heritability.ipynb.json

{
 "metadata": {
  "gist_id": "96f92cef075385ea4d55",
  "name": "",
  "signature": "sha256:39561068e6a598600e896406472b3ef22e3c6e2bdc8379e78e6fb0787b099a38"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import scipy as sp\n",
      "import pandas as pd\n",
      "import statsmodels as sm\n",
      "import matplotlib.pyplot as plt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import seaborn as sns\n",
      "sns.set_style(\"white\")\n",
      "sns.set_context(\"talk\", font_scale=1.25)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "loc = 50\n",
      "scale = 2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "parent_heights = sp.random.normal(loc=loc, scale=scale, size=500)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.hist(parent_heights)\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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HANA4gQ8AoHECHwBA4wQ+AIDGCXwAAI0T+AAAGifwAQA0TuADAGicwAcA0DiBDwCgcacP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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x114a9dd50>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h2 = 0.8\n",
      "S = 0.65"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "offspring_heights = []\n",
      "for p in parent_heights:\n",
      "    r = sp.random.random()\n",
      "    if r < h2:\n",
      "        if sp.random.random() > 0.5:\n",
      "            offspring_heights.append(p + p*sp.random.uniform(0, 0.1))\n",
      "        else:\n",
      "            offspring_heights.append(p - p*sp.random.uniform(0, 0.1))\n",
      "    else:\n",
      "        offspring_heights.append(sp.random.normal(scale=scale, loc=loc))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.hist(offspring_heights)\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAnwAAAG8CAYAAABE7Xh/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGifwAQA0TuADAGicwAcA0DiBDwCgcf8fZ6E/AyDd3t4AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x117021f50>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "reg = sp.stats.linregress(parent_heights, \n",
      "                          offspring_heights)\n",
      "print reg\n",
      "slope, intercept, r_value, p_value, std_err = reg"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(0.84072665868636876, 7.9811226306756353, 0.5179824997253174, 1.1337519327631468e-35, 0.062214246508029737)\n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.scatter(parent_heights, offspring_heights)\n",
      "plt.xlabel(\"Parent height (cm)\")\n",
      "plt.ylabel(\"Offpring height (cm)\")\n",
      "plt.title(\"y=%.5fx + %.5f ($r^2$ = %.2f, $p$ = %.5f)\" % (slope, \n",
      "                                                         intercept, \n",
      "                                                         r_value**2,\n",
      "                                                         p_value))\n",
      "plt.plot(parent_heights,parent_heights*slope+intercept, 'r-')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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jjgpi4wLptAHzZJi8MlkCeZm8EgeM1tq/BfqBdwH7k5/DMcC3AgbOuRekrMPr\ngF9VcL+IyJRTy0Cl3FazuECrUQFLXBBbrUC62SevNGsgL1NLmhbGK4EPA7cDP8LnYCyUPKnjuMOB\n3ay1twFvxI9XvBb4jHPuuQT3i4hMSbUKVIoFo+UGfY0MWMqZlDLVupk1MUfqIU3A+G7gSudctd9V\nr8UHmucDK4CjgQuA/YB/SnC/iEjTSxOM1aO1LmpsYqmgr1igNdkClsnSzSzSTNIEjM8B91bz4GFS\n8OOAx5xzvwk3/8ha+yxwqbX2s6Xud849VM06iYhUW5oWuKh9BwdPYf3624BkAWQ5AWeSoK8ZA61y\nWwur1XrbDGMHp1qLqTSpIAgS3Ywx/2KMud0Ys0fSx5R7M8a83hizyxhzXDn35+x3kDEmePTRRwMR\nkUbp61sfQCaAILxlgr6+9Yn3bW9fEm7LBJ2dlwYjIyNFjzUyMhJ0dl5adP+RkZGgr2990Ne3Pm97\nmjqmPWatFTunehy3keddWJdGXAOZPB599NHAGBMYYw4KyojN0rQwXgTcAvzaWvtt4H+JGLPonLss\naYHW2lnA+4BvO+dyU+bsFf78o7V2acz9f0hRfxGRSWlo6M0k7e6NailctWojra2tjI6OsmnTI2zf\nfj6Q39JZbitVtoVtwYL9WLDgRlpb9657y2OjJqU0U1d8s0/MkckvTcB4PH4t6d2AuE+RxAEjsDvw\nZfzYxM/mbP8Q8GfgUfwEm2L3353iWCIiDVEYjM2Zs4rR0Vn092+Y0I1ZuO+ee57Ls89+NrLcXPnr\nJs8jG8QAXH317QwNrQ7/WoX/X79tLMDp6loYBn37smCBDy6TBH2F3eednbWd7BLX/dsMXcMiU1lL\nECSb2GytfQA/M/pc4Df4MY0TOOceTlMBa+21wAnAxcBdwPzwGJ90zq0udX+Jsg8CHtqyZQvt7e1p\nqiUikliSYCW7T2ErX1SQlRv8bd58BvB1wAdl7e093Htv74T9cwM3v27yhUAb7e09DA2dj8+GBrAT\nGAROBHbS27uRW255fELQB5Q8p/7+DXR3L2I8ON1JX19tWtjigtN6B65J6iQlPP88tLTAbruV3leq\nYmhoiHnz5gG8Im2sBulaGGcD/+yc+07ag5RwBvA74GP4oPBB4HTn3DUJ7xcRaZikE1qyXYb9/RvC\nYDG/GzPbygc+QMsGXZs374/v1BkERvnoR18xIZAr7Bp96qm+sXWTR0cPYcWKwgBmFNhJZ+dqYN+I\nLuwbueURscWyAAAgAElEQVSWJ5oqr19c92+juoZrNQloyraW/vGP8KlPwbXXjm+77z549asbVydJ\nLE3A+Avg5dWugHNuFOgNb6nvFxFppGoEK6OjT0cGnfnd04vo6Lic7353D+66a0neflGy6yZnMhlu\nuSW/O/y442bR2jo4lhKn0B133Me2bStLnlPScY/1C4AywCZglNHRXdF7VLku1R47OOWScN9zD3z8\n4/DjH0ff/8wz9a2PlC/p7BhjzFuNMX8yxpxmjNm3nBk29b5plrSIpBU12zRuBmra2cVRM2t7e9dF\nljEyMhL09q4L5s9fFvT2ro3dr5yZ0Wnrk/R6lSq/nFm8ceWMjIwEHR09Aawcu3/OnJWJzrUaM4qr\nOUO5ktnqTeOMM4KcE4i+veQlQbBlS6NrOq1UOks6TfD1S2PMH8J0NruMMc8bY54Nb89kf5ZTiVrd\nFDCKSBpRAcXw8HDJYCxtEFIYYEQFCb2961IFcpUELYWPrWZgVc0AKO4ckwS5tQjGqh2EllPHhqfU\nefrpIHj5y0sHiW96UxD84hf1r58EQVDftDp3JWmwLLelU0Sk0aK6l089tSe2e7atrY3BwVM49dQe\nAK655ryS3YeF3ZhRXbtRYwsXLLiRzs7oLuBKukajHttsCboh/hxbW1vrXBuv2uMn06Y3algX9m9/\nC698Zen9TjkF/uVfYN99a1sfqbnEAaNz7pSo7dbaFuecAkURmZYymQyLFl0fBpWwaFH6L+yoyRNR\nYwtbW/euWyBXKgBNOhawXquQJDnOZFgRJe1EmrpO+Nm0CRYtKr3f3/4tPPoovPCF1a+DNE6a5khj\nzDxjzHeNMbNztg0YY35ojHljOU2ctbypS1pE0iinS7pWY86aaRWRQsPDw+HqM+sC2JFo9Zl6dJkm\nOU6169Lo56nmYx6XLSvd1QxBcPLJQbBrV/WOK1VXaZd0mjyM84FvAcPAu5xz94fbTwc+BbQD73DO\n/aRGsW1qysMoImlFtZzFtaZF5SLMprRJ8vi0dWm0TCbDoYeuYGhoZbhlNbCEvr4tiVq1Sp1TM55z\nKY2sc9VzQY6OwmGHwYMPlt733/4NPvrR8o4jdVdpHsY0AeNP8GMUj3HOPV1w397AD4CnnXPvSFuJ\nWlHAKCK1Fpc0u7NzNRs2fJB58/rC5f3eS2fndVUZY1bvICU/mXhhIvCN9PW1lgwYSwU3SoRdnopf\nC7/7HRx0ULJ9f/lLeM1r0pUvTaHSgDFN9+6IMeb0mPu7jDFPltPMWaubuqRFpB6y3ZzHHntmAGvC\nrtq1AawJZs5cOtZdCZcGsKPpZuamPZ5PXzMy1gXa3r4k0fFLdZ9OiZQyk8WXvpSsq3mvvYKgSYZC\nSGUq7ZJOsybPU8ABMffvBzybOmIVEZnk2tra6OpayH337QmcDBwPPAa0MDLyRXx39T745f1urfh4\n+RMd9gknOkycJAO+9am/fwP9/RvIZDJVOR4sA24CdtLe3sOdd15StFUr9/ijo6NlHV+q5A1v8Mvx\ntbTAuecW3+/442HXLh8yPv00qIVXIFXAeCtwlrV2TuEd1trX4T8Jv1utiomI1FI1AqlcAwObwnF9\nuUHVAxP2a2+/na6uhRUfL4lsF2939yK6uxcxb94VVTlXgPnz76Gvb5B77+1l9uzZiY6/adMjzJmz\nCt+NvTOcpTx+Lbq6FoYphaLvl5RGR8cDxJYWuCsmO97VV4+3K37ta35/kRxp8jBeBBwL3GmtvRP4\nTbj9YOCN+H+nu6tbPRGR6qtf7rpDgFX44JGSrXFJJU0PU62UK1HHu+mm3pLnsWrVTXnH3779fHp7\nb+RDH4pOGVOrtZmnlfvug0MPTbbvrbfCe95T2/rIlJEmD+MOa+3hwHJgAfAhfAvlI8AVwGXOuSdq\nUksRkSqqRe66wqDKB4ofo6Pj/7Fw4UZaW1vp6iodZCVRTrLwcmUnVCxYsC8LFmTPwwen/f0bgOKz\nna+++nZ89/y41ta9Y69z0gTkk2k2dc3r+qlPweWXJ9v3scdgv/2qe3yZFtK0MOKc+xM+YFxem+qI\niEwuucHA4OAprF8/GI7Vm0Vr6xa6uqofzCVNFl5poupis5aBki20vov+UnJbWF/2sovo6vpsWecc\nV6+6rW5ShprVNU2X8a5d6mKWihUNGK21H3DOfaOSwq21H3TO/XslZYiIpJGkNScukErTGtSowCVp\nC2mlXbzjxwmATWzbth+rVn2N1ta9Jxx/1aqNY8vz5Y87fA7YCEAQPFfG2cbVK/r4J530Ttavv22s\nLo0MJKvWmj06CnvtlWzfk0+G669PV75ICXEtjCustRcAnwP+wzmXaAZ0mJPxA/hk3i2AAkYRqYuk\nAVyxQCrp43NzEsatM11PW7dujwyOKllj2ssA1+HnNcLVV/ewdOlhE/a6+urbGRpaDfjrNjh4CmvW\nXBhu89dnx46dNbs+48fPsHLlpTz1VN9YXZq19bGkn/0MOjqS7TswAGecUdv6yLQWN0t6DnADcC3w\nhLX2a9bak6y1h1trZ1prW6y1u1lrX2KtPcJa+3Fr7Q3A48CVwFeBhK90EZF85cxiTpNuJhtILV9+\n4lgwUezxuXXZsWPH2MzfzZsnBk71UDibGFaxefP5E2ZBVzoTvKtrIe3tF+KDRX9N/EzwXXnHb2/v\nCbufx6/b+vW3sXTpmys+12L1Kn78LWGwWPo1UA+pZ35ffPH4rOZSweIDD4zPbFawKDVWtIXROfcc\nsMpaex2wBDgDWFyivPuAXmCtc646uRtEZNqpVVdvOZMPRkefzqvLmjVn57SaLSZ3jF6pMYLVmvyQ\nbSFdvLgnDFrPBdryWjircQ3b2tpYuvTNrFiRv721de+8FtrR0UNYsWJiucuWLeaWW8ofQxlXryTH\nbwaJhgXMmOHzHSbx3HOw++5VrqVIAmmyfBtjXmWMWWKM+awxZsAYs8YY8xljzMnGmAPKyRxey5tW\nehGZnMpd8SNuBZQkq6NE7dPbu66gLoV/7wiOPfbMYP78ZUFv79qiK55Ua3WW7KoyfX3rI+qWCebP\nX1b0vnJWTSn3uuVe92x9a7UaTf7xdwQzZnyiYXVJ5Jlnkq2yAkHQ3t64esqUUulKLw0P6mp5U8Ao\nMjlVskRcsaAgaZmFj5/4uB1Be/uysYCko6MnmDNnZclAMMnxSwU0hYFZ4bF9oLRjbLm+ai2zlyTQ\nShOMjYyMBL296yYE2ZUEdLmPHR4enlBOvZdTnOBXv0oeJH7+8/Wrl0wbChgVMIpMObX4cq+k1bKj\noydsWVwXdHT05AUkSVvySh0/yTlHldHbuzbo61sfzJ+/LAwWowPbugdIRYyMjOQFubBy7JrWMqBr\nyDrV/f3Jg8R7761tXWTaq+da0iIiiVQ62SI77quvb5C+vsGqjF+sZNm5lpY98Amoj6elZY+8CTPZ\nVC6VHD+TybB48Qq2bdsPn8Im+WSNbCLso4/uAHKvURtLlx5S1WuYRKnnfmBgE3fdtYzcJRS3bz+A\nU0/9fOIJS40We46zZo1PWlleImXxM8+Mh4yHHFK7CotUQzlR5mS5qYVRpP6Stg42YjxZOcesRstg\n3PELHw+XBjBStMu6kjGatVZYh/b2ieM6o1pk4cqwhbR2LYDVHEOaW84b37AyeSvii15UtfMRSUtd\n0goYRZpK0rF6jQ5ukqrG2MO05cO6sWtSWHbcsRo9qaPUuQRBEPT2rg0gv0t69uwTa94lHQTVuT59\nfeuD1/GT5EHiZz9b1XMQKVdTBYzGmBdUs7wq1EcBo0gVpPmiTRJgNWQ8WZlqGdyOjIwExx575oRr\nMX/+srHgsJrHrvbklULRAeP6vOfX77Mj3O5/7+1dV/Gxa2758uRB4t13N7q2IhPULWA0xjxkjDku\n5v4TjDF/KKcStbopYJRm0YxfhEnrlLbLtbd3bcnJFpMpYAyC6jx/US2FfjLNhXktbnPmrBw7RjWv\nU6Xpcco5RlT3euGkl9zzbTpJA0QIgqefbnRtRWJVGjDGrSU9G3gHfgR2C3Ag8C5r7T4Ru+8GfBRI\nNvpbZBpp1HrD1apT1Fq4ixf3cPTRHXnJp/PLzNDefjZLl76ZZcsmlhu3lnMzqnR5vajrvWDBvmzf\nfgB+Mk0ADAKjHHfcrLHrNTr6NH4d5lZgIf6juDxJ1jSudN3j7GSlVas2hkv1XQq0THh+/ZrS1V1f\nuiqefx72iFsxN19/3/qar1VdrWTvIpWKe2f8EVgBHJyzrSu8FXNVNSolMpVU+iXciDrlfkmNjo5O\nePzmzYexefOivECzcFm9oaHVtLYORn7BtbW1MTh4Cqee2gPANdecV9YX4WT5Mo263i9+cQ9wGJAB\ntoR7vpfWVv97JpPhP/7jMbKryMAqOjqeo6vrvKLHKed65D/XCVcbidHW1kZPz6ksW7Y4py5n5S2/\nuH37+WSvxfbtE9eXruvzet99cOihyfb98IfhxhvH/iwxB7pizfjPpkxfcUsDjlprjwVeEW66DbgM\n+H7E7s8DTzjnfl39KopIPRV+SXV0XM6cOavCVCjgl8I7l/HUJ+mD30wmw6JF17Nt20oAFi1K/0U4\n2b9M5849jN///jfcffclQD8AM2Ys56STLgRg1aqbctLPACxj4cKNRc+v1PWIatU96aRT8h4zZ84q\nOjouDwO6ylp+y22VTfK8VhxQ9vb6NZuTuO02eMc70pVfJc34z6ZMY0n7ro0xpxhjXlFOv3ejbhrD\nKM2gGWcEx9UpXXLo/LFpSc+zGmPzosrIThZplGJjHYtdm2JJv0dGRkqu1FJ6RZrSs7mjn+t1NR1v\nW+p1Us00RnnSjEfcubNq446rPYmomcf6SnOr2RjGQs6562sYt4pMWdlxXQMDg0B+99xkqVM2OXRX\n18K81p/CFqgFC/blxS/uYe7cw8bGLtaze3Hz5sOYN++KslorK61jXMtYsetdLOn3wMCmcPzfasCX\n197eQ1dXb9FjLViwX2GN2Lp1e945JWn1a21trWkLVqXvh8Stbrt2we67J69YEIz9mslkeMc7vjTW\nqv71r6/iBz84N/XrotJW8Mk21lemuKSRpTGm1RhzuTHmQWPMX4wxz+bcnsn+LCdqrdVNLYwi6ZVq\nwUmSfDo3h2Ca7ZXUMy7hdSXnm1Q5rUHFjj1e1kjgU8+sC3p718Yeq7d3bU5ZO8J1pUsnT59Mrd9B\nUOI6P/BA8lbEBQuK1iGq5Teb+ieNJK2ltUxzJJKrbi2MwKXAJ4EHgFuAqNHRQcQ2EZlESrUARbVS\nFWv1yf4e1RpUaatrtp6LF/ewefNhwFn4pfF2piqnkePEil3r/JalRXR2rmbZsvGWpWKzpxcs2I8X\nv7iH5557hu9/v6/kOU3G1u/CVrcvtX+Ic7o3Q/dJpQu/9VZ4z3tK7nbHHfck2laJpK2Plc7QF6mW\nNAHjR4BvAYuccwoMRaawenxJVeMYbW1t3HRTb/jF28L4Gs3x3XalZoGXo9zuw6jrEBc0TZw9fRGz\nZj3GN7/5an7+cz+Dur29Bz/7OioLWunj11PUcIC4OrW1tXHnr/towU8OYqjEAZ58EmbOTFWnuXMP\nYfPmVeTOUJ87N/1az3GvCU1okckmTcD4IuAWBYsiUijui7FWY7ByA43BwVNYvz5ZK9l4y84S4FZm\nz97K61//6FiwVW4dq91aVyxoGhjYVDB7+hIee+wCHnvsvLFtQ0MraW8/m6Gh1UD551Tr8aeJx/gF\nAey229ifJbNRBpV9TS1b9mE2bfo827f7XJGzZz8OzCKTyaS6Bs3YgitSrpYg4RvLWvtD4JfOuTNr\nW6XqsdYeBDy0ZcsW2tvbG10dkUkpadBQbL/c7Sed9E7Wr7+tZFlJ6lQ4+SYbaJSqb3//Brq75wHX\nkZ1QMnt2N6effgStra1Nnc8RsvVfxHjAuBPoAVbmbevt3Tg2qaacc4q7xtUSdS59fWEr26OPwgEH\nJCvo7W+HrVurVi/w579q1U18+ctb2bFjLtBKR8cjbN1aXs7QqPJrfX1Fcg0NDTFv3jyAVzjnHk5d\nQNLBjsaYTmPMiDHmHGPMS8oZMFnvmya9iFSmmpMiqllWsckESY7hHxudzibpeTRyEkL0ZJ/hIHd5\nwfb2ZcHw8HBFx6lHSpfCY3ycVcknrdx8c1XrEqW3d214XXeEr5mTgwsuWF218hv9WpLppdJJL7sV\nCySttc9aa58Jfz4L/AR4IT5r7/9aa5/P3pez3zPlxb0i0owKV2/x46w2NbysSo7R1bWQ9vbbE5WX\nyWTo799Af/8GMpnMWKtQd/ciursXMW/eFWQymarVv/B4UbLdnL29G2lvPxtYAszk8MP/wuzZZwIb\nGRo6n0WLrq9q3Wqhq2shj+3ZTkALAS1cNTZmsIg//Wk8ZPzAB2pevzvuuA/4GL41+nhgDVde+auq\nXdfssIPly09Uy6I0vbgxjDeUUZ7GN4rEmCxL2TW7YmMmkwSgbW1t3HnnJRx1VA9DQyvzHp+rWK7D\nWk1UKFyLe82ac8K1uBdHzpwtXH5vdPRVrFhxUdXqVrMcgDnjEdvCW8n9K1Tu+27u3MPYvPlW/NAF\nf12ffPILmpwi01M5zZKT5aYuaWkmzZjzrpRy6px2tZNK6pY0H2SaemYVW0mmnG7auGuS3T6e+28k\n7GZOd51q0YVctS7THTsSdzX/Dx1V7f6u5HU3MjISzJ59cs275kXqodIu6YYHdbW8KWCcOqbCWJ/J\nusxXmmtfTtLvRtY3Tunk2NHBR+HxkyYvH18KMNnrJOlxan2dirr++sRB4lPr1tXsn6lK33fDw8NB\ne/uymtRNpJ7qlrjbWruL/C7nbGaD3G3PAo8DdwG9zrm7K24ClWmv0uW1JpNm7LJOk6evVG65yZLf\nEaK7ZJctO4tlyyiaJiW6G3vfgmuyhMWLV4S/n894KpxLaW/vYWjosJJ1K/aeSJrCpWbvqZaSCW/G\nPf44vPSlAOwNbFmcacr0M7Nnz+bee3ubsm4idZU0sjTGrDDG/MEY85wx5lZjzCpjzOeMMV83xuw0\nxjxljNlgjPmWMSYTLh94RDlRbLVuamGcGiZry1yhJK1v+S1Olc90rbep8lxlFev2LtYyV7obeyTI\nnc3sfx/Ja8Hs7V1bskWr0utc1ecp6axmaEgLXT2GQohMBvVcGnB3fGviEc65X+beYa09ELgD+LVz\n7hJr7b7Aj4Fe4LhqBbcik1mpJL6FrXNDQys56qizuffef500LRo1myjRIIWtlclb5jLAJmCUjo5X\n8sc/Zq/JTfjVQ7J5B5fhl/g7fqwFs62tjWXLatfalslk2Lp1OzAKLCbBtJN8jz0G+++fbN+DD6b/\nYyvyci3We0WTaibPTvL8Z3sJ/PKNu+Xl9mzGHgSRxJJGlsaYHcaYC2Pu7zbGDOf8fZ4x5o/lRLHV\nuqmFcWqYjJNFyhHV6gPrJl0LXTVaYOLKaOQ4yFItcyMjI0FHR09eK+KcOSuD4eHhoK9vfeSkmfnz\nl6U+l3LfE4Xj8bI5Bks+/qqrkrckfu5zeQ+dSq3OSZ5//7zsyHsNdHZeGgwPD0+LzzFpXnWb9GKM\nedIY86mY+z9ljPlLzt+nGWNGyqlUtW4KGKeO6dANNDIyUvBl7r940ny5ToXrFBcM1eKfh1KTR170\notOCY475xFjQVyr4GZ/tHITdzeuC+fOXlTUxJc7w8HAwf/6yYP78ZEMX/OtryYT6Z+s2QYqu5uCh\nh2KPO1UCpVLP//j91ZthL1It9QwYv2OMGTbGvCLivnZjzKPGmK052waNMdvKqVS1bgoYZbLxLUBL\nAr+qRIKWnxyT8Ys5KsCN+1KudmtV1DXzq3tMbOmdMaMr+Od//nz4/Owoeo3H6xidHqdaLbDFZl7H\nj68sscJNmiBx165U9Z3s/8gEQen3mAJGaWb1DBhfa4z5kzHmaWPMTcaYy4wxFxtjvhq2Pj5pjJkT\n7nuXMWaXMeaEcipVrZsCRpmMyv1ynWxdf8W+fKPT2azL6dLdUbVzTJprcTwAOCvITkjq7V0b+fyM\njIwEc+asDGBNGKCtD4PH4nVN+5wXu0ZxwYxv+dyRF8S+btbSdEGilBwuoS5paVZ1m/TinPultXYO\ncDHwPuCD4V07gVuAHufcA9bal+JHfH/MOXdjlYdcikx59Ug9U0tJB/YXS8FTOHFmzpxVbNr0HNu3\nnw8sYsaMbp566kKgbWxSTbmTCUZHRydsmzv3sJxJKgCrgezEnT2AfRgaWklr62DR4zz33F+AR4Ev\n5pSxhNHRUfr7N+TVM81Eiuzjotxxxz1s27aS4pNLdgHrOJMWrshOdHks5uIAnHYafPnLJXaqnWac\nJBL3/hyfYLOJ0dFZwMZw0stZVZ18I9IQ5USZxpgWY8xLjDGzjDG7l1NGPW5qYZSpIGnrUy27pGtR\nh/xWsolj/cZXQFkbttisD2878iaKlHvexSaoZMu84IIrgz33/Mex7mfoCmC4ZMtmsa7f2bNPDo9X\nukU1eiJFfGvVxK708euUqhXxl78see3qYTIOsRBpZlrpRQGjTHK5wVF2YkWjVu8olnewvCAwPrCK\n677L70pdGxTmLuztXZv4mKVnPI+Egei6vHKDYHxiybHHnhUcfvjyFNdgYsB47LFnRtYz+USK/Puj\nJuv4rvBMAMmX4gsgGHnyyWIvicjnLep6VnucYj2HWEyVMZYicWoWMBpjnjXGfLjg72fCn4W37PZn\nyqlErW4KGKXZFQZjM2Z8IsidUBE1AaOWX5pJxxTGt64lr+/IyEjJyQD5s479/b2962KPmW1Zc84V\nnURUTl2TtrIWtly+/vUrij6XySdSxNdz5He/SxUklvOaiptsU+3WwHoFjGrJlOmi0oBxt5je6huA\nhwv+/mr4s/CWu11EEsofx7cPTz3VB2wB9mHbtrO54477GlYXPwZuU6oyTjrpncyY0Y0f2ryTGTO6\nOemkdxbdv62tjaOP7ogts7W1tei2TCbD6OjTtLf35B1z8+bz6e6ex2te8wWGhlYDxwPXsW3bkrwx\ncZ2dq8ce58dDRo8PzNZ1+fITWb78xNixZ21tbXzrW6cze/b9wAXAVwiCvzIykmHPPc+dcG2yY9v6\n+gbp6xucMH4xtp7XXeeX42tpoe3AA2Ov432vOwqCgP6+9bSQid23mGKvkWq8dgqlfX7KVYu6i0xF\nRSe9OOdOiftbZKpoxoH1WYUTMBqxckqa1VvWr78tnJDiB/Y/9dSFrF+/JXYST6nyi92fP1kkQ3v7\n2RxyyD78539eCOwPbODZZ7/A+KoqZ+NXVfHBZi0nIaxffxs7dlwVHjvD3Xd/ibvvPg0/H/Bs4M15\n1ybZRApfz+XdF8LMCxPV4w38kLvooLPTT6SBdM9nksk2lSr2/iv3+Wnm97PIpJa2SdIY80JjzHuM\nMaeH+Rf/zhjz8nKaN8PyZhhjng/T8OTetufsc7Ix5tfhetU/M8a8N2HZ6pKWWI3ujirVJV2tvH3l\n1KUwYXaSOpTbjViq/KT5GvO7tyfe396+ZMI40VrIr1vUCj7r03Wxpuhq3o0/B5AJOjp6xtIRRaV/\nKXUNkk62qXTiUbXXeU5bXrXqUM9xkBpzKeWo66QXY8xSY8yfw4DueWPMO40xC4wxzxlj+o0xLWkr\nYIw5MixvUfh79nZYeP8J4bEuMca8K8z7+Iwx5qgEZStglFjNkLswbtJLOWVU+oVb6aSZ8Yks68YC\ntFqIzkW4NufLf0ew556njQUC7e3LAudc4oTXlVyL/CBk4hhMWBcfmDz5ZKogMfe41Qokir03iq0w\nU86xq/3+q9U/LEkeX6/XfaP/yZXJq56Ju98fBnabjDFLwt/fGQZl3wr//njaCoRB6M6Y+x8wxqwr\n2PZjY8wtCcpWwCixmiFgrFSjvkCKfckWrldcq/oUO+/81XLuD9rblwS9veuKTuDJDzKrl2Q5e7ze\n3rU5s5djkn5/5SvJA8Q3v7mKVzJamuTg5QZczRIwliM/9dPEpOjt7UWWXKzQVPjMksaoZ8C4zRhz\nW04Oxl3GmHeG97UYY24xxtydtgLGmCuMMT8tct/fh8d5X8H284wxfzXG7FaibAWMEmsq/Lde6RdI\nOa1rcdet0elQ8o+fn9+xdDd28W2RM5NTzJyO3K+tLXmQeNttVb9+cXWLeo6jZnpHBdxJ30PN0CVd\njeOM/4NS+9e9AkYpV91WegEOA853zgXW2rw7wm3fYnxZgzQOB3az1t4GvBE/Kvxa4DPAq8N97i94\nzIPAC4CDgN+WcUwRoLYTHyaDqFVGBgdPYdGi62NXHim2Sku9V6iJXxUnA1wBnM3mzTBvnj+3wgkf\nc+cexubNxY6QATYBo4yO7sq/p+Da3XTT5SxceEC4skf+ZIu8era0JD6/PfkTR3ReNeH6l5J04kfc\nKjNR742o2cN33HFfiRVm4utV7vsvqqx6vZ8LX/9DQ5cyc+a5jIwcn7iMcifnpJm0JFJVSSNLY8wT\nxpgLwt/zWhjDbZcYY55IG7EaY/7P+DWqTzXGvNUY8xnj16u+Nhy/uMsYM7vgMceE219fomy1MMqk\nUW63XiWtKr61YuIqKqVaMOJaOSa2viyr2niudJM11k04t2IJrwvHnznniq4CE30NRoKiycf/8pfk\nrYhQlRbjWiRaL1Z2VJ7MYq2x1Wr9S1NWLSaIRF23Cy5YnXgoRqXXQpNepBz17JLeYIx5xBizrzHm\nxQVd0oeFgd+NaQ4edmW/1RjzqoLt3eFEl0+Hx9m/4P5swPi6EuUrYJRJoVFfIFGrqBRbkSRNffPH\nEe6oStdg2iDhmGM+MeHcCldyye57wQVrghe96LS8si+4YE3sdYibCb2IG5IHiYcemlefYmMHkz6/\naYLAcoLT4gF3/PNSbDhAOUFP0nrXqot6ZCSbnH1dAOuCjo6eVGM51a0sjVDLxN2FLgD2BH4FXBVu\n+5i19uvAdiDAdyMn5pwLnHM/cs79puCuzUAL8Lvw78K2+uzfT6Y5nkizqjR5cNKk0hPtBiwbOy4s\no2f+nVsAACAASURBVLPz1SUTJpdKNr1u3bcZGnozPudhdZIhp7lGbW1tvPWtR0w4Nwo+8rJdspdd\nthdPPvkFcsvevv3B2PrkJ5Ye5WEOJaCFgBa+yUfiT+Zb3xqPFe65J6bcncyZs4pNmx6hu3sR3d2L\nmDfvCjKZUom3M8CG8FZ833KSYxe+1kq9FsBf561bt08oa/Pmw1KcU3q1TMrd0rIHPiH88eHvlbwP\nRZpf4oDROfcI8AZ8MPfucPOHgfcC3wKOdM49kObg1tpZ1tql1trZBXftFf58JPz5yoL7DwaeBh5N\nczwRyRe1isrMmS8qGQBA8S/HTCbD1Vffh/8yXYQfR1j9YCBOJpPhjjvumbC98HzHA4qJ12Hu3MNi\ng6m2tjb+e9uFBLQR8DEOLPFx9JY5F7NjeJj+vvX03/PnsQApk8nQ37+B/v4NZDKZCQHYccfNYvv2\n84kLenLLeP/7j2TGjEvx134RM2ZcGrvazoIF+3HMMd0ce+ynWbBgv9hzKCYuUMoG5Zs3nw98nuz1\n9L8vnnBOhdcjSr1WgSlmYGATd901/s/IXXctSxWINrr+ImUpp1nSGLObMealxpj9jTF7lFNGWM7L\nwq7lzxRs/0I4rnEfY8xvc9PqhN3YtyutjkwljUyNU481gGfOPG4stU2tx2rmj0ksMq5wQl1HgtyU\nKEXTxfz1r8m7miHsslwflp+dTZsufU+p7suoMaP+3JN215a+TpXIv8YXjnXjQne4bbyO1R6bWKv3\nVTW6lDUOUeqtrom7a3ELJ7c8bYxZHo5N/LzxicDPDu//pzCo/LwxZr4x5sYwpY4Sd8uU0qgvkGof\nN+rLNJtypKOjJy8nYdxqJOXWNf/4wwGcFRizOHLiTX5AsSMvZ+OY73wneZA4a9ZYubkTIHwwuiO8\nDuPXJckEo1JBT/HrHR/MjD+utuPpxo8TlcD8yrxzqkXi7Vq8r6ZCOi6ZfuqWVsda2wpcAnwAmIVP\nazOhwdI5F7U9zhn4sYofAy7Gp8w53Tl3DYBz7lpr7Qz8AKQu4D5goXPuzpTHEWlq8Sliimu2tXML\n037AKuBcYB+2bz8A31Xt11jevn0Ptm/3qUjWrOlh6dJDWLbsw0XPId01ygDXA5dx//2waNHE9EAT\n07D8q7//iCPg5z9PdpiNG2Hx4rxNAwObGBoaTzUDZzNz5qmMjHwpYd3HlZMqpr39doaG/HWtd9qV\nwtdjV9dCvv71Vdx11xP45z7XD5g//wFuuqm35DkVe53HpQaC8t9XcaZ7Oi6ZppJGlmEL3y5jzP3G\nmI3GmOsjbteVE7XW6qYWRpnqirV0pEkoXatZpH1968MWtNzu0dxWpuiWseolb06ZSDlFV3Owc2ds\nHaLTrlxZsxVlospN3l2b3yU9Z46fTV5Oi1yx15OfjX96UDhrHdaU7F4fHh6OfZ1Wc8axuollKqtn\nWp3fG78sYOr1oht1U8AoU12a5duSPr7SLsDC/XLrkt8lHdVFub4qXaIjIyOlu3uffTZdkJjy+Lld\n79kcjlHXrRpBSiXjQvv6/PKFvb3rgt7edWG6mPJWbSl2zcfzfeaOYbxwLB1NrqiUTFErzGSfy2oF\njOpmlqmungHjU8aYpeUcpFE3BYwy1SVd6q7aefjSfLFG5e3LBim5QZUf5zcyFvRWI4gqrOdfNm9O\nHiC+4AVlHTd77Kg8fc2ukn8g4lp181szrwxmzjwuuOCCNanyNRarV7UCPeVGlKmunksDbsMv4yci\nTSJqmbC5cw+JWequ9ONLjXdLuyxg1Biy7N/LlmVYtWojV199O0NDlwItYd7B58JUMtFLEyaRHWf2\np9cfyYG/vc9/gs0v8aBrr4UlS1Idp1Amk2Hx4hVs334YPm1MG9u37xy7Rs025rQaxl8TI0APsBIY\nfz2Nj/nbBMykq2tDqvOeO/cw/vjH6NdptZYXHB0dTVwfkWkpaWRpjOk0xowYY84xxryknOi03je1\nMMp0UO7KG8UeX0otWmJy6+C7Hycu6ZdKiq7mo4/4TA1mz2ZnRC8J/Ezt9GljGqHcltHxLufxc585\nM3pmepI6VDIut9zjFM7gb7bnRqRSlbYwtgRBEBlIWmufBQL8iitZu+X8HQC7cn5vobxZ0jVjrT0I\neGjLli20t7c3ujoidVPLVqzCWamdneW1ABazcuXVrFjxGD4xAsAqentn0dOztOhjdgwNMfvlL098\njBYyjM9g3klfX/EW0jT6+zfQ3T0PuA7IzhK/iI6OF7F163kMDGyiu3tRTY5dDZlMhne840thUmqY\nM2cVP/jBuYlmMB966DkMDa2mGudWj1ZY/1zlPxe9vTfS2rp3TY8r0ihDQ0PMmzcP4BXOuYfTPj6u\nS/qGMuoTHX2KSF3VIpVIbtm1TSmSu1wh4e8bJ+62bRsceSQAhUtFRQr/Oe7v3wDdldeyuFvxwWK2\n/pewcOHGhgUfaYKv/BVMCFcwiQ76CstduvTNrFhRnTrV8vUbp7V176YJ3kWaTjnNkpPlpi5pkWSa\nKZ1IbJf3+9+fvLv5iisiy69lt7BP2L2kaP2rdexapU1KOtygWCqfdCvxNLbrt1nqMRU10+eJjJv0\nK73U8qaAUaaqan4gN9sXZ2F90oxHfDFPjM2qLXWMWn2h+bQwy4pez0qPneb5SjveNGnZUeUee+yZ\nwTHHfCI49tizJq6WU0Gdaqna76NavKZqlYqpVprt80TGKWBUwCjTTLU/kGv1BZ52ubaxbZ/7Sqog\ncXh4OJgx4xNj12PGjE+UNdkiSb3rWUaxstI8X+WmTUq3/GIQ/n7y2HOQzTtZrTo1u1oFSZW05DbK\nVHx+pwoFjAoYZZoplqy7muVVY9ZzsS+1qPse//73UwWJhUHN8PBwMH/+smD+/GWpg8XcstJ0q9aj\nhSfqWsUlsU7y+FoEMnBOkL+iT/3r1Ei1CpIqzbPaCAoYm5cCRgWMUqFm7t6JEvWB3N6+pKoJriu9\nDnFfGtn7ruWU5EHiZZfVpL6FZfmu5PjAp54BT6Ur+WTrW8uuUh/ArEkVJEy291wpChjHTcV/CKYK\nBYwKGKUCk/HDzU+sGB8jl819V8mXRrW/wIt+gaZoRVxzwep0ZZdxftFdq+tiyx5/zEjg80ReGRxz\nzCdqMsas2Lmm7e6vRKnyxnM3TlwKcboo9TlS7nMyGbukg2Dq/UMwVShgVMAoFZis3Se+W3JdGLCM\nNF29x7/oRlIFifWeyFGstTabfLq9fcmELu78JNXZoH1lkF33OO4LvdgXadz2tK2J4/vvCNrbl8RO\nQCkl6fFHRkaC3t61wfz5yyo63mRWrecwSbkKyKQc9VxLepcx5vmc266IbX81xvzOGPMNY8zh5VSo\nmjcFjFLKZA0Ym61lNPcLLLN9e6ogMe2XYKlZyIXinuOo6+icKznLOSp1jg/eM4ExiyOP5+u9JAz0\nd+StYFKt1qn81s/mWF95ugc3k/UzRqaeeq4l3QucBfwN8D3AAX8FDgbeg8+2+w3gRcCxwLuttW9x\nzv2sqokjRaqonLWUm0Htk2eTOOFzJpPhllfNZ/njP/EbSiXF/vSn4bLLxv7MlpokWXMmk2HRousZ\nGjof2Eh7++0MDl5S9rlHXceBgU0MDa2k2FrZbW1tsUmq779/vwnbRkdHOeqoz4croQCsZtu2JWPX\nN25t7qjrUvq52URu8vBt285m8eIejj66I/EKJplMhq1btwOLJpxLmtdG7qpAa9b0sHTpISxb9mGt\noiIy2SSNLI0xK40xTxhjXhtx34HGmB3GmIvCv/c1xjhjzH+UE8VW66YWRkliuraAlBoHV7IFM0Ur\n4oH8qmbpXEp1R/f2rsvpZq5O8uqJs4RXhuWvDPza0aVnNsO6sfOtRhf7yMhIcMEFa4KZM48L4Iyg\ncPKOb9lM1to4fowdAazIO8/Xv/7CcMxiecMHYF3DJuo0QrP1Bsj0Vc8u6R3GmAtj7u82xgzn/H2e\nMeaP5VSqWjcFjCLRSn2JVWPSSrXGGebKr9dIAOuC+fOXFR1XVzgDurd3bYpgKVlqnd7edWPj98aD\ntPy6xc1sTxtQRM+cXjth4smeey4dC5L99pHEXaL5x5g4XrbUxKC4uma77qdT2p2pFADL5FVpwLhb\nisbIFwLPxty/C99dnTUC7FlOq6eI1NbAwKacbtB9wm7QTRP2ezmPENBCQBvLu08qWW4LGY7svJQd\nw8N0dq4GdgI7w67+hRXXp6trYVju74EvAcezefNK5s27gkwmE1vm0NBKWlv3pq2tjUwmQ3//Bvr7\nN0x4XLabuq9vkL6+QbZsie7uz3YV9/ScSk/PUm66qZfOzuvCc26hs/NxrrnmPAYGNjE6+jRz5qwa\nux4ve9lFfPSjR4ydY5LjxbnjjvvYvv0Axtfg3odnn/0i8+dfzvz5PcDHGO/8T2tv4HjgxNRljD9f\nO8PbaqD46wCSvxYmk+xrZfnyE9UVL5NWmoDxJ8A51tpXFN5hrW3Hj2/clrP5vfhxjiIymaxaxfLu\nkwho4xEOjN/3E5+AICAzMkJ/3/qxgGf27NkMDp7C/Pk9zJ/fw+DgKVX5oswGc/PnX05ucJQmqMiO\nq+vunkd39yiHHnoOO3bsmHCcJF/wuYEn5Ad+g4OnsGjR9XR3L2LFihMIgufo7d1Ib+9G9tvvRVx2\n2RK6uxcxb94VAIkDisIgrLNzNXPnHha579FHdxQEsqWD94nHmMeMGd1jj58zZxUdHY8kKi/7fPX2\nbqS9/WxgCT6YLl0HEWkySZsijTGvNcb8yRjztDHmJmPMZcaYi40xXzXGPBne5oT73hXOoD6hnGbP\nat3UJS0SrbDbL01Xc/DrX6cuP106mNqMM8yWGZUWp709ulu7knMsVsdycitGHTt336hciC972Tlj\nXfBJyo4qM/v38PBw0fuSXrekj5mKXdIizaDSLumWIAgSB5dh6+LFwPsY737eCdwC9DjnHrDWvhS4\nCfiKc+7a6oa36VhrDwIe2rJlC+3t7Y2sikjzaWlJvu+uXan27+/fQHf3IrKzdGEnfX2DsbOgk868\nze6bO/u2s3N1ZFduVJm+bqP4btbk9Ut7jsXuByZs7+3dyC23PF7yfOJkMhlWrfoaP/7xL/nlL5/g\nscfeCrTS0fEIW7eeV/H1zF7L0dFRYBetrXsnnnGdVprXgogkMzQ0xLx58wBe4Zx7OHUB5USZxpgW\nY8xLjDGzjDG7l1NGPW5qYRTJ8b//m64lsQL1yD1X7kSC4eHhYObM6FyJaZQ6x7jZzJWsD12KL2u8\npRFWBr29a6t6LrmJyidr658mosh0U89JL2Occ4Fz7g/Oucecc8+XU4aI1MHatb5lsKUFXvrS+H0/\n+cn8kLECUePssmPW4iaclFI4ZnD58hPp6lrIwMCmROVl8ziOjFwCXBRZv2qcIxSfPBO1vbV171TH\njnPHHfeRO74TloXbylc4EcWXv2XSTkgZH8e6aGwcadrXosi0kzSyNMbMMMasMsY8Zox5Lmell9zb\n8+VErbW6qYVRpqUjjkjeivj/t3fncXKVdb7HPx2cBDK0ehm9CPZFhEz9HEXhJkZkRA3GJQpDIkgQ\nIbIEZIhsjTiECImdEOwImiFAnAECaAJKxng7GDAuCcgigzHRkcX5gWzSCYvbkE4CHRLq/vGcSldX\nV506VV1bd33fr1e9quusz3mq+tSvnvXRR6uWjEJTmpU7dV0l5tUtZViecq+x3ONUqt1eR8cNA0oL\nOzpuGNT5yxkep5Fp9hVpRrWc6eUK4CzgIeCnQG+++LMSQayIlKgC7REr3W4s3wwlfSVVaeAmursX\nMWcOrFpVvM1e/1KuMHvJ9OmzWbeu8KwsRVIIHM+ECV2DmimmlHaPccep1Mw97e1Tuf32haxf3w7A\nuHELaW8/f1Dnz50RCRYCpw+ZmZFEZPBKCRiPA5a7+2erlRipnWZtVD5srnvrVthzz+LbZRSpYs7t\n9LBiRemdLkozcOq65IFe+Rp5KshKBp933XV+VvB3fqL3Me782QFlb28vvb1v5Je/nE9LywgWLlxO\ne/vUIfW/1MifA5GGlbQoMpVK9aRSqdPLKcas10NV0vk167AVQ/66N2xIXtV8ySUlHbpWVXR978HA\natNiQ8tUoko6c5xSqpHr0TmikTpkJBnCZ9y4uXVPZ6kaKY9FaqGWUwP+OJVK3VzOSer1UMCYX7O2\n3xmS13355cmDxCefLPs01cqbQu0YOzquS7e1tZcc/BU6XrW++OvxI6ORftjkS8usWdcUDPgHey4F\ncCLVU8s2jOcCa83sMmAF8EfCdID9uPum3GUi1TRsqpkz2tpg48Zk2+7cCSPKGuygn2pU0eWr5u7q\nOoWlS9cyatQePPjghSxd2tdmLl8bxdxq6nzVppWqys0nSZqG+jnj/n/ypcX9RODoiqehtk0iRKRU\npQSMvyLMDT0reuSTBnYbbKKkuoZT+51Svmga9rp7e2H33ZNt+4lPwOrVFU9Ckk4XpQbmA4ONUzn0\n0Cvo7p4LKChoBMX+f8Ig3f1t3jwB+AOh40voWHPIIVfS2/tWFixYVtaPtnoE5iJSmlICxm8k2Ea9\npIeASvbIrLdSvmga6rofeQQOOijZtsuWwYknVjc9xJfUVaYE6M4oWOx7rxYuvI1Ro0YBMG3aRxou\noM/3I2PatFN2jQNZjRLtWv6wKf7/8xrZgWH4ey/gQuB7wCyOOOJVXnrpfzNnzgmAfgiIDFvl1GMP\nlYfaMA5/Q6pd4sKFydsjPvNMvVPbTzn5nNv+ra3t1AHH6FvW144xrtNLuXMtD0bunMq1aF9Yq/Z8\nxd7Xvnm3l0aPTQPes3zjPpb6P9hI7TZFhquqdXpJpVL7plKpPXJeF32Uk4hqPRQwDn8N/0VjljxI\n3Lmz3qktqNzAPC7YCp1eNiU6ZinvczU/E7X8gVKLoDFu+sLOzqXpjo7r0uPGzU3HBfWVyhN1ehGp\nrmp2eukGTgJuzXpdtMAStWGUGmqoamaAV1+FkSOTbXv44XDvvbteNnLnnXKrSXOrubPfq97ef2DO\nnGTXWErTg3xtJ6dOncOECWOZNu0jLF26dtc1NVIeZ6tVJ5B8/z9Av3OPHXsFHR2h6UDm/ys73ytV\nhV7NzksiMnhxAeNcwqwu2a+LURtGqap8QVXdv2geewzMkm27ZAmcdtqAxY3eS7RSgXn2e9XT08Oq\nVdVuq9cD3MDq1XNZvRrmzp3Jtm1fAVr79dqGZAFkrdoX1rITSO7/z4IFy/qde8OGLzN1auFzF/ts\nNPIPIREpQdKiyFQqdWK5xZj1eqhKenhpqOrnxYuTVzX//vdFD1fvtpj1qg5Met7yq6QHtq8LbfHS\nUXu89pI/T7XIq2LzQVczDeXMRV1IQ/3PijS5wVZJlzKA22Lg5GoFriLF9C912TMqdVlZuwS8971h\nDuaWFpgxI37bV1/t+7498MDapK9MmdLNmTOnMHPmFCZOvJqenp6anDtTunXRRSfFljxlSrE6O7vo\n7OyKLX3N3nbSpEdizp7dazv55ylpmgcn0zt5S/RYSGbY202bNvHOd57HzJm9zJw5sQrvV+Fzl6ru\n/7MiUjGlBIyvAFurlRCRhrNzZ1+A2NIC69cX3vaQQ/qXK76ulBGrQlXduHF9X9Ljxi1kxozJg0p+\nUkPlS72UQC2z7fLlHYwfv4hMvo4ePROYCGyhre3+GqS6PKNG7QGcDnRFj9MZNWoPenp6OPTQK+nu\nXgQcD9zEunWnVvT9KnRuEWlupXyrfRG41sx2AvcALwI7czfSTC9SLTVpP/bUU3DAAcm2vfba4iWN\nJUindwC3Zf0tg5Xbvm7atFksXbom+vsypkyp7biPue35gLzt+8Jn/eoBaVu8eGW/sSzDBFy3AaMq\nlsZ85/70pz/DJz95AQBLllzIvvvuW8KxGmtsTREpT0s6nayfipn1ALsT3ws67e4N00vazPYHnlqz\nZg1tbW31To5UQFUa0N98M5x6arJt//u/k3dwKcGCBcuYOXMKfYHAFjo7azPTRW6Hm/HjB3a4qXS+\nN0pHiFqmIzefx41bSDq9gw0bvgwMzPd8acv3OWlrO5dHH70qNu2lXmdPTw8LFy7ngQce4V3v2odv\nfetptm1bAMDo0TN5/PFZ/YLGuOM3ynst0uy6u7uZOHEiwNvd/emSD5C0sWMqlfpqgsecchpSVuuh\nTi9S0Ic/nLzTyvbtVU9OrTu95HaaiOtEUemOC83aESLfexw65SR/zwcOht6e3rhxY0n7JMnv/vuc\nMyDdkya1D+r4IlJ7VRu4ezg8FDDKLjt3Jg8Q//7va568an7p5gsOSzlXsWC21B67tQqO6zUzTCGV\nCBjLSWs5+d1/n/YB+2cHjPXu4S8iyVRz4O68zOwdwJHA/oQ2jI8Dt7v7syUXb4pU07PPwn77Jdv2\nG9+ACy6obnpiJBnnsJyqvXzjOx511JsrNsZf3/FPBe7kmmvO48EHL0vcxq1aShnXspwxMMt5L3Lb\n8/VVSW8Byh8MvfouBC4C+qqklyyZVcPzi0hDSBpZplKpEalU6rpUKrUzlUq9lvPoTaVSHeVErNV8\nqISxCd16a/KSxN/+tt6pTazcEsh8pT+TJg0sMYorEYo7d99cw/2rSSs1pmK5Sin1KrWEbDDpL6Up\nQKF9SjX4Kume9MEHX5T+2MfOSU+aNLAKXFXSIkNDLUsYv0IYa+HbwDeBJwjD8vw98CXgUjPrdvfr\nKx7VisQ58ki4885k277yCowaXI/SejTir+TMH4cd9i7+/OfkPVeLl37eSeitG9LW3T03Nm0NN51j\niQbzXuQrHYzbrxIzABWa/m/BgmXR64Gf4YH7fKXouJdD9f0UkYSSRpapVOrpVCq1PGZ9VyqVeqSc\nqLVaD5UwDlOvvZa8FHHffSt66mKlKdVqC1eopLDUkqJMeiuVzs2bN6fb2k4tuw1btfKrlFKvjRs3\npkeP/uKubUeP/mJsR5JCJZLVuJZqtA9UiaBIc6pZp5dUKrU1lUrNiFk/I5VKbSsnEdV6KGAcRl58\nMXmQOG/egN0r9WUe9wVe7Y4r2ceGuWnYlLh6sZodOjZu3Fj2FHvVyK/NmzenOzpuSH/sY2enP/rR\nL6Y7Om5I0KlnUzpMGRj+jgvK8l3vxo0bq3ItlQoYsz8D+ab+UycVkeGvlgHj2lQq9aOY9d9LpVL3\nlZOIaj0UMA5xP/5x8iBx/fqCh6lkYBL3BV7t3qKbN2+O2h/ekIbNDfVlX05QWq3Ss3Hj5vYLrMeO\nnR1bqlpKOvo+S5vScEO6re3U9MaNG6v23lfisztwKJ7yS4RFZOiqZRvGGcBqM+sidJd7FNgOjAHO\nASYDnzGzVPZO7v5YhWrPpRmcey5cfXWybbdtgz2KT1lWyfZ/9Zy5orW1lQkTxrJ6dfbAzY2h9j13\n81u8eCXr17fTlz/tbNhwGwsXLmfVqhfytgUs5T3t/1maTnf38Sxd2lW16ymn/WF8mqG7ez5tbbOj\nGWM0+4qIJFNKwPho9LwfcHSBbX6Y8zpN/Mww0uzSaRg5EnYkmArvkEPg17+ufppixDXwnzbtI1xz\nzbl0d38A+BTjx99U8Iu43I4ztQxYK9W5p9BxanktDzzwCOvW9U2pl/2joRKdNqp5LdnBeCU6wUAr\nZ5zxD4wapU4qIpJcKVMDnlLOCdz95nL2qwRNDdigtmyBt7wFtm4tvm0FxkdMMvXdYG3atIlDD71y\nV6lNW9tsHnww/5y75aYnE3j19vYCrzFq1B5V66VdqTwrdpxNmzYxffqVwMA5isP0dN/jgQd+x2GH\nvYv29qmJ8uiII/41KmUEWMjYsTuYPLmNOXNOYLBTL8ZdTzV7z2eOfffdG1i9Onsu6eLXUYvPv4g0\nvqpNDZhKpZ5MpVLHZ70+OZVKvb2ceu96PdSGsYE8/HDy9oi//nXFT1/Njh+l9hQup71brXu2VqpN\nXrmdhDZv3pweO3Z21LknrB83bm7izjQdHTekJ01qT3d0XFfW7DbFjl+pHuZJjtM/7eV1WKnFTDYi\n0tiq2YZxn+iRcRNwEvBUyVGpNKdly2DatGTbbt0Ko0dXLSnVbGO3ePHKqBq6egbbDrMeY0cWE3dN\nixevZMOG/YDjd61fv7490TW3trYye/b0AcvLnUkn3/LBfpZKqVrun09TgYVAKEFt3NlhRGS4iQsY\nHwHmmtn7gZ5o2XQzmxB3QHf/QoXSJkNNOg2nngrf/nbxbc85BxYtqn6aauZTwCLCANahSnrGjI68\nW9a640w57d4qlcZ6dhLKFRc0FcojoAJtBvvOkQk8e3tfHhAsT506mwkTxhYJ6FuB05k0KbOtqpZF\npEYKFT2mUqlDUqnUr1Kp1PY8UwEWfJRTzBmdb0QqlfpFKpW6K2vZ6AJTEW5IeExVSVfb1q3p9F57\nJatqXrGi3qmtikJDrRTbp5QqwsFUqZZbvVztqtdqVUmXk558edTRcV3J0yjGnbP/0Dbt0eel77iZ\n6uZ8g8FroG0RGaxqVkm/FTjS3V8AMLPXgGnufkuVYtd24P3A3VnLDgJagGOATVnLE/SWkKp5+ml4\n+9uTbfv44zBmTFWTU4pqVM329bJdCYxixoyrih631CrCWk+/Vsl8KnStcdfU2trK3XdfGHV6mR11\nejl/0NccV5KYsyXXX/87urvfNajzZQwc2mYubW3n0t2dKWVfCJwP7DmguYGm3hORhlAokkylUi+l\nUqnTsl4/lUqlzignKi32SAVbUqlUdyqVWpu1/IxUKrVlEMdVCWOlPPxwOn344cVLEd/61nR627Z6\npzav4VRSU0rpX6nXPZzyKVfctH75B7fenIbB50X+Eswb0p2dS6NSzE0D0iQiUkmDLWEcERNLtgAf\nNLPdo9dvowole2Y2ArgRWAI8FJ034z3Aw5U+pyR0xx2w997Q0gIHHQT33Zd/uzPO6Puu6+5ONJh2\nPfQv5cmU5Kysd7JKliklmzlzCjNnTmHixKvp6enZtW7BgmUsWLBs17JMCVVnZxednV1F2+A1QaUx\nFwAAHdhJREFUQj7lu45qys2jM87IdGJqJcxLcBuTJs0uu/3ijBmTGT9+EbAF2ML48Ytob5/KRRed\nxPLlHYwff1O/dTNmTK7UpYmIVERclfT3gVOAk81sZ7TsO2aWr0dDmhDopd19ZIlpOA/YF/gEsCI6\nVsbBwAgzW0uoru4hBJeXunuCkZ6lJDt2wFVXwYUXxm/3j/8IV14Jhx1Wm3RJP4V6F8+YMblgB42h\n1Eu2MoNT5xfXCSd3gOxVqzLbtTB+/AssX94R23M6TrHqd1U5i0ijiwsYzwI2EEr5RgKfB+4nflid\nZKOAR8xsDDAPmOLuW80sd5N3R8f8MjAHmADMAvYGTivlXFLAX/4CF18M110Xv91pp8GCBfCmN9Um\nXVXQSD12q6FSUyDWO58qOZVjrqTBWdx25Qa0cUH7UAroRaQ5FQwY3b0XuCbz2sw+D1xXqU4vZtZC\nqIa+zd1/VmD90cDz7v54tPheM3sVmG9m89xdY0KW65VX4IAD4LnnCm+zYAGcf36Yum8YGC4lOYUC\nukpVGw+XfCokaXBWaLtqBrQiIo0q8VzS7j4CwMzeCLS4+18Hee6zgRRwrJll0tFCqILezd13Avfm\n2W81cDmh9FEBY7kef3xgsLjXXnDjjTB5+LafGg4lOYUCukqWDNYzn+pdwikiIgMVnUs6Kuk7Bfgc\n8AEg0wnmFeAXwDLg2+5eanX0XcCHYzb5HKHF+R3uvmtInWgg8V8Ah7v7L4qcY380l3R+6TTccgvc\neit0dsJ73lPvFEkFNOKMLuVo5OvQ3MwiMhQNdi7p2IDRzPYFfgC8D9gO/Ap4DthB6KgyFvhb4EHg\nM+6+MemJzSxFpk4nSgthqoyRwJnAn4CngTnuPi9rv28ApwL/x91je20rYBRpfI0cHBYyFNMsIs1t\nsAFjwSrpaDidHwLvAGYC1+YGaGa2B3A68DXgdjP7gLu/kuTE7v5YnnP2AKPcfUP0+mZglpltB9YD\nkwi9qi8oFiyKVJIChNIkza9q9oiupuHQtEFEpBRxbRhPAw4BPuXuP863gbu/DFxtZg8BPwOmA9cO\nIj1p+ve0Pgt4hhCUfhV4AjjT3ZcM4hwiJRkKQU09AtpC5ywlv6rZgURBvohI5cQFjJ8HugoFi9nc\n/W4z+w/gJAYRMLr7J3Ne9wId0UOkLhq9V2zSAK2SAVTcORcuXF5ifvUAXdHfEyuS5qEQ5IuIDCVx\nM72kgLtKONbPCdXXIlJDSWZmiZsdppLn7Onp4frr7098nGnTPsLo0fOBKcAURo+ez7RpHxl0mhth\nthoRkeEkLmB8HfBqiccrqae0yFCQb1q3oTZ1W60CqMWLV9LdPZ/Qfy3k1xve8CV6e1/OG+wtXbqW\nbds6d6Vr27ZOli5dS09PD1OnzmHdur0JtxUFfSIi9RQXMD4OHFHCsT4EDOjIIjLUlToXc63VI6Dt\nO+dzwBLa2s7dVTKYPf8ynM1LL32VOXNOSFxC2Nvby8SJV7N69VzgeOBqQrV1OekbukG+iEgjKTis\njpnNBC4DjnD3fANoZ2/7IWAtcI67f6viqSyThtWRZlGsrV85YwcWO+amTZs49NAr6e6eu+uYXV2n\nMGXKzdF5biMEfJnRs7bQ2dm/LWO+dB111JuZM+eEfvvBbYwf/0JJwbo6vYiI9KnasDqEOqVTgB+a\n2QXAUnfvV0VtZiMJYyJeAfwGuLHUBIjI4BUb5qXU6f5yA7lrrpnNGWf8A+3tn92139Kla6Ngsa9z\ny9KlXbvOc/fdj7B6dfF056YrX7XzpEmPsHx5R0lBn4a+ERGpnGIDd78NuJ0wDd9m4NfA84S2jXsT\nBvR+A/BLYIq7P1/tBJdCJYwi5VmwYBkzZ04hrpQv3zbZJYillmpmSgR7e3tZufIPbNjw5UT7iYhI\ncdUsYcTdnzGz9xFKEacBhxFmYoEQNN4PfIcypgYUkaFmVL8hcorN+dza2kpX1ylMnz4bgCVLLkw8\ngPe4cQvp6Pguo0btUbQ0VEREqi82YIRdYyH+G/BvZrYbsBdhGr8/KkgUGZ5yg8HQQuWcftsUq+bu\n6emJ2jOGNo5TpiQfwHv9+naOO65xxroUEWl2RQPGbO6+E/hjldIiIg0iEwwuXHgb119/fzRUTkve\nUsRCQV2jD3guIiLJxQ2rIyJNrLW1ldmzp/Poo1fR2bmmqkMKaRgcEZHGFtvpZahTpxeR+im30wto\nGBwRkUqraqcXEZFylTqUj4bBERFpXAoYRaRqFASKiAwPasMoIiIiIrEUMIqIiIhILAWMIiIiIhJL\nAaOIiIiIxFKnF5FhREPTiIhINShgFBkmcsc9XLEiftxDERGRpFQlLU2pp6eHBQuWsWDBMnp6emq+\nfzX0n4pvz2gqvpX1TpaIiAwDKmGUpjPYkjiV5ImISLNRCaM0ncGWxDVqSZ7mYxYRkWpRCaPIEJbb\nyaWUqfhERESSakmn0/VOQ9WY2f7AU2vWrKGtra3eyZEGkVulPH784KqkS92/UholHSIi0vi6u7uZ\nOHEiwNvd/elS91cJozSd1tbWQZXEDXb/SulfNU5UNd6luZtFRKTiFDBKU2ptbR1UYDXY/UVERIYS\ndXoRGaLUyUVERGpFJYwiQ1SjVI2LiMjwp4BRZAhT1biIiNSCqqRFREREJJYCRhERERGJpYBRRERE\nRGIpYBQRERGRWAoYRURERCSWAkYRERERiaWAUURERERiKWAUERERkVgauFtK0tPTw+LFK4EwNZ1m\nFhERERn+FDBKYj09PUyceDXr1p0LwIoVi1izpvGno1OQKyIiMjiqkpbEFi9eGQWLewJ7sm7dubsC\nsUaVCXJnzpzCzJlTmDjxanp6euqdLBERkSFFAaMMa0MxyBUREWk0ChglsRkzJjN+/CJgC7CF8eMX\nMWPG5HonS0RERKpMAaMk1traypo159DZ2UVnZ9eQaL+oIFdERGTw1OlFStLa2spFF51U72Qklgly\nFy/uAmDGjMYPckVERBqNAkYZ9oZakCsiItJoVCUtIiIiIrFUwih1o/ERRUREhgYFjFIXQ3UQcBER\nkWakKmmpC42PKCIiMnQoYBQRERGRWAoYpS40PqKIiMjQoTaMUhcaH1FERGToUMAoZalED2eNjygi\nIjI0NEzAaGYjgPuAXnc/Imv5ycDFwH6AA19x9zvrk0oB9XAWERFpNo3UhrEdeD+QziwwsxOAG4Hv\nA1OA3wFdZnZoXVIogHo4i4iINJuGKGE0sxTQAWzKWTUPuMndL4le/8TM9gMuBY6qYRJFREREmlbd\nSxijqugbgSXAQ0BLtPwA4AAgt+iqC/hotJ/UgXo4i4iINJdGKGE8D9gX+ASwgr4q6XdEz4/lbP8E\nMBLYH3iyBumTHOrhLCIi0lzqGjCa2RhCtfMUd99qZtmr3xA99+Tslnn9+ionT2Koh7OIiEjzqFu1\nrpm1EKqhb3P3n+XZpCV6TudZB/BaVRImIiIiIv3Us4TxbCAFHGtmmXS0ACPMbDfgpWhZK/Bc1n6Z\nus+XEBEREZGqq2fAeAywN/BinnWvAl+I/h5D/3aMY4CXgWermjoRERERAeobMJ5JGMgvowVYROjQ\nciYhSJxFCCzvhF3V2FOAu9xdVdIiIiIiNVC3gNHdc3s/Y2Y9wCh33xC9vgy4wcz+B/gZcDIwDvhw\nLdMqIiIi0swabSzDNFmdXNz9RuBc4NPADwhtHie7+4P1SZ6IiIhI82mEcRh3cfdP5ll2DXBNHZIj\nIiIiIjReCaOIiIiINBgFjCIiIiISSwGjiIiIiMRSwCgiIiIisRQwioiIiEgsBYwiIiIiEksBo4iI\niIjEUsAoIiIiIrEUMIqIiIhILAWMIiIiIhJLAaOIiIiIxFLAKCIiIiKxFDCKiIiISCwFjCIiIiIS\nSwGjiIiIiMRSwCgiIiIisRQwioiIiEgsBYwiIiIiEksBo4iIiIjEUsAoIiIiIrEUMIqIiIhILAWM\nIiIiIhJLAaOIiIiIxFLAKCIiIiKxFDCKiIiISCwFjCIiIiISSwGjiIiIiMRSwCgiIiIisRQwioiI\niEgsBYwiIiIiEksBo4iIiIjEUsAoIiIiIrEUMIqIiIhILAWMIiIiIhJLAaOIiIiIxFLAKCIiIiKx\nFDCKiIiISCwFjCIiIiISSwGjiIiIiMRSwCgiIiIisRQwioiIiEgsBYwiIiIiEksBo4iIiIjEUsAo\nIiIiIrEUMIqIiIhILAWMIiIiIhJLAaOIiIiIxFLAKCIiIiKxFDCKiIiISCwFjCIiIiISSwGjiIiI\niMRSwCgiIiIisRQwioiIiEgsBYwiIiIiEut19U6AmY0AZgKnA3sDvwVmu/tPo/WjgR6gJWfX37j7\n2FqmVURERKQZ1T1gBOYD5wEXAw8BJwF3mNmH3P0/gYMIweIxwKas/bbWOqEiIiIizaiuAWNUengO\n8HV3vypavNbMPgycCfwncDCwzd276pRMERERkaZW7xLGV4DDgOdzlu8ARkZ/vwd4uJaJEhEREZE+\ndQ0Y3f01QjU0ZtYC7AtcABxAKGGEUMI4wszWAu8ntGe8EbjU3XfUPNEiIiIiTaaRekn/M/As0A5c\nD9wTLX83MAa4BfgEcA1wPnBdHdIoIiIi0nTqXSWdbS3wIeBQoAPY08xOBiYDz7n749F295rZq8B8\nM5vn7k/FHHM3gOefz63xFhEREWkeWbHQbuXs3zABo7s74MB9UfX014FZ7n5Pns1XA5cTSh/jAsZ9\nAE488cQKp1ZERERkSNoHeKLUnerdS/pNwJHAKnf/c9aq30TPbWb2SeAOd88eUmf36PlPRU6xDvgg\n8BywswJJFhERERmKdiMEi+vK2bneJYx/C9wEfAlYmLX840Av8AfgF8AcYF7W+uOA/wH+K+7g7t4L\n3FfB9IqIiIgMVSWXLGa0pNPpSiakZGb2bcKg3JcQhs/5BKHjy1x3n2dmNwInAF8F1gOTCJ1eLnD3\nRXVJtIiIiEgTqXcJI8AXgCcJA3i3Ab8HznL3G6L1ZwHPEKYO/CohOj7T3ZfUPqkiIiIizafuJYwi\nIiIi0tgaaRxGEREREWlAChhFREREJJYCRhERERGJ1QidXirKzEYQhtLpdfcjomWjgH8BphHmq34a\n+DfgWndvqkac+fKnlPXNoFAemNmHCAPG/1/CsE7fBy529211SWgdxeTRdMIwWfsROrDNd/f/qE8q\na8vMRhPmum/JWfUbdx8bbXMycDEhfxz4irvfWdOE1lGxPGr2e3WSz1DWtk15r074f9a09+qE+VPW\nfXrYBYyEIXneD9ydteybwOcJ4zn+GjiCMO5jK/C1Gqev3vLlTynrm8GAPDCz9wM/Bf4fMBtIAZ3A\nXoQvt2aTL49OJswDv4CQV0cDt5nZK+7+w3okssYOItykjwGyJxrYCmBmJwA3Eu459wCnAF1m9kF3\nf7C2Sa2b2DxC9+pi+ZOtWe/Vxf7Pmv1eXSx/yr5PD6uA0cxShHmoN2Utez1wJvBld88MDn6Xmf0d\ncCHNcRMC8udPKeubQUweLADucffPRq/XmtlI4GwzG+nu22uZznqKyaPTgZ+4+8XR67VmNp4wNFYz\nBIwHA9vcvavA+nnATe5+SfT6J2a2H3ApcFQtEtgACuaR7tVA8c8Q0PT36mJ51Oz36mL5U/Z9eti0\nYYyK528ElgAP0Vcc+3rgW8CqnF0c+F9m1lqzRNZRTP4kWt8MCuVBNIXl4YTP0S7uvsjdU01wA9ql\nyOfk9cCWnF3+Qvhl3wzeQ5h8YAAzOwA4AFiZs6oL+GiUr82gYB6hezXE5w+gezXx/2e6Vxf/DJV9\nnx5OJYznEdq8fAJYAaQB3L2bMCh4rsnAJnfvqVkK6ytv/pSwvhkUyoN3E27KL5nZCsJsQ9uB7xBK\nQ5rhJpQR9zlZBlxmZscAawj5NIlQOtQMDgZGmNlaQlVhD+GL/VLgHdE2j+Xs8wQwEtifMIHBcFcw\nj3SvBuLzZ0e0TbPfq+P+z3SvLv4ZKvs+PSx+1ZrZGEJ1zxfcPV9bj9zt/5nQNmZBtdPWCIrlT6n5\nNxwVyYM3R8/fAbqBI6NtTweuqlki66zY58TdrwCWExqY/xX4LrDE3Zslj94NjAFuIXyZX0OYxvQ6\n4A3RNrlBT+b162uRwAYQl0cDNNu9miL5o3s1EJ9Hb4q2aeZ7dbH/sSsp8z495EsYzayFUDR/m7v/\nLMH2pxIycLm7X13t9NVbsfwpNf+GowR5MDJ6/rm7nxf9fbeZ7QZ8zczmuvtztUhrvST5nETzwh8J\nnE2oKvsIMMvMut39spoltg6i/DkaeN7dH48W32tmrwLzgcyyQqVBr1U5iXVXLI/MbJ67P5W1fTPe\nq+Py5zJ0ry72f5b5/DTlvTrJ/xhhiuWy7tNDPmAkXHQKONbMMtfTQiiS3c3dd2Y2NLNLgLmEyPrE\nmqe0PmLzB5gRtz47/4axYnmUKQXKHf7kJ4SSj4OAYXsTihTLo0MIPRBPdPfvRuvvNTOAS81ssbv/\npdaJrpVoyJd786xaTRje45nodSv9PyuZdnkvVS91jSFBHr2b6Au/Ge/VCfLnRJr8Xl3C/1lT3qsT\n5M+nGcR9ejgEjMcAewMv5ln3qplNcPd7zOxaQi+g64CzmmFMr0hs/gA/j1ufyb8qpq8RFMujs6O/\nd89Zlyl5bIbPUrE8+lz09y9y1t0P/A2hiuSXVUtdnZnZW4B/Au5w9+yeq5nPzB+i5wPp345xDPAy\n8GzVE1lnCfLoT9F2TXmvTpA/s4HdaOJ7dYI8ejp6HpWza1PcqxPkz+jouaz79HAIGM8E9sx63QIs\nInxAzgQei4phzwIuzxrSolkUy58d9P8cDMi/2iSzrop+hoCLgM8CN2RtdxTwCsM4EMpSLI8y6w6n\n71c+wKGEm3T2suFoN+DfCeMHzstafhxh4ODfEL7MjgV+BLuqj6YAd7n7sK+Spnge/bbJ79XF8ufD\nhC/1jGa8VxfLow2EH18nEKrvM5rlXl0sfzI/KMq6T7ek08Mv4Daz1cAodz/CzN5JqKdfR+hdljsE\nwa+yep81hez8KWd9M8jNg2jQ5VsIjamXAu8jtAW5ogm/2IC8ebSacOO5FHiEcFOaRRh7cEbdEloj\nZnYj4Yvqq8B6Qs/D84EL3H2RmZ1G+MHxTeBnwMmEKqIPN8vA3XF5RMiTpr5XF/sM5dm+6e7VCf7P\nmvpenSB/yr5PD4cSxnzS9BU9H0248YwHHsiz3T7kL+IfzrLzp5z1zaBfHrj7d82sF7iEME7c88Bs\nd2+W3pv55H5OJhNuPGcDbYRhYi4Chn2HhchZhF/opxNu1k8AZ7r7EgB3v9HCtF3thLbDvwMmN0uw\nGCmYR2Y2E92rYz9DeTTjvbrY/1mz36uLfYbKvk8PyxJGEREREamcYTEOo4iIiIhUjwJGEREREYml\ngFFEREREYilgFBEREZFYChhFREREJJYCRhERERGJpYBRRERERGIN14G7RaSGzOxm4PM5i18DtgC/\nJcyy8MNap6sUZvZ2d38qZv0EYC0wzd1vqcD5Msc7yd1vLWO/ROkodl052/4L8EF3/6ek6SmXmb2N\nMBPFwe6+sdrnE5HBUQmjiFTS+cBJ0eNkYDawF9BlZp+pZ8LimNl1hDlYk6jUbAePEvLp/jL3L5qO\nUq7LzNoIs2N8pcz0lMTdnwFuBf61FucTkcFRCaOIVFKXu/8he4GZ3UqYfmoe8P26pKq4jwOP1fKE\n7v4iIWCqplKu63Lg5+7+2yqmJ9fXgSfN7HB3v6+G5xWREqmEUUSqyt3/BNwNmJm9sc7JidNS7wRU\nSdHrMrO9ganAoKvaS+Hu3cC9wHm1PK+IlE4ljCJSCzuj59cBmNko4MvAZ4EDCO0dHwa+5u4ro232\nJ5RMngt8DhgL/DTTvs7MTiMEGingJWAlMMvd/5yz/4nAIYQ2lm8Afglc4O4bou1ei9K2X/T3BHe/\nJ+Za3mBmi4HjgD2AB4Dz3P3RzAZmthvwJWA68DbgReB7wBx3fznaZgI5bRHNbHdCSewJwBsJgfYC\n4OfAKe7+naTpKPG6phMCyzuyF5pZCyH/zwDeDjxHCCrnu/v2rGv4OOE9+nS06w+As4GJwHxgDODA\n+XnScDtwhZnt4+7PFUifiNSZShhFpKrMbDTwfqA7Km0EuBm4FFgNfBHoBPYDfmBm7845xNeA3xOC\nw+9Fx5wH3EBoB3g+cBMhyLrXzPbMs//HCVWu8wmB54/M7G+i9dOAPxEC1pOA/y5ySVcABxPa+y0E\nPgD82MxGZm1zU3SuuwkBV1eU/h9FwWS27LaI3wMuAFYB/wK0RvuWk45SrutI4D5378lZfm107McI\nAfCPCG0cr8vZ7ibgLYQfAT8CTiUEgjcB/wFcDOwDrDCz1px97yD8kPh4TPpEpM5UwigilbSXmW2L\n/h4JHEgIDPcG2gHM7C2E6s957v7VzI5m9gvgZ4RSqYeyjvmku38+a7sDgVnR/nOylv8A+E9CwDU3\na/8dwKHuvj3a7mXgyug8q939FjObDzyfsLfyo4SexK9Fx9sOdADvA+4zsyMIAdp0d78pK313E9pw\nngh8J/eg0X5HA5e4++XRsn8H7gEOKyEdhwL3Jr2uqFTzvcDinOXvBM4Ernb387KWvwK0m9msrM2f\ncfdPReuXAEcQ8vej7r42Wr4VuJ4QsP88a98ngG3A4cC3C6VTROpLAaOIVNKGPMt6gA53vwrA3Z+P\nSpkyVaaY2QhgVPQyt4QwtwpzCqH6dJWZvSlr+VOEkrCj6B8w3pEJFiP/FT3/XfHLyWt5JkiL/Cp6\nfkv0fAzh2n6ck757ga1R+gYEjMBkQmnjoswCd99pZv9K/oCxUDr2TnohkbcCf0PIv2xHEvL5mpzl\nlxNKDl8kNAeA0Bwgk+a0mT0BjM4Ei5Gno+d9sg8Wbf80ocpbRBqUAkYRqaQTgReiv3cCfwF+5+47\ncrbbAXzezD4OvIPQxm33aF1uU5kXc14fGD0/WCANL+S8/mPO697oObdqOKnc478cPWeqgg8kXEN3\ngf3/T4HlY4AX3H1LzvJCvZyLpSOpTOC8OWf5/tHz77MXuvtfgb8CmFmhtOxg4PuWacearylUD/Cm\nPMtFpEEoYBSRSro/d1idXGa2B2HswYOANYT2er8hBCa/yrPLzpzXmUDvU8B2Bno15/VrebYZjNz0\n5NoN+B+g0LiTue0EM15H/ut5pcx0JJXJn9xArpSAOvcHAZQ2XuUIKnc9IlIFChhFpNamEnot95up\nxMzem3D/Z6LnZ939kewVZvYpBpaU1dozwEeBX+aWFprZsQwsjct4EphoZqPdfVvW8jHVSeYumfTs\nlbM8E/gfSFYpo5mNIfTk/kYF0/B31HgcTBEpjXpJi0itZapAd/XajYZvOTt6WeyH7O3Rc3anC8xs\nPKG08gtlpGknlbsf3k5o+5ebvs8QegxPLrBfF6FU74ysfVoIHU/KleS6XiCUbOZWlWeG2PnnnOXT\ngeOBPw8iXbtEvcb3oS9AFZEGpBJGEam1nxKqMJdG4whCqL5tI1S/vj5uZ3d/2MyuBb5oZm8mdLh4\nE3AOod3c/DLS9CIw1szOBO5092fLOEYmfavMbBUwM+rRfRehQ8fZhFK0awvs9xMzWw1808zeQRgO\nZzKh9zCUNyVh0euKxlO8nzD0Ufby/zKzG4ALomkD7yYM43M6cK27PxXNB11I0oHQDyKMI7km4fYi\nUgcqYRSRSkiTMKBx94cI1dLbCVPDXUzouTweWE8YkqXYMc4hBIhvIQyRcyZhSJ7DozmKk6Q321xC\n28KFwIdK2K/Q8mMJ82gfQpgr+bOEAa8nuPtLMfsdB3wr2v/rhOFmzorWbY/Zr9DypNe1GjjEzP42\nZ/mZwEzCUDgLgQmE9yt7ZpZ8aSn0eci37HBCSehPY9InInXWkk6X86NVREQqycxeD2x391dylh9L\nqMqe6O53Venc+xCG1TnD3ZdW4xwx574P2Ojux9fyvCJSGpUwiog0hmOArWZ2SM7y4whV+L+p1omj\nKfluJUyfWDNmdgBhjMlKdqARkSpQG0YRkcawijAczwoz+xaht/dHCe07O6PxD6tpHvCQmY1z9/VV\nPlfGRcAqd/9ljc4nImVSCaOISAOI5tn+R0I7zi8R2gymgBnuPitu3wqd/ylC0NhR7XMBmNn+hNLT\nL9bifCIyOGrDKCIiIiKxVMIoIiIiIrEUMIqIiIhILAWMIiIiIhJLAaOIiIiIxFLAKCIiIiKxFDCK\niIiISKz/DyZeoKV2TUmiAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x11755a610>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "$V_A = h^2S$"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "V_A = slope*S\n",
      "V_A"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "0.54647232814613966"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    }
   ],
   "metadata": {}
  }
 ]
}