stochastic_processes_preliminaries.ipynb

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    "# import of the libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cmp\n",
    "# %matplotlib inline\n",
    "%matplotlib notebook\n",
    "plt.rcParams['figure.figsize'] = (10.0, 5.0)\n",
    "import time\n",
    "import scipy.stats as spst\n",
    "import math\n",
    "from mpl_toolkits.mplot3d import Axes3D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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   "source": [
    "# import supporting module stochastic_processes\n",
    "import stochastic_processes as sp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Geometric brownian motion - change of measure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A plot of sample trajectories of geometric brownian motion process is produced below. \n",
    "\n",
    "The process has the dynamics:\n",
    "$$ dS(t) = \\mu S(t) dt + \\sigma S(t) dW(t) $$\n",
    "\n",
    "The process can be interpreted to be price of a stock that does not pay any dividends. Let's assume that this is the case. Suppose that the stock we are analysing follows the process with the following parameters:\n",
    "$$ dS(t) = 0.1 S(t) dt + \\sqrt{0.2} S(t) dW(t) $$\n",
    "\n",
    "under the real-world measure $ \\mathbb{P} $."
   ]
  },
  {
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   "source": [
    "# fix the parameters...\n",
    "x_0 = 100\n",
    "n = 500\n",
    "d_t = 1/250\n",
    "mu = 0.1\n",
    "sigma = 0.2\n",
    "\n",
    "# ... and produce trajectories\n",
    "trajs = []\n",
    "for k in range(5):\n",
    "    trajs.append(sp.do_gbm_trajectory(x_0, n, d_t, mu, sigma))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
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       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
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       "        targ = targ.parentNode;\n",
       "\n",
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       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
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       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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T+6x8cuHs/jLhCzK8wnqz5czjhPNYFcgij1x7/Xjf5rFPn8fioz3iW/+8z3uBwLY8LwnnO+IoRw0TfyFKv/mKntFURRHEiBzhKyLeXyM+g3Qh+D9Y2JMLvdt3L5nk0cBAjdajHSz/fhnW8L4ku9x/4tD+oA51Mf3i7gRP9/HfRnq/4gGOhpCDhom/u4LEO4MmALXOMohItCoJ8N9mE/cdItfusW9GxpeBjmW+MYwPLt5D05kI3CZ/sISxkloXGoJ18VPHk7xAf+CyNgTL9ijwCf+SEj9WMOUQIYS/xINH3I3C8E13G+BKVp9KUbjxZ+R/38DhPsL7J85Y0hdsEexJW4o7wd/5CDwM1sA+/eddYGrYI78INP1xYjv1PML+H/vGfON7Ia+NoVsmLY5bSfk796ciuDubeNjlVPvL2C+D3/r424M1/u35zwG8pHGBenVM3oHXTB7bd72xFlok08OAt8zU1H/fjbIh309ATI01rqACiEfRr6G94dJu3u6qXYFohjO75F0i23pDcz/MY97oI+KD3rC+Y6ayUFwv735sC/7lsh/Khpf9oqiKEERA3MlTsJ7grh1GNAyyBLsvo0r42ttgU3aBQjcaDHSz/bjnw3/P2L5HvdQiz/jBR/qRpBBDoL7ASpAcI0+Y7jUAcj8vlQff2sPa7aPXzrsf4h7WNwbM/E8UsRfIIph35Ap9Ljbzf8KlgRI70M+zCGDxrEdzvO2fIl08Wc0oht6vwCtX/wZjXSnIY9O+EvXl0DvUoN8RKb4Kw6QT1PF39kedzdk/vk5nvMPLWGM3sFRkB524+On3Zz2HDSP+OsCswf8H5APer7zKI0RMyr+vMmBij9FURQAsvqc8TK2ztt6yuP2tkNcY7hWgY1fAVpG/IV62GcOgmtINxYj/YIA4QoQuPx6wywff3s79YL/ck6H/Q9xPMyhwYEaU3Y8jeB+JH3Jhv/6NgjlML9AFMO+IVPgcX8uiDSCpRdk6Kwx/C/QfEIrkT7sMx+Nu1+AlrkfctB48VfscQ/Ug9/QdH1pqvibh+Z572XDtK0pwz6LA+QT7LBP473mO+wTMFcvnghZHdn3A4/RO/gQzLlrVbBfZCgHzSP+jIW4jvrJF5CVTtui+Gsrwz6d8p8KFX+KorQA1knM1lUA/+5xe8BPvBiYS5QX2PgXoGXEXwX8b6Z9uiV+sAu+WHs8G7rcfjAYe7y9HyBcAQKXn3XyvL+v6tfCfzmnw/8PsdGjuAYNp7ELvlxsscffHLgUmPNbnFZjNfZ+9F1wKBv+7ylfimHfkFngcf8azr0ZjcEQaCUNiGNd8OXHDuGMXnC7xRiK0XjxF+yCL0ZPSb6Pn/V+6Y6G0RL3Qw4aL/5Wetx9V5gMlvWe+L8PEK6p4s/63ju3gTY6kW1J1+lD0kZPGH8LvhQHyMfolXP6GGjt/bVb7dpYFCgPsu2G7/Nk9A7+E+bccH8fLHLQPOLPWAxls0O6T6Ntij9rW+U0P3HbQbafIuovJBfsb28+7Mu+qfnnQMWfoijNTAaC29vPuvlwXxv3N+0iwXsftwIb/wK0jPhzysMI8w3qN9INv3wf9ziYizS8B+eeFKD+MMtA3OlJ+98BwhUgcPkZjRFC9vvzJQnmtTRU/BmisRYyzMkJ3zJIQeO2ejCWXCe8N7z25U1PmELYLx1/Lswv/Hf4+GXD/z3lSzHsGzKnWdJfECCN9vD+OBFILBqNyiNB2GfFmIf4HuwXxrgc5nWPs/EvRuPFn/VD0N/8hDEarXbPXArMPQCfh/PiN7Govzpxc98POWi8+BtmSf9Gh/iACGTfLWnWeOLmBojbVPEXB+nRIJpvq4ddMPcqtTLcEuZnPn5TEVxj2NhCxd8HkDjIwixOQtwYerob5sbpvvZ+DZn7vtUT1t82QzloHvF3G8z3g11ZDoR8RGmL4u8UAN96/J71E/dXlvR9P2IE+9ubD/uyb2r+OVDxpyhKMzMa0nB/DbIPn3Uz8g6QDXyNr5uEbMRtZZrF73cwJ7mnQBpyNTBfhAU2+RegZcSfsdLZPTCXYe8KaSwZcac7xM+38RsBs7G4CdKYsDaGToOI362Q/csagrGnVQ2AHzmEK0Dg8ouFbJRLyMqR1qXQL4CsKmbUUUPFXzuYq1qehIgS62qICZBGWx6kDnwxGinGvWXdDy8RsmiB75DiTjAbLjPhXwRYN/V+HzIfFZDy+CnML6+BNvUORDH8N2SMr8jGPXS2xS8OMn92HmQY3VCfeG9Bhm9ZN8vuAGnAHoNz48If1k3eX4ZZn+0hz78xT6i5Nnk3hqMRMhzc2OQ9AcBvYC4W5e+Zu9YS/3XIxwzDzlgAZwGYAREQvvuKNvf9kIPGiz8AWAHzQ8rD8B7+aLyL/wB5Vn03UDd6gvfA/z6BQNPFHyD3kHWT9yEwn8EOkN7BVTY2OpFtse0YRFgam3rHQeYpG9ssbEH9YcNTEVxjuB3Mnu2jkLmgxoe7TABrPX5u2M/Rg8cuWo73bML81SfMcJswQPOJv34we7pfgXlPtIe8Pw7D+50farsCUYzmE3+A9ybreTDfM50gQ3WN94Dd/OFgf3vz4f8ZaUr+OVDxpyhKMzMK3j9SRiP+KMwfeON4F/X3youHNBSNMG5PXOOH53W0jgVf8mH+IBsNTOv1rYC9iLDGt+MKmL1XhLzUv0X9VdZ8l3YPRBzMBUMI6fEo9hw/t4QrQODyA6TBZt26oxzmCoMn4D35P9snbrrFL90m7VNh7j9mHKUwN+Q23Oy24gDko4E1XDmkoWddltyXJ33Cfw4pmz/6hJsE7y/cpTDnyxk/nt9DfbId8valGP4bMjGQr/7W66uA3CM18C4za0Mjx8evAlIm1nR2oOHDHwERWdZ0SuBdRtvgf3uLYjRN/AHm5tLW94Vxb74A6QUm/G9fcouPvSch5em7dclkm7jNeT/koGnirz3M+dHGUQbv96lx+Aq8fpbrqIUsWFLsOawiLNC71CAfzu+962FfB9Z7Oj1AHlayLfHGwazLY/B+lxbDfs7mVIt/IHrBeyXeKpg9ykb5Bdq31NijjZAPNb7cDO+yset9A5p3tU9jQRHjOAazXPfD3B/X7p5uql2BKIbzeyQdge+jQPk/YknD9z1DyEdLu6kgwf725sP5GWls/jlo3rJXFEUBIHPe7oB8rd0FaXDUeP7ugixYMdohfkfIC2s3zB/SzZBGWiycX2YFCCxeAjVYsuH/Rywf5gs6BmZP3HHI9X0I+0aiXXx/dIfYvwXygq+BNCr/DWnMXYH6w7SCoZcn/n54N7SmWsIUIDjxB0jPweswG/ufQ0Sv0dhtrPgzuAwisD+HNHiqAPwPwDuQHld/8x8AGfryJGRYYCWk/HZBerZ+ahO+A6THbDu8l8nPtwnbD8DjnrRPQur9U4jo9P2YYZAN//eUL8UILIgGQFbD3enJvxoyzHgTgEWoPweuJ2T43wsQkfetJ863kDq/Hf4blMFwPuSr80FIPR3z2PJ/cB5yWoymiz9Aeh82QMriOOSZvBnyjP7Nk4fvXBgr6ZBy2wa5V4wPOlshK/ZeAv/7vTXX/ZCDpok/gwsg87H2QkS/C8CXnrjz4X9z9SGQsvsK3o3MdEuYUIk/QHrK/gR5TsshH5GKID3KV6JhQ0Kz4V2+gzzpfAW5P/dB6tt3KK/BVDSsMdwR8hHkI8j9Y7wPn0FwcxmNOZqEd4+9QT+Lf4FDOjlBhJmKxok/QHrat0Duo3LI+2cBgGQ439NNtSsQxWh+8QfIR81XIM+PC/IBbT1kBIHTfpDB/PbmI/Az0pj8c6DiT1EUpUnkI/ALWnHGuiBOQ7YWUJSGEgNz5V27lRYVRVEURVEUxS/5UPHXVIZByrAajevBVJRguRpyr9XAe+6ooiiKoiiKogQkHyr+mkIiZNgKIcOHFKWp/BnSq5dmcesGWajFmN+V3/JmKYqiKIqiKJFOPrQx2Vj2wHuhiQnhNUdpI3wG856qhPdiG4TMPUwOm3WKoiiKoihKxJIPFX+NpQSyUMAWABPDbIvSdrgC8jzuhCyAYCxksx7ATdChxYqiKIqiKIqiKIqiKIqiKIqiKIqiKIqiKIqitEoYExOjhx566KGHHnrooYceEX0guH1xFSV6iYmJoaIoiqIoiqJEOgDc4W5bK0qrRsWfoiiKoiiK0haAij9FcUbFn6IoiqIoitIWgIo/RXFGxZ+iKIqiKIrSFoCKP0VxJpD4c7vddLlcerSRw+12t9DrV1EURVEUpWWBij9Fccaf+HO73Tx8+DB37drFnTt36tFGjl27dvHw4cMqAhVFURRFaXNAxZ+iOONP/BnCr6SkhFVVVWHvsdKj6UdVVRVLSkrqBKCiKIqiKEpbAir+FMUZO/HndrvrhJ/S9jAEoPb+KYqiKIrSloCKP0Vxxk78uVwu7ty5k1VVVWF4bJXmpqqqijt37qTL5Qq3KYqiKIqiKCEDKv4UxRkn8afioG2i9asoiqIoSlsEKv4UxRkVfybz58/ntddeG24zmp1orV9FURRFUdo2UPGnKM5EqvhLSEioO2JjY9m+ffu685tvvjmstk2ePJl33313i+b56KOP8rzzzmN8fDwnTZrkGDYS6ldRFEVRFKWhQMWfojgTqeLPyrBhw7hkyRLHMNXV1S1kTdPFX2NsXbVqFdesWcNbbrlFxZ+iKIqiKFEJVPwpijNtVfytW7eOaWlpXLx4MXv27Mnhw4eTJCdOnMgePXowKSmJWVlZ3LJlS12c2bNnewmnwsJCjho1iqmpqczIyGBubq5XHvn5+RwwYACTkpKYkZHB1atXMzc3l3FxcYyPj2dCQgIHDx5Mkjx06BDHjx/PLl26MD09nQsWLGBtba1fW0ePHs0HH3zQK78JEyZw3rx5jmXhew12RFr9KoqiKDYUFpKlpeG2QlFaFVDxpyjOtGXxFxsby9tvv52VlZWsqKggST755JMsLS1lVVUV58yZwz59+tRdp1U4lZWVsVevXszLy6PL5WJRURH79u3LtWvXkpSetrS0NG7YsIG1tbU8dOgQd+zYQdK+52/o0KG87rrrWF5ezqKiImZkZHD58uV+bX3llVd41lln1cU/cuQIO3bsyP379zuWhYo/RVGUNs7hw2R2NgmQU6aE2xpFaVVAxZ+iOBO0+Ovbl0xJaf6jb98GP+hO4q+8vNxvPJfLxbi4OBYWFpL0Fk4rV67kkCFDvMIvXLiQV111FUlyxIgRXLRokW26vuLvwIEDjImJ4dGjR+vclixZwqFDh/q11eVysWvXrty6dStJcunSpRw2bJhjOfheg9N1q/hTFEWJUK6/XoQfQKanh9saRWlVQMWfojjTlsVf9+7dvdxqamo4c+ZMZmZmMikpicnJyQTAjRs3kvQWTgsWLGB8fDyTk5PrjsTExLrho/369eOrr75qa4+v+Nu4cSNTUlK8wrz22mvMyMjwaytJ3nnnnZw+fTpJcvDgwXz66acDloWKP0VRlDaI2y1/9+wh27Uju3QhO3Ui27cnPVMIFEVR8acoAWnLwz7T0tK83FasWMF+/fpx7969dLvddLlcjI+P54YNG0h6C6fnnnvOsadt5MiRfnv+pkyZYtvzV1JSUufm2/PnaytJbt++nV27duW2bduYkJDAsrIyh1JgvWvwR6TVr6IoSlTz1Vdk167k7NkyzBMgH3qIvOAC+f+//zXDVlSQn38ufxUlCoGKP0VxJprEX25uLgcMGMCSkhJWVlZyxowZjI2NtRV/paWl7N27N5944gmePHmS1dXV3LFjBzdv3kxS5vz16NGDmzZtotvt9przN2PGDE6cONEr7wsvvJDTpk1jRUUF9+zZw8zMTD7++ON+bTUYNGgQzz33XF5zzTWOZVBdXc3KykrOmjWLEydOZGVlpd/6i7T6VRRFiWpeftkc5hkbS3bvTp44QV59tbgVFEi4EyfItDRx692b1He8EoVAxZ+iOBNN4q+srIxjx45lYmIie/fuzby8PCYnJ9uKP5LcvXs3x4wZw27dujElJYVZWSwQUU4AACAASURBVFl866236vyfeuop9u/fnwkJCczMzOSaNWvq4g0cOJDJycm84IILSJIHDx7kuHHjmJqayj59+nD+/Pn1Vvu0Y9myZQTA9evXO5bB7NmzCcDrGDFihG3YSKtfRVGUqOaBB0zxB5CLF4v73Lly/tRTcr5xo3e4oqLw2awoYQIq/hTFmbYg/kLFrFmzOKWVrZz2xhtvMD09nW5jvkcIiNb6VRRFiUimTjUFXd++5pDOZ54Rt9mz5XzZMm/x9/bbYTNZUcIFVPwpijMq/gS3283Ro0dz7ty54TaljsrKSl5yySV84IEHQppuNNavoihKxDJkiIi5bdvII0dM9w0bxP0Xv5Dzm26ScyP8smXhsVdRwghU/CmKMyr+hIyMDGZlZfHQoUPhNoUk+e6777JTp04cPny443YVjSEa61dRFCUicbvJzp1lZU/fVT2/+EJE3g9/KOeG6PvDH+Tvb3/b8vYqSpiBij9FcUbFX/Sh9asoihIhfP21CLkf/KC+n9tNnnIKmZoqwjAhQbZM+uc/Jc4VV7S8vYoSZqDiT1GcUfEXfWj9KoqiRAgffOA9tNMXo7dvzRr5e/HFMjQUIL///Za1VVFaAVDxpyjOqPiLPrR+FUVRIoTly0XIzZtn73/ffeJ/7rny9/bbxT0lRXoCQ7hYWKvmhRfIzz4LtxVKKwAq/hTFGRV/0YfWr6IoSoRwxx0i6v76V3v/f/3Le4XP998X9/PPl/Ovv245W8PFhx+avZ5K1AMVf4rijIq/6EPrV1EUJUL48Y9F2PznP/b+bjfZq5eEyc423SdOFLdNm1rGznCQl0cOGkSOHSvXmphYf1EcJeqAij9FcUbFX/Sh9asoihIhdOtGtm9POr2vZ8wg27WT+YEG8+eLIHrwwea3MRxUVUnZWHs9dWN7hSr+FCUgKv5M5s+fz2uvvTbcZjQ70Vq/iqIoEcVXX5nz+ZxwuUjfbYo++8z/KqFtgb/+tb7wA8gXX6wfdscO8tZbycOHW95OpcWBij9FcSZSxV9CQkLdERsby/bt29ed33zzzWG1bfLkybz77rtbLL/Kykpef/31TE9PZ2JiIvv3789nn33Wb/hIqF9FUZSoZ906ETRXX924+Gef3XZ7w4zhsH/8o/w/fbqcz5pVP+yYMeJ39tktb6fS4kDFn6I4E6niz8qwYcO4ZMkSxzDV1dUtZE3TxV9DbS0tLeW8efO4b98+ut1ufvjhh0xOTmZBQYFt+EirX0VRlKhk8WIRLQ891Lj4xtDP2bNDa1e4qayUYa49ephz/IyFby69tH74wYPNnsHly1vWVqXFgYo/RXGmrYq/devWMS0tjYsXL2bPnj05fPhwkuTEiRPZo0cPJiUlMSsri1u2bKmLM3v2bE6aNKnuvLCwkKNGjWJqaiozMjKYm5vrlUd+fj4HDBjApKQkZmRkcPXq1czNzWVcXBzj4+OZkJDAwYMHkyQPHTrE8ePHs0uXLkxPT+eCBQtY6/nRsrN19OjRfNBnrsaECRM4z99y3z6MGTOGCxYssPWLtPpVFEWJSq67TgTLm282Lv7nn5MdO8pG8J9/HlrbwsnHH0u5jB5tulVVkfHxMg/wwAHytttkQZijR8mePb2Hhj7wQNhMV5ofqPhTFGfasviLjY3l7bffzsrKSlZUVJAkn3zySZaWlrKqqopz5sxhnz596q7TKv7KysrYq1cv5uXl0eVysaioiH379uXatWtJkqtWrWJaWho3bNjA2tpaHjp0iDt27CBp3/M3dOhQXnfddSwvL2dRUREzMjK43PMF0s7WV155hWeddVZd/CNHjrBjx47cv39/wPIoLy9njx49uGbNGlv/SKtfRVGUqGTQIBErBw82Po25cyWNn/6UbMERMM3Kk0/KNc2Z4+1++eXi3qGDKfR++EP5+73vkevXk7GxZO/e4bFbaRGg4k9RnAlW/PXtK3vGNvfRt2/DH3Qn8VdeXu43nsvlYlxcHAsLC0l6i7+VK1dyyJAhXuEXLlzIq666iiQ5YsQILlq0yDZdX/F34MABxsTE8OjRo3VuS5Ys4dChQ/3a6nK52LVrV27dupUkuXTpUg4bNsyxHEiytraWkyZN4siRI+t6Fu2uW8WfoihKK6amRnrsUlKatlF7eTl5xhkigIJZ0Oyzz8hHH22dWya8+y6ZmmruYfjyy97+X39N9ukjfpdd5r0a6JgxEuY735HVU5tSpkqrBir+FMWZtiz+unfv7uVWU1PDmTNnMjMzk0lJSUxOTiYAbty4kaS3+FuwYAHj4+OZnJxcdyQmJtYNH+3Xrx9fffVVW3t8xd/GjRuZkpLiFea1115jRkaGX1tJ8s477+T06dNJkoMHD+bTTz/tWA5ut5s33HADs7KyWFpa6jecij9FUZRWTlGRiJaLLmp6Wp9/bu4FuHev/3CHD5tiad26pucbakaN8h6+aXctBw6Qjz0m8wInTTLD/uY34j9woJxbPsYqbQuo+FMihOkAPgZQBeBlH78BAN4DcAzAVwCWAIi3+PcC8DaAcgDFACY3JOO2POwzLS3Ny23FihXs168f9+7dS7fbTZfLxfj4eG7YsIGkt/h77rnnHHvaRo4c6bfnb8qUKbY9fyUlJXVuvj1/vraS5Pbt29m1a1du27aNCQkJLCsr82uP2+3mjTfeyEGDBvHYsWN+w5GRV7+KoihRxyuviEj51a9Ck95tt0l6r7ziP8zPfmaKpTlzZDuFl1+W3sPWwIQJpn1JSYF7J/PyzPCPPSZul14q5zt3Nr+9SliAij8lQvgZgCsALEV98bcdwJ8ggq8ngM8AzLD4vw8gD8ApALIBlAEYGGzG0ST+cnNzOWDAAJaUlLCyspIzZsxgbGysrfgrLS1l7969+cQTT/DkyZOsrq7mjh07uHnzZpIy569Hjx7ctGkT3W6315y/GTNmcOLEiV55X3jhhZw2bRorKiq4Z88eZmZm8vHHH/drq8GgQYN47rnn8pprrvF7/W63mzfffDN/8IMfeA0t9Uek1a+iKErUkZMjIuXPfw5Neo8/Lun5WzSspkYWTDHEUvfu5v+nn978w0BPniTfeot0+nhpXbXT8/HUkf/8xwy/fr24TZ3qfa60OaDiT4kwclBf/B0H8EPL+SIA+Z7/TwNQDSDV4r8SwCPBZhhN4q+srIxjx45lYmIie/fuzby8PCYnJ9uKP5LcvXs3x4wZw27dujElJYVZWVl866236vyfeuop9u/fnwkJCczMzKxbYGX37t0cOHAgk5OTecEFF5AkDx48yHHjxjE1NZV9+vTh/Pnz6632aceyZcsIgOsdfqj27t1LAOzQoYPX/oe33XabbfhIq19FUZSooLKSXLuWrKgwe7k80xKazObNkt4VV9j7HzhgiqquXU3RFBNj7hVYWUleeCF5112hscngk0/I735X8undm7Sswu2FMYfv5z937sE0cLvNOMaiObNmyflf/hI6+5VWBVT8KRFGDuqLv7kAlgHoAKA3gJ0ArvT4jQdwwCf8TADrgs2wLYi/UDFr1ixOmTIl3GZ48cYbbzA9PZ3uEE5Oj9b6VRRFadUYG5WfdpopvgIM4w+asjIRcpmZ9v7GhvLXXUeOH28OrTS2m1i1inzpJdOuUGIIXWNT+h/+sH6YEyfMVTsbwgsvSC+qwSOPSDqPPNI0mxtDVRX5zjttZ9XVVgpU/CkRRg7qi78fQgRfDQACeAZArMdvCoBtPuFvBPCRQx7zIA+GcdR7cKJRHLjdbo4ePZpz584Ntyl1VFZW8pJLLuEDId6TKBrrV1EUpVVTViZiy+hpA2SVzlBy+umS7vHj9f3+/GfxW7CAzM2V/2+5xdxWYfZscuJE07ZQfZA0eufat5cezw4dZPN2X4whnKNGNS2/v/xF0vHZjqnZqa2VHkuAvOOOls07yoCKPyXCyIG3+OsMoBTALZA5f10BrIEs+gJIz99+nzRmQHv+GkxGRgazsrJ46NChcJtCknz33XfZqVMnDh8+3HG7isYQjfWrKIrSqlm+XITB1Knkp59Kj9WuXaHNw1jQZdOm+n6/+Y34vfSSDO989FGypITculXchw2TDeMN8XfkSGhs2rXLew5fz54y99BXXL7xhoS7+eam5ffee8FvexFK/vAHs+zi48kg9uxVGgdU/CkRRg68xd8gAJU+YcZAVvUE7Of8PY8om/OnNAytX0VRlFaGsRm5Z1GxZmHBAv+9XmPHit+nn3q7V1SQ7dp5b7EAkNu3h8YmYyGae++V83POse+dXLZM3Js6EmbnTknn0kublk5DMbaYmDJF/t5wQ8vm31y43bIibKiGJ4cAqPhTIoQ4AB0B3A9gtef/9gCSAJRAhnK2g/QErgbwN0vcDyBzAk8BcDGicLVPpWFo/SqKorQidu8WQXDmmc27+fgXX8iwyqSk+vvcnXWW2GC3R2znzt6rbALk2283zRaXixw50kzXSG/4cDn37RmbOTM0C7UcPSrpDBzY+DSKimRTYt9N5v1x7BgZG0ump5v59+9v+u/aJeURibz+ulxPRkbz3rsNACr+lAghBzKfz3oUePwuBrAZss/fN5CewZ6WuL0AvAOgAsDniMJ9/pSGofWrKIrSipg7VxrQ99/f/HkZ+/3NmmW61daKKOze3T7Oj38sca6+2tyCYsWKptnx2Wem8EtIMEWnMS9u61bv8MaiME3tGXW7ZX6h3bzCYLnvPrFlwoTgwr/9toSfPFnOe/eW3tSTJ805iLm5jbcnnNx7r1mPzz0XbmtIqvhTlICo+Is+tH4VRVFaCW63ubpnS8wD++9/ycRE6Yl6/33y8GERdYBs42BHYSE5f75s9m7MTbzvvob19OzbJ4vaGBhz+AYPFiFocPPN9XsWjx4Vgdipk33PZEPp00euv6amcfGNHsvTTw8u/Jw53ns2XnaZnP/rX+SAAeYqq5GIMY/UWKW2FfT+QcWfojij4i/60PpVFEVpJXz0kbPwag6ef17yTE83hR9APvRQ4LiGaEtKIlNSSM8+uX6pqiKvv97sOTSwri5qxehJWrnSdHvoIXH71a+Cv0YnjPmVX3wh54cPB7+AjcslItTYA9EqaP2RnS3hd+yQ87vuMsvDKPtLLmnctYSC48elvCsrGx63Xz9zZVpAhjCHGaj4UxRnVPxFH1q/iqIorYTbb5dGc15ey+Y7ZowpPE49VQRQMPzrX94Lv5x1lvN8NWOrCGOVS6Nn6J57xO35573DP/yw9zBIt1uGSYZSWBh7F772mgx57dOHTE6WXlE7rL1Zmzd7X7/dyqlWXC7ylFNEKNfWituzz9ZfQOfMM0NzbY1h4UKx4Sc/aVi8EyfMvSON3s1HH20eGxsAVPwpijMq/qIPrV9FUZQwMm0aecEF0tPSrRsZF0d+803L2vDJJ6bwuPPO4OMdPlxfuDjNVzO2kDCOwkJxnzxZzj/4wDt8fr64G3vuGqtz/uhHDbs+J554wpz3uG+fadugQfWF7N//LsNkX3pJzh94QMJ27eo9lNMfW7ZIuJ/+1HT79FMzz379RBgmJIRvyOTll5v2vPFG8PH++U+JM24c+eGH8n9T92EMAVDxpyjOqPgzmT9/Pq9t6b1/wkC01q+iKErYcbtlyCRg9n6NGRMeW37xCxEd+/YFH6e21hQKP/pR4CGrxpwwY9GYp58Wd2PV0OJi7/DG6pG33SbnvltBhAJDUF50kazYaRWn69aZ4SoqZBVLY26iy2We33+//A2076DRk7lwoXe6sbGmePz+9+X/kpLQXWNDGDLEvP5x44KPZ/Tq/u53Mn+yc2dZOChc1+EBKv4UxZlIFX8JCQl1R2xsLNu3b193fnNTN4FtIpMnT+bddvsoNSP33HMP+/Tpw6SkJPbs2ZO//e1vWV1dbRs2EupXURSlTfL112ZD29g/78UXw2OLy9W4hrph/5o1ZK9ech1r1pB//GP93qvzzpOwRm/bjTeKu7Hoiu/vlDGs8he/kHOjh/Cttxpupz9qa8nUVNm03ph/N3iw/LX+dhursBrHjBny97LLRLQa8ZwYP96+hzM7W4ZLVlSYPW+h2jtx9WoRuMHSpUvjhp/ecYfEMXpFb71Vzn/zm4bZG2Kg4k9RnIlU8Wdl2LBhXLJkiWMYf0KoOWiq+GuMrYWFhSzzTDw/fPgwL7roIi5atMg2bKTVr6IoSsQyb57M6zNE0caN3oIiJaVxC22EkxtvlJUuy8vNxVz8zYFLTZUFUgzRe9ZZIvjatZO5fL4UFXkvgGKIxFCs8mll9GjJxxA+q1bJ3/POE/99+6QX65RTZFis7zW63eR3vyu2+e6ZaOB2y/YZ7dvXr2OXS8qPNFc4bciQS3/8+9+S1rBhwYU39h085xzyO9+ReZn+2iCVleSiReb8UGNPRmMo79dfy/zRuLiwLvwCFX+K4kxbFX/r1q1jWloaFy9ezJ49e3L48OEkyYkTJ7JHjx5MSkpiVlYWt2zZUhdn9uzZnDRpUt15YWEhR40axdTUVGZkZDDXZ15Dfn4+BwwYwKSkJGZkZHD16tXMzc1lXFwc4+PjmZCQwMGer4KHDh3i+PHj2aVLF6anp3PBggWs9Uz+trN19OjRfPDBB73ymzBhAufNmxewPA4fPsxhw4bxpptusvWPtPpVFEWJSE6eNAWD0btnzGkzjltvDa+NjcUQs3/9q/f1WD98lpaago8kzz7bW2gNHVo/3SNHxO8HPzB71wxBFkqM4ZiAiJXKSumJi4mR+ZdXXCF+990nYqdrV5mfaf2oOm2aeT12GEI20EquxhDSxx9v+nXNn29+VLD2wvqbT2jM2xs/XgQjQO7dK34lJSLyjXbHY4+J/6RJkl6XLtJ7at0yY9EiKcNly5p+LY0EKv4UxZlgxV/fR/oy5cGUZj/6PtK3wQ+6P/EXGxvL22+/nZWVlayoqCBJPvnkkywtLWVVVRXnzJnDPn361F2nVfyVlZWxV69ezMvLo8vlYlFREfv27cu1a9eSJFetWsW0tDRu2LCBtbW1PHToEHd4lnG26/kbOnQor7vuOpaXl7OoqIgZGRlcvny5X1tfeeUVnmX8YJI8cuQIO3bsyP0O+0AtWbKEiYmJBMBu3bpx27ZttuFU/CmK0ub45JPQDg0MBR9/bAqM735XenqMVRF/+EPpEQvVUL9w8e23Ip6M7Q+swwa3bxe3yy+X8xUr5LxHD/n7y1/WT6+2VnrT+vQhlywxh1uGmhMnTJsBcbvpJtMuQMSg0WNXUVF/MRhDxE6bZp+Hcb133eVsi/FBYM6cpl0TKYvWGNdkbGVx/LiIOLu9BFeuNG288Ub5/803xe/VV81FaUjymmvkPCaGLCiQ/88/3zu9kydlRdgwAhV/iuJMWxd/5cawChtcLhfj4uJY6BmyYBV/K1eu5JAhQ7zCL1y4kFdddRVJcsSIEX6HVfqKvwMHDjAmJoZHLUNDlixZwqGer552trpcLnbt2pVbt24lSS5dupTDghzGsWvXLv7ud7/jF8aL3+a6VfwpitKm6NBBGqNhbnh6YSxWYhwPPSS9JoAM/2wFG2KHhL//XfYrHDhQrs0Y8rd2rZwb+/O5XLK3oFEes2fbp9e1qyxEYywo889/No/dxmIv06fL+YYN5jxMgPzb35zjHz0qQvW737WvS2NIbKB0/vEPCTd1auOuw+B///O+3959V9z/9Cc5T0oyt5sgycWLTSG+fLn02gHmdg0zZ5pplZSQ3/ueeW7s79dUm5sBqPhTFGfa8rDP7t27e7nV1NRw5syZzMzMZFJSEpOTkwmAGzduJOkt/hYsWMD4+HgmJyfXHYmJiXXDR/v168dXX33V1h5f8bdx40ampKR4hXnttdeYkZHh11aSvPPOOznd86M0ePBgPm2skhYEL7zwAn9qXVraQqTVr6IoiiM1NWajdPTo4OIcOyaLdcyc6X+OU1Mx5nItWiSioksXs9H81VfNk2c4mTdPru0Pf5BzQ3QY56QIxdGjRRD+73/26VhFRmZm84rkwkJz7h0pw1jbtSPHjg0u3wsvFDs/+6y+n7HxeaBtPIzhoZ72RaMx9g80ejT/9CcRe6efbpansRDMt996C8X33hORahXrhvi2DtXt00eGlBruixc3zeZmACr+FMWZtiz+0tLSvNxWrFjBfv36ce/evXS73XS5XIyPj+eGDRtIeou/5557zrGnbeTIkX57/qZMmWLb81diWVXNt+fP11aS3L59O7t27cpt27YxISGhbkGXYHj22Wd5xhln2PpFWv0qiqI4YswNM4777/eeh2SH0dAFyAkTmscuYwjef//rvTBKTEzb6fWzYuxf96MfyZDX73xHzo3VIIPFuu9cKLd4CJbDhwPfPwa//73Y+fDD9dMAyP79A6fhcslCKZ06yfDSxrJggeT505+a80nXrfN+Np55RsK+/bbp1qGDCNRdu+R85EiyqsrsTTeEKUBOmWIOXQa8t8ZoJUDFn6I4E03iLzc3lwMGDGBJSQkrKys5Y8YMxsbG2oq/0tJS9u7dm0888QRPnjzJ6upq7tixg5s3byYpc/569OjBTZs20e12e835mzFjBidOnOiV94UXXshp06axoqKCe/bsYWZmJh/3TO72J/5IctCgQTz33HN5zTXX+L3+2tpa5uXl8ciRI3S73dyxYwfPPPPMul5DXyKtfhVFURxZv14aot27m70e99/vHMfopTKOgwdDa5PLJas8dusmQu+LL8i+fSUvz6iPNofbLT1DMTGyEIhRth9/3LB0jhyRzdR/9jNz3lpr5aOP5BqN1UkNVq8Wd2Nri0BceaWEf/31xtsyfbrZGwfIAi7GdhWGeDPaBcYiMw89RH7+ubhVVUmvZ2oq+cor5jNlfU6WLRNhe8oprbYHGyr+FMWZaBJ/ZWVlHDt2LBMTE9m7d2/m5eUxOTnZVvyR5O7duzlmzBh269aNKSkpzMrK4luWBQWeeuop9u/fnwkJCczMzOSaNWvq4g0cOJDJycm84IILSJIHDx7kuHHjmJqayj59+nD+/Pn1Vvu0Y9myZQTA9evX+73+2tpajho1il26dGGnTp2Ynp7OmTNnstLP8uGRVr+KoiiOGJtN5+SYi4ykpzv3rhlL/V98sfx94onQ2mTY8ZOfmG4lJTKkbvXq0ObVmjAECCBDJ++/v232chrU1IhY6tDBHD5aW2sOB/3rX4NL5/nnJbyfVbqD4uc/lzQ2bxZ7unYlR40SN0PMZWVJWGM1U88H7Tp8t+7IyTH/j4+XIaqk3MNLlzbe1mYEKv4UxZm2IP5CxaxZszhlypRwm+HFG2+8wfT0dLpD+OMZrfWrKEob5d57pXH67LNybgi6pUvNRS986dlTVql8/XUJO358aG0y5kjdeWdo023tGL2w55xTf3XMtoqxiM+sWSL8nnpKzgcNCn746JEj0uv2ne8EH8eXoUPNYcYXXCD/x8VJL6zLJXNOO3SQlU579ZL8fIeZVlXJsNu4OPlQUVkpQrF/f/LDDxtnVwsDFX+K4oyKP8HtdnP06NGcO3duuE2po7KykpdccgkfeOCBkKYbjfWrKEob5qqrzBU0SfLPf/aeX2cMazP48kvxO/dcWZo+IUFWQqyqCp1NxrC6vLzQpRkJuN0ifP0t5tIW+egjuX+M4cbnnSf/W/YRDopLL5V4K1c2zo7TTpP4VVWyYqfxDPzoR+JvbNXwq1+Z978dtbWyR6OB2x1RvbdQ8acozqj4EzIyMpiVlcVDhw6F2xSS5LvvvstOnTpx+PDhjttVNIZorF9FUdowWVnSmDXmh33zjdkYt/YIGrz5prhff72cjx0r5x98EDqbjIa2v55HpW3xr3+Zq5PGxsr8zobywQfmnNBrr234tiUJCdK7R8qzEBsr6f361+K2f7/MQzWei9tua7iNEQBU/CmKMyr+og+tX0VR2hTdusnQNmvvRHGxzOMD6m/CPX++OSyUJB95RM7vuy90Ng0Z0jwLySitF2NrB2NVzMZgLMwCkFdfHXy848clztlnm24jR9afd3jPPeJ2xRWy3UMbBCr+FMUZFX/Rh9avoihthmPH/C+p/8034tevn7e7sZXA1q1ybmxRMGJEaGxyu8nOnWXlUeum2krb5rbbTOHW2AWE9u8nb7nFeVimHcZegSNHmm6ffUbedZcMbTZwu8kDByJqGGdDgYo/RXFGxV/0ofWrKEqb4ZlnpNF77bX2/gMGeA8JdbtldcaOHc05fjU1snH1KaeEZt6fITob0nhXIp81a0zxt3t309JKS5MhmsH+Tr//fsN7C9soUPGnKM6o+Is+tH4VRWkzZGdLo/e99+z9jd6Yyy8njx41e0iMRTAMxowR91CsaPjhh5LWlVc2PS0lcigtldU0e/Vqes+aMWTzs8+CC//iixJ+5sym5dsGgIo/RXFGxV/0ofWrKEqbYP9+c4EMf8MrP/+cPPNMCTdunCz+ApC//a13uIcfFveGrvhcUSF7qFmX51+yRNKaM6dhaSmRzwcfyDDipvLrX8s99Je/BBc+N1fCP/xw0/OOcKDiT1GcUfEXfWj9KorSJjAavL/7nXO4sjIRiAB5/vnyd9Uq7zCGkMzMbFivzd13S7wVK+T8v/+V+X7WrScUpaGsWCH30L33Bhd+1qymbRPRhoCKP0VxRsWfyfz583mtv3kjbYhorV9FUdoIbjdZXU3+8pfS4F23LnCcF14w52Odeir59df1wxibwwe75UNtLfnd70qcq64St8mT5XzGjOCvR1F82bpV7qPRo4MLf+21Ev4f/2hWsyIBqPhTFGciVfwlJCTUHbGxsWzfvn3d+c033xxW2yZPnsy77747LHl/9dVX7Ny5M7OysvyGiYT6VRRF8cvIkbKQi9GbV1ISOE5trezrd9VV5M6d9mGefFLSu+GG4OzYsMEUlD16iCjt3p2MjydDvD+rEmWUl8uiRB06kC+/LMM5Kyr8h//xj+U+LCpqORtbKVDxpyjORKr4szJs2DAuESBAzQAAIABJREFUWbLEMUx1dXULWdN08dcUWydNmsSLL75YxZ+iKG2TqipTcAEyny9UlJbKip+nnurc0Db41a/EBmMz7ddek78XXBA6m5To5Y9/9L7X77/ff9jMTAlj3dYhSoGKP0Vxpq2Kv3Xr1jEtLY2LFy9mz549OXz4cJLkxIkT2aNHDyYlJTErK4tbtmypizN79mxOmjSp7rywsJCjRo1iamoqMzIymJub65VHfn4+BwwYwKSkJGZkZHD16tXMzc1lXFwc4+PjmZCQwMGDB5MkDx06xPHjx7NLly5MT0/nggULWOtZoMDO1tGjR/PBBx/0ym/ChAmcN2+e33J48803mZ2dzSeeeELFn6IobZPCQu8GcaiH6htDSV94QfYQ3LxZ5l2tXesd7vhxEYkdOpA33yxxsrJ0xUUldNTWyrDPxERzPqrdwkY1NdLb3LNny9vYCoGKP0VxJljxt2lTX27YkNLsx6ZNfRv8oPsTf7Gxsbz99ttZWVnJCs9X3CeffJKlpaWsqqrinDlz2KdPn7rrtIq/srIy9urVi3l5eXS5XCwqKmLfvn251tMAWLVqFdPS0rhhwwbW1tby0KFD3LFjB0n7nr+hQ4fyuuuuY3l5OYuKipiRkcHly5f7tfWVV17hWWedVRf/yJEj7NixI/fv329bBidOnGC/fv24a9cuFX+KorRd1q71Fn95eaFN/513JN2EBO98YmNlVU+DP/1J3K+/XuYcWsP6CkVFaSy1tbLXnzEftaCgfpiDB7XH2QJU/CmKM21d/JU7zLtwuVyMi4tjYWEhSW/xt3LlSg4ZMsQr/MKFC3mVZ1L/iBEjuGjRItt0fcXfgQMHGBMTw6NHj9a5LVmyhEOHDvVrq8vlYteuXbl161aS5NKlSzls2DC/1/LrX/+aczzLiqv4UxSlzbJokTR0TzlFet327Alt+jU1ZN++5hYSo0eTv/mNiL+EBJmL5XaTp58uYbZvlwb6pZea4u/bb0Nrk6I884zcW9ddV9/PmHtqLDoU5UDFn6I405aHfXbv3t3LraamhjNnzmRmZiaTkpKYnJxMANzoWY7bKv4WLFjA+Ph4Jicn1x2JiYl1w0f79evHV1991dYeX/G3ceNGpqSkeIV57bXXmJGR4ddWkrzzzjs5ffp0kuTgwYP59NNP2+b3ySef8IwzzmBlZSVJFX+KorRhbrxRGrqvvy5z9JqD4mJyyxbvLR8uv1zy3bbN7Gk5/3zT/9gxctAg2UtQUULN8eNk+/Zkly6y0q2V55+X+/Gee8JjWysDKv4UxZm2LP7S0tK83FasWMF+/fpx7969dLvddLlcjI+P54YNG0h6i7/nnnvOsadt5MiRfnv+pkyZYtvzV2JZkc6358/XVpLcvn07u3btym3btjEhIYFlZWW2+S1atIidOnViWloa09LSeOqppzI+Pp5paWkstWkcRVr9Koqi1DFsmDR09+5t2XzvuMPcH/Dvf5f/p071DtOQ/QEVpaFcdpncd++/7+1+//3i/vjj4bGrlQEVf4riTDSJv9zcXA4YMIAlJSWsrKzkjBkzGBsbayv+SktL2bt3bz7xxBM8efIkq6uruWPHDm7evJmkzPnr0aMHN23aRLfb7TXnb8aMGZw4caJX3hdeeCGnTZvGiooK7tmzh5mZmXzc86L2J/5IctCgQTz33HN5zTXX+L3+8vJyfvnll3XHww8/zPPOO49ffvkl3TaNkUirX0VRlDq+8x1Z3KIFV3AmSS5dKg3shQvJRx+V///wh5a1QYluHntM7rtf/9rb/YYbxP3tt8NjVysDKv4UxZloEn9lZWUcO3YsExMT2bt3b+bl5TE5OdlW/JHk7t27OWbMGHbr1o0pKSnMysriW2+9Vef/1FNPsX///kxISGBmZibXrFlTF2/gwIFMTk7mBZ4J2AcPHuS4ceOYmprKPn36cP78+fVW+7Rj2bJlBMD169cHXR467FNRlDbJ8ePSyO3fv+XzNhaCue46c3XP115reTuU6OWLL+S+69mTPHHCdB85Utw96xdEO1DxpyjOtAXxFypmzZrFKVOmhNsML9544w2mp6fb9uA1lmitX0VRIhxjYYvx41s+7/37Je+hQ8mLLpL/9+1reTuU6GbSJLn37rqL/OYb8pxzzIWGgtmbMgqAij9FcUbFn+B2uzl69GjOnTs33KbUUVlZyUsuuYQPPPBASNONxvpVFKUNcN990shdvLjl866pkQU30tLIrl3Jjh3FTVFaki++kP0l27Ujr7xSnoeYGJkPqJBU8acoAVHxJ2RkZDArK4uHDh0KtykkyXfffZedOnXi8OHDHberaAzRWL+KorQBRoyQxu6nn4Yn/zPPNHtZBg4Mjw2KsmyZeR+2a0d+/nm4LWpVQMWfojij4i/60PpVFCXiOHlS9vbr3Fn21QsHY8aYjW7dU00JFzU1ZFaW3Ie//GW4rWl1QMWfojij4i/60PpVFCXi+OADaeyGcx+9nBxzg/l//jN8dihKURF59dXkgQPhtqTVARV/SoQwHcDHAKoAvGzjfwuAPQDKAewDkG3x6wXgbY9fMYDJDclYxV/0ofWrKEpEUV1NXnyxCK+lS8NnR0UFWVBAVlaGzwZFURyBij8lQvgZgCsALEV98TcVwE4A5wKIgYi93hb/9wHkATgFIgrLAAwMNmMVf9GH1q+iKBGFsdDLoEEy/FNRFMUPUPGnRBg58BZ/sQD+C+AnfsKfBqAaQKrFbSWAR4LNUMVf9KH1qyhKxFBdLStstmtH7t0bbmsURWnlQMWfEmHkwFv89QZAALdDhnQeBPAnSC8fAIwHcMAnjZkA1gWboYq/6EPrV1GUVk9tLfnWW+Qzz0iv3+WXh9siRVEiAKj4UyKMHHiLvwsh4u8dSO9eDwCbATzk8Z8CYJtPGjcC+Mghj3mQB8M46j040SoO5s+fz2uvvTbcZjQ70Vq/iqJECF9/ba5maBx/+Uu4rVIUJQKAij8lwsiBt/gbCBF/IyxuEyBzAAHp+dvvk8YMREHPX0JCQt0RGxvL9u3b153ffPPNYbVt8uTJvPvuu1s8z/j4eK9y2bdvn23YSKhfRVGimN//XgRferr8TU4mQ7zfqaIobROo+FMijBx4i79OAE4C+LHFbQKAXZ7/7eb8PY8om/M3bNgwLlmyxDFMdXV1C1nTdPHXGFsbkmek1a+iKFHG1Kki+v7xD9niIVybuiuKEnFAxZ8SIcQB6AjgfgCrPf+39/itAPAWgGQAXQF8CHPYJwB8AGAZZB7gxYjC1T7txN+6deuYlpbGxYsXs2fPnhw+fDhJcuLEiezRoweTkpKYlZXFLVu21MWZPXs2J02aVHdeWFjIUaNGMTU1lRkZGczNzfXKIz8/nwMGDGBSUhIzMjK4evVq5ubmMi4urq4XbvDgwSTJQ4cOcfz48ezSpQvT09O5YMEC1no2KrazdfTo0XzwwQe98pswYQLnzZtnWwYq/hRFaTOMGCHib/fucFuiKEqEARV/SoSQAxneaT0KPH6JAJ4FUArgS3gv+ALI1g/vAKgA8DmicJ8/f+IvNjaWt99+OysrK1lRUUGSfPLJJ1laWsqqqirOmTOHffr0qbtOq/grKytjr169mJeXR5fLxaKiIvbt25dr164lSa5atYppaWncsGEDa2treejQIe7YsYOkvRAbOnQor7vuOpaXl7OoqIgZGRlcvny5X1tfeeUVnnXWWXXxjxw5wo4dO3L//v22ZTB58mR27tyZnTt35jnnnFOXth2RVr+KokQZ3/ueiD8d6qkoSgOBij9FcSZY8dd30yambNjQ7EffTZsa/KA7ib9yh8aDy+ViXFwcCwsLSXqLv5UrV3LIkCFe4RcuXMirrrqKJDlixAguWrTINl1f8XfgwAHGxMTw6NGjdW5Llizh0KFD/drqcrnYtWtXbt26lSS5dOlSDhs2zO+1fPzxx/z2229ZU1PDgoICduvWjS+88ILf61bxpyhKi7NlC7liBel2+w/jdpOdOpFdurScXYqitBmg4k9RnGnL4q979+5ebjU1NZw5cyYzMzOZlJTE5ORkAuDGjRtJeou/BQsWMD4+nsnJyXVHYmJi3fDRfv368dVXX7W1x1f8bdy4kSkpKV5hXnvtNWZkZPi1lSTvvPNOTp8+nSQ5ePBgPv3008EWCefPn89x48bZ+qn4UxSlxZk921y58513/Ic7ckTCDBzYcrYpitJmgIo/RXGmLQ/7TEtL83JbsWIF+/Xrx71799LtdtPlcjE+Pp4bNmwg6S3+nnvuOceetpEjR/rt+ZsyZYptz19JSUmdm2/Pn6+tJLl9+3Z27dqV27ZtY0JCAsvKyhxKwZv777+fY8eOtfWLtPpVFKUN0LmzKf4efth/uH//W8KMHt1ytimK0maAij9FcSaaxF9ubi4HDBjAkpISVlZWcsaMGYyNjbUVf6WlpezduzefeOIJnjx5ktXV1dyxYwc3b95MUub89ejRg5s2baLb7faa8zdjxgxOnDjRK+8LL7yQ06ZNY0VFBffs2cPMzEw+/vjjfm01GDRoEM8991xec801fq+/traWq1at4vHjx1lbW8uNGzeye/fuzM/Ptw0fafWrKEqEU1LivWffTTf5D/v66xLm1ltbzj5FUdoMUPGnKM5Ek/grKyvj2LFjmZiYyN69ezMvL4/Jycm24o8kd+/ezTFjxrBbt25MSUlhVlYW33rrrTr/p556iv3792dCQgIzMzO5Zs2aungDBw5kcnIyL7jgApLkwYMHOW7cOKamprJPnz6cP39+vdU+7Vi2bBkBcP369X6vv7a2lkOHDq0bmtq/f38uW7bMb/hIq19FUSKcTz8VQXf22fL34ov9h/3znyXMwoUtZ5+iKG0GqPhTFGfagvgLFbNmzeKUKVPCbYYXb7zxBtPT0+l2WiChgURr/SqKEiZeflkE3fTpZPv2pPGx6/hx8ssvvcMacwOfe67l7VQUJeKBij9FcUbFn+B2uzl69GjOnTs33KbUUVlZyUsuuYQPPPBASNONxvpVFKWFWL+e/Pprb7dFi0TQ5eaavX8lJWR2NnnqqeT//ifhfv97c2joe++1uOmKokQ+UPGnKM6o+BMyMjKYlZXFQ4cOhdsUkuS7777LTp06cfjw4Y7bVTSGaKxfRVFagE8+EeGWmUl+9ZXpfuut4r52Lfmzn8n/L75oCr3bbyc/+sh7XmBxcfiuQ1GUiAUq/hTFGRV/0YfWr6IozcLcuaZ4O/980liheNQocfvsM/Lee+X/73/fDNuhAzl8uPx/443kypXhvQ5FUSIWqPhTFGdU/EUfWr+KojQJl0t6+XxHJZx/vrlHHyCir7qaPOMMOT9xgnz+ee8evp//3Pw/NZWsqAjPNSmK0iaAij9FcUbFX/Sh9asoEYrbLYukhJtHHhGx1q4d+dRT4vbFF+J2+unksWPkOefI+bPPei/yUllJXnaZ+J1xBllbSz74oPT++dk7VVEUJVig4k9RnHESfydPngzDY6s0NydPnlTxpyjNwXvvkf/3f9IzFmrcbnLqVDI2lrzySlkwJVwY8/YAsmNHcs8e8vHH5fyOOyTMBx/IeY8e8tez7Q1JuZbXXycLC0236uqWvQZFUdokUPGnKM7YiT+3282ioiLu27ePJ06cYFVVFV0ulx4RflRVVfHEiRPct28fi4qKQrp9hKIoJIcNE6Hz5puhT/vpp72HS957b+jzCJbTTiNjYsh77hFbLrqIHDBA/t+8WcK43eSQIaa9L70UPnsVRYkaoOJPUZyxE38kWV1dzYMHD3Lnzp16tLHj4MGDrNav7IoSWmprycREETrz/p+98w6Polzb+JMKoUsvimJFRETsqGD/9NhAPeqxYgHx2I69gSxdwQIKgiBFkGZBUQQEZHY3lTRITyCENJKQ3jdld+7vj3dmdjfZbDbJppHnd11z7e7MO+88s7vZzD1PmyPWhYaK1gfuYMQI4fVbu1Yc45Zbmj9XSUnzw0fLyqzhnTU11jy/ut49APj7bxHy+cUXzbeVYRimCRCLP4ZxTkPiT8VisbS7x4oX9y0Wi6WNfn4ZpouRkGAVQXffLTxfQ4aIsEiTqWVzV1Zac+TMZqB3byE0zeamz5WVBQwfDlxyCRAeDlx9NRAY6Pr+QUHCloceEq+PHxf2EAE//1x/fHNsZBiGaSbE4o9hnNOY+GMYhmFcYPNmq/g76ywgJsb6+ujRls2dlCTmueMO8fq228Tr6OimzWM2A5MmWe065xzxOHas2LZrl/Dk3XuvsN8Rq1eLfebOta4zGICFC1noMQzT7hCLP4ZxDos/hmEYN/DGG0IUeXpaC5+oImvr1pbNfeCAmOf558VrtVfe2rVNm2f3bqs4tc0fVOe6807r62eeESGe+fn2c6gN23/7rWXnxDAM0woQiz+GcQ6LP4ZhmBZiW9xk6tT6wurjj1s2/7p19rmEu3aJ1y++2LR5pk0T+23cCAwYYG/vVVcJUejhAXh7i+3XXiseCwrE/hUVwKhRYvzJky07J4ZhmFaAWPwxjHNY/DEM0ymQZWDRIkCvb29L7DGbgSeeEIJo+HDA37+++Js6tWXHmDNHzKP21Dt9Wry+9FLX56iuBvr1E/30SkuBZcuAK68EcnOBkSOttk6cKJqz29q/eLGY4623xOsHH2zZ+TAMw7QSxOKPYZzD4o9hmE5BYKDjipLtzV9/CbvOPVdU9wSEp49ItERQC7W0hOeeE/McOGBdd+mlYl1Ojmtz7NvXsHBTPYJquOqKFfbib8QIIDlZhLSedZYoGsMwDNMBIRZ/DOMcFn8Mw3QKVO/XwIHtbYk9//2vsOuHH6zrLBbg+++BqCjhVfP0bFnFz9tvF8dISrKuU3Pvtm93bY6nnhLjN2+uv23TJqvQ+/FHIC1NhH6OGQPcd59Yf9ll4nH27OafB8MwTCtDLP4Yxjks/hiG6RRMnGgVKEVF7W2NQJaB884TeXK5uY7H3HOPsPmtt0R/vbocOtRwNVCTSTRHV6tyVlZat+3YIdbNnGm/T2UlUFxsv66oSLSc6NNH5O3VJSPD+t6qAjM0VKw/csRaxMbTUwhDhmGYDgqx+GMY57D4Yximw1BT41jYFRcDXl5WgRIe3va2OSIuTthz3XUNj1m/3iqeJk0SuXcqRUXWc3IUSrlkiXX7oEH229S8v9Gj7dffe68YW1ZmXbdypRj70ksN23njjSI81VEv0DffFPvfd1/D+zMMw3QAiMUfwziHxR/DMB2GF18UzcuPHbNf//vv9jloroY6AsJ79vLLgNHoXlsB4Isv6ve8c0RGBnDNNWLsuHHAe+8Jb9/+/dZzUpum23LjjfbnXZexY8V6o1E0lt+xQ3ghiUThGZWbbxbrDh9u2EaTyd6zaEtFhSi2c+KE8/NkGIZpZ4jFH8M4h8UfwzAdAlkGhg619pizRc2rU0XMggWuz7t4ccPiqaWobRJshVZDZGWJHDrVFi8vIdhsxZ1t+Gd+vvAYenvb9/iz5ZNPxDa1bYOtd3T5cjGmshLw9RW5krLsnvNmGIbpoBCLP4ZxDos/hmE6BGlp9sJo1y4gOFisv+gisX7LFvE4bZrrQuZf/2od8SfLwODBgI+P68VcZBk4ftzaMkFdHn9cPL7zjnXs1q1i3YwZYp/y8vrzxcTUbyuhLtOmiTF6fcOeRYZhmDMMYvHHMM5h8ccwTIdALWAyZIi9iOndWzxecQWQmmpdf9ZZjTcal2XRe49IhJO6k+PHxbzXX9/0fcvLgR49xP6+vkLgenoCw4aJqqZRUUKsEQkR3BCyLHL+iKwhoH36WB+vvho4/3zxetmyZp8qwzBMZ4FY/DGMc1j8MQzTIVC9YZs2Ab/+CjzwADBhglXsvfOOaKhuKwxt2ys4Qi3IonoTzWb32fvDD2Let99u3v6qt+/aa8Vr2xDQgQPF4/DhDefhqaxeLTyQcXGiQMwff4i+fHU9gZGRzbOTYRimE0Es/hjGOSz+GIZpd2RZNG+v28uuvBwYNUqs379frFPz/ohEM/W6hIQAO3cKMaVW2VSX7Gz32Txjhphz587m7f/332L/Dz4QrwMCRFEY2yIvGzY0b261ubzt4k7hyzAM00EhFn8M4xwWfwzDtCsFBcCVVwqB0r9//Vy+hATRqkBdbzIB+/aJ8Y88Yj/2n3/sBc+QIcCdd1o9iO5sEaHOeepU8+c4cqS+Z6+sTLwft97quO2CKyxfLmzbuhX4/POmVUdlGIbpxBCLP4ZxDos/hmHalW+/FULl8suB3btd26egwNo2wZZp08T6Bx8UXrPaWrH+1VfF+j/+cI/NtbWiaXpHraBpsTjuG8gwDHOGQyz+GMY5LP4YhmlX7rtPCDO9vmn7DRgA+PlZvWPV1UDfvkKUlZbaj120SBxj1Sr32JyQIOa79Vb3zMcwDMO4BWLxxzDOYfHHMEybYTIBs2eL4iSACHn08xOiraamaXNNnCgEWFqaeL17d8MtDdTiLLNnt8x+lZ9+EvO98YZ75mMYhmHcArH4YxjnsPhjGKbN2LDBmo83b561ncG//930uZ57zloIRpathWB27Kg/9sCBhhulN4fZs8V833/vnvkYhmEYt0As/hjGOSz+GIZpM556ynFD8i1bmj7X4sVi32++ATZvFs/Hj3dc1TI+Xmy/++6WnwMgcgqJgNBQ98zHMAzDuAVi8ccwzmHxxzBMmyDLov+cpyeg0wELF4pQzT17mlfVcs8ea96d2tcuMNDx2OJixwVimsv55wMeHkBFhXvmYxiGYdwCsfhjGOew+GMYpk1ITBQC7IYb3DNfba0QYar38OGHGx4ry0C/fqIYTFGR4zGpqa6JULXS6MUXN89uhmEYptUgFn8M4xwWfwzDtAlqSwdHjdlbOicREB3tfOxLL1nDROvyyy9i2+rVjR/zjz/E2Oeea57NDMMwTKtBLP6YTsKrRBRORNVE9EsDY0YTUZWD7WOIKIiIKokogYjubMqBWfwxDNMmqD349u1z35yVlcBNNwFvvtn42MhIcfyxY+v35rvhhoYrhdblvffE2HXrmmczwzAM02oQiz+mk/AQEU0hohXkWPx5EJGRiAx1tvsQUTIRfURE3YjoMSIqJaKhrh6YxR/DMG2CKrDU1gztwbXXChuOHLGuO3LE6j085xyRH3j6NJCXB7zwAnDeecArr1jHqy0mjh1re/sZhmEYpxCLP6aToSPH4m8GEf3oYPvtRJRHRF426wKJ6A1XD8jij2GYNqF/f/um7O3B/PlCuH31lXXdq6/aVx4dPRrw8QFGjbJfn5AgPI0+PsDgwfW9hwzDMEy7Qyz+mE6GjuqLv6FElEJEgx1sf5OIpDrjVxLRWlcPyOKPYZhWJy9PCKgrrmhfOwwGYceUKdZ1l1wi1t17b/0WFHfdJSqTEgHTp1v3dyU8lGEYhmlziMUf08nQUX3x9xMRvdTA9tlE9Hud8QuJaLuTY8wh8YehLu39d8owzJlOQIAQTY8+2r52mExAt27AgAHCA5mdLewaMwZYudIq+j78UBSGqagASkqAPn3Efu+8U99zyDAMw3QYiMUf08nQkb24u5eIgknk/Dna/iYRHaozxwpizx/DMB2JdeuEaJo9u70tASZPFrbExADbt4vnL78sGrYTAb17A+Xl9vu8+KLY5ucnHsPC2sV0hmEYxjnE4o/pZOjIXtwtI1HAJUdZyklU/DyhbL+diHKJyNNmnwDinD+GYToSaoXMH39sb0uATz4Rtlx+OTBwoHi+fbvoG/j0047bPfz+u9Ur2LOnGMswDMN0OIjFH9NJ8Cai7kS0gIh2Ks99iag3iZw/dfmciP4kkf9HZK32+QGJap//JiEWh7l6YBZ/DMO0OlOmdByPWV4ecPPN9rl92dnO9ykrA3x9xdg77mgbOxmGYZgmQyz+mE6CjohQZ9E3MK5uTuBlJEJDTUSUSNznj2GYjsDp08DMmUBSkrVyZklJe1slkGVg/37gsceAd991bZ//+z9xDjpd69rGMAzDNBti8ccwzmHxxzBMq/DMM0IsXXedeLzqqva2qGXs2QNcdBGQmNjeljAMwzANQCz+GMY5LP4YhnE7R48CHh72oZWzZrW3VQzDMMwZDrH4YxjnsPhjGMbtTJsmBN+AAVbxFxDQ3lYxDMMwZzjE4o9hnMPij2GYZpOWBmRk1F9/wQVC8G3YIB779eMKmQzDMEyrQyz+GMY5LP4YhmkSOTnAsmVAaqrw7PXvby8Ac3KE4LvsMtFU/a67gIUL289ehmEYpstALP4Yxjks/hiGcRmTSRRuUb15akjnrbcCFosY89tvYt306e1rK8MwDNPlIBZ/DOMcFn8Mw7jMa6/ZF3Hx9QVGjxbPjUYx5t13xeuNG9vXVoZhGKbLQSz+GMY5LP4YhsHcucBzz4n+d3WRZeCff4DoaMDHR3j89u8XIZ+zZgFffy3E3uzZYvzEieL1sWNtew4MwzBMl4dY/DGMc1j8MUwXp6YG8PMTgi0urv52g8He2/fJJ2K9KhQTEsT6G24Q+X6ensCwYY6FJMMwDMO0IsTij2Gcw+KPYbo44eFWYbdsWf3tn35q3d6zJ5Cfb79dloERIwAvL2D+fDHuzTfbxnaGYRiGsYFY/DGMc1j8MUwX55tvrOLunnsAvR6oqLBuf+wxsW3GDECSHM+h9vXr3l08hoW1iekMwzAMYwux+GMY57D4Y5guzhNP2Id1EgEff2zdftFFYl1xccNzHDokwj2JgIsv5pBPhmEYpl0gFn8M4xwWfwzTxRk1CvDwsBZqIQLGjRPbSkvF6wsuaHyeuDhR6dNgaF17GYZhGKYBiMUfwziHxR/DdDFkWRR5AYATJ4S4GzsWiIgAXnlFCEFvbxH66e8vtj/ySPvazDAMwzAuQCz+GMY5LP4YposxeTLQo4fI01NDPufPt25/5BGx7tAhaxuHhQvbzVyGYRiGcRVi8ccwzmHxxzBdiIqK+vl9ffva5/NIH9Z+AAAgAElEQVQtXy7Wz5sH3HyzeK7Xt5/NDMMwDOMixOKPYZzD4o9huhBHjwoxN3ky8NBD4vncufZjIiLE+vPOsxZwsVjaxVyGYRiGaQrE4o9hnMPij2HOcCwWIDtbPG7fLgTd22+L17Gx9Stzms3AVVc57/3HMAzDMB0QYvHHMM5h8ccwZzj//a8Qcb16AbfdJp6vXet8n/x84PrrgXPPBYqK2sRMhmEYhmkpxOKPYZzD4o9h2pEtW4Ddu1v3GBdeWD/Pz9/ftX2rq1vXNoZhGIZxI8Tij2Gcw+KPYdqJsjLRGL1379YTWWqfvmHDAD8/q/jLy2ud4zEMwzBMO0Is/hjGOSz+GKadCA62z6ubOhVIT2/eXOXl9XP3ACAgwNqnb+pU8XzAgJbZzTAMwzAdFGLxxzDOYfHHMO3EmjX1wzHffrvp8xgMgK8v8MUX9betXCnmXbAA2LxZPL/xxpbbzjAMwzAdEGLxxzDOYfHHMO3Ea6/VF3/PP9+0OSwWYMIEse8NN4h+fQcOiL58sgxMny62/fmn8A5OmQJs3do658MwDMMw7Qyx+GMY57D4Y5g25NQpIDRUPL/lFiHMhg61ir9Jk1yfS5aBpUut+3p7CwGovt60CbjmGvE8I6N1zodhGIZhOhDE4o9hnMPij2HaCFkGrrhCiLGXXwb69xdFWKKjRUimj48ozOIqH34o5vLxAcaOtYq+Xr3E47hxIhx04EDH+YAMwzAMc4ZBLP4Yxjks/himlTGZgIULrQ3WbZerrrKOGz1arCstbXxOiwXo00eIx5AQ4NtvrXMuXgycf7719Ycftt65MQzDMEwHglj8MYxzWPwxTCuzYoW94Js9W4R3EgEzZljH3X+/WBcZ2fic0dFi7K23itdxceK1lxeQnQ3Mmyde9+kDFBS0znkxDMMwTAeDWPwxjHNY/DFMKzNxolX4+foKMVZbC/z8M3D6tHXc22+LMdu3Nz7n6tVi7KxZ4rUsA888A8ydK15nZYmwz+++c//5MAzDMEwHhVj8MYxzWPwxTCty8qQQaaNGiT578+c3PFYVdM7GqDz9tBi7Z4/bTGUYhmGYzg6x+GMY57D4Y5hWZPFiew+dMw4dEmPPOQfYu7fhcVVVQkwSAUVF7rOVYRiGYTo5xOKPYZzD4o9hWglZBi6+WIi0+PjGx9fWij58REDfvoDZbN02fTpw331ARISo3kkkKnwyDMMwDKNBLP4Yxjks/hjGzcgy8PXXwJw51ubrTWHyZLFfYqJ4HRtrzRkcNEg83nMPEBjobssZhmEYplNDLP4Yxjks/hjGzQQH21f3/P77pu3/v//ZF3555RX7+S65RHgJGYZhGIaxg1j8MYxzWPwxjJt5/32rUBs2zLW+fbZs3Cj2/eADoKwM6N0b6N7d2h5i27bWsZthGIZhOjnE4o9hnMPij2HczCWXCJF27FjzCrJERYn9/+//RKsGImDaNKCwUBSCkWX328wwDMMwZwDE4o9hnMPij2HqUFgIrFkDrFvX9AbpCQlCrE2Y0Pzj19SIfoCDBwPjx4v5Dh9u/nwMwzAM00UgFn8M4xwWf0xTCEgLwJClQzBk6RDMkeZAPhO9UNOmWcM2H3qoaft++63Y75NPWmbDhAlWGyZMYG8fwzAMw7gAsfhjGOew+GOawsf/fAzSkba8vuf19jbJvWRnC69bv37AiBFCfB096vr+//2v2Oe331pmx6JFYh4PD2DHjpbNxTAMwzBdBGLxx3QSXiWicCKqJqJfbNYPJqItRJRJRKVEFElE99bZdwQR7SOiCiJKJaInm3JgFn9MU3h659MgHWHF4RUYsnQISEdYH7keAJBVmoWKmop2trCFfPKJEF3vvWf14k2eLEJBG+LECVGYBQBuucWa79dSKiuB8vKWz8MwDMMwXQRi8cd0Eh4ioilEtILsxd/5RPQOEZ1NRJ5EdD8RlRPRJTZjDET0LRH5EdEtRFRGRONdPTCLP6YpTNowCaQjpBSmIDA9EN7zvNF9QXfM+GMGPOd64t4t97a3iS3j0kuFeEtPB6qqgDFjxOvzz3dctfPgQcDTE3j0UfF60CCgWzf7Bu0MwzAMw7QJxOKP6WToyF78OSKSiJ5Rnl9ARLVE1N9m+xYi+srVA7L4Y5rCecvOg4fOA9XmagDA6rDV8JrrZRcKuitxF5YFL0NVbVU7W9tEqqsBLy/g7LOt60pKRNVNImDFCrFu9Wpg1SogL88aGtqtm/AAEgFXXNE+9jMMwzBMF4dY/DGdDB05F3+DichERFcrr6cS0ck6Y94logOuHpDFH+MqZosZ3vO8MeKLEXbrD2cexjO/PaOFhKrLp/6ftpOlzSQ2Voi3u+6yX3/kiFg/erTICVQLsQwaJB67dxePM2eKxyeeaB/7GYZhOjGyLGNBaiq2nz7d3qYwnRhi8cd0MnTUsPjrRkSHiOgHm3VPE9HROuOmE1GIk2PMIfGHoS7t/XfKdBIySjJAOsIN39/gcHtueS585vlo4u+sT89Csam4ja1sAT//LMTbG2/U33bTTWLbI49YxR8RcN99wE8/2a9bsKDtbWcYhunknKisBEkShgcGtrcpTCeGWPwxnQwdORZ/vkT0JxHtVp6rTCWilDpj3yH2/DGtQEBaAEhHePyXxxsc823ot3jn73fwwq4XQDrCXP3cNrSwhcydK8Tbd9/V3/bbb/YCb8UKYO1aoLZW5Ab262fd1tJKnwzDMF2QH7KzQZIEkiScrq5ub3OYTgqx+GM6GTqqL/58iWgXiYqe3epsc5Tz9yNxzh/jZmRZxo9RP4J0hPf2v9fo+LTiNHjN9cKgJYNQWVPZBha6gcceE+LN37/+NlkGbrhBbB8wQIg+W0JChFfwlluA4k7k7WQYhukgTE9M1MTfvoKC9jaH6aQQiz+mk+BNRN2JaAER7VSe+xKRDxH9TkQHlXWOMBLRShLVPicRV/tk3Iwsy7jqu6u0cM6VoStd2u/xXx4H6Qhrwte0soVu4vLLhbjLz3e8PTAQ8PYGXj/DehsyDMN0AC49fFgTf5MiI3FOUBBiud0N00SIxR/TSdAREeoseiKarDw3kWjxoC4f2ew7goj+JqJKIkoj7vPnNkwmoKamva1ofyKzIu0KufyZ9KdL+4WdCgPpCFeuvrKVLWwhsixaM3TrBgwe7HzsqVOiKqib+CYjg4sbMAzT5cmvqQFJErwU8acuH5040d6mMZ0MYvHHMM5h8eeYqirgwguBSZPa25L2Z6FxoZ34i8+Nd3nfS1dcCtIRUotSW9FCJ1Q10m5i+XKgd29g61bh9bvjjraxC4ChqAgkSehpMMDEfQEZhunCzElJAUkSHoqJsRN/EyMi2ts0ppNBLP4Yxjks/hyjagEioKs7Zm5afxNIR9gSvQXrI9c3ad/3D7wP0hG+OfxNK1nnhJ07Rd++5csbHnP99eJDHjxYPC5a1CamybKM6yMitAucPQ2FmjIMw5zh/JKbC5Ik9DYaEVdejlHBwSBJgockwVuvR1ndHGuGcQKx+GMY57D4c8ykSVbx9/PP7W1N+3A0+yim/T4NXnO9MPyL4ZBluclzBKUHgXSEOzfd2QoWNsLDDzuvwFlZCfj42FfxDA1tE9MOFBSAJAndDQaQJGFmUlKbHJdhGKY92Z2fj/uioxFRWgoAyKuuxsCAAJAkYa9yE2xdVhZeSEjAI7GxIEnC73l5zfr/w3RNiMUfwziHxZ89tbXAZ58JHeDhIR5fe63l84ZmhiIp3/EFfk5ZDuZIc5Bf0XG8P+GnwtHv035aqOerf73arHnMFjMGLx0M73neCD8V7mYrG2HkSKuomzix/nZ/f3vh16+fyP1rA56IiwNJElZkZsJL6Wtlsbm4OV1djQNc7Y5hmDOIGosF5wQFgSQJvno9/iksxLSEBJAk4b8OboCtPnVKi4644+jRdrCY6YwQiz+GcQ6LP3uWLhU6wNcXWLZMPB83runz1JhrsPf4Xqw4vAJZpVnwne+LkV+NhNliFRfJBcmIPR2LAZ8NAOkIc6Q57juRFmCRLbjkm0tAOsL7B95HcEYwqmobyZ1zwvKQ5SAdYdjnw5BenO5GS52Qmio+vAkTgCFDhIfPtmrc3r3A88+LMf37i8cpU9xuRlZVFRakpuL1Y8eQoBy/pLYWfgYD+hiNqDSbcduRIyBJwouJiZoAVO+ERyp3x5mOS0ltLabExOCX3Nz2NoVhOjSblT5+wwMDQZKEf0VFobvBgL5GI0ochHbmVFdjXGioFiGRWVWFGosFS9LS8G1mJtJNpnY4C6ajQyz+GMY5LP7sUVPAgoLE6/PPFx7AnJymzfPgtgc1r5ltm4T9yfsBAFE5UeixsIddIZXHfn7MbefRkhCZXYm7QDrC5A2T3RJqI8syXvrzJZCOMG7VOJRWlWJH7A68tuc1WGSLy3NsjtqMo9ku3v3dvFl8kG+8ATz6qHh+4IDYtny5vcdv82bgyiut292Ibd+qS0JCUGE248v0dJAk4YWEBABAUkUFRigXQxuyslCgVL0jScK2pn7xmki1pfH332Q2Y2N2NnK56bJD3k9O1j4vhunKBBYX496oKAwOCMDyjAy7bdlVVbhAyeU7WFiIHoqgI0nCY7GxTuf93/HjIEnC90o4qLrf8MBAmDkclKkDsfhjGOew+LOSny+E3siRovo/ALzzjlVDuIrZYkaPhT3gM8/HTtyRjvDUzqdQUlWCUctGad4wddvVa652y3lklGRgxBcjMHX7VBRWFjZp34qaClz//fUgHWF30m632AMIT+hdm+8C6QiTNkzSzjnsVJjD8bIs2wnPufq5IB1hyNIhKKsua/yAM2aID+6XX4BvvxXPH3wQePppwNMT6N5drBs0qPGKoC3gkpAQkCRhcmQkSJJwdXg4vJQiBhE2Xr1DhYUgScLdUVFYn5WlXdx8mpbm8rF25+cjrKTE5fHbT59Gd4MB7yYnNyjyi2pqMEmx/S4Ou6qHLMvaBS2LP6arsiIzE3cePQoPmyqdFwQHa78rGSYTLlZ+Cx+OiQEA3B8drY39ITvb6fx/KznSakTE8MBAXBEaCpIkBBcXt/r5MZ0LYvHHMM7p6uKvpgZYsgTIyAC2bRN6YMYM6/a8PNEJwMcHSElxbc743HiQjnDrxltx68ZbQTrCoCWD0HtRb/gt8NMqYD6842HIsgyzxYw+i/ug16JebvG02bZmmLjOQa6bA35L+A3nLz8fA5cMBOkIl397ucteOVcpNhXjspWX2YnhtRFr7cbIsowNRzag/2f98f6B9wEAW6K32O2zwLCg8YONGyc+zOxsIC7O3tPXu7coAJOdDTRBXDWVvOpqzeN3urraroJd3d5+ZlnGoIAA+Oj1uMGmCuiMxESXjnW4pAQkSTgvONil8ekmE/oajdpxZjXw5VYLLqgLh6Hao16UqkuRi41B/8zLw5VhYTheUWG3Ps1kwkMxMfiNQ0iZTkJxba32/T/L3x8bs7NxVVgYSJIQX16OU1VVOF/57Xs4JkaLNliVman9Hp5uJKrAZDZrnsKeBgOOlJbiKyWCoqHfLqbrQiz+GMY5XV38bdhgrfXx9NOOC0POny/WT5/e8DxHs4/io4MfodpcrYmVt/a9hT+T/gTpCG/sfQOv73ndTsQk5lkv7K9bex1IR8goyWj4IC4gyzLGrBwD0hF6L+oN0hHKq8sb3WfcqnGaXQ/teAhZpVktsqMhUotSNa8n6Qiv/PWK3Xb1/SIdwUPnAUOqAb7zfeE11wvfhX8Hn3k+6Lu4L0qrnIiQ8nLh3TvnHPUEgYsvBry9gS+/tM/9a0X+yMsDSRKeV8I7qywWhJSUNCigXrQJEVWXO13wtsmyjBttBGOqC3kwapGFp+Pj0dNgQA+DAYV1hMsuxf5RwcFYmpYGkiRcGx6OHadPO8zP6WpkVlVpuUvqEuSiF+IWJc/z6fh4vH7sGK4LD8fdUVHaRbKfwaDliDJMRyawuBgkSbgvOhpVirCbd/KkFrnwpFLc6rHYWNTahJmnm0zw0etxc2SkS8d5NDYWXpKE3UpF0GMVFSBJwojAQOzKy3MphJ3pGhCLP4ZxTlcXfx99ZHUIeXsDvXoBdSPniouBvn2F9y8zs/4cJVUlmmD5KfYnvP332yAdYXPUZgCicmZlTSUKKwsxaMkgkI5w75Z77eaY9vs0u5zA5hKVE6XlGd675V6QjhCZ5fyf6+HMwyAdYcJ3E1pU2MVVai21OJZ/zKFn8oMDH9gJ5L6L+4J0hFVhqwAAL+x6AaQjrAxd2fAB1CqeDz9sXZeXJ5Y2RM0FW5flmpDek5+viYh/lDDQC1zw5B1UxqrLm8ePY0pMDDIaEIFmWcbAgAD4Kv2zXk5K0qrtrT11CrUWC77JyICvXg+SJOwrKECl2YzRhw9rx/DV6/FkXBxSKiub9J50dsyyjG8zM3GyshJTlGbULyUmYpbSoHq9C591QU0NvOqIfNtFFYDXR0TAZDbjx5wc7aKaYToCVRaLdgNojVKRU3fypLb9SGkpSJJwblAQPCQJQwMDUe6gkvLRsjJkuxh2X2E2I63Ob9qFSigpSRI+OHGi+SfEnFEQiz+GcU5XF3+PPGITEehZiznLUpBXUV8kzJolxrz0Uv05Zv45UxMr7x94H7f9cBtIR4jLjas3dmf8Toz8aiRCM+37yX0W8BlIR1ge4qQheQNU1lRq4aJqSOkXQV/grX1vgXSEbTHbnO7/4q4XQTrC6rDVTT52c7HIFvRZ3Ac9F/a0Cy/990//BunI7j2duG6idn6RWZEgHWHMyjH1Q2Srq4EPP7S6cD/9tN5x04rT8OjPj9p5XVuLm5RcucQ6oX0NYZFlLMvIwBHFMzgiMBDeer3d3XJHvKUUQ7g3KspORLyXnOxwfIgSIqp6FWPLy+32e1y5U99Nr8c3NkUbKsxm/Jabi2kJCejn7w+SJFx6+DBMbdQeoyOwNScHJEm4MSICvno9Bvj7o9piwRZl/evHjiFJ+bxDS0pQoHhTK5SiOUvT0jBD8fD6KWFsfYxGHC0rQ2RpKX7NzYXJbMblSj7T3cpnOjslBXcePYpbjxzhfmdMu3PX0aPo7++PDJMJrx87BpIku2q3sizjuvBw7TdllaO7pm5g9alTuCQkBL56PfoajdwMngHA4o9hGqWri78xY5Q0sD4y+r9+lxZuaEw12o3LywMGDqwfFmqqNaH7gu6aULll4y0469Oz4LfAz66tQ2P8kfiHJnoaQpZlJBck24ml6JxodF/QHYv9F8MiWzDyq5Hw0HkgM+c4vnv9RpCOoJN0Dc6ZVpwG3/m+6L2oN0qqXC8W4g5uXn8zSEd2/Q8nfDcBpCMk5CXAa66XQ2/oDd/fANJRvc8I27fb5/b980+9Yz7/+/MgHeHZ355tjVPSqDCb4aPXY1BAQLMv1m9WxOPJRrxrqlCIUO62q8t5NgUXbPlE8VJ9mW5tu/FcQgIuO3zYziO12UkRhgqzGf939ChIkvBuAyLzTOQ+myIVtiG9kXXe+6uVC9/xYWHwLyrCeTZFYWyLXEyJicHfDvo5fp2RYTdW9cKSJOFYRQVOKSXvmdbDv6gIT8XHY39BQb2/o/yaGmRVVXVJIX7E5rv+WGys1qqmbpiyyWzGuqwszDt5stW/q88pYey2v2lM14VY/DGMc7qy+KupEaGew4cDv8UJ8eU9zxukI7y7/9164/futeYHqhEu+5P3g3SEqdunovei3vCc6wnSEW5af1OTbEkrTgPpCKNXjIYsy6i1WO9g/pn0J1756xUtL3Cufq627ZW/XgHpCJetvAz+af5CgK6fDNx0E/TnCkH6nx8esDvWytCVuHL1ldh7fC+e/e3ZdusxqOZAbo3eqq3r92k/rfDNQuNCvLnvzXoXWKvDVms5lXY895y9+KuTf5Vfka8J9b6L+7o9xFUqLMRT8fH4u6AA+5VCII82UsLcGc/Gx2shoA2RVVUFkiSMPnwYADBGCc3sr3jmQhxU/1SLMTjySKpeqfFhYXZN5x2RYVM05osz+KLLLMt4MTER48PC4G0jwsgm/6jcbNbWedYReaqgfigmBp+np+PSw4cb9Zjm19Rogq/ufPco3kA/gwFLW7FgUVfij7w8PBkXp3lqLbKMS23CnB+IjtaKkkSXlWmfyQPR0e1pdrug/kbYfi99XYhQaE1iysrgIYkqylsdtMfJr6nB+qwsbgvRRSAWfwzjnK4s/uLjARqQiO4fnAe/BX5a2KWzKpnvvy90xXXXAcdyT2qhlWvC12iVPUlHWB+53mU7CguBBQuAs+ddpQnJXot64XjBcXwd8nW9dhHnfHkOLLIF1eZq9P+sv7b+/q33C1vW/RcgQnY/b23bZZ+fj/f2vY1FxkX15uv/Wf829/oBwC9xv2jtLwCgoLIApCNcseoKp/tllmSCdIQLll9gFYayLFS8lxdw7rnApEn19lvsvxikI02gu6uVRUFNDWotFk1UqUVSSJKw+tSpZs87Vyma8J2TOX5Qmia/duwYAEBfVISv0tM1z9EbyvrI0lLcGBGh9Rgcc/iwQ69FXnU1XkxMxNEyF9ppKMdTq/Dtd+DB6ozkVlfbFc15QwlrUxfV+9fLaLQTcA/HxOC2I0eQajLh+6wsHCos1ITfJ82oSPhCQgJ6GY1YreRU9bGpzqouwwIDG/U+rT11Cr+7Od+1sPAQwsImoKTksFvndcS2nBxsys5uNS+bxaZdxw0REbgkJEQL2R4bGoqLlLyye6KiAED7GyLJtUqVZxLlZjN6GgzoaTBoDdtJknCO2hi3HfkhOxtekoTuBkO98M9Xlb/hjY20lGDODIjFH8M4pyuLv19+AeiB5zURpLZeGLRkEHzm+aCypn64XU0NMHEiQFevshNQqUWpWr7dwCUDYaptvOKiyjPPKM6qGz+1m/POTXeCdAS/BX5YG7EWAWkBmsA0pBrwW8Jv9YRcr0W9UPjf5wEiyB9/hB4fUb0xnnM98eHBDzF+9Xjcu+Xe+uGTbUR5dTm6L+iOfp/2Q425BmGnwjTx2xhXfSeEcnxuvFgREyPexBtvBEwmoM4//9zyXPT7tB+85nphvmE+SEd4eufTLT6HrKoq9DAY7NozdKsTotdc9ioFYK6PiGjwwvcBRYioHiiV09XV8NHr0d/fHyazWcvjUxd3XgT9mpsLkiRcFBLSYGGSuPJy7MrL6/D5geVmM84PDkYfoxFFNTWIU/IhBwUE4JOUFFwTHo5jFRXYkpODv+q8547Ycfo0vsnIaJZwqbVYUKx8j3/NzUV8ebn23brs8GGtwmuME6GeoNjf12h0q2cmOvp+SBJBkgjV1a1XSKnSxqM6PTGxVQTgoToFk+p6dsvNZpzl7w8/gwE1FotWvVL1DLpS5KcplNXWYk5KCuI6YLXX3cpv0n/iRD77HUrotytVidsC9bOp+3t4mfJZTVV6DDJnNsTij2Gc01XEX92LhhpzDV6bGw+a1Q3d5/ax83xN2T4FpCPMPjQbUTlR9eY6FFQIes/qcRv6+VAAwD8p/4B0hPmG+S7bFRYmNMuQIYDngBP1hBrpCN+Ff6eN/z7ie5COMP2P6Zi6fSpIR3jpz5e0sTpJB5x/vpj09Glt/cWveWDuZMLsqf0QEL1bFEcJCKgnktqaB7Y9oOX1bY/ZDtIR3vn7nfoDZRlYuhTYtw+Aten7wt/eBFatAq6/XpzzvHkOjzP9j+kgHeH1Pa+jvLocvRb1gt8CPxSbrKGhfx37C9E5TQvj+vn0abuLRd3Jk1pO3QgXvDLOkGUZ4xVv4qyUFPgXFdltz66qgpckYXBAgMOcmkeVHn2rMjO14iIkSRgZFOTWHBxZlrViMx87qLiXWVWFs5Qw1MEBAS4XwGkP3lMqtKoX9Woxi887SFjrrUp+1arMTOgUz/BXTmx7WykGRJLrbShcITR0nCb+EhMdVMFyE8aiIru/L0dhzC3lCUUwzD15Ei8mJuL3vDxMS0jAM/HxWuizmt8aWVqqib5tSpEfdwoKWZZxu/IZ337kiNvmdReqB01tyl5aW4sPT5xAbAcRqhsVb+T/jh9HSW0tZFlGfk2N9v3pYTDAZDbj5aQkXBgSgtwu5LXtShCLP4Zxzpku/kqqSnDnpjsxacMkVJvFD70sy5i8YbImjP6z8U27fT4P/FzbNuzzYXYFVoLSg3D999eL7VOfwuSlL+Gn6N+g1uQ4UXiiSRf8Dz8sNMu6dcBllwE05Rn838b7NAF63rLzUGO29l8rMhXBb4Ef/Bb4wWeeDwYuGYgiUxF6L+qNoZ8PRVn8UTHhhAkAgDlbpqP/HD/EHwsCHntMbDv7bGDoUPH8jTea+9a6hQ1HNmheOLU5/arA5cDLLwO7dlkHHjgg7PXzA+LikJiXCA+dB4a+Q6j0VnL8xowBHNyFDz8VDg+dBwYuGYjCSpE/N+OPGXYtI9QqogM+G4BTpa6Han504oTdxWlCeTkqzWY8FhuLNS0I+VT5Xem1p+Z4VSqes1qLBbMVkflOAwVXVI+GGpb5n7g4fHDiBCQnOYTN5WRlJfoYjfCUJBhtRKosy5p3QG1h8HR8vNuP7w4yFTGt5vXdFBmJfv7+8NXrkddBLhKDi4vxTnIyTGaz1l/tX0o4Yt3ei1UWCwYoolsVNy1Bls2IivoXkpJegV7vDYOhB/R6HwQEDIQsu8ejK8sy5p08iSlKM/BPlf6S6s2DrzOa3wf1dHU1/szL06rpAuJ766NUiqxw4pVWb+h8np4OD0kUU6qyWNDLaERPg8FtrTjUEF81pLSxvNu2Rg2BdbU9Q1uTqeRAqzmJX6Wna/1K1UVty0KSaG/DnHkQiz+Gcc6ZLP5qzDV2eXifB34OAAjJCBHr3j8L3jNuRFqhfRnqhLwEdJvfTdtP9QZV1lRqfefO+2wsqEcunnwSmDxZONvq9Mh2ibPPFmlqlZXA448LDaPXCxsHLhmIX+N/rbePGl5KOsJre14DAMTlxuFk0Ulg+XIxyRy9BzAAACAASURBVIcfauO14jGVlcDtt4vtHh6Ary/0EybgryNHUOrAG1NQU4NvMzNdu7BJSmrWG1BsKsbgpYNBOsLYBcNBOsLf028TNp53HvDXX8CUKSKcUy3kcvnlQHIyHn9K5Gl+9c5NohqPAztlWdaqg66NWKutDz8VDtIRLl1xKYpMRXj8l8e19/T2H253WcCrxTduOXKkVS4kZFnGisxMjFUqegYVF6PSbNZyCkmSEN/AXXdZlnGnIrxIcl44xh38qHhCBgUEaOGu4UplwDGHD6Owpgb9/f3hrdcj3YVG9G2BWZY1L6jayP695GSMsGneroa4dTRqLBb0NhrR3WDAjMREeEgSpiUkaEUttite6XHKd+cmF5tp16W2tgR5ebtQWPiP5u2TJEJ09H2IirobkkQoKtK75Zz+Z+Op9C8q0sKa5ygX7M8088ZBQnk5fGzCsR+IjkaayaQVVZrXiDBWwx0vVsTPw4q3T23FEe1ijqwzKs1mDA0MhIdkze90lHu7OTsb/4qKavMbEsmVlSBJwhWhoY0PbkfOsrnhMTggAK8ofUxVj6q6eClL3SqlTOeHWPwxjHPOZPH3ZdCXWiVM73ne6L2oN97b/x7u2ixaOtCEtfjPfxzvW1JVgk8OfQLSEZ757Rnc9sNtWq7YlO1TUFhkgYcHMGCAVZMYm5g6d/q0VcsAwKJF4vXXXzvfr7CyUBOhYafCrBtkGRg3TkwSHu54Z1kGiopQk5+PmVu3WgtH7NwJk01YmCzLWnl6ZwVHACjJkwRcdRXQjEa7W6O3asJr4LuEAj+bip09elifDx8O3HmneN6tG+IGETzmEIZ/MdzOO7o+Kws7lZ5Tm45uAulE0/u6rTcmbZikeXc953pi0JJBGPvtWJCOsDN+p0u2Dw0MhI9ej+pWrnS3MDUVJElYlpGhhcKdHxyMbQ4q29likWXszs/H+qysNilLr168XxgSApPZrHlM1GqgqrfSUXhoe3BzZCRGBgXhaFkZrlRCbGPKyjBfCamcGhODnA7i9XPEFzbFR+p6M9QS/PsKCjBM6RkZ1YhIscgySut4ENX8vsDAEXbiLyVlDk6d+k57HR//LCwW124AOfp72ankjqrLZ2lpGBgQAF+9HqcUj86lh5tXYEZ9nyZHRmo3TjyU4wwKCKh3znXJra62s21haioAaxjkTpsed01FlmW8l5yMiUoO52OxsVqxp2V1PJ01FguGKTcmHomNRUplpVtCuOv+NmRVVeGp+HhN1JbW1uJ6xb5ZzShe1JbMTkmBl2TNyVSLLiVWVOCd5GT0NBhwc2Sk9pvamPDvrMiyDIula/Y9JBZ/DOOcM1X8ZZVmofei3vCe54343HgtR0xdun1yFsinAps2NTyHMdXoMAfv57ifAShhmjY6xcbZ5pC33gJGjwbUqKN9+8R+zz4rXu/eLV6/+GLj53fgxAGsDF1p/087JMQqwpwgyzKeUe54D921C2M3bABJEvZv3KiN2WGTyzY9sZGG6Go4KRFwyy2NG1/XHosF703thZfuI2Q+eT9w1lnA/fdb51RDVJcvB/LzrTmNd9+NB7fcb9cuIqmiAiRJ6GkwILwoF91/mQ9aNBBB6fWr0ZVWleLRnx/VPtcvgr7QWneMWTmm0T6N2coF6fiwMKfj3MEBpXXEE3Fxmofqsw5Y5t8iy1o1zMWpqVrOouoJVAuQ3BgR0ehcsizbfb9NZjMejY3F/dHR+Dw9vcWhZ9k2IWJqIZVxilfDIssdJtSzMTYpnqC/8vMxMCAAXpKEg0rI73nBwbDIsuY56200NugpBoBZKSnoptdrRWQKCvbZCT5J8tCe5+TuwnfpidgmDdXWlZSE1JuztLbWLnzxQEEBehmNdiIiorQUQwIC7Lx8qrd7ovJdGRUcDA9JalSoOWJKTAxICUmusljw8YkTGBIQgCvDwrDPxSq1FypeP5IkBCo3ypYpVXVb0nLjpOJRU4VKXHk5DMoNntuOHLGLvKgrkFviDVVZmpaGAf7+dv0mVfFJkoSCmhot1/TGiAiUd/CiTRYlz8+27+mbx49r26stFtRaLFq/wo6YW+kOoqPvQ3DwBaiuPt3eprQ5xOKPYZxzJoo/WZbx4LYH6/XrO1F4AmvC1+CeNc+g+4Sf4OkJOHOcVJurtRYQ6uK3wA/l1eLi6YUX7MXf+PENz1VVBfTqJcZt3y50jFrlc/lyMSY93TrX6NHObatHbS1w331i5zVr7DYdLinB5aGhCFAuWNRS5SODgpBuMmGtcif8rY8/BmQZR8vK7MrK1wsXk2VRLKaoCKnl5djywAOQfXyEG9TTE2hqyf+UFGj9M9T5CwsBX1+rF9O2eltqqnCPlpdDOimBdIRr1lwDWZbtwsbOOvSnuKDf+6XTwxdWFiK7LFsTG7duvBU0zxdPhu1DUkUF8qqr61VUzK6qwmvKXf/nlEbfrUmRUrTgwpAQPKIUcjHUKQDTUUiurISvXq/lGtp6a2RZxgB/f3TT6xsMJ5ZlGeuzstDf3x+zbQTChqysemFbU2JicKqZIvAnmxsc6vd9RWZm4zt2YOYpF+29lPNZoHioZFnWitfMb8DTUWOxYKAiwF4/dgwVFYlY4n8v3pTuR1jYeByQvHC1/0Y85q+DJHnhi5Pie3jz4b0wGLpDkgjZ2Zvt5tyjhEv2Uz7LaosFl9iIqJWZmViUmqp54WYmJaHCbLbrp6ja+2/le69v4vfeonznfPX6FlWbDSguxtK0NDvx/KeSTzYzKQnZVVXYlpODSJucQldQQ0ovCglBuLJvlcWCQcpncVFICAqVkPq7lDDuWSkpGBsaCh+9Hn1aUMl1uSJeSZJwVViYdrPleaVpOknWnOGrwsK06rOdhb35+QhuoNCRWZbR12iEn8HQ6pEbbU1tbbF2Q+bo0TvclpPbWSAWfwzjnM4q/gLTAzURVlpVijXha7AleguKTcVaqN+FX1+Iihr7XLaiItGknQj49NPGjzNl+xR4zvXEkoAl8JzriSd/fVLb9v33Yh4vL2DkSPHcUdXvkBBRu6SuI0td/P3FOFkGBg2yrv/uu/pzNciTT4qdRo0CbISKLMu4JjwcJEm4SynHrYbDqCFgGSYTSJIwZsMGlEoSzg4KAkmiQERvoxG9jUbrnXuTSWumnv6vf2kXCMHPPQfMmCFs2Lq1nnlO+flnsd+rr9qv37jRqowbQJZljF89HqQjfBa0TGs6brvcGhGqneeMxETcFBmJCCcXaBuPbARtfA4kSZgQFobLQ0PhJVnzbyrNZrsL2LVuKOziCuoxexgM8JKkDn0HfpESUkWSZCfgAOB+xTPYUPXJH2z6h/UyGlGmVO2boHgR1546hXeSk7WL48diY5tloxqyty0nB2ZZRqrJ1Cahsa1JXnW1Vtn1yrAwFNnk4arhwg29X38pIoQkCQOMh/CL/2h0k/aKkLmSTKw58oHiVdcjMVdv97emP/kDDkqe2BH/hZ2XT/UCq2JOLfozLjTUTuD1Nhqx5tQpLV9R7ZnZTa/XKjJ+rty0ujcqCmZZxvGKChxyIY9VbddxczNzHp0Rr8x9YUgIfJXzGRwQ0KRCLZ8pnvy6IZ4J5eWax+295GQth/O84GDtfVJzjgObUcm11mLB0MBAeCn2kySKB81OSdFa13TT69HdYMCkyEjkNyepvYOjViluSCB2VvLz99h57E+f/rlF86Wnf4XU1MVusq71IRZ/DOOczij+9h3fB9IRxq8ej9zyXLvQvYu/uRi9FvWC51xPBKQF1Nv3hx+EznjqKdeOVWQqQkKe8Owk5SdpghMQNU48PESk4+uvi3k3bLDfX6+3F3qOFlsdEhxs1VCPPebiGxIXJ3YYOVK4D234qU4rAvUu85V1QhXH7hUXec8oeYCPxcZClmWt2fGJykogPl4kKCqGX79ihfUO/qZNwO+/N+3NVXn/fcdvnotEZkWi+4LuoK+vBUkShh782e6c+/v7C4+eTcL/U05CpfxzkkAH99UTkfcoF52qaLjtyBHsyc93a/80Z9jejb+8gxddAIBUkwl/5uVpFUpV1AqODYXKXa3crFDF3rqsLAQrlS3H23gnKpT+a82txqkWQsnsoJULm8um7Gy8euxYveqfhYr3+LIG8uZUz1pfSXjMz5U2aN+3VZmZmGbz/XtICaMcqdwoej5awivSwyDJWpEzt7oa3no9BgcEILqsTLupdHZQEBIrKmAsKsL5wcHo5+9f7+Jb/RuzDTkvqqnRblypHkqSJC2ioSFWZmaCJAkftUKeqcls1ryWtkvd1gc/5uTg4ZgYhyGragj+fgcRE9lVVehpMKCbXo+eBgM8JMlO8H6lCOKLQkLwYHQ0shx8l/Nrahze1PhbCSW/JypKa1th6+3rYTB0uGqj7maJ8lv0aQcMoW8JJ058AEkixMRMhSQRoqLuafIcJlMq4uOfRnb2Jk1E1ta6v9VKa0As/hjGOZ1R/NmKvf6fiX575351Lu7YdIe2foFhgTZ+zx7RSsFstqaS7d/vHlsOHgTS0kSxSSLg0Uftt3/8sVXkeXgAV1whnl99tXh+993156yoAHx8gEGDZMiP/BuYPh1ooJw/AGDWLIeuzD35+VrIjlqVrm4olconykWVerdXrcaoVkqbk5iIk1ddJY5z553I/P57u/lmhocLj6OPD9C7N7Btm3XykBBg2TJgxw5RufOff8R6iwWIiABuU6p7Rjetx54tv8T9ggFbXxX2rH0ItHsjSJI0L8g/Sg7UiMBAdNPrcZa/f4Oi7X/KhSf9sggkSfDVSxigPwCSJC0vqZ+/f5uLhnTFQ0uSqOrYWVE9UFMc9EeLKisDSSLfy18Zd0NEBN5UwnlX1QnLVEMZnfW6c0R2VRU8JAkXBAe36Fw6GyOUwi9qmJssywgtKdH+zvvq92KRdD08pX9AkiiXr/5+9HHgVQ8rKVGEgh4jJfE3d+nhw5BlWQspfOPYMQAi1yqlstJOUNRaLA492McqKvBsfHy9kN6TlZWYEBamedlIcl48qMJsxrmK6GyOd8wVzlHmVz1ndb+na23aN6j98WxRb3Y0FL6shvJ6ORApsYrn0VaUq5hlGe8qfSvn1PG+n66uxlRFwG/JyYFFlrEsIwO9bT7jCW2Qy9ze2FYjNreh0M2sqmrVHoMRERMhSYTy8jgEBg6HJHmiqqppIe2qgLRdiosDW8li90Is/hjGOZ1N/BWbitF9QXf0XdwX036fBg+dB0hHOHDiAEy1Jryw6wW88tcrWm++vDyge3ehLa65RqSRDRjQvLYMzqisFMfp18++b/qtt1rF3/33A1u2iDDRv/922JlAY9IksU8MKVVlhg8XjdnrIsvWAihKfk+txYIPT5zQ7kh/mZ6OnOpq9LcpgV33znSV2Yx3//c/eB48iPk2yfG2Fy4jt22D5d//BiwWbFFC8+5dtQokWYsy4MMPrSdsMAj7Ro2yd3WOGiU+gJkzreu6d29xw3m1WfOw7+/BBT8+iZkJMVpenlo84uMTJ7QLNLXfnSzLOFBQoPX5UntZ0aL+eC3iL5y15m7Qsivhe2AXSBIVAxurmthapJpMmJmU1KnLk1eazfBRPEJ1PRJqzuaX6emQZRmjlZsS6ne37gVytCIWhwUG1isA80N2Nh6OiXGYG/mo4uVqqEfimYrarDymrMwuD1B9j9eHTIEkEcIK0/HxiRPYbXMDyfZzIBvhPFMRjrbL6lOntLDQpubAuYpaPOh6J8WD1OIxjzQzNNgVblEiCoYEBGCvElnxhNIeJKe6Gt1t3r+HYmLwYmIiJkZE4KXERJTV1qKHwYB+SnSCIyyyjPDSUodeQ9uqzEOVKqBvHT+OpIoKPKyIO5JEWK3qCbZte9HTYLAT39ttIkWe7KAtTtyN+vltbVKSffNJN5m074SjG2DNoaoqSxN3ZnOF0n9zMGRZ1kRcWtpnTZrz6NE764m/zMxVbrG3tSEWfwzjnM4m/tZHrgfpCC/uEiUxj+UfQ3BGw3fv1fYJvXtbdcbzz7eObXffDa3lQ1iYeOzRA+jbV+g29X+7Kzf8dO9VgAhY6PkxcOmlihJ08I8iKEhsu+kmAEBxba12gdfXaMTPp62VvtJNJjwVH4+XEhMdX2g8/DAqfX2BQ4eE8Tt24HhFBbodOqRdEIQoHpYXExNBkoSfT59GL6MRfYxG65xffSVsevtta0iq6ha99lprTKutIDz77Ca91yonKyu1XBRV4OVUVWrif3udsNf48nJ8pwjae6KikFBeroUhfnjiBI4p1ULP0e8B6QiDlgwC6UiEleoIXwQ30oeDcQm1bPzxOv0lL6nTRPpzm1YGVzXgiZihfBevCQ/XStObZdlOqNiGyqkX6OcFB6OskxWwaClvK+L62fh47XdicEAAFqSm4mRlJfz9+8Fo7GX3+3CbTbi0GipIkoRXlJYStt4n1funLh8mtp5nVZZlDFNy1uqGuKrbhyvb01qxr+QLSjjsM/HxKKmthack4ZwgUV34oxMntPfKz0YEqovaT9KV6rcNcbyiAlFlZZAKC+2EJknWcFCSJLyQkIBDhYVYoOTjToqMxJ95eXZz5di0tFCLBZ3pqJVVzw4KQnJlpba+sKYG0xIScG5QkN3/UUDk1v47NhahJU0Pg1ylhCGrS3MLVqmYzRUIDByBgIAhMJsrkJ+/F5JEiI0VYUglJWFK6KeDMKMGkGULjMa+MBj8kJ29Eenpn0OSCElJL7fI1raCWPwxjHM6m/ibsn0KSEc4eOJgo2NraoSm8PAQ+Xl79wLvvgvUyat3G19/LXSMp6e9rnEU2tkYiXO2wotq0c+3AnkvzxYT2YZSAtAXFeGGHTuw/KGHULV2LYpqarTiLpeHhuKkzT+yJp2AbfPCl15C8cCBWPr443YhVmqBgLzqau1CPr68XIRSpqVBa2C4dKl4PneuOEZYmP2bs2SJ6E1Yp0KpyorMTFwUEoI0kwkxZWU4baOc1TywiRERqLZY4K3XY3igfVhKXnU1RgQGoq/RqFXlzKmuxgBFGPgoBQ1U76Aaqva/xGic/eXZWoXXH47+ANIRHv/l8aa9p4xD3lJEyPqsLESWlkKWZa2X2iUh1nYBp6urNS+FroEqlVUWi9YjzVuvx9GyMgQq3w11ecvGm62Kxba6099RkGUZa9IT7N6Xc4KCtEq2NTWFkCRCaOg4u/0CiovxUEwMkioqIMuyVmjHVjjcHRUFb+kg1koX4A7DZ5jg/yOe1c/EP5IH0tO/wOHDY5CSMsft5/SUki9XV8QAVq9wS4SVK6gFitSWEWquanRZGfr5+8NHr0dmVZVWXMRTknCgoADXKr/VJEl4qbF2Oi6SVVWFWSkpmBAWhhsjIpBVVaUVpbH9zFX7HHGZ4m1vSe/CzoaazzosMFCraKr+pqjLZpuQXTVXsDmeO7XtiPo/9A8H392mkJGxXPPMZWV9j2PHXleebwAAWCy1MBh6wmjsY1f1U5Zl5OfvRXr6lygo+NtuzvLyeEgSITJyMgCgsjIFkkSIiLix3vFNplSEh1+H/PzdLToPd0Is/hjGOZ1J/NVaatFncR/0WNgDVbWN3y07eLD54qs5FBcDz/63FsOGyxg71qpvVN3jKtUWC07NnInXaLkognm74j376CO7cZOUiwySJDx45IhWnGVyZGSzemHh1CnRI9DDQxSP6dZNO4lkJbxzXGgoQkpKtOeA9WLa7p/h6NFi30suEY9hYUiprMRFISHY9NNPIk/xoHMBn19To+Wg3HX0KLyUc9uSk4PBAQFaOXuSRNEHkkRuUl0ceTkzq6qwMDVV6++mhsherngPg4qLUV5djm8Of4N9x/ehtKoUnnM9ce5X5zb9fWXq8WudfmWvHTum9TB7oU4+41Px8fBycrEKCAH4shJ+uCg1Fe8ouU5qWKNtuxLVu9iaOTcdkYyMb7BBOhckiSqqv+bm2uW9lpZGQJII0dEPOp3n3eRkXBEaqoVJA0BJbS32J863CxHT673rhY25m82K8JoQFqYVFpJlGUdKSzFfyZVrqLWFu1BvXKh8qHj71Iqlah++75VWJWoRm0qzGRuV4jxJdTzg7ubX3Fw8qYTFqx7HhsJMv8nIwMUhIZ2mz6U7sMiyVoX4t9xc5CvFkc4NPIRPI+eDJGt4scVSg8kRwdrfUZXd31AkzOaGvczVFgt6G43oaTDgG+VG4yd18jGbZLelCoGBI7S/r7Cw8QgJuQiSRKiqsorVI0duhyQRysqOaucQG/uo3d9mTs6P2visrA2QJEJy8nsAVE9gb+Xm0BUwGPxw/Pj/AADHjr2mtJS4q9nn4W6IxR/DOKczib+g9CCQjnD3j87V3M6dwNNPW6tmNuBUcjv7CwrgKUn4Tin9P38+4OfX9DomMxIT4fnPP9h4893w85PRp2ctVt77IAbs2SOqbkL0UiNJwrnbtuHiXbu0f+rXhoe3vAVARYVISNyxQ3Sy37EDADBGuSOsesrUnmjf1glj2VdQALzxhlX9DhkCWCx4X7kgvyY83CUzPlAuomwXD8UzVHe9euf23SbmcEWXlWFlZqZW8EINlXKU/D9u1TiQjpBV6qCfB9MkbBusq4vaBmBjnaIYlWaz1iTeGeoNgIdiYnCBMle6yYS+RiN6GAyotViQpRx3TAMVL89UzOYKBAQMhiQRNgbdjsKaKqSmLkJIyEWorDwJADh9+mdIEuH48TebdYySkhCEhl6O9PQvUVIShqqqUzh+/E27C8zaWvcWXam1WLScrSfi4lBrcxNAXZoTmtcSbJuLkySKTQEiFPmPvLwG+1u2NiazWStYNd1NnsYziY3KjYS3jx/X+lM+EPg1DkmE8wP+BkkSkisrEXNiEbyl/drne1D5fAsLD0GSCFuPvGqXU2+WZcw9eRKfpaXhkFJ47IHoaO178i8HNyxdJTt7s1bVMyzsKjsRaEtKyhwlZ28FACAnZxskiRAcfB5OntRBkjxhNPZCcvK7iIy8CUZjL0gSITd3pzbH4cNj7P6WjcbeqKkphNHYB5JEMBi6w2xuYrRRK0Es/hjGOZ1B/JktZjz/+/NaJc8vgr5wOl51OqlLW/VtvlEJE3nARu01psMiSkuxLCMD5uxs4Nprkf3221olu5579+L/ZpaJLg7rfgFJ1ipyn/z6K0iSMPeFFxAdFQU/gwGDAgKQ0Yq5LQcLCzFKuah+NzlZu3NcWluLz9PT8bVyJ3NsaCjMgYFWD+Lvv8Miy1qpd5Iku/BNR1SazehjNKK7waCFydguF4aEIKe6WgvTVD14W5oZymeby7THtqG8DS/9+RJIR/g1/td62xLyErA7aTcKKxvvO8YI1Pf7laQk9LTJVUpuariyQrnZDE/J2pT6WuUmw+2KOIguK9NyQP+r5Kt1FdLTv6pXuMFg6KndsZdlGWlpn0GSCBkZ7strlWUzCgsPITr6QUgSoajI4La5VU5XV2tFT9SQVNWT76PXt2kVR0B4AtUbGcMDA9v8+M5YlZkJD0mC3kERpK6OekP1uvBw6BSv8dv+z0KSCC+HLABJEh6NjcV/pOni/7P0F0iyhpTHxf0Hm6URIElCb4MEQHwXpttExqjf03VZWai2WODbQOErVwkPv077uyopCYPR2BeSREhJ+cRuXEHBfkgSIS5OpC3Exz9rJ+5SUxfV8dr7ICTkYtTUWP+fpaTMhl7vjczMVYiOvl+Z7wm7/eqGj7YXxOKPYZzTGcSf6vFTl5jTDcfZJyXZC7/x4xsc6lZsc4zq5p05Y7wSGrRp7lzIRPjohReE92nTJpAk4dIDEaCzK7S5X46NhWX7dpy7bRtIknDywAEAophLW4TpWGTZYS5hZiawbr2MawPFhfaaU6cQnpmJWkX9qq0W1GWTg5LntqgX6f+Ji0NmVRUejY3VwrhsPXxhSggqSaL9QnMLeJjMZlwRGuq0hcLGIxtBOsJzvz9nt77aXI3BSweDdIQeC3vgZNHJZtnQ1diVl4ePT5yAWZaxr6AA3no9RgYFtajR+hibliWLlIIVqgd5XVaWFqK8o04BhzMZWbYgOHiUIvpW1gvFlCRCdvZGJCXNhCRRq+TupKYuVoTlsibtV1BwAEeP3onk5HecjkuurMQwpXjKTZGRSCgvx6yUlHb7nN9Tohzetsk17Si0ODLkDEUtIOSt12ve5NXSxZAkwhZppNb2RF1mSo+CJAln+fsjrjQHBkN3TJZ02vaimhrtuqCPZI3OuSosTAu3Vtt8NKcgUWlpuBKGOVb7zaytLcHp0z/BYrFPi6mtLYXB4AeDoTtMpnQEBg6DXu9t54kvK4tGVtZ6lJSEOPwNlmVZG1/3dyQp6WUlauDtJp9Ha0As/hjGOZ1B/M36ZxZIRxi8dDDm6ufW+2EyGoHbbweuvBI491wh+vr0EY+zZrWNjWoDbvUfhCsVvGKUggQkSTh7xw5cpgg+r4MHkTJ0KK78S9xZ9FptTTy/cf9+HLrmGpAk4VZ3NStsIevWifYVRMA5t/8/e+cd5kTVtvGzhaWDVEUUxQaCBbGgfirqC+KLvYuKHbvY9VVRQ1GKiCiiCKKCBVAURIrUk7a99957L9n0ZO7vjzNzktlks9llK87vunLtbjJz5kw25TzzPM99y0ueXhMXP5KB9APiz3vE3sA8kwmXx8RgU2kplhUU4NTQUKwuKsIsUYlwn1sWzuhw8AyfZAptczq5it47XSzbX24ox7Dlw0BUBIuOLoIgCBAEAbvTd8suTvyU+FObYzWYGzD/z/l+CRf9W4htajpuCwvJMJtQyseS+gtvSUzEEDGb/G/qZ6qtPQxKCeLjbwQA5Oa+Ly7aAlFR8QsoDYBONwLR0ZeI3mBpXTCHf0ApQVraY7DZapCX9wFMplyf+xgMSaA0kC8w27ooUGW1dnnvnL/U2WxYnJ+Pus72FFLoUqTvKUKZv+sh6upb/TPzK3xemIv59Ak8T+/DERqI52I3g1CKM/T/4FV6u+y772BpOLcaeYnejTn0HQyke4dVKQAAIABJREFUh2TWJ5J/aUcsZyRhl5KS9X5tn5e3CJQSREZOFsVcrm33MSVMphz+vCQn3wOzuVAce0qHx+xMiBL8KSj4pjcFfwdzDuLuHXdjb+Ze2J12hBeH4+/Mv3mvVXat51XUAwdkuiT8RikTmuwiX18PJD8yyTjXl4JXptGIq2JjcZEoLjLokKt/4LLwcPw2axZACPTilWzpFnjkKIbu24f5774LQr0bBncXtbXM2/Cnn5i6aUgIcM457Lm/4YBLUXCARoPQhgYEUuaDVWezcf+vpzMycImY+Tw1NBQnuUnzE8ok6FsasS/Oz8e81FSZUfTtSUkYqtV2acmrRFRJFE5acRKIiuDK767E0E+G4sy1Z4KoCO7ecTeIiuCtQ2+1Oc4Hxz4AUREMXz4cuXW+F8G9CV2hDp+FfXZc2bmuRCoDnuzW09dgt/Nep95c8mm1VqO4+As4HJ3r4SgJO1RU/AqAXcEvKfka5eVbAADZ2a/KruJ3Rd+O1VoJSgkiIs5FTMxlfNHoi8LCT2XzslqPTxVRQaEt3G0YpoXtFwWQbuXiRVK5ZHT0NKjV/aHWDMXd8Wq+TwCluDjsAAil+ChmKW8F+YGegaM0APvoICQkzOF9tuUWC4ZptQhWq5Ha3AybrQ5mc9ty5IIgICxsAigNgNXqX6uD3d4Evf5k/n4qKFh2PE8VIiPPh1odDKOR9Y9GRV0MSgmMxgwIgrONvbsWogR/Cgq+6S3B39rwtbLsSfCSYNnfE9dO9NjHbmctZYQA69YBOh0wciSzxevOtWmdqAx2bkQENogecvckJ+PO5GRMDA9HfFMTroqNxUOpqSizWHjdv/RlobvkEjz5/vv4RwrmKiuBffsAsHLJm2k6yIIcDFvvCoyGtDDn7U5KSpiQzYABLmuL338HDh9mf19ymRPJhmYu5y8Fe8vFMjxdfT1Guy3G3W+zEhLwQmYmZsTEYKMonNMWzQ6Hh8F3VxJXFodRK0fJXp8jVoxAVEmUX4JEDeYGDF8+nO971XdX9dpgqiUXfn0hiIogojii7Y17gCyjEQM1GnzRws9lT3U1y6JT2n4LlG4iK+sl0Y9rLmprD6KhwVU+7nA0y2Ta/aW5OQVqdTB0upGtqhA6HM1ISbkXsbFXIS+v60olwsJO91AD9bVwTUq6HZQS6PWjQSlBU1N8l81NQQFgAkI/lZdjfloavktUiX1xu1Bfr4Za3Y+/drOzX+cXTY7QQNxM30YgPYavS0qws4JdgJpD30MQpRit3oNjlCA/fwlCQ08Ve/Jc77M1opfpvJRkREaeD612qEyp0xuSMq836wVfGAyJSE9/AnFxM/0KMn1hMuWiqckl3pafvxiSv2BU1AUwmbq2EscXRAn+FBR80xuCP0EQcPYXZ4OoCFboVuCcL8/B+M/G4+afb8b5X53fajZl1y5PK4eGBqCbxd3wjygWMj8tDTEtlN4IdRn5EkpxvpghvD8lBU+mp2Pxtm3sJF5+udXxnU7mV0heczWOu/uWSefcMn5ITAS6ouXkzz9dGdaxY12ODYLASm9FZweUWixcyOOU0FDUu5VAlVksWF9SgndycmRqoQdaEVvpbeTW5eKXpF+gK9Thkg2XYG34WlgdVgQvCcapn53qc9/Pwj4DURE89ddTmP7tdBAVwZ6MPd00845TYajgAetSzdKenk6rSOW4LdlQWtpmr2lPEht7tSw40mgGwmIph9lcAK12GJdW9xdBcCI29qoO9dp1BfX1WmRnv4H8fBUyMp4BpQSFhSu8bisITuh0I6DRDEBGxtOglKC6+u9unrHCvw2LpQzZ2a+iuTmFv3ekIEYSOaGUoLT0W1itFeJrdDByct5Go42VkmcZjbLv/9n0A+h0J0EQHLxPLynpVgCAwZCM0JhrMIzuRjA9jJ10JD6hV+JC/W6fJfBSCWdR0WrZ/XU2G9YUFXVZWbvBbsfa4mKvNjnNzSktRKX8K0ftCogS/Cko+KY3BH+pVakgKoIrNl3h8ZjVYcU/2f/AbJdftRYE4IYbWKAhJsnaRanFgojGxk5RYpOUwdaXlMDmdOK/iYmYlZCAXysqvGa4JkdGwuxwsJOYOpWdRBtyz2+8AZD7ivgYkhGtRgP068eGuO02tq3dDjzwALtv3DgWPHYmy5axsVevZq4Q7qxbxx576SX2d5HZjJTmZu7B5Q2L04nTw8Jwdni4R5lnX0PKjFUbWy9Ru+3X20BUBOHF4diftR9ERTBtwzTUGGtwxaYr8FXkV506pz0Ze/Dc38/BaDNilX5Vh7N2vyb9yoO/6364DvpCPVc3zarJwoI9CxSxm+NA8udyv2Vnv4r8fOafFxY2wef+Nlu9LOitqzsCSgliYi7vUNawKzEaM8Qy0HO8logZDMliX9JMLhZTUvJ1D8xU4d9EXt6HsvefXj+Wvz4lWwV31VqbrRZ2u9x/1CEIsu/7D+gNSE6+kz3mMIPSIISFnQ5BEBATczkoJZhHXwChFI/TpzCdrgGhFDNiIr2uTwTBgfDwM8XA1NUyUGezYYTYOvHRcXgHtoYgCJgnekVKXqwNdjt2VVXB6nRCEAREREzyqjba3RAl+FNQ8E1PBn9GmxG3/norL4FrK5uwYQPwwosCqiw2fP45CzLOPbf9wY1TELhX3Kmhocg7zjKwmxMTQShFrFsjt8SHYsP3pdHRuDgqipV5SjLb4eHsJK7wDHpbcuQIQEZbMPLXWOytqcG6dcDttwMTJ7Ihhg5lPyMigEOH5P2Px2Ej5JWHHnL1VbakpoYFo6NGAe25+FhttaLmBBBHePiPh0FUBMfyjnl9PDVVwPBlYxCyNAQWuwWCIODK764EURHM2zkPREUwcNlA/Jn2Jx7d9Shm/jATCeUJxzWni7+5GERFcNNPN4GoCIZ+MrRDY7rbrUi3u7bfhaKGIpy+5nSezVRoP06nBZQGIjR0HEpKvkZ9vRpa7RCo1f1l5ZKtlWpVVe0CpYEoKvqc39dRhc3uIi7uOlBKUFd3FABb1BYVrUZl5Q4UFa0WF5Ef8EV3bu57PTxjhROdhITZ/L0WEXEeGhtdvcN2eyPU6v5i/6nvPrtRYhB2U/QBFBV9CbO5kD8WGTlVzGTvFtU6L0aOoQqB9BhGa4+iHz3CA8fnMzNhbHHhtKZmL5hFy2zZ/fe7idUcj3dga/xcUcHHH6zRoMZmw5ViT+PUyEhkGI0wGBJQUbGtx9sYiBL8KSj4pieDvz/S/pAtJBMrWv/AMhiAwYMB8kQeAo5RBFxbhYEDWXlheznSwnbg08LCtndqhUqrFQM0GgzTamHzEoXW22x4OiMDkY2NKLdY5AHik0/CXxd6i4X12Q0fDtTVAYMGuYK7u+4CNm1ivz/4ILBiBft9+HD286vOTSRh2jQ2bmsq6nffzR5f2zvXnF3KSv1KEBXBo7sehc0hD2br64GRZ+WBqAjO+mQGv39z3GaPoMr99vjuxzs8nzpTHQJUAR5jnrn2TI9semtoC7SYsWkGBiwbgABVAG748QY+TtDiIFyy4RL+95BPhqDZ2rmCJf8GmLIlQULCHH5fYeEqj0xgZeUOj32t1mpu4B4VdTG/XxJ66Qpvvc6gouJnSN5jTqcFqanzuAopM44OgMGQiPp6tSi28WhPT1nhBEYQnNBqh0OjGQSLpRROp+fFyOLiL5CT81abwc1f1dVeAzcA3BtPoxkEZrPC1KHvcvOzvYiuxTA1U/ueGRcHQRDgdFpQWLiKB49VVbv4mEmicvgQsb/eXfCqvejq67GisBCrCgtxpK4OgiCg3mbDGL0eAZT5IEoaB4RSDBOPeZ04TwDdIr7mC6IEfwp9hJcIITGEECshZGeLx4YRQrYTQgyEkHJCyBstHh9PCPmHEGIkhBQQQh5uz4F7Mvh7cdcCkFVngiwdiBt+vMHnB+oPPwDkvEaQI2LQ9oceS9Z2LFMkXSF7JSuLNWYntD8LIggCwhsa8IYoatJuPyezmUWzgwcDXjKG3vjvf1lQ9cQT7OfMmaxVsKqKKW+OHs0sF669lj3+4Yfs5wMPtPv0WsXhYEIvo0a1LqqTlMSyfwMHsp7Do0eBL79k5agnOrl1uRi5ciSIimD+n/Nlj732GkAuYKWTQbe+wvsx6831CFkaAqIiGLNqDMZ+OhYDlg3AFxFfIGRpCEatHAW7s2NP3p6MPbKg7+rNV+P2bbeDqAi+jGjdzHtT7Cb8GP8jVupXImhxEN//9m23Q1ugxcXfXIzZW2fz+6dtmIaH/ngIREXwY/yPHZprX6ShIRRRURegsZFdhXI6LTCZXCVX9fUav3rVKit3iGWer/H7BEFARsYC0abhBlBKkJW1ULZfaem30OlGygJE6fgREcyjzG7v5iZoP3E4zNDpRoDSAFG50CXuwrzDngPgkpWXrCoUFLqC5uY0Xmrclbhf1AkPP5MHmcfcLkp/rL8Xv9NRmBoRytXD3VV52X6u7wTJomJdcTFOCwtDEKWwtqMkqshsxvbKSrwveqK635bm5+Mlca20ICMDYW6exmeEhaHUYsEFonL5kbo6bC4rw0CNBr/3oJcqUYI/hT7C3YSQOwkhXxHP4G8LIeQvwoLACwkhVYSQ29we1xBCviaEDCSEXE9YkDjN3wP3ZPA3Ye1MkGNHcdaOrah0s0ZosNs9AsGZMwGyTvS7+4GJplwdGY+mdkYUuSYT+qnVGKXTodnhwDCtFoM0mnZ9UALAD2Vl/AMwWK1GUVtXuhobWcAnceAAi8zuvdfvY65dKy/nbOkl/9pr8sfLylgwOG5c56mf5uaysa+91vd2S5ey7S67zJWlvOkm+VNwolLYUIhxq8chQBWAzBpmK1BTAwQHAyG3L2QB0wXbsMxNafuu7XeBqAie+/s5lDWVoaypDADw35//C6Ii0BR4z97YbEBcHPv/lpV5ih29efBNbkx/9hdnQ1eoQ3JlMgJUAThl9SmoN9d7jBlRHCELGAd9PAhbErbAaDPK3pcZ1Rl8G5pPoc5X837AzqTB3IDw4vBOHbOzSEm5TwxM/gOLpQyRkVOhVgejqSkWgiBArx8jmikbfI6Tn68ShSTkVQCCIMBgSITJlC9KzF8qe5xl/AKQlvYo9/0qKvocdrsBlAYgPPzsTj/nzqSq6k/o9WN4cGexlCEr6yVERV0Am42JP7E+KVaGp6DQVZSVfQ9KCXJy3unS49TWHuRBXE3NAX6/IAi4NDoaJ+l0SMhmgi7rY14CoRRTwg7hKA2ATjcK1dV/y9RA62w2BFGKMXo9zA4HbhI9clP89Ex9t0XAN0ijwarCQnxeVISBGg36id66I3Q6VFmtEAQB35WV4cfycp7Z3Cl6qZ4RFoYBGg2C1WqEdpfPlheIEvwp9DFURB78DSIsG3iR230fE0J2ib+fTQixE0JGuj3+CyHkc38P2FPBX1FNPsb88zX/wLl471/4uqQE40RlzEujo5Er9uLt2ydm/ShFv61RIIPtGPozKz04JyICO6uq/DqmIAi8P29pfj4A5hFHKIWm3nMR7AvJhHy4Vtt21q+kBBgzhkWwEi+8wCKiLVv8PmZDA3DddWy3qVM9Azq93hX4nSeuky6/nP3dGf7ndjvw2WdsvGef9b2tzQZMn+6az7Bh7Ofmzcc/j77AKv0qEBXBM3ueAQD8/DNAiIARi5h6LTkpD9df79o+qiQKMzbNQGpVKr/v4EEg5KpvQVQEL+570eMYDgcwZw57XhcsYJnWCRPk5bhXbLoCREWQUyt/ATzy5yMgKoLp305HZbP8Cq2Uwbvg6wtwxaYrkFKZ0up5LlYvxhL1EgDs/XXWF2e16snZUaasn9JmWXhP4HCYoNEM5gu50NBx/Pf09MdhMuW6CUTofI6VnHyXz+0EQUB4+FlijxyT17Vaq8VSz4sAAI2N0Txz0dCgF2XX/b+41FPY7U2or9f69AbT60dDoxnY471ECicmguBEUtIdHuWUXYHd3ojw8InIyvJU+K632VBqYdUDev0YHKME59P1IJTia3o+amr2euwj9eItyGB+e6+K1Ui/+ZF5cwgCRul06KdWY2FWFj7Iy0OywXWhallBAbfIOVRb2+o4TkHAA249h58VFfnzVHQZRAn+FPoYKiIP/i4hhDgIIYFu991HCMkWf7+LEJLfYoy3CCGH/T1gTwV/D3//FgilmES/waX0U/6hEehmjTBcq8WWnGqMGQOQt5hx+HWrS1g/2SY7bhMDtyBK2868AdhbU8OOGREBi5jpk0yhH0tL83thUSNeaRsXGiozG/eKIABz57qioMJCICaGrdIDAljNZjsQBCAyksWTLXE6gVNOcfX+AcArr7C/f/21XYfhlJYCU6YwsZ35812n8bUfwntJSUD//sDkyS57iIcf7tg8+hoN5gYMWz4M/Zf2h9FmxIMPAuSc/dzXb8wYICQEaO3iLLfNGFwB8v5ABKoCsS9rHxoagGeeYf8TSeyn5e2661jwbbQZEbQ4CONWj/N4bRusBty45UYQFcH4z8YjujQaB3MO4prvr0G/Jf0wcuVImGztF0JaqlkKoiJ4/+j7HXnaPEipTOHZxW+iv+mUMTuL6uo9oJTIyi5TUx+GVjsMGs0AlJR8xe/3JbpSWroBlBJotUN9lmhWVe0US77O4gGT1DMHsAAxNHQ8KA3kqoXHa+TcW4iOngbF6F2hq0hLe4Sre9ps7bsQ3BH8WWvY7QYUFa3By5pHQSjFa8megR/gKvncK9okbRK9hqdFR7dpnRTRyC6qz26l9cXscOCN7Gzsrm77fScIAnZXV2N9SUmPX6QhSvCn0MdQEXnwdy0hpKHFNrMJIRXi7/MJIQktHl9ACInwcYyPCHtjSLceeXPesvltDDy2D+e/8in++H0C7qIv4+w/duBwZSXsTifecy9FuKcYQYc1GKrVoqDchs2fN/L+safSWVAofTjpGxoQ00oPnZT1c/8gK7dYcLJox7DGz6tVm8WSzxcyM9ve+Ngx+cr8/PNdv199tV/Haw/PP8+GXrWK/c0yTsCr7bMI46xcyfY/6SRm5j5mDBOQ8VcgNSeHlTw2NrIS1PHjO68EtbcjlXKqc/Xs+XviehAVwe703dyKY+dOlsGTkKqP9+5lj59yCkCm/A6iIghZNAqvvu6QvZxGjWLWGwEBwLx5rMyWiLaR+kI9V+T0htlu5gqeU9ZP4aqjREXwwbEPOnTORQ1FCFAFYPxn42GxWzo0hoQgCFw9lagIXtr30nGN19mkpj7MBRsKCpbzq/JS+SXrZyOiWMl8r2NYrVVQq4OhVvfnGb3WEASBZwjj429EcfEXoKJ5tERm5otgBur9xUyiuvNOuAdJSXlADHwnwmBI6unpKJxASIbpYWGn96gxeWukN1Wz6qioKI/HzA4Hhmq1GKzRMPsoAKFuPXnBarXMX7clkk1VT2fqOhuiBH8KfQwV8Z75C3C7714iz/zltRjjTdIHMn8AEJ+Ug+AQG55/nvW7FDwsroYBPPUUcNHCSlkt+pL8fGYuFxDAauIAbhC+JD+ff5AN1GhwoKYG96ak4OKoKKwpKkK+yYQASnFaWJiHl1xsUxP6qdUYrde3mcmLbWrCWDFYpHV1bZ/kRx+5evukFfuAAcyU7+jRjjxtPikrA958kylLAkBWFjvkjBnAokXyQ0rfCVu2AK+/zvZtyRVXyGPXjz7q+NyksbKyOj5GZ2G1Vssa5gVBQGnpRp/KiIIgoKkpFk1N8bJ9W2O5bjkr2fx5DcjoNBAVwXnrzoNTcHJ1VkKAK68E1Gpg0iQWYC9cKGb9CLBnD/DXX0D/569lQdDIbPTvDxQUsP+xVKFTXs6C6qIiFqATAjy/dQ2IimC5brnPeV6+8XIeYJ3z5TlIqkjqsMAMANy5/U4QFcFi9WKsDV+LrQlb0WTxT9RIwmA1YM5Pc2S9h9d+30ajaTfCzJpZD47dLj83ozEblAbKRFgiI6d4Haes7DtR3MSzrNcbdnsjoqOny8auqtrJH5e8/Vh/4CU9fgW+szCbi5CYeAtXNPWmxKig0BHS05/o9T6SkyOZzkFhiwqnFzMzQSjF/Smu0nyjw4Hp0dF83fRPK+WahWYzLhaFWlL97A/sKxAl+FPoY6iI956/C93uW0Z89/z9TPpAz5/E1VcDp5/ODH93fHcmZo5JwbvvugUcr7APt6uio1nQNnkye+CaawAwWWJCKSaEhfGy0ZZqVcRNnlgl9vq15Pr4eBBKkWBoXZjBKQg4TTzOwqws/xZWN93E5hsZ6fJe+N//OvJUdQhBYFk76fm85BJ2v17PFDkfeogFHISwMsRJk4Bvv2X7FRay+0eOZD+Dg1kZaEd55x02zrffds65dZTm5jRoNIMRGTkFZnMBAHA5+bCwCV7/r4LgRFbWK3xhHRMzo9XtJI7mHWW9cx89CHLjeyAqghW6FQCYXcfs2a4y3X795D+ll7h0iAe2vsCCoMm7sGCB7/P75hu2/5QPH/TpOSjxddTXPMBadHSR78H9IKkiycNe4vKNl8Ppo6fLHbPdjDu23QGiIpi6fiqiS6Mx+OPBGL58eK8IZgRBQGzsVaJAyyav20g2CzrdSQgLOwOUBnoVfUlMnCv28fn+H7kjqV9Kt+bmNP6Y02mDTndSq7YQfRlBELjqaWHhyp6ejsIJAMu894dWO6xNUaae5H9iJdSshASYxAzf7mqWERyr16PE4lll8Y14YfxDL4bvSQYDgsS10Znh4b3ic7UzIUrwp9BHCCaEDCAssPtT/D1EfGwrIWQ3IWQoIeQCwko+3dU+tYSQ9YSpfV5H+pDaJwAe6G3cyHo6JkxI44vfkBCA9HPigVmfo+amm4D4eHka6scfUf/ll7Ig78viYm7g/kJmJn51MyadEBaGilacx5e2Uf5QZrEgSqyPn+nmZ+MTp5MFfIMGMbWUDz8ELr3UlZbrJmbNcj1lgYHMWUKyi5But9wCjB3r+vu111jpKCEsaPv00+MP2g4eZOPdcUfnnFdHkTIIUrDncDQjMfG//D6DwVNYRFJj1OvHIjz8THHBTmXbFBauADPqPgXl5VvRaGlEgCoAA945E+TVCQhQBaCoQf76SklhQTUhwGOPsUyf9D9wr/KRArThty5rU7wnNpbtP+h/ZyFAFQBdVCPWr2eBpFrN+kUNBkDyAa4z1aH/0v4gKuJT3KU9SOWkj+16jJvMb0ve5rFdUUMRVFSFqmbW+/qx9mNuLTFp3SSuRiqVpObX53fK/I6H5uYUMQN1YasiJU1NcaA0CMnJdyIl5V4xGNsu28Zub4BaHQK9frRfmWR34uNv5K/XllmwsrLvkJn5PATB02Osr2M0ZoiZ1Kk9PRWFE4D09CdFi5XXe3oqPqmz2TBNzOZdFBWF6MZGnt3b30pfX6Lo/TfLSz/fisJCEEpxZ3Iy0k6wrB+gBH8KfQcVIQQtbmrxsWGEkB2EBXUVxLvP30FCiIkQUkj6kM8f4AoIHn10MSgl2HXfdIQEO3DLLcDu3cDs8amoIqPZRqedxn5eeqkscjl9+3Ye4JVZLCixWLCrqooHaD+UleGTggIYfNhCSN41/xVXxEaHg++/VhSFkUok/K6PT0kBN+TrQd57Tx7o7dsHjBjBguvTT2c+gFIsGxnpKhscPpxV2Kal+R7fX6xWlkUMCen2+JcjZfgiIs5BUtLtoiLi/bJMSkHBxwBYpiErayEyMhZAre4PjWYQjMZMbk6dknIfH1cQnKLYBgGlQWIv2BZM+nIyz37d+/MMmUS3xLp1wK23MjVXAFi/ngnsuKMt0IKoCB7c+SBqTbWs/6syGTSfeoxXWFuBgBs/BFERTF43hb9tpArk0aNdGUepWmhjzEaoqKoznmIAgMPpQGFDoWzuZ39xtkf275k9z4CoCE5acRL3SAxeEoy7d9yN3Lpcvt2zfz8LoiL4K+OvTptje6mp2YvIyMlITr5HfJ184nN7gyEZNlsNL8XU68fKBEsqK38TlUGfbPdcpHJRSnumZ7sniYycDEqJ1/eSgkJrmEz5SEiYhcLCFXA6bairo+L78uRuEXk5XmpsNtwgVihJWbtLo6NbvRDtEAQM1WoxRKuFo8U2t4j6B+E9aMfQlRAl+FNQ8E1PB38GAxMCmTQpCpQSJHxK0PDQ8y5D8EmTAEJgHxQAZzBh0UhuLmtUe+wxYNAg3PLJJ7y0s6PYnU4M0RzDIPURqOtqMUCjweTISHxRXIyhWq0su5ju75Wyr76SlXmazUWor9d2eI4dJSOD+fI9+aSrx4wQ4PbbWXKy5XfHDz+4AsWHHurcuTzzDBv3++87d1x/SUt7lIt0mEw5UKuD+SI6O/sNUEoQG3slAKC6eneLoJD1zjmdFtGbLAjp6U/AYinhyovx8Teipma/mJ2YjFs2PA2iIhj1CQFVh3j4tPlLramWB5GBiwNx3Q/XYcCyASAqgtiyWL5ds7WZZ9qIiuD8N17g/8uAAE9l0O6y3rjm+2tAVATx5fH8PqfgxMiVI/lcT1l9CoiK4LZfb/PYf0P0BhAVwcv7X8Zzfz+HqeunYuH+hWi2ds9Va0EQuOKkdDMa/RB8EsnMfE68YPAAv08ycK+s/L3d83E4zEhOvgslJb1LAbU7yMx8AZQSVFR0UMJY4V+HIDgQF3cNf+9GRV3ABZkqKjwrEnorgiDgy+Ji3t6yow07h9miJZXa7WqrQxAwXKvFwA74G/cViBL8KSj4pqeDPwBYswZYtswJvXYU1AcJHOdNYA+UlgKEwDpjEvS60Ug8NB345x/5zqWleO+pp0Aoxcet9PP5y2z6PgilGKA+4tEzeJJO1776+I0bXfV8R4/CZqtDWNjpoDQQJpNnDX53kJgoX/hv3ep9O6eTqUaGhLDAsTORxE9nz+7ccf3B4TBBqx0KjWYQHA4WNOTkvANKg1BS8pXopXYmKA1Ac3MqoqIuFpUaH0VGxrNwOl0lw+XlW7nHm14/FvHx18PdpDsi4lxQSvCWKgPk0g3Y+usivvAwmXK9zq+3HYFdAAAgAElEQVQtRq0cJeujk26zt7qeTEkdc9w7NzJriX5GDBoEDBnCnvchQ4Avv2S9tuQ4VGDbyxL1EhAVwZqwNfw+yUx+5g8zcdE3F/Hz+TnxZ4/9q43VGLBsAEKWhsjO/dUDnXcCvt7XDQ2hssAvKuqCdo1ttzfxcuGKim2y15pkZq7gH1VVf4gZ06d6eioKfQTJTiU6+hJZyXRu7ns9PbUOcayuDmuKijwyei35TlQmPzU0FMWiWEyCWA56Q3y8z337MkQJ/hQUfNMbgj+J1NSHmHrdNQTIz+c+BbnfXOpV3ECictYsqB59FIa4uHYdz+m0w2xmJZx2exN20DEYQPeDUIrzdH/iWHks5qWmYlZCApINBpwXEYHV/pR8ZmQw5Y4BA1gQCMhKC0tKvmrXPDsLhwMYPJgt+ufMAbz0iHPq6zvHGN7bHMaMYU9Pd7caSD5pki8awBb87mqNRUWfgRl2nypmAa9uNSiw2w3IynqJ/1/V6mC+kE9Lmw9KCebM+QcBAQJ0unP4dr4833wx6ONBXJHzf4f/h58Tf8akdZNAVASaAg32Zu4FURFM+HwCln9ex4P8tWtdPZ5PietlqSJ51izX+DodcP/9LCDsbOVvXaHOI6v3zuF3QFQEX0R8gSO5R0BUBP2X9m9VGVQq/ZT2GbFiBAIXByKqxFMC3Rd2px2xZbGIK4uD1cEC+h/jf8SolaOwLnId3jj4Bh758xGZ4qlk65Cb+y4iI6eivPzHdj8HdXXHxNdAIPcVi4m5rN3j/Nux2WpBaQDCws444YQqFLoG6fu3ru4oBEFAbe1BlJV9f8K/fgRBwIKMDO7712S3c29jb0IwJwpECf4UFHzTm4K/ysrfmULeHoKc3XNR+fp02IYQaI8NdCvNe81zx9Wr2Ur2rbfadTzJCLm4+Atetveq+j4E00NYTZmcekLCLNTWHvJ/UEFgaS1CmEoKXAIRUqYoMfGWds2zM9m9m/WUOXpQC2LePPb07N/ffcdkSoE3itL4u1rdzuEwIyxsAldq9Cb+0pL6ei0KCpajuno3v6+kZD0oJXj0URVeekktBpTjxNLQ6z0WHU6nFfX1Gp/CHxtjNmLC5xOQXp3O7/sh/gcQFcG8nfMw4fMJICqC/Vn7ERfHnuPJk1kmNzeXPe9SctxmYwH4ySezvysq5II/bSmKtherw4pBHw/C8OXDYbab8ebBNxGgCkDg4kAU1DPF1c/DP8eWhC2tjpFenY5+S/rh6s0sIP8u9jsQFcH1P17v9zy2J2/HmFVjeBB5x7Y7sDVhq9eM6nex3wFgF4aOHAvGviMBeOfQqzDbzW0cpXUqKn7hnwMsmOw+5d8TCUlttaEhvKenotAHiIycCkoJbDbvtgcnMjank5d/zk1MxFnh4SCUIqKxsaen1mUQJfhTUPBNbwr+BEFA7sH7XOVVRwgKXhrBxTXU6hDodCM9PZ7Ky1nj4Mknu8zr/DiWTjeSH0sq2ysoWA6TtRHFxV8iPPws/nhy8p2w2/34sExOZqvnSZP4XLKzXxflyVdAqx0ulh12fAHZ19m82aUw+tJLQBttCwBYs35e3ocIC5uAyMjz23z+cnLehlY7FBER56GpKR5VVbtAKcEff0xBWZnv10ht7SHEx9+Axsbo9pyWjMZGZhy8cuUcqNUsy1NW9gNCQ08RLwQMhFodgqKi1QDADbsTE+e2qiDp9TiWRgxcNpAHLPfsuIc/FhHhO7t60UXs/1BVxfo/CQEefJD1Bk6cyDLDPpxP2s1NP93EhV+IimDEihHYnry97R3dyKzJRIOZiRQ4nA5MWT/FLzsLAKgwVGDoJ0MRuDgQs7fOxrjV40BUBCFLQxC8JBhvHHwDREUwetVoEBXB2E/H4v7f74c+lV0keutXwv0LjweTKQcJCTdBoxkAg8FTiU+hbaQyvoyMZ3t6Kgq9HKfTBrW6H0JDT+npqfQYDXY7pohegYRS3JaU1NNT6lKIEvwpKPimNwV/AACDAXVzTkbCShZ06Y6yq+S1tYeRkDBLLP30IkcvrV7/+gtYuZKlPKqqPDaz2WoRG/t/SEl5QNbDI91qaw/ybQXBgaqqnTwIzMvzwwNt2TI2j4+ZYqTTaYVePxpqdTCs1kquFOh+nJbU1OxFauqDHubRJwpFRfLew9fbUNmurf1HJsxCKcHcuVtx2mks6Ssl0SyWMmRlLURBwXJQGsC3/eqrF/HXX6wHb/r0w7jooq5XGz1yxIYDBwbiwIGh0GgGQKsdBoejGZWV2xEbeyV0ulGgNAgazQCYzYUy+4n09MfbZWL94M4HuRBMRrX/TZoPPcSe/yVL2M+zzwZMJpfB/NSprETXaOzIM+DJbym/cZGa6d9O97C96OiYREUwY9OMNn0En/rrKRAVwZsH3wQA7E7fzYPmpZqlAICY0hhUGCr4c0pUBGt3h4BSgjt+OB1Bi4MwauUor0Iz2gItdqfv9tvP8ES0YugubLZ6/r5qbk5Fbu777avQUDhhcDiMKCpaA5utHnZ7k0d2r7k5TbzA+58emmHvIN9kwli9HsFq9Qln6t4SogR/Cgq+6XXBHwDU1aFy1Vy3Xqr+cDhMyM5+VVTH+81jF2H3LlRfTWB8YhYwfryr2akFaWmPtVBw/IQHlZQSmRS7hNlcJPaYnNb2gu3yywFCUB7zMXJz/4fq6j08cwgA5eU/igv8J+TzFwRUVf2J+nqNGBgQFBd/2Y4nrW/hbjw/ciQLOrzhcJgRHj4RlBLk5LyDsDBms7B+/ZUICmL7L1wINDZGiwqcrv/txo2rQCnB/v2DQCnBF19cg2nT2D4ffNC15zd3LvDmm0/xuWRmPuexTV7eR2IP4jzRCJxwBTp3G4m2OJx7GERFsGBP+2o1ly9nz4WkS/TLL+z+t96SB+fhnVhZZ7KZkFiRyHvtjhen4MTlGy8HURFsivVuuA4Af6b9CaIiGLNqDM8cCoKABXsW4L7f7pP19wFAk6UJf2f+jYvWnYIjxwh+/4fgq4gvMf/P+R7CNQBgsBp4T+a1318Lg1WeMq0wVGDh/oXIrPFfIVTBNy0/y8PDJ/b0lBR6gIKCj0Uxl2mIjJwKvX4MLJYy/rjU652V9XIPzrJ3UGW1nvCBH6AEfwoKbdIrgz8ANlsNz95IV+xKSzeCUoL8fE8/svKSH1igeJig8AFx1TpjhmybmpoD4gJ7JB+7uTmN+/1Q2rpnVkLCHFBKUFNzwOvjgiDAWpjEbCmmTOR9PdHRl8Bdltxub4JGMwha7RA4HK6USmXlDo8sZFTURbLeMKfTesJkCw4cYA4Yd9/tMn7/uYXI48aNwFdfLePBs8MBXHCBgO+/nyq+LmIwcCBw8skmrq6ZlPQYNm6cjmXL7sEZZwjYsMElFnT48NfIyWHHu+iirju3wkJ2jDPPtCMj40WEho7zKlTkcBi5ZYSkIGk2F/NA0Gj0P4uXWJEIm8P/bCHAdIkmTGBzvfBC1hsIuLw3pdu337Zr2G4npjQGAaoAjFw5EtXGalQYKlDYUAiHk71XShpLMGz5MASoArA/q32Npt8fvRKUEjz+A0FWTRbSqtIQoArAmFVjZMI025K3yfoFV+hWAGDZwJ8Tf8YZn58BoiK4//f7O+/E/+XY7U3Izn5N1kMpCXgp/HtITZ3n8d2ZlHQbL5/Pz2cewqWlG9oYSeFEgSjBn4KCb3pr8AcA0dGX8j48wCW33jIr4nAYERZ2Guul+odAfYjAMYCtXB3ZKVzRURLyqC77A6WfXo+81RdAcDohCAKKi9eipmav5yTy8oD9+3lwFh5+Npqa5KqiTqcFiYlzQY8FoPRWgrLPZ7f4MgqCzVbHt5eU/ioqfhHnb+Jz02gGITT0FERGTgGlhPedlZR8BUoDoFb3Q2Hhys58mnsUrdYVZAQEAKGh7P7CQmD48Dr8/fdwHDrUD8uW5XL/wddf/0Z8HTyAK6904tVXn+Nf+Hv3CrLA5YMPFvH/gdXKmgunTmWPHaczSKts2CDXH/KlKJeV9bJbuSfLBrOyVaYs2dXY7cDRo0CZ60I5jEZwY3hCgBdf7PJpHDcv7nsRREVw4dcXIkAVAKIiOOPzM7A1YSvv5Xv9nzbqi1vgcDRDrRmGQ0cJLv7qdP5/fHTXox69f3fvuJurkAYtDsLoVaOhLdCi/9L+sqDwvHXndep5K7D3V1bWK6CUoLy8dcEghe6luTkdRmMWAPZeSkm5HxUVnjYux0ts7NVu37UBfC0QGXk+EhJc38X19bpOP7ZC74QowZ+Cgm96c/BXUvIVdLqTYDRmA2B9HuxDfapsu8LClax87shMpC4Se/cWXo2yuQSaQ4FISbiLmyynpjwI3HSTa2Wb24bnmqjc6UxL5v16Wu1wmM1MoVAQBCQn3y0L9vTqEbK/4+PlaoS1tYdBKUFs7P8BAPLzl/Cg1marg81Wg5KSr0UBkP9CEASe2dJoBooB8cew2xs66ZnuWXQ6YOlS9u847zzAbAbeeAN48sn3QSnB228/LwvoQkPN0OtPBqWB2L6dCfUcOzYSZnMxXn9dnrXauDGKP48S777LHvuyE6tqf/nFZVx/xx1s/GNta5CgoSGMv05KStYDAMzmYv/LjLsIux3IzGTncc01rvudTvbY8VJZCXSm2Fy9uR5jPx0LoiIY9PEgXLHpCh5wBS0OQv+l/VFhqGjXmBUVv4JSgoMR1yO61CX+k1+fj5ClIei3pB8OZB9Ak6UJA5YNwPDlw2F1WHlpqHS79vtrMf3b6bwvszUrC4WOU139F++X9UV+vqrDVisK/mO1VkOrHYrQ0FPgdNr5Ba3w8InHba/g7ospCAK02mF87Kysl9HcnCozdGetI/1kF2AVTmyIEvwpKPimNwd/3ggNPRVqdT8uiOF02kXzdAJjYypKH2P9cpFh53mUguj1Y2GN+EceHfzm2T/IcThc7thbtkAQBK7cGRd3Lez2RpSWbgKlBBHaM1A+m0C7P5BfdUxMZH2LRUXy/iBBcCIq6gIx+7cNGs0gqNX9YTLl822cTgsiIs7jGSBKCWJiZqCu7ijU6n6glHnRWa2eojZ9EbvdgBdf3IuZM3/DN98IuPbaQzh0qB/U6v5ITS3G3LnMdH7ePLZ9YeEK/n/dsmUSPv2U9VJJPX3//S/rJSwvZ+qdFks5P1Z4ONvmP8fZ/y+tYUpKWN9cQAATsxkyhN2sfrS1ucy+CRobXX510hXr2trDHZ5ffb0WZnNhh/d3Otl5DBvmOtcHHwRGj/aqpeQ3FRWs5/Paazs+hjcOZB/AzB9mIqwoDACgKdBg+PLhICqCZ/Y80+7xMjKeAesx/t3jsR/jf+SB5qKji0BUBE/sZpnbckM57th2B/ov7Y+H/3iYL3Yf+P0BEBXB6tDVeHDng5j+7XQUNxYfxxkfHzm1Ofg91fPc+iLswmAgwsJOb/WCidlcwLNDzc3pXrdR6Byk7yxKCaqrd8uUtQ0G/5QmBcGBioqfkZW1EHl5i2AwJKKsbDMoJaiq2glA6sdn343yfQUYjdkwGjNQVbUL9fXqTj9Hhd4LUYI/BQXf9LXgTxJnqa7+S1Tj/EOW2TGWRcsCvqJ3zwY9wn6vKdjOlEAJAc4/n/18553WD5aa6goSX3kFAOu7i4m5TMwADgWlgaA0CI0rmIu2Y/UyVFf/DZMpDwZDEjIynobN5iktWVHxs2ye3pRE6+qOys+l6HMAgMGQyAPLzMw+UJPXBg5HM89sUkqwePG92L9/sFjG9aPbdq4gxOm0oLBwFXS6XejXz4J77mHZJEm10uls3fXD6WSuIMHBHVP9LCtjweXw4cCiRcyuQnqZ3Hsv+3nnnf6PV1t7GHl5H8muiEuvj7S0R9o/Qbi/doKQl/dRh8YAgKuuYueTkQHs2+c6Ty9aSm2yZw/w7LPAI4+4xqloXzLOA6fThvj465Gd/arXx+PK4vDy/pfbnfUDgIiISaCU8HLhlrx35D1Zhi+iOEI+N8Ep+5+uDV/r4SW4Ibpn+pDU+Wo+h/jy+B6ZQ2cj2fXk5r7n9fHS0m/5Z0xq6kMdOkZzcwpyct7066KKIAgoK/vea7/viYzNVgetdgh/riURK53uJFBKkJ+/1Of+RmMWrNZKfqFVumm1QxAaOl68+DoTAFBTs1/M+D7VDWem0FcgSvCnoOCbvhb8uX8hxMRcwb8MamqYkIMgCDwTmJo6D7DbUfP2TFTeQIDXXgNuvpmtOr/7jv2cNav1g/34o2uV6lb7ZrVWIT39CVAaiNDQ8Sgt3QTMnOlaJfuB02lHdPQ0aDSDkZJyHxwO7wpczCycBZgWSym/32arFb9Ug2A0yhUEbbZ6xMVdy+YFwG5vREHB8l5ncFtbexAJCbOQnHyX+P+8En//za4QHz0agMTENW2O0dTk+hfdcAP7+bIfom5PP8223bZNfv8bbwBz5rSetXM4gHPOkSePvd0k5cyO4nAYodUOhUYz0C9/Sau1CllZL6G0dCMAIDX1QbeFU5BXFVt/eO457+d3ySXMR7A1H0CtFpg/n73NzGbWN+htnJ9+6tC0OE1N8fw8GxpCj28wNyyWcjGDP6XVbRrMDRixYgSIimDahmltlrNFFEfIev+IimDh/oWdNmd/cTgdMqP77+O+7/Y5dAUmUw602uGglCA7+w3uBdrcnIr8fBXi4q4VSwCDIfUMt8dOx2IpRWjoqTyQkbJPrdHQEM6/p/5NVFRsA+vBvkP87iLQaoehru4Iq5KJOBcNDXqv+9rtDdBqh0CnGwmNZgA0msGorNyO9PSnZIEgpQRGYxby85d6ra5R+HdDlOBPQcE3fS34s1jKkZv7LqKjp/MvgYyMp2XG2Lm570GvHw2TSeznq6xkaRppxTl0KFuRDhgAjBjhSidJSH+/8IJrn8GDXXKIIk5JHt7pZGMOHeqxjS8EQfCrp6uxMRr19RqP+yUVs8LCVbL7y8u38iulVmslF0PIyfGR5exmamsPQa3uz/+HGs0gmM3FWLMmBkuW3ImlS1v3QWyJezB26aX+9ZLt2cO2l8pIAdaj11bwduiQ61pAdjYLakJCWJA0Zgx77LLL2vUyaBVpwZOQMMejTE0QHMjJeQdpafNhNGZArx/Le1uam9OhVveHVjsc6elPglKCsrLWF/hWayWcTgscDhPq63Wy91JqKstiTpnCRGCefZYpg0rP02WXedp0CALbXtrm3HPZz3HjgKeeYr//3/+xn/PnH99zJFmnSIvs9vgj+jNuZubzPrf7NPRTEBXBloS2hUZsDhv+s+U/eOXAK0itSgVREcza6uPiUyfRMgMZUxojyz6+9s9rXT6H7qK29hDPMKWnP4Hq6j0yNVCpakQK4lrLilutFR7KoZLis/t3T1LSbcjN/R/S059EVdVO2euvoOATvl129qsID5+I3Nz3Tlj/Vgn3cum4uJmglCltCoKA2Nir+HOSk/OWx/dfVdUu2f8qJ4d5cjocJkREnCNW+dzMy3el7Xz55ir8+yBK8Keg4Ju+FvxJOJ12lJZuQFXVH14fF1oaLW/e7FqNXi8KsMyYwf7OyQFqa1lEcOedrMlp0yaX2/VZZ7Gf6a30iUjKGNdd14ln2DaSWEhS0u2y+yU1UalsUFr8REVd3K3zaw3Wp3kGv0IfE3MZz1JaLCwb1Jrvnze2bmXZuldfBar9THAZjcDAgSymj4oCsrKY2Iz0ErmilYv1jz3mmbGy21mw9+abLBAMC/N/7r7nmMVVYPX6k2EwJMNsLoIgOJGScj//HzPxG8Kf0/Dws8TA5Tle/pmUdKts7MrK3xAff6OYIQxEfPyNSE6+U8yI3A+Ho/V/gKRmOnQo+/l4C40NKUCeNo3bXiIwkGUDAaCujmVsg4NZ+a1UntvUFIO6uiPtErnJzn5NtlhMTr4HDQ3hyMpaiPT0x1FaugEGQyIKCj5GVNQFSEq61WeAKAgOWda0snKHz+MLgtAh7z6bw4bgJcE49bNT271ve8iuzcbZX5yNqeun4tekX7ErfRdW6FaAqAge+uMhEBXB7K2zu3QO3Y3FUoLQ0HFuWb4AHuwlJt4MgGUJWWZ3MpxOC5xOV6q/ouJXaLVDoNEMRGXl7ygr+w6NjdHie2sinE4ramsP8WO43yIizuGBiCtIkd8KCj7ukeelu5BK+K3WahiNWSgv38q/j+32JpSWbuI9gOnpT4n9eVkoLd0oy/DpdCNkvdomUz5qag7AYimBXj8GOt0oxMRchtTUh+F0WnrqdBV6IUQJ/hQUfNNXg78OsXo1U+XYJJpBS9KQp58O9O/vvS5t3DhWLkqIa7+W/PILe/y17r2C7nRaoNEMgE43CoLghMVSgtrag9Drx0KtDuYqaO4399LRnkKyzXBX4OwJJIVR99uttzIPQKl38J9/WEBaUQE0N7OAZ9Ag7+WODge7htCZOJ1WZGQ86/Y/DER6+uNuwV4gX5SaTLm8pE2rHY7m5jQ4nXbodCOhVofw3lObrYZnR1q7paTc32oZoyAAxcUsoS5ZQhw+zALgVavY8yZpKTU2shLbzZs9x5EqsO+8EygsNPM+oejoaa2WQbckPv5GUEpQV3eEZwbaumVlvdLqeDk5b4rP7WnIy/tIFhR0NlPWTwFREdSbO9B46geVzZUYt3qcR59hyNIQEBWBOl+Nfkv6YdzqcV1y/J6ksvJ3nh0qL98Kh6MZBQXLZP13kpWQXn8y91RtbIz0yCqxyoQBoJQgP38J39/hMKO29hDKy7egsvJ3nhnUaofB4WiGVjuUi3O5Z6zS0o4z3d2LYUrFBFFRF/rczmTK4ZYMcXEzodEMavE9VeJTzZpVzRyfaqjCiQtRgj8FBd/8q4I/QF4TWF/PVvuEsGzf44+zlM7Bg8DEiWx1SinzIiCEOWIbjZ5jSkFkS5fybiAu7jpQStDUFMMzPuwL9Vo0NcUiNvYq6PWjxf4LgrKyH7p9jgBbKLGslYCYmMv5gr2nWbOG/avPPRdYsYJloQ4cYPdJ1wWuvhoICnKVOx5vqWJ7cTrtSE2dJxPFoZT1uGVlvQRKXep3+fkqxMTMQHNzKt9fsjlJT38K0dHTeDYxLW0+Kit/E0UTAnh5lvQ6Ki1t2939zz/ZczJ5MvDNN64g+oIL2raEKCsDJk2SttfLzq20VG7GbrOxMlunW0JfEATodKOgVveH02mHxVKGnJy3kZAwCwUFy1BTsx9ZWa8gNvYq5OUtQn29Bnr9aEglgS2zmwZDsphxGAWTKa/Ncz9e7tlxD4iKcHXSzubLiC9BVATzds7DjpQdeH7v8xj88WCuUmpz2HDB1xeAqAhqjDVtD9iHEAQBJSXfoLr671a3KSxcJXvNmc0FXGW3tHQjiorWIDJyMsLDz5Zt4wvJDkgqyU9IuAlJSbciNvZqnm2Mjb2qs0+311BevkW8wNJ2L2tzcwqvWqA0iFeoREdf0g0zVTiRIUrwp6Dgm39d8NcSQQD0eqChDc+8++93eQjExMgfk8ReWisL7UJyc98Ty43k1hYFBcv4NoLgRE3NAfEq91gUF3eiwV0r2Gx1yMh4GgUFy5CUdAfU6hAx4HiUf8H39iu3d93lmRm86CKgpgfXydnZr4JSUcwIrEzRaPQtMmQ2F/Ln31VSNUrml1VcvA65ue+K2Y8o8TV1bpvzEQRXBk+67d/vvxdgVRXw9tvAwoWfglKCn39mC+3t213qt1u2sPJcQlxeigAr72OvpUv9OxiAxsYILhIVH/8fOByuizmZmS+CUpeqblfzwbEPQFQE38V+1yXjz/lpDoiKILTIJYQj9SjO+WkOAGDeznk8C/hvw2IphV4/hr8nMjOf55+lvJ8brPxapxuBpKQ72hyzouIXMVPo8mOVEAQn1Or+0OvHdsn59Abi428ApQS1tf/4tb3DYUZTUyxMpnxUVm4HpQGy7y4FhY5AlOBPQcE3//rgz1+KioDx49kKdMAAJnUIAKWlrHlp9OjOUfloJ5JhPCs3GoL6ejVyc9/3UPZ0Om28v4tSApMpp0vnJamwuQcb0rHZ4qD3N+gnJbEq4UGDWEDzySf+9xR2FU6nDZWVv7dbNEIS/UlMvEXsHfTtLyddTPDHGLmmxiXwcv/9rW/ncJjR2Bjh9TFJ8TU6+mtQSrBu3X+weTMT4ZECP0KAhx927VNdvZtnNNuD1VrNRTtSUu4T59YMrXYY1Or+3aaKuy15G4iK4Pm9vkVlOoLBakDI0hCMWjkKDqerh9LutGNt+FqkVrHM8Mfaj0FUBJ+Gftrpc+gLCIJTDDpcn1Xl5Z7iPXa7QRYQtobd3sBLPfX6sR4+rJGR54NSAru9CTU1e5Ge/mSXfxZ3FwZDEqS+R4+eez+xWEra1fOroOANogR/Cgq+UYK/dmAyAUuWsFXo2LFAfj4zeiMEeM+7t1RXIwgCKiu3o7DwUzQ0tF0+lp+vEsuSVF06p8jIyaCUeW6Vl/8Ep9PqVgrVdwQm/v6bJYb7Ok6nDdXVe3wKubiTmvqwGKT7ZzJfUQF8+qk8K1pTsw+RkVNRXb0bAHhmpaVEviAI0OtPhlrdDw5HMw4eHIp9+4YgMNDBgz7JmmPqVNd+SUm3gdK2RVm8YbPVIjx8orjY38oz0t3Zj1XVXIV+S/ph5MqRMNvNnTr27vTdICqCR/707ROZUJ4AoiKYtG5Sr8/EdxVSn5rUK+vve6Q1kpJuB6UE1dV7vDx2q5i5f9jtmMM61aakJ2hoCOPl/MXFX/T0dBT+5RAl+FNQ8I0S/HUAydV70iRg5EjWEFbsO5PSWzCZciEJhFRU/Aq7vRWjtuOgqSkGlHr6WwmCA5WVv3lcDVfofRQVfS6WrX3i9XFfV+ebm9OQk/MWz4DodCPR3JzOS+Fa9jwZjZni62UGACA8fBYoJVi0KAGDBzNRmcZG1n8ZFMSuwbDXcQBCQ8d32N7BPWvORF5Oh8mU36GxOsoDvz8AoiL4KfEn7Ezdibm/zEV2bfZxj/v83udBVAS/Jv3a5rbXfH8NiIrgUM6h43qEdTUAACAASURBVD5uX0Xqg23L2sMfbLZaNDXFeX1MKttmpaGD+EWHxMSb4XRa/PL07EwaGyNRULBMVv7cXuz2Ri7YEhk5pdvPQUGhJUQJ/hQUfKMEfx3AbgfmznXVor34Yk/PqF3ExV3DFyAZGU93+vg5OW+JV4C7vrdQoWtoaGACLKGh45GR8TSamuL5Y2Vl30OtDvaaFTSZ8txUZgMRG/t/PAB0D7Sio6cjJeVeGAyJPIMnZaPz8j4SF5KTUVYWgzqx8vT229nbLTISyM39n9i3t8zv/kJvlJR8jfj4G5CcfDfM5sKOD9RBjuUdA1ERDPlkCFfjvHvH3ciuzUZhQ8fnM3X9VBAVQbmhvM1td6TsAFER3L7t9ja3PVHJyHgWanWw7HXeFRQXr3P77H0GguBAaOgpoDQIMTGXi7243VN2LAhOLu4UE3NFh48refOlpNzrV2msgkJXQ5TgT0HBN0rw10Gam4Fvv2UmcX2sXKqxMRoZGU9DpxsBSoNQVvYDamr2ddr4koR6d2dRFDoPh8MoC9YoDRJVMz/gNhEJCTfx7a3WKmRnv4HIyCniwvZZmEz5sNsNiIm5QhwjgAdtLW8REefxcjubrQ4JCTeBUoKoqAt4OeKHH7Lgb8MG12vslFPycOmlQIZvzZteiyAIeGbPMxi4bCBGrBiBMavG8CBw4tqJHSrFrDZWg6gIzlt3nl/b2xw2nPrZqQhQBSCvrutVTnsjDoepWz6vJOEtptbL6snds4FdedHM6bSivHwrMjNfgM1Wj9raQ/wiDXvPLujQuJIVTUXFtk6esYJCxyBK8Keg4Bsl+Pv3Uli4QrboqKujxz2m3d4ISgMRFnb68U9QoUeRAqzU1IdEwR7PoE0Sq5C8B1lZ5//JSjEltdna2oMQBCeqqnaiqSkeRUVrEBd3DcLDz0ZjY6Ts2IIgIDb2Slnf4a5dLPh7+eUGHDsWiO3bTwchAggBZszovuelK7A5bHA4HVgXuU7myedPCejh3MOY89McxJbF4kjuESzXLQdRESzY4/9ifol6CYiK4M2Dbx7PaSi0gWT3QCnhgb1kIE9pkHjBg3kOOhzmThM/EQQH98SklKCw8FNuS1Fa+q2YmQ+U+SD6wuFohs1WA0EQRL/RAJl6sIJCT0KU4E9BwTdK8PfvxeFoRlzcdbxRPyzsdCQn39WqIqMvnE4bUlLu5yV8qakPdcGMFboTozEDtbWsD0wQnDAaM5CW9gji4mby0t6cnHfQ3JwCSgOh149GXd2xDvfgtaSycofYDzUXAFBSwtRXZ83aB0oJ3n33EezezXoCAwNZMr6vY3PYsCZsDa7/8XoQFcHmuM0+txcEgXv1BagCZIHjT4k/+X3cCkMF+i3pB6IiuO6H67rMeF4BKCvbjMbGKP63IAjIz1+Kiopf+QWXmpr9CA+fiPj4G/0aUxAcsFhKvN5fVvYd0tIek120iYu7Dmp1MPT60XA6rSgqWiOWeZ+Kqqo/2zxefPwNUKuDkZJyr6xfV0GhN0CU4E9BwTdK8KcgCAJXqKOUIDn57naPIfWISbfS0g1dMFOF3oLFUiYuHscgMXGuWK62tlOP4XTaERp6KigNhNVaCQBYuBBYsOAdUEqwdOkmAMB997GMIKWdevgeZW/mXhAVwWO7HvO5XURxBIiKYNTKUQhQBWDK+ik8+CtqKGrXMbcmbMX4z8aDqAh+T/39OGZ/YpKYyCxfuhLJJF2tDuafpb7sVkymfDQ3p3J/vdTUeS38O79wUxUdgubmVGg0A9z6Dll22Om0IC3tEVGIZoBPAZimprgWFQABqKhoW1hIQaG7IErwp6DgGyX4UwAAu70JVVV/iCbEoyEITgiCIBMBaGgIQ0HBcq8eTkVFn8kWBM3Nqd05fYUeQCobY1njM+B0Wjr9GFlZC8WLCRvhdFqQnPwk9u8fKpauZQIA1qxhwd8n3oVJ+yT15noEqAIwce1En9s99ddTICqCb2O+RZ2pjtmslETiz7S2szfe+C72OxAVwftH3+/Q/icy553HXmcHu9CiVBAEWXkmywJ678dubk7lirruvXuJiTdDEATY7QbRxD4A+flLeWl1fPz1bmPvlY2ZkvKAeP8BPp/k5LsRG3sl/9yXevzy8hahsnJ7m56hCgrdDVGCPwUF3yjBn4I7cXEzwTyq/havJgeguvovAODKjd56A1NS7hODgNOQkDD7X+sZ9m/CJRjh3Ri7M6ivV/MFbUHBcr7IjY6+lb/GwsLYovy227pkCj3GtA3TQFQEObXeTcCLG4vRf2l/DPlkCBotnSOvH1MaA6IiuOWXWzplvBOF3FyXuPNppwENDV13LJMpDzExV/AgLTf3f163k7wCIyMnIz39cVgsZVxwKT9fhdTUh0ApQVrao7L98vI+EDN8g+FwyP0ly8q+B6UEWVmvoL5eKxOoaW5OgcVSBq12CDSaQbDbu/BJUFA4DogS/Cko+EYJ/hTcycv70EPUIzr6Ejiddu7Tlpe3yGO/sLDTQWkgHI4ToPFKwS8EwYnY2P9DXNy1nSZM4XkMB/T6MVCrg6HRDIZaHQKjMUu2jcUChIQAo0f3OeFdn7QlwvLs38+CqAgWHfV8P3YUs92MoMVBOG3NaZ025onAhg0s8BswgP1cv77rj9ncnC72510ju99uN4g+nIHQ68fISjQbG6NlJaOhoeNhNsvLf+vrNWDWDA94HNPd8N49mygJw0g93dnZb3TNSSsodAJECf4UFHyjBH8K7tTVHeNf9ikp93ExGEkQgKk5uky6bbZalJVtFlXqLu7BmSucqOTkvM1fe61lQa68ki3Ks4/fH73XUGGoQMjSEJy04iQ0W+UXVTKqMxC8JBgnrTip08VZJAGZamN1p47bl7nnHvb6WryY/Zw1C3j5ZWD16q47piAI0OlGQa0OkV1Uc+/P9tZn29QUg9TUh5GcfDes1gqvY9fU7IPV6v3/q9EMlgWAanUIL+1uacuioNAbIUrwp6DgGyX4U3DH4TBBrx+NiIhzYbc3oqpqp1giNNBtQRAEu70RDocRUVEXu4kHPNvT01c4AREEAUZjNurrta1mGF97jS3Kt27t5sl1MY/tegxERfBlxJe477f7MGLFCExZPwWXfnspiIpgdWjnRx+P/PkIiIrgSO6RTh+7L2K3AyedxLJ+RiMwdqyrBDQggAkNqdVdk3VOS5svCrk8DEEQYDLlgdIAhIaOR329uvMPCGZEHxFxLgyGBFRV/YHGxihZMFhb+0+XHFdBobMgSvCnoOAbJfhTaInVWg273QCAld2xkk72xa/XjwalBAkJc7gseWTk+YiJmeHh1aag0F389htbjD//PPu7vLxr+7K6i6SKJBAVwaCPB4GoCLdjICqC8786HzZH59hquLM6dDWIiuDhPx7ukvH7GocOsdfWXOY4ggULXMGf++2XXzr/2FZrNc+4FRevRW7uu2JP3+LOP5gPIiPP5y0ASj+3Qm+HKMGfgoJvlOBPoS3y85e69X1s5GVAktiAYu6r0NMUF7MF+LRpwB9/AP37A2edBTR2jg5Kj3LHtjt4wHcw5yD2Ze3D3F/mIqokqu2dO0BBfQHGrBoDoiJ4cveTXXKMvsSjj8qDu6NH2d8PPQRceqkr+Js/37/xGhsBWzti6qamONGeIUj87A3y6unXlWRmvghKCSord3TrcRUUOgJRgj8FBd8owZ9CW1gs5VCr+0GvP5lLiNfXa2EwJMDptPb09BQUADAVxoAAdpMW5DffDCxf3rcN4KNLoxG4OBCzt3afim5hQyH+v737Do+yStsAfichVCkCAktXVJQiUgTXgqJi+1ZWXEERVFRAVncXWMGK8oYqIII0AXEBqVKkCyJIbwoIoUivoQVIAoSElHnv74+TmcmQZJLIJBMm9++65srMW8/MOwPzzDnneUoPLM2CfQoyKi7jOnOBLjaWvOkmslgxz/fQtm1kQoLpXd68mQwOJqtVy/x4p06ZIaQtWmSvHadPT06p1VecERG5kG3mGklJMelmeRbJi6DgT8Q7BX+SFVFRK3nx4iZ/N0MkQ85i74ULkxMmkBUruoPAQYP83brr88e5P3jp6qVcPWfnhZ0JCxy/dXyunjcvGTDAvH/atvW+XYMGZrujR71v9+mn7vfkypXZa8vlyzs86q6KSPqg4E/EOwV/IhIIli8nH3yQXL/ePN69m+zTx3zRbtTIv227Ea05uoawwMcmPebvpvjFunVkSAhZpIh5L3njTDg0yUu5y/h48pZb3MFfgwbk9OnkU0+Zocoi4htQ8CfinYI/EQlUtk3WrGm+bB8+nHa9wxFYtQF9yWE7WOXLKgyygnjmsmfJgLXH1vLZqc/yWMwxP7UuZ+3fb+pGAuT//pf59vPmmW3r1yfPZzAFetw4s02rVmSTJp7JYoKCyF69yKj8O8JWxGeg4E/EOwV/IhLIevY0X7AHDvRcfvmyqQ94333ZCwBt29R4a9mSnDaNPHmSbNOGXLjQt+3OC7os6UJY4Lgt47ju2DpuPbWVeyL3sPzg8oQFvvdT3i32nZTkvq62TS5Z4g6u9uwx74v0evQSEsi7aicQpY6wc/fTWTpXQgLZtKl5n1WubN5ra9aYHxdI0+tXubJZv3Wree9ZltmnTx938fiyZcnw8Kw/vwkTyMcfN0lp9COGiAEFfxIgqgBYACAKwDkAUwCUTFlXAsAMAJcBnAbwXnYOrOBPRALZrl3mi3WNGmRySpnApCTy+efdPS9bt2b9eFu3pp/qv2bNnGm/P606soqwwNIDS7syjqa+VRxSkckO86LujtzNdj+045jfxjAu0b9FwC9eJKtXN71sJLlokblGf/87+c03ZGioeRwcbAKo6Gjy11/JZEcym/XvQXxQyvUcX5z5Io9EH8n0nHFxZm5g6vdEy5YmUcywYebxiy+mv++BA+6souXLk0cyOd2JE2StWp7n+uUX8r330u/hzm8cDnLTJvM5l/wHCv4kQCwAMBtAMQClAPwCYGTKukkA5sMEgXUBRAJ4LqsHVvAnIoGueXPzBXnWLNPr8vTT5nFIiPlrWVk/1n/+Y/Z5+22yXj3PL+Bx/o15fC7JkcQyA8sQFligdwH+bdrf+MC3D7D1rNZsOqEpYYErDq/g8ZjjrDSkkitgaj+vfZpjrTyyknP25Nzkto0byfHjyf37bbbpM5soHsHQWw5zw+HfPQL9QoXMrVMn93zQdu3M/SZvTTfPoWchNhz5MCsOqUhYYPH+xTnh9wlZyrYaHk7260fecYc74Kxa1dz3NnfQtsl33zXbPfGEeRwTk35PYPfuZrumTd3Po2RJz1qX+dW5c+7P+5tvmmvx8svkmTOZ7yuBAQr+JECEA2id6vG7AFYBKAogAcA9qdb1AzA3qwdW8Ccigc5ZqLtePXcPS9265M8/u5NvZEViohmaV6AAGRlphvtt2mS+4APk6tU5+zz8ocP8DoQF9lrZy2P5xN8nEhZY46sarmGgbWa3YfH+xVmsXzHGJ8W7tr149SKL9y9OWOCeyD0+b+OyZWTBgikB3r0TTAD3YUmiZ0GGWAUYUvaQR5BuWSa4qlDBXMugIBJBDuKfdUx9w94rSZLxSfH87JfPGBwWTFjgw/97mL1W9uLlhMv8+/S/s8eyHhm2KSqKvPVWz7IjmUlIIOvUMdsPHer+ceHZZ8kLKYk+bdv0YgNkRITJMJr6ud1zjw9e0BtYhw7p98xXqkQeP+7v1klugII/CRBvwPT8FQdQBibwex9AfQDJAIJTbdsKwIGsHljBn4gEOtt2z8lyDq1zfpl29tA884wJBjNy9Sr50kvu3pzUvvzSLO/XL+eeg7+cv3KeM3bOYJLDcwzd1aSrbDmjpau37+2FbzPJkcTWs1oTFrho3yLXtsM3DXdt98a8N3zaviNHyKJFzev/+utkoX8+lHaI6qO9+NZbZLlyJnBy9tA6g3aALPLISMIC6375UJoevg3HN7DGVzVcx7tv3H2EBYaEhTAyNjLDtk2f7j7+kiVZez6bN7uHpQLu+927m/XOYcyNG7v3uf9+z+Qx0dHk2dizDD+TxQmEAcLhMJ/tAgXcCXYKFTKfbYB85x1/t1ByAxT8SYC4E8AGAA6YN/VyAIUAPAwg5pptmwM44+VYvVKO4bz5+3MqIpLjzp4188Ccwz+dhg71LAyfUQDnHJJ3223koUOe6377zR1A5ie2bXPRvkVceWSla9m08GmEBXaY34Hrjq1j1aFVXb1+RfsVZWjvUK9ZQg9eOMhOCzqx5oia3HJyS6ZteOEF89q/2nM1+6/pb+Yifl6D05aHE1XXmoCta3X+sdfByEjPjJr9+6dc9zqmzYX6FOL64+vTPU9CcgLXHVvHQn0KeQSWY7eMJUmevnyaicmJ17w+pqD7k0+6k79kxezZZj7izTebOaahoeb+lStk376mzf37m21bzWzF6oNq8+nOK9miBQnYbD7qDVf7ftz/Y9ZPfINzzsd99FHz2k+aZEq/REWRxYqZsh3nzvm7lZLToOBPAkAwgKMwwzmLwPT+fQ1gIdw9f0Gptn8R6vkTEUkjMpJcuzbt8itXyJkzyRIlTCC4bh25YYPpFezRg1y61CwvU4Y8dSrt/klJ5E03mS+YMTE5/zzyspj4GIb2DmXJASV5x/A7XEHIU5Of4me/fEZY4Avfv5DuvkM2DPEIrh6d+Cg7LejEzgs7p0kic/68md8GkBXr7WGRvkVc+/VZ3YcOB1m6NInXHyUscNnBZWnOt2IFidBYons5BlvBWQqUui3tRlhg2UFlXXUQnTURvQ0Dza7wcHfil1deMc/zyy/Jv/zF3N+7l9x/fr/rOQeHBfOD4ZuIhmMJC7yp/02EBT49Of/8IuEMjK/N7EuSXbqYdb175367JHdBwZ8EgLIACKBCqmV1YXoBi8HM+aubal1faM6fiEi2TZ5sviD+5S9m+Ni184a81Xx7+22zzeDBudfevOqDnz9wBSVPTn6SuyN383LCZV5JvMJbh93qGhYaEx/DoRuHsv289vz50M+EBRbpW4R9V/dlzRE1PXrY/jr+r7ySeIW2bfO1ua+xbJdnicLRLF4yibcPrk9Y4P9N/T+2mtmK56+YYnt9+pC1W80kLLDJN03SDOe8eJHEgwMJC2w9vV2WnltUXBTfmv8WN57YyEpDKjE4LJg3f36zq505YeNGz/dhu5Smhq0KIyy4zl/7q0bEx0WJzwrwrV6biP9WInoF8dMhR2nbtsc8zEBi2+Tw4WTFiub1SS9JzuHD5gecKlXcWX8lMEHBnwSIgwDCABSESfIyCsCOlHXfAZgH0yNYB2bIp7J9iohkk217Joxo187U8GvWzAyz8zZ0b+9e8+WycmWTGCY/c9gOvrv4XVYbWo37zu/zWLdw30LCAhuObcgGYxu4gqaCfQoSFjh803CS5OQdk13lJO4ffz9hgd1/6s7pO6e79in87gMc8IuZT9h0QlM67LQXyGE72GhcI8ICZ+2e5bEuyZHEor3KMahXCPef35/t5zluyziPADW0d2iauZG+MnKkeU8WLmwSl9i2zbtG3uVKolN9WHV3Wx78nEFBZMgTpqcVL7Xk7Z83YcUhFXnuSs6Ne/zj3B/strQblx9aTtu2eSXxSpbKZFyv8HD3Z7ZFi4xrHj71lNlm8eIcb5L4ERT8SYCoA+BnmDp/UQB+AnB3yroSAL6HqfN3BqrzJyJyXbZuNfXgEhKyt5+Zc2V6EGfMIOfMIefPN7Xk4gOz08Wr9Eoj2LbN+mPquwKVJt80cSVTKTmgJC8nXCZpgrbxW8fzwIUDPHnpJEsOKMngsGCWGpBSg+/duz0Cr18jfs2wHSsOryAssN7X9Tza5Kxj+PSULKTizMAHP3/A0N6hrnb8mWymicmJWSojsWGDmV9KkptObCIssNG4RiTdgeiDw1sSsE2SGOssy/Wv5vE6fbH+i2y3Lz0O28HjMe70mWuPrWWpz931ERt/05hVh1ZlaO9Qbju1zSfnzMioUeZz98EH3rebM8dsV7s2+dNPOdok8SMo+BPxTsGfiIhvrFnjWXMt9a1xY5N0RsgZO2e45qntOLODq46sYqE+hdh7VfoTsvbvJ9/9ZoI7iHn+dT7cPNoVRLaY3sLr+WzbZpNvmhAWODV8Kg9eOEiS7LKki0fSlj8rNiHWNRdw+s7p2dp304lNLD+4PFvPap3ptmdjz/LExRMkyZdmvURY4Pit40ma57j66GomJCewXTtTviQ2loy4GME7+j1CtPmbKc0x7E6PQHP+3vks9Xkpztkzh8mO5CwPDe27uq8roczhqMOuoacdF3Rkw7ENPQLONrPbZOs1ya42bcxnbFnaaZ0eEhPJhg3dNT6vTdwkgQEK/kS8U/AnIuIbtk3ed587Rf+rr5q6gg8+aJZ17uzvFuYNSY4kvjHvDX654UvXMud8vms5s6wCJIqcJ4qdYaXKNs+eJc9dOcdB6wbxzOXMK3jP2j3LFYyEhIVw/fH1rDq0KoOsoCztn5kJv5vg9MOfP8zS9uFnwtliegsW7lvY1S5vQ0YTkhNY5csqhAU+MuERhoSF8JZBt2Q5WHv7bRJvmDIYKw6vIGnqGFYbWs3V61pucDneO+beTHshE5MTXbUdH/z2QVcQ/v6y90maXsEZO2dw5q6ZLDuoLEPCQng0+miW2vlnVK1qsqNeupT5tklJ7vfUV1/lWJPEj6DgT8Q7BX8iIr6zeLGpMzZ6tHtZdLSpN1aqVP4c/vlnHTlivqSXLm0ye/7jH+Qnn7izYGZHsiOZzSY2cwVQJQeUdAUvvrDt1DbCAp+Zknl2zej4aFYdWtVV/sIZ/HkbHvnDnh9cvaXO7cNWhWW5fVFRZPG/mpIW949qTpKu0hilB5b26KnbHbk7w+NEXIzgiM0j0tRSbDaxWbrBa6+VvQgLGfbqXq/jx817pH79rO+zfr3Z56mnzOPk5OyV4pC8DQr+RLxT8Cci4ltJ6XTgOAvEz5yZ++25kfz4I/nmm+SAAe46fB9mrTMtS2zb5jNTniEssPzg8twcsdknx72adJUF+xRkoT6FvA4jjU+K53PTnnMNh0xITnAFSKN/HZ3hfi2mtyAs8Ic9P3DHmR1cvH9xmrqCmflqeDLxb1N+o36PDxjUK5iF+hTi7sjdHLRukCuxzsjNI9Pd//Tl064SErDAv00zQ0krDanEs7Hpj2necWaHKyFPTpg61bxH/v3vrO+TnGx+UChUyAzFrlXLPO7RI/3PrtxYoOBPxDsFfyIiOW/xYvMl9YEHlA00Iz/9ZOZiXTtfcuNG357nQtwFDts4jKcvn/bpccduGetK/pJesfjE5EQ+OtHUHbxzxJ2MiTdFIZccWEJY4GtzX0v3uGdjzzIkLITlBpfLdsCX2sWLZMHGEzx67AYscP8a4UyM02hcI3aY3yFNBlRnkFpzRE2+Oe9NxiXGsdfKXtx1dleG53TYDt4y6BaG9g5lbEJsxts5yOnTyQsXvD+Hs2fJatXI980IU7Zubd4j8+dn+vQ9OGsn3n132nIuDoepI6le+uyLjI3klB1TmOzwXz0NKPgT8U7Bn4hIzktKMkk4ALJVq/SLzd+IkpJ8UzctMZEsU8ZdK7FaNXO/QoUba0je+K3jCQtsNbNVmnVjt5gC7A3GNvDoKbsQd8Ej++m1QdfU8KmEBb6z6J3rbl/7NxzEfaOI5j2I23/kc8+518UlxnkEhi/PfpkkeebyGY7+dTTLDS7HkLAQHos5lq1zOpPTLD2wNMNtJkww17tZM3cg2LYtefKk53bOzJ4AOWkSWayYuWU3UNu4kbzpJnOcsmXJhQvdNT7LlTP3a9QgL1/O3nHzo/ikeNYZXYcvfP8C3/vpPcIC+6/p77f2QMGfiHcK/kREcseJE+5C1AA5d+71He/KFdOb4y/JySZt/qOPXv+xdu1yf/knTXBcuLAZincjiU+KZ7nB5RgcFuyR5CQ+KZ6Vv6yc4dy+u0e6S1e8+sOr3HRik2u7DvM7EBY4Z8+c627fb7+Z3tU2bdwBdvPm5NGUptYeVdujbuHZ2LNsNbOVa1l6QW1mnGUoeizL+GI2aeL+XNx2m/v+q696bvfkk2l7hltnnig1XUeOmLmka9aYx//3f+5j/uUvWSsfIfSovRkcFsxi/YplOAw4N0DBn4h3Cv5ERHLPqVNkWJj5YnnffRkXpL6Ww0F27UpWr05u3+7uSaxQgYyJydk2Z2TTJveX5YMHr+9Y06eb43Tr5l526dKN1evnZK20XIXsJ/4+kfP3zmfnhZ0JC3xx5ovp7rPpxCYO2ziMZQaWYUhYiCuxS/t57V0ZOX1VoP3YMfP+Wb+erFnTHeyEh5t6fV2WdGHHBR0JC+z+U3eG9g5l6YGl2XtVb0ZcjMj2+Q5HHTbzDMekn5Vl+3bThkqVTLIkgLz3XtMDFxRk2mXbZGSkyaJ7yy3kiBHu997331/vK2IcPGh6G5cvNz2ON91k2nP0aOb75mfNv2vu0WP80fKP/NoeKPgT8U7Bn4hI7rJtsl4988XV2euQntOnyf/+l1y1yvSApO4ZcSZDAcjPP3fvM2KE2Tarw+DSS3CxZ0/W9v/0U3cbhg3zPKbDQW7bZr7Er1iR+bE+/tg95+pGF5cYx2YTm6XJiFnhiwqZDpnsuaKnqxxFhS8quPatO7pujrQ1KcmUIEFK8XPnEN695/YyyApynb/Lki7XdZ5bh93KICuI56+cT7OuUyf3e2j7dnOzbXeAV6wYWbmy+7325ptmv3nzTM/d1avX1bQM9ehhzjduXM4cPxAcjT7KICuIVb6swjaz27Dq0Kq8EJfJxM0cBgV/It4p+BMRyX2TJ5svlg8/nHHv31tveQ5vq1SJfPZZz2VBQWT58mRcnOkpK1rULO+Sznf1ixdNevvJk8kNG8iHHjL7p+45mTvX7F+mTOaBmHMOI0A+8YRZlpBgCtrXqWP+AuStt5r2efPcc2bbLVu8b3ejiE2IZdclitn7ygAAGLtJREFUXdljWQ8+M+UZVh9W3WspB6eouCi+Pvd1zvtjnqvHDBb41vy3cqyttk02bWpe/+++cy8funGo6/zbT2+/rnM4h67O2j3LY/mZMybrZvHiaXuwk5LI7t3N8N/gYPOjR+XKpsc5N/z4o3lN2rXLnfPdiJxJgD775TN/N8UFCv5EvFPwJyKS+5KT3b1/06a5lzsDwagoskgR0+tRqZJJEhMZaeb5ffihCfjeecddQmL0aHL8eM/AcOFCz3N++627J+WWW9zb3XqrOwOpMwgDzJC3Dh3IO+8kd+70PFZEhNnm9tvN8LzQUFPPcNCgtHOyALJPH8/9x40je/Vy9wpWq2a+4GcWJOY3s3bPYqUhlXxWkiIjztp3t93mOdR22MZhtFZa1338aeFmXljFTp2ZlGTe5/0mbeTjz0cQ8D638+JF897KbTEx5j1ZtWrun/tGkOxIZtWhVRlkBfFI9BF/N8cFCv5EvFPwJyLiH2vXugOohASyd2+yZEkTTN11l1n3TiYJHn//3WxXvbq7p+2jj9xZDFNnS2zRwjMg69iR/NvfzP3hw03AGRpqev1Sz6kCTI9jau+8467B989/mvv/+Y/pwQkNNbXTAPLrr03vYrVq7sDW2WbAJB/54w9z/847ffrySjY99pi5DsuX+/7YoyedNb2InxRmjX4PsFm/D83j1x9loULmx4S8qH5985po3l9aPx38ibDAJ757wt9N8QAFfyLeKfgTEfGf++83Xy6dPW6hoWTBgu6et927Mz/GM8+4g6m77zZBVpcu5vErr5htYmPN8LlSpcg77jCB1qVL5NatJjhzJtkAzBww2yZfe41s1MgElgA5e7ZZHh5uekRuvtnUZdu/330MZ0AYE+Ouz+d8js7ew//8xzwuX978dfZevph+LhTJJVOmuIc5OgP1X37JWg29HTtMb66z5/aHH8ilKZUdYmJM7zVeaplmHiQs8LdtCTnzhHzA+Tn64gt/tyTveX3u64QFTguflvnGuQgK/kS8U/AnIuI/gwe7g6aCBU0glZRk/u7fn/n+pEnfX7q06dk7cMAsi4szPX8hIeaLeffu7i/2cXGeCV0WLnTXNgPMEMDUpk1zr3voIXcq/uHD3dv84x/uAPLaBBx9+7oT0yQkmJ7F0FByzhzP3sXx47P/+onvXLlClihhAvvQUFPCw3ltvNW7czhMTTznsFFnIqCiRc2PDs4SCm3bkm+8lUzUm8TQ/9RxB38nf8u9J5lNq1e7X4OGDcmePf3dorzBYTtYbnA5FuhdgBev+rHeTDqg4E/EOwV/IiL+c/iw+8tl+/a+PXavXu6kMM4hlqtWpb9tbCz5669mSGZ6Zs1yz1EEyJdf9pwbdugQ+frr6Zd8cA7zbNzYndXzhRdMkOss7F6+fPYLdYvvvfeeuR5FingG5hs2pN329GkT6A0caLYpUSLtXE9nj3atWqanOTHRvOdt210SY+Tmkbn/RLNh6VLPbKO7dvm7Rf7328nfCAtsNrGZv5uSBhT8iXin4E9ExL8aNzYB2vbrS6iYxtmzJrlLcLBJp7937/UdLznZJJb58EPTg5dVtm2Syji/PJcsaYaOkibgBch+/a6vbeIbDodJrhIfT06aZIbiOuduprZ0qRlCnDrQmzXL9CLff79n4iDAlP241pIDS1y9f1W+rMJDUYdy50n+CQ6Huz5nr17+bo3/ha0KIyzwi/V5bzwsFPyJeKfgT0TEv44dI9ety5lj79t3/QXYfWHPHrJ1a5PIJnWq/ogIkyFUWT7zpvnzTcDz9tvmsW2TS5a4ewZbtDA/XFSu7M4YS5rkQSEhZpvHH0//2BfiLnjM/RuxeUTOP6HrcPCg57za/Mq2bd475l7CAvdE7vF3c9KAgj8R7xT8iYiISHqOHjUBz/33m+CnTh13b96wYWabHTvII0fS7vv442a7H3/M+Pi1R9V2BX8dF3TMkefgSw0bmudUqZKpiZkZ2zY1MP/6V5McKRAs2reIsMCGYxvSzoNRMBT8iXin4E9ERETSY9tmeGfhwu7akE2akFOnZr7v4cPuDLEZ2Xd+H2fsnEFYYONvGvuu4Tlkxgz361C3buY9gBs3uoPlxo3NvMcbyYrDK3ji4gnX44iLEaz3dT3CAhftW+THlmUMCv5EvFPwJyIiIhl55BF3ANO1q2eiH1+wbZs3f34zi/QtwmRHsm8PnkPuu8+8HmvXet+uc2eznTOx0SOP3DhDnNcfX09Y4FOTnyJJbji+gYX7FiYs8IFvH8iTvX6kgj+RTCn4ExERkYz07m3m9Q0ZknPnaDaxGWGBf5z7I+dO4kMTJriz1L7yikmS43T1Krl4MfnJJyYDaqFCZl5vo0Zmn08+8Vuzs+Xl2S8TFlioTyHGJ8W7rlGXJV0YFRfl7+ZlCAr+RLxT8CciIiIZsW3y/PmcPUe3pd0IC5yxc0bOnshH4uJM8iJnj2idOuR//2uCwtTzIgHy1VfNPhERppZnyZKm8H1edurSKRboXcA1H7Pv6r6EBd418i46bB93/foYFPyJeKfgT0RERPxp4u8TCQvssayHv5uSZbZtkrg4E9ukvj3yCDl+PLl8uecwz44dzfq+ff3W7Eydu3KOjb9pTFhgpSGVPDKyTto+yd/NyxQU/Il4p+BPRERE/OlQ1CHCAuuPqe/vpmRbUhK5ciU5fTr5z3+SQ4eampjpOXCADA01PYAbN17/eX0tLjGODcc2JCyw6YSm3HRikyvwa/JNEyY5cuCkPgYFfyLeKfgTERERf7tj+B2EBZ65fMbfTclRY8aY3r/gYFMC4ujR7O2fnEy+/77JwOrreZivz32dsMBHJjzC+KR42rbNakOrERa499xe354sh0DBn4h3Cv5ERETE3/61+F+EBX63/Tt/NyXH9etHVqligsB69bI+BzA6mnz6ac8hpqNH+6ZNERcjCAus8EUFnrtyzrX8UNShPFnMPSNQ8CfinYI/ERER8Tdn8fA2s9v86WMkJCfwaHQ2u9L8JCmJbN7cBHAlSpg5gjt3kv/6F3nxonu7HTvIjz4i588n77jDnWBmyhQzfLRoUfJESim+o9FHWW1oNTYa14jLDi4z58niUM1hG4cRFvj+svd9/VRzFRT8iXin4E9ERET8LTYhlkX7FWWRvkUYGRv5p47RY1kPBllBN0zW0OhoskMHMw+wSBHynntMcDdggEkoM3CgWZe6p69lS/LyZbP/xx+bZS+/bIK8B759wDVHLyQshD1X9GTBPgXZYGwDLt6/2GtbnPtuObnFY/mIEeRjj5HPP09G5d0KDy5Q8CfinYI/ERERyQucJR96ruiZ6bZz/5jL56Y9x0X7FtG2bdq2zerDqhMWWLx/cd498m7eP/5+frvt21xo+fXp1s0zwLv9drJtW3O/aFGya1eyQQOTJdSRqtJCbCxZoYKZPzh8zQTCAoM6NmHDd4d5ZOmEBd721W2u/Q5cOMDNEZt58arpYtwduZuwwFuH3epRvH3KFM92deuWay/JnwYFfyLeKfgTERGRvCDiYgRDe4eyxIASHLl5JG8ffjv/t+1/abazbZs1vqrhCmzazmnL7ae3ExYY2js0TeCzYO8CPzybrDt50gzhBMiyZd3BVvXqZHi4933ffddsW7n7383zve1nBgXb/PtkU6R91K+jWHtUbVcync0Rm12vS8OxDRkdH807R9xJWODg9YNdx920yQSewcHk1Klk8eKmF3LHjhx+Ma4TFPyJeKfgT0RERPKKnit6pumxSt0bRdJVgqDmiJqsOrSqx/afrPiEyw8tZ8TFCM7ePdtVr87Zy5VXffst+eGH5KRJJpirUcMUhs/MuHnhRJV1xMdFiQ9L8N6GCQTIQYMdPB5znCTZcUFHwgLn/jGXXRZ393i9np/xvOuvs4D7vn3kzTebdjgzivbrZx4HBZF9+uTUq3D9oOBPxDsFfyIiIpJX2LbNvqv7ssIXFVj5y8qEBW46scljm3//+G/CAkduHsnI2EhXbTpY4Prj6z22bTunLWGBQzcOzc2n8ac5HGa45enTmW8blxjH0gNLu557mc6tGB5ugrS77jJzCh0O8rlPzZDQznN6sKx1F2GBBZ7v5NqvQO8CPHXpFEkz1/Cxx8wx3k+V+yUpiRw0yPQAFihAHjyYQy/AdYKCPxHvFPyJiIhIXjRy80jCArss6eJatvzQchbrV4wFehdwJYaJjI1k7VG1edtXt6XJbvn76d9v2ALymZm8Y7JHL95HMyaRJJs2NcFbtWomUyjK7DXbdK9g/r59L3HLLtd+Laa+4DrmnDlm31q1yMTEtOccMMCsf+21XHqS2QQFfyLeKfgTERGRvOhs7FmGhIW4Mlf+uP9H15y+QesGeWybmJzIq0lX0xzDtm3WHV3X1SvYYX4HPj7pccYmxObW0/CJ81fO87W5r7Hb0m6u4ZmPTHjE9OjN/xefHP8CLyeYNKAxMSYDqCtZS5DNQp+6ewjrde3JqVNthv73DsICH26/lLZN/vqr6dkDyJ9/Tr8dsbFkuXJmLuCxY7n17LMOCv5EvFPwJyIiInnVlB1TWLx/cY8ernFbxmXrGF+s/yJNEpjsHsNfHLaDmyM2e8xt/ODnDzjx94muOZHOYDA12ya7dDGB3DvvkH1X92XpvhV500d3cM2u/STJheGrWfpvg4kgB0ePNplDATO/z5tPPzXb9eplegcfe8yUrLhmaqZfQMGfiHcK/kRERCQvOxZzjM2/a05YYNiqsGzvHx0fzRdnvsjbh9/OJ757grDAe8fcmyaRTF5h2zYHrx/M2766jcFhwQwOCyYs8MWZL7LkgJIetfxm757t5TgmeYsjbWzosnGjCeRCQszf1q0zb9/RoybxS+XKnuUgRo/2fwAIBX8i3in4ExERkbzOtm2evHTSJ8dpMLYBYYEbjm/wQct8b+auma4Ar+KQiiw/uDzH/DaGtm3z14hf+dKsl/jQ/x7KtHB7VjVv7g7gdu7M2j5PP222L1HCnQUUICtVImfM8Emz/hQo+BPxTsGfiIiI5Cfjt44nLLDdD+1ImqyZ+8/v99jmatJV7jybxUjIh47FHGP5weUJC1x+aHmunHPtWhO8/eMfWd9n+3ayVCkT8NWpYwK+hg1ND+LSpTnX1sxAwZ+Idwr+REREJD+5kniFpT4vxYJ9CvLM5TN88NsHCQvsuqQrW85oySk7prjq3w1cNzDH2rHh+AY2/qYxp4VPI0muO7bOVbqh04JOOXbe9OzaZZK5ZMe2beSTT5IrVriXxcaSCQm+bVt2QMGfBJAXAOwEcAXACQBtUpaXADADwGUApwG8l52DKvgTERGR/Kbb0m6EBdYaVStNMpgCvQt4PC7aryjbz2ufbjbRrFiwdwHfmPcGz8aeZcsZLfnk5Cf5zqJ3WGZgGcICg8OC+fVvX7vqGr7303tMTE6nzoJkCgr+JEA8BiACQFMAIQDKArg9Zd0kAPNhgsC6ACIBPJfVAyv4ExERkfzmcNRhV/BVsE9BTgufxnY/tGPHBR1dQV/XJV1Za1QtFutXjLDAp6c8nW5mTW+i46Nd56k2tFqaQPOZKc+4ErqkHooqfw4U/EmAWAegUzrLiwJIAHBPqmX9AMzN6oEV/ImIiEh+FB0fzYm/T+Qvh39xLXPYDr4x7w2+MucVV6B35vIZVw/h/L3zPY6RkJzArae28tLVS+me4/1l76fpRVxzdA3n753PWbtn0WE7uOrIKjYc25C1RtViVFxUzj3hfAAK/iQAhABIBPA+gH0ATgGYDKA0gPoAkgEEp9q+FYADWT24gj8RERER7xbvX0xYYONvGrtKRBy8cJD1x9R3DRUdunGoxz6bTmxigd4FWKxfMX68/GPCAgesHZDhOfJq6YkbCRT8SQCoCIAAfgdQGUBJAPMAfA/gYQAx12zfHMAZL8frBfPBcN78/TkVERERydNs23YFemO3jCVJV8mIe76+h0X7FWWQFcSxW8Yy4mIET1w84Rrm6Swov+/8PgV4OQwK/iQAlIIJ/t5KtawhgFi4e/6CUq17Eer5ExEREfGpNUfXsGCfggwOC+bnaz93BX7JjmT+sOcHj+GdJQaUICyw7Zy2CvhyERT8SYA4DuDNVI8bwmT9LAYz569uqnV9oTl/IiIiIj73/a7vPYK8IRuGuNYt3LeQnRZ0YtWhVQkL7DC/g7J25jIo+JMA8RmAbQAqALgJwByYYZ8A8B3MMNDiAOrADPlUtk8RERGRHPDmvDddJRpOXTqVZn2yI5mHog6px88PoOBPAkQBAMMARAE4B2AKTMIXwJR4+B6mzt8ZqM6fiIiISI6Jjo/mPV/fww7zO/i7KXINKPgT8U7Bn4iIiIgEAij4E/FOwZ+IiIiIBAIo+BPxTsGfiIiIiAQCKPgT8U7Bn4iIiIgEAij4E/FOwZ+IiIiIBAIo+BPxTsGfiIiIiAQCKPgT8U7Bn4iIiIgEAij4E/FOwZ+IiIiIBAIo+BPxTsGfiIiIiAQCKPgT8U7Bn4iIiIgEAij4E/FOwZ+IiIiIBAIo+BPxTsGfiIiIiAQCKPgT8U7Bn4iIiIgEAij4E/FOwZ+IiIiIBAIo+BPxTsGfiIiIiAQCKPgTyZTzg6Kbbrrppptuuummm2438o0QkTzL9ncDxG907fMnXff8S9c+f9J1z7907UUkDf3DkH/p2udPuu75l659/qTrnn/p2otIGvqHIf/Stc+fdN3zL137/EnXPf/StReRNHr5uwHiN7r2+ZOue/6la58/6brnX7r2IiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiJ5TCiA0QCiAVwAMAhAkF9bJL7wLwBbACQAmH3NuhIAZgC4DOA0gPeuWV8JwFIAVwAcBdA2JxsqPlUIwDcAjsBc3z8AtE+1Xtc+cPUBcAzAJQAnAXwJ8++7k6594LsFwHmYf/udMruutQBsABAH8+9F8xxvpfjKRACJAGJT3e5MtV6feRFJVxiAXwGUA1AVwD4A//Zri8QXXgDwPICRSBv8TQIwH+Y/hroAIgE8l2r9apgfBIoAeBTmP457c7a54iPFAPQGUAPmR5z7YX7YeSxlva594LoTQPGU+2UBrATwYar1uvaBbwrMdUwd/Hm7rqEADgL4GOaHo5dgfjyokDvNles0EcAXXtbrMy8i6ToBoEWqxx0B/O6ntojvWfAM/orC9Abek2pZPwBzU+7XAJAEoHSq9VMBDM25JkoO+wHAZ9C1z0/KAlgB4NuUx7r2ge9JAGsAvAF38JfZdX0cwDkAIanWrwfQJUdbKr4yERkHf/rMi0i6bgZAANVSLbsPZhiBhn4GBguewV99AMkAglMtawXgQMr9ljBDBlPrAeDnHGqf5KzCACIA/AO69vnBP2F+vSfMl/oGKct17QNbUQB7AdSGGebtDP4yu67dYHqIUxsFM3Rc8r6JAKJSbjsBdE61Tp95EUlXFZgvCaVSLbsjZVlhv7RIfM2CZ/D3MICYa7ZpDuBMyv1XAWy/Zn1HAJtyonGSo4JghoGthPkCoGuff9SEGf5bMeWxrn1gGwRgQMr99nAHf5ld108BzLtmfT+YeWKS9zWA6eUPgfmMn4G55oA+8yKSAWfPX9VUyxpBPX+BxEL6PX+pr++L8Pw18PA1x+gO/Rp4owkCMAbAbwBKpizTtc9fWsEkcwB07QNZPQD7YeZtAWl7/rxd124Afrlm/Uio5+9G9RGARSn39ZkXkQydgOcE4A7QnL9AYiH9OX91Uy3rC+/zAKZA8wBuJEEwk/i3wfzA46Rrn7+0AXAo5b6ufeDqCpOt8UzK7SLMtTwDoCG8X9fHYZKApB4auA6a83ej+gDA4pT7+syLSIZ6w3Tz3wIzDPQPKNtnICgAM3S3L0zCj8IACqas+w5mqE9xAHVgviSk/gFgDcy8jyIAmkIZwG40owDsAFAmnXW69oHrXZhrHgQz92sXgK9Trde1D0xFYbJzOm9dYIbzVYB5L3i7rs5snx/CZPtsBZPt8y+513y5Dq1hPs9BAP4KU87hrVTr9ZkXkXSFwnxBiIGZNDwYGvIZCCyYIb2pb6tS1pUA8D3MP/RnkH7tn59g6j4dg2r/3EiqwVzrq/Cs/TQmZb2ufeD6EabG2xWYRA5fwAQGTrr2+UN7pK3z5+261gawEUA8TNIY1fm7cayB+e52GcAepP3hXp95ERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERHJqv8HZd3ElhkeX2MAAAAASUVORK5CYII=\" width=\"999.4166358888987\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f725639cb70>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot the trajectories\n",
    "colors = ['r', 'b', 'g', 'y', 'c']\n",
    "fig_sample_traj = plt.figure(1)\n",
    "ax_sample_traj = fig_sample_traj.add_subplot(111)\n",
    "for k in range(5):\n",
    "    ax_sample_traj.plot(trajs[k], color=colors[k], label=\"Trajectory \" + str(k+1))\n",
    "ax_sample_traj.set_title('Sample trajectories of geometric brownian motion', fontsize=20)\n",
    "ax_sample_traj.legend(loc='upper left')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before proceeding, it is worth recalling that the solution to the SDE above is:\n",
    "$$ S(T) = S(0) \\exp\\left({(\\mu - \\frac{1}{2}\\sigma^2)T + \\sigma W(T)}\\right) $$\n",
    "With $S(0)$ being the starting price.\n",
    "\n",
    "It follows that the distribution of the price $S(T)$ is lognormal. This can be easily verified formally. Here, we take an informal approach of simulating the trajectories and fitting the lognormal distribution to the final prices (prices that correspond to the latest time instance for a given trajectory)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time passed:  15.472460419000072\n"
     ]
    }
   ],
   "source": [
    "N = 20000 # number of simulated tajectories\n",
    "list_of_final_prices = []\n",
    "# this might take a few seconds...\n",
    "time_start = time.perf_counter()\n",
    "for k in range(N):\n",
    "    list_of_final_prices.append(sp.do_gbm_trajectory(x_0, n, d_t, mu, sigma)[-1])\n",
    "time_end = time.perf_counter()\n",
    "print(\"Time passed: \", str(time_end-time_start))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"999.4166358888987\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'matplotlib.axes._subplots.AxesSubplot'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f7255d7ba58>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# now, let's plot the histogram:\n",
    "df_fin_prices = pd.DataFrame(data=list_of_final_prices, columns=['Values'])\n",
    "fig_histogram = plt.figure(2)\n",
    "prices_histogram = df_fin_prices.loc[:, 'Values'].hist(bins=50, color='r', normed=True, edgecolor='black', linewidth=2)\n",
    "print(type(prices_histogram))\n",
    "prices_histogram.set_title(\"Histogram of the simulated final prices\", fontsize=20)\n",
    "# add vertical line at the point of expectation\n",
    "vline_loc = df_fin_prices.loc[:, 'Values'].mean()\n",
    "prices_histogram.axvline(vline_loc, color='b', linestyle='dashed', linewidth=2.5)\n",
    "# and add the fitted lognormal distribution curve:\n",
    "lognorm_emp_mean = np.log(df_fin_prices.loc[:, 'Values']).mean()\n",
    "lognorm_emp_std = np.log(df_fin_prices.loc[:, 'Values']).std()\n",
    "lognorm_grid = np.linspace(df_fin_prices.loc[:, 'Values'].min(), df_fin_prices.loc[:, 'Values'].max(), 1000)\n",
    "lognorm_pdf = spst.lognorm.pdf(lognorm_grid, s=lognorm_emp_std, scale=np.exp(lognorm_emp_mean))\n",
    "prices_histogram.plot(lognorm_grid, lognorm_pdf, color='b', linewidth=2.25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking only the distribution of the final price is not really that compelling. So let's have a look at the distribution of the maximum of the stock price over a fixed time interval $[0, T]$. \n",
    "\n",
    "We start by looking at the distribution of the maximum of a standard Wiener process, which is driving the changes of $S(t)$, over the period [0, t]:\n",
    "\n",
    "$$ M(t) = \\sup \\left\\{s \\in [0,t]: W(s) \\right\\} $$\n",
    "\n",
    "\n",
    "The random variable $M(t)$ is called $running$ $maximum$.\n",
    "\n",
    "Using the reflection property of the Wiener process it can be demonstrated that $M(t)$ has the following c.d.f and p.d.f. under the real-world measure $\\mathbb{P}$: \n",
    "\n",
    "$$ F_{M(t)}(m) = 2 \\left( 1-P(W(t) \\leq m) \\right) = 2 \\left( 1 - P \\left( U \\leq \\frac{m}{\\sqrt{t}} \\right) \\right)$$\n",
    "\n",
    "$$ f_{M(t)}(m) = \\frac{2}{\\sqrt{2 \\pi t}} e^{-m^2/(2t)} $$\n",
    "\n",
    "Now, let's generate Wiener process trajectories and have the look at the empirical distribution of the maxima."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time elapsed:  2.25445462100015\n"
     ]
    }
   ],
   "source": [
    "N = 50000 # number of trajectories\n",
    "n = 500 # number of steps\n",
    "d_t = 1/250 # time step length\n",
    "list_of_maxima = []\n",
    "time_start = time.perf_counter()\n",
    "for k in range(N):\n",
    "    # Wiener process always starts at (0,0)\n",
    "    temp_traj = np.cumsum(np.hstack([np.zeros(1), np.random.normal(size=n, loc=0, scale=math.sqrt(d_t))]))\n",
    "    list_of_maxima.append(temp_traj.max())\n",
    "time_end = time.perf_counter()\n",
    "print(\"Time elapsed: \", str(time_end - time_start))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
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       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
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       "            fig.send_message(\"refresh\", {});\n",
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       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
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       "    this.ws.onmessage = this._make_on_message_function(this);\n",
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       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"999.4166358888987\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f7255bee748>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot the maxima\n",
    "maxima_dist_fig = plt.figure(3)\n",
    "maxima_dist_axes = maxima_dist_fig.add_subplot(111)\n",
    "maxima_dist_axes.hist(list_of_maxima, bins = 50, normed=True, label=\"Simulated maxima\", edgecolor='black', linewidth=1.33)\n",
    "# now add the above-mentioned density on top of it\n",
    "wiener_max_den_lambda = lambda m,t: 2/math.sqrt(2*math.pi*t)*np.exp(-m**2/(2*t))\n",
    "temp_range = np.linspace(min(list_of_maxima), max(list_of_maxima), 1000)\n",
    "max_dist_density = [wiener_max_den_lambda(m, 2) for m in temp_range]\n",
    "maxima_dist_axes.plot(temp_range, max_dist_density, color='r', linewidth=2.5, label = 'Derived density')\n",
    "maxima_dist_axes.legend(loc=\"upper right\", fontsize=16)\n",
    "maxima_dist_axes.set_title(\"Density function of the running maximum of Wiener process\", fontsize=22)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using the reflection property of the standard Wiener process it is also possible to prove that the joint probability density function of $(M(t), W(t))$ under the real-world measure $\\mathbb{P}$ is:\n",
    "\n",
    "$$ f_{M(t), W(t)}(m,w) = \\frac{2(2m-w)}{t\\sqrt{2 \\pi t}} \\exp \\left\\{ -\\frac{1}{2} \\frac{(2m-w)^2}{t} \\right\\} $$\n",
    "\n",
    "on the region  $ S = \\left\\{ (m,w) \\in \\mathbb{R}^2: m \\geq 0, m \\geq w  \\right\\} $."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# function to calculate the probability density function of the joint distribution of (M(t), W(t))\n",
    "def joint_density_max_and_wiener(m,w,t):\n",
    "    if m < w:\n",
    "        return 0\n",
    "    elif m < 0:\n",
    "        return 0\n",
    "    else:\n",
    "        const = ((2*(2*m-w))/(t*math.sqrt(t*math.pi*2)))\n",
    "        val = const*np.exp(-(2*m-w)**2/(2*t))\n",
    "    return val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# calculate the values of the p.d.f. of the joint distribution on a custom grid\n",
    "t = 5 # fixing a time value\n",
    "m_range = np.linspace(0,5,600)\n",
    "w_range = np.linspace(-5,5,600)\n",
    "M_rg, W_rg = np.meshgrid(m_range, w_range)\n",
    "\n",
    "temp_args = list(zip(np.ravel(M_rg), np.ravel(W_rg)))\n",
    "temp_vals = [joint_density_max_and_wiener(temp_arg[0], temp_arg[1],t) for temp_arg in temp_args]\n",
    "temp_vals = np.array(temp_vals).reshape(M_rg.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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width=\"1499.6832871494871\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f724e8804e0>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now, let's plot these values\n",
    "plt.rcParams['figure.figsize'] = (15.0, 8.0)\n",
    "joint_pdf_fig = plt.figure(4)\n",
    "joint_pdf_axes = joint_pdf_fig.add_subplot(111, projection='3d')\n",
    "joint_pdf_axes.plot_surface(M_rg, W_rg, temp_vals, cmap=cmp.summer)\n",
    "# add axes titles\n",
    "joint_pdf_axes.set_xlabel(\"running maximum of a trajectory\")\n",
    "joint_pdf_axes.set_ylabel(\"current value of a process\")\n",
    "joint_pdf_axes.set_zlabel(\"Value of joint p.d.f.\")\n",
    "joint_pdf_axes.set_title(\"Joint p.d.f. of M(t) and W(t)\", fontsize=20)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}