visualise-stockbot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from bidder import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib import animation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import functools\n",
    "import json\n",
    "from time import sleep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "account = \"TLB99029472\"\n",
    "venue = \"NUEX\"\n",
    "stock = \"NTU\"\n",
    "\n",
    "header['X-Starfighter-Authorization'] = \"c8bbc206d27988125aa25e396f2f290f22109dbe\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "asks, bids, askSize, bidSize = [[0]*2000]*4\n",
    "askmax, bidmax = [1]*2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def quote_updater(account, ws, message):\n",
    "    global asks, bids, askSize, bidSize, askmax, bidmax\n",
    "    \n",
    "    message = json.loads(message)\n",
    "    if 'quote' in message:\n",
    "        quote = message['quote']\n",
    "    else:\n",
    "        return\n",
    "    \n",
    "    if 'ask' in quote:\n",
    "        asks = asks[1:] + [quote['ask']]\n",
    "        askSize = askSize[1:] + [quote['askSize']]\n",
    "        if askSize[-1] > askmax:\n",
    "            askmax = askSize[-1]\n",
    "    else:\n",
    "        asks = asks[1:] + [asks[-1]]\n",
    "        askSize = askSize[1:] + [askSize[-1]]\n",
    "    \n",
    "    if 'bid' in quote:\n",
    "        bids = bids[1:] + [quote['bid']]\n",
    "        bidSize = bidSize[1:] + [quote['bidSize']]\n",
    "        if bidSize[-1] > bidmax:\n",
    "            bidmax = bidSize[-1]\n",
    "    else:\n",
    "        bids = bids[1:] + [bids[-1]]\n",
    "        bidSize = bidSize[1:] + [bidSize[-1]]\n",
    "    \n",
    "    #print quote.get('ask', None), quote.get('bid', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "thread = quote_websocket(account, venue, stock, functools.partial(quote_updater, account))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "window.mpl = {};\n",
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       "    } 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",
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       "            warnings.textContent = (\n",
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       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
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       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
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       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
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       "        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",
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       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
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       "\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",
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       "    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",
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       "        canvas_div.focus();\n",
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       "\n",
       "    window.setTimeout(set_focus, 100);\n",
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       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
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       "\n",
       "    // Define a callback function for later on.\n",
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       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
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       "    }\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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+zZCajFPYA1ZsMD/dehQX5HLb6lWTd80GawG7Q/zmpMCVLymSZM4D8MagnmEdiL4C8KNjzZKK6bbsGtP5GMcAWRNgDSGC32iaVM/nRTEnQUB9Rf/nSOP9K0K4cCTq6+WDjxQatEiv19etNcTRIhpnEUOoPn7+ed7VqWH3j1WK+Yt1akH/a1Wf1yuWbOMABZt42xfb0uMABJRy0RYVMmNcarD5BKK7O3eXcJq4ApzHyIb4h5qPxvJaIXgs0uvKOk7IfMdCRbc0RAV+vQtrS4v/K4+T0zUwBE7Kuu0U70nsD5gZXaFuuEH+OzNc6UDDvAnOCbZefN89SKy/Pqrv0tmF+w78iZXmAiZ6NnZE11Lnj0IKMwU09jTT/tqAI7aXIsy6pwYeTPMGn9JJlCUHIJvnIkM8xvKAeaxJAs4Hfj7D3q6ckf1v+F9r5qTr27m4xQZ5JPku1JyOyQlMtoRPMOqGNg6vykWKf57e4iQRH1jcWVBDhfGMWmRIFEs+Pkt9GEGXNu2nvO7N/BRvlB8UJQgFvxOoQ+FJ4p472JRhcHUretxS9ZZhi2PzlUIeCBfZTy1Kt67Jk70SQmLOi9iPGE2YDwSMQvJhGByze67x37SX3/5qiTzGZPfSSf55DiygAeZE+h39DEweekl/ypMrgVRYitVUr9nxur5Hvtne7hA/OBx7K0R3Jh+2KjzObjmuYKI2mHz3b76hxLM3AhZxyz800+5qs+UQ9V/6zNKeuRh6ZGGKlNqiw7YfYV2LrfBv54xwy4ckguGFCZh8IMs8hCC+FxhPmPsEcWczoV6ugWGyGsWP9r5++91zwFDtMcOK3XuLXvp9rcP1fz5RgDTuSnTvW6JEUA65I47+iM7mcKkR4AHZAPGxsLHZOb+DvmAZDCI0box8wQFCwyWJCcuMO9jXUAE4A/8gb+HC5sogk1vu28Hf3Y6+OCEa09AKhvXD3uXUI/X/lS3xtP03RerlXWJHwWI31/Yx9gzbVaSXnphi19RVEDkLXadqAyRhSg5CDWm6VdeSbheMS+kjXCWxhbDhMFkj+8jEy6TCRF3kE0WUaJVUETxrUJRobDAhRMxcw1O2rQNz3GhzixQSRTa6sg/v9XjVbvr6xu6+9bym5pL06cnt8HAL4ZGcMQKcs0C4wo4VK/uK7LbqqBCcCxgOKiAd0HMsZO5wuKHCkOhz5POCOLEQhYvdxrjh0Uv7Au7rb4lP8+F4LKhgJRA9lD8woVFnj4O2aKf5bcQTYovGLgRNQoRQ0WCMIEr7ewCiEgxdO+9ib2BHJR33ulFrMIp6doE+Q4Y4Mct8BOQ49L7v98/9dMUxVOr4r2V8cnG6/LLfR812plxiakB8sKmkY0aWJEUPVbhORBiEs2DO6pXOLjC3cd4OuEEaflyichm3uUsKvhNh+ZWbkHsRCTcZ584FvQKFfTRi7PUpk81b3NMgeRhnUVMhWPiprnffv6c7LiyswAPPbK+T8AggLyfOqEI8oCIgnsnXLdyxfUqvWa5VGUPb7pas8b/93gc2buQdSU8v/F8sEMtWLIksf6RiqtoUzYJCCB0PA4cAFBMTuXK6ZZr1uqww7J0zjnsH1ZqyRIjgKlopu3lnUVHALHRstjB1DBPYA6CDDLTYmvFb4dJEWdedrbsmHHoDgpzNQKCW785TALLLptfHsHaGSmiMCmh0tVttIs/G+WDvDDXT5u2VT3fK6He7f5W24fmaMSxDyhr7BivRggazOWu4I7CuPXWeSYazFSQOwgtFWRGCxe+jQmKBTPZ6FfkC0iBWzxgVeDNO1lcICZuYcQGy7+TioWFARWFgrKCLxXXUWgPFB1WBlYFVFl2o05dgbSwAOOIzeYgwcIadMLSgXp0nz4afH0Xz7VqZt1X/fYuCDngve77w6wcIowSymKLIuU7S+cmZwnWO6HLnMM6q2LYxwriQn1YFen7EHFUCNofvyxMnEgmdGjwRG1nDLAYuE6NqZM+w+bol18Sqk6RXYTCBBHB9MaCxU4oXByLoo0LYgJmYwI+jKdopWFDfwyhakHAcR9JpGBWxHfshhu8zR5dnEcgkDE02P9gNKALNT9tgG/GpB0KUpy5lnmPNkYy44VsyHgu44nCS9l8xSpOlYdpQfIYx/STaIV3MabZbLATRm2kb0GYI0gj8xb7VYbSijse9gmIa0c2NBC1jh29zfC7Ayp7U3a44MuLKx4WS4Q3qsRUT2FYs58fdvzD/jwFAWT3DIlFwYsSWc3SwJ798Nn9/ITTEyd6z2S/SoKFo47K+X44MS6RlGce26B7G5T156dwXwQ7NoHOFF6QdtzW99BeqJaoGSx6kHUU44su8ljvNWf9Jbot+sI556zUsmVGALd1k2zPzy86AohjNds2ZlYkfxYxJiZ2NnRyBiusit07HT4iiAIRCj7i+AqNwmTDmoiwF8WK4O3mWQ/ufaaK/w4m3FiFXSG7Q+wOv/yiFz45XHP+qKB3e5TUZ+8s1UvNS2hcgx7KesifqFEJwinBWJvYnWIO8bbFDGImO3Zv+CdBrPg7MyxKAAyTSZiJ3LspiRJWjoiWRt3D/APmrGb4LbEj5vuIimbRQKWBEGMGozz7rHTPPf4fCisfszaEHEWR65iVeS5bcEgk38OCCFlJsMArT18xQA8f8IWG3tDBU1nm1H/dn9Vp4IIU9/3Iw5i6KRAGcIZg01iXXur/e6Q6V5D3xbrHpR+iPcM5zyAwtAHOUpAhyCFkEZM7xBtzFW3DQkhHQt4msp0Fm/5Dob1oD5gK6nmkP1Rhfkd+n7V6tZbsdKDWjJ+pkrtV9LoFf+CueB14MQqo3XyzUz7dO1Cq+U4UUDDCXQI24eR8FDfMXyhlkLWgMNZ4JHvG235qpBJtXvfbGgLKBiiRwnOxYV5zjbeRhIczvyAe05VIJ0ozQHY+bzAkplqV56vc5pdvYrLCTxICCDOCxDH3oFBTGH9sBGIVRwDZ3bILzm/hgyCcWCZChYwufDffumlLlrJQ1B0pZc5gPujQQZ0211XffiW8uI5oxQ0BmsERMpRFHjfytMY+IUW9ZTP08cf+HBhFkaP/eF47Ez/zrRmBWwExHsCDAuaKyz/NtIaIOv/XLfq0b0l/A8j86grYobQSmZyuhY0hogHqH//PxopJkr5SqZIuefNCDzL2kCecsFJr1xoBTNemLA71KjoCyCRCHi12okj+9GLMkkwsLGrsBCF+LAaYkyJC+N3OL6p/TgykUehYS+u/vLdPLnhuvIkVJ3Immj599FyVt7XovNvUpVspDej5j554dVePZLr5l3XKcSceCX+Cs2KdYi6HZ2B92XXAe776gwmVH1i8WewhJ0yGkLR4E34ivYjVEBUumCS8SrJNhDDw3axuLBb8OzMrszOzZZh4Il8yU/PvTDwQdepHYbeOnyLPQkljlWBScslcXWLYBOoKIT9/TV89cNgQjbj+Tc/qPL9RWz8lBO1fkOK+H7bhpAHUJvoZRAxiRT/j2/GLjCjsQZxTOxwX/pAPUfO/p9Fn6ceRnRQ8ITcuPQlStvNZQh100c/8NxIUYwOyiB8CrIRCx6LfoLLRRuEVsCCYRbuH9qePsrpQkHQg/CyaEGhWcTYY9N1Q2fjXcu1YZQdtKVVGW7ZkeXuccKHrXVDmez85cFh9gbgDNIObDRLvYiMQlteR1hl4sL2QryxEg70iXikT6rTQET0f910Y2NREntsdCx+IGMzniis8sgL8/BPTEYoSSQRQ/2iOI/ZZraw5v+iNocfmnEYYI5ilnY8nCls4rx3/Tp0gIxAqOhjkB1Mo3wxBQcFkLNL/3dijzjAgVDz67Xffaes3g7ThljulE0700oBEi3Z2qfrCn4zgBuwQvFJnnurXIyLAjj7PHhwvktWqoAoP3PlfWibYHnWcMcMTLJm2mR6iFeY93gXp5xMp8Dy68ujznvLnOwggRJfvZbzStyDJsLt27by5k80Dz6n+Yx9/QxD4OdI1maLp/vh3U1z+aaYBppEGDbZq5qwS/rhnzaE4KwGbVVT4ZEtwKIBHXpk7mVOj+RaiErB5weSNMJCXDymNEM1/Magv380wAocDD1ypLVuMACbblJl8f9ERQHc6BzMso5uIT9QlBgcTHM7hzMKYR9ihutQMgWjDGGPj5gSRRBqNTS6T+kNv7O87h7uFLdrNzkQDi7vhBj3VtIyW3vqwOrxTRoP6LNeDT1f0SIIjgHAgZHhXmDixkLLJh+u6oJWtW8KzWXXfLsJEhxLEQsosx4KeTAl8XjYtXaF1pX2fPtaZsp3e1OoO73nAlV29NDtSmt8STZWWXS3IAKshqyIKIwsdjkAsDvgaJVhYzy77t4/uO2qkRl/f2uOWi55621do3Yye4LOyL3M+P/Qh59MIsQgzdBQ0Ik6iqA1YuOmWcB/IIOQ+rDQnXB3eD1HJb6QoOxXcBCAKkBwWRNQpKuYKHQ+S4OQPCEBhl8i8eLACWANtj+8FYwPiykIW8lVcu3CpKtSopL8XrFWl6uW9BZz1FpMdex/W+KfuCywAECLUaArqMUDTCVio2YBB1PHbcEouKx6kmo1jqCCQYERgTDau0l3XfXm7X0cww2SYSAHvli21pdZFnuDCcCQIBFGOsY23A68m88vGv1foxTtm657Wh+veh0OBBbBFSPsPP/hjGYkbVsqERWGi4EHMbeH2jFY/lGpMwI6gMKmACf27bVu9dvdMNV7cMM8vC8d4wFMQnGkLvuvQe8/yj7SMOFYTPsbchfV5sfbUnvrjP8JNe7OT7tXL+51pOz8p9iCLnvvkJUHiaOZ2+i9kn5cyVvluzPjLlmVzNbxPqg0Lgn8Cp0P4ETDRxMTRUZg64Kd8H/tsrEU7bF3jW2Gy/HQ1pUtv1agVh+uwowM3ozxRzOMCXoSKS7vT1uxsIy0YdE46FRtRx4bZ9DABxypsFKpV0911N2vuvBLZUwmbHaZapglcJ9kXVqtGMIsRwGSbMpPvLzoCyETJJIL5MIGCaoBQwmKCOYYBEM2VLt6jWEdYRxt1PtQnmmFCEL4RVYhByeLLwJ42TY8f2ler69TVW7121w/9V+q2B3byuJtbIxn3cKBwceo9Ih8TJRtXb72rUsafnVBSWPS4EXkQ0waTRLLR1YF5/ZJam/TlQP9cTj7n7lN+1ts/5A7aYF6EB0F0wpthrLouMJi1DBLrLKY33bhVB7x6r0/cMT9RZ1SqaMoqu3WUIrfQUyE2AIMGqVa7y3Xtlt666/I/Nf76lp4Z/Y8XOvlqQOTB8gn0E+8S516ABOByAwX3uvpn/RzCPeK5iDCINljH2GDA4+LtFWJWC3KGehXFPgYhQkAjC0U0n33vmXRy3CS4AFLEYhBZ8M3CYQtWUpBUHvEwjSSAjBcIDcQZxy5USBQ5yExI9V019y/tfEBlLf9jvSpWKZvjDSz8EBLW91K33KCzdhyv0uWCs2MhFhA/JCq+i8WR/2fgONMdKhiLf8Qmg7FN92P4/PbtTJ2x4H1PGau4S5YafHNpYof/0EfbtdPXm87zXKwocDSIBa4lkMKwn++V5b5UzRv3UoMnQz6vKLJ0HiYE5hHIDH6OLuMA4wQ1OsppF/B5RHuamz2vRyBRrGE+qNmokzwT1lOjhnZv9bga3LtB9zWLnc4KVz02oAhd7KtpPtRM+h2ukZd3u1Llrq+t8vX8JKaQOQwjCJnE6Tz77FbV2/CGKt1yie68ZqWqVQ4ibtm07r67hwn45GfPypCAB024OpjvaDx8pJ1JhbaGKOOis2aNtzfm8z2jyZD3/U0P+AYFOOmawEJBDabuLj6H71978DG+TBm4Ylx4wRZ1WXC+zj1xlb+hSbbQ8QDZHUFKmzs/Y/dstzFljsRiwsYgrwgWwD3gAGVt8f066QJsSiC8CAzswen3PKpSJSOA+T/jK9mG377uLzoCiPQdxeEXqxNZHNgI4g7l1iBcoSBcrIco+aypkb71eTUFr0N9eOyDo/3IOuQnFhNm9bDjNCyBwYpMz/axc2c9uksXbTrrXLX54gD9OGiVrr5tR4VhwLQAACAASURBVE/4cvVj8+qsc+F6QCB4L/MV6yQT38Mtqmrncd/6EwY3MivzMFgixNilsMjrg2L9/scf2rrnntp9ty365JMsb/GC+M6evVUtyz+vVZvLq+m/j3mmEzgo1cAsAwwQHaxOQADhc+5lOISzdiHQMLGySL18UHCGL5MZilostgRIqFhhRQ+7xYQJOveP93XL3t/r9pcP0eSqF3qmnKUtu/orYeQEShvBnOLtmMEENssigtzByhEqTJbwpDb1f/HVS2fWDl2DnzjrD5wGFy0s57ht5rtgH4thyoZoYxlmPYLThAufifB95Dev64xD/vTBvv56fdx6YQ6LKaLbPXVWqPQRB/v9OUIVy3d9I2/A9MSq6vwXWUnpxBBAVE36KlE7+OKFIsaXTVus3Y6oqlXLN2vHigG5C55N36GaNOPsX7aof7OJOu+4f/57M8yEnQfjgsHO38PHKPLRZ5yhdf9meS6EkAN841kMUX1o9q73jZGmTdXmQ49Qzxkn5VxjebHb4DkzIG8HdEhNt2767J+zsiP6qQJ7NDYDqFzhTd4N+4zUsYv6q0mp13Mihx8hzIjCHBJ5DjhtRWUjCvMHY4/5zXNBYBCyCQ0TfwblnDna2Ky5ymijdx28NVaBHLn9BwIi8yrDhznBeXzsWv5f/bPGPy2FfbEjuhDEzz9Yo19bfqThB9yms2uWyJWakz0Kz8xP4gKmAXj9pJta+goyBJAJhv9mruDvbIaZmDZs8IYom1RvLvqqh2+9YVwFBeU3PJSJJcF7AP+/7MLmk0k4cAk56vBNenn6Fbrk1OW+qp1s4WVhlyIU68j8l7yDQc/gZ0yzaXNCQKz3z5qlf446W5XW/+5ZydnbslHHaEa3cnGRdOUHHlip9u1NAUy2KTP5/qIhgKwC2FSY3COOUmLuh4Q49z/nssGOHA7BBO8GQjgoMpFGQ0FkQX+q74n+NphVnZ0ai1pkMlBMh6E8gQ/v1kOlTj1Jrw04TBOGrVGtK8t7C4sjgHxSNMsnEyM8hut4JMSi46a6qjOigc8wsF/ggwMLwOQBMWYLm0xZtEiL9j5JNUr8plWrsjwRDFEFkvdD2fP1VclL9fLah7JPU0KIZaFjgQuLZvA5eB2kjDkZsyjKBIsEimz/GwMfN1Zf1KBYbImPp+HCCxkPe+YZnfXGVd4Z8bhBYVGEYK54+32fdUVOzLBVVse8Ak1QTIjuCzoIu2QEBvoP1hmvKqMDH1RmTteIAeaINrQn6w/zNQKUU4Ty1Sw4OrGoRSH0bHTY1PA5KMXOIsTznXX9uMoLNf62tt5iseHWu1Rh0SxPIXWclvUDkfT0F2r5DezOIsxXJeNczEDELMqzKbyYRY7NCmQQxsImyous+i/Vyl+TFqnKsdW0bu1Wldsh9p6cdqHrc7vnohASC1n0nXumi58K1xQS4XJtMmcwfLJFfUzVr7+uzY0fV6mWL+fM+c5Lw4oPEcv4P7iFedIkfTb3aI8AYipFhIRk0m8gGuHUoViYGSP4+xakwGMgZTzbxWDRVeAGLm7Me3n4VCMGc4sWWvF4c+2iFbkym8SrB6QI1Rn+TlcB498uvU+HfNfBI+QMA8RkBHtIlFcCX+2e725Wl64lcsXs0B3g/+Ek+HlhASGl70+p28afe+vUUefH52j2tU9IG9ZLJUtp311XqN7Tlbydwtp1WV5beEG8/br5Ucuh4+Kc9dVZU9k7Qm5zTB90klDg30nHbNDjk6/XVWcvy0Em86p71N9RLOgwjA/Xtzxzc5S+T6d2QWpMRBDSyHyqbLiYOyhTp+rHkxqo9k5DvH0te1puo9syzYWDmleuXKmK/rP4nzRPblggpPO8yRTAPCGKe0HREEBkcogPs12oB2PSxe+KBZF5mjHA+kJhIwxBYcJlx8t4dj4fiX4yygOE8rm5t/nEz+UxZDvKn4jCIgNpYtc/6fFe2vGkw/XKV0dr6rh1OvaUch6HZAKnRGSpiVkl1Iq6E+rrlm/v8BcdJnSYI4wDEgWzincYeiIfO3++hu13q27ae2i2YuSlAnx8lcYtqaafK5+jR/brm50vlte6gMpwUCwLMwQFLgUvxR+O9iBwEzJV96zZajPgIF/NYOUIfKhysSU3EaL6ucIsPXWqTrv9oOxDXrAKo9CtGTrOdw9gxnf3us4BK8P+Ec66HYlJYDZxqi6PIMcu5kfMJ4gBA3stky6spcP+GKqdquzg1x8TVJUqKvPGq5o+PctTR4859F81u3CkLj81cDZCFknUxxEVg4/q0cMjD+H831gK6Yt0Qz4pTABdZpRyJTdo1QNPqtTlF+un21p50dII0w4SxCXaqN7nF/oqcjQCSB/npoIkF4fgQaYcAQzhzAJEPcrVIYrn/BwRuUvGLFDVk2tkE6dYXZbu4oL72Ry5VKDO8ulEecgFfS9cENHYB8A76VYsjOCGUufVGbbTtatK3nmrZs8t6fsKw3hg92xY3DnTqJj8iIyFiWHffb3NJ+s5giACDWPCxUuF64B7BLdjqQgX1Bn2lvBk1nemunA8AKZY1HbIPHsmOBBkErM4xI/1n4Bw3gkxdomVeYd3zPHYVlrS+DXtpcUel8hLEI83ZSy5pK6qfvlO9nMYI7RJNt44Wh9xhIZ+s95TWjGYOKELXGg3iFZkGpZ472Tj4uX7vD+Y7+rU0R53XKSzr9zNm9dRub4csEXLV5b0yO+qdaW893juMx938d1MQhHPdHF+d6f+UXc8U3IEmGPJYWPNQ2rX1hkbhqie3taNNZf4u/JkCko/axkvDQV80d1oWzYN9CUKnhPMpWB38tIvtcufETkPuQD1kJ04JHLiRH13dlPdXblvdrAyZJ37I9N/GgGUjAAm05GlwieALD6Rvkss4Mx8yP6hwqYOdY8oLoLSWI9ZJOnsLJ5MipHJnfPzuSwWTDDZyjyzHfYOtqThCI7goag+qHx8wrkrP9Xux9bQiwNP1IaV/6ptx7LeeuIyNjB5x8vZ6+rJwnDjhEd1Z/+r/IUHx2GXoR67XzK+b+4ls2fr28Pq6959B+ZMEedWtih2R1wQWezCVgwWWJe6gUUGP3EWIAQJBNOWL2/UirVlfHkNshOKoszRLjAuopDDD2en+sADOunkLJd5w1NxCKBcv2ytv1AzU3IPqyxmQBRSSAkXIWOwOPFct4q6l4ZsQszNuKnR7jQx1hcWzRUrtmrlkrV66J5/1bz9rv4KctNN2tqpk0poqx9xWF06cZdZenzFE7r6lMX++yCejjyEPxJ7JAsJ0X/UG7M47AzTaOfOHklgQ+HWB5fbFY4bmfcWqyqLxpLfNqpW9ek65MSddNQP7dRuv9eyE+7yaiyNPLNZ2Zd0bf0q8qTUcKHz8tHgEe1sxLwGD+3ZtKn+OuVyjzM5n3aIGXjSRPNPvMZvgxAL+m3YPFU/c79sVSnWaxgvtAXjGl87CAZKD2SCQGjGP0QZchQOUsVwwCdxnXOThHTBtfnNMw+yO+vfX+VPPFwTP5ihQ2qs8ycWdjqMAwI16Jd0DsYgvhkwtsCHDD7N8OSWWIV64R/K54fFHsYR38a0x16E4RYOImJc0V0gkIhSKIFsIBHbUHUgQMw5FDYhFLo8hb4y5qH3tVOr53R4iRnasDkILsmrLWP8vvTKu7R73y7Zyj8+ZtQjO3c3bPCUU7Rx6UqvjRh29E+KE7JcxqxEq4BFhH3UjEadfVJ2/fWqdPeVGjK2omfSBL8TT9iq1WtLeHPj8vU7ePO+p5R/kNuvlvWBvsDQo9/QJmzMc/A6BhQ+LFic+vXTGcv7eUT3ht0GSlfU9qrO3MxGMd8FZYGI/IiE3bQrezLM087QxWab6ZL5lL7rDmPJfqdj1UiwrI/LlmngX8fpkcrv5RmsbASweBNAcl5cQT8kVizoEGdLIpXwoXg2SUIXDjLzelfg4NRaEqeX898cJ3A/idxDnTivZ4T7e+ETQLa67NbCvljM1qwmBA+ECso+mRAgHUzmjnxwCe5IrKfJFCYu1nl4XyKFTSNiJWt+nd2H6JCjy+n5waf/ZxNK5CER10Aqrxz3lO7pc77vX4gM4hZnZowI80YBXuE5EH1zTBM9vH+/nJOGy3/nQhsL9HD/Jtrn2KM3a+36Uj6JRkFFtoUJs3qGC7Iu8kwU5QzFDxMaKdtQG1l0vbQhyK4QKUgXqzo7AcK4kcq40EXYsoDDSNyKyXu9FeRErV+62iOsWNrhMo7EOj+uJnt017rjTtWbb5XwZbiFC7Vhz+oqqw0esWdOP3WveXpo8eOqU6avT3IgF9GO2uJ+2JzzRGfLDyvA1nvMMZ7fGyJcRMaUqC0AGYAfT2j4nsYvqKzXfjpfLSq11KgzH8sRWAg5oUqlRg/XJy9Mz00AaRO3ySpIvkNYR+vW+vCfWh6PdY+AfLlDdJbUvk97nLJ/jsNf5w+Zrf3P20+bt+b0/4v82HCMCf75NDXkgIS/rNdY01yXpYtBqtgrsYGjO0DuMZfSFVDOIKk5kr+vW6dddtyoH6pcq6PKBIfV4s+A2ktjsBK786aRtFmdg3O92ezklSPYddFIaAloxdRKgXPgBoKV0BVM10yHkEDqjWUD7o6QGnlKZGQcDv6rd9YYrOPeb6izyv6oZf8GB6AXcCyvvPE+Vfywg5b36KeK99+kJ9c/q2Vbd1X7skFUOWMLK81vv3nzIAorB9lQqDvDMb8bc9xHvQM/nunpM82bbtLO9W7UqMkVvA2SLzpu1foNJbxx/c+mnb0qeD7f3aNnCEBTgL+DKY9EkMvhQuzcU9hIzpmjXT9/14u7e6zGh9mJv+lf+U484PxJo5w5TT9gjDL1MQfRn1mDSIlD32IvwqY3nCLUA5bgFyZCdqsvvqgvfj1Sz/Q4ONJbKleLGwEsvgQQ29hNAfkjEy8EkJwPUzk4SlIXSRzR0E8S4VqfB63PjHWaJLLaLic7mKT/k3Rc8DtJj0hyFO8Z4Y5U+AQQksf2HUUkSiFFF0QPYobVjwmQSX9bFLgC6zfvRL1gzmeCRW1nkLp8ZUjrTO4IA1gMMDmv+vtfPVNzhJ4Ycp5/YTT/jgQq7eUiHN1M9Xv+z5dRWJCYQd3Kk8t2kcBDIy/5+Wd9edLzevzAj3MmxMbExdYb1uWc1AvweG7xcm0dvEUbN5f05UDkKLbgzHCoL+FSsaJ6PDZVr7yX84xjLsekxO2Ylp2Vl3Zq81SQXBr7EqA5YoXpGN8ANhD8PxIL0jGypGuTILJ61cLl/5mOgkwj4Wo9e0w/LZ65Up33eNpXg4YP1+qd9tROWp29qJ21/wLdPe9J3Zz1gS9JQWJZiVxaDx6IPZQOxbejDrLlpw78PfC0J9MFgThu8UwI9qee0pKFG1W156t6pkoHLbjovlxH59JdGtVbq5evneDjHyo1J7XW4UPe9E1JEYnUE3o/8tM77+jDxWd7BNB1e0QblAsW0Pt3/dD7XNfmKHhVV83S4Rfvo/Vbc0YAR74TPzBgC3tf0JQQOUywECeUWOd2yP2QLYYM3YFrIenxCr8znyRqteeZ+Aqj3rFoR7go53gVazTdL5IAEhHr4nEgNOATPtQG/gmJZfij6MGxINXsk8KB8ryMLg35cd2fLjXlm9+13+xBGlyhthatTu487nVNX1X555vor7uf1O4bF+tRvaaNm7L0xpN//PetMJY99vBwYV/jMvIwbVG3KMH2cduE4AXwmfNakNT55ptV/tF6mji1rDfX+h4cW7V5Swnvw//aUsnDynPX7NTWl/aQhkOFfQ4Y4uqCIYUNBabm7OIi2Il8q1BBWW+08X7aenZNb1FAOaSf5PtgmhwRKpW94c4rWENY15gWIc0owCh+REDT9vRv+j5kOFeGARyiIZTIh507eyIpc2RewcpGAIsnAWRVHC6J2XtBSAHEtRjNK3xcBeFmTLeQRGZXmEMdSf2Djs6ZSxw0S0Y6QpvyekbkQC18AsjAgxBEIYBMnAQfsBCgnqOO8W/JBsHGmn2YwDANMBgRcYigQ1xi0kBJcWYWduv8HX7BWs/a+Vvd5zyBa5e2zZI6PQIR64xRr+rhzkf4sz3kGJsLBVJDxAH/FqgR3szHTJKf814nTdLnZ7ympge9l31Ie0ILfj4ucnm8tyh0SoBLlgbQ4VK2rK6uuVRV9tvRU/oo3O/EOxQvd3gIIijCzOI5a317IDMmW2WXMBjmycqM/YnCzEhjhSN+gxRDf0//K14OVTV/crWmj16pnk2m+NvwffbRP2X3VCX9kx1hft4B83TTxnd1R98r/PcizdFpwwQQ8klHYZVnF8MKj5MTK1FglqVv8+2JHkvrfduzz2rV/H+0c4+3dG+lj1Xiumu82JhwYawwvE7e7w9VOfI/NoQIet6OP6r9qpt9uSlWslvqTmQP45NBSH/Dfw6pkqj0IUP04a+neATQxUvwz8S2ANnn7X/3pdXgJBLe+13n2br47r20dmty6lQ+umPMS1Go2FyEI/RpCxc5y4LvDoJgnwG+qDLAgVkxXqo+5gnMtZELOBsZvBUY3vg1IoiHTcAI2OwTIAbxXFn5KJe5xEV7Mm91fnSmyg0fpP87v6ru/SbnCR75xWxT3/4qfeWl+v34y1S1Xm09OKmup5q7GITw87LPN3/J/1cXfOGCZBJ9N8G4TBHzOgW24BtvVOnnn9TM2aW8PoWSh0C7WSVU4vdFWpJV1Qt88Pwd34oeKMc0gHKMmhqVzGGZgJnDWlu1Ulajhqq+2xotOOrS5AigO/bwr7+0tdLu3vBh+mYjwfrijlxnWqe/MG2weWJjwuaAqSLiGGa/8+BXzYfcd5+3HkIs88oZbQSweBJAzu8h5ooT0zF+ORMwudXZhtULDSyklTcl7c7hVpImSCIJVGi7ppnBNZwnltcztj0BxLECL253aG/ojeyyGeisnQwCJkYEQ2eVSXRCSfQ6FBhiLSCZQRCqtxNjrWYj5zgXkz88A8Es+1hKHOHZojMoo5wekWgdPDPKiDZ69IpffKcWyJ2LZoEJQaKQDNwpEKxeyBDhXA9MOsgjzDbOISdcgXHj9Ml57dXi4Hfy3DUmWu/I61ymlQ2vv6XS19b2G5JGBFB2rqyyrISUyZN18P4b9ebbpTx+RHGnYfHf4QXEpcr6bcEWVatRUivf7K4bHq+hdSfhyZCzYLJ5v+Nq7bZPhB2KrfIVV2jRuMVetWiuaPwZngP8zuG9/A5btbDkPtpHC7Kd4i888Bddteco3Tr4Vo/nlJwx1V/VIwt9AzMTbQVRZKU+/ngt/7ecZ5Kib7Hzz0+0JCRs87wFKtX9HV29yxDtd9e5uRZm4oVwjZjxfC8d8tz12bVCpfmr/2h1XHOzT9BiEUD6HlIWkRSwN5idS9IOCWzYUB/23cEjgM7Uxz8zLrzcb84JL3Bm4lWftZytGxvuoZVbgqMfCtrJCuE+Jwq7k874NDZymAqZB/AtQ2EEBvomEOAH5vJfFkIVCv8R7JKYpCDuifqzxKjF1t8Xq0S1qpq/8/+pxqjeuveNwz0uH+Ge7d2NSZNx5J1vrv9cNlAw82MQQdRn07Kg9ygvwGjrdXVUonWr7IM63OFI61VGZebP1u+lanjeMt44bh0cMpwdpuzXxR0awx4asoT5l71jdnE7Jdj6d9/pt0VZKv9Fb+3Wu73H0nA9wvybb+uTI4B//60lGyt5RJWgFNxa4HH0N+cuEdkEWHpRv92mOPt3pHYWR0xQJUp4ogVuDnnFqhgBLH4EEH89VL5gWfQI4Lm4MUsaLGmspCdCHefCwAyMvx+KIT5/bLPXh64h+xGm4uYJPCOyTxa+AhiHACJ/E/TBjtv5zWCejfClLbQJlF0XkwsTP+sdixiDkEUU05yb9Bm4zK2457kTurycE8woMBcckQpYUPeP+Ot7PTHvHt9mAbF0kxnPxi7ATOfCir3M1Y1ySgUAh6wAW8JGzaqLpODSRSxcqN59SqjtYe0LJcVVtE+NmmsZ2x2qHaQAOZUQ6qwsbSy7o8peWNNbZF1aH57Jf0PigCFcUAOZOCeU+Z9K33+3Tmhzkzp08/OUhQvW7O+HbNZxJ5XyJUUX6YpduU4dzfthoWeyisXXUXvC/Jn/7tRug3bYsaQXgciidtlB03VQ+d/Vduq5HjFggWGCDz8T+N1RcawHbCYI7ubbIJeID8QcQJycU39C3SeIIi7Xq5tOLjdZNRse5yWCDReej7/apnYdVfL+/1KxZBPAtbf4qzbMJlpxcgu/Ie3B6pAwcGKjkbOyPFUF4sqlrEmMUfYu3oYJdZaP5V75zf/u07/onqcqa9mWKHb3hD688C6iDV3QCE+FBzC+4ecu2pgNKL56/AZPptsS2JG2hcoygcXKNZfPiiMQu3R08VLb0O5MOU6Fjsy/l+hrccNj2vvt6589oDcdeqRKjxmRfVSvMy2vLrWLKswYr4VlDvDmCs8F4dUW/iYrbFMP8hcyLWIZpusSAZzjeDpnqg07WjJ42AkkQwBZC4IcNUMmVfIEf8QDRAzWNvByhxFF4kMfI/CJeQUre9gXkPgtNtloAVSRPpnDpB0FbCOAxYsA7h+Yfk/GIha0Z34UwKPIPpL2CiArHysUBCqiZOeDmuLzKpe+LSJ3b6LzSp7XYSJg8cZVigXAmZpxHIdjsbhRWBiYROBe2SYadmT4dWH+gzUWsGRPsFU6+J7QVCqcQwE5h5kVAgiDYEbhneGdPvYESA6mTuQlwGNBwKkxKO/9e7U6L74sV96uAlY7123ulBP8wLLTWGHyZHECNIgE9ZM/CWIOy3FtEEXI75Htzecw8bVbcrV2vfgUXfxpXf25YddcdcCRmjY87YIKvrQL6cTOwi6/cmXN6DvDHSYQ9bMdAaRZ6YuQ/oM1SxPHbdYOxx3m3XPVQVO0cGVFjfuzhre7x7QTebQvJIMmQ0hjIud7aVKaFnM2/ltAk++Cyjtliir166ot69brieY7ez5F4QLhHHjGi6p91+45ZCuUhT/6jVanf2/1IyMSIYA4yCI14BOBFB+k2uCf6LeYSiGwOZQgF/0Lq5KvqLV5YLYebb6r/tqMR0pqC23DXslFMOPOwfBFEWQzCKmF9DEf4FvIeh7ZT1P7BVHeDvlBkmU3kOgxd3E+AozopxgdaHr6rncSSURhAwPJQuDnHvo7Bopw/FUiWAUCvRZP8I9P+1dltYP+zU4679K6LNthL+0yfoh+nbVBB1x1lDYPGxUcTrw6V16gsIKHQkle5siT2LxKw7hcEulQvpg4h/bE/yRHAJcuVb/hu3nNwdQN33QJxGM9wAkSKK74UYKj8yxx/vDMIZh+IX95ZQczAli8CCCOUh2DhI0ufQ0zJgkAeksiJwEeU/nxAcQ0zH34AI4MfAAvlxQ+nDXsRxjZNz0FsH79+ioTrMq1atUSf3IUBhKSh8ujF2+IxCGAyO1MNAyUTCnwOYhEs9O/8W1O4bNQo4GAyRl5EhLoCltkHCfZCeNIhA2GAIWQ82RBj6FNtB1Cri//VY3VFXaNEomcFiTXjnMwR8zXYUV96Z96qvjbz7q5/Keav6Zyrmuz8043Oc5fwVjpwQvJqndv/fT3Xh4XBOJoBVhZLFAW8NWBAFxX5jP1Hr1fdor9OgdN0Gdzj9L1N5Xy1DyiTiF0oTRk3jsQwQj0ILExPk4spvg54bdEPSOVu4RwDhJJf1T5fs3rP03Xf39fdJ80iD8rMRuKoGQTwPWBP6Z3tESU4nZd/D87ICqM6Z7+Vr685/+KsMs3odrgOoFyzs+emRBGyiIYBLvgldDs1tlq2mZnLd5UJaHP3JYXYTYj5skFV9DWdBFUPwq/IQqh6LIhYDMT6cK6LetXoGdjMWCThU+Bi8go0IP8m5z5ln0C5nD269F8VSF/Lm0JpJnpi41Tgqd5ZteQIAkv6GuJfy76qn2O1M7zp2RPhdlzS+XDtXvjOzT3ic46ZPNUbawe5MShQ0YwVPbBBNwTRIgYDQmLEAn9D8XR09mGCbRgZzZ0qHe6XIxTG+MjC3NjLVy6VJ8P280b57w7keJwp++hEuLlg08q6wPjCEKI+sd0DwlEBYwsAwcOFH8oGzZsUDvfj8kSQSfSACm+BpvWbhF1IH0LQR2D5OfkI4K3kSS8bf4XmHaR0px3A35+RAdjRiYKmL9z2KsjjS4KON4zwlVI3ASMd3U4u2ksMFlVmVGjzKoQQMwKcJdMKazR7Fa9k6BYbEPyF8oEJIJ5HTELHnXJeeu165xxuQNPWImRKVEDsWkzIUIKg5Ko2aCguLvsBwij7pjWWM/ClxIzHPck6iuE+vrYw+u10w6b1OCJ8poxI3eKT0giJOSyz+70H459nQmQNDctWmQfWQcBjVZY0Fg/MUkx2YL/s3830K3f3OzLv8TlnN9Jn/5+shp0OdqbnDHvEMEYPhqOyZl1hJxu7Pz53iAmwiNKBFyHuFnikDvHJggejD50/FWOh8BKySocegk+SIv7jlbnjbf7/SMWAQyieX4ctdUjRXwX4jIqOEOXLoY/FcofiivdDZ6NSuRxDxLDwYhZQYOE7Y2umK1WHSvot01VE/9WuzJxBLBtImFiFYgm1SX+JO9Kz9XhMj+hM2SD/w8HrUR7HG1POkXU0iB9YsJvzXF274QJWralonY78QBPT3AeMLhV/H5GHVVd+rN+2eN0/d/IjtFObcx+J8qlGyK5klm7q1hwYFleskj5kbbBucIFTsEayoXz+Q+7+mcc+4aPPEs4xQ+kmOmLMcdYw20EIo5KTVAOgfzsa+MVUwCLlwIYrS058dmlgeH3MyURr85pj3jUtwhUQ3cvvoC45BIc4vIA3heogO6avJ4Rrse2IYCYf8OnQARvZEF1Z4DnOVq2kwuYaPluzGjhwkBHZWEXChEh+hClJa6VBwLOak3BoSR0nESB0xokiDOcAsUA0yDEgMmMZmb3jhDpTG98D073ODo71SWRV5CGBz7DguDMKpH3EdkJkb6u9Gd+R6LwYkhgzZrerjnKcdPxXw/wzaPwJQAAIABJREFUVBa5CzUTZ3v+LQ9TG36s+PJA3Jmo8VlCGUSkxWc/4JOJfPp/15DoDmkSAhjtbGR3JZ2KoBuUkaBQ3d8/G63Om+7wFWKcKqOVhQu1tUYN7b7bVm/xd0mZ8T7A1IdFHYUMZdNF7aOm8SrcJrwOSi4TEmZK2v/E3XSX3lGnRRfr103V8/e9dnViCLjIHxTifOUViv54hgw8EjMj/TWe35p7AmobgRwMDTY8+SmYNbHEOmUeBTE7zUs5v58xtyy450VV7/SMZtR7Q8d3b+CZSWMVxhwKLmM+nBImbr24id34Dz94G7gC5eB3BHDZMvX9fhdvs5coAUS1ZPPM3o2C36Az80ICmU/YcFFwy80rgMwIYPEngPkZR9vi2sIngES1whKiEECirthJMiFkSsHRlwkzMneY85PDaspu1gVt4mLFGht57B07ZIQuduCIOCzYJM9lnWfHiFXAOUVvK2xZODB94o6EaoBVirgBJmF3khFty++YZvJjKnKxQzwfFcrx3PC3xOla3mVwYnzzogXtxsSEGRyGzosxtbkM/0jVRV3c0YAQwFyJzUKVwaxFBHYEAVz06Wh12VrXV5ojjxtxty9YoIX7nKZ9Syz0/Bcxn2H+4//pQ7QfMLgUgygUCJEstp7giIISCpk9VNN1TYWv1GunuzV78Y5FjVhmvA+7KzZU/C4jd5IFQIC9BV0MvzlcRSH7eRXIG+QE94b8mszZVDA2ne8gVoTsKN8gdzjz28wBs7X/t1007ax6Ovm6feJ6HLkMWvhyosKhYGefZhKPNbJTHjbMI1/k28sr0CLXo7IdFpfps+928chnduBgXiAW8u9GAI0AJtulEieAifoAeoff1vX17IgCAcRXKV6y1WQ/KN3uZ+JjgsBUGFmIWIXMsY4HPvUemXMBbOGj5pz4B19BJEJ5w3zMLhbTMb6GkLFofiOFhQkEkEhchCp86SB+vJPmxqXMuSdBeuEgLt1hIu+HaBDJhykKKzlkNrLAeViwWFD4bmchxVxCfVAVWBhy5dnKqwIu8yqrCE5j+CiQ5qWoC+oEHQGmj4k7Vo4KL7t4rRwhzd6RXh+P1jtZd/lBQnEIYP996qvJYV94picIH0QQggcJp++xUDtxGaWTzQnqZnZ0o8vJSEqCXUpr3bosr8qx4k6KGsbt7n0wczo1A48BWMwK/QdF3FkEGGYoieH8+oxh+iIEM8jr7m12YxWif5365vm//pFA4BXMl45eGARw+XJ99m1Fz0cSc24qihFAI4DJ9rsiJYDI3fgqZRIBRBljogtZa7PbDIJEclXSoLjDQcCIHTn+ZWEiw3+z7jPpIQ5hAYUwsSuHv/AezJG5HKGT7SGh+91JZxBPyBdWSKyNEFz8gjBt8AfBgm+KlYouWpXwnYNMspvHMR0zZGThnaiL+P6glGJqJjIRxZA/mKRZZCDR+SouPB2pFlCTiPrO13sjLyYCAykOuRiCF8sGROQ4UbuhnDbZBLDE3f7uIDLXjnvX/Pl6b9+n1eWsnh6fwA2BwAgWaHAlqtfl0EvkW5xfE36V4eTLidxr1ySIALsh2Hm2DJvgfWlymUsz6U7dwEcXNTm0j/A2F/QhPtGlnYl3miHR+QwRiCTiKPslxL24hckRlX34cC/Ygs1iOLgrIbhC6RA+HVLRS2FmBDAh5LbJRbk9xbfJa7bbhxY+AUQqQI7CwzWiQG5i+Xdttwjn88OYBFHBIIZhEQqfHWeiQ6Fh1wvpYSKEAOLTgo8OWVm2VYEfYXZm0YfUYgYm5RyEjb9Td04wwCfG5UlOtC6RZ6DGug9XPdKyEDiDmRx/RBYAFhMWlgJFmMMs6bNIEy5BWqIVT8V1EEAYMjn5guIla+4zWl1L3uNH6cYigL/+qp77P6d3zuzuKcnJFtqNRTjSZSHZ59r9IQTYlGBZCZ00U5zwcWdJk7YTtZmCz2z4HF5+g59hOHLJ+OMRQOYbLAGQQDaBbGKCwPTY0ISO2MBcjKtDgQngihX6dPDOXlwOGalSUUwBNAUw2X5XpASQAIH8hM0n+3HF8X6IDDvgSFcfxCE2ryy2LiMMGePxQYGzMKE517Di+N0QS76NtS5eQSCDDGPuhSRDQOhTECAUQAIw8l1whnL5XiKZd74fVgQ3ELSCIhSNAJa615dB3XlnkdUJCGDXs7rHDDLOzxcQ/Yy7pBflbmXbIED/ZJeFs3AU3+pt89LCeyqR9Lgb4BccTdnnTVgO2PiysSU7EX6C8Qigqx2bP/ZvJGEO4pLiE0AS6I8Y4c2XLo1M1Bvw9cMfwoX3u4uc8/aKFfpk0M7eAU1GAAuvr+T3SaYA5hexnNcXPgEkIRpe5VHMV2G/jeSqbXdvbwjgtkYkIM7g8QqmHpRIIlPd3AxpRjXAsZxYjnwXnI/c4auYeKLZ6/P90G14AwSQfJshfzBcA+b1Hq1uZev56ZpiEcB589TjgKbqdta7hUIAt+FX2qMdAnR6bPX4PHAKRTErzgRMcFYkn3KfgksLpAxTMBs6zLOsF3kVTLm4wbApjnL6aM7bYXz4PYwY4eWtRxCElEYtJ5zg+7bEit5buVKffLOTl/qURNepKKYAmgKYbL/bNgSQKEGctSIKAxrTXaqippIFy+7fThEgYMKdvRzrIOF0+nTyRRASHQrfZFzN7TVa3crd74eKE70Rrcybp+4HvqDuZ3XN86zRdPpkq0vxRQBzLXM/x4bHKrgQYAJmX1OgFEqJwAMBDFIMQADjZVryiDauFJEEkLGFo+zKlfp44E6ey64RwETA3zbXmAKYHK6FTwBdQrcoBJDIzVSGzScHld293SKA/IgEwbEQRCmle4lBAOd8OEbvlr/fjyjC7hatzJ2r7ge9qB5nd40aaZ3un271MwQKjABOf9iJR470XEXIC40PddSSFwFctUp9vtrRUx9JRZOKYgqgKYDJ9rvCJ4AkECM6kYiEiAIBTGXYfLJg2f2GQFoggJRCsNVDD2VXx0uG+/4Ydd+xvh9OHYsAzpmjdw9prp5nvWMEMC0a0ypRZAhAAEmzNGpUwQkgCRGJZAkIoDuHuMi+IfQiI4BGAJPtd4kTwESPgotDAElfksqw+WTBsvsNgbRAgDwt+NpGI4A7PeBn4I51XMOcOep2yMt6/+wusdWPtPhIq4QhUMgI4FgYHLeY59npsRRA1PVKlbxAq48GVPAeR4xOKooRQCOAyfa7wieAZD7GOZ2zbCIKBDCVYfPJgmX3GwJpgQAEEFeLUKg4yvrMnmPUo+KD/lEosQjg7NnqdmgLfVCzs3fmrxVDIGMQgAAGkl3SBHDNGn3Uv7wTFFMCoRFAI4DJdrwiJYDuwIVUOc0mC5bdbwikBQLXXOOf1RaNAO7SwE+IGCsx3+zZ6npYS314dkcjgGnRmFaJIkOAY5Jw2vvxRy+jDn++/TbG22MpgLhXkLV+zRr1/qK851JI/tNUFCOARgCT7XeFTwBJ5oRpioNiIwrjL5VRU8mCZfcbAmmBAAQQpZ3jUIKCa8X0HmPUc7eH/SRqsQjgL7+o6+GvqVfNjrFTYKTFR1olDIFCRoAFqGVLL2ojaQK4dq1699sh5rnlhVzzqI8zAmgEMNl+tm0IIMoE54VFIYDB+Eu23na/IZC5CHAcChutEAHEtWJa9zHqWekR/2Bmd5xCJEqzZumdI15X75odjABmbg/KzC/HBIUCMXq0SKJPJLA7TzwXILEUwL//9pMZrl2rXp/v4KUVHDkyNXAaATQCmGzPK3wCSMZ6FqYoBBAXjFSGzScLlt1vCKQFAhBAxlno+A0I4NR3x+i9yg39I+34E63MmqUuR7RWn3Pa5/8YrLT4eKuEIVBABEI+SEkTwHXr9OFn5bzj5zgSMxXFCKARwGT7XeETQE6Eb9RIYpGKKCEf3GTrbfcbApmLAJsrxlmIAHIk1ZSuY/X+Hg199S8WAZw5U13+7w19fM7b+vrrzIXQvjwDESAKkYEyZox3Zjonj8Q8DzuWAkiEPedQBgSQ4zmHD08NlkYAjQAm2/OKlACShimVYfPJgmX3GwJpgQAEkGPB2GgFJZsA7tnIjwBeuDB6VWfOVOej2uqTmu2MAKZFY1oligyBUBqKpAngv//qg0/Keue2GwEsshbM9SI7CSQ57AufALIwNW4s4ageUUJ5OJOrtd1tCGQyAgRYnXii9Oij2ShwJunkLmP1wV6P+kmgYxHAGTPU6ei39Nk5b+mrrzIZRPv2jEOAkwiIlho7Vu+9J3XuLA0dGgOFWAogKZb22EMKCGD79tKwYalB0hRAUwCT7XlFSgBDRzEmW2+73xDIXATiEcBqjaXZs/1AkGhl+nR1OuZt9T33TX35ZeZCaF+egQiEjqJKmgCuX6/3+5RRhw5GAFPZk0wBTA79wieAnOT92GMSyWojSq9eSmnUVHJQ2d2GQJogQJL144/3lfagENw4sfNYfVj9MWnWrLgEsOMx7fX5uW2NAKZJc1o1igiBvn39w+jHjfPOAe7YUfrhh3wqgH/8Ie25pxQQwLjP2MafZQqgKYDJdrFtQwAff1zivNIoBPDNN1MXNZUsWHa/IZAWCHDO9nHH5SCApFea0GmsPqzxuDRjhrRoUfSqTpumjsd1UL9z22rAgLT4GquEIVA0CEAAX3hBGj++4ASQJOtVq0obNui93qXjm5G38VcZATQCmGwXK3wCiG/SE09EJYAffqiUhs0nC5bdbwikBQIQwGOPlZo0ya4OBHB8x7Hqte8T0rRpfjLoaGXaNHU4rpO+OLeNEcC0aEyrRJEh8PnnUrNmHgH84AMprv9eLB/AEAHs2au0unSJ40e4jT/MCKARwGS7WOETwBNOkJ56Srryylx1gwCmMmw+WbDsfkMgLRC48UbpmGNyEEDya47rMFa99ntSmjo1NgGcOlXtj++iAee1Vv/+afE1VglDoGgQgAA2bSpNmFBwArh4sbTXXtLGjer5Yan4qWS28VcZATQCmGwXK1ICmOeuK9mvsfsNgUxAAAJ49NG+r21QIIBj249T7wOelKZMkVioopWff1b7E7vqy/Ne1xdfZAJY9o2GQIBAv37S8897BDBPMSKWAugI4KZN6vF+SXXtGieX4DYG3gigEcBku1jhE0Cc0595RqpdO1fdcLxNZdRUsmDZ/YZAWiBw003SUUflIICtWkmj243TRwc9Jf30U1wC+PaJ3fTVea2MAKZFY1oligwBCOBzz0kTJ4qAxLj+6LEIIK4V1apJAQGMe5zcNv4wI4BGAJPtYkVOAFMZNZUsWHa/IZAWCEAA/+//JIKtgpJNAA9+Wpo0ScJXKVqZMkXtTuqugee/JtZDK4ZAxiBQmARw82Z171lC774b5zzhbQysEcDiRwCflXSrpN0lbZA0XhKz+ORQX9ki6V9Jm+R/31ZJp0iaGrqmqaS7JEHgeEb9iN+PkvSmpOMlLZfUWRL3RJbCJ4BEJ7LLuuKKXC8j91KnTnFC77fxgLHHGwLbBQI33ywdeWQOAsgJO6PeGqc+hz7rmbjiEsCTe2jgeS2NAG4XncE+ImEE8HnAOjVpkvLMSRtLASS6fu+9pYAAdu8uffttwjUo1AuNABY/AniQpD8lrZBUSlIDSYTyVQ2IHh0EAniupO9i9BaSfz0g6SJJcyQ9F5DKgyWtlbSjpFmSukpqJol/J+f/a5LeiHjmtiGA+FlcfnlUAhg3+3qhDg97mCGwnSIAATziCD/aPiitW0sj3xynPoc95+U5E/nKopWfftJb/3tPg85/VfjEWzEEMgaBwiSAW7bo3e5Z3pnCQ4akBkEjgMWPAIZ7SllJ9SS1klRF0tLgRwjgeZJi7SvmSnpd0lvB9SUl4fH9iKT3Jd0mqYWkvQIyyWUQzQclQUDDpfAJIOkpiLSKQgAZLKkMm0/NMLW3GgKFjMAtt0iHH56LAI5oO04fH/G8d9i9OLIqDgEcfMGrIi2aFUMgYxAg7J0MFZMnK89jSWMpgJywU726tGWLur2b5R0pZwQwdT2oOJ4EcnFA1CoGBK21pP9S+vsKIA48pSXNl9RBUpcAYggbJl1MwqNDsA+UNEUSh4NCDg8LFEJ3CdcPl8Q7V4fuK3wCSHoKkm1edlmuXpHnAdyp60f2ZkOg+CAAATzsMOnJJ7Pr3KaNNPyNcfr4yKbS6NGxCeDkyXrzlA805IIWRgCLT4tbTQsDgcIkgFu3igAQAhsHDy6MyuX/GaYAFm8FcJdArePQzk9CzV9T0khJmyWdH5BFbD0dJe0taUFA8GaG7uklaaWkewKyWEHSDaHfDw18BKtLCmeILVIC2KOHvEHzXSzjdv7HgN1hCGQeArfeKh1yiK9mBAUCOKzNeH1yVFNp1Cjpr7+i4zJpktqe1lvfXfCyOBrViiGQMQhw9A1uEz/9pD59JAKnfvwxxtfHUgAXLpRq1JC2bvVSwJDazAhg6npQcVQAw2hR/2WSzggUvGhI4uMHETw9CPpIjQK4887SClwX8yjkJ3vpJenSS3NdiMNsKqOm8qq6/W4IFAsEohDAN96Qhr4+Xp8e00waOTJPAvh9rZf16afF4mutkoZA4SBQGARwwQJpn32yCSD5BAcNKpzq5fcppgAWbwWQ9iYQBFZ1i6RY0zGRw7UknRZ0kGg+gKh6+AB+EASEvJofH8D69eurTJky3uNr1arl/clRsrKkQiKAqYyayu8As+sNgbRE4LbbpIMOkp5+Ort62QTw2Bek4cOlv/+OXvWJE/XG6X00tFZzI4Bp2bhWqW2GwJdf+pHzP/2kjz+WOD4Rb4moJZYCGCKA77wjL5r4m2+2WY1zPXjgwIHiD2XDhg1qx9FavmsXFsCMK8VNASQYA3MtHtqVJb0k6ZrApEvY3rFB6hf8+Vw08IeSIIFeSwd+fkQBXyIJMsgqQGqZQ0JRwJiHiQLm+QdK4th3fAMLHgWcKAEkQe3LL0uXUL2cBfUPM3CqwuYzbnTYB2+fCNx+u3TggTkIYNu20netxuuz41/y8yzFIYBtzvhEw2q9qE/CjifbJ1L2VYbAfwhAADk9Z8qUghPA+fOl/fbzgkBSQQDDzWkKYPFTADl86YQgVQuMfWyQqmVC0LDYTVHv8NXbGASBvB3k8Qu3/fOS7pW0k6RxUfIAHimJ+8gDiMLYXtILUeaCxH0AC4kApjJs3uZCQ2C7QAACeMABfk6zoHCqwbevjddnJzT3z6Za6pIKRHzxhAlqc+anRgC3i45gH5EvBL76yj8/e8oUb/PTooUfMB+1xFIAIYD77+/lASSjBb6EgSCXr6oUxsVGAIsfASyMdi/MZxQ+AeSEAkbWxQQ75yypjpoqTODsWYZAyhC44w5/EYoggENaTlDfk5r7Evs//0Sv3vjxan1WX4248AVPBbFiCGQMAhDAxo2ln38uOAH89Vd/87V5s8hpyxgyApi6HlTcTMCpQyr6mwufAHJCAc4VF5GnOmdJddRUuoFv9TEECoQABBAz1LN4hvjlrbekwa9OUN+TX/YTk8UjgGd/rpEXNvPUCyuGQMYg8PXX0qOPegSQACg8lcZig4tWYimAEEDcLzZt8gggSiKPTUUxBdAUwGT7XZETwFRGTSULlt1vCKQFAnfeKe27by4COKjFBH1+yit+WOIykgtEKePG6fWa/TTKCGBaNKVVoggRgKk1aiRNnVpwAjhvnh+AtWmTd6wpRNIIYBG2YcSrTAFMDvvCJ4AcUUWCpQsvzFUznGZ79Upd2HxyUNndhkCaIAABJBUFZ24HhWDAga9MUL9TW/hhiXEIYKua/TX6oue90xCsGAIZgwC22oYNPQJIDkyylXFqYtSy447SmjVeupccBQJ48MHSxo0eAeQ5WJZTUUwBNAUw2X5X5ASwqMPmkwXI7jcE0g6BunX9ZLTRCOBpr/qSxHLShUYpY8eq1TkDNObi570UFlYMgYxBAAL4yCPStGl5E8BYJuC5c/0k7Bs3qmNHeedpE1ycimIE0Ahgsv2u8AkgZ5RyMn1kLkGOKOkiT3UoyrxJyQJk9xsCaYcABJDzSJ8nGYBf3n5b+qr5RH1xZkt/RYpFAMeM0WvnfaWxFz1nBDDtGtYqtE0RYOF5+GGPAHIONieWjh8f443xCOChh5KEzwjgNm2sxB5uJuDEcIp1VZETwFSGzScHld1tCKQJAnfdJVWrJjVtml2h9u2lL1+aqC/Oek3izNNYp/aMGaOW5w3U+Iuf8dwxrBgCGYMABPChh6Tp0z0C2KyZNMElYIsEIRYBnDPHP4d7wwZ16CB98YXEASOpKKYAmgKYbL8rfALI4OBYggsuyFW3VEdNJQuW3W8IpAUCMQjggBcnqn/NVlK/ftLKGAcDjB6tlud/YwQwLRrSKlGkCBAc1aCBRwAx3bJ/yjcBnD1bws99/Xqx6WKvZQSwSFsxx8tMAUwO+8IngMjjZKU9n+OLc5ZUR00lB5XdbQikCQJ33y1VrepLGEFBjej/wkT1P+d13zEpDgF89fxBmnjJ0yIi34ohkDEIQAAffFCaMcMbInhQTJwY4+tjBYFEEEDIHyQwFcUUQFMAk+13RU4AUxk1lSxYdr8hkBYI3HOPtOeeuQjgFy9M1IBzW/uhiatWRa/qjz/q1QsGa9KlT+sDTg63YghkCgKDB0sPPOARQERyYqhiEsBYJuBffpE47ODffz2/W9xtjQCmrgOZApgc9oVPAImQIifFeeflqhlRU/hepCpsPjmo7G5DIE0QgADusYfvxR4ULyKx6SR9eX5rPzlZLAI4apRaXPidJl/ypBHANGlOq0YRIQABrF9fmjnT893jIJ1Jk2K8O0ECyFrGs1JRTAE0BTDZflfkBDCVYfPJgmX3GwJpgcC990pVqkQngBe08c+nWr06elVHjdIrF36vKZc+offfT4uvsUoYAkWDACfk3H9/YgQwlgl41izp6KOldes8nYPMMqiJqShGAI0AJtvvCp8AkiQT79hzz81Vt1RHTSULlt1vCKQFAhDAypWlF1/Mro6XlPb5Sfqq1hv+CfWxCODIkXrloqH6+bIn9N57afE1VglDoGgQgADWqyfNmuWZbZ96Spo8Ocar4xHAY46R1q41Alg0rRb3LWYCTq4RjAAmh5/dbQgUPQL33SftvnsOAkiE/afPTdJXF7aVl+CPUwyilZEj9fLFwzT10seMABZ9y9kbU4nAt99KjJ1kCODMmdKxx3oEkPO3iSvBqpWKYgqgKYDJ9rvCJ4Cck4hD0jnn5KobwmAqo6aSBcvuNwTSAgEWsUqV/LOsguKlWHp2kr6+5C15zn1r10av6ogRan7JcE2/7DH17JkWX2OVMASKBgEIIOr5L79469ATT0g//RTj1bF8ACGAxx3nbbBIdoFboRHAomm+aG8xBTA57AufAB54oMRqVLNmrpqlOmoqOajsbkMgTRDAjLXbbjkIIKfsfPzMJH19aTt5zn2xCODw4Wp+6UhNv6yJEcA0aU6rRhEh8N13EgFUyRDAGTOk44/PJoBYlQlsTEUxBdAUwGT7XZETwFRGTSULlt1vCKQFAhDAXXeVmjfPrg4EsM/TkzXw8nbymN26ddGrOny4Xrp0lGZe3lg9eqTF11glDIGiQQACSA7N2bO99C2PPSZNmRLj1bF8ACGAJ5zg+di2bSvxSLIupaIYATQCmGy/K3wCeMAB0jvvSGefnatuqY6aShYsu98QSAsEiGSsWFF6+eXs6jDkej81Wd9c8bY8ZheLAA4bppcu/1GzLm+s7t3T4musEoZA0SDw/fcSp+gkQgBjmYCnT5dOPNEIYNG0WJ5vMRNwnhDFvcAIYHL42d2GQNEjEI8A1m4vvfuul6g2ahk2TC9ePka/XN7ICGDRt5y9MZUIQADr1pXmzPFy0TZuLP38c4wKxSOAJ53k5dnkxNOhQ/20m6kopgCaAphsvyt8Arj//lK3btJZZ+WqW6qjppIFy+43BNICAZLZ7rST9Mor2dXp2lX68ImfNOiq9v74i0UAf/hBL1wxTnOuaOjxRCuGQMYgAFu7887ECGAsE/C0adLJJxsBTJNOYwpgcg1RpAQw1VFTyUFldxsCaYJAFAII5/vg8Z806OoOvgvG+vXRKzt0qF6oPV5zazf0eKIVQyBjEIAA3nGHNHeuvv5aatRImjo1xtfHIoDccMop3lnbbdpIw4ZJn3ySGgRNATQFMNmeV/gEcL/95NmWzjwzV90ggKmMmkoWLLvfEEgLBDjPFBNVixbZ1YHMvf/YTxp8XSc/Cj8OAWxWe4Lm1X7ECGBaNKZVosgQ+OEH6fbbC40Atm4tDR9uBLDI2i/Ki0wBTA79wieA++7rRyGecUaumhE1RSqmVIXNJweV3W0IpAkCDz4olS+fgwBizn2vyU8aXKezn4dzw4bolf3+ezW9apLm135YmI2tGAIZgwAE8LbbpHnzvCPcHnlEwqIbtcTyAcRp8LTTpBUrBAEcMcI/eTEVxRRAUwCT7XdFTgBTGTafLFh2vyGQFghAAHfYQXr11ezqQAB7NvlJQ67v4h/FuHFjHAI4WfNrP2QEMC0a0ypRZAhgr7311mwC+PDDEkG9BSWAr78ujRrln7yYimIE0Ahgsv2u8AngPvv4iWhPPz1X3VIdNZUsWHa/IZAWCDRoIJUrl4MA4nXRvfEUfXtDF4mM67EI4Hff6fmrp2jhlQ08V0ErhkDGIAABvOUW6ddf9c030kMPxSGAsXwASRyIdWv5chkBTH3PMRNwcm1gBDA5/OxuQ6DoEYAAli0rtWyZ/W6PAD46Rd/e9I68Q0o3bYper2+/1XPXTNWiqx4UyaOtGAIZg0AEAWQYkdc5aolHAPFvX7ZMrVpJo0dLH32UGgRNASx+CuCzkm6VtLsknHTGS3pc0uRQFzpK0puSjpe0XFJnSU0juhh/v0sSBI5n1JcUjmdK5Bk8svAJYI0a0ocf+n4SESXVUVOpGab2VkOgkBFAuihTJgcBJPdzt0ZT9N3NXeUdUmoEsJBBt8cVewSI2LihE3lBAAAgAElEQVTpJmn+fA0aJOFJkW8CyOHBpDgzApgW3aG4KYAHSfpT0gpJpSQ1kNREUlVJWyXtKGmWJNyzm0k6WNJXkl6T9EaAeGNJD0i6SNIcSc8FpJJrOQE+kWe4xitSApjqqKm06LFWCUMgWQQggKVLS68xLfiFuKuuDafou1u6yctQu3lz9LcMGaJnr5uuxVc94AULWzEEMgaBCAJIMP3MmTG+PpYCCAHklKt//vGG39ixUu/eqUHQFMDipwCGe0pZSfUktZJURdJSSbdJIrfDXpK2BBdDEh+UBHmkzJX0uqS3gr+XlLRY0iOS3k/wGduOAFav7o+IU0/NNSpSHTWVmmFqbzUEChkBvNdLlpRngwoRwHce+Vnf39ZNXoKyuARwhpZcXV+dOhVyvexxhkA6I0DI7g03SAsWaPBgiXSa+SaAkydLNWt6BBAPjHHjjACmssmLmwIIVhcHRK1iQPJaS0LVo0DsDgvUPYfrKZKGS+L6EoFZmH8bHQJ+oCSOtX40gWesDt2XuALI2aPLsUjnUfbe2w+LIllmREm102xeVbffDYFigUAUAvjee1KXh3/W93d094nhFrd/jPiiwYP1TJ1Z+uPq+40AFovGtkoWGgIRBJATFWdhb4tWYimAEMBzzpGWLvUI4PjxUq9ehVbDfD3IFMDirQDuEqh1v0lyucRxy64g6YZQTzg08O+rHhDABQFJDIvXdMGVku6RlNczfjcCmK9xZhcbAumFAAnMsrLkhSEGBQLY+eGfNfTOHr5v4FY8SqKUQYP09PWz9dc19bx0gVYMgYxBYORIqU4daeFC70CCevUKQAAnTZLOPdcjgGRhmjjRd3lPRTECWLwJIH0GBXOZJLImo+AVfwWwWjU/Nfr//pdrTKQ6aioVg9TeaQgUOgJRCCCZlzo2mKof7urhp4cxAljosNsDizkCIQLIgQT33iv98kuMb4qlAML4zj9f+vtvI4Bp0B2Kowk4DBuBIASE3CLp0yCYg+yu+fUBRNXDB/CDBJ/h6uCZgOvXr68yRBVKqlWrlvcnR0FtSNQEbAQwDYaFVWG7RqBhQ5/g4VQblGwCeHdP/4SQWATwm2/01I1ztfSa+9Shw3aNkn2cIZATAbI2X3ut9Ntv3olUyRJAhhkW4Q9YdYuoDBw4UPyhbNiwQe3ateM/cQ/DAphxpbgRQAI6MNcSCVxZ0kuSrglMun8EEbyYdokC5rcDJQ0IlEEXBYyfH1HAlwQBIU8HpO+QUBRwXs/IQQBXrFihnXeGC8Yo+SGAe+0lffaZdPLJuR6W6qipjBsd9sHbJwJRCCCLUPsHp2rYPe9Jr7wSlwA+eeOvWnbtPd6BIVYMgYxBIEQAOZHq7rul2bNjfH0sBXDCBFQS6a+/vGFGUHBREsBwbc0EXPxMwF9IOiEgejD2sUG6lwmhhj1S0ttBHkDUQabpFyK66fOS7pW0k6RxUfIAJvIMHln4QSBxCGCqo6YyZqKzD92+EWjUyI/yJdo3KPghvf3AVA27933p5Zf9IBA2bpFl4EA9edN8I4Dbdw+xr4uGwI8/SldfLS1apMIigBwMgvqeimIEsPgRwFT0k3jvLHwCWLWq9Pnn0kkn5XpvqqOm0g18q48hUCAEHn3UT/QcQQDb1Z+q4fU+kJo3j00Av/5aT9y8UCuuu9s7Mc6KIZAxCIQI4PffS3XrSnPIpButxFIACfu96CLpzz+9fdbUqRIBWKkoRgCNACbb7wqfAO65p/TFF9KJJ+aqW6qjppIFy+43BNICAQggZ/2S8DkopKJ46/6pGl6/l/Tii75CWIKsURElIIAr69wt333IiiGQIQhwbtuVV0q//66kCODFF0t//GEEMA26TXHzAUwDyHJUwQhgurWI1ccQyAuBxo3xAM9FAN+8f5pGPNBLeuEFXyEkWXRk+eorPX7rIq267i4jgHnhbL9vXwiECODQodIdd0hzOVYhWomlAJL5+ZJLPAKI0D59un8KTyqKKYCmACbb7wqfAO6xhzRggHQCro45SyqippIFyO43BNIOAQjg+vVS27bZVePwnTfum66RDXpJzZrFJYCP3bpYa+rcqbfcWUJp94FWIUNgGyAwZoxUu7anACZFAC+9VFqyxAjgNmii/D7SFMD8Ipbz+iIlgKmOmkoOKrvbEEgTBJo0kdatk958M4IATtPIhz6Smjb1TcSlyDIVUb78Uo/dtsQIYJo0pVWjCBGAAF5xhbR4sX74QbrtNmnevBjvj6UAcvjvZZd5BPCll/yj5Hr0KMJvCL3KFEBTAJPteYVPAKtUkb76Sjr++Fx1gwCmMmoqWbDsfkMgLRCIQgA/+khqfe90jXr4I+n552MTwAED1OT2P7Xu+jvC/DEtPssqYQhsUwQgb5dfnk0Ab71V+vXXAhDA4Bm42nKUnBHAbdpqcR9uCmBy2BcpAUx11FRyUNndhkCaIPDYY9KaNQrbcDl++/W7p2tUwz7Sc8/5PoKlS+eu8IABanz7X1p/w+1hC3KafJhVwxDYhgiE1Lthw6RbbikAAQypiBBAThLp3n0b1jnOo00BNAUw2Z5X+ASwcmWJTOXHHZerbkYAk22u/2fvPKCkKLo2/JCTgIJZMaKIAcw5J8wRc04YMAHm8Bkxi/qZFcPvZw6Yw4o5gQEVFAUUEypiJogCwv7nne7V2dmZndnt2Z4e9q1z9sDudFVXP1U9/fatuve6vgkAOQTglUd8yvABD8N//pNbAD71FCcf8rMFoCdS4yMgB45w/54E4P77w9df19ECmOZIIl8rhZG5887SoLQAtACMOvOKLwDnnx+GDoXVVqvRt1J7TUWF5fomkAgCp50GU6eS7sb78MNwxeGfMvzkIXDWWYGTSJjesVqfn3qKkw79hVn7HJQeRSYRl+VOmECDEkjz4H3jDdhvPwvABuUdQ+NeAo4G2QIwGj/XNoH4CeQQgJcfNoa3Tx0CZ54Jf/0FrVrV7NuTT3LSYb9aAMY/aj5jqQkoiHMYw08CcN994Ztv6mgBTAsmLWd7OZHccUdpLswWQFsAo8684gvAzp3hxRdh1VVr9K3UXlNRYbm+CSSCwOmnw+TJpKfyeOQRuOzQMbx92qNwxhm5BeATTzDg8MnM3veA9EQiibgsd8IEGpRAWhaPN9+EffaxAGxQ3jE0bgtgNMixCsBSb5qNhsq1TSAhBCTwfv+9hgC89NAxvHP6YyCBqDAxrVvX7PATT9D/8ClU7rc/V12VkOtxN0wgDgLvvw/bbJNK4yYBuPfeMGFCHS2Aw4bBHnvAt9+moi1pD+Htt8fR+ZrnsAXQFsCoM6/4ArBTJ1KZtnv2rNE3C8Cow+X6JkBg4fvtN7jxxn9wDBkCFx8ylnfPeAy0RJxLAD7+OP2PmGoB6InU+AhIAPbqBT/9xFtvwV57RROAirakJWQLwNJNJVsAo7GPVQCW2msqGirXNoGEENAev19/rSYAH30ULjp4LO+e+XjgJTx9OrRpU7PDjz9Ovz7TaLLffgwalJDrcTdMIA4CH3wAW2/9jwDcc8+UIS97yRUIOk05SgDKgnjbbXF03hbAbJQtAKPNveILwPnmI5Vnp0ePGj2zAIw2WK5tAikCEoC//AI33fQPEAnAgQeN5b2znwAFis4lAB97jBP7TKfZAfty5ZXmaQKNiIAE4FZbwc8/k7aSW3cBqLXjb75Jhdv87jsYPLg0DL0E7CXgqDOvYQSg8uysskqNvpXaayoqLNc3gUQQUJiXn36Cm2/+pzuPPQYXHjiW9855Ck46KQgU3bZtze4++ignHvUnzfa3AEzEWLoT8RH48EPYcst/BGDv3oGAy1pyWQDTvEcsAOMbulxnsgUw2hgUXwDOOy8oyqYFYLSRcW0TyEUghwC84MBxjDj3KRgwAKZNg3btsgrAE476ixYH7MMVVxixCTQiAhKAW2yRsp6nRXOpuwBU/Jivv07FW584EW69tTQMbQG0BTDqzCu+AOzYkZSL1cor1+hbqb2mosJyfRNIBIGzz4ZJk+CWW/7pzuOPw/kHjGPEeU9D//65BeCQIZxw9ExaHLC3BWAiBtOdiI3AyJGw+eYpAZiW0KNuAjAtgrQFYGwjl/NEtgBGG4NYBWCpN81GQ+XaJpAQAjkE4Hn7f8b7FzwN/foFmUK0jJVZhgzh+KNn0erAvbj88oRcj7thAnEQkADcbLOUA1W9BWBaEuEst2EcV/HPOWwBtAUw6oQrvgDs0IHUDtuVVqrRNwvAqMPl+iZAkOs3Y+3piSfgnP0+44MLn4ETT8wtAB95hOOOmU2bg/bksstM0wQaEYFRo2DTTVMC8J13YOedg9soa8m1BzBNAGbZiRErTAtAC8CoEy5WAVjqTbNRYbm+CSSCQBYB+OST8J99P+ODgc/CCSfAlCnQvn3N7j78MMf1nWMBmIiBdCdiJSABuMkmqRiaEoA77QQ//FBHASgHx4MOSuWAswCMdfSynsxLwNHGoPgCUA8d2ddXXLFGzywAow2Wa5tAikCWG0kC8Ox9PufDi5+F44+vVQAe27eSdgfvwaWXmqcJNCICH30EG2+cEoDvvgs77hhNAGaJxhQrTFsAbQGMOuEaRgDq9ap79xp9K/Wm2aiwXN8EEkEgiwB86ik4a+/P+fDSCjj22CBXsLZjZJaHHqLvsU1of0hvLrkkEVfjTphAPAQkADfaKJVGUQJwhx0CX6qsJdcSsGLcHnIIfPFFtnCc8VxHeBYLQAvAqBOu+AJQN47uriwCsNSbZqPCcn0TSASBLJtpJQDP3PtzRl72PPTtG+QKlke+BWAihsydSACBjz+GDTdM3RvvvQfbbx9NAGbJyBjrRVoAWgBGnXDFF4CKPTZiBKywQo2+WQBGHS7XNwFIZaFXEtK0HFRPPw1n7PU5Iy8fCscck1sAPvggxxzfjI6H7M7FF5umCTQiAhKAG2yQso5LAG63Hfz4Yx0tgK+8AocdBuPHZ0vJHStMC0ALwKgTLlYBWOpNs1Fhub4JJIJAloCaEoCn7zmeUVcOhaOPTu1zQkHZM8sDD3DMCS3oeMhuFoCJGEx3IjYCaQJQNoptt62nADz8cPj8c04/PdhpccMNsV1BtRNZAJaXANT79vbAksA04FXgFCA9HfVXwELALIJrqwT2Bp5JG/m+wEnAAsAYoB/wetrnXQBNyU2Av4AHwmP+zjJNiy8AlX5KORe7datxOgvA0nxR+KxzGQHlVPzqK7j99n8u7Jln4NQ9vuCjQUPhqKNqFYBHn9CC+Q7djYsumsu4+HJMoDYCo0fDeuulHKQkALfZJsiomLXk2gP48stwxBEpAXjaaUG0peuvLw12C8DyEoADgYeBjwAl6bwRkKvsamnT50vgfOCOHFNqD0Dh/3cEhgN9APnyab1VWQ0lGkcCI4BjgU7AU8BLoQjMbLa6AJw58980UulH3nlnsJ9I+4rylVoEYKm9pvJ13Z+bQFkQyJJU+9ln4ZTe4/no6pegT59UrDPmm6/m5dx/P0ed2JrOh+3CQH0juZhAYyGQJgDffx969aqnANT99dlnFoAJmDflHAamJ/B+KNImhywlAC8A/n21rw5ZQu4DYEDan9XGI4C+zmX1ex5YGPgtPGYn4J7wPLIsppfqAlBxkvSGdOqpHP74Dnz844LBsT/+BK1awor/BndeZhm4994sM6BNG1DE9eWXr/GhBWAC7hh3ofwJXHBBag8SejELiwTgyb2/4ONrXgosFBaA5T/OvoLiEvjkE1hnnZTZTgJw663h559znCKXBfCll+DII1MC8NRT4Y8/4LrritvNQluzBbC8LICZ46rl36OAZdI+kABsAzQHvgf+B1wFVC3f/gocHS7rVlW7GegM9AaODz9Pj8GySGgd7AF8nFUAdulCh6ZNqZz+J393WZofnxjOkkvCXXdBy5bA0KGkImdKwRFET9fknz49hwCUkFxuuRofltprqtAby8eZQKIJZBGAzz0HJ+3+BR//92XQHqVffoFOWgDIKPfdx5H92rLA4Ttz4YWJvkp3zgSKSyBNAGqX0lZb1SIAFc922jSo1C6stPLii8Ee23HjLACLOzr1aq1cLYBbAo8Cu0lepV35RqFV8E9g3dBydz9weniMhKD2EVak1VE0r9WBrYGzws/XS/u8NSCptiHwVlYB+OyzdGjXjr6DluWGxxbl2mvh7rthuBaZVZR0/tFHQWYGAgfEpZaC2bOhScYI3NviIE7qdBs0a56KRhFqxlS9Um+ardcMcyUTSBoBKbfPPoP/+79/eiYBOGC3L3n2vHdY6JQDaTViWPYl4CeeoM/FS7PQETshHeliAo2GwKefwlprpYSdBOCWWwbvSVlLLgtgmgA85RT4809Sz8tSFFsAy9MCuENo2TsIeCLPxNExWtpdPDyuQSyADz00mYUX7sAeewSR0WW8U7zMf6JM3HorPPII6CmjFeEfYaGFYMaM0EKoP8ocOHIkJ2z4Hj9vfzBdVmyP4m7KO7GqWACW4mvC55zrCGQRgBUVwaZ2lRPa3MzVM/vyRuUGTKF6MOhmzOb+JU5h8f03tQCc6yaGL6hWAmkC8MMPYYst6iEAX3ghiLM5diwWgKWfb+VmAdwP0I4BOXO8UAC+AwF5Dy8WHqs9gNrzJy/gqiKHjyGhUNw43AOoZd/MPYBaJp6Zcc7UHsBOnfry669a64XjjuvFqFG9GDAgSJWTKhkCUGlGq3xC/ok1qx3lF19Mz1nvsv/pS9C1Zzv69wfF/lNReEDtu5BVvVReUwXw9iEmkHwCuteGDIF99vmnrxVjl2KbwdoFEiS5v/zyIBtjZjx2OQ/Laq90wfIlcTGBRkNgzBhYY43Uxj0JwM03D7bKZi25LIBpAvDkkwMjyH//Gx/BiooK9KMyc+ZMrg8epor4PiW+XiTnTOUkAOWVq0UXWQDfzIKwa+i88W4o1NYJl4Al7k4Oj9c3vLyA5djxNnB46AWsPX9VXsByEpFI1H5AbQJ6HHglnxfwsst2SG2IzdzykDrv4MGkNgz1Dh4ws2Y3peXVl/HDUeeyUDtFtJHsfJ7vtzmUxS4/kbfegsUXD/bK/h3uXnzzzWD/rR5IFoDJuYHckzIkoBss46nz/A896PXqGbRuNYcOHZvStWuwReOfbRzhZUo3PvhgsI1pE7mMuZhAYyGQJgDlp7jZZvUQgNoPf9xxMGYMJ50Es2bBNdeUBqCXgMtrCXhOGN9vRjhdquL8bRsKwrVkawOWDuP/SdDdBVwBzE6bYseE8QMVB/BT4ETgjbTPFQdQIWaq4gDKV1cWw0wPYFX5xwt4zJgOqeXfnSQtM4s8DrXRIVSH+qfptdewUqeJLNkheIU6c62hfNpzb257euGUAMwsMlY8/HAQoqxUeyZKc5v6rCbQ8AS01UK5TW+6Cb7+OmWMT4W5CHdtNHwHfAYTSDqBsWNhtdVS25UkADfdNAiXmbXksgBaACZqlMvJApgocGFnCgsEnaXnWkZaaaXgZUi+IXKaUu751q3hyitrVvjii8CZWG9dWSLEJJGN+2QCZUNAlr3dd4c5es0EmjaFAw+s5idSNtfijppAgxBIE4AKVCELeJ0F4PPPM7zP7Xzyn/t54IFgRevqqxukt3kbtQWwvCyAeQe0BAdEEoASftp4/vbbsK58lglCkx0k1xUXEzCB2AhI+GlvblX2N2U40L5bxWV3MQETIBW6hZ49U667EoAbb1xLboNcFsDnn6fnTkvQbMUV6Nw5WNHSi1cpigWgBWDUeVdvAaj9Rc2a/Xt6JQnR3xR6LDM0TNROur4JmIAJmIAJRCKQJgAVoWLDDYNcvlmLlrOU52277ap//NNPLPD+czw7vBNrrhmpN5ErWwBaAEadRPUWgFFP7PomYAImYAImEBsBxc5ceeVUHu2PxzRng507M3nspOyn33XXf/dRpB1x6F2bcsewFVLJEBZWvq0SFgtAC8Co088CMCpB1zcBEzABE0g+gUmTSKW4mjGDj1mJVfiYB1MR2aAHo+jGuOrX8NhjQUylsCiEmdJra+uTgkiXulgAWgBGnYMWgFEJur4JmIAJmEB5ENBm2cpKRo+GlXs2Y4UVKlNblrRf9t3hoQdV1ZWk73ECXn45cKyaMCEZl2oBaAEYdSZaAEYl6PomYAImYAJlRUBhYFZdFeQsJQGo5dwePWrfv65jFctWcTSTUCwALQCjzkMLwKgEXd8ETMAETKCsCCiWrRxBJPpUFLtWK8T5ihw/uijSbgKKBaAFYNRpaAEYlaDrm4AJmIAJmEDMBCwALQCjTjkLwKgEXd8ETMAETMAEYiZgAWgBGHXKWQBGJej6JmACJmACJhAzAQtAC8CoU84CMCpB1zcBEzABEzCBmAlYAFoARp1yFoBRCbq+CZiACZiACcRMwALQAjDqlLMAjErQ9U3ABEzABEwgZgIWgBaAUaecBWBUgq5vAiZgAiZgAjETsAC0AIw65SwAoxJ0fRMwARMwAROImYAFoAVg1ClnARiVoOubgAmYgAmYQMwELAAtAKNOOQvAqARd3wRMwARMwARiJmABaAEYdcpZAEYl6PomYAImYAImEDMBC0ALwKhTzgIwKkHXNwETMAETMIGYCVgAWgBGnXIWgFEJur4JmIAJmIAJxEzAAtACMOqUswCMStD1TcAETMAETCBmAhaAFoBRp5wFYFSCrm8CJmACJmACMROwALQAjDrlLACjEnR9EzABEzABE4iZgAWgBWDUKWcBGJWg65uACZiACZhAzAQsAC0Ao045C8CoBF3fBEzABEzABGImYAFYXgLwYmB7YElgGvAqcArwbdq86QLcAGwC/AU8APQD/k47pi9wErAAMCb8/PU6tlF1uAVgzDetT2cCJmACJmACUQlYAJaXABwIPAx8BLQFbgRWBFYLJ0ITYCQwAjgW6AQ8BbwUijwdtgdwC7AjMBzoA1wKrAB8R8AjXxvp884CMOpd6PomYAImYAImEDMBC8DyEoCZ06Mn8H4o9CaHVr/ngYWB38KDdwLuCY+ZFYrBD4ABaY2pjUcACUxZDvO1YQEY842apNNVVFTQq1evJHXJfWlAAh7vBoSbwKY93gkclAbqkgVgeQtALf8eBSwTzo/jgaOB7mnzZZHQstcD+Bj4NTxGS8NV5WagM9AbKKQNC8AGuiHLodn+/fszaNCgcuiq+1gEAh7vIkAsoyY83mU0WBG7agFYvgJwS+BRYDdgaDgPzgr3CK6XNi9aA9OBDYG3wr2A2kdYkXbMJcDqwNZAIW1YAEa88cq5uh8Q5Tx6de+7x7vuzMq5hse7nEevbn23ACxPAbgD8D/gIOCJtCGvzXq3CjC6oSyAEyZMoEMHbQd0mdsJnHHGGVx00UVz+2X6+kICHu/GNRU83o1nvCUAu3SR3ygdgSmN58r/vVI5PZRT2Q+4LnTmeCGj4xuH+/e07Ju5B1BLvDPDPYDa8ycv4Koip5Eh4R7AQtpIP+1iGV7I5cTSfTUBEzABEzCBxk5g8XCrWKPjUE4CUJ69FwCyAL6ZZaR0LXLwkMCTNVBewI8Dr6R5AWufn7yA5RzyNnB46AWsfYNVXsD52kg/tc65KDC10c0cX7AJmIAJmIAJlDeB9sD3QGV5X0b9el9OAnAOIE/eGeGlqu8atG3TBKHsuQoPUxUH8N7Q2qd6VeWYMH6g4gB+CpwIvJH2eSFt1I+2a5mACZiACZiACZhAAgiUkwBMAC53wQRMwARMwARMwATKn4AFYPmPoa/ABEzABEzABEzABOpEwAKwTrhqHHxeuI9QLsByJlGaOXkbu5QPgXOAs8NwQVXbCp4E5HCkohiS1wJrAL8DtwIa9/TieZDc8d4rvC8VOH4eoAWg7SRVpRjjW0gbySU0d/Us33hr7JUmVOlBq+53hQ5L/97Odz97vJMzZ5KYIjY5dPL0xAKw/kN1cphyTnsQxwMSEgcCy4diov4tu2acBDRuWwDyAM8sEgzjgNuB88OxfRa4ArgmPNjzIM7Rqvu5tgodwpQ+cnCGACzG+BbSRt177Rr1JVDbeKtNCUDd7y/nOEG++9njXd+RaZh6SUwR2zBX2gCtWgDWH+oXgFJCKCyNSjNgYuhxrPRzLuVBoDYBqFiTyhUtT+8qq5E8zI8Dlgsvz/OgPMZZjmHKC55uASzG+BbSRnkQmrt6mW28qwSgEgloLmQr+e5nj3ey50kSUsQmm1Ba7ywA6zdUWvLVcqCWDhROpqoow8hHGXEG63cG14qLgASg4kIqY4x+lDHmTOCrUOArRJCsvFVFYy6vcQUPbep5ENcwRT5PNkGgF7io45uvjWmRe+4G6kOgNgH4Q/gi8DVwU2gZ1jkK+V73eNdnNOKrk4QUsfFdbcQzWQDWD6ACR34TPjzGpjVxfxhRvE/9mnWtEhBYMYzjOAFQEPHLgXUAvUn+F2gH7JPWrxXC/UIKFyQB6HlQgkGrxymzCQItCUcd33xtKMaYS/wEcgnAzcKXvNmAlou1WnM6oJzwhXyve7zjH8tCz5iUFLGF9rfkx1kA1m8ICnlTrF/LrlVqAi2BycCOwHZFsBCV+np8/oCALYCNaybkEoCZFLQCICGofPGFfK/bApjMeZSkFLHJJJSlVxaA9R+qbHtF9LbfP3yrrH/LrllKAhKAWt7fObQIXlaPPYCeB6UcweznziYI5LRV3/HtByjQfCFtJI/G3N+jQgXgf4BewAYhklzf6x7v5M6ZpKWITS6pjJ5ZANZ/qLRvTOnptgf0pXFW+DDoZi/g+kMtQc09wg3hvwALhUvAsgasEoaJ0BK/vIDlbdYVeDrcG1jlBex5UIJBq8MptUwvxw8JAnlwK/WTlv+UG1zLv1HHV16h+dqoQ3d9aEQCtY33quE9rX3aVd7A9wESgdeH5813P3u8Iw5QkasnMUVskS+x4ZqzAIzG9lzgyPCh8p7jAEaDWaLayhe9bigGfgNeC+MCStSrrAzcEMYB1NKwUg0qJ3V68Two0eAVcFp5bd6RlsnD+xIAACAASURBVOuzKvab9oJprIsxvoW0UUBXfUgRCNQ23lrilcVX+3eVHlROILq3FduzLvezx7sIA1WkJpwiNgJIC8AI8FzVBEzABEzABEzABMqRgAVgOY6a+2wCJmACJmACJmACEQhYAEaA56omYAImYAImYAImUI4ELADLcdTcZxMwARMwARMwAROIQMACMAI8VzUBEzABEzABEzCBciRgAViOo+Y+m4AJmIAJmIAJmEAEAhaAEeC5qgmYgAmYgAmYgAmUIwELwHIcNffZBEzABEzABEzABCIQsACMAM9VTcAETMAETMAETKAcCVgAluOouc8mYAImYAImYAImEIGABWAEeK5qAiZgAiZgAiZgAuVIwAKwHEfNfTYBEzABEzABEzCBCAQsACPAc1UTMAETMAETMAETKEcCFoDlOGruswmYgAmYgAmYgAlEIGABGAGeq5qACZiACZiACZhAORKIUwB+DCyRBqkZ0AbYFXgc6AFcC6wB/A7cCpyXAVW/Hw50AEYAfYHRacfE1UY5jrX7bAImYAImYAImYAIpAnEKwEzkxwFnA4sDLYFxwO3A+cDywLPAFcA1YcWTgWOBbYHxwDnAgeGx04F5YmrDU8cETMAETMAETMAEyppAKQWgLHey/J0BHARcCiwKzAmJHg9IJC4X/v4FMAi4LvxdFsSJQD/gnhjbKOsBd+dNwARMwARMwARMoFQCcHOgAlgW+CYUdt1D617VqKwHvAF0BJqGy8L629tpw6Y2PgJOiqmNaZ4yJmACJmACJmACJlDuBEolAB8CWgM7hgAHA+2AfdKArhDu7+sSCkAJRYnEsWnH3A9MAfoAcbTxfcaAi5+sllPLfSK4/yZgAiZgAibQyAi0B/Rcr2xk15263FIIwEWAr4GdgOdC6FraLUcL4GLAt41x4viaTcAETMAETGAuICA/hO/mguuo8yWUQgCeCxwQLv9WdVjOHJfVYw+glLv2AN4bOoTE0UY6ZHkjT54wYQIdOui/LnM7gTPOOIOLLrpobr9MX19IwOPduKaCx7vxjPeUKVPo0kULjKltZlpJbHQlbgEoxw1Z/64OPXyrgMuDV0u78gIeCHQFng739VV5AWufn7yAtwfkEHJWKPq6AVVewHG0UUMATp482QKwkdw6/fv3Z9AgGaxdGgMBj3djGOV/r9Hj3XjGWwKwY0dpPwvAuEZ9N+DuMPTLrxknXRm4IYwDOBm4Ebgg4xhZD48EtG7/XpY4gHG1UdWtlAXQAjCu6VP68/gBUfoxiLMHHu84aZf+XB7v0o9BXD2wACzNHsC4xjeO81gAxkE5QeeoqKigV69eCeqRu9KQBDzeDUk3eW17vJM3Jg3VIwtAC8Coc8sCMCpB1zcBEzABEzCBmAlYAFoARp1yFoBRCbq+CZiACZiACcRMwALQAjDqlLMAjErQ9U3ABEzABEwgZgIWgBaAUaecBWBUgq5vAiZgAiZgAjETsAC0AIw65SwAoxJ0fRMwARMwAROImYAFoAVg1ClnARiVoOubgAmYgAmYQMwELAAtAKNOOQvAqARd3wRMwARMwARiJmABaAEYdcpZAEYl6PomYAImYAImEDMBC0ALwKhTzgIwKkHXNwETMAETMIGYCVgAWgBGnXIWgFEJur4JmIAJmIAJxEzAAtACMOqUswCMStD1TcAETMAEyoPAqFHw55//9rV9e1h00eD3eeaB5s3L4zoAC0ALwKiT1QIwKkHXNwETMAETSD6Br7+GpZaCRRb5t68//wyzZgW/SwxusAFsvDFssgmstx40aZLY67IAtACMOjktAKMSdH0TMAETMIHkE/jsM+jRo7oFcOZM0E9lJYwcCa+8Aq+/Ds8/D/fdB3vvndjrsgC0AIw6OS0AoxJ0fRMwARMwgeQTGDcOevasLgBz9XrrrWGvveCwwxJ7XRaAFoBRJ6cFYFSCrm8CJmACJpB8AnURgL16wR57wOGHJ/a6LADjF4DrARcCawGzgdHAhuEM6QFcC6wB/A7cCpyXMXv0u2aUhNcIoG/YRtVhcbVRdT4LwMTe3u6YCZiACZhA0QhIAK66Kkyfnr/JbbaB3r0tAPOTKukRce7QlPh7BjgOeAjQzlGJvXflPwSMA24HzgeWB54FrgCuCQmdDBwLbAuMB84BDgyP1YyMq430AbMALOn09clNwARMwARiITB2LKy2mgVgLLDjOUmcAvA14G1AQi6zHARcCsiffE744fGhWFwu/P0LYBBwXfh7M2Ai0A+4B4irDQvAeOamz2ICJmACJpAUAhKAq68Of/yRv0eyAO6+OxxxRP5jS3SEl4DjWwJuA0wFrgQ2BZYFvgQuBoaEwq57aN2rmg6yGL4BdASahsvC+ptEZFWpAD4CToqpjWkZc9UWwBLdvD6tCZiACZhAjATGjIE11ihMAG67Ley2mwVgjMNTn1PFZQFcDJgATAK2Bz4EdgbuBzYJ9/W1A/ZJu4gVwv19XUIB+A0gkTg27RjVnwL0AQYDDd3G9xaA9ZlmrmMCJmACJlDWBOoqAHfdFfro0ZzMYgtgfBZAWcrk2HEJcEbadHgO+ABoFYo77e+rKmVjAezbty8tW7ZM9btXr16pHxcTMAETMAETmGsISACuuSZMy1wIy3KF220Hu+ySOAFYUVGBflRmzpzJ9ddfr/9qlVGGpEZX4rIACuxnofNHNgH4KXBZPfYAyiKnPYD3hg4hcbSRPkm8BNzobhlfsAmYgAk0QgKffgprrVXWAjB91GwBjM8CKO5y6jgt3Oc3CtgxXALeGBgTLu3KC3gg0BV4OtzXV+UFrH1+8gLWErIcQs4KRV83oMoLWMvDDd2GBWAj/O7zJZuACZhAoyYgAbj22jBV2/nzFFkAd94Zjjwy35El+9wCMF4BqIE+NYzdJ5OrLILnAk+FM2Bl4IYwNMxk4EbggozZoeM1o9oD72WJAxhXG1XdsgWwZLevT2wCJmACJhAbgU8+gXXWKUwAbr897LSTBWBsg1O/E8W5BFy/Hia7lgVgssfHvTMBEzABEygGgboKwB13hKOOKsaZG6QNWwDjtwA2yECWsFELwBLC96lNoF4ERoyAW28FOW7NOy8ssAC0agWtW4M8F9trgcHFBEygGgEJwHXXhSkF+EvssAPoxwIw0ZPIFsBow2MBGI2fa5tA/AQGDoT77wcFq/35Z/jtN5gxA956CwYPDnKYupiACVQnMHo0rLeeBeBcNC8sAKMNpgVgNH6ubQLxE5AAVF7T//u/6ufeYAM4/njYa6/4++QzmkDSCUgArr8+TNYW/TxF1j/tAzz66HxHluxzLwF7CTjq5LMAjErQ9U0gbgIXXgiffZZdAB53HOy9d9w98vlMIPkEPv4Y9JJUiADU/j95AlsAJnpcbQGMNjwWgNH4ubYJxE9AAvDzz+HOO2taAC0A4x8Pn7E8CNRVACod3DHHJPbabAG0BTDq5LQAjErQ9U0gbgIXXADjx9cUgBtuCH37wj7pGSnj7pzPZwIJJSABqHvkdyX1ylMUAkZ7bC0A85Eq6ee2AEbDbwEYjZ9rm0D8BCwA42fuM5Y/gY8+go02sgAs/5H85wosAKMNpgVgNH6ubQLxEzj/fPjyS7jjjurn1sNNFgtbAOMfE58x+QQkADfeOPCaz1dkAezVK7CoJ7R4CdhLwFGnpgVgVIKubwJxE6hNAGrT+r77xt0jn88Ekk9g1CjYZJPCBKDSwG29tQVgwkfVFsBoA2QBGI2fa5tA/ATOOw++/hpuV9rwtCLrhgLXWgDGPyY+Y/IJ1FUAbrUVHHtsYq/LFkBbAKNOTgvAqARd3wTiJlCbAFTy+v32i7tHPp8JJJ+ABOCmm8Kvv+bv6y67wJZbWgDmJ1XSI2wBjIbfAjAaP9c2gfgJSAB+8w3cdlv1c2t5q08fC8D4R8RnLAcCI0fCZptZAJbDWBXYRwvAAkHlOMwCMBo/1zaB+Amcey5MmJBdAB5xBOy/f/x98hlNIOkEJAA33xx++SV/T2UB3GILUFzNhBYvAXsJOOrUtACMStD1TSBuAhKA334b5P1NL7IAWgDGPRo+X7kQ+PDDQNQVIgB33TUQixaAiR5dWwCjDY8FYDR+rm0C8RM45xz47ruaAlD7mw47DA44IP4++YwmkHQCdRWAWi5Wbu2EFlsA47UAngOcDUwnOG8l8CRQteO6B3AtsAagUOO3AudlzB39fjgg4TUCUJCh0WnHxNVG1SktABN6c7tbJpCTgAWgJ4cJ1J2ABKAcO37+OX/d3XYLHEYsAPOzKuERcVoAJQC3ADbOcr3zAOMAxWU4H1geeBa4ArgmPP5kQD7l2wLjAbV3YHisRGVcbaR33wKwhJPXpzaBehH4z39g4kS4Ve+YaUUWi0MPtQWwXlBdaa4n8MEHoNAuhQpAbak44YTEYrEFMH4LYC4BeBBwKbAoMCecMbIdawfpcuHvXwCDgOvC35sBE4F+wD1AXG1YACb2lnbHTKAAArUJwEMOgQP1XuliAiZQjYAEoII7//RTfjCyAFoA5udU4iPitgCeFC4By2L3FnAm8FUo7LqH1r0qJOsBbwAdgabhsrD+9nYaswrgI0DtShw2dBvTMsbLFsAST2Cf3gTqTEAC8Icf4JZbqlfVpvWDD7YArDNQV2gUBN5/P0jvVogA3H33IG2cLYCJnhpxCsAVganABGAR4HJgHaAn8F+gHbBPGq0Vwv19XUIB+E0o8MamHXM/MAXoA8ilr6Hb+N4CMNHz2Z0zgfwEzj4bJk3KLgAPOgj042ICJlCdQF0FoHJrn3hiYil6CTjeJeDMidASmAzsCGwXg/WuGFbErBbAvn370rKlLkcvSL1SPy4mYAIJJSAB+OOPcPPN1TuoEBda/rUATOjAuVslJSABuM02wb2Tr/TuDRtumDgBWFFRgX5UZs6cyfXXX6//apVRhqRGV+K0AGYTgPL23Tm0CF5Wjz2AsshpD+C9oUNIHG2kX4eXgBvdLeMLLnsCZ50VLGNlE4AKAaNlYBcTMIHqBEaMgG23LVwAbrAB9NPjOZnFFsB4LYB7AC8BCiO+ULgEvCGwShgWRku78gIeCHQFng739VV5AWufn7yAtwfkEHJWKPq6hfsK5QUcRxsWgMm8n90rEyiMgASgPBlvuqn68bIAWgAWxtBHNT4CEoDbbRdsn8hXZAG0AMxHqeSfx2kBfBxYN9yn9xvwWhgXUGJOZWXghjAOoJaGbwQuyCB0LnAk0B54L0scwLjaqOpWYRZAZR245x6Yf35Yailo3Rq0ZNy5M3TpAi1alHwiuAMm0GgInHlmkM0gUwAqxtl++4E8gV1MwASqE3jvPdh++8IE4B57wPrr2wKY8DkUpwBMOIp6da8wAaiUU7I6rLRSkIR+xgxtQAgeQn//DfPNB02bwl13BW9YLiZgAg1HwAKw4di65bmXQF0F4HrrQf/+ieXhJeB4l4ATOxEidKwwAaiAs488As89V/1Us2YF4Sh+/RWOPTawPhx1VITuuKoJmEBeAmecAb/9BjdqkSGtKMjtvvvaApgXoA9olAQkAHfYIXhm5St77gnrrmsBmI9TiT+3BTDaAEQTgOnn1o0l8/rRR0frkWubgAnUTqA2AbjPPkE2EBcTMIHqBN59F3bcsXABuM46MGBAYinaAmgLYNTJWZgAVMDZRx+FZ5XdLkfRjSUPq2OOidon1zcBE6iNgATg77/DDdpynFaU5WDvvS0APXtMIBsBCcCddgrSKOYrsgBaAOajVPLPbQGMNgTFE4C6sRQ/sG/faD1ybRMwgdoJnH46TJ6cXQDutRccdpgJmoAJZBJ45x3YeefCBKDuo7XXtgUw4bPIAjDaABUmABVv7PHH4Zlncp9NN5b2IGkvoIsJmEDDEZAAnDIFgiCw/xZZAC0AG467Wy5vAhKAu+wC32cmxMpyWbqP1loLTlL0tmQWLwF7CTjqzCyeANSNpVykxx8ftU+ubwImUBuB006DqVNrCkBZ4BW+4vDDzc8ETCCbBbBQAaitFGuuaQGY8FlkC2C0ASpMACre2JNPwtOKbZ2j7LorbLppopNnR0Pl2iaQEAISgNOmwXXXVe+QBWBCBsjdSCSBt98GPacKsQBKAK6xBpx8ciIvRZ2yBdAWwKiTs3gCcLfdYOONE5c7MSog1zeBxBE49VT444+aAlB5TpXBwBbAxA2ZO5QAAhKAek59913+zlgA5meUgCNsAYw2CIUJQMUbk/Xvqadyn2333YPk2QnOnRgNlWubQEII1CYAdR8ecURCOupumECCCAwfDro/ChGACqe0+uq2ACZo+LJ1xQIw2gAVTwBq71HCI6dHQ+XaJpAQAqecAn/+CddeW71DCsMkC4cFYEIGyt1IFAEJQFnIldo0X5EAXG010L2W0OIlYC8BR52ahQlAxRtTDEDtA8xVyiBuUlRYrm8CiSBQmwDUHqc+fRLRTXfCBBJFoC4CUBl1Vl3VAjBRA1izM7YARhug4gnAMnCbj4bKtU0gIQQkAP/6C/773+odUh5ueTlaACZkoNyNRBEYNizwki/EAigB2LMnaLtFQostgLYARp2ahQlAxRurqIAnnsh9vjLYNBsVluubQCIIyDNxxozsAlDxOI88MhHddCdMIFEEJAC1UjVhQv5uWQDmZ5SAI2wBjDYIhQvA558PgkHnKmWwZyIaKtc2gYQQkACcOROuuaamBdACMCGD5G4kjsBbbwWB0gsRgPvtBz162AKYuEGs3iELwGgDVJgAVLyxoUNrF4B6Y9INoxhlLiZgAg1HQNkJZs2qKQC33z5Idn/UUQ13brdsAuVKQAJQK1XffJP/CiQAV1kl0c8zLwGXbgn4UWBnYEvgpXA2bQpcCawA/ABcDtyUNtNaAlcBewL6/6vAMUC6S1IcbaRP/sIEoLwNX3wRHnss942jG2bllUFpqlxMwAQajoAE4N9/w9VXVz+HBWDDMXfL5U/gzTdBK1WFCMD99w+eZwk2aFgAlkYAHgjsF4q/rUIBuCQwGlDiwMHA+oA2zB0EVK2bKnHnBsAOwO+Afl8FWD28s5YAPomhjYYRgLphVlwRzjij/L8ofAUmkGQCAwbA7Nk1BeAOO4B+bAFM8ui5b6UiUFcBuNJKiTZoWADGLwAXB94ANgRkR66yAP4ntAiukTa3B4UCTyKxFfArsBdQFU25MzAR2Ax4E4ijjcxbrzALoLwNX34ZHpXhM0c54ABYYQU488xS3d4+rwk0DgK1CUBZAY8+unFw8FWaQF0ISABqq9LXX+evJYOGBWB+TiU+Iu49gBXAg8BtwJw0ATgEmASkf/PuAyhS6/xAT+B9YNHwuCpsY8NjlNQzjjYaTgAedBAstxycdVaJp4RPbwJzOYH+/aGyEq7SjpK0ov1/CgVjATiXTwBfXr0IvPEGaKtSIQJQBg2taCV4S5MtgPFaALVfT/v+eoWTTwJwC+Bl4AXgXSB9A9w24TKw9vvJYqg9f22BGWmTd3h4zEUxtVE/AShvw1dfhSHSqDnKwQfDssvC2WfX6950JRMwgQIJ1CYAlQ3kGH1VuZiACVQjIAEoy95XX+UHIwHYvXuitzRZAMYnAJcJl37XAaqCCNXFAtgD+CCiBbAYbWQVgH379qVlS+lU6NWrV+qnWilEAB5yCCy9NPxHK9kuJmACDUZAAlBlkHaZpJWddoJttrEAbDDwbrisCbz+OkjYFSIADzww2NKUsD3tFRUV6Edl5syZXK8YvdARmFLWY1PPzse1BCxnjptDyFXn1B6+ycADwHfALkBd9gBqaVj1tAfwrXAP4E7Ammks8u0jrGsbWQXg5MmT6dBB2wFzFHkb6uZ55JHcxxx6KCy5JJxzTj2H0tVMwAQKItCvHzRpkl0A6uWtb9+CmvFBJtCoCNRVAHbrlug97bYAxmcBbA10yrhZFL5FTh1DAaknefAOAG4H1g2Xdg9O8wLWPj95B2sZWV7A+n3lNNFY5QXc0G2kX0ZhTiCFCMDDDoPFF4fzzmtU3ym+WBOInYAEYNOmcKWiTqUVWQAtAGMfDp+wTAhIAMqy9+WX+Tus4ywA83Mq8RFxWQCzXeZsoCoMjD7fGFBgrm6ho8elodWwqq7WWPWNLeeQqjiAitgqK2BViaONugtAbTaXB9XDD+ce7sMPh0UXhfPPL/GU8OlNYC4ncOKJ0KxZTQGoLCBbb20L4Fw+/L68ehJ47TWQs2IhArAMnBptAYzPAljPGZf4aoVZAAsRgEccAQsvDBdckPiLdgdNoKwJSAA2bw5XXFH9MiQAt9oKjj22rC/PnTeBBiEgAShnxS++yN+8BWB+Rgk4opQWwARcfuQuFCYAtdlcibQfeij3Cfv0gQUXhAsvjNwpN2ACJlALgRNOgBYtagrAXXaBLbe0APTkMYFsBBTJQs6KhQhACcWuXRMd1swWQFsAo97oxROAyj7QuTMMHBi1T65vAiZQG4HaBOAWW8Bxx5mfCZhAJoG6CsCEhzWzALQAjHqTFyYAtdn87bfhQcXAzlEUfHa++eAihTR0MQETaDACxx8PrVrB5Uo3nlZ23RU239wCsMHAu+GyJiABqGgV48fnv4wyiGtrAWgBmH8i135EYQJQe43eead2Aajgsx07wsUXR+2T65uACdRGoDYBuNlmoM9dTMAEqhN45RVQtIpCBGAZxLW1ALQAjHqLFy4A330XHlDIwxxFscfat4dLLonaJ9c3ARPIJwBbt4bLLqt+1G67waabWgB69phANgISgIpW8fnn+flYAOZnlIAj7AQSbRAKE4BaahoxAu6/P/fZ5HnYtm3Nh1K0/rm2CZhAJgHt8WvTJrsA3GQT0B5BFxMwgeoEXn4ZFK2iEAGopeKllkp0ZitbAG0BjHqLF08A6qEkq0TmvqSoPXR9EzCB6gR0r+ll61KFGk0rsgBaAHq2mEB2AnUVgAnPbGUBaAEY9VYvTABqqemDD+C++3KfT/uOlE84MzZZ1B66vgmYQHUCsra3a1dTAO6+O2y8sS2Ani8mkI2ABKDClX32WX4+ZZDa1ALQAjD/RK79iOIJQC07KThtZnqqqD10fRMwgZoCcJ55au63lQDcaCNQoGgXEzCB6gReegmOPLIwAShnkS5d4NxzE0vRAtACMOrkLEwAaqlp5Ei4997c58uVoD5qD13fBEygOoFcDle9e8OGG1oAer6YQDYCEoCKVztuXH4+FoD5GSXgCDuBRBuE4gnA/v2hshKUNs7FBEyg4QjUJgA32AD0MuZiAiZQncCLL4Li1RYiAOUtvPjitgAmfA5ZAEYboMIEoEK7fPQR3HNP7rMNGACzZ8PVV0frkWubgAnUTiBXzM099oD117cA9PwxgWwE6ioAF1sMzjsvsSy9BOwl4KiTs3gC8KSTYNYsuOaaqH1yfRMwgdoI1CYA11sPZI13MQETqGkB1L0zdmx+MrIAWgDm51TiI2wBjDYAhQlAZfcYPRruvjv32U4+Gf76C669NlqPXNsETCC/BXDeeWumXZQF0ALQs8cEshN44QXQ9olCBKDiBS6yCJx/fmJp2gJoC2DUyVk8AXjKKTB9Olx3XdQ+ub4JmEBtBHLl3d5zT1h3XVsAPXtMIBsBCUCFUBozJj8fC8D8jBJwRJwWwP8ABwLzAzOBEcBpwMg0Dj0AmcDWAH4HbgUyNxHo98MBiS+10RcYXYI2dMrCBOBFF8Gnn8L//pd7yE89FaZNg+uvT8C0cBdMYC4mIAHYqRMMHFj9IiUA11kHtB/XxQRMoDqBoUNBQdQLEYCKF7jwwrYAJnwOxSkAlwN+BCYDzQFlXD8FWASoBOYB5F9+OyC78fLAs8AVQNXGuJOBY4FtgfHAOaGo1LHTY2yjaliLJwBPOw2mTIEbbkj4lHH3TKDMCSiURefONQXgXnvB2mtbAJb58Lr7DUSgrgJwoYXgggsaqDPRm/UScOmWgFsBRwNXAgsCvwAHAcrNtCgwJxxeicTjAIlHlS+AQUDVOmkzYCKguA1ysY2rjboJQFkatG/irrtyz9rTT4fff4cbb4w+s92CCZhAbgISgPPPDxdeWP0YCcC11gI5ZLmYgAnUtAAqY5VWs/IVWQAtAPNRKvnncVoAdbHbhUKtYyjyFPROVj0VCbvuoXWvCsx6wBuAjm8aLgvrb2+nkasAPgL0rR1HG9PSzl2YBVAPGsVOqk0Annkm/PIL3HRTySeFO2ACczUBZTNYYIGaAnDvvWHNNS0A5+rB98XVm8DzzwdpEgsRgLnusXqfvPgVbQEsnQVw3tBa9y3wSDi0g4F2wD5pQ71CuL+vSygAvwlFYrof+v3AFKAPEEcb39dLACp/4v/9X+5ZfNZZ8NNPcPPNxZ/pbtEETOBfArUJwDXWAHnku5iACVQnIAGoNImffJKfjAVgfkYJOCJuC2D6JevcvwEbhRa8OKx3xbAi1rAA9u3bl5YtW6aurVevXqmfakX7ID7/vHYBePbZMGkS3HJLAqaFu2ACczEBPZwWXLDm/qR99oEePWDIkMAhq3VrWHRRWG214O+rrAJdu0KLFnMxHF+aCeQgUFERBEkvRADm2mZRYrgVFRXoR2XmzJlcHzhdaoVRRqRGV0opAOUIIoeQA4AhoTPHZfXYAyiLnPYAKtGuvIzjaKNqohS2BCwBOH483Hln7gn2n//AxIlwqxyfXUzABBqMQK79SRKA3boF2QseeigQet98Ax98EGTy+fjjIFbnrrsGItHFBBoTgboKwGyOVgni5SXgeJeA5dCh5Vp5Ai8AKAZD73BJd1LowaulXXkB67OuwNPhvr4qL2Dt85MX8PahQ8hZoejrluYFHEcbdROACob55Zdwxx25p/8558C338JttyXoFnFXTGAuJJArRIUE4HLLBZZB7cdVqJj08vff8N//woMPwvDhcyEYX5IJ1EJAAlBZcpTUIF/J5Wmfr16Mn1sAxisAnwTWDIWezK3vhuFe3k8b85UBxUFRHEBZB+USm+lHfi5wJNAeeC9LVeYEqwAAIABJREFUHMC42lC3C7MAFiIAzz03sDbcLv3rYgIm0GAEcgWp3XffYIlXAvDXX2G++Wp24f77g2w9b77ZYN1zwyaQSALPPReESCpEAOYKtp6gC7MAjFcAJmjoi9aVwgSglpS+/rp2cadjvvqqdith0brthkygEROQANTevsxE9RKAyy4beAf/9hsoXVxmeeCBIF/3W281YoC+9EZJQAJQIZK0FSJfsQDMRygRn5dyD2AiAETsRPEEoKyEX3xR+z7BiJ11dRMwAeURypGofr/9YKmlghzBisnZUXvDM4qWf6++2gLQE6nxEXj22cBDvhABeMwxwQuU7qWEFlsAbQGMOjULE4Ba3p0wofb9fbI65AsVE7W3rm8CJhAIwMUXB92X6UUCcMkl4eKLYfJk6KDbO4sAvOoqGDbMJE2gcRGoiwA88EC4994g9u2GG0KrVtCkCTRtCu3bB7+XuFgAWgBGnYLFE4CFZAuJ2lvXNwETgMMOgy5dagrA/fcPhOGllwZpGfWgyizyDr7ySjuBeB41PgISgKecEnjE5yurrgojRwZe9cqClV6UbzsBTlQWgBaA+aZxvs8LE4Dy8P3uOxisONU5ikzlirD+v//lO6c/NwETiEKgNgG42GJw2WW5BeDDD8Pll8Pb6cmIonTGdU2gTAg88wycemphArBnTxg1CiorYdas4F/9KJi0RGQh2UQaGIsFoAVg1ClWPAGoZSd5V919d9Q+ub4JmEBtBCQAl1gC9GKWXg44ABZeGK64AqZOhXnmqdnKI48EFsJ33jFjE2hcBCQATzstEHb5SroATD9WAlD5hMeMyddCg39uAWgBGHWSFSYACwnyfMkl8PrrcN11sPTSUfvl+iZgArkIHHposNcvmwBUAnst8SoTSDtlpswoCgCtl7V3FcXKxQQaEYGnn4bTTy9MACpzjpaKZfVLL0OHwrHH1lwWLgFGC0ALwKjTrngCUBtmlaJKDx45jGgvkosJmEDxCUgAyttXL2bpRRZApYgbNAj++APatq157kcfBe3XfU8hSF1MoBERkAA844xgb1++orSJ8hbOFIAvvADyEB43Ll8LDf65BaAFYNRJVpgArEueX+Uf1ZuTMhK4mIAJFJ/AIYcEVvZMASjPxfnnB3n5Tp8ObdrUPPdjjwWBokeMKH6/3KIJJJlAMQTgiy+CsoQo4kWJiwWgBWDUKViYADzrLPjxR7jllvzn00NHb1jLL5//WB9hAiZQdwISgMssA3oxSy8SgMpfqjh/f/4JehnLLI8/HgSQfj89gVHdu+AaJlB2BJ56Cs48szAL4MorB3vaMy2AL70ESsX4+eclv3wLQAvAqJMwEIAnnEAHbR5XUawjlWbNQGZwbYbVvr6ffoKbb85/Pi07Kfm83OddTMAEik/g4IODjB+ZAvCgg4Lgtcr3+9df2WOVPfFEED7GArD44+IWk01AAlDGjA8/zN/PXALw5ZeDOJzjx+dvo4GPsAC0AIw6xQIBeMghdJgxI2iryt195szgTenLL2HOHNh8c5D5O1/RxnMtL62wQr4j/bkJmEB9CEgAKuevHmbpRQJQ2T+U61f3c8uWNVt/8slg6VgvaS4m0JgIaO7rpakQAbjSSvDJJzUtgK+8AtqDq6xXJS4WgBaAUadg/iVg5RTt1An0RlRIAE2FnpCHYffuUfvm+iZgAtkISOhpj22mAJQw1P13/fW1C8BCH4KmbwJzE4G6vPysuGIQ6y9zCfjVV0H3mQwjJS4WgBaAUadgfgGoM2hZuFABqOwDCjKrG8jFBEyg+ARqE4CywN9wA8iC36JFzXPXZR9U8XvuFk2gdASKIQBfew201/arr0p3HeGZLQAtAKNOwuILQOUfVZ5RmdBdTMAEik9AAlBOVtrQnl5kmZAT1k03BdkLmjevee66xEIrfs/dogmUjoD2vyp2ZiHbH7SCpWDPmRZAxbpVysWvvy7ddVgA/sM+9Fgo+ViUawcKF4ASdIqLlK9oD9KbbwYWQxcTMIHiE5AFQk5WmQJQ3sFKUi9nrb//Dhy5Mktd0mEVv+du0QRKR6AuDlC5BOAbb8C++8I335TuOiwAYxeAFwPbA0sC04BXgVOAb9NmQRfgBmAT4C/gAaAf8HfaMX2Bk4AFAOWS0eevl6CNqlMWXwDKC1FvSfIgdjEBEyg+AQlAOVkpqG16kQCU44fCNc2eDU2b1jz3s8/CyScX9jJX/J67RRMoHYG6hEDS/TV2bE0LoIwbe+8dJDsocfEScHxLwAOBh4GPAIXXvxHQJrfVwjkgS6TCiyu66rFAJ+Ap4KVQ5OmwPQAF0tsRGA70AS4F5C77nXbaxdRG+rQtXABqT5/iIuUr880H2iirVDouJmACxSegjB+yUGQKQHknatn31lsDz/2qkE7pPXjuORgwoLB7ufg9d4smUDoCEoDnn19YEHRZ2JXtI3MJ+K23YM894dt0209pLskCMD4BmDnCPQFFUpXQmxxa/Z4HFEzvt/DgnYB7wmNmhWJQsRcGpDWmNh4BJDBlOYyjjfoJQD1w5Bafr8hjWLGSFD/QxQRMoPgEJAD1Qqa8pulFAlDLvoMH13xwVR1XUQH9+hV2Lxe/527RBEpHoBgCUPvbe/eG72SzKW2xACydANTy71HAMuEUOB44GkiPfbJIaNmTKUyb534Nj9HScFVRZOXOQG8grjbqJwBlEpdbfL6iTASKF7jqqvmO9OcmYAL1IaBN6NqTmykADzssaO3223MLwOefhxNPtACsD3fXKW8CdUmDmMsCOHw47LYbfP99yVlYAJZGAG4JPArsBgwNZ4EismqP4Hpps0J5mKYDGwJvhXsBdUxF2jGXAKsDWwNxtdGwAlC5SIcOhdWqVsdLfp+4AyYwdxGQAJST1WmnVb8uCUAtWd1xR24BqHvz+OMLe5mbu6j5aho7AQnACy+E997LTyKXAFSIs112gYkT87fRwEdYAMYvAHcA/gccBDyRNr61We/kDaHNc1EsgMVoo8oSWUMA9u3bl5Zh1oBevXqhn2pFe4l0Q8gtPl9ZYAHQMtPq0rUuJmACRSew336Bk1WmAFSKKnn/3nVXsAcwW5EAPO64wu7lonfcDZpACQk8+igMHFiYAFSYpc8+q/ki9c47sNNO8MMPJbmQiooK9KMyc+ZMrlfQd+gITClJh0p80jjDwOwHXBc6c7yQcd0bh/v3tOybuQdQS7wzwz2A2vMnL+CqIqeRIeEewLjaqCEAJ0+eTAfF78tV6iIAF1wQ5Gm4xholnho+vQnMpQRqE4CK/3f33YEXcLbywgvQt2/g4ehiAo2JgATgRRcFmaryFWXa+fzzmgJQdXfYASZNytdCg39uC2B8FkB59l4AyAL4ZpaRlRCVg4cEnqyBcg55HHglzQtY+/zkBSznkLeBw0MvYO0brPICjqON+glAvREV8tBYaCFQsNk112zwG8AnMIFGSUACUF72p55a/fJlAVQO4PvuCyyB2Yr25x59dODh6GICjYlAMQSglo+3394CMCHzJi4LoNZT5Mk7I7xunbcS2DZNECoOoMLDVMUBvDe09qleVTkmjB+oOIDyqDgReCPt87jaqDpl4WFgChWACy8MCri59toJmSLuhgnMZQQUiFZe9pkC8Igj4M8/4YEHgkwg2cpLL8GRRwbLWy4m0JgIDBkCF19cmAWwa1cYP76mBXDECNh2W/jxx5KTswUwPgtgyQe7gTpQuACUSbwQq8Eii4A2266zTgN12c2aQCMnIAEoL/tTFIwgrUgATp8ODz0U5ALOVhSiScdpecvFBBoTAQnASy4B7ePLV3IJwPffB+2R/+mnfC00+OcWgBaAUSdZ8QXgoouCbrR1143aN9c3ARPIRmCffQIv+0wB2KcPTJsGjzwSLAVnK6+8AvIWlnXDxQQaEwHdF5deWpgAXHZZ+OKLmhZA5RHeaiv4+eeSk7MAtACMOgkLF4B6Iypk2WixxeDhh2G99Ig4Ubvp+iZgAv8QkACUl71SuqUXCcCpU0F7nf5SNsosRVl6lDJODzcXE2hMBCQAL7sMFMolX1lmGfjyy5oC8MMPYYst4Jdf8rXQ4J9bAFoARp1khQtAvREVsmy0+OLw4IOw/vpR++b6JmAC2QgoF6m87DMFoPb2/f47KONBLgH42mtw8MEWgJ5ZjY9AMQTgyJGw2Wbwq6K6lbZYAFoARp2BhQtAvREVsmzUpQvcfz9ssEHUvrm+CZhALgEoL/uT0iNKETh3/PYbPPlk4AySrbz+Ohx4YGDdcDGBxkRAK1OXX16YBXDppeGrr2paAEeNgk02Ce6zEhcLQAvAqFOw+AJwiSXg3nthQyVAcTEBEyg6gb32grXWqikAjzoq2Jv0zDOBM0i28sYboEwieri5mEBjIiABeMUVoHRu+UouAfjRR7DRRoGlvcTFAtACMOoULL4AXHLJIBCtbhIXEzCB4hOoTQDKO/G55+CPP3ILQMUR/Prr4vfLLZpAkgnIO/7KKwsTgEstFdwjSq2YXj7+OFjdmjy55FdqAWgBGHUSFi4A9UZUyMZx3ThKRbWxEpu4mIAJFJ2ABKDibA4YUL1pWQAVn+z55wNv4GzlzTdBTiTffFP0brlBE0g0AQnAQYNg2LD83ZQhQ/dIpgAcPTpwcJxS+sxrFoAWgPkncu1HFF8ASijeeWewT8LFBEyg+AT23DOIs5kpAJXhQzlKle5N3sDZyltvgQTkhAnF75dbNIEkEyiGAPzkk+Dey3V/xXj9FoAWgFGnW+ECUJa9QjaOy1nk9tth002j9s31TcAEshGQAFSczf79q38qAThxIijbRy4Lhawfe+wB335rtibQuAgoOsVVVxVmAdRedr0kZVoAP/002H+by8IeI1ELQAvAqNOt+AJQ4WIGDw5c5V1MwASKT0ACTstQmQLwmGMCYadYf7n2KGkD/O67w3dKP+5iAo2IgATg1VeDrOD5Si4BOGZMEIIp1x7bfO0W8XMLQAvAqNOpcAGoPRGFeA4qYPQtt8Dmm0ftm+ubgAlkIyABqDib/fpV/1QCUFYLxfrLJQAVBHfXXeH7783WBBoXAeXIvuaawgSgwpnpZSrTAjh2bJCFJ5eXfYxELQAtAKNOt8IFoN6ICvEcVM7gm24KoqW7mIAJFJ9A796BJ2KmAOzbN3hJk6NHrjAVyoO6yy4WgMUfFbeYdAISgP/9b3B/5Cu5BOC4cdCzZ+44m/naLeLnFoAWgFGnU+ECUDdEIZ6Dyy8PN9wAW24ZtW+ubwImkI2ABKDibJ54YvVPJQC1T1f7/HIFqn33Xdhpp2CvoIsJNCYCxRCASoe6yiq5M+3EyNMC0AIw6nQrvgDs1g2uuy5ImO1iAiZQfALaw6c4m9kEoLL1yMqXK1XVe+/BDjsE3sIuJtCYCChD1bXXFmYBVEpT7ZPNXAJWOtSVVoIZM0pOzgLQAjDqJCxcAOqGKCR0xAorBGb2rbeO2jfXNwETyEYglwA89liQhUIiL1eyen22/fYwaZLZmkDjIiABKOOEsuHkK7kEoF6wuneHmTPztdDgn1sAxisA9wL6Aj2BeYAWwJy0Ue4BXAusAShPzK3AeRmzQL8fDkh4jQjbG12CNqpOWXwBqJtDnla9ejX4DeATmECjJCABqEDrJ5xQ/fIlALVH6f33g5Rw2cqIEbDttkHAaBcTaEwE7rsPrr++MAG42GLBPtlMC6CSIWiVa9askpOzAIxXAGpNsxPQFhicIQAlCMcBtwPnA8sDzwJXANeEM+Vk4FhgW2A8cA5wYHisEnfG1Ub6xC1cAOqGKCR22IorBtHWt9mm5DeIO2ACcyWB3XYLAq1nCsDjjgOFqfjwQ1BKuGxF4lAvZ7k+nyuB+aJMAJAA1P7011/Pj2PRRYN9stkEoPa5//13/jYa+AgLwHgFYNVwKsXFSxkC8CDgUmDRNKvg8cBxwHJhxS+AQcB14e/NAO3EViyHe4C42mhYAaj9EUq4LSuDiwmYQPEJSAAq0Prx+opJKxKAClQ7alRuC98HHwT7c3NZCIvfW7doAskgUAwBKCcrhTqbPbvk12QBmBwBKGHXPbTuVU2M9QBtNugINA2XhfW3t9NmTgXwEXBSKA4buo3MBKGFWwD1RlRI8NiVV4bLLoPttiv5DeIOmMBcSUBx/BRoPVMA6nclq9dPriVeWQcVoinXHsG5EpgvygSAe++FG28szAK4yCKBo1SmBVBhlpTtak767q/S0LUATI4A1JJwO2CftKmwAqD9fV1CAajs6xJ4Y9OOuR9QVuk+4bJyQ7eRGf21+AKwRw+4+OJgo7mLCZhA8QlIACrQuix+6UUC8KOPQPlKczl5jBwZiMdcXsLF761bNIFkEJAAVIxaBUrPV3IJQMXCVVrUTGGYr70G+NwCMDkCsKwtgH379qVly5apKdqrV6/UT7XSpAnohigke4CCZA4cGISacDEBEyg+AQVylhUvUwBqT6AsfMpWkCvMi5aHtXxsAVj8cXGLySZwzz1w882FCcCFFw5eojKFnmLhKitWiQRgRUUF+lGZOXMm18upJVhllCGp0ZUmJbjibHsA5cxxWT32AMoipz2A94YOIXG0kY6scAugbohCgseuuipccAHsuGMJhsanNIFGQEACUIHW5fWbXiQAtcdPoWBy3auyEMqDOFeg6EaAz5fYSAlIACpNqXJl5ysLLRRso8gUegqFpqxYWgKWYaSExRbAeC2A2sen0C8SgPLwbQ9oJ6gCAmnpVku78gIeCHQFng739VV5AWufn76xtTYqh5CzQtHXDajyAo6jjYYVgMqTeN55QbYBFxMwgeIT2HnnwJEjmwCUl69ileWy1mt/oLKI5EoVV/zeukUTSAaBu++GW2+NJgAVCUNZseQE0lSSoHTFAjBeASgv3TuAynDIJf/1/80AbSpYGbghjAM4GbgRuCBjepwLHBmKx/eyxAGMq42qbhVuAdQbUSHZA1ZfHc45B/SQcjEBEyg+gVwCUJlBlOpNG9VzOWyNHg3rrw+T9RXlYgKNiEBdBOCCCwahkjItgLqvFCRaYWCaKZBH6YoFYLwCsHQj3XBnLr4AXGMNOPvsIOG8iwmYQPEJSAAq045y/6YXCUClgdM+pVwxOyUA11sPpjTKLUPFHwu3WD4EJAAHD4ZXXsnf51wCUJZ1xcRVIOjmzfO304BHWABaAEadXoULQN0QhaSPWnNNOPNMkKeiiwmYQPEJaHuFHLUyBWC/fjB8eCD+cqVtlIfwOuvA1KnF75dbNIEkE/jf/+C22woTgAssEMTKzLQAam+tQqIpFVwL7QgrXbEAtACMOvuKLwDXWgtOPx0UrNbFBEyg+AQkAJVp55hjqrctAThsWLD/T1bAbEWBonWPTssMCVr8brpFE0gUAQnA22+Hl1/O36355w9iZWYKQG2DUkSMGTMgjJyRv7GGOcIC0AIw6swqXADqjaiQ/KFrrw2nngrKV+piAiZQfALysFemnUwB2L9/kOdUD6lcAlCp4rRN448/it8vt2gCSSZw111wxx3RBOCkSfy6cHcmffhDSgAqJGCbNqW5aAtAC8CoM6/4AlDLSyefDL17R+2b65uACWQjIAGoTDtHH139UwlA5TnVi5oC1mYrihEoRy0LQM+txkagGALwxx/ZZKFPebvVxsye3QTdcpcqCWwJigWgBWDUaVe4AJRJvJAE8uuuCwMGwB57RO2b65uACWQjoCDryrSTIQAnHXUOA4d0Z7emj7HpD0oylKWMGweK1TldkadcTKAREZAAvPNOeOml/Bedawn4p59YY8FvOPv+lRn+QavUTorrrsvfXEMcYQFoARh1XhVdAP6x9maM2umsVKaC5ZeHzp2jdtH1TcAEqhGQANTPUUdV+/Mzu97K9o8dwVHt7+bGKftnh6Yg0UrX+OefhmoCjYvA//0f6KcQAagHl7LlZO4B/Plnei7wHQMf7saw91untgkqu1wpigWgBWDUeVe4ANQNIa+oPOWyJa/n3B+OpEXr5uy5ZxB308UETKCIBHIIwCd2uZ2dHz+UI9rfxy1T0tOSp537889h5ZXhr7+K2CE3ZQJlQEDiT1bAF1/M39lOnYJsOZkC8JdfWGn+H7hiyLIM/7B1KtymIsuUolgAWgBGnXeFC0DdEHrdyVPO6XI733bdlK5bL4OSDij7josJmEARCWj5V/sAMyyAj+z0f/R+8iAOnudh7piaYw+usoSsuGLgxehiAo2JgJZ/5QkcRQD++isrdP6Rax9fkuEj26SS7qjZUhQLQAvAqPOucAE433wFJZA/o8td/NptPbpus1wqJu2DD0btouubgAlUIyABqFAwRyqp0L/lgR3+x95PH8D+8zzG/6bmCMSuJ1b37kEcMxcTaEwEpNQUDPqFF/JftZ53SpeYaQH87Te6dvqFW59alOGj2qK46mqyFMUC0AIw6rwrugA8efH7+Gul1em6XbdUwPVHH43aRdc3AROoRkAewMoGkiEA79n+XvZ/Zl/2mucp7p+6Q3ZoX3wB3boFmQxcTKAxESiGAPz9d5aa73f+9+wCDP+oHUq9fd99pYFoAWgBGHXmFS4A55032BORp/Rb7EGa9FiFrjt259ln4ckn89Xw5yZgAnUiIAGoVIt9+lSrdue2D3DIc3uxe7vneHjaNtmb/PJLWG65IJepiwk0JgKKAag9SYVYAPW8U77sTAvg5MksPu9UHnp+XoZ/PA9vvQUPPVQaiBaAFoBRZ17RBeCxiw2h3Wrd6LrzSjzyCDz3XNQuur4JmEA1AgoCrVSLGQJw8DYPc0RFb3Zu9wKPTdsyO7SvvoJll4XZsw3VBBoXAQnAe++FoUPzX3fHjkG+7EwBOGUKC3eczpMvzcOwj+ZJJRUp1SqXBaAFYP6JXPsRhQtA3RDaE5GnHLnoEyyw1tJ03XWVgvfb5mvTn5uACaQRkABUqsUjjqiG5cathnDMC7uxXbtXeHraptmRKUD0MstYAHpCNT4CSgOn9dooAnDqVObvMIOhr7Zi2MftS7rKZQFoARj1Ji66ADx0kWdZct1F6Np7VW6+GV57LWoXXd8ETKAaAeUBVqrFDAF47ZaPcfyLu7B12zeo+GPD7NCUIk75q+bMMVQTaFwEJADvvx+efz7/dXfoAFOn1rQATpvGfO1n8dobTRk2umPK+qetTqUoFoAWgFHnXeECUDeE9kTkKQcsPJTuG3am656rc9VVQW56FxMwgSISkABUqsXDD6/W6FWbP0n/l3dks7bDeemPdbOfcMIEWGKJmg+2InbPTZlAIgkUQwD+8Qft55nDO2/NZtin8xZsUGwIHhaAFoC1zavzAD0hJPJGAH2B0RkVii4A917oZdbYZB667rMWAwfCe+81xNR3mybQiAnkEICXbfoMp766HRu1eY/Xpq+ZHdC330KXLhaAjXj6NNpLv+02eOCBwiyA7duTyvOWuQdw+nTatGvCqLf/YtiY+dC2Qu0DLEWxALQAzDXvTgaOBbYFxgPnAAcCywPpSUALF4C6IbQpNk/ZfcHX2WiLFnTdb13OPBNGjsxXw5/HSaCiooJevXrFeUqfq9gENH7KtZ1hAbxok+c477XNWKPNJ7w1fbXUWWuMt1IXLL54sATcpEmxe+b2SkzA93ctAyABqMC0FRX5R2meeeCPP2oKwD//pEXb5ox9dyrDx3Xixhvh9dfzN9cQR1gAWgDmmldfAIOAqjTVzYCJQD8gPTdH4QJQN4T2ROQpOy0wjF5b/E3XQzaiXz/45BOCDecKP9GsWfUfudq3bv1vi0o1pyT1euuq+tGDqkWLwGqR7YH1/fekwrFnKwp1oTbVd1lNZP149dXq7Ve94aWfU23pIasHpTYMa+P8IouAAvDKrVnLaOn1dHxmO+l/0/kPPDDov44bMiQQ07rW2opSdq27bhCA+/HHAw4tW8Kii8KkSdC06b880/+vNquytmywAXz6aeDA06MH/S+5hEFyIlBRfyTsNQZKDabsEIoR16ZNTdOt2lf+WDH56SfYfHOYOBE+/BAWWig4n3irzaoftaOgwyusELwJqB9V56267qox1b8LLBC0+8wzQaiSceOCeHWtWgV9WnppGDUq6K9+FlwQFlsM3nwTmjf/d55oiVPzQuOW3h/9X3NQ16i5oDd8zUH9XlUUIFnRXTPf/LONU9X1/fhjcD71oaof2menc6lo7isHr34XRx3TtSssvHBwPeqH/qbPV1opuLYqVvq/0jCqntpo2xa23hrOOQcOO6xar87faCiD3liL5Vp+w7szeqQ+69+/P4MG6asgLOqnmF10Ufb7Kds9ttFGsP76wXy95RZSOR41B6uKWF17bTAHct0XmfdI+u+6t44/PmhNT1SNja5b4615qS8RfQ/oe0T/6hz6ctEc0f9PPz14CuteqZobGtd27YJ5rHl91llwxRVBe5qTYpmZDSV9Lp5wAvTsGfRJ2SOUP7ZqjDROmqvqn87z1FNB39K/33TPb7wxyHlO6cfU76rx11hqDM44I2hfY3399bnnnJKqqz8qauuNN7LNxmC8hw1j0Hrr/fu5/n/IIcG1nnpqMNeqGIpdtv+n/03fOZqrY8cG92L692Tm/6vGNPPv2neqMdbf1Qf1aZ994PLLg3EvNC1hIfek+iDOWu4Vt/Sy1lqgrUyFZALJIQArZ8ykaeuWfL3oegybtSZXTzmUYZueDoqvqf5lPuOqxvyHHwLWGvtVVw0csTSHxEVmRH2XVj0f0u8r/V9/VwzDDcN9vSNGpOKATpk1i4767oGOQH7rTM5ZU74f+BW25thJ1MldV98Cb6d9rNeej4CT0v6WEoDLLjuZZs303xxl3Fho0TL4wguLnklKRqD5nF5uHziR/lPOoes8k9jrzzs4vdujNPtxIs1/nkizJpU0r5xJZ35hIoswcdE1aXnUoan7YeKY35l06iCaVM6hKZU0aVLJQvzI4k2+Y+SclWly7LEssdGSSM/ou1Pf30o19/0Z19Ly2y9ZTIqxAAARWklEQVTp0GYmPVt8ynItvqJZkzkpgTXt1xm806U33b97gZ+fHMakG4fQ4t23aL7w/LRoOjv107Xt98yiBaOmLZP6vXPLqcz+agJ/brEDK9xwPPMs1pHKlVZm9NvT6DDmHRZbeT6abRA+aKpuTkC9/vyPRZjTpFnwDGzSRFdBpf597Y1UQMTKLktQOfEHKiUuuy5H5aKL0bLZbFZsP4HKOZV8Oq0LzZvMpnXTmbSZ8wetR71Dk8m/pwTA5DYL8+NCq7Bss69S/dA+rvFNutJizgxa8xff/LUAzefMovmcmSzy0yh+XmJ12k6dRJdubZn1/Eu8u/IhtBj3CdfP+pQTu2/DH8070qrpLNr88TPLNR1Py9ZN+WzygkxovRxN5u9M0y/H07xzR1ZpO54WTf5mxLAZqesJr4omG20Iv09miZmfs/jk0dCpE5M6dWfMtMWD66+sZIEp45l/0mg6zvmN1jMm80H3fVl+vp9o1/TPf6bMu1O6MauyOS0qZ9Ly4/dpde8dLLHvBrTlz0DsSDxKlGn/qYR3ly7MbteBF35bg79/+g3mzIbWbVLnb/b3DOb/eQxrVr6bOv/URbvx0F87MqdSXxN62FUGD+ppwYtMsw7zsNcft9N28sRALKjccAM/9LuUR1vuxSJNJ7F28/d5adZGKe6rNx9FqyYzGTGrByP/Xomm06bQ9NKLaDJ4ME2/+Sp1LzSZM5umM/+iQ+XvbNVuGM1WXSUlUD9fcH3eabouLStnMGVmayp/+53Kps2onDOHyvk6Uzl7DpV//kXlNtuwyOYrsk6/9Xms1Z4sNutrlpoznqX5knGte/DOXz2CMTjxRJp0X+Effauu33fh54z+eh46tZ3Bk6OWTF3OwIH9OfPMNAE4cyaV51+Q/eUjfMB2bjWV+VoGLye/jPuF31ouRJO7/o8mr71Kk0MPpsnpp9PkyD7/autffqbTakvQ9tB9/vlC+LuyWaqflU2aMunPDjRtUpn6adt8Ju1bhVlI9GCbNYspgx+g3eSJNGvXOhD6e+0ViC29NEg8K+TNfPOl2mrSvBmVTzxJkyMOD0SgHqx6iKpITEjoSFBIjMqCI6GqFwQJjquvhmOOAeVD1heYRHq28sQTwcveuecGn0o4SGxKCGn+6EVH5x0zBhRWZ+21Yc01g8+qfiRilQpJX1QSPFttFYzx7Dmp+cGgQfz96xSazdueORdexJyHHqHZdr2CsU17qs35bTJ/33VvKgZry1ZNUi9xrLJKICDC987ZlU1T33mq13/oUAZttVXw2Vdfp/rQZOwY+OADkJAfMCAQFKnJmuXfzL9JYEic6KVKzDJfqNJFc7bPJHoUsFz9lfBWCCLtX5U4PvnkQFxrXAothVitzz8fTjsN9t//31Y1t3XNOl/633OdV98HVcaItGM0vJqa3z08jGGjO3DJ3Yvx7r5XB/NDL3Tpc6Dq/5qPeonVXFSbEvD6PtMLquaPxObZZ//7wpj2XEmd+rzzgtSP/fsHPVHy4cGDmXLRRXTcYgv9xQKw0PnTCI5bHPgG6A6MTbve+8O3hPTosSkBeN99E2jbthYBKGtT61bQcd5/vnTk+STjWmbR/TngiMnM/+e3nHVVJ2b8Op3Z02fw9/+3d66xcR1lGH7Prr2xk+bahBZBbiQU1Cb0JggUCVSgrYBQoCpCBEH6A4mChARCQqJcfoAo1z/cr4IfSCAqCgLSH0CbFKRCAk1KStqkVZGSJk4DtRNycRN77TV6z5ljNs7anl3Hm+3Jc6Qosj1nzszzzcx5zzcz3yxfqZHueWn/OHhwTKWRYb1q/z0aXH2V/tG/XF21IV2nXdLGW8c/Mv1R5RmrK8/s1Pyu09pbXasn/nu5XrboSPr/moX/0YpTe1W6Zr2OjS1JHTe+rr1Wmn/6iB7ZXVK/XhCKWNPq0tOqLVqikd4F6cesdUUe2cYfhu6HrlNFQ6oNj+iqS49o3cCDOnjjZt2/rUuJRjWmzKuzaVPmPMs/Srdvz5w5fn+dMyYOnkwHn3R8HKulX4LJwoXpz3aqbtyYOdc8M+FxYqpjWn1Ckd9NLnv9MXt2NHh88725Y7G3MqI7qj/SgcoabSvdlNZvYOAudXffnY7leVqz8N/MYoUOqGRH5dKlOlOalzoasxHmmBboRCZqu3s0NjKSCqvBucu06X1daRoH/TYP18H/+978435Opaah4VL6/tqwIcvT72fXwQ7EoaExVfuP67gW6dLyUd2+eX7q3x8rd4+3OQ2dkSpzdOTfSeqQWbViNHtAT49ODpZlR4Ovd9z8nEpdifoGetMx1k61sy7DK5X06ONlXX10a/puU1clLXO1/5geTjZoePFl6b1+b/kdvnRp5ohduTLj5N/P2/ewar7vxEnV1l+tWu8lmUOlVkudOqtfOKR1y57RnHJNf312jQ4dStL3hG1ooZg8d0pJpaJkbm9avGT/v6S+w3rg9A26ft5ePbtsXVqmgf4xnRrMVMErtUMLVy2W1l4x3k/8e9vcbfDNuk/bum7RaJLZZHT0LpXLdzfsp+f23uw31jeuhx3Q/sjq0rCUlLLnpVI6+wyQ/v/116PndMedc8fbvmOAZs6Jcy/rqFyfLVs2pr6+RN1JVS+ee1SlwRM60LVWixYlaRu1Q88aMF99YqfO/qeqWtV9SE8OrVYlGVZ5rKqyRtW1aMG4U9wvaTvn3K93/a2aav/0KnentnTfdb4ej/I+67bpd/TInn3at7+ip4ZXqqtUU7k2rHJvj8qV8rgD1/f7Pqd3u3AbsU61trTWGp+wqI1q8HRJhw8n46EXFy8e0/XHt+qB2o1aWDmtweFuVVU5C5Tzd7s93FfT0wczzjctf1wv6XtIY++8LRNjyjTyjh1Zu3T5d+/O7G1O/YdOa+djbls1ldNP1JrKPZVxRh4v3PZtj3zMqnfeWaO4XmZonta0bhd2mKd9RpmNzdHl9eW+737on53GTq7k3nu0Z94GLb2srKXP7FFSLis5dVyl3t607SdvfEPqQKtfYeT7PS54wsP/8skPjxker9zt/Wx/I9rJljtnXdbHfn9QteqIkp45aSsd/2g9NqBk3Xol5TAW101WpP2v7udk59+VjFaVvOaGs37vdNZvnnSyvvcqDDswcqep25zHYv/sfjRRD5pv/q3ZqG801LeP7lYy0C8tWZzWJh2A5s9X9RVXaMuW5c4GATjZYHYR/r4ZD+CLJB26CBlRZQhAAAIQgEARCNjp01eEijRbB6aAGxNrtAbwsJeITFgDaH5ezDP94r5mLUN6CEAAAhCAAARmk4B9r3635z7u2XxWx+WNAGxsEq/z8y7gt0qyGPx02AXs1e7T7DzoOBtTIAhAAAIQgAAEIHAWAQTg5A3CK5g/KMlfCI7G1ygOIM0JAhCAAAQgAAEIPO8IIACfdyajwBCAAAQgAAEIQGBmBBCAM+MXc1rIzJ7A3bNNwEG+PxOm9kO8E/1O0nvDgx0Q7puSrg/hgX7owAITCkU7mG0rtZ7/u4P33kHpLpHkbdH1B/meD/vG5NF6DbizGQLT2du2P+PN2tmW0HTtl0N+1Z/yNF1/xt7NWGR2034xLNVy3KZTkv4k6RMTNmd6q+93JL0+2P4XIaav20B+eYbPS7+WSdoX/l4fojomj9mt6SzkjgBsHWrsaSGtP4E720HAAtDBoF7X4GEWDE9K+rGkz4WTYHx0+dckfT2kpx20w0qtP8NB3ZZImusIYBME4Pmwb0werZeeO5slMJW9nZcFoPv7ZAeQTdefsXezFpnd9F+Q9MsQo9d9/LuSrnQ0s/BYaxyfp+XjXL2u32PBFklbg8hzsndJ+oGkt0naLsmh3r4s6eVhd3BMHrNby1nKHQHYOtjY00JafwJ3toPAVAJwcxgIvNM79xr5yIWPSHppKBztoB1Wmvkz/PXvQb/eA3g+7BuTx8xLTw7NEmhk71wAvim0hUZ5TtefsXezlmhvenv6dwWhdzx4/f4g6XJJx0JRbg3RPCwGq6EtPCLp43VFdR73OhZ8ZB7treV5ehoCsDWQzcQKbO0J3NUuAhaAdv17d7f//UXSpyTtD8cBOiB4OPstLZKni3yWlIOHOsJs7Kkx7aoPz2lMoJEg8BEfM7XvdHl4Woqr/QSmEoBHwofAAUnfC55hlzBmXMfe7bdlM0/09O+dkrKjXiR/sH8o9PM8Hx9947h/nsrfI+loSOOp4fz6viRHC789Mo9mytgxaRGArZmimdNCWnsCd7WLgKcLHMfxoCQPDF+V5LM2/CX5DUk+4+w9dYXxtIDXC3lNiAVg7Kkx7aoPz4kXgJ4Snql9p8vDMca42k9gMgF4Y/jIG/XhIMET9ElJfuHHjOvYu/22jH2iPbu/lnSbpD+GmxzCzeHc6g54Vk/42PfhwP7g91pAp/Fxr/n1JUnXSbo5hIGbLo/YMnZUOgRga+aI+VJsLWfuutAEfKaUpw68HuQt58FDdKHrw/MzAngAL66WMJkAnEjBMwAWghYDMeM6HsDObEcbJf1Ukqfof1tXxKk8gOvDxzwewM60aUeXKva0kI6uBIU7h4AFoKd13x48gl8Jp700swaw0akxoL6wBBoJgvdLatW+H5P0sxAgfro8LmzNL86nxwrAz0q6RdJrA6bJxnXs3bntyBEbvhU2c9w/oZje3Oc1gJ7dmbgG0FO8w2ENoNf8eSlQfnnTyK/CGsCYPDqXzhQlwwPYutk4LaR1dp10p3eAeXPAgKTLwhSwvQH+OnT/eCLsAvZi4LWS7gtrA/NdwLSDTrLmuWXxNL03flgQeAe3A7t7+s8Dv6d/Z2pf7wqdLo/OJlSs0k1l72tCn/5n3W7gn0uyCPx2wDBdf8bendVevLP385LsAXyoQdE8hnuDhwWevYHe+PEbSQ/W7QL2Oj/vAvbmkB2SPhA2/3l9sNcKxuTRWVQiS4MAjAQ1STJOC5kZv06424PBq4MY8Bfin0NcQHsCfK0LMaQcB9BTww4z4AGn/qIddIIlG5fBU0I/qTvrM4/95rVgtvX5sG9MHp1LqFglm8renuK1t9brd73705tAHB/OsT2b6c/Yu3PajGdmbMuhUKS8f3vjXi4IbW+P23kcQHvuLfR9X359OMQPdBzAvZI+Gjb75X+PyaNzqESWBAEYCYpkEIAABCAAAQhAoCgEEIBFsST1gAAEIAABCEAAApEEEICRoEgGAQhAAAIQgAAEikIAAVgUS1IPCEAAAhCAAAQgEEkAARgJimQQgAAEIAABCECgKAQQgEWxJPWAAAQgAAEIQAACkQQQgJGgSAYBCEAAAhCAAASKQgABWBRLUg8IQAACEIAABCAQSQABGAmKZBCAAAQgAAEIQKAoBBCARbEk9YAABCAAAQhAAAKRBBCAkaBIBgEIQAACEIAABIpCAAFYFEtSDwhAAAIQgAAEIBBJAAEYCYpkEIAABCAAAQhAoCgEEIBFsST1gAAEIAABCEAAApEEEICRoEgGAQhAAAIQgAAEikIAAVgUS1IPCEAAAhCAAAQgEEkAARgJimQQgAAEIAABCECgKAQQgEWxJPWAAAQgAAEIQAACkQQQgJGgSAYBCEAAAhCAAASKQgABWBRLUg8IQAACEIAABCAQSQABGAmKZBCAAAQgAAEIQKAoBBCARbEk9YAABCAAAQhAAAKRBBCAkaBIBgEIQAACEIAABIpCAAFYFEtSDwhAAAIQgAAEIBBJAAEYCYpkEIAABCAAAQhAoCgEEIBFsST1gAAEIAABCEAAApEEEICRoEgGAQhAAAIQgAAEikIAAVgUS1IPCEAAAhCAAAQgEEkAARgJimQQgAAEIAABCECgKAQQgEWxJPWAAAQgAAEIQAACkQQQgJGgSAYBCEAAAhCAAASKQgABWBRLUg8IQAACEIAABCAQSQABGAmKZBCAAAQgAAEIQKAoBBCARbEk9YAABCAAAQhAAAKRBP4HwPYY3ChFVTIAAAAASUVORK5CYII=\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, sharex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG:root:--- request header ---\n",
      "DEBUG:root:GET /ob/api/ws/TLB99029472/venues/NUEX/tickertape/stocks/NTU HTTP/1.1\r\n",
      "Upgrade: websocket\r\n",
      "Connection: Upgrade\r\n",
      "Host: api.stockfighter.io:443\r\n",
      "Origin: http://api.stockfighter.io:443\r\n",
      "Sec-WebSocket-Key: CimnYhJtJN31OUUNLwbcAA==\r\n",
      "Sec-WebSocket-Version: 13\r\n",
      "\r\n",
      "\n",
      "DEBUG:root:-----------------------\n",
      "DEBUG:root:--- response header ---\n"
     ]
    }
   ],
   "source": [
    "ax[0].clear()\n",
    "ax[1].clear()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n",
    "a1, = ax[0].plot(asks, color=\"red\")\n",
    "a2, = ax[0].plot(bids, color=\"blue\")\n",
    "b1, = ax[1].plot(askSize, color=\"red\")\n",
    "b2, = ax[1].plot(bidSize, color=\"blue\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def update(i):\n",
    "    ax[0].relim()\n",
    "    ax[1].relim()\n",
    "\n",
    "    ax[0].autoscale_view()\n",
    "    ax[1].autoscale_view()\n",
    "    \n",
    "    a1.set_ydata(asks)\n",
    "    a2.set_ydata(bids)\n",
    "    b1.set_ydata(askSize)\n",
    "    b2.set_ydata(bidSize)\n",
    "\n",
    "    return a1, a2, b1, b2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ani = animation.FuncAnimation(fig, update, interval=50, blit=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "draw()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}