multivariate-calculus/Fitting+the+distribution+of+heights+data.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fitting the distribution of heights data\n",
    "## Instructions\n",
    "\n",
    "In this assessment you will write code to perform a steepest descent to fit a Gaussian model to the distribution of heights data that was first introduced in *Mathematics for Machine Learning: Linear Algebra*.\n",
    "\n",
    "The algorithm is the same as you encountered in *Gradient descent in a sandpit* but this time instead of descending a pre-defined function, we shall descend the $\\chi^2$ (chi squared) function which is both a function of the parameters that we are to optimise, but also the data that the model is to fit to.\n",
    "\n",
    "## How to submit\n",
    "\n",
    "Complete all the tasks you are asked for in the worksheet. When you have finished and are happy with your code, press the **Submit Assingment** button at the top of this notebook.\n",
    "\n",
    "## Get started\n",
    "Run the cell below to load dependancies and generate the first figure in this worksheet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Run this cell first to load the dependancies for this assessment,\n",
    "# and generate the first figure.\n",
    "from readonly.HeightsModule import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Background\n",
    "If we have data for the heights of people in a population, it can be plotted as a histogram, i.e., a bar chart where each bar has a width representing a range of heights, and an area which is the probability of finding a person with a height in that range.\n",
    "We can look to model that data with a function, such as a Gaussian, which we can specify with two parameters, rather than holding all the data in the histogram.\n",
    "\n",
    "The Gaussian function is given as,\n",
    "$$f(\\mathbf{x};\\mu, \\sigma) = \\frac{1}{\\sigma\\sqrt{2\\pi}}\\exp\\left(-\\frac{(\\mathbf{x} - \\mu)^2}{2\\sigma^2}\\right)$$\n",
    "\n",
    "The figure above shows the data in orange, the model in magenta, and where they overlap in green.\n",
    "This particular model has not been fit well - there is not a strong overlap.\n",
    "\n",
    "Recall from the videos the definition of $\\chi^2$ as the squared difference of the data and the model, i.e $\\chi^2 = |\\mathbf{y} - f(\\mathbf{x};\\mu, \\sigma)|^2$. This is represented in the figure as the sum of the squares of the pink and orange bars.\n",
    "\n",
    "Don't forget that $\\mathbf{x}$ an $\\mathbf{y}$ are represented as vectors here, as these are lists of all of the data points, the |*abs-squared*|${}^2$ encodes squaring and summing of the residuals on each bar.\n",
    "\n",
    "To improve the fit, we will want to alter the parameters $\\mu$ and $\\sigma$, and ask how that changes the $\\chi^2$.\n",
    "That is, we will need to calculate the Jacobian,\n",
    "$$ \\mathbf{J} = \\left[ \\frac{\\partial ( \\chi^2 ) }{\\partial \\mu} , \\frac{\\partial ( \\chi^2 ) }{\\partial \\sigma} \\right]\\;. $$\n",
    "\n",
    "Let's look at the first term, $\\frac{\\partial ( \\chi^2 ) }{\\partial \\mu}$, using the multi-variate chain rule, this can be written as,\n",
    "$$ \\frac{\\partial ( \\chi^2 ) }{\\partial \\mu} = -2 (\\mathbf{y} - f(\\mathbf{x};\\mu, \\sigma)) \\cdot \\frac{\\partial f}{\\partial \\mu}(\\mathbf{x};\\mu, \\sigma)$$\n",
    "With a similar expression for $\\frac{\\partial ( \\chi^2 ) }{\\partial \\sigma}$; try and work out this expression for yourself.\n",
    "\n",
    "The Jacobians rely on the derivatives $\\frac{\\partial f}{\\partial \\mu}$ and $\\frac{\\partial f}{\\partial \\sigma}$.\n",
    "Write functions below for these."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# PACKAGE\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# GRADED FUNCTION\n",
    "\n",
    "# This is the Gaussian function.\n",
    "def f (x,mu,sig) :\n",
    "    return np.exp(-(x-mu)**2/(2*sig**2)) / np.sqrt(2*np.pi) / sig\n",
    "\n",
    "# Next up, the derivative with respect to μ.\n",
    "# If you wish, you may want to express this as f(x, mu, sig) multiplied by chain rule terms.\n",
    "# === COMPLETE THIS FUNCTION ===\n",
    "def dfdmu (x,mu,sig) :\n",
    "    return f(x, mu, sig) * (x - mu) / (sig ** 2)\n",
    "\n",
    "# Finally in this cell, the derivative with respect to σ.\n",
    "# === COMPLETE THIS FUNCTION ===\n",
    "def dfdsig (x,mu,sig) :\n",
    "    return f(x, mu, sig) * (-1 / sig + ((x - mu) ** 2) / sig ** 3 )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next recall that steepest descent shall move around in parameter space proportional to the negative of the Jacobian,\n",
    "i.e., $\\begin{bmatrix} \\delta\\mu \\\\ \\delta\\sigma \\end{bmatrix} \\propto -\\mathbf{J} $, with the constant of proportionality being the *aggression* of the algorithm.\n",
    "\n",
    "Modify the function below to include the $\\frac{\\partial ( \\chi^2 ) }{\\partial \\sigma}$ term of the Jacobian, the $\\frac{\\partial ( \\chi^2 ) }{\\partial \\mu}$ term has been included for you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# GRADED FUNCTION\n",
    "\n",
    "# Complete the expression for the Jacobian, the first term is done for you.\n",
    "# Implement the second.\n",
    "# === COMPLETE THIS FUNCTION ===\n",
    "def steepest_step (x, y, mu, sig, aggression) :\n",
    "    J = np.array([\n",
    "        -2*(y - f(x,mu,sig)) @ dfdmu(x,mu,sig),\n",
    "        -2*(y - f(x,mu,sig)) @ dfdsig(x,mu,sig) # Replace the ??? with the second element of the Jacobian.\n",
    "    ])\n",
    "    step = -J * aggression\n",
    "    return step"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test your code before submission\n",
    "To test the code you've written above, run all previous cells (select each cell, then press the play button [ ▶| ] or press shift-enter).\n",
    "You can then use the code below to test out your function.\n",
    "You don't need to submit these cells; you can edit and run them as much as you like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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       "\n",
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       "\n",
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       "\n",
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       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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k4NAArYAiVlbgrYy2vcA+qlfmBBq65n2vjqNU9sCqLSm+vjBQhdwkItfCtblBoA37e7Gjp19ePHIZgwO5tptYAIEuEMGAZAAaJ8lS+MCJgC6LnEEQJ0l0sdLW+Py9BdkQgC0K6DR3FzjJ6rc6QImALquNz4L0ALoU0A3AKypHcHBe9rw4fvVuHSxnAAYo4BX65GvVCO+0sC4wzktgLpUPrQAas9lVb4EPVqoaAFMrr4JoUjp3qQFMH7NFbcY+vgxQQugTwBK9cvdADAzc8baB3itvRBvvVFHACQARhRQBndoy9EC6CM3YJCLGC2AtADaFFAHxgQJ8Zo9dtbpa+6nqiSGWKW7WwlotAAGuRDp6qIFUKdTwlJuAGguvP9wM/ILQnjqB1vj9wGKEOBuZfKzgd7PPjM51ZwyTYcGeHwk+FW7xZfCAqjYo6ZurzgdvGsuJ1HW5ot0NsbZD+916fNWCu1Q5kGU7uFzCbC/7j0DkLxlT3hB+3lp265NNpz4hwdBTg3ceISpSHuFGeGrPiUoefzxII2h2mXrZy5pxsGPWzjIE28SDCwtgMGufilXmwYAd9/chW3b+/H8s1swPJQzrxEBMH6+EABVz48/iNe5aL272QmAjkFUBkEQACXyIgA655N7JDcBUPSxO6QkAKpeOSyUSAENANauG8GBu9vwwYlqNMXuAyQAEgBjFJAtuxqrm0+XsvrEGE1bCIAEwHgF1DAib/AS+EdhUfNlsaMF0K6AnzH0HBhCC2DSwYsuYJ8SawDQ7AP8+CcvovNaId58PWYfIAGQAEgAjFXA8TSqLZF0AatAyX5uKl3AyxMEogYq6f1kAyO6gL0HVNEC6BOAUv1yDQAaje69vwXFJZN48l+3IRyOcjcBkABIACQAzimgjAy1Q5x1ucdrCYAEQJXF2sdJILQArlxKogXQ59gYAPzx3/xvcbVIEZk37urBzht78fILm9Dflxcp7xUAFUEGkeq9u+PkqFJtfbpyjnuIsQ0+Ah6Urk21lUlKLK28h32s1fcMeqyF+e5rT6GtPnVd6n5pH1BlbkiPx75pW6GNqhSJTed5FKMUNOlCLE5UuFnV1ilFXYnuqb6H1yAFZYCCNA6+oNjHUWhS9ImmLf5yHur2ymnndaDWSD8uYOUWgL/9rZ9sA2BPz6F93Fd9OQKgzyHUAmBl1TgO3W/OBa7EuTOVBEArHto2/QiATheoGpR00C1NdzW0iQBsN+IqgV3dL+0DSgB0WnIUe+VE6FRCAQFQkFwXta0GYNHyFn9bAqBunks6EQC16yvLiQpoATA9HXj8kxcwNJiDV17aRAAkADrnk8gwSqDSWntpAUzqSqa1lNACqIRMWgCd89UmHQGQAOh1UaMF0Kty0eu0AGisLHccaMW69SPWPsDp6Qy6gGkBtJnPJCYkAOoeUVoAaQGMUYAuYAEcdaAkuqK9gniibQcaFy1dwLqlz0cpAqAP8cyliwHAzQ392HtbJ956fT3a24oJgARAAmCsAto9seIzSwAkABIA5xTw52LWRtVKjBkgZBIAfdKJ++UEQHeNFiyxGADMz5/CI483obmpBCeOrxMPJdDsx9IHaIj+PseXYrCIeo+WDwvVsgCgd020J1VoAjz0Y+hdX2niauaXuc770XLSXkSl5j5SucjbE1fK8qaMNNVaWeSQXw3/OcKFNUEGpuIgg0ys+nxElaosVMqoaM8RqpFOeNLcf//jb7tcLmD9GArPv2cLoPej67gH0DkOK2WF9Ilhy3f5YgDQtPLBR5qQmTWLZ37U6Pk8WD08KF+8vo5H8w4oyxME4l0TAqCwgDjmDgFQsIt4BgWZCZX758SDNdxPkfB3T++neeijYBUWKgKgZJ4T5qFyLinP81VDMQFw+aAl5s4EQJ/DsFgA3LWnC9t29OHFI5sxOJirssY5UoiorXPeYUcPmQRAu8q0AMYrImfPEUCRFkANOy7CGictbgTAWFVoASQAMg2MTwhK5csXC4AVlWNWOpgzpypxdi4dTCyRS29L23d6OCMAOuHMuya0ANIC6G2t8+4q9GeNIwC6wR4BkABIAPS2qvGqRQaBGMHS0sL42BMXMDqSjZdf3EwLYKwCS5IHkAAoTDrnV0prnNPaSRewxownp9BT7m/iHkCnK9OuCV3AdAHbFOAeQOEHPCnOnwKWBfA3/iyuEreN9rfvb0f9pmE8/aNGTExkuV9rexm71T9XoT/Xmy6xsNgWkbHcXcXqfnk8fSMC4EoADNrN7gh40ekrc5i7lpG+enezeh4LcVNJwFAoPbKKJNUJx9/fEhB3tTI3shhAINvrlBYaxX4/q35FDjn9XjwJdQOMAhXaa32lCCDRB60Iqmv2p0Ua4gRRMQ+0ThN9m+2DqKtfnF/adDnLoomuX5r5kGje/O1/+imeBBLg+pdyVXkBwLqNQ9h/5zWceK8GzU1lBMCoAp6hIwHseD1qzwIFAqDwc1EBlARA3RqoJEU9FMj46CSU+G/09Xu3Tqpf0NooaAKgbRB1oEQAdOpEANQtVyyVQAEvAJiZOYPHn7iE3p48HHu1ngBIALQU0ASPLA5OFcAWqdDx8QzjBEDdWkkAFNhUCZkEQAJgjALqHxjCvCEA6pYrlgoQAE1Vdx1sRU3tKJ76YfRUkIUgiC7geEimC1hnnaMLWADb5C5lSq6jC1jtUnSOl+aFr7dsCvNB3Ta6gJ0UH6QmOsumZj6YdkrlCIDJXQ/XfO1eLIBGlE2bB3Dbvk68+/Y6XG0pua6TvKcu3qyits4Evt9NuW9NGHVNmzVlElnA1NcGronYWSd4cA9gPMT7GQdpVeEeQIlkBHqyGY/UASVK65yffHF0AUu0KzAW9wDGikIA9I5ZzAPoXTvrSq8AmJ0dstzA19oL8dYbdTGtcIcstatQjngQrCLegwqCDFJQQ5wSADQwbQGleASZpIlkeBNJxl1j0TqnhElFqqAIKC99fdoTROSUOmKDBdGlr5RLmbKY52VBlwc5QS4/6a5Ki4oWnhxRIFJSZYklddYY+ZSOpa/PX3oXicOU/fcFwN50UgOQdo4oXOympcnW2F/9uvGiBdDzSscL/QCgufae+1pQVjZhuYFnZtKjghIA42ZW0KCkdB8nHbKD7tcKqY8AqFsXZRclAdChgOiOdQclf/BAAFSNg7jfQQdesuFZkaTcD2BzD6DTMKFbrtZUqecA1AKYBTAM4PMATgCoBvDXABoBTAL4HIBX3Hru1QJo6m1oHMAtt3bi7TfXo621mAC4FJYtAqBzEQhQdwKg24oR+TsBUAsK3iyUBEBJN6UbnxZA3UO8Bkol2yGyEiUqBTAQbdiPAfgagJsB/AWAluj/3wfgXwBsATC9UCf8AGBu7gwe+/hFmxuYFkBaAGMUULunpYhfYeYmuT4CoG7JIwASAO0zRU7l6K4TXcAS2LrrZvSnC1i3Xq3VUr8I4FcB3AJgBMBWAB3Rzr4N4CsAnk8WABo3492HWlBeMY6nfrgVoVCGuHPL7o5MunvSdFgNCk519Dn0PAa3SAOibS8tgLQAJnM14x5Ap/dQ0ttXAmKhQlt9tADSAugAbLqAnWt/MtfCFVy3cfXeH23fxwC0R//lxLT5nwA8E7UMJuyKHwugAbnNDf3Ye2sn3nlrHVqvmmhgxakJSwI7S2BRUp1xLACm1mWpDoJRWsoCTA7tJ0AlyMCbRBPbc0COj9QzMtdrnRS6oJ1lWZNk046qKTLISADk/E6TCsWr1SlR45fEGqXZB+bnlA51ZLRItk4A9uNSFb22ir1ySQZs00lprP2Bt71fydeXFkDVMrRmC/0CgM8A+LlFAOCXAJh/1icrJ3/DZ776l3ECqV+eaWnIzgnhsccvorOjAG++vpEAaJ9qfpIUEwCdv/jU6VKUkeGO8fKefJoAKECcNrGgAhSs2u2WMvEdq3OfyZcq3XF+IlIJgHHSq6FbC6I+5gQBcHWxkvbn9erq1eJaOw7A5GEx+/9MAMiSuoBNUw/cfRVV1aN4+kdbMTUVfzaw+bvjnU0LoHOEfWkiTBi1JUthsRUGkRZA3UOqPWtaPs5Ed4+kl6IF0CGxdg+kZ6CgBdCpOQHQoQktgElf/VbUDUwASH7U2mca9ikAfwLAmN7+XwDNMUEg3wewOZlBIHMvt431g7h9/zW8/14NLjeVC1Yb21e+YMc9yMS621KkFaEL2D6wOoud6O1UWuxoAVz6BYkASAC0K6B20Tqnqx2eaQFUWp25B9D5fln61XBZ77gJwPcA5EXTwHQD+DKA9wHUAPibaOTvFIBfAfCSW2v97gE09ZuzgU008MBALl592TBn/IcWQLsefmDHm8XOYmLuAXRfQNSWU7cnK/J3WgDVUSVKyLLts5KGQQsnwrVqGKEL2DleooWOABivgHJ7gnIO0wKoW4dZKoECEgDK1rOFLW+339GGjfXDePapRoyNZcfdTQWAAcJJohevHoCUgOZKugkAQAkZyxctLU2W5Yh4FtqhtB6r07k4rLjufY+QnbOcHvZ091AaO5O+tsnb+JRgp4YskeQEKLR95RE6TC1a2JMZU2m18QyoEiiIYupATLPv0BJFADZfZwu76+QrkEfZNu1Yy7mhtRHJiiAQJdhpAqDMSBEAk778re0bBAWAtetGcNfdrTh9qhLnzlQRAKMKqANqlOld9ODhw1Uun8FmG1OPkByhc8dDpYYn5bUEwODWLQKgDoqCPUaOAGhXXQ1xatj1obEi0loNk0qIleYXATC4dS4lawoKANPSwnj04xcRCqXjyDMmFmX+JU8LoG1q0QJIAHQqIGiyMpYkAiAB0AFjCgDSWllpAfRmYaQFMMF58Stj2VwdrQgKAE1vd+3pwrYdfXjlpU3o7TWxKpEPAZAAuLBJeBF75WgBXPKFhQBIACQAxiugcdHSApj8pYppYHxqHCQAFhdP4PAjzWhuKsWJ99YRABMFAdACSAsgLYD2N6qwkkmWEVsx7gF06OY59YxlstPBrgaAaAGUprQuCESrL13APgEo1S/XA6CglAAyDzzYjILCaSsn4MxMetQCaOd05R4w0dojjZif+nQnMGgCSKR9bNq9beq9gislObQSYv3s9wtcO/kIEtclQNsOqa/ybNXNOdeGLWcBbeJmqY3K5NCqU0S07VBuvpebqwt48bNHzZHgWrqlj71iWiuuug8+xtBxD3W/dHAq7sWUzXECPHuHNjs9q08aEfuvawcBcDkXwTVw76ABsHFbP26+pSvmaDjJvecH2AiATgWWITUMAVAYBp1DQh2gspLXFy14EQCdkKHYP6d2HyrqiljixIHQWQ8DhmcCoLsVW7svkgC4khfJVdC2oAEwO3vWygnY15uH116ppwVQmcuDFkCJp5RAJWmsBlT3h5QWQMkaIVhjJBghABIAHbxjwxtaAIU5Qgug+8rMIBCNRguWCRoAzcvy9v3t2Fg/hOeeacDoSLaQDJcWQPugEAAJgL4f5qWsgBZA79YzhdWOFkBxgnnXnC7gpVwdluxeOhPBkjVn9d0oGQBYWTWKe+69inNny3H6ZDUBUDEtCIAEQMU0WTlFCIDeYYQAGK8dLYC0AHpc2QiAHoWbu8wCwF//s/hatKccJEzJEcbDjzYhI3MWzzy5FeFwJBhk7iPHMeisgrI7Tndtss8H1roK9cEi2n5p4SnI+nSBDL7GS5jbWo29Bp/4ql/9LOq0k6oT9w+q7+teUIw+lC5T7inTX+oj0MJ2E20gg9g2H8ENUgit3BZ3VbTXLUXEr7ZfqqAd6QQW7R5DH8ESfnTSzidn83QRv+qgFeER+duv/lQbgDr3J3ttliAA+hzX5AAgsH1nD27a1YO33liP9rYSAmAcACtBbNlOB9EApQ5iCIAyxjm+Va5kBEB3UNS+sAmATgUCByVBZFUQiJjeR5EWyNxPC5TKE0O084kA6BNGPFyuXDY91JwilyQLAHNyQnj08Yvo6cnHsVc2EQAJgLEKOPnHT7CMyFhayI6/mBZAd8CyFKMFUEIbx3daS54mhYg2R5/WYhd0fSePQ08AACAASURBVLQA2oefFsBkYxQB0KfCyQJA06x9d7ShbuMwjjzbgJHhnOstpQtYCyfKclqXfaAWRVoA7Y+efjHSaSfbDvV38bI00AWsA2A/ljINPGvBMeh2+KmPAEgA9LLm+Lkmuauhn5atkmuTCYAVlWM4dF8LLl4ow0cf1BIAowpwD6ASbIVnyJeFTmFl9FW/+pknAAqmMpV6GsjQuuykG2rqtwyg6qhSXTQrLYDxo6EdQ22+PD/jpW6LozG0AKoeah+FCIA+xDOX5llBIP9XXC3BAUoYhx+5jNzcEJ7+0TbMzs6dDCK+2R1fak7fMBepLYriSRBKGBHf2fFf+ovkdWrirz6pX8HpLrOUdy2ljE5aGNOW8xwY4vEEEUttMR+hn4c22UuezgImwpNMVLrOeowq1r6clwL2/LlUbS1UR8ZKkKEbHa12vqBYsR9PPvbM2Qd1exVR1hGIF3QKUndF3yMt0IGi1P+/++pnGASiW2FYSlIguQAING7tw569XTj+zjq0XClN9E5M8KIUfZtOUJTeiepEwN6hxQ6o/oCNAGhXQAt22nIEQM0aSAC0q6S1HhEAJYp3hxsCoLtGEWB1liMAatY0lkmoQLIBMDNzBo994iJGhrPx0gtbjEkkCRa74CxbEaONzkVHAHQgmwDnOi1pAdQuUrQAxiqltQrRAqiDDH0ErQ8LnQ1kCIC6sSEACkYS7bLJcrICyQZAc9ebb+1AQ+MAjr60CX29+QRAxV60xCCqtFiKAR/BgTJdwMoVhS5gnVB0AcfrFKQr0qpZBxkEQCnVjNayaZvqdAHrnn0fpZL9c9hH01bHpVoAVO9lEl54xcVTePCRy7jaUoR3395gWQEdtqOESaVtJQOPeNW1RRpNh6VQ2weRw5TubuV+NH3+PY9QKPZVVEk11lK3tPNENTaJHkdbP8QFRQvsyrHxtTIo2+L5HspEyOr6PYJdhFkUed+U7fW1j0307ToV0LqKNXvPZKtY0Pv9hD6o98/ptgpoLLS+xiZgyNK68TVjrem7jOb6XIZ0AatXIhaUFFgKADQwcvCeFlRWjeHZpxoxMZGtggK1K1aOAlHdw+u+MFM5ATBe4rVgFSQA6l7s6tWUAOiQigAYPykIgMLTpARbAqB6JWLB5QTA2nXDuOtgG86eqcCZU9UqOCMACtZJpZWJFkClc4AWwPhnUWlRU6+mBEACoF0B+x5A5ZxTW9QCTtEj3ZcWQPUKkNSCylU+qW1Y1ZUvlQXQ7EF56JEmZGfP4JmntmFmxn4+sNIVSxewc7750kSYvpoIarqAnT9ilHDua8GgC9gTsPqyMtEFLECszlKsgTZfY6O0lOn3QOpc+wRAX6tYYBcTAH1KuXQACDQ09uPmvZ04cbwWzZfL4lquzj3oC3aU++yUL1m6gOkCjlVAzlvp8wG1X66cm57vqrTGqOunBZAWQFoA5xXQ7Gs1pZVgSxeweiViQUkBEQCVlozF5r3LyJi1zgeenMjE8881xAWDLFsyZ1/7B20A5CPRtBYe1Jr7GUPFtb5czMogoKADQ+RuKX5DaiN5fcCZOP7aJUvRBbEqnREnwaV+LlYEdyR4CTpYQmmdkzqhseJY14lBoGIWYR3saSJyRXm1kbyCFctPcIcS4jXWvoictgp96Ss2TmexTHKktVoP6UeXUnMCoHaRZDlRgaUEQNOAm3Z3YfuOPrz+Wh06O4qut4kAqMuXRwBUbhWQZrviNBfxISEAOl+o8oG2ulXWhxWEABivgAwZBECn0VGZykUNyuJPirgvCYC65cBPKa+/ff3cc01du9QAmJs3jUceu4Te3ny8dnQTATCqAC2AOgD2kxqGFkDb0uXHiEcAFN4DAaZpoQVQqS8tgADq1hSULKIzBMBFiCUVXWoANG247fZrqN88iJdf2Iz+/jyrWbQA6gCIFkBaAB3PsddVkACoggy6gHUWRbXFiy5ghaVQpzldwD4BKNUvXw4ALC6exOGHL6OttQhvvxn58UIAJADqwIYAqNNJsbIRAAmAdqOwj/1oBEBFfkNlcIe8tdX5wBIAFesciyRWwALAL//X+ALaEy006ULEhMnAXQevoqZ2FEeeacDoaHaC83e1efAkKJD6rIQHj3u+9NY5oW2+NPdRn/bIOFs5bY5G2WXrY2zES6V5otNEA1PqAA1lEIifZNMrZi3T7uOTGqyMNNaeEeu4hbZt2nao88qJnZVMOUKT7S/3AN3J5m4+NNGDncTTisCVoNsmBtko26beA+juehbzB/qqXwDA//zZNrqAV8yquPoaslwAWFk1invuvYrLl0rx/olaAiAB0MliSqDyc0whAdDjmqV9aRMACYBuVkbtXNJazwiAHh/q1XeZ190vq6+nSWrxcgGgSQZw7wNXUFIyiWefbsTUZJazh0oLo3ycmw8rEy2Akvks7jtaAD1aGMWTsBPtgUjSQ++h2oyMEHJyJpCdNY2szGlkZU1F/mVOIzNzBhkZM0hPj/w38r9nkYYw0tLm/4XNN+H4f7Mz6ZiZyUBoJgMzsxmR/z2dhenpLExNZ0b+G8rC5GQOpqaygbBiyfcBFDKvBpvyRbenkBZAlWXXj3XWVxoYWgA9LCOBX6JYDQK/55qqcPkAEFi3bhh3HmzD+XPlOH2yhgBoU2BJXMp0Acer7jVVjKlFabFciS5gA295uePIyxtHXu6Y9d/cnAkL+nKyJy3Ic/tYEDeTAQN1s+H0edibtVDQujwChLPWf9PNv4xZZETBMT194U2Js2FgajLHgsGJyRyMT+RifCwfY+N51j8Di9aWAwKgYHX0nnuRLmCFG9sobk9vGDhg0gVsn9gEQLdV2eXvywmA5ok5/NBl5OWH8NzTWzE9nWF7GXMPoGP4PFonIy9f6XHxtn+SFsDVagEMIy9vDIX5oygoGEFhwYj1XwN79ulhjmucnMy1YGtyyoBXLqamsy3Qmrasc9kITWciFMq0rHdzkOe6JCWw2hgozMwIITMrhCzL0misjNPIzjb/JpGbM4mc7Cnk5BoonXbcJhTKwMhoAUZGCjAa/a/5/zMzmXLSGu4B1IGiGBgSIFD6AHZtMm95ykl9UOYLVATLcA+g60rguwAB0KeEvgBQfAe6H7cWCw91Gwex745rOH2qEufOVMXVGHxksO6lrQclW1+11iPlfj9tbkB5D5yPqGKNVVDtnpcmqDfojJiQBEOx4uSSyFWKYBGlFU/dDu3zqb2vtr5oueysSRQXD6G4KPKvqHA4zpo3O5uGsfF8jFmWtHyMW9a0fIxPxFjUpHsq4Um81MfpHXPWPeNizo1aLPPzx5GfNw7z38KCUWRlheJuOzqah8GhIgwNFWFwqNiCQ8sVrW6Hd3esNprTbrWU5fVmiYoYp3Rgo22v3irozVWqP7tXOTa+rHHyLLZ/69BEvWdR4nDdeP0dg0AWuSKyeJwCyw2A5lf/g480ITtr1toLaH7Fz30IgDqIIwAqdUoBAMzNGUdpyUDkX+kA8nInrj9PxkU7PFyE4ZEijIwWWv8M+IXD6YtfFZcZAOcaLNlwjLWwsHDUgsGiwlEUFw8jP29eB2PZHBwsRv+A+VdiweF1DdQJmHVQoAUqAqADpxwCq6FT3LLpx9qnG2sC4OKXEb9X0ALoU8HlBkDT/M1bBrD3tg6c+qgK589VEgCjCtACqAM7tU5rEABNcEZ5WR8qynpRVtqP3NzJ68/P2FgeBoZKMTRcjCFj+RorSBSCsvhVZMUCYMTeZf8Yd7IBwRLzr2TI+q85m9x8LCAcKkJvbxl6esswOppv00lpZVJaFDXWOFoAtdZO5djQArj4Z3wVXEEA9DlIKwEAjRXwoUebkJk5i2ef2motyOZDC6AOgGgBVOq0RgAwP28UlRU9qCjvtdy7JpjCfEbH8jEwWHr939RUjs/VYYHLVxkA2tnMBKIUFQ+hvHQQpaVDKC0Zug6EExM5Fgiaf319ZTBucod9SmkppAWQLuDYuSPvWXQ+Z1prJ13AyVviUqLmlQCAsVbAjz6sxsXzFQRAywahBBsf+/H0+x1tj4OPe/pJDq3eeyeH2jqeaUcx7V487V5E7Sqy4H3DKMgfRVVlN6oru1BQMHbdctU3UI6+vnL09ldYQRpL9lnlABixE87DiYmCLisdQkV5Hyor+pGfH3EZmy0pPT1l6OyqRG9fKWZnI1tUtBY6AiABkACYvFWJFkCf2hoA/DHbSSAyFDhvJJXTAIVUxqSDMFZAkwriuacbLSugPg2Ke+BJQouiGPCgrM8uiTK4Qxoyf33VjU2CCAonFCmihWVe0QGrDLY+AkMEQbVzWJO6JfC0LUp4NPv5ams6UV3dhYL8CPRNTWWhu6cS3b1VGBgo9bZ/z+eaYYen69UtnMVl4btqI0HttShBVGt5mXMfmzQ4VZV9qKnuQUnJSBQG09HTU472jmr09ZZYgSRxL3elC1gOcHB0zKGXbBWSZNW6T53XatzTEQDWDbbGkiUbU5V9WCFJn2VNdH3wo+XfMwgkgNUshatYKQBoOGxLYz9u2duJDz+oxqUL5QRAH1Y2DYhb015kXfd0MQRAH789FwDAjPQQqqp6UFvTgbLSgRjoq0JXTxUGB0oQhoegjYDXOH0ErfLGKwwAY1tt8iBWV/egproXpaXD1p8mJ7PQfq0K165VR/cMJoq01QIaATCepnXwpIPpREfh6SJtteDtLKfrAwFQuUZIP/S9X8orjQIrCQBNaoeHH2uyksQaK+CcuyVupNRQ5N2ipLfG2eYQLYDOh0pp7fJzmov0JK82C2BRwQg2rG+zrH2ZGbPWvrOe3kpc66hFf3/ZioA+b9Yu5Tq7ggEwtmm5uRNYv67L+peXFwm4GRwsxNXWWnR0ljvXLOVeQWf3dfCQIMGhZ+shLYDedScAKp/1AIv5+BkeYCuWriqzyee7AG4EMA6gC8C/B3ARwMsANpn1KNqcvwLwbbemrSQANG3d0tCPW27txMkPq3DxwnxE8PV+EAB1kKVw41oV0QLo9ohIEqlP/RArj2puAhGqK7tRt77dikw1H5Or7lpnLbq6qxEKCccjurZ2aQqkkgVQTiI8awWPrF/XjZqaHiuAbWoqE23t1WhtrbFOKbE+BEDnhLQJShewd3c6XcBLs96tlLuYVeUBAE9Hl5ZfAfATAO6LAuB3AHx/MY1daQBorIBmL2BGRhhHnonPCxgBFimZr3LPnjYwQIInzQkctADq4FSmTse1ajezMOFXsgUwM2sadevbLPAzp1yY/a4G+FrbN2BkpGgxj++ylSUAzr+0zekl69Z3Y2PdNRQUTFgBIt09ZWhuXo+BgWJhjDSpS7xbovRJlAU2UyaM9uO2dOQ8lGaxOomyRku6gJdtoUjyjVPNAmiX83YA/2xS6fkCwF/707h61S5QZcSkoz4XULqeF/BkFc6fjbcCLltqGAW0aKFDra/08AQNmcpIY2ebvbvY9ZG8usdbDYpad7Rdd+UPB3G4Yr40CYo31rVhw/pr1mkc4xM5aGvbgPaO2hVt7VOv4V7duIlMZQrDiB5ElaCghZEEoFRePoj6+g5UVfZbv1X7+4vQdHkDentLrpvbNRHE2n1natiTMDTZR7wlmDiqhMlqEBU75vhS79oWJ4CzPoV2QUKyZUwW7vn3v/3TbQDq1M/oGiuoe0OssU7HdOdvAPQB+EIUANeb/ckATgP4jwCa3LpuWQBXGABaeQEfaUJW9ozjjGACoAReuscg2MAQAqDbs2X+blQy+8Y21bdgXW2nFeVuzqq9cnUjurqq9efnam623GVSHgDnB8AcS7dlcxvWreuxxnxoKB+XL29AZ1e5I3o4clU8oBIAtQEaBEAC4HIvfMtz/68A+ASAwwBMjoiNAK5G3zn/AcDnonsF7a37EgDzz/pk5eRv+Mmv/HlcGbWFKkkWQNOYjfWDuH3/NZw/W4FTJ6uvt48ASAC0T+iVagHMzprC5k0tlsXPQMDgYBGaW+rR22fyXOqgfXmWFo93JQA6hMvJmcDmTddQV9dlJZo2IHjh4kb09JQueNoIAZAAaJ9MtAA616U1uIqqFt8vA/gsgAcBRHJFOD8mk+kGAL0L1bgSLYBzv4gfeLAZBYVTlhVwcjLT+poASABc6QCYmRlC/carqK9rs1765pixpqbN6B+IvvSVP5xUK8FKKkQAlMxRkR/aWdPYsrkdGzd2WPubjWv4/IWNMXsEaQGMFc+Xy3Y5jn0zjbcHtwSYKzFSvROK6QJeSQvg0rTFWO9+Jgp//dFbGjoyZoXO6P//NIBvRaOCF2zVygVAoHbdCO462IpLF8vw4fu1BMAEBOxr7yH3ALo/tco9gCaqt25DO7ZsakFWVggjo/lourwZPT02ix8BMCEoxf1h1e0BlKZSfCdycibR0GD2gXYhPR3o6i7FuXObMDYWf4oLLYC0ANpnEwHQ+XylmgXQbPY0bl6zty+SkTSy589EBh8FYA7/NCec90TdvB+4vd0kAJRzsmmjb4VBcrzwlFastDDuvf8KSssmcOSZBoyNZcvJodWneWjaZlGWaqbpAiOUdSmCTBK0TI6MVkKG132B2usCd8+qYcxt5s/93Vahx0ARk7R5+/ZLKCwYs4I7mi5vQken2bogNTjYZctrbQq+0ooYLaesUV1MggDHa1HVRk3ghVWReEtNO+SLE93X7BHcurUV62r7rJyPzc21uNS0HjMzkaPm9OljdGJqTuRIfFshgEZ56okcCJFka6fIjpJO3iOtg+yXZO3UjhctgKrHn4USKbCyARCorBrFPfdeRcuVYhx/Zz0BUBrIZYgMJgBGBsJYdLY1Nlm54Ew6lytX63ClpU5OYn597Lwim/wUe61Nhw6LWTuVNaqLacBLV9lKA8A5Vc3JIjfsbEZx8RgmJrJw9lw9OjrKAdsxc4moMPBIU2m41S5V58VBgpI64pkAuJiHdlWX9br2repOB9n4lQ6Apq8H7mlBdfUYXnx+M4aH8oTuay2Kzku1IKNLmOyjHbQAOgZHPjNYJGDnteqVwasFMIyNde1obGi29vl1d1fg/KUGTMwlAF7wIVU3TvWoe61Nh06qJkQLKWtUF1v7ADgHdnV1ndi2rRXZWTPo6S3GqZNbMD5uHDqxH6XFShgyrUVJHBoCoEPRIMGWFsDFrDHxZb2ufd7vuMauXA0AWFI6ARMQ0tFRgDeP1RMA7QrQArikAJiXN44bd563ToIYG8/F+fON6O0rX0Rgb7DLltfalBy2iBVPWaO6WKoAYGSDvwkU2b69FRvruhEKpePcuY24ejV2GwEB0D4ZtXslNcBm6g6yPnVdgjtdC+x0AS9ieWJRpwKrAQBNq2/b1476TUN47ZV69HQX2Driw/IW6JFpPtpBC+AqsADGW/2uXl2Pi02b5929ahJTF1QtWV5rU3KYqg1zlixVYeWNdUmedZWtVBfwnF6xL3yTTHr3rsvIy5tCb28RTp5siFoDCYAEwHgFCICqFYeFEikgAqBkY9Mej6YIPvCSZzA/fwoPPnIZQ0M5ePkFc/DJ/GtvSVLDaAJNtAEEopZO0WUXqBIytWOoLqdwlWphWryn9kutTtKMl7TTrA1pyMudwI03nkdZ1Op3+sw2DAyY0x1iPkoSE8dV04zFlLG3RcdJi7mDo6wIbFKN6ra4Fwwc7MT2SuCllUoJbbZiGRkh7NhxFfX189bAlhZzKpL7JAt+X6DGEruY49bitdNb5wTN1e5p7Rhqx0tZztZkrWVPO4YEQO1zyHKiAqsFAE3jd+3pxLbt/XjnrfVovTr/8iUAur8UjH6BpouRYHeNAmB1VS9uvOGCdXxby9V1uHgpxupHALyuAAFQR7s612AEMMrLh7B7d8Qa2NFRio8+2oxQKJITNdFHCw9qGFFG/Nrz4Jn2aay4BEBvMGn0JQAS7HwpsJoAMCtrBg8/dgmh6XQcebYRs7PpVt8JgARAx0MgSrI4C6DJ67d922VsrOvA5FQWTp3ajr7+ssTPm24YQAugdslKXQtgbMSrSSx+001XsG5dn5UK68SJRgwN2bfBzGtKABTDgB2TTms9VoOyIvFzkHURADX2cO1ak6LlVhMAmiFq3NaHPTd34dRHVTh/zrhECID+LHvOia+KjF7jFkDj8t296yyKi0fR11+Ck6d2YGoqe+FVggCoW0XduS5aj3tB7Utcnd9PNOJp3YfBWwBjsM46Tu6GG65aP3jPnq3DlStynkkCIAFQ9yCu/lLKJXf1dzRZPVhtAGgWvwcfuYScnBk890wjpiYzaQFU7LuMgLLucUl1AKyo6MOuG89bLt/LzXVWUmfVb02dvLQAunMdATBBZKjJF3jLLZdQUDCJa9fKLJfw9eTRc6opLFGWe1Yqp95TJ7yRPF5LFzBdwF75Rrnkeq1+7V+XV1Qe/tSv/UlcR70EaSyklKM+KW3JIk7fWL9+GHccaEPTpVJ8cMIcEad07anvq6zPdl+1bpJYqy4wRIx4cfQs+Fx+uvuKErvOsTDqN17D9m3NmJ7OxEfG5dsnu3yVLJ3gsViCZWsZgkASHF+hWkSVzOI8IkOMT1ASppz0ztHewK2MivsuZMUzP0x27WrGunX9GBzMx7vvNmJycmHr9NLAnhIKHYIqLaxqwFTWp06/4uyX5qziwC2xQv//4Wv/UxsAc0JYSn6WYCVd27quRgA0L5p77m1BReU4XjiyBcND8edoRqxdwrgRAJ2ApiQZzbF3Ml9pgc0bdFsdUq4CC8Go2e+3c8dl1G3oxMhoHt5//0aML5DUWSkbAVC5fBIA46HFHR7C2Lr1GrZta7dOEHn33a0YGspPqDYBUJJGaXnT/siwTWL3MYy0ST02BEDBwKBcYFhMVmB1AiBQWjaO+w9fQVdXPo69YpJDx1MAAVBHRd7dwjqwWw0WQJNyY8/u86isGEBvbyk+/GgHQjMLR1oSAHUvVO26SwBcLABGlK2t7cWePc0Ih9Nw4kQDurttqYmiA6CGDF8Rv7QAxipAANQ+/d7L6d5y3utf81euVgA0A3Prbdewacsg3nx9A661F8eNFQFQ92ikOgDm5E5i781nUFQ0hta2apw914hwOBJdvtCHAEgAdCigthS5a7cYeCgrG8Ftt12EyZJw6lQ9WlqqnE1bkv1+BEACoNvKGezfdW+5YO+5pmpbzQCYkxPCQ482YWoyA88/13A9LYwZIAKg7tFIZQDMzZ3AbbeeQn7+JC5crEfzlQ0A3OEv4fxSrwy6sVFXJxXkHkB3+RR78UwlK20PoAQZ+fkT2LfvohUccvbsBjQ1mb3R8x9aAN2hOzLWuqTX3APo/ngtRYklWEmXohvLdw8JALV7ufRBD7Zh0qYQUezZ27q9F7tv7o6mham4LqQqkjVRZKzXHHKK9loNFMsJc8DHGb/iPZRmKxUU+uiDyCvKtqkDflwCPvLzxnHbbaeRmzOF02ca0NZeExka/YZCacA8P8jq7nu+Q7AX6l22uhev5HmUr1QEeAQNdkJDtBY6OTmyWKHrALndMzt7Gvv3X0Bx8TjOn6/FhQvr5rfGKAdMD4q6PuhAyfsc0UcQBwd2WlDU9D1RXZoE2uZaBoG4PjYssJACqx0A09LCePCRJuTkzuDIsw2YnIjs3SIASkEVut9Lax0A8/PHse+2U8jKmsbJ01vR0THvMiMA6tZLJU8kqEz3MiYAxivgBoCmdFZWCPv2XUBp6RguXqzBuXPrIxCoHDACoDaHoPscJgDq1hI/pXRvND93WOPXrnYANMNTu34Ydx1sQ0tzMY6/axY8AiAtgHKQioG/2287heysaXx0cjs6u+atxrQA6hc7JU8QAMXUJTrrmb2UBgDNNSaoaf/+iygrG52HQIXhNLFlS4iWFelcKucOVL5c7OLFyY3upQVQv04kuyQB0KfCawEAkRbGXXe3orZ2FEdfqkdfbz4tgD7cx2vVAphn9knddhLGVSbBHwFQv5gQANVE5RBV9lC716cFQFPO5AqMg8CzkR/Gbh9aAN2BlQDoNouW7u8EQJ9a5xWVhT/1pfhE0Grrkcd9YPq9g0LnEoBNYeEUDj/chKHBHLz0wmZxM7+/wBBnW4LNjSe4bKWxDTphtPIeDteoOs+ieANBTOkrXaoZTSLA7Owp3LH/FPLyJvHhR9vQ2Rlv+Zu/u/aeyvZqn8/VtpK580rCnouuMdGipP4yrqAeTt3deNbLXpsaRUosLHbB/b5q9+EC9VsQeIexBI7h1KkNuHzZFh0sjaEPi6VXnYIMvIjAmW7eBA679hv70VIZtf0PX/8ZJoLWrrEs51RgrQCg6dmNu7qwY2cf3n+vBpebyh2dJQB6h8zVDIAZGTPYt+80SopHcer0FrS1RQI+5A8BULVOEgAFmby7Su3sGAQAmgaaPYEHDp63ooPfe2+TdXzc9Q8B0DmGQUJbkHUlIFsCoGq1YqFECqwlAMzImMVDjzQhI3MWR56NnBMc+yEAph4AmiChvXvPoqpyEBcv1aGpye3UJAKgarUkAK4KADSNzMubsiAwOzuEN99sRF9fYaTtBEACoOphX7mFVpvjZMUpuZYA0Ii7oW4I++9sR8uVEhx/J37fCwEw9QDwhp2XUV/fidbWKivdi7u7mACoWqQIgKsGAE1DC4vGcPDgBczOpuHYse0YHc0hACrdrNo9mw6XMi2AqqXETyECoB/1zK/DNbIHMNavcdfBVtSuG8WrR+vR011w/U8EwNQCwPqNHbjhhmb09hXj+PGdyiTPBEDVkkIAXFUAaFzK1dVD2LevyYK/Y8e2YXpKOO7QD7R43CvJPYDaqGVnObqAVasVCy3kAv6kLQhEDtJw1iDlTNMEeKjPh1UnVo5vW37+FB56tBmjI1l48fkt1jmZkY+UG09QRn3f+PrkZL46oJA18Q5s2mTefpJS25VTRQ9bw6Dsl0sy57n7S9qVVwzi9tvOYmwsF2++dRNCoURn+7r/htQnadaNdUqtRsoN+ZImumAOJYmKcRfuwRiRdvnYBWZLIwAAIABJREFU2ydhoqZjSQKxzZu7sWt3G7q7C/HWG06LuNra5RH2LDXtNxH7qo3GFWeO48ugIVPuvq3NUr/UfXX2S+rDdxkEklLLaeCdNRbAtQaARqSdN/bixpt68NEHVbh4YS7ikwDomEBaGFNQ0EoBwNzcSdx110mY/X9vvrXLgsDEHwJg4ItKbIUEQB2M2EslCQDNbXbvvopNm3tx4Xw1zp01p4XMfwiAOvAkACZ11VBX7r56q6tKzYJrFQAzMsI4/PBl5OTM4PnntmBiPIsWQNGiprTGrRIANNBnIn7LykZw4sQ2dHU7o8Hjn3T3JUTR9WiVtAA6aUdnoaEF0KZAEgEwPX0WBw6a00LG8eYbDejpLrp+cwIgAXA1kZD76r2aerMMbV2rAGisUTW1Izhwdyva24y7w0R/0gK41i2ADQ1t2LatFVeu1ODsOZMP0u3jvoQQAN00XODvtACuOAugaZDJh3no3nOYmUnH0Zd3XN8PSAAkAPp42pf8UvfVe8mbtLpuuJYB0IzEvjvaULdxGG8e24Br14o1/JNgj5pk3eEewFhBl9sFXFIygv37T2F0NM9y/c7OpiseRvclhACokDFREQLgigRA06gN6/uw97YWdFwrxrvvmB9LaWJmGCmzstekz+a+3AMYPyW0WnIPoHORcV+9faxdqXBpBAD/OK6r6oAE5ZvRAQbqIAthwOVQXgHsIlMjJzeEhx5twvR0Ol54bgtCoQxb2QCtguIpJdIs0rkK1eMg3iLYe9hvoYU9dcCP0AftPcyLyyR7PnDgJHJzp/DGGzdhZDTfOSeUQSW651639CgfEd0tV2EpTbxDpFvKYA67BgEHd0gSa49gU+0LSzCGqnv4CCCQIQ7Ye+sV1NUN4MMP6nDlSoV4jIYWUMRgGUWuQXXSa+2PCdGIJzZEB+fqORZfUDWmFhDrrI6STt/9+s/yJJBVuC6umCavdQA0Qm9p6Mctt3Xi4vkyfPSh/RQIAqBAz67zUwtnSwWAu3Y1oa6uB2fO1OPKlVox3Z+ftnj97UkAdJ1K0QIEQFelkgCA5ri4e+87h5zsEF55ZTtGhnOcUBRkxK/F+jZQEuuXUqOIeO78kgDoOpXWSgHdz/C10tsk9CMVAND8Mr33gSsoK5/Ayy9uwkB/XoySBMDVDoCVlYO4/fbz6O4uwfHj2yN7PUUDqM4qqnvMdEsPAVCnJi2ACgBOAgCa0SkvH8GBg5cw0J+P115tdOyVpgVQYkx3qx0tgNpn33s53Srsvf41f2VqACBQXDyB+x9qxvBQDl56YXNycgPSBexkSR9uV42V0UQ03n33SWRnT+PVV/dgcjI70gYC4IpYu+gCVoBdIjegfQSTBIDmNjfd1IaGxh58cGIDWlrm0mZFGkAAJACuiMVEaAQB0OfIpAoAGplu2NWNnTf04tRHVTh/Lgm5AQmASw6AjY3t2LatDWfPbkRzc0xOMwKgz5UhmMsJgKsDAI0r+P4HziI9LYwXX9iB6en5xOkEQAJgMKtB8LUQAH1qagHgF+ODQMSTGpS+LN1JIBLKS65Y3fBq7mnumJEexgMPNSO/YNoKCBkdyU5wNKyyLbZi6qANsVs696T6HtK88DOG9voCTCBtGeyUbYtthkllcc89JzE+noPXjt2EcHg+6leeOTqNHV2VzImivn4eRt1c93OHYK/VgY14T+WlIng4rGLSHYT9Y2IxZUOEa7XuvUTBF44qFaSc7Htu2NCPW2+/iubmcnz4wYb5JiqDL8QuaKyWPvbsqQNvlKdyyNPE3d0bsZTaPktwz+9+g0Egwa5rKVZbKgGggaeKyjEcur8F3V35eO3oRjHli5wv0B0e1HBGAHRaCj0A4K23XkRNzQDeensH+vriU/wQAJO9kHmHJ23ALwEwfgyTDYAGYe460ISKylG8+kojBgaikfQEQMEEqPiRQQBM9iKk/Wme9Has2hukGgCagbr51g40NA7gxLu1aG4ulcyROkChBTBOJ5lrdZatxVoAKyoGsX//BbS3l+ODD83G9fgPATDZSxIBUKWwjxM9nAYlpeY+7llQNI777ruAgYG8+YAQAiABUDXZl76Q7u2y9O1aNXdMRQA0+10OP3IZWVmzeOHIFoyPmWPiYj90AbtO4GV1AYdx4MAZFBWN4+jRXZiYdJ71SwB0HUGfBZQwIt1FeSktgEttAYwEfOza3Y6Ghl68/XY9Oq6VJAjQVqZpoQs4bhC1VlxtbkC6gH0uY6l+eSoCoBnz6poRHDzUiq7OfBx7daMtbJQA6PpcLCMA1tb2Ye/eJly+XGMFf4h7VsUOuLvxpctE175c0FW2xAVW229ZJcURAB0KyAY1dz218OBn36EBwJycaRx+8DzGx7Pw8kvbEJ6V5iYB0GGhdZpsnWOv2OtpLiIA6pbS1bZq6nq1hKUMAD7xxT+Kt38t8rQNF+MZ7C9QbdCG+I6V2uYRRvbe1oEtDYN4791aXLkc4wqWOEGjiTryVAJMJVGo76GrT+169ejuVo+hcs6np4dxzz2nrJfU0aO7MTVlt94uUJF2njiqUC4zymK+IFOpU7KLqaxziRrhzjrRK90LeoWphE1TvqBFrtVe69Eqpr+nFLTgvHqh6N4dOzuxY2cX3jdpYa6UCSAjtEbTL4tuXNEpAQBp+6DYnxehLM+AprlWGz0tg72ubf/4jZ/jSSDJXuzWcv2pDIDGFfzQo83IyJjF8882YHIimvqAAOic8isEAOvqerFnTzMuXFiPixfXL+7RJAAuTq8FShMABRhZQwBobZN56BxCoXS8+Pz2mLypkX57jvglACqhkwCoWax8/ObWVL/2y6QyAJrRXb9+BHcebEN7WyHeet2kPkhwigQtgHEPgzbiWXqC1FZH51KJQ4dOW9a/l1/ejVBoPleZ6kklAKpk0hQiAK5tADS927a9Czfc2In33q1Da2t8sBwB0B3QaAHUrCT+yhAA/emHVAdAAzK339GGjfXDeOetdWhtKZFPkSAALjsAmiPf9u+/iKamGpw7Z/ZtLvJDAFykYImLEwDXPgBmZc3goUfOYGQkB6+8HH9EHAGQABjYYuKjolQDQBPu+F0ANwIYB9AF4N8DuGjiGgD8NQDzpE4C+ByAV9y0JQCmITvbRAU3wewve+HZLZiYdO4rk61WDr+oQ26tpUxOg6cLWpDvIdrenO3T5t9bAS7g22+/gKqqIcv6NzHhPLTeba7rg0XsNSmXGWUxeWR8XOza8eALEADXPgCaHu7e04YtDX147ZUt6OsruN5pAiABMPhVZfE1rqZVcw+AnwBQB8Cet8LMpp9RdN9c9wCAp6NbaX8lWud9AP4CQAuArwHYB+BfAGwBML1QvRYA/qoiCEQdfOAOLRKwaAND1LCjtfZEy61bP4y7DrbjWnsB3jxmhshOPJrADfe+m7HwB4U+wE58WoR+ibdwf9TUrl0ldMbWV1AwgXvvPYWOjlK8954z758T2XRjoXjmEiQLd17prtBCd/N3taofgRZyD9BIdDv1ldo9dfYbiTEQ6rs6mu0n+lbSQFWfNpeffBSGsg/umhQWTuKBBy+gra0Y775dP1+v54APU0X8ff3BpPeAj6BPEXH8KJLk9aGbNG/+8XcYBBLospakyn4ZwJ8CGAVwFcCU7T5mqtzq4d63A/hnAJsBjADYCqAjWs/bAL4C4HkCYEQBmX/mv719fzvqNw3j+Nvr0HKlJF421Tm/OuggAOpgJxYAb7qpBZs2deONN7ajv7/I9VFR/1Bwrck6p05TymdWet09VA1ZkkLu8EAAlBVYTQBoenDHnc1W2qwjz27H+Hh2pFM+QIYAGD8v/OwVJAAuyWLn+ybNAF6MumuNezaoz98A6APwDQDtAGL9Yv8E4JmoZTDh/WgBnH/xmj0vDz5yGZmZYeus4LgE0QRA1zmbLAtgRsYMDh/+EKOjOTh27IZEKB/XPgKg63D5LEAAdAiotFiuNgCsrBrGgYNXcP5cJc6criUAJsjTt9QWwOKSafzfX/63TAPjcyVbissHAHwawAsB3sxY9z4B4DCAvEUA4JcAmH/WJysnb8OP/8Z/j395irn2nC3XWrIc3lTBVrLcLuC53tXUjFoJoq+fFTzXVgKg9cO9cToX1aFsdGVO4VLWxLxZNQxsnc5D9UwWujKmcSk75m+WxQBonMqN/D0z5Py78GDMzYn163txyy3NOHVqI65cMVtd3T8EQHeN/JUgAKYKABpgfeiR80hDGM89uyPyA4wWQOfw233KSXQBr68bw6EHevBj236LAOhvIVuSq/8SgLECmv15QXy+DOCzAB4EYODSfIx72WyOogvYqLHIPYCxg3LLrZ3WWcEfnqjGpYvlkT+lAgDOQVzIQNo0LmWNXwe88pksfL5vAypnsjCTBmSEgZ6MafxRuVl/YP2taiYLoTQg0/wtM2T9rS8zhPJQZuTaUGb072noyZzGH1W0W3+/Dodz943C4xwA7tt3ARUVw3jhhT2YntalfiEABrHMLFQHATB1ABBWOpjtO7px7NXN6OkpJABqADhJAJidM4PHnriGjPQwPrPrKwTAZC91AdRvNi39PYCmqBVwDtpiq3aN2I0WNtY7EzBi4K8/poJYyDRBIN+P7g1cdBCI1F+9hU642gZPWleh/p66vXdaKMzIDOPww83IywvhhSObMDKcowrcWL5IXnHEnF8uEMhTPpOJL/RvjAJeGBnhNAvw/rC8FX1pIfxO7xbrbxkx1ttZhDGcNmN9UxjOQLrtbwPpIfz30mv4nwdrYQAy9toQwujOnMIfl7Xj8/2xcBgDj1kzyMmZwuHDJ9HZWYLjx+XgD7e9nYt5fgMFx8XcWH7o/NYQzPVK12YwN4upJchgDnVQhdALZf+1e7kknby7hXWnfkgH+srdkuszwSCHH76IliulOHF8g3VmsBOAxZ65c7IGpkwt2jGUOqadSz5OB3GMoY/2LjQfDhzqQf3mMbzxagV+/9/+MgEw8IUn+Ap3AjB78nbZqjbT0ry/zH8zFLc14akmiMSA5HC0vNlTeAeAGgBmT6CJ/DVBJiZC+CW3OqU9gKkOgAYUyyvGcO/9VzHQn4uXX6wHwukCUMWjx4oGQGPdCxkXbTa6MqZwMWrds4AnDHy9d4v1NzvgzSCMWWtzqdB/t8nl8ndT92jaDArCGSIcfr36KhoaOnGwfBLdH2zGhdFs0XVMAPQ5EG6XKwHIrZpF/1370tZUrH0Zy3SmucMioEhgJ43GalDyCGLWZYnB7tB9TSgqnsQzT+5AyLgB7B/RKCylS7G/BaVIXqkdKyfiVwXx2jm3COis3zyKA4d6cfVKHo4drcQ//s7PEwBVT+fyFnozCmi/C+C8EAVsWvfWcjSRACioHiW5m3Z3Y8fOPpw5XYGzp6pWLQAa696vDtTHWfd6M6bx/xV0oXo2B3smC7FtOk+2crpMSmMFNJ9Y69/cJcZKIFrUFBPdWAj/vKwDnw0VonA0H9PhNGQaq2Ss6zhaDwFQIaifIho48VN/omsJgPHKLDMAbmnoxZ5bOvDu2+ZkkGICoINjbRM2YADMzw/hkU90IDwLPP2DdZiczACjgJOx8ARf51h0z94Pgq/aX40EwMQAmJ4+i/seaEFJ6SRefbkevT358YUdrm1pLHTuab3rUZOP0LQjWi4MfKOvAVUz2ciMcdFq4Wwas3g/ewR7p4rirp/raciyD6aJfzPX/nNxN35yqFr8+5wbKREkGguhsTvG/j3iOp7G16tNystoYEkoy/ouLvBEmbrFPmL6cfD33Kmu9tgHVd2LKUQAVKmld4sK7KTReJkBMCd3Go9+7Dxarxbj3XeMM8pOQJJMtADGqiIbSSWN4r9LSwvj/oe6UF07iaMvVOFam4n7BAFQ9WQuf6H3APyXqBt4+VsT0wICYGIANH8pLDKJUK9gaioDLz63BdPTMZ76lQKAJgGkFYEb695NQ1oYeGC8DD81UpPQQteTMYW2jEnsniqKc8POqWIg7ttlrfi5oRoHRFowlj5lsaYdMK2/ZUzha1VX8LWeTagKxQOo+ftAxjRKZzKRuUj3smUdLO3AJ0cqUBkygSfh69bBP54LLPEITwRA4XnQwEkyVjVaAONVXWYANI05dP8lFBRM4+kntyMctv0YpQtYMV6658u+B/DGXYPYc+sgzp8txHtvRwMTCYA+c68mY9GS67wXgDlu42cBfLR0t3W/kwHAT3zhD+MKysEXzrq0aWA0QR/6gI+FgW3ur+oXuSJaeHPDAG69vQtXmotx/J111xvguIf2pA2pnNgOd+uhCa744uCmiHsXYQvihtJDOJc1hpumC1EymzhqdgIz+IfiTryeO4hv9DqthHMQ99sVl1EezsQX+uQgESPIF/rqxACS/syZ+ShgK4I4NsCkDV+wooedcDieNoN8pCEjLG+NNX016sS6nucCS75e1QKk6xIrO0p5BMdET5pXF7hVn64L7g+53xLeA37lfXF+2mODIHXTfECsH8ueOnBBkUJE3w6F1c0aA10gR+x9d97QhZ039OCVlzehrzfeI7KYoJLYKSD3a5n2+0lzcxF79OL6JQajaPc7ztdUWj6Fhz/WgaHBTDz3ZA1mZub3Y//T73IPoJ/lZKmuPRM9q7c0en5vbPTu3JN401I1JvY+BEDNUWhh3HV3O9atH8Wbr69He1vkJIplB8Aw8Dv9Wx0AFTu+C+3RM9a9b5W14GL2OKx9gv3x+wStKOCyq+jLCF0PVTKWRmPNMy7XuUCSuXeJZYW0p5CZA6oEOQSvp4iJhcPMafxrUTd+aXAdMmY1sVHzPTZ9+k5FGy7lTEbyDtpSy9ifMQKgYtVRU5azLl9nBitexuqmEQAFNRcPgGVlJjiuGefOVuDMqficnATAeInFSN5FWnHN+fQPP94Bk/TZwF9/X/QkluitCICK9WsFFDEpWtzWqn+zHO0kAGoAEMjJNaeEmFSO5pSQzZiYyFp2ANw6nY8vD2wSXajmxft8Xh+ezevFrw1uSuii/c8VTUIy5xzLfRsHeE5SckxXz8EYc3AYdWGbvXzl5SP4SutW5A8WwiSYmfsYK9+YsQ6G08V+G8vgm3lDaJzOc7iHr+cdjGk5AVCx6ritXAtUQQBUWrJWiQXQrH+PPX4eY6NZOPqSSTgx/yEABg+At9zej503DuPDEyU49aEz8IYAqFi/WCSxAgRAHQCa1DDr1g/jroPt6OrMx2uv1CHNvnctGS5gK31Lfsz+PhNPBOycLsBPj9Riw0yuOLgTaTP4h8IOvJ43aOXgs0cBG+ved0pbIomYbR+d+1yvm+r5s1XX2NiJW+sGcfP/eBClU9nzyaeNdbCwF/9uoHbBvYP2IJe44JGYexEAFaNDAJRMmwrhFpG7btUAoDkbuAU1tSN48gc74tyRBMBgAbB2/Tjue7Ab3V05ePHZasyaeDvbhwCoewyXu5Q5sq0ewJ8KDfkcgCsAnlyORhIAFwcyt9zagYbGQZz8sBIXzlXGD1nAAFgxk40vDsXv7xtOn8FwWgibZiJRYIk+lnu39Irl3rU+1ikfsSAZPeVD3GbovvdQ2qDm2QJo2me7eN++JlRVDeHZp2/GlgnT7pgj5syROt2bLAtfbGSzsf4Z0Mu2bLPO1kwjjO9UtlnRwnPu4aCihxONA/cA+qBHSVTuAbRRhiiS40uvcBZZOuLHcOu2Huza3YXXXqlHT3fB9Xt5vQf3ADqfkZycGTz6iWvIyAjj2R+uw+hoJiSXMgFwOahp8fd8xwTsAPgD4dIvRlPEmGTOS/6RAVBqhgYKzIlpYoRDXIWaoBCLCcQziRcHbLE31lm2Fj5GLiNjFvc/2ILCoikcfbEe/f3zIKauXzwL2aZ5GPjdwW1R162chPlU5ghqZ7OtQI/YSFqTmqU7YxpfLbsUB1b6+Ab3sfbVV3F6xd4zjIcfOYnR0Rwce227+Ewk2jv4Wt4gnhipRI6QuNsA4vMF/bh5sjDmWLr4Y+uk02KUT4P87OpFX/Jnf0luqNx7p8ZEZX32vukDKJSqaHO8eQi0mPvB5myJTiVRIu3eMwV0myT5h+67gtMnq3DubOyP4MXvKYz0VekmF4MqJJWCTSKtOqXF6ob9vu7pXeSxDuPQA91YXzeB11+pQEtzJNhG6j4BUPm8LnMxc2rHp6LHwNmb8gCAfwFQshxtJAAKqrtEBheXTFoQOD6eiRePbEYoFAE0X1BkYy5rf9/QFmQJKVJMYMdfF7Tj1bx+VJgo4KHNcVHAJrXLt0taIsEbMR89iywvABYUTuD++8+i6VIVTp/ekPixEPYOGsveF3vrRN3mKjL6BR49nKiVetGX4/FP/j2VwKZDmwRvQUUvCIDK6FMFAJr8qI8/cR7d3fl44zXj2Jr7EADj5fMGgNt2DuO2/f24fDEfb71eMa+uIC8BUPHwr4Ai5uzfXwLwPaEtPwXg/wEgpFZPfssJgIsHQHNF47Z+3Ly3Oy41TJAAeHi8HJ8ZWy/m5jPpW/6+8BqO5UaOlE4Lp8XvE8wcE9Og6FlkeQFwQ10f9u5twfF3N+PaNRM47/KJNx5a7mF73kEDfeZfopyD16OHc83Jiu4fdYYWvejuN12NJQiAzlHT5DdU5tRT8FqkSIAWQFPdPfc1o6hoEk/+wFjo554GAqBfACwtm8JDH+vA2Ggmnv1RzXXjQoIhBAFwdSyKzwIwmyUOAdbRCXMfYzp6BYDZ2f/wcnSFAOgNAM3OmAP3tKN23SjeeasWV1tKgrEAhoEDk6X46dF1yIecw8/Ayh+UNONiViQgRJ+PUTvDlhcAb7ihHY1bu/DSizsxOioHucT1xNZc4x42eQkrQplxwSPH8obwxHAFsgWr6mTaLL5b0oU38ke8pY9JJC0BUDXpaAG0KbDCAXDPLdfQ0DiAp3+01cqIEKVMj7BLF7ARLiNz1sr3V1QcwvNPV6OvNydOT7qAndNL/UNctQolr9CdAF4GYPKImJQw7QCMb+vnAWwGYBJFv5282yeu2QLAz38nvoDkAlUHOLjDgxhAIO73kwZcqn959gXm5IRw+OEryMqcxQtHNll71uyfxVgFTULknx9dj5tCkTyDcrLjWXSlT+GrpRfnZfQcyBHBR0eblWMtdNZX/+cu3n9HEyorR/D0U7sdpw1o94+arVeN0yYPYDa6MqdwKWvC+v+J3MPGRXgsd8g6UaVyJhOhNCAzbNsf6OUBJQB6US3hNaq0MmqaFHhFabH0kkT5+t1U7ZPch5IsHq1upiolZEqSbGnswy17O3Hs1Y3o6owGgmgsm9Z94wvKzfDTL+9Aqd0qIO8LdIf4ha7bf1cfGraN4v3jJThzUjpr2dmvf/q9X2gDIJzLF+hjt2IrWy0AaAS8G8D/AcAEexjLn7EEvg7gNwC8uVwKEwA1wJo4MKSyagz33NeKgf4cHH2pHrOz8QEbCQEwDGwz6V1mc9CdPomG6QJ8cqIGOVHr1LHsfhzJ7cH/MrIRlbPZ10/5MEevfbv4CvoypuenzBoDwMMPnraO3Hvl6A4BTv098pJ7ODZljJw+ZgrW6SJebk0ADHRpIwDa5fQDSjqglACwonIUh+5rwUcfVOPihejRZATAeEHFWBQJd8Oo3zyGA4d6ca0tF0dfqHQesyeAs/mKABjo8rIklZmw0TIA5jSQaI6OJbmveBMCoD8ANKLecFMPbripDxfPl+HDD+Kz40sAWDGbhS8Nb7HAzvwKiE1bYgDvrwracDprJBKQGs0DWDOTjU6TnDkzmr4ldjTXEABmZMzgY4+fRGtrKU68tylYAEzD/LF0oflj6UywTEfGJPZMFSZIHzN3usjE4h9UAuDiNVvgCgLgygDA7OxpPP7ERVy5XIL3jkePxyQAegLAgsJpPPrxDoRm0vDMD2sxOZEhRvxKXxIAA11eAq3M/CzqC7TGJFRWWlUS/qX//b/gymXDpVGSoAvYqfQCkcFpaWHLClhZNR53VJypxAGAYeD3hrajatacfztvLTQvttG0GXy55Cym0iMrqcwOOmBdjOvZ3ln1fR0XCrJJZrMFXMwlJWM4dO8FnD1biwvnawIHQKtC4x42x8TFnDxy13gxfnqwWkwfM5E2i38s7kJX5nR8PkKNRZAAGOiqRQBcGQBoHqKPffwCRq0TQcwupkRHC4tmsLhOpLIL2Bz19uBjHSgrn8bLz1eh81pkz7M2lQ8BMNDlJdDKjI/OuHh/AOCHAM4HWntAlZVXF4f//Nhvou1qLt59s9SKPpLIQwsFcu4+d1LQXbeIgAdJHxHidEAlahJzj9y8aTzwUIuVuPPF5zdhdCRyZqMdxIzb99eHG8RoVCu4o+gyLswFd2j34q0hC2Bt7SD27W/Gifc2orU16lqK0Vm9B1Ac/8QPTeNk4v2BJnp4KD2EwtmMxe8NJAAGtFLNMYZiA52iSKJGaXO+pfoeQNP/+x5oRm5uCM88tZUAKBGwwgW8785eNG4fxckPinHyg/lMcARA3bKh+Q2uqyn4UmavnzkBxPzbHQVAA4L/GgVD4WCX4BvhVmN+cVn4d//pq9jSOI7p6TR8cLwYF84WOoMDRKugTn7HS1sJNqsNCqurx3D3va0YHMjByy9sjO4HjO/sE+M1+ORkTVweurkxMuld/q6gHcdyzO6ACD460FkneSLzobM+0ULnfhPtDwJx/i0ArJu39GD3nna8fqwBvb1mHrr/eFCz3kIwFo6cLmICcWJPF5mrO9HewK9VXVlwb6Cvk0DcHt5V8HeVxc70wwe0OWTQJhYW9Qt6T510E22Ah+3agFO5iC1TB4aEccddbVi/YQTf/x/bI3vWtNfab7xcCZ61SbplGnPKZ48BcQkoqt88Gtn3156Do89Xxe/7U471937vFxkEsgrWQWMjn4NBE/FrEkM/FbUOmhQx5v8vy8fsAfz457+NdRsmsP+uARQUzqC7MxtvvlaGkeG58P4EQRBK60aqAKDhmuv7AS+U4sMTZj/gPO3snSrGL4/hfBx2AAAgAElEQVTVIxsZ4lhHLIBN1y2AqQiAN9x4DVu3dePF53dgdMwZVa2NxJB/YywMttLpImNpsygOZyTcG/jtilZcykm8N5AAqCQ7ZTHVIkkAFOBEJ7D2ODdjKd1zcxe2bu/H0082YHwsiwC4CAAsLJzGI3P7/n5Qi4kJ2zuBAKh61N1NFapqkl7I7GY35/2aj4nvfhTAxwF8DIAxc5hcgMYyKJ0VnNTGzQGguUlm5ixuvnUIO24cRSiUhg/fK8b5M4WRXya0AArGqPjpZ/6f2Q9orIBV1eN447X1uNZeZC2MH5uswqcn1lmWP3NUmwEDgxVzH/OdSe/yn0rOxzBO6lkA997Wgrq6ATz5w12YFY5zSyYAWmNhSx9TPZ2Nzw5XI1doy0TaDL5b0o038ocSPqMEQB140AKoWOaVUCAbNnXjsBgA3LqtD3tu6cbRFzeitzefAKgEQLPv7/CjnaionMJLR6rQ0S7kOlWONS2AiudmBRSZAfANAF+3tcVEAZj0ME8AeNwYkJa6rbEAOHfv6pop3HGwD0XFM+jtzsLbr5dhYEDIcUcLYNxwzeGa2Q9o8gMaeV45shk/0d2Ae6Yi+9nOZA7j7/Pa8bnRTY70Lt8quhyf3iUFXcB3HbiE4pIJPPv0TQlYT/ebz4sFUHr2FjpazuwN/MPyVpzNGXcElVyPp/KUO2apV4Hk3Y8uYEnbteEC3lA3hDvuuoa33liHttZiAqASAG/d34ftO0dw+qNifHiiVDhDWH9yCwEweWtXkDWb/X7PA+iOnvl7Lcb9OxXkjRZblwSAlnUqcxa7bzHWwJEIuJwssjapzs7Ov1q1G/JTyQU8D9GjuH9/N/Y+czdquiMHph/N7sXf5LVhxkT5mjyAMwXXI1EvmuPbHNSSehbAQ/eeR2bWLF58fueKAEAzTgvtDexKn0R6WhpKZuJPHfmj8jb0ZYbkU1oW+5Cu4vIEwLULgNU1o7j7UCvee7cGzZdLCYAKANy0ZRR33dOLro4cvHSk2vKuiYFHtACqVj2dOUBVVVILGQA006MDwAUAJnHSNgCXAHwWwPGk3n2Byi0A/F+/HV8iRtWy8inccWAA5ZXTGBzIxFvHytDbM2cNlADFfUiCDu6QM41IkQZCeyVtvEQLR4GuZjYHnemTGEEIvxHajLLJfJiX4Hdz2/BcTk8UanSRx0uSykUbQWzXSW39FQVOOCMPP3TOOv/y6EvbRABUu1SVgUaa565iJhOf76tD5cx87sCx9Fnkz6YjC+nW+Ma2K4QwujOm4BYgorl3ypTxtW/PrpIukENGM+/XSgSkP1jE3UWrPaVC3w5dXxPdt6x8HPc/aJJBV+HCOePhkCyb7v2SYzHc08eY8dOmkFFrpwQvsc0ug11SOoWHHuvE1HQanv1h7L4/pW5CZ7/3TQaBrIY10gDgXwD4dzGNNQD4+9EzgM1RcR8tR0fcANC0yexru3HXCHbdMmS5Nc+dKcRHJ0owMxN/6kWkbOoBoEns/GujW63cfub4NpPfzyhj9vtNZ4Rw4sE38FTXrJU0NfIhACaa6488dhrDw7l4/bWGFQOA1mhZewPzUB3KsvIBXsqewJ3jRfjFwdqFA0SyPSSPXo6FYLnvSQB0HQE1xIggprNE6mEMKCyawsOPXcbZ0+U4fbKKALgAAMae8/vCM9Xo6Y7dUkUAdJ38CQq404bXmoO9zuQEfCzqBrbXbII/zOeTwd5SV5sGAOfArrhkGncc7Edl1RSGBjPx9htl6O6M38CacgAYBr45cgOqbYmdjWbGEvTN0jPY8fhZZOfM4OXn6zE0ZB58AqA8O8P4+BMn0dVZhLff2ryyANDe4LQ03DVWjM8OLRAgUrxwgIjuCU2RUgRA14FeaQBozkJ//JOXcOlCKT44YZK2K0HG3lPRELm2LID7D/SiYesoTrxbgrOn7Of8KnWjBdDxjKwWAGwB8E0AfyY85Sb442+jx8O5LgJBF1gMAEZAMIwdN4xg995BZGYCF84V4P3jpQhNR6yBqQaA20IF+I3RrZYr0P4xkb2/X3gJvTU9OHT/VYyOZOGl5+sRCmU6h1HrilW6NtV5+rT3FQBIMxfV7bDmziw+8clTaG0twXvv1q94AFwoQMTA/7cqrlqWQn4UChAAXUVaaQCYkTGLT376Aq5cLsbxd8yuJiXIpBgANmwdwf4DfWhvjZzz61zYlLoRAFctAP5XAJ8GcD+A07Ze/DwA83cp663rouC3wGIBcO5+hUXT2H9gADW1kxgdzcC7b5ahvTUv5QDw7qly/Ox4HXKF3H4msfPf5rXhWE4fGrf14+a93WhrLcRbr68XEm1LTKizFOrzBerqU+2zU7j6Iz8IpBkq/25LT5/Fx584hdarpXjv+MYVD4ALBYiYl/VfFnWiO3sK1aFsdGVO4VLWhDaLjd/HevVdTwB0HbOVBoDmef3UT1xAS3Mx3n2bACgFc5RVTOLBRzsxMZ6BZ5805/w6DQVqcCYArloALAPwNIBbAHwXwHMAOgHsiKaGMUEgJjfgkn8iAPit+PuqgyDCaNw2iltuH0R2dtg6T/j422XWYdaxnxVtFRQUl4NUZGgxFsD/bWy7eHqESez8+wUXcSFz1Pp1vP/ODmzcNIKTH1bi/FnnMWfO2S0FreggTksaakCz3VYFiYkJUOxqBABP4+rVEpwwACh+lEZ/r5ZNNa9GblA+k4kvxASIZIYjQSFzFmGTKmYqbRYZ4TT0ZExbaWP6MkKq51zZU1VdfgoptvH7qT56rS4gQXMjPShJtel6G2Rwh2mFo81ydIOjwep2aE+9kKMb5CcxPYwfMwB4pQjvvrVOjmYVrlQdtyf9IFB2Vj3+SQz4MN3Oyg7h0Y93IjdvBkeeqkF/nzkeVDfP5T44r/3eN/8NTwLRLAoroIyhol8H8HPRfH9mNM0afzZ6SoiJCF7yjz8AjDQ3L38Gt9/Rj7r6CUxMpOOdN8rQ2pJ/vS9rGQAbQvn46tgOx9Fuc4mdv1J45jqLGZfJ/Q9eRXHxFF57pQ7dXfMayStsagGg0efxT5zG1ZZSnHivblUAoNXIMLB1Og9VoSx0Z07javoE/s+eRodVeC46+Lcrm1V8TgD0thyqAUCsngCopsy0MH78Jy/gaksR3nmTABirm9kqdeiBbuuELZM5o+ninIOPAOjtqZavWilr5GL7VA/A/BsEcDLgkzAX1ZYgADBywzDqN4/j9jsGkJNrIl7zcfytUkxOZqxst7CgltYCWD2bg6+ObkdxOAvG2mcmo3nJmxM+utOn8AcFF9GXbuJ/5j+FhVN44KGrVj7FF4/UY3w85rg9e1vUllhpyHWPxkqyAGZkzODxT5xBS0sp3l9NAGiTf+tUHr7YVyfuCzXz5P9n7z3A48iue89/N9AJjdzIkSAIRjCAOcchhzMczYyCg2yv7G8dZEtery1bWc8rWVayZFnvrd9n+/nZa1u2nGY8mTPMOecIgiBB5JyBzqH2O7e6gQ7V6IPuRmSXPnwcAbfuPTfUrV+de8JfZLfiidYa8TnlzWDEamIuwEOiWJvhvRg5rSQAUGmUeOPL1Tz59vxP/Hw9WltScfVSUUID6Dfs1asHUb16GE8eG3Htkv9pT3znIaEB5OwIiTJhRyB+ACg3odd7sGELaQOtwt7h5rVMND0zKnu++kk1Y7EBowTANE8yvmFZjAKPHoMqJ76dUodsaOGLA1ifZA6r5SkqNmPL9nb09+lx9lQJPB4lu5Aw+ZeZHsQsFdNkbPSm4Qh4TAM4h46AlR4s8g7+tEgfF5rz2Q4PfpbeNWH6OF+dCQCMbuNOAOA0AaBXA9janIqrlxMA6Bv1omIrdu7rQX+fRhz9+idPSBwBR/dMh7trtuyR8e3VNNYWbwCUwUPWBq7bOAC9wYOOdr34CrKYFbxfvX2dSwColVT4smUxFrmNIEeP7xkfozHJytJ0UneprytW9mDJsgE0NqSLSPrKHg/P1xEwrRvyAu7oIKNyUpBHr9lkBwfnPGuTcGSh6ibSABKc/H16B64YRgKOjZ9orCFLYLZsbgkNYOgiYZqjAcyCc9EGkHLHv/qJJ14v4IKEBpA8OdOcOHCoE5JHhSPv58Mc8s5LaAA5Wy63zGzZI7nyzrpyBICHfjfQCUTxWDCK40it1oOa9YNYWGWB06HCreuZeFpvhEoVRuMVNDpcKFT2guUtDY59og/a6F/K4vZ71krUuDNF0OefGJ7irmY47LyGzeahkrB9RzvyCy24eT0PzxoyQ+pQ7gHPCST+WUSCxYtBjgm47tArtejrT8Hli+URtcZjmjLeVLPr40zEhE4wEvCtvgrkurUBzkG+jCEWuGFVu5HuofRx0riDSFZLoIMIu19TvK1MAwHGprUL7j9PYCabsQ33lfVuvBd+mJwWAVUqy8urnz++CiFJFDsmQad34ZXXnuFpfQZu38wLo9xizEUsDh/MSVR2PGGOHbMNMmE5cKgLaekunD6ei64O/2DP3kGMJeahwr1vfC/hBDLFu9/8rn4qAdA3coVFNmzYOgCj0Y2Odh2uXTJNqA0cf7HzIGPaAFACPmMvxT5nnhDxf+ubcE7bN+ECmQjENFo39u1vhsHgwpnTpejvMwTU9TwC4Isv1cFs1uL82Qo2sDEj0rDrixkAfd7BA6UB6eMG1S5oPCpkQhM2fdz/Y3o2vpwTABjl5suADsI6XrEEAIYBQKPRiYOvNKKuNktENmBnEQnhdWYcPAU5WB7FYq6VJjueAChh685ecfJ1+3oGakWwZ2b9TM9rpS4kADDKLSJxmzwC0wGA9EbTaDxYs34Qixab4XSqcFtoA8kzKvxbbrZpAF+xF+DnHMVi3N7StuNtPaV2nviKpInLyLRj974WOJ1qnDxWDptt/Jj8eQTAffvrvbmAK9nANhsBUKwKn3ewWytyA9Mxb409Fb89VBw+fVxWy7iDSAIAIz1eYf7OI7sEACrrLEP4LAwApmfYsf9gMx7ez0btA9NzDYBLVwxjzbpBNDcacOGMybt3JQAwygeYfdts2SLZAs+2gtMFgL5+FxRZsdGrDezqJG1gNkZHlD1hZxMAbnOZ8FkbaaWAM5pe/L2uCVBHXn6RAJDqKykdwaatnejv0wlNoMebY/l5BMBde55Co3Hj+NHFcx8AFR72LdYM/NJwPnQKmWNsKjf+Na0blwwUHIDd/anfUng8FZMc/CNKTjM8gRMAGBsAmnKs2L2vFXdu5eDJ46znFgCLSizYsadXpEc9+kG++ICVrwQAcp7WWMpEfgPHUvtzcO90AyANqUYrYfXaQVQtGYXLpcK92xl4XJsGSQqczhkFQAlY7EkFhXpJkZLwi45SYc91N2kIPzE8gZtEZaieOABIY7J8ZR+WLe9Hk4iqLzuFPI8AuHlLE0w5Znzw3jKyuGQ9gYxp8NYT5XahaIkQXV3CQWSgNHyImIQGcHzOeRynsEZ4NyYAMDYALCoZwZZtnbh6KR8tzenPJQCmpTtx4OVO4el75IN8mEf9HR0TAMjawGMoFN0uHEOD8+1WGQD/PKhbCt6nSiMdhWOIv2ojN9+GTVsHhNFsX68WVy9mY2iQoqWHv6YDCnMkHb5orUKupANlctCKMM8qtKgs+JOUR7CrPLKChkMe7DGSsHV7BwqLzbhzMwdP6il5TOjFalMWjrVU2fUF4Siz+jDezeFFq1nXhvLyIbz/7hK4lXImKw4K+5chBfn9CL6VN74hDUrAn/QvVHQQIRvBL5mePJc2gBwnCEVc4bEeWxujjETMRhSL8e4NhVHufbxyXINHrk0dKbcWLhpEzfoenDtVjO6ulNBsJjSYDMrmthlbOSaMMeSVuyUJsyZy+khNc+HUsVx0dwY5fcTZ4UPpGXnje/9nIhMI602XKKQ4AjMJgCQQxX6jgJlLV4yIveLe7UzUPQzVBvqEn3IAlIAfWKuRJ+mQ7KeBoiOqLpUdX0q5P/aCZsETGwCBZI0be19ogTHVifNnihUzhbDanMMAuHxFFxYv6cOxI5WwmPW8p3aSYVr8K512APQ6iPz+YJnsIAJJHAfTBwYFEf+b9FaMqt3Ic8v5g5XCw/AGJY6lmIwRW4vRNcJ8XycAkDlQXMgiAFxW3Yfl1f049mEZhod0zxkAesSxL2W/oli39M4KAbQEAMa2JTDujvIznFHzc1JkpgHQN8ymHAc2betDRqYLvd1aXL1kwvBQqG3gVAPgYncqvmJbEvaI7geGx3icNCrEZsHYJACQ6kxLc2CPyBQCnDxaBoslcAxYbc5hAFxY2YdVq7tw7kw5+vt86ZMiPIxzDABFb7wOIgR6Q2oXXhvNRYXbIF6ipF92+uUP/klWMzt/8JRsW9Gx2SRFia4RJtckAJA5UJMBwJp13VhYNYT336qA3Z78XAHgilWDWLlmGI1PU3DpPGX6oE0oaA0nAHCSe8DkiycAcPJjFnDHbAFAAhvSBq6sGcKSZSMCgB7ey0Dt/fSASOpTDYA7nCZ8xlEekseVBo2CPv+TrhnnNXLoFxaMTRIAqd7ColFs2d6B4WEtTp8ogcs5nlGC1eYcBsCi4mFs3NSK69eK0dYSGhtRcbnPRQAM6ojBrcaP+qqEuYH/5csf/MemBm5ylxh3BIXbo2OzScoRXSNMrkkAIHOgJgOAWymOaYEZb72xCJBUzw0Ali4wY9vOPpHp4/iHeXB7nfYSADjJRz4OxZ83APwfAF4FQFFyawDc9o7hae/vvO6D+EcAf8EZ39kEgOPaQDs2bu1HRqYTA/0aXLlowmC/bBs41QBIGsCv2pYEHP/65KI8rlOtAfS1VbVkAKvW9KKrIwUXzlGaJXmpz3cAzMi0Ys/eZ6h9mIvHj+R4ixGveQCA5BzyhcGysJrnH2c1s/IHRxyraApMks3Uao/4mEtKkrz/eqBWS2INk7G8203/qsW/TvFxo6A9YcrJ5JoEADIHajIAuP+lJqhUEo4eXiBma3J5hMcnmNtmbOXiYwOYnWPHvhe7RI77ox/kwWqZwOkjoQFkPsXRF3veAHAngAYA5wG8HgSAPwHw9mSHkgDw5c//KOA2ZciIo2MI44VNL4wVq4axfKWcZePhvXShEQzMqyiLHVcolID/ZVkLAwLzuLrgETaAX/G3AQz201XU9inMCMvwTMK6DT2oqBzG40eZuHcnN/zUcttl5xEObYoHnrzHUbn78r3JyW688lodmpsycPOGHHMxmmvCTB3+FYaIzOsDVybWVAPYas3Ap0cLFPMHi/AwqZ246AsPw218isoR4BlTHUhPsyE13Q6DwQm9nn5c4kerdbNbJk2/w54s4l/axL8amEe1GBnRYWRY7zWB8J+TyMdsSo0rwglXSqZzB5OxlGE0SBYu7ChFGlFyFlDuAo/swwVR/vinGtDTbcD5s0Wy9EoZPRQnI7DdWEIATX2A5/Eg0gaDGwde6YRWK+H4h7kY8ColxroYsjSVCDD0d9wML0p9ffP7v55wAuE+x/OoXON8B0Af2GVmybaBWdlebeAFEwYHAj2F4wmAq10Z+CM7xaCDMNAnrV8SVOhW2fFDw2P0qR1jyygEMrggxqQCdRKwc3crcnJtuHo5Hy1NFF1e4eK2OwcAkHr30it1GB3R4pzIBhLdNdcAUNYAlitqAOnj488zm2ZIAyghLc0uQvNkmyzIyLDBaLRDHRShh2KfCYgTPxq4nGq4ScvnIo2fWny40TKVtYOS0AgmJXug07pESjG9Tv6X/uZ/UZio0REdBgZS0Ncn/9isfnaxPIZR1k5xl1YCAENGikD/ldcb8YTSwN3wfpzOYwCk9brvxW7k5DlEoGcK+BxyJQCQ+0TFrVx8P9fjJtaUV6QEgPQZZidlGYCvejWFEQWZrRpAHwDSv/TwLV85NKYNfHA30DYwXgColdT4vrVahH+5rR7Ee5oO5Es6dKntsuNH0GqbagCkftFLce/+Fui0bpw5VYKBfgXP2HkGgDt3P0OK0YGPDi+JuH7DFZhrAEianD/prwwJD0P9o4+QL5rqYU7ia9aiHjjKDmRwoKBwGDm5ZphMljGNHr3fKU3fyLAOIyP6sX/NFg3crkCNua99vlaM7pBA6RFTUx1IS7MhLd0u4DMj3Qa9wTXWJYtZI0CwqysNXZ2pATay4fqd0AAqjAxzcpQ0Tzm5FAS6DXdumVBf5w1ZNW8B0IMNWwZEFqva+2m4fYNskyMfKXOPxBMawOh3qwQAymNXCqDFa0zzeQCfo9jCYYb1CwDoR1zJOkPxa3/wlwFFZ8MRsD8A+oTLzHZg87Y+ZGbJ2sCrF01CDR8vAPyUoxivOYvggAdfMdxHj5p42ntxggFzQYypAfT1KzPLht17W+FwqnHqeCmsQZ7BSjH/YgkirbRupusImNpeu74NZeVD+OC9JV4bsclvEHMOAEV4GA3GwsOoJCRLauESQkFinmgs+HFGE8pdejlEjDe13ASZFCcxaLKWj6CvsGgYmZk2cS8dzw4NGtDXZxTA1d+XAqfT3+YpchNMxohQkQRDihMmkwykpI0kb3mfjL09RnR0pKOzIy1QO+hXawIA4wuAFQuHsG5jDy6cLURHu1GufJ4C4JLlQ6hZP4SONj3OnMjx2mMnADDy0z/1JRIAqDzGtIOTAZXsrjrBNRc0gP7iB2sDHz1Ix4O7maG2gQw7Q3/ILPLo8R3rCuH88Z+aVryr7QgctRkEQBKkuGQEm7d1ikDZwjPYX+PCBc85cgS8qKoP1au6cP5sOXp7vS+XSAs56O9zEQDllyiwyGkYg7wUTxI+P1wqIJC80Mkcwa2SkCSp0JvkxE8yKUSMc5KjIxenuJOlpYMoX9CP9HT5Y8fhUKOrM10AVU+3EW63smaP22B8ANC/NfnFq9M5UVA4gsLCEaGp9B0dd3cZ0fgsS8CgJI2fUycAML4AuGZtDxYtHsLhd8vHQ1XNQwAsLrVg++5eDA0m4/iH+SJnu5d2Qwc0cQTM3RbiVi4BgAB9klP26S7vqH4SwI+9XsERB9qQynQCYQOVQpNBgMJNj6YU92JcK+bAxq19yDY5RQ7GKxdM6Osdj8Q+Ka2gBHzNvhTLPeloV1nxdf19uFRBT7OS1i7SkXCY0edp00KzeSxeSp7BfejsSMHFs+OewWwt0BSDYizz6j9UuXlmbN/ZjLt38tHwhGJsRbqY2wCjGBscI4nk+zujzUhV7bBk4lfNoQ4xvhAx/y3r6aRCxGRmWrCgoh/FJUNITpbgcCShrTUDHe3p6O1NCUnJGEm+Cf/OtNHjtqEEcuQ4lJdvRnHxEAqLRoR9os2WhObGTDQ2ZsFiDpddiCccH2Ija4Vkxme0y7U7VBo4rsAxeKnu2tsGss9+503yAJYXOddxJaT/Sn3lwiTjKHZSsvm1m5XtwAsvdcPlVAmPX7PZT/vNGTulPjDnVbFbCvW9+YOEEwh375gP5f4GwCEABV7t3giA1QDO0EcxndoA6PUe8d7hdHiuAiD1jUIQLFk+gpVrBsUpKMUMJPtA2eBcUWWnRKfY5jLhdxyV4m/f1dWiNomGNehi1MeFh2gBkF4dPs/g+keZuHvba3zNhYw5AoBarQuHXq1HU2MGbt3wehhOuJiZA8Aoxp1DzrMlyjDajFTXImcKvji4QGj/gi+yDxQOIhprhGok5OWNYsmybmRny2X7+w1ofJYt4I/CssgXA04iCez/97hXN3GFOp0LZWWDWFAxIDLq0DuzrTUddY9yhFdx4MUTjstTHLsweYQZ7TJBIRbvXmV24niuSnj1E40YHqLTiPEPk/kEgHq9Gy++0gWd3o0TH+UGKBfCPSahYBu9x28CAHmbTBy2V15D87XUXAZA35ykZziwebusDfTFDRwaCMrLGOZlnCIl44fWVciABueTevHXugbld/asAEByiAF27pE9g69fyUPTsww+ZMwRAKSpOnioHnZbMk6f5HgCM7cBRrHZCIBbbZn4pZGCsMHJf5bWiYt6XwjQ0J0qJ2cUy5Z3IdtkFbH3Wloy0diQjaEhBU9GDpxMZjNksM7kqmNUKIpIIE1y5aJ+FBTKmXsIBB89zBUhZiYDuwkADBxzg8GFQ6834Wl9Om5dHw9PNV8AkMyM9h7oRm6+A5fOZaOxISV0iSY0gJN5bKesLGNLn7K250XF8wEABdupKG7guKdw3UNZGzgepV1ZG/NrjgV4wZUPM1z4ouEuhlWuWQ2ABCik5dhzoAW0EYfLGay4OOcQAG7Z1oK8/FG8/84SP+1UuEeOuQ0wis1GACQN4B+GCREzkQYwM8uC5cu7BAiRVrypMQuPH+fAZg13JDr3NYBK2pnMLCuWLusRIEgw19qSgQf382Cz8hxaEgAYSDtFxWZs3dmJG1dz8ezpeGiq+QGAHmzZ0Y8FCy2ofZCG29d5Hr+Kmt3EEfCUMxJjS59yGeZ0A/MFAH2TQHYpG7f0IzvHIdsGXsxBv882MGi1LHQb8U37CmFg//9pGnFC0y2qUTZ3jHykzIWH6I+ASTZZjvQMO3bvaxX6GnIKodAcEa85BICLl/ZiRXUPzp6mnMAKX+ABnWVuA4xi3DmMONa+Aow2I9YlAd8eWIRctyYgQw0dOXWpHfhGdqANINnEkcavYmG/qLqlOROPHlHWgonAzycFQ8MWUWC/AnGvjlFhmCIEgsuWd4v0ZWTMX/sgFw1PKYTJxJOUAMDAAV25ug9Llg/i6OESDA+N7zvzAQCrVw+ievUwWpoNuHDaxPb4TQDgZDaF+JWNx/YaP2nmYE0yAP4wUPIo8teOVxA6JSHVxb3+wDaDbQPJU/j+nQx4vOnUSFY1xV2zr0SFZMRT1Si+qXtA6SzliwtKjHAuscGewoLyazMv34Ltu9phtSbj5LEScWQ6zh2RgTXscuX2P7gCxnjIgB1ZNvLs3LGrBffv5qL+Mfk4xU5UPPGYWwqzWLy2BJNbgz8YLkeOWysMfbViFFV4nGzGjzIa4fHKk18wglVrOpCS4kRfbwru3CoUMfu4F8s+jQeotjsAACAASURBVFvZZMoxuE6uLnLBSMCWXzCK1TWdMBqd6O/X4/aNQgwN+cYocv3hxGCPXSQBw/WScd9UyBY8IhT/LzPLjrffWCByAE90saCQ6/ChWI7neKMkY7BsFZVmbN7ej75eDU4cyYXb5bWL5Rz3iqUZWJAb3y96W0zgzR/8RiITyGT2mUTZwBGYjwDo62FGppxFhGwDBwfknMK+9D0vugrwGecCeCDhj3X30ai2+DGGAsQqLRwGUUwlAJJI5RXD2LCpG/19Opw+WQyPNzE5B7JmMwBSLtlXXnuMzo5UXLlU8twDoO/FXuUyihAxGe5kfNKaL359TNeHu2kDqCm0QlfRg67sfjx8kC/CoUTSbgWvATbExHsjZXJXPACQRKf1tWx5DyqrZC3p0/psPHyQq5hqUrGrXChQJo+Iozctzh1M2fxloY/r1z/1DH09epw9VRi5HxxonQUAmJdvw+79PbBZ5Ry/5EU+dnHnOgGAEddDvAtM83d4vMWf+frmMwDS6NKGtbx6GCtWy0bylFO4/W4O/sy6BgYk40hSJ36qbQqcCK4GbBYAIAm+YmUflq0YQHNTKq5eIiiQtUMhF/dp4fY/uAHGeIg5Ycq2e28jjEYHPnivyg9kuJ1Q6D7rVlahyXJV3B50/7F7xZKL1y15om6PygNPkhsqdxJ6khz4cVp08QGfFwD0TQiltqtZ14GsbBsGB3S4cqkYFs5RORcKmJAVCuIKN3Jgim6Ls2z+1dE4vfBiGx7ez8SDu5FDNM0FDWBqmgsHXu4SGaeOfZiHoUG/VIOTGc8EAMZtn+NWxNytudU9f+XmOwD6ZpRsA8lTmLKIVB/eiorWEgzAgS/p78KqCkqxxQUgBvBMtQZQ7p8kgkSXlJrx6GEW7t81sSFLccVz+z/FALhiZTcWL+nHiaMLMDwWwiP6R54xXXyNWfRixLTJBMCzB/ifg0ug8wQ6M1DuYILA/5Y5ufiA8kpiq+Ji6kfIzexmIxfkctK4DBKWLu/F0mW9cDrUuHqlWATBnvCKM2TNFQCkWKSra/px9lQBujoi2eYyYwPOoAZQq3Nj/0vdSEt34ezJHLS3KphLcOc6AYDx3RMYtc3QNsyQbI4UeV4AkKZDnSTh5dJkfPrRBjE771TdxpvtNoUsInPnCNi3zOhIa+eeNphy7LhxLReNT8l7LejiPi2zBADJC3jbjlbcu5uLJ2N2gNxOKHSfdSur0IxrAEmzfaDMik/cWoskT2i2DuEdnEHxAf1MGxh70vMJgPLAkP3khk3tSE72CNvTJ/Wk4QqzHrhQoDTmDEKdrUfAO3a3IzfPhnfeKA+MsBBmbc1mDaBK5cGeA93Iy3fg+pVM1D9KY+X4DfuhlABAxg4T3yLM3Tq+jc6n2vSpmdLLnwt0AlEOoqwERdxjxmAnDYUR5Klnwmi2GI4nADSSGt93rEKBZEB7XjduvHYaQ0PJuHyBbAP9sogwjyiDXw58bZ8SmzGX8gRwRl+ze/e3wmh04cK5QnR2RE6jxj2ODYVJJiQrPiy8dSPbAT5Bb48BF85Rumv+8TH/GWWOezBLR3cbX6ywJVWgQNkbN7diTX8eqs+vhcYdGs6E0sb9zNiBC/rBSbYZWcM2yQpZxRlMFA4xWPUrFlLoqjHVjs3b2pCe7kBLcxpuXCtQDkOkTGgsWaKGuzhD52TlUKs9eP1TTejt1ePMScpFEHQxl04oFPIcORQ/TpjzELq+JGzd2YfyCisePUjFrWvyBzP7A4gV4iWWfoXeqwTT//Vnv5lwAmE9dYlCiiPwXACgBCyW0nDIVYj1HhMc8OCrujvIXtUtYgcSU1HMwIf304XbPx+KgsGWSQWK/MO9d2LwSk1zYM/+NiSpJeEUMjgwsQcov6+RCYjZA2WtSpibt+9qEZkr3n9nkXgRRy3vBEAVzdbA/F6JpuoJ79EbXNi+owk0z9brFfj4zXXQYDznre9m0gD+KL1x0hpAjpNF3DsV6kA5iSaY1KFUYxigIg3gug0dKC4ZRVdnCi5fLA7VdjHBg9lsiAcpF1hjAhZF4cKPZ26eFbtf6MDd29l49DBjTgPg6rWDWL5yBC2NBpw/Pa7pjWk8Q4YuAYCTeJCjKsp/50RV/fy/ab4DYI6kxZcdy5En6UQqLfrfMJz4b7p76FU5kJntwOZtsm1gX68WVy5mY8QvttXYClBcabMPAEleU44NO/e2w+FQi/AwVkuQUbPfso4aqKI9JhZt8zSAVHLx0j5Ur+zF2dOl6O1Jea4BUK93YseuJpHi7M6tAjx7mo0/HVyEXI82JD5gn9qJL2c+juKoOgagimG7nC0awHEAkLBmbRcWVg6hp9uAi+dLAiHwOQTAFav6sbx6EMePFImoAyEXc+nMtAawsmoUG7cOoLdbi5MU7sU9vh8lADCGh3gGbk0AYIyDnpWbLv3hX38TTx4ZROBk8XpWTHs2B4+AJeCHjjUC/pL9tCRkJN+lsuNL2jugX5P3F+UTXrJsRIRyqr2fIX4oe8JcBECSubjMjC3bOjE8pMGp4yVwOkPtxGQU48NYwFKbJgDMzLRh7/4m1Ndl4d7dvOjlDfucRLeFTLcGUKNxC/ijAOC3bhaiSYR4AcbiA3q0cEOCToQ1V2EITvxx1hOMqoMcnCLuF8y3eMR6Jldg9gEgyS9h1ZpuLKoaFOYUly4UewMDhw3Ux+r0ZI9exyqd4SPgFw62IsXownv/VQ6PUieYS2cmAbCw2Iqde3thMSfh6Pt5sNsD98W5BIAajQf//p3PJo6AWU9dopDiCGTlpUt/f+HL4m9dHRrUP9Kj+Zk+4KsoLBQy4SEUKHk2e1xNkTLEqLDEk4avOZeHPSL7rvYhHqvlPKF0ZZvs2Li1X2gD+/s0uHLBhKFBOXsCy76PC0VceojhqJjkrVoyiNVr+9DTrce5U4XKtkxMWULGODpukgeaO06isISDh56JF++RwwvIlSd0HccgS1z7pfiExSCctz6yhdy2sxkmk1VA8LhDjLeABFS5UpDn0cIGD37VXIxUJOOeZgQ/SW2MFKt3indGJhVwpQiqjv3CVqqfpcWTsHZ9FxYsHEZrSyquXS4UazFqiAvXz2j7xSRnljNGOBs4CUgxOvHK661obKBQU+P5fwO6E4M3b/CwcOVVMllQHBJJQrbJgX0He8S77djhXAwPK6QCZK2JcCf2gTcr9oFdf/jnhhQWq9aasWiJFb+0+msJAOTuHYlyoSNAR8C/9iffQdVSK8or7EhKBux2FRoe6/G4NoJWcJYD4E53Ln7VVQEDQrVfZCT/j8nPcDa5N2BQ6OEiu8Bl1cNCG3jvdibqHpJ3mAJ4BA8nF2yY0KU8vDyg8AHr6ppeVC0dQmuzEZcvyDECAy6mLHEFJe44eQUVWpjFdPRUjuGxjA1+veANSRg8Cx6PeO8SMQjnjWO5eVsLCgrMeFxnwoN7cty/ia41jjT83ijBMnBK24cGjQXdagfqky1RHAlHai3S3+c6ANIkSNi4qQMlZaNofJaOm9fyISk9nEwYUxyxWQ6AixYPYe2Gflw4m4e2ljDOZbMYACnry4FD3UjWeMSxb1+PTtnhgw1okb8opgIAM7Nd2LZ7GNkmF/p6k/EbW76cAMBIW1Di7+FHwN8GUKvzYOEiG6qWWZGZJR8ddbZrUPfQgLZmvUKUfN7x4VzRAPqPEmkDKW5geoZL2IpQTuHRkfC2dOJeLtgwoSseAEhfyJu2daG0zIz6ugzcuUlp1fyPtnmAMpMAmJNrwc49rXh434RHD3NCFzOvC3MQAEn71IHyBUNofJaBWzco8wKvs782WoydjmzxknNAEp8vvWoKEN2IviTnNG6J8wAAadTVErZsa0NBoQX37+ag7pFCEOR5DIC79nYgJ8+Od94og8uXIi14Fc1SAPSP9Xf+lAmtzQYheXy9iuUa/a94AqBIaLDKgtXrzOI1c+9WCu7dMuLNH/xWAgCncTebd00pOYHQQs4rcGLxMivKSCuYBFgtajypM4gf86hPoza7AZCeR7IBLIReWEb5LtkG0CbbAE4AY3T0tqpmCEuWj8DlUuHOzUw8qSNtYJiX8KwEQLJx9GDHng4Rv+vurWw8fiTbj4WDVqVFPpMASJvfy68+Fc4sJ4/Jmq2Ai8dEcw4AF1QMoGZdp0iHd/liybj9WaRdSAK+M1SFAo8uwGaS1j1pAr+RUc/lyEgtMf4+PwCQOpqU7MHufc0iRMy5MyXo6Q4KhDxPAZDsT1/7ZDM6O8hjViH8i28VzEIApDnbs78HuXkOXL9Msf5Sx9bsXAHAtAwXtu4aRl6+C0MDSbhwOl3kK6YrEQaGsQUlioQfAWUAHC+vN3iwaLFVaAVT0zziWLSjVYv6OgNam/ShLyUlJgwBo+mxAaRekBfwjxw10EINCo1BV7fKhh9oa9GncrA0KpQnknIKG1Pd6O7U4eolE8yjCtrAWQqA1GfaxHe/0A7Kj3z1Uh6aGwlklbWWsw0ASZ616zuFHdbRDxdgdCTIA3EeAmCK0YF9+xvgsCfh5PGFYZ14lOaqypmCPxqpCB8eJu0Z6icZIDr6PXT+ACCNgTGV5qUJDkcSjh0th8vfuWqeAmBFxQg2bOnFtUs5eNbg3TeUFsQsA0D6cNyxtxfFJTY8vJeKOzcCg+PPdgAk+ZdWW7Fm/ahQwtTeN+D2tdQA+/wEAEa/MyXuBEAA+NLv/FmgQkUJZFQSCosdqFpqQ0m5HWo1YDHLWsH6RwZYLXytoLJDxdRB4d86NsKIZHyk7sCVpF7UqUb8NCBK7Yb+jmKDUeyoqqWjcDlVuHMrE/V19DU5XpbvUavkUa2wHJlHxSwHFZprgwt7D7TDYHDhwpkCdHak8JxbJgGKwb3gj8nEj2NuHh0Dt6H2QTYePgg8Bo6B/xRsIuO7LSj2P2ITErbvagbFXTt/pjRyWrKgAdhmz8Ivm4ugD2P7+i/GdlzQDUxLyL+YnDQUISP4l9EDZrSOHBULyR6uG43P0nDjqp9GLBYv3ZBu8frFd5YIHUzuvTv3yqcH775ROvYhoixdlHHveF2Fsrzh2pREqJfKxRY01Kfg8gWCv6AHJY72fjS6IfKx6w8tKLR+O0fESdzwUBIunklDd2eo0uGtHyaOgCNup4kCE2sAOQDoX4PB4EblEptwHCGtoMcDtDbphNNIZztpZyY2rJ9OAEyRkvC/nZuE+F/R3EazOjg1Fg8Aff0nbeDGrX1ITXOju0uHKxdJG+gNn8N0ilE6f1OEmDgDIPUhLZ0CRbcjKUnC6ROFGOyX7WEiXkxZpgoAyRD/5Y89g9ulxpEP6RjYH7wjSj9Bgal1AokGABcu6sfqmm40PMkU8f4iXkFdkDWACxU1gHQM/MO0BlkDyHzxRmx/ggLzEQBp4LbtaEdBkQUXzxWio917rDgPAVCvd+GVj7ego82AC2fIiUy+ZjsArqwZQvXqEZHb9+wJ0yTC1oT2TFmxq1QuxJNH4cmIdJ+s9avZIGv9Ht034JZX66cEwAkAjGV3StzL1gAqDRVpAYtKHVi8zILiUjpOBYYGk/DogRHP6vXjxsIhjqdKuDM1GsAyTwq+71ojZPt17RVYVcFx0SYHgFQPaQNXrR3E4qWjcDpUuHktC88ajFCxQ5TMjAbQN4fZJht27euA26XCqePFGB2RQ91MeM00AAJYtaZHhLY5ebwUA37gOp80gEajA3sPPIPNloyTRytY+VZDvjuEDeDikADRNL/k/f65zAeyU3sCAEOXPPMYl8Bo/8EmeCQVjn1UBoc9WXE8owZgphxcLZ7Ss8251+f9e+lcLlqaxr1/ZzMALlo8ig1bBtHXo8EJCvTsUk+5w4eA4uA5m6QGMMXoFrZ+hcXjWr+ervG9OQGAoas4tr0/0kvvOfg79whYaSj8NXmp6S4sXmpF5RIrdDoJDgol80Q+Hh4aDFRdT6cGcL0nG19wLcUonPgt3TWFbkweAH2V5BfasGlrH+jBJc+yG1ezYbMGxZZSVu2FyDFdGkBfw4VFZmzd2QWrJRmnjxfDGix3sISzAACzsikodAue1JNmbDwcSmybwGzSAErYsbsZOblWnD1Vhr7eICeDcPuRwgBQgOgvjFQgxxsgmtLFUSYcuv4hpRVn9f0JAFSmIvauX1I6gk1bO9HanIorlwrnJQCSyQjZDdPxr9s9HgprtgJgSZkV23b1iVOZYx/kjgV6nmp7v9gA0IOKRTZs2DIKnV7C41o9blxOE46H/lcCABMAyN6cuAXjBYC+9pKSJRFKZvFyC7KyXeLXZLtQV5uClkY5lMx0AuBBdyE+467AM9Uovq69G1cApPepVuvGuo0DKK+wwGFX4/aNLDx7Sl/K3od3lgIgDUR5xQg2bunB8LAGp48VC8P2sNcsAEB6w+4/2CxsGQ+/t3DshTRfALCoZBibtrSj4Wkm7txkHP36JivcAIwFiNahW23Hdls2djizhRbwjzMeo1c99eFgotaAhVuIIeQRvRozWhtAf9E2b2tHcYlZZNvp7w01p4i6/7NAA5ie4cDBV9rQ+NQYEvx5NgJgQRGlwOwV+/DxD/MwOjL+MT5bATAlxY2N24dRUuYQkTYun0tDa7NCmj0lDSOAxBEwl3QS5RRHQAkAI2n7JhrKcbiTkJMnh5Ipr7CJANO0wEkjWF+X4uc0ItfGhUJl2ZS4Tn4rfsZVgZc8Rbiq6sNPNHW8VaDoBKPY8tgvi0stWL+pH4YUD9pa9Lh2yQSbLSnuThZchw/uHNIRT836PpHbk2wC6bhE8QoaEzZ0RQmOYk0o2FRWLh7EmrU9uH41D03PFBLS82Z4vFS0/ZpsOwHllUZPwgsHG4WDzpHDFfKRYixXcBMSoJfU+PbwEuEZ/0g9ircMneKYuDvJgfokcxxCw0QPY9yuhvJfnNucpB0f2dQeeIlCpKTgwtmi0G5wQS74TuZ9SuPGOdoNy9d+7das68PiZSM4caQAvT36wFuY8vFkYdrdTdAmZfnYe7AHHrcKxz/KCTl1EuErgi5mFxRtJXgx/iay95NQsYgyT41Aq5Pw9LEe1y+nCnilizduCQBkv4e4G8zzVm7qAHB8JOlIuHKJRdgK+pxGSBtY+yAFvd10PMzXCk4WAP/QuRTrJRM+ULfhX5KbeNMbBQBSxRqtB+s29GNBpQV2mxrXLmeHj5ofLAkTlOINgCSGL8m7iPN1pgCSfw5kn5zRghKzX4rzqgCAGq0bh159hoEBHc6cLOXN50Slou1XTC2HbltFxSMgbVJdbTYe3AuTamsybSoAIN2+zJmKL5krRU2UO5hCI9HRMAWJ/vPUBvTFpBWMM4wp9He2ASCJSMfApWWjOHG0BAP9UYJS9HSiADbRz4MPPCh26KufbIXNmoSP3iewDVpQTHrigQwTzsK0mZbuxAsv9yA5WcLJIzno7VGwaZ5FAEgJFzZvH0H5QrtQilw6l4a2IK0fb9wSAJgAwMm8FBTKTgcA+jYPimtUVGrHkuUWFJXITiN9PcnCaaS50cDLNKLQB0XG8P7y+841KJeM+IekBhxN6uSNVpQA6Ku8pMyCDZv7odN7xPHJzWvZcDojpJJjgtJUACAdra7d0IvKqhE0Nxpx5SLZ14V47gSMHfvBY/aLC4Ak1vpNnShfMIKjh8sxwnFgmfUAKGHPCxRg2I6PPlgIe6zaP+pvGAAkx4+/HFohwiL5X74g0V9Pq4tBExg9ePAeTAUzOyaIcOtXcoyJdIybnmHHgZda0N6WgovngrSATPniCbZceFAaE9+9peVmbN3Rg1s3svC4VkHTzu0Xq1z0AKg3uLH/5W5hh33upAntrYYwDh/MNhQXSiTPXe9NDPOEwmIbtuwaQUqKB00NOlw5nwa7V+vn3zR3DhNHwOwnO1FQaQSmEwDH2ldBpFhbusKMhVVWJHuPh5/UpaD+UQqs1gliCk4GACXg75ybkIJk/FnyQ9xWD/IWQYwASI3QxrRhS58IQmoxJ4kjYdKwhb2YoDQ1ACjnO92yrQsEr08ep+PW9YlTxs0kAFJquF172/C4LhP3bseoLZsFGsDcPDN27G7FU+HcMh5qg7dYw5QKA4BVLiO+OKocIoa0gT9MbUB9sjnKpp9PAKTB2rytAyWlZhz7sBRDQ342XCwAii/YcuFhIgDcubcT+QU2vPtm6ZgjRUB5br9Y5ZhwFlQXpXjb+2IvsrKduHw+C8+eyF7KyvZ+zDamCAA1Gg/WbhoVodMcDhWuXkjFsyekLVbeSblzmADAKLeqxG3yCMwUAPrGX6v1YJE4HqaYgm4RU5COh+tqjZBd4COjRjgNoFFKHosB+MXkW2hTW3nTHgcAlBuSUFllxpr1A9BoJDytTxVOIi4lbeBMAyDklHHbd8sb/+NH6YF5g6MFJWa/lCYmfBBpCftfaoJe78bh9yrC2y1yZjvafnHqDk/7AX9Zv6kdZeUjwvbPPMoIycNpOwwAUpDoX7EWhw0S/c+GNjlIdFTX8wuAFFpp7/5WOd/2Lb+PEhYAzS4ApCPVl19tQ0sTaTTHve1nEwASUO15sQemHCduX89A7f3xDCWzDQALiuzYvGNYmD91tGlw8Uy6UApMdCUAkLcBRaYDXj3PbSkBgL/9g8D+M1/aXG1UaDmF0CtqCcXe42HKOEJXf18y6h4Y0dhgEMa94uJ61aqABZIR33PViNt+Lfki7CqFF5RCffzsFYE3hxuPFKNLBI8uKLTDbE7C1UvZ6ArSBrIDBsd5boIXPuU/3rGnCxTw+v7dTDy8L+cNZsmnBM7cJ4vZL191CyspG0MPbl3PwdMngSme2PKGXU9coaMs59dXylX6yqtPMTSow+mTZVFWyL+NNIBfGq0Mmybuz1KfRq8BZMIOX1pGSSZzRjrGZbQUWCSkrxJePNQCslH94O0FYykyo/U05nut8iTnAgU5S6zd0I+qpeT8kY/e7iCbRm9zscgXKoui501Ix3xtUhD73ft7kV/gwL1babh3Oz2oLFfbN7l2AxpRntiAIklJbqzdZMaS5VY4nSrcuJKK+tpQrd9k5iZ4UN760WfbAJTwVsH8K5UAwBjndLYAoD/Y0fEw2QkuXGSFRivBalWjvjZF/NjsSl9OCkCpAjZ6TPgD9zIMw4nPaq4o0+M0AKA8RRIqF49izbpBoQ188pi0gZljwbJZgCWAhbfkuXCutHzImWX3vg5kZTtw45oJT+vTZx0AEqgeerVRHE8dOUzgFATjDM2xl2xjfIKiuN1vDkvLhrFxcydu3cgT4V+m/JKA744sRZ5Hi2S/wOUeSOhU2/G1tEccpbuymM81AAJLlw+genW/SLPY0e47jlQYKsY4xQJYSpPDhQxNshsf+2SrCKFy9IPC8EeUysaSrOUbCwCSHfn2Pf0oLbMJ2/GbV8k+MZzB67g43GwebBvQCACYm+/A1l1DSEv3oLNdg0tn0zE6oqz1486NkidzAgBZSy5RKNwIzEYA9Mmq1cjewwSDdDzsdgONTw2ovW8McvNXBsBD7mL8iqcCT1Uj+EbynRkGQLlXRtIGbutDfoEdw8PJuHzeJEKwzCYApP1UR/Y1+9uRmubC5Yu5aG2aIAm8b8KmUQNITVav6sXS5YM4f6YQnR3jWQoEJ88RANy2oxV5+RZ88G7lxHEY47iFmTwa/OFopQgBQ+8xrRcE/9bQFMPxr4hdEUcpmVUxm5x6DSBgSKGj02bh+X/5ghzHca5pABcvpbBQA7h60YRnT70p7pQYdkYA0INNWwdFft9nTw24dC4LkJRDKgWLPF0ASIC6ap0Z1avN4n1162oqHj0g2+/wH+4JAGQ+6wrFeOqQ6Ouf93fOZgD0vcTpoSoptwmnEUqOTVd7qxZ1D41obyWD61APW2KRX3MvxIueIlxW9eC/J1MMQEV1X8gcx/sIOLQBScTXWl0zKBR6D++no/ZepoIXtNKK5y35WDSAvmFKSXFi74EOYWt38Vw+OtoCISu0Xwogzn2CmJpN/+ooZt5LH2tEb48BZ08VB7Q0FwBQp3Ph0Mca0NFhxKULgfJzhy3qchQk2m1EvluH3Q4TFrmN6FU58LX0R3CoPNFV+5wDIA3azj3tMOVa8d5bC+ByJs0pAKR9lmz/kjUevPdmyYT7USwayug0gBLWrB/CsupRseefOWGSj9kZR7ECxJnlYtEAZmY5sGXnMEy5LhHd4vypdAwPRY7nmQDA6LYb+UM/ccU0AnMBAP07aMp1YNlKM0rLbaBcxMNDSXhca8TT+pQA5wriiS+6lmOtlI331K34WVLjLAJAuUeUYmnztj7hxTY4oBGewqQNnPBiglI8AJDkSE93YPcLHdBqPLh4PgIETrMGkOTbsLlLhIQ5eawE/X3j9kpzAQCLS0aweWsHblzLR2M8glpHuRPkuLX4zsgS6JCEy5oB3E8eQVeSffLBoRMAiMoq0qD14sLZAvHBNJc0gGULRrFley/u38nAg7sTmyNMLwBKWL1uCMtXjqK7S4tTx0zjjl9MsJtKACRwrl5jRvWaUfmD/m4K7t5MFRpAzpUAQM4oKZdJAGD0YyfuJAA8+NnvB2pPlCAjnuDBBQXFcvKUU9ynqqVmLFpqgV4vCdd6CiNDWkHZw0qFH7pqUAoj/k79BMfUnWHM52LQCgaPfRRjpFZLWLZiGMtXDcmbx710PLibIX/dxtE+MdwyUfapCfwtpYQiCCTPu3OnCtDdZeDLxl2f3DURVJ/IxPByCzrbKRMD2Sx5L+ZccMULmepYvj29w7u6phuUieXIB+UYjZf3b5Qd+oStEK/aC0QIDQc8UEOFHgoObXzCDw7NPI5VEjHuR7TBjcQAp5OBOFqPB19pxeNHGV4v+tDeRg1PSsGM2fMdyeGBnFg6YExz4b3/Kgo0R2DOaywgEzJdfuhcvXoYq2pG0NOtxakjpjG7afme6XD4UGjDK3B6pgvbdw/BlOPCQH+S8PDt76XkBspXLGOkdO/bf/7bCScQ9jOQKBgyAnMVAH0dIY+wBZVWv8S3CgAAIABJREFULK02IzPLJcLINFOWkXup+HHXLhHu4vvqB7itHpiVAOjrh9AGbpe1gX29WmEbODISupFEezwdCwDSvZlZdux+gSBawpkTBegPzngwGbs7JWGiBECqatM2ysRgxvGPSjA44NWgzgEA3HegGXq9Cx+8WzGzhxkS8L3RZSjwBNqi+oJDfy21lnfWwgSF+QyABCQf+3iziGVK65HdV87YTSEAFhZbsHNvDx49TBOhqgIujmyTSF/GsRX1QfLipaNYv3kI/X0anPgwRyGg/kwBoCS8e9duHBEnUQ/uGnH3RkpEM54EAMYXwhIawBjHc64DoOi+WAUSCovtWFZtBoWR0Vp1ePGnr4k/fyHpOtpVtlkNgCQnaQOrV5OdyzDcbhXu3MxEfR0ZYo8v85kCQJLPlGvDrr2dIiTPqROFGBoMjFnHPnaNMwBmZNqx/6VWtDRRFhPZ+J7rLR3t4xNbX4FkjRuvfrwBba2puHLRT3MZrUAx3CdCw5gXhQ8NY3zCCw3DBAU2FMXQp5Bbp0kDSO1uFgHVzXjnjXI4naGen7NRA7jvxU5kmex4/60iWK1BdmvMeY0FboLni8ZowUILtu4cEHZ0xz7MgX0sQYB/6ekHQEOKW8T1Ky51YGQ4CRfOpMsxaxlrLJYxSmgAQzeEBADGuEnOHwAcH4jMLCd2lSXj0zd2il/+7ONv40GdAU0NKQKsAq+ZPQJWmr6cPJuwDSTP584OHa5eMsFiljflmQRAaj+/wILtu7vEERFpAoeHxyEwNiiKwYEEwLZdHSgosODI4VKMUnq4Wa4BzC8wY/uudty+mSsygMzktd2RjV+xlkwQHLoV57X9kUVkgsJ8B0A61q9Z34ezJwvQ1ZkSyqLRetBOkQaQ9pt9L3ahoT4VVy9nh04Pc15jgZvgRovLaJ/pF5rUY4dz5P1vxuz9fA3TaZMNG7aMQKeX8KROj2uX08ZtzxMAGHmPiHOJBADGOKDzEQDFV7gnF7/vWYpRjQ1Hf/k9EU/QZlOLVHP1tUbYbBOkm+Pa3gWPPRM6OA4aycke1GwYEJlEnA6VyMnZ8MQIlYLHMzc4ttJS4dgABt9XVEJ5QrvhcKhx+kQhhodkCJxJADTlWLFnfzuam1Jx9WL+rAfARVUDWL22F2dOFqO3JxQSYnysJ3V7QgM48XBNxgaQaqKwPrv2deKmiKEZmkd3dmkAJezZ34WcPDs+fLcIIyMKXqvTDIAl5RZs29UvcuSe+CgHw0NeU5gZBEDK675p2zDKKuwiLi3l8G1pCgqSnQDASe078SicAMAYR1EJABWr5NpoTeC4MVav0qxx62eGcnlVKsUveypQj2F8y3ALlVVWLFluRlq6G24X0PDUgEf3U8c3F79OK3NcZE1hLNq5cG0WFFqxcWu/cHppb9Xj2qXs0COaaIFVUBvvEQouVVRiwZYd3XA61Dh1rBAjpHXjXrHIO0Eb23d1oLDYiqOHizE0FJrBgNdTZieY4xauttU1PahaMoQP3i2H1RLeaJwpTWzFyAbQvDwkODSBCoWG+aPUBzwbwFikYLw8udVPFti49fqXmwjiUlOdePm1Vjx6mIG7txQ0akoNBvWfyVysY0dqLpy8lPZxz4Fu8XFJsf+Uryk+ZvWrvrjUih17+2G3EfyZAvZntievQicUtZNMoKQQZJu3D0NvkNDYoMPVC+mw2xR2k6D62CnpGOsh3BpNOIFE8/Qm7hkbgfkKgL/hqcJ+qRAXVN34f5MoBiCxjoSSMpsII5ObJ8cTbG3W4cHdNPR2+x1lKqvFQldNULmpAEBqlLxvSRu4cJFZeDvfvJqNxgbSGnkFiAWomCAT0oRKBZ8mkLSpp44Wwmxmgkws8k7w7JKjyv6X2tDeFuQR7L1nNgHglu0dKCwy47/+szJMMNvp3aRMHi3+yLJIBId2Q4JO+AGr0KA241vGugQABk3HRABItryf/MVGtDQbcfl8mFy6wdM7IwAo4YWXukTGn8NvF8HsNTMJXXnTA4D5hTbs3t8nPiqPfxgIfwJimcCmzFORvKB9d42Xo4xIdNy7sMomgO/KxXQ0NXg/LJWESQDg9G5aM+s6N+19nZIG5ysAftVTjTVSNt5WteDfRAzAwCsnzyHiSpWU2YUSrKtDiwd3U9HRpoPyEe3MaAD9pS4qtmLDlj4YUjxoepaC65ezZa+4WIAqBgAk2UrLR7F5Ww/Mo8lCExhiQK60amORN8JTQAb4peVmnDxWjL7eQC3gbALAvQdaoNe5cfi9BVPyXEdVqS84tEcHraTGr9rl3MR/ZXgm4gNO6TWPNIA0Tq+QJ7AlGSeOFPGGbQYAsLDIil37eoSj2Y0rE2kqpx4Ac3Lt2PNiHyQPcPyjHAz2h35MTicAUiq3bbuHkJrmQWuzFpfPpQt7xLErAYC8dT3FpeK6p0+xrLOyemNGpnTo89+Fwx6aTSNAYO4R7Sw5Av6xez2KkYK/VdfjhLoz7NhT3mECwYpFVuHOP9CfjLoHqWhsMAS59M88AFIntDo3NmzuR2m5VcQ7vHopG50dlGoo8GLb48UIgNRqxcIRbNjSi+FhDc4cL4gMgVMIgKlpDhw81IreXj1On6CXr78HdRwfQea4hWvxldeeCY3LqeOlcRQqvlV91rIAW13Z6Fc58OXUh9FnCOGINc8AcO+BdhhTKaaeDNERr2kGQDoNOfByJ9LSXXj/rULYgj1/AwSeWgA0mRzYc6BX7L8nj5rQ202hnGJoU2GwuUfA6iQPVq8dxbKVFnjcwPXLaaivU0jlNuMAKAk4/edvfj4RBzDiw5UoEHYEsvPTpb87/2URxLK7IxldHRp0dSR7gyn73TaXAFACfurZBi2S8F31PdxVD06wAmRASDG6RAgZyjOp0UiwWNSoe2DEkzqjN/bU7ABAuSOSOA6mnJ3k3EL2O+QkQkcnvms6AZDarKwaxrqNfSKJPHkHT3gcPIUASLKs3dCDyqoRXDqfj9aW8Xymcf1ajBEAX/tEA/r7dTh3eppTwE1iL8zyaPD90eXCO/h8ci9qk0fRpY4iQwinzXkGgDv2dCIn14a3/oOp4Z1mAKyoHMWmrf2ovZ+GOzeD4v6FzFcMMKZ48jr+S6H5298HlRo4czwbXR0+rX0MbUYJgDm5DmzZNYSMTLdI5XbhTAaGB5P52Vym4QiYwL2swoHqNVZkZLnx88u/ngBAzv4yT8r8DwCvAigHUAPgtrdfZGjyT/QeBmAH8DkAZzl9Ts3KkL71L99AfqELxtTxHKDDQ2p0tstASP9aRhW8w6KEQr6tXGgPOMezGZIG/0vaIm7+ffU1dKis4r857ZK93aIlVixdMYoUo0d44NaLDCOpsFpCY3oFSMiEAo4ccr0KoVH8fpWS4sL6LQMoKrbBYknClQu0gYZqA/2oMGRA+aAYfGuobBWVI9iwuU98PJw8VihCN0TjZcxZt4HjHniHTufGSx9rFeB+5P0SuN0RtNuTbpDvPKNUNY3J6z/XgJ5uAy6cmdkYgJG6/vO2YhxyBmUIUdnxoxTKEOIIuJ3tuKDUaBwBULH6aEOvRBog/7/79WHb7i6QA9cb/8oEwGD5mIMZjUcxRRg49Hq7MH15/+3CgBSa7GPWCGA34bB5GyHgomNfus4cy0Z313gazLjLMYH9INlsrlo7iuWrLMLO8M4No0jnJrIxhbs4/eeG7VEsF9gAJTyoXGxH9Wob0jM9cLmAJ3U6fPX1P0oA4GSe0TlelgLbNQA4T+8QPwD8ewDNAL5J6VEBvEUncwBkT4cJLrIBfPG3vie0SqRSzit0oaCIfpxIzxgHwpFhNTraNOikn3YNrBayPVMAFMU3XmA5PgCFVsYBwCopDX8qER8Dv6w+B5dKfpj47apEUOYFC61YtnJUZBihvI7PnqTg4b1UoeVSvKYZAGUZJFRUWrB2g6wNrKtNxd2bmcrQE4vmLdQLRHEIFiwcxcYtvcIm8OSxAtgsvA+HSOt0wr8r9KtqyTBq1vXh/p0s1D6IpOGIonXmXCs+DgA+/vNP0dWRgovnZjEASsD3zStQIClkCFHZ8VXjw4BvFCazKA/2PAPArTu7UVxqwX/8C32rc3TPIeoj1qKMBgCrVw+C0qtdu5SFp/XjGnKxm3AdLTgAFBaeJGSZHNh3sE+8Qk4fzUaPOPYdv+IuR5h+kQkQ2fqZcl2y1u90OoYGw+zvAQKGdi5kLuIAgMnJEpassAnwM6RIwhnl0X0dau/rYbOq8c6PfycBgKwnZX4VIq8GfwAcBbAIgM/Y7SqArwE4Hqnb4wDoV9K7X5EGLL/QOQaEGZnjQDjYn4SOdg06WmUgFM4I4ba6oJclH8SiA8CtUi7+b2kZ+mHH7yRdGauE367/hi2hqMSOFatHkZfvEKnmmp4Z8OCOQggZJhREJ4fcjXDhYsjeiFLJ5ebZMTSowaXzJgz2B4VmmQYAJBkXLpI1gcPDyThNEBhsX8Qcp0hr129iQ4qSPdGLh1qg17vx4btlsNsjaG/ZjXkLxtAHmoZP/MJTdLQZcem8N3PJZNufhvIUH/DL1sVhM4T8wPA4IENIAgDHR2Dz9h6ULTALAJxQkzQ2j9MDgHqDC698vEN8xB55Pz9EtriDl8I6pbSXLxzsRVKyhNPHTOjuDIS/KQHRkMUpoWqpBes2e1O53THi7k2j2N9ZFweAYwBAjdaNpdV2LF9lE7nuzaMqPLhjwOOHOrhc4xt5AgBZszXvCvkDIAVvagfg/xT9B4CPAJBmcMJrIgD0v5GghWLRFRS7UFjsFD++I2N6aOjriUCQfro7NXD7LdJgauEDUHQA+LpUik9LFajDEP446U6MAOgDL0kA4IrVIyLVHF1tLTqhERRpgOgrnwkF/P5PfAQ8PjpyObIPWbpiGCvXDIn///BeOh7eyxh3ZpkmAKS2Fy0mm8B+kcaJbALJI3J8IjgakUgr1+/vYfpVXDoqAlY/rU/DzWu5k6iQUZQ510o1kbgf/7kGdHcZcOHs7NUAbnea8H/YSsNmCPmpvgXnNfIRHl0JABwfgY1be7BgoRlv/GsZ0wRhegBw45Y+LKwy48yJXHS0hcbKnGoApCxNew/0gkKsnD2RrSiDWEvx1kT61Ufvsc07hlBU4sDoiBoXTmd493Bql7mKpwgASTaCvqplNmi1AJ283bulF8e9lIIz+EoAIGOvnodFYgHAL1B6XN+YJGsNxYd+98eBQ8QCBQnpWR4UeWGQNIWUHocuOi7t6dSII2PSEvb1aAK+NPkAFDpznCPg3/RU4QUU4pyqC3+plmMACkBiBpGOZHtnynFg+SoKISPnF+7p1ggQbGtR8BZTWHzxksOPqAJaobheG7f2ISvbiYF+DS6fN8l5e1nzGuZpYR4B+9/tg0DzaJLwDh4d9YZ2iAGeFKUL2y8Ju/Z1IDfPhpNHi9DfF/rCi3pviKEPJO5rn3wmO4GcYoYJiVrQ6G9MaAAnOXb+NoC7ukRQ8v/82ew5Ajbl2LH/5S6RXvL0MeX4hHEHL78hpH1z9/5e0LHm+VPZaGsJ/zzGXQ7xapJETL/1W4ah1cqp3G5cThs7vZLBc2YAMD3TjerVVixcbEdSEjDQl4T7d/RoeKKF5PFucAqiJQBwks/oPCkefARs9jqARHcE/JvfDQJAxTdqyND5gwxpn7Ky3SgokbWDBIQa7/veYVcJGGxvpSNjLUaVHEqUQIn7kg0q93XPSqxGNv4LTfh3tX8MQGa/mO1SVpFl1aNYWGURDy3ZjhAINj41+AEvr02ldRkLKJLR8PKVw+KH9rQHdzJQ+yCdeRylSK0Bv+Q6j5BNIMUutFmTcOp4PkZHaFHwNIDxcCBJS3fgxUNtAoCPf1QUuf880WJLewfgpY81w+VS49iHJbN3SyIbQMsK5Ek6JPulICRbpw6VDV9JiV+GEEVbNqWRYb6fox5U7rGdYgPjwu070AljmgvvvsGb31D7sah7EEYXK+HFQ11Iz3Tiw3cLMDJMz6GiGiuk4djmRm5DOHwc8Hn7ZqGz3R/+eJPKDeWi1C9K5UbZPEoX2GExq3HpXDraW3jZi/hQGNgPZSVm4G/J9nBljQVlFU6hTCCHy3u39WhrUtgnFdbmO3/xuYQNYCyPyhy9NxgA/wEA/c7nBPI2AHI/4zmBxAEAx8bRC0/kRJGbT8fFDhSVOIWRLdll0TU8mCRgsLVFi652LdwKqm0qx8mZKyoMArafeDagCCn4a1UdTqn8YwDyYIzdrhdk9AY3lq4wo2qpWXxZjo4kiaDS5DTi8Sh4oMYCGcpUFArn3nJkbL15Wx8yMsnIWYvLF0zezX+SKz+oXS4A0hBRYObN23r9IJC38cYDAKmXK9f0Y9mKIdy6no36utDcrEFkyxoYdv/D1LZnf5uIE/f+W6Qhmr0XZQj5orUKuZIuIEPI+5oO/IeO3j3xuWKDjPjIIGqJEwC+9GqbOLI78j5PwzvVALhoyQjWbxrEw3sU9iXTO2DTA4Ck+SNvXzU5fBzLRleIzd/UAmBpuQ2bvKncnj3R4+qlNDnuLVPbNxUAmJPnxOr1VpSUya/o5kYN7t/WC/MpeR0qrOkEAIa+5+L46M+Fqv4GwCEAZDlOxjcjXuePfAA/9Xr+koHa7wI4xemQsAGcAgD0b5te5FqdR3gWF5XKQEgex3SRO3tXu0bY01HEdYIn38UGMT8AJIfff5Z2CMP1b6vu4L7KPwbg1ACgT16t1oOqZWYsWzEqjsPp6JM0gk/rjYH2G9MIgCQbwTjZBS5dMSJg+9a1TK/3H1MQqiQGAKTbAyGwwKsJnHiFxgsAk5I8OPhKmwii/eF7JRMHvWUOSawAuHVHJwqLLXjz38hZn9ko54GeijISsNiTijyPDstdadjuzoEFLnzReB8jKldcWpxvAPj6z7VgcEAjnKA411QCoE7vxqHXO0Sc0A/eKYDb5fsonXoAzDLZsY/gL0mGP3L4COWYqQFAcjLZsGUYi5YopHILA/tKcxVPAKQMI6vXWVFc6hTj0PhUizs39RjsD/I8TgAg57GZ7Tsnqw8zWmi6ADCgkyqIYJvFpQ7xk1foFEeodJF2sK1Vi/YWciYJ9HgKO1B+AJglafE33hiAv6e6gi6Vze+2qQVAnxgUZ4u0gRRYWm/wiJA5FEew/pE3qDTzfR/LEbDSKXZOnh1btvfBmOpGe6tepJKzKIVpURroGAHQHwLttiScOZkv2yVOcMULAKmJomIztu/uRmszhV4h+6cwkxDL3EziSV63sUd4S7/zZjkc8fZQnoQcky2ql9T4kWUl0iUNriX141byELrVdjxWj8bEsfMJAOmD61OfbpbX2lme89FUAuCWHX0or7Dg3CmTkGn8mloANOXKNn9kjnLmuAldHbKf4nQAIIHWlp3DSM+gvU6Li2fTQ+O4TpsGkCJJOMVRL4VYI6dJAr+7Nw0YGqBA07x5UNJYJo6AJ7uDJcoHjMDMAGDgWzZZ40FhkRMlZQ6hIfR5F5MzCQWibmvWoa1Fi5HhyPH3lkjp+LZUAw8k/IrqHNzeGIByp6cHAH0DnJTswaLFViytHoXR6IaDgkrXGvGoNhUEQZGueAMg9Z8CXa/dOICKSrMIcn37BsUCM0bWQsUBAKm/JWXycTBpIc6eygvJ1+s/JvEEQKp38/ZulJWbceViDpqepSkP/zQB4OKlg1i9th+njxeKgNBz6XrVUYBPOUrEi8sBD9RQoUdlxw8N9SHBobn9mk8ASGFODr7SIbzw793mxaCcKgAsLbdg264+tDYbBAAG7oE88IhmbgqKbNi5t19M/9mTgTZ/UwmAtOeuWT+KpSsswhnx9vVUPLqfAklp759iAARl7VjgEOBnynWL1HIN9Trcu2XA8ND4/p8AQO4uEVqOuV1H38B8v5MA8EDQEXAsL17Osa1imTGVlSS0gwSCxSUO5BcFaQdbtGht0gkwHIuv5SfwDikf/xeWoRc2fE51OWD6OB7E4TmRA4/Ky1EEla60ipzDZItHx95PHxvF8fB4dhFO/eGYhXvveDnyUNywZUCAaWe7DpcvZI+FagkXazCqZ0FBtIICG7bt7hHVnTuVh56uMN6ATHtHrlw6rRsHP9Ym0k599F6xMoQzHYC4bYYrl5dvxe4XOnl2ibE2Fs/7JeAH1moUSvoARxgXPOhS2fEVw/2YNIERRWW8tHkHiuFa4kGR0t2+F3l5hVlo2i+cNaGlkT6uorlC5WB03duQfC+ZPBx6vUugz+G382EL+uiMBuzGexJevuJSG3bs7Rfx6k5Tbt+eYE1/5JA3bCjy057l5Dmwbdcw0jLcwpbu4tk0jAxNENSZE8ol7DJR6r/8O3KIrKhyYFWNBRlZHricwONHejy8oxdhZ1gX0xb13YQTCGs4E4XCjMDsA8BAQSlkQEGxQ2gH6bjYpx0kz2LSChIM0pGxLw/uJ6Ry/CIq8BCD+KbKlylPrnOmANDXI9oYKHQMBZU25TjFF+rTx5RdJE2kTQu5mJ830WoKSRu4Zv0gFi02g8bz2uVsNDemhA02HdVDpMimKphySUPQLRyDzp/KRVenghYszgBI1RWXmrFtVw9amlJwSRwFB13TBIBarRuv/1wznj1NxbXLvGPCqMY/zjctdqfiK7YlYYNDf19fh8dJFJd+ii4GBc00AK5eO4BlK0bwwTuFGBnyGvVPejhiB8DN2/pRsciCi2ez0dTgf/QrCzMVAOiDP9qPT3xkEnaQoVd8AZD21ZU1ZlSvMYvj1dvXUvHogX8khjCDH2cABDyoWOTAqnUWUNIE2lMfPdCj9q4eNpsMftHaE8rzFXolAHDSD1biBv8RmO0AGDhbErKz3Sgpd6Ck3I6cPNkAnR56CkDd3KjHgbrV2OUuwhl04n+qHgXcPtMA6BOGNqzCYjtWrhkBeYPJIChrBANAcIoB0CdPcakVG7f0C3vFxqcpuHE1KyA2llyOKUwIUIU+bz5gzTbZsWtfN+jY5vzpPHS2B0HgFAAgSbNlRzfoaOzCmVy0tQRpaKYJAEmOQ683w+lIwtHDxXNmU9rhNOEzjvKwwaH/SduEc37BoePesTkAgLv2diM33443/61kPIbbpAciNgAsKLRhz4FeYet75oQJUMhrG28ApH1k+54B8TF+/EOKPRoOfuMHgKlpTmzbPYzcfCf6+5Jx4VQGBgcim9d4CThkVvhjMt4H2s8XVNoDwO/hPT0e3tWPKSZ8DSUAcNIPwoQ3RPlWiq8Qc7m2uQWAgcGcDSluoRmk2E6kJSRHks3v70Juez7OFj7Gz5xNYlPwwcvsAcCx7SAEBAnASCMo7B2ZqztaDWDAh4DejY1b+0Ff8BZLEq5fzkJ7qz+QMYWZBABS0cwsB3a/0AWyA712yYSmZ365SacIAMkrko6CiSWOvl8Em20Ks5RMsDls20nBgi146z/KmdkiZn6nSWgAw8+BDA8SXvtUmzDtOHq4MIb0KNEDoEbjxsFXu6DTeXD4nXz5ozImbZdSnwMrXLDQgs07BmG3q3FiQvijuuIBgBKWLLdgzYZRaDQSHt5NEfZ+Ho9qElq20H5NBgDJtGdhlR3VNRakZ8gaPwI/0vg5HMpHvQkAjO8eFuVbKb5CzOXaBAD+xncCu8B88XLs/YTuiKNVUSgzGVtEOs4sLnPgG207kWEz4tauq2hd0gjzqBotTboxu0HaIAIubrsMB5LoQUzWCFZTvuECOd9wc6NBxBIcCjlC4dr7hde8TfQKo6DWNRsGRTzDZ0IbmOn9ig1sN552gukZBIE9ItXgreuZqHuYLosY5vg46ufNrz5yRtm2s1cEpD1z0t8reOq3FF8Li5cOYc36AWEH2dEWekQXdT+n8kayAbStDBsc+kv6e+wPl+jEZBzwMoqEa5tve6ZcA33QHPxYJx49SBMOVsoXB+6it0XcvKMPFZVWXL2UiSd1E9ggKo4TR7bAXpGT27qNw2KvPXkkG8P+x94c8OTK4W2Wohhs3TWEgkKnsKm7dDYdne0TRxSIJ3iRVzOFlqleYxXhzOx2FWoJ/O7p5fiC3ovbpnI53vy/+5PPJwJBR7eRJO6iEZgvAEh9IW/Ef8FOkbXgv2dfg3VxJ0rLHSIUAF30hUaxBpsbdWhv0ckBqGcFAI6vRTo6IhAsKrGLX7Y263HvVppI6TYBFbEWMzd2HWlWN2wdQHEJaQPVuHoxKwRQ4gmAJLwhxSUgMCPTift30nH/TkaYuYkB0IJuXb+pD5VVoyIw7qOHvgDRMdTPmoVxPkpLd4ICBj+po1zF5KE5Ny4KDv0l+xIRHJq87bXiyVPhZFIX6pPMIvRSrGFhwo8Eg+4YRaYKAJdVD2H12iGcOpaHro5wqc44kMUDgOB+ULiXrbv6xb5x9mT2xKYbXPAKO54SVtWMYGXNKAYHkgX8jTu1+SgodKR5Hs8KYwQJlYttWL95RHyg1j004OYVo8ioE+niwthEgcAJ/JYsJ/CzwJAiwWpV4eEdA+oe6BRMZvj2fgkAjDR74f8+9bt19LLNiTvnEwDmQIe/wlYx7p/DJfSqCKIkZGS5UVpuFz8+u0HyzKLg0wSDrS06uJzjm4jyooqseYteAxi6VLJNDuEsUrZAjmPY0iSD4OCAwpcu8yngAqCseZOEAflarzaQbBRvXs8cG6d4AyC1SF6Lu/f1IDvHgbqHabh1gzIWBGkeuefiSk9f0DhRgOgDL3cgNc2F4x8VYKCf4pQxBzOGp3u8BQkvv9Ymmjz8NtkBTn3bMYgdeKs3OHS+pMdGVzbWeDKFU4EdHiR5w8L8QFcXdViYuQqAe1/sAuXifuvfS8RxpPI1NQCYYnThpde6xIft4XfyIoeaigkAJdRsoFSTZpHr/eQRkwhzFXLFSQNI2ZYomwd90JspldvZdHS06aY8mwf1R6WWULXMhlU1VqQYPSKVHGXteFyrh9sV/pnlQmcCAKPflebQjhl9J6fyzvkEgMuRiW+hBm548Ms4B09ADEB5FOmYsazCLn7y8uX8ixSjGb+EAAAgAElEQVSWhWCwsUEvawYVH+rpBUCx8ajIRo4CiI6A0hnRRY4u926lBxpYM5+CyQGgb7xc2Lh1AIVFdpGl5dI5Cuugi6+nsN8CJ1vAnXt7kJdvR8MTo/BMHgv3IxCJ2VkGAFKRzEwHXnipA+bRZGGz5XYzDchjeCj9e7B2Qx8oTdeH7xZhZJiXIi+GpuN/qwT80LYK+ZJOMSzMl+N+JMxQ7zGKhBuIWI6AyQzl47/QKmxnz5+eyLN7KgBQwt6DPcgvcODUMRM62sJpH/16HjUASli/eRhLlpvR06XBqaMmrwaMp7WcrAawuMyOLTuGoDdIaHiix7WLaeM2dgynIPE5yyznrwEk8KtcbMeqtRZx1Gu1qHDvVgrqavXwMBLgcNtMAGD021IMb4PoG51Pd84nANyFAvwulqEbVvyu6krEaaKvyrIKB8oX2pBfMA6DZE/S/EyP1madn03HzACgrxOU05e8hkvK5KNh0gjev5OGgT4tW3HEhqeQrpLNixk164dEWrnHtam4dyfDL6WUT8r4PI6kmdu2uxdFxTa0tRhw6bxp7JiH3QcmAFKxpSuGsLpmEE8ep+LG1ZyI6ybWAv6jRE4gO/Z04+7NLL9j6FhbmL77hVOIfWnYsDDf0z2Kc1gYBt0xikwFAIr4fzv6cO0SBVcPE2hcNBx/AFy2chhr1g3jca0R16/4cv1GWAdRACA9/1t2DIq4pp0dWpw5lu13BBtfANRoPVi3aWQsldvlC+liXw64mGDHhTECQOpj5RIbVtbINn42qwr37xhEaJkx5QCjXW6bkwVAitZQVuFEbr4bX37tiwkbwOnb7uZfSwSA+3/9TwM6phyomfdG5Tl8hNbFfbFPFET6U1iAX0AF7mMA30JgDEBqcaIjWrJ7K1tgFx7F+YVOEZ9ODi+jRVODDi3Neti9sZzC405kSIwkR+DIhNZHx6NkI+jTCJLm8sHdNPR2c7RHMcgHID3DiU3bB5CT6xDaQLIN7Or035CjB8DgI2XahDds6UdFpQV9vVqcPZELe6wp08KIR2EcKBxNQaEdl88HeSJPxSPvJwf189VPtsJmTcJH7xfOrWNgADtcOfiMYwEMCNWc2uDGP2oacS65N26jyPLSjAEAlQXlABuw50A3cvPsePs/iyKk9+OBUrAs4bSTeQV27H2xF8NDyTjyfu6Ex5L+dTIYxltclpc0nLteGEB+oUM41l04lSXbUY+V4vYrsJzSdFE0gs3bR8SRK6Vyu3SWYqUqaOc5R8xhaT/wZnWShKolVlTX2ES8WQI/CuVSe98AlzNw84hWUzxZ2POJbkgh6HNgwSInCorc4v1E4cM+tfTrCQCM2+7yHFaUkp4hvfw734bdRgtcXuRzFQA/j6XYjUKcRAf+CoExACcDXlqdR9gL0jFxoTe8zDgM6oXdILn5h/JEDIClCCfhgSoz24nqVSMoq7CJ41gC1bu3CATlfJvKVwzyeSskWFq8bBSraoaRrJHw5LERt65leLUA8QNAn/zVq4dQvXpYvNzOHM+DWSlgNve5nUA8Cg3z4sudoLk//mFBxDzF3CYVywXJUbO+H4uXjgg7xL7eieYvplan5GbSAH7VvkxRA0jZQX6a3IQTyd1sLXUkIWcrABpTXXj1kx3Ce//CmUhaZC4oBY6GUt/1ejdeerVbPItH3sv1euDyCHgyAEjPx94X+5FtcuHRgxTcvJIeYJpBkvKhKDwAarUerN/y/7P33kFyZdl558ks7w2qUCh4bxquG2jvp3sMOSIlamWWoY3gSlzthrhLI5FLDcmhFakQJQX/WJEabuxqY0OhXYU2QqREM8MxPdPeG6DRaDQaruCBQgHlfVZlbvzOeTfzZebLfDezqnva5ENkZFUh85n77rv3u98533emZMeuec0pfOvVdjl/hkVmiYd3FQAgi7DdKu6wHD9Cve+ruKNZq5lEbf7XWnAPIxs9uj9g47NlR0q27QL0LSno03SlS/UydL5BrlxskD/91z9XA4Bxg0bt/0u3QO9AZ+b/eulrkloUmZpMBq86mZpIyuREUt+np5NFD7vtMQICeVm+FJ/PajCAvy13y37pkf8kF+RP5FLRQfxFGrmvEobAa5Aw8fqN5jXIyuvGtUa5eL5Z7WVyKrQVAKwKAaA7Q1g5xCJbt8/pAHH9apOceKdDRgkNR7SA35/igVxbh+UGwppNTdXJay/2yu0Rj7yjUtC0zPWTI3f0/jGZm6uT55/prx6cxVzWmr4Feforw9l8wLAwaFXHkILzwDrkK3/thpw/2y5vvf7pUQNrm2RE/tX8oUhbGKa1ZcloneB/2Xh6VQQhn1QAePCeCTlwaFKe/V5fsaF5UedZHQDIYuypL99WRu7l53rk0pCzElpdAIi45OkfuaNuCu++3S4n3233N5b2CDO7j3Adjzwxoewbbg2vv1SC9Qu35woAYELSluN31HL8fMUdlYHdygAgla82b0/J9p1UvlqSZJ0DfQ1y4Vy9gr4wG/kX/9vP1gDgqg7On7OddfR0Zb7+f39dOjrT0t6Zkfb2tHa68Ab7NT2ZlAlA4XidTI7bz1MTder9lJek/0MEgN+Qh6RfmuUP5ZS8IMOrAgCzO0kkhNUpzODWHfOybv2iAq5UKiFXLjbJ0PlmuXmtqRgoR2JCP6DoS5vQ5B2dS5ojuGX7nDKC2EDACI5n7WOiAXvVXnt6CRnZvXdaDh8lN1DU++y9411l1I+lH644VfGmLTPy4KN3NLz1wrP9cvtWFWAzHtcqE3fkvjEtFffKCzA5Hl+qdMyI2KWqkdtT8md/svFTYwrtLhtbmK8t7FVbGBTAFkvIXaSrE/y1phMrbs5PIgAEiMH+Qe78xZ8Ollgsx6KW2F5UeO3Yzew/NC0fnmqTt/Py/lYPALLAfOordxSUvflqp+YYOuBfeML+rFj++SG2OHx0WvYfmpXlJZE3X+uQc6fLsH6xTVn++rlfW7YvyN1HZ6SzO8jxOw7j16IMm8/mf63xADCRSMvgxiXZsRuiISUNDSLpZRbz9XLhLPnoDZJajDa4rgFAn7tV+0zJFijMAeThaO/ISEdXWt3NeVFc297TUl9QshY2DJZwAmCorGGd/TxepzkUJdx8/cBZxFmXygFk4vmP8oQ6kv2GvCOnZcLvGL7zewFCaWpOy9Zt87Jt57yWIWIjjI4449KFZg3JKjD+mACgu1h89FANO/sYgODJ4+0BI+gHPL3Y2NCumCQefHRU6xtPjNfLm6/2ykjZUHTxjY0DgHxjYHBeHn1yRJO033iFXL0yJrdRPd7jXvORhx67LZu3zsqJY93ywUnnD7iKg0jEeezcPaks51uv98YICFbxPFZzVxmRp1Nr5aeWtkid5PuyLdctyFTvOXm26bJcTKfl/YlumU9H1L72OJ9PIgCkrOCjT96R944H/pWx17FyBpD++eiTY3J7pEGe+VZ/waJrdQDgwLoFeezpUa208eoL3XLxQqgykC/zFsMA9q1dlAcfm5TunmW5fateXnquy6og+canfc9DU5sysnX7ghw8MqvHI8SMjx8GzqnABsxbuBFdWiX+zgfXxbkQ1t22a1G2bEupwpnt1s06Of9howydayjKOY86txoAjG3y2gfKtUCUCCRy7kwk9AFiJciqiWLXsIad3cv6e0dHMXMIIJqALRyrk/HROq3ROD6alBlN5o2fjb0EJZxsIiFrpVm+kTAPwP8p87KMiall8zYfdjJGLBLVNrBv1IJERNLbZ0tIwO+loWYNE2OVkH+9KwBi8c2mx+/pXZIDd+eAIKFhQjflcwTd1fmdX7gt6Bt3HWQVP6mLBJiCd992uYEez6BnCByPtceeui1tbcty4linvH+CqiFRqQhVIkARqa9Py9M/gp9bSl56rk+uXl7lKh0R18oxf+xvXtek+m/+1/VVsagerfyRfuTxVL/81FJOEAJYG1v/loyvPyaJTFIyibQkMglZSqTl+ZG18uzwOq9xoPKT9hNt+O+3NGCj3//oXx+W1vZl+Ys/WRfvvVcqV67wZMoApzV9WBfd1rJr3/1mf5E4Iho7+YFCh2tQ+T70+LjmwL34g27z3AtvHqHdUu0LkMFU+e57p2XfwTkV2713rE1OHm/NsacVALui4xQ0gAK/nQvq44cnLMDv9PvNcup4s7Zh3OYLCgtBa0QvVB/a7bsWZdvOlLS22SdGbyfl4vlGGTrboAQKm+8xawAw7u7V/r9sC1QCAMvtSJnDzrR09WSkq3vZXj1pXWm51Y37PvmGgMGx0XoFhmN3+BnGMP9hrAQAHpAe+e3EPZLK4AH4XNT6LLKyRDRMqBwAsR/OV8Hg9nnZsmNer52NMDlA8MK5FpkYy9Umzjv2ipjC0mAHH8H9h6dkS0gs8u47nXJnpJxquMrrl4RQnP2BR8a0pJ0qhV8uVAqX6EWeAJBvUzXkiaduS8+alFw42yZvvNpTFHbzYRTL9Wfynr781ZtCTs4z3xmQ8VEflbXnYFMCxO+9CyuPcXnztTgbEc/jfMwf273cIb+2mBOEjK5/UybWH5dM0p6DvC2dlB+M9MuzwyifV3v7+ADglu2z8vDjo6rEP/GOH1tcPYuZEdwKvvLjI5qO8sy3+iJzfVcGAFnIzcg990/puPXsd3u1ykfRtgIAiJPBI09MKhgbGa6XV57vVJFX3rYqABAz+wU5fHRWSQqAH2zfqfdazN7Lk2X0BWOlAGBH57KGd3fsoSpVWi+TaNmFMw0a4oUgKdx8j1kDgKs9dnzO9rdaADDbbBEzb3MzwHBZugGEvcv66uld1nI64Q311ejtehm9Uyejtw0gEkoO5xhG3p5EQp6SQfmfE/vkRmZWfk5ei+YXPyIG0J1TPmDNSHevgUFyBkkyZuP6hs61KCBE1JBrt+Irq0a0UmqH4RxB8vWwjwEI5ucIZq8k6mRin4zc+WZk194ZufvohKoTz37YJsff6sqrtlK0swoAIN+FMXvkiTuyfuO83LzepEydC+Pw/ysFgOwDUQiVHRbm6+S73xqQ+bnqwpZ+12rXpCzgUkK++WefQhYwLfKvFw+rICRRl5JL9/x7kaT1+6htOZ2Q3z+1v+pwcOkO+fEAQBa9X/2JYWlpWZY//8+DOXPimCelWgCIPybM35p+mOkeuTwUCsmGjlktAOR6jtw/KXv3z8r4aK60m3++W3mWkdSNg/fMyP7DM4qV3n27TU6dCLF+4XZbEQCkLnxK7rlvRnr7lrUE6AcnQ8DPHecjBIAA9C07U7JzD7ZitgCanU3I0JlGuXC2QW7fKh8FqwHA2OlGP+AZEPPb2efxUx8HACy6ScHsTB5dzxoDg7xjMQA4DOcZplIiY3fq5c5IvYJCABTsYV6ZpURCflK2yd9ObJN3M6Pyu3L8EwAA80eztetSmi8IE9fYlNGwB2HZ82daFIxFlY1aTQDoQBH5euQIch5shKkpMZdXwD06cTH28Sg8X6wxYAMHBq2KyGsv9crIcAmbkwoBoF1PRo4+MCa79swoS4FCeHbWQNpqAED248x98SL8wXfWro5Ao8yotQ9T6iMTWgEFVfCnasuI9GUa5bcXDkiy/5yMbn5FMnWls+oTy/XyX24Mytujq618/ngA4NbtM/LQ42Ny8riJn3y36gBgRh5+fEwNmMnpJf2h1FYNAMQD7+HHx3VcGMbg+ZkeSS1aRGY1AGBX95I88oUJHePv3K6XV57rjGYWs+Cs+Op82o3IA8BvYHBJBR2nT7bI+8dbZD4q1LvKABBV8cD6Jdm1DzHHos5jlBy9NNSoeX2IOjKl10N5F1wDgH5PUw0A+rVTyU/9MAFg1EkxqUPXM1Cs6V/WFdyaviVpas4N6iikAIGjdwJQeKdBfnL4kDyWGZRnMtflf5fTnzAAmLtSBlpsZbbvmpP1GxdUPUtoAiUxSdZZ8UgVuYj57Vk+Lw4fQbz8qCzCOHjlolUWGR8rzFcM9urxpEWLR4IqIvdNaDj1HGzg213ZySV7zlUAQPtuRvbun9IqJXOzSXnxuT65s8ql6g7ePa65jdevNmuJr9I1Xj0fxjJtCQv440Eu4Lf+fNCr0L3nUT/6jwWPKKHgn+ufk/H175RlACWdlO/fWivP3SIXcDW3jx4A1tel5Ud/YlhDsbB/Diz5XIUPkMnPYSFfjrq70yoye/EHPWW5j0oBIBWRMHju60+pgO2V57vz+vhKACCs312HZpT5Y1F28nibllOLfYYqZAABfoR6BzekdHGNivjdt1tkbjbIqYu6MasCADOypm9Ztu9ekG07F7N5fcPX6+XM6Ua5dL5RnSKy26ocM7e7WgjY54mrfaY0AGzrznzxf/jdvP/3Zk+qzluLAiflEAbK5LQCwh6AYZ8BQwQpbnv4z74ga4b75eVtp+TbrRfktjKG9Xmu+JXkFPp0Ge/9FezMfY98HsLDhInX9BtTAoixfMFmGbsTAcaqbvPoKyKcdPDwlFBvk01LzGVVw7nv+EXPS+cOdnSm5P6HxtWzbG4uKe+80SWXNIRV+r57qZE5xYQISswHHxnTwu3k0A2di1IIe6DYyGbKyAMPj8n2XTNy8XyrvPpSb7RZuk+nKfmZ3Lnt2D0l9z04prY6x99msv8kbmXCfRmRP+hsl7nNr3swgOuUAfScFz0bojLBQ9xOowDQkfvGZe/+GXnrtS45c7oMU1tlrly4PcjhvfvolIrJvv+dNQUlGKu/Vq4LodOTXxrTsRRwdvwtrqXwOfE7RiFrxdjy0GOTGt1hwf7qC51y+xZjWv7my3ZFdZK1g6k84HfhLD6oLWpRFrf5A9viPTF2W17fgvT0hvL6zjbI+TONmroULRT2VYD7LWL+8t/UjKDj7nPt/8u0QPOnAgCGLiA0NhFCBgj29S3L//rh09K+0CLvPPWaXNt5Wb/AShBxye3herUYwDLBEm5jgIAf2qkaBEQBR1MSz8v2nfNqu8NGHg5AcOhsSy5fcJUBoGsLag1TYs7Zx2iO4NudMhb4CPo1SZx4JCPbdszJPfdNCHmhhMBff6Unu0ov7KaVAEC+i6Hy40/hWbYsH55ql2NvdRXkj1YLAC3cjNXHxs1zcvr99o8AmOXOjWN98UdRIS/Kd/7yI65KUvXoWB4UbJCk/KMD75ZlAJfSCfmXmgNInm/VJxLxRc+deX8s/4OocL/810bk9kijPPNXfeVzlFcIAHfsxv9yQqMdHKuYafS+iKJ22rB5Th550up7v/Zilwydb4kELSX+WBLIOYXv3gNzel9R9wIuS7F+1QDAvgFy/HKMH8DvvXdaZWqSvuTXJpUCQK6L0C55ffj2MSbi9oCQA9B3+xYh8zDbV9w1/Y9ZA4A+I0L1I7rP3j8Hn/k0A0B3exokKf8x8QVJJhLyW3VvyOjAHWUL+9emVHbv5PZ8noRglGe3hhv0HWBYVPHBD+2sKgDMdbWM9K21fEGYQULf2XzBD1vk2tXifMHVzBXERxD7GI7NRo4ghtJTE8Ur9+LHIw4A2jeampYVBG7fOafh77ff6JKhc1it5H+/UgCo+25eVqC2dmDRxCHPrwlNmisbLkjCf/JLI7pvwOWHp0rnYVU+dOSfG+DvS1+9qXWQv//tgfhFS+UHXOE34ifZv90/KocHrouUVAH3ZVXAnnO25znHn5vuyPtjuQ8Cln7kx2+p2v+v/nxtQe6sLxaNPzDtQT3cx58eVdus7/5ln9aLjoIUXo2Sd8iM7D0wI0fun1LvUvL9Rlwt8SoBqzZnhnBoSh55MqfwffXFzsD5oPRZ+gI20CS5hPfcP6t1cRkXw8DPHcF3f75gDGuvXXsXZPvuRWlqymglKCpykNd39XJDCNgWNJ5vGNuzzaOekRoD6NX7ax8q1QKfBQA4KK3yR0nzAPyH6RdlXBZDl5vR+o79A0vSP7Csps2EWynpxqYs4Z06Gb7RILduGiic81R7rjQEHNcryQ8kNLtjdy5fEKscWMHzZ1rVdJltNQGgOyfsYw4dmZJNW+a1jS5daJH3jnfI9FQ5JawfAHTH2LBxTu57eFxaW9MqhMHOxeXslLyuqEYrOCyT9JH7x1UcQhs9//0+Le8Wy/zG3RARoTTgF39kWLp7llTUcvFChWbUJY9R3HZH7qdG8LS8/kqvDJ37pAlC4kEMCOsL/TflyYERqcvUBT6ASVlKLMvzagGT8wH8tABAckEPH5nSRdHJdz0WAJ6Te2G3wCrliz96R8t+ffebfWaOHLn53Icc2IVdvu/hSdm1d1ZFGM99rzv/ma7yfHnmUPeS68e9PP5Wm3zwXgmFb8F1+AA2WP3DR2Y0145x8dKFRjn2ZqtMBmNgeJc++zP8Xzocy3NOTt/uuxakr98iMswTZ08j3GsMihwU3pCPFwBi0P1f/uDna6XgPMbt2kdKtMBnAQAeljXym8l7ZDGzLP9dpoQHYODTRzMwWPX2L8nagZT0r1uSgXU5J3b+H/8r8m1u3azXd8IvUVY0HzUADAMWck5gzHbsmdOanGyo6bCUAZwVsQPeZFf5D67pX5TDRyZlcIOtuMnbe//d9hLMR2UAkGsgif7o/eOybeecJksjRCHESntXwwCGu/mefVPKNOL59epLPXLj2uoYOuND+KWv3lL7j9df7q28Iknks1jcdg0Nafnq37gudfUZ+e4318n0lA8L+3ENdZ7AQ0Sak8uyv3tcOuqXZGqpXt4fpxJIPpv1aQCAa9ctaO1dPOu+/Rdr44UMhjIitvJt19e/KE9+6Y4CnWe+vSbGs9PzPmREmmHHn7I8XGqZv/D97jzrJD3RKs4XAcb9j1g1D8bKl1H4jvpbJpUDbO0dy3Lw7lnZsWde2+PGtQZ55/VWuTNS+lmoFgACjtdvTMnO3YuyaZupePGsvXCuSc5+0JRn3RJ9jI8SAJo4EksZXmsHl5XY+G/3f70GAD+uIe+zeJzmtq7MF386XwQS5aHhLQyJaKQioOSp+Iz+WPFfv5hYLz+TvEuuZWbk59Ov6hl4gzO9MDOvXrtuScOvsIUMZu6asaIheRmGEKYQUEjFBp/N+zyidhbR6AnJCJYyqIg3b1uQxkYLETOgXzjboiKONOfmd3re7CGTHzmCAMGwatjlCJZqC89ougxumJd7H5wQTFPxf3zzlW65PRJhGeN5Xe588Al86LFRDd0ALk8e74z3lfS4se2dKQUDrW2AwB4ZOr9SJjD6wtatn5cnvzii6uzvfWuVbGg8ri/+I57AI35H9olV3J2XyrbUeZUAQFgafeXHb0tdEjDeJxPjfmDcH9jagXnOEGWwEZodvhF6BnxDihHX1te3KI9/cVxBw+mTrfL26x2ReZfRlx99c1igHHlgWnbvm9cavu8db5P3381X+PqCscJTbmtbkkNHZmUHjF+dyPCNenn37VYFgPl5dn4dp9x5MPbv2kekZSHrTXvzWr0yfUPnClS82RMtzR66j/hfe9Q1ZGRNf1rLxQ2sX5Z16/MLKkxOJOTWjTr55R//Wg0A+o4xtc8Vt8BnAQD+vcQO+VvJbXIsc1t+L328CgCY3y5MxYQAAIKOJQQYUqSbDcBF7iCAENsW3imZFI3hKkQs4Z1EAsDcB8xSZkGFI+s3WWhkYSEhF8+3yPmzLaqCjkOClYaPYQQBghyX7erlcobS3sVXdF9cz/5DU2p3wbWcPd2mZtV5ie9VNCeT96NPWq1iJtSXn+/1KtlVdrxIiFAt5OkfGdGydK+91LPCcHDpC9t/aEItey6ca1XGMe6efjzjnN/E630uq7i71QaA9fXL8uUfu635Z88/06t2QL5bJQAQ8PeFL48qs/jcd6mnXVB9pioAiCn7nNz74KQCPsQejA+2Fe/QFwBu2LQgDzw6perhm9cb5LUXOyLD1P4gyM6IBRXAb+fueQV+t27Uy/G3W+XmtQbJRK1qPRu48DywpNq6Y1GBH56BbFTnOHe6US6caVTf0iyQi7zZqwsAYR97+9MyuGFJ1m9cUoavMbj9zDd3RpJy8xqpSnUK/HCLYPvLP6yFgH2fxdrnIlrgswAA/3HigDyWXCffSV+V/yNzWq/Sm3mLAVmuyRJJKkMsycBgSrAeIGyMoTObA4SAQVaoMIRO8eZ9HlG90/PcAASIHwCC23fPaR1gNpi0s6dbVN1XyqesUgDoTlNrDR+eks3OUPqCiUXyDaUrA4Bu35hV3/fwhAysW9SB7q3XuuXKpWDSqgIAsl/C/kfvn9AKJdPTdfLi99fI+NgKyrsF5wG4fPorI1qii5zAS0PVhpnLXVhGnnj6tlY9QTV94RNhEL2KiC0ai1Q9Xq8uAMzIY0+Nai7ssbc65IP3Oio6L098ImsH5uULXx6TdEbkB9/pjQ77VggA6fP3PzwpO/fMqTr2+We6Cyr/VA4AG5vSct9DU7J914IJuF5rl3MfAoij+68vACQV5MDds4JymNAr6TfvvpXP+PmC06gb5M6DcWvPgQU9fwAWZtF49Z35oElZxjJpgQW7XSkAJOpExZIlVRSv27AkTQHZi8hk5Gad3LhWJzevQzTUaS5oFGVbA4AVPY61Dxe2QO9AZ+aPvvsrqgZbXBR7X0jI/HxC2aSFOXvnb/o7/x/8XyYTX0g7Eoytcgj4nyfvlb2JbvkP6bPyXzOXPhIAWBgWZ8XGYDKwPiXr1qcUGBKOZWNQGb7eINevNcqtG40KxGLL2a0QAOa+nhFUawhHsFwBpOogd6FFzp1pUXAaHqyrBYBZ+5jelOYIIlYBCAM2qYzgxCK+IeDiy89ozuM9909o+Jbzf/v1LplfiPf3KvWUc63bd87IvQ+NSSadUNbuyqUqAVuoD7d3GAjEUPeVF3qr3Gd5ZNvYSA1YKzv2vW8NyNhq1iaualj8fADAQ0cmdaEDa/bKC90Vs68+AHDtwII8+eVRBR/fLwX+SoDkUmCXBeETT49rusi1K43y8rPdEaXqKgOAm7bA+k1qmPTq5UZ5/aUOmZ0p/zzGAUCYuD375xT88ZxTBvSdN9rk+kxjmr4AACAASURBVOViD9RqASA5tJu3Lsie/Tm2785InYK+obON+e0SccOie3rlALClNWD4Ni3J+k1L0t4RJhDq5MbVOq0WkgV8hc9lxLnVAGBVg1ftS64Fuvo6M7//n39N7UYAC7xcqDOulRYWRBbmkgoKAYz6mkvI/GxS5nifS+j7whyUdSKXNL3KAPDfJR+TnkST/EH6PXklM/yxAMDCtlEKv29JnejJk2PgdUpjVsq3bjTIzRuNGsoAEHqF8SpgAIvuVULEfKvmNASEJQ4boY0LZzGablGQtlIA6I5L4vqho5MyuN7EIpcvmljEN1cquq8lFFTd99C4MjC0I3l8Zz5o90vAL9ipu9a+/gV59Kk70tKS1sok77zZVWCuG9fzi29fe0dKw8HsE5PrM6crY4p8+oNZwwzrhPX9b6+VqUm/PDSPq6niI591AIiqdUoVvwgO8ODzzfsNN2YcANyybU4eegzmLyE/+HaveguW3DwZwHWDC+rvB+D44GSrvPNGhy54ohZZRRgj4lPt7Uty70M4AiwqCfDmyx0ydB66Kp6OLwUA6xvSsnf/vOw/NKtzz9RkUpXDQ+eC/foCsZINnNEUnp17F2TbjgVpaBTNUxw63yinTzaXrsXre1wPqrCxaVkGNywrw0dotzswjKaJx8eScv1KvVy7XK+h3bxqIWqpE3W7iv9YA4BVDF21r+RagBDw0z/9z/KapL5OFAjyYDY323tjEx5r9nP4xf83t9jfwjV8o9oYgDg3Y6BwdiYpszPuPSlzM0mZCf6WHaw8gGKjJOU/1T+th/vj5VPyjFwvfXsjRarxg1iAKKMwVv7fQoCNlS0gkHDxusFF9SMkr40NwHzzRoPcuErIuFEHvwQx5mo3D6CIrcu2XfOybce8JoKzIWhBOHJ5qDlfDejRJKWAI2wGdhCUuWMjRxAgmD+xeRwgry0yCgApVI8qcHKiTisw3Lzun4tlu8sdFybtwcfGZHDDgqo6X3quR8Zh1So9tdB5Eg5GvdnVtSTvv9euRtq+O/RVPGNE/ciTd9QY/Pt/1R/Y21Tbcar/3orCrNUf1lMsUj04tYk3I/dQeu3QjKpaf/CdNZ45o57HDY6x/9CM3H3flI6Fz32vR0a18k+ZLZoCy36BRejho9Oy//Cshgxff7kjm+9XDXtmZdxm1dqFsR1w9vbr7WrVFMfslboKBX53zcn+w3NZ4HfyeIuGkfOMouOQc3CAwn7Y3JJWMQe+fd09Ns7dvlUn5z5sUkHHwnxunPVS8lp3KNqi+j8CIRS66zelNLSLiMNt01MJuXG1Psvy4TSR2+LZRDuN4s998w9/oSYCWcl48nn/bhQA9GeFwrNlRuobRFpaRHgICRMADFmFtuh7Rlra7O/4vgEoozaee9hCHhD34uGZnkrKzFRSpqbqNBzNxNovzfI7dUdlXcLCeKlMWoZlTn4vfUxGxIyM87aPEQAWHtoBwnXrFzVsTD6hA4QAwJvXGjVkzDsMT0WbBwB0+2OS4BwIEW/cshAULE/IxQvNcu7DFivV5BG3jesjvWtSsv/QtGzaOq+7u3G9UU680yG3NbG9OpSFSGTfgWk5cGha6hsyOrm982ZnCYPcqBYsPC51hKfl8FFLkCfXEKFFtefHEVn1P/n0HVWTnzvTKm++2u0V/vcFgBxjy7ZZeejxUWVzYQLD3okV9ZsVfPizCwAzct9DE7J736ymSzz7vbCReFyD+QFAlPyIMnbfNStjd/Di69XFb+xWBgC2ti7LY09PqM8pArWXnu3K8/erFAD2DyzKQ49PqTvCxHidvPFyhwre3FYpAGT8I78vzPhRE/jCmSZZjmInKwKAGWXY9tw1L5u3plQ8AtmAmAPfPto4eq6JpNmKP1oSAJo1y6YtS7Jhk+XxORIEkuPGlXoN6RLaZYxnXFlt0FkDgLFPTe0D5Vpg9QCgHcVL9JAQYUAAELa1mVGzvWdUVdbanrb3tkwkFllcEE1q/hvf+bJ0zbZJUnKD51ImLTdlTn4hsIP5pADAwntA0jO5g4SLBzemst5+JihpkOtXGzV3x0fJG2nb49HtUTpv2bagSeIAFjb8u8gVJESMf16pLQ4Auu8h6IAR3Lp9TgEv5d8AglS4qGYDTKK+xTIGJTKLgeNvd8q5D32AWzTwpLTXo18Y1RJyAMA3X6siJBy6mLr6tDz2hVFZv2FBbXlefqHXrHnKbJUAQHZDXeIHHhlTo+vvf7vfk6GqpsWjv/NZBIAsjh54dFxzT1mwvPBMrywteQCzHCyKbWDSMh55Ykw2bV1QQPXCMz3Kvnu1ZwkAuG79gjz6hQldcJ860ar1fAvLrvkCQBi6e+6bkb375zR3+L1jbbrPov15AjTaFJuYQ0dmdPEPEHLAz+3T99yixtAdexcU+CGoYANwnTnVJJeHGmPTRKoBY9w/QrobNqdk05aUdHTZ2SPcGL5eJ9euNGhoF9Vu1EKymmO6664xgMWPV3VUQuxj+vn5wA8LABa2cNQEmKjLSFtbWto7eGWkTd/T0tGRlm0LPfLUs49LXYGhrD6MyWX583tfljNJJkhbfQEYYRQLBzLvideHZfNgzkr1rI5OEoQX1c5lcH1KGgJBCWwoVTIAg0wYkaDM59zKQDn+q7s3pUAQQ2Ytd7QkxgqeaS0SjvB5XwDoDkvprIP3WIk5TpfQMJVFRisEgrlLxQLHvANZQACa33ilW/3ySm+lhwsAOawa9hZUSHjpud74Ml9ljkT47MFHxxT4Dt9slBd+UJ5J8u6HoWPu2jst9z44rvWaf/CdPllcgUCm0hHPC7BUulOfz3uRbF4fyjsaE/tDj49pLWz65ovPxoP24tMtf9ymprQ88cVRZemGzjXLay92Z8cjr/Ys2D3gav/haQVX2FC9+nynLjiiNh+QxdjzwCNTOsaSHvIq1i4TlbBnuSNzblu3L8jhe2eksysts7NJOfF2q4V6zcc+u/mcW/jT1H/fs39elbwwbrB95043yYcfNMnURJ1nmoCVrvO5h8xBhHU3bU0p00eki21qMiFXLzXI1Uv1cuMaJUXj4YjvMX3DzjUG0GfQqH2mZAt8kgFgdKTQHrIvJAblHyb3SkuieIBK1aXkvYePybV9F/OuG3YNEIjfE3lkvBgwJsfrNMRcVqnrA7JWAADDzCnggUli/aZF2bhpQbp7bcRkvIIRhJ0gfxD/QQW0PudWsgfkD1pMhFi7UCqKHEYb6Ork4nkTjriSVJUCQHf4zu6UHLp7WrYEtYYBtafea5cb1/ySygsvtb4+rSXrdu+b0UNcONuqdjTRdVPjBmhynqbVc4+2PvFOp5w+ZVVJqtsycvSBCdmzb0bbEBBYShRTDQDknPYdnJS7j04G+++TSU+D4uquJzwNVw6yVnpMewh89uL1oeyOyI99+IkxLe938UKLvPK8X9jeBzy4z5Ab+8iTZsR86kSbHHsTkVCuX1UKADu7luShxy3ki6jshWe6ypSLK1Xgw9qJfd370LRs2LQoqcWEqnDPfIDtUul+XyoEzNi1fde8HLxnVljUItx6/90WLQuX9UotAF4+ALC5Oa1l4HbsWZDeNTYeUrbzg5NNWhYuT6DjeftLgTFUw4PrjeUjl8+xi8wfePBdvtggVy7Wy8R4AcvncdwaAPR5fv0/U+3I7H+Ez/gnFQD+g3wRSNRz7z/hF9+SYnzid9siw8nBV/dKt/xO3b3SECGeIBfwd9JvyZX2Uc3RYCBq71yWjq60dHamNdzqVnHu9sJ4AQh5qGENx8fsBThkcPGaoH2BWIVAEeGDhoo3pGTdhkUV5rAtpURZQXIHr19BTOJffinbrcucMxMjg/nWkHAE0Hn+TItcGmqWpVRBeMzvtmpbdvWk5K6DM7J1h4WGmcROnWjX/VYOuBLSs2ZRjt4/qWWuUNQhPKGkXKXKTZoDs+sHHx1X499bNxvl1Re7VyC2wIh3VoEg5wLrk/U0zBtbPBsvYjzauWdGmUD2/+oLPXL1sjP6/SgHL4/Z7iM4vGfk0fPIadl3YEYOH53SNdS77+Dz1+bX/zyFAUAvxB6IM7g/b7zSKUNno+5PfHvaJzKy5645OXL/lLoMfHCyRY6/WXk/Z0/1dWk5eGRW9h2c1X2dP9Os9XXjrF2iGhfgR17xwXvmlEFE6IbalvNbKEwl8biJBoiLc/tQIWPdQm7fnZES410VSl4qEG3aSi4fY2wul4/8c5S6hJYJ7YZFJHELgOjLrE7wQfsCRLt7MtK9Ji09vZYq9TNP/GpNBOL5tNc+FtECn1YAyKX8m7qHZZ20Sn0IBFoO4Kz8wrKVhMufY90ka/mGAEF9daelq2dZE54Bi2FMxKqPEPLEWJ0mE4+N2jt/KwIqHxEADF8DV9C7Bh+pRVm/cVH616WyYhIA7LXL5A5iapozoy7b8T3OmXAOwGrH7nkVdWiNzFRCLg81ae5d1lvQE8OEwTTO/3sPzMjOPbNCcXOYspPvtmuNY38gmLuvhIXvuW9S7+vMdJ28/boLi/mdnGuOurq03H3vlOy5a0av9Z03OuX8GZ88w+jW7h8gT2tMbWJOHm9XljKfYfE7v1L3kv2Td4gA671jHRpeX4mYJX6wjAcs8fuo/BMe2MFrp+SRPvT4uCr0WfDB+o3eqSAv1QMAYpr8yBPjyqyRVkDtXRTn1dTb5aKaW5fl4ccn9bnnOXn5+U4ZuVmNFZCFZynjRq41NcWxduE59mIiQy0MMNm1d159/NgX1l+nTrTIh++bs4APu1d4w2D7duydl937FjR8zAYAox4vuX2xizoPAMiYRulPwrq8nGKYXD7Ml69dqperlxtkYoxx3qtLFdHT1QHAjLR3ZqSnb1l6e9PS05eWnjVp6e5Oq7glvE1NJOSn7v21GgD0vT21zxW3wKcZAKIC/o26IzIgrbIkaamXpAzLrPyz5WNyJ1IFHD/JEgLt7F7WWsCAQsKvPT3GHjrVLq1IgvT4aJ3aRIzdrpM7Cg7JA8lnxSKPWCEDmA8A8/dIPc6BDeSmLOhEwyDMBmihKsnVS02a01Ry5eoBAMPHRzhCHt/23fNZb0EmN604gnDEQ8EcxaYyWe6+i+TzGc1BROHqgGBh3mYEss/7k01KM5pzyL4QnmAb48OQFjbHwOCCsoEIRADWr7/ULfPz1ZlRA3apKkFJOu7JKy/0hPpLfN+MG78ANY8/NSq9uv/mgv3HfbvS//eeFSvdcdnP+0/GpXYD+JlTpS9WVx+eapVjb3bGg4rC3cUAQHwxH3uKfpNWxhzmLwtcSog5yl04uYmYMGO3RR7dm691WN+psEE6upbkwUenVIAGS3fszXY5dzrHuvsCQADUtp0Lcve9M8r4katMqPfMqZa8spiVAECEaHsPEHFYVEYSJS25fRg2A3j9wv/RJnqcB2P7+o0p2bLdQB+iGTbsyK4Q1r2ENVdxLp+/4jn/auMAIOMUTB4l4Nb0LattDPmNhQ4Z1P0dvZ2U8TtJGRtNyjivsaQsLyXkm39Us4FZ1QHm87azTzMAdPdqr/TIYKJFbmTm5LSM659XBLwivsyABEPYAyBcs5R9h0kMb+QXEppgVQ1TCEi0uo2hna4iAMy/2IwCV6pybNi8qAAN0MpAxOr+yiXLHcwzoq4QAOauNSFd3SnZuXdOtu8y4YhWHBlqlgtnWlT4UIqBKpdOgApxz75ZtXthsoPFO/kuBrGtZSbpaPBENQTYwB275lSlR4iZfMNyys6oWwPIPvrghKpDuZevvdQtN65V6kFoLcckdP/D4yq2QcH74g96ArHJygFgbv9j2f2/9GzvCs24SwOpH8ZYWSHeyTvFtrYluef+SdmybT64j10V1fXN21kJAAgw2rt/Vu65b0oN0QF+5KXGfbcUukGcdPTBKWXfYddee6lA6OHZIPQ79fS7e0bq6qmz3SzHXm8vCs/GAUCub/PWRTl8dEYXx4DIk++2yumTLSoc88DJeaAVN4jN2xfVFBrjZjYYuNPvRyh5fdccoTZpaqbcmgG+jVty9dzv3K6Ty0P1CvyoCpIdq6Luq2cbF97D8NeIbvSsWVaAB9Bb08/P6WyxAK4bdwvOa3QkKXduJ2UsAHxZcUnEudUA4A9jFPoMHbOjpyvzv/zBr+sEyQqVh3g5jWt6wv62lNCJPc37ckLzzkjm5XPUrSye5D+eHMD8WxBxzKh75Au8IubiUjmAhNwIyfJgUwmEl0sadqfAIKlM4Z06FXGg2iTsFM9sFV+Efy6mCKpDwODGzaiLFzXEyoYiDyCI1Qzii8IcHT8okvtUVjiyb1bWDgQVR6aTcvGc2clo2Cu0+VwD4g682PYdnNacx/m5pJw53SpnP2iNYODKnzHh0fsfmpDu3iWZn09qCPbs6bbI9i/XRajacN/D41ryD6D7zutdashc+UYe14yCU/rA8besusnqhWzd/if01Kh2Qlh4YVVVwr6zceWtU+4b3nNxaCco0PcfmlJQzIII4/M3Xukqzk2r5FQjLr+3b1Huf3hC1vQvae7wCz8ooUr3YgBNTEGuH0wVqR2vvBjheRnTIAA2wCNKYdhI8ppfe5Fwb6O3wTHNYjl+82oyTVg2lRIVdrx/IlRn3CP0qk2cSSvYw6x5684FrTzFvHLhbJPmDWrpTI9KG9G3K6PjMWAPm5a+geVsSs/wjToVjFwaapBpGEXPY1TKAOJ9C8Bb0we7Z0CvcE6AdcQqBpPqO7cgDRAiMo7ZWOZ7/TUAWMlD+9n/LLJXSjDMBZf6L0Tk/yt32WsGOjP/7qWvVdUyyPlTSzy8BgxTgMTFhA4OhCBRlKUW7WfUYPxu76x2cjWG+dnAkAf08AVn0RRg0XWuJlPogA1hUpRqGj7uXdKVH6xhuMQe4JqBbpTw8QjvFkKO84vzMWk2WJ5/ZZgoU6/YWc3AZOpAkxE9PiHJsr6DHuCZIyKcYKLdtnM+G46GDYUVHDrfHNjYRN7EyD4IIwiDB6tCojbthgH0qffalEGLutaoHTERbidJ/e4pPS8MxU+83aFWN179LtgpYVysZ6iLSn9GOHDmA0/hQMGJAUwfemxcrwsxDwKRmZkqhDwlnl4Ayb0PmFKUZ4y8QM61moVHVQNERV9aRUAZ7Apro7sOmuIc4Dd8o1HB/83r5kIfx3aVPf3Q6cLSHb4XJfqcPk8AI/zzSjHNcVfKed//8JQMrEtpaPWdN9q1fKN3Pw0OQJUb1L2MQ7CHJ95B3VtQcaPwIgtAHAzdrn0AvzlVMKu44/1mZfxYTOVtMWAUNo4qHZRnc+PPCFU6TluVjnK+o9nBquB8XWgXI+jN2xaV6XNRGRg1fPmuXianryGIxOR24AuyovqBA4UQAP0Dywo0+wJmr609d4dhgSfHAXhJDePC7PEOACx7P6PAdETH+da//ce1HMCKxpnP9ocBgD8hIsd9L7O1oyvzd//pb2qCKUwOoU6S/JHCh39GNau/N5iJM2EE3gE1VGWIevc9Bz7HxM7goi/AoXunpvB80moMU1d4wUrJUW8YoGlQxxdQfLRMYXmlcEbzCLNs4RpKBS2pOarbaANCxrdHGuTOrXq5PVKv4pM8MYQHECsJikKXD5AxMLgo6zcsaj4UG+wgimIAISxh1rrB47j5rWuAEzC4eduCsmZc35VLTXL+w1YFPPnXVb63AOAwfka16expLl+0MnPeXoJBfWTYN6qUcM2AU3LAhm+UKE1T4rTIuQQIotAmvE5YeHKi8oR8mE6YQNhOAOVbr3dpeT7vyT72IctoyJNjkMeIUOj4W5UJY2IPsSofiINFvgfJqLADOx/6NxvlFgF+t27m3+OVA0Dy4OblyANTKu5BeEXId2KsPIgvdaX0BUKrLHZ43D481aL1cVMeebXh1unsXJKjD07Lxi2LGr3ByJn8PEQZsVsAPEh7IB9v38E5ZSABLIg7AJDkHvrn9llNXnz7XG6fVulAyftBk6Wj+N76ECjCJ5XaxJu2pWTjZnxT7crIjSOsizff8M36XA3kmJzNbLuUORfmxL61y7JWAd+S9K9dVsFGePwmbKus3ogxe6N3LFfPbd59rgYAY7uqzXO1LdwCFQNAcgCf+vu/k9eKkXO9BwAIAw8mbMAiDyoPJwCgsdF+Z+LV33mn5nCTSCM1hvXnoNZwU6ZI9VR4qxncAIXkZbFS5n2W9xl+t5/x/eMzBjZ+mAAwdPahtmxpJVRAXgiAMCV9BaAQkHvnVoOMAAiH62VkpFHDoXGbPyjGRtB8BwkVEzImj5CN9qU0HaDt6pWm2JJrpR5GFyLGJoLkczbuC8nx5063yuxsXUVPMjYtWGts3mr1hpngAYIwPGV3FDpBRCcHDk+rfyALG64Rpe/0lC8DlxAqfhw+MqXCFdjwE8exEanON3Bww7yKTWBZMPN9/SVClNWEl6N7BveAsncYB5MKcOd2g1ZkQSBTUePHdbyq/98XBUQfgBAlIfp9B2eUdYd5uXyxWW1dSi0QvCfjiEMCsu5/ZFLLKjK+0HcIYfq0ZdSVsqC4/2FqXWNqXq91fEdvV7aggIkk1Ltnv4W6h87Sp9vV1sX3WrGG4fsH7s7V6gU8moFzGMhENEoItEAObNu1oMCP8Y2N3D7UwfjoVePb19iwrIBv6w48UlP63HLIWzfJ52vU/RJ69w7txoSAiRQMrF+SteuW9UVUxylx6V+IMUaG6/QF6AP8xdUz9r0PUeKeKIK1xgBWPeB8Jr8IAJwKruwNEfkV/DLLXelHBQDjEWX+WRV7/hmriBAAmp1VKLlgzVpj2H7P1hjm91ZjLKM2HtbC+sIUYOc1D0gMfs6u1DzBbiGe9PIKVJRcDohaaby+tUsKBtfwvjaXvMzXsaC5Ndwgt4cbsmKTQmuESgBgYZvBFBHipFYwLF5WSHILA9Qm9R2kZFzhZOezGmvvWNLcJsAgAyz35trlJjl/rkXBSGwIPHSyeAkeODSTDfHhUfj+iXa5fqXERBxxgm3tS3LPvVO6DxjK0+9T+qrdQ82c2xmKzwcfM99AgNUbL3dVZikSXBMTODmGqKxZwJCnhprXB1T4jmbNzcsKAlFJ87zcGm7U66Xt/W13fI9WyecqB4AsXPr6Se6fV4EO4wLpJuc/bNH7ODMdx8RVfkzu0V2HZpSJpv3OftAix97qCMKXfvsLf6q9fVnz/LZsX9D0GMq4YcKcMTG/1wb4pYoPVTcYIwGQb75C3e0cgIwDHjB+O7FzOTyrUQmM8U+80yrnzzTlWLTQ2ZRiALFfImS8a9+CLuZJ92EfAD/cAtiKzqVMs3FPYfi27MD2ykAfYwaVNy6dt3y+4gVxJN1X1Jbh86ANLW9vWdYOLsu6waU8do/5A6A5crNObt2sl5FbyfjKH5E5kX59xAcAcs5/+Yf/pBYC9npKPh8f2iwil0WEJ//3ROSgiHy14NJ/UUR46Vbf2Lzhy//j78fjNU9QFA084qGBVw1hBU/FN9KOacwhg1dra1pa2l2NYasprPWF29L6/6UuhbAzoQ5WzDBU09NJmQ3eZ6aSxaXkCs5ldQBgxPUlMmpJQygFpo53FMluY0BEVHJnpEEHf3L6xkcjfADjb0PRwZnwCBNTuxSbmSghyfVrTToB+u8+oawjpad2753Td+4JE+CVi1QcaVYDZl9A0tGxrCE/QCVgFcuIMx9QaL41H8iVOcG16xbk6AOTGqIHRPD9D062lamxW5xjeejuKRWtKPtyrkWOv90hsxXn9AU2JQ9PKEtO1Zd33ujS+7maGykABw6jLp3V8yW14vqVZrlyuVluXG2qsAbuapyZz8Ro3p3cK3wpyXEDZLAR2saTEq/G2Fyy4HTjQFH4qtSvcv+M7Nozp1EMFP6vv9wpt2+FvQN9rsH4KZh/FLkAN0DNpaEmefPVDpmDDVeUFL8vJ8w4cLdZsZC+ceyNNrlwpnjRUOpaua59B+YUtNHfWBS/906LqoTL5YqGz44xYuuOBc3vw1uPDf88TKAvnGksCj2XB4AZFdQh4CCETX4dGww7oO/i+Ua5PNSQtbWKbqU4AGjpODaeMq6aOjdMIGC3Mny9XhCOUP2DRXde5RaP+xMJ4jzj3YlEWsglpARqthRqe0b/1tZhcxuRtb+z7+s1ALgaw89ncB+DInJGRHCELbkZA/jbBf8fwVB5iiq8qoh47isaqHnCjBJAkUGThwdQ2BK82+/2wOl7W7qoUogbkwGIrI7xqdP3SVdr2BjFYnPoUoC1uh7ngDIJ1Ro2RnncvyR9fUtaK9ltsFkoj2EJAYUjtxr0fH3YpFLsIWHEtYOWMzi4cTGbyA0AJV8R5g21IsctH4rNvzlMQrBevLgmNljZi+eatWZq+fq+fNr2x3527ZvVSRrmgBA2+XSEAdUDMKbrAErJl2NCpSwYQPD0+636fV9/Q1hJLEAI6XH80yfblJUsqppSePsLzq2lZVkrVGCxw0a4HMFJdIm76vqSa7NtO+bU4Bt/QjYU/jdvNKlCHCAOc1PUr+PxScmT8gVe9Lee3pSmRqxdt6i5n+TauY2FzrWrTcpeGtsVNKL3ucV/0IQks1oNx1Wsef/dVhUPFbdJ/P4wOd5/94zs2TenedSUM4P1Iyc2byuTs0Y/3bnHyq0BDsip45w+fD/fgy9/f/k7JEx+1+E52bZjQcOaGNx/cKJFzp9t9GThzUh59108t4t6LaSroLKF8QOs6f2IbxJJSFoGBpdk8/aUCjkAPWwsSqjCgT8fIg5+L9o8cvvoR339FsZdO2gh3XDuNTnlGsq9aXl7CFPCvqlxfn7Zcyo4l/IiE0gJFjSAUQoQZIIXVasM6EXNfzybMzMJmZkicpWQX/6xX6kBwOqHv8/UN9sC5s+M8IzlQxDyeLmr/LwBwKK2KAEKYBYIUQKqeLdVWO4VHkDCoAuQZTWGk5qPMjlJzWFjD92E4c0URty4ckwpoAcARciY8DFhZFhRtzHQMVFSPeDWMExhQS5O8EHf8DEsBqwgDCEJ9zAIbADhq5ctAlOEiAAAIABJREFUd5CJrSisWyYE3omKeMe8ikdobzaEGoT1qEccDcQK2DjywbbPK2NDezCAY4h96mRbrmpJ2Uff6iEfPjKtTCsKWr4LGCwH5MLttm7Dghy5f1Lz0ebmkqo4BsSVZDVL9EMA0JEHJlXYACCljuwHJ6sr/RU32gGgqaTCC4bNGZ8jTmEBgXXI6J0GtfWZmSoQJ8XtPPT/hRMjgIa0A9TQ1KXtXZMK7JSWsufAPUQwQJ4noJRXUYkxdwwP0GEfLfXBjJZcvOvArPZtNvJMT73XqsIogE2pEGipZrDQ8azsPTAX5GAC/NpUcBW5Mok6QMKYNoQiWLGQe/j+iRjgl20T2yEg+tARrsvAPmbx5Phdv2IAOs7yBGsp6vES4nW5wsM3MIJvkosXGovDoiWamIX44Eby+Uy568pbMm4S1iWfj1BrRt0hytzYiP3jHADQW7feQrkodB27x2IVgYYL5wLApybD+eHFO6weABqpoJWmuonipKWrK63sY0dXRsWWhdv8nKX4cE7TvIg8TfFuL/4/3F++9W9rIeAKhp7P9Ee3i8if4DUb9JALIvILIkJeYMmtpaMr89d/9jd1kuThYIKC+udn9yIfJRp4RNJsRccqAhQ/RAYw4uQi2qZcjp59HEUYKzUmLcrHZd91NZdv8Mnnw7WGmUBR9xK25T2rtPXonv6hcguLc14AQULHvBPidBO7soS36zWf8NYNBlxW2YRy/e5r+HQZ0DkGgJDcQReixh4IhgYTakCYAjgv82nbH/mCgDnAJYwaIeJzH7ao4jI3EJai9mApUioMIKeRDQB88kSbnkscJQgwgfk5dM+0tiMT7nvqIdga7SFY0G5qPbNrTpk8vMFgRt96tcs82Aq3suxkRhlFAKWVuEvKu293yND51VQL558Qk2j/Wlg3MxQnzxGWx230HVhVFjtzM3Xab7i3Zu+U1Imb69dbnbBbDghikYJBN0CCnwnft3Xkh984BtdIPiWAEzEE982HhdXzqxIAYpXE4mPvgdmckGSoSUE35xHefAEg7UiIFRYRwRs+fO++1SYo2MvbgOQfbRPmy/dOK+tOG+O/h92M39iRkcH1i1r3d916E8jA1MEa8vznHalEaBMbq30H5mX7rgXtB6TLwPRRpcOpnuNsVegP2LVs3bkoW7YtZhenADLCurzwSi0JsEuINnChgEFk39TxJZfPjXFYwaAGHr5uuXu3h+PG28oBIAyjgjut1UtZ0bR099rvRTXnl0WBHaQAL8q5TY4nFPTxdxZ52oWjO1jRsFEDgB6TZu0jpVvA1wdQweCygUIGfwcS9WcMpNVIOmQgHf45MJPOGU2bkbQzlObdXoGnYPCOKIOwQj5rsrIQsN/EGw8AdT8lkgmN0bCVHmXluoJ6w0zesFrhknLshlWeA4RZ9nDC8hALGaPKAGDxfWewspCagUKMm8MsIRMUQBDlMZMuIFXPwbPZ3RFhclAVAwY5DtdM34ERdMwg1+p2XG73gG1Cs+T4IUphs5yvFrl0oTk22Z/Pcz7UHMZTkAmMsCaMDobOy0vlVdVmpkuh+2lNDyDH8MSxdj12OE+qFLMLCEBxzPFhIghrY8ycV5rOo32txN1stsQdkzfl8hCK+OZLVjsWcmyYua4e8k+XBBUsZcWwwSnsz77HYAyYnoYtr1emnPaYmqiTsbFcjpfvvuLRWdSemGWp0LCkinLaFnEZuagmJGnVSjSlvln094IKFOT3AfzYJ/0VH76L5z3FNhlT57OgOnhkRhdvjIX478H6+eQ58n2sUjBvJt+N8Rul8nvHWq20WsQWZgC1Sse2Rdm9b17VsGyAKAQdsH2FzH4UAExSR3w97bso23YuZsuvAfrI5+MF61e4lcvtYyHRr8pcWL4ltWVx6lwWaTev16nimBfKXH02qlwU5MCYiRA7A6AHAwvIw2ORMG7hMwCDRx7kxDhje0Lf8QME5BU/q5WDTtdeNQBY1QhR+5JrgY6ezswvfePrimUSSRzfRZIJe7ffrXPrq85+ZxJzv+vPgX+g+xlqO4rerrbVAYasjNRsOmswnTOVVqPphdyLXBEGcWc2zWoV8OnPbK0MAOZdZ8GutNZwpwFDV28YgQeMWWGbAainJy2kTDh5QkPL9QrKGOgqybMr3fYZPfbawZQaz8KYudAr36HNYWLIt8KfEFAIMK0EEcL2ICJhkiW05sIxAF/YQSqSDF8vThaPOmeqOjCx7iDPLwhvc04AuUvnm81SptSWEGluIel9VnbvndVkfvoJoWVEH3G5hmalMiP7D89kE+apJQsjCDsVF9rn3I8+OKlsHmAYNhP7GirDVAKwmQBR8u7Bwqbe2DIEEOfOtK56jmDJtgzmLMYDLHW4x2bpxHtaxxPwkMNEMIK0NblVc+r3mQzYKw/kW+nAETPZM14RUt+g4e6FrGE5/RHQB/iL88yLJmjSanNE/8T7kn7OvQH4nT/jD9JR5FJ1AyaSaALjAGrjE8e4v/EWUDCru/bOKXBjIcr3qfd78nhLSUDrmjiT4Rp4xua1RBtODHx/6JxV6WAcKLU5AEh+shNxbNgY8ugbTcqFc00K+syuJdjKVhAxEYQCvXX26lmTywNdXMSqql5zDm9chUEs5VHo14kSybSOz8rgweT1MFbD5i1LU0H1RzV5nrCSbVqfdxSwZy8IjThGNNQA5dYSof8r7nU1AOh3X2ufKtECTYhA/vvfyscs0UaAXm2Y+6r5+NVjMI2JNKAwAIt5RtOBsbQDjaw61T+wwd7NZDpkNI2XYIP5CDrzT58TA0Q6o2k1lZ5PygLvC2YqrX6Cc4Hh9KwZTufNyh5h6+iP+E1weawhjKG+0vreHhFSBtxqCDl4TY5RIJx8lmDF6xVmjW45FNNqQRP4EmJF4/L7+AZqQ/Uk1Lyw0rmEfLYQFDG5DaxPqYhk/cZFvT42BlOYR6qREJ4Ns4NRZwnw4PuEh1ELcn7MIzCMMGyE2Aon8fCdoFoL4T5qGRMWZ+P4ADqsbsopIAFgfG/P/lllBMmRO3u6RVXDWRVnmU5JWBUAB7vDhg0O9Y6LQsMxXQehCGAD5grxEm2IgTe5hqtq6+LNnvg8iXxm1XeYd+CovWM/RH9Zv3FBQZpTs9PPyFelz3H/q2FSyZ0EsO3cPafPKtvN6w1y5lSLXL7Y6F15xVjqOd0XwIsxCUuYD081W78qqzw1w2W+T3iVsRfweeZUs5w53ax2V+U2UhxQ8ZLf5xaAsH0whkPn4hlZ2mDztpRs2b6o4VjH+COuuHoR1r9BAVJ0eDd8xyycSu4ezCHvqF7dRh7crRv1ykSSx0eFDb97lt8rEknSY9LS05u2Sk2weWsYb4vTdxD+wd4B7DCanpxg7E0oc1lov5XfEX2Zvag7E9WLSZ9AQW5uF41NIn/8i79cE4H4Dju1zxW3wEcHAEPH8rCQqYadAzQxUGIinTWWbjQzaR4OZSScwTTvwQslXuFqrrBlWPU6c+msyfRMUpVXGE0zKMyQ+zSfA4orAYBRfdOFe7lOBmUNJ3cbOHSsYaEYhfNWtnC8TvON8OvjXQGVmmF7bEX3y+w3NJdwrdnQUFe3KJcQcUnwcgn6cfcVVgwwuGHjoprqupyZSibmZL0oqwagg9GBeQHwM6mfO9OSrToSffWExJdkz12zCib5Lh58ADom33KqW5cjSHI/Yg9jSlo0Z6yw/nFUqyPwQBFKeJsmJ6+RihUIDixxzuNeaSZCRkPtO3fPKshhX6ioKb93/mxLBebWJY636nht1XdYBAAB+APrTJxUuNCgcgvG5gCTuIVGqTsAi0he6Y5d89p/eRYQP8H0nf+wORvej1c8s5BJKXAjZYKN8pAfnGyVofMFvpgRAFANsLcvyL6D8/p8sl2/ykKmWa5cDFkpRXwXEERodvddC3oObGbQTrUetwgDd0bfLxYdiFII7Tq7Fp47BCWXhgDVDbrILtwK94YAiOMPbrQ8PlfKje/BrhHKxZIF0GfRh9wWJ1rhk1qvnVrta6wuL4APhi9s+8IlwuaNjxK6Zdw0sAfoY7FdfA0efdizmgekh1mV2Xubc6gA6PEz1mZt+N/mZx2x+/9md80Gxm+UrH0qsgU+zQDQXVA1djEMfgDFllYbIDCVVrNpftYVlr2rp2Br6aokDHgM/AxMeAbyrh6Cqt7CSzAu6bh0x/TJ94ONcmBQ33uWpbvbWMNwuzhgCCDE8gFFJWXnIsO5HoCdQQuGUPMIg3xC58mmA/donQKaWzcaVbmZF7oqAWxcaA5GLxyaw+YCMIdXGpVJiti50PnSHih4t+9EyZqb1ACCAKJSOV2cM6ErWBysZADcBuialdkrX97LcrUwCOaYDMyEpE8ea4sNK3NcmB++i2AEIEGY7b1j7QpSvFFg0I2MjYJFmpX2dmOjYGoJc3NOVdnIeMx1lQ2vq75DoYxa30BKQ7ssJHr7cgsU+jiM6LWrjdp/ssywj5dbAbSEGd++m7Jm8zp+mJF5o+aj8l7IRpUCgDw/CJwAfqSCaErApUb54L0WXURFK4Nz7UZfxbtv7/55ZX9J1QB8EqYdD2pkFyCl7K8ALkAfYV6ABbmBMJWUZkMVXHQNBbmN2L5s22VMn/l3ks6AP1+jXLvckC9MiWhjcnoRa2DwvGFTSkOsbgPwWTgXxXd9nh1LVB/LB4DG6q0JavIC+hCEhAEl+yAPb5QxkNDtHUK4LJYdmxfRNyP/5NGHMyh9zbfPefkB8tTLT1+4TFglrFIbIhYjIHgRfSFiFfw+l5Bv/JMaA1jZ2FP7dF4LfF4BYA48+tAsGWlqCVZprWk1lW5ttQdYDaZ5mNtgFaMHBVhCAOFUAAoJoRqLGADHmehQgg8ALNWdCbvDFuJnxwQDY4eCMJzfx3dZ3SogvFNvtjUT5BrWR3saln12Mnqc/nWWSwgQon3cBgtJeNZVL4lnXvCAWxLUj+QPujAteWRXLzWq5yBMmRakLwFYCfsRTtOqI21pBWZ8B1BHqLRUjVXHqO07OKsiGTbsOs7qJF8uPJyQvrWL6iMIgGUjFH3mlNU+jgNzgDeA4K49s5oyAUgnJ+3yUHNsTlrhreEaAELq8bdlQfMdARmAcfXNG0FhWx8rgNH9esx1lQ2rK9mhMfmAZvo2ohRYaYQcjpHmebt5o1HbnHfLN4t4zj0AIIsS+gBtCdPmUhYADYTah84DqgNWKhYoUEsWmyNMk+c1QkGqCfl5p9+Pz8+jPAg1aHfuXlDwCFsOuEWUQY1eJwyJat26ZFo2bF7UMC+2KzwypIsA+jB9Lpdb2NiEPZCFd3knvGwMe4OGiAF9JUOhGXLIrYYugHHdRtpyKcu+cQ7XrxrgA/iVa8twHwNE6rimYxugjwgFeXq5q2cBx30iTAyrSl1efneMnq/SNlp8HIA7WLtgDmBOAGwq2Ou0d1i7qA1Bj3r5TVvxASUQKEIQ/D47Y8AvrPKOYjv/6hu/WAsBVzb41D4dboHegc7M//nC13SQ59HJJm3rL7lEbn2sAqsY/TGT0HJFLtFbbWT4vNrH2P+5353FTJ69zHJgNYNaWBXG9rupiU0l7NTFqhYOVMWqFEYxnAqriJMRauHi+7wSQOXzXfIVs76BgXdgbvVnZtOlFJOwXEVMYgAQYRL5v5KDbKRrSzSwJQcP5RovQJW9L+tkFN5oZwWD2RxDE5/wKlmuLQ+IueRtmAIG/XxAyCCMQTUWNITk+Llc4j05SiTWb9m2kA11cb6wZYhIeLGfqHwgtZ/YuKiMB2CIe0B/gg2CVUSVXEpViaciQBABi1bMmE+oCfCFs816zvl5ork2RzF76J4ZBa9sLAC09vGZFq00U24jt49j7t5nnnHcC4AnwFXL5eV5o8WPZ4hXqPFMiJyqK2FPtIlxqxyj/n56f+s1BJ5X9SD+EJV9IgZ4cb94VlAYu5d5BC6raW44H5UDkyunVkY3ERM1KHD2yguLQErJOsow2gKGF+DP2d8wIcOkEiKNNTsPWoRrYT/0HxYzblHEogu2buhsc6SVS/jUALvYr2zfuaDOAmzUnj11okXVuPleeblbodV2NqZk284F2bSNPFkbrwFup9834FZqUcLiEREIYg5SPni0GZ8JL1PdA8uWpcCyxB3RnbMaxgcKXfL4+L4TuFl98Xo1eOb4qGOjziEHdswgGTaP0K29W65eeLgxsZrV5L19K6lef7B6pdrGFjalFyIA/3atuuG8YG08Yzx37F0p5o52AtiZj1++l5/+fQqBIicQjBexC4eghSM+91d/XAOAlQ0+tU/ntUDXms7Mb/8/v6p/y3p2BX3TPWCogTXTLfDzyr4H5Ivz+1LlsFMTh1TF/L8piO1VqmbvSm+Ns5FhdcXgBFtELUqS9PXnQEGsKmH34v9QJeJfNm9WNFEDkg8AjM7ZyoECws7KHAaVR5RJDKqR6N+CcnVhv7Vwm7h6xpSos9J0Vo3Ela3Lz0f0YTZzQzfnoWo3xCc9QZ4hoeSO/IGWwc1sayy3kDAyEy7gIZ0pp1C0AZTJlZw7WBuqmLhrZSxmX8PkEN5o0PDx3FwxUCKnEANqTegPDKjdqp97ChCE3UNMEgXqTKG4oGCS/DCXrG7MoIHBKLNnjglzs333XLYCCgCZsBtgUEFdBBNJjqOykLvm9F47FhI2kbB2nNiE/MBtoXA29xhGEOapZKiwzIPEAoDwqAl8rMpGmKnlqyYwqtdqN7oomalT4Q/XyPFhTnmW/IGoOQmYWph8XXwAYfJIr8i9Wlup0FB6oUQ/x77ErJLqZRzGWs+zMlV6tnkyIuQDEzpG/Y44h7Zx4xNjAW3MQuHGdfwI/YAlYT9XPpG8vly5uqRcutCkLxipcoxwU0tagRvAj7AzGwwRfRTWrfT3rabt9t3k5i1oagsb1S2GzpntSnYBkgcoMloHF9AH04f6VfvCouX0EZ4GsOUYutyXGd85JsbO5PEB/hzgYywmd48cvps3zIcvW3O9oJ+yHwQgVO3gPvQGtXnJ53ZbVnl7m3EnCN+OmqeeA/0+eYGAVF1cqJcrfpT4usLcsfAwJi9qA2gC4izVxxg8Y/FIAbIQLfcJ4LlShrHo+KFT4vxplz/9g1+qMYArBQ6f5+9rCPin8lXAXuXconFSCfBU3MLMlQ4URlnJ8DdVC6MiRhms78HPajMTqIQLVMOmHjaFsKqHG5lw/O8wzFBWLTyP87pZVvA3VQmTf4F6eC6pFH0YdMUBQHcW5cUiFuLS/JASr1JMooUVLO9Q3125uuDnWOuY7AnmzpC27+x0ljUWTibPkL857y2+5nIMAYOEk2FImDBLVmsQsxSChSRs3L+WiSOlIMltgEqAIJMv4TzavFBUwqTBZMGES9jVJcIzUZD7hqKXF21RuJEviHiC0B6AEpCSZdvON2tOVzHIMd84kv8BZuSNGjNieWCAz1IsJMdAtct5cixYX1hBBCd5noDBiYb7iZbL0wop8xoaN0AAoGhWQEFINy7EXOopgHHs6rX60nj8uRfXVm4ze6ak5pCxWTTAzlrtovS55b1klD5vYiecT2qELmx0kcMCh5/rtOSin+lx6TPmnEiFAPhaTe2UTv5uYxHoREz0O/qvL8iFoYRlBfDB+DkQCbtKfh19kAWT3qMSzBPgHKYOpm/dBvPOZOFKbh2gD+asFLNJXh/hXYAfBsRsCBhMxdskk1rLtmDL0JeXZfvORTVndm3BuMYxqchx81pETXGEFc1cL/V6U7J+Y67iEACJ3D2YQsQbkSrdIJwEkwZYpFIHzy0gElGf22DJYPU0fBu8EGeUVd5qP7R+S1TDRHNW+1d9WXnvtLSdqE0BXcDaOfaOd2PumAf4Vilfwfx9+gFAm58s/9y9LC8doSJWV6QfNTeTo+xEjbhjGCP7t/bURCBlB6naf5ZvgR8OAIyMWRadaJyvWvYLsaIFUwvzQAEIWZErMFTfsuA9+3DZQ5Z78MpPgjyEWbUwVjKa3xesCHU1WKd/Y2XowhErVQsbk2hl6bRMnQ5oLmRmP0f5MDI422RqIhXYFH6emsKEty4X0vGwkGEyJSRHCBlAVCrHkJUyYNB8BOvVYLo0KMyFjQGDTKThCZr8HZg6XohLsoAg1KD4/Gk1ks1Wr9jZfVBO7vJQk+bkwRoVbvjXwQoWsm0wbbB8VjEh/86pUe/mRa09DABlwuZenz/brKBueiraM41zRKQCGHQVU7ANwU+Q83OgoxSHS31a6iYDXAEebNxPmEEYTHwRvUKgMYMjLENLG0n0sHLL2udg8dSCSRdXFKQ3dg/Xs3AEgediSVM5zIOTd/UBpGKIY9wXWETZC3C/GufsLknZpG6YJGOcAX3003D0gXQGclLNzgibkjrvdEcWoJTLg/Wiv7n7yEKIMDQLAYQRsKdRwMv9jVAjfRW2jnfAMvuAwQa8ke+aBTwFiMIZNZPaAPPGxljkWELCoK7PhsUo9BmUuwBN8ufYeE4vnm/QCiFYO0WZFRN+RTUM6CPfjo1TIuwKS3jtar2M3CwEzTZ+MmbBMJqXn72HQRhM451b9UEI18K45AfGLWrUV1UrcCxbBAPfPrXQMjBVuLEIxqQZCxctuTbhqnCwcE5EprdU7ufHHJKzazExoVP0OpGhqXr5v7iIGM8SwNOICauRzM8A5F//O7VawDWMt4IWaO3syvzdX/71yD1kH5+wfUiQK2hfMJrb5Qfq+ERuoEuvCBvBhvMJ+YyWnAtYA3IA+U7we646hGcYMxYABmfr+blwYzCRABKbVS2c0WL0ulIjVNUaVg2bcriUATZtw+CsoYIZYw+VRYRh5H0+8CCcM7axosmwqJk4Twnyp1z9YlMGW05VsdeVTh4MjhPGumiIQ8MaFgKcm04qYxVnPg0ogNXjxYQLO8fgHM59ZOClDjF5UKZKLh3Ga2tbVjaEcC0vZ3vDJGmh4kadwAGXhaFbJge+A7CDdXOhYo4LIwOryMRfyPI4to3Qrat3Cjgg94+JOQoMEiKGgQHUOVAGK0iOIWAgWn1r+WGYUpMryETABMVx+A4gtzwDZewnYBDlsxP4wFTDXuIrCPAmnFtRfyoYDVYi2YgeWFZrj/Zs0qcpJ8e7stUIntbkwpCcA+1Kn9NFSGBoDrNfuEVN9mbDZDlosK8WLs6xfK72NW3O4qQ8U0lu2bJ6YZIXS6UOFqKMDwBHrF8uX2iU+YVoxo7na3BDSoUc5MMS6eBZAGye+7BJgVgUeEMsA2OHRyAAzD3vhIQJDeOtV/hsw0KpcEPPM5X1OGR8unalXnMJOZ4LC+fuqi3kYPSU4R/AaH4py+5xrShwCQ0DGPEKLMwFDIdxeY6VwdOSm7bgBeyZqC1YeIRuZNa3j+obWpMdoJdUFpR0oOzmIQJSkCukMBmgzLpFQBIoM8dcYH93Ni5xoI6FuJIGShiIRpXMh9beLcpEhMBAXzZfsJYDWPS8eiKEFSCkz/hXfUvBfZzNwIBmYhL3yglErCRdrvRc7mcTjsA0LKlgJF8sYmXnrLScVRUJftY8Qfs5CzyrAIqGh43Obwny+mBM1N/J5fm5nL8ytjJuVa0DgQs1h0LOLvTMuw4as0lZTsdXB8i/f4FarbCOcVDTuNBb0H3XSndZiE4BooaWLdQMqCNnLwpoMHgyEZi59JKGe2BMws1M+zuLGgAWLypk5Id7TPnnfAM11BaQbPQLgKSCwsCLMKxsNFUsSkbL/3NVRDTP60ZDVkhidi9uWDGPQGw/EFA4AMmEDxBEmIFtRhZ46tfsOAg4AHUO+CIYgZ0j7y8bCgzdFPLhUCvv2jufVZoyUQAorlEt5UpjTBUHA4MqNtgCsxPEZYM61JiEa1j+DvY/VnINoBjHsHwkz70n/qPfkBfI82PpEMvS2r6c/RmbGxjIwo3ngv4D66t1hEecf1zcdGGLOFOXmkAKMMnP4dCkhTldn2lQ37hog2PzaFR1/ACM9lKROh72DMYuLzcv74JQwy/LesKtmxdl7cBSNvWC7549TYi3ON+V8LsCxS0pBX5uccBzBsA8f7ZRblzJXxjA6q5dbyFdxCPhihs83wg/Ll1AbMP3cicJUOxfa2FcmEFeYfaNZwyQ5/z8Rm7WZWveur1YRMEYPMYGK6NpIduocC1zhDNmtuobJvoA7JH3Hb9lpEFtwHJWXw7g8TcH6tx7OA8xat8uEqRK3uA1N2M5gUSEdPGvBIDlp8duUR6CEV/69h/XcgBj27L2gdIt0N7dmflH/+rr2Q+4rpmHgQLxh2Kc7AdyU0c29ONEIgGWyolGcoXh84QkQdk5V3JO8wKzJehyohEmgqyApN5+1txAfQUVR0pXKPK+/YQhnGCERHj9WYvbuzJWjnq3d/5uOYJBQryvGhdW0a0gHasYrCTDLKOyja3GcpTbGPCsikkOFOZVNlGm0f4vL2cxh3nzdt9QLwFodZNuWoUr5luVVgYjqgoLgzLAUJP0qe1KCTv381ROkUczEb6ClWByc+Fj3sPg0xK+sXFwZegsv9CxYvQLhCRqTh2wMi7pnQsixMdETXjV5RBaH7bvUZaOSTLM5nD+gC4A142rjVrizX2HzxHyJdfLMYOqJr7eqKbC+PaFFb6ESzG4Js+QELFTrzqTa1jIYuWyAQaOQWjR1VHW6xmrU6CKnx3sYLlcKBhJ2kWT6WFj+5Y0hBveCMm6e6SsL0xvwFCr4GOhQiY69kmz/NwmTb8w2yREGIAu8+IM3ulrbfmWHuFdsxDhXN3iI/duuYJxTLUyep1mqm51ui33kXYvVMMzcdPnLLfVBE/chyhmlqeU63AiJ9Sv5LaGQSpMMmII2D4VOqniOn8jHcFCyyntN06QAHgjJ+/qZSrmNFhea2hoACjDKBKi5fsuGgEo0u9ctmchF1I2lg6AyAumzi1YADEsbrBmQcABk2YjPv0zHZSOXJK1g1axyG08D4SeAae8k8NH3p5rL8ZrchR57gGYgGxAH8xeoUPCwoKZ2rtwLdU3NGVl0gQi3PRGAAAgAElEQVQYpXJt6VNZY2W17cqZKZvIyH4vF3p1gM4W4RYdyWPqAtbOqkpZaNavxm++eAbCgOegkRy/oICBS0uy4gaWy8jnGviZ1IumoFJWvchPHqzlAMYOO7UPlG4BcgC/8FO/mfeBleSoRatl41c83mbOJUGWPdBONKKl50hC5x1hCO88RPzNvYfEIlZazj1oucoi4ZV/uX4EeNTSctlQrlH6hJkoNefofc13coAxvtX1E6yOFRiimHSAMRR+zhlZW3i6lNUM+2JgyzKLDGIk3gfnZ+/B+c5aKDqaIbK2MnPTIKwcsIf8Tgg0qq4xoFCtZMaCd8yoC2xluEYNIQNcglc4D9C8vYIydJSDGm4IgS7LS3T5g7yHv2uTb4MCOyZCZzvDpDSwnooRsB8oIHPl6QBohPZg+8LMHSFBLFUwrcYjLpz0D9OXl/Qf3EMYS8AgDJ1T3nIvLF+sSa5jcr2c38ERqgBUrYxZzkYEEMS1u5xI2iQuzEvuIW1rDIuBHu5VoQrYdUtIiOyCaNEqIsCiGzOfe3d9NOcAYB5pdTxfKtJyOYPx+U5mrB4A0UB57OyRHPMcB/Ds/O15sXyw0EuV7ctFkz/3AZZUmaRxM0kndK4scmSo0PZv1iQ5djvcljCFsI/0IfLquF8adi7Yn3oNrqMKhvU/cu3cM8x5APYItQIcCxlxLJwIB2Mxg3pWn3HyEG/Wa1iYMK15btoGy7d+k4WeAX1uwcUiEsBnnnwNyqY5wAdAW78hpebNvBx7zv4Al8M36/T6UPgCkh3Yg9U2xXla8/9Q9QIWw+MT5zoxEdTQ1bHBfgZwFo4/1CnWShma90wo3cCdscP2rqb9JQIiHItxGHCbM1cu+Jn0HB23ubpcJKBw7M+/hSZIzIaEWywH0IQcOQEH/w+Yc4IOwJ1vsIlnTgmKBRMGqbtFKiE//6VframAawCv+hbo7O3M/NI3fi1/B6FVZWi9UnSQwnEx73eX86ffCiTx4b9lcwJz/6e+gYGXoHkH2v+5Ccd5C/IgL7sJiHCxhoRzYeGsj6AuTEMTqufTFgaxJC8DDkuJRbJMnqq10pYT0mKAs9xmqmKX7+ES4QMRSRDazYZ4Q6AgHpy7nEWXr2ig0LGJ2RxGrXiSzgttFZ4v7aym1foKfAqxBFHT0lyOYHZSyravhb3Vt418HQUbrPSXFDDmTQABy+fsZCz8a8IZgRqmQkdTWtasxbbEJlqsZMIhJlg7JllCvzArYaBG2JCQLCBqXcicmj5FWFbZvquN+jMAin/kAMK+wcKRQ+jK08E0EcIF4BE2dhMd6k3C0oR8YQhzth91JjwZatJwZHhCAYgBBgnZAiLYGNBhHgGDV680RhhVGzsISOB42Ja4fkZ/Ih/SqVgJ9cYBQne/qaKhpuZt9AkDhMrKNSP4SGuozNiItKp6uS1x7Il5dZr1kvvZ2HQDkgAh3t0CxPJhk0F4rPSCMT9Hz/oZINa9nFcgvxcu3rjnzkaGhYjzPeS9nFodE2WtsANjTR5gkN8aZpvZN/1O2epbgbcifoQRno3JpNXatjxAyykM30cFYogqroQXN5aLxmKF/gzLp3l5Hca+cf8Be9Tc5buOueb/lBncuiibt/Ic5HIXycNTZvCShXV1vA1YTNjHDZsp05jSXGcFlmlT5cIIDt+o0++4NAtCzn19hLot5w/DavLzwht5fhxTK28EFi6Av3Ab0c9gZF2+n8v9A/DRL6P6HXOEC7taRSYXhg3MlQPAV+iCUErcAUOcp8oNRWfc+M64TxUpN/7Hjfe0g5IETshRIOiA7bTnwt7J+7OX/czCKBNhM1ELAVePfWrfFJFPYg7gat0YNZYOcgHdezgHkIdKcwYDU+msyXQwefF39Q4McgZdiBhWBCaqiB3Lzlu2IjS2Lr/EXLbUXCAkcf9f7po5btZ2BpFI2MNQV4M2mdrK0N7dz3E2FrAzdk4BuxiUvtNQSdajzdiOUitrwKETjjCJq+pZhS6on83ag3OmvWAzCbvphEp+FaGgXpiofL9B9nnntjMndsyhs5Ux7y4rQ2d2HgAjhz8ZZAFCmgMW2NFwPmwwX7AZACgmUheW5TvYzdxGOMH3EJUsJTX5G7WnKou3oLoN/NECz0FjdwKPOOBjYPwLGATcOVsbJiaYPvf5sHcdFUtsgl7Qa3GmuxomvGlCFc6psHIJ50aY1wlkwuXP6LO3h/FqrLdwPHYqqL6nyxh5V/TgWfI9E7LZvxhA8MopjMkBdMIrW1DBorj+mQsRw+J1wOQVLLQ4D6dw1/A2voFa4caERqVyVC1fd9k8OgMwTKoD/RQwWWg6nLM7osKEpSYUiz8svwxA4xZBpkjO+V+6HFQLt9KP8vNoYVK5rwAr+jqAzAFbWDLsWq5cdHl5NgAB2vvXkW9ouXxOsWvm5w1y+WKDgkVyeIEVsGd8nhw+AKn7PPvifMKl2QCWLAQ0hKthXECfvbvxQcHwKEIv8jDNlJn90CcBsOZYAHC3KALtzXNFaDgq/xi2SxW7QejXQv7kIAcVNEIOC9oApkbUNJVsODXr+BCEVLOLmoCVC9uwNMc/CIAyF/7V1BoVcZi1k/vdiTj09wXLXY/zKNT69uEIVYNZvsDcUt0pHNHi2fv9n/5ajQGMv121T5RqgZb2rsxXfyanAtYhpJQNSCKQ9GfH+dxKPWsaHYoaur8lgx/ycwVtAsmZSjN52u+AhLx8wMAzMGwoXReYSjMJmo9gKPwb/GxhqHAoOAgB80A1xoejyvUaBlMDW8EqDfDFCs7lDap6K8gfDGT7Lm8QcBaeiGAZW5pFJwtNOg7AmPs5zOCxAi0X4i08Z/VqCwFDZ4ZtwpcAMPIOgAx+d7mPCiQDYMn94NhW9siVwCMf0PIEdSAvYZ7KOamBauDxFq6XDChhYOc4ripJL2KRPmNbClf8DKawN+GaxhOjFuJaq9UbLNE+DIb4PycMcJY0TE4zMwkNm5FnBePB5Oz6LJOY2oSgMFZ7CguLMUlpGHfrouZ3uY12Rl3qQn0jN7G7oTTckqo1EZ6Ew9EA0luEBQPBigvhAsZRLGO3AbALAxw7n0DFOmKgIxwSrG8gGd+AAm0AU1rITKgaHZAeBuiBDYv2V73ndj/oH87CJXLBU/SA5OfqqienpmHkwsCEwFCyKqMYygWE5TWfMzOLLkfWcy5OeATIU4DrLI0mw/l5ptI0UVbwCkQl2b9p/mE0InU5qMZOm+m5Cmgmc0DSKkYQkgSQ2ruCmyDsXMhC8kypMTJ5gBgj3wpyWjM2TsEuEi5dEwgqYM7DwIr+BeAjvKvK2Yzo84jKlr7PO8AsuxhaMGYQAYeVbBPN+zM7FgOWYZEFAMZV6bh+xdA1n7eXefUVMnss1m4RBr5Zp30a8Mc+Dfjm/Pf4udQYAfNlqSEm5FD1LnZVEzbGuprtYXsu7psZiue/XM6c7zjpbFbMmaH4lVXnBvmAmsKT01hpGwFsudd67GzOnuvjNt+Qx2f93n4H6OnzEMxH/O7DJIYfu7+5q5YDWEN3K2gBKoH8xr+3SiCVb2VCNeExNfg5b5gN2clY6DgUJtZVXK40ndrDBDYx2MzklZjTkLHLRzIWQn+HkQiVmTNlcaAUDkrNUYIuOJRVOkkyWSX0gbS8JfcerMp4eF3eYOAjmJvI7DO+g475OVmeiwOGuZ/t7xYSCIFITcpnNegSg22wcZ6G2XNhcNGBJTzY2GBkfzPhjO/mcsHUfwpAqOdkrJ7LJ7REaJsYCSTRfqqwC02+DixGCkhQGE+ZgERDc8HEDkPb2JyWbg0hu1CyVZIIb4BKl6QPMCIcR+iut8/ykHjBNLpwLt+lbVUtGngUknsE6FYlI5Uy1jI55hLcYY8dyMN6BkDApOZMhfl8uEwZ5+AAnlNO6sSLCfG6VN5EDegeoTReAAgBnPRhgLA7F6p2hBPuHUh1qmlV+I7VW55ZIHYJh0iVNesMPP003BsdUivVL3iGjOXL2T2546ykwo+arwfPAuDTWBQTNWkOLekSAUhlkoZ9oQ8pQ03/Cphq19dcNZFy10dEQC2ZAraavMOs9VFgf0T/BmRkmcGsGtkWPS7nrLC9eF6cGMrAjDHY9GtlflG8KuOVK8lILh/hzjDwRfBwWwUV5qHJO+cNwHMMH2A/DMgQRwAssXXhHRDFIgdmj7JsqIjdM+CYOkAbdiywdYxv/fj0DdgxwoCN8ZRFkNXVhVW1hSztj58guYIw8YUAkfZR/73Aew9jZXUNmLU0HwZ3QJw5JtiYkVXitrIgiB+pYAmz46iOUYFfXhAtYbwNL9DpQ7By5NQxkhg4C4BaHoDL/5uBu0CckZ0DrEhBJRsL4lxESWSRKFSQ28dCXKNPQZ6fLeJtEZ2NVmnUSuT//d1/WmMAK2n42mfzW+CzHAKu9F6reW0QFs6GigOLGNiQrDIY1s+xaiGWT5Pkly3MyaDVyMo0bDSdt1o1psOtXn3FJpxXXrg3FPrNsnuOyQusbsjFcnlY+nMqI+mMhWMamgC8ATgMWBlbrbqVrOV+ud/1fINrKte+TOrhULCyf0HZOg0HA2QbLZTrhCOE2vD4KmT9+LzZPPAyhgFwwOTf02OhKBdODn/XWcu4kC6TFqCqt9exGeYXF257DT0HfnGAMMxhu7qshJ3ZXORCcFw/TAWgjTAtEykLCWVWUCUXVJoAFKD8dLmKHEs90gIFc5ixoy8C7BQQEma+Wa82O5oPqUxMTuEbZhY5J/ar7TRmJfqyDFlRCNTuJUDJMW96r4P7i4CD3C76iRNXJYkCwNTbms2wYIEoxJ4jywEMv4dTEwglAnq5t2aLETw3hHtV/R5KSXApCrB3AdgLA/lwP8z6bc6GhSTGeDqwhy0Hn2vJWjQZiMwtVsx6BvAXxURyfTlhSlCKEQYyMFfnPrN/A9/GBlotY2dxks9s81mAotn0WLiURQl9HEZY8141BOxUxbkrphyaA3u8a59aZ4APwQYMX7a0HWXZhk3Vi0hkcjyhjN7AoH0+LD5RW6U7OTUv50dfsAWV1Q/HpqUwNA6DZyUizWSZNAo+o23R5URjVlM3nENZeA8dE5cVa+iCwIAkQE/fFy3/mw3mLNtvQ+OXsmy68HUsXIh5C/7uu2jnOLQLYMyiI0EUKBBmZHP3gv/LRYfcmJ0DnLqIDxhAEyDmWEL3c5aA0KpWITFjvYWEWcT/vcM1BrDSeb72+VALNLd1ZZ7++wVG0KVCwHktx7opnwHka2HPaF1aBTOFmzDCE0f+32xQ1jBwMMNYbeGCUHFQYzgbIub/kwlJutJyQd1htZYhFKzvFprScnJBaTl7zy8tp8phx/zV5wYN/lZJOTlWysqOOXYvsApQViNbXi6kEp6zhtPKJAHA0gk5BLbc4BbOaXHKZV/wWNjxwzmS4WT9cO6j/j0IFzvgybWllqgOb/cbYYBTuzF5u/qutpIvrUzmOFqFRJkBZx1jQoCGJiZLCyORfA/7F1YfKtBBuRmy59BKDhnRzzJBOTWx8+/jO6oiHrUcPyZZJlsFhX2wfksaeoMpLKoYEYSBYeno14BBY/6Wsr597F/zDxGkBDYf3G8+MwDIGzTWz21Mbgg3zKYGW4+knrcCwkHLbwxfM6yJyyEkFMh1wMAA2mAKzbMu8LDrwaonnyXlflv43UQ27gUwUlFGOId0gZJbIZTnNWoaUAyHfC3UlVZmyfpwaOGjYd/AWB3BSYzdkRnnhs6bMHYY2ClLmAjYpJywpRDYlRM/OeGTM2zPmaGbKbr9PWEMZMBuhy2SHDMYJVig/a2ONkpjU8MDlggvL6dgGy23znllwkQ7kQfNz/NC/9M0g8BEmb/Rv1Shu56FR67vAkBgAcn74316MqG2LYP62XyfP9qNMC77vT1s3qKAQ/bNebjycgr4s4AVsArgM5uXpkaYQMrtlbZ2UfBMWbXpgjy+GZHUkimkGatdNSYnxsgL8wbjZKXjXphxswV92PbL8r1VeBGk8yiAC2rFOzC3vEwfTmiepfVnA5664HeL5qZw7qEDpu7//ZW/7pFzoNPVujcW0PrDz37x12oMoNfYVPtQZAt8khlAl1zu3t3gk/f3IPFcQ79BIrpTEuesKmzi1xBwEMZSxRsikZCxtFMXq6F0ECY2A2l74BSaOkCqSkhWYQkFQOpvFmL9NFcl9IpbZfIwuzAq74QrTICSM65WVaU++AGzErCVXFMOEBvItXB2OIztvKPsXHPJxOGayvnfiTtn16Fob1eeyMJ2lkcWFqsouFcQbmFoEvzb23H4X9YcqsKQNKvsiQnLt1L7jylygZIBu2qVAVSN2ZvP4GmYKphcXZ6YAsoG8heXLb+qP99v0FnLMBkTrkMokRSr9gIgg5kLh15dKNh9nmtm8O/oMpYGMObajgmECdtVPAFEcO06aQ+a5YfbXF4gZtSa54jBcBZsWm6fKzmmgGDJLHGwK7EkecKYFsoEXBJOMyW2vTRPDduXNltc+Gz6vPAsBM+J+w7PgW6BEMSxhD77DE9sqICz9knBz05IpOHeRav9yrNqE61NvNmcwSB3MCtaaistVqJf5od9DcwtLtSZefyypS8wqbvjWMjPgVaXR5jOSyUIXzOLJDNLDxY1weIG4Ec/NPXochC6zqmYAX5hAQTPC/cfPz3LQcXfMJkNHbPIMQFGDvDRL2EBEZPcGq7TNsNrT0Uka7GryeUGEirGmFn3OwegNX8/QrnsMwyuYPUAhTwbXJ+ym4Fwo3eNGTaHOQNn7TI5Zu3tWF7GXBX4BE4JruY5113OvoX2VRuUQCWbn4rigJyxzmktBJDRMoQZ+m7gJmHAMmH1qcM15pXlDsQV2Z9z46NjEB3QqyRHj2fHKXlV5avAMqTyDZhCQCXnrvPXMulLVhnG1NFOdW8Rm7D3LWPMv/gHtVJwlYw5tc8WtAA5gL/1H34l+9cwQ5cb7COazfpm+dqZ2TnGmEInAgnvDebOTSRZPjHqb4HXfiZhFYJ1AgqLSJyAJGAIw0ISNZFGKBJ6j6u/WE1HyTJnLkScFVUEg5PmJ1pDKGBLWIjNqbzMI8qKf1fCOJY6VwYRm8At18bAby5fsjB0lwXQoQoslp9ZvJlhd0YZVjeoWi6i5ez4gEcGcldHmXCgyy8DuFpOUOmi7UzmFnJDsABcM/YWBhLQE5WHRDswOWsVjFkG2oSCZI6DRQ3l8wo3PmfAylgOLF/s88U2IywUnPE114MPHkrSQjELbcp5W0UOO3fnf8gEnDeZBqyRsywBsLiyVD09lpQfBeZoS8eOuZw6Sg7yM+0F4OHZs3vnQrzYvNjfnEjKBFZ2n3lXlr+gxKNV4+GVsQlM+5olyrsJOLtoC/J53YLFagrnfAI1HSEAXbz7PKcuid/AhvUHTeVQ1aUFIVh86MIjxEKSogFwLyc4cf3BFjmW1uAsbABcgDq91iA3kvN1bL0pmO2ZLsduWqqChU3pnyz+6JuwiBZCtj5dyHixSMKOBQaRRQj9v6fXQrThBQvXQL4dQJL+w/Ui0oCpK6yywbmQC8tChfECER3iFkBe4b0wRjmhn4Uho40YZ2lj9hvrSaq+fMaaO1Ea941+ExbJ2bidv5h13pIOvPncw0rGdM6Bxbb57hlTqMxbtr41Y3rGrHNCJU2zc5kujILQrlPyulA0C3ANSVcu+ii8hpoIpJK7WvtsUQt8khnAj/J2hRlDZf4CH0H+7gCT/hyISrITGCflyI9A8ezAnAOYulILgB1AzmcSY7dK9Wvyb25ADAM4BWjmcGCDTuDMj2+hOngFuVlMdhpKV6V0sILUULmrtJLRyd/9XqS6Dj7ne95R98nCFs4Hzux2XJvrYiBgUN2EXyrRW42BtQ4xDArXb7liTNyEzJhoogZ/q7UZmBcHDCn3hUmJiTVKHetqNMO8MrDzeSZuypFRuL1wMy9HC51yP7jnAFCYt/A5AQwJdXNO9DP2aybF+WwVn4P5IyRL2J0NcERYERAQlRsJMAScAqZpYzZlo5utbVx1jWrupfX90KIh6HvZHMBgUefuZTXHCAMs118AWsZyGwgJAwJ1AggWHZZHlc7m2vosOlwoz6U8wBjBbtokHjgRsLBxQDgAwwZS/Uck7mU2BUTZfOu/js3UMaPOQCl9wXwYi1dbLmxPPh0gj9QL7rIasXdaDmw4H5LPI85g0cKzw3Xg41e4YOH/piadcMv2pwKMwPPPXakDefT1/7+9M4GVpKrC8M8MAsMmEcQNVFzANaARFaMgihqDENwQlUQM4m5M3BJFFHGJolHccMFdQ0SMuCUoioIbrmxGFNxFcEUWGQZGBsx/77nd1fW65/Xrd/tN1/TXk8mb6Vd169Z3blX9de4553p8+aXPHHJh+oX99T3KsXoW4RZQ5loEeJl5yNf8+Cy9Za66kH9mkdh/oS31YfM9ugiy8KJFgmFvwfoStpQcBo2s9fKi0/AGmqvvE+OMq42dTZnCTS8MadYmXsyb4rEkSjaeLSUkqnm9JYdJw/Hxgv2ZAl7aSGLrAQL2AB7/ub4HsB3gnR7W4e1bgC65A4oeWpjqm75JcYDhASwNhIev+ZBc7A2u74la2JkkdhrhiANxhs1jFYFULqLGA8w3thxHWLwdZVog36gn/bjfKUMtstFKHEfxxPXiHu0NjKXt/FbbW5Uk3hYX4zNp/xbbrycCkjexn0WdhXLDmxjjIHtni7f11uxRKkkmG3mAJg+L4yMj+7m3dJS9gVtnMTNMYBQPYhJAERBehNuaNQ7mX3iGZck6P1D9UPYne25ykPqwLOUk9m7IYs/n7oeCvYE5xnHwGCnW67qcqGJxUbyMbW9Lqmd23apUesV/HPe44w4bUoB881OEoYWep0RdS6yIzVGlNco5Fq9Yrl3Z91YUb3zvIWjDxTWQBF2UYvL61jkWN79MlLjf3vVYCrX3HrzFQ5gvvLJduUbzi0lZzrE/5rM4KN7AxUZl/n2qs7Yu18G0Z2aBUIx4RNu252l0BvwYS2enKcco8ZTEaGq//xLT8ywOxCSXklReAcVLd2XP5mLHs1fOmbEeX+nlI72wbJGEvL2HFnoel+17gNeWtdfQnt48zpS2s8e5KVbNyS8KnkJ1X3KR9sGwC4sTj8cyxWtb5Cz+hS9Ybs+rG3kfC67+9ZY9W8M+KdPbmbgxDnNITr/SQxGJPsfidfa9I42LEGLjjYqlb1VCfHLCkqdjG2EPnjFJHsl+f/PAbhynPfvUm6ot4y4nfCw1U3jYmaS47d6sDkkgg1kIS7f93O8xrx7AcQ3vi78UiC7ewewxaImfqKLfnBbPN7UQQVuWgqPjeQTzAygv+VPiEPvTuLFKSpl68MM3vf3mB3Su5++7Uv/mXUSZf1Om3XM84+D0fM+TuGB6ve9BzLEoOXbGD5rFHnBN1iWDrmSH5kSDiA/csqwNO0S0uUyMPYGxWkSebipZrMOFXhIJkThggZhqdzlpJaaY/bAcNq2VPIEhDv2As/Apnho/FNsPYo+PJM5u8jRxtm9eUWNQyJUCthYUfqlweZG2FzBNwV2TM1jNqBRFTrGSbWG4IT/YPe1sgWqR4u0tBCx+c6Zlnoas9QLh82u/cI17LbW3S+UtSskLT6XaG7fB5yHdcvOqXrmnMj485lIMqVfmSXFkG1/Jxvv1gvojbnbAE51eWiIcw14/C9B4+fJLx7AXgVHnmqcMS1H5RtxuxBCXaXJ78HseMd8T7OHdIXsAh8WXWYQ6TCCJs/V5fKUkCb8s7LTQi2zv6dVeSefG7Cm0gHN8YfNcblibxZ7Hl49pQdgeW3lMh4fQx4xEr+22y9f9wAuKp3IdS7k+yrr4hSoyVUvJlHHHSJ5W71dj6IUS+IWzhB6Uy2rIS39bEMQtsZe1XpwDWWgOxv/VEJo+Xg4FyueQ7t9pPPefF1lA+o3KTod8f0mzR7H4UVnffnCWpv/7ZsklpoDHHVlsN5TAdrfd8dYjjz22H9fjOntR2mHQtb5wd2ffFmFRPAkDb/ohIlI8x8DScDG12kjaUBFQzdzinueh4VUq05utbODSu4GYtUYtwZAZMTXa9GrkG0EKDG6uH1wyhEsV9hQ4XAKIy42jfwMZd3j5xuBFxa+4fEtddslWvZi/UtS0V9evV5IljutK8OWNuMK0xLj9HWc7P5TylF0Wq16KyoHopdBv+ukHdsrey1N2qUDviDp0bs8i7KJfrElircRA5di+hUH+trm9KGlVhD9vlYtTlzWKY23iYdNrKQv5utX62Xlr0qoEpVRHSZYYNuWXytusXaVLfrlNmo7uLXOX1pjt1wxM4mP9Frr0V1vrxnWr85qou+Rs5qYYcyzgeedun/qbk1pyFm97es0C74KfbZsyl1OWZcmO9nFbq6j42Nmjs1pnnrFT8hgUG5h/s0Bzydq1+MkPllxeIv2MEIISgzVM6Oe40b7t08o6ZRm4xoo0pUSR293vgOsHsu3t5Rn3JcJjo7+WdWOZwqgT6BcEr8/sQt2lzNI4Y7gwc3xfrscZP0s2f69OYV5l5957edWWvKJHCc5vzh4s5Zguj5RWtojMWBdHd/0+C7/9H7c21e5rT5mag8eOs9hT/UuXj7lqCx108A0pDrB8PA5SIolr/f1jlR78sJtSokfzfllq+3mZNrf7gH3WL5iOTl7tlMG8qlesefc9XHB8w9B4ZQtRh27019wta+xmfvs85KZeMlrz/jsut41t145R9bOn1I7t/SxjNlaBSl5AZwGX+nul/FeJ/SsltRoi3/c7P/cOePz/4tpplGpZotcyTW33snvz9VRCkHqzMK0Ybn//6kNYC7jGmJnnNpzf+vd5BjBD5769pOtnqD/z3BVsMVvWxx6zYw9sMTu2uKPDfmenOyvbE6aAl8/7r5J2W34ztFCBALaoALFSE9iiEshKzWCPSiArNIMtKkCs1MRc2wIBuPxRNNcDaPn4qraALariXFZj2GJZ+KrvjD2qI524QWwxMbrqO861LdHol9AAAAtoSURBVBCAyx9Pcz2Alo+vagvYoirOZTWGLZaFr/rO2KM60okbxBYTo6u+41zbAgG4/PH0CknvXn4ztFCBALaoALFSE9iiEshKzWCPSiArNIMtKkCs1MRc2wIBWGkU0QwEIAABCEAAAhDoCgEEYFcsRT8hAAEIQAACEIBAJQIIwEogaQYCEIAABCAAAQh0hQACcLSl3ifpUEl3k/QgSRfGpufEd9fG/z8t6T3x720lfVzSvl6aVtLrJH2xK4Nhxvs5yh4ew2+U9CxJN0n6t6QDscdUrTnKFj+RVFYpdW2t+0vaW9LFXlSBa2MqNhlli4dK8u9sj20kfVLSiVwXU7FBaXSULfw8OEmS6/95HQ7HnX0HW0zVFh7zn5d0P0nrJP1T0osk/U7SrpI+I+me8cx4saTvzaM9EICjx+D+kv4g6QeSDmsJQF/MXx6y6xsk3UPSUZL2kOQH4n0lXTXVoT4fjY+yx8slHSDpCC8eIcmFPUthbuwxnbExyhbNoz0thPkD40tssbK28AurmX9V0u0k/UbSoyVdEt9zn6pvj2HXhZ+xl8cz4duS9pTkn3uFMOG6qG8Ht2gB+BhJZ4bofqkk35N8DXxC0l8kHR/OmjPiee2VzefKHgjAxQffn5YgAH8l6WhJP45mvyDpLEkfW/wwbDEmgbY9nMbvC/2yIftjjzGhTrhZ2xbNZnzj/WZ4Pvw9tpgQ8pi7tW1xQcxM2NOxu6TzJD0kXo6wxZhQJ9ysaYtdJF3R8Iy7SXvELT6+xHUxIeGl7+ax79m4u8dqUfdqOAp+GrN1FuZzdW0gABcfSMME4J3Ddey36deGp9At/Tfe8P4WzXrK5cZ4q1j8SGwxDoGmPXYM76qn2v12549L8pwW/8Ye4xCdfJtRAtCC41JJd40pea6NyRmPu2fbFvtI+kosDX57SS+IaS9sMS7Rybdr28L/f40kOwQ8HexZJT83fK/iHjU556Xs+VlJ/5F0gqQrW4LcdvlGeAbnyh4IwMWHUPti9sPNLn2ze4kkxw84zoAb6+Isa2zRtIentjy97hhAX9h+u/uRpCdKuoibaw3cG21jlAA8TpKnfg9v7D1XN9apk194gLYtHP/k6d9TIyzlXElPiClgbDFdA7Vt4TjYd0i6Q3iY7hTi3DGD2GK6tnDrdhAcIumxktYgAPvAEYCLD76NTXN5b3v47hJCZK7cx4ujm8oWbXv4BuobrOM1/Tk9ph497Y49pmKCXqPDrg3fU34fAdeeAi4fbLFythg27ejrwuEop3BdTNcQkhZ7ZvxakmPSzsYWU7fFqyI+/CBJ18TR1kYCSIkVZwp46mbo7gGaF7MzG3eW9I84naeGG9+Zwv44rsNeqGYSiL2DzkzlU4dA++b60UjQOTmC3R379HRJvqixRx3mo1oZ9qDzW7YzTn0dOBO+fLDFytlitaR/RViEs00tCM+X9IyIBcQWK2cLH8kevxIWdExMx3sq2BnB2GJ6tnC29bMlWfxd3TjMp0KklyQQJ3T6fuUkkLmyBx7A0YPvI5IOjqxSTzMWT5OnUlxawQ83CzsPMk83+rNdxBE44HSDpNdH3Mf0hvj8tDzMHg7ktSC34HBWoz8Wgv6LPaY3NkbZwkf0lONvY1q+2QOujenYY5Qt/NDztKNfWm8TiWhlyUpssbK2cIiKhYift/b+OXTIYUTco6ZjB7e6WzD2zJCf3f64TNjDYireMYGu1OHKEfbGfnce7YEAnN4ApGUIQAACEIAABCAwkwQQgDNpFjoFAQhAAAIQgAAEpkcAATg9trQMAQhAAAIQgAAEZpIAAnAmzUKnIAABCEAAAhCAwPQIIACnx5aWIQABCEAAAhCAwEwSQADOpFnoFAQgAAEIQAACEJgeAQTg9NjSMgQgAAEIQAACEJhJAgjAmTQLnYIABCAAAQhAAALTI4AAnB5bWoYABLpDwAVifxiF31m5pzt2o6cQgMCEBBCAE4JjNwhAYLMi8FZJ+0t61GZ1VpwMBCAAgREEEIAMDQhAAALSxZK8PNQ7gQEBCEBgHgggAOfBypwjBOaPwDaxBugxkrz4e/kcJukMSbePtbz9vReC/6Ok+0r6TWz4cElvkuSfq+P7N0v6SrTn718o6T2S7qMsIJ8r6a+S3i/Jx7lG0tslfWj+8HPGEIDArBNAAM66hegfBCAwCYF9Jf1U0oMkXdhowKLu6Fgsvnz9Mkn+u2d88UhJZ0s6X9J7JV0V7awLcWdBeaikKyS9TZK/PykE559jv+9Lerak5wzpwyTnwz4QgAAEqhJAAFbFSWMQgMCMEHi+pA9I2l7S+kafvipplaQnNb77VnjwXhnfORnEHsL7S/rfkPOxAGwLu+dJOkXSByW9NPaxF/JfISJfPyNc6AYEIACBRAAByECAAAQ2RwInS3qEpH1aJ/eXiPU7Nr7fMaaCHyfpXEnbhifvDZKcGDLsYwH4REl3aPzSCSTe/8mSvtz4/pLwRB61OULmnCAAge4SQAB213b0HAIQGE3gPEmXhaeubLVziL3DJZ0eX/rfH5a0q6SbJd0l4vgcz9eMHWweyd87BtCxf+Xj//uYB0o6p/G9p58dV3gExoIABCAwSwQQgLNkDfoCAQjUIOAp3v9KOk7SuxsNOm7PSRx7hTj0r5z56/vgkbHduB5ABGANS9EGBCCwyQggADcZeg4MAQhMiYA9c7+W9HJJ72sc48yo8+dp31siu/efkl4s6bTGdk7gsEfQMYD2CrY/eACnZDiahQAEVo4AAnDlWHMkCEBgZQg8U9KpUdrljZJulPSsiNtbK8m/PysKP387Ej6ubXRtv5jG/XkISK8MsnckkzixBAG4MnbkKBCAwBQJIACnCJemIQCBTULgRElPjxp9x0u6NTJ0r4yyLS7Z4qzcd0WSyEFDeukp3rdErJ/3dxzfCZK+hgDcJDbloBCAQGUCCMDKQGkOAhDY5ATs3bte0lMW6cmlUbalOU28yTtPByAAAQisBAEE4EpQ5hgQgMBKEnDtPYs6r9zBBwIQgAAEhhBAADIsIACBzYnAbpIul3SIpK9vTifGuUAAAhCoSQABWJMmbUEAAhCAAAQgAIEOEEAAdsBIdBECEIAABCAAAQjUJIAArEmTtiAAAQhAAAIQgEAHCCAAO2AkuggBCEAAAhCAAARqEkAA1qRJWxCAAAQgAAEIQKADBBCAHTASXYQABCAAAQhAAAI1CSAAa9KkLQhAAAIQgAAEINABAgjADhiJLkIAAhCAAAQgAIGaBBCANWnSFgQgAAEIQAACEOgAAQRgB4xEFyEAAQhAAAIQgEBNAgjAmjRpCwIQgAAEIAABCHSAAAKwA0aiixCAAAQgAAEIQKAmAQRgTZq0BQEIQAACEIAABDpAAAHYASPRRQhAAAIQgAAEIFCTAAKwJk3aggAEIAABCEAAAh0ggADsgJHoIgQgAAEIQAACEKhJAAFYkyZtQQACEIAABCAAgQ4QQAB2wEh0EQIQgAAEIAABCNQkgACsSZO2IAABCEAAAhCAQAcIIAA7YCS6CAEIQAACEIAABGoSQADWpElbEIAABCAAAQhAoAMEEIAdMBJdhAAEIAABCEAAAjUJIABr0qQtCEAAAhCAAAQg0AECCMAOGIkuQgACEIAABCAAgZoEEIA1adIWBCAAAQhAAAIQ6AABBGAHjEQXIQABCEAAAhCAQE0CCMCaNGkLAhCAAAQgAAEIdIAAArADRqKLEIAABCAAAQhAoCYBBGBNmrQFAQhAAAIQgAAEOkAAAdgBI9FFCEAAAhCAAAQgUJMAArAmTdqCAAQgAAEIQAACHSCAAOyAkegiBCAAAQhAAAIQqEkAAViTJm1BAAIQgAAEIACBDhBAAHbASHQRAhCAAAQgAAEI1CSAAKxJk7YgAAEIQAACEIBABwj8HxbtJzBcncJFAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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ELwAkAfq2DuSBYDGJg0uVIDW3Pwxlr8NAaAAkEQ7rlhtAeCHLhqJNi2b4XfPzw1+b4Zdj0nHAF4yti+mnj0A33rkdRw8eiIQY1S/rrjjijH44RPvYNOuA8F3lgXw4jF9cMVZ/fEff3oThzLXjuzXFbdfNgo/+tt72Lw7fe2U0X1wxfi++M8/v11Rrm8XfPLSkfjxk3OweffBdLlRZ+LycX3w7cferVSuMz5xyQj89Kl5p8qVWwAd9N1/w1l46t01+PAFQyIAGB5Zdw9nD+qGmyYNxHcefy8AursuHwEHwQ8+u+BUcWc5/NhFQ/CHl5cF1jb3adW8CIePlWRVOWVkL1w25gx8+4m5p/pbrlPbFk1x7zWj8eyc9bh50oCcAPjLGUuxafehUwAY6bPh2nRQeN3ZffDDZxZh/+H0mHVs3QyfmzYMz8/fhDlrd6XHLHxtjl3Ad00ZhCaFBfjFSysjJHbV2F4Y2K2NCYCWe3Z83464emwv/GT6igD63Kdl0yY4XG5xzbTgAHDKsK740YsrcOhYuTU2+ix6zXfm0ZYF0CQl6iQQy51cZ5tAZAEMT3d+o0n0QeEBLax7fjhzrfH1Ww9x/jYEgAJAZvmny8QFwKvOHYJLxg3Asg078PCL8wO3pvtMGNoLH7t8LH7x1Gws35h2W14/eTh6dGyNXz07B6UZ31hNA+A9152N4ydK8ZsX3j+lRSpVgH+/fQpeXbgB0+etTcOEEU3wj9echeMlpfjtixXwlEql8I1PXIDXFm3EjPlpK9Bnrx4XuJN/N73CohiU+/j5eHXRB4G1z33uvnJsUN/vZ1RYDwtTBfjax87Da4s34aX3N2aB0semDAv0nD5/Pb5yyzkUAAZwN2Uovv/EXOw5eBRf++i5eHflNrwwL90H93EWsq/dOhFzVm/H397J3L8BT4N6tsftFw/Fz55fiK17D2fpdOvkQUHfZi78AF+6flyiADi8Vwd85Pz++PGzi7H30PGg3UtH9cTEQV3wnb8vRGnmxcwAYKfWzfD5qcMwc9EWvLUq4z6vNNbVBUDn7r3lnDPxsxkrsddZHTOqhB80B5W3nnsmfv3K2sBimKOYnVibTSHDPN0CQAGgCbJyAUceH8qVnR/OXL0CQGZx8i+jGEB/DYMa4gJgl3atMGFYb0w7ZzB+/ewcLFyzDZ3btcT/+egFeHvJRvz9jbRr85pJQ9CnWwf88pn3cCIDiQF4hcCj8n+nTv0td0xU5fg0y2LzjdunYO7KLXj6nVUVShUA/3TjROwqPoz/fWlRFthUlvPrn7gQc1ZtxTPvVrgiXf/uu+Fs7Np/BI+8nHazfu1jkzF39TY8O7vCVer68oXrzsKu4iN49JW0q/XfPnoe5q3ejmffS0NX+f1//tpx2F18JAC8clAY3KsDbrtoGH7wtzmB9eort0zMCYBOpsKCAnTv0Bo3nTcQ+w8dwx9mpXX/t1snBnF8M8rhEgjq+/pHz8WmXQfxixfT929pN3XsmThvaA98+/G5OFaStmI5UB7Yox0+MnkQfvz0gqCuqgDQWV3TFrISLN+8DzMWbsKRStay8vEuv4eu7Vrghgl9sf/wcTz6RoWed0wZFMThOevfhcO6w1kgnTv3pcVbsHpbcc57mDKsOy4Y1g0/fn5Z4Nou17dc/zQAtq3SAuhmn/vR4FzA147rHVj+/vxOBVBb2l0yvCvO6d8JP3xxRaVYUzK2z2dTSULrgauGdc/6xfYZHWZy1KU7GLmY3n1JxbuRVjcmxrBa/SXgzBcyGI199GXqr4YmNFDV+Mkq3Jyj+ysXsNeKJQD0kq/i4rgAWP5G/drtl2DOis14fvZKfPGW84MX5g//8kZg6evesTX++WNTsH3vQZzIgMSu/Yfxuxfm5QTACUN64bZLR+e9uz/NWoT3VmTirAwr1vf+4bIg9m/m/HUVdRUAd181PlgqfvncvFNgE27sO5++BNPnrcNLGUtfObB95sqxwbvnVxmr4n99akpgDZyVsfSVA9U/TBsTvER//WLaMvjtOy7EzPkbMGtBxtKXAeC7po4K6vvt9DSMNWlSgH+6/my8u2ILXl+yOYjzqwoA/+3Wc4N4QvdZuWUvHnll+alNJfdcNQZHT5Tgt5Xi/fp2bYPPTB2FncVH8KOn5pvw5EDMbfCYu2Ynnp1bEe9WlErh81ePxuxV2/HW8m1BDJ0FgC4ecUzfTli3ozgAoN4dW+GC4T2C+MeHZiyLWIC/esOYU/fggO7Pb67N+qHw+WnD0aZFUWBBnbFwCw4dO4FzBnbFwO5t8YuZy7HTWdmM8b936rAAJv/4egV0VzawMQD45auHo3kmrnDN9gP46+yNOFFaaeUOteviEO+6sD/e37gX0xdvqzStBIDhZ8zetMsBkACQTZcSE7IFgIoBzPsGrtsCAsCE9PcFwLuuOguFhSls3X0AF47ui+//+XXs2JeJ/SrvI3FSQ7lFyG2kcDtwywEzcpuZuvYUH8HhY+WWneh0OB0B0MUJjuzbGT9+cl6wAzcfADrYKmqSQo/2rTBl9BmBNfG3M5cE78ex/bviw5MH4fm56zObQJrhQ+cPRJd2LbH7wBH8+OmMa7zS2LjNLndfMTJw8f5i+pIsELt0VO9g9/HPnlsU9C0XAFqxbW438u1TBuOJd9fh/fW7M5ycHjO3g7aoMBVsArlweA/sOXAMf3ht1al3/L1XDg92UD/y+mqsylj8ClMpfOHK4Vi34wCenLMxAoBul++nLx6Mp+Z8gPc3VOxQri4AdmvXPOibswBeMLgr9hw6hkfeXF9ha6ikXYumhbjjgn4oKTuJh193EFv1NmD2bGX6ZJGE1oO0ccYyT5BWMfJaASAJcV5WRgFg9IcHqXvMo+BkAUxwIaqiKgFgQjrTAJjjuLFp5wzCpeMHoKhJIf7frIV4d9kH0Z4RAFj5RVfuArZekuXfnZ4u4GxXsUvz4qDt0VeXBTtiH7j5HPz5teVYvXVvoGH7Vs3xT9efhb++uRKLN+xKp2/JkQewd+fWcFa/R19ZHuzgdeWmjjsT5w/riSaFqcDy9u7KrejTpW2QZsWBYrnF0v2vc7PeddkItGrWBL+csaTCber60bIp7rt2LP7y1mqszUBYu1ZNce9Vo/G3d9diyQd7T6WWyZVX8Ks3jA3SxTw7L20FtR7gXp1a4TOXDcOf31qDpZvSm1T+4dKh6N2pFb71+PwArsr7fMvEvsEGkV++tCISx3nl2F4Y168TfvDMkqyUPzQAGr1zUPmpiwYEVsDlW8pdz+nuOO0+fl7fYLf4w6+vw8HQphrzbq2dweYzZj3o+Zc/vxBAEvZItxuf3iV6ryyM0i7g0Is98RQl1nCRFjW/eyVTjTAuWp/+mvWTIEq2ax9LSM5ZNi4yPE/oHzYsYJKahJ4xbQLJaRpKiIgaWTW+ADiqfzf8wzUTMG/lFvw+cO0aAlYDAM8ZmowL+HPXTcCxEyVZm0AKUsC3br84/yaQa89KbyDJ2gRSgG9+4sKsTSD/ePX4IEau8iaQglQBvvnxyVmbQD575dig3O9nZOLuHAClCvCNj50fbAJxm0X6d28XbBbJ9XHw9/VH38oJgA6av/nxSZg+fwNeW7z5VDkHJx1bNw/cocdLSvAvHzoHb6/YipkLMqBeUAC3IeX2i4ehe/uW+OX0xdh98FhWN/p1bYu7LhteZd++9de5GTYzc56AAUAXPvCvt4zHS4s2443l24P6bpjQB+P6dTYB0Fnm/mfG8iwAdFPtS9eMxPqdB/H4u5Xi9ULUWaUL2AAxp9E/XzcCLy/djrdWpXcju2Lu+4+e2wdd2jbHw2+sxd5DGat0llom7UX0ZM9CZtKgCgC5dCkCQOMUDRLEaGtX0lDMQKxr02QxFtCyy9UXOBcACgATRVRfAPyHa87GqP7d8eATb2Plpt3eAFjZBVzVKRX5XMCXjO0XpHL51qOvZ6VouXPqWPzwiXexaVfaimOmgRnbF5eP75edBqZvF9xx+Wj8+O/vnUoh49LFXDauL75dKQ3MiD5dcPtlI/GTJ+diU3m6mFFnBOX+67F3TvVleJ/OuP3SkfjJU3ODNDAuCXOvTm2yxrZ1i6bBhpCXFmzE6i17sX5HcU4AdAmY/2HqqGDDyKINaQtg+DNhUFdcO6E/fvT0/CDhc3D/qQLcdsEQODftb2YuCfLyhXV3cXDO3Vz507pFET5y/iC8vHgz1mzbjw070ylvrDFzm0c+eVHIBWzMYhejeOfFQ/DYW2uxZFPaCjqsV3vcev4APPrGaqzcmh4zF3Jw35XDsXb7Afx9zsasMRzUvS1um9wf/++tdafKn2qqkiTVBUCXZPoTk/vh8dkbgzx/6XsFbj7nTPTr0gr/++b6IDk1m97FNvZxoCgA5ALyGQAQAAoAmZhSAWCi2OFdWX4fiHcTjaMCHwC8cEw/3HjB8MC9+Mzby/HK++u8AbCy6lW5gLMNLNHp4HLgfflDk7Dv4FHMmLc2yInnEkFv3LEfv5tekd7l7EE98eGLhuEXz87D2q1pt2Nzl0T65onYd+goZs5bjxbNmuC6cwdhw45iPDyzworn6rz/pgnYd/AYXnp/fbCZ4dqJg7BhZ3EkYfT9N7pyR/HSgkwi6HMGYqMrVylhdPh+c8UA3nnZCKzZui9I6uxOxejVsQ0uGN4zcNv+z3MLgvHo3blNYFXcuudQsDFnQI92OG9IDzw3d12wO7j8c/3E/jhnUHfMWLARa7buz/y8Suu5c/+RU7uAw9DhYgAfMNLA3DJpAHYfOBokdHYbN3p3ao3JQ7sHaV1+ObNiE8gnLxyEtTsOBMmiS8vK0KN9S7gE02738C9nLj+1WcRZNj918eAgHnLmos3ByR8TB3ZB3y5t8MtZK4JNIJUh/qZz+mBAtzb472eXZJ/GkdlkM6hb2+DexvfrhO7tmuP5BemNRC7p8/7MbuHbzuuHdTsPYmfxsaBvLk7RnSDi+vabV9aeOiHlyjE9cVa/jnhl2fag/CkqBLDrwLEqdwELAD1cdnRcXHQND7/IBYACQAHg6cc6AsCExswEQCIfmTvj90sfuQAvzl6FIWd2wZ7iw3hk5gIeAMNtUG5i28KU61xVl5bGHQXXr0cHlJSWBse5Pf22Owqu4ii0CUN64tYpI/Dzp+diTSb2LjhZwqUlmTQE/bu3DzZDLFy3I0gLU/laBx6dgyPj3FFw6XKLXLnZa7LLufratggg0p3QEZRbnz4yLutYupAG5QD4qDsKbl06l52DRHe827AzOqFjm2bBd86a5078eGPpllOxeO74t+vO6Y9u7VsGALht72G8vnQzln5QaVMEgAduGI8OrZubs+k3M5YGu3krg015wVwA6DZyjO7TCe1aNUNRYQGKD5/Ask178fKSir65Oi4d1QtDerUPjmdzn32HjmHp5n14e8X24PSN8o+7X3dixxVjemFor/ZBPOOWPYcxY9FmbNpTnqMwXdpt2Hjg2pFYsGEPnnt/c+SeXJ/vm2a7sp+c8wEWbExbHS8e3g2De7QNYh/dx7nPl20txjurd2WN171XDDlVJtzYH99Yhw27M/0j07v4QWFCC4Krhkx6bJWz4/2MvtFuPDK2jYbCkGvPko10gTLgkJbTA3bZvpj3T+pe4/Fu5P3HHMNAYza2L+Z48/WzLuZ4Y/P4dz6Dw8V7Gj3/NHoBklru4wCg2/Dx5VsvwIEjx/DgE+8EVsBBZ3TGdx59rV4BYEQjEjJNoMyx+SLaRnRkqnJlVy7NuA99rKJmfCYB+xYAuu/Ynay5zltOanxsviJTr5j3bzxd9Phb7VpPK+fu5eMCk1oRBIAs2LHlBIACwPDTSe+CDxUUAKaVFAAmtN7HAcCPXDIaYwf2wHf+9Frg1nSnf3ziinF4+q1lmLdqC1x8XtaHeXmScEbDlPnOJaGA7Qu5a5Pus72DJiSlzz1wIOLVX3J3q18b2Y0IABNaDMqrkQUwIihtAaItm9Ex82nDy/IqC2De8abHxg48NeqXBdBn1RIA+qhX6drqAuCYgT1w19Vn40aAj9kAACAASURBVNfPvIeFa9M7NZsWFeLOaeMDK+Dz767ErHmV0p2kTUWGoSz0HQtdFiSZ9ZNWHLY+5h5y/DTxgp0QZMoCGJ1PAsCEFgMBYFoB1u1KlpMFUBZAWQCTXaMEgAnp6QDwpq/8ItvK5OUWJMEr0RjAaJu268zHekZAbB0BoJ2ikbxXr7H2cWNy/WNcoDRgJ22xJeuzkzlz1lg6LjCh9SDgHzJmjbY6kfX5bcgwLGqENYbOH+gTn8bePxvH5pGTjrnf5He81icAJPvCWEVpay8Zx0r8oJALOP2cCwATWvAFgBbEJAcnaQNo/DbCU52OuyMtqvRJE2x9pAs4yThLWl8S2JKuTwBIvnQJYEsb6JKrz6cuP7egAawCwIgotMasdjFhnO4HPYeNF7gAkKYaASAtVdUFBYDx4YyxTgkA7VyLAkBZACNuMfrlKQC07J1RN2O8fImyAEZ/ZAgAEwKOhKoRACYkpB8AGq5X1tpFuYBJdzIdn8dZ9pKEk+QBML4mrLWPtjLmOB4w3EPaomZvU47ccKQ+evzJ+Zr4zmAO9thd2gk9+tWshnRjsRYWGvasbsYDm8B6GG6XsLrkEoqGghq2TuW0isZ0W5se5ph1+Vpsa0Njpg161y49r8kfMdoFbD5+AsBqLt+5igsATzcLoABQAJjQw1+tagSAjIXNawMJC880tLKgHD72zAe62TYtGyZ7rUe5mCArAKzWYlHjhQWACUksABQAchY7w3omC2DUOknGGXrFBSb07FevGgGgADBbAcZyJgtgdXaVG1AsC6AsgNVbqKtXWgAoABQARhSIgp31k9PD9SwA9DgxgbbiEFYm2pqW/+UclGDro3eQcu0mGbcnF3B0HGUBrB5X1HRpWQATUtgGwPhuRjreq4ZjAP3i3ayULwlrEjP9ip0rmk1RY8VAxr8vL43NZuPDOAexrE6GtZNI0h1cRe+Cth5gcnwSevarUw0LBckfI0fGSvnEXoWE8LJsGaJa9SUJbDm404ZRQicadhJPR2NYma1JSkJ2khrTmhD65rKKMvPu8e/craPglAamOkt31WUFgCR0mO9rblMJc8RbwA7EBhoBYA6dQuPDaJnmNTKXoQDQQhvLxBb5zi+voAAwKijpjqetjEQMIAlddm5In5g9k6gNScg2aOtxTE0EgMnBSRU1yQKYkMwCQAFgZCqxOf9IK6YNwKSVje5Ldn0CwIQWiEw1sgCygGEwccLwZLuZSVAiAIW2dskCSP7Y4eaOLID8miUA5LWqsqQAUAAoAAybD0k4Za2HZDk+LjChh78a1QgAuZe4JalcwKR2psWSBNsahmwaignAdndEz4nIJhC5gNOeG30SUSAAwP/zUFZdtPWEdItR59ealh7rFjm3K5vLj43Z8tKE3CzA5N+j+0Hv0K0/GrNjFnHbmgxv7towyI6FPbYc6VL2gMJEHvxqV+LjijWxKGo9sSmTK2d0j3JHmrflAyykTmxuQNrKRoISASj06SgxXcy5AIjdQMOGFDAWtZx9CelEA2ANg6hiANPzXABY7QXcvkAAaDFB0pDJbT4QAHK6CwATevirVQ0JNmQuOwrOcvSPBRSqDQFgZLMIq69pxSIAUwAYKED+sMkuJwBsmAA4CMDDADoD2A/gDgBLjPXvGgDfB1AIYFGmXDGAUQD+WKl8ewBtAXTMt8YLAAWAjFmMtjyaG1k4jWUB5Kyx+Z7pmvm7ANB4Y0e/IgE4SetUGqhkAQwrkKTGtL6yANbM8hOqtaFZAGcB+AOA3wO4BcBXAEwI3XNrAGsAXARgOYAHARwB8GVDcfc3tyTcm2806g8AGpDg4WJmYYJ1AbP10aBkvusZCxhTJteO4lrQOPZ9BdugI1ebD3qoXOKbTDzcs/Rxbmy6mHwPcPnf466IpuuUa5R1xdnWDqsNH8gkLSqhZmlIMLtLtplwbBtvPYp2mos9q5v74seCnCcJutm9rKK0Gz9/bkxZABueBbArgNUZa11Jxr29FcDkzPflT/GHANwFYFrmi+EApgPoHXrMmwNw118M4P18S7kAMGHrFJHKxbXIgE1QLlKfADAMigJAj6AYAaBFSYZlj7SwsdDhA5S0+1AAGB1IEm4jMYDxoTPJfIQCwIYHgGcBeBTAkEqTdTaArwJwlsHyz5cADAZwd+aLlgAOAGgGwIFj+ec2AK6sqzfvRwAoALQUCH9X85ZNWQDNnIR5n+BMAVkAjXd9frrlrU4CQAqmPMCWH4v4MMZuNAlbWWUBZBei2ikXd7mrnd5Vr5WkAfAlAI8D+J8c3bgfgPsXfIqatez1kX91nueKD/2y93DRRtrw2Mnp1V/WFUfmo6P7Yg0O1YYsgLIAGpMn7oqYn5FyrmZyAZPWJLmAKTgXAMoFzKJT3OWOrb82yyXpAu4HYDGAXgD2MTdROxZA64WVPYRUqpigGg6A2Jg9m8PI3IBkehc7I0vcNqz7z69voJwHsNP3QI9PtM/2qRz5x5s9zSNujGF61nHpXbxy+dkBhMxjbPePuNKEOOK6oAidtsWqkLTisLtKzSbyt2Hdf62ASMJuXD4u0ILWsHgeYGu6wKOD46U7Pe/yA1V6Gps7aLI6zcVO5joLmpv/zLyTCzitZUMCQHc/r2Q2gJRvAnHu37ND06ZNZhPIhZU2gRwF8EClcv8OwEHgx9k1XABogAgbxycAtMgz8h2T3iY3ZAkAmWc5rvtYAOgBOz47fgWAkWnNAFBuYDMgk43HFAAyS0y9KtPQANDF/zn46wTApXW5M5Pm5ZsAtgAoz9R8HYDvAmiSsfTdnkkb4wYnBWADgE8CeJkdLQGgADCsAA1sSVsU6eTVIesxa52Lucs4N5xaTxlpoTUvjb+sCQANQQlrlJclSgBIQpwsgJYC4e8YAJYFsGFaAFleS7ycAFAAKAAMKeBh2ZUL2LLEWMtWfvdsYO2RC5iDLNqiKBcwBV7ELmAG2NIWS27+M/UJAAWAiUKgFwDSFhujy+FcbnRd+V2CQWsJb+5IOqaQ3ywSuhH2yDwaYliLFas7Wc6cEmRcZJRYI7V5pYYhLYp8XCD5I4N+sglLoVWE3vBBFyThxLLOcVYhi//oeDfTKBi6t8Q3aFgAnFwsWk6g8DqWLdRnr7pIlzozNjlulgGl3D8euPGJtOGliXmz0WeH+LEjABQA0q8JpqAAkAQWaoeurTi9wYWBNgFgFM8SHpscvx6ikEmCojUrWEDNMaPyP9oCQFMj7sVOvrDrYDOCADDHpg0a0ASA+ReP+l+C+Alc/2+iPvRQACgADM9D9jQL2opJ7m6l6yM6zAIWuzOatyhzTzXbPwGgpUCCViZZAKMuShqmuHGwd9lyIEbn7aP7zLXL/VBgLbvkDwpZALnFswHuAqZvPOmCAkABIMFT9Sv9DtFhFrAEgBxgsesO+7K3909wcYFyAScHFKZFkYYpAWBkJMyzgJMbL7mA01rKAsiuyHnKWQBo50vzASWjE7FjAPPXFUwQjx2qXvDAuiMZd68x02l3sk8+Pg/teEsZl1ePyQ3oNV7mdLKWF5/+sg8rt6yRBlW2UeYdlqMuMlbQ5Lo6gD3zPUxaccgdv6bFiryWyUeXBjZOu7j10fUTFqvc/eXg0fx5YkJW/lx+1etLqGUvKCYBkGjjie/cjcPFe7iFIvYKUP8vbPQCJDVEAkASbFlQEABGlGIgLtfPOuZaAWBSq0G6HjK0LdijS30EgFGZTO70gRijCSK/nQVFAkDjGSDgLNfDYw8DB8DhXfACwPQ8FwBSK2/+QgJAAWB4lvhYT2UB5CyF9pPJLWuyAHLgybijk95RKgsgBzZ0bB9ptY1r7aShTQCYHyZqsQS3UtZih07XpngANE1gUWsPawELkQK9AcAceRLi2L4lnELGy0IVdpXT7llyvOj0O0nXxz3CzLywp4QxJxLftRsf9tg5cbqtKwx0pV+61p2R8MBdSuUQtLsRvx9+QMnk6Mtx3Bjtjs0vHn0PpKnY6xg1H/e5l6s4pJNXXeR8IjYkyQIoC2Ci7wQBIPcSZ1yRgWmahUyTp/LnweOtc0kDW9L1CQATfZDrSWUCQJ+YQgFgeBrbicCjk90PWgndBYD1ZIURACY6EAJAAaBhxmW+crQbLUdbFAWAiT7I9aQyAaAAMAJxLDzRblYBYD153OusG9zbo866d/o0LAAUADK0Z3ueBYAGAVMPv1zA+V2RroQPUDLHyMkFHKicNRh+1jQOzug25ALOElQuYFkAqRcMWygAwC8/lF3c9ETmd0+6SngXZXZ9dqxX9C7i1h/UVMPu2Vz3zx4ZxsW7seNgzAAvi501o9jYS2McSUshtanEvC+f++eeHhriyF0b5jzhZOc6zJbi9ljYMXYm13EV1jTsRVGnOvF0xo0lbbEyz/P1aZdwbaYpOxsA6XhCMh2N1znFHnOHtTwy/SN3bSe/GSW74Se++1mlgdEuYHYlz19OAMgZkxk4EwDm+AHgsalGAGiBbP7n2qsE984VAAoADXOf9ZXHJgiPjSb8TmOifwJAryUl6Yu5t3bSrTbA+gSA3FQSAHKmKNqSKwtgRFBZAGnyjGjHuHtlAcyR41EWwOh8CoOnALBe0Q/31q5XXa6fnREAclNJACgADCsgFzALbFw5uYDjuWzTYEtuPrGGQgAoAKyfeJKzV9xb+zS7qbrobt0BYOhu6fg8Lu4saUsUDYAmJ3F9pnbVsvGZtXIUnOWerKONIVE6i1rYfGLx2BWHjUdkc9mz7db04sExnJngj91oYd6CGWbGdYbdaBBulwVRtn4vOGPi00zTZq4NNDHdnTRgkiBqDTYbs5ew652J26PH2p7s+QEzGMP8Y6MYwLSU9WVZrOllt8brFwCymyrIcgLAKHiR7l7WokaVo39QRAeM3bRjPpwCwOjLjnzZCwBNoUh4iF7LgE2aO0LgwUI3ASxBr4gExznLmeceG6DksVuY0UkAWOMoUq0GBIDVkit3YQEgCXaW9Yh92bMwwuzSlQUwx07z0BxnNTceDQGgIQpndJMFkLZOke5eWQAtsjV+ZJA7kllojZ0axwfiZQFksUYAyCqVp1yLIA3Mz7NK8adZeLg2w5cy8BPYfq02rbd4wq5Icicr7Spm3ZHhcjTY1IZOprkzagE04dnj2gjrkcsBrV1dWQXZh5q8X7Y643Ua99JG5e71sDpZZ+GZG17rAihpSCKtjmR9iZ/6QbutrR88cVPj5K/LtLqmTaDRJzGknVzAaYlqegWMu/6ddtcJAFmI5aBAABhfT+uxZty9TJn0qkH2zfo94XGOsB3b6bNU1PTyR5v7OHQkU3nYPMX1hXXRhTvsFe8nAMwLLGmuyQ82afyJb8Wz3cxkPGKiG2MEgD4rG3ttTa+AbD9O+3ICQBIKZAGMzHXbiBlfTwEgu5zU9PLHQZfVW1kASatYXSV9JqxMLLCZ48/G7NGWTVJPuj7S9R57Z7QAkF3FfMrV9Aro07fT6loBYHxgsWLFZAGMr6cAkF06anr5EwBylkIPi5UA0LAee+gpAGQXjwZRrqZXwAYhEnMTLABSKUoCN1u0VS6mkAUHMraNToPCtmvcl8fuVnajQVQ7j/7aB/paN2ZY+6xHrhbGwprEkbhIcmyYunIeZ8g8TbmOQuSuNUuxsaIxm6BRj3Xjkv1gXa8+VibbQpl/x2viu1ZZ2GOsc+6mvFKNMBY1zmXLuuxZ93ziLmA7qDIKnowLmK4rWe3Cc1ExgOnhEwCSC22+YgJAD6ASABqgaFIWB5Rxd1WT7nkWsOiYQqNCn2vZ/nEK53vy038XABo6JZ22RABoUWcUxJKOAaShLf8cYFLFBM8TGe/IwrMA0F7HBIDc+p63lABQABils+i0scFGFsCwUgLAvEtOGjw9LIqsRcnqScTKRFh/coIy+7IXAAoAwwrEzLUoC2BaSAEgt87mLSUAFAAKALMV8IE4n2tlAcy7XOWGRxIoBYAWi4VpJFk3JgvscgHn37UsABQAcqskWYoGQKM+vw0P2eBFH91Gp/KoG7CjU36w9xEqZ/7yYesy4yLNgTWY0AzujJazO2iYFK2vyDaiZrf49VvPSVxXdI5njo33JB/Z+l2MtWyY5jkDPMhylLXPMuX5uHtJl2W9zvkXaBLOeWeoyVo7ffRkdxCTuifqtjXZzDQfR8SjAZj4ESMAFAAm+gIQAHqASB2cDiIANMz/ZKJpE8QEgImuJ3RsEwl2PmllKIuSD7CQICIATBooPXYLkxttqOPx6BjD/Ja9NIfnj8gVAAoAE12wBYACQMaMZ1ux4scA2nmVZQFM9OGui8pkAbRox7AKkVDkc5oFCTuyABIub1kA62I1ydmmYgATGg4TAMlTD5J1ARs3VBvHw5GpUWgXdQ3vDKY19xlD9lr6Xk0zm8Gd5nZea2JkfcdaRWnoJK2CdrFklybaahnujNWN/AaGnKuKaU3zWIMYa0dQPWEVCYqx1jjG3UnWxbsYfWDPNJUaQElaxQigtF2W0X5YmtPuzsQ1Zq1sMcfCdIH7jA0BnemJnfV54nufxeHiPckuMh7PcV1d2ugFSEp4ASCb346DE95SZljPCPASALqZH4ofZYEt4XQxAsD4q5AA0Ip35CCOOTM2Dc8ctEUsgGYsHleXAJAFO7acANBcZ+MvPbqysgICQAFg9IlIGna5R5i1sgoAiTVMFkA7yaEsgAbJhTaBCACjFmVZAIlFp/aKyAKYkNYCQAGgAJB4mNgTOchyRItBEbmAOb+1XMCc9dDWSQAYfh6j6YIsi531FLOWPbacLICc+YBdUVUuSwELAFnXFp8cOH9wvx2Kx7pJ429GoF2q5Iu9xuvzSFHCj5cxA+h4TO5xteWMm7rHmifcPdRKXCC75pBzjK2uxsvR8XlkT+j6ONjhjnTj6vKK92Pj3Yj4PKekLRMLFESqHTblizGstAuYHWs2NQy9I9fsdOTL2ABIa8eNV1jPJ773jziiGEAlgiaX1LzFBID54TSwxJAvZwGgADCsAO2uIOdY3oe6tgqwL3G2P3R9HLQJAMmNERHzFwcnpv3LC9iiNfoBJWm1M1MBha5lXcACQPZp9ypHr6lerTSCiwWAAsAIsJhecdYaKwAUAGYrwDlxa37Hb2A9M2w91Fc+FiZZAKMSs7DvBZQCwIaKMALAhEZWACgAFABmK0DH3ZEWO3qxIutL6NH3r4Z9ibMt0fXJAmjYyjjIYhJf01aspC12SdcnAGQfvdOtHL2mniY3NgjAwwA6A9gP4A4AS4y+XwPg+wAKASzKlCvOlOsA4EEAEwCcAPA0gK/mu/8AAB/4n9AbkI3Fih97FXWVsm1G78hyu/LxbknveOWmJu0qDkc7mLya7EYW66jtuorRNO2J4c6Yksefm+YzUwspZDjbab4numb+TlvxrOaTBjuyDbvPYdceCR2mrAkCRmCeJOtjLYq01ZLQhI5P5GYK7dqt6XvNdQJHxANs3RfpKmegO+f4Z7ehGMD0g8i9ZWtmLayJWmcB+AOA3wO4BcBXMiBXua3WANYAuAjA8gzsHQHw5UyhvwF4MwOI7qvuALbl66wAUABoIHXkKwGgpRK5DHlY9sgW8j3m3n/nXus5mhEARoRhduPmYIJcCf6ibQgAKU2YxNf8JqCYcZcCwGqtUfVlXaxWp3MU7gpgNYCOAEoycLsVwOTM9+WXfQjAXQCmZb4YDmA6gN4ABgJ4GUAfAGXV6ZQAUAAoACSeGFkACZEEgDZzWZGHJCiY5M25wGNDi1k921/up4IsgMazQrjeZQFseBbAswA8CmBIpSkxO+O+dZbB8s+XAAwGcHfmi5YADgBoBuAqAP8MYCGAswHszlgR5+dbtQWAAkABYL6nxPY5JB0raPWivvzS5V7rAkABIDdTBIACQGLVzVmkvqyLPvdQfm0SAHgdgL8AuCxjCbwSwK8B9M3EA1bu5/0A3L/gU9SsZa8P/8tvs+/DI+cbHdsWacOKATTkpftWG/XVPjzS+po0QcZZGhEWbN4+Oq+eNY5kLF80LJIbBzO2kdTJfNB9rII+K4eHS5lqlnTZUnXlYkIytsu8nI2pItqgE0hb+4fNsDDW2mfdWfwYQB6o8oMHe0wf36aHxZJJ0eJuiY2fjFmf/Uh4xACau5ujYxOen7IApjVqSACYhAvYWf2eAHBmpSm0E8CkkBs5MsNoCyBxTm0wMNbLyXzZh4ewNoAtaaDkwMPnfOBwj2l9SbDhN8uYFUa/ZKFIABifnwSAEe2oDR8BKGRfKgCMwpMA0NKEBXYPVznhehcANjwAdHf0SmYDSPkmELd710Fd5U+bzCaQCyttAjkK4IEMELtdwbdl3MDnAHgOQC8Ax6p60wgArd2i5lbbiIzs2bUCQFbPeJBp68vVZRsdyd+XLOzGRz37SgGgADCkAG+NM6ZUyBolABQAJr1kJV0fuUIn3WyN1efi/xz8dQLg0rrcmUnz8k0AWwA8lGnZuXq/C6AJgMUAbs+kjXF/dq5kl8+lRQb6HBi+mq/HDgBvDKWBMdOq+FgATZdiaAhZi1DSLmCmb07ExI9gM4xnhPWUhR3WsmcOq73l1wBgY3bR40MCGuMWZkGMqSvHA8OeBGNeTq5WdExhvoe6lv5uWs84QwndQxZGrBTPtgc4f8oTM120z2YMOoUKJx6zazVdE+uizG6X36GcdLxffjgN7ore3UzWR4wPHdtJ9410i4f6JgtgekzJJZVeZxptQQEgGRcnABQAxl0lyNVKABgVWAAYD+IEgDnOTE4yBpDYteszDmmEVx5AzlQQd3Fu5NcJAAWA4UeAtR765QbkHmtq84ksgHWyiskCGM+KkzbOJb3hIznroSyApAtYAFgn644sgAnKLgAUAAoA8z9QcgEb1jnLdcZxSH7BMyVkAZQFMDxZ5ALeQ/oU6MfstCvY6AVIasRMADSNMzULSrzVidx5S8ex1VF9dvCd4WbNP9UT3xlMxnsmf2RcXKtgfo2CX43s5gkyVtBrA4nPA8zdbvwWuNCu+PXnsoCZNXJWNpM7qXQ28S1xVIyhp7XPqw1blMi3DGTzm0y48eIhrr7Ux4K4lQbIGAjWehgq98T378GRYgFgTS+BfovbaXS1AFAAGLEACgCNJ9jaLW4Vq4WlqaabEABab2zLBBqFKWJDQQ4m5I94Y9sQAHKwa2ZuCX8pAKxPWFPTS2B9utca7YsAUAAoAAwpIAtgja45QeUJJnPO1VnGslXfd/zKAigLYOX5LQtgWg0BYEJLtABQACgAFABmKSALoCyAIQXkApYFMCHkSKQaAWAiMgIBAH7pZ1m18TFlHvAUisfiYwA5txuffNkSsmbjHYNfMGQ8WqScT549j2u9xseU2HKpcvMp/PuP2imc63mphR3E3Ayzc00m9JjXTDW0FY9tnrT2EEe85W4xuw32iC8fS5zVF7ZdNucfu3OXug82Ps3CZPOIs4Tj4hI/lo+JA/UAwJjHvlmWclkAZQFkV1OqnACQez3zUEwCqgAwIhSb5FoASD3aNV9IABjVmNp4kiNHXczEza4TAkCTRiNfsjpFh1EAWPMLCt+CLIC8VlWWFAAKAA0Si35F76omJ6aHNVIASGpc08UEgALAkAK8q5gENvpkDbI+dgNNhPcEgDW9nFSnfgFgddSqoqwFgOaxZx4vbMZ9SJ+rS4MI505k+hbIZ1WXdF+I1DBs6pHYLuacNxudRKx2tIs2tjvWctmzDwg5T9iwY3plogtSNxK3tuTD/cga6WKcW9g8Co5iAq5+23JkDQ3jTkzb7MIf1t1LX2vev7nlNaukOTT0CRoWE1s11sL9U7t7ybFIsi67SdOKG54Tf1MamFxvKGqdVKGQAgJA69VJQoEA0HieWBgjNaZS0rBtWo+/Rz/I6uxFJy6yJVsbyWHVWDfJGuliHKAJADlBGQudANA4b1gAWI01oOaLJrt61nx/620LAkABoGHb476iAZgkJVkAY68TcRdEDhuq0y2yRrqYANCwqXHWQ1kASZ0Ia6QAsDqLQI2Xjbve1XjHTrcGBIACQI72jFICQEq6ZG12ydZGclg1ljWyRrqYAFAAGFaAADZ3SZLQlmRdufpGhAXIBZyeCwLAaizJVRU1AdC4gN4Fa0GBGT8YasQq4wMYdMwi6z6sJ6lhaJ1IYGPGJnjikkvbkqO6HIGWFmMRjz+9y5q0TpLFzJ3MPs8qcas+1dPXksDG1sfH1Fk1snF2xrXELl2+b2w/OIild6iakpBQZEoSupbQKGCYBpvyJUpotXKvRPqdv/3gczoKTgDILrP5ywkABYDhWUJvNKHi8+zfa4lvDIncBEdOdD8EgPkXk2qU4CFLABhWgI7Riwtyca9LU2FkwPz6S0I2vUmFrC9kjRMAVuPhroWi3OpeCx053ZsQAAoABYCUApYpMvKdLIDciigAjOokC6CFiiSwCQC5B6+BlBIAJjSQAkABIIU/cgELABNac9IONs4tajdJQoFpPMzvy+b7xvaDu1cBoAAwYu0Nga1cwGmFBIAJLcYOAG/40oNZtVlWDDoGkHQLxj/iLGlgM97rZOxh4rkBjTHldDIv5KxT5h4YK94v4TYM8Wh3bKh7tNXN9m1HdaJXF7ogBY/WI03fW0LrQa5qTDgxAcunI/nhLIBH26domdTydqahwB51xFsO8SJyErFoOecJnbiZg2I656HXJg3jbkL3QcN5gse+pYcr+8YEgALAvItadQoIAAWADAHV57hAGpIEgNVZGrLKCgDrt7VPAGjwPw2jAsDYC0MdXejx07uOelxPmxUACgAFgNkKkBuI/RwR5ApGw20Nry8CQAEgM8XMzRJEepOgbtKyy56YwvdFAMiMbX0qQy6f9anL9bMvLdoYLmA2lQv5pmTcx+aLzkoMTLpn7WJsKpOk3czxXaphT6mtE5mixpiC7JFxdhoYs8IoT5JhAVZkBzXFqEKudmtCWc8lt7yQzeZ48Lk26ueqUVWvODeuVQO5+TRHgjfDAmQTRXZBgm89zgAAIABJREFUslEftzPtPvQQxYYd0ipGuTvzQ1JuhmNT1JCQXcMbPoL7CLdheqxNv3NEqCTHRi7gtLwNdfWs9fVeAGhSJmMUM6chA7s5J7AJ3iHrFHFecFA/SSdsOQFg9NEkJRYAkqsayWICQJPFOPBm0pnQcZENNOWLAJB8YOuwmAAwIfEFgAJAairVq4TRoR6TJCYLIDXSnoU4EPEwdgkABYBRK5t97IdhjTNnXn6rnSyAnutCspcLABPSUwAoAKSmkgCQtApTajZgJ4YAMDwD5AKWC5hZFRjrrFzAaSUFgMyMIsrQAGjURbs7CQsNXRftAjU7HH2Jk3FhtquUiylLMm7Py2VLjEPwcCVcLulj5MKDGDd9THohIZcScgcx8cilFzCyWba++lKOd+NylhgmjM/VRLstIyc8sMpxaUtY2DPvnhQvyZiyxPtBx+dx409v+PCxADJ9Tjo1Tsz6BIACQHbFosoJAEmIIzef2DzJWhnzUwELZyZ0kdTBtsGWEwBGH0VyKKhnuD4VIhkmR5c5yLLRgb02uxzfX65+AaBh7aOTfpOWQi93rDF7BID1aQmh+pL/TUlVo0ICQAFg1KLGPV4CQE4na5VpyABYiFIUFpTFWFxPovRkyl1dcW3mZZ8qKEBZFbQmC2BUbsalKAtgrvOLQ5QZ02IXWKfN5NAk7IYGSBZAWQBjLKy5LxEACgAFgMQjJRcwIRKQOlmKuzrMRMvUcap8uNDhsiL8dvtF6NW1A8YM6Ia+3duhU9uWKGqSwomSMuzafxhrt+zFgjU7sHnXgVOXlwPgycIUUJgBSCKvnCyAJDiahjMyDYosgJbIke8Y174AUAAYa2HNdZEFgKwb0y9uL9Qjj7Nm2fi8+pUb0LQLRb6MHgUXvY6OMfQwRbHWPrZcfXYL2yMT39pnhxl61JfoCpBsZU0LjuOeji9ixdHuKEOqWpWnTpZhRI+mONbhSvQY1jfvtR+8vxov//xJ7Fq3tQIEmzfHrhsuz0AgmVcu+io2XtjWVxwAWTfCvOzddWw563w8m38JF63HsWp2KJ7VE3JsGPdsWigDqEzlOfAKGwDJGEOvE1mIe/37Dz6PI8V7GubikfeJryjQ6AWohlZVFhUA1lVyaAFgWIEk07T4bAwRAMZfXcoBcNnRntUCwFSqEP2HT0DvQeNQUJAGx/1bDmLXqn04sP0wSo6VoEnzJmjTrSW6DO6Att1bBWXKSsuwcfY2rH9zC0pOnMDClx/Hrg9fjZNFRWa6GM7id/rF+wkABYDxn9rT70oBYEJjJgAUADJTibXsseVkAWyYS1gcACxq2hwjz70S7Tv3DKZi8daDWPvqNhzYdsTe3QugXe9WGDilJ1p1bhFcs2d9MRY/uQZznn1EAJh5oGUBlAWQWdtPxzINc/Wsg5EQAAoAmWnHgh1bTgDYMJew6gJgsxatMXby9WjZpj1OnizDoZXTMe/Z9ihIpS18VZ1BXJAqwJkTu6LPxG5B2YM7D+OP93wHH0ydIgtgzqN15QIOr3dMqhl6d7fXDuX8YyMXcHr0GubqybyJEy7Tok2Hkzfc/2B2rVY8Hns+sOk/MyCL2AbpF2NotWk798Lf2u2y1xrl6PhGC0ZD9RHHxaUfEDL1DDteZL5EuzrycSXmRHBvVDl2/Llx9Vlx6FyD7LNNyslWFykXP5czmhacwD2dXgTjAi5q1gLjL7wpgL/SkhNY+u7z6Lb/bSxbdh0KCtMAyHy6DG6HIVecgVSTFHas3oyH3lqDIycLLK9oLizKasYn7s7qL19f9GoWPGJb+1yT4Yt9jngjY+W8zlY2LyZdwEScXTAK4fORudgBfsevPVGij2Ko3QAADygGsKaXQGbdaRBlBIAknJK7QBPfaBKl0+i8MzcyCwAZ6eyHmNsZzi4AAsCoUoVNijDuwpvQpn1nlJScwII3nsTBXZsxrOW2agOgq71Dn9YYcW3fAAI3bN+PX01fhJJSbvNBuHc8sHGkzNcnAGR+jNh6CgDZ9aghlBMAJjSKAkABYGQq0RZLbhJyFjv+eAyuPlkAudExSnFcY1bPWgBHTJyGrr0GoKy0FAvfegZ7d25CqqwkNgCmIbAlRlzXH6nCFN5btQ2Pv7kq1s3xwMYJxdcnABQAZisQnjuyAKb1EQDGXt2zL3QAeH3IBcy6QC3LRmy3rWmwsoaZs87U99QwbKqdcKwcBz+sm9SGLtvYycZKchOTvQ/mzLQkdw8Hi4vX6sLNT04lvlRcK2NVMXZ86xUlHQB+rtP0Kl3AZw4ejwEjJwUXLZ0zA9s3rgj+f6qsNADA5UsvRUEqvbnD+uTCLudGTrXbj4vuvj647O/vrMI7yytSxARfMuk9zEZPP9izbyP/fdCJi73y+1lsnj8GLj2GpLXP6B8T75fuWXYb7HW0y552RWfrJABM6+G1RMdZ2BrqNQJAY2RpCxhrZeKggInbY8GJLWdvxvDRhHtSfPoXbkEAWI0zjUPi1TYAtu3YHeMvujFI9bJpzUKsWvDaqR4VnizF0BbbuAmUo9TieSfR/tb7MH5gD5woLcODT8/D9n2HK0oLAPPqKwAUAOadJHVcoKEB4CAADwPo7NJfAbgDwBJD42sAfB8IzkpalClXnCnnlrbFAEoz/30vgNfzjZMA0Ad2BIAR9cgnUwCY78ms3t+TtADGP8oNKCoowWc6zjItgIWFRZhw6UfQonU7FO/ZhnmvPhHs/C3/FBaUYmizbXilzRkoqXwcHClFQcFJdOu5H6+9cy7uuWoCurZvia17DuLBZ+ajtCxDfgLAvGoKAAWAeSdJHRcgXzN13Eu++VkA/gDg9wBuAfAVABNCl7cGsAbARQCWA3Bbd48A+HIlAOwAYB/fLCAAFABGLWo+mnCzTwDI6cSWSgoAHfx9uuOs2Ee5lfd31ZHOKC0/CSQDXQPHXYqeA0YHO37nzfxfHDmYvVQVpsowqPkuzOrcHyUFLpFz9T4FBWXo2XM3Zr50Nrq1a4fPXTMWhakUXl64ES/OW5+uTACYV1QBoAAw7ySp4wINCQC7AlgNoCOAkox72wWuTM58Xy71hwDcBWBa5ovhAKYD6F0rAGgyQXI7TVkgiB1j6PpvprexZjLpsrW3/EYqZE+l4GIvyU0r7HiZt2/F+9U8FNLu6HAECL0Lml214i8viccP1nSXQ0AUxPB1nk4e5RaNxWoCB3HbI70u6tAHHSZ9Nvj+wJIncWTDO+adHS8FXu/RH6UnqwJAO44tDYB7MPOls1Ba2gRTRp2BaWf1Q2lZGX7y1Dxs33s4mlfQzp8S6RubZsW8KZ/ccFaFPilJjPqiwGd2OKqJTzqWBOPzAlwzN3z7xBQmGStpik7qmV1MMYBpPeKv0OyCWnvlzgLwKIAhlZqcDeCrAJxlsPzzJQCDAdyd+aKlW0sBNMuAo5ux77tYagAvAfhXAIfy3QZtAWSBwoyfyw8PAsAcGzciM10AGHn8BYDxV8QcAMjk8YsmkAMsN66L97ty3E1o36oTduzfipkLnzKXpVSqDF17FmPbnk4oK2tSxdLFAWAKBfjC9ePRvUMrbNixHw89uwBlUROg9XYWAIYVsJhQABidOz45FAmwFwAKAHMB4JkANgJwGVQfysDhPcbqdj8A9y/4FDVr0evmr/46q1jyMCYAjCpAgpwA0Jo82d8JAOsdAFZ24w7rPgJnnTEBZSfL8NySp7DviB2lkkqVoEePvdi6tUMiAOhY78wubXDPNeOC+fL4Gysxe1XVu4LTE8uyHFmcmN9KlKM6+4QTD3iwaJlNPyMLoLWrOP/Y8q5ybu4w4yUAbHgAmJQLuPIsczkWfglglCyAlRSQCzjfdMg8XXIBc0IZWO/lm/C4OO6lNWQBLAfAZk2a4frRN6NpYVMs3boY8zbNySltTQCga+zG8wZh4pAeKD58DN97fDaOl1RsPLEymQgA5QJmYEwAGHeV9L8u7nLn33LN1PBKZgNI+SYQ5/49O9RUm8wmkAsrbQI5CuABlwMVwDEALt+BcwH/dyam8JP5upt2Af80VCyudcpOR8HE7dGpPOgULdbL2Zo25E5ej3Yt80zsE0PIIDMvK641aWK69nPNP7Z/fFxgeApzSwQ97/I9SKf+zrVLSky3mlTBdAzgDCw72gNl5Zs4clRueayauJ28zbed2shx9pnnYGi34Th64gieXPgETpSdyNQWhYxUqrSSBdAlOuA/rjYXA9ij827MmjkGpWUV17du0RRf/sh5aNa0CWbOWYOZc9eaFZ9MpYDCwhxMmN8i5CplwCFovN5Y+wwp6Bx18fPx2SkETT9zpIPsMXKJ5u7zieOk9YyORfgenvxvdxTc3viLDP9I1euSDU0AF//n4K8TAJfW5c5MmpdvAtiScem6AbkOwHcBuAAZl/Ll9kzaGGfx+0XGd+H+Ng/AfQD25BtFAaAAMN8cCf4uAKRkiu+L9U1ATXYvT7EkAbB58464buSNSKVSmL3hHazc4ZIXlH+SB0CUlGDfD1bjRHF5JqyK1iZ+7DKcf/s0nDh6HL+9479waE959qxKPWreDDuuvQQnCw34JOKzBIA5NmOQCaP5JMrWJCbduHFBLu51OX4U2PcqAGRXsYYGgOx9J15OACgApCaVAJCSSQBYYQGcNPAy9OnYD8VH9+PpxX8PWceSB8CTx05g1zdXYszFN6KgsGnWeKWKUpj06VFo1qYptizcieUvrMv6u0tNs+iVv2HHzVNRVmTsQBYAWnQS2zonC2A8N7ssgOkpJwAkX0f5igUA+MWQC9iMleMkZ9y95gDWSptcehfbZctdy5zmkcOgZk/rULN0/dbAJ+w+rjOrYPjeWDi1z9/L94hkFhxu/vutTGQbVI/jFXIWwM93mYGlR/K7gK0Wyl3A8/ucg6kjbgyKvLp6Fj7YuyFvhywXMOd4Tfs+AgD895UYf/mHUVDokiNkX919REcMmXomTpadxOzfL8PRfcdP9am05Djen/kYtt90BU5aAGj0vr67e+O6mVnrlBkr6ZWOJb8FLF2ChCezHGkpDHWlLuL9gjsN/fAQAAoA8y6k1SkgADRJKfIll6Mvx5FcCW4+EQAa4yUArM4jX2XZpADw+KS70btDX+w6uBMvLHuG6l9NA6CD8wl3DEXLDs2xdfFurJz+gQAwTRlZ4yMAJEHUI46T/fEgALSXjrr/qUwtafW/kABQABhWIPENGklbHqMdjgK7+ehxVlx7RpBLDlmsvi5rSQDgyC5AxwtcCDLw8soZ2Lx/E7UQ1jgAAug2vAOGTuuTtgL+bhmO7k9bAWUBrBgiAaAAkHpg67CQ1zJbh/2ud00LAAWAAsD8jyV91JrXyuR1cf6bIEokAYDnTLoEzXuMwp5Du/HcUjvps9WV2gBAZwU8585haNG+GbYu2o2VM9JWQAGgALCqx0MuYGLxqMUidb9S1uLN1mRTNgBGW2Rdj3aYFZFWxifNCusCpOMMyY0hZEwZqx11ZJxpxLK+NO7BZF3uUaozqyCpcdQESN4/aynkfifkqI3T2KcrSa0RaQCcGTsGsG3bdjj78k8E3Xl11Uv4YN9GO62K0eFUQSl69tyLLVtcIujqpYFx1WXHAGZvAqncXLcRHTF06pkoK01bAY8VH88GwCbRTSCmVcwS3cMtaFdHRkF6tBu5N7NJMuWLR8oTOqaQPkbOI6F36FJ+h7LVJhezaMdsZl/75H/fqzQw2gSS1HIPCAA9cgOScCIANOYr6xYmNRYAJrMm+ALgiAmXoduZQ7Hv8B48s+TJoFMkwqC2ALAg5WIB01bATfN2Ys0rmwWAlaePADAyaQWAyawvSdXi8ZM6qS40jHoEgAJAZibLAmhBLKNcjo1B3KW1nu/ABwCbtWiFSdM+iVSqEG+vmYU1e9I7f+sbALo+9RzbGYMu6Y3S46V451dLcezQkYpdwLIAGrNTFsCIKJa108cCSlwrC2B6FASA7AskTzkBoACQmUoCQAFgvnkyYOQk9BlyFkqP7MNfF/8VJ5B249ZHAEw1SeHczwxHUfMmWPv6Fqx/e5MAsHyAZQGUBTDfw17HfxcAJjQADgCv++JPsmrjXZbcMDC5Ac2a6Ji9qBg2sBCxiDl/XpBxgT6xjMbvmmh1Cd+DNY9Y9yxZzsoXaDfLzafwtTSckvcarxfllZNXk8USeszpapoWlODertWPASwsLMJ5V92BoqbNcGDZc3imeDNKCtyhRPzHbQKJHwN4MhMDuArjL/9QJg9g1W33O78HzpzYDccOHMebDy3A+zP+jG03Xl4reQCtnrGpQej8fmy+vIjlibT2sfXT+fhMVaJfmifGmQkII9eyGkfK+cRY+iQRD+cB/KFiAGUB5NfUvCUFgGxqEAFgbPAiQTEuyMW9LrgfdgNR3iepcQNg7wGjMXjshSg5cRx7X/42ZrbrWe8BsGmrJpj46eFIFaaw5Jk1ePEnPxcABtNYACgApBe8OilYT38/14kWXo0KAAWAkQmUNLAlXV+owwJAryUg6+J4FsACTJr6cbRo3Q6bVs9H05WP4aVO/es9ALobH3LFGeg+shMObD+EX33iawJAAWBagbDVThbA5BaZBGoSACYgoqsiAMB/CrmArRe2R/oRJjUM4ybOdcvstbSbmd55WvtWQSpVTGDY8gBbS+ikIY6tL2Zf7DCGhB6aU8Y+n1QzbF9qd6kLALDbTCw9HD4KLnckX6cefTHm/Gtx8mQZZr/4e/QrWxUTAEvQs+e+TBqYFCvQqXLpNDCVXMBm9o3sL1t1aYEJnxwa1PGn+36K+UMH42STqOuajWO03LPWjbCuyJp390YtfrbHkktlwu+WNVWJfkmMYYbYItfaoYzxjoIzx4HYtJGDpyOnr6RHIb/GT8oFHEhau6titZei0+cCAaD1EveAJ3NPSXJtCABtt234iRMAxluD4gDg6POvRecefbFzy1osfecpDGu+/bQBQKfSuFsHoV2v1lg6Yw5+v3q3AJDcBGLzihmgF4Wz2mjDJm+jLwTe18GOXwseBYDp4RMAxlvfI1cJAJODs2BiCgC5mSkLIKdTLS911QXA5i3bYtKVnwwszu+/8RT271h72gFgt2EdMOyqvig5XoJvPfIaDpWQCYRJwJAFsI5iCsnxoayxAkByvaqdYgLAhHQWAAoAo9YzY3KxwEaWo3cGW/OcaEMWwHgLRHUBsP/ISeg79GwcObQfbz//RxSmSk47AEwVFuDcz4xA05ZFePbtFXhlcfTsYsJGlBbcZ8cnCyzm0OZ3H6a7l3+3rFzAhsACwHgLSg1dJQBMSFgLAJmYvbQdlkxJYvJE6Fp2N6ZHmhU2NYx5/7ZpL3JnrIs2rsYE+2T6RI6NHRgZva+YIJaeJ9GL+bN1iTg7XhTjvlh3f0IPXHk1Xn1OuC+VqksD4EtYerg7ylB1HF5BQQrnX30nmjZviTWL3sKGFXNRmCrNAGC/mJtA/GIA9/znKoy9+EoUpJqRIqWBqO/kM9Hn3D7Yvf8w/uuxt6PeTRbsiDiunB1jNxqQbTCwRzJn7Ji1DBVHmmEh0z6D1+y10QYJxUSamkTjCXOBOBFT+NQPv6Cj4OQCJtc2opgAkAMAFh4FgBbtCwDJXwrEE1uz8S/VAcCuvQdh5LnTUFZWijef/R1OHDtSpwCIkhPo9fI6jBxXfftAqkUHdJryABzU/ur5+VixaU/2WAgAo4BFgqhPWhkBYDZ6CgDT07D6Tzi1tDa+QgJAAaCFZ+Hv2B3U5hMkC6AhcfwlLP6V+de36gDguItuRIcuvbF940osmf1iUHldWgBdIukeHfdg+5Y2KCsjVcq8X1Opk7j8rKno3HIAlmzYid9NXygArKwAYZ0KipObO2QBJDfLhAQVAAoA86/i1SghABQACgBDCpDsUI3HrMEBYMs2HXDu1I8H9zXvlcexb9eWegGA1U4jkyGRgoKTGD2gI0Z3ugllZSfxrT+9ieLDxyrGTRZAWQDDCpBxgdY6YVs2rc1HsgBa+tXGEu21vp8uF6cB8Md534BeeeWInHS1cvycMSisa7fexAWacZfxHxGvcTWbJR/NhK2CiVosyYe3VjaakH1JqpizAH6h+6y8MYADRp0XnPt7qHgP3p3+yKnm69oCmAWAdEydC2c+iTN678P49p9H25bN8ey7q/Dygg1VysrkbctZAd03Mo6NBFTKHdtQrH2G+NSOXzoRtM/YxLv2qR8pBtANK/mWSWpZbLj1CADNvC2MUcxOtkyd55tjCjNQJADMkWsne8i8XNbk495YAdD9aDjvqjvRrEUrrF74JjaunNcgALB3770o2HULpozuhx37DuG7j70tAMwowMNu/JQvicf7CQDJlez0KyYATGjMBIACwMhUOg13BssCmMyCwFgAO3XvizGTr0VZWRneeu53OH70cIMBwLlvT8IDN08O7uenT76HDdv35zbi0ZsgTBKJfGmnmolnKco9GwhAkwWQPArOZ2ziXSsLYHpmCwCTWe8zR8HJBZzXfmRZ5+oiNYwsgLIAJvTsW9UwADjy3CvRtfdA7Nq6DgvffCarmtPZBewsgC++OAafvfIc9O3eHu8u34y/vLZMAEgeU5YWigDMnOU4KLLb4DI1ygVcg4tHLVYtAExIbGcBvPa+bABk48LouD2rryGQsWPxohfy5/5ymzvMXIZEf9O/Qsg2WLcwm+MwYu6ycv6xE4TMF0hqYhfzeFwZt7hP32iZPO6BbIPOjcjUZ3WXeEcGANgjdwxgUdPmOP+aTyGVKsSit5/Djs1rsnrTpKAEw1rswEudEsoDSMa2uVtLpcrQq5fLI9gepaXVO0vYxQAGAPjCaIwfeAY+fOFwHD1egm/876s4XlKWY3crMxC5ki8b17L3SiRzztUz+9L8E+N0POPX76g6QhNLTDa2M6aVVRZAWQC5VYcsJQA0AIgECgEgB0Us3JtTVgBIPsmhYjUEgL0HjsbgsRcFOf9ef/a3OFlW1uAAMFVQhK9/4iI0bVKIR19ejLmrtgoAiWTJgf2PTAPjBWfWE2HCWLQgD7ICwHgLT+1cxb15aqcvp3UrAkABYNSgSD5e5GkWAkBuiahPFsCVhzuj7GR0Hoy/7ONo3aErNq+aj9Xvvxy5scJUGQa32H1aWwBPlKTw0SkjcPbgnli9ZQ9+/sxcAaAAMDLX+VQunLWX2WgjC6AsgNzbhCxlA6BpAot8ybqKrZDNyLWspacWjoyrz25hGhLoWEFurOnj3OpgAwmtCWnZJR8dPhCZBGW23ZosV5Q6gXs6v4KmTaKtNGnTHR0vuC/4w543foKS4q1mV46XAq9164dSZCohXZsFHi5c15FTLuDN7VFaFs8F/MILo1ByohADenbAPdeeHdzftx55HXsPHjXMSVbeNtM8ZZmiokBBbyrJb51ylcvdyyZbzg9oDJylNc9/1nLQmtm1/Nc+9aP7dBScNoEk9woQABpa1gZkxowLpGFHAMg9JB5wRtpJqU0rXGdrvlSTJqW4/KJ52L45eprGuH6TMPyMsdh7cDeem/eY2ZnCwjJ07XkQW3d3Qlk5hJ2GAOjG9l9um4wObVoEOQFnvb9eABhSoMG4e01mz4YxAWDNrz3VaYFee6tTaWMsKwAUAEYV4Da3eMVAWg8bC2Oh7tFQ7NOmNU3YBYO9L7a+GiznAPCKK97H5s0dcPJkhRXNaXzj2A+jVdNWmLvxPSzdtsjshTuOLXIax2kIgO7mrp44EJeM7Yetuw/g+399RwAoAMxWIKYVTxZA/wVMAOivYVCDAFAAKACM9zDRi1ADAMBubbrjimFXBUI9/v6fcfj4oQYPgD06tsYDH5oU3Of3//I2tu45GAIAuYANKia/Ss49mxOo2LhFayaHfrTIAhhvjaypq+i1twY60AXAxQAmAujhGArAbgArAbwOoOr08TXQIZ8q0wD4o1AV8VOD8Glawk3GtzqxbVo6sRsUauPIOLt/+XWiLWD13C3sMz6Ra9mYUp+HJ2Gwq8tFrVyGwAI4dQE2b3IWwIoendtvMgZ1HYLtxVsxfdlzud65XqlYfGL4XIeo63OEzwVpYM7YixeeH4WSksJTs+KBW85Fj05tMGv+Ojzz7qqcs6UQpSgscJVzuezCQFF6MgX3j6Inq5QZPkbGCob7bJ5xyz4oVh5ATpPayO9nBUZacXsR4CP1tTdBk5qY45p97dM/Vgygk6ku1sqLAHwRgPsZ7KKbNwLYBcBFB3cAcCaAVgA+APAbAC65Xu408uzzVMPlBIDcVBIAxgd0+2n10Z14KASAhEjRIhYApgpSuGX8bWjWpBneWfsGVu1c0WgA8JKxfXH1xEHYe+BIsBnEesE7+Ptcr7fRsvBELM3dRYdKi/CzTecaEEhCHAkoVgejsGMBC3trJOyQ6WJiJ27O1V0Tbi1Lbug7Ul8BIDtP/Mpxbw+/NipfPR2A8wX8DYCLfn4TwN6wbQbAcBc6AuBWAH0AfBLAs8l1I/maBIDcVBIACgCjVkZu7rBPbbK1sa1ml7MA8IwOfTBl8GUoLSvFX+c9iuOlxxsNAHZo3Rz/92MXBPf7syffw5qt4WUfcMmz7z/jdSw71AWlRuoceyQqUMFZDoe12oUfbDgfx0+Gt18LAJmZzIKiLICMmvW/TG2vld/IWPT2VEOaSwC0AfBkNa6p9aICQG4qCQAFgI0VAC8ceAn6dOqHD/ZuwCsrZ56SwUITn9M4KBduFSskdX0VLuCe3fZgxgvDs1zArrl7bpqI/j074u3FG/HXlxdHeuAA8Iv938big11RBjb9TEVHUijDyNY7BYDmMXIsAHPlBIC1jhg10iD31q6RptESQMXp5zXTRq3VGgDgF0IxgHSsGAkFxJm5frF4UbkaSlwgFWYW9wg5JxvVQK5i5PizERtxcwiS92A+VORKQsdZ+jy5Pvfh026la50FcOrUBdiUiQEsKizCh8ffhsJUE7y2ahbW71lXZUsUhOWowedaxw7B9b33YfPm9iijj4LLgENJKfZkIJ5VAAAgAElEQVT/aC1OFJdGejf66km47L6bcfTAYfzi1m+g9ER2maKmwEfuKcLiA11QVlARP1hRUdUxcAEAtnEAeF7EAkhuoM51BEfkXtiTMMIXsilf7OTI1oCTrmLj0qStfWbvCOHZnH9+mmT3TjGAaT3IZTuhVTG7mvcycYA7a6T2Wq5UAEjCozEutWEVpJhAABj/qSFXksYKgAM6D8L5Ay7EidLjeGzeo4EbuKqPD8T5XOsLgCePlWD3f6zGqIuuQ0GqadYtFrVoggvuHY9UYQoL/roCO1dlu4FPlh3GmHEzsKS4M0pTRgbtPBtDBIBpuVmwY8ux1j4BYPzls66uJJftGuneuwA6A5gGILwtrD2ArwD45xppuQYqFQAKAJlpZYOoLICMdnQZivbp2mIVDFsALxs6DT3b9cKanavw5trX8tbpA3E+1yYFgGMvvTkCgO6mR904AJ0HtseO5Xuw5OlsK6gDwJGjnhMA5oK4er7hQwCY97GudwXqEgCbA/gTgMkArsukfXG7f90O4S9ldgi72L/qfAYBeDgDlm7n8B0AlhgVXONSUgFwfgaXidWVKw6Vc/GK/wZgHID383XCAeA1X/hhVjE7wW/SqWHCPSPrZ3d31sZpHmwb9jlqkaFhLIo0I9Qnq6A1CelxJC8OFbO9yQkvG2R1tWI9zPegk38PAHDawsAF3KywBW4Z/1G4XcAzl7+ALfs3563FB+JSBXFcuBVdirqArd2d9i04C+Ce/1iNXADYdWgHjLi2P0pPlOGNny1A2YkylLtTHQCOGvU8Fhd3zuECrlq2cgvg99dHXcDmldZOVnN/snE15do0kSjypZdr06au6Lem99z6khxrVrvwJuDEj3gzbtVqI/Td0z/5Jx0FV8cuYDdybul3gXOfBvBLALcBaA3gIQDfAbAj70qZXWAWgD8A+D2AWzJWxAmhOlz9awC4dDTLATwI4AiAL1cqdw6Ar2d2I98gAMxWkIUC+oQLAaAxzWkqigIwCcpMBAg71tV8TokJFa3xdAXAQV2G4dx+5+PoiaP4y7xHTwFPVZo1VAAsLErh/M+NgfvfxU+txc4VewWAJrCQ8CgAJIE6lAdQABjoRr5lvJb3qi52gR53AfgBEGwKcW7h62OAn2ujK4DVADoCKMncmztl3VkY3fflnw9l2nSuZ/dxKWdcepremf92/XgFwM2ZhNQCwNAIslAgAOQeL9otbD1JsgDW2OLkU3FlC+BlQ65Cj3Y9sXLHcryzzmW+yv9pqADo7nzEdf3RdUgH7FixF0ueWisAFABGHwjTOMntULYtqgJA8vWRf3FKqMRnMjF+DrwezUCac7n+C4DvxmjjrEw9QypdOxvAVwE4y2D5x7mXBwO4uxLwHQDQLAOOziI4F8DvALiTywWAAsAsBWhLFOlnFgByTzutO1ddjZYqB8Bd23ri5nFp9++MZc9ja/EWqt2GDIAO/hwEOjfwmz9bgJLMbmC5gCtNDTbez5pNJFCyO5nppMzE6S3sjl/79DkBILV4VKMQZ6KoRoXVKOq2wT2RibNblrnOuW2dC9fB1+ft84BytpAEALqj6b4A4NpMK1UB4P0A3L/gU9SsRa8bHvh5flBgU3RYVMBYe1h3atz63R16tJG4VZCGrLB4VqwkOXvZNj1csWQTthGfmSfWrZJzk1Qpx8EldbTk1HKzDgCnTVuElsfPw8S+ldy/ROyY0zdeKpb0yNjXkrFdmet7996PzZvboZROA5NuuyIG8CYUpNxv6uyPgw7n/p0cuIELsfipNdixPL0bOADA0dWLAax8Vy4GcFSbnfj++knRRNBsDBwLVEa56NDGT9Fi7rxl+8beqxnHR92YHcZAnPKRJEwGcyZmTKFiANPjXMvLYtbkcpsr5hvTzbls/545JcS5g9lPEi7gb2dOHSk/i8hZJ10corMWPl1VR/hNINyb186/F702AlQecGbzikUTBjyZt2WV43a8+kCm3RUBYN4HSQCYVyK2QDkADmv9MXRvW8n9yxkxGjQAOg1HBm7gjtixci8W/92FZAsAs+aWB5zZhrja3/CRHtTsdgWA7ApSO+XqEgCrusOhANxJ6f2rKYOL3XMbQMo3gTj379mhOtzOYrfiXFhpE4g7h/gBo60acAELACMKWLPQB2QNiaNALQsgNQ4evxHZWNFqPuPxitfySucA8Lqr1mJSt89mu38FgMH4dRncAaOuH5DeDfzg+8H/ygJYaWoLAKPPOR0XWHXCcFexLIBpeWt5WazW2u0setXdBezi/xz8dcqkdbkzk+blmwBc8I3bXew+Lu2MizN0m1DcmUS3A3BpY8IfAaBpFpQFkJnJtLvb0FguYEbhapSp5ZXOAeCnbirEkPaX4+iJI/jLvD+l3WYCwGDQUkUpXHDPGBQ2rXADCwAFgOUK2PGJBhPKBVyNRTBatJaXRbggOedm3ViNXt/q1ovMBo9qXFa7RQMX8L3/nd0om0PO48i4iGWLdOOdjkfGJekWZnIF5ppB9KYNNhaPHDOrP3RfzItD05X9PUivGnTBSO/oK3lSrtUFwQHgVz8+HB2anYmV2/ndv+WdTKVK0SsTh1fVcWwWT7oYwLgxfAGceVxfHgM45tKbUFCQfRJIeADcRpBuQyvcwBUA2AmlBdZJIFUP4akYwHXRGEAWKCxCJ8M2IyHrXidtWLdKdsSr3YTbiPYlv3XO3Tob22fznxXvmv3dMz/5ovIA1oEF0G3wcGlYXgbw50ycX+UULW7sXZ6+8Zlj4hz8uZFziZpfrdUVvJqNCQC5WEEbYsjXfYJuYQFg9Omnd9mSw+XjYOCboEtW84n2K96+TSH+70cvhptnM5byu38bEwAGbuAbBqC0JO0GLjl6MLMJRADIxsrZnEiamS03swDQ78E/za6u7dXTbepw5//cC+DDGdhz8Xe7ARwD0C6Tx8/1a0EmOfRvARyv77oKAAWAjBnLxy0sC6ChQD21AE4e1RM3njci7f6dm3H/VmMRawwWwFSTFC74fNoNvOTptdi2ZJMAMDNHBIDmluLIEyQLYDUWFWv59Lu82le71C+TALj8fC4OzyVsHgWgBwB3NNweACsAvJHZqFHtBurqAhMAzdguchcse23ohtndw5Z1Rm5hczcKNaVoVyzrFjZpj/uSZyLi959Pf7nu5tCX6Bs1MtUrFLfV8Ovqc9efhQE9OmHF9mV08ufKPfVxw/pc6/pw6vpN7VBa5qJvjE8OI1PgAv7P1RhziUsDU7UL2NXqjoXrNqwjdq7ai4WPL0oD4P5OKE3FdwF/b925VBqYJN297l4o16vP5g5rGEiLnZlWhryWui/WbUtv5IjeLOsWZnIIPvNTuYCdwnHXu+qtqhWlHeDdmHHnVobBuPXVm+sEgNGhsGGUm3IsjDbYuEAanjx2MzOPvwCQWmMqv9fatGiKr33yIqQKCjB92bPYut8dSFS9jw/E+Vxb2wDYZVB7jLpxYOAGfv0nb2P40GcEgGmapCYMC2cCwFAMoAAwmF/c25iailShGZlS/wrgLQATAbxHXVnPCwkABYCGAuRX5GNIbhaRBTD+YkGORKSByq+X84b3xi0XDsfx0sP485xHUca9y7Pq9IE4n2trGwAru4EX/X0ZujX9gwBQAGg+wLIAxl/Xcl0Zd72L25NhAB4H4PL8uWXRbQCZA+D9TMyfi/vbHrfyurxOACgAJGkvUsxv84UsgEk+93EXxMqMd/c1Z2FI707YcmgBZi6ejZMnq1+rD8T5XFvbAOjaG3l9Oin09mU7ULDuhwJAAaAAMMlFrYq6qr8yJdOx0Rno+wuAzgDGZDZ/uHXU5f5zIOig0CVyPi0+DgCv/nx2GhjTEkOnhiGBKmzEZV12Pjtqa6MNY9QTdQuTZjK6TTqXHxsDauEkey33WHMScHWZDyk7T3yecI/u+TSb69qWzYrwjU9OQWFhCgt2/xULVu/1A8Cq4vBydIKK4Qsgw64guP6M/di8qS1KSwtztGJfnI4BXIMxl9xoHgVnVdZtWAeMuHYASo6XYs+sr2Px3nY5YgCrNqWm08DswvfWGjGAxs3aXlbOXEu5XutTvJ8lvNk/Lk1L3KPq/NLxcH1jzjh+5qf3Kw1MHbiAK0/D5zOnbyzJfOmOXRtb6Z+DxME1sUjXRJ0CQG4XsO3F5N7iNIwxcMvRT5DGg/uwljgW4gSAlO7s8FCV+Rc6e3BP3HbJKBw9fgLv7PopNn7QRgCYR9bCpilccO9YpApT2DfnYcxbtVMAaGhGQWcA9lYePLPCyJc0oMVsg67fBHYBoP8KlV1DPVs+k7692qtPACgADM82n53B1sytnRQykbuI/xA1QgvgnVPHYlS/bpi/egv2tXwEH3zQXgCYdwadxOibB6HzgPY4smkO3n79FQGgADAKp5bJ1mRCc6txVn2yAKblEADmXZy4AgJAAaAAMKRAIwPApk0K8e93XIyiJoX440vz0HvYSwJAavk8iR6jO2PYtH4oO34Yrz7xEEoKrPQzcgFzcsoCaNCjANCYPAJA6onKXygNgD/IKkifNsG+KKkj4zgXo21NMtyYpimqjtqwJjDrog2Vsyc+eV9sm3RcoG3vi3zLzhOyOub3H32r5iPisbx4Xepxcf5HPWeJUf264s5p43CipBTf+ONMXDp1YQIA2BalZbni8Ow4Pi6Gz92GDVTp64szMYA58gDmUMHFAO77zhqMvmgqClJF0VI5GK6oZRHO/9x5KEgVYP6sx7Dr/7N3HtBxVdfe/09RlyXbcrdsy7bc5SJ3sLEBUwwYmw4BAiQQWpKX9xJISKWEJC+QfMkjJEAghJLQgsF0XLCNe++9yr0XyZKsMuVb584daebeM3P3LZJGoz1reZGMTt2n/WbvffY5cYicN5xQ8QHMET6AY3RxAB3395NHao5qc5MFc5aNTRP4+4VmmEYKBLkp+aRxoGVgSzMLa+c6awBZA2hjq9dnZQDUy8RxyGQAlDAhEXbkzpeGa4AB0FBEdQnumDQYI/p2waaS43hj9ipcdc3mFgeA8PnQbcE+FBUT52WEeFuP+Q5S83rh4M612LpmPgMgZepZ9MWTwlms3wRO1sEASBnVRktjfpU2WtOaV0UMgAyAMglov6MDFVEbSfXiYABs0A3F43bhqXsuQUZaCt6euxFrdx9okQAotIdd25/F0YNZCPjNHS8D8oswos9EVJ8vx4KPX2YApMxYJ+GMAZAi8aRKY26FJlXXne0MAyADIAOgDnetLzIbOxM5rqL11uly9uuWhwemjIQ/EMDjr81Hjb+qxQKgMB8fPJCDQKxn5GLIPSc1HdeP+Kby1xVz3kHpKc0LKgYRWtgEHBIs1fRMvpHrJGSyBtDBXcd+UTa2WfuVJ1MJMgCUv7cr67UshAhNA6Stgxq2pDHeDJYppxLGLEwJFaMMFW0cGueGLq0t8hlGWOoWtYSx1jFd20lbE4m8X9w8cSAuHNQdOw6ewgsfr4TX68fVU7bgwH4bt4ANY/HJj3s7PnyixHB+KxBnlFcKHerApsCPWwZMQUrrbijZtgo71y00NeRhAHxmt94HUIpF5BuksmYQLlo0xnNu0qbZ8ZXTF+jkCxzy5kod/iQNsd427VB89jzHAYxxuplac5xYlQADoGQqUC8tUGGMSBQkCKbWyQBoeY0ThytG+QRgtdwyZzOKfj5x9yXIyUzD9AVbsGjTfgbAGBpAIwCc1qYnsvtPRmV5KRZ/+qqpgWIAVMVl58KHROIMgKamYbNK3Hx22QQXKwMgA6BOAjY0ao0SQ1DbYBvtlerwbO0utjI36m7Rs1Nr/NcNY5U6n3h9HkorqhkALQLg5JpK5E38kSLLpV/+C+VnT5DHkgGQATAkAYkGVPMVawBDkmo+uyx5G2iahAoAfjc6DIxcujJzrwyeJOlI2iiiOVlaJdXE6HAdRHqQ8wltCie2VlAqAD1P0rpKNlvr+Y9cgb7BDsMjcUo0zWLX1Dr1wv64ZFhP7Dt2Fn+evlT5a8gEvBUH9udaDwRtMRSLkRnWSGhW8oc1eyJvt27ncPBAK/hlPoBx/PiECfjys/uROe5HyM5thz2blmH3ppA8Y3/qCwwB4Ck8s3u0LgyMzDGO7AMnAwpZgwgm38Z4zUPeNDtP3NFCrVD6ZkubKB1EY9iTQeFnz/+In4JjADTaCul/ZwCkwQMJxJSfJjIApoGyHB4I7aPWSQJx8euKCtQMgJSVZs+kTKnBWppf3DERebmZ+GTpdsxdu4cB0CYAVvaYioJBF6D87Eks/fJNBkBVAtTLHQyAUglEfckAGBIH4VS0tim2tFwMgLSpxABIXRlETbG0OGvgaev2bAvVAHbJa4VHbx2vjMJv//01TpRWMgDaBMB93v4YdcXdihwXf/YaKs+dYQ2gidu9DIAMgNZPGWpOThclAQZABkDtkmANIG1OULeSRNQATh5ViCtH9cGRU+fwzLuL6rrCJmDrJuDN5XkYc/V9yMxujZ3rF6Fk60oGQAZA/asiYlbILrwQQs2wBpA1gNRzh5ROAODV3/1DVFpyyBOq9oRyq5b0XFwM5S+l/Jh64+blF+i4JlI2S4jEQgdFGlARq9UbAGjFx9A52spMWmOJaLD48W3jIbSAM1fuwhcrdkYB4DXX2vcBbIhQLPGELfziDP344ihYlLzdVR9Av7ln5MI+gJvO5aHX0ItR0H8kSk8dxYrZb6s1Et4CzjmF3+8ehZqA13hOEXz2FMaQq9QMy6f4xCmF2Iiz12TaPrlTpaQ50dJr6CfeYohTJ+PP/so+gDGPcsOZzQl0EmAAZADUTQoiiTEAUjcUG5BJrcJEuna5mfjFnROVHM++uxiHTpYxADoEgNlt8zH68tsUeYpXQaory2O+XRwWevgSCANgI1z4YAA0sVMkbtLE2lETV06GLWMAZABkADRcJvIE5F2InNBiQ8xlu7S4J8QN4NNllXjqza+jMgsTMGsArWsA/UEPJky7H2kZWdi2eh4O7FzHAEjVWNpKR7zxywBobrNI0NSJtaMmqJAozWIAZABkAKSsFEka8i5ETmixIeay/feNY1HQqQ3mr9uLGYu3MQCqr4g4YQIWADhg5CTkFw7B6WP7sXredAZAW2Cnn9vOh2SRrR82AZvbVRo3dWLtqI3bd0dry8jW+wBKo4BIzYLUG5/GtzubxO9QSJJq7nQ4nZPhYuimWP3UIfsUEkPD2GkL1VeONhTELYKYTLbobN0+pq5iG+2TVSFe/XjqW5OUPz33wVLsORJ9UzWkAdxmOw6gFR9Al9sfPxZfPJkFQ0/BWYU4O3nrfQDbQgBg2049MOLiGxEIBLBgxouoranStTwSL4QJeIjwAdwl8wG0YxaVCIz6jJw2a0L5+8n6ZecZOUJMPluvlBDKV7okSxf93ed/fYTjAHIYGOrpYZyOAZB2wlJBiZqOAVCOVMYzlsrstHG1E1AqoQHQ74croD9Qxg0pwE2XDsG5imo8/spMnR+/AMDJU3bi0FE7bwGXoSUDoMvtxsTrHkRKajo2L5+Jw3s3MwBqJEC9aEJNJ7+QQjMLU17gaPDyGQApW39dGuLubqrMFpmYAZA2lahgR03HAMgASNpwaNMzuii/H/mzl8JdXaOr4sb/vR89hvfFhs+XYc6f35c2ISXHg5wf9AS8HlITIxNZeY0jnD9ZNICiP4PGTkaXgoE4cWg31i38iAGQATBKAnKrOGsAqRuOlW2RWnaLShcCwGej+yx9WcLYjBsqhGgW1tRBNx1a99mTWzFl/ZLUIeUV2jR0FApp9k97r3mQXxaRCKUx2mdRbUdsGt3AQBt+x/cTI82jq9aHbl8swMBx18LjTamr35vuxcT/GQW324U1b2/BqT1n9WASqMGmhZ+izc96wZVGCEmiKcFSKBa1DLfLuglXFGHHjBvOe2B/KwRkT8HJRlE9rxUTcOl+bDrXFr5gCJo75Bdi2Pip8Pt9mP/hC/D7aqNLiDjrFRNwrjABj9SFgbEaykWprJmZe+2ElaE/j6cfSJJPIVWWFuP7UceLTcCxKMPxbbZlFMgAyACom+kMgLTFn+AAOHjiDVEA2GlQHgZO6QVftQ8Ln1uHoMREHAzUYP28DxkAKTMgDgB6PF5cfP1DivzXL/4Exw7Ux1rUHvYMgKqwbfgZMgBSJmzypGmirTd5BBjuCQMgAyADoFYCxO2FmMzpXYOqAdQC4ODrC9G+bxsc3XIKWz4Jvf2r/TAAOqMBFHIdOn4qOuYX4si+bdi49HPWABotBAZA/XrUqHFZA8gaQKNlZOrvDIAMgAyAyQ+Abq8bF/3XMHhSPNg4YxdObJe/U8sA6BwAdi4YgMFjr4KvthrzPnwRwYC/fqKxCVjy60N2k1f2K8XOjV9ZtTJDu+Y7NgGb4oqGTtxEv70buluNX366xAdQKtyG9gt0vHziFJG6NiYuFFLHhjqTyP6JkgLpean+o/pK6L6hlB4T54S0r5TyzaSx3hZpLRHFCR/A7l8sRFGECbh9n9YYckMf+H0BLHxuLfy1gRgawGpsmDcDbX5qwwfQ4pNqdnz4RGcs+fGpUqjPm42AX3b5JXY4lpAP4IGQD2CgPq83JQ0X3/Ag3G4P1sz/ACePlEhlHjYB/+/OEbSn4KRMRAsXIx90Tcw7WSKHY/kltL+f6L+O/2QEaD28C9k/UyP3z//6KM6Xn3F48zCzbyVG2hYvAKeGgQGQCh2JcTGEAZB+R0M2slbXDf0CCbUGh7cwAwAceE1PdC5qhxO7zmLDdI0/WkSTgwEGQKcAUIh1xCU3Iq9TDxzctRFbVs5mAAxLIJHNvQyA1E2sydI5vHs2WT+avGIGQAZAq5OQNYBWJSfyObyFxQFAl9uFi74/DCnpXmz5fC+ObDwZs+EMgM5pAIWQxYsgA0ddhpqqSsyf8RJkmi/WAIamI/XGc4Nf+GAAtLOxNUpeh3fPRmlzQlbCAMgAaHViMgBalVzjAmCbHjkYfls/5dbvwufXofa8jwFQIwEnTMDbylvD548+mlIzsjH+uoeV2tbMeQtnTxzUyd7jCmJAzlmwCVgyLW29wKEvjxTyhQHQzsbWKHkZAB0Sc3p26+DVD0fHAZQf7DQ/LmpevUmNWD7xSTJ5PELitGkiv0BynELN2JNBjGjHtOV3ZyeEDHlsowVgdCu2LjVx+OVLy1ZmXZHEobC0yhUfwC8XoWji9UoYkn6X90D+8I44s78Ma96OfvtXW4G4BOKED6CpeHpqI+z48IkioiBO+OKR3OJCiZS8PcpxYL/QALpNyd3j8uOSUweQGiNudpsLHkRKmx6o3LsI5Vs/k5Zd4wP+WDICtX5N7EXq5QNZqQ767dnRujU3f78Q/xlfAiG9IKKMi3GA5xjJdHnZBzA00Z3djU0t9+RKzAAoGU8GQL1QqCuOAZC0QTQmAI57eBjSW6Vix5x9OLD6WNz2MQCaB0Dl9ZNOZTiyPwMBnx4eB3Yvxog+41B+vgwfLnlDlX89FLjcQXQpOI+PPy2Ez6ehSAZA/Xwlgb2wthNu98r5jAGQtIs1XSLqcdR0LTRXcx8ArwNoB6AUwD0A9A9IAlMA/AGA2CU2qunKAGQBmAsgXa32CIAHAcivnUW0jQGQAVArAdYAyhavs1tOYwFgm26tMequQUqHFr+wDlVl+ufhInvLAGgNAONpD7PTc3DTiG8oYv543XScqhA+mBEA6AqiR0E5PpreiwFQs/TsaB4ZAM1BSHNK7exu3PQ9F/Amfhq+BuAmAD8BMErTrGwAuwFMBCDsOM8DOA/gUWHBUCHwnJrnfwBcDGCaUddkACg9/qQnFtFsS8grPxCJ5UtNh7QpQjWfUtPJ3vily9MYRunmTmdvLdvqgzyz7lvaiIlsmpT0jJI6iZmJyYzWW/3fHS+wrmhhAu4xcxGKJlyPvpN6ouCCLig7WoGVr8l+U0a3WAHA+fbDwCim1IiQKBS56Ey4IhNR2yMS2jHjWskbbprI2101H/s1PoDhfk8bdjPaZuVh3YHVWLt/ZZQ4XCoAznhfAKA583NdQTZu1WrHxnnokoy+g+ZpZZoQy5Obo6VqVh2K6uQkv7Wi66y0bRbzfv63R1FVfrbhNg/KQk2ANMkkgA4AdgFoC0B4Z4u+CQ3eePX7sLhvBnAvgMnqFwMBzBIXzTTjIfL/CkAxgOuMxooBkDaVGAD1M4ksEwZAY7I3Wqgm/h4JgOMeGo6svAzsXnAQJUsOG5bCAEjXAJoBwGHdRqK4+0icqTyNGWvfYwAkAhsV7KjpGAANt4BmkYB2ajeLrmAEgLcA9Ito7goAj6lm3fDXPwLQF8AD6heZAITGL00FR/H1HACDAZwAcCWAQ0YiYACkTSUy7BBte/TyokeQNYBCHqwBjLeuwwA45obbMe7B4UrSZa9sRMVJYTCI/2EAbBgAbJOZh+uKxW94YPqat1F2Xnj6hD6sAYw9J6lgR03HAGi0AzSPv9NO7ebRFycBUPRY2BB+DqAzgFD8gejPDwGIf8rHm5bRdeoPnjOUFPV2r9waKxuu6O/YBBxjCHSsQ5z61MsYRGCVtY4MsfLMum+JPWMANFitYQC89qffR59LeqDydBWW/n2D4RoXCRgAGwYAhWxvGnE7WqXnYFXJMmw8tI4BkDAjqWBHTccASBB6M0hCPysSvzNOm4BFjzsBEOH+Wxl1X9EAPhQdBkZ6x9oGUNAuFUh81qSjnDh+geSwLUTIIgGVtPvE5UAdQyKwSZNZDOUSc57aaTMFMYmiM1pH4b+TNbRy4VGriZsuBICLce9rTyC3SzZKlh3G7vn6+HOyQpRA0PM/oj0FJ/FjCvnSnVPDqcSIi6JUrM9sxQ8vsg928kfm9UvDwMR2Rgz5AFbgwL4s+AMSHz4166iCsSjKH4YT547h0/UfRgNgz3JIfQCpplLpYNIcKGkhT/QVNDx0yad549SreR6P6LNn9Yk3+YpQnBujhMA+gCFxOLxtO7Lv2ilkvnoBJHwJRJh/R2oKFECz4AsAACAASURBVDAnLoFMiLgEUgXgERX4qgGEX3j/AYBbAIwzahQDoF5CJBCLMQvlsEubrqR6GQBtLH7ajwejNRPv74kCgEVrNuM7//6F0tSVb2xG2eEKUrcYALPRUADYoVUnXDM05Jb97oo3UVkTGhPFBMwASL7wwwDIl0BoJyppy0uIRML/T8BfHgAR1uVbapiXpwAIz+0X1VZOBfCMsNwC2ATgbjVszGgAL6nhYYRsBCiKm8B7jXrHAMgAaDRH1FOKlow1gCQ5SRM5tKsJDeB1GS5c8vB1qD5Xg0V/rTc3GjWOAbDhAFDI/tbR30RmahaW7V6IrUdCt7IZANVZSVNYNsKNX9Ee1gAa7RVN+XeHtsqm7EJi1M0AyABImolUMzYDIEmcDQ2Aj0wajG7DCnFwzTFsn7WP3CYGwIYFwAt6X4T+nQfh8NmDmLnpUwbAyJnJAKhfp2wCbsitkrwvJm1CAYBXPSSUivUfms+e8tNVJxe5254sHeUmZzL7BcqmFEGeVBAjppOvLkI7QqoLy+uCPMes1kCdm+TyiX0lJiNXayFhtteN3zx4NdweN9a8sxWnS4RRgfYRl0A2Ch/Ax3rBlRbPh09enlN+eGafYxOt0dYt5wn5t4Z+fLLuqkUpeQtUH0CDZ+S6tM7HlUVTEAgG8M7y11Htq67XAP6npy4OoNz1jEhKkjaTzKfUmIJyhzddrU0VV5Ber+ypNm03KLECJU/IiWKo8pT5e2qq/fwFjgOoHD207YxTGUmAAZA2lUj+eTFmJh12COBFhC5ye6UcSmgHA6B8adGmk9GytPX3sf264o7JI1Bb5cOC59YgGKADAwNgjIscDgGg2+XGbWPuRpo3DQt3zMOu49sZAOPMdhKwxoQsGrTR3vSllSWHTglgSueTcR0MgCHBJcA2a2uPTpjMDIC0qUQGKuolDeINZ10yBkDa2mnBGsD7rxmJwYVdcHjjcWz5zNANOEqeDIANC4BC2BP6XoreHfpi/6m9+GrrTAZABsCQBFgDSNvbGQDJcjJMyADIAKibJFR4IsKoVMnotK+gthJqHwxXSDgBbZ409U/TVK8Hv7t/MlJTPFj3/lac3EU3/ypnEJuA5aFcHNIAimJ65PXEpQOuhC/gw9vLXoM/WBu6BcwmYJ2UWQMYLRLWALIGkHxkURLKAFB6YBMPe6sBo22ZSWVnM7W9jfCOMD1eoByVIr+l+lhKx56qnZRPAD0nUiaYSEMciyYBRaf7SpUJOR0RPNXyhhZ2xn1TRsFXXYv5f1oJBM358SkA+HXi+AA2uB+fKrcoH0ADPz7t0IV9APfvywLFd9Hr9uIbY+6B1+PF3K2zsP/0bgUAP5QAoFQrJJk7dH83WWbNjVfp3DQ2Tyo/IIh+gVKeJsY8JAdzllcigcw4dB/+k7T7NJnITcw0twwtAH/xwo/5LWDWAJJPD8OEDIAyKqIduk1hFmYAbITV77j20HAZxklAm4vhAu66cjhGDcjHriWbsPurs/B4U0xVzgCYFSMOYGwxmgVAUZLQAApN4O7jO7Fw5xwGQMUCSoMiBkCOA2huVzS1BbasxAyADICkGW8HilgDSBKxPBF9q/O4XfjtA5ORmZaCL599B66qfAZAouQbUwMomiR8AIUvYI2vGu+seA3dCspYA8gAKNFORkMxawBDIqLvisQNoKUmUwDwwd9Hd594YFM1YCSzsJTDqMNMDBdD7VdCm4VpMqGOjWze28lLDg0kr9ixZUh3KXCsytgFEeedVCQmmte/e3t894YL4Q8E8NLNT6D3sCssAGA1Nn79sS4MDFE3o4Ri6d6jXHkKrv5FDVpuS6FYIuSjy0+rVinBihYvXHVd3pIsBCRPwcmakepJxe1j74G4FTxr86dIabMVH75XoAsDIxt+sqZMkpmWl2baTFpzL1VuxOfhaDKnaUAZABkATRwJxkkZAPUyavDn3GL8hKFBCwOg8awWvxClDo+UrM6naSQAvHXSUIwfXIDt+47js+88g0EXXccASBzNxgZAYcYU8QC7tumG7Uc343DgcwZAOe3qtWIyP0NqXiK0aYuTQhyxLAZA4iI0kYx2CpoosKUmZQBkANRKgDWADu8GjQCAbpcLT3/nSrTKTMN7s9fi4LP/ZgBMYA2gAEDxIsiFhRNwvqYSy07+DR++14M1gHryYgCMkABrAFkD6OjpxADIAMgA6OiSkkwo679XqTn75LfDf900DoFgEL984TPkzZjPAJjgAJiRmolvjBHPuQNrTr6F1/6VwgDIABh3M2IAZAB09LQSADhZ4wNIvWlqx8ym1zLRTHZ07VRj+AXKhkJWL/UYl7EDIS9Rw0QdV+kEsxNCRiomiZyoM5vYX2pxOgCmuhgThsZqG8zmu+WSIZgwrBd2HjyJ596aj97zlmHghZfD4/WaKioYqMWmRXOQ+2hPwOJTcN17qM+iSfzh4jXG7aI/qSYrxxEzLjGUi6g/zJei3h4FFdhfIm4Qm5sUU4Zejw45nXCgfBWeeWWPHgCpEEt9bkwmOMLlC6oZU168rBM2/AyJfZB3iyZQXX8dNvfKo+XIZKK5BPLiTzgMDF8CMbWnx03MAEjbsOmwywBImp1NdKuY0jbpWNNYn1K842nEjHv6/snIzUrHf+ZtwKK1OzCtchWKhtPmtrZBm9YGsX98NwS95mIIinLsXORoiQBY1HUYRve6AOd9pfjx8zMZADWTUXrRhAHQ2sJ2fOdpugJbvACcEj0DIG0qMQBKtJNUTRlrAC0tV48rAPHP6NOzSx6+f/MlSrIn//EZKs5X4KrJe3DoQCaCAdr8Dtfh9gTQuXsVDh5rRX8RI6KBDIDm5N0qPQc3j7pDkeDv/z0LJUc0L7fQFFbSZ8SoWSnBplkDKKVO3ZdkOZEDS7MGMIF/exttzYn/dwZA2obNAMgAqJMAbepY2gQE+P13r7XI8voM82cPmILMnuNQe2Yfzix9UUnv87gwJzsffrgN80cmsANwrAE0bwIWMrtu+C1om5WHL5ZtxseLtkaPF5Xi2AQsgTEatElTaeXJJmBT+0hDJ27Arbehm55Y5SsA+MD/RjeKap6TpqP58mnjxckHlFaW436BxBAi9qDQ4u8aqi+e3OGPNPno8pQUR20fqSW0Z+TIm0ED+w7G6hLZpBxRQKrbh8f6rsbm0jbwB+P3cPy0B5CelYMda+Zh/7ZV8HoCGNjqLGbl5qMWEWZcAkyE/egO7DP/IkYdABaoPoAN/KSaVt5WfAClfnwy38U4fnKKD2DPSks+gKIPxT1Gorj7KBw+WYpf/3O24coga5mIz7LpzKyEeRJqpD4h2e+OrAGjQRy5XklxtBAvkr7KyVH/LbmvxnV8yT6AinzJe77hamrhCRgAiSBGBRsieMlZhDCtHW6HtPd2QInaPuq6I7SFILVQbYSyqM0yk84OAG442xaBOFq83LzOGHPl7UpzFnz0MqoqyuBx+zE45wwDIGGQEgEA87LbYlrxrUprH3/lSxw/Ux635QyANsCTAZCwKhI/CXnPT/yuNG0LGQAZALUSYA2gs2uyIQGw77AJKBg4CqWnjmL5zH8rDWcAzEKAqH1MBAB0uYK4beztyPC2xodfb8SsFdsZAMMSIJtepeo40kJmDSBJTAmViAHQoeGQAqBcLaT7Vq7sktyCpZhUqWZnSlmKsoc6RWS3dpMUConjSuy9PY2a05pCPcXS5quddUSeY+YrSXX78dO+q7HeQAN40dT7kJmdix1rF2Dv1pVKRd6wBjBHYwImNMOKGTWyWDv5jZ5UM2q+Nr+cHeT2TTtm3Pq8mRHP3xm1tv7vAgAnDRuF7tmjUHLkNH7/5ld1f6RbY2kprT/fZkPrRjaB0iCu4c29oh3RjSbPJXJfjc29ijQ0nf3ypcc4DAybgOmbi1FKBkAGQKM5Iv5OhX1KWUoaBsC4oqIAYE6bDrjgqm8q5Sz8+B+oLD/LAKjG4xNv8pIPbTV8jVU/PicAcEi/HIxof6cyfr946TOcKq0Mnf/UBUWI5RcqT0oohFoYAHVCksmcAZAwl+wnoap37NeU5CUwADIAUqY4A6BESk2sAewzdDx6DRqDsjPHsfSLN+sayBrALDQ3ACzoVYGh2Q+jbU4WPpy/oc4MzABoAzwlS5Zm7mUNIOVMaMo0DIAOSZ8BkAGQMpUYABMPAMdf+21ktWqDnesXYc/m5QyA7tBLIuJFjuYIgP7D1+Kykf2x/9gZ/O71OawBjCEBNgGfbfH80+IFQDm0KWkEAF55/++iklL956TpiFoRnWO8bETZL1A3hNSxkY491exKvMksq6MxQFFbr5VLFnHXBnkOU1aYtTSKCbjfmpg+gNmt22Hc1aF3ZBd9+k9UlJ12FgBViDLbejt+fK7IJ9XiPSMXw9zZVH58TpiAhQZw5fxh+PHtlysi/9XLX6i3gWkmW+umXf0IN/gtY72CTW1EYmj7pM2zY+6VLSJZ3EaCGZ99AEPCZAA0uzPHSM8ASMMYctiWBoYsBkD9eLVEACwcMg69i8bi3NmTWPL561FCccQEzABI3mGdAsDp73bH49+6Bu1bZ+OjBRvxxbJtci9Asp8ZuQtRCRkAJb6XDIDWJlMD5WIAdEiwDIAMgDoJsAaQtLoachMy0gBedO29yGzVWmf+FQ1nADT/IocdiLOTV9FmuIIQGkABgFMuGIrJY/vj4PGzePo1ERSaNYASHSVpfVr192MNIEm8TZqoIffeJu1YY1fOAMgAyACokUCCm4Bz2nbEBZNDN0YXfvIPVJ4L3f4NfxgAmy8Adm7TFj+/J2QGFkGhj53WvA0spRM7t3sleEUwRYZyOQ2nbAI2Ov/ZBBySEAOg0Uwh/l0GgFIkoh6KsnSEvORn1ZLZL5DEojYurZDKF4uLuLwSSVOo7Ru5C8SExPVkK1nE3E6L4wPYr3giCgaMVII/L1ODP8sAcKbFOIA91IsU/nh+eMr5rz+wnfHDMw9wojl2NHGNn7dediENYCWmv9MNvlo3nvrOVejQthU+WbQJny3eoptS9vz9KJBFAzvZXKe3jdKOGJApqdhRbZ9sblPN7lKhyPpKu9+t7dfMv/+U4wAyANo6ZqIyMwBSAcAGeFH9AkmAZqMdpPIZAJ1bXSZLkgDgltJc3VvA4657GOmZrbBz7Tzs37pCV4nXHcSAnFIwANLln0gAOPWiIlx94UDlbeCn/jGTAZAwjAyABCElURLqqZ1EXW6YrjAAUqeSDfBiANRNXsdvCyeZBjDF48OjvdYi1RvdsZQ2PdDmggeVL0/O/T0CVdHm33DqGj8wt20+fEGPqY1DASHWAJqXWc9K7C8x8xJIbA1g1/a5+OW3r1Ta8NQ/vsThk9FmYLqWTa6j036rV+SyBlCn3WYNoKk10dCJqad2Q7ej2ZevAOB3fhvdD6kZV99VqqnQargY8o1Xp83CxOfmZJ4IBGt3SJDEhKRwOUSTLVmeslntKMQqArC8dnQ5ibK0XKGJ5lLXhFFbvN4Arpu2B4f2pCMYrO/x6H4T0b/bUBw/exhfrnpfWoyAuC49q3HgSCv4/ebkbMeEKxpjJ78dLVx03WZALCRCO3WH8+4ryURAJm8Da59iAu5difffyVdMwOLzxH1XoXNeDj5dvBmfLNxkNF2kf7d8m9dh2JFiqPyZFn1SaluI5Zl5HSayMWRZWgzvIuqigD2bgNXj09KK4Ew6CTAAEsGW6O9GZhFiQgZA2fhoviPK0tbyJ3KUkwB4/S0lKNmTVQeAouzbxtyFjNRMLNu9CFsOb4wJgPafNbPrh2c+vx0IcwrizGnxouHRSQC8dvwgTBlXhKOnyvD4y19YmrpkaNFe5qBCF53sdCnJwZypbWEAtDRHmmsm4nbcXLvXeO1mAGQAJM021gASxeTM1iQ0gFoA7NK6KyYPngpxsL+z/A2crw29F6v9OKOFMw9w0RBmPj8DYL0GsHO7HDxx71XK0P761ZlKWBizHwZAyeULi9BKliVrAM1OU0vpndllLVWdXJkYABkASTOaAZAoJme2JhkAjiuciH6dB+Lw2UP4cuPHMdvDANj8TcBicH/17ckQ/oBfLN2CGV/Ltb3xJiUZWlgDaLi2ybJkADSUpRMJnNllnWhJMy9DAOAVGh9AsoM+FQooPnpEMx7Zj41SpzJ20k7oRpUcpkZSHrFrpLaQTYy2TNY2lhd1TsjWDbla44TGKdQG0AenUVe6AMAbbt1XZwJ2u9z4xpi7kZaSjsU7v8b2o/rwIOEG2tGk2ckbrQFsXAhzqu6YZlyp5ij0pSKzXuexb28GAv6QD1/kxyjgh/AB7Cl8AN+u1wCK/OIm8LQJg3GytAK/eOHTCEyzEULFqDFEX7RQ/wiFyaMFNU4MQemYUdtMSCeDPWKdFH+/kIij2zHz5Z9xGBhbHuSNuo0nfmUMgAyA+llKxidSVnvQao0UyT1oJgCY36Y7rii6BoFgAG8vex3VvqqYm4sdiLOT1ykIs+KH51TdiQSA7XKz8JuHpijj/My/vsLugyfVMWcA1E9+58y9Ie5iAExkeiHv74nciURoGwMgAyCJ4qiTlTWAVEnFTafVAE7oNwmFHfri4On9mLX5s7h57UCcnbxOQVhLBMAe3Srw4btd4FdvAYcH+JG7L0fvbu2xYPVOvP3FSikABl0uBNx6zSP1pQ7tZCJrp1gDqFuH1FvGZBmzBlC61zEAOnLMAAyADIAMgA4tJgeLiQRAjysF3xh7D1I8Kfh6+1fYfXwHA6BEAnbg1TCUi0zi6mlv1wQMvx+Vfz2I2jK/rpYhUy7AZf91I6rKKvHSN56Ev1afJpCagp1jByPo0UKgtXh+ZDhhAGQAdHDPM1NUsgFgHwCvA2gHoBTAPQA2SwQi7AF/ACCiuwqvYJFORAntAuCfAAoAVAPYCUBEiz1hJNQQAP5Gk0wv3ob2CySXL+kQ2T8vgfwCZeMit0ZqJEOc+WSZEOPxkdpmNNki/25HU6ith+jvaKZ5pCrog2i66kgA7NW+Hyb2m4Rafy3eXvYafAEfA2AcAAyZcWUaMZFJA0VEiIvDf4oPYIHqA+iPWW+cIavxo/SZfeg/9grAlRKVMCUzBZMeuRBujxur396IY9vCZuBQsoDfhx0rZmLHRcMQ8GqCflNDqGibRg2pQrCShoqmgagd8KRq3uRNIXSkCfz9ZJKbxT6AyowiHoOm992myjAXwBsAXgNwE4CfABilaUw2gN0AJgLYBuB5AOcBPAqgIwABkYvUPM8CaK8CYtw+MQBKT3H9l1RgsQEjJMgiznwGQKKgiCueXJpDPoWRAHj5oCkQPoC7ju/Agu1fGbbYCU1YU5ph7dbdXAFw4Pir4XKl6sa3+NYB6NA3D0e3nMT66WLrr//4fbXYtvQzBkApodsATx0UW/cxJIMtATIZAEMDQ96PDXfLpk/QAcAuAG0BiJ/2om9HAIxXvw+38GYA9wKYrH4xEMAsAPmSLgiI/B6Ai426xwDIAGg0R5QFZwNspeVTgZrUOOIYUsqKkYa84TgMgMcOtMcto++CuAU8c9OnOHTmgGEvGACbnwbw3B/3YcAFl8DljtYACo1Vx4EdMfTGofD7/Pj6/30NX3W9BjgQ8GHbsrnYdiFrAHULQ3aRw7JWlAHQcONpxATk/bgR22S1qhEA3gLQL6IA8cL7YwCEZjD8+RGAvgAeUL/IBHAOQJoKjuF0wg4g1AQfAfiTUaMYAInwQAUWG6BEgizizGcNIFFQRgtE/Tu5NIcBMKvqQozuNQ6VNZV4d/kb8ueiNH1gAGxeAOgK+FCw+DCKimPMMrcX7Sb9HO6UdJRtmI6qg6uiRnzTmiD+4y6C38Um4CjBMAASd7fml4y8HzeDrjkJgEIuLwIQWsUbhYuIpP8/BCD+KR9vanrXqx/+Y3QyIsTQY/LpW6F/4syG36Gkk2QActgvUIqTZCiQyIA006V0qmuKvXAspIY4rykk8Dm5X4SyYu8XtP47td94UwK48db9GJJzD/Ky22PTofVYsWcJqXgnADC+GTV2M6IvU8Tyw5Pnl+cl+GeJ4oLG8fhktYZLt+PHZ5w3fh+UfnepxKG9qQgE5PNs3MDLUdh1EI6cPoBZq6fXdcXtDqJrzxq8Pz06hmBIJDQTKCWeH/npNomQSSFV1DHUZ7euebPs76e0Jbpeqo8hXeaSnkqFHF3zrJd/znEA2QSsTB6ZCfgvAHoDuA5ADeW0UDSA92kugTAASpFSQlQUEYMMypaDSDMAkgaimQHgXXdUYnSHbymt/mjtf3CqPPoCQKw+MwDKAzInMgAW9KpCyZ6MmADYuXU+rh4yTYlPJzTBFdXlSndcbhFE+jz+8+8u8GlCyNBhxBiyGQClZKv7ki5zBkDLe3aSAaCQw3z1Akj4Eogw/47UCKiVeglkQsQlEBEN9hE13XPqRRABf+ImMOnDAEjUPBJfDJEyBmsASXORnEgzZMmqAXz0vh7o0WoszlaewQer3yGLhwEw+QBQzPFbx9yFrLRsRRO88cBaBsDIFeGkuVeUyxpA8n7TFAkb1x7T8D0U/n8C/vLUsC7iZ78I8/IUgMOqWVe0YqoICi8stwA2AbhbDRszTr0BLK6IheFvL4DrjZouAPDy+56OSkY2n0o1VsShoRziVPMsEbDo/dJLjazFc7wtxvIk+Q4q6gKj2RD6OxmoiJpiORRLv6U10Goqqh+n1fJj5SPKPTJ7SkoAz37/aqR7c7CqZBk2HFhDblUIAM9jXwkdhMKF28krypDmN1YwKdUbxdOLJwBRhbEpNnYJ1vKGOhbKW6U8Bef3mx/scP6SPelxwtcAo3pdiCHdinG6/FTdDwKhAezV+zze+3dnnQZQHqaP+oqIVlY0c7JUAyYTO+WlDeqLHAqw6Sux0xZdcdIbujSZyLsvWxTG5c16hU3AJo4y8p7ZYhMyANKGngFQIicGQOLkoSWLTDWgZzv84OZLla/eW/EmyqvFfS/axw7E2cnLANiwANg2Kw/Xj7xNmQQfrn5XcQlgAFTXBAMgbXNIklTmf2YlSced7gYDIE2iDIAMgLSZQpVT/NK+fe1ojB5QgCOlh/DFBnGhn/6xA3F28jIANiwACvlOG34L2rVqj82HNmDproUMgOFlwQBI3yCSICUDoEODyABIEyQDIBVsaEuTbLamDQ8tVTMxAaenpuCZ712LVK8XC3bMwa5j8Z9+03beDsTZycsA2PAAOLDLYFzQZwKqaqvw9tLXEHD52AQsJh4DIG0PTJJUtFMmSTrbkN1QAPDeaB9A+X0H2k1TmaMZCZ6oh3MC+QXKYp7IJyZNdtZ9FK2GjxEzi9Y22RxsDF9Bab26JjfRdmCj2niyGz+0F+6cPBK+QDXeWvoafH79+6/x9gQ7vnR28iqzycazaNb88OolYS2/fT++eh++GLd4DXwg3Z6QD6HwATR6Si7Nm4bbL/gWPG4PvtoyEyWndoYA8F+d9D6Akkli+TYvFbDk8VJ0LaGGVZHOc2pbZJkJr20o2XSXQIz982KtSXkYHFp5Wj/G2a/8gsPA0N3ZGxKdkqNsBkDrAMQASCQgG76CLREAf/zNSejVJQ+HKtZj1ppFCAaJclaFZQfi7ORlAGx4ABQyvnTAlejVoRAHTu/DrM2fMADGinnIAJgckEI1PiVtbxuwYwyADIC66UXkDdYAWl+YsWTXuV0OHr839Nrj6hP/woZtpQyARDG3BA2gEIV4F3rykGtDMQFXvI6O3U6wBlB+5Vk/c1gDSFxNiZ2MeEQldicSoXUMgAyADIAWV6KNXSgWAN54yVBcProfjpwsxbaav6NkdyYDIHF4WgoAirlz29hQTMBVJUtxLnURAyADIHGVJEcyG1tvcgjAqV6EAPDXmuJoUET3WZP5qBGGkOoXKFMRy24ZOB6jT1oxkadoMtYWZkfmNHNqrJllrb2KWZAagFDaQPKXhkuCOPxN5mHidrvw++9ORU5WOj6YvxZt+s7BXosAWNDrvBqXzvxzbFbzigGwBmGhoaPnlTvV2YnHZ8ePL9KHL+DXy9soDKLI3zOmD6A898iCsRjWYyRKz5/FmjMv4903aT6AMW5LRK0devw82ZKz8XQbrTjSe9hKUTJtHzX+oBYojQZRbbuT/n6hPkQLZfY/2AcwdKbwxxEJMADqxUiHLAZAyiRkAKRICRjapysevnE8/P4Afv73j3DltF0MgFLRMQDmpOfiljHfVKSz5uRb+Ps//KRLIAyANJLTQTAtm2KW13+sXfhgAIy9bzIA0s4Uw1QMgAyAhpNEScAaQJqcrKcS8CcgcO2Og3jlk4W46RsHGQAZAGNOqGuGXo/OrbviSOUmPPmXtQyAWkmxBtD6ZpTgORkAHRqg9KzWwcs0JmByjDaqiZZwC5QUKiYmh9CmA70Oh8uTKgppdejAy5bMZZOG1g5b5lNaFdIZTdIekssnJyStLrpMjItr3SoDv33oWnjcbvz1/YXYsu9gMwBAvWajQc2wBmI0NOPK8qtdsGPGjW/CjdXoetmF8lerYWA0czSO5qmwYz9cPOBy+IO1ePS56Sg75zOeaJQQKsRQLlJxEk2stvIS65Br42T6OZqGTs+XDavtC9UXXcfsf/ySw8CwCdh4nVNTMABK6YwkPjJQMgCS5CnHUwK0EZKEyiYnJLXXSQC8dnwRpowvwumySvz8hU/h9voZAEmjUJ+opQGgiAUoYgKmpaTjva9WYtbS7cYSYwDUyUjq80gw+Ta0uZcBMPZ0dnYnN142SZuCAZABkDK56bBj3VTcUgFQXP743UNTIbSAHy/ciM8Wb4E3JcAASJmYEWlaGgCKro8tHIei/GIcPVWKX7zwibHEGAAZAI1nScKnYAB0aIgYABkAKVOJAVAvJbpM4ku4uG8+HrxhPPyBAH76t09QWl7FABgwv8W3RABsnZWLm0aFLoM8++ZsbN93LP5kYwBkAKRs+AmexvzukOAdaqrmpWfl6nwALT/nJjph2UfNYqgYM3VKVUySeonpNzjwxwAAIABJREFUyBor6mwlPXNnXcNm63Yz0XxKhyKiUIjJtGNB8h2Mtegs1hkqznzm/77tYgzs2Qmrtx3ASx8uVkoRGsCbbz+EvbszLMUBDD0tFuNlijibjSWIsquFU/PX152OQCBO+JoY5jkjPz5RTSzLnjU/vlDDo/MSxz+iIUr+3tUo2S2egiPmV2Xmcgdxw5ipaJPWAys3l+ClDxbVjYb1cC4JHspFNn+pfoHyR4MNj9/GMffqm6Gtd47wAaw4a26SGPau+SVo8QJwasgYABkAaXOJtuQYAGlyCsu8Q5tsPP3gFOX//untedhaEtLgMAAyAFLWpQDAMUXdUdR2Gnz+AH78fx+grKJKycoAKAEqBkDKtEr4NOZ22YTvTtM1kAGQAZA2+2hLjgGQJqewzG+6dBiuGNMfx06X4VcvfV53PDEAMgBS1qUAwN6FNSjOeQi52Zn4YO5afL54MwNgDOEl9oUP1gBS5rxIY26XpZbaAtMxADIA0qY9bckxANLkJGSe4vXg99+biuyMNLw3Zy3mrKy/xckAyABIWZcCAHsVVuH83itx9bghOHW2HI89/5ESkJg1gKwBpMyh5piGvss2x941YpsVAPy25ik4qXQb2EevKeqMJWeSL574GUKbhvZ876IbSQ89k9i+gjLRE8VJ+/1HGxrpDLDlP2hi7Y4tKsC3p16AWp8fP/7LDFScr6nLrQDgHYdt+gAa+NJJ2hrTD48QFkMUR/HDiyUiat5E8+Oz48MXllnIBzANfslTcvGmVBgAZ8/oiacfuhFulwvPvTMP63cejOHwaDyQ1Ph50nZRLpnE6pAscLMsbQP7+4kq9TKgxQq0qmGU16l8GyWBkA9gqY3dzcQGlcBJW7wAnBobBkCJJBkA9UIhrzhyQl0dLQ0Af3rPFejZJQ9LNuzFa58ui5IHA2BsDSADYP1UCQPgu290wIM3XIphfbthy54j+OO/5zAAWvT3YwB0ii4arhzrp0zDtalZlswAyAColYA9jaX1pdmSALB3fjv85K7LFdE//eqX2H/0DAOgJ4DQ7eV0BOJowhgA5QDYu2sXPPrN0Jz61Uuf4NCxs5LNjTWAlIOaNYAUKTVdGuunTNO1OSFrFgA46dtPRbWNDgDOmYVt1SmTLJEmyCZVqlbQTlusvrdrp21W61QMsdbNzPLFQFvWxKElrjdanU57HT9w/XiMHNAdOw8cxzNvztG1VWgAb7njCPaIMDCamHhGLaaaUmUCisxr1hwpynMunEocH0DpyAbVumM8qWYwG6KeY/MZSTi6sHoTsHkTbp3MbJqA3329PWpr3Xji/ino1qktFq7didc+WarrtfyVN2MolCvTCPlC6jTSWrTcNqnJNkaVVDOztsNU0zatqxITsyIofaM1X815lU3AQkjmVihp+rXMRAyAxKlkB7KIxGIZqOy0zQbEWW5vzKVGGwuiOIkLmlanlR3H5Q/AJTlw2uZm4Tffvw5utxsvvvc11m7bLwXAG75xDCUHMhkASSPJACgAcNzQ3vj2tHGKX+mjf56Oc5WhkDDhj2XIogKQbKwYAPUgLpUJAyBpqTMAUsVknI4BkAoAxNvCMpETicUyUDEAGk90m9BpFgAF/PVZvhmemlpdzRO+MwUjb74YpUdP49V7fodgQK42SMnxIOO7XYVaLaoMoxnLGkDzAZWTRQPo9bjxzA9uRG52BmbMX4dPFmxgAIwiYGKQa9YA2thTGz6r0R7Y8C1IkhoYAIlTyQ5kMQASVwttLIjidLROswDo9vnRb9F69Bl1Bdweb11bPKkeTPrRhUjJSMGWL3di75IDMdpZi+3LZiPnx92BFAZA48FkDaDQAIrP1AlDMO3iYSgtP48f/990JUA0awBVCbAJ2HgpNYMUtJOiGXSkqZuoAOC3on0ArT/nJnpj0S9Q6k5G9TEjaueo5EBti2Tw7PgUSpWHWnnamfl2INZpU7G8s8TlYEcI0VVQpwSxYXXJFABcvAH9xl4Njzel7vvuozpj4FWF8FX7MP/PK+Cr9kuLDgZqsHXJF1IANGpL0/nhxfIBpDlGRWnhTD6JJhQ2dsKxOJO3IXwA48sudAu4Gu+oPoBibuRkpePZH9yoxJl8ZcYiLFm/22jKRP+9Mcy9ZLOwsVk0Zueswp4oUFNtQ4d3UfpAkPtXr/6Kw8CwCdjceo6XmgFQRnH676ix4RgArcuOrmVrngAoYPOi745EZtsM7Ft+CFtn7ol9djEAmtvkGACVSyDhz7euvRAXFRdi/9HTeOKlT0zLUpuBHlSaBvvUWIN2wEt2+UTeOmPItNMOJ98RZgAMzUznTgBzSyPpUjMAMgDSJjVVG8sAKCQg0wB2HtQeQ2/sj0AgiIXPr8T5s9UMgBESYA2gTINoXgMoRJrfoTWeenCqIt0/vjkbm/ccpi1zoibKjNZNlpYB0Bg6Q0MRnY4BkAGQvpAJKRkAGQAJ00T+m4v4M4yqPaX/rCNWTOhYY5qAL7y/GDmdsnF4w3FsmFH/7Jv0gGQNIGH0IpK0YA1gQfcqvP9mXpQGUEjmB3dehsF9u2H73iN49tUvYjOb24WgOyLsDsEUyQAoN9nSYZcB0NwCj07t3AlgpxVJkDcEgE9qekLT9tBvrbZsv0DZk3HkCUwgFPo4ECdsE/kKylpHgkeyMOU1EKViKpnQAPZfsgH9xlwNT0oK2hW2wcjbi5QyFr24GuXHK+OWV+8D2E13CcSoIXY0aXbyinZJ89OsgrZ8+OrqthhPz04sP2t564USyl+Dkt2puqfg5GFbImZAIICqFw6jtkzvS9q1qCdu/X/fVRK//d9/wZEt+6RTx5+Sgq0j+kRDoDYl2WdPUgU5Lw2KpJ1w0N9PlK8z+RLnsJPmXqWfmnq/+if7AAqx2NryjTbQlvR3BkDiVLJxMYQB0PqKsguAXlcAHle83Tv++PuDLviCZoMSh0zAkQA4+p4haNs9F8d3nMKad7YYCoQBkLguIyRpDcRCBTR+XocAsNaPc384iL6jJgGu+stGYbFccN8I5BW0wbFtJ7DyX+t18y7g92HX6jnYPHoAAt7o2+ZRickQxwColwANbCl+hgyAIema3x0Mt9yWmYABkDiVGACJC4SmPSYWJn9tRJs5xhAK+PtJ0Q5kpchv2lLaUFHrwe839TMNgZEAmNcrD2O/NVSpbtmr63D24DnDqhkAieuSAVABwP5jr4TLnaqbV+37tMXIOwYr3y96YRXOHauISuP31WLHii8ZADWSYw2g4RbVpAnM7w5N2tzErZwBkDiVGACJkzhxADDN7cfjw7Zhw5kcCE2e2Y/QHA5pU4Yn1w1AdSCOdkRScCQAjrprGDr0aYvT+0qx4vXowLyx2sQAaH68Gl+LFxo9a/U6qwGMBYCifeMeHBHyPd14DOunb2MA1C46is8jm4DNbp8Nmt787tCgzWm+hQsAvPSeaB9AudsZ7WCn+6NFl0euUyJqx0OvEPzuYo04uS2yAii+d3baZiOWn7S/lPaaWhq0OUYpUsxDBQCLt2HtqVwEYgFgnJ3E7QqiuG0pnlzX3yIAbsToG27F+AdHKU1e9a9NOLn7DKX5CAbVOICPWvQBVHzhLL6IYTFvNAzZqbsh4unFF7sdiIvnwxcT8CP+IPL36l2DvcIH0GfS3UA1AcsAMKzF6jSoPYbfPEh5cWbBX1eg4tT5utqFBnDnipnRGkCqPx3RLCyTAfUWsK28xPbR2iJ5QcTQQVNtPQUwRVJCeV/983GOA8gmYNIZQkrEAKgXkx2Is5OX5CvIAEia14kCgHc+/xg69G2HswfKsOxVvQ9WTEBgACSNc2QiaxAXKsFa3tCJnegAKH73TfjuaGS3y8ShDcew/oOtDIARE4cB0PRSa/IMrAF0aAgYABkALU8l1gDGFJ0wAV9ytgzf+PP3lTQr39yIU3vOkkXNGkCTmjDLENcCABBA56IOKL5pIATsLPzbSpSfCN1CZw0gFJkYf1gDaCyjxkvBAOiQrEMA+ISmNFnYFlmFNJMdzSxso05J08iaOOlMkrRF2n3iNHTQf5BYI2TaROqUoY0XtbQY6RyFR/k8FCbgJ4q3Y82pnNgm4DjdECbg4XlleGJtP6kJON4NZQGAP592AXoM7xvy/XuNrv0TTQoB4JfIsWUCNm9KtaYJqxeinfx28jalFs+WCVeAq9esCTgCRhQT8CH0H3sFILkEUjcy4hWaB0eiVcdsHNl8Amvf21wPgCtnYvOo/nW3gOWWSAokScKnKJOZuFdQTc/yN9NIldBgT99oOSM6d7s31HhjyJz7GpuAhaTI5yBpVrTgRAyANLCVcyJxGjIA6oWc5ADYr2s7PPrtyUq/V7y+HqdLSk3tMgyAjaUBtG/GbRYACKBj/3YYcVsoFuVCcSP4aHlIA8gAKFmb0TDGAGhq+2rwxMSTt8Hb4VQFfQC8DqAdAHFS3AMg9BMt+jMFwB8AiCuJG9V0ZWqS9wFcKLT9ANoAINmbGAAZALUSYA1gSCJ2NICP3nkZ+vXshFN7zijmX7MfBkAGwNhzxoIGUC1s3P0jkNulFY5tO4nVb29iAIwpZAZAs3tWY6ZPNgCcC+ANAK8BuAnATwCErg7Wf7IB7AYwEYC4y/88AHGd61E1yWUARIyJYwyAwgJKnCJsAtatWwZAewA4pE9X/NdtlyiFLHllNcoORcdeo2yUDIAMgA0BgO0L22LUnUNCc/PlNThVcoo1gFJBMwBS9qmmSkM83Zuqeabq7QBgF4C2AHyqefsIgPHq9+HCbgZwL4CQXQkYCGCWePdbU5uYueY0gHdrfACpUERMJ48+oslMLMtOuBhSO4QwqW2RDTMVPCV5ydCqzWvHnGqnvU6HlbEoz1ibgeIDOHyHfR/ANXIfQFn33S4XnnxgCrq0b41dSzZh2xfH4PHqX2gw3CHEW8BL2QdQLie5U5md27hRZly/BD7j+LGZ9+GL7lV0fpNHW9gHcIyBD2BElWPvLVZepTmzvxSLXlqhAOCmkf3ivwQiGQi6P500s+5LuYid9rOTzShj3zupI6OD4V1Eqyhm5rmvPcFhYJLMB3AEgLcA9IuYmisAPAZAaAbDnx8B6AvgAfWLTADiSYE0FRzD6RgAY52uVF88BkBDPglxMu0SEKmwmGNmfCAmEgBOKO6Du6eMhd8fwBv3P4v2XUYyABInAP0SCANgnUgtAGDr/Bxc+J3hShGr3l6PBf98kwFQq0XRTTGnQZQCnQoWRrWMATAkDuNTgbjpJECyxgbAHwIQ/5SPNzW96xX3/S5aDFQAIqYjad6IZbEGUDJjWQMoXcaNrQFMS/Hid9+7DrnZGZi/chvW/PwV9B1zFQMgcZNlABSBoE0ebRYAUAzHsJsGosvgDqg4VYlX7noS64cWsgYwYp7qtXEMgMRl3CjJTK6SRmmT1UrYBBwT6SXhWIigKB0M1gDqxcIm4Jjrtu4SCNEEPHXCEEybOBRV1bX42f9NR/6cVQyAJnZFBsDGA8CM1umY8P3R8HjdmP/Sx3hj3zEGQAZAE6u1aZMmEwAKSc5XL4CEL4EI8+9IjYhbqZdAJkRcAqkC8IgmnSkTcJqIA3j341FF0E17NgBN5wJINSfShp7sT0eFQtl8J8KTnFlp/dBqT+PFnjNckk2kKZSKrhHMx0ID+OSInVhzUo0DSBR5uL31ANjX8Cm4tjlZePrhqUhLTcGH89bi83nrMGjlZvQbPRFuj9dwaEIJ6hsYDNZi27Kvkf1DO0/BNXQcQL1WxIofXp28PQH07F2DEvEkmswPT00Yyx1P58dHjT9nKRZf/ZDa8uGrq7tWfQrO5CRVNYD9xlwBly4OYHwB9L+iN3qN646qc5V49M/v41ytcEFvrFh+kiVBCshsr310v0WN7JrA308djChBzX2dfQBj6ouIu2wiJhP+fwL+8gCIsC7fUsO8PAXgMIAX1UZPBfCMsNwC2ATgbjVsjPjzZwCGAuiq5tkJ4GKjzjIASpRiVA8DBkCj6RXz7/QfGZarUN4CbiwAfOimiRg5sAdOnS3HL174GH5fNW5zbUfRcJMHekR3N60NYs+FnQGXiPpE/9A1afoyzeVlABQSbK4A6E334uIfjEFqZirmLd+K1z9bygBYtyQYAOk7TuOntL6rNn5bE7pGBkAGQNIEJcIuqaxGukDSWAA4qHcX/PAOEYUJeP7deVi7/QBSUgK45dZjOLgnBYEAXSrhlB5PEF171mLfoYy42jBZyeYgLroEc3kZAJszAIq2dy3ugKHXDUIgEMTTr3yKPQdPIGjjpQ3ZVVayIpY1gPrlrBEeawBDImIApJ4pBukUALwr2gRMurQRcxQsmoUbwxRrA2LsmJRl09WWWVg7pnZkJ5sfCWQqljZPbxeXznIdAJpcM4oJuF0ZHl/dJ6YJ2Otx46mHpqJTXi427jqEP731lVKLAMDb7j6B3bvSEAyY367C5kwjc2hsADQ2pZrJSz3EDcOphCuVFOhsOBVzcQTtaPFCeS2acCNNwLtSaLAfKTthAv7jIfQbc7nEBGzIE/D7azHqzv7o3L87Sg6fxBMvfkx8G1cet8ROKBfZfKSbbCV9JQJljPgrUQXSodja7V6lMoKZee7rT6K6otT8hmJy70v05C1eAE4NEAMgTZIMgDQ52XmDmFiDPvxMjN2gMQDwmvGDceOk4aj1+fHLFz7C8TPlDIC9a0L+bHH8+GSHHQNgEwCgrxZlZzbj9ud/ALfbjTc/XYI5y7fSlmJCvd3LAEgbtORIxQDo0DgyANIEyQBIk1NLAsD2bVop2j8R/uWTBRuUyx/h/rMGkAGQuGJUH8Ja7G0KDaCvFrtWzsKQJ+7BZRcWobKqBo/93/soLRePTBl8GAAlAmINoNG0ceLvDIBOSFFEkWYTMEmSDIAkMdUBEDG1pWS6CyRNoAEUVT5695XoX9AJJ86cwy//9hFqfH4GQI8wh7IG0MzErjMhNyEA7hpXhN/+8Ba0bpWJ1VtK8NzbIVeGuB8GQAZAoznSQH9nAHRIsCEA/JWmNFpIFvpNTqpfoLYZtGF2vh20esm+krKxIvoj6lpCzCedHonkK2hDJtSpL0zAT43chTUnWyEQFJ0njqtaQdgH8MkVvVDtj76Je/Ho/rjz2guVlM+++jm27z0a1SyhAbzprtPYuy/dmg+g4lemgpTPjj9b4+UVArBjxrWTV1431XMx3G5rfnymAU4zgcP59+xKQcDkWCPCBxDaMDCE7vuFBnDVLGwc0RfDh/bG92+bpLTuhffmYtmGPXUtJRQVSkv0u6P71MlWe8Nq2aT7C7VfUkE5F0R67hvsAyjGx9xOTj0xWmA6BkApidBmgh2gIoIcAyBtKGSp7ANgAMPbncO7f6tFbU19DTkd2+Cuvz+C1Iw0rP9kCb76ywfSRqbkeJD+UBfAbQ7CmhKknIcw+vg5XzcZW+rNsMJ30eRrHMkCgAGvBw/fcgnGDO6F8soq/Oy56XWmYLIkqaBk56axJC/lHd0QoOrnoxRGtcmo/WIApC94GykZAG0ILzIrAyADoOWpZOe2sFTszi5ruwDogR/F7cuxcsk4BJFe1+Ix9xSjfWEeKs+ex9fPLYO/xi85VWqxY+VXaPVIPpBiLo4fA6CAMCegmYwtDIAj+iovgbTKTMdvv38DcrIzQqbgt+bE4ib5tkEFJQZAnfwoWlHWAIbE5uxJYfkEbP4ZGQAZAC3P4hYCgKuWT4TLlaGIqWBsVwyYXKj875VvbsDJ3Wek4gsGarBt2UwGQBOTizWA1kzAFX8+hH6jLwJcmhdnCPwb9Puwa91CbBlW/xbw8AEFePDWy5WRe3X6PCzbsFOGa6GDOBhA0BUB6yYA0B8AfMHIvNTJwiZgqqSSNR0DoEMjKwDwkm/+Mqo0+YWHhvULJFpEyZcM7PgFypVTNqYc1VQsDw5oONKOxhSM8fPK1hN0RG2fZQnHmDx6DaChKKMSuBHA8PblWLV8AuDKQE7nbFx433C4PW7sW3kImz8Tj+1Ef8JyYgA00uJJgkg7FU+vkc24tnz4wn6ThbWQ+QAamSfdQT96LTuOomLLqwe+2iC8KdH5c4bdhvQuQxHwVePM4ufhrzgpXTyBIOC2WHV5rRu/XtEtGgI1tdDjANrws5P1jACyjpudCebjuW88xXEAWQNo7iCLl5oBkLZ7kW8BExWKTgIqA6B8DJ0EQE9aNsY/MAJZeZk4d6wci19eg4BP/8QHAyD18goDYHirUADSIgB6vAH0zK/BwT0e+ENP+cb/aMSe4g7g4uozSNUoD13edLQd/314MtuitvQwziz9GxCQuDoA2HAqA7VqzEeC0lFpn8cVRHH7SvxsaQ9Ux3v3mQBioQ4zABoNfTL9nXZqJ1OPG6gvDIC0qcQASJMTeZo6aT5uBA3gkOuLkT+sE/y1fiz++2qUn6iUdpUBkAGQvAbUhHYBsFehT9Eeki6vaDhJAcjuNTi4Sw+Q7XI74Zqx34Db7cGWkjVYvnVuVNdSXQFcHjiDNSez4PeH9gcqAIob9iM7VDAARkqUNYDkpePwaUSuN+kSygBQqsSSHrJOmoVpQyo/6220Q95Z0jiT22JHK6jNa9FMLIppDE2hvKu0sSUJXemIcXkiRZpHhIHZHREGhlyDktAdDGB4h3Icq70dg6cNVr7b+Ml2HFh9xLggxQdwFlo90tXGJRCbYUnsmEIt5FVkZsOMaydvVN3UeHoRo2jHjBsP4EJQFB+LBISZgriIdtfl3UkEQM3MVfL38WHPTq/04s2Q7sMxts9FSq7ZGz7D3hO76kpIcflwTdVJBQB9KgAaL4xQinoA7F6nAaQr+2iYSblUEWoN1adQ2zsbWkcC7Ckt0whl3pu/ZhMwm4Cpy8w4HQOgREYEwIjNIcZwotRI9QvUNo8BsFEBcHTftmg9+gG4vW4c3nQc697fYryoRAoGQJpGSgJhyjNyJkOxMAA2DAAKuU4eOg3d2xWg1leDGavew5mKU8qoMQAyANI2Q+dTEU9Z5ytOthIZABkALc9p4ipsjAskMk62qwHMyMjChKn3wJOeg7Kj5Vj6jzXw1+r9/qTyYwA0DXGsATQPcQ2tARRzO82bhutG3YbczNYoO1+KD1e+g+raKgZAO36HrAG0fOzE0J/YKq/FZmYAZAC0PPmTGADdHi/GXnk7WrfvipqKGuXSx/mzVXRRMQAyAKqzpTmbgMMTvk1WW0wbeStSvak4fOYAPls7A17UsAlYuyNQA00zANL3UtkRbSs3Z66TgAKAd0aHgaFGWSRfjCCYVMllSRpH9sWzAyx2TK+E/seckpp6ydo0O+2VNcZOH6Tl6b8k9424foUG8Nej9mD1iWz1KTgi7LtcGDHxenTq0Q/BgB/LX1+F0yXnibWqyQQALnfAB9CGP9veRs4rem7nVQw7eYUyxsgXL94AWskbBjs7PnyiTXHzG7i71fvwmdce1tWt8QGMBaw92vXClUOuhdirtx3ehKXbZtIAUNIHxQewYwV+uqTeB9D5m7yyEaf6+xn7GZJD1BCdGynlsQ9gaEyJR7m5PbslpmYAJIKIHaCyA08MgJaXpVUALBp7JXr0G67UW7bxQyyZLg6D+pdAaA2qxbblC5H1PzYvgTQyxNmCMAZA01rP5gSAoq3DeozCmMJxyhJYX7IcnbfMML4EwgBI2jIYAEliYgCki8k4JQMgA6BWAo7fFm5GGsDCIePQr3iC0uJd6xcg59AXxosoRopNa4PYc0Gn6JcSiKXZAbGmyssaQBtauFihXBJIAxieuuP6XoyibsOU/3tuyydYvGp9/FvADICkVc8ASBITAyBdTMYpGQAZABkAQxIoGDASg0aHnsDat30ttq38HMVtyzHb2xY1kU9WGS8reDxB5Pfyo+RgGvxxAt3GKqqpIM5OvQyALQMAhavGpKKr0LtjX2X6blj0Efbv3BR7VTAAEnYMfcgXWSY2AYekwiZg0pQyTiQA8OI7fxGVkP5KhQSeqOZOQjrn/QJl8nA6hiCtDrLfovEQWg8pE3Ml0ZYXLRUtbh+lm3VpCBWLOUwyAauF9hw4CgNV+Du6bzvWzP8AHncAxXnl+DyjA2qDHlNNNPQpM+hDVFw6kwDZVHkVAPTEftXCSICGMjMogJI/ln+bHT8+w7wNqMUziuOnFZm2/yJ/7z5+7FbiABIWllqg2+XB1cOmomvbHkqsuvWLPsXBXRtiRIKWvPqi+ABW4qeLu8V/CYR405Yagpr8fJtGcBTtnJLFQX+/UHnRDZn3L44DyABotJOa+DsDIAOgBONJM4h8XBBgn1RhOBGhYjMA2GvQGAwYNUkp/eh+AX8fIhgIwOsJMgCaGhgGQClEJSEAimmR6XXj1qJrkJrXW5klGxZ/jv3b10pmDAOgDsSJoMgAKN+ACEeAyZ2rhSZnAGQAbMkA2GfYReg7LPTSgaL5+zoEf+LDAOg2vSuyBlCynyQpAKa6/LimphTuIfegXZdeylzZvHw29m5eodWf6eZR6BYwawANFxhrAKUiYgA0nDm0BAyADIDJDoAbT2XCH4weZ5fbjYFjr0HXwqEh+CvZgo0LZyAYrA/07PUEUNTmPJuAaVuJkooBsIUBYNVJrDvdCsMuvgUd8guVOSAAcPOKORHmUNYAsgbQxCZCSMoASBASJYkMAGX57PgFyt5u1Q+gDRCzFaJF3lvdt8QZR5cTrUC99ZSWj/qziRx7j1wtLSEtlT3/wTSvH78q3otUb7Q0XN405BbfgdT2fZQ/VJYsRfmWT6Rvgtb4gVmtOsAX0GvD4smO4o8Wb33ayd9UeRUAVN61rcWeXSkI+MxpEN1ev+U3cUXdhr54cQRumDeOFq8hYvFR9u66PvfxmfbhC5dP9gGU9F/RAFafxJoTmQgEUzBk/DXILwy9mS206Wu/ngG/r1balbAG8LHF+XF9AOXPKFNj+cmqtvh8GzVws7RK45iCSjZCEOn5/3qa3wLmSyDU7cE4HQMgA6DxLDGz4mhoR0t5l2jPAAAXXElEQVRlDwBTUoK4/ZuncGCnB6pVF22y2+GS4qnIzWqrdHvltvnYVLJKKgLlJm9hAHsPpEkd5BkA9WJjACTP7Drhmb3IESn1cF6zlzicBkCfelGpb/EE9C0OuVSUnjqK1XOno/LcGd1EYQCUbDkMgKSjSCQyv8rIRbeshAyADICkGU9ecbSEtFT2AfCO+85g944UBAIuFHbshwn9J8HrSYHPX4v5W2djz/GdMbtvpBViAGQAjNTC7dlpIwyM5jUO0poMaz2bWAO48VQ6av31K1q4VQy6YArcHg9qa6qwadHHOLZ/W1SXPK4ghravAmsAI8TCAEid9gyAZEkZJFQA8I6fGxcnuclJN3dKiteUJwcCp83CNNijX1q10T5aU0i/dRwNKRPj5xXZVOxgv2JNShI8ulwQGkABgPt3Z2Fs74no12WQUuTZyjOYvfEznKk4FXfeGwFgvMx28tZBRazgwAar1U7ddvI2ZbvJdcewxtkx49rJGw2QIhRLtNmc8o6wlTAu4SlUZwLe4dHVHT3N9IJLcftxRcUppEoiJHlzuyF3+O3wZLRWiqncuxjl22cCgXqTcLUPeHx5Pqrr+kwzlVoN5aI0hABZ8nQSs7NsHVq83Rtqmqxx0d/N//dv2ARMOhWNkYZTAGAAlHgjkggjJinp5hUZniz6MjIAyn9gCAD83sOt0Dv7KrRKz1ES7T2+S9H81fprDNe/HRiyk5cMMzF6YKduO3mbst3kuhkAo2aNHQBU5koPHw7sdMHv00/GtJR0TBw6BfkdQjeESytOY+GGL3D8zCG43UD3fkG88Wor1NaENz4GQJ0UNUDJABiSEPmINtzlW3gCBkAGQAmxWodY2XqyCLaxliZl8WdnpePWK0diwvD+SjE1vhos3bkA249sJq94OzBkJy8ZZhgAdTDTy0hrygDoKAD27hvAbkV7GHtVDuk+HKN6j4PX41WCRm86sBar9y5Bjz7n8foLWQyA6oiwBpC8NTMA0kUVPyUDIANgMgGgeD3mklH9ceNlI5GdmaZ07fCZA4rWr7zqnKllYwfi7ORlALThS8cAaHqOKyZkCyZgRXtIAEDRoNzMNrhk4BXo2LqL0r7Kmgrsq1iAZ/60FzXVrAEUMmEApE9dihKAXloLTpmWlROceHu0DyD5CTaisxypPKmPIXFgnGyHUiVtepFNr7TiQDIV29CmkdtLFLs0mdQtkigAsvZQm9ClRBoaObAA1186Avkd2ygJzlWcx6Har7Fo7TblEojZj6FvV5wiGQDNQ5xHPCOnXIYwn7cOmi3md+Im7h7lOTV96JuG9OOrD+Mi8eEjWFRDEBcGQHNrxAwAhnZVF4q6DcOI3hcgzRv6cVZy6Djem7kC67fvp76iJnfkkyxuJ59vk0eBIQhYeR2Olo4iADYBhwba3Ew1u/O3oPQMgJapQxbeUD41ibOVAVAyFgayEz8uhvfvgWmXFKOgSzulgEAggK+Wb8XHC1bhhm8ex+7toVvAZj8MgBZlZqSFizEQDIDm3uMNQ2/oEkjiA2B42NNTMjCmzzj061yEsHJg1/6jmD57lQKCxh8aUDkJXgyAxqPSmCnM70yN2bpmVBcDIAOgo9O1ATSArkAALs2v6PS0FFw0oj8uv7AIHfJy67qwfP0uzPhqNY6cOIsUbxC33VuGvXtTGQCJg9ykmkvWAMb1pZMNYXPSAEa23+0OYlhRHrynJ6C4f8+6Px06dgYzF2/AwtXbUV0ruVmipGQAJC7npE3GAOjQ0DIAMgA6NJVCxTgMgK5gAEXr98KjHgZdBhVg4OUj0W/iMKRlpYc0fv4Adi3ZhGX/mo2Te49EdSclx4P0BzohKK4dmvywBtD8NmsHIFkD2DI0gGIZCgDs1cuHf7+UgfxOHXH95aNRPLCgboVWVFZh0ertWLx6O/YcOK5ZuSEAFK87xlvXrAE0ueE1o+Tmd6Zm1LnGbKoMAKX1U330qP54WlIgjijJnzA2iei6ZiuWoYR2iN23bCommYljgBjVc6KpfAWlGg5/AJedO49R109BfnFXZOVl1iWrrfJh/6qD2LtkPyrPnJdkr8Wu1fPR6oddEEyRBCszWGiGABgnv528olg7+Zsqb1O2O7puuS9evOE28gGM58dXr4UzD3DhdpuK5RehAIv24dP+yDHWlJn144uUoZ288AdQ8/Jx1Jb564psk98exdPGY+AVI5GaEfIRFJ/TB45j29y12Ll4I06VHK373u/1Yt2ArgoEyi9QyEbcWCYKXFL89qgxBaXNsBZX8Ou3RBzAMuJp2Zgk0bh1tXgBOCVuBkCpyooo3oa/QaxtSEsAwOyMNPQr6ITBfbuhuF93tM3NjhLD6X1ncWjdURzeeAy+6voDRCurYLAGO1bMYQAkzma7AGc3vx1wZQCUBXI2hh07EGcnL2r8qPjzUfQqngi4oh/rTkn3otvwruhW3AVtuoUCSYc/lWcqcXTrCRzZchRrP/0Ey3p1RMDDAGhiiSdFUgZAh4aRAZABUAeZNm4ak6elWofQNnZom6Nc4OjboxP69+yM7p3ydMWUHTmnbPyH1h2Loe3T18wAaP42rXMQ1pR1swYwtBoSHwALR06CSwOAkSs5u10mug7rjC5FHZHdPitqkQvXj/1HTmLb3iPYuvcw9hw8jpNnIkI9yW9ukLYo1gCSxNRkiZINAPsAeB2AuMZYCuAeALKItVMA/EFYiABsVNOVqaMwBsDfAWQAOAjgmwAOGY0QGQBlBTloFrZliqW2Q+6gZiQi5e/09tGmpmVTMa14WkiZUMckH2IlspwxynMHA2jTKhMd83LRqV0u8jvloUeXdujWJQ8Zaam6kqprarGz5CjWbd6Lqg8Won3+CHi8KaSxqksUrFU0gNk/7KyYgMnaU7UAI7NgvMbYySvKtZO/qfI2ZbtldRuFX4kcPztmXEt5yWZc2Syrz2xLC6fOM2osP21L6ut214W/oVhOlW2n1oeKPx9D4chL4XKp69rApCrcPzr2b4eO/TugbY9ceLx6t47yyirsO3xS+Xfo2GkcOXkWR0+cxZmyithITGl0E5h7ZSPPJuCQVKyfUOaOkMZKPRfAGwBeA3ATgJ8AGKWpXNjBdgOYCEC8rP08AOH49KjwqQWwA8B3AMwD8AgAAYQ3G3WAAdBIQuEJR9UU0qZmMgGg1+NGVkYacrMz0CY3SwE98d/WrbLQJicT7du0QqfWrZCSrge9sPSryipxdPt+HNi4Bwc37MaxHQcR8NWbdwtHXAY3AyBpsjIAhjSADIDG08UOQNoFwPN/OYa+Iy5EMKwBNFZY1nfIFUBl1WFg4lD0K8xHn4LOyIi3v1TX4NjJUkVDeKa0HKdLK3CqLPTfM2XlKK+oQnllNXz+GC4lDIDGk6kRU9BO2UZskI2qOgDYBaAtAHHvXfRNXGUcr34fLlrA3L0AJqtfDAQwC0C+CotvAgi9ewW0AnACgHCgqIrXNgZA2sg1lAZQD4LRU1t76UV3CUazEtwuFzxuNzweN7xuN9zif4v/elz1/9+jfud2KemUtB43UlO8yr+0lBSkpor/epGi/H8v0rwepKV6FdDLzEhT/qv8y0xDWipdMyfMNpWnz+PciXKUHj6H0sNlyr/zpfJp6qupwr6Ni1A4/DK4U+j1hH7uswZQFpg43oy3A4+iXDv57eSV1c0AaLy3NRUAuoM+FK48haJi60f5hmUBbFimApvLhdxObdGhsCva9+6CDr2E/2B75Tu3h34BrKq6BkKLGALCKlSer4GwRoT/VVXXorq6FlW1PlTVhr6v9fnh9wfg8wfg9/uV/4b+qd/7fKG/+wIIBMW/IAKB0EUT8b/Ff5X/HQjU/e9YSknWACafBnAEgLcA9ItYrisAPAZAaAbDnx8B6AvgAfULcR1SODyI61LTANwP4MqI9OLu/FgAe+JtA506dwmuWFdvbdaBjmZ9av9uDDCa2sMZxC8ql16Va3TLVwdE2s5pGqTbXpzuj0YZ7XZb39CMt+vET1FTWYWKU2UoP12GitOlqDhdhnJhgjl0Arm5Bagqr0UwQP+p76+pwt6Ny1A4ZBwQCwBjiTzow46Vi5D9P8IE7LZgAg6ioLcPJbvN3+70eK3nDcGM9fxNlbcp2y2r2xwABtGztx97lbE2t86EvE3njTIBB9Gz0I+9u+K/qVvfqkgTsMgbUPOaa3dYZlbzK/1W6hYm4NAipFhTw7Des5sfB3e7TMtb5Hf5Aih78SR6DhkNIPoSSaScXG4XMttkIatdNrLyspCem4m0Vmlwe33IystFdrtceE38gDUvYes5AoF6OAzDYvf8znwLOMlMwI0NgD8EIP6FP51VjaP1mdr8cgpzennza7btFrfEfrfEPouJwv22vVyaTQE81s1mqGw3tFMc4rVdeHMpIJnULA1lAj4p3uA2MgGrF0aEGbklfcQlmZbWZzG+LbHfLbHPLXWsW2q/eY63nNOrpY511AgnEwCKjs1XL4CEL4EI8+9IzZwWfn3iEsiEiEsgwnFKXPgQl0B2Argv4hKIMP+KCyVGn5Y4oVpin/lwNFoJyfV3nuPJNZ7xesNjzWPdciSQZCZgMXDC/0/AnwiAJsK6fEsN8/IUgMMAXlRHdyqAZ1QV8CYAd6thY8SfLwDwEgDxPpbII8LAHCDMipa4ebTEPjMAEhZDEiXhOZ5Eg2nQFR5rHuuWI4EkBMCmHDzhD/j/mrIBTVB3S+yzEHNL7HdL7HNLHeuW2m+e401wiDRRlS11rKPEnWwm4CaaS1wtS4AlwBJgCbAEWAIsgeYjAQbA5jNW3FKWAEuAJcASYAmwBFgCjkiAAdARMXIhLAGWAEuAJcASYAmwBJqPBBgAjcfqOQDi0kgPAMUA1qlZ/glAxB4MAKhVA05/pf5NBJf+h/qyiPj7zwC8b1xVQqWI1e9wIy8FMBuACKz95yTpd6w+i9vlYvzF+9LiI96b/lOS9Fl0I1a/xf7wOIDbAVQDECGRLkmSfsfq83I1KLzopoiMOwjAUAAbACTzuhaRgIVMREB8cQFO7G/iopz4JHO/xVOhYv8SMQBFZGjhGxZ+OKC591uM4zsAxGtX4rlT8ajBQ+rLWCJsmng2tbe6th8GsCBJxjtev8VZLC599gFwA4AZEaducx9v0wDBAGgsMhEuRrwCsgjAdREAKJ6HO6tmF2Ao4K+dCoS/AtALwD0AegIQh8oAAKeMq0uYFLH6LRoo4iIK+Dum9jsMgM2937H6LABQ9DFyswgPVHPvs+hHrH7/QH0z+zYANQBE8NSjasebe7/jze/w2IrwTwKABydJn+ONtfhhK8b0Y/U5TfFO+sUAtqjfJ+N+Js4/EeFB7NNz1BeixH9FNAkBTM19jgsQEj/Uv1Dh9ntqSDMxrq8C2A/gCVVR8aF6VgllRjL3W/zQET9kRf+1e3pz77dpeGAApIusRAOAkTnFgvogAgDFm3DiveFlaqL31PeGX6FXlzApZf0W7yX/R/0FJQ6OMAAmS7+1fY4HgMnSZzHhtP0WYTHEAbJDMhuTpd/x1rU4OGcm4fyWjfVaVasttELdACxVY6gK4E+Wsdb2W/xgPxSh8RV/F5peAUViP0+mfou+iZi4whJVoL7gVBjxg048myq0YwKAk7nf4a1MtqcnW78NIYIB0FBEdQlkB8X/ArgZQBsAN6rBo0UG8baweG/4iJpbmFJEsGnxC6O5fbT9FlqRa1U1uoi5GAmAydJvGQB2UU0lQiPy04i3oZOlz9rDMUfVWItDIRwIXYQ5eledwMnS71gAKCBoO4DuqsYg2df1MAAfqaHB2qtvpQsYTPZ+i/H/MQDxI12Yg4WlR6xvMdeTZY6Hzxzxw/00gHBcXGHuD39E/79UNWPJ2m9h0YgHgMnWb0PWYAA0FFFcAAz/8TIAvwMwTjWVJdNEijwghQlQbBJC4ynM3y0FAAUMCFORWC/fBSD8ZYRfTTIfjm1VABQmUHFgCK3BEgBXAVifRIdjLAD8pWr6vSVii0jWdS26KHzFhPn3LdV95WsAV6om4GTut/Dv/D2AjqrmS7zpLkBY+EMmU7/FDznxw30SgAz1kYOWAICR/a5kAIwGHgZAZwBQlCJ8Zu4AsDrJVOiRB+Q16i9E4R8jPsKEInzDXgDw8yTqdzyzoOi30OZ2VQEpmcwG2n6LA1AckMIHVnyE2V+YRIUrQ7L0WzbWYl8Uz0UKh3nR3/AnWfos+hPZb5kpVIz1LAAvJ9FYa/st2/23AhC+csKnO1nGWzxzKvx4haIi7LdeoV4ACfv0JqMJWNbveBrAZBlvMtUwAJJFFbVhpqi3Qnep2YVjqdCMiRtVZ1QfEqExibwEIjRGwvm0uX3iwZBWAyh8Z5Kh35F9FjdBxdOC4sKL+AhTvzAPiVvB4pMsfZYdjn9XTfx/Uy8GCD8x4fIgDotk6bdsfgstibgFK+ayuMUf/iRLn7Vj7QFwQjX1ixuwAgjXALhV9QVM1n4LOQiNX9hV5zuq6VuYgsWN4GTot7jVLBQTAv7E2RT+iL1bzP3wJRBxwU3Md3EJJJn7HQ8Ak6HfpviCAdBYXOJdYKH5EuZPcYtXaEWGqLdgxW1YHwDxa0qYjMLhA7JUTZlwuvUD+IXqY2JcW+KkkPVbOA1HfrQA2Nz7Leuz0IAJc5gwlwgYEBAvNlVhBhWf5t5n0YdYYy3AV4CQuAEqPgIExb9k6He8+S3MoDvVG8CR8z2Zx1oAgjCFih884geu0PKGn7ZM5n4LFwcBSOIsFNo/4eIRfvu9ufc7X+2L0OCLc0t8RDinMarJW/gEiigVwoojtJ7zkmRtx+u3OIsfBCD8XIVMhDVHRPEQP4Ca+3ibpgcGQNMi4wwsAZYAS4AlwBJgCbAEmrcEGACb9/hx61kCLAGWAEuAJcASYAmYlgADoGmRcQaWAEuAJcASYAmwBFgCzVsCDIDNe/y49SwBlgBLgCXAEmAJsARMS4AB0LTIOANLgCXAEmAJsARYAiyB5i0BBsDmPX7cepYAS4AlwBJgCbAEWAKmJcAAaFpknIElwBJgCbAEWAIsAZZA85YAA2DzHj9uPUuAJcASYAmwBFgCLAHTEmAANC0yzsASYAmwBFgCLAGWAEugeUuAAbB5jx+3niXAEnBWAsMBrALwMIAX1aIzAMxXX8mYCKDc2Sq5NJYAS4Al0PgSYABsfJlzjSwBlkBiS+B9AOI92D7qU4/TAQwDcAGAo4nddG4dS4AlwBKgSYABkCYnTsUSYAm0HAkMBLBRfRd2AIA7AYwDsK3liIB7yhJgCSS7BBgAk32EuX8sAZbA/2/HDnGjDKAojH5hE3gUi8CiEXQFKBwShalCIQi+CYqEJWAhwSCxLAGDbkKa/AkJsn3NvDZHjOgkc+fOeRU3/3UEPlbPqwfV0+rrdUJ8hgABAlsFDMCtl9GLAIFTCrypzqv31atTFvHdBAgQuA0BA/A2VGUSIHCXBc6qT9WP6tHx+nOXf5DuBAgQ+F/AAPQ/QYAAgX8CT6ovx9O/i+pX9fb4mxMBAgTujYABeG9O6YcQIHBDgcfVt+pz9fLIele9OJ4C/r5hvo8TIEBgjYABuOYUihAgcEKBh9X36mf1rLo8uly9f/UU8EP1+oT9fDUBAgRGBQzAUU5hBAgQIECAAIH9Agbg/htpSIAAAQIECBAYFTAARzmFESBAgAABAgT2CxiA+2+kIQECBAgQIEBgVMAAHOUURoAAAQIECBDYL2AA7r+RhgQIECBAgACBUQEDcJRTGAECBAgQIEBgv4ABuP9GGhIgQIAAAQIERgUMwFFOYQQIECBAgACB/QIG4P4baUiAAAECBAgQGBUwAEc5hREgQIAAAQIE9gsYgPtvpCEBAgQIECBAYFTAABzlFEaAAAECBAgQ2C9gAO6/kYYECBAgQIAAgVEBA3CUUxgBAgQIECBAYL+AAbj/RhoSIECAAAECBEYFDMBRTmEECBAgQIAAgf0CBuD+G2lIgAABAgQIEBgVMABHOYURIECAAAECBPYL/AXHMa5uw7G/uAAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# First get the heights data, ranges and frequencies\n",
    "x,y = heights_data()\n",
    "\n",
    "# Next we'll assign trial values for these.\n",
    "mu = 155 ; sig = 6\n",
    "# We'll keep a track of these so we can plot their evolution.\n",
    "p = np.array([[mu, sig]])\n",
    "\n",
    "# Plot the histogram for our parameter guess\n",
    "histogram(f, [mu, sig])\n",
    "# Do a few rounds of steepest descent.\n",
    "for i in range(50) :\n",
    "    dmu, dsig = steepest_step(x, y, mu, sig, 2000)\n",
    "    mu += dmu\n",
    "    sig += dsig\n",
    "    p = np.append(p, [[mu,sig]], axis=0)\n",
    "# Plot the path through parameter space.\n",
    "contour(f, p)\n",
    "# Plot the final histogram.\n",
    "histogram(f, [mu, sig])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the path taken through parameter space is not necesarily the most direct path, as with steepest descent we always move perpendicular to the contours."
   ]
  }
 ],
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  "coursera": {
   "course_slug": "maths4ml-calculus",
   "graded_item_id": "ZRSga",
   "launcher_item_id": "KHwLd",
   "part_id": "ToENv"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
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 },
 "nbformat": 4,
 "nbformat_minor": 1
}