UnderstandingDistributionsThroughSampling.ipynb

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    "# Practice Assignment: Understanding Distributions Through Sampling\n",
    "\n",
    "** *This assignment is optional, and I encourage you to share your solutions with me and your peers in the discussion forums!* **\n",
    "\n",
    "\n",
    "To complete this assignment, create a code cell that:\n",
    "* Creates a number of subplots using the `pyplot subplots` or `matplotlib gridspec` functionality.\n",
    "* Creates an animation, pulling between 100 and 1000 samples from each of the random variables (`x1`, `x2`, `x3`, `x4`) for each plot and plotting this as we did in the lecture on animation.\n",
    "* **Bonus:** Go above and beyond and \"wow\" your classmates (and me!) by looking into matplotlib widgets and adding a widget which allows for parameterization of the distributions behind the sampling animations.\n",
    "\n",
    "\n",
    "Tips:\n",
    "* Before you start, think about the different ways you can create this visualization to be as interesting and effective as possible.\n",
    "* Take a look at the histograms below to get an idea of what the random variables look like, as well as their positioning with respect to one another. This is just a guide, so be creative in how you lay things out!\n",
    "* Try to keep the length of your animation reasonable (roughly between 10 and 30 seconds)."
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       "\n",
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       "\n",
       "\n",
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       "    fig.ondownload(fig, format);\n",
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       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
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       "    };\n",
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       "\n",
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       "}\n",
       "\n",
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       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
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       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
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       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
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       "        cursor = 'default';\n",
       "        break;\n",
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       "        break;\n",
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       "\n",
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       "    fig.message.textContent = msg['message'];\n",
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       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
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       "    return function socket_on_message(evt) {\n",
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       "            /* FIXME: We get \"Resource interpreted as Image but\n",
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       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
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       "                    fig.imageObj.src);\n",
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       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
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       "        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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f4a96af0a20>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib notebook\n",
    "\n",
    "# generate 4 random variables from the random, gamma, exponential, and uniform distributions\n",
    "x1 = np.random.normal(-2.5, 1, 10000)\n",
    "x2 = np.random.gamma(2, 1.5, 10000)\n",
    "x3 = np.random.exponential(2, 10000)+7\n",
    "x4 = np.random.uniform(14,20, 10000)\n",
    "\n",
    "# plot the histograms\n",
    "plt.figure(figsize=(9,3))\n",
    "plt.hist(x1, normed=True, bins=20, alpha=0.5)\n",
    "plt.hist(x2, normed=True, bins=20, alpha=0.5)\n",
    "plt.hist(x3, normed=True, bins=20, alpha=0.5)\n",
    "plt.hist(x4, normed=True, bins=20, alpha=0.5);\n",
    "plt.axis([-7,21,0,0.6])\n",
    "\n",
    "plt.text(x1.mean()-1.5, 0.5, 'x1\\nNormal')\n",
    "plt.text(x2.mean()-1.5, 0.5, 'x2\\nGamma')\n",
    "plt.text(x3.mean()-1.5, 0.5, 'x3\\nExponential')\n",
    "plt.text(x4.mean()-1.5, 0.5, 'x4\\nUniform')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.animation as animation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = [x1, x2, x3, x4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "axis1 = [-7,1,0,0.6]\n",
    "axis2 = [-1,12,0,0.6]\n",
    "axis3 = [7,17,0,0.6]\n",
    "axis4 = [13,21,0,0.6]\n",
    "axis = [axis1, axis2, axis3, axis4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bin1 = np.arange(-7,1,0.5)\n",
    "bin2 = np.arange(-1,12,0.5)\n",
    "bin3 = np.arange(7,17,0.5)\n",
    "bin4 = np.arange(13,21,0.5)\n",
    "bins = [bin1, bin2, bin3, bin4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "titles = ['x1: Normal', 'x2: Gamma', 'x3: Exponential', 'x4: Uniform'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "anno_x = [-2, 7, 13, 18]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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>"
      ]
     },
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     "output_type": "display_data"
    },
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lJ0INka9Ss3n1mWPL8nWk9Up3m3jSzTykh82+4iYbvKlIL7tOC9ltZrPaPRukt7UawBay1nT5SU/eH5f5kVrRWvGvORzxL1zw8mXxHkHxzjJW5v9vcPJiw+8cpAEgdYRwABsXUgZEAQaScCmi7cPeHuvk7dp+vw639Tq9G1JvmV21DSOAThqm8PK9TsDsFvmdWm7gn+2+PQZJVmjrYgB6G2zPjPGaZiIch6fseinst2LNiwsfctuNmXbLWIqdstmx2qx5q0Yecn9yG7v8YqDvDMJXUdWsPmmwDzDLtueDWbfKGhxaoHfe8C1t5v46bKf/Pv2vX7bQDAAh81wXocABCAAgbYRmLRe6/LaS9LnMvB2T7fETpOnH4T6vLxuGrSCrpvng2kXxaB+WtPlHVfSLeez+Wyq+WgT786wTsl+b7c554ewTl4h6eNbelNWp9hY+/AQeD7Kxasunf4ts/W6XzHrS+tMJ5uZ/S7Z6DUAfbxNlmdvvb4AxSsanbzqz+O2DstL2QfXRQw7H0/jlYI2kr2V3DrPD927yT93z3v0ykdfRkeCQOsIYAC2LqQMCAKNJWBB5G2oNmSy6bq0InCcp6VNMwBtwvnCi+4lFz4XxuexdNMwA7BXtFqo5d3SlmXtlYc+MNnJJqQP/c6mbLt524T7TcCsAWjjLXv2S29+i7Gs4MveJtyvbq+U9LmJTl4Z8NQB74BdEkcL66LJ20v6rXLEACxKkHwQgAAEINAmApPUa+a0TToKpns0jLWHL2CbdhplBeC4BuBWadeHtVLR5ONxfNNtb8rqFBuGXtU3KNmc614yUkar+Uxom2u9KWsA+mH2UkPa95bj7g28w1YsuqrskTmDjqTxmYHW0N7em7dasrdr1uA2CkkQaB0BDMDWhZQBQaDRBLIr3zyQYWeQFB1s0wxAj8tizSsfnXz+obdndFfGDTMAvc2jKwb9FNW3phVJvnCle5tbv60u2XZ9m6/PSymSsgagx5F3sUa3ruwWHpuh/Q527ubtvWUue5NcN48/67xNeJQvED5A+k99BokBWCTy5IEABCAAgTYSmJRe84US1iI2bZx+IMlnQ9tkqiNVcQZg70q4vBWARczDfgzyLuHI6hRv2fXumkFpHK3Wz1PIjts6qnvhX14fXpDpo3cFeVyDkreHe5u4k29r7m4Xz5bxQ2Sv5hu0/blfG5O+8bmOuUybEOgQwABkIkAAApEIvETSaZkOXS/Jq7VsgI2TmmgAery+9bi7pfUzmRvShhmA3jb7ywTMF4l4W22R5Ft5u1utD5D0kZ5C2XZtpvnnIikrKotsfckafsM+p4oYgLtJOiLT0R9J+kY6489PvH22kG8m7qYi/cUALBJ58kAAAhCAQBsJTEKvecurzRpvxXTy5+zLJfnM4bqSz8Xzg0unb0racYSOFDEAe3mencyt89P2Xm/P9U2+3VREgxTJkx1OEe2TzT9MqxXRZ9n6sgbgLyT550GpiAHonSzdm5ut83xuoE1l73jxedd+SP5gaqRsf0eYChSBQP0Ehn2xqr+H9AACEJgVAl6W7yX3K/YMuOhNs4M4NdUA9Go8Pwl3svDzdlcbVsMMwGmsAGySAeibo7tbg4tsXfah2t2b5fIMy7LCelbex4wTAhCAAATaTWASeu2ZyfDrfvb6RldvCb2jZpRZvTXqqrAiBqAfftsEdPpy2t46aPeDL97w1l+nzRO7XlRldUrbDEBvZ/bZiPY7fJaz59OgVZCeg/4e4nRNOie65ulH8xCongAGYPVMqRECEBiNgM8m2TYV9VluNl66578UObtkUKtNNQA9Jq/k84o+pyMl+SDsYQZg7xmAXgHolYDDUpkzAJtiAPrQ6e4WXt/u6/MQBx0q7TN/nK/7+YgBOGzW8DoEIAABCMwSgar12tMlecWXL39z+m1a/TXO2c9VxcNnB2d3O/gSCZuTZdIwA9Ba1zsRHpmMKj8Iz16G1q8tn+vcPc8OA7D/FmBfOucVf04nS9p6SND8ulcHOmEAlpnh5G0UAQzARoWLzkKgtQRsan0xjc7L8f1U09ssvFrLySuyfHOrtwSPkppsAPoMFPffyWfgWCi/X5JFqdPHJO3XB0r2FmAbq761d1CykHSZorcAN8UAtFg/Jw3c/91oCIctk1DsZsMAHOUdRxkIQAACEGgjgar1mj9jfd7bKgmWV+xvmrlhtm6GvhXXZlD3llsfH7JTyU4NMwBtfN6Q6vR/e3fC9Da3lqRLM7/EAOxvAO4r6aOJk/+7/5C4HSppn5QHA7DkJCd7cwhgADYnVvQUAm0lYEProsxFFd3LJfxE1KvfuobNz9L2iEFbIvIYNdkA9JiyW0OOS0+IhxmAx0vaIQH5TjpEe9Acerekj6cMNlotxntZN/EMwPUyT+uL3Ormp7/Zp8QYgG39y8O4IAABCECgDIGq9Zp3K1jn+XPWyabLJmnbZpl+TTqvH0b7go5uKrsrZZgB6F0a3RV/RW7L/ZykvTL9wQDsbwDazLOp5/RZSb7cLi/5sryrMqtQMQAn/a6i/toIYADWhp6GIQCBtN3BBx13zzGx+fKKDBkfvPzrzIHQ/jD/xAjkmm4Ari/p3DRun2Pis19sbDnlrQC0IPRh2t3k8wR/nMPON7OZ81Lp9bxz8ppoAHplo4V19wwYnwVokdcv2TC1cZpNGIAjvOEoAgEIQAACrSLg7alV6jUfx+GVfzYVnfzg0Sv/fOlGtPQoSb+StHbqmLfrehXg9wp2dJgB6J0X3u782FSfL7/wluh+6fnpte4ROc6DAdjfAPSldr7czslHC62RufCjl+3hkvbI/BIDsODkJlvzCGAANi9m9BgCbSKQXW7vbQ/e5utzTbJpZ837YHfyDV7e0mmzqkwaxwDsFW5ltr4O6mP2sGXfcuebaQclC82sOdrNm2cA+vVT0g16/n/fIPcfkk7sacS3DNv08gUjTj4w2XHwOXi9qYkGoMdg4d5dSXpxuhHu8szgLL7fLOnTaQu0zwi04HfCACzzTiMvBCAAAQi0kUCVeu1x6TKGZydQPqPYx538rgJw2Z0LB/as3BunemsBHyNi49LJ7VhPWYNZV/TbnWJtYVPzPzMXfOTpiuxttdaHfiDZe9bg9pKOkuSziu+S5O3JThiA/Q1AzzNfnOfVfU5fSysns/rWLL2w4E09TDEAx3m3UDY0AQzA0OGhcxBoNYEXSvpJMlwsnHz2Wp4Jlt3O6osqbFr5rMDetFIyvXp/b3OrK5R8zl33rJVuPj95dvv9UhQD0Kacjc/ev9uDDECfK3OWpKdkBvaHtJrQZqrPkbGh2q3TgnKLVKYfi6YagC9K26i75xva4DMXrwR8dNpy1D1z572SdpPkVZF5Qt2/L3u7XqvfzAwOAhCAAARaS6BqvXaCpNdkaPnzNHum3SCQ1jCfGZBhUgagm7Qu8MPYrnHZ7YYfXHtnho1MP2y13vQxKtZt3bMDu3l9C63PZe693dh67AJJi6WMHodXXPpMRK++9EPM7lZpm4BPS6aps2MA9jcAzcYmsM/N7iavtPSOmuvSWYtebel4+YztN2QWHGAAtvbPGQPDAGQOQAACdRBYWpLPY/P5L07Dzubw1tTfSHpCyu+l+j4rsDf1mnVFxzbogz6KAeix+PBpX46STYMMQOezCegnyxbwg5K3R3hLy/kDMjXVAPSQvLXD5+YsnDM+b63+cFot8H8YgEXfOuSDAAQgAIEWE5iEXss+QCuLzltjbdrkpUkagG7Tq8neJuldmVt4h43BfTpT0ieHbBu2MWi91l2x1q/eI1P7PtLFqyadMADzDUBvlf6yJO8mykteEejdPX7Ibv3nhAE4bFbzemMJYAA2NnR0HAKNJuAzOXw2h9Ml6Ty7e4eMyNso/OS0u4rL22F9ZmA2td0A9BNfb5HJnv0yzADs8vEZgN5SsrGkFSQtks7G89aV70r6qiSvjBuUmmwAelzPlPSOJJa9WtSrSP0U2GclWiCahVN2ezZbgBv9p4bOQwACEIDAGAQmodeabAB2UXrVmHWVdxh4J4W3Bnu1nzWqDSWvCrSh5IeqPxxw9nBvaKw53inppemht1emeZeKdy1Yg/ncRKciuxCK5Mm2X0T7ZPNnzdZ+nkJWkxcx1GzsWuc7DTN6nWdXScek/D4qyD/nJV/u5t0djpW3Bt8q6U/JkLX+M+Oy/R3jbUVRCNRHAAOwPva0DAEIQAACEIAABCAAAQhAAAIQgAAEIACBiRPAAJw4YhqAAAQgAAEIQAACEIAABCAAAQhAAAIQgEB9BDAA62NPyxCAAAQgAAEIQAACEIAABCAAAQhAAAIQmDgBDMCJI6YBCEAAAhCAAAQgAAEIQAACEIAABCAAAQjURwADsD72tAwBCEAAAhCAAAQgAAEIQAACEIAABCAAgYkTwACcOGIagAAEIAABCEAAAhCAAAQgAAEIQAACEIBAfQQwAOtjT8sQgAAEIAABCEAAAhCAAAQgAAEIQAACEJg4AQzAcohXk/Q2SVtJWlXSPyRdKekESZ+XdHe56gbmfrGkf5O0saQVJT0g6UZJ/yvpZ5KOk3Rnhe1RFQQgAAEIQAACEGgrATRcWyPLuCAAAQhAAAIQKEQAA7AQpk6mbSR9VdKSOUWuSMbgH4tX2Tfn4yQdI2nbIfWsLenXY7ZFcQhAAAIQgAAEINB2Ami4tkeY8UEAAhCAAAQgMJQABuBQRJ0MNtvOkrRYWnV3iKSfp593lPSmVI1NwHUl3VGs2jm5HptW962TXvmOpJPSKsMH06rDzSS9OhmSGIAjgqYYBCAAAQhAAAIzQQANNxNhZpAQgAAEIAABCAwjgAE4jNC818+QtEnahruppLN7iu0j6dD0uwMlfbBYtXNy/bekf09bi7eX9P2cehy3hVJ/RmyKYhCAAAQgAAEIQKD1BNBwrQ8xA4QABCAAAQhAoAgBDMDhlNaXdG7KdoSkPfoUeYSkSyStKek2SctJun941Qvk8Fl/v0y/saH4iZLlyQ4BCEAAAhCAAAQg8E8CaDhmAwQgAAEIQAACEEgEMACHT4WDJe2fsm2YMQN7S+4nyVuDnbaQdNrwqhfIcbykHST9XdIKku4tWZ7sEIAABCAAAQhAAAL/JICGYzZAAAIQgAAEIAABDMDCc6C7deQuSUsN2Ha7kaRfpVo/JOkDhVuQHpmMv0elM/9ek8p6m+9KabvvDZiCJYiSFQIQgAAEIACBWSeAhpv1GcD4IQABCEAAAhCYT4AVgMMnw82SlpH0G0nPGZDdt/f+Lb1+oiSf4Vc0rSfpvJTZxuF/SbKJuEsyHf3Sfekswo9IOr1oxeSDAAQgAAEIQAACM0oADTejgWfYEIAABCAAAQjMJYABOHhWeEXePSnLyZK2HjKJ7pS0hKRzJHlFYNFko+8rKbMvEdlJ0lNzCj+ctiR/rGjlmXyrDCnjlYhrSLpJkkWzbx4mQQACEIAABCBQLwHvCFg2deG36bKwensUv3U0XPwY0UMIQAACEIBA2wmE0nAYgIOnm8W2zTCnb0raccjsvDFdAOILQZ5ZYia/Q9KnUn6f/WfR+iNJ75f0v5KWlPRqSR+V9NiU75WSvleiDWe1eUiCAAQgAAEIQKC5BLxr4ILmdn9qPUfDTQ01DUEAAhCAAAQgUIBA7RoOA3BwlFaV9KeU5ThJOw8JqvO6zJWSVi8wAbpZDpB0UCb/TyS9vM8KPN8U/AtJvnX4MknPKGnqYQCWCApZIQABCEAAAgEJ1C4eAzLp1yU0XEMCRTchAAEIQAACM0Kgdg2HATh4pk3r6fG7JX0805XnSro4p2s+X3C79Nqz0wrBou+XYVuAV07bl3XeeedpxRVXLFov+SAAAQhAAAIQmBCBv/zlL1p//fW7tT9R0jUTaqpN1aLh2hRNxgIBCEAAAhBoIIFoGg4DcPAkmtb5MbtL+mLqis/eW25At94o6aj0uv//6ArfBzYIr3V91157rVZZZZhfWGHLVAUBCEAAAhCAQF8Cf/7zn7Xqql7Q1kn+nz+DaigBNKRyZboAACAASURBVNxQRGSAAAQgAAEIQGCSBKJpOAzA4dG+RdLjJ3wL8JaSfMmIk1f+eQVgXtoinQ/o1/dP5wIOH0WxHBiAxTiRCwIQgAAEIDA1AtHE49QGPn5DaLjxGVIDBCAAAQhAAAIjEoim4TAAhwfyDEmbSLpL0lKSHsgp4lt/f5Ve+5CkDwyven6O1SRdnX7ypR/e2puXsmbhPpI+UaKdYVkxAIcR4nUIQAACEIDAlAlEE49THv44zaHhxqFHWQhAAAIQgAAExiIQTcNhAA4P58FppZ1zbijp3Jwi+0k6JL3mVXqnDa96gRw+z+cJkm5PRmPehR1vlfTZVHInSd8o2c6g7BiAFcKkKghAAAIQgEAVBKKJxyrGNKU60HBTAk0zEIAABCAAAQjMJRBNw2EADp+lPnW7a/odIWmPPkV8K+8lktaUdFs6w+/+4VUvkONTkt6RfvMSST/NKf9zSS9Ir9kw7JzZV1HCAKwIJNVAAAIQgAAEqiIQTTxWNa4p1IOGmwJkmoAABCAAAQhAoD+BaBoOA7DYTO1uIfH2300lnd1TzFtxD02/O1DSB3tet2Fn487pWEm79mnWZt7lknxo9W8lbZxWA2az/puk49IvfGbg1sW6XzgXBmBhVGSEAAQgAAEITIdANPE4nVFX1goarjKUVAQBCEAAAhCAQBkC0TQcBmCx6K0t6SxJi0m6U5K3lNjQ8887StotVXOFpHUl3TGCAegiWSPRZuDHJPlMwCUlvUrSmyUtlIxBt/OHYt0vnAsDsDAqMkIAAhCAAASmQyCaeJzOqCtrBQ1XGUoqggAEIAABCECgDIFoGg4DsHj0tpH01WTG9Stl828rSX/s82KRFYDdYj5HcF9JebG5SdIr+6xCLD6S/JwYgFVQpA4IQAACEIBAhQSiiccKhzatqtBw0yJNOxCAAAQgAAEIzCcQTcNhAJabnL6td+9k9Nksuy8ZfidKOkzS3TnVlTEAXYVvFPZqP98+vKKkeyXZYPy+pM9J+nu5bhfOjQFYGBUZIQABCEAAAtMhEE08TmfUlbeChqscKRVCAAIQgAAEIDCIQDQNhwHIfM0SwABkPkAAAhCAAASCEYgmHoPhoTvzCKDhmAkQgAAEIACBYASiaTgMwGATpObuIB5rDgDNQwACEIAABHoJRBOPRCgkATRcyLDQKQhAAAIQmGUC0TQcBuAsz8a5Y0c8Mh8gAAEIQAACwQhEE4/B8NCdeQTQcMwECEAAAhCAQDAC0TQcBmCwCVJzdxCPNQeA5iEAAQhAAAK9BKKJRyIUkgAaLmRY6BQEIAABCMwygWgaDgNwlmfj3LEjHpkPEIAABCAAgWAEoonHYHjozjwCaDhmAgQgAAEIQCAYgWgaDgMw2ASpuTuIx5oDQPMQgAAEIACBXgLRxCMRCkkADRcyLHQKAhCAAARmmUA0DYcBOMuzce7YEY/MBwhAAAIQgEAwAtHEYzA8dGceATQcMwECEIAABCAQjEA0DYcBGGyC1NwdxGPNAaB5CEAAAhCAQC+BaOKRCIUkgIYLGRY6BQEIQAACs0wgmobDAJzl2Th37IhH5gMEIAABCEAgGIFo4jEYHrozjwAajpkAAQhAAAIQCEYgmobDAAw2QWruDuKx5gDQPAQgAAEIQKCXQDTxSIRCEkDDhQwLnYIABCAAgVkmEE3DRTMAL5B0tKSvS/r7LE+UmsaOeKwJPM1CAAIQgAAE8ghEE485/UTD1TuF0XD18qd1CEAAAhCAwBwC0TRcNAPwIUkPS/qHpO9IOkbST5lHUyOAeJwaahqCAAQgAAEIFCMQTTzm9BoNVyyck8qFhpsUWeqFAAQgAAEIjEggmoaLZgBeImmtxNZGoNOfJH0l/btmRO4UK0YA8ViME7kgAAEIQAACUyMQTTzmDBwNN7UZ0bchNFy9/GkdAhCAAAQgMIdANA0XzQA0sPUk/YekHSQtlTEDbQienrYIfzutEmSKVUsA8VgtT2qDAAQgAAEIjE0gmngcMCA03NjRHrkCNNzI6CgIAQhAAAIQmAyBaBouogHYJb+opFdJer2kF0p6RNoe7Nd9PuA30hZhnzlDqoYA4rEajtQCAQhAAAIQqIxANPFYYGBouAKQKs6ChqsYKNVBAAIQgAAExiUQTcNFNgCzrFdNRuAukp6UXuhuEb40rQr8qqS/jhugGS+PeJzxCcDwIQABCEAgHoFo4rEkITRcSWAjZkfDjQiOYhCAAAQgAIFJEYim4ZpiAGbj8YK0RdirAxfPmIH3S/qBpC9LOnVSAWx5vYjHlgeY4UEAAhCAQPMIRBOPYxBEw40Bb0hRNNzk2FIzBCAAAQhAYCQC0TRcEw3ALvgt0hbg5dMvPJbuqkBfFvJRSUdlfjdSwGasEOJxxgLOcCEAAQhAID6BaOKxAmJouAog9lSBhqueKTVCAAIQgAAExiIQTcM1zQBcQdLOknaV9PQe4++XktaQtFz6vc3AcyS9XNLtY0VtdgojHmcn1owUAhCAAAQaQiCaeBwRGxpuRHAFi6HhCoIiGwQgAAEIQGBaBKJpuCYYgItIekU6A/ClkhaS1O33n9MqQG/79ao/v7a1pH0kPS+t/vu0pHdPK8ANbwfx2PAA0n0IQGB2Cfzxj3/U+eefr/POO6/z7+KLL9Y999zTAXLMMcdo11397KxYeuCBB/SlL31JX/va1/T73/9ed955p1ZaaSW9+MUv1tve9jY94xnPKFTRLbfcos9+9rP67ne/q6uvvrpT5olPfKJe+cpXau+999bjH//4QvVccskl+tznPqef/vSnuv766/XoRz9aa6yxhl73utfpjW98oxZeeOFC9Zx66qk68sgjO5xuvvlmLbvsslpvvfW022676eUv9/PCmCmaeCxBCQ1XAtaYWdFwYwKkOAQgAIFpEUCzDSfdVM3WO7JoGi6yAficZPrtJGnpBNL99Vl/P5T0JUk/GrDF90hJb5T0f5KeMnyKkUMS4pFpAAEIQKCBBH7xi1/oBS/w8Wr9UxkD0Kbdlltu2THJ+qVFF11Uhx12WMd4G5TOPffcjtF3ww039M224oordozB9ddff2A9Rx11lPbaay/dd999ffO5/Mknn6xlllkmt56HHnqoY/IdffTRuXk8niOOOEKPeMQjws2AaOKxACA0XAFIFWdBw1UMlOogAAEITIIAmq3dmg0DsNy7xksBXpeMv2elol2T8op02++xkm4qUO1zJV0g6UFJfgJNGk4A8TicETkgAAEIhCNw+umna/PNN+/0ywbWmmuuqSWWWKKzEtCpqAH44IMPdozEM888s1PuVa96ld70pjdp6aWXlg29D3/4w7rppps6bfzwhz/MXTV37bXXap111umssvPqvHe+853aemsv0Fen3Kc+9Sl5leFyyy2nCy+8UKus4o+fuemUU07RNttsIxt4yy+/vN773vdqgw020N/+9jfZGPz2t7/dKbTxxhvLDBZayBsB5qb9999fH/2ojwaW1l57bb3nPe/RU57yFF155ZU69NBDO6slnZzv4IMPDhffhhiAaLh6Zw4arl7+tA4BCECgEAE0W7s1W+8kiKbhoq0AvDeZdd1+ee/SSWm1n8/4K5O86u8PaYVg/28EZWqbjbyIx9mIM6OEAARaRuAPf/iDvve973W2s9p48xbZr3zlK3r961/fGWlRA/DLX/6y3vCGN3TK7Lnnnvr85z+/AClvWXH9t99+u1ZffXVddtllfbff7rzzzjruuOM6ZU844QS95jWvWaAe/26HHXbo/G6XXXbp9LU33X///Z1tvldddZWWXHJJXXTRRR3TLpve8pa36Atf+MLAMV5xxRWdLcs2HNddd12dccYZWmyxxeZXc/fdd2uzzTbTBRdc0BmLx+SxRUrRxGMOGzRcvZMGDVcvf1qHAAQgUIgAmi1fl7ZBs/VOgmgaLpoB+FAC5kfx3uL7tTEu8HiMJG8fdjqi0LuRTIhH5gAEIACBlhAYxQBca621OgaYV/x5Fd/iiy8+h4ZX0nmlnFM/c89bfldeeeXOqr0ttthCP/qRT+uYm172spfpxz/+cWc14XXXXacVVvAdEf9MWZPwkEMO0X777TenEpt3Xj146623yn2/9NJL5+SxkXn44Yd3fn/22Wdrww03nJPnnHPO0UYbbdT5fT/js+4pEU085vBAw9U7UdBw9fKndQhAAAIjE0CzzUPXBs3WOwmiabhoBqCXGtj4m7cXhzRtAojHaROnPQhAYGIEPvjBD+rAAw/s1P/www/r3nvv7Vwk8Y1vfEN++urkrbJerbbHHnsUvkhiYh2uuOKyYtJPXZ/+9Kd3emEeXdOst1s2+Hx+n9NrX/taff3rX18giy/Z2H333Tu/O/744+ev9Outx6+5vJPP3vMZfdm00047dWLl9Je//GWOQdjN6766vNPll1+upz3tafOrcdxtEPriEK8mtLmZl/y6y9u8tPn5L/8SRyJFE485DNFwFb+HS1aHhisJjOwQgEAcAmi2crs20GxxNVvvuyqahoujbuP8/ZnlniAeZzn6jB0CLSOQFZM2rbzi7Ne//nXfUfqcOV9IEfECiFHDUtYAzG7/tfG244475jZto9Di8wlPeIKuueaaBfJlt/8OMu78mm8WdnKZY4/1Eb//TK7bRpzb8k3Eecl9tVno5DF0tz37Z28f7m4btin5xS9+Mbcev27zslvuSU960qjoKy8XTTxWPkAqrIIAGq4KitQBAQjUQgDNVs4ARLPF1Wy9b6BoGg4DsJY/cWEbRTyGDQ0dgwAEyhLIisnnPe95nTPevFrMZp+3uHq110EHHTR/VZjNoe7KtbJtRcxf1gB897vfrU9+8pOdofhSjOc8xxe59k/bbrutvv/973dWyd1xxx2dC0e6yefs+WKPxz72sbrtttsGonEenyfoswu7F5a4wJ133qnHPMYneUhuy+ZsXnJfn/tc3/sl7bPPPp1LPbrJF4443k6f/vSn9fa3vz23Hr/uy0qcfKuwb0KOkqKJxyhc6McCBNBwTAgIQKCxBNBs5QxANFtczdb7Joym4aIZgMtKmrdfS/qwpOuH/BVbWdJ700Uf/u/gbxqN/ZM4tY4jHqeGmoYgAIFJE8iKyUUWWUSnnXZa54bbbPJtsj477sYbb9SznvUs/eY3vxmpW9m2RqpA0mqrraarr7561OJzypU1AL3i75vf/GanHt/eu8wyy+T2Za+99pp/QYhX53W3DruAz/IzT1+8cckllwwcz7/+6792zu1zGa8I7CbX6e3ZTr7o47DDDsut55ZbbtGyy1o+qLNqsbtt2D/b1H3zm9/cee3EE0/Udtttl1vPSSedNP+ykmhmcDTxmAMRDVfZu3ekitBwI2GjEAQgEIEAmq2cAYhmi6vZet9P0TRcNAPQj94/Iem3kp5d8I+Rv639q6S3SVrwusKCFZBtPgHEI5MBAhBoDYGsmPTKru7qtt4B+kILX2zh1Wy+TMKr0sqmNhiAW221lU455ZTO0O+55x496lGPysWw7777zl9p55WVvhm4m7wa0JdzbLDBBvLlGoOS83jln28t9krCbjr//PO1/vrrd350W45PXnJfu5eVbL311vrBD34wP+vHP/5xvec97+n8fOqpp3a2geclv95d9feJT3xC73rXu8pOg4nljyYecwaKhpvYDChUMRquECYyQQACEQmg2coZgGi2uJqt9/0VTcNFMwB/LOnFkj6QVgAW+fv0nynvqZK2KlKAPLkEEI9MDghAoDUEsmLSW1K720R7B5hd+TVs62senJtuukn+N0565CMfucAFFuPU5bJlVwC+6EUv0v/8z/90mn3wwQcHnof4/ve/v7N92umXv/ylNt544/ndXWihhTo3AG+yySY644wzBg5j00037ZR3mQceeGB+Xv/Orzm9733v04c+9KHcetyWyzt5DD/96U/n53Uf3Venn/3sZ3rhC1+YW4/H7vJOLnfAAQeMG4LKykcTjzkDQ8NVFvGRKkLDjYSNQhCAQAQCaLZyBiCaLa5m630/RdNw0QxAb/ldXpIf0f+k4B8jG4anSbpO0qoFy5CtPwHEIzMDAhBoDYGsmLzrrrvmrxLrHWDW+LFhZeOqDamsAcjT5LhPk6OJx5z3Bxqu3j8caLh6+dM6BCAwBgE0WzkDEM0WV7NhAJb7Q3CfJD/G92neRQ9i8lbhiyW5bP5+pXL9mNXciMdZjTzjhkALCWTF5MMPP5w7wtNPP12bb7555/Wf//znc84JbCqasgYg58nEPU+mIQYgGq7ePxZouHr50zoEIDAGATRbOQMQzRZXs2EAlvtDcKukJSX5lPZfFizqfUfeY3RnKluwGNn6EEA8Mi0gAIHWEJimmGzDFuBIN8r5PMAll7Qc4BZgM2iIAYiGq/evJxquXv60DgEIjEEAzVbOAESzcQvwqG+3aFuAfV2gr/3bN10GUmRc+0j6mKQrJK1RpAB5cgkgHpkcEIBAawhMU0y24RKQL3/5y3rDG97Qib9v0vXT5bzkW3+vuOIKPeEJT9A111yzQLadd95Zxx13XOd3vtnXN/z2S35tpZVW6rzkMscee+wC2Vz3tdde27lh2LcC5yX3daedduq87DG8/vWvn5/1qquu0lOe8pTOz7vvvnvnVuC85NePPPLIzssu96QnPSnMe6EhBiAart4Zg4arlz+tQwACYxBAs5UzANFscTVb79sgmoaLZgAeJmlPSddKWkvSXUP+jjxa0qWSLHqOlrTbGH93KDqPo9l3vnStsop/JEEAAhBoJgHEZDkxaUPPZpvTHnvsocMPP7xv4G+44QatuOKKndde+9rX6utf//oC+Wyi2UxzOv7447XDDjv0rcevubzTEUccod12W/Aj3KaezT2nQUai++ryTpdffvkCF6l467c/y66//nqtscYauuyyy3In85prrtkxGldeeeXOZ6BvhY6SoonHHC5ouHonDBquXv60DgEIjEEAzYZma4tm630bRNNwcdTtPFI+z++iBO10Sf7WcEvO35JlJJ2Qtgv7cKcNJF0wxt8dimIAMgcgAIEWEZimmIyIrewZgB7DWmut1THJll566Y4Jtvjii88Z2kc/+lHtv//+nd+fcMIJes1rXrNAHhuENtF8O+8WW2yhH/3oR33xvOxlL9OPf/zjzm3D11133ZyVgq67ax4ecsgh2m+//ebUc/fdd3cMvltvvbXT90sv9TPBBdOee+4538w8++yzteGGG87Jc84552ijjTbq/N75P//5z4cKaTTxmAMHDVfvrMEArJc/rUMAAmMQQLOVMwDRbHE1W+/bIJqGi2YAmlf3CbJNvdslfS2dB/iXBNPLDjaV5P0+8w4Ikrxn581j/M2h6DwCiEdmAgQg0BoCiMnyYjK7peQtb3mLDjvMH8n/TFdeeaWe+9zn6vbbb9fqq6/eMQsXXnjhOXMmuw34xBNP1HbbbbdAHv9u++237/xul112kc3K3nT//fd3Vu15O67PA7zooovmb+ft5nUfv/CFL3R+POaYY7TrrrvOqccrG20OPvjgg1p33XXlm54XW2yx+fnuuecebbrpprrgggs6Y/nd736npz71qaHeB9HE4wA4aLj6Zg4arj72tAwBCIxJAM2GZvMUaoNm630rRNNwEQ1A3wLsg4DmHegj5V3d2O27DcJdJD005t8dimMAMgcgAIEWEZg1MXnSSSfpzjt9H9a8dOaZZ+roo306hjpn+228se/Mmpd8Lp9X4PUmm2SbbbaZzjrrrM5Lr371q/WmN71Jj3vc43TeeefpoIMOki888aq9H/7wh3r5y1/ed8Z49eA666yjm2++uWOqvetd79LWW2/dyetyn/zkJ/XAAw9o2WWX7Rh7eUdOnHLKKdpmm206qwmXX355HXDAAVp//fU7K/6OOuoofetb3+rU6bH5NueFFrKEmJu8YtErF53WXntt7bvvvh0z0Ybmxz72MV188cWd15zv4IMPDvcuiCYeBwBCw9U3ezAA62NPyxCAwJgE0Gxotu4Uarpm630rRNNwEQ3ALjMvDfBlIGvn/D25MF3+cdKYf28o/k8CiEdmAwQg0BoCsyYmn/jEJ865kCMvmDb5bJj1S7fccou23HJLnX/++X1fX3TRRTsrA9/4xjcOnCvnnnuuXvnKV8pbgvslm5Df/e53tcEGPsEjP9no22uvvXTffff1zWRD8OSTT9Yyy/hkkP7JBqKNTK9wzEs2SX1+oc3NaCmaeCzABw1XAFLFWdBwFQOlOghAYHoE0Gz5rNFsc9lE1my9vY2m4SIbgF123vJrE7Cr7H0moM8J7P+NYnp/p9rYEuKxjVFlTBCYUQKIydHEpEt5dZ6NN1/w4W2+d911V+fG3he96EXae++99YxnPKPQrLKZ+JnPfKZj9F199dWdMr5dd9ttt9Xb3/52Pf7xjy9UzyWXXKLPfvaz+tnPfta50GOJJZaQL+143ete1zEi+21D7lexVxTa5LO56b7ZNFxvvfU6l5bkrWYs1MEJZ4omHksMFw1XAtaYWdFwYwKkOAQgUB8BNBuarZdAUzUbBmB9f0douTwBxGN5ZpSAAAQgAAEITJRAgw3AiXKh8gUIoOGYEBCAAAQgAIFgBKJpuCasAAwWwlZ3B/HY6vAyOAhAAAIQaCKBaOKxiQxnoM9ouBkIMkOEAAQgAIFmEYim4TAAmzV/Jt1bxOOkCVM/BCAAAQhAoCSBaOKxZPfJPh0CaLjpcKYVCEAAAhCAQGEC0TRcVAPQ/XqppE0kPVnSYyT1v9rvn+h9W/BWhSNBxn4EEI/MCwhAAAIQgEAwAtHE4xA8aLh65g8arh7utAoBCEAAAhDIJRBNw0U0AH0d4H9LWr3EPPI4bAAOMwlLVDmTWRGPMxl2Bg0BCEAAApEJRBOPA1ih4eqbSGi4+tjTMgQgAAEIQKAvgWgaLpoB+FRJF0paQpL79qAkXxv4N0kPFZhTGxXIQ5Z8AohHZgcEIAABCEAgGIFo4jEHDxqu3nmDhquXP61DAAIQgAAE5hCIpuGiGYBfkbRzMvsOlvRpSbcyj6ZGAPE4NdQ0BAEIQAACEChGIJp4zOk1Gq5YOCeVCw03KbLUCwEIQAACEBiRQDQNF80A/JOklSUdJmnvERlTbHQCiMfR2VESAhCAAAQgMBEC0cRjziDRcBOJfuFK0XCFUZERAhCAAAQgMB0C0TRcNAPwXkmLSNpM0pnTCQmtZAggHpkOEIAABCAAgWAEoonHHDxouHrnDRquXv60DgEIQAACEJhDIJqGi2YA/lnSipLWk3QR82fqBBCPU0dOgxCAAAQgAIHBBKKJx5zeouHqnchouHr50zoEIAABCEAAA7DkHDhB0qsl7SLpqyXLkn18AojH8RlSAwQgAAEIQKBSAg0xANFwlUa9dGVouNLIKAABCEAAAhCYLIFoGi7aCkDf4ntGWv3n/y9y8+9kIzZbtSMeZyvejBYCEIAABBpAIJp4zEGGhqt3LqHh6uVP6xCAAAQgAIE5BKJpuGgGoIG9Q9InJH1H0hsk/Z15NDUCiMepoaYhCEAAAhCAQDEC0cTjgF6j4YqFdBK50HCToEqdEIAABCAAgTEIRNNw0QzA9yS220ryk+Q7JJ0q6feS7i7A/dACeciSTwDxyOyAAAQgAAEIBCMQTTzm4EHD1Ttv0HD18qd1CEAAAhCAwBwC0TRcNAPQW34fHnHeuNzCI5al2DwCiEdmAgQgAAEIQCAYgWjiMQcPGq7eeYOGq5c/rUMAAhCAAAQwAEvOgXHP/HtEyfbIviABxCMzAgIQgAAEIBCMQIMMwHHIoeHGocdD3PHoURoCEIAABCAwAQLRNFy0FYCLjsn8H2OWn/XiGICzPgMYPwQgAAEIhCMQTTzmAELD1Ttz0HD18qd1CEAAAhCAwBwC0TRcNAOQKVMvAcRjvfxpHQIQgAAEIBBePBKikATQcCHDQqcgAAEIQGCWCWAAznL0448d8Rg/RvQQAhCAAARmjEA08Thj+JsyXDRcUyJFPyEAAQhAYGYIRNNwrACcmalXaKCIx0KYyAQBCEAAAhCYHoFo4nF6I6elEgTQcCVgkRUCEIAABCAwDQLRNFxkA/D5knaVtJGkFSQtJmkdSb/PBOp5ktaQdIekE6cRwJa3gXhseYAZHgQgAAEINI9ANPFYgCAargCkirOg4SoGSnUQgAAEIACBcQlE03ARDcBHSfqSpNcm2N0+PizpmZJ+lwnCZpJ+LsmvPVXSVeMGaMbLIx5nfAIwfAhAAAIQiEcgmngcQAgNV9/0QcPVx56WIQABCEAAAn0JRNNwEQ3Ab0vaVpL79htJv5S0VzL5eg1AQ740rQLcX9KhzLuxCCAex8JHYQhAAAIQgED1BKKJxwEjRMNVH/6iNaLhipIiHwQgAAEIQGBKBKJpuGgGoI2/7ySzb29Jh6W4PDTAAPyQpAMk/UjSllOKY1ubQTy2NbKMCwIQgAAEGksgmnjMAYmGq3eGoeHq5U/rEIAABCAAgTkEomm4aAbgdyW9QtLxknbK0BtkADq/y/1J0hOZc2MRQDyOhY/CEIAABCAAgeoJRBOPOSNEw1Uf+jI1ouHK0CIvBCAAAQhAYAoEomm4aAbgdenCD5t6Jxc0ANeVdJ6keyQtMYUYtrkJxGObo8vYIAABCECgkQSiiccciGi4emcXGq5e/rQOAQhAAAIQmEMgmoaLZgDeK2mRdNvvrwsagM+VdIGkf6Sbgpl2oxNAPI7OjpIQgAAEIACBiRCIJh5zBomGm0j0C1eKhiuMiowQgAAEIACB6RCIpuGiGYA3S1pa0taSTi1oAP4/Sd+S5CfPq04njK1tBfHY2tAyMAhAAAIQaCqBaOIxhyMart4Jhoarlz+tQwACEIAABOYQiKbhohmAv5K0gaTeG30HnQH4FUk7SzolGYdMu9EJIB5HZ0dJCEAAAhCAwEQIRBOPOYNEw00k+oUrRcMVRkVGCEAAAhCAwHQIRNNwcUENZwAAIABJREFU0QxA3+brW32vl/RkSfelsOQZgBtKOkPSQpLeIumL0wlja1tBPLY2tAwMAhCAAASaSiCaeMzhiIard4Kh4erlT+sQgAAEIACBOQSiabhoBuBSkq6U5P9+T9Kukm6X1GsAut//JukzKa+3/66ezgFk2o1OAPE4OjtKQgACEIAABCZCIJp4zBkkGm4i0S9cKRquMCoyQgACEIAABKZDIJqGi2YAOgovk/T9tKrvTkk/k/RKSQ9L+m66JMTbhJeR5P57leCLJJ01nRC2uhXEY6vDy+AgAAEIQKCJBKKJxwEM0XD1TTA0XH3saRkCEIAABCDQl0A0DRfRADS4zSUdJ2mlRNHmXzZ1+32DpB0k/ZL5VgkBxGMlGKkEAhCAAAQgUB2BaOJxyMjQcNWFvkxNaLgytMgLAQhAAAIQmAKBaBouqgHoUCwq6d8lvULSumnFn8/6u1XSxWmV4Jck3TOFuM1KE4jHWYk044QABCAAgcYQiCYeC4BDwxWAVHEWNFzFQKkOAhCAAAQgMC6BaBousgHYj7X727sacNyYUP6fBBCPzAYIQAACEIBAMALRxOOIeNBwI4IrWAwNVxAU2SAAAQhAAALTIhBNwzXNAJxWnGa1HcTjrEaecUMAAhCAQFgC0cRjWFCz3TE03GzHn9FDAAIQgEBAAtE0HAZgwElSY5cQjzXCp2kIQAACEIBAPwLRxCNRCkkADRcyLHQKAhCAAARmmUA0DYcBOMuzce7YEY/MBwhAAAIQgEAwAtHEYzA8dGceATQcMwECEIAABCAQjEA0DRfNALx7jHj5bMAlxihPUcQjcwACEIAABCAQjkA08ZgDCA1X78zBAKyXP61DAAIQgAAE5hCIpuGiGYAPjTFnbAD6lmDS6AQQj6OzoyQEIAABCEBgIgSiicecQaLhJhL9wpWi4QqjIiMEIAABCEBgOgSiabhoBuAhBcLgVX5Pk/QCSYtIOlfSL1K5/QuUJ0s+AcQjswMCEIAABCAQjEA08ZiDBw1X77xBw9XLn9YhAAEIQAACcwhE03DRDMAyU2YFSV+W9BJJe0o6qkzhEfOuJultkraStKqkf0i6UtIJkj4vaZztL3ldWlzSJZKelDJcI+mJI/Z/WDHE4zBCvA4BCEAAAhCYMoFo4rGC4aPhKoDYUwUarnqm1AgBCEAAAhAYi0A0DddkA9CB8ArACyStIel5ki4cKzqDC28j6auSlszJdkUyBv9YcR8+IeldmToxACsGTHUQgAAEIACByASiiceKWKHhKgKZqsEArJYntUEAAhCAAATGJhBNwzXdAHRA/kPSlyQdL2mnsSPUv4K1JZ0laTFJd0ryNpefp593lPSmVMwm4LqS7qioH273fEn3p3+PkYQBWBFcqoEABCAAAQg0gUA08VghMzRcdTAxAKtjSU0QgAAEIACBSghE03BtMADXSSbZdWlbbiWB6qnkDEmbSHpA0qaSzu55fR9Jh6bfHSjpgxV0whea+HxDj+/9kt4gyVuQMQArgEsVEIAABCAAgaYQiCYeK+SGhqsOJgZgdSypCQIQgAAEIFAJgWgarg0GoLf+ninpPkmPqiRKC1ayfjLi/NsjJO3Rp41HpHP61pR0m6Tl0oq9cbrzTkmflHS5pGdJ8upCDMBxiFIWAhCAAAQg0EAC0cRjhQjRcNXBxACsjiU1QQACEIAABCohEE3DtcEA/Kik90j6i6SVK4nSgpUcLKl7u/CGGTOwt6n90tZg/34LSaeN0RcbfZdK8o3Hm0s6XdLVGIBjEKUoBCAAAQhAoKEEoonHCjGi4aqDiQFYHUtqggAEIAABCFRCIJqGa7IBuKikN0v6uCSvwPu6pH+vJEoLVtLd/nuXpKXSNuB+zWwk6VfphQ9J+sAYfTlZ0paSjpO0c6oHA3AMoBSFAAQgAAEINJVANPFYAUc0XAUQe6rAAKyeKTVCAAIQgAAExiIQTcNFMwBPKUDXZt/jJK0laXFJHsPdktaTdFmB8mWz3CxpGUm/kfScAYXdp7+l10+UtH3ZhlJ+XyryDUm3Snq6JLfvhAE4IlCKQQACEIAABJpMIJp4zGGJhpPQcE1+o9F3CEAAAhCAQMUEomm4aAbgQ5IeLsA82+/r08o/38pbdfKZgvekSr0qb+shDfiGYG/bPUeSVwSWTTYRbWIuL2l3SUdmKqjCAPTT4UFphXShiq699lqtssqw7GWHR34IQAACEIAABMoSiCYec/qPhkPDlZ3a5IcABCAAAQi0mkA0DRfNALRxNswAtMC8Q9L/SfqFpO9KundCs2ZZSTelur+peU92B6Ub0wUgl0h65gh9+lK67de3DD+/h0UVBuAwtvO7jAE4QvQoAgEIQAACEJgAgWjiMWeIaDjpDZLQcBN4D1AlBCAAAQhAoIkEomm4aAZgtJiuKulPqVPZ8/jy+um8LnOlpNVLDmbTdNnHg5LWkfS/PeUxAEsCJTsEIAABCECgDQSiiceGMEXDNSRQdBMCEIAABCDQVgLRNBwG4OCZNq0VgD4M22cM+sy/T0p6d59uVWEADtvTyxbgtv7lYVwQgAAEINBYAtHEY0NAouEaEii6CQEIQAACEGgrgWgaDgNw8Eyb1hmAvjX4fZKulbSmJN843JuqMACHva+4QW4YIV6HAAQgAAEITJlANPE45eGP2hwablRylIMABCAAAQhAoBIC0TQcBuDwsN4i6fETvgX4H5IeKekYSafldOlz6TZi9+etKY/PJ/yf4UMonAMDsDAqMkIAAhCAAASmQyCaeJzOqCtpBQ1XCUYqgQAEIAABCEBgFALRNFw0A3D7UaAWKHNCgTx5Wc6QtElalbeUpAdyMvrW31+l17yi7wMl2ix8OUdPnb4E5QUl2hmWFQNwGCFehwAEIAABCEyZQDTxmDN8NFy5eYGGK8eL3BCAAAQgAIHGEYim4aIZgL7hd1QzLG8yuL6Fx5gpB0vaP5XfUNK5OXXtJ+mQ9NoWA1by9Ss+6pgRj2MElqIQgAAEIACBJhCIJh5zmKHhyk0mNFw5XuSGAAQgAAEINI5ANA0X0QCsOqg21xYao9L1M6bfEZL26FPXIyRdks7vu03ScpLuH6PNfkU5A7BioFQHAQhAAAIQaAKBaOJxgAFYNU40XHGi7OIozoqcEIAABCAAgakQiKbhohmAvgV3SUmHSVpP0h8k/bek8yTdmCK0fHptZ0lPk3S+pL0k3T4ggpePGd3uNmBv/91U0tk99e0j6dD0uwMlfbDndW/T/Xn63bGSdh2hPxiAI0CjCARmncCnf3JFbQje8RL/iSZBAALjEogmHnPGg4bLDzQabtw3AeUhAAEIQAACDSQQTcNFMwAXkWSzzavuvJ3W5+g9mBNnr+qz0fZeSeckYy7vfL5xp8raks6StJikOyV5W7ANPf+8o6TdUgP+pr2upDswAMdFTnkIQKAKAhiAVVCkDgjUSyCaeMyhgYbDAKz3jULrEIAABCAAgWAEomm4aAbg2yV9StK3JW1XMHYnSfp/kt4t6dMFy4ySbRtJX00rFPuVt/m3laQ/9nmRFYCjEKcMBCAwNgEMwLERUgEEaicQTTzmAEHDYQDW/l6hAxCAAAQgAIFIBKJpuGgGoLfzPlfS1pJOLRi4l0s6WdKFaWtwwWIjZVtN0t7J6PNZK/clw+/EtG357pxaMQBHwk0hCEBgXAIYgOMSpDwE6icQTTzmEEHDYQDW/2ahBxCAAAQgAIFABKJpuGgG4K1phd06kn5dMG7enmvz7++SHlewDNn6E+AAaWYGBFpGoE4DsC6UnD1YF3nanRSBaOIxZ5xouElNgGL1ouGKcSIXBCAAAQhAYGoEomm4aAagL/JYQtIOkry1t0jyVuET0tl8vkCENDoBxOPo7CgJgZAEMABDhoVOQaAUgWjiMafzaLhSUa08MxqucqRUCAEIQAACEBiPQDQNF80A9G2/Xv3nCzd82+6w5P770pDnT2kL8LD+NP11xGPTI0j/IdBDAAOQKQGB5hOIJh5ziKLh6p1qaLh6+dM6BCAAAQhAYA6BaBoumgH4Nkn/JenhdBHIHpL+mjOPlpb0xXRZiPO/Q9JnmXNjEUA8joWPwhCIRwADMF5M6BEEyhKIJh5z+o+GKxvYavOj4arlSW0QgAAEIACBsQlE03DRDMCFJJ0paYNkAvpSDV/w4YOlb0q/Wz5d9rFl2i7sMfips1cBPjh2hGa7AsTjbMef0beQAAZgC4PKkGaOQDTxmBMANFy9MxMNVy9/WocABCAAAQjMIRBNw0UzAA3M5/j5TL+XJnpe3dcvdfv+E0nbp0tAmHLjEUA8jseP0hAIRwADMFxI6BAEShOIJh4HDAANVzq6lRVAw1WGkoogAAEIQAAC1RCIpuEiGoBd0q+W9GZJG0t6ZA/++9NKwcNLXBZSTQTbXQvisd3xZXQzSAADcAaDzpBbRyCaeCwAGA1XAFLFWdBwFQOlOghAAAIQgMC4BKJpuMgGYJe1zb+nS/KZf063Srpc0j/GDQbl5xBAPDIpINAyAhiALQsow5lJAtHEY4kgoOFKwBozKxpuTIAUhwAEIAABCFRNIJqGa4IBWHUMqC+fAOKR2QGBlhHAAGxZQBnOTBKIJh5nMgjxB42Gix8jeggBCEAAAjNGIJqGwwCcsQk4ZLiIR+YDBFpGAAOwZQFlODNJIJp4nMkgxB80Gi5+jOghBCAAAQjMGIFoGi6yAbiEpFdK2kjSCpIWl7S7pGszc2ZZSY9J24Gvm7G5NInhIh4nQZU6IVAjAQzAGuHTNAQqIhBNPBYYFhquAKSKs6DhKgZKdRCAAAQgAIFxCUTTcFENwDdK+pikpRJw99O3AT9T0u8yQdhZ0jGS7pW0sqTbxg3QjJdHPM74BGD47SOAAdi+mDKi2SMQTTwOiQAarp4pioarhzutQgACEIAABHIJRNNwEQ3A/5R0kCT37QFJv5f0rzkG4EKSvPLPKwF3k3Q0c28sAojHsfBRGALxCGAAxosJPYJAWQLRxOOA/qPhyga3uvxouOpYUhMEIAABCECgEgLRNFw0A/DZki5KpE+S9BZJt0h6KMcAdNbDJO0p6QRJO1YSpdmtBPE4u7Fn5C0lgAHY0sAyrJkiEE085sBHw9U7K9Fw9fKndQhAAAIQgMAcAtE0XDQD0Cv4Xi/pXEnPS6afIQ4yAF8r6WtppeBazLmxCCAex8JHYQjEI4ABGC8m9AgCZQlEE485/UfDlQ1stfnRcNXypDYIQAACEIDA2ASiabhoBuAfJT1Jks/2s6nXTYMMQF8ScpakOyQ9duwIzXYFiMfZjj+jbyEBDMAWBpUhzRyBaOIxJwBouHpnJhquXv60DgEIQAACEJhDIJqGi2YA3i1pUUnrSrq4oAHoLSfOe38qy7QbnQDicXR2lIRASAIYgCHDQqcgUIpANPGY03k0XKmoVp4ZDVc5UiqEAAQgAAEIjEcgmoaLZgD6Ft/HSHqRpNMLGoAvkfRjSTdLWn688Mx8acTjzE8BALSNAAZg2yLKeGaRQDTxmBMDNFy9kxMNVy9/WocABCAAAQjMIRBNw0UzAH8ryef47S7pSwUNwEMk7SvpV5I2Zs6NRQDxOBY+CkMgHgEMwHgxoUcQKEsgmnjM6T8armxgq82PhquWJ7VBAAIQgAAExiYQTcNFMwA/I+mtki6QtH4BA3AFSZdKWkrShyQdOHaEZrsCxONsx5/Rt5AABmALg8qQZo5ANPGYEwA0XL0zEw1XL39ahwAEIAABCMwhEE3DRTMAnybpEkkLSdpf0qGJYL9LQHxZyLcl+QzAeyQ9WdKNzLmxCCAex8JHYQjEI4ABGC8m9AgCZQlEE485/UfDlQ1stfnRcNXypDYIQAACEIDA2ASiabhoBqABv1fSQZIelnSmpG9J+q/0s1+7T9LzJW0laZEUkb0kHT52dKgA8cgcgEDLCGAAtiygDGcmCUQTjwOCgIarb4ai4epjT8sQgAAEIACBvgSiabiIBqDBvU/S+9NKQBuB/ZL77pWBFpsfY75VQgDxWAlGKoFAHAIYgHFiQU8gMCqBaOJxyDjQcKMGerxyaLjx+FEaAhCAAAQgUDmBaBouqgFo8N7a+x5JW0p6bE8k7k43/x4s6cLKozS7FSIeZzf2jLylBDAAWxpYhjVTBKKJxwLw0XAFIFWcBQ1XMVCqgwAEIAABCIxLIJqGi2wAdlm7j0+VtFxaEfhXSZdLun/cYFB+DgHEI5MCAi0jgAHYsoAynJkkEE08lggCGq4ErDGzouHGBEhxCEAAAhCAQNUEomm4aAagTT4nX+pxR9XwqW8oAcTjUERkgECzCGAANite9BYC/QhEE485UULD1Tt90XD18qd1CEAAAhCAwBwC0TRcNAOwe9vv2yV9jvkzdQKIx6kjp0EITJYABuBk+VI7BKZBIJp4zBkzGm4akyG/DTRcvfxpHQIQgAAEIIABWHIO3CXpUZI2knReybJkH58A4nF8htQAgVAEMABDhYPOQGAkAg0xANFwI0W3skJouMpQUhEEIAABCECgGgLRNFy0FYB/kPRkSc+XdE41yKmlBAHEYwlYZIVAEwhgADYhSvQRAoMJRBOPOb1Fw9U7kdFw9fKndQhAAAIQgMAcAtE0XDQD8HBJu0l6t6RPM3+mTgDxOHXkNAiByRLAAJwsX2qHwDQIRBOPOWNGw01jMuS3gYarlz+tQwACEIAABDAAS86BNSVdKOk2SWtLurFkebKPRwDxOB4/SkMgHAEMwHAhoUMQKE2gIQYgGq50ZCstgIarFCeVQQACEIAABMYnEE3DRVsBaMLbSTo2mX9eCfg9SQ+Oj54aChBAPBaARBYINIkABmCTokVfIdCfQDTxOCBOaLj6JjEarj72tAwBCEAAAhDoSyCahotmAJ6SqK0uyf8elnS3pMsk3TrECHTerZh3YxFAPI6Fj8IQiEcAAzBeTOgRBMoSiCYec/qPhisb2Grzo+Gq5UltEIAABCAAgbEJRNNw0QzAh5LpZ9C9fbPBl5ec168vNHaEZrsCxONsx5/Rt5AABmALg8qQZo5ANPGYEwA0XL0zEw1XL39ahwAEIAABCMwhEE3DRTMAffPvIKNv2JTaaFgGXh9IAPHIBIFAywhgALYsoAxnJglEE485QUDD1Ts70XD18qd1CEAAAhCAAAYgc6BRBBCPjQoXnYXAcAIYgMMZkQMC0Qk0xACMjrHt/UPDtT3CjA8CEIAABBpHIJqGi7YCsHEBbVmHEY8tCyjDgQAGIHMAAs0nEE08Np9oK0eAhmtlWBkUBCAAAQg0mUA0DYcB2OTZVH3fEY/VM6VGCNRKAAOwVvw0DoFKCEQTj5UMikqqJoCGq5oo9UEAAhCAAATGJBBNw9VpAD4hsbxuyO2+YyKneAkCiMcSsMgKgSYQwABsQpToIwQGE4gmHiWh4eJNWjRcvJjQIwhAAAIQmHEC0TRcnQagb4vzv2dJ+l2febG4pHXT78+Y8XkzreEjHqdFmnYgMCUCGIBTAk0zEJgggWjiMek3NNwEYz5C1Wi4EaBRBAIQgAAEIDBJAtE0XN0GoG/8fWaOAfgMSb9NInPhSQaFuucTQDwyGSDQMgIYgC0LKMOZSQLRxGPSZmi4WLMRDRcrHvQGAhCAAAQgoGgargkGoAXmQsydqRBAPE4FM41AYHoEMACnx5qWIDApAtHEYwkDEA03qUkxt1403PRY0xIEIAABCECgEIFoGg4DsFDYZiYT4nFmQs1Ap01gFo24aTOO0N47XvK0CN2gDy0jEE08YgCGnGBouJBhoVMQgAAEIDDLBKJpOAzAWZ6NPD0m+hCYGgEMwKmhrrUhDMBa8be28WjiEQMw5FTDAAwZFjoFAQhAAAKzTCCahsMAnOXZiAFI9CEwNQIYgFNDXWtDGIC14m9t49HEIwZgyKmGARgyLHQKAhCAAARmmUA0DYcBOMuzEQOQ6ENgagQwAKeGutaGMABrxd/axqOJRwzAkFMNAzBkWOgUBCAAAQjMMoFoGg4DcJZnIwYg0YfA1AhgAE4Nda0NYQDWir+1jUcTjxiAIacaBmDIsNApCEAAAhCYZQLRNFwEA/A/JP1fn0nxJEnHSPINci+QVKSvZ8zy5Kpg7IjHCiBSBQT6EcAAnI15gQE4G3Ge9iijiceMAYiGm/ZkyG8PDRcnFvQEAhCAAAQg0CEQTcMVMdUmFbqHkrlXVf02CheuqrIZrQfxOKOBZ9iTJ4ABOHnGEVrAAIwQhfb1IZp4zBiAVcFGw41PEg03PkNqgAAEIAABCFRKIJqGq9sArBKuxeNCVVY4g3UhHmcw6Ax5OgQwAKfDue5WMADrjkA7248mHpMBWCVsNNz4NNFw4zOkBghAAAIQgEClBKJpuDoNwA9USnZeZQdOoM5ZqhLxOEvRZqxTJYABOFXctTWGAVgb+lY3HE08SkLDxZtxaLh4MaFHEIAABCAw4wSiabg6DcAZnwohh494DBkWOtUGAhiAbYji8DFgAA5nRI7yBKKJx/IjoMQUCKDhpgCZJiAAAQhAAAJlCETTcBiAZaLX/ryIx/bHmBHWRAADsCbwU24WA3DKwGekuWjicUawN22YaLimRYz+QgACEIBA6wlE03AYgK2fcqUGiHgshYvMEChOAAOwOKsm58QAbHL04vY9mniMS2qme4aGm+nwM3gIQAACEIhIIJqGwwCMOEvq6xPisT72tNxyAhiALQ9wGh4G4GzEedqjjCYepz1+2itEAA1XCBOZIAABCEAAAtMjEE3DYQBOL/ZNaAnx2IQo0cdGEsAAbGTYSncaA7A0MgoUIBBNPBboMlmmTwANN33mtAgBCEAAAhAYSCCahsMAZMJmCSAemQ8QmBABDMAJgQ1WLQZgsIC0pDvRxGNLsLZtGGi4tkWU8UAAAhCAQOMJRNNwGICNn1KVDgDxWClOKoPAPwlgAM7GbMAAnI04T3uU0cTjtMdPe4UIoOEKYSITBCAAAQhAYHoEomk4DMDpxb4JLSEemxAl+thIAhiAjQxb6U5jAJZGRoECBKKJxwJdJsv0CaDhps+cFiEAAQhAAAIDCUTTcBiATNgsAcQj8wECEyKAATghsMGqxQAMFpCWdCeaeGwJ1rYNAw3XtogyHghAAAIQaDyBaBoOA7DxU6rSASAeK8VJZRD4JwEMwNmYDRiAsxHnaY8ymnic9vhprxABNFwhTGSCAAQgAAEITI9ANA2HATi92DehJcRjE6JEHxtJAAOwkWEr3WkMwNLIKFCAQDTxWKDLZJk+ATTc9JnTIgQgAAEIQGAggWgaDgOQCZslgHhkPkBgQgQwACcENli1GIDBAtKS7kQTjy3B2rZhoOHaFlHGAwEIQAACjScQTcNhADZ+SlU6AMRjpTipDAL/JIABOBuzAQNwNuI87VFGE4/THj/tFSKAhiuEiUwQgAAEIACB6RGIpuHqMgB3nhDy/55QvbNSLeJxViLNOKdOAANw6shraRADsBbsrW80mHhEw8WccWi4mHGhVxCAAAQgMMMEgmk41WUAPiTp4YrngetbuOI6Z606xOOsRZzxTo0ABuDUUNfaEAZgrfhb23gw8YiGiznT0HAx40KvIAABCEBghgkE03C1GoBVTwMbgAtVXemM1Yd4nLGAM9zpEcAAnB7rOlvCAKyTfnvbDiYebQBWndBw4xNFw43PkBogAAEIQAAClRIIpuFqMwBXG0D1cZKOkLSepEskHSvpPEk3pjLLp9d2kfRMSedL2l3SrZKuqTRas1cZ4nH2Ys6Ip0QAA3BKoGtuBgOw5gC0tPlg4hENF3OeoeFqjEuVn/F8jtQYSJqGAAQgUDGBYBquNgMwD+sjJf1K0tqSPiDpIwO2Cnv78n9KOkjShZKeL+m+iuM1a9UhHmct4ox3agSq/HIwtU7TUGkCfHErjYwCBQhEE485XUbDFYjlBLOg4UrCjfq5zOdIyUCSHQIQgEBgAtE0XF1nAOaF6F2SPi7pBEk7Fozj8ZJeI2m/VLZgMbL1IYB4ZFpAYEIEon7RmNBwZ7ZavrjNbOgnOvBo4jFnsGi4ic6CoZWj4YYiWjBD1M9lPkdKBpLsEIAABAITiKbhohmAXsn3HElbSfpRwThuIelUSRdLWqdgGbL1J4B4ZGZAYEIEon7RmNBwZ7ZavrjNbOgnOvBo4jFnsGi4ic6CoZWj4YYiwgAsiYjsEIAABCAwJoFoGi6aAXibpMdIWjcZekVwe7uwReftkpYqUoA8uQQQj0wOCEyIAAbghMAGqxYDMFhAWtKdaOIxBysart75hoYryT/q5zKfIyUDSXYIQAACgQlE03DRDMC/S3q0pNembcBFQrm9JG8DvkPSY4sUIA8GIHMAAtMmEPWLxrQ5tL09vri1PcL1jC+aeMyhgIarZ3p0W8UALMk/6ucynyMlA0l2CEAAAoEJRNNw0QzAc9INv+dK2ljSQ0Ni+QhJZ0naIN0UvGHg2Deha4jHJkSJPjaSQNQvGo2EGbjTfHELHJwGdy2aeMxBiYard46h4Uryj/q5zOdIyUCSHQIQgEBgAtE0XDQDcE9Jh6Wbf0+WtJukG3LiubykIyS9IuV/q6QvBI59E7qGeGxClOhjIwlE/aLRSJiBO80Xt8DBaXDXoonHHJRouHrnGBquJP+on8t8jpQMJNkhAAEIBCYQTcNFMwC9ou/0tPrvYUn/kHSapPMl3ZSMPht/60l6qaRFJXkMZ0p6QYEVg4GnRoiuIR5DhIFOtJFA1C8abWRd55j44lYn/fa2HU085pBGw9U7BdFwJflH/Vzmc6RkIMkOAQhAIDCBaBoumgHo0C0h6WtpZZ9/thHYL3X7/gNJr5N0Z+C4N6VriMemRIp+No5A1C8ajQMZvMN8cQseoIZ2L5p4HIARDVffHEPDlWQf9XOZz5GSgSQ7BCAAgcAEomm4iAZgN3xbSXpzWtm3eE9M70krBQ+X9MPA8W5a1xCPTYsY/W0MgahfNBoDsCFf8NGoAAAgAElEQVQd5YtbQwLVsG5GE48F8KHhCkCqOAsariTQqJ/LfI6UDCTZIQABCAQmEE3DRTYAu2H0lpKnSFo6/eJWSVdKejBwnJvaNcRjUyNHv8MTiPpFIzy4hnWQL24NC1hDuhtNPJbAhoYrAWvMrGi4kgCjfi7zOVIykGSHAAQgEJhANA3XBAMwcDhb1zXEY+tCyoCiEIj6RSMKn7b0gy9ubYlkrHFEE4+x6NCbRAANV3IqRP1c5nOkZCDJDgEIQCAwgWgaDgMw8GSpoWuIxxqg0+RsEIj6RWM26E9vlHxxmx7rWWopmnicJfYNGisarmSwon4u8zlSMpBkhwAEIBCYQDQNF9kAfKyk7SRtJGkFST4H8PWSrsnEdyVJS0m6V9JVU4j7apLeJsln26yabin2duQTJH1e0t1j9MHje5mkl0haV9Lqkh4t6XZJV0j6saQvSrphjDaGFUU8DiPE6xAYkUDULxojDodiOQT44sbUmASBaOKxwBjRcGi4AtOk3ixRP5f5HKl3XtA6BCAAgSoJRNNwUQ3AvSR9JBlg5u9++jbgZ0r6XSYgO0n6ajIAbV79rcpg9dS1TWpryZw2bNLZGPzjCH14lqSzMuPNq8Jm4G6SvjlCG0WKYAAWoUQeCIxAIOoXjRGGQpEBBPjixvSYBIFo4nHIGNFw/QGh4Sbx5hijzrZ/LvN5NMbkoCgEIACBighE03ARDcADJR2QTL9/SPptWhHXzwD04dJ/lrS8pD0kHVVRnHqrWTsZdItJulPSIZJ+Lsk/7yjpTamATUCv3rujZD82lvTLVMZGoG82vkDSXyUtK+lVqQ2P15ef2Iw8tWQbRbJjABahRB4IjECg7V80RkDSyiJ84WplWGsfVDTxOAAIGg4NV/v7pWgH2v65zOdR0ZlAPghAAAKTIxBNw0UzANeRdF7C/zVJb5X0d0kP5awAdNbPpHwnSdp+QqE7Q9Imkh6QtKmks3va2UfSoel3Fr8fLNmP50naW5LLZlc4ZqvZVtJ3kjHqbcdPTUxKNjUwOwZglTSpCwIZAm3/okGw5xHgCxczYRIEoonHnDGi4dBwk5j+E6uz7Z/LfB5NbOpQMQQgAIHCBKJpuGgG4DGSdpH0K0leFddNgwxAr8D7uqTLJa1ZOBLFM64v6dyU/Yi00rC3tFfmXZLav03ScpLuL95E4Zw2OV+dcltoX1S4ZLGMGIDFOJELAqUJtP2LRmkgLS3AF66WBrbmYUUTjzk40HCD5wkarub3UW/zbf9c5vMo2ISjOxCAwEwSiKbhohmAXtn2REmvk3R8QQNww2QYemtu3vl840y2gyXtnypwW10zsLfO/dLWYP9+C0mnjdNoTtm3SDosvebVjidW3AYGYMVAqQ4CXQJt/6JBpOcR4AsXM2ESBKKJx5wxouEGBx8NN4k3xxh1tv1zmc+jMSYHRSEAAQhURCCahotmAPoW3UXTOXoXFzQAn5NWwnnFnctWnbrbf+9KNw57G3C/5NuKvXLR6UOSPlB1RyS9U9InU71eCfjtitvAAKwYKNVBoEug7V80iPQ8AnzhYiZMgkA08ZgzRjTc4OCj4Sbx5hijzrZ/LvN5NMbkoCgEIACBighE03DRDEBvn32MpBenSza62AdtAfZqO1+IcXO6DKSiUM2vxvUuI+k3kmw25qXHZW4h9sq8SZxH+D1Jr0gdWEvSZRUPFgOwYqBUBwEMwNmaA3zhmq14T2u00cRjzrjRcIMnBBpuWm+Ygu1gABYERTYIQAACEBiZQDQNF80A/F9Jz5D0ZklHZigPMgA/JsmXcJyZLugYOTh9Cj5K0j3p9ydL2npI5d6GvISkcyR5RWCV6dmSLpS0ULoZ+VkjVG6Db1BaQdL5znDttddqlVWGZR+hBxSBwIwSaPsXjRkN65xhYwAyEyZBIJp4zBkjGi4/+Gi4it4YfJYWB8nnUXFW5IQABCAwKQLRNFw0A/DT6TbcX0t6biYIeQbgyunyDZ/95y23H644cMtKuinV+U1JvnBkULoxXQDiC0GeWWFfvLXZBue6qU6vAvzBCPU/XLQMBmBRUuSDQDECfGkpxqnpufjC1fQIxux/NPGYQwkN1x8MGq7CtxWfpcVh8nlUnBU5IQABCEyKQDQNF80AfIqk30laWNIHJR2UAtHPAHy6JN+o5hWDPp/vyWkbcJWxW1XSn1KFx0naeUjlzusyPgh79Qo7cpSkN6b6jpW064h1YwCOCI5iEBiXAF9axiXYjPJ84WpGnJrWy2jiMYcfGq4/GDRchW84PkuLw+TzqDgrckIAAhCYFIFoGi6aAWju75Z0qCSbVd6O6osuPpp+9uUavuzj+ZJeKukRKVC7STp6AkGLsALQNxD7JmIn89g8GZ6jDHfYnl62AI9ClTIQKECALy0FILUgC1+4WhDEgEOIJh4HIELDLQgHDVfx+4nP0uJA+TwqzoqcEIAABCZFIJqGi2gAmr3P9PN23kWS8dcvHu77g8kw/MyEAlb3GYC7S/piGtvvJW0i6ZYJjdXVcgnIBOFS9WwT4EvLbMSfL1yzEedpjzKaeBwyfjTcPEBouAm8UfgsLQ6Vz6PirMgJAQhAYFIEomm4qAag+a+ZzD1fvOGVeNn0d0mnSDoknQE4qXi5Xhtuj6/hFuDXSvpqWuV4jaSNJf15kgPFAJwwXaqfaQJ8aZmN8POFazbiPO1RRhOPBcaPhkPDFZgm5bPwWVqeWRUl+GyrgiJ1QAACs0ggmoaLbABm58cT0uUavgH3r5KukuRzAaeRzkgr73zO4FKSHshp1Lf+/iq95q3KvpRk1ORLPr6VzkL8S2rf5wpOOrECcNKEqX9mCfClZTZCz5ek2YjztEcZTTyWHD8abt7Z0JNOM6Hh+Cyd9DTqXz+fbfVwp1UIQKD5BKJpuKYYgHVG3ufv+QwXpw0lnZvTmf3SikS/vIWk00bs9IsknSzJt8bZ7NxM0qUj1lW22EyIx7JQyA+BKgj8f/bOBO6+qd7/n4sGlAYiIkoDGmVIA6qrlOFe/0ZNNBlKN7dJ1L0XDZS66pYhKZSKNA9SoqIySwMRmgwRkilk/L8+j7W1nd/ZZ+99zt5nr73Xe71evxfPc9Zew/u7zrM/+7PXwENLExTjL4OHpPhj1McWxiYee8QQDdejYFVpKvfSKpSaz8O9rXmmlAgBCKRBIDYNhwFYPu7Wz5l+B0naccwlPozk7LBs+ZowW9GHldRNTw/G4dKSvMzZZuCZdQuZIT8G4AzwuDR+Ajw4xB8jWjgdAR7OpuPWl6tiE4994SYJDdejYFVpKvfxKpSaz8M9pnmmlAgBCKRBIDYNhwFYbdxly4C9/HcjSSePXOYNr31ysdOekvYY+fxZkn4UfvdZSa8ZU+2TQx4vM/ZyY88i/Fm15jWWCwOwMZQUFCMBHhxijAptaoIAD2dNUIy3jNjEY7ykxrYMDdezgE1qLvfxboLJPaYb7tQKAQj0n0BsGi5WA3A5Sa8Me989UtL9JXn/v0npTkmrtzRE1g5m3JKSbpDkJSU29Pzz1pK2D/WeL2ldSdfXNADdbu8fuHy47q2SjivpyxWS/K/JhAHYJE3Kio4ADw7RhYQGNUSAh7OGQEZaTGzisQQTGg4N19o3ift4a2gnFsw9phvu1AoBCPSfQGwaLkYD0KffHhhMP0e8ahttAJaZhLOMoC3DqbzLFBRi829zSReO+bxsBqBnBB5as3HjZhrWLGKR7BiAsxLk+qgJ8OAQdXho3AwEeDibAV4PLo1NPE5AhoarNp7QcNU4LZKL+/iU4Ga8jHvMjAC5HAIQSJZAbBquqrk2r4A9R9IPcqbfnyT9SpL31aty6u9rW27oqpJ2DkafzbJbguH3ZUn7SbqxoH4MwJYDQ/EQqEKAB4cqlMjTRwI8nPUxatXbHJt4LGg5Gq56SDEAq7O6R07u41OCm/Ey7jEzAuRyCEAgWQKxabjYDECfnLtJMPy8BPiYZEdKNx1nBmA33Kl1TgR4cJgTaKqZOwEezuaOfK4VxiYeCzqPhpvrqFiksiQ0HPfxbgdZE7Vzv2qCImVAAAJ9IRCbhovNAPybJC+x/U9Jn+hLUAfUziTE44DiRVdqEuDBoSYwsveGAA9UvQnVVA2NTTwWdAINN1V0G7soCQ3Hfbyx8dJZQdyvOkNPxRCAQAcEYtNwsRmA10q6n6T1JP28g/ikXmUS4jH1IKfcfx4cUo7+sPvOA9Ww4xubeCygjYbrdhgmoeG4j3c7yJqonftVExQpAwIQ6AuB2DRcbAagTb8nSfKeeT/pS1AH1M4kxOOA4kVXahLgwaEmMLL3hgAPVL0J1VQNjU08FnQCDTdVdBu7KAkNx328sfHSWUHcrzpDT8UQgEAHBGLTcLEZgLtI+qCkvST9VwfxSb3KJMRj6kFOuf88OKQc/WH3nQeqYcc3NvFYQBsN1+0wTELDcR/vdpA1UTv3qyYoUgYEINAXArFpuNgMQC//PUXSamEW4Bl9CexA2pmEeBxIrOjGFAR4cJgCGpf0ggAPVL0I09SNjE08FnQEDTd1hBu5MAkNx328kbHSaSHcrzrFT+UQgMCcCcSm4WIzAB2Oh0v6mqS1JH1U0pcknS/p5jnHKsXqkhCPKQaWPt9FgAcHRsJQCfBANdTI3tWv2MTjBNpouO6GYhIajvt4dwOsqZq5XzVFknIgAIE+EIhNw8VoADqOj5P0Q0nL1QjqnZKWqJGfrIsSSEI8Evh0CfDgkG7sh95zHqiGHeHYxGMJbTRcN8MxCQ3HfbybwdVkrdyvmqRJWRCAQOwEYtNwMRqAO0v6iKTFJNVpnw3AxWMfAJG3LwnxGHkMaF6LBHhwaBEuRXdKgAeqTvG3Xnls4nFCh9FwrY+GwgqS0HDcx7sbYE3VzP2qKZKUAwEI9IFAbBqujsE2D76bSfpOqOgOST+V9EtJ10jyz2Vpz7IMfD6RQBLikTGQLgEeHNKN/dB7zgPVsCMcm3gsoI2G63YYJqHhuI93O8iaqJ37VRMUKQMCEOgLgdg0XGwG4I8kbSzpUkkWkr/uS2AH0s4kxONAYkU3piDAg8MU0LikFwR4oOpFmKZuZGzisaAjaLipI9zIhUloOO7jjYyVTgvhftUpfiqHAATmTCA2DRebAfhXSQ+U9AZJh845NlQnJSEeCXS6BHhwSDf2Q+85D1TDjnBs4rGANhqu22GYhIbjPt7tIGuidu5XTVCkDAhAoC8EYtNwsRmAXup7f0nrSjqrL0EdUDuTEI8DihddqUmAB4eawMjeGwI8UPUmVFM1NDbxWNAJNNxU0W3soiQ0HPfxxsZLZwVxv+oMPRVDAAIdEIhNw8VmAJ4u6SmSnhtOAe4gRElXmYR4TDrCiXeeB4fEB8CAu88D1YCDKyk28VhAGw3X7TBMQsNxH+92kDVRO/erJihSBgQg0BcCsWm42AzAt4UTgPeT9Ja+BHVA7UxCPA4oXnSlJgEeHGoCI3tvCPBA1ZtQTdXQ2MRjQSfQcFNFt7GLktBw3McbGy+dFcT9qjP0VAwBCHRAIDYNF5sBeC9JP5G0tqQXS/p2BzFKucokxGPKAU697zw4pD4Chtt/HqiGG1v3LDbxWEAbDdftMExCw3Ef73aQNVE796smKFIGBCDQFwKxabjYDMCHS3qApE9JWk/Sl8K/8yXdWCHIF1XIQ5ZiAkmIRwZAugR4cEg39kPvOQ9Uw45wbOKxgDYartthmISG4z7e7SBronbuV01QpAwIQKAvBGLTcLEZgHdIujME023L/r9KfJ13iSoZyVNIIAnxSPzTJcCDQ7qxH3rPeaAadoRjE48FtNFw3Q7DJDQc9/FuB1kTtXO/aoIiZUAAAn0hEJuGi9EAnDaWNgAXn/ZirlsgkIR4JNbpEuDBId3YD73nPFANO8KxiccJBuC0gUDDTUvun9cloeG4j88+ULougftV1xGgfghAYJ4EYtNwsRmA284YjM/OeH3qlychHlMPcsr958Eh5egPu+88UA07vrGJxwLaaLhuh2ESGo77eLeDrInauV81QZEyIACBvhCITcPFZgD2JY5DbWcS4nGowaNf5QR4cChnRI5+EuCBqp9xq9rq2MRj1XaTb64EktBw3MfnOqZaqYz7VStYKRQCEIiUQGwaDgMw0oHSUbOSEI8dsaXaCAjw4BBBEGhCKwR4oGoFazSFxiYeowFDQ/IEktBw3Mf7P+i5X/U/hvQAAhCoTiA2DRebAegNpP3v3ZL2qY6VnA0RSEI8NsSKYnpIgAeHHgaNJlciwANVJUy9zRSbeCwAiYbrdoQloeG4j3c7yGKrnXtfbBGhPRCAwCiB2DRcbAbgzZLuJemZkk5m+MydQBLice5UqTAaAjw4RBMKGtIwAR6CGgYaWXGxiccCPGi4bsdNEhqO+3i3gyy22rn3xRYR2gMBCGAA1hsDv5e0qqQNJJ1e71JyN0AgCfHYACeK6CkBHhx6GjiaXUqAh6BSRL3O0BMDEA3X7ShLQsNxH+92kMVWO/e+2CJCeyAAAQzAemPgMEmvlrSTpE/Wu5TcDRBIQjw2wIkiekqAB4eeBo5mlxLgIagUUa8z9MQARMN1O8qS0HDcx7sdZLHVzr0vtojQHghAAAOw3hhYJyz9vUjSUyRdV+9ycs9IIAnxOCMjLu8xAR4cehw8mj6RAA9Bwx4gPTEA0XDdDsMkNBz38W4HWWy1c++LLSK0BwIQwACsPwZ2kLSfpLPDTMCT6hfBFVMSSEI8TsmGywZAgAeHAQSRLowlwEPQsAdGTwxABwEN191QTELDcR/vboDFWDP3vhijQpsgAIE8gdg0XGyHgBwSYK0vaS1Jd0q6WNKvJP1N0u0ThpPzvp7hNhOBJMTjTIS4uNcEeHDodfho/AQCPAQNe3jEJh4LaKPhuh2GSWg47uPdDrLYaufeF1tEaA8EIDBKIDYNF5sBeEcw/TJuWfts7k1Kzuc8izPkZiKQhHiciRAX95oADw69Dh+NxwBMdgzEJh4LAoGG63aEJqHhuI93O8hiqx0DMLaI0B4IQAADsN4Y+OOIAVjvaukRdS8g/z0IJCEeiXm6BHhwSDf2Q+85D0HDjnBPDEA0XLfDMAkNx32820EWW+3c+2KLCO2BAAQwABkDfSKQhHjsU0Boa7MEeHBolielxUOAh6B4YtFGS3piALbRdcqsTiAJDcd9vPqASCEn974UokwfIdBvArFpuNiWAPc7uv1vfRLisf9hogfTEuDBYVpyXBc7AR6CYo/QbO2LTTzO1huubolAEhqO+3hLo6enxXLv62ngaDYEEiIQm4bDAExo8FXoahLisQIHsgyUAA8OAw0s3RIPQcMeBLGJx2HT7m3vktBw3Md7Oz6jbzj30ehDRAMh0EsCsWm4vhiAS0h6UIi4TwO+rZfRj7/RSYjH+MNAC9siwINDW2Qpt2sCPLh0HYF2649NPNbsLRquJrApsyeh4biPTzk6uKyUAPfRUkRkgAAEpiAQm4aL2QBcU9KbJG0i6dGS8icCXyDpB5I+Kek3U8SBS8YTSEI8Evx0CfDgkG7sh95zHlyGHeHYxGMF2mi4CpAazpKEhuM+3vCoobi7CXAfZTBAAAJtEIhNw8VqAO4t6R2SFssZf6PxuFPSHZI+LOndbQQrwTKTEI8JxpUuBwI8ODAUhkqAB5ehRvaufsUmHktoo+G6GY5JaDju490MrhRq5T6aQpTpIwTmTyA2DRejAfiJMPMva9u5kk6VdHkI10MlrS9prfCzjcD9JO08/3AOrsYkxOPgokaHKhPgwaEyKjL2jAAPLj0LWM3mxiYeJzQfDVcztg1mT0LDcR9vcMRQ1D0IcB9lQEAAAm0QiE3DxWYAPkPSTyTZ1LPxt72kkwoC8bSwBPgJIf+GE/K2EcshlpmEeBxi4OhTNQI8OFTjRK7+EeDBpX8xq9Pi2MRjQdvRcHWC2nzeJDQc9/HmBw4l3kWA+ygjAQIQaINAbBouNgPwc5JeJen3ktaRdG1JEB4g6UxJj5D0BUnbtBG0hMpMQjwmFE+6OkKABweGxFAJ8OAy1Mje1a/YxGMBbTRct8MwCQ3HfbzbQTbk2rmPDjm69A0C3RGITcPFZgD+QdLDJe0g6dMVw7SdpIMk/SkYgRUvI9sYAkmIRyKfLgEeHNKN/dB7zoPLsCMcm3gsoI2G63YYJqHhuI93O8iGXDv30SFHl75BoDsCsWm42AzAmyTdO+zx55l9VZJnCp4u6WZJS1W5gDyFBJIQj8Q/XQI8OKQb+6H3nAeXYUc4NvFYQBsN1+0wTELDcR/vdpANuXbuo0OOLn2DQHcEYtNwsRmAf5O0jKRnSzqxYpg2kvTjsFz4QRWvIdt4AkmIR4KfLgEeHNKN/dB7zoPLsCMcm3gsoI2G63YYJqHhuI93O8iGXDv30SFHl75BoDsCsWm42AzAn0t6kqR9Jb2zYpg+LOntks4K+wZWvIxsYwgkIR6JfLoEeHBIN/b0vD0CPDS1xzYrOTbxWNBjNFz7Q2FSDUloOO7j3Q6yIdfOvWzI0aVvEOiOQGwaLjYD8P2S3i3pFkmbSzq+JFSeKXiMpHtJ2kvSf3cX2kHUnIR4HESket4JBHzPA0jzIZAjwENT+8MhNvFY0GM0XPtDobcGIPf9bgcHtZcT4F5WzogcEIBAfQKxabjYDMDlJF0o6f6Sbpf0KUmHSPqFpDsC7sUkPVnS6yT5ABCbfz4t+FGS/lo/JFyRI4AByHCYCwEeBOaCmUogMBcCPDS1jzk28VjQYzRc+0MBA7BbxtQ+YALcywYcXLoGgQ4JxKbhYjMAHZrnSfpWOAzkzhArzwi8WpJ/XjZ85o/cfn+2haTjOozrUKrGABxKJCPvBwZg5AGieRCoQYCHphqwpswam3ic0A003JQxbuCyqDUc9/0GIkwRrRLgXtYqXgqHQLIEYtNwMRqAHhye4efZf+uWjJQzwizAXyY7oprteNTisdmuUlqXBHgQ6JI+dUOgWQI8NDXLc1xpsYnHkh6j4dofEuNqiFrDcd/vZlBQa3UC3MuqsyInBCBQnUBsGi5WAzAjup6kTSQ9XtKDwy89E/DsMOPv9OroyVmBQNTisUL7ydITAjwI9CRQNBMCFQjw0FQB0oxZYhOPFbuDhqsIqqFsUWs47vsNRZlioifAPTH6ENFACMyVQGwaLnYDcK7BoTJFLR6Jz3AI8CAwnFjSEwjwsNP+GIhNPLbfY2qYgkDUGo77/hQR5ZJeEuCe2Muw0WgItEYgNg2HAdhaqHtZcNTisZdEafRYAjwIMDAgMBwCPOy0H8vYxGP7PaaGKQhEreG4708RUS7pJQHuib0MG42GQGsEYtNwGICthbqXBUctHntJlEZjADIGIDBwAjzstB/g2MRj+z2mhikIRK3hMACniCiX9JIA98Reho1GQ6A1ArFpOAzA1kLdy4KjFo+9JEqjMQAZAxAYOAEedtoPcGzisf0eU8MUBKLWcBiAU0SUS3pJgHtiL8NGoyHQGoHYNFyXBuDtDVO+U9ISDZeZWnFRi8fUgjHk/vIgMOTo0rfUCPCw037EYxOPktBw7Ye9bg1Razju+3XDSf6+EuCe2NfI0W4ItEMgNg3XpQF4R8OIbQAu3nCZqRUXtXhMLRhD7i8PAkOOLn1LjQAPO+1HPDbxKAkN137Y69YQtYbjvl83nOSHgMT9lVEAgf4TiE3DdWkAHjpjON32zSQtK8n/jwE4I1CJU4BnR0gJVQjwIFCFEnkg0A8CPKC0H6fYxKMkNFz7Ya9bAwZgXWLkh0DkBLi/Rh4gmgeBCgRi03BdGoAVcBVm2UrSnpIeH3K4HxdJWm2WQrkWA5AxMB8CGIDz4UwtEJgHAR5Q2qccm3icscdouBkBFlyOAdgOV0qFQGcEuL92hp6KIdAYgdg0XN8MQM/4s/H3lJzxd5mkvSQdLOmWxiKVZkFRi8c0QzLMXmMADjOu9CpNAjygtB/32MTjlD1Gw00JruJlUWs47vsVo0g2COQIcH9lOECg/wRi03B9MQCfG4y/p+aMvyskfUjSgZJu7v/QiKIHUYvHKAjRiEYI8CDQCEYKgUAUBHhAaT8MsYnHmj1Gw9UENmX2qDUc9/0po8plSRPg/pp0+On8QAjEpuFiNwA3lvQ+Sc/IGX9/lfRhSftJunEg4yKWbkQtHmOBRDtmJ8CDwOwMKQECsRDgAaX9SMQmHiv2GA1XEVRD2aLWcNz3G4oyxSRFgPtrUuGmswMlEJuGi9UAfLqk90p6ds74u0bSvpI+JumGgY6PrrsVtXjsGg71N0eAB4HmWFISBLomwANK+xGITTyW9BgN1/6QGFdD1BqO+343g4JaIZAR4F7NWIBANwRi03CxGYDrhhl/z8sZf9cH08/m37XdhC2ZWqMWj8lEIYGO8iCQQJDpYjIEeKhoP9SxiceCHqPh2h8Kk2qIWsNx3+92cFA7BLhXMwYg0A2B2DRcLAbgk8KMvy1yxt/fwzJfL/e9uptwJVdr1OIxuWgMuMM8CAw4uHQtOQI8VLQf8tjE40iP0XDtD4EqNUSt4bjvVwkheSDQHgHu1e2xpWQITCIQm4br2gB8XDjc4//ljL+bwsEePuDjSobTXAlELR7nSoLKWiXAg0CreCkcAnMlwENF+7hjE4+hx2i49kNfp4aoNRz3/TqhJC8EmifAvbp5ppQIgSoEYtNwXRqAR0h6iSS3wf/+IekgSR+UdHkVmORpnEDU4rHx3lJgZwR4EOgMPRVDoHECPFQ0jnSRAmMTj5LQcO2HvW4NUWs47vt1w0l+CDRLgHt1szwpDQJVCcSm4bo0AO/IQfNMv49LurgqyIJ8n5vx+tQvj1o8ph6cIfWfB4EhRZO+pE6Ah4r2R0Bs4lESGq79sNetIWoNx32/bjjJD4FmCXCvbpYnpUGgKoHYNFzXBuCdVcFVyOeylqiQjyzFBKIWjwRuOAR4EBhOLOkJBHioaH8MxCYegwGIhms/9HVqiFrDcd+vEznuLfQAACAASURBVEryQqB5Atyrm2dKiRCoQiA2Dde1AViFWdU8FqKLV81MvrEEohaPxGw4BHgQGE4s6QkEeKhofwzEJh5HZgA2AQANNzvFqDUc9/3ZA0wJEJiFAPfqWehxLQSmJxCbhuvSANx4eoyFV57QQpkpFRm1eEwpEEPvKw8CQ48w/UuJAA8V7Uc7NvEoCQ3Xftjr1hC1huO+Xzec5IdAswS4VzfLk9IgUJVAbBquSwOwKjPyzY9A1OJxfhioqW0CPAi0TZjyITA/AjxUtM86NvHYfo+pYQoCUWs47vtTRJRLINAgAe7VDcKkKAjUIBCbhsMArBG8BLJGLR4T4J9MF3kQSCbUdDQBAjxUtB/k2MRj+z2mhikIRK3huO9PEVEugUCkBLjvRxoYmhUlgdg0HAZglMOks0ZFLR47o0LFjRPgQaBxpBQIgc4I8CDQPvrYxGP7PaaGKQhEreG4708RUS6BQKQEuO9HGhiaFSWB2DQcBmCUw6SzRkUtHjujQsWNE+BBoHGkFAiBzgjwINA++tjEY/s9poYpCESt4bjvTxFRLoFApAS470caGJoVJYHYNBwGYJTDpLNGRS0eO6My0IoR4wMNLN2CwJwJ8CDQPvDYxGP7PaaGKQhEreHQHFNElEsgkAABNEQCQU68i7FpOAzAxAfkSPejFo+EqlkCiPFmeVIaBCAwXwIpPTTEJh7nG2lqq0ggag2H5qgYRbJBIDECKd3LEwst3Q0EYtNwGIAMzTyBqMUjoWqWAGK8WZ6UBgEIzJdASg8NsYnH+Uaa2ioSiFrDoTkqRpFsEEiMQEr38sRCS3cxABkDPSAQtXjsAb9eNREx3qtw0VgIQGCEQEoPDRiADP8KBKLWcGiOChEkCwQSJJDSvTzB8NJlSbFpOGYAMizzBKIWj4SqWQKI8WZ5UhoEIDBfAik9NMQmHucbaWqrSCBqDYfmqBhFskEAAlMRSEkTTAWIizojEJuGwwDsbChEWXHU4jFKYj1uFGK8x8Gj6RCAgFIS+7GJR4ZflASi1nBojijHDI2CwGAIpKQJBhO0RDoSm4bDAExk4FXsZtTisWIfyFaRAGK8IiiyQQACURJISezHJh6jHBA0KmoNh+ZggEIAAm0SSEkTtMmRspsnEJuGwwCsF+NVJb1F0uaSVpH0D0m/k3SUpP0l3VivuMLcL5C0vaT1JD1E0pWSTpf0KUnHNFTHuGKiFo8t9jvJohHjSYadTkNgMARSEvuxiceeDiI0XIeBQ3N0CJ+qIZAAgZQ0QQLhHFQXY9NwGIDVh9eWkj4vaZmCS84PxuCF1YtcJOdiweR7/YQyPi1pB0l3zFBP0aUYgC1AjbVIxHiskaFdEIBAFQIpif3YxGOV+ESWBw3XcUDQHB0HgOohAIHKBFLSF5WhkHFqArFpOAzAaqFcW9LPJC0p6QZJe0v6Ufh5a0nbhWJsAq4r6fpqxS6Sy+XuGn57lqR9wgzD1SXtIsntcHK+d09Zx6TLMABbgBprkYjxWCNDuyAAgSoEUhLosYnHKvGJKA8aLoJgoDkiCAJNgAAEKhFISV9UAkKmmQjEpuEwAKuF80RJG0q6TdJGkk4eueydwazzr/eUtEe1Yu+R6zGSzpG0hKQzQj035XIsJemEYDC6HWtKmmW24bgmYgBOEbi+XoIY72vkaDcEIGACKQn02MRjz0YgGi6CgKE5IggCTYAABCoRSElfVAJCppkIxKbhMADLw7m+pFNDtoMk7TjmEi/dPTuYctdIWl7SreVF3yPHAZLeGH7zNEmnjLl+g5z56Pw71ayjLDsGYBmhAX2OGB9QMOkKBBIkkJJAj0089mi4oeEiCRaaI5JA0AwIQKC3BFLSPb0N0piGx6bhMADLR9deknYL2WzAZWbg6JVeuuuluU6bSjq2vOi7czgOl0haSdJ5wUgsutyfP1bSpeEgkjtr1FOWFQOwjNCAPkeMDyiYdAUCCRJISQjHJh57NNzQcJEEC80RSSBoBgQg0FsCKeme3gYJA3AQocuWjvxd0gPDMuBxHfOsvZPCB++VtHuN3j8y7PXnS4pmGWbF+XOfEOzk6/5Qo56yrBiAZYRa+BxR3AJUioQABCDQIoF5i3AMwKmDiYabGl2zF6J1muVJaRCAAARmITBvHTNLW/t+bWwajhmA5SPqSknLSfqlpCdPyP4gSVeHz78s6aXlRd+dYwtJ3w4/vVXSxyZc68/3DZ9vLum7Neopy4oBWEaohc8RxS1ApUgIQAACLRKYt3COTTy2iLbpotFwTROdsjy0zpTguAwCEIBACwTmrWNa6EJvioxNw2EATh4695WUHcRxtCQbdZOSTwheOuzf5xmBVZP3FTwwZH6JpK9MuPDFkmwwOvk6zwismmzwTUoPy/YePO2007TiiitWLZd8MxA4+MTfz3A1l0IAAhCAwLwJbLeRJ+DPL1122WVaf31vZ7eQVpP0p/nV3tua0HARhQ6tE1EwaAoEIACBhgg0qYeavE802a5ZUcWm4TAAJ0f0IZKuCFm+JGnrkgHwl3AAiA8EeUKNwZI/RfgFkr434Vp/ns36e4ek/61RT5P7BdaolqwQgAAEIAABCDREYD1JZzRU1pCLQcMNObr0DQIQgAAEINA/Ap1rOAzAyYNmFUkXhSyHS9qmZIw5r6/5naRH1RiP/y3J+wY6/aukH0649jmSjg+f+7r316gHA7AGLLJCAAIQgAAEIiTQuXiMkMm4JqHhehIomgkBCEAAAhBIhEDnGg4DcPJIG9rb47IlwPeWtEaY9eh9c25P4Iv4UEmnh376C3l5An1OsYvEOY2oE2fiPFQCi0uyJnH6taR/DLWjDfYLDdcgzBmK4u/yDPC4tFcEGOu9CheNnZEA4706wKg0HAbg5MANbf+Y6sM0nZx3H3wSZm9ekk7Xk+opcU4j3MSZOKdBgF5WIYCGq0Kp/Tz8XW6fMTXEQYCxHkccaMV8CDDe58O58VowAMuRXiVp2UROAS6nMbwc/PEaXkzH9Yg4E+c0CKTRS77PacS5iV6i4ZqgOFsZfF9n48fV/SHAWO9PrGjp7AQY77Mz7KQEDMBy7CdK2lDS3yU9UNJtBZf41N+Twmfez2/38qLvzuHjBL1voJNP9fXpvkXJn28fPvR1f6hRD1kXJcAfrzRGBXEmzmkQSKOXfJ/TiHMTvUTDNUFxtjL4vs7Gj6v7Q4Cx3p9Y0dLZCTDeZ2fYSQkYgOXY95K0W8i2gaRTCy7ZVdLe4bNNJR1bXvTdORwHLz1dSdJ5ktaccO25YZ++S8OSVQ72qAF6TFb+eM3Gry9XE+e+RGq2dhLn2fj15Wri3JdIdd9ONFz3MeD72n0MaMF8CDDW58OZWuIgwHiPIw61W4EBWI5s/ZzpVzQ7bzFJZwfj7hpJy0u6tbzoe+Q4QNIbw288m/CUMdfbgDw5/N75d6pZB9kXJcAfrzRGBXEmzmkQSKOXfJ/TiHMTvUTDNUFxtjL4vs7Gj6v7Q4Cx3p9Y0dLZCTDeZ2fYSQkYgNWwZ0tIvPx3o5wJl139Tkn7hB/2lLTHSLHPkvSj8LvPSnrNmGofI+k3knxKzBmhnpty+ZaU5HasG5YhryXpgmrNJ9cEAvzxSmN4EGfinAaBNHrJ9zmNODfVSzRcUySnK4fv63TcuKp/BBjr/YsZLZ6eAON9enadXokBWA3/2pJ+Jskm3A2SvKTEhp5/3jq3J9/5waC7fgoD0Jd4CbGXEjudJelDYW/A1SW9S5LbkeV7d7Wmk6uEAH+80hgixJk4p0EgjV7yfU4jzk31Eg3XFMnpyuH7Oh03ruofAcZ6/2JGi6cnwHifnl2nV2IAVse/paTPS1qm4BKbf5tLunDM51VmAPoyLyU+WNLrJjTrM8FwvKN608k5gQB/vNIYHsSZOKdBII1e8n1OI85N9hIN1yTNemXxfa3Hi9z9JcBY72/saHl9Aoz3+syiuAIDsF4YVpW0czD6POhvCYbflyXtJ+nGguKqGoDZ5ZsFk289SctJukrS6eGE4GPqNZncEIAABCAAAQhAIHkCaLjkhwAAIAABCEAAAmkTwABMO/70HgIQgAAEIAABCEAAAhCAAAQgAAEIQGDgBDAABx5gugcBCEAAAhCAAAQgAAEIQAACEIAABCCQNgEMwLTjT+8hAAEIQAACEIAABCAAAQhAAAIQgAAEBk4AA3DgAaZ7EIAABCAAAQhAAAIQgAAEIAABCEAAAmkTwABMO/70HgIQgAAEIAABCEAAAhCAAAQgAAEIQGDgBDAABx5gugcBCEAAAhCAAAQgAAEIQAACEIAABCCQNgEMwLTjT+8hAAEIQAACEIAABCAAAQhAAAIQgAAEBk4AA3DgAaZ7EIAABCAAAQhAAAIQgAAEIAABCEAAAmkTwABMO/70HgIQgAAEIAABCEAAAhCAAAQgAAEIQGDgBDAABx5gugcBCEAAAhCAAAQgAAEIQAACEIAABCCQNgEMwLTjT+/rEVha0mskvVDSGpKWk3SNpEsl/UzStyUdW69IckdO4AWSvptr456S9oi8zTSvmMBqkraU9CxJT5T0MEmLSbpK0hmSjpT0FUm3ATFaAqtKeoukzSWtIukfkn4n6ShJ+0u6MdqW0zAIpEeA72t6MU+tx3dW7PAJQXtUzE42CMydwPKS1g//1pPkf8uGVnw2PAPXaZSfobYP5TxE0pWSTpf0KUnH1CmIvM0SwABslielDZfAsyUdKslitij9UtKTh4sguZ7Z8D1nJOYYgP0dBu+T9B5JZfc9i5MXS7qov10dbMtt3n5e0jIFPTw/GIMXDpYAHYNAfwjwfe1PrGjp9AQwAKdnx5VxEZg0lusYgH6xbpPv9RO692lJO0i6Iy4EabSm7EEoDQr0EgKTCWwSZvfdN8z4+6SkH0u6QtJSktaUtIWkFSQ9DZiDIbCvpLeGOPutmBMGYH/Da7FhMfJ3SV+XdLykCyTdHL7DnlXmt51O/v1TJN3Q3+4OruVrh5nWS4a47C3pR5L889aStgs9tgm4rqTrB0eADkGgPwT4vvYnVrR0NgKZaXKgpAMmFGXt8YfZquJqCLRKIG8A+iX4eZKeF2qsYwBan+0arjtL0j5hpcbqknaR5PuDk/O9u9UeUfhYAhiADAwITCbgKcvnhinQv5D0fEl/Kbjk3pJuAeggCKwj6dSwFPTNkg4OvcIA7G94PyTpr5Is0seZQ4tL+qKkl4Yu7i7pvf3t7uBafqKkDcN3ciNJJ4/08J1BZPrXfE8HF3461DMCfF97FjCaOzWBzDThvjM1Qi6MhIDHsFfB+J+fdb1tTmZaVzUAHxNWTy0RttaxXrsp1z9PnPFyeL+o9XY7nkTDqo05DwAMwDkDp7reEchmDXlfqbUk/al3PaDBdQnYCPLNz2+obAL5QcYzjTAW6pLsX37vdfJnSTbzfx32CexfL4bXYu9JY0Pe6SBJO47popecnB3EpPdm9azdW4eHgh5BIHoCfF+jDxENbJAABmCDMCkqKgLTGICeBfvG0AuvijtlTI82yL3Edf6doup1Ao3BAEwgyHRxagIPCgd8eImZ9zLwXgWk4RN4h6QPS/JSQh8U4RsYBuDw45710Oav30za9Pc+kKTuCewlabfQDAvHzAwcbZmXnHhJidOmHMrUfeBoQZIE+L4mGfZkO40BmGzoB9/xugagfaVLJK0Ulg97dl9R8vLix4bnbB/oVnUvzcFDn0cHMQDnQZk6+krg1ZI+FxrvPf6ODv/v6cv+4+b9wTxFmj9afY3wou32zc4HfzjG/yrph+HUNgzA4cS4rCe/kvSEsEy46LCJsjL4vFkC2XJC76H0wAmnNNusPylU7eXbnsFLggAE5kuA7+t8eVNbtwQwALvlT+3tEahrAD4y7PXnFhWt1sha6899QrCTr2N/zPbiuEjJGIBzhE1VvSOwv6Q3hVb79F8f8vGBYAx5uZmTjzQ/SpJPGC3aG7B3HU+4wT6W3vs8fkHSqwKHZzEDMJkR4WWjl0ry3iWnSXpqMj2Pu6P+O7ucpLKT1j1r++rQlS/n9nOMu3e0DgLDIsD3dVjxpDeTCWQG4G8k+bnapsntki4PL6QOy2lIWEKgTwTqGoCeLPPt0EEfovixCZ315z5s0WlzSd/tE5i+txUDsO8RpP1tEvCsL5s/Tq+R5P0AbQyMS77R2zjyAyqpnwReEYw/7x/maek+5dkJA7Cf8Zym1V767SXgTv7v/05TCNc0SsCnr2cbSHsWtgXmpOSZ2V667X1nOJW90VBQGARKCfB9LUVEhoERqLIK6BvhOeLagfWd7gybQF0D0Psz+6A9p5dI+soEPC+W5Be1Tr7OMwJJcyKAATgn0FTTSwI287wHnNPNknw4hE9I8rJgz/Z7lCSfPGlz0OmPkp4k6bpe9jbtRj84nPbsGWDevPaTORwYgGmMDc/2+2kw+b2HiU1g7wNI6paAT2LPzPgvSdq6pDn+2+zvsQ8E8VJuEgQgMD8CfF/nx5qa4iDgrSm+Jen4sO+ZX0L5e7BxMDZ8uJiTTz59LodTxRE0WlGJQF0D0M/E+4SSXyDpexNq8efZrD9euFcKR3OZMACbY0lJwyPgY8lXz3VrG0mHj+lmfh8Db0L/oeGhGHyPDpH02nC4wNMl3ZHrMQbg4MO/sLz/DEkrhz09Nwn7Pw6/5/H30JtDXxSa6b+//js8KTmvr/ldeEkTfw9pIQSGQ4Dv63BiSU+qEfC+tF45Mi5ZW3hrmbXDhztL+ni1YskFgc4J1DUA/1uS9192yvZRL+rEc4Jp7s993fs7721CDcAATCjYA+5qlen3Zd23+eN9OvLJM0geF37hgwE8u29c8ts97xt2H0lnSXpKWWV8PhWBtuKcGXzes8Wnv/5ipHUYgFOFa+qL2opzUYPuH/bnWSdkeFfuDebUneDCxggwo6gxlBQEgdYJ8H1tHTEV9IyADzjwiaf3kuSJBY/uWftpbroE6hqAzADsyVjBAOxJoGjmRAJtGQYnS9og1PyRsNy3qCFeOviMMHNsSUm3ELPGCbQRZ5u2NncfI+mjkt42ptUYgI2HspPv87hKvV+VlyA8u+L3fL4kqM0E2FOMcQCB/hDg+9qfWNHS+RHw/rWbheoeJunP86uamiAwNYG6BiB7AE6Ner4XYgDOlze1tUNgjQaKvUzS6Oa8Pt3Xm5g6lU3bPyK3N9WK4fSvBppFETkCbcT55ZK+GPZk8YnP3rtlNK0Vpqf791/NbWp7KsfWtzI+24jzuIb6QJ+vSdoyfOhDfrZrpUcUOiuBqyR5pjWnAM9Kkush0D4Bvq/tM6aGfhHIHzC2vqTT+9V8WpsogboGIKcA92SgYAD2JFA0sxMCu0vaI9TsmWGeIVaU8mahl8BYAJPiJ+ADXA6dspnjlo1PWRSXzZnAYuHE5+xACR8u4VOg83s/zrlJVDeBwImSNpTkzda939JtBXl96u9J4TPvQ+O/4SQIQGC+BPi+zpc3tcVPwAcjeHmkEwZg/PGihXcRqGsAerm791928v74nhFYlPL75/u6PwB9fgQwAOfHmpr6R8DLAn8Ymr2fpP+Y0IUzw95/Pi14aYyE3gQbA7A3oWq0oQdLekMo8duSXjjBVGq0YgqbisBeknYLV3pbBs++HZd8CNPe4YNNJR07VW1cBAEIzEKA7+ss9Lh2iAS+I2nz0DEfNuZ9w0kQiJ1AXQPQvtIlklYK+16uOaGD50ryih9/F3x4VBPbPMXOM5r2YQBGEwoaEiGBxSV5abBn9P0pnAjsgyJG0yPCxr6eVXS8JJ8gShoOAfYAHE4s3ZN9Jb01dMnfV4vyfwyri4PrjWdMZKZf0Vtl//31wU0WnD6RcfmwtH9wMOgQBCInwPc18gDRvLkS8DOCDwG5N6fTz5U7lc1OoK4B6BoPkPTGULVXZZwyphl+ket99rP8O83eVEqoQwADsA4t8qZIYBdJHwod3zO3JDhj4X3EPIPo+eEX3jPwKymCGnCfMQCHE1wv6c+WhXqp6PPCstLh9HC4PcmWFXr570Y58Zj1OH/63Li/1cMlQ88gEB8Bvq/xxYQWNU/AewgfM2EFwQrh87VD1W8PLyGbbwklQqB5AtMYgD5U8TeSPInmjKDXbso1zQdl+v6wbvjeeJ/1C5pvOiVOIoAByPiAwGQCPtHuZ2F5r3MeKemzkq4IMwI9k8hvOJx8mqg3QGUa87BGFQbgMOLpJfwfD13xkoOXjTn4Z7Snv2UWWTTB9wOU/xZbPPqwHi8z/FH42Xs5bh9aen4QltdH03IaAoH0CPB9TS/mKfb4j5LuFQ6I84wm/2yzYzlJ1o47hP83m5+GFUKsOEhxpPSjz8+U9KhcUz2OfYCNk/WXD8vLp8MKuuWtWLwli9NZYSKN9wZcXdK7JGWGuPO9ux9ohtVKDMBhxZPetEPAp/p6lt86E4q3+eeHUB4624lBl6ViAHZJv7m6fyxp45rFeemOBT0pDgKebfF5ScsUNMfmn5d0XxhHc2kFBJImwPc16fAn0Xnrg1Ur9PSrYd9hb09BgkCsBGzobVujcUU+krdk8V7br5tQ1mfCi1sO36sBvKmsGIBNkaScoRPwUt/XS3q5JE9X9kmUf5V0miT/wfz60AEk3D8MwGEEHwNwGHH0w9bOwejzZuq3BMPvy5J8WNONw+gmvYDAIAjwfR1EGOlEAQG/VPQ/rwTySaaeMeUXVJ6lfnE4ld6rhrL9zgAJgZgJNGUAZn3cLJh864XvxlWSTg8nBHvpPKkjAhiAHYGnWghAAAIQgAAEIAABCEAAAhCAAAQgAAEIzIMABuA8KFMHBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQ6IoAB2BF4qoUABCAAAQhAAAIQgAAEIAABCEAAAhCAwDwIYADOgzJ1QAACEIAABCAAAQhAAAIQgAAEIAABCECgIwIYgB2Bp1oIQAACEIAABCAAAQhAAAIQgAAEIAABCMyDAAbgPChTBwQgAAEIQAACEIAABCAAAQhAAAIQgAAEOiKAAdgReKqFAAQgAAEIQAACEIAABCAAAQhAAAIQgMA8CGAAzoMydUAAAhCAAAQgAAEIQAACEIAABCAAAQhAoCMCGIAdgadaCEAAAhCAAAQgAAEIQAACEIAABCAAAQjMgwAG4DwoUwcEIAABCEAAAhCAAAQgAAEIQAACEIAABDoigAHYEXiqhQAEIAABCEAAAhCAAAQgAAEIQAACEIDAPAhgAM6DMnVAAAIQgAAEIAABCEAAAhCAAAQgAAEIQKAjAhiAHYGnWghAAAIQgAAEIAABCEAAAhCAAAQgAAEIzIMABuA8KFMHBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQ6IoAB2BF4qoUABCAAAQhAAAIQgAAEIAABCEAAAhCAwDwIYADOgzJ1QAACEIAABCAAAQhAAAIQgAAEIAABCECgIwIYgB2Bp1oIQAACEIAABCAAAQhAAAIQgAAEIAABCMyDAAbgPChTBwQgAIH5E9hR0oGh2hUlXT7/JlAjBCAAAQhAAAIQgEBNAmi4msDIDgEIVCOAAViNE7kgAAEITCJwkKTtQ4Z/lfTDGrieJ+n7If/HJe1c49pJWRGPDYGkGAhAAAIQgAAEBksADTfY0NIxCEBglAAGIGMCAhCAwOwEniHpp6GYQyW9rkaRh0t6Vci/rqQza1yLAdgQLIqBAAQgAAEIQCBJAmi4JMNOpyGQJgEMwDTjTq8hAIHmCVwoaXVJ10l6qKSbKlSxtKS/SPJ/z5H0+ArXVM3CDMCqpMgHAQhAAAIQgEDKBNBwKUefvkMgIQIYgAkFm65CAAKtEthd0h6hhpdLOrJCba+W9LmQb1dJH6pwTdUsGIBVSZEPAhCAAAQgAIGUCaDhUo4+fYdAQgQwABMKNl2FAARaJfBISX6D7L+rR0vaokJtx0p6rqQ7JD1c0qUVrqmaBQOwKinyQQACEIAABCCQMgE0XMrRp+8QSIgABmBCwaarEIBA6wR+IumZkm6T9DBJV0yocSVJF0taTNJxwQjMZ3+SpH+XtKGktSQ9RNItkv4c9hs8QNIZE8ovMwB9KvAKkrz5tfMWJc9kfJmk30paY0I+9/fNkjaV9AhJS4b+nxROIz6hdfpUAAEIQAACEIAABKYjgIZDw003crgKAj0igAHYo2DRVAhAIHoC20n6VGilT/P1qb5F6R2SPhw+3EaSDwPJ0vMlHVOht3vmlh2PZp+nAfhaSfsH06+o2QdK+g9Jt1foF1kgAAEIQAACEIDAPAmg4Yppo+HmORKpCwItEsAAbBEuRUMAAskReIAkz6y7b5idt94EAr+U9ERJN4RDQ/6ey+vlw0dI+o6kH4bZd9eHGXtPkPQWSSuH/EX7Dc7LAMzvY3iBpP0knSfpKkleUmNB/bzQ1r0lvTu5UUGHIQABCEAAAhCInQAaDg0X+xilfRCYmQAG4MwIKQACEIDAPQh8SdJLw2+8ZNZLZ0eTjT8bgE4+BGTbkQzLS/qHpGsL2Npg/J6kjSWdH5bm3jmSdx4G4Iqh/vuFZb5FM/z+V9LbwtLoR0v6I2MGAhCAAAQgAAEIREYADbdoQNBwkQ1SmgOBWQhgAM5Cj2shAAEILEpg8zBzz598QNJ/jYHkpb9eAuy0iaTjpwD5VEmnhOseL+mcDgxA988z+mzoPUbSrQX9uLekS8I+hv8j6X1T9JdLIAABCEAAAhCAQJsE0HCL0kXDtTniKBsCcyaAAThn4FQHAQgMnsASwezyARs2xrwMNj87z4d++PAPHwJiU2zVcArwJDCe8edZgZ5p5+udls4ZgK+U9MUODMBfS7L5+H+S/rMkst8OJyN7b8PNBj8K6CAEIAABCEAAAn0jgIYbHzE0XN9GMu2FQAEBDECGBgQgAIHmCewr6a2h2I0k+WS5LD1X0rHhhw9J2rWg+vtL8kEiPoF3TUmLT2jmuANH2l4C7FN+vW9h3fvIWZKe0jxySoQABCAAAQhAAAIzE0DDAuU72AAAIABJREFUFSNEw808vCgAAt0SqPvg1m1rqR0CEIBAPwg8WZJFktPBkrbPNdt7/vngDKfHSfrNmC55n7zjJD28YndtItpMzKe2DcBVJF1UsX35bN4T0XsjkiAAAQhAAAIQgEBsBNBwxRFBw8U2WmkPBGoSwACsCYzsEIAABCoS+JUkn9h7TTjl14d6eNnuX8J/z5S0bkFZp4fPvHTYBuJRuZN1XY7TUmEGnv9/N0kfHCmrbQNwNUl/CHUeEA4BqYLG7fdpwSQIQAACEIAABCAQIwE03PiooOFiHK20CQI1CGAA1oBFVghAAAI1CPiQDx/24fQSSV+R9CpJh4ffjVu264/yb57/W9L7C+pcOewl6I+nMQD/LMmn+I7OUBytLtv3ZfStr5coXxcy7y/pzTXYkBUCEIAABCAAAQjESgANF2tkaBcEIDATAQzAmfBxMQQgAIFCAjbXfNiH9+77pqStJH1f0vPCabkPk3TlmKt9oMfnw+99sm7RbDmX9/WQbxoD0Iaey7cxaYOyKGX5xi37uFDS6pJ+IWltxgIEIAABCEAAAhAYAAE03ACCSBcgAIFFCWAAMiogAAEItEfge5I2DYafD76wUWZD0LPq/q2g2m0lHRY+s6nma8alrGx/No0BmF3vZbw+qXhccpu9VNlpnAGY3yh7Y0kntoeSkiEAAQhAAAIQgMDcCKDh5oaaiiAAgXkRwACcF2nqgQAEUiTwCklfCB0/Jxz64R+zJcHjmDxd0s/CB/8n6T/HZPIJwzbfsjSNAehr9goFvEjS10bqeYCkH+ZO7B1nAHoZsn/v/Qg929EnHPvnccn3G5uentE47uCTFMcHfYYABCAAAQhAIE4CaLh/xgUNF+cYpVUQqE0AA7A2Mi6AAAQgUJnAkuHQD++Xl6W/hb33ssM8RgvzDEEbZF6e62QD8QhJl0laVdI2YTmxTcJnhDzTGIArSTo/HEhyo6QPhJOHfV9YT9LbJK0QDLsnFcwAdPUvD230dS7nUEl+a36ppHtL8mnBG0iyyeiDQ2wS+oRjEgQgAAEIQAACEIiVABoODRfr2KRdEJiaAAbg1Oi4EAIQgEAlAodIem0u50GSfELvpGQD7geSPAtvXPp5MAEvCh9OYwD6Uh9K8llJi42p5O+S/Pbb/142wQD0pS+U5H4WtTcr/nZJG0o6uRI5MkEAAhCAAAQgAIHuCKDh/skeDdfdOKRmCDRGAAOwMZQUBAEIQGAsAe+N9+PcJ561d1IFVo8Ie/t5D0FvRu0Td7189kuSDpTkv983zWgA+nIvOd4lzCZcRtLlYYaeTzA+T9KRFQxAl/NASdtLeoGktSQ9KOx96PLOlnR8OHDEpw+TIAABCEAAAhCAQOwE0HBouNjHKO2DQC0CGIC1cJEZAhCAAAQgAAEIQAACEIAABCAAAQhAAAL9IoAB2K940VoIQAACEIAABCAAAQhAAAIQgAAEIAABCNQigAFYCxeZIQABCEAAAhCAAAQgAAEIQAACEIAABCDQLwIYgP2KF62FAAQgAAEIQAACEIAABCAAAQhAAAIQgEAtAhiAtXCRGQIQgAAEIAABCEAAAhCAAAQgAAEIQAAC/SKAAdiveNFaCEAAAhCAAAQgAAEIQAACEIAABCAAAQjUIoABWAsXmSEAAQhAAAIQgAAEIAABCEAAAhCAAAQg0C8CGID9ihethQAEIAABCEAAAhCAAAQgAAEIQAACEIBALQIYgLVwkRkCEIAABCAAAQhAAAIQgAAEIAABCEAAAv0igAHYr3jRWghAAAIQgAAEIAABCEAAAhCAAAQgAAEI1CKAAVgLF5khAAEIQAACEIAABCAAAQhAAAIQgAAEINAvAhiA/YoXrYUABCAAAQhAAAIQgAAEIAABCEAAAhCAQC0CGIC1cJEZAhCAAAQgAAEIQAACEIAABCAAAQhAAAL9IoAB2K940VoIQAACEIAABCAAAQhAAAIQgAAEIAABCNQigAFYCxeZIQABCEAAAhCAAAQgAAEIQAACEIAABCDQLwIYgP2KF62FAAQgAAEIQAACEIAABCAAAQhAAAIQgEAtAhiAtXCRGQIQgAAEIAABCEAAAhCAAAQgAAEIQAAC/SKAAdiveNFaCEAAAhCAAAQgAAEIQAACEIAABCAAAQjUIoABWAsXmSEAAQhAAAIQgAAEIAABCEAAAhCAAAQg0C8CGID9ihethQAEIAABCEAAAhCAAAQgAAEIQAACEIBALQIYgLVwkRkCEIAABCAAAQhAAAIQgAAEIAABCEAAAv0igAHYr3jRWghAAAIQgAAEIAABCEAAAhCAAAQgAAEI1CKAAVgLF5khAAEIQAACEIAABCAAAQhAAAIQgAAEINAvAhiA/YoXrYUABCAAAQhAAAIQgAAEIAABCEAAAhCAQC0CGIC1cJEZAhCAAAQgAAEIQAACEIAABCAAAQhAAAL9IoAB2K940VoIQAACEIAABCAAAQhAAAIQgAAEIAABCNQigAFYCxeZIQABCEAAAhCAAAQgAAEIQAACEIAABCDQLwIYgP2KF62FAAQgAAEIQAACEIAABCAAAQhAAAIQgEAtAhiAtXCRGQIQgAAEIAABCEAAAhCAAAQgAAEIQAAC/SKAAdiveNFaCEAAAhCAAAQgAAEIQAACEIAABCAAAQjUIoABWAsXmSEAAQhAAAIQgAAEIAABCEAAAhCAAAQg0C8CGID9ihethQAEIAABCEAAAhCAAAQgAAEIQAACEIBALQIYgLVwkRkCEIAABCAAAQhAAAIQgAAEIAABCEAAAv0igAHYr3jRWghAAAIQgAAEIAABCEAAAhCAAAQgAAEI1CKAAVgLF5khAAEIQAACEIAABCAAAQhAAAIQgAAEINAvAhiA/YoXrYUABCAAAQhAAAIQgAAEIAABCEAAAhCAQC0CGIC1cJEZAhCAAAQgUInAYZK2DTlfK8k/zyPdmauEe/w8iFMHBCAAAQhAIB4Ce0jaPTRnT0n+eVJaX9JOkp4haUVJS6Ej4gkmLYFA0wR4OGiaKOVBIA0Cj5T0TElPkfR4SatJWkHSkpJulHSlpF9IOlrSUZJu6BDLHyWtOmX9VYTTlEVz2cAJYAAOPMB0DwIQgAAEGiewuKRTJK2bK/mzkl7TeE3lBT5L0o9mMMPy+nOeLwLrGIBvlLSfpMUKcOAVlI8TckCgVwT4UvcqXDQWAtEQsKG3dMXW/CW8WfxqxfxNZ8MAbJpoeuVNY+ZNc00TZJkB2ARFyoAABCAAgS4IvF3SR0YqxgCsF4mqBqBfjl8oaYlQ/O8lnSrp6lx1b65XNbkhAIHYCWAAxh4h2geBOAnkDcA/STpP0uWSbpL0QElPkPS4XNNtSrxB0iEddCdvAB4f2lq1Gd+V5H+ktAlMY+ZNc00TlDEAm6BIGRCAAAQgMG8CXl3y65ElqG4DBmC9SFQ1AHeVtHco+lhJm0u6rV5V5IYABPpGAAOwbxGjvRCIg8D+YVnEiZKuKGjSk4Lh52XCTl4avKaki+bcha6WYMy5m1TXIoGuzLxpuoQBOA01roEABCAAga4J/EDSJpL+FpYBvyA0CAOwnch4i56XhKJfJekL7VRDqRCAQEwEMABjigZtgcDwCDxY0m8lLRe69l+SPjDnbmIAzhn4AKvDABxgUOkSBCAAAQhEQ8B75GWrRLYL+0xnB2lhALYTpsxwden/KumH7VRDqRCAQEwEMABjigZtgcAwCXxa0utD17wP4Ivn3E0MwDkDH2B1GIADDCpdggAEIACBKAj4ELlzJT1I0k8kbSzpUEkYgO2G58eBtWt5tiT/TIIABAZOAANw4AGme8kT8H4qPo33/oGE9/v4UAkVnwa2U8hziaQnhuUY08L0/iKu18l7jGw6bUFTXtekAdgGz/wpcydI8s/+2/z/wql3XkptcXyNpF9J+nz4d0cNHhtI8vIOC7yVwmnNV0k6W9J3gtD+e0l54/aU8cbRr5C0TVje7Zme3jzam0jb+HXZddJ6oTy382GSHhDK8yxS78X4qQpjMR/vR0jyzytL2kHSv4UToe8l6WJJfvvtzca9j+W4VOcAmdETo6uahm7Lc8Lbd/f/sZI8c9ZLef8a9kP6fuBZ5TRtlgDXGXHkhQAEIACBIgJtaJ5xdWVLUW+R9ORgBubvoUOeATjOhLMG8CxIvzC3jvGhe5eFrXc+GrTbpFE7aQ/APNeykV9kClrreV9vL9F+TNAs1wdddVzQlL8pKXw1SX8IeazB/LPTM4P29X9XlLSMpP+T9J/hc58GbXPYKRsXPsF4a0mvlvR4ScsHzfzToPFOHmnLvSW9LNTj9j8kbGfkE58/GMZfGRs+h0BvCWAA9jZ0NBwClQn4hvi5kPtWSU+TdGbB1d4AODNtbDB5ScCsbwS/GYwXV2kDx0bMPFOTBqDb3TTPUQNwS0mHS/r3CZAsZraasP9idqlF42eC0JnE3MLSszSPmZBpVFAeLMmi/ekTrrFIs0gsMyv91t/lvahkYNgEtSj+yoR8owagHyYseG0mjks+uMZ74Bw95sO2DcBVJJ0ladkKXwibgS8PpuWk7BiAFWCSBQIQgAAEKhFoWvOMVmqt843wy/dL+u/w/6kagNbpXwovQccF6HZJbwyaqSiAbRqAr5O07wRN5Ta5jZ+Q9I7w/+PaOWoA2oj7eMEzwiQD0HWYl1+kjkvWRNa3mWn4KEnfCi+tx+W3CW1zMBuTlb4kZIJAnwhgAPYpWrQVAtMT+GIwD1zC+ZJ8MMfojK+HhhlmfhPm5Ldgu01f5cKVviF7lpXfzjk9b4KBkRcDzuv9YCwAZ01NG4BuT5M8Rw1AGz0vDDPATpPkt6j3CUZb9obUbfDsvWdIuq4A0FLhbfH6uc//HJbXeCaZRZDfsC4ePvfJbzaYisy1vKD83zCT029afbiLl+x4Rp1nmvqNsd++Zqls1qnHnfed8QExWTpH0i8luZ0ua8OcSWYx5weSos2q8/G2WfjJ0EcfPmPj1Lz8Rt3cPYPRyX1wX7K30Vk7PKvP5pyN8DXCL4tOkh49MbrKDECX6WVPTt703P32m3D322+o3U7P3rxvLkZeGnXShC8FBuCsfzG4HgIQgAAE8gSa1Dz5cj27y/dAr0y4IKw4uTlkqGsAtqEh8/rMzar73FxFf+ZnAP5HOJX3fuEFr7WVNaFXRFhPLxnY+KWq9d8pBcN0kgHo1SDWFU5eaWL2Tja8Lh0pz8ab45Ilm20fzv38D0leuWJ95Re51n+evZilr4VZjHldkn02agD6Jeybwoc+Cdoa0GaojUFr4beFz/IzAK0DHx40osdN1ha3wbrtgTle1k5+/jlDkl++Wgv6IEO/APcqGx8+Y93s5BfDjxujCQtw82sI9ItA3T9k/eodrYUABDICnv3km+mq4RdenmlzJEv+W+DZX9nyXN8gPbPLN986yeVY0NnM8Rs038xtZDj5Rm3hUZTaEG+uq4oAq9NH522SZ15g+s2jedmIemkQKvm2eTbdAZK8bNRp0oxK5/NbYie/jX17eCObn433aElHSFon5LMg8pJjMxtNeUFp0WdT0ssvLMq87DdLFlAeXzYTnWxm2eQbt8TYxrCXi1g0Olnk7RhmxeXrtwH2Lkm7BwHusp5QIM7y8XY7bWy6TI+/vAi1uPPSWgtrJ78d9pvtcamKmTd6XZVr/H10XLys29+5cTMl/X36n5DPdVjA+vtVNKsSA7AgiPwaAhCAAASmItCk5sk3wC/oslUho4dQpGgAWrP4xeQuYTac9UuWbFr5RaNfVjp5uWrRrLdJBmCef509AP1MYMMse2nsZwa/qP9LrkDrwvdJemfud9Y4njE4mvKa3xrV5fpF8ivDS+V8fpdrNk55AzDTol5ptP3Iqhgbkv69XyBnvK4Nq2c87szYy5az5K1ivE1R9jJ6kiac6kvERRCIhQAGYCyRoB0QaJ+AZ3v5Zp/dvD3L7Ouh2rfmbtA2VzxD0EZDleSTfX3DL0oWMJ4x9u6SpaDzMACLZm8Vtf3NE/rVFM/RN8zmbxPudwV1eymDDTYnmz028Ubzrh7il828dD/2LyjPIunnuf1XikRPXlC6KBuH3v9vXLJh5/FjwerkvVm8RGM05ZcW+U22xazfvBalfBss4DKDM58/bwCaz2aSvldQYH7Ju41Ks8gL7uyyKmbeaBXTXDOh6zowGJnO4z4VLdfGAJxEkc8gAAEIQGAaAk1pnqzujYIm9bOot6nJDvwYd9+tsgdgGxpy3jMA3Xcbon65Oy7Z/PNe0Gbme71fYHoG22hqwwD07DrHzMmrEPzi1i+txyXPHHxL+MAvlm2u5c02fzQaL6/EWLvCs0feAHQ5fq7x7D2biKPJL1mtj7PnHn8+aSx5VqX3DXRyez2TcJwmnOb7wzUQiIYABmA0oaAhEJgLAS9p9GwiJ8/a8gEf3szXhzb4DZuTZwZmBlOVRk0yAL181bP+vM9ZWWpDvLnOOvu4jbax7G9kEzxHBabN1CxGRcw8WyybtTduqbZ/5xlzTj4ExobuuCUYWfmebZgZdH6j6uUQflOaT3lBadFnYXX5hKD6sBm/YXXy21+/BR5NHhfeo8/J//Us1UnJxqLFrpd1uH0WZ6Mz4fLx/nZu/8lx5Tq+XhbtGYpO/j546clomsbMm+aaSX33Um5/Tyfx9GcYgCWDiI8hAAEIQGAqAk1oHlfse7nv917e6SWu3g7DB5PlU4ozAK0/rEMmJeuAbGsXH2xmnTOamjYAPSsuf6iHNeUkXe/9p63F/Hzh5FUYB400clTz75PTrZP6P2oA2jS0zi1KnrWYzQK0vvWS4Ssm5Pdy5uzltVeaeLsdEgQGRaDs4XZQnaUzEIDAwlsw3wyzgxu8hMBmz1qBjffrKDuIYRSjlw374Aonl+9ZVJ7Blu2Z5rdnnlXmvUOK9qtrMzRtGoBN8Bw1AD2j78ISIH6z6jesThaD2X4u2WVeSusTZZ18clqWt6hYLym2mZft3eKT3UZnzeUFpffs83KdScmz/jxL0GncuPLpbjbfnCwsvSS3SvISGLfPyePMb8PzKR9vn07sA1UmJfczW/peJKanMfPqXuMYPDX0yYak91PM9ih0+/2z++M0iT8GYJVRRB4IQAACEKhLoAnN4zr3yu0xXbTfc10DsG5fquSf9wxAv/ydtKLGbc4vm7YW9GEbo6lpA9Db+WSrSGy22XQrSz7Qw3saOvkFszVhPo0agGWmYnZt3gD07D7vZz0pud3Z3oLecua5JfnzGrNIE5b1nc8hEDUBDMCow0PjINAKAR8s4Bu49xbLJ2/+6zeP+f3cZmmAb+a+8WbmlN8WWkzN2wRsYw/APJdZeeYFpt+AZ4ewTGJvc88mn5PfaHpj6Mz48d91/y7bJ9Bvik+vEEgvKX1+yPeeINDzl+UFZf5EtqKiLbK8n4rTONHlJehfDZ97z0OLrirJ5XrWgNMWY07vzce77M2wy/DegNlSZs9WHXe4SF0zz+VWvcax8/J4vyHP3paXcbDpafNzXMIALKPH5xCAAAQgMC2BWTWP711exeAXXF6+me0BPNqeFA1AH8pRdvrsB4JmMC+vwPHPo6lpA/BgSd6D2sn7S+9UYfB4H/AjQz4fJJLptuzSvAHo/ca9f3SV5bZ5A9B7/G1V0hafLG1N61RFu3pPZu9D6FSkCSt0nywQiJcABmC8saFlEGiTgG9uvsllyaaB99DwzKImk80NzzL0zCanSYdWNFlvvqy2DUDXNQvPvAHovfiypb2TeHjWZn75rTfozoxVL4/1ibJZct5Jyx2yfPk95j6aO3Et+zwvKN8bDuSY1MbR0439cz55X8Jxb67rjAPvIZgfx742H+9HVjjFrYpRVyXPaLurXOPZsv7OZcugq/bdhqn7Ni5hAFalSD4IQAACEJiGwLSaxzMIvWrBOscvKm0G/ragASkagN4H2Zp5Uqpi7lXJ4zqqHgJiU/LfQ6O8vYyX65Yl6/7slGJr0vzpwL42bwBao1qrVkl5A3Dc3pGjZdTVrlW0W5V2kgcC0RLAAIw2NDQMAq0SyM/OckVeium3c+NOap21Id44+iehEL/l800+b1DNWn7Z9fMwAGfhmTfKvPlwtlfJpH7db8zpZZ7B6eTNln2SWpact0pcP5Lbp2/0lGiXVVVQZvWWGYB+I+s3s7OkcUuH8vH2TIVxJxrn66wi9qrkGe1HlWu+mDst2fsqWsx6P59zw16HPhAl29g6L5b/lDu0ZbReDMBZRhTXQgACEIBAGYFpNc/Okj4WCrem8J6CRSkGAzCvX91O75VddPDFuH54z+Jsj+Gi2WRVTbis/CparEoel1e1bq/iyLZ9mXSoXJ6BDyzJ9lT2zL5sVUqWp6qmGeWaNwCrHA5TlUVWTxXtVvb94HMIRE0AAzDq8NA4CLRCwMsMvYTQe7Dl0zjTp4kG+CRan6bl6f1OXmb6/SYKrlhG2wbgrDz7OAPQot2ialIqMwC9N6FnGjp9K/d2uWJYC7P1xQD06X02an0f9kEmnoE76c2/N6PO9jvEAJx1lHA9BCAAAQhMQ2AWzZM3V7wtzCQzbfXcthjeHsX7vWXJS2XHnX47TX8mXZO/7zrfsjW3ybH29UtYp3Fblvj3VU24rJ1VDK0qeerU3fYMwEmaZjQ+GIBNj3LKS44ABmByIafDEFjYXySbyu/DJjxLyssynKrsPzINQs8wzAxHLx3xzKd5pbYNwFl55o2yKyUtXwHMurl9/cr2APR+gd5vpyzV2QOwCQPw5blx4P0Ms2XiZe0s+7wvBqCXL3vGn9PR4eFgUt/88JCd9ocBWDYK+BwCEIAABNogMIvmyRuAs7Styuz+WcrPrvXsvbzRaO11ZsWCbZRa02XJGifbuzlfRB8MwPwegN7b27MAy1KdPQAxAMto8jkEGiSAAdggTIqCQA8I7BBOEHNTvbzQB3X4ZK7dQ9v/Gg4CyU5nbaJLnvZ/g6R7h8LGnTDbRD1FZbRpADbBc/SUOZ9oln/TPa5fPlnNJ6w5lZ0C7CU3Wd4iRt6M23sK+u22U9kpwE0YgN7DLuunZwF4f5gqS5XLxkobBqBPsfZbZ6eiEwtH21W2jMT76HwwXOT/7lbSMe+5886QBwOwbBTwOQQgAAEINE1gVs3TNwPQ/C6R5Bn7Tj6s66CKUK2jssPNvP2ND967ecy1fTAA86cAe+amnx3Kkg/c8CnFTmWnAGMAltHkcwg0SAADsEGYFAWByAk8VpIPmciW4vqG7oMfPPvPe/Q9LbT/eEne3yW/l9gsXdtc0ndyBXjfD9/s55XaMgCb4jlqAFYx1/wW2TP7nMaZR/6dDSYnx9xvrSfF88WSvhzyW6D6rfe1IwGquqQku6xsCbDz/UbSmuGCKkZllTHThgGYPyBle0l+G16WygxAm3nZRto2aN3/ouTv7O9zm2RjAJbR53MIQAACEGiSQFOap2qbYtgD0G3Nnwo76dTi0X4dHk6R9e8n7e/cBwNwjbA3cdZHH96SbUkyLp7WLD6sLFvRYuPYhwDmE3sAVv0mkA8CDRPAAGwYKMVBIFICnn13cu6tnZcS/luurZ6N9QtJ9w+/sznhQyHGJc8S80zBKsmzun4myeLByUsnbEbNM7VhADbJc9QA9J4xFlcWT+NSfv8Tm3o+vMVLufPJe+ecL8n7LzpNemvtU4NtEnpJjZNnu71uTMVtGIDbSrLId3K/n5HbNLpsjNikzJ+EnOVvwwD0YSU+tMSpikHrfGUG4IskfSWU6fj5O5Id+DHa97wB6c8wAMtGB59DAAIQgEBTBJrUPFXbFIsBaF1iAy9LfmH61ZJOPD28WM802CskHVFwTR8MQDf9BEkbhT540oAPBfHMxnFpX0lvDR9cF2ZQeiVQPmEAVv0mkA8CDRPAAGwYKMVBIFIC+eWDNk2eOLI3iZu9jSSfqOXkJZner8Sm4Gj6Wji0wIeG+GQwn+41mix6fNiHD3mwQZUlH3TgGYbjUl4M+POqSy3LkLdhADbJM28AmruFtpfGvjQYc/n+mcknc8upJx3ccoCkN4aLHSMfumEjyQdOZMnLjb0fYzab0ELN5uO4k3PbMAA9+/RYSc8JDXL9uwQTctzm4F5Cs6Wk7cL4fcmY4LdhAHqZfCbe/Z3wd6PsJMAyA/BBYWlRNiP3C2FfnWtyfXJ/bcS7v14evXT4DAOw7FvP5xCAAAQg0BSBJjVP1TbVNQDb0pBub37fQ9/7rVOsp0Z1gLWv97neLyz59bWnS7IhOE4r+/O+GIDuw4m5PcM9keANkq7IBdT61S9Jd8397u2SbAiOJgzAqt8E8kGgYQIYgA0DpTgIREjA5soPwmwwzxjbTNL3Ctp5pCRv3Ot0rqR1wl6B+ex5IWRT4tfBMPKSUd/8PTPL140eZvG23Kmv46pvS7zlDSGbj+fViJH3fsn2acsua5rn6FLZq8NhLI7VKSEO9wlLtD1TM0uOj5dtjy7VzT63sWRhmZl7/r374zfZfhPrWYJ+m5sdAGNx6oM5sllpo5jaMABdh2eUenyunavQRqBnrF4aZsXZLPPyIy8X9n6FTn4D7zfxo6kNA/ABYSPwJUNlXo5rtjbrsqXVNjL9L0tlBqDzWSj/T+4ax957OrrfPjTHY8Omn2Pz+pxBjwFY40tMVghAAAIQmJpA05qnakNiMgCtQWx+PX6MTvGe2Z69v0LQZD78I0vWXBsWvFTN8vTFAHR73yHpw7n++RC6H0m6WJIZPTu3l7SzfV2SVzuM24IGA7DqN4F8EGiYAAZgw0ApDgKREfASXO/TkW1gXLbXmJeD/lLSw0M//IbTewXmkzfz9ey0qslmiQ+tyDZDLrpuHgZg1TZn+cziybmL2uA5agB6abZng/nU16Jkk2irgiWw+WvuJ+kzFeLlU+5sMPkk4KLUlgHo+mys+Q2x3yZnBt+kWPkAm/dJ2ntMpjYMQFfjZdSeVVl03xxdGlzFALT5ekiYfVvUX5uMnvnOMRxcAAAgAElEQVTpmYfZsnAMwLrfZPJDAAIQgEBdAm1onqptiMkAdJutp6wBPMMvW9o7qS/WU753/6Wkw30yAN0Va0XrNa9QKEo2RD0L0rP/irY2wQCs+k0gHwQaJoAB2DBQioNAZAQ8m8tv35zODrPBxp1Clm+2Z4X5jV4mcGxIeap/lvz79cPsJM8u88yslYM48n4gnpFmE8b7/fk6z+4qEgD5evtgALbBc9xhGf7b7Nlt3iPPy7X9ZtlGkM1cm4OfG1nKWzbsPFPw1SFmKwXD7aowJnxAi02oshN42zQAs/Z7DLwqLAn20nHPDvR485iykWxD1rM4PYPVswTHpbYMQNflvYC8mbWXANtU9yzL7D46jQGYtd9mrw8Xcbl+i/43SRdJ+maIjWcYVBXL+Tft3OPLvhl8DgEIQAACRQTa0DxVacdmAGbttjaxCWit/GhJNkmtU3zftv7w/nhHSTqjYkf7ZgC6W57l6K1JfNKxeZiB93H2TEBvDWRN6UPeJqWqmma0jPw+2N62yD9PSnW1a5WXtxVDSzYIxEmAh4M440KrIACBdAhUOS03HRr0FAIQgAAEIAABCEAAAhCAAAQaJ4AB2DhSCoQABCBQiwAGYC1cZIYABCAAAQhAAAIQgAAEIACBugQwAOsSIz8EIACBZglgADbLk9IgAAEIQAACEIAABCAAAQhAYIQABiBDAgIQgEC3BDAAu+VP7RCAAAQgAAEIQAACEIAABAZPAANw8CGmgxCAQOQEMAAjDxDNgwAEIAABCEAAAhCAAAQg0HcCGIB9jyDthwAE+k4AA7DvEaT9EIAABCAAAQhAAAIQgAAEIieAARh5gGgeBCAweAIYgIMPMR2EAAQgAAEIQAACEIAABCDQLQEMwHr8V5X0FkmbS1pF0j8k/U7SUZL2l3RjveIm5t5E0qskPVPSipJuk/QXSb+SdLykwyXd0GB9FAUBCEAAAhCAAASGSgANN9TI0i8IQAACEIAABCoRwACshGkh05aSPi9pmYJLzg/G4IXVixyb80GSDpX07yXlrC3pFzPWxeUQgAAEIAABCEBg6ATQcEOPMP2DAAQgAAEIQKCUAAZgKaKFDDbbfiZpyTDrbm9JPwo/by1pu1CMTcB1JV1frdhFcj0gzO5bJ3zydUlfCbMMbw+zDjeW9KJgSGIATgmayyAAAQhAAAIQSIIAGi6JMNNJCEAAAhCAAATKCGAAlhG66/MTJW0YluFuJOnkkcveKWmf8Ls9Je1RrdhFcn1O0qvD0uKXSvpWQTmO2+KhPVNWxWUQgAAEIAABCEBg8ATQcIMPMR2EAAQgAAEIQKAKAQzAckrrSzo1ZDtI0o5jLllM0tmS1pR0jaTlJd1aXvQ9cnivv5+E39hQ/EjN68kOAQhAAAIQgAAEIPBPAmg4RgMEIAABCEAAAhAIBDAAy4fCXpJ2C9k2yJmBo1fuKslLg502lXRsedH3yHGkpJdJulbSQyXdXPN6skMAAhCAAAQgAAEI/JMAGo7RAAEIQAACEIAABDAAK4+BbOnI3yU9cMKy26dJOimU+l5Ju1euQbp3MP7uG/b8e0m41st8VwrLfS/HFKxBlKwQgAAEIAABCKROAA2X+gig/xCAAAQgAAEI3E2AGYDlg+FKSctJ+qWkJ0/I7tN7rw6ff1mS9/CrmtaTdFrIbOPwY5JsIm4bTEd/dEvYi/ADkn5ctWDyQQACEIAABCAAgUQJoOESDTzdhgAEIAABCEBgUQIYgJNHhWfk3RSyHC1pi5JBdIOkpSWdIskzAqsmG32Hhcw+ROQVkh5dcPGdYUnyh6oWnsu3csk1nom4hqQrJFk0++RhEgQgAAEIQAAC3RLwioCHhCb4/nwpB4GVBgQNV4qIDBCAAAQgAAEItEwgr+F+HQ58bbnK4uIxACejt9i2Geb0JUlbl0TqL+EAEB8I8oQaUX2rpH1Dfu/9Z9H6PUn/I+lXkpaR9CJJH5T0gJBvK0nfrFGHs9o8JEEAAhCAAAQg0G8Cq0i6pN9daL31aLjWEVMBBCAAAQhAAAI1CHjl5xk18jeeFQNwMlIL7ItClsMlbVMSAef1Nb+T9Kga0fovSe/L5f+BpBeMmYHnk4JPkORTh8+V9Liaph4GYI2gkBUCEIAABCAQKQEMwPLAoOHKGZEDAhCAAAQgAIH5EcAAnB/rqWqa19vjd0j6cK6FT5F0VkGLvb/gi8NnTwozBKt2rmwJ8MPC8mWddtppWnHFFauWSz4IQAACEIAABFoicNlll2n99dfPSrd4/AVLgEtho+FKEZEBAhCAAAQgAIE2CYxouNUk/anN+srKZgbgZELz2j9mB0mfDE3x3j7LT2jWGyQdHD73/3+mLMg1PrdBeLHzX3zxxVp55TK/sEbJZIUABCAAAQhAYCoCl1xyiVZZxRPaFhKz/6pRRMNV40QuCEAAAhCAAARaIhCbhsMALA/0VZKWbfkU4M0k+ZARJ8/88wzAorRp2B/Qn+8W9gUs70W1HBiA1TiRCwIQgAAEIDA3ArGJx7l1fPaK0HCzM6QECEAAAhCAAASmJBCbhsMALA/kiZI2lPR3SQ+csOTGp/6eFIp7r6Tdy4u+O8eqkv4YfvKhH17aW5TyZuE7JX2kRj1lWTEAywjxOQQgAAEIQGDOBGITj3Pu/izVoeFmoce1EIAABCAAAQjMRCA2DYcBWB7OvcJMO+fcQNKpBZfsKmnv8Jln6R1bXvQ9cngt+MMlXReMxqIDO/5D0sfDla+QdETNeiZlxwBsECZFQQACEIAABJogEJt4bKJPcyoDDTcn0FQDAQhAAAIQgMCiBGLTcBiA5aPUu25npt9BknYcc4lP5T1b0pqSrgl7+N1aXvQ9cuwr6a3hN8+VdFzB9T+S9KzwmQ3DhT37GkoYgA2BpBgIQAACEIBAUwRiE49N9WsO5aDh5gCZKiAAAQhAAAIQGE8gNg2HAVhtpGZLSG6TtJGkk0cu81LcfcLv9pS0x8jnNuxs3Dl9VtJrxlRrM++3krxp9a8lPTPMBsxnfZWkw8MvvGfgFtWaXzkXBmBlVGSEAAQgAAEIzIdAbOJxPr1urBY0XGMoKQgCEIAABCAAgToEYtNwGIDVore2pJ9JWlLSDZK8pMSGnn/eWtL2oZjzJa0r6fopDEBfkjcSbQZ+SJL3BFxG0gslvVHS4sEYdD0XVGt+5VwYgJVRkRECEIAABCAwHwKxicf59LqxWtBwjaGkIAhAAAIQgAAE6hCITcNhAFaP3paSPh/MuHFX2fzbXNKFYz6sMgMwu8z7CL5LUlFsrpC01ZhZiNV7UpwTA7AJipQBAQhAAAIQaJBAbOKxwa7Nqyg03LxIUw8EIAABCEAAAncTiE3DYQDWG5w+rXfnYPTZLLslGH5flrSfpBsLiqtjALoInyjs2X4+fXhFSTdLssH4LUmfkHRtvWZXzo0BWBkVGSEAAQhAAALzIRCbeJxPrxuvBQ3XOFIKhAAEIAABCEBgEoHYNBwGIOM1TwADkPEAAQhAAAIQiIxAbOIxMjw05y4CaDhGAgQgAAEIQCAyArFpOAzAyAZIx81BPHYcAKqHAAQgAAEIjBKITTwSoSgJoOGiDAuNggAEIACBlAnEpuEwAFMejYv2HfHIeIAABCAAAQhERiA28RgZHppzFwE0HCMBAhCAAAQgEBmB2DQcBmBkA6Tj5iAeOw4A1UMAAhCAAARGCcQmHolQlATQcFGGhUZBAAIQgEDKBGLTcBiAKY/GRfuOeGQ8QAACEIAABCIjEJt4jAwPzbmLABqOkQABCEAAAhCIjEBsGg4DMLIB0nFzEI8dB4DqIQABCEAAAqMEYhOPRChKAmi4KMNCoyAAAQhAIGUCsWk4DMCUR+OifUc8Mh4gAAEIQAACkRGITTxGhofm3EUADcdIgAAEIAABCERGIDYNhwEY2QDpuDmIx44DQPUQgAAEIACBUQKxiUciFCUBNFyUYaFREIAABCCQMoHYNBwGYMqjcdG+Ix4ZDxCAAAQgAIHICMQmHiPDQ3PuIoCGYyRAAAIQgAAEIiMQm4bDAIxsgHTcHMRjxwGgeghAAAIQgMAogdjEIxGKkgAaLsqw0CgIQAACEEiZQGwaLjYD8AxJn5H0RUnXpjxQOuo74rEj8FQLAQhAAAIQKCIQm3gsaCcartshjIbrlj+1QwACEIAABBYhEJuGi80AvEPSnZL+Ienrkg6VdBzjaG4EEI9zQ01FEIAABCAAgWoEYhOPBa1Gw1ULZ1u50HBtkaVcCEAAAhCAwJQEYtNwsRmAZ0taK7C1Eeh0kaTDwr8/Tcmdy6oRQDxW40QuCEAAAhCAwNwIxCYeCzqOhpvbiBhbERquW/7UDgEIQAACEFiEQGwaLjYD0MDWk/Q6SS+T9MCcGWhD8MdhifDXwixBhlizBBCPzfKkNAhAAAIQgMDMBGITjxM6hIabOdpTF4CGmxodF0IAAhCAAATaIRCbhovRAMzI30fSCyW9VtJzJC0Wlgf7c+8PeERYIuw9Z0jNEEA8NsORUiAAAQhAAAKNEYhNPFboGBquAqSGs6DhGgZKcRCAAAQgAIFZCcSm4WI2APOsVwlG4LaSHhE+yJYInxNmBX5e0l9nDVDi1yMeEx8AdB8CEIAABOIjEJt4rEkIDVcT2JTZ0XBTguMyCEAAAhCAQFsEYtNwfTEA8/F4Vlgi7NmBS+XMwFslfVvSIZKOaSuAAy8X8TjwANM9CEAAAhDoH4HYxOMMBNFwM8AruRQN1x5bSoYABCAAAQhMRSA2DddHAzADv2lYArxC+IX7ks0K9GEhH5R0cO53UwUssYsQj4kFnO5CAAIQgED8BGITjw0QQ8M1AHGkCDRc80wpEQIQgAAEIDATgdg0XN8MwIdK2kbSayQ9dsT4+4mkNSQtH35vM/AUSS+QdN1MUUvnYsRjOrGmpxCAAAQg0BMCsYnHKbGh4aYEV/EyNFxFUGSDAAQgAAEIzItAbBquDwbgvST9W9gD8HmSFpeUtfuSMAvQy34968+fbSHpnZKeHmb/fVTSO+YV4J7Xg3jseQBpPgQgMBwCF154oU4//XSddtppC//OOuss3XTTTQsdPPTQQ/Wa1/hdWLV022236dOf/rS+8IUv6LzzztMNN9yglVZaSZtssone8pa36HGPe1ylgq666ip9/OMf1ze+8Q398Y9/XLhmtdVW01ZbbaWdd95Zyy67bKVyzj77bH3iE5/Qcccdpz//+c+63/3upzXWWEOvfOUr9YY3vEFLLLFEpXKOOeYYfepTn1rgdOWVV+ohD3mI1ltvPW2//fZ6wQv8/m8YKTbxWIMqGq4GrBmzouFmBMjlEIAABLoigOYrJ99XzRebhovZAHxyMP1eIenBYUi4vd7r7zuSPi3pexOW+H5K0hsk/UHS6uVDihySEI8MAwhAAAIREDjhhBP0rGd5u7TxqY4BaNNus802WzDJxqX73Oc+2m+//RaMt0np1FNPXTD6Lr/88rHZVlxxxQVjcP31159YzsEHH6w3v/nNuuWWW8bm8/VHH320lltuucJy7rjjjgWT7zOf+UxhHvfnoIMO0mKLLRZBRGdrQmzisUJv0HAVIDWcBQ3XMFCKgwAEIDAPAmi+YWu+2DRcbAagpw68Mhh/T8yZfv7f88Npv5+VdEWFL+NTJJ0h6XZJfgNNKieAeCxnRA4IQAACrRP48Y9/rGc/+9kL9djAWnPNNbX00ksvzAR0qmoA3n777QtG4k9/+tOF6174whdqu+2204Mf/GDZ0Hv/+9+vK664YqGO73znO4Wz5i6++GKts846C7PsPDvvbW97m7bYwhPutXDdvvvuK88yXH755XXmmWdq5ZV9O1k0ffe739WWW24pG3grrLCC3vOe9+ipT32qrr76atkY/NrXvrZw0TOf+UyZweKLe2L/omm33XbTBz/orX6ltddeW7vssotWX311/e53v9M+++yzMFvSyfn22muv1uPVdgWxiceC/qLh2h4Ik8tHw3XLn9ohAAEITEUAzTdszRebhovNALw5mHVZu7zW6Sthtp/3+KuTPOvvgjBDcPwTRJ3S0siLeEwjzvQSAhCInMAFF1ygb37zmwvLWW28eYnsYYcdpte+9rULLa9qAB5yyCF6/etfv3DNm970Ju2///736LmXnLj86667To961KN07rnnjl1+u8022+jwww9fuPaoo47SS17yknuU49+97GUvW/jdtttuu9DW0XTrrbcuLPP9/e9/r2WWWUY///nPF0y7fNppp510wAEHTOzj+eefv7Bk2YbjuuuuqxNPPFFLLrnk3cXceOON2njjjXXGGWcs9MV9ct/6nGITjwUs0XDdDjI0XLf8qR0CEIDAVATQfMW6dgiaLzYNF5sBeEf41vjVvZf4fmGGAzzuL8nLh50OmurbmN5FiMf0Yk6PIQCBnhCYxgBca621Fgwwz/jzLL6lllpqkd56Jp1nyjmNM/e85PdhD3vYwqy9TTfdVN/7nnffWDQ9//nP1/e///2F2YSXXnqpHvpQn/nwz5Q3Cffee2/tuuuuixRi886zB//2t7/JbT/nnHMWyWMj88ADD1z4/cknn6wNNthgkTynnHKKnva0py38fpzx2ZOQ393M2MRjAT80XLcDCw3XLX9qhwAEINAYATTfXSiHoPli03CxGYCemmDj7661O6R5E0A8zps49UEAApUJ7LHHHtpzzz0X8t955526+eabFw6SOOKII+S3p05eKuvZajvuuGPlgyQqN6DjjHXFoN+aPvaxj11otXlkptloN2zwef8+p5e//OX64he/eI8sPmRjhx12WPjdkUceefdMv9Fy/Jmvd/Lee96jL59e8YpXLMTK6bLLLlvEIMzyuq2+3um3v/2tHvOYx9xdjONug9AHh3g2oc3NouTPfb3NS5uf//IvsUme6gMqNvFY0HI0XPWQtpETDdcGVcqEAAQ6IYDmq7fqA80Xr+aLTcP1Vw138qdo8JX+f/bOA1q6qrzfzxLsAVHBDogtihUFBBXUGDQKRvO3BE2CJirYYond2E2wx2iwYA2WRAUTEwuWKIoNBFvEGhsiVhSUpkj5r/dy7udw75yZc+acmfPO7OesxdLvzq7P+86Z3/xmn70VjysfYicogeUlMCoGw7SKFWdf+tKXxk4o9pmLAylW4QCI9Qm2NQBHH/8N4+3AAw+sDX4YhSEed9ppJ04++eRLlBt9/HeScRevxcnCcUWdI46ILXt/f0XbYcRFX3EScd0VYw2zMK6Yw/pjz/HveHx4/bHhMCVf+9rX1rYTr4d5uV5vl112WdrkzyYelxbkag9cDbfa8XV2EiiKgJqvnQGo5sur+bJpOA3Aom6lUyereJyKyAISkMBQBEbF4O1ud7u1Pd5itViYffGIa6z2ev7zn79lVViYQ+sr14Yac5/9tjUAn/jEJ/Kyl71sbQhxKMatbhUHs46/7nWve/Hf//3fa6vkzjzzzLUDR9av2GcvDva40pWuxBlnnDFxSlEm9hOMvQvXDyyJCmeddRbbbBM7c0D0FeZs3RVjvfWt4xwveNKTnrR2qMf6FQeORLzjevnLX87jHve42nbi9TisJK44VThOQl7WK5t4XFaOKz5uNdyKB9jpSaAkAmq+dgagmi+v5sum4bIZgDsAFz/fBf8A/GjKje7awN9XB33E/07+ZlLSXXO2uSoeZ+NmLQlIYAEERsXgpS99aT784Q+vnXA7esVpsrF33E9/+lNucYtb8OUvf3mmkY32NVMDwM4778z3v//9WatvqtfWAIwVf+985zvX2onTe7fffvvasTz60Y/eckBIrM5bf3Q4KsRefsEzDt446aSTJs7nZje72dq+fVEnVgSuX9FmPJ4dVxz0cdhhh9W2c9ppp7HDDiEHWFu1uP7YcPw7TN1HPOIRa68deeSR3Pe+961t56ijjtpyWMmym8HZxGMNdDVcb+/2mRpSw82EzUoSkEBGAmq+dgagmi+v5sum4bIZgPFT/UuBrwC3bHgzim93NwMeA1zyeMOGDVhsCwHFo8kgAQmkJTAqBmNl1/rqto0DjgMt4mCLWM0Wh0nEqrS21yoYgPvvvz8f+MAH1qZ+7rnncrnLXa4Ww1Oe8pQtK+1iZWWcDLx+xWrAOJzjtre9LXG4xqQrysTKvzi1OFYSrl8nnHACe+6559o/o6+IT90VY10/rOSAAw7gve9975aiL3nJS3jyk5+89u+jjz567THwuiteX1/199KXvpQnPOEJbdMgTfls4rEGjBpu2IxRww3L394lIIEeCaj52hmAar68mi+bhstmAH4I+GPg2dUKwCa3kadXZY8G9m9SwTK1BBSPJocEJJCWwKgYjEdS1x8T3Tjg0ZVf0x59rZvsz372M+K/LtdlLnOZSxxg0aWtqNt2BeBd7nIXPvaxj611e8EFF0zcD/FZz3rW2uPTcX3yk5/kDne4w5bhbrXVVmsnAO+zzz4ce+yxE6ex7777rtWPOueff/6WsvG3eC2uZz7zmTzvec+rbSf6ivpxxRz+53/+Z0vZGGOMNa6PfvSj/NEf/VFtOzH3qB9X1HvGM57RNQSD1c8mHmtAqOEGy5C1jtVww/K3dwlIoEcCar52BqCaL6/my6bhshmA8cjv1YH4Sf8jDe8hYRh+GDgV2LFhHYuNJ6B4NDMkIIG0BEbF4Nlnn71lldjGAY8aP2FYhXG1CldbA9Bfg/P+Gtw2H7OJx5rxq+HaBrbf8mq4fnnamgQkMCABNV87A1DNl1fzZdNw2QzA84D42T92/266cVM8KvxFIOrWP9804A1sibpWPC5RsByqBEojMCoGL7rootrpf/zjH+fOd77z2uvHHHPMpn0Cl5VbWwPQ/WDy7gfTNgezicea8avh2ga23/JquH552poEJDAgATVfOwNQzZdX82XTcNkMwNOBbYHY1f2TDe858ZxSPJN0VlW3YTWLjSGgeDQtJCCBtAQWKQZX4RHgTCfCxX6A224bH++eAjzLGyybeKyZgxpuluD2V0cN1x9LW5KABAYmoOZrZwCq+TwFuOlbNpsBGMcLxjGBT6kOA2kyjycBLwK+Bdy4SQXL1BJQPJocEpBAWgKLFIOrcAjIm970Jh7ykIesxTNO0o1fh+uuOPX3W9/6FjvttBMnn3zyJYoddNBBvPWtb137W5zsGyf8jrvitWtd61prL0WdI4444hLFou1TTjll7YThOBW47oqxPvCBD1x7Oebw13/911uKfve73+X617/+2r8POeSQtVOB6654/XWve93ay1Fvl112SZvb0wa2JAagGm5aIOf7uhpuvnxtXQISWCABNV87A1DNl1fzZdNw2QzAw4BHAqcAuwJnT7nP/AHw1Wrj4zcCBy/wvrSKXSkeVzGqzkkCK0JAMdhODIahF2ZbXA9/+MN5zWteMzYTfvKTn3DNa15z7bUHPOAB/Nu//dslyoWJFmZaXO94xzv48z//87HtxGtRP67DDz+cgw++5EdymHph7sU1yUiMsUb9uL75zW9e4iCVePT7Ote5Dj/60Y+48Y1vzNe//vXa7L7JTW6yZjRe+9rXXjMe41ToZb2yiccajmq4YRNMDTcsf3uXgAR6JKDmU/OtiubLpuGyqeHYz+8L1b3j40B8yzit5l6yPfCu6nHh2AzqtsCJPd53SmxK8Vhi1J2zBJaEwCLFYEYkbfcAjDnsuuuuaybZVa5ylTUT7ApXuMKmqb3whS/kaU972trf3/Wud3G/+93vEmXCIAwTLU7nvdvd7sYHP/jBsXj+5E/+hA996ENrpw2feuqpm1YKRtvr5uELXvACnvrUp25q55xzzlkz+E4//fS1sX/1q/Eb3yWvRz7ykVvMzM9+9rPstddem8ocd9xx7L333mt/j/KvetWrMoa08ZiyiceagavhGkd0LgXVcHPBaqMSkMAQBNR87QxANV9ezZdNw2UzACN3139BDlPv18Dbq/0Af1zdfGKZwr5APB908YZCEM/4PGKIm9OK9al4XLGAOh0JrBIBxWB7MTj6SMijHvUoDjssPmJ/f33nO9/h1re+Nb/+9a+5wQ1usGYWbr311pvSZvQx4COPPJL73ve+lygTf7v//e+/9rcHPehBhFm58frd7363tmovHseN/QC/8IUvbHmcd71sjPHVr3712j/f/OY38+AHP3hTO7GyMczBCy64gN1335046fnyl7/8lnLnnnsu++67LyeeeOLaXL72ta9xwxvecKnfCtnE4wSYarjhMk0NNxx7e5aABHomoOZT80VKrYLmy6bhMhqAcQpwbBx08QZAUHfU4/rYwyB8EHBhz/edEptTPJYYdecsgSUhUJoYPOqoozjrrDjf6uLrU5/6FG98Y+x2wdrefne4Q5yBdfEV+/LFCryNV5hkd7zjHfn0pz+99tJ97nMfHvawh3HlK1+Zz33uczz/+c8nDjyJVXvve9/7uPvd7z42G2L14G1ucxt+/vOfr5lqT3jCEzjggAPWyka9l73sZZx//vnssMMOa8ZerOIbd33gAx/gnve859pqwqtf/eo84xnPYM8991xb8ff617+ed7/73WvVYm5xmvNWW4Uk2HzFisVYuRjXbrvtxlOe8pQ1MzEMzRe96EV88YtfXHstyh166KFj21imP2YTjxPYqeGGSyw13HDs7VkCEuiZgJpPzbeeUsuu+bJpuIwG4HqsYylBHAayW8395PPV4R9H9Xy/Kbk5xWPJ0XfuEkhOoDQxeN3rXnfTgRx1IQqTLwyzcddpp53GPe5xD0444YSxr1/2spddWxn40Ic+dGIGHH/88dz73vcmHgked4UJ+Z73vIfb3jZ25Ki/wuh79KMfzXnnnTe2UBiC73//+9l++9jpY/wVBmIYmbHCse4KkzT2Lwxzc9mvbOKxAU81XANIPRdRw/UM1OYkIIHhCKj56tmr+Tazyaz5smm4zAbgemTjkd8wAde/CcSegLFP4PhvIMPdp1ahZ8XjKkTROWfqmCQAACAASURBVEhgRQkoBmcTg1ErVueF8RYHfMRjvmefffbaib13uctdeOxjH8tNb3rTRlkTZuIrXvGKNaPv+9///lqdOF33Xve6F4973OO46lWv2qidk046iVe+8pV89KMfXTvQ44pXvCJxaMdf/MVfrBmR4x5DHtdwrCgMky/MzRhbmIZ77LHH2qEldasZGw0wWaFs4rEFHjVcC1gdi6rhOgK0ugQkkIeAmk/Nt5HAsmq+bBpuGQzAPHei1R+J4nH1Y+wMJSABCUhgyQhkE49Lhq+U4arhSom085SABCQggaUhkE3DaQAuTeosZKCKx4VgthMJSEACEpBAcwLZxGPzkVtygQTUcAuEbVcSkIAEJCCBJgSyaTgNwCZRK6eM4rGcWDtTCUhAAhJYEgLZxOOSYCttmGq40iLufCUgAQlIID2BbBouqwEY47orsA9wPWAbYPxRgL8PeZwWvH/6DMg9QMVj7vg4OglIQAISKJBANvE4JQRquGFyVA03DHd7lYAEJCABCdQSyKbhMhqAcXzgW4AbtMijmEcYgNNMwhZNFllU8Vhk2J20BCQgAQlkJpBNPE5gpYYbLpHUcMOxt2cJSEACEpDAWALZNFw2A/CGwOeBKwIxtguAOGbwl8CFDXJq7wZlLFJPQPFodkhAAhKQgASSEcgmHmvwqOGGzRs13LD87V0CEpCABCSwiUA2DZfNAPxX4KDK7DsUeDlwunm0MAKKx4WhtiMJSEACEpBAMwLZxGPNqNVwzcI5r1JquHmRtV0JSEACEpDAjASyabhsBuAPgGsDhwGPnZGx1WYnoHicnZ01JSABCUhAAnMhkE081kxSDTeX6DduVA3XGJUFJSABCUhAAoshkE3DZTMAfwNcGrgj8KnFhMReRggoHk0HCUhAAhKQQDIC2cRjDR413LB5o4Yblr+9S0ACEpCABDYRyKbhshmAPwSuCewBfMH8WTgBxePCkduhBCQgAQlIYDKBbOKxZrRquGETWQ03LH97l4AEJCABCWgAtsyBdwH3AR4EvK1lXYt3J6B47M7QFiQgAQlIQAK9ElgSA1AN12vUWzemhmuNzAoSkIAEJCCB+RLIpuGyrQCMU3yPrVb/xf9vcvLvfCNWVuuKx7Li7WwlIAEJSGAJCGQTjzXI1HDD5pIablj+9i4BCUhAAhLYRCCbhstmAAawxwMvBf4TeAjwK/NoYQQUjwtDbUcSkIAEJCCBZgSyiccJo1bDNQvpPEqp4eZB1TYlIAEJSEACHQhk03DZDMAnV2zvBcQvyWcCRwPfAM5pwP3FDcpYpJ6A4tHskIAEJCABCSQjkE081uBRww2bN2q4YfnbuwQkIAEJSGATgWwaLpsBGI/8XjRj3kS9rWesa7WLCSgezQQJSEACEpBAMgLZxGMNHjXcsHmjhhuWv71LQAISkIAENABb5kDXPf8u1bI/i1+SgOLRjJCABCQgAQkkI7BEBmAXcmq4LvT8EbcbPWtLQAISkIAE5kAgm4bLtgLwsh2Z/7Zj/dKrawCWngHOXwISkIAE0hHIJh5rAKnhhs0cNdyw/O1dAhKQgAQksIlANg2XzQA0ZYYloHgclr+9S0ACEpCABNKLR0OUkoAaLmVYHJQEJCABCZRMQAOw5Ojnn7viMX+MHKEEJCABCRRGIJt4LAz/skxXDbcskXKcEpCABCRQDIFsGs4VgMWkXqOJKh4bYbKQBCQgAQlIYHEEsonHxc3cnloQUMO1gGVRCUhAAhKQwCIIZNNwmQ3A2wMPBvYGrgFcHrgN8I2RQN0OuDFwJnDkIgK44n0oHlc8wE5PAhKQgASWj0A28diAoBquAaSei6jhegZqcxKQgAQkIIGuBLJpuIwG4OWANwAPqGCvj/Ei4ObA10aCcEfgGCBeuyHw3a4BKry+4rHwBHD6EpCABCSQj0A28TiBkBpuuPRRww3H3p4lIAEJSEACYwlk03AZDcD/AO4FxNi+DHwSeHRl8m00AAPyV6tVgE8DXmzedSKgeOyEz8oSkIAEJCCB/glkE48TZqiG6z/8TVtUwzUlZTkJSEACEpDAgghk03DZDMAw/v6zMvseCxxWxeXCCQbg84BnAB8E7rGgOK5qN4rHVY2s85KABCQggaUlkE081oBUww2bYWq4YfnbuwQkIAEJSGATgWwaLpsB+B7gT4F3AA8coTfJAIzyUe8HwHXNuU4EFI+d8FlZAhKQgAQk0D+BbOKxZoZquP5D36ZFNVwbWpaVgAQkIAEJLIBANg2XzQA8tTrwI0y99zc0AHcHPgecC1xxATFc5S62iMdnvf0TbLdDnL3S//X4/W7Uf6O2KAEJSEACElhRAtnEYw1mNdyw+acBOCx/e5eABCQgAQlsIpBNw2UzAH8DXLo67fdLDQ3AWwMnAr+tTgo27WYnoAE4OztrSkACEpCABOZCIJt4rJmkGm4u0W/cqAZgY1QWlIAEJCABCSyGQDYNl80A/DlwFeAA4OiGBuCfAe8G4pfnHRcTxpXtRQNwZUPrxCQgAQlIYFkJZBOPNRzVcMMmmAbgsPztXQISkIAEJLCJQDYNl80A/AxwW2Djib6T9gD8V+Ag4AOVcWjazU5AA3B2dtaUgAQkIAEJzIVANvFYM0k13Fyi37hRDcDGqCwoAQlIQAISWAyBbBoumwEYp/nGqb4/Aq4HnFeFpc4A3As4FtgKeBTw2sWEcWV70QBc2dA6MQlIQAISWFYC2cRjDUc13LAJpgE4LH97l4AEJCABCWwikE3DZTMAtwO+A8T//hfwYODXwEYDMMb9l8ArqrLx+O8Nqn0ATbvZCWgAzs7OmhKQgAQkIIG5EMgmHmsmqYabS/QbN6oB2BiVBSUgAQlIQAKLIZBNw2UzACMKfwL8d7Wq7yzgo8C9gYuA91SHhMRjwtsDMf5YJXgX4NOLCeFK96IBuNLhdXISkIAEJLCMBLKJxwkM1XDDJZgG4HDs7VkCEpCABCQwlkA2DZfRAAxwdwbeClyrohjm3+i1Pu6fAH8OfNJ864WABmAvGG1EAhKQgAQk0B+BbOJxyszUcP2Fvk1LGoBtaFlWAhKQgAQksAAC2TRcVgMwQnFZ4K+APwV2r1b8xV5/pwNfrFYJvgE4dwFxK6ULDcBSIu08JSABCUhgaQhkE48NwKnhGkDquYgGYM9AbU4CEpCABCTQlUA2DZfZABzHOsa7cTVg15hY//cENADNBglIQAISkEAyAtnE44x41HAzgmtYTQOwISiLSUACEpCABBZFIJuGWzYDcFFxKrUfDcBSI++8JSABCUggLYFs4jEtqLIHpgFYdvydvQQkIAEJJCSQTcNpACZMkgGHpAE4IHy7loAEJCABCYwjkE08GqWUBDQAU4bFQUlAAhKQQMkEsmk4DcCSs3Hz3DUAzQcJSEACEpBAMgLZxGMyPA7nYgIagGaCBCQgAQlIIBmBbBoumwF4Tod4xd6AV+xQ36oj4vFZb/8E2+1wjbkwefx+N5pLuzYqAQlIQAISWEUC2cRjDWM13LDJpwE4LH97l4AEJCABCWwikE3DZTMAL+yQM2EAxinBXrMTcAXg7OysKQEJSEACEpgLgWzisWaSari5RL9xoxqAjVFZUAISkIAEJLAYAtk0XDYD8AUNwhCr/GIJ2Z2ASwPHA5+o6j2tQX2L1BPQADQ7JCABCUhAAskIZBOPNXjUcMPmjQbgsPztXQISkIAEJLCJQDYNl80AbJMy8Xzqm4D9gEcCr29TecayOwOPAfYHdgR+C3wHeBfwKqDL4y91Q7oCcBKwS1XgZOC6M45/WjUNwGmEfF0CEpCABCSwYALZxGMP01fD9QBxQxMagP0ztUUJSEACEpBAJwLZNNwyG4ARiFgBeCJwY+B2wOc7RWdy5XsCbwO2rSn2rcoY/HbPY3gp8ISRNjUAewZscxKQgAQkIIHMBLKJx55YqeF6Alk1owHYL09bk4AEJCABCXQmkE3DLbsBGAH5G+ANwDuAB3aO0PgGdgM+DVweOAuIx1yOqf59IPCwqlqYgLsDZ/Y0juj3BOB31X/bABqAPcG1GQlIQAISkMAyEMgmHntkpobrD6YGYH8sbUkCEpCABCTQC4FsGm4VDMDbVCbZqdVjub0EakMjxwL7AOcD+wKf3fD6k4AXV397LvCcHgYRB5rE/oYxv2cBDwHiEWQNwB7g2oQEJCABCUhgWQhkE489clPD9QdTA7A/lrYkAQlIQAIS6IVANg23CgZgPPr7KeA84HK9ROmSjexZGXHx18OBh4/p41LVPn03Ac4Arlat2OsynL8DXgZ8E7gFEKsLNQC7ELWuBCQgAQlIYAkJZBOPPSJUw/UHUwOwP5a2JAEJSEACEuiFQDYNtwoG4AuBJwM/Bq7dS5Qu2cihwPrpwnuNmIEbu3pq9Whw/P1uwIc7jCWMvq8CceLxnYGPA9/XAOxA1KoSkIAEJCCBJSWQTTz2iFEN1x9MDcD+WNqSBCQgAQlIoBcC2TTcMhuAlwUeAbwEiBV4/wb8VS9RumQj64//ng1sVz0GPK6bvYHPVC88D3h2h7G8H7gH8FbgoKodDcAOQK0qAQlIQAISWFYC2cRjDxzVcD1A3NCEBmD/TG1RAhKQgAQk0IlANg2XzQD8QAO6YfZdGdgVuAIQczgH2AP4eoP6bYv8HNge+DJwqwmVY0y/rF4/Erh/246q8nGoyL8DpwN/CET/cWkAzgjUahKQgAQkIIFlJpBNPNawVMNBCg13yimncJ3rhB/oJQEJSEACEpDAkASyabhsBuCFwEUNAjQ67h9VK//iVN6+r9hT8Nyq0ViVd8CUDuKE4Hhs9zggVgS2vcJEDBPz6sAhwOtGGujDAJymBq9RHajCs97+CbbbIf7Z//X4/W7Uf6O2KAEJSEACElhRAtnEYw1mNVwSDacBuKI3AqclAQlIQAJLRyCbhstmAIZxNs0ADIF5JvA94BPAe4DfzCkTdgB+VrX9Ti7+ZXfS9dPqAJCTgJvPMKY3VKf9xinDt9/Aog8DcBrbLUPWAJwhelaRgAQkIAEJzIFANvFYM0U1HDwEGFzDaQDO4U1okxKQgAQkIIEZCGTTcNkMwBmQzrXKjsAPqh5G9+Or6zTKRp3vADdoObJ9q8M+LgBuA/zvhvoagC2BWlwCEpCABCSwCgSyicclYVqshtMAXJIMdZgSkIAEJLDyBLJpOA3AySm3qBWAsRl27DEYe/69DHjimGH1YQD6CPDK32KcoAQkIAEJrBqBbOJxSfgWq+E0AJckQx2mBCQgAQmsPIFsGk4DcHLKLWoPwDg1+JnAKcBNgDhxeOPVhwE47Q225QQ5HwGehsrXJSABCUhAAoshkE08LmbWnXspVsNpAHbOHRuQgAQkIAEJ9EIgm4bTAJwe1tOAq875FODfApcB3gx8uGZI/1KdRhzj+duqTOxP+LHpU2hcQgOwMSoLSkACEpCABBZDIJt4XMyse+mlSA2nAdhL7tiIBCQgAQlIoDOBbBoumwF4/86Exzfwrg7tHgvsU63K2w44v6atOPX3M9VrsaLv2S36bHw4x4Y24xCUO7XoZ1pRDcBphHxdAhKQgAQksGAC2cRjzfTVcO3yYm4aTgOwXSAsLQEJSEACEpgXgWwaLpsBGCf8zmqG1cUs2tu6Q0APBZ5W1d8LOL6mracCL6heu9uElXzjqs8657mJRx8B7pAxVpWABCQgAQn0SCCbeKyZmhquXcznpuE0ANsFwtISkIAEJCCBeRHIpuEyGoB9sw9zbasOje45YvodDjx8TFuXAk6q9u87A7ga8LsOfY6r6h6APQO1OQlIQAISkMAyEMgmHicYgH3jVMM1J7rlKQ4NwObQLCkBCUhAAhKYJ4FsGi6bARin4G4LHAbsAfwf8Bbgc8BPq8BcvXrtIOBGwAnAo4FfTwjcNzsGdf0x4Hj8d1/gsxvaexLw4upvzwWes+H1eEz3mOpvRwAPnmE8GoAzQLOKBCQgAQlIYNkJZBOPNTzVcPWJtlANpwG47O94xy8BCUhAAqtCIJuGy2YAXhoIsy1W3cXjtLGP3gU1wY9VfWG0/T1wXGXM1e3P1zV/dgM+DVweOAuIx4LD0It/HwgcXHXwLWB34EwNwHrkj98vfFsvCUhAAhKQgASaEMgmHmvGrIbTAGySzpaRgAQkIAEJFEMgm4bLZgA+Dvgn4D+A+zbMiqOAPwOeCLy8YZ1Zit0TeFu1QnFc/TD/9ge+PeZFVwCOQNEAnCX9rCMBCUhAAqUSyCYea+KghtMALPUt6rwlIAEJSEACYwlk03DZDMB4nPfWwAHA0Q1z6O7A+4HPV48GN6w2U7GdgcdWRl/stXJeZfgdWT22fE5NqxqAGoAzJZyVJCABCUhAAtnEY01E1HAagL5ZJSABCUhAAhIYIZBNw2UzAE+vVtjdBvhSw8yJx3PD/PsVcOWGdSw2nsCWDaQ9BdgUkYAEJCABCeQgkE081lBRww2bLh4CMix/e5eABCQgAQlsIpBNw2UzAOMgjysCfw7Eo71NrnhU+F3V3nxxgIjX7AQ0AGdnZ00JSEACEpDAXAhkE481k1TDzSX6jRvVAGyMyoISkIAEJCCBxRDIpuGyGYBx2m+s/osDN+K03WlXjD8ODbn9gh4BnjaeZX9dA3DZI+j4JSABCUhg5QhkE481gNVww2aeBuCw/O1dAhKQgAQksIlANg2XzQB8DPDPwEXVQSAPB35Rk0dXAV5bHRYS5R8PvNKc60RAA7ATPitLQAISkIAE+ieQTTzWzFAN13/o27SoAdiGlmUlIAEJSEACCyCQTcNlMwC3Aj4F3LYyAeNQjTjgIzaW/ln1t6tXh33co3pcOOYQvzrHKsALFhDDVe5CA3CVo+vcJCABCUhgKQlkE481ENVww2aXBuCw/O1dAhKQgAQksIlANg2XzQAMYLGPX+zpd9eKXqzuG3etj/0jwP2rQ0BMuW4ENAC78bO2BCQgAQlIoHcC2cTjhAmq4XqPfuMGNQAbo7KgBCQgAQlIYDEEsmm4jAbgeiTuAzwCuANwmQ3h+V21UvA1LQ4LWUyEl7sXDcDljp+jl4AEJCCBFSSQTTw2QKyGawCp5yIagD0DtTkJSEACEpBAVwLZNFxmA3CddZh/fwjEnn9xnQ58E/ht12BYfxMBDUCTQgISkIAEJJCMQDbx2AKPGq4FrI5FNQA7ArS6BCQgAQlIoG8C2TTcMhiAfcfA9uoJaACaHRKQgAQkIIFkBLKJx2R4HM7FBDQAzQQJSEACEpBAMgLZNJwGYLIEGXg4GoADB8DuJSABCUhAAhsJZBOPRiglAQ3AlGFxUBKQgAQkUDKBbBouswF4ReDewN7ANYArAIcAp4wk0A7ANtXjwKeWnFg9zV0DsCeQNiMBCUhAAhLoi0A28dhgXmq4BpB6LqIB2DNQm5OABCQgAQl0JZBNw2U1AB8KvAjYrgIe44zTgG8OfG0kCAcBbwZ+A1wbOKNrgAqvrwFYeAI4fQlIQAISyEcgm3icQkgNN0wKaQAOw91eJSABCUhAArUEsmm4jAbg04HnAzG284FvADerMQC3AmLlX6wEPBh4o7nXiYAGYCd8VpaABCQgAQn0TyCbeJwwQzVc/+Fv2qIGYFNSlpOABCQgAQksiEA2DZfNALwl8IUqFkcBjwJOAy6sMQCj6GHAI4F3AQcuKI6r2o0G4KpG1nlJQAISkMDSEsgmHmtAquGGzTANwGH527sEJCABCUhgE4FsGi6bARgr+P4aOB64XWX6BcRJBuADgLdXKwV3Nec6EdAA7ITPyhKQgAQkIIH+CWQTjzUzVMP1H/o2LWoAtqFlWQlIQAISkMACCGTTcNkMwG8DuwCxt1+YeuvXJAMwDgn5NHAmcKUFxHCVu1iIAbgIgI/f70aL6MY+JCABCUhAAnMnkE081kxYDTf3TJjYgQbgsPztXQISkIAEJLCJQDYNl80APAe4LLA78MWGBmA8chJlf1fVNe1mJ6ABODs7a0pAAhKQgATmQiCbeKyZpBpuLtFv3KgGYGNUFpSABCQgAQkshkA2DZfNAIxTfLcB7gJ8vKEBuB/wIeDnwNUXE8aV7UUDcGVD68QkIAEJSGBZCWQTjzUc1XDDJpgG4LD87V0CEpCABCSwiUA2DZfNAPwKEPv4HQK8oaEB+ALgKcBngDuYc50IaAB2wmdlCUhAAhKQQP8EsonHmhmq4foPfZsWNQDb0LKsBCQgAQlIYAEEsmm4bAbgK4C/BU4E9mxgAF4D+CqwHfA84LkLiOEqd6EBuMrRdW4SkIAEJLCUBLKJxxqIarhhs0sDcFj+9i4BCUhAAhLYRCCbhstmAMbJDScBWwFPA15cERx3CEgcFvIfQOwBeC5wPeCn5lwnAhqAnfBZWQISkIAEJNA/gWzisWaGarj+Q9+mRQ3ANrQsKwEJSEACElgAgWwaLpsBGCH4e+D5wEXAp4B3A/9c/TteOw+4PbA/cOkqZo8GXrOA+K16FxqAqx5h5ycBCUhAAktHIJt4nABQDTdcdmkADsfeniUgAQlIQAJjCWTTcBkNwAD3TOBZ1UrAMALHXTH2WBkYYvNF5lsvBDQAe8FoIxKQgAQkIIH+CGQTj1NmpobrL/RtWtIAbEPLshKQgAQkIIEFEMim4bIagBGKeLT3ycA9gCttiM051cm/hwKfX0DcSulCA7CUSDtPCUhAAhJYGgLZxGMDcGq4BpB6LqIB2DNQm5OABCQgAQl0JZBNw2U2ANdZxxhvCFytWhH4C+CbwO+6BsP6mwhoAJoUEpCABCQggWQEsonHFnjUcC1gdSyqAdgRoNUlIAEJSEACfRPIpuGyGYBh8sUVh3qc2Td825tKQANwKiILSEACEpCABBZLIJt4rJm9Gm6xabGxNw3AYfnbuwQkIAEJSGATgWwaLpsBuH7a7+OAfzF/Fk5AA3DhyO1QAhKQgAQkMJlANvFYM1o13LCJrAE4LH97l4AEJCABCWgAtsyBs4HLAXsDn2tZ1+LdCWgAdmdoCxKQgAQkIIFeCSyJAaiG6zXqrRvTAGyNzAoSkIAEJCCB+RLIpuGyrQD8P+B6wO2B4+YbClsfQ0AD0LSQgAQkIAEJJCOQTTzW4FHDDZs3GoDD8rd3CUhAAhKQwCYC2TRcNgPwNcDBwBOBl5s/CyegAbhw5HYoAQlIQAISmEwgm3isGa0abthE1gAclr+9S0ACEpCABDQAW+bATYDPA2cAuwE/bVnf4t0IaAB242dtCUhAAhKQQO8ElsQAVMP1HvlWDWoAtsJlYQlIQAISkMD8CWTTcNlWAEYE7gscUZl/sRLwv4AL5h8aewA0AE0DCUhAAhKQQDIC2cTjBDxquOFyRwNwOPb2LAEJSEACEhhLIJuGy2YAfqCidgMg/rsIOAf4OnD6FCMwyu5v3nUioAHYCZ+VJSABCUhAAv0TyCYea2aohus/9G1a1ABsQ8uyEpCABCQggQUQyKbhshmAF1amX4Ri49jC4Ku7omy8vtUCYrjKXWgArnJ0nZsEJCABCSwlgWzisQaiGm7Y7NIAHJa/vUtAAhKQgAQ2Ecim4bIZgHHy7ySjb1pK7T2tgK9PJKABaIJIQAISkIAEkhHIJh5r8Kjhhs0bDcBh+du7BCQgAQlIQAPQHFgqAhqASxUuBysBCUhAAiUQWBIDsIRQZJ6jBmDm6Dg2CUhAAhIokkA2DZdtBWCRSZFo0hqAiYLhUCQgAQlIQAJBIJt4NCopCWgApgyLg5KABCQggZIJZNNwGoAlZ+PmuWsAmg8SkIAEJCCBZASyicdkeBzOxQQ0AM0ECUhAAhKQQDIC2TTckAbgTlVsTp1yum+yEK70cDQAVzq8Tk4CEpCABJaRQDbxCKjh8iWSBmC+mDgiCUhAAhIonEA2DTekARinxcV/twC+NiYvrgDsXv392MLzZlHT1wBcFGn7kYAEJCABCTQkkE08VvpNDdcwfgsqpgG4INB2IwEJSEACEmhKIJuGG9oAjBN/b15jAN4U+EolMrduCthynQhoAHbCZ2UJSEACEpBA/wSyicdKm6nh+g91lxY1ALvQs64EJCABCUhgDgSyabhlMABDYG41h1jY5GYCGoBmhQQkIAEJSCAZgWzisYUBqIZbXC5pAC6OtT1JQAISkIAEGhHIpuE0ABuFrZhCGoDFhNqJSkACEpDAshDIJh41AFNmjgZgyrA4KAlIQAISKJlANg2nAVhyNm6euwag+SABCUhAAhJIRiCbeNQATJYgFw9HAzBlWByUBCQgAQmUTCCbhtMALDkbNQCNvgQkIAEJSCA9gWziUQMwZcpoAKYMi4OSgAQkIIGSCWTTcBqAJWejBqDRl4AEJCABCaQnkE08agCmTBkNwJRhcVASkIAEJFAygWwaTgOw5GzUADT6EpCABCQggfQEsolHDcCUKaMBmDIsDkoCEpCABEomkE3DZTAA/wb43pik2AV4MxAnyN0JaDLWY0tOrh7m7h6APUC0CQlIQAISkECfBLKJxxEDUA3XZ6C7taUB2I2ftSUgAQlIQAK9E8im4ZqYar1DqBq8sDL3+mo/jMKt+2qs0HY0AAsNvNOWgAQkIIG8BLKJxxEDsC9oarjuJDUAuzO0BQlIQAISkECvBLJpuKENwD7hhnjcqs8GC2xLA7DAoDtlCUhAAhLITSCbeKwMwD6hqeG609QA7M7QFiQgAQlIQAK9Esim4YY0AJ/dK9mLG3vuHNosqUkNwJKi7VwlIAEJSGApCGQTj4AaLl/maADmi4kjkoAEJCCBwglk03BDGoCFp0LK6WsApgyLg5KABCQggZIJZBOPJcci8dw1ABMHx6FJQAISkECZBLJpOA3AMvOwbtYagOaDBCQgAQlIIBmBbOIxGR6HczEBDUAzQQISkIAEJJCMQDYNpwGYLEEGHo4G4MABsHsJSEACEpDARgLZxKMRSklAAzBlWByUBCQgAQmUTCCbhtMALDkbN89dA9B8kIAEJCABCSQjkE08xitohAAAIABJREFUJsPjcC4moAFoJkhAAhKQgASSEcim4TQAkyXIwMPRABw4AHYvAQlIQAIS2Eggm3g0QikJaACmDIuDkoAEJCCBkglk03AagCVn4+a5awCaDxKQgAQkIIFkBLKJx2R4HM7FBDQAzQQJSEACEpBAMgLZNJwGYLIEGXg4GoADB8DuJSABCUhAAhsJZBOPRiglAQ3AlGFxUBKQgAQkUDKBbBpOA7DkbNw8dw1A80ECEpCABCSQjEA28ZgMj8O5mIAGoJkgAQlIQAISSEYgm4bTAEyWIAMPRwNw4ADYvQQkIAEJSGAjgWzi0QilJKABmDIsDkoCEpCABEomkE3DaQCWnI2b564BaD5IQAISkIAEkhHIJh6T4XE4FxPQADQTJCABCUhAAskIZNNwGoDJEmTg4ayMAThvjo/f70bz7sL2JSABCUhAAmsEsolHw5KSgAZgyrA4KAlIQAISKJlANg2nAVhyNm6euwZgw3zQAGwIymISkIAEJNCZQDbx2HlCNjAPAhqA86BqmxKQgAQkIIEOBLJpOA3ADsFcwaoagA2DqgHYEJTFJCABCUigM4Fs4rHzhGxgHgQ0AOdB1TYlIAEJSEACHQhk03BDGYAHdWA4qepb5tRuKc1qADaMtAZgQ1AWk4AEJCCBzgSSiUc1XOeIzqUBDcC5YLVRCUhAAhKQwOwEkmk4hjIALwQumh3j2JrR3tY9t1lacxqADSOuAdgQlMUkIAEJSKAzgWTiUQ3XOaJzaUADcC5YbVQCEpCABCQwO4FkGm5QA3B2iuNrhgG4Vd+NFtaeBmDDgGsANgRlMQlIQAIS6EwgmXgMA7DvSw3XnagGYHeGtiABCUhAAhLolUAyDTeYAbjzBKpXBg4H9gBOAo4APgf8tKpz9eq1BwE3B04ADgFOB07uNVrlNaYB2DDmGoANQVlMAhKQgAQ6E0gmHtVwnSM6lwY0AOeC1UYlIAEJSEACsxNIpuEGMwDrCF4G+AywG/Bs4B8nPCocjy8/HXg+8Hng9sB5s4fGmoAGYMM00ABsCMpiEpCABCTQmUA28VgzITVc50h3akADsBM+K0tAAhKQgAT6J5BNww21B2Ad2ScALwHeBRzYEP87gPsBT63qNqxmsTEENAAbpoUGYENQFpOABCQggc4EsonHmgmp4TpHulMDGoCd8FlZAhKQgAQk0D+BbBoumwEYK/luBewPfLAh/rsBRwNfBG7TsI7FxhPQAGyYGRqADUFZTAISkIAEOhPIJh5rJqSG6xzpTg1oAHbCZ2UJSEACEpBA/wSyabhsBuAZwDbA7pWh1yQC8bhwiM5fA9s1qWCZWgIagA2TQwOwISiLSUACEpBAZwLZxGPNhNRwnSPdqQENwE74rCwBCUhAAhLon0A2DZfNAPwV8AfAA6rHgJtE4P5APAZ8JnClJhUsowHYNQc0ALsStL4EJCABCTQlkE081oxbDdc0oPMppwE4H662KgEJSEACEpiZQDYNl80APK464fd44A7AhVNIXwr4NHDb6qTgvWaOjBWDgCsAG+aBBmBDUBaTgAQkIIHOBLKJx5oJqeE6R7pTAxqAnfBZWQISkIAEJNA/gWwaLpsB+EjgsOrk3/cDBwM/qQnD1YHDgT+tyv8t8Or+Q1ZUixqADcOtAdgQlMUkIAEJSKAzgWzisWZCarjOke7UgAZgJ3xWloAEJCABCfRPIJuGy2YAxoq+j1er/y4Cfgt8GDgB+Fll9IXxtwdwV+CyQMzhU8CdGqwY7D+iq9WiBmDDeGoANgRlMQlIQAIS6Ewgm3ismZAarnOkOzWgAdgJn5UlIAEJSEAC/RPIpuGyGYBB/IrA26uVffHvMALHXetjfy/wF8BZ/YeruBY1ABuGXAOwISiLSUACEpBAZwLZxOOECanhOkd75gY0AGdGZ0UJSEACEpDAfAhk03AZDcB18vsDj6hW9l1hQzjOrVYKvgZ433xCVWSrGoANw64B2BCUxSQgAQlIoDOBbOKxwYTUcA0g9VxEA7BnoDYnAQlIQAIS6Eogm4bLbACus45HSq4PXKX6w+nAd4ALugbD+psIaAA2TAoNwIagLCYBCUhAAp0JZBOPLSakhmsBq2NRDcCOAK0uAQlIQAIS6JtANg23DAZg3zGwvXoCGoANs0MDsCEoi0lAAhKQQGcC2cRj5wnZwDwIaADOg6ptSkACEpCABDoQyKbhNAA7BHMFq2oANgyqBmBDUBaTgAQkIIHOBLKJx84TsoF5ENAAnAdV25SABCQgAQl0IJBNw2U2AK8E3BfYG7gGEPsA/jVw8gj/awHbAb8BvtshLk2r7gw8Boi9bXasTimOx5HfBbwKOKdpQ2PKxfz+BNgP2B24AfAHwK+BbwEfAl4L/KRDH9OqagBOI1S9rgHYEJTFJCABCUigM4Fs4rHBhNRwA2q4U045hetcJySdlwQkIAEJSEACQxLIpuGyGoCPBv6xMsAiXjHOOA345sDXRgL4QOBtlQEYSueXcwzuPau+tq3pI0y6MAa/PcMYbgF8emS+dU2EGXgw8M4Z+mhSRQOwCSVAA7AhKItJQAISkEBnAtnE45QJqeHGA1qYhtMA7PyWswEJSEACEpBALwSyabiMBuBzgWdUpt9vga9UK+LGGYCxufQPgasDDwde30uUNjeyW2XQXR44C3gBcAwQ/z4QeFhVJUzAWL13Zstx3AH4ZFUnjMA42fhE4BfADsD/q/qI+cbhJ2FGHt2yjybFNQCbUFpQGU3GBYG2GwlIQALJCWQTjxNwqeESaDgNwORvaIcnAQlIQALFEMim4bIZgLcBPldlw9uBvwV+BVxYswIwir6iKncUcP85ZdKxwD7A+cC+wGc39PMk4MXV30L8PqflOG4HPBaIuqMrHEebuRfwn5UxGo8d37Bi0rKricU1APuk2bEtDcCOAK0uAQlIYEUIZBOPNVjVcEk0nAbgirzxnYYEJCABCSw9gWwaLpsB+GbgQcBngFgVt35NMgBjBd6/Ad8EbjKHDNkTOL5q9/BqpeHGbmJl3klV/2cAVwN+N4exhMl5n6rdENpf6LkPDcCegXZpTgOwCz3rSkACElgdAtnEYw1ZNdzklFuYhtMAXJ33vjORgAQkIIHlJpBNw2UzAGNl23WBvwDe0dAA3KsyDOPR3Lr9+bpkzaHA06oGoq91M3Bjm0+tHg2Ov98N+HCXTmvqPgo4rHotVjse2XMfGoA9A+3SnAZgF3rWlYAEJLA6BLKJxxqyarjJKbcwDacBuDrvfWciAQlIQALLTSCbhstmAMYpupet9tH7YkMD8FbVSrhYcRd1+77WH/89uzpxOB4DHnfFacWxcjGu5wHP7nsgwN8BL6vajZWA/9FzHxqAPQPt0pwGYBd61pWABCSwOgSyiccasmq4ySm3MA2nAbg6731nIgEJSEACy00gm4bLZgDG47PbAH9cHbKxHu1JjwDHars4EOPn1WEgfWdItLs98GUgzMa668ojpxDHyrx57Ef4X8CfVgPYFfh6z5PVAOwZaJfmNAC70LOuBCQggdUhkE081pBVw01OuYVpOA3A1XnvOxMJSEACElhuAtk0XDYD8H+BmwKPAF43EupJBuCLgDiE41PVAR19ZsjlgHOrBt8PHDCl8XgM+YrAcUCsCOzzuiXweWCr6mTkW8zQeBh8k65rACdEgWe9/RNst0P802soAhqAQ5G3XwlIQAK5CGQTjzV01HD1abNQDacBmOv962gkIAEJSKBcAtk0XDYD8OXVabhfAm49kiZ1BuC1q8M3Yu+/eOT2H3pOrR2An1VtvhOIA0cmXT+tDgCJA0Fu3uNY4tHmMDh3r9qMVYDvnaH9i5rW0QBsSmp+5TQA58fWliUgAQksE4Fs4rGGnRpuPJiFazgNwGV6dztWCUhAAhJYZQLZNFw2A/D6wNeArYHnAM+vkmGcAfiHQJyoFisGY3++61WPAfeZPzsCP6gafCtw0JTGo2zUiY2wb9DjQF4PPLRq7wjgwTO2rQE4I7ghqmkADkHdPiUgAQnkI5BNPNYQUsONB7NwDacBmO897IgkIAEJSKBMAtk0XDYDMLLiicCLgTCr4nHUOOjihdW/43CNOOzj9sBdgUtVaXQw8MY5pFSGFYBxAnGcRBxX8LhzZXjOMl0fAZ6F2kB1NAAHAm+3EpCABJIRyCYeJ+BRw10SziAaTgMw2RvY4UhAAhKQQLEEsmm4jAZgJEfs6ReP8166Mv7GJUyM/YLKMHzFnDJq6D0ADwFeW83tG8A+wGlzmms06yEgc4TbtmkNwLbELC8BCUhgNQlkE49TKKvhLgY0mIbTAFzN+4CzkoAEJCCB5SOQTcNlNQAjsjepzL04eCNW4o1evwI+ALyg2gNwnpkQhttVBzgF+AHA26pVjicDdwB+OM+JagDOmW7L5jUAWwKzuAQkIIEVJZBNPDbArIYbUMNpADbIUItIQAISkIAEFkAgm4bLbACOhmOn6nCNOAH3F8B3gdgXcBHXsdXKu9hncDvg/JpO49Tfz1SvxaPKcSjJrFcc8vHuai/EH1f9x76C875cAThvwi3a1wBsAcuiEpCABFaYQDbx2BK1Gu7ivaHnfW3RcBqA80Zt+xKQgAQkIIFmBLJpuGUxAJvRnU+p2H8v9nCJay/g+JpunlqtSIyX7wZ8eMbh3AV4PxCnxoXZeUfgqzO21baaBmBbYnMsrwE4R7g2LQEJSGCJCGQTj0uErkgNpwG4RBnqUCUgAQlIYKUJZNNwGoDT023PEdPvcODhY6rEYSQnVY8tn1GtVozDStpet6uMwysC8ZhzmIGfb9tIh/IagB3g9V1VA7BvorYnAQlIYDkJZBOPS0SxSA2nAbhEGepQJSABCUhgpQlk03AagM3Sbf0x4Hj8d1/gsxuqxYbXcXJxXM8FnrPh9TsBx1R/OwJ48Jhub1WViceM43HjWEX46WbD662UBmBvKLs3pAHYnaEtSEACElgFAtnE45IxLU7DaQAuWYY6XAlIQAISWFkC2TRcVgNwe+Avqr3vrgdsA8T+f5Oui4DrzylzdqvMuMsDZwHxSEkYevHvA4GDq36/BewOnNnSAIxxx/6BV6vqPR74nylz+RkQ//V5aQD2SbNjWxqAHQFaXQISkMCKEMgmHqdgVcMNrOE0AFfkje80JCABCUhg6Qlk03AZDcA4/fY1lekXAW86xjAAp5mEXRLontWpvNvWNBLm3/7At8e8Pm0FYKwIfHPLwY1badiyiU3FNQC7EuyxvgZgjzBtSgISkMASE8gmHiegVMM1y7O5ajgNwGZBsJQEJCABCUhg3gSyabim5tq8uay3/0fAR0ZMv5OB/wViX70mp/7+9ZwHujPw2MroC7PsvMrwOxI4DDinpn8NwDkHZhWb1wBcxag6JwlIQALtCWQTjzUzUMM1D60GYHNWlpSABCQgAQksLYFsGi6bARgn5/5xZfjFI8BHL22kl3PgrgBMFDcNwETBcCgSkIAEBiSQTTzWoFDDDZgjwBYN5wrAYQNh7xKQgAQkIIF1Atk0XDYD8HQgHrF9HPAvps3CCWgALhx5fYcagImC4VAkIAEJDEggm3isQaGGGzBHNACHhW/vEpBAPwRe/pHYVWuYy+9ew3Bf9V6zabhsBuCvgD8A9gC+sOrJkHB+GoCJguKHUKJgOBQJSEACAxLIJh5rUKjhBswRDcBh4du7BCTQDwENwH442koeAtk0XDYDMEy/WwKxZ94n84StmJFoACYKtQZgomA4FAlIQAIDEsgmHmtQqOEGzBENwGHgD2VWlKgRh2IdmVUi72HeUVBinEuc81D5NUS/2TRcNgPwycALgUOBZwwRoML71ABMlACKjUTBcCgSkIAEBiSQTTzWoFDDDZgjGoDDwB/qi3uJGnEo1hqAi31vDRnnxc40R28l3ksWTT6bhstmAMbjv8cB161WAZ646AAV3p8GYKIE8IacKBgORQISkMCABLKJxxoUargBc0QDcBj4Q5kVJWrEoVgPaQA652He1/Y6fwIl3cOyabhsBmBk207AfwC7Ai8H3gnEbqC/mX8qFt+DBmCiFCjpxpgIu0ORgAQkkI5ANvE4AZAabrjsKfYU4CFNkqHCXaJGHDLOQ/F2zkO9w+x33gSGek/Ne17j2s+m4TIagMHtpsDHgO1bBOkiYOsW5S26mYAGYEFZUdKNt6CwOlUJSGAFCWQTj1MQq+GGyUENwGG4F9frUPpxSDOsuCAPuO+hcS4j24a6jwxBN5uGy2gAPhZ4KXApoM34wgDcaoigrlCfGoArFMxpUynpxjuNha9LQAISyEwgm3icwEoNN1wiaQAOx76onofSjxpDi00z47xY3qX1NlR+DcE5m4ZrY7Atgtc9gPdVHV0IfAr4MnAGEP+edj13WgFfn0hAA7CgBCnpxltQWJ2qBCSwggSyiccaxGq4YXNPA3BY/sX0PpR+1ABcbIoZ58XyLq23ofJrCM7ZNFw2A/AY4I7AqUAIya8MEaSC+9QALCj4Jd14CwqrU5WABFaQQDbxWINYDTds7mkADsvf3iWwUgSG+p6g0btSaVQ7maHyawi62TRcNgPwF8B2wEOBNw8RoML71AAsKAFKuvEWFFanKgEJrCCBbOKxBrEabtjc0wAclr+9S0ACEpBAQwIlfQ/NpuGyGYDxqO82wO7AFxvmj8X6I6AB2B/L9C2VdONNHwwHKAEJSGACgWzisWaoarhhs1gDcFj+9i4BCUhAAg0JlPQ9NJuGy2YAngDcGtivOgW4YQpZrCcCGoA9gVyGZkq68S5DPByjBCQggToC2cRjzTjVcMOmsAbgsPztXQISkIAEGhIo6XtoNg2XzQD8u+oE4MOAxzTMH4v1R0ADsD+W6Vsq6cabPhgOUAISkMAEAtnEY81Q1XDDZrEG4LD87V0CEpCABBoSKOl7aDYNl80AvDTwSWA34L7AexvmkMX6IaAB2A/HpWilpBvvUgTEQUpAAhKoIZBNPNYMUw03bAZrAA7L394lIAEJSKAhgZK+h2bTcNkMwJ2AKwGvA/YA3ln99y3gnAb59IMGZSxST0ADsKDsKOnGW1BYnaoEJLCCBLKJxxrEarhhc08DcFj+9i4BCUhAAg0JlPQ9NJuGy2YAXghcVOVNjG39/zdJpSi7dZOClqkloAFYUHKUdOMtKKxOVQISWEEC2cRjDWI13LC5pwE4LH97l4AEJCCBhgRK+h6aTcNlNAAbps2mYmEAbjVrZeutEdAALCgRSrrxFhRWpyoBCawggWzicYIBOCt9Ndys5H5fTwOwO0NbkIAEJCCBBRAo6XtoNg2XzQB8UMd8O6Jj/dKrawAWlAEl3XgLCqtTlYAEVpBANvFYg1gNN2zuaQAOy9/eJSABCUigIYGSvodm03DZDMCGKWOxORHQAJwT2IzNlnTjzcjfMUlAAhJoSiCbeGw6bsstlIAG4EJx25kEJCABCcxKoKTvodk0nAbgrFm7mvU0AFczrmNnVdKNt6CwOlUJSGAFCWQTjyuIeBWmpAG4ClF0DhKQgAQKIFDS99BsGi6bARgbSMd/TwdeXEDuZ5uiBmC2iMxxPCXdeOeI0aYlIAEJzJ1ANvFYM2E13NwzYWIHGoDD8rd3CUhAAhJoSKCk76HZNFw2A/A3wKWBOwCfbZg/FuuPgAZgfyzTt1TSjTd9MBygBCQggQkEsonHmqGq4YbNYg3AYfnbuwQkIAEJNCRQ0vfQbBoumwH4XWBnYC/ghIb5Y7H+CGgA9sfSloCSbu4GXAISkMC8CGQTjzXzVMPNKwGatasB2IyTpSQgAQlIYGACJX1HzKbhshmA/wr8FfAo4LUD52WJ3WsAlhj1Oc65pJv7HDHatAQkUDiBbOKxJhxquGHzVANwWP72LgEJSEACDQmU9B0xm4bLZgDepnr09wfArYFfN8whi/VDQAOwH462UhEo6eZu0CUgAQnMi0A28VgzTzXcvBKgWbsagM04WUoCEpCABAYmUNJ3xGwaLpsBGKl4CHAYcFK1EvAzA+dnSd1rAJYU7QXMtaSb+wJw2oUEJFAogWzicUIY1HDD5agG4HDs7VkCEpCABFoQKOk7YjYNl80AfFOVN3sCuwIXAacA/wucDlwwIa+i7ENa5J1FNxPQADQreiVQ0s29V3A2JgEJSGCEQDbxWBMcNdywWasBOCx/e5eABCQggYYESvqOmE3DZTMAL6xMv/XUWR9fmHuTrigXZbZqmHMWG09AA9DM6JVASTf3XsHZmAQkIIHlMwDVcMNmrQbgsPztXQISkIAEGhIo6TuiBuDkpPj+BgOwYQptKbZL2wqWvwQBDUATolcCJd3cewVnYxKQgASWzwBUww2btRqAw/K3dwlIQAISaEigpO+IGoANk8JigxDQABwE++p2WtLNfXWj6MwkIIGhCWQTj0PzsP+xBDQATQwJSEACElgKAiV9R8ym4bI9ArwUCbvCg9QAXOHgDjG1km7uQ/C1TwlIoAwC2cRjGdSXbpYagEsXMgcsAQlIoEwCJX1HzKbhNADLfM/VzVoD0HzolUBJN/dewdmYBCQggREC2cSjwUlJQAMwZVgclAQkIAEJbCRQ0nfEbBpuWQzArYErV4kTpwGf79toLgQ0AOeCtdxGS7q5lxtlZy4BCcybQDbx2HK+ariWwGYsrgE4IzirSUACEpDAYgmU9B0xm4bLbADeBHgk8MfADYHRE4H/D/gI8Frga4tN15XuTQNwpcO7+MmVdHNfPF17lIAESiGQTTw24K6GawCp5yIagD0DtTkJSEACEpgPgZK+I2bTcFkNwBcATwQuNWL8bcy+i4ALgZcAT59PahbXqgZgcSGf74RLurnPl6StS0ACJRPIJh6nxEINN0yyagAOw91eJSABCUigJYGSviNm03AZDcB/qVb+rY/t68DxwE+qvLoGsCewa/XvMAIPAx7bMu8svpmABqBZ0SuBkm7uvYKzMQlIQAIjBLKJxwnBUcMNl7kagMOxt2cJSEACEmhBoKTviNk0XDYD8PbAJ4Ew9cL4Oxj4TE0u7V09Anzzqvw+E8q2SMeii2oAFh3+/idf0s29f3q2KAEJSOBiAtnEY01c1HDDJqwG4LD87V0CEpCABBoSKOk7YjYNl80AfAvwl8B3gdsAv5qSQ1cCPg/sArwdOKhhzllsPAENQDOjVwIl3dx7BWdjEpCABEYIZBOPNcFRww2btRqAw/K3dwlIQAISaEigpO+I2TRcNgPwe8BOwCHAGxrmz8OAw4GTKyOwYTWLjSGgAWhaLBWBkj48liowDlYCEuiVQDbxWDM5NVyvUW/dmAZga2RWkIAEJCCBIQiU9B0um4bLZgCeC1ym2uMvVvY1uWKl4AnAb4ArNKlgmVoCGoAmx1IRKOnDY6kC42AlIIFeCWQTjzWTU8P1GvXWjWkAtkZmBQlIQAISGIJASd/hsmm4bAbg6cC2wJ2BYxsm477Ax6vHha/csI7FxhPQADQzlopASR8eSxUYBysBCfRKIJt4rJmcGq7XqLduTAOwNTIrSEACEpDAEARK+g6XTcNlMwC/ANwS+CfgSQ2T8SXAE4AvVvsGNqxmsTEENABNi6UiUNKHx1IFxsFKQAK9EsgmHmsmp4brNeqtG9MAbI3MChKQgAQkMASBkr7DZdNw2QzAfwCeDpwH7A98dEpCxkrBo4FLA4cCzxwigVeoTw3AFQpmCVMp6cOjhHg6RwlIYDyBbOKxJk5quGETWANwWP72LgEJSEACDQmU9B0um4bLZgBuD3wb2Aa4AHgd8CbgS8CFVT5dCrgV8DdAHAAS5l+cFnwD4BcNc85i4wloAJoZS0WgpA+PpQqMg5WABHolkE081kxODddr1Fs3pgHYGpkVJCABCUhgCAIlfYfLpuGyGYCRf3cF/rs6DOSiKiFjReAvgfj3VavX4qUYf7x2APA/QyTvivWpAbhiAV316ZT04bHqsXR+EpBAPYFs4nFCrNRwwyWyBuBw7O1ZAhKQgARaECjpO1w2DZfRAIzUiRV+sfpv9yl5dGK1CvDLLfLNovUENADNjqUiUNKHx1IFxsFKQAK9EsgmHqdMTg3Xa/QbN6YB2BiVBSUgAQlIYEgCJX2Hy6bhshqA6/m4B/DHwM2Aq1R/jJWAJ1Ur/k4YMnFXsG8NwBUM6ipPqaQPj1WOo3OTgAQmE8gmHhvGSw3XEFRPxTQAewJpMxKQgAQkMF8CJX2Hy6bhshuA8808W99IQAPQnFgqAiV9eCxVYBysBCTQK4Fs4rHXydlYXwQ0APsiaTsSkIAEJDBXAiV9h8um4TQA55raS9e4BuDShcwBz5NASR9O8+Ro2xKQQDcC2cRjt9lYe04ENADnBNZmJSABCUigXwIlfcfKpuE0APvN5WVvTQNw2SPo+HslUNKHU6/gbEwCEuiVQDbx2OvkbKwvAhqAfZG0HQlIQAISmCuBkr5jZdNwGoBzTe2la1wDcOlC5oDnSaCkD6d5crRtCUigG4Fs4rHbbKw9JwIagHMCa7MSkIAEJNAvgZK+Y2XTcEMagBf0m0ZcBGzdc5ulNacBWFrEne9EAiV9OJkKEpBAXgLZxCOghsuXLhqA+WLiiCQgAQlIYAyBkr5jZdNwQxqAF/b8bggDcKue2yytOQ3A0iLufDUAzQEJSCA9gWziEVDD5csaDcB8MXFEEpCABCSgAciOO+64TiH+zw+HTIohDcA3d5x4jP0ewFWB+P8agB2BAhqA3RnawgoRKOnXqRUKm1ORwMoRSGgAquHyZZkGYL6YOCIJSEACEtAA1ADs4V1wb+C5wM2qtsIA/AFw3R7aLrkJDcCSo+/cNxHQADQpJCCBDAQSGoBdsKjhutCrr6sBOB+utioBCUhAAj0TKOk7VjYNN+QKwFnSKFb8hfF36xHj78fAocDrgfNmadQ6WwhoAJoMEhghUNKHk4GXgATyEsgmHmckpYabEVzDahqADUFZTAISkIAEhiVQ0nesbBpuWQzA/Srj77YYegUvAAAgAElEQVQjxt/PgBcBrwF+M2wKr0zvGoArE0on0geBkj6c+uBlGxKQwHwIZBOPLWephmsJbMbiGoAzgrOaBCQgAQkslkBJ37GyabjsBuAdgecDtx8x/n4BvAQ4DDhnsam68r1pAK58iJ1gGwIlfTi14WJZCUhgsQSyiceGs1fDNQTVUzENwJ5A2owEJCABCcyXQEnfsbJpuKwG4O2A5wF3HjH+zgD+Cfhn4Kz5pmSxrWsAFht6Jz6OQEkfTmaABCSQl0A28TiFlBpumFTSAByGu71KQAISkEBLAiV9x8qm4bIZgLtXK/7uOmL8nVmZfmH+/aplblm8HQENwHa8LC2BzgRK+gDsDMsGJFAogWzisSYMarhh81MDcFj+9i4BCUhAAg0JlPT9J5uGy2IA3rJa8XfAiPF3dvWYbzzu+8uGuWSxbgQ0ALvxs7YEWhMo6QOwNRwrSEACawSyiccNYVHD5chTDcAccXAUEpCABCQwhUBJ33+yabihDcCbVod7/NmI8XdudbBHHPDxc989CyWgAbhQ3HYmASjpA9B4S0ACsxHIJh6rWajhZgvnvGppAM6LrO1KQAISkECvBEr6/pNNww1pAP47cD8gxhD//RY4HHgh8JNeM8zGmhLQAGxKynIS6IlASR+APSGzGQkURyCbeATUcPmyUAMwX0wckQQkIAEJjCFQ0vefbBpuSAPwwpFciJV+rwRO6fgOeUvH+qVX1wAsPQOc/8IJlPQBuHC4diiBFSGQTTwCarh8uaUBmC8mjkgCEpCABDQA2XHHHdcpxP/54ZBJMbQBeFGPk4+2tu6xvRKb0gAsMerOeaUJaDCudHidXCEEkhqAarhc+acBmCsejkYCEpCABGoIlPT9JJuGG9oA7PNNEUJ0qz4bLLAtDcACg+6UV5tASR+wqx1JZ1cygWziccMKwD5Co4brTlEDsDtDW5CABCQggQUQKOn7STYNN6QBeMc55NYn5tBmSU1qAJYUbedaBIGSPmCLCKiTLJJANvEIqOHyZaIGYL6YOCIJSEACEhhDoKTvJ9k03JAGoG+GfAQ0APPFxBFJoBOBkj5gO4GysgQSE8gmHhOjKnloGoAlR9+5S0ACElgiAiV9P8mm4TQAl+iNsoChagAuALJdSGCRBEr6gF0kV/uSwCIJZBOPi5y7fTUmoAHYGJUFJSABCUhgSAIlfT/JpuE0AIfM/Hx9awDmi4kjkkAnAiV9wHYCZWUJJCaQTTwmRlXy0DQAS46+c5eABCSwRARK+n6STcNpAC7RG2UBQ9UAXABku5DAIgmU9AG7SK72JYFFEsgmHhc5d/tqTEADsDEqC0pAAhKQwJAESvp+kk3DaQAOmfn5+tYAzBcTRySBTgRK+oDtBMrKEkhMIJt4TIyq5KFpAJYcfecuAQlIYIkIlPT9JJuG0wBcojfKAoaqAbgAyHYhgVUjUNKH+KrFzvksB4Fs4nE5qBU3Sg3A4kLuhCUgAQksJ4GSvjtk03AagMv5npnXqDUA50XWdiUggZkJlCQSZoZkxZUmkE08rjTs5Z2cBuDyxs6RS0ACEiiKQEnaPpuG0wAs6q02dbIagFMRWUACElg0gZJEwqLZ2t9yEMgmHpeDWnGj1AAsLuROWAISkMByEihJ22fTcBqAy/memdeoNQDnRdZ2JSCBmQmUJBJmhmTFlSaQTTyuNOzlnZwG4PLGzpFLQAISKIpASdo+m4bTACzqrTZ1shqAUxFZQAISWDSBkkTCotna33IQyCYel4NacaPUACwu5E5YAhKQwHISKEnbZ9NwGoDL+Z6Z16g1AOdF1nYlIIHUBEoSIqkD4eDGEsgmHg1TSgIagCnD4qAkIAEJSGAjgZJ0dzYNpwHY7v24M/AYYH9gR+C3wHeAdwGvAs5p11xt6bsDBwN7ADsAPwdOAF4HHN1TH+Oa0QCcI1ybloAE8hIoSYjkjYIjqyOQTTwuaaSK0XCnnHIK17lOSLoyrpd/5FtlTNRZSkACElgRAiXp7mwaTgOw+ZvonsDbgG1rqoT6CGPw282b3FTyUpXJ95AJbbwBOAS4sEM/dVU1AOcA1SYlIIH8BEoSIvmj4Qg3EsgmHpcwQkVpOA3AJcxQhywBCUigIAIl6e5sGk4DsNkbbTfg08DlgbOAFwDHVP8+EHhY1UyYgLsDZzZrdlOpaPep1V+/CLy4WmF4feDJQIwjrij39Bn7mFRNA3AOUG1SAhLIT6AkIZI/Go5QA7DXHChOw2kA9po/NiYBCUhAAj0TKEl3awD2nDwLau5YYB/gfGBf4LMb+n1SZdbFn58LPGeGcd0I+CqwNXBi1c+5I+1cAfhEZTDGOG7ScbXhuCFqAM4QOKtIQAISGJpASUJqaNZD9J9NPA7BoEOfxWk4DcAO2WJVCUhAAhKYO4GSdGs2DecKwOnpvSdwfFXscODhY6rEo7snVabcGcDVgN9Nb/oSJV4NPKL6y97AcWPq7zViPkb5R7XsY1pxDcBphHxdAhKQQKEEShJr2UKcTTxm4zNhPEVqOA3AJcpQhyoBCUigQAIlacpsGk4DcPob7lDgaVWxMODWzcCNNePR3Xg0N667AR+e3vSWEhGHHwLXAr5RGYl11eP1PwROrQ4iuahFP9OKagBOI+TrEpCABCQwFwIlicG2ALOJx7bjH7B8kRpOA3DAjLNrCUhAAhKYSqAkzZdNw2kATk1P1h8dORvYrnoMeFytWLX3meqF5wHPnt70lhLXq/b6iz/UrTJcLxyvxwnBcUW977XoZ1pRDcBphHxdAhKQgATmQqAkMdgWYDbx2Hb8A5YvUsNpAA6YcXYtAQlIQAJTCZSk+bJpOA3AqenJz4HtgS8Dt5pQ/MrAL6vXjwTuP73pLSUOAN5b/evxwD9PqBuv/1P1epw6/IEW/UwrqgE4jZCvS0ACEpDAXAiUJAbbAswmHtuOf8DyRWo4DcABM86uJSABCUhgKoGSNF82DacBODk9LwesH8TxfiCMuklXnBB8xWr/vlgR2PSKfQVfUxW+H3DUhIr3BcJgjCvqxYrAplcYfJOua6/vPfi4Vx7JtleNrQy9JCABCUhAAhJoQuBh+8bC/P6vH//4x+y5Z2xnt3btAXxpwhMJ/Q9gOVssVsN97nOf45rXvOZyRm2GUb/+2O/OUMsqEpCABCQwFIF56aWh5jOp3w0a7rrAyUOOUwNwMv0dgJ9VRd4JHDglWD+tDgCJA0Fu3iKwo6cI3x344IS68fr6qr8nAi9r0U+f+wW26NaiEpCABCQgAQn0SGDHau/gHptcuabUcCsXUickAQlIQAISWGoC8SPuiUPOQANwMv0Q2D+oirwVOGhKsKJs1PkOcIMWgX0mEPsGxnUX4GMT6v4R8NHq9aj3Dy360QBsAcuiEpCABCQggaQENACnB0YNN52RJSQgAQlIQAISWBwBDcDFsZ6pp1X79XjaI8CXAW5crXqMfXMumInasJWuAZxQDSHeYD8ZdjjF9m4chg+9MRg+BjEC42Ac+iCwFRCaJK74fD7VR4CnYlXDTUW09AW8vy59CBtNwDg3wrT0hYzz0oew0QRKjPOohvsK8NtGpOZUyBWAk8Gu2v4xc0qjVM1uOcikWo35w1SjK2cwxmH4WBuD4WMQIzAOxiEHgfJGoYZb/Zh7f139GPs5WkaMjbNxLofAwDPVAJwegNOAqxZyCvB0GvlLKAZzxMg4DB8HYzB8DBS0OWJgHPLEYdEjUcMtmvhi+/NzbrG8h+rNOA9FfrH9GufF8h6qN+M8FPmqXw3A6QE4FtgHOBvYbsIjN3Hq72eq5mI/v2dPb3pLiTg2MPYNjCtO9Y3TfeuueP3g6sWo970W/ZRQ1JtKjigbh+HjYAyGj4HGU44YGIc8cVj0SNRwiya+2P78nFss76F6M85DkV9sv8Z5sbyH6s04D0W+6lcDcHoADgWeVhXbCzi+pspTgRdUr90N+PD0preUiDjEo6rXAr4B3GRC3a9X+/TF/j+xwbUHe1wSljeVFok3x6LGYY5wGzZtDBqCmnMx4zBnwA2bNw4NQa1YMTXcigV0w3R8X692fNdnZ5yNcxkEypil7+eB46wBOD0Ae46YfnWr8y4FnFQZd2cAVwN+N73pS5R4NfCI6i+xmvC4MfXDgPxs9fco/6iWfZRQ3JtKjigbh+HjYAyGj0GMwDgYhxwEyhyFGm614+79dbXjqwFYRnyNs3Eui8DAs9UAbBaA9UdIzgf2HTHh1ms/CXhx9Y/nAs/Z0OydgGOqvx0BPHhMtzcCvgbEKTEnVv2cO1Lu8kCMY/fqMeRdgf9rNvyiSikGc4TbOAwfB2MwfAw0AHPEwDjkicMQI1HDDUF9MX36ObcYzkP3YpyHjsBi+jfOi+E8dC/GeeAIaAA2C8BuwKeBMOHOAuKRkjD04t8HjuzJ963KoDtzBgMwqsQjxPEocVxfBF5U7Q14feApQIxjvdzTmw29uFLeVHKE3DgMHwdjMHwMNJ5yxMA45InDECNRww1BfTF9+jm3GM5D92Kch47AYvo3zovhPHQvxnngCGgANg/APYG3AdvWVAnzb3/g22Neb7ICMKrFo8SvB/5mwrDeWBmOFzYfelElvankCLdxGD4OxmD4GGg85YiBccgTh6FGooYbivx8+/Vzbr58s7RunLNEYr7jMM7z5ZuldeM8cCQ0ANsFYGfgsZXRF8l7XmX4HQkcBpxT01xTA3C9+j0qk28PYHvgNOCE6oTgo9sN2dISkIAEJCABCUigeAJquOJTQAASkIAEJCCBsgloAJYdf2cvAQlIQAISkIAEJCABCUhAAhKQgAQksOIENABXPMBOTwISkIAEJCABCUhAAhKQgAQkIAEJSKBsAhqAZcff2UtAAhKQgAQkIAEJSEACEpCABCQgAQmsOAENwBUPsNOTgAQkIAEJSEACEpCABCQgAQlIQAISKJuABmDZ8Xf2EpCABCQgAQlIQAISkIAEJCABCUhAAitOQANwxQPs9CQgAQlIQAISkIAEJCABCUhAAhKQgATKJqABWHb8nb0EJCABCUhAAhKQgAQkIAEJSEACEpDAihPQAFzxADs9CUhAAhKQgAQkIAEJSEACEpCABCQggbIJaACWHX9nLwEJSEACEpCABCQgAQlIQAISkIAEJLDiBDQAVzzATk8CEpCABCQgAQlIQAISkIAEJCABCUigbAIagGXHf5VmfxngIOB+wC2AqwC/A04FPgO8vvrfVZrzouZyNWDP6r89gPjvqlXnRwAPbjmQuwMHV+3sAPwcOAF4HXB0y7ZKKt5HHK4A/AmwH7A7cAPgD4BfA98CPgS8FvhJSWBbzLWPGNR1F7E5CdilKnAycN0WYyup6Dzi8MfAXwJ3AK4JnA/8FPhf4KPAW4GzSoLsXCWwYALzeF+vT8H764KDOaW7ecTae3iuGMdo+oxz6KFHABHn6wNXBM4EvgF8sNKuP8uHoIgRxfeJe1T6aVcgvtvFd/AfAZ8G3gh8qgUJvye2gDVLUQ3AWahZJxuBnYH3AzedMrB/AR4LXJRtAsnHM4lXGwPwUpXJ95AJ830DcAhwYXImQwyvaxzCGI8P4jD8Jl1hBoZB+84hJpm8z64xmDS9lwJPGCmgAVhPq884XBl4M3CvKbm3G/Cl5Pnp8CSwzAT6fF9v5OD9NVdm9Blr7+G5Yjs6mr7i/FfA4cDlJ0z1l8CBwEfy4ljJkR0L7NNgZm8BHgacN6Gs3xMbgOyjiAZgHxRtY0gClwa+OGL+xWqNfwK+CWxT/RoRX6rjl6K4nga8cMgBL2Hfox/gP6h+bbtrNY82BuALgKdW9SJmLwa+U/2S92QgvmDHFeWevoSc5j3krnGIlU2frAYZRuD7gBOBX1S/1v2/6sM5PoAvAO7pisxNIe0ag7ocidyPVbDxi2n8F/cuDcD6d1RfcbhStbrvNlVX/wkcVd2X4j2wI3BH4D7V+0EDcN53OdsvmUBf7+uNDL2/5suqvmLtPTxfbEdH1Eecbw+EyRTaNBYHxPeO/6pWl+0EPKj6fI5+zwVuBnw3N5aVGt23q+9xsdrvyOp7RnxX3ArYu/ph+9rVjP8deOCE2fs9cUGpoQG4INB2MzcC961uONHBZ6tfIeKL2+gVX+7itTALz6jMjni8y6sZgedW5kQYFPFIXCzD/15VtakBeCPgq8DWlem0b/VBvT6CeDznE9VjqRGbmwDxoeL1ewJd43C7agVstPO1GrCxCipMkPhsCHP2hq6YvQSprjEYhz1E0vFA3KeeBcQK2VjVrAFY/+7vKw7xi3SsLPgtcH/gv2u6jPdDxMnPDe/IEpgfgb7e16Mj9P46v3h1abmvWHsP7xKF+dftI87xY/X+1VAfBbx6zLBfBvxd9fdXAY+e/9TsoSIQ8Yn34burxQMbwWxfPX0U3wPjih9Vw9DdePk9cYEppQG4QNh2NRcCsdrv8VXLfwq8t6aX/wD+rHotHoX8ylxGU0ajsxiA8YEde3fEFb8IHTcG1V6VURsvRfn4oPeqJzBLHJrwjBVQseIprjClvtCkUqFl+ohBiNYQr7FqOe5NsRejBmC7hJolDqMrYp8ExCOCXhKQQB4Cs7yvN47e+2ueeE4aySyx9h6+HLEdHeUscY5He+Mx73haJcykcVesBI0FHnGFZl1f1b98hFZzxAeMfD+P7bgeM2aafk9cYOw1ABcI267mQuCwEaMoln3HKrNx10uAJ1YvxGaln5/LaMpotO0HeNxnfghcq3p8OFb31V2xme8fVoe3xON37tdYz6ptHJpmZxiv8b6KK1ZFxZJ+r/EEusYgjL64Z8UWBXcGPg58XwOwdbrNEod3AH8O/Aq4BvCb1r1aQQISmCeBWd7Xo+Px/jrP6PTb9iyx9h7ebwwW0doscY7Dt0IjxZY1cQhh3RUHCoZBGIep3XwRk7GPxgQifuuHqH1gZEXnegN+T2yMsp+CGoD9cLSV4Qj8LfDKqvsmKwDDUNquOvV0uFEvd89tP8CvVz1OGrOOTXwfPmH68XocQBFX1Ft/1Hi5ic1n9G3j0HQU6ysmonysBIzVs17jCXSNQRxeFCenxQmzcYp5XBqA7bOtbRzi1Pgw/i5X7fkXp8fHFY8Lxg8V8b9xEramYPtYWEMCfRFo+77e2K/3174iMf922sbae/j8YzKPHtrGOcYQCzZuPWUF4LbVZ3qUj0dRY3sorzwErlLFL0YUT+rF9/XRy++JC46VBuCCgdtd7wTi157Yqyxu/nGwQewtsHEPwNgAOh45DcHwduAvex9FWQ22/QAfXfodj2v/8wRc8Xo81h1X7PkRvxR5jSfQNg5NOcbmyusfzrsCX29ascByXWIQp9XFhsinV6te49fruDQA2ydS2zjEKoLPVd08u7onPa/aTDx+IIorTqqLfWr+sVqZ2X5U1pCABLoQaPu+Hu3L+2sX8ouv2zbW3sMXH6M+emwb5+gzTo59XdV5bCX02jEDGX3Kaz/gf/oYrG30RiC24FpfTBAHQD5lQ8t+T+wNdbOGNACbcbJUbgJhVsQX6ThIIk6XDYMp9tH6AyBOj4pTgONUzdgXIlbbxEEWXrMTaPsBHiv+XlN1FyttYo+5umv0UJeoFysCvcYTaBuHJhxvWf3aGiugYp/M2JPOq57ArDGI/WzCWL06cMiIuI2eNADbZ1zbOMSpgf9adROblMepdHHgzbgrVo3H6fEvaj8sa0hAAh0ItH1fr3fl/bUD9IGqto219/CBAtWx27Zxju5Cj76pekoiTgGO/x8Hdv0YiFOA4yCve1fjih/sntFxjFbvl0Cc3hwHce5ZNTtuGy6/J/bLfGprGoBTEVlgSQjcuDL64gTNjXkdhl8cLf564JwlmU/mYbb9AI8N9uMXn7juDnxwwuTi9fVVf7FnYxyO4DWeQNs4TON4WeBT1UnMUXbSI/XT2irl9Vlj8IbqtN8QRfEjxehelxqA7bOnbRxGVxrHY77xKHDcl+IU5v+tVpTH4+8vBGJz8bjiC0asjvWSgAQWQ6Dt+3p9VN5fFxOfPntpG2vv4X3SX1xbbeM8OrJYIPB0IJ7q2ngdAxzqyr/FBbJFT7EIZ/2QtVgFuH7I4GgTfk9sAbSPohqAfVC0jaEJxKO9zwEeCuxQM5jYPPb51a9GQ4932ftv+wH+TCAer4vrLsDHJgD4I+Cj1etR7x+WHdYcx982DtOGEgZ5vIfiOgJ48LQKvs4sMdi3eqQ0tiqIk+rCcBq9NADbJ1bbOMQKgfg8WL8+Uv04sXH7iDhl8hNA/IIdKzZv6sFE7YNjDQnMSKDt+zq68f46I+yBq7WNtffwgQM2Y/dt47zeTRweGKvwY5HA1mP6jh/y3lMd9njqjGOzWv8EYluueBw7Yvaz6nCW+N+Nl98T+2c/sUUNwAUDt7veCcTJQkcD+1R7/8WKsTcD361Wddy2WtURX+RilU2sKlvfY673wRTSYNsPcH/ZmU9itI3DpFHEI47x62lcJ1Qn0p49n2GvVKttYxCrLL9c7fkX96r1k8lHoWgAtk+RtnEI7rFn0PoVG4zH9hHjrjgFe31D8XhEfqNh23601pCABJoQaPu+9v7ahGrOMm1j7T08ZxynjaptnKO9+H4XB0fEavyTq0d840e7X1bbqMTTKvGDXhw08SPgrsBXpw3E1+dOIH4w/SQQWzKEQXu3al/lcR37PXHu4bhkBxqACwZud70TGN34NVYsxcqljVf88vDhytSI/SPiy158CfeajUDbD3D3dpiN87RabeNQ117sQbe+qfI3KrF12rTOfX2NQNsYxErY+KXzFCB+0R5nsmoAtk+utnEYzfk4fOVqE7qMVbGxOjau+P9vbD88a0hAAjMQaPu+9v46A+QkVdrG2nt4ksC1HEbbOIepHwc9Xhv4SfX4b/zvxivMpnjSK7bziFODY585r+EI7FJtKXStanFOPPY7aQsVvycuOFYagAsGbne9Eoj8DaMifvWJQz/+cELrsc9W7G8WVxwSEvuHeM1GoO0HuKc7zcZ5Wq22cRjX3gOAt1WPOMYvq7FS9ofTOvb1LQTaxuC31WnksUo5fpQYd/0LEKebx73tb6sC8cjEpEfnSw9J2zjEYVDvr6DFyr/4Uajuil+t1/ctjZWysS+glwQkMH8Cbd/X3l/nH5N59dA21t7D5xWJ+bbbNs73qh7tjVH9/ciTKuNGObqNza1c6DHfQE5oPUy/WPl3verJu1ic85Ypo/F74oLDpQG4YOB21yuBa1SnQEWj7wQOnNB6/Cp0bvV6fJmLfSS8ZiPQ9gM8PgTiF7y44lTf+KWn7orXD65ejHrfm22IRdRqG4eNUOKxiXdXe3PEaWrxmMV6nIoA2MMk28Zg9LCPNt3HPnR3alOhsLJt47BzddpyYIpHeuPR3rpr9ItmPKayvpl1YYidrgQWTqDt+9r768JD1FuHbWPtPbw39AttqG2cn1od4hiDnHaI4Ogqsvg+GN8LvRZLIH68Dr26a9Xto4FXNRiC3xMbQOqziAZgnzRta9EE4kYTj2/FFUbG+j5N48axDfDr6oX3Afdc9GBXqL+2H+Bxn4lVZfGrUDxiGo8+1l2x0X6c6Byb+O7ohvsTs6ZtHEYbi8NYYgVUPF7xCyA26nXPlPZv0rYx8Atqe8ZNarSNQ7QZK153qj4Xtptwr4lVmK+sBvFA4N+bDMgyEpBAZwJt39feXzsjH6yBtrH2Hj5YqDp13DbOo3s9xve2+P5Wd41+Vsf3wfhe6LU4ArFHYzypsv5ERZi3cXBLk8vviU0o9VhGA7BHmDa1cAJxMuPpwLbVxq/xi+D5NaMYXV4cj9g9ZuGjXZ0O236Ax8xfDTyiQrA3cNwYHHsBn63+HuUftTrI5jKTWeIQA7ld9fhpHKDzq+pk5tgzxas9gVljMKkn9wBcTBziMKj1rSD2q06qG9fzMSOrL8MwjP0bvSQggfkT8P46f8ZZepgl1t7Ds0Sv+Tjaxjn2jjuqav7FwFMmdBXlonxctwG+0HxYluxI4ArV94rYbiuuf6wOa2nTrN8T29DqWFYDsCNAqw9O4N+A2McsrucA/7+9O4+Z7prjAP4N0qitRKgqqkpjp9KGWNo/0NqCVBCUxtb4w1IiQmONPUJSoU1tLUVVhNhCq22sJbEvbWgbBKVFYt9aW35xnpg+78zzzJ2ZOzP3nc9JGt53zj3n3M+578yZ35zlVWNaVCcQ1f5/W1OSa0+nSftvrfyGBtCArh/gdUuHJrk4ybXbRr1HjizJrtf3badD1ca9FcStvrp0ABarbOIs/VD7olRAo2Y81QEU9W/hK6u8iYHXPUsf7HbLAoC7Ce35+iz9UMG8H7VNw7/f9r/cmiW+VcNxSc5sf6gZs/VDkkSAwHIEZvl3vVvLvL/uJrSa12fpa+/hq+mreWrt2s81Vq0VQRVg+lOSCjDV5/X2VMuDa3ZgTQyp/PVs1KGPUv8C+7RTmuv05UonJzlxhmp9T5wBbdZLBABnlXPdugjUctGavVQfDpXqqPg6CfjH7YtdzSqrN6L6MKh0fpIHrUvjB9KOOhji9iNtraXXdfpypQoevWvbfZwx4b5en6SmhFeqjfdranjtOXdI+1XvsPZa5TtpIDbLbOa8/VDOF46ceFqzn87b5Qbq8In6T/qfwLx9MI2jL6i7Ky2qH2pPv5pVUKmCgfWeVHsC1qzyY9us5frRogKD9eOEHyV27xs5CMwqsKh/1zvV7/111t5Z7HWL6mvv4Yvtl0WXtoh+flmSOuG70p+T1Cquz7UVYPsnqYNCntn2s648T26H2y36XpQ3XqCWWtd4qVItAa7v3Dttx3BVO7hzXGm+Jy7pKRMAXBK0anoVqIBe7ctUgamdUr0x1b4QtWxYml6gAnrHT589k95X6pe5OqXraTuU9e52CIhf7vZEmrcf6iSuOn22S6oZtTWzVvqfwLx9MI2jL6i7Ky2yH2rAWcuKJr1vVQD80SPbE+zeOjkIEJhFYJH/rifV7/11lpNyw9EAAA78SURBVJ5Z/DWL7Gvv4Yvvn0WVuIh+rs/mWu79vB0+p6u9V7fJAw7qWlTvTVdO171Xa//lmgk6LvmeOJ353LkEAOcmVMCaCNw0ydPbKVF3aUscaynpFUm+nqSWCn/CoRIz9dYiPsBHK65TNeuk3yNa0Pa3rY/qBODPzNTCzbho3n4QAJz/OZm3D6ZpgS+ouystuh9qX9Lao7ROwj4gyd/bL9T1mVGzDWqvTIkAgX4FFv3velxrvb/224fTlr7ovvYePq38cvMtsp9rX79ntJUYted7rfyqGYGXtZNn6zvEJcu9PbXN8L16pwDgFqjviT0/WgKAPQMrngABAgQIECBAgAABAgQIECBAgMAqBQQAV6mvbgIECBAgQIAAAQIECBAgQIAAAQI9CwgA9gyseAIECBAgQIAAAQIECBAgQIAAAQKrFBAAXKW+ugkQIECAAAECBAgQIECAAAECBAj0LCAA2DOw4gkQIECAAAECBAgQIECAAAECBAisUkAAcJX66iZAgAABAgQIECBAgAABAgQIECDQs4AAYM/AiidAgAABAgQIECBAgAABAgQIECCwSgEBwFXqq5sAAQIECBAgQIAAAQIECBAgQIBAzwICgD0DK54AAQIECBAgQIAAAQIECBAgQIDAKgUEAFepr24CBAgQIECAAAECBAgQIECAAAECPQsIAPYMrHgCBAgQIECAAAECBAgQIECAAAECqxQQAFylvroJECBAgAABAgQIECBAgAABAgQI9CwgANgzsOIJECBAgAABAgQIECBAgAABAgQIrFJAAHCV+uomQIAAAQIECBAgQIAAAQIECBAg0LOAAGDPwIonQIAAAQIECBAgQIAAAQIECBAgsEoBAcBV6qubAAECBAgQIECAAAECBAgQIECAQM8CAoA9AyueAAECBAgQIECAAAECBAgQIECAwCoFBABXqa9uAgQI9CfwrCSntuIPSHJFf1UpmQABAgQIECBAYEECxnALglQMAQLXFBAA9EQQIEBgfoHTkpzQinlgkgs6FHl0knNa/rcmeV6Ha3fKavC4IEjFECBAgAABAnutgDHcXtu1bowAge0CAoCeCQIECMwvcL8kX27FnJ7kaR2KPDPJcS3/4Um+2eFaAcAFYSmGAAECBAgQ2EgBY7iN7HY3TWAzBQQAN7Pf3TUBAosXuCzJIUn+mOQWSf42RRXXT3Jlkvrfi5LcdYprps1iBuC0UvIRIECAAAECmyxgDLfJve/eCWyQgADgBnW2WyVAoFeBVyR5ZavhCUk+NEVtT07yvpbvxUneOMU102YRAJxWSj4CBAgQIEBgkwWM4Ta59907gQ0SEADcoM52qwQI9CpwuyT1C3K9r346ySOmqO3cJA9O8u8kt0ly+RTXTJtFAHBaKfkIECBAgACBTRYwhtvk3nfvBDZIQABwgzrbrRIg0LvAl5LcP8k/kxyY5Nc71HjLJD9Pcq0k57VA4Gj2eyR5VJIHJLlzkpsluSrJL9t+g6ck+cYO5e8WAKxTgfdPUptfV95JqWYyPj7Jj5LccYd8db/PTnJMkoOT7Nvu/8J2GvEXetdXAQECBAgQIEBgNgFjOGO42Z4cVxEYkIAA4IA6S1MJEFh7gWcmeUdrZZ3mW6f6TkovTPKm9uJTktRhIFvpIUk+M8Xdvmpk2fH27MsMAD41ydtb0G9Ss09N8pwk/5rivmQhQIAAAQIECCxTwBhusrYx3DKfRHUR6FFAALBHXEUTILBxAvslqZl1122z847YQeC7Se6e5M/t0JC/jOSt5cNnJflUkgva7Ls/tRl7d0vy3CS3avkn7Te4rADg6D6GlyZ5W5IfJvltklpSUwPqo1tbX5/kpI17KtwwAQIECBAgsO4CxnDGcOv+jGofgbkFBADnJlQAAQIEriFwdpLHtb+pJbO1dHZ7qsBfBQAr1SEgx2/LcPMk/0jyhwm2FWD8bJKjklzSlub+Z1veZQQAD2j136At8500w+/NSV7QlkbfIclPPTMECBAgQIAAgTUTMIbbs0OM4dbsIdUcAvMICADOo+daAgQI7Cnw8DZzr155bZKXjkGqpb+1BLjSg5KcPwPkvZN8rV131yQXrSAAWPdXM/oqoHdokqsn3Mc+SX7R9jF8eZJXz3C/LiFAgAABAgQI9ClgDLenrjFcn0+csgksWUAAcMngqiNAYK8XuE4LdtUBGxUYq2Wwo7Pz6tCPOvyjDgGpoNhB7RTgnWBqxl/NCqyZdnV9peuPBACflOSDKwgAfj9JBR9PTnLiLj37yXYycu1t+LC9/ilwgwQIECBAgMDQBIzhxveYMdzQnmTtJTBBQADQo0GAAIHFC7wlyfNbsUcmqZPlttKDk5zb/vDGJC+eUP0Nk9RBInUC752SXHuHZo47cKTvJcB1ym/tW9j1c+TbSe61eHIlEiBAgAABAgTmFjCGm0xoDDf346UAAqsV6PrFbbWtVTsBAgSGIXDPJDVIqvTOJCeMNLv2/KuDMyrdJcnFY26p9sk7L8ltprzdCiJWMHE09R0AvHWSn03ZvtFstSdi7Y0oESBAgAABAgTWTcAYbnKPGMOt29OqPQQ6CggAdgSTnQABAlMKfC9Jndj7+3bKbx3qUct2r2z/+80kh08o6+vttVo6XAHED4+crFvlVLpem4FX//8lSd6wray+A4C3TfKTVucp7RCQaWiq/XVasESAAAECBAgQWEcBY7jxvWIMt45PqzYR6CAgANgBS1YCBAh0EKhDPuqwj0qPTfKRJMclObP93bhlu/XS6C/PL0vymgl13qrtJVgvzxIA/GWSOsV3+wzF7dVt7fuy/VffWqL8x5b57Ume3cFGVgIECBAgQIDAugoYw61rz2gXAQJzCQgAzsXnYgIECEwUqOBaHfZRe/d9PMmjk5yT5Oh2Wu6BSX4z5uo60OP97e/rZN1Js+WqvI+1fLMEACugV+VXYLIClJPSVr5xyz4uS3JIku8kOcyzQIAAAQIECBDYCwSM4faCTnQLBAjsKSAA6KkgQIBAfwKfTXJMC/jVwRcVKKuAYM2qe+SEao9PckZ7rYJqdc24tFV2vTZLAHDr+lrGWycVj0vV5lqqXGlcAHB0o+yjknyxP0olEyBAgAABAgSWJmAMtzRqFREgsCwBAcBlSauHAIFNFHhikg+0G7+oHfpRf9xaEjzO5L5JvtJeODnJiWMy1QnDFXzbSrMEAOua17UCHpPko9vq2S/JBSMn9o4LANYy5Pr72o+wZjvWCcf153GpPm8q6FkzGscdfLKJz4d7JkCAAAECBNZTwBju//1iDLeez6hWEegsIADYmcwFBAgQmFpg33boR+2Xt5V+1/be2zrMY3thNUOwAmS1PLdSBRDPSvKrJAcleUpbTlxBwvu1PLMEAG+Z5JJ2IMlfk7y2nTxcnwtHJHlBkv1bwO4eE2YAVvVPaG2s66qc05PUr+aXJ9knSZ0WfJ8kFWSsg0MqSFgnHEsECBAgQIAAgXUVMIYzhlvXZ1O7CMwsIAA4M50LCRAgMJXAe5I8dSTnaUnqhN6dUgXgPpekZuGNS99qQcCftRdnCQDWpXUoyXuTXGtMJX9JUr9+13+P3yEAWJcem6Tuc1J7t4r/V5IHJPnqVHIyESBAgAABAgRWJ2AM9397Y7jVPYdqJrAwAQHAhVEqiAABAmMFam+8z4+8UrP2LpzC6uC2t1/tIVibUdeJu7V89uwkpyap9++/zRkArMtryfGL2mzCGyW5os3QqxOMf5jkQ1MEAKucGyc5IclDk9w5yU3a3odV3g+SnN8OHKnThyUCBAgQIECAwLoLGMMZw637M6p9BDoJCAB24pKZAAECBAgQIECAAAECBAgQIECAwLAEBACH1V9aS4AAAQIECBAgQIAAAQIECBAgQKCTgABgJy6ZCRAgQIAAAQIECBAgQIAAAQIECAxLQABwWP2ltQQIECBAgAABAgQIECBAgAABAgQ6CQgAduKSmQABAgQIECBAgAABAgQIECBAgMCwBAQAh9VfWkuAAAECBAgQIECAAAECBAgQIECgk4AAYCcumQkQIECAAAECBAgQIECAAAECBAgMS0AAcFj9pbUECBAgQIAAAQIECBAgQIAAAQIEOgkIAHbikpkAAQIECBAgQIAAAQIECBAgQIDAsAQEAIfVX1pLgAABAgQIECBAgAABAgQIECBAoJOAAGAnLpkJECBAgAABAgQIECBAgAABAgQIDEtAAHBY/aW1BAgQIECAAAECBAgQIECAAAECBDoJCAB24pKZAAECBAgQIECAAAECBAgQIECAwLAEBACH1V9aS4AAAQIECBAgQIAAAQIECBAgQKCTgABgJy6ZCRAgQIAAAQIECBAgQIAAAQIECAxLQABwWP2ltQQIECBAgAABAgQIECBAgAABAgQ6CQgAduKSmQABAgQIECBAgAABAgQIECBAgMCwBAQAh9VfWkuAAAECBAgQIECAAAECBAgQIECgk4AAYCcumQkQIECAAAECBAgQIECAAAECBAgMS0AAcFj9pbUECBAgQIAAAQIECBAgQIAAAQIEOgkIAHbikpkAAQIECBAgQIAAAQIECBAgQIDAsAQEAIfVX1pLgAABAgQIECBAgAABAgQIECBAoJOAAGAnLpkJECBAgAABAgQIECBAgAABAgQIDEtAAHBY/aW1BAgQIECAAAECBAgQIECAAAECBDoJCAB24pKZAAECBAgQIECAAAECBAgQIECAwLAEBACH1V9aS4AAAQIECBAgQIAAAQIECBAgQKCTgABgJy6ZCRAgQIAAAQIECBAgQIAAAQIECAxLQABwWP2ltQQIECBAgAABAgQIECBAgAABAgQ6CQgAduKSmQABAgQIECBAgAABAgQIECBAgMCwBAQAh9VfWkuAAAECBAgQIECAAAECBAgQIECgk4AAYCcumQkQIECAAAECBAgQIECAAAECBAgMS0AAcFj9pbUECBAgQIAAAQIECBAgQIAAAQIEOgkIAHbikpkAAQIECBAgQIAAAQIECBAgQIDAsAQEAIfVX1pLgAABAgQIECBAgAABAgQIECBAoJOAAGAnLpkJECBAgAABAgQIECBAgAABAgQIDEtAAHBY/aW1BAgQIECAAAECBAgQIECAAAECBDoJ/BfLHDqcuRk2cAAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, sharey=True)\n",
    "axs = [ax1,ax2,ax3,ax4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# create the function that will do the plotting, where curr is the current frame\n",
    "def update(curr):\n",
    "    # check if animation is at the last frame, and if so, stop the animation a\n",
    "    if curr == 100: \n",
    "        a.event_source.stop()\n",
    "    for i in range(len(axs)):\n",
    "        axs[i].cla()\n",
    "        axs[i].hist(x[i][:100*curr], normed=True, bins=bins[i], alpha=0.5)\n",
    "        axs[i].axis(axis[i])\n",
    "        axs[i].set_title(titles[i])\n",
    "        axs[i].set_ylabel('Normed Frequency')\n",
    "        axs[i].set_xlabel('Value')\n",
    "        axs[i].annotate('n = {}'.format(100*curr), [anno_x[i],0.5])\n",
    "    plt.tight_layout() # automatically adjust the locations of axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "a = animation.FuncAnimation(fig, update, interval=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}