Chapter 7 Trial and Error Searching and Data Fitting.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chapter 7: TRIAL-AND-ERROR SEARCHING AND DATA FITTING"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](1.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](2.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](3.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](4-copy.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TASK: CHAPTER 7: IMPLEMENTATION: BISECTION ALGORITHM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](4a.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](05.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TASK: CHAPTER 7: IMPLEMENTATION: NEWTON-RAPHSON ALGORITHM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](5a.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](6.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](7.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# IMPLEMENTATION: NEWTON-RAPHSON ALGORITHM EXERCISE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](8.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LET'S CODE!!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7.2.1 Implementation of Bisection Algorithm and Newton Raphson Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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       "\n",
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       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "'In mathematics, a singularity is in general a point at which a given mathematical object is not defined, \\nor a point where the mathematical object ceases to be well-behaved in some particular way, \\nsuch as the lack of differentiability or analyticity. For example, the real function f(x)=1/x \\nhas a singularity at x=0, where it seems to \"explode\" to plus/minus infinity and is hence not defined '"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Page 144 Implementation: Bisection Algorithm\n",
    "import matplotlib.pyplot as plt\n",
    "from numpy import *\n",
    "from scipy import interpolate \n",
    "%matplotlib notebook\n",
    "\n",
    "#TASK 1&2: Visualizing the function\n",
    "#The function to call tangent\n",
    "def ftan(x):\n",
    "    return sqrt(10-x)*tan(sqrt(10-x))-sqrt(x)\n",
    "\n",
    "#Lets write the bisection method function for tangent\n",
    "def bisection_tan(xplus, xminus,n,eps):\n",
    "    for i in range (0,n):\n",
    "        x = (xplus+xminus)/2\n",
    "        print(i,x,ftan(x))     #This is where you had a mistake of f(x) instead of fb(x) so it was making your code run wrongly\n",
    "        if (ftan(x)*ftan(xplus))>0 :\n",
    "            xplus = x\n",
    "        else :\n",
    "            xminus = x\n",
    "        if abs(ftan(x)) <= eps :\n",
    "            print(\"The root is found with a value: \",x,\" with a precision = \",eps,ftan(x))\n",
    "            return x\n",
    "        if i == (n-1):\n",
    "            print(\"The root is not found\")\n",
    "a = 6\n",
    "b = 9.9\n",
    "eps = 1e-6\n",
    "n = 100\n",
    "E = arange(a,b,0.05)\n",
    "\n",
    "#Computing the root if it available (but remember tan has some singularities around the y-axis as x=0, tan(x)=sin(x)/cos(x))\n",
    "#it approaches infinity\n",
    "root = bisection_tan(a,b,n,eps)\n",
    "\n",
    "#Lets visualize the function by plotting\n",
    "plt.plot(E,ftan(E))\n",
    "#plt.plot(x,f(x))\n",
    "plt.grid()\n",
    "plt.title(\"A plot of Tangent function with some singularities\\n\")\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"ftan(x)\")\n",
    "plt.show()\n",
    "\n",
    "\"\"\"In mathematics, a singularity is in general a point at which a given mathematical object is not defined, \n",
    "or a point where the mathematical object ceases to be well-behaved in some particular way, \n",
    "such as the lack of differentiability or analyticity. For example, the real function f(x)=1/x \n",
    "has a singularity at x=0, where it seems to \"explode\" to plus/minus infinity and is hence not defined \"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 5.05 -3.947659005508041\n",
      "1 7.475 -1.6388679972355598\n",
      "2 8.6875 0.18886649385546406\n",
      "3 8.08125 -0.8514113725772324\n",
      "4 8.384375 -0.37624073255891777\n",
      "5 8.5359375 -0.10756491540889468\n",
      "6 8.61171875 0.0367493739955882\n",
      "7 8.573828124999999 -0.03632317901496518\n",
      "8 8.5927734375 -2.282778231332827e-05\n",
      "9 8.60224609375 0.018303372853979427\n",
      "10 8.597509765625 0.009125413952056016\n",
      "11 8.5951416015625 0.004547592855873361\n",
      "12 8.59395751953125 0.002261459272811406\n",
      "13 8.593365478515626 0.0011190851528699586\n",
      "14 8.593069458007813 0.0005480710651004639\n",
      "15 8.592921447753906 0.0002626072398346224\n",
      "16 8.592847442626953 0.00011988612880720062\n",
      "17 8.592810440063477 4.852827331447429e-05\n",
      "18 8.592791938781739 1.285002052453521e-05\n",
      "19 8.592782688140868 -4.988937139405181e-06\n",
      "20 8.592787313461304 3.93052763314472e-06\n",
      "21 8.592785000801086 -5.292082683183708e-07\n",
      "\n",
      "The root is found with a value:  8.592785000801086 \n",
      "\n",
      "With a precision =  1e-06 \n",
      "\n",
      "The residue f(x)= -5.292082683183708e-07\n"
     ]
    },
    {
     "data": {
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       "        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",
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       "        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",
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       "    this._init_canvas(this);\n",
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       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "#The function to call cotanget of x...\n",
    "def fcot(x):\n",
    "    return sqrt(x)*(1/(tan(sqrt(10-x))))-sqrt(10-x)\n",
    "\n",
    "#Lets write the bisection method function for cotangent\n",
    "def bisection_cot(xplus, xminus,n,eps):\n",
    "    for i in range (0,n):\n",
    "        x = (xplus+xminus)/2\n",
    "        print(i,x,fcot(x))     \n",
    "        if (fcot(x)*fcot(xplus))>0 :\n",
    "            xplus = x\n",
    "        else :\n",
    "            xminus = x\n",
    "        if abs(fcot(x)) <= eps :\n",
    "            \n",
    "            print(\"\\nThe root is found with a value: \",x,\"\\n\\nWith a precision = \",eps, \"\\n\\nThe residue f(x)=\",fcot(x))\n",
    "            return x\n",
    "        if i == (n-1):\n",
    "            print(\"The root is not found\")\n",
    "\n",
    "#If you set a about -30, a=-30, b =9.9, you can clearly see where the curve cuts twice the x-axis about x=0.004 or less\n",
    "#if you zoom further and at x=8.5927 \n",
    "#but lets adjust the a to be small\n",
    "a = 0.2\n",
    "b = 9.9\n",
    "eps = 1e-6\n",
    "n = 100\n",
    "E = arange(a,b,0.05)\n",
    "#Computing the root using the bisection cot function\n",
    "\n",
    "root = bisection_cot(a,b,n,eps)\n",
    "\n",
    "#Visualizing the function of cotangent\n",
    "plt.plot(E,fcot(E))\n",
    "plt.grid()\n",
    "plt.title(\"A plot of Cotangent function without some singularities for the larger root\\n\")\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"fcot(x)\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 0.020050000000000002 4.9252694578922895\n",
      "1 0.010075 2.0961859453179494\n",
      "2 0.0050875 0.4258267843396437\n",
      "3 0.00259375 -0.6502909751849328\n",
      "4 0.0038406250000000003 -0.07543671392108564\n",
      "5 0.0044640625 0.1821603595067467\n",
      "6 0.004152343750000001 0.05531495287079524\n",
      "7 0.0039964843750000005 -0.009541690805440428\n",
      "8 0.0040744140625 0.02301233299078076\n",
      "9 0.004035449218750001 0.006767242931943862\n",
      "10 0.004015966796875001 -0.0013791801115088376\n",
      "11 0.004025708007812501 0.0026960343855533253\n",
      "12 0.004020837402343751 0.0006589288747278488\n",
      "13 0.004018402099609376 -0.0003600000594308206\n",
      "14 0.004019619750976564 0.00014949578178669043\n",
      "15 0.004019010925292971 -0.0001052442933491271\n",
      "16 0.0040193153381347674 2.212770536935693e-05\n",
      "17 0.004019163131713869 -4.155780362768979e-05\n",
      "18 0.004019239234924319 -9.714926586301686e-06\n",
      "19 0.004019277286529543 6.206420035681504e-06\n",
      "20 0.004019258260726931 -1.754245614549177e-06\n",
      "21 0.004019267773628237 2.226089125478836e-06\n",
      "22 0.004019263017177584 2.3592223419299785e-07\n",
      "\n",
      "The root is found with a value:  0.004019263017177584 \n",
      "\n",
      "With a precision =  1e-06 \n",
      "\n",
      "The residue f(x)= 2.3592223419299785e-07\n"
     ]
    },
    {
     "data": {
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       "        return MozWebSocket;\n",
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       "        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",
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       "        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",
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       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
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       "    this.root = $('<div/>');\n",
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       "    this.root.attr('style', 'display: inline-block');\n",
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       "    $(parent_element).append(this.root);\n",
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       "    this._init_toolbar(this);\n",
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       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Duplicate of the code to show the smaller root\n",
    "\n",
    "%matplotlib notebook\n",
    "a = 0.0001\n",
    "b = 0.04\n",
    "eps = 1e-6\n",
    "n = 100\n",
    "E = arange(a,b,0.00001)\n",
    "#Computing the root using the bisection cot function\n",
    "\n",
    "root = bisection_cot(a,b,n,eps)\n",
    "\n",
    "#Visualizing the function of cotangent\n",
    "plt.plot(E,fcot(E))\n",
    "plt.grid()\n",
    "plt.title(\"A plot of Cotangent function without some singularities for a small root\\n\")\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"fcot(x)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 \t 9 \t -1.4425922753450977\n",
      "1 \t 8.462189102355724 \t 0.7030563101025789\n",
      "2 \t 8.568554073487059 \t 0.11796190478986723\n",
      "3 \t 8.592214175153929 \t 0.0027227779584038103\n",
      "4 \t 8.592784925464331 \t 1.6667135120940202e-06\n",
      "5 \t 8.592785275229708 \t 6.217248937900877e-13\n",
      "\n",
      "\n",
      "The root is found =  8.592785275229838 \n",
      "\n",
      "The residue f(x)= 3.552713678800501e-15 \n",
      "\n",
      "With precision=   1e-13\n"
     ]
    }
   ],
   "source": [
    "#task 2\n",
    "# Newton Raphson Method for finding the root\n",
    "\n",
    "%matplotlib notebook\n",
    "def f(x):\n",
    "    E = sqrt(10-x)*tan(sqrt(10-x))-sqrt(x)\n",
    "    return E\n",
    "x = 9 ; dx = 3e-1 ; n = 300 ; eps = 1e-13      #eps = 0.00002    #eps=0.2\n",
    "\n",
    "\n",
    "for i in range (0,n+1):\n",
    "    F = f(x)\n",
    "    if abs(f(x)) <= eps:\n",
    "        print (\"\\n\\nThe root is found = \",x,\"\\n\\nThe residue f(x)=\",f(x),\"\\n\\nWith precision=  \",eps)\n",
    "        break\n",
    "    print(i,\"\\t\",x,\"\\t\",f(x))\n",
    "    \n",
    "    df = (f(x+dx/2)-f(x-dx/2))/dx\n",
    "    dx = -F/df\n",
    "    x += dx\n",
    "    if i == n :\n",
    "        print(\"root Not found\")\n",
    "\n",
    "# No need to plot the tan function again \n",
    "#x = arange(6,9,0.01)\n",
    "#plt.plot(x,f(x))\n",
    "#plt.grid()\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the root is equal to the value=  1.013663545694694 \n",
      "\n",
      "with precision eps= :  0.2 \n",
      "\n",
      "The residue F = 0.04384595822041604\n"
     ]
    }
   ],
   "source": [
    "#Newton Raphson method\n",
    "%matplotlib notebook\n",
    "def f(x):\n",
    "    return 2*cos(x)-x\n",
    "x = 4 ; dx = 3e-1 ; n = 100 ; eps = 0.2\n",
    "for i in range (0,n+1):\n",
    "    F = f(x)\n",
    "    if abs(F)<=eps:\n",
    "        print(\"the root is equal to the value= \",x,\"\\n\\nwith precision eps= : \",eps, \"\\n\\nThe residue F =\",F)\n",
    "        break\n",
    "    df = (f(x+dx/2)-f(x-dx/2))/dx\n",
    "    dx = -F/df\n",
    "    x += dx\n",
    "    if i == n:\n",
    "        print (\"root NOT found\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7.5 Problem 3: FITTING AN EXPERIMENT SPECTRUM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Fitting Using Lagrange polynomial Function and Spline (Page 150)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](10.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](11.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](12.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](13.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](14.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LET'S CODE DATA FITTING"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](lagrange.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter the value of E whose P is needed=200\n",
      "4.7\n"
     ]
    }
   ],
   "source": [
    "#Task 1 \n",
    "x= array([0,25,50,75,100,125,150,175,200],float)     #E, Energy\n",
    "y= array([10.6,16.0,45,83.5,52.8,19.9,10.8,8.25,4.7],float) #g, Cross-section scattering\n",
    "\n",
    "l = len(x)   #length of the data\n",
    "n = l-1 #polynomial degree\n",
    "xp =float(input(\"Enter the value of E whose P is needed=\"))\n",
    "P =0     #P capital initialize\n",
    "for i in range(n+1):\n",
    "    p=1   #initialize the product\n",
    "    for j in range(n+1):\n",
    "        if j !=i:\n",
    "            p *= (xp-x[j])/(x[i]-x[j])\n",
    "    P +=y[i]*p\n",
    "\n",
    "print(P)   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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hx1x7mRnUI1togztm5voFDJwyOQ6r1xwY4DvqKOOcmwj28sFHAbXpk+fXqgdtNu0WQyE0lGkI01bwr7+8ssvzvFnBiLjF7b4O/aRY3XEEUc49xeRM4NwZMtgsc3uDS9zWDIiIALZIWATiGNA6p///KcT8OL1BNQZDE4x0MaAPXV//Lc6W8xAWqdOnbB582ZH13JxhDqfeo1Bey5eJOoLV5fRN+GiTrt27RwbQT326aefOiB4Dyr1Ib+Bad+46E0dzqt4qJ/efffdQjbN9QFsfA3WQ13MQCB1P20l9TgDWuw/F45orxIfL2IbuVGCbWL7uEmAwUJ+q9NGMIiYanHFHWXaDl43RL4TJ0507Df1LZPrHyQLxDEP7Tx1PblxrNxEO0m/g+OUWCZl6HOw7Ez6a34ZZme2q9SgElAgLqgjo3alJEBlSUXK1Snuaigu0bngBZ/8mKZj4a5wu4E4fsxTodNgxKdUypgOFe8roILnLi33bgIayWOOOcYJwjHFv8JkUuyU79Onj7M7wr3njvfaMdDIMlmPm7jb4PXXX8df/vKXQq8DcnWOjgOdVK74cPeam2wDcXSUDjzwQMeR4g437mxgYt00VnxRkCnx1VQ6UjS68fc10Nnh6h8/Nvjh8e9//3t3u7wcTeXuRzpz8fc+0VmjI0nnjzvzuMqmJAIiEF0C3DXFYDx1OB0gLq5QN1I3cEHCdagSCbg/Z1CGepF6jYn6kg4LgyiJd4j6CcSxTOo+6iv3RVU6KAyw0TmiQ0HnxU3U1VxkGTBggKMfXbv0ww8/OM4cdSMXHEy7B8iDgTfqXAa2uEMj3lbQEYy3BW7fGHjkbjQutjBR53PBhTzIk8E22g13Nxt3x7Gd3Cnm6n/m40IKd0jQUaQddR0fOmF0xuiUJe5Gp61jEJAOKu/7cxdS6JwyKMfdeHTW4u8B9Ho0lYFH2keOLRMDZieccILjEHPXG3eeu4k7/K699lrn91xYcoO7dHBp8xiEYzvdHYW0ZfxOYDsTA6UuH5atQFx09ZB6Fi0CNoE490GgRJ3MhZwzzjjD8TN4qsYtk/qCNoG7lKlrqAfdxB1l7ndrqkAcde/YsWMdnZiYGFCi3qK+cxN1OHdgM9BEHU1d7SbXB+Dfvfoa1N20sfSR6IOwL0y0Z6yb9oYpPhBHvc9g48qVKx3fgbbBTQyQ0SZQz9LOeXndvDjfJVkgjnWlezQ1k/6aH4bR+hem3nghoECcF0qSCRQBGgR+DNMAJq5AJTaUQRvXmeAqN3dfMbkf9jyywlWUxJRKGbtBwBdeeKHQERrmZ2DK/dC3CcTROWR/4o/BMOjFo008vsT/vBgtGjoayKuvvtrZFZBohL06CAyW/f3vf3fK4spafKIR5goc25QYiCtuktAR5qogDbSbvATiUpXJsuiQ86PI/SAI1CRVY0RABDJKgLqIwfwlS5YUKpd6kiv9PP6TeFTddYoYtP/HP/5RKB+dnFNOOcW5joA7mtzkNxDn7riLr4QLBo8++mghXckdvtwdwcAXP9QTg4juLm46TNyNUFxi0Io2jcdK6ZyZktu3xIAa87GdbC+PplI3x7Pkzj4uhlD3x++wo5NIJy0xyMXy6LhyJwMDbVzUoQ1jkIuOGO0ybR53qsUntw08TsrxcZPXQByvQKCTG5+4w50Bx/jd4rSvDF6yHXQK6WzGJ+5Y5E5Bzg0eRWVyd73zZ2x7/LixPAZaeSWDVztrGiv9XgREILsEbAJxxbWEGwIYzKeucHcMu9/j3DXLXXDx+oInTaj7GMRKFYjjAgAXAmwSF3xY7tlnn+0skrjJDWjZ+Bpun5LtzuauOHexIz4Qx53MvI6AR3V5p2ti4u8ow7axjaYUxEBcthmamOj30SOgQFz0xjTyPaJho+PED3V+sBeX3KOclOHHNZ02JvfDnuXwwzoxJQsS8W44OhX86GYgKDE4xuAUjwcx2QTiGLyjI5OYeLyGQSY6nvG7zChHZ46OKXfgcdWf9XFFjE4Hj45yV0CiEfbqILA9DLLxmI17RDS+bXRqWE+yQBwDbaybOyt4nwU/OJi4+4NOI3/v7trwGojjtnbuTqDzwxU3rjQy8UgRd3bwZ0oiIALRJ8DACfUL79LkMUHqGVcfcDcWdz7FH1t1nR/qCFc3x1OiLuLiAnWTm89PII6LKLQJ8UdcWQ8dKQbU6JTQOWHi4g93wvE4Kf+fmKgjGRjiUVce/TEl7sTgIhPr4DHY+Ls4E/O6fUu2m5y70LjTmkeQ6EQmJvIhR44Bk2sP+X/aoGR3wfE4EY8J8dgUj34yaMfgXaq+0WYw4Ec7y7rc8fMaiGP53MURnzhH6Bxz0Y6Ld0w8sspjtwzEchdjssQ8vJuJwUMeyXKPR/MuWO4OTEy8m4m72r3aWdO46vciIALZJWAbiKPuo99BfcZd1bzKhonHUxmEiw8wufoi2eIA83ADABfMUwXiTBsNuPuOuovBN+oo2kH3zkvqLncBgXW5AS0bX4MBJwbZEndzuyNCG0VbFR+I4443tom2mfo1Mbk7qHlMlAE+UwpiIC7bDE1M9PvoEVAgLnpjGvkeubvSeMkyj4kWl3hklKv4NLg0oolHU+k8JXMgkgWJ6OwwIMb/EndluG1wHTubQBy3qPOIZWKKv7TVPe5Ew09nijvyUiXm44qVm2yPpvK+Nn4EpPoQcFe1EgNxbBPvtWBAMlUiV/f1Wi+BODo2dGDdD55k5cazjvzkVwdFQAR2E6AzRP3G4ygMBnHhgAsIbqLeZ2CHDw4kS9yZxkUN/sfdW0x+AnG0Me61BPH1JNO93OnAhxVMiYFFOlumxJ1avOuMLJj4yBCPo/KYUuKOcbdvzJN4T4971CfZbjmWmxgMc+0h7yviPXLJEo8Qc4cfd+tx1x4f+uGxT7Y3lQ3jTjzuwGNQjrvzktWdylZydxv7H5+S2Rku4px77rkmtM7veb0Fj97yISTe6cT/aOcSk3udhAJxnrBKSARKnIBNII47fHkENX5HcGIHqO/deyxN+oK7nXkHW6pA3Jw5c5w7KBMTv3cZxOP92Km+famrGSBzk2uHbHwN+kX87qaPlOyxId5nzQBkfCCOR/e5+8+UEu10KvkgBuKyzdDETr+PHgEF4qI3ppHvkevIxF/qnKrTdAD4uEKqxxpSGbLiAnHcccBdWskSnT46EDaBuFQf7skCcby4moEp9oc7K2gMWScDjLyLgvczcMcBnapEI+zVQeAuQ+624388npqYkgXi6IRyZyH7zXa5r9q6l3TzGFbixa6mQBwvd+UdUHTG6OSQB50+96OA40AHUIG4yP+TVwdFoFgC7s6zxEUSUyDO3bGVbiAu/gXP+IYmcyRcB407t9w765J1Lv4xAtPwc/cY7wbibg3ehccjkkwMNvEuODelCjLy96nu3HHzpgrEFbcw5QbiGIyjE+sG4hiM4x1CyZIbiGMwjtcPMHndEZd4cTjzJrMzbjt4jIu2qbjEByE4Fu6jFMmOOTO/AnGmWarfi0CwCHgNxPEbk3dn8lQG9Tf/o+7mzl2WwWsRuMMrfnHa1fO2+iLZd388NVd38boXHvPkNzJ3K9MHYOCM38eJ9si0GJ+sTlMgzl3Eite57mmlrl27Oo/2pErxD7IVNyOCGIiz8df8MAzWvxC1JhcEFIjLBWXVkVECdDh4/JKr1DQC8XerJVZER4Sr31xBYoAolVORmC/V0VRejsrjlpk8mmqj2PmaHbfFc3WOwbj45N55lG4gjvcw0QDaHE194okn0Lt3b+fpdPclu/i2MYDGo8HxRtsUiONF2rzklvcG8aXc+ET+HAt+ICkQl9F/XipMBEJHwD1+6Dojbge8Hk2Nv7bAz444m0AcjzXycv/ERyIyCZ2LGHSGuJuLR4V4BJMpk4G4+KOp7vHNxD64zprXo6kMvjEQR93OqxZsj6Z6DcS5l2hzkY7XLHhJ3LXOnZc6muqFlmREIPgEvAbiuDuNgTheF8Nj7YmJO3y54BEfiHP1hd+jqcl0Ges977zzMGrUKOe6Fl4lEJ8YKOQd2pkIxHFnMb/RUx1NZfCPd3/Gt5MP8PCVbF5HYHpoyMvsCHsgzg9DL1wkEy0CCsRFazzzoje8C4FGkfe78WJmGrpkiffFcKWHzhll3eOdlDWtsKcKEvFJbN5DxFUpGsT4FP8yUbZ2xHHXGY8rxR/bcdvg3u2WbiCO99Vx63j8nTpuHayXdxIlPtbA+4nooHCFjjsV45N7LxB/Fm+0ebyXwVQydZ9lj8/H4z8MBrrHmuJ/x2PJ7hEABeLy4p+9OpnHBPhvPNXLqMTiPnCQ6IC4eZItKvDoPY/hc1cUdxO7KduBOHenL4+G8ohotpK7SyP+LrpMBuLY7uIea2BwlM6YzWMNQ4cOdRZdEh9rcO0eg3/uy+Lx3IrbRZLMlvOaCj5ywfnB3dzuzrvixoIOJh3NZJev895YHiVmWV53nmdr3FWuCIiANwJeA3H85ud3Knf48qXn+MQ7Rvlvn9cfxAfieI8pv6EZGONdk/H2iz4M7Q6P0qc6mpoqEMcyWXb8Lm63Pe69dJkIxPG+Ue5a5ikcLorHJ3f3dOI3vXtih0FI91VYbyORXMpPIM71RVJtJGCf2LdUCyqmV1NtNk74YZgOL+UNJwEF4sI5bnnfajozvAeHH8DcEs4db/EXZfNxACpBGkneM8bjlPHJbyDODQDRMeARIO70YuLOA7bHvZchW4E4roDxUu1E4zh69Gjn3h3u1ks3EMdjTlzJ4YcFV/ncu3RYNoNjfFWVKf6jg/VzBwZXDGmk3WfVeYSXx1u5ophotLmNnk5azZo1HX6JF51zZx2ffOfuR17y6u585B0UvFCcdxQxKRCX9+pAACJOgIst1Bf//Oc/i9wBxoUJ7viaP3++o+ep793kOj9cPOCCgLsYw5V86hBeaM27dvr167c7T7YDcazI3TnAermYRD3oJjppfCyBR3t4hKe4xCOoDOZRR8cfBWKgicEp2sn4F74zHYhz9T6PSdEeukdtuZuNeps/S9yNzkAbA260C3RqXVvBYChtF/U6d73zegM3uYE2Bvd4D1Fisg3EMb+7M5FjMWLEiN13l7plc27QbrkLbhwXOtVsJ3dq0za5iTvl3HteFYiLuDJS9yJDwGsgjo/58Ag+9fTUqVN3v/bMx+C4IMwdaonfxPxeZtCeO8r4KMPVV1+9m5sbLOIPbANxrv7kCRReyeD2YcKECTj11FOdRfJMBOKou6lXufONZfPaGyYuxjMY6O4MjA8Y0t+iHH0InpKhvYkPQHLnNL/l+eIqbYYp+QnEuXkS7Y5blxtE7NKli3NaKjFlMhDnh6GJiX4fPQIKxEVvTPOmRzyKyeATj7PwNVTelcD7EXhskx/QpUuXdj6Ok+2Y8xuIY9CHl05zWzhX0enM8QOdq+Xc4cAt2by3LP5xgUwqdjqTNGI08kceeaRzLxsdUX4c0PAweJVuII4TiMaSzh37xpVAXkbuvhRFB4tPtccH4thf3lfHlT8GJ5mHHyl8NIL3MDFxVTFxlY/3BpElnSvm50u0zMvjsXyRicdv6ZgxMMhX9xgcpHHjyiTbwx0ICsTlzT95dTRPCTBgxaOc/Kjnhz4DIgzMMxBFPUA9RX1IPexe8E9UlKfu4s4sBqyor5mPf6ZDQZ3NuzDjd1nlIhDHo7B0Zhjs4QM/1JF0eLhwwd3bfHghMUCYbOi5K4LHPxmE4yIInRs6O9S1LIMv19GJcl/4znQgjm1y707jfaC0TWwLnR3Wz9dROSbxQUIG6cidL4LTbtNesc0cE9qMK6+80hnr+MTgKq894C425mXwjve2cUGKyU8gjnOmW7duTqCS3w20P5wrDNJypwptFW09d2S7ifeccg7xagRyp6PN4CCPhNEhZ0BPgbg8VVLqdugIuEEiXvmSKnFxh8F494SGq+f4f+pWfotzgZwBoMQHzHjSgwsO1GvUL7RdXEimf0J9wV1bd9xxh3PHnJtMd8RxIYBlUWfyZBBtG+0G63KvhslEII7tcYE/fLEAACAASURBVIN+vOuMeo995jc9/SfaUS70sO74l7onTpzo3AfKb3W2g9/w1K+01ew3281HHly/oLhJ4ycQx5M2DRs2dF71Jnu2jePMhRPy51iwXQyu0vZw8Yi+Ik8U8b7QTPprfhmG7h+SGpwWAQXi0sKnzCVNgB/7/GjnCjo/nql8uXJFo9GnT5+U9xT4DcSxvww68bgPjQR3clHR84OeW515vw0fT4h/RS7Tip3Gj3XRmHFHIJ8qpwGmcWbAKhOBOPaTjhFX+ukw0ZHj5eJ0fLj6xwBn4kcHV8PYLu5GZP957JS75LhFnSt1DKAlBuJoDBlA5FZ7jiU/aviBQrZM5Mtt8czLwBz7x1f9aFRpbBWIK+l/gapfBLJPgMER6hUeJ+ViBz+2uepOfUv9x9VtHqd3A05ui/gBzo9uBrd4bIfHUpiXNsLV2e6DMm6eXATiWBeDOcOGDXN2HdM5o11hu7i4wgAQF0IYbCouMajFy8Cpq1kGFy24a4N6ki+Kk0l8/7IRiGP7nn32WacvDCzSJlE389VWOrGJfClPZ4y7RNh37mTkuPHVWu7y4EMOiYll0uYwaEaHjnY+3tn0E4hz6+CiEwNoXMzioh6Zs2weW+ZCn7sTxJVn8JOOs3udAheIOLe4IMYFJAXisq8PVIMIZIJAcdcduOW7CyL8NqWvwatb6GtwwYe7aRlI47dwsm9ilsHvZ34Xc3GEiYsj3I3LBQpuEqDe5GKGm0yBOMoxoMXv4smTJzs74KijuFv8H//4hxN0ylQgjovc3L3MV76pp6kbea8md/Rx4Ys/S3Y/KG0sF094eoff6DztQj+Jixdnn322s5CeaKuTjaefQBzL4eIadTK/FciHiQFEsmWirqcO5yIevyPYT9efybS/5pdhJua3yggHAQXiwjFOamUICNAocgcAP+DpNCqJgAiIgAiUHIFkTknJtUY1i4AIiIAIiACc6xR4qocL68XtyAsiK+6C42YG3o3nXjsTxHYGuU1iGOTRyW3bFIjLLW/VFgECPPrKIynxr7VyFYUrPdylxnvkuBtBSQREQAREoOQIKBBXcuxVswiIgAjkMwEez+SuZe5QcxN3SPFuNx7BZyCLR0297MwrCY48cs+2x+9q5skV3r/NUyzcdcYXwJVSExBDzQ4TAQXiTIT0exFIIMAdb9zazKM0vOOGxyf5d949wCOYPCYbVMOqwRQBERCBfCGgQFy+jLT6KQIiIALBIsDdbrx3jPe48S4yHm/lnZI82srg1ttvv737uGSwWh5rTa9evZzrHHiklNcm8G7Tr776yjnOyatweDw/2dUDQexLSbVJDEuKfHjqVSAuPGOllgaEwIsvvui8HMqdcVzx4l0HvDycd+JcfvnlhXbKBaTJaoYIiIAI5B0BBeLybsjVYREQAREIBAHegcx7lnk/Ge9N472g7gM11113nXO/aZAT71rj7j0G33hPK+964/2f55xzjnMvdfxr30HuR0m2TQxLkn446lYgLhzjpFaKgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiEnIACcSEfQDVfBERABERABERABERABERABERABERABEQgHAQUiAvHOKmVIiACIiACIiACIiACIiACIiACIiACIiACISegQFzIB1DNFwEREAEREAEREAEREAEREAEREAEREAERCAcBBeLCMU5qpQiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIQMgJKBAX8gEMU/P56s64ceNQUFCgJ6/DNHB50Fa+ZrVgwQKcdNJJqFWrVh70WF0UgfARkA0J35jlS4tlQ/JlpNXPMBOQDQnz6EW77bIh0R7fVL1TIC4/x71Eev3888+jW7duJVK3KhUBLwSee+45XHjhhV5EJSMCIpBjArIhOQau6qwJyIZYI1MGEcgZAdmQnKFWRT4JyIb4BBfSbArEhXTgwtjsiRMnon379qCSady4cZEurF+/Hl9++SWOPPJIVKlSJYxdzGmbxcsOd3G85syZ4wSJP/30U7Rr186uYEmLgAjkhIBsSGYxy4bY8ZQNseMlaREIGgHZkMyNiOyHHUsTL/khdjyjIq1AXFRGMgT9+Oqrr5wgG4NtLVu2LNLiNWvW4OOPP0bHjh1RrVq1EPSoZJsoXnb8i+Nlmpt2NUlaBEQgGwRM/06lE+2oi1fmeJnmpl1NkhYBEcgGAdO/U+lE79TFyjsrSpp4meamXW2SDgsBBeLCMlIRaKdJyZiUVAQQZLQL4mWHU4E4O16SFoGgEZANyeyIyIbY8ZQNseMlaREIGgHZkMyNiOyHHUsTL9PctKtN0mEhoEBcWEYqAu00KRmTkooAgox2QbzscMqJsuMlaREIGgHZkMyOiGyIHU/ZEDtekhaBoBGQDcnciMh+2LE08TLNTbvaJB0WAgrEhWWkItBOk5IxKakIIMhoF8TLDqecKDtekhaBoBGQDcnsiMiG2PGUDbHjJWkRCBoB2ZDMjYjshx1LEy/T3LSrTdJhIaBAXFhGKgLtNCkZk5KKAIKMdkG87HDKibLjJWkRCBoB2ZDMjohsiB1P2RA7XpIWgaARkA3J3IjIftixNPEyzU272iQdFgIKxIVlpCLQTpOSMSmpCCDIaBfEyw6nnCg7XpIWgaARkA3J7IjIhtjxlA2x4yVpEQgaAdmQzI2I7IcdSxMv09y0q03SYSGgQFxYRioC7TQpGZOSigCCjHZBvOxwyomy4yVpEQgaAdmQzI6IbIgdT9kQO16SFoGgEZANydyIyH7YsTTxMs1Nu9okHRYCCsSFZaQi0E6TkjEpqQggyGgXxMsOp5woO16SFoGgEZANyeyIyIbY8ZQNseMlaREIGgHZkMyNiOyHHUsTL9PctKtN0mEhoEBcWEYqAu00KRmTkooAgox2QbzscMqJsuMlaREIGgHZkMyOiGyIHU/ZEDtekhaBoBGQDcnciMh+2LE08TLNTbvaJB0WAgrEhWWkItBOk5IxKakIIMhoF8TLDqecKDtekhaBoBGQDcnsiMiG2PGUDbHjJWkRCBoB2ZDMjYjshx1LEy/T3LSrTdJhIaBAXFhGKgLtNCkZk5KKAIKMdkG87HDKibLjJWkRCBoB2ZDMjohsiB1P2RA7XpIWgaARkA3J3IjIftixNPEyzU272iQdFgIKxIVlpCLQTpOSMSmpCCDIaBfEyw6nnCg7XpIWgaARkA3J7IjIhtjxlA2x4yVpEQgaAdmQzI2I7IcdSxMv09y0q03SYSGgQFxYRioC7TQpGZOSigCCjHZBvOxwyomy4yVpEQgaAdmQzI6IbIgdT9kQO16SFoGgEZANydyIyH7YsTTxMs1Nu9okHRYCCsSFZaQi0E6TkjEpqQggyGgXxMsOp5woO16SFoGgEZANyeyIyIbY8ZQNseMlaREIGgHZkMyNiOyHHUsTL9PctKtN0mEhoEBcWEYqAu00KRmTkgo9gunTgTFjgDVrgGrVgLPPBpo1892tyPPyTSZ5RjlRGQaq4kQgxwTy3oYAmL1kHcbN+gXrtmxD1YrlcHKTOmhct6qvkZANscMmG2LHS9IiEDQCsiGZGxHZDzuWJl6muWlXm6TDQkCBuLCMVATaaVIyJiUVWgTz5gGXXgpMmFC0C8ccA/z738BBB1l3L7K8rEl4yyAnyhsnSYlAUAnkrQ0B8P7sZbjl9W+wZM2WIsPTqqAG7u3SDAW1KlsNnWyIFS7IhtjxkrQIBI1APtuQTI+F7IcdURMv09y0q03SYSGgQFxYRioC7TQpGZOSCiWC778H2rYFVqxI3fxatYBJk6yDcZHklcVBlhOVRbgqWgRyQCAfbciCFRtx5QtfY8bitcUSrl6pHMb0bmcVjJMNsZu0siF2vCQtAkEjkI82JFtjIPthR9bEyzQ37WqTdFgIKBAXlpGKQDtNSsakpEKJoEOH5DvhEjvDnXGffGLVxUjysiJgJywnyo6XpEUgaATyzYb8uGIjzn58IlZv2uZpKLgzblSvNp5kKSQb4hmVIygbYsdL0iIQNAL5ZkOyyV/2w46uiZdpbtrVJumwEFAgLiwjFYF2mpSMSUmFDgHvhDviCO/NprzFnXGR4+WdlC9JOVG+sCmTCASGQL7ZkHOHTcIXC1ZZ8X/qb0fh+Ma1PeWRDfGEabeQbIgdL0mLQNAI5JsNySZ/2Q87uiZeprlpV5ukw0JAgbiwjFQE2mlSMiYlFToEgwYBgwd7bzblBw70LB85Xp577k9QTpQ/bsolAkEhkE82hI8ynPpIkntFDYNRsVxpjO3bwdMRVdkQu5ktG2LHS9IiEDQC+WRDimM//9cN2L9GJZQtU9r3EMl+2KEz8TLNTbvaJB0WAgrEhWWkItBOk5IxKanQIejXDxgyxHuz+/YFHn7Ys3zkeHnuuT9BOVH+uCmXCASFQD7ZkIfe+w5Dxn/vC73XI6qyIXZ4ZUPseElaBIJGIJ9sSCr24+cswxX//RrnHlUfgzs38T1Esh926Ey8THPTrjZJh4WAAnFhGakItNOkZExKKnQItCMuUEMmJypQw6HGiIA1gXyyIYPfmIWRExdYM3IzvNP3GDSuW7XY/JGzub5pecsoG+KNk6REIKgE8smGJBuDLdt24Lj7P8KStbHXt9+9qgMa1a7ia7hkP+ywmXiZ5qZdbZIOCwEF4sIyUhFop0nJmJRU6BDojrhADZmcqEANhxojAtYE8smGDHztGzwz6SdrRm6Gfp0ORr9OjRSI802waEbZkAzCVFEiUAIE8smGuHjXbNqKvz8zFac0qYPTm++L75atx0VPfeH82oudSDVMkfPZsjwfTbxMczPLzVPxJURAgbgSAp+P1ZqUjElJhZKZXk0NzLDJiQrMUKghIuCLQD7ZkL88MgHfLFnnixMzdW9XgIGnH65AnG+CCsRlEJ2KEoFAEMgnG+ICf/GLn3HdKzOdvz54bnN0PqIejr7zfazYsBWH1K6CcVd18DU2kfTZfJHwlsnEyzQ3vdUiqbARUCAubCMW4vaalIxJSYWy6/PmAW3aACtWpG5+rVrApEnAQQdZdTGSvKwI2AkrEGfHS9IiEDQC+WJD/D7UED9eXnY6yIbYzXDZEDtekhaBoBHIFxsSz/3JT+bj0fHz8NuOnfjypk6oUrEcbhgzE/+d/LMjNr5/RzTce0/roZL9sENm4mWam3a1STosBBSIC8tIRaCdJiVjUlKhRcBg3CWXABMnFu3CMccA//63dRCOBUWWV5YGWk5UlsCqWBHIEYF8sSHpPNTgDsVTfzsKxzeuXezIyIbYTVzZEDtekhaBoBHIFxuSyJ13w81Zug4tGlR3fvXp9yvQ7anJzp//dWIjXHHcwdZDJfthh8zEyzQ37WqTdFgIKBAXlpGKQDtNSsakpEKN4Oefgf33/6MLe+8NvP8+0KyZ725FmpdvKqkzyonKAlQVKQI5JJAvNiTdhxo4JF5eTpUNsZu8siF2vCQtAkEjkC82xMR9+46dOPL297F28za0ObAmXujZ2pSlyO9lP+yQmXiZ5qZdbZIOCwEF4sIyUhFop0nJmJRUqBFMmQK0avVHF6pWBdauTatLkeaVFpnkmeVEZQGqihSBHBLIFxuSiR1xHBbTy6myIXaTVzbEjpekRSBoBPLFhnjhfsnIL/DRt7+iSoWymD7wRJQuXcpLtt0ysh9WuIynmExz0642SYeFgAJxYRmpCLTTpGQirdTfegv4y18KjyIDcQzI+UyR5uWTSXHZ5ERlAaqKFIEcEsgXG5KJO+I4LKZ74mRD7CavbIgdL0mLQNAI5IsNcbkvWr0J+1SpiPJlSxcZigff/RaPfDDP+fn7V3fEQfvY3RMn+2E3u028THPTrjZJh4WAAnFhGakItNOkZExKKtQIeA/c3/9euAuzZgGHHea7W5Hm5ZtK6oxyorIAVUWKQA4J5JMNOXfYJHyxYFVadE0vp8qG2OGVDbHjJWkRCBqBfLIhZH/c/R9h0erNOLVpHTx8fotCw/H+7GXo8Z+pzs/4murZLetbDZfshxUu7Yizw5U30grE5c1Ql3xH880AFiJ+113ADTcUHoSxY4GTTvI9MDKCdujkRNnxkrQIBI1AvtiQBSs24soXvsaMxeldX6AdcZmdwbIhmeWp0kQg1wTyxYaQ6/ot29B00LsO4nOPqo97uzQvhHv5+i1odcd452eXtC3AoDMOtxoO+SBWuBSIs8OVN9IKxOXNUJd8R/PJABah3a8fMGRI4R+PGFF0l5zFMMkIWsAyvDJrmpt2NUlaBEQgGwRM/06joBN/XLERZz8+Eas3bUsboe6ISxthoQIUiMssT5UmArkmkA82xGX6+Q8rcf6Tnzt/va3z4bioTUER3G3uGo+la7egRYNqGNO7ndVwRMHeWnU4TWETL9PcTLN6ZQ8oAQXiAjowUWyWScmYlFSomVxwAfDCC4W7MHAgMGiQ725FmpdvKqkzyonKAlQVKQI5JJAPNiQTR1I5JHo1NfMTUzYk80xVogjkkkA+2BCX54gJP+D2t+Y4fx3Tuy1aNKheBPVlz07FuFnLUKFsaXwz+CSUK1P0LrlU4yMfxG7mmniZ5qZdbZIOCwEF4sIyUhlq58KFC3Hrrbdi/PjxWLp0KWrXro2OHTvixhtvRKNGjXbXsmPHDtx3330YMWIEmGe//fZDjx49cM0116BMmTK+WmNSMiYl5avSoGQ6/njggw+AOnWAZcuAXbtiu+G4K85nijQvn0yKyyYnKgtQVaQI5JBA1G1Iph5pqFKxLN64oj0KalUudnRkQ+wmr2yIHS9Ji0AyAvJDcjMv/vXSdIz+chH4GOrsW09GxXJFfbehH87DfeO+dRr01pXtcfi+e3lunOyHZ1SOoImX6fvGrjZJh4WAAnFhGakMtHPlypVo0qQJtm7din/+85844IADMG/ePDzxxBMoVaoUZs6cifr1Y5d19u7d2/l59+7d0bZtW3z22WcYOXKk8/OhQ4f6ao1JyZiUlK9Kg5KpSROAjzMcdRSwaBHwyy/AiScC48b5bmGkefmmkjqjnKgsQFWReUdATlT2hvyh977DkPHfZ6QC7oi7t0uzYoNxsiF2qGVD7HhJWgQSCcgPyd2c6DrsM0xZsBr1q++BT689LmnFH8xdhkufjj3YMOT8I9D5iHqeGyj74RmVAnF2qPJKWoG4PBruxx9/HJdffjlef/11nH766bt7/vLLL6NLly546KGH0K9fPycg17x5c/Tp0wdD4u4169u3Lx599FFMnz4dTZs2tSaX14G4vfcGVqwATjsNWL4cmDIl9mIqg3M+k4ygHTg5UXa8JC0CcqJyOwcGvzELIycu8Fxp+TKlsXXHzpTy1SuVc+79SbUzTjbEM2qjI2X6vrGrSdIiEE0C8kNyN65/uuN9/Lr+N7Q/qBae63F00op/WrkRHe/7yPld3+MPxlUn/HEyytRS2Q8TocK/N/GSDbHjGRVpBeKiMpIe+nH33Xfj+uuvx5QpU3AUd2b9niZNmuTsehs+fDh69uzpHFO988478cMPPzi75tz0448/4sADD8QNN9yAO+64w0ONhUVMSsakpKwrDEqG7duB8uVjx1EvvRRYvRoYMwaoUgVYt853KyPLyzeR4jMqEJclsCo2bwjIicruUGdyR5zb0uLuipMNsRtP2RA7XpIWgUQC8kNyMyc2bd2Ow26Jnbi58OgGuOOs5Jsnduzchec+/wkN994Th9atglp7VvDcQNkPz6gcQRMvk49sV5ukw0JAgbiwjFQG2skAXKtWrdC6dWvcf//9KCgocI6mXn311diwYYMToKtatSpOOukkZ9fbLzw+mZB4p1yLFi0wduxY6xaZlIxJSVlXGJQM5Fi3bqw1110HbNoEPPJI7O9r1wJVq/pqaWR5+aJhziQnysxIEiJQHAE5UdmdH5m6Iy6xlaleT5UNsRtP2RA7XpIWgUQC8kNyMyfmLF2HU4ZMcCq78dTG+EeHAzNeseyHHVITL5OPbFebpMNCQIG4sIxUhtr55JNPOjvaeE+Dmzp06IBXXnkFNWvWdH7EY6fly5fHl19+WaTWli1bYtu2bc7x1eISH4Lgf/Fpzpw56NatGz766CPn6GtiWr9+PaiIWEcV7haLSCo9cyaqdujg9GbznXcC27ZhD76YCmDdZ59hZ+PGvnoaVV6+YHjIVBwvBp6PPfZYZ85z/imJgAgUJSAnKvuzIlOvpsa3tF+ng9GvU9EjRybHIPu9DVcNCsSFa7zU2mASkB+S/XEZ/+1K9B8z16noobMPxZ8bxfy7TCb5IHY0Tbzkh9jxjIq0AnFRGUmP/RgzZgyGDRvm7Ho76KCDnIAaX0flIw7jxo1D5cqV0bBhQ+c1VT7QkJh4hHX58uXOTrri0qBBgzB48OCkIg888IBTR76kvadNQ9tBg5zuTr36aqBUKRz1wAPO3z8bOBC/tmiRLygC28/58+ejf//+CsQFdoTUsKAQkBOV3ZH4efVmXPyfGVizeXvKisqXKYWtO3Z5bsgFR9XFgE5Fd0SYHAPPFeSJoBZz8mSg1c2sEpAfklW8TuHjF5fC6z/HXkm9tvl27Fsp+3WqhvQIyA9Jj19YcysQF9aR89Fu7no777zznF1n8Y8tvPvuu05g7p577sGAAQO0I84H2+KylPvf/1C5Vy9HZMNrr2FXuXKocuqpzt83DRmCrRdf7KtGOVF22ORE2fGStAgkIyAnKvvz4tfNwAvzy2D++lJFKmtYZRf2rbQLE5aV9tyQk+vvwCn7eQ/ceS5YgrsJyInSZBABMwH5IWZGmZC49Z15eGX6MqeoSf1bY49ysaBcsrRozRaMmb4MP63ajIta7Yvm9bxdlyMfxG6kTLy0I86OZ1SkFYiLykh66EfHjh3x66+/Yvbs2UWkeTccj6i++eabuiPOA0srEe5++9e/Yll4pJfHbgsKYn/nEdXfd8tZlenh4k/b8qIur2NFUR9h9S/bBOREZZvwH+V/u2wjer74DdZu3o4KZUvhjKa10bVFHTTapzL4u/NGTvPcmFGXHuHkS0wmx8BzBXkiqMWcPBlodTNrBOSHZA1toYL/+uTnmPTDStSpWhGf33B8sZVOW7gGZw6d6MgMPuNw/K3t7/6Joam62sBuLE28dEecHc+oSCsQF5WR9NCPQw45xJH69ttvC0nv2rXLuZOtffv2ziMMvEPurrvu0qupHph6EhkwALjvvpjo8uVAtWpAhQp/vKL61FOeikkUMil1X4VGOJMCcREeXHUtJwTkRGUf84IVGzFg9Ax8sWBVkcr4Auq9XZqhoFZleL1LTq+mZm7MZEMyx1Il5ScB+SG5Gfe2d43HkrVbcPQBNfC/y9oUW+m6LdvQbNC7qFiuNPocdzAu//NBnhopH8QTpt1CJl4KxNnxjIq0AnFRGUkP/ejcuTPeeOMNTJw4EW3a/KGYR48eja5du+LGG2/E7bff7ryYypdR+/TpgyFDhuwuuW/fvnj00Ucxbdo0NGvWzEONhUVMSsakpKwrDEqGSy4BnnkGKFMG2LoVKF0a2HdfgI9ZnHgiMC72xLhtiiwvWxAe5eVEeQQlMRFIQUBOVHanxo8rNuLsxydi9aZtKSuqXqkcxvRu5/z+LI+yDNwlS7IhduMpG2LHS9IikEhAfkj258SWbTtw6M1jnYrOO2o/3NPF7K8tWbPZ2T1XunTR6xBStVj2w24sTbxMPrJdbZIOCwEF4sIyUhloJx9f4MuQFSpUQO/evZ0HE/hYAy/frlGjBr7++mvUqVPHqalXr14YPnw4unfvjnbt2jnBu5EjR+Kyyy5zHnvwk0xKxqSk/NQZiDynnAKMHQuQrfuSbKtWwJQpAF9MTXJU2Eu7I8vLS+d9yMiJ8gFNWUQgjoCcqOxOB9tdbl53z8mRysy4yYZkhqNKyV8C8kOyP/bzf92A4x/42KnompMO8bzDzbZl8kHsiJl4mXxku9okHRYCCsSFZaQy1M4ZM2bg1ltvxdSpU7FkyRInAHfCCSc4O+H233//3bVs374d9957L0aMGIFFixahfv366NGjh/OYQ9myZX21xqRkTErKV6VByNSyJfD11wB3EU6fHmvROecAr7wSuy9u3TpfrYwsL180zJnkRJkZSUIEiiMgJyp782P2knU49ZEJnit4p+8xaFw3dqn2nKXrcMZjn2Lbjl2oWrEsTm++L7q13n/371MVKhviGbcjKBtix0vSIpCMgPyQ7M6LlRt+w+vTl+CXtVvQ6bDa+FNBjaxUKPthh9XEy+Qj29Um6bAQUCAuLCMVgXaalIxJSYUWQb16wJIlwAknAO++G+tG377AI4/E/rxmDbDXXtbdiywvaxLeMsiJ8sZJUiJQHAE5UdmZHw+99x2GjP/ec+H9Oh2Mfp0aIZ1dcbIhnnErEGeHStIiEEgCeeuHeBwN3hm+axdv0DEfUZX98Aj1dzETL9PctKtN0mEhoEBcWEYqAu00KRmTkgolAlq08uWB7duBbt2AZ5+NdeP++4Frron9+ZtvgMMPt+5eJHlZU/CeQYE476wkKQJBJBBlGzL4jVkYOXGBZ+zd2xXg4jYFnu+US3ZPnGyIZ9wKxNmhkrQIBJJAlG1IOsA//u5X3P7mbCxavRnPXNoKrQ4w76KT/bAjbuJlmpt2tUk6LAQUiAvLSEWgnSYlY1JSoUSwahVQs2as6f37xwJwTC++CPz1r7E/v/MOcPLJ1t2LJC9rCt4zKBDnnZUkRSCIBKJsQ/zsiPts3sqkr6smjl2ql1NlQ+xmuWyIHS9Ji0DQCETZhqTDeuK8FbhwxGSniAfPbY6zW9Y3Fif7YURUSMDEyzQ37WqTdFgIKBAXlpGKQDtNSsakpEKJYM4c4LDDYk2/5x5gwIDYnydOBNq3j/35//4P6NHDunuR5GVNwXsGOVHeWUlSBIJIIMo2xPaOuKEXtMDl//3a8zDF3ynnZpIN8YzPEZQNseMlaREIGoEo2xCXNe+H48upDWpUQusDf98IYBiIn1ZuRMf7NaOAdgAAIABJREFUPnKkrj6hEa48/mDj0Ml+GBEVEjDxMs1Nu9okHRYCCsSFZaQi0E6TkjEpqVAi+Ogj4M9/jjX96aeBv/0t9ueffgIKCmJ/vuUWYPBg6+5Fkpc1Be8Z5ER5ZyVJEQgigajbEJtXU9s0rOnrTrn4cZUNsZvlsiF2vCQtAkEjEHUbQt6nPTIBs5asw6F1qmBsvw6ehmDr9p045OZ3nPvhzj2qPu7t0tyYT/bDiKiQgImXaW7a1SbpsBBQIC4sIxWBdpqUjElJhRLBqFHAeefFmh5/BHXbNqBCBThW79JLgaeesu5eJHlZU/CeQU6Ud1aSFIEgEoi6DeHDC2c9PhGrN21Lib96pXIY07sdnpm0wPpOuYGnF76LVDbEbpbLhtjxkrQIBI1A1G0IeR91+3tYsWErjj1kbzzdvZXnIWhz13gsXbsFbQ6siRd6tjbmk/0wIlIgzg5RXkorEJeXw14ync4HA1iE7KOPAldeGfvxl18CLVv+IbLvvsDSpYVfU7UYGhlBC1g6VmQHS9IiEEAC+WBDGIy7etQ0fPXzmiIjwLve7u3SDHx4wc+dcnxlNT7JhthNcgXi7HhJWgSCRiAfbMjPKzdh6drNqFCuDI7Yr5rnIXB3ZO9XYw9MGHCcMZ/shxGRlb01zU272iQdFgIKxIVlpCLQTpOSiaRSv+km4I47YqO3aBFQr94fI3n00cAXXwCNGwOzZ1uPcCR5WVPwnkFOlHdWkhSBIBLIFxsyb/l6dHrwE2cIjtq/OtofXAsnHV4HjetW3T0stnfK6Y649Ge0bEj6DFWCCJQkgXyxIX4YX/2/aXjl68UoW7oU5t52MsqWKV1sMfJB7CibeJnmpl1tkg4LAQXiwjJSEWinScmYlFQoEfTsGXuMgWnrVqBcuT+6cc45wCuvAHvuCaxbB5QqZdXFSPKyImAnLCfKjpekRSBoBPLFhsS/YPfweUfgzBZxCzhxg2Jzp9yoXm2KDKdsiN0Mlw2x4yVpEQgagXyxIX64P/jut3jkg3lO1onXHYd61fZQIM4PyBR5TPbWNDcz2BQVFSACCsQFaDCi3hSTkjEpqVDy6dwZeP11oEYNYOXKwl3o1w8YMiT2szVrgL32supiJHlZEbATlhNlx0vSIhA0AvliQ175ahGuHjXdwf/ffxyNtg1rJR0KmzvleJw1McmG2M1w2RA7XpIWgaARyBcb4of7qCkLMeDlGU7WF3u2Nr64KvthR9nEyzQ37WqTdFgIKBAXlpGKQDtNSsakpEKJoHVrYPJk4NBDgTlzCnfh/vuBa66J/WzmTKBJE6suRpKXFQE7YTlRdrwkLQJBI5APNoRHTm9/azY+mx9buPm/i4/ECYfVSTkUDMYNGD0DXyxYVUQm/k65ZAXIhtjNcNkQO16SFoGgEYi6DXn168V455ulqLvXHujX6WBUq1Te8xB8+v0KdHtqsiNf3E5st0DZD89oHUETL9PctKtN0mEhoEBcWEYqAu00KRmTkgolggMOABYsADp2BD76qHAX/vc/4PzzYz+Lf1HVY0cjyctj3/2IyYnyQ015RCA4BKJsQ9IJqHGE5ixdhxtemYmvF8YeeXipVxv8qaBGsYMnG2I3t2VD7HhJWgSCRiDKNoSsB78xa/dr2jMHnYgqFeOuwzEMxrzlG9DpwY8dqWtPPhT/PLah7EcGJ7DJ3prmZgaboqICRECBuAANRtSbYlIyJiUVSj6VKwObNgHnngsw8BafJk4E2reP/eTJJ4F//MOqi5HkZUXATlhOlB0vSYtA0AhE1Yb8uGIjzn58IlZv2pYSefVK5TCmdzvnxdRU6clP5uPOt+c6v373qg5oVLuKHKkMTmLZkAzCVFEiUAIEompDXJS9n/8Sb8/8BZXLl8GsW0+2Irzht+1oMnCck+eStgUYdMbhsh9WBIsXNvlsprmZwaaoqAARUCAuQIMR9aaYlIxJSYWOz4YNQJXfHaE+fYBHHinchZ9/BvbfP/azW24BBg+26mLkeFn13l5YTpQ9M+UQgSARiKoNSffRBXeMXpu2GH1fnOb89T+XtkKHRnvLkcrgBJYNySBMFSUCJUAgqjbERenakoKalfDRNX+2Jtx04Dis/207Tjq8NoZfdJTshzXB1BlMPptpbmawKSoqQAQUiAvQYES9KSYlY1JSoeMzfz5w0EGxZt92G3DTTYW7sG0bULEisHMn0L078O9/W3Uxcrysem8vLCfKnplyiECQCETRhvBOuFMfmeAZ8zt9j0HjulWTyn/+w0qc/+Tnzu/aH1QLR+5fHSc3qZNSXjbEM3ZHUDbEjpekRSBoBKJoQ+IZH3f/R/hhxUZH97/8z7bW+E948GN8v3wDmtffC69d8fuJnRSlyH7Y4TXxMs1Nu9okHRYCCsSFZaQi0E6TkjEpqdAh+OwzoF27WLNTHT2tVw9YsgQ44QTg3Xetuhg5Xla9txeWE2XPTDlEIEgEomhDHnrvOwwZ/71nzLyAu1+nRkXkecfclS9+jRmL1hb5XapHG2RDPGNXIM4OlaRFIJAEomhD4kE3HTQO67d429GWbIAuemoyJny/ArWrVsDkGzoVO4ayH3ZT3MTLNDftapN0WAgoEBeWkYpAO01KxqSkQofg1VeBs86KNfu114AzzijaheJeVTV0OHK8sjzACsRlGbCKF4EsE4iiDYm/XNsLvu7tCjDw9MJ39/i9Y042xAvxP2RkQ+x4SVoEgkYgijbEZbxl2w4cevNY568XHt0Ad5zV1Br/NS9Nx0tfLkKpUsB3t5+CcmVKpyxD9sMOr4mXaW7a1SbpsBBQIC4sIxWBdpqUjElJhQ7B8OFAr16xZn/+OXD00UW70KUL8PLLAB91WL8ejvXzmCLHy2O//YrJifJLTvlEIBgEomhDMrEjzu8dc7IhdvNaNsSOl6RFIGgEomhDXMaL12xGu7s/cP7a9/iDcdUJRXdOm8bj2c9/wgdzlqHOXnvgxtMaY88KZRWIM0Hz+HuTvTXNTY/VSCxkBBSIC9mAhbm5JiVjUlKh6/uttwIDB8aa/cMPwAEHFO3CVVcBDz8c+/nq1UC1ap67GTlennvuT1BOlD9uyiUCQSEQRRuS7h1x6eSXDbGb2bIhdrwkLQJBIxBFG+Iynr5wDToPnej89bYzm+Ci1r8/BpelQZD9sANr4mWam3a1STosBBSIC8tIRaCdJiVjUlKhQ3DFFcDQobFmb9wIVKpUtAsPPAD861+xn8+cCTRp4rmbkePluef+BOVE+eOmXCIQFAJRtSF+d7RxXNLZUScbYjezZUPseElaBIJGIKo2hJzHz1mGvz8z1UE+rFtLnNykblbxy37Y4TXxMs1Nu9okHRYCCsSFZaQi0E6TkjEpqdAh6NoVGD0a2HPP2LHTZGnUKOC882K/eftt4JRTPHczcrw899yfoJwof9yUSwSCQiCqNoQPLZz1+ESs3rQtJerqlcphTO92KKhVuZBMOnfMyYbYzWzZEDtekhaBoBGIqg0h5/9N+RnXvjzTQT66VxscVVAjq/hlP+zwmniZ5qZdbZIOCwEF4sIyUhFop0nJmJRU6BB06ABMmAAceCAwf37y5nt5WTVFxyPHK8sDLCcqy4BVvAhkmUCUbQiDcQNGz8AXC1YVoZjq1VMKakdcliddXPGyIbljrZpEIBsEomxDhn44D/eN+9bB9uG/jsUBCYs2Xnju2rULy9f/hqVrt6BiudI4tE7VlNnkg3gh+oeMiZdpbtrVJumwEFAgLiwjFYF2mpSMSUmFDsEhhwDffQe0aQMw4JYsLVwINGgQ+83NNwO8V85jihwvj/32KyYnyi855ROBYBDIBxvS67mpGPvNMgf4lccdhFOa1kXjuqmdId0Rl7u5KRuSO9aqSQSyQSDKNiR+d/TMQSeiSsVy1ggZiDvk5rHYun0nTm++Lx79awsF4qwpJs9g8tlMczNDzVAxASOgQFzABiTKzTEpGZOSCh2b6tWBNWuAM88ExoxJ3vzt24EKFYCdO4FLLgFGjvTczcjx8txzf4JyovxxUy4RCAqBfLAhPZ6ZivfnLEO1SuUw7ZYTPaH3e8ecbIgnvLuFZEPseElaBIJGIMo2pM8LX+ON6UtQoWxpzL3tZJQqVcoX/o73fYifVm7Cnwqq46VebRWI80WxaCaTvTXNzQw1Q8UEjIACcQEbkCg3x6RkTEoqVGx++w2oWDHW5MsuA4YNS938+vWBxYuBTp2A997z3M1I8fLca/+CcqL8s1NOEQgCgXywIbwr7uuf1+CgffbE+1d39ITd7x1zsiGe8CoQZ4dJ0iIQWAJRtiF/ffJzTPphJepV2wMTrzvO9xjwrrmtO3ahoGYlHHPw3grE+SZZOKPJ3prmZoaaoWICRkCBuIANSJSbY1IyJiUVKjY2R05btwYmTwZ4lHXuXM/djBQvz732L6hAnH92yikCQSCQDzbkmHs/wMJVm9H6wBp4sWcbz9j93DEnG+IZryMoG2LHS9IiEDQCUbYhJzz4Mb5fvgHN96uG1y5vl3X0sh92iE28THPTrjZJh4WAAnFhGakItNOkZExKKlQIpk4F/vSnWJMfewy4/PLUzXdfV61cOfa6qsft5JHilYPBlROVA8iqQgSySCAfbEjjm8di87YdOK1ZXQy9oKU1zSk/rkLX4ZOcfC0bVMMdZzVNececbIgdXtkQO16SFoGgEYiyDTl1yATMW74BHRrVwoi//e5/ZHEAZD/s4Jp4meamXW2SDgsBBeLCMlIRaKdJyZiUVKgQvP02cNppsSa/9BLQpUvq5l91FfDww7Hfr1oF8G45DylSvDz0N10ROVHpElR+EShZAlG3IV/9vApnPx4LojWvvxfuPqdZsQ81JBsN57Ltm8Zi646d6HzEvhhyvi7bztSslQ3JFEmVIwIlQyDqNoT6/7ftO1GxXJmsA5YPYofYxMs0N+1qk3RYCCgQF5aRikA7TUrGpKRChYCPLlx6aazJn3wCHHNM6uY/+CDQv3/s9zNmAE2beupqpHh56nF6QnKi0uOn3CJQ0gSiakP8HCstbiza3jUeS9ZuQduGNfHff7ROKSobYjejZUPseElaBIJGIKo2JJOcF6/ZjA/mLsev67bgjCPqOfeVJkuyH3bUTbxMc9OuNkmHhYACcWEZqQi006RkTEoqVAjuvhu4/vpYk3nvG+9/S5VGjQLOOy/227feAk491VNXI8XLU4/TE5ITlR4/5RaBkiYQRRvy44qNOPvxiVi9aVtKvNUrlcOY3u1QUKuypyHo/NinmL5oLRrV3hPvXpX6wQfZEE84dwvJhtjxkrQIBI1AFG1IphlP+P5XXPTUF06xj/y1Bc5ovm/SKmQ/7MibeJnmpl1tkg4LAQXiwjJSEWinScmYlFSoEFx9NfDQQ7Emr14NVKuWuvmTJgFtf38ifPhwoGdPT12NFC9PPU5PSE5UevyUWwRKmkAUbci5wybhiwWrjGhbFdTAqF7eHm/4+9NTMH7ucjCA9/UtJ6YsWzbEiL2QgGyIHS9Ji0DQCETRhmSa8dxf1uHkhyc4xd50WmP0OOZABeIyANlkb01zMwNNUBEBJKBAXAAHJapNMikZk5IKFZcLLwT++1+gfHlgy5biH2CIf2H1ppuA227z1NVI8fLU4/SE5ESlx0+5RaCkCUTNhsxesg6nPhJzeLykd/oe4+nOuMuenYpxs5Y5RfY57iCc2rRu0nyyIV6o/yEjG2LHS9IiEDQCUbMhLt83pi/BTa9+gxqVy+Oh847AEfsVs/hvGJRVG7ei5W3vOVKXdTgQ15/aOGkO2Q+72W3iZZqbdrVJOiwEFIgLy0hFoJ0mJWNSUqFC0KkTMH48sN9+wM8/F9/07duBChWAnTuBSy4BeL+chxQpXh76m66InKh0CSq/CJQsgajZkIfe+w5Dxn/vGWq/TgejX6dGKeVt75qTDfGM3hGUDbHjJWkRCBqBqNkQl+8zny3AwNdnOX99s097NKm3l2/0O3fuwiE3v4NtO3bhrBb1nMBesiT7YYfYxMs0N+1qk3RYCCgQF5aRikA7TUrGpKRChYAPLnzzDXDkkcDUqeam168PLF4MHH888P77ZnmDU+CpgDwTkhOVZwOu7kaOQNRsyOA3ZmHkxAWex6l7uwIMPP3wpPJ+7pqLlM31TNG/oGyIf3bKKQJBIBA1G+IyfW/2Mrw0dSFWb9qKxy5oidpVK6aFu81d47F07Ra0P6gWnutxtAJxadGMZTbZW9PczEATVEQACSgQF8BBiWqTTErGpKRCxaV2bWD58tjDC3yAwZTatAE+/zz2qAMfd/CQIsXLQ3/TFZETlS5B5ReBkiUQNRuSyR1xfu6akw2xm8+yIXa8JC0CQSMQNRuSLb5eHvyR/bCjb+Jlmpt2tUk6LAQUiAvLSEWgnSYlY1JSoUGwY0fsbjgeNe3eHfj3v81N79oVGD0aqFQJ2LCh+Dvlfi8tMrzMdDIiIScqIxhViAiUGIGo2ZBM3RHntxzZELupLBtix0vSIhA0AlGzIdni2+OZqXh/zjJUq1QO01I8+CP7YUffxMs0N+1qk3RYCCgQF5aRikA7TUrGpKRCg2DZMqBOnVhzr70WuPtuc9PjX1ldtQqoXt2YJzK8jD3NjICcqMxwVCkiUFIEomhD/OxkS+Tvd2edbIjdTJYNseMlaREIGoEo2pBsML7+lZl44YvY/dbf3n4yKpQtU6Qa2Q878iZeprlpV5ukw0JAgbiwjFQE2mlSMiYlFRoEM2YAzZvHmvvgg8BVV5mbTrn+/WNy06cDzZoZ80SGl7GnmRGQE5UZjipFBEqKQBRtCB9YOOvxiVi9aVtKrNUrlcOY3u1QUKtyUhm/d83JhtjNZNkQO16SFoGgEYiiDXGCZb+sR8VypZ1XU6tULJc29vjFnYnXHYd61fZQIC5NqiZ7a5qbaVav7AEloEBcQAcmis0yKRmTkgoNEz62cMIJseY+/zxwwQXmpr/0EnDuuTE53inHu+UMKTK8TB3N0O/lRGUIpIoRgRIiEFUbwmDcNaOnY8qC1UXItiqogXu7NEsZhGMG7YjLzYSUDckNZ9UiAtkiEFUb0u7uD7B4zeZiH1ewYfr85J9w45hvnCxjerdFiwZFT+nIB7Ehqsca7Gjlj7QCcfkz1iXe06gawCJgGXzr1i32Ywbl+BKqKU2aBLRtG5MaNgy47DJTDuMLPMYC8kxATlSeDbi6GzkCUbYhG3/bjsMHjnPGrHHdKjjp8DrOf43rVjWOo+6IMyLKiIBsSEYwqhARKDECUbUhjW8ei83bduAvzeo6r6amm96d9Qt6PvulU8zwi450bFFiUiDOjrKJl2lu2tUm6bAQUCAuLCMVgXaalIxJSYUGQfwxUx5TbdrU3PRFi4D99ovJ3XQTcNttxjyR4WXsaWYE5ERlhqNKEYGSIhBlG7Jw1SYcc++HDtr+JzRCn+MPtsLs56452RArxMUufpnmpl1NkhYBEcgGAdO/0zDqxC3bduDQm8c6uC5usz9u7dwkbXRf/7waZz3+mVPO7Wc2QbfW+xcpM4ys0gaTRgEmXqa5mUbVyhpgAgrEBXhwotY0k5IxKanQ8LjuOuCee2LN5cMN++xjbvr27UCFCrGXVv/2N+Dpp415IsPL2NPMCCgQlxmOKkUESopAlG3I9IVr0HnoxGIdn+K4+7lrTjbEbibLhtjxkrQIBI1AFG3I0rWb0eauDxzUfY8/GFed0Cht7PELQ1d1aoS+nYouDMl+2GE28TLNTbvaJB0WAgrEhWWkItBOk5IxKanQIOjePRZIK10a2LoVKFP0taGkfeGOOO6M41FWHmk1pMjwMnU0Q7+XE5UhkCpGBEqIQJRtyIffLkf3kVMcsk9c2BKnNK1rTZnBuAGjZ+CLBauK5E1215xsiB1i2RA7XpIWgaARiKINmbVkLU575FMH9aDTD8Ml7Q5IG3v8LruLWu+P284sustO9sMOs4mXaW7a1SbpsBBQIC4sI5WBdl5yySV45plnUpZ0++2348Ybb3R+v2PHDtx3330YMWIEFi5ciP322w89evTANddcgzJeA0sJNZmUjElJZQBBborgQwvvvAPUrg388ov3Otu0AT7/HGjUCPj2W2O+yPAy9jQzAnKiMsNRpeQvAdmQ7I39y18uQv+XpjsVvNizNVofWNN3ZXOWrsONY2biq5/XOGW8dFkb/OmAGkXKkw2xQywbYsdL0iKQSEA2JPNzYuK8FbhwxGSn4CHnH4HOR9TLSCVNBo7Dht+245QmdfBEtyNlP9KkarK3Jh85zeqVPaAEFIgL6MBko1mTJk3C/PnzixQ9ZMgQTJ06FV9++SVatoxd8tm7d2888cQT6N69O9q2bYvPPvsMI0eOdH4+dOhQX80zKRmTkvJVaUlkOvJI4KuvYnfD8Y44r4mvpvL11EqVgA0bgFKlis0ZGV5e+aQpJycqTYDKnvcEZEOyNwVGTPgBt781x6ngvas64ODaVdKq7ImP5uOesXOdMsb374iGe+8pRyotosW/emf6vkmzamUXgUgQkA3J/DC+MX0J+rzwtVPwfy5thQ6N9s5IJcfe9yEWrNyEPxVUx0u9fn9MLq5k+SB2mE28ZEPseEZFWoG4qIykz35s2rQJderUQUFBAWb8HjSaOXMmmjdvjj59+oBBOjf17dsXjz76KKZPn46mXh4gSGiTScmYlJTPLuY+m3vEtFMn4L33vNd/9dXAQw/F5FeuBGoU3cEQX1hkeHknlJakAnFp4VNmEUhKQDYkMxODQTMGz5im3tQJtfaskFbBo6YudI6pMr3Uqw3+VKAdcWkBhQJx6fJTfhFIRkA2JL158Z9JC3DLa7OcQt7s0x5N6u2VXoG/5+Zr3BXLlcbeVSqgSsVyRcqUD2KH2cTL5CPb1SbpsBBQIC4sI5Wldj7//PPo1q0b7r//fvTv39+phcdT77zzTvzwww844IA/7hr48ccfceCBB+KGG27AHXfcYd0ik5IxKSnrCksiw65dQMWKsbvhLrwQeO45761gEI7BOKbp04FmzYrNGwle3umkLalAXNoIVYAIFCEgG5L+pKDDc83o6Zi1ZN3vzlQ7NKlXLa2Cx89Zhr8/M9UpY1i3lji5SdE752RD7BDLhtjxkrQIeCEgG+KFUmqZIe9/j4fe/84RmHjdcahXbY/0CvSYW/bDI6jfxUy8TD6yXW2SDgsBBeLCMlJZaueJJ56IDz/8EIsWLUJt3mkG4KSTTnJ2vf2S5H4zyrRo0QJjx8aeyrZJJiVjUlI2dZWY7OrVf+xkY1DtgQe8N4XHUnk8lenNN4HTTis2byR4eaeTtqScqLQRqgARKEJANsT/pLB9XMGmpmkL1+BMwyussiE2RLUjzo6WpEXAGwHZEG+cUkkNen0Wnv5sgfPr2beehErly6ZXoMfcsh8eQf0uZuJl8pHtapN0WAgoEBeWkcpCOxcvXowGDRrglFNOwZsM/PyeeOy0fPnyzp1xiYl3yG3btg08vlpcWrp0KfhffJozZ46z++6jjz5yjr4mpvXr14OKiHVUqZLe/ThZwOWpyNLffYeqRx/tyG4eOBC/9evnKR+FykyZgionnujIb3rwQWzl66vFpCjw8gwnA4LF8WLg+dhjjy10T2IGqlQRIhBpArIh/of3p1Wb8bdnZ2DN5u0pC6m2R1n85+JmaFDdfofD4jVbcNqwmA3vfUwD9Gy3XyRtrv8RsM8pG2LPTDlEoDgCsiHpz4/rXv8WY2evQIWypfF5/9YoZbhfOv0aYyXIB7EjaeIlP8SOZ1SkFYiLykj66Mfdd9+N66+/Hi+99BK6dOmyu4SGDRs6u+P4QENi4sMNy5cvx7x584qtcdCgQRg8eHBSmQceeACsI4qp5qxZaP/7y7Nf9emDhccf77mbFVeswEk9ejjy33btirk82qqUEwJ8xIRHs+MfLMlJxapEBEJMQDbE/+A98k0ZzF9f/IM8LL1hlV24sskO64p+2wEM+CK2M2LfSrvQrAb/24l6la2LUgYPBGRDPECSiAgkEJANSX9KPDG7NOauLY29yu/CrUfa24pULZi3Dvh4aWms31YK5x6wA/vKdqQ/WMWUIBuSVbyBLVyBuMAOTfYbdthhhznHT7lzrUKFPy6G1o44/+zLvfoqKv++k23DqFHYfsIJ3gvbsQN71a6NUjt2YOtf/4pNjz9ebF7T6or3ivNDUrsZ8mOc1cvcEZAN8cf622Ubcd7IaZ4zj7r0CDTax7sX9PPqzRj01jx8tSh251x8alm/KgaddpCzy042xPMQOIKyIXa8JC0CJgKyISZC5t9f8PR0zP5lAw7euxJe+nsLcwaPEu/PXYF/vfqtI/1Il8bocFDhB39kPzyC/F3MxEs74ux4RkVagbiojKRlP6ZMmYJWrVqhd+/eGDp0aKHcuiPOEma8+GOPAX36xH4ydSpw5JF2hbkvrh53HDB+fLF5TfcN2FUcfWndERf9MVYPc0dANsQ/64fe+w5Dxn/vuYB+nQ5Gv06NPMn/uGIjzn58IlZv2pZSvnqlchjTux2qld2Gjz/+GB07dkS1auk9DuGpcSEXkg0J+QCq+YEiIBuSmeHoeN+H+GnlJhx9QA3877I2mSkUwJQFq3DpyCmoVaUCbjqtMY5vHLtH3E3yQexQm3jpjjg7nlGRViAuKiNp2Y8rrrjCCcBNnjzZCcjFJ76Ketddd+nVVEumjvjNNwO33x7LuXAhUL++XSlt2wKTJgGNGgHfxlaiUiWTUrerOPrScqKiP8bqYe4IyIb4Zz34jVkYOTF2ubaX1L1dAQaefrgXUZw7bBK+WLDKKNuqoAaePL+xAnFGUn8IyIZYwJKoCBgIyIZkZoo0H/wu1m7ehhMPq40nLz4qM4UC2LVrV7H3zckHsUNt4qVAnB3PqEgrEBeVkbTox9atW7Hvvvtin332wezZs4vk5PZYvozap08fDBkyZPfv+/bti0cffRTTpk1Ds2bNLGqMiZpV969aAAAgAElEQVSUjElJWVdYEhkuuwx48slYzb/9BpQvb9cKvprK11P32APYuBEo5tLVSPCyo5OWtJyotPApswjsJiAbkt5kyNaOuNlL1uHURyZ4bhyPvC6dM1U74jwSkw3xCEpiImAgIBuSmSmyc+cuNLzxbezaBXQ9sj7u61r0IbzM1FS0FPkgdmRNvEw+sl1tkg4LAQXiwjJSGWznK6+8gnPOOQe8JPXaa69NWnKvXr0wfPhwdO/eHe3atcPEiRMxcuRIXHbZZRg2bJiv1piUjElJ+ao015nOPBN47TWgenVglXlXQpHm9e8PPPhg7McrVwI1Ct/JEC8fCV45HB85UTmEraoiTUA2JL3htQ2YvdP3GDSuW9VYqW2Ar1f7/dB4x48KxBnJxgRkQzyCkpgIGAjIhmRmimzbsRPPTvoJazZvw+H7VsVJh9fJTMEeSpEP4gFSnIiJl8lHtqtN0mEhoEBcWEYqg+3s3Lkz3nzzTSxcuNDZGZcsbd++Hffeey9GjBiBRYsWoX79+ujRowcGDBiAsmVjL7HZJpOSMSkp2/pKRL5NG+Dzz4FDDgHmzrVvwkMPAVdfHcs3bRrQPPXqViR42RPynUNOlG90yigChQjIhqQ/IWyOkI7q5e3eH9sjrxccVRdHl1uoQJzH4ZQN8QhKYiJgICAbEp4pwiOqv23fiYrlyhRqtHwQuzE08TL5yHa1STosBBSIC8tIRaCdJiVjUlKhQNCwIfDDD0CHDsDHH9s3efRooGvXWL433wROOy1lGZHgZU/Idw45Ub7RKaMIBIJAlGzIghUbcZbHRxUKanl7MVU74rI7TWVDsstXpYtAtglEyYZkmxXL7/HMVEz4/lcU1KyMcVd1UCAuDegmn800N9OoWlkDTECBuAAPTtSaZlIyJiUVCh577hm7243BtFGj7JvM3XTcVcf0xBNAr14KxNlTTJpDTlSGQKoYESghAlGzIQzGDRg9I+njCnxM4d4uzeA1CMchsT3yqjvi7CaybIgdL0mLQNAIRM2GZJvvpU9PwQdzl6Nm5fL48uYTFIhLA7jJxzXNzTSqVtYAE1AgLsCDE7WmmZSMSUkFngcDcAzEMV1xBfDoo/ZNXrz4j5dWb7zxjxdYk5QUel72dNLKIScqLXzKLAIlTiCqNmTA6OkYNXWRw7dnhwNxVot6nu6ESzYgNkde9Wqq3ZSWDbHjJWkRCBqBqNmQecs3YOqCVdhrj3JofWBNVK9s+UCcYYD+9dJ0jP5yEUqXAubdcSpK8w+/J/kgdrPbxMs0N+1qk3RYCCgQF5aRikA7TUrGpKQCj4BHUnk0lenWW4Gbb7Zv8o4dQIUKAP9/8cXAM8+kLCP0vOzppJVDTlRa+JRZBEqcQFRtyPWvzMALXyx0+M674xSULVPaN2ubI6/Vym7Dxx9/rDviPNKWDfEISmIiEFACUbMhz0/+CTeO+cah/drl7dB8v2oZJX/XO3Mw/OMfnDK/uvkE1IgL9MkHsUNt4mWam3a1STosBBSIC8tIRaCdJiVjUlKBRxB/rHT4cKBnT39NbtAAWLgQOO44YPx4BeL8USySS05UhkCqGBEoIQJRtSG9nv0SY2f9gioVy2LmoJPSpuv1yGvobW7apOwKkA2x4yVpEQgagajZkKEfzsN94751MH98zbHYv6a3+0S9jsuTn8zHnW/HHp57/+oOOGifKruzyn54pRiTM/EyzU272iQdFgIKxIVlpCLQTpOSMSmpwCN47TXgzDNjzXz1VaBzZ39NbtsWmDQJOPhg4LvvUpYRel7+6PjOJSfKNzplFIFAEIiqDTlv+CRM/nEVGtSohE8G/DljrHlkqcuwSU55LRpUw51nNS105FU2xA61bIgdL0mLQNAIRM2G/Lr+NyxcvQlrN21Dm4Y1i7xsmi5/Hkvl8VSmF3u2do6/ukn2w46uiZdpbtrVJumwEFAgLiwjFYF2mpSMSUkFHsGTTwKXXRZrJgNprVv7a/J558Ueethjj9jDD6X+uJMhvsDQ8/JHx3cuOVG+0SmjCASCQFRtyEkPfYJvl61Hs/p74fUr2meM9a5du9DopnewbccunN2iHh4874hCZcuG2KGWDbHjJWkRCBqBqNqQbHH+cO5ydH96ilP84xe2xKlN6yoQ5xO2yd6a5qbPapUt4AQUiAv4AEWpeSYlY1JSgWdx223ALbfEmjl/PnDggf6a3L8/8OCDsbwrVgA1/1iBUiDOH1LmkhPln51yikAQCETVhhx95/tYtu43dGi0N/5zaauMom51x/tYvv43dGy0N55JKDv0NjejpMyFyYaYGUlCBIJMIKo2JFvMZyxagzMem+gUf1vnw3FRmwIF4nzCNtlb09z0Wa2yBZyAAnEBH6AoNc+kZExKKvAs+vQBHnss1swNG4DKPu9qePhh4KqrYuVMmwY0b56066HnleMBlROVY+CqTgQyTCCKNoS71g65eSy2bt+JzkfsiyHnt8gotZMf/gRzf0m+2042xA61bIgdL0mLQNAIRNGGZJPxotWb0P6eD50q+nU6GP06NVIgzidwk701zU2f1SpbwAkoEBfwAYpS80xKxqSkAs/i3HOBl16KBeAYiPObRo8GunaN5X7jDeAvf1Egzi/LuHxyojIAUUWIQAkSiKIN2bR1Ow67ZZxD9ZK2BRh0xuEZJfzXJz/HpB9Won71PfDptccVKjv0NjejpMyFyYaYGUlCBIJMIGo25PY3Z2PDb9txaJ0quKTdARlHv3nrDjS+ZaxT7sVt9setnZvsrkP2ww63iZdpbtrVJumwEFAgLiwjFYF2mpSMSUkFHkHHjsAnnwAHHAD8EHvu21eaPPmP++WeeALo1StpMaHn5QuO/0xyovyzU04RCAKBKNqQxWs2o93dHzh4E3ccZIL55f/9Cm/NWIpK5ctg9q0nFypSNsSOsGyIHS9Ji0DQCETNhrS9azyWrN2C9gfVwnM9js4K7sNuGYtNW3fgtKZ1MfTClgrE+aRssremuemzWmULOAEF4gI+QFFqnknJmJRU4Fk0bgzMnRsLovGxBr9p8WKgfv1Y7htuAO64Q4E4vyzj8smJygBEFSECJUggijbk9WmLceWL0xyqxzbaG9eecmihl03TxX3zq9/g2c9/coqZe9vJhV7VC73NTReOZX7ZEEtgEheBgBGImg05/Jax2JgkSJZJ7O3v+QCLVm9G6wNr4MWebXYXLfthR9nEyzQ37WqTdFgIKBAXlpGKQDtNSsakpAKPoEYNYPVqoHNn4NVX/Td3xw6gQgWA/7/4YuCZZxSI80/T00eDaW5moHoVIQIikCYB07/TMNmQBSs2YsDoGfhiwaoiVFoV1MC9XZqhoJbPe0bjSrz+lZl44YufnZ9c2q4AXY/ab3egL0y80pw6GcmuQFxGMKoQESgxAlGyIdt27MTBN77jsLzg6Aa486ymWeHa+bFPMX3RWjSqvSfevaqjp2/qrDQk5IWa7K1pboa8+2p+CgIKxGlq5IyAScmYlFTOGuqnoq1bY8Ezpp49geHD/ZTyR54GDYCFC4E//xn4IHZsKTGFmld6dHzllhPlC5syiUBgCETFhvy4YiPOfnwiVm/alpJt9UrlMKZ3O9/BOC+Bvmplt+Hjj/+fvesAz+l64z8hRkIEMWImiBXEXkGMIJSqUXvUaEtUUaNG/Vtq79BaVXTY1KpRsYkRe8YWW4gVEiHr/5z7SRskzr3fd797z/3y3ufpU/G9533f83vP9/68b849Zw98fHzg7OwsTJxFdYQ4RNTIkF+EgDwEbIVD2GzDX7xCpTHbpYn3rlME3/qVkAeCQqnui49g54UHyOGYHsdGNvh3NNUgyoDk4cVbm8qskbRREKBGnFEiZQN+8pIML0kJDcHt20CBAiYXv/sO+PFHy9z19gYOHAA8PIBLl5LVZWi8LEPHrNFURJkFGw0iBIRBwFY4pM3cg8nuhHsXaLYzbmWv/14FkhsIuY2+3zqXwfXTwdSIkwkscYhMoEiMEBAUAVvhEAbv1YcvUH/qHgnpYY1L4EufIlZBfdCqU1h97Dbs0gCXxzZBWvYHAFSDKIObhxdvbSqzRtJGQYAacUaJlA34yUsyvCQlNATHjwMVK5pcnDUL+Oory9xt2xZYuRLImBGIigLSmIgv6WNovCxDx6zRVESZBRsNIgSEQcAWOOT83Qg0mblPNqZb+tVSfGac3EZfhfxO6FrgMTXiZEaDOEQmUCRGCAiKgC1wSCK0x28+QcvZB6QfJ7Qsg3ZVCloF9fGbQzBvr+kCumPf+SJHZtPbP1SDKIObhxdvbSqzRtJGQYAacUaJlA34yUsyvCQlNARbtgBNmphcZA20Tz+1zN1Bg4CpU006wsOBHDne02dovCxDx6zRVESZBRsNIgSEQcAWOGR64CUE7LgsG1OlN6kqbfQNKRuLDk3o1VQ5ASEOkYMSyRAC4iJgCxySiO6uiw/QbdER6cfZHSugSRlXqwC/4dRdbDp9V2rADWxQjBpxZqLMq9l4a9NMszRMcASoESd4gGzJPV6S4SUpobFYvBjo1s3k4p49QO3alrk7YwYwYIBJx4kTQLly1IizDNEP/vaOtzYtNE3DCQFCQAUEeN9TI3DIqI3nsCgoVDYa3bzd8H0zT9nySht9fvnjMKFTbTojTgbC1IiTARKJEAICI2ALHJII7/qTd9DvzY3bS3pWhXdRF02RNwLfagoIxxgPL97aFGku5It6CFAjTj0sSRMHAV6S4SUpoQGeOBEYOtTkYkgIUMLCQ1PXrAFatzbp27gRaNqUGnEWLgAqoiwEkIYTAjojYAscorRRpnRHnNJGn0+eeAR8VosacTLWNnGIDJBIhBAQGAFb4JBEeP84dAMj1501lQlf1USZ/Fk1Rd7QNZumSJmM8fDirU0dXCaTGiBAjTgNQCYTJgR4SYaXpITGceBAYNo0k4uPHwPZslnm7uHDQLVqJh2zZwO9e7+nz9B4WYaOWaOpiDILNhpECAiDgC1wiNJXR5WeEae00Uc74uQvb+IQ+ViRJCEgIgK2wCGJuM7efQWTtl6UftwzuA4K5XDUFHKqQZTBzcOLtzaVWSNpoyBAjTijRMoG/OQlGV6SEhqCTp2AJUuA9OmB6OhkL1dQ5P/du0C+fKYhw4cDY8dSI04RgO8LUxFlIYA0nBDQGQFb4RC5lymYc2uq0kYfnREnf1ETh8jHiiQJARERsBUOYdhO2HIBc/dclWA+MbIBsjmmtwrkcfEJuPk4Co8jXyObgz0K58ws2TF0zWYVpD6slIcXb23q4DKZ1AABasRpADKZMCHASzK8JCU0jg0aANu3A/nzA7duWe5qXJzpxtTYWKBzZ+D336kRZyGqVERZCCANJwR0RsBWOCQ0PBItZgfhSVRMioiygmetvzfcXJTvcpDb6KNbU5UtaOIQZXiRNCEgGgK2wiEM1+Frz2Dp4ZsSxJfHNoZ9WjurwB31Ohal/vePpLtr9UIY1bw0NeLMQJpX4/LWphkmaYgBEKBGnAGCZCsu8pIML0kJjYOXF3D6NFChAnDsmDquFioE3LwJ1K0L7NxJjTgLUaUiykIAaTghoDMCtsQhrBk3ePUpHAl98h6qbCfcpNZlzWrCMWVyG32/dS6D66eD4eNDt6bKWdrEIXJQIhlCQFwEbIlDvlp6HH+fvgeH9GlxfrSfVUEvMXILomPi0bSsK37qUIEacWagzatxeWvTDJM0xAAIUCPOAEGyFRd5SYaXpITGIU8eICwMaNwY2LxZHVe9vYEDB4CiRYHLl6kRZyGqVERZCCANJwR0RsDWOOR5dAzK/LBNQtUzrxMalMqNRp55UNLVyWKkWTNuyOrTCA59nGKjzzldDPbs2UONOJloE4fIBIrECAFBEbAlDumyMBh7Lz1EHqeMODS8vlUR/+1AKDKks0PRXJlRyS07NeLMQJtX4/LWphkmaYgBEKBGnAGCZCsu8pIML0kJiwN7jZSdDRcfD3z2GbBokTqutmsHrFhhekU1Kuq9c+cMi5c66CjWQkWUYshoACEgFAK2xiG3Hkeh1qRdEsYDGxRD3/oequMdci8Cw/46g5O3nkq61/SugYqFTJcJEYcog5s4RBleJE0IiIaALXHIJz8HSXm9WO7M2DbAR3OoiT+UQc7Di7c2lVkjaaMgQI04o0TKBvzkJRlekhIWggcPgNy5Te4NGQJMnKiOq4MGAVOnmnQ9fAi4uLyl17B4qYOOYi1URCmGjAYQAkIhYGsccvbOMzSdtV/C+Mfmnuhc3c0qeM/ccRnTAi9JuvcNqYsC2R2kPxOHKIObOEQZXiRNCIiGgC1xiN+Mvbhw/zkqFcqG1b1raA418YcyyHl48damMmskbRQEqBFnlEjZgJ+8JMNLUsJCcPYsUKaMyT3WOPvmG3VcDQgA+vc36TpxAihX7i29hsVLHXQUa6EiSjFkNIAQEAoBW+OQfZcfovOvwRLGM9uXx8deea2C9x+HbmDkurOS7g1feaNsfmfpz8QhyuAmDlGGF0kTAqIhYGscEh0Th1cx8cjqYK851MQfyiDn4cVbm8qskbRREKBGnFEiZQN+8pIML0kJC8GOHYCvr8m9P/8EOnZUx9U1a4DWrU26NmwAmjV7S69h8VIHHcVaqIhSDBkNIASEQsDWOGTjqbvou+yEhPHv3augdrGcVsH779N38dVSk53fuleBzxs7xCHK4CYOUYYXSRMCoiFgaxyiFb5nbj/DkdDHeBL1Gr3rFIFD+nT0ixyF4PP4lrc2FZojcYMgQI04gwTKFtzkJRlekhIWg6VL/2u+BQb+15Sz1OHgYKBqVZOW2bOB3r2pEWcBplREWQAeDSUEBEDA1jgkpZ1qakN94Eo4Oiw4LKmd0bYcPimfT/qzYTlXbYBk6iMOkQkUiRECgiJgaxyiFcw/7byMKdtMxxvsHVwXBXM4EH8oBJ/Ht7y1qdAciRsEAWrEGSRQtuAmL8nwkpSwGEyf/t/rqKdOAWXLquPq3btAPlPBhGHDgHHjqBFnAbJURFkAHg0lBARAwNY4JLnixhowswsbGgfsk1T/r2kpdK/pTo04M4AmDjEDNBpCCAiEgK1xiFbQLjl8AyPWmo43WOtfA+ULZqNGnELweTUub20qNEfiBkGAGnEGCZQtuMlLMrwkJSwGrEk2YYLJvfv3/7u4wVKH2W2s7MbU2Figc2fg99+pEWcBplREWQAeDSUEBEDA1jhkzN/nsWD/dQnZU983RNZM1jnn5/6zaFQbv0Oy83W9ovimYXFqxJmxnolDzACNhhACAiFgKxwSGh6JzxYFwymTPb6oXRhNy1rnfNHE0G09ew+9/jwu/bjws0qoVyI3NeIUrmtejctbmwrNkbhBEKBGnEECZQtu8pIML0kJi0H37sCiRYCdHfD6NZA2rXquFioE3LwJ1KkD7NpFjTgLkKUiygLwaCghIAACtsYhg1adwupjt5HWLg2ujG2MNGnSWAVldqB3iZFbJd2dqhXEmE9MlwsZlnOtghJfKXEIHyOSIARERsBWOOTEzSdoMfuABPX4lmXQvkpBq8J++NojtJ1/SLIx5VMvtK6Yn/hDIeI8vuWtTYXmSNwgCFAjTtBAXbhwAVevXsXjx4+RkJDwnpddunQR1POU3eIlGV6SEnbCH30EbN4M5MoFhIWp62bNmkBQEFC0KHD5MjXiLECXiigLwKOhhkOAOMR0M6jIT8/fjmJ7SBiyO6bH8ZENrOpqie+2IDo2Hm45HNC8XD74lc4D10zx2LNnD3x8fODsLD5eVgVIhnLiEBkgkYjNIEAcIm5OPHvnGUb/fR4RL2MwxK+4tEPNms+VB8/hO22vZGJ4kxL4onYRasQpBJxX4/JqZIXmSNwgCFAjTrBA3bx5E507d8b+/fuTbcAxd9lvzePYa4sGe3hJhpekhJ1u5crA0aNA6dLAmTPqutm+PbB8uekV1agoFvx/9RsWL3URkq2NiijZUJGggREgDjFGY+n83Qj0/O0I7j6LhnMmeyz7ohpKujqpvvLYK0xDVp9GcOjj93RXyO+EJi6P0dqPGnFygCcOkYMSyRgdAeIQY3CIluvs0YtXqDhmu2Syl08RDG1cghpxCgPAq9l4NbJCcyRuEASoESdYoJo0aSL9hnrcuHHSb6mzZcuWrIeF2CuLBnt4SYaXpISdbsGCwK1bQP36wHYTUan2DB4MTJliUvfwIeDi8q9qw+KlGjjKFFERpQwvkjYmAsQhYhdRH2qMVXHLjkmty8LNxVGVxXc9PBItZwfhSVRMivoc0yVgWY+KKOvuqopNW1ZCHGLL0aW5JSJAHCI2h+ixUuPiE1B0xGawF7TaVMqPSa29qBGnMBC8mo1XIys0R+IGQYAacYIFytHREQMHDsTo0aMF88xyd3hJhpekLPfAChoYK7HdauxsuA4dgCVL1DUycybQr59J5/HjQPny1IgzE2EqoswEjoYZCgHiEHGLKDmNsWwO9ljr761KM67N3IPJ7oR7d0GznXF/fVXLUOtcD2eJQ/RAnWxqjQBxiLgcovVaSGqv/Oht0i91fEvmxoKulagRpzAYvBqXVyMrNEfiBkGAGnGCBSp37tz4/vvv4e/vL5hnlrvDSzK8JGW5B1bQ8PQpkLhrccAAYNo0dY389RfQqpVJ54YNQLNm1IgzE2EqoswEjoYZCgHiEHGLKLmNMbYzbmWv6hatO/bqa5OZ+2Tr2NKvllVejZXtgAEEiUMMECRy0WIEiEPE5ZDE4D6LikECEpA5QzqkS2tncczlKKg/dTeuPoxEhYLO+MvfmxpxckBLIsOrcXk1skJzJG4QBKgRJ1igBgwYgHPnzmHbtm2CeWa5O7wkw0tSlntgBQ2XLgHFi5sUjx8PDB2qrpEjR4AqVUw6f/4ZSNKgNSRe6qKjSBsVUYrgImGDIkAcImYRpXVjbHrgJQTsePuCnw8t6f6+HujvW8ygq14bt4lDtMGZrOiLAHGImBySdFV8t+4M/jx0U/qrS2MaI3066zfjPp17AEdCn8DdxRG7BtWhRpzCrymvZuPVyArNkbhBEKBGnGCBOnv2LLp37458+fJJu+Lc3NyQNm3a97wsXLiwYJ7z3eElGV6S4lvQQWLfPqB2bZPhhQuBbt3UdeLePSBvXpPOYcOAceP+1W9IvNRFR5E2KqIUwUXCBkWAOETMIkrrxtiojeewKChU9iru5u2G75t5ypZPjYLEIakx6qlvzsQhYnJI0pXYb/kJrD95FxnS2eHimMaaLNIv/ziKf86FwSljOpz+oRE14hSizqvZeDWyQnMkbhAEqBEnWKDs7OykW1ETEhKk/6f00K2pggRu9Wrg009NzmzaBDRpoq5j8fFAhgxAbCzQqRPwxx/UiDMTYSqizASOhhkKAeIQMYsorRtjWjf+DPUlMdNZ4hAzgaNhhkKAOERMDkm6iLotCsauiw+RM0sGHBnhq8n6GvbXaSwLviXZujK2MV48j5AuF2QXCzo7O2vig5GNUCPOyNGznu/UiLMetmZp/uGHHz7YgEtUys6RM9rD6/bzkpSQ82Wvi371lck19hpppUrqu+nmBty4AdSpA+zaRY04MxGmIspM4GiYoRAgDhGzMNC6Mab1q7CG+pKY6SxxiJnA0TBDIUAcIiaHJF1EreYcwLEbT1A4pyN2DqyjyfqatPUCZu++Ktk6+p0v0sW+pEacAuR5NS6vRlZgikQNhAA14gwULKO7yksyvCQl5PxZQzTxhtubN4ECBdR3s1YtYP9+oEgR4MoVasSZiTAVUWYCR8MIAUEQMDKH6NEYk3s5BN2aKm+BE4fIw4mkCAFRETAyhyTFtMG0Pbj84AXKFXDGuj7emsC9YN81jNkUItkKHFAbOTPEUSNOAfK8Gpe3NhWYIlEDIUCNOAMFSy1X7927h9GjR2PTpk0ICwtDjhw5UKVKFcybNw/stqTE55dffkFAQACuXLmCnDlzokOHDmC/KcuUKZNZrvCSDC9JmWXU2oN69QLmzTNZiY42vUaq9tO+PbB8uUn3y5fAm1eWDYmX2tgo0EdFlAKwSJQQEBABo3OI3MaYGremsvCFhkeixewgPImKSTGajukSsKxHRZR1dxUw4mK5RBwiVjzIG+MiQHWIZbGrPn4H7j2LRi0PF/zRo6plymSOXnPsNgauOiVJr/iiGopnT0uNOJnYMTFezcb7940CUyRqIASoESdgsNj5bwsXLsT69etx/fp16VVVd3d3fPLJJ/jss8+SvbxB7jQuX76M2rVrS800pit//vx4+PAhDh48iMmTJ8PDw0NSNWnSJHz77bdo3rw5PvroI5w/fx6zZs2Cn58f/v77b7nm3pLjJRlekjLLqLUHtWgBrFsHsPMRnjyxjrUhQ4DJk026HzwAcuaU/mhIvKyDkCytVETJgomEbAABa3IIg4eKKPMWiZzGWDYHe6z194abi6N5Rt4ZxWwOWX0awaGP39PHdsI1cXmM1n50xo8csIlD5KBEMraAgDU5hOoQy1dI6e//wYtXsWhSJg9md6xouUIZGnZdeIBui49IknM7VUC1/JmoEScDt0QRXs3Gq5EVmCJRAyFAjTjBgvXixQs0atQIhw4dkpplrAHHntDQUERFRaF69er4559/4Oio/B/p7AKIqlWrghEsO2Azc+bMyc6eNeYKFSqEBg0aSM3AxGf69On45ptvpEYca84pfXhJhpeklNrTRL5GDeDgQaBYMeDiReuYnDkT6NfPpPv4caB8eemPhsTLOgjJ0kpFlCyYSMjgCFiTQxg0VERZtkA+1BhjO+EmtS6rWhMuqacnbz7FJ7ODpL/yyp8VE1qVhWumeCqkFISTOEQBWCRqWASsySFUh1i+LOLiE1Bk+GZJUdtKBTCxdVnLlcrQ8OxljLTLOrtjeumSiOjI58QfMnBLFOHVbLwaWYEpEjUQAtSIEyxYgwYNwrRp0zBhwgR8/fXXyJgxo+Thq1evMHPmTAwdOlRqhrHda0qfnTt3on0RrAkAACAASURBVH79+ti4cSOaNm2K6OhosNuR0qdP/5Yq9krqF198ASZft27dfz9jjUD2GmvLli2xZMkSpebBSzK8JKXYoBYDihYFrl4F2Dlue/dax+LatUDLlibdrDH68cfSHw2Jl3UQkqWViihZMJGQwRGwJodQEaXe4ui95Bi2nLkvKfy6XlE0LuOKkq5O6hlIRlOJkVsQHROPZl55Mat9eeIQhWgThygEjMQNiYA1OYTqEMuXBGuIeY3aJinqWdMd3zUtZblSMzRQDaIMNB5evBpZmTWSNgoC1IgTLFJubm7w9fXFggULkvWsR48e2L59O26wWzQVPkOGDJEaeLt378bw4cNx4MAB6bVXtkuONf/Ybjv2fPnll5g/f760A+/d8+CY7LNnz3DhwgWF1tlmruOoWLEijh07hgoVKrw3npekFBvUYkCWLMCLF0Dr1sCqVdaxyG5jrVLFpPunn4A+faQ/GhIv6yAkSysVUbJgIiGDI2BNDqEiSr3F0WfJcWw6cw+O6dPi3Gg/9RR/QNO75woRhyiDnThEGV4kbUwErMkhVIdYvibuPH0J7wk7JUX9fT3Q37eY5UrN0ED8oQw0Hl68GlmZNZI2CgLUiBMsUhkyZJAuSOjFLgFI5pk7dy769esn7ZBT+rAz5tirpi4uLqhVqxbat2+Pu3fvShc3sKZbcHAwypQpg2bNmklNukePHr1ngu2GCwwMxPPnzz9onp0hxP5L+oSEhKBTp05SI9DLy+u98UwnS0SsSZeFNbhEf6Ki4Jwvn+Tlq5498dKMXYpyppgmLAxZS5SQRKP790c0u6kVkGJgKLzkTNaKMh/C69SpU6hTp06KTWIrukWqCQFVEbAmh1ARpV6oOi44hKArj5DPOROChtZTT/EHNDUO2IeQexEonc8Jf/etRb/MUYg6NeIUAkbihkTAmhxCdYjlS+Lyg0h8uvCkpGhQfXd0qpzXcqVmaKAaRBloPLyoDlGGp61IUyNOsEiy30Sxs9nY66HJPT179pQaYebsiGM77Xbs2CG9nsp21SU++/btky5w+PTTT7Fy5Urpc9Y0Y026dx92cyqTiY2N/SBy7HbVUaNGJSszdepUFClSRDDklbuTKSwMDb/8UhoY0r49LrVtq1yJnBHx8WjWpg3sYmNxy8cHxwcMkDOKZBQgcPXqVQwcOJAacQowI1ExEbAmh1ARpV7M2y86iZCwSBTP5YgV3cupp/gDmr5cdhaHbzyDq1MGbPGvRL/MUYg6/TJHIWAkbkgErMkhVIdYviSuRgAzz6WTFLUvEodquRIsVypTw7pQOzyMBnJmBD5xi5c5isTkIEB1iByUbE+GGnGCxZSd/8Z2xE2cOBF9+/YF+80Ue16/fo2ffvoJbEcC2xHHmllKH7bTjV20sHjxYnTt2vWt4Yx4X758ibCwMNoRJxPYtEePIkuDBpJ01LRpeN2tm8yRysWyeHkh7c2biPX2xos3t9byfrui3Iptj6AiyrbjS7MzIWBNDqEiSr1VNup4Wjx+lQYeTvH4ylObgmbxJTuceGSH9HYJmFw1Tr3JkCZQEUWLwFYQsCaHUB1i+SrZe+Uxvl4dIima2qIE6hfPYblSmRpa/3oCVx5GwdM1M+a2LExv5cjEjYnxajbaEacATBsSpUacYMFkX1S2I+3o0aPSraaJt6Zev34d7CajypUrS7vaUrrx9EPTYa+7zps3D1u2bIGf39tn0lSrVk1KqKzhR2fEyVwUGzYAzZubhNmFCp98InOgGWLsMoj9+4HChU2XQ9AZcYpBpNeKFENGAwyIgDU5hIoo9RZEzemH8OJVHHyL58CUFqajB6z9jP3nKladMF0QcXhQdbx+GUmFlALQ6Zc5CsAiUcMiYE0OoTrE8mWx/uQd9FtuejX1zx5VUdPDxXKlMjV0+OUQLtx/jlKuTvipdXG6NVUmbnJqNjojTgGYNiRKjTgBgxkTEyNd1sBuN2UNOPawhlzz5s3RvXt32Nvbm+X1r7/+CvZqK3vtlf0/6ZM/f37px9u3b0sXNbBm3Lu3prIdc9mzZ6dbUxOBY68Pf/GF6acDB4A3l12YFRzeoA4dgGXLAHbDbXQ0kCYNne/Dw+ydz6kRpxAwEjcsAtbiECqi1FkScfEJKDJ8s6SsXeUCmNCqrDqKOVqmbbuImTuvSFKHhtVHxoRoKqQUIE8cogAsEjU0AtbiEKpDLF8Wfx66ge/WnZUUre/jDa8CzpYrlamB3ZzOLvljD+/yAZkqU40YDy9qxKWapfDWRKkRl4riHh4ejkKFCkkXMgQFBSFt2rTS7NnrqmynA7uRlTUAHzx4IMk1atQI69at+xeh6dOnS689bdiwQZJX+vCSDC9JKbVndfmxY4HvvjOZuXIFsOa5d0OGAImXQYSFAblyEQkqDDAVUQoBI3FC4B0EqIhSZ0k8iXyN8j8GSsq+9CmMYY1LqqOYo2Xc5hDM33tNkupYtSCae2bHvZCj8PHxgbOzdsWcJpO1ghHiECuASipTFQJUh1ge7jm7r2Li1guSop0DfVA4Z2bLlZqhwXA1mxlzVHMIDy9ejaymL6RLHASoESdOLDTxhJ0/179/f+nW1DZt2uDOnTuYOXMmHB0dpYPqCxQoIPkxYcIEDBs2DOxw7o8++gjnz5/HrFmzwM4IYq+2mvPwkgwvSZlj06pjvv4amDXLZILdIpvZimTI7DB77Dl2DKhQgRpxCoNLRZRCwEicEHgHASqi1FkS18MjUXfKbknZEL/i8K9TVB3FKWgJDY/EkNWnERz6+D2JIlkSML1DRZR1d7WqD7agnDjEFqJIc9AbAapDLIvA/svh2B4ShufRsfhf01LI6mDeW1KWeUE74pTix6txeTWyUnskbwwEqBGnc5xGjx4tbfNlTa906dKB/cx7mPzIkSN5Yil+/ueff2LatGlSc83BwUG6pXX8+PEozM4fS/Kw8+QYYbJDiHPmzIn27dtLN6GyMeY8vCTDS1Lm2LTqGHZL6sqVAMMjMtKqpqQz6Fq2NNlguxSbN6dGnELEqYhSCBiJGwIBrTmEiijLl8WJm0/QYvYBSdG4FmXQoWpBy5WmoIE1/VrODsKTqJgUbThnSod1fWrCzcXRan7YgmLiEFuIIs3hXQS05hBmn+oQY69D9orqk6dPsW/vXtpRLTOUvBqXVyPLNENiBkOAGnE6B8zOzk5qxLHDUVmDi/3Me5h8XJzxbjzjJRlekuLhovnndeoAe/YAbm7Am7P8rObD0aNA5com9T/9BPTpQ404hWBTEaUQMBI3BAJ6cAgVUZYtjd8PhuJ/689JSpqUyYO+9TxQ0tXJMqUpjG4z92CyO+HeFa/ilh0re1W3ig+2opQ4xFYiSfNIioAeHKJXBGyuDtEYyB0hYRj21xk8iXqNnz8thZc3TlEjTmYMeDUub23KNENiBkOAGnEGC5iR3eUlGV6SEm7upUoBISFA1arAoUPWde/+fcD1zatD337L3h2mRpxCxKmIUggYiRMCgiFgdA750CuirBE2qXVZVXelnb8bgSYz98mO4pZ+tazWEJTthMCCxCECB4dcIwRkIGB0DpExRauK7Ln0EF0XBks2JjYvjowPzlEjTibivBqXtzZlmiExgyFAjTiDBczI7vKSDC9JCTf3HDmAx4+Bjz8G1q+3rnvx8UDGjEBMDNCxI9vXT404hYhTEaUQMBInBARDwMgcIucV0WwO9ljr761aM2564CUE7LgsO4r9fT3Q37eYbPnUJkgcktoiTvO1NQSMzCGJsTh87RFi4xOQI3N6lMhjnZ3UKcX9zO1naPbTfunjYQ0LI8/zS9SIk/kl4dW4vLUp0wyJGQwBasQJFjB2k+kff/yBDh06JOvZihUrpM/o1VSdA8caYunTm5z4/HNg/nzrO+TuDoSGArVrS6/E8pK69R0ylgUqoowVL/LWPASIQ/YIWRjo8YroqI3nsCgoVPZC6ubthu+becqWT22CxCGpLeKpc77EIWJySOJqbBKwD+fvRcAzrxM2fV1L00V6+0kUak7cJdnsXbMASsRdF5JvNQVFpjFezUaNOJlA2pgYNeIECyg7q4Gdv5NSI27ZsmXo3LkzYmNjBfOc7w4vyfCSFN+ChhJ37wL58pkMjhgBjBljfeOsAbdvH8Au1bh6lRpxChGnIkohYCRuSASIQ8QrovR6RZR2xKn7FSYOURdP0iYmAsQh4nFI0pVSa9JO3Hr8EtUKZ8fyL7Q91zPyVSw8v/9Hcqd9RVdUS3+LGnEyv8a8GpdXI8s0Q2IGQ4AacYIFjBHgkiVLpBtKk3v69+8vNerCw8MF85zvDi/J8JIU34KGEidOABUqmAzOnAn07Wt942yX5LJlpp14L1/iaUQE9uwR+x8M1gdFvgUqouRjRZLGRYA4RLycqFdDTK8GoHG/PR/2nDjEViNL80qKAHGIeBySND77Lj/E48jXyJrJHnWK59J08bLbUouP3IrXsfFoXMoFflnvUyNOZgR4NS6vRpZphsQMhgA14gQIWEBAANh/7AkNDUXOnDnh6Oj4nmfsS/zs2TO0bdsWS5cuFcBzZS7wkgwvSSmzZmXprVuBxo1NRlasANq0sbJBAOyShkmTTHbCwvA0fXpqxClAnYooBWCRqKEQIA4xhUtUDtHzFVE9Xok11JdHgbPEIQrAIlFDIUAcIjaHiLSYqo3bgfsR0aju7ox2ecKpESczOLx/n/BqZJlmSMxgCFAjToCALVq0CAsXLpQ8CQoKQrFixaRmXNInTZo0UnOuUqVKGDx4MJyctD2gUw2YeEmGl6TU8EE1Hb/9Bnz2mUnd7t2Aj49qqlNUNGsW8PXXpo+PHsXTIkWoEacAdSqiFIBFooZCgDhE7CJKrx1xDBV2U2uL2UF4EhWT4pp2zpQO6/rUVO2SCEN9eRQ4SxyiACwSNRQCxCFic4hIi6lxwD6E3ItAydyO6FX4GTXiZAaHV+PyamSZZkjMYAhQI06wgLm7u0u74z5mN3Ha2MNLMrwkJRQckycDQ4aYXDp/HihZ0vrurVsHtGhhsrNuHZ76+FAjTgHqVEQpAItEDYsAcYh4rxXp/Yooa8YNWX0awaGP31vXRbIkYHqHiijr7mrYNa+V48QhWiFNdvREgDhEPA7Rcz28a7vDL4dw4OojuDplwFDPSGrEyQwOr8bl1cgyzZCYwRCgRpzBAmZkd3lJhpekhJr7oEHA1Kkmlx49ArJnt757R48ClSub7MyahaedOlEjTgHqVEQpAItECQEBETAyh4jwiijbxTBy/VkcDX0iRfeX9p6ICj1FhZTMtU4cIhMoEiMEBEXAyBzCIH0QEY1fg64jS4Z00vlwpfNl1RzpPkuPY9Ppe8hkb4cJlV4Tf8iMAK/G5a1NmWZIzGAIUCNOsIAdOHBAaq4MGzYsWc8mTJggJb3q1bW9KUcNmHhJhpek1PBBNR2dOwN//gnY2wOvXgFp0qimOkVFYWFAnjymj7/9Fk+HDqVGnALUqYhSABaJGhYB4hAxdzPIeUU0m4M91vp7W/UV0V/2XsPYzSHS+v6rZ3ncOneECimZ33biEJlAkZihESAOEZND2KI6cfMJWsw+IK2vcS3KoEPVgpqvtZHrzuKPQzcku1OqxsK3rg+cnZ0198NoBnk1Lq9GNtp8yV95CFAjTh5Omkk1atQIWbJkwerVq5O12aZNG7x48QKbN2/WzCe1DPGSDC9JqeWHKnoaNgQCA4F8+YDbt1VRyVUSHw9kzAjExAAdOuDpzz9TI44L2n8CVEQpAItEDYsAcYi4RRRrxg1adQpHb5h2pCV9qrhlx6TWZa3ahGP2Vh29hcGrT0umF3YsjefXTlIjTua3nThEJlAkZmgEiEPE5RB2Y2rnX4Ol9TWrfXk088qr+VqbFngJM3dcluyOqhCL5g2pEScnCLwal1cjy7FBMsZDgBpxgsUsd+7c+Pbbb/HNN98k69mMGTPAdsXdv39fMM/57vCSDC9J8S1oKFGuHHDqFFC+PHD8uHaGCxcGrl8HatfG0/XrqRGnAHkqohSARaKGRYA4RNwiii2q+8+iUW38Dml9lcufFXVK5EIjzzwo6arNBUzbz4eh5+9HJfvTWpZA2ntnqREn89tOHCITKBIzNALEIeJyyOYz9+C/xFRzLOpWGXWL59J8rS0Ouo4fNp6X7A4pG4sOTagRJycIvBqXVyPLsUEyxkOAGnGCxSxTpkyYOnUq/P39k/Xs559/xsCBAxEdHS2Y53x3eEmGl6T4FjSUcHUFWDPUzw/YskU7w7VrA/v2Ae7ueHr8ODXiFCBPRZQCsEjUsAgQh4hbRLFFdfH+czSasVdaXyOblkKPmu6arrVjN56g1RzTq03/a1wEOZ5epEaczAgQh8gEisQMjQBxiLgcsvLILQxZY9rRvKZ3dVQspMH51O+s5vUn76Df8pPS3/qXisMXH9emV1NlfON5NS6vRpZhgkQMiAA14gQLWsmSJeHl5YXly5cn61m7du3AvqyXLl0SzHO+O7wkw0tSfAsaSbBXRNOnB+LigK5dgcWLNTIMoGNHYOlSyf7Te/ewZ98+KqJkok9FlEygSMzQCBCHiFtEsYV1+NojtJ1/SFpjUz71QuuK+TVdb9cevkC9qXskm/3qFELhV1eJQ2RGgDhEJlAkZmgEiEPE5ZBf91/Hj3+bdqP90782iufJovla23vpIbosNL0e29UjDgNaUSNOThB4NS6vRpZjg2SMhwA14gSL2f/+9z+MHTsWM2fORJ8+fd7ybvbs2ejbt690kcOYMWME85zvDi/J8JIU34JGEuHhQM6cJmODBwOTJmlk2HRJQ6K9ZxcvYndICBVRMtGnIkomUCRmaASIQ8QtotjC2nbuPr7445i0xhZ0qQTfUrk1XW9PIl+j/I+Bks0uVfKiYtqbxCEyI0AcIhMoEjM0AsQh4nJIwPbLmL7dtBEjaGg95HPOpPlaO3vnGZrO2i/Zbe0eh+/aUiNOThB4NS6vRpZjg2SMhwA14gSLWVRUFOrUqYNjx46hYMGCKF26tOTh2bNncePGDVSqVAm7d++Gg4ODYJ7z3eElGV6S4lvQSOLcOeBNXDBlCjBwoEaGAfz0E9C3r2Tv+a5d2PnsGRVRMtGnIkomUCRmaASIQ8QtotjCWnn0Foa8uSxhVa/qqOym7atFcfEJ8BixGfEJQPMyuVAv813iEJnfeOIQmUCRmKERIA4Rl0PGbjqPX/Zdl9bXqe8bImsme83XWlhENAasOInM9oAbHsD/E2rEyQkCr8bl1chybJCM8RCgRpyAMWPnv02ZMgWrVq3C5cumm2k8PDzQtm1b6Xy4DBkyCOg13yVekuElKb4FjSR27gTq1zcZ++MPoFMnjQwDWLcOaNFCshf555/YnjkzFVEy0aciSiZQJGZ4BIhDxD08esG+axizKURaY4EDasMjt/avFpUfvQ1PomJQp2h2tMj5gDhE5jeeOEQmUCRmeASIQ8TkkGF/ncay4FvS+ro6rgnS2qXRba0ZpmbTDaG3DfPw4tXIgkyD3FAZAWrEqQwoqUsZAV6S4SUpYbBdtgzo0MHkzrZtQIMG2rl27BhQqZJkL2riRAQWL05FlEz0qYiSCRSJEQKCImALHDLln4v4adcVCeHg4fWRyymj5mh7T9yBO0+i4eJoj0rZXqF7wwqoUiyf5n4YzSBxiNEiRv4SAm8jYHQO+Wrpcfx9+h4c0qfF+dF+uobXMDWbrij9Z5yHF29tCjINckNlBKgRpzKgpC4VNOICAoD+/U0TPXkS8PLSLuxhYUCePJK96K+/xj/16lEjTib6VETJBIrECAFBEeD9Q5X3D10RpjVy3Vn8ceiG5MqFH/2Q0T6tZm6FhkdKr8UGhz5+z2YVt+yY1Los3FwcNfPHaIaIQ4wWMfKXELCtRtxni4Kx++JD5MqSAcEjfHUNrxH4VleA3jHOw4v37xuR5kK+qIcANeLUw1I1TVevXgU7LHX79u149OgRtm3bhnr16uHhw4fSq6n+/v6oVq2aava0UsRLMrwkpZWfXDvDhwPjx5vE7t37tzHGHaeGALuxNVMm4PVrvG7dGls6daJGnExcqYiSCRSJGR4B4hAxXytiC6vvshPYeOouMtrb4cKPjTVba9fDI9FydpD0SmpKTzYHe6z196ZmXAoAEYdotlzJkM4IEIeIySGt5xzA0RtPUDinI3YOrKPbKnka9RrX7objYPARdGwiJla6gWMGf7AhvBpZtPmQP+ogQI04dXBUTcuFCxdQo0YNxMfHS822wMBA6T/WiGNPxYoVUa5cOfz666+q2dRKES/JGKYR16MHsHAhkCaN1BBDunRaQWiyU7gwcP06YqtXx6Zvv6VGnEz0qYiSCRSJGRoB4hBxD9pmC6vLwmDsvfQQeZwy4tDwN2eNarDi2sw9mOxOuHdNs51xK3tV18Aj45kgDjFezMhj5QgQh4jLIX4z9uLC/efwyp8V67+qqTy4Ko3ouOAQgq48Qrb0Cdj1TU04OzurpNl21fBqXF6NbLvIpO6ZUSNOsPi3bNkSR44cQXBwMOzt7ZErVy5pZ1xiI27EiBFYvXo1Ll68KJjnfHd4SYaXpPgWNJJo2hTYtAnImRN48EAjo0nM+PgAe/cirlAh/B0QQI04mRGgIkomUCRmaASIQ8Qtos7fjUC3RcEIe/4KORzT48+eVVHS1cnq643ZbTJzn2w7W/rV0sQv2Q4JIkgcIkggyA2rIkAcIi6HeE/YiTtPX8K7aA4s6anfm1GJZ9Wlt0tA8BBqxMn5QvJqXF6NLMcGyRgPAWrECRaz7NmzY/DgwRg2bJj0WmrOnDnfasTNnz9fej31+fPngnnOd4eXZHhJim9BI4kqVYAjRwBPT+DsWY2MJjHTsSOwdCkS7O2xYcUK+NStS7+NkhEFKqJkgEQihkeAOES8Ikrvs9mmB15CwA7TDexynv6+HujvW0yOaKqSIQ5JVeFOtZMlDhGPQxIXo9eobXj2MgaNPHNjXmfTxW16PNvO3UfI7UcIu3kVg1vXQrZs2fRww1A2eTUur0Y21GTJWdkIUCNONlTaCGbKlAkBAQH44osvkm3ETZ06FaNGjUJERIQ2DqlohZdkeElKRVcsU1WoEHDzJsBeF96xwzJd5oweOhSYOFEauXXxYlRr3pwacTJwpCJKBkgkYngEiEPEKqJEOJtt1MZzWBQUKnttd/N2w/fNPGXLpxZB4pDUEunUPU/iELE4JHE1JiQkoOiILYiLT0CrCvkxtY2GF8Ul85UwTM0myNeZhxevRhZkGuSGyghQI05lQC1V5+XlhSpVquCXX35JthHn5+eHZ8+e4eDBg5aa0nw8L8nwkpTmDidnMCHBdFnCq1dA+/bSzjTNn59+Avr2lczumTIFXj16UCNORhCoiJIBEokYHgHiELGKKBHOZqMdcep8rYlD1MGRtIiNAHGIWBySuFqiY+JQYuRW6cfParjhh4/1/WWJIWo2gb5qPLx4NbJAUyFXVESAGnEqgqmGqunTp2Po0KFYvnw5ateuLb2aumPHDunPY8aMwejRozF37lx8/vnnapjTVAcvyfCSlKbOpmSM7UTMmtX0af/+wPTp2ru1fj3wySeS3cNDh6L4t99SI05GFKiIkgESiRgeAeIQcYooUc5mE8UPo3+5iEOMHkHyXw4CxCHicEjSeMXHJ+Dhi1d4Hh0Lxwxp4Zo1k5xwWk3GEDWb1WavXDEPL16NrNwijTACAtSIEyxK7LbUtm3bYs2aNcibNy/u3bsHd3d3PHz4UDoXjn22bNkywbyW5w4vyfCSlDwrVpa6fBko9ubsnHHjgGHDrGwwGfXHjgGVTGdDPPT0RJamTZGxQwegbFntfTGQRSqiDBQsctVsBIhDxCmiRNqJJsLOPLMXtSADiUMECQS5YVUEiEPE4RCrBtoC5Y8jX2PT8VAcO3sB7etVRNXi+SzQljqG8mpcXo2cOlBKfbOkRpygMV+1apW0K45dI85I0cPDAx06dEC7du0E9ZjvFi/J8JIU34IGEvv3A7VqmQz9+ivQvbsGRpOYuHIF6NwZOHTofbvMr4ULgaJFtfXJINaoiDJIoMhNVRAgDnFWBUdLlIh0Nhu7MKLF7CA8iYpJcUrZHOyx1t8bbi6OlkzbZscSh9hsaGliySBAHKI/h4i6MM/eeYams/ZL7g1tUBi96pcU1VVh/OLVuLwaWZiJkCOqIkCNOFXhJGUfQoCXZHhJSgh016wBWrc2ufL338BHH2nnFtuNV6MGEB6esk0XF4CdH0jNuPcwoiJKu6VKlggBayBgNA4RaUcci4fet7daY01oqZM4REu0yRYhoD4CRuMQ9RFQR+Odpy/hPWGnpKxXzQIY2pTeyOEhy6txeWuTp58+NyYC1IgzSNxu3LghXd5Qvnx5pEmTxiBev+0mL8nwkpQQk54zB/D3N7kSHAxUrqydW7VrA/v28e2xnXF79/LlUpkEFVGpLOA03bcQIA7RfkGIejZbyL0IaXdcdEw8cmWMx08dKqBKMXq1iLdCiEN4CNHntowAcYi+0T187RF+2nUFmTOkQ996HiiV10k3h16+jkPJ/5kujmhXwRUT2lTQzRejGObVuLwa2SjzJD+VIUCNOGV4WV16zpw52LdvH5YmuY3zq6++Avt79pQuXRo7d+5Ejhw5rO6L2gZ4SYaXpNT2xyx9P/wAjBplGnrjBlCwoFlqFA86dQooV07+MCZPZ8a9hRcVUfKXD0kaFwHiELHO9xH1bLZ6U3bjWngk3LMkYG2fmnThj4yvPHGIDJBIxPAIEIeIxSGJC2rNsdsYuOqU9OOKL6qhamF968AS321BdGw8/Eq6YG7XqoZf99aeAK/G5dXI1vaP9OuDADXi9ME9RauVK1dGxYoVpZtR2RMUFIRatWqhTZs2UhNu/Pjx8Pf3x+TJkwXznO8OL8nwkhTfggYSvXsDb2KDly+BjBk1MAogaQNQjkUm//33ciRTjQwVUakm1Kl60UE2dQAAIABJREFUosQhYhVRop7N1mrOARy78QS5MiZgW39qxMlJGsQhclAiGaMjQBwiFockrqd1J+5g4tYLePEqFsu/qAbPvFl1XWpVxwYi7PlrVHNzxvJe3rr6YgTjvBqXVyMbYY7ko3IEqBGnHDOrjnBxccH333+Pvn37SnYGDBgAdmDqzZs3YWdnh8GDB2P9+vW4dOmSVf2whnJekuElKWv4pFhny5bA2rVA1qzA06eKh5s9oH9/ICBA/vB+/YAZM+TLpwJJKqJSQZBpiiAOEa+IEvFstp6/HcX2kDA4pktA0CBqxMlJHcQhclAiGaMjQBwiHoeIuKYaTduNiw8iUSK3I7YOqCOii0L5xKtxeTWyUJMhZ1RDgBpxqkGpjiIHBwf89NNP6P7mNs4yZcqA/XZqIbsNE+xSzIVgr6pGRUWpY1BDLbwkw0tSGrqasqmaNdk2RcDDA9CyGUo74iwOPxVRFkNICgyAAHGIuEXU578dQWDIA2kV9avvAb/SeVDSVZ9zfoasPoWVR28jDRJwdIg3cmTPZoDVra+LxCH64k/WtUGAOERcDtFmBciz0nbufhwOfYY8TulxaHgDeYNSsRSvxuXVyKkYOpueOjXiBAtvsWLF8NFHH2H69OnSLjg3NzcsXrwYXbp0kTxlr6ROnDgR4R+6OVOwOSW6w0syvCQlxLRYA+7KFYA15ORcnKCW03RGnMVIUhFlMYSkwAAIEIeIW0R98ftRbDsfBmcHe5z8X0NdV9P4LSGYt+ea5MOur6vAPW9OXf0xgnHiECNEiXy0FAHiEHE5xNLYqjm+12+HsTUkHBnt7XDhx8ZqqrZJXbwal1cj2yQoNClQI06wRTBixAhMnToVPXv2xOHDh3Hx4kWEhoYie/bskqcdO3bE5cuXEcxu7DTYw0syvCQlxHSdnIDnz4FWrYDVq7V1iW5NtQhvKqIsgo8GGwQB4hBxi6g28w4i+PpjuOVwwO7BdXVdUfP2XMX4LRckH9Z+Xh7li+TV1R8jGCcOMUKUyEdLESAOEZNDEhISkCZNGkvDq9r4oSuPY/nxe5K+kNF+yJQ+rWq6bVERr8bl1ci2iAnNCdSIE20RvHz5Er1798aGDRukW8xYU65FixaSm8+ePUPevHnRr18/jBs3TjTXuf7wkgwvSXENWFuAXc7g4GCy4u8P/PyztS2+rZ/txKteHfjQbkgXF+DgQaBoUW19M4A1KqIMECRy0WIEiEPELKJYYBtN34uLYc/hVcAZ6/voe7j1jO2XMGP7ZWm9NS+TC73qFdftNVmLF71GCohDNAKazOiKAHGImBzy+e9HcejqIxTI7oDN/WrpukaY8fEbT2Ne0C3JjwND6yGvcybdfRLZAV6Ny6uRRZ4b+WY+ArQjznzsNB8ZHx+P58+fg53fYG9vr7l9Sw3ykgwvSVlq3+LxN24Abm4mNXrdSsqacez8wORei61Vix0iSE24FAJNRZTF3wBSYHAEiEP0DWDVcdsRFvEKtYvlxO/dq+jijIgXR+gChBlGiUPMAI2G2BQCxCH6hbPtvIM4LMiOaobC3B0hmBBoOt7g7741UTqfvre46hcZeZZ5NS6vRpZnhaSMhgA14gSPGCO927dvI0+ePEifPr3g3n7YPV6S4SUp3SfPXgeuWtXkxpw5QK9e+rl0+jTia9SAXWQk4tzdkXbdOqBsWf38MYBlKqIMECRyUXUEiENUh9RshcW/24JXsfH42CsvZrYvb7YecwdeD49Ey9lBeBIVk6KKbA72WOvvDTcXR3PN2Ow44hCbDS1N7AMIEIeIsTw+mrkP5+5GoHQ+J/zdV/8dccsPXMbQDZckcP7sURU1PVzEAEpQL3g1Lq9GFnRa5JaFCFAjzkIArT08LCxMeh01MDAQ9erVs7Y5q+rnJRlekrKqc3KUb9wIfPyxSfKvv4A3rwzLGWoNmVgvL6Q7fRpxnp5Ie/asNUzYlE4qomwqnDQZmQgQh8gEyspi0TFxKDFyq2SlS/VCGN28tJUtvq++zdyDCA59zLVbxS07VvaqzpVLbQLEIakt4jRfhgBxiBjrwGfyLtx4FIWq7tmx4kv98/PWk6HotfycBA77xRL7BRM9KSPAq3F5NTJha5sIUCNO8LgyAnR1dcX27dupEad3rH79FejZ0+RFUBBQo4auHsX4+cH+n38Qnz077B490tUXIxinIsoIUSIf1UaAOERtRM3TFxYRjarjdkiDv65XFN80LG6eIjNHnb8bgSYz98kevaVfLToz7h20iENkLx8StCEEiEPECGbFHwPxKPI1fEvmwoKulXV36tCF22i3+JTkx6iPPdG1xpuje3T3TEwHqBEnZlz09ooacXpHgGOfCFCgALELMkaMMDl0+bLuZ7G96tYNGRYvNvnDLpLImFEgsMRzhYoo8WJCHlkfAeIQ62Msx8LF+8/RaMZeSXRk01LoUdNdzjDVZKYHXkLADtPlDHKe/r4e6O9bTI5oqpEhDkk1oaaJJkGAOESM5ZB4tMEn5fJiRjvtjzZ4F4ULN8PgN/uo9NfEF/w1Qo04PkapUYIacYJHXU0CDA0Nhbt78v/479GjBxYsWPAvGnFxcZg8ebL0d7du3UKBAgXQs2dPDB48GGnTmndFNW/bLS9J6R6qfv2AmTNNbkREAFmy6OrSy+HDkWn8eJMP164BKcRWVycFMk5FlEDBIFc0Q4A4RDOoP2jo8LVHaDv/kCQz5VMvtK6YX1PHRm08h0VBobJtdvN2w/fNPGXLpwZB4pDUEGWa47sIEIfovyZi4uLhMWKL5EjHqgUxtkUZ3Z26//ARqk01cZpexy3oDoICB3g1Lq9GVmCKRA2EADXiBA9WZGQkpkyZgq5du8It8cZOM31ObMQ1b94crVu3fktL0aJFUa1atX//zt/fH3PmzEG3bt1Qo0YNHDhwAIsWLQL7+59//tksD3hJhpekzDKq5qB27YAVK4BMmYDISCBNGjW1K9YVNWsWHL7+2jSO3aJas6ZiHalpABVRqSnaNNdEBIhDxFgLC/Zdw5hNIZIzzcq6wr9uUU1f/aQdcZavA+IQyzEkDcZDgDhE/5g9jXqNcqMDJUe+9CmMYY1L6u4Uy4fz1u9F7aoVUCx/TuTInEF3n0R2gFfj8mpkkedGvpmPADXizMfOcCMTG3EjRozAmDFjUvT/zJkz8PLyQt++fREQEPCvXL9+/TBr1iycOnUKZcoo/20ML8nwkpTugLPLMnbtAgoVAkLl7yywlt8vVq1C5jZtTOpZgzDxz9YyaHC9VEQZPIDkvu4IEIcoD0FoeCSGrD6d7CUJ7FKESa3LanJDKZ0Rpzx2744gDrEcQ9KQuhEgDjEv/rceR6HWpF3S4EENi+Greh7mKVJxlPA1m4pzVUMVDy9ejayGD6RDPASoESdYTG7fvi29Clq9+n834oSEhGDSpEl49OgROnfujE8//dQsr5MSIGvGsScT2931zsM+GzduHK5du/bWq6zXr19H4cKFMXz4cIwdO1axD7wkw0tSig2qPcDTEzh/HqhSBTh8WG3tivVF7N8Pp1pvrjCfNg0YMECxjtQ0gIqo1BTt1DtX4pA98PHxgbOzs+6L4Hp4JFrODsKTqJgUfcnmYI+1/t6aNOPo1lTLlgRxiGX40WhjIEAcIg6HJK6YkHsRaBxgumzn+2al0M1b2zNGk1u5wtdsgn3deHjxamTBpkPuqIQANeJUAlItNW3atMG9e/ewj71qCIB9cUuUKCE14TJkyICXL19i48aNaNKkiWKTiY24zJkz48WLF9J49kpq//790adPn3/1NWrUSNr1dv/+/fds5M6dG+XLl8fWrVsV2+clGV6SUmxQ7QEuLgC7nbRZM2DDBrW1K9b37No1ZC1SxDRu4EBgyhTFOlLTACqiUlO0U+9ciUPEKaJEa3yx3XktBGoMGu1bShxitIiRv+YgQBwiDockxu9o6GO0nntQ+nFy67L4tFIBc0Kr6hjhazZVZ2u5Mh5evBrZcg9Ig4gIUCNOsKiwc+DYxQkjR46UPGPntLFXRNkXtHjx4qhbt660i23Hjh2KPb958ya6d++OTz75BIUKFcLdu3elyxiOHj2KQYMGSZczsIe9dpo+fXocO3bsPRsVKlRATEwM2OurH3pYM5H9l/RhO/s6deqE3bt3S6++vvs8f/5cmiezkUXnixDecy4mBs65ckl//apLF7xM8squ4kCoNOB5RATyFi2KtDExeN2qFaKSXLahkgmbUvOh9cUaz3Xq1JHWPFt/9BACRkWAOEQMDrkYFom2i07KXkYru5dDsVyOsuXNFbz55CV+2HQFx29HvM/v+Z3ww0dFUTDb+zvlzbVnS+OIQ2wpmjSXlBAgDhGDQ5LGZ//VJ/hq1Xnpr6a2KIH6xXPovoBZPpz/zwk8TOeC6Lg0mN6yBNLofHa27qB8wAFejUt1iMjRs55v1IizHrZmaXZwcJAuQ2CXJLDn448/Bvvy7mJnkwHSGW3sfDd2i5EaD7sdtV69eti/fz8uXbqEIkWKSP+xnW/sgoZ3H3Zxw4MHD3DlypUPmv/hhx8watSoZGWmTp0q2TDSk+HxY/h17y65fKl1a4R06iSE+75ffgnHsDCEe3oiyIzXhYWYhABOXL16FQMHDqRGnACxIBcsQ4A4xDL81Bq95ZYdtt62k63OL38cGhdIkC1vqeCdSGDDTTtceGry8TOPWJR3sVRr6h1PHJJ6Y29rMycOES+iJ8LTYPHltJJjvUvGoYSzdlzxITTWXLfD3vsmDplUJRYZTC7SYwYCxCFmgGYDQ6gRJ1gQc+XKJZ3Bxl4XjY+PR/bs2aU/s8YWe+bPny/9HBUVpZrn7FVX1vCbN28evvjiC9oRlwyyac+cQZbataVPoiZMwOsvv1QNf3MVsQatQ6NGyBESgrjChfE8mR2M5uq2xXG0m8EWo0pzehcB4hAxdjNM2n4NS4++vSv8Q6u1QyVXDPEtrOmC/uvYTYwOvCXZnNfOE1Xd9D9XT1MAFBojDlEIGIkbEgHikLc55H7EK8zZdxM1i2RDgxL6/Lbir1P3MXrLVWk9/dGlLMrkzaL72mL5cPyGE/jndlpkzWSPZd28kDsL3ZyaUmBoR5zuS1ZIB6gRJ1hYGjRogMePH2Pbtm1YtWqVdHZbUFAQqlWrJnk6bNgwLFu2DOy8N7We06dPS6+KsgsYWBOQzohLBtl//gH8/EwfLF8OtG2rFvxm62HnDUQ2bYp8QUHs1g0gMhKgbeEp4knn+5i91GiggRAgDhHjfJ/pgZcQsOOy7JXT39cD/X2LyZZXQ3DzievwX2F63Wlm+/L42CuvGmptVgdxiM2GliaWBAHikLc55JuVJ/HX8TsSQlfGNka6tPJ3Oqu1sBbsu4Yxm0IkdYEDasMjt/6NOJYPd+zag7p1aiN7tmxqTdVm9dAZcTYbWosmRo04i+BTf/DevXvh5+eHV69eScrZmXDbt2//1xA7v61UqVJYsWKFasb/+usvtGrVSjovjp1Px5px48ePp1tTkyL8xx9Aly6mv2GvCdepoxr+5ipiST28a1cUTbw44vFjgMgwRTipiDJ3pdE4IyFAHCJGI+783Qg0mWm6dEnOs6VfLZR0dZIjqprMoQu30W7xKUnfqI890bWGm2q6bVERcYgtRpXm9C4CxCFvc0i1cTtwPyIaeZwy4tDw+rosmBnbL2HGdtMvdg4OqwfXrPqf48lrLOkClMBGeXjRZQ0CB8+KrlEjzorgmqv6woUL0o44Z2dntGvXTro4gT1sp9yPP/4oXbbg4+OjWD0bz151TfqwW1i9vb1x9uxZsPfTCxQoIN2Yym5GZZdEBCS5lKBfv37SGXUnT55E2bJlFdvnJRleklJsUM0B7EbSwYNNGs+dA0qVUlO7WboYXrcHDEDpxYtN48+eBTw9zdKVGgZREZUaokxzZAgQh/hI/Kn3I9qtqe/iceFmGPxmH5X++uv6HvimgbY78vSOj1L7xCFKESN5oyJAHPIfh7DdzSduPUUOx/SY3racLiFdd+IO/j59Fy9exWJB18rInCGdLn4kNSp0zaY7Ou87wMOLVyMLOCVySQUEqBGnAohGUdGyZUvpbDn2mmv+/PmlW1N/++03aecb2wE3dOjQf6fSq1cv6cw4dmkEa9Sx12MXLVqEL7/8EnPnzjVryrwkw0tSZhlVaxBrwrFmHHvCw4Ec+t9YxPC68uOPqDRtmskv9vpsw4Zqzdjm9FARZXMhpQlpjABxiDLAQ8Mj0WJ2EJ5ExaQ4MJuDPdb6e8PNxfo3pr7rxP2Hj1Bt6iHprztXK4QfPymtbIKpTJo4JJUFnKarOgLEIapDqptCoWs23VBJ2TAPL16NLOCUyCUVEKBGnAogqqkiMjISERERcHV1/Vctu6V0zpw5ePToETp06PDveXFK7f76669S4+3ixYvS7rrMmTOjQoUKYDvd2GUNSZ/Y2FhMmjRJel319u3bUuOuZ8+eGDJkCNKlM+83Mbwkw0tSSuerqjx7LZW9nsrmzl4bttP+jIh358PwOvvzz6j53XemjxYtAj77TNVp25IyKqJsKZo0l5QQIA4R49XUxPiwZtyAFSelHRXvPlXcsmNS67K6NOGYLywnVpm0H6/j0+CjMq74uWMF+mJ9AAHiEFoeqQEB4pCUOeTu05fSxQSOAuxI03stsny4efseLLieBc+i49CxWiHaVW0mf7BhvBpZ73iTfesgQI046+BqttauXbvizJkz0heSPdHR0ShdurS0a409rAm2Z88eVK9e3Wwbeg3kJRmhG3Hsoga24yxvXuCO6dBWvR+G19Hly+Hbu7fJlTFjgBEj9HZLWPtURAkbGnJMRQSIQ8RqxLHQXnnwHL7T9kpRruyWDd5FXdDIM4/mZ8K9u8xYTqw3fT8ev0qD6oVzYNkXpkuh6EkeAeIQWhmpAQHikPc55PTtp+i//CSuhUfSxTZvvgSJlzUMPGzanNGhakGMa1EmNXxFzJojr8bl1chmGaVBwiNAjTjBQlS0aFFp19vo0aMlz9gONvZ66MaNG6WbTdlFDu7u7tLPRnt4SYaXpHSdb/nywMmTQLlywIkTurqSaJzhtX/bNjRNvMGVNeRmzxbCNxGdoCJKxKiQT2ojQBwiXiPuSOhjfDr3oBRqtgOuTaUCaofdLH0sJ/rN2I/70WnAXpHtUt0NfqX1bxCaNRkNBhGHaAAymdAdAeKQ/zjk2sMXePYyBg7p06HRDNMvU3rWdMd3TbU9J/p6eCTs0gBOGe2RzdF0brjeT2I+HHE8A168ikPj0nkwp1NFvd0S1j6vxuXVyMJOjByzCAFqxFkEn/qD2eui7IIEdnspe9q0aYMbN27g8OHD0s/Tpk3DlClTpPPdjPbwkgwvSek6X7YT7t49oFEjYOtWXV1JNJ6IV7OuXWH37BnQvDmwbp0QvonoBBVRIkaFfFIbAeIQ8RpxgefD8PnvpksR5neuiIaeedQOu2J97JXZb5Yfx/HbEe+N1fuVWcWT0WgAcYhGQJMZXREgDvmPQ0ZtPIdFQaFvxaNF+XyaX9rgN2MvLtx/jrL5s2LDVzV1XR/v1iCTQzLj9tNoVHXPjhVfGu9tLa3A5NW4vBpZKz/JjrYIUCNOW7y51titpuxm1D59+kiyuXLlQvfu3TFhwgTpZ3ZmG7vNlN12arSHl2R4SUq3+cbHA+zm2rg4gJ0V99tvurmS1HAiXk2HDkXaCxeASpWAI0eE8E1EJ6iIEjEq5JPaCBCHiNeIW3X0FgavPi2FelWv6qjs9vbt5WqvAZ4+truipcCXSPD81+tz4hC9kCe7WiJAHPIfh/RYfAQ7LjyAU8Z00rlw955Fo5aHC/7oUVXLkKDmxJ24/eQlahTJgaWfi3GEQGI+/CXUGWfvvUCx3JmxbYCPprgYyRivxuXVyEaaK/kqHwFqxMnHShNJdkNpxowZsX37dun10xYtWiAwMBD16tWT7P/vf/+Tbi+9deuWJv6oaYSXZHhJSk1fFOl69AhwcTENGTQImDxZ0XBrCSfi1SQgAPa7dgl1fp215myJXiqiLEGPxhoFAeIQ8Rpxv+y9hrGbQ6QlFDigNjxyZ9F1ObWZexDBoY+5PrCdcSt70Q6HRKCIQ7hLhgRsAAHikP84xHfaHlx58AJl8mVFAhJw9k6EdLbnln61NI30iiM3Ef7iNVyzZkTLCvk1tZ2SscR8uOpBTuy/+gQumTPg6He+QvgmohO8GpdXI4s4J/LJcgSoEWc5hqpqWLduHVq1agUnJyewm4s8PT1x7Ngx2L25pbNGjRpwcXHBhg0bVLWrhTJekuElKS18TNbG+fOAp6fpI9aEY804AZ5EvPxWrkSGpUtNN7myG13NvNVWgClZ1QUqoqwKLykXBAHiEPEacZP/uYCfd12VVkjwiPrIlSWjbqvl/N0INJm5T7Z9VnCywpMe0y2z7LIsHx8fODs7vwUJ7983hB8hYBQEiENM33Enp6wo8b+teB0bj6ZlXfHiVSx2X3yInFky4MgIajgl5sPA5674++xDpLVLgytjGyNNmjRGWeqa+smrcYlDNA2HMMaoESdMKP5zZOfOnfj777+lf+j5+/tLjTf2PHr0CJ9//jm6dOmCTz75REDPP+wSL8nwkpRuE2a7zd7sSMTvvwOdO+vmSlLDiXg12rcPGadONX10+zaQL58Q/onmBBVRokWE/LEWAsQh7zdKrIW1HL3D157B0sM3JdFLYxojfTo7OcOsIjM98BICdlyWrbu/rwf6+xaTLW/LgsQhthxdmltSBIhDfPDKLiOqjtshweJfpwjCIl5hzfHbUsPp8pjGsGO3J6TiJzEfHo0tiD+OmM4tP/W/hsjqYJ+KUUl56rwal1cjE6i2iQA14mwzrkLOipdkeElKt0mtWAG0a2cy/88/QMOGurmS1HAiXg0uX4bD4MGmj4KDgcqVhfBPNCeoiBItIuQPIaAMAaNySJ8lx7HpzD04pk+Lc6P9lE1aZenkDh//kIlu3m74vtmbHeEq+2I0dcQhRosY+UsIvI2AEg558CotGk433ZQ6smkpPIiIxry916Sfj49sgOyC3F6qV4wT8+GV9EUwa88NyY1dg+rA3cVRL5eEtsurcXlrU+jJkXNmI0CNOLOhs+7A+Ph4sC/l9evXpW2+7u7uqFChgqG3/PKSDC9JWRfxD2ifORPo188kcOIEUK6cbq4kNZyIV/3ISGTu2NH00dq1gAF3S2oBKBVRWqBMNkRBgDjk7VcH9YxLxwWHEHTlEfI5Z0LQUNN5r3o9tCPOfOSJQ8zHjkYaD4HUziHXIxLQYvYBKXDjW5bBi+hYXc76fBYVg42n7yJzhnTwKuAsTKMrMR8+ci6O0VtMRy+s6V0dFQvpexmRqN80Xo3Lq5FFnRf5ZRkC1IizDD+rjGbnv7GbUW+z1wwBJCQkSA24AgUKYNasWWjWrJlV7FpbKS/J8JKUtf1LUf+IEcC4caaP794FXF11cyWp4US86mXJgiz165s++vlnwN9fCP9Ec4KKKNEiQv5YCwHiELFeTW0SsA/n70XAM68TNn2t7SHf764xOiPO/G8dcYj52NFIYyFAHOKD8+Gx6LDgsBS4gHblEBefgG9WnpJ+XvZ5NVQvkkOToJ67+wwfzdwv2Rr1sSe61nDTxC7PSGI+jHctjQF/XZDEf+lSCQ1K5eYNTZWf82pcXo2cKkFLBZOmRpxgQWbnMjRs2BB58uTBl19+iVKlSkkenj9/HvPmzUNYWBi2bduGunXrCuY53x1ekuElKb4FK0n07An8+ivADiB9/VqYyxAS8apTrBiyvlknGD4cGDvWSkAYWy0VUcaOH3kvDwHiELEua2CNr7bzDuL5q1gUyJYJ87tU0v3yA7o1Vd536V0p4hDzcKNRxkKAOMTEIUfuvsLnvx/9t8GUIZ0duiwMln6e1b48mnnl1SSwh689Qtv5hyRbUz/1QquKYt2a6lSkPLr9eUbyb2KrMmhbuaAmuBjNCK/G5dXIRpsv+SsPAWrEycNJM6k6derg/v37OHjwILJly/aWXfYlrlatGlxdXbGLXSBgsIeXZHhJSrfpfvwxsHEjwC7NePhQNzdSLApq1oRzrlxAfDzQtSuweLEwPorkCBVRIkWDfLEWAsQhYjTiQsMjMWT1aQSHPn4v1FXcsmNS67Jw0+ksHeZbi9lBeBIVk+IyzOZgj7X+3rr5aK3vhyV6iUMsQY/GGgUB4hATh+wJjUS/5SelsC3pWRXODvb/7kz7oVkpfObtrklId4SEocdvpobgvM4V0cgzjyZ2eUYS86FbmSpoPv+4JP6tXwn0rlOENzRVfs6rcXk1cqoELRVMmhpxggU5S5YsGDlyJIYMGZKsZxMnTsSYMWPw/PlzwTznu8NLMrwkxbdgJYmqVU2XILBdZ+fOWcmIcrVv4eXpaXpttkEDYNs25cpSwQgqolJBkGmKIA7RvxF3PTwSLQVvdLFm3DfLj+P47QjhGoWifo2JQ0SNDPmlJgLEISYO2XIpAsP+Mu30+su/hnTGZ+Itql/VLYpBjYqrCXuKutafvPNWQ9C7qIsmdnlGEvNhuSo14BNg2in4eS13jPjI9CYXPW8jwKtxeTUy4WmbCFAjTrC48ghw8uTJGD16NDXitIybmxtw4wbAXgfeuVNLyx+09VZSZze5HjkiXLNQGLAAUBElUjTIF2shQByifyPOKK9+spy4dPMeLLyaCeGRMciZOQN+71FF91dnrfXdsFQvcYilCNJ4IyBAHGLikDVnn+DHv89LIfunf20UzukIjxFbpJ/bVymA8S3LahLOJYdvYMTas5KtdX28Ua6AGBcRJebDWrVro/Lkg9IZeq0q5MfUNl6a4GI0I9SIM1rEtPGXGnHa4CzbCkv+7By44OBgODk5vTUuIiICVapUkc6P2717t2ydogjyuv28JKXLPBISAAcHIDoaaNcOWLZMFzeSM/oWXt26AevWAc7OwJMnwvgokiNURIliLcF2AAAgAElEQVQUDfLFWggQh+jbiDPSZQiJOXH5fRccvP4UuZ0y4PBwX2stTcPrJQ4xfAhpAjIQIA4xccifxx9iyrZLEmL7htRFgewOKDd6G55GxcC3ZG4s6FpJBpqWi8zbcxXjt5guQ9j+jQ+K5spsuVIVNCTNh74/HUX4i1eoWzwnFnWrooJ221PBq3F5NbLtIUIzYghQI06wdRAYGIjGjRsjb9686NWrF0qWLCl5mHhZw71797Blyxb4+hrvH8u8JMNLUrqE6sABwNvbZJq9ojp/PlBWm9+C8eb7Fl7sZtfZs01DIiNNzUN63kKAiihaEKkBAeIQfRtx0wMvIWDHZdlLrb+vB/r7FpMtr6ZgYk78J8IVm889hH3aNLg0prF0Szs97yNAHEKrIjUgQBxi4pB5h+5jzu6rUsiPfucLl8wZ4DttD648eIHyBZ2lMzS1eKZtu4iZO69Ipg4Pr4/cThm1MMu1kTQfDt90Fc+jY1G+gDO+aajNK7tcBwUT4NW4vBpZsOmQOyohQI04lYBUU82aNWvQr18/3L17999/ECckJCBfvnwICAhAy5Yt1TSnmS5ekuElKc0cZYauXAG6dwf27XvfbK1awMKFQNGimrr0rrG38GJNONaMY8+lS4CHh66+iWiciigRo0I+WQMB4hAfOLPdwTo8ozaew6KgUNmWu3m74ftmnrLl1RRMzIlHYgvizyN3JdWnf2gIp4z2apqxGV3EITYTSpoIBwHiEB/M2HsHiw+YcnnIaD9kSp8WE7ZckHZ+sV1pvXy0uZQgKaecG9UIjhnSCbF+harZhEDkw07w8OLVyAaYIrloBgLUiDMDNC2GxMXF4dixY7h+/bpkzt3dHRUrVkTatGm1MG8VG7wkw0tSVnEqOaWXLwM1agDh4SmbZDeoHjyoazPuLbzYa6ns9VT2sNeWfXw0g8sohqiIMkqkyE81ECAO0acRZ8QdcVfSF8GsPTekZbdrUB2463Sbqxrr3po6iEOsiS7pFg2B1M4hYwNvYNWx22AbhK+Na6LbTuEhq09h5VH9/Xh3fQpTs4n2xUnBHx5evBrZINMkNxUiQI04hYBZUzwyMlK6MbVu3bpo1qyZNU3popuXZHhJSjOna9dOfifcuw6wnXF792rm1gdJkF3UwC5sYM+SJUCHDrr5JaphKqJEjQz5pRYCxCFPsWePvq+mGvGMuEfOxTF6i+kVrDW9q6NioexqLUmb0kMcYlPhpMkkgwBxyH8cci48FhfuP8fr2Hj0rqPN7rfkFqX/kmPYfOY+smRIhzOjGgmzboWp2YRB5MOO8PDi1cgGmSa5qRABasQpBMza4g4ODpg1axZ69OhhbVOa6+clGV6S0sThU6eAcuXkm2LyOp0Z9xZed+8Cnm9eb5o8GRg0SP4cUokkFVGpJNCpfJrEIfo24tjyM9KtqaxxeduhKCbvML2C1bSsK/rULUo3pyaTR4hDUnlyTSXTJw7Rn0OSLrUuC4Ox99JD5HHKiEPD6wuzCpPmQ8csTngS9RqPI1/DLYcjMtob9+0tawHMq3F5NbK1/CK9+iJAjTh98X/PetWqVVG/fn2MGzdOMM8sd4eXZHhJynIPZGj44Qdg1CgZgm9EmPz338uXV1HyLbyY3mzZTNr79wemT1fRkm2ooiLKNuJIs/gwAsQh+hdRoeGRaDE7CE+iYlIMVjYHe+mwbzcdXwM9ff0eBiw9hqvP37+coYpbdkxqXVZX/0T7rhOHiBYR8scaCBCHpMwhT6Ne48ajKEREx8CrgLMm52m2mnMAx248kc6lY7emivIkzYfrzj3BDxvPS65t+romPPNmFcVNYfzg1bi8GlmYiZAjqiJAjThV4bRc2datW9GhQwds3LgR3om3dVquVggNvCTDS1KaTII1sQIC5Jvq1w+YMUO+vIqSb+GVNSuQOTMQFQW0aQOsWKGiJdtQRUWUbcSRZvFhBIhD9G/EsQixZtyQ1acRHPr4vYCJ0OS6zpqFP+/H05exQjcLRfq+E4eIFA3yxVoIEIekzCGrjt7C4NWnJehX96qOSm7Wf42/0fS9uBj2XGr8re+jzU2tctZW0ny490YUvl52Qhr2R48qqOWRU46KVCXDq3F5NXKqAisVTZYacYIFu0uXLtIlDRcuXICXlxeKFCmCTJkyveVlmjRp8NtvvwnmOd8dXpLhJSm+BRUkjLojjt0QyG5KZbe9sgbu/v0qgGFbKqiIsq140mySR4A4RIxGXGJ0/Gbslc4ZypopHbp5u6ORZx4hXvs0yuuzIn3PiUNEigb5Yi0EiENMHLLj6gu8jotH/myZ/m0sbT17H73+PCZBv/CzSqhXIre1wvCvXu8JO3Hn6UvULOqCP3tWtbo9uQaS5sPw12mx9sQdZHfMgIalcqNAdge5alKNHK/G5dXIqQaoVDZRasQJFnA7OzuuR6wRx24zMtrDSzK8JKXJfI16RhxrxNWpA+zZA7i5AW9u29UEM4MYoSLKIIEiNy1CgDhErEZc3Sm7wXafVXbLhlW9algUW7UGG+lCCbXmrIYe4hA1UCQdoiNAHGLikCZzjuHus+i3GmC3n0Rh98WHcMpkj6ru2ZHbKaPVw+k1ahuevYxBI8/cmNe5ktXtyTUgRM0m11kB5Hh48WpkAaZALlgBAWrEWQFUUpk8Arwkw0tSmuFqxFtTWSOuY0dg6VIgfXogOhrSnev0/IsAFVG0GAgBYyNgGA5JAnNiEdWgVG780kWMImp64CUE7LgsezH09/VAf99isuVtVZA4xFYjS/NKLQgo4ZA6M4PxNCpG2uE1X6fcnZCQAI8RWxAbn4BWFfJjahsvYUIlTM0mDCIfdoSHF29tGmSa5KZCBKgRpxAwEjcfAV6S+T971wEV1dGFPwQEEaQI9oK99y62KNZfY9fEkmhi71GjscSS2GvUWGPURKPRGE3U2BAVFXvvXewdbGBB5D/znhUX5u3ue2/n7d45JycJzNzy3dl7uXdn5vKclOWczVzJrneWKwfcu5f4Qn9/YNcuIGdOM4mrN/0jvL79FpgwQWZw9y7AZKRBhTjaA4SAnSBgmBjyGu+Xca+Qa/A6xMcDzUtmxtgmhYWwxPDVJzA/XO6SqmS0DQrE0Hqvu3IrWWCnc6gQZ6eGJbUcBgFzYsjd58548vwlUrq5IHdaL5tgxApx+y9HSXIEeLqhYEZxmiAIk7PZxDLmM+Xhxdub5nOkFUZAgApxglhp1qxZSJ06NZo2bZqoRMuWLUNUVBQ6duwoiNTmicFzMjwnZR43K2ezYhxrenBIfnz0g1GxIjBvnk2LcEyej/BiTSO++UYWlV2xLSxG0melJVRbTkmUalASIQERoBhiwifa2E73nzxHiRGbJCk6Vs6OAbXz2VgimT2diLPMDBRDLMONVhkDAYoh4sUQkXdOQn8YdvYubj98Jl3brVUwncii20Q2Xo7Ly5FtIjQx1RwBKsRpDjGfwfLly9G8eXOEhISgatWqiS4IDQ1FjRo1sGLFCtSvX59PWLAZPCfDc1K6q7NiBdC4scy2Xj2gRAmgYUNhClwf4bVsGdC8uSzv2rVA7dq6QyYyQ0qiRLYOyWYNAhRDZPREiyHn7zxB8KQwSbYBtfOiY+Uc1phZtbX0RpxlUFIMsQw3WiU+AhRDlMeQ33dF4GFMLLIHeOJ/hdOLb1yNJEzoDyuP34LL92PAuoIv61ROI67GJcv7+4SXIxtXc5I8KQSoECfA/mBFtTcfUJ44rFDn7e2NlStX8qYK93uek+E5Kd0Vev+E2eHDQBFx3mYwmXSGhwMVKsgw/fIL0K6d7pCJzJCSKJGtQ7JZgwDFEOVJlDU4m7t2X0Qkms7aJS0b16QwmpXMbC4JzeZT11TzoaUYYj5mtMIYCFAMUR5DCg7dIF0V/V+h9JjesrgxDKyBlAn9YaMZ4Th45QFyBKREaJ8qGnA0NklejsvLkY2tPUmfGAJUiBNgb6RPnx69evVC//79udKMGzcOP/30E27cuMGdK9oEnpPhOSnd9endG5g8WWYbGQn4+uouQlIMP8IrIgLIlk1eMnw4MGSIUPLaWhhKomxtAeKvFQIUQ5QnUVrZwBTdjSduocPCA9KvWKMG1rBBlBFxLxoNpu/Ag6cvExXJ18MVK7sEIdA/pShi21QOiiE2hZ+Ya4gAxZAPY0je4mUxdft1eLg6o37RjKiQ692by+VHh0rdVCvm8sfCr8toaBXg3O3HmBceAS93FzQslhH50qfSlJ85xBP6w3a/7cemU7fh4+GKw0NqmEPKIebyclxejuwQIDmgklSIE8Dobm5umD17Ntq0acOVZsGCBdIbcc+fP+fOFW0Cz8nwnJTu+rBrqex6qqcn8OiRcF1IP8KL7Qn3163UO3QAZs/WHTKRGVISJbJ1SDZrEKAYImYhbnLIGUwJPS8J16xkJrQNyiZUInX00k18s/gALjz+uMM2u17ETvFREe7dJ5NiiDVeitaKjADFkA9jSNo8JfDZgiPSD3+oXwBflAt8a75aP23D6VuPUSSTN/7t9voWikbG3XTyNtr9vl+iPqd1CdQoIM7bawn9Yf/lR7F0/1VJ1vMja8PFOZlGqBiTLC/H5eXIxtSapOYhQIU4HkI6/D4gIEA6Dde3b18utwkTJmDs2LG4y7piGmzwnAzPSemubqlSwP79QP78wIkTurPnMTSJV0CA3O21bl1g9WoeCYf6PSVRDmVuh1KWYsiHSVTlypXh4+Njsz3ATpv1W34UeyMiP5JBpALXG5+YPl9JLD54B/8clk/ai/Senc2MaIIxxRCRrEGyqIkAxZAPY4hX9qL46o/j0g8nNC2CJiUyvYX7zbX+bP4psaWvtlcwVx25gR5L5KZxi9uVQfmc707mqWl/S2gl9Ifj1p/GjK0XJFL7BgUjwMvNErJ2u4aX4/JyZLsFxsEVo0KcABsgODgYcXFx2LJlC1ca9kZcsmTJsGmT3InNSIPnZHhOSndd06YF7tyRmx6w5geCDZN4sXfsjh4FihUDDh4UTGLbikNJlG3xJ+7aIUAx5MMkypaFuEv3osHeyomKiU3U4KJc+XzfJ16LdkLdaTskmYd/WgBfln93AkS7nWssyhRDjGUvklY5AhRDPowhLpkLo+uyk9IPZ7QsjjqF3jVlaPfbPmw6dQf+nsmxf3B15SBbOPNl3CtEP49DiuTOSO4izimzhP5w7vaLGPHfKUnL9b0qIm86ca7RWgi9qst4OS4vR1ZVGCImDAJUiBPAFPPmzUP79u0xd+5ctG3bNlGJfvvtN3z11Vf49ddfFV1jFUC1D0TgORmek9JVn6dPAQ8PmWXHjsCsWbqyV8LMJF516gDr1gFp0gC3bysh4zBzKIlyGFM7nKIUQz5MomxZiDNSE4T3feIzJ3eUHR0qAdm9ak70qZHH4T5HPIUphvAQot8bFQGKIR/GkNi0BdD3nzPSD+e3LYVP8qR5a9reSw9jxaHrSO6cDGdG1IKT08dX+426D8yRO6E/XHnoGr5ZKl/nFe30njl6aTWXl+PycmSt5CK6tkWACnG2xV/izk7DsZNuO3bsQOvWraViW5EiRZAqVSo8fvwYhw8fBguSixYtQsWKFREaGiqdijPa4DkZnpPSVd9z54DcuWWWI0cCAwfqyl4JM5N4tW8PzJ0rL3/xAnB1VULKIeZQEuUQZnZIJSmGfJhE2aoQd/LGI9SZul3xHlzXs6JN34x73yd6eKZC7sHrJNk/L50FoxsVUqyHo0ykGOIolnY8PSmGfBhDHvrlw5D/zkk/XNaxHEpn83u7KYb+exy/7bos/f/pH2vB3dXZ8TYMgIT+cNvZu/hi3l4Ji2mfF0O9IhkcEpfElObluLwcmcC0TwSoECeIXR89eiQV4FasWGHy25X4+Hg0atRIKsixAp0RB8/J8JyUrjqHhgLBwTLLhQuBVq10Za+EmUm8hg4FfvhBXn75MpAlixJSDjGHkiiHMLPDKkkx5OPEQO/NMDnkLKaEysmbktErOBd6Bb/+wkfJApXnJPSJhYdtwKNnL1Ejf1rM+aKkytyMT45iiPFtSBokjgDFkHcx5JZXbozeeFECa033CiiY0fstcBM3nsG0zXITnr0DqyFNqtdN0hxscyX0h8evP3z7vMGwevnRJiibgyGStLq8HJeXIxOY9okAFeIEsyv7IK5cuRKnTp0CC4qs6JY/f340aNAAxYsXF0xa88ThORmekzKPm5Wz580Dvv5aJhIWBlSqZCVB9ZebxGvOHPkqLRu7dgFly6rP2KAUKYkyqOFIbLMQoBgSBludiBu++gTmh0cotlfboEAMrVdA8Xy1Jyb0iVUnbsXFu9EokdUXf3curzY7w9OjGGJ4E5ICChCgGBKGS+458NMW+dTb5j6VkT3A8y1yv2y7iJFr5bfQNvWuhJxpvBSgatmUMetOY+uZO0jl7oqlHcsKdQ02oT+8+fApyo3eLCnao2pO9KbnDT4wOi/H5eXIlu0gWiU6AlSIE91CdiQfz8nwnJSuUAwbBgwfLrO8dAkIFO/hapN4rVkD1Ksny718OdC4sa6wicyMkiiRrUOyEQJ8BESPIUY/EVd36nYcv/EIXu4u+CooG2oVTGfTq7P8HaHvDIoh+uJN3AgBtRFQGkNOJMuGOeFXJfa7B1RDOu93p96W7ruC/n8fk37HvrBgX1xoNbr8cQBrj92Cl5sLjg2vqRUbi+gm9IfPX8Yhz+D1Eq0WZbJgVEN63uB9YHk5Lm9vWmQkWiQ8AlSIE95E9iMgz8nwnJSuSHz1FTB/PsDe4nv2TMi31kzidegQ8Obk5JQpQI8eusImMjNKokS2DslGCPARED2GGPWNuGyFS2PEhgjsjYj8yAilA/0wrklhBPqn5BvIzmdQDLFzA5N6do+A0hhyIC4Lft97Q8LjyNAa8E7x7r3ldcduovMfB6XfLWhbClXea+SgNoCtf92D7efuIb23O3YNqKY2eavomfKHhYZuwOPnL1GrQDrMal3CKvr2tpiX4/L2pr3hQfrICFAhjnaCbgjwnAzPSekmKGPE3odj78RlygRclb8VE22YxOvOHSBtWlnU/v2BMWNEE9tm8lASZTPoiTEhoAoCRoghRuua+tf6MEw/444HT18maiNfD1es7BLk8MU4iiGqfIyJCCFgMwSUxpAdzzLhr0O3JDnPjawNV+d3DfLCz99Dy7l7pN9N/bwYPtWwKUGjGeE4eOUBcqbxxKbelW2GmynGpvxh5fFbcPl+DNgXOMs6lRNKXlsLw8txeXvT1vITf20QoEKcNrgSVRMI8JwMz0npCirrmMo6p5YvD4SH68paKTOTeL16Bbi7A7GxcoMJ1miChoQAJVG0EQgBYyNghBgScS8aDWeEIyomVvjCFvOJjafvwIXHTtyNQYkVxRDuJqEJhIDgCCiNIRsfpcd/J+4iuXMynB1Z+wOtjl57gE9/lvOCEQ0KolXZrJppXWNyGM7efoKimX3wT9cgzfhYQtjU39Qs9h268gDZA1Jic58qlpC12zW8HJe3N+0WGAdXjApxDr4B9FSf52R4Tko3WVkxy8MDeP4c+OwzYMkS3VibwyhRvLJmBa5cAapWlU/10aBCHO0BQsAOEDBKDGHFuI6LDuDMrccfoS7SVc89Z66j+fzDinfGup4VHfrNOPoyR/FWoYmEgJAIKI0hq+6nRejZ+0jl7oKjwz58m4359yoTtkr69auVB12q5NRM1/KjQ3Hj4TNUyOmPRe3KaMbHEsKm/GG73/Zj06nb8PFwxeEhNSwha7dreDkub2/aLTAOrhgV4hx8A2zevBnVqsnvDpw7dw45c74LKE+fPsWwYcOwePFi3L17V/pdz5490b59e4tQ4zkZnpOyiKkli27fBtKlk1f26weMHWsJFc3XJIpXuXLA7t1AnjzA6dOay2EUBpREGcVSJCchYBoBw8QQAKuO3ECPJYckRWrkT4v8GVKhZgGxmh+MXn0Us18/SK5kz/UKzoVewbmVTLXLORRD7NKspJSNERAxD/n7TgC2XYiCv6cb9g8O/gChyOgXKP5jiPSzTpVz4LvaeTVDsPCwDXj07CVqFkiL2a1LasbHEsKm/GH/5UexdL/8nM/5kbXh8t6VXkt42NMaXo7L+/vGnrAgXd4hQIU4B94NL168QJEiRXD16lVER0d/VIj73//+h40bN6Jbt27Inz8//vvvP/z7778YN24cvv32W7OR4zkZnpMym6GlC/btA0qXlldPnw506WIpJU3XJYpXkybA338Dnp7A449PZGgqlMDEKYkS2DgkmmEREDGJqly5Mnx8fGyK6YLwSxi2+qQkw5ruFVAwo7dN5THFfODyg1i8/6ZiudoGBWJovQKK59vbRIoh9mZR0sfWCIiah/x5yx+7Lj1ABm937EzQJCE27hVyDVonQadld9D4+HjkGLgWr+KBJiUyYULTIrY21wf8TfnDUzcfISr6Bfw8kyN3Gi8kS8Z/9kAopTQUhpfj8nJkDUUj0jZEgApxNgTfFOsr7EphEsPJyQkpUqRA6tSpwf7bmjF69Gj89NNPaNGihfTv90/ErVmzBvXq1cOkSZPwzTffvGVTv359hISE4PLlywgICDCLPc/J8JyUWcysmcyKWKyYxcbq1UDdutZQ02xtonj17AlMnSrzffQI8PLSTAYjEaYkykjWIlktRUDPGCJqEiVCIW5SyFlMDT0nmXHnd1WRwSeFpSbVbB2diDMPWooh5uFFs42JgJ4xRNQ8ZOF1P+y/8ghZU3sg7NtPPjLkkasP4OnugtQpk8PHI7kmhn76Ig75hqyXaLcpH4hhn4r1JYgwOZsm6KtPlIcXL0dWXyKiKAICVIgTwQrvyZAsWTJFBTZWjPvkk0+kq6MlSpjfIpoV0tgpt59//lkqqg0fPvyDQlzLli2xYsUKREZGSoW/N2PLli2oWrUq5syZY/YVVZ6T4Tkp3Uw1eTLQu7fM7sgRoHBh3VibwyhRvNhV2u++k0mdOgXk1e7YvDny2nouJVG2tgDx1wMBvWII00XUJEqEQtzgf45h0W75i7XTP9aCu6uzHuY3iwe9EWcWXNTwxzy4aLZBEdArhoich8y74osj1x/btFvpncfPUHqk/M5zt09yom/NPELtKGFyNqFQSVwYHl68HNkgapKYZiJAhTgzAdN6+vz586Xi2MWLF8GKYblZ904AZ86ckd5qy5UrF7744gvp/xcuXAh2IiEsLAylSpUySzR2su3OnTvYuXOnVIRLWIjLkycPfH19sZu9NfbeYO/GeXh4oGPHjpg1a5ZZPHlOhuekzGJmzWR2AvCnn2QKUVGAja84JaZKongtWgS0bi0vY80aWNMGGpRE0R5wCAT0iiEiJ1EiFOK6/HEAa4/dQsrkzjjxQy0h9x6LIdQ1Vblp6Msc5VjRTOMioFcMETkPqVSpElJ6eSPuVTxSJLfNlyiX7kXjk9dNIdg7dOw9OpGGMDmbSKAkIQsPL16ObBA1SUwzEaBCnJmAaT2dXQWdPn069uzZA39//w/YscJZ2bJlpaui3bt3x82bN1GsWDHpRBx7v03pYNdOWQDcu3evtJadqktYiPPy8kKNGjXwN7ummWD4+fkhKCgIq9m1zUQGk4398/44deoUWrVqha1bt0pv0yUcjx8/BnNExYsXB+Nvq+HRujWSr1mDeC8vPLx8GbDyCrBWeiSGl8u2bfCsX19iGz1zJmJZ51caSGp/HTlyBFWqVMGBAwek/UeDEDAqAnrEEIaNyEmUCIW45rN3Yc+lSGT2S4Ht/cT8MoQlBsvXh+HnM+548PRlolve18MVK7sEIdA/pVE/FqrITYU4VWAkIoIjoEcMoTyEvwlO3nqCFguOSBMH1siOZsXT8xfpOMPU39RRMbGYu/MqImNiEZzHH9XypNZRIrFZ8XJcykPEtp9W0lEhTitkLaSbI0cOtGvXDgMGDDBJYdSoUWDfVrH33NgYPHiwVLiLYie3FAx2oq1AgQKoXr06Zs+eLa0wVYhzdnZG8+bNpVN4CUeGDBmka62bNm1KlOMbmqYmTJw4EUxPUUflPn3gc+ECHmXJgi1v3loTVVgTcnlev45qXbtKvznZujXONW5sIOltI+qFCxfQp08fKsTZBn7iqiICWscQJiolUXyDNZp7EBfvPUXB9J5Y9KVYj2y/kf5NYpAmewGMD7uJg9cefaRY8UypMOx/OZHFV7w37vhWUHcGfZmjLp5ETUwEtI4h9pCHhF53QsQTJ7g5A61yvtLEkOceOuHnk/JpvNY541AyIF4TPmoSffQC+P6Ai0QyOMMr1MuqDTZqyiwKLcpDRLGEvnJQIU5fvLnc2HtsI0eORO83b5QlWMG+qRo0aBBYIGNj7ty50um4N//PY8AKdzNmzMDZs2ffnrijE3EfopYqVy4ku3cPsdWrI3rZMh6kNvt9oknB48fwyZJFkut5hw54yt6Mo0En4mgPOAQCWscQe0iitN4I16OBycecERvvBH+3eHyVJw4ZDXCYjMm94Gwy3HmWDC5O8ehdyBhya21PJfQpiVKCEs0xAgJaxxB7yEN6LT+Frecj4ZvCBVt6ltHErFvP3Uevv09LtKc0zofKufw04WMpUVM5yMtX8Sg1bidcnJ3wWfH06FMtm6Xk7W4dnYizO5OqohAV4lSBUT0iBQsWhIuLC3bt2vVBkwTGISYmRrqa+urVKxw/flxiOmTIEOmE3NWrV7lC3LhxA9mzZ0evXr2kU3dvxtSpUzFt2jSEhoYiMDBQmuOwb8SxAqeHhwxNp07AzJlcXG01Icn3BlKlAh4/Bho1AkxcL7aVzLbkS9eKbIk+8dYLAS1jCNPBHpIorWxxJeophv133jAny0wlBiPWn8fyw7cliPb2LYfkLsm0gstwdOlEnOFMRgJbgICWMcQoecgfN1LjyYt4lM7mZ7JbaZ9lRxBy8hZSe7phS98qFqDMX7Ly0DV8s1S+mrqkfVmUyyHWNc/E/qZ+/CwWnm4uimmNAI0AACAASURBVBoP8lGwnxn0Rpz92FJNTagQpyaaKtBasmSJ1KSBHQ1v3779B80afvnlF1y6dElq0tCiRQvEx8cjb9680ntryxSc3Dp8+LD0plxSI2XKlHjy5IlEf+XKlY7XNfXsWSDP685Eo0YBiVwRVsHUVpNI0qnnywecPg2ULQvs2mU1L3sgQIU4e7Ai6cBDQMsYYpQkyhZvxLGHtRvNCAd7IyexIdpba6Z84qSQs5gaKj99sfO7qsjgQ1dS39iTYgjP+9Dv7QEBLWOIUfKQ4UdSyO+c5UuDuV+a1wxPrT2wcPdlfP+PfOhiTfcKKJjRWy3SqtDhFZZUYWJHRHh4UbMGOzK2GapQIc4MsPSa+scff6Bv3764ffv2228UWNEtXbp0GDt2LFq/7ojJOqYeO3YM7M229On5j3g+fPgQISEhH6nBinh//fWXdCouU6ZMaNCggdSI4dNPPwW7CsuaQ7wZ7IFuRiMiIgJp0qQxCxKek+E5KbOYWTqZ4VOjhryadR9t2dJSSpqvSxKvatWAzZuBzJmBK1c0l8UIDCiJMoKVSEY1ENAqhhglibJFIa7ZrF3YGxHJNV/pQD8s61SOO0+PCaZ84vvJ379dg1Aks48eohiCB8UQQ5iJhFQBAa1iiFHykKW3/PEkNh7MXw+um18FRM0nwU7EzQ67iMfPXkon4rKkfn1bx3xSmqwQImfTRDNtiPLw4uXI2khFVG2NABXibG2BRPjHxcVh//79UsGLFeGyZcuGkiVLgjVRUHuYeiOO8ahVq5Z0XZW9QceaM7AHuv/991+MHj0a3333ndli8JwMz0mZzdCSBb/+Cry5trttG1CxoiVUdFmTJF5ffAEsXAi4uADPnwPJ6HoRJVG6bEtiIggCWsQQoyRRehfiTt54hDpTtyu2/LqeFZEvfSrF87WaaMonrj9+E50WHZRYstMgBTJ4o1bBdELIqxUOSulSDFGKFM2zBwS0iCGJ4UJ5iPF2jBA5m4Fg4+HFy5ENpCqJagYCVIgzAyx7nZpYAGRv0g0dOhTsmPrdu3el67I9e/ZEx44dLYKC52R4TsoipuYuGjoU+OEHeVVEBJA1q7kUdJufJF7sSu2YMbIst24BadPqJpeojCiJEtUyJJfREXD0JGpyyFlMeX2dU4ktewXnQq/g3EqmajonoU+MuBeNzn8cwKmbjz/iy06GjGtSGIH+Bug6oRFqFEM0ApbIOjwClIcYbwsk5g/n7bgEdrL63pPn0vMGXu6uxlNOA4l5OS4vR9ZAJCIpAAJUiBPACImJEB0dLb3Rxk7EJRxZXnfFFFj8j0TjORmek9JF17ZtgQUL5BNk7CQZO1Em6EgSr2nTgB49ZMkPHACKFxdUC/3EoiRKP6yJkxgI6BVDHD2JGr76BOaHRyg2etugQAytV0DxfK0mvu8To166Gu6NO61wSYwuxRC9ESd+tkZArxiil55q5SHrj9/C0FXH8eTZS8xvW1pq6uBoIzF/+PPmc5iw8awEx9a+VRz6y5v39wQvx+XtTUfbX46iLxXiBLN0bGwsRowYgdmzZ0un0BIb7Mi40QbPyfCclC76GuhttSTxWrECaNxYhmz1aqBuXV3gE5kJJVEiW4dkUwsBiiFh0Ptqqj2ciOvw5ynDvXGn1mdGKR2KIUqRonlGRsDRY8jWrWEoXjYIAX6+Utdo52ROH5mTFeI6LTog/Xxem5Komlf9WydPX8Qlyl+E/ZWYP/xz7xV8t+KYJOLfncuhRFbHK1Kasg8vx+XlyCLYnGRQHwEqxKmPqVUUO3fujDlz5kiNElgy4evra5Lel19+aRUfWyzmORmek9JF5ly5gPPngaAgYMcOXVhayiRJvHbvBsq9fhB81izAwuvElsom4jpKokS0CsmkNgIUQ/QvxBn9jbh0eUui+fzDireiKG/cKRZYpYkUQ1QCksgIjYCjx5ANm8PQf698G+brCtnwvYlmDeHn76Hl3D3SnCmfFUX9ohlVt2mruXuw4/w95EzjiU29K6tO31qCifnDkJO30f73/RL5Wa1KSG+M0gB4OS4vRyYM7RMBKsQJZtfUqVODdSadN2+eYJJZLw7PyfCclPUScCi8egWkSAG8eAF8/jmweLHmLK1hkCReV68Cb64vf//9u3fvrGFo8LWURBncgCS+IgQohuhfiGOGMXLX1JPJsmF2+FVF+4tNEuWNO8UCqzSRYohKQBIZoRFw9BiydlMYBu6XC3GdKufAd7XzfmSvw1cfoMH0cOnnIxsWRMsy6r8nXX96OI5cfYA8ab2w4ZtKwu2ZxPzhoStRaDhjp6bYCAeGAoF4OS4vR1bAgqYYEAEqxAlmtFSpUmHChAno0KGDYJJZLw7PyfCclPUScCiwpgbp08uT+vd/1+xAc8aWMUgSr9hYwM0NYO8Lfv01MHeuZUzsaBUlUXZkTFIlUQQohtimEMcaHTScEY6omNhEbePr4YqVXYKEeTPnjU/cE5sZi/ffVPypEuWNO8UCqzSRYohKQBIZoRFw9BiyKiQMQw7IhbgeVXOid408H9nr/J0nCJ4UJv18YJ286FAph+o2nR12ARH3oxHg6WZSBtUZmkkwMX94NTIGFcdtkaj1rp4bParlMpOyfU7n5bi8HNk+USGtqBAn2B5o0KABAgIC8MsvvwgmmfXi8JwMz0lZLwGHwt69QJky8qQZM4DOnTVnaQ0DLl7p0gG3bwO1agHr1lnDyi7WUhJlF2YkJTgIUAyxTSGOmYUV4/otP2ryrTURu46+8Yl0Ik6ZW6EYogwnmmVsBBw9hqzcGIbhB+VCXJ/qudHdRCHp9qNnKDMqVJqTWLHO2LuAL31i/pC9bZdvyHqJwBflsuKH+gX5xBxgBi9n4+XIDgCRQ6pIhTjBzH716lVUrVoVXbt2BXunwY2darKTwXMyPCelOQzLlwNNm8ps1qwB/vc/zVlaw4CLV4kSwMGDQOHCwJEj1rCyi7WURNmFGUkJDgIUQ2xXiHtjmvzfr0dMbByy+nmgYfGMqFkgHfKlTyXc3n3jE+mNOGWmoRiiDCeaZWwEHD2G/LU+DCMPy4U4di2VXU9NOKKfv0SBoRukH9MJ4crw8fH5AKICQ9Yj+kUc6hRKhxktSxj7A6GS9LycjZcjqyQGkREMASrECWaQLFmy4OnTp4iMjISTkxPSpk0LZ2fnD6RkP798+bJgkvPF4TkZnpPic7ByxqRJQJ8+MpGjR4FChawkqO1yLl716skFxdSpgXv3tBXGANQpiTKAkUhEqxGgGGLbQtyz2Djk/V4+DdCyTBaMbChuHHnfJ1LXVP5Hj2IIHyOaYXwEHD2G/LkuDGOOyIU41qiBNWxIOOLj45F94Frp9ZemJTJhfNMixje8mRok5Q8rj9+Cy/djwE6CL+v0unGcmfTtbTovZ+PlyPaGB+kjI0CFOMF2QpUqVaQCHG9s2SLfvzfS4DkZnpPSXNeePYGpU2U2Dx4A3t6as7SGARevTp2A2bNlFk+fAu7u1rAz/FpKogxvQlJAAQIUQ2xbiLv+4CmCxmyWLNWzWi58Uz23AqvZZsr7PvHBS1fDvXGnN2oUQ/RGnPjZAgFHjyF/rA3D+KNyIe7H+gXQulygSTMUGroBj5+/1OTU14uXr7Dzwj14ubsgk68H0qYS7+/3pPxhk5k7sf9yFLL7p8TmvlVssY2F48nL2Xg5snAKkUCqIECFOFVgJCJKEOA5GZ6TUsLDqjkNGwL//AOkSgU8fGgVKT0Wc/H68UdgyBBZlIsXgWwff6unh5yi8KAkShRLkByEgGUICB9D2GHqaw/w6c9yN70fGxRE67Lqd9OzDL2PVyX0iUZ7404tHJTSoRiiFCmaRwiIiYCSGPLbmjBMPi4X4sY0KoTPSmcxqUy50aG4+fAZKubyx8KvX78vrZLaNx8+RbnR8hc6rNkBa3og2kjKH3ZaeADrT9yCl5sLjg2vKZroNpGHl7Px9qZNhCammiNAhTjNISYGbxDgORmek9IcyTdvqhUsCBw7pjk7axlw8fr1V6BdO5nN9u1AhQrWsjT0ekqiDG0+Ep4QgPAxBMDm07fx1YL9krVmtiyO2oVed+IW0H6J+cTVR26g+5JDksRV8gSgf628Qr5xpzekFEP0Rpz4EQLqIqAkhsxbHYapJ+RC3MSmRdC4RCaTQlSfFIZzd56gWBYfqRu2muP8nccInrRNIjmoTj60r5RdTfKq0ErKH37/z3Es3C0/oXT6x1pwd/3wiSVVBDAYEV7OxtubBlOXxFWIABXiFAJF06xHgOdkeE7Kegk4FAIC5LfUWJMG9raa4IOL1/r1QO3ashZLlwLNmgmukbbiURKlLb5EnRDQGgHRY8jJG48wKeQMNp26I0ExoWlhNCmRWWtYLKafmE98vyNgt09yom/NPBbzsKeFFEPsyZqkiyMioCSGzFm1DTNOyoWjqZ8Xw6dFMpiEqsH0cBy++gC50ngipHdlVeE8dCUKDWfslGiOblQInydyKk9VpmYSS8ofTg09h0khZyWK2/t9gsx+HmZSt7/pvJyNtzftDxHSiCFAhTgb74NkyZKB/fPo0SN4eHhI/817I479/uXLlzaW3Hz2PCfDc1LmczRjRUwMkDKlvKBzZ2DGDDMW22YqFy/WcKLI6wdkWSOKb76xjaCCcKUkShBDkBiqIkAx5B2cXJ+oKvLviBn1SmdieL2Me4Vcg9dJD5E3K5kJ45o43kPkprYKxRCNPkBE1qYIUAz5MIbM/GcbZp+WC3GzWhVHrYKmTzW3/nUPtp+7hwze7tg5oJqqNtx+7i5a/7pXoplUMVBVpmYSS8ofLtl7BQNWyDeLVnQpj+JZfM2kbn/TeX+f8HJk+0OENGIIUCHOxvtg2LBhUuFt0KBBcHFxwZv/54k1dOhQ3hThfs9zMjwnpalCZ84AefPKLEaPBr77TlN2ahDn4nX/PuDvL7Ni3WAnTFCDrWFpUBJlWNOR4EkgQDHkHThcn6jBTrp0LxqNZoQjKiY2Ueq+Hq7S1aVA/9df9mgghyUkk8Kr5IgQ3HvyAp/kCcD8tqUtIW93ayiG2J1JSSHgbd5BeQjr0/YAP6/chrln5ELcr1+WRLV8aU3uk86LDmDd8VtSQ4Vjw9R9B2398ZvotOigxHd+m1L4JG8a4fZqUv4w5ORttP9dfqJhdusSqFkgnXDy6y0Q7+8TXo6st7zETx8EqBCnD87EBRD7fZ+NG4GarwPpH38ALVoIbzOeU5eOM6RIATx/Dnz+ObB4sfA6aSkgJVFaoku0CQHtEeD9ocr1iRqI2GzWLuyNiORSLh3oh2WdynHn6TkhKbw+mbAVrMjolzK51HCiVsF0Dv9OHMUQPXcn8SIE1EdASQz5acU2LDgrF+J+/6o0KuUOMCnIt38dwV8HrsHJCbg4qg73NpM52vy1/yq+XX5UWvJXp3IoFehnznJd5iblD9mVXXZ1l42RDQuiZRlxmxbpAhbkIm9YWOJd3Xl7Uy85iY++CFAhTl+8k+T25MkTVK5cGe3atUNndj3SzgbPyfCclKZwzJ0LtG8vszBIYwNFeGXPDly6BFSqBISFaQqh6MQpiRLdQiSftQhQDEn6D11r8U24nr0JV2fqdsVk1/WsKFQxy5RPNOo1W8VGsGIixRArwKOlhkCAYsgDTFy+DQvPy4W4Je3LolyO1CZtN2zVCSzYGSH97sTwmkjpJjd4UGPMD7+E4atPSqTW9qiI/BlSqUFWVRpJ+cNbD5+h3e/7EODpJr1vV4NOxFEhTtXdZz/EqBAnmC19fHwwfvx4tH9TFBJMPmvEEboQN2QI8OOPsnqXLwNZTLcrt0Z/tdcqKsRVrAjs2AHkzAmcO6e2CIaiR0mUocxFwlqIAMWQxL9xthDSRJdNDjmLKaHK/Wqv4FzoFZxbbTEsppfQJxr5mq3FIJixkGKIGWDRVMMi4OgxZOxf27DkglyI+7tzOZTIavo02qLdl7Hm6A14urliYrMi8E7hqprNp4Wew0TBmx0oykFUQ8T4hHh48XJk4yNAGphCgApxgu2LunXrIk2aNJg3b55gklkvDs/J8JyU9RIkQaFNG+C33wBnZ+DZM8BFvW+2tJJbEV7NmwPLlslXVKOjIZ2hd9BBSZSDGt7B1KYYol8hbvjqE5gfLp+IUDLaBgViaL0CSqbqMiehTzTyNVs9AKMYogfKxMPWCDh6DBm1bBuWXZQLcau6BaFwJh/dTTJ67SnM3nZR4nt4SHX4eCTXXQYeQ0U5CI+IA/2ehxcvR3YgqBxKVSrECWbuc+fOoVq1aujYsSO6desGb29vwSS0XByek+E5Kcs5K1hZtSqwZYt8Eo6diDPAUIRX797A5MmyNpGRgK/jdi6iJMoAm5pEtBoBiiH6FeLs6UTcjZhkhr5ma/UHRwEBiiEKQKIphkfA0WPI3FXbcN0lPZycXdG7Rm5k8vXQ3aYDVx7D4j1XJL7nRtaGq3My3WXgMVSUg/CIONDveXjxcmQHgsqhVKVCnGDmzpIlC2JiYhAVFSVJ5ufnhxTsNNN7g3VZvWyQYtH7cvOcDM9JaWqqHDmAixeBChXkN+IMMBThNXEi0LevrM3x40ABcU5j6A0xJVF6I078bIEAxRD9CnH29Ebc/H13DH3NVo/PGsUQPVAmHrZGgGKIfjEkMVv3WHIIq47cgLtrMpz+sbatt4RJ/rwc5MXLV7gf/RwPYmKFehvVVmDy8OLlyLaSm/hqiwAV4rTF12zqVapUUdR5Zws7vWWwwXMyPCelmbqvXgHu7kBsrNwtlXVNNcBQhNeSJe86wG7YANSoYQDNtBGRkihtcCWqYiFAMUTfJMrI1znf94lTtl839DVbPT6FFEP0QJl42BoBiiHKYsjLuFd48DQW0c9fwjdlcqRyV++NuLbz92LLmbvw93TD/sHBtt4SFhXiui0+iDVHb0rFxFM/1FKU2wqpqEpC8XI2Xo6skhhERjAEqBAnmEHsWRyek+E5Kc2wuXkTyJBBJv/dd8Do0ZqxUpOwIry2bQMqV5bZzp8PsLfwHHRQEuWghie17QYBEWMI6zLacEY4omJiE8XZ18MVK7sEIdA/pVC2eN8n0ok4vmkohvAxohmEgMgIqBlDdl24j89/2S2pO7l5ETQslkk11ZvO2ol9EVHI7p8Sm/tWUY2umoR4Ocj7b6geG1YDXioWKtXUQy9aPLx4e1MvOYmPvghQIU5fvB2aG8/J8JyUZuDt2QOULSuTnzED6NxZM1ZqElaE1/nzQK5cMtsRI4BBg9QUwVC0KIkylLlIWELgIwREjSGsGNdv+VHsjYj8SObSgX4Y16SwcEU4Juj7PpHeiON/4CiG8DGiGYSAyAgoiSErNoQhR8Fi8PP2Rr70XnBJ5H22Y9ceot7POyR1f2xQEK3LZlVN9Vo/bcPpW49ROJM3VnWroBpdNQnxcpCtZ+7g4OUoBHi5oXGJTPBILn4TPDXxSUiLhxdvb2opG9G2HQJUiLMd9klyDgkJwaZNm3Dnzh3069cP+fLlw+PHj7Fv3z4ULVpUejvOaIPnZHhOSjN9//oLaNZMJv/ff0CdOpqxUpOwIryePgU8Xj80ywqMrNDooIOSKAc1vIOqTTFE/053Q/89jt92yc1+2pYPRLNSmYV+GyehTzTyNVs9PuYUQ/RAmXiIgoCjxpDev23H5ptyc4QjQ2vAO4XpK6d3Hz/H/PBLSOnmgsq5A1Awo3rN9SqM3YxrUU9RPkdqLG7/+qCAKBvjtRyKchDBZLalODy8eDmyLWUn3tohQIU47bC1iPKLFy/QuHFjrF27FvHx8dKdehYMq1atiufPnyNjxozo2bMnvv/+e4vo23IRz8nwnJRmsr/f0ODYMaBgQc1YqUlYMV6saMuaf9SvD/zzj5oiGIoWJVGGMhcJayECFEOUve9jIbxJLnu/EHfyh5rCnwBI6BONfM1WC3smpEkxRA+UiYetEXD0GNJjwXZsuyUX4tjbZimSO+tukiLDN+Lh01jUyJ8Wc74oqTt/JQwV5yBKiDnAHB5evBzZASBySBWpECeY2QcPHoyxY8diypQpCA4ORt68eaWTcawQx0bHjh1x+PBh7GHXKQ02eE6G56Q0U7dHD2DaNJn8w4dAqlSasVKTsGK8WGHxxAmgZElg3z41RTAULUqiDGUuEtZCBCiG2K4Q13nRAaw7fguebi44PrymhRbUb5kpn2jUa7Z6oEYxRA+UiYetEXD0GPLbmjB4Z84LFzd3fF46C5yTOelukn8PX8ejp7HI4JMC1fKl1Z2/EoaKcxAlxBxgDg8vXo7sABA5pIpUiBPM7NmzZ0f16tUxe/Zs3L9/HwEBAR8U4iZPnozRo0dLV1aNNnhOhuekNNO3QQPg338Bb2/2aI5mbNQmrBivmjWBjRvlhhTXr6sthmHoURJlGFORoFYgQDHEdoW4JjN3Yv/lKGTzT4ktgj6w/f7WSsonnrr5CL2XHcapm4/h5ASs6VYBBVS8emXFFrfZUoohNoOeGOuIAMUQ28UQHc1sNSteDhL3Kh6hp27jzuPnyOLngUq5A6zmaWQCPLx4ObKRdSfZE0eACnGC7Q43NzdMnz4d7dq1M1mImzNnDnr06IFnz54JJjlfHJ6T4TkpPgcLZxQvDhw6BBQqBBw9aiER/ZcpxqttW2DBAiBZMuD5c8DFMR9MpSRK/z1KHPVHgGKIbZKokzce4fNfduHh05fI4O2OX9uUEvp9OLYzeTFk7PrTmLn1grSJ9w0Klh7dduRBMcSRre84ulMMUR5DWEOCqJgX8EvpJr0T50iDFz/Y80q5B69DbFw8GhbLiMnNizoSPB/pysOLlyM7NHh2rDwV4gQzLnsDjl0/HTJkiMlCHCvC/ffff7hwQf7j2EiD52R4TkozXf39gfv3gbp1gdWrNWOjNmHFeA0eDIwcKbO/dg3ImFFtUQxBj5IoQ5iJhLQSAYohypMoK6GWlhv5KicvhiwIv4Rhq09Keq7pXkHVx8jVwF5vGhRD9Eac+NkCAYohymNI+dGhuPHwGSrm8sfCr8vYwlw248mLH0ywoDGbcf2B2E0n9AKQhxcvR9ZLTuKjLwJUiNMXby63r7/+WmrOcOzYMbx8+fKDq6mnT59GyZIlweawN+SMNnhOhuekNNE3Ohrw9JRJd+kCTJ+uCRstiCrGa+ZMWTc29u4FSpXSQhzhaVISJbyJSEAVEKAYojyJshbuS/ei0WhGOKJiYhMl5evhipVdghDon9Jadqqv58WQdcduovMfByW+wfnSoEAGb9QqmE74k36qA/WaIMUQrZAluiIh4OgxZMqKbfDNmANpfL3wWeksSZqm+qQwnLvzBMWy+Eh+Xo1x48FTrDx0HancXRCU0x/ZA17nKGoQV5EGL34wVg2mh+Pw1QfImcYTm3pXVpG78Ujx8OLlyMbTmCRWggAV4pSgpOOcq1evSsU2Dw8PNGnSBJMmTUKnTp2kDqq///47vL29wT6sadOK+XhnUlDxnAzPSWlihtOngXz5ZNJjxgD9+2vCRguiivFi79+xd/DYWLny3X9rIZTANCmJEtg4JJpqCFAM0a8Q12zWLuyNiOTarnSgH5Z1Ksedp/eEpHwiO+nHinDsrbiEg+kzrklhIYuLWmJIMURLdIm2KAg4egxpMWs7Tj5IhjRebtg7KDhJs7wpNOVK44kQlQpN4efvoeVcuSHflM+Kon5RMW+xKMlBOi7cjw0nbsPL3QXHhonfwEjLzyAPL16OrKVsRNt2CFAhznbYJ8r50qVL6NatGzZs2IBXr15J85ycnKQmDjNnzkS2bNkElJovEs/J8JwUn4MFMzZsAGrVkhcuXgx8/rkFRGyzRDFe+/e/OwXHTvy9OR1nG7FtxpWSKJtBT4x1RoBiSGX4+Phoijp7E67O1O2KeazrWVG4k2SJ+USjn/RTbBQzJ1IMMRMwmm5YBBw5hjSbuR1nHyZDRp8UCP+uapI2bP3rHmw/d096F3TngGqq2Hv98VvotOiARGtem5KomlfMgxdKcpDv/zmOhbsvS7qc+qEWUiR3VgUjIxLh4cXLkY2oM8nMR4AKcXyMbDbj4cOHOHv2rFSMy5EjB/zZW2YGHjwnw3NSmqj+yy9Ahw4y6R07gCB1jpZrImsCoorxunHj3btwAwe+ey9ODyEF4kFJlEDGIFF0QYBiiHYwTw45iymh5xQz6BWcC72Ccyuer8fExHyi0U/6aYUdxRCtkCW6oiLgiDGk8fQduPDYSVH3604LD2D9iVvSNdKjKp34ehYbh9uPnuHxs5fI7OcB7xSuQm4PJTnItNBzmBhyVpI/7NsqyJpavCca9AKXhxcvR9ZLTuKjLwJUiNMXby43dv20UqVKCAwMNDk3IiIC27ZtwxdffMGlJdoEnpPhOSlN9Pn+e2DECJn0lStA5syasNGCqGK84uIANzeA/fvLL+UOqg44KIlyQKM7oMoUQ/S5mjp89QnMD49QvMPaBgViaL0CiufrMdGUT7SHk35aYUcxRCtkia5ICDh6DGnw8w5EPHFC7rSe2PhN0u+a9Vl2BH8fvIZkTsCFUXWk20uOMpTkIMv2XUW/v49KkPzVqRxKBfo5Cjwf6cnDi5cjOyxwdq44FeIEM7CzszMWLlyIFi1amJRs6dKl0u/iWFHFYIPnZHhOShN1WWHq998BZ2fg+XP53wYZZuGVKRNw/TpQvTqwcaNBNFRXTEqi1MWTqImJAMUQfQpx9noizh700uqTSTFEK2SJrkgIOHoMqTttB65FO6FAhlT4r0fFJE0zbNUJLNgpfyHjaFcvleQgW87cQdv5+yR8fm5RDHULZxBpq+sqCw8vXo6sq7DETDcEqBCnG9TKGCVLlgyLFi1KtBC3YMECdOjQAS9evFBGUKBZPCfDc1KaqPLJJ8DWrUDWrECE8tMNmshiJlGz8CpdGti3D8ifHzhxwkxO9jGdkij7sCNpkTQCFEP0KcTZw8kxUz7RHk76aeUjKIZohSzRFQkBR48h9vrn1gAAIABJREFUtafswM2nTiia2Qf/dE36uZrxG05j+pYLkvn2DQpGgJebSKbUVBYlOcj7cXJI3fz4qoIx3zhXA0geXrwcWQ0ZiIZ4CFAhTgCbXLlyBezKKRtVqlTB4MGDERz8caeeqKgojB49Gvfv38e5c8rfphFARUkEnpPhOSlN9MieHbh0CahYEdi2TRMWWhE1C6+GDYF//gHYA+ZRUVqJJDRdSqKENg8JZwUCFENk8MzyiVbg/Wap0d9SM4UXnYhLfGNQDFHhQ0MkhESAYsi7GFLjpx2488wJSrpdz9h6HuPWn5EWb+lbRXpXztoxd/tF7L4YKXUandi0CJKxe68CDiXx9t6T5yg5YpMkfafKOfBd7bwCaqKPSDy8eDmyPlISF70RoEKc3oib4Dd8+HCwf3hvC8THx0urp0+fjs6dOwsguXki8JwMz0mZx03BbHa9N0UKIDYWaNkSWLRIwSJxppiFV9euwIwZsvDR0YCHhziK6CQJJVE6AU1sdEeAYogMuVk+UQUrRdyLRsMZ4YiKiU2Umq+HK1Z2CUKgCgmaCiJ/QILeiDMPUYoh5uFFs42DAMWQdzGk6uQdiHzuhKCcqfFHu7JJGnHhrgh8/698y2RN9woomNHbaqP3WHIIq47cgLtrMpz+sbbV9LQioCTevnoVj9yD1+Hlq3g0KpYRk5oX1Uoc4eny8OLlyMIrSAJahAAV4iyCTd1Fhw4dkk6LsUIbu3b69ddfo2zZD50/K9KlTJkSJUqUQM6cOdUVQCdqPCfDc1Kqi/l+N9EBA4BRo1RnoSVBs/Biug0aJIvDTlMadA9ZgyclUdagR2tFRoBiyLskKixMn6upb/YDK8b1W34UeyMiP9oi7ETFuCaFhSzCMWET84lGP+mn1WeVYohWyBJdWyNAMeRdDKk8cQcexjqhSp4ALGhbOknTrDh4Db2XHZHm/NmhLMpmT221KdvO34stZ+7C39MN+wd/fDvKagYqEVCag5QbHYqbD58pKmyqJJqQZHh48XJkIZUioaxGgApxVkOoLgH2rVTjxo1RsGBBdQkLQI3nZHhOSnUVdu8GypWTyc6cCXTqpDoLLQmahddvvwFt2sjisDfxKifdCUpLuW1Fm5IoWyFPfPVEgGKIvoU4Ztsnz1+i4NANkpnzpfdCzQLppH/ypU+lp+nN5pWYTzT6ST+zgVC4gGKIQqBomqERcPQYEjRhB6JfOqF6/rT45YuSSdpyw4lb6LjwgDRn7hclEZw/rdW2bzprJ/ZFRCG7f0ps7lvFanpaEVCagzSYHo7DVx8gZxpPbOrteLnHG/x5ePFyZK3sSHRtiwAV4myL/0fcv/rqK3Ts2BFlypQxKdnevXsxa9YszJs3TzDJ+eLwnAzPSfE5mDlj2TKgeXN50dq1QG1xj4Cb0swsvEJCgBo1ZDJ//AEk0pXXTAQNNZ2SKEOZi4S1EAGKIfoX4i7efYKqE8Mki/WrlQddqhjj1HpSPtHIJ/0s/Ohwl1EM4UJEE+wAAUePIWXH78CzOCf8r1B6TG9ZPEmL7jx/Dy3m7pHmTPmsKOoXzWj1Dqj10zacvvUYhTN5Y1W3ClbT04qA0hyk86IDWHf8FjzdXHB8eE2txBGeLg8vXo4svIIkoEUIUCHOIti0W8TrVrR06VKpo2oce9/MYIPnZHhOSnV1J0wAvv1WJnv8OFCggOostCRoFl4nT77Tb/x4oG9fLUUTkjYlUUKahYRSGQGKIfoX4nZduI/Pf9ktWZI9rt24RCaVraoNOSUxZO+l+2g2W9ateBYfjGxYSPiTftqglfQbhLy/b7SSiegSAmoj4OgxpNTYHYiNd0KDohnw02fFkoT3yNUHqD89XJozsmFBtCyT1WpzVBi7GdeinqJ8jtRY3D7pN+qsZmYFASXxg5EftuoEFuyUGxIeG1YDXu6uVnA17lIeXhRDjGtbaySnQpw16GmwlhcAZ8yYgb59+yImJkYD7tqS5DkZnpNSXbru3YGff5bJPnwIpBL7GlFC/c3C68EDwNdXJtGrFzB5supwik6QCnGiW4jkUwMBiiH6FuJO3niEqaFnsf7Ebcl8oxoWQosyWdQwpeY0lMQQ9nZtviHr8Sz2FeoWTo+fWyR9QkRzoW3IgGKIDcEn1roh4OgxpNiYHYiHE5qWyITxTYskifv5O08QPEk+DT2gdl50rJzDajsV/WEjHsTEokb+tJjDuRprNTMrCCiJH4z87LALGL3utMRpU+9KyJnGywquxl3Kw4uXIxtXc5I8KQSoECfA/ti2bRu2sne72DcHw4ahUaNGKFy48EeSRUVF4c8//0TmzJnBrqiaO06dOiV1Zz1w4ABu3rwJFmyzZ8+ONm3aSF1Y3dzc3pJkJ+7Gjx+PuXPn4urVqxLPdu3a4dtvv4Wzs7O5rKX5PCfDc1IWMU1qUf36wKpVgI8PEBWlOnmtCZqFF+u46+kJsAJus2bA0qVaiyccfUqihDMJCaQSAhRDZCDN8olWYm8PVzeV4lVl/BZE3I9Byay+WN65vJXIGXc5xRDj2o4kTxoBiiEyPvcjo1Bi3E7pv9kXKuyLlaTG7UfPUGZUqDSlR9Wc6F0jj1VbjX3xkWvQ6y6jxTNiUjNxu4wqjR9XI2OkE37pvd2R0TcFXJ2TWYWRURfz8OLlyEbVm+ROGgEqxAmwQ960DWeisO6ozBEnNjJlyoRFixahUqVKZku+ceNGTJgwQXp/jtFhxbbw8HAsWbIE//vf/7B69eq3NLt06YKZM2eibdu2KF++PHbu3In58+eD/Xz69Olm82YLeE6G56QsYprUomLFgMOHAVb0PCJ3PTLSMBuv3LnljqlBQcCOHUZSVRVZKYlSBUYiIiACFENko5jtEy205aV70Wg0IxxRMbGJUvD1cMXKLkHCdkw1B69607bj2PVHSJncGe0qZketguI3orDQtEkuoxiiBapEUwQEKIbIVrh19z7KTpSv4rcpH4hhnyb9ZM2Ll6+w8eQtpHRzQQ5/T2RJ7WGVOWNevET+IXLjHyX8rWJm5WK94q2VYgqznIcXL0cWRhESRFUEqBCnKpyWEWMn3SIjI6UCXO7cuTFx4kR8+umnHxBjBbqUKVMibVrrO/IklLJbt25Sce306dPIkycPjh07hiJFiqB79+6YMmXK2+k9e/bEtGnTcOTIERQqlPS3RKaQ4DkZnpOyDN0kVqVODURGAvXqySfjDDbMxqtKFSAsDAgMBC5dMpi21otLSZT1GBIFMRGgGCLbxWyfaKE5m83ahb0RkdzVpQP9sKzT687c3Nn6T+DhZQ+n/tRElWKImmgSLZEQoBgiW+PqrXuo+JPcfKF9xWwY9L/8uprp/RN23avmRB8rT9hpKTwvfmjJ24i0eXjxcmQj6kwy8xGgQhwfI11nhIWFIX/+/AgICNCNLzslx66c7t69WzotN2jQIIwaNQoXL15EtmzZ3spx6dIl6SrrwIEDMXLkSLPl4zkZnpMym2FSC548Abxev1PQteu7t+JUZaItMbPxatkSWLwYSJ4cePaMHb/UVkDBqFMSJZhBSBxNEKAYou0bcexNuDpTtyu23bqeFYVtbpCUT7SXU3+KDaVgIsUQBSDRFMMj4Mgx5F5kFP5ctw2FihZDtnT+Vp9wM3cznL/zGMGTtknLBtbJiw6VrH9zzlwZlM43OwdRSthO5/Hw4uXIdgqLw6tFhTgH3AKs0QP7Jzo6WnprrmvXrnB1dcX58+eRIkUK1KxZUzr1duvWrY/QYSfyihUrhvXr15uNHM/J8JyU2QyTWvB+F9GxY4F+/VQlrwcxs/FiHWJZp1g27t4F/P31EFMYHpRECWMKEsTgCDhyDJkcchZTQs8ptmCv4FzoFZxb8Xw9JyblE+3l1J+aeFIMURNNouXICDhyDEnK7gevRKHRDPmNujGNCuGz0uI2/jEnB5m08QzO3XmCzH4eGFgnn0NufR5evBzZIUFzAKWpECegkV+8eIGVK1di37590lWbV69efSAlu6b666+/Wiw5awjB3oN4M9gpuDlz5rxtEMGunSZPnlxq6pBwFC9eHLGxsdL11aQGawbB/nl/sGYRrVq1khpTsKuvCcfjx4+ld+QYD683p9Us1jLphS6bNsGzaVNpUvTcuYht3FgjTtqRNRcvt5kzkWLgQEmgR9u341XBgtoJJyDlpPBihecqVapIe57tPxqEgJERoBiiXQwZt+kiFu//MLYltVdalEyPfsHZhdxOifnEM7ej0Xz+YcUyL/uqKHKnSal4vlEnUgwxquVIbnMRoBiiPIYsO3gT1x48g08KV3xVLpO5UH8wP/xiFLouOyn9bFyDPKiRV9wvzM3JQZrNO4yzd6KRJ01KLP1K3AYUVhmPs5iHF+UhWqIvLm0qxAlmG1a8qlq1Ks6cOQMfHx88fPgQfn5+YO83sIKcv78/PD09pWujlg62lv1z//59bN68GUePHsXo0aOlQgQbOXLkkN6iYw0aEg7WuOHOnTvS6bmkRsJi3/tz2Rt4jIctR9YNG1B05kxJhG1jxiAqb15biqML7wzh4Sg1frzEa9f33+NOiRK68DUCkwsXLqBPnz5UiDOCsUjGJBGgGKLtBll3NRnWX1Pe9a1WpjjUzpx4AyZtpbWMuiPoaBkyia+iGKI2okTPVghQDDEP+UnHnHH5iRPSpYjHgKJx5i1OMPvgPSf8ds5Z+mnnfHHI62Os2JGY8rNPJcP5R07I4AF8U8g6jKwCWODFFEMENo6GolEhTkNwLSHdpk0b6TTcmjVrkC9fPqRJkwabNm2SOpeOHTsWCxYskE6UZc2a1RLyJtdMnjwZ/fv3l66jMp6OcCLOfcQIuE+cKOHx8PhxxGfMqBqeehHifbuSUA7n3bvhVbu29OOYKVPw4osv9BJVCD50mkEIM5AQGiNAMUTbU9X2dFosMZ9oT6f+1Py4UQxRE02iJSoCjhxDzt+4j7FrTyJNQGo0KJoBpbL6cM3U6c8T2B3xAOlSJcf6LqW485OasPzwLYxYf0GasvCLwiiU4fVb1lZR1WaxOTkI6y7r6uwEdqPLUQcPLzoR55g7gwpxgtk9ffr00vXN8ePHSyfWWNOGkJAQVKtWTZK06evrlH/99Zdqkt++fRvp0qV724TBId6IY0WohQsBFxe5cYGz/A2UkQbvvYGPdImIAN4032BXk4cMMZK6VstK7/tYDSERMAACFEO0bdbAtoC9vJ+WmE+0p3fw1PzIUgxRE02iJSoCjhxDdp6+hhYLjkim+bFBQbQuyz/0EBn9As7JnJAyuTNcnJWfljZl/9lhFzB63WnpV6F9KiNHgKeo20S3LuXCAmCmYLycjd6IMxNQO5lOhTjBDOnu7o7p06fj66+/Bquee3t7499//0W9evUkSWfOnInBgwdLRTq1RkREhNQdtXPnzpgxY4ZUkGNXVe26ayq7hhsWBgQGApcuqQWlrnR4Tv0jYZ4/B9zd5R936ADMnq2rvLZmRkmUrS1A/PVAgGKI9oW4iHvRaDgjHFExsYma1NfDFSu7BCHQX9y30xLzifbUGVbNzxzFEDXRJFqiIuDIMWTHqav48vcjiIt3skmzhFlhFzAt9ByiX8Rh76BqSOP1+m92ATeL2TmIgDroKRIPLyrE6WkNcXhRIU4cW0iSZMmSBZ06dZKKYWykSpVKaqzwzTffSP8/btw4jBo1SvomwtzB3nZjV10Tjn79+kkn8Ni11y+//FK6oso6o3bv3h1Tpkx5O71nz56YNm0aDh8+/Laxgzky8JwMz0mZw4s7l50MYyfEKlWSC3IGHBbhFRAA3LsH1K0LrF5tQK0tF5mSKMuxo5XGQYBiiPaFOLYbWDGu3/Kj2BsR+dHmKB3oh3FNCgtdhGNCU9dU8z7XFEPMw4tmGxMBiiFyDGEHIWx1lTLuVTySOcFm/JXsXEtykPj4eMTGxSO5i3UnB5XIJ9ocHl68HFk0fUgedRCgQpw6OKpGpWHDhoiLi8OqVaskmo0aNZI6iS5cuFBq1tC6dWvkzp1bejfO3MFos5N0rClD5syZpT/CN2zYgNDQUFSoUAFbtmyBC7uqCUjFwNmzZ6Nt27YICgpCeHg45s+fj44dO2LWrFnmspbm85wMz0lZxNTUorg4+WTYy5dAq1byFVUDDovwKloUOHIEKFaMGcSAWlsuMiVRlmNHK42DAMUQfQpxb3ZE2/l7seXMXSlp6l41F2oVTId86VMZYsMk5RPt5dSfmoagGKImmkRLVAQohugbQ0TdBzy5zMlBbj58iha/7MH1B0/Rs1oudP0kJ4+83f2ehxcvR7Y7QEghCQEqxAm2EVavXo158+Zh8eLFSJEiBc6dO4dKlSpJnUrZNwnszThWPCvKCipmjqVLl0qn3liX1Lt378LNzQ158+ZF8+bNpdNv7P/fjJcvX0qn7+bOnYtr164hU6ZMaNeuHdjpuTfFOjPZi1OIu34dyPS6xTg7eThypLmqCDGf59RNClmnDrBuHcBORt6+LYQeeglBSZReSBMfWyJAMUTfJKrZ7F3YeykSmXxTYEf/qrY0vdm8eTHEHk79mQ1KEgsohqiJJtESFQGKIebFkHXHbuLXHZfw5PlLzGpVQviT0GrtO178eJ/P0xdxyDdkvfSjlmWyYGTDQmqJYRg6PLyoEGcYU6oqKBXiVIVTG2JPnjzB5s2b4ezsLJ1O8/Hhd/HRRhLrqPKcDM9JWcf9vdW7dgHly8s/YKf7OnZUjbSehCzCq317YO5cWcwXLwBXVz1FtikvSqJsCj8xtyECFEO0AZ+9pfbZnF149OwlMni749c2pQxzGo4hojSGnLr5COM3nMHm03ckICc1K4JGxV9/maUNtEJSpRgipFlIKB0QoBiSOMiL91zBwJXHpAn/dA1C0czGzNHM3UZK48cbusV/DAFrbPFJngDMb1vaXHaGn8/Di5cjGx4AUsAkAlSIo42hGwI8J8NzUqoJunQp8NlnMjl2OqxWLdVI60nIIryGDgV++EEW8/Jl9iihniLblBclUTaFn5gTAlYjIEoMsZeTYubEkC2n76Dtgn2SDVkiVTiTj6Gu4Vq9+TiFS97eVIM/0SAECAHrEOB9TkOORGDAiuPwTOmBEQ0Lo0Iufy7DVUduoMeSQ9K8RV+XUbQmMaKsI/e1qBgUz+qLn1sU5/K25QRz4geTs+607Th+/RHypPXChm8q2VJ0m/Dm4cXbmzYRmphqjgAV4jSH2DwGO3fuRFhYGAYMGGBy4ZgxY6RHRMuVK2ceYQFm85wMz0mppsK4cUD//jK5EyeA/PlVI60nIYvwmjPn3QlAdjKwbFk9RbYpLyrE2RR+Yq4TAhRDzLtWZK5ZLt2LRiM76JjK9FYaQ1jhsduSg1ISlXAYpTGFuXY2NZ9iiBooEg3REXDkGPLPvgvo9fdpyUS/fFES1fOn5Zrr/S8pZrUqjloF03PXJDahwtjNuBb1FOVzpMbi9mL/fa40frzRtcPv+7Hx5G14ubng2PCaFmNk1IU8vHg5slH1JrmTRoAKcYLtkJo1a8LLywvLly83KVmzZs3AjoivXbtWMMn54vCcDM9J8TkonNGtGzB9ujz50SPAy0vhQrGmWYTXf//JHVPZYHuscWOxlNJQGkqiNASXSAuDAMUQbQtx7MSCqU6pCTcAK1At6yT2F2ZKYog9FR6t/ZBSDLEWQVpvBAQcOYas2HMBvVfKhbj5bUrhk7xpuCbbFxGJprN2SfPGNymMpiUzc9ckNqHvX0dw6+EzFMiQCgPq5LOYjh4LlcSP9+UYtuoEFuyMkH50ZGgNeKdwnKdxmM48vHg5sh42JR76I0CFOP0xT5Jj2rRp0b9/f/Tu3dvkvJ9++gnsVNytW7cEk5wvDs/J8JwUn4PCGZ9+CqxeDfj6ApGRCheJN80ivA4dAoq/Pu4+ZQrQo4d4imkkESVRGgFLZIVCgGKIdoU49iZcnanbFdt7Xc+KQr8ZpySG2FPhUbHhEplIMcRaBGm9ERBw5BiybPd59PvnjGSm378qjUq5A7gmY29o1p4ix4Wh9fKjbVA27hp7mKAkfryv59ztFzHiv1PSj0SPjVrYh4cXL0fWQiaiaXsEqBBnext8IAHrlDpx4kR06dLFpGTTp09Hnz598OzZM8Ek54vDczI8J8XnoHAG6zh75AhQpAhw+LDCReJNswivO3eAtK+P2rPruWPGiKeYRhJREqURsERWKAQohmhXiJscchZTQs8ptnev4FzoFZxb8Xy9J/JiiL0VHq3Fl2KItQjSeiMg4MgxZMnOcxiw6qxkpsXtyqB8Tv4bcVcjY1Bx3BZpTZ/qudG9Wi4jmNlqGXnxIyGDtcduossfB6Uf//plSVTLx7/2a7WQAhHg4cXLkQVShURREQEqxKkIphqk8uXLhyJFiuDPP/80Se6zzz4D+7CePSsHCiMNnpPhOSnVdPXzA6KigHr1gFWrVCOrNyGL8Hr1CnB3B2JjgVatgIUL9RbbZvwoibIZ9MRYRwQohmhXiBu++gTmh8tXa5SMtkGBGFqvgJKpNpnDiyH2Vni0FmSKIdYiSOuNgIAjx5BFO85i8Br5y5alHcqiTPbUXJM9iHmBoj+ESPM6Vsou/JVSrkIKJ/DiR0Iyh68+QIPp4dKPf6xfAK3LBSrkZB/TeHjxcmT7QIG0SIgAFeIE2xNDhgzByJEjMXXqVHTt2vUD6WbMmIHu3btLjRxGjBghmOR8cXhOhuek+BwUzHj8GEiVSp7I3oqbNk3BIjGnWIxX1qzAlStA1apAaKiYymkgFSVRGoBKJIVDgGKIdoU4eytM8WKIvRUerf2wUgyxFkFabwQEHDmG/LbtDIauPS+ZaXmncigZ6Mc1WWzcK+QatE6a16JMFoxqWIi7xtSEpy/icP1BDLzcXeHj4Qo3F2eL6Oi1iBc/Espx5/EzlB4p5xydKufAd7Xz6iWqEHx4ePFyZCGUICFUR4AKcapDah3BmJgYVKlSBQcOHECWLFlQsGBBieDx48dx+fJllCxZElu3boWHh4d1jGywmudkeE5KFZFZl9TXmIJ1T/32W1XI2oKIxXiVLw+wjql58gCn5UdpHWFQEuUIViYdKYZoV4izt6uavBhib4VHa70DxRBrEaT1RkDAkWPIvLDT+GHdBclMK7uUR7EsvopMlvf7dXgW+wqfFsmAqZ8XU7Qm4aQDlyPReKbc9GFs40JoXiqLRXT0WsSLHwnlePUqHnm/X48XcdbhpJd+avPh4cXLkdWWh+iJgQAV4sSwwwdSsPffJkyYgL/++gvnzslHpHPlyoXmzZtL78O5ubkJKDVfJJ6T4TkpPgcFM9atA+rUkSey67/NmytYJOYUi/Fq0gT4+2/A0xNgJwQdZFAS5SCGJjWlN0QphvhoshPsqXkBL4bYW+HR2g1BMcRaBGm9URBw1Bjyy5ZTGLnhomSm1d0qoFAmb0UmKzliE+49eY6qedNgXptSitYknLTl9B20XbBP+vHMlsVRu1B6i+jotYgXP0zJUXn8Fly+H4MSWX3xd+fyeokqBB8eXrwcWQglSAjVEaBCnOqQEsHEEOA5GZ6TUgXZ2bOBTp1kUjt3AuXKqULWFkQsxqtnT2DqVFnkR48ALy9biK87T0qidIecGBICqiIgQgyJuBeNhjPCERUTm6huvh6uWNklCIH+KVXVX21iSmKIPRUercWPYoi1CNJ6QsC2CPBiyKzQUxgTIhfi1vaoiPwZXj9lwxH7kwlbceleNEoH+mFZJ8vyin8PX0fPP+UGcou+LoMKufiNImyJppL4kVC+Fr/sxs4L95E2lRv2DAy2pfi68+bhxdubugtMDHVBgApxusBMTBgCPCfDc1KqoDhoEDBqlEzq2jUgY0ZVyNqCiMV4sSu5rGMqG6dOAXkd450GSqJssUuJJyGgHgJCxBAArBjX489DOHrt4UfKsURsXJPCwhfhmOBKYog9FR6t3YkUQ6xFkNYTArZFgBdDpoecxPjQS5KQG3pVQp50yr6orjdtB45df4h86VNhXc+KFim5aPdlDP7nuLT2365BKJJZm1PdFglnYpGS+JFw2Xd/H8Wf+65KPz79Yy24u4r9Dp5aWCmJt7y9qaYsREscBKgQJ4Atbt++jTNnzqBYsWLweu90UlxcHEaPHo3ffvsN169fR/78+aUmDbVq1RJAavNF4DkZS5y62VK0bg0sWgS4ugLPngHJkplNQpQFFuPF9Gc4sMGaNbCmDQ4wKIlyACM7qIoUQ2TDW+wTLdg3O87dQ6tf90grK+XyR/GsvqhZIJ2UiBllKMWLFeP6LT+KvRGRH6lmpMKjtXahGGItgrReVAQohsiWmbrhBCZtkTtjb+pdGTnTeCoy2edzdmPXxfvI7JcC2/tZ9jf1zK0XMHa9/G7zlr5VkM0OTlQnBG/6lvMYv+GMnH70qYwcAcrwVWQEwSfx4i0vRxZcPRLPQgSoEGchcGou6927N+bOnYtbt2590IShZ8+e+Pnnn5EqVSrkyJEDp06dQmxsLLZv344yZcqoKYIutHhOhuekVBGyUiVg+3YgWzbgonz83KjDYry2bHlXfPv993dFOaMCoVBuSqIUAkXTDIcAxRDZZBb7RDMtzt5OmxRyBptO3ZFWjm9SGE1LZjaTiu2nm4vXqZuP0Gz2Ljx+9hIeyZ3RsFhGtCqb1VDFR2tQpxhiDXq0VmQEKIbI1pm8/jimbL0s/ffWvlUUn2xu//t+hJy8DfYswaEhNSwy9bj1pzFjq9woYv/gYPh7iv0euLnxg+m16sgN9FhySNJxfttS+CRPGouwMuIiHl68HNmIOpPMfASoEMfHSPMZpUqVQp48ebCInVR6Pe7evYuMGTMiMDAQu3fvhp+fHy5evIhy5cpJXVWXLl2quVxqM+A5GZ6TUkWewEDg8mWgcmVg61ZVSNqKiMV4nTnz7jrq6NHAd9/ZSgVd+VISpSvcxExHBCiGyGBb7BMV2sreToaZg5e96a7Q5B9MoxhiCWqoN+UQAAAgAElEQVS0xggIUAyRrTRh7TH8vO2K9N/b+32CzH4eiszXe+lhrDh0Ha7OTjg7ojacnJwUrXt/0qCVx/DHHpk3o5HcRewbO+bEjzd6nr71COPXn5FwbVYys+I3+MwGU8AFPLx4ObKAKpFIKiBAhTgVQLSWRJo0adC3b1/069fvLanFixejVatWmDlzJjp27Pj2599++y3+/PNPXL0q37E30uA5GZ6TslrXuDiAdZxl/2ZXM9lpMAMPi/F68uRdg4bu3d81bjAwFkpEpyRKCUo0x4gIUAyRrWaxT1RgdPYQdyM7adLwRl2leNmj7gpM/tEUiiGWoEZrjIAAxRDZSmPXHMXMHXJ+tWtAVaT3TqHIfGPWncaaozfg6eaCVd0qWFRE67b4INYcvYkUrs449aP4TxApjR+KAHSASTy8eDmyA0DkkCpSIU4As6dIkUK6gvr111+/laZHjx6YPn269HZczpw53/6cXWHt2rUrnj9/LoDk5onAczI8J2UeNxOzWXOGzK+vD7GmDSNGWE3SlgSswsvbW+6Y2qgR8PfftlRDN96UROkGNTHSGQGKITLgVvlEjs3ssXuoUrzsUXdLPqIUQyxBjdYYAQGKIbKVRq06gjk7r0n/vXdgNaRJ5a6b+b6Ytxfbzt5FulTu2D2wmm58LWWkNH5YSt/e1vHw4uXI9oYH6SMjQIU4AXZCrly50KxZM4wcOfKtNMWLF8fly5dx//79DyScNWsWBg0a9NHPBVCDKwLPyfCcFJcBb8LOnUBQkDxr9mygQwfeCqF/bxVe+fIBp08DZcsCu3YJradawlESpRaSREc0BCiGyBaxyicmYVT2JlydqdsVm511zTNC0wYleNmr7oqN+d5EiiGWoEZrjIAAxRDZSrNCT2Fh+AW4e6TE312C4OORXDfz1Z8ejiNXHyBPWi9s+KaSbnwtZaQkflhK2x7X8fDi5cj2iAnpRIU4IfZA69atsXnzZuzfvx/p06fHrl27EBQUhM8++wzsiur7o1u3bti2bRuOHj0qhOzmCMFzMjwnZQ4vk3P//BP4/HP5V+vXAzVrWk3SlgSswis4WO6Yyk4IXpHfpLD3QUmUvVvYcfWjGCLb3iqfmMT2mRxyFlNCzyneYL2Cc6FXcG7F8201UQle9qq7JZhTDLEENVpjBAQohmgbQ5TsgU8mbAV7BqBUoC/+6lReyRKbzlESP0wJGBn9AhfvPsH1B09Rv2hGm+qgJ3MeXrwcWU9ZiZd+CNCJOP2wTpQTu35arFgxuLi4SNdQT58+jbi4OKkgx07GvRmvXr1C1qxZUbduXentOKMNnpPhOSmr9R079l1jgpMnAXYqzMDDKry++AJYuBBwcQHYNedkYj8Kq4aZKIlSA0WiISICFEO0TaKGrz6B+eERik3fNigQQ+sVUDzfVhOVxBB71d0SzCmGWIIarTECAhRD1IkhL+NeSYRcnM3/m7r4jyFgRargfGkw98tSwm8bJfHDlBLDVp3Agp1yPD0ypAa8PVyF11UNAXl48XJkNWQgGuIhQIU4QWzCOqP++OOPUmfUbNmyYeDAgahQocIH0oWGhqJXr16YNGkSqlevLojkysXgORmek1LOKZGZXbsCM2bIv3z8GPD0tJqkLQlYhdeAAcCYMbL4t24BadPaUhVdeFMSpQvMxMRGCFAMoRNx5m49JTGETsS9Q5ViiLk7jOYbCQGKIZbHkPDz99D+9/2IeRGHWa2Ko1bB9GaZPj4+HjkHrUPcq3g0Kp4Rk5oVNWu9LSYriR+m5Jq34xJ+WHNS+tWa7hVQMKO3LcTXnScPL16OrLvAxFAXBKgQpwvMxIQhwHMyPCdlNYr16gFr1gB+fkCCt/espm0DAlbh9fPPAOuYysaBA8B7Jy9toIouLCmJ0gVmYkIIaIaArWKIvb6TpiSG2KvulmxSiiGWoEZrCAFxEODFkLv3I7F923ZUqVIJfr6+igXfHxGJJrPk95bHNS6MZqVeN4ZTSOHJ85coOHSDNNueTlSbUv/c7cfYFxGFzH4pUCyLr9Rp1hEGL97y9qYjYOSIOlIhzhGtbiOdeU6G56SsFrtIEYC9rVe0KHDokNXkbE3AKrxWrAAaN5ZVWL0aqFvX1upozp+SKM0hJgaEgKYI2DKG2GPnUKUxxB51t2SjUgyxBDVaQwiIgwAvhvT5cz/+PnxbEvjCqDpwTuakSPirkTEYu/40vNxd0bBYRpTO5qdo3ZtJNx48Rfkxm6X/tac3Rs0Cwc4n8+Itb2/aOTwOqx4V4hzW9PorznMyPCdltcTs260HD4BPPwX+/ddqcrYmYBVee/bIHVPZmDUL6Njx/+ydB5QVxbaGfyYQJaPknHOUPIASDaAiBlCvgKCAD0FQVLheMCAKkhFFEcwIBkwoSHKAAckZJOc8xCFPeqv7AA7DzKmuPt2nq/v8vdZb78rZVbX3t+vUf2pPd5fT4dg+PjdRtiPmACRgKwEnNWRv7AU8NDEGpy/Gpxtj7qyRmNmrEUrky2YrB6s6N6ohXozdDENqiBlqbEMC6hAQaciL36zEzA3HdYf3DLsXGTIYK8QFGuHWI+dwz1jfydyD21ZCl0YlA+3S9vZG9cN2R1wygIiXaG66JEy6KUmAhThJYDQ3T0C0yIgWKfMjAzh3Dsh57T0E2iOZ48YF1J0KjQPideAAUKyYL4zXXwfefFOFkGz1gZsoW/GycxKwnYCjGgJAK0g9/80abD587pZY65bIg+EdqrmmCKcFIKMhWuwDvt+AFXtPeSJ2M5OVGmKGGtuQgDoERBry9ZLt+H3lNhQsWBDvP14naI4fO3cZ368+iLOX4tG6cn7ULi53R13QHE0xkIx+OOGfamOKeInmpmrx0B9rCLAQZw1H9mKAgGiRES1SBoZI32TTJqBqVd/nI0YAL70UUHcqNA6IV3w8kCkTkJwMPPMMMHmyCiHZ6gM3UbbiZeckYDsBJzXEXyGqSqEcmNCplquKcLKFuOvJ1e7c+Ch6F35ed1j/p9rFc6NxmXxoU6UAKhbMYfsccHIAaoiT9Dk2CQROwEkNCdx7tXoIZA8Svf0Elu06iZPnr2DEI9XVCswmb0S8RHPTJrfYrcMEWIhzOAGhNLxokREtUgGx+v134L77fF1Mnw48+mhA3anQOGBeBQv6Tkxt0wb44w8VQrLVB26ibMXLzknAdgJOacie2Ato77HHUs0W4rSCZO9pa7Hx0Nlb8u3GuwJlJi01RIYWbUlAPQJ2asiuE+dx+sJVZIoIR9Ui3j8JNJA9yOs/bcKXf+/TJ8jGIa30d+t5/RLxEs1Nr/MJ1fhYiAvVzDsQt2iRES1SAbmsvQetZ09fF8uW/ft+tIA6dbZxwLxq19aOsgWqVQPWr3c2mCCMzk1UECBzCBKwkYBTGuLVwwpkNcSrBUmjU5YaYpQU7UhATQJ2akjTEQux7+RF1CuZB9Ofa6AmAAu9ktWPlEN/umQP3vpti/5Pv/VujCqFWbgUzU0LU8euFCLAQpxCyfC6K6JFJpBFXchu4EBg2DCf2aFDQKFCwiaqGwTMSzu0QjsxNW9eIDZW9XAD9o+bqIARsgMScJSAExqy5fA53DvO9xJtI9cffaJc84imrIZ4tSBpJK+aDTXEKCnakYCaBEQasnzbISxevhr16tREVKWiUkG0Hb9Ev1NYe0Rf0wGZa92BM9h38gJyZIlEo9L5kDEiTKa5I7ay+pHSyQX/HEPXz1bp/zS+Y020re7+PZkoCSJeorkp6p+fu5MAC3HuzJsrvRYtMqJFKqCgn3wS+PprIDISuHwZCFNf5ETxBsyrRw9g0iTfMJcuAZkzi4Z09efcRLk6fXSeBOCEhoyeux1j5+8wTL9vi7Lo26KcYXsnDWU0xMsFSaM5oIYYJUU7ElCTgEhD/vPJUizadRp5s0Vi9eutpIJ4YvLfiNl5EoVzZUHMq3dLtR388yZ8vsz3qObWN9sgS8ZwqfZOGMvoR2r/dp84j7tHRuv/3K9lObzQvKwTIQR1TBEv0dwMqrMcLGgEWIgLGmoOJFpkRItUQASjooAlS4BSpYBduwLqSpXGAfN66y3gf//zhbN7N1BS/ePSA2HPTVQg9NiWBJwn4ISGvPHrZkyN2Ws4+C6NSmBw28qG7Z00lNEQLxckjeaAGmKUFO1IQE0CIg154uOliNl9Gndkz4gVg1pKBdHzq9X4Y9NR5MgcgQ1DWku1fXH6OsxcewgZw8Ow7e02yJAhg1R7J4xl9CO1f/GJSajw+mwkJiWjfc3CGPVYDSdCCOqYIl6iuRlUZzlY0AiwEBc01BxItMiIFqmACBYvDuzfDzRrBixcGFBXqjQOmNeUKb4TU7Vr8WKgcWNVQrPFD26ibMHKTkkgaASc0BAvF6BkNMTLBUmjE5gaYpQU7UhATQIiDXn8oxj8vfcMCubIhGUDW0gFMeD79Zix6iC0GtquofciLMx4MU17/+bhM5dw8WoiWlbKLzWuU8Yy+pGWj81GLMTekxdRs1guzOzVyKkwgjauiJdobgbNUQ4UVAIsxAUVd2gPJlpkRIuUaXoJCb7HLhMTgf/8B/j8c9NdqdQwYF6zZwP33OMLySMnyfrLDzdRKs1e+kIC8gSc0BAvP5IpoyFeLkganYnUEKOkaEcCahIQacgjE5dg5f6zKJIrM5a82lwqiLd/24LJS/bobTYMaYUcHj8JVEY/0gLZZeoKLNx2Qr+DcP3gVq64C1BqQqQyFvESzc1AxmZbdQmwEKdubjznmWiRES1SpoEcOAAUK+Zr/t//AtojmR64Aua1caPvxFTtGjUKePFFD1BJPwRuojydXgYXAgSc0hCvHlIgoyFeLkga/epQQ4ySoh0JqElApCHtJyzGmoPnUDxPZkQPkCvEjZu/A6PmbtcDX/LKXSiSO6uaECzySkY/0hpy6Kwt+GSxr3C5YlBz3JE9dN9TrTEQzU2L0sZuFCPAQpxiCfGyO6JFJtBFPV12MTH/Pnb58cdA9+6ewBwwr5MngXz5fCz69wfef98TXNILgpsoT6eXwYUAAac0ZG/sBTw0MQanL8anSzl31kj98ZoS+bK5JhOyGuLVgqTRhFFDjJKiHQmoSUCkIQ+MX4T1h+JQKl8WLHhJ7sCFz2L2YMivW/TAf38hCpUK5VATgkVeyepH6mFnrDyAAT9s0P/5m+710LD0tf2IRf6p1o2Il2huqhYP/bGGAAtx1nBkLwYIiBYZ0SJlYIi0Tb75BnjiCd9nc+YAreROQjI9rs0NA+aVnAxkyQJcuQJ07AhonDx8cRPl4eQytJAg4JiGAJi35Ri0dwCdSqMYV7dEHgzvUM1VRThtwshqiFcLkka/PNQQo6RoRwJqEhBpyP1jo7HpyHmUvT0r5va/SyqIH1YfRP/v1uttpj9bH/VK5TXcXtOWbJkiUK9kHrSpUtBwOycNZfUjta9r9p9G+4lL9X9+84HK+E+DEk6GY/vYIl6iuWm7gxzAEQIsxDmCPTQHFS0yokXKNLV33wVee83XfOtWoEIF012p1NASXqVL+05MbdIEiPYdJe7Vi5sor2aWcYUKASc0RCs+Dfh+A1bsPXUL5sK5sugbiOYV3fFy7dQBmNEQjccL09Ziw6GzaU67akVyYtzjNV1XlDTyHaKGGKFEGxJQl4BIQ+4Z/Re2HruACvmzYfaLzaQCmbvlGLp/sUpv88l/6hg+dOFyfKJ+gqh2/adBcbz5QBWpcZ0yNqMfKX09dzke1Yb8qf/TU/WL460H3RG3Wd4iXqK5aXZctlObAAtxaufHU96JFhnRImUaRq9ewIcf+pqfPw9kc8+jQ/5itoRXVBSwZAlQpgywY4dpxG5oyE2UG7JEH0kgfQLB1hDtJLv2Hnwk9TphMxridSZmNVc0N/m9JgEScJ6A6HvaauRCbD9xEZUL3oZZfZpKObx890k89vHfepuRj1THw7WLGGp/9Oxl1B82X7ftfXcZ9G9V3lA7p43M6Edqn+u/Mx9Hz11G/VJ58O2zDZwOydbxRbxEc9NW59i5YwRYiHMMfegNLFpkRIuUaWL33w/MmgXkzQvExpruRrWGlvB6/HHfianaI6oXLkA/d92jFwtxHk0swwoZAsHWEK+/E82MhnidCQtxIbOcMNAQJCDSkLvfX4DdsZdQrXB2/NK7iRShrUfO4Z6xi/U2g9tWQpdGJQ21T9nuf/dXQtfGxtoZ6txGIzP6kdqdpz5djsU7YpHvtoxY9d+WNnrrfNciXqK56XwE9MAOAizE2UGVfaZJQLTIiBYp01i1k0G1E0Jr1tSOpTHdjWoNLeHVrx8werQvtFOngNy5VQvTMn9YiLMMJTsiAUcIBFNDQuGUUFkNCQUmLMQ58tXmoCQQFAIiDWk2fAH2nrqEmkVyYOb/RUn5dPD0RTR+b6Hepl/LcniheVlD7ZfujEWnyct12zGP1cCDNQsbaue0kax+pOXvG79uxtSYvfpHa15viTzZMjodlm3ji3iJ5qZtjrFjRwmwEOco/tAaXLTIiBYp07Ry5QLOngUeeAD46SfT3ajW0BJeI0cCL73kC23TJqByZdXCtMwfFuIsQ8mOSMARAsHUkNFzt2PsfOOP6/dtURZ9W5RzhIvZQWU1JBSY+GNJDTE709iOBNQgINKQqHfn48CZy6hTLAe+7yVXiEv5zrNujUviv/dXMhT0rA1H8Pw3vpsEPutyJ5qVv8NQO6eNZPUjLX+/Wb4fA2du1D+a8VwD1C2Zx+mwbBtfxEs0N21zjB07SoCFOEfxh9bgokVGtEiZoqUV4LRCnHa98AIwdqypblRsZAmvb7/1nZiqXR46UTatfHETpeIspk8kYJxAMDUk5V/qjXjYpVEJDG7rrj9kyGpIKDDxl2tqiJFvAm1IQF0CIg1p8M48HDl3BfVK5MT0Ho2lAklKSkbpQb8jORl4tE4RDO9Q3VD7L//eh9d/2qTb/vx8I1Qvem3PYqi1c0ay+pGWpyv3nsIjHy1D8bxZ8Ua7yq4pQpqhLuIlmptmxmQb9QmwEKd+jizzcNWqVfjqq6+wYMEC7NmzB9myZUPlypXx2muvoUWLFjeNk5iYiBEjRmDy5Mk4cOAAihYtim7duuHll19GeHi4KZ9Ei4xokTI1qPZIqvZoqna9/z7Qv7+pblRsZAmvRYuAptdeSDt1KtC5s4qhWuITN1GWYGQnJOAYgWBqSCjc/SWrIaHAhIU4x77eHDgECKi+D6k7dC6Ox11Fw5K58M1zjaQzUm3IHJy7nIA2lQvgo6dqG2o/fv4OjJy7XbddPOAuFM2T1VA7p41k9SMtf68mJOFKQiKyZ450OhzbxxfxEv2+sd1BDuAIARbiHMHuzKAdOnRAdHQ0Hn74YdSqVQvnz5/H1KlTsWnTJkycOBE9e/a84VivXr3w4YcfokuXLmjYsCGWLl2q22r//sEHH5gKQLTIiBYpU4NqhzRohzVo14wZwCOPmOpGxUaW8Nq1y3diqnY1aAC0agW0b/9v8VLFwE36xEKcSXBsRgLXCKi+ibJkTbwWayi8D02WVygw8fdlp4ZwKSSBwAiovg+p89afiL0Qj6jSufFl94bSwX65bC8yZMiAUrdnQ8PS+Qy1T3mn8cYhrVxTlJLVD0MwPGwk4iXaI3sYTUiHxkJcCKU/JiYGderUQaZMmW5EfenSJdSoUQMnTpzA8ePHERERgY0bN6J69ero3bs3xqZ4lLNPnz4YP3481q9fj6pVq0qTEy0yokVKekCtwYcfAr16+Zr+/TdQr56pblRsFDCvnTt9d8DFxNwaXlQUMGXKv0U6FQFI+sRNlCQwmpNAKgKqb6ICXhNTxev1E0LN8PI6ExbiuOyRgH0EVN+H1HxjDk5fSkCzsnnw2TMN7AORoucXp6/DzLWHEBmeAdvfvkcv5LnhMqMfbojLLh9FvER7ZLv8Yr/OEmAhzln+Sozev39/jBo1Cvv379cfQR00aBDeeecd7N69GyVL/nuMtvY4a6lSpTBw4EAMHTpU2nfRIiNapKQH1Bq89hrw7ru+pocPAwULmupGxUYB8dqxA2jYEIiNTT+0fPmAZcs8U4xjIU7FWUyf3ERA9U1UQGtiGolYsuMEOk9diYSk5HTTlDtrJGb2aoQS+bK5KZW6r2Z47Y29gIcmxuD0xXi/8VYrkhPjHq/pSi7pBUYNcd0Up8MuIaDKPuSzRduwccs2NK1TBe3qlAoKvc5TV+CvbSdwe/ZMWDno5tcEBcUBk4OY0Q9/Q8Wev4IskeHIlinCpEdqNxPxEu2R1Y6O3pklwEKcWXIeatexY0d8//33+o9y7b1xrVu31u96O3r06C1R5s+fHzVr1sTs2bOlCYgWGdEiJT2g1qBTJ2DaNCBjRuDSJSAszFQ3KjYKiFeTJsDixeKwtDvjtPfIeeDiJsoDSWQIShJQZRMV0JqYiuye2AtoLyg4RYRl0E+5a1z2diXzInLKLC+tGPfCtLXYcOis3yHcXKRMKzBqiGhG8XMSMEfA0/sQAZIHJizB+oNnUT5/dsx5sYk5gA60MqsfqV1dve8Uen61BsfjrmBCp5q4v1ohB6Kxf0gRL9Ee2X4POYITBFiIc4K6QmNu3bpVfzT1/vvvxw8//KB7pj12mjFjRqxevfoWT7V3y8XHx+uPr/q7jhw5Au3/Ul7aWE8++ST++usv/dHX1FdcXBy0hUgbI3v27JZQuq1NG0QsX47EkiURt8Z3PLhXLrO8wjZuRA6tEGfwOrd4MZKqVDFora6ZP15a4blZs2b6nNfmHy8SIAHjBLy4iQqFRzBFGwN/MyAU+KSOn4U442sCLUnAKAEv7UO2HD2PDYficPZSPLrUL4KMEeI//t//0WocPHMZtYvmwKdPyL/2xyhnq+3M7kFS+3HozGXc95Fvv/lMgyLo3bS41a4q0Z+IF/chSqQp6E6wEBd05OoMePbsWTRo0EAvmGkLQLFixXTnSpcuDe3ON+2AhtSXdnCD9i65ndr7xfxcQ4YMwRtvvJGmxciRI/UxgnG17NYNWWNjcaJqVSx9661gDKn8GOWnTUOF6dMN+/nP449j2+OPG7Z3o+GuXbug3dXDQpwbs0efnSTgpU3UdY7bjl3AY1PXGcY6o2sNlLvDfY+mijYG6QEIFT6p4+cfcwx/JWhIAoYIeG0f8vuBMMw56Cu+vVErAbn+fSV3ujxeWRGOy4kZUC1PEp4pn2SIm5eMkpOBSf+E4Y7MQOXcySifK/1XQXgp7tSxcB/i5eymHxsLcaGZd2iHNGiPoK5cuVJ/zLRp06Y3SHjmjriEBOTMnx8ZkpJwtWNHXJw40VPZNruJyvLaa8j00UeGWVzp0QOXhg0zbK+qITdRqmaGfrmVgNc2Udfz8MeBMMy+tpkykps2RRJxT9HQ2TyQz62zgpsoI98U2pDAvwRU3IdMjdmDQwcPoEn1smhSQf6d0t+sOozh8/boQU7vUgPl8/v/A018YhLuHLFMt3+4Rn683qaMa6aI2T2IawK02FERL94RZzFwl3THQpxLEmWlm1evXkW7du2wYMEC/Pjjj/pjqSkvz7wjbv9+oPi1W5xffx14800rMTrel+nHioYMAdK5WzHNoDT7wYMdjzdQB/hYUaAE2Z4E1N5EiX7oGs3f8Hm78c2qm1+t4K9tpzoFMaBFcF7sbTQGI3ZmeYUKn9QM+cccI7OKNiQgJqDiPiQpKRmlBv6uO9++en6M6lhHHEgqi+PnLuPYuSvIlTUSBXJmRmS4/0dTj8ddRt2h8/VeejUrjQFtKkiP6VQD03sQpxx2eFwRL74jzuEEOTQ8C3EOgXdq2ISEBHTo0AG//vorvv76azyexiOH2qmow4YNc/+pqUuWANphA9r1ySdAt25OYbdlXNGinu6g69cDNWoY90mzr1bNuL2ilizEKZoYuuU6AipuojSIptfEVBkYPXc7xs7fYTgvfVuURd8W5Qzbq2Jolleo8EmdJ2qIKjOXfriZgKr7EO3utLKD/tDRPlKzAEY8Vtt2zDuPx6Hl6EXQHs/8730V0S3KPX/QMasftkNVdAARLxbiFE2czW6xEGczYJW6T0pKQqdOnTB9+nR8/PHH6N69e5ruabfHaiej9u7dG2PHjr1h06dPH4wfPx7r1q1DNROFGdEiI1qkpFl+/TXw5JO+Zn/+CbRsKd2Fyg0C4sVTU29KrWhuqjwP6BsJBJOAqpsoKwtxWw6fw73jDJwqfQ38H32iULFgjmCmwZKxzGpIqPBhIc6SacZOSOAGAZX3Idodcat2HsbKVatwV6N6qFS8QFAyl5iUrB/uEBmeAdkzRwZlTCsGMasfaY2dnJyMf47GYd2BM8iVJRL3VJV/LNiKmOzsQ8SL+xA76avbNwtx6ubGcs/69euH0aNH6++D65bG3WEtW7bUD2nQrh49emDSpEno0qULGjVqhJiYGEydOhXPPfccPpJ4v1jKIESLjGiRkgaivdds4EBfs3/+AcqXl+5C5QYB8dIO22jQAIiNTT/EfPmAZcuAMu55Z4W/fPFuBpVnM31zAwGVN1Eav4DWxFQJCIVTQQPhZZRPtcI58Uvvxm6Y3kIfqSFCRDQgAb8EQm4f4uH5EIh+pMaiFeJqvz0Ppy5cRf1SefDtsw08R07ES7RH9hwQBqQTYCEuhCZCs2bNEB0dnW7ECxcuhGajXdpdD8OHD8fkyZNx8OBBFClSRC/eDRgwABEREaaoiRYZ0SIlPWjPnsD1ouGFC0DWrNJdqNwgYF5aMa5rV2BxGnd+1KwJzJjhmSKcaJMumpsqzwP6RgLBIhAqm6i9sRfwwrS12HDorF+0ubNGYmavRiiRz30nporWRNGc0hi1m7AE5y4n+DXNmSUSPz/vXkYpg2MhTjQr+DkJ+Cfg9X3IlYREvPbjRpy5GI+osvnQpVFJz06JgPcgqch0mboCC7edQLaM4dgwpDXCwzJ4ip2IF/chnkq34WBYiDOMioaBEhAtMqJFSnr8++4Dfv8d0O7sOnFCurnqDR3doE0AACAASURBVCzjtWEDMHOm767Bb7/1hf3888CECaojkPKPmygpXDQmgVsIeH0TpQW8J/YC2k+MwemL8X5nQLUiOTHu8ZquLcIFWojT2muFuA0H/RcrNbu6JfJgRg/33+FADeGiSALuJmD3PkS7s0t7z1xCUjLa1yqMUY9KvI/ZZWgt24Nci3vsvB0YPW+7/l9z+jZB+QLZXUbEv7siXqK56SkYDOYGARbiOBmCRkC0yIgWKWlHq1YFNm0CatUCVq+Wbq56A8t5aW+L1Zht3gzkzg0cOQJkyqQ6BsP+cRNlGBUNSUBJAsHQEKOPXHqhuBSIhoTie+KoIUouC3SKBAwT8KchZy/GY8B3axB74jg6Nq6IDvXNvZalzttzEXv+Ku6ucAemdL7Tr28TFuzAbxuO6KesTu1cF1kyhhuOxWnDQPQjLd+jt5/A01NW6B+993BVPHZnMadDtHR8ES/R7xtLnWFnyhBgIU6ZVHjfEdEiI1qkpAhpRaWcOYG4OODBB313fHnsspTXdTbvvw+8/LLvv7RHUx95xDPUuInyTCoZSIgSsFtDQq24FIiGhOLJqdSQEF14GLZnCPjTkCNnL6HBsAV6rD0aF8Wr91czFXeLUdHYefw8ahbLpb+6wN/Vb8Y6/LjmkP4Y5o6370GYix7HDEQ/0mKiFUJrvPWnfoJsh9pF8P4j1U3xV7WRiJfo942qcdGvwAiwEBcYP7aWICBaZESLlMRQ2lu7fXd1aVefPsCYMVLN3WBsKa/rAR89ChQpAiQmAvfeC8ya5QYUhnzkJsoQJhqRgLIE7NaQUCsuBaIhb/y6GVNj9hqeK10alcDgtpUN26toSA1RMSv0iQSME/CnIQdOXUTU8IV6Z89HFcPL91U13nEKy0c+WoqVe0+jZL5sWPiS773b6V2j5m5H9LbjSAbwy/+561CbQPQjPR5txizST08tmicLFg+42xR/VRuJeIl+36gaF/0KjAALcYHxY2sJAqJFRrRISQwFaO89q37trykjRwL9+kk1d4OxpbxSBty2LfDbb0BYGHDwIFDQG8eIcxPlhllNH0kgfQJ2a0ioFZcC0ZBQK1pqs5IawtWJBNxNwJ+G7Dt5AU1H/KUH+ELT4uh3TxVTwXb/YhXmbjkG7aCa9YNbmerDDY0C0Y/04hvyy2Z8ttT3B56lr96NQrmyuAGFIR9FvES/bwwNQiPXEWAhznUpc6/DokVGtEhJRa4VkrSCknZ99x3QoYNUczcYW8orZcA//PAvr+HD/31U1Q1Q/PjITZTLE0j3Q56A3RoSasWlQDRE9jHeT5+ug+YV87t6DlNDXJ0+Ok8C8Kchu06cR/OR0TqlF+8qgT6tzd3BO+D79Zix6iAyZAB2Dr3Xc6d/Xp9GgehHelPxj41H0PPrNfrHox+rjodqFvHMrBXxEv2+8QwIBnITARbiOCGCRkC0yIgWKSlHJ070nfypXcuXA3XrSjV3g7GlvFIGfOUKUKgQcOoUUKmS78AL7ReFyy9uolyeQLof8gTs1hDZ4tIffaJQsWAO1+YlUA0xerCFBih31kj9fUkl8mXzJC/R3HRt0HScBDxEwN/3dPuxOLQavUiPtv/dJdC7lblC3LDft2LSot16P2teb4k82TJ6iOC/oQSqH2lBOXn+Cmq/PU//6LE6RfFeB3Pv6VMRuIgXNUTFrNnvEwtx9jPmCNcIiBYZ0SIlBfLVV4H33vM10U7/LFBAqrkbjC3llTrg3r2BCRN8/+qRQiYLcW6Y1fSRBNInYLeG7Im9gJajopGQpL2xx/8V6qemanT2xl7AQxNjcPpivAiX/rnbmVFDDKWZRiSgLAF/GpLyDzGvtCiJni0qmYrjw7924b3Z/+ht5/dvitK335ZmP1cTknA87jLy3ZYJmSPdc1rq9WDs2oO0Gh2N7cfOo0TerPjr5btM5UDFRiJeot83KsZEnwInwEJc4AzZg0ECokVGtEgZHMZn1rEj8O23QMaMwKVLvvedeeyylFdqNqtXA3Xq+P61Z09Au8PQ5Rc3US5PIN0PeQJ2a4jRO7wiwjJgXr+mrr67S5tMVmjIvC3H0O2LVYbnppvvIqSGGE4zDUlASQL+NGTTobO4f/wS3e+BrUrh2bsrmoph+sr9eOWHjXrbH3o2QO3iedLsJ+V4bz1YBU/VL25qPKcaWaEfafn+v5834Ytl+/SPlrxyF4rkzupUiJaOK+Il+n1jqTPsTBkCLMQpkwrvOyJaZESLlBShRo2ApUuBMmWAHTukmrrF2FJeqYPWzg/XDrvYuBHIlct3V2HmzG5Bk6af3ES5On10ngT8vt9HwxPImhhqj6UGyuv6dAyl9+pRQ7gIkYC7Cfjbh6w7cAYPfhCjB/h6m9J4plkFU8H+ufkonv1ytd520lO10bpy2k/kLNx2HF2mrtTtPuhUC/dVc9fBaIHorT+w2kEX2oEX2jX0oSp4op67CpTpxSbiJdojm5qMbKQ8ARbilE+RdxwULTKiRcowifXrgagoIC4OKFEC+PlnoJp33jNwnYNlvNIDO2oU0L+/79Pp04FHHzWcAhUNuYlSMSv0iQSME7BTQ0KpoGSlhoTSSbPUEOPfVVqSgIoE/GnI6n2n8PCHy3S3h9xTBp2bljcVQsqCnr873WasOoAB32/Qx5jxXAPULZn2nXOmnAhCI7v2IBeuJKDGm38iPjEZLSvlxyf/ufZ0ThBiCnSIJTtisfHQWfRsVvqWrkS8RL9vAvWN7dUkwEKcmnnxpFeiRUa0SAmh7NwJdO0KLF58q6lWmJsyxXeHnEeugHmJOBw7BhQuDCQmAvfcA/z+u6iF0p9zE6V0eugcCQgJ2KkhoVRQsrIQF0oFTGqI8CtKAxJQmoA/DVmx5xQeneQrxL11X1k8FVXOVCyHz1xCw3cX6G1fuLsM+rVKu6D3wcKdGDFnm2638KVmKOmyg2zs3IN0+uRvLN11EtkyhmPt/1ohY4T6rxfafPgsOny4DJfiE9GrWWkMaHPzHZUiXqLfN6YmIxspT4CFOOVT5B0HRYuMaJHyS0J7/LRhQyA2Nn2zfPmAZcs8U4wLiJfRadWuHfDrr7537B044DtN1aUXN1EuTRzdJoFrBOzUkFAqKFlZiAulR3qpIVyKSMDdBPxpyNJdsej0yXI9wHfalkOnRmVNBRufmISyg/7Q2z5+Z1G8+3DaT+QM+WUzPlu6V7fb9EZr3JYpwtR4TjWycw/y8aJdeOd334EX33Srh4Zl8jkVpuFxR/25DeMX7oT2Zp/X7qmA55refFeciJfo941hR2joKgIsxLkqXe52VrTIiBYpv9E3aZL2nXCpG2l3xi3yHU/u9isgXkaD//FH4OGHfdbvvgu88orRlsrZcROlXEroEAlIEbBTQ0Lp0IHr0K3SkFA55IIaIvV1pTEJKEfAn4Ys3nECT326Qvf5vQfK4bEG5gpxWvvab83FyQtXcVf52zG1S900OTz/zRrM2nAEWSLDseXN1siQIYNyvPw5ZJV+pDXG9mNxaD1mkX7Sdv9W5V3z2O7xc5exYu8p3F/t1psWRLxEv29cNTnorGECLMQZRkXDQAmIFhnRIpXu+No74WrUMO6eZu+Bd8aZ5mWcFHD1qu8uuJMngQoVgC1bAJf9WDCy6RTNTRlktCUBErCHgOh7anZN3BN7Ae0nxuD0xXhDjmubgxk9GhiyVdnILK/UMe2NvYAWo6KRkJQsDNfN7FiIE6aXBiSgNAF/GpLy8IT3HyyPDvXNv8qmzZhF+OdoHCoXyoFZL0SlyUR7DFZ7HLZYnqxYNOAupbml5ZxV+pFW38nJyYg9fxW3Z8/kOi6aw6v2nsKXf++Dpo0jH62OMndkFx4mJfp940oQdFpIgIU4ISIaWEVAtMiYXtSHDAHeeMO4m5r94MHG7RW1NM1LNp4+fYBx43yt/v4bqFdPtgcl7LmJUiINdIIETBOwS0OM3tGlOZ47ayRm9mqEEi57n4+dG6lQeTyVGmL6q8uGJKAEAX8aMn/rMTzzue+0ztHtK+Chure+cN9oEP+ZsgJr959GxYI59IMY0rrufv8v7I69gNrFc+OHng2Ndq2MXdD2IMpEbNyR2ZuOosdXvpNzP3qyNtpUKcBCnHF8IWXJQlxIpdvZYO3aRKFvX2DsWOPBaYWlMWOM2ytqGTQRXLsWqFXLR6FHD+DDDxUl4t8tbqJcmTY6TQI3CNihIbJFpE+froPmFfN7IitWaUiovF+PGuKJac8gQpiAPw2Zs/konvvSVzwZ16Ei2tUpZZpUQmISIsL9HzBQdfAcxF1JQJvKBfDRU7VNj+VUQ6v0wyn/rRo3MSkZO47HoXz+7DceL9521PdorXa90qaCfoqqiJfo941V/rIftQiwEKdWPjztjWiRES1S6cLhHXHIlSuXfXNHe/Oo9ujvhg1AzpzA0aNA5sz2jWdTz9xE2QSW3ZJAkAjYoSGhUkRKK0WmNTdVZ7Inzj5cqzBGPirxOokgzS/RMNQQESF+TgJqE/CnIb9vPIJeX6/RA/jg0Uq4r1ZJ24K5dDURFf83W+//qfrF8daDVWwby66OrdIPf/5pj6huPnwOi3acQM+mpZV8j971P+YVz5sVbz5QBU3L3Y7L8Ymo8Lovv4/VKYr3OlRjIc6uiejyflmIc3kC3eS+HZsoPX6+I87eQpzGePRooF8/33SbNg14/HE3TT3dV26iXJcyOkwCNxGwQ0Nki0hdGpXA4LaVPZEZqzZSssXMzJFhmN2niese76WGeGLaM4gQJuBPQ7Siz6nTZ/BX9CI0a9oEefPkto3UvpMX0HTEX3r//VqWwwvNzR8MYZuTgo6t0g9/w4ybvwOj5m7XTX7s1RC1itmXE7Mcv1y2F6//vFlvnvKE10bvLsChM5f0gya0x5NFvES/b8z6x3ZqE2AhTu38eMo70SIjWqT8wtAendQeoRRdPDVVRCjtz48fBwoXBhISgNatgdm+v/S46eImyk3Zoq8kcCsBOzREtojUt0VZ9G1RzhPpCUhzUxCQfbxXa+rGQxuoIZ6Y9gwihAnYoSH+cGrFPe3RxdSPqcbsjMUTk5frTUc+Uh0P1y7iuqxYpR/+At98+CzuG7dEN3n+rtJ4uXUF5Tj1+XYtfl53GOFhGbBhcCtkyxSh+/jE5L8Rs/OkfuDEykEtWIhTLnNqOMRCnBp5CAkvbBPAxETfo5ObNvnnmC8fsGwZUMb8SUgqJSoYInhTvA8+CPz8MxAWBuzf7yvMuejiJspFyaKrJJAGATs0ZO6WY+j+he8F3UauP/pE6S/g9sJlpYbIHHhxnZ3bWFJDvDDrGUMoE7BDQ9Liqb0jrOtnK3Ei7gqGtKuMTvWK3WT27Yr9ePXHjfq/aXdLaXdNue2yUj/8xT5m3nY0KXc7ahbNpeSjqY3fW4CDpy+hSuEc+K33vyfkDpq5EV8v36+HtumN1ki4dB7R0dFo2rRpmk8xieam2+YH/TVGgIU4Y5xoZQEB0SJjelHXDmrQDmzQrttvB06cuNVb7U64KVM8U4TTAjTNy2wuf/oJeOghX+thw4BXXzXbkyPtuIlyBDsHJQHLCNihITIFJDfexeUPvpUasjf2AtqMWYTLCUmG8+22uwupIYZTS0MSUJKAHRqSVqAHTl1E1PCF+kdprXMj5vyDDxbu0j9f9trdKJgzi5K8gqUfrgv+msPHzl1GvXfm6//1dIPieOOBf9/1N3nxbrw9a6v+2W+9G6NItmQW4tyaaBv9ZiHORrjs+mYCtgigdmdWpUrAhQtA7tzA1q3AsWPAzJnA6dO+f9OKR9WqeS4dVm6iDMG5etV3F1xsLFC+vI91hgyGmqpgxE2UClmgDyRgnoDVGiL7SKWXTkzVsmC1hvSfsQ4/rDlkOMFue98eNcRwamlIAkoS8Kchv204jLFzt+HSxQsY27EWapcpZDqGKwmJeHrKCuTPkVk/FfWeqgVv6uuFaWvxy/rDyBgehn/eaoOwMPf8lr4eiNX6YRq2gw1THvAxrmNNtKv+75yZv/UYnvncd7f9+I41EVU8KwtxDuZK1aFZiFM1Mx70y+pNFLTTPNu2BWbN8tH69FOga1cPkks7JEdEULvzULsDUbu0x3zr13cNb26iXJMqOkoCaRKwWkNC+f1wdhTiZHl2blgcQ9q557RAaggXJhJwNwF/GpLypfvfdq6O+hXse2/bQxNjsHb/GZTMlw0LX2rmSqhO7EEOnr6oP55aOJcadxC+9dsWfLpkj56/mFfvvsmv3SfO4+6R0fpn/VuWw1O1b2chzpUz3V6nWYizly97T0HA6k0UvvsOePRR3wjNmgELFrjqDq1AJ4cTIoh164CaNX2uP/ssMGlSoGEErT03UUFDzYFIwBYCVmuI1+/gEiXBag2RvcOwSqEc+O2Ff9+pI/LX6c+pIU5ngOOTQGAE/GnIrA1H8OHC7Th7Lg4TnqiN6qVuvostsJFvbv3T2kPYdiwOt2WKwPN3ufO91Vbrhz++F64k4MXp6zBv6zE8dmdRDGuvxlNOHT5cilX7TuOO7JmwYlCLm0KIT0xChddn64d1PFyrCF5vVZyFOCu/RB7pi4U4jyTSDWFYuonSHjutWNH3GGqmTMCGDUA5b5xkZzSXwRTBm3zSDsZYvx7IkQM4ehTIosZfpkTcuIkSEeLnJKA2ASs1ZE/sBdzj8XeaibJph4bcP24xNh0+Jxr6xuduOrCBGmI4rTQkASUJWKkhSgYYRKfs0I/03NdOn71//BJsPnwOmSPDsOzV5sidLWMQo711qITEJFQd8icuxSeiRcX8mPx0nVuM6rw9D7Hnr+Cu8rdj9EPlWIhzNGNqDs5CnJp58aRXlgrgc88BH3/s4/TWW8B//+tJZv6CCqYI3uRHysMxvvkG6NjRFey5iXJFmugkCaRLwEoNkTmk4bpDbioaGZlGdmjI4J834fNl+4wMr9u46fFUaojhtNKQBJQkYKWGiALU7ojad/IitEcU65fOixyZI0VNXPW5HfrhD8B3qw7g5e836CZ9mpfFiy2dvflCOxm39ZhFuj/ao6e9m5e9xf2Wo6Kx4/h5VC+aC58/UZmFOFfN8OA4y0JccDhzFACWCeDixUCTJj6m2kENa9cCGZ39y4gTCQ62CN6IUTuVtlAhICEBaNUKmDPHifClx+QmShoZG5CAUgSs0hDZRyg1CF47MVWLyQ4NeePXzZgas9fwvMkUEYY5fZugRL5shts4ZUgNcYo8xyUBawhYpSFGvJm+cj9e+WGjbjqte300KJ3XSDPX2NihH/6Cv5qQhCbDF+LoucvImSUSS1+9G9kyRTjGa8aqAxhwrTD4WZc70az8Hbf48uikZVix5xSK582Kn7vXZCHOsWypOzALcermxnOeWSKAV64A2qOR//zj4xMTAzRs6DlWRgIKtgje5JN2Eu1PP/neyaedXFvEvpfaGmFhxIabKCOUaEMC6hKwREMAyB4qoD0KM7uPO4pFMtmzQ0Nk2Wr+uqXISQ2RmV20JQH1CPjTkMvxiTh56jSWxsSgxV1NkDt37oACWLX3FDp8tEzv4+0Hq+DJ+sX1/7163yn8czQORXNnRd2SeZA5MjygcZxqbId+iGKZvHg33p61VTf7730V0S2qlKiJbZ+//tMmfPm37+7v1f9tgby3ZbplrOe+XIU5m48hR+YILOpbj4U427Lh3o5ZiHNv7lznuSWbqDfeAIYM8cXesycwcaLrOFjlsBMieMP3n38GHnzQ959DhwIDB1oVlm39cBNlG1p2TAJBIWCJhgCQvWvr4VqFMfLRGkGJMZiD2KEhZu421GL+9Ok6aF4xfzDDlx6LGiKNjA1IQCkC/jRk1NztGDd/h+7vnOfroHzRwNajUxeuotZbc/X+ujYqif+1raT/75Qnba55vSXyOPyuM7MJskM/RL5ohzY0em8BzlyMR77bMmHxgLuQJaMzhcwHPojB+gNn9JNStRNT07pe/WEDvl15QP9o1YCGiFm8CE2bNkWuXLluMRf9vhGx4efuJMBCnDvz5kqvRYuMcFHfutV3N9zVq75HI7dsAXLmdCULK5wW8rJikPT6iI8HChcGtMdUy5YFtm1T/sRabqLsnBDsmwTsJxCwhlxzUfY9Zn1blEXfFs6+j8YOunZpiJn377nhrkNqiB2zkH2SQPAI+NOQ9+dsw4SFO3Vn5ve+E6UL3/qooaynNd/8E6cvxqNpudvxede6evNun6/EvK3H9RNTNw5phQzakyUuvOzSDxGKDxbuxIg523SzQfdWRPcmwb8rTntMtsqQOdD+/71VC2DiE7XTdHvMvO34btVB5M4WiQ8fqYg1y2NYiBMlOMQ+ZyEuxBLuZLgBbaKSkoBmzQDt/XDa9eOPgPZ4ZAhfTongDeQvvgiMGeP7Txc8IsxNVAh/WRi6JwgEpCEpCHj5ZE+ZRNulIXtjL+gvsb6SkCTjjvKPqFJDpNJJYxJQjoA/DXn3j3/wUfQu3ee/+tRFiYK3B+z/wx8uxep9p1E0TxYsHuC7a0p7BHbz4bM4fOYy2lYvFPAYTnVgl36I4jl/JUF/V5x2x6F2N6F2V1yw3xW36dBZ/RRX7RrQpjx6NSsjclv4TlbR7xvhADRwJQEW4lyZNnc6LVpk/C7qn3wCPPusL3DtkciZM90JwUKvnRLBGyFs2ABUr+77z+7d/z3F1sIYreyKmygrabIvEgg+gYA05Jq787YcQ7cvVhl2vkqhHPjthSjD9m4ytFNDZO86vM5N5ZNpqSFumt30lQRuJeBPQ4bO2oJPFu/RGy3uWw9FC+QLGOGA79djxqqD+uuUt77ZxrXvg0sLhJ36IQI/KXoXhv3he1d4eieWivoI5PNpK/bjtR99B3F83a0eGpURzxURL9Hvm0D8ZVt1CbAQp25uPOeZaJFJd5E6cgSoWBE4exbInt33SKoLDgewO4GiRd3u8fX+a9XynVqbIweg5Slr1qAMa2YQbqLMUGMbElCHgGkNuRbCntgLuGfMIlyWuFOrc8PiGNKuijoQLPTETg0x+644lXlTQyycfOyKBBwg4E9DUr47dGm/+ih0R+CnnGp32Gl32mnX7L5RqFAghwNR2zOknfoh8vjS1UQ0HbEQx+OuIHumCEQPuCuo79rT7sbT7nTcePAMnokqpZ/iKrpEvES/b0T983N3EmAhzp15c6XXokUm3UXqsceAGTN8MU+YADz/vCvjt9pp0aJu9Xhp9jduHNCnj++jr74CnngiKMOaGYSbKDPU2IYE1CFgWkOuhWDm3WVdGpXA4LaV1YFgoSd2a4gZ3pHhGTD3xaYokS+bhZFa0xU1xBqO7IUEnCLgT0NS3sW7/KUGyJ8vT8Buzt1yDN2v3YE9/OFqePTOogH3qUoHduuHKM6vl+/DoJmbdLNujUviv/f7DsNQ8bqSkIjTp89g+dIlfEecigly0CcW4hyEH2pDm9pE/fYb0LatD1X9+sCSJUC4MyfkqJYvp0VQ5xEb6zs4Qzu8oUULYK7vhCgVL26iVMwKfSIB4wRMaci17mUfSb3ulVcPatDis1tDtHfFtZG8A1HzK0fmCPzyf42VK8ZRQ4x/V2lJAioS8Kchg2ZuxNfL9+tuaydc5suTO+AQzl6Mx51D5+FqYhIalcmL+IRkZIwIQ8tK+fF0wxIB9+9kB3brhyi2+MQktBwVjb0nLyJjeBgWvNQURXKr9VTOvpMXcM/Yxbh4NRF9mhVHqSu7WIgTJTbEPmchLsQS7mS40puo8+eBSpWAAweAiAhgzRqgalUnQ1BqbKdF8AaM9u197+zTXoKxdy9QrJhSnK47w02UkmmhUyRgmIC0hlzr2cwjqdedUvmdZYbBpWMYDA0xWwCtVjgnfundONAQLW1PDbEUJzsjgaAT8Kchr/6wAd+uPKD7tPaVhsidO/BCnNZXz69W449NR2+KtX3Nwhj1WI2gx2/lgMHQD5G/szYcwfPfrNHNVGSqPcJa6y3fDQpP1yuMWmH7WIgTJTXEPmchLsQS7mS40puolKdyDhwIDB3qpPvKja2CCOpQfvkFeOABH5+33wYGDVKOleYQN1FKpoVOkYBhAtIacq1nM49Iak3rlsiDGT0aGPbPbYbB0pB6Q+fhWNwVaTyfPl0HzSvml25nVwNqiF1k2S8JBIeAPw15+bv1+G71QYQhGWtebYxcuXJZ4lTKx1Ovd/hu+6p4vK6af7Q2GnSw9MOfP8nJyXjwgxisP3hWvxdgVu8oVCpk73v4fll/GNofmKoVyak/apwjc/rvh0tMSsYL09Yid7ZI1CqUFeFHNrEQZ3SChYgdC3EhkmgVwpTaRO3Y4XsUNSkJKFMG0E7ozJJFhTCU8UEFEdRhaI+laodnHD/uy9X27b674xS7uIlSLCF0hwQkCUhpyLVNlNlDAzJHhmF2nybKPR4picyvebA0xOwJqhFhwLx+zZTJATXEytnHvkgg+AT8aUi/6evw49pDCM+QjNWvWFeIu5qQhHrvzMPpi/F6wHVL5sEXXeu6/gTVYOmHaJYs23USHT/5G7myRuK9h6uhdeUCoiYBff7Sd+vx/WrfSbgbBrdCdj+FuJQDiXiJft8E5DQbK0uAhThlU+M9x0SLzI1FqmFD5GrZEli/3gdh/nzg7ru9ByTAiESLeoDdyzXv3x8YNcrXpksX3ymq2kZYe2y1WjW5vmyy5ibKJrDslgSCRMCwhjRtqt/NoL2j7KGJMTc2QDJuqnY3lozvRm2DpSFmi6FaHOEZgM+71kXjsrcbDcs2O2qIbWjZMQkEhYA/DdHuXNLudsoYlowVA6wrxGmBTYrehWF//IPmFe7AhE61kCWj+991HSz9MDIxZqw6oBfgjJxeaqQ/fza9p63FHxuPoHjerJjfv5nh7kS8RL9vDA9EQ1cRYCHOVelyt7N+F5n163F52jQc2rwZxeLiEBkd7Qu2c2dg6lR3B26T96JF3aZh0+425aEaqS2iooApU3x3yzl4cRPlIHwOTQIWEPCnIVqx9wnVEgAAIABJREFUZ8qi7Vi54ygismTFxfgkHDkr/zik5qbXH0m9nopgaojZx4M1X7VinLbhcfokVWqIBV9idkECDhLwpyHPf70GszYeQebwZPz9srWFOC3ks5fig1IoChbeYOpHsGIyOs7l+EQcPXtZSpNEvFiIM0rfW3YsxHkrn0pHk+Yis3Mn0LUrsHjxrb5rBzQsXQrceafScTnlnGhRD5pf2mPEDRv6TlBN78qXD1i2zNFiHDdRQZsRHIgEbCGQloZod71pdzJsOHTWkjFD4ZFUJwpxWp7aTliCuMsJpvKUOSIMs/s6+6gwNcRU6tiIBJQh4K/Y0ePL1Zi9+SiyRiRj6UvWF+KUgWCRI8rsQSyKx65uDp+5hENnLuHoyTNIOriR74izC7RL+2UhzqWJc6PbtwigSwo4qrJWRgSbNEm7kJoanHZn3KJFjuHkJsox9ByYBCwhkFpDtNNQH5iwBOdMFnfScioUHkl1ohCnjakV41qNjsbVxGRT80F78+jQh6qgU73iptoH2ogaEihBticBZwn4K8R1+3wV5m09htsik7GkPwtxokwpswdJ4ah2OMLP6w7h53WHoWl5RHiYKAzbP+8/Yz1+WHNQv7P7/XoJuKuZ79UZqS/eEWd7KpQcgIU4JdNin1Pnz5/H+++/j9WrV2PVqlU4evQonn76aXz22We3DJqYmIgRI0Zg8uTJOHDgAIoWLYpu3brh5ZdfRni4/PsNbllkXFLAsS8bgfWshAhq7/GrIXEEu2bv0DvjuIkKbL6xNQloBFTSkEAed0wrm/lzZMLygS1CJtFOaIh22ly3L1YFxLjsHbfhk//UkXosKKABrzWmhlhBkX2EOgGVNCRlLrpMXYGF204gR2QyFrEQJ5ymTuiHyKkPFu7EiDnbdLP3Hq6Kx+609mTaI2cvIX/2zAgLM34g3dBZW/DJ4j26T8PuTMA9zVmIE+UxlD5nIS6Usq39RXrvXpQsWRIFCxZE7dq18dtvv6VbiOvVqxc+/PBDdOnSBQ0bNsTSpUsxdepUaP/+wQcfSJO7qRCnFfJcUsCRDjRIDZQQwSFDgDfeMB6xZj94sHF7Cy25ibIQJrsKWQKqaEjmAmVw77g0XmkQQGY6NyyOIe2qBNCDu5o6pSHtJizBhoOBPUocEZYBn3W5M6iHOFBD3DW/6a2aBFTRkFq1at0E6KlPl2PxjljkypiMv/rxjjjR7HFKP/z5FXv+CpoMX4ik5GT0b1ke3ZuUEoVh+PPk5GTUfGsutLvuOtUrhtfuqWiobcri4KAaCXikDQtxhsCFiBELcSGS6OthXrlyBbGxsShcuDASEhIQGRmZZiFu48aNqF69Onr37o2xY8feoNSnTx+MHz8e69evR9WqVaXo3VSI++UX1xRwpIIMorESIti3L5BifgjD79MHGDNGaGaHATdRdlBln6FGQBUNiT55G8bO32Ep/j/6RKFiwRyW9qlyZ05pSKDvi7vONNiHOFBDVJ7N9M0tBFTRkNSFuMmLd2Pj/pM4G3sUY56OSvPxQbcwDoafTumHKLYF/xxDlUI5cUeOzCJTqc93nziPu0f6DhLs1aw0BrSpYKj9l3/vw+s/bdJtX6qagCfvYyHOELgQMWIhLkQSnVaY/gpxgwYNwjvvvIPdu3frd9Bdv/bs2YNSpUph4MCBGDp0qBS9mwpxX3zhmgKOVJBBNFZCBHlHXBAzzqFIQC0CTmrIr4cyYWrMXsuAhMpJqSmBOakhWjHu3rGLcTE+MaAcBvMQBxbiAkoVG5PALQSc1JDUhTjNOSfXRLdNj1Bj9e2K/Xj1x416mib/pw5aVMpvKGU/rjmIfjPW67a9KyXgmXYsxBkCFyJGLMSFSKJlC3GtW7fW73rT3iGX+sqfPz9q1qyJ2bNnS9HjHXFSuITGSoig7DviZs0C7r1XGJsdBtxE2UGVfYYyAX+bKLs1xMo74nJnjcTMXo2C/s4xp+eO0xqiFeOaj/wLJs9uuIEvWIc4UEOcnrEc32sEnNQQFuICm01O60dg3su37vvtWvy07jC018Ot/V8r5MwSaaiT2ZuOosdXq3XbZyskoteDTXhYgyFyoWHEQlxo5DnNKP0JoPbYacaMGfVDHVJfmnjFx8dDe3w1vevIkSPQ/i/ltXXrVjz55JP466+/UDMsDDm0wxoMXucWL0ZSldB5d48RLHFxcdCKm1o+smfPbqSJLTa33XsvIpYtM9R3co4cuDhhAuLbtjVkb6WRP15a0blZs2b6fE/rx5mVfrAvEvAKASc1RHtH3GNT1wWMslKB2/DuA+VQLHeWgPtyWwcqaMjfe0+j1/QtSDJ3kOpNyEvlzYIxHSralktqiNtmOP1VnYCTGqK9fif1pcKaqHrOrvunOivtnW6Ld53GN6uOYORD5ZEtU4RptFpfrSeuwvG4q6hUIBu+6Wz8kLqle3wap12dyybimVY109yzcR9iOj2ubshCnKvTF5jz/gSwdOnS0O580w5oSH1pBzccP34cO3fuTNeBIUOG4I10XuI/cuRIaP03GjgQ+bb4Fid/V2ylSoh55x2RGT93iEC2I0cQ9coryHTuXLoeJEZEIDwh4cbnu++9F5u7dEFSpLG/KNkd2q5du9C/f38W4uwGzf49RcBpDRm3KRy74oyfXpYSfgYk45GSiWhUwFMpcWUwJy4B764PR0KyuVzeHHQyHnUgr9QQV049Ou0wAac1xOHwObyNBFaeyICvdobrI9xXNBGtipj/a8/xS8DQdb5C3t0Fk/BAiSTDnu+JA8Zs8rXtWDoR9e9I2w9qiGGknjJkIc5T6ZQLxum/RIXt3o3bWrVC2MmT6TqelDcvzv/5J5JKWXfyjRwlda1V+muUlsus//d/ad4Zl9CgAS6OH4/IOXOQecgQZIiP16Em1KiBi1OmICnFOwjtpM27Geyky75DkYDTGrL/9CU88dl6xF2Re8+Y3XdOuWUuqKQhWi4f+nhNwI+pXmefL1skXr+nNJqWyWtZOqghlqFkRyTg+x3o59A4u5/M4R1xgU1ClfQjrUguxyei7aTVOHE+HtkzhWNWzzrIkdncXXE/rDuKt2bv0ocZ16EimpTJYxje9uMX8OgU39377Usk4sX7eEecYXghYMhCXAgkOb0QlXg3g3ZXXdeuwOLFt7oZFQVMmQKUKRPCWUo/dCXfz7BhAzBzJnD6NJA7N/DQQ0C1av8GsWIF8NhjwN5rL1nXHqmdPBl49FHbc8z3+9iOmAOEGAEVNER7z9gL09Ziw6GzQvr5c2TCOw9VRfOKxl6yLOzQ5QaqaciSHSfQeepKJFjxnOq13JS94zZ88p86lrz/jxri8glP95UjoIKGpISi2pqoXMJSOOQGVp8v3YvBv2zWvX6heVn0a1nOFFLtN8Yv633vh1s/uBWyZzb+NM/+kxfRZMRCfVztzryhT/AdcaaS4NFGLMR5NLFGwvIngNqpqMOGDbPv1NRatW52ccMGXJo2DYc3bUKhKlWQpWPHmws4RgIKMRs3iGCaKTlzxld81Qp2168ePYDRo4HM1h43bvQH1k0HiaSemyE2rxguCRgloJKGbD1yDlMWbceKHUcQmSUbMmQIR1hYBmSJDEeVQjnwRP3iqFgwh9HQQsJORQ3RCqvdv1iFHcfPW5YDqw5zYCHOspSwIxLQCaikIZo/Kq6Jqk4VN7C6kpCIu0b8hcNnLyNbxnAsfuVu5MmWUQppQmIS6gydhzMX41G9aC78/HwjqfYn4q7gzqHz9DYtCydhxFNRPKxBiqC3jVmI83Z+/UbnTwC1l0ZqJ6P27t0bY8eOvdFPnz59MH78eKxbtw7VUt7pZICjqNjhhkXdQJhBM3E1r+RkYMIE4KWXgKtXfcy0F+fOmAGUu/YXK+1EVq1YpxXucuUC2rcPqDjLTVTQpiYHChEC1BB3J1plDflm+T4MmrkJ5t/qc2tuAr07jhri7vlO79UjQA1RLydGPVJZP1LGMG3Ffrz2o+9wwe5RJTHovkpGQ9Tt/t59Eo9//Lf+v19qVQ7/d3dZqfYXryag0v/m6G2aFEjCuM4sxEkB9LgxC3EeT3Ba4U2YMEH/q09SUhIGDx6sF9zaa0UOAO3atbtRYOvRowcmTZqELl26oFGjRoiJicHUqVPx3HPP4aOPPpImx0KcNDK/Ddwign6D0E7l1R5L3b3bZ3bbbYB2yMdPP1n+uDI3UdbOP/YWugSoId7Iveoaot0d12bMIlxOMP5ibFFmArk7jhoiosvPScAYAWqIMU4qW6muH9fZxScmoeWoaOw9eREZI8IQ/XIzFMxp/JT0t37bgk+X7NG7m9O3CcoXyC6VlqSkZJQe9Du0+w/q3Z6ESc+wECcF0OPGLMR5PMFphVeiRAns27cvzci1Qlvnzp31z7S/VA0fPhyTJ0/GwYMHUaRIEXTr1g0DBgxARIT8Cy9ZiLN2srlFBIVRnz0LdO8OfPed0FQ3yJcPWLZM+t2B3EQZw0srEhARoIaICLnjczdoiFaMaz7yL8sOcbieGTN3x1FD3DGv6aX6BKgh6udI5KEb9ON6DNr73bT3vGnXI7WLYMQj1UXh6Z8nJyej6Yi/sP/URRTLk1Uv4mXIIH+6d+X/zcaFq4momTcJU7uzEGcIfogYsRAXIolWIUwW4qzNgptEUBi59qeiSZOAXr005ROaQzvIY9EisV0KC26ipHDRmASUI0ANsTYlbtEQOw5x0EhGhGXAZ13uROOytxsCSw0xhIlGJKAsAWqIdalxi35oEWt3pbWdsASbD5+DVkeb1TsKlQqJ3xn7z9FzaDPGd5jgM41L4vX75R5rvU67ztvzEHv+CirlSsI3PViIs24Wur8nFuLcn0PXREABtDZVbhJBQ5Fr74SrUcOQqW6k2Uu8p5CbKONoaUkCKhKghlibFTdpiB2HOGg0wzMA8/s3M3SqKjXE2vnH3kgg2ASoIdYRd5N+aFEv3RmLTpOX6wAalcmLr56pJ7y77Y1fN2NqzF69zYznGqBuyTymADYdsRD7Tl5EmRzJ+L5XYx7WYIqiNxuxEOfNvCoZFQXQ2rS4TQSF0Q8Z4ns/nNFLsx882Ki139OwRHPT8CA0JAESsI2A6HvquTXRNpK+jt3ISzvE4b8/bUKSgRunjeLLHBGG2X2bCItxLMQZJUo7ElCTADXEury4UT+e+Wwl5v9zXIcwvmNNtK1eKF0g2iEL9d6Zj7jLCSh9ezbM69dUWLhLr7MfVh/E6bjziN27HT0ebMJCnHXT0PU9sRDn+hS6JwAKoLW5cqMI+iXQty+Q4oReIa0+fYAxY4Rm1w24iTKMioYkoCQBaoi1aXGrhthxd5yRQxyoIdbOP/ZGAsEmQA2xjrgb9WNP7AW0HrMIVxOSkO+2TJjfvylyZolME8qWw+fQ7fOVOHz2Mv53fyV0bVwyIHgiXqK5GdDgbKwsARbilE2N9xwTLTKiRcp7RAKLyHO8eEdcYBOCrUnA4wSoIdYm2O0aMn/rMQz8cQOOxV21DEy1Ijkx7vGaad4dx0KcZZjZEQk4QoAaYh12t+rH+Pk7MHLudh3EAzUKYcxjNdK90y0hMQkL/jmOeiXzImfWtAt2RomKeInmptFxaOcuAizEuStfrvZWtMiIFilXB2+D857jxXfE2TBL2CUJeIcANcTaXHpFQ6x+XDV31kjM7NXolmIcC3HWzj/2RgLBJkANsY64W/XjSkIi2o2PwbZjcTqMtx+sgifrF7cOTDo9iXiJ5qbtDnIARwiwEOcI9tAcVLTIiBap0KSWftSe5NWkCbDYd0KR30s7pEEr3Elc3ERJwKIpCShIgBpibVK8pCFWP65arXBO/NK78U3AqSHWzj/2RgLBJkANsY64m/Vj5/E4tJsQg4tXEzHw3gp4tknpG2B2nTiPormzImNEmGWwlu8+iVW7jmHrjp14uxPfEWcZWA90xEKcB5LolhAogNZmys0imC6JnTuBBg2A2Fj/sLJmBebPB+rXNwyVmyjDqGhIAkoSoIZYmxYvaoiVd8d9+nQdNK+Y/wZ0aoi184+9kUCwCVBDrCPudv34Zf1hbD1yDq+0qXADyrcr9uPN37bgvqoFMbxDNdOHM6Sm/PpPm/Dl3/v0f175cgPcnvfW01dFc9O6zLEnlQiwEKdSNjzui2iRcfuiHuz0eZaXVozr2jXtO+OKFwf2+cQMOXMCCxYAtWoZQs9NlCFMNCIBZQlQQ6xNjVc1xKq747QbIub1a3bjEVVqiLXzj72RQLAJUEOsI+5F/Xjrty34dMkeHdLUznfirgp3WAJs2B9bMSl6t95XdJ+6KF7w9lv6Fc1NSxxhJ8oRYCFOuZR41yHRIuPFRd3ObHqe14YNwMyZwOnTQO7cwEMPAVWrAoMGAcOG+dDmzQv89RdQpYoQNTdRQkQ0IAGlCVBDrE2P1zVEuztu0MxNSA4AW3gG4POuddG47O2ghgQAkk1JQAEC1BDrkuBF/Zi+cj/e/HULXmxZDs80LmnZHXFHzl7CwWOnsGHtKjzYsgny5snNQpx1U9HVPbEQ5+r0uct5CqC1+fKiCBoilJwMvPgiMHaszzx/fmDRIqBcOb/NuYkyRJdGJKAsAWqItakJBQ3R7o5rM2YRLickmYanFePm92+GXBHxiI6ORtOmTZErV66b+hPNTdODsyEJkIBlBETf01BYE62C6UVW2kEO4RkyICLcuvfDXect4iWam1bljf2oRYCFOLXy4WlvRIuMaJHyNBwTwYU0L60Y17MnMGmSj1zhwr5HWUuWTJckC3EmJhmbkIBCBKgh1iYjVDREK8Y1H/kXEgO4NS5rxnB826U69mxYwUKctdOQvZFA0AhQQ6xDHSr6YRUxES/R3LTKD/ajFgEW4tTKh6e9ES0yokXK03BMBBfyvJKSgC5dgC++8NErUcJ3Z1zRomnSZCHOxCRjExJQiAA1xNpkhJKGLNlxAp2nrkRCkvlqXPZM4ehT8Qo6tOEdcdbORPZGAsEhQA2xjnMo6YcV1ES8RHPTCh/Yh3oEWIhTLyee9Ui0yIgWKc+CMRkYeQFISACeeAKYMcNHsWxZXzGuQIFbqLIQZ3KisRkJKEKAGmJtIkJNQ7Q74/7z6XLsP33JNMhi2ZLxS+/GfDTVNEE2JAHnCFBDrGMfavoRCLkth89h3NytOHD0OF6+rzqaVSl2S3eiuRnI+GyrLgEW4tTNjec8Ey0yXNTlUk5e13jFxwMdOgC//OL7h8qVfQc45Mt3E1AW4uTmF61JQDUC1BBrMxKqGtJyVDR2HD9vGua4DhXRrk6pm9qL5qbpwdiQBEjAMgKi72morolmAJOVcWoxO2PxxOTleoNh7cqhY8OyLMQZx+dpSxbiPJ1etYKjAFqbD4pgCp5XrgDt2gF//un7xxo1gAULfKetXrtYiLN2/rE3Egg2AWqItcRDVUO0O+PaTliCuMsJpoBmDM+AP19sihL5st1oL5qbpgZiIxIgAUsJiL6nobommoFMVsaprd1/Gg9NXKo3eL1NaTzTrAILccbxedqShThPp1et4CiA1uaDIpiK58WLwH33+e6G06569YC5c4Hs2YH163F52jQc2rwZhStXRuZOnYBq1biJsnZKsjcSsJUANcRavKGsIVox7t6xi3ExPtEU1GwZwzHrhagbxTjR3DQ1CBuRAAlYSkD0PQ3lNVEWNFkZJ7b9WBxajV6kN+h/dwn0blWZhTjj+DxtyUKcp9OrVnAUQGvzQRFMg2dcHNC6NbBsme/DOnWATJmAmJhbjaOigClTgDJlIJqb1maOvZEACZghIPqeck2UoxrqvAI9TTV7pgj82ruxXowTzU25zNCaBEjADgKi72mor4kyzMnKOK2Dpy+i8XsL9QbPRxXDy/dVZSHOOD5PW7IQ5+n0qhUcBdDafFAE0+F55gzQvDmwZo0YuPYeuWXLsObcOdSuXRurV69GrVq1xO1oQQIkEHQC1BBrkVNDAO001aenrECiycNUc2SOwC//1xin9m+jhlg7PdkbCVhOgBpiHVLqh3GWpy5cRa235uoNutQvjMEP1mAhzjg+T1uyEOfp9KoVHAXQ2nxQBP3wPHkSKFYM0B5XFV1RUVgzZgw3USJO/JwEHCZADbE2AdQQH0/tzrgWo6KRkGSuGle3RB68WjcTNcTa6cneSMByAtQQ65BSP4yzvByfiAqvz9YbPFarAN57tDYLccbxedqShThPp1et4CiA1uaDIuiH5/r1vgMbDF5rvv0WtR9/nHfEGeRFMxJwggA1xFrq1JB/ec7bcgzdvlhlGvDIu7KjQ5um1BDTBNmQBOwnQA2xjjH1wzjL5ORklBn4u37ndbuqd2DcE3eyEGccn6ctWYjzdHrVCo4CaG0+KIJ+eA4ZArzxhmHga559FrU//pibKMPEaEgCwSdADbGWOTXkZp7tJizBhoNnTUF+uPhVjOrVnhpiih4bkUBwCFBDrONM/ZBjWWXwbJy/kogW5fNicpf6LMTJ4fOsNQtxnk2teoFRAK3NCUXQD8++fYGxYw0DX9OxI2pPm8ZNlGFiNCSB4BOghljLnBpyM0/tEdW2E5Yg7nKCNOjWBS7i4xcfpYZIk2MDEggeAWqIdaypH3IsP1+0Ddu3bUOL+jVwV9ViLMTJ4fOsNQtxnk2teoFRAK3NCUXQD0/eEWftZGNvJKAAAWqItUmghtzKUy/GjV+CuCtyxTjeEWft3GRvJGAHAWqIdVSpH3IsRbxEc1NuNFq7hQALcW7JlAf8FC0yokXKAwgsDYG8/ODkO+IsnWvsjARUIEANsTYL1JC0eWrFuPvGLcaFq4mGgfMdcYZR0ZAEHCNADbEOPfVDjqWIl2huyo1Ga7cQYCHOLZnygJ+iRUa0SHkAgaUhkJcAZ5MmwOLFYuY8NVXMiBYkoAABaoi1SaCGpM9T5s44nppq7bxkbyRgFwFqiHVkqR9yLEW8RHNTbjRau4UAC3FuyZQH/BQtMqJFygMILA2BvAQ4d+4EGjQAYmPTN8yXD1i2DGvOnUPt2rX5fh9LZyg7IwFrCVBDrOVJDfHPUyvGaQc4nPPzzrjcWSMxs1cjnNq/jRpi7fRkbyRgOQFqiHVIqR9yLEW8RHNTbjRau4UAC3FuyZQH/BQtMqJFygMILA2BvAzg1IpxXbumfWdcVBQwZQpQpgxEc9PASDQhARKwmYDoe8o1US4B5CXmpRXjBny/ASv2nrrFWLsTbniHaiiRLxs1RIySFiTgOAFqiHUpoH7IsRTxEs1NudFo7RYCLMS5JVMe8FO0yIgWKQ8gsDQE8pLAuWEDLk2bhsObNqFQlSrI0rEjUK3ajQ5Ec1NiJJqSAAnYRED0PeWaKAeevIzz2nrkHH5evRdbd+5DxTLF8UDtEqhYMAc1xDhCWpKA4wSoIdalgPohx1LESzQ35UajtVsIsBDnlkx5wE/RIiNapDyAwNIQyEsOpz9eorkpNxKtSYAE7CAg+p5yTZSjTl7W8RLNTbmRaE0CJGAHAdH3lGuicepkZZyVZiniJZqbcqPR2i0EWIhzS6Y84KdokREtUh5AYGkI5CWHk4U4OV60JgHVCFBDrM0INUSOJzVEjhetSUA1AtQQ6zJC/ZBjKeIlmptyo9HaLQRYiHNLpjzgp2iRES1SHkBgaQjkJYeTmyg5XrQmAdUIUEOszQg1RI4nNUSOF61JQDUC1BDrMkL9kGMp4iWam3Kj0dotBFiIc0umPOCnaJERLVIeQGBpCOQlh5ObKDletCYB1QhQQ6zNCDVEjic1RI4XrUlANQLUEOsyQv2QYyniJZqbcqPR2i0EWIhzS6Y84KdokREtUh5AYGkI5CWHk5soOV60JgHVCFBDrM0INUSOJzVEjhetSUA1AtQQ6zJC/ZBjKeIlmptyo9HaLQRYiHNLpjzgp2iRES1SHkBgaQjkJYeTmyg5XrQmAdUIUEOszQg1RI4nNUSOF61JQDUC1BDrMkL9kGMp4iWam3Kj0dotBFiIc0umPOCnaJERLVIeQGBpCOQlh5ObKDletCYB1QhQQ6zNCDVEjic1RI4XrUlANQLUEOsyQv2QYyniJZqbcqPR2i0EWIhzS6Y84KdokREtUh5AYGkI5CWHk5soOV60JgHVCFBDrM0INUSOJzVEjhetSUA1AtQQ6zJC/ZBjKeIlmptyo9HaLQRYiHNLpjzgp2iRES1SHkBgaQjkJYeTmyg5XrQmAdUIUEOszQg1RI4nNUSOF61JQDUC1BDrMkL9kGMp4iWam3Kj0dotBFiIc0umPOCnaJERLVIeQGBpCOQlh5ObKDletCYB1QhQQ6zNCDVEjic1RI4XrUlANQLUEOsyQv2QYyniJZqbcqPR2i0EWIhzS6Y84KdokREtUh5AYGkI5CWHk5soOV60JgHVCFBDrM0INUSOJzVEjhetSUA1AtQQ6zJC/ZBjKeIlmptyo9HaLQRYiHNLpjzgp2iRES1SHkBgaQjkJYeTmyg5XrQmAdUIUEOszQg1RI4nNUSOF61JQDUC1BDrMkL9kGMp4iWam3Kj0dotBFiIc0umPOCnaJERLVIeQGBpCOQlh5ObKDletCYB1QhQQ6zNCDVEjic1RI4XrUlANQLUEOsyQv2QYyniJZqbcqPR2i0EWIhzS6Y84KdokREtUh5AYGkI5CWHk5soOV60JgHVCFBDrM0INUSOJzVEjhetSUA1AtQQ6zJC/ZBjKeIlmptyo9HaLQRYiHNLpjzgZ0xMDBo3boyvvvoKFStWvCWiuLg4rF69GrVr10b27Nk9ELG9IZCXHF9/vLZu3Yonn3wSS5YsQaNGjeQ6pjUJkEBQCFBDrMVMDZHjSQ2R40VrElCNADXEuoxQP+RYinhxHyLH0yvWLMR5JZMuiOPrr7/Wix28SEBVAlqR+IknnlDVPfpFAiFNgBoS0ul3RfDUEFekiU6GKAFqSIgm3kVhU0NclCwLXGUhzgKI7MIYgdjYWMyZMwclSpRAlixZbml0/a8B6d0xZ2yU0LEiL7ln7/deAAAXxUlEQVRc++N16dIl7N27F61bt0a+fPnkOqY1CZBAUAhQQ6zFTA2R40kNkeNFaxJQjQA1xLqMUD/kWIp4cR8ix9Mr1izEeSWTHoiDz8fLJZG8yEuOAK1JwNsEuCbK5Ze8yEuOAK1JwNsEuCYazy9ZGWelWZKXHK9QsWYhLlQy7YI4uUjJJYm8yEuOAK1JwNsEuCbK5Ze8yEuOAK1JwNsEuCYazy9ZGWfFQpwcq1CyZiEulLKteKxc1OUSRF7kJUeA1iTgbQJcE+XyS17kJUeA1iTgbQJcE43nl6yMs2IhTo5VKFmzEBdK2VY8Vi7qcgkiL/KSI0BrEvA2Aa6JcvklL/KSI0BrEvA2Aa6JxvNLVsZZsRAnxyqUrFmIC6VsKx7rkSNHMGnSJDz33HMoWLCg4t467x55yeWAvOR40ZoE3EaA33G5jJEXeckRoDUJeJsA10Tj+SUr46w0S/KS4xUq1izEhUqmGScJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkICjBFiIcxQ/BycBEiABEiABEiABEiABEiABEiABEiABEggVAizEhUqmGScJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkICjBFiIcxQ/BycBEiABEiABEiABEiABEiABEiABEiABEggVAizEhUqmGScJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkICjBFiIcxQ/BycBEiABEiABEiABEiABEiABEiABEiABEggVAizEhUqmFY0zMTERI0aMwOTJk3HgwAEULVoU3bp1w8svv4zw8HBFvbbWrfPnz+P999/H6tWrsWrVKhw9ehRPP/00Pvvss1sGkuElY2ttRPb1pvH56quvsGDBAuzZswfZsmVD5cqV8dprr6FFixY3DSwTv4ytfdGxZxIgAVkC/O4C1BDjs4YaYpwVLUkgFAhQQ6ghMvOcGiJDi7YiAizEiQjxc1sJ9OrVCx9++CG6dOmChg0bYunSpZg6dSq0f//ggw9sHVuVzvfu3YuSJUuiYMGCqF27Nn777bd0C3EyvGRsVWEh8qNDhw6Ijo7Gww8/jFq1aukbUG2+bNq0CRMnTkTPnj1vdCETv4ytyEd+TgIkEDwC/O4C1BDj840aYpwVLUkgFAhQQ6ghMvOcGiJDi7YiAizEiQjxc9sIbNy4EdWrV0fv3r0xduzYG+P06dMH48ePx/r161G1alXbxlel4ytXriA2NhaFCxdGQkICIiMj0yzEyfCSsVWFgxE/YmJiUKdOHWTKlOmG+aVLl1CjRg2cOHECx48fR0REBGTil7E14iNtSIAEgkOA310fZ2qI8flGDTHOipYk4HUC1BBqiOwcp4bIEqO9PwIsxHF+OEZg0KBBeOedd7B79279jrDrl/bIYalSpTBw4EAMHTrUMf+cGNhfIU6Gl4ytE3FaPWb//v0xatQo7N+/X3+8WSZ+GVur/WZ/JEAC5gnwu3srO2qIuflEDTHHja1IwM0EqCHUEKvmLzXEKpKh1Q8LcaGVb6Wibd26tX7Xm/ZOtNRX/vz5UbNmTcyePVspn+12xt8mSoaXjK3dMQWj/44dO+L777/HmTNn9PfGycQvYxuMWDgGCZCAMQL87sptomR4ydgay5baVtQQtfND70jADgKhts4ZYch9iBFKt9pQQ8xxC/VWLMSF+gxwMH7tsdOMGTPqhxSkvrT3f8XHx+uPGIbS5U8AZXjJ2Lqd79atW/VHU++//3788MMPejgy8cvYup0V/ScBLxHgd1euECfDS8bW7XOKGuL2DNJ/EjBHIJTWOaOEuA8xSupfO2qIPDO28BFgIY4zwTECpUuXhnbnm3ZAQ+pLO7hBe9/Xzp07HfPPiYH9CaAMLxlbJ+K0asyzZ8+iQYMGOHLkiH53ZbFixfSuZeKXsbXKb/ZDAiQQOAF+d+UKcTK8ZGwDz6RzPVBDnGPPkUnAaQKhss7JcOY+RIYWQA2R40XrmwmwEMcZ4RgB/iVKbhMlw0vG1rEJEODA2iEN2mMFK1eu1B9hbtq06Y0eZeKXsQ3QZTYnARKwkAC/u9SQQKYTNSQQemxLAu4nQA2hhgQyi6khgdBjW40AC3GcB44R4LsZ5ARQhpeMrWMTIICBr169inbt2mHBggX48ccf9cdSU14y8cvYBuAym5IACVhMgN9daojZKUUNMUuO7UjAOwSoIdQQs7OZGmKWHNulJMBCHOeDYwS0U1GHDRvGU1NTZMDfLeEyvGRsHZsAJgfWGHXo0AG//vorvv76azz++OO39CQTv4ytSZfZjARIwAYC/O7KbaJkeMnY2pBaW7ukhtiKl52TgGsIeHmdM5sE7kPE5KghYka0MEaAhThjnGhlAwHtnV7ayai9e/fG2LFjb4zQp08fjB8/HuvWrUO1atVsGFndLv0JoAwvGVt1adzqWVJSEjp16oTp06fj448/Rvfu3dN0XyZ+GVs3saKvJOB1AvzuyhXiZHjJ2LppnlFD3JQt+koC9hLw6joXCDXuQ/zTo4YEMrvYNjUBFuI4Jxwl0KNHD0yaNAldunRBo0aNEBMTg6lTp+K5557DRx995KhvwRx8woQJOHPmDLQFfvDgwXqBsn379roL2iOY1wuSMrxkbIMZayBj9evXD6NHj9bfB9etW7dbumrZsqV+AIh2ycQvYxuI/2xLAiRgLQF+d308qSHG5hU1xBgnWpFAqBCghlBDZOY6NUSGFm1FBFiIExHi57YS0P7yMnz4cEyePBkHDx5EkSJF9ALLgAEDEBERYevYKnVeokQJ7Nu3L02XtMJk586d9c9keMnYqsTCny/NmjVDdHR0uiYLFy6EZkNWbsko/SSBwAh4cZ0zQ4QaYowaNcQYJ1qRQKgQoIb4Mk0NMTbjqSHGONHKGAEW4oxxohUJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJBESAhbiA8LExCZAACZAACZAACZAACZAACZAACZAACZAACRgj8P/t3XuwjdUfx/EvEpqKyq2LOlQjtyFUuoqSkltEGJIJhUpFSdNViI4OXZA0kz/cco1qaKpBzUSlFIPCoKbbqKgYKd3ms2bWmX322ax9cbazPe/1z+/XPuvZz/O81v71nfn81oUgLjkneiGAAAIIIIAAAggggAACCCCAAAIIIJCRAEFcRnxcjAACCCCAAAIIIIAAAggggAACCCCAQHICBHHJOdELAQQQQAABBBBAAAEEEEAAAQQQQACBjAQI4jLi42IEEEAAAQQQQAABBBBAAAEEEEAAAQSSEyCIS86JXggggAACCCCAAAIIIIAAAggggAACCGQkQBCXER8XI4AAAggggAACCCCAAAIIIIAAAgggkJwAQVxyTvRCAAEEEEAAAQQQQAABBBBAAAEEEEAgIwGCuIz4uBgBBBBAAAEEEEAAAQQQQAABBBBAAIHkBAjiknOiFwIIIIAAAggggAACCCCAAAIIIIAAAhkJEMRlxMfFCCCAAAIIIIAAAggggAACCCCAAAIIJCdAEJecE71KmcDKlSutVatWh3yqTp062euvv17Knjq7j3P11VfbqlWrDnnTdevWWZMmTZJ6KFlXrlzZmc6YMcP69evnrnvttdese/fuxb7j3nvvteeee859vnXrVjvvvPOSuo86/f3333bWWWe5+3311VeHvG706NH26KOP2ptvvmk33nhj0t9PRwQQQIAaEv4NUEPCRvRAAIFoClBDwuNODQkb0SPaAgRx0R7/nH17XwBvv/1207/o41utWrWsZcuWOft+R+LB5bJ+/Xp7/vnnE36dwqtTTjkleKs9e/ZY9erV7aWXXjJ5+yCuYsWKdu2119obb7xR5DsUpJ155pn2+++/24EDB1IO4vRlw4YNs4KCAlu9erW1aNEi4TNecMEF9uuvv9q3335rxx13XPA96IAAAgh4AWpI+LdADQkb0QMBBKIpQA0Jjzs1JGxEj2gLEMRFe/xz9u19AZw+fbr179+/1LzH/v37TQFV2bJlj/ozqQBu27bNBVWZtFmzZtmtt95q33//vdWoUaMwiOvWrZstXrzYfV6tWrXCW2iGWocOHdxMuXnz5qUVxClAbNy4sQ0aNMimTJlS7PE/+ugjF9Ddf//99uyzz2byelyLAAIRFKCGhAedGhI2ogcCCERTgBoSHndqSNiIHtEWIIiL9vjn7NunUgD9DK7ly5fbJ598YtOmTbOffvrJmjVr5kIeBT6xTWHa+PHjbe7cubZz5063RPL666+3sWPHuiWTvj3xxBP25JNP2meffWYKBBcuXOi+d/fu3ValShXbtWuXm9mlYEqzxK644gq3XPO6665zs/j0XOp7xhlnWJ8+fdx3xLeGDRtamTJlbMOGDSmP1ZEqgLfccot98803bnaamvecP3++9e7d2/Lz8+3uu+8ufD4FcNu3b7f27ds7n/ilqb/88os99dRTbpmrD/Fuuukm01JTufl24YUXuvv+8MMPdvzxxxd5/yFDhrix+/zzz4uNX8pQXIAAApEToIaEh5waEjaiBwIIRFOAGhIed2pI2Ige0RYgiIv2+Ofs2/sCOHHiRBcGxbcTTzzRzUyLDY6aN2/u/rlXr15uyeSECRPs5JNPdkGRX9r4119/ub3ntH+almE2atTIhUGTJ0+2k046yYVuVatWdd/jgziFZfqsS5cutnfvXtP+aOXKlbOLLrrINm7caHfccYf7ng8//NDt2fbHH3+4Pc0UaKkp6FJI+OOPP1qlSpUKX+XTTz81PbOeU4Feqk0FcMuWLW55anzTjL1TTz01+JUHDx50s91GjBhhI0eOLOL5zjvvuFDz66+/to8//tj97bfffrOaNWvauHHjTEta44M4fXbJJZfYzz//bAMHDrQ6derYl19+aVOnTrV69eq5sK9ChQruuyZNmmT33XefCzhl65vGSOGllh9rnGgIIIBAqgLUkLAYNSRsRA8EEIimADUkPO7UkLARPaItQBAX7fHP2bcPbZL6wgsv2F133VUkONIMKy1pLF++vPtcM7I0E+utt96ydu3auc80u+vhhx+2999/3y699NJCH828Uij2wAMP2NNPP+0+90Gc9kl7++23iyxHVXCn++s/Bw8eXPg9CrMUUvXt27cwiNO1mnGnJaAKCX3TLDPty6alpVoSmmo73Capp512mgvDQu3dd9+1Nm3auBl5ChzV/Iw4BXEKFTt27GibN2827dn28ssvm2arfffdd27GWnwQp7/NnDnTBZrnnntu4e39cla9r4JLNc0o1F5zCi1jD97QclgFcwphFXrSEEAAgVQFqCFhMWpI2IgeCCAQTQFqSHjcqSFhI3pEW4AgLtrjn7Nv7wug9gi74YYbir2HQiG/jNQHR7Ehjy7Q7CzNCtNhBn5pZdOmTd0ySAVD8e3KK680zbTT8lY1H8QpGOrcuXOR7grWNANOYVfsskotXdXBB7FB3L///mt5eXluRphCOTXNRDv99NPtsssus6VLl6Y1TiqAmpE3Z86cYtfrma666qrg995zzz3OQktNfYsN4nQPzU4bMGCAjRkzxi2/1fJSXeN9/NLU//77z82ua926dcJ932SgsdSSV98U8mm2oJaw+pmICk/1/Qr7ZElDAAEEUhWghoTFqCFhI3oggEA0Bagh4XGnhoSN6BFtAYK4aI9/zr59unsztG3btsg7a/81BUaPP/64+/yEE05ws7wO1c4++2y3FFPNB01a+qmlp7FNQaDCrkTLQnVSaadOnQpnxOm6xx57zAVZWgarWWB+1teiRYvcrL102pHYm6F27druWbVM1LfYIE6zAYcOHWpLliwxzZ47//zz3d56Wm4bH8RphltoZp/CQS3f9U3LUm+++WbzMxy1v5yCP41jugFlOpZcgwACx5YANSQ8ntSQsBE9EEAgmgLUkPC4U0PCRvSItgBBXLTHP2ffPp0CqKWUCo5im4I4hXAKjdS0r5xmxY0aNSqhjf6uWV9q8UFT7AV169Z1e50lG8Tt2LHDLdXUgRAPPfSQC780o04zwfxS2lQHK9MC6E8ufe+999wstkMFcWvXrnX74amP/rvf6y7eR59rlp9mD2qJaqKm2XR+Lz/9XfvB6RrZaB86v+R3wYIF1rVr11RJ6I8AAgg4AWpI+IdADQkb0QMBBKIpQA0Jjzs1JGxEj2gLEMRFe/xz9u1LqgBqZpuWheoAgVA7XBCXytJUfx8FWTohVPvTaVbcoEGD3Cmr6bZMC6Bm6OmgCC2n9YdZ6FniZ8TpswYNGtimTZvcARevvPKKe+R4n3/++ce0N12LFi3cctNkmz8hVfvQaUnvtm3bEp6kmuz30Q8BBBCghoR/A9SQsBE9EEAgmgLUkPC4U0PCRvSItgBBXLTHP2ffvqQKoA5i0GENr776qt12221FfLTHmfZ80z5niYKm2M4vvvii23cumcMa/HU6xKBPnz7Ws2dPt6+bTgRt0qRJ2mOUaQHU6aY61TR+j7lEQZz2ttOJp926dXOh3KF8dBDD9OnT3TLW2Fl26q+gTqeuxp/mqplwehYd0KClujr8Qq40BBBAIF0BakhYjhoSNqIHAghEU4AaEh53akjYiB7RFiCIi/b45+zb+wKoGVj6F318q1y5snXo0MF9nCg48v3jl6b++eef7pTQDz74wO1NpmWoWhqqpaPaB6179+42evToYBB34MABa9asmZtZp/BJM+201FSz3fbv32/t27d3YV9s0950WoapMKpx48amk1rjm59ltmLFioTvHdtfLlpeqsMoEjUdPnHOOeck/JuWkWovNp3kqmAwth3OM7ZfohmDu3fvtssvv9zNalPoKCMFcPpnhWy6pn///sWeqX79+u5kVjWdfHvxxRfn7G+XB0cAgaMvQA2hhhz9XyFPgAACuSpADaGG5Opvl+cuPQIEcaVnLHiSFARCx4Zrjza/vDSVIE6PoDBOhxPMnj3btmzZ4oI4ncCqGVx33nmnNWzYMBjEqYPCrGHDhrkTPnUyasuWLd1SU83uUqA3ZcqUYm+s5ag63VX31yEI8W348OFWUFDgloHqQIjDtcMdG67rNNOtR48eCb9Cs9Y080zLUrVv25EK4vQ9ChrHjx9vOohBB19UqlTJdAiGDmDQMtRE4eC4ceNs5MiR7p19IJfCz4WuCCCAQBEBagg1hP9JIIAAAukKUEOoIen+drgOAS9AEMdvAYEsCujUz6pVq7pDGRQsxTeFb1OnTnWHNKhffNOhCHl5eTZ//vwSfWrNJtTMPR3UQEMAAQQQKB0C1JDSMQ48BQIIIJCLAtSQXBw1nvlYFSCIO1ZHlvc66gJaaqrZXrHtwQcftPz8/ITLK/ft22e1atWya665xnQqaHzbs2eP1ahRw7744gurV69eib7fM888405CbdWqVYnehy9HAAEEEEgsQA3hl4EAAgggkK4ANSRdOa5DIDsCBHHZceYuERTQ4QIVKlRwS1HLli3rZpctXbrUOnfubIsXLy4U0f5z2j9OS2GXLVtma9asYQ+0CP5eeGUEEEAgVoAawu8BAQQQQCBdAWpIunJch0B2BAjisuPMXSIoMG3aNLff2/bt203/r5T2QdPBB4888ogL6Hzze9jVrFnT/U37pNEQQAABBKItQA2J9vjz9ggggEAmAtSQTPS4FoGSFyCIK3lj7oAAAggggAACCCCAAAIIIIAAAggggIARxPEjQAABBBBAAAEEEEAAAQQQQAABBBBAIAsCBHFZQOYWCCCAAAIIIIAAAggggAACCCCAAAIIEMTxG0AAAQQQQAABBBBAAAEEEEAAAQQQQCALAgRxWUDmFggggAACCCCAAAIIIIAAAggggAACCBDE8RtAAAEEEEAAAQQQQAABBBBAAAEEEEAgCwIEcVlA5hYIIIAAAggggAACCCCAAAIIIIAAAggQxPEbQAABBBBAAAEEEEAAAQQQQAABBBBAIAsCBHFZQOYWCCCAAAIIIIAAAggggAACCCCAAAIIEMTxG0AAAQQQQAABBBBAAAEEEEAAAQQQQCALAgRxWUDmFggggAACCCCAAAIIIIAAAggggAACCBDE8RtAAAEEEEAAAQQQQAABBBBAAAEEEEAgCwIEcVlA5hYIIIAAAggggAACCCCAAAIIIIAAAggQxPEbQAABBBBAAAEEEEAAAQQQQAABBBBAIAsC/wOS/NoELMFV5gAAAABJRU5ErkJggg==\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Data given in the task for fitting using lagrange, from Table 7.1\n",
    "E = array([0,25,50,75,100,125,150,175,200],float)\n",
    "g = array([10.6,16.0,45,83.5,52.8,19.9,10.8,8.25,4.7],float)\n",
    "\n",
    "\n",
    "#For the Lagrange method\n",
    "E_Lagrange = linspace(E[0],E[-1],100)   #lets create a new dataset\n",
    "g_Lagrange =array([],float)     #empty array\n",
    "\n",
    "#lets apply a spline function on our function/plot   \n",
    "#check scipy, spline\n",
    "E_smooth = linspace(E.min(),E.max(),100)\n",
    "g_interp = interpolate.splrep(E, g, s=0)\n",
    "g_smooth = interpolate.splev(E_smooth, g_interp, der=0)\n",
    "\n",
    "#see the slide above for the formula\n",
    "for e in E_Lagrange:\n",
    "    yp =0\n",
    "    for xi,yi in zip(E,g):\n",
    "        yp += yi*prod((e-E[E!=xi])/(xi-E[E!=xi]))    #applying conditional indices /index\n",
    "    g_Lagrange = append(g_Lagrange,yp)\n",
    "    \n",
    "\n",
    "plt.figure(figsize=(10,5))    \n",
    "\n",
    "plt.subplot(151)\n",
    "plt.plot(E,g,\"r-o\")\n",
    "plt.grid()\n",
    "plt.title(\"Original data\")\n",
    "plt.xlabel(\"Energy, E /MeV\")\n",
    "plt.ylabel(\"Scattering Cross-section\")\n",
    "\n",
    "plt.subplot(153)\n",
    "plt.plot(E_smooth,g_smooth, \"-o\")\n",
    "plt.grid()\n",
    "plt.title(\"Spline smoothed\")\n",
    "plt.xlabel(\"Energy, E /MeV\")\n",
    "plt.ylabel(\"Scattering Cross-section\")\n",
    "\n",
    "plt.subplot(155)\n",
    "plt.plot(E_Lagrange,g_Lagrange,\"-.\")    #Lagrange fitting plot\n",
    "plt.grid()\n",
    "plt.xlabel(\"Energy, E /MeV\")\n",
    "plt.title(\"Lagrange fitting\")\n",
    "plt.ylabel(\"Scattering Cross-section\")\n",
    "\n",
    "plt.show()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1100\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(11,6))    \n",
    "#combined figure\n",
    "plt.plot(E,g,\"r-o\")\n",
    "plt.plot(E_smooth,g_smooth)\n",
    "plt.plot(E_Lagrange,g_Lagrange,\"-.\")\n",
    "plt.grid()\n",
    "plt.legend([\"g_Original\",\"g_smooth_spline\",\"gplt_Lagrange\"])\n",
    "plt.ylabel(\"Scattering Cross-section\")\n",
    "plt.xlabel(\"Energy, E  /(MeV)\")\n",
    "plt.title('A plot of scattering cross-section versus Energy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}