{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "div.output_area, .ui-wrapper {\n",
       "  margin-left: auto !important;\n",
       "  margin-right: auto !important;\n",
       "}\n",
       "</style>\n",
       "\n",
       "\n",
       "<style>\n",
       "\n",
       "h1.bigtitle {\n",
       "    margin: 4cm 1cm 4cm 1cm;\n",
       "    font-size: 300%;\n",
       "}\n",
       "\n",
       "h1.title { \n",
       "    font-size: 250%;\n",
       "}\n",
       "\n",
       ".rendered_html h1 {\n",
       "    margin: 0.25em 0em 0.5em;\n",
       "    color: #015C9C;\n",
       "    text-align: center;\n",
       "    line-height: 1.2; \n",
       "    page-break-before: always;\n",
       "}\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Custom styling, borrowed from https://github.com/ellisonbg/talk-2013-scipy\n",
    "\n",
    "from IPython import display\n",
    "\n",
    "\n",
    "# Make plots centered. H/T to http://stackoverflow.com/a/27168595/1068170\n",
    "STYLE = \"\"\"\\\n",
    "<style>\n",
    "div.output_area, .ui-wrapper {\n",
    "  margin-left: auto !important;\n",
    "  margin-right: auto !important;\n",
    "}\n",
    "</style>\n",
    "\"\"\"\n",
    "\n",
    "\n",
    "SLIDES_STYLE = \"\"\"\n",
    "<style>\n",
    "\n",
    "h1.bigtitle {\n",
    "    margin: 4cm 1cm 4cm 1cm;\n",
    "    font-size: 300%;\n",
    "}\n",
    "\n",
    "h1.title { \n",
    "    font-size: 250%;\n",
    "}\n",
    "\n",
    ".rendered_html h1 {\n",
    "    margin: 0.25em 0em 0.5em;\n",
    "    color: #015C9C;\n",
    "    text-align: center;\n",
    "    line-height: 1.2; \n",
    "    page-break-before: always;\n",
    "}\n",
    "</style>\n",
    "\"\"\"\n",
    "\n",
    "STYLE = STYLE + '\\n' + SLIDES_STYLE\n",
    "\n",
    "display.display(display.HTML(STYLE))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$u_t + \\left[f(u)\\right]_x = 0$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1 class=\"bigtitle\">Finite Volume</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$w(x, t) = \\frac{1}{\\Delta x} \\int_{x - \\Delta x / 2}^{x + \\Delta x / 2} u(s, t) \\, ds$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\begin{align*}\n",
    "w_t &= \\frac{1}{\\Delta x} \\int_{x - \\Delta x / 2}^{x + \\Delta x / 2} u_t \\, ds \\\\\n",
    "&= \\frac{1}{\\Delta x} \\int_{x - \\Delta x / 2}^{x + \\Delta x / 2} -\\left[f(u)\\right]_s \\, ds \\\\\n",
    "&= -\\frac{f\\left(u\\left(x + \\Delta x / 2, t\\right)\\right) - f\\left(u\\left(x - \\Delta x / 2, t\\right)\\right)}{\\Delta x}\n",
    "\\end{align*}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\begin{align*}\n",
    "u_j^n &= u\\left(j \\Delta x, n \\Delta t\\right) \\\\\n",
    "w_j^n &= w\\left(j \\Delta x, n \\Delta t\\right)\n",
    "\\end{align*}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\frac{d}{dt} w_j^n = -\\frac{1}{\\Delta x}\\left(f\\left(u_{j + \\frac{1}{2}}\\right) - f\\left(u_{j - \\frac{1}{2}}\\right)\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\left\\{w_j^n\\right\\}_j \\overset{?}{\\longrightarrow} \\left\\{u_{j + \\frac{1}{2}}^n\\right\\}_j$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "> WENO interpolation ... [is] used ... to transfer information from one domain to another in a high order, nonoscillatory fashion\n",
    "\n",
    "![WENO Transfer Quote](weno_transfer_quote.png \"WENO Paper Quote\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1 class=\"bigtitle\">Finite Difference</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\frac{d}{dt} u_j^n = -\\frac{1}{\\Delta x}\\left(\\widehat{f}_{j + \\frac{1}{2}} - \\widehat{f}_{j - \\frac{1}{2}}\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Define $h(x)$ implicitly via\n",
    "$$\\frac{1}{\\Delta x} \\int_{x - \\Delta x / 2}^{x + \\Delta x / 2} h(s) \\, ds = f(u(x))$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\frac{1}{\\Delta x} \\int_{x - \\Delta x / 2}^{x + \\Delta x / 2} h(s) \\, ds = f(u(x))$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$\\Longrightarrow \\frac{1}{\\Delta x} \\left(h\\left(x_{j + \\frac{1}{2}}\\right) -h\\left(x_{j - \\frac{1}{2}}\\right)\\right) = \\left[f(u)\\right]_x$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$\\Longrightarrow \\frac{1}{\\Delta x} \\left(h\\left(x_{j + \\frac{1}{2}}\\right) -h\\left(x_{j - \\frac{1}{2}}\\right)\\right) \\approx \\frac{1}{\\Delta x}\\left(\\widehat{f}_{j + \\frac{1}{2}} - \\widehat{f}_{j - \\frac{1}{2}}\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\widehat{f}_{j + \\frac{1}{2}} = h\\left(x_{j + \\frac{1}{2}}\\right) = h_{j + \\frac{1}{2}}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\overline{h}_j^n = \\frac{1}{\\Delta x} \\int_{x - \\Delta x / 2}^{x + \\Delta x / 2} h(s) \\, ds = f\\left(u_j^n\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$\\left\\{\\overline{h}_j^n\\right\\}_j \\overset{?}{\\longrightarrow} \\left\\{h_{j + \\frac{1}{2}}^n\\right\\}_j$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import seaborn\n",
    "import sympy\n",
    "\n",
    "import weno_computations\n",
    "\n",
    "seaborn.set_palette('husl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
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Na/mAAAAApagVaKdasmRJbNiwIbq7u89428HB4+O5q/NWs9lV7O4RZe9v9zJ3jyh7/2az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\naAAAAEkINAAAgCT+D18c+l8aBnLpAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2ab9c5a790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Sx9ixYwf93fvff0be//4tr1l517vevVPr2da6tzZhQndeemnFsF53qNczjdQ4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\nAQAAlMT/D2yJ4fr3QajmAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2ab9c5a5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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V1emOO+7QmDFjEl0bEsVxFNheIF/ZccJZEliWpUDhJwrWBaW8C9wup1VGjbpKaWlp+vvf\nV2vjxg361a9+I18KjqHc3G4aO3aclixZrKqqqjMmy0hV7bUvAAC8LK6AtmLFCuXk5Ojhhx/W8ePH\nNXHiRAKaqWxbgQ/y5TtRQThLJp9PgU/2KZSVKeV2c7uauOXk5Gr8+AmSpK9+9VqXq2md6667we0S\n2kR77QsAAK+KK6CNHz9e48bV30Bu27YCAeYaMZJtK7Blh3wVlUwI4gafT/auvfKVVcg+t5/b1QAA\nACAFxJWsOnToIEmqqKjQnXfeqbvuuiuhRSEBQiEFtu6Qr6KKcOamz56VFnKk0HmENAAAADQv7lNf\nBw4c0A9/+ENNnjxZ1113XSJrQmvZtgJb8wlnkr54x61hX9/2u78kb3m/T/7ig3Is6dKbrw+7/KZN\n28O+Pnz44FYtH2k5AAAAmCmugFZaWqrvfe97mjNnjq644oqo18vL8+7sYsnq3bFthd79QLZdJ6tT\nRlK2GY2OHdNd2a4vQkCNVE9bLN/4/0fL5AuFpLQzf+0ijQ+fL/z7R7u8279zbm/fbV7vH9Hz+ljx\ncv/07l1e7t/LvUfDchzHiXWlefPmadWqVRo4cKAcx5FlWXryySeVnt78H+Ft/dBWUyXjgbWS6mdr\n3JYv37Fyo86cdeyYrqqqWrfLcMUZvdu2gv3Plt2vt3tFJUnSxr2hvNw/B97YeXWsSPyu0Ls3ebl/\nL/cuRXeMjOsM2uzZszV79ux4VkVbcRwFPtwp39ETzNZoMp9PgU/3KRjwy+79BberAQAAgGH4S76d\n8Bfuka+0jHCWCiyf/Ls+lXWw1O1KAAAAYBj+mm8HfHuK5D9QKvnZnanCsnwKFO6RdfS426UAAADA\nIPxFn+J8+w8pULRfijCZBMxlSUr7qFAqr3S7FAAAABiCgJbCrCNH5d+1V7LYjSnLdpS2vUCq8eYk\nKgAAAGiKv+xTVUWl0nbsEufNUp9VF1Tgg3wpFHK7FAAAALiMgJaKauvqz7rE/oQEmMiy5DtZrcCH\nhexTAAAAjyOgpRrbVmBbvqzaoNuVIJEsS76y4/Lt+tTtSgAAAOAiAlqK8efvkq/ypFEPokaC+H0K\nFB+Sb/8htysBAACASwhoKcS3d7/8h8sIZ+2Zzyf/rr2yjpe7XQkAAABcQEBLEdaRY/J/so9nnXmA\nJdXfj1bLzI4AAABew1/7qeBktdLyd8nizJlnWMGgAts/ZtIQAAAAjyGgmc6268+m2LbblSCZLEu+\n8kr5C/e4XQkAAACSiIBmOP/He+SrOul2GXCDzyf/gVJZB0vdrgQAAABJQkAzmG//IfkPljIpiJf5\nLKXt/ESqrHK7EgAAACQBAc1UlVUK7C5iUhBIjqO0j3ZymSsAAIAH8Ne/iWxbaR8WMkEEGlknq+Uv\n4H40AACA9o6AZiB/wR5Z1TVulwGTWJb8h0vlO1jidiUAAABoQwQ0w/gOHpb/MPedIQyfT4Gdn0gn\nq92uBAAAAG2EgGaSk9UK7Nwr+dgtiMCRAh9x+SsAAEB7RRIwheMo8NFO/vBGi3wVVfLt3ut2GQAA\nAGgDBDRD+Pbsk6+i0u0ykAp8Pvn3HZR19LjblQAAACDBCGgGsI6Xy7/vAJc2ImqWz6dA/m4pFHK7\nFAAAACQQicBttq1AwS5ZTAqCGFl1dfLn73a7DAAAACQQAc1l/sJPZFXXul0GUpFlyV9aJuvQEbcr\nAQAAQIIQ0FxkHTkq/0Gm1Ecr+HwK7PpUqqtzuxIAAAAkAAHNLaGQAoV7JB/hDK1jBYNc6ggAANBO\nENBc4v/4E1m1QbfLQHtgWfKXHZN1sNTtSgAAANBKBDQXWEeOyn+YSxuRQA2XOtZyqSMAAEAqI6Al\nWyikQOEnTKmPhLNCIfk/5lJHAACAVEZKSDJ/4aeyOMuBtmBZ8pceY1ZHAACAFEZASyLr2HH5D5dw\naSPajv+zSx15gDUAAEBKCrhdgGfYtgIffyJZZGK0LSsYVPrf31Fgb7F8pUdld89R7YhhCl50ntul\nAQAAoAUEtCTx7dkn62Q1956hzflKjyqt4PN70fwlZeqwfI1OSoQ0AAAAw8WVFhzH0dy5c3XLLbdo\n6tSpKioqSnRd7YpdXil/8UHCGZLCX3Qg7Ovp72xOciUAAACIVVyJYc2aNaqtrdXixYs1ffp0zZ8/\nP9F1tR+OI3tboSzuO0OSWFUnw77uKz2a5EoAAAAQq7gC2qZNmzRq1ChJ0pAhQ7R9+/aEFtWe+PYf\nknP0hNtlwEOcjh3Cvm53z0lyJQAAAIhVXPegVVRUKCsr6/M3CQRk27Z8hl7CN3z44LCvb9oUPlgm\nbPl3N8v/SbGU2fTH/MU7bg27/Lbf/SXs661dPtJyaJ9Cfc6Sr+DM56HVfvlSF6oBAABALOIKaJ07\nd1ZlZWXj19GGs7y8rBaXaQs+S1LwzGnHcw8dDL98hCnKY10+59BhKbezJKlTx8zPl/eH/1l16p4d\n/v1buXyk5ZLp1P69Jum9d8+WndVB9sefShWVsnp2V+CaK5R56YXJrUPu/c6bwuv9I3peHyte7p/e\nvcvL/Xu592hYjuM4sa60evVqrVu3TvPnz9eWLVu0cOFCPfHEEy2uV1JSHleRrWWVlCnto8LkTtJh\n26q75AI5OV2Ul5flWu8m8HL/9O7N3iVv98+BN3ZeHSsSvyv07k1e7t/LvUvRHSPjOoM2duxYrV+/\nXrfccoskMUnI6RxHobxcOTld3K4EAAAAQAqJK6BZlqWf/exnia6l/fD5FDq3v9tVAAAAAEgxZs7q\nkcpsW8G+vaT0NLcrAQAAAJBiCGgJ5nTsILvPWW6XAQAAACAFEdASybYVPKefxEOpAQAAAMSBgJYo\njqNQblc5uUwMAgAAACA+BLREsSyFzu3ndhUAAAAAUhgBLREcR8Gz8qQO3n0YMwAAAIDWI6AlgBMI\nyO5/tttlAAAAAEhxBLTWCoUU6tdLCsT1SDkAAAAAaERAayW7cyfZvXq6XQYAAACAdoCA1hp2SKGB\nfZhWHwAAAEBCENBawc7pKie3q9tlAAAAAGgnCGhxcmxbwXP6ul0GAAAAgHaEgBYPx5Hdo5vUqaPb\nlQAAAABoRwho8bAshTh7BgAAACDBCGixchwFz+ohpae7XQkAAACAdoaAFqP6h1L3drsMAAAAAO0Q\nAS0Wtq3Q2V/godQAAAAA2gQBLQZORrrsPme5XQYAAACAdoqAFq1QSKE+Z/FQagAAAABthoAWJadT\nR9m9erpdBgAAAIB2jIAWjZCtYN/enD0DAAAA0KYIaFGwszrJ6ZHrdhkAAAAA2jkCWktCtkL9OHsG\nAAAAoO0R0Fpgd+ksp3uO22UAAAAA8AACWnPskEL9zna7CgAAAAAeQUBrht2li5zcLm6XAQAAAMAj\nCGiR2LZC/Xu5XQUAAAAADyGgRWB3zZbTlbNnAAAAAJKHgBZOw8yNAAAAAJBEBLQw7JxsOV2z3S4D\nAAAAgMcQ0E7H2TMAAAAALiGgnYazZwAAAADcQkA7lR1SqB8zNwIAAABwRyCelSoqKjRjxgxVVlaq\nrq5O9957r4YOHZro2pLO7sLMjQAAAADcE1dAe/rppzVixAhNnTpVe/bs0fTp07V06dJE15ZcIVuh\nvpw9AwAAAOCeuALa7bffrvT0dElSMBhURkZGQotyg53dWU5uV7fLAAAAAOBhLQa0JUuWaNGiRU1e\nmz9/vgYPHqySkhLNnDlTs2fPbrMCkyIUUqjvWW5XAQAAAMDjLMdxnHhWLCgo0IwZM3TPPfdo5MiR\nia4roeyDJQq+v0OWL/ycKFbnjvJfeaksy0pyZQAAAADwubgucdy5c6d+9KMf6ZFHHtGgQYOiXq+k\npDyezbWaVValtKpaKVxAC4VU17uXnNKKNtt+Xl6Wa72bwMv907s3e5e83X9eXpbbJaQcr44Vid8V\nevcmL/fv5d6l6I6RcQW0BQsWqLa2VvPmzZPjOMrOztajjz4az1u5zunYQU7P7m6XAQAAAADxBbSF\nCxcmuo42d7SyXDlZp02hb9sK9e4pxXhp4+7du1RUtFf5+R9pypRp6tixUwIrddexY8fUtWv7nizl\n6NGjysnJSdr2GC9mSvQ4OH0/S+37LFIq73sAAEzmiQdVv7J2tfaWHj7jdScjXXavnjG/37p1a3Tx\nxYN18cVf1Ntvv5WIEo1RWlqiv/3tr26X0WZWrVqpoqJPk7pNxot52mIctOf9HE6q7nsAAEznv//+\n++9P1saqqmqTtalG27Zt1b49e3TtwAsbz5S9uOEtVdfUKu+LF8vpmq2VK5fr44/z9fTTT6pfv/7q\n1q1bs+85bNhl6tixk7ZseV9nn91HPXt+odnlO3XKiNj78uVLVVNTrS984fNZJGOtJ17htp2b201F\nRXt18OAB9e3bPyHbaa7/ZNq2bav27SvSV796bdTrtHb/dOqUoUGDvhjTeImkue3+9rcLNGDAQHXq\n1Dmu925JuJ+D1Px4MWW/ny7cOEjE7+HpnwsDB/aLq//Vq1epuLhYK1YsVTAYVN++/SRJ+/cXa/Hi\nP+vEiePavXuXBg48J+b3bk6kfiPV09K+R2xM/F1JFlM/K5KB3r3Zu+Tt/r3cuxTdMbJdn0ELBoP6\n05/+qG9PuFGSVFNXp7/98w0t27Bejs+S3ecsvfvuP3XRRRdrwoSJuu66CfrFL+ZG9d4nT55UVVWl\nLrlkaLPL7d69M+zrNTU1euGF5/TSS8t06kSa8dYTi0jbbjBu3PV65ZWVqq6uTvi23dIwFr71rUlR\nLZ/o/RPteImkue3u3Fmo9evflm3HNSFrxDEqtTxWpNQaL6ePAzf2c3M/7+LifVq06Cl95Sujdfnl\nV+jpp38vSXIcR/PnP6DbbvuOhgy5VK+88lJU9US77Uj9RqqnQSrtewAAUkW7DmivvrpSV101Rr7P\nZm/MSEvTt0eM1jk9z1Iot4vk86moaK+WL18qSTr77L46dOhAVO/9r3/9UzfffJuKi/c1u9wbb6wN\n+3pGRoa++c2bz/hX8HjriUWkbZ9qwoT/o+efbz+XL50+FlqS6P0T7XiJJNJ2g8GgDh48oB49esT1\nvlLkMSpFN1ak1BkvZ3wmuLCfm/t59+59thYufFKSVFj4sUaO/IokafPmTcrKylbHjh2Vm9tNDz74\n66jqiXbbkfqNVM+pUmXfAwCQKuKaJCRVvPLKSi1Y8L9SeVXTb1hW48yN3/jGt3Ty5ElJ0gcfbNGX\nvvTlxsXeeOPvsixLBQX5GjjwHL333r90331ztGzZEq1Zs1rLly/VrbdOVe/eZ0esIdZnq8VSz4YN\n72rWrMSfYZOkL33py/rDH57QlCm3t8n7J1vjWGilWMfLggW/jGm8xLrd9evf1MiRV+m55/7cZPlY\nxkoinv+XKuMl2nGQiM+FoUMvDPveLf28O3XqrLff/of27y/WXXfdLUkqKMhXXV2t/vnPt1VaWqI+\nffrq0kuHx/yZEGnbzfUbrp5Tpcq+BwAgVbTbgHbgwH5lZnZQZmZm04DmOHIyMqRAfet+v1+dO3dW\neXm51q1bo7lz50mSPvlkj4YMGaaMjAw9//xiTZ36XXXpUj8L5MSJN2nixJuiqiPW54DHU09b8Pv9\n6t27t3bs+FAXXnhxVOvU1taquHifBgwY2GZ1xaPJWGilth4vsWx3z57d6t27j/x+f5NlYx0rcT6r\n/oz6TB8vsYyDttzPLf28A4GARo68SjU1tZoz5149+OAC2XZI1dXVGjFipGzb1rRpk/Tznz8U82dC\npG1H6jdSPaevG+u+BwAAkSU1oI0adXmL/3rsOI4sy9Kbb25o1bY2btygQYMuOPP9JTmdOzZ5zbZt\nPfPMH/TTnz7QOO12//4DJNXfm3HppcOVmZmpyy+/osXt7t9frLffflOWZclxHH300XY988wzKi+v\nls9naeLEmxQINP9jj6ce27b14ovPh70PqVev3rryylEt1n66QYMu1MaN70X9R1dZ2RGtW7dGAwb8\nR7PLJXMcSOHHQmt+XokaL7HWcPp23313vSSpsLBAZWVH9MYbazR+/IQWawk3Rp9/frEcx4l6jIZj\n+niJ9JkQSaL2c7w/7/PPH6T775+lY8eOqUePnurRo37GWZ/Pp4qKCuXmdlNWVlaztcSy7XD9Rqrn\n9On1Y91wzMATAAAaX0lEQVT3AAAgsqQGtLfeei9p2yoo2KHLLvu3M163c7tKgaZnHJYte0GTJk1W\nbm43rV79qq69dpx27dqpjIwMvffev3TFFfWX+2zcuCHse56qV6/e+va3P5+IorKyQlOnTo3pienx\n1OPz+fTNb94c9TaiccEFF+nFF5fEtE40l8slcxxI4cdCa35eseyf8eO/GvF9Yq3h9O2OHz+h8Xuv\nvPKSRo++Rl26dG1xrIQbo9/61i0x/QzCMX28RPpMiCRRnwux/LxXrHhRGza8q1/84iEdOVKq7t3z\nlJ2dreHDL2+cGCQUCikrK1uHDx/S8ePHmq0llm2H6zdSPaeLZ98DAIDw2u0ljocPHzpzOvOQrRe2\nvacdOz6U4ziybVvHjx/TY4/9Vn/4wxOS6v8l+Nprx+ndd9crIyNDX/jCWdq1a6eOHTumUaNGx1xH\nc5czvfjikia1DBt2mdatW6Pf/e5/26ye5rZ9ury8HiopOfP5cakm7FiIgpv753SRtivVT4NeVLRX\nzz//V02ePC3mWlq65C6asSKZP14ijYNk7+fmft6jRl2ltLQ0/f3vq7Vx4wb96le/kc/nU25uN40d\nO05LlixWVVWV7r57Vly1RNp2pH5HjvxK2HpOZ/q+BwAglSQ9oL3yyks6duyYioo+1T33/ESStG9f\nkWbNmqFnnnkuYds5ceLEGc+EsrtkaeLo2zRx0m1NXr/66mvOWP+2276TkDrS09Mjfu/GG2/SjTc2\nvWfl6quvadN6mtv26Tp3ztKJE8djet9o72dK1jiQwo+FaLi5f04XabuSdO2143XttePjrqW5MSpF\nN1Yk88dLpHGQ7P3c3M87Jye38czo6c/ru+66G5p8PXjwFxO27Uj95uZ2i1jPqeLZ9wAAILykBrTd\nu3cpPT1do0Zdpe9///bGP7TeeWd9zGc4Vq5cLsnR+vVv67vf/Q+dd975Tb5fXn5CnTp1+vwF21bo\n7J6tbSFmkydPS/o2EyUrK0snTpwI+72amho98sgvFQqFGl+rqqrS/v37dPBg0ynJb731ZvXv//m9\nP4kcBw2WL1+q/v0HaMiQS8/43hljAU0kaowmarxcd90NGjp0WOPXsYyXP/3pj+rTp68KCvI1btz1\njQ9VlswZB25+JrTVtpvb9wAAIDZJDWhVVZUaPfqrWrToqSYTIGzZskmXXhr+sqlwGh6qOnDguerS\npat+8Yu5WrSo6XN4LMvX5F/nnY4d5HTPbX0THhIKheT3h39uWEZGRuMfyg0OHjygVatW6vbb/73J\n63l5WU3uwUvUOJDq//BfuXKZVq16WT/84Y/CLnP6WEDbSNR4OV2042Xbtq0qKtqryZOn6aKLBuvX\nv36wyYyDjIO209y+BwAAsUlqQBs8+BJJ0qpVK3XffXMaX9+6dXNMz9ApKtqrd955W3fdNTPiQ2Sz\ns7NVWVmp7t3zJEmhs3po1Ff+LSHPfGqPws2CV1VVqaysxE/ln6hxIH3+oOGCgvyIy5w+FqToZgZE\nZCaOl/ff36gLL7xIUv09UTt2fNTkfRgHiZHMfQ8AgBcl/R60vXs/0bFjRxsvYdq5s1DBYEiDBl2o\nDz7YoksuGdriezT3UNUG2dnZqqiokCQ5XbPkdOua9NkDG5x+BilVVFZWhp2xLRESMQ6idepYaJCs\nsZCq+z4ebo+XsrIjTS559Pv9Ki8vV1ZWlqTkjwP2PQAAiEfSr0mpra1TZmZm48N11659vfHZRNu2\nbY3qPU5/qOqPfjTzjGV69eqt4uJ99V+kpUlhZh5LppUrl2vlymW6774ZKiz8uMn3fvvbBTp8+JBL\nlUVWXLxPZ53Vq03eOxHjIFpNxoKhli9fqq1bNzd+3dx4MZXb48W2Hfl8nz9CIxQKNrnszuRx0NL+\nNvUzokFb7nsAALwm6WfQzj33PF111Rj98Y9PqnPnzrrkkqHKz9+hRYue0g03TIz64b0tPVT1ggsu\nVkHBjsapyN305ptvRrxnbufOQq1f/7a+9a1bXa7yTPn5H+mCCy6KevlAIE0ZGRlRLdvSOJAS9/Bt\nk8bC6cLdQxfNPZYmcnu85OXlqbr6ZOM6tu2oY8fPJwUxdRy0tL9N/oxoEOu+BwAAkbnyHLS7757V\n5OsrrhjR5OtoHt4b7qGqp7r88i9pxYqlrS82AT755BPl5xeecc9cMBjUwYMH1KNHD5crDK+gIF/f\n//7/jXr57t2769Zbp0a9fEvjIFEP3zZpLJwu3D100dxjaSK3x8tll/2bVq16WVL9z/CCCy5s8n1T\nx0Fz+9v0z4gGse57AAAQWUo+qLq5h/Y2yMnJUWZmpk6cOK7sbHdvXr/tttu0d2/9Q1xPvWdu/fo3\nNXLkVXruuT+7WV5YNTU1OnbsqPr16+92KS1q6UHKJo2FaERzj6VpTBgvF100WG+99Q+9/vqrKiz8\nWP/939ObfN/UcdDc/jb5M6KBCfseAID2JCUDWnMP7T3VxIk36eWXX9KkSZOTUFVkp98zN3fuPO3Z\ns1u9e/dpvKfGNH//+2pdd90Et8uISjQPUjZlLEQj3HgxnSnjpeEsztix4S9jNHEcRNrfpn9GNDBl\n3wMA0F606wfXjBz5FX300XZVV1e7XcoZ98zl53+kwsICrVq1UmVlR/TGG2t0/Pgxt8uUVH9Z1Vtv\nvaHrrvu626UkjEljIRot3WNpklQaL6aOg3D72+TPiAaptO8BAEgV7TqgSdIdd/xQixY95XYZjffM\ndevWXatXv6rx4yc0/peb202jR1+jLl26ul2mJOkvf3lG06b9u3wuz3yZaKaMhWicPl5MlmrjxcRx\nEG5/m/wZ0SDV9j0AAKmg3R9Ve/c+W1/60pf1j3+sc62GV199Vb/73f9q6tRbNGHCWL322iuN31u9\nepWKivbq+ef/qmPH3P/X8ffe+5f69x/YOIV5e2LCWAin4R66l19eofff36h169boscd+G3a8mCYV\nx4tp46DhntpI+9u0z4gGqbjvAQBIBZbjOGfOYd5GvPLQ1tN56YG14Xi5f3r3Zu+St/vPy8tyu4SU\n49WxIvG7Qu/e5OX+vdy7FN0xst2fQQMAAACAVEFAAwAAAABDENAAAAAAwBAENAAAAAAwBAENAAAA\nAAxBQAMAAAAAQxDQAAAAAMAQBDQAAAAAMAQBDQAAAAAM0aqAtmvXLl122WWqra1NVD0AAAAA4Flx\nB7SKigo9/PDDysjISGQ9AAAAAOBZcQe0OXPm6Mc//rEyMzMTWQ8AAAAAeFagpQWWLFmiRYsWNXmt\nV69euv766zVo0CA5jtNmxQEAAACAl1hOHAnra1/7mnr27CnHcbR161YNGTJEzz77bFvUBwAAAACe\nEVdAO9WYMWP02muvKS0tLVE1AQAAAIAntXqafcuyuMwRAAAAABKg1WfQAAAAAACJwYOqAQAAAMAQ\nBDQAAAAAMAQBDQAAAAAMQUADAAAAAEMQ0AAAAADAEAQ0AAAAADAEAQ0AAAAADEFAAwAAAABDENAA\nAAAAwBAENAAAAAAwBAENAAAAAAxBQAMAAAAAQxDQAAAAAMAQBDQAAAAAMAQBDQAAAAAMQUADAAAA\nAEMQ0AAAAADAEAQ0AAAAADA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bt8+5+eab3S4j6fbv3+984xvfcJYuXep2Ka4qLS11rr76\naufkyZNul5JSvHiM9Prx0XE4RnqNV4+PjsMx0nGiOz4m5Z8rHn/8cS1btkyS1LFjR/n9/mRs1hg7\nd+7Uj370I/3qV7/SyJEj3S4HbWzYsGH6xz/+IUnasmWLzj//fJcrco/z2WVbXlFaWqrvfe97uvvu\nu3XjjTe6XU7SLVu2TI8//rgkKSMjQz6fzzP/Kt4aXj5Gcnz0Ho6R9bx2fJS8fYyM9fiYlIs/b7rp\nJt1zzz164YUX5DiO524IXbBggWprazVv3jw5jqPs7Gw9+uijbpeFNjJ27FitX79et9xyiyR5bryf\nyrIst0tIqscff1wnTpzQwoUL9eijj8qyLD355JON99i0d+PGjdO9996ryZMnKxgMavbs2Z7pvTW8\nfIzk+Og9HCPree34KHn7GBnr8dFyvBjhAQAAAMBAXHsCAAAAAIYgoAEAAACAIQhoAAAAAGAIAhoA\nAAAAGIKABgAAAACGIKABAAAAgCEIaAAAAABgCAIaAAAAABji/wPoXCrvIRO6+QAAAABJRU5ErkJg\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a959edf10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xEklz2925s1Dr178t245rQtaIY1RqeaxIqTVeTh8Hbuzn5n7excX7tGjRU/rK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\nAIYgoAEAAACAIQhoAAAAAGA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+Okm2a9cu55prrkn2Zl2Xn5/vTJgwwXnrrbfcLsUV//rX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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a959c9dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AAAAwAkLhLBVOvVLiMkckCSMpmVxXkZOnSZziBgAACIz0rLEqnHypPMU99x5w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\nv6olS5bouuuuS3ZdAAAAABA4CQW0qqo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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a95c8a310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AAMTAsmy11m6VZacrf/Q5XpcDn4grLbiuq0WLFumqq67SwoULVVlZmei6RhSn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\nCGgAAAAAYAgCGgAAAAAYgoAGAAAAAIY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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a95c8a090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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rrW6rLDtThWPO8boc+ERCacF1XS1atEhXXXWVFi5cqKqqqmTXNaI4za0K7DtI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\nIKABAAAAgCEIaAAAAABgCAIaAAAAABi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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2ab9c5a610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BTyRVLTiOoyVLluj666/XLbfcovr6+lTnyip2Z5cCew9QnCEtAvX7Y76e++76\nNCcBACDzGRNQV9NGdTVtcTsKfCKpiuG1115TX1+fnnzySf3TP/2T7r///lTnyh6OI3tzjQzPnSFN\nTLg75utWU2uakwAAkB2MsdRxaI3CbbVuR4EPJFWgrVu3TgsWLJAkzZs3T1u28BeF4Vj7Dspp7XA7\nBnzEKSyI+bo9aUKakwAAkD2MjDr2vaWezga3oyDLJfUMWigUUklJyUcfEgzKtm1ZHr2Fb/78uTFf\nX7cudmGZsuVXr1dg114pf+jXfNbXboy5/OZf/CHm62NdfrjlkJ2ix0+VVX3sfGh9Hz/XhTQAAGSX\ntobXVTHrKuUWVLodBVkqqQKtuLhYXV1dg/+OtzirrCwZdZnxYBlJkWOHHa84eCD28sMMUZ7o8hMO\nHpIqiiVJRYX5Hy0fiP1dFU0qjf35Y1x+uOXS6cj2+03a2z6pVHZJgeztu6VQl8yUSQpefqHyzz09\nvTnk3u+8V/i9/Yif3/uKW+0vCE6S1TfZlXUfVpbn6updlcltj7S+o0D/FFmB3KTef6hr9GXGjeOo\nfOo5ys0vdy2C3/d5ozFOEpM7vPrqq1q5cqXuv/9+bdiwQQ899JB++ctfjvq+xsbOpEKOlWlsUc7W\nmvQO0mHb6j/7NDkTylRZWeJa273Az+2n7f5su+Tv9nPgTZxf+4rE7wptz1xte99Ud+t2GSuQ8HsL\ni/IU7uodh1Sjc+yoymderoLSWa6sPxu2/VjEc4xM6grapz/9aa1atUrXX3+9JDFIyNEcR9HKCjkT\nytxOAgAAgHFQNm2Bov0h9XXtl2GeW6RQUgWaMUY//OEPU50le1iWoifPcjsFAAAAxokxRhOOv0LN\ndc8r0tvBiN1IGcr9VLNtRWZOk3Jz3E4CAACAcWQFgqqYdY0CQf8+a4/Uo0BLMaewQPbxU92OAQAA\ngDQIBAtUPvMKidsckSL0pFSybUVOOkHiEjcAAIBv5BZMUvmMT8pRwmPvAcegQEsVx1G0olxOBQOD\nAAAA+E1+yUyVTv4bOU7s6ZeAeFGgpYoxip58gtspAAAA4JKiSXNVOOE0OTZFGpJHgZYKjqPI1Eqp\ngAdEAQAA/Kx06sXKLZ6qJKYaBiRRoKWEEwzKnjXD7RgAAABwmTFG5cd/WoHcIrejIENRoI1VNKro\nCdOkYFJTygEAACDLBAK5qpj5GRkr4HYUZCAKtDGyi4tkT5vidgwAAAB4SDCvXGXTF8pxbLejIMNQ\noI2FHVXHj3yPAAAgAElEQVT0xOMZVh8AAADHyC+ZqZLJ58uxKdIQPwq0MbAnlMupKHc7BgAAADyq\nuHKe8stmcSUNcaNAS5Jj24qcNNPtGAAAAPC48hkLFcybwMiOiAsFWjIcR/bkiVJRodtJAAAA4HHG\nBDThhCtkArluR0EGoEBLhjGKcvUMAAAAcQrmFKt8+kI54ioaRkaBlijHUWTqZCmXv4AAAAAgfvkl\nM1RSOV+OHXE7CjyMybsSNDAp9XS3YwAAACBJ8+fPjfn6unVbxn35oklnKxpsVzhcI2MGrpVc+aUf\nxlz+laeWxHx9bMs7enfV5TGXgzdwBS0Rtq3ojOOYlBoAAABJMcZo8klXKJBb4nYUeBSVRgKcvFzZ\nx091OwYAAADGYLgrX+laPhDI0YTjL1fzzhckOcNe+RrOWJZ37GhC70X6cQUtXtGoosdPZVJqAAAA\njFlOfoVKp14kx6FgwlAUaHFyigplT5vidgwAAABkicIJp6qg/FQmscYQFGjxiNqKzJzO1TMAAACk\nVNm0SxTMm+B2DHgIBVoc7JIiOZMr3I4BAACALGOMpQnHXy5jAm5HgUdQoI0mait6AlfPAAAAMD6C\neaUqnXYxtzpCEgXaqOyyYjmTuOwMAACA8VNQdpIKJ/A8GijQRmZHFT1hhtspAAAA4AOlUy9WTl65\n2zHgMgq0EdhlZXIqytyOAQAAAB8wxlL58Z+SDKfofsbWH45tKzprmtspAAAA4CPBvHKVHnch86P5\nGAXaMOzyUjnlXD0DAABAehVOmKP80hN5Hs2nKNBiOTxyIwAAAOCCsmmfUCCn2O0YcAEFWgz2hFI5\n5aVuxwAAAIBPWYGgymd80u0YcAEF2tG4egYAAAAPyC2crKLKc3gezWco0I7C1TMAAAB4RfGkc5Rb\neJwcx3E7CtKEAu1IdlTRExi5EQAAAN5gjFH5jMtkrBy3oyBNkirQQqGQvva1r+nmm2/W9ddfrw0b\nNqQ6lyvsMkZuBAAAgLcEcgpVNu0ibnX0iaQKtN/+9re66KKL9Pjjj+v+++/Xvffem+pc6Re1FZ3J\n1TMAAAB4T0HZScovO4mh930gmMybbrvtNuXm5kqSIpGI8vLyUhrKDXZpsZyKcrdjAAAAADGVTV2g\nvvBBOZFut6NgHI1aoD3zzDNaunTpkNfuv/9+zZ07V42Njbrzzjt19913j1vAtIhGFZ051e0UAAAA\nwLCsQFDl0y5Vy+6XZQxDSWQr4yQ5JEx1dbW+/e1v67vf/a4uueSSVOdKKftAoyLvb5OxYndkU1yo\nwMXnyhiT5mQAAABAYpr2rFLbgY0yViDh99p2RNNOuVpFE2aPQzKkQlK3ONbW1uqb3/ymfvazn2nO\nnDlxv6+xsTOZ1Y2ZaQkrJ9wnxSrQolH1T58mpyk0buuvrCxxre1e4Of203Z/tl3yd/srK0vcjpBx\n/NpXJH5XaLs/jbX9Tv5c9UVrFO3uSPy9dlTNLSGFI+58/2z70Y+RSRVoDz74oPr6+vTjH/9YjuOo\ntLRU//mf/5nMR7nOKSyQM2WS2zEAAACAuBhjqWzGQjXvfEHc/5V9kirQHnrooVTnGHetXZ2aUHLU\nEPq2rej0KVKCtzbu3LlD9fV7VFW1VTfffKsKC4tSmNRdbW1tKi/P7sFSWltbNWHChLStj/7iTanu\nB0dvZym7ryJl8rYHgGyQmz9RxZPOUahxnYxJ/FZHeJcvni58+fVXtafp0DGvO3m5sqdNSfjzVq58\nTWeeOVdnnnmW3n77rVRE9Iympkb993//l9sxxs2KFctVX787reukv3jPePSDbN7OsWTqtgeAbFJc\neY5yCirdjoEUC/zgBz/4QbpWFg73pWtVgzZv3qiGujpdceLpg1fKnlvzlnp6+1R51plyyku1fPky\nbd9epd/+9tc64YRZmjhx4oifed5556uwsEgbNryvGTOO15Qpx424fFFR3rBtX7bsWfX29ui44z4a\nRTLRPMmKte6Kiomqr9+jAwf2a+bMWSlZz0jtT6fNmzeqoaFen/rUFXG/Z6zbp6goT3PmnJVQfxnO\nSOv9+c8f1OzZJ6qoqDipzx5NrO9BGrm/eGW7Hy1WP0jF7+HR+4UTTzwhqfa/+uoK7d27Vy+88Kwi\nkYhmzjxBkrRv3149+eQT6uho186dO3TiiScl/NkjGa69w+UZbdsjMV78XUkXr+4r0oG2+7PtUura\nb4xRbuFUhVur4n+T4yi/7ETl5LlzFwTbfvRjZFZfQYtEIvr973+nL177OUlSb3+//vudN/T8mlVy\nLCP7+KlavfodnXHGmbr22kW6+uprdd99S+L67O7uboXDXTr77HNGXG7nztqYr/f29uqPf3xKL774\nvI4cSDPZPIkYbt2HXXnlNXr55eXq6elJ+brdcrgvfOELN8S1fKq3T7z9ZTgjrbe2tkarVr0t205q\nQNZh+6g0el+RMqu/HN0P3NjOI33fe/c2aOnSR/WJTyzUBRdcqN/+9leSJMdxdP/99+qmm/5e8+ad\nq5dffjGuPPGue7j2DpfnsEza9gCQrYJ5ZSqefJ4cJ+p2FKRIVhdor7yyXJdeepmsD0dvzMvJ0Rcv\nWqiTpkxVtKJMsizV1+/RsmXPSpJmzJipgwf3x/XZf/3rO/rSl27S3r0NIy73xhuvx3w9Ly9Pn//8\nl475K3iyeRIx3LqPdO21/4+efjp7bl86ui+MJtXbJ97+Mpzh1huJRHTgwH5Nnjw5qc+Vhu+jUnx9\nRcqc/nLMPsGF7TzS9z19+gw99NCvJUk1Ndt1ySWfkCStX79OJSWlKiwsVEXFRP3kJz+NK0+86x6u\nvcPlOVKmbHsAyGZFE89STkHij+3Am5IaJCRTvPzycj344H9IneGhPzBmcOTGv/u7L6i7e2A29k2b\nNuhjH/v44GJvvPEXGWNUXV2lE088Se+991fdddc9ev75Z/Taa69q2bJndeONt2j69BnDZkh0brVE\n8qxZs1rf+17qr7BJ0sc+9nH95je/1M033zYun59ug31hjBLtLw8++G8J9ZdE17tq1Zu65JJL9dRT\nTwxZPpG+kor5/zKlv8TbD1KxXzjnnNNjfvZo33dRUbHefvt/tG/fXt1xx3ckSdXVVerv79M777yt\npqZGHX/8TJ177vyE9wnDrXuk9sbKc6RM2fYAkM2MMSqffqmadjwnyXY7DsYoawu0/fv3KT+/QPn5\n+UMLNMeRk5cnBQeaHggEVFxcrM7OTq1c+ZqWLPmxJGnXrjrNm3ee8vLy9PTTT+qWW76ssrKBUSAX\nLbpOixZdF1eOROcBTybPeAgEApo+fbq2bftAp59+Zlzv6evr0969DZo9+8Rxy5WMIX1hjMa7vySy\n3rq6nZo+/XgFAkNHbkq0ryQ5V/0x+bzeXxLpB+O5nUf7voPBoC655FL19vbpnnv+WT/5yYOy7ah6\nenp00UWXyLZt3XrrDfrRjx5IeJ8w3LqHa+9weY5+b6LbHgCQesG8UhVPPk+dB//KqI4ZLq0F2oIF\nF4z612PHcWSM0ZtvrhnTutauXaM5c0479vMlOcWFQ16zbVuPPfYbff/79w4Ouz1r1sDs6qtXv6Nz\nz52v/Px8XXDBhaOud9++vXr77TdljJHjONq6dYsee+wxdXb2yLKMFi26TsHgyF97Mnls29Zzzz0d\n8zmkadOm6+KLF4ya/Whz5pyutWvfi/ukq6WlWStXvqbZs78y4nLp7AdS7L4wlu8rVf0l0QxHr3f1\n6lWSpJqaarW0NOuNN17TVVddO2qWWH306aeflOM4cffRWLzeX4bbJwwnVds52e/71FPn6Ac/+J7a\n2to0efIUTZ48cOuKZVkKhUKqqJiokpKSEbMksu5Y7R0uz9HD6ye67QEA46No4lz1dNQp0tPsdhSM\nQVoLtLfeei9t66qu3qbzz/+bY163K8ql4NC/Kjz//B91ww2LVVExUa+++oquuOJK7dhRq7y8PL33\n3l914YUDt/usXbsm5mceadq06friFz8aiKKrK6RbbrkloRnTk8ljWZY+//kvxb2OeJx22hl67rln\nEnpPPLfLpbMfSLH7wli+r0S2z1VXfWrYz0k0w9Hrveqqawd/9vLLL2rhwstVVlY+al+J1Ue/8IXr\nE/oOYvF6fxlunzCcVO0XEvm+X3jhOa1Zs1r33feAmpubNGlSpUpLSzV//gWDA4NEo1GVlJTq0KGD\nam9vGzFLIuuO1d7h8hwtmW0PAEi9obc6jv0OGbgja29xPHTo4LHDmUdt/XHze9q27QM5jiPbttXe\n3qaHH/65fvObX0oa+EvwFVdcqdWrVykvL0/HHTdVO3bUqq2tTQsWLEw4x0i3Mz333DNDspx33vla\nufI1/eIX/zFueUZa99EqKyersfHY+eMyTcy+EAc3t8/RhluvNDAMen39Hj399H9p8eJbE84y2i13\n8fQVyfv9Zbh+kO7tPNL3vWDBpcrJydFf/vKq1q5do3//9/8ry7JUUTFRn/70lXrmmScVDof1ne98\nL6ksw617uPZecsknYuY5mte3PQD4STCvTEWV5yh0aC23OmaotBdoL7/8otra2lRfv1vf/e6/SJIa\nGur1ve99W4899lTK1tPR0XHMnFB2WYkWLbxJi264acjrn/zk5ce8/6ab/j4lOXJzc4f92ec+d50+\n97mhz6x88pOXj2uekdZ9tOLiEnV0tCf0ufE+z5SufiDF7gvxcHP7HG249UrSFVdcpSuuuCrpLCP1\nUSm+viJ5v78M1w/SvZ1H+r4nTKgYvDJ69Hx9V1/92SH/njv3rJSte7j2VlRMHDbPkZLZ9gCA8VM8\naZ56O3Yp0tvqdhQkIa0F2s6dO5Sbm6sFCy7VV7962+CJ1rvvrkr4Csfy5cskOVq16m19+ctf0Smn\nnDrk552dHSoqKvroBdtWdEb6hx9dvPjWtK8zVUpKStTR0RHzZ729vfrZz/5N0ehHc26Ew2Ht29eg\nAweGDkl+441f0qxZHz37k8p+cNiyZc9q1qzZmjfv3GN+dkxfwBCp6qOp6i9XX/1ZnXPOeYP/TqS/\n/P73v9Pxx89UdXWVrrzymsFJlSXv9AM39wnjte6Rtj0AIP2MMSqb/gk17VymsY/VjHRLa4EWDndp\n4cJPaenSR4cMgLBhwzqde27s26ZiOTyp6oknnqyysnLdd98SLV06dB4eY6whf513CgvkTKoYeyN8\nJBqNKhCIPW9YXl7e4InyYQcO7NeKFct1223/OOT1ysqSIc/gpaofSAMn/suXP68VK17S7bd/M+Yy\nR/cFjI9U9ZejxdtfNm/eqPr6PVq8+FadccZc/fSnPxky4iD9YPyMtO0BAO7Iya9Q0cS56mrcKGNx\nq2MmSWuBNnfu2ZKkFSuW66677hl8fePG9QnNoVNfv0fvvvu27rjjzmEnkS0tLVVXV5cmTaqUJEWn\nTtaCT/xNSuZ8ykaxRsELh7tUUpL6ofxT1Q+kjyYarq6uGnaZo/uCFN/IgBieF/vL+++v1emnnyFp\n4Jmobdu2Dvkc+kFqpHPbAwDGpmTyfPV27la0L/7B6uC+tD+DtmfPLrW1tQ7ewlRbW6NIJKo5c07X\npk0bdPbZ54z6GSNNqnpYaWmpQqGQJMkpL5EzsTztowcedvQVpEzR1dUVc8S2VEhFP4jXkX3hsHT1\nhUzd9slwu7+0tDQPueUxEAios7NTJSUlktLfD9j2AAC3GWOpbNoCNdctlzHc6ZAp0r6l+vr6lZ+f\nPzi57uuv/3lwbqLNmzfG9RlHT6r6zW/eecwy06ZN1969DQP/yMmRYow8lk7Lly/T8uXP6667vq2a\nmu1Dfvbznz+oQ4cOupRseHv3Nmjq1Gnj8tmp6AfxGtIXPGrZsme1ceP6wX+P1F+8yu3+YtuOrCNu\n4YhGI0Nuu/NyPxhte3t1H3HYeG57AMDY5BZOUeGEOXIc2+0oiFPar6CdfPIpuvTSy/S73/1axcXF\nOvvsc1RVtU1Llz6qz352UdyT9442qeppp52p6uptg0ORu+nNN98c9pm52toarVr1tr7whRtdTnms\nqqqtOu20M+JePhjMUV5eXlzLjtYPpNRNvu2lvnC0WM/QxfOMpRe53V8qKyvV09M9+B7bdlRY+NGg\nIF7tB6Ntby/vIw5LdNsDANKrZMqF6g01yI50j74wXOfKPGjf+c73hvz7wgsvGvLveCbvjTWp6pEu\nuOBjeuGFZ8ceNgV27dqlqqqaY56Zi0QiOnBgvyZPnuxywtiqq6v01a/+f3EvP2nSJN144y1xLz9a\nP0jV5Nte6gtHi/UMXTzPWHqR2/3l/PP/RitWvCRp4Ds87bTTh/zcq/1gpO3t9X3EYYluewBAelmB\noEqPu1Cte15zOwrikJETVY80ae9hEyZMUH5+vjo62lVa6u7D6zfddJP27BmYxPXIZ+ZWrXpTl1xy\nqZ566gk348XU29urtrZWnXDCLLejjGq0iZS91BfiEc8zll7jhf5yxhlz9dZb/6M///kV1dRs1//+\n3/805Ode7QcjbW8v7yMO88K2BwCMLr90lvJKT1Bvxy63o2AUGVmgjTRp75EWLbpOL730om64YXEa\nUg3v6Gfmliz5serqdmr69OMHn6nxmr/85VVdffW1bseISzwTKXulL8QjVn/xOq/0l8NXcT796di3\nMXqxHwy3vb2+jzjMK9seADC6smmXqDHkzeex8ZGsHs7lkks+oa1bt6inp8ftKMc8M1dVtVU1NdVa\nsWK5Wlqa9cYbr6m9vc3tmJIGbqt66603dPXVf+t2lJTxUl+Ix2jPWHpJJvUXr/aDWNvby/uIwzJp\n2wMApECwQMWTz5fJ7hIg42X91vna127X0qWPuh1j8Jm5iRMn6dVXX9FVV107+F9FxUQtXHi5ysrK\n3Y4pSfrDHx7Trbf+oyyXR75MNa/0hXgc3V+8LNP6ixf7Qazt7eV9xGGZtu0BAFLxpLOUV3K82zEw\ngqw/qk6fPkMf+9jH9T//s9K1DK+88op+8Yv/0C23XK9rr/20/vSnlwd/9uqrK1Rfv0dPP/1famtz\n/6/j7733V82adeLgEObZxAt9IZbDz9C99NILev/9tVq58jU9/PDPY/YXr8nE/uK1fnD4mdrhtrfX\n9hGHZeK2BwAMMMa4HQEjMI7jHDuG+Tjxy6StR/PThLWx+Ln9tN2fbZf83f7KyhK3I2Qcv/YVid8V\n2u5Pfm6/n9suxXeMzPoraAAAAACQKSjQAAAAAMAjKNAAAAAAwCMo0AAAAADAIyjQAAAAAMAjKNAA\nAAAAwCMo0AAAAADAIyjQAAAAAMAjKNAAAAAAwCPGVKDt2LFD559/vvr6+lKVBwAAAAB8K+kCLRQK\n6V//9V+Vl5eXyjwAAAAA4FtJF2j33HOPvvWtbyk/Pz+VeQAAAADAt4KjLfDMM89o6dKlQ16bNm2a\nrrnmGs2ZM0eO44xbOAAAAADwE+MkUWF95jOf0ZQpU+Q4jjZu3Kh58+bp8ccfH498AAAAAOAbSRVo\nR7rsssv0pz/9STk5OanKBAAAAAC+NOZh9o0x3OYIAAAAACkw5itoAAAAAIDUYKJqAAAAAPAICjQA\nAAAA8AgKNAAAAADwCAo0AAAAAPAICjQAAAAA8AgKNAAAAADwCAo0AAAAAPAICjQAAAAA8AgKNAAA\nAADwCAo0AAAAAPAICjQAAAAA8AgKNAAAAADwCAo0AAAAAPAICjQAAAAA8AgKNAAAAADwCAo0AAAA\nAPAICjQAAAAA8AgKNAAAAADwCAo0AAAAAPAICjQAAAAA8AgKNAAAAADwCAo0AAAAAPAICjQAAAAA\n8AgKNAAAAADwCAo0AAAAAPAICjQAAAAA8AgKNAAAAADwCAo0AAAAAPAICjQAAAAA8AgKNAAAAADw\nCAo0AAAAAPAICjQAAAAA8AgKNAAAAADwiGCyb/zlL3+p119/XZFIRIsXL9aiRYtSmQsAAAAAfCep\nAm3NmjVav369nnzySYXDYT366KOpzgUAAAAAvmMcx3ESfdODDz4oY4xqamrU1dWlO++8U2eeeeZ4\n5AMAAAAA30jqClpra6v27dunRx55RPX19fr617+uV155JdXZAAAAAMBXkirQysvLddJJJykYDGr2\n7NnKy8tTS0uLKioqhn2P4zgyxiQdFACAbMTxEQBwpKQKtPnz5+vxxx/XrbfeqoMHD6qnp0cTJkwY\n8T3GGDU2diYVMtNVVpb4tu2Sv9tP2/3Zdsnf7a+sLHE7Qkbx8/FR4neFtvuTn9vv57ZL8R0jkyrQ\nFi5cqLVr1+q6666T4zhasmQJf/0DAAAAgDFKepj9b3/726nMAQAAAAC+x0TVAAAAAOARFGgAAAAA\n4BEUaAAAAADgERRoAAAAAOARFGgAAAAA4BEUaAAAAADgERRoyGpNPQfkOI7bMYC0auttVr/d53YM\nAACQBAo0ZLW94Z061NPgdgwgrT5o/6uiTsTtGAAAIAkUaMhqOSZH9V01bscA0sZ2bDX27HU7BgAA\nSBIFGrLewZ4G2Y7tdgwgLfaHd3N7IwAAGYwCDVmvL9qrveE6t2MAadEQ3iHLBNyOAQAAkkSBhqwX\nsILaF97pdgxg3NlOVI08cwkAQEajQIMvHOxpUMRm0ARkt92h7epncBAAADIaBRp8wXZs7QlVux0D\nGFf7uncpwO2NAABkNAo0+IJlLO3r5jk0ZK++aI+aeva5HQMAAIwRBRp8o6l3v3oj3W7HAMZFXWib\n2xEAAEAKUKDBN4wC2hH6wO0YwLjY371HxrBLBwAg03E0h28YY3Sge4/bMYCU6+rvUEvvQbdjAACA\nFKBAg6+09zepva/F7RhASu0IbVHABN2OAQAAUoACDb5iKai60Fa3YwAp4ziODobrZYxxOwoAAEgB\nCjT4ijFGB7vr5TiO21GAlGjq2a/OaLvbMQAAQIpQoMF3uiMhHejhWTRkh11dVQqaHLdjAACAFKFA\ng+9YVlB7QtvdjgGMme1Edai7we0YAAAghSjQ4EuHevYqYkfcjgGMSX1XrfqcXrdjAACAFKJAgy9F\nnah2MbEvMlxDeAejNwIAkGUo0OBLlrG0N1zndgwgab2RbjX27HM7BgAASDEKNPhWS+9BdfV3uB0D\nSMqO0BYZduEAAGQdju7wLcsEtCO0xe0YQFL2h3cz9xkAAFmIAg2+ZYzR/vAe5kRDxmnuPaj2/la3\nYwAAgHFAgQZfC0c6mBMNGWdX5zYFLQYHAQAgG1GgwdcCVo72hGrcjgHEzXai2t/NHxUAAMhWFGjw\nvYM99eqP9rkdA4jL7tB29Tv0VwAAstWYCrTm5mYtXLhQdXUMV47MZTu26kJb3Y4BxKUhXKuACbgd\nAwAAjJOkC7RIJKIlS5YoPz8/lXmAtGNONGSKrv4ONfUccDsGAAAYR0kXaA888IBuuOEGTZ48OZV5\nAFe09TWqrbfJ7RjAiGo7N8vi6hkAAFktqQLt2Wef1cSJE3XxxRczRDmyQsDK0c7QB27HAIblOI4O\ndO9h7jMAALKccZKosBYvXjx4klBVVaXZs2fr4Ycf1sSJE1MeEBiLDYfeVVXLxriWDZig/u7U23i+\nB560u6NGb+/9kwJm9OH1+6J9+sKcf1BBsCgNyQAAQColNZHO73//+8H/v/nmm3XvvffGVZw1NnYm\ns7qMV1lZ4tu2S+62v72tW13h+Ea8izrdWle3TrNLTk/Z+v287f3cdin17d9waIN6em1Jo/fnfrtX\nTU0h5QfslK0/EZWVJa6sN5Pxu+LP9tN2f7Zd8nf7/dx2Kb5j5JiH2ed2G2SLgAloTxdzosF7uiNd\nOtTT4HYMAACQBkldQTvSY489loocgCe09B1UR3+rSnMmuB0FGFTbuUWGaSsBAPAFjvjAEQImqB0d\nW9yOAQxyHEf7uuu4WwEAAJ+gQAOOsr97l2wn6nYMQJK0L7xL3f3+vVcfAAC/oUADjtJr92p3aLvb\nMQBJ0u6ualnWmO9GBwAAGYICDTjKwGAhFGhwX5jBQQAA8B0KNCCGlr5DauttcjsGfK62cyODgwAA\n4DMc+YEYAiao2k4GC4F7bMfWvvAuBgcBAMBnKNCAYRzo3qWIHXE7BnyqIbxD3dEut2MAAIA0o0AD\nhhFxotrZ+YHbMeBTu0NVChgGBwEAwG8o0IBhWMZSfbjW7RjwoY6+VjX1HnA7BgAAcAEFGjCCjv4W\nHere63YM+ExN50aungEA4FMUaMAIAiaoHQwWgjSKRPu1v3u32zEAAIBLKNCAURzqaVB3hMEakB47\nQx8wOA0AAD5GgQaMyqimc6PbIeADjuNoT1etLMOuGQAAv+IsABiFMUYNXXWynajbUZDlDvTsUWek\n1e0YAADARRRoQBx67W7tClW7HQNZrq5zK4ODAADgcxRoQBwCJqDdoSq3YyCLhfrbdKiHEUMBAPA7\nCjQgTm19zWrs3ud2DGSp7R2bZNglAwDge5wNAHEKWEHVdm5yOwayUH+0T3u762SMcTsKAABwGQUa\nkICDPQ0KRzrdjoEsU9O5STZD6wMAAFGgAQkxslTdvt7tGMgijuOovqtWhqH1AQCAKNCAhBhjtDe8\nU5Fov9tRkCXqu2oUjoTcjgEAADyCAg1IUMSJqoZn0ZAidaFtClgBt2MAAACPoEADEmQZS3vC22U7\ntttRkOEau/eppfeQ2zEAAICHUKABSQhHQtrTtd3tGMhwNZ2bFLCYmBoAAHyEAg1IQsAEtbNzq9sx\nkMEGJqZucDsGAADwGAo0IEkd/c060L3H7RjIUFXt65mYGgAAHIOzAyBJlgmqpoPBQpC4nmi39oWZ\nmBoAAByLAg0Yg6be/QzygIRVtb8vx+0QAADAkyjQgDEImKC2t29wOwYySCTar71dtVw9AwAAMVGg\nAWN0oKdeof42t2MgQ2zv3KiIE3E7BgAA8CgKNGCMjIy2tb/vdgxkANuJandXlYxh1wsAAGLjLAEY\nI2OM9od3qTvS5XYUeFxtx2b1RnvcjgEAADyMAg1IAUfStvZ1bseAh9mOrbpQlSwTcDsKAADwsKQK\ntJ5ttQ8AABPdSURBVEgkojvvvFM33XSTvvjFL+r1119PdS4goxhj1BDewdURDGtX5zaFo51uxwAA\nAB6XVIH2wgsvaMKECXriiSf0q1/9Sj/60Y9SnQvIOI7jaFv7WrdjwIMcx1FtaIsCJuh2FAAA4HFJ\nnS1cddVVuvLKKyVJtm0rGOSkAzDGqL6rVmeUna/cQL7bceAhu0JVCkc6ub0RAACMKqnKqqCgQJIU\nCoX0jW98Q3fccUdKQwGp8qXLblTE7j/m9QeWL4m5/Hev/WHM1+Nf3tH3zH3avKE25vLz58+N+fq6\ndVvGZfnhlvODdH/Xwy3vOI5qO7fors/eF3P58eiL973wzzGXAQAA3pf0pa/9+/fr9ttv1+LFi3X1\n1VfH9Z7KypJkV5fx/Nx2yb32W5aRcY59vagwN+byw80dHP/yRlFFVTYhV7nBPElD225ZsVcw3Pcz\n1uXd7ndurj/d33Ws5SsrS1Tb+oGc3HAK+lb8yxcW5GnSpGIVBItifwg8x+3fVbf5uf203b/83H4/\ntz0exnGcGKevI2tqatItt9yie+65RxdeeGHc72ts9OcD8pWVJb5tu+Ru+7e2vqfaUHqvIjmOo1nF\nczSv4mJfb3s/t10aaP+hQx16bf8z6o6G0rrufrtX18y4RfmBwrSu9zAOvInz+++KX9tP2/3Zdsnf\n7fdz26X4jpFJDRLyyCOPqKOjQw899JBuvvlm3XLLLerr60vmo4CsY4zRnq4a9TGio+/t7qpWV6Td\n7RgAACCDJHWL4913362777471VmArGE7tra2r9X0465yOwpc4jiOtndsZGAQAACQECaqBsbB4ato\n3f1ht6PAJdWtm9QV6XA7BgAAyDAUaMA4cRxHGxrfdTsGXGA7trY1b2DeMwAAkDAKNGCcGGNU17Fd\n4Yh/H4T1q5qOTQpH0jswCAAAyA4UaMA4Mo60pe2vbsdAGkXsfu3o/EABnj0DAABJoEADxpExRvvD\nu9Te1+x2FKRJVfv76rMZwRMAACSHAg0YZ8YEtKVtjdsxkAZ90R7VhbbJMuxaAQBAcjiLANKgsWev\nGrv3uR0D42xL2xrZju12DAAAkMEo0IA0sExAH7SvkeM4bkfBOAn1t6v+/2/v3mOjrPM9jn+eZ6ad\nFnqhQsHrsmy4rGeLILq6SwAPLKwQZU/wGK3houg/xsSgFAuKES8hzTEGjUlJCERC0IgGCTEnMQYO\naliOi1gpCiJsQZGLrC30NqXtXJ7f+QMPAQWh05n5PZ3n/fqLTjp9Pj8Y+p3PzPP85sw/5TiO7SgA\nAKAPo6ABWdLS3aijHf+0HQMZsrdlpxx+pQIAgF7i2QSQJa4b1v7WLzgFLgc1dv2gk53f244BAABy\nAAUNyKLOZFQH2+ptx0AaGWO0r3mnXLbVBwAAaUBBA7LIdUJqaP9KsSTbsOeKIx0H1RJrtB0DAADk\nCAoakGVJL6mvWv5hOwbSIGkS+qa1Tq4bth0FAADkCAoakGWO4+hYxyE1dzfZjoJe2t9Sp65kp+0Y\nAAAgh1DQAAscx9VXzZ+y7X4fdibRrsPtX/Oh1AAAIK14ZgFYcjr2L33fcdB2DKRoz+kdMqJgAwCA\n9KKgAZa4Tkhft+5SwovbjoIe+uHMEf2r8ygfSg0AANKOggZYFEt2a1/LTtsx0AOe8bS35R9sDAIA\nADKCggZY5DiuvoseUEuMDUP6iv2tn6sjEbUdAwAA5CgKGmCZ47iqP/13NgzpA6LxVh1q28vGIAAA\nIGN4lgH4QEt3ow5Hv7YdA5ex+/R2ievOAABABlHQAB9w3bD2t36ursQZ21FwCd9FD6ip+wfbMQAA\nQI6joAE+kfSS2t283XYMXEQs2aV9zTsVctgYBAAAZBYFDfAJx3F0svOojnUcth0FP7P79HYlTMJ2\nDAAAEAAUNMBHQk5IXzZ/qliy23YU/ORYx2H9cOY7PvMMAABkBQUN8Jm416365r/bjgFJ8WRMX7V8\nymeeAQCArKGgAT7jOI5OdBzmVEcf2N28nXczAQBAVlHQAB9y3bC+bN6h7mSX7SiBdSzaoONnvuXU\nRgAAkFUUNMCn4l5cX5z62HaMQOpKdurL5k8VckK2owAAgIChoAE+5TiOTnYd1eH2fbajBIoxRp83\nbVPcxG1HAQAAAURBA3ws5IS1r2WX2mMttqMERkPbl2rqOsGpjQAAwAoKGuBzRka7Tv2PPOPZjpLz\nmrubtL/tC3ZtBAAA1qRU0IwxWrZsmSorKzVv3jwdPXo03bkAnKct3qI9p3fYjpHTEsm4dp3aajsG\nAAAIuJQK2tatWxWLxbRhwwZVVVWppqYm3bkAnMd1XB3pOKBj0QbbUXJW3emP1Zk4YzsGAAAIuJQK\nWl1dnSZOnChJGjNmjPbu3ZvWUAB+yXVCqm/5X65Hy4BD7Xv1Q+cRrjsDAADWpVTQotGoiouLz30d\nDofleVwfA2SaZ5La2bRVCY8dBtOlqeuk9rXsksuW+gAAwAdSuhK+qKhIHR0d5772PE+uy34j8B8j\nI2OMveOb9B8/mmhV3amP9cdBf0nrz003z3i+39gkluzSZ01bM/IYycS//ZUf3M5hAQBA76VU0MaN\nG6ePPvpI06dPV319vUaOHHlF9ysvL778N+WoIK9dsrf+m0vG6bozV1s5dibFkl3a2vimv5+Hn7Id\n4HKMSvLLNP63k2wHSTtHjq4dMIgP2u5DmBHBXT9rD64grz/Ia78SjknhJV5jjJ5//nkdOHBAklRT\nU6Nhw4Zd9n6Nje09T5gDysuLA7t2Kdjrz+TaGzuP69PGDyWfXjfVv1++Os7EbMe4pMJQf02++h6F\nM7SlftAf9+iZoD5WJP6vsPZgCvL6g7x26cpmZErPTBzH0QsvvJDKXQGkSXnhdRpd9md92bxDDu+U\n9EjYCevP5XdmrJwBAACkigvHgD5sWPGN+l1xhTwvaTtKn+FIum3QNBXlldqOAgAA8AsUNKCPqxhw\nu67pN9T3G3L4gWeSGls2UYMKcu+6RAAAkBsoaEAf5ziO/jjoL7oqf7DVHSv9zjNJ/aH0Nt1QNNx2\nFAAAgEuioAE5wHVcjR88Q8V5AyhpF+GZpIYXj9aI0ptsRwEAAPhVFDQgR4TdsCYMvkv9wkWUtPN4\nXlK/LbpRFWW3244CAABwWRQ0IIfkhyKaOGSmCsP9KGk6W85u6D9cY8rG244CAABwRShoQI4pCBVq\n0uC/qTDcP9AlzfOS+k3RCI0beIccn35WHAAAwM9R0IAcVBDupzuG/If6h4sDWdI8k9TQot/r5qsm\nUc4AAECfQkEDclQkVKBJQ/6mkvwymQBtwe+ZpIaX3KSbB06gnAEAgD6HggbksPxQRJOGzNSgyLWB\n+Jw0Yzz9ofQ2VQy4zXYUAACAlFDQgBwXcsIaP3i6hvYfIc8kbcfJGEeObhk4ma30AQBAnxa2HQBA\n5jmOo5sHTlJReID2t34u5dCpf8YYRUIFun3QNJVFym3HAQAA6BUKGhAgI0pvUmn+Vfr81EeKe/E+\nf42WZ5IqiwzWnwb9VZFQge04AAAAvcYpjkDADC68XlOu/k+VRQb16VMePZPU8OLRmjR4JuUMAADk\nDAoaEEAF4X6aOHimRpaM7XPb8BtjFHELNL58uirKbu/z7wICAACcj1McgYByHEf/NuBWXVM4VLtP\nb1dbvFmu4+/XbIzxdF3/32ls2QSF3TzbcQAAANKOggbksFtuqbjo7XV1e8/9uSxSrslXz9KBtnrN\nmjRLkpF04btS//Xfyy76cxbf/cJFb0//9xs5cpUfiijkhC/If77z13up7wEAAPAzChoAOY6j35fe\nrMJQP8W8biVNQj8vaXacLYt5bkRhN0+OLzIBAABkDgUNyGE9fRfpiy++liS1xZr1desunez8Xs6v\nXKp6qXe+evv9nvGU5+bp3Y/f1Y2ltyjsXtmvKt41AwAAfR0FDcAvlOSX6U/lf1VHvFXftO3WyTNH\nFDeJjF+jljQJFYdLdX3/ERpRMlohh19RAAAgWHj2A+CS+ueV6paB/67kVQl9275fJzuPqKn7pCQn\nbWUt6SWU70Y0uOB63VA0XEMKbmBnRgAAEFgUNACXFXLCGl4yWsNLRivuxXSs45Cauk+oNXZK7fFW\nGRmFnPBli5UxRgkTV56br9K8q1SaN1BXF/5Ggwuv9/0OkgAAANlAQQPQI3luvoYV36hhxTdKkhJe\nXM2xH9Uca1J34oxiJqaEF1dR/3y1e11ynZDynDzluwUqDPfXoMg1KsobQCEDAAC4CAoagF4Ju3kq\nL7hO5QXXXXB7eXmxGhvbLaUCAADom3gJGwAAAAB8goIGAAAAAD5BQQMAAAAAn6CgAQAAAIBPUNAA\nAAAAwCcoaAAAAADgExQ0AAAAAPAJChoAAAAA+AQFDQAAAAB8IpzKnaLRqBYtWqSOjg7F43EtWbJE\nY8eOTXc2AAAAAAiUlAra2rVrNX78eM2bN0/ffvutqqqqtGnTpnRnAwAAAIBASamgzZ8/X/n5+ZKk\nRCKhSCSS1lAAAAAAEESXLWgbN27UunXrLritpqZGFRUVamxsVHV1tZYuXZqxgAAAAAAQFI4xxqRy\nxwMHDmjRokVavHixJkyYkO5cAAAAABA4KRW0hoYGPf7443rttdc0atSoK75fY2N7Tw+VE8rLiwO7\ndinY62ftwVy7FOz1l5cX247Q5wT1sSLxf4W1B1OQ1x/ktUtXNiNTugZtxYoVisViWr58uYwxKikp\nUW1tbSo/CgAAAADwk5QK2sqVK9OdAwAAAAACjw+qBgAAAACfoKABAAAAgE9Q0AAAAADAJyhoAAAA\nAOATFDQAAAAA8AkKGgAAAAD4BAUNAAAAAHyCggYAAAAAPkFBAwAAAACfoKABAAAAgE9Q0AAAAADA\nJyhoAAAAAOATFDQAAAAA8AkKGgAAAAD4BAUNAAAAAHyCggYAAAAAPkFBAwAAAACfoKABAAAAgE9Q\n0AAAAADAJyhoAAAAAOATFDQAAAAA8AkKGgAAAAD4BAUNAAAAAHyCggYAAAAAPkFBAwAAAACfoKAB\nAAAAgE9Q0AAAAADAJyhoAAAAAOATFDQAAAAA8AkKGgAAAAD4BAUNAAAAAHyCggYAAAAAPkFBAwAA\nAACf6FVBO3TokG699VbFYrF05QEAAACAwEq5oEWjUb388suKRCLpzAMAAAAAgZVyQXvuuee0cOFC\nFRQUpDMPAAAAAARW+HLfsHHjRq1bt+6C26699lrdddddGjVqlIwxGQsHAAAAAEHimBQa1p133qkh\nQ4bIGKM9e/ZozJgxWr9+fSbyAQAAAEBgpFTQzjdlyhR9+OGHysvLS1cmAAAAAAikXm+z7zgOpzkC\nAAAAQBr0+h00AAAAAEB68EHVAAAAAOATFDQAAAAA8AkKGgAAAAD4RFYKWmdnpx577DHNmTNHDz/8\nsH788cdsHNY3otGoHn30Uc2dO1eVlZWqr6+3HSnrtmzZoqqqKtsxssIYo2XLlqmyslLz5s3T0aNH\nbUeyYs+ePZo7d67tGFmVSCRUXV2t2bNn67777tO2bdtsR8oqz/P0zDPP6IEHHtDs2bPV0NBgO1Kf\nEOQZyXw8ixkZLEGcj1KwZ2RP52NWCtq7776riooKvfnmm5o5c6ZWr16djcP6xtq1azV+/HitX79e\nNTU1evHFF21Hyqrly5fr1VdftR0ja7Zu3apYLKYNGzaoqqpKNTU1tiNl3Zo1a/Tss88qHo/bjpJV\n77//vsrKyvTWW29p9erVeumll2xHyqpt27bJcRy9/fbbWrBggVasWGE7Up8Q5BkZ9PkoMSODNiOD\nOh+lYM/Ins7HcDZCPfjgg+e24j9x4oRKS0uzcVjfmD9/vvLz8yWdffUgEolYTpRd48aN07Rp0/TO\nO+/YjpIVdXV1mjhxoiRpzJgx2rt3r+VE2Td06FDV1taqurradpSsmjFjhqZPny7p7Ktl4XBWfsX6\nxtSpUzVlyhRJ0vHjxwP3uz5VQZ6RQZ+PEjMyaDMyqPNRCvaM7Ol8TPvfzMaNG7Vu3boLbqupqVFF\nRYUeeughHTx4UG+88Ua6D+sbv7b+xsZGVVdXa+nSpZbSZdal1j5jxgx99tlnllJlXzQaVXFx8bmv\nw+GwPM+T6wbnks9p06bp+PHjtmNkXWFhoaSzj4EFCxboySeftJwo+1zX1dNPP60tW7bo9ddftx3H\nd4I8I4M8HyVm5P8L+owM6nyUmJE9mo8myw4dOmSmTp2a7cNa980335i7777bbN++3XYUK3bu3GkW\nLlxoO0ZW1NTUmA8++ODc13fccYe9MBYdO3bM3H///bZjZN2JEyfMPffcYzZt2mQ7ilVNTU1m8uTJ\nprOz03aUPiWIMzLo89EYZmTQBHU+GsOMNObK5mNWXq5YtWqVNm/eLEnq16+fQqFQNg7rGw0NDXri\niSf0yiuvaMKECbbjIMPGjRunTz75RJJUX1+vkSNHWk5kj/nptK2gaGpq0iOPPKKnnnpKs2bNsh0n\n6zZv3qxVq1ZJkiKRiFzXDcyr4r0R5BnJfAweZuRZQZuPUrBnZE/nY1ZO/rz33nu1ePFivffeezLG\nBO6C0BUrVigWi2n58uUyxqikpES1tbW2YyFDpk2bph07dqiyslKSAvd4P5/jOLYjZNWqVavU1tam\nlStXqra2Vo7jaM2aNeeuscl106dP15IlSzRnzhwlEgktXbo0MGvvjSDPSOZj8DAjzwrafJSCPSN7\nOh8dE8QKDwAAAAA+xLknAAAAAOATFDQAAAAA8AkKGgAAAAD4BAUNAAAAAHyCggYAAAAAPkFBAwAA\nAACfoKABAAAAgE9Q0AAAAADAJ/4PSW/4uvPyAmMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a95cbd110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZqtzxFzodBx4RVbVg27aWLFmim2++WXfccYcqKipinSupWC1t8lVVU5whLnwV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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a95c8a210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZqtzxFzodBx4RVbVg27aWLFmim2++WXfccYcqKipinSupWC1t8lVVU5whLnwV\nRwZ8PPX9bXFOAgBA4jMMn9pqd6it9iOno8AjoqoY3nzzTXV1den555/XP//zP+vhhx+Oda7kYduy\ndpXK4L4zxIkRaB/wcbO2Ic5JAABIDoZhqvnYZgUa9zkdBR4QVYG2detWzZ8/X5I0Z84cffQRf1EY\njHn4qOyGZqdjwEPszIwBH7fGjYlzEgAAkochQ82HN6ijpdLpKEhyUd2D1traqpycnE/fxO+XZVky\nXXoJ37x5swZ8fOvWgQvLmC2/aZt8B6uk9P4f83nfuXXA5Xf9+rkBHx/p8oMth+QUmjJBZsnJ86F1\nffZ8B9IAAJBcGivfUsG0a5SaUeh0FCSpqAq07OxstbW19f0cbnFWWJgz7DKjwTQkBU8edrzgaPXA\nyw8yRHmky485ekwqyJYkZWWmf7q8b+DPKmtc7sDvP8LlB1suno5vv9fEve3jcmXlZMjae0hqbZMx\nfpz8V12i9PPPjm8OOfc77xZebz/C5/W+4lT7M/zjZHYVObLuXnlpjq7eUYnc9mDDe/J1j5fpS43q\n9cfahl9m1Ni28ifMVWp6vmMRvL7PG45hRzG5w7p167R+/Xo9/PDD2r59u5544gn95je/GfZ1NTUt\nUYUcKaOmXim7S+M7SIdlqXv2WbLH5KmwMMextruBl9tP273Zdsnb7efAGzmv9hWJ3xXanrgaq95R\ne8NeGaYv4tdmZqUp0NY5CqmGZ1sh5U+9Shm50xxZfzJs+5EI5xgZ1Rm0L37xi9q4caNuvvlmSWKQ\nkBPZtkKFBbLH5DmdBAAAAKMgb+J8hbpb1dV2RAbz3CKGoirQDMPQz3/+81hnSR6mqdDp05xOAQAA\ngFFiGIbGTFmourLlCnY2M2I3YoZyP9YsS8GpE6XUFKeTAAAAYBSZPr8Kpl0nn9+799oj9ijQYszO\nzJA1ZYLTMQAAABAHPn+G8qculLjMETFCT4oly1LwtFMlTnEDAAB4RmrGOOVP/rxsRTz2HnASCrRY\nsW2FCvJlFzAwCAAAgNek50xVbtFnZNsDT78EhIsCLVYMQ6HTT3U6BQAAABySNW6WMsecJduiSEP0\nKNBiwbYVnFAoZXCDKAAAgJflTrhMqdkTFMVUw4AkCrSYsP1+WdMmOx0DAAAADjMMQ/lTvihfapbT\nUZCgKNBGKhRS6NSJkj+qKeUAAACQZHy+VBVM/ZIM0+d0FCQgCrQRsrKzZE0c73QMAAAAuIg/LV95\nkxbIti2IInc+AAAgAElEQVSnoyDBUKCNhBVSaMYUhtUHAADASdJzpiqn6ELZFkUawkeBNgLWmHzZ\nBflOxwAAAIBLZRfOUXreNM6kIWwUaFGyLUvB06Y6HQMAAAAulz95gfxpYxjZEWGhQIuGbcsqGitl\nZTqdBAAAAC5nGD6NOXWhDF+q01GQACjQomEYCnH2DAAAAGHyp2Qrf9IC2eIsGoZGgRYp21ZwQpGU\nyl9AAAAAEL70nMnKKZwn2wo6HQUuxuRdEeqZlHqS0zEAAAAQpXnzZg34+NatH4368lnjZivkb1Ig\nUCrD6DlXcvVNPx9w+bUvLBnw8ZEtb+v9jVcNuBzcgTNokbAshSafwqTUAAAAiIphGCo6baF8qTlO\nR4FLUWlEwE5LlTVlgtMxAAAAMAKDnfmK1/I+X4rGTLlKdQdek2QPeuZrMCNZ3rZCEb0W8ccZtHCF\nQgpNmcCk1AAAABixlPQC5U64VLZNwYT+KNDCZGdlypo43ukYAAAASBKZY85URv6ZTGKNfijQwhGy\nFJw6ibNnAAAAiKm8iZfLnzbG6RhwEQq0MFg5WbKLCpyOAQAAgCRjGKbGTLlKhuFzOgpcggJtOCFL\noVM5ewYAAIDR4U/LVe7Ey7jUEZIo0IZl5WXLHsdpZwAAAIyejLzTlDmG+9FAgTY0K6TQqZOdTgEA\nAAAPyJ1wmVLS8p2OAYdRoA3BysuTXZDndAwAAAB4gGGYyp/yBcngK7qXsfUHY1kKTZvodAoAAAB4\niD8tX7mnXML8aB5GgTYIKz9Xdj5nzwAAABBfmWNmKj13BvejeRQF2kB6R24EAAAAHJA38XPypWQ7\nHQMOoEAbgDUmV3Z+rtMxAAAA4FGmz6/8yZ93OgYcQIF2Is6eAQAAwAVSM4uUVTiX+9E8hgLtBJw9\nAwAAgFtkj5ur1MxTZNu201EQJxRox7NCCp3KyI0AAABwB8MwlD/5ShlmitNRECdRFWitra36zne+\no9tvv10333yztm/fHutcjrDyGLkRAAAA7uJLyVTexEu51NEjoirQfv/73+vSSy/VM888o4cfflgP\nPPBArHPFX8hSaCpnzwAAAOA+GXmnKT3vNIbe9wB/NC+66667lJqaKkkKBoNKS0uLaSgnWLnZsgvy\nnY4BAAAADChvwnx1BY7KDrY7HQWjaNgC7aWXXtLSpUv7Pfbwww9r1qxZqqmp0b333qsf//jHoxYw\nLkIhhaZOcDoFAAAAMCjT51f+xCtUf2i1DIOhJJKVYUc5JExJSYl+8IMf6Ec/+pEuv/zyWOeKKau6\nRsEP98gwB+7IRnamfJedL8Mw4pwMAAAAiExt+UY1Vu+QYfoifq1lBTXxjGuVNWb6KCRDLER1ieO+\nffv0ve99T48//rhmzpwZ9utqalqiWd2IGfUBpQS6pIEKtFBI3ZMmyq5tHbX1FxbmONZ2N/By+2m7\nN9suebv9hYU5TkdIOF7tKxK/K7Tdm0bafjt9lrpCpQq1N0f+WiukuvpWBYLOfP5s++GPkVEVaI89\n9pi6urr00EMPybZt5ebm6r//+7+jeSvH2ZkZssePczoGAAAAEBbDMJU3eYHqDrwmrv9KPlEVaE88\n8USsc4y6hrYWjck5YQh9y1Jo0ngpwksbDxzYr4qKchUX79btt9+pzMysGCZ1VmNjo/Lzk3uwlIaG\nBo0ZMyZu66O/uFOs+8GJ21lK7rNIibztASAZpKaPVfa4uWqt2SrDiPxSR7iXJ+4uXP3WOpXXHjvp\ncTstVdbE8RG/3/r1b+rcc2fp3HPP07vvbohFRNeora3R//7vn5yOMWrWrFmpiopDcV0n/cV9RqMf\nJPN2HkiibnsASCbZhXOVklHodAzEmO9nP/vZz+K1skCgK16r6rNr1w5VlpVp4Yyz+86Uvbp5gzo6\nu1R43rmy83O1cuUK7d1brN///rc69dRpGjt27JDvecEFFyozM0vbt3+oyZOnaPz4U4ZcPisrbdC2\nr1jxijo7O3TKKZ+OIhlpnmgNtO6CgrGqqChXdfURTZ06LSbrGar98bRr1w5VVlboC19YGPZrRrp9\nsrLSNHPmeRH1l8EMtd5f/eoxTZ8+Q1lZ2VG993AG+hykofuLW7b7iQbqB7H4PTxxvzBjxqlRtX/d\nujWqqqrSa6+9omAwqKlTT5UkHT5cpeeff1bNzU06cGC/Zsw4LeL3Hspg7R0sz3DbHpFx4+9KvLh1\nXxEPtN2bbZdi137DMJSaOUGBhuLwX2TbSs+boZQ0Z66CYNsPf4xM6jNowWBQf/zjH/SN62+QJHV2\nd+t/33tbyzdvlG0asqZM0KZN7+mcc87V9dcv0rXXXq8HH1wS1nu3t7crEGjT7Nlzh1zuwIF9Az7e\n2dmpl19+Qa+/vlzHD6QZbZ5IDLbuXldffZ1Wr16pjo6OmK/bKb194etfvyWs5WO9fcLtL4MZar37\n9pVq48Z3ZVlRDcg6aB+Vhu8rUmL1lxP7gRPbeajPu6qqUkuXPq3PfW6BLrroEv3+9/8jSbJtWw8/\n/IBuu+3vNGfO+Vq9+vWw8oS77sHaO1ieXom07QEgWfnT8pRddIFsO+R0FMRIUhdoa9eu1BVXXCnz\nk9Eb01JS9I1LF+i08RMUKsiTTFMVFeVaseIVSdLkyVN19OiRsN77b397TzfddJuqqiqHXO7tt98a\n8PG0tDR97Ws3nfRX8GjzRGKwdR/v+uv/H734YvJcvnRiXxhOrLdPuP1lMIOtNxgMqrr6iIqKiqJ6\nX2nwPiqF11ekxOkvJ+0THNjOQ33ekyZN1hNP/FaSVFq6V5df/jlJ0rZtW5WTk6vMzEwVFIzVI4/8\nMqw84a57sPYOlud4ibLtASCZZY09TykZkd+2A3eKapCQRLF69Uo99th/SS2B/k8YRt/IjV/96tfV\n3t4zG/vOndt18cWf7Vvs7bf/IsMwVFJSrBkzTtMHH/xN9933Uy1f/pLefHOdVqx4RbfeeocmTZo8\naIZI51aLJM/mzZt0//2xP8MmSRdf/Fn97ne/0e233zUq7x9vfX1hhCLtL4899ouI+kuk69248R1d\nfvkVeuGFZ/stH0lficX8f4nSX8LtB7HYL8yde/aA7z3c552Vla133/2rDh+u0j33/FCSVFJSrO7u\nLr333ruqra3RlClTdf758yLeJwy27qHaO1Ce4yXKtgeAZGYYhvInXaHa/a9KspyOgxFK2gLtyJHD\nSk/PUHp6ev8CzbZlp6VJ/p6m+3w+ZWdnq6WlRevXv6klSx6SJB08WKY5cy5QWlqaXnzxed1xxzeV\nl9czCuSiRTdq0aIbw8oR6Tzg0eQZDT6fT5MmTdKePR/r7LPPDes1XV1dqqqq1PTpM0YtVzT69YUR\nGu3+Esl6y8oOaNKkKfL5+o/cFGlfiXKu+pPyub2/RNIPRnM7D/d5+/1+XX75Fers7NJPf/oveuSR\nx2RZIXV0dOjSSy+XZVm6885b9G//9mjE+4TB1j1YewfLc+JrI932AIDY86flKrvoArUc/RujOia4\nuBZo8+dfNOxfj23blmEYeuedzSNa15YtmzVz5lknv78kOzuz32OWZWnZst/pJz95oG/Y7WnTemZX\n37TpPZ1//jylp6froosuGXa9hw9X6d1335FhGLJtW7t3f6Rly5appaVDpmlo0aIb5fcP/bFHk8ey\nLL366osD3oc0ceIkXXbZ/GGzn2jmzLO1ZcsHYX/pqq+v0/r1b2r69G8NuVw8+4E0cF8YyecVq/4S\naYYT17tp00ZJUmlpierr6/T222/qmmuuHzbLQH30xRefl23bYffRgbi9vwy2TxhMrLZztJ/3mWfO\n1M9+dr8aGxtVVDReRUU9l66YpqnW1lYVFIxVTk7OkFkiWfdA7R0sz4nD60e67QEAoyNr7Cx1NJcp\n2FHndBSMQFwLtA0bPojbukpK9ujCCz9z0uNWQb7k7/9XheXLX9YttyxWQcFYrVu3VgsXXq39+/cp\nLS1NH3zwN11ySc/lPlu2bB7wPY83ceIkfeMbnw5E0dbWqjvuuCOiGdOjyWOapr72tZvCXkc4zjrr\nHL366ksRvSacy+Xi2Q+kgfvCSD6vSLbPNdd8YdD3iTTDieu95prr+55bvfp1LVhwlfLy8oftKwP1\n0a9//eaIPoOBuL2/DLZPGEys9guRfN6vvfaqNm/epAcffFR1dbUaN65Qubm5mjfvor6BQUKhkHJy\ncnXs2FE1NTUOmSWSdQ/U3sHynCiabQ8AiL3+lzqO/AoZOCNpL3E8duzoycOZhyy9vOsD7dnzsWzb\nlmVZampq1JNP/kq/+91vJPX8JXjhwqu1adNGpaWl6ZRTJmj//n1qbGzU/PkLIs4x1OVMr776Ur8s\nF1xwodavf1O//vV/jVqeodZ9osLCItXUnDx/XKIZsC+Ewcntc6LB1iv1DINeUVGuF1/8kxYvvjPi\nLMNdchdOX5Hc318G6wfx3s5Dfd7z51+hlJQU/eUv67Rly2b953/+X5mmqYKCsfriF6/WSy89r0Ag\noB/+8P6osgy27sHae/nlnxswz4ncvu0BwEv8aXnKKpyr1mNbuNQxQcW9QFu9+nU1NjaqouKQfvSj\nf5UkVVZW6P77f6Bly16I2Xqam5tPmhPKysvRogW3adEtt/V7/POfv+qk199229/FJEdqauqgz91w\nw4264Yb+96x8/vNXjWqeodZ9ouzsHDU3N0X0vuHezxSvfiAN3BfC4eT2OdFg65WkhQuv0cKF10Sd\nZag+KoXXVyT395fB+kG8t/NQn/eYMQV9Z0ZPnK/v2mu/3O/nWbPOi9m6B2tvQcHYQfMcL5ptDwAY\nPdnj5qiz+aCCnQ1OR0EU4lqgHTiwX6mpqZo//wp9+9t39X3Rev/9jRGf4Vi5coUkWxs3vqtvfvNb\nOuOMM/s939LSrKysrE8fsCyFJsd/+NHFi++M+zpjJScnR83NzQM+19nZqccf/4VCoU/n3AgEAjp8\nuFLV1f2HJL/11ps0bdqn9/7Esh/0WrHiFU2bNl1z5px/0nMn9QX0E6s+Gqv+cu21X9bcuRf0/RxJ\nf/njH/+gKVOmqqSkWFdffV3fpMqSe/qBk/uE0Vr3UNseABB/hmEob9LnVHtghUY+VjPiLa4FWiDQ\npgULvqClS5/uNwDC9u1bdf75A182NZDeSVVnzDhdeXn5evDBJVq6tP88PIZh9vvrvJ2ZIXtcwcgb\n4SGhUEg+38DzhqWlpfV9Ue5VXX1Ea9as1F13/UO/xwsLc/rdgxerfiD1fPFfuXK51qxZpbvv/t6A\ny5zYFzA6YtVfThRuf9m1a4cqKsq1ePGdOuecWfrlLx/pN+Ig/WD0DLXtAQDOSEkvUNbYWWqr2SHD\n5FLHRBLXAm3WrNmSpDVrVuq++37a9/iOHdsimkOnoqJc77//ru65595BJ5HNzc1VW1ubxo0rlCSF\nJhRp/uc+E5M5n5LRQKPgBQJtysmJ/VD+seoH0qcTDZeUFA+6zIl9QQpvZEAMzo395cMPt+jss8+R\n1HNP1J49u/u9D/0gNuK57QEAI5NTNE+dLYcU6gp/sDo4L+73oJWXH1RjY0PfJUz79pUqGAxp5syz\ntXPnds2ePXfY9xhqUtVeubm5am1tlSTZ+Tmyx+bHffTAXieeQUoUbW1tA47YFgux6AfhOr4v9IpX\nX0jUbR8Np/tLfX1dv0sefT6fWlpalJOTIyn+/YBtDwBwmmGYyps4X3VlK2UYXOmQKOK+pbq6upWe\nnt43ue5bb73RNzfRrl07wnqPEydV/d737j1pmYkTJ6mqqrLnh5QUaYCRx+Jp5coVWrlyue677wcq\nLd3b77lf/eoxHTt21KFkg6uqqtSECRNH5b1j0Q/C1a8vuNSKFa9ox45tfT8P1V/cyun+Ylm2zOMu\n4QiFgv0uu3NzPxhue7t1H9FrNLc9AGBkUjPHK3PMTNm25XQUhCnuZ9BOP/0MXXHFlfrDH36r7Oxs\nzZ49V8XFe7R06dP68pcXhT1573CTqp511rkqKdnTNxS5k955551B75nbt69UGze+q69//VaHU56s\nuHi3zjrrnLCX9/tTlJaWFtayw/UDKXaTb7upL5xooHvowrnH0o2c7i+FhYXq6Gjve41l2crM/HRQ\nELf2g+G2t5v3Eb0i3fYAgPjKGX+JOlsrZQXbh18YjnNkHrQf/vD+fj9fcsml/X4OZ/LegSZVPd5F\nF12s1157ZeRhY+DgwYMqLi496Z65YDCo6uojKioqcjjhwEpKivXtb/9/YS8/btw43XrrHWEvP1w/\niNXk227qCyca6B66cO6xdCOn+8uFF35Ga9asktTzGZ511tn9nndrPxhqe7t9H9Er0m0PAIgv0+dX\n7imXqKH8TaejIAwJOVH1UJP29hozZozS09PV3Nyk3Fxnb16/7bbbVF7eM4nr8ffMbdz4ji6//Aq9\n8MKzTsYbUGdnpxobG3TqqdOcjjKs4SZSdlNfCEc491i6jRv6yznnzNKGDX/VG2+sVWnpXv3TP/1z\nv+fd2g+G2t5u3kf0csO2BwAMLz13mtJyT1Vn80Gno2AYCVmgDTVp7/EWLbpRq1a9rltuWRyHVIM7\n8Z65JUseUlnZAU2aNKXvnhq3+ctf1unaa693OkZYwplI2S19IRwD9Re3c0t/6T2L88UvDnwZoxv7\nwWDb2+37iF5u2fYAgOHlTbxcNa3uvB8bn0rq4Vwuv/xz2r37I3V0dDgd5aR75oqLd6u0tERr1qxU\nfX2d3n77TTU1NTodU1LPZVUbNryta6/9itNRYsZNfSEcw91j6SaJ1F/c2g8G2t5u3kf0SqRtDwCQ\nfP4MZRddKCO5S4CEl/Rb5zvfuVtLlz7tdIy+e+bGjh2ndevW6pprru/7V1AwVgsWXKW8vHynY0qS\nnntume688x9kOjzyZay5pS+E48T+4maJ1l/c2A8G2t5u3kf0SrRtDwCQssedp7ScKU7HwBCS/qg6\nadJkXXzxZ/XXv653LMPatWv161//l+6442Zdf/0X9ec/r+57bt26NaqoKNeLL/5JjY3O/3X8gw/+\npmnTZvQNYZ5M3NAXBtJ7D92qVa/pww+3aP36N/Xkk78asL+4TSL2F7f1g957agfb3m7bR/RKxG0P\nAOhhGIbTETAEw7btk8cwHyVembT1RF6asHYgXm4/bfdm2yVvt7+wMMfpCAnHq31F4neFtnuTl9vv\n5bZL4R0jk/4MGgAAAAAkCgo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkK\nNAAAAABwCQo0AAAAAHAJCjQAAAAAcIkRFWj79+/XhRdeqK6urljlAQAAAADPirpAa21t1X/8x38o\nLS0tlnkAAAAAwLOiLtB++tOf6vvf/77S09NjmQcAAAAAPMs/3AIvvfSSli5d2u+xiRMn6rrrrtPM\nmTNl2/aohQMAAAAALzHsKCqsL33pSxo/frxs29aOHTs0Z84cPfPMM6ORDwAAAAA8I6oC7XhXXnml\n/vznPyslJSVWmQAAAADAk0Y8zL5hGFzmCAAAAAAxMOIzaAAAAACA2GCiagAAAABwCQo0AAAAAHAJ\nCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkK\nNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0\nAAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQA\nAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAA\nAABwCQo0AAAAAHAJCjQAAAAAcAl/tC/8zW9+o7feekvBYFCLFy/WokWLYpkLAAAAADwnqgJt8+bN\n2rZtm55//nkFAgE9/fTTsc4FAAAAAJ5j2LZtR/qixx57TIZhqLS0VG1tbbr33nt17rnnjkY+AAAA\nAPCMqM6gNTQ06PDhw3rqqadUUVGh7373u1q7dm2sswEAAACAp0RVoOXn5+u0006T3+/X9OnTlZaW\npvr6ehUUFAz6Gtu2ZRhG1EEBAEhGHB8BAMeLqkCbN2+ennnmGd155506evSoOjo6NGbMmCFfYxiG\nampaogqZ6AoLczzbdsnb7aft3my75O32FxbmOB0hoXj5+Cjxu0LbvcnL7fdy26XwjpFRFWgLFizQ\nli1bdOONN8q2bS1ZsoS//gEAAADACEU9zP4PfvCDWOYAAAAAAM9jomoAAAAAcAkKNAAAAABwCQo0\nAAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQktdqOatm27XQMIK4aO+vUbXU5HQMAAESB\nAg1JrSpwQMc6Kp2OAcTVx01/U8gOOh0DAABEgQINSS3FSFFFW6nTMYC4sWxLNR1VTscAAABRokBD\n0jvaUSnLtpyOAcTFkcAhLm8EACCBUaAh6XWFOlUVKHM6BhAXlYH9Mg2f0zEAAECUKNCQ9HymX4cD\nB5yOAYw6yw6phnsuAQBIaBRo8ISjHZUKWgyagOR2qHWvuhkcBACAhEaBBk+wbEvlrSVOxwBG1eH2\ng/JxeSMAAAmNAg2eYBqmDrdzHxqSV1eoQ7Udh52OAQAARogCDZ5R23lEncF2p2MAo6KsdY/TEQAA\nQAxQoMEzDPm0v/Vjp2MAo+JIe7kMg106AACJjqM5PMMwDFW3lzsdA4i5tu5m1XcedToGAACIAQo0\neEpTd62auuqdjgHE1P7Wj+Qz/E7HAAAAMUCBBk8x5VdZ626nYwAxY9u2jgYqZBiG01EAAEAMUKDB\nUwzD0NH2Ctm27XQUICZqO46oJdTkdAwAABAjFGjwnPZgq6o7uBcNyeFgW7H8RorTMQAAQIxQoMFz\nTNOv8ta9TscARsyyQzrWXul0DAAAEEMUaPCkYx1VClpBp2MAI1LRtk9ddqfTMQAAQAxRoMGTQnZI\nB5nYFwmuMrCf0RsBAEgyFGjwJNMwVRUoczoGELXOYLtqOg47HQMAAMQYBRo8q77zqNq6m52OAURl\nf+tHMtiFAwCQdDi6w7NMw6f9rR85HQOIypHAIeY+AwAgCVGgwbMMw9CRQDlzoiHh1HUeVVN3g9Mx\nAADAKKBAg6cFgs3MiYaEc7Blj/wmg4MAAJCMKNDgaT4zReWtpU7HAMJm2SEdaeePCgAAJCsKNHje\n0Y4KdYe6nI4BhOVQ61512/RXAACS1YgKtLq6Oi1YsEBlZQxXjsRl2ZbKWnc7HQMIS2Vgn3yGz+kY\nAABglERdoAWDQS1ZskTp6emxzAPEHXOiIVG0dTertqPa6RgAAGAURV2gPfroo7rllltUVFQUyzyA\nIxq7atTYWet0DGBI+1p2yeTsGQAASS2qAu2VV17R2LFjddlllzFEOZKCz0zRgdaPnY4BDMq2bVW3\nlzP3GQAASc6wo6iwFi9e3Pclobi4WNOnT9eTTz6psWPHxjwgMBLbj72v4vodYS3rM/z66pl3cX8P\nXOlQc6nerfqzfMbww+t3hbr09Zl/rwx/VhySAQCAWIpqIp0//vGPff+//fbb9cADD4RVnNXUtESz\nuoRXWJjj2bZLzra/qbFdbYHwRrwL2e3aWrZV03POjtn6vbztvdx2Kfbt335suzo6LUnD9+duq1O1\nta1K91kxW38kCgtzHFlvIuN3xZvtp+3ebLvk7fZ7ue1SeMfIEQ+zz+U2SBY+w6fyNuZEg/u0B9t0\nrKPS6RgAACAOojqDdrxly5bFIgfgCvVdR9Xc3aDclDFORwH67Gv5SAbTVgIA4Akc8YHj+Ay/9jd/\n5HQMoI9t2zrcXsbVCgAAeAQFGnCCI+0HZdkhp2MAkqTDgYNq7/butfoAAHgNBRpwgk6rU4da9zod\nA5AkHWorkWmO+Gp0AACQICjQgBP0DBZCgQbnBRgcBAAAz6FAAwZQ33VMjZ21TseAx+1r2cHgIAAA\neAxHfmAAPsOvfS0MFgLnWLalw4GDDA4CAIDHUKABg6huP6igFXQ6BjyqMrBf7aE2p2MAAIA4o0AD\nBhG0QzrQ8rHTMeBRh1qL5TMYHAQAAK/xXIG2YsUr2rFjm9MxhvT44/+p1tZWHTiwX8uXv+x0nCEl\nwucZLdMwVRHY53QMeFBzV4NqO6udjgEAABzgmQKts7NTL7/8gl5/fbls23Y6zpB27PhQN9+8SMuW\n/U4LF17jdJwBJdLnORLN3fU61l7ldAx4TGnLDs6eAQDgUZ75BpCWlqavfe0mlZQUOx1lWN/4xq26\n5prrnY4xpET6PEfCZ/i1v+UjFWVMcjoKPCIY6taR9kNOxwAAAA7xzBm0RFJfX6dNm97TM8/8XuXl\nfFFz2rGOSrUHGawB8XGg9WMGpwEAwMM8cwZtKPPnXzTsUNa2bcswDL3zzuaI37+rq0tlZQc0ffqM\nsJa/7ba/kyTNnj1H99xzt5566vdxyRkr4eSU3JE1PIZKW3Zo9phLnQ6CJGfbtsrb9sk0+NsZAABe\nRYEmacOGD0b1/WtqarR+/ZuaPv1bwy77zjtva8eObfrHf7xH6ekZ2rdvb99zo50zVk7MWViYo5qa\nFofSjJxhGKpsK9Os/ItlGj6n4yCJVXeUqyXYwP1nAAB4GH+mjZNwJ5vNysrSVVctlCRVVpZr1qw5\noxkLYeq02nWwtcTpGEhyZS27Kc4AAPA4TxVor776kvbs+VirVr2mDz/c0u+51atf13PPPaNHH32w\n77HKygrdccdNcc04b95F2revVCtXrtC6dWv185//uytzSonxecaKz/DpUGtyD4gCZ7V2N+pYByOG\nAgDgdZ76U+0NN9yoG2648aTHDxzYr9TUVM2ff4W+/e279KMf/ask6f33N2r8+FP6LfvHP/5BU6ZM\nVUlJsa6++jpNnXpqWOuOZCj6L3950YCPR5JT6pmjbNq06Zoz5/yw1x2JcD/PXgPlXLlyhSRbGze+\nq5PYzToAABqpSURBVG9+81s644wzRyVrLDR21amm/bAKMyY6HQVJaG/zThne+psZ4Lh582YN+PjW\nrR95YvnBlgPgLE8VaIMJBNq0YMEXtHTp07rssvl9j2/fvlXnn39h38+7du1QRUW5Fi++U+ecM0u/\n/OUjeuSRx/q9V2dnpx5//BcKhUJ9j4VCXSorO6jq6iP9lr322i9r7twLYp6zs7NTK1cu15o1q3T3\n3d8b8j1XrXpNmzdvGvQSTNu2lZKSon/5l5/I7w+vu4Sbc9Om93TOOedqxozTlZeXrwcfXKKlS/8U\n1jqc4DP92teykwINMdcd6lJVe1nYl0IDAIDkRYEmadas2ZKkNWtW6r77ftr3+I4d23T77Z+eAfrw\nwy06++xzJEmFhUXas2f3Se+VlpbWd2arV1dXs5599gXdddc/xCVnJHOUXXfdV3TddV8ZUa5oc1ZU\nlOv999/VPffcq8mTp+ro0SMnvZfbHO2oVCDYokx/jtNRkERKW3bKsoIyGL0RiKtIzyB5bXkAzvBM\ngdY79PuJlxr2DvN+6NBBNTY29J3R2revVMFgSDNnnq2dO7dr9uy5qq+v63eJns/nU0tLi3JyYvdl\nPRY54yEWOb/61a+rvb1dkrRz53ZdfPFn45J9JAyZKmnapvPHfs7pKEgStm2rom0fxRkAAJDkoQJt\nw4YPtG7dGmVkZGj79m2aN+8iXXrp5X3Pd3d3Kz09XT5fzzDqb731hmbOPEtSz6WNs2fPlWXZMs1P\nh1kPhYLy+WL7pWrDhg90+HCVVq9+XaeddrpsW7ryyqsiyhkPscjp8/mUnZ2tlpYWrV//ppYseSgu\n2UfCMAxVBQ7ovPzPyu9LcToOkkBFW6kCwVb5TKZwAAAAHhrFsaqqUkuXPq358xfooosu1tNPP9Xv\n+dNPP0NXXHGl/vCH3+qll57/pIDwa+nSp3X11ddJkgoLC9XR0d73GsuylZmZFdOctm3r4Ycf0K23\n3q45c87XqlWvRZwzHiLJ+cwzzwya07IsLVv2O/3kJw9ozJgxccs/EkE7pNKWnU7HQJIoa91DcQYA\nAPp45gzapEmT9cQTv5UklZbu1fz5V5y0zA9/eH+/ny+55NJ+P1944We0Zs0qST33T5111tlhrTsl\nJUVpaWlhLbtt21bl5OQqMzNLmZlZeuSRX0acMx4iydk7UfVAOZcvf1m33LJYBQVjtW7dWi1cePWo\nZx8p0zBVHtirmXnny+SyNIxATfth1Xcek8/0zK4YAAAMw1PfCrKysvXuu3/V4cNVuueeH0b8+nPO\nmaUNG/6qN95Yq9LSvfqnf/rnsF5XVFSkW2+9I6xlS0qK9f+3d69BUpUHGsefc7pnhoG5MMiMF7xm\nEWIyBgWjhkBcECJ4+aCbUgww0eRDUtmkiGIAxYIYQ01tyiIpa6HCYmkRtaIWcV0qVVlXgnEJMSAj\nAwxycRCQa5yBufXc+nLe/UBkQQaZabrPe7rP//eJOXV6zvMyPfP2033OexKJuP7617+oublJV1xx\npW68cdyAs356jzJjjDzP09ixN53/QQOQiZxvv71Wv/nNv+v55/9DkjR69HU5UdAkqSsZ08ede3R1\nyRdtR0EO+7BjG+UMAACcIVSvDKLRqCZMuE29vXEtWrTgrCXy++P73/9XSdLUqdkpEp6XUk9Pj8aP\nnyDP8/TQQw/qt799dcDf51z3KMuUTOScNGmKJk2acv4dAyjiRPVRxwcUNKTt5I2pD8l1OL0RAAD8\nv1CenzVq1Ght2LBera2ttqOcparqYlVVXSxJcl1XsVhMHR0dllOdLVdyZlN74riOdX9sOwZy1K62\nLdyYGgAAnCU0rw7WrPlPPfnkfEnS8ePNGj68UmVlZZZTnW3cuK/qxInjkqRUKqXS0rKMLuOfKbmS\nM5tcJ6oP21ksBAPXk+rWkS5uTA0AAM4WmlMcJ068TQUFBfrTn/5Hmzdv0jPPPCvXDV4/HTbsIk2d\nOk2rV7+irq6usxYECYpcyZltzb1HdaL3Ew0rqrIdBTlkV9v7MpKoZwAA4LNCU9AqKoZp+vS7JUm3\n3/5Ny2k+35133mM7Qr/kSs5sijhR7Wmr161VwX5OITiSqYQOdzby6RkAAOhT8D5CAnLMsZ6DiiWC\ndz0jgmlPx1YlTdJ2DAAAEFAUNOACOXK0s+192zGQAzyT0oHOXXK4fx4AADgHXiUAF8hxHB3t2q/u\nZKftKAi4xvbt6k312I4BAAACjIIGZICRtLOtznYMBJhnPO2L7eK+ZwAA4HOlVdCSyaTmzZunmTNn\n6v7779e6desynQvIKY7j6FDXXj4dwTnt79iprlS47hUIAAAGLq2CtmbNGlVUVOjll1/WypUr9fTT\nT2c6F5BzjDHa2bbZdgwEkDFGjbEGRZzQLJwLAADSlNarhenTp2vatGmSJM/zFI3yogNwHEcHOxv1\npfKbVBgZZDsOAmR/bJe6kh2c3ggAAM4rrWZVXFwsSYrFYpozZ44eeeSRjIYCMuWByd9W0kuctf3f\n/rC4z/3n3/1Un9v7v7/RE84vtL2+sc/9x42r7nN7XV1DVvY/135h4Pf/9bn2N8aosaNBj9/ziz73\nz8Zz8RdrFvS5DwCcLih/J23sH+b5UQr2zybb++fCzz7tj76OHj2qH/3oR5o1a5buvPPOfj2msrI0\n3cPlvDCPXbI3ftd15Jiztw8ZXNjn/ue6d3D/93eUUkrlFYUqjBZJOnPsrtv3Ac71/3Oh+9t+3tk8\nvt//133tX1lZqsaWHTKFXRl4bvV//8HFRRo+vETF0SF9fxMEju3fVdvCPP4w/5387OP8zBOE5xw/\nezt5gvCzPx/HGNPHy9fP19zcrJqaGi1atEi33nprvx/X1BTOC+QrK0tDO3bJ7vg/aHlPjTF/3ykx\nxujqktEaM+zrof7Zh3ns0snxf/JJu9YeXa3uVMzXYye8Xt11eY0GRQb7etxP5cLkFzRh/10J6/gZ\nezjHLoV7/GEeu9S/OTKtRUJWrFih9vZ2LV++XLNnz1ZNTY3i8Xg63wrIO47j6OPODxVnRcfQO9C5\nW53JNtsxAABADknrFMeFCxdq4cKFmc4C5A3PePqgbbNGXDLddhRYYozRnvatLAwCAAAGhBtVA1nw\n6ado3Yku21Fgye6WbepMttuOAQAAcgwFDcgSY4zqm961HQMWeMbTzuP13PcMAAAMGAUNyBLHcbSv\nfY+6kuG9EDasPmzfpq6kvwuDAACA/EBBA7LIMVJD60bbMeCjpJfQ3o4dinDtGQAASAMFDcgix3F0\ntGu/2uLHbUeBT3a1va+4xwqeAAAgPRQ0IMscJ6KG1k22Y8AH8VSP9sV2ynX40woAANLDqwjAB009\nh9XUfcR2DGRZQ+smecazHQMAAOQwChrgA9eJaEfbJhljbEdBlsQSbTrY9aEcx7EdBQAA5DAKGuCT\n1t4mHez80HYMZElD60Y5/EkFAAAXiFcTgE9cN6qdbe9zClweauo5qmPdH9uOAQAA8gAFDfBRdyqm\nPe31tmMgg4wx2tGyUS7L6gMAgAygoAE+cp2IGju2K55iGfZ8caBzj1rjTbZjAACAPEFBA3yW8lLa\n3vo32zGQASmT1K62Orlu1HYUAACQJyhogM8cx9Ghzr1q6W22HQUXaGdrnXpS3bZjAACAPEJBAyxw\nHFfbW95l2f0c1pXs0EcdH3BTagAAkFG8sgAsORH/uz7u3GM7BtK09cQGGVGwAQBAZlHQAEtcJ6IP\n2t5T0kvYjoIBOtp1QH/vPshNqQEAQMZR0ACL4qle7WjdaDsGBsAznhpa/8bCIAAAICsoaIBFjuNq\nf2y3WuMsGJIrdrZtVmcyZjsGAADIUxQ0wDLHcVV/4i8sGJIDYok27W1vYGEQAACQNbzKAAKgtbdJ\nH8U+sB0D57HlxHqJ684AAEAWUdCAAHDdqHa2bVZPsst2FJzD/thuNfcetR0DAADkOQoaEBApL6Ut\nLettx0Af4qke7WjZqIjDwiAAACC7KGhAQDiOo2PdB3Wo8yPbUfAZW06sV9IkbccAAAAhQEEDAiTi\nRLSt5V3FU722o+AfDnV+pKNd+7nnGQAA8AUFDQiYhNer+pa/2I4BSYlUXNtb3+WeZwAAwDcUNCBg\nHMfRkc6PONUxALa0rOfTTAAA4CsKGhBArhvVtpYN6k312I4SWodijTrctY9TGwEAgK8oaEBAJbyE\n3j/+Z9sxQqkn1a1tLe8q4kRsRwEAACFDQQMCynEcHes5qI86dtiOEirGGG1uXqeESdiOAgAAQoiC\nBgRYxIlqR+t76oi32o4SGo3t29Tcc4RTGwEAgBUUNCDgjIzeO/4necazHSXvtfQ2a2f7+6zaCAAA\nrEmroBljtHjxYs2YMUM1NTU6ePBgpnMBOE17olVbT2ywHSOvJVMJvXd8re0YAAAg5NIqaGvXrlU8\nHtcrr7yiuXPnqra2NtO5AJzGdVwd6NytQ7FG21HyVt2JP6s72WU7BgAACLm0ClpdXZ0mTpwoSRoz\nZowaGhoyGgrA2VwnovrWv3I9Whbs7WjQ0e4DXHcGAACsS6ugxWIxlZaWnvo6Go3K87g+Bsg2z6S0\nsXmtkh4rDGZKc88x7Wh9Ty5L6gMAgABI60r4kpISdXZ2nvra8zy5LuuNIHiMjIwx9o5vMn/8WLJN\ndcf/rK8Ovz2j3zfTPOMFfmGTeKpHm5rXZuU5ko2fff8PbuewyE3jxlX3ub2uru+zY/Jp/3PtAwA2\npVXQxo4dq7ffflvTpk1TfX29Ro0a1a/HVVaWnn+nPBXmsUv2xn9j2ViN6LrEyrGzKZ7q0dqml4L9\nOvy47QDnY1RWWKHxV3/DdpCMc+TosqHDudF2DrE5R7hu36f2nitTNvY//d9+5gnC3ByEDLaEeexS\nuMcf5rH3h2PSeIvXGKOf/exn2r17tySptrZW11xzzXkf19TUMfCEeaCysjS0Y5fCPf5sjr2p+7De\nbXpTCuh1U0MGF6qzK247xjkVR4Zo0iX3KZqlJfXD/rzHwIT1uSLxu8LYwynM4w/z2KX+zZFpvTJx\nHEdPPfVUOg8FkCGVxSN0fcXXtK1lgxw+KRmQqBPV1yrvyFo5AwAASBcXjgE57JrS6/SF0mp5Xsp2\nlJzhSLp5+FSVFJTbjgIAAHAWChqQ46qH3qJLB18V+AU5gsAzKd1QMVHDB+XfdYkAACA/UNCAHOc4\njr46/HYNK6yyumJl0HkmpS+X36wrSkbajgIAAHBOFDQgD7iOq/FV01VaMJSS1gfPpDSy9HpdW/4V\n21EAAAA+F1fIA3ki6kY1oeouvfP3/1Jj+3Y1xrYrlmhVScFQjSy9XiMGf8F2RCs8L6WrS69TdcUt\ntqMAAACcFwUNyCOFkSINjpZqS8v/ntrWkWjRlhMnvw5bSfO8lK4YMlJjKsbbjgIAANAvnOII5Jm1\nR1/rc3tjx3afk9jleSldWXKtxl50m5yA3isOAADgs/gEDcgzR7sO9Lk9lmj1OYk9nknpqpIv6oZh\nX6ecAQCAnMInaECeuXTwVX1uLykY6nMSOzyT0siyr+jGiyZQzgAAQM6hoAF5ZvqIWX1u/6eSap+T\n+M8YT18uv1nVQ2+2HQUAACAtnOII5Jmbh98uSfrvwy/rSPd+XVZ8taZd9m0VuIU60LlHrhOxnDA7\nHDkae9EkXT4kXAuhAACA/EJBA/LQzcNvP1XUTlcSHaqdbZulPDr1zxijosgg3TJ8qiqKKm3HAQAA\nuCAUNCBEri3/isoLh2nz8beV8BI5f42WZ1KqKKrSrcO/qaLIINtxAAAALhjXoAEhU1V8uSZf8i+q\nKBouz6Rsx0mbZ1IaWXq9vlF1D+UMAADkDQoaEEKDooM1seoejSq7QcYY23EGxBijIneQxldOU3XF\nLTn/KSAAAMDpOMURCCnHcfSloTfp0uKrtOXEerUnWuQ6wX7PxhhPI4Z8QTdUTFDULbAdBwAAIOMo\naEAeGzeu76X16+oaTv27oqhSky65V7vb63XvN+6VZCSd+anUv/1hcZ/fZ/7dT/W5PfP7GzlyVRgp\nUsSJnpH/dKeP91z7AADQn/kxn/dnjgw2ChoAOY6jL5bfqOLIYMW9XqVMUp8taXacLIsFbpGiboGc\nQGQCAADIHsf4eAFKU1OHX4cKlMrK0tCOXQr3+HN17O3xFn3Q9p6OdX8sR25a13kNGVyozq54Wsf3\njKcCt0BXDhmt68rHKerm3ntJufqzz4TKylLbEXJOWJ8rEr8rjD2cwjz+MI9d6t8cmXuvegBkXVlh\nhW6t/KY6E23a1b5Fx7oOKGGSWb9GLWWSKo2W6/Ih1+rasusVcfgTBQAAwoVXPwDOaUhBucZd9M9K\nDUtqX8dOHes+oObeY5KcjJW1lJdUoVukqkGX64qSkbp40BWszAgAAEKLggbgvCJOVCPLrtfIsuuV\n8OI61LlXzb1H1BY/ro5Em4yMIk70vMXKGKOkSajALVR5wTCVF1ykS4qvVFXx5YFfQRIAAMAPFDQA\nA1LgFuqa0ut0Tel1kqSkl1BL/BO1xJvVm+xS3MSV9BIqGVKoDq9HrhNRgVOgQneQiqNDNLzoUpUU\nDKWQAQAA9IGCBuCCRN0CVQ4aocpBI87YHvaLgAEAANLBW9gAAAAAEBAUNAAAAAAICAoaAAAAAAQE\nBQ0AAAAAAoKCBgAAAAABQUEDAAAAgICgoAEAAABAQFDQAAAAACAgKGgAAAAAEBDRdB4Ui8X02GOP\nqbOzU4lEQgsWLNANN9yQ6WwAAAAAECppFbQXXnhB48ePV01Njfbt26e5c+fq9ddfz3Q2AAAAAAiV\ntAraww8/rMLCQklSMplUUVFRRkMBAAAAQBidt6CtXr1aq1atOmNbbW2tqqur1dTUpHnz5mnhwoVZ\nCwgAAAAAYeEYY0w6D9y9e7cee+wxzZ8/XxMmTMh0LgAAAAAInbQKWmNjo3784x/r17/+tUaPHt3v\nxzU1dQz0UHmhsrI0tGOXwj1+xh7OsUvhHn9lZantCDknrM8Vid8Vxh5OYR5/mMcu9W+OTOsatKVL\nlyoej2vJkiUyxqisrEzLli1L51sBAAAAAP4hrYK2fPnyTOcAAAAAgNDjRtUAAAAAEBAUNAAAAAAI\nCAoaAAAAAAQEBQ0AAAAAAoKCBgAAAAABQUEDAAAAgICgoAEAAABAQFDQAAAAACAgKGgAAAAAEBAU\nNAAAAAAICAoaAAAAAAQEBQ0AAAAAAoKCBgAAAAABQUEDAAAAgICgoAEAAABAQFDQAAAAACAgKGgA\nAAAAEBAUNAAAAAAICAoaAAAAAAQEBQ0AAAAAAoKCBgAAAAABQUEDAAAAgICgoAEAAABAQFDQAAAA\nACAgKGgAAAAAEBAUNAAAAAAICAoaAAAAAAQEBQ0AAAAAAoKCBgAAAAABQUEDAAAAgICgoAEAAABA\nQFDQAAAAACAgKGgAAAAAEBAXVND27t2rm266SfF4PFN5AAAAACC00i5osVhMv/zlL1VUVJTJPAAA\nAAAQWmkXtEWLFunRRx/VoEGDMpkHAAAAAEIrer4dVq9erVWrVp2x7bLLLtNdd92l0aNHyxiTtXAA\nAAAAECaOSaNh3XHHHbr44otljNHWrVs1ZswYvfjii9nIBwAAAAChkVZBO93kyZP15ptvqqCgIFOZ\nAAAAACCULniZfcdxOM0RAAAAADLggj9BAwAAAABkBjeqBgAAAICAoKABAAAAQEBQ0AAAAAAgIHwp\naN3d3frhD3+oWbNm6bvf/a4++eQTPw4bGLFYTD/4wQ80e/ZszZgxQ/X19bYj+e6tt97S3Llzbcfw\nhTFGixcv1owZM1RTU6ODBw/ajmTF1q1bNXv2bNsxfJVMJjVv3jzNnDlT999/v9atW2c7kq88z9MT\nTzyhBx98UDNnzlRjY6PtSDkhzHMk8+NJzJHhEsb5UQr3HDnQ+dGXgvbaa6+purpaL730ku655x6t\nXLnSj8MGxgsvvKDx48frxRdfVG1trX7+85/bjuSrJUuW6Fe/+pXtGL5Zu3at4vG4XnnlFc2dO1e1\ntbW2I/nuueee05NPPqlEImE7iq/WrFmjiooKvfzyy1q5cqWefvpp25F8tW7dOjmOo9/97neaM2eO\nli5dajtSTgjzHBn2+VFijgzbHBnW+VEK9xw50Pkx6keo73znO6eW4j9y5IjKy8v9OGxgPPzwwyos\nLJR08t2DoqIiy4n8NXbsWE2dOlWvvvqq7Si+qKur08SJEyVJY8aMUUNDg+VE/rvqqqu0bNkyzZs3\nz3YUX02fPl3Tpk2TdPLdsmjUlz+xgTFlyhRNnjxZknT48OHQ/a1PV5jnyLDPjxJzZNjmyLDOj1K4\n58iBzo8Z/59ZvXq1Vq1adca22tpaVVdX66GHHtKePXv0/PPPZ/qwgfF5429qatK8efO0cOFCS+my\n61xjnz59ujZt2mQplf9isZhKS0tPfR2NRuV5nlw3PJd8Tp06VYcPH7Ydw3fFxcWSTj4H5syZo0ce\necRyIv+5rqvHH39cb731lp599lnbcQInzHNkmOdHiTnyU2GfI8M6P0rMkQOaH43P9u7da6ZMmeL3\nYa3btWuXufvuu8369ettR7Fi48aN5tFHH7Udwxe1tbXmj3/846mvb7vtNnthLDp06JB54IEHbMfw\n3ZEjR8x9991nXn/9ddtRrGpubjaTJk0y3d3dtqPklDDOkWGfH41hjgybsM6PxjBHGtO/+dGXtytW\nrFihN954Q5I0ePBgRSIRPw4bGI2NjfrJT36iZ555RhMmTLAdB1k2duxYvfPOO5Kk+vp6jRo1ynIi\ne8w/TtsKi+bmZn3ve9/TT3/6U91777224/jujTfe0IoVKyRJRUVFcl03NO+KX4gwz5HMj+HDHHlS\n2OZHKdxz5EDnR19O/vzWt76l+fPn6/e//72MMaG7IHTp0qWKx+NasmSJjDEqKyvTsmXLbMdClkyd\nOlUbNmzQjBkzJCl0z/fTOY5jO4KvVqxYofb2di1fvlzLli2T4zh67rnnTl1jk++mTZumBQsWaNas\nWUomk1q4cGFoxn4hwjxHMj+GD3PkSWGbH6Vwz5EDnR8dE8YKDwAAAAABxLknAAAAABAQFDQAAAAA\nCAgKGgAAAAAEBAUNAAAAAAKCggYAAAAAAUFBAwAAAICAoKABAAAAQEBQ0AAAAAAgIP4PZa5+byCS\n7zcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a95cb9c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mrkqnnOt0HHhEUtWCbdtasWKFrrvuOt18881qaGhIda6sYnX3ynegieIMaeFr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a957c93d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mrkqnnOt0HHhEUtWCbdtasWKFrrvuOt18881qaGhIda6sYnX3ynegieIMaeFr\nOBTz8dw3t6Q5CQAAmc8wfOpt2abelnedjgKPSKpieOmllxQKhfTII4/on//5n3XPPfekOlf2sG1Z\n2+tkcN8Z0sQI9MV83GxpT3MSAACyg2GY6jqyUYGOXU5HgQckVaBt3rxZS5YskSQtWrRI777LLwoj\nMQ8elt3e5XQMeIhdWBDzcWvypDQnAQAgexgy1HXwNfV3NzodBVkuqXvQenp6VFJS8uGL+P2yLEum\nSy/hW7x4YczHN2+OXVimbPkNW+Tbd0DKH/42n/GVG2Iuv/3nf4j5+HiXH2k5ZKfozKkya4+fDy30\n0bMdSAMAQHbpaHxZFXOuUG5BldNRkKWSKtCKi4vV29s79O94i7OqqpIxl5kIpiEpcvyw4xWHm2Iv\nP8IQ5YkuP+nwEamiWJJUVJj/4fK+2O9V0eTS2K8/zuVHWi6djm6/16S97ZNLZZUUyNq5X+rplTFl\nsvyXnq/8s09Lbw4595l3C6+3H/Hzel9xqv0F/skyQ9WOrHtQWZ6jq3dUJrc90v6GfOEpMn25ST3/\nSO/Yy0wY21b51LOUm1/uWASv7/PGYthJTO7w4osvat26dbrnnnu0detW/exnP9Mvf/nLMZ/X3Nyd\nVMjxMprblLOjLr2DdFiWwmeeKntSmaqqShxruxt4uf203Zttl7zdfg68ifNqX5H4rND2zNVx4FX1\nte+UYfoSfm5hUZ4CvcEJSDU224qqfNalKiid48j6s2Hbj0c8x8ikzqB98pOf1Pr163XddddJEoOE\nHMu2Fa2qkD2pzOkkAAAAmABl05YoGu5RqPeQDOa5RQolVaAZhqHvf//7qc6SPUxT0ZPmOJ0CAAAA\nE8QwDE2aeZla9z6tSLCLEbuRMpT7qWZZisyaJuXmOJ0EAAAAE8j0+VUx5yr5/N691x6pR4GWYnZh\ngayZU52OAQAAgDTw+QtUPusyicsckSL0pFSyLEVOnC1xihsAAMAzcgsmq3zGx2Ur4bH3gONQoKWK\nbStaUS67goFBAAAAvCa/ZJZKq/9Gth17+iUgXhRoqWIYip402+kUAAAAcEjR5IUqnHSqbIsiDcmj\nQEsF21ZkapVUwA2iAAAAXlY69ULlFk9VElMNA5Io0FLC9vtlzZnhdAwAAAA4zDAMlc/8pHy5RU5H\nQYaiQBuvaFTR2dMkf1JTygEAACDL+Hy5qpj1KRmmz+koyEAUaONkFRfJmjbF6RgAAABwEX9eucqm\nL5VtW06p7gu9AAAgAElEQVRHQYahQBsPK6rovJkMqw8AAIDj5JfMUkn1ubItijTEjwJtHKxJ5bIr\nyp2OAQAAAJcqrlqk/LI5nElD3CjQkmRbliInznI6BgAAAFyufMZS+fMmMbIj4kKBlgzbllVdKRUV\nOp0EAAAALmcYPk2afZkMX67TUZABKNCSYRiKcvYMAAAAcfLnFKt8+lLZ4iwaRkeBlijbVmRqtZTL\nLyAAAACIX37JDJVULZZtRZyOAhdj8q4EDUxKPd3pGAAAAEjS4sULYz6+efO7E7580eQzFfV3KhCo\nk2EMnCu5/Avfj7n8C4+uiPn4+Ja39eb6S2MuB3fgDFoiLEvRGScwKTUAAACSYhiGqk+8TL7cEqej\nwKWoNBJg5+XKmjnV6RgAAAAYh5HOfKVreZ8vR5NmXqrWPc9Iskc88zWS8SxvW9GEnov04wxavKJR\nRWdOZVJqAAAAjFtOfoVKp14g26ZgwnAUaHGyiwplTZvidAwAAABkicJJp6ig/BQmscYwFGjxiFqK\nzJrO2TMAAACkVNm0i+TPm+R0DLgIBVocrJIi2dUVTscAAABAljEMU5NmXirD8DkdBS5BgTaWqKXo\nbM6eAQAAYGL480pVOu1CLnWEJAq0MVllxbInc9oZAAAAE6eg7EQVTuJ+NFCgjc6KKjp7htMpAAAA\n4AGlUy9UTl650zHgMAq0UVhlZbIrypyOAQAAAA8wDFPlMz8hGXxF9zK2/kgsS9E505xOAQAAAA/x\n55Wr9ITzmR/NwyjQRmCVl8ou5+wZAAAA0qtw0nzll87jfjSPokCLZXDkRgAAAMABZdM+Jl9OsdMx\n4AAKtBisSaWyy0udjgEAAACPMn1+lc/4uNMx4AAKtGNx9gwAAAAukFtYraKqs7gfzWMo0I7B2TMA\nAAC4RfHks5RbeIJs23Y6CtKEAu1oVlTR2YzcCAAAAHcwDEPlMy6RYeY4HQVpklSB1tPTo6985Su6\n6aabdN1112nr1q2pzuUIq4yRGwEAAOAuvpxClU27gEsdPSKpAu03v/mNLrjgAj388MO65557dPfd\nd6c6V/pFLUVncfYMAAAA7lNQdqLyy05k6H0P8CfzpFtvvVW5ubmSpEgkory8vJSGcoJVWiy7otzp\nGAAAAEBMZVOXKBQ4LDvS53QUTKAxC7THH39cK1euHPbYPffco4ULF6q5uVl33nmnvv3tb09YwLSI\nRhWdNdXpFAAAAMCITJ9f5dMuVtv+52UYDCWRrQw7ySFhamtrdccdd+ib3/ymLrroolTnSimrqVmR\nt9+XYcbuyEZxoXwXni3DMNKcDAAAAEhMS/16dTRtk2H6En6uZUU07eQrVTRp7gQkQyokdYnjrl27\n9LWvfU0PPPCA5s+fH/fzmpu7k1nduBltAeUEQlKsAi0aVXj6NNktPRO2/qqqEsfa7gZebj9t92bb\nJW+3v6qqxOkIGcerfUXis0LbvWm87bfzFyoUrVO0ryvx51pRtbb1KBBx5v1n2499jEyqQLv//vsV\nCoX0wx/+ULZtq7S0VP/1X/+VzEs5zi4skD1lstMxAAAAgLgYhqmyGUvVuucZcf1X9kmqQPvZz36W\n6hwTrr23W5NKjhlC37IUnT5FSvDSxj17dquhoV41NTt00023qLCwKIVJndXR0aHy8uweLKW9vV2T\nJk1K2/roL+6U6n5w7HaWsvssUiZvewDIBrn5lSqefJZ6mjfLMBK/1BHu5Ym7C59/+UXVtxw57nE7\nL1fWtCkJv966dS9pwYKFWrDgDL3++mupiOgaLS3N+t///R+nY0yYtWvXqKFhf1rXSX9xn4noB9m8\nnWPJ1G0PANmkuOos5RRUOR0DKeb73ve+9710rSwQCKVrVUO2b9+mxr17ddm804bOlD218TX1B0Oq\nOmOB7PJSrVmzWjt31ug3v/mVZs+eo8rKylFf85xzzlVhYZG2bn1bM2bM1JQpJ4y6fFFR3ohtX736\nSQWD/TrhhA9HkUw0T7JirbuiolINDfVqajqkWbPmpGQ9o7U/nbZv36bGxgZ94hOXxf2c8W6foqI8\nzZ9/RkL9ZSSjrfenP71fc+fOU1FRcVKvPZZY74M0en9xy3Y/Vqx+kIrP4bH7hXnzZifV/hdfXKsD\nBw7omWeeVCQS0axZsyVJBw8e0COP/F5dXZ3as2e35s07MeHXHs1I7R0pz1jbHolx42clXdy6r0gH\n2u7Ntkupa79hGMotnKpAe038T7Jt5ZfNU06eM1dBsO3HPkZm9Rm0SCSi3/3ut/r81ddIkoLhsP73\njVf09Mb1sk1D1syp2rDhDZ1++gJdffUyXXnl1frBD1bE9dp9fX0KBHp15plnjbrcnj27Yj4eDAb1\nxBOP6tlnn9bRA2kmmycRI6170OWXX6Xnn1+j/v7+lK/bKYN94XOfuz6u5VO9feLtLyMZbb27dtVp\n/frXZVlJDcg6Yh+Vxu4rUmb1l2P7gRPbebT3+8CBRq1c+ZA+9rGlOu+88/Wb3/y3JMm2bd1zz926\n8ca/06JFZ+v555+NK0+86x6pvSPlGZRJ2x4AspU/r0zF1efItqNOR0GKZHWB9sILa3TxxZfI/GD0\nxrycHH3+gqU6ccpURSvKJNNUQ0O9Vq9+UpI0Y8YsHT58KK7X/utf39AXvnCjDhxoHHW5V155Oebj\neXl5+uxnv3Dcr+DJ5knESOs+2tVX/x899lj2XL50bF8YS6q3T7z9ZSQjrTcSiaip6ZCqq6uTel1p\n5D4qxddXpMzpL8ftExzYzqO939Onz9DPfvYrSVJd3U5ddNHHJElbtmxWSUmpCgsLVVFRqXvv/Ulc\neeJd90jtHSnP0TJl2wNANiuqPEM5BYnftgN3SmqQkEzx/PNrdP/9/yl1B4b/wTCGRm7827/9nPr6\nBmZjf+edrfrIRz46tNgrr/xZhmGotrZG8+adqLfe+qu+9a3v6umnH9dLL72o1auf1A033Kzp02eM\nmCHRudUSybNx4wbddVfqz7BJ0kc+8lH9+te/1E033Tohr59uQ31hnBLtL/ff/6OE+kui612//lVd\ndNHFevTR3w9bPpG+kor5/zKlv8TbD1KxXzjrrNNivvZY73dRUbFef/0vOnjwgG6//RuSpNraGoXD\nIb3xxutqaWnWzJmzdPbZixPeJ4y07tHaGyvP0TJl2wNANjMMQ+XTL1bL7qckWU7HwThlbYF26NBB\n5ecXKD8/f3iBZtuy8/Ik/0DTfT6fiouL1d3drXXrXtKKFT+UJO3bt1eLFp2jvLw8PfbYI7r55i+q\nrGxgFMhly67VsmXXxpUj0XnAk8kzEXw+n6ZPn673339Pp522IK7nhEIhHTjQqLlz501YrmQM6wvj\nNNH9JZH17t27R9Onz5TPN3zkpkT7SpJz1R+Xz+39JZF+MJHbeaz32+/366KLLlYwGNJ3v/svuvfe\n+2VZUfX39+uCCy6SZVm65Zbr9W//dl/C+4SR1j1Se0fKc+xzE932AIDU8+eVqrj6HHUf/iujOma4\ntBZoS5acN+avx7ZtyzAMvfrqxnGta9OmjZo//9TjX1+SXVw47DHLsrRq1a/1ne/cPTTs9pw5A7Or\nb9jwhs4+e7Hy8/N13nnnj7negwcP6PXXX5VhGLJtWzt2vKtVq1apu7tfpmlo2bJr5feP/rYnk8ey\nLD311GMx70OaNm26LrxwyZjZjzV//mnatOmtuL90tbW1at26lzR37pdGXS6d/UCK3RfG836lqr8k\nmuHY9W7YsF6SVFdXq7a2Vr3yyku64oqrx8wSq48+9tgjsm077j4ai9v7y0j7hJGkajsn+36fcsp8\nfe97d6mjo0PV1VNUXT1w6Yppmurp6VFFRaVKSkpGzZLIumO1d6Q8xw6vn+i2BwBMjKLKherv2qtI\nf6vTUTAOaS3QXnvtrbStq7b2fZ177t8c97hVUS75h/+q8PTTT+j665eroqJSL774gi677HLt3r1L\neXl5euutv+r88wcu99m0aWPM1zzatGnT9fnPfzgQRW9vj26++eaEZkxPJo9pmvrsZ78Q9zriceqp\np+uppx5P6DnxXC6Xzn4gxe4L43m/Etk+V1zxiRFfJ9EMx673iiuuHvrb888/q6VLL1VZWfmYfSVW\nH/3c565L6D2Ixe39ZaR9wkhStV9I5P1+5pmntHHjBv3gB/eptbVFkydXqbS0VIsXnzc0MEg0GlVJ\nSamOHDmszs6OUbMksu5Y7R0pz7GS2fYAgNQbfqnj+K+QgTOy9hLHI0cOHz+cedTSE9vf0vvvvyfb\ntmVZljo7O/Tggz/Vr3/9S0kDvwRfdtnl2rBhvfLy8nTCCVO1e/cudXR0aMmSpQnnGO1ypqeeenxY\nlnPOOVfr1r2kn//8Pycsz2jrPlZVVbWam4+fPy7TxOwLcXBy+xxrpPVKA8OgNzTU67HH/kfLl9+S\ncJaxLrmLp69I7u8vI/WDdG/n0d7vJUsuVk5Ojv785xe1adNG/fjH/59M01RFRaU++cnL9fjjjygQ\nCOgb37grqSwjrXuk9l500cdi5jmW27c9AHiJP69MRVVnqefIJi51zFBpL9Cef/5ZdXR0qKFhv775\nzX+VJDU2Nuiuu+7QqlWPpmw9XV1dx80JZZWVaNnSG7Xs+huHPf7xj1963PNvvPHvUpIjNzd3xL9d\nc821uuaa4fesfPzjl05ontHWfazi4hJ1dXUm9Lrx3s+Urn4gxe4L8XBy+xxrpPVK0mWXXaHLLrsi\n6Syj9VEpvr4iub+/jNQP0r2dR3u/J02qGDozeux8fVde+elh/1648IyUrXuk9lZUVI6Y52jJbHsA\nwMQpnrxIwa59igTbnY6CJKS1QNuzZ7dyc3O1ZMnF+vKXbx36ovXmm+sTPsOxZs1qSbbWr39dX/zi\nl3TyyacM+3t3d5eKioo+fMCyFJ2R/uFHly+/Je3rTJWSkhJ1dXXF/FswGNQDD/xI0eiHc24EAgEd\nPNiopqbhQ5LfcMMXNGfOh/f+pLIfDFq9+knNmTNXixadfdzfjusLGCZVfTRV/eXKKz+ts846Z+jf\nifSX3/3ut5o5c5Zqa2t0+eVXDU2qLLmnHzi5T5iodY+27QEA6WcYhsqmf0wte1Zr/GM1I93SWqAF\nAr1auvQTWrnyoWEDIGzdullnnx37sqlYBidVnTfvJJWVlesHP1ihlSuHz8NjGOawX+ftwgLZkyvG\n3wgPiUaj8vlizxuWl5c39EV5UFPTIa1du0a33voPwx6vqioZdg9eqvqBNPDFf82ap7V27XO67bav\nxVzm2L6AiZGq/nKsePvL9u3b1NBQr+XLb9Hppy/UT35y77ARB+kHE2e0bQ8AcEZOfoWKKheqt3mb\nDJNLHTNJWgu0hQvPlCStXbtG3/rWd4ce37ZtS0Jz6DQ01OvNN1/X7bffOeIksqWlpert7dXkyVWS\npOjUai352N+kZM6nbBRrFLxAoFclJakfyj9V/UD6cKLh2tqaEZc5ti9I8Y0MiJG5sb+8/fYmnXba\n6ZIG7ol6//0dw16HfpAa6dz2AIDxKalerGD3fkVD8Q9WB+el/R60+vp96uhoH7qEadeuOkUiUc2f\nf5reeWerzjzzrDFfY7RJVQeVlpaqp6dHkmSXl8iuLE/76IGDjj2DlCl6e3tjjtiWCqnoB/E6ui8M\nSldfyNRtnwyn+0tbW+uwSx59Pp+6u7tVUlIiKf39gG0PAHCaYZgqm7ZErXvXyDC40iFTpH1LhUJh\n5efnD02u+/LLfxqam2j79m1xvcaxk6p+7Wt3HrfMtGnTdeBA48A/cnKkGCOPpdOaNau1Zs3T+ta3\n7lBd3c5hf/vpT+/XkSOHHUo2sgMHGjV16rQJee1U9IN4DesLLrV69ZPatm3L0L9H6y9u5XR/sSxb\n5lGXcESjkWGX3bm5H4y1vd26jxg0kdseADA+uYVTVDhpvmzbcjoK4pT2M2gnnXSyLr74Ev32t79S\ncXGxzjzzLNXUvK+VKx/Spz+9LO7Je8eaVPXUUxeotvb9oaHInfTqq6+OeM/crl11Wr/+dX3uczc4\nnPJ4NTU7dOqpp8e9vN+fo7y8vLiWHasfSKmbfNtNfeFYse6hi+ceSzdyur9UVVWpv79v6DmWZauw\n8MNBQdzaD8ba3m7eRwxKdNsDANKrZMr5CvY0yor0jb0wHOfIPGjf+MZdw/59/vkXDPt3PJP3xppU\n9WjnnfcRPfPMk+MPmwL79u1TTU3dcffMRSIRNTUdUnV1tcMJY6utrdGXv/z/xr385MmTdcMNN8e9\n/Fj9IFWTb7upLxwr1j108dxj6UZO95dzz/0brV37nKSB9/DUU08b9ne39oPRtrfb9xGDEt32AID0\nMn1+lZ5wvtrrX3I6CuKQkRNVjzZp76BJkyYpPz9fXV2dKi119ub1G2+8UfX1A5O4Hn3P3Pr1r+qi\niy7Wo4/+3sl4MQWDQXV0tGv27DlORxnTWBMpu6kvxCOeeyzdxg395fTTF+q11/6iP/3pBdXV7dT/\n/b//POzvbu0Ho21vN+8jBrlh2wMAxpZfOkd5pbMV7NrndBSMISMLtNEm7T3asmXX6rnnntX11y9P\nQ6qRHXvP3IoVP9TevXs0ffrMoXtq3ObPf35RV155tdMx4hLPRMpu6QvxiNVf3M4t/WXwLM4nPxn7\nMkY39oORtrfb9xGD3LLtAQBjK5t2kZp73Hk/Nj6U1cO5XHTRx7Rjx7vq7+93Ospx98zV1OxQXV2t\n1q5do7a2Vr3yykvq7OxwOqakgcuqXnvtFV155WecjpIybuoL8RjrHks3yaT+4tZ+EGt7u3kfMSiT\ntj0AQPL5C1Rcfa6M7C4BMl7Wb52vfOU2rVz5kNMxhu6Zq6ycrBdffEFXXHH10H8VFZVauvRSlZWV\nOx1TkvSHP6zSLbf8g0yHR75MNbf0hXgc21/cLNP6ixv7Qazt7eZ9xKBM2/YAAKl48hnKK5npdAyM\nIuuPqtOnz9BHPvJR/eUv6xzL8MILL+jnP/9P3Xzzdbr66k/qj398fuhvL764Vg0N9Xrssf9RR4fz\nv46/9dZfNWfOvKEhzLOJG/pCLIP30D333DN6++1NWrfuJT344E9j9he3ycT+4rZ+MHhP7Ujb2237\niEGZuO0BAAMMw3A6AkZh2LZ9/BjmE8Qrk7Yey0sT1sbi5fbTdm+2XfJ2+6uqSpyOkHG82lckPiu0\n3Zu83H4vt12K7xiZ9WfQAAAAACBTUKABAAAAgEtQoAEAAACAS1CgAQAAAIBLUKABAAAAgEtQoAEA\nAACAS1CgAQAAAIBLUKABAAAAgEtQoAEAAACAS4yrQNu9e7fOPfdchUKhVOUBAAAAAM9KukDr6enR\nf/zHfygvLy+VeQAAAADAs5Iu0L773e/q61//uvLz81OZBwAAAAA8yz/WAo8//rhWrlw57LFp06bp\nqquu0vz582Xb9oSFAwAAAAAvMewkKqxPfepTmjJlimzb1rZt27Ro0SI9/PDDE5EPAAAAADwjqQLt\naJdccon++Mc/KicnJ1WZAAAAAMCTxj3MvmEYXOYIAAAAACkw7jNoAAAAAIDUYKJqAAAAAHAJCjQA\nAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAA\nAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAA\nAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAA\ncAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABw\nCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCX+yT/zlL3+pl19+WZFIRMuXL9eyZctSmQsAAAAAPCep\nAm3jxo3asmWLHnnkEQUCAT300EOpzgUAAAAAnmPYtm0n+qT7779fhmGorq5Ovb29uvPOO7VgwYKJ\nyAcAAAAAnpHUGbT29nYdPHhQv/jFL9TQ0KCvfvWreuGFF1KdDQAAAAA8JakCrby8XCeeeKL8fr/m\nzp2rvLw8tbW1qaKiYsTn2LYtwzCSDgoAQDbi+AgAqfGXAw3a2dk+6jLTi4p15ex5aUqUnKQKtMWL\nF+vhhx/WLbfcosOHD6u/v1+TJk0a9TmGYai5uTupkJmuqqrEs22XvN1+2u7Ntkvebn9VVYnTETKK\nl4+PEp8V2u5NXm7/RLa9sa1TvcHgqMt0WX5H3/t4jpFJFWhLly7Vpk2bdO2118q2ba1YsYJf/wAA\nAAA4pjsScjpCSiQ9zP4dd9yRyhwAAAAAkJSwZak3HJHPzPyTRkxUDQAAACCjNfcHZCnhweldiQIN\nAAAAQEZrDvYpx8yO0iY7WgEAAADAszrDow8Okkko0AAAAABktK5wdgwQIlGgAQAAAMhglm1ToAEA\nAACAG3SGgwpaUadjpAwFGrJaS3+TbDs7RvQB4tURbFXYyp5fEgEAGM3Bvt6sGSBEokBDljsQ2KMj\n/Y1OxwDS6r3OvypqR5yOAQBAWnSGQzKMzJ//bBAFGrJajpGjht46p2MAaWPZlpr7DzgdAwCAtOnK\nohEcJQo0eMDh/kZZtuV0DCAtDgX2c3kjAMBTsmmAEIkCDR4QigZ1ILDX6RhAWjQGdss0fE7HAAAg\nLQKRsALR7LqsnwINWc9n+nUwsMfpGMCEs+yomrnnEgDgIQf7euXLovvPJAo0eMTh/kZFrOz6dQU4\n1v6enQozOAgAwEPaw0GZFGhA5rFsS/U9tU7HACbUwb598nF5IwDAQ7Lt/jOJAg0eYRqmDvZxHxqy\nVyjar5b+g07HAAAgrbJtBEeJAg0e0hI8pGCkz+kYwITY2/O+0xEAAEirsGWpKxx2OkbKUaDBMwz5\ntLvnPadjABPiUF+9DINdOgDAOw7390qynY6RchzN4RmGYaipr97pGEDK9Ya71BY87HQMAADSqiXY\nJ7+ZfeVM9rUIGEVnuEWdoTanYwAptbvnXfkMv9MxAABIq45Q9t1/JlGgwWNM+bW3Z4fTMYCUsW1b\nhwMNMrJsiGEAAMbSmYX3n0kUaPAYwzB0uK9Btp191yvDm1r6D6k72ul0DAAA0ipiWeqKcAYNyAp9\nkR419XMvGrLDvt4a+Y0cp2MAAJBWTf29srL0B3cKNHiOafpV37PT6RjAuFl2VEf6Gp2OAQBA2jVn\n6QAhEgUaPOpI/wFFrIjTMYBxaejdpZCdnZd3AAAwmmwdIESiQINHRe2o9jGxLzJcY2A3ozcCADyp\nIxxyOsKEoUCDJ5mGqQOBvU7HAJIWjPSpuf+g0zEAAEi7sGWpO0KBBmSdtuBh9Ya7nI4BJGV3z7sy\n2IUDADzoUF9vVo/IzdEdnmUaPu3uedfpGEBSDgX2M/cZAMCTmkOBrB0gRKJAg4cZhqFDgfqs/gUG\n2ak1eFid4XanYwAA4IjOUPZe3ihRoMHjApEu5kRDxtnX/b78JoODAAC8qTOcvSM4ShRo8DifmaP6\nnjqnYwBxs+yoDvXxowIAwJtCVlRdWTyCo0SBBuhwf4PC0ez+oCN77O/ZqbBNfwUAeNPBQK+y/Rbs\ncRVora2tWrp0qfbuZbhyZC7LtrS3Z4fTMYC4NAZ2yWf4nI4BAIAjWkJ98hnZfY4p6dZFIhGtWLFC\n+fn5qcwDpB1zoiFT9Ia71NLf5HQMAAAc0xHK7vvPpHEUaPfdd5+uv/56VVdXpzIP4IiOULM6gi1O\nxwBGtat7u0zOngEAPKw9ywcIkZIs0J588klVVlbqwgsvZIhyZAWfmaM9Pe85HQMYkW3bauqrZ+4z\nAIBn9YRD6o2EnY4x4Qw7iQpr+fLlQ18SampqNHfuXD344IOqrKxMeUBgPLYeeVM1bdviWtZn+PW3\np9zK/T1wpf1ddXr9wB/lM8YeXj8UDelz8/9eBf6iNCQDACA9trc2642mgzLH8WPl9KJiXTl7XgpT\npV5SE+n87ne/G/r/m266SXfffXdcxVlzc3cyq8t4VVUlnm275Gz7Ozv61BuIb8S7qN2nzXs3a27J\naSlbv5e3vZfbLqW+/VuPbFV/0JI0dn8OW0G1tPQo32elbP2JqKoqcWS9mYzPijfbT9u92XbJ2+0f\nT9t3t7Spr298Ixl3WX5H3/t4jpHjHgKFy22QLXyGT/W9zIkG9+mL9OpIf6PTMQAAcJQXBgiRkjyD\ndrRVq1alIgfgCm2hw+oKt6s0Z5LTUYAhu7rflcG0lQAAD4vattpDwayfA01iompgGJ/h1+6ud52O\nAQyxbVsH+/ZytQIAwNOO9AcUsZ25dD/dKNCAYxzq2yfLjjodA5AkHQzsU1/Ym/cpAAAw6FBfr3JM\nb5Qu3mglkICgFdT+np1OxwAkSft7a2Wa474aHQCAjNYe6nc6QtpQoAHHGBgshAINzgswOAgAAJK8\nMUH1IAo0IIa20BF1BFucjgGP29W9jcFBAACeF4iEPTFB9SCO/EAMPsOvXd0MFgLnWLalg4F9DA4C\nAPC8hkD3uCanzjQUaMAImvr2KWJFnI4Bj2oM7FZftNfpGAAAOK4tFKRAAyBF7Kj2dL/ndAx41P6e\nGvkMBgcBAKDNQwOESB4s0FavflLbtm1xOsaoHnjgx+rp6dGePbv19NNPOB1nVJnwfibLNEw1BHY5\nHQMe1BVqV0uwyekYAAA4Lmrb6gh5Z4AQyUMFWjAY1BNPPKpnn31atm07HWdU27a9reuuW6ZVq36t\nyy67wuk4MWXS+zkeXeE2Hek74HQMeExd9zbOngEAIKmpr0dhj0xQPcgz3wDy8vL02c9+QbW1NU5H\nGdPnP3+DrrjiaqdjjCqT3s/x8Bl+7e5+V9UF052OAo+IRMM61Lff6RgAHGbbtrojIR3q71VXOKze\ncEhB21IwGlXYjsqybdmSZEt+01SOYSrHNFXg86vQn6NiX46mFhSpLCeXwYaQ0Q71BzwzQfUgzxRo\nmeVDpbEAACAASURBVKStrVUbNryhurpaXXzxJZo1a7bTkTztSH+j+iK9KvAXOR0FHrCn5z1FrIhM\nw1sHI8DrbNtWS7Bf9YEutYWCag31qT8alc8wxhwcIRy11Bfj9SJttgp8fpXn5qkyN1+zC0s1OS+f\ngg0ZpdVj959JFGiSpCVLzhtzZ2XbtgzD0Kuvbkz49UOhkPbu3aO5c+fFtfyNN/6dJOnMMxfp9ttv\n0y9+8Zu05EyVeHJK7sgaH0N13dt05qQLnA6CLGfbtup7d1GcAR5h27aa+nq1p7dTTX296o5E5Dc/\nPH6O56yBYRjKMQxFbEstwT61BPv0Xmebivx+Tckv1LyiMk0rKKJYg6vZtq22IAWaJ7322lsT+vrN\nzc1at+4lzZ37pTGXffXVV7Rt2xb94z/ervz8Au3atXPobxOdM1WOzVlVVaLm5m6H0oyfYRhq7N2r\nheUfkWn4nI6DLNbUX6/uSDv3nwFZLhSN6P2udjV3NKqxvWuoEDu6OJsIftNQ0IqqPtCtPb2dKvHl\nakZhsRaWVarQnzOh6waS0RLsV9CKcokjJka8v1AVFRXp0ksvkyQ1NtZr4cJFExkLcQpafdrXU6t5\nJac7HQVZbG/3DoozIIv1RMLa1t6sfYEuWbatkqJ8x754+g1TfVZEO7vbtbO7XdMLi7WgtFLV+YWO\n5AFiaQx0y+/Bs7ye+ibw1FOP6/3335Nt27IsS+ecc+7Q355//ll1dHSooWG/vvnNf5UkNTY26K67\n7tCqVY+mLePixefp2Wef1u7du9TUdEjf//6/D/u7W3JK8b+fP/7xfY7mTAWf4dP+nhoKNEyYnnCH\njvQf4CwtkIW6w0FtaW9WfWDgahIjjvvK0mXwB+SDfb1qCPTohPxCLSqr0pQCCjU4rzXU78nLcD1V\noF1zzbW65pprj3t8z57dys3N1ZIlF+vLX751qPB58831mjLlhGHL/u53v9XMmbNUW1ujyy+/Ku4B\nPBIZiv7Tn14W8/FEckoDc5TNmTNXixadHfe6ExHv+zkoVs41a1ZLsrV+/ev64he/pJNPPmVCsqZC\nR6hVzX0HVVUwzekoyEI7u96R4Z2ZTwBXWLx4YczHN29+NyXLn3POAoUs67ghwr/7zOqYy9/9mf8T\n8/GJWv7Y5XyGoeZgn/54eL9OyC/U4knVqswriPlawESzbVttYe/dfyZ5rEAbSSDQq6VLP6GVKx/S\nhRcuGXp869bNOvvsD88Kbd++TQ0N9Vq+/BadfvpC/eQn9+ree+8f9lrBYFAPPPAjRaPRocei0ZD2\n7t2npqZDw5a98spP66yzzkl5zmAwqDVrntbatc/pttu+NuprPvfcM9q4ccOIv07Ytq2cnBz9y798\nR35/fN0l3pwbNryh009foHnzTvr/27vzMCmqe2/g36rumZ597xl2RJBFR5BNEUFkMyDqVaNxhWju\nc2/uc988V42KGo0kRi9Z1JvXXHnDdQsxXjUhBomKAoKyqcgyLAqzCAyzT8/e2/RSdd4/JowgPcNM\nT3ef6q7v53nyPJmyevp7ero49auqcw6ys3Pw1FMrsGbNG316DxksqhUVzoMs0CjiApofNd7jprxK\nSJSIhBD4sqMZHi2IeFwp9FShtqHuBM5Lz8b0vELYLDxlpNhqD/jhCQZNN/4MYIEGACgunggA2LDh\nXTz66BPd2w8c2I+lS7+5A7Rv3x5MmND1iJvdXogjR74663fZbLbuO1un+P0deP31t3DPPf8Sk5z9\nWaNsyZLrsWTJ9QPKFW7OqqqT+PTTHbj//uUYNmwEGhrqzvpdRtPQWQ1P0Ik0a6bsKJRAyp0HoetB\nKJy9kSimerrzNZD9m31efNpcjxZfJ37aw52snvR050vW/oqi4IS7HdUeJ4pz8nFRVj4vJFHMnDTp\n+DPARAXaqanfv/2o4alp3isrT6CtrbX7jlZFRTmCQQ3jxk3AwYMlmDjxErS0NJ/xiJ7FYoHT6URm\nZuRO1iORMxYikfOmm26B19u1csvBgyW47LLLY5J9IBSoKG3fj8n5V8qOQglCCIEqdwWLM6I4pwuB\nPS2NKHW2QFUUWKI8I2OsKIoCDQL7WhyodDtxef5g5NlSZMciE2j2eU17QcA0Bdr27V9g48YNSE1N\nRUnJfkydOh0zZ87q/u+BQAApKSmwWLoG6G/Zsgnjxo0H0PVo48SJl0DXBVT1mwH8mhaExRLZk6rt\n279AbW0N3n//7xg9egyEAObNW9CvnLEQiZwWiwUZGRlwOp3YunUzVqx4OibZB0JRFNR4juHinMth\ntXBKYhq4Knc5PEEXLConByGKVy0+L3Y01aE94DPM5B+RZlEVtAV82FB/AhMy8zA5127ak2eKjWa/\nT3YEaUxzybamphpr1ryM2bOvwvTpl+Hll1ef8d/HjLkAc+bMwx/+8BLWrn3zHwWEFWvWvIxFi5YA\nAOx2Ozo7vd2v0XWBtLT0iOYUQmDlyidxxx1LMWnSZLz33vp+54yF/uR87bXXesyp6zr++MdX8NOf\nPonc3NyY5R+IoNBQ7jwoOwYliOOuIyzOiOKUEAKH2puwob4SzqA/YYuzbzvc0YT36o6j3cQn0BRd\nroAfrqBfdgxpTHMHbejQYVi16iUAQHl5GWbPnnPWPg899JMzfp4xY+YZP0+bdik2bHgPQNf4qfHj\nJ/TpvZOSkmCz2fq07/79e5GZmYW0tHSkpaXjl798tt85Y6E/OU8tVB0q57p1f8Xtt9+FvLx8bNz4\nAa6+elHUsw+Uqqg46SnDuOzJUPlYGg2Aw1uLFl8jLKpp/ikmShgBTcO2phrUeNwJ8zhjX1kUFe0B\nP96vO4EpuXaMy8qTHYkSzHF3h2nHnwEmKtAAID09Azt2fILa2hrcf/9D/X79hRcWY/v2T7Bp0wco\nLy/Df/zHA316XWFhIe64Y1mf9i0tPYpAwI9du3agqcmB4cNHYPLkqf3O2tsaZZEQiZxbt27G73//\n33jllf8BAIwbNyEuCjQA8ARdOOkuw3kZ42VHoThW7jzI4owoDjX7vPjEUQNPMGC64ux0OgQ+b2lA\ng8+DmfmDYeXTABQhDhOPPwNMVqBZrVbMmjUHPp8fTzzxyFlT5PfFD3/4fwAACxdGp5DQdQ2dnZ2Y\nOXMWdF3H3XffHtbCzj2tURYpkcg5d+4CzJ274Nw7GpBFseKY8ysWaBS2roWpq7kwNVGcOeZqx2dN\ndRAKTH0CeYpFUVDpdqLV58OcwmHISe7bE0NEPRFCoNlvzvXPTjHl81ljx47Dzp3b0dbWJjvKWQoL\ni1BYWAQAUFUVLpcLTqdTcqqzxUvOaOoINKPee1J2DIpTR9v3c2FqojgihMD+lkbsbKqFYF12BlVR\n4NIC2FB3ApWuDtlxKM61+n1wBwOyY0hlmrOD9ev/hscffxgA0NzchIICO7KysiSnOtvUqdPR0tIM\nANA0DZmZWRGdxj9S4iVnNKmKFeUdnCyE+q9T86LWw4WpieKFJgQ+cdTgcHuzaSYCCYcOgW1NNTjQ\n6jhrGR6ivqo0+fgzwESPOM6ePQdJSUn46KON2LNnN5555nmoBlyZPC8vHwsXLsLatW/C4/GcNSGI\nUcRLzmhr8tWhxdeIPFuh7CgUR46274MAYO7uhyg++DUNmxuq0Oz3QjXxeLO+UhUFB9qa0BLoxJX2\nYbCY/ESb+q/J32n6C5imKdByc/OwePG1AID586+WnKZ311xznewIfRIvOaPJolhR1l6CGYXG/k6R\ncQS1AGrcFabvfIjigScYwMb6k3CZaAr9SLCoCqo9LmyoO4GFRcNhs5jmdJMGSBcCTT7vuXdMcMa7\nhUQUZ+o7q+AKGG88IxlTmfMAgiIoOwYRnUO734f3607AFfTzgkoYVEVBm78T79WdQAfXS6M+auz0\nwKdrsmNIxwKNaIAUKDjSvk92DIoDutBQ6T4KhevnERlai8+LD+sr4dM1FmcDoCgKvFoQH9RXoqHT\nLTsOxYEqrxNJBhyCFGv8BIgGSFEU1HlOwBtk50O9q+g4BJ9m7qmDiYyuyefFpoYqBIQuO0rCCAgd\nWxqqUe0x12zP1H9NPvaRAAs0oogQAI6075UdgwxMFzqOu45y3TMiA2vodGNzw0kEWZxFnA6BbY4a\nHHO1y45CBqUJHc0s0ACEWaAFg0EsX74cd955J773ve9hy5Ytkc5FFFcURUG152veHaEenXAegUfj\n1WMio3J0erGlsRoap4ePGgFgV3MdSjtaZEchA6r2uKHx4giAMGdxXL9+PXJzc/HrX/8a7e3tuOGG\nGzBv3rxIZyOKK0IIHGnfg0vyZsmOQgYjhECF6zAsCmcyIzKiZp8XHzWchA4WZ9GmANjd0oCM7FQM\nRarsOGQgNV4XrBx/BiDMO2iLFy/GvffeCwDQdR1WK086iBRFQZW7An7eRaNvOeE6Ck+Qd8+IjKjF\n58VHDVXQWJzFjKoo+KyhFofam2RHIQNxdHpkRzCMsCqr1NSuKx4ulwv33nsv7r///oiGIoqUW+fd\ngaAeOGv7r95dEXL/h6/9ecjtfd9f4CfKUzhUUhFy/6lTi0Nu37v3cFT272k/M4j1Z93T/kIIVDgP\n49Hrngq5fzS+i0+tfyTkPkR0pg6/D5sbzTshyJPX/1PI7U+sfyfq+1sUFSUtDuhCYFKOHUBs/902\nc/8IGKePPGXylIvg0QLousf6jWh8F1dt3BxyHyMJ+9ZXXV0dfvSjH+Guu+7CNddc06fX2O2Z4b5d\n3DNz2wF57VdVBUqIi6Lpackh9+9pNuW+769Ag4bs3GQkW20Azmy7qoZ+g54+n4HuL/t7J/P9Y/1Z\nh9rfbs9EReuXEMmeCHy3+r5/WqoNBQUZSLWmh/4lZDiyj1XZZLTfEwjgg+NVSE5JQuijKjbS02zS\n3runxbd7yhTp/TMzUlDh70COSMW0wsEx/XfbCMecmfvIb79OV8Q/vi9nvi4a38WszBRD/P17owjR\n/9GwTU1NWLZsGZ544gnMmDGjz69zOMz5iI/dnmnatgNy2/9V6xeocMX2KpkQAudljMOkvCtM/bc3\nc9uBrvY3NnZgc91aeDVXTN87oPuwZNgypFjSYvq+pxi94zMisx8rsW6/Xwvi/bpK6YtQp6fZ4PaY\ncxHn09uu6wKTcgsw8R930szAzH1kqLZvqj+JRl9sHnEclJKO+UXDY/JeofSljwxrDNrq1avR0dGB\nVatWYenSpVi2bBn8fn84v4oo4SiKgpPuco5FI1S6S+EOckppIiPRhMDGhirpxRl9Q1UVlLQ2cUya\nSWlCcPzZt4T1iONjjz2Gxx57LNJZiBKGLnR81b4HQwctlh2FJBFCoKzjANc9IzIQIQS2Nlah1d/Z\n4yNSJIdFVbC/1QELVFyYnSc7DsVQlbsDAaHDqnAGx1P4SRBFwam7aN4ArwiZVWnrQbiDHbJjENFp\nPm+uR53XzeLMoCyKgr2tDSh3tsmOQjFU0+nm9Prfwk+DKEqEEChxfCo7BkmgCx1Hmku47hmRgRxs\nc6DM1cbizOBURcHnzXU44eLj4WbR2OmVHcFwWKARRYmiKDjeUcb1r0yovOMgPMHYTgxCRD075mrH\ngbYmWFicxQVFUbCzuQ7VHvafia494Ee735wT5fSGBRpRFCkCONz2uewYFENBPYCvnV/CwrFnRIbg\n6PTis6Y63jmLQ9sctWjodMuOQVF0zNUGaw9T8psZCzSiKFIUBXWeE2j3N8uOQjFytH0f/Dpn8CQy\nAncwgI8dVRA8/4tLAgIfN9ag1c9/UxNVfaeHs6mGwAKNKMoUxYLDbbtlx6AY8GudOO46ApUzURFJ\nF9Q1bG6ogk/TZEehAQgKHZvrq+AKBmRHoQjzaUE0+Tj+LBSeRRDFgKOzBg5vrewYFGWH23ZDF7rs\nGESmJ4TAdkctOgI+Xp1PAD49iE31lfBrQdlRKIIqnJwIpics0IhiQFUs+LJ9N4QQsqNQlLgC7ajy\nlPNkkMgADrQ5UO1xcdxZglAUBe5gAJsaqqCxH00YtZ1c8qInLNCIYqTN50CVu1x2DIqSw22fQ+E/\nqUTSVbo6cKi9GSonHkgoiqKgxd+JrY1VvNiZAIK6jkYf14rtCc8miGJEVa040r6Pj8AlIEdnHeq9\nJ2XHIDK9Nr8Pu5o5Y2OiUhUFtV4XdjXXyY5CA3TM3c67ob1ggUYUQ17NhbKOEtkxKIKEEPiy9XOo\nnFafSKqApmFLQxV08KQvkVkUFV+72nGg1SE7Cg1AtcfFdQl7wQKNKIZUxYIK5yH4NU4ZnCgq3WVo\n8/NEgUgmIQS2N9XAo3GmPzOwKAoOtjehwtkmOwqFQRM6Gjr5eGNvWKARxZimazjU9pnsGBQBmgji\naPteqKpVdhQiUzvY1oQaj5uT9JiIqij4vKUeNR6X7CjUT8c7OuDXufxFb1igEcWYoiiodn+NVl+T\n7Cg0QEfa9qJT4xouRDLVeFw41N7ESUFMansTF7KON8c72mBVWYL0hp8OkQSKouJQ66eciSqOeYJO\nHHN+xUWpiSRyBwPY0VTLO2cmpgmBjxqq4A1yjbR4oAuBajfvep4LzyyIJGnxN+Cku0x2DArTgZad\nEJyMgEgaXQh83FiNAB+VMr1OLYjNDScR5HfB8CrdHehkMX1OLNCIJFEVC75q/wJBnYPa402dpxIN\n3ipetSeS6IuWBjT7O3kcEhRFQVvAh48dNXwyxeBOuDv4eGMf8BMiksiv+fBl2+eyY1A/6ELH4bbP\nODEIkUQnXO0oc7Zymm7qpioK6rxu7G5pkB2FehDUddRx9sY+YYFGJJGiqDjhKkWbnxOGxIsj7Xvg\nDvL5eSJZnAE/Pmuu52LUdBZVUVDa0Yqv2ltkR6EQKlxtCApddoy4wAKNSDJFUVHSsoOPZcQBV6Ad\nX3cc5sQgRJLoQmCbowYax39SDyyqgn2tDajyOGVHoW+p8jh517uPeJZBZABtPgeOub6SHYPOYX/L\ndoCdC5E0p8adEfVGURTscNRy+n0D8WlB1HdyWZq+YoFGZACqasWR9j3oDPLZbKM64SpFk69Odgwi\n06p0d3DcGfWZDk6/byRlzjaAd777jAUakUFouob9rdtlx6AQ/Fonvmz9HBaFE4MQyeAOBjjujPqt\nUwvio4YqaBxCIF2118Xjtx9YoBEZhKIoqPdWodp9THYU+pb9LdsRFLwKSySDEALbGmu43hn1m6Io\naA10YpujmuO8JeoI+NDI2Rv7hQUakYFYFAsOtn4Kv+aTHYX+odp9DHWeE1xriUiSkjYHHD4vj0EK\ni6ooqHK7sK+1UXYU0/qqvYWPJvcTCzQigwnoPpS07pAdgwAEND8OtX3KNc+IJGnwuvFlezMsKk/u\nKHwWVcGXHS0od7bJjmI6uhA46XHxAks/8ayDyGAURUGt+xiqU0dhWPr5suOY2v7W7fBrPnYsRBL4\nNQ3bm2p5/FFEWBQFu1vq8VVHMzbVn8RJjwsj0jJwy/CxmFM4VHa8hHXC1Q6vFoBV5T2h/mCBRmRA\nqmrFwdadsKcMgc2SIjuOKVW7KlDjOQ6LYpEdhciUdjbXoVMLskCjiKl0d2BXc333zyc8TvymdC8A\nsEiLkq/d7SzOwsBPjMigAnoA+5o/lh3DlDo1Lw62fsrijEiSso5WVHmcLM4oor7saAm5/S/V5TFO\nYg7uYAB1nBwkLCzQiAxKURTUd1bhmPNL2VFMRQiBPU1bEBAB2VGITMkZ8GFvayMnFaCI6wj4Q26v\n8jhjnMQcvmpvYaERJn5uRAZmUaz4su0LOP0c2BwrFR0H0dTJcS9EMuhC4BNHDXQuaEtRkJWUHHL7\n8LTMGCdJfEIIVHk62JeGiQUakcEJCHzR/BF0ocuOkvBafU040rGPszYSSbKvtREt/k7ZMShBXZSV\nF3L7LcMuiHGSxHfC44QzyPVDwxVWgSaEwIoVK3Dbbbdh2bJlqKqqinQuIjpNR6ANB1p2yo6R0IJa\nAF80b5Ydg8i06r1uHO1ogUXhtWOKjpHpWZiZPwg5SclQAOQkJePy/EEYlpYuO1rCKe1ogZXLY4Qt\nrMvEmzdvht/vx5tvvokDBw5g5cqVWLVqVaSzEdE/qIqKSncp7LbBGJYxRnachLS35WN4gx4+jkEk\nQUDTsLOpjscfRd3I9CyMTM86Y9vnzfXIsCShKJWFWiQ0+7xo8Hlh5fEctrAuU+3duxezZ88GAEya\nNAmHDx+OaCgiOpuqWFDStovj0aLga+dh1HkreXJIJMmnzXXwapyYh+QQAD521MAZ8MmOkhAOtzez\nOBugsAo0l8uFzMxvBlRarVboOsfHEEWbLjR83rQZQZ0nMpHS1FmPL9u+gMop9YmkKGttwQk3p9Qn\nuYJCx6b6Kvg1jpsaCG8wgJMel+wYcS+sRxwzMjLgdru7f9Z1HSoXoSMDEhAQQt5sYEJE/v1dwXbs\nbf4Y0wvmR/T3RpoudMNPbOLXOrG7aXNUviPR+Nv3/c3lvC3Fp6lTi0N+ZfbsORRy/2nTLg65PZz9\nPVoQ25tqoCroPl5+8U83hNz/p++sC7l9IPv3tE+sSP13QjIjtt2tBbCpoQqLBo+EguheMNCFgG6w\n9kfCwfZmAAK9NU32395o37tQwirQpkyZgq1bt2LRokUoKSnB2LFj+/Q6u92805iaue2AvPZPzpqC\noZ5BUt47mvxaJzY7/mTs8/Bm2QHORSArORczz7tSdpCIU6BgSE4BF9qOIzL7iE5dgxbiYsrbjmMh\n9/f08ChiOPtnJiXj8qLBQNE325+xhj41+c7o80NuH8j+Pe1D5qUJgQ2Ok+jUtOi+kSO6v14GIYAL\ncnKxqNDYx1WOLQX29AzZMXqliDDKSCEEfvazn6G0tBQAsHLlSowaNeqcr3M4zLkQoN2eadq2A+Zu\nfzTb7vDW4FPHh4BBHwtKT0uG2xN6UVAjSLWkY+6gm2CN0pT6Zv/eU//I/K58WF+JJp835u9rgYrr\nh47CyMF5pj5W2Hbj8QaDeL/uODr16BVp6Wk2uD2JNeZNhYqbh49B0jmeqjPy3z4W+tJHhnVmoigK\nfv7zn4fzUiKKEHvqUFycezkOtu6Ewjsl/WJVrLjc/p2oFWdE1DtdF5hhL0KaNUl2FKKzpFqtmF80\nAh/UVUKDsR/VNwohBMZkZp+zOKO+4adIFMdGZU7A+ZnF0KN4lS/RKAAuLViIjKRs2VGITEkIgRHp\nmRidwWOQjCsn2YarCodGeSRa4rAoFlySa5cdI2GwQCOKc8U5l2Fw2kjDT8hhBLrQcEnubBSkJN64\nRKJ4kWKxYmbBENkxiM5pUGo6ZuYP7nXCC+q66HJBBu+eRRI/SaI4pygKphfMR15yYVzMTCSLLjRc\nlH0phnOhbyJpdCEws2AwT+QobpyXkY1peYXQ2b32yKJYMIl3zyKK/0ISJQBVUTGzcDEyk3JYpIWg\nCw1jMi/GBdkTZUchMi1dCIzNzMWQVGPPnkb0beOz8lCcnQeN/etZdCFwAceeRRxHyBMlCKtqxazC\nJfik4R1UdBxChesQXIE2ZCTlYEzmxRiaZuxpb6NF1zWclzkBxbmXyY5CZGpZ1mRMyys6945EBjQ5\ntxA+XUN5RxtUlSPTTrEqFkzK4d2zSGOBRpRAki02pFkzsb91W/c2Z6AV+1u6fjZbkabrGoanj8Gk\n3JmyoxCZ3iz7EFgMuiwIUV9cljcIfk3HCU8Hv8voWjOuODuXd8+igJ8oUYLZXPfnkNsrnIdinEQu\nXdcwIuMCTMmfA4UdKZE0mi5QnJWPfFuq7ChEA6IoCmbZh2BISjp0Pu6ITGsyLs4pkB0jIbFAI0ow\ndZ7KkNtdgbYYJ5FHFxpGZozH5LwrWZwRSVZgS8FEnsRRglAVBXOLhqPQlmrqIk0XAlNy7VDZx0YF\nCzSiBDM4bWTI7RlJOTFOIocuNIzJmojJ+bNYnBFJpioKZtuH8VikhGJRFCwYNAL5yammnZirKCUN\nI9OzZMdIWCzQiBLM4qF3hdw+OqM4xkliTwgdF2VfiuKcS2VHITI9TQhMzSlEZlKS7ChEEWdRVFw9\naASyk2ymK9KEAKbncsKfaOIkIUQJ5tKC+QCAD2peR633BIaknodFQ+5AkpqMSncZVMUiOWF0KFAw\nJX8uhqWbayIUIiMSQmBoajrGZuXKjkIUNVZVxaLB5+GDuhNoD/hMcadYFwJjMnKQa0uRHSWhsUAj\nSkCXFszvLtROl2HNwZH2PUACdSJCCNgsKbisYCFybZzql8gIbBYLZhUMkR2DKOqSVBWLB5+HD+oq\n0RboTPgiLd2ahEvzefcs2viII5GJXJA9ETPsV8OqWBPikQxdaMixFWDuoJtYnBEZhC4EZuQNhs3C\na8BkDl130kYiJzklIfrWnggAl+cPhkVh+RBt/ISJTKYwdRjmDfoucm0F0IUmO07YdKFhTObFuLLw\nOtgsfNSCyAh0IXB+RjaGp2fKjkIUU1ZVxaJBI5GfoLM76kJgdHoWBqemy45iCizQiEwoxZqG2YXX\nYWzWJXF3tU8IAZuagpn2RSjOvSzhHychiicZ1mTMyB8kOwaRFFZVxdWDRmJwajq0OOtbzyXDmoxL\neWzHDAs0IpNSFAUX5kzDlUXXIcOaDV3osiOdkxA6hqaPwvzBN6MwdZjsOET0LbPsfPyJzM2iKJhf\nOBwj0zKh64lTpM3MH8RjO4b4gDhRAps6NfTU+nv3Hu7+/7k2O+YOuhGlHSW48cob0fWU+Zl3pX71\n7oqQv+fha38ecnvk9xdQoCLZYoNFsZ6R/3Snt7enfYgo8nQhUJydD7stTXYUoj7pS/8Y7v6KouDH\nixfBp2kIfOvi5xPr3wn5e568/p9Cbo/W/j3t9226EJiWV4QiPtoYUyyFiQiKomB89mSkWtJgUazo\nKtKMoCtHkmpDivVUNiIymvzkFFySw4l6iE5ns1iQrMbvqbYuBM5Lz8KErDzZUUxHETEcgOJwOGP1\nVoZit2eatu2Audsfr23v8Lfiq/YvUO89CQVqWOO80tOS4fb4w3p/XehIUpMwIn0cJmRPhVWNQzIg\nUAAAFchJREFUv8IsXv/2kWC3c4KI/pL5XfmwvhJNPm/Yr1cVBdcOPj/sBanNfqyw7Ymv0t2BXU11\n0E+7+JmeZoPb45OYqndCCGQn23DN4FGwRHist5n+9qH0pY+Mv7MeIoq6rORczLBfDXegHUc79qPe\nU4mACEKN8vPnmggi05qNYekX4IKsi3nHjMjgNCEwPbco7OKMyAxGpmch05qMjx3V8AQDcTG5VYrF\ninmFwyNenFHf8OyHiHqUnpSNqflXQcsL4rjzCOq9lWjy1QNQIlasaXoQyaoNhSnDMDxjDIpShsdF\n50VkdkIIDE/LwNisXNlRiAwvz5aC64acj62NVWjo9MiO06tkVcXVg0Yg3coLL7KwQCOic7IoVozJ\nuhhjsi5GQPej2v01mny1aPc3wxloh4CARbGes7ASQiAoAkhSk5GdlIfspHwMSh2BwtRhUb87R0SR\nlWKxYlbBUNkxiOJGkqpiYdEI7G91oFJzy44TUpKiYkHRCGQl2WRHMTUWaETUL0lqMkZlTsCozAkA\ngKAeQKu/Ea3+JviCHviFH0E9gIz0ZDj1TqiKBUlKEpLVFKRa01FgG4yMpBwWZERxTAiBKwqGICmO\nJ0AgkkFRFEzJK8TFqQrWl5XBqwUN89RIkqJiftFw5CanyI5ieizQiGhArGoS7ClDYU8580q62QcB\nEyUqXQhMyMrDYE67TRS2IRkZuH7oaOxqqkWlxyl1rJcQAhnWJMwvGo5M3jkzBF76IiIioj7LS07B\n1NxC2TGI4l6SqmJO4TDMsw9DqsUKPXYTq3fThYA9JQ1LhpzP4sxAeAeNiIiI+kSFgivtwwzzSBZR\nIhiWnonBaRnY19KIMlcbhNBjdoxNyMrD1NxCHtMGwwKNiIiIzknXBWbYB3NKfaIosCgKpucX4aLs\nPOxtdaDS0w4IRKVw0oVAbnIKLs8fhHxbasR/Pw0cCzQiIiLqlS4EzsvIwuiMbNlRiBJamjUJs+1D\nMClQgENtTTjpcSIodKgRKNQ0XSDdasW4rFxclJXPu2YGxgKNiIiIepVpTcLMgsGyYxCZRlZSMq6w\nD8Fluo6jHS046XWh2ecFgH4Va0IIaEIg35aKcZk5GJ2RE5Fij6KLBRoRERH1SPnHuDMLl8Ygijmr\nqqI4pwDFOQXw6xq+drWhsdOLjoAfrqAfPl2HLgQUBVAACChIUlSkWi3Ittpgt6VidEY2MpKSZTeF\n+oEFGhEREYWkCYHL8gqRZ+O6SESyJasWTMjKx4Ssrp+FEPBqGoJCR0DXEdR1pFmtSLcm8S5ZnGOB\nRkRERGfRhcDItEyMy8qTHYWIQlAUBWlWnsonIj6vQERERGfJsCZjln2I7BhERKYTVtntcrnw4IMP\nwu12IxAI4JFHHsEll1wS6WxEREQkgQIFVxUO5bgzIiIJwirQXn31VcycORPLli3D8ePH8cADD+Dt\nt9+OdDYiIiKKMV0XuLxgEHKTOe6MiEiGsAq0e+65B8nJXbPBBINB2Gy2iIYiIiKi2NOFwOjMbIzJ\nzJEdhYjItM5ZoK1duxZr1qw5Y9vKlStRXFwMh8OB5cuX47HHHotaQCIiIoo+IQRykm2Ykc/1zoiI\nZFKEECKcF5aWluLBBx/Eww8/jFmzZkU6FxEREcXAO8cr0Oj1IElVcfPosVwviYhIsrAecayoqMB9\n992H3/72txg3blyfX+dwOMN5u7hnt2eatu2AudvPtpuz7YC522+3Z8qOEHdkflecrk64On2YVzQc\n3jYfvPDF9P3Nfqyw7eZk5vabue1A3/rIsAq05557Dn6/H08//TSEEMjKysILL7wQzq8iIiIiiYK6\njsm5dgxJTZcdhYiIEGaBtmrVqkjnICIiIgkmZhdgeDrvehIRGQUXOCEiIjIxFmdERMbCAo2IiIiI\niMggWKAREREREREZBAs0IiIiOss777yNAwf2y44RUaHatHHjBmzb9jF+97vnsHPndknJIud3v3sO\njY0NAIBgMIjf/OY/4Xa7JKfqn3Xr1mLDhnfx2muvoqGhXnacsCTi8UOxwwKNiIiIuvl8Pvz1r2/h\n739fhzCXSjWcntpUU1ONNWtexpVXXoXp02fg1VdflJhy4CoqyrFz5w7oelcbGxsb8O677+CGG67B\n9dd/B9deuxBbt26WnLJ3R48eQWlpKRYvvhbf/e6tWLXqedmR+iURjx+KvbBmcSQiIqLEZLPZ8N3v\n3orS0qOyo0RMT20aOnQYVq16CQBQXl6GWbOulBEvIoLBIOrr61BYWNi9zeFwYO3av8NuL4Su63j3\n3Xcwd+4CiSnPbd++L1BUVAQASEtLQ3l5qeRE/ZOIxw/FHu+gERERkWmlp2dgx45PUFtbgzvuWCY7\nTth27tyGyy+/4oy7NpMmXQK7vatgW7/+bVx99WJZ8fosNTUNwWCw++e2tjZ0dHRITEQUe7yDRkRE\nRP02e/Z0KIrS6z5CCCiKgm3bdscoVf9ZrVbMmjUHPp8fTzzxCH75y+cAGKN9fr8fNTXVGDXq/F73\nO378GIYOHQ6LxRLyvx87VgFN05GSknLG9mi3sa/5T3fVVfOwevUL3bmDwSCs1rPbZYS/z0CMHz8+\nrvNTdLFAIyIion7bvv0L2REiauzYcfjZz36CtrY25OTkGKJ9LS3N2Lp1M0aN+tde9zt69CsAQHl5\nKVpamvHxx5uxePG1yM7OAQD8+c9v4NprbzjrddFuY1/zny43Nw+33HI7du7cjvz8fJx33iikpaWf\ntZ8R/j4DcfToUTgcTtkxyKD4iCMRERGZ0vr1f8Pjjz8MAGhubkJBgR1ZWVmSU53pXHdZAGDx4mu7\n/5eXl4+rrlrQXZwBwO7dnyEnJ6eX3xA9fcl/upqaaqxd+yauuGI2hBCYP39hlJIRGRcLNCIiIjrD\n3/62FkeOfIn33luPffv29Ljf++//Hf/7v6/hV796qntbdXUVli27NRYx+yVUm2bPnoMrrpiNjz7a\niA8/fB/PPPM8VPWbU6N4ah/QtWRAVdVJ/OUvb6Ctra17e1JSUo+Fp9HamJ9fgCFDhuHDD9/Hvn17\ncOutd/a4r9Gyn5KIxw/FFh9xJCIiojPceOPNuPHGm3vd59ixr5GcnIzZs+fghz+8Bw8//DgA4NNP\nd6KoaFC/3u/dd98BILBz5w784Af/igsuGBtu9B6FalNubh4WL74WADB//tVn/LdItu+Ud955G+ed\nNwqTJk3u82v6M1X71VcvDjkRyFtvrQu5f1/b+Kc//QHDh49AaelRLFq0BCNGjIxKfgBISUnB0qV3\nn3O//v59wvnsw9WX46e8vLzP+WNxfJCxsEAjIiKifvN43LjqqvlYs+ZlXHHF7O7tJSV7MXnytD7/\nnm3btuHCCy/C+eePQXZ2Dp56agXWrHkj5L7vvbceu3d/1uNjc0IIJCUl4ZFHfgqrdWCnOJFqH9C1\nNta7767Dhg3v4Uc/uq/HfX77299A07TTMnhQW1uN+vq6M/a95prrcMklU/qVIZS+tPHQoQOoqjqJ\nu+66GxdeWIxnn/1l90QqA8m/cOGcqGc/letcn/0psfx+uVyuPuX/7LNdfT4+KHGwQCMiIqJ+Ky6e\nCADYsOFdPProE93bDxzYj6VL7+nz7zlx4gSOHi3H/fcvx7BhI9DQUNfjvkuWXI8lS64PP3Q/RKp9\nQN/WxrLZbN13UU6pr6/Dhg3v4p57/qVf79dXvbfxBwCAffv2YMKECwEAdnshjhz5KuTvinX+vv59\n+rMuWSy/X5MnT4bD4Txn/qqqk/j00x19Oj4ocbBAIyIiMrlTU5af/jhaqJ+BM6f+rqw8gba21u67\nORUV5QgGNYwbNwEHD5Zg4sRLzvned955J06ebAQAHDxYgssuuzySTQPQc/tOtef0bZFuXyz0p32n\ntp27jeNx8GAJWlqaz3jkzmKxwOl0IjMzM6L5T3f6Hax4+Pv0lL+3z/7IkSN9yn/TTbfA6/UCiN7x\nQcbDAo2IiMjktm//Ahs3bkBqaipKSvZj6tTpmDlzFl5/fQ2GDRuBsrKusUfDh48443WBQAApKSnd\n629t2bIJ48aNB9D1aFxfTpAtFgsyMjLgdDqxdetmrFjxdFTaV1tbg/ff/ztGjx4DIYB58xYAQK9t\njET7YiHc9gG9t/HgwRIIIaCq36xDpmlBWCyRnWNu+/Yv8N576yGEwK5dXeOsxoy54Jz5jfL36Sl/\nJI6fWBwfZDws0IiIiEyupqYaa9a8jNdfX4ukpGS8+OL/Q2ZmJk6erMSdd34fF154UcixR2PGXIA5\nc+bhD394CRkZGZg48RIcPXoEa9a8jOuu61p3S9d1/O1vf4Gunz1ZxJAhQ3HDDddA13X88Y+v4Kc/\nfRK5ubkRb58QAitXPolf/eo5dHZ24umnf4558xbg4MGSXtsYifadPr4oWsJtX1/a+N5769HZ6e3e\nX9dFyHXJBuKzz3Zh/PgLMXr0GGRnZ+MXv3gCa9a8EZG/TyyEyv/gg49E5PgBEPXjg4yHBRoREZHJ\nDR06DKtWvQQAKC8vw6xZV/Z57NFDD/3kjJ9nzJh5xs+qquK73+192vB16/6K22+/C3l5+di48QNc\nffWicJsS0v79e5GZmYW0tHSkpaXjl798tnv7udoYifaFy2pNgs1mO+d+A2kf0Hsbp027FBs2vAeg\nazzU+PETIp6/p3FWkfj7xMK389fX10bksz8l2scHGQ8LNCIiIkJ6egZ27PgEtbU1uO++B7Fq1f+N\n+tgjAPjggw/w+9//N1555X8AAOPGTYj4CWhp6VEEAn7s2rUDTU0ODB8+ApMnT43J+KpTTq2NJYSA\nruuYMuXcM0EWFBTgjjuWnXO/aLbvwguLsX37J9i06QOUl5fhP/7jgT6/tq/5expnFam/TziffX+c\nnv/QoQOYMWMmWlqaUVhYNODsW7dujvrxQcbDAo2IiIhgtVoxa9Yc+Hx+rFjxKAoLi6I+9ggAFi1a\nhKlTr4j47z2drmvo7OzEzJmzoOs67r77dvzxj29B16M/vuqUvqyNFa5ot++HP/w/AICFC6NTGHx7\nnNXPfvafABCx/NH87IEz82/ZsgkrVjyNV175n4hknzt3AebOXRDJuBQHovOvEBEREcWlsWPHYefO\n7cjLy4/62KNYKSws6r6boaoq3G43nE4n7HZ7QrQxEdp3+jirnJwcAIjb/Lm5uXGVnYyHBRoREZHJ\nrV//Nzz++MMAgObmJhQU2HHZZZejrKwUQP/HHhnN1KnT0dLSDADQNA0ZGZnIzMzEtGmXory8DEB8\ntzER2ndqnFV+fgE2bvwAAOI6//TplyXM8UOxp4jTF2mIMofDGau3MhS7PdO0bQfM3X623ZxtB8zd\nfrs98uN3Ep3s70praws++2wXkpOTsWfPbtxyy204//wxWL36BZx//miUl5fhuutuOGua8EiI1bHy\n/vt/h8fjhsfjwZQp01FcfDEAxKSNPYlk243Yvt6c3vatWzdj5cpfIDk5GUDXOKtnn30egHHzn+7M\n/ALjxl2IZ599vtfsZu8jzNp2oG99JAu0GOAX0bztZ9vN2XbA3O1ngdZ/Zv2uADxW2HZzMnP7zdx2\noG99JB9xJCIiIiIiMggWaERERERERAbBAo2IiIiIiMggWKAREREREREZBAs0IiIiIiIig2CBRkRE\nREREZBAs0IiIiIiIiAyCBRoREREREZFBsEAjIiIiIiIyiAEVaF9//TWmTZsGv98fqTxERERERESm\nFXaB5nK58Otf/xo2my2SeYiIiIiIiEwr7ALtiSeewI9//GOkpKREMg8REREREZFpWc+1w9q1a7Fm\nzZoztg0ZMgRLlizBuHHjIISIWjgiIiIiIiIzUUQYFdZ3vvMdFBUVQQiBAwcOYNKkSXjttdeikY+I\niIiIiMg0wirQTjdv3jx8+OGHSEpKilQmIiIiIiIiUxrwNPuKovAxRyIiIiIioggY8B00IiIiIiIi\nigwuVE1ERERERGQQLNCIiIiIiIgMggUaERERERGRQcSkQPN6vfj3f/933HXXXfjBD36AxsbGWLyt\nYbhcLvzbv/0bli5dittuuw0lJSWyI8Xcpk2b8MADD8iOERNCCKxYsQK33XYbli1bhqqqKtmRpDhw\n4ACWLl0qO0ZMBYNBLF++HHfeeSe+973vYcuWLbIjxZSu6/jJT36C22+/HXfeeScqKipkR4oLZu4j\n2T92YR9pLmbsHwFz95H97R9jUqD9+c9/RnFxMf70pz/huuuuw4svvhiLtzWMV199FTNnzsRrr72G\nlStX4sknn5QdKaaefvpp/Nd//ZfsGDGzefNm+P1+vPnmm3jggQewcuVK2ZFi7qWXXsLjjz+OQCAg\nO0pMrV+/Hrm5uXj99dfx4osv4he/+IXsSDG1ZcsWKIqCN954A/feey+ee+452ZHigpn7SLP3jwD7\nSLP1kWbtHwFz95H97R+tsQj1/e9/v3sq/traWmRnZ8fibQ3jnnvuQXJyMoCuqwc2m01yotiaMmUK\nFi5ciLfeekt2lJjYu3cvZs+eDQCYNGkSDh8+LDlR7I0cORIvvPACli9fLjtKTC1evBiLFi0C0HW1\nzGqNyT+xhrFgwQLMmzcPAFBTU2O6f+vDZeY+0uz9I8A+0mx9pFn7R8DcfWR/+8eIfzJr167FmjVr\nzti2cuVKFBcX4+6770ZZWRleeeWVSL+tYfTWfofDgeXLl+Oxxx6TlC66emr74sWLsXv3bkmpYs/l\nciEzM7P7Z6vVCl3XoarmGfK5cOFC1NTUyI4Rc6mpqQC6vgP33nsv7r//fsmJYk9VVTz66KPYtGkT\nnn/+edlxDMfMfaSZ+0eAfeQpZu8jzdo/Auwj+9U/ihj7+uuvxYIFC2L9ttIdPXpUXHvttWL79u2y\no0jx+eefix//+MeyY8TEypUrxYYNG7p/njNnjrwwElVXV4tbb71VdoyYq62tFTfddJN4++23ZUeR\nqqmpScydO1d4vV7ZUeKKGftIs/ePQrCPNBuz9o9CsI8Uom/9Y0wuV6xevRrr1q0DAKSlpcFiscTi\nbQ2joqIC9913H5555hnMmjVLdhyKsilTpuCTTz4BAJSUlGDs2LGSE8kj/vHYllk0NTXhn//5n/HQ\nQw/hxhtvlB0n5tatW4fVq1cDAGw2G1RVNc1V8YEwcx/J/tF82Ed2MVv/CJi7j+xv/xiThz9vvvlm\nPPzww/jrX/8KIYTpBoQ+99xz8Pv9ePrppyGEQFZWFl544QXZsShKFi5ciJ07d+K2224DANN930+n\nKIrsCDG1evVqdHR0YNWqVXjhhRegKApeeuml7jE2iW7RokV45JFHcNdddyEYDOKxxx4zTdsHwsx9\nJPtH82Ef2cVs/SNg7j6yv/2jIsxYwhMRERERERkQnz0hIiIiIiIyCBZoREREREREBsECjYiIiIiI\nyCBYoBERERERERkECzQiIiIiIiKDYIFGRERERERkECzQiIiIiIiIDIIFGhERERERkUH8f9V64pSs\nACGvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a9574fe50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mrkqnnOt0HHhEUtWCbdtasWKFrrvuOt18881qaGhIda6sYnX3ynegieIMaeFr\nOBTz8dw3t6Q5CQAAmc8wfOpt2abelnedjgKPSKpieOmllxQKhfTII4/on//5n3XPPfekOlf2sG1Z\n2+tkcN8Z0sQI9MV83GxpT3MSAACyg2GY6jqyUYGOXU5HgQckVaBt3rxZS5YskSQtWrRI777LLwoj\nMQ8elt3e5XQMeIhdWBDzcWvypDQnAQAgexgy1HXwNfV3NzodBVkuqXvQenp6VFJS8uGL+P2yLEum\nSy/hW7x4YczHN2+OXVimbPkNW+Tbd0DKH/42n/GVG2Iuv/3nf4j5+HiXH2k5ZKfozKkya4+fDy30\n0bMdSAMAQHbpaHxZFXOuUG5BldNRkKWSKtCKi4vV29s79O94i7OqqpIxl5kIpiEpcvyw4xWHm2Iv\nP8IQ5YkuP+nwEamiWJJUVJj/4fK+2O9V0eTS2K8/zuVHWi6djm6/16S97ZNLZZUUyNq5X+rplTFl\nsvyXnq/8s09Lbw4595l3C6+3H/Hzel9xqv0F/skyQ9WOrHtQWZ6jq3dUJrc90v6GfOEpMn25ST3/\nSO/Yy0wY21b51LOUm1/uWASv7/PGYthJTO7w4osvat26dbrnnnu0detW/exnP9Mvf/nLMZ/X3Nyd\nVMjxMprblLOjLr2DdFiWwmeeKntSmaqqShxruxt4uf203Zttl7zdfg68ifNqX5H4rND2zNVx4FX1\nte+UYfoSfm5hUZ4CvcEJSDU224qqfNalKiid48j6s2Hbj0c8x8ikzqB98pOf1Pr163XddddJEoOE\nHMu2Fa2qkD2pzOkkAAAAmABl05YoGu5RqPeQDOa5RQolVaAZhqHvf//7qc6SPUxT0ZPmOJ0CAAAA\nE8QwDE2aeZla9z6tSLCLEbuRMpT7qWZZisyaJuXmOJ0EAAAAE8j0+VUx5yr5/N691x6pR4GWYnZh\ngayZU52OAQAAgDTw+QtUPusyicsckSL0pFSyLEVOnC1xihsAAMAzcgsmq3zGx2Ur4bH3gONQoKWK\nbStaUS67goFBAAAAvCa/ZJZKq/9Gth17+iUgXhRoqWIYip402+kUAAAAcEjR5IUqnHSqbIsiDcmj\nQEsF21ZkapVUwA2iAAAAXlY69ULlFk9VElMNA5Io0FLC9vtlzZnhdAwAAAA4zDAMlc/8pHy5RU5H\nQYaiQBuvaFTR2dMkf1JTygEAACDL+Hy5qpj1KRmmz+koyEAUaONkFRfJmjbF6RgAAABwEX9eucqm\nL5VtW06p7gu9AAAgAElEQVRHQYahQBsPK6rovJkMqw8AAIDj5JfMUkn1ubItijTEjwJtHKxJ5bIr\nyp2OAQAAAJcqrlqk/LI5nElD3CjQkmRbliInznI6BgAAAFyufMZS+fMmMbIj4kKBlgzbllVdKRUV\nOp0EAAAALmcYPk2afZkMX67TUZABKNCSYRiKcvYMAAAAcfLnFKt8+lLZ4iwaRkeBlijbVmRqtZTL\nLyAAAACIX37JDJVULZZtRZyOAhdj8q4EDUxKPd3pGAAAAEjS4sULYz6+efO7E7580eQzFfV3KhCo\nk2EMnCu5/Avfj7n8C4+uiPn4+Ja39eb6S2MuB3fgDFoiLEvRGScwKTUAAACSYhiGqk+8TL7cEqej\nwKWoNBJg5+XKmjnV6RgAAAAYh5HOfKVreZ8vR5NmXqrWPc9Iskc88zWS8SxvW9GEnov04wxavKJR\nRWdOZVJqAAAAjFtOfoVKp14g26ZgwnAUaHGyiwplTZvidAwAAABkicJJp6ig/BQmscYwFGjxiFqK\nzJrO2TMAAACkVNm0i+TPm+R0DLgIBVocrJIi2dUVTscAAABAljEMU5NmXirD8DkdBS5BgTaWqKXo\nbM6eAQAAYGL480pVOu1CLnWEJAq0MVllxbInc9oZAAAAE6eg7EQVTuJ+NFCgjc6KKjp7htMpAAAA\n4AGlUy9UTl650zHgMAq0UVhlZbIrypyOAQAAAA8wDFPlMz8hGXxF9zK2/kgsS9E505xOAQAAAA/x\n55Wr9ITzmR/NwyjQRmCVl8ou5+wZAAAA0qtw0nzll87jfjSPokCLZXDkRgAAAMABZdM+Jl9OsdMx\n4AAKtBisSaWyy0udjgEAAACPMn1+lc/4uNMx4AAKtGNx9gwAAAAukFtYraKqs7gfzWMo0I7B2TMA\nAAC4RfHks5RbeIJs23Y6CtKEAu1oVlTR2YzcCAAAAHcwDEPlMy6RYeY4HQVpklSB1tPTo6985Su6\n6aabdN1112nr1q2pzuUIq4yRGwEAAOAuvpxClU27gEsdPSKpAu03v/mNLrjgAj388MO65557dPfd\nd6c6V/pFLUVncfYMAAAA7lNQdqLyy05k6H0P8CfzpFtvvVW5ubmSpEgkory8vJSGcoJVWiy7otzp\nGAAAAEBMZVOXKBQ4LDvS53QUTKAxC7THH39cK1euHPbYPffco4ULF6q5uVl33nmnvv3tb09YwLSI\nRhWdNdXpFAAAAMCITJ9f5dMuVtv+52UYDCWRrQw7ySFhamtrdccdd+ib3/ymLrroolTnSimrqVmR\nt9+XYcbuyEZxoXwXni3DMNKcDAAAAEhMS/16dTRtk2H6En6uZUU07eQrVTRp7gQkQyokdYnjrl27\n9LWvfU0PPPCA5s+fH/fzmpu7k1nduBltAeUEQlKsAi0aVXj6NNktPRO2/qqqEsfa7gZebj9t92bb\nJW+3v6qqxOkIGcerfUXis0LbvWm87bfzFyoUrVO0ryvx51pRtbb1KBBx5v1n2499jEyqQLv//vsV\nCoX0wx/+ULZtq7S0VP/1X/+VzEs5zi4skD1lstMxAAAAgLgYhqmyGUvVuucZcf1X9kmqQPvZz36W\n6hwTrr23W5NKjhlC37IUnT5FSvDSxj17dquhoV41NTt00023qLCwKIVJndXR0aHy8uweLKW9vV2T\nJk1K2/roL+6U6n5w7HaWsvssUiZvewDIBrn5lSqefJZ6mjfLMBK/1BHu5Ym7C59/+UXVtxw57nE7\nL1fWtCkJv966dS9pwYKFWrDgDL3++mupiOgaLS3N+t///R+nY0yYtWvXqKFhf1rXSX9xn4noB9m8\nnWPJ1G0PANmkuOos5RRUOR0DKeb73ve+9710rSwQCKVrVUO2b9+mxr17ddm804bOlD218TX1B0Oq\nOmOB7PJSrVmzWjt31ug3v/mVZs+eo8rKylFf85xzzlVhYZG2bn1bM2bM1JQpJ4y6fFFR3ohtX736\nSQWD/TrhhA9HkUw0T7JirbuiolINDfVqajqkWbPmpGQ9o7U/nbZv36bGxgZ94hOXxf2c8W6foqI8\nzZ9/RkL9ZSSjrfenP71fc+fOU1FRcVKvPZZY74M0en9xy3Y/Vqx+kIrP4bH7hXnzZifV/hdfXKsD\nBw7omWeeVCQS0axZsyVJBw8e0COP/F5dXZ3as2e35s07MeHXHs1I7R0pz1jbHolx42clXdy6r0gH\n2u7Ntkupa79hGMotnKpAe038T7Jt5ZfNU06eM1dBsO3HPkZm9Rm0SCSi3/3ut/r81ddIkoLhsP73\njVf09Mb1sk1D1syp2rDhDZ1++gJdffUyXXnl1frBD1bE9dp9fX0KBHp15plnjbrcnj27Yj4eDAb1\nxBOP6tlnn9bRA2kmmycRI6170OWXX6Xnn1+j/v7+lK/bKYN94XOfuz6u5VO9feLtLyMZbb27dtVp\n/frXZVlJDcg6Yh+Vxu4rUmb1l2P7gRPbebT3+8CBRq1c+ZA+9rGlOu+88/Wb3/y3JMm2bd1zz926\n8ca/06JFZ+v555+NK0+86x6pvSPlGZRJ2x4AspU/r0zF1efItqNOR0GKZHWB9sILa3TxxZfI/GD0\nxrycHH3+gqU6ccpURSvKJNNUQ0O9Vq9+UpI0Y8YsHT58KK7X/utf39AXvnCjDhxoHHW5V155Oebj\neXl5+uxnv3Dcr+DJ5knESOs+2tVX/x899lj2XL50bF8YS6q3T7z9ZSQjrTcSiaip6ZCqq6uTel1p\n5D4qxddXpMzpL8ftExzYzqO939Onz9DPfvYrSVJd3U5ddNHHJElbtmxWSUmpCgsLVVFRqXvv/Ulc\neeJd90jtHSnP0TJl2wNANiuqPEM5BYnftgN3SmqQkEzx/PNrdP/9/yl1B4b/wTCGRm7827/9nPr6\nBmZjf+edrfrIRz46tNgrr/xZhmGotrZG8+adqLfe+qu+9a3v6umnH9dLL72o1auf1A033Kzp02eM\nmCHRudUSybNx4wbddVfqz7BJ0kc+8lH9+te/1E033Tohr59uQ31hnBLtL/ff/6OE+kui612//lVd\ndNHFevTR3w9bPpG+kor5/zKlv8TbD1KxXzjrrNNivvZY73dRUbFef/0vOnjwgG6//RuSpNraGoXD\nIb3xxutqaWnWzJmzdPbZixPeJ4y07tHaGyvP0TJl2wNANjMMQ+XTL1bL7qckWU7HwThlbYF26NBB\n5ecXKD8/f3iBZtuy8/Ik/0DTfT6fiouL1d3drXXrXtKKFT+UJO3bt1eLFp2jvLw8PfbYI7r55i+q\nrGxgFMhly67VsmXXxpUj0XnAk8kzEXw+n6ZPn673339Pp522IK7nhEIhHTjQqLlz501YrmQM6wvj\nNNH9JZH17t27R9Onz5TPN3zkpkT7SpJz1R+Xz+39JZF+MJHbeaz32+/366KLLlYwGNJ3v/svuvfe\n+2VZUfX39+uCCy6SZVm65Zbr9W//dl/C+4SR1j1Se0fKc+xzE932AIDU8+eVqrj6HHUf/iujOma4\ntBZoS5acN+avx7ZtyzAMvfrqxnGta9OmjZo//9TjX1+SXVw47DHLsrRq1a/1ne/cPTTs9pw5A7Or\nb9jwhs4+e7Hy8/N13nnnj7negwcP6PXXX5VhGLJtWzt2vKtVq1apu7tfpmlo2bJr5feP/rYnk8ey\nLD311GMx70OaNm26LrxwyZjZjzV//mnatOmtuL90tbW1at26lzR37pdGXS6d/UCK3RfG836lqr8k\nmuHY9W7YsF6SVFdXq7a2Vr3yyku64oqrx8wSq48+9tgjsm077j4ai9v7y0j7hJGkajsn+36fcsp8\nfe97d6mjo0PV1VNUXT1w6Yppmurp6VFFRaVKSkpGzZLIumO1d6Q8xw6vn+i2BwBMjKLKherv2qtI\nf6vTUTAOaS3QXnvtrbStq7b2fZ177t8c97hVUS75h/+q8PTTT+j665eroqJSL774gi677HLt3r1L\neXl5euutv+r88wcu99m0aWPM1zzatGnT9fnPfzgQRW9vj26++eaEZkxPJo9pmvrsZ78Q9zriceqp\np+uppx5P6DnxXC6Xzn4gxe4L43m/Etk+V1zxiRFfJ9EMx673iiuuHvrb888/q6VLL1VZWfmYfSVW\nH/3c565L6D2Ixe39ZaR9wkhStV9I5P1+5pmntHHjBv3gB/eptbVFkydXqbS0VIsXnzc0MEg0GlVJ\nSamOHDmszs6OUbMksu5Y7R0pz7GS2fYAgNQbfqnj+K+QgTOy9hLHI0cOHz+cedTSE9vf0vvvvyfb\ntmVZljo7O/Tggz/Vr3/9S0kDvwRfdtnl2rBhvfLy8nTCCVO1e/cudXR0aMmSpQnnGO1ypqeeenxY\nlnPOOVfr1r2kn//8Pycsz2jrPlZVVbWam4+fPy7TxOwLcXBy+xxrpPVKA8OgNzTU67HH/kfLl9+S\ncJaxLrmLp69I7u8vI/WDdG/n0d7vJUsuVk5Ojv785xe1adNG/fjH/59M01RFRaU++cnL9fjjjygQ\nCOgb37grqSwjrXuk9l500cdi5jmW27c9AHiJP69MRVVnqefIJi51zFBpL9Cef/5ZdXR0qKFhv775\nzX+VJDU2Nuiuu+7QqlWPpmw9XV1dx80JZZWVaNnSG7Xs+huHPf7xj1963PNvvPHvUpIjNzd3xL9d\nc821uuaa4fesfPzjl05ontHWfazi4hJ1dXUm9Lrx3s+Urn4gxe4L8XBy+xxrpPVK0mWXXaHLLrsi\n6Syj9VEpvr4iub+/jNQP0r2dR3u/J02qGDozeux8fVde+elh/1648IyUrXuk9lZUVI6Y52jJbHsA\nwMQpnrxIwa59igTbnY6CJKS1QNuzZ7dyc3O1ZMnF+vKXbx36ovXmm+sTPsOxZs1qSbbWr39dX/zi\nl3TyyacM+3t3d5eKioo+fMCyFJ2R/uFHly+/Je3rTJWSkhJ1dXXF/FswGNQDD/xI0eiHc24EAgEd\nPNiopqbhQ5LfcMMXNGfOh/f+pLIfDFq9+knNmTNXixadfdzfjusLGCZVfTRV/eXKKz+ts846Z+jf\nifSX3/3ut5o5c5Zqa2t0+eVXDU2qLLmnHzi5T5iodY+27QEA6WcYhsqmf0wte1Zr/GM1I93SWqAF\nAr1auvQTWrnyoWEDIGzdullnnx37sqlYBidVnTfvJJWVlesHP1ihlSuHz8NjGOawX+ftwgLZkyvG\n3wgPiUaj8vlizxuWl5c39EV5UFPTIa1du0a33voPwx6vqioZdg9eqvqBNPDFf82ap7V27XO67bav\nxVzm2L6AiZGq/nKsePvL9u3b1NBQr+XLb9Hppy/UT35y77ARB+kHE2e0bQ8AcEZOfoWKKheqt3mb\nDJNLHTNJWgu0hQvPlCStXbtG3/rWd4ce37ZtS0Jz6DQ01OvNN1/X7bffOeIksqWlpert7dXkyVWS\npOjUai352N+kZM6nbBRrFLxAoFclJakfyj9V/UD6cKLh2tqaEZc5ti9I8Y0MiJG5sb+8/fYmnXba\n6ZIG7ol6//0dw16HfpAa6dz2AIDxKalerGD3fkVD8Q9WB+el/R60+vp96uhoH7qEadeuOkUiUc2f\nf5reeWerzjzzrDFfY7RJVQeVlpaqp6dHkmSXl8iuLE/76IGDjj2DlCl6e3tjjtiWCqnoB/E6ui8M\nSldfyNRtnwyn+0tbW+uwSx59Pp+6u7tVUlIiKf39gG0PAHCaYZgqm7ZErXvXyDC40iFTpH1LhUJh\n5efnD02u+/LLfxqam2j79m1xvcaxk6p+7Wt3HrfMtGnTdeBA48A/cnKkGCOPpdOaNau1Zs3T+ta3\n7lBd3c5hf/vpT+/XkSOHHUo2sgMHGjV16rQJee1U9IN4DesLLrV69ZPatm3L0L9H6y9u5XR/sSxb\n5lGXcESjkWGX3bm5H4y1vd26jxg0kdseADA+uYVTVDhpvmzbcjoK4pT2M2gnnXSyLr74Ev32t79S\ncXGxzjzzLNXUvK+VKx/Spz+9LO7Je8eaVPXUUxeotvb9oaHInfTqq6+OeM/crl11Wr/+dX3uczc4\nnPJ4NTU7dOqpp8e9vN+fo7y8vLiWHasfSKmbfNtNfeFYse6hi+ceSzdyur9UVVWpv79v6DmWZauw\n8MNBQdzaD8ba3m7eRwxKdNsDANKrZMr5CvY0yor0jb0wHOfIPGjf+MZdw/59/vkXDPt3PJP3xppU\n9WjnnfcRPfPMk+MPmwL79u1TTU3dcffMRSIRNTUdUnV1tcMJY6utrdGXv/z/xr385MmTdcMNN8e9\n/Fj9IFWTb7upLxwr1j108dxj6UZO95dzz/0brV37nKSB9/DUU08b9ne39oPRtrfb9xGDEt32AID0\nMn1+lZ5wvtrrX3I6CuKQkRNVjzZp76BJkyYpPz9fXV2dKi119ub1G2+8UfX1A5O4Hn3P3Pr1r+qi\niy7Wo4/+3sl4MQWDQXV0tGv27DlORxnTWBMpu6kvxCOeeyzdxg395fTTF+q11/6iP/3pBdXV7dT/\n/b//POzvbu0Ho21vN+8jBrlh2wMAxpZfOkd5pbMV7NrndBSMISMLtNEm7T3asmXX6rnnntX11y9P\nQ6qRHXvP3IoVP9TevXs0ffrMoXtq3ObPf35RV155tdMx4hLPRMpu6QvxiNVf3M4t/WXwLM4nPxn7\nMkY39oORtrfb9xGD3LLtAQBjK5t2kZp73Hk/Nj6U1cO5XHTRx7Rjx7vq7+93Ospx98zV1OxQXV2t\n1q5do7a2Vr3yykvq7OxwOqakgcuqXnvtFV155WecjpIybuoL8RjrHks3yaT+4tZ+EGt7u3kfMSiT\ntj0AQPL5C1Rcfa6M7C4BMl7Wb52vfOU2rVz5kNMxhu6Zq6ycrBdffEFXXHH10H8VFZVauvRSlZWV\nOx1TkvSHP6zSLbf8g0yHR75MNbf0hXgc21/cLNP6ixv7Qazt7eZ9xKBM2/YAAKl48hnKK5npdAyM\nIuuPqtOnz9BHPvJR/eUv6xzL8MILL+jnP/9P3Xzzdbr66k/qj398fuhvL764Vg0N9Xrssf9RR4fz\nv46/9dZfNWfOvKEhzLOJG/pCLIP30D333DN6++1NWrfuJT344E9j9he3ycT+4rZ+MHhP7Ujb2237\niEGZuO0BAAMMw3A6AkZh2LZ9/BjmE8Qrk7Yey0sT1sbi5fbTdm+2XfJ2+6uqSpyOkHG82lckPiu0\n3Zu83H4vt12K7xiZ9WfQAAAAACBTUKABAAAAgEtQoAEAAACAS1CgAQAAAIBLUKABAAAAgEtQoAEA\nAACAS1CgAQAAAIBLUKABAAAAgEtQoAEAAACAS4yrQNu9e7fOPfdchUKhVOUBAAAAAM9KukDr6enR\nf/zHfygvLy+VeQAAAADAs5Iu0L773e/q61//uvLz81OZBwAAAAA8yz/WAo8//rhWrlw57LFp06bp\nqquu0vz582Xb9oSFAwAAAAAvMewkKqxPfepTmjJlimzb1rZt27Ro0SI9/PDDE5EPAAAAADwjqQLt\naJdccon++Mc/KicnJ1WZAAAAAMCTxj3MvmEYXOYIAAAAACkw7jNoAAAAAIDUYKJqAAAAAHAJCjQA\nAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAA\nAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAA\nAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAA\ncAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABw\nCQo0AAAAAHAJCjQAAAAAcAkKNAAAAABwCX+yT/zlL3+pl19+WZFIRMuXL9eyZctSmQsAAAAAPCep\nAm3jxo3asmWLHnnkEQUCAT300EOpzgUAAAAAnmPYtm0n+qT7779fhmGorq5Ovb29uvPOO7VgwYKJ\nyAcAAAAAnpHUGbT29nYdPHhQv/jFL9TQ0KCvfvWreuGFF1KdDQAAAAA8JakCrby8XCeeeKL8fr/m\nzp2rvLw8tbW1qaKiYsTn2LYtwzCSDgoAQDbi+AgAqfGXAw3a2dk+6jLTi4p15ex5aUqUnKQKtMWL\nF+vhhx/WLbfcosOHD6u/v1+TJk0a9TmGYai5uTupkJmuqqrEs22XvN1+2u7Ntkvebn9VVYnTETKK\nl4+PEp8V2u5NXm7/RLa9sa1TvcHgqMt0WX5H3/t4jpFJFWhLly7Vpk2bdO2118q2ba1YsYJf/wAA\nAAA4pjsScjpCSiQ9zP4dd9yRyhwAAAAAkJSwZak3HJHPzPyTRkxUDQAAACCjNfcHZCnhweldiQIN\nAAAAQEZrDvYpx8yO0iY7WgEAAADAszrDow8Okkko0AAAAABktK5wdgwQIlGgAQAAAMhglm1ToAEA\nAACAG3SGgwpaUadjpAwFGrJaS3+TbDs7RvQB4tURbFXYyp5fEgEAGM3Bvt6sGSBEokBDljsQ2KMj\n/Y1OxwDS6r3OvypqR5yOAQBAWnSGQzKMzJ//bBAFGrJajpGjht46p2MAaWPZlpr7DzgdAwCAtOnK\nohEcJQo0eMDh/kZZtuV0DCAtDgX2c3kjAMBTsmmAEIkCDR4QigZ1ILDX6RhAWjQGdss0fE7HAAAg\nLQKRsALR7LqsnwINWc9n+nUwsMfpGMCEs+yomrnnEgDgIQf7euXLovvPJAo0eMTh/kZFrOz6dQU4\n1v6enQozOAgAwEPaw0GZFGhA5rFsS/U9tU7HACbUwb598nF5IwDAQ7Lt/jOJAg0eYRqmDvZxHxqy\nVyjar5b+g07HAAAgrbJtBEeJAg0e0hI8pGCkz+kYwITY2/O+0xEAAEirsGWpKxx2OkbKUaDBMwz5\ntLvnPadjABPiUF+9DINdOgDAOw7390qynY6RchzN4RmGYaipr97pGEDK9Ya71BY87HQMAADSqiXY\nJ7+ZfeVM9rUIGEVnuEWdoTanYwAptbvnXfkMv9MxAABIq45Q9t1/JlGgwWNM+bW3Z4fTMYCUsW1b\nhwMNMrJsiGEAAMbSmYX3n0kUaPAYwzB0uK9Btp191yvDm1r6D6k72ul0DAAA0ipiWeqKcAYNyAp9\nkR419XMvGrLDvt4a+Y0cp2MAAJBWTf29srL0B3cKNHiOafpV37PT6RjAuFl2VEf6Gp2OAQBA2jVn\n6QAhEgUaPOpI/wFFrIjTMYBxaejdpZCdnZd3AAAwmmwdIESiQINHRe2o9jGxLzJcY2A3ozcCADyp\nIxxyOsKEoUCDJ5mGqQOBvU7HAJIWjPSpuf+g0zEAAEi7sGWpO0KBBmSdtuBh9Ya7nI4BJGV3z7sy\n2IUDADzoUF9vVo/IzdEdnmUaPu3uedfpGEBSDgX2M/cZAMCTmkOBrB0gRKJAg4cZhqFDgfqs/gUG\n2ak1eFid4XanYwAA4IjOUPZe3ihRoMHjApEu5kRDxtnX/b78JoODAAC8qTOcvSM4ShRo8DifmaP6\nnjqnYwBxs+yoDvXxowIAwJtCVlRdWTyCo0SBBuhwf4PC0ez+oCN77O/ZqbBNfwUAeNPBQK+y/Rbs\ncRVora2tWrp0qfbuZbhyZC7LtrS3Z4fTMYC4NAZ2yWf4nI4BAIAjWkJ98hnZfY4p6dZFIhGtWLFC\n+fn5qcwDpB1zoiFT9Ia71NLf5HQMAAAc0xHK7vvPpHEUaPfdd5+uv/56VVdXpzIP4IiOULM6gi1O\nxwBGtat7u0zOngEAPKw9ywcIkZIs0J588klVVlbqwgsvZIhyZAWfmaM9Pe85HQMYkW3bauqrZ+4z\nAIBn9YRD6o2EnY4x4Qw7iQpr+fLlQ18SampqNHfuXD344IOqrKxMeUBgPLYeeVM1bdviWtZn+PW3\np9zK/T1wpf1ddXr9wB/lM8YeXj8UDelz8/9eBf6iNCQDACA9trc2642mgzLH8WPl9KJiXTl7XgpT\npV5SE+n87ne/G/r/m266SXfffXdcxVlzc3cyq8t4VVUlnm275Gz7Ozv61BuIb8S7qN2nzXs3a27J\naSlbv5e3vZfbLqW+/VuPbFV/0JI0dn8OW0G1tPQo32elbP2JqKoqcWS9mYzPijfbT9u92XbJ2+0f\nT9t3t7Spr298Ixl3WX5H3/t4jpHjHgKFy22QLXyGT/W9zIkG9+mL9OpIf6PTMQAAcJQXBgiRkjyD\ndrRVq1alIgfgCm2hw+oKt6s0Z5LTUYAhu7rflcG0lQAAD4vattpDwayfA01iompgGJ/h1+6ud52O\nAQyxbVsH+/ZytQIAwNOO9AcUsZ25dD/dKNCAYxzq2yfLjjodA5AkHQzsU1/Ym/cpAAAw6FBfr3JM\nb5Qu3mglkICgFdT+np1OxwAkSft7a2Wa474aHQCAjNYe6nc6QtpQoAHHGBgshAINzgswOAgAAJK8\nMUH1IAo0IIa20BF1BFucjgGP29W9jcFBAACeF4iEPTFB9SCO/EAMPsOvXd0MFgLnWLalg4F9DA4C\nAPC8hkD3uCanzjQUaMAImvr2KWJFnI4Bj2oM7FZftNfpGAAAOK4tFKRAAyBF7Kj2dL/ndAx41P6e\nGvkMBgcBAKDNQwOESB4s0FavflLbtm1xOsaoHnjgx+rp6dGePbv19NNPOB1nVJnwfibLNEw1BHY5\nHQMe1BVqV0uwyekYAAA4Lmrb6gh5Z4AQyUMFWjAY1BNPPKpnn31atm07HWdU27a9reuuW6ZVq36t\nyy67wuk4MWXS+zkeXeE2Hek74HQMeExd9zbOngEAIKmpr0dhj0xQPcgz3wDy8vL02c9+QbW1NU5H\nGdPnP3+DrrjiaqdjjCqT3s/x8Bl+7e5+V9UF052OAo+IRMM61Lff6RgAHGbbtrojIR3q71VXOKze\ncEhB21IwGlXYjsqybdmSZEt+01SOYSrHNFXg86vQn6NiX46mFhSpLCeXwYaQ0Q71BzwzQfUgzxRo\nmeVDpbEAACAASURBVKStrVUbNryhurpaXXzxJZo1a7bTkTztSH+j+iK9KvAXOR0FHrCn5z1FrIhM\nw1sHI8DrbNtWS7Bf9YEutYWCag31qT8alc8wxhwcIRy11Bfj9SJttgp8fpXn5qkyN1+zC0s1OS+f\ngg0ZpdVj959JFGiSpCVLzhtzZ2XbtgzD0Kuvbkz49UOhkPbu3aO5c+fFtfyNN/6dJOnMMxfp9ttv\n0y9+8Zu05EyVeHJK7sgaH0N13dt05qQLnA6CLGfbtup7d1GcAR5h27aa+nq1p7dTTX296o5E5Dc/\nPH6O56yBYRjKMQxFbEstwT61BPv0Xmebivx+Tckv1LyiMk0rKKJYg6vZtq22IAWaJ7322lsT+vrN\nzc1at+4lzZ37pTGXffXVV7Rt2xb94z/ervz8Au3atXPobxOdM1WOzVlVVaLm5m6H0oyfYRhq7N2r\nheUfkWn4nI6DLNbUX6/uSDv3nwFZLhSN6P2udjV3NKqxvWuoEDu6OJsIftNQ0IqqPtCtPb2dKvHl\nakZhsRaWVarQnzOh6waS0RLsV9CKcokjJka8v1AVFRXp0ksvkyQ1NtZr4cJFExkLcQpafdrXU6t5\nJac7HQVZbG/3DoozIIv1RMLa1t6sfYEuWbatkqJ8x754+g1TfVZEO7vbtbO7XdMLi7WgtFLV+YWO\n5AFiaQx0y+/Bs7ye+ibw1FOP6/3335Nt27IsS+ecc+7Q355//ll1dHSooWG/vvnNf5UkNTY26K67\n7tCqVY+mLePixefp2Wef1u7du9TUdEjf//6/D/u7W3JK8b+fP/7xfY7mTAWf4dP+nhoKNEyYnnCH\njvQf4CwtkIW6w0FtaW9WfWDgahIjjvvK0mXwB+SDfb1qCPTohPxCLSqr0pQCCjU4rzXU78nLcD1V\noF1zzbW65pprj3t8z57dys3N1ZIlF+vLX751qPB58831mjLlhGHL/u53v9XMmbNUW1ujyy+/Ku4B\nPBIZiv7Tn14W8/FEckoDc5TNmTNXixadHfe6ExHv+zkoVs41a1ZLsrV+/ev64he/pJNPPmVCsqZC\nR6hVzX0HVVUwzekoyEI7u96R4Z2ZTwBXWLx4YczHN29+NyXLn3POAoUs67ghwr/7zOqYy9/9mf8T\n8/GJWv7Y5XyGoeZgn/54eL9OyC/U4knVqswriPlawESzbVttYe/dfyZ5rEAbSSDQq6VLP6GVKx/S\nhRcuGXp869bNOvvsD88Kbd++TQ0N9Vq+/BadfvpC/eQn9+ree+8f9lrBYFAPPPAjRaPRocei0ZD2\n7t2npqZDw5a98spP66yzzkl5zmAwqDVrntbatc/pttu+NuprPvfcM9q4ccOIv07Ytq2cnBz9y798\nR35/fN0l3pwbNryh009foHnzTvr/27vzMKmqO2/g33uruqu36r262UFBENKKbIoIIpsBt1GzuKBE\nM89M5pk3z6jRoMaFROOQ1cmbjLxhNBqiTkxCjBIVBQQVcEGWZlHohaXpvavX2td73j86tCDVTXV1\nVZ1bdb+f5/F57Mutqu+prtvn/urecw4KCgrx4x+vwrp1f4zqNWQwqWbUOg+wQKO4C4YDaPQeN+S3\nhETpSAiBzxwd8IRDSMWVQk8VahubT2BcbgFmFZfBYuIpIyVXTzAATyhkuPFnAAs0AEBFxcUAgI0b\n38DDDz/et33//n24884vrgDt3bsbkyf33uJms5Xh8OHPz3oui8XSd2XrlEDAgZdf/hPuvvtfkpJz\nMGuUXXvtDbj22huGlCvWnPX1J/HRRztw330rMWrUGLS2Np/1XHrT6muAJ+REjtkqOwqlkRrnAWha\nCApnbyRKqv6ufA1l/w6/Fx91tKDT78Nj/VzJ6k9/V75k7a8oCk64e9DgcaKisARfyS/hF0mUNCcN\nOv4MMFCBdmrq9y/fanhqmve6uhPo7u7qu6JVW1uDUCiMSZMm48CBSlx88SXo7Ow44xY9k8kEp9MJ\nqzV+J+vxyJkM8ch5883fgNfbu3LLgQOVuOyyy5OSfSgUqKjq2YdpJVfKjkJpQgiBenctizOiFKcJ\ngd2dbahydkJVFJgSPCNjsiiKgjAE9nbaUed24vKS4Si2ZMmORQbQ4fca9gsBwxRo27d/ik2bNiI7\nOxuVlfswY8YszJkzt+/fg8EgsrKyYDL1DtDfunUzJk26EEDvrY0XX3wJNE1AVb8YwB8Oh2Ayxfek\navv2T9HU1Ii33vo7xo+fACGAhQsXDypnMsQjp8lkQl5eHpxOJ7Zt24JVq55KSvahUBQFjZ5juKjw\ncphNnJKYhq7eXQNPyAWTyslBiFJVp9+LHe3N6An6dTP5R7yZVAXdQT82tpzAZGsxphXZDHvyTMnR\nEfDLjiCNYb6ybWxswLp1v8O8eVdh1qzL8LvfrT3j3ydMuADz5y/E73//HNavf+UfBYQZ69b9DkuX\nXgsAsNls8Pm8fY/RNIGcnNy45hRCYPXqJ3D77Xdi6tRpePPNDYPOmQyDyfniiy/2m1PTNPzhD8/j\nsceeQFFRUdLyD0VIhFHjPCA7BqWJ467DLM6IUpQQAgd72rGxpQ7OUCBti7MvO+Rox5vNx9Fj4BNo\nSixXMABXKCA7hjSGuYI2cuQorFnzHACgpqYa8+bNP2uf73//B2f8PHv2nDN+njnzUmzc+CaA3vFT\nF144OarXzsjIgMViiWrfffv2wGrNR05OLnJycvGTn/xy0DmTYTA5Ty1UHSnna6/9FbfddgeKi0uw\nadPbuPrqpQnPPlSqouKkpxqTCqZB5W1pNAR2bxM6/W0wqYb5U0yUNoLhMD5ob0Sjx502tzNGy6So\n6AkG8FbzCUwvsmFSfrHsSJRmjrsdhh1/BhioQAOA3Nw87NjxPpqaGnHffd8f9OOnTKnA9u3vY/Pm\nt1FTU43/+I/7o3pcWVkZbr99RVT7VlUdQTAYwIcf7kB7ux2jR4/BtGkzBp11oDXK4iEeObdt24Lf\n/va/8fzz/wMAmDRpckoUaADgCblw0l2NcXkXyo5CKazGeYDFGVEK6vB78b69EZ5Q0HDF2ek0CHzS\n2YpWvwdzSobDzLsBKE7sBh5/BhisQDObzZg7dz78/gAef/yhs6bIj8Z3vvN/AABLliSmkNC0MHw+\nH+bMmQtN03DXXbfFtLBzf2uUxUs8ci5YsBgLFiw+9446ZFLMOOb8nAUaxax3YeoGLkxNlGKOuXrw\ncXszhAJDn0CeYlIU1Lmd6PL7Mb9sFAozo7tjiKg/Qgh0BIy5/tkphrw/a+LESdi5czu6u7tlRzlL\nWVk5ysrKAQCqqsLlcsHpdEpOdbZUyZlIjmAHWrwnZcegFHWkZx8XpiZKIUII7Otsw872JgjWZWdQ\nFQWucBAbm0+gzuWQHYdSXFfAD3coKDuGVIY5O9iw4W949NEHAQAdHe0oLbUhPz9fcqqzzZgxC52d\nHQCAcDgMqzU/rtP4x0uq5EwkVTGjxsHJQmjwfGEvmjxcmJooVYSFwPv2Rhzq6TDMRCCx0CDwQXsj\n9nfZz1qGhyhadQYffwYY6BbHefPmIyMjA+++uwm7d+/CL37xa6g6XJm8uLgES5Ysxfr1r8Dj8Zw1\nIYhepErORGv3N6PT34ZiS5nsKJRCjvTshQBg7O6HKDUEwmFsaa1HR8AL1cDjzaKlKgr2d7ejM+jD\nlbZRMBn8RJsGrz3gM/wXmIYp0IqKirFs2XUAgEWLrpacZmDXXHO97AhRSZWciWRSzKjuqcTsMn1/\npkg/QuEgGt21hu98iFKBJxTEppaTcBloCv14MKkKGjwubGw+gSXlo2ExGeZ0k4ZIEwLtfu+5d0xz\n+ruERJRiWnz1cAX1N56R9KnauR8hEZIdg4jOoSfgx1vNJ+AKBfiFSgxURUF3wIc3m0/AwfXSKEpt\nPg/8Wlh2DOlYoBENkQIFh3v2yo5BKUATYdS5j0Dh+nlEutbp9+Kdljr4tTCLsyFQFAXecAhvt9Sh\n1eeWHYdSQL3XiQwdDkFKNr4DREOkKAqaPSfgDbHzoYHVOg7CHzb21MFEetfu92Jzaz2CQpMdJW0E\nhYatrQ1o8BhrtmcavHY/+0iABRpRXAgAh3v2yI5BOqYJDcddR7juGZGOtfrc2NJ6EiEWZ3GnQeAD\neyOOuXpkRyGdCgsNHSzQAMRYoIVCIaxcuRLLly/HN7/5TWzdujXeuYhSiqIoaPAc5dUR6tcJ52F4\nwvz2mEiv7D4vtrY1IMzp4RNGAPiwoxlVjk7ZUUiHGjxuhPnlCIAYZ3HcsGEDioqK8LOf/Qw9PT24\n8cYbsXDhwnhnI0opQggc7tmNS4rnyo5COiOEQK3rEEwKZzIj0qMOvxfvtp6EBhZniaYA2NXZiryC\nbIxEtuw4pCONXhfMHH8GIMYraMuWLcM999wDANA0DWYzTzqIFEVBvbsWAV5Foy854ToCT4hXz4j0\nqNPvxbut9QizOEsaVVHwcWsTDva0y45COmL3eWRH0I2YKqvs7N5vPFwuF+655x7cd999cQ1FFC+3\nLLwdIS141vafvrEq4v4PXvejiNuj31/gB8qPcbCyNuL+M2ZURNy+Z8+hhOzf335GkOz3ur/9hRCo\ndR7Cw9f/OOL+ifgs/njDQxH3IaIzOQJ+bGkz7oQgT9zwTxG3P77h9YTvb1JUVHbaoQmBqYU2AMn9\nu23k/hHQTx95yrTpX4EnHETvNdYvJOKzuGbTloj76EnMl76am5vx3e9+F3fccQeuueaaqB5js1lj\nfbmUZ+S2A/Lar6oKlAhfiubmZEbcv7/ZlKPfX0EYYRQUZSLTbAFwZttVNfIL9Pf+DHV/2Z87ma+f\n7Pc60v42mxW1XZ9BZHri8NmKfv+cbAtKS/OQbc6N/CSkO7KPVdlktN8TDOLt4/XIzMpA5KMqOXJz\nLNJeu7/Ft/vLFO/9rXlZqA04UCiyMbNseFL/buvhmDNyH/nlx2mK+Mfn5czHJeKzmG/N0sXvfyCK\nEIMfDdve3o4VK1bg8ccfx+zZs6N+nN1uzFt8bDarYdsOyG3/512fotaV3G/JhBAYlzcJU4uvMPTv\n3shtB3rb39bmwJbm9fCGXUl97aDmx7WjViDLlJPU1z1F7x2fHhn9WEl2+wPhEN5qrpO+CHVujgVu\njzEXcT697ZomMLWoFBf/40qaERi5j4zU9s0tJ9HmT84tjsOycrGofHRSXiuSaPrImMagrV27Fg6H\nA2vWrMGdd96JFStWIBAIxPJURGlHURScdNdwLBqhzl0Fd4hTShPpSVgIbGqtl16c0RdUVUFlVzvH\npBlUWAiOP/uSmG5xfOSRR/DII4/EOwtR2tCEhs97dmPksGWyo5AkQghUO/Zz3TMiHRFCYFtbPboC\nvn5vkSI5TKqCfV12mKBiSkGx7DiURPVuB4JCg1nhDI6n8J0gSoBTV9G8QX4jZFRVXQfgDjlkxyCi\n03zS0YJmr5vFmU6ZFAV7ulpR4+yWHYWSqNHn5vT6X8J3gyhBhBCotH8kOwZJoAkNhzsque4ZkY4c\n6Laj2tXN4kznVEXBJx3NOOHi7eFG0ebzyo6gOyzQiBJEURQcd1Rz/SsDqnEcgCeU3IlBiKh/x1w9\n2N/dDhOLs5SgKAp2djSjwcP+M931BAPoCRhzopyBsEAjSiBFAIe6P5Edg5IopAVx1PkZTBx7RqQL\ndp8XH7c388pZCvrA3oRWn1t2DEqgY65umPuZkt/IWKARJZCiKGj2nEBPoEN2FEqSIz17EdA4gyeR\nHrhDQbxnr4fg+V9KEhB4r60RXQH+TU1XLT4PZ1ONgAUaUYIpigmHunfJjkFJEAj7cNx1GCpnoiKS\nLqSFsaW1Hv5wWHYUGoKQ0LClpR6uUFB2FIozfziEdj/Hn0XCswiiJLD7GmH3NsmOQQl2qHsXNKHJ\njkFkeEIIbLc3wRH089v5NODXQtjcUodAOCQ7CsVRrZMTwfSHBRpREqiKCZ/17IIQQnYUShBXsAf1\nnhqeDBLpwP5uOxo8Lo47SxOKosAdCmJzaz3C7EfTRpOPS170hwUaUZJ0++2od9fIjkEJcqj7Eyj8\nk0okXZ3LgYM9HVA58UBaURQFnQEftrXV88vONBDSNLT5uVZsf3g2QZQkqmrG4Z69vAUuDdl9zWjx\nnpQdg8jwugN+fNjBGRvTlaooaPK68GFHs+woNETH3D28GjoAFmhESeQNu1DtqJQdg+JICIHPuj6B\nymn1iaQKhsPY2loPDTzpS2cmRcVRVw/2d9llR6EhaPC4uC7hAFigESWRqphQ6zyIQJhTBqeLOnc1\nugM8USCSSQiB7e2N8IQ5058RmBQFB3raUevslh2FYhAWGlp9vL1xICzQiJIsrIVxsPtj2TEoDsIi\nhCM9e6CqZtlRiAztQHc7Gj1uTtJjIKqi4JPOFjR6XLKj0CAddzgQ0Lj8xUBYoBElmaIoaHAfRZe/\nXXYUGqLD3XvgC3MNFyKZGj0uHOxp56QgBrW9nQtZp5rjjm6YVZYgA+G7QySBoqg42PURZ6JKYZ6Q\nE8ecn3NRaiKJ3KEgdrQ38cqZgYWFwLut9fCGuEZaKtCEQIObVz3PhWcWRJJ0Blpx0l0tOwbFaH/n\nTghORkAkjSYE3mtrQJC3ShmeLxzCltaTCPGzoHt1bgd8LKbPiQUakSSqYsLnPZ8ipHFQe6pp9tSh\n1VvPb+2JJPq0sxUdAR+PQ4KiKOgO+vGevZF3pujcCbeDtzdGge8QkUSBsB+fdX8iOwYNgiY0HOr+\nmBODEEl0wtWDamcXp+mmPqqioNnrxq7O1gH366p/F1Vbvo39f1uIqi3fRlf9u0lKSCFNQzNnb4wK\nCzQiiRRFxQlXFboDnDAkVRzu2Q13iPfPE8niDAbwcUcLF6Oms6iKgipHFz7v6Yz471317+Lkp0/C\n5zgGCA0+xzGc/PRJFmlJUuvqRkhosmOkBBZoRJIpiorKzh28LSMFuII9OOo4xIlBiCTRhMAH9kaE\nOf6T+mFSFeztakW9x3nWv7VVvRzxMW3V/5voWASg3uPkVe8o8SyDSAe6/XYcc30uOwadw77O7QA7\nFyJpTo07IxqIoijYYW86a/p9n/NExP19jsjbKX784RBafFyWJlos0Ih0QFXNONyzG74Q783WqxOu\nKrT7m2XHIDKsOreD484oahrOnn4/yzou4r5Z+ZG3U/xUO7sBXvmOGgs0Ip0Ia2Hs69ouOwZFEAj7\n8FnXJzApnBiESAZ3KMhxZzRovnAI77bWI/yPIQRlk5ZH3K9s4u3JjGVIDV4Xj99BYIFGpBOKoqDF\nW48G9zHZUehL9nVuR0hw3RYiGYQQ+KCtkeud0aApioKuoA8f2BsghEDR6EUYM+sxZBWMBxQTsgrG\nY8ysx1A0epHsqGnNEfSjjbM3Dgq/DibSEZNiwoGuj1CWNRKZJovsOASgwX0MzZ4TnFafSJLKbjvs\nfi9MKr99p8FTFQX1bhf2mtswo7gcRaMXsSBLss97Onlr8iDxChqRzgQ1Pyq7dsiOQQCC4QAOdn/E\n4oxIklavG5/1dLA4oyExqQo+c3SixtktO4rhaELgpMfFBeUHiWcdRDqjKAqa3MfQkH0eRuWeLzuO\noe3r2o5A2M+OhUiCQDiM7e1NPP4oLkyKgl2dLfjc0YHNLSdx0uPCmJw8fGP0RMwvGyk7Xto64eqB\nNxyEWeU1ocFggUakQ6pqxoGunbBljYDFlCU7jiE1uGrR6DkOk2KSHYXIkHZ2NMMXDrFAo7ipczvw\nYUdL388nPE78vGoPALBIS5Cj7h4WZzHgO0akU0EtiL0d78mOYUi+sBcHuj5icUYkSbWjC/UeJ4sz\niqvPHJ0Rt/+loSbJSYzBHQqimZODxIQFGpFOKYqCFl89jjk/kx3FUIQQ2N2+FUERlB2FyJCcQT/2\ndLVxUgGKO0cwEHF7vceZ5CTG8HlPJwuNGPEWRyIdMylmfNb9KWyWkbBmFsqOYwi1jgNo9zVxYhAi\nCTQh8L69ERoXtKUEyM/IxIymbtxR78RYTwh1OWa8NNqKY+OGyY6WdoQQqPc4eBU8RixsiXROQODT\njnehCU12lLTX5W/HYcdeFmdEkuztakNnwCc7BqWp2xzAqqoujPeEYAYw3hPCqqou3OPPkR0t7Zzw\nOOEMcf3QWMVUoAkhsGrVKtx6661YsWIF6uvr452LiE7jCHZjf+dO2THSWigcxKcdW2THIDKsFq8b\nRxydMCn87pgS4+qjbRG3Tz54NMlJ0l+VoxNmLo8Rs5j+Cm7ZsgWBQACvvPIK7r//fqxevTreuYjo\nNKqios5dhQZXrewoaWtP53vwhjiYmUiGYDiMne3NvB2KEqqoJ/Lf+MzOHrR63UlOk746/F60+r2y\nY6S0mAq0PXv2YN68eQCAqVOn4tChQ3ENRURnUxUTKrs/hDPAhTbj7ajzEJq9dTw5JJLko45meMOc\nmIcSq6sg8q2MXQU5eM/eCGfQn+RE6elQTwfM7E+HJKYCzeVywWq19v1sNpuhaRwfQ5Romgjjk/Yt\nCGk8kYmXdl8LPuv+FCqn1CeSorqrEyfcnFKfEm/vlLERt++bMhYhoWFzSz0CYY6bGgpvKIiTHpfs\nGCkvppHweXl5cLu/uBSsaRpULkJHOiQgIIS82cCEiP/ru0I92NPxHmaVLorr88abJjTdT2wSCPuw\nq31LQj4jifjdR//icl6WUtOMGRURPzK7dx+MuP/MmRdF3B7L/p5wCNvbG6Eq6DtenvynGyPu/9jr\nr0XcPpT9+9snWaT+nZBMRttrx5YBEJj2+UkU9XjQVZCDfVPG9G4XAu5wEJtb67F0+FgoSOwXBpoQ\n0NLwd3+gpwOAwEBNk/25T4VjLqYCbfr06di2bRuWLl2KyspKTJw4MarH2WzWc++UpozcdkBe+6fl\nT8dIT/pNnxsI+7DF/pK+z8M7ZAc4F4H8zCLMGXel7CBxp0DBiMJSLrSdQmT2ET4tjHCEL1NetR+L\nuL+nn1sRY9nfmpGJy8uHA+VfbP+FOfKpyVfHnx9x+1D2728fSmPjz4dj4eVwnPrxH/+dEhYCG+0n\n4QuHE5vDntinl0EI4ILCIiwt0/dxVWjJgi03T3aMASkihjJSCIEf/vCHqKqqAgCsXr0a55133jkf\nZ7cbcyFAm81q2LYDxm5/Ittu9zbiI/s7gE5vC8rNyYTbE3lRUD3INuViwbCbYU7QlPpG/9zT4Mj8\nrLzTUod2CQP6TVBxw8jzMHZ4saGPFbZdf7yhEN5qPg6flrgiLTfHArcnvca8qVDx9dETkHGOu+r0\n/LtPhmj6yJjOTBRFwY9+9KNYHkpEcWLLHomLii7Hga6dUHilZFDMihmX276asOKMiAamaQKzbeXI\nMWfIjkJ0lmyzGYvKx+Dt5jqEoe9b9fVCCIEJ1oJzFmcUHb6LRCnsPOtknG+tgJbAb/nSjQLg0tIl\nyMsokB2FyJCEEBiTa8X4PB6DpF+FmRZcVTYywSPR0odJMeGSIpvsGGmDBRpRiqsovAzDc8bqfkIO\nPdBEGJcUzUNpVvqNSyRKFVkmM+aUjpAdg+ichmXnYk7J8AEnvKDeL10uyOPVs3jiO0mU4hRFwazS\nRSjOLEuJmYlk0UQYXym4FKPzJsiOQmRYmhCYUzqcJ3KUMsblFWBmcRk0dq/9MikmTOXVs7jiX0ii\nNKAqKuaULYM1o5BFWgSaCGOC9SJcUHCx7ChEhqUJgYnWIozI1vfsaURfdmF+MSoKihFm/3oWTQhc\nwLFncccR8kRpwqyaMbfsWrzf+jpqHQdR6zoIV7AbeRmFmGC9CCNz9D3tbaJoWhjjrJNRUXSZ7ChE\nhpZvzsTM4vJz70iUQLva38XGxpfQ7KnD8JyxWDbyDlwaxbqi04rK4NfCqHF0Q1U5Mu0Us2LC1EJe\nPYs3FmhEaSTTZEGO2Yp9XR/0bXMGu7Cvs/dnoxVpmhbG6NwJmFo0R3YUIsObaxsBk06XBSFj2NX+\nLp6reaLv50bPsb6foynSLisehkBYwwmPg59l9K4ZV1FQxKtnCcB3lCjNbGn+c8Tttc6DSU4il6aF\nMSbvAkwvmQ+FHSmRNGFNoCK/BCWWbNlRyOA2Nr4UcfvbjS9H9XhFUTDXNgIjsnKh8XZHWM2ZuKiw\nVHaMtMQCjSjNNHvqIm53BbuTnEQeTYQxNu9CTCu+ksUZkWSllixczJM40oH++scm74mon0NVFCwo\nH40yS7ahizRNCEwvskFlH5sQLNCI0szwnLERt+dlFCY5iRyaCGNC/sWYVjKXxRmRZKqiYJ5tFI9F\n0oX++scR2eMG9TwmRcHiYWNQkplt2Im5yrNyMDY3X3aMtMUCjSjNLBt5R8Tt4/Mqkpwk+YTQ8JWC\nS1FReKnsKESGFxYCMwrLYM3IkB2FCED//ePSkcsH/VwmRcXVw8agIMNiuCJNCGBWESf8SSROEkKU\nZk4NdH678WU0eU9gRPY4LB1xOzLUTNS5q6EqJskJE0OBguklCzAq11gToRDpkRACI7NzMTG/SHYU\noj4R+8eRy6OaICQSs6pi6fBxeLv5BHqCfkNcKdaEwIS8QhRZsmRHSWss0IjS0KWliyJ2OHnmQhzu\n2Q2kUScihIDFlIXLSpegyMKpfon0wGIyYW7pCNkxiM7SX/8YqwxVxbLh4/B2cx26g760L9JyzRm4\ntIRXzxKNtzgSGcgFBRdjtu1qmBVzWtySoYkwCi2lWDDsZhZnRDqhCYHZxcNhMfE7YDKG3itpY1GY\nmZUWfWt/BIDLS4bDpLB8SDS+w0QGU5Y9CguHfQ1FllJoIiw7Tsw0EcYE60W4sux6WEy81YJIDzQh\ncH5eAUbnWmVHIUoqs6pi6bCxKEnT2R01ITA+Nx/Ds3NlRzEEFmhEBpRlzsG8susxMf+SlPu2TwgB\ni5qFObalqCi6LO1vJyFKJXnmTMwuGSY7BpEUZlXF1cPGYnh2LsIp1reeS545E5fy2E4aFmhEBqUo\nCqYUzsSV5dcjz1wATWiyI52TEBpG5p6HRcO/jrLsUbLjENGXzLXx9icyNpOiYFHZaIzNsULTqY1b\nswAAFt1JREFU0qdIm1MyjMd2EvEGcaI0NmNG5Kn19+w51Pf/RRYbFgy7CVWOStx05U3ovcv8zKtS\nP31jVcTnefC6H0XcHv/9BRSoyDRZYFLMZ+Q/3ent7W8fIoo/TQhUFJTAZsmRHYUoKtH0j7HurygK\nvrdsKfzhMIJf+vLz8Q2vR3yeJ274p4jbE7V/f/t9mSYEZhaXo5y3NiYVS2EigqIouLBgGrJNOTAp\nZvQWaXrQmyNDtSDLfCobEelNSWYWLinkRD1Ep7OYTMhUU/dUWxMC43LzMTm/WHYUw1FEEgeg2O3O\nZL2UrthsVsO2HTB2+1O17Y5AFz7v+RQt3pNQoMY0zis3JxNuTyCm19eEhgw1A2NyJ2FywQyY1dQr\nzFL1dx8PNhsniBgsmZ+Vd1rq0O73xvx4VVFw3fDzY16Q2ujHCtue/urcDnzY3gzttC8/c3MscHv8\nElMNTAiBgkwLrhl+HkxxHuttpN99JNH0kal31kNECZefWYTZtqvhDvbgiGMfWjx1CIoQ1ATffx4W\nIVjNBRiVewEuyL+IV8yIdC4sBGYVlcdcnBEZwdjcfFjNmXjP3gBPKJgSk1tlmcxYWDY67sUZRYdn\nP0TUr9yMAswouQrh4hCOOw+jxVuHdn8LACVuxVpYCyFTtaAsaxRG501AedbolOi8iIxOCIHROXmY\nmF8kOwqR7hVbsnD9iPOxra0erT6P7DgDylRVXD1sDHLN/OJFFhZoRHROJsWMCfkXYUL+RQhqATS4\nj6Ld34SeQAecwR4ICJgU8zkLKyEEQiKIDDUTBRnFKMgowbDsMSjLHpXwq3NEFF9ZJjPmlo6UHYMo\nZWSoKpaUj8G+Ljvqwm7ZcSLKUFQsLh+D/AyL7CiGxgKNiAYlQ83EedbJOM86GQAQ0oLoCrShK9AO\nf8iDgAggpAWRl5sJp+aDqpiQoWQgU81CtjkXpZbhyMsoZEFGlMKEELiidAQyUngCBCIZFEXB9OIy\nXJStYEN1NbzhkG7uGslQVCwqH42izCzZUQyPBRoRDYlZzYAtayRsWWd+k270QcBE6UoTApPzizGc\n024TxWxEXh5uGDkeH7Y3oc7jlDrWSwiBPHMGFpWPhpVXznSBX30RERFR1IozszCjqEx2DKKUl6Gq\nmF82Cgtto5BtMkNL3sTqfTQhYMvKwbUjzmdxpiO8gkZERERRUaHgStso3dySRZQORuVaMTwnD3s7\n21Dt6oYQWtKOscn5xZhRVMZjWmdYoBEREdE5aZrAbNtwTqlPlAAmRcGsknJ8paAYe7rsqPP0AAIJ\nKZw0IVCUmYXLS4ahxJId9+enoWOBRkRERAPShMC4vHyMzyuQHYUoreWYMzDPNgJTg6U42N2Okx4n\nQkKDGodCLawJ5JrNmJRfhK/kl/CqmY6xQCMiIqIBWc0ZmFM6XHYMIsPIz8jEFbYRuEzTcMTRiZNe\nFzr8XgAYVLEmhEBYCJRYsjHJWojxeYVxKfYosVigERERUb+Uf4w7M3FpDKKkM6sqKgpLUVFYioAW\nxlFXN9p8XjiCAbhCAfg1DZoQUBRAASCgIENRkW02ocBsgc2SjfF5BcjLyJTdFBoEFmhEREQUUVgI\nXFZchmIL10Uiki1TNWFyfgkm5/f+LISANxxGSGgIahpCmoYcsxm55gxeJUtxLNCIiIjoLJoQGJtj\nxaT8YtlRiCgCRVGQY+apfDri/QpERER0ljxzJubaRsiOQURkODGV3S6XCw888ADcbjeCwSAeeugh\nXHLJJfHORkRERBIoUHBV2UiOOyMikiCmAu2FF17AnDlzsGLFChw/fhz3338/Xn311XhnIyIioiTT\nNIHLS4ehKJPjzoiIZIipQLv77ruRmdk7G0woFILFYolrKCIiIko+TQiMtxZggrVQdhQiIsM6Z4G2\nfv16rFu37oxtq1evRkVFBex2O1auXIlHHnkkYQGJiIgo8YQQKMy0YHYJ1zsjIpJJEUKIWB5YVVWF\nBx54AA8++CDmzp0b71xERESUBK8fr0Wb14MMVcXXx0/keklERJLFdItjbW0t7r33XvzqV7/CpEmT\non6c3e6M5eVSns1mNWzbAWO3n203ZtsBY7ffZrPKjpByZH5WnC4fXD4/FpaPhrfbDy/8SX19ox8r\nbLsxGbn9Rm47EF0fGVOB9vTTTyMQCOCpp56CEAL5+fl45plnYnkqIiIikiikaZhWZMOI7FzZUYiI\nCDEWaGvWrIl3DiIiIpLg4oJSjM7lVU8iIr3gAidEREQGxuKMiEhfWKARERERERHpBAs0IiIiIiIi\nnWCBRkRERGd5/fVXsX//Ptkx4ipSmzZt2ogPPngPv/nN09i5c7ukZPHzm988jba2VgBAKBTCz3/+\nn3C7XZJTDc5rr63Hxo1v4MUXX0Bra4vsODFJx+OHkocFGhEREfXx+/3461//hL///TXEuFSq7vTX\npsbGBqxb9ztceeVVmDVrNl544VmJKYeutrYGO3fugKb1trGtrRVvvPE6brzxGtxww1dx3XVLsG3b\nFskpB3bkyGFUVVVh2bLr8LWv3YI1a34tO9KgpOPxQ8kX0yyORERElJ4sFgu+9rVbUFV1RHaUuOmv\nTSNHjsKaNc8BAGpqqjF37pUy4sVFKBRCS0szysrK+rbZ7XasX/932Gxl0DQNb7zxOhYsWCwx5bnt\n3fspysvLAQA5OTmoqamSnGhw0vH4oeTjFTQiIiIyrNzcPOzY8T6amhpx++0rZMeJ2c6dH+Dyy684\n46rN1KmXwGbrLdg2bHgVV1+9TFa8qGVn5yAUCvX93N3dDYfDITERUfLxChoREREN2rx5s6AoyoD7\nCCGgKAo++GBXklINntlsxty58+H3B/D44w/hJz95GoA+2hcIBNDY2IDzzjt/wP2OHz+GkSNHw2Qy\nRfz3Y8dqEQ5ryMrKOmN7otsYbf7TXXXVQqxd+0xf7lAoBLP57Hbp4fczFBdeeGFK56fEYoFGRERE\ng7Z9+6eyI8TVxImT8MMf/gDd3d0oLCzURfs6OzuwbdsWnHfevw6435EjnwMAamqq0NnZgffe24Jl\ny65DQUEhAODPf/4jrrvuxrMel+g2Rpv/dEVFxfjGN27Dzp3bUVJSgnHjzkNOTu5Z++nh9zMUR44c\ngd3ulB2DdIq3OBIREZEhbdjwNzz66IMAgI6OdpSW2pCfny851ZnOdZUFAJYtu67vv+LiElx11eK+\n4gwAdu36GIWFhQM8Q+JEk/90jY0NWL/+FVxxxTwIIbBo0ZIEJSPSLxZoREREdIa//W09Dh/+DG++\nuQF79+7ud7+33vo7/vd/X8RPf/rjvm0NDfVYseKWZMQclEhtmjdvPq64Yh7efXcT3nnnLfziF7+G\nqn5xapRK7QN6lwyorz+Jv/zlj+ju7u7bnpGR0W/hqbc2lpSUYsSIUXjnnbewd+9u3HLL8n731Vv2\nU9Lx+KHk4i2OREREdIabbvo6brrp6wPuc+zYUWRmZmLevPn4znfuxoMPPgoA+OijnSgvHzao13vj\njdcBCOzcuQPf/va/4oILJsYavV+R2lRUVIxly64DACxadPUZ/xbP9p3y+uuvYty48zB16rSoHzOY\nqdqvvnpZxIlA/vSn1yLuH20bX3rp9xg9egyqqo5g6dJrMWbM2ITkB4CsrCzceedd59xvsL+fWN77\nWEVz/NTU1ESdPxnHB+kLCzQiIiIaNI/HjauuWoR1636HK66Y17e9snIPpk2bGfXzfPDBB5gy5Ss4\n//wJKCgoxI9/vArr1v0x4r5vvrkBu3Z93O9tc0IIZGRk4KGHHoPZPLRTnHi1D+hdG+uNN17Dxo1v\n4rvfvbfffX71q58jHA6flsGDpqYGtLQ0n7HvNddcj0sumT6oDJFE08aDB/ejvv4k7rjjLkyZUoFf\n/vInfROpDCX/kiXzE579VK5zvfenJPPz5XK5osr/8ccfRn18UPpggUZERESDVlFxMQBg48Y38PDD\nj/dt379/H+688+6on+fEiRM4cqQG9923EqNGjUFra3O/+1577Q249tobYg89CPFqHxDd2lgWi6Xv\nKsopLS3N2LjxDdx9978M6vWiNXAbvw0A2Lt3NyZPngIAsNnKcPjw5xGfK9n5o/39DGZdsmR+vqZN\nmwa73XnO/PX1J/HRRzuiOj4ofbBAIyIiMrhTU5affjtapJ+BM6f+rqs7ge7urr6rObW1NQiFwpg0\naTIOHKjExRdfcs7XXr58OU6ebAMAHDhQicsuuzyeTQPQf/tOtef0bfFuXzIMpn2ntp27jRfiwIFK\ndHZ2nHHLnclkgtPphNVqjWv+051+BSsVfj/95R/ovT98+HBU+W+++Rvwer0AEnd8kP6wQCMiIjK4\n7ds/xaZNG5GdnY3Kyn2YMWMW5syZi5dfXodRo8agurp37NHo0WPOeFwwGERWVlbf+ltbt27GpEkX\nAui9NS6aE2STyYS8vDw4nU5s27YFq1Y9lZD2NTU14q23/o7x4ydACGDhwsUAMGAb49G+ZIi1fcDA\nbTxwoBJCCKjqF+uQhcMhmEzxnWNu+/ZP8eabGyCEwIcf9o6zmjDhgnPm18vvp7/88Th+knF8kP6w\nQCMiIjK4xsYGrFv3O7z88npkZGTi2Wf/H6xWK06erMPy5d/ClClfiTj2aMKECzB//kL8/vfPIS8v\nDxdffAmOHDmMdet+h+uv7113S9M0/O1vf4GmnT1ZxIgRI3HjjddA0zT84Q/P47HHnkBRUVHc2yeE\nwOrVT+CnP30aPp8PTz31IyxcuBgHDlQO2MZ4tO/08UWJEmv7omnjm29ugM/n7dtf00TEdcmG4uOP\nP8SFF07B+PETUFBQgCeffBzr1v0xLr+fZIiU/4EHHorL8QMg4ccH6Q8LNCIiIoMbOXIU1qx5DgBQ\nU1ONuXOvjHrs0fe//4Mzfp49e84ZP6uqiq99beBpw1977a+47bY7UFxcgk2b3sbVVy+NtSkR7du3\nB1ZrPnJycpGTk4uf/OSXfdvP1cZ4tC9WZnMGLBbLOfcbSvuAgds4c+al2LjxTQC946EuvHBy3PP3\nN84qHr+fZPhy/paWpri896ck+vgg/WGBRkRERMjNzcOOHe+jqakR9977ANas+b8JH3sEAG+//TZ+\n+9v/xvPP/w8AYNKkyXE/Aa2qOoJgMIAPP9yB9nY7Ro8eg2nTZiRlfNUpp9bGEkJA0zRMn37umSBL\nS0tx++0rzrlfIts3ZUoFtm9/H5s3v42ammr8x3/cH/Vjo83f3zireP1+YnnvB+P0/AcP7sfs2XPQ\n2dmBsrLyIWfftm1Lwo8P0h8WaERERASz2Yy5c+fD7w9g1aqHUVZWnvCxRwCwdOlSzJhxRdyf93Sa\nFobP58OcOXOhaRruuus2/OEPf4KmJX581SnRrI0Vq0S37zvf+T8AgCVLElMYfHmc1Q9/+J8AELf8\niXzvgTPzb926GatWPYXnn/+fuGRfsGAxFixYHM+4lAIS81eIiIiIUtLEiZOwc+d2FBeXJHzsUbKU\nlZX3Xc1QVRVutxtOpxM2my0t2pgO7Tt9nFVhYSEApGz+oqKilMpO+sMCjYiIyOA2bPgbHn30QQBA\nR0c7SkttuOyyy1FdXQVg8GOP9GbGjFno7OwAAITDYeTlWWG1WjFz5qWoqakGkNptTIf2nRpnVVJS\nik2b3gaAlM4/a9ZlaXP8UPIp4vRFGhLMbncm66V0xWazGrbtgLHbz7Ybs+2Asdtvs8V//E66k/1Z\n6erqxMcff4jMzEzs3r0L3/jGrTj//AlYu/YZnH/+eNTUVOP66288a5rweEjWsfLWW3+Hx+OGx+PB\n9OmzUFFxEQAkpY39iWfb9di+gZze9m3btmD16ieRmZkJoHec1S9/+WsA+s1/ujPzC0yaNAW//OWv\nB8xu9D7CqG0HousjWaAlAT+Ixm0/227MtgPGbj8LtMEz6mcF4LHCthuTkdtv5LYD0fWRvMWRiIiI\niIhIJ1igERERERER6QQLNCIiIiIiIp1ggUZERERERKQTLNCIiIiIiIh0ggUaERERERGRTrBAIyIi\nIiIi0gkWaERERERERDrBAo2IiIiIiEgnhlSgHT16FDNnzkQgEIhXHiIiIiIiIsOKuUBzuVz42c9+\nBovFEs88REREREREhhVzgfb444/je9/7HrKysuKZh4iIiIiIyLDM59ph/fr1WLdu3RnbRowYgWuv\nvRaTJk2CECJh4YiIiIiIiIxEETFUWF/96ldRXl4OIQT279+PqVOn4sUXX0xEPiIiIiIiIsOIqUA7\n3cKFC/HOO+8gIyMjXpmIiIiIiIgMacjT7CuKwtsciYiIiIiI4mDIV9CIiIiIiIgoPrhQNRERERER\nkU6wQCMiIiIiItIJFmhEREREREQ6kZQCzev14t///d9xxx134Nvf/jba2tqS8bK64XK58G//9m+4\n8847ceutt6KyslJ2pKTbvHkz7r//ftkxkkIIgVWrVuHWW2/FihUrUF9fLzuSFPv378edd94pO0ZS\nhUIhrFy5EsuXL8c3v/lNbN26VXakpNI0DT/4wQ9w2223Yfny5aitrZUdKSUYuY9k/9iLfaSxGLF/\nBIzdRw62f0xKgfbnP/8ZFRUVeOmll3D99dfj2WefTcbL6sYLL7yAOXPm4MUXX8Tq1avxxBNPyI6U\nVE899RT+67/+S3aMpNmyZQsCgQBeeeUV3H///Vi9erXsSEn33HPP4dFHH0UwGJQdJak2bNiAoqIi\nvPzyy3j22Wfx5JNPyo6UVFu3boWiKPjjH/+Ie+65B08//bTsSCnByH2k0ftHgH2k0fpIo/aPgLH7\nyMH2j+ZkhPrWt77VNxV/U1MTCgoKkvGyunH33XcjMzMTQO+3BxaLRXKi5Jo+fTqWLFmCP/3pT7Kj\nJMWePXswb948AMDUqVNx6NAhyYmSb+zYsXjmmWewcuVK2VGSatmyZVi6dCmA3m/LzOak/InVjcWL\nF2PhwoUAgMbGRsP9rY+VkftIo/ePAPtIo/WRRu0fAWP3kYPtH+P+zqxfvx7r1q07Y9vq1atRUVGB\nu+66C9XV1Xj++efj/bK6MVD77XY7Vq5ciUceeURSusTqr+3Lli3Drl27JKVKPpfLBavV2vez2WyG\npmlQVeMM+VyyZAkaGxtlx0i67OxsAL2fgXvuuQf33Xef5ETJp6oqHn74YWzevBm//vWvZcfRHSP3\nkUbuHwH2kacYvY80av8IsI8cVP8okuzo0aNi8eLFyX5Z6Y4cOSKuu+46sX37dtlRpPjkk0/E9773\nPdkxkmL16tVi48aNfT/Pnz9fXhiJGhoaxC233CI7RtI1NTWJm2++Wbz66quyo0jV3t4uFixYILxe\nr+woKcWIfaTR+0ch2EcajVH7RyHYRwoRXf+YlK8r1q5di9deew0AkJOTA5PJlIyX1Y3a2lrce++9\n+MUvfoG5c+fKjkMJNn36dLz//vsAgMrKSkycOFFyInnEP27bMor29nb88z//M77//e/jpptukh0n\n6V577TWsXbsWAGCxWKCqqmG+FR8KI/eR7B+Nh31kL6P1j4Cx+8jB9o9Jufnz61//Oh588EH89a9/\nhRDCcANCn376aQQCATz11FMQQiA/Px/PPPOM7FiUIEuWLMHOnTtx6623AoDhPu+nUxRFdoSkWrt2\nLRwOB9asWYNnnnkGiqLgueee6xtjk+6WLl2Khx56CHfccQdCoRAeeeQRw7R9KIzcR7J/NB72kb2M\n1j8Cxu4jB9s/KsKIJTwREREREZEO8d4TIiIiIiIinWCBRkREREREpBMs0IiIiIiIiHSCBRoRERER\nEZFOsEAjIiIiIiLSCRZoREREREREOsECjYiIiIiISCdYoBEREREREenE/wcMWVmJzzPHwwAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a95de4390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_intro_plots(12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# The slide below can be produced with the following:\n",
    "(approx_minus2, approx_minus1, \n",
    " approx_zero, approx_all) = weno_computations.interp_simple_stencils()\n",
    "\n",
    "approx_minus2 = approx_minus2.replace('=', '&=')\n",
    "approx_minus1 = approx_minus1.replace('=', '&=')\n",
    "approx_zero = approx_zero.replace('=', '&=')\n",
    "approx_all = approx_all.replace('=', '&=')\n",
    "\n",
    "all_math = r\"\"\"\\begin{align*}\n",
    "%s \\\\ %s \\\\ %s \\\\ %s \\end{align*}\n",
    "\"\"\" % (approx_minus2, approx_minus1, approx_zero, approx_all)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$u^{{(1)}}_{{j + \\frac{1}{2}}} = \\frac{1}{3}\\overline{u}_{j-2} - \\frac{7}{6}\\overline{u}_{j-1} + \\frac{11}{6}\\overline{u}_{j}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$u^{{(2)}}_{{j + \\frac{1}{2}}} = -\\frac{1}{6}\\overline{u}_{j-1} + \\frac{5}{6}\\overline{u}_{j} + \\frac{1}{3}\\overline{u}_{j+1}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$u^{{(3)}}_{{j + \\frac{1}{2}}} = \\frac{1}{3}\\overline{u}_{j} + \\frac{5}{6}\\overline{u}_{j+1} - \\frac{1}{6}\\overline{u}_{j+2}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$u^{{(\\ast)}}_{{j + \\frac{1}{2}}} = \\frac{1}{30}\\overline{u}_{j-2} - \\frac{13}{60}\\overline{u}_{j-1} + \\frac{47}{60}\\overline{u}_{j} + \\frac{9}{20}\\overline{u}_{j+1} -\\frac{1}{20}\\overline{u}_{j+2}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\frac{1}{3}\\overline{u}_{j-2} - \\frac{7}{6}\\overline{u}_{j-1} + \\frac{11}{6}\\overline{u}_{j} = u\\left(x_{j + \\frac{1}{2}}\\right) - \\frac{\\Delta x^3 u_0'''}{4} + \\mathcal{O}\\left(\\Delta x^4\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$-\\frac{1}{6}\\overline{u}_{j-1} + \\frac{5}{6}\\overline{u}_{j} + \\frac{1}{3}\\overline{u}_{j+1} = u\\left(x_{j + \\frac{1}{2}}\\right) + \\frac{\\Delta x^3 u_0'''}{12} + \\mathcal{O}\\left(\\Delta x^4\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$\\frac{1}{3}\\overline{u}_{j} + \\frac{5}{6}\\overline{u}_{j+1} - \\frac{1}{6}\\overline{u}_{j+2} = u\\left(x_{j + \\frac{1}{2}}\\right) - \\frac{\\Delta x^3 u_0'''}{12} + \\mathcal{O}\\left(\\Delta x^4\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$u^{{(\\ast)}}_{{j + \\frac{1}{2}}} = u\\left(x_{j + \\frac{1}{2}}\\right) - \\frac{\\Delta x^5 u_0'''}{60} + \\mathcal{O}\\left(\\Delta x^6\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\left(\\Delta x\\right) \\overline{u} = \\int_a^b u(x) \\, dx = u_0(b - a) + u_0' \\left(\\frac{b^2 - a^2}{2}\\right) + u_0'' \\left(\\frac{b^3 - a^3}{6}\\right) + \\cdots$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Putting the **W** in **WENO**:\n",
    "$$u^{{(\\ast)}}_{{j + \\frac{1}{2}}} = \\frac{1}{10} u^{{(1)}}_{{j + \\frac{1}{2}}} + \\frac{6}{10} u^{{(2)}}_{{j + \\frac{1}{2}}} + \\frac{3}{10} u^{{(3)}}_{{j + \\frac{1}{2}}}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "What about the other letters?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "What about shocks?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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8Pkbs/xlZV1Qt5wEAAA4Bvi8FAAAgIbEGAACQkFgDAABISKwBAAAkJNYAAAAS\nEmsAAAAJiTUAAICE/h+gQ/5HQF5a+AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a95ce3810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.discontinuity_to_volume_single_cell(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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rAAAACYk1AACAhMQaAABAQmINAAAgIbEGAACQkFgDAABISKwBAAAkJNYAAAASEmsAAAAJ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\nAAAgIbEGAACQkFgDAABISKwBAAAk9P8BaCMJegHy5JAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a9570af90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.discontinuity_to_volume_single_cell(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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WAnAvQhwAAHCcd4sPa09lqd1lAIAtCHEAAMBxDEP6sLRQ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\nAQAAAIBD/h+ntThui+a7awAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a95d011d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_shock_plot_single_cell()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\frac{1}{10} u^{{(1)}}_{{j + \\frac{1}{2}}} + \\frac{6}{10} u^{{(2)}}_{{j + \\frac{1}{2}}} + \\frac{3}{10} u^{{(3)}}_{{j + \\frac{1}{2}}} \\longrightarrow \\frac{2}{3} u^{{(2)}}_{{j + \\frac{1}{2}}} + \\frac{1}{3} u^{{(3)}}_{{j + \\frac{1}{2}}}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SawAAAAmJNQAAgITEGgAAQEJiDQAAICGxBgAAkJBYAwAASEisAQAAJCTWAAAA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\nrAEAACQk1gAAABL6P+zDLawNjWcnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a9570a910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.discontinuity_to_volume()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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EAfHCGFnVPnnzPpO4IBsAgNg6vsfcIXrMoWMR4oB4Yoysyip58z8nyAEAEGNN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\nUl5v8z/ZTzUH9uvXv9kOx1hqbV4Oh8M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0yOsnzHIkDvCZgAnqYKpJrzY+r7eaViuabne7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\npqZnXSaT0YMPPqglS5boiSee0NNPP63W1tZBKxgAAAAA/Kx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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a95edbe90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weno_computations.make_shock_plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Smoothness indicator when approximating a point in the interval $I = \\left(x_j - \\frac{\\Delta x}{2}, x_j + \\frac{\\Delta x}{2}\\right]$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$\\beta = \\sum_k \\Delta x^{2k - 1} \\int_I \\left(\\frac{d^k}{dx^k} p\\right)^2 dx$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Large $\\beta$ indicates that the approximation $p(x)$ is not smooth nearby our point."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Recall the **W** in **WENO**:\n",
    "$$u^{{(\\ast)}}_{{j + \\frac{1}{2}}} = \\frac{1}{10} u^{{(1)}}_{{j + \\frac{1}{2}}} + \\frac{6}{10} u^{{(2)}}_{{j + \\frac{1}{2}}} + \\frac{3}{10} u^{{(3)}}_{{j + \\frac{1}{2}}}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Rather than using these directly, incorporate a penalty for each polynomial approximation's (lack of) smoothness: $\\beta^{(1)}$, $\\beta^{(2)}$, $\\beta^{(3)}$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\widetilde{w}^{(1)} = \\frac{0.1}{\\left(\\varepsilon + \\beta^{(1)}\\right)^2}, \\;\n",
    "\\widetilde{w}^{(2)} = \\frac{0.6}{\\left(\\varepsilon + \\beta^{(2)}\\right)^2}, \\;\n",
    "\\widetilde{w}^{(3)} = \\frac{0.3}{\\left(\\varepsilon + \\beta^{(3)}\\right)^2}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$w^{(j)} = \\frac{\\widetilde{w}^{(j)}}{\\widetilde{w}^{(1)} + \\widetilde{w}^{(2)} + \\widetilde{w}^{(3)}}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$w^{(1)} u^{{(1)}}_{{j + \\frac{1}{2}}} + w^{(2)} u^{{(2)}}_{{j + \\frac{1}{2}}} + w^{(3)} u^{{(3)}}_{{j + \\frac{1}{2}}}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1 class=\"bigtitle\">Back to Conservation Law</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\dot{\\overline{u}} = -\\frac{1}{\\Delta x}\\left(\\widehat{f}\\left(u_{j + \\frac{1}{2}}^-, u_{j + \\frac{1}{2}}^+\\right) - \\widehat{f}\\left(u_{j - \\frac{1}{2}}^-, u_{j - \\frac{1}{2}}^+\\right)\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$u_{j + \\frac{1}{2}}^- \\longrightarrow \\text{Reconstruct from } \\overline{u}_{j - 2}, \\overline{u}_{j - 1}, \\overline{u}_{j}, \\overline{u}_{j + 1}, \\overline{u}_{j + 2}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$u_{j + \\frac{1}{2}}^+ \\longrightarrow \\text{Reconstruct from } \\overline{u}_{j - 1}, \\overline{u}_{j}, \\overline{u}_{j + 1}, \\overline{u}_{j + 2}, \\overline{u}_{j + 3}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\dot{\\overline{u}} = L\\left(\\overline{u}\\right)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "TV-diminishing / strong stability preserving RK scheme\n",
    "\n",
    "$$\\begin{array}{c | c c c}\n",
    "  0 &     &     &   \\\\\n",
    "  1 &   1 &     &   \\\\\n",
    "1/2 & 1/4 & 1/4 &   \\\\\n",
    "\\hline\n",
    "    & 1/6 & 1/6 & 2/3\n",
    "\\end{array}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "![Stability Preserving](tvd_scheme.png \"TVD RK Scheme\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1 class=\"bigtitle\">Example</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "![WENO Example Part 1](traffic_flow_example1.png \"WENO Traffic Flow\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "![WENO Example Part 2](traffic_flow_example2.png \"WENO Traffic Flow\")"
   ]
  }
 ],
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