fixing_steiner_tree_bug.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "\n",
    "import pickle as pkl\n",
    "from graph_tool import Graph, load_graph\n",
    "from glob import glob\n",
    "from utils import earliest_obs_node\n",
    "from gt_utils import edges_to_directed_tree, get_roots\n",
    "from feasibility import is_arborescence\n",
    "from tqdm import tqdm\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from gt_utils import edges2graph\n",
    "g = load_graph('data/grid-64/graph.gt')\n",
    "p = 'outputs/paper_experiment/grid-64/si/no-order/qs/0.2/50.pkl'\n",
    "infection_times, source, obs_nodes, true_edges, pred_edges = pkl.load(open(p, 'rb'))\n",
    "t = edges2graph(g, pred_edges)\n",
    "\n",
    "assert is_arborescence(t)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from graph_tool.all import GraphView, min_spanning_tree\n",
    "from steiner_tree import build_closure, get_steiner_tree\n",
    "\n",
    "gc, eweight, r2pred = build_closure(g, obs_nodes)\n",
    "\n",
    "tree_map = min_spanning_tree(gc, eweight, root=None)\n",
    "gc_tree = GraphView(gc, directed=False, efilt=tree_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "root = earliest_obs_node(obs_nodes, infection_times)\n",
    "t = get_steiner_tree(g, root, obs_nodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
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       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
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       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
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       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
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       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
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       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
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       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
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       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
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       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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HP3www/h7eWJju3boODKaRgMBsycOROAsjkKAO7ubtjy/aoymXm7LDUaDIpe1KN0lk6YMAHd7++CpAaJePONLIgIfv/9d8u6SmZp+Rxt3749HBxMOHN0L37+bi3c3d2rJUcbNGgAg8GAzh3b4q1Z0+Dk5GTZyVIyR8vPbdiwITw9PSEi0Gg0eOXll9GnT58ay1LugFB1qiXFpwQ8UOq2BSLy73LrRUlxcfqJSIAUF2dkuXWWisi8CmbUSHGWLjB/f3/ExdTF1vXfQKPRICQkBACwfft2eHh44MyZM4rP/+OPPyAicDKbgbxz6NnjQYwaNQpOTk7Yt2+f4vNK+/zzz+Hi4gKTyYiundtDp9OVOQUsKSkJX3/9dZXn/PnnnzAYDPjxPx9bynHa1LFo2SzZUqAlt78wYhge6NIeAf5+WLt2bZVnl2jbti3WrFkDAJg/v/jUhK6dO0Cn0+GB++8HAHz00UeKv3Gy/M5Pp04d4e7mioXzZqJj+wwMHDDAasVZurRXr16N0JBgeHi448zRvYiMCMcXX3yBKVOmICUlBXl5eYrPBIDHH38cOnt7HD2wA+8vnAs3NzcUFRVh0aJF6NChgyIz/4oaLs57NkeB/8/SxzIz0bB+Ajq0S8dH778DEcHixYsBWDdLQ0ND4GAyAXnn8MqkcWjfrl215OiBAwdgMplgNBjw2OB+0Gq1OHXqlOXnSuUoACQkxGPBzFfx+7FfK5Wl3l6eeO211xSZXaIkS/fs2QOz2Qy9Xo/aoSHw8vKyvGqtdJaWz9EXxoyBo6MD3p77Bp4ZlomGDRtUS44eP34cIgIPdzecOboXDz3QFa+++qriOVp+7sqVK+Hl5Ql3N1f8d+1K2Nvb4+jRowBQI1nKHRCqbhopfiNl7I3vrXLkbujQoRg+fDiGDx+u6C+gldGtW1fY29tjy09fQ6PRoFu3rpafJSUlKXbk7urVq2WOFNWvnwiT0Yhu93WEk5MTXnrpJTRv3lyRWXea/eADD8DJyQlt22bAbDZjz549AIpL1d3d3fJLRVU98MD98HB3s5y33LVTW+TsXg9cysGgvg8jKiIM4WGh6PPIA1i6cBb8/f0UO28aALKzs5GWlobY2FgkJCTg5ZdfxuTJkzF79mw0adIEERERSEpKssqRpNI7Pz/++CPs7e2h0+nQunUrnD171mrFWbq0c3Jy4OjoiAB/Pwzq3xtmsxkvvPACkpKSFD3VsPwvCv8YPhwe7m745otP8MvG76DT6VBQUAAAMJlMuHDhgmKzb2Xt2rWWTBk6dGhNF+c9n6OvvvoqYupFw2x2xKhnn4SI3HRgQ4ksLZ9lnTp2hL29PR556AE4Ojpi6NCh1ZajgwcPhouLC5o2TYGjo6PVcnT69OlokBiHxPh6d8zS+zu3g06nw/HjxxWZXaJ0lkZHR+PRRx/FO++8g927d1s1S0vn6K5du6DX66HX6xEbG4P//e9/1ZKj+fn5xafRenrg2aefgLOzMzIzMxXP0fJz33vvPTSon4CkBolY9ckHcHBwKPPnWx1ZamM5SipjLyJXReT+G9/3kbs7d/m02Mi5y+VLZPz48XB2doadnR1cXFwslxTMzs6Gp6cnTp48qcjc7OxsJCYmWk796tKlC7KysjB16lTs2bMHTZs2VfTSjbeb3bVrV+Tk5AAAli5davkFPS4uDkuXLlVs7ubNm+Ho6Ij/bf76plMFSi9/nN6HhvXjMfGllxSbXdPK7/ysWLECAJCZmYmAgADodDr4+PggPDxc8dmlS3vJkiXQ6XRITm6Mxx9/HA0aNCjz/LfGzDVr1kCj0SC1ZTN4e3vh6RtvqFyxYgUCAwMVn30nNnDk7p7LUaBslv7555+Ij4+HRqNBWFgYkpOTLc8HJbO0oix7++23MXnyZKxbt+6ezNELFy7AwcEBq5a9c9scLco9gp7du+LBBx5QbHZNs5Uc/eqrr6DX69GgQX08/PDDVsvR0nPPnTsHPz8/6OztEV6nDpo1a2p5X1NNZKkN5Cjd454SEa8bX3tK8cv9F0TE+8ZtZim+LOQkETFK8dVbcqTs1VtGiMgRKb5kpElEpkjxFV5s4uottyqRoqKiW4Yd3b0XxoyBv58vtv+4psLSvJCzE21atUDTpsq+lK1mFT2PSz6TpU6dOkhMTERCQgKSk5OtNnP27NkYP3685VKS8fHxaNOmTY1cs78GivOez1Gg4iw9cuSI5WfMUuUsXboUZrMZny5dUGGOXjt3AE8M6oPAwACcOHGipjf3nlATOVp+bkxMDIYMGYKsrCwkJSXVaJZyB4Ss7XMR+U2Krzt/QkRWikj9cuvEiMgPUnxE76SIvFjB/Uy4cT9XxEavX0/Vo6ioCJMmToRer0e7NqlYunAWfvzPcnzx8XsY0r8nHB0d0blTJz4HyGpqoDiZo6S4kp2QpAYJmD/zFaz7cjm++fwDjH52KLy8PBAfH2fZASRSGndA6F7D4lSJkydPYuJLLyE+Lg4BAf6IiAjHwAEDFPvcD6JbUUFxMkdVIjc3F7Nnz0Zy48YIDAxAWFht3N+tG7766iurXHaYqIQKcpRUhsVJRFalguJkjhKRVakgR0llWJxEZFUqKE7mKBFZlQpylFSGxUlEVqWC4mSOEpFVqSBHSWVYnERkVSooTuYoEVmVCnKUVIbFSURWpYLiZI4SkVWpIEdJZVicRGRVKihO5igRWZUKcpRUhsVJRFalguJkjhKRVakgR0llWJxEZFUqKE7mKBFZlQpylFSGxUlEVqWC4mSOEpFVqSBHSWVYnERkVSooTuYoEVmVCnKUVIbFSURWpYLiZI4SkVWpIEdJZVicRGRVKihO5igRWZUKcpRUhsVJRFalguJkjhKRVakgR0llWJxEZFUqKE7mKBFZlQpylFSGxUlEVqWC4mSOEpFVqSBHSWVYnFaSl5eH3NzcKi95eXk1/VCIqkQFxckctRLmKFExFeQoqQyL0wry8vJgNBpLwqJKi9FoZHnS35oKipM5agXMUaL/p4IcJZVhcVpBSVAc27MBucd33fVybM8GKPn3k5ubi6VLl2LmzJmYP38+fv31V0XutzLOnTuHFStWYNGiRfj000/5nFMRFRQnc9QKbDVHr127hs8//xyzZ8/G3Llz8cMPP6CoqEiR+76Tq1evYvXq1Vi0aBGWL1+OEydOVMtcqnkqyFFSGRanFZQERe7xXcClnLteco/vUqQ4T506hccffwxmRwfEhgehc4sEtG5cD0aDHs2bNsHq1asVeuQ327NnD/r2fhRGowGxEcFo0TAaUbUD4OhgQmbmEBw+fNhqs8k2qKA4maNWYGs5+scff+DFF1+Ej5cnQvy90LFZPNqmxMDNxQnRkeGYN2+e1XZETp8+jeHDn4FrLRfUDvRBi4bRSKwbCr1ehwfv74YtW7ZYZS7ZDhXkKKkMi9MKbKk4s7OzYWdnB7PJgIhATySG+2PpxD4oXDcNg+9LhquTCSKCkSNHKvgnUMzb2xtarQbuLo6ICvHB0lcG4Y/1M9AlNR7Bvm6o5eQAnc4eK1euVHw22Q4VFCdz1ApsKUcvXboEg14Po16H2n7uSCiVo493S4GHiyNEBN26dUVhYaGCfwqAv78/7O3t4exoRHiQF5a+PNCSo7X9PeDp6gQ7rRazZ89WdC7ZFhXkKKlMjRbnO++8A41Gg08//RQAsHHjRiQnJyMxMRF169bFa6+9Vi1zN23ahKZNmyI+Ph6JiYn473//W6X7r6g4g4MCEBURhoS4ukiMr4dl780BLuXgwPbvkdK4ASLq1EajBgn43+avFSvOP//8E1ERdeDsYMT2hc+icN20Msv3s4fi2Ipx8PNwhoPJiM8++6xKj7u0AwcOQKPRYNyQDijcMsey/LF+Bla/MdTyfecWcdDpdPjtt98Umw0AwcHBiIqKQkJCAhITE7Fs2TIAQEZGBuLj45GQkIAWLVpg+/btis693ewS5Z9/9zoVFCdzFPdujgJAl84dYTTosGHeM7fM0UDvWvD3csPkyZOq9LhLu3z5Muzt7fFIu0Yo2Dz7ljk6uFszaLVabNq0SbHZAHPUlqggR0llaqw4c3JykJKSgpSUFEuAJCQkYNWqVQCACxcuwMvLC3v27LH63ICAAEtZ7t+/H0FBQfjzzz/vekZFxRkaEoidP39509G5Vi1TsOit6cClHCxf/CaS6scrVpxLlixBZIgfQnxcK9wBKVlCfN0wqmcaGic1uOvHXN5jj2XC0WTA9n+PKbMDUn7ZuOg5mAx6jBs3TrHZABAaGoqdO3fedHvpP8sVK1YgPj5e0bm3mw1U/PxTyq0K+05Fbm0qKE7mKO7dHN2xYwdMRgOCvGvdMUfnPfcQXGs5448//rjrx13a3LlzodfZY+v7o2+bo5sWPw8Xswld7+ukyNwSzFHmKJG11EhxFhUVIT09Hdu2bUNqaipWrFiBy5cvo379+li8eDEA4OjRowgMDMTp06etNnfZsmXYtm0bjEZjmfXi4uKwYsWKu55TUXGGBAdgx/q1ZUrzTPY2uLg4o/D3w5bbfLw9cWjHOkWKMyU5Ca8/3RUhvm6Ir+OHuDBfDOzUGKc/f+mm4lw3ZxgcHYzYunXrXT/u0o/f7OgAXw8XxEcEIC7cHwO7NsXpr1+7qTh7d2yMLqnx8PXxQn5+fpVnlwgJCcGOHTsAFL9pdP78+XjllVdw6NAhyzoLFy5EYmKiYjMrml1a+eef0sV5q8K+XZFXBxUUp03k6MqVK3Hp0qVqz9GPP/74ns7RzMwh6N8puVI5um3hP1AvLADvvPPOXT/uEkVFRYiLqQt3F8dK5eiALinQ6exx9OjRKs8uUTrLioqKsHz5ckyZMqXMKy3M0eqhghwllamR4szKysJLL70EAKhfvz5cXV0hIqhfPxGBgYEICgqCg4ODpUStMTcxMRFmsxkajQY6nQ5z584FUHwagcFgwPTp0+96zq2KMz62LuJiojGo78M4e3g7tv6wClERYWXKtFGDBHy7emmZ4jx9+jSuXLmCS5cu4eLFizh//jzOnDmDU6dO4cSJEzh27BiOHDmC7OxsHDhwAPv27cOvv/4KjUaDQ8teQM7HL6Jw3TTkf/dPjOqVhvbJ0TcV5/aFz6J9SgyGDx+ODRs2YOPGjdi4cSM2bdpkWTZv3ozNmzdjy5Yt2LJlC7Zu3YqtW7di27Zt2LZtG7Zv347t27dj/vz5CPDxQM7qKSjcMgf5G2dhVN8MtG9ar0xpTn7iPqTE1cblddPh6GDErl27FPl7BorLKz4+HnFxcQgODkJ4nTB07tgOrq6u6Natm+V5puTMimanpKQgJqYeWrduhREjRlief9YoztKFvXv3bjz7j39g/PjxCAoKqrDIq4sKirPGc7RJkyYIDg6GiCAoKBD+/v7VkqPJycnw9fWFRqOBVqvFyy+/DMA2c/Ru/35i60Zhxcv9K52jY/qkY8CA/nf9uEucP38eIoKdy8ZWKkev/jQDjePC8cEHH1R5donSWZaYkABvby/0eLAbHBwc0KZNm2rL0bZt2yIxMRGNGzfC4MGDqy1HT506hRfGjMHIESMQEBDAHCVSULUX5+7du5GcnIyCggIAgIODA3r2eACnc/bAy8sTnTt3BlD85unAwEDFTh0oP9fR0RG9ez6E65dPIaN1GgICAlC/fn307t0b6enpmDVr1l3Pqqg4j+3ZAFzKQcHFbDw3/HF0yEjD1h9WITK8bHEm1Y+/qTgrs2g0Gtjb20Ov18NkMsHBwaF456XcUboTK8fD2dFYYXHe1zwGTk5O8PX1ha+vL3x8fODj4wNvb294e3vDy8sLXl5e8PT0hKenJzw8PODu7g53d3e4ubnBzc0Nrq6uMJvNCPVzL1OSJ9a+XDz3xvevPd0NSXWD8fv3/0Lhljnw9nDFxo0bFfm7BoBjx44BAE6ePAkRQXqrlkDeOXRsn4FXX30VALBo0SJ06NBBsZnlZ69atQoGgwEJcTHo0+sh6PV6yykp1irO+Ph4REVFQafToUf3bmiV2hx6vUDWZTIAACAASURBVB5xcXGIi4vDoEGDcPbsWUXn3okKirPGc9TLywvNmybj3PH9qBMWivi4OADWz1Fvb2+0bJ6C65dP4fEh/eHi4mKzOXq3fz9hoUH4z/TMSufolCEd0PPhh+76cZc4evQoRATXN82qdI62SYnD/Pnzqzy7REmWFRQUwNHRsfg03bxzGDNqOHr16gnA+jl64MAB2Nvbo250JJ4f8TS0Wi2ys7MBWDdHY2Ji4OzsjNZpLfBw927QarWoV68ec5RIIdVenG+++Sb8/PwQGhqKkJAQiAjcXF0xafxo2NvboU+f3pZ1u3fvjgULFlhlrkajQa1aLpg7MwvjxoxA9+4PWtaNjo6u0hso73T1lt8ObIazsxPOHt4OZ2enO546kJ2djfPnz+P333/HpUuXcPXqVeTl5SE/Px8FBQUVXvqxqKgIDiYj1s0ehgtfTLaUZNbQ+9AyIazC4mwSV0eRP+/169fD3dUZZ7/5p6Uos555AC3rh1u+bhAdhAvfTUPhljm4/OPr0Ot12L9/f5Vnl3f16lXo9Xo4OJhw5uheREaE4+2337b83GQy4cKFC4rPBYApU6aga+eOcHIyY+a/XrlxdDoIISEhMBqN8Pb2trzypoSSwp4zZw6CAgPRoV06ruWehMFgwN69e1FQUIDnnnvOKr8s3I4KirPGc1Sr1cLZyYxJ40dDp9MhPj7Osq41c1Sr1cJsdsTcmVn4+N/vIjIywrKureXo3f79JCc1wOxnH6h0jmZ2TcGTTz5514+7xKVLlyAi+HXZi5XK0cItc1AvPAjLly+v8uyKREREwGAw4Mq5HHRsn4Gnn3rK8jNr5uiqVasQEV4HTk5mzJ2ZBTs7O/j4+Fg9R9etWweTyYT2bdOBvHOoGx2FDz/8kDlK96yXRWSniOSKyAkR+UBEAsqtEygin4vIJRE5IyIzRcS+3DpDReSwiFwRkS0i0vwW82r88pEBAQHw8vRA/z49ISKWo9Nnz55FUFAQNmzYYJW5tWvXhpOTGV06dYDJZMJXX30FAJg3bx6SkpKqdN/li/Pqqb34/divlnKcNnUsUpsnA5dykNaiCd59cxpwKQcfLZqj6Jsn+zzaC73bJSEx3N9y7nKX5jE4vHwsCtdNw5AuTRDg5QKdvR08XByh0QjOnDlTpccOANevX4eXpwdq+3tYzl3ukhqPw6sm4+iaqdBoNKgT6InEyEAkRASgtr8HYutFK3YN/atXr+L333+3fN+zZ09oNBqICNq3b2d5r8mKFSsQGBioyMyKZn/33XfQ6/WoUzsUfR99GOHhdSxHjq1x5K7E6tWr4e7uDrOjIz56/x0YDAacP38eAPDbb7/B2dnZKnNvpQaKU3U5GhUVBQcHBwzq/yg0Gg0ef+wxANbP0djYWOj1enTt3BEuLi6Y8frrAO6tHJ02bRqS6oZWKke93Zyg1Wiwbt26Kj32Es2aNinzXrrb5WhMHT84OpgUex6Wz9Enn3wS9vb2EBHExsZYusLaOXrs2DEYDAYEBwVg7PPPwtnZGSdPngRg3Rw9cuSI5eDVz9+thYuLC9avXw9ANTlKKjNFRBKluAidReR9Edle6ucaKS7WhSLiKMUlukNEppdap7uIXBSRZjfu5wkRuSwi/hXMq/HiTEtLw1NPPYUXXngB06dPR4MGDZCQkIB69erh9RtlZq2548ePx7Rp05CZmYmIiAhERESgS5cuOH78eJXuu3xxZu9ch8T4epZzl7t2aouc3euBSznYt/VbNGlUHxF1aiOpfjx2bfxKseLcuHEjnBwdLOcu32op+CELfdo3wqM9H6nS4y5twoQJaNkwCvkbZ6H8GybLX5Y3LjIYc+bMUWx2dnY2EhMTLecPd+3aFXv37sX27dvRqFEjxMXFIT4+Hm3atFH8nN7ys5OSktC0aQp69HiozIcupqWlKVqcpQu7qKgIaampN17lq4V3333Xst60adPQsmVLxeZWRg0Upypz9MUXX8SYMWMwfvz4as3RrKwsTJs2DX369Lknc/T8+fMwGg34fvbQ2+ZoySsjcTF1FTuYsmLFCgT4eOBiqVc5KloKNs/GQxlJyMwcoshcoOIcPXDgALZs2VLtOdqiRQukpaaiY4cO+Pnnny3rWTNHAeChhx6CnZ0dDAYDxr7wguV2leQoqVy8iBSKiMuN71uKyDURcS21zn1SXIy6G9//V0SmlbufbSLyQgX3X+PFeS+ylQ/QKioqwoD+/VEvzB9HPxl3y52PF/tnwMvTXdFPJb9w4QIiwsMwqFvzW+6E/LF+Bh5Ib4AGiQm4evWqYrPVqKJfFg4fPoxDhw7ddHtOTk61bpsNFCdz9G9I6Rz19/fHG2+8cVcfFDhjxgx4uDpj04KbPwekZPlgwqNwMBnx/fffK/ZnUFBQgLZt0pGWFH3LnZCCzbPxwsAO8PH2VPQKWGpUUY4eOXIEBw8eZI6S6owSkexS3z8lInvKreMrIkUiEnPj+wsi0qPcOm+JyPIK7p/FaQW2sgMCAPn5+RjQvx9qOZvxTI+W2LloJC79ZypOf/4SFjzfAw2iQxHo74dff/1VwT+BYjk5OYiOjEBCVAjeGtsLuT8Uv1Hy/LdZeGPkQ4gM9UdSg/qKXiKUbI8NFCdz9G9I6RxNSEiARqOB0WjEI4888pc//PS1116D0aBH7/aN8OObTyL3y6k4v2YyVr4yAG2bxMDJ7Ig1a9Yo/udw6dIlZKS3RpCfJ14e1hUnv3wFBZtn4+pPM7Bkcn+kJEQgMMDPKleiItthAzlKKpIuxUfk2pS6bayI/FxuPaMUF2fKje8LRKRtuXVeEZH/VDCDxWkFtrQDAhS/EvLDDz/gkR4PQaezt1w5K6ZuFObMmYNLly4p9MhvduXKFcydOxdxMXUhIrDTaiEiaJzUAO+9916VPqiM/h5quDiZo39T1sjRs2fPol+/fjCZTBARxMXFYfXq1ZXept27d2PYsKFwdjJbcjTAzwcTJ078yzs0f8X169fx0UcfoVVqC4iIJcfr1A7Bv/71L6u9AZxsB3dAqLp0kuLzj+8rd/vtjtzVu/E9j9zVMFvbASktPz8fZ8+exZUrVxQ7T7kyioqKsGXLFogo80Z3+vuoweJkjv6NKZ2ja9eutdx3YWEh5s+fj9DQUIgIXF1dMWrUKOTl5VVq2woKCnD+/Hnk5uZWa44Cxe9JOXDgAE6cOHFXp5PR3xN3QKg69JLi0kyv4GctRORPqfjcZf2N7/8rIlnl/r+tcptzl4cOHYrhw4dj+PDhZUKa7k5JUBzbswG5x3fd9XJszwbFd0BqUsl17enet3btWkumDB06tCaKkzn6N6d0joqI5QPsStu1axcyMjJgZ2cHOzs7pKen83Qmsgk2kKOkIsOkuDSb3uLnGhH5RUTeERGziARJ8dVdSl+95UEpPnrXTIrfUPm4FF9q0iav3nIvysvLg9ForPSHCN5uMRqNlT4qZ+tycnK4A6JCNXDkjjl6D1AyR+3s7CxfN23aFNevX69w3ujRo+Hm5gYRQXBwMObOnctXGcgm8BUQsrYiKb46y6Uby+Ub/y1dpIEisurGz86KyAz5/yu3lHhCRI6IyFUpvn59s1vMY3FaSV5eHnJzc6u83Cs7H0DxDohGo6npzaBqVgPFyRy9R9xNjrq6uiI5ORk7duyAnZ0doqOjISJIS0uz7NC4urri4MGDt5y7Zs0aJCQkQERgMpnQp0+fav/ka6LSuANC9xoWJ1WbI0eOcAdEhVRQnMxRGzJz5kyICHJycvDBBx9ARNC9e3eICB588EEEBQVBRKDVarFkyZLb3tfp06fRq1cvGI1GaDQa1K9fH19//XU1PRKi/6eCHCWVYXFStTly5Ai0Wm1NbwZVMxUUJ3PUxjg7OyMjIwMA0LdvX2g0GowaNQoigoEDB6Jt27aWU7L69et3x/srLCzEzJkzLTsv7u7uGDt2LK5du2bth0IEQBU5SirD4qRqc/jwYe6AqJAKipM5amMmTZoEjUZjOW0qPDwcZrMZkydPhojgmWeewZgxYyw7IeHh4bh48WKl7nvHjh1o1aoVtFot7O3t0b59e+zdu9eaD4dIDTlKKsPipGpz+PBh2NnZ1fRmUDVTQXEyR21MYWEhTCYT7r//fgDFl641Go1ISEjAhAkTICIYPXo0PvroI2i1WssHFK5bt67SM65evYp//OMfqFWrFkQEYWFheOedd6z1kEjlVJCjpDIsTqo22dnZ3AFRIRUUJ3PUBo0YMQJ2dna4fPkyAODrr7+2vPpRcjrW5MmTsWvXLpjNZmg0GogIJk2a9JdnrVy5EjExMRARODg4YNCgQZV+RYWoMlSQo6QyLE6qNtnZ2bC3t6/pzaBqpoLiZI7aoOvXr0Ov16Nv376W255//nmICFavXo1hw4ZBRDB9+nTk5uaidu3alp2Q1NTUCi/VeyfHjh1D9+7dodfrodFokJSUhO+//17BR0VqpYIcJZVhcVK1OXToEHdAVEgFxckctVGDBw+GTqcr82bxRo0awWAw4LfffkO/fv0gInjrrbdQWFiI9u3bW66Q5enpedtL9d5OYWEhpk2bBn9/f4gIvLy8MGnSpLvaqSECVJGjpDIsTqo2hw4dgk6nq+nNoGqmguJkjtqoq1evwt7eHk8++aTltry8PLi4uCA4OBiFhYWWS/SWXJK35M3per0ednZ2d7xU751s2rQJzZs3h1arhU6nw3333Yfs7Owq3SepjwpylFSGxUnV5uDBg9wBUSEVFCdz1IY9/PDDMBqNZT7RfMeOHdBqtejRowcAoGPHjtBoNPjkk08AAB999BHs7OwsH1xY+jSuu3X58mU8+eSTcHZ2hoggIiICH3zwQZXvl9RBBTlKKsPipGpz8OBB6PX6mt4MqmYqKE7mqA27ePEitFotxo4dW+b2N954AyJiuXJVWloatFot1qxZAwD49ddf4eTkBJ1OZ9lhUOqN5R9++CGioqIgIjCbzXj88cf5/KHbUkGOksqwOKnaHDhwgDsgKqSC4mSO2riOHTvC0dGxzKsgANChQwfY2dlh//79KCwsRHJyMrRareWN4xcvXkTt2rWh1WphMBhgMpn+0qV67+TIkSPo1q0bdDodNBoNUlJSsH79esXun+4dKshRUhkWJ1Wb/fv3w2Aw1PRmUDVTQXEyR23cb7/9Bo1Gg6ysrDK3FxYWwtfXFx4eHrh+/ToKCwsRHx8Pe3t7bNq0ybJOu3btICLw8PCARqPBSy+9pOj2Xb9+HS+//DJ8fHwgIvD19cWrr7560w4TqZcKcpRUhsVJ1Wb//v0wGo01vRlUzVRQnMzRv4HU1FS4urredHtOTg50Oh3S0tIAFO9wREVFQafTYceOHZb1Ro8eDRFBQEAARAQtW7a0ylWtfvzxRzRp0gQajQZ6vR73338/cnJyFJ9Dfy8qyFFSGRYnVZt9+/ZxB0SFVFCczNG/gYMHD0JEsGDBgpt+9uGHH1o+mBAArl27htDQUBgMBuzdu7fMenZ2dvD09IS9vT08PDzu+lK9d5Kbm4vHHnsMZrMZIoLo6GgsX77cKrPI9qkgR0llWJwqsn//frzxxhuYPHky3njjDezbt6/aZh86dAhTp06FTqfDkiVLcO7cuWqbXVhYiBMnTuDQoUP4/fffq20uFVNBcTJH/yaSkpLg4+NT4c8GDhwIjUZjeQ9GXl4e/P39YTKZcOTIEct63377LQwGA3Q6HRwcHGBnZ4fFixdbdbuXLFmC8PBwiAhMJhNatmyJN998E4cPH7bq3NKKiopw+vRpHDx4EGfPnq22uVRMBTlKKsPiVIENGzYgo3Ua9Dp7tG0YgUfT4tCuYST0Onukp7W06psef/rpJ7TPSIdeZ49mUUFIi/ZHgzB/GA169O39qFWvh3/mzBlMmTIFwUHFp0zY2dlBo9GgY4d2WL16tdXPr963bx+effZZdGjfFm0z0jFw4ED89NNPKCoqsupcW6OC4mSO/k3s2LEDInLLVxIiIyPh6OiIy5cvAyi+dK6XlxfMZjM2bNiARx7qDr1Oh2YxoejeJAptE0LhYNDBpLdHamqq1bZ7//79ePSRh2HQ6RAb6IG0KH8kBnnATqtBi6ZNsHHjRqvNvnr1KubNm4eE+FiICOzt7SEiSG6chPfeew9//vmn1WYDwKlTpzB58mR07tQRbdJboecjD+Ozzz5DQUGBVefaGhXkKKkMi7MavfPOO9BoNPj0008BAP3790dERAQSEhLQrFkzbN68WfGZq1atgqODEZ0ahEGjEax4rhsKl49Cv7RY1A1wh08tR2i1GkyaNEnx2R9++CEcjAZ0ig8unj2sLQoWZKJgQSZ+eak72tQLgohg5MiRis/euHEjPD3c0SolHstnj0Te7n+jYP9HyPnhLYx/qge8Pd3wUPcHrVKeZ8+eRaeOHaDX6/FIt7aY/cpIvJX1PIYO6A4XZyckJsTj119/VXyurVJBcTJHq1FVczQmJgZBQUEV/uzixYswmUyIjY0tc5uzszMMOnukRAXclKMxgR4IcHeCRiNwcXbG+fPnlXuwKP4gQ7dazmge4XdTjh55rRd6NAqDiKBx48aKH1Q5evQo6tWNQlx0bbw15TH8vn0xCg8sx7kt7+KNcQMRGRaIRkkNcObMGUXnAsWnwT32WCYMBgMyUptgxuR/YP6/xmDMM/0Q4OeD4KBAyyWT1UAFOUoqU2PFWb5Ezpw5g3bt2iE8PByxsbH44YcfqmXu1KlTERkZCa1Wa7nNGnJycpCSkoKUlBTLnM8//9xSGKtWrUJISIiiM/fu3QuzowmzBqUjJdIfKZH+luK8uOhpFC4fhcLlo/DPPqkQEezevVux2Rs3boSD0YC3+6eiSZg3moR5lynOCzP7IynUC1G+teBsdlT0lKy9e/fCtZYLskb3xYKXn4BGo8GKuc+h8MBytGxUF6EBXoiNCILJaED9xERFX5E4f/48oqMicX/HNEyf+Aw0Gg1Wvvcaik5tQNGpDRj9VF+4uTpDq9WiUaNGis0trfxzvHHjxkhMTERiYiJiYmKg0WiqdQdIBcXJHP0b5eiPP/4IEcF//vOfCn/+7bffQqPRWD49/fLly/D39cbQ9om3zdEPnuls+QT1ksv4VtWpU6fg6e6KMR3r3zZHk0I8odVooNPp0KNHD5w4caLKsy9evIjIiDoY0D0d86Y8VmGOxkeHwMXZEYEB/rh69aoCj7hYfn4+OrRvhwbxdTFlzOM35ejY4f3h7ekGjUZTZmdRScxRIuuqkeKsqEQGDBhgubTh5s2bERAQoPhLrBXN3bRpE7Kzs5GWlma14iwqKkJ6ejq2bduG1NTUCuecO3cOer1e0SNYj2UOQe+0OLSOC8aW1/oitV6gpThLL99MeBgGnR0GDxqo2Oz7u3TGP9rGo3W0PzaPewAtI/3KFOejTcKxYlhb9EmJQJi3K1555RXFZj/4QDc81rMtDn//JlLqRyKlfqSlOFMb18PKuc+j8MBynPx5AVyczfjpp58Um/1Q9wfRpV1LHNr0MVKSYpGSFGspzumThuOBjmm4fuInTHwuE8HBQdXyHC9t+fLliIuLU3TmnaigOJmjf7McDQsLQ0RExC1//uKLL0JE8Omnn2Lu3LlICPNH69g756ijQQdXZ0fFLtU7YcIEtIkNuWOO9k2JQPMIP0TWCYODgwNEBLGxsVX6u5g4cSKaJ9XDwf/Ovm2O/rHr34iLro05c+ZU+fGWmDx5MmKi6+DX7z+4bY6uePc1mExG/Pbbb4rNBpijRNWh2ouzfIk8++yz6N+vH/R6PY4fP25Zr3Hjxvjmm2+sNnfGjBkYM2YMpk+fjry8vFsWmhKysrIsZdSyZUt07twZ0dFR6NatK06dOgUAGDt2LLp27arYzEuXLsHs6IAnOzTAhB5NUbh81E3F+Vy3xgjzqQV3JxPmZmbAwWRU5E3ax48fh87eHs93SMT4Lg1RsCCzTHF++Fgb9E2JQMGCTPRNiUC/ppEICfRXZOfrxIkT0Ot12P/1LLROicOWla8htXG9MsVZ8nXhgeV4ql9H9Or5SJXnAsCxY8eg1+txaOPHSG+RhK1fvYfUlPqW4gzw88L+nz9C0akNyD/+I/x9vfHZZ58pMhu4+Tm+aNEi/PLLL2VOM2vfvj1mzJih2MzKUEFx1niOTpkyBQMHDIBer8f+/fst61k7RxcuXIgJEyZg4sSJOH36dLXlaGpqKgYOGICYmHpITW1pORJd2RxdvXo1RAQbNmy45TpNmjSBXq9H3chwPNgkslI5+vnoB2Cwt0ObNm2qfKne69evw8/bE/2aRlYqR0d3TIRBr8Pp06fxzjvvoHbt2hAR1KpVCyNGjEBeXt5fmh3g74tP3hxVqRxd8PITiKkXrciryfn5+fDz9cFni7LumKNFpzYgI7WJoqcQl3+OL126FL/88kuZf9/MUaKqq/biLF0iUVFRMJsd8ezTxafJPPH445b1HnroISxcuNAqc5OSkmA0GvHoI92RmBCHdu3aWq04d+/ejeTkZMtRyNDQUAQG+mPVJx+g230d0b59OyxevBhRUVGKnke7ceNGuDo7IjnCD/kfjqiwOEuWr8b3QFIdH/i611LkDekff/wxogK80Li2F67NG1ymOE9M6434QHdcmNnfUpxZDyVDRMrsgN6tuXPnomVyHP75fB9MeKrHTWWZ2rgeosMCEBcVjB4dm+KzeaNhMhkVKc6JEyeiU0Zz/HP8k5gwcjCKTm2wFGfuwW+g09njtXFPIrlBDJIbxODBzq3QuVPHKs8tUfo5HhMTA51OB7PZjMjICPz22284duwYHB0dFT9H/U5UUJw1mqMNGjSAXq/HE5kDoNVq0bRpiuX5bM0cbdasGTw8PNChXRu0aZ2KOnXqoHnz5tWSo7GxsXByMmPZkrfx7NNPIDAwEO+9995fylF/f3/Ex8ff8ud5eXlwcXGBiKB+be9K52jz6ABoNBo888wz0Ol08PDwKLNTWFkHDx6EvZ220jk6/eEURAd6Y/Xq1Zb7+N///od27drBzs4OWq0WrVq1KvPZJrfy888/w93VBa+OerRSObrri+kwGPR39TjL+/TTTxEc6IfXXhxWqRwd8UQvBAUGVHluidLP8YYNG8LZ2RnOzs5wd3fHli1bmKNECqnW4ixfIh4eHujbqwfOnzgAg0GPgAB/y7rdu3dXrDgr2glISW4E5J3D2WP7ICJo2rSpVYrzzTffhJ+fH0JDQxESEgKtVguz2RFzZ2bhp/+ugYuLCyIiIhT55bu077//Hm7OjvBzMyPUywUhXi4w6u3hXcsRc4Zk3FSeUf5uCPB0VeRo6eLFixHm4wa/Wg4I9XBCiIcTjDo7eDubMKtXM/i4/P/tZoMO7mYjtFqNIuU1depUtE9tgOSECOTv/fCm4jy67i3LUbuZ4wciItQPIoI//vijyrN7P9oLwwZ2R3KDGFw/8VOZ4jy350toNBpMej4TRac24PDmFXB3dUFISHCV5wI3P8f1ej2GP/kYCq6cRueO7fCP4cMxadIk9OjRQ5F5f4UKirNGczQkJAQtmqXg/IkDMBmNEBHLL0fWzNHY2Fj4+fqi6I+zKLx6BgEB/khISKiWHLW3t4fRaMDcmVm4ci4HIoKwsLC/lKMffPABRAS7du265Trr168v/mRyV8dK52hqXCgiIyMhIsjMzISvr+9dXap3586dMOp1fylHfV2d8NFHH910X9euXcPYsWPh7u4OEUFQUBBmz559y1edV69ejbAQ/0rnaN06AfDxcsfPP//8lx5jRbKyspCRmlzpHPXxKn5M165dq/Ls8s9xN1dXdLuvI5B3DmNGDUd669bMUSKFVGtxVlQiOp0OLzw3HDp7ezRpkmxZt1GjRoqdOlB+rk6ng52dHSaNH41Fb8+B2WxGixYtrPrmyRJ16tSBh4c73po1DdGRETCbzTh69Kjic/bs2QOjQY/cxc9YyrHkyF3+hyOwf9Zgy+0/v9wbbmYjHIwGRd5U98UXXyDE2x3X5w+xnKtc/tzlkqVvSgQmdk0q80tTVcyYMQMxkSHw83ZDaIAXQgK8YDTo4e1RC3MmDrGUZsli0Oug0WgUOf2r96O90DmjGfx8PBEa5IeQQF8YjQZ4e7phzquj4OzkiOxNn1hOHWienAAfH+8qzwVufo6LCFxda2HuzCxkDuqLxzIzUbt2bXz11VeKzPsrVFCcNZqjOp0OWq0WI4c/CYNeDzc3N8tpP9bMUYPBAI1Gg9EjnsZP/10Dk8mERo0aVUuOJiQkwGg0Yvprk9G0SWPo9foyn9VRWZ6enmjSpMktf15YWAi9zh5b/9m3Ujnq7mRCXKgf3n//fTz//PMQEbRu3Rrt2rWDiKBPnz6V3raTJ09Co9Hg7Ix+lcrRaT2awNfdBd9+++1t73ft2rVITEyEiMBoNKJXr144ffp0mXW+++47uLo4VTpHjQYdHB1M2LlzZ6Uf361kZWWhflxUpXO0c0YziIgiVzSs6IChk5MZc2dmYc6M15CS0oQ5SqSQGr18ZPPmzdGkSTLMZjM8PDzw9NNPAyh+Q6M13jxZomXLlmjZsiVEBC4uLvjss8+seu5yaWlpaejXty/SW7eGVqtFYGAgEhMTkZCQgMTERFy4cEGROUVFRUiIrYe5mW0tBZkWE4QVz3XDlfeHo2mUP2KDPJEQ4oVmUQEY2aURYqIjFTkVKS8vD+6uLvhqRCdLQaZGVVyc/ZpGomNcMFq3bK7Aoy6+zr/JZMS5Le9ayrHkyN31fcvw24a3LbcvmzkCrs6OSEttocjs8ePHo2v7VEsxlhy5+3TRP1F0agOG9OmG2a+MRNGpDTi350vUcjEjJeXWv/xURWhoKBwdHdG8aRM4OzvjrbfeQnBwsFVm3YkKirNGczQ1NRX33XcfXFxc4OTkhAEDBgCwfo6mpqaiZ8+elgNJ07KyqjVHR44cibYZGdBqtfD397+rHJ0zZw5E5LY7L30e9ALQ4QAAIABJREFU7YXMjIRK5ejczAw4Opgsz4WST04PCQnBxIkTodFoEB4eXumDLU0bJ2FajyaVytHBLaLh6+WB/Pz8St336dOn0bt3bxhvvGqWkJCAtWvXArjxHkKzIzZ8/EqlctTbwwU+3l6KvArxySefICw0EAUn11cqR708XOHp6V7luRWJiYmBXq9Hq9QWcHBwwLhx45ijRAqp0eIsfcWU06dPIyMjA+Hh4YiJiVHsMoa3m5uXl4dJkyYhICAARqMRnp6eCAwMrNZP6bamefPmISrIu8yrIBUtl98fjnohvopexWTkiBFoExuC/HlDbirL0su5N/oh0NMVH3/8sWKzm6Yk45/P97EUZFpyDFbMfQ6Xd76PhrFhiIsKRnxUCFo1iYWft/stP5Tsrzpy5Ah0Oh2ObvvMUpxpTRtY3jx5bs+XuK9tc8REhSEmOgyutZzxySefKDK7vLS0NEyePBlvv/02srOz0bNnT0WuynM3VFCcqs7R/Px8vPTSS3/bHHVxcUF6evotf75hwwY4OZqQ/WbmbXO04KOR6JIchSGDB5X5/3fs2AGz2QxHR0csWbIEZrMZJpOpUn8377//Pmr7uOPirP63zdFr8wajRXQQXnzxxb/8+AsLCzFnzhwEBwdDRODm5obRo0cjM3MIHu2aesccbZ0Sh2YN62Ls2LF/eXZFrl27Bm9vL6xdOuOOORobXZyl48aNU2R2eWlpaXj99dexYMECbNu2jTlKpCB+gNY97Nq1a0hr0Ryt48PKXK++9JK7+Blk1A9Hi6Ypin4o39mzZ1EnNBhDUmMsb6CsaOejWVQgOrTNUPQo7ZdffglHBxO+fX/iTacKlCz5ez9E725pSIiPrfQRw8ro2uU+PHRfepmjdxUtr417EkFBgXd9hZy/ExUUJ3P0b2zq1KnQaDQ3nYZU2mOZQxAR4HnLnZD8D0dgcJt4uJgdKrwk7MWLFxEaGgo7OzssXLgQcXFx0Gg0mDBhwm23LT8/H+lpLZFWL9jyhvPyS97cQejTLBrREXVw8eLFKv1Z/Prrr2jdurXlTetGgx7zpj5+yxwtPLAcr4x8FF6eHjh58mSVZpc2btw41I+LxuVD3942R9d8MB0mk1Hx91DaIhXkKKkMi/Mel5ubi4z0VvB0dcbz9zfBjn/1x4n5T2Dn9AEY80AKvFydkZ6Wqsjld8s7cuQI6kaGo26gN97o2RQnpvXG5TkDsf/lR/BC5wbwdnVGp/ZtceXKFcVnz58/Hw4ORrw4rHuZN0xe37cMX747Dq1S4hEdFaHIB3aVdurUKYTVDsX/sXfmYVGV7R+/z+wr+7APO8i+ugAiiyzuS5K5LxSmr1qpr5qaCy5Zmryab25pZelrmrmVqJFmvhiaimSar5khpEhGSkgIiuP39wcyPxAGBjgM6pzPdZ3rcs4589znjMz3O/d5nud+Rj7fC7cuZdYzzIqC/2LpGxOhVCpw6tQpVmM/qRiBcXI6+hSj0Wggk8kaLd/74MEDTPzHBEjFQoyJ80f20pG4vnEiLr83Dulj4uDpaA0HOxsQEYYOHaozTlJSEogIM2fOxMSJE0FEiI6ObnTo0p07d9AjoTvsLU2xYEBH/PLWMJStfQnX00dh5dBIdHBUIdDPB9euXWv1Z1FDRUUFZsyYAYVCAaGAj5Tnu+P8gZV1Eo/Te5djeP8YWFla4MyZM6zFBoDKykrExcaga+dg5J/ZW09HH9zIxrb1i6FQyLFt2zZWYz+pGIGOchgZnHEaARqNBl9//TUGDegHsUj0aLVeIQb264vMzExWFz98nLt372Lz5s3oHBpcI57g8Xjo17snDh482Kaxjx07hj69e0IkEqJTUAfEhAfC2dEWKitLzJo1i7X5No9TVFSEuNgYSKUSvDh8ADavno8ta9Iwc/JoqKws4OXpgZycnDaJ/SRiBMbJ6ehTzsyZM8Hj8Zr8Pzx79iz8fL0h5PNARODz+YiK6IJPP/0U9+7dw/r160FESE1N1dnGzJkzQURITEzE559/DqFQCEtLy0arAD548AD79+9H76QEMAyj1dKITmHYunUrq73Xj7N27VqorCzB5/Hg7mSD8JAO8PF0hkwmxbhxqcjLy2uTuHfv3sXoUSMhFAoxsFcsNv5rDv6zbhHenPMPeLg5wdpa1WZDWJ9EjEBHOdqZIUT0XyIqJSINEfEeOx5IRMeI6G8iuk5ECxpoYyERFRJRGRF9S0R+jcTjjNPIePjwISorK1mZbN5cTpw4AVNT0zY1y4bIy8vDZ599ho8//hgHDx40WPwffvgBEyZMQEx0FLpGhmPY0CFtnvA9ibSTcRpSSzkdfcqpqqqCWCzGqFGj9Drfx8cHUqm0wZ7jFStWgIjw6quv6nz/9u3btZPTz58/ry3V+/HHHzcZu7KyEn/88QfKy8v1ula2OH/+PLp27QqBQKCdtM7mIpe6yM/Px+zZs9E9LgYR4Z0xoH8/bcJnTHAJCEdbk0jVxplC9U1TQUQ3iGgJEYmIyJ+IrhHRa7XOmUFEBUTkS0RiIlpK1eYq0xGPM04Og5GbmwsLC4v2vgwOA9NOxmlILeV09BlgwoQJEAgEeq0YXlJSAplMBj8/vwaPL168GESE2bNn62yjZnK6QqFAbm4uevXq1exSve2BRqPBqlWr4OjoCCKCSqXCggULjGI+W3vCJSAchiKG6pvmGCL6/bF9rxLRL7Ve5xHR5Fqv+UT0BxGN0BGHM04Og5GbmwtLy7Ypl8jx5NLOxmkILeV09BmgoqICAoEAEydO1Ov8rKwsMAyDCRMmNHi8Zh2QJUuW6Gyj9uT07du3Iz09vdmletuTnJwcxMTEgMfjQSAQoE+fPrhy5Up7X9YzCZeAcBiKhkzzX0R08LHzIh6dp6DqP8qHRNTlsXO+IqIVOuJwxslhMM6ePcslIEbIE5iAsK2lnI4+IwwfPhxisVjvp/lpaWkgIp1zEV555RUQEVauXKmzjdqT02fNmoXTp09rS/U2tajgk0J5eTmmTJkCU1NTEBE8PT2bvfI7R+NwCQiHoWjINDcR0aePnef96Dx7InKkatPs8Ng524nofR1xOOPkMBg5OTmwsrJq78vgMDBPYALCtpZyOvqMUFpaCh6P1+jQqceJioqCUCjUWYUqJSUFRIQNGzY02k7N5PSkpCSUlpbqXar3SePzzz+Hr68viAhyuRzjx49vdXlgjnbXUQ4jwqA9IJMmTcLUqVMxdepU7UqoHBxsc+bMGahUqva+DA4DcOjQIa2mTJo06UlLQNqkB4TT0WeD/v37Qy6X610s4t69e7CwsICDg4PO9wwZMgRE1GSvQO3J6SUlJXqX6n0SKSgoQHJyMkQiERiGQXh4OLKystr7sp4qniAd5TAiGjLN0dSyccs3iZsDwvEEcObMGVhbW7f3ZXAYmCewB4RtLeV09BmiqKgIDMNg2bJler/n4sWL4PP5ja4l0rdvXzAM02Tp2HPnzkEul0OhUODcuXPYvXu3XqV6n1Q0Gg2WL18OOzs7EBFsbW2xdOlSbtJ6M+F6QDjaGh5VV1xJomrTlD16zVD1k7lCIlpMRBKqrtxSQHUrt0wnonyqLhcpJaI3qbq6C1cFi6PdOX36NJeAGCHtZJyG1FJOR58xunfvDjMzs2a9Z8OGDSAirF27Vuc58fHx4PF4OHDgQKNtlZSUwMXFRTs5/dq1a80q1fukcvLkSXTt2hUMw1Sv7zFwIPLz89v7sp4KuASEo60ZQ9Vd/5pHW82/ox8d96fq2vblVF1Gcl4DbaQRURFV17f/lrh1QDieEE6dOgUbG5v2vgwOA9NOxmlILeV09BkjLy8PRIT169c3632DBg0Cj8fDhQsXGjyu0WgQEREBHo/X5ARzjUaDxMRE7eR0jUaD3r17g4gwatSop3o9odLSUkycOBFKpRJEBG9vb+zYsaO9L+uJhktAOJ41OOPkMBinTp2Cra1te18Gh4ExAuPkdPQZpEuXLs3usdVoNFCr1TA3N9c5Z0Oj0SA4OBgCgQAnT55sss3ak9M1Gg1Wrlz5VJXqbYpt27ahQ4cOICIolUpMnjwZZWVl7X1ZTxxGoKMcRgZnnBwG4/vvv+cSECPECIyT09FnkPPnz4OIsH379ma9r7CwECKRCJGRkTrP0Wg08Pb2hlAoxLlz55psc9u2beDz+XB1dUVJSQlOnz4NpVL5VJXqbYq8vDwMGDAAQqEQPB4PUVFROHXqVHtf1hODEegoh5HBGSeHwTh58iTs7Oza+zI4DIwRGCeno88oAQEBUKvVzX7f3r17QUSYN2+eznOqqqrg5uYGsViMS5cuNdlm7cnp58+fR1lZGYKCgsAwDBYsWNDsa3xSqaqqwpIlS2BtbQ0igr29PVasWPFUDzljAyPQUQ4jgzNODoNx4sQJ2Nvbt/dlcBgYIzBOTkefUbKzs0FELSqrPHHiRDAMg2PHjuk8p6KiAo6OjpBKpXpNxi4pKYGzszP4fL52zsTkyZNBROjWrdtTV6q3KY4dO4bOnTuDYRiIRCI8//zzOtdbedYxAh3lMDI44+QwGCdOnICDg0N7XwaHgTEC4+R09BnG09MTnp6eLXpvQEAApFJpowvxlZWVwcbGBgqFAoWFhU22+fjkdAB1SvXq05vytFFSUoJx48ZBLpeDiODn54e9e/e292UZFCPQUQ4jgzNODoORnZ3NJSBGiBEYJ6ejzzCHDh0CESE7O7vZ7y0tLYVcLoe3t3ej55WUlMDCwgKmpqYoLi7Wq+0ZM2aAiNCjRw9oNBpcu3YN9vb24PP52Lx5c7Ov9Wlh8+bN8PDwABHB1NQUU6dORXl5eXtfVptjBDrKYWRwxslhML777js4Ojq292VwGBgjME5OR59x1Go1AgICWvTe7OxsMAyD1NTURs8rLi6GqakpLCwsGu0xqU3N5HQ3NzeUlJTUKdU7YsSIZ3rexKVLl9CrVy8IBALweDzExsYiNze3vS+rzTACHeUwMjjj5GCViooKlJaWNrhlZmbCwcFB5/GaraKior1v46mhsc9b362tP28jME5OR59xduzYASLC+fPnW/T+JUuWgIiwc+fORs8rLCyEXC6HtbU1ioqK9Pr+ZmVlQSaTQS6X48SJEygtLcVbb70FIoKHh8czUaq3Me7du4d58+bBysoKRAS1Wo3Vq1c3K/nidJSDw/BwxsnBGhUVFZCIxTUi2eJNIhZzSYgeVFRUQCJh4fOWtO3nbQTGyemoEWBtbY0uXbq0+P0xMTEQCoUoKCho9Lz//e9/4DGt+04TEcQiIRQKxTNVqrcpDh8+jLCwMDAMA4lEgmHDhqGoqKjR93A6ysHRPnDGaWAuXbqEjz/+GBs2bMDu3bsNOnb1xx9/xIYNG/Duu+9i27Zt+Ouvv1htv0YgL41LROGkXi3aLo2rnlzJ5t/k3bt3cfbsWWRnZ+OXX37Bw4cPWWtbH+7fv4+///6b9bg1n3f+8hG4/e+UFm35y0ew/nnruk56do2T01EDc+PGDfznP//B+vXr8emnn+o9b6I1bNiwAUSE48eP48MPP8SqVavw0Ucf6TVxHKh+Um9paQl7e/tGn86zqaOFhYXaUr2NlQTWh6qqKpw/fx7fffcdLly4gAcPHrSqveby4MEDlJWV6aWjxcXFGDNmDKRSKYgIgYGByMjIaPBcTkc5ONoHzjgNRGZmJrp3j4NYLEZ013D0TIxDBy8PmJmZYcprr7WpgR44cABRXTpDKhYh3tsJ/fxdEKS2gVwqwcupL+HGjRusxKkRyMJJvVA2rX+LtsJJvVgT8ry8PEx57VWYKRUwk0lhb2YCkUCAYD9fbNy4EZWVlSzcdcPcuXMH69atQ6Cfj/YJmVIhx/jx4/RaeEwfaj7v2/9OwYNN41u03f53CmecrYfTUQNx7tw5DH7+eYhEInTuGIKeiXEIDQ6AWCzGqFEj8fPPP7dZ7LNnz0IuEUHA4yHKwwH9A1wQ6W4PkVCA5wcOwI8//thkG5cuXQKfz0ffvn11nsOmjtbMJakp1RsVFdXsUr1//vknFi9eDLWtDeRiERzMTSAXi+DiYI+33noLt2/fblZ7zeH+/fvYuXMn4qKjwDAMiAhCoQCDk5/D0aNHm0xGNBoNNmzYABcXFxARzM3NMXPmzDo9FZyOcnC0DwY3zqSkJAQFBSE4OBjR0dH44YcfUFlZiYEDB6JDhw4IDg5GUlISrly50uZxG9rfFpPYfLy9wePxYGdrjYjOocg9fgC4U4CHpfk4nvk5Avy8QUTYtGkT67G9vTuAxzCwU0oQ7miBUxPiUZmWDCdTGZzNZDCVCCEUCLB69epWx3rcOOOdVQhQmSBQZYKuDpb4bmQMyqb1x63X+mJ8sCvczeTwtzLBMB9H1hOQI0eOwEQuwyAvNQ707YzbLyWhJLUHro2Jx8ooX3ipzBEdGcF6LxAA5Obmwt7WBqEdnLBx2kD8tm0G/vh8Nr5792Wk9OoEqUSMWbNeb3WPCGecTwycjhpAR8PCwsDj8aCyskCnsCCtjuJOAX469TWiu3YBEWH58uWsxw4NDQWPYaCSi9HJwbyOjrqZy2ElE4PHYzB//vwm2/rwww9BRDo1l00ddXFx0SYhe/fubXap3p9//hnO9vaIcrLB1oRgFL+YiJLUHvjjxUR8HB+ECEcbeDg74ddff9X/w9STGzduICQoAK4OKixL7YErH09D8eez8eP7kzHjhWhYmimR/NwA3L17V6/2Lly4gMTERPD5fPD5fCQkJOD8+fOcjnJwtBMGN87asfbs2YOgoCDcu3cPBw8e1O5/7733EBsb2+ZxG9vPFhkZGZDLZThxeA9wpwB7tr2PoABfrXEW/JSNyC5hsLG2gpOTmtWFpPbv3w+5RISs1DhUpiXjsyHhCLQxRWVaMpzNZDjzjwRULBiEyRFe8HBx1lvIdfG4cdZ+gretfycEqExQNq0/JoW64R8hrtpjeRN6sJqA/PDDD+DzeHCQSxBgqUSkrTn++1wE8kbGIcBSiUBLJfwtlJAJ+GAYBn/++Wer7rs2P//8MwQCAWwtFAh2t0V0gAty1k2EJnMxvlwyCqEe9vBWW0Eo4KNfv36tivW4cSb6OSJIbYlgtSW6ednhzPxkPNg0Hvun9EJHFxWC1JYId7fB2QXPc8bJLpyOtrGOXrp0CQqFAlveX9mojro6q6FQKHD9+nVWY8ulEmwe1EmnjlamJWNd/1CYKuTIy8trss3BgweDx+M12BvKpo7KZDLtyukAmlWq948//oBELIKVRIQAi4Z1NNBSCVOREESEq1evtujzbYiSkhLI5TKYK6QIcmtYR/1dbCATCxESHNys4WAVFRWYNWsWLCwstJPWidNRDg6D065DBz766COEhITU23/mzBm4uroaPK6u/a0hvEsXrHp7gdYoP1q3AiFBftoekIS4KJzNykBMVBfY2lhj+/btrMWO6BiK5T0CUZmWjMq0ZLw/IAwhdmZa4zw9odo4784fBB97q1bXjm9s6MC6HsEItjbFzVd6w0QkQNHk3m02BGtAn9542c8ZJak9UJLaA1sTguFvodS+rtnmdvSAWCDQOTa4JfTv2xsv9gyDJnMxNJmLsWvBMAS52UKTuRgWSil+fH8yNJmL8dXbY0BErRqO9XgCUvsJ3q5JSQhSW+LP1WNhqZDgwuIX8GDTeHz7en/4O1hwxskunI7qsb81vDxuHFJGvtCkjsZ2C0fnjiGYM3s2a7HHjxuHUWHuTepoZVoyBge5YuqUKU22qdFo4OzsDFNT03oTl9nU0atXr9ZbOV2j0aBPnz4gIgwfPlznfJR58+aim5ONtvdYl44u6uwFc4kYS5cubf2H/Yg33ngDXQPccO9gWqM6enbdRBARtm3b1qI4Bw4cgL+/P6ejHBztQLsY5+jRo6FWq2Fra4uwsFCEhoZgy5YtdY5PnTq1zeI6ODggMTERwcFBeGPOHIwaNQpqtRpOTk64cOECa/HOnj0LuVyOv66dx+hhyVA72sNJ7YAL338N3CnAijffwMI504A7BYjtFo6UkYPRrVsUK7Fzc3MhE4vw++v9MCLICY4mUqhNZTg7MVFrnIE2pgiwMUVKqAuWJPijc0jrnlo2ZJzDfB3hqJRCrZTi1OhYnBwVC2cTGaZ18kCojRm6Olhi//MRrCUgv/32G4QCPn4cGq01yDXR/gi0rG+c3mZyDHKzQ++kxFbddw35+fkQCgW4uvWf2gTkg+nPIdTDHprMxbAyleHYv1KhyVyM3PWTIBULMXVq0z9WdNHY0IEPUmIR4mSF7+cOQgdbszrHTKQi7VM9zjhZoV111MHBAbGxMQgMDMCihQu1Q/vaWkfVajWGvPACAgMDkDJ2LIYNG9YmOvrXX39BJpMh57/79dLRhXOmQaWyYmWOV2lpKeRSCbJf7q6Xju4aFglzE6VevclFRUUQi8X1KmuxraMajQYJCQkgIsyulZitWrUKDMPA3d29Xqne+/fvw87KEp/1CNVLR6cGusLZ3o6Vien37t2DrbUVMt4crZeOmsjEiI+NbnE8Tkc5ONqHdntyd+fOHSgUCni4u+LDDauhUCjw/fff480330RkZGSblrPz8fGBrY01dn26Ge5urli1ciUA4JNPPkHv3r1Zi7Nq1Sr065WofWqHOwX4ZMNK9E6Kw0+nvkZ4pxA8KMnTGueGd98Cj8djZfGoNWvWoIevs/bJXGVaMj54riN6etqiMi0ZV6b2QmVaMsrnD8L0rl6IdVWBiHD//v0Wx2zsyd37PUOQ5GqNrBHRYIiwqVcoyqb1x3cjY2ApFWmHD7Q2Adm4cSOinO1QktoDQz3t4SCXwFEhQXZy1zqmeahfZ9jKxPj++a7g8XisGGd6ejp6dPGBJnMxRiUEQ60yhZO1qfZpXeaysbAylcHZxgymcgneTk2Co71ti+M1ZJyjIrygtlDAyUKBcwsH4/a/U2ClkOD47IF4sGk89kzuAR7DYNekJM442aNde0BcXV3hYG+Hnf/5EGq1IzZt2mQQHe3RowdMTUyw97NPEB0ViRdTUgCwr6NHjx6Fk9pRbx3ds+19KJUKvSaFN8Xx48dhb26it4729LSBuUKGM2fO6NV+RkYGiAhz5szR7mNTRw8cOICsrCxkZ2dj+PDhICJERETg9OnTyM3NxaeffgqZTAaxWIxPPvkEly9fxpUrV7Bnzx5YyKW49VKSXjp6MyUBCrGYlbk/X3/9NRysLVB1aKFeOvrZvKEgohYXcuF0lIOjfWg347xw4QJkMhmkUilu37iCpITuGDRoEDp16oQ7d+60aWwzMzNIxGLcvnEFi+bPwqhRI7XHpFIpa1U9li5dimGDB9QxTtwpgFQqwdIFM2FvZwNXFzVcnB0hkYihsrIEEbHyo+Gdd95BcpBrHeOsTEuGVMBH0ev96uzL/2cfKEUCEFGrPvumqrfIBHzkTegBAY/Bnan9tPvDbMy0T+9am4CsWLECA7yc6pjkupgAJKqt6uwb5eWA1wJdkT+qO4iIlcnos2bNwoR+XbRP7TSZi7F5ZjJ6dfbC/YMLERvkiv+urH5y9/17E6Ayk4PHMPD19YWfnx/8/f0REBCAgIAABAYGaif1BgcHIyQkBKGhoQgNDUVYWBg6duyI0NBQnU/uNr8Uh14BTniwaTyOzOiHaC87dHRRYXJ3f/g7WGDfqz0542SPdtPRhw8fgs/nQyKp1rMZUycjIiLCIDoaHd0NIpEQt29cwd7PPkFg4P+vFM6mjmZkZMDPp4PeOmpjrYKJUomTJ0+2OnZmZiY8ba301lETsQCOlqbIysrSO8aUKVNARDhy5AgAdnW0NZudTKy3jpak9oClRNjqmDWVrgJcbfTWUTsLJQQ8Bnw+HwKBAAKBAEKhEEKhECKRSLuJxWLtJpFIIJFIIJVKIZFIOB3l4GgHDGqcf/31l7bka3l5OczNzaFQyLHirYUQCoXw8fFpk6pEteMC1RVNJBIx3lu1DHZ2tli/fj2A6smTarWatbjvv/8+IjqH4cblU1rT3LPtfagd7euZaWy3cPxr6TzIZDJW1ovYvHkzQp1tcPWfvbUG+dmQcDiaSFHyxkDcnNVfu39ZUgBC7cwgFglb1ftS2zivT+qFX15OqjN50lEpRdm0/khwVmHXc11QNq0/zr8UDyupSHtuaxOQDRs2INrFvt4wASmfh6ujuqMktQeuj4mHUsjH6cFROPtCNzAMg6qqqhbfdw1paWkYlRRWxzg1mYshFQtxYvV4eDla1tnv52wNqUSMgwcP4sCBA8jIyMD+/fuxf/9+fPnll/jiiy+wb98+7Nu3D3v37sWePXuwe/du7Nq1C7t27cInn3zSaPUWqUiA4nfH1tl3d30qzGViXH5rGGec7NFuOgoAvr4+kEok2PBeOhQKOVxdXQ2io8mDBkEoFGDd6hUICgzAPyZMAMC+jp48eRJmZmb47eIJvXR0x+Y1EIlE+OWXX1odOzc3F0qpGD+/1lMvHe3qZAmJSIj//e9/zYoTFBQEiUSCW7dutamOajQanD59GnK5HAqFAqdPn0ZpaSlKSkowbtw4EBE6deqEPXv2wEoh087/aEpH/3wxCUqJGFu3bsXJkydx/PhxZGVl4dixYzh69CiOHDmCw4cPIzMzE4cOHUJGRga+/PJLrbbt3r0bn3/+OXbu3Ilp06bBz9VObx3t6GUPIsK8efOQnp6OFStWYPny5Vi2bBneeustLF26FIsXL8bChQuRlpaGBQsWYN68eZg7dy7mzJmDadOmcTrKwdEOGNQ4CwoK0LlzZ+3T3cjISMTFxSGqa1cwDAMPDw+EhIQgODgY4eHhbRY3NjYWzw0ciC5dOkOtVmv3JyYmsrZGA1A9xlcoFCLQ3weB/j4ICvBFYlw3nMs+VM8446Ij0CepO0aPHsVK7D///BNioRD+1iYIsDFFoI0p4t2sceYfCfjfaz0RbGumHbvc39seo0NdMXLYkFbFrG2cF1MT0NHWDP5WJgg5UIk5AAAgAElEQVRQmaC7swonRsVozTJabQU/KyUCVSbY1r8Ta3NAfv31Vwj5fBwbGF5nErqDXKJ9vbqbHyJszVGS2gNvdPREYmxMq+67hkOHDkFlboK8LdPqTEJXq0zx+2ezYCIT46dNr0KTuRg/fzQFMrEQsd26tjhe7aEDt1aPxbUVI+tMnlRbKPBg03hcTx+l3T+7TwiSw9y4yZPs0q46GhMTg/79+yEiItygOhofH48XX3wRnTt3go2NDQICAtpERx88eAB7ezt4urvopaOTXh6NoKBAVh7kaDQauDg6wM1crpeOvpngj0CfDs2OXVZWBoVCAU9PT4Po6K1bt+Dk5AQ+n4+dO3dq9+/duxcikQjm5uYwN1Hig7hAvXR0W2II7FVWrDzIuXbtGgQCPk6sflkvHVXKxLC1UbU4NqejHBztA7eAVhsz5IUXkDpmaD2jfHwr/PkUlEoFK8MGahgzcgSGBrugYsGgekMIam+/TusNE5kE2dnZrYr3pCxEGBsVBVuZGH4WCvhbKBHnYIms5yK1xtnFxgzrYvxxY2wCHM1MsHfv3lbddw0ajQZOage421kg0M0GQW62SAh1xw8bJkGTuRjb5ryAAFcbBLvbIsDVBhamcnzxxRctjlfbOPOWDUcnV2sEOlogSG2JBF9H5KZVl4l8qZs3vG3N4GljilERXnWe9HHGyQqcjrYxS998ExGdw1B1+9dGdfTuzZ/h59MBGzZsYC32v/71L4Q6WaN07sBGdbTkjYHwtbfCunXrWhTn1KlTYBhGO1ejrXVUo9EgPj6+3hyUa9euwcHBATwimIgETero7ZeSEONsi7S0tBbdd0P0SIyHnYWySR0NdLNBgJs9Fi1a1OJYnI5ycLQPnHG2MVeuXIGlpSXenD8DD0vzGzTNG5dPIdDfF2PHjmHlqV0NBQUFsLO2wsxoH51JSN603vCzt0LKmNGsLYzX3gnIqVOnIJeIsTk+qN5QrJrt95RE9HF3QGTnTqw8tavhgw8+gMrcBJc+mlJvCEHNVnVoIV7q3QmB/r6tmvzOLaD1xMDpaBtTWloKf38/jBzyHO7futKgjpb/fgn9eiUgIiKc1cn35eXl6BgciIH+zvjrjYaTkNtzBqCXjxpdu3RqVexly5Zp50OwoaPHjh1rMub06dNBROjVq5d2CG5N5SwRj4cZIe71hmLVbLdfSsKUYHeobW3xxx9/tPi+H+fEiROQSSX46u2xOnVUk7kYK//RG1YW5vj9999bHIvTUQ6O9oEzTgOQm5sLOztbRHQJw9aNq/DXtfO4f+sKfs45iplTJsDS0gKjR49qVQUqXVy8eBHODvYIVltjbb9QFEzvgz9nD0DOPxLwamQHmMmlGDtqJCuxn5QEBAC+/PJLyCUSjPZ1xn+fi6iTeGyMC0SQnRU6BgexughhDa/PnAkrcyU2TB2Asi/m1THM79+bgL6RvnB3dcZvv/3WqjiccT4xcDpqAG7cuIGQkGB08PLAu8vScPPXHFTd/hWFP5/CskWz4eKsRlRU13olZdmguLgY4R1D4WxlhiUJ/rg8pRduzRmAS6/1xII4X1jJxIiODGdl4n1MTAxrOkpE6NixY5Mrn2/duhU8Hg9ubm51/o5nzpwJMZ+HOAcr7O3VUZuI3HopCbt6hiHBxQ6Otja4ePFiq+/7cbZs2QKZVIIlKQm4uXNWHR29vHkqJvTrAjPT1hcb4HSUg6N94IzTQNy+fRsrV66El5en1hj4fD6eT07GkSNHWO35eJyysjJs2LABgT4dtLGFAgGGDX4eWVlZrMV+khIQAPjpp5+Q+mIKZBIxHM1N4WVtCVOpBB7OTkhPT0d5eTkLd90wW7duRYCvN8yUcvQO90H/SB8EezlBIZdh/PhxrDwt5IzziYHTUQNRWVmJLVu2ICI8vE71pLi4WHz22Wdt8hCnhqqqKnz++efo3i2qTuzoyOprWb16NStxbt26xZqOJiQkQKWqLrHerVs35Ofn64ybm5sLuVwOpVJZZx2XQ4cOQSISQcznwVIuhZe1JayUclhbmGPO7Nmt6n1oim+++QZx0VEQi4To0cUXL8SFoFuQB0QiIV54flCzJ/s/zq1btxAUFMTpKAdHO8AZp4F5+PAhbt++jcLCQr0Wq2Kbu3fv4tatW6wOO6rhSUtAaigpKcGxY8dw6NAh5OTksLLOij48fPgQx48fx9ixY+Hs7IwtW7awel9cAvLEwOloO1BaWorr16+jrKzM4LHv3buHP//8E/fu3QMAREREQKVSsdI2mzpKRHBzc8OiRYtgamoKhmGQlJSEoqKiBmPrmpxeXl6u/aE+bNgwZGdna+/dEPz0009Ys2YNli9fjo0bN6KwsLDVbW7duhVisRgymYzTUQ6OdoAzTg7WqBHIS+MSUTipV4u2S+MS21zIDc327dsRGRnJertcAvLEwOmokXPhwgUQEbZu3drqttjU0aNHj8LCwgJ8Ph8rV67EsmXLIJfLwTAMBg4ciJKSknrxdU1OB4BXX30VRISuXbsaNAFhk4qKCu39de/eHTdv3uR0lIOjHeCMk4M1KioqIBGL6wxPaMkmEYvbdAVnQ/Ppp5+2aQKSv3wEbv87pUVb/vIRnHG2Hk5HORAUFAQHB4dWt8O2jlZVVSE5ORlE1Wt8lJSUYO7cuZBIJODxeBg+fHiDvUgNTU4HgH379kEkEsHCwqLJuSVPGocOHYJcLodIJMKWLVsAAL169eJ0lIOjHeCMk4NVKioqUFpa2uC2Z88eeHh46Dxesz1LyQfQdglIRUUFJBIWfqhI2jbhMwLj5HSUAydPngQR4csvv2x1WzU6WlJSAhcXFyiVShQVFaG0tBQnTpyoHqJVWFhHN0tKSmBjYwMnJ6cGdfTLL7/Urvy9c+dOVFVVYcqUKRCJRBAIBBg3bly9Xg1dk9NrSvXy+Xx8+OGHrb7ftkaj0WDIkCEgIoSEhGgLFQwbNgxEBJGw9au4czrKwfH/LCSiQiIqI6JvicivgXM44+QwGF999RW8vb3b+zIMTlslIEDjCZ++W1snfE+5cXI6yqE3Xl5ecHd3Z7XN4uJiiMVidOzYEQBw7tw5EFGDvRY5OTkgIixcuLDBtsrKyhAVVT2Jvk+fPrh37x4qKiqQmpoKgUAAkUiEqVOn1pkjqGtyukajQd++fbXzQgw1t665nD59GpaWluDz+UhPT9fur1n5fe3atfV0dODAgTAxMdG+JiLs2LGD01EODj2YQUQFRORLRGIiWkpE14lI9th5nHFyGAxjTkC6dm35iudPO0+xcXI6ytEsMjMzQUTIyspitd1Dhw6BiDBjxgxtAqKrit+IESPA5/N1TjQHgA0bNkAgEMDU1BTHjx8HUJ2cDBs2DDweD1KpFPPmzdMmFbompwPA6tWrtb0kxcXFLN0xO7zyyitgGAZubm4oKCjQ7p86dSqICMuXL2/wfWZmZkhOTta+JiIcOHCgza+3MZ5iHeUwMvKIaHKt13wi+oOIRjx2HmecHAbjq6++go+PT3tfhsHhEpCn1jg5HeVoNk5OTvD392e93WnTpmmf2FMjCUhVVRVMTU0RFBTUaHtFRUXw9vYGEWH8+PF1ko0BAwaAYRgoFArtj3SNRoPu3buDiDB37tw6beXk5ECpVEIikeDIkSMs3G3ruHLlCtRqNRiGwYwZM+ocmzdvHogICxYsaPC9NQUFTp8+rd1HRDh06FBbXnKTPMU6ymFEmBDRQyLq8tj+r4hoRQPncsbJYRAOHTpklAnItm3buATk6TNOTkc5WsTOnTtBRMjNzWW97dDQUIhEIhBRo0N+anpMNm7c2GSbc+fOBcMwcHBwwOXLl7X7i4qKkJiYCIZhYGZmhvXr1wP4/0To8cnp5eXlCAkJAcMw9RIUQ7J48WLweDxYW1vj3LlzdY7VrDQ/bdo0ne8fMWIEFApFnX1EhMOHD7fJ9erLU6qjHEaGI1UbZ4fH9m8novcf28cZJ4fB4BIQ4+QpNU5ORzlajI2NDTp16sR6u+Xl5dp1K5paSDUpKQlisVivdVIuXLgAW1tb8Hg8LF68uM6x/Px87bwRlUqFrVu3YsuWLeDxeHB3d6/3d19TqjcyMtKgpXpv3rwJPz8/EBHGjBlTb07KmjVrtL09jWFhYYH+/fvX2UdE7d6z85TqKIeR0ewnd5MmTcLUqVMxderUdu9m5Hh2OXjwIHx9fdv7MgyOMSYghw4d0mrKpEmTnkbj5HSUo8Vs3LgRRIQrV66w3vaWLVtARBg+fHij55WXl0MikSAuLk6vdjUaDcaOHQsigr+/f735HBcvXkRYWBiICA4ODlixYkWDk9OBuqV6L1682LwbbAEbN26EUCiEiYkJjh49Wu/45s2b9frMLl++DCLSzoupgYhw7NgxNi9ZL54BHeUwQhoau3yTuLHLHO2IMScgUVFR7X0Z7cZT/OSO01GOFmNubo7Y2FjW262pdEXU9MKHH3/8MYgI+/bt07v9o0ePQqlUQigUNlhiNycnB/7+/iAiqNVqqFQq8Pl8fP7553XOKywsbPNSvbWrevXu3bvBHpedO3dqF15sipSUFMhksnr7qYGkxNA8xTrKYWRMJ6J8qi4ZKSWiN4noGnHVWzjakQMHDsDPz6+9L8Pg/Oc//+ESkKfTODkd5WgxK1asAMMwKCwsZLXd06dPg4iQkJAAgUDQZC9LWFgYlEplndK6TXHv3j0kJSWBiBAXF9fgfJOsrCx4enqCiCCVShucnK7RaNC/f/82KdW7b9++OuuaNERGRgYYhkFCQoJebVpbW6Nnz5719hMRsrOzW3W9reUp1lEOIySNiIqI6G/i6tdzPAFwCYhx8pQbZxpxOsrRAjQaDRQKBfr06cNquzUJSEVFBaytrWFtbd1oclFcXAyBQIDBgwc3O9a2bdsgFoshl8uRmZnZ4DkHDhyAk5OTtlcmKiqqXqLBZqneqqoqDBgwAESELl266PzeHT16FDweDxEREXq1W1BQ0OBkc41GAyLCqVOnWnXdreUp11EOjnpwxslhMDIyMrgExAgxAuPkdJSjQebOnQsej4eSkhLW2jx16hSICFVVVcjLy4NAIEBiYmKj76mp/nTy5Mlmx7t16xZCQkK0cyh09WLs3LkTpqamICKIxWLk5OTUOZ6bmwsTExNIJJIWV5Q6fvw4zMzMIBAIsGbNGp3nnTx5EgKBAEFBQXr3ukyYMAESiaTe/qqqqnpledsDI9BRDiODM04Og5GRkdEm9fGfdLgE5Jk3Tk5HORpEo9FAIpFg6NChrLVZk4DU/LDeunVro4vq1eDh4QFra+sWD4NatmwZeDweVCpVvfK2tUlLS9P2hnTs2BHXrl3THisvL0doaCiICHPmzNE7tkajQWpqKogI3t7ejQ5rO3/+PIRCITp06NCse7Wzs0N8fHy9/ffu3WuzssrNwQh0lMPI4IyTw2AYcwLSrVu39r6MdsMIjJPTUQ6dvPLKK+Dz+U2WzdWXkydP1klAAGD06NFgGKbRp/RXrlwBwzB45ZVXWhw7Ly8Pzs7ODS7wV5tbt27BzMxMm4j07NkTN2/e1B6fMmWK3qV6L168CDs7O/B4PJ2LB9Zw+fJliMViuLi4NKsEcGFhIYgIGRkZ9Y6Vl5eDiBpNugyBEegoh5HBGSeHwdi/fz8CAgLa+zJYp6KiAqWlpTq3999/HxEREY2eU1pa2ujCYk8zRmCcnI5y6OTevXsQCoVITU1lpb2aBKQ2Go0GHh4eUCqVjSY6U6ZMAcMwdRYcbAmTJ08GwzDw8PCo08Px+DXFxsaCiCAQCMDj8TBo0CDt96SmVK+5ubm2VO/jWvrPf/4TRAQ7OzucOXOmUf28cOECpFIp7Ozsmq2lr776KsRicYPHysrKQET1Sg0bGiPQUQ4jgzNODoPxLCYgFRUVkIjF2id9rdkkYvEzmYQYgXFyOsrRKGPGjIFIJGJlYb7s7Ox6CQhQPdlcIpEgNDRU53s1Gg1sbW3h5ubW6us4deoUzM3NwefzsXr1ap3nTZ06FUQEd3d3iMVi8Pl8jBo1CuXl5SgsLISjoyP4fD7WrVvHipZKxKJm66ijoyOio6MbPFZSUgIiMsh6Jo1hBDrKYWQYnXFqNBocPHgQ8+fPx8yZM/HOO+8gPz/fYLEPHTqEpUuXYsGCBVi/fn2rK4I0h0uXLmHr1q344IMPsH//flRWVhosdlFREdLS0uDs7IwTJ06wWo5Rn9gHDhzAnj17kJ2dzWrsGlO4MCwGBaPjW7xdGBYDNr+LDx8+xNWrV/Hjjz+ioKAADx8+ZKXdlmAExml0OgpU/wBdtGgRZsyYgSVLlhh0jPzp06exfPlyzJ8/HytXrsSvv/5qsNg3btzA9u3bsWnTJuzatUuvCeZlZWXg8/mYNm1aq2KXlpbi3XffBRHh6NGj9X5oHz58GESEqVOn6myjZg7J0qVLmxX7zp07yMzMxO7du/HNN9+goqICVVVVGDRoEIgInTt31vkdqL1y+vjx4yEUCiEQCDBhwgRUVFRoS/VSK7W0JTpaXFwMIqq3jkkNFy5c0FbHak4pY7YxAh3lMDKMxjgfPnyIje+/Dzc3V9jaWGPsiMGYmDoKvZO6QyQSoW+fPrh06VKbxV6/fj3cXZ1hY2mGYUmdMLZPOKKCvSAWizBqxHDWa8XX5tChQ+geGw2xSIiuwV6I7+wLV0drqKwsMGvW6/jrr7/aLPb333+PwQMHQCQQwEUph6tEBDOpBK4O9li2bBlr46J1xX5+wAAI+Xw4y+XwUihgKhbDydYWb7/9Niuxa0yhYHQ8SlJ7tHgrGB3PSgJSWlqKVatWwcvFGXweD0qJGDyGgZ+nB9auXYu///671ffckmuiZ9s4jUZHgWo96dgxDEqlAsMGD8CkcaPxwqC+kMlkiAgPx7fffttmsTMyMtApLAQKuRSD4kKQ0jccPSP9IRIJ0btnEn744Yc2i52bm4vByYMgEgnR0dcN8V384O+hhkwqQepLL+Lq1auNvn/QoEGQSqUtegBy5coVTBg3DgqJBA4KGZxFAtjIZbA0McHM6dPx+++/a8+dOXMmiAgHDhzQ2d7QoUMhEAhQVFTUZOxff/0VE8aNg1wshr1UCi+FAtYSCcwVCsz45z9RVFRUZ02O3bt3N9hOTk4OZDIZTExMkJubi5SUFPD5fIjFYkyfPh0LFixotZa2REdnzJgBoVBY5//l/v372Lp1K8JDQ8AwDMQ8BkI+Dw7WKixatKjOfBZDYQQ6ymFkGNQ4KysrMXDgQHTo0AHBwcFISkqqt4jSkSNHwOfz8e6777Ia19PTE3w+Hy5OjkiMi8Kv57KAOwWIiQqHk6M9rCwtwOfzMX36dNbiAtVDdNzcXCHg8+Bsa46Ejp64vH02NFnp0GSl4x/PRUIpE0MoEOhdr1xfKisr4e/vDx7DwM7SBLEh7vhlxxxostLR2dcJHg5WUEjFEIvFYBgG58+fZzV2WFgYGCJYCPgIlYvwlbc9LgY5YYu7NZxFAkj4PEglYqSlpbEW9/HYpkTwJcL7RPiCCMuI4EAEMcNAKpFg7969rYrVUALS3cES/hZKBFgqEWlrjv8+F4GS1B7IGRyFztZm8DCVIUxlipPJXVlNQPLy8uDh7IRgK3Os9HHEpRhfXI3zx8VoXyz3doCvpSn8O3jh+vXrrbrn5mIExmk0OhoaGgqGYeBgZ4vuMZF1dNRZ7QB7OxswDIOUlBTW4tbEDgoKqo6tMkX3MI86Ojp1SDTMlTLweEyjQ5BaGjsiIgIMw0BlpkBUoKtWR7v4OqGDkzXMlTLw+fxGdbS4uBgMw2DhwoXNit2tWzfwGAYmAh4CZf+vo596WMNdLICCz4NAwK8zKbxTp04Qi8U6fyhXVVXBxMSk0c+qsrIS0dHR4DEMFETwqqWjK4jgTAQZw0AoEGDz5s0oKytDZGQkiAj9+/dvsLeguLgYarUaAoEAu3fvRmlpKYYMGQKGYbQ9IDVaaigddXZ2ruO9paWliO0aCRdTJeZ72OJclA+uxvnjSqwf3g9wQjcbS1hbmNcrM9zWGIGOchgZBjfOgwcPal+/9957iI2NrfMF69y5M/r378+qcX7wwQcwNTXBL7nHgDsFeG/FIsRFRwB3ChDbLRxf7PgAuFOApQtmws7OFnfu3GEt9qpVq2BhqkDezjegyUrHv6c+h9gQd2iy0rHy1QEYFBOIe0eXY/Lz0fBwc8H9+/dZi71jxw7IJGJ8v3FKvdg1272jy9E10A1SqQQPHjxgLXZGRgbEAgE+cLPGxSAnzHUwRxeFGBeDnOAtEWKdqwq5AWpEmZtAKBTip59+Yi32gQMHIOLzseiRWY4nQsCjf1sRYQkRdhEhSCiESCTC3bt3WxyroQSk9r+3JgTD30KJktQeiLa3wLqYAJSk9sDH8UEIVZmwloDcunULUokY5kI+fBUSdDaVIaOTO67G+WOsoyUcJUIwRIi3NoOflyerf+NNYQTGaRQ6+t1330EsFuPwF/9pVEf3bd8EuVzO6nf666+/hlgswn/XTNapo/e/fQcbZg6GiVLBao9yTk4OxGIRtqWN1Kmjmqx0DIkPgUAgwB9//KGzraSkJJiYmOgd+6effoJcIsE8RwudOvpToBojVCbg8XjadT4qKipgamoKV1dXnT0uGRkZICJ8+OGHDR6/ePEiZGIxXm5ER/cRIYlhwOfxcOPGDQDA2rVrIRAIYGZm1uDq4bUnp8+ePVu74rq5uXkdLTWEjtbM79i6dSsA4MGDB7AwM4NcwIe3XKxTR1McLWFhYmLQoX9GoKMcRka7Dh04c+YMXF1dta9HjRqFL774AmPHjmXNOB8+fAh/fz98sGY5cKcAuFOAM8f2w9VFrTXOfds3AXcK8LA0H6HBAVi3bh0rsR88eABntQN2LBqtNalTm6bA1c4Cmqx0OFqb4udPq5/i3f/2HTjbq7Br1y5WYj98+BBBAX5Y88/kBmPX3pI6d4CJQob9+/ezEhsAwkNDMMPODBeDnHAxyAk7PW3hKOLjYpATfKVCvO1kiYtBTtjvZQsew2DHjh2sxY4IDcWYR0b5BRH+RQQbImwlgrDW/p1E4DMM5s2b1+JYTQ3BWhPtj0BLJX4ZEQelUIBbLyVpj9lIRch9oRsrCciC+fPR2coMv8b64WqcPzb4O8FHIcHVOH98FuKKk5EdoJYI8WWYO4KszLBq1aoW33NzMQLjfOZ1FACGDx+GVyekNKmjuFOAlJEvYML48azF7tu7J+aOSWxSRzVZ6egTFdCq7/TjjB45AhOe69qkjvbs4g1PtTWWLFmis62a1bYbm7Rdm/GpqRigalpHD3vbQchjMH/+fO17c3NzwePxMGzYMJ3tx8fHQyKRoKysrN6xCS+/jDihsEkd3UcECcNg1KhR2vcWFhaiQ4cOICJMmDChwSQoOTkZRASGYbBp06ZGtbStdHTu3LkQCATa69uzZw/slHJc6ObTqI4e6OSBZAdLjB05Uq84bGAEOsphZLSrccbHx8Pc3AwuLs4Y//LLGDt2LACwapxZWVkwNzdD+e+XtOY4elgypk56SWucPh08EOjvg6HJ/fH2wlkICGBnrYr9+/fD3toClUeXa01qVM+OmPJCNP766k0IBXwsn9gX4X7OCPdzxtCEEMTHxbASOzs7GyYKGe5kLq0Xu7ZpFuyaB7lUhJkj4tCrR+Or6epLbm4upEIhTvo7ao1zgLkcY6yUuBjkhN1etrAX8mEn5EPKYxBnKkO/nj1ZiX3u3DlIBAJsq2WQcUQY8OjfNkR4/dG/04nAI4KPl1eL4+kyzaGe9nCQS+CokCA7uSu+HRgBL1N5nXPCVKb4snenVicg9+/fh52VJT4IcMbVOH9cjfPHO94O8HtknDWb4yPjXOXrCE9nJ4NNTDcC42xXHe3Xrx9sbGzg4OCAAf37Y8yYMQDY1dHi4mKIxWJcyvlGLx3d++lGKBQKVnra8vPzIRQKULBrnl46+vrI7rC1VrHSm1x93yKc/2SGXjq6+Y1hcHK0b7Q3uWvXrrC0tGwydmlpKeRiMXZ62uqlo8MtFXB1sK/zY3/VqlUgImzevLnBGGVlZZBIJEhISKiz/86dO5CLxUjXU0f5RDBTKOrd95w5c8AwDBwdHbXDBDUaDYYPHw4igqOjI3g8Hjw9PXHt2rV6WtrWOuru7o6OHTtqXydEd8N0d1u9dPRgJw9IRELcunVLr1itxQh0lMPIaDfjnD17Nng8Ht5b+TY+XL8aPB4PR48eBcCucb777rsY0KeH1jTfnD8DkV3CUPHHz8CdAly/9L322HsrFsHLwxVExEq1iwULFmBM7y5ak1oyrhci/V1QfvhtFGcsBsMwWDyuFzRZ6cjb+QZUZgrIZVIW7hp466238Hx8aIOxaxvnotSeeKF7MH7YPJ212O+88w4SrM21pvmarSlCZCLkBqhxMcgJvc1kSH/05C7T2x5WAh4kQiErsdPT0xEhlWpNcyQRvInw+aPXq4kQSgT3R4bagQgCHq/F8ZrqAVkXE4BEtRW+HRgBz8eMM1RlwkoCcvLkSVjKpLgS64dBtmawFwthLxbiq84eDRrnpRhfSIVCg5WVNALjbDcdXbJkCcRiMaa9+g/s3PYhhEIh1qxZA4BdHT169ChcnJ301lFfb09YsDROfteuXQjxdtFbR+2tTMAwDCvVDQ8cOIAOLvZ66+i9o8shEPDrzcmpzaVLl0BE+PjjjxuN/dVXX8HJRKG3jtoK+RDwmHqxe/XqBT6fr3Ptjw8//LDeInxff/017Jqho4FE4OlYX+T8+fOwsbEBj8fD5MmToVKpwOPx8NZbbwGormgmk8mgVCp1amlb6GhZWZm29wUA/v77bxARvovw0ktHr8b5w19lju3btzcZiw2MQEc5jIx2Mc533nkHvr6+sLAwx8O7xcjY8ymEQiFUKhVcXFygUChgaWmJuXPntjrW8uXL8cKgfsCdAryzZA46hQbhTuFPWoKMc+8AACAASURBVLN8fKupQ85GhaRZs2ZhwsDqrvvlE/uik48af331pta0TOQS/PrZG3W68AUCfqvjAtVdyy/2C9cZu2Zzs7fEVyvHI2/nG2AYhpWn4gsWLMAg6+phA9PtzBAgFeH0o96QbD8HiBjSmurFICfEKCUgIlbK4y5cuBAJIhG+IEIKETyJsL3WU7zHN/tqQW9xwqlPFSwpn9emQ7AOHjwIT0uzOiaZ7uOAOAuFTuO0VcobHJ/dFhiBcbabjnbs2BFEhOtXziNjz6eQSaUwNTVlXUe/+uordPDy0F9HJWLY2liz8je2bds2RAZ56q2jz8cFQSDgs1LVcOfOnejk5663jmqy0mGikOHHH39stN2QkBDY29s3es6uXbvgb6m/jvYwlUEqENQrh1yz9odKpdKpc6GhoTAxMdEe37NnDzwVCr11VE0EuVCoM+HUaDTw9fUFEUEoFOLMmTN1jhcXF8PBwaFRLWVbRxcvXgw+n6+955rV0C/H+Omto3EOKqxfv77JWGxgBDrKYWQY3DjT09MRFhaG69evw9HREWNGDsX0KZOgUCiQl5cHgN0nd1u2bEFIkD/Sl85FWEgA/rp2XmuSD0rycPPXHO3rz7esg52tNZRKJSs/xFeuXImELr5YMak/wjo44vbBJXVM6+UBEXhvWvUcjeKMxbA2V8DG2oqFu66O3SPCX2dsTVY6MleOh7OtOTRZ6fjvmsmwtDBjLXaMyhwz7c3gJxXh+1pDsS4EqmHG5+Ej9+rJ6d/5OcBKwINMxyq0zeXdd99FJ6kULxLBgwifPmaUH9f69yQiOBG1KvbjCUj+6O743/DYOpMnHeQSlKT2QDc7C6yN9kdJag9sZnESelZWFmwUcuTF+tUxSgmPwQ+PKrjUNs4rsX5QiEVN/khiCyMwznbT0b/++gsxMdFIjI/F4gWzoVAokJmZCYBdHf3xxx8hl8vxVtrreumok6M9hEKhVtNbwzfffAM7lTmWT+yrl446qkxBRKwMjfnmm2/gYGOpM/bjOnr74BIwDNNkpbnTp0+DiLBv3z6d5xw5cgR2Cjlm2Omno7ZCPngM02A54Pz8fAgEAnTv3r3BWDdv3oRAINDOFzl69ChUEoneOur+qCe5oUnZ+fn5cHFxAcMwSE5OhkKhgEgkqtcDVDMhvGB0vEF0tKaKXA01OnWmq7deOno1zh9hNpbYsmVLk7HYwAh0lMPIMKhxXr9+HQzDwMPDAyEhIfDx8YFKpcLw4cPw/fffa89LSUlhzThLS0shlUqr47q5ICTID8GBvgjvFILy3y+hY0ggAv19EBTgi4S4KAzok4R/TJjASuzr169DKBSAYQgejlYI8XRAsKc9wv2ctWbZL8oP/m62CHCzQ7CXGq+/PpOV2FevXoVAwNcZW5OVjmGJIUh7sQc0Wel4qV8Exo17iZXYly9fhpDHA0MEJ5EAPlIhvCVCBMlEuBjkhA/crOEnFcFbIoSHRIiOSilGvPACK7GvXLkCwaPYdkRwI4Lro6FWXxBhOFWX4XUgQhciJPF4GJqc3OJ4jycgPw6NRpjKFH4WCvhbKBHnYIms5yJRktoDpwdHodOj8pGhKhNks1SGt7y8HKZyGd73V2tNcoO/E+zFwgaf3H0Y6Aw7K0tWK641hhEYZ7vqaEBAAGxtbTF48PN11mBgU0cfPnwIb+8OeuvojNfGo2tkJCuxq6qqYGttpbeO9on0ZW0+W2VlJSwtzPTW0XdfG4jwzmF6te3t7d3oiuQVFRUwlcv01tHepjL4e3rofHi2Y8cOEJF26NPjLF26FESEU6dOoaKiAmZyud46+iIRvF1d68VetmwZ+Hw+VCqVtmemoqICiYmJICLEx8drF1OsraVtraMVFRVgGEY7XLGGYD9fzHCz1ktHs8K9IOTz8dtvvzUaiy2MQEc5jAyjWEBrwvjx6NszAZq/ruocMoA7Bbh4+jCkUimrT4aTnxuAlL5d8OC/K+o9Oau95Xw4DUKhoMnFrJpD3949MWVITKNxNVnpyP98LmRSCauLeCXGxOBlG9M6QwQa2r7zc4BSLGJ1OFBSbCySGUbncIGabSsRFEIhjh8/3uJYT8pChCljx8JMKIC3XAIfhQRR5nIcfPSUbri9OezEAggZBiqRAFI+D/NZrBLUFEZgnEaho+vWrYO3lwfKblxsVEdvF/wIF2e1trQpG6SlpSEiwB0V3yxrVMuKvkiDrZU5vvjiC9Ziz549G/GdvFF17J1GY5d9/RY8nWzxySef6NXukSNHtCua62L6tGmIszTFT4HqRnX0hwA1vM2UTVZwTElJAcMw2nK9j+Pm5gYbGxtoNBrMnD4dnUQi7GtCR3cTwUMqxdq1a7XtFBcXIzAwEESE4cOHNzi8duvWrRCJRFAoFDh8+DArWqqvji5fvhw8Hq/ekLR33nkHEn51Cd6mdNRUwMfAPr0bjcMmRqCjHEaGURhncXExPDzc8eKoIbh/60qDpnnh+6+hdnTAnNmzWY2dl5cHG2srzBqVoDMJOfvRP2GnMm+0fGNLuHDhAkxNlFg95Tmdpvnb7vnwc3fAyy+nshr7zJkzkEvEeFttqdM0s/0cEGSuxPMDBrBakSknJwdysRivNWKa24jgI5FgUL9+rYr9pCQg+fn5sDBRYr6nXZ2ndbW3vFg/THW1ga2VZZ2Vk9saIzBOo9DR+/fvIyE+HjFR4bhd8GODOnrz1xx07hiCAf37s7quUFlZGUKCAvBcbDD+fmwCeM1WuHcBQjo4Y+gLg1mZT1bDn3/+CQ83F4wf2BX3v204CbmTuRQ9I/wQHRWJe/fu6d22s7MzfH19dR4vKiqCg7U1Um3NdCYhPwSo0cfKFEE+PnrNXfTy8oJcLm+w9O7ly5fBMAymTJmC33//HY7W1hjE4+lMQnYTIU4oRECHDvj7778BAJs3b4ZIJIJSqcThw4cbvZZbt24hKCgIRASFQmGwBMTPzw/+/vWrXd69exe+nh4Y4qjClceGtNbe1vqpIROLcPr06SY/b7YwAh3lMDKMwjgB4Nq1awgODoK9nS0WzpmGs1kZuJTzDQ7t/gTPD+wDkUiEeXPntklp0osXL8LV2QnervZY+eoAXPzP68jb+Qb+j73zDm+qbP/4fbJX03TvTQdtaQulpVD2KiCULSBQKHtWlixRlCGgICgqQ0D4IXtI5QWRpchQGSIvyBBkbymrQClt8v39kTZv90hOkmqez3U9l8k5J+d+nmC/39zPecb38weja7NYSCRiTJ8+3Syxjxw5AidHDZrWDsOmGX3wfO9s5Bz4CBfWTcL4nk3haG+H1L59eFn1qyi7d++GnVyOJBcNVga5Ggz0SIQXxnpq4KlSILl1a5M2AiyNvXv3wk4uR6JUiulEBgP9mgh9ieAmk6FtUpLJsatKAgIAP//8MxzVdujg5Yz02KBCicemmgFo5eEENydHnDp1yqQ2VxYbME6b0dHMzEwkt2sHtdoOaUNScWTPVlw48QMOfr8ZQ/r3glKpRLdurxuG1fDJ33//jXoJ8fBwccCUPi3w+8pxuLJ5Cg4vTsOQjvWhUsqR0qtnpRKAinLlyhWEhVRDVLAvFr/VFRk7ZyD3p7m4nf4e5gxtC38vVzRqkIhHjx5V6r5bt24FEZW5Wti5c+fg4+6GOEd7LPBzxqk8HT1RwxszfBxRXWOH6OrVcefOnQrFzMjIgFwuR1RUVInnR44cCY7Tr6Z1/vx5+Li5IVImw/i8hCN/D6U0IgTJ5agRFobbt2/j+fPnaNSoEYgILVu2rNC/w4kTJxAZGWnYBZ0skIBkZ2dDIBBg3rx5JZ6/du0agv39UM/VASuj/Ax7K11pEom98cHo4+sKpVTK61O2imADOsqwMWzGOAH9xoDbt29H61at4ODgAJlMBh8fb7w1blyZyybyQVZWFlavXo26deIglUrAcRzcXV0wduwYXLx40ayx79+/jw8++AB+Pl4GkRcKhejcsT327dtn1v0grly5gnFjxsDBTgWpUAiFUAABx6FhQh1s2LCB117Soly9ehXjx42Dg0oFmUgEtUQCAcehQXw8b7GrUgIC6J+4DR00CCq5DP4aNWJcneBjbwd7pQJpI0bgxo0bJre5stiAcdqUjup0Ohw5cgS9evWEi4szpFIpXF1d0C81tdjqRnyj1Wqxc+dOtG3TCgq5fvU8jb0affuk4OjRo2aN/ezZMyxduhTRNSIMG+gRERo3rI+NGzcaPafK3d0dsbFlzxvJyMjArFmz4OfhDrFAALmAg0ggQERwNSxatKjSqzb+8MMP4DgOI0eOLHZOq9XC1dUVwcHBAICHDx9izpw58HXXx7aXSCASCFA9MBBffPEFnj17hh07dkChUEAqlVZoWdqzZ88iNjYWRAQvLy9s27YNJ0+etEgC8umnn4LjuDKT5IyMDEx5+224OjrAVSlHkEKCYEcNpGIRenZ73eKdOIBN6CjDxrAp46xK8DlEoDIx7927h+vXrxsel1uKrKwsfPLJJwgPD8etW7csGvvly5c4d+4cfv/9d9y+fZvXe1e1BCSfp0+fYteuXdi4cSO+//57i/97F8QGjJPpqJWwho7qdDo8ePAA165dw+PHj02+X/4+HKXt01GQ3NxcrFy5EkSEy5cvm9R5NGXKFBARtm/fXuzckSNHQESYM2eO4ZhWq8XFixfx22+/GWLn5OSgU6dOICLUrl273CdAV69eRWJiIogILi4uheYJWWoOSHR0NMLCwir0HWVnZ+PTTz817JNy//79Cn3OHNiAjjJsDGacDIuxefPmQrvO/hvIN4UzPRrhWkozo8uZHo14TUCqEjZgnExHGSbh6OiIBg0aVOja3bt3g4h4iZuQkACJRFLi8K2uXbtCJBLh77//LvGzv/zyCxwcHCAUCrFgwYIy49y5cwfNmzcHx3HQaDQl7p3Bh5aWp6M5OTkQCAT44IMPyv1u8jl48CBv37cp2ICOMmwMZpwMi7F582bExcVZuxq8kpWVZdi80tQik0rNMnbe2tiAcTIdZZjE/PnzwXFchYZI8pmAZGVlQaPRwM/Pr9jTpJycHKhUqmKdRlqtFkOGDAERITg4uMw6Z2RkIDk5GRzHQaVSYe7cuWXWhQ8tFXBcqX+LS5YsAcdxlRqy9sMPP7AEhMEwA8w4GRbj35iAAHrjfPLkSall2rRp6NSpU5nXPHny5F+ZfAA2YZxMRxkmodVqYWdnh1atWpV77a5du3j9QXz69GkIBAJ06dKl2Ln09HQQkWHTwPPnz8PLywscx2FSGStGZmZmonv37hAIBJDL5Zg6dWqFhsuVpKVr166FTCaDUCiEUCjEkydPcPnyZXh6ekIoFOLrr782XHv06FGIxWKEhoaWGC82NhbVqlWrxLfzv+WSrY0N6CjDxmDGybAYmzZtQnx8vLWrYXFmz55t2GHYFrEB42Q6yjCZqVOnguO4cndw5zsBAYCFCxeCiPDll18WO9ekSRPIZDJMmjQJAoEAHh4eOHPmTIn3ycrKQv/+/SESiSCRSDBu3DheVljMzMyEl5d+EZX27dsjJycHOTk5hlW3pk6darj26NGjEAqFiI2NLZSEaLVaCIXCQtdWBD6fOJmCDegow8ZgxsmwGLaagMycORO9evWydjWshg0YJ9NRhslotVrIZLISn0QUZOfOnWb5QZycnAyhUIjz588XOn7p0iXD8Kb+/fuX+GQhJycHI0eOhFgshkgkwpAhQ3hfDnn8+PGG+zs4OBg2U0xLSwMRoW3btoa67d27FwKBAM2aNTN8ftWqVUbNszPX911ZbEBHGTYGM06Gxdi4cSPq1Klj7WpYnOnTpyMlJcXa1bAaNmCcTEcZvDBq1CgIhcISNwnMx1w/iLVaLby8vODk5GRIHr744guIRCLI5XIQEXbt2lXsM5MmTTIMkerdu3ellwSuKGPGjIFSqcSNGzcQHBwMjuMwbNgwAPrNDwUCAYKDgw3f3ebNm8FxHDp37gxAP+He39+/0nF37NjBEhAGwwww42RYDFtNQN5//3307dvX2tWwGjZgnExHGbyQnZ0NsViM1NTUUq8x5w/iGzduQCwWIzExEQkJCSAiJCcnIycnB9HR0bC3t0dOTg60Wi0++OADKJVKCAQCdOrUqdKbMFaWtLQ0qFQqw/uJEyeC4zj4+vri0qVLOHbsGORyOdRqNc6ePQsAWLZsGYgI/fr1g1gsxsSJEysdN38ejLWxAR1lWJEoItpJRLeJSEdETUu4RkNEa4joERE9JKLVRGRf5JouRHSOiJ4T0R9E1LGMmMw4GRZjw4YNSEhIsHY1LM67776L/v37W7saVsPCxsl0lPGPJjU1FWKxuNQhTObukR83bhyICCKRCNu2bTMcv3PnDoRCIWrXrg21Wg2O49CqVSvcu3fPbHUpyLBhw6BWqwsdO336NFxdXSEQCDBr1iz8/fff8PLygkgkwtatWwEAc+fONQwhK29+TUls27aNJSCMfz1hRNSfiGKJSEslG+cOItpNRA5E5EhEe4hoW4HzdYgoi4g6EJGIiDoR0QsiqlVKTGacDIthqwnIlClTMHDgQGtXw2pY2DiZjjL+0Tx//hxCoRCjRo0q8by5EpDs7Gy0adMGRAQ3NzdwHIdDhw4Zzq9cudIwFCs2NhbXrl3jvQ5lMWTIENjb2xc7rtVq0bt3bxARoqOjce/ePTRs2LDQ5HRvb28QEWbNmlXpuJs3b2YJCMOmKKnnzjfveGSBY1F5x7zz3q8goi1FPreViL4sJQ4zTobFWL9+PerWrWvtalicSZMmYciQIdauhtWwonEyHWX8I+nSpQtkMlmJE763b9/O+w/iAwcOQK1WQywWG1bCCgsLg1KpxKpVq+Du7g4iQp06deDl5QUPDw+L70I/YMAAaDSaUs/v3bsXKpUKEokEq1evNkxOT05OhlgsRlRUFIioxE0Qy2LTpk3gOM7U6psMS0AYlqIk40wmfa9cUV4SUdu8178R0YQi5ycR0fFS4jDjZFgMW01AJkyYYJgsaYtUsQSE6SijypORkQGO40pcMpbPBESr1aJPnz4gIkRERBQaTpX/w5vyniycOnUKAHD27FlwHIdx48bxUoeK0rdvXzg6OpZ5TVZWFpo1awYiQvPmzQ0bDxIRLl68iG7duoHjOGzYsKHCcdevX88SEMY/lq9Ib4TavP8WLftL+ExJxtmLiO6UcO1dInoj7/UlIhpc5PwQIvqzlLox42RYjHXr1qFevXrWrobFGTduHJKSkizeY1hV4Mk4mY4ybIpWrVpBpVIV0w2+JkWfPn0abm5uEAgEmDFjhuH4wYMHERwcDCKCj48PiKhYB8rQoUMhEAhw+fJlk+tRUXr16lXi91ESq1atgkQigUqlQkhICIgI9vb2OH/+PJKSksBxXLEVvUpj7dq1LAFh/GNRkH6ccWnFroTPlNZz96KEa18S0Wt5r1nPHaPKYqsJSPfu3UFE+Pnnn61dFavAk3EyHWXYFDdu3ADHcZg/f36h43wkIOPHjwfHcfDx8cGlS5cAACdOnEBERASICAEBAdi7dy8A/QaJRFRoQrpWq4WLiwtCQkJMqkdlaNGiRaV09O+//zYMuwoKCjJMTt+2bRvq1KkDoVCII0eOlHuf1atXswSEYVOUNnZZS8XHLmuJyCvv/Qoi2lzkc1uonLHLw4cPx+jRozF69OgK9wowGJVl7dq1SExMtHY1LE6tmjVBRBgzZoy1q2Ixdu3aZdCU4cOHV6UhWExHGf8YGjRoUGzYkSmrMl27dg1BQUHgOA4jR44EoB9SFRsbCyKCl5cX0tPTi30uMTEREokEt27dMhw7dOgQiAhz5841qi6VJSTvqUxldDR/F3OO4+Dq6opatWoZJqeHh4dDLBbj9OnTZd5j1apVVktAqoiOMmwEKRHJSG+cSXnvhQXObyeiXUTkRETORPQ9EX1T4Hwd0vfutSf96i0dSb+MJFu9hWF1bDEB0el0UMvliCWCt5sbdDodb/fOysrCkydPTC5ZWVm81akkrNBzx3SU8a/gzz//BBFhxYoVhmPGJiDz5s2DUCiEk5MTjh07hsuXLyMxMRFEBBcXF3z99delfjY7OxsODg7w9vYuNASqU6dOEIlERi1vWxl0Oh2UUmmldTQpKQmurq64dOkSvL29wXGcIdlq164dfH19IZPJcO7cuVL18fPPPwfHcbaoowwbwo/+N8a5YHm3wDUaIvqaiB6Tfg37/6Pi/zN2Jv369S+I6Czpl5IsDWacDN4o7wfxl19+iYSEBKsLuSU5fvw4JAIBJhBBJhbjxIkTvNw3KysLMonEsL69KUUmkZj1O7ewcTIdZfzjKailMTExcHV1Nbz/+uuvkf//W0V0NCMjw9Dz361bN9y4cQPNmzcHx3HQaDQVXhXqzJkzEAgE6Nixo+FYdnY2lEol4uPjzfI95HP8+HGIOa7SOqpQKDBgwAAA+mFjQ4cONSwznL9zurOzMzimowyGxWHGyeCFf9IPYksyYcIERAoEmEqEGKkUk4zYibck8s1oBRHWm1BW5H3n5tQAGzBOpqMM3uBLS2USCVasWAGpVAqlUolNmzYhOTkZHMdBpVIZNXRq8eLFICq8lG3+E5mynqCYyoQJExDBcZXS0QMHDoCIik2UP3LkCDQaDYRCIcRiMezs7EzWUqajDEblYcZpQXJzc5Geno60tDT0S03F2LFjcejQIV6H5ZTF7du3sW3bNqxfvx779u3Dq1eveLt3vjjOJ8JiE8p8noVcp9Ph4MGD+PLLL7FkyRLs2rULOTk5vNy7IrEDvL3xOhGmEqErEQJ9fHj5987/vtcT4VsTynpmnHzAdNSC6HQ6HD58GGPHjkW/1FSkpaUhPT0dubm5Fon/+PFj7NixA+vWrcPOnTvx9OlTXu/Ph5bm6ygRoVGjRujcuTMEAgHkcjmmTp1q1Ip8Z86cwYoVKxATEwOO43Ds2DHDuYYNG0Iul5ul48hYHW3bti2cnJxKPJeTk4P27duDiCAWi03WUqajDEblYcZpIVasWAFfb094uzliRPsETOnZGP1bx8HeToGoiOrYs2eP2WL/+uuv6NSuHSRCIYLt7FBDbQdXuRyuDg6Y8vbbePTokckx8sVxMRFWmVAW8yTkOp0OS5cuRYi/P1QSCSKUStRQKuEkk8HD2RkzZsxAdna2ye0ui9OnT0MqEmFynnFOIoJUJMKZM2dMvjdLQKoUTEctxN69exEVUR32dkr0bx2HKT0bY2SHuvB2c4SvtyeWL19utth//fUXBvXrB4VUCj+VEjXUavgolVDJZBg6aBCuXLnCSxw+tDRfR+vVqwehUAiJRIJx48YZ1fmyY8cO1I2NhUQoRHWlElEKBRw4DiIiDB82DA8ePMCTJ08gkUjQunVrXr6DghiroyqVCikpKWVes3XrVkjynjaxBITBsCwWN860tDT4+/uD4zjDxkaAfizpiBEjEBwcjKioKPTu3dvscTMyMhATE4OaNWuiZs2aCAkJgVgs5uUHeUESEupAwHHgiHD8iyHQ7p4O7e7p2D6jN2KC3OHlrAbHcRgxYgSvcdPS0uDi4gIiQpJUjK/tZNhvr8BshRQhAg4eHAelQAB/L69Cq5sYQ1HTXEaEWkTwIIIvESKJ8GHeuYVEqEEENyJ4E2EyzwnIixcv4OPjAyHHQUOEYCK8TfpewdZEsM+LEREWhufPn5vU7qK8fPkSHTp0QGhoKNzd3aHiOKTlGWcMESQcB3d3d9SvX79QD2JlKZqAbCFCAhG8iBBAhJpEWJp3rhkR/POOhxBhOjNOvmE6agEdbdOmDbg8HT3yyaBCOlqzmgf83TQQCgTo2LEDr3EB4PXXX4cgb0O7KXIJ9tsrDFrqK+Cg4jiIhEKsW7fO5FgFtdRUHRUKhRgyZIhRnS0vX75EZEQEOCKoiVCtgI62IYImL4abszNu3LhhGJ6Vv3yvKZiqo0ePHgUR4ezZs+XGunHjhkFLmY4yGJbD4sZ58OBB3Lp1CwEBAYWMc9SoUUhLSzO8L7gjqznjFmTu3LlITk7mNe7OnTuhlMuwZ05fBLg74OTi4QbjdLST479LR0C7ezqWjtY/Di6tbsbw2WefQSYSwZEjfKnSJx/fquVQc4SVee/nKyRQcRyiwsJMeiJQUgIytoAh9iZCWN7rBkTomPf6PSI4EuErHhOQyRMnQiMW4708s+ycZ57ziTCaCFOIEEgED7EYXTt1MipGl86d4ergUKy4aDSwV6ng6uAAiUiEmDzTmkqEHkToRASJSAR7lQoCgaDEe7g6OKBL585lxi8pAZlawBAH5/04+ZYK9+wtIIIdM06+YTpaAHPo6KVLlyCTSrB8bIcydXTXrBQQETZv3sxb7GvXrsFOLkcfqRgeHFeqlraTiCAUCHjtzDFVR+/cuWN0PTZs2ACpUIgxZehoNSIEcxzCQ0Lw6tUr1KhRAxqNpsJDvMylowqxGGKOK1dHC37f+QkI01EGwzJYbeiAv78/Tp06BZ1Oh7t370KtViMzM9Nica9evYp169bh5MmThnPh4eH49ttveY3XvEkjfNCvBbS7p8PfTVPIOJ3tFTjw8QBod0/HycXDIZeKkZa3NjsfNE1MRKpMAvcCprlYJYOPgDP04O23V0BBBDeZDBs2bDA6VnnDBt4jgkveaxnpe+/yzwURYQJPCUhmZiZUcjnS8oxyPhHG5Jnz/AKlGhG6E0EiFOLChQuVjnPkyBF4urrCQShEdyL0L6EMJMIA0vcUTs0r7+Qd70kEARH6Fbi+OxEchEJ4urqWu0FWeUOwPiZ9z2jR4zOZcZoDq+soAKvoaEZGBjZu3IgffvjBMCbfHDo6evQodGsaUyEdtVdK0aRhA95ijxk1Co2Ucuy3V5SppfvUcgiJ0C811aR4ZWnpexbSUZ1Oh8iQEHSpgI6mEsFJIsGWLVtw69YtCIVC9OnTp0JxzKWjaiIopdIKbTRYlpYyHWUwzIdVjTM9PR3VfKUgcQAAIABJREFUqlUzTAQbPnw4ateujYYNG2Lfvn1mi7tmzRrY2dkhrnYtKJVKrFixAocPH4aHh4dRk/NK4+LFi5BKxLizYUKJxrl7Tl842yvg56aBvVKG+UPbQGNvx8tEvgsXLkAsFGKLnbyQaW5Xy2HPET5TSrHfXoHpCgkERGgpFiIxrrbR8cpLQBKJkESEz4kgLnIuPs9g+DDOxYsXw18ux8cFTLI2ERqVYJz9iVBbIsGbRiZ9Dx8+RId27WAvlaJ3AXMsWKJJ/0i/6PEGpO/JzH/fmwgaqRQdk5MrNHSlvASkCRHaF3jfmQjueab5ATNOvrGqjh48eBANGtQ3DLlJSUmxiI7u3bsXPj4+iIwIh6OjA8aMHm0WHX358iUcNGr8OK9/hXR087vdIZWIjepYKMqLFy+gUSoxP08vy9NSjgh2CgVevnxpdMyytNRSOvrzzz9DIRZjdgV1tA0REvOW4n3nnXfAcVyhzr2y4FtH1RIJhEQ4ePBgpb7vkrSU6SiDYT6sapx1ExIwbHA/7N+lX8avbt26AICTJ0/C2dkZ9+/fN0vcVq1aYeybw4CsB9j49XIEBQWif//+mDBhAq+xtm7dilphfgajLGicr757H42jA/DTfH3P3a+fDYGHox2EQgEuXrxocuzFixejttqumGnut1dgvlKKaKEAoUIBOkpECBBweEuuXwnE2BWiyjLNLnlG9WWecUqKnI8rwThPnz6NK1eu4PLly/jrr79w6dIl/Pnnn7hw4QLOnz+Pc+fO4Y8//sCZM2dw+vRp/Pe//8Xvv/+O1i1aoHUBg2xD+kf3H5ZinClECPb1xffff4/vvvsOO3bswPbt25Geno5vvvkGW7ZswaZNm7BhwwasW7cOa9aswerVq7Fq1Sp89dVXWLZsGVJSUiARiZDIcZhSwAybEsGH9OOmC5pmRyI4E2Ec6YcxJHIcJEIhevfujSVLlmDZsmVYvnw5VqxYgZUrV2LVqlVYvXo1vv76a6xduxbr1q3DV199Vapp9soz5c0lnJtO+jkx3zDj5BOr6mifPn3QrElD7N2xBRzpd7MGzK+jb775Jlo0awzdi79x/tTPICKkpKTwrqOXLl2CSCRE7vfTKqyj0cE+2LJli8mxf/75ZzjKZNinLv4EpCQt9RdwkItEJu33U5qWGqOjhw8fxqlTp3Dy5EmcOHECJ06cwLFjx3Ds2DEcPXoUR48exS+//IIjR47gyJEjOHToEA4dOoShQ4ciRiKpsI5OJP2TiP/85z/Yvn07XFxc4OjoiG3btmHbtm3YunUrtm7dis2bN2Pz5s0GTd2wYQPWr1+PdevWYeDAgXodFQhM0lE/Pz9IpVIsXLgQCxcuxKeffooFCxZgwYIFmD9/PubPn4958+Zh3rx5mDt3LqZNm1ailjIdZTDMi1WNMyQkGBtWL8ODm39CIBCgSZPGhvNxcXFm6b3z9/dHu3bt0L9vT+he/I2ln3+MkJBg2NnZ8dJjVpCNGzciPiKwxATk6GdDEOrtbDin3T0dcaFekIjFFZo4Vx5z585FYztViaZZsHyvlsOOIyxVSU0S0NJMsxvpJ+0VPF506EAgFR86QETgOA4CgcCwXrtEIoFUKoVMJoNCoYBSqYRKpYKdnR3s7e2h0WigEInQPs8ck0k/cXNWEdMsaJyDiKAUiRAWFobw8HBERkYiKioKMTExqFWrFmrXro34+HjUrVsXiYmJaNCgARo1aoQmTZqgWbNmaNGiBZKSktCgQQPYK5XwEAiQRoQWRPDMM+aCptmZCE6kH0M9kggeAgHslUo0bNgQrVu3RlJSElq2bInmzZujWbNmaNKkCRo3boxGjRqhQYMGqF+/PurVq4e4uLgSTTM1zxjLWtHFO+87YMbJG1bV0bZtX8Pk8aPx4OafEAqFcHR0NJw3p46OHTsWdRPi8OrpHfxy4HsIBAKz6Oj58+chk0oqpaPV/T2wfv16k2Pv2bMHviqVQS8roqUuMhl++ukno2OWpKWm6KixpWYldHRqJe/NcVyJhYggIoIrUaV01DXvcwKBwHB/oVAIkUhUahGLxRCLxRCJRMW0lOkog2F+rGqcY8eMgYuLMwak9oJIJMKYMWMAAJcvX4aLiwtu375tlrjp6enw8PCAm5srFAoF0tLS0KABf2OG8zly5AicNHZ48Z+pxYzzzoYJUCuk+GNZGrS7p+PCV6PgoJJBIBDg4cOHJsdevnw5okpJQDbbyQ2ve0pFaCgSYqVKBqFAYPTQiZJMswfpe80WUeGkpAEROuS9nkr8TkIfkJqKxhyH9nkG8UEJplnQOLsSoW5srFGxipKVlYWhQ4ZALBDAKe/HQEHT7JLX1lGkf/KiEIsxbOhQo4bclTRsoF9eu9YVOPYNEZYUeD+X9MMH8q9hxskLVtXRRYsWQaFQIDXlDchkMnTsoF8Fytw6eujQIcTERMPJyRFSqRSvd+1qFh19/PgxhEIhLq0aUyEddVLLoVErcejQIZNjHz9+HGqJBHtKeQJSVEsbiARQiEU4ffq00TGLaqkpOnrr1i08f/4cz58/R1ZWFrKzs5GdnY2cnBzk5OSUqvefffYZqisUFdbRN0m/QznR/xYAGDhwIAQCAa5evVqp9puio2fPngUR4ejRo5X+vvO1lOkog2EZLG6cgwcPhre3N8RiMdzd3eHh4YG3334bK1asQJMmTVCjRg3ExMTgm2++MWvcoKAgHD58GLdv30ZiYiJWrVrFazwA0Gq1CAkKQNOagfB2VkMsEsLdUYVgLydod0/HmkldUSPADTFB7ogKdENyvTB06sDP6jF37tyBgOPgyOl7hhw5gnfehMk2YiF8BRy8BRxaioXYrpbjDbkU7U1Yw72oac4nAkf6CXx+pO9BC6L/LR8ZSf9bPnJSAVM1NQHZvXs31BL9WGxn0i+n6JVXh4LLR4qJoCKCiOMwe/Zso9tdlJs3b4KIoCD9WGH3vDZOJf0QBfu8Y2oiyGQyo5PNoqb5Vd737UH6ntAAIoSSfvhA9bz2BxAhnNjYZTNgdR319vbGlClT8NFHH1lUR6tVq4ZffvkFly5dMpuOAkDnju0RHeRRIR0d0T4BwUH+vMxDyc3NhberK2qLBHDJ2/uiLC19SyZGoJeXSbELaqm1dPTmzZsQ5T1NqIiOSojwRvfuaNiwIcRiMa5duwatVgsnJyeEhYUZFZ+M0NGUlBSoVKpKxSqopUxHGQzLwTbQMjMLFixARKAnnqRPKTRMoGj56//GwEGt4mUN9Xy6duiAZLm0xOECBUu6Wg5HmdSk2FVlI0KtVosAb+9Cq7eUVoYRQS6V4vHjx0a3uyg3b96EUCDAOCp5MmV+GUtk0pKdbCPCKgXTUTOzf/9+OKhVhqcgpZUn6VMQGeiFjz/+mLfYM2fORLRSYXgKUlrZo5YjXKnAvHnzTIrH50aEpvw/mfzaa6gvEJSro+8SQSYS4bfffkN2djacnJzg6ekJrVaLAwcOgIiwYMGCSsU2VkednJzQtm3bSsXiQ0uZjjIYlYcZp5nJzs5G86aN0SA6CHc3TizRNP9YloYgb1cMHz7MsJQlH5w/fx4apRLDCmycVbR8q5YjWqlA26Qkk2JXlQQEAL7//nvIxGL0L8M0R5N+tZTPP//c6DglsXDhQgQrFIVM8l3SD1N4t4h5VlMo8NlnnxkVhyUgVQqmo2ZGp9NhxIjhCPRywZllI0vU0XubJqJhdBCaNWlk0p5GRXn06BFC/P3xmkJWahKyWy1HK4UM4dWq4enTpybF4zMBKW+38LK4cOEC7FUqtOO4QqsKFixTieApk2FAv36Gz50/fx5CodCwF0z79u0hFouRkZFR4djG6Ojly5dBRDhw4ECl2skSEAbDOjDjtADPnz9Hl04dIJdJkdo6DjtmpuDwJ4Ow+d0eSE6MhFgswlvjxvG6dGU+v/zyC5zUasSrlJiu+N9Y5q12cgyUieEul6NNi+Ym7whelRIQQL8CmVwqRbRMhsFEmE2EOaQfq1xHLIZUJMLcuXNNilESifHxaE2Fe+gC8yZXhkmlhXr0WhGhfp06RsVhCUiVgumoBdBqtRj/1lsQi0VIrh+JTe92x+FPBmHHzBSkto6DXCZF547t8ezZM95jX7t2DaEBAQhVKvCWXIKdeTq6Qy3HWLkEwUoFIoKDcfPmTZNj8ZmAEBFatmxp9JPW48ePw8XBAdXkcvQi/bCjj0g/KbyJUAiVRIJ+ffoUWz1x2bJlICJ8/vnnyM7OhlKpNKxyWRFK0tGAcnR0wIABUCgUlW4jS0AYDOvAjNOCnDp1CoMGDUBwoD883V0RHhqMSZMm4dq1a2aNe/fuXUybNg2ezs4QcPplIokIjerWxaZNm5Cbm2tyjKqWgADA9evX8fbkyXDWaAxmrJTJMHTwYJN6Bkvj3r17EAgEGJ1njL2IYC+Vws3JCfPmzUOn9u1hL5WiV9750aQfPmDMMqksAalSMB21INeuXcPkyZMRERYCT3dXBAf6Y+CA/vj999/NGjczMxNffPEFqgcG6ucniPU6GhkcjCVLlpjciZMPnwnItGnToFKpwHEc2rRpg3v37lW6Pg8fPsT8+fMR6ONj0FGRUIiuHTviwIEDpT4579KlCwQCAU6fPo1Nmzbp9aoCK5OVpqNqpRLx8fGl6qizszOSkpIq3T6WgDAY1oEZpw2Rk5ODK1eu4OzZs7zvDVAVE5B8tFotHjx4gPv37xu9z0lFWLJkCQIVCkwhQn2hEAqpFMuXL0f9+vXx9ddfQ6fTYdmyZZBLJEgUCjGFCAEKBZYuXVrpWCwBqVIwHbUhdDodbty4gT/++AM3b97kddgswP8cEK1WixkzZkCpVILjOLRv375Sw6EKtvvRo0e4e/duhTZa1Gq18PX1hUajQVZWFhITE6FQKMpd9a80HQ0KCkKTJk1K1FF/uRxEhN27d1e6XY8ePWIJCINhBZhxMnghXxzn55mfsWW+BYTcXDSpXx+1ieArkyEiNBTnzp0DANSrVw/r1q0zXHf27FlEhIbCVyZDLBGaGrF0af73vSLP/IwtK5hx8gHTUQZv8KGlJemoVqvFO++8A7lcDoFAgC5duuDRo0dmbcudO3cgkUiQkJCAR48eQSKRlDtJvDQdDQwMRPPmzQ3XFdVRCccZVceEhASTtZTpKINReZhxMnghKysLMonE8IjelCKTSIzaG8OaZGRkQCgQgCPCiGHDCtU/Pj4emzZtKnR9VlYWhg8dCo70wwcquxzvP+n7tgHjZDrK4A2+/rZL+7vWarWYOHEiZDIZhEIhevTogczMTLO1Z/v27SAiTJ48GQsXLgQRlbo5Zlk66ufnV2yIVb6OEumXz62sjjZt2hREBEnesGRzfN98YQM6yrAxmHEyeCMrKwtPnjwxufzTkg9Av/+Ik4MDtm/fXuxcbGwstm7dWuLntm/fDicHB6OGDvxTvm8bME6mowxe4eNvu7y/65ycHIwePRpSqRRCoRApKSm8zWMpSlpaGjiOww8//ICIiAg4ODiUuOhKWTrq4+ODNm3aFDt+584dEBHsVKpK6WhSUhI4jsPWrVst8n2big3oKMPGYMbJYPCATqcrdVx0TEwM0tPTS/3sy5cveR9HXpWwAeNkOsr4x5KdnY0RI0ZALBZDJBJhwIABZvkxHRUVBblcjtOnT0MgECA1NbXYNWXpqJeXl2Fp34KMHj0aEomkUjqanJwMjuMqNCm+qmADOsqwMZhxMhhmJjIyEjt27LB2NayGDRgn01HGP56srCwMHjwYIpEIYrEYQ4cO5XU/lczMTKhUKoSGhmLy5MngOA6nTp2q8Oc9PDzQsWPHYsd9fHzQoBLz6Lp06QIiwurVqyv8maqADegow8ZgxslgmJnq1atj165d1q6G1bAB42Q6yvjX8Pz5c/Tt2xcikQgSiQSjRo3ibfXAX375BRzHITU1FT4+PvDx8anwZ93d3dG5c+dCxzIyMkBE2LBhQ4Xu0bNnTxARli1bVql6VwVsQEcZNgYzTgbDzAQHB2Pv3r3WrobVsAHjZDrK+NeRmZmJnj17QigUQiqV4q233uIlEZk1axaICB9++CE4jsPkyZMr9DlXV1d069at0LGJEydCLBZXaBPf1NRUEOk3R/wnYgM6yrAxmHEyGGYmMDAQP/zwg7WrYTVswDiZjjL+tTx58gRdu3aFQCCAXC7HlClTKvSDvyyaNm0KkUhkuG9FNuN1cXHBG2+8UeiYv78/EhISyv3skCFD9Esbz59vdJ2tjQ3oKMPGYMbJYJgZPz8//PTTT9auhtWwAeNkOsr415ORkYGOHTtCIBBAoVDg/fffNzoRycnJgYuLC9zd3aHRaBAREVHuZ5ycnJCSkmJ4n68rq1atKvNzo0aNAhFh1qxZRtW1qmADOsqwMZhxMhhmxsvLC0eOHLF2NayGDRgn01GGzfD333+jbdu24DgOKpUKs2bNMioR+fPPPyEUClGnTh0QERYuXFjm9Q4ODoVWzpo6dSqEQmGZscePHw8iwvvvv1/p+lU1bEBHGTYGM04Gw8y4u7vj119/tXY1rIYNGCfTUYbNcefOHcNeGmq1GvPmzav0PVauXAkiQnh4OCQSSZk7s2s0GgwcONDwvlq1aoiNjS31+nfeecewAeK/ARvQUYaNwYyTwTAzzs7OOH78uLWrYTVswDiZjjJslhs3bqBZs2bgOA4ajabSk7y7d+8OgUAAmUyGxMTEUq9Tq9UYOnQoAP1KXRzHYcmSJSVeO2PGDBARxo0bV6m6VGVsQEcZVqQ3ER0iogwi+puI9hNRvSLXSIjo87zzT4joWyLyLnJNYyI6QUTPiegvIhpSRkxmnAyGmXFwcMDvv/9u7WpYDQsbJ9NRBsMKXL16FQ0bNgQRwdHREV9++WWFPqfVahEQEAC5XA4iwqZNm0q8zs7ODiNHjgQAfPDBBxAIBCWuyvXhhx+CiDBixAjjG1MFYQkIw5wMJaIWRKQkIiERvUlET4nIs8A1nxPR76Q3SxURrSKi3wqc9yWiZ6Q3SxERNSSix0TUvpSYzDgZDDOjVqtx+vRpa1fDaljYOJmOMhhW5NKlS6hXrx6ICC4uLuVOEgeAe/fuQSqVQqlUQqlUlrgBolKpxOjRowEAYWFhiI6OLnbNggULQESFhmr9W2AJCMPSPKL/mZ6U9L1xbQucdyKiV0SUmPf+XdL32hXkYyLaU8r9mXEyGCaSlZWFJ0+elFrkcjmOHj1a5jVZWVnWbobZqALGyXSUwbAwZ8+eRXx8PIgI7u7uWL9+fZnXb9u2DUQEjuPQpk2bYhqpUCiQlpaGe/fugYgwZ86cQufnzZsHIkKfPn0s00ALUwV0lGFD1CG9KfrnvY8iIi0RuRW57gIRjch7vZWIFhU534OIHpQSgxkng2ECWVlZkEml+cZgdJFJpf/aJMTKxsl0lMGwIqdPn0atWrVARPD09MTWrVuLXcOXjoqEAqajDEYBviIiHelNT1dC2V/CZ3yI6AoRvV/gWP28e0iLXPsLEU3Oe72XiGYVOd+K9AZcEsw4GQwTyDeFMz0a4VpKM6PKmR6NwPffYWZmJm7duoWnT5/ydk9j4ck4mY4yGP9gTpw4gaioKBARfHx8sH37dsO5qqqjWVlZuH37Nh4+fAidTsfbfY2BJSAMY1AQkWMZxa7I9dWI6DIVN0Cz9dwNHz4co0ePxujRo7Fr1y6r/pH9m3n58iXWrl2Ltm1aIS42BvXr1sGoUW/iwoULFol/584drFu3DkuXLsXGjRuRkZFhkbgAcP36dezcuRPp6ek4duyYxcT8+vXr+OCDDzBo4AAMGzYMixYt4tWg8k3hWkozPBqQZFS5ltKMF+N89eoVNmzYgEYN6xfqFaybEI/Vq1fj5cuXPLW6fHbt2mXQlOHDh/NhnExHGQD0k5a///57dOvaBXVq10LdOrXRt28Kfv75Z4voytOnT7FlyxYsXboUa9aswdWrV80eM5+MjAzs3r0b33zzDX766Se8evXKInEfPnyIhQsXYujQIRg8aBDmzJmD27dvG3WvX375BRERESAi+Pv7Y9euXVVKR3U6Hfbu3YtOHTtAKBQadDQ0JBgLFiwoc6lgvjGDjjIYpRJFRLfpfz1xBSlp7LIzEWXT/1Z5eZeIjhf5HBu7XAVIT0+Hq4sTqvl5YNaIDtgwewBWTeuD7q3qQCIRo1OH9mb7dzh16hS6dekEiViE2oEeaBHhjxg/d8ilUvTt3QsXL140S1wA+PHHH5Hctg3EYhHCg7wRHeoHezslqocGY+HChSVONuSDmzdvokPb1yAWCfFaDX+Mb1odYxuHIT7IE0q5DGkjh/Pyg7yqGOeDBw9Qr24CAny98OHbg3Dr2Hq8urwLd3/biAXvDUNIkC9q1YzBnTt3TG5zZbFCzx3T0X8pJ0+eRGhwEFydNJiY2grrZvXHmpn9MLxbE6jtlKgTF2u2hODmzZsYOmQwVAo5wr1d0DzCDwnBXhCLhGjXupVZNxv9448/0LdPCuQyKar5uqNmmD/cnDTwcHPFu+++i4cPH5ol7rNnzzB44ADIpVLUC/bCuMbV8VaT6kiK8IVELMLrnTvi3r17Rt374MGDCA0NBREhMDCwSuhodnY2evV8A06OGkwY1h0XDnyF7L++w6Mz27D6k4moGxsJTw93q6xqyJ6AMMxJPdIvHZlWxjWfkX61Fh/S9/itosKTJfNXbxlMRGIiakCFJ2AWxerGuWPHDtSqVQsxMTGoUaNGhVbM4IPvvvsOtWvXRnR0NOrWrYtTp06ZLVbr1q3BcRw4jnBizSRoj38B7fEvcOGb91AvKhCB3s5Qq+SoEVEdz5494zV2hw4dwHEciAjp/Roid24P5M7tgZH1Q+Cp1i97qFYped8oLy0tDY6OjiAiDGiXgKubp+DFvjlo3yASIT4u8HXTQCmXom5CHd7b3LdvX0PP1Y4BjQxtbhHijmhPDUJc7GAnE6N2zRiTxwsXTUAGR/jCVyUHR4SDHesVM8nPGkaCI8KaFjV5M84XL17Azc0VCrkUHMfh9++XQHd9D3TX98DP2w1h1XwQXT0QDvZ28PX1sfiwLAsbp03qKPDv19IePXrodZQIR1dPKKaj1Xxc4OpoB1cXZ1y/fp3X2L1794ZQKAARYfUbdQvpqLe9Qj+PSyIud6J1ZUlLS4ObmxuICJ0aR+P3leMK6WigpxMc1AoE+Pny3uahQ4dCKpGAiLC+d2IxHa3uqoazUgYfDw+jn4YAwL59+4olINbQUZ1Oh7CwUEjEolJ1NCY8CB6ujlDbqfDXX38Z3WZjYAkIw5zsJ6Jc0i8ZmZlXnhLRxALXSIhoIemHAjwlou1E5FXkPg1Jb67PST8EYXAZMa1unI6Ojjhz5gwA/TriMpmM9x+kRXn06BGcnJxw7tw5APqemMjISLPE0i8vKMGKqb0R4OWEk+smG4yzaVwoVr7fB9rjX2DtzFSoFFKMHj2Kt9jnz5+HXCbFgva1EOCoxG9jWhlM5MfhzXH9nfYIcFRidKMwODtoTDKRokybNg0qhQyezmqc/GostAfn4cW+OdgxdyC0B+dBe3Ae5g5vB3uVHB3bt+Mtrk6nQ3CgP3rVDirW5oczuhher+lZDwqJCMOHDjEpXtEEZGfbeJzt0Qh+dvJixvnf7g0R76pBvKuGV+NctGgRAv08ceng/yHAx72QcQb4uOPU7qXQXd+D7L++Q51a4Zg9e7ZJba4sFjZOm9RR4N+tpVqtFl6eHhjfp2WZOrpxzgA4O6jQrEkj3mI/efIE7q7OGFwvuEwd/bRjLBQyKX7++WfeYn/11VdQyGVw0ahK1dFP3uwAdyc1IqqH4sWLF7zFbtWyORIC3eFfho5uSqkPB7kEDerWMSlWVdDRw4cPQ6mQ47fvFpWpo7rre5DarRV6vtHDpDZXFpaAMP5tWN04nZ2dMWzYMEyYMAGbNm2Ct7d3iZsL8cnx48cRGBiIN97ogVZJSdiyZQvUajVOnjzJe6wPPvgAzepEQHv8C/h7/s847+6ZA3uVHDlHPzMYqaO9EnYqJW8/Ggb0S0VqQjBy5/aAv0NhE8kv+cfb1PDDlClv8xJXp9MhNDgIyyZ2g7+Ho8E4i5ajy0bBz80BSoUMx44d4yX2vn374KxW4tms10ttc+7cHljerQ5CXdWQy6QmDV8obQiWr6qwcT7s3xKNPZ1woENd1Pdw4M04dTodakSGY/ncsdBd3wP/IsZZ9P3GRe8gwN8Pubm5Rre5stiAcVpdR7VaLVQqFbp3747du3fj1KlTFtHSH3/8ERqNBi2aN8fH8+ZBp9OZRUt37twJD1dHvPxlYbk66upoB4lEjLNnz/IS+7PPPkPtAHfkfNS9XB2d0CwCyW1a8RIXALp27oQ3X29Uro76ezgispoPVqxYwUvc27dvQyIW4cLEtuXqaJSHBiq5FEePHjU6nrV1FAB6vtEDaf07VUhHz/2wAlKpxOjhZ8ZgAzrKsDGsapw6nQ61atWCSCSCUql/jL18+XKzx3348CGEQiFatWyGebOnQSqVQiAQ4JtvvuE9VnBQADbOGVgsATn29USE+bsZTFN7/AvERfghwNsN//d//2dy3MePH0Mhk+L46FYVSkD+M6AR3JwdeZmTsW/fPjg7qPF87+wyjbN3q9oY9XpDDO6QiNS+fUyOCwBdO3bAW00jSm1z71h/+GgU8NUocGpcG9QL9sInn3xidLyKGuf0+FBMqhWERwOSeDXOCxcuQCaT4tmF7aUaZ3R4IKKqB6J/99a4dWw9NPZq3hK+imADxmn1BGTsmDFwd3OFTKYfhqdQKLBv3z6zx23Xri3EYhHeGj0Cnp4eGDpkiFm0tHPH9pgyoE2FdDQ+wh/NE6pj7NgxJsfV6XQID6mGFd3qVEhHL7+dDLFIyMs8lNu3b0MiEePP9ZMqpKOfj+2M2JpRvEzEnzZtGpIifCuso0MSQ5HaJ8XoeNbWUZ1OB5lMit++W1TNAuzjAAAgAElEQVQhHb3/+2YkxkVh2bJlRre5stiAjjJsDKsa5927d0FE2LltPZD1AE0bNYCdnZ3ZV2e6desWiAgN69dF7VoxqBYUADc3N/znP//hNY5Op4NQKMTFbdMqloCE+6Fl3Qi8//77Jsfev38//F0dihlkacb56sPuUEglhiEcpjBx4kT0a5sA7cF5pRrnjIGtUS/SH8/3zsa+T4fCx8vD5LgAEBrojx0DG5fZ5ty5PbCyRwJah3ni7eYR6N+vr9HxKmKcP3dORJyrPR70a8m7cR4+fBie7i6l9tRd/3UtdNf3IOfKLowf2g1tmsYjLNjfoqs02YBxWj0BcXd3R0xUJA7t24Fp705EixbN4eHhYXYtdXJywuJP56JRg3rw8vRASEgIIiMjedfSmtGR2DJ3UIV1dEjnhujUIdnkuA8ePAAR4VHesKPydDR3bg/EB3lh7dq1Jsdeu3Yt4iICK6yjf++Yrq8rD6s0vd6pA2a/FlNhHd3QOxFx0TWMjmdtHX327BmICH+f2lJhHe2W3BRz5swxus2VxQZ0lGFjWNU4jxw5Ao7jsGrZ5/jz9K8ICgxAQEAA9u7da9a42dnZ8PDwwISxadiwehk0Gg1UKv4nlel0OohEIvy57f0KDcFyd1KjQ5NamD59usmxt2/fjhq+bhVOQHLn9oCLvcqkx+j5DB8+HGO7Ny7VOD8c1hZx1X3w+PuZ0B6chxMrxkBjrzY5LgAE+nhh9+Am5Rpn7twekIuFmNA0HCk9jR/LWxHjnJcYDg+FFH52cviq5JAJBXCVS/BxYrjJxnny5EnYq+2gvba7ROMsWG4f3wC1nQLenm746aefjG5zZbEB47R6AlK9ehgcHRxw89JpNG/aCKNHjUJcXJzZtbRZs6Z4vXMH/GfrWoSFhmDmjBlwcHDgXUtja0Zh80fFE5DSdHRiahK6dOpgctxr166BiPDqw+4V1tFm4X689IwvXboUzetEVFhHcw58BCLiZTJ6x7avYV5yzQrr6P/1SEB0eKjR8ayto7m5ueA4DpcPr66wjr7WvB4WLlxodJsriw3oKMPGsKpx3rt3DwqFAnZ2duA4Dp06dYSTkxNu3Lhh9th79uxBw4YNEBERjpYtW6JLly5miRNRPRSrpvUpZpza41+gSe0QrHgvBdrjX2DD7AGoHe6HEH9PXlZSOXLkCJzVSmR/2K1Cxvl4ZheIRUJefjhMmTIFvVrFlWicc4cnIzbUGw+/m2E4tnPuQPj7epscFwAa1q2DTzvGFmtzxvTOuPFuB0O7t/RtAB+NAt1igzBp0iSj41V06EDBwmfP3cuXL+Hs5Ih96z8qZpzPLmzHozPbDMY5953BqBVZDSqV0qJ/8zZgnFZPQPbv329Y7a5x40Y4ceKERbT09u3bSEpqierVwzBm9GhMmjTJLFrao/vrGJfSokI6Ghfuh07Na5v0d53P06dPQUS4OqV9hXQ056PuCPNyKXG378qyceNGRIX4VlhHb22byttGfCOGD8PAeiEV1tGZbaLxWlILo+NZW0cBILFeAj5+d2iFdDSxdgQUCrlFl+O1AR1l2BhWN87169ejRo0aiI6ORlRUFO/LGJbGgAEDEBYWhuDgYKSkpJjtO1iwYAHcnOzh7aaBWCSEu5Mawb6u0B7/Aue2TEXdqACE+LoiLtwPS97uCWcnB172p8jJyYG3uxtahrrD214BsVAAdzsZgp3tkDu3BwYlVCt03FUlRUxkOC/jh3/99VeIRSJ4Odvr2+xoh2BvZ1zf+i44jkM1b2fUDPZCTLAnEiL88EZSHNLSRpocFwCWLVsGR6UM3vbyQm2+MiUZcT5OiPLQINpTg+Yh7tg7pCmkYjHOnz9vdLyixtk3zBueShnEAg5ucgmC1IpixtnAw5FX4xw/fjz8fdzh7eECsVgEdxdHBAd44fLh1agZWc0wdrlDUiI6t2mIIUNMW/mrstiAcVpdRwFg3bp1iIyMRExMzL9OS/fv3w+pRAwv1/J1dO/iNyGRiHl7CpPUrAlq+zhWSEd9NArYKRXIzMw0OW7+XEU3B1WFdHTO0LZo3LA+Dy0Gjh07BpFQAE91+Tp6fHQrBLg6YOPGjUbHqwo6umbNGqjtVPD2cC5XR6e82ROJ9RKMbq8x2ICOMmyMKmGc/2YePXoEtZ3KsExkaeXJTx8jJswfb789mbfY06ZNQ/1gT8NTkNLKs1mvI9zLGUuXLuUtdu1aMfhoeLsSJ00WLFc2T4FUYloSUJDnz5/Dwd4Oa3vVK7PNuXN7YHiDMDRr1MCkeFVhI8Lr16/DwUGDhdNHlDhkIL+s/Hg87OxU+PPPP01qc2WxAeNkOmpmdDodoiLDMbZ3izJ1NOfoZ+jcvDaS27bhLXZ6ejo8HdV4ML1zmXqS81F3dIj2x/BhQ3mLndq3D3q3ji9XRzP3zIK/l6tJSUBR4mvFYEKziHJ1dHGXOHi4Opu0K3tV0NGXL18ivHoYBvVqh9yr35eqo4e2LoBKpcDOnTuNbq8x2ICOMmwMZpwWYPfu3VDIZZg/tgteHPmkmGme2zIV8TWC0KJZU153Bn/8+DGqB1dDnzrByJpTchKSOasr2tbwQ924WJM35SvI/v37oZDLsG12v1JN8+Y3UxER5IXBgwfyFhcAvv32WyjlUqzvnYicj7oXa/PLOd0wsXkknB00uHTpkkmxqoJxAvrJ6BqNPQa88Rr+2LeskGH++dNKjEztCDs7Ffbs2WNSe43BBoyT6agFuHDhAlycnTCye1Nk/DC3mI7e2jULXVvGIbhaIO7fv89b3NzcXLyW1BKJ1TxLTUJefdgdY5tEwNvDDbdu3eIt9l9//QUnRw1mD2mL3J/mlpp8tEmMRIPEuiYlAUU5c+YMNGoVpreJKbETK+ej7ljerQ4UMqnJK65VFR29evUqggID0KZpAg5umW+YW6e7vgd3f9uIGeNToVQq8Pnnn5vUXmOwAR1l2BjMOC3EgQMHEFItEC6O9hjTqzk+m9gd80Z3RvO6kZBKJRg0aAAvQ6+KcvPmTdSoHorqns74tGMs7r3fCa8+7I6b73bAnLY1EeDqgMQ68Xjw4AHvsbds2QKlQo6ereJwaNFIg4He/GYq3u/fCm5OGqT06mmWvQrS09OhVilRy98di7vE4eCIFvhhWDO83yoK3k72CA7wN2yeZgpVxTgB/caTvXq+AalUglpRYWjVJAFxMeGQSCTo9npX/Pe//zW5vcZgA8bJdNRCXLp0CfUS4qGQy9C/YwMsHN8Nn4zrim6t4iGRiPFa6yRek498nj17htdatYSnoxpTk2rgypRkvPqwOzKmd8ay1+sg1t8dAb7evD3JLcjx48fh6uKElgkRSJ/dH69+/Ajag/PwaNdMfDamE8ICPFG/XoJJ+xmVxsmTJ+Hn7YkAVwfMei0GPw5vjp9GNMfCjrUR6e0CR40au3fvNjlOVdLR+/fvIy0tDfb2aoRW80NS4zpoUCcGUqkEzZo2tkonDmATOsqwMZhxWhCdToe9e/eib98UtGnVAh3bt8PMmTNx9+5ds8bNysrCV199hbiY6HwBAxGhUWJdbNiwgddes6JcuHABI0eOgNpOBYVcCo1aBYFAgFYtm+Pbb7/lZc5JaWRmZmLx4sWoUysGnq7O8PV0R6vmTbFt2zbekp6qZJz53L9/H2vXrsWiRYuwZs0a3Llzh5f7GosNGCfTUQvz22+/YfjwYWjbJgnJbdvgrbfGmX1oYW5uLrZv345WzZsW0tGI0GB88cUXePr0qdli3717F++99x483d0glYjhYK+CUChAXGwMVqxYYZbOq3xevXqFTZs2oXmjhvDxcIOXmwsS42tj+fLleP78OS8xqqKOPnv2DFu3bsXixYuxatUqsySXlcEGdJRhYzDjtDEePXqE69evW/zf/Pnz5/jjjz9w8uRJsydcliTfFM70aIRrKc2MKmd6NOLVOKsaNmCcTEdtjMzMTNy4cQMZGRlm7UQpSk5ODs6fP4/ffvsN165ds1hcc8N0tHxsQEcZNgYzTgbDBLKysiCTSgv1iBpTZFIpr3NwqhI2YJxMRxkME2A6Wj42oKMMG4MZJ4NhIllZWXjy5IlJ5d9qmoBNGCfTUQbDRJiOlo0N6CjDxmDGyWAwzIoNGCfTUQaDYVZsQEcZNgYzTgaDYVZswDiZjjIYDLNiAzrKsDGYcTIYDLNiA8bJdJTBYJgVG9BRho3BjJPBYJgVGzBOpqMMBsOs2ICOMmwMZpwMBsOs2IBxMh1lMBhmxQZ0lGFjMONkMBhmxQaMk+kog8EwKzagowwbgxkng8EwKzZgnExHGQyGWbEBHWXYGMw4GQyGWbEB42Q6ymAwzIoN6CjDxmDGyWAwzIoNGCfTUQaDYVZsQEcZNgYzTgaDYVZswDiZjjIYDLNiAzrKsDGYcTIYDLNiA8bJdJTBYJgVG9BRho3BjJPBYJgVGzBOpqMMBsOs2ICOMmwMZpwMBsOs2IBxMh1lMBhmxQZ0lGFjMONkMMzIo0ePcOnSJdy+fRs6nc7s8bRaLb777jtMnjwZo0aNwowZM3D+/Hmzxy0LGzBOpqMMhhnJzMzE5cuXcePGDeTk5Fgk5tGjRzF16lSMGjUK77zzDg4fPmwRDS8NG9BRhhVJJqJTRPQwrxwnos5FrtEQ0RoiepR3zWoisi9yTRciOkdEz4noDyLqWEZMZpwMBs/k5uZi69ataN64IYgIQqEARITgAD/MmzcPDx8+NEvcFStWIDDAD+4ujujXuRHSejVHp5bxkEolaNq4IX7//XezxC0PCxsn01EG41/CgQMH0K1LJ4hEQggEHIgIrk6OmDRpIq5fv26WmHv37kXtWjFQKeV4o109vNm7BXol14e9WoXoGhHYsWOHWeKWB0tAGObEI6/k04CIXhBRjQLHdhDRbiJyICJHItpDRNsKnK9DRFlE1IGIRETUKe8etUqJWSWM8+LFi6hXrx5CQkIQHx+Ps2fPWrU+DIaxZGZmok1SC/i4OGBmpzq4Oa83cr4chGeL+mPNoGaoG+oDbw93nD59mte477wzBU4Oaqz5cDBu/zgfMWG+qFldX4J8XCAQcFApFTh48CCvcSuChY2T6SjTUcY/HK1Wi5EjhsNepcDopBicm9kdOV8OwsslA/Hd6NfQvnYw7JQK7Ny5k9e469evh0Iuw7zx3XFl94eFdLSaryuEAgEUchmWL1/Oa9yKwBIQhqXgiKg+6U2vU94xXyLSEVFkgeui8o55/z97dx7eRLm2AfxJtyzdN9pCV6Bl70bLvhWhrAKCiLKqoCAgUGVzQ3BfQM85oKAgHOQcP0QFEVAQFT0ogrIvIiBgLYgUBIqUsrS9vz+mLWlIocBMEjv377rmsknGPG9Ccj+dyZu3JZfni8hHNve1VETmVlDHJRpn+/bt8e677wIAPvzwQ6Snp2tec8yYMYiNjYXBYMCOHTs0r1fqwoUL6NWrF+rUqYPk5GRkZmbil19+cVh9PYqJiUHdunWRnJyMlJQULFmyRJM6hYWF6NopE63rReHPf92LwnnDcX7OMIxq3wDxYf5IjAzCgGbxeOL2NISHhiA7O1uVuh988AGCAvywe/lzKNo9/6rt1fF34faMZLzx1CAEBQbgxIkTqtStLCc2Tuaoxpij+uKoLJ04YTxqhgdh/4v32M3Rgc3j8d8Hb4PFZMS3336rSs1du3bBYjFh5exx18zRL+ZPgMVswg8//KBK3criAQhpzU+UaQEXRWmI34iIseS2HqKclbN1QUS6l/y8VUQm2dz+mCjTECqq59TGmZubC39/fxQVFZVdFx4ejoMHD2pad/369Th69Cji4uIc3jg/++yzssuzZs1Cu3btHFY/MzMTSUlJSE5ORps2bbBt2zaH1QaUaUIGgwHLly93WM24uDjs3LlT8zorVqxARJA/TpYcfBTOG44xHRrh4dsall3+/bXBuDz3QfRrmoAHhg1VpW6TtFT86/EBdptm0e75qF+rOj6eNQZFu+cjo1lDvPTSS6rUrSwnNE7mKJijWnJ2jgJVN0sPHToEL08P7Hmu3zVztHDecDzfuymapaWqUnfYsKEYeme7SuXomIGZ6H93P1XqVhYPQOhmLBClCRaV/Nd2+8rO/+MlypzjSaKcxRMRGSgix+zs+4eI9C/5+RcRGW5z+wgR2V/B2JzeOH/44QcEBQUhJiYGrVu3wr59+9CkSROsW7dO07pnzpzBuLFjYbFY8Nxzz2lay9bly5exb98+nDp1Cps3b0ZcXJzDalv/Wy9btgxJSUkOq52dnY0WLVqgRYsWDm2asbGx2L59e7lfzrTQpWMHPN0zraxJnn3jfviZvXBm1v1l15VuPzzVGxazCWfOnLmlmlu3boW3xYxT38+y2zTXL3ocEaH+uLxzHop2z8f7r41EbEyUQ79MqVLjZI5ew5YtWxAWFoZatWoiMbERvvrqK4fk6OXLl/H8c8/BYrFgzMMPo7CwUNN61oqLi3Ho0CEcO3ZMVzkKODdLtT7YmjhxAnqnJ1QqR//8173wNhuxZcuWW6qZl5cHi8WMLR9OrVSO/rTieRiNXsjNzVXpUVdujMIDELpBFlHmGVe0+V7j/10lIqNKfu4hylQCWxdEpFvJz3+7M3eTJ0+Gp6cn1q76CKOGD0WjRg2Rnp6ueePs0qUzMtq2RmBgAHx9ffHBBx9oWq/UqVOnkJqaAi8vLxiNRrRt2xZZWVkOqX3p0iU8M20aetx+O155+WW88847SElJcUjt8+fPo1bNmujevRsaNGjg0KZZrVo1uLu7w2AwoGGDBpo0jfz8fBgMBhx8uX9Zc9w29U7EhvhiYpdkpMWGonVCBD5/tHvZ7YmxEbc8hWHevHlo37xRhWft7u/dGhOHdim7fHrjGxARnD59WqVHfn0qNU7m6DXMmzcPbm5uWLp4IV57+Vn4+fkhNTVV8xydNHEi6tZJQFBgAKKjIvHUk09qWq9UYWEh+vTpDQ8PD7i5uSE5OdlhOVpcXIx5c+eiV6+eGP/oo5g9e7bDcrS4uBizZ89GeHg4Jowfj7Zt2zosS7dt2wYPDw+ICPz8/HDvvfdqMp0zPi4Gy0Z3qnSODmhRF0888cQt1fzxxx8REuRf6Rwt2j0fMZFh+Prrr1V61NfHAxBytM9F5F8lP0eLcvbPdu5ykYjUKLk8X0Q+tLmPj+Q6c5dHjRqFrKwsZGVlYfXq1Q57QwHA/ffdB6OXF4ryc3Fg9w9wd3d3yNQBT09P/Lzje8TGRGPIwLsxYvhwTeuVevrpp5HRthUu5v2Ou/veAQ8PD5w/f94htR995BHUr1cXaY2T4eHuDn9/f+zevdshtVNTUxERHoYpj4+Hh4cHJk6c6JC6Z8+ehclkwqL5b+LHb9fCx8cbqanqfGRv7ejRoxARXHjrgXKfchgMgneHtUfhvOHYPKUPQnxMOPa6Mn2gU3ItzJ49+5bqzp49G53bpNhtmmd/mA1fbxP2rnyh7Lr8LW9BRHD8+HGVHrl9q1evLsuUUaNGObtxVvkcnTFjBjw83FGUn4ui/Fx4e3sjJCRE8xxNS2uM9xfNQ2xMNJ6f9jiaN2+mab1SS5cuRXR0FP48egBjRj4AEcH+/fsdUnvhwoUIDQ1B45QkGL28YDabHZajr77yCvz9/ZDRthVqxsUiJjraYQcgDRs2wOiHhmH/rk1okp6Kli1bomvXrqrXCQ70x6Yne1c6Ryd0TsaIEbfWvzds2IAa4SGVztGi3fMRH1cDn3/+uUqP2j4Xy1GqwgaJSLyIuImISZSP/C+LSGerfVaIyGoRCRaREBFZIyLLrG5vKsrZvZ6irN5yhyjLSLrs6i3Lli2Dh4cH7urdE7dltEFio0YO+fJkcnISRjxwL8LDqiE6KhIzZ87UvCYAPJKVhSED78arL0xFg3p14OnpqfnUoFJJSYlYunghUHASC96eiYSEBE0aiK09e/bA3d0dm/63Big4iZjoKGRkOGa+9uHDh+Hm5oaC00eAgpO4LaMNTCaT6nXOnDkDEUHuP4aUNc7j/xgCD3c3XJ77YNl1abGhZWfvmteNLvvS8M1avnw5asVEoHDXO1c1zren3YvWjRPKXbfto2kwGr1w6dIllR759Tn4zJ0uc/Snn36Cm5sbbu/WGYP634WQkBA0btxY87qDBw9CZocMhIdXQ5O0VDwwbJjmNQHlICA1JQmvvDAVqSmJMJlMDlv1a/DgQXj6iQlAwUls/f4rmM1mh+QooBzw1YqLReG54/jwvQXw8fF22AGIn58fNn/3BVBwEpPHj8Xd/frBz89P9TrR1cOxdnz3SufoiIwGGD9+/C3VPHz4MDw9PXDyu5mVytGzP8yGxWxy2IEnwE9ASFtTReSQiPwlIidE5DtR1qK3FiAi/xGRM6J8yfJdufrF2EeU9evPi8hPoiwlWRGnN04AePXVVxEUFIiAgACkpqY65E194MABtGnTGu7u7hg4YIDD5i7v3r0bRqMRvr4+CA0NwfhHH3VIXQDo3/8edOnUAd+s/QRtW7fEQyNGwGw2a/Z3KUrNnj0bnp6e8PP1RfWIcBgMBvj4+GDOnDma1gWUZXFTU1PQtnVLDL13ALy8vNCkSRPV6xQXFyOpQT3MGdym3BzlzAaRWDG2CwrnDceBF+9BqK8JOdMH4tdXBsDL0wO//vrrLdUtKChASHAQ1r4z4arG2TKlNhY8P7TcdSPv6YAhgweq9Kgrx8GNc6roNEcXLVqE4OAg+Pn5ITEx0SE5eurUKfTp0xvu7u7IzOx4y99pupG6QUFBsFgsqBkXi06dMh12IuelF19Eg/p18eVnS3Hf4P5o0aK5Q3IUAFo0bw6j0Yga1SNgsVjg5uaGsLAwh2Tp4EGDUCchHmNHDYe3tzeGDRuGtm3bql9nQH+Mui2xUjlaMGcYqgf7Y+XKlbdct2Xzpnht0t2VytE5U4cgJanR3/G7dEQuwyUapzMMHz4ckZGR8PT0RHh4OOLj4x1S98iRIzAYDAgNDUXNmjWRnJyMZs0cM23h8OHD6NKlM6Kjo3D33f3w3//+F1FRUQ6p/fPPPyMtrTECAgIQFlbNYd+5OXToEBITExEWFoaQkBBkZGSotvytrbfffhtJsRG49PaVM3UHXrwH7epWR6MaQUiOCsZHozJROG84JndLxe1dO6tSd+LEiWjbpD4ubHu7wjnMRbvnY9+nL8LH24JNmzapUreydNA4maNOytFq1aohNjYWSUlJDsvREydOYMjgwYiJicFtt7XHW2+95bAc/fPPP9GlS2f4+/ujffsMh34Jfd++fYiMjERISAji4uLQq1cvTbJ048aN8LWYypYyv1aO/t/wDoiLjlTlBOJ7772H6BrVkPvtv66Zo6e+n4WEuBqYO3euCo+28nSQo6Qzum2cepSdnY0mTZogMTERSUlJ6Nixo0OXziyVkZHh0C+hO8q5c+cQXzMWozsklpsuYLstH9MZFpMR33//vSp18/LykJTYEH06NcG5zXPsNs2fVjyPuKhwZGWNU6XmjY5PqnbjZI7qiKvkKFA1s7S4uBhdMjugY6NY/PXm0ApzdMe0vgj288b8+fNVqVtYWIjed/REWsNaOPr163ZzNPfbf6Flah107tTRodNYAV3kKOkMGyeRin755RfERtVA1+SaWDexR7kDkQMv3oNHOyfDYjKq/ge8cnNz0bJ5M4QE+WPi0K747r9PYOfHz2Ll7HG4s3NTeHl5YtKkiQ6bpmJNB42TOUqkory8PLRomo7GNSPw4cjMcot7HP/HELzctxkCfCyYNnWqqnUvXLiAgQPugcVswv192uKL+ROw8+Nnse7fkzC8X3v4eJvRp3cv5Ofnq1q3MnSQo6QzbJxEKjt+/Diyxo1DgJ8vakWEoE2DWDSuXQOeHh7o3fN2zaZAFRcX48svv0Sf3r0QVi0Evj7eiI2Jwvjxjzr1r0TroHEyR4lUdv78eTz//POIrhGBiGB/tK4fi2Z1omHy8kTbls3xySefaFZ727ZteOCBYahRPRw+PhZUjwjDfffdix9//FGzmtejgxwlnWHjJNJIfn4+Vq5ciYULF+KDDz5ATk6Os4fkFDponMxRIo0UFhbiyy+/xLvvvovFixdjz549zh6SU+ggR0ln2DiJSFM6aJzMUSLSlA5ylHSGjZOINKWDxskcJSJN6SBHSWfYOIlIUzponMxRItKUDnKUdIaNk4g0pYPGyRwlIk3pIEdJZ9g4iUhTOmiczFEi0pQOcpR0ho2TiDSlg8bJHCUiTekgR0ln2DiJSFM6aJzMUSLSlA5ylHSGjZOINKWDxskcJSJN6SBHSWfYOIlIUzponMxRItKUDnKUdIaNk4g0pYPGyRwlIk3pIEdJZ9g4iUhTOmiczFEi0pQOcpR0ho2TiDSlg8bJHCUiTekgR0ln2DiJSFM6aJzMUSLSlA5ylHSGjZOINKWDxskcJSJN6SBHSWfYOIlIUzponMxRItKUDnKUdIaNk4g0pYPGyRwlIk3pIEdJZ9g4iUhTOmiczFEi0pQOcpR0ho2TiDSlg8bJHCUiTekgR0ln2DiJSFM6aJzMUSLSlA5ylHSGjZOINKWDxskcJSJN6SBHSWfYOIlIUzponMxRItKUDnKUdIaNk4g0pYPGyRwlIk3pIEfJRYwTkWIRecbm+igRWSEiZ0UkV0RmioiHzT6jROSwiJwTkc0i0voaddg4iUhTTmyczFEiqhJ4AEKOUEdEDorIdinfOA0islNEFoiItyhNdIeIvG61T18ROS0irURpqCNF5C8RqVFBLTZOItKUkxonc5SIqgwegJDW3ERko4j0EJF1Ur5xthWRiyISaHVdD1Eao2fJ5a9EZIbNfW4VkScqqOdSjXP16tXOHkIZVxoL4Frj4Vjsc6WxAK4zHic0TuaoC3Gl8XAs9rnSWADXGo+rjIUHIKS1J0VkUcnPto1zjIjstdk/QpQpBg1LLp8SkX42+7wlIh9WUM+lGmdWVpazh7hwegwAACAASURBVFDGlcYCuNZ4OBb7XGksgOuMxwmNkznqQlxpPByLfa40FsC1xuMqY+EBCN2MBaI0t6KS/9puX5XslyQiv4pIQMll28b5pIh8b3PfppL7aFFyuVBEOtns85KIfF7B2Ng4K+BKYwFcazwci32uNBbAdcajUuNkjlaSq/y7l3Kl8XAs9rnSWADXGo+rjIUHIHQzLCISdI3NV5R5xjtEpJfV/3cjZ+4alFy+qTN3OTk5yMvLc/o2atQop4/BFcfiauPhWFx/LK40npycHDUaJ3P0b/bv7orj4VhcfyyuNh5XGYtKOUp0lRhRzuzlisiJku2SiOSLyK6SfdqIyAWxP3fZq+TyVyIy3ea+t0jFc5driPKC5saNGzett4q+xK2WGGGOcuPGrWpvWuco6YxBRKrbbBtEWZklzGqf7SIyX0R8RCRaRLZJ+dVb7hTl7F0rUb5Q+ZAoS01W9II1lNzmx40bN24abjVEyRstMUe5ceNWlTdH5CiRfCX2169fKcrZuhMi8k+5snJLqZGizIHOF2X9+laajpKIyHUxR4mIiIiIiIiIiIiIiIiIiEgD40RZ8cXetIQVosx1zhWRmaKsKmNtlIgcFpFzokxLaH0T9XuIslLNqZJts4j0sdknQET+K8pfIz4lypr+/jb73CnKajb5IrJHRO64ibEMEpFvReRPUaZifCVXluIs5SUib5Tcnicin4hIpM0+7UT5kmq+KH99ecRNjEVEJFFEPhWR30X5N2pvZx9HPTcVmSYiR0WZvvK1XFk5SE39ROR/ojzfRaL8YTlriSLyjSivwyMi8rSG43xRlL+cnVdyf+/J1f/+jnrvTBGRX0TkTEmdz0RZdtaaI58ba8vk6tdsO7n2+6Iy7y1XxRwtz5WylDmqYI7axxwlcoI6oryAt0v5xmkQJRwWiIi3KEGwQ8p/MbOvKGHdSpRQGCnKG+9GV2SIKNlKtRaR8yLSyOq6VaKsuR8oyhKba0XkY6vbm4pIgSjLbXqISO+S+0i9wbE8JCIdRXnM7iIyVpTwq261zxuiPF+RonxpdaEofxW5VLQoITWiZCxtRAm2njc4FhGRuiIyVEQai9Iw7DVORz039kwQkWwRqS8iRhF5QZRwtqhw39Y6itI875OrG6ePKL9YPCdK8DYUkRxR/u20GOfzIpIiynPpJ8ovLdusbnfkeydervyS5CEij4jIH3LlS4mOfm5KDRaRNVL+NRsj139fXO+95aqYo1dzpSxljiqYo/YxR4kczE1ENopy5mydlG+cbUXkothfmrL0y5lficgMm/vcKhUvTVkZBlHC5LwoAS+iNCHrv0osopyNKJYrR/XzReQjm/taKiJzb2EspU7LlTe3UZSzDt2tbg8WZWnPliWXp4hydsLaa6I0tFth78yds5+bQyIy2uqyuyhnkAaocN/2tJWrG+cQUZqF9XVjROSA1WUtx5lUMqbSBuas945RlLPwRaK8JkWc89xEivJl7Ugp/5q93vuiMu8tV8QcrTxXyFLmKHP0WpijRA7wpCgfM4vc2B/nKg3pU3Jjf5zrWvxEaU4XS2p8I8obSUQJnQI7/88FufIm2yoik2xuf0yUj2RvRVNR3rixJZcTRQmmMJv99smV8FkqIrNtbr9HRE7e4ljsNU5nPjd+JWNqanP9Grn6byaoxV7jfE2Uj8ytNS/Zz0e0H+dEUZpPKUe/d7qK8t4pFuUvdr9qdZsznps1opxtFin/mr3e+6L0F5BrvbdcEXO0clwlS5mjzFF7mKNEt2iBKC/WopL/2m5fleyXJMrRdUDJZdvG+aSIfG9z36aS+yidx1soIp1s9nlJlI+xb2Qs1rxEmVc7Sa58/DlQRI7Z2fcPEelf8vMvIjLc5vYRIrL/FsYSJcrc0mlW17UquQ+jzb4bReTxkp+/EGV+q7XOojTfUjczHnuNU43n5maVnpmpY3P9YhF5+xbvuyL2Guc8Efk/m/3qluxXXbQdZwdRzsh1tLpOjffOzQgQZUqA9bx/Rz83I0VpnKWKRSSj5OfrvS8q895yFOboFbZZ4UpZyhy9OczRijFHiW6SRZT5qxVtvqLMG9whylzWUjdy5q70i1XXO/tQmbFUZJUoXy4TUc5OnbezzwUR6Vby8/XOTt3oWGqLcjbG9o2u1lm7m3luKjpzd6vPzc3S+5m77qKcMethc70a752bZRBlPnDpvH9HPjc1RZknHWV13Y2cuavMe8tRmKNX2GaFK2Upc/TmMEevjTlKpJEYUV6guaKsknBClKPnfBHZVbJPG1HC1978S6+Sy1/J1W+uLXJr8y9LfS4i/yr5ObpkvLbzc4vkypfN5svVofOR3Nz83ERRAsDe2QJ78ytDRJnyUHpWZopc3ZS0/A6II58bW/bmvR4Xx85dHiw3Nz/3VsY5QJSm2cHObc5873iI8vosnffvyOdmiCiP2zpXikV5nuaIyFNy43OXS99brjh3mTl6fa6YpcxR5uj1MEeJNGIQ5WND622DKKtLhFnts12U0PURJaC3SfkVKO4U5QxEK1G+FPaQKKuc3OgKFINEWYXCTZSPWEeIyGVRPlYstUJEVovyZaoQUc4sLLO6vakoZ7B6ihIed4jyJrzRFUpaiLJs5Jhr7DNLlLNhUaKcYVso5QMhWpRVKoaL8ry0lvJfvrxRRrny0XOnksvuVrc76rmxZ7woU1AaiIhZlJVNckT91VvcRHncmaI0TkvJZYMor8+jIvKsKM9TQ1FWI7FeoUTNcY4W5d+zojB35HtnjIhUK/k5VJSP+0/JlfexI58bk1ydK8WirFQTIJV7X1zvveVKmKPX5mpZyhxljlaEOUrkRF+J/fXrV4pyxuGEiPxTrqw+UWqkKG+6fFHOVLW6idpTRTl7UFrnO1GCxVqAiPxHlI9FT4vIu6J87Gmtjygf2Z4XkZ+k/NSIyvpKlHmlZ0vG81fJz5Ot9vESZT3ykyW3rZCrA6+NKAGQX/LYbOcOV1aMXJnjbL1NsdrHUc9NRaaKMn/6nGi3fv0QKf88lP7cpuT2hqKsb58vyhnXpzQcZ7EoZ5POypXXyVkp30gd9d5ZIcpj+kuUBvmxXP0LkSOfG1u2S55e731RmfeWK2OOXuFKWcocVTBH7WOOEhERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERERER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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from plot_utils import plot_snapshot\n",
    "import networkx as nx\n",
    "from networkx.drawing.nx_agraph import graphviz_layout\n",
    "from utils import build_minimum_tree\n",
    "from gt_utils import extract_edges\n",
    "\n",
    "gnx = nx.read_graphml('data/grid/2-6/graph.graphml')\n",
    "gnx = nx.relabel_nodes(gnx, {i: int(i) for i in gnx.nodes_iter()})\n",
    "pos = graphviz_layout(gnx, root=0)\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots(2, 2, figsize=(10, 10))\n",
    "plot_snapshot(gnx, pos, infection_times, queried_nodes=obs_nodes, source_node=source, with_labels=True,\n",
    "              ax=ax[0, 0],\n",
    "              edges=extract_edges(t))\n",
    "plot_snapshot(gnx, pos, infection_times, queried_nodes=obs_nodes, source_node=source, with_labels=True,\n",
    "              ax=ax[0, 1],\n",
    "              edges=extract_edges(gc))\n",
    "plot_snapshot(gnx, pos, infection_times, queried_nodes=obs_nodes, source_node=source, with_labels=True,\n",
    "              ax=ax[1, 0],\n",
    "              edges=extract_edges(gc_tree))\n",
    "if True:  \n",
    "    correct_t = build_minimum_tree(g, root, obs_nodes, extract_edges(t))\n",
    "    plot_snapshot(gnx, pos, infection_times, queried_nodes=obs_nodes, source_node=source, with_labels=True,\n",
    "                  ax=ax[1, 1],\n",
    "                  edges=extract_edges(correct_t))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}