwnHGnvQfn6wMAAOsnYALYYsdbYHG8vV42n/9Dy7fVy6W9ZwBw7JnNErmqOreqPlNVt1fVnmXXAwAAAMCaWcxgqqoTkrwtyd9NciDJx6rqmu7+1HIrAzj2bfVMhuNtpoQLy8/PrX98T358He+b9wvmz0xKgPWbRcCU5Owkt3f355Kkqq5Mcn4SAROw7dbzS+drzzyU9X6rPd7u5MdDW7U/dFbt/+jx9vVZb/2r9n5txKp9Tedu1XpmI9b7s3j31pWyLY6F92w9VvH71qr97Dje3uMrzn3MFlWyccfbe/ZwzGWJ3KlJvrCwf2AaAwAAAGDJqruXXcNDqqoXJ3lBd//ktP+yJGd3908tHHNxkoun3e9O8pltL3RrPDHJnyy7CGDD9DDMnz6GedPDMH/6eHX8le7+zqM9MJclcgeSnL6wf1qSOxcP6O7Lkly2nUVth6r6H929a9l1ABujh2H+9DHMmx6G+dPH8zCXJXIfS3JGVT25qr49yQVJrllyTQAAAABkJjOYuvtQVb06yfuSnJDk8u6+bcllAQAAAJCZBExJ0t3XJ7l+2XUswTG37A+OM3oY5k8fw7zpYZg/fTwDs7jINwAAAACray7XYAIAAABgRQmYVlRVnVtVn6mq26tqz7LrAe5XVZdX1V1V9cmFsZOr6oaq+uz0+QnTeFXVr029fEtVPXPhORdOx3+2qi5cxmuB41FVnV5VH6iqT1fVbVX109O4PoaZqKpHVdVHq+oPpj7+F9P4k6vqI1NP/s50g6BU1SOn/dunx3cunOt10/hnquoFy3lFcHyqqhOq6uaqunba18MzJmBaQVV1QpK3JXlhkqcmeUlVPXW5VQELrkhy7hFje5Lc2N1nJLlx2k/W+viM6ePiJG9P1v6QTfL6JD+Q5Owkrz/8xyyw5Q4leW13f0+SZyV51fRzVh/DfNyb5Lnd/YwkZyU5t6qeleRNSd4y9fHdSS6ajr8oyd3d/ZQkb5mOy9T7FyR5WtZ+tv+b6XdxYHv8dJJPL+zr4RkTMK2ms5Pc3t2f6+5vJLkyyflLrgmYdPcHk3z5iOHzk+ydtvcmedHC+Dt7zYeTnFRVpyR5QZIbuvvL3X13khvyF0MrYAt09xe7++PT9tey9ovtqdHHMBtTPx6cdr9t+ugkz03ynmn8yD4+3N/vSfK8qqpp/Mruvre770hye9Z+Fwe2WFWdluS8JL8x7Vf08KwJmFbTqUm+sLB/YBoDVteO7v5isvbHa5InTeMP1M/6HFbANMX++5J8JPoYZmVaWvOJJHdlLeD9oyRf6e5D0yGLPfnn/To9fk+S74g+hmX61SQ/l+Sb0/53RA/PmoBpNdVRxtzuD+bpgfpZn8OSVdVjk/zHJD/T3V99sEOPMqaPYcm6+77uPivJaVmbsfA9Rzts+qyPYYVU1Q8luau7b1ocPsqhenhGBEyr6UCS0xf2T0ty55JqAR6eL01LZjJ9vmsaf6B+1uewRFX1bVkLl97V3f9pGtbHMEPd/ZUk+7J2TbWTqurE6aHFnvzzfp0ef3zWlrvrY1iOZyf54aran7VLwjw3azOa9PCMCZhW08eSnDFdQf/bs3bRsmuWXBPw4K5JcvgOUhcmuXph/OXTXaieleSeaenN+5I8v6qeMF0U+PnTGLDFpms2vCPJp7v7VxYe0scwE1X1nVV10rT96CR/J2vXU/tAkh+ZDjuyjw/3948k+b3u7mn8gukOVU/O2sX8P7o9rwKOX939uu4+rbt3Zu3v3d/r7pdGD8/aiQ99CNutuw9V1auz9kvqCUku7+7bllwWMKmqdyfZneSJVXUga3eRujTJVVV1UZLPJ3nxdPj1SX4waxcc/HqSVyRJd3+5qt6QtUA5SX6pu4+8cDiwNZ6d5GVJbp2u35IkPx99DHNySpK9092iHpHkqu6+tqo+leTKqvqXSW7OWpic6fNvVdXtWZv1cEGSdPdtVXVVkk9l7Q6Tr+ru+7b5tQD3++fRw7NVa6EfAAAAAGyMJXIAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMETABACxBVf1GVT31IY550UMdAwCwCqq7l10DAABHUVVXJLm2u9+z7FoAAB6MGUwAAJugqnZW1R9W1d6quqWq3lNVf6mqnldVN1fVrVV1eVU9cjp+X1XtmrYPVtUbq+oPqurDVbWjqv5Wkh9O8stV9Ymq+mtVdUlVfWo6/5XLfL0AAIsETAAAm+e7k1zW3U9P8tUkr0lyRZIf6+4zk5yY5J8e5XmPSfLh7n5Gkg8meWV3fyjJNUl+trvP6u4/SrInyfdN5/8nW/5qAAAeJgETAMDm+UJ3//dp+7eTPC/JHd39P6exvUn+9lGe940k107bNyXZ+QDnvyXJu6rqHyU5tCkVAwBsAgETAMDm2ejFLf9f339hzPuyNtPpaM5L8rYk35/kpqp6oOMAALaVgAkAYPN8V1X9zWn7JUnen2RnVT1lGntZkv+yjvN9LcnjkqSqHpHk9O7+QJKfS3JSksduStUAAIMETAAAm+fTSS6sqluSnJzkLUlekeQ/VNWtSb6Z5N+u43xXJvnZqro5yRlJfns6z81J3tLdX9nU6gEANqjun40NAMBGVdXOJNd29/cuuRQAgG1nBhMAAAAAQ8xgAgAAAGCIGUwAAAAADBEwAQAAADBEwAQAAADAEAETAAAAAEMETAAAAAAMETABAAAAMOT/AyDP7HAVgQoWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(nums)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(nums[nums >= 200])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " (4, ('(anonymous user #193354)', 3566)),\n",
       " (5, ('Robert Xiao (AoC++)', 3537)),\n",
       " (6, ('goffrie', 3467)),\n",
       " (7, ('tckmn', 3221)),\n",
       " (8, ('Sophie Alpert (AoC++)', 3077)),\n",
       " (9, ('nthistle', 3073)),\n",
       " (10, ('Kevin Sun', 2952)),\n",
       " (11, ('hyper-neutrino', 2763)),\n",
       " (12, ('arknave (AoC++)', 2477)),\n",
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       " (14, ('Lewin Gan', 2335)),\n",
       " (15, ('Jonathan Paulson (AoC++)', 2334)),\n",
       " (16, ('bluepichu', 2320)),\n",
       " (17, ('Nathan Fenner (AoC++)', 2297)),\n",
       " (18, ('D. Salgado', 2284)),\n",
       " (19, ('m-schm', 2271)),\n",
       " (20, ('Christopher Lambert', 2233)),\n",
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       " (22, ('(anonymous user #1014764)', 2081)),\n",
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       " (27, ('huzecong', 1881)),\n",
       " (28, ('Martin Camacho (AoC++)', 1867)),\n",
       " (29, ('Carl Schildkraut', 1846)),\n",
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       " (32, ('ZED.Charley William Thairo', 1584)),\n",
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       " (91, ('Unihedron (AoC++)', 644)),\n",
       " (92, ('glguy (AoC++)', 637)),\n",
       " (93, ('(anonymous user #380)', 637)),\n",
       " (94, ('gengkev (AoC++)', 623)),\n",
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       " (96, ('Utkarsh Kukreti (AoC++)', 621)),\n",
       " (97, ('Matthew Ramina', 613)),\n",
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       " (99, ('lucifer1004', 597)),\n",
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       " (102, ('Starwort', 586)),\n",
       " (103, ('jes', 585)),\n",
       " (104, ('Sp3000', 578)),\n",
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       " (106, ('Erik Amirell Eklöf', 572)),\n",
       " (107, ('coolcomputery', 571)),\n",
       " (108, ('monster860', 570)),\n",
       " (109, ('Timothy Elling', 569)),\n",
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       " (119, ('smartspot2', 537)),\n",
       " (120, ('kentonlam (AoC++)', 534)),\n",
       " (121, ('Paul Draper', 534)),\n",
       " (122, ('Jouni K. Seppänen (AoC++) (Sponsor)', 528)),\n",
       " (123, ('Joshua Wise (AoC++)', 523)),\n",
       " (124, ('Craig Gidney', 516)),\n",
       " (125, ('Cameron Aavik (AoC++)', 515)),\n",
       " (126, ('Keenan G', 507)),\n",
       " (127, ('Jacob Wood', 505)),\n",
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       " (131, ('(anonymous user #1080715)', 486)),\n",
       " (132, ('jebouin (AoC++)', 484)),\n",
       " (133, ('(anonymous user #14124)', 478)),\n",
       " (134, ('RafaÅ\\x82 BurczyÅ\\x84ski', 477)),\n",
       " (135, ('jhawthorn (AoC++) (Sponsor)', 474)),\n",
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       " (137, ('jhurwitz', 472)),\n",
       " (138, ('Niak', 471)),\n",
       " (139, ('Andrey Anurin (AoC++)', 469)),\n",
       " (140, ('(anonymous user #912684)', 467)),\n",
       " (141, ('MarshallOfSound', 465)),\n",
       " (142, ('Alex Oro', 465)),\n",
       " (143, ('Colton Pauderis (AoC++)', 463)),\n",
       " (144, ('LyricLy', 462)),\n",
       " (145, ('Matt Gruskin (AoC++)', 452)),\n",
       " (146, ('tjjfvi', 448)),\n",
       " (147, ('sburuiana (AoC++)', 447)),\n",
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