phoenix-interactive.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### *Modelling ancient areas for date palms (Phoenix species, Arecaceae): Bayesian analysis of biological and cultural evidence*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Select **Cell-> Run All** to get interactive maps.\n",
    "\n",
    "(Press the button [^] to show the source code.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Individual evidences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "hide_input": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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+9NPF2VvQ2WWAUT5MIAQCQYQSpWvnr4BoqfFyd5BoLSqOm3aOLi4OMrejsosA4jyYQAhEgwglCrb+P1ZEEJg3pIPZO8gUFpVPXEiGRs2LMfDh9dlb0tllQFE+TCAEAkGEEqV7cKPzkAIgdUb1sveQaCU0vKSAUT5MIAQCQYQSpVtbOLnEELg4/0fy95BoLQqe/BgEj76KEH2dlRWGUCUDwMIkWAAoVTZRr3/CYQQOHbiM9k7CJRWZd95ZwA6d/aRvR2VVQYQ5cMAQiQYQChVtqPiNkAIge++Py17B4HSquyvv16SvQ2VWQYQ5cMAQiQYQChVtu9GfQAhBH759bLsHQRKKS0vGUCUDwMIkWAAoVTZ9h8eCwNDI9k7B5TSbAQH98CkSaNlb0dllAFE+TCAEAkGEEqVbUDoWJhb28veOaCUZmP+/GnYsmWF7O2ojDKAKB8GECLBAEKpsu3UezCc6zSQvXNAKaXlKQOI8mEAIRIMIJQq21adguDRzFv2zgGlNBu5uVn4/PNP8N13J2RvS2WTAUT5MIAQCQYQSpVtQ89OaN2hu+ydA0ppNh48uIbq1U0xffoE2dtS2WQAUT4MIESCAYRSZVu7fnN0Dxwge+eAUqr2zJnDuHfviuztqGwygCgfBhAiwQBCqbK1rVkHA94ZJnvngFJa+c19mIWLOenIyE7BxZx05D7M0thzM4AoHwYQIsEAQqmyNTWzxPAxUbJ3TCilarOyTiMoyB+nTh2UvS1laebNNMQejkLIrmAEJfkjZFcwYg9HIfNmmkaenwFE+TCAEAkGEEqV6+rUO9DW1kFM3BzZOyeUvtTcLDy6mI5HGSl4dDEdqlzN/Wouh3fvXkL79q2RlrZL9raUlZk30xC2NxSBSX4ITw7DxNQIhCeHITDJD2F7QzUSQhhAlA8DCJFgAKFUuS7fcxlCCCxa/qHsHRRKi/JRZhr+jI1CXkgw8oL8kRcSjD9jo/AoUzO/mtM3N/dhFmIPRyEwyQ8xhyIxOW2MZMyhSAQm+SHuSHS5T8diAFE+DCBEggGEUuU6f8tXEEJg3ZZNsndSKH3RR5lp+CssFHmBfngcHobHEyPwODwMeYF++CsstFKHkIcPr+PixeN4+PC67G15Uy/mpCNkVzDCk8MKhI98w5OHIGRXMC7mpJdrOxhAlA8DCJFgAKFUuU5beQhCCOw7uE/2TgqlBczNUo98BPrhcUwkHk8e868xkcgL9MOfcdGVdjpWcvJWCCFw9uwR2dvypmZkpyAoyR8TUyOKDCDRqREITuqBjOyUcm0HA4jyYQAhEgwglCrX8Qt3QgiBk18elb2TQunzPrqYjryQYPXIx/PhI9/wIcgLCVavCakA7S1rf/zxArZvX4Mff7wge1ve1Is56QhcG4BmA1vBxM4cZk5W6DmjN0dASIlhACESDCCUKtcR09dACIEr187I3kmh9HkfZaQgL8hfPe2qqAASHYG84B54lFG+v5rT0pubex0f7/8YXQL6QFtXB1o6WrBv5QYLN0cIIWDX2AUDV4RyDQgpNgwgRIIBhFLlOnDsIgghcO/+Ndk7K5Q+b1UfAVGp1B3miRMjZG9HSb11+zymzpoLl7ruEELAys4JXQYNg/eifmgeH4DOq99D8/AAVLOuDqEl4NypHpK/3KmR95MBRNkwgBAJBhBKlWuf96aimrGp7B0WSgtZxdeAqFTZ2Lx5BerWrYUffjgve1uKY9rnqejVfyAMjUygpa2NJq27YfTsLUhIuY3EQzmI23sUgRsmwXtlX7SI74lWy4PRKMQXhsYmMDQyQfiEGPz086Vyax8DiPJhACESDCCUKle//4yGlZ2j7B0XSouy4C5YQ/A4OkI98hHoh8eVfBcslSpb2gHrwYNr+Prrz2RvT1H+9PMlzFvyAdwatYQQAtXNrREQOhbzt3xV5DknIfU25u3PwIw9hzFvfwYSUm9jya4L6BwYBm0dXVjZOeL9+BXIzS373b8YQJQPAwiRYAChVLm27zEQtVwbyd6JofRlFqgDEtxDXQckLrrSh4/nPXgwCUIIHD+eDJUqGzk531aI7Xk/WLUKJtXNIYRA/WY+GD5tNVYduFHq89HMdV+gsXdXCCHg1qgl9h7YW6btZQBRPgwgRIIBhFLl2rJ9LzRu6SN7R4bSV1rFKqG/6K+/XsKuXeuQ+8/r7t69E/r27Sn9XY4wsmXHR9DR1UPTNn6Yue6LMj0vjVuwHTVrN4AQAp38AvH1NyfKpM0MIMqHAYRIMIBQqlwbNGsHH98esnewKKXFNzl5K5KTt0KlykZmZhocHR3w1VeHNPb8KYcPwNDIBO4tOmDlp9nlcm5KOHgLg8YtRnVzK+jpG+Cd4aNx6/abrYVhAFE+DCBEggGEUuXq7NoYAX1CZe9QUUpL5/nzxzBixDv49Vf14u3x40ciNja67J7jhdGnL08fhZmFNVxcm2D53ivlfo5avucy/EMioadvADMLa8yYt7DUu/YxgCgfBhAiwQBCqXK1snNGaNhI2TtRlNKycerUsZg/fxpUqmxcuZKB/fu3lPpYBdbfBPkjJ7AHnKubw9baAYt3nNPouWr+lq/QqlMQhBBwrtMAm7ZvK/HrYQBRPgwgRIIBhFLlamRSHeETYmTvNFFKy9Zffvkerq51sHz53FI9vuAOZGG4Gzkcjc2tYKmnj0MdArFzzVFZzlkxy5JRx12941ardl3wxcnDxX5NDCDKhwGESDCAUKpME1JuQ0tLC9PnzJe9s0QpLVvv3buCTz/dhitXMkr++BdqsDyKjkB7RxcY6ephm99buOETgNODY5D4T30PTbs69Q6GTUmApa0jtHV0EfzWYFy5dua1r4sBRPkwgBAJBhBKlenS3d9BCIGlK1fK3lmilFYcn69C/79Jkejj6g4dLW2s6twHZ98ejwtBQ3HNty+SNmfIeg5bkZyF4LApMKxmAiOT6hgbM/2VC9UZQJQPAwiRYAChVJnOXHsMQohSzaWmlFZs165dik2b4kv12EcZKcgL8sfjiRGIaOYJIQTmtPHH2bfH4+zb4/FNSCSy2/XE7oTDsp/HEg/lYPGOc2gfMAha2trQ1dNHq3ZdMGvR+7h2/ZsCr4sBRPkwgBAJBhBKlWnrrv1hZGKGq1lnZe8sUUrL1pCQYAwa1L9Uj80fAZnbyhtCCIxr3l4KHxVpBORF523+Ev2Hx6Kuhye0tLSgraOLpl7tMXXWXFz8/jQDSCWAAYRIMIBQqjzHLdgBIQRi5y2UvaNEKS0fS12gMDcLa3v1gpYQGNigRYHwcTZ0nOxrQIrjoqQzeCtiLuo3bQttbR1oaWmhlmtDBhCFwwBCJBhAKFWWK5KzYONQG+5NW+HBg6pVUZpWEO9fxe+HduKPravw+6GdUN2/Kn+bqOTWnUnQ1dVDT/tauN62By4EDcU3IZG4EDQUN3wCcClgkGy7YJXGJTvPY9C4xdLuWQwgyoUBhEgwgFCqLAPeHgcdXT18nq65ysmU5vvHzrXI6+yDpy5OeOpgi6cuTsjr7IM/dq6VvW2VxfXrl6FOHRf88sv3JX5s6pEUGBqZokGzdvhoVRpOvzsJ13z7IrtdT1zz7YvTg2MUFT6ed+qKFAYQhcMAQiQYQChVjjPXHoOOrh7eHR4peyeJVj3/2LkWT+rXw1N7Gzxp4oEn3i3wpImH+v/r12MIKSOPHtuDUeMHIyM7BRdz0vHbg8s4dGkntp5ZhUOXduJ+btEjTqfPHIeZhQ2c6zXC8j2X1eeNlNtI2pyB3QmH1Ws+KvC0q9fJAKJ8GECIBAMIpcpwdeoduDbyhm3NWvjxp5L/MkrpG3n/qnrkw94GT9p44omP17+28cRTexvk+bbjdKw3NPNmGmIPRyFkVzCCkvzRfoM3ai93hsMSOzgssYXLMid03uiDnd8WDHtXrp2BvVMdWNk5Y/H2b2Q/X5WHDCDKhwGESDCAUKoM3xm/BEIIbEzaKnsniVY9fz+0E09dnNQjH8+Hj3ybuOOpi5N6TUgFaK8SzbyZhiF73oJ3dAuEffQ2+mwPQI2FZjCYawCLReZossodTVZ5wH6JDeqvqCeFkJwfvoOrR3OYmlli9vrjsp+ryksGEOXDAEIkGEAorfi+v/NbGJvWQOcewbJ3kpTs/dyrxZrKQgv7x9ZVeOpgq552VVQA8W6Bpw52+GPrKtnbqkRzH2Yh9nAUusV3gBACfWYGoNYyJ5jMN0LNJXawWGQOl2WOaLuuFdqs9YT9Ehv4bmqHn+9+D08fXxgYGmHyhwdkP1eVpwwgyocBhEgwgFBa8fXu0g/GpjXw/ZVM2TtKSnXnt2vReaMPXJY5vXIqCy1ajoCUrbkPs3AxJ11a53H+zjGE7ArGqP1DEL5tCP6zNQhmC6rDZrEVnD5wgP0SW1gvtkTLxKbwWe+FJqvc4fyBI7z8OkNbRxdj5m6T/TxV3jKAKB8GECJR2QPIqoM3MXfTKSQcvCV7Wygtjfk1P+LmL5K906RUd367FvVX1IP9Ehs0WeUB77UtipzKQl9hSdaA5Gbh0cV0PMpIwaOL6VDlcrvo531xnUfIrmCM2P8ufDe1w8TUCExOG4PgpB4wmW+Mmkvt4PSBAxyX2sNykTkaLnVHvQg3WHWxhY6jHoQQGBK9XPbzlCZkAFE+DCBEojIHkFnr0uHi1hRCCBgYGqFeQy90CR6KsEnxmLUuHQkK3g2EVg3/rfnhhdzcUhYlq+Lez72Kzht9YL/EBm3WesJnvZfk81NZOB3r9RbcBcv9n12w3AvsgvUoMw1/xkYhLyQYeUH+yAsJxp+xUXiUmSZ7+yuCmTfTELY3FIFJfghPDsPE1AiEJ4eh6+YOqPthLTTsWx9+Yzrj7d39YLagOizjLGD+rjkMfYygba8DoSUghIC2qS70G1dDYPRE2c9TmpIBRPkwgBCJyhhAVqfeQejo+dA3qAbbmrWx+MN4RE6cgg5de8HGwQVCqE/ghkamcGvSGl37jcDQyaswZ+NJrE69I3v7Kc03v+bH0ePsvJXWQ5d2wmWZE5qs8igQPvJtssodLsuccOgSpw4Vx4J1QOzUdUB820nh46+wUOQF+uFxeBgeT4zA4/Aw5AX64a+w0CofQvLXeQQm+SHmUCQmp42RnJQ6Gu4rXFHd2xR127nBtWsj6NjqStcrrRraMGhuBJsBteE8uQmqz7OF+7IOWJlyU/bzlKZkAFE+DCBEorIFkMXbv0GjVr4QQqBnv1DcyblY6CJw7fpZbEzailHjJ6FtZ39Y2taUTvJGJmZo0Kwd/AZEYPi0RMzb/CVDCZXFuDVHoaOrh8EjxsjecVKyW8+sgsMSW3ivbVFkAPFe2wIOS+yw9UwVXTxdmulSRVVCz81Sj3wE+uFxTCQeTx7zrzGRyAv0w59x0VV6OtbFnHSE7ApGeHJYgfCRb9PhLSF0/rkW2ZrBso0T9PpVg84EfRjPNYfjYg84Lm4Is/l2sFvkivDtG2U/T2lSBhDlwwBCJCpTABkVux4m1S1QvYYVEtavK9GF4dKVTKzdshHDIifAu0M3mFvZSaHEpLoFPFp2RI+3xmBU7Hos3PZ1mYSShNTbmLc/AzP2HMa8/RlISC37KWGaeA5a9iak3Ea9hl6wrVkLP/18SfaOk5LlCMjLLcvpUo8upiMvJFg98vF8+Mg3fAjyQoLVIacCvHY5zMhOQVCSv7TOQxr9SIlEkz6tIIRADS9btFn0H3iv7IsW8T3h9kEbWC10gdl8O9SYbwfLBU5wX9ahyoWPxEMMIJUBBhAiURkCyPK9V9C2ewiEEPBq3xXfXy6bnYLOf/clEtavQ9iosfBs64vqNaykUFLd3BqNvbqg58AJiJi1qcSFn+L2HkXghkn/XGQC4L2yLwI3TELc3qNl9r5o4jlo+fjO+PchhMDm7dtk7zQpXa4BKdqyni71KCMFeUH+6uMUFUCiI5AX3AOPMlJkf+0a959RpqzDGxG5ohsi9g2RwseE5HA4t3aFEAJ1gz3htaIP5uw7VeCHo/iD2Yje/QlGJK1B9O5PqrN5JmQAACAASURBVNS0q+dlAFE+DCBEQukBZNIH+2Bt7wIDQyPMmLugXBfq5uZex9lvT+LDxES8M3w0mnt3gEl1cymUmFvZo2kbPwS+OxFj5m7Dkp3ni2xz3N6jaJ8wEM3jA+CbOBQ91o6Bb+JQNI8PQPuEgWUSEDTxHLR8XLzjHIxMzODbo4/8HadKYsFdsNz/2QXLveruglUO06U4AvKS9+W5Uaa/gvxxvos7tg5wxdI1byN8+zBY1LOHtp4Omo8IQPP4AARtiOFI9UtkAFE+DCBEQqkBZNWBGwgIHQstbW24ejTHya+OynJxyc29jtNn0rF05UqEho1E45Y+qGZsKoUSS1tHtGgXgOCwKRgVux6j4tbDK7IPag9tgRYje6odEYDmw3ug2TB/uLzTFC2G9sS70R/g3agP8M74JXhn/PsYOHYR3h6zEG9HLsBbo+chJHwOQsJnY8DIWeg/Ig79h8ei37Dp6PPeVASHTYZ73w6w7+kGt6A2cAtsA9fereHayxv1enrBtntduAa0RvcB4fAPGY2wSfGYs/EU17pUEL19+7LmRzlYsA6IHVyWOcF3U7uqFz5U5RQWuAak8PtcxCjTL2F9cKa1E9Z42cLU3Bj6ptXQMqa3+seh1YP449ArZABRPgwgREKJAWTmui/g4tYU2to6GDZ6PH67V7GmTuTmXsfJL49i0fIPMeCdYfBo5g2DasZSKHkTtbS1oa2jCx1dPejq6UPPwBD6BtVgUM0YhkYmMKpmAiMjY+gb6UHPxAD6ptVgYGYEAzNjGJqboJqFCQwtjGFgaQRLOweYW9tLxzatYYUmrbshaHAMJizaheV7r8j+WVc1xy3Yzpof5Sgroastr+lSBTvcQ/A4OkIdZgL98Lgy7oKVm4VH54/h90824o89G/Ho/LF/A9YrAtnWnr4w1dGGnYkBGsV2gvfKvgjaEMPw8RoZQJQPAwiRUFIAWZ16B2+Nngc9A0PYOdbBvoP75L8AFdMHD7Jw4fuv8MmJj9B9VWeMTApDxI5hiNw1HGM+HoExn4zE2D0jEfnJcPTa1B1Hv9+Pu3ev4Ld7V/HgQdZrp5Y9P8x/398HX/g44NC73li6dmChnVaiUyMQnNQDGdnqzsXlq19j9Yb1eHd4JBq39IGhkYkUdpzqeKB9wCAMjl6GWevSOUpSjq5IzoK1Qy3W/KDlbnlOlyqwsD24h3phe1x0xQ4fRe3qVYzX+XjUYDxp7I6njg5q69fDXwMC8cf+LXh0/liR7/EHvl2go6WN1tYOyGjni6Wrt3KDkGLKAKJ8GECIhFICyKKks2jUqjOEEOjVf2CR2+sqwddtwxiePAQhu4JxMaf4F/4Xh/nvjhmElB518E0bF5wOaFQohLzuOe7dv4a0o6mYPmc+uvfuDweXetIoibFpDTRq1Rm9B0Vh7PztWLbnkuzfjcpiQOhYdc2PExW4o0Yrh+U9XUpBldAL1jWxVdc16eyDP3a+fGreo8w05PUJwFMXRzyp44In7m546mCLZ8ZGeGZUDU+dauKvAYH427edNMr030mRiGjmCSEE+tRrhMwB4chu1xO7Ew7Lfu5RigwgyocBhEgoIYCMnLFOvb2uuRUSN26Q/YL1Jr6qEFXMoUgEJvkh7kg0ch8W84L9T0fir97dcS+sL34J7YF7YX1xbKA3dgTXwUWfukgb0gZTUiNL/xyqbFy/cQ7rtmzCe+Hj0Ny7A4xMqqtHSbS04FCrPnz83sKgcYsRt+ZzJKTcRkLqbczZdxKRO7YicsdWzNl3SmO/8ClxlEaq+TGSNT+oZqxy06WKsGBld49/Krt7FKjsXuhxuVn4c8YEPGngiidudfGkWSM8s7XGMwtzPLO3xTNzMzwzr4EndV3wtI4L/nqrDx6MD4d/7XrQEgLjmrfHmdBxuBA0FNd8+yJpc4bs5x+lyACifBhAiERFDiDL91xG2+7/gRAC3h26VZpFuZk30xC2NxSBSX4ITx6C6NQIhCcPQWCSH8L2hiLzZvEv/I8upiO3izfueNjjjrMpchyMccfZFFcb2yG1qzOS/VxwulMdzNs0qNTPUZQPHmTh2InPMHPBYgT0CYVTnfrQ0tKCEAIGRsYwd68J0y5WMBlsAbMZ9nBc7IHOie+Vao5zwsFbWLzjHGasPoJxC3bgvckrMWDkLPiHjIaP31to0robajdoDis7Z2mtjbaOLgwMjWBsWgNmlrawsnOCnVNdONZxR636zVCvoRfcm7dHY68uaO7TA606BaFNtwHo0HMQfIOHovuAcAS8PQ6Bgyeh37AZCAmfg4FjF2FI9HIMm5KAUXEbMGbuNkxYtAuTPtiHqStSEJv4OeZsPIkF2zLx/s5vsWzPJaz49PprAxFrftDSmPswCxdz0pGRnYKLOekl+kEhX0VOlyor719Vj3zY2+BJG0888fH61zaeeGpvgzzfdoWmYz26mI68Xt3w1K0unrRsiqfONdXhw9EBz5wc1CHEogaeutbGkzq18EO92mhiZQsDHV28374Xzr49HmdDx+GGTwBOD45BYgqnXhVXBhDlwwBCJCpqAJm4dK+6Q2lohNh5C185J74sLsSaNvNmGmIPRyFkVzCCk3ogZFcw4o5ElzgYXFsTi7u2xshxMMZNNyvc8LDDTTcr5DgYI7t2dRzv7oqvWjtg7MJ2pX6O4nrr9nnMX7sQdYLdoN/AEFpG2tLULR1rPRi0MIJzSGOM/GAdlu25hDkbT2HSsv0YFbcBA8cuQuC7E9E5MAyeHQNRv2lbONSqD9MaVtDS1i60GF9P3wCWtjVRt0ETeLb1Rffe/REaNhJjJ03DjLkLEBM7G+NipmPU+El4L3wc3n5vFPoPfA+9BwyCf9B/0LlHMHx8e6BVuy5o5tUeHs284erRHC71PODgUg/W9s4wt7KDiZkFDKoZQ0dX7402D9DV04ehkSlMzSxhbmUPa4dacHBxg3O9RnCq48GaH7REPn/+CEryR8iuYMQejirdv20FTZcqS38/tBNPXZzUIx/Ph498m7jjqYuTek3Ic497lJGCvzv7qANI88Z4Zm2pDh1O/wQQR3t1AKnlhLNtvOCsowtrPX0kdQjENyGRuBA0FDd8AnApYBB2ruGicwaQqgUDCJGoaAFk1YEb8A+JhJa2NtwatsCp06/eXrdML8Qa9k2DU+6DqzjZvyXuWhjgjpsNbjZ2kLzR0B45Dsa47WGP3D5dcTZ9Y7mHs9yHWZjx2QQ0WOEKt/i6aL3GE03nNIHLu3Vg0c4GujX1IbRfsruXlhZMzCzgWMsNjVq0QYeuvdDnrcEYFjkB02bPQ/yaRHy8/2OcPH0Ut26fl2WR9oMHWfjp50vIvvktvrt0Gl9/cwInMj7HZ8cOITk1Gbv27saWHR9hzaaN+DAxEYs/jMfsRe9j2ux5iJ4Wh8iJUzB8TBQGjxiDkMEj0Cd0CHr2C0W3Xv0wacZMfPGFcjZVoPJZcAQ1DBNTIxCeHFZmo5ul8bffrmLrziT0HzQUznXd0cy7A0LDRmLR8g9x9MRnuHf/muzv24v+sXUVnjrYqqddFRVAvFvgqYMd/ti6qsDjCoyAeNTHM0tzdehwKjgCkmpvBxNdPTQwNMZnXfvjmm9fZLfriWu+fXF6cAzDBwNIlYQBhEhUpAAyc90XcHFtAm0dXQyLnPDa7XUr4oVYk17J2IkT7RyR3cAad53McbORQ4EQctPVEr9ZVsNvI0M08qvmxZx09NrWDW7xdeG5plmBitM+673gmdgUdRfXgudkT0xaEItN27ch7Wgqvrt0usJtpaxpV6xYAH19PVy+fEr2ttBiKNOoQZmvIXsDb9z6Fu/Hr0An/yAYmZhBCAEzCxu07tofjb27wtza4d8RSwND1PNohp79QjFl5lx8nPwJcn74TtbPsLQjIM+vAXla2xnPrCz+HQFxdMAzixpYbWQEHSHgY1MT33TojaSNJ5G0OQO7Ew6r13xw2hUDSBWFAYRIVIQAsjr1Dt6KmAs9A0PYO9XB/pT9iroQy+W3KatwyssWX/Zwx4/11CHkTn1b3Gxojzv1bfGroxl+sa6Gy6tnaKQ9Gdkp6LzRB27xddFmnWehANJmnSdcP6yLzpvaSVsAU7X37l1BSsp22dtBX2+BdRNB/up1E7FRGlk3UR676JXEzLMnMHHGLDT1ai9NS3Ss44GA0LGY8uFBJLzQsV6y6wLGLdiBfsNmwNu3L2rWagBtbR1pm29757ro0K0XwifEYN2WTbj4/WnNfZalXAOS/x3I3wXrmbkZnplVxzM7azypXh1RevoQQiDE2Q3X2vpznQcDCHkOBhAiIXcAWZR0Fg09O0EIgd4DBhX7VzG5L8QVwSsZO3GivROO9vbAl70aI7tpTfxcyxJ3nc3xcy1LZNe3xpmWdriSsVMj7SnOCIjbh3XQ66NulfpzeVOTk7fi4UPWAamIFlXZ+nF4GPIC/fCXBnaOyshOQVCSPyamRhR53nuxxs+b+uBBFvan7Me7I8bAua67tMGDe/P2CAmfjXmbvyzxOX9FchamxKdg0LjF6NR7MOo2bAXDaibSaImZhTWat+6It98bhcUfxuOLk4fLbQpXwV2w3P/ZBcv91btgPfddeDxqMJ641cEzYyP8YaCPID09aAmByfWaILttD67zYAAhL8AAQiTkDCAjZ6yFcXVzmFlYY82mjRX6QlwRzX1wFUeG+CDDywZHQj3x+dutcCqoKb4KaIRTgY2R0coGR8LaIfeBZqY3vbgGpO26VlL4aLuuFVw/rAP3Fa6YcTiqUo9MvYknT34KIQQ+/ljZ201XSsu7dkYx1MQPLz/+dAmJGzcgoG8oaljaQggBI5Pq8OocjGFTErDsk+/L/FqQkHIbczaexPBpiejx1hg09uoCcyt7KZQYGBrBtWEL9O4/EFNnz8PeA3vLbApXwTogduo6IL7tXhk+nv9OPDp/DNdiY9DEzBzVtLWR2KAl13mUkwwgyocBhEjIEUCW77mMNt0GQAiB1h39cPnq1xXyQqwELxxeiy+610OGlw2O9nbHkZAWONrbHRleNviiez1cOFyMi2gZmnkzDX22B8BlmSPqLHdBi8QmaLG6MWovd4HLMif02R5Q6dfmvKnHju2VvQ20sOVZPby4ltfU0++vZGLmwsVo3dEPBoZGEELAys4ZXYKHYsKiXVh14IYsHc4lO89j7Pzt6Dt0Grw6B8PBxa3AFC4Hl3ro2L03IqJisH7rZnx/uZRbtZeiEnq+nx07BEubmjCzsMHcmRu4zqMcZQBRPgwgRELTAWTikj2wsnOCQTVjzFywuNS7GXENyL9eOLwWR4b44ER7J5zyssOJ9k44EtZO4+Ej38ybaRi1fzAar3KH01IHOC51QONV7ghPHsLwUQIPHPgIt26dlb0dVO2jjBTkBflLla0LGR2BvOAeeJRRvqOuZVFH6OHDbBw98RkiomJQv7EntLS0oKWlhTruLRA8ZDLi1nxeYQt6xu/PwpQPD2Lg2EXo2Otd1PXwlOr/CCFQw9IWLdt0xqBhEViyYiWOZ3yOBw8KXwfu517FoUs7sfXMKhy6tBP3c0s+UrxuyyYYGpmgZu0GmL/1tOzvTWWXAUT5MIAQCU0FkOe3163f2BMZmccqxIW4spj74CquZOzEtymrcCVjp8amXb20PQ+zcP7OMXxyfiP2nN+I83eOVYkwWFb++OMFWFiYY9q0cbK3haqtCCMg+ZamjtBv964iafcODHhnGGxr1pZ2p2raujveGf8+Fm//RvYOZmlNSLmN2RtOYPi01fAPGY1GrTrD7J/pY/lTuGp7NEKnoJ4YPX0ipqyfgnaJreGyzAkOS2zhsswJnTf6YOe3xf/RZsqsudDW1kGjVp2xfM9l2d+DqiADiPJhACESmgggM9ceg3O9xtDW0cWIsdFluqCwrAr6UVrRPHPmMHKrSFE4RVgB1oA8b3HqCN26fR5LV66Eb48+MDatASEEqptbo51/KCJmbkL8/izZO5Xl6eId5zAwbjE8+neEpacTDO1MILT+qT+kJaBna4DqLS1gFWiDGsNqoO782q8NIffuX8OAQUMhhECnwCFYdfCm7K+zqsgAonwYQIhEeQaQ1al3EBI+B3oGhnBwrovk1GTZLsSUKtUTJ5JZpLCCWGAXrFGD8dfwQfhrQCDyunbAYw3sglUcz5w7iZjY2Wjm1QG6uuotYWvWagD/kEhMXv5poa1yK7Nxe4+ifcJANI8PgG/iUPitGQ2zWfbQGaEHwyATmLSxhKGLCbT0taXREl0zfbRo2wnvDB+NpStX4uSXR6UpXHdyLsK7QzdoaWtjwMhZsr++qiYDiPJhACES5RVAFiWdgUfLjhBCIPA/78hedIpSJfrw4XW0a+eNXr26yd4WqlbafrWxO546OuCpowOeNHbH41GDZQkgubnX8emhZAwZNRa1XBtKW+XWb+aDASNnYe6mU7J3HOUwIfU2AjdMQvP4AASsHYee68ajzaoBqDanOkzmWsF4rjksFzii3hIv1HvfCy6Tm8DibUdU62iK2s2aw8zC5t8pXNWMUb+xJxxrucHA0AgRMzfJ/vqqogwgyocBhEiURwAZMX2NtL3u2s0l216XUlrQrKzTuHv3kuztoGofZabhryFvIa9rB/z1nyD8NXwQHo8aorFaICpVNn7+5RLWbN6IXv0HwtxavV1tNWNTeHYMxHuTV+KDj7+TvbMot/P2Z8B7ZV/4Jg5Fz3Xj0XPdeLSI7wmDOcYwn28Ps3m2MJ1riVrvN4PrUm+4LvVGnSUtUWO+HUYkrUHioRws3v4Nxsz7CH3CpsKzYyDqN/PBtJWpsr+2qioDiPJhACESZRlAlu25hDZd1dvrtunkX6rtdSmlRXvxYjo2bvxQ9nZUaWVeB/LZsUNo29lf2vXJ0tYRnYPew7gFO2TbKreiOmPPYbSID0CPtWOkAJI/AmI6zxrm8xxgPNcCzosbSwHEcXFDWC5wQvTuT2RvPy0sA4jyYQAhEmUVQKKX7IGlrSMMjUwwc2Hpt9ellBZtVFQ46tWrjd9+uyx7W6qqcu+E1avf2zA2rYHAwZMwY/WRCrtVbkWwqBGQHmvHwnKBMwzmGBcaAam7xAtm8+3gvqwDVqZwYXlFlAFE+TCAEImyCCCho+dL2+t++fUXsncSKK2M3rt3BXfunINKlY2UlO1ISUmSvU1VTblrgTTx9EGztv6ydwSVYFFrQHquGw/PFYEwmlMDurMNUH2eDWq/3wKOixvCbL4d7Ba5Inz7RtnbXll908DMAKJ8GECIRFkEkJ4DJ0AIUW67XFFKC9q3b0/4+raDSqVeqJ6WtgsPHpTd9ta0aOUeAbGyc0T3/qNk70gqxRd3wfJfGwnfxKHSWg+z+XaoMd8Olguc4L6sA8NHOTlz7TE4uNRH177D3+g4DCDKhwGESJRFAFnx6XXUrN0AjrXr46efuViW0vL24cPrUpX0EyeSIYTA/v1boFJl49atswwj5aWMa0B+/uUStLS1MXDsItk7lEoybu9RBG6YBO+VfdEivie8V/ZF0IYYTP/kMKJ3f4IRSWsQvfsTTrsqJ8NnboRhNRMIIVC7fvM3OhYDiPJhACESZbUGZEbCYejq6mPAO8Pk7yRQWoXMzc3CkSMf4/79q1CpstGvXy906tRW+vvDh1yPVZYWqAUSPgSPoyPUIx+BfuVaC+SLk4chhMD4hTtl71QqzYTU25i3PwMz9hzGvP0ZSEitOrVQZHvPU26j9zvR0NLSgneHbggNGwkjE7M3OiYDiPJhACESZbkLVt+h06ClpYWtOzk3nVK5PHp0D/bt2wyVKhuXLp2Eg4Mdjh3bK3u7KpOPMtPUIyEhwcgL7oG8kGD8GRddrlvwJm7cACEE5m89LXvnktJXuXzPZTRr6w8hBMLCx+HBgywsWbECQggs2XWh1MdlAFE+DCBEoiwDSMLBW3Bt3BqWNjWRffNb2TsJlFZ1L106iVGjBuPOHfW/x9jYaEyfPl72dlUKc7Pw6GI6HmWkqNd8lNPWu/lGTY2Frp5+lapkTpXnnI0n4eDiBoNqxohfkyh9f1MOH4AQApM+2FfqYzOAKB8GECJR1oUI523+EobVTNC1Zz/5OwiU0gJOnz4eU6aMhUqVjR9/vIDRo9/D99+flL1d9PX2eWsw7Jzqyd7BpPRljpm7DUYm1WFbszY+Tz9U4Pt7684FCCEwOHpZqY/PAKJ8GECIRHlUQn93wlIIIbAsIaHEF9nch1m4mJOOjOwUXMxJR+7D8v1VkdKq6vHjybC1tcaFC+qtsw8c+IhTtSqwLdp0QmPvrrJ3Mil90dWpd9DnvanQ0tZGi9adcP3GuSK/wzUsbeEfElnq52EAUT4MIESiPALI6tQ7aNbWDybVzXHh+6+KfYHNvJmG2MNRCNkVjKAkf4TsCkbs4Shk3iy/edVUg2p4ygp9vbnPfQa+vu0QFOQPlSobDx5cw7Fje7mAvQJpW7M2ugQPlb2zSenzxu+7Bs+OgRBCYNDQCNy7//Id+Bo2b42W7XuV+rkYQJQPAwiRKI8AkngoB+/v/BbVza3Qsq1vsaqiZ95MQ9jeUAQm+SE8OQwTUyMQnhyGwCQ/hO0NZQhRuAUW7Qb5qxftxkaV66JdWjIfPLiGmzfPQKXKxsGDSRBCSCMid+6ckzWMPHx4HUuXzpLWslQ1f7t3Fdo6ungrYq7sHU5K8523+Us41fGAvkE1LFmx4rXf4x593oJTHY9SPx8DiPJhACES5RVAEg/lIGLmJvWxZ8975Ukp92EWYg9HITDJDzGHIjE5bYxkzKFIBCb5Ie5INKdjKdSC25aGqatIh4chL9APf5XjtqW09N6/fxUHDyZJoaN7907o0ydA+rsmwsj9+1cxe3YMfvrpIr7++jMYGhpIu3tVNb/8+gsIITBm3keydzopTTyUg/ELd8KkugWs7Zxw6EhKsb7HkROnwMDQqNQV0RlAlA8DCJEozwCSeCgH7fxDYWBohJNfHn3pSeliTjpCdgUjPDmsQPjINzx5CEJ2BeNiTvlUF6blqIyF22jZeeDAR/j0021QqbKRmZmG2rWdkVnOwfHcuaMwM6uOjz/eAJUqG9nZmdLfRo9+Dzt3rpX9fdGUG7ZtgRACczaekr3jSau2q1PvYMDIWdDW1kHjlj64cu1Msb/H8WsSIYTAwo/OlOq5GUCUDwMIkSjvALJ87xVY2TnDrWEL/HbvapEnpYzsFAQl+WNiaoQ06jEqeTDe2xuKUcmDEZUSjuCkHsjILt6vLLTi+OhiOvJCgtUjH8+Hj3zDhyAvJFi9JqQCtLfcrQTrYM6dO4qwsFD8+uslqFTZiImJxOLFsWV2/DNnDktFFe/cKbyY9bffLsPf3xerVy+GSpUt3bcyOzluDrR1dLHqIKt1U/lckZyF1l37QwiBAe8Me+k1/WUePZ4GIQQmLN5dqudnAFE+DCBEorwDSOKhHExcsgda2toYMTa6yJPS8yMgQ/cNRIcNrdFwZX3Uj6+Hhivrw3tNc/TY2oUjIAr0UUYK8oL81dOuigog0RHIC+6BRxmVP1xW1nUwkZFDMWvWJKhU6lGK6OhwXL+eWapj3bp1FqamJpg7d8pr75s/DWzkyHfRr18v2d+H8nTAoKGwdqgleweUVl0XbMuEi1tT6OkbYN6SD0r1Pf75l0vQ0tbGwLGLStUGBhDlwwBCJDQRQBIP5cDvP6OhraOLTw8lFzop5a8B6bzJB00TGqJ+fF14rmmGNus80TKxKeyX2KBlYhN8dePQG13EqeblCMg/70MVWQeTkpIES0tzabpUcvJWnD79+n+3ublZUqDYs2cTfv75u2I/50cfJWDFigVQqbLxyy/fV8q6Jl7tu8KjZUfZO6G0ajpxyR5UN7eChbUDklMLX8NLorWdE7r1G1mqdjCAKB8GECKhqQCy8tNsONXxQE0XV/zw4/cFOx8Ps7DnwiY0WOkGm8VWaLG6Cdqs84RnYlO4xddF04SG6LzJhwvRlSjXgFS59+DBg3+34WzevDEGDeoPlSobv/56CV99VTiM3L9/Fd26dcT8+dPe+LnnzZsKU1PjSrdbVk0XV3TqPVj2jiitesYsS4aOrh7cm3rh+8ulG9l83mZe7dG0jV+p2sIAonwYQIiEpgJI4qEcxCZ+Dl09ffR9OwwqlTp47Lu4BSP2vQPfje1g+741LBeZw2axFWovc0bDlfXRYUMbDN03kAvRFWzBX/+H4HF0hHrkI9APjyvRr/8vff1VeBTo7t1L0mjI9u3qBajffPM5VKps/PDDeel+06aNw549m974+X744Tx27VoHlUo9qrJy5QJprYpSffAgC3r6BhgwYqbsnVFatUxIuQ1LW0e41K2Pu3evlMn3OSjkXdg7u5aqPQwgyocBhEhoMoAkHspBj7fGQFtHF19lH8Ko5MGo+2Et2C+xhcsyR1guMof7CjfUXu6M+vH1ELIrSNqWNzo1ggvRFWyB9Q/BPdTrH+KiK334UKm4Dibfu3cvYf/+LdL/t27tiSVLZpXb833++SfQ1dXFkSMfy/7a38Sz356EEAIRszbJ3iGlVcvIOVshhMDHyZ+U2fc5amosdPX0kXDwVonbwwCifBhAiISmA0j/EXHQMzTEkD1vwX2FK2ovd0HrtS3ReJU7TOebwGqRBZolNETtZc5omdgEI/e/i5hDkRwBqQxWgh2gSmNVHgF5lTt2rMHSpeUXQFSqbFy+fEr67/DwIUhN3SH76y6p23aqi0LOXHtM9g4prVo2beMH5zoNilVMuLiu3bwRQgjM25xR4vYwgCgfBhAioekA0nPgBBiYGaPr5g7wWOEGz8Rm8FnvhbbrWsH5g5owmlcNZguqw2JhDZjON4FrfB2039Caa0Cocq1ia0Aqoj/8cB5eXi2wdetKqFTq6Vlyt6m4zpi7AFpaWljx6XXZO6S06rjwozPQ1tZBTOzsMv0+nzx9FEIIjJ2XVOI2MYAoHwYQIqHpANIuKBSGnO7+ewAAIABJREFUNib4z64g1I+vizbrPOGz3gs+673gvsIVhnMNoDNbBxaLasB8QQ24flgb9ktsUH9FPez8tuoUHqOVy6q+DqYi+PDhdWmnrXfeGYBRowbL3qbiGBo2EhY2NWXvkNKqZe9BUdA3qIbsm2W7ocNv965CR1cPIeFzStwmBhDlwwBCJDQdQJp3C4CxU3UM3zcIDVfWLzgCsswR1ReYwnCOAcwWmP47ArKeIyCyWkWnTpW1VXkdTEUzPn4+EhPfh0qVjR9/vIBbt87K3iaVSr2D2Jkzh3H79jdQqbKxa9c6mFtao37TtrJ3SGnVMeHgLZhbO8Av6D/l8j23d6qDzkHvlbhdDCDKhwGESGg6gDRp3xVm9a0QnjwEHTa0hlt8XbRd1wotE5vCerElbBZbwWqRBZw+cCjzNSC5D7NwMScdGdkpuJiTzjBTDCtr8TzZZJircE6ePAZ2djYa2y3r4cPruHbtK+n/339/JhYsUG9BfOfOtxBCYN06daG35OStsLSxR4Pm7WXvlNKqY8SsTRBCYN/BfeXyb6BVuy5o6NmpxO1iAFE+DCBEQtMBpJGXLxxb1EVgkh/e2/s2mq1uBLf4uvBY4QaLhTVgtqA6LBdZoGlCQwzdNxCT08aUyS5YmTfTEHs4CiG7ghGU5I+QXcGIPRyFzJvsSL9MxRTPY6eevoHXr2dix441UKmyce/eFWzYsLxALZPSev/+VahU6lGNqVPHSrtxbdiwHEII3LlzDipVNsaPH4nIyKHS41JStksjICpVNvyDQ+Di1lT2TimtOjb27oparg3LdPH58w4YNBTWDrVK3C4GEOXDAEIkNB1AXBt5w7trF4TtDUVgkh9CdgWj3Xov1P7ACdXmqqdeeSY2LRA+JqeNeaMRkMybadLzhSeHYWJqBMKTwxCY5IewvaEMIUWpkIXTHKGhZemePZugra1dZMHEV3n58iksWDANP/10ESpVNoYPfwetW3tKf3dzq4NVqxZCpcrG1atfIilpNX755ftiHTtk8IhSddYoLY3zt56GlrY2ps6aW27/zqbOmgttbR2sOnCjRG1jAFE+DCBEQtMBxKluQ/TuP7DQiETPbV3Rak0ztFnniUmpowuEj5hDkQhM8ivVGpDch1mIPRyFwCQ/qaZIWRy3squErWMVM0JDFeWFC19ApVJPlQoPH4KTJw9ApcrG119/ht2710v38/Jqgblzp0ClUtccMTQ0wOnT6uBy4MBH2LJlRZm0Z9T4STA2rSF7x5RWDXu+PR4G1Yxx6/b5Mvn+FuWWHR9BCIFZ69JL1DYGEOXDAEIkNB1ArO1dEBo2EipV4TUZX9049NxIxRBEp0YgPHnIG41UXMxJR8iuYIQnhxUIH2UxslKZrfDF8xQyQkOV6/XrmWjQwBV796ortMfERMLe3lb6++zZMVJhxdzcrHLb2nfq7HnQ0tZGQspt2TuntHK76uBN1LC0Q0Cf0HL9tyUV15xZsuKaDCDKhwGESGg6gJjWsMLwMVEvPTE9PzISnNQDIbuCEXckutTTpDKyUxCU5I+JqRFFBhBWWC/aij4CUtHbRyuHz68FuXPn22JPmypLl65YASEEPvj4O9k7qLRyOypuA4QQ+PRQcjn/u8qCnoEh+g+PLVH7GECUDwMIkdB0ANHTN0D0tLhXnpxKslvV8ePJmDlzorS//4tyBKSUVvARhgo/QkNpGblp+zYIITB30ynZO6i0ctuoVWfUqd9EI99r5zoN0D5gUInaxwCifBhAiIQmA8iqAzcghMDMhYvf6MSVm5uF7OxMqFTZ2L17PYQQBba1LHBfrgEptRW5eB5HQGhV8UBaMoQQmBKvmR+JaNV0wbZMaGlpYcbcBRr5Xrft7I/6zXxK1EYGEOXDAEIkNBlAlu6+qJ5KsGrVG524/vOfILRt2woqVcHqxi+z4C5YZbO2pKpYYYvnVfARGkrLyq/OpEMIgbHztyMx5TaSNmdgd8JhJG3OQCLXhdAycs5G9bqMVevXaeR7PXBoOMytHUrURgYQ5cMAQiQ0GUDmbf4SQghs2LalRCeqe/euID5+Pr7++jOoVNn47LPdSEvbVeA+3313QtoCsyjLem1JlbKC1tmoyCM0lJaVN26qixOOHTYDp9+dhGu+fXGjXQCu+fbF6XcnYeeao7J3XqnyXZ16B+bWDhgwaKhGvtczFyyGEALx+7OK3UYGEOXDAEIkNBlAZqw+AiEEPk7+pFgnqPxdZe7evYSaNe2xeHFs0RfoG19DV1cX8fHzX308VkKvdFbYERpKy8jc3OvQ1tZGXEMv3PAJwIXgofgmZAwuBA/FDZ8AXOoxkCGEloneXfrBpZ6HRr7XO/fshhACMxIOF7t9DCDKhwGESGgygExcuhdCCHye/vrOYUrKdri4OOLGja+hUmXjhx9evSf5xx9vwI8/XpC9s0BlsIKO0FBaJuZmwcyg2v9n78zDas77//8+53TOaVFp0UZFJZKtpJAsWaKoMCY7MZjsY8nYiwhZWyTDYET2kpYJo0FDjIlsSUL3jBnk1Bjfe9x+476fvz+OPjRiWk59ziev53U9LpcZznnlOp93r0fvDXOs7fHj8Jn4ccSsNwyfibvu3rgwNpiWYxE1Zszs9RCJRLh1+1Ktf66vXj8PxhgmL46rdH0kIMIPCQiFS10KyPQVytNcLv109r2DUtl+jrt3L2LChJHIz7/AfwNAEATBE89yM9FUuwHG2rUpLx+vueo3Abc9Byv3hKhBE0sIl5W7lFKwISam1j/XZZcRzt+UXOn6SECEHxIQCpe6FJDPFmwBYwwFhTkVDkg//ngCXbp0xI0b7xeUD7Fw4UwsWzaX94aBIAhCVTzLSkF7XX34NWtVoYBcDpiGgq4+OFCFpSwE8T4aWTSF36eja/1z7RcwBgbG5tiS+qDStZGACD8kIBQudSkgo2etBWMMT4pvVzggXb9+Fr17d8fNm+eqNaAFB0/DokVf8N4wEARBqIpnuZnobmyKXuZNaQaEqHW69hsOC2u7Wv1MP32aDwNjM/T0DaxSbSQgwg8JCIVLXQrIJ5OWQq6p/c5g9P33SR88wYogCOKjRZGPAc0d4KZnSHtAiFpn/PwoMMZw5doPtfaZPnzsMBhj+GLNgSrVRgIi/JCAULjUpYAMHDUb+oaNyg1EDx9eg4mJMWbNmqySge3nn6/i2LFv+G8aCIIgVMSQfr6w122oPAXLbwIuB0zDVb/Xp2B5j6JTsAiVsWbvZTDGEL5hY619noeNmwRdfSPEHL9XpdpIQIQfEhAKl7oUkN5DJsGsic07g1FmZiJ+/fW6Sga2NWuWQCaT4sGDiveZEARBCI2xk6bDyKARdw9IQVcf5T0gY4NJPgiVY2Ftj37+AbXyWVYo7sC0cVO4ew2rcl0kIMIPCQiFS10KiEf/kWhm3walpQWIiVmNzz8f+4+3mFeVBw9ykJubyXvDQBAEoSpmBi+CXFObbkIn6oQeA8eikblVrXyW00+mgjGGqaG7qlwXCYjwQwJC4VKXAtKxhx9aO3dGaWkBNm5cgbFjA7jLBlVNSckdlcvN31+f76aE7r8giI+D0NXKAzyijhXw3pwS9Z/Ji+PAGEP2j9+r/LM8PmgmNLV1EXnsTpXrIgERfkhAKFzqUkBad/SEY3vXWv9mff36WTg6tsTp00dr7T1GjBiMXr08uN8PGTIABw9u595/y5Y13Mb6+/cvq3yTfbkbwP36KW8AXzKbbgAniHpIVNxWMMawZu9l3ptTov6z7kAuRCIRloWvUfln2cqmJTr28KtWXSQgwg8JCIVLXQqIubU9GGM4fz6tVr9ZP316G6NHD8W5c8dV+rpr1y7Dpk1hKC0twNGjO7F7dxRKS5WzIV5ePZGQEIfS0gLExyvvOyksVN4mO2zYILi5deBep3v3LjWq7Vl2Ov4TOBwvfb3wIigQL+ZOwYugQLz09cJ/AoeThBBEPWP0xKlgjGHVN9m8N6fEx4GVXWt49h+k0s/x2R9OgTGGiQtjq1UTCYjwQwJC4VKXAmLfrgscnWp/BqS2mDhxNKZNm1CpP/vbbze4ZVpnziQhNXUfSkuVsuLm1gHJyXuqV4ciXznz4euFF8HT8GL+9DcET8NLXy/8uXQOLcciiHqAQnEHwwMngzEGnxGzeG9KiY+H3oMnwsDYDAqF6pYbT509H1KZHJuO5lWrJhIQ4YcEhMKlLgXEtecgtGzrUmffvJOT9+Dbbw/U+HXy8pTnodf2vpLK8Cw3Ey8D/JUzH2/LRxlB4/AywF+5J0QNGiiCIKrHk+LbGDBkBBhj+GTSUt4bUuLjYmroTjDGkHnuhMo+081bOaFdZ69q10QCIvyQgFC41KWA9BkyGSYW1nX2DbxzZxeMGDEYpaUFOHhwO06ePITS0gL88ksuYmPX4tatLJSWFuDChTTExkZwf2///m04fjwepaUF2L59Ixo00FH5yVqXLmXgwIGvqvz3nmWl4KVfP+Wyq4oEZM4UvPTvj2dZKbw3UARBVI9Hj26hW58BEInFGD0rgvdmlPj42Hj4JsRiCRaErFDJZ/rylXNgjGHsnA3VrokERPghAaFwqdOb0CcugUyupdIp3Q9RWHiJm7FwcmqDceOGobRUuUmcMYYjR75GaWkBwsMXQVtbi/t7Xbp0xNChvigtVcpKZOQqlc98TJw4Gg4O9lV+XZoBIYj6zb9+vg6XLp6QaEgxadFW3htR4uPFxsEZHr18VPK5nrc4BGKJBtYdyK12PSQgwg8JCIVLXQrI+PlRYIzh7r26vyTw0aMbePLkFkpLlUupnjy5xR0BrFDk4+nT29yfrYtlVvfvX8ajRzeq/ndpDwhB1FsK7+XAoZ0rZHItTA/bw3sDSnzc9AuYBl19Izx9WvPvJ607dIGDk0eN6iEBEX5IQChc6lJAvlhzAIwxnD6bwfs3enXh4cNrVf475U/BGocXc6YoZz58vfCCTsEiCEFy41Y2mtm3hnYDPcxdd4T35pMgZq7aC8YY0k+m1uizfTPvIsRiCYZPXVmjekhAhB8SEAqXuhSQkG2ZYIxhd0I879/s1YGzZ5Ohq6uDs2ePVfnvlrsHxL+/8h6QpXNIPghCgPyYcxYWVrbQbWiMRdHpvDeeBBGbVoTNifnQ0JBh9oIlNfp8L1u1BiKRCKvjL9WoHhIQ4YcEhMKlLgVk4+GbyrPsN2zk/Ru+OlBcnIdFi77A7dvnq/cadBM6QQiesz+cgpFpYxg2aozQr77nvekkiLexb9sJbt361Ogz7uLuCdtWLjWuhQRE+CEBoXCpSwGJTSuCXEsHM+Yt5P2bPkEQBN+knUiBnoExTJvYYOXuC7w3mwTxdwaOmg0tHV08Kb5drc/4vftXoCGVYchni2tcCwmI8EMCQuFS1wJi0rgZho7+jPdv/OrEhg3LsW3bet7rIAii7jiYeBDaDfRgZdcaaxNyeG80CaIi5kQcBmMMiSmJ1fqcr90cCcYYVnx9rsa1kIAIPyQgFC51LSDNW7uhh5cv79/81YmAAP9K37BOEITw2f7NLsjkWrBzdMWGQ9d5bzIJ4n1EHSuATK4Fv09HV2sWxKP3AFjaOqqkFhIQ4YcEhMKlrgWkQ7eBaO3cmfcGQJ3g+3Z1giDqjk1btkBDQwZHlx7YfPQ27w0mQfwT3iNmgjGGps0dcTDxYKU/6788vAG5lg4Gjp6jkjpIQIQfEhAKl7oWkD5DJkPf0KTa60nrKwpFPs6cSeK9DoIgao+Q8DUQicXo0G0goo4V8N5YEkRlCd6QBCu7NmCMobfPEFy7fuEfP+/RX20DYwxLt55USQ0kIMIPCQiFS10LyJeblQPI5q2xvDcD6kRc3DqIRCJcv36W91oIglA9XyxYDMYYuvYbjpjj93hvKAmiqsQcv4cR01ZBR7chtHR0MXvBEjx+kvfez3zfgZ/AtIkNtqQ+UMn7k4AIPyQgFC51LSCxaUVo1tIJ7Tp25b0hUCd++SUXqan7aDkWQQgQRUk+cosykVWQgtyiTChK3hyJrVDcwfgg5RKWvp98rrJmjCD4ImL/VXj0HwmRSARLmxaIP7jvnWfi8ZM86Og2hNenU1X2viQgwg8JCIULHwIybu5GuhGdIIh6QXZhOpZkzEbAfn/4xfdDwH5/LMmYjezCdDx9mo/Bw8eBMQb/cfN5bxwJQpV8uTkFzVo4gTGGHv38kJObxT0Xu/btAWMMX246rrL3IwERfkhAKFz4EJDIY3egq2+EQcPH8d48qBNPntxCv36e2Lp1He+1EATxz2QXpiPwyHD4xnshKCkQc1OnICgpEL7xXhhzIACdvfpCJBJh2NQw3ptFgqgNYlLuY/SsCOjqG0GupYPp8xbg0aNb8P10NAwaWah0xo8ERPghAaFw4UNAYtOK0C9gKjS1dXHvwVXemwh1YtKk0di3byvvdRBEaXEe/khLwPPd0fgjLQGlxe9f6/0xoijJx5KM2fCN90Jw2jTMT5/OMSspCIbtTSESizB27kbem0SCqG3WHbiGHgPHQiQWw8LaDrr6RujpN16l70ECIvyQgFC48CUgK3edh0gsxpfLVvDeSKgL//rXFTx+fJP3OgjieUIcXvZ0xytrS7yyMMUra0u87OmO5wlxvNemLuQWZSJgvz+CkgLLycfMw5Nh6mgFsYYE9pM6Iywxi/fmkCDqikXR6bB17AjGGOZGHFbpa5OACD8kIBQufAlIbFoR2nfxQpNmLaBQ0Mbr4uI8tGnjgKlTx/NeC/Fx8zwhDn+1sMMrcxP81bYV/nJzxl9tWyl/38KOJOQ1WQUp8Ivvh7mpUzj5mLZ/IgxtzSCRS9Fxtj+cN/tg8eEM3ptCgqhLtqQ+QOj2Myp/XRIQ4YcEhMKFTwGZuWovGGPYs38v780En5SdfPX115tx8eK3vNdDfMQU5ylnPsxN8FdnF/zl7vqGzi54ZW6Cl55daTlW6bszIJ/vGQ99S2NIdTThvnAYPGMnwC1qMM2AEISKIAERfkhAKFz4FJAtqQ9gZmkL917evDcTfFBScgdTp47H4sWzea+FIEpLC/BHWgJeWVsqZz7elo8y2jrglbWlck+IGtTLJ2/vAQn8agx0TPQhb6iDbiGj4R03E06bveG3PRgxqfd5b9wIoj5AAiL8kIBQuPApILFpRQgICoVYooHLV87x3lDwwYIFM7BmzVLe6yCI0tICPN8djVcWpsplVxUJiJszXlmY4fnuaN5rVQeyC9MxYL03pPpyaBrrotvKMfCMnQCnzd7w2DIKS4+c4r1pI4j6AgmI8EMCQuHCt4BsOHwDci0djJs8nfdmoq5ISYnHjh2beK+DIP5OfZsBKS6+icyMSBzbtwCZGZEoLlbNIQ8KxR1kZX+H5WsioK2nD93GxnAK6w/nzT5wixoMv+3BJB8EoWJIQIQfEhAKF74FJDatCN18RkHfsBF+/e3jOAFqzJhP0adPd7r1nFA/6tEekNTDIfhqkBUOd9BGcls5DnfQxleDrJB6OKTKr1V4Pwc7936DidNno6O7J3T1jcAYA2MM9m07Ye3+KwhLzMLiwxkIS8yiZVfER8uGQ9fh0t0XA0bNVvlrk4AIPyQgFC7qICBLYk+CMYZNsbG8Ny21RVFRDjIzE1FaWoDffruBYgE0cMTHSflTsBxen4LlIKhTsFIPh2Cfux6S28ixu4cBdnibYncPAyS3kWOfu94HJaS4+DYyvkvF4rBV6OcfgCbNWkAkEoExBk1tXTg4ecB7+AxMDd2JiIQrvDd8BKEuhGzLhJmlLcQSDYhEIsxbf1Slr08CIvyQgFC4qIOAxKYVQUMqw9xFy3hvXGqLwMDhaNrUksSDEATl7wExU94D4tlVEPJRXHwTXw2yQnIbObb7mGHHQAuO7T5mSG4jx7Yh1txyrBu3shHz1TaMnjgVbTq4Q1O7ARhjEInFaNysJbr2H4HRsyKwdOspxKTQzAZBVMT0sD3QbqAHc0sbnPo+HbYt28Lcqjkij91R2XuQgAg/JCAULuoiINoN9DFldjDvzYuqKSrKQWlpAQoLL+Hy5ZO810MQlUagN6FnZkTicAdt5czHW/KxY6AFtnqbY6mTLgKbSOHayQWNzK24pVS6DY3RrlNf+I+bj1nhCdh4+CbvTR1BqDtbUh/gk4lLIBKL0aFzTxQUKr/npZ1IgViiAZ+RX6jsvUhAhB8SEAoXdREQA2PzercR/cGDn2Bn1wzXrp3hvRaC+Fg4tm8BktvKsb2fCVb3MsFEJwN4NtWBTUMZNMRK2dAQMTS2bIyefuMxfn4UwnZmYUvqA96bOYIQEpHH7qBz76FgjGHYuEl4Uny73LM4euJUSDSkWLr1pErejwRE+CEBoXBRFwExbWyDgDETeW9eVMmDBz9h1KhPcO7ccd5rIYj6zoOiXOw5sBfDhvuio74E+jIRN7thqCmBs6kWBrfQx5ft9PBNWy2ERcXw3sARhFBZHX8JzVo6QUMqQ1jE+gqfyV8e3oC5pQ1sHJxVsnyRBET4IQGhcFEXAbG0aYWBQ0fx3sQQBKH+PH2aj9NnMxC6ei0GDBkBa7tWEIslYIxBpqkNOyM5hhhL8FlbA4R1M0Nkn8aI7NMYm3ubI9FRjvXeTRGVXMB7E0cQQuTLTcfR0MgMDY1McST5yAef1b2HEsAYQ0BQaI3flwRE+CEBoXBRFwGxceiAPgOG8N7YqJLi4jzk5f2Ax48/juOFCaK2uXf/Clw9ekO7gT43u2FmaYfOfYZixPRwLIr5FjHH7yF07QrsctNDoqMccV0NEdXLDHFdDZHoKMdON32Erl3BexNHEEJkfHAkpDI5bB3aISc3q1LP7YAhIyDX0sHKXedr9N4kIMIPCQiFi7oISMv2XeHR24f3BkeVXL6sPF74+PF43mshiPpA7I7tYIzB69OpmBEWj/UHr713TAlduwIbvK2R0F4bR1vLkdBeG+u9m5J8EEQ1iDl+D15Dp4AxBs/+g/DLwxuVfm4LCnPQ0MgUrTv2rNFeKxIQ4YcEhMJFXQSkbac+6OjuyXuDo0p++SUX+/dvQ2HhJd5rIYj6wISps6DdQL/STUxUcgHComIQEr4EYVExtOyK+OhYvOUEvli9Hyu+Pofo5LvVeo0Nh2+gdUdPiMRiTJ+3AApF1S/R3bw1FowxjJ8fVe2vhQRE+CEBoXBRFwFx6e6L1h268N7gEAShvrh27Q0HJw/emzqCEApmlnbcckWRSISGRmawcegAl+6+6Ds0CMOmhmFq6E4s3nKiwqOnQ7efgZmlHbR0dBG3c0eNnl/3Xt7Q1TdCxP6r1fpaSECEHxIQChd1EZAufQPQvJUT7w2OKrl79yLWrl2GO3eyea+FIOoDBsZm8Bo6hfemjiCEQpe+n6KhkSm+2r0Ti5avxJiJ09Cr/yA4tHOFsVkTiCUanKAwxqDdQB9NbBzQtlMftOrQHWKxBGZNbHD6bEaNn9+r189Du4Ee3HoNqdbXQgIi/JCAULioi4D08B0HK5uWvDc4quTs2WOQyaT4/vsk3mshCKFz9fp5MMYwcWEs700dQQiFz5d8BcYYzmSdrPC5elJ8G5d+OouEwwewav1GfD5rHgYMGQHnTj1gYW2HgPHTcefuTyp7jpeuXA3GGKaH7any10ICIvyQgFC4qIuA9B0aBNPGTXlvcgiCUE9itisbqbCdWbw3dQQhFDYdzYNUJseMeQt5f4ZLSwugUNxB6w5dYGTaBJuO5lXpayEBEX5IQChc1EVABoyaDX1DE94HR4Ig1JPxQTOho2dAN5YTRBVp49oLrdq78f4Ml3H2h1OQyuToNeizKn0dJCDCDwkIhYu6CMjgCQuhpaPL+8CoSrKyUtCtW2dcu3aG91oIQuh07NoLDs7deG/mCEJojJgeDrFYgrz8H3l/jsuYOns+RGIx5m9KrvTXQQIi/JCAULioi4AMm7ICEg0p74OiKrl48VsMHuyDW7cqd1kTQRDvR9/QBP0CpvLezBGE0AjfcwmMMaxct4H357iMx0/y0LS5Ixo3bVnp44FJQIQfEhAKF3UREP9x8yGTa1XrfHGCIOo3OblZYIxh8uI43ps5ghAi1vbt4NFLvS77PZaWBLFYAt+x8yr1NZCACD8kIBQu6iIgDk4ecO7Ug/cBUZU8eXILDx7kQKHI570WghAy0dvilD/B3XWe90aOIITIwNFzoKndAL/+dpP35/ltho2bBA2pDMu2nf7Hr4EERPghAaFwUQcBiUzKh1SuqTandKiKgwe3gzGGGzfO8l4LQQiZcZ/PgK6+EW1AJ4hqsijmWzDGsP2bXbw/z2/zr5+vw8TCGnaOrohJuf/Br4EERPghAaFwUQcBmRWeAMYYUk8c530wVCV5eT/g668349dfr/NeC0EIlfOXMqHX0BgdPAbw3sQRhFDZkvoAho0awy9gDO/P9N/ZtW8PGGMYMW3VB78GEhDhhwSEwkUdBKRfwFTo6hvh6VNaqkQQxBvu3stBk2YtYGxmhYiEK7w3cQQhZHoMHAsjk8ZqudfSy+9TaGrrIvybi++tnwRE+CEBoXBRBwFpat8e3foM4H0AVDW5uZmIiVmNR49u8F4LQQiNx0/y4NSpO7R0dLEs7jvemzeCEDozwuLVdrVBfsFl6Bs2QrtOfd+71JIERPghAaFw4VtA1h24BpFYjMVh4bwPgKpm585IMMbw4EEO77XURxQl+cgtykRWQQpyizKhKKEZtPqEX8AYiMUSzFi5l/fGjSDqA1HHCqCp1QATps7i/fmuiPXR0WCMYeLC2ArrJwERfkhAKFz4FpDJi5Wn21y49D3vg5+qKSm5g+LiPJSUqN90t9DJLkzHkozZCNjvD7/4fgjY748lGbORXZjOe21EzZm7aJlyTfj0cN6bNoKoT3TwGADblm15f8YrQqG4A7dufaFn0AjrDlx7p3YSEOGHBITChW8B6eYzGqaNm/I+8BHCIbswHYFHhsM33gtBSYGYmzoFQUmB8I33QuCR4SQhAuMambahAAAgAElEQVTvM1lbdnwFkViMXoM+471ZI4j6RuC8TWCMISdXPS/IvXzlHDS1ddGlb8A7tZOACD8kIBQufAuIaRMb+AwezvugVxskJe1Gv36eKC7O472W+oKiJB9LMmbDN94LwWnTMD99Okdw2jT4xnth6Yk5tBxLIPx9JqtXuCc0NGWw79gZMcfv8d6sEUR9Y92BXIjFEiwIDeP9+X8fC0JWgDGGhVGp5WonARF+SEAoXPgUkJW7L4AxhnVRUbwPeLVBmYA8fXqb91rqC7lFmQjY74+gpMBy8lFGUNI4BOz3R25RJu+1Eh8muzAd4w4PQ++d3fBpgh+GfTUEmoYNoNVYD13Wf4qlR07x3qwRRH2keZtOcOniyfsY8D7OXjgFxtg7+79IQIQfEhAKFz4FZMwX6yASiXDr9iXeBzxCACjy8WPmDswId8fKr0fhy9Rp7wjInNQp8I/vj6yCFP7rJd6LoiQfnyeORcvI5nCMagG7CBvIrDQh0ZPCbcVgOG32ht/2YMSkfvhiMoIgqs6QzxZDQyrDg6Jc3seCijiYdAiMMSyKTi9XNwmI8EMCQuHCp4C49vRHM/s2vA92tcXTp7dp9kNFPMtOx59LZqNkcB+cd7PAhR62SB/bCeviRtIMiABJzN0F201NYbPRGs4x7aDnZACRVASjaU1gtbYN3KKGwC1qMMISs3hv1giivhH61fdgjGFTbCzvY0FFRG9THk4TvudSubpJQIQfEhAKF74EZEvqA+gZGGN44GTeB7vaYs2apZDLZbzXIXSeZafjP4HD8dLXC38GjUPmcFck9rNGrrstLni35iSE9oAIA0VJPiYljoFFhCk6xXWAaT8LMMZgPrY57CJcYbbaDs3Xd4LTJm8sPpzBe7NGEPURM0s79B34Ce/jQUUsXbkajDFEHSsoVzMJiPBDAkLhwpeALN5yAowx7Nizm/fBrrbIzk5HbGwE73UIGkU+/lwyGy99vfAieBpezJ+On2eMRNKnrbHP3waXO1sjZYwbphwdS6dgCYTcokwM2NMH9pts0Hi0FRhjMPK2RPN1bmi+zg1N17aHabgd2m/yohkQgqglPPqPhJWtA+/jQUUEfREMLR3dd2omARF+SEAoXPgSkE8mLYWGVIZ//Xy90oOS4mkebmUlICclGreyEqB4SqdL1Xee5WbiZYA/XgQF4sX86Rw/zxiJ06M6IaW/DU67W2BaZB8sPTGH5EMAZBWkwC++HxzmtAKTMOh2bAS7CFdOQGwjOqLhSjP0jA2kPSAEUUv0GvQZzK1seR8PKmLo6M/QyKLpOzWTgAg/JCAULnwJSOuOnmjdoUulB6SrGXE4Mc4dZzwscc7VFGc8LHFinDuuZsTxPlhWxNmzyRgwoA/dgl5DnmWl4KVfP7yYO6WcgLyYPx1/Bk/Do2mjUNy/K/IzdtCyK4GQW5SJvhv6QENHBrmNDkzDbNE0wgm26zqiaYQTGoVbo1F4M8xIiOe9SSOI+orX0CloZGbJ+3hQEb18BsPGwfmdmklAhB8SEAoXPgQkOvku5Fo6mDxzbqUGo6sZcTjd1w5ZriY4NbAVTgQ449TAVshyNcHpvnZqKSEpKXvRo0cX/PKLep4yUhF/vxBOHRr6982AcASNw8sAfzzLpU3nQuF2wY/QNTeEvJE2Oq0ZCvv1XdB4TUuYrW4Oi9UtYLHGHp6x42n2gyBqEZ8Rs2BgbMb7eFARHTr3RNtOfd6pmQRE+CEBoXDhQ0DmRhwGYwxHjx/9x4FI8TQPJ8a5I8vVBCeGu+DkSFeOE8NdlP89sKvaLMd6/PgmSkruoLS0gPtVCPz9QriA/f5YkjGb/yVNFewB4QieptyYvnQOShX8yxLxzzx6dAttOrhDs4EuOiwdCKfN3ugZOx7dt4yBa+QgtNrQA11jRtIdIARRy/iOnYcG+oa8jwkVYduyLd2EXk9DAkLhwoeA+Iz8AtoN9PCk+J+PqL2VlYAzHpY4NbBVOfko49RAB5zxsMStrATeB82SkjsYOLAvJk0azXstVSG7MB2BR4bDN94LQUmBmJs6BUFJgWqzqfvtU7BeBI3DizlTlDMfvl54ETgcz7Jp34cQUCjuwHvQcIglGpgVnoClR07Bd/s8uEUNhvNmH7hFDYbf9mCSD4KoA4Z8tgia2rq8jwsVYWzWBF5Dp7xTMwmI8EMCQuHCh4DYOnZEp+5elRqIclKicc7VFCcCnCsUkBMBzjjnaoaclGjeB83S0gLExkZg796tvNdR6aawJB9LMmbDN94LwWnlL/ZTp2Nty+4BeRngj5f+/fEywB9/Lp1D8iEgZsxbCMYYRs9ay40FMan3EZaYhcWHMxCWmEXLrgiijggICoWGVD2PiZdramPIZ4vfqZkERPghAaFwqWsB2Xj4JsQSDQQvCa3UQCSkGRAhkluUiYD9/ghKCnznVnG1u9hPkY9nuZl4lpWi3PNBy67Uig+dUhcZtxUikQh9P/mc98aLIIgijJgeDsYYFAr1Wir8r5+vgzGGcXM2vlMzCYjwQwJC4VLXAlK2/yP1xPFKNzVC2APy8OE1DBkyAKdP//O+FnWi7EjUualTKhSQOalT4B/fH1kFKbzXSqgvHzqlLiUjGXJNbbTv4oWYFJrhIAh1YMzs9WCM4dGjW7yPH29z8fIZMMYwbfnud2omARF+SEAoXOpaQMbO2QDGGB4UVf50qPKnYDm8PgXLQa1OwSosvISuXd3w7bcHeK+lKghqBoRQS/7plLpm1k1hadMKm47m8d50EQShZHxwJBhjuPfgavWe/Ye5+PeCmXgxbBD+vWAmSh+q5sTHpNQkMMbw5eZ3exISEOGHBITCpa4FxGfELOgbNqpWk/PmJ6xmyp+wBnZVC/kQMkLZA0KoJ/80Q/mNoyEYY5i4YAvvDRfxDyQXIjHiEL5duBWJEYcQm1zIf01ErTFp0VYwxpCX/2OVn/s/xw/Hf+Vy/I8xjv/K5fhz/PAajylxO3eAMYaVu86/UzMJiPBDAkLhUtcC4tpzEFq0cal2s6OuN6EL6cjdv1P+FKxxmJM6BUFJ49TmFCxCffmnPVqfNDNCA4kYG6L38d5wEe8nddkOFLX3wO+mlnhuZIbfTS1R1N4Dqct28F4bUTtMWfY1GGO4cu2HKj3zf44fjv+KxfgvY/ifWIz/aUjwv9e//69YXGMJWb52HRhj2JyY/07NJCDCDwkIhUtdC4iNgzN69R/Ee+OkavbujYW2thbu3r3Iey3V4e17QPzj+yNgvz+WnphD8kF8kA+dUvft8I4w0pTCx0gLUeu38t5wERWTumwHFJZ2eG5ohsc2jnjo4ILHNo54bmgGhaUdSUg9ZUZYPBhjyP7x+8o/8w9z8V+5XCkfGhL8TyZ9g4ZEKSGa8hotx5oxbyHkmtoV1kwCIvyQgFC41LWA6BkYY3zQTN4bJ1Xz00+nEB6+CE+eqNeGvqqgjjehE+rNh2ZAVvVoCcYY1jmYICruEO8NF1EByYUoau+B54ZmeOjoioet3d7g6IrnhmYocurGLceiY5PrD1+sOQDGGDLPnaj08/7vBTOVS67E4vLyUYZYjP8xptwTUs0xZcT4z2Fk2qTCmklAhB8SEAqXuhSQjUdugTGG5WvX8d44EQRRcz60B6SnlTEsZBLs8vdAzHHaT6COJEYcwu+mlsqZj7fl4zWPbRzxu6klEiMO/e3iSG+4RQ2G7/Z5dHGkQJm3IRGMMXz7XVqln/cXwwYpBeTvsx9vzYL8jzG8GFb9VQ79/D6FtX27CmsmARF+SEAoXOpSQBbHZIAxhgNHD/LeOKma8+fTkJq6j/c6CKKuqeiUuuP9W0BLLMIwK0NEbqYlPOrKtwu34rmRGR46uFQoIA8dOuAPIzPsm7sUHjEj4bTZG56xE9A/bjo8YyfAabM3PGJGkoQIkLJmPik1qdLPel3MgLh69Ebrjj0/WDMJiHBDAkLhUpcCMnnxNjDGkHv9Au9Nk6qZNGk0HBzsea+DIPjg76fULWiuPP1q6ZLVvDdagiXlPuJ3ZuFATAbid2YhthbuUKnsDMj84OFw2uwN77iZ8Nk2i8M7biacNnvDb3swLccSGEtiT1b9B4J1sAfE3tEZnXp/UmHNJCDCDwkIhUtdCsiQzxZBrqmtdjevqoJffsnF7dvnea+DIPji7VPq2rRpB9tWLrw3WUIlYespXBgzD7c9B+NuV2/c9hyMC2PmIWGrimcaKrEHpKB9R3Te6A/P2Anl5KMMz9gJcIsajLDELN7/3YjKE7pdeeHf7oT4Kj3ntX0Klmnjpug9ZFKFNZOACD8kIBQudSkg3XxGw9KmBe+NEkEQtceVaz9AJBZj5Aya/agOCVtP4Ub/kbjr7o2r/hNwOWA6rvpPwF13b9zoP1LlEvLuKVgduFOwnlo1xzdfLofzZm/0j5teoYD0i5sG580+WHw4g/d/O6LyrNx1HowxbNv1dZWf8QrvAdFUzT0gWjq6GBS4oMKaSUCEHxIQCpe6FJBWHbrDrVtf3huk2uDLL2cgNnYt73UQBN9Mn7cAGlIZ1h+8xnuTJThS7uPCmHm46+6NH4fPxI8jZr1h+EzcdffGhbHBKl+O9fY9IH+U3QPi1A2py3YgLDELblGDaQaknrFm72UwxhC9rZqX+dbCTei//nYTjDGMnhVRYc0kIMIPCQiFS10KiEnjZhg6agLvDVJtMGLEYISGBvNeB0HwjZVNSzh39eG9wRIi8TuzcNtzMK76TygvH6+56jcBtz0HK/eEqPr933MTekzqffhun0d7QOoZ6w5cUx6THRXF+5hRRk5uFhhjmLLs6wprJgERfkhAKFzqSkBijt+DREOK4CWhvA9yBEHUDqknjoMxhiC6vK5aHIjJwN2u3rgcML1CAbkcMA0FXX1wIKZulzstPXKq3ClY/eKmvTkFa8soOgVLgGw+ehuMMaxav5H3cePv40fwhqQKayYBEX5IQChc6kpA5q0/CsYY4nbu4H2QIwiidhg6+jM00DNEdPJd3hssIcLrDMg/UP4eEB+4RQ2G3/Zgkg+BEn28EIwxLFu1hvdxo4yv936jvCtsx7kKayYBEX5IQChc6kJAwvdcQkMjMzSzb4NfHt7gfZBTNb/9dgP6+nrYuTOS91oIgi8eP8mDvmEj9PQN5L25Eiw87QGpLHQTev1CJBZjQcgK3seOMlZv3ATGGDYevllhvSQgwg8JCIVLbQvIpqN5sLJrDYNG5sjJzeJ9gFMV+fkXMGLEYGRnp+PJk1sICZmHEyfq3wWLBFFZtu36GowxfLnpOO+NlZApdwqW3wRcDpiGq36vT8HyHqX6o3iJjxapTI7ZC5bwPnaUMWfhUmhIZdiS+qDCeklAhB8SEAqX2hSQmJT7aNfZC3JNbaRkJPM+uFWHkpI3d5Z8+eUMTJum3ET/66/X4eTUBikpe9/5cwTxMdLDyxdmlnbvbR6Iv42Pxwqwa2UM9s1dgl0rYxBzrID7f2/fA1LQ1Ud5D8jYYJIPQqVo6ehi6uz5vI8dZYydNB0GxubvrZcERPghAaFwqU0B6TNkMkQiUfWP+eOZjIyDMDc35S4YXL16MZYunct7XQShbty7fwVSuSb8x83nvakSAnsWrMBPrazxs5E2ftOX42cjbfzUyhp7Fqx48+fq4CZ04uNGt6ExJk6fzfv4UcaAISNgaev43npJQIQfEhAKl9oSkJEzVoMxhllfLuZ9UKsueXk/YMaMicjL+4H3WghCnVkWvgYikQgrd1/gvalSd/YsWIF7Znp4pCfH7SaGuG5rhttNDPFIT457ZnrlJYQgahEDY3OMnTSd9/GjjC49+8HBudt76yUBEX5IQChcakNAZq7aC7FEAwOGjIBCIcylSamp+2BjY43Cwku810IQfKN4dB33Y5ahcMEE3I9ZBsWj6+X+f2vnzmjRrgvvDZW6E3OsAD+1ssYjPTly7cxxrXljjlw7czzSk+OnVk3LLcciiNqikbk1hgdO5n18KcOhnStce/q/t14SEOGHBITCRdUCsizuO2jp6KK9qwcePb7F+4BWXe7evYjAwOG4cyeb91oIgk8Kl09Fsbk+/pRL8EIqwp9yCYrN9VG4fCpKSwtw8fIZiEQijPliHe8Nlbqza2UMfjbSxu0mhuXko4zbTQzxs5E2dq2M4b1Wov5jZmmHISMDeR9jyrCwsoOn/4T31ksCIvyQgFC4qFJAIhKuwNjMCo2tm6OgMIf3wYwgiJpRuHwqnutI8UIqwu86Gnimo4F/y8T4j5jhuaYYhcunYvLMuZDKNd97dCbxhn1zl+A3fTmu25pVKCDXbc3wm74c++Yu4b1Wov5jadMKA4eO4n2cKaOBviF8x8x9b70kIMIPCQiFi6oEJPLYHdi2coGuvhF+uHia94FMVezbtxUhIfN4r4Mg6hrFo+soNtfHC6kIf2hr4P+JGP7L3vCKMZQ0kMLc0uaDyyaIN9AMCKFONG3RHv38PuV9rCktLcCT4tsQiUQYMT38vfWSgAg/JCAULqoQkC2pD+DacxA0pDIcTKxfd2EsXToX/fv3gkKRz3stBFGX3I9Zhj/lEvyfTIJXb0nHX69//S9juMgYGGOYvuIb3pspIUB7QAh1ws7RFT37+/M+1pSWFuD6rWwwxjB5cdx76yUBEX5IQChcVCEgA0fNBmMMqzds5H0QUzUkHsTHSuGCCXghZtzMx1+M4S/RG14xhmmMwUzEEEnLryrNh07BKjTTp1OwiDqjRXt3ePT24X2sKS0twMnMNDDGMCfi8HvrJQERfkhAKFxqKiDj50eBMYYJU2fxPoDVJhkZB5GTc4r3Ogiirrgfswz/0Xhr5kNUnheMwZgxzBIxHJq7nPdmSkhUfA9IU5IPok5p3bEn3Lr14X2sKS0twJ79e8EYw7Jtp99bLwmI8EMCQuFSEwEJ2/kDNKQy9OzvL9jjdivDkye30LixOXcLOkF8DCgeXcfvDaT4XwWzH3+JGJJeL7+6KGFIHTuJ92ZKaHzoJnSCqAvadfaCc+cevI81paUFWBel/GHmugO5762XBET4IQGhcKmJgAQt2wHGGHJys3gfvGqbK1e+o+VYxEdHoX+3cpvOX4ne7P8YwhjaiBj+TyahGRCCECAdug1E6w5deB9nSksLELx0OcRiCWJS7r+3XhIQ4YcEhMKlJgIycsZqiEQiPH6Sx/vgVVfk51/gvQaCqCsUj67jdz15udOv/ssYnjAGOWMIFzP8YtIQMYn5vDdTBEFUDbdeQ9CyrYtqxoqSfOQWZSKrIAW5RZlQlFTtB3bjp8yCnoHxB+slARF+SEAoXGoiIANGzYaegTHvTVJdcerUYUilUpw6dZj3WgiitlA8zcOtrATkpETjVlYC7i4LwnNtKV5KGP6UifGHjga2yyVgjCFXLsWxidN5b6QIgqg67l7DYNuybY3HjOzCdCzJmI2A/f7wi++HgP3+WJIxG9mF6ZV+Db+AMbBo2uKD9ZKACD8kIBQuNRGQbj6jYGXrwHvDVFc8fXobGzeuwMOH13ivhSBqg6sZcTgxzh1nPCxxztUUZzwscWKcO6595l3uNvRcqQgSxjDRsSWi4g4h5ngh780UQRBVo/uAMTX+Hp5dmI7AI8PhG++FoKRAzE2dgqCkQPjGeyHwyPBKS0i33gNg37bzB+slARF+SEAoXGoiIO27eKG9WzfemyY+KCmpv5vuiY+TqxlxON3XDlmuJjg1sBVOBDjj1AAHZLduiAttDZExyxvXF4zBtdG9calrM/RvpA19iQiHnBtj9yAPRG7ewXtDRRBE5enlPwHmVrbVHjMUJflYkjEbvvFeCE6bhvnp0zE/fTpGRY+Ex+eecFvkhrlHp1dqOVbrDl3QwWPAB+slARF+SEAoXGoiIDYOzugzYAjvjVNds2XLGvTt24MkhKg3KJ7m4cQ4d2S5muDEcBecHOmK7/o1R25TLTzSYfg/DYYSOcMdYwnyzGW42Eofe3s1h1QswidNG+FEOzMkdrUjCSEIAeE1dAoamVlWe9zILcpEwH5/BCUFcvIxbEMANLRkYK9PyWOMwcjMAm7d+mDspOmIiIzE6bMZeFJ8u9xrWdq0QPcBYz5YLwmI8EMCQuFSEwExMm2CEeM/5715qmuOHt2Jzz8fi0ePbvBeC0GogltZCTjjYYlTA1tx8nHHTIoSTQaFJsNvOgzFWgy/yxj+rcFQaCTGd1528Lc3g1wiRkxvJ5xoZ4bdg7rRciyCEAjeI2bCwNis2uNGVkEK/OL7YW7qlNczHyMgbaCJhs3M0Gf9ZHRZHADrke3QaeAQODh3g55BI05KpDI5mtm3Qd+Bn2Bm8CLo6DaEz8gvPlgvCYjwQwJC4VJdAdmS+gBSmRxfLFjMe/NEEETNyEmJxjlXU5wIcMbJ4R1xuYUunmgrpeNfDcX4tQHDvyUML8QML0QMf0oY7huKcbRnM2hrSNC3qSkOejoitaMlouIO8d5YEQTxzwwavwBSmRzpJ1OrNW68PQMybutoyPV1oNfEGH03fg6fbbPgGTsBblGDEZaYxb3nmn0/Yeaqvfhk0lJ07jMUVs3bQCqTgzGGsXM2fLBeEhDhhwSEwqW6ArLh0HUwxrBm02bemyc+KCm5g+jocBw6tIP3Wgiiprw9A3JqgAMKTDRQrM3wUE+EX3VFeK7B8B8xw59ihmdSpYw8kzLcNpdhrK0xJCIRNnZvjYz2Zohav5X3xoogiH9mbUIOLG1aQUtHF/EH91V53CjbA9JzQzdoGepCx9QAvddNgs+2WfCOmwmnzd7w2x6MmNT33+0Rm1aEmOP3ELbzB8Qcv/fBP0cCIvyQgFC4VFdAlm07DcZYtQat+oKnZ1dMn/4Z73UQRE15ew/Id31scN9QrFx61YDhd6ly5qNUxvBcQ/n7/9NgKNFkeGAowVl7XTSUS9HNTJ9mQAhCYGw4fAMt2nWBhlSG9dHRVR47jp7bCy0TXcgMtdBl1TD0i5sGz9gJcNrsDY8to7D0yCmV1UoCIvyQgFC4VFdAvli9H4wxZJ47wXvzxBePH9/kvQaCUBVlp2Dl2OngqaZyqdULEcNfTDn78VhLuRH93xKG/5Mol2fdbCxDnoUMUxxMIWIMKzydhbEHJLkQiRGH8O3CrUiMOITYZAHUTBC1ROSxO3Dp7guRSITgJaGVHjNu3b6EJs1aQNfQCL3CJ8ItajCcN/vALWow/LYHq1Q+YtNIQOpDSEAoXKorIOPnR4ExhsJ7Obw3TnxSUnIHycl78OTJLd5rIYia8v2mqbhmrYlnMob/xxheveb/MeUsyNPXAvJCwvCzPkOOjRYKjSU476AHM00pHB3b8d5M/ROpy3agqL0Hfje1xHMjM/xuaomi9h5IXUYneBEfLzEp9+HpPwGMMYyeOBUKxYdPeSy8lwObFm2hq2+EZXHfISb1PsISs7D4cAbCErP+cdlVdSABEX5IQChcqisgn0xaCqlc8x8HqfrOTz+dAmMMu3ZF8l4LQdSEsmVYFx30cNdIjD80GP7zegbkJXv9q4jhmQbDIx2Gu400UGgswQNDCU4OaoOFsyaCMYY5EYd5b6beR+qyHVBY2uG5oRke2zjioYMLHts44rmhGRSWdiQhxEfNltQHGDxhIRhj6Os7FI+f5FU4VjwoykXLti7QbqCHhVFpdVYfCYjwQwJC4VJdAek7NAiNzK14b5rUgYKCbOTl/cB7HQRRE25lJeBM1ya4YqONAlMprlvJ8VBPhP+IlbMgf73moS7DqT42OOXTApda6eHkoDYofnwdT5/mw9quFWxbuWBL6gPem6l3SC5EUXsPPDc0w0NHVzxs7fYGR1c8NzRDkVM3Wo5FfPSMm7sRYokGXLp44kFRbrlx4uGvN9CuY1fItXQwb0NindZFAiL8kIBQuFRXQNx6DYF96w68N00E8dFSnIc/0hLwfHc0/khLQGlxxT+trCw5KdHIbmuAPHMpcptqIce+AXKaN8BtcykUmsrN57/LGO4ZSZDZwxpZriY43dcOVzPiUKzIQ9qNBExeMwWMMUxe+hVi04oQlVKIOQcOYVL8Vsw5cAhRKfw194kRh/C7qaVy5uNt+XjNYxtH/G5qqdwTogZNIEHwyfSwPZBrasOuVXvczLuI0tICPHp0C27d+iiP4F+9v85rIgERfkhAKFyqKyAOzt3QuUc//pswHlEo8uHu7oqEhDjeayE+Lp4nxOFlT3e8srbEKwtTvLK2xMue7nheg8/irawEnG9vhEJjCXLsdJQC8prrVpr4WV+EErnyZKzz7QxxIrArrmbEISEnDj13uMN6fRMYhjeEpJkGpGaa8IqdipYbusJgpTl0w4xgsNIcLTd0RdBefpY5fbtwK54bmeGhg0uFAvLQoQP+MDLDtwvpGGGCiE0rwpebjkNX3whmTWxw9sIpdO87EBINKaaG7uSlHhIQ4YcEhMKlugLSuFlLDBw6ivdGjE+KinIwevRQnDx5iPdaiI+H5wlx+KuFHV6Zm+Cvtq3wl5sz/mrbSvn7FnbVlhDF0zyc9G+NfzUUI9das5yA/GSngwITKW5YynG+rQEu7F4GxdM8JOTEoUWkHQzCG0InTBvSUCnEE8TK244HMUhCpNBarg/t0IbQDNWFLFQLBqss8Hn89jpvXmgGhCCqTuj2M2hkbg0NDRlEYjEmLozlrRYSEOGHBITCpboCotvQGJ9N+4L3ZowgPiqK85QzH+Ym+KuzC/5yd31DZxe8MjfBS8+u1V6OdSUtFtestfCLnkgpIbY6yG2qhQJTKW5YauKioz5OBHaF4mkeihV56LnDHQbhDSEPlUESKoFsuQzyUBlYSwbWkIEtZtBcrgvN5bqQhmpCFCKBKESChistsPjQt3XbwNAeEIKoFmv2Xka7Tn0xPjiS1zpIQIQfEhAKl+oISPTxQohEIixesYr/hownSkruYP/+bfjttxu810J8PPyRloBX1pbKmY+35aOMtg54ZW2p3BNSzfcoO4r3Xw3FKDSW4KQJRucAACAASURBVLa5FFdstHHRUZ/b81FaWoC0GwmwXt8EmsvlYCGsPFMYmIiB9WdgISJIQzUhD9WB5vIGEIdIIQ7RQJuNfVR+T8A/8e4pWB24U7CeWjWnU7AIQo0hARF+SEAoXKojIOF7LoExhuivtn2wkSkuvonMjEgc27cAmRmRKC6uPxf3nTmTBMYYUlLiea+F+Hh4vjsaryxMlcuuKhIQN2e8sjDD891Vv9H4ba6kxeCkf2ucb2eIH1rr40RnEySPdsGVb7dyf2b3pWjormzASYcoRARxiPiNhLRnYNoMbAGDLFTrzUxIiDbEIRI0WdMKftuDa+W+gA/x9j0gf5TdA+LUjeSDINQcEhDhhwSEwqU6AlI2CCSmJL63gUk9HIKvBlnhcAdtJLeV43AHbXw1yAqph0N4b+JURXZ2Op4+vc17HcTHQ13MgJRx/s5xLNv2KSav6IhREa4I2OuLJRmzkV2YjtLSAhy/Hg9pqAZYCIP4tXyUE5BZDEzCwHowSEM1OQGRhWhBHKIBh/UecIsajLDErLpvZugmdIIQHCQgwg8JCIVLdQRkauhOMMZw+cq5ChuX1MMh2Oeuh+Q2cuzuYYAd3qbY3cMAyW3k2OeuV68khPgAKj4mliio9T0gZWQXpiPwyHD4xnshKCkQc1OnICgpEL7xXgg8MhzZhelIvrYH0uXScjMgohBR+aVYnRiYjEEarBQQeYgOJCEakIdqwyN6FJw3+2Dx4QzeGxuCINQfEhDhhwSEwqU6AjJq5howxvDo0a13Gpfi4pv4apAVktvIsd3HDDsGWnBs9zFDchs5tg2xFvRyrMzMRHTq5IKbNysWMKJ2jokl3vzbvjkFy+H1KVgONToFS1GSj9yiTGQVpODKg++wOOML+MZ7IThtGuanT+cITpsG33gvLD0xB7suRaJhuD5Ef9//8TbzlALCOougESKHJEQKSagUFqtbomfseP5mQAiCEBwkIMIPCQiFS3UEZPLiODDGcPT40XcamcyMSBzuoK2c+XhLPsrY3cMAhztoIzMjkvdGrrqcPn0Ugwf7oJh+ol8htXVMLFH+3/iN4JkpBc+za7X+bbML07EkYzYC9vvDL74fBnzTB22iHTBs/6By8lFGUNI4BOz3x86LkWi0xujdWY+3+ZSBiRlYx9eb0UPkMF5lDY+YUXDa7M3LHhCCIIQJCYjwQwJC4VIdAYk5fg+mTWzg4u75TjNzbN8CJLeVY4e3aYUCsqO/KY61lePYvgW8N3FELVBHS4SIApUscatoqdWnCX4wjzBF25hWmHB05DsCMid1Cvz29EP85S3cJnSNEMm7MyGfKE/CErWWQLJEBmmIDAYrGsM1cjCcNnvDY8uoOj8FiyAI4UICIvyQgFC4VPcekHFzN4IxhqTUpHINTX2fAcnN/R4nTx5CSckd3mtRR+pykzRRfRQl+bjy4DtMOjoavXd2w7zUqZxgfJ40Fo5RLdBsozW6be/8zjKsYfv90SbaAV22dYRsuYzbgC4Llb7ZBzL4tXy0FaPlOg9Yr20H41XWMFhpgfabvOC3PZjkgyCIKkECIvyQgFC4VFdAoo8XwsSiGVy79i7X2Px9D0icjylivRshzse0XuwBWbBgBgwMGuLJk3f3vxB1d0xsfeftPRm5RZlQlORX/GcV+XiWm4lnWSl4lpuJUsV7/txblC25GrCnD5qss4D9Zlt0296Jm+0ITpuGbts7wWajNVpF2uPzpLGcfEw4MgLWG5rAIbI5+uzsDq0VmtAN04EkRMItxRL5i8AYg8RZBlmINpw3+8A7bia6xYyBwwYPTNu3m5ZdEQRRZUhAhB8SEAqX6gpIbFoRxs7ZAMYYjn97rFyDk3o4BHu6NMBRRwmi3aWI6ClDtLsURx0l2NOlgaBPwXr69DZ+/PEE73WoKzQDUnP+vicjYL9/ueNvy3h2Pg1/ThuP33t1hqK7C0oG9cG/F3+BZ9npH3ztsiVXQxN80WyDJRwi7dFsozXaxThyEjLh6Ei0jXGERYQphib4Yk7qFHyeOBYtI5vDeoMlBu/1QbsYR0hDNSBbLoPWCk3Ilksh9pWAiRhkLlposNwYWsv10Dl6KHy2zYJn7ATadE4QRLUhARF+SEAoXGoiINHHC9HIoik6dfd6t8lZ6YKwvlrY216Cw60l2NteghVeWghc6fJOI0XUI2gPSI34+56MeceDsCjuE0wP74K5sQORXZCK0lLlJvQ/2tqjpJEuHppp414THdyyN8AdZ2s8GuFdoYQoSvKxJGM2fOO9MP7ICLhudYL+Kj00DNeH8WpDGK8xhEtsO27JVdlSqwF7+sA/vj+3Ob3/7l5ov6U17DfbQndlA2iESqATpg3JAA0wxiDuqAH95WaQL9eB8Sor9I+bAe+4mbTpnCCIGkECIvyQgFC41ERAYtOKMOaLdWCMIfVEyjtNzrzkIMyI6ocZ4V0xI6of5iUHcUd4vndJiRqzZMkcjBnzaa29fqWX3ag5tXFM7MfA289OcNo0rIsbifSxnXDZswVyu9riO3dznAzsimd7Y/FHO3soDLWQZ6OHOw4muN/CBA+b6OOOdQNca2eGornj3lmOlVuUiYD9/hi2fxAnEI0jzGAY3hDmEaZoGK4Pg3B9fLrfjztud0nGbFx58B2+z0/C8lNfwiW2HdpEt4L9Zlt02dYRDpHNobVCE2JvMRhjYG4iSJbJIAmRQWu5Ppw3+8AzdgJtOicIosaQgAg/JCAULjUVkOjkuzA2s0SXnv3KNTlBSYEfPMIztyiT94avqsTErMaiRbNq5bUru+xGKKjymNiPhbefnXVxI3HBuzWuudvi7KD2ODXMBacGOuCCqwX+7WCDZwbauGWjh7utLVDY5jWtLfDI0gA3m+vjSi8HlF79rtzrZxWkwC++H7p+5coJhNOWNjBd2wiGqw1gtqYRdMK00SbKAQP39OUuHNz9YxQcIu2ht1L39WlXIuiubACHyOZw/8oVRn6NwBiDqLMYbJkIGiEyGK5qDPv1neG82QduUYNp0zlBEDWGBET4IQGhcKmpgMSmvbmYMP1kKtfkzE2dUqGAzEmdAv/4/sgqSOG94VMXKnPrNN81Vgu6Cb1KlD07844HIX1sJ1xzt8XJER1xcqQrTo50RcYIFyT3tcK/jfTwu44U+S0bvZGP1zxoYYqfrfTxU3sT5GfsKPf6uUWZGLCnD+w32cAltj3cv3JFl20d0SqqBcwjTKC/Sg86YdpovM4c049NwNHcXfCL7w9JqKTCOz60VmjCcIAxGGNo2NMcBistYB7eHM3XdcL8gykIS8zC4sMZCEvMomVXBEHUGBIQ4YcEhMJFFQISnXwXRqZN4N7Lu97OgHz77QFcvXpa5a/792U377t1WqjLsYjKU/bsLIr7BJc9W+DsoPacfJwc6YqUgHbI6N0Uz80N8YeWBPea6iHf0bT8LIijOR6b6+OiUyP8mFleQBQl+ZiUOAYWEaboFNcBTlvawGp9YzRaYwTD8IbQWakDswhTtIt2xKSjo+EU06bc3R6SEAnEb1862IuBMQb9XqYwDbeF1do2cI0aTBvNCYKoFUhAhB8SEAoXVQhIbFoRRs5YDZFIhG+/S62XDbWTUxsMHepba01nfRM2ouqUyej08C7I7WqLU8NcOPk4MaIj9g2yxXcDHPCzlT4U2iLcN5Tgkq0mcux1cbuViXIGxN4ET411kDTADrn3v3vnPRJzd8F2U1M0WW8B49WGMAxvCJM1xtBd2QDyFTJohGhAHCKG4UoDaC3VgHsgw6BPGdwDGSRLGKShGkr56KGUD9aDwXiVFVqs70K3mxMEUauQgAg/JCAULqoSkKhjBTBs1Bjd+gz425KicZiTOgVBSeMEvaTo55+v4ubNcyp/XVqyRrxNdmE65sYOxHfu5jg10AEZI1yQEtAO+wbZYv9gO+wfZIebzfXxWE8DeWZSFJrJkWMtwyVbOW7b6qPEUAu3bfQRtW1shZKvKMnH54ljYLzaCLorG6DBSh3u/o638R7OkG7DUNCQ4V+6yl/TbRj6D2MQdVfe88E8GUQhGmi1oTt6xo6njeYEQdQqJCDCDwkIhYuqBCQ2rQgjpq2CSCTCqe/Ty22q9o/vj4D9/lh6Yo4g5aO0tAD37v1YK69LMyA1o1iRh7QbCdh9KRppNxJQrBD+PpPsglScGOeO824WSPC3xaEhLfDdqE44HtAO+/xtcNvZEoV2hvihpTYuNZXhppkEdwwZivQZfrKUYnqQNRJy4rhT1c7dSUbajQScvZOM3KJMHLm6EzYbrWG82pATDouJDM8Zw/9jDH8yhuvaSvG4bMZwxlL5a1EDhs+0Xs989Ba9XpalAfv1nWmjOUEQtQ4JiPBDAkLhokoBiTpWAEOTxtDQkMHRqRMmTJuF6L0xyLx5TNDHyhYUZMPExBjR0eEqf23aA1J9EnLi0HOHO6w3WMIiwhTWGyzRc4c7EnLqwUlbF9JQPHIgir3c8WTCJ/ht6kik9LfB5c7WuODdGl+HDED8py1wwEmGdHsxUltIsMFDA95fWqLzNhf4x/fHpKOj4bKlHfRW6UJrhRYarTZCnx3dMenoaLSJduDk4yVj+C9j+N9b/JcxvGIMmdZKTlsxBOgq5WOSkXI5FgthMFlliwUH02ijOUEQtQ4JiPBDAkLhokoBiU0rQvg3FzF0cgjaduoDTW1dMMagqd0ALu6emDV/MdJPpkKhuMN/g1dF1q5dhoKC7Fp57fq4ZK22SciJQ4tIO5hHmKBtdCu4xTmjbXQrmEeYoEWkXb2QkGfZ6fhzyWy8DPBHcf+uOO1ugdQxblgXNxLBadPQbZsb3BdboN9cczjN14dOqCZM1hjDdE0jyJbLwEIYREsZrGcytA5S/ipaytBojTE0QiTl5OPvAlLGK6aUjyGv5WPu6+VY7oEM4hANTPomlvemhCCIjwMSEOGHBITCRdUC8jbRxwsRvCEJvmPnoUW7LtCQysAYg15DY3TrMwCLV6zCDxdVf7JUbXL//mWkpSWo/HXr25K12qRYkYeeO9xh/v/ZO/O4GtP3j1/PWTp1Wk6rdiUphSQpVJasMZIZIzFD2cu+70qyTba0aazNRMiSURnZR9axb9myj0FiMMMYvr/P74+njiKE6jmH+/N6vV99RfWcx3wf9/tc931d0VXQKMkdXos9lDRKcod5dBX4LvP+LLZjPSy4gEcnd+HC1qUYtLAVwjYEY+yWweiyuiOqzDaGYoYeZJEaEEeIwEVwkBS2zOWmEHy/J8z3IKTVJKxxIqxwIYzzJTgVykjrju+WjyJ6FW67GmbIb8e6rssfTPeJ6y74goTBYHw5MAFR/zABYVGmIgXkdWI2XsCQ6SvR5tsw2DjUBSfipyfb2DvjXv554Rd7ZWDgwF6wtDTHnTtnyv17fy6T0CuarDOpsJlnDZc45xLyUYRLnBNs5lkj60z5i6JQFN+q12t9NzgutId2lByyyVyJTlWiyYSaAwnzPAnnDflzHGeMCTtsCMvrErZUJxywIGx0IPz7HvEowo4IX+nwW7GOmPIVEN8QXdZql8FgVCpMQNQ/TEBYlKlMAXmduWtPISB4LIgIh47sEXyRVxZu3z6NI0e2CX4dXzLJh+NgEW0KzyS3UgXEM8kNFtFmSD4c987vo27CdzBvC4LXdYXTwhow/aEKvirsVHVZn/CHNi8bh80ImXaEUyaE8waE3daE/Za8hJwyIZwy5v/cITP+wPn75COP+OrHNBPCLmv+a7dUJ7jMbIFJ67YKviBhMBhfDkxA1D9MQFiUEVJAErOuY3LiNhARVqap17vV9+6dQ1hYCE6e3C34tXxJFDy4gOWHFsI82hQ1Y+zRKMkd9RPrwjWhNuon1kXjHxuUqQJSfMtbx5S2CFwdgMlbR6j8lreNJ1egxgI7dAgS4bQx4bY24aY24U8tQoGM8JwjPBMRbmjz4lF0iHyXNeGOnJAvI1zT4f9sWQTkRyKIiLDLhJeP0yaEjkGabNggg8GodJiAqH+YgLAoI7SAzF9/DkSEqOi5gi/uPoSLFw/CwcEOq1YtEvxavhSKpOHbVf4wnmUEWaQGFDN0YTBTH0azDGAy2wjWcyxgPNvwnWdASh76D8GozDCEpoeoxaH/3RfSYTvDHFvsePm4JSfc1eLl4KYO4W8R4T+OF5HDpq8E5IAlLx1PxYR8DUK+JuFSGQSkKxHcqHAOSHV+Poj97IZs2CCDwah0mICof5iAsCgjtIAkZl2Htq4++g4eIfji7kO5d++c8n/n538GB55VmNelocUyH2hEaoCL4CCL1IDJLCMYzTKAbJoMipl6mLMnotTvo85tjw/mbUHPtC7wCeFwWZ+vfNzVIlzVI1xVEG7pEP6WEJ6I+e5Vt+WEXVV5ATlszn/+mYivlvwpJxwwe/ch9BdEMCFCTcdX50ukEZpoEBvA5n0wGIxKhwmI+ocJCIsyqiAg1tVrwa9TV8EXeB9LZORYNG/uVUJIGOXH69IwJmsQmixpCMs5ZtCbrgvJVDE0IqVQzNCFzVwreCS5YUr2SOQX5L5xxkNdBz8WCVizJY3RuQuHPwq3Xd3Q5eXjqoJwU5fwREL4S8LLwz8cIU+PcNaQcMaQ8Iwj/CPmt2HlKXg5OW9QuoT8jwjHC89/UA9+5ocoQoKa83wweV224AsRBoPx5cEERP3DBIRFGVUQkLqN2sDVw0fwRd7HsnlzCiZOHI4HD9Rvvok68Lo0DEjviVqxjnBf5IrGPzaAY0x1WM2xQMeUthidNRCh6cHwS/bF4E293zjjkXIkAR1T2mJUZlipAjIyMwwBKX7IuZQh+OsuoriA9d/YA637auKGLr+lqqj6cVXB/+8HMl40XhaTiv8R3/HqP+J/75Y24ZDFq+1Z5/UJz14TkMt6hEY1CSQh0ESCKEKM2vN9MXndNsEXIQwG48uECYj6hwkIizKqICDNO/aCubWd4Au9T4HJR8WRcymjhDT0Wh8Exxh7NPqRnwHS6Ed3OMbYI2R9EMZuGYzgdV1hO88azZY2fuOMR+fUDvBL9lWrCkhxARuTNQiu82pitzVf7bihXUxAFPz5jrdVNP5XKCBXdfkD6rurvuqQdcKIcNCMEOFN+KYzQTyJQDUIZMdXP2xmu7JtVwwGQ1CYgKh/mICwKKMKAtK572RIZZpqOSG9iAkThsLPrwUTkQrgXRUQr8UecE+si1qxjhiQ3hNjsgbBY1E9WM0xR/+NPd4449Hh59Zovswb/j+rzxmQ1wWsy+qO6NhVhD/l/JaqP+S8VPwhf/eZjv8VTja/qEs4bkI4bUw4XoWwzZY/YD62BT/AkCIINJlAUgK14H/defFkwRcfDAbjy4YJiPqHCQiLMqogIP0mLgIR4fTZg4Iv9j6WlSsTERk5VvDrqGzy757GgeRw7JzVGweSw5F/93S5/4y3nQFxjKmORknucIipjiZLGmFM1iD039gDVnMt4LnI7Q3BKKpw+CW3QOfUDoUH2oMxMjMMoenBKtsF63UBG5M1CPUT6yKsPYfrhec+/hHz5z7KMljwtpiQ6kRIdCMsdiWsdSLEu/MDDCmikJDC8x99CVyECH1+ihN88cFgML5smICof5iAsCijCgIyLoZ/qGzM2Cj4Yo9RdnYvGIjDzgpcMxTjDz0O1wzFOOyswO4FA8v9Z5XsghWM4HVd4RzrAPPoKnCOdUDwuq4ITQ9Gs6VesJ1njZB1Xd95xiPlSKJyDkhAih8CVwdgSvZIlZOPhw9L79z1zcr2MJilD+dQfvDgP+K3Vz5e52+OkF6DsNqZsMKFr3yUkI8IAjUjkCaBphDk0wwwck2a4IsPBoPxZcMERP3DBIRFGVUQkOjU4yAizI179+RqVWX+/Gk4dOhXwa+jMtm9YCAumkpxS4/DWUsZjleX46ylDLf0OFw0lVaYhBSXBr/kFmi+zBt+yb5KiRjySx/4Jbco0xkPdZqEXlzA/JJbwHiGAaoN5eDSn7DHmvBIWnYBeSzi2+rWGVD4sT/BZmix7VcRBKpKICcCFyFGtej6iM3IE3zxwWAwvmyYgKh/mICwKKMKApKQeQ0aMi0MGT1B8IXeh3L79mlYWJhi7typgl9LZZF/9zQOOytwS4/DUXs5jjnoKDlqL8ctPQ6HaikqbDtWcWl4vdVufkGu2s75eB8H87ag/4YecB8mx3hfvnqx3YbfgvVUVPYtWBd0CU6hhHGF32NNYSVknC9fCRGNF4FEBGrHz/3ovmK24AsPBoPBYAKi/mECwqKMKghIYtZ1mFnbo1NQsOCLvI/h3r1zuHPnjODXUVkcSA7HNUMxzlrKSshHEWctZbhmKMaB5PBy/9n5BbnIOpOK5MNxyDqTivyC3Dc+t+9SRontWqp+xuNDXnvYLC8schdhrRNhQUMR0pz54YPPC9vsvks8ig6oT+hpgRUNNbHWiTC3ISHSh/+41omQUJ9g1b7w/McggtO8JmziOYPBUAmYgKh/mICwKKMqAuJcvyk8m7QSfJH3Idy/fx7Xrx8T/Doqm52zeuMPPQ7Hq8tLFZDj1eW4peCwc1bvcv25qceS0HypF2zmWcMi2hQ286xRJ64m6sQ5lfhc86VemLMnQm3OeJSFg3lbMHhjCCJaiLGjKn9+Y5krYakL4aHGqwrIy/fIx1VdQlIna/xSR4bwJoTwpsVowktIg6oE0iMookwxMW2r4IsOBoPBSMxiAvI5hAkIizKqIiA+ft1hY+8s+ELvQ1izZjHkci2cPLlb8GupTISogKQeS4LjQnuYR1eBS5wzPJPcYDvPGuKpYkimimEz1xqeSW5wiXOGeXQVOC60x8qjiWpzxuNdFJ3/mNajKv7Q4YXjLw1+EOElBeGWnPBMzFdBXlDpW7H+R4RbWoShMW2Q3kAXsY0lmNqMQ0TTkhIy15NgrUnQduLQZVmk4AsOBoPBKIIJiPqHCQiLMqoiIB17joFcRyH4Yu9DyM3dh+joiM9i9seHHMiu7DMg+QW5aL7UC+bRVdAoiR8+2PjHBlDM0IMkQgzpVCkUM/WUv9coyR3m0VXgu8wb+QW5gt/bT/17mbx1BKaOqIfbVeT4R0K4rU24pkv4Q5sXkYca/CH05xwvH884wpPCaegvifCUCGuqEfpO90D3Kc7YVEcD03wIkc1EiGwmKiEhYzz57VfVWspY5ysGg6FSMAFR/zABYVFGVQQkZHQMiAhXrh4XfNFXFm7fLv8D1kJRvLtUx5S2CFwdgMlbR7xzu9K7umBdMCvfLlhZZ1JhM88aLnHO8FrsAa/FHqgd5wRZpAbkUVqQR2lBFqmB2nFOyt93KdyWlXUmVfD7+ymcvL4LQSn+OFPXHH/pa+KunHBLl3CtaPq5Li8ht7T5Csdzjuc/jm/Ne0lBSPTWhP8kOzjHOqDeGAWSXfgzH8UrHxFNCdObSxHiIAERwaG/Av1SFgm+4GAwGIwimICof5iAsCijKgIyKnodiAi/7sgSfNH3PnbsWA9TUxPs3btZ8Gv5VErO1wjBqMwwhKaHlOnAdvE5ILcU/ByQQ7XKfw5I8uE4WESbwjPJTSkYjjH2kEZKoTtdGzpR2pBGSuG40F75+55JbrCINkPyYfVs7VxEzqUMjJvsgXxTXdy0M8YtQynuyQvlo5A/tPntWDusCYvdCKP8tRDRXhtBwTroO8cHvdK6om58LRjPNoTeNG2M8+XPepR2BqSFPsFEm4PRNEtWAWEwGCoFExD1DxMQFmVURUBm/HQQRISEJYsFX/S9j2vXjmLo0H64e/es4NfyKZQ24O5DW9ZWxiT0L70CMmd4AxQYypHnZIaLdgrc1iHc1SLc0CVc1SPc1OarHb9WJzQfbYL6iXWV0+FHZw1EkyUN4RBTHSazjMBFcHAKI/xcm/BrNX4SeqQ3f/ZjrRPBSINgUIdgOduZzf5gMBgqBRMQ9Q8TEBZlVEVA4jdfgUgswZjJqjtPIz8/F1eu/P7hC/37uTiXk4pjGXE4l5OKgvuqcS7h5PVdCFwdUKahfYLe9y/8DMjiOV1w20QTN+2McaSGNo5YcriiT/hTzotIvoxwX5MQ1IkgjhBBO0qOKrON0XJ5E3Rb8zWcYx1RI8YO0qkS1BxImNCMcMicr5z8KSecNCFsdCD0b1zYfrcrQWOqFrounyb4goPBYDCKYAKi/mECwqKMqghIYtZ1GJtZo2twP8EXfW9jzJhBqFatKv78s+wzP05sTUJ2sBf2+Fhjr4cp9vhYIzvYCye2Jgn+enIuZaBjSluMygwrVUBGZoYhIMUPOZcyBL/Wkl2wnOCZ5AabEl2wrAq7YDkpu2ClHhP+HpcHBy9sxqm6prinL8VeGw67bQi7qhIOWBIOm/EiscWOIJpcbJJ5IVrTtKA/UwHjWYaoOZCwuyp/YP1fjp8b8i/xgwwPmhPMmhKII9A4AkVw0J1mjElpvwr+XGAwGIzELCYgn0OYgLAoo0oCUtW+NtoGBAq+4Hsbp07tweLF88r8509sTcLO1vbI8aiC7R2ckR3ohu0dnJHjUQU7W9sLLiHqUgEpouQcELPCOSBOxeaA8J/zXeb92chHEbmLI3DNQo4buoQjpoQ91vzHG7qE0yaEdkFvykcRoggOkikcNjoQ/hXx4vFEwnfPeiwmHCTCKCIYiAlkWfQ1EogiJPCKC2KDCBkMhkrABET9wwSERRlVEZCEzGuQ6+ih/9BRgi/23lion9yFP/449UFfU3A/F9nBXsjxqILsIHds6+6hJDvInf98iLeg27HK4wxIZVOWSejqvu3qbX9XM0c3xK92hMv6hOu6hEv6hC3V3y0fRdgNIvwl5eXjgZSwU0oYIibYEr/typAI34sIVt35Py+JkIGLEMP2h7qI2pgj+MKDwWAwmICof5iAsCijKgIye+UREBEWJCQIvtgrzoMHF+Hi4ozOnTt80Nedy0nFHh9rbO/gXEI+itjewQl7fKxxLkfYQ9Ilu2AFY2RmGELTg8vUBYtReZy8vgvNl3pBJsUBwwAAIABJREFUNkUMrxBCpy4Er5DSt12VxrCWhH1EGMIRqhZKhxEReooIG6SEByK+de/wVvz2K2mEJkQRYlT9wQWT1rFp6AwGQ3iYgKh/mICwKKMqAjJ89hoQEbbvVr0F7969m3HkyLYP+ppjGXHY62GK7EC3UgUkO9ANez3McCxD+DaxxeeABKT4IXB1AKZkj2TyIQBvGwiZcykDzZd6QWe6vEzCQREECidQHwI1IujLeOkwJkKwiJAuJeRrEB7KeIqqI1N9+O1X4ggJpFO14DKvFauAMBgMlYAJiPqHCQiLMqoiIN0GzYBIJMbtP1WntW1GRgru3z//UV+rLhWQ9y18GZXHwbwtmPDrMPgu84ZLnDPqxtdCl9SOiN87Az+ljUHQZEe4jtEDN+U90tGblw5SFHa10ibYVSNs4QiPOf7sR5F4PJTxv34qIjwTETp/UyQgUuhPt4D/4tHsDAiDwVAJmICof5iAsCijKgLiG9AbZlZ2gi8Cizh1ag+kUini4mZ+1NeX6xmQ/Fw8zkrFk+Q4PM5KxcN8/mvuXt6Hy76uuFHDFJd9XXH38j7B7xvj4ziYtwUtljeBYoYeRBEipVDUHEgY50v4qS5hXS0RfqrLYZwv/3mldEwhUC8CNSSQ3ivpoAYE6kmgKRzEkwhX9PhtVk/E/PT0hxr8xydi/vNXFATxJIJ0qgw6Ucaov7ADpqzfLviig8FgMBKzmIB8DmECwqKMqgiIc/2m8PBpKfhCsDg7d2746ArIw4evd8FyKuyC5aTsgnU8K/G980GepCbheXMvvLSxxksLU7y0sca/TRrijrEc/yPC/xXjJRGu1akq+H1Tdcqz2pOffxa7Mufhtynf4dSkEJxfPQc5uenK71uWn1Xw4AICV3eERqS0RDWj5kBCQn1+QODchoRIH/7jWidCnBuh6tcE8iwmHTqF0hFcKCUR/HkOrUgFdKOMEdpOjIcahOccX/H4W8x/fF5YFenfjiCP1IfFzJrwTezN5IPBYKgUTEDUP0xAWJRRFQExMrVSiRkg9++fx5Il8/HgwcVy+X4l54CY8XNAQryxe94AbAuojf11DXGgjgF2e1u+MR/kSWoSXjja46V5FbxwccYLTzc8sjDGcyL8r5DiAlL0ubJISMGd07gaH4688b1xNT4cBXfKf4K5KlL8vEvHlLYIXB2AyVtHfNR5l8x1EdjS0AR/6orwREr4W0J4oEk4Xk2OmWMaYkB6TwzY2PO9P+tw3q/Qjip5toObwlc+1joRwpsQwpu+YooPwV2nmHR4ECikuHS8kg9FlBl8E3uj6/JpMJtlj7B2EpzXJzyWEP4R8R/PGxCG+yvQbcVMDFqVjMgNv7FtVwwGQ+VgAqL+YQLCoowqCEjMhvPgOA7hM2YLvkC9dOkgiAhLlswvt+/5+iT0XfMG4JSNJm7oi5BnLMZ5cymO28lxqJbi1XyQ/Fy+8mFeBS8aueOFlwce2lng6Vvko7iEvCR653asvMiByDdX4KlMjGdSDk9lYuSbK5AXOVDw+1/R8vGq41cIRmWGITQ95KM6fmWui8BuJzkeyQhPpIQ/tQm3dAgPCn9901gDwb2NYTPPCl1Xd3rrz0r+PRZmM41hM5RQO5RgM5SXD5uhhBUufMWjuHyENyW0tOPlY2BVDs4jDKEZqQdphBZEEVJII2SoMrMaGscGIvTnxSVkInTlUtSc5wPjKWYI7KyBEa3F6BGoh24Jk5hwMBgMlYcJiPqHCQiLMqogIBPjtoCIsHbjWsEXqQ8fXsLvv2ejoODjtuW8r7JwPCsRp2y0cEuPw0lbTRyz18ZJWy1cMpXijLUmDtVSIDvEG482/4yXNtZ85cPLA/81rI+/tER48RbxeJ3Lvq6litDZsE74W1OMfyUc/tKVocBIjr/0ZHgm5fBEW/rZSkh5zjzJzz+LJR2tcVebwxMNDjf0OVzX53BDX4QbCg73tAh/yQi7HTRQc241NFnSSPkzi/+skHVdUWuQCOObE9JqEn61I6xzIKQ4E350JeyzJER6lZSP3vUIIo7gY0XYWFsTnUZ5wHluMzjObYyGsZ0xeNVP75SJ2Iw8jFyThn4pizByTRpiM/IEX1QwGAxGWWACov5hAsKijCoISO+xcSAi5F74XfCF6qfwvspCwf1cbAuojRv6Ipy00cQxBx0lR+21ccmUr4Ts9rbEzahheGlhiheebnjh5YG/HKviOff2ysfr3KyqKHFtJ7YmYev3nngi4/CCI/wjITzWEuGBgSYeVNFBgbEcz6Qc8i0USmkquH0SNyOH4kbvTrgZORQFt08Kfo8/lvKc+r5r60LscpThkSbhnq74lXwUckuPcF9GuKUQoffI6qgV64gB6T1L/Kx68XXgPIjDKmfCKRPCGWPCH3LCM46vYL0gvi1ugYzwiz0vH2O9CPqaBCs9wpwGhA31jREVG49J67YiamMOq2IwGAyVJzr1ONp3G4aart5o+XVf9BmfgKjl+5CQee29X8sERP3DBIRFGVUQkPbdh0NP31jwRWoRv/zyMzp2aINHmave6Dz1Lvl4oi3FMymHv3Q18EAhwyO5BP+KOTyR85WFczmp2O9qhDxjMY7Za5cQkGMOOjhpq4Xz5lIccDHAhdnDSlRA7psryiwf/0eEPEtt5aH2osPwZ+x08FxE+EdKeCLj8FRK+FuDU0rIX3oyPJWJcTU+HDcGB+FvHRleiAgvOcILEeFvHRluDA4S/O/nY8i5lIGOKW0xKjOsVAEZmRmGgBQ/5FzKeO/32rRqPA5XleCJBuG2/psCcl1BuKdFuKfDYWx/OzgutEev9UHKnzXsl/7QjNDAXE9+mvkZY8JlBd+Jqkg8/iPCv4W//kdM2FSd4GRM0JQQhnoQ1jmLsKRjA8RvZhUMBoOh+kxbthfNOvSEVKYJqUwT9Rs1h5GpJX+WjQh6BsZwadgK/j1HY+iMlZi37swb34MJiPqHCQiLMqogIO5N/eFU10PwRWoRGROHo62hAR5aWyo7Tz1v7oUnqUml/vmCO6eRb67AMymHBwoNPNYS4R8pv9D/R8J3Gco3luPohrk46GKAXHMpTtpqvSEgx6prI89YjP11DXFuz8/KMyD/NayPB7pS5dmPd4lI0e/vr6mNA8nhyL97WtkO+KSLKf7jCI81CI81RXisKcJTaWElxEQHBUZ8FeRWQyc8l4jwgiM8k4rwVFOMZ1L+188lIpWTkJt/HsXEpM4YMM0DE5M64+afR9/4M6pUAWm1rAlshxCOmhIuGBJ2WfGS8YL4Csizwqnkzwtb5r4gwhwJ/490zxr8wfQVngrELFgi+KKCwWAw3sWE2Cy4N/WHSCSGjp4BeoUOxdncQ6+ezaf3IzZpEb7rE4Y69b2gJdcFEYHjOJhXrYFGrb5Ft0EzMCE2C2Pnb2ICouZhAsKijCoIiLWdM9p1Uo1FbWmdp164OPO/drQvVUKuxofjqUyMR3IJ/tbglBWGx5ocnsg4PBMRnosIvwf7Yo+3FY7byXHJVIqjNV6rgBQeTN/WqQ4K7ucqr+W5sQGeaHB48Zp8vK0L1hMJ4ZYeh/2uRtgWUBv7XI2xvYMzfm9UVVkBKRKQJzL+eh8YavEVEA0RnmqI8YIjPNUU46lc+gpN/vN/68pUZjvW4B+aYEILDitcCGuc+YPbE1pwGPxDk5KSqEJnQJwXOqB1d8JVPcJ+C74C8qKw4vFMXIiIr4LkaxL2iQkyInytzb++8JZyTP1hmuALCwaDwSiNhMxrGDpjFZzcmoCIYGxmhVGTwnH9xqn3Pl/v37+A7Xu2IGLmbHz1TTfY1qgFkUgMIoJEKmMCouZhAsKijNACEp9xFVKZJoaMmSj4YrZ456l/G9bHHY96eOHlwdPIHS/Nq+C5r/cb27HyxvfGMwmHx4WL+ceanHKB/1hThCca/ALzRD1zZPdsjEPOCpyxkuGSaWElxF4bJ200+YPpNlo4nhVfQoj+cnXEMymH/wo7XL2tEvI/4hevZy1lyDWXYmczWxx2VuCakRg7WtkhO9AND+XiN6og/0gJDxQaeCbl8EhPxr8TLxWVlI9CnklFeCEi3IwcKvjf1+Afmrx1TkZCfXpDQkp2wQrGyMwwhKYHl1sXrD+KdcG6UaILVkCJn9V0aWP4dedwVY9wwIJwUZ//e31WioBc1iLYcQQXIkzzJLiMrIIpa38VfIHBYDAYrxO/+Qr6jE9AVfs6ICLY2Dtj5rz5uHuvDAN338H1G6ewat1qBPYIYQKi5mECwqKM0AIStXwfiAiLli3l36l+rWVtmSaFlxOPs1KV5y6+MTJAS329VwLi5YEXLk54aWPNnwkp9nVX48PxVIPDU3FR5UNUgn+kfAXklKMCOYtGYWdrexxyVuCEnRznzaXIMxbjhr4Ip2y1sHvBm12ozu35GcfrmOCKqQbuyfnp1cVF5EUhDySEo9X56srvNfWwLagBtrd3xA19EY7ZyZEd5I7jbhZ4JuHwH1d4FkTKL3b/lfBdsG41cMTL0qofxaogLznCjd6dBJWPm38exYQWnHJORkTTV4Q34SVkfAvuje1YxeeABKT4IXB1AKZkjyzfOSB2/ByQ0PRg5RyQgBQ/dFndEUN+6YNlh2JQf7QCR035GRxvVEAKt2D9KyJ0lhDkRDgqIUwK8WEHzRkMhsoRs/ECggZOh4m5DYgIdep7YUnychQUlM88rSJ2705nAqLmYQLCoozQAjI46mcQEfYd2vna0D5Tfmjfa8P5KpInyXHKzlN76jhhVx2nkgLi6YaXFmZ4khxX4usK7pxGvpEWXrxWWXisKcJjGb/Yf6glQo57FRzLiHv1Or2tcNDFkN8q1akOjmcllnpdBfdzkR3spaycXDQR44qhCH9pEB6LCX9z/FTri1XEfDvfqprY0bYGtnX3wLagBjhhJ8cNfRG2t3fEtu4eOO5mgYdyMZ6L+IXvcxEh34Lv1nUzciheiFS/AjIxqbNyTkZx+Shirie/XWliUuc376cAk9BTjiRg8Kbe6JLaER1T2sJtYW3MKzqEbshPJC86A/Kc4wVkkZg/97FUxKHAzAaJ6ZcEX2gwGAxGEXPWnIR/j1HQ1TcGJxLBp0V7bMzYWGHPfSYg6h8mICzKCC0g3/aPgFRDhiOZidjZ2h45HlWwvYMzsgPdsL2DM3I8qrwazlfBi9riFZAS4vGeCsjDh5dwJqwT/i1855o/A8J//I8jPJMQTjobYY+PNc7lpCql4kMqPUWdrIpXTq4rODyQEQo0CflahFxzvvKhlI9CdrSqjquGYhx21sP2Dk7IDnTDtnYOOGOngzM19HBiVFCJ1rt/68hU/gzIgGkeWOPMb7sqTUAifQirnQkDpgnf3OBtAxCbjDLGqlp8G95bcl5AXhZ2wDomImgToTtH+EdbF7vD2JkPBoOhGkxPPoAWAb0h05RDqiHDV52747f92yv8WcoERP3DBIRFGaEFpEn772BtV1PZqSk7yL3E4jk7yJ3/fIh3xW/HKnYG5HnD+oitZoP9dZzfewakSCiON7DCEw2+ovAfx398KBfjeD2zcnkNpVZOAmpj26Qu2O9qhJ3NbLEtqEGJ+7etuwe2d3DC/nr8n+WrS2Z8dSnEu1SxuzE4SOW7YH1KBaQyedfh95GbQ+EySILxzQnravJbsR5LCQ8Lz3zUIMIJQxG2D4gQfMHBYHzuJGRew6DIZPj3GIUO341A++7D0S5oCNoGDkKbLgPRuvMAtPymH1p06oPmHXuhmX8wmn7VAz7tvoO3Xzd4temKRq2+RcOWneHp+zUaNOsI96b+qO/zFep5+cG1cRvUbdgadTxaoHaD5nCu3xRO9Xzg6OqFmq7e6D02TvB78D4mJWTDs8U3EIklkOso0KPvIJw+e7DSnqdMQNQ/TEBYlBFaQBxcGqFRw0bY42ON7R2c31g8Fy2gi1cPKpKizlNHjAyhw4mgJxKhtVwHk7S1sdHCHBcS5rxTEHa2qIazdjo47WiI3z2tsL2dY7lWcUqrnBRt0XqfwOXfPV3mqkupc0B0VWcOyMeeAako3rat613tf7ut+QbyKDmkU0RwGqWJxkO14T5CBzXtpRCLCH6tNWEYboKRa9IEX3gwGJ8zw2ethp2TG4gIOnoGUBiawMDYDIYmFjAytYSJeVWYWtrCzMoOFlXtYWXrAGs7R9jYO8O2Rm3YObrA3tkVDrXc4FjHHU51PVCrXkPUqd8YLu5ecPVsArdGzeDe2BcePi3RsGlrNGrWFt4t2qFJy69Q260RiAieLb7B/HVnBb8fxUnIvIYRs9eidgNfEBEMTSwwbNwkXLl2otKf+0xA1D9MQFiUEVpAFIZV0MXfD3s9TPmtQaUISHagG/Z6mOFYRlylPOTi+vWDlkiEOhIpRmtpo6WGJvTFEuXAJKMqlmjcvC1Ch4/BilU/41LeMeXXljzH8u5KQ3lStEWL38LmVLiFzemT5EfVJ6GX6ILlWdgFy5P/dbz7m12wKoqDeVswKXMogma7o+skRwTNdsekzKE4mLflnQMQA1b6QWe6NvSm68Is2hQms40g764NIoK2vz6sZjtDf7oZ+qUsEnwRwmB8joydvwk1Xb1BRLBzdMHiCjg4XaZnbcFFRM6OhkxLG8ZmVTF63kbB7018xlX0n5SEajXrgYhgVc0RkT/MwZ075wR75jMBUf8wAWFRRkgBmZd2GkSEiaMGqUQF5F7+eXTvFQoignuTDlg9PQW/TliEjdFpSNh0GZFL96LPuHi0/KYfatRpCJmWtlJKzK3t0NwvACPGT8bq9an4fVtypXfyEkp+hKT4HJDVhXNAxpcyB6SiOJi3Bb2m1sOyBlLsseGwqxqHVXXFmNZaCyHT3bHh5Ip3VkB0p+tAf4Ye3BJc4BzpBJGWCPI6ClT/oQGsZteC0QxrVgFhMMqZSfFbUbdha35hbeuABQkJgojH6+w9sB01nOtBJBKjw3cjEL/5SqXfm4WbLqL7kFkwtbQDEcHZ1ROJS5eoxP1hAqL+YQLCooyQAlI01TQ9Y73gZ0AuXj4Kt4bNwIlE+Lr3BCRkXnvv9cdvvoIpi7ahx4i5aPpVD9g6uEIi0QARQSSWwMbeGX6dumJi5HRkbP2lUt45ErKNsVCUZRJ6hdzrBxewsIcDbujy7YwfSQkPNAjXFIR91hwWN5Bg+BxfTNo6vNQzIKMywmA8ywi607XhEe8GLVsdSAw0YDetPqpHe0Ax3QxO85ogNiNP8AUbg/E5MHXxbrg39QfHcTAxr4qo6Lm4l39e8GdYce7cPYee/QaDE4lQvVYDRC3PUV5/fOZVRG3MwaR1WxG1Madc23LPSzuNgJBx0DMwAcdxaNSsLdI2rRP8fhSHCYj6hwkIizJCCkjPkfNARLhy7cR7txAd3BSHFat+xnd9wlDdqS5qONfDwBFjse/Qzk9+qG3blQVTy2qQ6ygwOOrnT3pNsZsuYVxMBoIGTkfj1l1gaVsTnEgEIoJUQwaHWm7oFBSMqOi52PnbVty///EtYBnCsnf+INzR5Od3/CUh3NMk3NYiPNIg3NPiJSSqrRxpR38sMQBxxKb+6DuvCQInOaB9lBNsoi2h1UwOEhEsBjnCanYtKKabwWxWDYSuXCr4oo3BUHemJx+AV5uuEInEMDA2w/ipUYJuJSoLq9athpGpJTTluug1ZiGmrN8O/yWj4Rn7Ndxi2sEz9mv4LxmNKeu3f9K9mfnzYbT6pj80tXQgkWjAr1NX7Pxtq+CvvzSYgKh/mICwKCOkgLTpMhCGJhbKh0vxLUR7Gpgiqa4perhWQ23nWpDKNEFE0FUYwb2pP1wbt4VUQ6bcuxs2YsxHyciCxETItLRhYeOIyKW/VcjrXLAhFyOj16Fz38lwb+oPEwtb5dYtTbkuatdvjM2/bhL84c4oOwX3zuKGscYbk+mfc4T7mryEXFUQVrqI8NO6scoBiEHhtTCllRQ/uRDSanFY4yZDfw8FiAjytgroTzeD0QxrOM1rwuSDwfhEZq86iuYde0Ei0YCOwhBDxkzEzVtnBH9+lJWLl4+iaesOICJU8agGl9mt4JvYG35Jg+Gb2Bv1YtrBJ777OyUkIfMa5qw5hUnxWzFw6gp0HzIL7YKGoFGrb1HNyQ0isQSacl106zUAx0/tE/w1vwsmIOofJiAsyggpIK6N26BuA2/lw2XfoZ0YHzENDRs2grY2f75CQ6aFWu7N8E2fSZgY/yviM16VnOevP4feY+NQz8tPKSjVHOogdPgY7D24450Psvv3LyB4wBAQEVwbt8X89ecq9bXPWXMKQ6JS4N9zNIzNqsLF3Uvwhzuj7Fz4vo1SPl4U43+FszweFm7H2mlLSF4WhocPL2HQbJ9Xh+Yb8ofmw90ICjGhtkKMgRG90S9lEUauSWPbrhiMT2DOmlNoGzgQMk05tLR10WfQcFy5elzw58bHcL/gPFoN9YNIJoaWsR4aj+2C9j8OQ/sfh8Fv0RDUmdESzcKDERq+FN0GzYBf18Fo1PJbOLp6wdTKDjJNufINLyICJxLBwNgM1Z3qQkNDBrcGnsi7ckzw11kWmICof5iAsCgjpICYWdvDsY472nUKgol5Vf7shEgMOyc3tAsaghGz1yJ2U9mmP89ffw59xsXDzbudUkZsHWpjwLDRbwxIyrtyDB7eLcFxHPx7jCrTeY+KpGgrWs57pEmdKc/p40JTcOc0HihkStl4QYQXXCFFlRAiPBIT9tgQZq8IQdeV/hjnS8q2weFNCZObEKrpE3Q0CEsdRJjbzhaxv7Bp5wzGxzJ//Tn49xwNuY4eNGRa6NZrAHIv/C74M+NTKGrl3SW+MwztzcGJOBjWsIS2qT7EGpI35cLEHDWc68G7RTt07t4LQ0ZPQPTChVi7cS0OH/0Nd+/x5wIfPLiIHTvW4+jRih8gWF4wAVH/MAFhUUZIAdHW1QcRwczaHs38gzFgyhLMSzv9yd93wYbcN2WkRi30HzoKK1b9DAsbe2jKdREWvkzwfzATs64jZsN5aGnronvvUMEf8A8flr8sFG0/ClwdgI4pbRG4OgCTt47Awbwt5XvdlXQA/2p8OJ5JOWXV420S8lRESHLjUGW6IWyGknJwYnhTnua2/KKhhwvfPjjVVQtRsfGC//fIYLyLhekXMCvld4T/uBNj5qVjcNTP6DMuHt0Gz0SnXuPRNnAgmrT/Hh7NA1C7gS/sazWAha0jDIzNoSnXRXVnd3QbPBNz1pwq12v6tl84dPWNIZFoIKBrT5w4vV/wZ2l5ULyV96jNA1E/qDGqetaAc7t68OzhgxYj2qDhpIZI3bFCKRefK0xA1D9MQFiUEVJApizajpk/HarQn7FgQy76jE+Am3d7aMi0QEQwtbJD+I87Bf+HvDjNOvSEnoGx4Acjy1sWDuZtKXYAOwSjMsMQmh4C/5Q2CFkfVG4SUrIFsSnfgjjYq0JaEOeN741nEg7/il7Jh1JCCvk/IhTICC1HmMA62hK1QwlrnAu3XTUlhLgSOCI0qcr/OtKHsNZZjIiZkwX/b5Hx+RKfcRXz1p3B9BX7MSl+K0b8kIbQ8KUIHjUfgaFT0eH7kWj5TT94tekKN+/2cKrnAxuHujC1tOMX91KNEu+4l3j3neMg19GDkaklqlZ3grOrJzx8WqJF+6/RqWtP9Ow/GKHDx6Bew6bgRCJIJBpw826H0PCliPvl8ke9nrjNeeg+ZBYMTCwgEonR2v9bHPx9t+AL5fLkXcNMx24ZjND0YASuDsDJ67vK/D0fPLiI77//FhkZKwV/fR8CExD1DxMQFmWEHkRYmcRsOI9hM1NVbtJsYhbfl56IMC8+vtQHb8G9szi/dh6ypn+H1IUhyDyejPyC8n23q7xloeDBBUzeOqLUFrRjsgbBP6UNpmSP/OQKS8kOas6FHdScy3UCfXGuxofjqUyMJ5pi/PeahBQ/lP5zA014LfaA4cySFZAxjQl6MkJVBb8NK7wpXwH5yUXEKiCM9xK/+Qqilu/DuAWbMXTGSvSdkIjvhs7GN30moV3QEDT3D4Fni2/g0rAVatRpCCs7JxiZWkGuoweO494qEBKJBvT0jWFmZYfqNV1Qt4E3vHz90DYgEIE9+qLPoOEYNSkcUdFzEbc4CSvTUpGVnYFDR/Yg78qxD+rod/zUPgwePR5VqzsVTh83RDP/YIxbsLlsLdAzrqLXmIWoYlENRIQmrb7Crr3Zgi+QK4KKeI5eu3YMXl4eSEtbKvjr+xCYgKh/mICwKPMlCYiqU82xHuo1bPrGQzd3cQSO1zHGVQMRbuoS8vQJ2+3FGB5mh9Rj5bO4roh/5Crinbs3rvt+bqXPkCm4cxr55go8k3L4S0eKfyWccutVEX/oEHzi3OC12AMms43BTSGM8yWsqUlwNCJoSQjDi7ZjNSk8G9JKm50BYSAh8xqiV5/A2AW/oM+4eAQEj4W3XzfUdPWGibkNRGJJqQKhKdeBgYk5rKo5wrGOO9wb+6J5247w//Y7fNcnDANHjMWEqVH4IWYhflyxDOs2rcPO37bi5On9uPWHcJ2hMrM3o8v3faAwNCncklsdHQK6IXLSDMQmpSF+c16JezNgyhJY2tYEEaGBdwtkZm8WfGFc0ZR8cygYIzPDEJoeXO6VZFWHCYj6hwkIizJMQFSH74f9AI7jsP/wqwV57uIIXDWX46Yu4ZgZYb+NCCfMeRE5a8IhpI9xuUhIRchC8b3LpX3PkZlhCEjxQ86ljI++7nM5qdjjY43tHZxLyEcR2zs4YY+PNc7lpJbrP4R5kQPxRFvKS4iuBv7SleJvTRH+FRMKNAmRgabwWuwBr8UecIpxAEUQag4kfGvNLxZ7OfDbruZ68vIR704YEBEi+H+DjMohZuMFTFm0HWERyxAYOhUtAnqjbqM2sLJzgqaWTgmx0NLWhW2NWmjcvC0Ce/TFmMlTsWjZUmz+dRP2HdqJ8xd//yz2/t+9l4vZk4bCu6oJZCIOHBHq6srQ180BP8yOw9AZK2Hr4ArHEkCwAAAgAElEQVQiQm23xlibnib4NVcmxbfHBqT4IXB1AKZkj/wo+Th6dDsePBB+svmHwgRE/cMEhEUZJiCqw4INudDU0kGPvoPw8CG/7eqCqzX+1CEcMScctZZgfzUJ9ttJsd9Wglu6HLbZi9AiqdEnb8eqCFmojArIsYw47PUwRXagW6kCkh3ohr0eZjiWEVfu/xjmRQ5EvrkCT2ViPJNyeCoT47aZNsZ20oVLnLNSQBoluUNjqhTUj8CJCO7W/Has1c78x7EtCPWH6LPWu58R8ZuvYPqK/Rg+ew2+HxaNdkFD4NG8E+yc6kNhWOWNrU9mVnZw9WyCDp27Y+CIsZgTG4tNWem4cOmI4Iu+yqL4Vsr0to4YWt8GtQ34FrISjr9X9s6uWJbyEx48EP56haA8GoScOLETRIRVqxYJ/no+FCYg6h8mICzKMAFRLXzafQd9I1PcvZeLa/Mn4C+5GPc1Cflywl0dDtcMRDhuxUvISQsxrhgQAsIMkHXm097hrwhZKG1b15D1A+AZ3ARugQ1RvbMjvHv7Ymx4JMJnzMaMufMxJzYWC5MWIWn5UqxY9TNS163Bhs0bkJmdgR17fkXOwR04cnwvTp87iEt5x3BkWzJ2eVt9cgWkoOAi7t7Lxa0/zuDKtRO4ePkozp0/jFOnD+DI8b04+Ptu/HZgO3btzca2XVnIys7Apqx0pK1LRcrgXlgR+BUW9++BRUsSUXOQMxTB+rDrVx12fexRrVd1VOlmCjIkkDmBJhBshhJqh/IfdaYq2NBBNYMf7nYS4xZsRp/xCegUMh4+ft3h5NYEJha2EEukJSRD38gUNV3c0cKvE4IHDMHUWT8gZe0q/H7stw86O/G58q6tlMlf1UGYlQ4mN3NG/j3Vnl6uDty5cwarV/+ImzdPCH4tHwoTEPUPExAWZZiAqBYTYjNBRIidPAGXapnhmZhwW4twS4dwV5tQoEX4U4fDcSsJDtpKcFOPEPydDpIPf9o7/BV1YLz43uX209tD21QBTiKCREcDYi0pJBoa7zwYW1ZERNAQiSCXiqGnIYGhpgZM5TJYysQwkWvC0MQcCsMq0NM3hrauPjTlutCQaUEi0YBIJP7kn18mdDiIB0uhEaENjalyyCP14TDHi8mHirIw/QLCk3Zg4NQVCAyNRMuv+8K1cRtY2zlDU6772vkLXdjYO6NRs7b49vs+ym1SO/b8Kuj5CnVBqK2UDPWCCYj6hwkIizJMQFQPEwtDeMoJt7X5gXbPOcK/IsI/YsITCeGJlHBLl3DSXFRuFZCHDyvuoONvuRlw69wIJOIgr6qAy+RW6LhkDKas3658zfGbryBmw3nMXXsKs1cdxfTkA4hc+humLNqOCbFZGDt/E0ZGr8PQGSsxcOoKDJi8GH3GxSN41HwEBQWjf3UThFro4rvqpvi2hgW+sTVBoIk2Olrqo1XLdmgXNARffTcC/j1GISBkHL7pMxHf9gtHYGgkggZOR/chs9Bj+BwEj5qPXmNj0XdCAvpPSkJo+FIMnLoCQ6JSMGxmKkb8kIZRc9Zj7PxNGL8wAxPjf8WURdsQ8eMuRC79DVHL92HmT4fQM2EeakxrCIPJllBMqQLDqVaoOccH/X9Owsg1aWziuQoQn3EVM346iBGz16LHiLlo120oPH2/RnVndyiMTEsIhlgihallNbh6+OCrb7ohbMQYRC9ciPTMdORe+B0FBeq3n16VEHIr5ZfE+fP70a3b1zh1ao/g1/IxMAFR/zABYVGGCYhq0W9qd/S25N/R365PeFbY5vV5IU/EhH9EhH8khHtaVG5nQIooz4OODx9ewu6cbajuVBcikRjNA0MwfnUmojbmID7zarnet4UxS5HcyQeZDayx1dUMmQ2skdypCRbGCFddiM3IY7KhgkyK34rm/iGQ6yhKSIbCsAoc67ijuV8AgvsPRvjM2fh59UocPvob7uWfF3zx9TnDKiCVw44d6+Hk5IC8vMOCX8vHwARE/cMEhEUZJiCqw/z0XExpKcMGG4IWEYbKCI+lryZr/6+wxeuzwpav+ZqEXr2NSu2C9SlTwcvjoGNBwUWMj5gGDZkWTCxsMWZeeoXfv/jNeYhNSkPs3EVvtO9kfNnMX3cW3YfMUnZR0tM3RmDPfkhcugTbd2/BjZunBV9cfckI0U5baMrjOfulwQRE/cMEhEUZJiCqw6AfhiPZhbDElcO3MoIlER5KCM/EhP9ek5DnHOGEGYfla0e/8ZCuzKngpXHy9AG4e/mCiODj1x0LNuQKfm8ZXx4Jmdcwet5GNG4dCJmmHJxIhPqNmmNBQgLu3GGHmVWNkgNFnQoHijpV2EBRISleae6Y0haBqwMweeuICp3ncevWSVy4cEDw1/4pMAFR/zABYVGGCYjq0HdSZ6xxJkR5i7DcmN8Wsk5EeKjB81jCb8l6LCXka3PINZPiyKYF7/hHvOKngr9OzKJE6CgMoatvjLDwZYLfU8aXR3TqcXTuNwUWNg4gIhiZWqL3wGE4fPQ3wRdQjHdT8s0TM/7NkxDvz04+Xp21C8GozDCEpodU+FDBpKQ5EIvFuHz5kOD34GNhAqL+YQLCogwTENWhqAIyr6EI6x0JdYnwFRH+KhIQKS8g97Q5XDaV4pqhGAeSw5UPZyG3MVy5ehxtOnYBEcGlYSvMXnVU8PvJ+HKIz7iKIdNXon6TDpBINCCWSOHVoh2WJC9nbW7VjE/ZPlop5OficVYqniTH4XFWKh7mf9j21oroNlgW8vIOIyUlQfj79wkwAVH/MAFhUYYJiOpQdAZkrRMh0Y3wg4QgJsJFMeHvwupHgSbhbFUtXDKR4Ly5FEeLVUCEOsi5duNamJhXhUxTju5DZiEh85rg95LxZTDzp0Pw7zEKxmbWICJYVK2OIaMn4PS5g4IvlhifH09Sk/C8uRde2ljjpYUpXtpY43lzLzxJLVuFpjKGs37OMAFR/zABYVGGCYhq0W9qdyS6i5BRnXBMwR9GnyjmKyB35IQzZmJcMpXivLkG9tczKiETld3K8s6dc+jRdxA4kQh2Tm6IXPqb4PeP8fkTtzkPA6YsQR2PFuBEIkhlmmj11TdYvX4Na4fLqDCepCbhhaM9XppXwQsXZ7zwdMMLF2f+1472ZZKQnEsZ6JjSFqMyw0oVkJGZYQhI8UPOpYxyvfZt29IwdGg/3Lp1UvD7+Cns3LWBCYiahwkIizJMQFSPflO7I9xXA0dNCYESghVHuCUn5BlyyLXQwO+OujjkrHhjO1VlVkB27PkV1RzqQCSWoMP3IxHHOk4xKpjIpb+hTZeBUBhWARHBztEF4yOm4XLeMcEXRozPnPxcvvJhXgUvGrnjhZfHKxq546V5FTz39X7vdiyhKiC7d6fD2dkRx4/vEP5efgKrM5KYgKh5mICwKMMERDWZn56LsUM74ofqcv7vx9EIO1pUw65mNshxL/1AeWWcASkouIjRkyIglWnC1MoO4xZsFvxeMT5fFqZfQMjoGDi4NAIRQUtbF/5dvkfG1l8EXwwxvhweZ6XipY01X/koLh9FuDjhpY01fybkHd9HyDMgnwNL0xcwAVHzMAFhUYYJiGoTs2AJ6psbQSbisMjJ6L1dYSqyleWp0wdQr2FTEBGaftUDMRvOC35/GJ8nrw8LdHb1RFT0XDavgyEIT5Lj8NLClN92VZqAeLrhpYUZniS/f3tryS5YwRiZGYbQ9OAK74L18OElPHig3lsUWQVE/cMEhEUZJiCqz/y0M7CtVgM6OjrY+NP891YwKqKV5fUbp2Bboxb0DIwxKDJZ8HvC+DwZMHnxq2GBBsYICumP3XuzBV/4ML5syqsCUkTxOSABKX4IXB2AKdkjK1Q+2rb1Ra9e3QS/l58COwOi/mECwqIMExD1IDr1OKpYVEMVCxucPvv+Dj/l2cqyoOAifFp+BQ2ZFibGbRH8XjA+nfjMq4jamINJ67YiamMO4jOvCns9m6+gzbdhICLUqe/FhgUyVItyOgNSnMqehL5o0RysXv2j8PfyE2BdsNQ/TEBYlGECoj5ELt0LPQNjVK/pgmvXK6+bSb8hI0FE6DshUfB7wPh0pqzfDv8lo+EZ+zXcYtrBM/Zr+C8ZjSnrtwtyPXPWnIJz/abgRCIMHj2edbJiqCQlu2A5FXbBcvqgLliMT4MJiPqHCQiLMkxA1ItxMRmQacrh3tgXd++95d22ggt4dHIXHuVk4NHJXXhY8PHvrMUsSgQRoX334YK/dsa7id+ch9ikNMTOXYTYpDTEl9KZbMr67fCJ7456Me3gm9gbfkmD4ZvYG/Vi2sEnvnulS8jkxG0wsbCFXEeBJcnLBV/gMBjvouQcEDN+Doivt1rIx5Urv2P16h9x7576VhaZgKh/mICwKMMERP0YFJkMkVgCv05d33i3+NHBLXg6eQSeBwbgece2eB4YgKeTR+DRwQ/fW/zrjizItLRRz8sP8RnCbtFhvJuFMUuR3MkHmQ2ske1qhswG1kju5IOFMUuVfyY+8yr8l4xGvZh2aJc0FO1/HKakXdJQ1Itph45LxlTadqz+k36ETEsbVtUcsffAdsEXNwxGmfiESehCkp6eXLh4V9//rzEBUf8wAWFRhgmIetJj+BwQEXqFDVM+nB8d3IJ/Q4Lw3L8NnoWG4NmoMDwLDcFz/zb4NyTogyTk3PnDMDGzhpWdExZsyBX89TLezsKYpdjobY/sumZY61sLq9q5Y61vLWTXNcNGb3ulhERtzIFn7NfwTexdQj6K8E3sDc/YrxG1MadCrzc+4yradRsKIkLj5m1x5doJwRc2DMbnzu3bp3H69G8o+ISKuNAwAVH/MAFhUYYJiPri32MUiAiTp8/Cw4ILfOXDvw2ejRmEZ2MHv2LMIDz3b4OnU0aWaTvWnTvnUNutEXT0DBG1fJ/gr5PxduI35yG5kw+y65ohpb0HVn7lqSSlvQey65ohuVMTxG/Ow6R1W+EW0w5+SYNLFZC2SYPgFtMek9ZtrbDrnbfuDFwatgLHceg7eAQ778FgMMoMExD1DxMQFmWYgKgvCZnX4OPXHSKRGIt/mI3ngQF85aO4fBQRGozngQH8mZD3POT9u3wPkViCEbPXCv4aGe8mNikNmQ2ssda3Vgn5KGKtby1kNrBGbFKa4BWQiB93wcy6OjTluohfrN7deBgMdWTixGFYuHCG4NfxsTABUf8wAWFRhgmIehO3OQ91PFtCpiHDHq/G/Lar0gRkZBieB/jhUU7GOx/w4yOmgYjQbfBMwV8b4/3Ezl2EbFczrGrnXqqArPSrj62uZoidu0jQMyBhEcugKdeFubUddv62VfCFDIPxJRIc3BWTJ48U/Do+FiYg6h8mICzKMAFRf2I2nEd1O2cYSWXYE+CPf0YP+qgKSMraVRCJJWj6VQ/BXxOjbHxIBSQx680uWG2TBr3qgpXwXbl3wUrIvAb/nqPBcRwaeLfA5bxjgi9iGAyGesIERP3DBIRFGSYgnwfRK4+iqp4BP0FaQwYvi6oY5NYAyV+1x8X+Ie89A3Lg8C7oKAzh4NIIcb9cFvz1MMrGh5wBKfqaknNA2sMz9mt0XDKm3OVj/vpzcPNuByJCcP/BuH9ffQ+/MhifC/n5uXjwQD3PXjEBUf8wAWFRhgnI58PyBZuxyL05hlWtgSam1jDS1AIRgYhgqqkF7wZe6D90FJal/IRLxd6JvnLtBKra1YSxmTWiV58Q/HUwPozXu2Ct9Kv/qguWT40SrXiLqOhJ6JFL98LStiZkWtpYkJAg+MKFwWBcQlraUkgkEly4cEDwa/kYmICof5iAsCjDBOTzInXRdhzoMRrnfb/GRa922NW4LWY06wj/NoFwcGkETS0dpZSYWdmhuV8A6tRvDJmWNiYlZAt+/YyPo/gckK3KOSBNSpWPimZIVArkOgqYWtoie2eW4IsWBoPBc/bsXsydOxXXrqnnVkgmIOofJiAsyjAB+QzJuIqU5TlYE78VKctzkFhsiGB8xlWEJ+1Az5Hz0KxDT1RzrAc9AxMMmLJE+OtmfBJlmYRekSRkXsM3fSaCE4ng6tkEFy4dEXzBwmAw1JCCC3h0chce5WTw5xYLtw4zAVH/MAFhUYYJCIPB+BTmrzuLET+kwb2pP4gIQSH9cS//vPCLGAaD8QabN6dgx471gl/H23h0cAs/0yowAM87tsXzwAA8nTwCjw5uYQLyGYQJCIsyTEA+I37Jw8boNPw6YRE2Rqch8ZfKfQec8fkzL+00hs9ajW/6TESDZh1hamUHjuNARNCU62DW/AWCL2AYDMbbadCgHoKCOgl+HaXx6OAW/BsSxA/UDQ3h28qH8k1U/g0Jwp4VsUxA1DxMQFiUYQLyeZAZvhTXXX3wl6k1nhiZ4S9Ta1x39UFmeOWfAWB8HsxZcxJDZ6xEp5DxqN+kA0wsbJXnh6QyTTjUckPHLt8jfMZsZGZvxp075wRfwDAYjHeTl3cY9++rYIWy4AJf+fBvg2djXmslP2YQnvu3wb6+3zEBUfMwAWFRhgmI+pMZvhQF1vZ4YmiGu3a18IeTO+7a1cITQzMUWNszCWG8l+jU4xg87Sd07DkG9bz8YGxmrZQNmaYcNV3c8XVQMCJnRyN7Zxbu3ssVfsHCYDA+Gx6d3IXngQF85aO0YbqhwTjYqhkTEDUPExAWZZiAqDm/5PGVDwNT3HRugFu1PPBHbU+eWh54YmiG6/WasO1YDCWzVx7BwKnL0eG7EajbqA0MTCyUsqEp10Wteg3x7Xe9MWPufOzY8ys7z8FgfEZs374OrVs3w61bJwW/luI8ysnA845t+W1XpQnIyDAcbNaYCYiahwkIizJMQNSbjdFpmKmrr1xAEhE4IoiJIOU4yDgOWsRBU0MGTS0daGnrQq6jgLaeAXQVRtAzMIbCsAr0jcxgYGIBwyqWMDazhpl1dYSMjhH89TE+noTMa5j50yGEhi9F+27DUMezJRRGpsr/TuQ6CtSp74Wuwf0we0EMftu3nQ0LZDA+c3bvTkebNs1VbhYIq4B8GWECwqIMExD1JnNcPCxFIrTQ0UOCbTXE2VbDQltbLPh/9s47LIrrbcNnG0tfqhRBFBAEayxYwIYFS1RMjERNVNQYe2LBlogtFqyg2LtiwIaoFEEECyoapShgAFGwISKQ+jMmfnm+PzZMWEGDCswOvPd13ZfCLrvvzsKZefY0m4ZYZ2ODNVbWWKenh/mDh+CrOd9gqs88TJ45BxO+9sH4aTMxbsp0jJn0NbwnTMOoL6fi8y8mY8TYiWjfpRcYY/jwsxnYHJHL++skK6ffwevoN/wrNG3bDfqGJlzY0FUYoVX7LhgxdiLWBgbi0tU4FBUJczdkkiRroTQHpE5AAYTgoAAibOeMnAXGGC7bNsJfri7lbeGElzbW+CUy+K1OBkVFWRg/dQYYY+jQcwg2nsjm/bWSb3bCgh3QUxhDS0cPbTp2x6jxU+G/ZQuu3bhAYYMkSc5nz37EgwcpvNfxqqqrYI3G85mT8HziaOXXtApWrYACCMFBAUTYOrbshDY6enhpUQ9/dWyrGj46tsVLi3p44e6GksJ3mzS8Yt16SKUacGjRAWsO3eT99ZLlXX80HZ16DwVjDC5uPXErPZH3CwmSJNXXZs2a4IsvPue9jopU2QfEs69yHxDfmbQPSC2BAgjBQQFEuPpujQVjDGu9x+IvR3tlCGnhhL/at1b2fFjUw1+O9vg1eNt7nRC+PxoCHT0DmFvbYcmui7y/bvJfZ64+ChNza8i1dOC7bCX1dJAk+Z8eOrQD8fHHea/jtdJO6LUWCiAEBwUQ4dptwCjoKYzx6HEafg3ehhfdXfHSxhovLc3x0sYaL9zd3jt8lHo+4QzM6jeEnsIYPuuO8/7a67obT2TD45NJEIlEcGzeFgmJZ/m/aCBJkqxGKYAIHwogBAcFEGG6/mg6NLV08dm4Sf820IW38UtkMH7dF6ic8/GOw65eZ/rtq3Bs3hYyDTnGzdvM+zGoq367OQZWts6QSGWY8LUPLZNLkuRbmZp6DmvWLFLPDQnfIAUQ4UMBhOCgACJMP538HURiMa7duFCjJ4CHj9LQtfcAMMYw2HserZBVg24Kv4ePx30LqUwD9W0a49TpE7xfEJAkKTwPHdoBqVSKjIwE3mt5GymACB8KIAQHBRDhuTkiF5Y2DujQ1YOXk0BRURZGfjEFjDG49R2OwJN3eD8mtd1ley/DoUVHMMYw5LOxePgojfeLAZIk1dei4kyk5sUjITscqXnxKCr+d4+fp08zUFjFPeQ1IQUQ4UMBhOCgACI8p/sdAmMMuw/u5/VksHC5H8QSKZxad8G6I7d4Py610c0RuRg9az00tfVgZGqJvd8f4P0igCRJ9TYxJwoLomfAK8QTg4L6wCvEEwuiZyAxJ4r32t5HCiDChwIIwUEBRHi2dusHywZ2arHi0d7vD0BLRw+WNo5Ytvcy78emNrk6JAWt3fqBMYbufT2RdecG7+83SZLqbWJOFLyPDcPAIA9MDPPGrIhJmBjmjYFBHvA+NgyJOVHIz09Du3atEB5+kPd630YKIMKHAgjBQQFEWK7YfxVisQQz5/vyfjIo9Ux8JEzMraBvaIq5AfR7VBVOWbIPCqN60NZVYFVAAO/vMUny4muWYyUrtqg4EwuiZ2BgkAdmR07BnKipnLMjp2BgkAd8Y2bix8zL+PTTwbh0KYL3mt9GCiDChwIIwUEBRFj2G/4V5Fo6yLmbxPvJoKw3b12BnVNLaMi1MMF3Z5W+5oDjmfhuzyXMWX8CExfuwohpKzFwlA+6D/RGmy4D4NiyEzr0HILRM9djxf6rvL9H76N/6G106f85GGNo5dIZSanCmiRKklWlyoZ0g/ooN6RbMAM/Jwp7GFF1mpoXD68QT0wM81YJH6VODBsNrxBPpObF817ru0gBRPhQACE4KIAIx40nsqFvaIoPh4zg/URQkXn3b6Jjtz4QiUT45MtFr30dmyNyse7ILSzecQ4zVx/FF/O34NNJS9F/+Nfo3O8ztOrkAVunNjC1bAhNLV0wxsqpqzBCfZvGaNa6I9x69EMD2ybcbWZWtujS/3OM/2Yr1hxK5f19q6xz1p+AWX1byOSa8Pl2kVoMsSNJPvw5MQp/eA/Di4EeeD7RG89nTcLzid54MdADf3gPoxDyGhOywzEoqA9mRUyqMIDMjJgEz6C+2HtqIx49usl7vW8rBRDhQwGE4KAAIhzHzgkEYwwxcZG8nwhe57NnmRg68gswxtDe/SN4DJ2MTr2Holk7d9g0bgGjevUhlWmUCxRiiRQGxmawsXdGq/Zd0KP/R/Aa+QWmzJqLJavWYMe+PQiPPonkm5dQ8LTi1VtuZSRiVcAG9P9oGMzqNwRjDCKRCA3sm6Hnx+MxZck+rD+Wwfv7+KqBJ++g//CvIRZLYNekBeIuRPP+PpJkqW9aTalaLMpU9nwM9MDz2VPwfM7Uf509BS8GeuB/vjMrHI5VWHQbkWnB2HctEJFpwSgsEt5KT+9jZXpAhn4/CHr6Opg//yve631bKYAIHwogBAcFEOFo17QdnFu15/0kUBnnLlwKXYURjM3qw86pJdq59UAfTy98Nm4SZsxbAD//AOwLDsKZ+Ehk/HgNz55V/UXN1evnsXCFH7r39YTCqB4XdOyatkO/4V9hht9hbDyRzet7unB7HGwcWkIslsB7wjQ8eZLB+3tHkqXysZrSz6nxeOHlqez5KBs+Sp04Gi+8PJVzQsr8XHDSNnTf5QqbddawXG0Gm3XW6L7LFcFJ23g/jjVlZeaALIiegYSEU0hLq9k9pKpCCiDChwIIwUEBRBh+s+k0GGNYs2ED7ycBIVpUlIWz509j9oLF6NitD7R1FWCMQUOuBafWXTDYex7m+p/CplN3a+T93ByRi08nLYVMrgmz+o1w9MRR3o8RSZa1MqspVcfz/pwQjheD+iiHXVUUQGZOwgvPvvg5IZz7meCkbXDcYA+L1fXQItAZ7be1RotAZ1isrgfHDfZ1KoSovm+jMTNiEiaGja72960mpAAifCiAEBwUQIShW9/hMDA2o0/Iq8inhT/iRGQYpsyaiw86dIWGXAuMMWjr6qNlRw94TVwM362x1bLT+4oD1+DcpisYYxgwZARy81J5Px4kWdbKrqZUHcOx3rYHpLDoNrrvcoXF6nrouK0tXHe4cHbc1hYWq+vBfbdbnRqOVbbnyjOoL7xCPOEbMxOJOVFYsmQOtmxZzXuN7yIFEOFDAYTgoACi/q49fBMaci2MmfQ17yeA2urj/HR8fzQEYyZ+BaeWLpBIZWCMQWFUDy7dPfH516vw3Z5L7/1ejpu3GTp6BlAYmWLr7l28v26SrEheV1N6yzkgkWnBsFlnjRaBzirho9QWgU6wWWeNyLRg3o9rTfq6uTsjRnyMOXOm8l7fu0gBRPhQACE4KICov0PG+0IskSL55iXeTwB1xdy8VOzYtwefjh6PRg7NIRKJwBiDiXkDuPUZBm+fAHy1/CBmrT6KuQHh+HZzDBbvPI/l+xOxKjgJ64+mY+OJbK4HZe3hm3DpPhiMMXTq3gfpt6/y/hpJ8nVWdjWlhOzwanl+1VWwRuP5zEnKno+BHnj+yipY+64FwnK1Gdpva11hAGm/rTUsV5tj37VA3o8r+X5SABE+FEAIDgog6u2m8HuoZ9kInXt+yHvjX5fNzL4O/82bMchrJCxt7CtcGrgiRSIRZHJNSKQyaMi1sXTVGlpel1R71WE/CZV9QDz7KvcB8Z1Zbgle6gGpvA8fpqK4WLjtDwUQ4UMBhOCgAKLeTliwA4wxHDwawnvjT/5rxo/XkJB4FrHnonDq9AkcDjuCfcFB2LZ3FwK2boGffwCW+K3G/MXfYca8BbBpZIv2HdrxXjdJVkY+54CoWImd0GkOSOUdO3YE2rVrxXsd7yoFEOFDAYTgoACivm46dReWNg5o1roTfWoucNPTLyI/P433OkiysgppNSXVVbCc/lkFy6lOroL1JrCdyFkAACAASURBVGNiDuPgwS281/GuUgARPhRACA4KIOrryBlrwRhD6KlQ3ht+smrMzb0h6CEQZN3yTasp8V3bq6ruA2IOm3XWcN/tRuGjFkkBRPhQACE4KICopxtOZMHItD46de/De6NPVo3JyWehp6eDo0d3814LSVbWGt8J/T2s6zuhv8mLF08hMHAFCguFe0wogAgfCiAEBwUQ9XTIeF+IxRLEXYjmvdEnq8bi4iysXPktsrISea+FJMm65YoV38DCwkzQPbAUQIQPBRCCgwKI+rnuaBp09Y3QZ5AX7w0+SZIkWTt88kTY89AogAgfCiAEBwUQ9bPf8K8g05Djh6QLvDf4ZNW7f38gRoz4mPc6SLK2WViYjviIdbjgOwK3FoxByan9KBHwkCNSVQogwocCCMFBAUS99Dt4HXJNbXiNGs97Y09Wj/v3B+Kjj/oL/tNIklQnI44uwukOJsjXE+M3GcPvUoaftSUoaNEIeX6zkBQeiIyEYBQ9q3uBJDr6MBwd7XDz5nnea3kfKYAIHwogBAcFEPWy28DR0NbVx+3MH3hv7EmSJNXdouJMHAj6Cmcd5fhZg+FXDREK9SR4oifGTxoMf4gZfpOLkd5YgfOdrREz2hUp0XVrZazLlyMxbtxngp6AXlJCAaQ2QAGE4KAAoj4u2XUREqkME7724b2hJ6vX4uIsHDq0A5cvR/JeC0kK1cScKHwT+RWW9dJEvjbDzxoM9xUiPDKUokBfgl80GJ6LlCHkqZkeYvs3QYJLPcT1tq9zIaQ2SAFE+FAAITgogKiPLt0HQ2FUD3n3b/Le0JPVa2HhbTRq1AAzZkzkvRaSVHeLijOReu8srsXtwIVQP1yN24HQ5N0YffRTfLyiJaLtRPhJzpCvy5BnIEKeQoQSTYbfpAy/aDD8T8Lwu5YE13o5IWZYWyS41EOMt1udGI5VVJSJw4d34v79ZN5reV8pgAgfCiAEBwUQ9fCbTachEokwb9FS3ht5smbMykoU9JKYJFkTJuZEIWDHSGwf3ADH2mrjZAs5jrfTw5r+hug33wZjF3+Ay9Yi/KLB8EDBcN9AjId6DL/KlOHjZznDbxKG/2mIkeJmjzMjXBA7wAnnO1sjIyGY99dX7ccvMQqMMYSF7eO9lveVAojwoQBCcFAAUQ+btXOHWf1GePIkg/dGnqxZ09Mv8l4DSaqjiTlRmLKqCw501MXxphJs6CiBXzcZAl1lCG0qwb4O2vh8gplKD8h9AzEe6yl7P36Sl+8BOTPCBTFerXHRxRxJ4YG8v8bqtrg4CzduxCI/X/iLXlAAET4UQAgOCiD8O2PVETDGsCpgA+8NPFmzhoRsh0QiwfXrZ3ivhSTVyaLiTEwMHQm/fvoIaybDCncNrO2lizW9dLDcXYbFXRlONpNjTT8DLO4hVc4BkTPcVzA80hPhV6lyTshvEobnEoZCM32cGda2zvWA1CYpgAgfCiAEBwUQft0ckQtbp9Zo5NAMz55l8t7AkzVrfn4atmxZjadPqeeLJMuanHsWHovtcKSNFja7aWJNLx2s662Ldb11saaXNpZ0EyGgoxgnXPQx7EtjnG4swU8ayqFX+ToMP8kY/hAxvBAx/KIjRVLXxsrejzo2B+Tjjz/E4cM7ea+jKqQAInwogBAcFED4dYLvTjDGsHP/Xt4bd5IkSXXxaPIu9JxpiqhWuljdXY61vXS5ALK2ly6WdZfiuy4Mka10MGCuNcYsa4sjbbXxSFcZQn7/p+ejWFuM5HZWiPFqjdgBTnVqFawnT9LQv38vHDq0g/daqkIKIMKHAgjBQQGEPzedugtLGwc0a9MJRUU0GbkuO2/eNEyZMpb3OkhSXTySvAsd5tfDiXb65XpA1vXWhV8PTfh3YDjUWo7uvtYYF/oZJhz7HJ8sbY7lY+xxftZHyFw1HWdGdsT5zta46GKu3AfE261OhI/aKAUQ4UMBhOCgAMKfI2esBWMMoadCeW/YSX7181uABQtm8l4HSaqLybln0WJDE6zqp0B4c034uf/bC7K2ly5WuMsQ1kwGv/4KtNjQBIMO9IFXiCd8Y2YiMSeKe5yiZ7eRkRBc53ZCT0yMwvr1tWtVRQogwocCCMFBAYQfN4Rlwsi0Pjp178N7o06SJKluFhVnYsLxUXCfY4YDHXUQ1kyGTa4aWOuuiU2uGghtKsGBTrqY598Xx1P3IiE7HKl58Sgqprl0JSXZ+Oab6XBycqgVq1+VSgFE+FAAITgogPDjkC8WQCyWIO5CNO+NOqkePnp0E8uWzUdWViLvtZCkOpiYE4XBB/uh33wb+PVTIPgDDRxrJsHBVhKs6KeHxRs9VXo7yGxub6Hi4qxasflgWSmACB8KIAQHBZCad93RNOjoG6Lv4E95b9BJ9TEn5xoUCn3s3UvLMZNkqYk5Ufj29HQM2NsTn65sg7GLP8C8rYMRmrybejtKVIeY/RCzB507d0Bo6J4qe/zCglu4sm8h4laOxZV9C1FYcIu310oBRPhQACE4KIDUvP2GTYNMQ47rybQBHalqbfvEkiSrwqLiTKTmxdMwq1dMid6GmNGuOOdWH1eaGyKuuSG6Wynw/YY5VfL45/wn45qzArlGEjzSFyHXSIJrzgqc85/My+ulACJ8KIAQHBRAala/g9ch19TGp6PH837yIkmSJIVpSvQ2xPW2x9WmClxvpIWL9aTIMZHgvoEYN200XxsSKjsp/5z/ZGSZyfBQX4T0+nIk22kjvb4cD/VFyDKT8RJCKIAIHwogBAcFkJq124BR0NbVx+3MH3g/gZHq56FDO2BhYYaHD1N5r4UkSfW06NltxIx2xdWmCqRZa2KajhgWEhEu2WojtaEmHuqLcLOhFpIjt6j8XGmPyXk3KyQ2N8ANJwNc7m6P9D3foaTo316lwoJbuOaswEN9EW7YayPJQZfzhr02HuqLcLWposaHY1EAET4UQAgOCiA155JdFyGRyjDhax/eT2CkepqYGIU5c6biwYMU3mshSVI9zUgIxjm3+ki21Ua2mQynG2phlYUmFxJSbTRx30CMM4Obcz0cXI+JswIZVpoo0BXjFw2G36XKzRpz+rfHz4nKCf1X9i1ErpEE6fXlKuGj1PT6cuQaSXBl38Iafd0UQIQPBRCCgwJIzenS3RMKo3rIu3+T9xMYSZJkXbO2zCVJCg/EleaGCDSU4FIDzfIhwV4HOSYSXG5lzA2zihntiqvOCmSZyVCiJUaJthhPFFI80RfjFxnDT1piFPZ1w8+JUYhbORaP9EVIttOuMIAk22njoUKEuJU1u3kqBRDhQwGE4KAAUjN+ExgFkUiEeYtq18ZQZNX67NmPiIsLRXY2LcVLklVpYk4UFkTPgFeIJwYFKTctXBA9Q5DL+GYkBON0UwMYiBhmGGuUCwipDbXwo4UMiS2MuLke592skNxIC4U6YhTrSPDYUIrHRjI8NpLhiUKCnzQYnljq4/dvp+PKHl/qASGqBQogBAcFkJqxWbvuMKvfCE+eZPB+8iLV1ydP0sAYw5Ytq3ivhSRri4k5UfA+NgwDgzwwMcwbsyImYWKYNwYGecD72DDBhZCiZ7dxxrMZLumJkGyjGhJuNNZFtpkMybbaOO9mxU04T2xhiDumUhTriPHE4N/w8dhIhseGMhRrifDIRI4Sj84o+uE0zQEhqgUKIAQHBZDqd4bfYTDGsCqA9ncg/9vz58OQm5vEex0kWRssKs7EgugZGBjkgdmRUzAnairn7MgpGBjkAd+YmYIZjhUbexTjx3+OH05twE0b5YTzVBtNJNnrILWhFrLNZEizkuOqswIx3m7cqleXWxnjvkH53g9lD4gUhbpiPDCVo9jtA/ycEP7GVbAyzWkVLOLdoABCcFAAqV43R+TC1qk1Gjk0w7NnwjjBkSRJCt3S+R5Hk3fhw/29MOH4aJXwUerEsNHwCvFEal487zVXxh071sHV1QWPHt3EOf/JuGmjhfsGYuSYSPCjhbLn46qzAnG97ZESvU15LP7pMXmkJ0Kx9is9IIYyFOmIkW8gxX0LHZR4dMbPqcpjUXYfkIcK5T4gV5vSPiDEu0MBhOCgAFK9TliwA4wx7Ny/l/cTFykM169fii1bVvNeB0kK1bLzPbrvdoXVGku47WiPsaEjygWQmRGT4BnUFwnZ4bzX/Sbz89O4/xeVWTI3OXILzng2w+VWxkhsYYTzblaI8XbjwkfZ+91soImf5AwlWmI8NpDiiUKKIh0xCvQleGiigSc2xvj92+nlluSlndCJqoICCMFBAaT63HTqLiwaNEbzNq4oLub/BEYKwxEjPsaECaN4r4Mkheir8z2+CP0MDv62sF1vg1abm5ULIULoAcnLS4Kjox3Wr694EZO32Vww01IDv2gw/KrBUKQtQr5CgnwjDRTU00Fh/y7cUrzqKAUQ4UMBhOCgAFJ9jpy+BowxhJ4K5b3hJkmSrO1WNN9jduQUdNnZAY39beEQYIcuOzuq3CaEOSDFxVn49tsZ+OGHmPd+rOTITbjUwx655pp4aiBDgbEmHtmZ4rG3p1qHj5ISCiC1AQogBAcFkOpxQ1gmDE0t4erel/dGmyRJsi6YmhcPrxBPTAzzVunlGHNsOJw2OqD+Ggs0WmeNscdGYGLYaLVfBaugIB3nz4e988+/bt+Tome3kXHhINJ2LUbOPj+UJMWqDLtSVymACB8KIAQHBZDq8aOx8yEWSxB3IZr3RpsUloGBK+DgYMt7HSQpNBOywzEoqA9mRUziwsfY0BHosrMD7P0bwXilIbSWaqHRehv03dcDvjEz1TZ8lJRkw9d3FvT19ZCbe+OtfzYxJwrfnpqK8T6OmDbWEuN9HPHtqalq/Xr/SwogwocCCMFBAaRqDQj9Ed0HjYFIJMKATz7jvcEmhWd09GHMnTsNxcVZvNdCkkLy1R6QsaEj0GpzMzgE2KF5oBOcAhrDao0lOmxrjSHBA3D5TiTvNb/JJ0/ScPr0obf+ucScKEyfYo8zdiLcMWC4r8dwx4Ah2k6EKRMa4PKdCN5f27tIAUT4UAAhOCiAVJ0zVx+FqWVDyDTkmOYzH08Lf+S9wSZJkqwrlp0D4hMxGV12dkDDddawXmMJk5VG0F2mg3p+JnDb3h7dd7sKYu7HuxwD3+ktkGaqDB43zBkuWDNcN1d+fcuE4YtxZmofviqSAojwoQBCcFAAeX8DQn+Eu+dYiEQiODRtTcOuyPfyyZM0xMWFIi+PNiMkybe1dBWsnnu6wGadNYxXGsJghQIGKxQwW2WKphubwCHADs4bHdB3n7varn61ceNy6OnpvHUI+SErAmfsxLivw5BmzJBlwJBmwnDOWul9PYYoO4Yhe/sIbjgWBRDhQwGE4KAA8n7OWnMM9SwbQSrTwJRZc6nXg3xvk5PPgjGGsLB9vNdCkkI0MScK40M/h/5yPeh8pw1TP2M0WGuFDzY3h+sOF3Ta3g72/rZw3uiAi1knea+3Ii9disCqVQtRWFjxkrolJRXv0bFn/XAUaDL8T8zwF2N4yZT//i5hyDRkuGHGkG3AMPwrK7XvAXpVCiDChwIIwUEB5N0MOJ6JHoPHQSQSobHzBzh7/jTvjTNZO3z6NAPnz4fh4cNU3mshSaEacesg6q8xR2N/W7TZ0hKdtreD6w4XzhaBTrBZZ43ItGDea30Xz/lPxlVnBe4ZifFQX4R7RmJcdVbggqM2Fzr+EDE8Fyn//YsxvBAxZCkY8vQYZo5voPb7n7xqiKcrBRCBQwGE4KAA8vb6rA2FWX1b6vUgSZJUUy9knUSTDY3R2N+2XPjotL0dGvvbwmmDAy6oaQ9IQUE6jhzZhfT0i+VuO+c/GZlmUjzQY0iyEOGSjQhJFiI80FWGjP9jDH8whueSMv4TQv4nZsjWZ/D5pq0gdoAv9ea4frgiZhRABA4FEIKDAkjlDTieiZ4fj4dILIa9cyvq9SCrze++m4cDBzbxXgdJCtXUvHj03dcDzhsd4Rhgh7ZbWqLj9rZou6UlHAPs4LzREX339VDbHoDHj2+BMYYtW1arfL+w4BauNNHFAz2GizYiXLKV4bKtDJdsZUg3VoaP0h6Q52LVEPIHU96eVI9hwqERb9UDUtnd1qvDwkfJKNGW4CqjACJ0KIAQHBRAKqfPuuMws1L2ekyaMZt6PchqdejQQZg27Qve6yBJoVq6Ilb33a7ovLMDmm50hOMGezTd6IguOzsIYhWsW7cuoKAgXeV7l/cuwF1DhiRzES7/Ez5KvWP4b/j4858ejz/EyiDyR5k5ISHtdd9qB/iU6G2IGe2K852tcdHFDOc7WyNmtCtSorfVyHFIm++NP0UMlyQUQIQOBRCCgwLIm90QloleH38JkVgMO6eWiD0nrFVDSJIk66qlK2INONAbIw59jJFHvDDi0McYcKC3Wu+A/ibDlnjhgR7DFRtJuQCSYSLCX/8EkBINhv9J/g0if/4zH+R3CYPPuAaVfv0p0dsQ19seCS71EDvAGTGffID4bja45qyP853qIzmy+ntqb37mjr8Yw0UpBRChQwGE4KAA8npnrwuDubUdpFINTJw+GwVPa67LmSSLijLx4EEK73WQpJBNzInCgugZ8ArxhGdQXwwNHoRpJ8ch6PpmpObFq3UPiJ/fAixdOlfle6GbJyDHgCHZQlwugFyykeB/YuUwq3xthvsKEfJ1GAq0GR5rKcNHlhHDghOV2xG96NltxIx2RYJLPcQMa4uzfRrjB0d93LbUwF1jCfJ1GX6w00T04YXVehypB6T2QAGE4KAAUt4NYZnoPWSCstejSQuciRfehk2k8G3X7gOMGTOc9zpIUugWFWciNS8eQde3YOrJsRgaMgiDgvrAK8QTC6JnqG1PyIwZEzFlyliV793IjkJcYxke6DFcbihVDSENpSiWK4db/S5RBo8H+sp/f5cwFGkyHJ/SvdJhISMhGOc7WyN2gDPO9mmMtAaauGckwQMFwxNthiI5w68yhlRzMVb4tK+240hzQGoPFEAIDgogqs5ZfwLm1vaQSjUw4Wsf6vUgefPgwS2IiTnMex0kWRssHY41MMgDE8O8MStiEiaGeWNgkIeghmMVFWdixez2SDcV4YEeQ4qFGIkNJUixEOOBHkN6PRFCOhvirrEEv8gYfpcy/CJjyDGRIGZ6v7d6rqTwQFx0MUPMJx/gB0d93DOS4LEOw1Mthgd6DHn6DM/kDE90GK5ZiTF1hVu1HUdaBat2QAGE4KAA8k+vx4kseHwyCSKxGLaOLRATR70eJEmStcHSCekDgzwwO3IK5kRN5ZwdOeWtJmTXtBXthJ6YE4X5XzVFnL0UOYYM9/UZcgwZzjaWYv5XTZGYE4WCx8mIW+aN01+6I26ZNwoeJ7/1c5f2gMR3s8FtSw08UIjwVIshV6H0gZ4yfKSYi5CnYNjSXQ++UdOr7TjSPiDChwIIwUEBJA8z/A7DokFjSKQyjJ82k3o9SLVx27Y1OH58L+91kKSQTc2Lh1eIJyaGeauEj1Inho1Wy035DhzYBJlMhvv3y4eHxJwoLAifhqlzm8NnfENMndscC8K/qtIeiNI5INec9XHXWKIc0qX3bwB5qsVwz4DhSkMpso1FiHGWY8xat2o7jrQTuvChAEJw1OUAsmDLGTR36QHGGOycWuL0Wer1INVLV1eXcmPASZJ8OxOywzEoqA9mRUyqMIDMjJhUpZvylc45ScgOf6+J7snJZ7F69SI8fJharc/zJlOit+F8p/rI1xOhWK4cdvVATxk+HukyJFlJ8EMDKdLMxDjrJMeYxR9U+eaGpXuQHPSfQwFE4FAAITjqYgBZvj8RnXoPhUgshqlFA/j5B+DZM/XreifJp08zeK+BJIVuTfaAlF11SwgT3StjcuQmJNnp4FcZQ+E/cz7uGSjDx+VGUtw2FSPRRorQNtpV3gNSdg+SnU2NKIAIHAogBEddCiBrD9+ExyeTINOQQ1dhhJnzffE4P73KGkqSrC6Liiggk+S7ys0BOeCBL4+PhPexYZgQNgqzI6dU6RyQqp7oXlSUicOHdyI5+SzvxzApfCMyLDWUcz7MGK40VPZ83DYVI7m+BOcc5Fj7oXGVzgF5dQ+STb2aUAAROBRACI66EEA2nMjCkC8WQEfPADK5JkZ+MQU5d5N4b9BJsjJ26tQOPj6Tea+DJIVscNI2tN7SAlZrLWG73gZOGxrDZesH6L7btUpWwaqOie7FxVnQ1tbCsmXzeT9+JSXZOOc/GSkN5MjVZ8g0Ykirx5BmJsZNCwkinTUwdZlrlfX0vLoHyZkRLtjctykFEIFDAYTgqM0BZFP4PXj7+MPYzAoisRh9B3+KpNQE3htxknwb165djLCwfbzXQZJCtbRnovtuV7Tf2hrOGx1gu74hrNZYoPWWFghO2vbez1Fdw7xu376kVkMxb5zagMhu9ZFeT4xncoZfpAw/yRkeKSRIa2mB2zsWVcnzlN2D5MwIFwogtQQKIARHbQ0g074LgrWdsrFq36UXYs8Ld/wtSZIk+W6+2jMxO3IKJoSNwphjw/Dl8ZEYcKB3lQy/qumJ7nxYOh8juYkCv2ow/E/C8FRHhGwbPeQ2MkShoRwPrfSrJIRwe5B4taYAUougAEJw1LYAMn9jBJw+6AzGGByatsb3R0N4b7RJ8n0sLs7C4cM7cf58GO+1kKTQrIkJ6AVPb2Fb8Ff4eL49PlvdHj6nJlbZ82zYsByzZ0/h5diVrj6VFB6IhK2zENfLDgltTPHIUIZfNER4oi9GkY4YBfoS3LUzwp2m5ig0lCOrtQ2Knr7f/ErqAamdUAAhOGpLAPluTwJcug8GYwwW1rbw37wZRUXlN3AiSSHq6GhHy/GS5DtY3T0Tu/dNxqp+CgS1EuOwM8O+FgyLessxZlnbKtnscMmSOfD2Hlajx6zo2W0kbJ2F2P6OuNTGFBfbmiLDSo5McxmutDHDT1oiPNWT4LGRDI8NZSjSEeORsQbuNLNAbiNDPDHVRvaRDe9dA80BqX1QACE4hB5AVoekoMfgcZBKNaAwMsW8RUtpI0Gy1pmTc63CHZFJknyz1dkDsnvfZOx0keGoswibXOVY010T/h3EOOzEsLWtGN7ftcHEsNHvvAoWH6ZEb8OZD52QYyrFQ30RsupJkdJQE/eMxLhrLEGukRS/yRgeG0iVAcRIhicKKQp1xchpbII7TmZ4aihHRuC8Kqnl31WwnGgVrFoABRCCQ6gBJOB4Jjy950JLRw9yLR2Mnfw17uWm8N54kyRJkupjRatT+URMxvBDH2NQUB+47nDBN6fffunYgqe3sKqfAkedRVjbUxvreutiXW9drO6pjWXdpDjsxPBtTwn673F/731Aiooya+QDiJTobTjb0xY/msuQYyJBkp02Uhtq4Z6RBMWaDGnWGrhvKFbO/SjtAfmnF+SZjhh3bQ2rrAekbE3/7gNiTAFE4FAAITiEFkA2nbqLz79eDUMTC4glUgwc+jlupSfyfpIjyeq0uDgLPXp0xtq1i3mvhSSFZtn9Ofru6wGbdVbQW6YLzaVy6C7TgcvWD956JawjxxciqJUEm1zlXPgoDSDL3TXg30E5HKv/0ib4Nnr6OweQ8PAgSKVSpKZW3eZ+FVk65CmxuSFuW2ogtaEWkhx0keSgi1QbTZTIGR4oRLjZQI5fNBh+lTE8NpSq9oDYG1XZHJBXa6Od0GsHFEAIDqEEkM0RuZi0aDcsbRzBGINbj344n3CG9xMbSdaUM2dOREjIdt7rIEkhmpgTBa+QQdBfrgv5UjkMVihgvcYSDv52sFhdD44b7N8qhGzbPhZHm4qwrscrvR/dpVjaXYIVXSU45Mzwma/zew3B+vHHy1izZhHu3v2hWo9P6aTvc25WyDKTIclehwsgN+x18FAhwk9yhpvWcjxUiFGiJcYvchGe6olRpMVQoC/BUwMNPKiiVbAq8ty5MAogAocCCMEhhAAyZ/0JNG7eAYwxOLdqj2Mnj/F+MiNJkiSFY2HRbXTb1Qn1/EzQItAZzQKd0HJTU7TZ0hIdt7WFxep6cN/thsKiys0hfLUHZG0vXSx318DS7hIsd5choKMY+1syjFvXpcp2W4+OPlxtx6d02dvYPo3L9YAkOegizVqOIk2G+wbKeSHXWpnisaEMv8kYfpMxFBhqIKu1TbWFj5ISCiC1AQogBIc6B5DFO8+jTecPwRiDVUMHbN65g1a2IuusxcVZiIsLRUpKHO+1kKTQjEwLhs06azj426HB2vow9TOG8UpDmPoZo8Ha+nDwt4XNOmtEpgVX6vFenQOyppcOvusuxTJ3GZZ1k+KIM8MiDzm3JO/7LvcbHn4QjDGcPn2oWo5PaQ/ImQ+b4AdHfWSbyXCjTC9IakMt3DERI8dUgnQrOS66mOG8a31c7O2IH2Z9guwjG6p02FVFUgARPhRACA51DCD+obfRbcAoiCVSGJqYY+FyPzwt/JH3ExhJ8mlRUSZMTY0xY8ZE3mshSaG571ogTP2MYepnDMMVBjD1M4GZnwlM/Uz++doYpn4m2HctsNKPWXYVrMBOMizvIkJABzGOODNsbSdWWYq3KjYiDA8/yP2/qiell1329qyHPdIaaCLbTKbsCbHTxl1jCTLNZYjrYYuL23yQFB6IjIRgFD2ruVUnKYAIHwogBIe6BZDNEbn4wLUvNORamPC1D+4/uMX7iYsk1cVr16Lx9GkG73WQpNCMuHUQBsv1obNMG7qLtWD/tRStJoph/7UUuou1oLNMGwbL9RFx6+BbPS63D0hLMQ45M+xvqez5KBs+qmrDw1KDg7ehffs2yM1NqtJjVHbZ23OdrXDdQQ/Z9aR4pC9CjokUsQOckBL9dpP1q1IKIMKHAgjBoW4BZOAoHzDG4L95M+8nLJIkSbJ2eOPeGRivNITTZIa57gx7WzAcclb+O9edwWkyg/FKQ9y4d+atH7vg6S0cCl2AL5a0wYffOWHWyQkq4aOq5oCUevbsMYwa5YVnz6p+ZEDZZW8vtquHhDYmdh4pzwAAIABJREFUiO3fBBe3+dRob0dFUgARPhRACA51CiCTF++BSCTCqPFTeT9ZkaQ6+vRpBgYP7oegIAroJPk2Xsg6iXZfa2NzG4bDTgxrOzAs6az897ATw+Y2DC5f6+BC1sl3fo6yy/1ODBuNmRGTqn0jwnPnwhAeHlSlj1m67C0fw6z+67VSABE2FEAIDnUJIIu2x0NLRw9tXd3x7Nn7f0JEkrXVoUMHUQAhybc0LHkPvunOcNaGIcSJYVcrhkVdGBZ2ZVjYRRlC5vUQISx5z3s9T2JOFBZEz4BXiCc8g/rCK8QTvjEzq20X9E8+GYgOHdrWyEaFfEsBRPhQACE41CGArDuaBnNre1hY2+JOTtWOaSVJkiTJrV9+gIe6DMUaDD9pMBTJGbINGL5vxrCkmxjr2iuHY/kf+PK9n6uoOBOpefFIyA5Hal58lQy7ep0FBenIybmGkpJs5ObeEFwQeZveFgogwocCCMHBdwDZFH4PLTt6QFNbF2fPn+a9MSRJIZiaeg537lzlvQ6SFILn/Ccjx1CE3yUMj7QZcvUZHukog0iBFsPBZgxLOyvnhKzZ5MV7ve/i06cZaNq0CaZPn8B7LZVVZb6JixnOd7ZGzGjX1050pwAifCiAEBx8B5APP5sBxhgCd/C3sgZJCsknT9KgqSnHd9/N470WklR3Cwtu4UoTXTzSYcjXZrivx3BP8Y/6yhCSbcjg76Jcwepw6ALea35Xt29fiytXInmvozKWXXErdoAzYrxaI3aAMxJc6iGut32FIYQCiPChAEJw8BlAJvjuBGMMYyd9zXtjSJJCMiLie+Tm3uC9DpJUd49vmYgcQ4YkM4YchbLH457+vyHkkQ5DkYZybsiKvnooeCr8pd+fPs3AuHGfITX1/Zf8rQ7L7jkSM6wtzoxw4YwZ1lb5fW+3csOxKIAIHwogBAdfAWThtrPQ1NJFhy69adI5SZIkWeUWFWdi1VdtcF+P4UpDCa5bivBQVxlC7uspg8gDXYbfJAzRdiLs3jeZ95qrwrS0C2jc2BYnTx7gvZaKLN11PXaAs0r4KDV2gBPOd7ZGRoLqrvQUQIQPBRCCg48Asu7ILZjVt0V9m8a4ey+Z98aQJIXmo0c3MW7cZ4iKCuG9FpJUV1Pz4jF1TnPkGDIkW4hx2VaG65Yi5CiUw7EKtBieyZXu/qoL7/VWpYWFyt6D4uIsXLhwgvd6ypoUHoiLLmaI8WpdYQCJ8WqNiy7mSApX3ZWeAojwoQBCcNR0ANkUfg/NXXpAS0cP5xPO8N4QkqQQLS7OgotLa+zbt5H3WkhSXU3IDseg3T1xzkGOB3oMlxtKcdlWhksNpbhmJcZ1C+UQrEuO2igsEP7Qq4rcvz8QYrEYV6+qzyIv1ANSd6EAQnDUdADpN2waRCIRtuzayXsjSJIkSdZeU/PilftwTG+J2/XEeKDHkGIhRmJDCVIslF+n1xPjxMqRvNdaXRYVZeLo0d3c1+qwTC/NAam7UAAhOGoygHz57TYwxjB+2kzeG0CSrA3evHkeYWH7eK+DJNXRouJMLIiegYFBHlg2sy3OOchx15Dhvj7DXUOG2MZSrJzdoVr36VAnd+8OQP/+vZCfn8Z7LaqrYDn9swqWE62CVcuhAEJw1FQA8d16BnItHbi690VREf+fwJBkbXDcuM/g4GDLjfcmSVLVxJwoeB8bhoFBHph4+DP4LnTDoslNMWG2E7yDP6m2HcrV0cOHd2L06E/VohekpOTVfUDMlfuAeLvRPiC1GAogBEdNBJC1h2/C1LIhrBo54m5uCu+NHknWFgsK0pGRkYCSEuVQC77rIUl1NDEnCguiZ8ArxBOeQX2Vw7JiZtap8PGqMTGHcfky/3uG0E7odQsKIARHdQeQTafuomnbbtDWVeDilVjeGzuSrI3m56ehW7dO2LRpJe+1kKQ6WlScidS8eCRkhyM1L77ODLt6nV27dkKfPu681/E2UgARPhRACI7qDiAeQydDJBZjx97dvDdeJFlbLSrKxOTJYxAR8T3vtZAkqf7m5SXh7t0feK/jbaQAInwogBAc1RlAxs3bDMYYJs+YzXvDRZJ1xeLiLBw5sov3OkiSVG+zshJx8uQBwQzfpAAifCiAEBzVFUC+3RQNDbkWuvT8kCadk2QNGhq6B4wxxMcf570WkiTV1+3b14IxhkePbvJeS2WkACJ8KIAQHNURQNYcSoWJeQM0sG2C3LxU3hstkqxrqtvOxyRJqp95eUlISoqlHhCixqAAQnBUdQAJPJUDpw86Q0fPAJeuxvHeYJFkXfTixVNITj7Lex2k+ljwOBlxy7xx+kt3xC3zRsHjZN5rIsm3kQKI8KEAQnBUdQDp9fGXEInF2HNwP++NFUnWVfv164n27dvwXgepHsZM74e7xhL8KmX4n4ThdwnDfYUIp0d2eOOyp2Tt9saNWHzxxefIzk7kvZbKSAFE+FAAITiqMoD4bo0FYwxTZs3lvaEiybrso0c3kZREy16TyvDxk5zhhYjhfyKGF4zhT8bwkjH8IWa41NL4tRu/kbXbc+fC4OzsiJQUYYxWoAAifCiAEBxVGUBGTFsJkViMe7TZIEnyprrsckzyb8HjZNxXiPFnafj4xz/EyiDykjH8KmU4625DIYRUeymACB8KIARHVQaQTr290MC2Ce+NFEnWVQsK0uHgYIv9+wN5r4Xk37PfjcRzMcP/xMqhVy9EDM/FDM8lSv9kDH8xhpQGmojxdqPhWHXQ4uIsLF06F7m5SbzX8l9SABE+FEAIjqoMIJY2Duj30TDeGymSrKvm5SVh2rQvcOVKJO+1kPwb/Wlr/MUYfpUwvBCrho/nEoY//ukFSW2gifOdrZGREMx7zWTNeuNGLBQKfRw6tIP3Wv5LCiDChwIIwVFVAWTd0TSIRCL4LlvJeyNFqodFxZlIzYtHQnY4UvPiUVQsjKUeSbK2GD2+G/5kDL+Ly/d+lA0gV5vo4aKLOZLCqeesLnrv3nXu/2fOHOG9ntdJAUT4UAAhOKoqgHy1/HswxnAmnj55JbORmBOFBdEz4BXiiUFBfeAV4okF0TOQmBPFe2211ZSUOPj7f4f8/DTeayHVw9TYHfhJg+HPfyafqwQQkTJ8PBczxLnVpx4QEmfOHAFjDCdPHuC9loqkACJ8KIAQHFUVQAaO8oGWth6ePaNPueu6iTlR8D42DAODPDAxzBuzIiZhYpg3Bh7wwJDgAQi6voV6RKrBwMAVMDIyxOPHt3ivhVQPi57dxqWWxvhDrJzr8SdTBo8/RP98LWLINpEgoW09mgNCoqQkGydPHuAWsnjwQL0WlKEAInwogBAcVRVAWnTohRZtXXlvoEh+LSrOxILoGRgY5IHZkVMwJ2oq5kRNxdjQEei8oz2s1lrCaUNjDA0eRD0i1aC6XTCQ/JsSvQ1J9jr4VaLs8Sj1uYjhoS7DVWcF4nrb0ypYpIrh4QdhbGyoVvPJKIAIHwogBEdVBJDNEbnQNzTB519M5r2BIvk1NS8eXiGemBjmrRI+Wm1uBocAO7QIdIbzRgeMODQEA4M84H1sGIWQKjA39wYtv0u+1pTobTg9wgW3rDWQr8PwRJvhR1MxLn9gjBhvNwofZDlzc29g7txpePbsR95rKZUCiPChAEJwVEUA+W5PAhhjCNxBJ7G6bkJ2OAYF9cGsiEmYEzUVsyOnoMvODnAIsEOn7e3QcXtbOG6wx5hjwzA7cgoGBnnAN2YmDcd6D9PTL6J9+9b49NPBvNdCqq9Fz24jIyEY10/448q+hbhxwh8ZCcE07Ir8TxMSwtGnjztycq7xWgcFEOFDAYTgqIoAMnZOIBhjuJWeyHtDSfLrqz0gE8JGoelGR7Td0gquO1zQdktLNN3oiAlhozAnaiomho2GV4gnUvPiea9dnc3NTeKGV0VGBmPo0EFcj0fnzh3QqVM7hIcH8V4nSZK1z8jIYHTv7opHj27yWgcFEOFDAYTgqIoA0sNzLEzNrXlvJEn+fXUOiPexYXAMsEPH7W3RaXs7OAbYocvOjtz8kJkRk+AZ1BcJ2eG81863hYX/fhK9e3cAAgKWoaQkG48f34JIJMLmzX4oKcnGsWO74ebWngskly5FIDX1HO/1kyRZ+01Lu4DVqxfxMuSTAojwoQBCcFRFALF1ao2uvQfw3jCS6mHZVbA+OzwEThsao0WgMxwD7NBqczOMDR3BzQ+pqz0gxcVZ2LBhOc6dC0NJSTYOH94JqVSKO3euoqQkGxMmjMKQIf/+Te3fH4hbty7wXjdJknXbNWsWwcrKkped0ymACB8KIATH+waQjSeyIZVpYPq8b3lvGEn1sXQfkKEhg+C0oTGs1ligy84OKuGjts8BuXfvOvbs2cD1VMyf/xXc3d242y0tzbB06VyUlCg/VVyzZhEvJ3WSJMm3sbSdys29UaOrZFEAET4UQAiO9w0gc/xPgjGGoyeO8t4okupl6U7oQdc3Y0jwAAw40BsTw0ZjZsQkTAwbXStWwcrKSkRs7L+/+x991B9+fr4oKfn3ZFl6e0jIdqxc+W9QLzvkiiRJUmhOmuQNS0tzPHlSM5ufUgARPhRACI73DSBeExdDKtXAo8e0+zL5esvujO4Z1BdeIZ7wjZkpyPBx/Phe7hPAb775GsbGhtxt06dPwK5d/igpycbTpxnckCqSJN/dwsJ0xEdvwInv5yE+egMKC9N5r4nMxsOHqYiLC62x56MAInwogBAc7xtAXLoPhp1TS94bQlK9LSrORHLuWRxJ3oWjybuQnHtWkMOuHjxIgYmJEebNm4aSkmzcvn0JSUmxtAcHSVaTEUcXYcfgBjjaRhsnW8hxtI02dgxugIiji3ivjVR69eppnD17rNqfhwKI8KEAQnC8TwDZHJELE3NreH46ivcGkFRfy/Z+DArqA68QT0Hugl4aMn74IYaGT5FkDRhxdBG+d9XHyeZy7OtmiF39zLCvmyFONpfje1d9CiFq4oABvdG5c4dqfx4KIMKHAgjBURpARkxbiXkbwt/KkdNXgzGGBUsW4dy5MJIs594TGzFgtQe6LO2IIWsH4POATzBk7QB0WdoRA1Z7YO+JjbzXWBmnTRuPvn3dERcXynstJFkXjI09gm+7m2O9vQwL3Izh29mEc4GbMdbby/CNuzliY4/wXmtd9/DhHYiMDK7259m2bQ0FEIFDAYTgePz4MRhjJEmSJEmSaq22tjby8vL4vnQi3hEKIIQKjx8/xo0bN0iSJEmSJNVWCh/ChgIIQRAEQRAEQRA1BgUQgiAIgiAIgiBqDAogBEEQBEEQBEHUGBRACIIgCIIgCIKoMSiAEARBEARBEARRY1AAIQiCIAiCIAiixqAAQhAEQRAEQRBEjUEBhCAIgiAIgiCIGoMCCEEQBEEQBEEQNQYFEIIgCIIgCIIgagwKIATxDsTHx4MxhpKSktfeZ+HChWjZsuUbH2fUqFEYNGhQVZf3VjUIBcYYjh8/XqWPWZn3sSa4d+8eGGNITk7mtY6a4r/ey8q8L3v27IFCoaiO8ipdgxBQh3aIIAjiVSiAEHWOUaNGgTEGxhikUikaNWqEmTNn4rfffqv0Y1Tm4uTXX3/Fs2fP/rOWdznx5+bmQkNDAz///PMb70cB5M3wcZFZ0Xv+8uVL5Ofn46+//qqxOt6Fsn87ZfXw8Hirx/mv9/LFixfIz8/H33///dr7vE8AadiwIaKiot54n9oSQKqzHSIIgnhXKIAQdY5Ro0ahT58+yM/Px/3793Hw4EFoaWlhwoQJlX6Mqro4edcTf0BAAHr37v2f96MA8mbUJYAIhbJ/O2UtLi5+q8epivfyXQNIamoq9PT08Mcff7zxfrUlgFQGIf9OEgQhTCiAEHWOik6248aNg7m5eaUfo/TiJDY2Fm3atIGWlhY6duyIH3/8kbvPqxf/L1++xPTp06FQKGBkZAQfHx+MHDlSpZa///4bfn5+aNSoETQ1NdGiRQscOXKk3PO7u7sjMDCQq6Vdu3bQ1taGQqFAp06dkJubq1LD/v37YWNjA319fXh5eeGXX37hHuuPP/7A1KlTYWpqCrlcDldXV1y7do27vXXr1lizZg339aBBgyCRSLjel/z8fDDGVF57WUpr2Lp1K6ysrKClpYUhQ4aoXNhdu3YNPXv2hLGxMfT19dGlSxfcuHFD5XHKXrSWDlk6dOgQ3NzcoKmpibZt2yIzMxPXrl1DmzZtoKOjAw8PDzx9+vR1b2OFF5lHjx6Fs7MzNDQ0YGNjo/LaS4+Xj48PrKysoKGhAXt7e+zcuROA8j0eM2YMGjZsCE1NTTg4OMDf31/lWLzaexAfH1/hEKxz586hXbt20NDQgLm5OebMmaPSQ9K1a1dMnToVPj4+MDQ0hJmZGRYuXFju2FtbW0NDQwMWFhaYOnXqa49FZaiqC1XGGHbs2AFPT09oaWnB3t4eJ06c4G6v6H3Zs2cPrK2toaWlBU9PT6xZs6ZcADl58iRat24NuVyORo0aYdGiReV6lZYsWYIhQ4YAUPYkfvjhhzAwMIC2tjacnZ0RERGhUsOb/sYBYPPmzbC1tYVMJoODgwP279/P3TZjxgx8+OGH3Nfr168HYwzh4eHc9xwcHLB169bXHqv09HT07dsXOjo6qFevHj777DMUFhYCALZu3QpLS0v83//9n8rPDBgwACNHjgRQPe1QZY/NiRMn0KZNG8jlchgbG2Pw4MHcbS9evICPjw8sLS2hra0NFxcXxMfHc7e/6b0hCEL4UAAh6hwVXURNnToVxsbG3Nc2NjblLubKUnoCbt++Pc6dO4f09HR07twZnTp14u7z6onfz88PCoUCR48eRUZGBsaOHQs9PT2VWubPn48mTZrg9OnTyMnJwZ49eyCXy3Hu3DnuPiUlJZDJZLh//z7++usvKBQKzJo1C3fu3EFGRgb27t2LvLw8rgZdXV189NFHuHXrFi5cuABzc3PMnz+fe7xp06bB0tISkZGRSE9Px6hRo2BoaIiioiIAqhdRf//9N4yMjGBiYsJdDHz//fdvDG8LFy6Ejo4O3N3dkZycjPPnz8Pe3h7Dhw/n7nP27FkcOHAAGRkZ3LExMzNTCUoVBZDSY5WRkYEOHTqgdevW6NatGxISEpCUlAR7e/s39my9eqF7/fp1iMViLFmyBJmZmdizZw+0tLSwZ88e7meGDh0Ka2trhIaGIicnB7GxsQgJCQEA/Pnnn/D19cW1a9dw9+5dBAUFQVtbG4cOHQKgHA4zdOhQlV6EFy9elAsgDx8+hLa2NiZNmoTbt2/j+PHjMDExUfmd7Nq1K/T19bFo0SJkZWVh3759EIlEiImJAQAcOXIE+vr6iIyMRF5eHq5evYrt27e/9lhUhsoEkFGjRqFr165vvA9jDFZWVvj++++RnZ2NadOmQVdXl/ude/V9SUxMhEgkwooVK5CZmYmAgAAYGBioBJDTp09DX18fe/fuRU5ODmJiYtCwYUMsWrRI5bnbtm2LAwcOAAD69++PXr164ebNm8jJycGpU6dw/vx5lRre9DceGhoKmUyGTZs2ITMzE2vXroVEIkFcXBwAZSBSKBRcQPD09ISJiQl8fHwA/Bveb9++XeFxevz4MUxMTDBv3jzcvn0bSUlJ6NWrF7p37w4AKCoqgoaGBmJjY7mfKS4uhoaGBqKjowFUTztUmWMTHh4OiUQCX19fZGRkICUlBcuWLeNuHz58ODp16oQLFy7gzp07WL16NeRyObKysv7zvSEIQvhQACHqHK9eRF29ehXGxsYYOnQo9z13d3ds3LjxtY9R9hPAUiIiIsAYw/PnzwGUP/FbWFhg5cqV3Nd//fUXrKysuFp+++03aGpq4vLlyyrPNXbsWAwbNoz7+uDBg2jdujUA5QUIY0wloJRl4cKF0NbWVrmQ9/HxQfv27bnnlMlkOHjwIHf7n3/+CUtLS6xatQqA6kVUSkoKTE1NMX36dO4iavz48fDy8nrtsVq4cCEkEgkePHjAfS8qKgpisRj5+fkV/szLly+hp6eHU6dOcd+rKICU9jwAQHBwMBhjOHv2LPe9FStWwNHR8bW1vXqhO3z4cPTq1UvlPj4+PnB2dgYAZGZmgjGGM2fOvPYxX2XSpEn4+OOPua8ruoh/NYDMnz8fjo6OKnMgNm3aBF1dXe5itmvXrnBzc1N5nHbt2mHOnDkAgLVr18LBwQF//vlnpWv9L0aNGgWJRAIdHR0VlyxZwt1n7ty5+Pzzz9/4OIwxfPvtt9zXv/32G0QiETcv49X3ZdiwYejTp4/KY3h5eakEkM6dO2P58uUq9zlw4AAsLCy4rx8+fAiZTMYFnebNm5cLKKVU5m+8U6dO+OKLL1R+7pNPPkG/fv0AAD/99BPEYjGuX7+Ov//+G8bGxlixYgXatWsHQBnezczMXnucFixYUG6o5YMHD8AYQ2ZmJgBg4MCBGDNmDHf7tm3bYG5ujpcvXwKonnaoMsemY8eOGDFiRIWv686dOxCJRHj06JHK93v06IF58+YBePN7QxCE8KEAQtQ5yl5EyeVyiMViDB48GAUFBZV+jNITcNnhPUlJSWCMqfQ+lJ74f/rpJzDGyn2C5+npyZ34r127BsZYuYs7mUwGFxcX7meGDh2qcmIePXo05HI5PvzwQ/j7++Px48fcbQsXLuQunktZt24dGjVqBEA5Hp4xxg3ZKluXt7c3V3vpRVRAQACGDBmCkydPcjU5ODhg8+bNrz1WCxcu5J6vlNLjURqcCgoK8OWXX6Jx48bQ19eHjo4ORCIRNm3axP1MRQGk7FCxuLi4cu/J7t27YWho+NraXr3Q/eCDD8pd9ISFhUEmk+Hly5c4dOgQJBLJGy/qt2zZgjZt2sDExIR7/0ovOIHKBZDBgwdj9OjRKvdJSUlR+f3q2rUrJk2apHKfgQMHcu/b/fv3YW1tDSsrK4wbNw6hoaHvPcl91KhR6NmzJ7Kzs1UsvaCvLIwxHD58WOV7+vr62LdvH4Dy70urVq2wePFilfv7+/urBBBtbW1oamqq/O1oamqCMYbff/8dgHK4VLdu3bif2bFjB6RSKTp16gRfX1+kpqZyt1Xmb9zQ0BB79+4tV1fZ3/fSIYypqakwNTXleih++eUXjB8/XuWDj1fp168fZDJZuTaBMYbIyEgAwKFDh6BQKLg5LV26dMHXX3/NPUZ1tEOVOTZaWlrYvXt3ha/r8OHDFT6HVCrljseb3huCIIQPBRCizlH2Iio3N/edPiGuaIx6cnIyGGO4d+8egLc/8ScmJnIX5a9e4N2/fx+AsndCX1+/3HKtSUlJWL58OTp27AhdXV1cuXKlXA2lrF+/HjY2/9/evYVE8bBxHF+zdRU854YamnQyqMhIzIQoKkmRUJcCo4N2YRAqmleCURcSKF1YZnlT5KURpgWhdiN4URkpYeYxJYSgAxEdsEjh97+QnddJd13ff02vb9/P3erozs7sLPObeZ5nV0uae1Lrlp2dbbqq6j6Jcrlcqq+v18ePHxUQEKCRkRHZbDYNDAx43FbzBZBPnz6ZtkdmZqaSk5N1//599ff3a3R0VFFRUaqtrTX+Zr4AMns7eOob8Nao7MuJbktLixFA7t275zWA3Lp1S4GBgbp69ap6e3s1OjqqU6dOmfaBLwFkdgB0c7+/3O+F3bt3q7S01LRMdna28vPzjceTk5O6e/euSkpKFB0drZ07d/6rOyK/sgfk5yb0sLAwo9Tt5/2ydevWBQNIYGCgampq5hw7o6Ojxl2jjIwM03tKmglqDQ0Nys3Nld1uV11d3bzrIM09xiMiIozQ5FZbW6s1a9YYj90ljHV1dUbvybZt29TW1rZgeM/IyJDL5Zr3Nbmn9k1OTiokJETNzc2amJiQn5+fnj59avyP3/E55Mu2iYyM9BhAmpqa5O/vr6GhoTnPMfuuqKd9A2DpI4Dgr/MrTqIWG0CkmdKHmpoa4/HU1JTi4uKMdfn8+bMcDoepifVnHR0dio+P97puqampRrPxQgHk69evCggImFOCtWrVKl28eNH4WXl5ubKyshQVFaX+/n5JMyfrJ06c0MqVK72uj7sEa3a5RXt7u6kEKzg42PS6JyYmZLPZLA8gnkqwNm3aZDyvn5+fxxKs4uJi7d271/Szffv2mfZBYWGhqTF5vtfjqQQrJCTEVIK1UACZbWhoSDabbU5z/2L8qQBy5MgRZWZmmpbPy8sz7du0tDRTaP7Zly9f5HA4NDY25nGZiooKbdmyZd51kOYe455KsLKysozH7hLGnJwcY3BEWVmZMdL4xYsXHtfH/T5Y6M5Vfn6+XC6Xampq5pQc/o7PIV+2zZ49ezyWYLlLGbu6ury+rtlm7xsASx8BBH8dX06ifO0BWUwAqa6uVkREhO7cuaPBwUEVFhbOaf6srKzUihUr1NjYqJcvX6q3t1f19fVGmUdRUZGKi4uN5cfHx1VRUaGHDx/q1atX6ujoUGRkpHFVdaEAIkmlpaWKjY1VW1ubqQl99mhV95V/p9NpnBSXlZXJ399fhw8f9rot3U3o+/fv17Nnz9TV1aUNGzYoLy/PWCYpKUnp6ekaGBjQ48ePtWvXLgUFBVkeQHp6ekxN6I2NjXOa0AsKChQXF6eWlhaNj4+rs7PTaDK/dOmSQkND1d7eruHhYZ09e1ahoaGmfXDhwgXFx8draGhI79+/148fPzw2oRcVFWlwcFCtra3zNqF7CyA3b97U9evX9fz5c42NjamyslJBQUELfieEN57G8LqnMkm+94AsJoA8evRIfn5+qqmp0fDwsK5cuTJvE/ry5ct1/vx59ff3a2BgQE1NTaqsrJQ005S/efNm03OWlpaqvb1d4+Pj6unpUUpKilEC5Msx7r471tDQoJGREaMJffY0J3cJo7+/vxHeW1tbjePJm9evX8vpdOrQoUPq7u7W2NiYOjo6dPLkSaPHQ5IePHggh8OhxMREVVVVmf7H7/gc8mXbdHZ2atmyZUYTel9fnyn4HD051ZTbAAADPUlEQVR6VAkJCWpubtb4+LiePHmi6upqY7iFt30DYOkjgOCv40sA8XUK1mICyNTUlEpLSxUaGqrw8HCVl5fPO/7y8uXLSkxMlN1ul9Pp1IEDB4ySibi4ONPV9zdv3ignJ0cxMTHG2Nhz584ZV8l9CSDfvn1TSUmJoqKi5h3DK82cRPn7+xslJNLMyZfNZjOu6nriXodr164pNjZWgYGBcrlcpoDT29ur5ORkORwOrV+/Xrdv39bq1astDyDSf8bw2u12xcfHm+4EubfXmTNnjG2+bt06o9Tk+/fvKigoUFhYmMLDw3X69GlVVFSY9sG7d++Unp6u4ODgfz2G11sAaWlp0Y4dO4yemtTUVFPT8H/D0xcRzr7q7usUrMUEEEm6ceOGMcb54MGD847hbW9vV1pamoKCghQaGqqUlBRj8texY8eMMOJWXFystWvXyuFwyOl06vjx40ZA8+UYl7yP4XXbvn27Kbx/+PBBfn5+puPJk5GREeXm5io8PFxBQUHauHGjysrKTHfHpqenFRMTI5vNNucOz+/4HPJ12zQ3NyspKUkBAQGKioqSy+UyfueeGJeQkCC73a7o6Gjl5uaqr69vwX0DYOkjgABLRE9Pj8LCwn7pVCMr/D99GSKWpunpaUVGRqq7u/tPrwoAQAQQYMno7u72Wpf9v4oAgj/t7du3qqqqMt01AAD8OQQQAL8VAQQAAMxGAAEAAABgGQIIAAAAAMsQQAAAAABYhgACAAAAwDIEEAAAAACWIYAAAAAAsAwBBAAAAIBlCCAAAAAALEMAAQAAAGAZAggAAAAAyxBAAAAAAFiGAAIAAADAMgQQAAAAAJYhgAAAAACwDAEEAAAAgGUIIAAAAAAsQwABAAAAYBkCCAAAAADLEEAAAAAAWIYAAgAAAMAyBBAAAAAAliGAAAAAALAMAQQAAACAZQggAAAAACxDAAEAAABgGQIIAAAAAMsQQAAAAABYhgACAAAAwDIEEAAAAACWIYAAAAAAsAwBBAAAAIBlCCAAAAAALEMAAQAAAGAZAggAAAAAyxBAAAAAAFiGAAIAAADAMgQQAAAAAJYhgAAAAACwDAEEAAAAgGUIIAAAAAAs8w9fEutmwvXfzAAAAABJRU5ErkJggg==\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from collections import Counter\n",
    "\n",
    "df = pd.read_csv('http://robot.inf.um.es/material/data/evidence_data.csv',sep=';')\n",
    "\n",
    "evi_name = list(df.columns)[4:18]\n",
    "evi_short = \"palmGrov coin datRe inflor leave stemCh pollen phytol texts potter paint jewel rockP sculpt\".split()\n",
    "\n",
    "bindf = df[df.columns[4:18]]\n",
    "\n",
    "palm_type = list(df.Taxa[df[\"Palm groves\"]==1])\n",
    "\n",
    "bindata = np.array(bindf)\n",
    "\n",
    "location = df[[\"Longitude\",\"Latitude\"]].apply(np.vectorize(lambda x: float(x.replace(',','.'))))\n",
    "\n",
    "\n",
    "\n",
    "import cartopy\n",
    "import cartopy.feature as cpf\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import matplotlib.ticker as mticker\n",
    "from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER\n",
    "\n",
    "lat_lon = cartopy.crs.PlateCarree()\n",
    "\n",
    "def genmap(extent, figsize, grid=2):\n",
    "    fig = plt.figure(figsize=figsize)\n",
    "    ax = fig.gca(projection=cartopy.crs.Mercator())\n",
    "    lon1,lon2,lat1,lat2 = extent\n",
    "    \n",
    "    ax.add_feature(cpf.LAND)\n",
    "    ax.add_feature(cpf.OCEAN)\n",
    "    ax.add_feature(cpf.COASTLINE)\n",
    "    ax.add_feature(cpf.BORDERS, linestyle=':')\n",
    "    ax.add_feature(cpf.LAKES,   alpha=0.5)\n",
    "    ax.add_feature(cpf.RIVERS)\n",
    "\n",
    "    if grid is not None:\n",
    "        gl = ax.gridlines(crs=lat_lon, draw_labels=True,\n",
    "                          linewidth=2, color='gray', alpha=0.5, linestyle='--')\n",
    "        gl.xlabels_top = False\n",
    "        gl.ylabels_left = False\n",
    "        gl.xlines = True\n",
    "        gl.ylocator = mticker.FixedLocator(range(lat1-grid,lat2+grid,grid))\n",
    "        gl.xlocator = mticker.FixedLocator(range(lon1-grid,lon2+grid,grid))\n",
    "        gl.xformatter = LONGITUDE_FORMATTER\n",
    "        gl.yformatter = LATITUDE_FORMATTER\n",
    "        gl.xlabel_style = {'size': 8, 'color': 'gray'}\n",
    "        gl.ylabel_style = {'size': 12, 'color': 'gray'}\n",
    "\n",
    "    ax.set_extent(extent,crs=lat_lon)\n",
    "    return fig\n",
    "\n",
    "\n",
    "pos_idx = bindata[:,0]==1\n",
    "neg_idx = bindata[:,0]==0\n",
    "\n",
    "fig = genmap(figsize=(8,6), extent=[-10, 10, 32, 45], grid=None)\n",
    "#genmap(figsize=(18,18), extent=[-20,70,4,54], grid=None);\n",
    "pos = plt.scatter(*np.array(location[pos_idx]).T, transform=lat_lon, alpha=0.5,color='green');\n",
    "neg = plt.scatter(*np.array(location[neg_idx]).T, transform=lat_lon, alpha=0.5,color='red');\n",
    "\n",
    "plt.text(0.1,-0.05,\"P: hide/show palm locations   E: hide/show evidences\", transform=fig.gca().transAxes)\n",
    "plt.title('Individual evidences',fontsize=14);\n",
    "cosa = plt.text(0,40,'',transform=lat_lon,fontsize=10)\n",
    "\n",
    "def hover(event):\n",
    "    \n",
    "    cont, ind = pos.contains(event)\n",
    "    if cont:\n",
    "        p = pos.get_offsets()[ind[\"ind\"][0]]\n",
    "        cosa.set_position(p)\n",
    "        k = ind[\"ind\"][0]\n",
    "        cosa.set_text(palm_type[k])\n",
    "        fig.canvas.draw_idle()\n",
    "        \n",
    "\n",
    "    cont, ind = neg.contains(event)\n",
    "    if cont:\n",
    "        p = neg.get_offsets()[ind[\"ind\"][0]]\n",
    "        cosa.set_position(p)\n",
    "        k = ind[\"ind\"][0]\n",
    "        v = bindata[neg_idx][k]\n",
    "        cosa.set_text(evi_short[np.argmax(v)])\n",
    "        fig.canvas.draw_idle()\n",
    "        \n",
    "fig.canvas.mpl_connect(\"motion_notify_event\", hover);\n",
    "\n",
    "def on_key_press(event):\n",
    "    if event.key == 'p':\n",
    "        pos.set_visible(not pos.get_visible())\n",
    "    if event.key == 'e':\n",
    "        neg.set_visible(not neg.get_visible())\n",
    "    fig.canvas.draw_idle()\n",
    "        \n",
    "fig.canvas.mpl_connect('key_press_event', on_key_press);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "hide_input": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def makeGrid(size=2, offset=0):\n",
    "    fun = lambda x: np.floor_divide(x-offset,size).astype(int)\n",
    "    x1,x2,y1,y2 = fun(np.array(region))-[0,1,0,1]\n",
    "    #print(x1,x2,y1,y2)\n",
    "    celllocs = np.array( location.apply(fun ))\n",
    "    cells = {tuple(x) for x in celllocs}\n",
    "    allcells = {(x,y) for x in range(x1,x2+1) for y in range(y1,y2+1)}\n",
    "    #emptycells = allcells.difference(cells)\n",
    "    #print(len(emptycells))\n",
    "    celldic = { x : np.where( np.all(celllocs == x,axis=1) )[0] for x in allcells }\n",
    "    data  = { x: bindata[v] for x,v in celldic.items() }\n",
    "    dataN = { x: d.sum(axis=0) for x,d in data.items() }\n",
    "    dataB = { x: (v>0).astype(int) for x,v in dataN.items() }\n",
    "    dataP = { x: v[1:] for x,v in dataB.items() if v[0] == 1 }\n",
    "    dataN = { x: v[1:] for x,v in dataB.items() if v[0] == 0 }\n",
    "    S = np.array([v for _,v in dataP.items()]).mean(axis=0)\n",
    "    E = np.array([1-v for _,v in dataN.items()]).mean(axis=0)\n",
    "    loc = lambda x: size/2 + x*size + offset\n",
    "    dataL = { x: loc(np.array(x)) for x in allcells }\n",
    "    return data, dataB, dataP, dataN, dataL, S,E\n",
    "\n",
    "\n",
    "def sig(z):\n",
    "    return 1/(1+10**(-z/10))\n",
    "\n",
    "def lb(p):\n",
    "    return 10*np.log10(max(p,1e-20))\n",
    "\n",
    "def llr(p):\n",
    "    return lb(p) - lb(1-p)\n",
    "\n",
    "def mkTest(s,e):\n",
    "    p = lb(s)   - lb(1-e)\n",
    "    n = lb(1-s) - lb(e) \n",
    "    return lambda x: p if x else n\n",
    "\n",
    "\n",
    "#region = [0,10,0,10]\n",
    "region = [-30,74,10,54]\n",
    "\n",
    "Ss,Es  = zip(* [ makeGrid( s,o)[-2:] for s in [1.5, 1.75, 2, 2.25, 2.5, 3]\n",
    "                                     for o in [s*v for v in [0,0.1,0.2,0.3,0.4,0.5]]])\n",
    "Ss = np.array(Ss)\n",
    "Es = np.array(Es)\n",
    "\n",
    "tests = [ mkTest(s,e) for s,e in zip(np.mean(Ss,axis=0),np.mean(Es,axis=0)) ]\n",
    "\n",
    "\n",
    "# [Jeffreys scale of evidence](https://en.wikipedia.org/wiki/Bayes_factor#Interpretation)\n",
    "\n",
    "def colorpred(t,p):\n",
    "    if t==1 and p>0.5: return 'green'\n",
    "    if t==0 and p<0.5: return 'black'\n",
    "    if t==0 and p>0.5: return (0.3,0.8,0.3)\n",
    "    if t==1 and p<0.5: return 'gray'\n",
    "\n",
    "def colorevidence(t,e):\n",
    "    if e<5: return 'green'\n",
    "    if t==0 and p<0.5: return 'black'\n",
    "    if t==0 and p>0.5: return (0.3,0.8,0.3)\n",
    "    if t==1 and p<0.5: return 'gray'\n",
    "    \n",
    "    \n",
    "#dataB, _, _, dataL, _, _ = makeGrid()\n",
    "_, dataB, _, _, dataL, _, _ = makeGrid(size=1.9,offset=-0.15)\n",
    "\n",
    "\n",
    "fig = genmap(figsize=(9,5), extent=region, grid=None)\n",
    "\n",
    "pl=[]\n",
    "vl=[]\n",
    "el=[]\n",
    "\n",
    "for c,v in (dataB).items():\n",
    "    e = sum([t(x) for t,x in zip(tests,v[1:])])\n",
    "    p = sig(e)\n",
    "    col = colorpred(v[0],p)\n",
    "    if e>0:\n",
    "        vl.append(v[1:])\n",
    "        pl.append(dataL[c])\n",
    "        el.append((e,p))\n",
    "        plt.plot(*dataL[c],'.',color='green', markerSize=min(e,30)*0.7, transform=lat_lon)\n",
    "\n",
    "plt.title('Probability of palm', fontsize=14)\n",
    "plt.text(0.3,-0.05,\"Hover to show strength of evidence\", transform=fig.gca().transAxes)\n",
    "cosa = plt.text(0,40,'',transform=lat_lon,fontsize=10)        \n",
    "ax = fig.gca()\n",
    "\n",
    "def on_plot_hover(event):\n",
    "    for k,curve in enumerate(ax.get_lines()):\n",
    "        if curve.contains(event)[0]:\n",
    "            e,p = el[k]\n",
    "            cosa.set_text(f'{e:.0f}db, {100*p:.2f}%\\n'+', '.join([evi_short[1+x] for x in np.where(vl[k])[0]]))\n",
    "            cosa.set_position(pl[k])\n",
    "            cosa.set_color('red')\n",
    "            fig.canvas.draw_idle()\n",
    "\n",
    "fig.canvas.mpl_connect('motion_notify_event', on_plot_hover);"
   ]
  }
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