Transfer_function2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do `Kernel -> Restart & Run All` in top menu to run the notebook"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from matplotlib import cm\n",
    "from scipy.signal import freqs_zpk, zpk2tf\n",
    "from ipywidgets import widgets\n",
    "from numpy import pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# compute transfer function from zeros and poles\n",
    "def transfer_func(s, n, p):\n",
    "    nom = 1\n",
    "    for i in range(n.shape[0]):\n",
    "        nom *= (s-n[i])\n",
    "    denom = 1\n",
    "    for i in range(p.shape[0]):\n",
    "        denom *= (s-p[i])\n",
    "    return nom / denom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# prepare x (real) and y (imaginary) axis \n",
    "# for plotting the transfer function\n",
    "x = np.arange(-2, 2, 0.1)\n",
    "y = np.arange(-2, 2, 0.1)\n",
    "X,Y = np.meshgrid(x,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transfer function from zeros and poles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# create the transfer function from zeros and poles\n",
    "n = np.array([])\n",
    "p = np.array([0.5+1j, 0.5-1j])\n",
    "\n",
    "tr_f = transfer_func(X + 1j*Y, n, p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "              'Firefox 4 and 5 are also supported but you ' +\n",
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       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
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       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
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       "\n",
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       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
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       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
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       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the magnitude of the transfer function as a heatmap\n",
    "fig = plt.figure()\n",
    "f = plt.imshow(np.minimum(np.abs(tr_f),5), interpolation='none', extent=[-2,2,-2,2])\n",
    "plt.colorbar()\n",
    "cmap = f.get_cmap()\n",
    "\n",
    "plt.gca().set_xlabel('$\\mathbb{R}\\{s\\}$')\n",
    "plt.gca().set_ylabel('$\\mathbb{I}\\{s\\}$')\n",
    "\n",
    "im = np.linspace(-2,2,1000)\n",
    "#plt.plot(np.zeros(im.shape), im, linewidth=2, color='red')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Frequency response from transfer function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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EtEvXM6JIZEfI29BGEaCR7GOBO9iBwmhiZfLtHE1CaJSDL/sK1S0eGw1CUsqukmY3O4nooUyNi/3uM6zLHfeRy9jk1z7RMKy2QIFtp5FQmhyKwmhravId8hguXblbBXPnUdCXpsuIipxXqd0vMV7jDeGREQnk5C/R+/sQxsRJdDRJU8HZOxM9bP/Y/XJk7HaO0DKvkfxs5L+i/34iIgsdDSn2HskPPviveS+q63k/gyKXEREMXQ0XHYSEV3mw2alNsqhJ3nBVUFHx8yTG53tbnN+XuH8fI+P+suI6EMSwm0PkrBEVEPuiXk7iOifftjHMAzDMAzDTDG20tFcTVlEdMjl3M0k5D06k7wF4a9JyA3zHAmbo18kQTzqyX1SexEJk0kdCZGYnqTxk/cWk+CxfIiEaG0gYXmap83LnZ83kCA2QMISuDud5STyTxBeQET9JOR72U5C7idfyXuNJGwIf4aEABsRLu2PxVi2ijZVkRC6/CESksESKR9v8R7jjSGRkFx2iIT17veSsNwwkoScTURCHqEXndf+02nn9X72f6w+eeKrPSL/BaGS/p9JwrMoJhB+gIieJ6JqEvYMjvVdbSVvQSgm6LWQ8OyE01ExJZegV4mNvtCTt+CaR0KEw4MkiDbPstvZxpXO+neQ77xLp5HwA0ENCclz73W2V0bufU4g4cceJfYx04/jSPjRZDEXLly4cOESoHIWhW7LjW8wi9m/fz+ICAUFBXj77bdx8skno7+/HwDwm9/8Btdccw0AICwsDDfeeKN0nVjHlZycHBARDh06JB276aabsHDhQpjNZulYQ0MDjj/+eHgO/Y4dO0BE+N///V+347feeitOPfVUL5t1Op107LXXXvM6BgD33HMPwsLCvGwV23LllltuwYIFC2AwGKRj1dXVmDt3rlvde++9F2eccQZsNpvb9bfffjuWLFkiOzau+LJVtOl3v/ud1zVKx1vpGALAkiVLsG3btjFtTUlJARHh66+/lo750/+x+qS0PUD59+hP/++++27MmTMHBQUFXvcdHR0F4Pu7knsGb7nlFsybNw9NTU3SMYvFgpNPPhlXXXXVhGz0RVhYGHbs2OF2rKSkRM6b6VW6u7sBAE8//TSICD09PV73f/3117FgwQLY7fYx7bj//vtx4oknKrJvtjEZ765J4CxS8Exx4cKFCxcufpazaKoR6olDKHEVhG1tbTj++OPx1VdfweFw4MQTT8QHH3wAwFsQunL48GHYbDa0t7fjO9/5Dv76178CAIaHh3HiiSfi97//vdc1N910EzyHXpwo5+fnux1/4403QETS5DQYglC09fbbb/eqe8MNN0h1R0dH8Z3vfAf3338/2tvb3YpoV2Zmpuw4jWeraFNaWtqY1/sab9d7jDeGgPCdbtq0yU2se+Ip0Pztv9I++WpPxF9BOF7/R0ZGsHjxYtx8881j2qNUEA4PD2PhwoW47bbbvO7xwAMPYM6cOVLb/nxHvpATXAcPHgQRYc+ePfj666+9yqmnnorly5dL9R966CEcf/zxsvd/+umnMXfuXKSkpIxpR3h4OIgIfX1949o325is91eQWUxEMBqNsNvtXLhw4cKFyzEVo9EoCsLFIX6/eRPqiUMocRWEAPDzn/8ct9xyCw4cOIB58+ahq6sLgLyH8JlnnsHZZ5+N4447zk31/+EPfwAgeEeICM8++6xXu48++qhPQdja2ipro16vd/scSEHY0tICIsIzzzwzpq1Wq3XcXz2++eYbr3u4Mp4gbG5u9rpGyXi73mO8MQSAL7/8EgsWLMCcOXNwySWXYMeOHW7eLcBboPnb/7H6JEegBOF4/W9tbQUR4amnnhrTHqWCcKznZ8+ePSAiVFZW+mXjWMgJrsceewxz587F4OCgV/3+/n7MmTPHTQCPJQjr6+txxhlngIhw8cUX49VXX4XFYvGq9/jjj4OIvDzYLAhnliC028f/kYJhGIZhxsNut7MgnIp4CsJDhw5h/vz5uOyyy9wmj56C8N5778WcOXPw2GOP4euvv0Z8fDwSEhJw6qmn4p577gEwcUHY3t4ua6M4+fZHEG7dulVWSIjL5USUCkKx3p133omEhATZYrVave7hyniC0LP/gLLxHusecmMGCN/RO++8g5tvvhkLFy7EggULoNFopPOeAs3f/o/VJzl8CUKl36PS/k8FQaj0O5JDTnD99Kc/xdq1a2XrFxUVedknjp3D4ZC9pqenBwcPHsSvf/1rzJ8/H4sWLfLyft93331YuHChIvtmG5Pw6poMWBAyDMMwAYMF4RTFUxD29PTgxBNPBBHhyy+/lOp5CsIlS5a4eaYAYGBgAHPnzpUEyvDwMBYsWOD3ktGJCMLXX39ddjL96KOPYsmSJV7t33XXXRNaMjo8PIyTTz5Z8Z44OXzZOpZ4UjLeY91DidiwWq0466yzcMUVV0jHPAWav/0PlCBU+j0q7b/SJaO+vit/low++OCDsktGAy0Iv//97+PWW2+VrX/o0CEQEf7zn/9Ixz755BMQEcrKysZtr7a2FieccAIeeeQRt+M//elP8YMf/ECRfbONSXuBBRcWhAzDMEzAYEE4RfEUhABw4MAB7Ny5020ZmKcgPOWUU7B161a3e7366qsgIjeBsmXLFr+DykxEEL733nsgIpSUlLhd+/bbb3tNei0WCxYtWuTVvtKgMlu3bsW8efNQUVEBT9ra2ryOeeLL1rHEk9LxVjqGw8PDUnARVy655BJs2rRJ+iwn0Pzpf6AEodLv0R+xpSSojK/vyldQmfnz57sda21txeLFi2WDygRSEIoeyqefflq2vrjXr6GhQTrW1NQEIsJHH33kVlfuuzIYDJgzZw5efvllt+OnnHIK/vznP49r32wkCK+qq4goioQotiCiWxRcczUJ0WyHiKiRhOi4/sCCkGEYhgkYLAinKHKCUA5PQXj33Xdj7ty5+Mtf/oK9e/di69atOPvss72WMBYWFmLevHlYvnw5XnnlFezatQtnnnkmLrzwwoAKwvz8fBARbrjhBhw6dAiff/45ent7YbPZcNJJJ2HlypXYs2cPdu3ahaVLl+Liiy/2ar+srAwLFizAsmXL8PLLL+OFF17Aaaedhg0bNrjVbW1tRVhYGBYuXCj1/6WXXsJvfvMb/M///M+4Y+7L1rHEk9LxVjqGXV1dOOmkk3DPPffgjTfewL59+3DbbbeBiLB7927pOjmB5k//AyUIlX6P/ogtk8mE008/HQsXLsRf//pX7N27Fzt37sT5558v7Z319V3J3a+yshInnXQSzjrrLLz44ot45ZVXsHLlSsyfPx+5ubkTstEXnoIrNjYWRITPP/9ctv6WLVuwaNEiSeiKrF+/3svbe/vtt2P9+vV48skn8cEHH+D555/H2WefjWXLlqGjo0OqV1hYCCJCYmLiuPbNRoLwqvoFEb1ARLeSMkG4goSUKruJ6Fwi+hMRDRPRZj/aZEHIMAzDBAwWhFOUiQrCrq4u/OEPf8B3v/tdLFq0CJs3b0ZtbS3CwsLcBAoAJCUl4aKLLsK8efOwcuVK7N27F3/729+wYMECt3rHIggB4B//+AfOOusszJkzx+18fHw81q9fj3nz5mHdunX45JNPZNNOAEBaWhp+8IMfSLa+//77snWtViu2bduGpUuX4oQTTsDpp5+O6667Dvv27RtzHMeydSzxpHS8lY7h0NAQ/v73v+PCCy/EySefjJNOOgkXXngh3n33XbfrfAk0pf0PlCAElH2P/ootg8GAu+++G9/73vcwf/58rFy5Etu2bcPQ0JBUR+678nW/4uJibN68GYsWLcLChQtxzTXXIDs7W9GYHIsgFL3F5eXlsvVXrFiByy67zOv4G2+8gUWLFrmtBvjoo49w7bXXSmOyevVqPPLII17e3/DwcCxbtsxLZMrZNxsJ9muLxheErxBRpcexL4go1o92WBAyDMMwAYMFIePGzTffjNWrV4faDIaZlgRKcHV3d+OUU07Bhx9+6Nd1g4ODOP3007Fnz56g2jedCfZri8YXhOlEtMfj2B+IyO5HOywIZzja9l5ElprxXmoj3kyow0cZWsRXtcLW4x2tmGECycjIKBqsPfi22IT3UhuxJ6Ee/87UIqXWiu6+w6E2jwkSLAhnMZ4h6evr63HCCSfgj3/8Y4gsYpjpTSAF18svv4x169ZhZGRE8TXvvfceli5dKpviItD2TVeC/dqi8QVhPRE94XHsBue1J/q4Zj4JL2mxnEUsCGccPYNH8H5qI67bnYqwcLXP8vM96fggvQmdvUPj35RhFFLTYsfOyEpseiHB57O3Yrsad32Uh7jKFtlVKMz0hQXhLOb000/H9u3bsW/fPjz11FM45ZRTcNJJJ6G+vj7UpjHMtGSqC66pbt9kEOzXFgVHEO50nncrLAhnBqOjo/iqoBkbn4uTJt5rntTglncy8dcvSrD9v+V4+NMiXP+Gu1A895kYvBJTw14b5pioabHj3gMFbs/Wuqc1+NW7WXj0S+H5e/DjQlzzWopbnV++nYkqM/8bNFNgQTiLEXPIzZ8/H4sXL8bmzZtRVFQUarMYZtoy1QXXVLdvMgj2a4uCs2SUPYQzFMfAYdx7IF+aZF/9Wgo+zzPAPiAv8jp7h3AoW4ef70mXrvnBPxIQWWpmjw3jFz2DR/CPqCqsfCIaYeFqLN+uxoMfFyKxuhVDR+RXpujae7FLU41zno5BWLgaq56Ixt60Rn72ZgAsCBmGYZhZQ7BfW6QsqEyFx7HPiIPKzDoMtj5peeiapzR4P7URR4aVLREfHR1FXGWL2/LSew/k8zJSRhGF+k5c8XKS9Ow8+HEhGtt6FF9vdQzgvoNHvYqPfVnqU0Qy0wMWhAzDMMysIQivqkVEtNFZQESPOv9/mfP8S0R0yKW+mHbiVSI6h4geJk47Mesw2Ppw2a5EhIWrcemLiSgzdk3oPoNHhvHPxHqseVKDsHA1LtuViEJ9x/gXMrOS0dFRvJPSIHkFr3g5Ccm11gnf62C2TrrXgx8X4rDCHzSYqQcLQoZhGGbWEIRX1dUks7+PiA44zx8golSZa0pISEzfRJyYflZh6urHj14SvDPX7U6F1T5wzPesMtulPV6rnojGl/nNAbCUmUkMHB7Gnz8rlrx6f/qs2OfSZH9IrrFKP0hs+7QIwyO8fHQ6woKQYRiGmTWE+r0WIFgQTlP6ho5I+/+ueS0lIGJQpGfwCB7+tEia8L+kqcEIT84ZAO09g7j1nUzpB4NPcvUB3feXWN2K1U8KnsJXYmoCdl9m8mBByDAMw8waQv1eCxAsCKchIyOjePDjQmcgmHiYuvrHv8hPRkdHsTu+ThKF2z4t4r1dsxy9rRc/fkXwSF+wIxZZDe1BaefbYpP03KlKTEFpgwkeLAgZhmGYWUOo32sBggXhNOSD9CaEhaux+sloFOiCu8/vm2Kj5LH5w/58DBweDmp7zNSkwerAD18U8gpe9WqyX4FjJsJLmhopbUWDNbhtMYGFBSHDMAwzawj1ey1AsCCcZlRb7NI+q0PZuklpM7nWirVPCW3evjcHvYNHJqVdZmpQae7GRc/HIyxcjZ+9kQarI3DLk30xPDKKOz7IRVi4Gjf+K52909MIFoQMwzDMrCHU77UAwYJwGjF4ZBg/eyNNSg0xmTnbcptsOP/ZWISFq3HLO5lwBCCICDP1KTJ04oIdwve+5V8Zk5qOpNU+gAufi0NYuBqvxvJ+wukCC0KGYRhm1hDq91qAYEE4jdiTUC/tG2zvGZz09kubu7BhpzBB/9W7WewpnOFUmLqx3vkjwK/fywpIJFF/iamwICxcjZVPRKPKzP9OTQdYEDIME3RGR0cxOjqKkZERDA8P48iRIzh8+DAGBwdx5MiRSf3FnJndhPq9FiBYEE4TtO29WONcthlZag6ZHRWmbslj9Nu92egf4j2FM5G6Vgc2Or1zv3k/G31DoRP/D38iRLy9+e1MTkUxDWBByDCM38iJu6GhIQwODmJgYAD9/f3o6+uDzWaDzWZDd46ywBwAACAASURBVHc3urq60NXVhc7OTnR2dqKjowPt7e1wOBzo7+/H0NAQjhw5guHhYRaITNAI9XstQLAgnAaMjo7izg+F/VR3fpgb8n/Xig2d0vLROz/M5UAzMwxdey82vSAEkPnlWxkhXx7cah+QPJWTtW+WmTgsCBlmluPLe+cq8Pr6+tDT0wOHwwG73S4r7jxLZ2cncnNzUVxcLNUXhaHNZkNLSwu0Wi06OjrQ398vlb6+PvT396OnpwcDAwOSQAz1ZIqZGYT6vRYgWBBOA6LLhWVza57SQNfeG2pzAAD5ug6c+0yMFH2Ug37MDExd/fjRS0Jqic1vpqGrb/L2DI7FwWwdwsLVuPC5OHT38f7VqQwLQoaZQSgRd/39/ejt7UVPTw/sdrsk0qqqqmCxWCSR51pEgdfZ2ekm7sRrrVYrTCYT9Ho96uvrUVVVhdLSUsTHxyM+Ph6pqalISEiARqNBREQEVCoVIiIiEB0dDZVKhcTERBQXF0On06GrqwsDAwNITU1FU1OTJBQHBwcxNDSE4eFhjIyMsEBkJkSo32sBggXhFGfoyAiuejUZYeFq7I6vC7U5bmQ1tkvRRx84VIgjwywKpzNWxwCufi0FYeFqXPNaCtock79P1RdHhkdw/RupCAtX48Xo6lCbw4wBC0KGmcIoXZopeu98Lc2U8955iru4uDhotVrJe9fc3IympibU1taivLwcRUVFyM3NRUZGBpKSkhAbG4uoqCioVCqoVCqo1WrEx8cjJSUFmZmZyMvLQ0JCAtLT01FXVwetVguTyQSr1Sq13d7eDpvNBr1ej5KSEiQnJ0OlUiE+Ph7R0dEoKipy8yCK3sP+/n4MDAxIy0xZIDJKCfV7LUCwIJzi/DtTi7BwNTa9kDAlg7ik1bVJaTD++kUJRniP17Sks3dIimB7xctJsHT3h9okL5JrrYKn/EkNmjv6Qm0O4wMWhAwzSRzL0kxR4HV0dKCpqQk5OTmynjxP711nZyesVivMZjN0Op2b9y4/Px9ZWVmS904UdiqVCpGRkYiJiUFiYiLS0tKQk5ODwsJClJWVoaamBo2NjTAYDLBYLNIeQYfD4VVycnJQXl4ue667uxttbW1wOBwYHByUSk9PD4xGIzQaDRISEhAREYGYmBjk5eWhvr4e7e3tsgJRvC8LRGYsQv1eCxAsCKcw9oHDUmCPT3MNoTbHJ3GVLVj5hJC8fvt/y/nfzGmGfeAwtvwrA2HhalzyQgL0tqmxLNkT1720D39aFGpzGB+wIGSYCaJE3LkKpbG8d57/Lyfuuru70d7ejqqqKsTFxaGpqQk1NTWS9y4nJwfp6emS9y4yMlISeNHR0W7eu/z8fJSUlKCyshJ1dXXQ6XSIiYlBfX09urq6YLfbZUWcv0WJIOzp6XEThGJJSkpCc3Mz+vr6YDabUVlZifT0dERGRiI6OhrZ2dmora1Fa2sr+vr6UFFRgfz8fEkksgeRkSPU77UAwYJwCvNabC3CwtW49vWUKb8cM6LUjOXb1QgLV+P5qCr+d3Ka0Dd0BL9+Lwth4Wpc9Hw86lsdoTZpTKotduk5q7bwv1tTERaEDIPgLM202WxQqVRoaWmRFXei985kMkneu8rKSpSUlEjeu5SUFGn5pCjuIiIiEBERgaSkJKSnpyMnJwdFRUUoLy+XvHfNzc1oaWmBzWZTLO5iY2NhMBgCIgTFkp2djYqKigkJwsTERBiNRq/j/f39aGlpQXV1NbKysqBWqxEVFYW4uDgkJyfDYrG4eQ5d/58jmTKhfq8FCBaEU5SuviEpkmdMhSXU5ijiy/xmhIULk/XdcbWhNocZh8Ejw5LHbf2OWFSYukNtkiK2fSqkoXjw48JQm8LIwIKQmXEoXZrpGlilsbER7e3tbgLP38Aq7e3taGlpgcFgQGNjI6qrq6FSqZCXlyd57xITExETEyPrvUtNTUVWVpbkvauqqkJ9fT10Oh3MZjPa2trQ1dWFpqYmJCUlBVS4BUsQZmVlobKyckKCMCEhASaTSfacaxkYGEBbWxvS09MRFxcHjUaDyMhIpKeno6KiAiaTCT09PbKRTDs7OzE4OMiRTGcRoX6vBQgWhFOU3fF1UqTH6bQv70CWThKF76Y0htocxgeHh0fwx4MFCAtX49xnYlCo7wy1SYqpa3Wwl3AKw4KQmfJMRmAVtVoNk8kkCbyOjg60trbCZDJBq9Wirq5O8t7l5eUhMzNT8t6p1WpJ3EVFRSE2NhZJSUnIyMiQBKHovWtqapK8dx0dHRNamtnU1ITExMRpIQgzMzNRVVU1piDs7e2VFXrx8fEwm83jCkKxlJSUoKSkBAMDA7DZbGhoaEBeXh5iY2MRERGBlJQUlJWVobm5GQ6HkPtQpVK5Ba0ZHBzE4cOHOZLpDCbU77UAwYJwCtLdfxjrncnfo8unh3fQlXdTGiVRuD9TG2pzGA+GR0bx58+KpVQmWQ3toTbJbx52egkf+oS9hFMNFoTMpHIsgVXa2tpQUFAAm83mU9z58t61tbXBYrG4ee/KyspQWFiI7OxsREREIC4uzs17FxERIQU2Eb13BQUFKC0tlbx3er3ezXvnKXoiIiJgtVoDKrKCKQhFsRRIQVhdXe1TELa3t/sUhLGxsbBYLIoFYXFxMcrKymTPiZ7VwsJCxMfHQ6VSISkpCSqVCg0NDeju7nb7cYEjmc5cQv1eCxAsCKcg/0ysR1i4Gj/dnTqtvIOu7I6rlUThl/nNoTaHcTIyMorHvy5DWLgaq56IRlJNa6hNmhC1LQ7p+WIv4dSCBSEzYY4l591Elma2t7dDpVKhra0Nra2tMBqNkveuoqICxcXFkvcuOTkZcXFxst675ORkZGRkIDc3F0VFRaioqIBarUZFRQWMRiNaW1sn7L2TE4Stra3TQhDGxMQEXBBmZGRMWBDGxMSgpaVFsSAU91EqqWu329HU1CTlQBRTXRQWFqKpqQmdnZ2yAlFcaswCcfoS6vdagGBBOMXoGTyCDTuFyKIRpeZQmzNhRkdH8XxUFcLC1Vi+fXr3ZaYwOjqKHRGVCAtXY8V2NdRl08/77MrDnwhewkc+Lw61KYwLLAgZiUAtzayurpbyx4217070/oneO71ej4aGBlRXV6O0tBQFBQXIzs5GWloaEhMTodFo3AKruHrvsrOzJe9ddXU1GhoaJO9de3u7z7QIwfSOORwOREZGoqWlJaD31Gq100YQpqeno6amZkKCUKPRwGq1KhaEBQUFqKioUFzf4XBApVJJP1g0NzejrKwMKSkpiIiIQGxsLPLz89HQ0ACbzYb+/n40NzcjISGBI5lOY0L9XgsQLAinGB9maKXE4MPT1DsoMjo6iie+KUdYuBorn4hGXGVLqE2a1YhRa8PC1fi60Bhqc46ZClO39GyZuqZe3sTZCgvCGYoS7504EXY45HPeeXrrxst5193dDZvNhuLiYqSmpkpJzUXvnZjUXPTeeSY1F6NEZmRkIC8vD8XFxaioqEBtbS20Wi0MBoMUtTNQaRHEEhcXF/D9cw6HA1FRUdNKEBqNxoDeMy0tDbW1tRMShNHR0Whra1Ms8PLz81FVVaW4vt1uh0qlkvYOupbe3l6YTCZUVFQgLS0NkZGR0Gg0SE1NRUxMDKxWq2yQGleByJFMpyahfq8FCBaEU4gjwyP40UtJUz7voD+MjIzi0S9KpITiaXVtoTZpVvJ2coMkBg9l60JtTsD43b4cKdUJMzVgQThN8GdppjjZHiuwSktLC1QqFWw227jeO7PZDL1e75bUXPTeiUnNNRoNIiIi3Dx4YlLz7OxsKam5q/fOYrEo8t6JRZzAi8nMA1ni4+Oh0+mCIggtFkvABWFCQkLAbdVoNFNKEKrVarS3tysWeLm5uaiurlZcv6urCyqVCgMDA+PWFVNd5OXlSWku1Go1srKyUF1djZaWFq+lpeLnwcGjgWo4kmnoCfV7LUCwIJxCqMssUj64gcPDoTYnYBwZHsGDHxciLFyNdU9rkNtkC7VJswrR6xwWrsb7qTMr8mtyrRVh4Wqc90wMuvsPh9ocBiwIQ4KcuDt8+LDs0kyLxYKOjg6/o2Z6eu5E711LSwuam5tRX18PlUqF0tJSFBUVSd47Mam5nPdOTGoueu/EpOZarRZGoxFWqxWdnZ2oqalBWlpawAWLwxGcPXkOhwMJCQnQarUBv69arYbZbA6KILR3d6Gjqwpttli0tB2CpfUlmFsfhbnlblgtv4bD+jDsHbGw2+2wd9cI/2/7EJ3tu9HZlT8pgjA1NRV1dXVex+12O2w2m5QSQk6ERUVFwWazKRZ4OTk5qK2tVVy/o6MDERERiusPDg5Cq9UiLS0N/f39sFqtqK2tRXZ2NqKjoxEVFYWMjAxUVlbCbDajt7cX/f390Ov1SE1N5UimU4RQv9cCBAvCKcQt72QKOfzi60JtSsAZOjKCrf/OQ1i4Guc/G4uS5q5QmzQr+CC96WhuyBn4XI2OjuJnb6QhLFyN92aY2J2usCCcJDo6OvCLX/xCEmpKA6tERUXBZDJ5ee86Ozsl752Y1Fz03olJzUXvXXR0tOS9i4yMRExMjBRIIzMz081719jYCIPBAIvFApvNpth751rq6+uRkpISFEEYDI+bw+FAYmIimpqaAn7f6OjogAvCqkYNGvRrYGxeC5tpDdpMa2EzX4QW4zq0GNfB1LwObaaLMGRZjSHLKgxYVqLPvEIqvZaL0GlajQ7zBehquQG2tp3o7KiCRqOByWSakE3iMykG+xGXC8fExCA9PV3Kw5iUlOSVh1Gj0SA3Nxf19fWw2WySxy4yMhIdHR2KxVp2djbq6uoU129vb0dUVJRfgrCxsREZGRlexwcGBtDe3o76+nrk5uYiJiYGERER0v5W0aM7ViRTFoiTQ6jfawGCBeEUoVDfIS2rbHMMhtqcoDBweBi37xWW+G3YGYcqMz93wWRv2tH0H6/H1c7Yd8JXBc0IC1fjhy8mYOjISKjNmfWwIJwkurq6QEQwGAxe4k5cOid675qamlBTU4Py8nIpwbY4mfb03olJzV29dyUlJZL3TqfTwWQySd471713kZGRQfG2BStxerAElsPhQFJSEhobG4Ni70RFlmcx2zJgMS5Hm/ECtJrWos20Dq0mQQS2mTbC3Cz8f7d5DRzm9RiwnOsmBPvNK9BvWQG7+WLYTKvRZlqFHvM6DFlWos9yHuLjP5ZstdvtUi5GV4FXXl6OoqIiSeAlJiZK4sc12I+4XDg6Ohrp6eleeRhbW1vR3t4Oq9UKk8mEyspKpKenSz9Y5ObmQqVSwWQyKVrSOTg4iMzMTDQ0NCgWd21tbYiOjvZLENbX1yMrK2vcegMDA+js7ERjYyNSU1MlAZycnIySkhLo9XrY7XZOdRECQv1eCxAsCKcI4pLKv39dGmpTgkrv4BHc6vSEbnwuDuXG7lCbNCN5L7XRzTM4k//9HzwyjE0vJEz7yLwzBRaEQcRmsyEmJgYff/wxXn/9dXz3u9/FTTfdhHvuuUdKah4dHS2JO3EynJSUJHlVoqKikJubi5qaGsl719LSMmHvnWtRq9VB8bbpdLqg7HFzOIKzrNHhcCAlJQUNDQ1T2t66lj0wm85Atm4NoprOR1zTecjRngezcQ3aTeegw7QKdvNKdJtWotW0ER3mC9FlXooO89mwmc9Cm+lM2ExnodW4BjbTMnSZlsLcvBZ6Yxj6zKth1l2MuLhYt/2gERERkkdZfCbF9A6iwBsrVUdycrLPce3q6kJ7ezv6+vokIdXX1weLxYKKigq39vPy8tDQ0ICOjg6fAjEjIwONjY2KxV1raytiYmL8EoQ1NTXIycmZkIjs7u6GTqdDUVGR5KFPSEhAUVERtFoturq6JIHY1dWF5ORk9PX1sUAMMKF+rwUIFoRTgOaOPqzYLkze61odoTYn6HT3H8Yv3xZE4fpnY5Gv6wi1STMK1wAybybMvGWicrwRX4ewcDV+9W5WqE2Z9UxbQbhr1y5s2rQJixYtwve+9z3cfPPNqK2tHbfDKSkpuOiiizBv3jysWrUK+/fv96rz1VdfYd26dZg/fz7Wr1+P6OjoCQ1uSkoKzjnnHFx55ZW49dZbceqpp+L3v/89XnrpJdTX17t57+SSmjscwVvK6HAEJ6qkw+GAwWBAXFxcUGyOjY0NSjTQ1NRU1NfXT+kxLjc/DLPpDMQ3XQB10/mI1p6PLxouRo52PQYtK6TSZ16BMu1GpDadgzbzmW7FajoDBsMq2M1LYTcvRadpGYoMS1GkX4qm5tWob7pbEnieHuWJlLE8r3KCUCz9/f1QqVTo7OyE2WyWon2OJRDT0tKg1WoVCzWLxYLY2Fi/xF1VVRXy8vL8uqa2tlZWRIp/K6WlpUhOToZKpUJcXJwULVWMgMqRTANLqN9rAYIF4RTg5ZgahIWrcccHuaE2ZdLoGTyC37yfjbBwNc55OgYZ9e2hNmnaMzo6il2aakkM/jOxPtQmTRqt9gGseiIaYeFqVJrZ6xxKpq0g3Lx5M/bv34/KykqUlpbihhtuwLJly9Db2+vzGq1Wi4ULF+Kxxx5DdXU13nrrLcydOxexsbFSnaysLMydOxevvvoqqqur8fTTT+OEE05ARUXFMQ/2aaed5vfeupSUlKAIFYdDSLWg1+sDfl+j0QiNRhMUm+Pj44Nic1pammzwk2MtSnP7iUFWWlpaYDAY0NjYiJqaGpSVlaGwsBDZ2dnIqrsOZtMZ+E/dpYjWCoLwk/pLcKD+cjQZ1mLQsgItxlXI0K1FkrO0mM70EoXNxmVoM62URGF1s1MUGpaiUL8UHV2BS5Mx1g8aYwnCvr4+qFQqOBwOr+OeAlHMFxgXF4fa2lrFS0xNJhPi4+P9EncVFRUoKCjwW0Tm5+ePW6+3txdGoxHl5eWSQBSXz9bV1aGtrc1LIHIkU/8J9XstQLAgDDGDR4Zx0fPxCAtXI3aW5enrHxrG3R/lSXsn46taQ23StOXI8Age/7psxkYTVcK2T4VE9eH/KQu1KbOaaSsIPWlrawMRIS0tzWedxx9/HOeff77bsd/+9rfYvHmz9Pm2227DjTfe6Fbn0ksvxQMPPOCPObKsXr0akZGRfk2oMzIyfCb2DsRkPRiRNc1mM9RqdVBsDlY00LESqE+kiAJPo9GgsrISjY2NqK6uRllZmVfKDs+gP7GxsUhKSkJGRgZyc3OlfIxFuh9AazwL/6m/QhKEB+svw4H6y/FJ/Q9Rol+LRO0aSQwm6dZCa1zmJQhbTWcipekKdJoEQdhsXCsJwiLDUjRa/zspz9hYgrC3txcqlcpnBFI5gRgVFeUmEBsbG9HZ2enzWqPRiMTERL/EXVlZGYqLi/0WkYWFhX5d09raCo1GA4vFgsrKSmRkZCAqKgrR0dHIzs5GTU0NrFar297D/v5+NDQ0wGQyuQlEXmbqTqjfawGCBWGI+bbYhLBwNS7blYgjw7MvIMbgkWHcf6hASjD+ZX5zqE2adgwcPjqGK7ar8UX+zMhh6S/5ug4ptUlX31CozZm1zBhB2NDQACIa05N35ZVX4i9/+YvbsX//+99YvHix9Hnp0qV488033eo8++yz2LBhgz/myLJx40Z89tlnfk2os7OzUVlZGRRxNdb+rmMpLS0tfgtfpSUpKSkoS2gzMjJQXV09rsCzWCwwGAxoaGhAdXW1lJPRM6qruC9UjKIpJ/DElB3jLRsWS7lhLSoMyxHRKHgIVY0X4ED95c5yGSIbz3cTg0m6tSg2eC8bTWzagHdrf46Yxo3oNi2FzbTaTRCWmZ8I2LiOJeDHEoQ9PT1QqVQ+cxTKlaSkJGkZdnl5OVJTU90EYlNTE7q6uqT6BoMBycnJfgm1kpISlJSUBF1Ems1mL+9lf38/WltbUVNTg6ysLCkfYkZGBqqqqmCxWJCVlYXa2lqOZDoGoX6vBQgWhCHmV+9mzbrlfZ4cGR7Bo1+WHA2CEjdzI2IGmu6+w1Lk1jVPahBTMbu8zK6Mjo7i53vSERauxr60plCbM2uZEYJwZGQEN954I6644oox661Zswa7du1yOxYdHQ0iQn9/PwDghBNOwGeffeZW55133sH3v/99peb45Morr8TevXv9mlDn5eWhrKwsKOJqrKThx1KsVitUKtUx7z+TK4ESsWJkV4vFAr1ej6SkJGRlZXkJPM/AP1FRUYiNjUVycjIyMjK8cjKKgqStrQ1dXV0BW5Zr7tCipnkZsnVroG7agGjt+fi6YeNRQVh3Gb6ov9hLECbp1sBqOuPoclHTGuypvhb/qrkeb9Vcg1ztubCbl6LMRRDmN/+/gH1f8fHx0Ol0fgtCh8MBlUole85XSUxMhNFo9PI0igIxJSUFERERiIuLQ0FBAYqKipCUlOSXUCsqKkJZWZlf1xQXF/t9jRLvpZjqoq6uDrm5udBoNFCpVIiPj0d5ebmU45EjmboT6vdagGBBGEKqzHaEhaux6oloWO0DoTYnpIyOjuK12FpJFD76RQmnEBgHva0X176eIiVmz2rgfZif5xkQFq7Gj19JwsjI7HkfTSVmhCB88MEHERYWBqPROGa9UAvCG264Abt37/ZrQl1YWIji4uKgCMLMzMwxvWITLTabDSqV6pijoMoVX4nOPQWeXF5GMbKrWq12E3hxcXFQq9WIj4+XTdthNpslgRdIQeRPKWhRQWs8CzFNF0vLRT+r3yQJwg/rfoSPai+XEYRrYTSJAWXOxMG6n2BPzXV4s/o6vFVzDd6quQa1hjVoaD4qCHMMlwRUEPoSxGMJwu7ubqhUKsX7AQcHBxEfHw+z2TxmHXGfXllZGeLj46VALgUFBdBqteju7h7z+oKCAlRUVPgl7goLC/2+Rq/XIyUlxa9rBgYGkJSUhMLCQmlPZUREBFJSUlBaWgqDweCV6kIUiSaTCX19fbNCIIb6vRYgWBCGkCe+KUdYuBoPf1IUalOmDJ/lGbDSGRzkd/tyeOmfD/K0Hdj4XJy03JgDqQj0Dw3jgh2xCAtXI62uLdTmzEqmvSDctm0bzj77bGi12nHrhnrJ6O23347nnnvOrwl1SUkJCgoKgiIIs7OzUVFREfD7dnZ2ShEiJ3oPUeCZzWY3gRcbGyvlXJQTeGq1GnFxcUhOTvbKyyhGdhUFnqtgzcnJCcpYJCQkBEQQxhpegsl4Bj6ru1wShIfqL5UE4dvVP8GeqmtkBWGNYalzqegF2FNznZcgfLfmJ6hrPkcShNn61QHz7o7lIRUFoRgUxbV0dXX5LQhjY2NhsVgU129sbER6erokEFNSUiQPW2FhoaxAzMvLQ3V1tV9CTYwa6s81TU1NSEtL8+uawUFh2Wxzc7PbOGq1WhQWFiIhIQEqlQqJiYkoLi6GTqeTUl1ERETAZrPNikimoX6vBQgWhCHCMXAY5z4Tg7BwNbIbbaE2Z0qRUmvFec6xufKVZFRb+Pl05auCZqx5UoOwcDVueitj1nuXPXlWVYGwcDUe+qQw1KbMSqatIBwdHcW2bdtw5plnor5e2Rr+xx9/HOvXr3c79rvf/c4rqMyWLVvc6lx++eUBCSpz33334f/+7//8mlCXl5cjJycnKIIwWMtRRe+OzWZzO9bW1gaz2QydTicJvJKSEuTl5UkCT/TWeQo8UQTGxMQgPT0dVVVVqK+vh16vh9lsRnt7+zF5JHNzc1FeXh4UQRiIIDga7f3QGc/CgbofIlp7PqIaz8cBZ0CZA/WX46WKn2Fn2Y2ygjBLtxo1hhWSGBTLezVHReFHtVehUC8Iwlx9GLS23ID0f6w0IWMJws7OTkRERPglhmJiYtDa2qq4vlySedGD6JoKwlUgZmZmora21i+7cnJy/L6mvr4emZmZfgvC8bykdrsder0eJSUlbv1TqVSora1FR0fHjI9kGur3WoBgQRgiDmXrEBauxnW7U6ft30AwqTLbccXLSVJaCk44LgSP2f7fo5FEHzhUiP6h4VCbNeWothxdit3mGAy1ObOOaSsIH3roISxZsgSpqaloaWmRirj0EwC2b9+Ou+66S/ospp34+9//jpqaGrzzzjuyaSeOP/54vP7666ipqcGOHTsClnbib3/7Gx588EG/JtRVVVXIzMwMiiAsKCiY8HLUrq4uN4FXV1eHyspKSeCJnoi4uDhERUW5Cbz4+HikpKQgKysL+fn5KC0tVSzwsrKyUFVVFfCxCJY4DlQeyVjtjagwLMdXDRchWns+/tt4oUtAmcvxeMmteKTot7KCMFl3DvbVXuElCPfV/kwShG/VXIMM7UoUGZaiQL8MuaY9Aen/WGk3Ojs7fQrCjo4OREZG+iWGNBoNrFar4vq+8gO6lp6eHjQ3N7sJRI1Gg6KiIuh0Otjt9nHbycrKQn19vV99UWKbL1Hc0tKiuH5PTw90Oh1UKpW0x1LM81hfXw+bzeYmEF33IroKxOm0zDTU77UAwYIwRNz4LyH4xYcZ469Kmq109g7hzg9zJQH0j6iqWbuvsLmjT3pmlm9XY09CPe+RG4Nfvp2JsHA13puF6TdCzbQVhCQY7VVcE83fc889+MlPfuJ2XUpKCjZu3Ih58+Zh5cqVPhPTr127FvPmzcP5558/4cT0nuzcuRN33HGHXxPq2tpapKWlBUUQFhcXo7Cw0E3gmUwmN4FXXFyMvLw8ZGRkIDk5GbGxsW4CLzo62k3gFRQUoLS0FBEREaisrIRer4fFYjlmD55YgrXMNT8/HyUlJQG/b6CioiZpL0W27hy3hPSiGDxYfwUeKroDDxXdgXjtOi9BqG66HB/V/thLEO6t/bmbIPyq/iIhF6FhKeL1fwyYIDQajV7H7XY7rFYrzGazsESx34KBnkwM2L/AYMfr6G19BObaGzBk/SX62v4Xg91fYLC/Ryi9FRh0RGGw6z3YOz/BQL8gytRqNdrb2xWLoZqaGuTm5voluNLS0lBcXOzmYUtISBhTIGZkZKCxsdGvdpTmLvQs/o7B4KD7fk0xjUdlZSXSg4qT2AAAIABJREFU09MRGRmJ6OhoyctptVqlJaV9fX3QaDTo7OycVpFMQ/lOCyAsCEOA6MFY/WQ0Onp5j9xYDI+M4uWYGkkU3vivdDRYe0Jt1qSiKbdI++I2PhfHe+MU8EW+EFzm6tdSpuw7ZKYybQXhdGT37t24+eab/ZpQNzQ0IDk52e+JeFdXF6xWK0wmE7RaLerq6lBRUYHi4mLk5uYiIyMDMTExiIqKkhV4qampbgKvuroaDQ0NMBgMsFgssNlsYwo8tVoNi8UScIGVm5sbFE/esXhLxxOEjY2Nx3SPru5OZOjOgabph14J6QVBeLUkCDVN53kJwjcrb5IVhO/UbHYThP+svE5aNhqvu/6Yn7na2lpERUUhJycHOTk5SEtLQ2JiIjQaDdRRX6C59jr0m9Zi0LwKhy1rMGQ5D4ctKzHkUgZaNqLPvBJDlnUYbjkXR1rWYLhlNY60nIMe83lwWC5Al3kNuluuRE3lzWht/RwD/coik05EdKWlpUGr1UqfHQ4HDAYDSkpKkJSUJAnE4uJi6PV62O12pKamQqfT+dXORHIXDg4OIiIiYszci3LFZrMhKipK9lx/fz9aWlpQXV3tluoiMzMTlZWVUKlU0j5EX5FMp9pLPdTvtQDBgjAEPB9VJS35Y5QRV9mCC51BVNY9rcGnuYYp929CoLEPHMajXxxNx3Hz25kwd/WPfyGD3sEj0j5U3qM7ubAgnET27duH6667zq9JtlarRXx8PDo7O70m254CLykpCbGxsYiMjHQTeAkJCUhNTUV2drabwMvJyUFqaqok8AKZJkKj0cBkMgVcYIlLTAN938LCQhQVFQX8vsnJyccsCGus2cjXr8bn9Zd7JaQ/UH85Pqi9ThKE3zRscBODcdpz8GDBHdhb8xMvQbjHJbDMWzXX4O2KnyG5SUhSn6zdgO7ubin3omtgH9d9n3JeY41Gg4SEBKSlpSEiIgLZ2dkoLy9HbW0ttNomVOr+jmL9BnSYN+KwZTUOW87FkGUdDltWugnCw5ZVGLCciwHLSvSYV6DHvAIDlnU43HIhus1rYTOtgt1yEdpNy2EyLoW++SwYjGdC3/qHoImulJQU6PV6n+flBGJkZCQyMzOl4DpK2iktLfU732F/f78U3def66xWKzQajaK6AwMDaGtrQ21tLbKysqT+paeno6KiAmaz2S3VxcDA1AuaEOr3WoBgQTjJHB4ewcXPxyMsXI3E6tZQmzOtaLUP4Pcf5EgCaeu/82Ds7Au1WUEho74dl+9KlJLNvxpbM2uXy06U7f8Vovg+8nlxqE2ZVbAgnEQ+//xzXHrppVIETavVCqPR6CbwioqKkJubi/T0dCQlJckmOfcUeGVlZaiurkZjYyMMBgNaWloUCbzq6uqg7U8cK5jIsZRgefKKioqk5bOBLCkpKcecNzHV+AEK9avwSf0mmYT0l+PNqs2SIPy0bpObIDxU90PcV3A3/ln1cy9B+IaHIHyv8nq8X/VjFBmWIkO3Ev+N+tgrsI/rvk9Xr7GvZ06tVsNsNsPhcKCzy4BM/RZoms6ThG1s0yaom36EcsMmdJtWo8O8Aq2mFWhuXo4q3So0GMJgM63AgGUVHObVsJnWoMn4I5To1qNAtwEZ2h9D03gJvqz/ETIbL4DZdAYazT9VJG7KyspQVFTkl3jyjOI5XhH/FrKyspCYmOgW5XMsgTiRfIc9PT1QqVTo7e316zqz2Yy4uDi/rhkcFPZ5isGjGhoakJeXh9jYWCnVRVlZGczmqRdQItTvtQDBgnCSia1sQVi4GpteSMCRYZ7g+8vIyCj2pTVJUTbPfSYGH2ZoMTxD9tNZHQN45PNiSfRe9WoyCvUdoTZrWlJm7EJYuBprntJw+pJJZNoLwrS0NGzZsgVnnHEGiAjffvvtmPXvuece2b2H5513nlRn//79Xufnz58/oQH+8ssvcdddd2Hz5s1YtWoVlixZgnnz5uHOO+9ERESEmzclOzsbhYWFKCsrQ01NDRobG1FbWwu1Wo2Ojo6AJ3oP5v7EQOXfkxNuwfDkBSu9R0pKCurr64/pHt9qw5GtXQtV0wXeCenrL8eO8i2SINxb82M3QfiP8htwX8HdeL70Vi9B+KaHINxbfTX+UnwbCvRLkalbjYLmA8e879N16XC87jp80bAJ8dpzXHIpXuHsx2XI1F2IXP1y2fJZ3SY8V3GTS9mCFyt/jl1Vv5DKf2svh9l0BhpMGxUJmpKSEr+9cAkJCTCZTH5dExcXJ6XDcDgc0Ov1KC4ulgRiUlISSkpKpB9QBgeFVBWVlZV+tSPuBZQL0jNWaW5uRlJSkt+CsK2tDdHR0W7HBgYG0NnZiaamJimH6lQjVO+zAMOCcJK590ABwsLV2BVdHWpTpjUNVgd+/V6W297CnKbpuzTw8PAIDmbrsN65V3D5djWeVVWgd/BIqE2btoyOjuKGfwqBeD7i4E2TxrQXhBqNBk899RS++eYbRYKwu7vbLSqp0WjEKaecgh07dkh19u/fj8WLF7vVa22d2BKRyMhIvPDCC9i7dy9eeOEFrFu3DhkZGVKS6PEm1K2trYiMjAyKaJvo/kQlJVDBVDxLcXFxUISbmMA+0PdNTU1FXV2d4vp2ux02mw0tLS0wGAxoaGjAwZrbkNR0oWxC+gN1l+FPRb+VBOFrFT+VxGCs9hw8UHAH7iu4G38r/t24gvD9mivxSPHtiG86Bzn685Bs+Psx9z8qKkoShP9t2IQvGjYhThSETRe4pM64DFEN630IwjD8s+JaD0F4E16p/JmbINxbeZ3gITSuVCRoiouL/fbCuYo7pWWsdBhiGoji4mIpT2BSUhLi4+ORn5+Pnp4evzx2/qbqGBwchE6nQ2pqqt/XWSwWxMbGjlnn8OHDE/p3M5iE+r0WIFgQTiJtjkEp6Xp9qyPU5kx7RkZG8WmuQRJRYeFq3HugAI1t0yfozOjoKKLLLbjmtRSpD1v+lYEyY1eoTZsRHMrRIyxcjZ+9kTbj95xOFaa9IHSFFAhCT7799lscd9xx0Ov10rH9+/djyZIl/jY/LiUlJTjllFP8mlC3t7dL+4ICLVa0Wi0SExMDfl+HIzBLJX0Jt7y8vIDft6ysLCj3TU1NRU1Njdfy4PLychQWFkrBVhISEqDRaBAREQGVSoWoqCjExsYiOTkZ+2uuQVTDD2UT0rtGGH2o6A48WXqzy3LRS3Ffwd24r+Bu3F9wF/4pIwj/5SII36n5CR4pvh17Kq9BgeEcRGv9C4AkVyIjIwVxayvDFw2bnGkzhCWj/2k86un8qPZH+LLuYllBmK1bgZfLN3sJwterfuomCPdUXg+98Uw0NZ+F2oZKdHV1jSlWCgsLUVFRETBx56tER0crjvxpt9uh0+kQGxsLjUYDlUqF5ORklJSUoLm5eUyBKOexU1IaGxuRkZHh93XNzc1ITExkQRgaWBBOIvvSmhAWrsYv384MtSkzivaeQTz9bYUktlc+EY1HvyhBg3Xqiu6RkVEkVrdK6RHCwtW4+Pl4HMzWzZjlr1OB7v7DWPuUsLy43NgdanNmBbNeEG7ZsgXXX3+927H9+/dj7ty5WLZsGc4++2z88pe/RGVlpb/meNHY2Ijjjz/er6WfnZ2dUKlU6OjoCLhY0ev1iIuLC4ogTEtL88szprSUl5cjNzcwSdM975uTk6OorrgH1Gw2S8FWXHMwuqboEPd+isuDExMTkZaWhpycHBQVFbkEW9HCZDLBarWiq6vLrb2vGy7BVw2XIVp7PiIbN7glpP933bVugvDhot8h0Zl6QlwuKpa3an7m5SV8q8bdS/i34tvxSPHtyNGth7rpkoAIwtbWVpRY3sEXDZsQ1bhe1tP5dvVPsL/mcllBGNd4Ll4su8FLEL5RfZ27IKy+FvXNy2AwnglN9geIiIiQksqLy5ddxcpElmVGR0ejra3Nr2siIyPR0dHh1zViqoru7m7odDoUFRVJCeSTk5NRWlrqJRBbWloQExPjt7CbaM5DJZ7FI0em3rKpUL/XAgQLwklidHQU17+RirBwNT7O0Y9/AeM3DVYH7j2QLwms5dvVePDjQhTqO6aMd2joyAi+LjRKz4K4D/KN+Dr08PLQoPDnz4Q9mc+ojj0PODM+s1oQms1mzJ07F19++aXb8ezsbBw8eBAlJSVITU3Fli1bsHjxYhiNRn9NcsNqtYKI0NbWpnhCbbfboVKp/LpGaTEajYiJiQmKIMzIyEBNTU3A71tRUYHs7OyA3tNut6O0tBTp6elobm5GY2MjqqurUVZWhoKCAmRlZSE1NRXx8fFQq9WSyFOr1bI5GF0D/KSkpKCysnLC+z/NHU2IbNqAr50J6f/T+CO3/YPv1tzgJggfKroDsdoNiNWeg/udy0XFsqf6F16C8F8egvD/in+PR4pvx96qnyCm6Vx0dduOaWwjIiJgtVqRZnjIfbmoh6fzpfLN+Ffl1bKC8EDVZXiuZIuXIHyz6hovQVhiWA+T8QwUtbyP3t5eNDc3u0X8FPfrNTc3Izs7G9XV1X6JoKioKNhsNsX1BwYGpNQM/rTjK1VFd3c3tFotCgsLvQRiZWXlhILDTDTnYUNDw7iexVkkCLcRkZ6IBokoj4h+OE79O4iojIj6iaiFiP5NRKf60R4LwkmitFkIcLH2KQ26+6eex3smUWbswv2HCiTBJS4Z3J+pRXdfaMa+2mLHc5FVuMgZYTYsXI31z8Zil6YabY7BkNg0W0ivb0NYuBobdsZh4PBwqM2Z8cxqQbhr1y6ceuqpGBr6/+y9eVxTd77/f2a6Tu/3zv3N/O6d3t7vHcOOCq6tVWtbO1Nnpq22ta211mrtYmtrN61LUHBB2SHBtW6ta11qqw1wQhISlkCAhAABkkDYCfuuRgVq1df3j5BDDgmQg0njcl6Px+ePhHNOPonLyZP3+/16De9idO3aNXh7eyMkJITplmjq6ekBQRCoqalh9KXa0nbnbLhqamoCSZIuAcLs7Gzo9XqnX1ev1zvkjHrhwgW0t7fb5DBau7jKZDKIRCKqTVMgEEAsFiM1NRVZWVlQqVQoLCyETqdDRUUFamtr0dTUhI6ODodbeG8VjNUtP+NMxXRs0czF6YrHcabybzQgjNa9ZgOEgqoncMwwnQaDH6nfRaz+dTvRE38fBIRv4cvCRQjSzMe5imkwtKXc0p+XQCAwxxrUvNRvKGOuECZVBdAqnWsLXsf2ohftAuGGgvkILnzVBgh3ltKBkF/6PFKqZqCp8TEoG9fawInJZEJtbS0NpiQSCRWX4IgZC9Ocv6tXr0IgEMBkcixuwrIcdTO1BkRLi6nF4bOhocEhx9GSkhLGbqt9fX0oKysbsbJ4jwDhWwRB/EIQxPsEQYwnCOIgQRAXCIL4yxDHzyII4gZBEF8SBOFJEMTTBEHoCII4z+A1WSD8jRT8s9kC/4tTt59B0t2q8lYT1p4tgn9IMgVhPhuFePc7FU6pjOi47DoQu3nzJnRNFxEvLceLOzJpcDo9XIb9GVW41Mv+YuC30PUbNzGjP8KDLG5293buet2zQHjz5k34+Phg1apVDh2/YMECLFq0iOmWbF7zvvvuYxysLhQKXZLp50rDmtzcXJSUlDjtehazlaKiIqSlpaGyspLKxMvLy6My8SQSCS0Tz5LDaO3iWlJSgrKyMlRXV6OhoQGtra3QarXIyspy+ueQlZWF0tLSUZ8vMkZil/4VPCNbi2dka7FTN58GhOs0b9kA4cnyWTbtoh+p38XW4pGNZdYUvoEv+9tGd+pfgaIh/Jb+zCzV7XNVM3CmciqSa8xOqeeqJlm9jxlYplyGNflv2DWUeUOxAusKXrcDhM/RgDBOPwe7tf8yA2H9whGBJjMzE3l5eVCpVBCJREhMTKT+vNra2tDb22u32sck52+0URCjcTOtqalBWloaampqoFarIZFIaBEQQwHiaMx1+vr6oNPpoFarhz3m+vXb77e6LrhVqQiC2GP1+PcEQTQRBBE0xPFrCYKoHvTcFwRBNDJ4TRYIfwP1XruOCf3GJ5kV7e7ezj2niz3XcCynFv+Kl9PAjMMl8a94OTYLtEgqbkJ1++VRz+/1XrsObeNFHM+pxeenCjE9XEZ7HZ+NQnxyIh9pZW1s3IgbFCs2gMMlseywyt1buet1zwJheno6CIKAVjtyb/L169fh7++P1atXM92Sjf70pz8hOzub0RdrV2X6WQxrnB1nYTKZoFKphg2Qv3TpErq7u9Ha2oqGhgZUV1ejrKwMxcXFyM/PR05ODjIyMiCVSmlZjImJiUhMTER6ejoUCgWViafX66lMvObmZodyGK1XWVmZS4BQoVDcUqX0bNUKrFEvp4Dww+wVNJAaDIOfFryDnfrnbdpFP1K/i9X5S0YEwiDNfAoIvy74EGTte6PeuyUGobqlBGcqn0BC1QSqXfR05eM0p9Qlyg/xgXKpDRBm1XhhvmIlvsx7ywYIdw2qEEbr/4mP8t5BQ8NjyDM+OyLQZGVlobKykoK9zs5OlJeXIycnByRJgiRJ5Obmory8HJ2dnbhy5Qrjap8FiplGQYjFYrS0tDA6x14L54ULF1BdXW0DiCUlJWhsbMSVK1egVqsZz1L29fWhqKgIhYWF9zoQPkgQxHWCIOYPev4YQRAJQ5wziyCIawRBvEQQxO8IgniUIIhMwlxZdFQsEP4GSihqAodLYmaEjDUMcbMq2y5jT1ol5u3KsoFDDpeEf0gyXtqZiQ+PqhHysxY7pBU4KK/G8dw6nFQacURRg/0ZVYgVG7D2bBGWfqfCszFp8Aiyf60Pj6rxQ149uq6wOXjuVE3HFXC4JDyDSLRc7HX3du5q3fFAePnyZSpPjCAI8Pl8KtMLAIKCgrB06VKb85YsWYLp06fbvWZoaCgkEgmqq6tRUFCARYsW4eGHH4Zer7+Fj9qsMWPGMDZykUqljNtMHVmWYOnu7m6nXM/abCUrKwtZWVnQ6XQoLCyEUqlEVlYWUlNTqWqMxWxFJBJBJpMhMzMTSqUShYWF0Gq1KC8vR21tLRobG9He3o4LFy6goqIC6enpTv8sDAYDMjMznX7dW22dPVbxGl7NMMPgbNlqTBNtwJFyi6HMTLtA+FXBQhsY/Ej9Lj5SjQyEm4tepoDwU/VyHDYsuGUglNd9izOVT0BcMxCdcaLiSQoIvzU8hSXKD7FE+SFyaj1pQJhYMQHzFSvxseodGyDcXfovGhBG6F/AYuUHqG7goKAucESgyczMRHV1td2f9fb2oq2tDaWlpcjKykJiYiLVkllRUeHwTGB3d/eooiCEQiHa2toYneOIOUx3dzeqqqqQl5dHhcgLhUJkZmaisbERV69edfj1LNX2exwI/4cw30BnDno+hjBXDofSmwRBXCYI4tf+8xMJgnhgmOMfIsw3acv6vwQLhC7Xkm+V4HBJxEkM7t4KKyt1XO6DsKQZmwRavLw7i9ZaOpo1OVSCxYdysUNageyqDvT8cvv9v3Uvy5Jb+U16lbu3clfrjgdCS6Vv8Fq2bBkAcxD97NmzaedcvHgRf/jDH3Dw4EG711y1ahXGjBmDBx98EI8++iheeuklpwUsBwQE4KeffmL0xdrSIulsWLF8Ye/stG8ccunSJXR1dVGZeBazlaKiIspsJT093cZsRSgUgiRJJCcnIycnB2q1GsXFxSgrK0NVVRXq6+vR2tqKrq4uxtXJqqoql2QnlpeXQy6XuwQIdTrdqM/fXboA/0gzA+HzqV9hmmgDYkvm4GjFTOwre8YuEC7Nec8uEC5XLR0RCMNLXqCAcIV6CaJK3hj13i9cuGD++1DzFc5UPgFRzZN25wd3lz5HAaG8xpsGhHu0L2C+YiXezX3ftkJY9vIgIHwR76nehdYYgGIjB1d7hs/wG8q4xd66evUqamtrqRk9i4NpQUEB6urqYDLZrxp2dnYiKSmJMRAyNa/p6zObw6hUKkbndHd3QyaTIT09nQLEjIwMaq5yOEBUqVQjmvLcuHH7tVg5+TY1GiAcTxBEM0EQ6wiCmEgQxL8IgighCOK7YV5nK2HnPscCoevUdKGHqh7VdV5x93ZYDaPrN26iuv0ypPpWnMitQ6zYgKBzxVh1RoMVx/Px4VE1Vp4swOofNNgk0GJPWiV+UNcju7ID7aa+28bJlJV9/ZBXDw6XxN/i0tk/KxfqjgfCO03Tp0/HkSNHGH2xlsvlMBgMTgGUCxcuoK2tDY2NjaiuroZAIEBhYSEKCgqoTDyZTDZkJp5CoYBKpYJGo4Fer0dFRQXq6urQ3NxMM1uxzPY5G7Cqq6tdkp3oqspjTk7OqIHwwsVubNa8g2dla/qBcBWmiTZgadZ7OFoxE3G6OTYw+FnBYswUr8VH6qW2QJi3FPGlc4YFQr7+eQoIPy9YhE/y3kdNp9bhv1fW7b8ajQYCgQBnS1/qbxmdCGFNAM5XTaTNQYYVv0gBoazanwaEK1TvYb5iJRYoPrYBwh2l822A8FP120ivmQ698a9ouDh8O2NaWhrq6uoYwZNAIEBfX9+QDqZFRUW0Wb3RZAOO1pnUkm3JFD7lcjlqamrQ29tLqyBaDJfkcrldQMzOzkZ5efm9DoSjaRk9QRDET4Oee5ow34gfG+IctkL4G2t3agU4XBJv7s9x91ZYsbqndbnvV4wNEYHDJZFf1+3u7dy1YoHwN9acOXOwe/duRmAwXNuhpU2zubmZysSzmK2oVCrKbEUsFlNmK9aZeAKBAFlZWTaZeA0NDXYz8RxdxcXFLskLrK2thVQqdfp1KysrXVJ5zM3NhVY7MlDZW2VtOXgr80tqfvA56deYJtpAtY2GFL1iA4RrC5dgmmgDVqiX2K0SxuheogFhlO5f4Onn0qDwi4K3KChcmPUVjuq+pVWHrU18hvp7lZmZiZycHDMQVszC+cqpVLvomcqpNCBcXbCAAkKyKoCCwfQaX8xXrKTWNptgelsgXJX/Jr4tfR6G+v+Fpu3YsLAik8kccvK0rvYlJiba/ZklUD4/P5+a1cvIyIBarUZycjKjGcLROpNaWueZAmFaWhqMRqNdMO3q6kJlZSVlvGMNiDKZjJrBHGrdjr/NdcGtSkUQxG6rx78nzAYxQ5nKnCMI4syg52YS5hvx/zj4muwMoQt18+ZNzI5JA4dL4qy63t3bYcXqntfqHzTgcEkEnStx91buWrFA+BvrtddeQ0RExJAQYG22YsnES0tLo75cWsxWUlJSaGYrjmTitbS02LRpJicnu8TBVKfTOT0v0GQyoa6ujvEMpiOrqqoKqampLgHC0bqt/lR1Gs9LN1BAOFO8ngLC2JI5+KzgbRsg/Dj3Y0wTbcCHKjszhOp3Eax5laoMril4A8/IvsY/U7/G25mfYmuxGQy/tALCN+Sf42vFaloUh6U6bDHxsff3ymQyz6j+mHQCZyqfQGLVTAoIv6+YRjPGeVf5HgWEP1VMo4Dwp4rJNCAMGwSEkbpXbIBwfeHr+DTvbVTW/19kNoQMCytMnTyZVPsslbbMzEyqyj6cg6n1Gq0zqSMzffZWSkqKQ5/DYEBMSEhAQkICMjMzodPp0NzcbAO+9wgQvkWY8weXEQQxjiCIA4Q5duLR/p9HEgRx3Or49wjz7OCnBEF4EWaTGTUx/MzhYLFA6ELl1XZRweNX2NBxVqzcruyqDioDkp3xdI1YIPwN1NvbC6PRCLVajTlz5mDRokVYvXo10tLSqEw8i9mKpU0zMTERIpGIel4qlVKZeBazFaaZePaWqxxMS0tLHcoLZLrq6+shEomcfl1XtaIqlUrGMSOWtUWzA8+lbKQZyljWO5nv2cDgyoLF+FvKWvPPsz+wC4Rf5y9ArPZFLMj6iALNF1LXYrZsDWbL1uCtrA/xSd7bFBC+p/wE7+Z8Mar9d3Z24lj6VpypfAJnK2dQQGg9P2hxGLWsE4a/DcwP6mbTK4Ql9HD67dq5NkAYrHkFi5XLUVHvDUnd0mEBRyKRoLm52WFwam1thUgkYgRbDQ0NkEql6OjogMFgoBxMhUIhcnNzUVFRgc7OThogWmZ7h4NGe0ulUkGv1zMGQpFIhNbWVsbnSSQSVFVVoaKiAkqlEsnJyUhMTKQB4j3QMmrR5wRBGAlzHqGKIIjpVj87ShBExqDjvyAIQk+Yg+mbCYL4njC3gToqFghdqHU/FoHDJbH2bJG7t8KKFSsAN27cxKyoVHC4JH4ubHT3du5K3RVAKJfLMW/ePDz22GMORU8MZUTT0tJCO+7s2bPw9/fHQw89hMDAQAiFwlF9yF5eXvjd736H//qv/8Kf//xnjB07Fs8//zxIkqTMVqwz8bq7u2nVlsLCQqjVaqfDislkdjCtra11+nUNBoNLTFoaGxuRnJzs9OvW1NS4pBV1NEB48eJFtLe3Y2lWCP4uC6IZyljWM0lB+CjvXRoQfl24gPr5yxkr7QLhgsyPMLt/JtGy/i7jUkA4W7YG/0j7El8WmKHwQ9W7eCnjc+jamDuldnZ24ru8D3Cm8gn8VDUZwpoACKom0NpFDxlm0YDwG/1cCgjXF7xGA8JQLR0It2nn2QDh1qK5WKxcDp0xEMKaOSOCEJNoh+bmZojFYkbQVFdXh/T0dNpzPT09aG1thV6vpxxMRSIR8vLyUF1djebm5lE5k+bk5MBgMDA+jyRJdHR03DJIWqI7LIAokUjuBZdRd4kFQhfp6i+/Yvwm87ySqqbL3dthxYpVv+Kl5eBwSbxzSOnurdyVuiuAMDk5GcHBwTh//jwjICwvL0dLSwu1rH+bnZ2djfvuuw8xMTEoLS1FSEgIHnjgAYdyCweru7ub+mK0ceNGfPDBB4y+WLtqHs9kMiE1NRVVVVVOv66rTFqamppAkqTTr1tXV4eUlBSnX9eSxzhU5qK1W6tEIqHcWn/++Wf8S7Yas6VraYYyluV3bisWZ31GA8JPVB9TP58lWWsDg0tzP8ATyUE0GHxGthYzxOtpQPisbA3ezv7cHD2RvxizpGtxoOww4/e4n3hRAAAgAElEQVTe0dGBwyVz8UPlk1R18Oyg+cGd+r/RgDCy5HUo6zyQU+uBt7KX04Bw66AKYagdIAwrnofFyuVQVD8OcfXUYYGGabRDY2MjUlJSGEFTTU0N5HL5sMdcvXoVTU1NKCkpQXp6OtUGPpKD6eBlnavo6Ort7UVCQgK6u7sZA6EjTqi3o9x9X3OSWCB0kX7MbwCHS+LZmLTbsuWZFat7VfVdV8HhkvAIItF4ocfd27nrdFcAobUIBkB44cKFIY9ZuHAh5s6dS3tu+vTpWLFixWi2RSkyMhILFy5k9MVap9MxDrN3dGVkZKC8vNzp13XVTF5LSwuSkpKcfl2j0choNnG4SA5r05WkpCSqDdiSuWiZx7NkLup0Oppba2dnJzKMJXjeCtqsDWUeF26A70+hmCvj0oBwhtWMoT1jmWdT1mAyGWwDhE+lrKMB4WzZ15iaHISP8pbgi4JFmC1di09UWxl/pu3t7ThpmIWT5QPzgydp84Mzsa34JRoQritcBGWdByTVY2kwOF+xEltKXrZxGo3UDW4ZfQeLlctxWDsHmTU+UGQrYDAYbNoyR1MZq6+vR2pqKiNoqqqqsgmLdwQ8SZKERqOhjJ/S0tJsHEwHr4yMDNTU1DB6rdEa2DjihPrLL7dnoLO772tOEguELtLC/TngcEnsklW4eyusWLEapEUHctl/ny7SPQ2EHA4H//3f/405c+ZAoVDQjvnrX/+K+Ph42nObN2/GxIkTR7MtSnv27MGLL77I6It1WVmZS0LTTSYTsrKyUFZW5vTruqoFs7W1FQkJCU6/bn19PZKTk9HZ2UlzbNXpdCgsLIRSqURWVpbdWc+hIjkqKyuhUCiQl5fHOHORV3wa05PtG8pMTAyB37lQPJG4mYLBJbnv02BwmmgDPsobiJ54I2sFJpEhmESGYJaUDoRPS9fiGekaGhQ+kRyE56Tr8HnBIrwiX40X01cznlWta67E6YoncLx8oEJ4rGI6DQi/zF9IA8LlqnehrPPA94ZpNkC4qfgVGyCM1tPnCNdr3sNi5XJ8mrcY2bW+yC+VUm2ZYrEYarUaNTU1MJlMSExMRFdXl8MQZK/9c6RVXl6OnJwcRuc0NTXRKpH2HEwtTp/WRi6pqal23UKHWyaTCQKBgFEgfV+fOXZDIBDg8uWhsx5ZIHSpWCB0gYydAxWIJrYCwYrVbaef2Aq+y3RPAqHBYMD+/fuRn5+P7OxsvP/++7j//vtRUFBAHfPAAw/g1KlTtPP27t2Lv/zlL6PZFqVjx47h6aefZvTF2lXtlybTrQenDwkDLnIDbW9vh0AgcBiuLLEcTU1NqK2tRXl5ObRarU3uoqVV0+IIKZFIaI6t1rOe9fX1dmc97S21Wo3CwkLG7/PjHB4eF26waygz7vxm+J0Lhd+5UCxTms1l5qZ/ZgOEy5TmgPqP1cvwRHIQBYQzJOttqoQzxfQq4UzJOkxN3ojXs1bg7ZzPMEu6BhkNuYzeg6Lue5ypfAJ79c/ip8rJSByUP3i0YiaWKN+nAeES5YfIrvVETMk/bIBwc/GbIwIht+hdLFYux2LlcqRUPwlt+1mqEtbY2Iji4mKkpaVRf9b5+flobGx0CIgcaf8cvMrKyqBUKhmd09DQAJlMNuTPu7u7UVlZSRm5JCUlQaFQQCgUory8nJEZjSVbkamBjcX4Zrg4DRYIXSoWCF0gnsQADpfEkm/ZGSVWrG5HsTO+rtM9CYT29Oyzz2LJkiXUY1cB4fnz5zF58mRGX6xrampc4oBpMplNT0YbizDcamhocIkbaGdnJwQCAVpaWtDY2IiamhoYDAYqlNs6lsMa8oRCIVJSUpCRkYGcnBzKot+Su2gwGECS5KhzF4da+fn5owLCl1I34UkR166hjN9PWykgfDl9JT4teAezxGttgHBB1sf4SP0uFitWUTA4iQzBNJHtHOF0EX2O8OmUtZiavBFTkzfilcyVmCVdh42Fhxi9h5+ruPiu9Bk8229i82H2YhoMHil/ygYGlyg/RGqNHz7PW2QDhMFF79oAYYTuBRoQrtO8TQHhMcOLyGrcPizQKJVKiMViJCYmUtXy9vZ2u4A0mvZPnU6HvLw8RucwqUT29vZSDqaJiYlISkqiOZh2dXUNC3sdHR0gSZLR/vr6hs9ktKxr167d0v+VrpK772tOEguETtaNGzfxVKTZxVCgYV0MWbG6XcW6ALtGLBD2a+3atZgxYwb12FUto1KpFD4+Poy+WDOdb2Oy1Go1NBqN06/b1NQEoVDo0LH2shct83iDTVcsIegCgYAKQZfL5cjNzUVBQQG0Wu2oYjlcZVZTUFCAgoICRufUd7TiKck6zJSsszGUscwPWoBwVvJavKdaZgOD00QbMCf1K3ysXoJJZDANCKdataIOBYTPytZQQDhdzMXT0nWYm76Z0fs4Wf4O1uW/Qb3G/LRPcLh8AAgjS+baBUJB5UTMV3xiA4RfFbw3IhB+XbiAAsJNmqVIqfvQLqxYz85Z3DENBgOys7ORlJSE5ORkqFQqVFdX4+LFi+jr60NFRQWys7MZgVNJSQkKCgoYnVNdXc24EtnXZ56JbGtroxxMMzMzqVZZi4Op5b1Y1miiNPr6+tDW1obk5GQWCN0nFgidrKyK/pyzLWL0Xrv93HFZsWJlFpsT6hqxQNivOXPm4LXXXqMeL1y4EPPmzaMdM3PmzFs2lVGpVHj00UcZfbF2VdSCBVjy8/Odft3m5mYkJiZSpiuVlZXQ6/XQaDRQqVSU6YqlOmPPdMV6Hs9iutLY2AiBQICOjg6n79cVZjWj+Xy/1aZjpni9ebZPthZzZAOQNyEhhIJBv3OhGHd+M17OWGkXCJ8UcfFC6uc0GJxEhtg1lpkpsWcss7F/bcDz0hDMkq6Dwuj4vOlRwzzMTV85kHco/Rzx2vkUEK4vfM0uEO7UPWcDg/MVK/G+cuQK4VrNGxQQvq9aifPVr9uFleHC33t6etDc3AytVku5flp+8ZCRkcEoML6oqAgajYYRbFVUVEChUDCGtISEBJuZSHsOplKplHIwNRqNjJ1T+/ps5xztrV9/vT1v1O6+rzlJLBA6WV+eLgSHS2Lj+RJ3b4UVK1bD6ObNm5gdkwYOl8SP+Q3u3s5do7sCCC9fvgyNRgONRgOCIMDn86HRaGA0GgEAQUFBWLp0KXV8fHw8BAIBKisrodVq8dVXX+H3v/89ZDIZdUx2djbuv/9+xMXFoaysDFu2bBl17IS1SktL8W//9m+MAMFVzpomk4lyxXTk2EuXLg1rupKZmQmZTIbk5OQhTVfy8vJQVFSE0tJSVFVVwWg0oqWlxWHTlUuXLrkECFtbW5GYmOj0z7ewsJAxEK7KOYwp5EAVb4YomIK8see20IDQ71wonhBy7VcIU4LxjGSNDRA6bizDpaBwVvJWzJKuxdeq7xx6Dx3dzYgoegsvpH9OvcbjZDCWZL1PAeFn6kV2gfBz9Vt2gXBZrr0K4YuDZghfo4Bwcc6nOGR4xS6sWP4eOTI7ePnyZaqN0+IaK5fLodfr0dbWNmxLZkFBAYqLixnBlsFgQG5uLqNzenp6IBAIbCqA9t5LfX09zcE0MTERxcXFwzqYDl5Go3FEx1UWCF0qFgidqIs91+AXnAwOl4Smfmj3cVasWN0e2p1aAQ6XxML9Oe7eyl2juwIIhwqaX7ZsGQBg2bJlmD17NnV8dHQ0vL298fDDD+PPf/4znnvuOaSlpdlc9+zZs/Dz88ODDz6IgICAUQfTW6uhoYGKvHAUEJgaqTBZxcXFUCgUNvN41qYrUqkUQqGQatUkSRIpKSlDmq40NDSgoaGB+oLq7D0LBAK0tbU59ZptbW0ucS/VaDRQq9WMzpkni8HUfkOZ52Rrhpwf9DsXCp+zoRh/frNdIBz7w3Y8J1pvFwjtGcvMkqy1aywzNXkjZolC8GQyF3PTt+JC/5+pdauvJXrDUgU+q/oWL8m+wvNpq/CMbC2eTVmLiUkheEq0hgLC91XL7ALhkpwP7ALhktwPRgTCjcWvUkD4ZvbHiNHaB0LLDCETMxWdTge1Wo3u7m5UVFQgNzcXJElSM3uVlZU2eX5qtRo6nY4R3On1esZzh5aK53Cun/ZWeXk5pFKpjYOpTqdDS0vLkKYxjhjssEDoUrFA6ER9r6wDh0tiDi+DdS5kxeoOUNOFHngEkeBwSRg7r7p7O3eF7gogvJN08eJFEASBhoYGhwGhq6sLAoEA3d3dDh1/4cIFtLW12YSgj2S6IpVKqXm8waYrjY2NaG9vdxhkLXt2tkmLyWSOC2htbXXqNV0F3RqNxuEKrAWynhRuwrT+APnnpcFDzg/6nQuF16kweJ/abgODEwWb4HkyHI+fC7MLhIONZWZK1mNy4gaa26i1scxMUTB8f9iG2dL1CBEep7X62qsCr8qMwtP9M5DPyNbi6ZT1mJgUgolJIdiln4ODhll2YfCd3A/xSurndoFwcc6HNkAYpXuDBoSbSl6mgHBR7kdYW7AUHSbbbL7u7m4kJCQwgid784A9PT1obW2FTqeDXC5HQkICUlJSUFhYCKPRiNzcXJSWljJ6Ha1Wi/z8fEbnOOL6aW8Nbk8dysF0sNmOI/OU16/fnnNY7r6vOUksEDpRr+5RgMMlcUBe5e6tsGLFykEt+VYJDpcEL6Xc3Vu5K8QC4W+s69evgyAIRtl/Fy5cgEAgQH19vY3pinUIulgspkxXEhISKNOVzMxMWgi6temKVquFXC53OrRZ9tzZ2en0ayclJaG5udmp1+zo6HBJRbOoqAgqlcrh4zONpZgi3IgZYnMFb2rCABAGDpof9DsXCo/jEeAci8JU4UYaEPqc3gbPk+HwPBmGSUm2QPhE8kYzrIk3Yvy5zfA6vR1eZ7bD60wY/M5uw5TEDZievB5ThWYgnCLcCP8fwjBduBGvSOKoVt+hojdeTt+IOalfDpjWiAeAcHPh2+Dp5tgFwgWKj/EsGWIXCN/KXm4DhKEli2hAuFU7jwLCt3OXY4niK+S22LY2dnZ2IikpiRE8OTIPeOXKFdTX16OwsBBSqRQCgQASiQRarXbYihvT1xm8urq6GANuX9/wsRjWDqYWsx1LNTQnJwcKhWLYCisLhC4VC4ROUmWbCRwuCa8NQrSZet29HVasWDkogaYRHC6JpyJTceMGW9m/VbFA6AY98sgjUCqVqK2tpc3jWZuuWIegO2K6UllZCaPRiObmZnR2djpc6XJVxqFlRqu9vd3p1xYKhWhsbHTqNS1xFs6uaDIFwq0qAaaQGylDmckJQ88Pep/dBs6xKHCORWGCYJNNddCyHk/YagOEjyduhu+pbfA6HW61wvrBMAxeZ8Lg80MYfE5ux5R+KJx8LgJeZ7bjOclW1HYMDeQ5DRo8LeHiRav5wSeSgyggXKZYia1F8+wC4QtpXyDwp012gXBB9sc2QLimYCENCLfrXhqYIVQux8up67G/4jsbWGlvb2cct1BYWMh4HlAulyMvLw9KpRJCoRBJSUnIyclBeXn5kJEQo5k7HM376esbaIN15Nienh60tLRAr9dDLBZDIBAM62DKAqFLxQKhkxQhLAWHS+LDo3nu3gorVqwYqPfadQRuEYPDJZFd2eHu7dzxuiuAUC6XY968eXjsscccchk9d+4c5syZg//8z//Ev//7v2PGjBkQi8W0Y44cOWIzk/jQQw+N6kNubGzE0qVL8c9//hOTJk3CQw89hN///vf4n//5HyoEfSjTFUsIelJSktMhyGQyobq6GqmpqU6/rslkQkJCgtNbO00mE0QiEaOWW0cW07ZcR1dxcTGUSqXDxy9K3YfJ5EaqzXJq0kar+UF6ddDzVBgFhL4/bLNTHTSvCT/Q20YnJoXA+0QkPI5FDALCcKpKaFmcYxEYfyYSk5KCEXBuC7zOhGHq+Uisz/1pyPcQpP4W08VBeCl9oGV0ErmRAsLpyVysKXjDLhDOJNfD90yoXSB8XbHCBgi/LniTBoQR+hfxdu6HFBA+m7wRG4o228CNI7EJg1d+fj60Wi2jczIzM1FdXU1V3Nrb21FaWoqsrCyq1TY/Px+1tbUwmUzo6+tDXl4e47nDlpaWUcVHFBcXo7CwkPF5Go0GBQUFaGxsRHFxMc3BtLCwEHV1dejr6xvV/5eulltvas4TC4RO0K/Xb+CJMCk4XBIibYu7t8OKFSuG2nC+BBwuidVnNO7eyh2vuwIIk5OTERwcjPPnzzsEhF999RWio6ORl5eHiooKbNiwAQ888AAKCwupY44cOYI//vGPaGlpoVZra+uoPuSuri5s374dBw8ehEAggLe3Nw4ePMgI8EQiEerr650OV7W1tUhJSXEJEJIk6fTWTpPJBLFYDKPR6NRrdnd3QyAQoKury6nXLSkpQU5ODrq6utDS0jKiO+vMhK0IOL8JY7+NBGdvDHyPheGJ5A14QriRNj/o+2MoOMcjKSDkHIvE40Lb6qDnyXB4nwijwaDniXBwjkWCczhyRCD0OB4OjxMR8Pw+DAHnN5ufPx2G55L4Q77nF1M3Y7o4CM9ILfOD6ygYtKzF2R/YBcKxP2yF58lwvJplC4SvZn1qA4TrCt+wAcJ3cj+ggHBWchCWK7+wC1BisZgRBOXl5UGv1zM6Jz09nYKjwevq1atobGxEUVERUlNTIRAIkJaWRsVCMJkHbGxsHFV8xGiqkX19ZrOcwXB8+fJlGI1GFBYWQiaToaPj9vyNrbvva04SC4ROUGpZKzhcElO2peCXX2+4ezusWLFiqAJjNzhcEv4hyTD13p7Zt3eK7gogtBYxyhzC8ePHIzQ0lHp85MgR/Md//MdotjCipkyZglOnTjECC6lUSlURnLnq6+shFotdAoTJyckuqWqmpKQ4/bOwmHI4OvNocdgcKmfR0vJrmekUCARUNXgod9biqnI8Tm6C56EIcPbGYsw3MeDsjYX/yW2Ykkh3F/X/YbsVDPa3jf68CT5nttkAoefJcExJ3NwPg2FmGDwWCc4RO0B4OowGhJ6nBqCQczwcY09HmauEZ+OQWqOz+VwKmg2YLlqPZ1MGYjOekgwGwmC8krHSBgYXZn9M7Xde5md2q4SbS16hAWGQ5jUbIFyqfJ8CwuckX2Nh5ko0d7bR4MWRHL3BS6lUoqysjNE5qampqK+vd+jYS5cuoaamBiKRCCRJUoYuBoMBHR0dw87rORID4SzIdfSzuHHj9vyC7e77mpPEAqETtOJ4PjhcElsTde7eCitWrEahmzdv4u9x6eBwSZzJM7p7O3e0WCAEcOPGDfz1r3/F7t27qeeOHDmC++67D2PGjMH//u//4pVXXoFO55ybxrPPPosDBw4wApa0tDRUVVU5Ha6ampogFApdAoRisdglVU2ZTIaamhqnXtMy89ja2orW1lY0NDQMa94znMOmdcuvWq1GVlaWQ7OJETnJePxsJDy+iTUD4V4zEHL2xsLv9Hb6/OD34TZA6PV9mF0Y9DwZDv9T2+B7MmIABvuXx/HBbaNh8DkTbtM26nGifx2NhNepMPiejsD7opM272Gd6jhmiIMoU5zBhjITk0IwhdyAOZJVNkD4Utrn1H5fzPjCLhAGF8+nAeGm4ldtgHCZ8j0KCP+Z+iVeS/sK2wSHkJqaiuLiYjQ1NcFoNEIqlTKCIMvsH5NzUlJS0NjYyOicrKwsVFZWUoYuCoUCSUlJEIlEyMvLQ01NDS5dukQ7p6amBhkZGYzBLjc3FwaDgfF5CoUCFRUVwx5zu9r3u/u+5iSxQHiL6rzcB+8NQnC4JMpa2M+RFas7Vd+kV4HDJfHGN9nu3sodLRYIYc4l/NOf/oS2tjbquZycHBw7dgwajQYZGRmYN28e/vjHP6KhoWE026Jp7ty5iIuLYwQscrkcBoPB6XDV0tLikkB2k8lcyaurq3P6dVNTUxnB8VAxHGq1GtnZ2UhPT4dEIqEqecOZ91RVVcFoNKK1tXVIh03rpdPpkJOT49A+X/zpG/juN0OgzzdxFAxy9sTC45toqmXU98fQfqCjAyFnfzQ8vreFQY/vw8E5EGUDg5xjkfCw0zYaeCaG3jZ6LJwCQs6xCPgeiYXn6TAEHuWjubOD9h7+kRKO6eIgzLSKnLA2lJmYFILHk0IwXRBkA4RPJ6+l9jw3bbVdIAwqeo0GhMsU72FJ5ns0IHxftYwCwrkZn+N58UZs13yH2tpa5OXlUUZNJEmioqLCJjtwJFBjAk5isRgtLS2MzsnIyEBtbS3tuZ6eHjQ1NaGkpARpaWkQCASQyWQoKipCQ0MDysvLkZWVxRjssrKyUFVVxfi8jIwM1NTYxnmwQPibiQXCW9ShzGpwuCRe3p3l7q2wYsXqFtR6qRee/ZmENR1X3L2dO1b3PBCePHkSjzzyCKRS6bDHXbt2Dd7e3ggJCRnNtmhatGgRtm7dygiCFAoF9Hq90+HKlaH3rqjkmUwmpKeno7y8HB0dHWhsbERNTQ0MBgNKSkqGzVocKoajoqICdXV1EAgEaGxsdOpnodfrkZ2dPeJxrV2dGLuXD9+DZggcf3AHBYS++3nw2BUH7+Ph8DsXirE/RNjA4LhjZoD0OBZhA4ScQ1Hg7IsB54gtENqdIzwSAa9TVm2jJ8MGKoQnIuB3JA6cw1EIPBWLz0WCAfhtrcUz4i2YLg7CrJSBjMMpJH1+0PfMNow9GWYDhON/3ELt+QXpertAuE7zBgWDn+SsMFcvj4fjZemnCOsPqf8gbykFhPMzP8W4n0KxUrWdApXe3l6UlZVBLBYjMzOTlh1YX1+PK1eu2AUcuVxOGcQ4upKTk9HW1sboHEfaTE0m8/xvfn4+xGIxEhISIBQKUVpaira2tmHbS0eCT2ftkQVCl4oFwlvQzZs38Q9+BjhcEsdz69y9HVasWN2ilh1WgcMlESMuc/dW7ljd00B4+vRp/OEPfwBJkg4dv2DBAixatGg026Lpo48+wtq1axmBRW5uLkpKSpwOV66KWzCZmLe5Xrp0CZ2dnWhqakJtbS3Ky8uh1WpRUFCA3NxcyOVySKVSJCQkUJAnFAohlUohl8uRm5uLgoICaLVaKmuRSQxHYmIiWlpanPoZ6PV6KBSKEY+Lz86A5844eO+LoyDQAoTjDsTDY1ccPHbFwPfHUIw/FWsDhL4H+48/FEWvDh6OBGd/rHkdjLYFwqOR8DgRDq+T4fA5FY7xx+PAORANzv4YeB2KAedQlPkahwaA0PNoJDgHY+B7PAbeB+JQ1252kv085xieFm/CkyIuFZvxtGS9jaGMx/EIcI5GYVH2RxQMvpX9EW3fTydz7QLh14VvIlT7MpbIP6CqpJ7fm+ciZyd9jTDdPCzPW0IB4RuKFfA5ux1vyNfRYMW6xdI6O1AikSAhIQFZWVkoKyujze6lp6czhqekpCR0dHQwOodpm2lvby80Gg3S0tKQk5MDkiQhFAqhVCpRVVWFCxcu3BLY2VsSiQRNTU3DHnO7yt33NSeJBcJbUFH9BXC4JPyCk3GxhzWiYMXqThdZ3AwOl8SMCBmus5mEo9I9C4SnTp3Cww8/DIFA4NB1r1+/Dn9/f6xevXo026JpzZo1WLFiBSOwyMvLg0ajcTq0WQLkne2uaTKZkJGRAYPBgK6uLlre4lAOmxbII0kSKSkpyMjIQE5ODvLz81FSUgKDwYDa2lqkpaVBq9U6PUTeFYH3paWlDgHhSyeOYNy+eKpF1AKDY/bEwHN3XD8QxmHcwVh4HKXDoP+xgeM5ewfaRr1ORJgrgxYg3B9jC4TfRYKzL9oMgQdjBtbeGPrj/THwP8gH53AkOMcj4HEwGmMORsP/EA/vJ/2IS5cuYZYwAtPFQZgu5lLVwanCDTQYDEwIAedoFDhHozBf/hkFhG/I19CzExM32AXC1YWL8G7mB+AcG6iSep0cMMqZ9fMmLMsdaBldmPMRfM5ux9+lq9BwYQDMqqqqkJmZaReuurq6UF5eToWxi0Qi5OfnQyKRMK4QJiQkONySalmjaTO1VMf7+gbyArVaLTIyMpCQkEDFQQyugDoCdvaWUCgctvL5yy+/3PL/k66Su+9rThILhLegjf1W9V+eLhz5YFasWN326r12HRO3SsDhkpCXt7t7O3ek7gogvHz5MjQaDTQaDQiCAJ/Ph0ajgdFodhwKCgrC0qVLqeNPnjyJ+++/H3v37qXFSly8eJE6JjQ0lPoCWFBQgEWLFuHhhx+GXq+/5Q89NDQU77zzDiOwKCgoQH5+vtOhbTQB8pcuXaJiFIZz2LSu5A3nsFlTU4PGxka0t7c7VKlUKBQoLS11+mdBkiSampqces2ysjJkZWUNe8yFixfhu5OPSYd2grM3Ft57BuYHx+yNoWDQY1ccvKLj4H84jm4ms9tq3nBvLDyORsDz+3Bw9kdbwaB5eR+1gsID0Wb43NMPi4MAkHPA6vGBGHC+iQHnm1iM2R+NcUd45irhtzz47ufhQLEM08hQTBcH0RxGJyYG04Bw3PktFBDOS1lDAeGMRC4NCCf9HGIXCN9VrKbBIOdYFLxPbqdB7tPkWgoIF+Uuh8/Z7Zgt5uKwYcB0pbKyEgqFYkTwsY6GsPx9zsjIgE6nQ2tr67Ctmb29vRAIBDaB7Y7AVnt7O6NzLP//2fuZdRxESkoKEhISIJfLodPpQJIkWltbGQNhYmIiurq6WCB0n1ggHKV6frmOwM1icLgkFGyYNStWd402CbTgcEl8cYr9Rc9odFcAYXp6uk2IPEEQWLZsGQBg2bJlmD17NnX87Nmzhz0eAFatWoUxY8bgwQcfxKOPPoqXXnqJllN4K+Lz+Xj11VcZgUVRURFUKpXTIchkGmiV7O7uRmtrK+rr62/ZYbO6uhrp6ekoKipyejtqdnY2dDrbyINbXa6IySgrK0NmZuawxxxTq+AZHwfvvea2T/99fAruxn4TPwCEO+LgFcOD/07eABDti6bBIGdvLDj7ozH2+1gbGOTsj0Xg4XhwDkfCz6ollbM31gx7B1JeG3QAACAASURBVGOGrxLuMwMh55tYsxNq/zkee2Ix+aftmJa0CdPFQZiRPACEExIGzQ/+EEoB4eykDQPzg2e30IBw/I9b7OQQfobAU7ZmOv6n6e6pAadD8Wb2x1isXI63c5fD52woZiRtwue531HAUl5ejpycHEYQJJFIUFtbi6qqKiiVSqo1U6VSobq62sb588qVKxAIzDOWTF4nKSkJnZ2djM6xVNEdOba7uxuVlZVQKpXUL2tyc3MdNtjp6ekZEXRZIHS5WCAcpX4ubASHS+KpyFTcYFvLWLG6a1TcwLaC34ruCiC803To0CE8//zzjMBCq9U67FZJqz454LBpgTtHHDbr6+sddtjMycmBVqt1Ori5ap5SJBKhoaHBqdc0GAyQy+XDHvP6ye/hu4s/4CjaD2le38TBY6dVdTA2Dl6xPHjF8uBxIBqcY1Hw2BVrA4Re38Rh7CG+XSD028uDxw7bczh7Ym2BcDAkWlUJOd/EYvwePry/iYPXoSj4n9uKGaKNZiC0ipyYkDhofvBEOAWEE89uMucPKj62McLxPR1qA4T/Egcj4DjfNn/xTBwNCCedicQzieupKmHA+U3wObsNCzLCKWApKytDbm4uI+gSiUS0Vk7r1kzLvyPraAtLtuXVq1cdfg1LVXG4uT97S6VSMc4TtLyW0WiEXq+nDHYkEgny8/NRV1eHy5cv25xnMpkgEAiGNN/p6+vDtWu3783Y3fc1J4kFwlFq8aFccLgk4qXl7t4KK1asnKibN2/in3w5OFwS3ytZsyimYoHQDTpz5gyefPJJRmBRWlpKtR5evHgR7e3tTnPYFAqFKC8vR1dXl1MdNlUqFYqLi50Obkql0iXXFYvFMBqNvykQXrx4Ef674jFp324zmFkBnjc/blC7KI8CQk9+LDzsVQd3x8InloeAPTtsgfCbWHjxePCMi7M9b28sPHbRq4Eeu2PB2RmDcfv45mrhNzEIPLCDAkKfvTx4xMdh3NEIjD23GdPFQZiWzMUzUkv+4KBA+sRNFAxyjkbB+4TZafQF2Zd2shPD8GqWdXVwJfwPRcDzUIxthfBkzKAKYTQ4+2LweuYnWKxcjumJW/rbRjdSwKLX66FSqRgB1EhzcyaTiRZtkZSUBIFAgPLycofnCK9evTqqqmJOTg7jPEFLBdMa+q5cuYKGhgZoNBrIZDIIBAKkp6ejpKQEzc3N6OnpoeaOh2uXZYHQ5WKBcBSq77oKDpeERxCJhu6r7t4OK1asnKyDcnOczKt7FO7eyh0nFgjdIKFQiHHjxtHA4NKlS+jo6BjSYTMlJQWJiYkQCoXDOmzqdDqUl5ejrq7OYYdNV+UFqtVqlxjhuMpgRyKROP1zKC8vR0ZGxpA/P5SdC88dPIz9Jt4GCD2tgNAzbqA66BXLg1c0Dx58O9XBmDh4xfHM65s4Ggz6xPPgGc+DJ48Hzm7bcz3jYuHJi8PY3fEDlckd9Cqlx444BOzcCU9eHDi7YzF2Dx++P4Qi8LwZCB8nB9pFZwk304Bw7I9baUDIORqFhYqP8RS53g4QhuPVzC8pIHxBEmSeqdwfbZu/eJzeMup1LAqcfbF48qeNWKxcjinng+FzdjumJm1ASbsRfX190Ol0UKvVjACKSStnb28vjEYjBAKBTbRFQ0PDkNU1k2nk6pu9NZqMRMv8cE9Pz5DHXLx4EdXV1VCpVEhOTkZSUhLkcjkSEhLQ2dk5JBSyQOhysUA4CvFTysHhknjnkNLdW2HFipUL1G7qg9cGIThcEpVtJndv547SXQOEcrkc8+bNw2OPPeaw02h6ejqmTJmCBx98EN7e3jhy5IjNMWfPnoW/vz8eeughBAYGQigUMtkWpcrKSpw8eRI8Hg9vv/02vLy8MG3aNKxatcohh021Wk05AnZ0dDjVYTM1NRXV1dVOB6yCggIUFBQ4/br5+fkoLCx0+nVTUlJQW1vr1GtWVFQMC4TPf/sdJkRHYMXypdj+2jys/GAJxvO2wyM+dsjqoFcsD97hPPiE82iOpB78WPPP+4HQj8ejYNAjPs4Mg/3LK5YefO8TawZFz1h6VdJjVxw84umPfXj91+Hz4HsgGv7ntmJyQrAZCBOt5gfPb6IBoc+pbTZA+KZ8FQJ/3GwXCP8pW0VVB8cfiTAD4Td2gNBOlIbZXTUKC7JW4BkyxAyECWHYqROhr8/syllQUMAIoJg6hnZ0dIAkSaryVl9fj4KCgmGjLSxtpo7mCFqWI0Hxg1d3dzcSEhIcPr63txft7e0oLCxEQkICEhMTIRKJoFarUVNTQ5uh/PXXX0f1/+RvIXff15wkFggZ6saNm3gqMhUcLgmBptHd22HFipWL9OHRPHC4JCKEpe7eyh2luwYIk5OTERwcjPPnzzsEhDU1NXjkkUfw9ddfo7S0FLt378Z9990HsVhMHZOdnY377rsPMTExKC0tRUhICB544AFotVrGH/TRo0fx9NNP44033sBbb70FDw8PhIaGQigUUg6bw0FeXV0dUlJSnA5BJpM56L2iosLp19VoNFCr1U6/rqscV6VSKWpqapx6TYPBgNTUVDQ2NlIznBajnoMCEp8s/xAd/+f/AARBrUt/eBhb5s+Hx85+KOSbzWSsq4O+23nwDeMjcNdOqlXUK2YABi1r7B4+DQQ9rauEO2PhHx8P73g+PPlmwPOM49kAoMeuOPjs4NEeB+7aCY/4WHid3A7/c1swNWkjxh7fDs99kZhGBuEZ2VpMEmyhAaHn8XAbIHw2YR08T4bZBcK/ib/GfMVKvJwaZOW6Go0xR0cAwmOR8DoQB86+WDz1cxBekJiBcMJPkfhQcQB9fX0oKipCYWEhIxhi6hja1taG5ORku9eyjrawgFV+fj4MBgMEAgEjsOvr60NaWhqMRiOjc9rb2yEUChm/VmNjI6RSKeXAWlxcjLS0NNoMZWdnJ+P/I38rufu+5iSxQMhQWRUd4HBJTNgiRu+16+7eDitWrFwkia4FHC6JqdtS8MuvN9y9nTtGdw0QWotwAAjXr1+PgIAA2nNvvfUW/vWvf1GPFy5ciLlz59KOmT59OlasWDHarQEAqqqqcP/99zOa12toaEBycrJLgDAzMxMGg8Hp1y0uLoZSqXT6dTUaDfLy8px+XZlM5lCl1Dp2Y3C2Ym5uLuRyOaRS6bAznBqNBjve/YCCwMb/+BNEE6ai9s//ST1HTp6IsXERdquDvmF8+Ibx4R/BN8NgdJwNDHpF8+ATagcG43nw7L8OBYJWyyu6H/52mquDgfwd8A6Pw0TeTnhH8eAdxYNfNB+ee6Pg+0MofL7fBs5ec4TFmD3m7MTJ50IwKXGgQjghIcRcuRsEhH4nttmFQc+T4XhauA7zFSsx+VgErbXVFgijzNe2hsIDMeDsi4XngUjMSebC5+x2+Jzdjpelsejr60NhYSGKioochqDRzPY1NzdDLBY7dG1LtEVKSgqjaAvLYhpm39fXh5aWFof2N3jV1dUhLS3N5vlLly6hpqaGqhjernL3fc1JYoGQob44VQgOl0TIz8x/ocuKFas7R79ev4FpYVJwuCTI4mZ3b+eO0T0LhM888wy++uor2nOHDx/GH//4R+rxX//6V8THx9OO2bx5MyZOnDjarQEA2tvbQRAEo+y/5uZmJCUluQQIFQoF9Hq90687WmdUR0DTFREcqampKC0tpVXzLI6sltgNkUhE5dElJibSshUt7b0GgwE1NTVoampCWVkZUlNTbV6r/vQP+PX3vwcIAj9MmYHJIXEYG8LD+OA4bPvna/jl9/cBBIH0sf7wi4yxWx20LO9wHq1V1CuOB68YHnxDefAN58Mngg6DXtE8eEeal39MPB0I4/p/Fs6D9yDA9I3mU6/jGRcLjyMR8D25DZw9ZnObMXtiwNkTZ147YxHw00CFcMr57TYwyDkaBZ9DMUMC4YzEILwkXWcz6zjmiB0gPDwICA9Gg7MvFpx9sRh3PJQCwplnI9HY2MgopqGvz5zlx3S2z1JJYwJbra2tSE5OdjjawrIGO6A6shoaGhjvr6+vD1VVVcjMzBz2mOvXb98KjLvva04SC4QM1H3lF/gGJ4PDJVHccMHd22HFipWLFSs2gMMlseRbdl7YUd2zQOjr64uIiAjac0KhEARBoKenBwDwwAMP4NSpU7Rj9u7di7/85S+j3RoAoLe3FwRBMGpPbGtrg0AgcKoLqGW5KsZBr9dDoVA4/bolJSXIzc116FhHq3nWZj32qnl6vR6VlZUwGo1U7IYjr19dXW0LhLW16P7//gQQBBICHse4jTwEhsRj7CY+xobwMTaYj6VLV6Ln/gcAgsDPU6bCO9o8H+gTRodB3218+G02V+1o8NYPg77hfPhs58GPHw/P+AEQ9I7iwzuKD/+oeHhFW4FgJA/e0Xx4R/MxLnqHDWRO5u2CdwQPnF3R8DwcDs7umIE5xt2xFBB6xMfB99twCggDT0fYBUJfPn9IIJyduBUTjoXaAuFhO0D43aDW0UMDQDhmXwx8+4Ew8HAsdiaeRkJCAqRSKSorKx1qA3XEgGXwqq+vR2pqKiPYampqQkpKCvV4pGgLy35GE2ZfV1eH9PR0xkDoSIYjC4QuFwuEDHQo0+w8+OKOTNy8yWYPsmJ1t6u+6yo8gkhwuCSMnayjsCNigdBKvxUQ3rx5E/fffz+KioochqDOzk4qn8zZgKVSqRjtxdHlSCj7aJZOp0N2djYtesNeNU8sFlP5iomJiRCLxcNW89LS0pzeOltdXQ2ZTEZ7rnfBmwBBoPrP/4Up66MQENIPgpvMMDi2//HHiz7Ctf4q4nfPPIvxMfHws4bBMD78tvDhv4UPvy0DVULfbQMwaFl+oXz4hg6AoPXy3cyDz/YBELRekyN3wWe72cDGO4oH7xgeODEx4ByKNDui7howpuHsjhsAQl4cPPmxmPCzuW3U94SddtHv4uAdzYfXiQi7QDju++124zHGfGcHCL8dBITfRtGAMOBUjHmO8HsevpYkQaFQICsrCxkZGUhISEBqaipKSkrQ0tJiF/ociVoYvGpraxkDV319PWQy2ZA/N5kGoi0srp85OTkQCARoampi9FrV1dUjVvrsLUciO1ggdLlYIHRQN2/exN/j0sHhkjiRy2aTsWJ1r2jJt0pwuCSiRWXu3sodoXsWCN3ZMgoAf/rTnxhVzyxfSDs7O50OWPn5+S5xAx0pcmHwsq7mGY3GIat5FsizRG84Us1zpLIql8udDoQ1NTU0ILwqEgEEgRvE7/DmslUYF8zHuA18WnXQAoTTQvdg/cuLqZlC/px5NBicvG0X/PuB0H+LuRIYGLMTvmF0IPQLM1/XfzMdBH0i+fDb1F9l3MKHT3g/CEbyERC1E77bzMeMj9wB3208eEfw4B0WB8+90eDsiOk3mDFDmv8uPgWDnjsHWlD9j4SZ5weP2AKh565YeEfz4XM4yi4QBuzj2wVCzrd2nEYHA+F3A0DI2RcLz51mIPT9PgJPHNwLpVKJsrIyG8gSCoUgSRJKpZLWotnV1YXExESXAxeTqp3F9VOv10MgEDgcbWFZFRUVyM7OZgyExcXFIzq03rhx+w7yu/u+5iSxQOiglNWd4HBJjNskgqn39o1DYcWKlXOVXNIMDpfEE2FSXLt++96Tbhfds0C4fv16BAYG0p57++23bUxl5s2bRztm5syZt2wqAwBjxoyBWCxmBEsJCQloa2tzOri5yg20qqoKaWlpuHjx4pDVvOzs7BGreWq1GsXFxVQ1T6PRICMjw6nRGyaT2VynrKzM6UAolUrNj7u7cT0gACAInJk0EwEh8RgfPFAdnBK6k4LBCSHxGBdkhsXI51+loHDD/IVmINzKx/jN8TQgnLh1BwK27aBXB7f3g+NWM/T5bTHD4NjIeASE7YDvdj61/LbwEbjdfL5PZP+K4GNsKB9jw+PNraKxMfCIj4HPDh58dg7EXnjFDlQHvSPjKCD02RGLgDO2+YOcI1HwjjFXJT332QHC4+HwCouzC4SBh3eMDISHBwEhLxYBP0TD+/R2eO/k4bRUgvLycruQ1draCq1WSzlnpqeno6CgAElJSYwqhBUVFVAoFIwhUi6XMzrHEjB/4cIFh6ItLKu0tBRKpZIxEBYWFqK4uJgFQveKBUIH9eVps5kM96did2+FFStWv6GuXb+Bx7ebzWVE2hZ3b+e2110DhJcvX4ZGo4FGowFBEODz+dBoNDAajQCAoKAgLF26lDreEjuxbt06lJWVYe/evXZjJ+6//37ExcWhrKwMW7ZsGXXsxGAFBATgxx9/ZAQXJEmiubnZ6eA2GjfQS5cuobu72241T6lUQi6XQywWU5U8e9W8wsLCUVXzysvLIZfLnf45ZGVlobS01KnXrK2tpeJCenk8gCBw8eFH8PTqcIwL5mP8xoHqYMCm+IHqYMhujNtgBsJxXD4Oz3geIAhc/93v8Oni9zE+mE+DQf9gPiYGx2PcRj4Cw3dQMDhuMx/+WweW3xY+/Dfy4beNT4fBzeYKol8oH49H7IZvPzz6bjeb1kwK3wXPbXHwjIqBd1R/FEV0P7DtjIWHVbuoXyyfZlQzeX+sDRB6HIim2lJ9dsfaAKHXnmj4hpkdVAcDoceeGBsg9D8cQwNCz6PRNCD02BmLwEN8eP+wHd47eHj72GFUVFSMCD+XLl1CdXU1srKyqPnSvLw81NbW4vLly8OeazAYkJubywi2RgORluxC61bX4aIt6urqcPnyZWi1WuTn5zMGwry8POj1ehYI3SsWCB1Q95Vf4LuRNZNhxepeVWRyGThcEssOq9y9ldtedw0QpqenW94IbS1btgwAsGzZMsyePdvmnMmTJ+PBBx+El5fXkMH0fn5+ePDBBxEQEDDqYPrBmj59Oo4cOcIILkQiERoaGpwOQjqdjnIDvXjxIjo6OpxSzSsuLoZYLEZHR4dTq3kVFRVIT093+ufgCrdVKj/SaMSNP/8ZIAhsm/M6AoPjze2hwWYgnLplFwWD49bzB2BwAx8BX/Mxfh0PP014EiAI/HLffXj33U8HYHATH+O5fHP7aTAf44J4GL89HgFb42kw6L+Zj3FB5td4YutuMwhu48M/xAyCftvMKzAkHuO3xcMv1Ayavlt48N3Cw6S4HfCO4iGAHw+PXXHw3WkGQq/oARj05MfZxFiMi+LZAOGEvTsoIPSN49GB8EQ4/CLN5jkeO+y0jO62BUKPQ/QKoecxeoXQY3csfCLj4HMmDD774hC4Kx5VVVUOQ1BLSwtEIhGam5tRXFyM1NRUJCQkQC6XQ6/Xo7293W4FbqRZO2dAZFdX14gB89bRFjKZDAkJCRCJREhPT3c42sKycnNzYTAYhj3mdjbucOtNzXligdABWcxkXtrJmsmwYnUvqrbjCjhcEh5BJBq6WXOZ4XTXAOGdpn/84x/YvXs3I7hISUlBXV0dYygZXM2rrKyEXq+nqnkpKSlISkqiOW0KhUJIpdIhq3ktLS0jVvPq6+sZtcU6uqqqquxGOdzqysnJgU6nczoQSiQS/PLZZwBBoPL/fxQzNu7AuOB+CNzU3y66aaBdNJAbT8Hg+HX9az0fE9bGIsVnAkAQuPLAg1iw/Cv4bzH/nILBfiAMWM3D2E1WMLjJalaxf41fw0NA8AAI+m3hY1LoDjMkbuIhMDQevpv58A3hwWdrHPxDefCP5cNjZxy8ogcAzSvGql00gg6EflF8+G7jweMIvV3UPzaeAkKvaB48T1hVB/dFUXOSnnw7baN7YszXGa5l9FgkPPYPAOH4fTvgE8nHxKM8eByKhFd8HM4zgLXB7p+WylxlZSVycnKQlJREVeCMRiOuXLkCrVYLtVrNCO70ej3y8vIYndPR0QGSJBlXFa3zMh2JtrCsrKysEWH6dv7y7e77mpPEAuEIunnzJv7WbybzvZI1k2HF6l7V4kO54HBJ8CQGd2/lthYLhG7S66+/joiICEZwkZqaSgtOH1zNs1TlRqrmpaWl0ap5SqUSUqkUjY2NTq3mNTY2QigUOh3cBhu1OGvl5uZCq9U69ZpGoxGZ336Lm/ffDxAEPlrwMQJW8zHpK/N6ct0uTPyCj4ANZhgcv45PaxUdv8YMg+PX8zF+LR9Tv4hG7hhfgCBw4Q+PYMG7q21h8GsexnP5mMDlY2wwD4Gb+AgIHgSDa3kYG2xeAVw+JobwMXazeTZxbBAPfht5GL+Rjwmh8fDdzIPvVh58Y/kYH8mHx644eEf1w9kuertoAG8HHQi38OC3jQ+vXdEUEI7dH2fjZjr++EAe4XhePAWEgfwd9o1lBkdPHLYFQr/9PAoIx+6Lh08kH74xfEw4YYbWt09+7zBANTQ0DOv+2dPTg8bGRmg0GkilUiQkJEAsFiMjIwOdnZ0OV+BKSkoYt3FaqpdMzunr64NKpUJpaanD0RaWlZ6ejrq6OhYI3SsWCEdQrpWZzOW+X929HVasWLlJiUVN4HBJTA+X4VfWXGZIsUDoJr333nvYsGGDDUAMV82zVO1kMpndap5cLqeqeTqdzuFqnsX8xdmA1dzcjKSkJKdf13ouz5lLqVSiuLjYqdesr69H2/TpAEEg02s8pn2xA5M/5WPm6l2Y9Bkfk1by8PgX8Zj0OR8TvjC3h9JaRdcPrMBVfASu4WPaF5EoeowDEAQuP/gQliz9vN+tdAAGLSvwKx4C1vIGYDCEj8D1A06mYzfwMH4dzwyjwXyM4/LgF8zD2A08jO3PRwwIjcfk6F3wijTnC3rsiKXcRb2jrLIH+XHw5NFD7seHxsNvGx9Td+yigHB8vG28xcTvzG2j4w/H0pxUfSJ4doHQ3CJqtY5GgXN0UIVwz8AcocfeWMooZ+Je84xjwK4dDoOa0WhEWlqaw7DV3d0NuVwOiUSCxMRESCQSyv3z6tWrQ55XVFQEjUbDCOzsVS8dWTk5OXaNdSy/dBkcbVFRUYHu7m7IZDI0NDQMe+3bWe6+rzlJLBCOoC9Omc1kgs6xZjKsWN3L6vv1OqZsSwGHSyJF3+ru7dy2YoHwN1Rrayvy8/NBkiT+/ve/44UXXsCbb75JORmOVM2TSCT4f+y9d1hUd97+fzZuNJt9Nsmz2d/us9n9ht01ibHTexEEBKRJL0Nn6L0NKBYstJlzZuhNRESNyT55AjiCIiIIIiDFRlVEQUSxhsRoit6/P44cGAeVMRhcM/d1fa6dOXPOmQ9zbRhfvN/v+25sbMTFixdx5coVjI6Ozkg1T8QJcwbXtWvXUFZWNuP3vXz58ktpRX0ZeYyje/YABIEf33gDtg6xkPWjIB9IQS6QwvJACrJ+JJYHUfTyp7AsgIJClADLY/lYHD0Bg8uCSSyJpJilEZiIlr/PBwgC3/32TYRZumLJEzC4NJTE4kgSi6JILAknsZBDQn79xKziomgSC2NpGJRbl4aFcSSWrOdjQTwNhAtjSPrYNgH+xSWhFxaHCJYDUlaZIMbJBhoJcZg/aX5wOZUuWh1MICfaURN4kCl63C6ayhcDQvk8Af65Zxs+JXkiQLggiT8lEH5aSIo7je54EghTReYIF6TQQLgwVYB/kiQ+EfBRfu7ctODp4sWLqK2tlQi4xrMu7927h6GhIbS3tzOA2NDQgN7eXty+fVvkmra2tuc6eD65BgcHceTIEYmB8NixY89t/RyPtujq6sKxY8dQVlaGsrIynDhx4qlw+/3338/2r9pnara/12ZIUiB8hm5NMpM5M3R3trcjlVRSzbISD3RBhiMEa3vTbG/lldVrB4SZmZmQkZHBvHnzoKysjObmpzsLubm5TWlEs2jRIuacoqIisdfnzZv3IluDlpYW/vSnP2HJkiX45z//CSUlJbi6uuLIkSPo6+tjqnm3bt2asprX2Ng44y2NLxOwbty4gdLS0mllAEqyhoaGUFlZOeP7bWlpQUdHx8++D5OnODSEe/M/AggCe5doQTmQrg4q+fPp6qAfSf9vEA2Jy8eXPwlZbxJLwsjHlUEa6MZhcGkoiWUhJBSDk1H7z0VMJEWumj6WRnOxiENBmZOOxVEkFkdTWBxNXyMbSWFZKImFcRSU4zPoltF4CsvjBFgQTwPgp3EkVDdk0FXDdSQWJXARvcYJp//+d+Z9Jq+vFOSwPDkBMpk8LE1NEwHCxfGT5hM3U5ifmYKFOeLtovNTKCxPE2BRcSo+2kqKVgi3kPjHFEC4dLto9MT8rBQsoLj4R+5EpfAfWaJOox+nTsRpLEimq4ROn302LXi6cOGCxJmCU7lx3r9/Hzdv3kR3dzfq6+tRVlaGw4cP49SpUxgeHkZzczPOTRNSfw6sPngwvdbPJ9e3336L8vJyNDU1MXD7ZLSFFAh/EUmB8BnKq7sAGY4Qpun1s70VqaSS6hXQ4K17+EesEDIcIfpHv5nt7bySeq2AcN++fZg7dy527NiBzs5OsNlsvPfee7h+/fqU59+9excjIyPMGhoawh//+Eds3LiROaeoqAjvvPOOyHnXrr1YyXmyFXtSUhJsbW0lAo2XUcEaG6Nn/SoqKmb8vrdu3WLy0WZ6vy9jNvHkyZNob29/JujdvHkTV69excDAAHp6epiZr6lmNk8HBNAxE/Pehr7bVsj6U5Bjk0yr6HJ/ujooO14pfAyE8t4kZP0pLPejX1saMgkGwyksCyKxNJx+LBvMRfGyFQygnfrrh3DwWseA4OJoCkuD6Urh4igKiyNILA0gsSSEhGK0AArRaVCMTcPSIB4Wh5N0VTGahNzaZCQar8Hwu//N3PvH37yBtr//C6VLFdHy4b/wkPgNQBDo///+BI31a/FPcpKhDJeHTzeJAuEnSVwsSJkaCBfy+JBLF4jA4PianyZuLPOvNNpYZkkehQUJPCxcR2HZegE+jaewYAOJT1K4+JgvWiH8Vypvom10C10l1MjKnVbb6IvEQTQ1NaG7u/u5gHX58mW0traisrISZWVlqK6uxvnz53H37t1pw2p9fb3EQDid1s+pKoZlZWW4ffv2lNEWG+RFcwAAIABJREFUBw8exJkzZ17o9+Mvpdn+XpshSYHwKfrp4SNoJB+BDEeIfS2XZ3s7Ukkl1Ssiz6IWyHCE2FR+bra38krqtQJCZWVlBAYGMs8fPnyIDz74AElJSdO6/quvvsJvfvMbXLo04UhWVFSEd999V9KtPFeZmZkwNjaWCFhaW1vR1tY24yD0smb97ty5g9LSUty6dWvG9ysUCmfsfl9//TVu3LiBxsZGNDQ0iERtNDQ04MiRI8w/1ktLSyEUClFVVYXa2lqcOHGCmdmcXOW9MzCAe394FyAIJKutgUpQGpb7kZD3p6FPNSSNaRWV856AQbnHMDi+5L1IyPk8rhCG0yA5DoNLQ0moh6ZjWQiFmFUsjM19i4mlKFLUgXrQFqhFZ2BxJEXDYBiJZcGPwTD88eNoCmrR6bSLaSgJ5dCt4OsY49bvfs+A4I3f/wF8bWOohW/GkvF5xHUU7F3CMfzOewBBoOcvf8WSxG0MEC7YwBOFwc0Ulibx8UmyOAzOT6HwcSKFRVPA4MdbKSwSiLeNLk8X4NNNPFFDnbhJs5HxFJZvTMP8ZN6kcPoJIPw4gcKCFArLyQzsaW57Lgj19PSgsbFRIng6fvz4lDN6z4Kturo6NDY2oq6uDmVlZYy5y9WrV8XMXX7O3h48eICDBw9iZGREomvu3buH0tJSjI2NTfnalStXRH5/vop6SV9XgQRBXCII4gFBEM0EQSg/5/x5BEFsIwjiMkEQ3z++1lOC95MC4VN0uPMaZDhCLE84hPs//DTb25FKKqleEdX2jkKGI8SSjQfxrdRoSkyvDRB+//33mDNnDr766iuR466urjA3N5/WPUxNTWFgYCByrKioCHPmzMGHH36Iv//97zA3N8e5cz//rwu7du2CpqamRODS0dGBlpaWGQe369evv5RZv/HA7Bs3bszofUdGRlBeXj6t9x8dHcXQ0BD6+/vR1dWFU6dOobm5GfX19aiurkZFRQVjzlNeXg6hUMiY83R0dKCzsxMXLlzA4OAgrl27Nu1q56CTG0AQuPDeX6Dty6Org4/BTzGIT1cIgyjI+UyqDPpTkPWdAEIVHz7k/CjI+VGQ96WgGZ4hAoPKQQIsC6GYtcoxHsdkPmVA7t5v5+KLZapwdgyGYjgJuUg+FkfRRjN0JZDC8gAeFsfw4GkbhN0Kmvhm7jzm+qF3/ohNRjbQGjedmWROo7Q2HQvXUtALXI/R3/8BIAj8W0mRAUL5hDQxIFwcTWJhovj84PwUCsqbM7FkA39KIJTlp4vA4OJ0AT3/uO6JuI21okD46Tp6lvKTJBIy2VwsyJhoGf1oK4Ul6yj8i0dCNzHnuVXCrq4uNDU1SQRP04lneHJNnusbG6MNlMbNXYRCIZqamsSiITo7OyXOO3zw4AEOHDiA0dFRia75+uuvUVpa+lQ4ffDgAX744Yef/fvxZeolfFXZEzTUeRAEsYggiHyCIO4QBPHnZ1xTRhBEE0EQ+gRB/IMgCDWCIDQkeE8pED5FrO1NkOEIkXiga7a3IpVUUr1CevjwEXRSa6RRNE/RawOEw8PDIAgCjY2NIsejo6OhrKw8revnzJmDzz//XOR4Y2MjiouL0dHRgdraWpiamuKdd97B0NCQJNsT01dffQVZWVmJQOjMmTM4ceLEjIPb+KzfTIbHj6+ysjJcv359Ru959epVlJaWYnBwEBcuXEBnZyc6OjrQ1NSEY8eO4fDhwyIurBUVFaiurkZ9fT3TdtvV1YX+/n4MDQ3h+vXruHv3Ljo6OnDy5Mmfvb/B2nr88MYcgCAQvMoHKt4UlN1IaLPToOTKgyKLC0UvEvJ+JNMqKhtAQTUgjYFBrcB0yPmSDBBq+qRBlk1C0ZuHZWEUlP0nQHBZMD2XuCyYbif1M2Oj+/0PRGb97rz1No7941PsldVCrpohMtUM8dlSDTT8YwG+nvc7kXP7/vRXxKxyxpKYVBoC19JAKB8rYIBwSTgPC9fSEMayC2LaR118ffAJl8KCBEoMCOWiBVjEIcVg8KOtJJZEUZDlTA2EctwJIFyYxscSDoUl0fR7TwZC2Q1pokAYT2FhzGMo3MjDgvQJIPw4iY71+CSJxJL1JLbt3Ie2tranGqWcO3dO4nzAuro6XLx4UaJramtrMTAwMGX18Pr16yLREEePHmWyDiXNO3zw4AHKy8tx69Ytia65ffs2ysrKnnnOrxAImwmCyJz0/A2CIIYJgoh9yvlGBEHcJQjijz/jPaVAOIUujH7DhFAP3pKGUEsllVSi2l5/ETIcIVbx617peKTZkBQIHysxMRHvv//+cw0RfvjhB8yfPx/x8fGSbE9M1dXV+OijjyQCja6uLjQ0NMw4tN2+ffultHaOjY1h//79GBkZmfY+rl27xsRtnDt3Du3t7Thx4gTq6upQVVUFoVDIgF5lZSWOHDmChoYGtLS04PTp0+ju7mZcWCXNVByvHv4sWB0aQc9faffPxg8+hZYLBVVnHlRZJJRdSCg78qDkSkLJlYS2pwCa3gKosimoeE+0iSqx6crhOAwqu5OQ86GYpcjiQiVgHAZJyHtyaRgMpiAXREE1KA3LA0l4rglA1ccKTCvps9bY3LdQukgRQeZsLIriQiFGgIVrKSwJ49Htl7F8BgaXRVIMDC5cS0E1Oh0l8loAQWDg/fehuoEvBoOLOHSrquLadPHq4MYM+rW49CmBcFlSGu0smk5h6WP31cXRFJbG8cUqhAvXiQLhougJ19UF60h8kjgBhYvj6LnDBVtI6GzNQXt7Ow4ePMjELEye43uRfMCamhqJTVuOHDmCwcHBaVXq+vv70dTUhPLycpSXl6OlpQUDAwMYGxNv53xyfffdd8wfgSTZ3+joKA4cOPDMc3788dVuxZnhr6m5BEH8RBCE5RPHiwm6CjiVsgmCqCYIIpmgwbGPIAgeQRC/k+B9pUA4hTaWnYMMRwivnS2zvRWppJLqFdTd737Ap/GVkOEI0dR/c7a380rptQHCn9My+ujRI3z00UcICwub1nvZ2NjAwcFBku2Jqbm5GX/+858lgo3e3l7U1dXNOLS9rNbOsbExCIVCZq7u0qVL6Ovrw9mzZ9HW1obGxkbU1tbi0KFD2L9/P0pLS5lA78lxG2fOnEFPTw8GBgYwPDzMVAhn2qzm9OnTaGpqeuHrb966jf9VNafzAX/7FmzM10HZiQcVBy6UXUioOHIZGFSbBIa6HmlQYvGg6MqFnDcJJd+JVlFFV94EDLJJKLrwIM+mIM+moODGhbz7BAwu9+FBzofHzCZqB6XTDqYBXHhahGCTri12yOvii0Ua+GKJGgpkVyJhpQ1c7SIgG8aFQiAPi2IoLA/g0jAYymPAalkYjwFC2TCSgcElUfR8omJoEm68/V8AQWDjKmsxIFSKEdDtqlEUPpo0R/hpIh9LHs84Loum8PEWcSBcuJWPBekklscJRMxyVOIzxNtGY0WBUGlDhkgUx6KYCSBU2JyORRwKKklZWBxLYVftSdy/fx83btxAZ2cnamtrUVZWhpqaGtTW1qKpqWnauYUPHryYaUtVVRWuXLki0TWtra1oaWnBmTNncOTIEZSVlaG2thadnZ0YHR2dcs/ffPMNSktL8e2330r0XlevXsXBgwelQDihDwj6C1TtieOpBF05nEoHCXrWUEjQs4YmBD1DWPSM95lH0F/S4+tvhBQIRfTNgx+xeMNByHCEONY3OtvbkUoqqV5RxX55BjIcIQL2tM32Vl4pvTZACNCmMkFBQczzhw8f4m9/+9tzTWWOHj0KgiBw9uzZ577HTz/9hAULFiA8PFzS7Ymoq6sLb7/9tkTA8bIC5MfG6NbOa9euTfv8Jx03e3t7RRw3x3MVJ8/nHTp0CEePHkVjYyNaW1tx9uxZ9Pb24tKlS7h69epT4zaeXOMVzdu3b8/oZ/BzWnJv376DFLsY/PQbunVyq5YrVJx4ULWjYVDLXQBll8eVQVf+RJXQlQ8lFxoOVVxI6HqmQcc3HXJ+FLR80ybBIAUddtoEDHpT0PQWQM6LgrZ/GuTduROZhgEktAInTGsU3GhoXB5EQT1YgGWhFBTZPCwNIyHry8XSCAqy/lwsino8ZxhHB9bLRtNQtTicSwPWegqLI3lYGDcBhGrhE5CWqGcJEASu/eEdLF2fPGEms57ConGX0ygKC+MmnEaXhPOY44ujKCzdJN42umgLH3KTKoPjSzVOHAiVN2RM2TLKZDNGUFi8jgbCTzfQx5bE0hVMrS3is4RjY2Po7+/HoUOHUFZWhsrKSrS2tmJwcPCZAfPjcDc8PCwRcL2I0cuT8RZ3797F+fPnceLECezfv5/Z8+XLlxkAHP8jkCSA++DBAwwNDaG6uloKhBN6ESCsIgjiPkEQ7046ZkUQxCPi6VXCTcQUEUlSIJzQrsYByHCE0OUdxcOH0lYwqaSSamp1Xf0aMhwh5scdwLWv78/2dl4ZvVZAuG/fPsybNw87d+5EV1cXfHx88N577zExEbGxsXBxcRG7jsViQUVFZcp7JiQk4NChQ+jv70dbWxscHBzw1ltvobOzU9LtiWhoaAgEQUhU5RoYGEBVVdVLAUKhUIirV68yjpvDw8O4ePEienp6RBw3a2pqRBw39+/fL+K42dbWJuK4WVlZyZhgzNRex91Lb968OaOfwdmzZ9HY2Cjxdbdu3cFmPy7G3qRn8Sr+oQQVJx60WXy6MsgioexEQ5+O+yQYnASJSs48aLlQdFupCwkV6xRoeQkgxyYhxyah5MRlYFDenZ5DlPemIO9NQckxFQruPKi4k9Bi87EikK4MLg+koOTFY1pJ5dlcLAulIO+ZiqVhJJRC+JCN4GN5GF0NXBhNYlkwXR1UieIzULU0mMtUB+VDJ2YHF0fysDhiIutQNjwVV39Pu44mrF7DAKFssCj0KcUJaGfRzSRTHWRWpGgw/cdb6JZUxXCBGBCqcMSBUGltuggQym9IFwFC1XWZWBZKYcnG8VZWeqmty8SyOAEyK6bOGhwPmb9y5Qo6OjqYDL7jx4+jr69vytbLyspKieHuRYxeTpw4gZ6enilf++677zA8PIxTp07h8OHDKCsrw7Fjx3Dq1CmUl5dLDIQDAwPPzTz86adX29lxhr+mXqRltJggiAtPHFtI0F/EHz/lGmmF8Bl69OgRVpK1kOEIUdRwcba3I5VUUr3issk5DhmOEFRV72xv5ZXRawWEAJCRkYEPP/wQc+fOhbKyMpqampjX3NzcoKOjI3L+3bt38bvf/Q75+flT3i8sLIy531/+8heYmJigvb39RbYm9r4EQWBoaGja4DE4OPjCgezjjptXrlxBf38/uru7RRw3y8rKRIxYhEIhDh8+zDhutre3o7OzE+fPn5fIcfPw4cO4ePHijILbuNPh6OjojN733LlzOH78uETXDF25jiCXVAz9/n2AIHD6fRnoOiRD25GEqi0X2i4U1B3oVlENNwrKzjQYqjrxoMJ6DIMsHrRZEzC4gsWnIZJFQtudj1U+mQwMqnrzoerFZ2BQzYkLBU8eFLxIKLnxoO5OQsGLhIJzCpTtU6DqzoO6LwVNXz6UgvjQ8KMgH0hCOYCColcq5DxTocBKhoJnKtS9eVANIKHiy4O8Rwpk2SlY7pNCB9ivp7B8LYWFsRPVQdUQ0aqdYhgf27StAILApT++j0838bB4AzURe/F4yUXRTqOq69JEYTCKgmKkaIVQMYpuh1UPTxMDQvkYgRgQyselTek0Or4WR5BYFkphaSgFucSJdtIlkRSWcwQw3rod96Zw0HyyCjceMN/V1cVERNTU1ODs2bO4fv067t+//0Jwt3//fty8eVOiaxoaGnD+/PlpnXv79m309vaitrYWpaWlOHToENrb26dV8Xzw4AHOnz//3MzDXxkQEgRdCcyY9PwNgiCuEE83lfEhCOI7giD+a9IxC4IgHhLTnyOUzhBOUsP5G5DhCLFofSXG7r/apkZSSSXV7Kv81DBkOEIobKmSxtM81msHhP8p+umnn0AQBLq7u6cNH8PDw2L5e3fu3MH169cxNDQ0peNmdXW1COgdOHBAxHGzo6MDXV1dqKioQGdnJ+O4OVOQdeTIEVy4cGFGwW1s7OW4l0pq2nOucwC+tokY/K8/AQSBkbf/CCuTjdAyTYG2JRcallzoreFCw4qLFdY8aJglQ9uexEp3AVZ4p9OzhO4UbKMLGRh031ACVVcKyiwSmu58uK7dBRVnEmsiC+CdtBeGkbkMDHps20PDnxcJk8gcrAhMh4IXCQ0fPnT80iDvTUHVi4KKBz13qOyQAjk2CXlPEopuXLot1Yt2OFXzpSDr/zgWg5VCR2EEUNDwF0AliA+5gFTI+qRMzA5yaHOZyYCmESCAil8S7j52LQ1wcIfykxXAx2v5Jj4WR4gfV4iaCKeXWyfA0iAaCBX9SDEgXBxNG8OIOI2uFYg5jS6ZZCyzmENhaQjFQKFiHF1BXBrLh0IIH8uj+eD9u0YMcp4XMj82NoaLFy+iqakJQqGQqaL39vZOe07v/v37zGysJED4Im6m47OAQ0NDaG9vZyqeDQ0N6O3txe3bt6e8rru7GydOnJACoajsCXom0I2gK315BB078ZfHrycRBLFr0vn/RRDEEEEQ/ybomAptgjaWKZDgPaVAOEkejwOn15c+f+xDKqmkkuqHnx5CNbEaMhwhPj85ONvbeSUkBcJZ1O9///unxhxM5bjZ3NyM0tJS1NXV4fDhw4zj5vhs02THzVOnTknkuFldXT3jlbyxsTHU1tair69vxu9bXl4+bffS6a7u7m7U19dP69z/+6oZwQYxGHn7v2kY/N1/w0E/DnqWXOhY0DCoY5ZCw6ANF6bumdCw4sLUMxNrfHNhxs4Ge+Me+G75jIFBj427GRhc4Z0O++hCqDiTUHEmYRuRDx0PAVay02EXmwcbTjYDg6YRmVDz5UPBi4RBaAZWhmZB3puCcVQu9MKyIM+m4LKtBAq+fKgFpME4Og9yfhRMwrMhG0BBwZ+C4uM8RFUPLpOLqOPDn8hI9ORCw5+et1u4loJ6sCiYKYdSWPYY3goUVgIEgZMf/hNLwnhTAqFmiGDK44sj6ciKRRtJyD+O1BhveZ0KCBWiRYFw0RROo/IxApEqoWJEGpaF0lAo609hGYdPt5OGp0M9NhNaUVnouXxVBHIaGxuf2pb55Bpv0xyvwI2DVl9f3zNh71mh789aNTU1uHz5skTXPDkLOF7x7OnpYToGDh8+jI6ODly5coXJHTx37txzIy4ePnw4279an6mX9HUVREyEzDcTBKEy6bWdBEHUPnH+pwRBHCboSuEQQRAkIXUZfSGdvz7GRE1cvPHtbG9HKqmk+g9Rbu0FyHCEMKSkERSAFAh/UT169Ah37txBV1cXjhw5gr///e/w8vJCWFgY47hZVVX1VMfNcSDs7u5mHDdv3rw5I/N5NTU1OH/+/IyD27Fjx9DT0zPj9xUKhRgeHp7Re/b09DzXxfXOnTvYsH4fKCUWvpszFyAIXHn7fTgarIW2aQr0rEloWHLhFroDGlZcmLhlwMSVDw0rLsy9smHOzoa6NRe6jhQcg/OhbsOFbXAuPOIKoe72GAa9+DD2TWdg0C4iF+ouFFScSazwEMA2ooA+zilEQPLnMAzPgYIXCZt1RdAJoWHQen0RtEPoVlPXxD1Q8OVD2V8A283FkPOjYLelGApBfMgGUnBIKsHyQApqYQJoRWVheSAFrYhMKAULGCBc4SeAnB8FdX8+ZGMoyEU8UR30m4C3lR4bmRxGe+dQMehTCqag6Tt15XBxFAVZDgmlSTA4vhQixOcIVSP44m2ja0XbRtXWZYoAoVpUBgOEqhHpkPWjK4ey4XzI+lHQ5GTBIr4Q9+5NtI5K0pY5DoWlpaX4+uuvcevWLXR3d+PYsWMoKytDdXU1zpw5g5GREZEZvrGxsRdy/jx8+LDEzqTPmwX89ttvcfnyZbS2tqKyspKJ4qivr39uHuOvFAh/aUmB8LFivzwNGY4Q3sUnZ3srUkkl1X+Q7n73AxatpyMo6nqlzsSvJRBmZmZCRkYG8+bNg7KyMpqbm5967rjD6JNrZGRE5LwvvvgCCxYswLx587BkyRIcOHBA4n1dv34dBEHg7bffxvz58/Huu+9CQ0MDbDYbZ86cea7j5riZysvIC6yrq0Nvb++M37ehoQFdXV0zft+KigpcuXJlRu85Plv11M+o9gzC12xF418WM/l9rX/6GNbmW2DskAZLz2xoWnLhGUnDoBFLADOPdBoMXQUwdOFD3ZoLPUcS5l7pULfmQt2aC9ewfPp81zSw44vhMKkyyN60h3lsFpwHi5B85rnXht30YxaJgMTP4bV1L1gJJXDZuhvqgemQZ1NwS9oDeV8KCn4UnLaV0JXBtfnQiMiEbAAFN95eBvpM12Uzjx2SdjGPnZN3MzEYcn4U2NQ+KK/LYKDMYEOuGLzt/1QRIAgc+FROrAKo4cuHPJvCsilaRhdHUdD2F4fBZcEUNELEgVArKl0MCBWjRCuEKutEoyeUoycqhMtCacdWjbAMyMbS0KsQSEHRj0J4+lcM5Bw7dgz9/f3TBq5vv/0WpaWl+Oabb0SOf/PNNxgYGEBzczMOHDiAiooKtLS04NKlS7h58+YLOX++iDPphQsXnjsLOLl6eOPGDaa1vLS0FNXV1Th9+jSuXr3KVA/H16v+l9bZ/E6bQUmBEMCNbx7g43UVkOEI0Xzx1mxvRyqppPoP06ZyOrvUpfDpnPBr0WsHhPv27cPcuXOxY8cOdHZ2gs1m47333sP169enPH8cCHt7ezEyMsKsyX/lPn78OObMmYPU1FR0dXUhPj4eb7755rRiKibr0aNHuHv3LvMPJjk5OezZs2fawPKyzFTGxsZQX1//UsCtsbER586dm/H7VlZWYnBwcEbv2dfXh6NHj4p95pcvX8E2Nh9l/9TCD7+hK18/vjEHXyqYws0jDa7eGbBlCWDtzIerTyacfLLgHpwLz7ACGLmkwcRVACM3GgBXe2bCyi8X6tZcaNnywOaUQMOKnjN0DduBVax0aFrz4MEpRmjiF0xl0DGmCPrsTLpK6JkGy6DMSdC4F6os+rHnht1Qc6Wwgp2OwOTP4bZ5NzwT9yCI/DdsE3bCLH47jNflQzaAgtXmIsgH022hDonFDAA6JZcwj9UjMqAblc3AoH50DjQC0uGYXMJAmU1SsRi8rQ/eBhAEfnjjDej4bWJgz5m/h4nSWJO4QwwGjdfnwSAkfUog1IvIEK8QRk4YyyxZS0E9Kg0rQ9KhGSKAWhgfyhEUlCMpLJkUPyEXIxABQs2gDHreMiwNqiFpkPOjoOJHt9furaLbI2trazEwMDBt4Br/b/VJWHqyinj16lWcPn2acQAtLS1FT0/PU2f4plovYl7T09ODxsZGia558OABmpubcfbsWQwMDKClpQUVFRUQCoVoampi3ISlQPiLSAqEAKiqXshwhDDPqH/l/38nlVRSvXq6fPMe/hkrhAxHiJ6RsdnezqzqtQNCZWVlBAYGMs8fPnyIDz744KlZhONAeOfOnafe087ODqtXrxY5pqKiAl9f3xfZIiNtbW3k5uZKBC379++f8dm5cXA7e/bsjN+3qakJp0+fnvH7Hjp0CJcvX37h65/MURz/B/KBAwfQ0NCAI0eOYP9+IaIDMpC12BI//uYNpip45v35WG+xFobGKXD1zIGJBQljCxKeftuhsyoZzl65MLdLh45RCtx8C2DuSMEnqhi+nF2w8qVhcKUTH27hRQwM+nBKoGNLPm4zzYRzSCHTchq69XM4RO+AijOJ1QE5sAqjW0bVXSh4jlcJnUl4J+yB8mN30vHHKi4k3DfuhrILCR3vNFjHFELNk4Lz+mK4b9sNt5Q9sN+2C6rh6VgeSEEzMhPaMROVQreUvSLVQaeEXYypjYtgLyxTdoqBm9nGQiixKXT85R8AQSBTfRUWR1HQ2JANjZAMBggdkneJwODKLfnQDsqAMpuCYphA/L5bd4gBoeaGbJhvLYBBJH2dgheJlX4ZzHzl+NLwJKEeQEE26jEUhkwCwpAM5mfSCc6EnB8FJT8+tP3SYRCajZ5LVyWe0xuv5ktS7RscHER5eTkzwzdehRsZGXkmWJaXl+PWrVsSgV1nZ+dzWz+nWsePH0dvb69I9fD69es4d+4cjh49irKyMjx48OBn/V582Zrt77UZ0q8eCO//8BPkNldBhiNE+anh2d6OVFJJ9R8qv5JWyHCEiP73qdneyqzqtQLC77//HnPmzMFXX30lctzV1RXm5uZTXjMOhDIyMvif//kf6Ovro6GhQeSc//f//h/4fL7IsQ0bNmDZsmWSblFEq1evBo/HkwhkXkar5MsEt5aWFnR0dMz4fQ8fPoyBgYEpQe/WrVsYGRnBpUuX0NvbizNnzqC1tRXHjx9HTU0NDh48yFRjhEIhqqqqUFdXh9raWlRUVKCttQNpSf8LP5ds+LJysM18PUAQOP/XTxAr74ng4CLo6ichMGQnVhqnwtoxAw5uOdBZlQx2UBEMzUnoGKXAP6wYeqZcaBunwDOgEKusKBhY8hAUuweh6z6Drj0FTSsu/OJ2M2DoEFQAM88saFhxoW3Dg2/sxGt+a3cjYONe2EUWYoUHxUCiugsFjw27GQD03EjDoKoLCbf1JVB2IaHlKYBd7A4ouZLQ9c2ARUQBlFxJaHoJYBW1HaYRubBalwt33mcMDFps2gEFfz4Dg85bdzPgJO9NQcmHghu5VwTalgeTsF5XCAUvEnErWABBYPT3f8Dy8FQ4JO9iYFDOh4J6cDpkObS5jFxsGiziCxmAM1sv3oYqG8qHfNxE/IQjfw/0Q7NhHpMnAn/KbApaAekixywj8qDoQULRg4SmHwV1P5IBQsXQiRgPVbYAOgHpjx1YBdDxy4BNZAEqKmlHzumC082bN1FeXi4RbF27dg2VlZV48IBuOb106RJaWlpw4MABHDjLmkIZAAAgAElEQVRwAC0tLRgYGBBpQx13Jp0qB/FZ68yZM2hra5MYCOvq6p7ZOvvNN9+88pWa2f5emyH96oFwT9NlyHCEUE86gh9/erXnVqWSSqpXV62XbkGGI8THayswOvZq/0HzZeq1AsLh4WEQBIHGxkaR49HR0VBWVp7ymp6eHuTm5jLA4OHhgd/+9rdoa2tjznnzzTexd+9ekeuysrLw5z//WdItisjR0RGbNm2SuDJ26dKlGQeskydPor29fcbv29raira2thm51+3btzEyMsIE3jc1NaGtrQ2NjY04evQo4+hYWlqK8vJyHDp0CLW1tThx4gTa2tpw7tw5nD9/HpcvX54yR/HEsTZsiStAXHAxwtiF8HfPR4hfESxX87DJfitWm6QiILAIFpYUQiNKYLCaCxevfJjbCqCzKhmB4buwwjgFK4xTEBC+C9rGKdA2ToGTZzpWmKRC2zgFHgGFMLEVQNs4BWucMhEatxfuoTugZc0FO2YXdO0psSqhhhUXvrEl0LblQcOKC1u/PJh7CuAZVwzPdSXwfAyD6m58uMbvevyYoh+7kFB358Np3U465sKDD/u4Ijr/0JWEy/pdzGPriGys9MuEa/IeyAfzYbG+kIFBzdAM6IVliwChx+bdMI/Kh3zoRDWPlVjCQJiKewpu/O4PAEEgyc5bBAbHlxW3mG4lTd0tAnDW6/OmbBu15BVDd3MenLaVQNGdhKI7CdaGIrGKoHPCLpHnrlt2M0Co6EHCLCgDZpF5kA/lY1koBRX2xM+l4yGAtn86NAPSoe5CQc8nHVZBmei/eGna4DQ6OooDBw5IBFvDw8OoqqoSO37//n2MjIzgzJkzqK6uZsLle3p6MDo6OuWs4vNWR0cHTp06JTEQTqdS+qprtr/XZki/aiB8+PARdHlHIcMRouBY/2xvRyqppPoPl2VWA2Q4QpCHemZ7K7OmXz0QTiVtbW2wWCzm+csCQh8fH0RFRUkERdXV1ejv759xcGtvb0dra+tLue/TojXG1507d3Dt2jUMDg4yERvt7e04ceKEmPNqeXk5Dh48iP3796OmpgZtbW04e/Ys+vr6cOnSJYyMjOD27dvTdl7t7OjHFzuOInXdF4jwyoenLYVwn0KEsQsRHViM6OBd8HTMRoBnAewtBLAz58PTJQcrtbYiyH8HTE24cHHORnhYCYKDi+EfVISgCBoG9S14YIcUMWAYELGLAUNn7zxYOWdC2zgFuqapCI7eDf/IXXAKLIBz8HaYetAxFbr2FLxjdjFg6B2zC3oOtGuplU8OrHxyoWHFhVPIdgQlfAb3+BKYBueCta4Yyi4k1NwosOKLoeRKQtmVhOuGEgYAvTbvYR5bRuRD7XHkhTKLREDSZ9CLnJgddH2iOrg6Kh+angIou5BwS9mDZcEUNKOzsCJItF0zT86QbrP92/wpgdA2sQhWidvFgE4vJGNKIAzK/hIaPgIGBhXdSVjF5Itd75X0mchz3eBMKHlOAKFuQBqUWSRWBWXDKXU37DfvnABCTwrKTjxo+wqg7SGAlqsAGs4knMO249btryWu9k13DQ4OikRBPG2Nh8s3NDQwle6Ojo4pDV6etk6ePIlz585JDIRVVVXPdDT9/vvvf9bvxF9Cs/29NkP6VQNhddc1yHCEWLLhoDSIXiqppPrZEp6+ChmOEMsTDuHbBz/O9nZmRa8VEL5Iy+hUioqKgqqqKvP8ZbWMRkVFwdfXVyLAOnr06EvJ9Tt16hSam5tn9J53795Fa2sr6uvrceHCBXR2dqKjowNNTU1PzVIcj9hobW19pvPqi34Od27fRdPRs9iVXomkyN2IZW/HWr9CRHtvR5RXPpxMkhDmtR02BqkIYRfCWCcRob47YKC5FYHs7TBblQpzEy58vbdDT2cbXJyy4WCXAb0ViXB3y4WtTRr0dBPBZhcgNGwXfAOLYGLNg1fQDgYM/cN3YaU5D9rGKbBiZcHZO3/itYhdsHHNRkBUCdzDi2AfQDuQalpzRdpHrdnp0HcSQMOKizWTwNCQlQbnsEJY+OWAvX43ghP3QccnHUquJDw37WYA0G3jRGVQ3z8Thv5ZDAxah+dC1ZkHI/8smMcXwnpjERQmVdCU2HzYxuxg8hO1vATQX5cH160lYmC2ymEDfnyDnr+0t4oUA0LTqEyo+lJi1yl4kTBcn8+AoFJ4Gly37IYTZ6cIDCq6k1D1oqDqI3qPNXGFYvezjisUqRJaRxcyP7PPts+wMiwH8t4UtIIyoO5CQsWJB31P2tRHh0VC04mErV8uLg8938BleHgYhw4dkgi2Ll26hKNHj0p0zY0bN1BaWoqTJ0+KGLyMZ4o+7bqmpiZ0d3dLDISVlZW4du2aFAhnX79aIHz06BGss49DhiPEtgNds70dqaSS6jXQTw8fQSe15lfddfBaASFAm8oEBQUxzx8+fIi//e1vTzWVmUr6+vpYs2YN89zOzg6mpqYi56ipqf1sU5mEhAQ4OTlJBDTHjh1Dd3f3jAPh2bNn0djYOG3QGx0dxZUrV9Df34+uri50dHSgubkZx44dw+HDh3HgwAGUlpYyVb0jR46goaEBJ0+exOnTp9HT0/OzshTr6uqmnW84cuU6Dv27ETmbv0RCwA7Es7djrVcBotzyEOGaB1+bdAQ4ZcPLJg02hsnwZeXCwZwPN/sMuNplwkw/BYE+hViptRVebrmwtuRDT2cbggKLYKifjJW6iQgO2gn9lUnQ001EUOBOGK1KhZ5uItzdcmBhwYW7ey6CwooRGr2bgT+fkJ1YZUVB2zgFq20FItDoE0q/ZsXKRDBnD0Li90JrUvuopjX92CVsBwxZaXTOoWcW1vjmQN2aixUOFFwjdkDdmgtNWx5CEj6Dx/oS6LDTYcsphJoHH0quJFTdKdhzihgwMgnMxgoPAVSceFBx4mGllwAum4pFqoOs+AkYHF820VlTQp19bAGqPpQFCAJffqoiAoMG4dkw8EyHeWT2lNe68ej5RL21ubCKoaM41FworPDLEINCqyfmCBW9SawIFq1WeiV9JgKE7G2fMT+3qgsFm+ACuG6mK6FuG3dDxYkHTVc+XCLpWc1VziR0HLgwZQlQfqDhmcD1ZPD7dFZ/fz/q6uokBkKhUIgHD+jW0mvXruHs2bM4cuQIysrKUFdXh+7ubty8eVPE4Ob48ePo6+uTGAj379+PmzdvSoFw9vWrBcKm/pvMvM+1r+/P9nakkkqq10SfNdNzycrbDuPBjz/N9nZ+cb12QLhv3z7MmzcPO3fuRFdXF3x8fPDee+/h2rVrAIDY2Fi4uLgw5/P5fJSWluL8+fM4e/YsQkND8cYbb6C6upo55/jx4/jtb38LHo+H7u5ubNy48YViJ54URVEwNzeXCISOHz/+UmIcurq6UF9fjxs3bmB4eBgXL15Ed3c3Tp06hZaWFtTX16O6uprJISstLUVFRQWqq6uZsOpTp06hu7sbFy9exPDwMG7cuIFz587h+PHjM77f+vr6Z4JxZ9t5fJF7CFTMXqxzywHHNQfRrBxEOGWD45aHSJdcxHpvR5RHPmK8tiOUlQsfmzS4WqRijc42hHoUwFhlMwJccmFvTMLemIdI/yL4OOcgIqAIMWEl8PbIh5NDBjw986GnmwhzMxK+voXQ002E/sokEUh0d8+FrV0GdPWS4OGZj6jYz2DNyoK2cQrc/bfD3CGdaTP1C9vJgKG7/3aY2adB2zgF1i5ZCIndDfeQHdC24cIxIAtaNvRcoX1gPozdM6BuzYUBKw1OoduZnEO/tROVRcfg7fDdsBemoXlQciXhsbGEgSINdz7MArMZGFR15MHKPwPajiRWhdJOnEZhWVBzo0Rg0MA3E8aemXDaWCwCYGZR+dD1SIOPfiBAELj/2zeh47oFcj4UNIIyYB1aAFUHHjw27p4SCK3iC2C5eQcM/LMYJ1UVZxLuG0vEgNBhrXjbqctm0fs6biwWrRDGTlQIlVkkfDbthboND54b98Bj217mc/DduBcOAVkwC8qFuVsGrLwysNqeQiQnm/nDxJMxEZcvX0ZNTY1EsNXX14eGhgaJrnlWa+qdO3fQ19eH48ePo7y8HFVVVejo6MDw8DBqa2tx8eJFid5r3MDmzp07Tz3nhx9e/fa92f5emyH9aoHQpbAZMhwh4v7vzGxvRSqppHqN9ODHn6CyrRoyHCH2Nl+e7e384nrtgBAAMjIy8OGHH2Lu3LlQVlZGU1MT85qbmxt0dHSY5ykpKZg/fz7eeust/PGPf8SKFStQU1Mjds8vvvgCn3zyCebOnYvFixe/UDD9kyooKICenp5EIPQibqDjEQvDw8NMxMLp06dx8uRJJmJhvHWztLQUBw4cwOHDh3Hs2DE0Nzejo6MDXV1d6O/vx5UrVzA6Ooq7d+9O6727u7tRX18/40DY0NCAzs5O5vn1qzdQu78F2xP/D+vdcxDvloNohwzEe+Yj0iEDHNdcBFrwEeGYDS8THsKcssHST0Gocw6stbYhzD0Pxsqb4LaGC5uVKXA05sGflQsDpQT4sXJhb8KDgWoCQrwLYb4yBfpqWxDMph87WAgQE1aC8OBiWK8RwME+HW6uudDTTYShQTJYLAH0ViZDVy8Jbu65sLOnwdDAMAVh4bsQELIT1s6ZcPDIga1rNrSNU7BidQr8w4uZmUMnzzxYu9AAqWfGhX9EMdwCC+AcmAs73wzo2JNQt+bCxD0DtgH5DAx6Re9kYNDCKxMGTnxorBmvLmZjhZeAASK7iFwGglScePCMLYaaLQ9qtjwYuKfDJDIHRgEZIjCo5kbBKaIIarY8rAnOZ6If1P0ENPA58qDqwEXvex8ABAG+iikUfSm4xBZD1YEHVQcedFz50PRPFwM6u5hcaLtTIjCo4kzCJixHDAhXh+eIXe+ZuFfkuaqvAOpsgQgUGgVmT7TKRhZC3YYHdRseTNk5cOPshIoTDys80rDSngfPyJ0I2LgXJqx0+MfugZt/AXz8csBP3Ysv//1/qK6uxpkzZ3Dt2jX09/ejtrZWIuDq6enBiRMnJLrmaUY0T65vv/0Wg4ODaG1tRWVlJUpLS1FbW8vMI0/nvb799tvnGthIgfAX068SCE8P3YEMR4h/xR3A5Zv3Zns7Ukkl1Wum7fUXIcMRQju15lfnXvxaAuF/ivbt2wdlZWWJQKi1tZVxAx2PWLh69epTIxYqKytFIhYOHz6Muro6NDU1oaOjA52dnbhw4QJOnz6NI0eOiDlv/tzV29uLurq6lwKEB/73CHZyy7DZKw/RNgJErCERbZeOcGs+OM5ZCLdJQ5xrLiLtMxHnnodol1xwPPIR45aLGI98RLrlguNdgCiPfER70TOEbhYpiPbdAQ+rdDiuJhHglgcDlQSwLAXwcsqGvtoWOK1Jg5dTDvTVtsDKiIcAzwLoq2+BgcYWhPgUwsUmHcG+hfD3KYAzKxu6eknQ10+Cj08+A4YsVg6cnLKgq5cEvZVJCAreCVe3XASGFsOVXQAX34IJM5pI0ZlDJ69c5jWvoALomnFh750JR/9MrHYX0DBoxYW9fyYDg+aeGTB0EtAwuIYLr6id0FrDhaGTAOwNe+CTsFcEBj3W7oK6HY8BQjVbHoI27MVK30wRILQNyhI5x3MLDWFeG3bTMPh4bVW2AwgCI79/D95rixgYHF+2saLGMNYRWVC35sIuJFsMCLXdBVDxpESAUMmDhF6IaNuq7bodMIvJh1lMAUyj82EanQ/3zaJuo15b9opUCW2CChgoDFi3F36c3VjhLoBtUCY0LblwDNwOS7csGNjzERi9G/5RJQgJL0F87F6kp3yJz3dXYP/+/RAKhaisrMTQ0BDu3bs3LeB6kWzAwcFBHDlyROJK38GDB9HS0oKamhqUlZWhtrYWXV1duHHjxlOzE+/evYvS0tJnGtdIgfAX068SCH130XlhYfs6ZnsrUkkl1Wuoe9//CNmEQ5DhCFHacWW2t/OLSgqEs6iKigosXLhwSuCZHLHQ19eHs2fPoq2tDVVVVaioqMDBgweZiIX9+/ejqqqKiVhob29nIhYGBwenjFh4cvX396O6unrGwe38+fOoqamZkXt1tZ/HF1kHscUrF/4Gm+FnsAWhplyEW1IIMklFhBUf/sYpiLBOA9sgBWHWafA2TEGgBR/+ZhTc9ZIRap+JNYobEe6cA1vNrfBYzUOAbQaMlscj0CETVpqbYaa8CWFueTBX2wKnVVxE+RQixCMPQR75iPAvgrFOIvTVtiDQqwDmBinQV98CN7sMuNplQF99C0x0ExHiU4hVWttgYZCKiKCd8PfJg4FhMvRWJsHDMxv6+jQYOjhkwd09D7p6SdDVS4KffyFMVvPg6JQJtn8+vALyGPizd0uHgQWda7jSLBWOnpnMayzvXKxaQ2GlBRfuwQXwiihgYNDSOxNGrHQGBn1iSqC9hgdNSy40LbnwidoFj6id0PNKh4oTD9ahBdBlCURAz3/tHmhacuEWtROqrnTLqGd8icg5arY86LpQYMVtF4FBVUcetOySceMtOoJik4qjGBDaRNBAqMKm4B6/i6lwukYWiQGhijMJ89BMsSphQPLn8NqyFx7xJbD0zYHGGi6s2bnMz62xhgtfzm4YOQtgG5wNn4S9CEn5N7Q808TaRtVteDByz4SeFQ+WrlmwCciAvgMfmpZc+HN2wzdiFxz98hEQvgvha/ciOvYzrI3bh42cfUiO/zcyUr7AF599xTjinjhx4rnVuPE/5kgCdwMDAxJXIh88oM1hRkZGGNA7f/48GhsbmbiW9vZ2XLlyRQT+ppOt+OOPr74722x/r82QfnVA2HdtDDIcIWQ4QvReG5vt7UgllVSvqdKr+yDDEcKQqsPDh692ru5MSgqEv7Du37+PCxcu4NixY9i4cSMWLlwIFouF1NRU1NbW4tChQ2IRC0ePHkVjYyPa2tpw7NgxHD16FJcvX2YiFmYCti5duoRDhw7NOBD+HNDsOdWP/8urwlavXERZ8MCxphBilIQ4OwH89BMQvDoRHPt0RFrxsdY5ExFWfMSxshDlkAGOUxY4ztmIcc5GjEsOYt3zEO6QiWjXPITYZ8LHgo9wVg6Mlq2Dv20GXI15MJLdADfzFFhpb8Mq+Q0Ids2FtW4iDOU3IMA5B45GXBgqbATbNhOhnvkI9doOT4cshPrtgKHmVuirb4G/Rz7szPjQV98Cc4MUhPjugKHWNuhrbIWnczZ8PXPh6pwBA8MksFgC6BvQYGiyOhX2DnwGDJ1ZGTAzJ+lqoksWQiOKYfo4v9DOLQd2bjmTKoglWLGabi01seHDw68QOkYpcGbnwzdqJwydJyqDLsH50JoEg+zIXdCx4ELLLBVrPLPB4uyEmU+OCOSxOSXM+ZqWXLhyCmEalAVtR0oMCK3Y6XAIyhQDQlVHHv5X2wYgCPS991eo2nNFodCRB4vY7WDF7GRgUN2aC00bHoz8ssSA0HvTHii6k1D35sMmIhumHmlw9MsWgT+NNVz4xe0Web7SgQ8dKy40LVKhaZEKHSsebDxywI4tgdu6EpiF5EHdlsdAoV/sbmiZpULLLBUR6/fBxDmdBmP/QviFFiMkdg+sHDIQydmLwKBiRISXIJ7zGaICCxDimYnMpDIcKm/G6dNnmGrceIbgk3OHp06dQkdHh0Rgd+HCBdTX10sMhEKhEDdu3BA7fu/ePQwNDaGtrU0EZi9cuIArV66goqJCCoSvhn51QBi+rwMyHCF8dp2c7a1IJZVUr7Hu3vsBizcchAxHiMOd12Z7O7+YXlsgzMzMhIyMDObNmwdlZWU0Nzc/9dwvv/wS+vr6+NOf/oQ//OEPUFVVxcGDB0XOKSoqGv+gmDVv3jyJ95WXl4c333wTMjIyWLZsGT744APY29sjLy+PiVgYGRkRiViYvDo7O1+KScvQ0BAqKytn/L4DAwOoqqp67nlff/01zjb34IuMCiS4ZoKzhoc4GwqRZqmIs+MjypKHODsBQkySEWuXBm+9BPjob0GoOQ+uapsQbsWHi0YC/IxSEGROwUYuHmHWaXDV2QaW1haE2qbDYnk8fEx4CLDkw2hhHAKt0uBtwgNLNwkcrwJEuubCzyYNnpZc2Btug6H8BriakfC2SYehwkbY6icj1D0fRkqbsEpxE0I9CmCzMgWWOokI8cxDmE8+LPSToa++Be6OaTA3SIa+xlaY6G6Dix0FA82t0NfYCntLEi52afBkZcKVlQ4WSwAj4xTo6iXByDgVgUE7GTB0cs6GCysberqJMNBPRgxnL4LCdkHPjAt9cx58w4oZMLRzy4GtSzZ0jFKgY5QCr4AdMLakYO+RC8+InXAPK4T2mgmwYwXkYsVjGNQyS4WRLR+OXtmwCZgAQiufDGhbcUWAcJUTH64RBWIw6BhSCANbCrpWPJgH5ojAoGNQDkyMN+HenLkAQSBEhy0ChGa+OQjdsE8EBseX7/o9YkDoxCkCe8NuGDjyGbjTXsOFvgMpAoBGLL4YJDr55zDXaFqkwj+mBNqmqdA2TYWRvQBRGz+HnX8+1G14sAnIn/h87AWwdc5CYFQJHPzyoWuSCkuHdASE7YKeUQqiYj6Dk3M2IkNLEOCdhwCPLKwLK8H6kBJsi/4M/y6uw+WLw+jt7UV9fT3KysqYucPr16+jtbUVp0+flgjsent70djYKHHLaFlZmRiQTnXe6OgoOjs7cfToUeaPVJ2dnRgdHZ2ytfSnn159Z7bZ/VabMf2qgPDyzXv4V9wByHCEODV4Z7a3I5VUUr3mSqrohgxHCIvMBjx69OuoEr6WQLhv3z7MnTsXO3bsQGdnJ9hsNt577z1cv359yvNDQ0ORkpKClpYW9PX1IS4uDm+++Sba29uZc4qKivDOO+9gZGSEWePOpZLohx9+wMOH9KBqf38/5syZI1HkQk9Pz0uZyRseHoZQKJzx+16+fBkHDx4UO35j9CZOVLVjZ+KXWGdDIc6aRIwlF5w1PESZpyJkVSKiLLhwV1qHkFVJCDFOhovCWoSYpCDQMAkOy2PAXpkAL50t8NBKQKSNAN4rtiLaPh0RtmkItxEgyjELsa458DXhIdg6Hd4mPJgsikOofSbcDVJhvHgtQu2z4GbIxapFa+FvnQ5vcwqrlqyFy6oU+Nny4WGRAjfzZLDtKKxW2wxDhY1gmXFhtyoZhoqbsFo9AR7WPBirJsBQcROcV3Ph55QJf9cc2JqSCPDKxxpjHvQ1tsJUPwWhfkVMxdBxTRp83fNhZpAKf68CeHvmwNyCS88V6iXCz287VhmmQE83EaareQgIKIKebuLjOItcREbthu1joxmvwB0wtuIzMBgQtgu6xinQWZUMnVXJ8PLLh7NXNszc6AqXnXcGdCxSGdgxsOFhjZOAMa1xCi3AGt9cGDgIRGDQhJUBe48crLZPg7HnxPygbWABjBwE0DJPhZZ5KryiixkY9ObsgrYFffzzf2kCBIGWv3zMwKBjWCFMHdNh5pQBbTueGBBa+eYwILjCUwCnUBpkrT3SRMBO0yIVLsF5YgBo5Z0p8tw9YqfINRZumdAxS2Wg0CNoB3RWJcPddzt8InfBLaSQ+ZwCo3djhWEyWB55CIvdC51VyTC1FiA0pBjOrjkICtyJ8JBd8PHIRiA7FzFBxYgP34P1oSVYF1iMDcHFKCArcL5rEN988w0GBgbQ1NQEoVCI8vJy1NTUYGhoaNoB811dXWhubpYICL/77juUlpZibGx6ZjKTq5EHDx7EiRMnsH//fhw8eBBtbW0ic5JSIPzF9KsCwqgvTkGGIwRre9PzT5ZKKqmk+pkaHXuABfEVkOEIUdMzNTu8bnotgVBZWRmBgYHM84cPH+KDDz6QKItw0aJFSEhIYJ4XFRXh3XfffdEtTanR0VEQBIHr169PG7BmciZv8rp27RrKy8tn/L7jbWZ9Z/pxoLgGgtAdiDJJRKwlF5EmSYi15MJXcwP8V2xCqFEi3BTj4KUWjzCTZHhrbISn6npEWfIQoL8NkZY8RFtT4NgKEGCUCB/DLXDRiIfVkhgEmaXCRSMBDgrrEWGbDifVBNgprEeEfQYcVRNgLRuPSMdMsFelIthKgCiXLIQ5ZsBRZxs8TVPBMkzCqiVrYae9GW6rk2C0bB1M5OLhZZEKS7UErFoWD9fVyfCySoWHJQ8W2lsR7JYHaz0aDG0NUhDiUQAjZRoMvWwywLbLhKd1BsJ9diDEZwdsTCnoa2yFkU4iwvyLYKybBH2NrbA04iGYXQh99S2wWU0iNGAHfLxyGPhzdkqH1Ro+8zwgYAeMjeicw5V6iQgK2g4nt8zHMJgMZ88MBgRXrEqGq1cWVhgmY4VhMlaapCI4phgrrUgGcowdBLByTmcqjdrGKbBzzUJg7G4RGDR2ToeDZy60TVKgbZIC95AdULfjwdI3F6asDAYGx5dzdBG8Y0voltTHx2z04/Djb+igerZ+EOz8MqFnwWVgzMk/e8oqoXlAFliRBTC0pZhzvUJ3iAGho3++GBC6hxeKPNey4mE1K13kOs+QIua+2qapcPLIZT5Dd598sNzTYOacAT0rElZOGVhhmAwjMx7Cw0rAcs+FG7sARvrJCA0uhodLLqzNeGC7ZoFlk44I3yKEeG1HpHchon0KwWFvR6x3Icj4f6P9RB8DaXV1daitrRVp1XxewPzZs2clnjscGxtDaWnptM1uxtfFixeZnMTvvvsO/z97Zx7fVJkvbu5vZu6MztXRGcddKrLvpbTQFrq3ycnevU2bZmnSdEmztmnSfd/3QssOOqPOdmemYhEQWRQGERdQUHFfEBVRQFxnRn1+f1SCserVGe9Fsc/n8340yTmnb05oT57zXd6jR4/yyCOP+Oa7d+9e3nzzzW/1b+T/Buf7uvYt8YMRwudPvOuLDj780snzPZ1xxhnnB0LzpicI8IygWLb7BxElvOCE8O9//zs/+tGP+Otf/+r3vFarRalUfq1jfPzxx9xwww0sW7bM99yGDRv40YjceZAAACAASURBVI9+xMSJE7n++utRKpUcPnz4X5mijw8++IAJEyb4mk18nfH888+zbdu2b13cTpw4wfDw8DdeIP6LxtHnj7Hrr3tZU/M7SqXNGEJcuOWtlEpbKJG0kD3bSVFkLXZRM4aF5WgXeLALzRTHN1Ic34g3pYey5G5KFB3kRdbhUnZiCK0mK7Acl6qLvOgmUmd5cKq6Mcc1kzzTjVncgCGmFrO4iWJlB860XlIWVJK9pJ48SSvymR6SAiswiJtInF+BZLoHo9BCVkQDqvmVFKf24shehlnVS3J4PQ7NCtKjWhDPq0In7aZYPYQwvwrx/CrykntIj2kiS9xCfkY/jtxVKJY2IwquQy10Y9WtRhxShyi4jtyUZZgzBkclMW057uJbMGlWEL+kifgljVjN60kUdRAf3og4ogmree1o05rwRnQZAxSZVyIWja5lKIhbyVKfE0O5tJ1sdT+x0S3ERrdg0A9hdWzwiYxI2YXZssEng9GiNqyO3xAnasOQvxZlznLk2QNk6Ff4yWBqzjIkyk5iJe1k5q9gaWInQlY/atMqnwyeHdaq35GkHxwjgxHKDvJd64lO6hzz/B0Bi2DCBB67foafhEXKO0jWDoyRwVznzTg8t43ZNlY1VuyWqjpIL/CPEoqz+4lK7fJ7LrNgud8+RufNfsc2Wtf5zmOUuI3MrF5ECW0UWjZQWvF73/k05q8jPrqFwvz1lJbeRlxkM0nyboqMQyTJOim13IIzfwPuolsoMa/HU3AzbtM6yoxrKTOuwa1bTZP9Vu7f+bhvsfizqZqHDh36X6k7PHXqFMPDw1/aTfTLxtk1Db8otfTEiRM88cQTnD59+t/6m/h/wfm+rn1L/GCE0PFp7aB+/ZeXfYwzzjjjfNu8+c6HzKzeTIBnhLt/ALWEF5wQHjt2jAkTJrB3716/591uN4sWLfpax2hvb+fyyy/3SzHdu3cvt9xyCwcOHGDXrl3I5XIuvfRSjh49+q9ME4BPPvmEH//4xxw8ePDfTsH8d8dbb73F8PDwVzapOX36NKdPn+bUqVOcOnWKkydPcvSFV7h34/1saPojNend5AaWUiJupETSRJm8lYLwStJusqAPLsEcXo5mtgvtPDdlynacQgulinbs4mbciZ0URNWTPtWFTdSCQ9JG+owSTOE1lCg7yYuowyq04kzswJnYjm5JNfqIGoyx9SimukgNLMMQW0vyvDLkU13oY2rJDq8mNbAcR2oPrvQ+LKpuNJFNuDIHyQhtQJjmoVDVS2FiH8IML8nBtZRkr0Ad0YRZ3oMndw3l5nVIF1QjnleFVT2ETtqNeF4V8uBabNmDJIU3IJ5XhUZoxapdjlbZgyi4jkyhC9tnxFCr7CU/c1QMhcX1WPRDWHKHEEWMNqPJSOwkRTrasTQ+vBFNSg8p0lFRlMe1YS9ch1az3CeD6oxeFLJOnwzm6leRmtxHbFQzJuNqTAXr0BhWnYsMStqx2G4hJr7VN7T6VVhLb/WTQX3BWiSqbt9+CfJO0ozLSMruGyODydn9JKZ0k6QbGCN9OaZBohPa0BWtGhs5lFbxz//3I5gwgeKwgrFSaByVQklOH7kFa3zROGl635hti8puHSOEhV7/RjIq3SD2ytsx2TeQZ99Anm0dRa71aPOGyDQMkKjpRabuRkg7F6mMVnYgT+n2CWF6znJiY1t8UVmH/RaKLRsQK7qw2n5DXGQzCdEteEtuI0+3imRlNynidux563Dmb0AZ1Uppwc3oVb3YdaspMaym1LAGj3EtFeZ1eHSrKdUPsOm/7/tCgfuqusPHHnvsG4ndiRMnuPPOO7/RPmfTU/ft2/eV25xNh/8uc76va98SPwghfOb4GSZ5RzuLPnb0u3+zYZxxxrmwaNs8Wkso9N13wXccHRfCz3Hbbbdx8cUXs23btq/c7h//+AeTJ0+mqqrqX5mmj1/+8pfs2bPnG6Vgbtq06VuVwdOnT3Py5EmGh4c5fvw4J0+e5OTJk7z11lu8+eabvvH80y+y8y97WF/3e6pTu9DOcKCfU0KZrIUScRNuaQvZM+yYQ7w44hooWlpN2o0WCpdUUSJtpii6mtxQN1lznRRE11AQUUvyjVaMoZVYExrRh5SjC/FikzRSJKrDFFlF+pwSDEsryA72IL2uGG1oBebYOpJnlJA6241D1UmxtA2Hqgu7qht3xgCqmWWkzPVSIG0jPaQSYVIJ+uhGrKoeFDM86CObqTSsxqtbhTamBXVEM66sIRIX1CDM8FKg7MWSMoBkVjmS2eWUaFZSolmBTT1IWlQLTu0qX/QwObwRe85KlIvrEc+vRhVWhymlE1NKNymxzagim9Ald/nEMDG6mdzUXt/jLGknrvw1aJL7iA9vJEncSfGn6aPx4Y0kijpG00nDGhEtacJiWkeZ81biYlo+lcFmdDn9xMe0EBvVTGxUM2bjGpLl3ViLNiBL7EGW1IPRvNZPBo2mtSjl3cTHtVH0aWOa3MI1xEs7/CKKiqRuMjJ6UGT0+MlgmqYPibyDmPhWUtQDxKV2E6HsIDqxkyL7LUQntBGd0IYssQdp1jlhTM9dgVozxB3XLYYJEzjwy0lEytr9o3P2DZgdGxDJOv3mkm9bP0YIU3RDRHxGBsUZvZhtazEVrEadvQxB0kFMbCtp6T1+7z8mvhWt9pxgx8a0kGsYJEnVSXZWL7mmIewltyBRnZPCQsu5Gs4s9XJEMS0oxB3Yim9GlzVEXGQzcqGT7KQ+MpVdWM2rUUQ3Iwqtx2v9DXb9Ggo1KynMGKLMvJ6ijEEKUpbhNqwhV9JFnrIDW3o/zY7f8vDfjnyhcL3zzjs8//zzfnWHO3fu/EZ1h6+//jqbN2/+xkL4ddJTx4Xw/4wfhBAW3/4IAZ4RTLeMdxYdZ5xx/u85+e7ffR1HNx969XxP53+VC04I/52U0d/97ndcdNFFjIyMfK2flZqaSmZm5r8yTR8BAQHfKOL32muvfaNav89G9T4rep+XvRMnTjAyMsLOnTs5fPhxHr3/MFtu28GaqlvxSJvJvLGQ7CnF2CKrKRU34haasEXVoJ/rwh5Thz2mDt2cElInFlIqNOOWtuCWt2AM9qAPdFMYWU1uiAflNWbUM+3khnvQhZRiCCtDt9iNOaoKbbAH2TWF6BdXYEloJCfIi3JiMU5FO6WqLtxJPVglbZQkdVMQ14LkBhu5EQ24knpQL6hEdqODYmkndmU3NkU3pWkDlGYsQxvRgDCphLTgSkxCM4lzyxEml1Io68Ka1EdWeAPOjGW4NSsoTulHmFmOMrAah3oQdWQzwsxyEhfWUJTSS1pYPXpxKyZVB6akThSLahHPr0a5uA5TcjfykDrfY4OyHY3Qijm9j9S4NpymtSiWNI02owlrxGlciyqiBVFwHeJFdXgtt+DMX484spn48EaKjWtJFrqID2skPqyRvOwVZKv6SAhtwJyzkkLTWoyGVT4RjI9pRpfdR3xkE3ERo8OkW4WteIOfCOXmDhEX2+KLLsZGt2A0DRAntPkJWFbOcpTybmKjW0hJ6UOROUCktB1j4VoShHa/Y+ZZRzuMGgvW+WTw7Ch0/oYIZQdm+81IFV3ExLeSvtTD3/9jNEroXpTrEzyteQ05mhVk61b4zSVa1IZE1Um0smOMFGaZBsjW95Oe3jP6vmJaMBiGfJ1azw597mp/ITSs8hNCsaidlKRe3/lMiG1BJWsnI7mH/LxV2B2/QSHr8m1vK77Zd54NmiH0aQPY89dj0q9CGtlMQmgD+ZqVOI1rycscxGlahzKsEadhLZbMQWTBtXjy1lGqXUmpbhU6cTPWtAHcOSvRRrdQZVrLEwdf+FL5ev/999m1a9cX1h2+8847X7rfsWPHuPvuu7+xEB44cOB/TE/9PtRZnO/r2rfEBS+ER147w42fRgcfP3bhvs9xxhnnu0331iM/iHUJLzghhNGmMsXFxb7HH3/8Mdddd91XNpW5/fbb+dnPfsbw8PDX+hkfffQR06dPx+l0/qvTBGD27Nn86U9/+sa1fqdOnRqTvvlFovf58dZbb/nE8OTJkxx9/hX+NvIAv+v8C8td67DFVCG/TEtagBlTUAmWJRUULiqnJL4eS3gl9uhabFE1GOaWoLzCiG6uC2tsNYUR5eQv9ZIyqZCc+Q70wSVkzbIhu8JIzjwXlthqLDHVFEZVo5lXSnFcA0VRdSROtJA6xYo+tAxjeAXmiBrciZ2UqDpxSNtRTLSiWVCBS9GJObIeyTVF5IbVUpbSi0PRiVPZhUXSjjOpl9Q5XmSTnBTLOrHKOpHf5EI1rZSSlD4cSb24UvvRxzRhkrSQtqgKYYqb5KAqihK7SAuuRpjiJjW4mnxlKyZZC2lhtSQtqsEkb0MZWIUws5y0sHosqX2oFlQjnV2BNWMZ5XnrUMe3I55fTWJYIy7dapLCGhHPq0IaVENecg8pEQ0YlB3oE7uxaFaQKXQhCh6NEhaoh9CpehEtrEW0sBZz+iDe4t+QJO4kPqwRZXw7trx1iMIaSAhtICG0HptpLcqYVkxZg2Sl9ZOa1IM6tdcnKHFLG9Fm9CD+NCVVm9mLTNGBQT/oJ4LihDYs5nXERTRRZF5HnKSdaFEbRcUbECe0+22bo12JzfVbYhNax0TbVImd6AwDY2QwOmE0XbXUc/uYff4wMQImTOCF/7oSSVInJvMqX+QzO6t/jBBGi9rIyRv8tH6wgyxtH5npveRk+0f6YmNaSE8bIC6+zU8I88zrxswhL2+N337Flpt9Qhgb1YzZtPrcOY1oIlczQE5yH7b8deQb15Ce1Od7rSB3JQmL6xGHNWDI6MGsXkZiXBtFutGlSrKELjwFN5Or6h8VQ+0qbFlDlOevJyuqleRFNbiyB3FlDuJIX4YrYzm25H6W1/2Fl5577QsFbM+ePTzzzDN+dYfbt2//yrrDl19+mR07dnxjIXzwwQc5dOjQuBB+N7jghbDgtw8R4Bmh8NaHzvdUxhlnnB8wp9/7B3NqR6OEdxw8dr6n87/GBSmEv//97/npT3/KzTffzBNPPIHZbOayyy7zLRPh9XrJycnxbX/bbbfx4x//mMHBQb9lJT7bIKG+vp6tW7fy3HPP8fDDD5OZmcnPfvYzHn/88X/j9ENoaCjr16//WlG9N998k9dff53h4WEee+wxXn/9dT/ROztOnjzpE8XTp09z5swZ3njtBI/seozhFZtZZltHubyFclkLxnku8he6cUTVUBxeQc7UYjRTLFijKjCGuDAEOciYXID0FzlkTMpHF2jDEOTAuMiFNtCOenox5lAPeYs9ZNxkQXWVCXtcPaWSFryqDgyBZejmlOJIaMIW00D6ZBspAcW45e24Fe14EjvRBXkxR9RQEFNL+kwHwq/No6mj4mbyI+pwytpxyTvwpPaiCapAcq2F/OhGXKpuMueXI7mumGKhDXdaH6WpvRgi6jHFNFIkbUM5vRThRgf6qDpy4+qRTXGhmllKnrQBs7yJpPnlCFPcaKLqMIpbkE4vQ5jixihqx5rchz6mlRL1IEVJfTjUQ8jmViLMLCc7ugVn1hCqBTUIM8vJWNJEed46nDkrkS6oRhpUgyNnJRkxrYjnVSGeV0Veci9ZCa2kRjZgTOkmR9lFQdaQTwSToltw5K5Bsrge0cJaZGENOPNWo03u+1QEG0iTtKNWdpCwuN43cjN6Mar7UQrtxEU0oZJ2Yswe8qWdxoc3kiptJzdzAJ3mnBBmpi0jJ3O5n/DkGVZht//GTwRjo1uQCp1Y8tZRkLuGuM8JYWHBeuTiDpRCB4qkbj8ZTEnvIzu9n4yUXuJE/vvJo2o49ZOfw4QJrJydOOZn5ujHRgkLLOux2m5GLun0E7fM9O4xUlhUtGFMlFCjXeE3B4Nxtd8+ooQ20lP7/Y6tyxr0nR9RdDPJQpvv88hUdKBRdaBP7yFV0UlOaq/vc7EaViMJrqMgfTmewg2kxbUiCqrBoVtNZnQLzpyVeExrUYbUkhRajzmpA3v6AF7DGowJ7aQurMGVsRxP9iDOlH42dG3izeOn/ATs3nvv5fnnn/8f6w63b9/OoUOHOH78OM8995yvW+g3Gfv27ePJJ58cF8LvBhe0EB54+RQBnhFu9I7w1Otnzvd0xhlnnB84/fc8TYBnhKiOHfzjo+9+acS/wgUphADLli1j4sSJ/Od//ieLFi1i375z6xfpdDqioqJ8j6OiosYsOj9hwgR0Op1vG4fD4TveVVddhVQq9Vun8F8lMDAQu93OiRMnvjKq91nRO3LkCNu3b2fjxo3cf//9vPjii5w5c4b33nuP9957jzNvn2HbbbsYcq3HK2kke1IhmsmFOGOrsYR7KAzzoJ1pRXGZFtUVOvTzrBhDHJgWOciaXojkvzSoJxdiWlhCXogb3Vw7xmAX2bMsGBY4KQwvJ3deKfLLDBjmleBVtOGWtlAibibxGjN5wV6cCU1YImtJnWjBML+MiqROPKoOrHENSK/Iw7SoEpekjYKltcivLiA3pIKKlG68KT2YllSjmliMbrGX3CUVJE+xI7/OQmFMAw5pG1ZxMwXxDRiW1pIf30DKzBKEa4tRB3kwRFWTPKsU1VQnBZJGLIpWdJG1CAEOMhZWYkvsJmtRDcKNTlLnV+BK7cci76RI0UFaSBX6hEY0kQ0IU9xIprmxJvZRKO9GmOImJ7KZct0qvPrVSOdUIMwsH60/zF6BKqjGl2rq1q3CrVuNTtKFeF4VRenLMap6fWKYGdOKObkb+cIadPI2MkTN5KZ2o1ja4JPDDKEVtaQNUVANQnAt+ZkDFOeuRLK00SccupQBctOWkxBST0JIPcqoVjy235Is6fKJYEJ4AzbzOqQRoymM4vAG9Fl9GLSDyEXtfjKYquwhL2clxqwVyCTnGtbkZA2SlTLwaWfUJqwF64mJbyVe3IbZuMrvGOrUHmISWolOaEOT3Ys4pvlcdE0/6Cdj6RkD3BqWDRMm8PaPL0K1pMpPCA36c01xco1ryM9dQ8LSJqwFG/yELTaqGZ1m6AuihP3ExvkLYWHRBuISWlGoekhL70eTvZyCvFVoMgdQp/eRntKDybAMhdBOfPTosdNSuon9TBquTr3MJ4QJoQ3oU89Fe7Nk3ZTmrcOmW0WquAO7YTWiwBpEgTXYNCvRCh04clbgzV+PbEE14jkV2LOGKFT1kStvpUy/ClVgFbJZ5Xi1q3CmDuBWD+LJHiJxVhnpQVX8YcU23jnzLh9++CE7duzgpZde+kpJ+3zd4cjICFu2bPlGdYdno5FPP/30V27zfeC8XtS+PS5YIfzkk09IX7mXAM8Irj8cPN/TGWecccbhnQ//ycLGuwnwjHDL3hfO93T+V7hghfD7QlxcHBdddBHTpk2jvr6ep556yhfVe+edd3jnnXd8ovf58frrr/PQQw8xMjLCpk2b2LNnD4888ggPPvggO7fvYnXrBqqym8iamo9wUSbpASb0c62YgpzkBjooDPOgvqkQ43wn1qUVoxHCaVYMsx24xU04omtxxtRhCnSjuEyPelIRBaEezGFuTKElaGbZSAsowhJRgzO+AWOQh8Sr8nAmNOKWteJVdaCbW4rkMgOmhV5comaKImrRzHJRImmlRNaGW9WBZq4b8a/y0C/0YolvQL+onKSbrJijqzFHV2GMrERxgwXptYXkLPJgjKwieaoD4apCCuMbcCjbsMvbkU9yoF5QiSuxh9wl9QjXWUmaXopD1Y1N3klJSh+mmGaKpJ1Yld3Ip5Yi3OgkN7oZV0o/yXPL0Uc2UqTsIE/aTMrC0bRS2QwPtuR+8oQOhCluhCluStWDVOSuIWNJI8LMclIX1eNQD5KyuB5hZjnCzHJM8g7yFB3kKjqQLKgmaUk9enkrksAqxHMrEc+rxJTYRVpUIxqhlWxpK8kxzZgzBhAvrEEUNDqsmpWoRZ1IFtZh169GLe/BYVqHENrok8EMSRdFmpWIFtZiTBkgJ2WAdEUPZs0KP3lRxbVRkLMCQ3qfn6zlG1ahSujw1SvmpA4gEzow6YcQolp8Mnh26HP6SU/q8pPBs8NWvIF84+oxz4uim0lK7iJe3EaheQ2S6FZE4fU8f/FVMGECm64O9hPC+JgWykpuRa8e8vvZydJupOL2MVJozlvrJ4QScRuGnL5RAVb3k53UjSq+lQxZu985yVR0Igpt8Im2KLQeQ9oAokX1JMa2kaPqp9z6G+zGtTjy1lFkWE1J4QYkS5s+lexG9Ml9PinMlLQhCx6tJdVKuvEWbMCWtYKMuHZsOSsRz61APKcCc2IfRUl9uLKH8OSuIXlRFcIML7niTuwpAzhSByjXr8Ii7yZlXiX6yGacSX0UCR1U61aya+NDbNu2jVdeeeVrS93777/Pww8/zNatW311h/v27fsf6w4//PBDdu3a9YXRyLPj73//+/n+c/q1ON/XtW+JC1YItz/5OgGeEaZW3sUrp94/39MZZ5xxxgHgN/e/SIBnhKCGu3nnw3+e7+l864wL4XeA999/n9tvv524uDh+8pOfIJfLufXWW9m3bx9//vOfefzxx3niiSd45JFHuP/++9m1axdbt25l48aNDA8Pc+edd7J582Y2bdrE8PAwmzdvZt++fTz77LO8+uqrvPXWWzy293HW1/yOCkUrjshq8oPcJF9pRPELLfbIGsqEBrzSZoxzS5BeoiXzRguWsEpcsfXYo2ooiW9AM9VKQYgXZ2w9BYvLSb7WTMoNZszhbooiK7FG15I6sQjFFSbyQytwxjdQEFZJ4ZIqiqNrMIdXUBBRRfZsJ8JluaTeZEG/yP1pcxkP2hA3OUFuzFHVZM93I1yRR9o0B8XxTVjiG7HEN2AIq0ATXEZeTA3ps0oRripEs6Acl7ITc1QDloQWXKoubPJOrNJOFDe5EK63YYpqwpXYQ8b8ctQLKnGnD+DOWIYxthnhRieSm1xY5KOiKJsyKooWeQfWpE4yw6t9EcN8WTv62GafGGaG12KWt6JLaESY5UU6uxyjvB11ZKNPDLOimrGlD+DMGkQd04IwrxJb1hA5oo5RMZxbSVpEE/bsQbRCO3plB6IF1WRL29Ere3wRJnFgNbacVWil3TgNa5AtbUK8uAGH8dNmNZ9GF8UhtThz11BiXv+ZusMGCnJWkpLQ4ZNItbyLNGUn2vQenwieHcq4VvKzB1DEtfnJWMLSJux561BGtlCoHyt91rx1JCd0YNau/EJZtBetI03R5XdM21wzH0/4D5gwAdd8IwlxrVjz15Ot6kOt7EUS0zpGSIvy1owRwuyMHrLTu9GmdZMmaSMhtJ5kURvC0kY/AdQk9fg9TghtwJ63zi8NV5vUjxB2TriVkS1kCp2+c6xa2oxW2kWO0EVx1grc5vWjn42iB/GiOkxpfYjnVyOeX40suBajogvxnAoyo1soy12NLWMZubJOdJJ2UkPrEGZ4SVxYhSNjGbaUfkqzh3BnDZEeXINsehklGcvJXlxDkbQTT+ZySlP7sUg6sCa2sHfnI98o9fPw4cM8+OCDfPDBBxw/fvxr1R1++OGHbN++nZdffnlcCL8bXJBC+NHHn5DQs4sAzwgtdz1xvqczzjjjjOPjHx99TEznTgI8I3RvPXK+p/OtMy6E3yHsdjvTp0/noosuYsKECfzoRz/iV7/6FWvWrGHv3r08/PDDHD58mGeeeYajR4/yxhtv8Pbbb/tFDU+dOsWTTz7JPffcw5133sn+/fs5evQo7777rm+bo88dY2Tt3bTk9KO8XIduuhXr0irskdWYg9xYwipG/3+hB0dMLcVLqsieXIzk5xrsUTV4pC14ZS3o57gQ/ktL2sRCDEEudEEONHNs5C4qIWumlZxAB/pgFxlTixFfqidtkgVLTDXFsTVYYmuRXWVGO8+NXdRMUVQdquuKUF1XiCepC29SFw6hFeGKfFKnunAIbdhELSRPsiO7pgir0ERBXA3a0HKEq4tQ3WTHJmnDJmlDNcmB5BoLJcouyjMGsEo6EK63oZjswqbooljSgexGJ8L1NgriWyhN78Mi60C40YFsiou8hCb00fVIJjlHU0sXeDBLGjEKjchmjNYYGuKbMIpakUwdFcPUhTV4NCsoy1lJ5tImhJnl5Mm6saYuQzKrHGGGF9mcCpyZg5Rkr8Ck7EU8t5KUpU04c1aiDK5FPGc0cqQTd+LIHiIvuRdRYDWiwBq08k50si6fZIjnV+PUrsKTv94nKaKFtegTe8kWOnwSmSVpJ1PeTk5ip09uzo7c1F5yFF3oUvv9ZFCb0oViaSOi4Dp0SX0kijqJX9JEdvIAxvRB3/7yiBb06tH6uqyUAczZK3xClZzQQaqyxyeCmvRl5GevJCGkHod5/RjBu+Pq0WUojl/ya7JELX6ylpvVP2Z7IaoFlayTVFU3+dohdMn9iBY1UKxf7Sd2CYtHf97nBVCb2jUmcpoq7vTfL2+d3/kyq4cQBZ8714akfmTBtb7PozBtOcL8KmRB1WiFDpy6IfKTu9FK2kiPaSQjuuHcZyxtQZjhRTLDiya6EWtqN5bEbooSeylRD/puONiS+9GE1ZMvaqc0Yxke9TKs8i4KRO2UpPQiXG9FOtFGm2UDx148/rWE8NFHH+WRR8ZK5FfVHX7wwQds3bqVY8eOjQvhd4MLUgj/sP9lAjwjzKvbyun3/nG+pzPOOOOM48ddj71KgGeEGVWbOf72B+d7Ot8q40L4HWLz5s1s3LiRhx9+mFdffZUtW7agVqv56U9/yuLFi31Nb74shfTz47XXXuPhhx9m06ZNbN26lUOHDvHmm2/6bXPyxEm2/2E3HbmDeCRNWMIqyAwoRPyzLLKnFmOPqcYSWUF+aBmyS7Uofqkje6YF/QI7mtlW9Auc5AaVkD3LijnMQ25wKUnXmRH9PIeceQ6c4ga8qnZ0c0sRX2pAO7cUZ0IT1ph61NMcWCLrKJW0UiprpyiqHuW1hUiuyMMcXo1T0kZBRB1OSSsFUfUUxzXhkLSRObMU4Yp8MmeWXBFdVAAAIABJREFUYhM3Y46uxRhVSeZ8NznB5dhl7WiDKxGuLkI+0Up+TANFoiaKhCYyg8pJnuXGGFtL5kIvwvU2hOttZC+uJF/cRJG0hezQamRTSiiSdZAvbvOJYebCKkrTB7AmdpG9tA5hipvsiDoKlV0oZnkRpriRTi8bjfCoBylQ9CDM8JIUVIMra4jMJU0IM7wIM7xkLm3Cq1+NLWPQTwStGYMIsysQzxodjuwVuHQr/EQwM74ZraTNF13MFjeTKbSgV3X6RFAUWIMQVIslazkZMS0Ua1aeiwxKuynKXuFLSZWFNlBsWE2mspd89ZAv9fHsUEvbKdSvQBreNEYqM6XdlFhuRrq0aYyIGTMHSZZ3YTOtRby4wbePeHEDmpQ+n9xJopvJVzVx4j8vhQkT+OvVi/1kTVjSRFbSue2zkvpxmtZS8jlhSwipRxXdRqrYv+mOZGkT2co+v2MmizpQxPiLp1mzjMTYVlIS2kmXdJKj6iUvY5AMoZPkuHaUES3Y9Kv8BNyc0e/32eiV7b7PRTy3EnNily9SnBpaT0FiJ7lCCwZJM5a0bjLD6hGme0gMrMai6kWYXIowuRR7ch+FknZsiT241ctxJPVgjG4mLbCSktR+FDeN3tBQh5TjTOymWGjHndLHrb2bOH3y7a8UwkceeYRHH330a9cdns1A2LhxI0899dSX1h3+4x/fjy/w5/u69i1xwQnh+3//iMXN9xDgGWH1vc+d7+mMM84444zhk08+IXFwDwGeEcr/8tj5ns63yrgQfg84efIkg4ODBAUFcfHFF6PRaLj77rv9on5fNc5+udu9ezfDw8Ns376dhx56iMOHD/vSUHfu3Mldm+5iqHUNVTnNZE4uQPYLLZoZVvJCSjEtLEUz3YplSQXmYC/FEdU4YusxBZYh+4WepKvyKJO2UCYdXaRedbUZ4VId6hlW9MEucoPd5C0qx5HQiCmkHKeomeKoOlImWhBfakA33403sROPqhNzWDXCL/MwLKwYbTwTUYvsqnxSJtnwpnRTltSFaUktkqsKkF5bRO6SKvJjakmd7iRtppPcyEr0SyrQhZejCLAiXF1E8jQn+XH15C6pQbuoEpusndzIelyJPeQsqvGJYX5sC87EHsxxLbiSe0lbUIFV2U2xvAvp5BKEG50kzfbgTOmjWNFFkaIDxSwPifPLyZe1kR5S4/tSr1naSJlmBaVZQ8jmVCDM8GJIaMeetgzZrHKEaR6EaR6KU/twapb7iaA6ugltQpNPJrQJzehl7RhVnYjnnRMO5aJarJnLSA5rwKlbhRBUiyiwBot6CI2409fIRjyvCoduNS7TWuRhDT4ZFAXVoAhvwKVfTYlx7RgZLMwaQh3fhjqhFfnSRj/5KtauQp3QiUbSRWJs6+ckrAFjWg/G1O4x0pYQUk9KQjupsm6KtCtIjGxGtLCWiimjDWaYMIHK6dl+spavGcRuXIMhqd9v7sW6VWOObdGNjRIWaleSreilULMCh2ENDv1qvIU3Y1T1oY5vR7m4HvH8anKkrX7nLCvhMzWfcyuRLqgiW9RMUlgd6thmdJJ2nNpBitMGsGcN4shegce4BqO8m/TIZqSBVVjTl5+TwsX15IraEaaWIUwtQxvTSOI8L5mhNZgl7XhyRjuKFsm6sCX2ooto8KU0O5N7kd3oJGm6G3NMM+XqZegjq3AldlORtRyr0EZeVAMWURtbbt/zpeK2f/9+Hn/88W9Ud/jKK68wPDzMXXfd9aV1h+NC+H/KBSeEy3c8Q4BnhPDW7Xzwj4/O93TGGWeccb6Q/S+8RYBnhJvKN/HM8QunC/K4EH7POHDgAFarlV/+8pdMnjyZuro6nnrqKZ555hn27dvHiy++yFNPPcVjjz3Ggw8+yO7du7nnnnt89YV33HEHIyMjbNy4kTvuuINt27bx0EMP8eyzz/LKK69w4sQJX8fSJx58ivW1v8cjbcYZU0dBiJekK00IF2vID/FQLm/FK2/FGOhGuDiH5GsLKAqvwhnfQGF4JS5RE7lBZejnl5AfXk7OPAeKK02I/0tLcVQtHmUHHmU7aTdaEV9qIGu6A1tcA0XRdWgDyyiKqUUf4sG0pILc8HJUEy2If5VH4iQLuUu8mCIryYusQn5dEanTnRTFN2COrEV+vQXhygL0YRXkxVZjjq1Bcq0F4eoitMGVuJRd5IbVIr3WQkFsEyVJPZSm9pG1sMonhnkxTTgTRxe8t8m7KBQ6yBe14UjqRTWjbPRL+iQnRdJO7Ik9OJJ6UYfVIkwuRRtThz6uCcmUUTEUppRSKO+gOKUL5fyKT0WwjJyYejTR9T45yI5owJLSg1nR7RMIYWY52rg2HBmDyOdW4sgcJG1pE8pFdVjVy1GG1PgijOI5FTiyB3HnrvGTGiGwCodmBZnRLeiETjSyLkRBNYgX1uDQriI9+pwEObSrEBbVo1X2UZC23C/6lS1uRxHRRIaknUxRi180Ui1uRbKkAXFYPebMAZIjm8911/yctKWLOnEa1mDPWTXaPOczEbc/XzmaOnrqxxejDimjMHsIY1IPkgU16BPb/WRQFFRDUlQLqZ+pi0wIqUcUUofTvA67fjVO/WpMiX0oQuqwqP3fj3h+NTpFh99jZWgdKRENfufPlNztF/XLjG4lbWmT75zLg6oxq3p9n5d0TgXW1AGEaR5kM8tRL2nCq1uFLbkfV8Ygbs0KXBnLyRM6UYc3YIj3v5FgFDUhm1KCEOBANd2NO30AU1TTp+ttdmNXdlCQ0ExuZB2m+Foy53mR3mAlZaYbl7ILyTVFow2XYpp44J7Hxgje/fffz5EjR75R3eH777/vW//0y+oOvy9ycr6va98SF5QQvv72B8ys3kyAZ4S/PHL0fE9nnHHGGecrMd3yIAGeEXLWPfC9WG7p6zAuhN9Djh8/TlpaGjNmzOCiiy7iP/7jP5gwYQKTJ0/m7rvvZvfu3ezfv59HH32UI0eO8OKLL/Laa69x8uRJX1Tx3Xff5dVXX+XBBx9kZGSEbdu2cfjwYd56660vjDI+/8SL/LF3Iw3qXhSX6ZFdqsU4vxRHdC22yGqsS6uxRdWinmLFsrQaZ1wDecFeZJfnop5sxSNvxSlqIC/US+K1+Ygv0ZMSUEhuiBtTmAdTuIfMmXbk1+SjW1iKMdxL5gwH4suMZM5w4JQ1U6JoQxvkRfyrPIRfmzEvqcUla8MYWoVN3IIlrhFjWDUuRSeGxdUIVxYgXFmANricgvha8mKrSZ7qRLi6CENoDSWqLnQhVaM1iJMceNP78WYO+EUMdWF1lCT3kh1cjWZRDc6kXvSRDdhUXWQEVSAEOBACHKQFeskTNaKPqUUTOfrlPnGuF0NCA6kLKhAmlSBMKiEtqIrSrOWYJZ0+EZTO8GBLGSBPPNrF1CTqoEjVS67Q5VeDKMzwkrywFrdmBWXaVUjmVfqkxCDpxCBp8wlJYWovkgXVFGcOohV3+EmjKqQWt2kNOmmXn/iI51WRsrSBgrRuFItqx8hTRmwzRZn9JEc0+8mgKLAG8YIanIYVZAudY16TLKwjP3MIjaIXu3aVrwOneH41LsMaPyGULajkxUuvhQkTOPyLSUjnVSBfUE6HPJU95iCecM1ltzmIdmUasuAKREE15GcsI1veTaF6GaakHhJD60gKqyMxvN7vvckW1pAZ1+z3npLCG0mPafV7zpw8gBBY7bevXt72uVTQPqTzz53/lPAGcuLafFKomF9FobLXFwWWz66gOKnPVxuomluBRd6NMKkEyU0laMIbcCT3Yha1YBY3ky9twhBXgy6imuzQSkyiOhRTHQjX25AG2DEnNCC53opwbTHpczzYJG0kTXagWVBOUWwT3tQ+bKJWXLJ2Oi3reergue6gZxez/yZCeObMGYaHh3n33Xf9nj958iRHjhzhvvvu4+DB78cSAef7uvYtcUEJofP3BwjwjJA4uIePP74wvlyNM844Fy4vnHiXqRV3EeAZYdvjr5/v6XwrjAvh95B3332XtrY2fvvb37Jjxw527NhBdXU1N910E1dccQXFxcXs37//a9canjlzhmeffZb77ruPO+64gz179vjSwb5o+5efeYU/9m3EEV2LaYEbe3QtReGVZNxYhOS/tOQv9pC/xIs53EP2bBvSy/WILs4hbVIhplA35iUe8sI8iC/Vo7gqj5z5DvLCvGjnlZA9w4lL3ExhZC0uSevoOoVX5SO+zEj2rBLKlB2UqTopiKxD/Ks8kifZsCY0Yxe3kD7NSfJNNlzyNhySVlzyDtRzyhCuLEByVQGmJTUUxddjWFKBLqwc6XUWdCFVuJSdPjEUri7CHFOPQ9WBMbreJ4aJ00vIja4hK8SL7EY7hugassOqMCU0khvTgOTGUTEUbnRQKG7DldyHM7kP2VQ3wqQSMhZVYUxoRDXLgzCpBOUMD271IO7sIdRhDT5RkEx1U5zYS6GsiyJF92h64QwvmUsacWUOkji/yieShvh2nFlDFCX3+0UUhZleDEIrenETaRH1fjKoFVrIim4YTV+VtiDMHxWe5CUNFCT3IptfhXhWBTpxB+lRLaNplEIntqwhn4DqhE7SoltHZS+4Dlv2EBlRoxEzrbQF8aeNcM6OvOQBbOohdLLuMZIpBFZjyRpCsaQRh3YlJmUvxqlm3vt//wkTJrBv4UzOlP8aai/lo5pf+P333cor6VXnogqpwfA5YRPPrcSo7PG9P5/YSbuRh9T5zaHEsAZL5hAVhTfTUfknVnXfxV9v3c3w7/7G1uEHuXfrQR7Y/QQ7tz7I8B+3sWH1H1m/6vcM/2krO7fu54Hdj7Pv3se5f9dhdmx6hM3/vY+//nY3f1q/i5v7NrOs/s+0ltxKTcFaKk0rMUvb0UQ2kL6oBpO42XezQDbVTW5sve8mQ9LsMowxDb5/g6lz3RiW1pA2uwx9WC1WoR1PWh8OWTtORSee1F5KlB3YhVasohbK0/owL60jd1EVuqAKlpfdxisvvM6uXbt44YUXvpEQnjp1iuHhYT744IMv3WY8ZfT/lAtGCB9+6SQBnhECPCMcfPnU+Z7OOOOMM87XovWuJwnwjBDZsYMP//n9T3MfF8ILiI8//pidO3eSk5PDRRddxMKFC+nv7+fYsWNfWw7ffPNNDh06xNatWxkZGeGBBx7gmWee4bnnnuPJJ5/kwIED7Nu3j3vvvZetW7dy+81/oCG/k+L4CvQLnKTekI/oZxoUvzRgDHLjTKjHLWkic3IxootzyLipGGtULY64BowLPTjiGzAGe9HMdpK7yI020InyKjPiS/SYF1fiVXXgUXWSNasE8WVGpFfkYQ6rxiW0UBRVj0vahnp2Cdlz3DgkrVhiG1BeX4T4V3kYFlXgTemhLKmbtGmuUTG8ugBDaCX5sbVkBZZiWFpB+hwXqbOcGCIqUS9w+8QweZoTu7INZ2IH0ol2hOusSG6wUSRqxa7oIml6KXnRTdgUXWiX1ONK7iMzqBLhBjvCDXaSZrgpyxigXDOIapbX98U/e0k1uXENyKeWopjmxpU2QE5EE670ZWQvafClDgqTSzEltFGuW0nWkkafCEqml1Go6EYf14JkqhuzvB1VUBWS2eXohWbSQms+E5kqJ1fWSo6oySeCnx2OjEHchjXIA2t89YtnR1HKAF7jWiSfiYT5IpLSbkoNq8mMbhnzWmFaH+KgGrTSNrJim33Hy4xsITO23U/GDPJuLGn96CTtfseonZgK034MNZfwSc2lUDt2fFwzOmrj1EjmVqIRt4yRQpduFeJ5VSgX1WPJGKSj4o8M376HnVsO8uShFzn51umv/btxdrz77rscO3aMAwcOsGXLFjZu3MiuXbt46KGHOHjwIPv372f37t1s27aNO++807c0zLZt27jvvvvYv38/jz32GE8//TQvvfQSrxw9xkvPHeOpQy9y4P4j7Nl6gK1/up+/rNvBrf2b+U33CL3u26g1rsCZ0okzrQ1tWAWakAqyF1bgSetDcUMxwlWFKG6w4lJ0IL+2COGKfJTXF+OUtqG4thDx5SYU1xRSre/mycNPfSMhPHHiBHfeeedXbvPPf34/1mU639e1b4kLQgg//vgTlMt2E+AZofSP348I8zjjjDMOjC5WH9K0jQDPCEM7nz3f0/m3GRfCC5TTp0+zatUqFi9ezEUXXYRareauu+7yRf1OnjzJG2+8wdGjR3nmmWc4fPgwDz/8MH/729/YsWMHmzdvZnh42Dc2btzItm3b2L9/v2/pi5dfftlv6YuXnj7Kfy/bRFVSJ8LFOUgu0WGc78YRW481oobiiBqsUbWk3FBI/uIKnPGN5IdWorwyj4ybrJRKW7BE1pAX7iVtchHiS/SIL9VjCCzDq+qgPKmT7NmliC8zkjTRQnFMAw5RM5o5pZhCKymKqUMTWEZBTA26YA+SK/MR/yoPxfWF5MVUYo6rImWawy+V1CJqQhPkISfYgz68nJTpTooSGimMa0J2w2hDGsk1RbiTuqlQD5AdVIlwnRXhOiuZgRW4EnswRjSQFVSJK7GHpJluisTt2BVdKKeU+KI7+vB6KjRD5MW3Itzo9I2s8CqM8Q2kzPViT+ohcW458hllFMg60EY2+CRSMaMMo7iRXFEjqcFVvoiiMMVN0rwK7Cm9ONL6fSIoTPOgmFOBM305+phWipQ9pCyq9YlgVmQDhcpuZDO9ZITWkyfv8YlbvrKX4uR+JNM9JAfVUJjU5xO1jMgmXFlDpATXkrW0CU1cm5/IpS5pwKkexJU9OEYwxbMqSI9oICWyEb2slfSl9Z/pwFlH2tJzyzLI55XxoedyqLnkC2Xws1J4pvzXyOeUkRbeREZUM/KFNeQqOygrWMaq/j+x976HOXny1DcWvzNnzvDGG2/w8ssv8/TTT3Po0CG/utyRkRHf78amTZt864Lefffd7N+/n+eee47jx49z+vTpr90A6psI6SOPPMLWrVu588472bt3L0eefIpjL7/G0edf5bknX+KJh5/h4N4n2XfPAXbdeT8jt97Df6/dRH/dau763Y4x6Z9fNV577TU2b978ldt89NH34w7p+b6ufUtcEEL4hwdHl5mYXbOF42curBbu44wzzoXPnx8+SoBnhFnVm3n9e74MxbgQXuA899xzFBQUMHv2bH7yk59w2WWX8fOf/5zg4GDuuOMOtm7dyq5du7j//vs5cOAATzzxBM8//zzHjh3jzTff5J133uHtt9/mmWeeYdeuXdxxxx3s3buXF1544UtTSt977z2ePfQCtzT+CcOcEtSTrdgia3HE1GOYW0Lir01YI2soXlqDPa4eW0w9WdPsiH6uRXyJDkd8I25ZC8Ux1SivykN8iR7ZFUb0C0opiKjAFOrBsKgMyRUmEicWoQ0pRb+ojKQAC/Kr8zEvrSRvaRXFCY0YQ6uQXjUqhqqJFpySVjwp3Vjims6J4YJyXPIOzEtrSZniwBRZTepsF4bwSiyiZtJmlCJcVYhwVSGGxVWUZw7gUHYiuW60hku4thhzTBMuVTe6xTW4EntIn+dFOcWFXdFFkbgNaYD909TTUqyqDorkbWQGV/rSA4UABxkLvRjjaskTNyKdUuqTQX10E8WKTpTT3WgW11Ks7EaY4iY3rg1HSj/KGR7ftlZVL4a4dkoyB0kLrvUTx7TgGtw5KyhQdPuijWeHYnY55YbV5Em6/KRSmOZBNqsct24V9nT/7qjCNA8pwTVkxTShiW/GILQgnen1vWaUtiGeVY54VgXCnAoMQhv6hGayIutQBlZ9Ls21HH1CB0mL68lT9HBbvukrRfDz48+uYv6wdieHHnmOM2+P/rt84403OHz4sK/5yZ49e3j66ac5ffq0T/bO3hA5K3t79uwZI3tbt27l3nvv5YEHHvCry3399dfHyN7nG67s3r2bp59+mlOnvrmQft0Owi+//DL79+9ny5YtDA8Ps2XLFrZv38727du56667fM2kNm/ezI4dO9i7d69PVE+fPs0777zzpR1Jz45XXnmFbdu2jQvhd4fvvRCe+eAfLGy8mwDPCKvu/f7fXR9nnHF+eHz88bllKJy/P3C+p/NvMS6EFziHDh0iNzeX6upqli9fTkVFBTKZjMsuu4z4+HhuueWWL20k80XjxIkTPProo2zZsoW77rqLAwcOcPz48a/c59E9j7PMsYHiT5vNFIZWkHSVGdHPNGROsmCPr6M4php9YAnyX+Ui+rkW2RW5aObaMIaWYo7worjKhPgSPaprzBiCSylYWoluXin2uAaMIRVkzXThEDVjjW0kdZIV8WVGNHNKKVN1UKroID+iDunVBYh/lYfsmgIKo+opU3XiSepG8Wl6XepkJ3ZxKzZRC8k32TEtqUa72EvqTAf5sXXkhlcjuXq0g6PsOgvlGf2UZ/STOb/cJ4ayiTZM0XXkRdeSF1tLyhw3wvU2FFOcGKJq0IZXIbnehmqqiyJpKxnBVVgVneRGNPhSTYUb7KhDKrAo29EuqfOTRtUMN47EHkpSRxcsPyuCwqQSCiUd2JTdpAdW4Eg518AkZUE1rvRl5CwZjTi60gZQzC5HmFpGxuI6ilRdJC+oGE1RFbcgn1PuSzfNk7ahiahHmFxKrrgRYVqZT/hU8yvJV7Sjj20mV9Q2RiSFaR48utW41INkLK73E1B9XAuKwEpfzWOu0I4jbRnWpD4SA6vYnTufj6q/ngx+UncZ/7wt00+STpw4wdGjR3n22Wc5fPgw+/bt4+677/ZF8c6OLVu2sGvXLvbt28fBgwc5cuQIL7zwAq+99hqnTp36tyJ7J06c4PHHH2fnzp1+3Ti/7u/bu+++y6lTp3jttdd44YUXePLJJzl48CD79u1j165dbNmyhTvuuMO3HMSOHTvYvXu377Xh4WHuueceHn30UU6cODFGJN9++21OnTrlG2+//bbvJs/nBfHFF19kx44d40L43eF7L4S1dxwmwDNCTOdO/v7Pj8/3dMYZZ5xx/iUOvnzKVwe977k3z/d0/mXGhfAHyrFjx2hpaWHq1KlcfvnlFBYWsnfv3m+Utvbyyy+zb98+Nm7cyI4dOzhy5AinTp3i5MmTvi+xR44c4eDBgzzwwAPs3LGTlS3rcUirMSx0kj6pEPHFOYh+piHl+nyKo6uwxdWSt8iL+BIdop9rSb+pGGt0Lc6ERpwJjRgXehBfoifphgIMIaXkL6kka5oD/Tw3TlEz2sAy7KJmbHGNpE6yjdYd/tpMmbIDt7KDoqh6lJ/WU4kvN5EbUoFb0YEnsQvNPC/CFflIriwgf2kdTmk72gXlZM11kxdZjSKgmJwQD8aISpKn2H0RxpxFZZiiqzBGVaOcZPfVICpvtFEsbsGd3I0+rNaXaqqa6sIu76RYaCNjrhdXUg+KKSXIb3JhlXVSLO1AduNoR8msRRVkh1Wij6yjWNaBalqpTxoVU0ooy1hOSVo/mtBaP3EUAhx4swcpyxpE8ZkIojCpBOGmEooTO7EkdiCd5varWRQml6KPr8cobUQ1xzvmtWJVD4WKHuwp/ShmnXtd8f/ZO++wps73jb+IWxR33agIinsgOHArhCHiZO89ww4bB7i1fm1r7bBql6M/BxJABEU2iAIigoiICLgRVFpbldy/P2JOCTMg076f6zqX5oycN8kh77nzPM/9yHHguI6fsrpJcQtcN30Ns+U7wBrnBvba/0FtEkdIEKpN4sDL8Fu4aB/E+ll+QucwW7kDWXZyTYoQVhxYWCsiVl3sZWRkIDc3F4WFhSgsLMTNmzeFonh5eXmtFsX7888/UVZWhtzcXCbKHhMTg1u3bqGoqIhpFXPz5k2kpqYy9bkC8RoWFobo6GgkJCQw/UPv3buH4uJiPH/+vN5IvcABND4+HiEhIYiOjkZWVhaePHkiJHQF4rCiooIRh4LIoUAcCkynGhKEVVWd46a+vee1FqJTC8LMh+UY68W/gYq/+7y9h0OhUCifhPfZLEhxuFi+N6bTGsxQQfgfh8fjIT4+HiYmJujTpw9mzpyJffv2obi4uM70tBcvXqC0tBQFBQXIyclBeno6EhMTERkZyUQrzp8/Dy6Xy9zEpqWl4datW7h79y4ePnyIp0+f4lHxE5z/9iK2m3yNTWPsoNzTACq9DWE8xRXOy7fAddU2uKsEQbW/KZT7GMFgkjPYy/nppZbyXnBetQ3rx9hhw1g7GM9xhbkiB9rSjtAYZAGn5VthtygA7BXbwF6xDdoT2FDpZwqVfqawmucHzprdcFXbiQ3jnRhhuH68I6yU/GC91B9mC3zAGmwN1mBraI11gOkCL5jO98ZGWTaslvhj3QQnrBnnCDMlX1guDoDmGEewhtrAbJ4/2Ko7wVbbBQfl7Vg9xpFJNV0r7Qwf3YPw3HAAmuNdmIii2mhH2K3cDrc1e+Gx/ksmtZQ1ygkmCzfDVWs/9Gb5wHLZFn60cTQbqye4wkF9N+xUdkJ1DBsGCv6wVt4OlpQzNs32ga3qDmjP8gZrNBuaMm4wWRYI1jg3bJjtAwvlbdgwwwssKWdoyLjBfvUesKTdsW66L5zXHYDF8mCwpJyhJecJS5XtjEjTUfCH09p90FcMhOmSbdCfv0VIxK2d7gPndQfga3xYKN1VsNiv3o+1M/1gr7kfzusOYMMMH7DGusBixXZsmOVfS3jecJJH1Uc30UYjhIH98foHTdy/fx+PHj0Saq/S2PLixYtaUbyWEIc16w+r9wWtGakUpKUmJSUxZjOC+lxBT9BPXSoqKnDv3j0kJSUx58vIyEBpaWktcfj69WtGHApqjTMyMpCYmNhgaikVhG1KpxWE7z9UQe1/cZDicME+kd7ew6FQKJRPpuLPf1PgD0bfbe/hNAsqCCkMJSUl8PDwgIyMDMTFxTFt2jQoKipi9erVTOTl/PnzQrVIN27cwO3bt5nG9kVFRUhPT0d4eDgiIiKQmZmJZ8+eNXizejezAL/uOAvjya5Q7mkAdUkTWMz2hPPyLXBQCoDrqm0wmuIK5T5GMJp24P8rAAAgAElEQVTiyheGSzdDT8YJ9kr+sJnviw1j7WAq7w6TOW7QnuAIlb4m0JdzgcOyAFjM94a1kg90JjoxwnD1MEtYLvaC9RJf6E5xYYQha5AlzOZ6w019Bzhae7B6JN+xlO9a6gtX9Z2wWhgAtsp2GMzigDXUBhsmOcNqiT8sFvhDfZgtDGZ4wUV9FzZNdoez2i44rArmu0AOtYHacDu4qO+Go9ouOGvswYaJbkxEkTXMDo4qO+CtcxCmCzYzopE1wgHqUk6wWbkNDurB0Jr0r1kNa5QT1si6wnRJAKxXbcG6j6JRsKyfwoHT6j1wXbsfenP9hSKIGhPc4Ki+Bxztg7W2saScsWmmD3yNvoXFiqBa29ZP84Kd+l44rdkPR819WC3rzmxzWXeAEYVr5LzgpLkfbM19sFXZifXTvYVMdVhjXaAz1xebFPxgpRGMIPdDOPHzGWT/5tekCOHf145/smh68eIFcnJyGHEYGxuLO3fu4OXLl3X+MFJSUsKkpF6/fp2pPwwLC6u3/jAvL0+o/rC8vBz5+flISEjAhQsX6o3iteTy+vVrFBYWIjU1FaGhoQgLC0NCQgLS09Nx8+ZNXLt2DXFxcULClcvlIjMzExUVFXj16hUqKytriUMqCNuUTisIf4grgBSHi+mbI/H8zd/tPRwKhUJpEc5nlECKw4WMbzjuP69s7+E0GSoIKQypqakYN24cFi1aBHV1dSxYsACzZ8+GoqIigoODkZmZ2aCRTM2b5gcPHiApKQkhISG4evUq7t69yziS1n2j+gYJodcQsHEfVCWMsHqgGazkveCyYivs5vvCSt4LjksCoDHIDHqyTrBZ6ANLRQ42jrXF+jE2MFNwx/qxNjCc6QITeTdoyzqA1c8UGoMtYKPkC8t5XnBcvhkWCt5QH2TBiENXlWB4au6Cw/KtWDPSDir9zaHS3xzrxznBTW0nvNbtg+lcH0YYqg+3gc3izXBV3QG2cjAsFwQwEcVNk11gvSQA5vN8oTfVnW/5P8oea8ez4cTaATZrB9ZJO0N9hB3YqjuhM40DIwUf2KsEQX8Wh4ko6s/2hN5cTxjO84apki80xzkxonHjZHfYKgfBemUQTBb6Mw3KWSMcsFbWDa5afAFmp7IT6lJsJlVVS9YdLmv3w0Z5J5w192HdRHdm26apXnBQ2431U7zgorUftso7oSbFT1u1XBbMCMbVsm6wWLEVJov9oSnjClvV7bXF4lQO2Gv3wGpVEDTGuwgJ1A0zONCew48OGi4MxHbnI+CeisGDwiLGxOjPP//En6/KwNs+GrzAhqOEvEBJ8LaPxp+vRK+DbWiprKxEWVkZI5gEtXhhYWFM3WzNlFSBIZMgJbW59YevXr1CQUEBE8W7dOkSMjMz8ejRo2aJQ1GFa0hICLhcLkJCQpjU0rS0NBQWFuLp06fM32z1usOXL18y4lBgSsPjdY6G4u09r7UQnVIQlpT/BTn/CEhxuPg9tai9h0OhUCgtBo/Hg8GPKZDicKH3Q3KnmRMFUEEoAtu3b4e8vDwkJCQwZMgQrFmzBnfu3Gn0uJiYGMyaNQvdu3eHtLQ0jh492vqDbWHevXuHCxcuQEtLC926dcPSpUtx5MgRvHjxQuQb0/LycuTm5uLy5cu4cOECUlNTUVxcLHSTW1lZKVR7mBqfhi9dv4P2ODuoSRpDX84RJrNdoD/ZEetGWsJ0jit0Jthjg5QtrOZxYLPQB/oTnaAmaQL7RQGwUvSFuTwHlgu8oDfZEWoD+Kmn5nM4YK/cBvbKIDgt24pN4/jRRJW+JjCcwm98766xE6azvcEaYMGIQ9M53vBetxcemruEahDXjLKD/bKt8NDcDTeNXYxoVBlkiY2T2LBc7Afzhb6wXREI9ZF2H6OEtjCY4wHTBV7YJOcCi0V+WDfBGawvbKElzYbtyq2wW7ENWmOd4LAqGEbyvmANs8OmyR5w0dgNuxVBUB/lAOslW2G2kB9JXDfRDeZLAmCowIH6SHuYzvPjbxvpCHUpNuxW7YDL6j3YKOcO2+VB0J/jx4jBDVM84bJ6D+xXbYer5l6skRGOQK6b5AG25l64b9yP1dKuQttYo5xgpOSHTXO8YLYsAAaKvlAd5fSxLYc3jOYFMGJQa6IH/I0P48LxWBTeLWn0uvn75jm+4KtHFPI+CsJn8cdF+qGiLpOWjIwMJCcn12vSkpSUhGvXriExMRGXLl3C+fPnceXKFeTk5DTJjKm5UbyUlBRwuVxcvHgR6enpKCkpQWVlZYOvJSYmRqhtTEREBGJiYhoVrpWVlXj06BEyMzOZ6GBiYiJSUlJQWFiIyspKVFRUIDc3F5cuXcKPP/6IzZs3w8LCAqqqqti9e3d7f12JRHvPay1EpxOEPB4PFsfTIMXhYv2hRFRVda6bJQqFQmmMBy8qIesbDikOF2fTi9t7OE2CCkIRUFFRwdGjR5GdnY3MzEyoqalhzJgxqKysPyR8//599O7dG66ursjJycFXX30FcXFxXLx4sQ1H3rI8efIEe/fuhZycHCQlJWFpaYn4+PhGoxeCqMujR4+Qk5ODq1ev4sKFCwgNDcXFixcRERHB3IhXN9BIS0tDVlYWLvx8Ed5rdkBzsDksZ3vCZfkW2C/ww8bRtrCczYHTkkBsGmsHB6UAfsP7WZ5QlTSB0WRXsFdsgck0viupyWw3rBlhCeU+Rlg/2hauKkGwXRgAV5VgWMh7Q22AGVT6mmD1EEt4auyECysY7BXbsEn631RTtYHm8Fi9E27q22Gu4AO1wZaMaFw93BpWi31gtcQb62QchcTh2vEOsF7mD2e1YKyXdmYiiqzB1jCe7Q331bvhtX4/Nsi4MmY1rKE2MJnrB/fVfDfUjZPcmAgi6wtbGMzyhtvq3eCs3Y9Nk92Ftq2WcoDJAm84qAZBe4qHUFoqa5gdTBX94a1zENZLt0J1hL3QNu1pHjBR8of50gAYKHgLRSAtl2+BxngXqEmxYbFkCxzVdsJgtjf0ZnpBf64PIzJZIx2hOsoRTup7cHTXBaReuYVXFU2vh/s78yx420czbqLV/60KHoWC8K9x8eJFhIaGIiUlBXl5eSgsLGzUpOXy5cu1TFpKSkqEo5R1LAKjltjYWCbynZub2+Li8NWrV3j69CmKiopw584dJCcn16rTrf5aEhMTmfTtgoIClJaWoqysTOSIfmVlJdPCIjExEadOncL//vc/7N+/H3p6ehAXF4eEhATExMQgJiaGESNGQFFRERs2bICzszP27duH5OTk9v6KEon2ntdaiE4nCEMySyHF4ULaOwx5T16393AoFAqlVfj6Sj6kOFzM3BKJZ687T1o8FYTN4NmzZyCEIDY2tt59PD09MWXKFKF12traUFFRae3htTo8Hg/JycmwsLCAhIQEZGVlYW9vj127dsHT0xNpaWlMpKJm1EVw83r9+nWkpKQgOjqaibrk5eU1aKJRcv8Rjm05DcNJzjCb7g7nZfyG93rSjlg/3BouK7bCQM4ZVgo+cFm5FbYL/KA1zAprhlrAecUWmM5wh+0CX9gs9IHORAew+hlDtb8J7BcHwGqeD5yWb4Xjss3QkWFDpa8JWP1MYK7AgdlcT1gs8ILRLDdoDLVkxKHhDBdYLvCG9WI/GM/2hOog4Yii++pdcFXbCaMZHCaiqDLAAtqTnMFWDYKz2g7oTnEXEo46cm7grNsPN43d0JviKSQc10s7g7N+H9w198B4to/QtnXj2HBfsweuq3fDdtk2qI+0Z0TlOhk2jOZ5wUDeC1bLAqAzzZ3ZpjvTHdrT3MAabgdDBW/YrNgCg9leUBthBye1HdCQcmLEoM50Lzir74br6j2wXRFUS2SuHuMEr03/g5/J1zgU/AtO/HIaV69eZdxnmy2QXpXhr5Sj+Pv4Rrz9dgXe/LgGD7l7kJacgPj4eERFRdVqJxEREYH4+HhkZWUhPz+/xU1aqovDuLg4xjk0Jyen0eh59bYY+fn5tVI5q/dAjIqKQlxcHK5du4asrCzk5eXh9u3bSE5ORlhYGMLCwnDt2jU8ePCgQfFXWVmJFy9eICMjA1wuF99++y18fHxgZGSE5cuXQ1ZWFn369AEhBAMGDMDUqVOhqqoKa2trBAUFYf/+/bC3t4eioiL09PQ6XSpMdVppurInhDwghPxNCEklhCiIeNxCQsgHQkhmE8/XqQTh09dvMWNLJKQ4XHwZldfew6FQKJRW492HKqge4BtnWf2c1mnmSyoIm0F+fj4IIbh161a9+yxatAhsNlto3U8//YR+/fq19vDahA8fPmDkyJFMxKBnz54YM2YMZsyYgd9++w3Z2dkoKCgQOepy+/ZtREVFITQ0FGlpabXcD4XT6d4g5v+SwFHbDgNZNpwWB8B5aSBMprhAra8R7Ob7wEbBG4aTXcBeuhlOSwJhIMuGSm9DWMpzYDGXA/1JTrBQ9ITxTBdojbCEcm9D6Mo5wGA6GzoTHWCu6AmTWW7Q/IIfUTSa5grbRf4wl/eCi3IQbBb4QXOoFVT6msB4mjvYK4NgNd8PrqztsFL0hdrHGkX9j/0RLef7wVV1BywUfaE6iB9VXDvWDhZKPjCc7QkX1R2wVgqE+hfWfNE40RXOrB3Qn+YJZ9YOOCzfBq3R9lAZYAFdOTc4rgqGxgg7WCkFwG7FFuhMceULyqmuMJT3BGuoDbTGO8JkvhdM53thzRh7GM31xIaJzowY3DDRBeyPdY2eWvugPspeKMqoMcoB7lr74L3pAEwV/IQil+oj7eG6eg/WSrvAW/sgThwMR076PaHPqby8HHfu3GFaLcTFxTGN4esTSHXVulUXSJcuXUJcXJyQSUtRURHTaL2yshIlJSW4ceMGwsPDER4ejuvXr9dKUW7ppby8HHl5eYiNjcX58+cRFRWFlJQU3Lx5E+np6UhKSsKVK1fqbYsh6IFYX8P7+kReaWkp0tPTERERgRMnTmDZsmVgs9kIDAyEjY0NNDQ0MHPmTAwePBiEEHTv3h3jx4/H4sWLYWBgAC8vLxw6dAhcLhdZWVmoqKgAj8drcALrLOYx9dEKU5U2IeQfQogpIWQyIeR7Qkg5IWRoI8f1J4QUEEIiyWcsCHk8Hiw/poqqHojDuw+d+/qhUCiUxrhd+grS3mGQ4nBxPqOkvYcjElQQNpGqqiqoq6tj4cKFdW6PjY2FhoYGxMXFQQjBuXPnmG1hYWEghOCvv/5i1sXExAg+AKHl8ePHrf5aPpW0tDQUFxfj/fv3APhC2dvbGyNGjMDIkSPh4eGBrKwskW+qBTVM169fB5fLxaVLl5Cdnd1gOt69W4X4yuUo9Cc4wHouB/ZKPjCb4YrVA02wScoG5vJu0BpuAYPJjjCZ5Qx9OUdoDDDFprG2sFTkYN1Ia5jP8YDNQm8YTGVDbYAJNo6zhd0iP6wfbQubeb5wWbUN1oo+0BhkDj1ZNpxXbMPakTawVvSF66ogWM/zhcYgc+hOcILzym1Y/YUVLOS94aoSDNuFAVgzzBq6Mmy4rAqC2hBLGE71gLNyMOwWB0JrlC3Wj7ODiYIHWAMtsHaMAxyWbYXjym3Qm+wKvcmusFzg+zG6aA6dyc4wnceBwUxX6E1zgf5MNya6qDbMGubzfeG4chvYKsHQmyocfdQYbgv7ZVvhprkThrM5YA2xFooyGs32hpPKdrhq7Ibdsm1YM9oBrMHWUPvCFq4au7F6tAM0RtrDRW0Xfgo+i2tXsvCqon6TIMFnKjBpSUlJYWrbwsPDERkZ2ahA+hSTlsrKShQXF+P69esICwtDeHg4bty4wdThNVX0CWronjx5ggcPHuDOnTu10lIF0fDQ0FCEhoYyrzUhIQG5ublMKqeo5xfUC5aWliIlJQX/93//hy+//BJubm7Q1tbGwoULISUlhW7dumHs2LGYOXMmJCQkIC4ujgkTJmDnzp04deoUkpKSUFpaivfv33eaXytbi1aYqlIJIV9Xe9yFEFJKCPFq5LiThJBthJDN5DMWhALnPWnvMNwu7fjjpVAolJbgQNRdSHG4mLElEk9fv23v4TQKFYRNxMbGBlJSUigurrtYNDw8HL6+vhg+fHiTBGFeXh4eP37MLJ35V/gPHz4gPDwcGzZsQPfu3aGkpITvvvuu0fYTwlHA1ygoKEBcXByTUpqeno7bt2/XaQTyf6f/D7td/geDyQ7Qn+gAKwUPWM31gM44W6wZZAanxf7Qn+AIw0kuYC8JBHtJIIwmsbFumCVclm+G9jh76Eg7fGxj4Q0daTtoDjWH1TwO1o2ywdoRNrBX8ofLiq2wlPeC9jgHuKzcirXDraE2wBSWc73hsmobbBf4QX+iM1xWbYPmF/wIouFUNziv2ganZVthOtMTTsu3MBFEzeHWMJP3hMU8DgymO8NojhtU+psxqafask6wUvKF7RJ/2Cz2Z9ar9DcHa6AFLBR84b1uL9zUdkJjmI1QaurqEbbgrN0LN/WdsFEKFNpuMNUDdku3QneyGyyUfGE01wNaUvZgDbQAWzkY68fz6xzVh9nCcVUwDvufQvKlDJQ9fykkVl6+fIlHjx7VaWxSPV1YYGySlJSE1NRUxMfHM7WjCQkJuH//vsj1bs1ZBPVxaWlpCAsLQ0REBNLT04Ui0a9fvxZK5bx16xbTO1AQvRaIvaioKMTHxzM9NvPz85lG8dXTUsvLy3H37l2mOfzly5eRnZ2NW7duCb2HWVlZiIiIwHfffQd/f3+Ymppi1apVkJOTQ79+/UAIQd++fSEnJwdlZWVYWFhgy5Yt+Omnn3D58mXcvXuXcfrk8XjIysrC4cOH2/uroEPSwtNUd8JP+dSqsf44ISSkgeNMCSHXCCFdyWcsCKunih6I6py9uSgUCqU5vKvWc9XieMdPHaWCsAnY29tj1KhRuH//fqP7Llq0qJYgrCtlVCAIy8vLW3y8HYHnz5/jwIEDmDZtGvr27QsTExNcuXIFlZWVePXqFYqLi/Ho0SPcv38fOTk59QqK0NBQXLhwASEhIYiKisL169eRn5+PkpISPH/+XEhMXIvKQOCGvdAZaweHBb5wXhoIq9meWDPIDLaK3rCS52D1QBNYzeHAedlm2C/whfYYWzgu8ofZdHeo9DKAkZwLHBb5wVLBExvH2sB0tiu0pR2g3NsQ60fbwH6hH1yWb4HVHC+4rtyKTeMcoNzHCKx+xjCZ7ga7RX6wVOTAdrEPNIdZMk6ma4ZbwXCGCyzme8B2iQ/UB5kz21T6GsNgsiuclbfAYbk/tEbbMPWKKv1MoTrADJ6rd8Fj9U7YL94MrRG2/5rdDLKAi0owLOb5wYW1XWi79gQ2nFYGQWWABfQmu4OtHAynVUHQneQK+6VboDfFnRGKqkOsYDTXA8H2X+HcsQgU5Bc2Gg2raWwiqklLZWUlnjx5gszMTERGRoLL5eLatWt4+PBhi4tDQaSytLQU9+7dw7Vr1xAVFcW0WhDUIIaEhDTaO7Ap53zz5g0KCgpw9epV/Prrrzh06BAOHDiAbt26YciQIZCQkAAhBF27doWUlBSUlJSgq6sLDw8PfPXVVwgJCUF6ejpevnzZaConRTRaeJoaQfgT6Pwa63cTfuSwLmQIIU8JIbIfH28mjQvCHoQ/SQuWkaSDC0Iejwezo9cgxeFC7X80VZRCofz3yHn0ChN8+Kmj/3e9Y7uOUkEoAjweD/b29hgxYgTu3hXtV05PT89aglBXV7eWqYxAEEpJSWHYsGFYuXIlEhISWnT8HYFLly5BT08P48ePh7i4OPr27YsuXbpgzZo1jMV/dafEugSFIHXu2rVrCA0NRXR0NHJycmo1DhcsD+48xLcex7FxlDXMprqCvSQQTkr+MJrIhrGcM5wW+0OtryE2jrKG/QIfuCzbDGt5DqznesFuvi+UexpAVcIIptPdYbfAB2azXWE03Ql6E+2h3NMAyj0NsGaIOYymOcNU3hWm8q7YJG0L5d6GHxcD6Eg7wG6RH1yUt8B8jieU+xgxi2p/Uzgu2QzO6p1wXLoZ60fZCm03n+MF28V+sJjvBf1pzlg9xOKj2Y0pHJdugdF0D1gp+sJFORh2SgHQGs6PZLooB0NjCN/8xniaOz86uXwr7JQCYDnPTyjKqDncBs6qQTjofRQnvjuHy1FXarlZcrlcXL58GdeuXROKhrWkSYsgXVhQDxcWFobr16+LlN5ZVypnZmYmUlJSGmwnIYg4Z2ZmIj4+nnG9zczMxOPHjxs8ryCV88mTJ0hLS8O5c+dw8OBBeHh4QE9PD4sXL8a4cePQo0cPEEIwePBgzJo1C5qamrCzs8PmzZthY2ODBQsWoF+/fkztHqX1aeFpqqmCUJwQkkYIsam2bjNpXBBuJnWUFnRkQfhzUiG/SbNPOHIfd9xxUigUSmsicB2d7B+BBy86bsN6KghFwNbWFpKSkrh69apQWmf11E8vLy8YGhoyj+/fvw9CCLS0tJCbm4tvvvmmVtuJ2NhYLF26lEkJ27FjB0xNTdG1a1fcuHGjzrF01t6Gf/zxB5ycnLB7924cO3YMAQEBWLVqFXr27AkNDQ2cPn26wab1daWU5ufnM/b/iYmJKCwsrDOy9PL5S5z9Jhxm09ywdqgFbOZy4Lw0EHbzfGAo6wTnpYFYN9wSyj30oDPODlZzPWCl4AHjqWyYz3EBS8IAyj30oNJbHzoTbGA6yxmmc1xgKu8C5V4G1cShBWwVfeClvgMeqsFYO8yK2abc0wB60o7w0tgJd1YwLOW9oD7AjBGP2mPt4aq8DfaLAuCycivMZ/NbZyj3NoTFHA6sFL2hNcIaRjNdYSLvBsNpLlg9xALs5VuhPZ7fS1FjsAWTumq/OADslVug0s+kWgTSBOvH2oGjHYwttvvx44HjuBhxkXGxrMuk5cmTJ8jIyBASaQ0Z/rSUOKxZ+5eamorc3Fzk5eUhKysL165dQ1xcnJDDKJfLZVqWNLWdhCCt9MGDB0hJSUFoaChOnToFQ0NDHDp0CD/88APTc4/FYmHq1Kno378/CCHo3bs3ZGVlsWLFCpiYmMDf3x8//vgjIiMjkZubi8rKygbF3tu3Hb+24HOihaeppqaM9if8CfdDtYVXbd3yes7TqSKEeU9eM724jsQ3nlFDoVAonysfqnjY+G0SpDhcrPk6ocNmS1BBKAKkjl9mCSFCYszY2BhLliypddy4ceMYZ7+a4k1Qb3j27FmhaKLAAbAmn2Nvw/v37yMgIABjxozBsGHD4OLigvT09CYJiBcvXiArKwsXL15EWFgY0tPT8eTJE+Ym/8WLFygtLUVBQQHO/hgKh8U+UO6hh3UjLGA0xQHGMxyhJ2sDkxlO2DjGCqu66UK5hy50x9vBRtELjov94K68DZtG20C5hx6Ue+hBVcIQJlOc4bDYB5bz3bFpnDVUeuox29X7GcFTLQgerCA4Lg6A7nhHRhiq9zeF84otsFbwhvNyfusM3XEOUO5pAG0pOzgv2wz1gaYwmeYG9vItcFq6GYaTnGGt6AMLeS8mgqg1whJGM51hrugOayUvaI2wEoowsiRN4LDSH5tN9uPY3lNIikllUh+batIicO9MS0tjGqVnZmbi6dOnnyT+qn8+9+7dw+3bt3Hjxg0kJibi8uXLCAsLE2onceHCBURHRyMtLU1IvDblxwRBKueDBw+QkJCAEydOYPfu3XBycsK6deugoKCAsWPHYtasWZg4cSK6dOmCXr16Ydq0aXB1dcWBAwdw5swZpKWl4dmzZ6iqqqLRvU5EK0xVqYSQr6o97kIIKSF1m8p0IYRMrbEcIoTc+fj/PiKes8PWEL599wEqX8ZCisOF0ZFU+rdBoVD+85SU/4VpgRchxeFiz8U77T2cOqGCsBUhNVJGRd3X3d0d8+bNq7XP59zbsKqqCpcuXYKOjg569OiBefPm4dChQ4ywq+/GXlAXdv/+fdy+fRtJSUm4ePEiUw9WvS+dwNQkPT0dV8PjsM1wP9T7GkKlhw6MJjrCUckX7CX+cFrkB/v5PljVTReruumC1UsfxnLOcFkWCE/lbXBa5AfVPobMdpWe+rCS94StEgems9nQkbaFah8DRhxazvaAg5If0x7DbLob1PoaQVXCEOylgdCVdsSmMXawX+AH9tJAmM9054vRBV5QlTSGcm9DqA0wgb6cI0xmO8NktguMZzpXS03lL7qTHBFotA9Hg0/jesxNlJeJXu/WVBH34MEDJCcnMwItOzu7Vv+9yspKlJeX4/Hjx3WazggcR6t/PsnJycjIyEBubm4th9HXr1+jsLBQ6Ly3bt3C48ePa5332bNnuHHjBi5cuIBvvvmGieAvW7YMMjIy6NWrF9Nzb/r06VBXV4e1tTWCg4Pxyy+/4OrVqygsLMQ///yDyspKnD59Grt3727vPxNKC9AKU5U24fcfNCaEyBFCviP8thNffNy+gxDycwPHbyafkanM5gvZkOJwMWfbpU7VlJlCoVBak9CbpZDicDHWi4vkghftPZxaUEHYipBmCsKVK1di7dq1tfb53HsbCigrK8PBgwcxbdo09OzZE0uWLIGVlRUMDQ1x+vTpOhveC+rCBDWId+/eRUZGBi5fvoyQkBAkJyfX2bz7SfFT/BL8f9AebY1VXbWh1kcfppOd4aTkB9dlgfBkbcPq/kZY1VUbq7pqg9VTFyaT2fBSDwZHNRjm092g3teIEYdrBpvBaYkvTGc6w3iGEwwmOUCjvzFWddOFsZwzbOd5Y+0wC5jPcoO1oidMpjtj7RfmMJnBxobRFlDuoQdWb33oTrCFhbwbrOd5wmmZP9T7mwiln24cbYt9tt/jSOBJxJ5LwcOCEuTn5zNN0uPi4pCfn9+kyFlTl1evXuHRo0fIyMhAVFQU81lcunQJkZGRTCqnwHQmISGhSaYz9f0I8OrVK9y+fRsRERE4ffo0lJWVMX78eEyePBlycnIYNGgQCCHo0aMHJkyYgKVLl8LQ0BA+Pj44fPgwwsPDkZ2djdevX1Ojlv8grTRdOf3icIwAACAASURBVBBCigi/H2EqIUSx2rZjhJCrDRy7mXwmgvBy7hNIcbiQ4nBxJfdpew+HQqFQOhTupzMhxeFi3vZovKz8p72HIwQVhC3MmzdvkJGRgYyMDBBCsH//fmRkZKCoqAhA7VrDL7/8EufPnwchBAcOHACbzUaXLl0QHR1d67llZGSwfft2oXV1tbL4HJg4cSIIIRg4cCCGDBkCGRkZzJo1C4GBgYzZiKhi4tmzZ8jMzERERAQiIiKQmZlZqwXGq4pXiPo9FjbyHKzssgkru2yCuoQBzKa4wG3lZniqbIONvCfU+ugz4lC5uw5clgfCdXkgnBb7wXy6CyMe1frow3yOKzZKWUF/kh2MpzvCQM4OWkNNsH6kOcxmuUCllz5UeunDcKIj7OZ7w1HJD+wlATCb5sZEF5V76GH9cCts1t6PnwJPIfpEPB7kFTf4esvKynD79m1ER0fjwoULSElJQVFRUZOElyCVs6SkRORm8SkpKYiPj0dkZCTOnz+Pq1ev4u7duyIbzwhSOYuLi5GcnIzTp09j3759cHFxwcaNGzF//nyMGTMGXbt2hZiYGIYPHw4FBQWsX78empqakJGRgbi4OAIDA/H48WN8+PCBij1KLdp3VmsxOpwgfFj2J6Zv5reYCAzJbu/hUCgUSoej8u/3WLonBlIcLgyPpOJDVce5R6GCsIWpr9G8sbExgNq1hrt27YK0tDQIIZCQkMDSpUtx5cqVOp97yJAh6N+/P3r06AEFBQWkpqbWKwg7c8N7ACgtLRUy23j79i1OnToFZWVldOvWDSwWC7///jvKy8ubFF0qKipiUg5jYmKQl5dXq5VAamQ6dhgdhEp3XSFxaD7dBU5LfWG/kAM9aVuweukx29cNN4XRNAcYTXGA+RwXmEx1wtqhZlDpoQMbBU/oS9tBTUIfOuOtYTrTCVbybjCf7gqXZYHQkDRmIoybRtvAW2MHft91DtEn41F45+EnRfEEbR0iIiIQHh7O9N4rKysTaveRnp6OpKQkoVTOhprFN1aH+OLFC2RnZzOmL9HR0Th69ChKS0uRmZmJsLAwfPvtt/D19YWxsTFWrFiBSZMmMW0YJCUlMWXKFLBYLFhaWmLbtm04duwYrly5gnv37uHt27d1ir3Hjx+jrKysLS9VSiejXSazlqdDCcK/33+AxsF4SHG40Pw6AX+//9DeQ6JQKJQOSc6jV5joxzfd+jIqr72Hw0AFYQeBNJJeevLkSYiJiWHlypW4ffs2LC0t0b9/fxw4cKDOlNHPseG9gKKiImzduhXjxo3DkCFD4OjoiLS0tCYJpYqKCty5c4dJKY2Li0NmZiays7MZU5PTx8/ATy8IG0aZYWWXDVgpxl/U+ujCYSEHdvM9YavIgclkNjT6GWJll03YMMwCzov9oTvWFjbynnBeEgD7ed7QG2cHmzmesJjpxkQXN46xBHulLw77HcPVs0koLXzUYqmcT58+RVFREfLy8nDz5k2kpKQgOjqaaa5e3aCleruPgoICRjA21XRG4PwaExODn3/+Gdu3b4ednR2MjY1haGiIgQMHQlxcHF26dMHw4cOxePFi6OnpgcPh4JtvvsGFCxdw8+ZNlJeX01ROSqvR3vNaC9GhBKHP2SxIcbiYsSUSJeWfV7YKhUKhtDT/d72YqSe8mvesvYcDgArCDgNpRBAqKChg1qxZmDp1KgC+CcuIESMwY8aMOk1lPveG9wD/Pbhy5QoMDAzQs2dPyMvL4+DBg3j0iC+sXr9+jRcvXtSKhNVlahIaGso0KI+JicHNmzdx//59PHr0CEX3HuKX4NPwVN4C3THWUBbfyIhDq5lucJjvDYcFPmAr+cJqphvWDjLB6r4GYC/yxYbhFlgzwBhOC32xz/owzn4Vhsy4W3j5/CVevnyJnJwcJrUzNTUVDx8+bFCIvXnzBs+fP0dxcTHy8/Nx69YtpKWlIT4+XiiVMzQ0FFFRUYiPj0daWppQ/8AnT54gPz8fCQkJCAkJwdWrV+uMlFYXe4I+gdeuXcOZM2dw4MABuLu7Q0dHB0pKShg7diy6desGQgiGDh2KOXPmYM2aNXBwcMDu3btx4sQJxMXF4Y8//oClpSVsbGza+/Kh/Edp52mtpegwgvBs+r83NjF3aN0ghUKhiILXmX9/SCt++Wd7D4cKwvZE1HrDf/75B+Li4jh8+DB69+4NDw8P5ObmQkFBAWJiYnW2nfivNLwHAB6Ph71790JFRQWDBg2CuLg4hgwZgq5du2L//v0IDw/H5cuX642ECWrr3rx5g8LCQiQmJiIkJASxsbHIz89nauAqyl/hwncXEbhuF+wVOdAfZwvlrpuwUmwD9MbagL3IF2aT2di8YQ+ObT6JmD8ScD+3SOTUzhs3biAsLAxhYWFITExERkYGk8p55coVhIeHM6mckZGRuHr1KlJTU5lUTkFLiYqKCpGje+Xl5cjNzcXly5fx888/Y8GCBbC3t4evry/MzMygrKyMKVOmQFJSkklrnjRpElatWgUzMzNs3rwZR44cQVRUFPLy8vDXX3/RyB6lQ9PO01pL0SEEYXZpBSb5RUCKw8W+Sx0n9YlCoVA6Om/fVUu1/yoeb9+1b6o9FYTtiKj1hqWlpSCEMDVeM2fORPfu3SEpKYlx48bV+dz+/v4YOHAgunXrBjk5OWhoaHyWDe8F6OjowMbGBsHBwQgODoaxsTGkpaUxYcIEBAQEIC8vr0lpl+Xl5Uz0LjQ0FNeuXUNJSQkjtBJDU7Hd4AAOexxD+NFo3E7NRUV5/Y6elZWVTKP3Bw8e4M6dO8jMzERKSgquXr0q5JrK5XKZSF94eDgSExNx9+5dPHr0CC9fvmxyKuebN29w//59xMXF4bfffsOuXbvg4OAALS0tzJ07F8OHD2dMWmbPno0+ffqge/fumDt3Lg4ePIhz587hxo0bKCsroz33KNi+fTvk5eUhISGBIUOGYM2aNbhzp/G+Sh3lO6Y957QWpN0F4bPXf2P+9ugOaY5AoVAonYHqZlwuJzPa9f6KCsJOQHVBWB0PDw8oKCjU2v/kyZPo3r07fvrpJ6F6w/nz5/9nGt4DwD///IMzZ85ATU0N3bp1w8qVK/Hzzz/j5cuXTRJUjx8/xo0bN8DlchEZGYlbt26hrKxMaL/Xr1/j2bNnePjwIfLz85GVlcWkckZFRTG1e1wuF9HR0UhISEBaWhqys7OZVM7nz58LOYFWVFQgLy8PMTExCAkJQVJSEvLz85lzC1I5nz59iuvXr+P8+fP46quvwOFwoK+vjyVLlkBaWho9e/YEIQSDBg3CzJkzoaGhAVtbW+zYsQO//vor4uLiUFRUhHfv3jG1e4mJifj111/b+yOkdEBUVFRw9OhRZGdnIzMzE2pqahgzZgwqKyvrPaYjfce097zWQrSrIPz7/Qes/SYBUhwulu2JQcVf79plHBQKhdLZibv7DOO9wyDF4eJQzL12GwcVhJ0AQcpozRpDIyMjaGpq1tpfQUEB9vb2zGNBveGiRYv+cw3vBZSWlmL79u2QkZHBwIEDYWtri+TkZJFFYVlZGYqLi5Geno5Lly4x/fUuXryIsLAwxqQlMjISsbGxSE1Nxc2bN5GXl4eioiI8ffq0yT0BBVHF3NxcXLx4Eb///js8PT3Rt29fTJw4EdLS0ujfvz8IIejVqxdkZGSwbNkyGBsbw8/PD99//z0uXryInJwcvHnzhkb2KK3Cs2fPQAhBbGxsvft0pO+Y9p7XWoh2E4Q8Hg9uH3tpTQu8iIJnb9p8DBQKhfI5cTypkKnFvnT7SbuMgQrCToKCggIcHByYx1VVVRg5ciR27NghtF9D4nHw4MH/6Yb3AP9mJj4+HiYmJujduzdmzpyJrVu34vz58/juu+8QHR2NzMxMJCcn10rljIiIQExMDJKTk5GWloaEhASEh4cjNDQUqampKC0tFTmdU5DKWVRUhMTERJw8eRJ79+4Fm83G+vXrMW/ePIwaNQpdunRBly5dMHLkSMybNw/r16+HiYkJFBUV0atXL+jo6ODp06c0lZNSJ7GxsdDQ0MDw4cMbNa4CmteuJj8/H4QQ3Lp1q959OtJ3TDtOaS1JuwnC72MLIMXhYpwXF7EdxB2PQqFQOju+5/gmM3L+Ech51Pbf7VQQtiNNuYE/efIkevTogWPHjiEnJwdWVlbo378/njzh/5IgMKARpJey2WycP3+ecaKcM2cOCCH/+Yb3AoyNjTFhwgR0794dhBD07t0bo0ePRmBgIJPKee/ePZSUlODFixf1NnWvrKxEaWkp0tLSGGfPEydOICcnB8+fP0dGRgZCQ0Nx6NAh+Pj4wNDQEMuWLYOsrCx69+4NQggGDBiAadOmQVVVFdbW1ggODsbx48cRExOD+/fv4++//67zWvnzzz9RUlLSDu8epbMQHh4OX19fnD17tkmCUNR2NVVVVVBXV8fChQsbfN6O9B3TfjNai9IugvBi9mOM8+JCisPFTwn32/TcFAqF8jnz7kMV9H5IhhSHiwU7LuPp67eNH9SCUEHYifjqq68wZswYdO/eHQoKCkhJSWG21TSgsbOzY+rHBg4ciNGjR2PSpEl1Pm/Nm7WysjIsWbIEhBD069cPZmZmePOm4bQgY2PjWlGFjpxyKqgHzM3NRWVlJXJzc+Hu7o4vvvgCo0ePho+PD3JychrsuXf37l1cvnwZx44dQ3BwMOzs7MBmszFv3jyIi4uDEIKuXbti/PjxWLx4MQwMDODt7Y1Dhw6By+Xi1q1bePXqFe25R2kTSBMEoajtamxsbCAlJYXi4uIG96OCsMVpc0GYVlgGWV9+M2WvM1n0O4tCoVBamPI//8HSPTGQ4nCh9r84vH7bdvXZVBC2IYIJ9N69e/j2228RGhoqtB4Abt68KZJjX300td4QqJ3OxWKxMHr0aPTp0wfx8fGYMGECdHV1GzyvsbExWCyWUFTh5cuXzX4d7cW7d+8QEhICTU1NdOvWDQsWLIChoSFcXV2xadMmLFy4EFJSUujatSsIIRg2bBjmzp2LtWvXwsnJCXv37sWpU6dw5swZuLu7Q1paGvfv01/SKQ3T1NROoOmunaI8b1Pa1djb22PUqFEiXd80ZbTFaVNBmP/0NeOEZ37sGt5/qDtiTKFQKJRP48GLSszeeglSHC70fkjGP+/b5vuWCsJ2YNu2bfjtt9+goqIi5LJ36tQpyMjIoGvXrpgzZ06zfzkXtd5QgKenJ9PwPicnh4nuCSJ8EREREBMTQ2lpab3nNDY2xpo1a5o13o7K48eP4erqiuHDh8PCwgJbt27FTz/9hMuXLyM/Px9v375t9Fdy+is6RRSamtrZHNdOUZ73zp07OHz4MK5fv47ExESYmprWalfD4/Fgb2+PESNG4O7duyK9vurfMQJ0dXWpqUzzaTNB+OTVWyzYcRlSHC7WfJ2Av/5p315ZFAqF8rlzs7gccv78Hq9OJ9JR1QZtfaggbEOqqqrw8OFDuLu7o7CwEL///jsj+qqqqiArK4v169cjOzsbGRkZzT6PqPWGAgQ3lx4eHggKCkKvXr2Ebi7fv38PcXFxnD17tt5zGhsbQ1JSEkOGDIGsrCxsbGzw4sWLZr8GCqWj8vXXX0NKSgo9evSAgoICUlNT6923OSYtRATh1hzXTlGety4E6c4CbG1tISkpiatXrwplBFT/Aauh75jc3Fx88803tO3Ep9EmgvDV23dgHYiDFIeLpXtiUFb5T6uej0KhUCh8ruY9g/THdhRB3Nutfj4qCNsAQZTo0qVLiI2NxY4dO3DhwgWUlZUx+8THx6Nr1664fbtlPnRR6g2rI2h4Ly4ujm7dutVKPxsyZAgOHTpU57mCgoIgIyOD7t27Q0JCAufOnYOcnBzmzp2LDx/q/jWZx+PB398fw4YNQ8+ePbFixQqRow0USntRX4/Pp0+f1rl/U01aANGEW3NSMEV53rpwd3cXaldD6hC4hBCh74yGvmO6d++O8ePH08b0n0arC8LKv98zvQbnbItC0Ys/W+1cFAqFQqnNmRvFkOLwjby+vpLfqueigrCN4PF4CAwMxOvXr7F161Y8fPhQaLu2tjaUlJTwzz+1f4EVCMqqqqp6BVZjcDicem/kBEtubi6Cg4MhKytb6/iGBGFAQAD2798PV1dXSEpKAgAKCgrqdTUFgJ07d0JSUhLnz5/HzZs3oampiXHjxuHt27Z1VaJQmkJ9PT7rS8duqkkLIJpwa45JiyjPWxcrV66ss11NZ6VdJrOWp1UF4dt3H6DzXTLTazC7tKJVzkOhUCiUhhG0+pHicPFDXEGrnYcKwjaAx+MhPT0dgYGBuHHjBn788UcAQFRUFBYtWoRNmzZBTEwMISEhQscI+PDhQ62bPEGE4caNGzAyMkJaWlqDY3j27Blyc3MbXP755x8cOXIE/fv3FzpWlJRRADh69CgjCAFg8ODBOHz4cJ3vx7Bhw7Bnzx5mXUVFBXr06IETJ040eA4KRVSaktoJNG7S0hzDpqaYtAggLSgI37x5g4yMDGRkZIAQgv379yMjIwNFRUUAaqd2fvnll0LtathsNrp06VLvDzudkfad1VqMVhOEf7//AOOfUiHF4WJKwEVkPBT9xwwKhUKhtDwHou4yovDnpMJWOQcVhG1ASEgI8vLysHXrViQlJaGigv9r6/Pnz6Guro5JkyYhJiamzmNjY2Ph5OSEhQsXYtmyZThz5ozQ9rKyMqirq0NaWhpXr1795LEKTGWuX7/OrIuMjGzUVAYQFoTFxcW1RK4AQfSwZp3k4sWL4eTk9MmvgUJpamqnKCYtgpYuSUlJQsd6eHhAQUGhzucVxaSlJqQFU0brq2E0NjYGUDu1c9euXULtapYuXYorV640OJbORrtNaC3LpwvCd2+BzBPASX3gJzXgpD7ep/8Gu2OJkOJwMdEvHKn3yxp/HgqFQqG0KjweD7sichlReOraw8YPaiJUELYyFRUVsLS0hI2NDRwdHWulfObm5qJfv344deoUs04QHczLy8O8efOwadMmREVFwdPTE+PHj4e2trbQjcCDBw8wcuRIBAcHCx3fXFgsFmbNmoXU1FQkJCRARkamVtuJiRMnMhHDN2/ewN3dHX5+fujbty+io6Mxe/ZsyMjI4O+//671/ImJiSCE4NGjR0LrN27ciE2bNn3S2CkUoOmpnaKYtDRHENZFTZOWmhARTWU6imtnZ6Odp7WW4tMEYW4YsGMMENgP2NwfCOwH3sd/ywOGw8pvG+LvPm/ZN55CoVAozYbH42HLhduQ4nAx1ouL02ktKwqpIGwDeDweYmJikJiYCABChhJ37txBly5d6nQVTU5OhqysLL7//ntmXXp6Or777juh/W7evImuXbvW+fzNoaysDHJyco3WHApS1v766y8oKyujb9++THqcpaUl42paEysrKxBC0LNnT6EU04YEYWdrfE9pHmVlZdDT00Pfvn0hKSkJMzMzvHnzpsFj6ro2xMTEPqkXJ1A74taclNG6qGnSAjQ9tbMjuXZ2Ntp4Gmstmi8Ic8OAQMmPS79aS1VAP/ACJfn7USgUCqXDwOPx4Hsui4kU/pL8oMWemwrCVqaxaJ27uzvk5OTw55+1HdzevXsHNzc3zJgxA8ePH2fWV4+6VVVVwcfHB6NHj265QUP0msPq1KwhrA9HR0cQQmBgYCC0f0Mpo59L43tKw7BYLMyYMQMpKSmIj4/HhAkTakWna1Lz2hCIqqZE8kStyWtqj8+6qMukpampnYJjOoJrZ2ej/Wa0FqV5gvDd24+RwbrF4L+LJH+/d9Tki0KhUDoSPB4PgSHZjCj8Mf5+izwvFYRtRE1hKHg8bNgwJtVTkE5aUlLCuBK+e/cOe/fuhbS0NGNGU5MJEybA19dX6DnaA1EFocBURltbm9n/1atXDZrKfI6N7zsrQUFBmD9/Pnr16iXS5w2I1mZEUL9a3SApIiKi0frVmtdGc1I7RRWETe3x+V8waelstPO01lI0TxBmnmhECNZYMk+2zodAoVAolGbD4/Gws1pNYUu0pKCCsB15+PAhJCQkarl37tmzB35+fkLNq3V1dbFw4cJaz/HmzRuMHTsWP/zwQ6uPtz6KioqQkZGBLVu2QEJCgkl9q57qV73mEOC3nejduzd69+6NrKwsrFmzpsG2E7TxfcehrjYjjSFKm5HmOtzWvDYsLS2bnNrZlL5+Tenx+V8waelstPe81kI0TxCe1GdqBhtdNvfn70+hUCiUDgePxxNyH03M/7S6byoI25EXL15AW1sbYmJiOHbsGHg8HqqqqvDHH39g0qRJmDBhAoKCghAUFITevXsjODgY7969A/BvnWBKSgr09fXRtWtX/Pbbb+3yOuqq4SKECDmnkhqNq3k8HjQ1NSEmJoYePXpgxYoVyMvLq/ccJ06cQEhICLKyskRqfE9pfZoaEW6szUhzemACdV8bffr0qWUq01BqJzVp+e/QnnNaC9I8QfiTWtMihEfVWudDoFAoFEqL8O3Ve9genvPJhpJUEHYATp48icuXL9daf+TIEaiqqsLKygpHjhyptf3x48cYPHgwVqxYARsbmzr3aStEbXxfHVEERWFhIczMzDB27Fj07NkT48ePR0BAAHJzcxtsfC9KiuLnTHPSOptq3COqILS2thbp2miuIKyJoK1Jt27dRE7tbAmTlg8fPiArKwsJCQn1GipR2p+2nMNaERohpFAoFEqLQQVhO1KfG2jNqJcgKggI1yJ++eWXGDBgANPXsD1pLROaiIgImJiYIDIyEgUFBQgJCcHQoUPh5uZWb+N7QLQUxc+Z5qR1NtW4R1RByOVyQQhBbGys0PWgoqICFovFXBvNTRmti8GDB0NbW1vk1E7g001akpOTMXjwYAwdOhQbNmwQ+ruldBzae15rIWgNIYVCoVBaDCoIOzAfPnyoNwT88uVLKCgowMrKCsCnt5poD0QVFDXZvXs3Ro8eXW/je1FTFP8LiPoet1aEFxC976TAVOb69evMusjIyEZNZWpSXFxc77UhKllZWTAxMcHQoUNx69atWts/fPiA9+/f48OHD8zfnuDfU6dOQUxMDJmZmc0+P6X1aK/5rIWhLqMUCoVCaTGoIOxE8Hg8xMfH48yZM9i/fz/ExMRw+/ZtZltnoakmNILG98nJySgsLISenh569+5db+N7Qcpgzd6ODbW1aEvqS4OtGUGtSXPSYEUVbc+ePYOWlhYkJCQwYMAAjB07Ftra2khOTv7kNiNN+TxYLBZmzZqF1NRUJCQkQEZGplbbiYaujejoaMyePbvea4PH4zEirqqqql73340bN2Lu3Lk4cuRInS1hGuLZs2cYMWIEU9Pbmf42/wu097zWQjS/D+Gd8Ab7EDLb7oS3/JtPoVAolA4JFYSdCB6Ph19//RVdu3bFqFGj4OrqCqDzRQebakIjaHw/ZMgQdOvWDWJiYli0aFG9dVqiRqTai4bSYBuiOWmwTYnCNtW4p6mmMnv37mXW1ddmpKysDLq6upCQkEC/fv1gampaqzF9Q9eGlJQULC0tm13DJ3itEydOhLOzc537vH79Gr/88gt0dXWhpKQELS0toWhgRUUFpk2bxrSxeP/+fbPGQmkd2m9Ga1GaLwgBftP5HWP+rRWs/u+OMVQMUigUyn8MKgg7KY8fP0ZlZSWAzicIgealKJaUlEBaWhrm5uYNPndHF4R1sXv3bowbN67e7TweD3369Gm1tM66EET2ahr3NLfNSP/+/RnB2VibkdagoqICly9fxt69e+Ht7Q02mw1tbW1oamoiISFBaN/ly5fD1ta2zuf56quvsHjxYrDZbOzZswdbt25Famqq0D6amppCbWJolLDj0NbzWCvxaYIQ4KeDZp7kG8ccVeP/m3mSpolSKBTKfxAqCCntQlNNaEpLSyEjIwNDQ8NGBXBHTxmtC19fX8yZM6fe7YLXdPbsWaH3SF5eHgYGBp+c1lkfdRn3NLfNiL+/P7744guR2oy0JAIxxuVy4ebmBnNzc/j5+aGgoACpqan4/vvv8c033wjVLlpaWoLFYjGPq7d5UVRUxPHjx5ltb9++rXVNhoeHQ0lJCbKysh32mvuv0n4zWovy6YKQQqFQKJSPUEFI6fCUlJRARkYGOjo6IvUdbEqKYkcgPz8f/fr1w/fff1/vPs2Nen6KIGwJc5aOgEAQXrp0Cd9++y2ys7NRWFgIAMjMzMS5c+eQnZ0t1MdTR0cHs2bNAgChWsPU1FTMmjULBgYGOHv2LIqKiuo859OnT6Gqqoo5c+bgxIkTNELYgWjvea2F6EcIQXFxMV69ekUXutCFLnShyyctxcXFHVcQUiiEkJGEkHxCSPTH/w+rtlTnDiFkbbXHHEJIOSFEkxAyjRBynhBynxDSsxXHupM0ktJJCJlU45iRhJB7hJAfG3nuBR+PH15j/WlCyKk69h9DCJlJCAkghLz5+P+ZhBCJavtUf88kCCF7CCHzCCFjCSErCCE3CCF3CSE9GhlbZ2EmISSQEGJFCBH7uG4CIcST8F/vDMK/rnYTQq4TQgzqeI6ehBALwr8ewwghtwj/M6h5XSkRQniEkMkt+gooFD4jSePfNXShC13oQhe6NHUZSSiUDogJqf+irQ4+7itAjBCylRDyhBDyN+HfwMu27lDJEMIXfA0t3avtP4LwBdfPhJAujTz3eMJ/jTNrrI8lhPyvjv2Pkbrfs6XV9qn+nvUihEQSQp4RQt4RQh4QQr4nhHzRyLg6C5KEkA2EEHlCiG+19VKEkHDCv1YIIWQ1ISSPEFJICDn4cZ0YqZsphBB1whd+y2psW0EIeU/47yuF0tKIEf6k3a8FFoG4bKnna6uFjpuO+3Med2ceOx135x33SFL/PQ+FQmkFRhK+GDxBCBEXYX8xQshjQohbtXX9CF/s6rT46D4/ehO+6BtICIkihGwjhHxDCEkmtSOBYoQQY8IXemNqbOtPCBlQ7fESwhfQ0jX2m0b4z/rKeAAACGBJREFUgrC1f4SgUD6VfoR/M9GvvQfSROi42xY67rans46djrtt6azjplD+83SmNNjPiS2EHyUMJPy00d8IP0KqRWqL8j6EkLeEENUa6z0IIT8QQr4jhPxBCEkhhFjWcfx4wheECz4+pr+4UToqnfVmgo67baHjbns669jpuNuWzjpuCuU/jwnpPGmwnwtDCSHKhJD9hJDBH9c5E0JkCCFOhJDR1fYVI3yBV0r49YKCdYTwBeJhwheT2wghLCKcBixOCBlH+Om2JYSfolr9eAqlo9FZbybouNsWOu62p7OOnY67bems46ZQKJQ2R4fw6/oOkX+NfSQJ30gnmxCyj/wboRXUc94ghBxv4nn6EUJ+JfwaTGvCjzRSKB2ZHoSQzaTzmUfRcbctdNxtT2cdOx1329JZx02hUChtjiHhG+24EL75j4AhhF8XWB1B+qcDIeQp4dcSCkxnBNHDrh//rcsMSJSaUAqFQqFQKBQKhUKhdGAkCD/lU4XwW3E0BYFwpFAoFAqFQqFQKBRKB6ALaby9B4VCoVAoFAqFQqFQKIQQagZDoVAoFAqFQqFQKBQK5TNgLCHkCCGkkPDbqhQQfjuW7g0cQ8i/DsePPx4XTfgOvW2JLyEkiRDyFyGkQsRjjpHaTs4XW2NwjdCcsXeE93wg4Tsqvyb8cR8h/FT6hjhG2v49///27izUqjIK4Pg/kUKQwiIqjSCRbNYy1ErqRBDaQ8NL9dbJiGh4CMrUHoIgaAajQYqyU4END1E0WBhkIZSNQhQlBUYWZjSYRdlkD+tc3Hd7hr2Pd+/zpf8fXHBP18W6h8te99t7rWuIRl5/AOuA2X3ObwAfAtuBLxjdzbtOZeJu0LkzeX5cVdXOAF4Evm3//xcUuKbB8PNdNu4GaeR7KfAesA3YQowbm17gugbDz7kkSUrQfOAxYgTLVGKm6XfA3X2uW0wUBOcDJwIvUP8M1FuIplD3UK4gXMXoWa+Tqgiuj0FiTyHnq4D1wBxgHjE/d2Wfa1rUm/OLiZvey4BjiZE/PxGjhjo5EviN+FkcQzQP+5t4V7xOZeNuEAXJUYzObd2vQSwAbiVmJBcprFLJd9m4G6SR71eJYu44YAbwMvAVvTuYp5JzSZL0P7GIKDS62YdYpbohs+8AYlXjkgrj6qZJuYLw+coiKa9JsdhTyPkxxA3xKZl984muy5N7XNei3pyvA+7PbI8jZsgu6XL+HcSooaynqX/luGzcDeLnke+KPUxFCqtU8p1VpiBMKd8QndF3ECue3aSYc0mSlLBbgfd7HJ9K3IDMzO1/E7i3qqB6aFKuIPyZeNTqc2A5cFAlURXTpFjsKeR8IbFilTWeWGm4sMd1LerL+b7tePI3948TK6qdvAUsy+27DNg6tqH1NEjcDeIzsZH4Y8Fq4PRqwiusSGGVQr7zyhSEG0kn3wDTiLiO73FOijmXJEmJmkbcJFzR45zTiBuQw3L7nwWeqSiuXpoULwgvIR6LPYG4AfwUeJfhjYRpUiz2FHJ+E1HQ5W0BrupxXZ05n0zk6dTc/juJFbhONhDvZWWd2/4+E8Y0uu4GiXs6cCUwi/h8rAD+Ak6uKMYiihRWKeQ7r0jcKeZ7HPASsLbPeSnmXJIkVex2OjdAyH4dnbtmCtFs4JE+37vK4mSQuJsULwjzRlbezh7w+qwqY08h54MWhHljmfO8vakg7ORN4MmxCmoAe3JB2Mmw872cWLE8vM95KeZckiRV7GDiJr7XV7aT6GTipuEJ+jdJqPLxxbJxw+4VhADfE3/5311Vxp5Czgd9ZLSTscp53t70yGgndwFvj1VQA9iTHxntZJj5vh/4mmgY00+KOZckSQmZQhSDT1HsMb6RBifXZ/btz/+jqUze4URTlPPGLJpympRrKjPMnI80lZmV2XcO/ZvK5FWd83XAfZntccAmejeV+Ti3byXDaSpTJu5OVgPPjWVQJRVtKpNCvrMGLQiHke99iGLwG4qPnUkx55IkKRFTiNEBr7f/nW2nnvUZo1eBFhOrRSPvhj1P/SMQjiBWzG4mZnLNbH9l5+Jl455I/EV/LjF/8WzgA6IY3q+WiHcqGzukkfNVxCyz2URDjQ3sOnZi2Dm/mCiULyWK2IeIvB3SPn4bsRI+YqQl/53EaujVDG/sRJm4ryNGkEwjGoosA/6hmkdxe5nIzs/vDmKcykziMw7p5rts3Knk+0Hij0hnMvr3dfbRz1RzLkmSEtSk+3tjWTsYPch4ZEj6ZuIm9nViPledWnSOu5E5Jxv3BOA14p23P4l3bx5m5w13nVqUix3SyPmBRAG4jXjcbAW7DqZPIefXErPZthMrb3Myx1rAmtz5DeCj9vlfMryh3WXivpF45/d34AfgDeCsOoLMadD5s9xqH2+RZr4blIs7lXx3+33dzJzTIs2cS5IkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkaS+1HFjb5dgmYEmNsUiSJEmSanIc8A9wWpfjq4Gn6wtHkiRJklSXFvBOj+PPAGtqiUSSJEmSVJvxwC/Aosy+h4DLM9uvAKvqDEqSJEmSVL3pwA5gfnt7HPAjcFHmnE3APTXHJUmSJEmq2ByiIJzX3l7Q3j6vvT03d1ySJEmStIc4FPgXeAA4CfgEeAl4tL29nmgqI0mSJEnaAy0FtgKbgYXADGAj8CvwFDBpaJFJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJktTXfxaRH44Wvxr5AAAAAElFTkSuQmCC\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "365e49b79bf04f9294998c75ada3d820"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the magnitude of the transfer function as a 3D graph\n",
    "fig = plt.figure(figsize=(9,3))\n",
    "\n",
    "# plot of transfer function\n",
    "ax1 = fig.add_subplot(1, 2, 1, projection='3d')\n",
    "ax1.plot_surface(X, Y, np.minimum(np.abs(tr_f),2), cmap=cmap)\n",
    "tr_f_imag = transfer_func(np.zeros(im.shape) + 1j* im, n, p)\n",
    "ax1.plot(np.zeros(im.shape) , im, np.minimum(np.abs(tr_f_imag),2), color='red')\n",
    "ax1.set_xlabel('$\\mathbb{R}\\{s\\}$')\n",
    "ax1.set_ylabel('$\\mathbb{I}\\{s\\}$')\n",
    "ax1.set_title('Magnitude transfer function $|H(s)|$')\n",
    "\n",
    "# plot of frequency response\n",
    "w,h = freqs_zpk(n,p,1,im)\n",
    "h = np.abs(h)\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "ax2.plot(w,np.abs(h))\n",
    "ax2.set_xlabel('$\\omega$')\n",
    "ax2.set_title('Magnitude frequency response $|H(j\\omega)|$')\n",
    "\n",
    "# get the moving orange dot\n",
    "point_plot, = ax1.plot([0],[im[0]],[np.minimum(np.abs(tr_f_imag),2)[0]],'o', markersize=8)\n",
    "point_plot2, = ax2.plot([im[0]],[h[0]],'o',markersize=8)\n",
    "\n",
    "def plot_point(i=0):\n",
    "    point_plot.set_data([0], [im[i]])\n",
    "    point_plot.set_3d_properties([np.minimum(np.abs(tr_f_imag),2)[i]])\n",
    "    point_plot2.set_data([im[i]],[h[i]])\n",
    "    plt.draw()\n",
    "\n",
    "widgets.interact(plot_point, \n",
    "                 i = (0, im.shape[0]-1, 1))\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}