{
 "metadata": {
  "name": "",
  "signature": "sha256:cf83dc9e6288480ac94c44a5983b4ee421f0ade792a9fac64bc00719263386c0"
 },
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Rich Output"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In Python, objects can declare their textual representation using the `__repr__` method.  IPython expands on this idea and allows objects to declare other, rich representations including:\n",
      "\n",
      "* HTML\n",
      "* JSON\n",
      "* PNG\n",
      "* JPEG\n",
      "* SVG\n",
      "* LaTeX\n",
      "\n",
      "A single object can declare some or all of these representations; all are handled by IPython's *display system*. This Notebook shows how you can use this display system to incorporate a broad range of content into your Notebooks."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Basic display imports"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The `display` function is a general purpose tool for displaying different representations of objects. Think of it as `print` for these rich representations."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import display"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A few points:\n",
      "\n",
      "* Calling `display` on an object will send **all** possible representations to the Notebook.\n",
      "* These representations are stored in the Notebook document.\n",
      "* In general the Notebook will use the richest available representation.\n",
      "\n",
      "If you want to display a particular representation, there are specific functions for that:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import (\n",
      "    display_pretty, display_html, display_jpeg,\n",
      "    display_png, display_json, display_latex, display_svg\n",
      ")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Images"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "To work with images (JPEG, PNG) use the `Image` class."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Image"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "i = Image(filename='../images/ipython_logo.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Returning an `Image` object from an expression will automatically display it:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "i"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "png": 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       "prompt_number": 5,
       "text": [
        "<IPython.core.display.Image object>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Or you can pass an object with a rich representation to `display`:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "display(i)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<IPython.core.display.Image object>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "An image can also be displayed from raw data or a URL."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Image(url='http://python.org/images/python-logo.gif')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<img src=\"http://python.org/images/python-logo.gif\"/>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "<IPython.core.display.Image object>"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "SVG images are also supported out of the box."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import SVG\n",
      "SVG(filename='../images/python_logo.svg')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "svg": [
        "<svg height=\"115.02pt\" id=\"svg2\" inkscape:version=\"0.43\" sodipodi:docbase=\"/home/sdeibel\" sodipodi:docname=\"logo-python-generic.svg\" sodipodi:version=\"0.32\" version=\"1.0\" width=\"388.84pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:cc=\"http://web.resource.org/cc/\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:inkscape=\"http://www.inkscape.org/namespaces/inkscape\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\" xmlns:sodipodi=\"http://inkscape.sourceforge.net/DTD/sodipodi-0.dtd\" xmlns:svg=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
        "  <metadata id=\"metadata2193\">\n",
        "    <rdf:RDF>\n",
        "      <cc:Work rdf:about=\"\">\n",
        "        <dc:format>image/svg+xml</dc:format>\n",
        "        <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
        "      </cc:Work>\n",
        "    </rdf:RDF>\n",
        "  </metadata>\n",
        "  <sodipodi:namedview bordercolor=\"#666666\" borderopacity=\"1.0\" id=\"base\" inkscape:current-layer=\"svg2\" inkscape:cx=\"243.02499\" inkscape:cy=\"71.887497\" inkscape:pageopacity=\"0.0\" inkscape:pageshadow=\"2\" inkscape:window-height=\"543\" inkscape:window-width=\"791\" inkscape:window-x=\"0\" inkscape:window-y=\"0\" inkscape:zoom=\"1.4340089\" pagecolor=\"#ffffff\"/>\n",
        "  <defs id=\"defs4\">\n",
        "    <linearGradient id=\"linearGradient2795\">\n",
        "      <stop id=\"stop2797\" offset=\"0\" style=\"stop-color:#b8b8b8;stop-opacity:0.49803922\"/>\n",
        "      <stop id=\"stop2799\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient2787\">\n",
        "      <stop id=\"stop2789\" offset=\"0\" style=\"stop-color:#7f7f7f;stop-opacity:0.5\"/>\n",
        "      <stop id=\"stop2791\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient3676\">\n",
        "      <stop id=\"stop3678\" offset=\"0\" style=\"stop-color:#b2b2b2;stop-opacity:0.5\"/>\n",
        "      <stop id=\"stop3680\" offset=\"1\" style=\"stop-color:#b3b3b3;stop-opacity:0\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient3236\">\n",
        "      <stop id=\"stop3244\" offset=\"0\" style=\"stop-color:#f4f4f4;stop-opacity:1\"/>\n",
        "      <stop id=\"stop3240\" offset=\"1\" style=\"stop-color:#ffffff;stop-opacity:1\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient4671\">\n",
        "      <stop id=\"stop4673\" offset=\"0\" style=\"stop-color:#ffd43b;stop-opacity:1\"/>\n",
        "      <stop id=\"stop4675\" offset=\"1\" style=\"stop-color:#ffe873;stop-opacity:1\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient4689\">\n",
        "      <stop id=\"stop4691\" offset=\"0\" style=\"stop-color:#5a9fd4;stop-opacity:1\"/>\n",
        "      <stop id=\"stop4693\" offset=\"1\" style=\"stop-color:#306998;stop-opacity:1\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient gradientTransform=\"translate(100.2702,99.61116)\" gradientUnits=\"userSpaceOnUse\" id=\"linearGradient2987\" x1=\"224.23996\" x2=\"-65.308502\" xlink:href=\"#linearGradient4671\" y1=\"144.75717\" y2=\"144.75717\"/>\n",
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       "text": [
        "<IPython.core.display.SVG object>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Embedded vs non-embedded Images"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "By default, image data is embedded in the notebook document so that the images can be viewed offline. However it is also possible to tell the `Image` class to only store a *link* to the image. Let's see how this works using a webcam at Berkeley."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Image\n",
      "img_url = 'http://www.lawrencehallofscience.org/static/scienceview/scienceview.berkeley.edu/html/view/view_assets/images/newview.jpg'\n",
      "\n",
      "# by default Image data are embedded\n",
      "Embed      = Image(img_url)\n",
      "\n",
      "# if kwarg `url` is given, the embedding is assumed to be false\n",
      "SoftLinked = Image(url=img_url)\n",
      "\n",
      "# In each case, embed can be specified explicitly with the `embed` kwarg\n",
      "# ForceEmbed = Image(url=img_url, embed=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is the embedded version. Note that this image was pulled from the webcam when this code cell was originally run and stored in the Notebook. Unless we rerun this cell, this is not todays image."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Embed"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
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oCITmOR80BIMmZwnIJoKQST/pE1KAgZnAMUepRB9u9ReQBYEAfpHt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\nTLiN8bFraIISojbIUkmcGsTa0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ndIjsDJmBn6f19y1tb/AE5lNwBqDHkuhp9aEFseqFhJ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\n",
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "<IPython.core.display.Image object>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is today's image from same webcam at Berkeley, (refreshed every minutes, if you reload the notebook), visible only with an active internet connection, that should be different from the previous one. Notebooks saved with this kind of image will be smaller and always reflect the current version of the source, but the image won't display offline."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "SoftLinked"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<img src=\"http://www.lawrencehallofscience.org/static/scienceview/scienceview.berkeley.edu/html/view/view_assets/images/newview.jpg\"/>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "<IPython.core.display.Image object>"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Of course, if you re-run this Notebook, the two images will be the same again."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "HTML"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Python objects can declare HTML representations that will be displayed in the Notebook. If you have some HTML you want to display, simply use the `HTML` class."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "s = \"\"\"<table>\n",
      "<tr>\n",
      "<th>Header 1</th>\n",
      "<th>Header 2</th>\n",
      "</tr>\n",
      "<tr>\n",
      "<td>row 1, cell 1</td>\n",
      "<td>row 1, cell 2</td>\n",
      "</tr>\n",
      "<tr>\n",
      "<td>row 2, cell 1</td>\n",
      "<td>row 2, cell 2</td>\n",
      "</tr>\n",
      "</table>\"\"\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h = HTML(s)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "display(h)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<table>\n",
        "<tr>\n",
        "<th>Header 1</th>\n",
        "<th>Header 2</th>\n",
        "</tr>\n",
        "<tr>\n",
        "<td>row 1, cell 1</td>\n",
        "<td>row 1, cell 2</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td>row 2, cell 1</td>\n",
        "<td>row 2, cell 2</td>\n",
        "</tr>\n",
        "</table>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML object>"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can also use the `%%html` cell magic to accomplish the same thing."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%html\n",
      "<table>\n",
      "<tr>\n",
      "<th>Header 1</th>\n",
      "<th>Header 2</th>\n",
      "</tr>\n",
      "<tr>\n",
      "<td>row 1, cell 1</td>\n",
      "<td>row 1, cell 2</td>\n",
      "</tr>\n",
      "<tr>\n",
      "<td>row 2, cell 1</td>\n",
      "<td>row 2, cell 2</td>\n",
      "</tr>\n",
      "</table>"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<table>\n",
        "<tr>\n",
        "<th>Header 1</th>\n",
        "<th>Header 2</th>\n",
        "</tr>\n",
        "<tr>\n",
        "<td>row 1, cell 1</td>\n",
        "<td>row 1, cell 2</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td>row 2, cell 1</td>\n",
        "<td>row 2, cell 2</td>\n",
        "</tr>\n",
        "</table>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML object>"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "JavaScript"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The Notebook also enables objects to declare a JavaScript representation. At first, this may seem odd as  output is inherently visual and JavaScript is a programming language. However, this opens the door for rich output that leverages the full power of JavaScript and associated libraries such as [d3.js](http://d3js.org) for output."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Javascript"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Pass a string of JavaScript source code to the `JavaScript` object and then display it."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "js = Javascript('alert(\"hi\")');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "display(js)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "javascript": [
        "alert(\"hi\")"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript object>"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The same thing can be accomplished using the `%%javascript` cell magic:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%javascript\n",
      "\n",
      "alert(\"hi\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "javascript": [
        "\n",
        "alert(\"hi\");"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript object>"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is a more complicated example that loads `d3.js` from a CDN, uses the `%%html` magic to load CSS styles onto the page and then runs ones of the `d3.js` examples."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Javascript(\n",
      "    \"\"\"$.getScript('//cdnjs.cloudflare.com/ajax/libs/d3/3.2.2/d3.v3.min.js')\"\"\"\n",
      ")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "javascript": [
        "$.getScript('//cdnjs.cloudflare.com/ajax/libs/d3/3.2.2/d3.v3.min.js')"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 21,
       "text": [
        "<IPython.core.display.Javascript object>"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%html\n",
      "<style type=\"text/css\">\n",
      "\n",
      "circle {\n",
      "  fill: rgb(31, 119, 180);\n",
      "  fill-opacity: .25;\n",
      "  stroke: rgb(31, 119, 180);\n",
      "  stroke-width: 1px;\n",
      "}\n",
      "\n",
      ".leaf circle {\n",
      "  fill: #ff7f0e;\n",
      "  fill-opacity: 1;\n",
      "}\n",
      "\n",
      "text {\n",
      "  font: 10px sans-serif;\n",
      "}\n",
      "\n",
      "</style>"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<style type=\"text/css\">\n",
        "\n",
        "circle {\n",
        "  fill: rgb(31, 119, 180);\n",
        "  fill-opacity: .25;\n",
        "  stroke: rgb(31, 119, 180);\n",
        "  stroke-width: 1px;\n",
        "}\n",
        "\n",
        ".leaf circle {\n",
        "  fill: #ff7f0e;\n",
        "  fill-opacity: 1;\n",
        "}\n",
        "\n",
        "text {\n",
        "  font: 10px sans-serif;\n",
        "}\n",
        "\n",
        "</style>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML object>"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%javascript\n",
      "\n",
      "// element is the jQuery element we will append to\n",
      "var e = element.get(0);\n",
      "    \n",
      "var diameter = 600,\n",
      "    format = d3.format(\",d\");\n",
      "\n",
      "var pack = d3.layout.pack()\n",
      "    .size([diameter - 4, diameter - 4])\n",
      "    .value(function(d) { return d.size; });\n",
      "\n",
      "var svg = d3.select(e).append(\"svg\")\n",
      "    .attr(\"width\", diameter)\n",
      "    .attr(\"height\", diameter)\n",
      "  .append(\"g\")\n",
      "    .attr(\"transform\", \"translate(2,2)\");\n",
      "\n",
      "d3.json(\"data/flare.json\", function(error, root) {\n",
      "  var node = svg.datum(root).selectAll(\".node\")\n",
      "      .data(pack.nodes)\n",
      "    .enter().append(\"g\")\n",
      "      .attr(\"class\", function(d) { return d.children ? \"node\" : \"leaf node\"; })\n",
      "      .attr(\"transform\", function(d) { return \"translate(\" + d.x + \",\" + d.y + \")\"; });\n",
      "\n",
      "  node.append(\"title\")\n",
      "      .text(function(d) { return d.name + (d.children ? \"\" : \": \" + format(d.size)); });\n",
      "\n",
      "  node.append(\"circle\")\n",
      "      .attr(\"r\", function(d) { return d.r; });\n",
      "\n",
      "  node.filter(function(d) { return !d.children; }).append(\"text\")\n",
      "      .attr(\"dy\", \".3em\")\n",
      "      .style(\"text-anchor\", \"middle\")\n",
      "      .text(function(d) { return d.name.substring(0, d.r / 3); });\n",
      "});\n",
      "\n",
      "d3.select(self.frameElement).style(\"height\", diameter + \"px\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "javascript": [
        "\n",
        "// element is the jQuery element we will append to\n",
        "var e = element.get(0);\n",
        "    \n",
        "var diameter = 600,\n",
        "    format = d3.format(\",d\");\n",
        "\n",
        "var pack = d3.layout.pack()\n",
        "    .size([diameter - 4, diameter - 4])\n",
        "    .value(function(d) { return d.size; });\n",
        "\n",
        "var svg = d3.select(e).append(\"svg\")\n",
        "    .attr(\"width\", diameter)\n",
        "    .attr(\"height\", diameter)\n",
        "  .append(\"g\")\n",
        "    .attr(\"transform\", \"translate(2,2)\");\n",
        "\n",
        "d3.json(\"data/flare.json\", function(error, root) {\n",
        "  var node = svg.datum(root).selectAll(\".node\")\n",
        "      .data(pack.nodes)\n",
        "    .enter().append(\"g\")\n",
        "      .attr(\"class\", function(d) { return d.children ? \"node\" : \"leaf node\"; })\n",
        "      .attr(\"transform\", function(d) { return \"translate(\" + d.x + \",\" + d.y + \")\"; });\n",
        "\n",
        "  node.append(\"title\")\n",
        "      .text(function(d) { return d.name + (d.children ? \"\" : \": \" + format(d.size)); });\n",
        "\n",
        "  node.append(\"circle\")\n",
        "      .attr(\"r\", function(d) { return d.r; });\n",
        "\n",
        "  node.filter(function(d) { return !d.children; }).append(\"text\")\n",
        "      .attr(\"dy\", \".3em\")\n",
        "      .style(\"text-anchor\", \"middle\")\n",
        "      .text(function(d) { return d.name.substring(0, d.r / 3); });\n",
        "});\n",
        "\n",
        "d3.select(self.frameElement).style(\"height\", diameter + \"px\");"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript object>"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "LaTeX"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The IPython display system also has builtin support for the display of mathematical expressions typeset in LaTeX, which is rendered in the browser using [MathJax](http://mathjax.org)."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can pass raw LaTeX test as a string to the `Math` object:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Math\n",
      "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 24,
       "text": [
        "<IPython.core.display.Math object>"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "With the `Latex` class, you have to include the delimiters yourself.  This allows you to use other LaTeX modes such as `eqnarray`:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Latex\n",
      "Latex(r\"\"\"\\begin{eqnarray}\n",
      "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
      "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
      "\\end{eqnarray}\"\"\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{eqnarray}\n",
        "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
        "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
        "\\end{eqnarray}"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
        "<IPython.core.display.Latex object>"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Or you can enter LaTeX directly with the `%%latex` cell magic:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%latex\n",
      "\\begin{align}\n",
      "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
      "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
      "\\end{align}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{align}\n",
        "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
        "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
        "\\end{align}"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Latex object>"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Audio"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "IPython makes it easy to work with sounds interactively. The `Audio` display class allows you to create an audio control that is embedded in the Notebook. The interface is analogous to the interface of the `Image` display class. All audio formats supported by the browser can be used. Note that no single format is presently supported in all browsers."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Audio\n",
      "Audio(url=\"http://www.nch.com.au/acm/8k16bitpcm.wav\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "                <audio controls=\"controls\" >\n",
        "                    <source src=\"http://www.nch.com.au/acm/8k16bitpcm.wav\" type=\"audio/x-wav\" />\n",
        "                    Your browser does not support the audio element.\n",
        "                </audio>\n",
        "              "
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 27,
       "text": [
        "<IPython.lib.display.Audio object>"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A NumPy array can be auralized automatically. The `Audio` class normalizes and encodes the data and embeds the resulting audio in the Notebook.\n",
      "\n",
      "For instance, when two sine waves with almost the same frequency are superimposed a phenomena known as [beats](https://en.wikipedia.org/wiki/Beat_%28acoustics%29) occur. This can be auralised as follows:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "max_time = 3\n",
      "f1 = 220.0\n",
      "f2 = 224.0\n",
      "rate = 8000.0\n",
      "L = 3\n",
      "times = np.linspace(0,L,rate*L)\n",
      "signal = np.sin(2*np.pi*f1*times) + np.sin(2*np.pi*f2*times)\n",
      "\n",
      "Audio(data=signal, rate=rate)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "                <audio controls=\"controls\" >\n",
        "                    <source 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rLudBZKiidaExYN5ht2MwZbYo76z9sX22SDv0ARhGigvhELgU7Niim4Jd+17D31legV0H2r+XApNvDqjJloRifvV5enQaL3pq/Sc/pBliGuDOILWhDCLF5U+oj6yncTM2C7uHATvGfsunUI8VE9jYW8UeCN9Z37We4J1nWtzXmpO/ju+J0cSQfxU5izRbb2xq4KcVpCMh2iCE4GYg+OJxJPuoPywcsO/10ftYQNkGaMue0JQVJdj22+7ePJ9WH/gfJ92xWycX41PEj28KCgT//zr5pjRrL3Bq2ScDJAYh86BWIDBgveIyZLsn/qvdsLR1mzsoALBGCMuIEIcVItj92/9eFh+33+EfVt3k214YG9Q9T2aKfsTwv2Y5yzSI74ZrJqcH5AIh5yBBoBRgmyIKJI4nzmvrMED1qHr3AEJGHwtjUGhUyxjtW/beFZ+/H/AfbR3B24EYQ9Rpj5WKr8Uh/5b6ObS0b62rCKdjpBch9OBHYBJgkSI4ZHVnrquFsFZ1ebqFgE9F64sxEDiUntiF29UeOp9r3+Ufap3IG4/YWxRIj/vKnAVTf8w6cbTtL+XrfydWpEUiHKCn4CpgoCI9pHCnn+utMDT1D/qUABfFr4rxz/fUXphHm5rdxd9+H7/fDx33G0pYYRRaD9iKw4WEAAW6sjUy8C7riWfgJIviXmDioFygyCJaJIBn4quicBz1Kvpjv9xFasqlz6aUClgy2wfdt172X0DfGt2PW3AYFZRdz+vK5YW0gAL6+rVE8IgsJyg/5OqiuaE3oKihCOKNpOTn9uulsA61C7pz/51FHkpNz0WT4xeIWt0dD16UXyfejZ1QWwFYOJQTj/TKwgXjgEO7CzXi8PEsWCi1ZWGjLiGmoQ5homLYJR4oHOv3MAq1MnoFv5tEykoqDtUTaNcIGlpcjl4YnrVeJ9z6Gr2XiZQ7D7OK2EXQwIb7YrYMMWks22kAJi+ju6Iu4Y2iFKN5pWwoVKwW8FF1HzoZf1bEr4m7jlXS3Jay2YDcNN1DnimdqVxNGmVXSNPUD6eK6AX8AIx7gHa/8a9tcGmfppSkYWLQYmXinyPyJc6o3mxFMKK1EvovvxBETolCjghSftXJWRCbQxzV3UTdEtvJWfiW9lNej1DK8MXkgNO75Hb98gOuFqpS50/lHqOKYxbjQaSBJoXpeeyCMP71DboIfwiEJ8jADa2RkFVMWEqauhvQHIgcZJsvWTcWUhMaTy7KsoXKARv8DbdE8uTujSsZaCBl8yRcI9+kO2UmZxEp5y0NsSZ1T3okvv/DvAh0TMYREdS8l2+ZmpsyW7NbXxp/GGHV29KHTsHKrMXsQST8e7eU81JvUyvyaMWm3aVFJMAlDGYhZ/CqZe2n8Vk1mToEfvaDS8ggTFLQRFPa1oCY5Ro+Godagxm5V7iVFFIlzklKX4XKgW48rfgss8twKCycqf6nneZEpfcl86bx6KOrNi4Qsdc16nooPq2DGAeEy9QPqFLoFb4Xmpkz2YUZkNieVvvUe5F1jcWKCkXkgXb843iLtI8wyu2Xqspo8mdZpsQnMKfW6anr127H8mC2A7pQfqUC4MciiwtO/xHlFKkWvBfUWK2YSVevFewTkdD3TXZJrMW6AX79G/kxNRzxuq5ia+gp2miDKCZoAmkQKoLsyW+NcvW2ZTp9Pl3Cp0a6SnlNyVES04LVipbg10EXbVZsFMoS15AqjNvJR0WKwYW9lrmcNfNydi97rNarFSnAaVypaGocq63ti7BhM1X2zvqu/lfCa8YMid6NB9AykkxUR1WaFgEWPZUWE9YRzU9QDHYI2UVWQYp90voMNpIzfPBirhTsYSsQaqYqoWt77KqunfECdAE3QPrmPlQCLsWaSTwMPA7FUUbTMtQBVO6Uu1PuEpEQ845oC4UIowUcgY0+D/qAd3f0DbGV72GtvWxxq8GsLKys7ffvv3HxNLe3u3rivlLB8UUkSFMLZs3MUDMRjxLX00pTZ1K0kXuPio2zCslIJITdAY0+Tbs39+P1JzKUsLvu6K3jLW4tSS4urxUw73LstXj4Pjsk/lRBs8Srh6RKSUzITtKQXJFe0dXRwtFqkBaOk0yxCgLHnUSXwYo+ivuyOJV2CLPdceIwYe9jrupu9a9AcIGyLbP0tgS4yXutPlkBdsQwRvCJZEu6zWaO3Q/XEFIQTo/RjuLNTkuiyXHGzgRMwYO+x3wt+Us3MPTvcxOx57Dx8HUwcPDgsfyzOTTI9xr5XPv7fmFBOwOzxjkIeQpkzDBNUY5CjsCOzE5qDWFMPIpJCJaGdoP7gXk+wryq+gQ4HvYI9I6zeHJMcg0yOjJO80S0kXYoN/r5+LwPvq2AwMN2hX5HSIlHyvEL+4yiTSJNPMy1i9LK3olkB7HFlsOkAWr/O7zoOv/40XdpNdH00zQyM7Ezj3QJtNk19TcSeOR6nDyqPr5AiML5hIHGlEgkyWoKXIs3i3kLYcs1CniJdQg0xoOFL0MGQVf/cn1k+705x3iOt1w2djWhdV+1cDWPtni3I7hG+db7R30LPtOAk4J9Q8RFnMb9B9zI9clECcXJ/AlpyNPIAYc7hYzEQELiQQB/pj3gfHr6/7m4eKv34HdY9xc3Gndft+K4nDmEutI8On1yPu1AYUHCg0aEo8WSBoqHSIfJCApIDYfVB2VGhEX5hI2DicJ4QOP/ln5aPTg7+XrkugA5kDkXONZ4zPk4uVV6HbrK+9V89H3ffwxAcwFKQomDqcRkhTTFlsYIBkfGV0Y4Ba5FPsRvQ4aCzAHIAMJ/wv7RPfR88zwSu5c7A/raupu6hrrZOxA7pzwY/N/9tX5Sv3CACMEUwc5CsEM2Q5zEIURChIAEmoRUhDBDscMdgrhBx8FRgJu/6v8E/q697D1A/S+8unxhvGX8Rby/vJF9N31uPfF+fP7MP5oAIwCiwRWBuEHIgkQCqgK6ArQCmUKrQmwCHoHFQaOBPUCVQG9/zj+0vyW+4v6uPkh+cf4rPjL+CP5rPlf+jX7JPwk/Sr+Lf8kAAkB1AGBAgsDcAOvA8kDwAOXA1MD+AKNAhcCnQEkAbIATAD2/7H/gP9j/1v/Zf9//6X/1P8GADgAZQCJAJ8ApQCXAHYAQAD3/5z/Mv++/kT+y/1X/e/8mvxc/Dr8Ovxd/Kb8FP2n/Vz+Lv8YABMBGAIdAxkEAwXRBXsG+AZCB1MHKAe/BhkGNwUfBNgCaQHf/0T+pPwO+475NPgL9x72efUi9SD1dvUj9if3e/gX+vD7+v0kAGACmgTCBsQIkAoVDEUNFA54DmwO7Q37DJsL1gm3B0wFqALe/wP9Lfp19+/0svLQ8FzvZO7x7Qrusu7n76Hx1/N49nP5svwaAJQDBAdOClcNBhBEEv0TIBWjFX0VrRQ3EyMRfg5bC9EH+gPz/9r70ff282nwSe2u6rDoYefO5v/m9ees6RnsLO/O8uf2Vvv7/7EEVAm/Dc8RYRVZGJ0aGBy7HIAcZRtvGaoWKxMKD2QKXgUdAMv6j/WU8AHs/eeo5B7id+DB3wXgReF545Pmfuod70306fnF/7MFhwsRESYWnBpPHh8h9CK8I3AjDSKcHy0c2Re+EgMN0wZeANX5avNR7bvn0+LD3q3bqtnO2CLZp9pT3RXh0eVm66rxbPh6/5wGnA1DFFsatB8hJH4nrymfKkUqoCi6JaYhgxx2FqsPWAizAPn4ZPEx6pnj0N0F2WHVAdP80VzSINQ/16PbK+Gv5/7u4PYa/2sHkw9SF2oeoyTKKbYtRDBfMfswGC/CKxEnJSEsGloS6gkdATj4fu81557f9thy0z/PgsxQy7jLuM1D0UHWjtz6403sSPWm/h8IaRE7Gk8iZilGL8AzrTb1N4s3cDWwMWcsvCXfHQ0ViAubAZH3ue1f5M7bStQOzk7JMcbRxDzFcsdky/bQ/9dK4JnppfMg/rgIHRP8HAkm+i2RNJc55TxdPvE9ojt/N6YxQiqKIcEXMA0rAgb3Fuyy4SzYz8/eyJHDE8CDvu6+VcGnxcXLg9Ol3Obm+PGH/TYJrxSVH5MpWjKlOTg/5kKQRCZEqUEpPcc2sy4qJXMa4A7MApT2luov37rUicvmww2+L7psuNS4ZrsSwLTGHc8M2TbkRfDd/JsJHRYCIuwshTaAPp5ErEiKSiVKf0epQsc7DDO6KCAdlxB+Az32OenY3HvRfMcqv8e4ibSRsvGyqrWousfB0sqE1Yzhje4j/OUJaBdDJBIwdjodQ8NJMk5FUOlPH036R6BASDc4LMYfUBI/BAD2AOit2nDOqMOsusOzJa/3rE2tJ7BwtQO9psYR0uve0uxb+xUKjxhXJgEzKj55R6VOc1O9VW1VhFIYTU5FYzuhL2IiDBQNBdz16+ax2JzLE8BytgWvB6qip+un4KpvsG24nsK1zlXcF+uH+i0Kkhk8KLk1oEGRSz9TbFjsWqxaqlf9Uc1JWD/vMvAkxhXoBdH1++Xj1gDJvrx9spCqNaWYos+i3KWoqwe0vL51y8/ZXemn+SwKcBryKTg41ERiT45XF13QX6JfjFylVhdOJEMgNm0nfhfNBt31L+VG1Z7Gq7nRrmimsaDcnQCeHqEgp9ivBrtUyFvXqOe9+BQKKht3K306xkfpUo9bcmFkZEpkJmELWypSxEYwOdgpMRm7BwD2h+TY03fE3LZwq5CigJxymYCZqpzbouOrf7dVxfvU+eXL9+YJwBvMLIY8ckojVj5feWWjaKFocmUtXwBWMkocPCws2xqwCDn2A+Sc0o3CU7RdqAqfpJhelVOVhZjeniyoKrR8wrPSU+TT9qMJMhzwLVI+10wPWZhiKGmKbKJsbmkFY5dZbE3hPmcufByrCYb2ouOQ0d/AEbKZpdqbIZWkkX6Rs5Qsm7ekDLHMv4bQuOLX9UwJghzjLuE/9U6qW51lfmwXcEtwFm2QZupcblB8QYYwEB6oCuf2Y+O10G+/GLAnowKZ+pFFjgOON5HJl4ehJ65IvXbOLOHY9OIIsBymLzJByVDzXUhod29Gc5dzZnDKafZfNVPoQ4YylR+oC1n3RuML0D2+aK4HoYSWMI9Gi+aKFI64lJ+ef6v0uobMr9/Z82cIvBw4MEVCVFLpX5lqEXIVdoV2W3OxbLhivVUkRmU0CSGmDNz3SuOQz0m9Aq07n2CUxoypiCmITYv8kQOcF6nRuLnKRN7b8t0HqBybMBpDlVOLYY9sSnSBeBB583VBby1lBFgsSB82aSKjDW74beNFz5K856vEnZmSvopvhs+F5IiYj7aZ8abkthLJ79zh8UUHdhzPMLJDi1TXYiduInaIejh7K3h4cVJnCFr/SbM3tCOaDgz5r+Mozxm8FqujnDCRGImahNqD3YaOjbqXEaUttZLHsNvs8KAGJhzVMAxEN1XOY2FvlXcqfPt8AXpUcyVpxFuYSx455iSMD7b5DeQ5z927j6rWmyWQ14csg0uCOYXiixGWeaOxszzGitr/7/EFuhutMCpEmFVwZD1wpHhkfVZ+c3vRdKNqOF33TF46/iV1EGr6h+R3z927U6pgm3iP+oYmgiSB+oOUir6UKqJxshPFgNkb7zoFMxtbMA1EsFW8ZLpwT3k2fkl/gHzvdctrYV4YTnE7+iZTESX7GuXfzxi8X6o+myqPgoaJgWWAIYOmicKTKKFusRjElNhD7nsEkxrdL7VDgFWzZNlwlHmfftJ/JX2tdptsPV/7TlM81yclEub7xuVx0Iy8tKpxmzqPb4ZUgRGAroIZiR+Tc6CssE7Dxtd47bgD3Bk3LyRDCFVXZJtwdHmffvJ/ZH0IdxFtyl+dTwU9lCjoEqv8iOYq0Tm9T6v3m6iPwYaJgSaApILviNaSDKArsLXCGte87PECEBlqLlxCSVSnY/9v8Hg2fqh/O30BdyxtCWD8T4Q9LymcE3P9XucK0h2+MKzPnHKQeIcmgqWAAYMoieiS95/ur1HCkdYR7CoCMBh4LV5BRlOmYgdvCHhlffR+qXyXdu1s9l8YUM49pik9FDr+R+gO0zW/Va35nZiRkYgqg46BxoPDiVWTMqD0ryHCLdZ662MBPxdjLCxAAFJVYbRtvnYtfNd9sHvJdVJskl/vT+I99ynKFAD/QOk01IDAvK5xnxeTDIqWhN+C84TCih+UvqA/sCjC7tX36p4APhYsK8g+eVC2XwlsE3WOelJ8UHqZdFpr3V6BT789IipCFcL/SOp71fzBYrA3oe6U54tnhpiEh4YkjEOVnaHQsGfC19WL6uD/LxXXKTU9s07KXQZqCHOLeGZ6iXgGcwhq1V3NTmU9JSqjFX4AXOvf1qbDRrJHoxuXII6biLeGgIjojcSWzqKosd7C6dU26ib/FhRlKHQ7sUyWW69noXAmdhR4XnYScVpoe1zSTdI8/inrFTQBe+xe2HzFZrSfpZuZtZAxizqJ3YoMkJ+YUKTGso3DJdb76XX+8xLYJok5dkoaWQdl321gc191z3O+blJm0FqRTAU8rikZFuABoe332XvHvbY9qGyco5MnjiCMnI2QktOaJKYqtHfEi9ba6c39yRE0JXY3A0hbVg9ixWo8cEly4HALbPFj1FgKS/86MiksFoICzu6n26HJSrkdq4qf6JZ4kWWPvJBylWCdSKjUtZnFHNfV6TH9mhB6Iz41XUVaU8teV2e9bNVukW37aDlhiFY9ScA5iigiFhgD/+9r3evLCbw9rvOif5ojlQeTOpSvmESgvKrEt/XG2tft6aP8aA+tIeMyhkIcUD5bl2PmaAZr5mmRZSpe7VMrR0c4tyf7FZ8DMvFA31bO976ZsaKmZ54lmQOXEphGnH2jfa34uYvIxNgj6iP8NQ7PH2kwgT+kTG1XiV+8ZN5m4WXPYchaBVHURJU2tya2FRcEZPIl4d/QEsIttZWqmqJ4nVabQpwzoAini7BwvFnK2tl46rP7Aw3kHdItUjz1SFlTMVtAYGFihmG3XRRX0007Qqo0iiVRFX4ElfMW44PTVMX2uMeuFqcbovufxqBzpOOq47Mqv2DMHdvt6lX71AvtGyEr/DgTRQlPk1Z4W5Rd2VxOWRJTVkphP4gyMiTNFNMEwfQS5T/WvMjwvDWz1asHp/Ckm6UEqQyvgrckwp3Oi9yB6wr7qwruGVsogzUCQX9Ks1FoVnpY3VeXVMROlEZHPC8wrSIpFBUF6PUV5xDZRcwXwdq31LA6rC6qvarhrX6zaLtexRHRJt427NL6iAnoF4El6zHHPMFFlkwTURhTllKVTy5KjULvOKEt/CBjE0IFBvcd6fLb7M9mxbG8DravsbOvKLAHsze4j7/UyLrT7d8L7bD6bgjeFZciNy5kONJAQEeAS3JNCU1MSlJFRT5bNd4qIB9+ElkFG/gn6+PerNPaybbBfrtgt3m11rVxuDS998OEzJbW3eEB7qP6XwfUE6EfayrfM7c7t0GyRY1HO0fBRDZAvjmPMeonGx13EVsFJPkx7d7hg9duzuXGIMFJvXu7w7scvnDCm8hs0KPZ+OMY7636XAbKEaAciiY9L3U2/zuwP25BMEH4Ptw6/jSMLcUk7BpQEEUFIfo57+LkbNsf0znM7sZkw7XB68ECxObHeM2I1N/cOuZP8M/6ZgXFD5oZmiKAKhExHTZ9ORs77Tr2OEk1BjBWKXEhlRgJDxcFD/s88evnZN/n16zR48ytySHISMgfypTNidLX2EngpOim8Qj7gATFDZAWnB6uJZArFjAgM5g0dzTAMoIv2yrwJPIdGRaiDdIE7vs48/bqZuPB3DrX+dId0LnO1c5u0HPTzNdU3d3jNOsd81r7qQPNC4UTlhrMIPYl8CmeLOwt1C1aLIspgSVdIEkadxMdDHQEu/wr9f/tb+er4d7cLNmv1njVjNXp1oHZPN384Zrn5+2y9MT75QLgCX0QjBbdG0kgsSP8JRwnCifKJWkj/B+gG3oWshB5Cv4Ddv0S9wTxeuue5pPid99e3VjcaNyL3bbf1eLM5nzrvPBk9kb8MwL/B3sNgBLmFo4aXR1BHy4gHiAXHyEdURq+FoYSzQ24CG8DHv7t+AP0hu+X61To0uUk5FPjY+NP5A/mkejA64DvsvM0+OH8lQEsBoIKdg7sEckU+xZyGCcZFhlEGLkWhBS6EXIOyArbBsgCsv64+vf2jPOR8BvuOuz76mPqduov64bsbe7T8KPzxPYe+pX9CwFpBJQHcwrzDAEPjxCWEQ4S+BFYETUQmw6ZDEEKqAfjBAkCMv9y/N75i/eI9eTzqPLc8YPxnfEm8hbzZPQC9uL38/kj/GD+lwC4ArQEegb/BzkJIAqxCukKygpZCpsJmQheB/UFbQTSAjIBnP8Z/rb8fvt4+qn5F/nD+Kz40fgs+bn5cPpI+zn8Ov0//kL/OAAbAeQBjgIVA3cDswPKA74DkwNMA/AChAINApMBGwGpAEQA7/+s/33/Yv9b/2b/gf+p/9j/CgA8AGkAiwCgAKQAlQByADoA8P+T/yn/tP46/sH9Tv3n/JT8WPw5/Dv8Yvyt/B/9tf1s/kH/LAApAS4CMgMuBBUF4QWHBgAHRgdSByIHtAYIBiIFBgS6AkkBvv8h/oH87fpw+Rn49PYN9m71HvUk9YH1NvZA95v4PPoa/Cf+UwCQAskE7wbtCLMKMgxaDSAOfA5mDt0N4gx5C6wJhgcWBW0Cov/G/PL5Pfe89IbyrfBD71Xu7e0T7sfuB/DM8Qv0tfa2+fn8ZADfA0wHkgqUDTsQbhIbFDEVphVyFZUUERPwEEAOFAuCB6UDnP+D+3z3p/Mi8AvtfeqN6E3ny+YM5xPo2elU7HTvIvND97j7XgAVBbUJGg4gEqcVkRjEGi4cvxxxHEMbOxlnFtkSqw78CfAErf9a+iL1LvCm66/naeTy4V7gvd8W4Gvhs+Pf5trqhu/C9GT6QwAxBgEMgxGMFvMalB5QIQ8jwSNdI+MhXB/ZG3MXSRKDDEwG0/9K+eXy1exL53Tid95324zZydg32dXamd1x4UHm5us28gD5EQA0By8OyxTVGhwgdCS5J9AppSovKm4obiVCIQoc6xUUD7cHDgBV+MbwnukV41/drNgh1d7S9tF00lbUkdcO3K3hROih7473zP8bCD0Q8Bf4HhwlKir6LWowZTHhMN8uayueJpogjRmrETEJXwB798jui+YG33TYC9P2zlnMScvTy/TNoNG71iLdo+QH7Q32cf/oCCoS7xrxIvAptC8ONNk2/TdvNzA1TjHmKx8lKx1IFLcKxAC89uzsoOMj27jTms37yALGyMRaxbbHy8t+0aTYCOFp6oH0Av+ZCfYTxh2+JpQuDDXvORY9Zj7SPVs7EzcXMZQpwyDmFkkMPQEZ9jLr3eBt1yzPXMg0w9+/eL4Ov5/BGcZbzDnUdd3L5+vygP4vCp4VdCBbKgUzLjqaPx5Dm0QFRFxBszwrNvUtTySDGeINyAGR9ZvpRt7p09bKV8OnvfW5X7j1uLW7jMBXx+PP79kw5U7x7f2pCiIX9iLHLUA3FT8JRepIl0oCSixHKkIeOz8yzicdHIMPYwIk9Sno2tuX0LnGjr5XuEi0grIVs/+1LLt2wqfLedaZ4qvvSf0JC4IYSyX+MEA7v0M4SnZOVVDFT8hMckfrP2w2OyuvHikRDwPR9NvmnNl6zdbCBLpKs96u5axxrYCw/LW+vYrHFtMK4APulfxOC70Zcif/MwQ/KEgjT71Tz1VIVSlSiEyORHk6ky45IdESygOZ9LPljdeVyjK/vbWCrrqpjqcQqD6rArExuY7Dys+H3Vvs1Pt5C9MaaSnINohCTEzHU7xYAluHWktXZlEDSWE+0jG2I3kUkQR69LDkrtXpx867vLEEquKkgaL1oj2mQqzWtLm/mMwR27PqB/uMC8QbMCtXOctFKVAfWG1d6V99XylcB1ZETSJC9TQkJiAWZAV19NLj/9N4xa24Ba7TpVigwp0lnoKhwKewsA+8hcms2A7pLvqFC48cxiyrO8pIu1MoXM5hf2QlZMBgaFpOUbZF+TeAKMIXQgaH9BnjgtJCw9G1maryoSGcVZmlmRGdgaPDrJK4k8Za1m/nTPlnCzUdKi7CPYJLAFffX9tlwmh8aAplhV4dVRpJ2TrGKl4ZJwew9IbiNtFKwTyze6dknj+YPZV4le+YiJ8TqUa1xcMf1NflY/gzC7cdXS+bP/RN9llCY5BprWx+bARpWGKtWEtMkz31LPEaEwjv9BbiHdCPv++wrqQtm7eUgJGikR6V2pukpTCyH8H+0UnkdffqChQeXTA3QR1Qm1xOZutsPXAocKts4GX6W0ZPJEAJL3kcBAlC9crhNc8TvuuuMqJNmIqRHo4mjqOReph5olOvpL74z8jigvaNCk4eLDGTQvtR7V4Baepvb3N1c/pvF2kCXwZSiEL/MPMd+Amp9aHhf87WvDGtCqDHlbuOG4sHi4CObJWWn7GsWLwRzlXhjvUdCmYeyjGxQ5BT62BZa4lyQXZkdu9y/GvAYYlUvUTWMl4f7Qoh9pvh+s3Yu8KrNp6dk0yMeohJiLmLspL+nE6qPLpMzPPfmfSdCVweNjKPRNlUlGJVbcd0sXjyeId1i24xZMtWv0aJNLYg4Aup9rXhps0Zu5+quJzQkT6KPYbthVGJT5Czmi2oU7iryqXep/MNCTIecjIvRdZV52PzbqN2vHoce8B3wXBUZstYjUgXNvoh0QxA9+7hgc2ZusepkJtikJSIZYT1g0mHRo65mE+mobYwyWzdufJvCOkdfzKQRYlW5GQycBt4YHzgfJZ5nHImaIVaI0p+NycjvA3k90bijM1WujqpvppSj0+H9IJkgqOFmYwRl7mkKLXex0vc0PHGB4MdXjK0RfBWi2UTcS55nX0+fgp7GnSjafdbf0u7ODwkoQ6T+LvixM1RuvmoQpqhjm6G64E7gWKES4u+lWuj6bO3xkTb8PASBwAdDzKbRQxX22WUcdx5cn4zfxh8OXXLaiBdoEzMOTUlfA9L+UvjKc6IugGpHZpPjvOFS4F6gIeDW4rBlGii57K9xVnaGvBWBmMclTFHRd9W1mW2cSR63n6/f8B8+HWca/1dgk2uOhImTRAK+vXjuM76ulOpTZpcjt6FE4EjgBODzYkclLKhJLLyxIvZT++UBa4b8TC4RGlWfGV6cQd64X7hfwF9VnYVbIxeJk5hO88mERHQ+rbkcc+lu+2p0ZrIji2GRYE1gAWDoInRk0qhobFYxN7Yku7MBOEaJDDwQ6xVzWTgcIV5e36af9p8UnYzbM1eiE7iO2wnxhGY+43lUdCJvM2qqZuQj+KG4IGygGCD1YnfkzChYLHxw1LY5e0DBP8ZMS/xQqhUzWPpb594rH3pfkx863X3a75eqE4wPOcnaxJj/HnmV9GivfOr0py1kPmH44KXgSKEbYpJlGehYrG9w+nXSu04AwsZGS69QWFTe2KXblZ3dXzOfVZ7InVga19ehE5JPD4o/RIt/XbngdLwvlutS540knOJTITmgkuFaIsNle6hqLG+w6XXwexuAgUY3ixWQNhR2mDrbKt12XpMfPp59nNvaq9dHE4tPG8oexP1/YPozNNwwAWvE6AMlE6LHIachNuGxYwtlseiMrL2w4fXTuyoAfEWgyu+Pg5Q7V7naqFz13hiejd4aHIiaa5cb03aO3ko5BO6/p7pNtUfwu6wJqI7loiNT4i5htCIhI6nl/GjArNkxJDX8evmANAVCir4PAhOtVyOaDlxcnYTeBB2eXB7Z1xbfUxQO1woNRR4/8Xqvdb8wxKzgqS9mB2Q5Io6iSmLo5B7mWulF7QKxcLXq+srAKMUdSgGO8ZLNVrjZXZurXNhdYVzKm56ZblZRUuOOhYobhQuAPbrX9gDxnC1JaeRmw2T2Y0djOWNIZOomzancbXpxR3Yf+t5/28TxybqOExJcFfnYlpriXBNcppwfWshY8ZXyEmTOaYnjRTcAC7tGdozyAW4DKq0nlSWK5FgjwCR/JUtnlGpELcAx6LYbuvR/jQSAiWoNp5GaVSfX+lnCm3bbk9tdGhwYIRVBkhgOAsnkBR/AWvu6duHys26M60hou6Z1pQAk3mUM5kIobqr9LhPyFLZeOs1/vQQKCNCNL1DI1ENXCdkM2kNa6hpEGVqXfRSAEb0NkYmeBQVAqzvy93+zMW9lrDXpdmd2Jj7lk2Yw5w4pHCuHLvXyS3an+um/bMPPSG7Ma5Aok01WBVgB2XnZqhlVWESWhhQt0NRNVUlQhScAu7wvt+Uz+rAM7TQqRCiLZ1Mm3mcqaC5p3Kxhr2WyzPb5Osm/XEOQx8XL3M96kkbVLlbimBsYlJhRV1oVvFMLEF1Mzkk7xMUAy/yv+FG0jnEBrgKrpCm0aHwn/mg4qSLq760MsCNzWXcR+y2/DENPB1YLBE6/UXCTxZXwVugXalc41hvUoFJYD5jMfIifBN8A23zy+MR1a7HC7yAslWrwKbjpMqla6mpr1G4HsO6z8LdyexY/PYLKxuBKYo24UEwSzFSrlaHWLFXM1QsTstFVTscL38h6xLQA6b04OXy10bLPcAtt1qw9ashqueqQa4RtCm8R8Yc0krfau0N/MAKExmXJuMymT1oRg1NV1EmU25SOU+gSdJBDTifLOIfOhISBNj1++fl2vvOmsQOvJq1bbGlr02wX7PAuEPArcmz1P3gK+7V+5EJ9habIx8vKjlvQbFHwEuATeZM+EnQRJg9ijTvKRoeaRE+BAL3Gero3czSG8kewRG7Ibdrtfi1wrixvZ3ETc1819niC++z+20I1xSSIEMrlzRKPCBC70WbRxtHdES+PyA5zzANJykceBBWBCH4OOz34LTWvs1YxrrADr1tu+G7Zb7iwjLJI9F22t7kDPCn+1MHuRJ+HVEn5i/9NmA86D99QRNBsz5wOm003Sz8IxAaaA9XBDX5Vu4P5K/afdK3y5HGLsOnwQbCRMRNyADOL9We3QvnLPGx+0cGnRBjGk4jGiuMMXU2sTkpO9Q6uDjoNIQvuSi9IM8XOA5BBDr6b/At57neVdc30Y7Me8kTyF/IWcrvzQPTa9nz4F/pbPLS+0gFhg5DFz4fOCb+K2YwTzOlNGI0iTIsL2gqZSRSHWkV6QwUBDH7g/JN6s7iQNzT1q7S8c+tzunOoNDE0zfY1t1z5NjryvML/FoEdwwjFCQbRSFXJjcqxyz4LcItKyxBKR4l5B++Gd4SewvPAxf8jfRt7evmOuGE3OvYidZt1Z3VFNfF2ZjdbOIa6HTuR/Vc/HwDcQoFEQUXRBycIO0jICYmJ/smoiUqI6gfOhsEFjEQ8AlyA+z8jfaJ8AzrP+ZH4kDfPt1O3HbcsN3w3yLjKufn6zLx4PbF/LECdwjsDeQSPBfSGo8dXx82IBIg9h7uHAwaahYmEmMNSAj+Aq79gfie8yzvS+sW6KblCuRM427jbeQ95s/oC+zV7w/0lvhG/fkBiwbaCsUOLxL/FCIXiRgtGQwZKhiQFk4UeREoDncKhQZxAlz+Zfqq9kjzV/Dt7Rns5+pf6n/qRuup7JzuC/Hj8wr3Z/rf/VQBrwTUB6wKIw0nD6sQpRESEvARRBEXEHMOagwMCm4HpgTMAfb+Ofyq+V33YfXF85Py0PGB8aTxNvIu84P0KPYM+CD6UvyP/sUA5ALcBJ0GHAhPCTAKuQrqCsQKTAqHCYAIQQfWBUsErwIQAXr/+v2b/Gb7ZPqb+Q75v/it+Nb4NvnH+YH6XPtO/E/9Vf5X/0wALQHzAZsCHwN9A7YDygO7A44DRQPnAnoCAwKJAREBoAA8AOn/p/96/2H/W/9o/4T/rP/c/w4AQABsAI4AoQCkAJMAbgA1AOn/i/8f/6r+MP63/UX94PyO/FT8OPw9/Gb8tfwq/cP9ff5U/0EAPgFEAkgDQgQoBfAFkwYIB0kHUAcbB6gG9wUMBewDnQIpAZz//v1f/Mz6Uvn/99/2/fVk9Rz1KPWM9Un2Wve7+GL6RPxV/oMAvwL4BBsHFQnWCk4Mbw0sDn4OXw7MDcgMVwuBCVUH3wQzAmX/ify3+QX3ivRb8orwKu9H7uvtHO7c7ifw9/FA9PL2+vlB/a4AKQSUB9UK0Q1uEJcSOBRCFagVZhV7FOkSvBABDssKMgdQA0X/LPso91jz3O/P7E3qa+g758nmG+cx6Afqkey973bzn/ca/MMAeQUVCnQOcRLrFccY6hpCHMEcYRwgGwcZIhaFEkwOlAmBBDv/6fm19MjvS+ti5y3kx+FH4LvfKeCS4e7jLec36/HvNvXg+sEArwZ6DPQR8RZJG9gefyEoI8MjSCO3IRsfhBsMF9QRAgzDBUj/wPhf8lns3OYW4i3eQ9tx2cfYTtkF2+HdzuGy5mfsw/KV+aoAywfADlIVThuCIMQk8SfuKagqFio6KCAl3SCQG2AVew4WB2r/svcp8AvpkuLw3FTY5NS90vPRj9KO1OXXe9ww4troRvA7+HwAywjmEI0YhB+TJYgqPC6OMGkxxTCjLhErKSYNIOwY+xB3CKL/v/YT7uPlcN7116bSsM4zzEXL8cs0zv/RONe43U7lwu3T9joAsAnrEqIbkSN4Kh8wWTQCNwI4TzftNOkwYiuAJHYcgRPmCe//6PUf7OLiedoo0yjNq8jWxcPEe8X8xzbMCdJM2cfhO+te9eT/eQrOFI8ecSctL4Q1RDpFPWw+sD0RO6M2hTDkKPofChZgC08ALfVP6grgsdaMzt7H28Kuv3G+Mr/swY3G9Mzx1Ejesujf83r/JguMFlEhISuuM7M6+D9SQ6NE4EMMQTk8izU1LXMjkhjkDMMAjvSi6F7dGdMmysvCRL2+uVa4G7kJvAvB/cer0NXaK+ZY8v3+twsmGOgjny74N6c/cEUjSaFK3EnWRqZBcjpuMeAmFxtvDkgBC/Qa597atc/5xfW967cMtHeyPLNYtrS7KcN/zHDXqOPJ8G7+LQybGVAm6DEIPF5EqUq1TmFQnU9tTOZGMz+MNTwqlx0AEN8Bo/O45Y3Yh8wHwl+51LKbrtismq3esIy2fL5wyB7ULOE279D9hwzqGooo+zTaP9NInU8CVN5VH1XJUfRLy0OLOYMtDiCVEYUCV/N85GvWkclUvgy1A65yqX6nOqigq5qx+rmCxOLQut6g7SL9xgwTHJQq1DdtQwNNSlQHWRNbXVrnVspQNUhnPbMweiIrEzoDJfNm43rU1cbiugCxfKmUpG+iH6OjpuCsqbW6wL/NVdwK7Gf86gwWHWwsczq+RutQq1i+XfxfUl/CW2VVbUwbQcgz2CTAFPsDDfN34rvSVMS0tz2tQqUEoK2dUJ7soWWojLEbvbnK/9l26qD79gzzHRIu1jzKSYhUvFwlYpZk+mNVYMBZblCkRL42JSdSFsgEDvOt4S7REMLLtMapWaHHmz2Z0Jl+nSukp62oudTHvNfm6M766AypHoYv+z6PTNhXfGA3ZttoUmidZNddNVT/R5I5XinfF54FJ/MK4dPPCsApsp6mxJ3glyOVopVdmTig/qlnthHFjtVd5/T5www6H8cw4kAMT9ha52PyaclsVGyVaKdhvlcnS0E8gCtlGXwGWPOM4KzOQ77Rr8ejhJpSlGKRzJGOlY6clqZZs3bCeNPc5RP5iAylH9UxiUJAUYZd+2ZTbV1w/m86bCplBVsZTsg+iS3hGmAHnvMz4LfNu7zCrUKhnZcfkf2NT44UkjKZcaODsATAfdFm5C34NwzsH7Ay8UMpU+FftWlXcJJzTXOIb19oCF7SUCRBdi9QHEgI+PP+3/bMc7v+qxGfEZVLjveKL4vyjiaWkqDorb+9n8/94kP30wsPIFgzGUXHVOdhE2z7cmh2PXZ8ckFrwmBPU1FDRDGxHTIJZvTt32fMa7qHqjad4JLXi1OIb4gsjG6T/p2Kq6q74s2k4Vj2XAsPIM4zAUYYVphjFW4+ddp4zXgUdc5tMGONVU5F8DIBHx0K5fT+3wnMo7lcqbGbDZHFiRKGEYbDiQ2Rtpttqce5R8xd4G711QrtHxM0qUYeV/JkuW8ed+h6+HpNdwNwUWWJVxdHeDQ/IAYLdfUw4N3LG7l9qIKamY8XiDeEGIS6hwSPvZmSpxm40soq34b0PgqsHyc0EUfWV/Rl/XCaeJB8v3wled5xIWdBWalI2zVnIewLEvaB4OHL07jqp6uZhI7OhsOChIIUhleNFpj+paK2g8kO3qPzmglLHws0OkdDWKBm4nGxedB9H36aelxznmiyWgNKFDd3IswMvPbx4BTMyLijpyuZz43phbeBWIHShAiMw5axpGW1X8gK3cby6gjMHsEzJkdkWPVmZ3Jjeqh+Fn+qe310xmnaWyNLIzhvI6UNcfd94XXM+7iopwGZeo1rhROBlYD0gxeLxpWuo2S0Zscg3PLxMQgyHkoz1UY6WPNmjXKuehd/pX9UfD11mGq3XAZMBjlKJHUOL/gl4gLNa7n3py6ZhI1ThdmAO4B+g4aKH5X2oqCzmsZT2yjxbwd+HacySEbGV5tmU3KTehx/yn+XfJ51E2tJXatMujkJJTkP9Pjm4rrNFbqPqLGZ7Y2ghQmBS4Bug1eK0ZSMohuz/8Wk2mrwpwaxHNsxgUUKV+5lu3EUerh+hX90fJx1NGuMXQ9NPTqoJfAPvvm+45vO+LpvqYeatY5ShqGBxYDFg4mK3ZRvoteylMUV2rrv2wXOG+YwgUQGVu5kxXAveex91n7oezl1/GqCXTNNjzomJpgQjPqs5KLPE7yVqrGb2Y9oh6GCqIGEhB6LQpWiotSyW8Wo2RvvDQXWGswvS0O+VJxjc2/nd7d8v332enN0amonXRRNrTqCJi8RW/ut5c/QY70ArCudWJHiiAmE9IKqhRSMApYkoxSzV8Ve2Y3uPgTMGY0u4UEyU/phx209dhx7P3ydeUxzfWl9XLJMmDq6JrMRKfzA5h/S576srfSeMZO8iteFqIQ2h22NG5f2o5izh8U42RLucQOxGCwtREBlUQpgwmszdBx5WHred8NxNmiDWw1MTDrMJiQS9fzi55DTnMCZrwqhYZX2jAmIwoYniSaPj5gYpWC07sU52aztpwKIF6wreD5aT89dZ2nLcbl2DHi7ddlvlWY4WiNLyzm4Jn4SvP0R6R/Vf8LDsWuj5peMj56KQIl8iz+RXJqLpmy1isZh2V3t4gFTFg8qfzwSTUpbuWYHb/RzXHU1c5BtnGSeWPVJEzl8JsISfv5M6srWjsQntBKmvZp9kpKNIYwzjreTgpxNqLy2Xsex2SbtJQEUFVcoWjqSSoBYumPqa9FwS3JNcOpqSmK0VoJIIzgYJuwSN/+P647Yx8bDtv+o453FleOQYY9KkYyW/55eqlC4acgq2gjtcADNE4cmDjjbR3JVbWB3aFJt224Hbedno198VMxG/TaLJf0S5//Z7GnaJsmUuSysVaFimY+UAJO+lLyZ0aG9rCm6q8nM2gTtx/+AEqIknjXxRCVS1lyxZHppD2tlaYpkplz3UdJEnzXTJPMSigAo7lncqMuWvJivEKVQnZGY+JaOmEWd+KRor0O8JcuY2xztKP8wEakiCzPXQZxO+FicYE5l62ZpZdZgVlkmT5ZCCjTyI84SIgF571reSs7Hvz6zEKmLoeecR5u1nCShcKhesqC+1syO3FDtmP7fD6AgWTCRPtpK11Q8XNBgcmIYYc1ctlULTBlAPjLmIosSqwHK8GrgCtEiwxq3Ua0Qpo2h6Z8woValN6ydtT7BvM6v3aLtF/6ODokejC0iO+RGeFCUVwRcp11zXHNYyFGoSFw9PDCwISsSJAIa8ofi5NOkxiq7z7HZqn2m26T9pdepS7AjuRrE2dD73hHupv1ADWccpiqON71C3UuqUu9WkFiAV8tTj00ARWA6BS5QIKwRjAJm863k1dZJymi/hbbkr7WrGKoWq6WuqLTuvDTHKtNw4J/uR/33Cz0aqifYM2k+DEeATZZRL1NCUthODkkUQSg3myvGHg8R4QKs9Nvm2tkOztDDb7sqtS+xm694sLyzTLn6wIrKrtUP4kvv+/y0Cg0YnSQFMO05CUIeSPxLik2+TJ9JSUToPLYz/SgTHVMQIwPq9Q3p79zv0V/IicCouue2YLUethe5Mr5GxRjOZNjX4xbww/x6CdoVgSEYLE012TyGQihGpkf3RiNEQz9+OAwwLyY2G3gPUQMf90DrEeDn1RDNzsVZwNe8YrsDvLK+V8PNyd7RStvH5QHxofxKCKYTWh4VKI0wgTe+PB1Ah0H0QGo+ADrbMywsMSMzGX4OaQNJ+HTtPeP02d7ROcs3xvvCnMEjwonEt8iMztfVXt7e5wryk/wnB3QRKhsAJLErBTLLNuI5Mzu4Onc4hDQBLxkoByAIF2YNawNm+aTvb+YQ3sXWxdA9zE3JCch5yJbKTs6A0wLan+Eb6jLznfwRBkYP9hfdH8AmaiyzMHszrzRKNFAy1C70KdcjsRy5FC8MVgN1+s7xpek54sDbbdZm0sfPo87/ztbQFtSk2FreCuV97Hj0vfwKBSANwBSwG7whtiZ6Ku4sAS6uLfkr9Ci4JGkfMhlFEtoKKgN0+/Hz2+xp5szgLNys2GXWZNWw1ULXDNr23d7inOgC79z19fwTBAILixF9F6oc7SAnJEEmLifqJnkl6SJSH9IajRWvD2cJ5wJi/An2DvCe6uLl/eEL3x/dR9yG3NbdK+Bw44jnU+yo8V33RP0uA+8IWw5HE5AXFRu/HXofPSADINMeuBzFGRUWxRH5DNkHjAI+/RX4O/PT7v/q2+d85fLjRuN744zkbeYO6VfsLPBt9Pn4q/1cAuoGMgsTD3ESMxVHF54YMhkAGQ4YZhYXFDYR3A0lCi4GGQIG/hP6XvYF8x7wwO3569bqW+qK6l7rzuzL7kTxI/RQ97H6Kf6dAfUEFAjlClMNTA/FELQRFBLnETAR+A9MDjoM1gk0B2oEjwG6/gD8dvkv9zv1qPN+8sXxgPGs8UfyR/Ok9E72N/hO+oL8v/70ABADAwXABjkIZQk+CsAK6gq9Cj4KdAloCCQHtgUpBI0C7QBZ/9v9f/xP+1H6jfkF+bv4rvjc+EH51fmS+m/7Y/xl/Wv+bP9fAD4BAwKnAigDgwO5A8oDuQOJAz4D3wJwAvkBfwEHAZgANQDj/6P/d/9f/1z/av+H/7D/4f8TAEQAbwCQAKIAowCRAGoALwDi/4L/Fv+g/ib+rf08/dj8iPxR/Df8P/xs/L78Nf3R/Y7+Z/9VAFQBWQJdA1YEOgX/BZ8GEAdMB04HFAebBuYF9gTRA38CCQF6/9z9Pfyr+jT55PfJ9u71W/UZ9S31mfVc9nX32/iI+m/8gv6yAO8CJwVHBz0J+QpqDIINNw6ADlcOuw2tDDMLVgkjB6gE+AEo/0z8fPnO9lj0MPJp8BLvOu7q7Sfu8u5J8CTydvQv9z36if34AHIE2wcYCw0OoRDAElQUUBWpFVkVXxTBEocQwA2CCuIG+wLt/tX61PYK85bvlOwf6kvoKufI5irnUeg36s/sCPDL8/z3fPwnAd0FdQrNDsASLxb8GA8bVRzCHE4c+xrQGNsVMRLrDSoJEgTJ/nj5SfRk7/LqFufx457hMuC63z7gu+Er5Hvnlutd8Kz1XPtAAS0H8gxjElQXnRsZH60hQCPDIzEjiSHXHiwboxZdEYELOwW8/jX42/He62/muuHl3RHbV9nG2GfZN9sq3i7iJOfp7FDzK/pCAWIIUQ/YFcUb5yATJSgoCiqoKvspBCjQJHUgFBvTFOENdAbF/g73jO966BHig9z/16nUn9Ly0azSyNQ72OvctuJy6evw6fguAXsJjxEqGQ8gCCbkKnsurjBqMaYwZS61KrIlfh9KGEsQvQfk/gP2X+085dvdd9dE0mzOD8xEyxLMds5h0rfXUN775X7umfcEAXgKqxNUHC8k/SqIMKE0JzcEOC03pzSCMNwq3yO/G7oSFAkZ/xT1VOsm4tLZmtK5zF7IrsXAxJ/FRsijzJfS9tmI4g3sPPbFAFkLpBVWHyIowi/6NZU6cD1vPoo9xDowNvAvMSgvHywVdwpi/0H0bek53/bV7s1ix4XCgL9uvlm/PMIFx5DNrNUd35rp1PRyAB0MeRctIuUrUzQ1O1NAgkOnRLhDuEC8O+k0cSyVIp8X5Au//4vzqud43E3SeclDwuW8i7lRuEW5YLyNwabId9G82yjnYvMMAMUMKRnYJHUvrTg2QNRFWUmnSrFJfUYgQcI5mzDvJREaWg0tAPLyDebk2dfOPMVgvYO307NwsmiztLY/vN7DWs1p2Ljk6fGU/1ANsxpUJ9AyzDz5RBZL8E5oUHBPDUxXRnc+qjQ6KX0c1g6vAHXyl+SA15fLO8G+uGOyXa7QrMetQLEgtz2/Wcko1U/iavAK/74NFhygKfM1rUB6SRNQQ1TnVfFUZFFcSwRDmzhxLOIeVxBBARXyR+NM1ZHIer1ftImtL6l0p2ioB6w2sse6ecX80e/f5+5w/hEOUh28K904T0S2TchUTVkfWy1aflYrUGNHaTyRLz0h2xHjAdDxHuJJ08TF+rlHsPmoSqRhok+jDqeErYC2vsHozprdY+3H/UgOZx6lLYw7rUepUTJZCl4LYCJfVVu/VJFLEUCXMosjXxOSAqbxHeF50TTDvrZ5rLektZ+dnYCeWqIPqWyyKr7wy1Tb3+sS/WUOVR9cL/09xkpRVUxddmKnZMpj5V8TWYlPj0OANcgl4RRNA5bxQ+Dcz+HAyLP4qMagc5sqmQCa753bpJCuw7oYyR/ZX+pR/GgOGyDfMDBAmE2rWBRhjmbvaCFoKmQlXUlT30ZIOPQnYBYUBKDxkN9zzs6+G7HGpSidhpcNldOV0ZntoO+qi7dhxv/W5OiF+1IOuyAuMiRCIVC1W4ZkT2rgbCRsH2jvYMtW/knsOgkq1xfjBMHxBN8+zfq8t67louGZ85NJkfuRBJZHnY2nhrTQw/XUcOey+iUONCFJM9hDX1JtXqFntW12cM9vw2tvZAxa6ExqPQcsRxm6Bfrxnt49zGa7nqxXoPOWu5DijX6OjJLumW2kt7FowQTTBebY+eENhyExNEtFU1TQYGJqvXCvcx9zEG+gZwldmk+9P+otqxqXBknyXd5vyxO60KoenmCU4o3Zil2La4/mlpOhI68rvzDRp+T5+IgNtiHkNH5G+VXeYsdsZ3OHdhB2BHKAar5fEVLjQa8vAxx3B6zyQd7WygK5UKk7nCmSaYsxiJuIpYwwlAOfyqwcvXrPV+MY+BsNwCFkNW5HU1eWZM9urnX9eKF4m3QLbSliSlTZQ1QxSx1ZCCLzSd5wyjK4HaivmlCQU4nuhTyGPIrQkb6csao/u+bNF+I295wMpyGxNR5IYFj3ZXhwk3cOe8561XY/b0dkQ1adRdcygh47Carzct48yqK3N6d6mdeOoIcPhEGEM4jIj8ea2qiVuXbM6uBU9g0MbCHMNY5IH1n/ZsJxE3m5fJd8rXgZcRZm+FcsRzQ0pB8bCkH0vt45ylO3nqadmL2NU4aYgquCi4YcjiGZSKchuCvL0t929W4LESG2Nb1IkVmwZ6xyLnr8ffl9I3qYcpJnZ1mESGs1sSD3Cub0KN9nykO3U6YZmASNa4WJgX2BR4XLjM+X/KXmtgnK0d6d9MIKlyBwNa1ItlkJaDVz43rXfvN+NXu6c7toj1qiSXg2piHNC5j1sd/EynO3U6bsl6uM6YTjgLiAaITZi9CW+aTltRHJ6d3L8wsK/x/8NF9IkFkKaF1zMXtJf4R/4Xt8dI9pbVuFSlo3gSKbDFT2V+BPy9+3oKYWmLKMzoSmgFuA74NHiyiWQKQgtUbIHN0B80oJTB9bNNRHHlm1ZyZzGXtRf6t/J3zfdAtqAFwrSw84QCNgDRn3F+EGzIi4NqeWmBmNGYXTgGmA3YMVi9iV06OZtKjHa9xC8oIIfx6PMw1HY1gKZ5BynHrvfml/BnzgdC9qR1yTS5U44SMZDuX38OHnzGy5Fqhsmd+NyYVpgeCAMYREi+CVs6NRtDrH2tuQ8bQHmh2ZMg1GYFcKZptxuXklfr1+fnuAdPtpQFy6S+s4YyTEDrX44eLxzYi6PKmVmgKP3oZngsCB7YTUi0GW4aNKtP3GaNvs8OIGnxx8MdZEFla4ZEpwcnjzfKl9j3q/c21p6luhSw45xCRgD4j55uMhz9u7qaoQnIGQVojNgwmDD4bHjPyWXqSFtPPGGNtZ8A4GkBs5MGhDiFQUY51uyXZZeyx8OnmccoZoRltFS/84AiXqD1z6/uR10GK9WKzbnVuSMIqZhbqEl4cajhCYKqUCtRzH7NrX7zoFcBrTLsdBuFIiYZdsv3RbeUd6f3cYcUVnU1qnSrs4HCViEDD7J+bs0Ry/Sa70n4yUaozKh9GGhInOj32ZRabCtXrH5Npp72gEPxlNLfU/p1DjXjtqVnL4dv53YHU0b6tlEFnFSUM4EiXGEAD8XueC0wbBeLBYohOXAY9dikyJ1YvikUObr6fFtg3IAtsQ75kDARinK/Q9Wk5bXIpnkW81dFF13nLxbLljflehSJU34CQUEcz8o+g21R3D4rIEpe6Z85FRjSuMh45UlGGdaakLuNbIR9vN7tECtxbmKcg700uLWYdkc2wScUJy+29Qam9hnlU5R7E2iCRLEZH98ekF117FhrX2pxidPZWikGmPmpEil9afcKuUudXJs9uj7g8CZRULKHI5FEl4VjZh/miTbdVuumxUZ9BecFOORZc1CCRpEU7+SOvr2MfHX7grq4+g3JhNlASTCpVLmqCixK1huwvLSNyR7lcBCxQZJvY2IUYjU5pdNmW8aQxrHGn/Y9xb9VChQ0Y0XyNuEQH/pOzo2lXKa7uerk+kzZxQmPuW1JjNnb2lZLBvvXbMBd2a7qoArBITJFg0/UKST7dZHWGPZepmJWVSYJZYME5yQcAyjSJYEaj/BO733ATNpr5MslWoC6GnnEib9pykoSupTrO+vxjO7N2+7goASxH7IZkxqz/HS49VuVwQYXJi2WBRXABVIUsDPwMxkiEmEUEAZu8X39LPDcIztp2slKVNoeifbaHOpeisgbZNwu/P+9797nj/6Q/UH70uMDzHRyhRDVhDXKpdOVz+Vx1Ry0dUPBIvbSDYEMwAx/BE4bvSnMVMuiKxYqpAptikNaZIqvGw+rkaxfrRNeBa7/T+iQ6hHcgrjziVQ4ZMHlMsV5NYS1deU+9MMERoOe0sHx9tEEcBJvJ847zVT8mWvuG1cq95qxOqSasOr0S1t70kyDnUl+HU74L+LQ1lG7woyzQ1P6xH703RUTRTEVJzTnlIUkBBNpQqqR3kD7EBgPO85dHYI80Kw9S6vrT2sJavprAdtNy5tcFpy6vWIuNs8CH+1gsiGZ0l6DCsOqBChkg0TJBNkkxCSb9DNDzfMgooCRw9DwgC0/QB6PjbE9Gmx/i/Q7qwtlq1R7Zvube+8sXnzk7Z1eQi8dT9hwraFm8i6yz/NWU96EJdRq1H0EbPQ8Q+2TdGL08lQhp4DkwCHfZK6i3fHdVlzEjF+r+kvFu7KbwCv9DDasqb0iDcsOb28Zr9QQmSFDQf1ygwMQI4GD1PQI5B0UAePo05RTN4K2UiVBiVDXsCXveT7G3iOtlB0b7K4MXLwpXBRMLRxCTJGs+C1iHfsejo8nb9BghKEvAbsCRGLHoyHjcPOjs7mTozOB00ei54J08fQBaTDJQCkvjZ7rTlad041lbQ7sshyQLIlsjWyq/O/tOa2k3i2Or582f92QYGEKcYeyBFJ9Ms/TCkM7Y0LzQUMnkufSlIIw4cBxR0C5gCufka8f/opOFD2wrWINKgz5zOGM8O0WvUFNng3qLlI+0n9W/9uQXIDVsVOhwxIhMnvCoTLQguly3FK6UoUSTtHqQYqxE3CoUC0fpU80vs6eVf4Nbbb9hD1l7VxdVy11XaVd5R4x/pkO9y9o39qQSSCxAS8xcPHT0hXyRhJjQn1iZNJaYi+h5oGhUVLQ/eCFsC2PuF9ZTvMuqG5bXh194D3ULcl9z+3Wjgv+Po58DsHvLZ98L9qwNnCckOqRPjF1cb7R2UH0Eg8x+vHoEcfhm+FWMRjwxpBxoCzfyq99jye+616qDnUuXb40LjieOs5J7mTumj7IPwzPRc+Q/+vwJJB4kLYQ+yEmcVaxeyGDUZ9BjyFzsW3xPzEJAN0gnYBcIBsP3B+RP2wvLm75Tt2+vF6ljqlep36/Ps/O5+8WX0l/f6+nP+5gE6BVQIHQuBDXEP3hDBERYS3REbEdkPIw4KDKAJ+gYtBFIBf/7I+0P5AvcW9YvzavK78X/xtfFY8mHzxPR09mL4fPqx/O/+IgE7AysF4gZVCHsJTQrHCuoKtgowCmAJTwgHB5YFBwRqAssAOP+9/WT8N/s++n/5/Pi3+LD44/hL+eP5o/qD+3j8e/2B/oH/cwBQARICswIxA4kDvAPKA7YDgwM3A9YCZwLvAXUB/QCPAC0A3f+e/3T/Xv9c/2z/iv+0/+X/FwBIAHMAkgCjAKMAjwBmACkA2v96/wz/lv4b/qP9M/3Q/IL8Tfw2/EH8cfzG/EH94P2f/nr/agBpAW8CcwNqBEsFDgaqBhcHTgdMBwwHjgbUBd8EtwNhAugAV/+5/Rv8i/oW+cv3tPbf9VP1GPUz9ab1cfaQ9/34rvqa/LD+4gAfA1UFcgdlCRoLhQyVDUEOgQ5ODqkNkgwPCyoJ8AZwBL0B6/4P/EH5l/Yn9AbySPD77i7u6e0y7grvbPBR8qz0bveC+tH9QgG8BCMIWgtIDtMQ5xJvFF4VqRVLFUMUlxJREIANOAqRBqYClv5/+oH2vfJR71rs8eks6BvnyeY753PoaOoO7VPwIPRZ+N78jAFABtUKJQ8PE3EWLxkyG2ccwRw7HNUamRiUFdsRig3BCKIDWP4I+d3zAO+Z6szmt+N34R7gvN9U4ObhaeTM5/bryfAi9tj7vwGqB2oN0hK3F+8bWh/YIVUjwiMYI1ohkh7UGjkW5RD+CrEEMf6s91fxZOsD5l/hnt3h2j/ZyNiC2Wvbdt6P4pjnbO3f88D62wH4COEPXRY7HEkhYCVcKCQqpirdKcsnfiQMIJYaRRRHDdIFIP5r9vDu6ueR4RjcrNdx1IPS9NHL0gXVk9hc3T3jCuqR8Zj54AEqCjYSxBmYIHsmPiu4Ls0waDGEMCQuVyo4Je4epheZDwIHJv5H9avsl+RJ3fzW5NErzu/LRcs1zLvOxtI42OreqeY872D4zwFAC2oUBR3LJIEr7jDnNEo3AjgHN140FzBTKjwjBhvxEUEIQv5A9Inqa+Es2Q/STMwUyInFwcTGxZLIE80n06LaS+Ph7Bv3qAE5DHoWHCDRKFUwbDbkOpc9bz5hPXQ6uzVZL30nYh5NFI0JdP5W84zoad4+1VPN6cYywla/br6Dv5DCgMcuzmnW89+E6sn1bAEUDWUYByOmLPY0tDuqQK5DqESMQ2FAPDtENKwrtSGrFuQKuv6J8rPmlNuC0c7IvsGJvFy5ULhyubq8EsJSyUXSptwm6G30HAHSDSsaxiVIMF85wkA0RotJqUqCSR9GlkAQOcUv/SQIGUQME//a8QHl7Nj7zYLEz7wet5+zbrKYsxW3zryXxDfOZdnL5QnzuQByDskbVii1M409kUV/SydPbFA/T6lLw0W4PcUzNShhG6wNgP9J8XbjddaqynPAIbj2sSSuy6z5raaxuLcCwEbKNdZ0457xRAD1DkAdtSrpNn1BHUqFUH9U7FW+VPxQwEo5Qqc3XCu0HRkP/v/U8BPiLtSTx6O8trMTrfCobqecqHKs1rKXu3TGGdMm4S7wvv9cD5Ae4izjOSxFZE5CVY9ZJlv5WRBWh0+NRmg7bC79H4oQiwB88NjgGtK2xBW5k697qAakWaKEo36nLK5at8XCFNDi3rzuKP+mD7cf3S6hPJhIY1K0WVFeFGDtXuNaE1SxSgQ/ZDE7Iv0RKAFA8MXfOdAXwsy1uqsxpGyfk522ns6ivalQsz6/Ks2s3ErthP7UD7UgozAhP75LFVbWXcNismSUY29fYlihTnZCPzRqJG8T0wEf8Nrejc62v8qyL6g3oCSbHpk2mmaekKV9r+G7XsqF2tnr0/3oD4whNjJjQZxOelmmYeBm/WjrZ7FjblxYUrxF+zaHJt4UigIY8BjeFc2VvRCw8qSSnDKX/pQJlkuap6Hjq7O4tMdy2GzqF/3hDzoikzNkQzBRjVwgZaVq8Wzua6RnM2DSVdFIlDmQKEkWSwMs8H3d0su0u6GtCKJEmZqTN5ExkoCWBp6IqLe1LcV01gXpUfzCD8EiuzQkRXpTTl9CaBBuinCab0ZrrmMNWbNLBzyCKqwXFQRX8ArdxMoVun6rcZ9Oll2QzY2zjgqTsZpvpfCyzsKO1Kbng/uKDyEjrzWiRndVumEKax5xxXPqcpFu3GYFXF5OUj5bLAUZ5gSa8L3c7Mm4uKepMJ20k3+NwYqRi+qPq5eaomKwmcDD0lLmsPo8D1sjbTbeRydX0GN2bcxzoXbddYRxuWm2Xs9QcEAXLlMavAXy8JfcSMmctx6oRZt4kQGLFojOiCSN+JQNoA+ukr4W0Qvl2PnaDm8j9jbYSIpYj2WEbxh2GXlveBx0QmwdYQNTYEK1L5MblQZf8ZXc2cjDtuOmspmZj+eI0IVthruKmZLLnfururyIz9Pj/vhjDl4jTDeQSZ1Z9mYycQF4LnueelZ2dW45Y/hUH0QyMcMccAff8bfcncgttvald5gajjCH74NwhLKIk5DXmyeqFbsdzqziI/jaDSsjbjcGSmNaBWiBcoV523xofC94T3AGZapWqkWLMuAdSghw8vzclMjXtVillZf8jN+FdILZggmH5o4ympeopLnWzJnhSvdBDdUiXjc7Stpaumhvc6R6In7MfaZ5znGCZhhYAEe/M+keIQkR82LdvcjDtQelDJc/jPOEYoGpgcSFlY3fmEynari3y5vgdPaZDGAiHTcwSgRbF2n8c1x7/37Ifrl68HKrZz9ZHUjKNNwf9Qm/8+fdFsnutQSl25bii26EuoDhgOOEoozgl0imarfAyrTfpPXlC8shrDblSeFaHGkodK57c39cf2d7tXN/aB5aAEmsNbYgwQp69IrenslYtk2lA5fni1CEeoCCgGiEDYw3l46lpLb0yefe2/QlCxkhDDZcSXJayWjzc5h7fn+Gf7B7GXT9aLNaqEliNnYhhgs/9UrfVMoAt+KlgZdLjJmEpICNgFKE2Ivklh+lG7ZUyTXeG/RcCkwgQDWWSLhZIGhecx17H39Gf5J7HnQlafxaEkrqNhkiQQwL9iTgNsvjt8GmVZgQjUeFOIEBgaSEBIzplvyk0LXjyKDdZ/OMCWUfSTSWR7RYIWdrcjx6V36efg17wXP0aPlaPUpDN54i7wzf9hfhQcwAueinfpkyjlqGNILegVyFkYxGlyalxbWiyCvdv/K2CGceKjNcRmlXzmUacfd4J32MfSF6BHNraKhaKUpsNwQjkA229yDidc1Wulap+pqxj9GHmIMlg3uGf437l52l+rWSyNXcJvLdB1Qd4zHrRNlVKWRtb053kHsRfNB45nGJZwpa00ljN0kjIQ6Q+D3jzs7huwirx5yLkaqJYoXShP+Hzo4KmWOmcLa0yKLcnfECBy0ceDBGQwVUNWJnbUV1k3kwehl3Z3BOZh1ZPUknN2sjoQ5r+W3kS9Cgvf2s456+k+SLkYfnhuiJfJBxmnanKLcKyZHcJvEoBvUa6i5uQfFR818Ia9xyMnfqd/90iG67ZOJXZEi4NmkjDg9E+q3l6dGQvzGvSqFHlnyOI4pfiTSMipIwnNmoIriTyaXcxPBQBa4ZPS1nP55PZl1VaBZwb3Q/dYFyTGzQYllWSEcUNkMjZg8a+/vmpdOuwaKx+6MkmW+RFo07jOKO9pRGnomqXrlRyt/cdvB9BFoYcisyPRBNkVpPZfZsTXEzcqNvsmmPYIJU60U8NfYiqQ/r+1ToftX5w02086ZSnLqUZpB2j/CRvpeyoIas3LpFyz/dPvCvA/sWjCnTOklKeFf6YYBpz23JbmZsvGb4XV9STEQuNIMi1A+1/LfpcNdsxi+3LqrNn1yYEpQPk1uV4Jpzo9CunLxtzMbdH/DpApQVjidMOE1HHVRZXrVl92kCa85obmMOW/BPa0LrMugh6A92/SLredkFyUS6qK2So0+cFZgDlyCZWp6GpmSxnb7KzXTeGPAtAicUeyWiNR9Eg1BwWpphymXiZtxkyV/RVzZNSkBzMSYh4Q8t/pHsltvBy4q9X7Gep5GgbJxOmz2dKqLrqUK038Bdz0vfLPB8AbYSVCPWMsJAsExDVjJdSmFtYpRgz1tGVDRK6T3HLzsgwA/Y/gPuxd2czvzAT7Xtqx2lE6Hsn6+hTKadrWi3X8Mj0UngWvDYAEQRHiHsLzs9pkjUUYJYfFynXfpbhVdtUOtGSjvmLSgfhA91/3bvA+CU0ZjEc7l5sPCpB6bapHGmvqqcsdS6HcYe03DhpPBCANIP2h7nLIw5aUQqTY5TZFeSWBBX7VJKTF1DbTjSK+0dLA8CAOfwTOKk1FnIx71AtQSvQqsUqoGre6/jtYO+F8lL1cDiC/G8/2IOjBzLKbo1/j9ISFpOB1I1U9xRCk7fR40/VjWLKYoctw6AAFTyn+TL1zvMSMI9ule0wbCUr9mwgbRvunPCS8yq1zfkjvFH//cMNRqbJskxaTsyQ+tIaEySTWFM4kgxQ347BTIUJ/8aJg7tALzz+OYD2zvQ8MZqv+G5frZXtXW2zLk+v6HGuM862tXlLvLk/pML2hdaI7strjbuPUZDjkawR6RGd0NCPjI3fi5sJE0Zdw1GARz1VelL3lTUvMvExJ+/dLxYu1K8Vr9MxArLWtP53Jvn7PKU/jcKfBUNIJcp0jGAOHA9fUCSQapAzj0XOa0ywiqXIXQXqgyMAXP2s+ue4YPYp9BFyozFn8KRwWnCHMWUyavPL9fk34bpx/NY/uUIHxO1HF4l2SztMm43Ojo/O3c67De0M/Et1CaVHncVwAu+Ab/3D+765MTcrdXpz6LL+cj+x7bIGcsSz3/UNdv74pbrwPQx/qAHxBBXGRYhyCc6LUUxyzO7NBE01TEcLgQptyJpG1UTuQraAf74Z/Ba6BLhyNqp1dzRfM+YzjPPSNHC1IXZaN885srt1vUg/mgGbw72FcMcpCJtJ/sqNS0MLn0tjytUKOgjbx4WGBARlQngAS76ufK762rl9N+C2zXYI9Za1dzVpNeg2rfexeOj6R/wCPcl/kAFIQyUEmgYcR2KIZUkfiY4J8EmHyViIqEe/RmcFKkOVAjPAU/7AvUb78fpLOVu4abe6Nw+3KvcKN6m4BHkSegu7ZbyVvhB/igE3gk3DwoUNBiXGxoerB9EIOIfiR5JHDQZZxUAESMM+AaoAV78P/d28iXubOpn5yvlxeM/45njzuTR5o/p8ezb8Cv1wPl0/iIDpwfgC60P8hKYFY0XxRg3GeUY1BcPFqYTrxBDDX8JgQVqAVr9b/nI9YDyr+9p7b3rtepX6qLqkesZ7S3vuPGm9N33RPu+/i8CfgWSCFQLrw2UD/YQzhEXEtIRBRG4D/oN2QtpCb8G8QMVAUP+kPsQ+db28fRu81fysvF/8b/xa/J78+b0m/aO+Kv64fwe/1ABZgNSBQMHcAiPCVoKzQroCq0KIQpMCTUI6gZ1BeUDRwKpABj/n/1J/CH7LPpy+fT4tPiy+On4Vvny+bX6lvuN/JH9l/6W/4YAYQEgAr8COgOPA78DygOzA34DMAPNAl0C5QFqAfQAhgAmANf/mv9x/13/Xf9u/43/uP/p/xsATAB2AJQApACiAIwAYgAjANP/cf8D/4v+Ef6Z/Sr9yfx9/Er8NvxE/Hf8z/xN/e79sP6N/38AfwGFAogDfQRdBR0GtQYdB1AHSQcEB4EGwgXJBJwDQwLIADX/lv35+2r6+fix96D20PVK9Rb1OfWz9YX2q/ce+dX6xfze/hEBTwOEBZ4HjAk8C58MqA1LDoEORQ6WDXUM6gr+CL0GOASBAa7+0/sG+WD29vPd8Sfw5e4j7urtP+4i74/wf/Lj9Kz3xvoa/o0BBgVpCJsLgg4EEQ0TiRRrFagVOxUlFGwSGhA+De0JPwZQAj7+KPou9nDyDe8h7MXpDugM58vmTueV6JnqTu2f8Hf0t/hB/fEBpAY0C30PXROyFmIZVBt3HL4cJRyuGmAYSxWFESgNVggzA+b9l/hx853uQuqC5n/jUeEN4L/fbOAT4qnkHehX7DfxmfZV/D4CJwjiDUATGBhBHJgfAiJpI74j/SIpIUseehrOFWwQewooBKX9IvfT8OvqmOUG4Vrds9oq2czYn9mh28Pe8eIN6PDtbvRX+3MCjglwEOEWrxyrIasljig7KqIqvSmRJyokoR8XGrUTrAwvBXv9yfVV7lznE+Gv21vXO9Rp0vjR7dJE1e3Yz93G46XqOPJH+pEC2QrdEl4aICHsJpUr8i7oMGQxYDDgLfYpvSRcHgEX5g5HBmj9jPT56/LjuNyD1ofR7M3Ry0rLXMwDzy3Tu9iF31nn+u8n+ZkCBwwoFbMdZiUCLFExKjVqN/433zYSNKovyCmXIkwaJxFuB2z9bfPA6bHgiNiG0ePLzcdnxcXE8cXiyIbNutNQ2xDktu3694oCGA1PF98gfinmMNw2Lzu8PWs+NT0gOkI1vy7GJpMdbROiCIX9a/Ks55vdiNS7zHPG4sEvv3K+sb/owv7H0M4p18zgbuu/9mYCCg5QGeAjZS2WNTA8/kDXQ6VEXEMGQLg6mzPjKtMgthXjCbT9iPG+5bHautAnyDzBMbwwuVO4o7kYvZvCAcoV05HdJul59SwC3g4rG7ImGTEOOklBkUa5SaZKUEm9RQhAWjjtLggk/xctC/j9w/D34/bXIc3Mw0G8vrZus3CyzLN6t2C9VMUYz2Pa3uYq9N8BlA/eHFUplzRLPiRG40taT2pQCk9CSyxF9jzdMi8nRBqADE/+HPBX4mzVv8muv4e3jbHvrcysL64RslS4y8A1y0TXm+TT8n4BLBBpHscr3DdJQrxK8lC3VO1Vh1SOUB9KakGxNkQqhBzaDbn+k+/h4BPTmMbQuxGzoqy1qG2n1KjirHqza7xxxzjUX+J38QwBphDLHwYu5joGRg9PuFXLWShbwFmeVd5OtEVkOkUtvB45DzT/KO+T3+7QrMM1uOOuAqjHo1aivaPzp9iuObjQw0PRLOAX8IgAAxEFIREwsz1/SRhTMlqTXhhgs15sWmNTzUnzPS4w6SCaEL//2u5u3v3O/cDftACrr6Mnn46d8J5Ho3GqObRVwGfOBd617vb/QhEUIugxQkCyTNVWXF4KY7hkWWP1XqtXtE1aQfwyCSP8EVgAqO5z3UDNjr7QsWqnrp/bmhaZcZrjnkmmbrADvajL7dtU7Vb/ZhH7IoozkUKcT0NaM2IsZwVpsGczY7FbYlGVRKs1GCVcE/8Aku6h3LrLX7wLrySkAZzklvSURJbKmmai3azfuQrJ59n166n+bxG4I/U0n0Q8UmBdtWX2avxss2skZ3Ff1VShRzk4FSe4FLIBl+7422nKcrqQrDChrJhGkyuRbZICl8qeiKnsto7G9deb6vH9XRFNJCs2bEaQVCpg3mhmbpdwXm/DauhiClh6SqI6+ygPFm8Cte5420/Jx7hiqpGesJUFkL6N7o6Nk3mbdaYttDjEGtZJ6S/9MxG5JCo39UeXVp9irGt5cdVzr3INbhJm/FoeTeM8yipdFzQD7O4g22vIX7eCqEecD5Mija+Ky4tvkHaYpaOmsQzCWdT/52f88BD+JPM3O0lRWL1kHm4rdLR2o3X/cO1oqF2IT/o+fiyiGAAEOu/u2r3HO7bwplWazJCgigKICImqjcWVHaFZrwvAs9LB5pj7lxAcJYY4Pkq7WYNmMnB8di95NniWc3RrDGC3UeRAFC7ZGdAEnu/k2kXHWbWtpbuY6I6BiLmFpYZBi2mT3p5IrTm+LdGQ5cb6KRAUJeQ4/krWWvBn5nFpeEZ7Z3rQdaVtJWKoU55Ciy8CG6QFFvD+2gHHu7S6pHqXZI3GhtSDp4Q3iWOR7Jx4q5i8x89w5PL5pw/oJA05e0uiWwRpOXPxefd8M3yqd39v8GNXVSVE3zAaHHgGoPA82/LGX7QWpJOWQYxxhVeCDYOOh7aPSJvqqSq7hM5h4x75FA+YJAM5tksfXL9pLHQTe0B+mX0ief5wa2XEVnhFDzIfHUsHPPGd2xXHRrTAowWWgIuChEOB24FHhmWO9pmgqPO5Z81m4kz4cA4mJMY4r0tNXCBqvHTPeyB/l343eiFylGbqV5RGGTMQHhsI5/Ef3GvHbbS5o9GVIIv6g5eAEYFkhXCN9pidp/O4ccyB4X73vg2VI1g4Z0stXChq63QjfJd/LX/neudyamfKWHhH+jPpHucIoPLA3PHH1bQApPWVIYvZg1WAr4DnhNqMS5jipiy4pcu04Lb2/wzkIro34ErAW9hpuXQRfKV/Wn8ye05z6mdgWSFIsTSpH6wJZfN/3abIe7WTpHGWhIsfhHyAt4DPhKOM9pdwpqG3BMsB4PX1NQwXIu82G0oHWzBpJ3SYe0h/HX8Xe1VzFGitWY1IPDVPIGgKM/Ra3ojJXrZxpUWXRozLhA2BKYEdhcuM95dKplO3kMpp3z71YwsvIfc1GkkEWjFoNXO5eoN+d36Vevxy52etWb1ImTXYIBoLCfVP35XKfLeZpm6YaI3dhQeCBILShVSNUJhvpkO3Ssrv3pL0igouINU030e4WN9m5HF1eVV9aH2teUNyY2diWa1IxzVCIb8L5fVc4MzL1LgIqOqZ545Th2mDR4Pthj6OAZnhpnK3NMqU3vPzrAkWH4oza0YmVzllOHDNd7978XtgeClxhmbJWF5IxDWOIVYMxfZ+4SnNY7q9qbmbwZAriTKF8oRtiIiPCZqgp+K3T8pZ3mTzygjpHRoywURPVUJjMG7EdcR5EnqtdrBvUWXjV85HkDW3Id4Mp/e14qzOJ7y2q9ed9ZJli1+HA4dSijGRaputqJK4nMpA3uXy6AepHIYw5EI2U/1g0Gtbc2V3z3eXdNdtxWOwVv5GKjW/IVQNifj941HQHb7vrUKggJX8jfCJeYmZjDmTIp0HqoK5HMtK3njyBwdZG9Au1UDdUG1eGmmVcKN0J3UecqBr4mEwVe1FkTSjIbcNaflV5RbSQ8BmsPeiYJjwkOGMUYxDj56VMJ+tq7W6z8t53h/yKAb7GfwsmD5JTpNbEmZ0bYJxHnJFbw1pqV9iU5pEwzNiIQYORvq55vnTlsIYs/SlkZs9lDGQio9Lkl+Yk6GhrSi8t8zM3tvxTgWQGAsrMDx6S3NYuWL8aQVut24NbB9mG11JUQZDwjL8ID8OHfsp6PfVFMUCtjWpEZ/hl9yTIJOxlXqbS6Tfr9y90s1F367xewQcFwEpnzl1SBFVE18vZi1q82p6aNhiOlrlTjJBjTFwIGAO7Pug6QzYuMchubes26LWm9+XEZdymeyeVadostC/Ic/l35jxrwOhFeEm6DY9RXBRJVsRYgBm1maNZDpfCFc4TB8/JDC9H2oOs/wf6zjagMpxvHew7aYboDacWZuKnbSir6o6tQPCpNCr4Jvx7gIhFKwkEDTWQZRN8VamXYBhY2JLYElbh1NCScw8hy7jHloObv2h7HXcac3vv2+0QaurpN6g9Z/2oc6mV65TuHTEW9KZ4bjxOQKdEmYiGDFCPoBJfFLyWLFcn122WwdXuU8GRjw6tyziHTAOHf4l7sPeb9CXw5241a+CqdOl4aSzpjirSrKxuyPHRNSu4u/xkAEZEREgBC6HOjlFyk35U5hXjFjRVndSoUuGQm83tCq5HOsNv/6p7x7hj9Nlx/y8pLScrg+rGaq9q+2vhrZTvw3KYNbq40Ly9gCWD7Ed2CqnNsNA4EjATjlSMFOjUZ1NQkfFPmk0gChpG4sNUf8q8YPjxtZWy4nBqbnzs5CwmK8Qseq0B7s0wzDNrNhN5bDybAAXDkgblyemMiI8wUNMSZhMkE0tTH1IoELEOikxHCbzGQ4N0/+m8u/lEdplzz7G4L6DuU+2WbWntiy6yr9Tx4vQKNvX5jvz9P+eDNgYRCSJLlo3cz6gQ7tGr0d1RhtDvT2HNrMtiCNWGHUMQQAc9GHoa92P0xfLRMRIv0i8Wbt+vK2/y8StyxvU092H6OPzjv8sC2YW4yBUKnAy+zjEPadAkkGAQHs9njgSMgoqxyCTFr8LngCJ9dTq0eDP1xDQ0Mk8xXbCkcGQwmvFBso+0N7XquBc6qf0O//ECfMTeB0KJmktXTO6N2E6QDtSOqI3RzNmLS4m2h2sFOwK5wDs9kbtQeQh3CTVfs9Zy9PI/MfZyF/LeM8D1dHbrONV7Ij1/P5nCIIRBRqwIUkony2KMe4zvDTxM5QxvC2JKCUixBqhEv0JHAFD+LXvtueC4E7aS9Wb0VrPls5Sz4XRHNX42fHf1uZx7oX20v4XBxUPjhZKHRUjxSc4K1QtDi5hLVcrASh9I+8dhhd0EPIIOwGM+R/yLevs5IvfMNv81wXWWNX21djX7doZ3zvkKOqv8J73vv7VBbAMFxPcGNId1iHJJJkmOiepJu8kGyJGHpEZIhQlDssHRAHF+n/0o+5d6dTkKeF33s/cPdzA3FPe5+Bj5Kzone0O89P4wP6kBFQKow9qFIUY1RtFHsIfRiDOH2IeDxzqGA4VnBC3C4gGNwHu+9b2FfLP7SXqMOcF5bLjPuOr4/HkBOfR6UDtM/GL9SP62f6EAwQINQz4DzETyRWvF9YYOBnWGLUX4RVsE2oQ9gwsCSsFEwEF/R75fvVA8nnvP+2h66fqV+qw6qzrQO1f7/Px6PQl+I77CP93AsMF0QiKC9wNtw8OEdkRFhLGEe4Qlw/QDagLMgmEBrQD2AAI/lj73fiq9s30U/NF8qnxgPHJ8X7ylvMH9cP2ufjZ+hH9Tv9+AZEDeAUlB4sIpAlnCtMK5wqlChIKNwkcCMwGVQXDAyQChgD3/oH9L/wK+xr6Zfns+LL4tPjw+GH5AfrG+qr7o/yn/az+q/+ZAHIBLwLLAkIDlAPBA8kDrwN4AygDxAJTAtoBYAHqAH4AHgDR/5b/b/9d/17/cP+R/7z/7f8fAFAAeQCWAKQAoQCJAF0AHQDL/2j/+f6B/gf+kP0h/cL8d/xH/Db8R/x9/Nj8Wf39/cL+of+UAJUBmwKdA5EEbgUrBr8GJAdSB0UH+wZzBq8FsQSBAyUCpwAT/3P91/tK+tz4mPeM9sL1Q/UW9UD1wvWb9sf3QPn9+vD8DP9BAX4DsgXJB7IJXAu5DLkNVA6ADjsOgg1YDMUK0QiKBgAERgFx/pb7zPgq9sbztPEI8NDuGe7s7UzuO++08K3yG/Xs9wv7Y/7XAU8FsAjdC7wONREyE6IUdhWlFSoVBxRAEuIP+wyiCe0F+gHn/dL52/Uk8sru6eua6fLnAOfO5mLnuejN6o/t7fDO9Bb5pP1VAgcHkwvUD6kT8haTGXQbhRy6HA4chBolGAEVLRHFDOsHwgJ0/Sf4B/M77uvpO+ZI4y3h/d/D34bgQeLr5HDoueyl8RH30vy8AqMIWA6tE3gYkBzVHyoieiO5I+Ei9SADHh4aYhXyD/cJngMZ/Zn2UfBz6i7lruAX3YfaFtnS2L/Z2dsT31bjg+h17v707fsLAyQK/hBkFyIdCiL0Jb4oUCqcKpspVCfUIzQflxklEw8MjATW/Cb1u+3O5pfgSNsM1wfUUtL/0RLThtVK2UTeUORA6+Dy9vpDA4gLgxP2GqYhXCfqKyovATFdMTkwmi2TKUAkxx1bFjIOiwWq/NHzR+tP4yncDNYs0bDNtstRy4XMTc+W00DZI+AK6Lrw7/ljA84M5RVhHv4lgCyyMWo1hzf3N7M2wzM7Lzsp8CGRGVwQmgaV/Jry+Oj53+fX/9B8y4nHSMXNxB7GNcn7zU/UANzW5Izu2fhtA/YNIhiiISkqdDFJN3c73T1kPgU9yTnHNCIuDCbDHIwStweX/ILxzebP3NTTJcwAxpbBDL95vuO/QsN/yHPP69em4VrstvdfA/8OORq2JCIuMzapPE5B/UOeRClDpz8yOvAyGSrvH8AU4Qiv/IjwyuTR2fTPgse9wN27CblauNi5er0nw7PK6NN/3ibqhvY9A+oPKRycJ+gxujrOQelG4kmgShlJWEV3P6E3ES4RI/MWFgrd/K3v7eID10rMGMO3u2G2QrN2sgS04rf3vRPG+89j2/PnTPUFA7UQ8R1SKnY1Bj+0RkRMiE9lUNFO1kqRRDA88jEmJiUZVAsf/fHuOuFl1NjI7L7ytiixvq3RrGqugLL0uJfBKMxW2MPlCfS5AmERkB/WLMw4EkNYS1tR6lToVUtUHFB7SZhAtzUrKVMbmgx0/VTusN/70aDFALtxsjWsgKhwpxGpVq0jtEO9csha1ZnjwPJaAu8RBSEnL+Y73Ua1TylWA1olW4NZJ1UxTtZEXDkcLHkd5g3c/dXtUN7Ez6TCWLc4ro2njaNZovyjbKiIrxy53sR00nfhcvHpAV4SUSJEMcI+Y0rJU6pa0F4XYHNe8FmvUuZI3jz2LpYfNg9V/nXtGt3Czee/9bNKqjOj6J6OnTCfxKMpqya1b8Gnz2DfIfBoAbASciMqM2BBok2QV9xeS2O5ZBljdV7wVsJMOUC2MaYhhxDe/jLtDtz2y2q92rCqpiqfl5oVmbKaZJ8Ip2SxKb71zFfd0O7YAOQSaCTbNL1DmFAIW7ticmcIaW9nsGLwWmhQakNYNKcj2BF2/w3tLdthyi67Ca5ao3abm5bxlIaWT5sqo9utD7tiyl7bgO05APwSNCVVNtdFQ1MvXkRmQmsAbXFrnmarXtRTbEbaNpclJxMZAAPtddoDyTS5hKtdoBmY+ZIlka6SiZeTn46qJbjyx3nZM+yQ//gS1iWXN7BHolUBYXRptm6fcB1vO2odYgFXPUk5OXIncRTJABTt6Nndx363TKm2nRaVs4+1jS+PFpRGnICnbrWmxanX7Orb/toSTyaiOERJs1d+Y0lszXHfc25yg21DZe5Z2UtyOzYptBWCAT7thNntxgu2Yqdkm3CSy4ykigyM+ZBHmbak7rKBw/HVreke/qMSnyZ2OZRKdVmkZcFuhHTAdmJ1dHAaaJVcPU6BPeEq7xZEAoLtSNk1xt20yKVrmSeQRYr0h0eJNY6ZljGiprCIwVTUeOhZ/VQSxyYSOqBL6FpxZ9pw2XY+efd3CnOfavZeZ1BkP3AsHhgLA9ztNNm0xfOzfaTKlz2OIoioheSGzYs+lPafm668v9TST+eP/O4RyCZ5OmhMClzlaJNyynhYeyl6RHXPbAxhVFIZQeEtQBnXA03uRtloxU6zg6ODlrSMY4bBg+SEw4k5kgaezqwfvnPRNObC+3MRoiapOuxM3Fz+aexzVnoMffd7HneobtViAFSdQjEvUxqlBNHuftlTxeyy2aKWlY2LCoVBgkmDGYiNkGScQqu1vDTQKuXz+uUQWCalOixNXl2+auJ0fHtYfl99mHgncE9ka1XtQ14wVBt0BWjv2tlxxc2yfqIElceKGIQqgRSC0YY7jxKb+ql/uxrPMuQl+kYQ6yVsOilNkV0ja3d1O3w7f19+rnlLcXllkVYIRWUxQhxCBhDwWNrDxfGydKLMlGSKjIN7gEiB7IVFjhKa9qh/uiXOT+NZ+ZYPXCUBOuVMdF0va6l1kny1f/d+YHoTck9mcVfrRUYyGh0MB8fw99pGxlWzt6LtlGKKaYM2gOSAbYWtjWWZOqi4uVnNguKR+NgOrSRmOWBMCl3hanp1gnzFfyd/rXp8ctJmCViVRv4y2x3RB4vxttv6xvqzSaNolcOKrINbgOmAUoVzjQ2ZxqcrubbMzuHP9w4O4COaOJxLUlw6aul0DHxrf+1+lXqGcv9mWFgFR4szgx6PCFvykdzdx920JqQ6loOLVoTqgFiBnYWZjQuZnKfauD/MNOEW9zoN9iKhN5tKT1s9afhzLnuofkl+F3oxctVmXVg4R+wzDx9ECTTzid3syP21TqVil6SMZoXhgTCCT4YejmCZvafGuPXLteBm9l0M8iF9Nl5JAlrqZ6ly7Hl8fT19Mnl8cVVmFlgtRx80fx/uCRT0md4lyle3v6bfmCKO24ZBg3CDZocDjwyaKqjvuNnLVODC9XoL1iAuNedHblhDZvxwRnjoe8l76XdncH5lg1flRiM00B+LCvr0wd+Iy+m4d6ivmv2Ps4gIhRiF4ohHkA6b4qhXue3LE+Ar9ZIKox+5MzlGk1ZKZPNuPXbvee55O3bzbk9kpFZdRvczAiAbC+P1/+AQzbK6c6rQnDKS7IozhyaHworrkWic6Kn/uTLM8d+k9KgJXB4eMlZEdlQCYpJs1HORd613KXQgbcpieVWVRZkzEyCaC872T+K8zq+8saw+n7+UhI3DiZiJBY3tkxmeOavnuqjM8d8t9L0IAx1hMEFCGFJuX9ppDnHRdAl1tXHvau9gAlSNRAozAiAIDLj3sOOK0Ny+Lq/4oaGXeJCzjG6MqY9Llh+g16wPvFDNFODJ89MHmhuDLvw/fU+PXM5m7G2xcQNy4W5jaL5ePlJFQ0kyzR9iDKD4H+V30jjB57H7pNaaxpMCkKOPrZIFmXqiwK53vSvOW+B48+0GJBqILIo9p0xqWXJjcmo0bp5urmt8ZTlcL1C9QVQxdB+oDIT5m+aA1L/D2bRCqFmea5eskzeTDpYZnCil9LAevznPxuA98wwGoxhyKu86mUkCVshfo2Zeat1qIGg8YmJZ1032Py0w9h7ZDGL6Ieii1m7GAbjLqymiY5uulyWXyZmEnyiocbMFwXrQV+EY8zIFGhdEKCw4WEZZUtVbgmIwZsNmOWSnXjpWNUvwPdIuUx7yDDj7runb2ELJXLuSr0Cmq58GnGqb251Eo3irNrYqw+7RDeIK82AEihUBJkc15UJ0TptXFF6wYVNi/F++WsNSTEisO0UtiR3zDAX8QOso2zjM5b6Ts5uqPqSuoASgQqJVpxWvQrmNxZTT6uIW85kD9hOrI0EyRj9XSiBTXVnhXJFdbFuEVgBPHkUrOYYrmhzbDMb81eyG3U3PmcLLtzavGamjpe2k+aa2q/2yk7wsyGzV7eM6894CYBJGIR4vfjsGRmZOYFTGV4JYjlb9UfRKrEFvNpUphBupDHv9a+7y333SdcY1vAy0N67hqiKq/qtjsC23JsAFy3bXFuV58zACyhDUHuIrkDeEQXRJIk9mUihTZVEsTaFG+T15M3MnSBpdDCH+APBp4sTVdMrNwBq5k7NjsJ+vS7FXtaK7+MMYzrDZZebT85IBNw9YHJAogTPXPExEqEnETIlN9EsVSAtCBzpLMCIl5hj1C7j+kfHp5CDZks6OxVq+Krkktl+13baQulnACMhh0Rjc2udJ9AMBqA3VGSslVS8DOPU+90PlRqpHQka8QjU92jXnLKIiXhdyCz3/HPNu543cy9J1ysfD9L4gvF27rrwIwE3FUszf1K/edOna9IYAIQxOF7ghDysMM3M5FD7OQI9BUkAlPSI4dDFPKfYfsRXTCrH/oPT26QbgHNd7z13J78RQwpTBu8K8xXzK09CP2HHhMuuH9RwAogrFFDketCb3LcozBDiFOj07KjpVN9gy2CyHJR4d4RMYChEAGvZ/7IrjgNue1BfPE8uxyP7H/siny+HPiNVv3F7kFe1Q9sb/LQk+ErIaSCLIKAEuzDEPNLs0zTNQMVotCyiQIR0a7RFBCV4AifcF7xTn89/X2e/UXdE7z5fOcs/E0XjVbdp84HPnGu8194T/xQe6DyYX0B2FIxsocitxLQ0uQy0cK6wnECNuHfUW1w9OCJYA6viF8aDqcOQj3+Daxtfq1VjVEtYP2Dzbft+y5K7qQPE1+Fb/awY9DZkTThkyHh8i+ySyJjknjya9JNMh6h0kGacToQ1AB7gAPfr+8yzu9Oh85OXgSd643D3c2NyB3ijht+QP6QzuhvNR+T//IAXKCg8QyRTTGBIcbh7XH0UguR85HtMbnhi1FDgQSwsXBsUAf/ts9rTxe+3e6fnm4OSf4z/jvuMW5TnnFeqP7Yzx6/WH+j3/5gNhCIoMQxBvE/kVzxflGDcZxRiVF7MVMRMkEKgM2AjUBLsAsPzO+DX1//FE7xftheua6ljqvurI62ntku8v8iv1bPjX+1L/vwIGBg4JwAsJDtkPJBHkERUSuRHWEHYPpQ12C/sISQZ3A5sAzf0h+6v4f/ap9DjzNPKh8YLx1PGR8rLzKvXr9uX4CPtB/X3/qwG8A54FRQemCLcJdArYCuQKnAoDCiEJAQiuBjQFoQMCAmQA1/5j/RT89PoJ+lj55fiw+Lf4+Pht+RD62Pq++7j8vP3C/r//rACDAT0C1gJLA5oDwwPIA6wDcgMgA7sCSQLQAVYB4QB1ABcAy/+S/23/XP9f/3L/lP/A//L/JABUAHwAmAClAJ8AhgBZABcAxP9g/+/+d/79/Yb9Gf27/HL8Rfw2/Er8g/zh/GX9Df7T/rT/qQCrAbECsgOkBH8FOQbKBioHUwdBB/IGZQacBZoEZQMGAoYA8P5R/bX7Kvq/+ID3efa09Tz1FvVH9dD1sfbk92P5JPsc/Tv/cQGuA+AF9AfYCX0L0gzKDVwOfw4wDm0NOwyfCqMIVgbHAwoBNP5a+5L49PWW843x6e+87hDu7u1b7lXv2fDd8lT1LPhR+6z+IQKZBfYIHQz1DmQRVxO6FIEVoRUZFecTExKpD7gMVgmbBaQBj/17+Yn12PGH7rLrcOnW5/Tm0+Z3597oAevR7TvxJvV1+Qf+ugJqB/ELKxD1EzEXwxmTG5IctBz2G1oa6he1FNQQYgx/B1ICAv24953y2u2W6fTlEuMK4e7fyt+h4HHiLuXE6BztFPKJ90/9OwMgCc4OGRTWGN4cECBQIoojsiPCIsAguR3BGfQUdw9zCRQDjvwQ9s/v/OnG5Fjg1txe2gXZ2tjg2RPcZN+84/vo++6P9YT8pAO5CowR5heUHWgiOybsKGMqkyp3KRUnfCPGHhUZkxJzC+kDMfyF9CLtQuYc4OLav9bV0z7SCNI508nVqdm73tzk3euJ86b79QM2DCgUjRsqIsknPCxgLxcxUzEPMFItLSnAIzIdsxV9Dc8E7PsX85fqruKb25jV1NB3zZ7LW8uxzJrPAtTI2cLgveh68bj6LgSUDaEWDR+VJv0sETKnNaE37TeFNnIzyS6rKEch0xiRD8YFv/vI8THoQ99H13zQGMtIxyzF18RPxovJdM7m1LLcneVj77n5TwTUDvUYYiLRKgAysze8O/o9WT7SPG85STSDLVEl8RuqEcsGqfuY8PDlBNwj05PLkMVNwe2+g74YwKDDA8ka0K/YguJH7a34WQT0DyIbiiXdLs42Hj2bQR9Ek0TyQkY/qDlCMkwpCR/IE98HqvuI79fj89gxz+DGQsCMu+W4ZbgRuuC9tsNpy73Ubt8p65P3TQT1ECcdhCizMmM7T0I+RwhKlUrfSO9E4j7lNjQtGCLnFf4IwvuX7ubhEdZ2y2jCMLsIthqzgLJAtE+4kb7WxuHQZdwK6W/2KwTVEQMfTStTNr0/QEehTLNPW1CTTmZK8kNmOwUxGyUFGCgK7vvG7R7gYdPzxy6+YLbHsJKt2qyprvOymLlnwh3Nadnt5kD18wOWErYg5C25OddD70u/URlV31ULVKZP00jDP7o0DiggGloLMPwV7YHe5NCrxDW61LHNq0+oeadSqc+t0LQfvnbJf9bV5Ar0qAM3Ez4iRjDiPK9HV1CVVjZaHVtAWatUgE31Q1I47yo1HJMMhPyE7A7dnc6gwX+2ka0dp1ejYKI/pOqoPrADuu/FqNPE4s/ySgO5E5sjczLOP0JLdVQeWwdfEGAvXnBZ9lH6R8c7ui1BHtEN7PwR7Mfbi8zUvg+zmKm7oq6elJ12n0ek5asWto3C6dC94I/x2gIcFM0kajR6Qo5OR1hXX4djtGTTYvBdMFbNSxY/bDBCIBIPZP2+66var8pJvOiv7qWrnliaGZn5muufy6deslK/Rc7D3k3wWgJhFNMlKTbkRJBRyFs9Y7NnBWkoZydiKVpqTztCAjM1IlQQ6/2I67rZDMkAugytlqLwmliW85TNltmb86PdrkO8vsvY3AzvywGIFK4msTcMR0ZU+F7NZodrAG0qaxJm313NUjNFeTUXJJURgf5w6/XYoMf6t3yqkJ+Ml7GSJZH2kheYYaCXq2K5WMn+2sztLwGSFF4nADnwSK9W02EEagBvoHDVbqxpTGH0VftHzTfnJdISJP9z61rYbcY4tjqo35yDlGaPs413j6aUGZ2QqLS2Fsc52ZHshwCBFOMnFzqPSspYWGTfbBty43MncvNsb2TbWJBK/TmhJwoU0v+S6+rXcsW7tEemhprWkXuMn4pTjIqRHZrLpTq0+sSL113r1f9VFD4o9jrpS5VahWZdb9d0xnYcdeNvQ2d+W+5MBDxDKTsViADL66TXsMSDs6SkhZiHj/CJ7YeOiceOcpdLo/ixCMP21TDqGv8PFHAonDv+TA9cWWh8cTB3R3mxd3hyxWnaXRJP4T3KKmIWRgEc7IfXJsSRslKj3paYjcmHnoUph1+MGZUTofKvQsF91A/pWP6yE3koCjzOTTld02k7cyV5ZHvkebJ09GvtX/tQkD80LH0XCwKF7JHX08PksVGikZUKjAaGtIMnhVWKFZMmnyiuqr8i0/vnkv0/E1soQjxYThJe82qYdLV6Gn20e412zG21YaVSEEF/LYoY0wID7cLXt8N8saGhoJTeiqqEMoKLg6qIaZGFnZ+sQ77n0fXmyPy2EhcoQzyeTplet2uTdd57aX4dfQd4S28uYw1UXkKpLocZnQOV7RnY0MNYsUKhCZQVirSDF4FUgmGHF5AznFirD73P0AHm/fsbEq4nDzygTtBeIWwrdqB8Tn8gfh55cHBXZDNVd0OvL3MaaAQ67pTYHsR4sTOhzZOuiSaDZoCFgXuGII8zm1SqELzczx/lNPtuESInqDtfTrZeL2xgdvt8y3+7ftN5OHEvZRNWW0SPMEobMAXv7jHZn8TasXSh65Oqif+CH4AfgfmFho6EmpepSLsPz1LkbPqxEHUmDjvcTU5e5Gszdu183X/tfiJ6pHGzZa1WBkVIMQsc9gWz7+7ZUsV+sgOiZJQIikCDQYAigdyFSo4qmiGpubprzp3jqvnmD6clQzoZTZhdP2uldXl8hn+1fg16sXHjZf9WeEXXMbUctQaE8MvaNMZgs+CiNZXHiuiDzYCOgSSGbI4lmvSoZbrxzQDj7vgQD7wkSTkXTJVcQmq1dJ57xX4VfpJ5X3G+ZQdXr0U8MkUdbQdf8cTbRceBtAmkXZbmi/aEwoFjgtKG7Y51mhCpTLqizX3iOvgwDrUjIjjYSkdb72hnc116nH0MfbF4rnBCZcZWqkV0MrodHAhE8tncgsjdtXul2pdkjWqGIIOgg+WHzo8cm3epcLqBzRfikfdHDZQi0DZfSbFZR2e6cbd4C3ybe2x3nm9wZDlWZ0V/MhIewAgv8wbe6clztzWnrJk/j0CI5IREhV2JDZEZnCqq0bqOzc7h8/ZZDFshVTWtR9NXTWWxb692E3rDecJ1MG5IY2FV50RaMkseVwkg9Erfd8tBuTWpz5t1kXmKDodPhzmLq5JsnSercbvKzaThY/ZnCw0gtDPERbJVAmNObUd0t3eGd7RzY2zKYT5UKEQGMmUe3wkT9aLgKs1Du3erQJ4ElBGNnIm/iXeNp5QVn3CsT7w2zprh4/VyCqse7zGoQ09TamCUaoBx+XTldEVxOWr2X89SKkOBMV8eVwoI9g3iAc94vfqt/qDplgaQi4yRjBaQ/5YToQWubb3UzrLhc/V+CTgdCDBcQa1Qh12GZ11u2nHicXZus2fOXRVR7UHLMDYevgr89ofj99Dcv7qwBqQgmlWT2I/DjxWTspllo+Ovyb6jz+zhFvWLCLcbAi7hPtBNXFomZOJqXm6Abklr02RSWxFPcUDjL+odEQvt9w/lC9NtwrWzU6eonfyWgpNTk3CWvpwKpgyyZcCj0EnizfSdByka4Ss7PLpK7VZ4YBFniGrDasFnnGGFWMRMtj7KLnodUAvZ+KLmOtUnxea246p7ofaahJc+lyWaIaAAqX60PsLW0cvimfS0BpEYpiltOW5HPVN/XO9iW2arZt9jDl5nVS9Kvjx+LecceQu++T7ogNcHyEq6sq6YpUCf25uBmzKe2KNFrDa3VcQ603Hje/TSBfIWVCd7NvFDUE9AWH5e22E+YqhfLVr7UVNHiDoBLC4ciwuc+uDp3NkLy969vLL5qdejg6AXoJOi4afXrzW6qcbQ1DzkdPT5BE0V7yRoM0dAKku+U8NZC11/XR5b/FVETjJEFzhSKlAbhgtv+4frStwuzp/B/baarrWoeaX+pESnOay0s3i9OMmX1i3lh/QsBKUTeSI2MHI8z0b+TsJU8FdyWEZWflFDSs5AazVzKE0aZws2/C/tx95t0YfFcrt4s9etuKoxqkOs3bDYt/zAAcyO2EPmsvRrA/0R9h/qLHY4QkIESoBPj1IbUyJRtkz8RSo9hjJkJiUZLwvx/NfuUeHF1JTJFcCOuDizO7Crr4qxyLVBvMDEAs+12n7n9/S3AlUQZx2HKVk0ij3URAFK60x+TbhLqUdyQUc5aS8mJNcX3Aqd/X3w4+My2MHN4sTWvdS4/rVptRa397rrwMDIOdIK3d7oV/UTArIO0BoRJh0wqTh0P0tEC0ehRwtGWUKpPCo1Fyy6IWUWbwo4/h7yfeax2wvS1clNw6S++7tlu+K8ZsDSxfvMpdWM32Lq0fWAARUNNRiLIscrpTPnOWE+8kCIQSFAzDykN9QwkygjH84U5wnD/rfzGuk932zW6c7tyKXELsKawerCEcb0ymzRQtk64grsZ/b+AH8LlxX4Hlwngi41NEo4pjo4O/45BTdmMkgs3SRgHBQTRAk8/0n1uOvV4uHaGtSyztDKkcgDyCfJ8stM0BDWD90R5dbtGPePAPMJ+RJdG94iRSlgLgwyLTS3NKczCjH1LIwn+iB1GTgRhQih/8/2Ve5z5mbfYtmV1CHRH8+bzpbPBtLW1eTaCOEQ6MPv5fc0AHIIXxC8F1Me8iNvKKorjC0KLiIt3ypUJ6Ei6xxiFjoPqwfy/0n47PAV6vbjvt6S2pLX0dVb1TDWR9iM2+TfK+U169HxzPjv/wAHyg0aFL8Zjx5nIislySY3J3QmiSSJIYwdtRgrExsNtgYtALT5ffO37Y3oJ+Sk4B3eo9w/3PHcsN5s4Q3ldOl97v/zz/m9/5wFPgt6ECYVIRlNHJUe6h9DIKIfDh6XG1EYWhTSD94KpgVTABD7BPZV8SftmenF5r3kj+NB49LjPOVv51nq4O3m8Uv26/qi/0gEvQjeDIwQrBMnFu0X9Bg1GbMYcxeDFfUS3g9ZDIQIfQRkAFv8fvjs9MDxEO/v7Gvrjupa6s/q5euS7cXvbPJu9bT4Ifyc/wcDSgZLCfULNA75DzkR7RETEqsRvRBTD3oNRAvDCA4GOgNeAJP96vp6+FT2h/Qe8yPymvGE8eDxpvLO8031E/cR+Tf7cP2t/9kB5gPEBWUHwAjKCX8K3AriCpIK8wkMCecHkAYTBX8D3wFCALf+Rv36+976+PlM+d74rvi6+AD5efkf+uv60vvO/NL91/7U/78AlAFLAuECUwOeA8UDxwOoA2wDGQOyAj8CxgFMAdcAbQAQAMb/jv9r/1z/YP91/5f/xP/2/ygAVwB/AJoApQCeAIMAVAARALz/V//l/m3+8/18/RD9tPxt/EL8NvxN/In86/xy/Rz+5f7I/74AwQHGAscDuASQBUcG1AYvB1QHPQfpBlcGiAWCBEoD5wFkAM7+Lv2T+wv6ovhn92X2p/U29Rf1T/Xg9cf2AfiG+Uz7SP1p/6AB3QMNBh4I/gmcC+oM2g1jDn0OJA5YDRwMeAp1CCIGjgPOAPf9HftY+L/1Z/Nl8cvvqO4I7vLtau5x7//wDfON9Wz4l/v1/msC4gU8CV0MLQ+TEXoT0RSKFZ0VBRXGE+URbw90DAkJSAVOATj9Jfk49Y7xRu5860fpvOfq5tnmjucF6TfrFO6K8X711Plr/h8DzAdODIAQQBRvF/EZsRudHK0c3BsuGqwXaRR6EP0LEwfiAZH8SPcz8nrtQumv5d/i6eDi39Lfv+Cj4nLlGumA7YXyAfjN/boDnAlED4QUNBkrHUogdSKYI6gjoiKJIG0dYhmGFPwO7giKAgL8h/VO74bpYOQE4JfcNtr22OTYBNpP3LffI+R06YPvIPYb/TwETgsZEmYYBB7EIn8mFyl0KogqUSnUJiIjVR6RGAES1QpFA4z74/OJ7Lflo99/2nXWptMs0hTSYtMQ1graNN9q5XvsM/RX/KYE4wzMFCMcrCI0KI0ski8rMUcx4y8HLcYoPyOaHAoVyAwSBC77XvLn6Q7iENsl1X7QQM2Jy2jL4Mzqz3DUUtpk4XDpO/KA+/gEWg5cF7cfKSd3LWwy4TW4N983UzYdM1QuGSicIBUYxA7xBOn69/Br54/eqtb6z7fKCscTxeXEg8bjye/OgNVm3WbmO/Ca+jEFsQ/GGSEjeCuIMho4/jsVPks+nDwSOccz4SyUJB4bxxDfBbv6sO8U5TvbdNICyyTFCMHQvpK+UMABxIvJw9B22WDjNu6k+VMF6BAIHF0mlC9lN5A95EE9RIVEt0LgPhs5kjF9KCIezxLcBqX6ie7l4hbYcc5Cxsq/P7vFuHO4TrpJvknEIcyV1V/gLOyh+F0F/xEjHmopfDMJPMxCj0cqSodKoEiCREo+JjZULB0h2RTlB6f6gu3g4CLVpcq7wa66tLX3so6ygLTAuC6/nMfJ0WndIuqS91AF9RITIEYsLDdxQMlH+UzYT01QUU7ySU9DmjoUMA4k4xb6CL76newE31/SEcdzvdK1a7Bqreis7a5qsz+6OcMVzn/aGOh49i4FyhPaIe8uojqYRIJMH1JDVdJVxlMsTyZI6T67M/Am6xgYCuv61+tT3dHPucNsuTyxaasjqIanmKlNroG1/r59yqXXEuZV9fYEfxR1I2Mx3D1+SPRQ/FZlWhBb+VgrVMtMEENEN8Ep7ho/Cy37M+vO23jNn8Cqte6ssqYno2yiiKRtqfew7boEx9/UE+Qs9KsEExXjJKAz1kAdTB1VjVs6XwVg5V3qWDlRCkesOn0s6hxrDIL7r+p22lbLxb0tsuyoSaJ6np+dwJ/PpKesC7euwy7SHOL98k0EiBUmJqc1kEN1T/hYzV++Y6pkiGJmXWtV00ruPSEv2x6cDen7SupJ2WvJLLv7rjilMZ4fmiKZRJt3oJOoXLN/wJfPMeDL8d0D3RU8J3U3CEaDUoNcumPuZ/1o22aZYV5ZZ04JQaoxwCDODmH8BepJ2LnH1bgTrNahb5oalvqUGpdpnMKk5K96vR3NU96Y8F0DExYmKAs5PEhEVbxfUWfGa/ls3WqBZQ1dw1H3QxU0lSIBEOj83ul210DGw7Z4qceeBZdvkiuRQ5OpmDWhpqyjusLKhtxm788CKxbkKGc6LEq4V6BijmpEb5twiG4YaXZg41S2Rl82WSQyEX791OnO1gHF9rQspw+c9ZMgj7eNxI87lfGdpan9t4rIzNo37jMCJhZ1KYk71kvcWS1lcG1kcuBz2XFdbJRjw1dDSYU4CSZfEiD+5+lS1vvDb7Mwpa6ZQpExjKGKoIwhkvma5qaKtXfGKNkN7YsBBRbbKXM8Ok2wW2Fn9G8jdcZ2z3RLb2VmYVqaS4Q6oieFE8z+FeoC1i7DLrKFo6aX7o6iieyH2olfj1GYaqRPs4zEm9fq69oAyhUXKiI9WE4yXTxpGHKAd0l5ZXfgceVouVy6TVo8ISmkFIL/Xerb1ZvCM7EroviV+ox3h5qFdYf4jPqVNqJNscvCKdbR6iAAdRUpKpk9ME9jXr1q3HN5eWh7mXkZdBJryV6eTwQ+hSq4FT4Avure1UHCf7AjoaaUZ4uwha6DcoXtiveTSqCHrzjB1NTC6WL/CRUSKtg9wU9CX+FrPnUNeyF9anv0delsj2BEUYA/zCvAFgABNusJ1h7CEbBuoK6TN4pQhCmC04NCiUySq54ArtS/ndPB6J3+hhTTKd89DFDOX6tsPXY6fHJ+1nxvd2huB2KrUstA8iy5F8YBw+ta1jLC6K8KoBOTaYlXgwyBm4L4h/mQWp26rKK+iNLQ59b97xNvKa89ElAJYBht2Hb/fFt/2n2IeI5vMWPQU+NB9i2iGI0CZOzR1nzCBLD3n9SS/4jFgliAyoEQhwGQWZy3q6S9ltHw5g/9RBPmKEs91U/0XyptEXdcfdp/d34/eVhwCWSxVMdC1i54GVUDGO1s1/vCY7A2oO+S+Iicgg6AYYGMhmWPqZv4qty8ydAk5kj8iBI6KLI8VE+NX+Fs53ZSfe9/rH6RecZwj2RMVXRDjy86GhoE2+0p2K3DBbHDoGWTU4nbgi6AYYFshiePTZuAqku8I9Bt5YX7vRFsJ+g7kk7YXj5sWnbffJt/d35+edZwwmShVehDITDmGtsEre4G2Y/E6LGfoTWUEYqAg7eAyoGxhkaPRJtQqvO7pc/N5Mb65RCAJu06j03WXUJrbHUGfNx+2n0GeYhwoGStVSNEiTB5G5YFi+8C2qLFCbPIol2VL4uNhKqBnIJch8OPkJtoqta7U89G5A/6ARB2JcQ5T0yHXO9pHnTHerV91HwpeNtvKmRxVSNExzDzG0oGdPAa2+LGaLQ8pNuWrIz/hQWD1oNriJ+QMpzJqvS7K8/a42D5FA9QJG4400rvWkZocnIjeSZ8ZnvodtBuXWPqVOdD2DBRHPQGZvFM3E3IAbb4pa6YiI7Vh8iEeIXeidmRKZ11q068Mc+K47v4Hw4RI+42HEkPWUpmaHAcdzF6kXlCdWdtPGIZVG5DuzCTHJIHXfKX3eHJ1Lf8p9Oav5ANivCGf4e2i3GTdZ5rrOa8Zc9Y4yP4JQ28IUc1L0fpVv1jBG6zdNd3V3c6c6BrxWD+UrdCcDC2HCQIWvP33pvL3LlDqkidT5OljHuJ64nvjWeVF6Csrbu9yM9E45n3JwxRIHozDEWBVGFhSGvscRp1unTQcHxp+V6YUcNB9S+6HKcIWPRr4HrNGLzLrAqgNpaaj2mMuoyJkLiXDaI3r86+WtBQ4x73KAvUHooxuELZUXleN2jJbv1xu3EGbv5m2VzoT5FASy+dHBkJWPXw4XrPhL6SrxajcJnqkrWP6Y+Ck2OaVqQLsR/AHdF+47T2KQpIHXovNED0Tklb1GRNa4JuXG7faiZkZ1rvTSE/cC5eHHoJVfaE45nRH8GUsmmm+5ySll6TdpPYlmid8aYps67BENLO4132LQmtG00thD3WS9RXImF7Z61qompcZ/Zgo1etS3M9ZC39G8cJUPcl5dTT5MPOtQCq06COml+XXZeHmsKg3amOtXrDNNNA5Br2NQgHGgUrqzqBSB1UJV1WY4BmjmaAY3BdkFQkSYk7KCx5GwAKRfjP5ijW0MY8udat9aTanrabnJuOnnGkF606uIPFidTW5Oz1QwdYGKUorDf6RChQ4FjiXgBiJGJPX5hZL1FVRmI5uirRGiMKM/mC6JPY4MncvOmxW6l0o16gMKDponKonrAsu8jHDtaQ5dT1WQajFjEmizREQflLWFQkWjFdaF3LWnBVg01CQwA3HSkFGi8KGPo66hDbEc2owDO2A65WqFSlFKWUp8Gsb7RgvkfKxNdu5tP1eQXpFKsjSzFiPZNHkU8gVRVYXlj5VftQjkntP2Q0TycVGSQK8/r0657dX9CdxLK66LJ8rZOqQ6qNrFuxh7jWwf/Mqdlx5+v1pQQuExUh7y1aOf1CkErZT7NSCVPbUD1MVEVYPJAxUyUAGAAKwfuw7TrgyNO4yGC/Brjhshewu6/OsT2247yKxe7PvduY6Bv23QNzEXQefCouNTk+WEVWSg9Nb013SzlH1kCEOIUuKCPHFsMJgvxp7+DiRtf0zDnEV72BuNu1drVUt2K7gMF7yRTT/t3j6WX2IwO7D8ob9CbjMEw57j+aRCxHlEfRRfNBGjx3NEYr0SBqFWwJNP0g8Y3l1tpN0TnJ18JXvtq7cLsavcjAW8amzW3Wa+BR68r2eQIIDhoZWyN9LDs0WTqrPhJBfUHtP288IjcxMNQnTh7qE/oI1f3Q8j/odt6+1VrOgchexA/Co8Ebw2nGb8sG0vfZBOPj7Ej34AFbDGcWth8BKAovnDSOOMQ6LzvPObI28jG2KzIkoRtHEm8IZf549PPqIeJE2pnTUM6QynXIC8hTyUDMutCa1rHdxeWX7uH3WgG4CrMTBhxyI78pvS5IMkg0sDR+M8EwjiwKJ2IgyxiCEMgH4/4W9qbt1OXb3u/YPtTo0AXPoc68z0rSNtZd25bhruht8JX45gAgCQIRURjVHl0kwSjgK6QtBC7/LJ8q+yYwImcczxWcDgcHTf+o91Xwiul941reRtpg17vVYdVR1oLY39tM4KXlvetk8mT5hgCUB1YOmhQvGuserSJZJd4mMidWJlMkPSEtHUUYrxKWDCsGov8t+f3yQu0n6NPjZODz3ZDcRNwM3eHeseFk5drp7+559E36OwAXBrML4xCCFW0Zhxy7HvsfPyCJH+IdWBsDGP8TbA9xCjUF4/+i+pz19vDV7Fbpkeab5IDjRePo42Plp+ef6jHuQfKs9k/7BQCqBBkJMg3UEOcTVBYLGAEZMhmfGFAXUhW3EpcPCgwvCCYEDQAG/C/4pfSC8d3uyexT64PqXerg6gPsvO3676nysvX8+Gz85v9OA40GiAkpDF8OGRBOEfYRDxKcEaQQMA9ODRELiwjTBf0CIgBY/bT6Sfgq9mX0BfMT8pTxiPHs8bvy6/Nw9Tz3Pvlm+6D93P8GAhAE6QWFB9kI3QmKCuAK3gqHCuIJ9QjMB3IG8gRcA7wBIQCX/ij94fvJ+uf5QfnY+K34vvgI+YX5L/r9+uf74/zo/e3+6P/SAKQBWQLsAloDowPGA8YDpANmAxEDqQI1ArwBQgHOAGQACQDA/4r/af9b/2H/d/+b/8j/+v8sAFsAgQCbAKUAnQCAAE8ACgC0/07/3P5j/un9c/0I/a38afxA/Df8UfyQ/PX8f/0s/vf+3P/TANYB3ALcA8sEoQVUBt0GNQdUBzkH3wZIBnUFagQuA8gBQwCr/gv9cvvr+Yb4UPdT9pv1MPUY9Vj18PXe9h/4qvl1+3T9mP/QAQ0EOwZICCMKuwsCDeoNaQ56DhcOQg39C1AKRgjtBVUDkgC6/eH6H/iK9TnzP/Gu75buAO727Xvuje8n8T/zx/Wt+N37Pv+2AisGgQmdDGQPwBGcE+YUkhWWFfEUpBO2ETQPLwy8CPUE9wDg/ND45vRD8QXuR+sg6aPn4ebg5qXnLelu61nu2vHX9TT6z/6DAy8IqwzVEIoUqxceGs0bpxykHMAbABpuFxsUIBCYC6cGcQEf/Nn2yvEa7e/oa+Ws4srg19/c397g1uK45XHp5u328nv4S/44BBcKuA/uFJAZdh2CIJcipCOdI38iUSAfHQIZFRR/DmgI/wF3+//0ze4S6frjsd9Z3BDa6djw2CnajdwM4I3k7+kL8LL2sv3UBOMLpRLlGHIeHiPCJkApgip7KigpkCbGIuMdDBhtETcKoQLn+kPz8ust5SzfHtos1nnTHNIi0o7TWNZt2q/f+eUa7d30B/1YBZANbxW3HCwjnCjaLMMvPDE4MbQvuSxcKLsiARxgFBIMVQNw+qXxOelw4YbatdQq0A3Nd8t3yxLNPNDh1N7aB+Im6v3ySvzCBR4PFRhgILsn7i3FMhg2zDfPNx82xjLdLYUn8B9VF/YNHAQS+ibwpubc3Q7We89Yys/G/sT2xLrGP8ptzxzWHN4x5xTxe/sTBo0QlRrdIxwsDjN+OD08LD45PmI8sjhDMz0s1CNJGuMP8gTN+cjuOeR12sfRdcq6xMbAuL6kvozAZsQVym/RPto/5CXvnPpMBtsR7hwuJ0ow+jf/PSpCV0RyRHlCeD6LON4wqyc4HdUR2AWh+Yvt9eE817PNpsVWv/W6qbiFuI66tr7fxNvMb9ZS4THtr/ltBggTHR9OKkM0rDxGQ9xHSEp0Sl5IEUSuPWQ1cSshIMoTzAaM+W7s29801NbJEsEuumO117KhssS0NLnPv2XItNJv3jvrtfh2BhMUIiE8LQM4IUFNSE5N+k86UAtOekmpQso5IS//IsEVzAeO+XTr7N1g0TLGvLxItROwRq37rDWv5bPruhDEEM+X20XpsPdoBv0U/CL3L4k7VkURTXtSaFW/VXxTrU52Rw0+uDLQJbUX1win+ZvqKNzAzsvCqLiosAqr/KeYp+Opz642tuG/hsvO2FHnofZFBsUVqSR8MtI+SUmOUV9Xjlr/WqxYplMSTChCMzaQKKYZ6gnV+ePpkdpWzKK/2LRQrEum/KJ9otak9am1sdu7G8gX1mPlifUMBmwWKibLNNtB9UzAVfdbZ1/0X5ddYFh3UBZGjTk8K5EbBQsY+k3pJ9kjyrm8ULFEqNuhSp6vnRCgXKVsrQS408R2033jbPS/BfIWfifhNqNEWVClWT5g8GOaZDdi11yiVNVJxDzSLXMdJQxu+tfo6tcqyBK6Ea6HpL2d7JkxmZabCKFgqV+0sMHt0KDhSvNgBVcXpCi+OChHclM5XTJkJGjuaIlmBmGOWGBN0z9OMEkfSA3W+oLo29Zpxq+3HqsbofSZ45UIlWyX/pyVpe+wtb5/ztHfJvLvBJwXnClhOmlJPlZ7YM9nAGzsbIpq6mQ3XLRQt0KtMhIhbQ5P+03o+dXjxJG1eagEnoSWM5I3kZaTQpkOormt6LsvzBDeAfFuBMMXZyrKO2RLvFhnYxNrgm+QcDRuf2ibX8xTbUXtNMoikQ/Y+zboRdWXw7izJKZDm26T4I7AjRiQ1pXPnr+qSrkAymHc3u/fA8oXBSv4PBlN6Vr8ZfptpXLXc4ZxwWu1YqZW8kcJN28kshBu/D3ovdSGwieyHqTbmLWQ7YupivSMvpLbmwWo37b2x8bav+5CA7UXdivsPYdOxlw4aIRwaXW/dnt0rm6CZT9ZQ0oBOf8lzxEQ/WDoYtSwwd2wa6LMlluOWonyhy2K/Y81mY6lqbQSxkLZpe2bAoQXuyulPq5PUF4aaq5yyndFeRJ3QnEAaJNbXEzQOnYn5RK9/Z/oMtQUwdqvCqEYlWGMK4eehceHl43gll2jrLJYxNfXk+zqATcX1iskP41QiF+ga3d0x3lme0h5enMraqBdPE51PNQo8hNy/vjoLdSywB6v+5+/k8qKYYWvg8OFjIvflHSh6rDJwofWi+sxAdIWxitqPyVRbWDKbN11XnsifRp7VnUBbGRf4E/tPRYq9RQu/2rpUdSJwKquQJ/DkpWJ/YMngiOE4Yk1k9efZq9pwVXVj+pyAFUWjSt3P3ZR/2CYbeB2jnx2fod80XaAbdtgRVE1Pzgr6hXw//LpntSYwHyu154kksSIAYMIgemClYjikYaeIa45wELUoemw/8EVLStMP4FRPmEKboB3V31hf4597HembgRiaVJMQDos0BazAJDqEdXewJSuwZ7gkVaIbIJRgBaCrIfpkIWdHq08v1LTw+jq/hoVpyrqPkZRK2Efbrx3t33jfy1+pHhyb95iSlMvQRotpRd5AUHrqtVawfGu/J75kUyIQIIEgKqBJYdLkNScX6xzvoTS9+ck/l8U/SlUPsdQyGDYbZR3r336f2R++Hjhb2Zj51PdQdQtaBg+AgXsZtYLwpGviJ9tkqWIfIIhgKiBA4cJkHWc5Kvgvd3RP+dg/ZQTLymKPQZQFGA3bQl3P32ofzJ+6Hj0b5xjP1RUQmguFRkBA9jsRNfuwnOwZKA7k2GJIIOogA6CRYclkGmcsKuFvV3RnOaf/LkSQSiOPARPEl88bB12aHztfph9dHiqb35jT1STQtQurBm/A7ntQtgCxJaxjaFjlH6KKoSZgd2C7IefkLGcxKtjvQXREebk+9IRNCdjO8JNwl3patB0KnvIfZV8m3cCbwxjF1SYQhcvKxp3BKbuXdlExfayAqPhlfuLm4XxghOE94h2kU2dIKx8vdjQn+Uw++AQCiYKOkJMKFw/aSNzh3k7fCp7Xnb7bUVillNiQi4vkBonBZ3vldq0xpO0wKS1l9aNb4eyhLGFZoqrkj6exazPvdfQSOWE+uUPxiSFOIhKRVpBZxlxgXdIell5vXSYbCphzVLxQRkv2RrOBZzw5ttNyGq2x6bcmQ6Qp4nYhraHOYw9lISftK1fvgLRDeXk+eMOaSPXNpVIHFjyZLRuGXXwdyN3uXLXarpfuVFDQdcuBRtoBqHxTt0Pyni4E6lUnJ+SPoxiiR6KbY4slh6h7K4rv1vR8ORP+dsN9iECNWxGrlVSYvdrUnI1dYl0VHC6aPZdXVBZQGcuFBv1Bqnyy972y7u6oasan4iVNI9NjOmMApF2mAujbbAzwOPR8eTJ+NEMbyAJMxBEAFNmX+NoL28Zco1xkG1DZt9bt04xP8gtAxt0B7TzW+AAzjC9bq4rosaYhZKYjxWQ9ZMam0ulN7J5wZnSEuVT+McL1x7vMIRBFFAxXH1lsmugbjJubmpyY3ZZyUzNPfos0RriB7/0++Eq0NS/eLGEpVScLpY/k56TRZcXnt2nSbT7wn/TVOXu970KLx22Lso+7ky2WMdh3mfMantq8WZLYLxWk0otPPwrfxo+CMf1qeNx0qPCu7QhqTCgK5o/l4KX75ppob6qo7a6xJXUt+Wc97YJextiLOY7kEn4VMZdt2OgZmtmHGPOXLRTFkhQOs8qChqGCMz2YuXS1JvFM7j/rFakep6Vm76b754Qpe6tQrm0xtrVPeZd97QIvRn0Kdo4/kX7UHxZQl8hYgVi8V7/WF5QVEU5OHIpcxm6CMr3JedL17nI3bsascOoFqM9oE6gRKMHqWmxJrzpyE/X5eY097kH+BdwJ6w1PULDTO5UgVpRXUxdc1rgVL5MT0LmNeUnuRjZCMH47ujZ2fjLtb9utXGt+6czpS6l6adNrS61TL9Yy/PYsecg98YGLBbaJF0yTz5USCBQeVU2WEVYp1V0UNVICD9bMyom3BfhCK/5uup43FXPt8P2uV2yJK1zqluq26zesTm5s8IAzsXaoOgk994FXhQzIvIuOjqzQxdLLlDTUvNSkFC/S6dEgjuYMEAk2xbRCJL6iewl383S38evvoK3jrL4r9CvFrK2tom9WMbe0Mbcs+lA9wIFkBKAH24rADbkPthFpkouTVxNM0vFRjdAvzefLSkithWpCGj7V+7e4VzWKcyTw9u8M7i9tYi1lbfRuxnCOcrx0/Pe6ep09zMEwxDCHNUnpjHrOWZA5kRKR4RHk0WJQYg7wTNyKuYfbxRoCC/8IvCf5P7ZkdCfyGTCDr69u3+7Vb0twebGU84310zhQuzC93ID+g7+GSokMS3ONMc68T4uQW9BtT8PPJ02iy8TJ3gdBRMNCOj86fFm57HdE9XOzRfIG8T0wbDBUMPExu3Lo9Kv2s/jve0p+MICNw02F3IgpCiQLwA1zjjeOiM7njlcNnsxIiuEI+AaeRGZB4/9qPMv6m/hqtka0/DNU8pbyBbIgsmRzCrRJtdU3nvmWu+r+CMCfAtsFK4cBCQ3KhcvgjJgNKY0UzN1MCUshybIHyAYyw8LByX+XfX47DblUd5/2OnTsdDuzqrO5M+R0pjW2Nsm4k7pGPFG+ZcBzAmlEeUYVh/HJBApEyy6Lfwt2SxeKp8mviHiGzoV/Q1iBqj+CPe+7wHpBuP43f3ZMden1WjVdNa+2DTctuAg5kbs9vL8+R4BKAjiDhgVnBpFH/EihSXxJisnNiYcJO8gzBzUFzESDwygBRf/pfh98s7sw+eA4ybgy91/3ErcKd0U3/jhvOVB6mHv8/TL+rkAkQYmDEwR3RW3Gb8c3x4KIDogbx+0HRkbtBeiEwUPAwrEBHL/NPo09ZnwhOwT6V/me+Ry40rjAOSM5eDn5eqE7pzyDve0+2kACwV0CYQNHBEhFIAWJxgMGS0ZihgsFyAVehJPD7sL2wfOA7f/svvg9130RPGr7qPsO+t56mLq8uoi7OftL/Dm8vb1RPm2/C8AlgPPBsQJXQyJDjgQYRH9EQsSjRGJEAsPIg3eClMIlwXAAub/Hv1++hn4APZD9O3yBPKP8Yzx+fHR8gj0lPVl92v5lfvQ/QoAMwI5BA4GpAfyCO4JlQrjCtoKfQrRCd8IsQdTBtEEOgOaAQAAd/4L/cj7tPrX+Tb50vis+ML4EPmS+T/6D/v7+/n8/v0C//3/5AC1AWcC9wJiA6cDxwPEA6ADYAMJA6ACKwKyATgBxQBcAAIAu/+H/2f/W/9i/3n/nv/M//7/MABeAIQAnQClAJsAfQBKAAQArP9E/9L+Wf7f/Wn9//ym/GT8Pvw4/FX8l/z//Iz9O/4J//D/6ADsAfIC8APeBLEFYgbnBjkHVAc0B9UGOAZhBVEEEQOpASIAif7p/FD7zPlr+Dj3QfaP9Sv1GvVh9QD29vY9+M75nvug/cf/AAI8BGgGcghICtoLGQ35DW8Odg4KDisN3QsoChcIuAUcA1YAff2l+ub3VvUL8xnxku+E7vrt/O2M7qrvT/Fx8wH27/gk/Ij/AAN0BsYJ2wybD+0RvRP7FJkVjxXcFIEThhH4DukLbgiiBKAAifx6+Jb0+vDF7RPr+eiM59nm6ea/51bppeue7iryMfaU+jP/6AORCAgNKRHTFOYXShrnG7AcmhyjG9EZLhfME8QPMgs6BgABrvtr9mLxvOyd6Cjle+Kt4M7f6N/+4AvjAObJ6UzuZ/P0+Mn+twSSCiwQVxXrGcAduCC4Iq4jkCNbIhYg0BygGKQTAQ7iB3QB6/p49E7unuiX42DfHtzs2d7Y/9hR2s3cYuD35GvqlPBF90r+bQV3DDATYxnfHnYjAydoKY4qayr9KEsmaCJvHYYX2BCYCf0BQvqj8lvrpeS23r7Z5tVP0w/SM9K906PW0tos4Inmuu2I9bj9CQY8DhEWSR2rIwMpJi3wL0oxJjGDL2ks8Cc2ImYbtRNaC5gCs/nt8Izo0+D/2UfU2c/bzGfListGzZHQVNVs26vi3OrA8xP9jAbjD84YBiFMKGMuGzNNNt03uzfnNWwyYy3vJkEfkxYoDUYDPPlW7+LlK9111f/O/MmXxuzECsX0xp7K7c+71tXe/efu8Vz89QZoEWQbmCS9LJIz3zh4PD8+JT4lPE84vDKWKxMjchn+DgYE4Pjh7WDjsNkc0evJVMSHwKO+ub7MwM7Eosoe0gnbIOUV8JX7RQfNEtId/Cf9MIs4az5sQm5EXUQ3Qgs+9zcoMNgmTRzaENUEnPiN7AfhZNb4zA7F5b6vupG4nLjSuia/eMWZzUzXR+I37r76fAcQFBYgMCsGNUs9vEMlSGJKXkoXSJ1DDz2fNIwqIh+6ErIFcfhb69jeSdMKyWzAs7kWtbuyt7INtay5dMAxyaLTd99V7Nr5mwcxFS8iMS7XOM5BzkieTRdQJFDBTf5I/0H3OCsu7iGcFJ0GXvhM6tXcYtBXxQm8w7S/ryetEa2Br2W0mrvpxA3Qsdxz6un4ogcvFhwk/TBtPBBGnE3SUolVqVUuUypOwkYtPbMxrSR+FpQHY/hf6f7asc3gwee3GLCvqtmnr6czqlWv77bHwJPM+dmS6O33kgcLF9wlkzPEPw9KI1K9V7Ja6FpbWB1TVEs7QR81XSddGJUIfviU6FXZNsunvgu0tqvppdWilKIopYGqd7LNvDbJUte15uj2bAfEF28n8jXcQshNX1ZcXI9f3l9DXdFXsU8fRWw4+ik3Gp0Jr/js59nX9Miwu3ewoKdzoSCexZ1koO2lNq4BufrFwNTf5Nz1MQdbGNMoGDiyRThRTVqqYBxkhWThYUNc01PTSJY7gSwJHK0K9Phm54zW68b8uC2t2qNOnb6ZRpnsm5+hMqpltePCRNIS48r04gbRGAkqAzpFSFxU612kZFRo2mgyZm5guVdVTJk+8C7RHcELTPkB527VHcWMti+qZqB/mbGVG5XEl5mdbab/sfS/489Q4bTzgQYlGRArtDuSSjNXNWFIaDRs2Wwxak5kXFugT3NBQzGMH9cMt/m95n7UicNitH+nRp0Ilv6RSJHvk9+Z7KLQrjC9n82c353yDgZZGegrKj2ZTLtZKWSSa7pvf3Dbbd9nul6xUiBEeDM4Ie8NMvqZ5r3TMcJ/siClfprskqeO0Y1xkHaWsp/dq5u6esv43YbxiwVtGZIsZD5YTvFbxmZ/buFyyHMscR9r0GGFVZ1GizXTIgUPvPqU5irTFcHjsBKjDpgtkK+Lt4pOjWCTwpwpqTe4eMln3HHw+gRjGQ8tYj/QT9ddCWkPcal1snYidApummQZWOdIezdZJBgQVPut5sTSNcCPr1ah+JXOjRiJ/oeHiqGQH5q3pgi2nMfs2mHvXAQ8GV4tJUD/UGlf8Wo+cw54Onm5dp1wFGdpWvtKQznJJSUR9/vj5ovSkL+Eru2fPZTPi+aGqIUgiDuOzZeJpBC06MWI2VfuswP4GIEtrEDmUadgfWwLdQ56XnvveNVyPmlyXNdM4johJysSpfw0537SJr/Crdme35IzihiFt4MahjGMzZWkolKyXsQ92FXtAQOaGHgt+UCFUpJhrW12dql7HH3DerF0E2s0XndOVjxdKCgTW/2f55zS975HrRie3pH6iLGDLIJ5hIWKI5QIodCwAcMP117sRwIiGEUtC0HbUipigG59d9x8cn4yfC12kmyqX9pPmz19KRkUGP4i6OTSAb8UraqdOpEliLGCCoE9gzmJ0JK4n42v1MH/1XPriAGTF+os5UDqUm1i9W4heKh9YH87fUl3uG3TYP1QsT58Kv0U2v696FPTQ78prZCd85CzhxqCUYBogk6I1pG2noqu18AQ1ZfqxQDuFmYsh0CzUl5iDm9geAt+5H/cfQN4hW6tYd9RlD9bK9EVnv9s6erTvb+DrcidCZGnh+uBAYD6gcWHNpEDnsmtDsBD1MvpAAA=\" type=\"audio/wav\" />\n",
        "                    Your browser does not support the audio element.\n",
        "                </audio>\n",
        "              "
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 28,
       "text": [
        "<IPython.lib.display.Audio object>"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Video"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "More exotic objects can also be displayed, as long as their representation supports the IPython display protocol.  For example, videos hosted externally on YouTube are easy to load:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import YouTubeVideo\n",
      "YouTubeVideo('sjfsUzECqK0')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "        <iframe\n",
        "            width=\"400\"\n",
        "            height=300\"\n",
        "            src=\"https://www.youtube.com/embed/sjfsUzECqK0\"\n",
        "            frameborder=\"0\"\n",
        "            allowfullscreen\n",
        "        ></iframe>\n",
        "        "
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 29,
       "text": [
        "<IPython.lib.display.YouTubeVideo at 0x107c1eb50>"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Using the nascent video capabilities of modern browsers, you may also be able to display local\n",
      "videos.  At the moment this doesn't work very well in all browsers, so it may or may not work for you;\n",
      "we will continue testing this and looking for ways to make it more robust.  \n",
      "\n",
      "The following cell loads a local file called  `animation.m4v`, encodes the raw video as base64 for http\n",
      "transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control bar at the bottom with a play/pause button and a location slider."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML\n",
      "from base64 import b64encode\n",
      "video = open(\"../images/animation.m4v\", \"rb\").read()\n",
      "video_encoded = b64encode(video).decode('ascii')\n",
      "video_tag = '<video controls alt=\"test\" src=\"data:video/x-m4v;base64,{0}\">'.format(video_encoded)\n",
      "HTML(data=video_tag)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<video controls alt=\"test\" 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       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "<IPython.core.display.HTML object>"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "External sites"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia\n",
      "page for mobile users:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import IFrame\n",
      "IFrame('http://ipython.org', width='100%', height=350)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "        <iframe\n",
        "            width=\"100%\"\n",
        "            height=350\"\n",
        "            src=\"http://ipython.org\"\n",
        "            frameborder=\"0\"\n",
        "            allowfullscreen\n",
        "        ></iframe>\n",
        "        "
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 31,
       "text": [
        "<IPython.lib.display.IFrame at 0x107c1ecd0>"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Links to local files"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "IPython provides builtin display classes for generating links to local files. Create a link to a single file using the `FileLink` object:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import FileLink, FileLinks\n",
      "FileLink('Cell Magics.ipynb')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<a href='Cell Magics.ipynb' target='_blank'>Cell Magics.ipynb</a><br>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 33,
       "text": [
        "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/IPython Kernel/Cell Magics.ipynb"
       ]
      }
     ],
     "prompt_number": 33
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Alternatively, to generate links to all of the files in a directory, use the `FileLinks` object, passing `'.'` to indicate that we want links generated for the current working directory. Note that if there were other directories under the current directory, `FileLinks` would work in a recursive manner creating links to files in all sub-directories as well."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "FileLinks('.')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "./<br>\n",
        "&nbsp;&nbsp;<a href='./Animations Using clear_output.ipynb' target='_blank'>Animations Using clear_output.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Background Jobs.ipynb' target='_blank'>Background Jobs.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Beyond Plain Python.ipynb' target='_blank'>Beyond Plain Python.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Capturing Output.ipynb' target='_blank'>Capturing Output.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Cell Magics.ipynb' target='_blank'>Cell Magics.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Custom Display Logic.ipynb' target='_blank'>Custom Display Logic.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./example-demo.py' target='_blank'>example-demo.py</a><br>\n",
        "&nbsp;&nbsp;<a href='./Index.ipynb' target='_blank'>Index.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./ipython-completion.bash' target='_blank'>ipython-completion.bash</a><br>\n",
        "&nbsp;&nbsp;<a href='./ipython-get-history.py' target='_blank'>ipython-get-history.py</a><br>\n",
        "&nbsp;&nbsp;<a href='./ipython-qtconsole.desktop' target='_blank'>ipython-qtconsole.desktop</a><br>\n",
        "&nbsp;&nbsp;<a href='./ipython.desktop' target='_blank'>ipython.desktop</a><br>\n",
        "&nbsp;&nbsp;<a href='./Plotting in the Notebook.ipynb' target='_blank'>Plotting in the Notebook.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Raw Input in the Notebook.ipynb' target='_blank'>Raw Input in the Notebook.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Rich Output.ipynb' target='_blank'>Rich Output.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Script Magics.ipynb' target='_blank'>Script Magics.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./SymPy.ipynb' target='_blank'>SymPy.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Terminal Usage.ipynb' target='_blank'>Terminal Usage.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Third Party Rich Output.ipynb' target='_blank'>Third Party Rich Output.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Trapezoid Rule.ipynb' target='_blank'>Trapezoid Rule.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='./Working With External Code.ipynb' target='_blank'>Working With External Code.ipynb</a><br>\n",
        "./data/<br>\n",
        "&nbsp;&nbsp;<a href='./data/flare.json' target='_blank'>flare.json</a><br>\n",
        "./gui/<br>\n",
        "&nbsp;&nbsp;<a href='./gui/gui-glut.py' target='_blank'>gui-glut.py</a><br>\n",
        "&nbsp;&nbsp;<a href='./gui/gui-gtk.py' target='_blank'>gui-gtk.py</a><br>\n",
        "&nbsp;&nbsp;<a href='./gui/gui-gtk3.py' target='_blank'>gui-gtk3.py</a><br>\n",
        "&nbsp;&nbsp;<a href='./gui/gui-pyglet.py' target='_blank'>gui-pyglet.py</a><br>\n",
        "&nbsp;&nbsp;<a href='./gui/gui-qt.py' target='_blank'>gui-qt.py</a><br>\n",
        "&nbsp;&nbsp;<a href='./gui/gui-tk.py' target='_blank'>gui-tk.py</a><br>\n",
        "&nbsp;&nbsp;<a href='./gui/gui-wx.py' target='_blank'>gui-wx.py</a><br>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 34,
       "text": [
        "./\n",
        "  Animations Using clear_output.ipynb\n",
        "  Background Jobs.ipynb\n",
        "  Beyond Plain Python.ipynb\n",
        "  Capturing Output.ipynb\n",
        "  Cell Magics.ipynb\n",
        "  Custom Display Logic.ipynb\n",
        "  example-demo.py\n",
        "  Index.ipynb\n",
        "  ipython-completion.bash\n",
        "  ipython-get-history.py\n",
        "  ipython-qtconsole.desktop\n",
        "  ipython.desktop\n",
        "  Plotting in the Notebook.ipynb\n",
        "  Raw Input in the Notebook.ipynb\n",
        "  Rich Output.ipynb\n",
        "  Script Magics.ipynb\n",
        "  SymPy.ipynb\n",
        "  Terminal Usage.ipynb\n",
        "  Third Party Rich Output.ipynb\n",
        "  Trapezoid Rule.ipynb\n",
        "  Working With External Code.ipynb\n",
        "./data/\n",
        "  flare.json\n",
        "./gui/\n",
        "  gui-glut.py\n",
        "  gui-gtk.py\n",
        "  gui-gtk3.py\n",
        "  gui-pyglet.py\n",
        "  gui-qt.py\n",
        "  gui-tk.py\n",
        "  gui-wx.py"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Rich output and security"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The IPython Notebook allows arbitrary code execution in both the IPython kernel and in the browser, though HTML and JavaScript output. More importantly, because IPython has a JavaScript API for running code in the browser, HTML and JavaScript output can actually trigger code to be run in the kernel. This poses a significant security risk as it would allow IPython Notebooks to execute arbitrary code on your computers.\n",
      "\n",
      "To protect against these risks, the IPython Notebook has a security model that specifies how dangerous output is handled. Here is a short summary:\n",
      "\n",
      "* When you run code in the Notebook, all rich output is displayed.\n",
      "* When you open a notebook, rich output is only displayed if it doesn't contain security vulberabilities,...\n",
      "* ..or if you have trusted a notebook, all rich output will run upon opening it.\n",
      "\n",
      "A full description of the IPython security model can be found on [this page](http://ipython.org/ipython-doc/dev/notebook/security.html)."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Rich output and nbviewer"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Much of the power of the Notebook is that it enables users to share notebooks with each other using http://nbviewer.ipython.org, without installing IPython locally. As of IPython 2.0, notebooks rendere on nbviewer will display all output, including HTML and JavaScript. Furthermore, to provide a consistent JavaScript environment on the live Notebook and nbviewer, the following JavaScript libraries are loaded onto the nbviewer page, *before* the notebook and its output is displayed:\n",
      "\n",
      "* [jQuery](http://jquery.com/)\n",
      "* [RequireJS](http://requirejs.org/)\n",
      "\n",
      "Libraries such as [mpld3](http://mpld3.github.io/) use these capabilities to generate interactive visualizations that work on nbviewer."
     ]
    }
   ],
   "metadata": {}
  }
 ]
}