Breve_exploracion.ipynb

{
 "cells": [
  {
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   "metadata": {
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     "slide_type": "slide"
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   "source": [
    "# Breve exploración de metapoblaciones en paisajes fragmentados\n",
    "\n",
    "Por Irene Ramos Pérez"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## *¿Cómo sobreviven las especies en paisajes fragmentados por actividades agrícolas?*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "slideshow": {
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   "outputs": [],
   "source": [
    "# Módulos necesarios\n",
    "import numpy\n",
    "from ipywidgets import interactive\n",
    "from scipy.integrate import odeint\n",
    "from matplotlib import pyplot\n",
    "from IPython.display import display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false,
    "slideshow": {
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   },
   "outputs": [],
   "source": [
    "numpy.set_printoptions(precision=3)\n",
    "%matplotlib inline\n",
    "pyplot.style.use('seaborn-deep')\n",
    "pyplot.rcParams['font.family'] = 'serif'\n",
    "pyplot.rcParams['font.size'] = 18\n",
    "pyplot.rcParams['axes.labelsize'] = 24\n",
    "pyplot.rcParams['figure.figsize'] = (12, 7)\n",
    "pyplot.rcParams['figure.dpi'] = 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 1. Metapoblaciones\n",
    "![Image](./figuras/diagrama_levins_s.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Metapoblación\n",
    "\n",
    "Hace casi 50 años, Richard Levins imaginó cómo una especie podría sobrevivir en un paisaje fragmentado. En su modelo, el paisaje está compuesto por parches de hábitat y áreas inhabitables, y algunos de los parches están ocupados por una población local que, debido a variaciones ambientales, corre un riesgo de extinción. Las poblaciones locales son independientes, pero los individuos pueden migrar colonizando nuevos parches de hábitat. Este conjunto de poblaciones locales que interactúan a través de la migración de individuos se llama *metapoblación*: una población de poblaciones. El balance entre extinción y colonización determina la supervivencia de las especies en el paisaje."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Modelo clásico - (Levins 1969)\n",
    "Aunque sólo una fracción $h$ de parches son habitables, los individuos se pueden mover en todo el paisaje y en un tiempo $t$, una proporción $p(t)$ de parches están ocupados. Como los parches de hábitat son similares, tienen la misma probabilidad de ser colonizados, $c$, y las poblaciones locales tienen la misma probabilidad de extinción $e$; tanto la probabilidad de colonización como de extinción varían entre especies. La tasa a la que aparecen nuevas poblaciones, es decir, la tasa a la que se ocupan los parches, depende de la probabilidad de colonización $c$, de la proporción de parches habitados $p$ (de donde provienen los individuos) y de la proporción de parches no habitados $h-p$ (hacia donde van los individuos): $$ Colonización = c p (h-p). $$\n",
    "\n",
    "Por otro lado, la tasa a la que desaparecen las poblaciones, es decir, la tasa a la que se desocupan los parches, depende de la probabilidad de extinción local $e$ y de la proporción de parches habitados $p$: $$ Extinción = e p. $$\n",
    "\n",
    "Entonces la proporción de parches habitados cambia en el tiempo de acuerdo a $$\\frac{dp}{dt} = cp(h-p) -ep.$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Supervivencia de la metapoblación\n",
    "\n",
    "La metapoblación alcanza el equilibrio $p^*$ cuando las tasas de colonización y extinción son iguales, es decir, cuando $$ cp(h-p)=ep, $$ de donde, $$p^*=h-\\frac{e}{c}.$$\n",
    "\n",
    "Este valor $p^*$ es la proporción de parches ocupados que conforman la metapoblación en el largo plazo. \n",
    "\n",
    "Cuando todo el paisaje es habitable ($h = 1$), la metapoblación sobrevive ($p^* > 0$) si la probabilidad de colonización es mayor a la probabilidad de extinción, es decir, si $c>e$. Al disminuir la proporción de parches habitables, también disminuye la tasa de colonización. La razón entre las probabilidades de colonización y extinción contrarrestra la pérdida de hábitat en tanto $h>\\frac{e}{c}$; la metapoblación se extingue si la pérdida de hábitat cruza ese umbral, incluso si aún hay parches habitables. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "##### Exploración"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def levins(parches_ocupados, t, colonización, hábitat, extinción): \n",
    "    \"\"\"\n",
    "    Modelo de metapoblaciones de Levins (1969)\n",
    "    Cambio en el tiempo de los parches_ocupados, entre todos los parches\n",
    "    \"\"\"\n",
    "    d_parches_ocupados = colonización * parches_ocupados * (hábitat-parches_ocupados) \\\n",
    "                        - extinción * parches_ocupados\n",
    "    return d_parches_ocupados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
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   },
   "outputs": [],
   "source": [
    "def graficar_levins(colonización=0.8, extinción=0.2, hábitat=1):\n",
    "    tiempo = numpy.linspace(0, 40, 41)\n",
    "    población_inicial=1.0\n",
    "    \n",
    "    parches_ocupados = odeint(levins, población_inicial, tiempo, \n",
    "           args=(colonización, hábitat, extinción))\n",
    "    \n",
    "    pyplot.figure()\n",
    "    pyplot.plot(tiempo, parches_ocupados[:], \n",
    "                label = \"e/c= {:.3f}\".format(extinción/colonización), lw=4)\n",
    "    pyplot.ylim(-0.05, 1.1)\n",
    "    pyplot.xlabel('tiempo')\n",
    "    pyplot.ylabel('parches ocupados')\n",
    "    pyplot.title('Metapoblación con $e/c= {:.2f}$\\n'.format(extinción/colonización))\n",
    "    #pyplot.tight_layout()\n",
    "    \n",
    "x = interactive(graficar_levins, \n",
    "                colonización = (0, 1, 0.1),\n",
    "                extinción = (0, 1, 0.1),\n",
    "                hábitat = (0, 1, 0.1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": false,
    "slideshow": {
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    }
   },
   "outputs": [
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u6b+SJEmSJEmj2LhLNGTmxzKzLTPb+3jVXTEiM3+RmXMy88DMbPjUn5mrM/PD\nmbkgM7fKzNmZ+ZzM/MFQYr/0T/exbkPHUJqQJEmSJKmlxl2iYSxbu76Dy68f0NQOkiRJkiSNKiYa\nRpkLHD4hSZIkSRrDTDS00Lztes9Jed0dD/Pgo0+2IBpJkiRJkobOREMLHb7fDr32ZcKFi5e1IBpJ\nkiRJkobOREMLHbrvHNraotf+C666h66urHOEJEmSJEmjm4mGFpo5fTKH7DOn1/7ljzzJTXc/0oKI\nJEmSJEkaGhMNLfacw3apu/98J4WUJEmSJI1BJhpa7LD95jFj2qRe+39/7f2sXd/RgogkSZIkSRo8\nEw0tNnFCG8cesnOv/es2dPL7a+9vQUSSJEmSJA2eiYZR4IRD59fdf8HVDp+QJEmSJI0tJhpGgT12\n3oan7Tiz1/4b7nyE5Y880YKIJEmSJEkaHBMNo8QJDSaFvOCqZSMciSRJkiRJg2eiYZQ4duHOtLdF\nr/0XXn0PXV3ZgogkSZIkSRo4Ew2jxNbTJ3PYfnN77X9w5Vquv/PhFkQkSZIkSdLAmWgYRZ7TYPjE\n+Vc5KaQkSZIkaWww0TCKHLLvXLaZPrnX/j9c9wBPrtvYgogkSZIkSRoYEw2jyIT2No49ZOde+zds\n7OTSP93fgogkSZIkSRoYEw2jTOPVJxw+IUmSJEka/Uw0jDK77TCTPXfeutf+m5c+yn0PrWlBRJIk\nSZIkNc9EwyjUaFJIezVIkiRJkkY7Ew2j0LMW7syE9t4fzYVXL6OzK1sQkSRJkiRJzTHRMArNmDaJ\nI/af12v/I6vWce3tD7UgIkmSJEmSmmOiYZRqOHziSodPSJIkSZJGLxMNo9TBT5/NtjMn99p/+Q0P\nsGbtxhZEJEmSJElS/0w0jFLt7W0cd8j8Xvs3dnRx6TX3tiAiSZIkSZL6Z6JhFDuh4eoTy0Y4EkmS\nJEmSmmOiYRSbP3cGe+8yq9f+W+9ZybIVq1sQkSRJkiRJfTPRMMqdcHijXg1OCilJkiRJGn1MNIxy\nxzxjJyZN6P0xXXj1Mjo7u1oQkSRJkiRJjZloGOWmT53IkQfs0Gv/ytXruea2h1oQkSRJkiRJjZlo\nGAMaTQp5/pUOn5AkSZIkjS4mGsaAg/aazfZbT+m1/4obl/P4ExtaEJEkSZIkSfWZaBgD2tuC4w6d\n32t/R2cXv7vm3hZEJEmSJElSfSYaxojnNBg+4eoTkiRJkqTRxETDGLHj7Onsu9u2vfbfce8qlj7w\neAsikiQKfcczAAAgAElEQVRJkiSpNxMNY8hzDrdXgyRJkiRpdDPRMIYcfdCOTJrY3mv/xYvvpaOz\nqwURSZIkSZK0ORMNY8i0KRP5iwN36LX/sTXrWXzzihZEJEmSJEnS5kw0jDEnNJgU8nyHT0iSJEmS\nRgETDWPMAXtsz5xZU3vtv+qmFaxas74FEUmSJEmStImJhjGmrS04/tDevRo6u5KLl9zbgogkSZIk\nSdrERMMYdMJh8+vud/UJSZIkSVKrmWgYg+ZttxX777Fdr/133/84d977WAsikiRJkiSpYKJhjHpO\ng0khL7h62QhHIkmSJEnSJiYaxqijDtyRKZPae+2/ePG9bOzoakFEkiRJkiSZaBizpk6ewNEH7dRr\n/+onN3DVTctbEJEkSZIkSSYaxrRGk0Ke76SQkiRJkqQWMdEwhi3YfTvmbTet1/7FtzzIysfXtSAi\nSZIkSdKWzkTDGBYRnFBnUsiuruSixfe2ICJJkiRJ0pbORMMYd/yh84novf+Cq+8hM0c+IEmSJEnS\nFs1Ewxg3Z9Y0Dtpzdq/99yxfze3LHmtBRJIkSZKkLZmJhnGg0aSQFzgppCRJkiRphJloGAeOPGAH\npk2Z0Gv/JUvu5ZFVa1sQkSRJkiRpS2WiYRyYMmkCxzxjp177n1jXwce/fgVr13e0ICpJkiRJ0pbI\nRMM48ZzDe68+AXDXfav4/HcW09XlxJCSJEmSpOFnomGc2GfXbTliwby6ZVfcuJyzf3nTCEckSZIk\nSdoSmWgYR961aCHz506vW/bji+/gN3/88whHJEmSJEna0phoGEemT53IR04/kplbTapb/p8/upZr\nb39ohKOSJEmSJG1JTDSMM/O224oPveFwJrT3/mg7u5JPnX0V9z64ugWRSZIkSZK2BCYaxqH9nrYd\n73zFM+qWPbF2Ix//+hU8/sSGEY5KkiRJkrQlMNEwTh17yHxe8ZdPr1v2wMNP8Kmzr2RjR9cIRyVJ\nkiRJGu9MNIxjrzpxH44+aMe6ZTfc+Qhf+uGfyHTZS0mSJElSdUw0jGNtbcG7Fi1k711m1S2/4Kpl\n/PDC20c4KkmSJEnSeGaiYZybPLGdD73xcGbPmlq3/Fu/upnfX3f/CEclSZIkSRqvTDRsAWbNmMJH\nTj+SqZMn1C3/l+8u4fZlK0c4KkmSJEnSeGSiYQux2w4zed9ph9IWvcs2bOzkH79+BQ+tXDvygUmS\nJEmSxpURTzRExJyImDbS5xUcuu9cTn/R/nXLVq5ezye+cQVr13eMcFSSJEmSpPGkkkRDRMyKiF1q\nXr3ajYj3RsQK4AFgdURcHRHPreL8at5JR+/OXx21W92yu+5fxT9/ezGdXa5EIUmSJEkanKp6NFwK\n3F3z2rm2MCI+CXwGmA1E+VoI/DIiFlUUg5oQEbzlxQewcO85dcuvvGk53/zFjSMclSRJkiRpvBhy\noiEiFgL7USQPVgO/ANbUlO8PvK/8sedX5W3Af0bE7KHGoea1t7fxvtMOZf7cGXXLf3LJnZx3+dIR\njUmSJEmSND5U0aPhBeX7H4HdM/NFmfloTfm7as5zN/AsYBpwJHADMAN4fQVxaAC2mjqRj5x+BFtP\nn1S3/D9/fB1/uu3BEY5KkiRJkjTWVZFoOBroBE7vkWAgIiYCp9bsenlmXpaZ6zLzSuA0ip4QztXQ\nAvO224oPvf4IJk7o/WvQ1ZV8+uyrWLZidQsikyRJkiSNVVUkGhYA12TmzXXKng3MpBgycWFmLqkt\nzMxrgesohl6oBfZ92ra84xUH1y17Yl0HH//6H1m1Zv0IRyVJkiRJGquqSDRsTzEkop6TarbPblBn\nKTCrgjg0SMcu3JlFJ+5dt2z5I0/yyW9eycaOzhGOSpIkSZI0FlWRaOgEpjQoe3H5vh74SYM69s0f\nBRaduDfPOninumU33f0oXzz3T2S67KUkSZIkqW9VJBoeAvbquTMijgPmUwyb+G1mrulZpzQPeKyC\nOHqef1JEvD8ilkTE4xGxMiL+EBFvjYgYYtsvjIifRMS9EbE+ItZExA0R8W8R8bSqrmEkRQTvfMXB\n7LNr/c4lFy2+l3MvuG2Eo5IkSZIkjTVVJBr+BOwdESd07ygf5D9aU+f79Q6MiKnA4cAdFcRR2+52\nwNXAJylWw3ge8BLgfuA/gd9GRP3lFvpv++vAzyjmn/g8cCzFhJeLgTOAGyLihUO8hJaYNLGdD73h\nCOZsO61u+bd/fQuXXXvfCEclSZIkSRpLqkg0nEuxcsT/RsSnIuIM4CKKZSwBVtJ42MRHKJa3XNKg\nfLB+SDFJ5b9m5tsy8w+ZeXFmngr8FDiBIuEwIBHxeuANQBfwvMz8QmZenpnnZebrgK8AU4H/iYht\nq7qYkbTNjMl85I1HMHXyhLrlX/juEm67Z+UIRyVJkiRJGiuqSDR8jyJRMB14H/CvwDFlWQKfzsy1\n3ZUjYoeIeEVE/LCsn8BvKoiju/2XUvQ2WAd8rE6VD5bvr4uI+sstNPaa8v3qzLyiTvm/le8zgRcM\nsO1RY9cdZvL+1x5KW50BJhs6uvjHb1zBgyufHPnAJEmSJEmj3pATDZnZBbwQuIqiZ0P3C+CrmfnP\nPQ45GTgHOKWs9yjwf0ONo8ab2LSc5uN14r0FuLk89xsH2PZOZduNVtlYWrM9b4BtjyqH7DOXt7z4\ngLplj61ezwe/dBmXX3+/E0RKkiRJkjZTv3/8AGXm8og4kmK+goMpehNcnpnX1Kl+NZv3NLghMzdW\nEUdETASOL3+8qo+qVwH7UvQ6OGMAp/gzsDeNkwi1+yudd6IVXnD07tz70Bp+cVnvvMqDK9fyyW9e\nxTP2ms2bX7w/u8yb2YIIJUmSJEmjTSWJBoAsvtq+qHz1VW8xxcSJw2FfYCJFr4OlfdTrLts1ImZk\nZrNLbH4LOBE4IiJ2y8ye53hV+X478Msm2xzV3nTy/jzw8BMsvuXBuuV/uv0hzvj8xbzgL57Gq07c\nm+nTBjXHpiRJkiRpnKhijobRZJea7Yf6qFdbtnOzjWfmd4F/okhm/DwijouIqRExNyLOBD5EscrF\nX2XmhgHEPWq1t7fxvtMOZdd5MxrW6epKfn7pXbz10xdw3uVL6exyOIUkSZIkbanGW6Kh9ml4XR/1\nassG1Oc/Mz8MHAY8CFwAPAE8QLGU5heBF2XmXQNpc7SbNmUiH3/rUey7W98LaTz+xAa+9MNrefe/\nXsKNdz0yQtFJkiRJkkaTyhMNETErIt4dEb+MiKURsaZ8LY2IX5Rls6o+70iIiIkR8UngCmBX4M3A\nUcDzKFaceBdwd0S8rXVRDo9tZ07h028/mjMXHcysGZP7rHvXfav4wJcu43PfvpqHH1vbZ11JkiRJ\n0vhS2RwNABHxfuDvgWndu2qKdwHmA88H/iEiPpGZn63y/EDtXAtT+qhXW9ZrZYo+/BA4iWKixwMz\ns7ZnxG8j4iLg18AXI6IjM78ygLZHvba24PhDd+HI/Xfg3PNv46e/u5OOzsbDJH53zX1cceNyXnb8\nXrzk2D2ZNLF9BKOVJEmSJLVCJT0aonAuxfCBaWy+xOVmVcvXdOBTEXFuRNSrN1j31GzP7qNebdm9\nzTQcEc+kSDIk8IkeSQYAMvM3wKUU1/j3zbQ7Fk2bMpHXv3ABX/q74zl037l91l2/oZNvn3cLf/PZ\nC10OU5IkSZK2AFX1aPg0cGrNzw9QrCxxN7Cm3Dcd2B1YCOxA8TD+UuBTwAcqiuNmYCPFde3WR73u\nsj8PYMWJo2q2r++j3rXAMcBOEbF9Zj7cqOKZZ57J1ltvvdm+RYsWsWjRoiZDaq0dZ0/no286kqtv\nXsHXfno99z30RMO6Dz76JJ/85lUctNf2vPnFB7Cry2FKkiRJ0rA455xzOOecczbbt2rVqhE7fwz1\nG+aI2Au4keLh/hLgQ5n5h36OOZpi9YZjKBIDCzLzjiEFsqntX1HMmfCLzDy5QZ0bgX2AL2XmO5ps\n973AZyl6NByamdc0qPfvwN+W9bbLzMfq1FkILF68eDELFy5s5vSj3saOLn5+6V187/9uZe36jj7r\ntrWFy2FKkiRJ0ghasmQJhxxyCMAhmblkOM9VxdCJ0ymSDN8FTugvyQCQmZcBxwHfK489vYI4un2t\nfD8hInqtyRgRewP7UiQC/nsA7d5Qs31gH/UOKt/vrZdkGK8mTmjjlOP25MsfOIHnHLZLn3W7l8N8\ny6cu4NeXuxymJEmSJI0nVSQankOxxOPfZGZXsweVdd8KrAVOrCCO7nZ/TNGzYgrw0TpVPkWRZPhm\nz14JEXFSRDwYEddHRM+n5fOBWymGfHwoIqb1KCcink/RSyMplrrc4syaOYV3vvJgPv/OZ7H3Ln0v\nLrL6yQ38xw+v5d1fcDlMSZIkSRovqkg07ApcNoC5Dp5SHnMpxYoUVTqVYh6FMyPiPyLiqIg4LiJ+\nCLwIuACotwTlm4Htgf2AU3rE2gG8BPgzsAdwfUS8KSKeGREnRsRngJ9QJjGAz1d8TWPK03eZxWfP\nOKa55TDvL5fD/J+reWily2FKkiRJ0lhWxWSQM4BHh3D8o2UblcnMRyLiMOBdwCLgNUAnxWSRf9PH\nspNfAY4ElgM/rtPuLRGxgCIhcTLFPBPbUMwz8QBwLkVPiQuqvJ6xasDLYf7pPq64aTnHLtyZI/ff\ngQP33N4lMSVJkiRpjKliMsj7gLsy85hBHn8ZsHtm7jikQMaQ8TgZZDPuf2gNX/vZDVx104qm6k+e\n1M7BT5/N4fvN49D95jJrxpRhjlCSJEmSxqeRnAyyih4NtwLHRMTumXnXQA4sV6w4EvhdBXFolNtx\n9nQ+cnpzy2ECrN/QyR9vWM4fb1hORDEc44gF8zh8wTx2mTuDiBihyCVJkiRJzaoi0XAecCxwbkQ8\nLzMfbuagiJgNfJ9icsVfVRCHxohD953LQXvN5heX3cU5v+1/OUyATLj1zyu59c8r+davbmbuttOK\npMN+81iwx3ZMaK9iuhFJkiRJ0lBVMXRiG+AuYGvgEYpJEH+UmXc0qL8nxWSN76aYePFRYI/MXDWk\nQMaQLXXoRD0rH1/Ht351M+dfdc+g29hqygQW7jOXwxfM49B95jB92qQKI5QkSZKksW8kh04MOdEA\nEBGnAWdTrLjQ7XFgKbCm/Hk6sBsws/uwsv5pmfndIQcxhpho6O2Oex/j139YypU3Leex1esH3U5b\nW7Dgadtx+IJ5HL5gLjtuP73CKCVJkiRpbBprczSQmf8TEXOAz7BpycytgQN7VK0dVN8JvHdLSzKo\nvj133oYzXv4MurqS25et5MqbVnDljctZ+sDjA2qnqyu5/s6Huf7Oh/n6z25g/tzpHL5fMa/D3rtu\nS3ub8zpIkiRJ0nCqpEfDU41FHAt8Djikn6pXAn+XmZdWdvIxxB4NzVvx6JNceeNyrrxpOTfc+XCf\ny2P2Z+ZWk9hz/jbMnzOD+XOnM3/uDObPncEMh1pIkiRJGufGXI+Gbpl5MXBYRBwGnAAsALYrix8B\nbgDOz8zFVZ5X49fcbadx0jG7c9Ixu/Pkuo0sufVBrrhxOVfftII1azcOqK3Hn9jAklseZMktD262\nf5vpk5k/dwY7z53O/Dkz2KXc3nbmFFe2kCRJkqQBqjTR0C0zrwKuGo62teWaNmUiRx+0E0cftBOd\nnV3cvPRRrrhxOVfeuJz7H+57qcy+PLZmPY+tWc/1d26+YMq0KRPK3g9FD4id585g/pwZzNl2mkMw\nJEmSJKmBYUk0SMOtvb2N/ffYnv332J7TT96fex9czZU3ruDKm5Zz892P0FXBiKAn13Vw6z0rufWe\nlZvtnzShjZ3mFL0fdp67qQfE7G2mMnXyBHtBSJIkSdqitTzREBGnA3+RmW9sdSwau3aeM4Od58zg\nlOP25PEnNnD1zcVkkktufZC16zsqPdeGji7uvv9x7r6/90SVkya0sfWMyWw9fTLblK+tp09im9p9\n5fbWW02ivb2tzhkkSZIkaexqeaIBOBp4LWCiQZWYudUkjj90PscfOp+NHZ1cf+cjLL55BXfdv4pl\nK1azas2GYTv3ho4uHlq5lodWrm2q/oxpk9hmxiS2mT6lSEhMn8zWM7oTFJsSE1tNncjUye1MnNA+\nbLFLkiRJUhVGQ6JBGjYTJ7SzcO85LNx7zlP7Hn9iA8tWrC5eD67m3hVruGfFah5+rLnkQJVWP7mB\n1U9uYNmKNU3Vn9AeTJk0gSmTJzB1cjtTJk1g6uQJ5b52pk7e9PPUye1Mqd2eNIGpUyYwtTx+yqSi\n/sQJbQ73kCRJklSZphINEXHhMMaw7zC2LfUyc6tJLNh9Oxbsvt1m+9eu7+DeB1ezbMWapxIR9z64\nmgcefqKSOR+q0NGZrFm7ccArbvQlAia0tzFxQvGqv93OhPbY7L1x3U3bE9rbaG8L2tqi5r2tx8+9\n3xvV6VneFhARRFD+HERsvt8kiiRJkjSymu3RcCwwXI9aMYxtS02bOnkCe82fxV7zZ222f2NHJ/c/\n9ATLeiQh7ntoDRs7uloUbXUyYWNH17i4lnq6kw2bkg+btjfb19ZjX3lwBJu2u9uj2FksPtKd0KjZ\nZlOCo7Z+vbbKo8qCp942S5A8Va/evvKcPa/5qW02+2HzepsdM4h6DdSrEj0bbVBvIAZy/FhOOI3h\n0IdVvd8pSZLU2H1Lbxmxcw1k6EQz/0fPJusNtK7UMhMntLPrDjPZdYeZm+3v7EoefPRJlq1YzQOP\nPMGqNet5bPV6Vq3ZwGNr1vHYmg08tno9GzZ2tihyQZFIyUyKNIo5TUmSJG2ZVq14aMTONZBEw3nA\nZ/oofyNwGnAL8FPgBuARoHvg+1RgO2B/4CRgP+B64D1Adf3ApRHS3hbssP1W7LD9Vn3WW7u+o0hC\nPJWIKN4fW1MmJZ7aXs/qJzeQPgtLkiRJGsMGkmhYnpmX1CuIiI8BpwCvyszvNdHWByPilcBXgbdk\n5ssHEIc0pnRP0Dhvu74TEgCdnV08/sSGzZMSazawdn0H69Z3sHZD8b5uQydr1236ee2GzmL/+g42\njNMhEJIkSZLGhiGvOhERRwIfAk7NzJ80e1xmfi8i1gI/joiTM/NnQ41FGuva29uYNXMKs2ZOGXQb\nnZ1dRSJifUeRoNjQwbr1nZuSEus7WbehKFu7roMNHZ10dCYbOzrZ2NFFR2cxX0NHRxcbu7fL90bl\nXaNltkxJkiRJLddsomEHNg2B6OmtwB0DSTJ0y8yfRsTtFEMuTDRIFWhvb2OrqW1sNXXiiJ2zsyvp\n6CyTDzUJiY7OIgnR2ZV0dtVu51PbXU9td222v7Mz6cqyTmcXnVlbt3hlV9JVzsGQlHMxdCWZ0JW5\naX6GrLNvs3qbl3d1JUk+NYylu7zYZrOyrmLHUzHQo7xX/R5JmaeOK48t3mqO31Txqe2nhteUbW+2\nr0fbPZruUa+mvGZ/M3Xq1+i/IBvUHuiQoQFVH+bxSMPZ+pgdSjVmA5ckafyKJyaN2LmaSjRk5oo+\nio8BFg8hhmuBw4dwvKQWK5acbGfyxPZWhyJJkiSpjiVLZvPzL4/MudoqaGMHYChfnU4A5lQQhyRJ\nkiRJarEqEg3rgSNiEIuUR0QbcGTZhiRJkiRJGuOqSDTcDswDPjCIYz9A0SPitgrikCRJkiRJLVZF\nouHHQACfiIizIqLfYRARMScivgR8gmIerR9UEIckSZIkSWqxIS9vCXwReBuwM/A3wJsj4nJgCfBn\nYE1ZbzqwG3Aw8Myacy8FvlRBHJIkSZIkqcWGnGjIzCcj4sXA+cAsiokhjylfjXTP5/Aw8KLMXDfU\nOCRJkiRJUutVMXSCzLyGopfC5eWuYFMyoVbt/kuAIzLzhipikCRJkiRJrVdJogEgM2/LzL8ATgS+\nQzFsInq87ga+BZyQmcdl5t1VnV+SJEmSJLVeFXM0bCYzz6cYRkFETKIYTgGwMjM3VH0+SZIkSZI0\nelSeaKhVJhZWDOc5JEmSJEnS6FHZ0InBioinR8SzWh2HJEmSJEkaupYnGoAPAhe1OghJkiRJkjR0\noyHRIEmSJEmSxolK52iIiDbg2RRLXc4DtqL+Mpe1jq4yBkmSJEmS1DqVJRoi4rnAWcDuAz0UyKri\nkCRJkiRJrVNJoiEiXg58h2IoRn89GLqZXJAkSZIkaZwZcqIhImYDXwPagRuAc4AHgNOBo4A39jhk\nOnAw8ApgGkWC4vyhxiFJkiRJklqvih4Nb6VIHvwCeElmdgJExLOBozLz7HoHRcTHgF8CzwXOqCAO\nSZIkSZLUYlWsOvEcoAN4V3eSoRmZuQw4BdgGeFMFcUiSJEmSpBarItGwD3BdZt410AMz8w7g98AL\nKohDkiRJkiS1WBWJhlnA3XX2dwFERHs/x98H7FdBHJIkSZIkqcWqSDSsp/5cD6vL9x37OX42sHUF\ncUiSJEmSpBarItFwP/D0OvuXl+/PbXRguWLF0cC6CuKQJEmSJEktVkWi4Vpgn4g4psf+xUAAH4+I\np/U8KCKmAd8GpgK3VxCHJEmSJElqsSqWt7wQeBnww4h4A/DrzEzgYuARYC5wXUR8D1gCbAT2Al4F\n7AQkxTKXkiRJkiRpjKuiR8PPgE6KuRZ+Dvw/gMzcCHyKolfDNOCNwFnAl4H3UiQZAB4u90uSJEmS\npDFuyD0aMvOBiPgURS8FgJtrir8AHAIsqj2EIvkAsAp4aWY+PNQ4JEmSJElS61UxdILM/EiD/Qm8\nOiLOA94EHAhMAe4Ffg18NjPvrSIGSZIkSZLUepUkGvqTmf8D/M9InEuSJEmSJLVOFXM0SJIkSZIk\nASYaJEmSJElShYZl6EREHAscDewNbFvufhS4BbgsMy8ZjvNKkiRJkqTWqjTREBGvBz4M7NZPvbuB\nf8jMb1d5fkmSJEmS1FqVDJ2IiEkR8SPg6xRJhu7lK6PHq3vf7sDZEfH9iBiRCSklSZIkSdLwq+oh\n/1vAS3rsWw38GVhT/jwd2BWYWf4cwKlAB/DqiuKQJEmSJEktNOREQ0T8FfDy8scHgH8B/jcz72pQ\nf3fgFOBMYAfglRHxrcz8zVBjkSRJkiRJrVXF0Ik3le+XAQsy8/ONkgwAmXlXZv4zsAD4fbn7LRXE\nIUmSJEmSWqyKRMPhwAbgFZn5WLMHlXVfAWwEjqggDkmSJEmS1GJVJBq2By7NzAcGemBm3g9cCmxX\nQRySJEmSJKnFqkg0PAasGMLxDwKPVhCHJEmSJElqsSoSDXcBOw/h+J2AWyqIQ5IkSZIktVgViYaf\nA8+MiPkDPTAidgGOAs5pUP7+iLhwiPFJkiRJkqQRUkWi4SyK4Q/fi4iZzR5U1j0HuBr47wbV9gGe\nPeQIJUmSJEnSiBhyoiEzVwMnAbsBt0TEeyLi6Y3qR8ReEfEe4GZgLXByZnYONQ5JkiRJktR6E4ba\nQETcVW5OAWYBnwU+GxHrgZXA+rJ8clk+uftQoAO4MiIaNT97qPFJkiRJkqSRM+REA0VPhiy3u9+D\nIvEwr0fdqKmX9D+JZNS0KUmSJEmSRrkqEg2wKYEw1P2SJEmSJGkMqyrR8EPg7ypqq9Y/A6cMQ7uS\nJEmSJGkYVJVoWJOZf66oradExJqq25QkSZIkScOniuUth1PgMAtJkiRJksaMIfdoyMxhS1Zk5uuB\n1w9X+5IkSZIkqVqjvUeDJEmSJEkaQ1qeaIiI90fEha2OQ5IkSZIkDV3LEw3w/9m78zDLqvrs+99b\nRkFoAcdggBAVEEWlxeAEKgoYHHFsNaKAIcLLg0TjkDjhRNQoGDUqGkVEOnkelcTgrAgOhAg0QdFG\nRAEHQBCwGRRo4ff+sXfBoaiqrqqzqk9V8f1c17nOqb2Gvcrtaqru2nsttgd2H/UgJEmSJEnS8OZD\n0CBJkiRJkhaJoReDTHJzi4FIkiRJkqSFr8UdDWnwai7J+v36DyuSXJPk6iSnJTkoydDnTPKwJP+S\n5CdJru3PcX6SE5P8bZKNWnwfkiRJkiQtJKN8dKLmquMkWwBnAu8ETgf2Bp4FXAJ8GPhakvWH6P9t\nwBnAPYDXALsB+wKnAs8A3gPcb4hvQZIkSZKkBWnoRyd6x1bV/lNVSLIecHdgO7pf/P8a+Bzwyqq6\nsdE4xnwW2BE4uqpeNXD8lCQn0oUBHwYOmGnHSd4C/ANwWFV9YFzxN5L8ke57kyRJkiTpTmet3dFQ\nVaur6oqq+m5VvQF4ILADcELL8yR5Nt0uFjcAR0xQ5fX9+35JHj7Dvh8C/D3wvQlChjH/CLwCuGwm\nfUuSJEmStBi0CBo+BXx3po2q6nfA84C9k7ygwTjGHEj3WMbJVXXNBOc9D1hJtzbElHdhTOA1wDp0\n3/OEquriqjpmonNLkiRJkrTYDR00VNXLquoTs2x7OfBtunBgaP3jGU/svzxjiqpn0AUN+8yg7/Xp\n1nmAbt0HSZIkSZI0zigXgxxzFfDgRn3tAKzXf75oinpjZVsn2WSafe8EjO0kcXGS5yX5apLLk1yX\n5IIkH0+y44xHLUmSJEnSIjEfgoZtgSWN+tpq4PMVU9QbLJvu7hAPGvj8ceAY4Bt0d0XsSbew5UuA\nFUleOs0+JUmSJElaVFrtOjErSfYEHgn8qlGXg3cn3DBFvcGyTafZ9+b9e4BnA7tV1WkD5acl+Rnw\nEeCjSc6tqjOn2bckSZIkSYvC0EFDkq3WXOtW6wObAX9OdxfAC/vj3x52HGvBxv17AV8fFzJ0BVXH\nJHk93Z0V/8BtazpIkiRJknSn0OKOhovofvmejQCrgX9qMA6Aawc+bzhFvcGy6e4O8YeBz1MFI6fS\nPUKxR5JU1Wz/t5EkSZIkacFp9ehEZtluFXBgVZ3TaBy/GPh8zynqDZZN97GNqwY+/2aKer/u3zem\ne9ziyskqHn744SxZcvvlKZYtW8ayZcumOSRJkiRJkm5v+fLlLF++/HbHVq1atdbO3ypouI4pfqEe\nsJruDoIL6O4K+LequmrqJjOysj/HusA2U9QbK7u4qq6dot6gcwc+rzNFvWmHLkcddRQ777zzdKtL\nkuXNs1oAACAASURBVCRJkrRGE/0Be8WKFSxdunStnL9V0PDZqtq/UV+zVlWrk3wT2Bt4xBRVd6F7\n3OOkGXR/DvA7uh0yplqXYsv+/Zqqmk74IkmSJEnSojEftrds7eP9+x5JNhlfmGQ7YAe6oOGT0+20\nqlYDy+nuWNhjiqq7931/cbp9S5IkSZK0WLQIGt4PfK1BP01U1efpFmTcEHjzBFWOpAsCjq2qswcL\nkjwtyeVJfjjJbhpH0N3V8BdJnjq+MMnf0N3t8HvgrcN9J5IkSZIkLTxDPzpRVYe3GEhjzwG+CRye\nZCPgeGAD4BDgGX3ZwRO0ezlwD2ALYF/g6MHCqrq8DxhOApYneRddyLIu3VaWh9EFES+oqvPn4PuS\nJEmSJGleW4yPTtCvjbAL8DpgV+ArwOeBPwFeUVV7VtVNEzQ9Bvgt8KO+/kR9n0b36MVHgRcBJ/f9\n7wm8D9ixqubNHR6SJEmSJK1NTRaDTPIoul/sx1xfVf86Sd330f3Cf1RV/U+L80+kX1PhPf1rum1O\nAu41jXq/AV7dvyRJkiRJUq/VrhPHAA8a+Po3wIRBA7AJ8DzguUk+BBxWVdVoHJIkSZIkaYSGDhqS\n7ALs2H+5GvhPpt428r+Ah9JtP3kI3S4Ohw47DkmSJEmSNHot1mjYp3//OfCwqnpeVR03WeWq+kJV\nPRJ4OrAKODjJIxuMQ5IkSZIkjViLoOFRdNtFvqCqVk63Ub8ewsvp7mh4eYNxSJIkSZKkEWsRNOwA\n/LCqzpxpw6r6HHAhsFuDcUiSJEmSpBFrETRsAZw3RPuVwP0ajEOSJEmSJI1Yi6BhWNePegCSJEmS\nJKmNFkHD5cBDhmj/4L4PSZIkSZK0wLUIGs4Ctk/y5Jk2TLIn3RoPZzUYhyRJkiRJGrEWQcN/0O0c\n8Zkk017UMcnuwGfodqw4scE4JEmSJEnSiLUIGpYDPwXuAXwryZeS7J/koUmWJFmnfy1J8rAkByT5\nMnAy3UKSP+n7kCRJkiRJC9y6w3ZQVTcnWQacCmwM7NW/1iTAtcCyqrpl2HFIkiRJkqTRa7LrRFWt\nAP4SuIwuQKB/n+p1CfCUqjqnxRgkSZIkSdLoNdvesqq+A+wEvI/uToXJrALeDTy0qk5rdX5JkiRJ\nkjR6Qz86Maiqfgu8OslrgV2AHenWYQC4EjgXOLOqbm55XkmSJEmSND80DRrG9EHC6f1LkiRJkiTd\nSTR7dEKSJEmSJGlO7mgASHIXYCu6bS8BfgtcXFU1V+eUJEmSJEmj1TxoSLIXcAiwG7DJuOJrk3wb\n+EBVfb31uSVJkiRJ0mg1e3QiyRZJvgR8CdgH2JQ7bmm5aV/2lSRfTLLFZP1JkiRJkqSFp0nQkGRz\n4LvAXtwWKkxavX/tDXwnyWYtxiBJkiRJkkav1aMTnwa26z+vAr4MnAlcCFzXH78bsC2wFHgKsKRv\n82ngqY3GIUmSJEmSRmjooCHJE+iCg1uAI4Ejq+r3a2izMfD6/vWUJI+vqlOGHYskSZIkSRqtFo9O\nLAMKeE1VvXFNIQNAVV1fVW8AXkP3GMULG4xDkiRJkiSNWIugYTfgMuCoWbQ9qm+7W4NxSJIkSZKk\nEWsRNNwX+H5V1UwbVtUtwOl9H5IkSZIkaYFrETSsB9w4RPub+j4kSZIkSdIC1yJouBx48BDtH9z3\nIUmSJEmSFrgWQcOZwA5JnjzThkn2Ah4EnNVgHJIkSZIkacRaBA3/SbdzxAlJHj/dRv22mJ+h27Hi\nxAbjkCRJkiRJI9YiaDgB+CmwBfDNJF9JcmCShyVZkmSd/rWkP3Zgkq8A3wA2B87v+5AkSZIkSQvc\nusN2UFU3J1kGnApsDDy5f61JgGuBZf3uE5IkSZIkaYFrcUcDVbUC2Ae4jC5AoH+f6nUJ8JSq+t8W\nY5AkSZIkSaPXJGgAqKpvAw8F3kd3p8JkVgHvBh5aVae1Or8kSZIkSRq9oR+dGFRVVwCvTvJaYBdg\nR7q1GwCuBM4Fzqyqm1ueV5IkSZIkzQ9Ng4YxfZBwev+SJEmSJEl3Es0enZAkSZIkSTJokCRJkiRJ\nzRg0SJIkSZKkZgwaJEmSJElSMwYNkiRJkiSpGYMGSZIkSZLUjEGDJEmSJElqxqBBkiRJkiQ1Y9Ag\nSZIkSZKaMWiQJEmSJEnNGDRIkiRJkqRmDBokSZIkSVIz666tEyW5C/AUYEfgOuA7VfXDtXV+SZIk\nSZI095oEDUmeB2w/cOjoqrpmoHxL4IvAQ8a1+3fgpVV1U4txSJIkSZKk0Ro6aEiyIfBRYFMgQAHH\nAtf05QE+D+w0QfPnAzcDfzXsOCRJkiRJ0ui1WKNhb2AJXchwAvAc4LKB8ucDu9AFEADnA/8X+FHf\n5oVJ/qLBOCRJkiRJ0oi1CBr2pAsR/rGqXlxVJ457FOKggc+fAh5UVS+oqocAH6QLG17SYBySJEmS\nJGnEWgQNjwCuBt4+viDJvYDd6IKIa4DDquqWgSpvBH4PPLrBOCRJkiRJ0oi1CBr+HDinqn4/Qdk+\ndHcsAJwwuEAkQFWtAs4Etm4wDkmSJEmSNGItgoZNuP2aDIOeNvD5M5PUuRS4W4NxSJIkSZKkEWsR\nNFwP3Gv8wSR3A/aie2zikqo6bZL2AW5oMA5JkiRJkjRiLYKGi4Gd+20uB+0H3LX//Lkp2j8AuLzB\nOCRJkiRJ0oi1CBq+C9wdeMfYgSQ7AG8aqPNvEzVM8kDgYcDKBuOQJEmSJEkj1iJo+Bjd4xGvTHJJ\nkrOAs4F79MdXVNXp4xv1O1Ic33/5vQbjkCRJkiRJIzZ00FBV5wDvoVtr4T50dyis13+9Gjh0sH6S\nJyT5MvBzYGl/+KRhxyFJkiRJkkavxR0NVNXrgf8D/ILbtrP8AbDnBHczPJBukciN+rpnV9W5LcYh\nSZIkSZJGa91WHVXVB4EPJtkcuLGqrp+k6meArwx8fU2rMUiSJEmSpNFqFjSMqaqr1lB+HXBd6/NK\nkiRJkqTRa/LohCRJkiRJEsxh0JBkgyQPSLLLXJ1DkiRJkiTNL00fnUiyKXAAsAx4aN9/DZ4nyVeA\nHwNHVdUvW55fkiRJkiSNVrM7GpI8CTgP+Ce6bSvHtrjMuKpbAocB5yU5oNX5JUmSJEnS6DUJGpI8\nATgJuDcThwuDPkIXSNwVOCbJ/i3GIEmSJEmSRm/ooCHJhnRbVq4P3AL8F/BK4OnA18bXr6oPVdWO\nwOF0j1UcneS+w45DkiRJkiSNXos1GvYH7gP8Gnh6VZ09VpDk2ZM1qqr3J1kfeFffxzsajEWSJEmS\nJI1Qi0cn/pLuzoTnDoYM03Q0cCWwV4NxSJIkSZKkEWsRNDwU+EFVnT7ThlW1Gjgd2L7BOCRJkiRJ\n0oi1CBq2oFvccbZWAUsajEOSJEmSJI1Yi6DhJmCDIdr/CXBdg3FIkiRJkqQRaxE0XAI8KsmM+0qy\nOfBouoUkm0qyfpLXJlmR5JokVyc5LclBSabafnOm57lLkv9JckuSm1v1K0mSJEnSQtQiaDgVuBfw\nD7No+wFgPeDkBuO4VZItgDOBd9KtAbE38Cy6UOTDwNf6HS9aeBWwC92CmJIkSZIk3am1CBqOAwK8\nJcnRSTZbU4Mk2yb5ArCM7hf0YxuMY9BngR2Bo6vq4Ko6rapOqarnAP8J7EEXOAwlyXbAEcC1dP8b\nSJIkSZJ0pzZ00FBV/w38X7pftA8FfpXkpCRvBB4IkGT/JIf1QcR/A+cD+9CFDJ+uqv8ddhxjkjwb\n2B24gS4EGO/1/ft+SR4+xHkCfAK4FPjIbPuRJEmSJGkxWbdRP/sDfw4sBe4KPKV/QRdAfGxc/bG/\n/p8G/E2jMYw5kC7AOLmqrhlfWFXnJVlJt6Xm/nThyGwcBuwKPBl43Cz7kCRJkiRpUWnx6ARV9Xu6\nuwg+1R8Kt4UJg2sXjB0vuvBhj6q6scUYAJKsBzyx//KMKaqe0Y9jn1me58+BtwMfq6qm60tIkiRJ\nkrSQNQkaoAsbquplwE506x/8hNuChbHXT4APAQ+pqoNahgy9HegWlwS4aIp6Y2VbJ9lkFuf5V+Aq\n4O9m0VaSJEmSpEWr1aMTt6qqc4FDAJKsC2zeF11VVX9sfb5xthr4fMUU9QbL7gesnO4JkhxC96jE\nU6vq2pkNT5IkSZKkxa150DCoDxYun8tzjDN4d8INU9QbLNt0up0n2QY4Eji+qr48o5FJkiRJknQn\n0OzRidlK8ugkLxn1OKbpY8D1wCtHPRBJkiRJkuajkQcNwMuBTzbqa/BRhg2nqDdYdoedKSaS5OV0\nC00eUlVXz2JskiRJkiQtenP66MQI/GLg8z2nqDdY9qs1dZpkS+A9wIlV9flZju0ODj/8cJYsWXK7\nY8uWLWPZsmWtTiFJkiRJupNZvnw5y5cvv92xVatWrbXzp6rWXGs6HSXrAHsCjwXuDywB1p9G0x2A\ne1XVOg3GsB5wHV2AckRVvXWSescCLwEuqqptp9HvfsAngFsmqXIXbtu2c6xOAW+tqrdP0N/OwFln\nnXUWO++885pOL0mSJEnSUFasWMHSpUsBllbVirk8V5M7GpI8GjgO+LPZNKf7pXxoVbU6yTeBvYFH\nTFF1l/6cJ02z6xOBM6YoPwR4Rf95J7rvCdbuQpiSJEmSJI3c0EFDkvsDXwU24rZfsEfp43RBwx5J\nNhm/BWWS7ejuoriFaa4NUVXXAD+erDzJ5QN1p71VpiRJkiRJi02LOxpeB2zcf/428HXgZ8Dv6LaR\nXNPdCq+je+Siiar6fJJTgd2ANwOvHlflyH5Mx1bV2YMFSZ4G/CvwG2CfqvoFkiRJkiRp2loEDXvQ\n/eL+sqo6bqaNk7y0wRjGew7wTeDwJBsBxwMb0D3i8Iy+7OAJ2r0cuAewBbAvcPRkJ0iyBLhf/+W9\nBo7v2H+8qap+Oty3IUmSJEnSwtIiaLgPcM5sQobeldx+t4ihVdWVSXYBXgksA14M3AysBF5RVcdM\n0vQYYFfgMmBNu0s8k+7Ri7E7Nsbef9C/XwyscaFJSZIkSZIWkxZBwzV0v8DPSlW9mjs+3jC0qlpN\ntyXle2bQ5iQG7k5YQ91PAZ+a3egkSZIkSVqc7tKgjx/TbWUpSZIkSZLu5FoEDccCu/VrFsxYkmck\neVODcUiSJEmSpBFrETQcB3wX+PckG6+p8gSeSbc7hCRJkiRJWuCGDhqqquh2efglcH6SNyTZNcnm\nSdYZeoSSJEmSJGnBmNZikElunmZ/AY7oX2NtZzEsSZIkSZK0EE1314nppAXFbVs8zjRdqDVXkSRJ\nkiRJ812L7S3HeOuCJEmSJEl3cjNZo+HYqrpL6xfdYpKSJEmSJGkRaLHrxLB8bEKSJEmSpEViukHD\nNcDv52gM5wHfnqO+JUmSJEnSWjStNRqq6u5zNYCqehfwrrnqX5IkSZIkrT3z4dEJSZIkSZK0SKz1\noCHJg5MsWdvnlSRJkiRJc69J0JDkDUlWDLy+OkX1w4DLkvxLkjl7JEOSJEmSJK1901qjYSpJNgJe\nDWwCpD/86zU02wA4CHhKkidU1UXDjkOSJEmSJI1eizsa9gI27T9/B3gq8MAp6r8e+P+AnwNbA19I\nMnTgIUmSJEmSRq9V0ADwGeDxVfWlqvrDZJWr6rdV9S/AUuBUYEfgxQ3GIUmSJEmSRqxF0LAzcD1w\naFXVdBtV1TXAy4E/As9vMA5JkiRJkjRiLYKGPwP+p6pWzbRhVV0AnAM8rME4JEmSJEnSiLUIGjYF\nLh2i/c+BzRuMQ5IkSZIkjViLoOE6YJhtKjeme/RCkiRJkiQtcC2Chl8Dj0my/kwb9m0eA/yqwTgk\nSZIkSdKItQgaTgGWAG+fRdu3922/1WAckiRJkiRpxFoEDcf2769K8okk911TgyT3TfIJ4NVADfQh\nSZIkSZIWsHWH7aCqViT5DPBiYD/gxUlOB84CLqJbwwHgbnQ7VCwFdqULOQo4vqrOHnYckiRJkiRp\n9IYOGnoHAQ8EHtn3+Zj+NZn076f1bSVJkiRJ0iLQ4tEJquoPwOOBT9LdpRBuCxMGjR0v4GPAHlV1\nY4sxSJIkSZKk0WsSNABU1Q1VdQCwE/Bh4HxuCxbGXj8BPgQ8pKoOMmSQJEmSJGlxafXoxK2q6kfA\nIQBJ1gU274uuqqo/tj6fJEmSJEmaP4YOGpLsNu7Qyqq6AqAPFi4f9hySJEmSJGlhaHFHwyl0ay6M\n+SvghAb9SpIkSZKkBabVoxMBrgU+B5zbqE9JkiRJkrTAtAoargMeWlUXNepPkiRJkiQtQC2ChmuB\nbxsySJIkSZKkFttb/hr4Q4N+JEmSJEnSAtciaPg6sHS2jZO8NsnJDcYhSZIkSZJGrEXQ8BHgvkn+\napbttwd2bzAOSZIkSZI0YkMHDVW1Evgb4CNJDk3SIryQJEmSJEkL0NCLQSZ5Sf/xBOBo4O+TfAX4\nEXA1sHoNXdx/2DFIkiRJkqT5ocWuE8cC1X8OcG/gJZPWvqMMtJckSZIkSQtYi6ABurBgqq8lSZIk\nSdKdQKug4QLge7Ns+1hg20bjkCRJkiRJI9QqaPhuVe0/m4ZJPolBgyRJkiRJi4I7REiSJEmSpGZa\n3NHwfuB/hmj/ceCUBuOQJEmSJEkjNnTQUFWHD9n+e8x+fQdJkiRJkjSPjPzRiSQPTLLbqMchSZIk\nSZKGN/KgAXg98K1RD0KSJEmSJA1vPgQNkiRJkiRpkWi1vSUASe4C7A48CrgPsDGQNTR7bMsxSJIk\nSZKk0WkWNCTZC/ggsO1MmwLVahySJEmSJGl0mgQNSZ4HfIbuUYw13cEwxnBBkiRJkqRFZuigIck9\ngY8D6wDnAsuBS4EDgEcD+49rcjfg4cDzgY3oAopvDDsOSZIkSZI0ei3uaDiILjw4CXhWVd0MkGR3\n4NFV9amJGiU5AvgisBdwaINxSJIkSZKkEWux68STgD8CrxwLGaajqn4J7AvcHTiwwTgkSZIkSdKI\ntQgatgd+UFU/n2nDqroA+B6wT4NxSJIkSZKkEWsRNGwGXDjB8VsAkqyzhva/Bh7UYBySJEmSJGnE\nWgQNNzLxWg/X9u9/sob29wSWNBiHJEmSJEkasRZBwyXAAyc4fln/vtdkDfsdKx4L3NBgHJIkSZIk\nacRaBA3nANsnedy442cBAd6a5M/GN0qyEXA8cFfgpw3GIUmSJEmSRqzF9pYnA88FPpvkZcCXq6qA\nU4ArgXsDP0jyb8AKYDXwAOCFwJZA0W1zKUmSJEmSFrgWdzR8AbiZbq2F/wL+HqCqVgNH0t3VsBGw\nP/BB4KPAq+lCBoDf9sclSZIkSdICN/QdDVV1aZIj6e5SAFg5UHwUsBRYNtiELnwAWAU8u6p+O+w4\nJEmSJEnS6LV4dIKqetMkxwt4UZKvAAcCOwEbAr8Cvgy8u6p+1WIMkiRJkiRp9JoEDWtSVZ8GPr02\nziVJkiRJkkanxRoNkiRJkiRJgEGDJEmSJElqaE4enUjyeOCxwHbA5v3hq4DzgO9W1alzcV5JkiRJ\nkjRaTYOGJC8F3ghss4Z6FwJvqarjW55fkiRJkiSNVpNHJ5Ksn+RzwL/ShQxj21dm3Gvs2LbAp5L8\ne5K1siClJEmSJEmae61+yT8OeNa4Y9cCFwPX9V/fDdga2LT/OsBzgD8CL2o0DkmSJEmSNEJDBw1J\n/hJ4Xv/lpcD7gBOr6ueT1N8W2Bc4HLgv8IIkx1XVV4cdiyRJkiRJGq0Wj04c2L9/F9ixqt47WcgA\nUFU/r6p/AnYEvtcf/usG45AkSZIkSSPWImh4JHAT8Pyq+t10G/V1nw+sBv6iwTgkSZIkSdKItQga\n7gF8p6ounWnDqroE+A6wRYNxSJIkSZKkEWsRNPwO+M0Q7S8Hrmowjtvpd8J4bZIVSa5JcnWS05Ic\nlCRr7mHCPjdK8uJ+t4yfJfl9kuuTXJDk00ke1/r7kCRJkiRpIWkRNPwcuN8Q7bcEzmswjlsl2QI4\nE3gncDqwN92uGJcAHwa+lmT9Gfa5M/BLuh02dgDeBjwReBK37bpxapIPNPo2JEmSJElacFpsb/lf\nwFuS/GlV/XImDZNsBTwaOHiS8tcCe1XVE2c4ps/SLTZ5dFW9auD4KUlOBJ5BFzgcMIM+7wtsBqwA\nHlVVqwfK/jvJ94EvAQcnubCq3jfDMUuSJEmStOC1uKPhg3SPP/xbkk2n26ivu5zuzoNPTlJte2D3\nmQwmybP7NjcAR0xQ5fX9+35JHj6TvoEC3jYuZOgKqr5Ct95EgFfOsF9JkiRJkhaFoYOGqroWeBqw\nDXBeklcleeBk9ZM8IMmrgJXAH4CnV9XNw45jwIF0gcDJVXXNBOM9rz93gP1n0O/PgPcCp05R55z+\nfcskm82gb0mSJEmSFoWhH51I8vP+44Z0jxa8G3h3khuBq4Eb+/IN+vINxpoCfwS+P8XajPec4VjW\no1s3AeCMKaqeQbfOwj7AodPpuw8oXrOGamOByS10IYokSZIkSXcqLdZo2IbuDgIG3kMXPNxnXN0M\n1CvWvIhkBvqcjh2A9fo2F01Rb6xs6ySb9HdltPCA/v3MqrqhUZ+SJEmSJC0YLdZogC4QGHzN9Phk\nr5naauDzFVPUGywbZseMW/U7XTyJLuR4d4s+JUmSJElaaFrc0QDdLg9/16ivQf8E7DuD+psMfJ7q\njoLBsmkvYLkGrwbWBz5XVSc26lOSJEmSpAWlVdBwXVVd3KivWyW5rnWfcyHJ44BXAefRLUYpSZIk\nSdKdUqtHJ+bKTB+hGFxrYcMp6g2W3WFniplIsj3weeCXwJOqatUw/UmSJEmStJANfUdDVc1ZWFFV\nLwVeOoMmvxj4PNWOFYNlv5pB/7eTZDvgZLqwYo+qumS2fUmSJEmStBi0enRivlgJrKb7vraZot5Y\n2cWz3XEiyUOAbwC/A55YVb+eaR+HH344S5Ysud2xZcuWsWzZstkMSZIkSZIkli9fzvLly293bNWq\ntXfzfapmsnvk/JfkS8DewElV9fRJ6vwI2B74UFX9n1mcY2fga8ClwJOr6rKBsnXodrK4rKpunKL9\nWWeddRY777zzTE8vSZIkSdKMrFixgqVLlwIsraoVc3mu+b5Gw2x8vH/fI8km4wv7xx12oNuG8pMz\n7TzJrsA36R7T2H0wZOjdD7gQ+IuZ9i1JkiRJ0kK36IKGqvo8cCrdgo9vnqDKkXQhw7FVdfZgQZKn\nJbk8yQ+TbDW+YZLdgK8C59M9LnHVBP2n71+SJEmSpDudxbZGw5jn0N11cHiSjYDjgQ2AQ4Bn9GUH\nT9Du5cA9gC2AfYGjxwqS/AXwZeCuwEOAXyYTbogxk10yJEmSJElaVBZl0FBVVybZBXglsAx4MXAz\n3WKRr6iqYyZpegywK3AZ3ZaVg3alu0ui6EKLKYcwy6FLkiRJkrSgLcqgAaCqVgPv6V/TbXMScK9J\nyt4PvL/N6CRJkiRJWpwW3RoNkiRJkiRpdAwaJEmSJElSMwYNkiRJkiSpGYMGSZIkSZLUjEGDJEmS\nJElqxqBBkiRJkiQ1Y9AgSZIkSZKaMWiQJEmSJEnNGDRIkiRJkqRmDBokSZIkSVIzBg2SJEmSJKkZ\ngwZJkiRJktSMQYMkSZIkSWrGoEGSJEmSJDVj0CBJkiRJkpoxaJAkSZIkSc0YNEiSJEmSpGYMGiRJ\nkiRJUjMGDZIkSZIkqRmDBkmSJEmS1IxBgyRJkiRJasagQZIkSZIkNWPQIEmSJEmSmjFokCRJkiRJ\nzRg0SJIkSZKkZgwaJEmSJElSMwYNkiRJkiSpGYMGSZIkSZLUjEGDJEmSJElqxqBBkiRJkiQ1Y9Ag\nSZIkSZKaMWiQJEmSJEnNGDRIkiRJkqRmDBokSZIkSVIzBg2SJEmSJKkZgwZJkiRJktSMQYMkSZIk\nSWrGoEGSJEmSJDVj0CBJkiRJkpoxaJAkSZIkSc0YNEiSJEmSpGYMGiRJkiRJUjMGDZIkSZIkqRmD\nBkmSJEmS1IxBgyRJkiRJasagQZIkSZIkNWPQIEmSJEmSmjFokCRJkiRJzRg0SJIkSZKkZgwaJEmS\nJElSMwYNkiRJkiSpGYMGSZIkSZLUjEGDJEmSJElqxqBBkiRJkiQ1Y9AgSZIkSZKaMWiQJEmSJEnN\nGDRIkiRJkqRmDBokSZIkSVIzBg2SJEmSJKkZgwZJkiRJktSMQYMkSZIkSWrGoEGSJEmSJDVj0CBJ\nkiRJkpoxaJAkSZIkSc0YNEiSJEmSpGYMGiRJkiRJUjMGDZIkSZIkqRmDBkmSJEmS1IxBgyRJkiRJ\nasagQZIkSZIkNWPQIEmSJEmSmjFokCRJkiRJzRg0SJIkSZKkZgwaJEmSJElSMwYNkiRJkiSpGYMG\nSZIkSZLUzKINGpKsn+S1SVYkuSbJ1UlOS3JQkgzZ96ZJ3pHkx0muT3JFkm8meX6r8UuSJEmStBAt\nyqAhyRbAmcA7gdOBvYFnAZcAHwa+lmT9WfZ9f+Bc4DXA54AnAH8FBFie5LihvwFJkiRJkhaodUc9\ngDnyWWBH4OiqetXA8VOSnAg8gy5wOGAmnfbhxBeBLYFXVtUHBsq+AZwGvCjJT6vqbUN+D5IkSZIk\nLTiL7o6GJM8GdgduAI6YoMrr+/f9kjx8ht0fCjyA7s6IDw4WVNUfgTfR3dnw2iT3mWHfkiRJkiQt\neIsuaAAOBAo4uaquGV9YVecBK+kCgf1n2PcBfd//UVU1QfnXgGuBuwIvmmHfkiRJkiQteIsqaEiy\nHvDE/sszpqh6Bl3QsM8M+t4G2H6qvqvqFuDsmfYtSZIkSdJisaiCBmAHYL3+80VT1Bsr2zrJJtPs\ne6cJ2k/V905T1JEkSZIkaVFabEHDVgOfr5ii3mDZ/eao782S3HWafUuSJEmStCgstqBh8O6EG6ao\nN1i26TzoW5IkSZKkRWGxBQ2SJEmSJGmEFlvQcO3A5w2nqDdYdoedKUbQtyRJkiRJi8K6ox5AY78Y\n+HzPKeoNlv1qln2vXEPfV1fVH6bq8PDDD2fJkiW3O7Zs2TKWLVs2zSFJkiRJknR7y5cvZ/nyer+Y\ngwAAFt9JREFU5bc7tmrVqrV2/sUWNKwEVtN9X9tMUW+s7OKqunaKeoN+MK79t9fQ9w8mKb/VUUcd\nxc477zzN00uSJEmStGYT/QF7xYoVLF26dK2cf1E9OlFVq4FvAgEeMUXVXYACTppB3xcB5/VfTth3\nkrsAD+/7/uJ0+5YkSZIkabFYVEFD7+P9+x5JNhlfmGQ7YAe6MOCTs+g7wDMnKd+TbneKG4ATZti3\nJEmSJEkL3qILGqrq88CpdIsyvnmCKkfShQzHVtXZgwVJnpbk8iQ/TLLVBG0/CJwPbJnk0HFt1wXe\n2vd9ZFVdOvx3I0mSJEnSwrLY1mgY8xy6RygOT7IRcDywAXAI8Iy+7OAJ2r0cuAewBbAvcPRgYVXd\nlGSfvv17k9yL7vGLzYHXAEuB46vq7XPxTUmSJEmSNN8tujsaAKrqSrp1GF4H7Ap8Bfg88CfAK6pq\nz6q6aYKmxwC/BX7U15+o758BDwHeRRdGnAwcB9wMvKCq9mv73UiSJEmStHAs1jsaxhaGfE//mm6b\nk4B7TaPetcAb+5ckSZIkSeotyjsaJEmSJEnSaBg0SJIkSZKkZgwaJEmSJElSMwYNkiRJkiSpGYMG\nSZIkSZLUjEGDJEmSJElqxqBBkiRJkiQ1Y9AgSZIkSZKaMWiQJEmSJEnNGDRIkiRJkqRmDBqkRpYv\nXz7qIaghr+fi4vVcXLyei4/XdHHxei4uXk/NhkGD1Ij/CC8uXs/Fxeu5uHg9Fx+v6eLi9VxcvJ6a\nDYMGSZIkSZLUjEGDJEmSJElqxqBBkiRJkiQ1s+6oB3AntSHAypUrRz0ONbRq1SpWrFgx6mGoEa/n\n4uL1XFy8nouP13Rx8XouLl7PxWPg988N5/pcqaq5PofGSfJC4DOjHockSZIk6U7nRVV1wlyewKBh\nBJJsAewFXATcMNrRSJIkSZLuBDYEtgG+WlVXzuWJDBokSZIkSVIzLgYpSZIkSZKaMWiQJEmSJEnN\nGDSsRUnWT/LaJCuSXJPk6iSnJTkoSUY9Pk1fklum8frnUY9Tt5fOIf38uyXJVjNou2mSdyT5cZLr\nk1yR5JtJnj+XY9bkZnM9k2w9zfn7t2vjexAkWTfJvkk+lWRlkuuS/CHJxUk+m+Sp0+jD+TlPDHM9\nnZ/zU//z6z5Jjup/bv1tktX9v73n9Me3XUMfztF5Ypjr6RxdOPp/b8eux5Q/H83V/DRoWEvSLQB5\nJvBO4HRgb+BZwCXAh4GvJVl/dCPULPwBuG6Klwt9ziNJdgS+B3wAuBsw7QVqktwfOBd4DfA54AnA\nXwEBlic5rvmANaVhrmfveiafu9cCNzUbrCaVZEu6hZE/C+xGdz337j8f3b9/Icnnk6w3SR/Oz3mi\nxfXsOT/nlw8D/wW8FPgG8HxgV2A/up9jDwN+lOTpEzV2js47Q13PnnN0HkvyXGBfup+Npvz5aE7n\nZ1X5Wgsv4FvAzcB7Jyg7EbgF+NdRj9PXtK/nLcDjRj0OX9O+XkfQBT+nAO/or9/NwFbTaLs+8JO+\n/qHjytYFvt+XvXHU3+ed5TXk9dy6r/uno/4+fBXAjv31uwhYMkH5Q+h+YL0Z+OcJyp2f8+jV4Ho6\nP+fhC/hkf10eM0n5F/rrfiWwwbgy5+g8ew15PZ2j8/wFbAFcBqxa089Hcz0/vaNhLUjybGB3uh+M\nj5igyuv79/2SPHytDUzD8nGXheMw4LCqejxw/gzbHgo8gC7l/+BgQVX9EXgT3f8XXpvkPsMPVdMw\nzPUc4/ydPwo4qqpW3aGg6ofAcrrrdWCSjcZVcX7OP8NczzHOz/nlV8AXqup7k5Qf37/fHXjwuDLn\n6PwzzPUc4xydvz5IFyAcOY26czo/DRrWjgPp/sN7clVdM76wqs4DVtJdyP3X8tikO4Mdquqjs2x7\nAN38/Y/qI95xvkZ3m+BdgRfN8hyamWGup+aX3wLvpfsL2mTO6d83ALYbV+b8nF+GvZ6ah6rqjVX1\nrCmq3Djw+dpxZc7ReWbI66l5LMkz6R6F+Vvg0mk0mdP5adAwx/pnEJ/Yf3nGFFXPoAsa9pnzQUl3\nMlU1nX9s7yDJNsD2/ZcTzt+qugU4G+fvWjPb66n5p6p+U1WvqaoLp6h288Dn68Y+OD/nn2Gupxa0\nF/bv362qW+8yc44uWBNeT81vSe4O/Avw1ao6dhr1t2GO56dBw9zbARhb8OiiKeqNlW2dZJO5HJCa\neXSSE5L8JMm1SS5P8p0kf5dk01EPTk3sNPD5oinqjZXtNEUdzR8BnpLkP5P8rF8V/9IkX0/yN0k2\nGPUAdTsP6N8vAy4YOO78XJgmu55jnJ8LQJKNkzwmyb8Dz6FbRG7fcdWcowvENK/nrdVxjs5H/wxs\nDLx8mvXnfH4aNMy9we1Erpii3mDZ/eZoLGrrLXS3iR4MPA74a7pVeN8FnJvkYaMbmhqZ6fzdLMld\n53A8auc9wA+Al9HN31cCm9L9NeDMJFuPcGzqJVkHeDbdrZ3/NO7WTufnArOG6znI+TlPJdk2yR/p\nbqf+DvAw4DlV9dyqunJcdefoPDfD6znIOTqPJNkHeDHwuqr61TSbzfn8XHcmlTUrg3cnTLXd4WCZ\nfw2f/74FvK2qThk49r/AfyT5FN22MF9K8pA1/EOt+W228/cPczMcNXAD8E3glVX1o4HjZyf5HPBV\nuq2dvpjk4VW1ehSD1K0OBO5Nty30P48rc34uPFNdT3B+LgS/pPvL5l3p1tj4a+BzSb4BHFBVvxyo\n6xyd/2ZyPcE5Ou/0d1F/BDi1qj48g6ZzPj+9o0GaharaY1zIMOhv6bbvujfwqrU2KElr1D9D/uRx\nPyCNlf2R7q8y0D329rK1OjjdTpIHAu+mu8X+BVV18xqaaB6bzvV0fs5/VbW6qn5cVWdV1Qn97j8f\nB54EfCfJFqMdoWZiptfTOTovvQ/YnC7InVcMGube4GqtG05Rb7DsDjtTaOHo72A4k+4ZtqeOeDga\njvP3Tqbffu+S/kvn74gkuTfwRbrQds+q+sUE1ZyfC8Q0r+caOT/nrVfRPTr6p8AbBo47Rxemya7n\nGjlH164ke9LtWPjGqvrZDJvP+fw0aJh7g/8xvecU9QbLpvtsjeavsev+ZyMdhYY10/l7dVV5y+fC\n9wu6oND5OwL9L6UnA5sBe1XVuZNUdX4uADO4ntPl/JxnqupausdhAjx9oMg5ugBNcT2nyzm6FiS5\nG/Ax4PvA0RNVmeTzmDmfnwYNc28lMPZ80jZT1Bsru7if4FrYJprQWnh+MPB5mynqjZX9YIo6Wjic\nvyOS5H7At4EtgMdX1Yopqjs/57kZXs9pd9ugD7X3m/59y4FjztGFa6LrOV3O0bVjKd0GAkuBG5Os\nHnzRPQIz5oL++E1JPtYfm/P5adAwx/pFUL5JN+keMUXVXehWYT5pbYxLs5fko0n2W0O1sZVcL5rj\n4WgOVdVFwHn9lxPO3yR3AR5ON3+/uHZGptlKcmKSp6yh2lZ01/OiuR+RxvR7en8b2AjYffxfvpNs\nnWTjsa+dn/PbTK9nf8z5Oc8k+ZMkK5M8eg1Vl/Tvq8YOOEfnn2GuZ9/eOTp/fB94CPDQSV5vGqi7\nd3/sYWPH18b8NGhYO8YSpT2SbDK+MMl2dIumFPDJtTkwzcqedNtzTSjJPekmrMHR4vBxuqDwmZOU\n70m3cu8NwAlra1CatWcAk/6Q1G9Le9/+S+fvWpLkAcCpdHNtt6r6yQTVLuSO//Y6P+ehIa6n83P+\nWY9uN4JdJ6uQZEPgUXQ/95w2rtg5Or8Mez2do/NEVf2hX8hzwhfw64HqPx0ou3Tg+JzOT4OGtaCq\nPk/3H9wNgTdPUOVIusl8bFWdvTbHplnbO8mjJil7P90/5FfQrQSrhe2DwPnAlkkOHSxIsi7wVrr5\ne+S4f7w1f+2XZNvxB5Osz23POf4Ug9+1IsmD6P4beRPdL6UXzqC583OeGfJ6gvNzvjosyb0mKftH\nulXvC3jPuDLn6Pw02+sJztHFZE7n57pNhqjpeA7dIxSHJ9kIOB7YADiELh38JnDw6IanGbiG7raw\nbyT5Z7ofqH4DbAu8Angi3YKez6qqK0Y2St2qv8tk7D+o9xso2m7gLqMLq+r349tW1U1J9qGbo+/t\n/8N8Et1/hF9D92zc8VX19jn7BnQ7w1xPulWW7wackeS9dLceXgU8CDic7rbClcBTq+qmuRi/btP/\nsHoKcA+6X0x/nEz6eG/d4YDzc14Z9nri/JyPbqL7a+b96K7n0cAZdD/3/Bnwcrrbsm8ADq6q2/0F\n3Dk67wx1PXGOzmv975hji3BO+PPR4Nakcz0/UzXRv/OaC0nWo9tfdhlwf+Bmusl4bFUdM8qxafr6\nhG+f/vVIukVS7koXQKwEvgB8rKpWTdaH1q4kb6a7m2iqf/CeUFXfnqKPTej+0d2X7pr/HjgH+GhV\n/b92o9WaDHM9k9wVeBbdD1JL6bbv2gC4mm6ho8/R/Zt8Y+tx646SPAP4/AyavKyqjpugH+fnPDDs\n9XR+zk9JNqP7g9mTgZ3oFgjcgO6XzgvodhU5Zqq7V5yj88cw19M5Or8l2R34FhP/fBSgqmqdCdrN\nyfw0aJAkSZIkSc24RoMkSZIkSWrGoEGSJEmSJDVj0CBJkiRJkpoxaJAkSZIkSc0YNEiSJEmSpGYM\nGiRJkiRJUjMGDZIkSZIkqRmDBkmSJEmS1IxBgyRJkiRJasagQZIkSZIkNWPQIEmSJEmSmjFokCRJ\nt0pyRJLfJTkxyXqjHo8kSVp4UlWjHoMkSWosyUOBZ/Zf/m9V/ec02twfOB8Y++HgwKr65BwNUZIk\nLVLrjnoAkiRpTjwMeHP/+VhgjUEDkIH3AtZpPyxJkrTY+eiEJEmL27RvXayqnwLvBK4Bvgx8eq4G\nJUmSFi+DBkmSdKuqekNV3b2qnlpVN456PJIkaeExaJAkSZIkSc0YNEiStDhlzVUkSZLaM2iQJGkR\nSXJLkluAT4wdAl46dnzca7e+ze6TlH9i0hPd/pyPSvLhJD/ut8b8fZJfJjkpycFJNpyi7dmTnHur\nvnzfJF9P8pskf0hyXpIjk9x9XD+bJXlHknOTXJ/kiiRfTPLkKc693yTnflNfvnOSj/TnXJXkuiQr\nk7w3ydbT+d9m4FzPTHJ8kguSXNu/Lkjy6STPmElfkiTNd25vKUnSIjIQDtwfeCzdYpA/A747rmoB\n76qq85NsB7x2gnafqqr9pzjXRnSBxvP6+pcD/w3cCGwP7EQXdFwGvKiqvjVBH28Btuq/fA5wt76v\nPwfeCDwXOAW4DnhEfzzAT4HHVNVvk2wLnAz8FvgJcE9gN2D9vt/DquoDE5z7McAB/ZcP618FHAGs\nBt4KXNV/T38AHgw8qD//9cBBVXXCZP/79OfYFvi3fuwFXAic3RfvDGzT9/d94PlVdfFU/UmStBAY\nNEiStAgl2Q/4JNMIDGbTrg8ZTgWW9nXfAryjqm4ZqLMr8P+ALYGbgKdW1TemOPeFwNZ9f58AtgOe\nWVVXDdQ5Cjisr/MV4Jl0v6S/rqq+OlBvx358m9GFBjtW1c+mOPeb6bYDLWAlsAPwNuBtVXXzQL19\ngM8AmwC3AM+tqv+YpM8dgG8B96ILKg6squXj6rwQ+DiwIV0gs1tVXTDZOCVJWgh8dEKSJM3Gh7gt\nZPhAVb1tMGQAqKrTgacDNwPrAccl2XQN/RbdX/ifBzxrMGTovQ74/9u7u1DNqjKA4/8nZ/JiNKMx\nx8g+DGXQmXQqS8EomBsjpE9TAk0bR8GmLIguhGgc7wr6IMlispkpUEJJ6kIx0IbCBkWzZBzRIgdG\na5IssSyUmXy6WGtz9mzfj/0e3jnnPcf/Dw57rfM+e6317nO1nrPXWs/V8gXATcDN7SRD7Xsf8K3a\n1krm3lzo4wxge2Ze304y1HbvBK6u7b4G2B4RJ3YbiIhjKUmWk+p32tJNMtT2bgW+UKtrgNsjYuUE\nY5UkaeaYaJAkSROJiPXA5bX6ImWpwUCZ+XvgLsrEfA3jJ/xBmZjfkpn/GNDeS8BvmJvoXwxsH9LW\n3a3yB8b02+7/ZcobGgNl5m3AozV2NfD5AWFXUZZZJPBEZu4a0ecO4I+1vbOAXm+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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2121ac29358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Vulnerabilidad ante la pérdida de hábitat\n",
    "\n",
    "Ante la pérdida de hábitat, la metapoblación es sensible a variaciones ambientales. \n",
    "\n",
    "Para observar esta vulnerabilidad graficaremos las tasas de colonización y extinción en función de la proporción de parches ocupados. La tasa de colonización tiene la forma de una parábola y la de extinción, de una recta:\n",
    "\n",
    "$$ Colonización = c p (h-p) = cph - cp^2,$$\n",
    "$$ Extinción = e p. $$\n",
    "\n",
    "El punto de equlibirio $p^*$ ocurre en la intersección de las curvas. De nuevo, observemos que existe un punto de equilibrio si $h>\\frac{e}{c}$ y que la pérdida de hábitat disminuye la tasa de colonización.\n",
    "\n",
    "Ahora imaginemos una especie afectada por alguna variación ambiental la cual incrementa su probabilidad de extinción, por ejemplo, una epidemia. La especie sobreviviría si este cambio ocurre cuando una gran proporción del paisaje es habitable, pero se extinguiría a nivel regional si ha ocurrido una pérdida significativa de hábitat."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "##### Exploración"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def graficar_tasas_levins(colonización=0.8, extinción=0.2, hábitat=1):\n",
    "    parches = numpy.linspace(0, 1, 50)\n",
    "    equilibrio = hábitat - extinción/colonización\n",
    "    \n",
    "    if equilibrio < 0:\n",
    "        equilibrio = 0\n",
    "    tasa_colonización = colonización * parches * (hábitat - parches)\n",
    "    tasa_extinción = extinción * parches\n",
    "    \n",
    "    pyplot.figure()\n",
    "    \n",
    "    pyplot.plot(parches, tasa_colonización, lw=5, label='colonización')\n",
    "    pyplot.plot(parches, tasa_extinción, '--', lw=5, label='extinción')\n",
    "    pyplot.plot(equilibrio, equilibrio * extinción, \"o\", ms=10, c='r')\n",
    "    pyplot.plot(equilibrio, 0.005, \"^\", ms=15, c='r')\n",
    "\n",
    "    pyplot.ylim(0, 0.3)\n",
    "    pyplot.xlim(0, 1.01)\n",
    "    \n",
    "    pyplot.xlabel('parches ocupados')\n",
    "    pyplot.ylabel('tasas')\n",
    "    pyplot.title('Equilibrio entre tasas con $p^*={:.2f}$'.format(equilibrio))\n",
    "    pyplot.legend(loc='upper right', fontsize = \"small\")\n",
    "\n",
    "    \n",
    "y = interactive(graficar_tasas_levins, \n",
    "                colonización = (0, 1, 0.1),\n",
    "                hábitat = (0, 1, 0.1),\n",
    "                extinción = (0, 1, 0.1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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yI418tHwPH/+0hyljA7hk9ggmRA1BKdk1IYQw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srrK7E2Lw1rTSk4Wl8BF4MT4gZFwt7OXvU5k4PH48sdK2BVTn3D0M/JHVOCJyAxeAK8XD27unQi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\nawAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2121c3c8470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 2. Calidad del paisaje\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Ahora veremos cómo en un paisaje donde se realizan actividades agrícolas, la calidad de las áreas donde están distribuidos los parches de hábitat también influye en la dinámica de metapoblaciones. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Un parche - (Vandermeer & Carvajal 2001)\n",
    "\n",
    "![Image](./figuras/diagrama_vandermeer_s.png)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "La población dentro de un parche de hábitat, $x_t$, tiene una tasa de crecimiento $r$ y se comporta de acuerdo al modelo logístico, $$x_{t+1}=rx_{t}(1-x_t).$$\n",
    "\n",
    "En cada tiempo una fracción de la población $e$ emigra del parche hacia el exterior. La proporción de individuos que emigra depende de la calidad del paisaje alrededor del parche: entre mayor es la calidad del paisaje, mayor es la proporción de individuos que emigra. Al incorporar la emigración en la dinámica de población local obtenemos $$x_{t+1} = r x_{t}(1- x_{t})- e x_{t}.$$\n",
    "\n",
    "Debido a la emigración, también hay una cantidad de individuos $y_t$ fuera del parche y en cada tiempo una fracción $i$ regresa al interior, pero el resto muere. La proporción de individuos que inmigra depende de qué tan aislado está el parche. Al incorporar la inmigración a la dinámica local de población, junto con la dinámica de la población fuera del parche, obtenemos las siguientes ecuaciones: \n",
    "\n",
    "$$\\begin{aligned}\n",
    "x_{t+1} &= r(x_{t}+iy_{t})(1- x_{t}- i y_{t})- e x_{t} \\\\\n",
    "y_{t+1} &= e x_{t}.\n",
    "\\end{aligned}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Supervivencia de la metapoblación"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Ahora la supervivencia de la metapoblación depende tanto de la dinámica de población local como de la calidad del paisaje. \n",
    "\n",
    "En un paisaje de muy baja calidad ($e=0$), no ocurre emigración y la población en el parche está aislada. Incrementar la calidad del paisaje induce una dinámica de metapoblación.\n",
    "\n",
    "La población podría tener una tasa de crecimiento que le permitiera sobrevivir de forma aislada, incluso siguiendo un comportamiento caótico (por ejemplo con $r=3.8$). En este caso, al aumentar la calidad del paisaje la población pasa a formar parte de una metapoblación y el parche experimenta extinciones periódicas, es decir, su supervivencia ahora depende de los individuos fuera del parche. Si la población sobrevivía de forma aislada, ahora es vulnerable a variaciones ambientales que pudieran afectar la dinámica de metapoblación.\n",
    "\n",
    "Por otro lado, cuando la tasa de crecimiento de la población en el parche es demasiado grande ($r>4$), la población se extingue si está aislada ($e=0$), pero sobrebrevive como una metapoblación cuando el paisaje a su alrededor permite la emigración, aunque sólo hasta cierto punto: si la calidad del paisaje es muy alta, el parche se vuelve vulnerable a variaciones ambientales como en el caso anterior."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "##### Exploración"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def vandermeer(x, y, r, i, e):\n",
    "    \"\"\"\n",
    "    Modelo de metapoblaciones de Vandermeer & Carvajal (2001).\n",
    "    \n",
    "    Parámetros\n",
    "    x: densidad de población en parche\n",
    "    y: densidad de población fuera de parche\n",
    "    r: tasa de crecimiento\n",
    "    i: proporción de individuos que inmigra al parche\n",
    "       (medida del aislamiento del parche)\n",
    "    e: proporción de individuos que emigra del parche \n",
    "       (medida de la calidad del paisaje de alrededor)\n",
    "    \"\"\"\n",
    "    x_next = r * (x + i*y)*(1 - x - i*y) - e*x\n",
    "    if x_next <= 0.001:\n",
    "        x_next = 0\n",
    "    \n",
    "    y_next = e * x\n",
    "    if y_next <= 0.001:\n",
    "        y_next = 0\n",
    "        \n",
    "    return x_next, y_next"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def graficar_vandermeer(e, r=4.01):    \n",
    "    tiempo = 40\n",
    "    x_0 = 0.1 # densidad de población en parche\n",
    "    y_0 = 0 # densidad de población fuera de parche\n",
    "    i = 0.4 # inmigración hacia el parche\n",
    "    \n",
    "    x = [0]*(tiempo + 1)\n",
    "    y = [0]*(tiempo + 1)\n",
    "    x[0] = x_0\n",
    "    y[0] = y_0\n",
    "    for t in range(tiempo):\n",
    "        x[t+1], y[t+1] = vandermeer(x[t], y[t], r, i, e)\n",
    "        \n",
    "    pyplot.figure()\n",
    "    pyplot.plot(numpy.linspace(0, tiempo, tiempo+1), x, lw=3)\n",
    "    pyplot.plot(numpy.linspace(0, tiempo, tiempo+1), numpy.zeros(tiempo+1), '--', c='red', lw=4)\n",
    "    pyplot.ylim(-0.01, 1.1)\n",
    "    pyplot.xlabel('tiempo')\n",
    "    pyplot.ylabel('población')\n",
    "    pyplot.title('Población en parche de hábitat')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "w = interactive(graficar_vandermeer, r={'3.8': 3.8, '4.01':4.01}, e=(0, 1, 0.1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
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BwGFJgYBDymhMAACArCLggLIkMhx62hMnS5RUzF2xCRVSMsNhhJKK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\nIylGSnygdkdmPga8g2Kkw1sj4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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2121b9e87b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(w)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Referencias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "1. González González, C., López Martínez, R., Hernández López, S., & Benítez, M. (2016). A dynamical model to study the effect of landscape agricultural management on the conservation of native ecological networks. *Agroecology and Sustainable Food Systems, 40*(9), 922–940. http://doi.org/10.1080/21683565.2016.1209271\n",
    "2. Levins, R. (1969). Some demographic and genetic consequences of environmental heterogeneity for biological control. *Bulletin of the Entomological Society of America, 15*(3), 237–240. http://doi.org/10.1093/besa/15.3.237\n",
    "3. Vandermeer, J., & Carvajal, R. (2001). Metapopulation dynamics and the quality of the matrix. *The American Naturalist, 158*(3), 211–220. http://doi.org/10.1086/321318"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "    font-weight: 400;\n",
       "    width:700px;\n",
       "    margin-left:auto;\n",
       "    margin-right:auto;\n",
       "}\n",
       "\n",
       "\n",
       "/* Formatting for header cells */\n",
       ".text_cell_render h1 {\n",
       "    font-family: 'Alegreya', serif;\n",
       "    font-style:regular;\n",
       "    font-weight: 500;    \n",
       "    font-size: 50pt;\n",
       "    line-height: 100%;\n",
       "    color: rgb(6, 56, 82);\n",
       "    margin-bottom: 0.5em;\n",
       "    margin-top: 0.5em;\n",
       "    display: block;\n",
       "}   \n",
       ".text_cell_render h2 {\n",
       "    font-family: 'Alegreya', serif;\n",
       "    font-weight: 400;\n",
       "    font-size: 30pt;\n",
       "    line-height: 100%;\n",
       "    color: rgb(6, 56, 82);\n",
       "    margin-bottom: 0.1em;\n",
       "    margin-top: 0.3em;\n",
       "    display: block;\n",
       "}   \n",
       "\n",
       ".text_cell_render h3 {\n",
       "    font-family: 'Alegreya', serif;\n",
       "    margin-top:16px;\n",
       "    font-size: 22pt;\n",
       "    font-weight: 500;\n",
       "    margin-bottom: 3px;\n",
       "    font-style: regular;\n",
       "    color: rgb(6, 56, 82);\n",
       "}\n",
       "\n",
       ".text_cell_render h4 {    /*Use this for captions*/\n",
       "    font-family: 'Alegreya', serif;\n",
       "    font-size: 12pt;\n",
       "    text-align: center;\n",
       "    margin-left:50px;\n",
       "    margin-top: 0.5em;\n",
       "    margin-bottom: 2em;\n",
       "    font-style: regular;\n",
       "}\n",
       "\n",
       ".text_cell_render h5 {  /*Use this for small titles*/\n",
       "    font-family: 'Alegreya', sans-serif;\n",
       "    font-weight: 400;\n",
       "    font-size: 16pt;\n",
       "    color: rgb(240, 129, 15);\n",
       "    font-style: italic;\n",
       "    margin-top: 0.8em;\n",
       "    margin-bottom: 0px\n",
       "}\n",
       "\n",
       ".text_cell_render h6 { /*use this for copyright note*/\n",
       "    font-family: 'PT Mono', sans-serif;\n",
       "    font-weight: 300;\n",
       "    font-size: 9pt;\n",
       "    line-height: 100%;\n",
       "    color: grey;\n",
       "    margin-bottom: 1px;\n",
       "    margin-top: 1px;\n",
       "}\n",
       "\n",
       ".CodeMirror{\n",
       "        font-family: \"PT Mono\";\n",
       "        font-size: 90%;\n",
       "}\n",
       "\n",
       "</style>\n",
       "<script>\n",
       "    MathJax.Hub.Config({\n",
       "                        TeX: {\n",
       "                           extensions: [\"AMSmath.js\"],\n",
       "                           equationNumbers: { autoNumber: \"AMS\", useLabelIds: true}\n",
       "                           },\n",
       "                tex2jax: {\n",
       "                    inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n",
       "                    displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ]\n",
       "                },\n",
       "                displayAlign: 'center', // Change this to 'center' to center equations.\n",
       "                \"HTML-CSS\": {\n",
       "                    styles: {'.MathJax_Display': {\"margin\": 4}}\n",
       "                }\n",
       "        });\n",
       "</script><link href='http://fonts.googleapis.com/css?family=Lato:100,300,400,500,700,800,900,100italic,300italic,400italic,500italic,700italic,800italic,900italic' rel='stylesheet' type='text/css'>\n",
       "<link href='http://fonts.googleapis.com/css?family=PT+Mono' rel='stylesheet' type='text/css'>\n",
       "<link href='http://fonts.googleapis.com/css?family=Shadows+Into+Light' rel='stylesheet' type='text/css'>\n",
       "<link href='http://fonts.googleapis.com/css?family=Alegreya' rel='stylesheet' type='text/css'>\n",
       "<style>\n",
       "\n",
       "@font-face {\n",
       "    font-family: \"Computer Modern\";\n",
       "    src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
       "}\n",
       "\n",
       "#notebook_panel { /* main background */\n",
       "    /*background: rgb(245,245,245);*/\n",
       "}\n",
       "\n",
       "div.cell { /* set cell width */\n",
       "    width: 850px;\n",
       "}\n",
       "\n",
       "div #notebook { /* centre the content */\n",
       "    width: 1000px;\n",
       "    margin: auto;\n",
       "    padding-left: 0em;\n",
       "}\n",
       "\n",
       "#notebook li { /* More space between bullet points */\n",
       "margin-top:0.8em;\n",
       "}\n",
       "\n",
       "/* draw border around running cells */\n",
       "div.cell.border-box-sizing.code_cell.running { \n",
       "    border: 1px solid #111;\n",
       "}\n",
       "\n",
       "/* Put a solid color box around each cell and its output, visually linking them*/\n",
       "div.cell.code_cell {\n",
       "    border-radius: 0px; \n",
       "    padding: 0.5em;\n",
       "    margin-left:1em;\n",
       "    margin-top: 1em;\n",
       "}\n",
       "\n",
       "div.text_cell_render{\n",
       "    font-family: 'Lato', sans-serif;\n",
       "    line-height: 140%;\n",
       "    font-size: 125%;\n",
       "    font-weight: 400;\n",
       "    width:700px;\n",
       "    margin-left:auto;\n",
       "    margin-right:auto;\n",
       "}\n",
       "\n",
       "\n",
       "/* Formatting for header cells */\n",
       ".text_cell_render h1 {\n",
       "    font-family: 'Alegreya', serif;\n",
       "    font-style:regular;\n",
       "    font-weight: 500;    \n",
       "    font-size: 50pt;\n",
       "    line-height: 100%;\n",
       "    color: rgb(6, 56, 82);\n",
       "    margin-bottom: 0.5em;\n",
       "    margin-top: 0.5em;\n",
       "    display: block;\n",
       "}   \n",
       ".text_cell_render h2 {\n",
       "    font-family: 'Alegreya', serif;\n",
       "    font-weight: 400;\n",
       "    font-size: 30pt;\n",
       "    line-height: 100%;\n",
       "    color: rgb(6, 56, 82);\n",
       "    margin-bottom: 0.1em;\n",
       "    margin-top: 0.3em;\n",
       "    display: block;\n",
       "}   \n",
       "\n",
       ".text_cell_render h3 {\n",
       "    font-family: 'Alegreya', serif;\n",
       "    margin-top:16px;\n",
       "    font-size: 22pt;\n",
       "    font-weight: 500;\n",
       "    margin-bottom: 3px;\n",
       "    font-style: regular;\n",
       "    color: rgb(6, 56, 82);\n",
       "}\n",
       "\n",
       ".text_cell_render h4 {    /*Use this for captions*/\n",
       "    font-family: 'Alegreya', serif;\n",
       "    font-size: 12pt;\n",
       "    text-align: center;\n",
       "    margin-left:50px;\n",
       "    margin-top: 0.5em;\n",
       "    margin-bottom: 2em;\n",
       "    font-style: regular;\n",
       "}\n",
       "\n",
       ".text_cell_render h5 {  /*Use this for small titles*/\n",
       "    font-family: 'Alegreya', sans-serif;\n",
       "    font-weight: 400;\n",
       "    font-size: 16pt;\n",
       "    color: rgb(240, 129, 15);\n",
       "    font-style: italic;\n",
       "    margin-top: 0.8em;\n",
       "    margin-bottom: 0px\n",
       "}\n",
       "\n",
       ".text_cell_render h6 { /*use this for copyright note*/\n",
       "    font-family: 'PT Mono', sans-serif;\n",
       "    font-weight: 300;\n",
       "    font-size: 9pt;\n",
       "    line-height: 100%;\n",
       "    color: grey;\n",
       "    margin-bottom: 1px;\n",
       "    margin-top: 1px;\n",
       "}\n",
       "\n",
       ".CodeMirror{\n",
       "        font-family: \"PT Mono\";\n",
       "        font-size: 90%;\n",
       "}\n",
       "\n",
       "</style>\n",
       "<script>\n",
       "    MathJax.Hub.Config({\n",
       "                        TeX: {\n",
       "                           extensions: [\"AMSmath.js\"],\n",
       "                           equationNumbers: { autoNumber: \"AMS\", useLabelIds: true}\n",
       "                           },\n",
       "                tex2jax: {\n",
       "                    inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n",
       "                    displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ]\n",
       "                },\n",
       "                displayAlign: 'center', // Change this to 'center' to center equations.\n",
       "                \"HTML-CSS\": {\n",
       "                    styles: {'.MathJax_Display': {\"margin\": 4}}\n",
       "                }\n",
       "        });\n",
       "</script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.core.display import HTML\n",
    "css_file = \"style.css\"\n",
    "HTML(open(css_file, \"r\").read())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}