alexbernal0
4/20/2017 - 2:25 AM

Python Linear Regression

Python Linear Regression

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import pandas_datareader.data as web\n",
    "import datetime\n",
    " \n",
    "# We will look at stock prices over the past year, starting at January 1, 2016\n",
    "start = datetime.datetime(2016,1,1)\n",
    "end = datetime.date.today()\n",
    " \n",
    "# Let's get Apple stock data; Apple's ticker symbol is AAPL\n",
    "# First argument is the series we want, second is the source (\"yahoo\" for Yahoo! Finance), third is the start date, fourth is the end date\n",
    "apple = web.DataReader(\"AAPL\", \"yahoo\", start, end)\n",
    " \n",
    "type(apple)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "109.89705023076922"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Avg Stock Value\n",
    "apple[\"Adj Close\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Stock Volatility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0xb6bc710>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jGgR6RSs766ZYC7JW9OR9W65kp7TZrg4CeNbpDUelbgezvtgRcPvTcNyeSatB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\nIfGNAUcyVv5c7+H4Z/Sczp4sGCMHqZ4N25C8d8GbrfBNtWOhp4bP6G0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XhOj5Z/T4cYbf\nkEEzegDv+LzlmnW4bpNDues0o0fJK22WtZjUTUN3d1jpmAN99KQZPXrgvee22bbw7q8/hlK9jc/9\nr8t8hbhD3Yx3Ez51amFZhpblaNhGpmk9fjI0WWqIGZK6tNhRR60TdZMSpGqIR2FY5Oyh+aSI3p17\nzqCQ1nG9h7YJOPcIUYmGutKxPHIABw2LUu4tNThSnTf4LBk9A6FiLCE+egCwbbSIfWfDN8Ra04Sm\nKrFoj7SWCERPd7rMJ+dq2OgZ1vd2huNEmI8efafclVYURTAOvDTqqAhqfu2353+2BCJ6wT56tz12\nErfZ1hPeqNiF3lKevdPzNV/ji0JVFVy2tg+/sP30hBhLwKZEdOKoJDyuYfpirQ1DU1FI65GNzkk7\nsXIQPSbWupSuYm1/3oXoyc/lxGIDPbkUdE0VhV4gopdyEL1cWkOlYWK+1hJr5bM3D2Gx3nbNT0WF\naTEhVkGhSyMJyxHlBqd5k6UCRW/OcBumm+Ezet5GqqFz66NTAR56FF7qJr13tDvjQ4ejghqfh6fc\nhV4cerCuqejOctN0UehJdgHDxTTW2oqMn7j7ALrSOl504QrXZzxn6xD2nl4UVgYAzzk+fvcBbBwq\n4OUXj/m+t5COr7p5YraK2UoTR6YrsRXJaU/asqILmqr4qJu1poknTy7g8nV97n+XjV/oUSMuk1Jj\n6QwAXsaU87rslRcVeUODqkjUzamKi5Ivx1hvVtxTR6YquGCsO7Lh1ldw3+9BQXYrzTZHzryIXj6t\nY8dot2i0RsXEYh2FtI5XXboSX7z3KA55PGErzTbyhg5FUXxK7zR2RIhe2hZjaZqmuH87zejJYixA\n9LUzLYb5Wgur7Oe4usRGYVDsHp/HuoG8WOOWU4ylAuC3APwdgM8BeB2Ag0s7zPMXkYiebK9gOSaU\nsX30AmbuNFWBqiT30QOkQk9S2QtF9Brcy63LlsD3ImOL9RZXjurQBddUxbfZHZ4qY709mCu66haz\nqSXOsY90ZwLtFdqWJc7tc7YO4U3PWutD5ro7IDGWxTiiF1CopnUNH3rJdhcd1KFuBm/c1NUkeeo4\n0rb+jdehZkbN6Mmqm157hb/43j48cnwOH3vlTpenGUVOUDc7P6iPnZjDLX97H544uTyeMxT1lmkP\nSTtoblRUmzzppWFsebEjHnqQeI38XPYFzCnGCRqaT2qvcO+hKTx7y2DgdaTkkwq9Fd2Z2OI4dD9H\nSdSX620UDB05Q7N99OxCL+Q8CzGWgGd5+0gR47O10EKXfAnDRAfk8BV6khgLAJ9ipzPUH39TCWJB\nyNfA6/upqQpalpXIXoF+h/yMEw1ox2hAoWdoqHqsWeotE6fmazg2UwncvMv1NkyLJbLdAHgXe7LU\nCEX0AE7fPD5TxcHJklj3A6mbMWh1dJ47FTSlegtdGd32Cu08V0xFB0+MHKXF1f05jM9WBdpG9zY9\n6vScky1QkOrmxat78KwN/VjTl7eFdTitkPaMazcOQFWAnx2cjvxNFGcX62iaFtb0OWITzlq9PE0y\neu69iJ630BPUzWbbN7bgbaTqKk88TwZYK1DkUm56mfAF68li58oeZFJqR/pmW2pMPuNF9MirsUPz\nrS9vYKbSlNYqRXiMjRSzQnr/4EQZL9k16tsPyMf0jj3OrNUP903iyFQFv/v8zYF5TCGB6i+hhc4s\nYmf9AkIq1/Tn0JXRfdTN3ePzaFsMl691i1z15t3UzYMTJfzNDw8FNsRobZEN0+OobtLzJK/rcamb\niqKgK8NHZxZqLUyVGj7FTYqVPVmcmqvBtBiOz1SFr3JY9OUMzFWDR3IYY/j3x0/i6r/8MT707b2c\n+phyZvRIwCZv6NgxWsTphXpHNHpisY6hYhofuHkr8mkdH/r2Xtc6Xm2YovHHx4Wca+iIYrnFWFpt\nvtdkbdufsGi0nBk9Ws9OBzDcKMheZqgrDUNTlw3RY4xh9/g8dq3qQUrjIkhJ1LCjZvT+HMBtAO4A\n8BzG2K0AdgP4nqIobzzXA1/OMC3/TByFahdlpk3dpEQ+am6Mot4yA1U3AcdYG3DP6IX56GU882Vy\nBz/KRy+f1px5FE+yJW+MUaF7VDcti+GZSafDowvqj+WjlqzozmCu2vJxo03LUcy7fG0fPnzrDt/3\n0rGFJajlpt96ICo6ibHQRkwJVjVG4t4yvTN6MsUyHNGTlZtkOt7tj53Elx44hrdfty7U2FQUrDGO\njxaqmXKjwzuTRaPNC1nZyDQqSPiHCj0Z/aLzIBcMFPK9JM9DRKkIBoWXkhEn5qotobblja5MCsWM\njoNnedIzkqDQcxC9aOpmIcNp1zw5spP5kHVHbvx4Y7tduITRN71+k1GhqdzsmTZXw1PoeZOBpc3o\n+VkNcmHvTVZS9vrUNC2fGE1Y0Joor0tPnVpAf94IRJByhl+85dhMBYzx7vkzHpQDcNDCUkIxiIkF\n/qyMBlAWKa6wEYLvPXlWvLZUMZb4PnptFLMprvQYQD9ijOH939iND9z+JDYOFXDxKp7cymIshqZi\nbX8ObYuJgoOeS0JSB+yZ8ShEb8doN/7l7Vcha2hcEdW2V6A9ozuXwq5VPbHn9EgFdHWfn7q5XIge\nFXO+Gb28gblKSySfhMwyFuB962mk6rYYC1Hngmb0Mh562Rmio/VkYOgqLlvT17HQk/dC770eh7oJ\n8EJPFqFyIXrdGde5f61E26RY1ZfDRat6cMee0+K1k/as19XrBwK/syut85mqGCIYj59wpOd/YSOc\nYR56FETdXNWXQzGT8iF6Dx+bhaIAl652I3rdWS5SRc/nlx84hk/+8CBe8Ml7fPdsXUL0NFWBoakd\n9xrTYqLAk3PJuNRNgM93l+ptcb3DCr2x3izOLtZxfKaCpmlhXadCL2/AtJhvP37y5AJe8dkH8Nvf\neAKL9Ra+9eg4qg0Thqb6qJv5tIYLbN2CTvTNicUGVhQz6C+k8Xsv2IIHj8zgO08491C52UbO3g+K\nGd2lhkprFDWbKG+n2cEgoSOKqVID1ZYpgIhNw/z8eanPclBu0FdIcxbJMomxnF6oY6rUECNNXQH3\nalREtU9vYYw9H8CNAN4IAIyx7wB4PgC/hvd/YXAxlvC/11WV++gxJi3+0ZviYyfmcOGHvy+U0bwJ\nGDfWthd2k/kQPW++lgtF9NTQYfpKkyN6usYhf6/61GKtJbjYUaFrquuzzy7WUWuZ4sHXpTkZ77A4\nybV/V3qw+PF39rzqJKJByWPQjF5QyDN6P7TnAOSgjXg0AXWzbbmV/mQaZ9DGJyN+wl7BTuL3nl7A\nB29/Elet78MfvHBr6HcmUd2khWM5ud6A06lKxUT0yENvlUD0nORJzO9EFHppe1GlSELdBGwF1wQz\nes22hVrLdNlaeGO0JysK3OFiJrKzN7lYx3v+5TGU6i1pRi+8aKs0eZcxZ2gu1dqw4pA+K6jQ2dFB\nsa7eNIWaW5zoyqSE14/sowc4m5nzXtveIUGxE2Qxk3Uheu5EmaibbdPy2UuERSGAuvnUqUXsGOsO\nRDYdFN25xkcltb1DE+GFXlLDZur4RiF620eKyBuaUPXsyaWC7RVaJnRViUQ6k/jocUTPz/AAOPXt\n9sdP4XVXrMad77sWPTZFURZjMXRVIDc0p0fPJSUhhOhdu2kQN2wZ7NiMLKQ1NE0L0+WGy/Ps+s2D\n2HNyPpZP3AnbwFme0RNMmWUSY5mzf6dXSbUvn0LTtMQaLV8H73yZ6RkzMTRC9KrossUkvOFFHU7N\n15DSFFFQX7muDwcmSpFy/7TXKEr4jF6nZlFvzsBsxWOYbtO+VxTTyBoaRroz2LqiCxdK4mNyvGTn\nCPaeXhR792KtBUUJHz8JQu7D4vHxedHYo0KvE9Wx2y7aV/flUMzqPnuFh4/NYstwl8hlKHo8uc3h\nyTLW9nOPu1/7p1/gg7fvEYl43XN+Mx1QJIA3CYgxtRTqJsCtExZrrVDFTYqxniwsBjxoNwviFHqA\nMyozU27gg7fvwa2fuQ/HZ6r42Ct24qtvvRL1llNQ0bPopm7yfe0pSZDlqw8ew9u/8ojr+84u1AWa\n9rorVmPnym585M594vxWG20xs92fNzBfa4ln8MxCDQMFQ4wnCHsFe0zAK3Qkxz/dfxQKgJfu4pTi\ntf15aKoSuFdQ0L7alzOQN5ILgB04W8Knf3TINy6w20arnULPf69GRdSu+pSiKJ8D8BUAP6MXGWNt\nxtjfxP6GiFAU5YWKohxQFOWwoigfWOrnyMIgQaGqvBg0LSYg5E6b4oGzJbRMJhZF78dzY21+EVtt\nyyfG4vPR8yB6RB3lYizhPnrUueZDye6bZrHeikxkKbyG6fSbvIhe22Q+RO+q9X3YMVrE5+494kJB\nvRtWUIQheowxfOTOp/GvD48DQOCMXlDQOTw5V8XbvvIIbv6be/C1h46Lh2LeM6MXT4zF7d0l//8g\nuhTdP03JXoEKna8+eByGpuLvfvWSSDotJb1xjo+SnDhFa5JwEL14M3peRE/eqCiRCkpGaYHPpDRX\ncRckdBMVPQkRPdoEouZX6T4ppHVhIxCG9D96fA537jmDx084iWfYOaMufleaz+jJM67hhunh1M3B\nrjQGCgaeDul8EnUzbnRldFGs6poiNsGUpgizaQrqZj5+Yh6//tVHRQc+KoLo7nTtNVXxISIpe0Ce\nfP3iRD7tFmNptE0cnCjhggDaJhBMlz5iJ5uabZosB2PMKfQSzlkQCj8SMqMH8ObbJWt6xVo80p0N\nEWOxOl7b+DN6fL/g3m3+99Iz/sILViCta2Kta0iIXkpTxCwWeaZRwnGxnYT024X8TduH8aU3X9GR\nUkwUv/mqu3H57M2DYAy473Bn+uaJ2Sp0yfuVH6vbBiluVJttvP+bu8XsJAXtL0HUTcAkO7PBAAAg\nAElEQVQZHZDPrbdJYAYgem2L4dBkOZC2CfD9Qt4ryACaRJOu2tAPxqLn9Og52ThYwJmFuuuejmOY\nDvCC1jWjZ1PIAIfW9rFX7sRfveqi0GtOwlj/aUvlz9v3pBqSvxXs3KBTs6XeMvH06UXcctEodFUR\n56ITokeo87qBPLrSbpSkbVp47Picy1aBgix/aB09PFnGlev6ccd7r8U7n70e33h4HC/81L24//C0\n2CuJOZEJ8EX0hskYqOdFeVZaVwOtqMKCFwMtPDNVQUpTxNyYN+i+u99+ztYNxiz0Kk3MVpq46ZP3\n4JuPnMRbrlmHH//uDXj15atwyeoekV+mdT5WkNIULNh013xaR0/OwFhP1oXo/fTAFH68f1KsZcz2\nD6T7S1MV/NlLL8BUuYFP/ZALs3BAxBZ36kqDMSdvOi2ZpQNOY6XZtmDoWuiM3mK9ha89eBw3Xzgi\nCl9D52yGQ5PhXpC0Bji2Mcn2jjv2nMZf/+Cgj5a5e3wOhq4K2xqO6C1DoccYewOAvwXwEcbYbyc6\n2hihKIoG4DMAbgawHcDrFEXZvpTP4oOr4QkCIXqmpOrWyUePNr2JRf5fb1GT0hSB6DUDxFi865x/\nRs82bJSom97EsWojegBPGn2qm7W2sF6ICk1VXJ/thfIdRNHyUUsURcE7rl+PI1MV/Gj/pHjdu2EF\nBS2G3gR9rtrC5+89ik//iD+oQTN6QUHnkHyD1vTl8Yf/8RTe9uVHMF1uYLZCHVcDaV2NZ69guhFM\nGd0IKkZowZLtFWhRqjZNDHSlfTNI3lBVBWm9M30DcBaOOB3NJOHM6AXfe96g7v3K3iw0VXF5zlEi\nFSSkQRt4VjKLBZaI6CUq9GxacASaQIhLdzYljs3ry0ZBv3d8rioldCGFnv2cFjI6cmkNMxUnYQz1\n0ZNUeL2hKAq2jRRDEb2khV4ho2O27FA36Z5fN5D32zvYidZXHjyOu/aeFaqKURHmowdwNM+b1Oma\nIhKf+NRNN6J38GwZbYsJOpA3aB2V14RnpspYUcxg/UAeBye8AhWON2pSRM/xFevgeSUJPKwopgPF\nWGotM9I2A5Bn9Dohem1nRi/gPifUnpJfQ2oCNW3fKU1VMNSV5kbZdqG8UGshZ2gCDfZKuHcKWcRJ\nRrR2ruxBTy6Fnx3oTN88PlPFWG/Wdf/GZSt4Y9+ZEm5/7JRQRaWg596P6DmJL+Cm8nu77qbFXDN6\nKU3FQq2FB4/M4Pk73OIlFFkPMnBmoeYqaLkiZPScHv37C22LAHlOTyB6AYwMOXptdVEXomffm0SN\nu27TYOgzCPA1d7iYxvFp3iToNH5CiF4nRsHe0wtoWwyXrunF6r6cKNI7zbTduHUIX3nLFdgx2s0R\nPWlGb9+ZEipNE5et9RPY6B6Yr7YwW2liptLEpuECMikNH7x5G771689CWlfx+i/8HD/ex/Mmeo6z\nhtYxSef2Cm7q5lAx3Pw9KIp2MfDMVBlr+/1rOwU1PO8/PINCWu9YHMv3+97TC5itNPHZ11+CP7pl\nu7iWiqLgVbZyJ+0vcoOJcqsdo0WXxcKJWe7vTPn3rD32MCwhmRet6sFrL1+NLz1wDPvPLqLadJTb\nyWqM9tyzC3XXjLCY0TMtGDaiVw/IE7/20HGUGm2869kbXK9vGurCoQjqJiF6/QXDns9PlrfR+72q\nprvH57FjtCjOZTGjLxt1E4yxJxlj+xMdafy4AsBhxtgRxlgTwL8CeOlSPsi0GKLyA6IGmcyZ0evU\n/XQKPd6N9xZ6hq3eAzgJHykNBb0/46HryTN6YR3Ziq26CdiInufCLsSkbqY0P6LXnU0JClXKhej5\n0dEXXziCsZ4sPn/PEfFaO8K70PnNfAjX6zdDCfu1GwewbiCPzcPBlAJvUDL7yLFZaKqC29/9LPzx\nS7bj3sPTeOGn7sE9h6bQldZh6GrsbopX6U9GFMKKEfLac66/XfC346sGZo3OXT0AmLWpDsvF9aYg\nRM9J5qKfh/sOTWPrii705AxkdDWYuhmJ6KmuYiTpjF5PzoikJnljUSB6nQu9nlxKdKbDrgn93vHZ\nmrgmFgteR6gwyNvWKHJPKYy66awHwUvy9tEiDk2UAxP0WjP+jB5gdwPtAkmmbm4a8gsHpXUVXRld\nCDfRuhgVUdTNoOJHV1WxLgbdQ0FB6yJtjE/a6m0XjIYVegHUzemKvf50+bq0clMtydA7wNc3RUHH\n7jshBSlNQX8hHViQcD/P6HMSf0aPED0lsElBapuUHKv23kRUJ0NToSgKVFXBmr68QPQoWd84VEBX\nRsfGYf99FBWyLYuc9Guqgms3DuCeQ1MdlU/HbQ89OeI2sbxB82DexipRN72FSW/eje7IBbf3M4J8\n9Hj+ouD1AQbVAEfS5qtNwTbwWnekdQ2XrO6NNE6n+578XA97Cj0+RxV9n/XnDTRNS/xOGdFbUYw/\nO9YrGcx3KvSEvUuHwoiEWC5e1YO1NgLTldE7rou6pgpVZhIvoaCm1hXr/Ihet1ToHQ6gRl66phd3\nvu869OcNfPnB4wAc78htK4q488kz+PB39obuNzJ1k9KsJPN5AIQCJbdWCM+x6F5aqLWwbsBvweAN\nudAjtsrWAKXjX7lkDIW0LoRQKLfKGZpo9u0Y7cbR6Qoqtrox+fORCigBLd776/dfsAV5Q8Nnf/oM\nFy201xDKacmy5vRCzTWnb+icPdJsSzN6nmtQb5n4p/uO4vrN/qbFpuECjs9UQy0WjtsN8d6cwWeP\nE+Zt9H6ZTdAyLTx5akHQNgHeAFlO1c3zGWMAxqU/n7RfSxymxUKhf0Aq9CwHdYhb6FGXM0yMxbSY\nhOZ1pm7Sg+22VwjuyFalGzhvBCB6Mambmuq2V/B6qrgQPdNfwOmairdeuw6/ODYrBp6tCKVTiiC5\nW8CxW3jzNWvxk9+9wQWtRwVRH6pNE5uHu5BP63jzNetwx3uvxUAhjUePz4m5klxMfnTbYi4UodOM\nHr2n1jLFtaZz67VqiAojpKvuDeoiL7e5ukD0QoSA5Kg223jk2JzYEL3UE4fWFT6jl0lpLmQiCQIF\n8E2r1Gh3fG4pBKIXgRbTBtSbMzoK/dDvHZ+rugrOoCSSnlNO3XT/znB7BdtHL6RRsH2kiKZpBYqG\n1NvBCrFhIRcgKU0Rz1XQDIeiKLjjvdfizvdeh0xKjVnoBYix2OchqMOua4o473ERPd1OMokm+9Tp\nBXRldOH95g2B6NnXhjGGI1MVrB/MY9NwASdmq66ZWXmtTYrozVd58hq1JwG8M21oKvrzaW6cHeKj\nd67Uza89dBzv/vqjmKs4qptB3zVVbkBTFfRJ1MSUTXUi3ymKNf05kdQs2sl6VyaFh//38/CSnX7f\nyqjIS+qMxAKhuH7zIKZKDew7E06XAoDjAYWejEgmCVqXvWvufLWJYkb3FUSCukmFnlSwe7vu3tEI\nykduvnBE0NO8MVzMoG0xzFabMC2Gs4t1n3UH99NbDG2GUQK5baQIXVVc6whvFHXet+h3TizUBbpL\nRfpIxDyqN/ryhtjX5qst11ymN+RZ3Ipt+B4Uj5+Yx1hPFkPFjKDaDcVUqKQoeuhwDx+bxVhPNjA/\n6ZGuORV6mzzrZ9bQcOuuUZG00zn+1Gt34c3XrMWXHjiGP/nu04HHIivE0zqS9Pd0ZXTMVps4MVPF\nhqFwOmYmpYkGXKf5PMBT6M3zQm+4239sQ10Z/Pz/uRG32qJ0dK/Laqw7RotgDNh3ZhFT5YZoqJLg\n0ESJf/6Q59nozRu4afsK/PTAFBZrLbHP9hccRK9s+9fK96Zh5+00shM0o/etR8YxXW7i3Te40TyA\njzuZFnP5iFI8dGQG/3z/MbxgxzAMXUU+nRzRo31nWtpnD5wtod6yXIVe13Iiev8dQlGUdyiK8oii\nKI9MTQVTOCzGXH5d3uD2AgyWRN3sWOiVHeiYH4f774nrK28ipv0dQAwfPYmqFTSjR11UuoG90r9k\nTRBLjMWWL6c4POn2VHGoo5zeGpRsvebyVShmdHzORvXiIHoA0J3VfYszdc3iHLscqqqIxXLXKqfT\nsnm4C9/+jWvwvuduxBuvWgvAllOP8ZC12u4ZvXQcRE9XXckfzVc1PfN+UUEUgk4xe54KPUL0NFWB\nokQnQz8/MoumaeG6TVwZjRd6MqIXLiQiF3rnQt3syabAmD9xCgtqJkQhekRZ6c6lOiqh0usn52oe\nc+QARE8ykPdKjIetO2TREYYI0+B60JxePUYxIIc8t5jSud/ZSy4aFfLn3ljTn0fW0DDYlU6E6Ckx\nET1uVs/Pb9znB7A9tuxzvffUAi4YDRZiAfyI3lyVy46vHyxg83AXGHOjHPLznXRGL64acial4ZI1\nPZxyqCqhYiydrm0nw/R/+fkJ/NCmj20dKYaqbk4uNnzUWs5cYWiaJlK6u9A7MVuFZavvUcMxE9Pm\nQ44wRA/gc3oAcM8hj5Jhy8T393LF0oVaC/PVViii14nS6g2ibwcher0BtFQqjGl0wIXo1b2InlvE\njO73Nz1rTejxEJIzsciV90yL+YqPq9bzOb1fhMzpUROjmE1hTX/Oda9z1Ljz+kEJ/tnFukB3b9k5\nis/86iWBRu9hISN6nQTlaKyj3Gjjg7c/iXd+9ZHA9z1+Yg4Xr+aJMCF6ca0IKLpsc3bT4sysh4/N\nBaJ5AC+6enIp/PzIDA5NlpBNaYEqu6+4xDEed8RYNPzxS3bg7detw//5xYlAyi23V/BQN5dQuNZb\nfBwnCtEDnDm9OIVeJqUhZ/uiesVOvJFP62I9oHu9IFG1ZeXN8VnHtoDmnCdsxHA4QITmeduGsFBr\nYabSFPss0U6nSg2cmXebpQOSGIuN6FEuQ3l727Twj/ccwSWre1zUegpivXgFWU7OVfHurz+G1f05\nfPxVFwHgBW1cJW8K2p9kRG/3OKHVDoV42Wb0KBQeb1AU5UP2n1crinJF7G8Ij1MAZA3elfZrrmCM\nfY4xdhlj7LLBQb/xMeDvknmDi5FYMBkT3etOPnrehCYI0WvZkuAUFmOBSQ7gN8mmzSBsRo8WZrqB\nSdqYotRog7F41gS6qsC0k/GFagvTZbenijzLwAs4/22RT+t4w1VrcNfeszg6zWXJ4xV6/tkqKljj\noJHeoPN40coe1+tpXcP7n78Fb79+PQDHN6tTtCyPGEsMRC+lqS5Zd5m6GZd6RhSCTuEUestL3SRE\nT1EUpFTV5wUoxz2HppDWVUE1S6fUkBm9cOpm1rZy0KQ/JwkSeIjix8vhzOhFIXo2dTObEhtVJ+rm\nydmqy/cnKGGW1WTl+SNdVSKUOm1EL4S6uW6ggExKDZzTq8VM1CjkQo8oW3/7uosDPR/lGCykRQMs\nKoKaXZTkBCVfKdVRoYtLfQb4mlSxE7N9Z0u4YCxYiIW/16Z62s/RERvRWC9Rx2VBFheid54KPQD4\n5Gt24VOv2SVEObwRxzpD6zCjV2228cIdK3Dgz1+IV166EildCRQomSo3fPQwEsrxI3p5NNoWJkp1\nYduw1JBtbLznbbjIVRz/+u6DuOTPfoCvPcRpcN96ZBzv/Oqj2HfGMeCWFTfp2IGlUDf5+72WQnPV\npk+IBeDPk6YqYl2QC/Yg1U1533zprjF86JbtQt06KCjJnVxsOGbpHkTvolXdSOtqKH2TFEHzho6N\nQwWXaXrcGV8q9CYWG4K50p1N4cUJEdxeW9QFiEHdpBm9ehtPnVoQNhpynF2o4/RCHRfb53C9KPSS\nUx0Bvn4fm6liutwInM8D+L118wUrcPfTE3jq1AI2DhUCEfwdo0Wxvnif4/fftAWr+3L4wG17fPsO\nYw6S58zoJfs98jofZpZOsdLeC9d3EGKhIFT29EI9NiOLnke5sTNcTKM/b2Dv6QXxHAOcngw41M0g\n2up1mwfFmkTFYzHLVYVn7GMD3OrHQozF9mylfZOe+e/uOY2TczW864aNgQ2r9YN5KApcVP9a08Q7\nv/ooWm0Ln3/jZSKv5Yhesr2D1ospaUZv9/g8+vKGi63SlUmm6BknK/17AFeDm6UDQAlcROVc42EA\nmxRFWacoigHgtQC+s5QPslg0dVNVFJgWT0Di+OgxxvyFXpAYi2m5Ej3GZCECzzHYAhzVFr+QpjSj\nF0QnpYSEEpReu9CjzyfEIpaPnpRE0ALvRfQUxfHRCxNZedOz1iKlqvjcPc8EnpOg6MkZvkJvIcGx\ne4M2pF2reyLflzP0ePYKXsN0KZkJ8tEDbETPfiDTukOLbSagbqZ1rWOhxxgTnc9lt1eQ6H5cWCj8\nWO45OIUr1/c7HUldc/noRalu0iaVNXinnwb+kyJ6N24bRn/ewCfuPtBxXgeIhxoPdaXRldYx1pv1\nUau9Qb93ptLEZKkhkPYgAQ1B3cw4iJ5u05zMEE8vKgDDmieaqmDLcFcgopfERw8ACmnnnMSlSgJI\ngOj555QFdTNoRk9TRGMrrNANipzBCz3y9gryIKOgBP27T5xBs23hiG2tsH4wjzX9eaQ0BQcngwu9\nOJ3T2x49KVCSJIXeSHcWq/pynE4ZOqPXodAT+0fwvVW2DYVFZ10Npm5OLjZ8qIFh73NN00JKd66n\nUN6crgrq5lJDTvyCaHx/dMt2vPaKVcimNNz22EkAjsLk/rOLwgJplQfRo9nzTvPH3qBn3ZukzVdb\nPiEWgO/tvbmUWKtldW+vGItX7GzdQB5vuXZdJApKCf7EYl1Q2rzWHTSn9/OjMxifreLZH/8Jfi4h\nRbQXZg0NG4fcc0ZxZ3wFordQj93QDPwcOycwLYb5Wsvlr+oNQvQWai2cmK2KcyzH7nE+TuJD9DqI\niniDCqPFesuZzwtQ3KR4yUWjqDZNPHxsLrSQ4qIkq6Aq/qZ81tDwly+/EMdmqkJBksJF3bT/mxSh\nlPe+9cuI6AH8XpipNHHWIwwUFbTXyFRtRVGwfbSIp065GzaE6J1drKM/bwTmVYW0jivX8+tDI06K\noqA/n8Z0R0TP5DN6EtPOshg++9NnsHm4gBu3DgX+hkxKw+q+nGg4M8bw+7ftwdNnFvHp113sAlCy\nqc7FmGUxPHRkRjTyg2b0yChdXiPiKtVTxHlar2SMvQdAHQAYY3MAkslqBQRjrA3gNwB8H8A+AN9k\njO1dymfRMHNY6JqD6MXx0as0TR/k6l2IRadTNiKXEL2gwjNrOAo/8oyeMEyXjokuuED0cgZapiP5\nTcVSnE4qUVcBv+ImBad3+u0V5BgqZvArF4/htkc58KrFSBK7synhnULhJOHxpYIpMganDQQJR8gR\nR/GIMWb76IXYK4TN6GlOoZczNJcoTxJEr5Psd7Vpujbj5QrTYpiwF1CAo5hhXe9T8zU8M1XB9Zsc\nQ1vuA+QWY5HvYzlocSfKLSWtSRG9QlrH+27chIeOzOKnMVT4yJ+pYITfY7qm4nu/eR3ecs06H+Lu\nDZedhMVE8hWURMrUTSoIuVG1EoqcRhXLFNtHi9h3dtFX6J4TdTNBwpaUuikXenSveZNxgK89groZ\ns1EC8C5upWEKhbL+Qvi2NFBI4w9fvA0/3DeBX/n7+/Gx7x+AoasY68kipanYMFhw0XFkz1Kvf6k3\nxmer+J1vPSHQpiSFHgVfo/33Xj0G2uLM6AX/faXRdtGlSADES/WcKjd8yaTsO+Wd0QO4+AAXBUu+\nllPIqHfQfnbNxgH86UsvwMsuHsWekwsoN9oiET84UcbxALN0IJkYS73lrLUOddO95s5Vmz5rEIpe\nSSyqbTeUC2k90F4hDhNGDipYJhYbYiYqCEW5an0/nj6ziA/e/iSOz1TxlNQUqgqGkIYNg3zOiGYs\n4zICiLZaa5mxG5phn2MxTs8zLRb5rGTt8YL9Z0toWwz1luXbCx8/MQ9DUwW9faSYwXWbBnDNxv5E\nx0VIzEKthYePzqInl4qkPF65rl+grVGI2VuuXceFWQIKz2s2DuDVl63E5+89gqdOOeqTsgYC5ZKJ\nCz3796woZjp6FV841o3ubPTvlYMYZmc8wkBRYQhEz32v7RjtxqHJEp6ZKmOoK411A3nhRTq5WA+d\nXQUgCjJ5Fr6/wIvQM/YsqfzvaT65YbOv5ELvx/sncXCijHfdsCESONo0VMCjx+YwXW7gH+85gu8+\ncRq/94IteI6nOMynNVSa7dDG9FOnFvDKf3gAr/3cQ/jXX3C5EspZaUaP22OUXfN5QLRtVFDEeVpb\nthUCAwBFUQYBJONChARj7HuMsc2MsQ2MsY8s9XM6zYtRoRPXXmFKmEM7N7DPMF33z+jxQi8Y0QPg\nGvx0DNOdGT25o0sXXEb0AGDOngMQxVIsHz1V0EmemSrD0FSs9Hiq0Hs62Sa8/fp1okCJg+gFUzdb\n0FUlcbIP8N+7c2V3x80ySE3JGy2RXIeIsUQgepWGU4gLRK8df0YvralotqOPT54FS0oBiIrx2Soa\nbQubbXU8PYK6ee9BXlSREAsQIMZihquNEg1Ynk8AkiN6ADdLXdOfw//7n/tjKAxyyeVOghir+nLI\npLTYqpsUtOkGzVVVGg4aT53Gok3vMkPQBUryoxC27SNFzFdbLl8+gBK1BAWSh7oZNwYLGcxVWx1n\nS8UaKH30qr4c7nzftYGdUl2TqJsJkuB8Wkel2caM3f0kae2weNt16/GXL78Q89UWLl/bi394g+N3\nuWm4y0PdtL3FUlpHMZbbH+ONL6K1LqXQS6nh1M3OM3rhiJ5pMdRapgs1I2TOO18+U/Yjeo4Yi3tt\nG+3JIqVxUY9yo31uiJ5B3fhopdKr1w/AtBj+4/FTgtJ18GwJJ2ar6Msbvi63M5LQOV1565cfxu98\n6wkA4dTNKOEQbibuUDc1VbGV8aLFWOKEoavozxuYKNVxar6GQloPHNm4an2fy3dQppgTIySb0kRR\nQk3fOM0EgF8bWueTNIi8QcggCVpEibEoCj+PchE050H1Hh+fx/bRoqDfq6qCr771Sty4bTjRcdE5\nLdXbeOT4HC5b09dR5O+WnVxoJKrQ01RF+J8Fxf9+0Xb05Q38wW17xL1qMQdcWPqMHv89UUIsFLfs\nHMEjf/g81zoRFX05Aydmqyg12i77gqgQqpue77hgrIiWyfCzg1NY1ZfDaE9WUDfPLtYD5/Monr9j\nBXKGhjX9zm8cKKQxXW7gzEINg4W0616l/K7SaHPVWOFv3cbf//QwVvZm8RL7mobFO67fgPlaEy/9\nu/vx0bv245adIz4bBoDnhoz5c4f5ahN/9B9P4da/uw8nZqtQFQfBozWH/rxnfAGMwVfoxRnZkiPO\n0/ppAP8OYEhRlI8AuA/AXyT6lvMcVqdCT1FEBzOOGAsVetskyVjvxweJsXDVTfLRC0D0UhpqLfeM\nni4hIfJGXfEgetQRJ38QmnOLRd1UHXuFZybLgX5ZusbnhzqZz28c6sLztvFkLc6GVczyoVH5fJMt\nRNKhfYAbsn70FTs7vi+OvYKTXEsLQRzqpqaKRDBnaGjbw9stk8VX3YwhxkIbmqqEi4QsJSihJd8r\nI4K6ee+haawoZlyKYpmU5pvRC9v4qRkgCrzU0hA9gJ+z33vBFhyYKOF2m8IVFnEVaSk6qm62TVcS\nOiwQPf95K9mbSFrXRBLblUkJP8+gEIheBHVxe4AgS8vkw/ZJzmfxHBA9AC5fwKAIs5jZMdodmDhp\nqkPdTHI8eVuMZUb41nUmmrzuitW4/wPPxWffcCmeu9VJBDcPFXByriY2WiruRrozkTN6jDHc/ji/\nF6dLDTDGlojoqWABdh21piWSkdB/GzGjJ0YAJGTboTQ69+5MpQGL+VEDamh6aemaqmBVXw5PneL3\n4lLmrSmyKQ2KgkjjbIBL1qc0BZ/9KR8d2DhUwIGJEk7MVnxoHuA08DpRN8dnq7j/8IygetG6XJH2\nj2bbQrnRDkX0MoZDxecsEUWIe8gRV8TMG0PFDCZt6uZIdyZw77xoVQ/Stqlzj0QlBXgim01xWXtC\nbYhqHHdGT1EU8fvPBdEjGvUx24ex07NSSOs4Ou2oHLrEsEwLe07OC9rmuQShyc9MlXF0uoLLQ+bz\n5Hj9latx1fq+QFP1uNGdS+FPb92BvacX8YX7jgIgMRb+98/a0I83XLW6I4vJG/R74qB03B84/jXt\nyxuCqZWUuull2eywLXHmbEGlsZ4sZitN1FsmJhYbkYXkaE8Wj3/oJlcjur9gYKbMET2vGixpdJQb\nbaR0B2y499A0Hjsxj3dev76jzcgV6/rwlbdciflqE1tXFPGxV+4MfB4JpKE81LQYvvHwCTz3Ez/D\n139+HG+8ei1+9Ds3iByZv5fEWPg9TrTki3yI3jJTNxljXwfw+wD+EsAZAC9jjH0r0bec5zA7SP07\n9gqSGEucQk/qwng3IK5cxlybCPfRs98fcOEzKU0kNJZA9FSxIbmom4To2Q+F16tnsRaf/qhJlDGS\nFPeGTOfptBG9/ToueNLJyBdwFnG5s7lYX3oHePNwl6t7ExZx7BVa0pwkhbyBZUKUpPiMXsv+Hv6e\ntsWSIXoxxFgogV1RzCwrokf88k2E6IXIrZsWw32Hp3HdpgHXQhZE3Qwt9DziK15kL2m8+MIRXLSy\nG3/9g4ORPoRkDh036HjCET0Toz1Z8TuouxpI3ay3BWqWk4bE+axsiI+e/XoUHXrLiiIUBS5BFmF2\nnNBHjyKJ+AkVAZ3om2EWM2GRWoK9AsAThkpDQvQSzuTIQc8CJb/lRguqwrvDUTN6jx6fw/GZKjIp\nFdPlBipNE6bFIlGKoJAtbuSIg7Y4M3oBhZ5EI6YQ+410704uksF0iBhLAC19bX9eIC3nguipqoJc\nSut4zrKGhl2renBqvoaujI5bdo7g5FwNB86WAgs9RVFsAaTodfaOPWcAQDSvyEdPXnPJCzZoRg/g\niCx9D1kUFQIKPc6YSV4kDRfTnLoZkLxSZFIaPv26i/HZN1yKwULah+jRXpVP6xjtzjiFXtPs2Eyg\nIDTuXGf0AOCobZreafzEu47LoyD7A6TnlxrUrPjxfq5QG6a4Kcf6wQL+9R1XixK7IdIAACAASURB\nVPOy1Lj5whG8YMcwPvmDg/jKg8dQrrfFfTLak8Wfv+zCxMU15Yxe24flCFl9Ni5100H03Pfamr6c\noJau6s2KwvHwZBkzFb9AlDe8ip8kGnZ63u2hBzj5XctkMDRHCfzLDxxDIa3jlZeuQpy4Yl0ffvJ7\nN+C2d13tU9amoM+uNk3c/thJ3PTXP8Mf3PYkNgzmccd7r8OHb92B7mwKRdu/kTEmmkuE6O0en8f6\nwbxvfV126qaiKBsAHGWMfQbAUwBuUhTl3J+qZQzLik4qdNsw3GIslo/elO3d4Sr0vDN6gdTNYA8p\nipxkkh2M6PnFWOih8Eo4J7EoSEk+eov1YIlomhHxDosHxRXr+vCFN16GWztA3ICTAMj0zcVaKzH0\nnDQ4omdGCncIo29pAaX7I62rod1lQzIMp4fctFgiMZZYiJ69Ua/szYkGwf2Hp/Efj/vEaRPFoYkS\nxnqyYnFNacEqfHtOzmOh1sJ1m91qtxnd66PHIqibnhm9c6BuAjx5+8DN23BmoY4vP3As9H2LtWSI\nXudCjyMrROcmOklQErkg3d8FQd1McQn9MHuFgKaDNwppHWv78y5Er76EQq/govElR/Q6F3rha2BQ\n6KoqisMkCSRX3TQxU2lCVRAp6tApSBnvgI12VxomCmkdXRndhex447bHTiGb0vCiC0cwU2kuWWgq\nqPhijMVCW6J89GQasfgu3Y/o0TUNQ/T4M+6+Nqv7csJM/lwKPYDTueJ8xtXr+dzVpWt6hUnzdLnp\nU9ykCFMzleM7T5wG4FCsHOqmsxZQcRGkugk4jV/AMUUvpPVAMZalIHrDXRlMLNZxer6GsZ7wxPcF\nO1Zg20gRvXnDhXzVmqYrwd4gKW/WW1ZsRgAheknWDd9n2F63grqZjS6SaL2iQlVGKh+3peejVEvj\nBiXP9x+eRjal+cyyz3f86UsvgKGr+NC392LdQB5vuGr1OX3eWE8WX/y1y/Cqy+IVL0miX8ohvWbm\nYUFrnHdeUFUVbLdzbaJuAsDn7z0CxjiimejYCgaabQvHZ6q+WVbDQ+OkkYdjM1XcsnMkUV4y1JUJ\nLfIAp7n286OzeP83n0AmpeHvX38JvvnOqwU7ByBPvDZqLROMcSpztWmi2mwLIRZvnA8xltsAmIqi\nbATwj+CWCP+S6FvOc3BEL/zvNZsy5aJuRhQAk6UGdFUR1DYgWHWzaVNaKFxiLEHUTYlOSDRNVZrR\nk9GBatOL6PELS8l/HLEJcew2oskYH2YOQqpStvR7HERPURQ8b/swumN0rSn5krtwi/Vo75zliJyh\nieIrLNoiufZzuMNom4CbXkbva5m2N0tMRCKOGAtt1GO9WTFj8bl7juB3vvWEa54oaRycKLtmCrji\nn/9Y7j00DUUBrt044Ho97fXRsxIgeksUY5Hj6g39uGHLID7zk8OhBsGlejuRQEQnH716y0RGV7HK\nVnakLmNQoTdTbgp0ie6ProzumpX1BiXpnRDh7SNFF6JXt8VjlizGkgBdSIroxaVmy8VtJ9qMHAV7\n2H263EBf3ug4jxkVa/rzMHQVh+zniiPCKY7KhCB69ZaJO/acxs0XrMCavjzmqy0xRL8U6ibgLvRo\nPe5kZh0k5kVBxYqruLe/qxlQ6PlVN3lDqmFavuR+rVRcnet6XohZ6F1lJ32Xr+1z2YEEifwA/LdG\nIXqHJ0vYd2aRCwLZa2yj5ffRo7U4jLqZ0lWhwGtaFnRNQTGTQtk3o2d1bKQGxXCRoxTT5WYsOfu+\nnNuOqdpsI5dy7oENgwU8M1mBZcVrJojPtRP89LkgenlC9GzqZoc8gtgRZKkkI5WPn5jDQMHwaQ4s\nJWhdbLQtXLKm55zmEJcSw8UMvvDGy/Cp1+zC937zOmxMSNUMihu3DS+ZPRMVBBYoCpLP6AXkrFT4\nrLKpmwBvwGweLsRCVuUgr9a2xXy0Ute8nqa4zs0rL12J5Qza+++xdQ6++KbL8KILR3z7YjGTwmKt\nJdabNfZatnt8HtPlJi4OLPSWf0bPshUyXw7g7xhjvwcgmXHKeY5OqpuawoswM6a9wlSpgYFC2rXp\nhRqmt72FHgt8P2BTN+PO6DXciF7BHoSmbhaZ1MZJbnQpEai3zMDEQbeT/fYSqSVhQYu4jOjRjN75\nDFpMotQqKQGQ6WJ0f0RtfEGCLabFOL0pLqKnxZvR01QFw8WMaBDMV5swLYY//vbeWDYD3jAthmem\nygLBABxPSG/cc3AKF451+2gpmZTqslfgNIjg360LRI+sGVQYurqkrrYcf/DCrSg12vh7e17HG0ln\n9Mj2wTs4TVG3LQxW9eWgKo7CY9B5m600RceTGjXFTEo0XIKibVpQlM5zr9tHizgxWxWIPhWmSTqR\nhYyfxhcnaAauU6EXZjETFvLzl9RHjzFgfLbWUYilU2iqgo2DBRyccKib+bTmMmX3xg/3TaBUb+Pl\nl6wU9wMlr0nXt1QAdTMuLZf2vtjUTT2AummzWLyIXsqe3W4FeISukaTYzxXRe/72YTxnS7CkuRxX\nrO3Db964Ca+6bCVW9+XEKMaasEIvQlEY4HYbigLcsGVIUDYFdVNCcqmhFEYvlambLbtZysVYPIie\nufQZPVru48xEcUTP2XOrHkRv41ABtZaJM4t11JrxfTgFdfMcEL1sSoOhq0JOP86MHuDMKckF7O4T\n89i1qndJ8/7e0DVVJOdXrE2GIi1XXLm+Hy+7eOyc98fzHbS/ecVOoiLIMJ3iWRv6kUmp2DhUwHAx\nA0XhdmWvv3JN4msrU/hHeoKpm/T/Kc9b25/DpWvOHRWWg9bcB57hOgdhDZpiVsdivSXGtVbbo0k/\nfJpTiHet8h/X+VLdfB2ANwK4w37t/GbpCUKY80Y8GLyTztE2R4wl/DNJZrqQ1sVGEmaY7p7RCxci\nAPgCR1QrZ0ZPcRViFEIO2b4RaRBaIHoJEAvqkjfavJALShyI4rIUVbCoCKZuts9peD9O0IId5T/X\nFiiKlGiSSmTExid3MymRb5nJZvTiUDdnKy305gzkDU18/nythUJax4NHZnDnk2difZccJ2zFTZpJ\nAkiIx30si/UWHh+fx/WbBr0f4RNj8SryyaF5Cr2soZ0TmkexbaSIl1+8El964JgwEZYj6Yyerqmu\nWTFv1FsWMikVb75mLT75ml3i9wQiepWGg+iJGT1urxBK3YxBmQYgKC77z3DkSRR6icRY+LMXp7CU\nI61r6M6mOpqmO4bpcRG9YHuTTkEb6YnZaqS1QtzYPFwQiB5RNwsZf7JOcftjpzDSncHVG/pFF5mU\nDDvR0bwRhMrVYxbxUYgeFakuRC/ASHyq1EAxo/v2Bpe9gu6+nmulWelzsVcAgA++aBvecu26ju/T\nNRW/fdNmDHVleHFuMxNWh1E3VSXQnxDge/V395zGVev6sbov56NuViXq5pzNSAkaewDc1E3TZEip\naviMXoJmBoUsET8WYyaqL59y+e5WpRk9wFGJPDRRSuTDSb8/SUPGG4qioC9niDGRfIf7m9bxjUMF\ndGcds/W5ShNHpivLIsRCQWtjUhTp/29BBX9cIRbAuWeCEL2btg/j0T+8CQOFNAxdxWAhjWxKw69c\nMpb42GRRLh91U3fvNd3ZFBQFeNVlq5alWSAHPW/T5WbkDGlXhouxUGOJmBI/2j+BtK5i64gf2U3r\nWqJmS5x3vhncMP0jjLGjiqKsA/DV2N9wnoM2t0hET5VVN/3omTemSrzQUxRFbOB+6ibfAL0S1ZHU\nTUmMRT5uVVWgKh57hWYbhq66qExkUgkkm0GiBJK6u4GInr0htpdILQmLwEKvfm6+S3FCUPEi5mvo\n2snJpapyA/so6mYQokfqh8tpmD5baaA/bwg54lrTxFyliZddPIrtI0V85M59HZVFvUGJ7Gap0CMJ\n9SNTZdz2KFcQfODwDEyL4bpNA77PyOiaoJUBthiLHnzPeKmbq3pzy0KzAYD3P38zAOATdx9wvW5Z\nDKUl0INlsSRv1Ns8GVrTn8dLd41J0u3uJNK0GGYrTbHZ9GQNbF3RhQvHuCVIWNLZNq1YSLqjvMlF\nMOh4k9Bz0jovalOamnhzi+Oll1SMRU58E4mx2M/FqfnaOQmxUGwa7sLphTpK9RZKjTYKmRS60joa\nbcvXlJkqNfCzg1Oi+z7Yxa83FXpxaO1yUINJLtZqzXhFvKJwVkgQS8VRb3Y+Qw+gbk6WGsIb0nVc\nkrq0F9Eb68mK5/tcEb2lxpbhLqR1FcMhgg0pLZwiv/f0Io5MVfCSi0ZtgSl+vulaN03nuhOKFCrG\nojtCS6Rc3ZXhgmAy0sobqUsTY6EIE2ORozdnwLSYmBGsNk1kJeomFXp77Xnf2NRN+/efC6IHOAVj\ndwz1bXrO1w3k0Jc3MGsX3btP8vm85Sz0ujKcObWcn/k/MZxCL/5eTntmkIWDoiiu12++YAXe+ez1\nSwIEBqS9YLQDotdfSOPb77kG77h+feLv6RRyQRt1PxF1k2j2JCx1fKaKC8a6Q5ufUVY03oijuvk0\ngN8F8KSiKBcAOMkY+2jsbzjPQVTJKLU6TVVgMgaTMag2VTJqRm+q1BAmpQM2lcW7FqX0sBm9CB89\nI8BHzz5ur/R6rWn6Ol19eRnRi1/o0WZcFoVeAKKnqmhbFswlUkvCwlvokTHt+U4M6CHbd6aEd3zl\nEbz/G7vxF9/bh8/d8wxuf+wk7jk4hQNnedHjTbBTkpFmUATN6FUTysPHE2NpoTefEt9RarSwWG+j\nP5/Gn750B84s1PGZnxyO9X0UpLjpntHjBchXHjyO3/nWEzg6XcG9h6aQNzRcEkBn8HrORdkr9OYM\nqBKP/zeftwn/9uvPSnTMYTHWk8WbnrUW//74KeyT5tYqzTYslpzekE1pgrblDT6jJyfL/BnxJpHz\n1SYs5lBbDF3FXb91PZ6zdchWNw1T3YzX6R/qSqM/b4g5vbiojxzkTbUU5bzBQpxCz6avx/x4eb1Z\nCqJnWswlDrDUoObHockyyvUWCjZ1E+AqaDf/zb346QFOp/n27lMwLYaXX8w7zgLRm4wnGe8Nobpp\n+qmbcZJw8or1RjlgRs8IoG7Ke54cNEschNo7hvNL80RdjnjPczfi06+7OJTRQ2tbUHx3z2noqoIX\nXrACmRS3yWmblmsNoObofLXlonp5Q1ed9ZyeZTrn8oynyRiWAobJiF4cFIUSccoXqs22S5CnP2+g\nJ5cSqqnZDnOgFL1iXTu3691naw7EaYiQ8MTa/jx6cg6it/vEPFQF2Lly+YqyFd0ZXLqm97zMtf1P\nimImBUP3+zFHhVPodT63f/LSC/Bbz9u8pGOje19TFZ9ip7zn0fHsXHl+5jHl/D0a0dNRaZpCSV9W\nEO707+JGx3cqinIDgC8DOAZAAbBKUZRfY4zdE/tbzmOYMRE9QUtUFNtXL/zzZipNMaswWEhDVfzC\nAmm70ykn64xFCxEEFXqUMHJlUHlGz/RB3L15QyS0C7UW1g/Ek80lFJM2nEAxFuGjtzRqSVhkUhrS\nuioKPWELcZ6pm/SQffSu/Zhc5AjtVLkRWFx5k2RDVyMXerkrlBPIIb+u6ZidTkqgGGOhHc3ZahOb\nhwviO87aRtk9uRQuW9uHl188hs/fcxSvvHQV1g10tpwAuIeerLgJ8AWvXG8LSt63HhnHPYemcPWG\ngcAFUFaozKd1juiFdKlXdGdw/weeK5S5UpqK5dxD333DBvzrL07go3ftx5fefAUACKpd0nssEtGz\nqZsUdA94k0hC3IMQpiip97bpVzUMCkXh5rtU6C2FugkQXaTV+Y2eGOxK4wm7kx4WURYzQSHfO0nE\nYeSEIY6HXqegudWDZ0sSdZPfQw8fm8W+M4v44n1HccOWIdz+2CnsXNktKNB0vY9OV6DFoKN5g4pd\neRRAzOjF+Cy+p/nvrWB7BT91c7LUCOw60yyxxVig0uKa/hwqjfay057ixobBQqRPWFhzhTGGO544\ng2s3DaAvbzjNq7blYlqUG2302g3W3lw4+sTVSW3qpk1JpPWn1GiJgobP6CVPKvvzvGHWmzNiFSFU\nkM1Wm1iLvI+6qSjcT+9JKvRi3q80C3su1E3AEbWJ0xB5xaUrsaI7g/5CGn05A2cX+T74+Pg8Ng93\n+VQczyX++tW7AvUV/m+4Q1UV/PObLk9k3UD3TFxT9qVGSlPRk0shl9J8oIUX0TufQUwsTVVw4cpw\nBVdiHk3Yc9K9eQPd2RQWaq2OlM+4EeeMfwLA8xljBwBAUZTNAP4PgEtjf8t5DELmolAobhhuifkz\nTVVE19kbsxUudkGJw2CXEZiwpDTVdr13EkOLsUghgmxKQ7PNj0NQN+03ejuy3g4cYCtpCepm/Bk9\n2liIxpMOEWOJ66OXNLqzKSxUk9tCnEvQxnVyroZ3Xr8eH3zRNjDGUGq0MV3i6mXT5QYabVNIdlOk\npKHsoHBTN/k1IAplEh89gCNCXh8YCp5cGKLgp1k0EgT4wM1bcffTE/iT7+7FP7/p8ljJ1sGJsktN\nFuDd6JbJBFLz1QePo9RoC79Eb8hJEcCTl6B7iiIJvSNp9OQMvOc5G/GX/7kfT51awAVj3eIeSypB\nnE1p0aqbKT+i5y3cpoWnW7CFSbUZQt206V5xYvtoEV964BhapuUgegkLvUJaD/2tURGPunkOYiwh\nFOCgkE3Al4O6uao3h0xKxcGJMsqNNgrplEgiHznGjWvvPzyNnx2cwtNnFvEnt+6QjkUT/pL9eSNx\n4ePMjgfM6MW4tmHWHdVGG4ripm7SdxEazRiLRPRaJt+zghDgWy8aTWzk/MsMPmLhPy+PnZjHqfka\nfsemf8vNq4YkyER75ly1Faq4CdD5t8VYbBo2iR7Jc3pUBCYNXVO5QFwx3n1OdkwC0Wu0fY3jjYMF\nPHqc39fxZ/T4mhq3oRn6OQkKvbGeLF5tWwRQs9uyGHafmMOLY1g8JQmvGNH/jfC4ZqN/rCMqHDGW\n81voAZxhEWTh5bJXOM+qqrRubxnuirRhIGSOGvk5Q0N/wehY6H3h1y7DivfFO5Y4ZzxFRR4AMMYO\nKory30+MJWJjVaXZGNWeZwijc5y2k2ny8rh0TZ+g+MlB3U3ZlNtizkYdNqMH8E6tF4n0Do1zg1M/\nojdfa9nc+6XM6IXP82g22rDcqpsARHcCABZqhLacbx89/vmZlIq32QWLovAuazGTwnq/xogI7p8V\nfm7lBYI691U7KYs/o2cnW+3gQs+yGOaqTfTlDfEdp+cJ0eOb5FAxg9963ib8+Z378KN9k3je9uHI\n7yTFTe/c3f/X3p3HS5JWdcL/nYjI5a61L11VXV29VC/VTVd3U93QQgsNNMLLJmijqIArH1FxGUaZ\nFwbF0ZlX31EcURlFxUFfxWWGTT/ugoCCQMu+NA29Ub1U115199ye948nnsgn80ZmRsSNzIi48ft+\nPvWpurfuEvdGZmSc55znnKqnz/3pRd2QwezrCGvEAqyfOddsd3o6OU7a0w/vBP5GB/U37N/SzejF\n3Adar7qhXTeVUlhrdVCrrL9Z7g/0zizqG6udITfNFddBWGdE/XUUKlEDvUvm0Wh18MCpJSvrE+85\nO1f3evbNRrVrroblRtsPhMJ/v+0hDanC9IxXiJXR637/jQ4sBvTrxFW7Z3HfEwv+z+cGL8L3PHwu\nqHp4/Z9/Dp4jeNHR7k2m2c/9yLmVRGXpbsjCQZxAz3XD9+gtrrUxU/V6Ak+zsm4yUItreoZTWBBh\n9qK3Vfj+43HM6EqTboC0/jn9l597DFXPwV3+NdNUuaw2232lm/rf55cbQwe6m+ZsSnXHOJnnh93M\np9VRQ7eZDHNk33zk5hfm+XB2STdkWW621y1e2uX7UQO9NAamA92MY9zZl3qPnm7CcnG1xb10BWKu\n7cMW0dPyfU87FPr6NMmMnusItkxVcOzQ8G6e5j7+cT/Qm6152Dlbw8WV5tDS2D0R5xcC0QK9e0Tk\n9wD8f/7b3w3gnsjfYczanWgZPVOy5/mNTwZl9EzWZL//C/72Jx8Ina9hbvTsFsz2HL2w46lbZX7r\nM3q9e/SW18IyehUoBZxZXMNyox35hsKsmC+u6Ru7sNW4iitYbXbGl9HrK90c9x49c5P/itsOxl6l\n+x/fcdPQG8ewZiwrCfboAbrDW9h6+HKzHewzmwoCPT+jZ/3uXv1Nh/CnnzqO//JXX8YdV+8cmB0E\ndHfCRquzrtzC7A89vbiGF964D3/3pROYqbkDhxDXvN5ArxGx7HBczIXSZPKSlgfXPSc0y2VKuaZC\nA72+0k2T0Qt5/JjFlDC6G1+032HQkOXxC4masQA621lxV2N9DoCgRPjexy/i2KHwznTm0ho1qeUl\nXGW1X8jTKN0E9D69f/jyE/rr173ge9x74iJuvnQr2gr43PHzuOvInnXXCBPoJalW6DYJs/dp+4+7\nCDdGniNoDhiv0P860m0kpL/+oGHpQLcksa3Uhsv1smCaydjaHYW/+vzjeNY1u4MFvVqw71iXbprX\nLFP6em650dPAqp+5npvtD/WKBIsEPXv0NtDs7PdedSxyptgEUueWG1hrdaDU+seRHejFHpi+weu9\naeoS9z5g63QFq80OPn7/aQAInTFG+WSqNSaR0fvup1wW+v7+rpvj9sc/+JSR+xjn12X0PHz/0w7h\nwkoztZL4KL/x1wL4UQAmSfhRAG9P5bunIFg9HnLxdB0JbtaCZiwDVtYfPadvpg9sDb/JNcxgbLsF\nsxoxR2/KyoR0/IDKnMhK/x69RntdK+ftfpbgoTN6/kzUG4puM5bBN4V6BEUr9a6bgL6Ym9WKSZVu\nXrJlCr/zyievG/YdxdERLx72zeh0ULoZL6NnvsaghiwmiKpX3CBzYQI9u4So4jp48wuP4NXv/CTe\n++lH8Z23HRz4Pc2Q9cN9NywV18HCagsLqy3s31rHr959FI712OxXt26KAIR25Jsk81gyAZ5ZQY/d\njKXqBoORbd1zYb9IrJ97Bug9eo50s642/RwflNHrRN4be8VOPdz7y49dDG6U4pZuvujoJXjkXPyb\npGN+c55PPnR2YKAXf7xCsq6bvc0l0im5unrPHN7z6UcBALO1SvDcUwq49pJ5XLNnDp87fh7fFtL2\nO+i0GrPjJtBd7Q6boxfl3B7YNt3TkMhYbLTW7Ynpz0afDIalh3fdNCWeVbd4DSr0vtje59wnHjiD\n04trPRlZu0qh0epg+0y1J9A7v9wMfU7b3wfQ56/V1uWZ5vpz0doL29rAQmrUhSBAV5pUXMHZpe7P\nMNNfumkHehGzLPWKi9uv2DF0z1EUdtfNOExJ6gfvPYm5mjd0fybli7lHGFbGOKljAMaf0QOAG/aP\nfp6Y+5fHL6yg4gqqnoPn3ZDuqPKRv3Gl1BqAt/p/cse8Lo5qxmJe1PQePWdg181Hz69gtuaNLPsK\nz+iNnqMH6BfwVt+Q9/5y0uVGa33XTf8i9y9fOwUg+gwTcxOxNKTrppnxNZaM3nQF9/rlr5NqxgIA\n33L93rF8XXOBEOne/JsxDtWIN6pVL3qgZx43/Xv0jG8+vBPX75vHOz76AF5+7NKBix5mtEJ/Rq/q\nSbC3bOdsDXdeO3xwsXn8rFmlm1mu9s/VPIh0H1tJFxPsOZe2sMHV3oBA/fSi3lcZ9hxyncGlm+bm\nMArPdXDt3jl8+fGLuOnSrfAcib06+ZKb4s8nAvReuCt3zeBTD54Fnhn+MUFVw5jHK/Tu0Usro9d9\nbsxYpZsAcO3eOXzHrZdi+0wVzz2y/tpiynWTVCt093yub8YybP+r8cxrduHX/+lrOLvU6Mk0Lq21\n1t3gm+dqw/9eJ4dl9BLun8yLiuusG0Hzl59/DDNVF8+yrnPBNa3Vxlqrg11zNTx4egmLay0opXB+\npTlwtIL5PgDQbJmGZk6QLUxjj15c9txdswjZH8zt2zqFmudgrdWJtVD07tc8dcPHF+zRGxI8h36e\n/9j+2P1ncNvl24cu8FO+PP+GS1DznIkEWIP0ZvTy8dgx98InLqyOrVHNwN+4iHxBRD4/6M9YjiYB\nswI67OLpOhKsSroicB091DTMI+dWsH/r1MiUqbmw2xk9u3QzLNCzOzS2+5ov9G+mX1prB117DLMR\n+g//7WHM1z1889VDNppZvP6umyE3DibQbI3hhaindDPh/qk8MReLqusEQXTsjJ7VjCWMyZb1Z/RE\n1jcZERG85puvwAOnlvBP954c+D3ve2IR+7dOrbuY2PuiopS5Bqvf/l6WZqsTa7U5bY4jmKt19xaa\ngC9uRq8+oBlL91ysLzHsb4BxZnFtYNChy+uGjFeIsT/tyCXz+PJjF/35WJPNtNx2+Xbc8/C5gUHr\nsKqGMF7CrpuOo+ddVj0ntXIgu7HInFW6CQDX7p1HzXPxoqP7Qm8wNxTohTVjiThHDwDuvGY3lAI+\nct+pnvfHKd3cPaB0M/h3hs/xpMy+SqPZ7uBvvngCdx3Z0xP41D27dLMdBMtLay1cXG2h3VFDm7FU\nrOu5nokZPl6hlXCOXhJmP5u5pvXvjXIdwRV+RmzS4wS2J8zomXOw1uqwbLNgjuybx48963Cmx2Bf\nwzbaUCgt5j5lqdFetyiXlmE/6QsBvGjIn1ww903DVnbsPXqO449XGJLR2x9hNoh5AezJ6HWGd5wz\nF1M9RLW/ZKl3tT80o+dfHM8vN/GSm/ZHvjib7xPM0QvZx+W5pt0/Un8h2jJVweJaC612BxdWmqhX\nnKF7yfLO3CjpgfZ+CW/MPXrm518Laf4BWBk9r9sB9OJqC1umKqHZohc86RLs3zqF3/3oAwO/531P\nLPRkLPp/HiC8iUi/daWbnWz36AE6e2eXbta8+I8xPV5h/fnongs7o+dnYFrrSzcHlRF6jgxcYGp1\n4mVFj+ybx7nlJh46vRSp/X6abj20HQurraAUuF830ItXuuk6EnuFfqbmYWeCLpeD7N86FTzfZmt6\nhqX50tcM2aMFdLOKaTVjCcskD/Kk/VuwY6aKD321d6HHjImwrS/dXEXVicIH1wAAIABJREFUdUKP\nuzLhUqe0eX179L7y+EWcX26ua1zV03Wz1Qn22C412jjvD0sf2ozFKt00+22nqy4c6W3Goitm0vnZ\nRjEZvUGlm0C3fDPOHM40XLt3Dj/yzCt7sqpRmPl7AHDzweFNLoj6TXqPXhT2gnSUGYNJDPxJlVIP\nK6Ue9j/mCevtk9Dz9HKhO15h8Me41jBTV3SwF9ahDAAePbeM/VtHB3pBRq8RntEbNEcP0C8m7U6n\np/uW3Z6501H+3Ju+jJ61onj3sfUNYgYxNxFDSzcdCW5o05yjB3RvfC6utnBxJXq30LzqzeiZQK8V\nvC/O12i0B7fzB7pzCM3976AuZZ6rO8h95bH1+3QAvXr/wOmldfvzgN4ShkgZvb5mLHqPXraXhPm6\nnTVuxh6tAPgD00MzeiGlm+bGPE5Gzw1vmAH4pZsxXniOXKIbsnz6G+cnntG71d+b96mHzob+/8WV\nZrxhrv7PnaSUZrbmpTJawXAcCUqbZ2puMFx+35b6yOHOG8nohTZjabZRcaOV5TqO4BnX7MJH7jvV\n8zWWQvboeX2lm6cW9JzRsNesPN4YxVHtC/S++Ki+Pt64vzcb1A30OlhrdjBX9+A5gqW1Fs75o4GG\nZvT6Szf9Pc6zNS9YYDUdOSee0RtQugl0y/jjzn3cKM918DPPuzZ2t1z7HAxrPU8UJo8LV2ZRCBjf\n/sUoP+lfALCXrdv++3Jh2DgDw3XQ0+XSc8IzegurTVxcbUXM6PUGT0C0OXrA6D16ZiW3P7qvV1zM\nVF1cs2cOT4qwydMwD+4gozdgjp5pWDOOrpuAHvJ+cbU59kYs41a1M3p9pZthQ4WHfY21gXv0uqWb\nIhKsxg7b0zDocQ0M7rgJ9F78oux1sm+KAJ3VyvomcMtUpdt1c7WVaHxHvRLeddP8nPZeKRHxy8LW\nZ/QGZUW9IXv0mu3oc/QA3RgE0M+pSQd6B7ZNYe98HZ98MDzQO73YCJ3JNogJmuOUbRq75mqRFubi\nMIshczV9nZqvV3DN3tGz4ja2R299F9eVRjtWSd2d1+zGueVmz0B7XbrZ+1yoBkFJt3Rz0AJPz41R\nAQM9z+3dEvGFRy9gvu7h0u29j5lulYIer1CvuJiuun6gpzN622aGZPT6SjfNc3mu3r0umcOYxB49\nQB+vvUcvLKP33U85iLe+/OjQRjN5smWqAhHd/be/WR3RKPZiYtb3LDaT/BhXR9IoX9VTSgWt6JRS\nDRHJzTOso7oB3CD2HhDXcfRcvZAbrmC0QuKM3vCOc0Gg12iva3pi79Ez5aBh0f1rn3klrt+/JVap\nUrfr5uCMnmdn9MYU6J1fbuDiSmvsoxXGzdR226WbZtU0dkZvZDMW/XFTVRcLa62hDQEcRwaODbnv\niUUACG0Rbn6GLVOVSOWO9k0R4M+Ay3h1bH7Kw0OndTfaM4trieaqTVVctDrKby7T/XnMXsT+503F\ndYJ9ToBu5LCw2godrQCYxZzB4xWiNN0wZmseDu2YxkNnlideuikiuO3y7fjY/WfQ6ah15ZanF9ci\nlQAb5vGX5DH0tu+8OfUKhCft34L3febRIIP35hceidT46qrds9gzX8N1fhAeh/kZ7K6bq814+y/v\nOLwTjgD/fO9J3OKXtYXNOwz26HW6gd6l2weNUrEyejlZAY9Dd5PuXhO/9NgF3BDy+mme20uNFjpK\nX8d1Ns4u3RyS0bO7bna6oyhma16wR8/8vtNeSB1k+7Seu2te98Myejtma3jZLdGrg7JmBsffwrJN\nSkBEd7VstLLtFN5vru7hxMXxzRiM8pOeEpEXmzdE5CUATo/laBLoHzwexr6wuo7+2LDSTTNaIUpG\nb9QcvbBAzww1NgPTB+3RMw1ewup1f+xZh3HnNfHq2rsD0/Wxhm1C9dxuoJf2C5HZ23BhpYkLK82x\nD0sft0pQauYEL+hxm7HURgV6fcGFWZUfNmDWEcGAXh9Bx82rhmT0os4is5uxKKXQaGef0Zu3Vs7P\nLA7Oqg0TzETsy+qthezRA9a3bjejGQaVEvY3XLI1YzZjAbrz9OoZ3IA/69rdOL24hs9a2SPj9OIa\nds5FD7RN6WaSBaa9W+qJzvUwr7jtIP7ydU8PFqSed8PekSNXAJ1d/MQbnxOppXY/87P3l27G2Tu1\ndbqKWw5uw4e+qhuytNodrDY7624egv2lVtfNsEYsQH9GLzc7NiKret1GbM12B/c+vhB6fsxz+4Jf\nplmrOJipeTqjtxS/dLOb0euWbppzO7mMXhVKAY9d0Pc1kxhUPQl/8L234j89/9qsD4MKquY/V/PS\njAXodggfV0Yvyk/6wwDeKCLfEJHjAN4A4DVjOZoEgtLNEV03DUcGz9EzGb0DMTJ6dulmzxy9kN+s\nydCt+oGevUfPHgExLKOXhGeVbtY8JzQb6DnO2EpL7NLNh84s4ZKUS60mzd6jZ/ZbLDfjZfTMRWZU\n6aZZ0Td/D1tVdh0MLN287+QiDmxb33ET6JYzRB0sb459tdkJApesbwLnrc6ucQMN48A2ndW470Rv\nk5GwrpuAGSbdPX9nFk2gN2iPnjMw0GslGFFx3V4d6E26kQKgywRdR4Lh4rbTMQPtoHQzJyusVc9J\nlJXbiLDSzbgZPQC489rd+MKjF3ByYRVL/uLTuoye011karY7OLvUiFa6maMbo6h0Rk8/R7/2xCIa\n7Q6u37f+3JpsurmG1Dzd7Xip0cL55QZEhpfkru+6qd+erXtBMxZ7+8gkmHP6iQd0ifW4OvpN2g37\nt0R+rSLqZ65jeXm9AboNWaYn3YzFUErdr5R6KoAjAK5TSn2TUur+sRxNAvEzeqIzHyE3xI+eW0HV\nLw0YxdzQ945X0IN1gQEZPa9b7tm/R8+zgs9hNfVJdDN6g/d8eD2/o3SfAGa14nPHL2BhtYWjGxy2\nmrWqXbppmrH4AX/kPXoRSzfNDYjJ7g7r/DbocQ3ojF7Y/jzAzuhFe/EUET1/qdkOyqKyHK8A6Juw\n5UYbq802zi03E2V5nnrFdojoGU02cy76AyrP6Q30urMIB49XGFS62WrHn19pMnqT3qMH6NmYT7l8\n+7pAr9HSnXWTBXrFyxilJSjd7Om62Ynd9v6Z1+iROx/+6qlut8W+QM/x96m3Op3gMRs2LB0ofjMW\nzxqv8MXHLgAIH2KsF0DtQE+XbppmLPP18G7HRlC62e70VOvM1SvdjF57shm9Z1+7B5ftmMaH/ZEb\nWSwIEeWN3TU9L8wevSzGK/RQSi0C+NOxHMUGBF03h9wkeH2BXv8GbeOR8yvYt7UeqcW3GR7bO15B\nDR2v4LkOqq5u+NBWfXv0rNV+8wKdVnQfzNFba4U2YjHfP/j3mDJ6H/EHvd94oNjdsswNadV11u3V\njN91c/TAdACYqkYr3VQKQUMgo9Xu4IFTS6H784DuuY+zSlr3h4ub48/6JtCUAz94eglA9KDVtnW6\niuv2zuPjfYHeyoDSzYonPft/gozeoPEKrvTs47W1OvFnEWYZ6AHAc4/swddPLuKBU4vB+84s6cAh\nzgBzc33KerEgS+aaa78urSaYkXjkknnsnqvhn796KugEHJbFNwHQyYuDZ+gBvcF3nva0RGV33fzS\noxcwU3Vx+Y6ZdR9nFq+CQK/i+M1Y2njg9CL2zg/fo2kW+JpthaZVrTNbC8noTej3OFV18cvfdqM+\nPldydWNLlJU8Z/QmPjB9gP1jOYoN6ETI6NnZNUd0Ri+0dPNctBl6QPdFz/4yHYWhe/QAv7Nfo412\nu3dPziQyejrQC79xqPSVkaap5rmoVxx8/eQi6hVnYGapKOxmLOZ3tRKzdNN83MhmLH5wYdpfD+s0\nZo6l/7H98NllNNqd0NEK+lj058UJjuoVB6vNTnATlYfSTQB44JQJ9JL1i7r9yh3492+cC37/QG8H\nVFvFcXoC9VFBTrAPKyTr2uqoICsQ1d75Oi7ZUs+sjMnMIrOzeqcXdLAbL6OXvxfeSTNBbm9Grz1w\nYW4QEcGd1+zGR752KghaZkMWDCuubkhghqUPegwVvhmLtaj7hUcv4Pp9WwYu5NYrbrDPt+a5mK15\nePzCCj5+/xk858jwffH2bMJ2RwXlsXN1Dwv+15z0Hj0AeOoVO/BDd1yOK3cV+zWXKC3dQC8/FSTm\n/iXLZiy2z4zlKDagHaHuvT+j5w7oTvjo+ZXIrbrDbkp69ugNOBxTytHq61bXs0fPZPRSOummFLPd\nUaHD0oHezqRpd7EDgK1T+ub3+n1bCr9yX3X177Dq2c1YWsH7oqj5QcPgQK8DR7oXI1N2M2yfiHk4\n9a9hmEYsYcPSge65j5vRW2m2g8ds1jfppvTBZJeSNui4/YodaLQ6+Mw3uk1GgjLavnOru272ZvSq\nfslXGPM8bIUMTdelm/Fv6t/3o0/Djz/7cKzPS8uBbdM4csl8b6AXlK+ydDOObtfN5M1YjDuv3YWF\n1RY+fJ/umRa2YGgyXSf9QG/3/OYcr1Dxm5x1OgrHz63gil3rs3lG3XNxYaU7D3Wm5uHiqu7C+cIb\n9w39PuYx3PADvaAZS83DWquDRqvTrT6K0TE7DW/8v67DX//4HRP9nkR5VfUr6+J0rh+3cY9XiHTl\nFpEpEblGKfX9YzmKDWgHpZJD9ui5vRk9NySjt9ps49TCWtCQYZSwG/qOVTY36HhMu+V2p9PbdTMs\no5fSSbe/z6AW7t4YM3pAN0C5seD784DeFSHzuwrm6EW8We3O0Rs8MN3M0AO6N2vDmrGYhYP+RYyv\n+aMVBq3qmpX6OLPPpkyg19LfK+tAz7TCf2ADpZsAcNsV2+EI8PEHuuWbq602qp6zLhPg9c3RO73Y\nwM6Z6sAXkEpwM78+uG914jdjAYA98/WxlXtEcdeRPfj3b5wLArxT/t+x5ui5zOiFlW7GnaNnPO2q\nnfAcwV99/jEA4a8jZpHCZPQGlRvbr3NFLP0LMm2dDpZDZgra6hUHF1d6u24CulPxtSPmKJrfjVkU\nCsYr+CVZi2utYI/epJqxGCISaTsKURlUPCd317JuM5aMAj0ReRGAzwL4W//tm0TkA2M5mgTMPdOw\ni2d/05OwrpuPX1gFEG2GHtB7U2Iu6qPGKwC6qcZSo4W2wro9euaYul03092jB6zfZxR8TF/QmTYT\n6B0t+P48wNqj57nB42Cl0YZI9Bdx8zWGjVewb/LMY2HYHD3zOO9/bA/ruAnoVWcA2BejG+pU1cVK\nw9qjl/Ucvf6MXsJyxvl6BU/avwUfv787QWat2QkdYVBxHTSt3/WZpbWBoxWAwaW1gM7ojSOTPm53\nHdkDpYAPfuUkgO4+xXjjFfw9eiW+GfWCbG/yOXrGXL2CWw9tD8qYB+/R6+Dkwiq2z1QH3vj0vs7l\n6+YoiiDT1upgudkOSuDD1CtuMDNPl27qj33hjZeMXP23XweAbvberNAvrraCBZ4iPs+JNouaNRYr\nL7rjFbIr3XwLgNsAnAcApdRnAVw+lqNJICiHGPKT9HfdDAv04szQA3ozN2bIdEcNb8YCALP1ChYG\nZPTMau7yWhuuI6nN+XAjZfS670+76ybQfSBvpoxe1XV6VuLjlAOYwZ1rA5uxdHpu8qaDZixDMnoy\nKKO3MLARCwB889W78O4feiquGbFqbZuuulhudG9e4u4vS9v8lP79PHBqCfWKM/SGbpSnXrkDnz1+\nPrhpM9nVfhVX0Gz1jlcYNqjdC/bxrA/0mlZL9iK5ft889m+dwt/75ZunF9cwXXVjjYYxz6G8rbJO\nUmhGL2GgB3S7bwLh81irrt5femphbWj2tRqyoFkkJgBbXGtBqeEr5rWKG4ykqHkOtvtZzlFlm0D3\n/Jm92nbXTQBYWGtG2mZCRONVzWFGzyzgmwXrtEX5aZtKqQt97wvv4Z4B04xlWOmmHVA5ji5j6L/X\nevT8MoBkGT0TkNkZvUE3/HM1PUC11V6/R69lzdGbrrqp1RBXrBvIKM1YxrGyvmuuii1TFRwK6XhW\nNN3xCtLzoh13D0vNb4gQZrXZ7gnKX3DjXvzkcw4HAU2YoHTT+pKm4+bhAfvzAP3Yu/3KHbGOfari\nYbmRo9LNKXND1cLO2dqGnju3X7EDzbbCPQ/r+VODAz2npwzzzOLa0G6TYUOxjZbVkr1IRAR3HdmD\nj35Nd3k8vbgWu2zWBLhF/PnT4jgCR7r7N5VSiffoAXqenhG278OUbp5cWBu4Pw/YDKWb+jFlGtMM\nq5Kxs/a1ioOX3rwf7//Rp+GqCM3DzO8mCPRcE+jp3/3CaisI4sv8OCfKmu6tkK9r2TdduRNve8XN\nuOXgtrF8/Sg/7ZdE5LsAuCJyWER+A8DHxnI0CXQvnoN/FLudsSsCV9a3OH/03AocAfZuGd5G2aiG\nBXod/QI97Do+U3OxtNbqmbUD6BckO6OX5jwNe4/ioEDP7QuG0/bjzz6MP/qB2zbFXgFz7k0GL2lG\nolYZFuh1espsr9o9h598ztVDAxhzmu2ujkHHzd3Rs3VRTFf7xitkfBM4VXGD85B0f55x66Ht8BwJ\nxiysNjuh3Q8910HDujE/szR8ULh5jjVDsritjipsk6K7juzBWquDj37tNE6PCHbDcLyCZo/YWWt1\noNTg6/Uoh3fPYv/WKTgSPn7DlG6OyuhthmYsAHBh2QR6w/bodX9PNc/FVNXF0UujbTUw32e10Z/R\n65ZudjN6xfs9Em0WNc9JrVouLa4jePHRfWO7P47y074OwPUA1gC8G8BFAD85lqNJwFw8h1077T16\njqMvtP1z9B45v4K98/XIkb4ZOgt0XyBM6eaw7OJsraIv+n1z9Oxy0qVGK7UZekDvCmLYXiOgN+s3\njhXHS7ZMFX5+niEiunOT/7s05zHuKlHVdbA2JKMXt7V6WDOW036zhVFzoOLSpZt2181sA3gRCcqD\nk45WMGZqHm48sCVoyLLaCi+hq7p2Fr6NtVYHO4aUbprfUfgevWTNWPLgtsu3Y77u4R++/AROLwwP\ndsMECyUFDCTS5FlVHaapR9LSTRHBc6/fgz3z9dDFoYpdurmJM3pm8SBSRq+yfvE2+vfpK910e/fo\nLaw1mdEjyoEfvOMKvOF512Z9GBM1Mm2klFoG8CYAbxIRF8CMUmp17EcWUUeNrnvvGa8gAtdZn9F7\nJMYMPUOXbrWDF0AzR29ooFf3sNho+e3U7XLJ7mDX5Ua6GT0vQunmuLtubjZvefH1ePJlOs1e8QO2\nuDdCVW946Wbc1fxgj5712DaBZNygcRTTjKU7Ry/7m8D5uoezI7JqUX3TlTvxPz98PxbXWlhptINx\nGDb7OXtm0czQG5bR8xtu9F17Oh1d8l3EPXqAfvzfee1ufPDek1BK4ZbL4pWfmAWSsjepsPdpm9mN\nSUs3AeANz7sWr33mlaH/V3UdnF5soNHuYPfc4EUge/Ehb+VOUcQq3bSe47Gv5aYZS9M0Y+nruunv\ny7f/j4gm78kxX582gyhdN/9EROZFZAbAFwB8WUR+evyHFk1QDjGspC2sGYtaX7oZdX+eYV5EzE2g\nmaM3bHvQbM2FUsDCanPdfL8go7fWSnVwYk9GL0IzFq44jvZdTzkYNC8xN6hxMzJDA71W/EAv6Opo\nPbbN1097NX6q4mK52Q6+fh5uArcEGb2NB3q3X7kD7Y7Cpx48i9VWJ3yPnucEjVVO+90mh5UtmoY1\n/eMVmpugG99dR/bg7FID55ab2BUzo5o0I77ZeNaez5UNZvQAHbgMCuI8V/DYed2AbNj8zGrBXxfM\nY+riqulkPaR007NLN+M9FrtdN/3nsv+7mq939w6bim0GekQ0SVGuZkeUUhcBfCuAv4HuuPnKsR5V\nDEGXy2HjFfoCKkekJ+vRandw4uJq7IyeuXmuWRk9NSqjV9MX/gsrzb7xCtYevUY71dlYjiNB8Dkw\no+cwo5dUd49evJuymucGe9z6DdoXNkzYwHST0avFPLZRpqsu2h1lzQ/M/iY9rdJNQK/6VV0HH3/g\nDNaa7fDxCo6sy+jtHDCPDOg+r/oHprc3QUnXM67eFQQFcUdbVBIulGw2unRTPxZMx9e0M/FGxXWC\nLNfuIedLRFBxdYfgPA0Yjso8p+KXbsZfZBPpltyahdOapzszL1jjFfj6SkSTFOVVpCIiFehA7wNK\nqSZy1HUzSUbP68voPbGwhnZHYf/WaMPSjYrbH+gpdDrDm7GYUo4LK82eUi17YLrpupkmswcvSqBX\n1BKyrJjfVzXNjF5qpZvdduFpmqp2H8dAPm7Szep50hl6tnrFxU0Ht+Lj958Z2nUzCPSWRmf0TMau\nv3TTZAWL3Ixkrl4JOrfGzaiaktY8LBZkqWI1YzEZvaTNWKJ8L2NYRg/QWb08lGYnYZpEXYxRuimS\n7HpWcR0s+zNwzeupiGCu7vU0Yynygg4RFU+Uq/fvAHgIwAyAj4jIZdANWXIhymyanvEKoscr2Kvq\ncWfoGd1Ar9uMpa3U0OyiGYjYUegbr6Bf5JVSqXfd1F/fLzONMBiXK47xmBv4JPs6TCDWT2f0EpZu\nhuzRGzQ/MSlzw9QN9LK/ETSjJ9Io3QT0mIUvPXYBZxYbA7pudq8jJqM3dI6eH9C0+0o3WzlpaLNR\ndx3ZA2B4hiiMuT6XfYHJHrGz0WYso9iPtVHnq+Llb8BwVGaB01ynhlXKmC0YtYTZy6rrrJujB/j7\n8te64xX4+kpEkxSlGcvbALzNetfDInLn+A4pnm7XzcEXz/55da5IT2fCuDP0jO4ePf1iomKUbgK9\nLwYV6yY97a6b9veK0oylyHuFsmB+t7G7bnoOlpdbof+32mz37BmJImxg+lrTZPTSL90EuivlWY9X\nAOzSzZQCvSt34Nf/6WtYWGsNzOiZ0tvTiw3M1byhwXkwFHtA6WbRbwC//ckH4DqCm2POAjLPm6IG\nE2nxXEGz01u6uZFmLMOY33m94oTO2ev/2KI+NL2+ZizDfp9mMSfptdJzJWiiY7+GztYqWFhtom0y\n9yVf0CCiyYrSjGWLiLxVRO7x//wqdHYvF0wJ5rByiP79Z3bjE8DK6MUO9EJKN0fM0bNfVHtKSq2y\nrrS7bgLdF54oc/SKfsM5aabkLknXzXGPVzCBSOqlm/7j6OJqfko3t0/rbNqwuWBx3Hxwa/B7Cw/0\nrIzeUmPk/DjzOFlXuum/XSn4DWC94uIVtx2Mff1gMxbNcyQIBtJoxjKM+V3vngsfv2CruvkbMBxV\nMEfPlG4O+X2ahbWkjasqrhME6PasvLm61zMwna+vRDRJUa5o7wSwAODl/p+LAP5gnAcVh9mPNCyL\n1jMM3C/d7M3orWDHTDX26mnN610B1OMVRs3RswI96+NMMGqGqaed0XOd7gpuGPuFnHsI4kma0at5\nTmgzlla7g1ZHxS/dFJMV7r5vrTmmrpt9pZt52MPz8mOX4vdffQxbpiujPziCmufi2CGdnQptxuL2\njlcYNloBsJqx9AV6plyvrJl0s0hQ1p/f8Jz1XTfHtUev6unfdZQy26rnFHKGHtA7XqHqOUP3wdat\n0s0k7NLNivUaOlfTgV6wR6/kj3MimqwoV7QrlVI/p5R6wP/z8wCuGPeBRRVtj17v/jN7XhGQbIYe\nEJLR8+dhDVshNc1YgG4WTx9Xbxvo1DN6pnRzQFkKu24ml3iPnucEgZhtNeHsO3MP01O62erAkfSD\n927ppn685mHFf9tMFc++bk+qX/P2K3SDkXrIIpDndvfVnllsDB2WDnTPQf8eveXGeG/q844ZPa3i\n2nP0xlu6aV4TRzViAQrejMXK6M2M+F12SzeT/ayeK+vm6AH2Hj123SSiyYtyRVsRkaebN0TkaQBW\nxndI8ZjtLsO6btoVUa7o8Qo9pZvn48/QA6xAr9It3VQjSjdnrExdzx49P1iI0h0sCa9vP2G/3oxe\nMV/Us9LtuplORm814Wq+BBm93q6bNc9NvTX6VKW36+ZmXaU2nSTDFkhMl9VmW+HM0uiMnmd9vO0R\nv3R8X4Jr0GYwU/Xw3CN7cOuh7VkfSqbckPEK4y/dHB3oVTwpbBBuZ/SGzdAD7Ixest95xXWw2ugd\nrwDo0s3FtVawAMeKGSKapChpo9cCeJeIbAEgAM4C+N5xHlQcQenmkNehnoyeq/fomc9TSuGx8yt4\n1jW7Y39v04CibpdudoaXkdY8F1W/iUPYvjiz5ynNOXrA6GYs3KOXXDBHL24zFjd8vELSQM8NacbS\naHVS77gJhHTd3KSLA0cPbMUPPP1y3Hnt+uuDuZlrtDs4uxQlo2e6bvYGesfP6mZQlyaoKtgMHEfw\njlcdy/owMudZpcBjH6/gl25GzegVcYYe0H3ONVqdkYunQUYv4fXScyS866bfjMUs8Ay7PyAiSluU\nrpufBXBUROb9t3MzWgHoNmMZFpz0BDHiN2NR3SYKq81OotLNal+WLEozFkCXcpxdaoTu0Ysy2DUJ\nd0Tppt1MgyuO8ZhMjbl5iqpWcQcEeqZ0M9l4hf6B6Wk3YgF6Az3PkaFdb4vMcx28+YVHQv/PZDlO\nLayho4bP0NNfy2T0es/58XPLmK66Q0cz0ObnORJcD1abHVQ9Z2yLbmZhZvdcfeTHHtw+XdhAz+4G\nPDLQ8za4R89zQhuuzNU9NNsqyNJu1uoHIsqngYGeiPyHAe8HACil3jqmY4qlHbcZi4OerptJO24C\n3Rs9k8lRavQePUA3ZDm71Ajfo+fveRpVZpL0WAft++rPelJ03cdBvMDMZHb7BRm9mDcc5mHXP0dv\nHI0UzN6hhdVm6qMbisIsjpy4sAoAo0s3Q+YcAsDxsyu4dFtxb6YpHZ7rYMkPBvR4lfFlyc01K0pG\n760vv2lsxzFudlOUUa+ptRRKN8P+Pefvyz+33ADAihkimqxhV765iR3FBgSdrKKOVxA9Ry8I9M4n\nG5YO2Hv0uqWbSqmhZaRAtywzdI/e6pgzehFKN5nRiydoJhEzo1f1HLQ7Cq12p2dPR+LSzZDxCmaP\nXtqmrMd8HkYrZME8/09c1NeQnSMycoO6bj5ybhmXbi9n2SZ1VRzjfhkKAAAgAElEQVQJGvWsNNpj\na8QCxCvdLHK23g64opZuJl0YG9TQzHTaPr/s72fepGXuRJRPAwM9v7tm7kXputm//0yPV9BBmcno\nHdg6Hft7V4PxCv2lm8NfGOf8C7/b1w0U6JZujmuPXpRmLFxxjMe8cNcSDEwH9B6v3kAvYemm2aNn\nZ/Sa4ynd9PxOfI32eDKGRWCeUycurAEYndEzzzF7YLpSCsfPLuOpfndPKq+eZizN9tgasQDdKpTd\n8+nMnMwru0xyesRr6obHK3h2Rs8u3dTjXsxrO19fiWiSogxMf5eIbLXe3iYi7xzvYUXXUQoiw8sl\ne0s3xWpaoTN6szUP81PxA6v1A9P1n1GBnhmxELZHz3TdHNUKOi4vKN0cMF6hZ49eOW/ck0o6R8/c\nbPXv0+tm9OKWbvqlgX0D08cR6AHd8s2iduTbKHNjd+KCXiwatUfPDUo3u+f73HITS402Lt0ef6GJ\nNpdKXzOWcY7beNHRffhvL31SpD16RWZfm0aPV0ivdDMso2dKN1kxQ0STFOUO7Ual1HnzhlLqHICb\nx3dI8bQ7auhoBWB9MxYT1LQ6HT1Db+tUov0xQTMW/4VB+Rm9UV8qKN0MCa7MHL1Rq49xjWzGYgV3\nfB2KJ+kcPZNdXRfotTZYutk3MH1ce+hMKVRZmwuY5+yJi6sQAbZNR5ujZ49XKHvHTeqy946vNsdb\nurlnvo7vesrBsX39vLCDr1G/T7MnciNdN7v/Xr9Hz5RuMqNHRJMU5YrmiMg284aIbEe0sQwT0VZq\n5B6C/tp5R7o3xI+eTzYsHRg0Ry9CRi8o3bSOq2+OXtplO54jcGTwfirz/T1H2BQiJvM4SJrRW1uX\n0dNvx30MhA9Mb4+ttLLsGT27Gcv26erIGziTVbebsRw/5wd6zOiVnudKsAiw0hhv6WZZuI4EC68z\nkefoJbue2R0+vZ7Szb6Zowz0iGiCogRsvwrg4yLyF/7bdwP4r+M7pHg6ETJ6duDlOhLcELeVwqPn\nlnHssm0DPnO4yro9eog0XmFuSOnmhZUmpipu6qt+nuugXhk8ONt8f642xmd+Z3EDKvPx6wM9ndGL\nu7IcVro5rvEKQDejF3d+4GZhnv8nLq6OLNsEus8xuxnL8bP+HmFm9Eqv4jjBIsBKs40tU5WMj2hz\nqPjzSkdm9DZYumlfB72Q0s3z7LpJRBmIMkfvD0XkHgDP8t/1MqXUl8d7WNG1O6MvnPbqmivdjN6F\nlSYurrY2ntHzXxjanWjNWEIzetbA9Jla+iu5niNDSwHNz8LVxvhMZiduwGMCsMF79DbejEUPTB9T\n6WZFP45Lm9FzunP0rtg5O/Ljg0DPGqlx/Nwytk5XgoYNVF6uK2h1rD16YyzdLJOKI2hg9B491xHc\n/eQDePpVOxN9n57STeuaOGtl9JwR/QSIiNIWqQTTD+xyE9zZomTQ+puxmAvyN87osqkkM/QAe49e\nvDl6YXv0zM3yxZVW6jP0AP07GDaXyZS4cLUxvqQZPbNA0D9LrztHL78D0wEEN6LlHa/Q/X1HyeiF\njVc4fnYZl25j2SbpgMSUbq6ydDM1OuhqR3pd/e93H038fXpKN63X0ZrnourprGJZqx+IKDuZXHVE\n5L+LyL0i8nkRea/d1TOuVqe3NX0YszHa7StPNI0QNprRq1e6pZsqSunmsIzeSjP1GXqAzjaNWiH2\nHBn5u6T1zOMr9h69gRm9ztD9lIOED0xvj690s1LuPXr2c2XniNEKgF4Acp1u1gYAHjm3whl6BECP\n27FLNxnopcNcn6bHUCljqw7ougmEv+YTEU1CVndo/wDgBqXUjQDuA/B/J/1C7c7o5iempM38bZq3\nfMMP9A4kzeh5vaWbHT+jt5HxCo12J/UZegDwA3dcjjc879qhH+M5Dl+IEqgk7Lo5ONBrD91POUjo\nwPTm+ObcTZe8GYt9Y7djxLB0w3MkyOh1OnqOJzN6BOjriBmvsNrsxB6vQuHM9XkcC6i23q6bfYGe\n/5rPrRFENGmZvJIopf5eKdXy3/w3AAfifP7xs8t4yn/7Rzx8Zkk3YxnxU5iOkqbjsQmwHj67jKrr\nRFqND7NlqgLXkWDPXdRmLDMhq3t2O+ZxvCDdcnAbvuX6vUM/xnOFL0QJuEFGL97vrtt1s93z/tVW\nshla3fmQ/c1YxnODM1Xy0k279HrUsPTgcxxB2y/PO7mwhka7gwPsuEnQj6d2R0EpxYxeirwg0Btv\ns3BTuumGdK4OFndLeq0kouzkYUzC9wP4szif8IVHL+CJi2t48PQS2mp0182go2RIRm/f1vrI8QyD\nvODGS3D1njlsm6nCkeh79GbD5uhZ/x7VBnpcKi4zeklsNKMXNl4hyU1e0HXTzxgppcY6ML3sGT37\n594eNaPnOkFGLxitwI6bBL1g1OqoYLwKm7GkIyjdHPPvc1hDs7laZeD/ERGN09ju0ETkH0XkiyF/\nXmJ9zJsAtAD88ZCv8xoRuUdE7jl16hQAPbcK0CVvnc7oOXqmlNIEMZ61Ry/p/jxAl2zesH9L8D30\nHL3RGT3TNtvOtNgB1rj3EgziOszoJWGysXE32u+dr2Oq4uKX//Ze3H9qMXj/arOdaGhvf+mmCSCT\nDgAeZcpfkKiMKZDMOzuTuTNCMxbAlG7q8xIMS2dGj6CbsQDAwtp4ZqmWlemOO/aMXt/9hS3I6PH1\nlYgmbGx3aEqp5yilbgj5834AEJHvBfBCAN+tlFVrtv7rvEMpdUwpdWzXrl0AgCcu6kCv2VY6oxdx\nYHp/M5azS43EHTf76UAPkcYrXLlrBr/+nTfhWdfuXneMQIYZPUcSZzfLzEuY0ds2U8Uf/9BTsLja\nwsve/jF84oEzAPw9egnKLbvjFfTbQaA3rtLNSsnn6Nl79CKWbrqOBBlXM0MvrWsQFZsp61tc1bsa\nGOilo+JNZo+eXbrZL2jGwtEKRDRhWXXdfB6AnwHwYqXUctzPP+EHeo12G+0oA9P7RgfYgdj+rems\npov4zVgiNIcREbzkpv09+7DsDn5ZZfQ812FGLwHzO0tSwnjLwW147488DTtnq3jl738S7/vMo4kb\nMQRdN4OMnt77N/5mLOV8zPTu0YuW0au4TtBC//i5ZeyZryXaj0mbj8k8LZhAj6WbqTAVF+NeQDXX\n/7DXgTnu0SOijGS1FP+bAOYA/IOIfFZEfjvOJ5vSzWZL6UAvQnBiD0q3P34jpZs2RwTKZPQS/Fbz\nkNHzXAkai1B0SefoGQd3TOM9r30abrlsK37yzz6Lf3/4XLJmLKZ0088YNYKM3rhKN8u9R89kMquu\nE6zYj9Kb0eMMPeoyCweLazrQ4wJAOsxC1LgDZ/N9wu5HZoOum+W8VhJRdrLqunmVUupSpdRN/p8f\njvP5pnRzrd2JHug5sq50E0ivbMoRfYMdpXRz0PEZ4y4xGcTjHr1EKm6yPXq2LdMV/OH3PwUvu3k/\nVpoJu272DUxfG3OgV/ZmLCYLv2O2GnkUhme10Ncz9BjokWauvQur3KOXporroOLK2Cob7O9j/22b\n9ZuxcI8eEU1aHrpuxqKUCko3m61O5MDKc6yMnvXxB1LM6LUjztELU7FW+sYxRy8KztFLZq7uwZGN\nn7eq5+BXX34UNx3cioMJAoB1pZvN8e7RK3vppvm5o5ZtAv54hY5Cs93B4xdW2HGTAmbh4CJLN1Pl\nuc5EgmYT4IXu0eMcPSLKSOECvYsrraD9dCNGRs8Jyeg5AuzdUk/luEQQlG4m2W9t1+5nldGrcI5e\nIi+48RJcuWs2cov9YUQEr7r9UKLP7TZj6d2jN7aumxW/62ZJM3pmcWbHTPQ5nKaF/mPnV9BR4Aw9\nCpjXJTZjSVfVlYksnpqFn9DxCuy6SUQZKdwdmsnmAXoPUlshUqdIuyzRfPye+XpqN6mOo8crJM3o\n5WOPHjN6SdQ8F0cv3Zr1YQwer8DSzbEwi0dxMnoVV9Bqd4KOm9yjR0Zl3R69cj6v0jZV9TBfr4z9\n+wRz9EIqHJjRI6KsFC6j9/iFleDfzbaeoxelcsx1nCDAMxfbNNuauzHm6IUfX/Zz9F56834GegXW\nPzB9Us1Yxr33Jc92zFRx2faZyB/vOoJWR3WHpW9n6SZpphHW436zsa3TG68QIOD1d10ddDIdp27p\nJvfoEVF+FC7Qe6I/oxexdNNzJChtMxm3tDpuAvomO+ocvUHHZ2SV0fuep16WyfeldAzO6I13jl5Z\n9+gBwAd+7OnYOh09W1BxHLTaCsfPLsNzBJdsYaBHmhm4/dUTF7FtuoIdKZSCE3BoZ/SFmI0wmbyw\n6+FsjV03iSgbhbvqnLiwBkCXtTTaHbQjBlauNQzcHUNGzxHdKKbTQeQOfDaR7h7CmYwyelRswR69\noOumv0dvTBm3+XollSY0RbZ3Sz1Wh1QzXuH4uRXs2zrFFX4KmGYsXz2xgKt2zyZ6HaHsVCM0Y2Gc\nR0STVrg7tBMXV4OVTpPRi7KXQY9XMP/Wf6eZ0XNE0OmYjF6yr2FuAqczyuhRsQVdNzuT6bq5ZbqC\nP33N7bhh//xYvv5m5LmCtVZbz9Bj2SZZTFXHUqONq3bPZXw0FFewR29o101GekQ0WYW76jxxcTVo\notL0u25GHa9gMh768wU37k+vgYYj8PfoJWvGAnRLd7Iq3aRi6x+YHpRujrGpw22Xb+fCRAyev0fv\nkXMclk697CYeh3fPZngklIQXdN1cf701VQ/M4BPRpBXuDu3EhVXs3VLH4loLDX+OXtTxCqZ088C2\naXzlvzwvKJVJQ88evYRf1vwcnJ9ESfSXbjb80s2NDHKndLmOg4XVFk4vNjgsnXrYr2OH9zDQK5rq\nkK6bFX+WH7tuEtGkFe4O0GT0qp7TnaMXM6MHINUgD9C190opf45esou55zqouk6puxhScusGpk8g\no0fxVFzB8bO64+YBDksniz2m5DBLNwtnWOkmAMzWPWb0iGjiCnUHqBRwZqmBvX7pZqOldOlmhIun\naw1MHwcnGK+QvHTTdSSz0QpUfCKiS4j7SjeZ0csPM14BADN61MMECLM1D3vmaxkfDcVlMnlh4xUA\nPYqlzI2riCgbxbrqCPDO7z2Gg9tn8MGvnkSj7ZduRuy6Of5Ab2PNWCqOoOoW65RQvriOWOMV2vAc\nST17TcnZq/3co0c2s7eLHTeLqToio/cbr7iZgR4RTVyhrjoC4FnX7gEAVF1BM8YcvS1TlbE2ORHR\nJXOdjWT0XEF9TB0SqRxEJCjdbLQ6YxutQMmYoHuq4mLnLOekUZfJCLERSzEFzVgGzBU9vIfluEQ0\neYUK9GxVz8FqM3qg96t3Hx3rKqkjYu3RS/Y1PMfBNFf8aANckZ7STe73zBcvaAg1xawN9TCPDTZi\nKaZRe/SIiLJQ2Kii4urude2IXTd3z9fHejyuP0dvI3v0PEcww46btAG6dFP/e63ZGdsMPUrGrPZz\nfx71u3T7NO68Zheefd2erA+FEggCPZbKE1GOFDbQq7qOHq/QSR5YpUn8OXob2aM3W/ewbYblXJSc\nI9bA9FabHTdzxuzDupQdN6lPveLiD77vtqwPgxKqBHP0sr8fISIyihvoeTrQ06WbWR9NfzOWZBf6\nX3v5TahXmIGh5JyeZizco5c3pvqAGT2izcVk9DhCgYjypLiBnuvP0YtYujlu3Tl6SLz35tDOmZSP\nisrGlW6gp5uxcOEgT0zp5gF23CTaVEwmr5KHlWciIl9hr0gmo9fpJM+gpak7Ry956SbRRjmOoK3H\n57EZSw55QUaPpZtEm4mIoOKOd4wTEVFchc3oVVwHzXYHCvkolZCgdDMfewapnHoHprdZupkzZrWf\nGT2izec51+3BLQe3ZX0YRESBwgZ6JqPnOJKLwMpJoRkL0UbZpZtrrQ5mOa4jV158dB+2TVexZaqS\n9aEQUcr+5/c8OetDICLqUdi7wKrnoNlW8JCPLld6jp7OpnA+FmXFcfoHpnOPXp5csWsWV+zinDQi\nIiIav8IGehW/GQvEyUXppsnobWSOHtFGOX0D0zlegYiIiKicCnsXaPYemfLNrIkI2h1dusmmW5SV\n3oHpbVT5YCQiIiIqpcLeBZrhpIDel5Q1RwClgPYG5ugRbZQjCEo3mdEjIiIiKq/C3gXamYo8ZPTM\neIWNzNEj2qh1pZvco0dERERUSoUN9CpW2/g8ZPR0yRzn6FG2zOMQMM1YCvsUJyIiIqINKOxdoJ3R\ny8M2JM7RozxwRA9MV0qh0ebAdCIiIqKyKuxdoH0D6zrZ/xh6jx7n6FG2HEd3f222dVavkodVECIi\nIiKauMLeBeYto+eInl+muEePMmQGprf9fXp5mDFJRERERJOXgxApGTujl4dSSUeAdsf8O/vjoXJy\nHD3mo9nRD8Y8zJgkIiIioskrbKBX6cnoZX8zq+fo6ZvrHBwOlZTp/tpi6SYRERFRqRX2LrB3j172\nkZUjQMsvl8vDuAcqJ1cEnQ7Q8hcdPJePRSIiIqIyKmygZ2cq8lAqqbsd6kAvB4dDJeU4emC6yehx\njx4RERFRORU20KvlLqMnwc11HgJPKiczML0b6BX2KU5EREREG1DYu8Bqzgami3TL5XIQd1JJuY7u\n/srSTSIiIqJyK2ygl7dmLHbpJjN6lBXdjKW7X5QZPSIiIqJyKuxdYN6asbiOBDfXnKNHWXEE6HQU\nmm1m9IiIiIjKrLCBXsW6gc1Dl0sRoB3s0cv4YKi0XH+OHgemExEREZVbYQO9musG/87DHj1Huhk9\nlm5SVswcvaZpxsI5ekRERESlVNi7wIrXDabycC/rCKw9ehkfDJVWd2C6Lt2s8MFIREREVEo5CJGS\nqeZwjp7pdMg9epSV/tLNPOxfJSIiIqLJK2yg57lOkDnLw82s+N0OgXwEnlROjiNQCmh2WLpJRERE\nVGaFvgs0IxbyEOjZh5CDw6GScgR6jp4p3WTXTSIiIqJSKnSgZ0Ys5CPQk9B/E02S689zbLF0k4iI\niKjUih3omYxeDgIr+346B4dDJWVKN1t+180KSzeJiIiISqnQd4Emo5ePOXrM6FH2TPdX0xiIGT0i\nIiKicip0oJevPXr2uIfsj4fKyXXE36PnZ/ScQj/FiYiIiCihQt8FBhm9HGTQWLpJeeCIQKluRs9j\nMxYiIiKiUip2oJejjJ59DHkIPKmczBy9pp/R83Lw3CAiIiKiySt0oFfx8tOMhXv0KA8c6R2Yzjl6\nREREROVU6LvAWo4yepyjR3mgSzeBZpulm0RERERlVuhAr+Lpm9h8BHrdYxBm9CgjruMPTO+wdJOI\niIiozDIN9ETk9SKiRGRnks/v7tFL9bASYUaP8mBd6Sa7bhIRERGVUmZ3gSJyKYDnAvhG0q9hxivk\nYU8c9+hRHpiB6UHpJlcdiIiIiEopy+X+XwPwMwBU0i9gxivkrXSTSRTKiivdOXqO6MCPiIiIiMon\nk5BERF4C4FGl1OcifOxrROQeEbnn1KlTPf+X3zl62R8PlZMjQLuj9+ix4yYRERFReXnj+sIi8o8A\n9ob815sAvBG6bHMkpdQ7ALwDAI4dO9aT/cvTHD2Hc/QoB8zjsNnusGyTiIiIqMTGFugppZ4T9n4R\neRKAywF8zs98HQDwaRG5TSl1Is73MBm9PNzQCpuxUA6YmZKNFgM9IiIiojIbW6A3iFLqCwB2m7dF\n5CEAx5RSp+N+raAZSw5uaB02Y6EcMM+FtVY7eH4QERERUfkU+k4waMaSg8DK7Zmjl+GBUKk5VkYv\nDyXNRERERJSNiWf0+imlDiX93Dxl9HpLN7M/Hionk8RrtDvM6BERERGVWKHvBGt5Ha/AQI8yYh57\na80OPJePQyIiIqKyKnSgd+uh7XjukT2YrrhZH0pPA5YcxJ1UUkHpZpulm0RERERllnnp5kbcdvl2\n3Hb59qwPA0Bv+Sjn6FFW3KAZSwcVp9DrOERERES0AbwTTIn0lG5meCBUauaxt9Zi6SYRERFRmTHQ\nS4nDZiyUAyazzDl6REREROXGQC8lbMZCedAdmN6Gx66bRERERKXFO8GU2MkTxnmUlaDrJufoERER\nEZUaA72UCDN6lAN26WaFe/SIiIiISouBXkp6Sjf5W6WM2APTPT4QiYiIiEqLd4IpsbdDuczoUUZ6\nBqazdJOIiIiotBjopcTO6HGOHmXFHpjO8QpERERE5cVALyWco0d5YBqwtDuKXTeJiIiISox3ginh\nHD3KA/txyNJNIiIiovJioJcSztGjPLAfe2zGQkRERFRevBNMCefoUR7Ys/M4XoGIiIiovBjopaRn\njx5L5igjdkaPA9OJiIiIyouBXkocNmOhHHB6Mnp8ehMRERGVFe8EU8JmLJQHLjN6RERERAQGeqnp\nnaOX4YFQqfV03eQePSIiIqLSYqCXEmFGj3Kgp3STXTeJiIiISot3ginheAXKA7tck6WbREREROXF\nQC8l9k01768pK/YiA8crEBEREZUXA72USM8cPd5gUzZ69+jx6U1ERERUVrwTTAnHK1Ae2Jlljw9E\nIiIiotJioJcS7tGjPLAfewz0iIiIiMqLgV5KOEeP8qAn0GPpJhEREVFp8U4wJcI5epQDLN0kIiIi\nIoCBXmqY0aM8sJN4zOgRERERlRfvBFPCZiyUB8I9ekREREQEBnqpYTMWygO3Z48eH4dEREREZcVA\nLyW9c/SyOw4qt949enx6ExEREZUV7wRTYrJ4IhyYTtmxH3os3SQiIiIqLwZ6KTGZFJZtUpZ6Mnos\n3SQiIiIqLQZ6KTH310yiUJbsPXoVdt0kIiIiKi3eCabElGsyo0dZssuGXa46EBEREZUWA72UdDN6\nvLmm7NjBXYWlm0RERESlxUAvJU6Q0cv4QKjUesYrsOsmERERUWnxTjAlDks3KQfEekazdJOIiIio\nvBjopcTEd4zzKEtsxkJEREREAAO91DhmvAKzKJQhO4vHjB4RERFReTHQSwmbsVAe2A8/NmMhIiIi\nKi8GeilhMxbKg55mLCzdJCIiIiot3gmmpLtHj5EeZccu1/S46kBERERUWgz0UsKMHuWBCAM9IiIi\nImKglxqX4xUoJ0xWj6WbREREROXFO8GUcI4e5YVZdGBGj4iIiKi8GOilxAyqZpxHWTOPQY9dN4mI\niIhKi4FeSpjRo7wwpZsVh09vIiIiorLinWBKunP0sj0OIlcEIoDDByMRERFRaTHQSwkzepQXIszm\nEREREZUd7wZT0p2jl+1xELmO9MzTIyIiIqLyYaCXEmb0KC9cR9iIhYiIiKjkMgv0ROR1InKviHxJ\nRP7frI4jLQz0KC9EBBXO0CMiIiIqNS+LbyoidwJ4CYCjSqk1EdmdxXGkyWHpJuWEK8JcPREREVHJ\nZRLoAXgtgF9SSq0BgFLqZEbHkRphRo9ywnUEjsr6KIiIiIgoS1mt+18N4A4R+YSIfFhEbs3oOFLl\nOgI2O6SsOQ7gsXSTiIiIqNTGltETkX8EsDfkv97kf9/tAJ4K4FYAfy4iVyil1uUhROQ1AF4DAAcP\nHhzX4abCEWb0KHuOiC7fJCIiIqLSGlugp5R6zqD/E5HXAniPH9h9UkQ6AHYCOBXydd4B4B0AcOzY\nsVwXpIlIUMJJlBVX2HWTiIiIqOyyqu96H4A7AUBErgZQBXA6o2NJjSMA768pa44j8FhDTERERFRq\nWTVjeSeAd4rIFwE0ALw6rGyzaBwRlm5S5hwBM3pEREREJZdJoKeUagD4niy+9zgx0KM8cETgOXwc\nEhEREZUZ67tSJMI5epQ9l6WbRERERKXHu8EUMaNHeeCwGQsRERFR6THQS5Ej4Bw9ytxc3cOWqUrW\nh0FEREREGcqqGcumxIwe5cGv3H2Ue/SIiIiISo6BXoo4R4/yYN/WqawPgYiIiIgyxkLDFLmOLt8k\nIiIiIiLKEgO9FLF0k4iIiIiI8oCBXop0oJf1URARERERUdkx0EuRnqPHSI+IiIiIiLLFQC9FzOgR\nEREREVEeMNBLkSPgHj0iIiIiIsocA70UsRkLERERERHlAefopeiOwztx+c6ZrA+DiIiIiIhKjoFe\nin7+JTdkfQhEREREREQs3SQiIiIiItpsGOgRERERERFtMgz0iIiIiIiINhkGekRERERERJsMAz0i\nIiIiIqJNhoEeERERERHRJsNAj4iIiIiIaJNhoEdERERERLTJMNAjIiIiIiLaZBjoERERERERbTIM\n9IiIiIiIiDYZBnpERERERESbDAM9IiIiIiKiTYaBHhERERER0SbDQI+IiIiIiGiTYaBHRERERES0\nyTDQIyIiIiIi2mQY6BEREREREW0yopTK+hgiE5FTAB7O+jiox04Ap7M+CIqF56x4eM6KieeteHjO\nioXnK/94jsbjMqXUrlEfVKhAj/JHRO5RSh3L+jgoOp6z4uE5Kyaet+LhOSsWnq/84znKFks3iYiI\niIiINhkGekRERERERJsMAz3aqHdkfQAUG89Z8fCcFRPPW/HwnBULz1f+8RxliHv0iIiIiIiINhlm\n9IiIiIiIiDYZBnpEREQJiYhkfQxERERhGOjRSCKyy/o3b2oKQESeaZ83yjcReb2IPNf/N59jxTJn\n/sFzl388R8XDc5Z/vE/MLwZ6NJCIPE9EPgrgN0TkNwBAcVNnrvnn7CMAvhvAWtbHQ8OJyHNF5O8A\nvAHAqwA+x4pCRO4SkX8B8Csi8jMAz12eichLRORdAI5mfSwUDc9Z/vE+Mf+8rA+A8sVfiXEA/ACA\n7wfw/wD4NIDfE5E7lVIfyvL4aD3/nAmA7wDwOwB+QCn1F9keFQ3in68KgJ8F8Azo51gVwK0iUgHQ\n4gtlvonIAQBvAfBLAP4ZwJ+KyA6l1BtERHj+8kVE7gTwCwCaAG4XkYeVUucyPiwKYZ4/PGf5xfvE\nYmFGjwLmAquUagP4FwBPV0q9H0ADwEUAXxcRz3xshodKPuucdQA8BuAPAXzd/7+Xi8gBP3jgOcsB\n63w1ALxfKXWHUuqvAZwD8J1KqSaDhHzqe/5cC+ALSqm/VP/jqGgAAAsDSURBVEotAPgtAD8lIlfz\n/OXSgwCeC+CnATwFwI3ZHg6F6VskeRDAt4DnLFd4n1g8DPQIACAiPwbgPSLyUyJyiVLqy0qplojc\nAuA9AA4B+BUAv28+JaNDJZ91zv6DiOyEvuh+HsDbReSrAO4G8BsA3m4+JZsjJSD0OfYp//0VpdSH\nATwgIs/P9igpTN+5mwdwH4Cni8g3+R+yG8CXALzJ/3g+1zIkIj8iIt/m/1sAHFdKnVBKfRDAEwCe\nISL7Mz1I6tH3HNurlHpIKfU4z1l+8D6xmBjoEUTkpQBeDeBt0KtmbxKRm/z/PgfgFUqpW6FT9C8Q\nkSf7GSTKSN85exKAnwdwFYC/gi4l+06l1N3Q5+xbec6yNeA5ZvadtERkO4CHAbQzOkQaIOTc/TL0\n/tdfA/AaEflX6GzRywDcJCKHmNXLhojMichvQ5dFv0tEPP9cKCv4/mMAV0NniezP5U1pRkKeY//Z\nugcBeM4yx/vE4mKgR4C+eL7dr6t+C3TJxE8AgFLqQaXUN/x/LwH4cwDTGR0ndfWfs4cA/LRS6jEA\nP6+U+gwA+Hsa3gdgNqPjJG3Yc0wppc4CmAJwJwCICK/N+RF27n5eKfX7AH4IwE8ppb4LwDcAfBK6\nfIky4JfRflgptRd60eu3/P8KSgKVUp8H8CkAN4jIs0TkDf77GZxnJ+w59uPmP3nOcoH3iQXFm4kS\ns1bDHoDu0gil1MPQL5DTIvKSvo//z9DZo69O8jipa8g5+wCAeRF5sVJq1fr4NwO4HsC9kz5WGvkc\nm+l7jv0xgNtEpM6V0OwNOXfvB7BdRF7q76n8pP9xvwBgBsDCxA+W7PP1Af/vnwTwChE5rJRqi4hn\nfcy7AfwggD8DsLPv82lCYl4fec4ywPvE4mOgVyIickxEdpu3rdWw/w1g2XrCnoAu/7vO/7zni24j\nfjWAlyulTk7uqMst5jn7EIAj/ufdISIfgj5n36aUemKCh11aSZ5j1gtpHcCfguWbmUjwXLvG/7zD\nIvJ+ADdAZ/eaEzzs0hp0vpRSSyLiKKVOQO9P/j3//S2/m+MMdPnZFwDcqJT6afvzaXxE5Dki8mTz\ndtTro4jMAvh18JyNXZJz5H8e7xNzioFeCYjI9SLyMQA/B2Cr9X4BAL9s7D0AfkRERCl1AbrUb8r/\n0K8A+GGl1KuUUo9P9ujLKYVz9hCAH1VKvZLnbPw2cL5q1gvp+5VSv8tAYbI2cO7q/oeegH6uvZgL\nKuM37Hz1lzwrpf4TgMtF5HYR2SMit/qlZT+ulHoBr42TISI3i8jfAHgv9F5y8/6RzzH/+rgK4Cd4\nzsZnA+eI94k5x0CvHH4CwHuVUi9SSt0H6D1A5gZTRKYB/D10e/53iMg+ADdDt8uF3/3qi9kcemlt\n9JwdV0p9OZtDL6Wk56tlvoDS7app8pKeuyag94UppR7J5tBLaeD5Ukp1/OzPFuvjfxnAvwL4KPx9\nQ8w2TIaIuCLyDgC/Cz3j9U/QzQB5MZ5jLZ6z8UjhHPE+MecY6G1i/hN4OwAF4Df9971U9LDfaf/t\nX4RewdkD4PXQbYz/BMB56GHANEE8Z8XC81VcPHfFEvF8/QJ0idkN/tvPB/A6AG8FcL3SY0xoQvzF\nq78FcIdS6n3Qz6U7Re9DbgGAiLwFfI5lhudo8xOWOG8uIvIMAKtKqU/4b9cBfAbAfwTwCuhNzCcA\nrEB3tXoXgJ9VSn3d+hrTSqnlSR97WfGcFQvPV3Hx3BXLRs+XiBwBsKCUOp7B4ZdS/zmz3i8Ang3g\nOwC8QSl1VvQey/8B4M1Kqfutj+VzbIx4jkpGKcU/m+APgDno+umzAN4JYJv1fz8DvWfrVf7b+wF8\nAsCzrY9xsv4ZyvaH56xYf3i+ivuH565Yf1I4X27WP0PZ/gw6Z9BDs01S4QB098Z9IZ/P5xjPEf+M\n4Q9LNzePBoAPAvge6Brqu63/ezt044BdAKCUehTAhwFUgGB/A9u5Tx7PWbHwfBUXz12xbPR8cb/r\n5IWeM+Xzz8sj0EH5t9ufyOfYxPAclRADvQITkVeJyDNEZKtSag26jfQ/ArgPwDERuRoAlFKL0GUt\nrxKRm0TktQCeAz3wEnzyTg7PWbHwfBUXz12x8HwVT9RzZoIEEfEAfA3Akv11eM7Gh+eIuEevYPwa\n6r3QG2E7AO6HHtL7E0qp0/7HHAbwauga7F+0Pvc7AByFHqD9RqXUlyZ8+KXEc1YsPF/FxXNXLDxf\nxZP0nFmBxK8BWFRKvTmTH6AEeI7IxkCvQETEVUq1/RWYn1VKfY+IuNAbZfcrpV5mfexLAdwF3W3s\ncQANpVRTRETxpE8Mz1mx8HwVF89dsfB8Fc8Gztkj0Psml3jOxovniPp5WR8AjeY/SX8BgCsifw1g\nHkAb0K1xReQnADwmIs9QfvtopdR7ReQ66La5swDuBPAVPnkng+esWHi+iovnrlh4voqH5yz/eI5o\nEO7RyznRbXD/HcA2AF+HfiI3oeec3AYEtdNv8f+Yz7sbwJsAfAjAjUqpr0z0wEuM56xYeL6Ki+eu\nWHi+iofnLP94jmgYlm7mnIjcAeCQUuqP/LffDuAL0HODXqeUerKIOAB2A3gb9OyTB/3Pg1Lqoxkd\nemnxnBULz1dx8dwVC89X8fCc5R/PEQ3DjF7+/TuAP/fT8gDwrwAOKqX+F3SK/nX+Ss0BAC2llOk8\n9lE+eTPDc1YsPF/FxXNXLDxfxcNzln88RzQQA72cU0otK6XWVHcu0F0ATvn//j4A14nIXwF4N4DP\nZHGM1IvnrFh4voqL565YeL6Kh+cs/3iOaBg2YykIf6VGAdgD4AP+uxcAvBHADQAeVHpwLOUEz1mx\n8HwVF89dsfB8FQ/PWf7xHFEYZvSKowOgAuA0gBv91Zk3A+gopf6FT95c4jkrFp6v4uK5Kxaer+Lh\nOcs/niNah81YCkREngrgY/6fP1BK/X7Gh0Qj8JwVC89XcfHcFQvPV/HwnOUfzxH1Y6BXICJyAMAr\nAbxVKbWW9fHQaDxnxcLzVVw8d8XC81U8PGf5x3NE/RjoERERERERbTLco0dERERERLTJMNAjIiIi\nIiLaZBjoERERERERbTIM9IiIiIiIiDYZBnpERERERESbDAM9IiIqPRFpi8hnReRLIvI5EXm9iAx9\njRSRQyLyXZM6RiIiojgY6BEREQErSqmblFLXA7gLwPMB/NyIzzkEgIEeERHlEufoERFR6YnIolJq\n1nr7CgCfArATwGUA/gjAjP/fP6aU+piI/BuA6wA8COBdAN4G4JcAPBNADcBvKaV+Z2I/BBERkYWB\nHhERlV5/oOe/7zyAawAsAOgopVZF5DCAdyuljonIMwH8R6XUC/2Pfw2A3UqpXxSRGoB/BXC3UurB\nif4wREREALysD4CIiCjnKgB+U0RuAtAGcPWAj3sugBtF5Nv9t7cAOAyd8SMiIpooBnpERER9/NLN\nNoCT0Hv1ngBwFHpv++qgTwPwOqXU303kIImIiIZgMxYiIiKLiOwC8NsAflPp/Q1bADyulOoAeCUA\n1//QBQBz1qf+HYDXikjF/zpXi8gMiIiIMsCMHhERETAlIp+FLtNsQTdfeav/f28H8H9E5FUA/hbA\nkv/+zwNoi8jnAPwvAL8O3Ynz0yIiAE4B+NZJ/QBEREQ2NmMhIiIiIiLaZFi6SUREREREtMkw0CMi\nIiIiItpkGOgRERERERFtMgz0iIiIiIiINhkGekRERERERJsMAz0iIiIiIqJNhoEeERERERHRJsNA\nj4iIiIiIaJP5/wEZZNXcp+hfmQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb5557f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Daily Stock Return\n",
    "ret = apple[\"Adj Close\"].pct_change()  # calculating returns is also easy with pandas. Just call .pct_change() \n",
    "(100*ret).plot() # plot % return\n",
    "ylabel('close-close % change')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.217321742942\n"
     ]
    }
   ],
   "source": [
    " # Compute daily volatility  \n",
    "historical_vol_daily = np.std(ret,axis=0)  \n",
    "\n",
    "# Convert daily volatility to annual volatility, assuming 252 trading days  \n",
    "historical_vol_annually = historical_vol_daily*math.sqrt(252)  \n",
    "\n",
    "# Return estimate of annual volatility  \n",
    "print(historical_vol_annually)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Linear regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "from pylab import *\n",
    "import pandas as pd\n",
    "import pandas_datareader.data as web\n",
    "import datetime\n",
    "import sys\n",
    "import numpy as np\n",
    "import scipy as sp\n",
    "import pylab\n",
    "from scipy.optimize import leastsq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pandas_datareader.data as web\n",
    "import datetime\n",
    " \n",
    "# We will look at stock prices over the past year, starting at January 1, 2016\n",
    "start = datetime.datetime(2015,4,1)\n",
    "end = datetime.datetime(2015,6,1)\n",
    " \n",
    "# Let's get Apple stock data; Apple's ticker symbol is AAPL\n",
    "# First argument is the series we want, second is the source (\"yahoo\" for Yahoo! Finance), third is the start date, fourth is the end date\n",
    "jpm = web.DataReader(\"JPM\", \"yahoo\", start, end)\n",
    "spy = web.DataReader(\"SPY\", \"yahoo\", start, end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "# we're using yahoo finance data, pandas datareader will import the data we need\n",
    "\n",
    "from pandas_datareader.data import DataReader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "symbols = [\"JPM\", \"SPY\"]\n",
    "# df is the main dataframe that'll hold the Adjusted closing prices\n",
    "df = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  JPM         SPY\n",
      "Date                             \n",
      "2015-04-01  56.797905  197.326422\n",
      "2015-04-02  57.337935  198.036303\n",
      "2015-04-06  57.290564  199.369719\n",
      "2015-04-07  57.650582  198.842105\n",
      "2015-04-08  57.840067  199.513607\n"
     ]
    }
   ],
   "source": [
    "for symbol in symbols:\n",
    "    dftemp = DataReader(symbol,\"yahoo\",start)\n",
    "    \n",
    "    # we only need the adjusted close price.\n",
    "    df[symbol] = dftemp[\"Adj Close\"]\n",
    "\n",
    "# lets take a look,\n",
    "print df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "formula: y = [ 1.21354543]x + [ 125.97901614]\n"
     ]
    }
   ],
   "source": [
    "npMatrix = np.matrix(df)\n",
    "X, Y = npMatrix[:,0], npMatrix[:,1]\n",
    "mdl = LinearRegression().fit(X,Y) # either this or the next line\n",
    "#mdl = LinearRegression().fit(filtered_data[['x']],filtered_data.y)\n",
    "m = mdl.coef_[0]\n",
    "b = mdl.intercept_\n",
    "print \"formula: y = {0}x + {1}\".format(m, b) # following slope intercept form"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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uewBvRq+JtnUEWgHHAQPMrHaayyxSLcTeE6MyfRhGEV15kEJacgTj6MXdHMj7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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xe489390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X,Y, color='blue')\n",
    "plt.plot([0,100],[b,m*100+b],'r')\n",
    "plt.title('Linear Regression JPM / SPY', fontsize = 20)\n",
    "plt.xlabel('JPM', fontsize = 15)\n",
    "plt.ylabel('SPY', fontsize = 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}