IK_3D_HTM_Jacobian

IK_3D.ipynb

{
  "cells": [
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# Inverse Kinematics 3D link arm"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-05-21T04:02:02.759832Z",
          "end_time": "2021-05-21T04:02:02.776870Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "%matplotlib notebook\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom numpy.linalg import pinv, norm\nfrom numpy import sin, cos, pi\ntau = 2 * pi",
      "execution_count": 55,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-05-21T04:05:29.881596Z",
          "end_time": "2021-05-21T04:05:29.922541Z"
        },
        "code_folding": [
          45,
          53,
          101
        ],
        "trusted": true
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      "cell_type": "code",
      "source": "def H(axis, vec, theta): # Homogeneous transformation matrix\n    if axis == 'X':\n        return np.array([[1,          0,           0, vec[0]],\n                         [0, cos(theta), -sin(theta), vec[1]],\n                         [0, sin(theta),  cos(theta), vec[2]],\n                         [0,          0,           0,      1]])\n    elif axis == 'Y':\n        return np.array([[cos(theta), 0, -sin(theta), vec[0]],\n                         [         0, 1,           0, vec[1]],\n                         [sin(theta), 0,  cos(theta), vec[2]],\n                         [         0, 0,           0,      1]])\n    elif axis == 'Z':\n        return np.array([[cos(theta), -sin(theta), 0, vec[0]],\n                         [sin(theta),  cos(theta), 0, vec[1]],\n                         [         0,           0, 1, vec[2]],\n                         [         0,           0, 0,      1]])\n    else:\n        return np.array([[1, 0, 0, vec[0]],\n                         [0, 1, 0, vec[0]],\n                         [0, 0, 1, vec[0]],\n                         [0, 0, 0,      1]])\n    \ndef FK(L, TH): # Forward kinemtics function\n    N = len(L)\n    T = H('Z', L[0], TH[0])\n    V = np.array(T[:3,-1])\n    for i in range(1, N-1):\n        T = T @ H('Y', L[i], TH[i])\n        V = np.c_[V, T[:3,-1]]\n    EE = T @ np.array([[1,0,0,1]]).T\n    V = np.c_[V, EE[:3, -1]]\n    return V\n\ndef angleLimit(TH, MinA, MaxA):\n    THCOPY = TH.copy()\n    for i in range(len(TH)):\n        THCOPY[i] = TH[i] % tau\n        if THCOPY[i] > pi:\n            THCOPY[i] -= tau\n        if THCOPY[i] < MinA[i]:\n            THCOPY[i] = MinA[i]\n        if THCOPY[i] > MaxA[i]:\n            THCOPY[i] = MaxA[i]\n    return THCOPY\n\ndef conv(TH):\n    THCOPY = TH.copy()\n    for i in range(len(TH)):\n        THCOPY[i] = TH[i] % tau\n        if THCOPY[i] > pi:\n            THCOPY[i] -= tau\n    return THCOPY # not in use for this time\n\ndef Plot3D(V): # 3D Plot\n    n = len(V[0])\n    fig = plt.figure(figsize=(6,6))\n    fig.subplots_adjust(bottom=0.1, left=0, top=0.9, right=0.95, wspace=0.3, hspace=0.3)\n    ax = fig.add_subplot(221, projection='3d', proj_type='ortho')\n    ax.set_box_aspect([1,1,1])\n    ax.set_xlim([-1, n-1])\n    ax.set_ylim([-1, n-1])\n    ax.set_zlim([0, n])\n    ax.tick_params(axis='x', labelsize=6)\n    ax.tick_params(axis='y', labelsize=6)\n    ax.tick_params(axis='z', labelsize=6)\n    ax.set_xlabel('X', fontsize=8, rotation='horizontal')\n    ax.set_ylabel('Y', fontsize=8, rotation='horizontal')\n    ax.set_zlabel('Z', fontsize=8, rotation='horizontal')\n\n    ax1 = fig.add_subplot(222)\n    ax1.set_title('Top view(X-Y)', fontsize=10)\n    ax1.set_xlabel('X', fontsize=8)\n    ax1.set_ylabel('Y', fontsize=8, rotation='horizontal')\n    ax1.tick_params(axis='x', labelsize=6)\n    ax1.tick_params(axis='y', labelsize=6)\n    ax1.set_aspect('equal')\n    ax1.axis([-1,n-1,-1,n-1])\n    ax1.grid()\n\n    ax2 = fig.add_subplot(224)\n    ax2.set_title('Front view(X-Z)', fontsize=10)\n    ax2.set_xlabel('X', fontsize=8)\n    ax2.set_ylabel('Z', fontsize=8, rotation='horizontal')\n    ax2.tick_params(axis='x', labelsize=6)\n    ax2.tick_params(axis='y', labelsize=6)\n    ax2.set_aspect('equal')\n    ax2.axis([-1,n-1,-1,n-1])\n    ax2.grid()\n\n    ax.plot3D(V[0], V[1], V[2])\n    ax.plot3D(V[0], V[1], V[2], 'o', ms=4)\n    ax1.plot(V[0], V[1])\n    ax1.plot(V[0], V[1], 'o', ms=4)\n    ax2.plot([-1, n-1], [0, 0], 'k-')\n    ax2.plot(V[0], V[2])\n    ax2.plot(V[0], V[2], 'o', ms=4)\n    \n    ax.plot3D([Target[0]],[Target[1]],[Target[2]], 'rx', ms=10)\n    ax1.plot([Target[0]],[Target[1]], 'rx', ms=10)\n    ax2.plot([Target[0]],[Target[2]], 'rx', ms=10)\n\ndef Jacobian(V): # Jacobian matrix\n    UX = np.array([1, 0, 0])\n    UY = np.array([0,-1, 0])\n    UZ = np.array([0, 0, 1])\n    J = []\n    for i in range(N):\n        if i == 0:\n            J.append(np.cross(UZ, V[:, -1] - V[:, i]))\n        else:\n            J.append(np.cross(UY, V[:, -1] - V[:, i]))\n    return np.array(J).T\n\ndef TargetVec(Target, L): # Target vector correction (if no reach to the target)\n    tv = np.array(Target) - np.array(L[1])\n    sumL = np.sum(L[2:])\n    if norm(tv) > sumL:\n        tv = tv * sumL / norm(tv)\n        print('Target overwritten:', tv)\n    return tv + np.array(L[1])",
      "execution_count": 63,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Forward Kinematics:"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-05-21T04:05:32.008837Z",
          "end_time": "2021-05-21T04:05:32.245967Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "N = 4 # the number of links (N > 2)\nTH = np.array([0, pi/2] + [0]*(N-2)) # theta at each joint\nMinA = [-pi,  0] + [-pi/2] * (N-2)   # minimum angles for angle limit\nMaxA = [ pi, pi] + [ pi/2] * (N-2)   # maximum angles for angle limit\nTH = angleLimit(TH, MinA, MaxA)\nBaseVec  = [0,0,0]\nStandVec = [0,0,0.5]\nLinkVec  = [1,0,0]\nL = [BaseVec, StandVec] + [LinkVec] * (N-1)\n\nTarget = TargetVec([N*0.5, N*0.4, N*0.3], L)\nV = FK(L, TH)\nPlot3D(V)",
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "display_data",
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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\nmpl.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\nmpl.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\nmpl.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\nmpl.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], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.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,\n        0,\n        fig.canvas.width / mpl.ratio,\n        fig.canvas.height / mpl.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    var cursor = msg['cursor'];\n    switch (cursor) {\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\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.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.\nmpl.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\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                evt.data\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\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(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\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(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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 */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    var canvas_pos = mpl.findpos(event);\n\n    if (name === 'button_press') {\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, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.which === this._key) {\n            return;\n        } else {\n            this._key = event.which;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.which !== 17) {\n        value += 'ctrl+';\n    }\n    if (event.altKey && event.which !== 18) {\n        value += 'alt+';\n    }\n    if (event.shiftKey && event.which !== 16) {\n        value += 'shift+';\n    }\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, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\nmpl.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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(msg['content']['data']);\n    });\n    return ws;\n};\n\nmpl.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 = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / mpl.ratio;\n    fig.root.removeEventListener('remove', this._remove_fig_handler);\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.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.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'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.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 () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function () {\n    this.close_ws(this, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n    el.addEventListener('remove', this._remove_fig_handler);\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('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    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.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\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\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.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.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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\" width=\"600\">"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Inverse Kinematics:"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-05-21T04:05:41.332668Z",
          "end_time": "2021-05-21T04:05:41.932333Z"
        },
        "code_folding": [],
        "trusted": true
      },
      "cell_type": "code",
      "source": "Target = TargetVec([2.0, 1.0, 1.5], L)\nMinA = [-pi,  0] + [-pi/2] * (N-2)\nMaxA = [ pi, pi] + [ pi/2] * (N-2)\nscaler = 0.1\nloop = 0\n\nwhile True:\n    global TH\n    V = FK(L, TH)\n    J = Jacobian(V)\n    EE = V[:, -1]\n    Error = Target - EE\n    if norm(Error) < 1e-4:\n        print('Error Norm  :', norm(Error))\n        print('Target      :', Target)\n        print('End-Effector:', V[:, -1])\n        print('Loop:', loop)\n        Plot3D(V)\n        break\n    dTheta = pinv(J) @ Error * scaler\n    TH += dTheta\n    TH = angleLimit(TH, MinA, MaxA)\n    loop += 1\n    if loop > 1000:\n        print('over 1000 loops')\n        break",
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Error Norm  : 9.844014996561271e-05\nTarget      : [2.  1.  1.5]\nEnd-Effector: [1.99995445 1.00000391 1.50008718]\nLoop: 453\nTH: [26.5656628   0.          1.629683   74.69418108]\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<IPython.core.display.Javascript object>",
            "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.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(\n            '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\nmpl.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 = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(this.root);\n\n    this._init_header(this);\n    this._init_canvas(this);\n    this._init_toolbar(this);\n\n    var fig = this;\n\n    this.waiting = false;\n\n    this.ws.onopen = function () {\n        fig.send_message('supports_binary', { value: fig.supports_binary });\n        fig.send_message('send_image_mode', {});\n        if (mpl.ratio !== 1) {\n            fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n        }\n        fig.send_message('refresh', {});\n    };\n\n    this.imageObj.onload = function () {\n        if (fig.image_mode === 'full') {\n            // Full images could contain transparency (where diff images\n            // almost always do), so we need to clear the canvas so that\n            // there is no ghosting.\n            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n        }\n        fig.context.drawImage(fig.imageObj, 0, 0);\n    };\n\n    this.imageObj.onunload = function () {\n        fig.ws.close();\n    };\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute('style', 'box-sizing: content-box;');\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n    );\n\n    var resizeObserver = new ResizeObserver(function (entries) {\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * mpl.ratio);\n                canvas.setAttribute('height', height * mpl.ratio);\n            }\n            canvas.setAttribute(\n                'style',\n                'width: ' + width + 'px; height: ' + height + 'px;'\n            );\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    resizeObserver.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        return function (event) {\n            return fig.mouse_event(event, name);\n        };\n    }\n\n    rubberband_canvas.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    rubberband_canvas.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    rubberband_canvas.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\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\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.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,\n        0,\n        fig.canvas.width / mpl.ratio,\n        fig.canvas.height / mpl.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    var cursor = msg['cursor'];\n    switch (cursor) {\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\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.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.\nmpl.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\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                evt.data\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\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(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\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(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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 */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    var canvas_pos = mpl.findpos(event);\n\n    if (name === 'button_press') {\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, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.which === this._key) {\n            return;\n        } else {\n            this._key = event.which;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.which !== 17) {\n        value += 'ctrl+';\n    }\n    if (event.altKey && event.which !== 18) {\n        value += 'alt+';\n    }\n    if (event.shiftKey && event.which !== 16) {\n        value += 'shift+';\n    }\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, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\nmpl.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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(msg['content']['data']);\n    });\n    return ws;\n};\n\nmpl.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 = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / mpl.ratio;\n    fig.root.removeEventListener('remove', this._remove_fig_handler);\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.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.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'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.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 () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function () {\n    this.close_ws(this, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n    el.addEventListener('remove', this._remove_fig_handler);\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('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    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.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\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\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.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.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n"
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vSjce++9ZXOdddZZUewkoZT3FpQvnXan9/vQhz5U8aVqFj527NjYZFyiSSfypcgjsCSrXvGKV/TKQxVFanqu3lLZSNJG2/EeeOCBHmOUCEw9ptT4/MEHHwyjRo3qdt1nP/vZ8Bd/8RexCimJxHRBVvT85Cc/CcuWLcuFUFsH/+mf/ileKwaSSZJtqnaSiLv77rvjFsJaY8+ePV15Ro4cGfPo92x1Vh459sQTT8StiNpOKFmpkxMJCECg+QQQWM1nzDtAAAIQgAAEIAABCEAAAjUQqCSwJAxOOeWUeFqd4nnPe15QVc3UqVNj0/d/+7d/C9/97nfjz6ZPnx5UHVR64l1WYB133HFxW5tOlJOsUhXX6tWrY8NvVU4pSqVS3ts4/vjjg6qJVAWVcpV7rSqCdA+K5cuXd5NM1QTW3r17g+5BIkaVY29605uCqrkmTpwY9LMbb7wxfPrTnw7qHaVeUStXruwm9f7rv/4r/PEf/3F8b+U46qijug1REi4r9775zW9GTtlIJwIec8wxYcWKFd1+pv5QF154YTz175FHHol884TGroov9T9TBZeapqfG6hJqat5eb6Qm7Hq9KrC+8pWvhEWLFoX169dHRqpIyyPH1FNLa0UnIKrPFwEBCDSfAAKr+Yx5BwhAAAIQgAAEIAABCECgBgKVBFZW9rzhDW+I1TmSI9lQY+2Pfexj8Vt/8zd/03X6XLomK7D0vdKtZPqe+iFJlK1atSpWFkmEzZ8/v4Y7CLFHknolKX7xi1+EY489tuzrTzrppHjinoTbPffc0+2aagJLcu2SSy6JYujaa68t+x7aFnnCCSfECqtzzjkn/Md//EfXe6gRuaqzFP/yL/8S3v72t3f9TFsZJ0yYEPmmnlGq2NL7pdDWRVUwqfLqL//yL8OnPvWpbuNPWyPL3Vs1mD/60Y96nAD4ghe8IN5no6EG7f/+7/8e0yinqsMUkllvfOMbc6WXRNP16tWl9VK6DnMl4SIIQKAmAgismnBxMQQgAAEIQAACEIAABCDQbAKVBJZOoEvbvrT9b+jQoT2GoiotVe+kihqJm0MPPbTruqzAKtfMO12oXlJpy9073/nOrt5Jee9dckhNvrU1UFvi1GerNFRhpOoxhbahpd5c6breBJa2HqrSSn2mtN0uybJy45Oc0j0MGDAg9vwaPHhw12XabilWqsS68soru75/xRVXROGlrXvve9/7goSh/qzG6ikk+FS9pLjqqqtiv61sqJeY+mZJoEnS1RqpAbxepzEr17Rp02pN0+N6CTetJW2JTJHtt5XnDd7//vd3yVHly3MaYp68XAMBCFQmgMBidUAAAhCAAAQgAAEIQAAChSJQTmBpi6CEkKKaUPrEJz4RpYtC4kQCJUVWYFU7yU4iTCfizZo1K2zYsKFmRqkCST2ufvWrX/U4rU6VYqoYU0gizZ49u9t79CawkmDSCyTpetv2pnvQvSi0rVDVZSne8Y53hC984Qvx9dk+WGpif9lllwVVXYnlpEmTYpVRtg+WxJnknKrUtE2xtFG87nvHjh1xW+MPfvCDmvip8bsEWKpKU+8tMap0MmBNyZ85xTBth9Q2U4m5cj3TKuXNrjGtDa0RAgIQaC4BBFZz+ZIdAhCAAAQgAAEIQAACEKiRQDmBld1S9rWvfS1WBFWKbPPwL33pS/FEwRRZgaWm4KpiqhRpm5jEjSqdKp1sWOn1WcmkPknql5SNdAqgthdqm2Fp9Caw1DhdDdRrDfW90kmNKVR1lU7jy/bBUu8uyaPU90rbAFX1lu2Dpebx6jmmUwh1GmRpqPLtySefjKc56kTDWkLbPz/5yU92e4l6fKnPWblQxZt+lQtt80uVbtmfp21/6qV2/fXX1zK88K//+q+xd5qiVJLWlIiLIQCB3AQQWLlRcSEEIAABCEAAAhCAAAQg0AoC5QRWVrT88Ic/7NEfKTsuVcSkhuQXX3xxVzWWrskKLEmp7PbC0nv7wAc+EPR6hSqJUr+ovAzUjFyv0e/qraSeSSnUV0viR6HthapkKo3eBJakUGpsnnc8uk451QMqhe5LlVKK1AcrVbtlK67+7M/+LMqj1AdL/a9UFaXKq0pbJNWb6/HHHw95TvbL3oNk2HOf+9x4yp+kn+YoVXBVOs2wtLdZNl8lQdWIwNJpkeeff358GzXHT1spa5kLroUABGojgMCqjRdXQwACEIAABCAAAQhAAAJNJlBNYOkkOfUsqhTaaqbeToreBNb+/ft7rarK9jmqR2Dp/ZNoGjZsWNx+N3DgwDiuVGGk7XfaXpgkUvaeehNYqT+UqsJ0kmLeUGP20q1+2rqokxJTHyyJMY072/NKzd+zfbB0Ap9O4lOoCuvlL395jyGkUwxPO+208NOf/jTXENUzTCcrSvClvlfq3aWeVXv27AnKqV5YiWNK2mqBlX0/zV/a3prrJrkIAhCoiwACqy5svAgCEIAABCAAAQhAAAIQaBaBTtlCKD7XXHNN7AGlSNvvVL2knlISHy960YuCtkeWi94EliqhLr300vgyVUyVE2B55+fcc88N2mqZ+mBpa5y2yGVPHdRYtd0yVWV9/etfjxVI+loN5cv1plLvseXLl0fRJSGVJ7J9wf7xH/8xvPe9740vy1Y8qTIunTSZJ2elaxqpwNK9a0yKapV8jYyR10IAAr8ngMBiNUAAAhCAAAQgAAEIQAAChSLQaBN39U5ShZOikSbu8+fPj829623irvdXRdG4cePCrl27gnpGfec73wnZHl2lW/qyE9GbwFKD9dTbq7cceSY2VVzpWvXBetnLXhZ++ctfdut3pZ9l+2DpNf/93//dq5xKIkxN0h977LEeTexLx6YqMMkuCaFjjjkm3HrrreGggw6Kl/32t78NJ554YvzewQcfHHtuaX4aiUYE1otf/OKgrayNrI1Gxs5rIdAfCSCw+uOsc88QgAAEIAABCEAAAhAoMIFyAkvD1TYyCRb1Xrr33nvD0KFDe9yF+ibp9Lp169aFESNGxJP1sn2uslu/JGq+973vlSWxYsWKuJVNUe3Uw2oozzvvvHDJJZfEcWgrouSaKpy0DU7bCrW9sFz0JrDuv//+2Jj8wIEDUfpovBI79UT2hMe//du/DRdddFGPEweVN/XBEo9vfOMbsf/Ve97znqDTCMtF2naon0kEaktipVBVmnpV/exnP4v3oftJWxTTa5RjyZIl8Z7VI+uWW26pKsV649GIwNIaVOWZmEgmEhCAQPMJILCaz5h3gAAEIAABCEAAAhCAAARqIFBJYH3+858P7373u2MmNSJXU/QkIVJ6CZgPf/jD8UuJoo9//OPd3rm0V5JEzGte85pu16jX0qmnnhqbc6tHlX6XFKs3tI1O2+kUuocLLrggPPLII/F99f6VojeBpdekrX/6s05M/OIXv1hRYumEvquuuiq85S1vKft26dRBNV5XtVS2/1V6QRJS6Rp9XxVlqiwrF1u2bOk6/U8N4HWKYKXQdkhtWVT0tkVQ7D760Y/G6yTOJNDqjXoFlk5jVDWaotHqt3rHzusg0B8JILD646xzzxCAAAQgAAEIQAACECgwgUoCS9VVp5xySqy8Uag5uKTHtGnTYqWVJImEikKCQX2XtH0tG1mBdeyxx0Y5JRF01llnxUooNSeX9NJJhgpVT6VeR40gS4JIDdQfffTRmErVX6oCqxTVBJZEm8SYKpMUqlDTtj1tv9N9633Wrl0brr322nD11VfHLXeqbCoX2o6YrSTK9r9K16c+WOlrCSBtjXzOc55T8R4kwlQNp6bwl19+ednrlFdj3717dxAnzUFpk/b0QjXeV2WW5kf3qNzqzVVP1CuwVD0nztreqLGrdxgBAQg0nwACq/mMeQcIQAACEIAABCAAAQhAoAYClQSWUjz88MNR+vz85z+vmFEnEKp5+uTJk3tckxVYqqR5wQteEDZv3lw216te9apw5ZVX1r01L5v0Qx/6UNyal0JNzyXddIpgpagmsBIPySH1Y6oWz3/+88N1111X9jLJpde//vVdP0sN50svTn2w9H0JMcmm3kKnQKqiSrJJ2yV1smBpnHnmmeEHP/hBrKbTaYXaSthb3HjjjVFeatuhXvv973+/2q2X/Xm9Akscr7/++nDGGWfk4l7X4HgRBCDQgwACi0UBAQhAAAIQgAAEIAABCBSKQG8CSwNVQ281Eb/iiitiBZWklqqnJFRUSaVqokpiKCuwJEC0lU+n3akh+datW8OAAQNihY8qbCSGXKEG5bNnz+5Kp/za8tdb5BFY6fUSU5JQN910UxRjaoQuJhJO6hf1kpe8JJx++uldTdFL3zdbXZVOGlSfp9LQFsQvf/nL8dvazvm5z32u13tQhZZOXNR4NGeve93rul2v0wzPPvvs+D3Nm05DzBOpQbyuLbcNNE+OegSWeo/pfrQGq1XQ5RkD10AAAvkJILDys+JKCEAAAhCAAAQgAAEIQKDNCZQKrDa/nbYY/tvf/vYo61Ttpu2M7Rwf+chHwoUXXhhlpLYvqkcaAQEItIYAAqs1nHkXCEAAAhCAAAQgAAEIQKAABBBYrZ+Ebdu2hRkzZoQnn3wy3HzzzV0N7Vs/ksbeUT3HVB2o0xfLVZM1lp1XQwAC1QggsKoR4ucQgAAEIAABCEAAAhCAQMcQQGD1zVS+733vC5/4xCfaum+Umvu///3vD8cdd1y49dZbe5yA2TdkeVcI9B8CCKz+M9fcKQQgAAEIQAACEIAABPo9AQRW3ywBnTD46U9/Or75e9/73h6nQ/bNqGp710svvTTs3LkzvPKVrwwLFiyo7cVcDQEINEwAgdUwQhJAAAIQgAAEIAABCEAAAu1CAIHVLjPFOCEAAQh0J4DAYkVAAAIQgAAEIAABCEAAAv2GAAKr30w1NwoBCHQYAQRWh00otwMBCEAAAhCAAAQgAAEIQAACEIAABDqNAAKr02aU+4EABCAAAQhAAAIQgAAEIAABCEAAAh1GAIHVYRPK7UAAAhCAAAQgAAEIQAACEIAABCAAgU4jgMDqtBnlfiAAAQhAAAIQgAAEIAABCEAAAhCAQIcRQGB12IRyOxCAAAQgAAEIQAACEIAABCAAAQhAoNMIILA6bUa5HwhAAAIQgAAEINBCApdddll461vfGoYMGRL27NnTwnfmrSAAAQhAAAIQ6E8EEFj9aba5VwhAAAIQgAAEIGAkcP/994e5c+dGefXYY48hsIxsSQUBCEAAAhCAQHcCCCxWBAQgAAEIQAACEIBAXQRe+tKXhmc961nhiCOOCN/61rcQWHVR5EUQgAAEIAABCOQhgMDKQ4lrIAABCEAAAhCAAAS6Ebj88svDO9/5zrBu3bpwwQUXILBYHxCAAAQgAAEINJUAAqupeEkOAQhAAAIQgAAEOo/Azp07w5w5c8JFF10UJdYb3/jGmgXWr371q17B7Nu3L6xfvz6MGTMmjBo1Khx88MGdB5I7ggAEIACBwhJ46qmnwq5du+L45s+fHwYOHFjYsfaXgSGw+stMc58QgAAEIAABCEDAROCss84KDzzwQLjpppviFsJ6BJZeR0AAAhCAAATagcBtt90WjjvuuHYYakePEYHV0dPLzUEAAhCAAAQgAAEvgW9/+9vh7LPPDitXroxVWAoElpcx2SAAAQhAoFgEEFjFmA8EVjHmgVFAAAIQgAAEIACBwhPYs2dPmDFjRjjnnHNi36sU2kZ41VVXBW0LHDBgQDyVsFpU20K4bdu2cOKJJ8Y0P/7xj8PkyZOrpeTnvRDYv39/uPXWW+MVS5cuDYceeii86iQAyzrBVXgZPH08YeljqUxbt24NL3rRi2LSzZs3hylTpnjfgGw1E0Bg1YyMF0AAAhCAAAQgAIH+SWDLli1h6tSpvd78y1/+8vDd7363YUASXBMnTox5Nm7cGGbOnNlwzv6c4De/+U340Y9+FBGcfvrpYdCgQf0ZR0P3DsuG8PV4MTx9PGHpY6lMv/zlL8OsWbNiUv1PlQkTJnjfgGw1E0Bg1YyMF0AAAhCAAAQgAO8zWYQAACAASURBVIH+SUCN1ZcvX97j5i+++OJwww03hGuuuSaMHDkyzJs3r2FACKyGEXZLwIOtjycsfSyVCZ4+nrD0sURgeVm6siGwXCTJAwEIQAACEIAABPopgXp6YFVDhcCqRqi2n/NgWxuv3q6GpY8lAguWXgLebFRgeXk6siGwHBTJAQEIQAACEIAABPoxAQRW8Scf6eKbI1j6WCKwYOkl4M2GwPLydGRDYDkokgMCEIAABCAAAQhAwEqACiwrTrZpGXEisIww2UJohcnatOKkB5YXpyUbAsuCkST9mcDvfve78KxnPas/I+DeIQABCEAAAnYCCCwvUh5sfTxh6WOpTPD08YSlj6UyUYHl5enIhsByUCRHvyQgcfXb3/423vtBBx3ULxlw0xCAAAQgAIFmEUBgecnyYOvjCUsfSwQWLL0EvNkQWF6ejmwILAdFcvQ7ApJXTz/9dHjyySfDwQcfHAYMGEAVVr9bBdwwBCAAAQg0kwACy0sX6eLjCUsfSwQWLL0EvNkQWF6ejmwILAdFcvQrApJXTz31VPyl48Sf/exnxwos/ZLM0u/6HgEBCEAAAhCAQP0EEFj1syv3SqSLjycsfSwRWLD0EvBmQ2B5eTqyIbAcFMnRbwhIXh04cCBuHZTAeuKJJ7qElaSVemHpV1Zope/3G0jcKAQgAAEIQMBAAIFlgJhJgXTx8YSljyUCC5ZeAt5sCCwvT0c2BJaDIjn6BQFJq/3790dxpZCo0tcpVq9eHfbs2ROmTp0aJkyYEKuwskJL1Vn6RcP3frFcuEkIQAACEGiQAAKrQYAlL0e6+HjC0scSgQVLLwFvNgSWl6cjGwLLQZEcHU9A8kqVV3fffXfYunVrGDNmTJg/f37sgZVE1e233x4ef/zxKLDGjRsXmehn6edpWyHVWR2/XLhBCEAAAhAwEEBgGSBmUiBdfDxh6WOJwIKll4A3GwLLy9ORDYHloEiOjiagZu2qutL2wXXr1oVt27aF5zznObH6Sr9GjBgRRo4cGe67775YgTVjxowwceLEuM1Qv/Q6/VLlVVZmpeqs1DeL6qyOXkbcHAQgAAEI1EgAgVUjsCqXI118PGHpY4nAgqWXgDcbAsvL05ENgeWgSI6OJJBOGpTASjJq48aNUVRJPunn5eKII44I06ZNC0OHDu26TtdmhZZeV6k6K9sInu2GHbm0uCkIQAACEMhBAIGVA1INlyBdaoCFDPTBypGJtZkDUs5LYJkTVM7LEFg5QbXwMgRWC2HzVu1DIJ00KHmV5JOE0x133BEeeuiheCOHHHJI7HWlbYOPPPJI0LXZ0M8ls1Stpd8HDBgQf1wqs7LVWdm+WZJXqW+Wth0is9pn/TBSCEAAAhBonAACq3GG2Qw82Pp4wtLHUpng6eMJSx9LZUJgeXk6siGwHBTJ0VEEsvJKVVMpVHm1YcOG+KWE0vHHH991AqG+d9ttt8VTCSWu1BsrG5JPw4YNizJL2w2HDBmSqzore4Kh3jPbCB6h1VHLjpuBAAQgAIESAggs75LgwdbHE5Y+lggsWHoJeLMhsLw8HdkQWA6K5OgYApJXataetvulG1u/fn3sfZVi1KhRYeHChV1N3CWaVqxYEaux1ANr9OjR4de//nX89fDDD8d82Tj00EOjzNIv9dCSmFLkrc7S+yWhRXVWxyw/bgQCEIAABDIEEFje5YB08fGEpY8lAguWXgLebAgsL09HNgSWgyI5OoJAOmkwSSTdlL63atWqrm2Dqpzau3dvj1MISwXWpEmTupgox6OPPtoltFSllQ1VUg0fPrxLaA0ePLjm6qxsI/h02mFHTAo3AQEIQAAC/ZYAAss79UgXH09Y+lgisGDpJeDNhsDy8nRkQ2A5KJKj7QlkTxrUnyWVtA1QPa92794d70+VVfqethKOGTMmzJ8/v2IFVlZglcKRwFJVlqqz1DurtDpr4MCB3aqzVGGVGsZXOtkw2ztLf05Ci+qstl+a3AAEIACBfksAgeWdeqSLjycsfSwRWLD0EvBmQ2B5eTqyIbAcFMnRtgTKnTQoeaUqq9tvvz3s378/yizJqnHjxoW77747bN26tSGBlYUlWSaJlbYb7tu3rxtLyajS6ixdoHGXbjfUOPUre7qhvs5uNaQ6q22XKgOHAAQg0O8IILC8U4508fGEpY8lAguWXgLebAgsL09HNgSWgyI52pJAOXklwSOZdOedd8ZTBVXJtHjx4lgRpXALrCw4jUfVWUlmadthqrxK1w0aNKirOktiK1VnZYVW+nM5mUV1VlsuVQYNAQhAoF8SQGB5px3p4uMJSx9LBBYsvQS82RBYXp6ObAgsB0VytB2B0pMG9bXkjv6xLEmlryWLjjnmmHDYYYd13V8zBVYpxKeeeqpbdZaqwbKh8R5xxBFRaOl3jVeRKrOyv6fqrPT6rMhK2w2pzmq7ZcyAIQABCHQ0AQSWd3qRLj6esPSxRGDB0kvAmw2B5eXpyIbAclAkR1sRqHTS4D333BM2b94c7+Xwww8PS5YsCTotMButFFjZ99WYta0xVWc99thjPaqz1GA+nWyo8UtIpWqsJLO2bNkST1NU9daCBQviNdmth5JZ+pW+31YTy2AhAAEIQKCjCCCwvNOJdPHxhKWPJQILll4C3mwILC9PRzYEloMiOdqGgJqgq7IpNUPXwCV31qxZE3bs2BHvQw3aJXe0Pa80+kpglY7jwIEDsTrroYceig3h1Vw+Gxp7qs6S1EoibtOmTUESa8SIEWHu3Lnx3qv1zpLQ0jUEBCAAAQhAoJUEEFhe2kgXH09Y+lgisGDpJeDNhsDy8nRkQ2A5KJKjLQhIWkn8pGokDVoya+XKlUH9phRTpkwJs2fPrihsiiKwssB1P3v27IkySxVajz/+eI/50DZIiSxtQ5Sok9xauHBhj+2GemGqvspWZ0mIpWbwVGe1xXJnkBCAAATangACyzuFSBcfT1j6WCKwYOkl4M2GwPLydGRDYDkokqPwBNSQXbIqNW5XRZH+8XHHHXfExumKo48+OkyePLnXeymiwCodsKqxVJUlmaXfJe1K45BDDgnTp0+PUkt/VpSeapiqs8oJrdQ3i+qswi99BggBCECgbQkgsLxTh3Tx8YSljyUCC5ZeAt5sCCwvT0c2BJaDIjkKS6DcSYOSV+ohpcoryR1VFqkaafTo0VXvox0EVvYmdP+qyEq9s3bv3t3jHocOHRpF1siRI4P+LD6lpxqqek0hmZUVWvpeqszS71RnVV1CXAABCEAAAjkJILBygsp5GdIlJ6gcl8EyB6QaLoFnDbCqXApLH0tlQmB5eTqyIbAcFMlRSALZkwZTdZEEi7bQqeeVpIx6Q6lZu5qe54l2E1il97Rx48Z40qKqrlI/sOw1AwYM6GoEr22G+lrRW3VWdquh5BfVWXlWEtdAAAIQgEA1AgisaoRq+zkPtrXx6u1qWPpYKhM8fTxh6WOJwPKydGVDYLlIkqdQBCqdNLh169YgiaNQX6hjjjkmDBo0KPfY211gpSbuklNqVJ+tzlIfrdKQ2EsnG4pXaXWWJJhYK1J1VrYKi+qs3EuLCyEAAQhAoIQAAsu7JHiw9fGEpY8lAguWXgLebFRgeXk6siGwHBTJUSgCleSV5JP+MayQlFm0aFFXhVHeG+gkgaX7z8a+ffu6+mapd5b6hmVDVVtJZkmAqdJKkbc6S2IrK7Q42TDvquM6CEAAAv2TAALLO+9IFx9PWPpYIrBg6SXgzYbA8vJ0ZENgOSiSozAEyp00qO+tWrUqntKnGD9+fJg7d26sGKo1OllgZVmImU5mTL2zUqP7dI3kU7Y6a8iQIXVXZ0mE1TMXtc4d10MAAhCAQHsRQGB55wvp4uMJSx9LBBYsvQS82RBYXp6ObAgsB0VyFIKAKoYkXSSqVOkzbty4oBP5dNJgal4+c+bMMG3atChb6on+IrBK2egfaklmPfLII7F/VjbUSyxVZ40YMSJWZ6Wthbo2bTXMnmyY7Z1FdVY9q5HXQAACEOhsAggs7/wiXXw8YeljicCCpZeANxsCy8vTkQ2B5aBIjj4lkD1p8L777gvr1q0LqghSjyfJq/3790dhNX/+/Ci1Gon+KrCyzJIoTEJL/4jLhlgPHz48nmooqaUeY5V6Z+n7+pU93VC5so3gqc5qZMXyWghAAALtSwCB5Z07pIuPJyx9LBFYsPQS8GZDYHl5OrIhsBwUydFnBLLySlU+27ZtC5JMqgh66qmnYh8nnaS3ePHioL5NjQYCqydBbS/MVmelyqt0pQRWqs6S2FJ1nK5Jv0qrs/S6AwcORLE1ePDgKLeS0NJr662ea3TueT0EIAABCLSWAALLyxvp4uMJSx9LBBYsvQS82RBYXp6ObAgsB0Vy9AkBCZAkqZIE2b59e6zAysoTnTSoE/QcgcDqnaKEobYYSmhpK6eq37IhGaUthklopRMgszJL20BXr14dX3bKKad0q86SvCo92dAxr+SAAAQgAIHiEUBgeecE6eLjCUsfSwQWLL0EvNkQWF6ejmwILAdFcrScQKWTBleuXNnVrF1NxiWvdHqeKxBY+Ulqjvbu3Rt0oqFk1mOPPdbVFytlUYVVtjpLgksCS1s/k8BKcqt0q2H6WtVZqRE81Vn554crIQABCBSdAALLO0NIFx9PWPpYIrBg6SXgzYbA8vJ0ZENgOSiSo6UEVG2lyqvUHFxvLsmxZs2asGPHjjgWVeksW7Ys/u4MBFb9NDVnkllpu6Ea7GdDc6XqLEkt9TJTaA41t6nCLv1erncW1Vn1zw2vhAAEIFBEAggs76wgXXw8YeljicCCpZeANxsCy8vTkQ2B5aBIjpYRkMBQf6QkNfTGEiOqvFLlTgpJkFNPPdU+LgSWB6nmb8+ePV0yS9VZ5WLSpEmxQkvVdKrOKu2blU5DTCcaZk82lBBL2w3T9z2jJwsEIAABCLSCAALLSxnp4uMJSx9LBBYsvQS82RBYXp6ObAgsB0VytISA+itlK69UcaN/QGi7mRqJK8aOHRseeOCBeAqh+ie5A4HlJvp/+SQlU3WWthtqnrOhLYJqwi+Zpd/VpF9RqTqrnNDKnmzIVsPmzCNZIQABCDgJILCcNEP8N9OPfvSjmPT000+PpwQT9RGAZX3cKr0Knj6esPSxVCYElpenIxsCy0GRHE0lUHrSoKpuJCBUtaPKK8kPVdosWrQoNg3XVkIEVvkp2bRpU9iyZUuUQOJVxMj2wBo2bFh4/PHHewxz6NChXb2zdI3WQ2/VWVmhpWRUZxVx5hkTBCAAge4EEFjeFcGDrY8nLH0slQmePp6w9LFEYHlZurIhsFwkydMUAtmTBlO1jWSEel3dddddUVqoGkfN2iUy9I9dBFblqWgHgSUxefvtt8ebUA8s9cpKfbNUpVVanTVgwIBu1VmpaX9aL6lvlr5Ojd+zv+vPVGc15eNLUghAAAINEUBgNYSvx4t5sPXxhKWPJQILll4C3mxUYHl5OrIhsBwUydEUApVOGlQFkf4yURx22GFRXqUyeARW71PRjgIre0eSUbt3746nGkpqqY9WaUhkppMNValVWp2VhJZeJxlarjorCS16ZzXlo01SCEAAArkIILByYcp9EdIlN6qqF8KyKqKaLoBnTbh6vRiWPpbKhMDy8nRkQ2A5KJLDTqDcSYN6E/Wg0j9oFZIUixcvjtUzKRBYnS2wSu9OW0az1Vnqk5YNVWNpu+TIkSPjCYeq1lL0Vp2VbQSfqrOS0KJ3lv2jTkIIQAACFQkgsLyLgwdbH09Y+lgqEzx9PGHpY4nA8rJ0ZUNguUiSx0ag3EmDEhOrVq2KskIxYcKEMGfOnFg9kw0EVv8SWNm71brR9sMktPbu3dsNhuRTqs6S0FKftDzVWdkqrHSqoYSWXovQsn3sSQQBCECgBwEElndR8GDr4wlLH0sEFiy9BLzZqMDy8nRkQ2A5KJLDRiCdNJgat0sQqMpGJw2m7WKzZs0KU6dOLSsPEFj9V2CV3vm+ffu6VWdJcGVDvdPSVkNVZ6VKvrzVWRJbSWjpd2SW7a8BEkEAAhCIBBBY3oWAdPHxhKWPJQILll4C3mwILC9PRzYEloMiORomUOmkQUkryStJLAmCBQsWhLFjx1Z8PwQWAqscAYnRbHXWE0880e0yra3hw4d3Ca3BgwdXrc7S2tTrVMmlrYnZRvCllYENf0BIAAEIQKAfEkBgeScd6eLjCUsfSwQWLL0EvNkQWF6ejmwILAdFcjREIJ00qAqZ9EsCQI26tW1Q8kGCYMmSJbGPUW+BwEJg5VmMElhpq+Gjjz4a1102Bg4c2K06SxVWWqeKtEZvvvnmuDbnzp0br832ztKfk9CiOivPjHANBCAAgZ4EEFjeVYF08fGEpY8lAguWXgLebAgsL09HNgSWgyI56iaQ5JVEQDodTg//27Ztiw3bFaqG0UmDqnSpFggsBFa1NVL6c629Rx55pEtoaethNrQeS6uz9PMbbrghCqx58+bFn2stp75Y2dMN9b3sVkOqs2qdIa6HAAT6KwEElnfmkS4+nrD0sURgwdJLwJsNgeXl6ciGwHJQJEddBPTAf+DAga6KlpREf1Fs2bIlfikxoMornSaXJxBYCKw866TSNVqTpdVZqfIqvUZCVRVX999/f1y7CxcujCcd6rrUPyv9WfKqVGZRndXIDPFaCECgPxFAYHlnG+ni4wlLH0sEFiy9BLzZEFheno5sCCwHRXLUTEAP/k899VQ3eaWH/rvuuis8+OCDMd+RRx4Z5s+fH6tX8gYCC4GVd63kuU5rNFudpV5spaGTDdWXTRJr0KBB8cdZkZUqC6nOykOcayAAAQj8ngACy7sakC4+nrD0sURgwdJLwJsNgeXl6ciGwHJQJEdNBPRAr8qr9JCvF+vrlStXxkbbCp0yqNMGaz3ZDYGFwKppMdZwsdbr3r17u/XOKn25trmmkw0PP/zwWH1VrjJL30s9s7K9syRr03bD9P0ahsilEIAABDqKAALLO51IFx9PWPpYIrBg6SXgzYbA8vJ0ZENgOSiSIzcB9QzKVl5JUOkfAbfffnv8XV/PmTMnTJw4MXfO7IUILARWXQunjhddf/31sYJQBwtIbD355JPdskhEqSorCa1DDz00/rye6iw1hK9V5tZxS7wEAhCAQKEIILC804F08fGEpY8lAguWXgLebAgsL09HNgSWgyI5qhLQQ7vklU58W7NmTXyIX7p0afz6zjvvjBVYeuBftGhRGDVqVNV8lS5AYCGw6l48Nb4wNXFPPbB2797dVZ31+OOP98h22GGHdcksbTssV52VTkOkOqvGyeByCECgIwkgsLzTinTx8YSljyUCC5ZeAt5sCCwvT0c2BJaDIjl6JZA9aVD9hG677bZ4vfpbJZml6hSdNKgH+0aiVQJr9OjRsd+R/gGjKpuRI0eG1atXB4mLGTNmhEmTJjVyG0177aZNm2KDfI1ZsrCIoW2kqshTLFu2rIhDjGPKCixVWWVD1VgPP/xwFFr6XYI2G6qoylZnpUMKUnVW6puVTjYsJ7SUI203pDqrsMuEgUEAAg0QQGA1AK/MS5EuPp6w9LFUJnj6eMLSx1KZEFheno5sCCwHRXJUJFB60qAqrn7xi190u37o0KFRXg0cOLBhkq0SWAMGDOghJSQZJB4mTJgQZs6cWcgtXwishpdYV4LeBFb2XfQZkNiUzNIvVWqVhsRtEqH6PEhIlfbOylZnZYWWciWRpd/pneWbYzJBAAJ9SwCB5eXPg62PJyx9LBFYsPQS8GZDYHl5OrIhsBwUyVGWQLmTBksFliqXVAmkahJHNFtgqcpq+/btXUNV/yMJCfX1yoYEl6pyUpWNvi5CILB8s5BXYJW+o04yzFZnVVo7af2ktdNbdVa2Ebzklz5PqUKL6izfnJMJAhBoLQEElpc30sXHE5Y+lggsWHoJeLMhsLw8HdkQWA6K5OhBoNxJg+qBpa1h6aRBVSqpYbsevl3RTIEl+abtj6kSZsGCBWH48OFx6Hv27InbIUsbeaf70ol0qZm3eiH1lVRAYLlWWu9bCPO+i9ZStjpL66g0yq2dbHVW2m6o1+mzlH6lNUZ1Vt7Z4DoIQKBoBBBY3hlBuvh4wtLHEoEFSy8BbzYElpenIxsCy0GRHN0IpJMGU+N2PUir6uSOO+6IoifF6aefbpVXytssgbVjx47Y4yrJK1VWLVmyJAqrJAxWrFgRZcSUKVPidsjU/0g8sqF+R0lmKY+r+izPMkRg5aGU75p6K7B6y75v376urYbqF5d37VSqztLpiOq/NXjw4CBxqrWaFVp9JVLzEeYqCECgvxNAYHlXANLFxxOWPpYILFh6CXizIbC8PB3ZEFgOiuSIBJKw0kO3RI9+6QFZW+xWrlwZJVbq7aPrzzjjDHslkltg6Z7U9HzDhg3xHlPvqzFjxsQm9OUEVraJuxio4iz1P5JQyIZ4ZCtshgwZYmeSfT8Elu/D2gyBlR2d1o6q/tLaeeKJJ3KtnWx11tq1a+Prx40bF6ZPn16xOksS1VkJ6aNMJghAoD8TQGB5Zx/p4uMJSx9LBBYsvQS82RBYXp6ObAgsB0VyRHmlXj6SV6kaRA/Eu3btipVL+r7kz6xZs4IeqttBYEkgrF+/Ptx3331xvKqWUiWL/kGdV2CVLg39gydVZqkPUqroStfpNMZUnaX+Wu7qLASW78PabIFVae1o/ag6q9zaUU85rR+tHVVa3XXXXfEzqO26U6dO7WoML3Ga3WqYvqY6y7c+yAQBCDROAIHVOMNsBqSLjycsfSwRWLD0EvBmQ2B5eTqyIbAcFPt5jqy8Sv149HAs8SMBpJD40UmD2s60fPnywgssybhVq1bFh3+FKljmzZsXK7G2bt1at8DKLhVJvWyFjf4xlA1JBfXYSlJi0KBBDVdnIbB8H9ZWC6xKa+ehhx4K2npYbu2oQlBVfxJYksflemdpnZUKLeVKTeCpzvKtGTJBAAK1EUBg1car2tVIl2qE8v8clvlZ5bkSnnko5bsGlvk45b0KgZWXVOuuQ2C1jnVHvpMeiCWl0pbBdJMbN26MokehapDFixcH9X6SsCm6wJIMUL8u9bNSaEugtl/pIf/uu++2CazSBaEtYmm7mDiVVthIYKXqLIktVcvUGgisWolVvr4vBVZ2VPoMpsq+VJ2l72VDEurII4+M6yetnSSzUsVk+rpSdVYSWlp39M7yrSMyQQAClQkgsLyrgwdbH09Y+lgqEzx9PGHpY6lMCCwvT0c2BJaDYj/NIcGiSqWsvNJDsLYtPfjgg5GKHprVKyrJlqILLPXr0kmJklh6SFfV1fjx47tmuJkCK7uMVJ2lbWJJaJVW2KjCTWIwCS3JrTyBwMpDKd81RRFYpaPVZzJV9j3wwAM9RGiltZMVWamSslx1lr5XerJhPmJcBQEIQKA2Agis2nhVu5oH22qE8v8clvlZ5bkSnnko5bsGlvk45b0KgZWXVOuuQ2C1jnVHvZMecFV5lR56dXP6Ws3a1bRcMW3atDBz5sxu1RpFFljaiqXxSx6p2kRVYxJE2WiVwMq+pxiXVmeVVthoi2a2OqtSQ24Elu9jWFSBlb1D9Z/TutZBARJP+mzmWTv1VGelrYZUZ/nWGJkg0N8JILC8K4AHWx9PWPpYKhM8fTxh6WOpTAgsL09HNgSWg2I/yyHBk6280gOrBIu23ekvTX09Z86cMHHixB5kiiqw9I9kNZfXg7uqmdSv67DDDusx/r4QWKWDEHtVZ0lMqEJLfY6yoeqYbHXWwIEDu36MwPJ9WNtBYKUm7vosSiZr7ejwgFTZl3ftUJ3lWzdkggAE8hNAYOVnledKHmzzUMp3DSzzccp7FTzzkqp+HSyrM6rlCgRWLbRacy0CqzWcO+Jd9BAreaVfadugKn0kU1S5pIdjyRNVLqnxeLkomsDSPekvJokdhSpVlixZEnQaYLkogsDKjkvj37NnT5eQUN+u0gqbIUOGdFVnSV6oN5lOVFy0aFEh16WqhLSNU7Fs2bJCjlGDakeB1dvaSZWT2WskcVNl37Bhw+LJhdlG8NkKTP0s9c9KWw/190Habph+XtgJZWAQgEDhCCCwvFPCg62PJyx9LJUJnj6esPSxVCYElpenIxsCy0GxH+TInjSYHlr1QKoeO2vWrIkPtar0UeXS0KFDKxIpksCShFOFiu5BMXr06LBw4cJem6MXTWCVgtY2zmyFjb7OhsSC5kpSSwKrkqjryyWNwPLRL63A6i1ztbWjLYISnxJa+j2tnUrVWeWEVvZkQ7Ya+uaZTBDoVAIILO/M8mDr4wlLH0sEFiy9BLzZEFheno5sCCwHxQ7PUemkwc2bN4d77rkn3r2kleRVdrtaOSxFEVjaOqWqMVWPKSZPnhyOOuqoqqerFV1gZZlr3tSUPm0XS6cqZq/RvGUrbIogFRBYvr9QahFYjrXTW3VWVmjpvUobwRdh7fnIkwkCEHAQQGA5KP4+B9LFxxOWPpYILFh6CXizIbC8PB3ZEFgOih2co9xJg7pd9Yvavn17vPNRo0bFyiVVV1SLIggs9etasWJF7NulOProo6PAyhPtJLBK70fSbv369bF3VqrEyl6j+UsySxU2hxxySB4k9msQWD6k9QqscmsniVBV+Gm7cDYGDBjQrTorrZ1UnZVONdTX2W2GSWrpe51SnXX99deH5z//+WUn8ZZbbgnHH3+8b4LJBIEOJ4DA8k4w0sXHE5Y+lsoETx9PWPpYKhMCy8vTkQ2B5aDYoTnKnTSo/ld33nln3KamUHNoCaBKp96VoulrgaWKKzWb13YpVYBIvGnrYN5oZ4Gle0xN3NXkXadEJimhSq3SUM+jJLRUqdWqChkEVt7VWP06l8DKvpP+XlA1X1o76sGWZ+1kq7OS0NLr9u3bFysFJcHGjBkT5Zgkqz6fEyZM6DORWp1u+SuSwPrYxz7WQ2TNmzev7OEQ9b4Xr4NApxNAYHlnmAdba6bX6wAAIABJREFUH09Y+lgisGDpJeDNhsDy8nRkQ2A5KHZgjnTSYGrcLnmxf//+KH/SA+vs2bPDlClTahIbfSmwduzYEVavXh0b0Kt/j5q1q2l7LdEpAqu0ibvmNltho/nPhuRCtjpLXzcrEFg+ss0QWKWjq7Z2VI2l9aaDHSRO09pJ1Vn3339/3Io8ePDg+JlUT7r58+fHt7n33nujaG2nSALrm9/8ZjjrrLPaaeiMFQKFI4DA8k4J0sXHE5Y+lggsWHoJeLMhsLw8HdkQWA6KHZSj3EmDkleqkJC80jY0VVstWLAgHHnkkTXfeV8ILN3Tli1bwoYNG+J4dbKa+nUNGjSo5vF3qsDKgpDgk0RKQmvv3r3dOGk9pOosSQk1hHdWZyGwal6WFV/QCoFV69qRNE4yVGtHW5H12dSf9bnUA6v+fkFg+dYBmSDQrgQQWN6ZQ7r4eMLSxxKBBUsvAW82BJaXpyMbAstBsUNypGbtklX6s6qU1Jdm165dsXJJVTmqplCVxPDhw+u661YLLMkYSadt27bF8erBWafv1VtB1B8EVunEaotXklnagllanaV1koSEKmzy9ELrbfEgsOr6aJV9UasFVukg9A/8dCqmftfnMRtaOzr4QXOuCiz1h7rvvvuCttq1u8DS1mR9bnRfJ5xwQrjwwgvDySef7JtcMkGgHxBAYHknGeni4wlLH0sEFiy9BLzZEFheno5sCCwHxQ7IIWGl3jPaDvSTn/wk3pEeuiQs1PhboQexY489Nv5eb7RSYGn86telfjqK8ePHh7lz5+bu11XuHvujwMpykIDQHCahlRrhp2tUiSW5mYSW1kqt1VkIrHo/XT1f19cCKzsiic9sZV/p2tG1N998c1DFn7bf7dy5sy23EOp006997WvhtNNOi58DbY/85Cc/GTZu3Bh+8IMfhDPOOMM3wWSCQIcTQGB5Jxjp4uMJSx9LBBYsvQS82RBYXp6ObAgsB8U2z5EqryQntEXwpz/9abyjsWPHxn40ClXWLF68uOGGyq0SWNoeqEqg1Jx85syZsZdOrTKldGr7u8Aq5aF/wGWrs0orbFRdk63OUmPuaoHAqkYo/8+LJLBKRy2BpbWjLYRpm+r5558ftm7dGi/V5/d1r3tdeO1rXxtlUCPiPD+x5lypv/fU10u9wFatWtWcNyErBDqQAALLO6lIFx9PWPpYIrBg6SXgzYbA8vJ0ZENgOSi2cQ4JB1Ve6ff05ySw0m1JZOnhK+9Jg73haJXAkqiSmNPvGvu4ceMss4TAqoxRFTapOktVb9p6mA2tn9LqrHLZEFiWpRqTFFlgpbtUE3f1wJKw+upXvxp+9rOfhQcffLAbBInQt7/97eEzn/mMD06LM73jHe8IX/jCF4LEXT3991o8XN4OAr0SUHXzBz/4wa6/Y7SmdbDLu971rnDOOefY6CGwbChjIqSLjycsfSxZm7D0EvBmQ2B5eTqyIbAcFNs0R7mTBvUf5JtuuqnrjqZPnx5mzJjRcOVSSthsgZUEk95Pfa5UNaaqB1cgsPKRlDxMFTaqstG863vZ0ANPqs6S2ErVWQisfIzzXNVOAktN3JcuXRoPXDjxxBPjaaf6/Re/+EU4cOBA7CF10UUX5bntQl4jAffFL34xPkBKyBEQaGcCOm3zyiuvjH3dtD1fVZRXXHFF/N6HP/zhcMEFF1huD4FlwdiVBOni4wlLH0sEFiy9BLzZEFheno5sCCwHxTbLkY6vz1ZeqVJJwuH222/vqpyRuNIvZzRTYKlR+9q1a+NwdT8nnXRSPHHQGQis+mhqramfWtpuqF5r2VB1lkSjhJbE45o1a+KPly1bVt8btuBVN9xwQ2xov3DhwjjuIkY7CqzSJu6jRo2KffnUv05bgdsxtPZVCap7UY8sAgKdSkAHMWhbsD7HjkBgOSj+PgfSxccTlj6WygRPH09Y+lgqEwLLy9ORDYHloNhGOSSv9NCtX2nboOSBTgjTlgCJhhQSQEOHDrXeXTMElu5JDZI3b97cNVb1yzn11FOtY1cyBFbjSDVf+r/1SWap4qq0Oiu9iyroDj/8cMv21cZH3j0DAstDNG0hTBVY7X4K4dlnnx0mTZoUD7wYOXJk/IfPpz71qdiQ/pprrgkvfOELPeDIAoECEjjzzDPDunXrwqZNmyyjQ2BZMHYl4cHWxxOWPpYILFh6CXizIbC8PB3ZEFgOim2SI500KHmVqrAkr/R/S1W5pO/pWPtUHdMOAkv3oiqTHTt2xFkYNmxYePzxx4Mehk855RT7zCCw7EijNJVATUJLBwlkQ1sLU3WWKp20RosQCCzPLHSawLr44ovDN77xjSjUtQ1Sa1fbrD7wgQ+E4447zgONLBAoCIH0P8JUZajTQ3UQwyWXXBLOPffcXCOUoOotdJDMc5/73HiJ/luvtgZE/QTUm/LGG2+MCfQ/+djODMv6CXhfydr08YSlj6Uy6X9Aqopeod0+EyZM8L4B2WomgMCqGVl7viB70mD2pDj9X1J9MBWSP9oOpSbKiqILLImOO+64I/ZXUkyZMiWKK8k4BFb5dar5Vo8hPVQvWrSocItZ61QyUqKwUmhbaOqdpTXrOFygHhAIrHqo9XxNpwksDxWyQKA9CKTebhrtIYccEj772c8GHViQN2o5Gfiyyy6LVY0EBCAAAQhAoFUEdDDVW97ylvh2CKxWUe/9fRBYxZiHpo6i9KTB9GYSPaq+Uqg3i+SV4tprr42/F1lgaQua+nWpb5dizpw5cduO/m+u+ichsMovqaILLI0628RdVXSpMktVWmrmnQ2dXJetztIDVKsCgeUhjcDycCQLBPqCgLb87ty5M/76/ve/H770pS+Fj3/84+Gv/uqvcg0HgZULExdBAAIQgEAfEUBg9RH4Xt4WgVW8ObGOSPJKD/1py6CSa9ud+l1JCCgkfo4++ujY+FzbuYousLRVQZVXui9tL5N4Gz16dLwXBFbvy6fdBFa2ibvWsLaHJqG1e/fuHjernm2qztL/pdefa3k4qvWDh8CqlVj56xFYHo5kgUARCKj6SpVS+p9j+h9j1YIthNUIeX/O1iIfT1j6WCoTPH08YeljqUxsIfTydGRDYDkoFjSHRJWEVGrcrod5/aUm+aMKJsVRRx0VJk+e3PWgX3SBpX4Y6oMhMadeSEuWLIlNvlMgsDpXYJXembaQZquzsgcQ6FqdZpi2GqpKS187A4HloYnA8nAkCwSKQOArX/lKePOb3xyWL18eli5d2vCQaOLeMMJuCWg87uMJSx9LZYKnjycsfSyViSbuXp6ObAgsB8WC5Sh30qDklapXdIS7HvzVN0iVS2PGjOk2+qIKLN2TmiLrtEGF+iAdc8wxYdCgQd3Gj8DqPwIre6cSmtnqLDXPLg2JziS0tH4arc5CYHn+4kNgeTiSBQJFIPCGN7whXHHFFbGXYZ4KrGpjRmBVI1Tbz3mwrY1Xb1fD0scSgQVLLwFvNgSWl6cjGwLLQbFAOSqdNKj+FKtXr46VS+oTpMql4cOH9xh5EQWWxqxjudNWA0kINSAvV1GDwOqfAqv0rnWSZrY6S9WI2dBnIFudpV5atQYCq1Zi5a9HYHk4kgUCrSTwtre9LR78ohMC9T/C1CNEpxDqBM6//uu/Dp/4xCcsw0FgWTB2JUG6+HjC0scSgQVLLwFvNgSWl6cjGwLLQbEgObLyKnvSoE5MWL9+fRylmpurcmnw4MFlR100gaXxqF+X/nGs0NGlathe6eQ5BBYCq5SAPgtqDJ+EVto+m65TJVa2OkufkTzVWQgsz198CCwPR7JAoJUEtFVQv3RirE4CVlWrqrp1UtM555xjGwoCy4YyJkK6+HjC0seStQlLLwFvNgSWl6cjGwLLQbEAOSSv1NRcD+tJXukhXOJKpwQp1Ado8eLFvfYCKpLAUr8unTSYmnXPnDkzTJs2rVe5gMBCYFX7OOofnUlm6UCArOzVa9VbLVVnjRgxIlSqzkJgVSOd7+cIrHycuAoC/ZEAAss760gXH09Y+lgisGDpJeDNhsDy8nRkQ2A5KPZxDj2ASzxl5ZX+rC2Du3btiqMbN25cmDdvXsXKpXQLRRFY6mckeaWtYBJx8+fPj/dQLRBYCKxqayT7c20tVPVAElr6B2k2tPa01VanGkpqqedaqs5CYNVCuvK1CCwPR7JAoBMJILC8s4p08fGEpY8lAguWXgLebAgsL09HNgSWg2If5ih30qAqsXTSoCSQYvr06WHGjBm5tkUVQWBJumnboO5Nfa5UNabqsTyBwEJg5Vknla554oknumSWxFZpdZYEVqrOSqdhatuMvlfE0Bj1eZo4cWJQBWMRA4FVxFlhTBAoBgEElncekC4+nrD0sURgwdJLwJsNgeXl6ciGwHJQ7IMc2jJYWnmlyhA9gKtySdvv9LWqrsaPH597hH0tsLTdUT01dH/q06V+XepJlDcQWAisvGul2nUSqNpimKqz9JkqF/p8TZo0qceJmNXyt+LnCKxWUOY9IACBZhFAYHnJIl18PGHpY4nAgqWXgDcbAsvL05ENgeWg2OIckjt6uNavtG1QTc0ffvjhWLkkCaW+PapcqrUypK8Elu5p48aNYfPmzZGmtm3ppESdFldLILAQWLWsl7zXan2WVmfpe9mQcE3VWVq/lQ4ayPuejusQWA6K5IAABPqKAALLSx7p4uMJSx9LBBYsvQS82RBYXp6ObAgsB8UW5sieNJiqsPSgvH379rB27dpYuTRw4MBw7LHHxlOBao2+EFgScXrQ3rFjRxyujuResGBBOOigg2odfkBgIbBqXjR1vECfk5tuuikKZMlifZ0NrV01gE9CS5/JvggEVl9Q5z0hAAEXAQSWi+T/5UG6+HjC0seStQlLLwFvNgSWl6cjGwLLQbFFOdJJg5s2bQpPPvlkFD1Dhw4N+vree++Noxg2bFjcdqeT1OqJVgus1K9L/YYUU6dODbNmzcrVr6vc/SGwep91rZUtW7bEnmKLFi2qZ4k0/TWPPfZY3AarWLZsWdPfr943SE3cJVv1eUtbDTX+0tA22CSzDj/88JZVZyGw6p1dXgcBCBSBAALLOwtIFx9PWPpYIrBg6SXgzYbA8vJ0ZENgOSi2IEe235UenNWPR/2t9ND8wAMPxBGMHj06Vi6pIqTeaKXAOvnkk2OzeW3NUsyZMyf2EmokWimwdCqixi4ZpObeK1asiI3z1TC/0ftohEFvr0Vg+chWOoVQUlbbeZPQ0tfZ0OdTa0ZCS7/XK5vz3AkCKw8lroEABIpKAIHlnRmki48nLH0sEViw9BLwZkNgeXk6siGwHBSbnEPySg/Bacvgz372syiwVNWxd+/e+O6TJ08ORx11VN2VS+kWWimwdMKg7kvbrVQNNGrUqIZJtkpgZdlr0Nquqao4/dKpj5qPIgYCyzcrlQRW9h30md29e3eXzEong2avURVlqs5SBaUOX3AFAstFkjwQgEBfEEBgeakjXXw8YeljicCCpZeANxsCy8vTkQ2B5aDYxBzqDyWplBq36+FWD84SJSkkrqZMmWIZRSsFlgas6hNtedSDuyOaLbDWrVsXdFJiCs1HaTNv9SQbOXJkl5SotRG9g0OlHAgsH908Aqv03fS5zVZnlfbOktTNVmc1unYQWL75JhMEINB6AggsL3Oki48nLH0sEViw9BLwZkNgeXk6siGwHBSbkKPcSYOSJarguPXWW+M76mtVLqkXliuaKbB0TxJA27Zti8NV1ZKazTsbXDdTYKlaTI279+/fH8c/YcKEKA5VBffII49EsaVqudKQnEsVNqq2cVbY1DrvCKxaiVW+vh6Blc2mz4M+z2mroSq13GsHgeWbbzJBAAKtJ4DA8jJHuvh4wtLHEoEFSy8BbzYElpenIxsCy0HRnKPSSYMPPvhgPK0vSZKZM2fG7WrOaJbA0pglr/SP0RQveMELgipOnNEsgaVeV2osnrZsSr4tXbo0boFUxZV+pR5Y6kWmUKVNuQqbJLNUaeO+/2osEVjVCOX/eaMCq/SdJEaTzNLaUfVlNlSNla3OyrN2EFj555MrIQCB4hFAYHnnBOni4wlLH0sEFiy9BLzZEFheno5sCCwHRWOOrLzKVvOoumfDhg3xndK2tYULF4axY8ca3z1E4XLttdfGnCeddFI85bDRkOS5884748N5Ns444wx7NVIzBJZOSFSzeW3/SuxV9TZ//vz4vVKBlZq4a/50Il2SEkl+ZRnoRLoktCTFml2dhcBqdDX//vVugZUdWbW1o3WSKvu0XVU92cqtHQSWb77JBAEItJ4AAsvLHOni4wlLH0sEFiy9BLzZEFheno5sCCwHRVMOySvJHj28ZuWVxFXqu6QKDIkQVWu0g8DSf+BVubRnz55IaeLEiV1bCNtBYKnqbdWqVXE+UgXMjh074rbNagKrdFmo8X6SWdpyWK7CJlud1chpkpWWJALL9GENIfai0xzqc6h5a2ZUWzvqJZfWzogRI7pOIkVgNXNWyA0BCDSbAALLSxjp4uMJSx9LBBYsvQS82RBYXp6ObAgsB0VDjtKTBpVS31u9enXYtWtXfIdx48aFefPmhRtvvDGeQlh0gaXqI1UuSbapSknCZ9CgQWH58uXxfoousLZs2RLWr18fx6oKFzWb37p1a/xVj8DKLhPNrSq7ktDSFsVsqJpG1VmpGfzgwYMt1VkILMOH9ZkUrRRYta6d4cOHR6Gl9SVZKnGsLcdFjPvvvz9Wl+ozpm25kvX6e05x7733hmnTphVx2IwJAhBoAQEElhcy0sXHE5Y+lsoETx9PWPpYKhMCy8vTkQ2B5aDYYI5yJw1qa9rKlStjk2eFtqWp35XExvXXX194gbVz585YuaR7U6+eJUuWBFWGSNoUXWCpEu7uu+/uqnrTuBcvXhwrsPR9h8AqXTL6j022Oqu0GbwqbJLM0ngOOuigulYdAqsubGVf1FcCq9a1o+u1PVUiqJG14yPXPRMCq1lkyQuB9ieAwPLOIQ+2Pp6w9LFEYMHSS8CbDYHl5enIhsByUKwzR6WTBrVFUJVLqrKSsFI1wvjx47vepegCSxUUatiuUOWQKpdUXaEousBSDzCJt9KqN1WQKZolsLJLSNIvVWc99NBDcR1kQ2tCIiJtGRPjvIHAykuq+nVFEVi1rB2t41SdpfVTy9qpTqS+KxBY9XHjVRDoDwQQWN5ZRrr4eMLSxxKBBUsvAW82BJaXpyMbAstBsY4c5eSVHi5VhaOG55IY6oGkyp/S/jpFFVi6J20F0tY7hR6UVXmlyqUURRZYEkUSh6nqTRVvqnzLNsduhcDKLicxTdVZklnip+9lQ9syk8wS896qsxBYdXxYK7ykiAKrdO3o7xJtIVQFn6o6G1k7PnLdMyGwmkWWvBBofwIILO8cIl18PGHpY4nAgqWXgDcbAsvL05ENgeWgWGOO0pMG9bXklR7kVLmkryUlVLmkrT+lUUSBJeGmfl1qeq448sgjY8+rUplSVIG1e/fu2Gw+Vb3NnTs3TJgwoQf7Vgus0gGoQkxCIm03VH+xbGgdZauztI6ygcCq8cPay+VFF1gaeraJ+9SpU6uuHR0SIRmq30vXjo8cAqtZLMkLgU4jgMDyzijSxccTlj6WCCxYegl4syGwvDwd2RBYDoo15Kh00qCaFUsuKNS8W5VLqpooF0UTWJIoqlxS03aFHpRnzZpVtul4EQWWZJD6jUkOVap6S/PQ1wIrux60lrTdNMks8S+tsNEWsWx1lqrj9EuCYtGiRTWs3NZdqvuQTFQsW7asdW9c4zu1m8DKNnHPs3a07TetHf2dlLbR1oip6uVUYFVFxAUQ6LcEEFjeqUe6+HjC0scSgQVLLwFvNgSWl6cjGwLLQTFnDjXmliTR76lJtx4k16xZE3bs2BGz6HS7BQsW9LoNrEgCa8+ePVE26D/k2mo3Z86ceOJZpSiawNI/jteuXRvFz8CBA2PV29ChQyuOv0gCq3SQWlsPP/xwl9DSlrFsqBpOUlQnHqbtnTmXbksvQ2D5cGcrsHo7hfDAgQPdqrPKrZ1UnSWpVUmu1zNyBFY91HgNBPoHAQSWd56RLj6esPSxRGDB0kvAmw2B5eXpyIbAclDMkUPCSg+JEiVJXkk4pB41SjF58uRw1FFHla1cyr5FUQSWZIkql3RfkiOq6Bk1alSvNIoisDQP99xzT1Dlm2LYsGFRXlV7MC+ywMqC1/1JLmars0onRttTU4WN7r9ZFTY5Ph7dLkFg1Uqs8vV5BVZfrh0Elm++yQSBTiOAwPLOKNLFxxOWPpYILFh6CXizIbC8PB3ZEFgOilVyqD+UZFVq3K5KJf2HT9vuVA2jOProo6PAyhNFEFjbt2+P/XV0T5I+kj+SINWiCAJLAlFjf+CBB+JwR48eHavetH2wWrSLwCq9D0lGCUdtH9S2w9LQvWcrbLKN96sxcf8cgeUjWo/AKrd2kgjVGtJaykajaweB5ZtvMkGg0wggsLwzinTx8YSlj6UywdPHE5Y+lsqEwPLydGRDYDkoVshR7qRBySudcid5lSqXFi5cGCVK3uhLgaV7Uq8ufZgV2m4neaXtd3mirwWWtkapakyN0BV5q97SvbWrwErjT03cJRslrCQm1MC+NDSv2eqs7EmMeea5kWsQWI3Q6/5ah8DKZtTnX39/JaHV29oZOXJk/Puh2trpdIF12WWXhbe+9a1BPcVUFUlAAAL5CSCw8rPKcyUPtnko5bsGlvk45b0KnnlJVb8OltUZ1XIFAqsWWq25FoHVJM7ZkwbTtkFt0dIpfXqoVBWQKpfUrF0NkmuJvhJYGrP6RemBU6EHVG0bzFO5lO6vLwWWqt3UrytVIGm75pQpU2pBHzpFYGWbuEvqZStsVC2YjQEDBnSrztLXzQwElo+uW2CVjizP2kkiVGuu3NrpZIGle9OJppJXWtcILN/aJlP/IIDA8s4zD7Y+nrD0sVQmePp4wtLHUpkQWF6ejmwILAfFkhyVThrcunVr2LhxY7xa/YdUuVTPUfV9IbBULaZ+XRIdCjVq17bHWvsm9ZXA0vuq6k0P3Bqzqt7UML/W6ESBlWUgSZmtsCn3wK3qLUkJCUyt42oVNrUyRmDVSqzy9c0WWLWuHcn6JLTS2ulkgfXSl740fj4k7771rW8hsHxLm0z9hAACyzvRPNj6eMLSxxKBBUsvAW82BJaXpyMbAstBMZOjkrxav3592LZtW7xSD3CqXKq3kqXVAkv/kVblUpIZs2fPjpVL9YiLvhBYOuFx9erVsepNvZ0kDmutektT3OkCq/TjsH///m7VWernlg3xTEJixIgRda/pbE4Elu8vpVYKrHrXjv4eUU89VSktXbo03HfffWHevHkxnQ5ZmDZtmg9ICzNdfvnl4Z3vfGdYt25duOCCCxBYLWTPW3UOAQSWdy6RLj6esPSxRGDB0kvAmw2B5eXpyIbAclB8Jkc6aVAPjWp2rCol/Vq1alV46KGH4lXjx4+PW0pqrVzKDrOVAkv3pMoliQyNWc3OjzzyyLqptVJgnXzyybFp+YYNG+J49YAseTV48OC6x9/fBFYWlNaC5FLabljaDF4iIlthI971SE4EVt3Ls8cL+1Jg1bJ2dK3+ftGa0ommr3nNa9paYO3cuTPMmTMnXHTRRVFivfGNb0Rg+ZY1mfoRAQSWd7KRLj6esPSxRGDB0kvAmw2B5eXpyIbAclB8Joe22alCZcWKFfEhf9KkSbFZeGp0PHPmzFhNUM9DfV8ILG0R1JZH3ZOqxdSvS1U2jUSrBJYklba4qZpDoS08ixcvbrhCqD8LrNJ51z/eJGq11vW7BFc21OMtW52Vt1caAquRT1j31xZFYJVbO9m+a6pcVVx44YWxR6A+r5Lmn/nMZ8LZZ58d5XM7xVlnnRVPOb3pppvi3/cIrHaaPcZaJAIILO9sIF18PGHpY4nAgqWXgDcbAsvL05ENgeWg+EwOPcDv27cvVizp4UyVBJI/eoCZP39+GDdunOXdWlWBlQYrGXTsscc2VLmUcrVKYCX2el9x15akRqre0vgRWOWXsNa55jZJCf3DLhv6DAwfPrxLaGlNVRK5CCzLXxMxSVEFVvYOtbVa/zjQejjvvPO6pHO6RttUn/e854VzzjknvOENb/DBaVKmb3/721G66bRTVWEpEFhNgk3ajieAwPJOMdLFxxOWPpYILFh6CXizIbC8PB3ZEFgOis/kUBWBqgZuueWW2AhbocolVf6oosAVzRRYqiL7yU9+0jVUVVxp/HqIdESzBdbmzZu7tgxqvDNmzAjTp09vuOot3TsCK98q0ImPSWZpzkurswYOHNitOkvCMQUCKx/jPFe1g8AqbeJ+3XXXhfPPPz/o0Av9vaODFxTveMc7wqWXXprntvvsGvUJ1N85km3qe5VC2wivuuqqoIdx/Teh3SrK+gwob9zvCSCwvEsA6eLjCUsfS2WCp48nLH0slQmB5eXpyIbAclB8JocElpoOr127Nn5HW6aOP/74eFKbM5olsFRFo5MGd+3aFYerLXiSV1m50Oh9NFNgaavmbbfdFiThFKp6U88xZyCwaqepdaWttEloqUoxG6qMkyhN2w0lLHRogGLZsmW1v2GLXnHDDTfECkudaKmxFzHaUWBlm7hr/JLSV199dXj1q19d6PWg+VfPvalTp/a6FF7+8peH7373u0VcLowJAoUjgMDyTgkPtj6esPSxVCZ4+njC0sdSmRBYXp6ObAgsB8VncqhflARHismTJwf1kXJHMwSWKse09VHVLylOPPHEMGzYMOvwmyWw1CRfW3bSKXmq8DnttNOsY1cyBFZjSCV5S6uzUv+jlFm9s7QeFZpDx9bPxkZd/tUILA/V0gqsdj6FUHJ2+fLlPcBcfPHFQevlmmuuif9jIJ2y6CFIFgh0LgEElnduebD18YSljyUCC5ZeAt5sCCwvT0c2BJaD4jM5VGXy85//PFYsqYpEW9fUuN0dboGlbS9AMwXBAAAgAElEQVSqeNF/jNWHJgmFk046KQwdOtQ6/GYILP0DV1VvGre256gCS1t0TjnlFOvYEVh2nOGpp56K1VkSkGoEn8RVeid9lrLVWRKTRQkElmcmOklgVSJCDyzPWiFL/yOAwPLOOdLFxxOWPpYILFh6CXizIbC8PB3ZEFgOis/kkEDRNqn169fH39tBYGmcqlySSNCWR22709eKogss8dZfKps2bYrjPfzww8PYsWMjfwRW+YUtVtrmpJ5sixYtMq7+xlNpPvfu3RskNPSrXGhe01ZDzXdfVmchsBqfc2VAYHk4kgUCnUgAgeWdVaSLjycsfSwRWLD0EvBmQ2B5eTqyIbAcFDMCS5VXK1asiBUlRRdYenBcs2ZNrFxSZcsxxxwTBg0aFK699trCCyw1BVd/HB1Vrxg9enTsRaSvdU8IrPYTWGnE2Sbuc+fO7eqdlXqbpetUnSURl4SWth62MhBYHtr9QWB5SJEFAv2PAALLO+dIFx9PWPpYIrBg6SXgzYbA8vJ0ZENgOSi2mcBKzebvueeeOHL1uVqyZEmUWKrEKrrAkiRUlZi2ninUa+yoo46K2x/1j10EVuVFXeQKrHICKzVx15pVk/7UCD6d8pm9Ux2WIJmlHkNa01oPzQwElocuAsvDkSwQ6EQCCCzvrCJdfDxh6WOJwIKll4A3GwLLy9ORDYHloNhGAkuVSxI827dvj6MeNWpUrFzS9kFF0QWWGoCrwk2/K9QkXwIrBQKr9wXdrgKr9K4kMdUzKwktrdtsaD2nyixVaR1yyCHGT/r/pUJgeZAisDwcyQKBTiSAwPLOKtLFxxOWPpYILFh6CXizIbC8PB3ZEFgOim0isLQFS5VLevBXTJo0KVYuZfsIFVlgqeJKJyXqPrR9TOJNWwezgcDqHwIre5eqzlJFVpJZqtQqDVVkJaGlgwkc1VkILM9fnggsD0eyQKATCSCwvLOKdPHxhKWPJQILll4C3mwILC9PRzYEloNiGwgsVSzppEE1yVbMnj07TJkypceDfFEF1o4dO8Lq1auDKsjU60hbHtXEuzQQWP1PYJXesU4ylMxKFVpPP/10t0t0UmW2Oktf1xMIrHqo9XwNAsvDkSwQ6EQCCCzvrCJdfDxh6WOJwIKll4A3GwLLy9ORDYHloFhwgZWaYmvblaqtFixYEI488siyd140gaXqGp2at2HDhjhe9TlKzebL3QACC4GVJSDhqfWfqrOSwM1eIxGahJbWV97qLASW5y9PBJaHI1kg0IkEEFjeWUW6+HjC0scSgQVLLwFvNgSWl6cjGwLLQbHAAuvBBx8Mq1atipVL6gOkyqXhw4dXvOsiCSyN+e677w7btm2L45VkWLRoUeitYgaBhcDqjcC+ffu6ZJa2pJZWZ+kzkq3OSr3hyuVEYHn+8kRgeTiSBQKdSACB5Z1VpIuPJyx9LBFYsPQS8GZDYHl5OrIhsBwUCyqwVLm0fv36OLohQ4bEyqXBgwf3esdFEVgax5133hkeeuihON7x48eHuXPnduvXVe5GEFgIrLwfaQnSRx99tEtopYMB0utViaXqLJ1qKKmlz062OguBlZd079chsDwcyQKBTiSAwPLOKtLFxxOWPpYILFh6CXizIbC8PB3ZEFgOigUTWNp2J3G1devWOLIRI0aExYsX5zqJrQgCS1Uy6teVmnHPnDkzTJs2LdfWLgQWAqvej7T+MZq2Gqo6S4IrGwMHDuyqztJn6qabbooVXDpMQIKriHHXXXeFXbt2hYkTJwZ9jooYCKwizgpjgkAxCCCwvPOAdPHxhKWPJQILll4C3mwILC9PRzYEloNigQSWBJSane/cuTOOauzYsWH+/PlVK5cShr4WWDpNTvJKjbhV7aKxjxs3LvcsIbAQWLkXSy8XSkyl6ixVAUqqZkO95JLg0kmetaxRx/jy5kBg5SXFdRCAQBEJILC8s4J08fGEpY8lAguWXgLebAgsL09HNgSWg2JBBJakj+SPJJBi+vTpYcaMGbkql4ogsFQpom2Dkgfqc6WqsSOOOKKmGUJgIbBqWjA5LlZFo7YX6lRDySyJLX0vG4MGDeqqzlKPuYMOOihH5uZfgsBqPmPeAQIQaB4BBJaXLdLFxxOWPpYILFh6CXizIbC8PB3ZEFgOigUQWNpuJ3mlShFVLqlf1IQJE2q+u76qwFKj9nXr1kUxIBmgfl06Ea7WQGAhsGpdM7Ver8+IthiuWbOmh8hSLlVnaYthagav9dxXgcDqK/K8LwQg4CCAwHJQ/H0OpIuPJyx9LBFYsPQS8GZDYHl5OrIhsBwU+1hgqW/PypUrgx6sdWqaKpfq7cnTaoEldBs3bgybN2+OFNU0WyclHnrooXXNDAILgVXXwqnjRamJ+6xZs2LVoD6Hjz32WA+ppebvSWapOkuCq1WBwGoVad4HAhBoBgEElpcq0sXHE5Y+lggsWHoJeLMhsLw8HdkQWA6KfSiw1IcnVYKoybQql4YOHVr3XbVSYL3whS+MY9+xY0cc75gxY8KCBQsa2n7VSoGl3kfatinukhIrVqyI2ze1bXPSpEl1z0EzX7hp06ag0ym1NXPRokXNfKu6c0sCqZpQsWzZsrrzNPuF5U4h1OdHWw1TM/gnn3yy2zC0tVDsk9CqV9TmvTcEVl5SXAcBCBSRAALLOytIFx9PWPpYIrBg6SXgzYbA8vJ0ZENgOSj2kcCS8HnwwQfjuw8bNixWLkmmNBKtFFiqRlE/IcWUKVPC7Nmza+rXVe4+WyWwtEVM2zbFa8iQIWHkyJHxtDf1SkJgNbICQ6xialeBlb1zbYfds2dPl8zSfZWGtskmmaXPsLs6C4HV2Frk1RCAQN8SQGB5+SNdfDxh6WOJwIKll4A3GwLLy9ORDYHloNhigfXTn/40Vv6kGDVqVFi4cGHcPthotFJgpbHOmTPHVrHUKoHVG2dJiYkTJ8ZKm2ZX2NQ631Rg1Uqs8vXlKrB6y37gwIEumaUqLX2dDX1+s9VZhxxySMODRWA1jJAEEIBAHxJAYHnhI118PGHpY4nAgqWXgDcbAsvL05ENgeWg2EKBpYfe6667rqvPjraqHX300Q1XLiUMzRZYata+du3a+HbaTiXxNnr0aNssNFNgqaJm+fLlsUJIoa2aqhxTJZaERDr9MXszuiZbYaMG+30ZCCwf/VoFVvadtZa0bnSqobYb6s+l4Vg7CCzffJMJAhBoPQEElpc50sXHE5Y+lggsWHoJeLMhsLw8HdkQWA6KLRJY2p6mrVV79+6N7zhu3LjYM8oZzRRYDzzwQFi9enWXfDvhhBNi03ZnNEtgpV5j27dvj8NVdcyJJ54Y9H1t+9Kv2267LW4ZUwWWToMUy2wMGDCgW4WNvm51ILB8xBsRWKWjUK+s1DdLMtS1dhBYvvkmEwQg0HoCCCwvc6SLjycsfSwRWLD0EvBmQ2B5eTqyIbAcFFsgsNQr6o477gjZptCqXho7dqzxDkJ8cL722mtjzpNOOqmhhvBpYKo20SmDOm0wG2eccYatcizlbYbAUtWbTnmUWEihqjHJQ81HEljZJu4TJkzoVmEjsVUa6nmk6iz1z5L0akV1FgLL93FxCqzsqCRFVc2XhFYjaweB5ZtvMkEAAq0ngMDyMke6+HjC0scSgQVLLwFvNgSWl6cjGwLLQbHJAkuN2letWhWrfVJfHImTdhBYGvO6deuC/hGqUMVV2oLXDgJLVW8Sh0kiqHn7I488Ek9MnD9/fkWBVXoKoXqWZStsnn766W4rT/Oq/keSWXqPZlVnIbB8H/hmCazSEeZZO2mbqtZQthceAss332SCAARaTwCB5WWOdPHxhKWPJQILll4C3mwILC9PRzYEloNikwSWKpe2bt0a1q9fH99Bp90dc8wxcauatqgVXWCpmuvOO++MfX4UqkrStkeNX1F0gZVOw0tVVqq4krzSnNQqsLLLTFJPuZPQSltC0zWqxJLoS1JC8+6qzkJg+T7wrRJYjawdzbc+fzpUYObMmb6bN2a6//77w4YNG+Lfb0uXLg333XdfmDdvXnyHe++9N0ybNs34bqSCAATaiQACyztbSBcfT1j6WCKwYOkl4M2GwPLydGRDYDkoNkFgSXJIXOlhTqHKisWLF8fKnOuvv77wAkuCTf26UnNqPTzrQVTiRo3Qiy6wSqvelixZEoYPHx7uvvvuhgVW6ZITq2x1luY+GzrJMMksVWc1ctokAsv3ge8LgVU6ev0DWmtH21v1q3TtaHurvqfKPp322cja8ZHrngmB1Syy5IVA+xNAYHnnEOni4wlLH0sEFiy9BLzZEFheno5sCCwHRbPAUuWStgzu2rUrZlbVkioS9DCqKLrAUv8eySttfVLlkLba6R4U6uVVdIG1ZcuWHlVvgwcPjuNvhsDKLkHJBjFKQktbGLMhnhJpSWhpXLVUZyGwfB/4Igis7N1oW2p27egf18614yOHwGoWS/JCoNMIILC8M4p08fGEpY8lAguWXgLebAgsL09HNgSWg6JRYKkaRz2XJIEUM2bMCNOnT+8mKYossCTdtG1QD9OqFlPVmKrHUhRZYGnLpqretEVQoWonjT/1HWuFwCpdjhJYqqyR0NL2xdIKm4EDB3arzjrooIN6XdEILN8HvmgCq9zaUQ+s0i2q6TqtHVVm6fOptV5t7fjIIbCaxZK8EOg0Aggs74wiXXw8YeljicCCpZeANxsCy8vTkQ2B5aBoEljabqfKJUksVdWo6mr8+PE9RlhUgaXtjqpQkghSZZD6damvTTaKKrBU9bZ69eqwc+fOOFyd7qjKsVT1lu6h2RVYvS1HSUFJrFSdpXWSDY1VIkLVWZISqWosew0Cy/eBL7rA0p2mJu76e0TrIs/a0XWDBg3ygaqSiS2ELUPNG0Gg7QggsLxThnTx8YSljyUCC5ZeAt5sCCwvT0c2BJaDokFgqdGyKpckUtSnRpU/epAsF0UTWBJWGzduDJs3b47D1RY39YzKVi6l+yiiwNJWR4nDVPWmijdVvpXbmteXAiu7FsRc1VlJSIirvpcNCay01VBzIsGFwPJ94NtJYGWbuNe7dnzkumdCYDWLLHkh0P4EEFjeOUS6+HjC0scSgQVLLwFvNgSWl6cjGwLLQbFBgaV/oK1duzYKCG3rOfbYY8Nhhx1WcWRFEliqClKVx44dO+J4dTqfTuurtB2paAKrtOpt7ty58bTESlEUgVU6PonPbHWWpFw2NB+qztIak/RShdaiRYuMq9+XKp3+qIzLli3zJTZnaleBVWntSKJrbejUzXJrJ8lQ/R3lDASWkya5INBZBBBY3vlEuvh4wtLHUpng6eMJSx9LZUJgeXk6siGwHBSfySE5oIe/FStWxKPrVcnT29H1ul4fClXFKA4//PBYuaRT53qLoggs3av6dUlKKaZOnRpmzZrVa1PxIgksPayvXLmyq+pNQkc9gXqLogqs7Ji1rtT3KFVnSQiVVmdJaKVtZVp3pVsljR+LmlMhsGpGVvEFaQthtgKrt+xaJ3v27Om2dkqv17bgJLMcaweB5ZtvMkGg0wggsLwzyoOtjycsfSwRWLD0EvBmQ2B5eTqyIbAcFOsQWGrGrYfLBx54IL569OjRYeHChbkaKRdBYEmQaNtdOiVvzpw5YdKkSVVpFkVg6aF5zZo1XVVv6tc1dOjQquNvB4FVehMHDhyI1VmSqurxVdoIXjJLFVlJSlQTqFUhNXgBAqtBgJmX1yqwyq2ddIiAhKjWUjYcaweB5ZtvMkGg0wggsLwzinTx8YSljyUCC5ZeAt5sCCwvT0c2BJaDYo0CS5VLqvyRVFBMnjw5HHXUUb1WLmWH2dcCSw+0Gr8eZvUAq8qlUaNG5SLZ1wJLFSb33HNPuPfee+N4hw0bFqve8m6LakeBlZ0Y3bdOWVSTbp0Smfp+Za/R9lXJLFWjiU+5XmC5JrvOixBYdYIr87JGBVY2pT472nKbKvvKrR1JYMnQWtZOpwks9TL84Ac/2NVAX5+12bNnh3e9613hnHPO8U0umSDQDwggsLyTjHTx8YSljyUCC5ZeAt5sCCwvT0c2BJaDYg0CSxVLqlxKR9tLXE2ZMqWmUfSlwNq+fXt8MNPDrCp1VLkkyZE3+lJgqfJIVVe6B4Wkm6re1DQ/b7S7wCpt4i6Zmips9HtphY3YZKuzyjXmz8su73UIrLykql/nFFil75ZdO5Ja6sOWDa2dVNWnNVRp7XSawNLfz1deeWU4+eST4zZd/V1/xRVXxO99+MMfDhdccEH1ieMKCEAgEkBgeRcC0sXHE5Y+lggsWHoJeLMhsLw8HdkQWA6KOQWWKq7UMypVLkmeaOtgrdEXAkvCSvJDH2KFKi0kr/JWLqV77CuBJeaqGpOkUWi749FHH11zdVGnCazs2tMcq6omVdio2qY0JCuTlNAaaEZ1FgKr1r8RKl/fTIHlWjudJrAqzcbxxx8f5fl9993nm+A+yHTaaacFHWBQS5T24KvltVzbvwkgsLzzj3Tx8YSljyUCC5ZeAt5sCCwvT0c2BJaDYg6BpVP6Vq9eHfsPqRJB8kcNkOuJVgssjXndunXx/4QqtD1I2wZrqVzqS4FVrupN2zbrkS+dLLBK16JOMsxWZ5VW2GgLYrbCRl87AoHloPh/OVolsMqtnSRCtYZ0Wmk2smtH60zbetUcfunSpVHwzJs3L16uLa/Tpk3zAenDTGeeeWb8ezQd2tGHQ2norc8777z4PwOqha7R373671w66KPaa/g5BEoJILC8awLp4uMJSx9LZYKnjycsfSyVCYHl5enIhsByUHwmR7lTCGfMmBG2bNkSNmzYEK9SfyHJK/VFqTdaKbBUYaWeLnoYVUyYMCGoYXu9p9a1ugJL76eqN2130phV9TZmzJh60Yf+JLCykCQxs9VZOqmuNPSgmoSW1nk9glA5EVh1L88eL+wrgVW6djSnSWil7dOlg5XU0smt+qwuWLAg/ridBZY+M/qlyttvfvOb4fzzzw+XXHJJOPfcc30TXNBMV199dZCw038Tv/Od74RXvOIVBR0pwyo6AQSWd4Z4sPXxhKWPpTLB08cTlj6WyoTA8vJ0ZENgOSg+k6NUYKlyQFvXtm3bFq9QH5jFixf/f/beBMquqsr/35VQmSABlMxzQuaEhDHMYFDAKG0vFRwQfoDi0AttW8EBkUFUBJoWpVsbBe1W0QZtFGlFMMxTgBAyD5A5f0IGBGQIJCHJf31Oar/cunnDve/t9959r/ZZq1YlVffue873nPeqzqe+e59QPLuSViuAddhhh8mSJUtEYcXo0aNl+PDhZYMJxlxLgEV/586dm3O9Uax9v/32q0T6Dguw4qK99dZbOSDBBj3usMFlGHVnpXHrOcCqaIm2uzkLACvN2rn22mvDawzIzMb1kUceycEsO1VqE+mzn/2s3HjjjeFhvB6uv/56+dznPlebh9fxKfy84+ccwBJox7i9uQLlKuAAq1zl8t/nG1s7PV1LOy0dYLmWtgrYRnOAZaunRTQHWBYqFgBYPXr0CCkUNIr5TpgwoWznUrSbtQJYgDYAHM6lSZMmSf/+/StWq1YAiw0jTg4aqUm43piPSltHdWAV0w2XCfOqDhtd83oPTizcWaSeArWYh2LuLAdYla7S3fdnEWBFR8faIX2QTSr/5pS+6PrhPei4446T6dOnB0cPp/k1SiMVcuPGjeHjzjvvlJ/85Cdy9dVXy4UXXtgoQ0jdT9KMjz/+eHn88cfliCOOkIcffrhg8f7Uwf2GDqmAAyzbaXfoYqena2mnpQMs19JWAdtoDrBs9bSI5gDLQsUYwHriiSdC2og20ghJjSk3pSrexVoBLJ7LBhLn0v7772+iVLUBFn/9X7hwYa6vVq43DegAq/Qy4Jc6hVm8DgAT0cbplQqzWFedO3du930HWKU1TnpF1gEW44gWceeQAE7rI+VOa+7pWE8//XS57bbbkg49c9fhvrrppptCIXdOQG3GBpy77rrrgtOVGlhpT9htRk18TJUp4ACrMv3idzt0sdPTtbTTkkiup52erqWdlkRygGWrp0U0B1gWKrbFIIWQjTt/fdZNO7VcBgwYYPgUkWoCrJUrV+bqdVH/6vDDDw8OJqtWTYDFX/+Bh3p6HrpTDLrcel35xuwAK91KILVQ3VkvvviikHoYbUBdIJamG+LOcoCVTuNiVzcawIoXcb/55psDCPnTn/4k3/zmN+Xcc8+1E6fGkX7+85/LeeedJzNnzgzF6put4TL7wAc+EOpe/eEPfwj/9ta8Ctx3333yq1/9Sh577LFQJgFoSdmBSy+9NDierZoDLCsld8Xxja2dnq6lnZa+Nl1LWwVsoznAstXTIpoDLAsV22Js2LBBnnrqqVw9IACKFiM2fExVABabDgrNU3BeGykgOJgsW7UAFmCEYu0UGqfhHJs2bZqZ6001cIBV/mpgjcXdWXwt2jjcoGfPniHtisYcZrU9+OCD4bXOwQAAuCy2RgdYWsSddcIfBeJuvSxqXqhPZ599ttxyyy3CibTN5sAiXZK6V5w4+aUvfSm4sLw1twI4IvmDHZ852GXTpk1h3mfNmiV333232Xu3AyzbdeTQxU5P19JOSyK5nnZ6upZ2WhLJAZatnhbRHGBZqNgWA/hD0XAcP2y2SBscNWqU4RN2hbJ2YLEJnzdvngDgou2YY44JMMGyVQNg4bh6+umn27l7cI1RO8e6OcCyUxTHXNSdtWXLlj2CqzOLz5Wc3GnX692RHGDZqBpNIYw7sBrxFMJPf/rTQiokfwCgGD3OQ1Iib731VrnooovkmmuusREuI1Gok8h7Le5X5o+6V5UeVJKRoXk3iijAHxn69OnT7goOfKFkAs7nGTNmmOjnAMtExlwQ39ja6ela2mlJJNfTTk/X0k5LIjnAstXTIpoDLAsV22LgEqAgMX9h5y/RjQCwgAY4l0jbolGzRF1YjQCw2BzOmTNHgCGcdDdo0KDQfwdY+Rf2ihUrgj4466ZMmWK4+isLxWvnjTfeCH/RB6TqyZfRqKQXKtAiXcUyNbSc3jvAKke1Pe9pNoBFqiAfwG4A7T777BNcep/61KdCkfpmaziuvv/974f3FNI9hwwZ0mxD9PGkUADXrL6mU9xW8FIHWBYq7o7hG1s7PV1LOy0dYLmWtgrYRnOAZaunRTQHWBYqRgAWJ99hoQesZB1gAQlwLvFDmFpEpAFw0qD+5TTrAItfbCnYDvygXhf1N9gwLliwwAFWgXWdVYAV7W60BhbrEailJ0rqdaSSsWFWoEVh+Fo3B1g2ijcbwLJRpTGi3HHHHfKP//iP4ecH/z7ttNMao+Pey6oowHv30KFDQ/rg7bffnugZ8cMa4je98MILwc1IIyWa36u8la8A5RYeeuihEIATQ/ndyVt5CriW5elW6C7X005P19JOSyKRDTBp0qQQlJqPmCW81VcBB1iG+gNSGgVg4RDjr+WkfwADcONQlwUnU9YBljrdeEOhka5D0VggBr8MO8AqvKgbDWCxEWK+ga16sqG6BaOjxOWiMIv1UAt3lgMsmzdPB1g2OtY6Ck5O6l7xRwNOH7z22mtr3QV/XsYUwGFIqiwHFSQt5J7mdGZO8eQEW2+ugCvgCrgCrkCtFMCUgoveAVatFC/9HAdYpTVKfEWjACyOcecvmfQX6MMvmmz6aVkHWNQWo+/8VZZGDQ4K5ZM+SHOAVXy5NiLAio8I6AqAVaDF/6ONtRB1Z3Xp0iXxazjNhQ6w0qhV+FoHWDY61jIKf6g59thjw6ElRx99tPBa0PfgWvbDn5UdBTgl9Nvf/rbccMMNcsEFFyTumAOsxFL5ha6AK+AKuAJ1UMABVh1EL/FIB1iGc5J1gEX/ABjk8tIo0A68ilrIswyw2DThGnv55ZdD/0lVGDt2bLuTBh1gNT/Aio6QNU0Rf4VZegpl9BrWedSdlWbDVExNB1g2b54OsGx0rGWUf/7nf5Yf/vCH4XXFe/LgwYNr+Xh/VsYUuOKKK+Tyyy+X73znO3LxxRen6p2nEKaSq+KLPbWoYglzAVxLOy2J5Hra6ela2mlJJE8htNXTIpoDLAsV22JkGWDhXKJeFJtFGjZ80gbjfzXPKsDavHlzqNdFoW8a4IqC8/HmAKtjAaz4aIGcCrNwabGeo43T0aLurEpOS3OAZfPm6QDLRsdaRaG20Yc+9KHwh4P/+7//k+nTp9fq0f6cDCqg8AqAddlll5n30Iu420rqhcft9HQt7bQkkutpp6draaclkbyIu62eFtEcYFmomHGARYoVJ/Wxsafx1/Jx48blrROURYBFjRXgFeOgthEnenE8fb7mAKtjA6zo6IG2OLIUaOU72ZDUWVwkAF3qaKVxZznAsnnzdIBlo2OtonACKHXoOBWUGlhJGmllSa9NEs+vyYYCV155pVx66aVyySWXCP+uRnOAZauqb2zt9HQt7bR0gOVa2ipgG80Blq2eFtEcYFmomGGAxQ9Y4I9u3seMGROcS4U26lkDWOvXr5d58+YJMIJaRqQ87rvvvgVnzQGWA6xCCmzZsqWdO2v79u3tLmV9aarh/vvvL6XcWQ6wbN48HWDZ6FirKGkgr/bp/vvvlxNPPLFWXfTn1ECB6667LhTvP/XUU/M6r4488kiTXjjAMpExF8Shi52erqWdlg6wXEtbBWyjOcCy1dMimgMsCxUzCrD4K/ns2bOFjTvOJYqd9+vXr+iIswKwSMfklKulS5eG/u69994BXvFX/2LNAZYDrCQvaYAorw91Z2lqqt7LJh1QqkCL9RffuDvASqJ06WscYJXWyK9wBbKmAECS98BCjZ/hFs0BloWKu2M4dLHT07W009IBlmtpq4BtNAdYtnpaRHOAZaFiBgHWxo0bZe7cuYLLBCfJIYccIrhKSrUsACzgwuLFi2Xt2rWhu9QsIv2klCOGax1gOcAqtcbzfZ9fRPVkQz6zBqON0zqj7ixqxznAKkfpPe9xgGWjo0dxBZpRAZ2iBkwAACAASURBVAdYtrPq0MVOT9fSTksHWK6lrQK20Rxg2eppEc0BloWKGQNYq1evDgCIhmPpsMMOK+lcUhnqDbB4PuBt06ZNoUsDBgyQiRMn5q3XlW/qHGA5wKr0JQ30pe4a7ixgFgcIRBtOLOoAcQ0uA5yN1NDKYps/f354LVH3btSoUVnsYjhYAqclLrepU6fKmjVrwmuexskvI0aMyGS/vVOugCtQfQUcYNlq7NDFTk/X0k5LB1iupa0CttEcYNnqaRHNAZaFihkBWGymlyxZIgAsGo4rnEvU9kna6gmwOPaVlEcKb9MOPPBAGTlyZKrC2g6wHGAlXetJrwNgaaoh0CruzuL11bt37+DQ4jXXuXPnpKGrfp0DrKpL7A9wBVyBKirgAMtWXIcudnq6lnZaOsByLW0VsI3mAMtWT4toDrAsVMwAwMI1gnOJ1EFa//79g4sh7Wa6XgDrtddeC8XmgVg4XOj7wIEDU8+OAywHWKkXTYobeJ29/PLLAWjhHIo3as0BsTTdsHv37imi21/qAMteU4/oCrgCtVPAAZat1g5d7PR0Le20dIDlWtoqYBvNAZatnhbRHGBZqFhngEWRdpxLFKWmkXJDulA5p0XVA2C9+OKL8swzz4R6XdQWwjUGACinOcBygFXOuinnngceeCC4sUhz5RdZTSmMxiKFV2EWaYcArlo2B1i1VNuf5Qq4AtYKOMCyVdShi52erqWdlg6wXEtbBWyjOcCy1dMimgMsCxXrCLB69uwZnEv8IAVYTZgwQQYNGlT2qGoNsPjldNGiRaGWEG4VThrcZ599yu6/AywHWGUvnpQ3xou489pRdxYOLcBytOGGjLqzunXrlvKJ6S93gJVeM7/DFXAFsqOAAyzbuXDoYqena2mnpQMs19JWAdtoDrBs9bSI5gDLQsU6ASzqQ1Hvio0zzqUpU6ZUXEy6lgBr+PDhsnLlyqDevvvuG05K5LS3SlqtABY1j3DfkPLIKYkU8V62bJmQCkntriFDhlQyjKrdu2LFClm1alXoM+sliw0nIVCWNm3atCx2MfSp2CmEANk33nhDcBcCs6jrFj9WnqLl6s5i/VfDneUAK7PLxzvmCrgCCRRwgJVApBSXOHRJIVaJS11LOy0dYLmWtgrYRnOAZaunRTQHWBYq1glg4bhiU4yTA+cSbqxKWy0Blva1b9++4SS3tPW68o21VgCLvpLymK/16dMnpHBWCuMqnct89zvAslO1GMCKP2Xbtm3hREM92XDr1q3tLmE9ARUVaFmtHQdYdvPtkVwBV6D2CjjAstXcoYudnq6lnZYOsFxLWwVsoznAstXTIpoDLAsVawiwAFb33ntvcF3RevXqFZxLVulI1QZYmzZtyrlr6P/QoUNl7NixZdXrqgfAolbXhg0bwqOBDhTLx12jJydG+0QqpAIJ5qkaDpu0y9cBVlrFCl+fBmBFo/AaxqmnJxsWWzs4+1g75dSz45kOsOzm2yO5Aq5A7RVwgGWruUMXOz1dSzstHWC5lrYK2EZzgGWrp0U0B1gWKtYIYJGytmDBAlm3bl14Io6rqVOnhvRBq1ZNgEVK1VNPPRXS7miAq2HDhll1PcSppgML3efNmxeeA4w6/PDDg8uKf6Ob1iLj/8xVtDFHUYdNly5dTMedNJgDrKRKlb6uXIAVj4wbS91ZQC2F03oda0dBKGsozdpxgFV6Hv0KV8AVyK4CDrBs58ahi52erqWdlkRyPe30dC3ttCSSAyxbPS2iOcCyULEtBs4KNqOzZs0KtW+oUUUqmUUjBQn3DxtdbaTdcQKaZasWwKK4NSclMg5tp5xyStnOkkJjrgbAYl4BP7yBacMZQw0p5htgxQfzjpuGeefEOXXY4LaJN1w1CiUAkeU6bNLOvQOstIoVvt4KYEWfwFpjDVmtHQdYdvPtkVwBV6D2CjjAstXcN7Z2erqWdloSyfW009O1tNOSSA6wbPW0iOYAy0LFthjVAlibN28O7h4cTDQcGYCmyZMnhxQ2y1YNgLV+/frgXMKV1NramoNYjQCw6PPChQvl+eefDzKTqomDjLpdkyZNyguw4kXcgVwKJACQcYcNmkQdNvy/Ws0Blp2y1QBY8d5xkmG0dlbateMAy26+PZIr4ArUXgEHWLaa+8bWTk/X0k5LB1iupa0CttEcYNnqaRHNAZaFilUEWHoimzp9cF0tWbIkQJSsAyyAHqcMPvvss0EhakLhSMNJRss6wMItNmfOnACfaIMHDw5OqTVr1qQCWNElBhCLOmxef/31PVYgJ9Ip0EIzS3eWAyy7F3wtAFZ87fB+oDBUgXb0mvjaIeWYunOsXSs3qJ2CuyIBh5cuXSqcykhKNK+viRMnhu8tX75cRowYYf1Ij+cKuAINooADLNuJcuhip6draaclkVxPOz1dSzstieQAy1ZPi2gOsCxUbIth7cCiWPjcuXODc4m6NxRrJzXtgQceyDzAos+LFy+WtWvXBnUAMqTcsemeOXNm+FqWARZv/rjeFDCNGTMm1OsCHq5evbpsgBVfboDIqMMmfrIh8x51Z1Va78wBlt0LvtYAK9/aUZhFim6+tUNqK2ts4MCBwhrOYnOAlcVZ8T65AtlQwAGW7Tz4xtZOT9fSTksHWK6lrQK20Rxg2eppEc0BloWKVQBYq1atCrCEhjPh0EMPlR49eoT/Zx1gkeaEc4k6YDQ2zxMmTAh1ol555ZXMAyxcLtTrIn2LPuN669evXxgLUM4SYEWXH9APfRRKkDoabTixog4b1kVad5YDLLsXfL0BVpq1w7XAb2q3AUR5L0m7duyUax/JAVa1lPW4zagAPyeOOeaY8HP085//vPzwhz8sOEzcjPzs5Q8xf/7zn+W9731vw0niAMt2yhy62OnpWtpp6QDLtbRVwDaaAyxbPS2iOcCyUNEQYOHiUpcPYffff385+OCD2508lmWAhdsD55IWLidtiRQg3SxnHWBt3LgxuN5ws1CLCtcbc6CtmgArvhT55SjqsImfbMgJiAok6GPnzp1LrmYHWCUlSnxBlgBWobUDCCf9ON6o5abOvqRrJ7EwKS90gJVSML+8wytAXUZ+NvHHoocffliOPvrovJpMnz5d7rrrLjnzzDPlV7/6VUPq5gDLdtocutjp6VraaekAy7W0VcA2mgMsWz0tojnAslDRCGDxyyjFzoEoNAq0UygcF1C0ZRVgUdsJeIVzCWBF3+OnJGYZYOGsAlDRcKjgesPlFG21BFjR5wLUou4sfnGKNvQGRCiUULdefHk7wLJ7wWcZYOkotYg7oBNohSsSyBxtvL/gziq1duyUax/JAVa1lPW4zazA5ZdfLldccYWMGzcu1JXkDxrRdsstt8gnPvGJ8EcOfm7xuRGbAyzbWXPoYqena2mnJZFcTzs9XUs7LYnkAMtWT4toDrAsVGyLUUkNLKAP8AcIRBs5cqRwml2+NJ8sAiwKRZM2qM4lXGPveMc79lA3iwArietNB1IvgBUXkvRCdWehadyd1b179xyQAE6oO8sBlt0LvpEAlhZxZ62rsw+Yxdrha9FWaO3YKecAq1paetyOowDOSn7OLlq0SC655BK58sorc4PntQ3Y4jMg6+Mf/3jDCuMAy3bqfGNrp6draaelAyzX0lYB22gOsGz1tIjmAMtCxQoBFul2wCucEQAralYMGjSoYM+yBrAo1M4v0WyE2fziXOL0vHwtawAL4EbKoLreqHWFc6xQOl5WAFZUW8ZAEW+AFhsWYGi04bBRdxZF9HG8ABcpqp/Fpidv0rdp06ZlsYuhT40IsOJi4vrUtcP6KbZ2cGjx+rZu7sCyVtTjdRQFqINFPSx+XvE7BD+7aDivAFekEP7pT39qaDkcYNlOn0MXOz1dSzstHWC5lrYK2EZzgGWrp0U0B1gWKlYAsNg0Yv9nI8kJc/xFlY1isZYVgAWwevbZZ2XlypWhuxQYpy5HPJUhOpYsASw26xRrB5jQqNVFza5ixa2zCLCi+jIn6s4CZjG2uMOG60knGzt2bEgdi6eoGr4kygrlAKss2fLepCmE6sAqFpl1AuBUZ1++tUNqqqYaWq0dB1h28+2ROp4CX/jCF+SGG26Qww8/XB5//HH561//Goq180ckamUNGTKkoUVxgGU7fQ5d7PR0Le20dIDlWtoqYBvNAZatnhbRHGBZqFgmwGLjtmDBggAYAAo4l3r27FmyR1kAWLh+2ByvX78+9Ldv377htL5ShcSzArA4lYm/WPMLCMBq/Pjxwia/VMs6wIr3HzD60ksv5aBEvKA38xWtncU6rHdzgGU3A2kAVjlrByefAq1i4LrYiBxg2c23R+p4CvCzbOLEieF0XOpi/fznPw//BmpdcMEFDS+IAyzbKXToYqena2mnpQMs19JWAdtoDrBs9bSI5gDLQsWUAAtgtWzZMlm+fHm4s1evXsG5lBQe1BtgAUFwLgGjaMOGDZMxY8YUdS6pzFkAWFHXGwAH11vSAreNBrCiy5t1t3TpUlm3bl1w+wG34o2/2iuQYF3Ww53lAMvuTakSgBVfO2yUo+4sq7XTbADrvvvuCye+PfbYY0J6NU61ww47TC699NLwRwpvroC1An/5y1+C60obpxJyOmE93r+tx+YAy1ZRhy52erqWdlo6wHItbRWwjeYAy1ZPi2gOsCxUTAGwKLaN6wqIQOvdu7dMnjw5AIWkrZ4AixQjnEukqdFwLqVJUag3wCrX9aZz08gAizFEi7hTay3qztq2bVu7JciaVIcNn8t12CRd13qdA6y0ihW+3gpgxZ/AWgFm6foptnYAol26dCnYyWYDWKeffnrQhs+8P3LAxXXXXSezZs2Su+++O9N13exWnkeqtQJnnXVWAKe81jhQhSLuzdAcYNnOokMXOz1dSzstHWC5lrYK2EZzgGWrp0U0B1gWKiYEWGzycC5RNJkG+OGXzGI1l/J1r14Ai37Tf8aBcwnw1qdPn1QK1gtg4T7C8YbzjZbW9daMACtaxB19OExAHTZ6GmZ0cklvjbqz0q7bpAvFAVZSpUpfVy2AFX2yrh1qrrF+WEfxVmztNBvA4kCI+Psi7jVOlSXVa8aMGaUnzq9wBVIq8F//9V9y7rnnytChQ2XVqlUp787u5Q6wbOfGoYudnq6lnZYOsFxLWwVsoznAstXTIpoDLAsVEwAsHEs4l3Aw0SigTepdOa0eAOuFF16QefPmhXpdOHFIhQECpW31AFgWrrdmB1jxeSRNNOrOiqcbtra25txZQC3+b9UcYFkpKaFOHQ6gJEXcrZ7K2lEQyhoqtXYAPqS27r333jJ16lRZs2ZNAD00oDOHKzRD40RNhXXNMB4fQ7YUcICVrfnIam8cutjNjGtpp6UDLNfSVgHbaA6wbPW0iOYAy0LFEgALaINziY0dNSlwLlH0vNxWS4BFTSROGeS0QRr/B1517969rO7XGmDhFuOURzbSNDbyuN7KrQ3STCmEUQdWsckEAOKqUYcNbpJ4A2aqOwu3TSXuLAdYZb208t5UD4AV7QhrBzefAq18a4faf2+99VaoAXjUUUeFulHNBrBY0zhjgFi333673QR7JFegTQEHWL4Ukijg0CWJSsmucS2T6ZT0KtczqVKlr3MtS2uU5goHWGnUqs21DrAMdcadBKSi1gmb/ZEjRwaX0ty5c4WNHLUpKNZOUd9KWq0Alm4msfDTABQUPE9Trys+zloCLEBb1PVGoXlcb5XAlY4IsOJzuGXLlnYOG06kjDbWOTWzKIzPCYdp3VkOsCp5d2h/b70BVtq1c9tttwXYTK02TlJbtGhRUziwPvGJT8itt94qM2fO9ELudsvbI0UUcIDlyyGJAr6xTaJSsmtcy2Q6Jb3K9UyqVOnrXMvSGqW5wgFWGrVqc60DLEOd4wAL4IPzgEZ6DEClR48eFT+xVgAL0KYnDQ4aNCgUJC7XuaSDrhXAws0BNFTX20EHHST9+vWrWHsHWO0lRGOAkzpsNEVWrwIW7rvvvjl3Fq+DUgDRAVbFyzQXIGsAKzoyXTvU66G+Hu+fn/nMZ4SUQm2kFH7wgx+U6dOnC4cOlFo7dsrZRfrmN78p3/72t+WGG26QCy64wC6wR3IFHGD5GkipgG9sUwpW5HLX0k5LIrmednq6lnZaEskBlq2eFtEcYFmo2BZDAdZTTz2VA1d8CzcKzqW0TpRCXasVwNLnjxo1KrggLDaPtQJY2ncr15vGc4BV/AVDKli0/hGQItqon6aphriz8rn5HGDZvSllGWDpKLUuFK9VHEr33HNPLuU6qgSn+uHQaqR2xRVXyOWXXy7f+c535OKLL26krntfG0wBd2A12ITVqbu+sbUT3rW009IBlmtpq4BtNAdYtnpaRHOAZaFiBGBRrP3BBx8MJ/XRBgwYEOq5VOpcinazmgCL9J0nn3wyPA5ghXOpf//+ZipVG2BxfPj69etDfy1dbw6w0i8B4BXzrUCL10a0sb5w+SnQwp3I1xxgpde60B2NBLDyFXE/55xz5NFHHw1//brmmmvkoosushOnypEUXgGwLrvssio/zcN3dAUcYHX0FZBs/A5dkumU5CrXMolKya9xPZNrVepK17KUQum+7wArnV61uNoBlqHKvGHgIKBoMQ2HyRFHHGHiXKoFwOK0MgCQ1jQCvJE6aNmqBbBwvy1ZsiTUzaEBDE888cRQd8yyuQOrfDUBWHqyISljcXcWaZ/ALA4IWLZsWXgQRa+z2gDVvFY4lIF+Z7E1OsDSUwj55YFU1D59+mRR5j36dOWVV8qll14ql1xyifBvb65AtRVwgFVthZsjvm9s7ebRtbTTkkiup52erqWdlkRygGWrp0U0B1gWKrbFWLBgQTj2XRtF3Em/s27VcGBxdD0Fk6PtmGOOEU6Us2zVAFhvv/22zJs3r13tHNw8xx9/vGXXQywHWDaSAn6AWOrOIvUwX+P1AxyyqB1n0/PdURxg2SiqKYT5HFgKsGyeVJso1113nVx44YVy6qmn5nVeHXnkkbXpiD/FFWgCBThEhtODaZyGXI3fqZpApsRD8I1tYqlKXuhalpQo1QWuZyq5il7sWtppSSQHWLZ6WkRzgGWhYlsMNuXUv+KNAxdWIwAsnEtLly4VCinTcDmQwkVrBIDFiXicNKiut969ewtOMjbDxx13nOHs7grlAMtc0lC8G3eWwiwgJ1+LNgCWphqSdmiZklvuiBxglatc+/uaDWDh/GRtFGrxtW2jokdxBZpTAQdYtvPqG1s7PV1LOy2J5Hra6ela2mnpAMtWS6toDrCslBQJm25OvZs1a5a8+OKLmQdYADecSxs2bAgqcErfuHHj5P77728IgPXaa68FeIV7h9pJnFJGwwnnACv/wl6xYkWAlRwsMGXKFMPVbxeKNENSWWkUfQdSRlvnzp1Deq4CLVIP69EcYNmo3mwAy0YVj+IKuAIo4ADLdh34xtZOT9fSTksHWK6lrQK20dyBZaunRTQHWBYqtsVoJIAFaAP+qNtq+PDhMnr06FDTZ8aMGZkHWLh1nnnmGSF9kJPsgDEHHHBA+GXXAVbhRd0IACtaxP1d73qXvPHGGzl3Ft+LO1iAlQqzcBDWyp3lAMvmzdMBlo2OHsUVaEYFHGDZzqpDFzs9XUs7LR1guZa2CthGc4Blq6dFNAdYFio2GMB6/fXXA7zihy/OJVxXQ4YMCaMACGUdYLHhBVIBMnDfHHrooblaXQ6wii/oRgNY8SLunO4ZrZ0FiI023Fm4yxRo4eCqVnOAZaOsAywbHT2KK9CMCjjAsp1Vhy52erqWdlo6wHItbRWwjeYAy1ZPi2gOsCxUbCCARXoWziVAAJt9nEvUjdKWZYAFsOJ0Oi2U36tXLznkkEMCxNLmAKu5AVZ0dKwHYCzpujjytA5a9Jp99tknB7NYL5buLAdYNm+eDrBsdPQorkAzKuAAy3ZWHbrY6ela2mnpAMu1tFXANpoDLFs9LaI5wLJQsUEA1rp162T+/PnBuYQzBecSm/poyyrA2rFjR3BdMQYa0G3y5MkhfTDaHGB1HIAVHyluLAAtMIvPQNpoY61E3VldunSp6NXvAKsi+XI3O8Cy0dGjuALNqIADLNtZdehip6draaelAyzX0lYB22gOsGz1tIjmAMtCxYwDLIAVqWO8AGk9e/YM8Cpf8essAixABK4xoASNdEfSHkl/jDcHWB0XYEVHzprHkaUnG1LwP96At5pqyGsi33oqpqYDLJs3TwdYNjp6FFegGRVwgGU7qw5d7PR0Le20dIDlWtoqYBvNAZatnhbRHGBZqJhhgIVzaeHChcImkUahc9IG484llSFrAGvz5s2hXheFvGljx46VoUOHFoQNDrAcYOVTAHeWwixAKOs82lpbW3MwC5cW/y/VHGCVUijZ9x1gJdPJr3IFOqICDrBsZ92hi52erqWdlg6wXEtbBWyjOcCy1dMimgMsCxUzCrBwLs2ZMyds3GmDBg2S8ePHF60DlCWA9corr8js2bMF+EDtIlIG+/btW3TGHGA5wCr1kgbqRt1Z1NGKN04zVHcWdbTyubMcYJVSOtn3HWAl08mvcgU6ogIOsGxn3aGLnZ6upZ2WDrBcS1sFbKM5wLLV0yKaAywLFTMIsPjBinNJN+ejR4+W4cOHl0yTygrA2rBhg8ydO1eADdQqolj7fvvtV3K2HGA5wCq5SGIXvPXWW+1qZ23fvr3dFaw/hVm4s9S96AArrdL5r3eAZaOjR3EFmlEBB1i2s+rQxU5P19JOSwdYrqWtArbRHGDZ6mkRzQGWhYoZA1h///vfg3Npy5Ytwbk0adIk6d+/f6KR1htgUbto9erVsmTJktDfvffeO9Tr6tGjR6L+O8BygJVooRS4CGCK80/TDUlhjTacWOrOWrlyZQCsOAMBXFlsHNqwadMmGTx4sIwaNSqLXQzpzUuXLg2v9alTp8qaNWtk4sSJoa+cODpixIhM9ts75Qq4AtVXwAGWrcYOXez0dC3ttHSA5VraKmAbzQGWrZ4W0RxgWaiYIYC1cePG4FzCRUIdH5xL+++/f+JR1hNgAa8WL14cNrA03C4HH3xwonpEOkAHWA6wEi/2BBfyC6rCrJdffjkAq3gDXg0cODC8zjp37pwgau0ucYBVO639Sa6AK2CvgAMsW00dutjp6VraaekAy7W0VcA2mgMsWz0tojnAslAxIwAL5xIAiIZjCecSroY0rV4Ai+cC3nCL0AYMGBBcGDjI0jQHWA6w0qyXNNcChaPuLH55jTbcWUAsTTdM6hpM04e01zrASquYX+8KuAJZUsABlu1sOHSx09O1tNPSAZZraauAbTQHWLZ6WkRzgGWhYp0BFs4lUnBWrVoVekKtKJxX1O5J2+oBsKhBRMojhbVpI0eOlAMPPLBkva58Y3OA5QAr7Zov9/oHHnggOLIo8s4pmbwOo6179+45mMVrsh7uLAdY5c6u3+cKuAJZUMABlu0sOHSx09O1tNPSAZZraauAbTQHWLZ6WkRzgGWhYh0BVp8+fWTevHlC0XNav379Qs2rcjfLtQZYFJmn2DwQCwcLrivSscptDrAcYJW7dtLeFy3iDqAixZB0wxdffDHUn4s2nIRRdxZwqxbNAVYtVPZnuAKuQLUUcIBlq6xDFzs9XUs7LR1guZa2CthGc4Blq6dFNAdYFirWCWCNHz8+FECmaDuNUwY5bRAQVG6rJcA67LDDZM6cOcIzOdmNeleVFsOuFcACHAItKPJNrS4+1EWGe2zIkCHlTkFV71uxYkVw6tHfKVOmVPVZ5QZnPQM1adOmTSs3TNXvK3QKIU4s1oXCLMYTd2eRXqiphqyjtKmySQfnACupUn6dK+AKZFEBB1i2s+LQxU5P19JOSwdYrqWtArbRHGDZ6mkRzQGWhYp1AlikCG7dujUAK2AWJ41V2moJsOg3G/tu3boJMItUrEpbrQBW165d27lscLwxHvQbOnRoSIPMYnOAZTcrhQBW/AmsiZdeeilXDJ7XbLSxdqLuLF4PVs0BlpWSHscVcAXqoYADLFvVHbrY6ela2mnpAMu1tFXANpoDLFs9LaI5wLJQscYA67777gvgisbmFydN7969TUZSbYBFmtUTTzyR62uvXr1CsXmAkEWrNsBasGCB8AxtFMmn/lG88XV12Oy7775Vc9ik1cwBVlrFCl+fFGBFIwBsSZvVkw3VPRm9BpCra4fXRyXuLAdYdvPtkVwBV6D2CjjAstXcoYudnq6lnZYOsFxLWwVsoznAstXTIpoDLAsVawiw1q1bF2pe0VpbW+WII46Qnj17mo2imgCLgtekhrF5p5GGd9BBB4X0QatWTYAFqHr88ceDy4o2duzYMAY9ne7ZZ5+Vbdu27TEUICMpewolrGBdOZo5wCpHtfz3lAOw4pFYL1F3Vnz98NqIrp20BzM4wLKbb4/kCrgCtVfAAZat5g5d7PR0Le20dIDlWtoqYBvNAZatnhbRHGBZqFgDgIVzY/ny5bJs2bJcj0kbtK61VC2AhWPsmWeeCYWutZ188skVuUvyTV21ABaQgf4rYKBuEWmPWnweSKU1sAYNGhTgIqBOT1aM9hXgGHXYVFKzLO3ydYCVVrHC11sArGh0XuOvvfZazp1lsXYcYNnNt0dyBVyB2ivgAMtWc4cudnq6lnZaOsByLW0VsI3mAMtWT4toDrAsVKwywMK5tHDhwlCwnUZKEV+bPHmy9O/f33AEEtxFM2bMCDGPOeYYE3cXBa1xXsVT7U455ZSKCs7XCmDhegMEABgAVTiu+vbtG+qOcdocAIqPuXPnBgBB/SvqYNEAd1GHjbq3tO84bBRm4bRJ67BJO/kOsNIqVjuAFX8Sa0dTDVlD8bUDJI26s/h/vDnAsptvj+QKuAK1V8ABlq3mDl3s9HQt7bR0gOVa2ipgG80Blq2eFtEcYFmoWEWAheMH5w8bWBqF2jdu3BjASSMArFdeeSXAK8YB/AHukGpHyzrAAlgBfHjjouGcoiYRTZrffAAAIABJREFUIJHUQQCWQgU+M0/My7BhwwQXFlAL2KifiYerRqEEsCveiK9Ai+dZu7McYNm94K0dWMV6BrBmvbz44oth/VBHq9DaOeCAA8KBCKwdB1h28+2RXAFXoPYKOMCy1dyhi52erqWdlg6wXEtbBWyjOcCy1dMimgMsCxWrBLD44Qj80c3qmDFjAhxh40zqWtYB1vr160O9LjbfOIso1g7EmTlzZuYBFn1etGhRrmA7UAC9eRNbs2ZNAFPqfunevXuAcjjNaNT1AkTRGK86tBRkaVFuYFfUYYOzK9pw1ETdWfkcNmmXrwOstIoVvr6WACvei1Jrh9cb65M1CTQFfI8aNcpu8IaRAMJLly4VDj6YOnVqeH1NnDgxPIG06REjRhg+zUO5Aq5AIyngAMt2thy62OnpWtpp6QDLtbRVwDaaAyxbPS2iOcCyULEKAIvTyYBXpBEBPIAi/fr1C0964IEHMg2wgDarVq0Km1IabpBDDjlEevToITiysg6wcIvNmTMnV2weN9W4cePCWHC/AeUYY75G6iB1yfJ9X2EW98XdWQAz5lyBVjzdkuuj7ix12KRdvg6w0ipW+Pp6Aqxor0qtHa7l4ADWMUAUUGTt7KtEVQdYlajn97oCza2AAyzb+XXoYqena2mnpQMs19JWAdtoDrBs9bSI5gDLQkVjgAUkoZ4SjhxcN8Cf/fffP9fTLAMsNtOLFy+WtWvXhv7iAjn44IPDOGhZB1hx19vo0aNz9awYGx+kC1KMno13tCi9TpDWtWLOKPbO2IsBLXVoASrVnYXDTmEWz4i7swASaIszjOckPcnRAZbdCz4rACs+oujaIeUw3lg76uxLs3bslGsfyQFWtZT1uK5A4yvgAMt2Dh262OnpWtpp6QDLtbRVwDaaAyxbPS2iOcCyUNEQYOFcWrJkSYiIY4mT7vgcbVkFWIAdwNumTZtCdwcMGBBSgRTKZB1g4YDiJEHSs+gzfcf1BrQCQPFZnVP8Uq3zBBDo3bt3SNXKd3IczilgE7AA90u+FnVnad0sfRbPBfwp0NJURY3DdYAyhRKsl0IOGwdYdi/4rAKs6AhxCwKxcOyxjipZO3bKOcCqlpYe1xVoNgUcYNnOqEMXOz1dSzstHWC5lrYK2EZzgGWrp0U0B1gWKhoALAAGQGT16tUhGrAD51K+U+myCLBwfQB/FOAceOCBoWB7HKRk1YEVd72h/b777hs2/TQ+K4hbtmxZbp64ZsqUKbl50tpEWmw738lxgCZ1Z+GcKuXOihaCpy9ACD3ZEHeW9lGXcrdu3do5bCier80Blt0LvhEAVryIeyVrx045B1jV0tLjugLNpoADLNsZdehip6draaelAyzX0lYB22gOsGz1tIjmAMtCxQoBFpADpwQQhda/f3+ZNGlSO+dStJtZA1icjka9LiAWwIq+477K17IIsCgaTcF2Gu4lUjYpzB6HV4CmBQsW5Oapb9++MmHChHC6Yr6mtYmAWXzkOzkOAKZAi2fma8XcWaQWqjuLZzAH0Qb8irqzKKyPyw9HGOAti03rv9G3adOmZbGLoU+NCLCiYrJ2AKDq7Mu3dgCtrE/WS9wJajUxnkJopaTHcQWaTwEHWLZz6tDFTk/X0k5LIrmednq6lnZaEskBlq2eFtEcYFmo2BYD0EDR9VmzZgVggQOp1MlfOHZwLrFpp3HiFvcUK7KcJYDFOJ955plQowk3Ec4lNryFWpYAFvNFoXmADg3QQ//VFaWpgwAqLeyu88RpkLjM0hTDBhCoMwtoEK9rhdtOYQFgi+emcWdxLQ4bBRJoHb+fsQFMe/bsGUBdIfhm+LJIHcoBVmrJCt4Qd2AVujDJ2gFgaZoqr5VoanAlPXaAVYl6fq8r0NwKOMCynV/f2Nrp6VraaekAy7W0VcA2mgMsWz0tojnAslCxTICFIwfnEj8EASG4eTgprFTLCsCiUDvOJTa/uIcOPfTQUGunWMsKwAIe4XrbsGFD6C61rqh5xTxovSu+ziYdKASk03kaO3ZsonkqpoPWtVJ3Vr5TB6PuLNIC87W4O0uhAp+12LwCLWBptHGNOmwAE4UcYKXWo/X3HWDZKZoUYMWfWGrtAD6ja6fQ+kwyEgdYSVTya1yBjqmAAyzbeXfoYqena2mnpQMs19JWAdtoDrBs9bSI5gDLQsUyABZQASjCRhFXDOlcnCiXpNUbYAFNeDFTT4kGaMHNQzHzUi0LACvuehs+fHhwU9H0pEEtoE5/58yZE+aJTftBBx2UeJ5KaRH9Pr8IKcyivlWhulZAA/QGPsXdVfr/6KmGOg6+ByRj3vKdnEhfKDCvDht9RpoxWF3rAMtKSZFyAVa0B7p2FIQyP/G1V8nacYBlN98eyRVoNgUcYNnOqEMXOz1dywRaPvKIyLHHJriwwhTCFM9J1JkGv8jXpu0EOsCy1dMimgMsCxVTAiw2bNRSYhOIcwHnEildSVs9ARbOJTbF1FKiUQcKqJM0Fa3eACvuehs3blxwU+U7aZAxLly4MMwTcI70wjTzlHQ+49dpbSIFWvwgijagFCBLTzYsBA7zubNIl+SDFDDGrVCC1NdoYz6Jr0ArCZwsd7zx+xxgWSlpA7DivSGdFgjK+gS2Vrp2mg1gURPwyiuvDOCbP1Kg02WXXSaXX3653cR6JFeggyjgAMt2on1ja6ena1lCS37mXXGFyPe+J/LVr5YUvmw9r75a5GtfE7nsMhH/ORt0LlvLkrPUMS9wgJW9eXeAZTgnpWpg8X1OsFu+fHl4aq9evYJzKW36Tb0AFhtVNmTq4KEO1JgxY1LVgaonwGKzTf/ZgANocL0BaKLwSlPwgDw6T6RFAq/SzpPV0sI5BWhiI5zv1EFS/7QQPGuqmDuLgvWkfgLAJk+enLsWsKf1ufQkyWj/0UBhlj7DanwOsKqlZHUAVrS3vKclXTs4TFk78bpxzQaweO/gvYXX1+jRo+Wmm25ygFW9Je6Rm1wBB1i2E+wbWzs9XcsiWuKIOu643RckgFhl6anwSp/08MOJHV92KyF7kcrSMnvDyEyPHGBlZipyHXGAZTgnxQAWkATX1bp168ITe/fuHTY4pA+mbfUAWEAU6nVRD4qGc2no0KFpux5OzJs5c2a475RTTkkFv5I8jF920ZmUpuMiPzzRHeeYuqkAh0AZhVd8XcHPkiVLcvMEtMFhVs48Jelv2mtwZwHi1J1V6OS4qDtL0734vHjx4nA/DixqftEYt37wfwCfOrO4lv9HG1pE3VkUn7ds7sCyU9MihTBNb4DcrBnWT9K102wAK5rKy+uU93p3YKVZRX6tK7BbAQdYtqvBN7Z2erqWJbSMw6USECu1ninj28189iOl1jL7Q6prDx1g1VX+vA93gGU4J4UAFgAA5w8bOtqQIUOEQuDlnuJVa4CF64eTEtW5BHjr06dPWcrVGmAxJ9Tq4s2HpqfvAV3i8EoLu+s8DRw4sKJ5KkugFDdpbSKFWflOHdST46hpBShQ9xx1vxgfrVTtLBxZCrRIj4o3NI26s9KczJhvuA6wUiyCEpfWGmBFu8O6KrV2cGS1traG9cVaPfLIIwWXoMJVXJCczNqozQFWo86c9zsrCjjAsp0J39ja6elaJtAyBWRKpWeKuAl62XSXpNKy6UZvPyAHWPaaVhrRAValCkbuzwewgAQ4l/SUOVLuSL2rZJNfS4BFvzmtD9hDHSScS8CQclstAdYxxxwTalgBbmikMEXT5hRgkU6Ik4maNaRD0UaNGhUcZpXMU7kalXsfheYVNLFxjp86qHGBTRStB+LFi3Er0NJC8FoEXmErDpuoO4tnRhswIurO4v9pmwOstIoVvr6eACveK9Zj1J0VXztcv3Tp0lBT66qrrgpuTwdYdmvBI7kCjaiAAyzbWfONrZ2ermVCLRPCpsR6JoyXsHdNeVliLZty9PaDcoBlr2mlER1gVapg5P44wAJebdq0KWzIAACkovXr16/iJ9YKYAFwVq9eHfpLuh3F5qm3VEmrFcDCzUFfgS20wYMHBzeVAhrcVgpncBXhkNN5mjBhgsk8VaJTpfdqbSLgHRuAfKCKOdVUQ1xU6JHmZEMAYNRho/Av2ndgp7qzeF4SIOgAq9LZ331/lgBWdFTRtcNhCQpbL7roouCW5P0S+Pn5z39ezjzzzACek6wdO+VsIrkDy0ZHj9JxFXCAZTv3vrG109O1TKFlAuiUSM8EcVL0qmkvTaRl047efmAOsOw1rTSiA6xKFSwCsBQI4HTBuUTdIYtWK4ClfQVAUJS4HDdNfLy1AlhRGIPrjbRNGhtnPhRescFkkw/QYnyM02qeLOa6khjAu7lz54ax4TJDA5xmjLlQXSuKu/OBFmndWcSOOmx4brTxOlCYBTgrVFfMAVYls97+3qwCrGgvtQYWa/Taa6+VJ598MqzTaBswYIB89rOflW9+85t24tQgkgOsGojsj2hqBRxg2U6vb2zt9HQtU2pZAj6V1NPhVWLBS2qZOJJfiAIOsLK3DhxgGc6JOrAefvjhXMogxcRxLuEIsmrVBFhsHImvDRcZjqRy63XVGmDxJqOnB9LnSZMmSd++fdudNKjwil+MKdhOY344adBynqzmu5w4OjbWJKcnMjYcUDStTaSnDgKM4k3rWgHz9L74NcRRVwxaa9oh/wYSAiu1mLem0GoMro26s3idaCwHWOXMeP57GglgsQamTp0aflE49dRTg3uVVFdObqV95Stfkav5BbaBmgOsBpos72omFXCAZTstvrG109O1LEPLIhDqrfVLZdGffyqt2zfLmMmHS5dR00T2bzssyuFVKrF9baaSq+TFDrBKSlTzCxxgGUrOph3HC0WIaYCDo48+OtQasmzVAljAq1mzZuXqQOHY4bRBy9SdajqwNm7cGFIB1Tl0xBFHBEjCvND4rCCONyOdJyANKUrW82Q550ljMXY2/KtWrQq3UCQbVxn1ywo1rWulxeAL1bXCNYVWOKfSurP4Yaq1sygkr3OifaJ/6s7CiUM9Mtq0adOSDr3m1z344IPB3cbaoe9ZbI0IsOJF3Hn/ueuuu4SadmjdSM0BViPNlvc1jQKk3l955ZXhvZqfu6z1apy26QArzayUvtY3tqU1SnqFa5lUqdh1cRj19QtEJmyQnc/dIy2yM3Jxi8iok0UW9hW56t93f73EaYZl9qqpbvO1aTudDrBs9bSI5gDLQsW2GAsWLMi5f/gSp2eNHj3a8Am7QlUDYFHLiGLz0cLfbBhx4li2agEsanUtXrw411XqXx177LF7wCvAC/ME7KLhzsJhBjRp9AZMoWj9hg0bwlA4KZLT3NKMTWsTKczKd+ogUAxgQ6phIcdaMXcW/VR3FlCLH7TRFk3/xJHDMywhqtU8O8CyUVJTCNWB5acQ2ujqUVyBairAH0n44whQmd9zbrrpJgdY1RTcKLZvbI2EFAm/u9xzzz0h4Mknn1xxjVi7njVApDjEOqmryLF5/tD6yBaRe7fsHpDDq0ST62szkUyJL3KAlViqml3oAMtQak7Neuihh4LLhzePkSNHhtPsrJs1wCJVh7+iAhZw16gDpxEAFqCENEAtNg/sYB7YDB911FG51EEgDnWf+EsxsI7GaZCkKGURjqRdM7iocP8Bhmi459hUhHTJxx6THUcfnTZkuB6gqTCL+lZxd5bWtQJmHbBkiew85piS7ixNN1Q3HPOl7iz6H3dn4WTkBEmgGQ6wNECurEEnvMkBVkKhSlzWjAALxxhpswDg8847T04//XQ544wzghLTp09vmlRlmxXgURpRAXXh8jOmmk5Dd2DZrg7f2Nrp6VpWqOXFn2/vrIpDrDi8wqn13RsqfGjHuN3Xpu08O8Cy1dMimgMsCxXbYvALHZsWQAK/0DUCwFq7dq0sWrQoQAdcS/xF9fHHHw8jyjrAArihtbqpOOERkIITC+hB7TFS0wAlQBLgFW/q/MLNiYSDBg0ynP36hdKx8ZnG2Dh1kdb6ne9I63e/K1u/9S15+8tfrqiT0bpWrO/oqYMH3n67TPjFL2TV//t/8tqXvxzmodCJlXF3loIsPjOnbFi0jlm8w1xDbE03rPRUzEoEcYBViXq7721GgAUcV6geV2nlypUBnntzBZpFAQdYjTOTvrG1myvXskItbzlD5Od/bO+wUogVh1d8/bwPiHz81gof2jFu97VpO88OsGz1tIjmAMtCxQjAwglDHamsAywgwrPPPitspmjUigL4AAhmzJiReYCFM2j27NmiBchJ1wQYvvDCCyFFUBspkBQhB3LpaXwHHXRQcPQ0Q8OxhHsOdxlzx9h69+4dhobzqtt73pMbpgXEimqmda26Xn+9DP3xj3Pfevi735WXxo8P8FBTDVlfOKfitbOif8XX4vo45ICNNFIIcWfxemKu4/fjuFOYhTvL6rCBJGvDAVYSlUpf04wAq/So/QpXoHkUqARg8QeLYo2f6dSzpFHTj5/z3spXgFqnZArQjj/++PDHPm/lKeBalqcbd7X8fY10/c+pu2pexWFV9xaRNyO1sNqg1k5pkS2ffVJ27rvrD7TeCivga9N2dfBHdQ4Fo2H8aBYDhK1KtY3mAMtQbz2FMOsAC5DDL4Lr168Po6cOFOADwECKWNYBFs4f6nWpm2r8+PHCaYk4hOg/KYX8Qh1Pd2OswI7+/fuHz41etJ35o+YV42YsnDRIfapo2+u666TLpZfmvmQNseLxn//CF2TR+98fHG/RBpwCMFEIHgdVoV+aeQ2RdjVv3rxw+4knnpiDUswnaYyabggsjjbWb9SdVe1fzB1g2bx5OsCy0dGjuAL1UqASgJUmhZ86W83yx6d6zZU/1xXIggKD//awHLLmp7u7EodY+p1YWuHsIefL2ncel4UheB86kAL8jPvUpz7lACtDc+4Ay3AyGgFgsenHuaS1koYPH56rlYQUWQdYwAvcOfQTYEHKIzAKKEfTkwb5jMOMzXGhhiuIX4b5wKmV5hdpw2WTOhTrjPQkLK006n0Brwql01ULYhWLC8DS2ln5Th0ELjFvAC2gG84pdVfx1w1NvyKNlXlRd5Z+5lpApsIsdeJFxUQXdWcx19buLAdYqZdu3hscYNno6FFcgXop4ACrXsr7c12BxlRgxMa7ZdLzt7Tv/DWvtXde4cT6SvuDpOYP/ISs6HNyYw7ae92wCjjAyt7UOcAynJOsAyzqc+FcUncMziWKfUdblgEWG13SA9EZAHLIIYcEeAOs4mt8KAjBhbVu3bowNAAVBc2BdrwJFStGrsXCW1tbDVeGXSjGytgUzAGAcM+V6q81xEoTD7iozikODMDaHG1a1wr3FO4rPUWRuaCel7Z8tbMUSpFCGXVn8f9o43CCqDuL9MZKmwOsShXcdb8DLBsdPYorUC8FKgFYnkJY21nz1CI7vV3L8rRc+MJrMvdPN8on//avuwMkdGBtnf4D2T7pI+U9uAPd5WvTdrI9hdBWT4toDrAsVGyLkWWAhQsG5xUbe3Uuaa2krAMsdOXNY9myZaGrOHZwHJE2F4dXwBLSz4AZNPKUx4wZ0859U6wYOffg8om6s6ihlQV3FnCRseE6og0YMEDGjRuX2FmUBjoVe1lUEoe5jLuz4nWteDa1rahrRtoh2iepnRV1ZwHC1J2lp05Gx4TjTt1ZrKdy5tcBls2bpwMsGx09iitQLwUqAVil+uynEJZSKN33vbhzOr2KXe1atqnz8mqRVY+IbHlVpGsvkWHHiuw/dA/pFjz/d7l+xnMyY/EGGdSySR7q8kXp1JK8BpZIi8gX54ns1/4P73Yz2jyRfG3azqUXcbfV0yKaAywLFTMOsCiCCvgAAuA8oVh7vFaSypA1BxawCdeVuqmAbjiO1GmlAAsox18cSC/EaUYbNWqUDB06tCSc0GLk/BIO9CBmtKGZphrieMLNU+umY9OT/yhkS/pnWvBSCXxizJXeH9eN9Ybjih8OcdcU1zLPaK61s4CW+YBXMXcWabNRd1a8NhrzqTCL5yStjeYAy+ZV4ADLRkeP4grUSwEHWPVSPv1zfWObXrNCd3R4LZ9/WuSBq0Weu0eEYuy51iIy6mSRE78qMvBQiYKrqJY3t14rJz0+008htFuSuUgdfm0aa+oAy1hQg3AOsAxE1BBZc2DRH04ZpBYUDScR8KpQrSSuyRLAAmgApNRNRbojbioakImP6Ml1nMYHrAB6TJw4MRSnT9uIiVtN6zflK0auqWhALVIY00KktH3CTYQOnLzIsyZMmBAK0ZfbikGolr+vlU5rHpOWLa/Kzq69ZMeQo3MnvljDK/oPkGNsmlaI64r5K3TqoNa1Yg60blkadxbzi54KKxUIRrUE7irQKlYbzQFWuSuw/X0OsGx09CiuQK0VuOuuu8IfjHhPPe+88+T000+XM844I3Rj+vTpwUlbaXMHVqUKtr/fN7Z2enZoLRf9UeR/Pymyvf1hOlF1d3TqIv95wMVyzZrReUW//Ikb5ZwH7tz9vVjB9j1OJ/z6BSLfvcFuAps4Uodem1WYVwdYVRC1wpAOsCoUMHp7lgAWG/VFixaJ1pdgQ07aXSn3UFYAFuCIel3qpgJcab2uOLyirhKnKvJ1akFR2J3UM4uWpBh51J2FE8yyAVpwz5EaydwxNuBNpS0Oo7Zd9DnpNHGDdFpx765jjdsaxxbvGHGS7FjQV1qv/XHu6xanGQIm586dG6ApY8NZxzrVpnWtFCbmO3VQ3VnMdyl3VrQYvNbOAgpqqiH90cMAtA+sp6g7K1przAFWpatw1/0OsGx09CiuQK0VGDZsWO7Ajfiz+eMZ36+0OcCqVMH29/vG1k7PDqslzqufnVoUXqnKW3buJadvvUzm7RzZTvh/efp2+ecZP9v9tTi80u/Ea2N973siX/2q3SQ2aaQOuzarNJ8OsKokbAVhHWBVIF781qwALIAArhatlUQdKAq2JzmFLQsAixPlgFfqppo0aVJwU2m6YNR5xYl1S5cuDVPBX3uBdBZ/9c23LKLFyIEq/ICINi1GrkCr0n7wizsF21lXuOYYGw4kqxaHWJLwFwgLeEVKKIBVC/IzNhyChRrXqXNK3Vnxa7kf2KTurFKphvGTDVlXrD0FWgpP9Tlcr+4s5njWrFlhTU6ePLkdeLOaH4s4gF0A7+DBg0NKbRabA6wszor3yRXIhgIOsGznwTe2dnp2WC1vOUPkubsTCzlj+8HyqW0Xhev379EqP3r+r3LUTyIF3HFWTdwoO5+9u90fUEPNq9GniCzoI3LVv+9+nkOsktp32LVZUpnyLnCAVZ5u1bzLAZahulkAWLxpAX80NYrT99LUSqo3wKIeEq4cwACOGsAG0EDrUvFZQRxvKGvWrAkziAMHd1Kp0/ispjtJMXIAlsIs+pfUnUVsCtavWrUqdJeC8owtaW2mNGNsvfzCds6qPSBW7K9fOLW2XR75xSPNw6iSsHOnrFixInzQSNFjjtOeCgjcBDRpKmC+UwcVZqE966IY0MrnziKtMerOitdG06HjMsAdWMrdmFIqk8sdYJnI6EFcAVegTgo4wLIV3je2dnp2SC0p2P6DybGaV8U13bGzRd7f6T/k/SdMlU8++lvpesnFeWHUW+uXyqI//1Rat78pYyYfLl1GT9tdsP3qq0W+9jWHWAmXb4dcmwm1KecyB1jlqFbdexxgGepbb4DFaWvAK62VREpW2lpJ9QRYABscRzScRocccoh069ZtD3iFzrox59p+/fqFulBJHGaG090uFLqRgqbpbsxBtGkxcgVaheqQ4fJauHBhKGxO69OnT6jnlRR+pR1f19+dJZ1/8afERTS3/7/3y5YP/SLtY8L1mtbKoQI0tMBdVyn4YT2ocwr98506CATVQvCFXGzxQvBRqBU9uRKola82GqBM0w2Bl9WujZZkEhxgJVHJr3EFXIGsKuAAy3ZmfGNrp2eH1PKZW0Tu+KfUIr71vn+XbvetKwqhSurpECux7iW1TBzJL0QBB1jZWwcOsAznpJ4AizQhipgDQHCbAH/KqZVUD4CFboCr1atXh9mg3ziOABt8L3rSIM4bxqmQAncZJ/JlARboUqLPOOAUZgFX4u4fIErUnQXg0rFxPY0TFEn7qtbYKNje7capuyzb8ToD3VtE3oycKtOWXkhNrLc+80SusHvSlw8OKZx1FMinkdJGXbNqjE3rWqk7K37qoNa1Yp0BnXSdxceiQCueash1AKwnnngizCvfj88v4FVhFs+pFoAspb8DrFIK+fddAVcgywo4wLKdHd/Y2unZIbWc+WORv0ScUEnl3DRN5Ed/2H11njTARHo6xEqkeCItE0XyixxgZXMNOMAynJd6ASzS6KgnRMP5wUmD5dZKqjXAArhRpHzjxo2h/zjGcBzRFF7xbwAPNYn0xDqgwbhx42TgwIGGM1idUEmKkZMmSI0nTYUbO3ZsgDzVbJ3n3ypd7/ri7kfEIZZ+J1Yba8v0H8j2ibtOmkrS+EHKvGlNKdJaSbmrBryK90frWilMzHfqINprumEhZ1w+d9YjjzwSgDEuMsai6YZ6oqL2hbUbd2cl0c3iGgdYFip6DFfAFaiXAg6wbJX3ja2dnh1NywXP/12e/P0Nct6L16YTMWEh9sR6OsQqqX9iLUtG8gtQwB1Y2VsHDrAM56TWAIsUQZxIWiuJTTLOq0pqJdUSYJ144okye/bsnJsKJ9WIESPCjMRPGsS5U+zEOsNprGqoJMXIgSikReLQIvWtWqmRe836qXS579L2473mtfbOK5xYX+nZ7pqtJ10pbx/6qUQ64SbDMRctyE9aZL0acEmdWQCn+KmDvHaAWaQbArZwThWqnTVz5swcwOIe5klroynMeuWVV/a4n/lVd1aa2mjlaOYAqxzV/B5XwBXIigIOsGxnwje2dnp2FC0BV9fPeE5mLN4gg1o2yUNdviidWiIO/WKSJoRXhEilp0Osogs5lZZ2L4mmjeQAK3tT6wDLcE5qDbDYYGu6GcADJ0iRr2XTAAAgAElEQVSlqUq1BFikWQEUcK9Qw2rAgAG5eleABU3domZSmhPrDKe06qH45Xzx4sUFn0N6G7BD0w0rgZPxh1TbgYWrDoCiBflJC2XNZqVpXSt1Z+U7dTDqzmK9aqPemboeWbuargvEUuDIZ15PwFcFWoVqoyk0K+QAK1czB1jlKuf3uQKuQBYUcIBlOwu+sbXTs9m1jIKrqGo3t14rJ3V+prSQKeBVaoDFDQ6xCs5Bs6/N0ovP9goHWLZ6WkRzgGWhYluMWgGs+++/PxRq10YdKNKyLFKyagmw6D+ABrCB40XdMNGTBleuXFnxiXWGU2wWirWCc47TBmn77LNP0AGnkgKVQsXIFWbhzqpkzqtVA4uxkdb67LPPhrGRzspJg9Zwxmwy2gLxA1+1B1DFTx3UulZ8XQvR8zVcjwqt1K0VLQCvIJbvAckUZhWqjabuLOBZpe47B1jWq8TjuQKuQC0VcIBlq7ZvbO30bFYtC4ErVe6gluXyu65XSBd5u7CYa94W+fnm3d/PU/MqfnNZesYh1sMPixx7rN0kN2iksrRs0LHWotsOsGqhcrpnOMBKp1fRq2sBsKjh8+ijj+bSknB/WNZKqjbA4k1g+fLlQUfd/AM4tFA7GmoqFs4k6xPrDKe77FCMlaL1zz//fIgBsCAdNH4aX5Ji5AqziEFx8rTN+hRC5m/p0qWydu3a0BWcSZMnTy6rb2nHYnk9MBXnlAItfhmIN+aL1x5z0LVr17yPj9fOijq0qHcWdWcBL6MNNyVgV4FWoWcUG7cDLMtV4bFcAVeg1go4wLJV3De2dno2m5alwFX4na5Hq5x//Ag59x3zpfsdnxbZ3v73lnbqPrhN5IE3RRLAK+4rW0+FWJddJnL55XYT3MCRytaygcdcza47wKqmuuXFdoBVnm4FN6tsQmfNmhU2vtR04hQ5q4YrhGLYWugb5xUnuVm2agEsNvK4jRRe0ecTTjgh1OuKwyvgQa1OrLPULkks9KVoPS4cGkXoKdheymmTpBg59ZQUaOHoSuLOar38Qmm99se7ux4r2B4/nXDbRZ+TbZf/a96hakF+1j6Ngvzjx48vObYkutX7GgrsL1iwIJwuma9pXSuAndYti9fOKuXO0pMrWRv53HfMqcKspLXRHGDVe+X4810BV6ASBRxgVaLenvf6xtZOz2bRMg24OvuoYbJP1712ifj80yIPXiPy7N0cuxQRtkVk9CkiJ3xFZOWbiR1RFen5yCOJn2O3ArIbqSItszusuvXMAVbdpC/4YAdYhnNSTQfWunXrQj2h6KYYZwuQwLJVA2ABX9j8M4Zoe/e73x3+q6laQBxqYtXrxDpLHfPF0rEpBDnwwANl2LBhiUBTPF6SYuQKs3Dx5HNn7XXdddLl0kgR9zi80ofG6hhs/da35O0vf7ldl3CLMW+AHhrF+PlIAtGqrXul8YHSFKLXenOcoAioAjQB6/KdOsj30Z3POKcKFYJXfdSZpSCTZwKseQafFVrrWHB/Rd1ZhWqjOcCqdPb9flfAFainAg6wbNX3ja2dno2uZdngKi7hy6tFVj8q8tarIt16iQw7VmS/IamFbnQ9Uw+4ije4lrbiOsCy1dMimgMsCxXbYlQDYBFzxYoV4QhPWs+ePUOdJIBBIwAsNt6ADTbhNIrNr1+/Pvx72rRpYWOvNYJwnWTpxDrDpREcNejA3DHeiRMnBi0sWpJi5FF3Fimbrf/2b+3g1W9O+oD0PuoVmdZpTrvTZXZKi+wY+W7ZMb9PO6dWFGIB5BibFuTHdUVB/mZo1KxibPwywLzhlhs0aFBuaFrXSlMN85062KNHj9zJhrx+iZPWncX60dpZCgmj+hJXi/3rM/i+A6xmWIU+Bleg4yrgAMt27n1ja6dno2ppBq7spAyRGlVPYxlMwrmWJjLmgjjAstXTIpoDLAsVqwSwABMLFy7M1UrCUUOh70ceeSTAgqwDrM2bN8vTTz8dClfTSHekMPWTTz4Z/o/7iDHxNQCAnliHW4ii31k6sa6SZbJp06YwNlLsGBvzpqfWVRK30L2lipGP++MfZfTPfpa7ffWXL5YT9jo6/J8jkqe2LJavndhHeu33Ttkx+CjZue/g8L24YwuIteGcc0JKJM49XEGMDWdQMzTqUwFUGRv1qKhTxnot1rhWnVms6UJ1rdShxXoo5s6KFoOPurMUZgGGeWa0EVNPNdywYUPoD7W6LNOZLeeXWnDUTQOsTp06NRwAAOClkXKMk8+bK+AKdEwFHGDZzrtvbO30bDQtswqudEYaTU+7lWQfybW01dQBlq2eFtEcYFmo2BbD0oGFc4nNs9ZKYgM6bty4UE/ogQceyDzAwokye/bssIGnz2z++/TpI0AtAFy0AQf0BELcKsArPjdDo5g5Bdtp1ElibGzUa9XixcgH3nKLTPjFL3KPX3T22fLT48+S3z+3+1TLkb17yJ2fm5q3i3GIxf3PffCDoSA/Y6NOUzM0Dg8AHvOaJgWQseFsStO4V+taAbN4TcQbemmqYTnuLCB31J1VqEYXMJiTSpPWRkszzkqvdYBVqYJ+vyvQvAo4wLKdW9/Y2unZKFpmHVw5wLJbk66lvZZEdIBVHV0rieoAqxL1YvdaASx+KOJc0s0oG08Ktmu9nKwDLFwfFGFnc01tHjb/FJ3WYu2kQG3cuDHAuXwb7nKKkRtOo0ko1gJveKtXrw7xAAi45wrVKjJ5aIkgheDT9+d3llWvt+TuPm303nLRu0cElxhwMd7icZaff7684+qrC57EV4uxWT2DeVu5cmXusAGAD+sXQFdpA0pH3VmF6lqhOx/luLNwZkZrZykY1r6z/rQQPOAsfvJlpWMs534HWOWo5ve4Ah1DAQdYtvPcKNDFdtTViZZ1LRsFXDl0sV+fWV+b9iOubkQHWNXVt5zoDrDKUa3APRYAi0LROJeocYVzadKkSXsUas8qwGL8ABt1HOE0OuSQQ8LmXwu185lxcS2pZ3piHS4XUqHybbhLFSM3nEKTUIyBovVAOlrfvn1lwoQJeWGQyQMTBMmX/rfli1+Ules2ygd+vqTd+TGfG7ddxu63M8wTkEP1x0Gmaa37/OhH7Zxc+Qq7J+hWpi5hbIsXL84dNgDowTlYDcjD+sc5pbWz8p06qHWtALqFnG1aQw4hma9oyiHjoX4X7ymMIZ5qyLWAVQVavF7rUXTfAVamXgbeGVcgUwo4wLKdDt/Y2umZVS0bDVw5wLJbk66lvZZEdIBVHV0rieoAqxL1YvdWCrAAHjiXtFYS8CdfraQsAizGzuaf+jU0wAeOIxw8fE/dV/yftMJ8J9ZxHWlWuqnX2lkqM5vreDHyemy4iy2Z+Il11PnitMF69jMfvNJTBP+8YINcePui3JC67tUi/3HS3rL5tb/vUZuJtE7WJnCVdth998nAH/4wd28jQyzcUABVPWxg4MCBoWC71p0yfJvIG4p1o+sel1a+ula8pvjgNQCQSlI7a9GiRSEuKcgUn9faWdT3UqisHQIiK8zifaca4C7f4B1gVXt1eXxXoHEVcIBlO3dZhS62o6xNtKxp2ajgyqGL/XrN2tq0H2FtIzrAqq3eSZ7mACuJSgmvqQRg4VwCANEABYceemjBWklZA1hstgFvFCuncQIdjiOawiv+DQzQU92SnFhXqhg5zi49eS0L6VClTqxLuIxMLysGr3jQ1/+wWO6Yt+tUSNoJo94pP/7YQQGgFCtGDpDDmTXq9tul93XX5e5vRIjFOgOoKjCl2PnQoUPrBh21rpUCrXynDpKSy9oHNBWqF8drDzck8wiQU5DK6xAQCSxWoIUG0RaFxTwH9121IKwDLNOXvAdzBZpKAQdYttPpG1s7PbOiZaODK52RrOhpt0LqF8m1tNXeAZatnhbRHGBZqNgWoxyAxT2cwLVq1aoQhQ0pNXeK1UrKEsACRJHyqClQI0eOzJ0axkacDza+bJpxt0RPrCM9i81xkhYvRp5vw412mu7Gpr5aG+58/S3nxLok467kmk6PPSbd3vOegnBpx86dcsK/PSZ/e2Nr7ppvnDpKzjxiULvHRseWrz8H3n57u3TCzXffLXLssZV0vWb3sm6BV3rYAOC1X79+NXt+kgfxGlOYyOdCda1Y/7iz1PUIkCOVFXcZ7iuFcvp61M/0gcMVou6suLsLgKXuLH1Gkr4nucYBVhKV/BpXoGMq4ADLdt59Y2unZ721bBZw5QDLbk26lvZaEtEBVnV0rSSqA6xK1IvdmxZgsREF6FD0nMbGmZpX+QpnRx+VFYCFM4Ri8+qmYvOP+0rTBaPwilPdSGdCI4sT69ic66Y+XzoUG26FWYWKkVtNvcWJdVZ9icdp/c53pPW735V8zqhFL7wmH/7prHa3/OWCI2XIO7rnvsbaBIJoQX7SQoGD8WLkCrGWfOQjsvyss3LOOKAHqWlZbDgGef0xNgqmMzbgTJYbfdU023yHIGhdK15jpCRzPe8nkydPbufUitfO0lRJdWfxmtI51pRR1YVreE0p0OK1VklzgFWJen6vK9DcCjjAsp3fekMX29HUN1q9tGw2cOXQxX4d12tt2o8kGxEdYGVjHqK9cIBlOCdpABabQpxLFFimjRgxQkhdSuIaygLAIr1pzpw5IdWMWjls/knjU3eIFmtnbCtWrAgnu9FIfeJaS6jBM3F3acoVQC3a8hUjt5j2ap5YZ9G/HHB47DHZcfTRe4S88eFV8oP7d80LDXAFwKJpQX7etGkU+MYZGIcV0WLk2+6/X9YOHbrHcyhGrjCRouFJ1rjl+PPFolYbzkcaQI6xFUrFq3ZfKonPLylRd1a8rhWx+/TpI7179w4F29WdFX2muq2iBeDVncX31J3F64v3q7g7C92i7qy0dcMcYFWyAvxeV6C5FXCAZTu/vrG107PWWjYruNIZqbWedishe5FcS9s5cYBlq6dFNAdYFiq2xUgKsF5//fXgXOINho3i+PHjQ5HlpK3eAItfKBcuXJhzU1Gvi02sOq/QQTexuK5wKNHYRCdxmCXVId91PBt3lsIs3CrxDTcwRmtn4SRJu+HmubU8sa4SPYrde9Z/zZan1+wCqLQzjxgo3zh1dBgbcId5pgEmSffEpVSqkYoXdWflK0au2vO5WKpsqWeV833WwrPPPps7bADHFe6kWvejnL6XugeQy+tSHZ3x67WuFfPJuselVeg1pJCR14Z+cC3zCSzWdEPmO9oAZFF3VqFnRO9pRoDFe/wll1wit912W9CLAwG+9rWvyUc/+tFS0+jfdwVcgYgCDrBsl4NvbO30rJWWzQ6udEZqpafdCshuJNfSdm4cYNnqaRHNAZaFim0xkgAsNjM4r9gIstnD+YE7JU2rF8BifMuWLZPly5eH7uKm4qREwEYcXrGZxqEFQKIB6MaMGVNz902pYuTMARt6dQgl2XDX+8S6NGul0LWvvrVNjrn2Udm+c2fuEoq3HzN8X5k/f34AgLT+/fsHwFou5KPGVLFi5LiCVHucWtV0Z7EmSYcktY7Wt2/fcNhAqZRdC72rHSMOr3Bd4eokFRD986XZ6iEIrH9ey8xxHPaWcmcBahRmqZs0OlaFxcBK5jrfOmpGgHXyySfLU089Jd/73vdk9OjR8utf/1puuukmueWWW+TjH/94tZeDx3cFmkYBB1i2U+kbWzs9q61lRwFXDrDs1qRraa8lER1gVUfXSqI6wKpEvdi9pQDWunXrAhzQOlA4l9i0p231AFgAKvqubio2yLipdNOrqUv8X091I/WIBrgaMmRI2mGaX4/ubLij7qz4Q/bZZ5926W7xDXfWTqwrV6R7Fm+UL/52Ye72Lp07yf1fOEyWLpwveuodAIQPK6gULUYOyI27s3BBKcwCqiRxfCUdPym7AFU9bGDYsGG5U/mSxsjqdbigOAVUYTGvNaBJdN40zRbYRO2vfGm2OKfUnUWKbxxmMf58tbP0NQLYjbqz+H+0kWpMfGAWnzWNuNkA1p///Gd53/veF6DVxz72sZwEQC0ccqSvNgM0zerrwfvVXAo4wLKdz2pDF9veZjtatbTsaODKoYv9Oq/W2rTvaWNEdICVvXlygGU4J4UAFl/HtYR7iQa0Al4lcfvk616tARYbZE5qw8VB4zQzoBTjip80qKe6sXllYwvkAnZlsdHHeDHy+IY7mu4GBMn6iXVJdb70ziXyu2d2pXbSpg7tJeeN2JwryI/rioL81WpajFz1ByxGmxYjV6AFWCwXpBGbedPDBkjn4lS+ZmhAYsamsJixlUpH1rpWCnJ5XRc6dVDdWWif1p0FCFV3loLDqOa8D/L6Yi0AdXBrTZ06Nfx74sSJ4VLeN4GojdTOP/98+Z//+Z/wfgm00/ab3/wmuK8effRROTpPTbpGGqP31RWolQIOsGyV9o2tnZ7WWnZUcKUzYq2n3Uw3XiTX0nbOHGDZ6mkRzQGWhYptMfIBrJEjR4a/uuMyoFEHipo70Y1N2i7UEmDhFKBeF3WlaGyQcXjkg1ekZsVPrCNtqBFatBg5G/t8G24dh6Z+4lhpxMZYp13/uGx4bUuu+x8cvlNO6Lc9rEvWJ+Cilq1UMXLcOlF3VtLXD44g3EmassvYgCbN0HBc4SpTWEydMt5f0jata6VAK9+pg6wHdWfhlEvrzgKCR91ZcfcdfeZ1RWzm+sQTTwzDaESAddRRR4XDLJ588sl2U8HPAcDcjTfeKJ/+9KfTTpNf7wp0SAUcYNlOu29s7fS00rKjgyudESs97Wa4cSO5lrZz5wDLVk+LaA6wLFRsixEHWKQpAULYuNFwRowbN66sekLRbtYKYOGeWrJkSdggs7nUDbLWu+Kznly2du3aUBybVujEOkOpqx4qWowcMBc/3Y30tnoWI69EgOc2vi4f+M+n2oW4eMrbMnT/bqEmG26neja01tpNQBV1F2mfWHPAQwVaHCCQz51Fyi6HCPC6BIowtnJSduupRaFnr1+/PoBxtAL6MDbqWFXa4mm2+U4d1LpWzIHWLUvjzqLPuLOYWxxaUffdt771reAo472SNfDLX/5STjvttIrfMyvVJc39pG/iGvvLX/7S7jbSr3E1fve735Wvf/3raUL6ta5Ah1XAAZbt1PvG1k7PSrV0cNV+LirV025mGz+Sa2k7hw6wbPW0iOYAy0LFthhxgAXk0DowpNwBtMpNg6oHwCIFUDfIFGtnsxov1q6nuumJdWxqcblY1i8ynKJUoeIn1gFBGFc83Y2gtSxGnmoQeS6++bE1ct2MXYX4ae/oulP+9YQeAYJoXaJKn2F5PwArmu4Wh4ndu3cPMEtrK7FuV6xYET5orNspU6aUnbJrOZZKY7EmV69eHQpK0qoNi7Wuleqf79RBdWdxomMpd5YC7+jJhoxHD4Y455xzcrW8VCuK7Z966qly+umnh9pSWW8ALJy3d911V7uuKsC66qqrwomE3lwBV6C0Ag6wSmuU5grf2KZRq/i15Wrp4Cq/ruXqaTejzRPJtbSdSwdYtnpaRHOAZaFiWwwFWI8//rjoiVxs1HAu9evXz+xJ1XRgsWG99957c33FjQO8AmzE4ZUWdrc4sc5MHKNAxU6sq2cxcovhnfuLZ+SJVbtOh6SdNKyrXH/m1IYoLJ2kGDmQUdPgAFs4CZOmHFroW60YvN5wRGo6MuCI95ZawWLe39Q5xWs+36mDvF8AEtWdVSrVEKC1YcOG4N4ExgEaf/e738nVV18tq1ataiflueeeKz/72c+qJa9ZXE8hNJPSA7kC4gDLdhH4xtZOz7RaOriqDhC0m9HmiZR2bTbPyKszEgdY1dG1kqgOsCpRL3YvmzV+2Zo9e3b4DvDqiCOOEJwJlq1aAIsNMilX6qbCVUSxedIHteYVn/m/nupWrRPrLPVKGyvNiXW1LEaedhz5rn/l9TfluO/PlO07d3/3hjMmyklj09dOsuhPJTGSFCMnvVBTDYEq8VMlK3l+Le+lZtS8efNCyh2NVDSLdORKxhBNs6Vf+U4dVJjFeyCgLR/QwpmEA4u5OuywwwKgAzrSHn744ZAqycl+n/zkJ+Uf/uEfKulyTe6lvhUF2+NF3CnszqmEXsS9JtPgD2kSBRxg2U6kb2zt9EyqpYOrZJon1TNZtI59lWtpO/8OsGz1tIjmAMtCxbYYK1euDJtMbRQ75zQ361YNgMUGmWLXmzZtynX3yCOPDOlXCq/4BgCAFDqKR+upbtU+sc5av2LxKj2xrlrFyC00IBXv5/c8Lf8x7+1cuL06tcjjFx0re3fdfVqaxbNqHQPdAcdaLwvHVbxQOOAV15KmG5J62AiN1xl1oTR1lfS04cOHm6QjW42f9wgcWZpqqGA7Gp8aXVoIHrcVDQgGNGdsuLdIP6Z2GZ9p/NLAeC1Sr63GWioOqYPTp08PJxF+5CMfyV3+3ve+N/x84JRF1qI3V8AVKK2AA6zSGqW5wje2adQqfm0pLR1cpdO6lJ7ponXsq11L2/l3gGWrp0U0B1gWKrbFoNj3zJkzw+aEzTMbr1GjRhk+YVcoa4DFBpmTBuObTlJhcEVosXbgFQXp2YQxvnqdWGcuaFvA+Il1pGcBO8ptVsXIy31+9D49se6Wpdvl0Q2dct+aOmw/+fnZB1s8om4xACcAVWAIa5ST3vr06ROgiAKVQsXI1Z2FQyiL7ixek8ArXIFAnAkTJkj//v3rpnXSB9NfXFlaqD0OE3Fj4fBkXfI9xkadQObj5ptvlq9+9avhUbfcckuofVWrNMmk4yt13cknnyyzZs0KqZAHHnhgcGT99Kc/lV/96ldy5plnlrrdv+8KuAJtCjjAsl0KvrG107OQlg6uytPY12Z5uuW7y7W005JIDrBs9bSI5gDLQsW2GLgQSIeheDSbt0YAWGyQgVfqpiItCUcEberUqQFgsblkc48zYvHixcGR1a1bNk6ss5o+5o1UpWqeWFeqGDmaKlDBqWLl0qDG0IIFC2T79h1y5Zy95G9v7VbtyyeNkE8eM9RKxprHARrPnz8/QFYgBzWU8qXslipGDoxVdxZzkIVi9sAfYDF1v+gfYyMNstEacxN1Z8UPQeCkVkDPu971rvBec8MNN+SG+NBDD8lxxx3XaEMO8PQb3/iG3HbbbQH6jx07Npw8+NGPfrThxuIddgXqqYADLFv1fWNrp2dcy+UvbZXrZzwnMxZvKPiQ/Xu0yvnHj5Czjxom+zS4891OyV2RfG3aKepa2mnpAMtWS6toDrCslBQJ8AMXCH95Z/OZdYBFH3F36AaZU+hIGbzvvvuCKpwoRg0bPgBdnBZGIxWIzXQWNvmVTh9zVo8T65IUIwdWKNACJKZt8RPrXpPucsnj29qF+f1nDpcxffdJGzoT15OKtXTp0tAX9GH9JtEpSTFyXgeqPU6hWqewsWmjYDt9JdWRsWnaXSbEr6ATvI9QtF3bgw8+KN///vfbRcRBd+GFF8rZZ58tnELozRVwBTqmAg6wbOfdN7Z2eqqWa18Xmb21n9y39MWCwR1cldbd12ZpjZJe4VomVSrZde7ASqZTLa9ygGWodiMBrLVr1wanlW6QOWlQ0wVxfURrYUUlYhNNGhMQq9abesOpCqFwhuAow1lGq9eJddUoRs7YgDtakB930fwt75RrZqzMydinZxe5/4tHN9w8ohdjYw3TcFwBVMtNMytVjJy4UXcWYLdajbEtW7YsdwIf8IyxVfOZ1RpLPG4+WEytK4qaX3XVVWHM69evb3cbzjNOdaW4uzdXwBXoeAo4wLKdc9/YptDz5dUiqx4R2fKqSNdeIsOOFdl/t2N91oqNcvlvn5AFL+8uyxCP7uAqud6+NpNrVepK17KUQum+7wArnV61uNoBlqHKjQCw6CMvRFxHNDbIuDv0hDDAh46D9CwK08fr13Af7qtouhsbzUZqpJQB6kjvoQ0aNCjU4MlCHST0pl9av4l6QtFGH9UZxxzEi5EXOrHus7+ZL48s3zVe2gen9Jdv/8PYRpq24BYkZVABa79+/QJQtZo3LUau9ZtIb4s34K2ufUuQy9hIYyXlk4YLiXpeVqmk9ZxoPeGUVF2awmL+/6EPfSiMm/Yv//IvwblKIXScoIyd10EzuD3rqb8/2xVoVAUcYNnOnG9sE+j5/NMiD1wt8tw95FZEbmgRGXWyLJ9wgVw1t4enCiaQMs0lvjbTqFX8WtfSTksiOcCy1dMimgMsCxXbYmQdYOnmX10OpOZwXD1OqvhJg7z5kV6op7oBeIAEbCb1ayod98fT3eLurJa/r5VOax6Tli2vys6uvWTHkKNl576DDdVPHkrH9sYbb4SbKLQ/dOjQTDqRmJc0xcipo8VpkvET67a8vUOOuvYR4bO27394gpwyvk9y4ep8JSCPYu0KlTiJr9on1CUpRq4wC6hYiQuMsVErisZ6ZF02usuRsQCLWZMvv/xyGNvgwYNl9OjR4WsUaAdi4TCjyPlZZ52VGzOvUxySuEO9uQKuQMdUwAGW7bz7xraEnov+KPK/nxTZvrXghVt27iVf2HaB3L3jiD2uccdV+evV12b52sXvdC3ttHSAZaulVTQHWFZKZrwGFmlSs2fPDqd+0YYNG5Y7IRF3RPSkQT3VjY0n0IrT+Hr37p1TqlQxchxBbOrZ0B+wdY10e/x66bTiXmmJ/CVrp7TIjhEnybZjviw7+k8xnIXiofKdWFeqxk6W4FupYuTR0eMoGzJkiND/ZU/dI7c/sVRekx4yc8d4eUH6yKMXHSO9urXWTPtKHgSQA6hGDxsYOHBgJSFT31uqGDkBSWdUoLXPPvskAlCAVMbGLxw0Cn4DeZqhxWEx4Iqx3X333XLOOecE0Ep65m9/+9tcEfdmGLePwRVwBWwUcIBlo6NG8Y1tET1xXv3s1KLwSu8GYp2+9TKZt3Nk+NJ+3Vvl0yd4cfZKVquvzUrUa3+va2mnJZHcgWWrp0U0B1gWKrbFyKoDiw0yJw2qc4qTBtlEarpgFF6RNsiJdXwNVwTphaRJFWpajBW1kc4AACAASURBVFzT3QAM2vq/8pQcuurH0nnn2wXv39m5i2w97UeyffT7DGcif6ikJ9bp3Z1emCOtj16XGfgWH1W0GDmuOnWU6XX7vbFCJrx4p7zzpdnt4OGOnS0yu+thMvEj36opPCx3gkmnxK1DaiSpqgBV4Gi9G2uddU+6IR+8FqKNtLcAcdtgbr40W1xJjA0wSbocjsgoLK73GCt5fhwW69h+8pOfyEUXXRT0GjFihPzxj3+U8ePHJ4J9lfTH73UFXIHGU8ABlu2c+ca2iJ63nCHy3N2JBZ+x/WD5550XyrsG7JDLP/4uOWC/nonv9Qv3VMDXpt2qcC3ttCSSAyxbPS2iOcCyULEtRhYBFhtknFe6QVY3VRxekarEqW68SGkUawdexesrFZOL8QNR2My/teIxOWjWV4rCK40FxNry8TuqClPSnljX+dk/SZc7/0laitjIawnfiukePbGOFDbqmnVb+VeZsvyGzMDDcl9mFNjXwwZIj2RN4mzKWuP1hLtRQW4cJvL6irqzeH1R6wpYzOsG2EWx9mKwOGtjLtafKCwGhDM25u2SSy6RH/7wh+HWqVOnyu9//3vp379/Iw3N++oKuAI1VMABlq3YvrEtoCcF238wOVbzqrj2ZBL839jrZEf3A+Tkk09O9fuy7aw2RzRfm3bz6FraaekAy1ZLq2gOsKyUzGAKIa4cCpWzuWaDzOa/Z8+eOecVG2dSBPnMsfbRE+sAXeXW80HSrr87SzqvmJFY3Zf6nyD/36k3S9e9OkmXzp12fQ4fLbJXp8InvJR6gI4NgEVLcmIdzquuv/5AUXhVS/hWaIyFTqzr9rdFifu/o1OrvPSBX0v3A4/JlAMm34l1rN9GKebNLw8Ks3CQ8RqMNtxYejgCMIs6TwC6Rm/MG6813k9oCsL5+vnnny9/+MMfwtc/+MEPyn//939nEkY2+hx4/12BZlLAAZbtbPrGtoCez9wicsc/pRZ79pDzZe07j3OAlVq5PW/wtWkgYlsI19JOSwdYtlpaRXOAZaVkhgAWm0VOD9RNJM4HNshs/tV5pfCK/wO5cE3RBgwYIKQYVnKqGzWXut04tV3aWimZSWs7bsv18rzsrrWl93RuacnBLMAWH61tkEuBF7BLoZd+bu0k8urLf5Otb70pe7XslHfs20uGDuovXVv3CmAsxOrcSVrb7tVYI+/7tPRce3+pLue+v33ke2TLh36R+HqLC4udWJcWHq7vNUVmj/1qrnZTJcXILcZW6MS6RjvpUrVgrnBCKtDSWlf6fdxZ1IHSVEOgTyM23lOWLl0qa9euDd3nYIfJkyeHEzU/+tGPypNPPhm+/qUvfUmuvvrqkA7qzRVwBVyBYgo4wLJdH76x3VPPBc//Xeb/7/fkYy/9KLXY8wd+Qlb0OdkBVmrl9rzB16aBiG0hXEs7LYnkKYS2elpEc4BloWJbjCykELL55+Qu3UQCI9hEUl9HTxrkM//XU91ee+21MAJOdONkt0pPPus8/1bpetcXUyv75a2flf/dcXzq+yxvGNSySR7q8kXp1BI9Orn4E3ZIi7xX/l3Wt/SWTi0t0iIiLS187P43X6eF7/O9cM3uf+e+Hr636+udwi27/83X+Rrz9+bmzaGGENd169pVevToHmL23bFRbnjxPOnU7ujn4v3HBv/XCdfJm10OyF1YTjFyi3nId2IdxegrXZMWfas0Bo4r6l0BdGgAZQ5XYD6jTQ9BAGgBgXitZr2xFgHhQDoaaYGAcH7of/jDHw5AHSh+/fXXywUXXNAU85n1OfH+uQLNoIADLNtZ9I3tbj0BV9fPeE5mLN4gH+78oPxr642pxXYHVmrJCt7ga9O1tFPANpIDLFs9LaI5wLJQsS1GvQEWG+Q5c+bkNpGc0kZxZJrCK/7NRlJPdQNiAQcmTJhgVotmr1k/lS73XZpa2cu3nS3/tf3U1PdZ3lDuLzFZgG/oUG7/1x95mazodWSAK/Fi5NQw0pP1AKLVcs7kO7EunKLYBv8s57nWsSj4zkmDvO5oBx54YDgJFOCM5vkOQdDXqrqzmIM0NelqNUbeQxibgnAKswPCH330UfnYxz4W3Ge4QG+55RY57bTTmmI+a6WtP8cV6OgKOMCyXQEOCUSi4ErVLeePl9E//nkNrMrXqa/NyjXUCK6lnZZEcoBlq6dFNAdYFipmAGCxQeakQd1Ejho1KmyQaWySoycNki6IWwJQAYzAocUm2ao1sgPr3M53yWWtv0wtRRbgG50ut/9bT7pS3j70U2GdABxYI0CVJMXILQBTvhPr+vTpk3oesnjDq6++GgAPbiu0mjhxovTr12+PruohCAqzKAofd2eRXqgwEZdcJam+FlopCOf9h7EBzHFf3XrrrfK5z30ujJn/33HHHXLYYYc5vLIQ3WO4Ah1IAQdYtpPdkTe2+cBVVN2bW6+Vkzo/k1hwykf8X6+zwvUOsBLLVvDCjrw2K1evfQTX0lZRB1i2elpEc4BloWKdARYbZOCVuqnYILNpjJ80yGb3+eeflyVLloSNMW4OCmNb19wppwYWf8na/OknZMveA2Tr9h2y5e0dsvXtHbJl2w752yt/l41/e1lefOkVefWNN2XbDpG3+dgp4d97dekmXbrvLdu27wzX8b0dnTrLvvu/U3a0dA7xQiyNyefwtZ3ha/p1vnbazvvLspE3ugNry/QfyPaJZ+zxaihVjJzC4wpUgKDlpLtFT6zj4ADWJCcpNkPbtGmTzJ8/P8BixgYsJi0wScNRqSARqAUMija0xhHHB3NQ6yLwCsLpp4JwoNo111wjV155Zegq70V33nlnDqYnGbdf4wq4Aq6AKuAAy3YtdMSNbSlwhcL792iVb0x5Uz4091OJDvCRzl3krTPvkLvnb3KAZbREO+LaNJIu7+/u99xzj69NI4EdYBkJaRjGAZahmPVIIWTjSNqgbpA5rp4NsqaBAbHUpbF8+XJZtWpVGDGAgGtJD6tGS1tIPGkhdCCdbur5rCe5RceAJqRo4XJJfZLiK2uk+0+OTFWAHvj25Pv/Km/1GBAqT1HSaMfOnbl/sy74+o62b+q/+SrXho+2f4drIv/m3o2bNsn6DRv4snTp1lUGDx4qra17tT1n973E2fvN5+UjM/8xdf/f+swTsnPfwUWXgnUx8nwn1rEme/ToUY0lWfOY1KEDFtMqhcVohdsp6s6KD4g0PYWJvL6r6c4ChFNrj34BzoCOvJd84QtfkF/+cpeD8d3vfrfcdtttiYFdzSfIH+gKuAKZV8ABlu0UdSRIkBRcnX/8CDn7qGGyT9e9RBb9UeR/Pymyvf0fjNrNQucuIh+6Wd4c/h5xSGC3PjvS2rRTLX8k19JWYQdYtnpaRHOAZaFiW4xaA6xBgwYFR5W6qQ499NCwUY6fNMj3Fy5cKBuAICJCahbOiHLcMknl6vTCHOn66w8k+kvWzs5dZMvH75Ad/ackDR+u03Q3Tj6Lp7ppoHKKkVcLvqUaXNv4ACDMMQ2HEw6eUjWoatF/1tTmzZsDUAEkUscpTTHyQifWpQaOaUWtwfWMjR92q1evDk+rBiym2H3UncX/o401os4sPlMw3qIxNkA4RdlpvXr1CiCctXDWWWfJ/ffvOr3z3HPPlR//+Mdmz7Xou8dwBVyBxlPAAZbtnHWEjW1Z4Coq8/NPizx4jcizd4c/KO5uLSKjTxE54SsiAw+VjqCl7eorHs31tFPbtbTTkkgOsGz1tIjmAMtCxbYYtQJYbBJxImljg3zIIYcEsBE/aVBPdaOeDm3o0KFCfSyLukWlpOv87J+ky53/VBRiAa+2nvYj2T76faXC7fH9+Il1pE2ihQKVeDFyNvHRTX0hEFQL+FZqsDjLqFPGWGgU5B87dmwiV009+k9/qZ2VpBg5UHHZsmXtTqyjdlI1HUOl9Lb6PmtuwYIFQlokrW/fvuGAhGrCYl7zpBGr9vw73gBN6s7i3+W8/gHGgPD169eH8L1795ZJkyYJG0xOGly0aFH4OumDF198cVPMp9W68DiugCtQngIOsMrTrdBdzbyxrRhcxUV7ebXI6kdF3npVpFsvkWHHiuw3JHdVM2tpu+qSRXM9k+mU5CrXMolKya9xgJVcq1pd6QDLUOlaACw2yPfee29wH+kGmU0kG9L4SYO4IigezRsZDQAyeHDxNDFDOUIoYMprf/2evPOFh6RTy+6/ZJF2t2Pku2Xb0V9K7bwibqkT69SdpQ6htMXIqw3fiulc6MS6NNChnv1PUoxcxw90HDduXFUBj/WaLhSPGlWk81KQnsYhCqSyppk3i77SD4VZ+dJscblFQW6SNGJgMWNTEM7pkIBw3l/OOOOMALUAxDfddJOceeaZNR+zhW4ewxVwBbKngAMs2zlpxo2tObhKKHkzaplw6FW5zPW0k9W1tNOSSA6wbPW0iOYAy0LFthjVBlhsTGfPnp3bROKAIH2HFj9pUE91Y+OJ+wPIxfX1aI8s+5t86zf3ytSWxdKzZbO0dOslX/nU2SVrLhXqa/zEOtIhcboUa8A8Tbki3U0BoN6Trxg58K31sX+TTstntKspVSl8K9ZPTpEECkQL8uc7sS7JPNaj//n6xRpE8xdeeEEoah5vrE/SI9UhVOti5Em0LHUNgFRhMcAKWEyKb70b6zzqztJTSqP9wrWo2vfs2XMP+KQgnM+0Mf8/e2cCbmO59vFbHBocyQkRGTOLMstcZGj6kowJh5SU6nBKZEhCJ6eBThmKU+aEKDJkKGQqGTeO2TF3pMSXSr7r/3Se/b17WXvvd611r7Xed63/fV372uz9vvf7PL/nWWvv57/voXRpI4TPnz/fpApi7hDEZs6cKfXr16d4Fe9F5/NJIIEIUMDSXcxEOtjGS7iyK5JILHV3WXjeyDM8bsHuIks9lvBEAUuXp4Y3ClgaFP/rI5oCFg6J6DRoD5F4JEQpCDc28goHZ6RhodYVUn1weEV0BQosI20oXgYB6+Epm1Mfn/+POWTZU7XDGo5Gx7rMipGDIQrh41CPg3nOX0/JZYe+lCznf5CLOXLJb4VrhS2+ZTRpRM0gbTCcjnUZ+UVXyFiMP6MxODvWQbDCvsVethE9zntjWYw8rE0YcBNSJxGdhDRKzO2mm24ye8eLhug+ZxOEwDRbvF84u0rifQdzgwiJ14UVwt9++23561//at5jSpQoIXPnzhWkgdJIgARIQJMABSxNmr9Hr/u98Hi8hSsKWLp7kjz1eSbC61yfSvgeKWCFzy5ad1LAUiQbLQELB2REXtloKhwk8W8beeTsNIjC0agvBIMQAPEq3hEtGgJWYMc6dKrD3CLtWOcsRg4BCaxDKUautX3QsQ7F6G1Bfsztqquu0nIfVz/BOtZhb8LiVYxcCwiiyiAWY92QQod1QxSTHwzvGxAQbZotuhymZ4iga9KkiRHCUd9q9OjR5tJatWrJ7NmzM42A9AMPjpEESMB7BChg6a6Jnw+2XhGuKLjo7kny1Ofp59e5Po3IPVLAipyhtgcKWIpEoyFg4YCMqBx7QEaxdqQqIZICBdlRiwZRE7arm7NjHSJBvNDVLVIBK5Yd6xBFg8O6jVIBZ6dBPHSmu6HrYyQWi451kYwvknvT61iXXkc8t8XIbf0mpL7Fur6U5YGxohMfOvLBvCIWR7Je+IUH+x5pnvhshVyks6LDIMSrYsWKyfr1681jULh94sSJCSO0RsKO95IACUSHAAUsXa5+PNh6Tbii4KK7J8lTn6cfX+f6FPQ8UsDSY6nliQKWFkk02714UVCnasOGDSaqAak1KHQcjtkD8q5du1IPyBCvcPhftWpVaiohDvA4yOO5Nr0wlI514Ywt1HsiEbCQ4gQBDzxhKPodq451boqRI0rKplyhu14onfTi0bEu1LUL9/r0OtaF0o0vGsXIw52P8z7MLSUlRY4cOWK+DEENYnF6XS01nhkrH5gbIgFxaITh/Qavv2eeeSbNELCODRo0kObNm0urVq1i3hwiVjz4HBIggfgSoICly99PB1uvClcUXHT3JHnq8/TT61x/9voeKWDpM43UIwWsSAk67tcSsHCIREt6e4jEARnF2iGO4BmIjjh48KBJdwssRo5DNIp+Q1RBpFAogoEiijSuwhWwEPmBaDNbeLp48eKCj3hF3dhi5LbDGwQWp4E11spGCGWUuumVjnXRWPPAjnUo+I3C35Gsm0Yxco25Ym4QdBClB/OaWBzJHBF9uGXLljRiMTpEQkR/6KGHzHsPRDvUxQIHax988IGJxqKRAAmQgDYBCli6RP1wsPW6cEXBRXdPkqc+Tz+8zvVnHT2PFLCixzZczxSwwiUX5D4NAQuHSIg2EKlg6GSGQyTMFmvHvyFmobsYrnUeJp3DCixGHq+aSrYLYc3Ltssf5fcuhH26PpRhIXTU47GpkhA+EHVVsGBBxdWKzBXWAsKarR8USjFyr3asi4zI73cH61iHNFdtC7UYuUYqLX4hwJ7E+sEQXYk03kiEOW0u4foDTxRrt2IxokeLFi0qX3zxhbRr187UykJtrylTpkjDhg1lxYoVpgshigGvW7dOEH1IIwESIAFtAhSwdIl6+WDrF+HKroiXWerumth4I089zmSpxxKeKGDp8tTwRgFLg+J/fUQqYOENB50GbTHlUqVKmQMyDBEo+LCdBm1XN9uxDilMSPex0UHxKkYeiPOyo9/ImcXD5E9Hv5DLslxM/fZFySK/Fb9Nfrn1L/JbgcppbnN2rENEGeaGqCYvm9ti5KiZhV/I/dCxLlTeEDkCO9bly5cvVDchX+8sRo79bwUm68im2dpUT9SrClV0smIxIucgDNsGCiEP1oM3QLSCMIeIRysWI1V36tSp0qNHDyOQQzz+6KOPpEqVKiGz8+CUOSQSIAGfEKCApbtQXjzY+k24ooCluyfJU5+nF1/n+rOMnUcKWLFj7fZJFLDcknJxXSQCFg7IEK/sIRLt6pEKiMO5jbyy4hUKte/YsSPDjnUQSCBiWUEr2sXIg+HJuusTyT6vh2S5kDbVznntxazZ5ee7/iEXSrUwX86oY52LJfDEJW6KkWMtIQogBQ3FsUMVVDwxUccgjh8/Llu3bjX7FU0FkPKK2mzxMPzgtvseqX6BabYQeq2YhTTbzGpXoag50gbhB5FcmFuiRBxBLN60aZNACAeHSpUqmbmNGDFCXnzxRbN8EJDnzp2bKqbHY035TBIggeQkQAFLd929dLD1q3BFwUV3T5KnPk8vvc71Zxd7jxSwYs88sydSwMqMUAjfD1fAwgEZkSs2murmm282h3978MZnWxwcXc/2799vRoVrcJiGYJCRRbsYebBnI/Iqx5R7MhSv7H0QsX5qO0f+de6PprMbDKIO5pZex7oQliXul0I8RGHsEydOBB0LRBFbNwufM1vPuE/IMQDsrQMHDpjwWhjSVLF/I+3OqDVHvKYQGWYFLdvowPqHcHjNNdekClpXXnllGjHx0KFDRiyG4XuYGz4nggUTi7H3evbsKZMnTzZTbNKkiUyfPj1hBLtEWDfOgQSSiQAFLN3V9sLB1u/ClV0RL7DU3R3x9UaeevzJUo8lPFHA0uWp4Y0ClgbF//oIR8BCMXYUbLcHZHQaxOE/ULyC723btgkiXWD58+eX8uXLh1WkXbMYeXr4csx8ULLuXeKa7nd5a8jnhR4z1+fNm1cQgeaFAvSuJ5DOhYEd6xDxg7RQK6rYmkPO2yFM2ggh1B3yanRWYMc6CEGI4NGoNxUp9/Tuh4DlTLMNjM7Caw/sISTiOttIAVFJmJufxMX0GOC9BEJ4oFiM1MsOHTqY+lawrl27yptvvpkQc47WfqJfEiCB6BKggKXLN54H20QRrihg6e5J8tTnGc/Xuf5s4u+RAlb81yBwBBSwFNckFAEL1yIqx0ZT4YCM6A6k8diUQXyGiGO7un3//fdmtCiuXLJkSRVhI5Ji5Omhy/L9Ibl8TA3JIv9f8yozzKiJtbj8SLm2xM0Rd6zL7Fmx+r6bjnXxKEauMf9gHetQaN9GCmo8I9o+EJ2FFMP00mzt8yEiQizGZ78b5uwUwlGjDPW8EGmGToIpKSlmikOHDpVnn33WV+vp97Xh+EmABC4lQAFLd1fE42CbaMIVBRfdPUme+jzj8TrXn4V3PFLA8s5a2JFQwFJcE7cCFg6RqKljo6lQ6wqHSETaBHYatF3d8GYEK1OmjBQuXFhx1GlduS1GbqNUgqX4Zd0yXXIseDLkMR6pMUBy13805Pu8eAPWC2mhtiC/m451boqRQ+i06YbhFCPXYBXYsa548eKCD69GirmZs02zxWsSKZF4jQYaUgdtZByizfwk1mEuKECPele2Yya6Q2JfovZe69atzfsRXs/vvvuutG3b1tfr6WbNeQ0JkID3CVDA0l2jWB5sE1W4ouCiuyfJU59nLF/n+qP3nkcKWN5bEwpYimviRsDCIRIHRhtNVaxYMRNNBQvsNIiDJg6cEJUQiYViyjhAx8rcFCNHrSp7qLfFyLNtGCfZlw4IeZg/3zZEfq3SNeT7vHZDYMc6RO9ApAzVtIuRh/r8YNcH61iHYvSJYBAb0Y3PNjwoVKiQEZQRoYXmCk7D6xHpoFbI9UrNr/TWwQrhtgZY6dKljRD+ySefSOfOnQVfx1xmzpwp9erVo3iVCBuacyCBBCBAAUt3EWNxsE104YqCi+6eJE99nrF4neuP2rseKWB5b20oYCmuSWYCFg7IEK/wxoJolbJlywoOycE6DR47dsyk+sAnoiKQXhjvFCaIbzbdCt3LkEbmNNQ+wiG46OlVkm/1oJDJnm/+ulyo8EDI93npBhTk37JlS2pBfq2OdZEWI9dgFKxjHUScRDCkEkIsxp6GOIV6V4h0g+E1iNeu3fsQn/E1pyEazopZiJLzUnQWhHBEA0IIx7isEP7WW2/JM888Y95/EImFToOI8KSRAAmQgFcIUMDSXYloHmyTRbii4KK7J8lTn2c0X+f6o/W+RwpY3lsjCliKa5KRgIUDMqI7bDQVDsg48DrFK3voRQrT7t27zchwMIZ4dfnllyuONHJXGDcijeyh3lmM/IrzJ6Xx9t4h18D6qftauXh19NIjI591xh6cHesQkYOC/NHqWIeC2xCUwP+7775LLfpvR+gsRg6RKdKC+DhEoBsf9jj2IvYk9mYi2NGjR0MSi51ptlgDCLtOQx07G52F13g8O2kiLXDr1q1mf6AAve2i2LdvX/nHP/5hhl27dm2ZPXu2oB4WjQRIgAS8RIAClu5qRONgm2zCFQUX3T1Jnvo8o/E61x+lfzxSwPLeWlHAUlyT9ASsI0eOmKgcG00FYQOHfyte4esQr/AZIgGuhyECBNESOBB73QKLkVfd9bJc98Mm18O+UKKxnG/5nuvrvXQh1g1vbhAeYbHuWJdZMXLsLdRssqmeoYhqmBvEVNtsAGmiiCqLpyijtfaY2969e80HDBGOmFsoYrFNs7Viok0Ndo4Rfi17dJiMRa0wjAv7EfsSdtVVVxnxCnulS5cuJnUQ9sADD8iECROiJrRqrRX9kAAJJCcBCli66655sE1W4YqCi+6eJE99npqvc/3R+c8jBSzvrRkFLMU1CRSwUNgakS/2EImDLMQrREIEile2sDsitWDXX3+9SefxUiqSW1SY29l/fSF55z0ol/32S6a3XcyaXc63+0h+K1A502u9dgHWDREuJ06cMEPLnz+/6VgXacRTuPO0xcgRmQVRBdFZgelubouRp9exLl5zC5dJsPuwR7dv3y6IvoJBYKpYsWLEYjGisayYhc+I1nIa0mxtEX58xnuBtmFu6HCKgx8M0WAQwjGeVq1ayddff22+jvTBF198MeI5a4+f/kiABEjAEqCApbsXNA62yS5c2RXRYKm7uv72Rp5660eWeizhiQKWLk8NbxSwNCj+10eggAXByqbW4YCMtEEbaWUFLIgBtqub7ViHou5FixaNSaSG4vQvcZV11yeSfW4PyfJb2hQr54UXsmSTzTc+IRdKtTAiAg7bfog4wxwgVqC2kI26wZph7WIRYeN23VDTCaKoTfV0W4w8WMe6UqVKeWpubhkEXgdRCV1ArViMOnQoaq4tFuP9AHsjWJqtHVOwJgjhzgv3Yb0xN4hVMBTYhxAOQatly5Zy8OBBI66OHj1aunfvnhDrGQkv3ksCJOBtAhSwdNcnkoMthau0axEJS91VTQxv5Km3jmSpx5ICli5LLW8UsLRI/rfYMw7+69atSz0cwz26fdniyDjUIrIFIgcOzLarG+7D/8PtWKc4DTVXmNueLz6Q4gc/kPw/bEpTE+uiZJFvr7lFtue9S05fVTz1meASmO7mJUHIDhQ1qFDTzBbkx/pCCPGyuS1GjjQ3Z+c9iDs33HCDl6fmemxYL6wb1g+G4uVFihSJiZAD8dAZnZVeEwRbDB7RWqEYhHDMzQrhJUqUMEL4ihUrpH379kZMg2A2depUadasWUzmHMr4eS0JkAAJBBKggKW7J8I52FK4Cr4G4bDUXc3E8kaeeutJlnosKWDpstTyRgFLi+R/BSwcEleuXGlEKpjz8I+oK3xY8QoiQTQ61ilOKWxXgR3rbil+reQ5kyJZzv8gF3Pkkt8K1zIF28+dO5caoRKLYuRhT8hxY2DHOtvVTcN3LH1kVowcY4GYhXTWeBcj1+CC1yYi5qxYXKFCBZPyGQ/D+4AzOsuKTs6xoJaarZ2FmnkZCblWCIdIhuusED558mTp2bOnSWWEwPrRRx+ZWlheFIXjsQ58JgmQgLcJUMDSXZ9QDrYUrjJmHwpL3VVMTG/kqbeuZKnHkgKWLkstbxSwtEiKmHpDa9euFZumha5eKArt7DRoxSvb1Q2PR8c4HCpRaDkR7PDhw5KSkhJyx7poFiPX4hpqxzqt50bbD6KzUKh9z549l9TMss+ORzFyrXmjRhnEYrwWEdmE1yUEIq8YoqdsqiEEUiuA2/GhaL6zdpYzzRb3IW0Q9+DrmBuE12kDmQAAIABJREFUx5deekmGDRtmXCB9ee7cuQkTSeeVdeM4SIAEokuAApYu3/O7lsnRT1+V7Bd+lHxFSkm2Kh1FitRO8xAKV+6YUyRwx8ntVeTpllTm15Fl5oxCuYI1sEKhFZtrKWApct61a5cRbiBSQRAoVqyYoJA7DAdnW2MHXd3i1bFOcbqXuMKcIYDs27fPfC+SjnWaxcg15ozxYF6YHyycjnUa44iGj2Ad6xCdhDQ7Www+HsXIteaKuk+oAQVDAXuIxaF0YtQah1s/eK+AGG7Z23RHez/eX2x0FkQr20XRCuEQsXr06CHTpk0ztzRt2tT8G6IWjQRIgAS0CCBytH///jJjxgxTNgGp9M8++6y0adNG6xGmGQXKMMDwOxbSvmlhEPhmssiigXLx3EnJEnj7lXlFmgyWrXnvlNeW/EuWpBxP9wHXXPkH6VavuHSsVVRy5vB+h+wwSLm+hSKBa1SuLiRPV5hcXUSWrjC5vogClmtUMbuQApYiatvZDL/I4QCK+jOoQ2PFKwgFXupYpzh1E/2xbds2OX7891988ubNa7q6aXWsC7cYucYcsX4QJo8cOWLcaXWs0xhbpD4wtx07dgii5mC2Y52z/pKbYuQQR2yEEIRLL6SoYdw48EDAgkH0QXRSqLWlImUc6f1Is7W1s/DegjULtOXLl0u5cuWkTp06pjj7F198YS55+OGHZdSoUVHpdhjpvHg/CZCAvwk0adJE1q9fL8OHDxc0+ZgyZYqMHz9ekLrcrl07lclRwFLAuOh5kdVvZOjoooiM+eVOGX4h+LpRuLoUH0UChb3pcEGeejzJUo8lPFHA0uWp4Y0ClgbF//rAgRnpgxs2bDAHTkR5oAsYxBwcmjdt2uTpjnXhooh1xzq3xchtMWwIF+F2mItVx7pw2UdyX7COdWXLls2UVWbFyLNnz54m3S0eghEEVaQMnjx50iC67rrrTF2ocPdBJJw178W88N4CYQ6/oMDwtU6dOpmGEGANgQtf6927t4wYMcL3c9bkR18kQAI6BObPny8tWrQwolXbtm1TnULUwh+zbMfTSJ9GAStCgoi8mtPDlZOLF0X+8kt3mfVb/dTrKVylj44igatt5foi8nSNKtMLyTJTRCFdQAErJFwxuZgCliJmREoERn1Y9zatEP9PpK5umDM6n+FzvOZmi5HbKBUIak5DShUii2xBbNQTcmPx7FjnZnyRXBOsYx1SXkONnNIuRh7JnOy9ENhQrP2HH34wX8K8EAkZ6tw0xqLtA3sbc0MBeBgEcuzTJ5980gh2gZ0NS5YsKX379pUuXbpoDyVh/SGCpFu3bqYmYbDi+gk7cU6MBEIggNcIUpMRbe6syYcup4i+WrVqldSunba2UgjuUy+lgBUONcc9L5cUOff7H3Lc2MmLuaTa+beFwlXmtCgSZM4olCvIMxRaGV9Llnos4YkCli5PDW8UsDQoipiDToECBaRq1arSuHFjqVu3rinOjl++Ag/OiAK55pprUgUVL9fjyQjP6dOnzWEaAhLmhJRBFK6Pp0FARCSKLYhtD/rOMbkpRu6ljnXaPIN1rMPe1bBIipFrPB+vQwiqGAded4goQxfFRDDUwsLcbOQV6s2gs+C8efOMQAUxEa8/1PjCdYcOHTLTHjt2rBFkaJkTQCotIvUgXuE9gAJW5sx4RXISqFWrlon0XLduXRoAiL5CDcUxY8aYFObMDL8jZWRonFK9enVzCUR6/DGC5o7AZYfWSPYp915a8yqD25FK+EGFMdLo9hZyVZLXuMqMMn7P+Pzzz81l9erVk8svvzyzW/j9DAiQp972IEs9lvCE+sc448LwuzV+96bFlwAFLCX+aE9/7733pvGGwzNUW6Qvde3a1fyAg3gAkcVpELBsdBCELT+kOaHWFep54dCMlDEcmlH7yGuGiBUbmYXPboqRI+0MXd282rEuEsaBHevQnQ7RadGwUIqRY/9DNIgkSgr1oZCmiygkRATcdNNNJpUxEcwpFqOuHH6Qgtno0aNNhBXeU1CDBmIWPuP/OEgizadDhw4mUouWOYG77rrL7EG8JmbOnEkBK3NkvCJJCeB9Bk1qPv300zQEIDjh/QZdUPHelJmF8p6P6Ei879HcEah04B0pemqFu4sdV+3PU182FflzyPfxBhIgARJIRAI4O+EcD6OA5Y0VpoCltA5IoVuyZIl88sknsmDBgtToB7hHBAiEE4gFd9xxh9x6663mgI0XBNKdnIbDqU13w+EbUVxesmAd6yBeeW2cwZi5KUaOv6DhLxcwzOmWW27xdMe6UPYG/tKNgu3gYDvWQTSKlWVWjBzsrZCL10AoDQBQYH/79u1mbvCDPZkzZ85YTS2qzzl27JgRo5xiMUTvZ555Rt5++23zbBRvnzVrlqm3RwuPwKRJk0z3RuwjdFajgBUeR96VHAQgYCEaCr/vOM0KWMOGDTMdCTMzCliZEQr/+9X2vi4Fv/8qZAdHrq4q64s/EfJ9vIEESIAEEpEABSzvrSoFLOU1QcQPuoBNnDjReMaBHIJIYCoKWkEj1RAFT4sUKWLSVfARGJ2FQ7hGMXKNaeIAvXPnTpMWCQvWsU7jObHykVkxchTEtoIKxMR4FCPXYIE9tXv3btm/f79xh46B6MaHyLl4GVJPUDvFpnratDg7HmeaLdinJ7Rhbnv37jUfMKSHQrxyW+csXvN381zMDWuGtYPhvQBzgxjeuXPn1IMjWta/++67vhCR3cw7HtecOHHCdHF84YUXjIiFovgUsOKxEnymXwgwhdD7K/WHBU9Jts1TQx7orze1l1+ajQz5vmS7gWlauitOnno8yVKPJTwxhVCXp4Y3ClgaFB0+8NdH1MFCRAiELLSwh3iF6Cyk8yxatMh8z2k4nCO9sGnTplKzZk3zLaS7aRUj15hiuB3rNJ4dbR8QU5AyCDEFhui4wGLY+CsxhB8raEFMCOUvx9GeQ3r+MTdE7yDlE4YaSahPEkp0U7THDqEG0VlWzIKwFSjkImLMmWaL8UNQRbQMXnMwfB+pdc6CwtEee7T8Y26IlkNNJhhEPKREIr21VatWpsYVDCk6Q4YM8dR6RotJNP3ef//9Zh+tXLnSvK4pYEWTNn0nAgHUt0LB9sAi7ijsjq6ELOLugVU+sFpkQrPQB9JlocgNv/8uSkufAAtl6+4O8tTjSZZ6LOGJRdx1eWp4o4ClQTHABwqbL126VJ566qk0IgcO5TiY4vsQsxYuXChr1qwxhVCdhkgARGfhA+mHqH8TbjFyjelpdazTGIu2j/Q61uHrVlBBbaXANUKEjzPdzYuiSWDHOkT6IfLP68IbxEMwB38IuTal0669jc7CD2jb/bJw4cKmu6fX5+Zm/waKxXgPwNxSUlIEQgvy77Hf3nzzTVOcPRHm7IZLtK758MMPTdc0iIJ474VRwIoWbfpNFAJIHWzevLnpRNi6devUaTVr1sz8QejgwYMqwjq7EEa4Y0LsQihX5RXp83vULy1jAhQJdHcIeerxJEs9lhSwdFlqeaOApUUyDD8QtHBIX7x4sUkHgqCFCAunoTB6w4YNTe2satWqGSHFbTHyMIZ0yS3R7FinMb5IfLjtWBfrYuSRzMneG6xjHUQevxleI5iLFRMh5gZGZyEVEo0SUP8pd+7cvmiCkN46BIrFJUuWNCnGy5cvl/bt28sPP/xgmiVMnz7dvCdQvIpsR+M9AIxR6B51r6whjXDu3LkmXRqpw7GsFRfZjHg3CcSOAEogbNiwQUaMGGFeR4jIGjdunKCeHN6vNIwCVoQUv5ksMqeHeyf3/kOkss7auX+oP6+kSKC7buSpx5Ms9VhSwNJlqeWNApYWyQj94FAOcQq/DCI6C5198O/AwzrSiPBL4+233y758+c3kSoQmQIN6W5IO0KUEA684Rx0Y9mxLkJ8Id8eSce6aBYjD3kiQW5ASge68aFWku1YlyjFvSHe4q/7gSmeFgPmi31v976f2loHisVI9cRr/P3335fHH3/czBkiJDqeooZZOK9pjf2VSD5QY6xYsWIZTumee+6ROXPmJNK0ORcSUCEAAbhfv34yY8YM87tImTJlTFoz6vJpGQUsBZKLnhdZ/Ubmjmo/IdJkSObX8QpDgCKB7kYgTz2eZKnHkgKWLkstbxSwtEgq+4Fwhe5jiMqCmIUoLfyC6LRrrrlGbrvtNlM7CwdapIzhmsDDPSJU7IHebTHyeHesU8aZxl1gxzqwQ/HvcCyUYuQQE9E9LpqGPbN161YjfGLdUfQbAmYiGAptb9myJbUbH7p6Ip3QRmcFS7O1TRDAHqIurveiIfISc8N+QsQP5obxor7Vyy+/bIaMtYR45cdIOi8yx5gQ8YY07kAbPny4rFixwkTGYu9ATKSRAAnEngAFLCXmiMRaPFAunj0pWQJdIm2w8WBGXoWImiJBiMAyuZw89XiSpR5LeGINLF2eGt4oYGlQjLIPiBGIplm7dm1qdBbqaDkN0RhVqlQxaUUNGjQwhy5EqwR2P8Q9SLNKrxi5FzvWaeEN1rEO4pVWlI6bYuQQsKyYCAFSq5h6eh3rtOamtQbh+MHcUE9l165d5nakc0HMQWF3p0HAxZ7HB0QtvGachrpRTiHXK50KUdMKBdthmBPmhn3x6KOPmsgGGGrNID0nUcTIcPZBLO9hDaxY0uazSCB9AhSwdHfH+V3L5Oinr0r2C2clX5HSkq1qRxZsDxMxRYIwwaVzG3nq8SRLPZbwRAFLl6eGNwpYGhRj7AMHevxSh+gARGd99tlnpjaO05AyZqOzkHaIN7PMipEj4mPnzp2e7lgXLup4dKxzU4w8T548qWJioCDjdq6BHevgExE8Xiws73ZO9jrsdexJiDwwiH6YG6KUMjLch9eEjc4KfH3gXohBVsgNN8021Pk4r8cY8UPxwIED5st4/UFQRSqh7eKFr0PIev311zOdcyRj4b1pCVDA4o4gAW8QoICluw482OrxJEs9lvBEnno8yVKPJTxRwNLlqeGNApYGxTj6wCEYHfPQstoKWtu2bUszIqRN1ahRw9TOQnQWDso42NsObsGGX6BAAdORy6spV6EgRyQOakKhNhQMKVilSpWK6dzcFCNHZJEVVNwWIw/WsQ51SBJh3ZBOh3pX2KuwSPYkXiM2MgufA9NsIYiBva2fhfTLaBrmhlRPpEXCUOuqfPnyRsxq2bKliTZDVCWKI/fu3Zv1rqK5GPRNAiTgWQIUsHSXhgdbPZ5kqceSAhZZ6hLQ9UYBS5enhjcKWBoUPeQD0Tg4BNtC8MuWLTNd3JwGIQBF4FE7q2zZsibiClEfgYd2pJ9ZQQVRPVrpbrHEhV8wNm7cmMoAwtUNN9wQd0EAohoi4myEENLfnOamGHmwjnVFixaN+9w01heCE9bNNigoXry44EOjcDleI6iXZQWt9Jog2L2P+mgaz7VcsNZIAbY1u7BmJUqUkHXr1pnix6iHhWi8iRMnSqtWrVSfrbE29EECJEACsSJAAUuXNEUXPZ5kqceSAhZZ6hLQ9UYBS5enhjcKWBoUPeoDUT/4AWuLES9atMikYzkNNZkQrYNDNUQtdBBCZBbucxquQfqWjVLxQ1t5CAQQCjA3jN92dfPacmGdIKKEUowcoiQEHgg9EFcQvQNhMhEMddswNwh0mBsiAQsWLBi1qeE5zugsREc5DcKuU8jNLH0xo4HadcPrC3NDtNz1118vs2fPlm7dupk5I/0X/69duzbFq6itOh2TAAn4gQAFLN1Vouiix5Ms9VhSwCJLXQK63ihg6fLU8EYBS4OiT3wg8gQvQtTNQrrh0qVLUwtdI60QHdsg9CDVEMXgb7zxRiOsIPUOIovTECFiD/Waxci1UDo71kFwQGFszNEPhugsK6gEK0aO6CysJdYEda5QNwlrkAiGeSNtECl+mBvqXSH6L1YGrqdPn04VEwOjFyE6Ib3TFoPHa8ZtdBZeRxBUMTesIWrTYW6jRo0yreixnqVLl5Z58+aZ1x6NBEiABJKdAAUs3R1A0UWPJ1nqsaSARZa6BHS9UcDS5anhjQKWBkWf+cBBGbV1EG0FwyEaH7t3704zE3Rpq1OnjhG08BmRKBAYECXiNIheGsXItTCiY52NNEOEGcQrfPaj+aEYuRbXw4cPS0pKihFykL6KdYNAFE/DL6g2Mg4pnxC4nIbXiDM6K73C+UePHhXUpsPccA/mhjn26dNHxo0bZ1zWq1dPPvzwQ+OPRgIkQAIkIKZhDepWwlAbkOJ+ZLuCoktk/Jx3k6UeS3giTz2eZKnHEp4oYOny1PBGAUuDos984BDdoUMHmTJlijRu3FhmzJghqPMD8QCRWfhAUfjAukyoQQQxCx/FihUzXd4QrRIYnRVOMXINhOF2rNN4drR9BHasQ1QZvhbvYuQa88Y89uzZI/v27TPu0BEQUWUQerxkSC10RmcFNkFAJJZNs4UIZUXT/fv3p4rDEOQgXuG1hU53CxcuNFNs166dvPPOO0bUopEACZAACfxOgAKW7k7gwVaPJ1nqsaSARZa6BHS9UcDS5anhjQKWBkUf+kDtpDfeeEOefPJJCazpY6N+lixZYsQsHLLxS6TTkEKIiBEUgq9Vq5ZJPUSkSjjFyDXwQVzYsmWLKYANi6RjncZ4NH2k17EOgglERBshFOti5BpzREQTIpOOHTtm3KH+U8WKFX3RMADphTbVE+mBgdFZEKPwurBCF9IOkTaI9Nb777/fdMaEIX1w8ODBvpizxprTBwmQAAm4JUAByy0pd9dRdHHHyc1VZOmGkvtryNM9q8yuJMvMCIX2fQpYofGKxdUUsGJB2cfPgJiFgznqEqGzIcSs1atXS2Cha9TuQTQXorMQ7o9IFdtlzTl9RKDYlCvUpMIBP1IL7FiH6DB0dXNbmyjS50fz/mAd60qWLBl0brEsRq4xZ9T6Qk0o7BUYukOiS6Qf1w2vB2dXycA0W3QUhEhXrVo1+fjjj020GdIN33rrLfnzn//syzlr7AH6IAESIIGMCFDA0t0fPNjq8SRLPZbwRJ56PMlSjyU8UcDS5anhjQKWBsUk8gFBCwf1xYsXp0ZnHT9+PA0BiFQNGjQw0VnVq1c3AhgiVSBYOA0HeFsMG5/DSRmLdce6WC51sI51hQoVcjUEt8XIrZiItM9YCkeISkKnQRudBAEUAlYiWODc8Jrp3r27ibyyBuH2nnvukUceeUTq168f1t5PBFaZzQECJyLUbHQlIj+xVx577DGTBk0jARJIbAIUsHTXlwdbPZ5kqceSAhZZ6hLQ9UYBS5enhjcKWBoUk9QHDuaIPPn666+NmIXuhuvWrbsklapChQomMgsRWtddd53paojUt0BD7SMrqODfmQkqgR3rkJ4FISwRLFjHukiKe2dWjBzpblZMREH+9IqRa7BFxBWECQiaEHKQMpgvXz4N13H3gX0NYQ6Rc5hb+fLlTV2s/v37y/Lly00qbuDeR8dPvHZolxIAs2nTppkmEtdff71A1J08ebL52pAhQwxXGgmQQOISoIClu7YUXfR4kqUeSwpYZKlLQNcbBSxdnhreKGBpUKQPQwCCFqJMkGaIAzmitFCfyWlIG2zUqJGJzqpSpYoRMSBEhVqM/MiRI7J9+3ZPdazT2gbBOtahyL6WhVOMPDMx0e3YEK23detWI3KiqyWKtWNPJIKh/hoihcAXdeUwNwixqG/1yiuvmCmigDs6gH711VcmJRfpuMOGDTPdCGnuCdSsWVPwHoCOozQSIIHEJUABS3dtKbro8SRLPZYUsMhSl4CuNwpYujw1vFHA0qBIH5cQgJgFcWr9+vWptbNwaA80HOgRnQVRC1E4ELOQFhhoEDkQgYQoIYhk6OwGg7ADH+GkH3pt2cAMtZHQkQ9mO9ZFuzNdZsXIkbZlI+MQTZQ1a9aQ0WFuBw4cMHnkMKQsYt3gOxHs0KFDsmPHDjMVdB/E3BCBhRTBDz74wHz9zjvvNNFDELWsIdIOBq409wTAEgL23r173d/EK0mABHxHgAKW7pJRdNHjSZZ6LOGJPPV4kqUeS3iigKXLU8MbBSwNivSRKQEIGIiYQGQWPtDh0BbvtjdDnLrtttukWbNmplsbCmGj3lZgwXh7fSKJV4hISklJMYxgtmNdNFP5gi1aZsXIIcogxdCKiRBrMjPMbefOnamdLHE/1jew+2Vmfrz4fezrXbt2pUYC5c6dWypVqmQaGLRt21a+/PJLM2zUbHr11VcTYs7xWAfsIXxA8IMg2KtXLxk9erSpLUYjARJIXAIUsHTXlgdbPZ5kqceSAhZZ6hLQ9UYBS5enhjcKWBoU6SMkAjj0o0YQDvdIo4KghdQrp0EoqVq1qqA+EArCI8Jq27Ztkj9//jTXIbUNokG8ipGHNPF0LkakGro8QqyDodZPmTJlVDo0RjI+rBOis5AGisg4iAf4mtMgYDmjswK7SiI1FGtrU0kLFCgg5cqVi/vcIuFi74XYh3RIW5wdexM1rxBF17JlS9m9e7ep4/a3v/1Nnn766UxrummMKVF9IJJtzJgxZnpIPX3ttdfk0UcfTdTpcl4kQAL/JUABS3crUHTR40mWeizhiTz1eJKlHkt4ooCly1PDGwUsDYr0EREBRFYgBcsWgl+6dKmcOXMmjU+IJBBBUAR+3LhxJuUKgg/udVosi5FHNOn/3owfMihobtMmb7zxRilSpIgnxQ6IUWCOdcDH+fPn0yBAaqGNzrIF5zE3u5YlSpSQYsWKeXJuoa4lBFjMDZFWsKJFiwrmt2bNGmnTpo0R/CDuvffee3LfffclxJxDZaR5PWpdQSjEx7x582Ts2LGmlljv3r01H0NfJEACHiNAAUt3QXiw1eNJlnosKWCRpS4BXW8UsHR5anijgKVBkT7UCCDCB6mDX3zxhRG05syZk1rvCpEXEHcQ4VKjRg0TnVW/fn1TKwqCwblz59KMA9EvELpshBAEBa1i5BoTDtaxDgKdHwzrBNHNilkQcgKjs8Dafg1RV4gsSwRDVBo6DeKXV8wR0XKY26xZs+Thhx82+xf13LB3UWzcS3suEfhjDoi+Gj9+vEm5zZs3b6JMi/MgARIIIEABS3dLUHTR40mWeiwpYJGlLgFdbxSwdHlqeKOApUGRPqJCYPbs2dKuXTsjCKDeFWoLoRA8fmlwGsSDxo0bm86GpUuXNsIK0t0Co7M0ipFrTTRYxzqkQvrVbDdJCFqYW2BXSdTyckZn+bXoPiLQNm3aZOaHiDPU8sK8kNI2YMAAI9iVLVtW5s6dKyVLlvTrcnp+3BMmTJAuXbqYiDeI2TQSIIHEJEABS3ddKbro8SRLPZYUsMhSl4CuNwpYujw1vFHA0qBIH1EhgAgWpF8hwgW1shB9hSirZcuWmbpZCxcuNHWGnIYordq1a5vorLp165raWYjOggjmNNRqCozOisokgjh1dqyDqIaOdejKlwiGwwaK0cMgWiGlM1hXSQiSNjIOHSb9EKV09OhRU4cNIhX2FdYN8/vLX/4i77zzjpkz6rXNnDnTFOGnRY9Ax44dTUfHY8eOMQIrepjpmQTiToAClu4SUHTR40mWeiwpYJGlLgFdbxSwdHlqeKOApUGRPqJG4MMPP5RGjRoZsSnQEGG1Y8cOI2Yh3RBph4F1mVCbqEmTJuYDNYqQtofuh6EWI9eYYHod6yC6+d0wtz179pj0TliuXLmkcuXKRuhBvSiIiLYYPKK1nIZuhBB8bGdDr/HA3DAvzA8G8Q1zw7weeughWbRokfl6hw4dTH02iFo0HQJIycReql69umnggD2ELoTTp0+XPn36yMsvv6zzIHohARLwJAEKWLrLQtFFjydZ6rGEJ/LU40mWeizhiQKWLk8NbxSwNCjSR9wJQGRAsfDPPvvMiFmIzkLhZ6dBWEBUFqKzbr31VhMh5KYYuYYgkV7HOqSh+d0wN0QmHT9+3EwF9Z8qVKhgUuwCDeuEelm2dlZgsX5cj4gsK2hBvIhndBZEUkSUodYSDCJbxYoVTeTP/fffn9o9E+mD+EiE9fTSfkSqID6wBhCeUe8OqcRdu3Y1giGNBEggsQlQwNJdXx5s9XiSpR5LClhkqUtA1xsFLF2eGt4oYGlQpA9PEYBIAuFh69atJvUQYtaqVasuqcuEjn+IzEL9LKQnQlgJVowch2YbHYQ6VUg/DMUQqYOi34j+giEqDPWR4inMhDL+jK7F3FATCuIC7IYbbpBSpUq5nhsi5mxkFqK0AmtnIRrLGZ2FaK1YGSLFNm/ebDovwgoVKmTmhn3VqlUrOXz4sGA8Y8aMkU6dOrmec6zGz+eQAAmQgN8JUMDSXUGKLno8yVKPJQUsstQloOuNApYuTw1vFLA0KNKHpwlA0EJRd0RnWUEL9YychhpU6GiIQvC2KDQEFQg0Tgu1GHmwjnUQQhLBUI8Mwpzt/ogC+hCwwjWIjs7orMDaWRD8EJ1la2dBWIyWCIhfTDE3rB8MYifmtmTJEkH9JUSOQcycMWOG3H777VEbR7gseR8JkAAJJAIBCli6q0jRRY8nWeqxpIBFlroEdL1RwNLlqeGNApYGRfrwDQEbnQVxAqmGqJ+FTmaBHQvLlStnIrPwgS6HiDCCuBJoGRUjD9axDuJLIhh4fPPNN4IoJUSkoRtf3rx5VaeGwvs21RAskaroNNTXsmIWOgFCXNQwrDPmBvESc0M6JNIiUaj96aefNuNAxB46DSKdMFoimsZc6IMESIAE/EyAApbu6lF00eNJlnosKWCRpS4BXW8UsHR5anijgKVBkT58SwCCFkSSxYsXp9bOOnnyZJr5oA5Tw4YNTXRW1apVjYCB6KyMipEjFW7nzp1pOtZB7EoEQ60rpNFB9EOKH7rxgVE0Dc9CFJ1NN7SRUfaZEJFQ6N+mGyKiLhxhCWuPtEE8D+mBKNaOdRs0aJD8/e9/N4/DHkCHTAibNBIgARIggegRoICly5aiix5PstRjSQGLLHUJ6HqjgKXLU8MbBSwNivR/AdCLAAAgAElEQVSREAQgZkGc2rBhg0k1RHQW/h3YsRBFpFE767bbbjOd0RAdFKwYOaBA4EE0FyKFwhFUvAQWHA4cOGC6ccAgEkG8uuKKK2I+TKQt2s6G4B8YQYfC+87oLDfF1VH0H6Ij7MorrzRzw5qhE96sWbPM1++++26ZNGmSEbVoJEACJEAC0SVAAUuXL0UXPZ5kqceSAhZZ6hLQ9UYBS5enhjcKWBoU6SMhCUCwQbc5CFn4QJQWooCchqgfCFmIzkKq2erVq6VgwYIS2LkwnsXINRYHAtGOHTtM4XIYUvaQNhjLourpzQOio43OQoQWfql0GtIAsU5W0II45TSs865du1K7VqK2FURKpEm2bdvWpJjCnnjiCXnllVc8MWeNNaUPEiABEvA6AQpYuitE0UWPJ1nqsaSARZa6BHS9UcDS5anhjQKWBkX6SHgCEDmQMggxw9bOQp0kp0EggYCCaB+knDVv3twIK/EsRq6xMEiHRFodIp5gEOjKli0bcjdGjbFk5gPrhOgsWzsL/AMj6CBgWTELkVTbt28XmzZ63XXXSfny5WXPnj3SsmVL8xkC2MiRI6VXr16+j6LLjB+/TwIkQAJeIkABS3c1KLro8SRLPZYUsMhSl4CuNwpYujw1vFHA0qBIH0lHAKIIfrGGmIX0MkRn2TQ2CCDbtm0zRc3Roe6OO+4w0Ur4ZSeWxcg1FgWF1FHw3opwJUqUkGLFivlGyIH4Bua2dhbmE8xwDdarQYMGRqRs3bq1uQ9iF1IG7733Xt/MWWPd6YMESIAEvECAApbuKlB00eNJlnosKWCRpS4BXW8UsHR5anijgKVBkT6SlgAikyBQIdUQaYKojbV3714T1eM0RGVVr17dfB8iydVXX21EFUQLOU2rGLnGgqCuF8Sr8+fPG/EGwlyBAgU0XMfFB0RHFH8HdxSi/+GHH1LHMXnyZPnggw+kUKFCAtEL64nOg+g0iHXze/2yuADnQ0mABEggQgIUsCIEGHA7RRc9nmSpx5ICFlnqEtD1RgFLl6eGNwpYGhTpI2kJnDhxQmrWrGmKuEPsqFWrlonEQrFzWwh+2bJlRjhxGtLwEJ2F2llIx0OEE9LdNIqRaywGRB6Ic6gvlS1bNtOND3WkEsEQWbVp0yYjVNn6WKhvBbHOaTlz5jSCI1JBu3TpQhEryOIvXbrURKih9tuhQ4cE9cPQpXHAgAFSpUqVRNgunAMJkEAcCVDA0oVP0UWPJ1nqsaSARZa6BHS9UcDS5anhjQKWBkX6SGoC6FwHkQfpdYGGqB/8krNixQqTbrhw4UJTMNxpKIQO4QuRXHXr1jVpa6g3FWoxcq1FwIEBBdsxdnQYRDc+dBxMBDty5IiJjsPcUGgfwhw+o74V0kAhwKBQPQRJKyaioHtgvbNEYKExh1atWpm9is/otolaYqgXhu6d2OuNGjXSeAx9kAAJJCkBCli6C0/RRY8nWeqxpIBFlroEdL1RwNLlqeGNApYGRfogAZcEIIpAwEJXQwhan3/+uQTWZSpcuLCJ/IGgdeONNxoxJbNi5BBekKYYiUHU2b17t+zfv9+4QZojBB6kRvrdMDekduIDhuLtmBvSIzt27ChLliwxX8e/x44dayLiFi1aZNYI3SX/+te/+h1BVMaPCESkWjoN7EqWLGm4Wa5ReTidkgAJJDwBCli6S0zRRY8nWeqxpIBFlroEdL1RwNLlqeGNApYGRfoggTAI2JpMSMOynQ2teGTd5ciRQ+rUqWPELHxGtBYiXgJFL6TC5cmTJ7W7HiKnQjGkCqLwPGpDwSBKQICIVBQLZQzRuhaiIaKujh49ah6BDoQVK1Y0/7///vtl69at5uvoHPn88897srtitNhEyy8irxDJhuhEGgmQAAmES4ACVrjkgt9H0UWPJ1nqsYQn8tTjSZZ6LOGJApYuTw1vFLA0KNIHCURIAGIWhJaUlBQjZuFj5cqV8ssvv6TxjDTFxo0bmwgtdANEIfLTp0+blDinIeUPQg0+EJ0FgSs9+/nnn02K3Pfff28uKVKkiIn8SoTC5eCHeleIYIMhug1zQ30vpL1BxEKEGaKuEH2VCHOOcCtGfDv2EfYQRCx06KSRAAmQQLgEKGCFS44Cli65S71RJNAlTJ56PMlSjyUFLF2WWt4oYGmRpB8SUCQAQQriFOoy2dpZiGhxGmploWYWCsGjhhZEKhRfhyDlNERR/elPfzJiFj6j5pM1FJdH8XJbb6tMmTJG5EkEw5wwN1tAv1SpUmZuqM3UqVMnkyaIwvToPgixheKVzqp36NBBpk+fLmvWrGEhdx2k9EICSUuAApbu0vNgq8eTLPVYwhN56vEkSz2WFLB0WWp5o4ClRZJ+SCBKBGx0FiKJrJiFrm9I+3MaxCcbnVWoUCETmWWjqpzXof4ThCykJ+7Zs8d044PIhbS6vHnzRmkWsXWLeSOqDGIehD2kQyItcty4cdK7d2/DDhFs6BxZvnx5ildKy4MUzBdffFFGjRolPXv2VPJKNyRAAslKgAKW7srzYKvHkyz1WFLAIktdArremEKoy1PDGwUsDYr0QQIxJABBC3WwUCB7/vz5pti4rV1lhwGRqkGDBqZ2VvXq1U16Iu4JTEnE9RB4ihYtaqKTEqFgOwqLb9myxcwZNcPQRTFnzpymvtXrr79uEIHJnDlzpECBAjFcucR+1ODBg00dsaFDh8pzzz2X2JPl7EiABGJCgAKWLmaKLno8yVKPJQUsstQloOuNApYuTw1vFLA0KNIHCcSJAMQsRBN9/fXXRsxCd8P169cb8cZpiEBC3azbbrvNdEHE91FPK9By5cqVWjsL//ZbWt3BgwdTC4cjxRLiFaxbt25GsILde++98v777xtRi6ZDwIpXELAGDhyo45ReSIAEkp4ABSzdLUDRRY8nWeqxpIBFlroEdL1RwNLlqeGNApYGRfogAY8QgKCFCCTUeYKYhRpaqItlDcXdbU2oFi1amIgZpBAiOgufnYboJVs3C5/xf68a5o2Od4cOHTJDRG2rSpUqmeLtbdq0kbVr15qvP/nkk/K3v/1NsmXL5tWp+G5cQ4YMkQEDBkj//v0F/6aRAAmQgBYBClhaJH/3Q9FFjydZ6rHk3iRLXQK63ihg6fLU8EYBKxOKZ86cMYcy1NNBQWiIAYgwwMGfRgJeJgBRBymDiMiaPXu2qf+EwvCwsmXLGsEHkVi33HKLqZ2FQuaoEwUxCwXOA+3qq69Ojc5CiqJXorMQgYaUwZMnT5ohIy0Q80N9r5YtW8revXtNmuSrr74qjz/+uGfG7eW943ZsI0eONDXF0EggWORVzZo13bridSRAAiRwCQEKWLqbgqKLHk+y1GNJAYssdQnoeqOApctTwxsFrEwo7t+/XypXrmyiOdDFbPz48RSwNHYefcSMAEQrdCvcvHmzeSZS6CDofPbZZ5cUeUdxd6QZNmvWTG666Sb56aef5NSpU5cUjEetLERl4SNPnjxxi846f/68EZYhNMNQmL148eKCIveIvEIEFqLOJk+eLHfffTfFK+VdhzprK1asSNcrRFQaCZAACYRLgAJWuOSC30fRRY8nWeqxpIBFlroEdL1RwNLlqeGNAlYmFO0BDNEmiL5ClzZGYGlsPfqIFQHs4e7du8s///lPmThxorRt21bwNXTo+/LLL1NrZyGKyWkQuapVq2ZqZzVs2FBy585torNsCqK9Fq8NfM8KWhCMYhGdhSgxiFcQ2fC8cuXKmeir6dOny6OPPmrmd91118lHH31k5hGLMcVqTfkcEiABEkgGAhSwdFeZooseT7LUY0kBiyx1Ceh6o4Cly1PDGwWsEChSwAoBFi/1FAGkEm7bts1EEwYzpBKiAPqCBQtM7aylS5dekkYIMQjRWUgXK1++vJw7d85EZwUWjL/88ssFkVw2Oisa9aYgpCGiDHW74B/RYqh7hfpWL7zwgpkixjhv3jwTlUUjARIgARLwHwEKWLprRtFFjydZ6rGkgEWWugR0vVHA0uWp4Y0CVggUKWCFAIuX+pYAorMQ1fT5558bQWvRokWSkpKSZj4QjWrUqCF33HGH1K9f33T0g6gEUctpiHqCsGSjs9AZMNJIqCNHjsj27dtNFBnEMnQaREpjr1695L333jOPv/3222XGjBnm2TQSIAESIAF/EqCApbtuFF30eJKlHksKWGSpS0DXGwUsXZ4a3ihghUCRAlYIsHhpwhBAhBUKoUPMwsfy5ctNJyOnFSpUyBSCR3QWasUhvQ/1pwKjs6644opUMQviUtasWV1zgmCFwuz79u0z9+TKlctElGEsDz74oIkag3Xq1EnefvttyZEjh2vfvJAESIAESMB7BChg6a4JRRc9nmSpx5ICFlnqEtD1RgFLl6eGt6QSsHDwRi0fN4baOoHpVhSw3JDjNYlMACISoqyWLVuWmm4IcctpiIa69dZbTe0sFI+HkIToLER1OQ01tlAA3kZnQdxKzyCEIerq6NGj5hLUoqtYsaIcPnzYdBrE92BIH+zXr58pUk8jARIgARLwNwEKWLrrR9FFjydZ6rGkgEWWugR0vVHA0uWp4S2pBCwcfj/55BNX3O677z5zuHYaBSxX6HhREhGAsLRjx47U6KyVK1cKOgM6rWjRokbMwkeJEiUEXRFPnz5tUgCdhuLvtnYWorOsCIX6XZs2bTIRXbDChQubKK9vvvlGWrVqJceOHTMphOgQ2qFDh4hTFJNo+ThVEiABEvA0AQpYustD0UWPJ1nqsaSARZa6BHS9UcDS5anhLakErEiBUcCKlCDvT2QCEKTOnDkjn332WWp01qFDh9JMGTWr6tWrZ2pn1a5d26QQIjorUPTC1yEgI00QUVY2eqt06dJGwEIqI1IF0RER182cOVMaNGhA8SqRNxjnRgIkkHQEKGDpLjlFFz2eZKnHkgIWWeoS0PVGAUuXp4Y3ClghUKSAFQIsXprUBCBmITpr69atMn/+fNPZcPXq1aZroNNuvPFGE5mF+llFihSR77//3nwERmehcDvuv+eee0wNrGeffdb4L168uMydO9d0HKSRAAmQAAkkFgEKWLrrSdFFjydZ6rGkgEWWugR0vVHA0uWp4Y0ClguKiPZApAeiS7p06WLSlh544AFzZ/PmzQWd1WgkQALpE4AghRTAJUuWGEFr4cKFJvXPaUghREdDFIJHBBZ+YNSqVcvU0JozZ45MnDjRXI50wZ9//tmIV7NmzZJKlSoRPQmQAAmQQAISoIClu6gUXfR4kqUeSwpYZKlLQNcbBSxdnhreKGC5oIgaPgcOHAh6JaJB8H0aCZCAOwI2OguNEiAOIzprzZo1qR0Ls2TJYhzhOqQLjho1SjZv3iwTJkyQ/fv3XxKddcstt8jixYsvqVnnbjSJfxWE9yFDhpiaYWCOSNKBAwfKoEGDEn/ynCEJkICvCVDA0l0+ii56PMlSjyUFLLLUJaDrjQKWLk8NbxSwNCjG0MePP/4o/fv3lxkzZsipU6ekTJkyJp2qTZs2MRwFH0UCegQgVJ08edKIWUOHDjWRVzCIV6iPha6HiMi6cOGC5MyZ09TQQm0sRHEhqguphxCSrfClN7LE8ATRDx1VEamG4vcodk8BKzHWlrMggUQnQAFLd4UpuujxJEs9lhSwyFKXgK43Cli6PDW8UcDSoBhDH6gXtH79ehk+fLg5jE6ZMsUcSCdPnizt2rWL4Uj4KBLQJdC+fXuzn2HNmjUzogtSDrHfrY0cOVKeeuopI1ahnta6detMRNHdd9+tO5gE8mbriYEZ6/gl0MJyKiSQBAQoYOkuMkUXPZ5kqceSAhZZ6hLQ9UYBS5enhjcKWBoUY+QDtYNatGhhDvlt27ZNfSpErW3btsnBgwdNpAqNBPxIAGmAqCn3/PPPmw8ILhBfUCvr4YcfNimCqIPFSKvwV5cCVvjseCcJkEDsCVDA0mVO0UWPJ1nqsaSARZa6BHS9UcDS5anhjQKWBsUY+ejWrZtMmzbNpE1ly5Yt9alTp0410VerVq2S2rVrx2g0fAwJ6BPYs2ePlChRQt8xPRoCFLC4EUiABPxEgAKW7mpRdNHjSZZ6LClgkaUuAV1vFLB0eWp4o4ClQTFGPtCRDXWAkDblNERfVahQQcaMGWMiVWgkQAIkEIwABSzuCxIgAT8RoIClu1oUXfR4kqUeSwpYZKlLQNcbBSxdnhreKGBpUIyRD9S8Kl68uOna5rSjR49KwYIF5aWXXpK+ffvGaDR8DAmQgN8IUMDy24pxvCSQ3AQoYOmuP0UXPZ5kqceSAhZZ6hLQ9UYBS5enhjcKWBoUY+QDAhbSq9CtLZiANWzYMNORkEYCJEACwQhQwOK+IAES8BMBCli6q0XRRY8nWeqxpIBFlroEdL1RwNLlqeGNApYGxRj5YAphjEDzMSSQoAQoYCXownJaJJCgBChg6S4sRRc9nmSpx5ICFlnqEtD1RgFLl6eGNwpYGhRj5AP1rVCwPbCIOwq7oyshi7jHaCH4GBLwKQEKWD5dOA6bBJKUAAUs3YWn6KLHkyz1WFLAIktdArreKGDp8tTwRgFLg2KMfCB1sHnz5qYTYevWrVOf2qxZM9m8ebMcPHhQsmbNGqPR8DEkQAJ+IYD3jrNnz8qZM2ekS5cu0qpVK3nggQfM8PGecuWVV/plKhwnCZBAEhGggKW72BRd9HiSpR5LClhkqUtA1xsFLF2eGt4oYGlQjKGPJk2ayIYNG2TEiBFSsmRJE5E1btw4mTRpkrRv3z6GI+GjSIAE/EKgaNGicuDAgaDD3bdvn+D7NBIgARLwGgEKWLorQtFFjydZ6rGkgEWWugR0vVHA0uWp4Y0ClgbFGPr48ccfpV+/fjJjxgw5deqUlClTxnQebNOmTQxHwUeRAAmQAAmQAAmQQHQJUMDS5UvRRY8nWeqxpIBFlroEdL1RwNLlqeGNApYGRfpIQwBpSkOGDJFvvvlGNm7cKKi7M3DgQBk0aBBJkQAJkAAJkAAJkIArAhSwXGFyfRFFF9eoMr2QLDNFFNIF5BkSrgwvJks9lvBEAUuXp4Y3ClgaFOkjDYH9+/dL5cqVpVKlSlKqVCkZP348BSzuERIgARIgARIggZAIUMAKCVemF/Ngmyki1xeQpWtUri4kT1eYXF1Elq4wub6IApZrVDG7kAJWzFAnz4MuXrxoJpslSxYTfZU3b14KWMmz/JwpCZAACZAACagQoIClgjHVCQ+2ejzJUo8lPJGnHk+y1GMJTxSwdHlqeKOApUGRPtIlQAGLm4MESIAESIAESCAcAhSwwqGW/j082OrxJEs9lhSwyFKXgK43Cli6PDW8UcDSoEgfFLC4B0iABEiABEiABFQJUMBSxckoF0WcFLAUYTICSxUm96YqTkZg6eJU8UYBSwUjnaRHgBFY3BskQAIkQAIkkDgEYtmohQKW7r7hwVaPJ1nqsYQn8tTjSZZ6LOGJEVi6PDW8UcDSoEgf6RKggMXNQQIkQAIkQAKJQyCWjVooYOnuGx5s9XiSpR5LClhkqUtA1xsFLF2eGt4oYGlQpA8KWNwDJBABgR9//FH69+8vM2bMkFOnTkmZMmXk2WeflTZt2kTglbeSAAmQgD6BWDZqoYClu34UXfR4kqUeSwpYZKlLQNcbBSxdnhreKGBpUKQPCljcAyQQAYEmTZrI+vXrZfjw4VKqVCmZMmWKjB8/XiZPnizt2rWLwDNvJQESIIHoEYh2lDUFLN21o+iix5Ms9VhSwCJLXQK63ihg6fLU8EYBS4MifVDA4h4ggTAJzJ8/X1q0aGFEq7Zt26Z6gai1bds2OXjwoGTNmjVM77yNBEiABKJHIFIBCwJVRnbo0CGpXbu2uWTx4sVSpEiR6E0mCTyfP39e1q5da2Zao0YNyZEjRxLMOjpTJEtdruSpx5Ms9VjC04EDB6Rx48bG6b59+6Ro0aK6D6C3kAlQwAoZGW9wQ2DBggVy9uxZQbHXLl26SKtWreSBBx4wtzZv3lyuvPJKN254DQkkPIFu3brJtGnT5LvvvpNs2bKlznfq1Kkm+mrVqlWpB7iEh8EJkgAJ+IpApAJWlixZfDVfDpYESIAESCB5Caxbt06qVauWvAA8MnMKWB5ZiEQbBtRpKNbBjOp1oq025xMJgVq1asmFCxcEPxSdhuirChUqyJgxY+Thhx+O5BG8lwRIgASCEli+fLk0bNjQFZ2NGzdK5cqV01xLAcsVOl5EAiRAAiSQAATmzZsnd955ZwLMxN9ToIDl7/Xj6MMksHTpUpk0aZKsXr1akKKQO3duqVq1qgwYMECqVKkSplfeRgKhE0DNq+LFi8unn36a5uajR49KwYIF5aWXXpK+ffuG7ph3kAAJkEAmBPA+88knn7jidN9990mePHlUBazMUgjxB6969eqZZ+LndeHChV2NlRcFJ4D1rl69uvkm/mhSoEABogqTAFmGCS6d28hTjydZ6rGEJ2cqO+phlSxZUvcB9BYyAQpYISPjDYlAACmN//nPf0xqY7ly5eTkyZMycuRI2bBhgyxcuFAaNWqUCNPkHHxAAAJWiRIlBGm3TrMC1rBhw0xHQhoJkAAJeI1ApBFYmc3HWcQdh4hChQpldgu/nwEB8tTbHmSpxxKeyFOPJ1nqseTe1GWp5Y0ClhZJ+vEVgRMnTki+fPnSjPnHH380qjrStpYsWeKr+XCw/iXAFMLga/fbb7/JrbfeKmvWrJHHH39c3njjjXQXGYXuy5cvL3gNoyh+s2bN/LshOHIS8BEBClg+WiyKBKqLRZFAFScFLEWc3JuKMPm+qQtTyRsFLCWQdJMYBBB5dfjwYdm5c2diTIiz8DwB1LdCwfbAIu4o7I6uhMlcxB11wG655Rb59ddf5Ysvvki3mD0aQyCCrX379iY1mEYCJBBdArFq1MKDmO46kqceT7LUYwlP5KnHkyz1WHJv6rLU8kYBS4sk/fiewPfff29adEPEmjVrlu/nwwn4gwAOghBgIFi1bt06ddCIItq8ebMguihr1qz+mEwURjlo0CAZPHiwlC1bVlBEOrDt++TJk6VDhw5y7bXXSkpKivlMIwESiC6BWDVq4UFMdx3JU48nWeqxpEhAlroEdL3xta7LU8MbBSwNivSREARwCJ4+fbpJWWIh94RYUt9MokmTJqb+2ogRI0waKyKyxo0bZ6KJEFWUzPbzzz/LzTffLNu3b5f+/fvLkCFDUnEgfQnCFj5DyGrXrl0yo+LcSSDhCPDgoLuk5KnHkyz1WFLAIktdArre+FrX5anhjQKWBkX68D2B559/Xl588UUZNWqU9OzZ0/fz4QT8RQC1m/r16yczZsyQU6dOSZkyZUznwTZt2vhrIlEaLURl1MNCJNpXX30lFStWNE+C6AzhChFsbjupRWmIdEsCJBAFAjw46EIlTz2eZKnHkgIWWeoS0PXG17ouTw1vFLA0KNKHrwkgPQlpSkOHDpXnnnvO13Ph4EkgUQk88cQTRmCuVq2afPnll7J48WJTrD1nzpyCWlk33HBDok6d8yKBpCXAg4Pu0pOnHk+y1GNJAYssdQnoeuNrXZenhjcKWBoU6cO3BKx4BQFr4MCBvp0HB04CiU4AUWroEHrgwAEjOE+YMMH8m1GTib7ynF8yE+DBQXf1yVOPJ1nqsaSARZa6BHS98bWuy1PDGwUsDYr04UsCqKUzYMCAS+rq+HIyHDQJJAGBTz/91ERdWatdu7bpTnjZZZclwew5RRIgARIgARIgARIgARJIbgIUsJJ7/ZN29iNHjpTevXtL06ZNg0Ze1axZM2nZcOIk4GUCDz74oClunz17dvnmm29MEXcaCZAACZAACZAACZAACZBA4hOggJX4a8wZBiHQoEEDWbFiRbpsLl68SG4kQAIeJDBx4kTp3LmzFClSRPbv3+/BEXJIJEACJEACJEACJEACJEAC0SBAASsaVOmTBBQIILoEnem2bNkiJ0+elCuuuEJKly4tjz32mOm+RiOBZCRAASsZV51zJgESIAESIAESIAESIAERCljcBSTgUQLLly+XadOmSZ06deT666+Xs2fPyuTJk83XUL+rf//+Hh05h0UC0SNAASt6bOmZBEiABEiABEiABEiABLxMgAKWl1eHYyOBIARQn+vIkSNy8OBB8iGBpCNAASvplpwTJgESIAESIAESIAESIAFDgAIWNwIJ+IzAnXfeKdu3b5e9e/f6bOQcLglEToACVuQM6YEESIAESIAESIAESIAE/EiAApYfV41jTioCv/32m+Dju+++kw8++EB69eolo0ePlu7duycVB69N9syZMyaVE7XKNm7cKN9++63paDlo0CCvDTWhxkMBK6GWk5MhARIgARIgARIgARIgAdcEKGC5RsULSSA+BB555BEZM2aMeXj27Nnltddek0cffTQ+g+FTUwmgA17lypWlUqVKUqpUKRk/fjwFrBjsDwpYMYDMR5AACZAACZAACZAACZCABwlQwPLgonBIJOAkgFpXJ06cMB/z5s2TsWPHyogRI6R3794EFUcCFy9eNE/PkiWLib7KmzcvBawYrAcFrBhA5iNIgARIgARIgARIgARIwIMEKGB5cFE4JBLIiACirxDtg0LuEE1o8SdAASv+a8ARkAAJJAcBpm+Ht84//vij6V48Y8YMOXXqlJQpU0aeffZZadOmTXgOk/gu7kG9xV+6dKlMmjRJVq9eLYcOHZLcuXNL1apVZcCAAVKlShW9ByWBJ5S06Nevn2zZskVOnjwpV1xxhZQuXVoee+wx6dChQxIQiO4Ucfbq1q2bXHXVVYL3U1r8CFDAih97PpkEwiIwYcIE6dKli6xZs0Zq1KgRlg/epEuAApYuT3ojARIggfQIMH07vL3RpEkTWb9+vQwfPtykvU+ZMsX8MWzy5MnSrl278Jwm6V3cg3oL36pVK/nPf/4j+FyuXDkjvIwcOVI2bNggCxculEaNGuk9LME9LV++XKZNmyZ16tSR66+/Xk1euCkAACAASURBVM6ePWte3/gaarZCwKaFR+Dw4cNSvnx5I159//33FLDCw6h2FwUsNZR0RAKxIdCxY0fzA+nYsWOMwIoN8kyfQgErU0S8gARIgARUCDB9O3SM8+fPlxYtWhjRqm3btqkOIGpt27ZNUKoga9asoTtO0ju4B/UWHuUx8uXLl8YholtKliwpFSpUkCVLlug9LEk91axZ02Rt4HVOC4/AXXfdZUqG5MmTR2bOnEkBKzyMandRwFJDSUckoEvg4Ycflly5ckn16tUlf/78ps4SuhBOnz5d+vTpIy+//LLuA5PYG/5q1bBhQ1cE0HEQxdudRgHLFTpeRAIkQAKqBPje6w4n0l4QhYFuxtmyZUu9aerUqSb6atWqVVK7dm13zngVf/7HYA8g8gpRLzt37ozB0xL7EXfeeads375d9u7dm9gTjdLskOLao0cPwxBRbBSwogQ6BLcUsEKAxUtJIJYEkCqIj5SUFDl9+rTkzJnTdLzr2rWrp3PZ/ZgjfvToUfnkk09cLe99991n/gJDAcsVLl5EAiRAAlEjQAHLHdpatWrJhQsXZN26dWluQPQVolzQ6Rh/NKOFToB7MHRmmd2BFK0iRYqY9MFZs2Zldjm/H0Dgt99+E3xAsMYfvnv16iWjR4+W7t27k1WIBBAhiNTWF154wYhYnTp1ooAVIsNoXE4BKxpU6ZMEkpRAsuaI8xfYJN3wnDYJkEBcCfC91x1+1LwqXry4fPrpp2luwB9vChYsKC+99JL07dvXnTNelYYA96D+hkDBcWQboNYrC7mHzveRRx4xojQse/bs8tprrwkaQNFCJ3D//fcL3idXrlxpUggpYIXOMBp3UMCKBlX6JIEkJZCsOeL8BTZJNzynTQIkEBEBpm9HhM/1zRCwSpQoIQsWLAgqYA0bNsx0JKSFToA//0NnltEdzz//vLz44osyatQo6dmzp67zJPGGWleIHMLHvHnzZOzYsTJixAjp3bt3khDQmeaHH35oUqxROgRRWDAKWDpsI/VCAStSgryfBEjAEEjGHHEcBtDlBS210RkSXXQeeOABw6N58+Zy5ZVXcneQAAmQAAmkQ4Dp27HZGkwhjB5nClh6bAcPHiyDBg2SoUOHynPPPafnOMk9IfoK5T1QyD1v3rxJTsPd9G0jAUQDOrs3Io1w7ty58u9//1v+8Ic/mK6EtNgToIAVe+Z8IgkkHIFkzREvWrSoHDhwIOh67tu3T/B9GgmQAAmQQHQIUDxwxxX1rVCwPbCIOwq7oyshi7i74xjsKu7B8Nk577TiFQSsgQMH6jilF0MA9XTxR1akZNaoUYNUXBDYv3+/FCtWLMMr77nnHpkzZ44Lb7xEmwAFLG2i9EcCSUiAOeJJuOicMgmQAAnEmQDFA3cLgGhhRAVDsGrdunXqTc2aNZPNmzcLUo6yZs3qzhmvSkOAezDyDTFkyBAZMGCAiXTBv2m6BDp27CiTJ0+WY8eOMQLLJdqffvrJCH6BNnz4cFmxYoVJx7722mtNEwxa7AlQwIo9cz6RBBKKAHPEE2o5ORkSIAES8DwBpm+HvkRNmjSRDRs2mFo4JUuWNBFZ48aNM+n/7du3D91hkt/BPaizAUaOHGlqMzVt2jRo5FXNmjV1HpQEXhBpmStXLqlevbrkz59fIK6iCyEK4vfp00defvnlJKAQ3SmyBlZ0+br1TgHLLSleRwIkcAkB5ohzU5AACZAACcSaANO3QyeOn9f9+vWTGTNmyKlTp6RMmTKm82CbNm1Cd8Y7TIkAlhCIfCM0aNDARLSkZxcvXoz8IUniAamC+EhJSZHTp09Lzpw5pVKlStK1a1dBLSda5AQoYEXOUMMDBSwNivRBAklKgDniSbrwnDYJkAAJkAAJkAAJkAAJkAAJxJgABawYA+fjSCCRCDBHPJFWk3MhARIgARIgARIgARIgARIgAe8SoIDl3bXhyEjAtwQYYuvbpePASYAESIAESIAESIAESIAESMCTBChgeXJZOCgS8DcBClj+Xj+OngRIgARIgARIgARIgARIgAS8RoACltdWhOMhARIgARIgARIgARIgARIgARIgARIgARJIQ4ACFjcECZAACZAACZAACZAACZAACZAACZAACZCApwlQwPL08nBwJEACJEACJEACJEACJEACJEACJEACJEACFLC4B0iABEiABEiABEiABEiABEiABEiABEiABDxNgAKWp5fHP4NbuHChNG3aVHLmzCnbt2+XwoULBx384MGDZdCgQVKmTBnZtGmTZM+e3T+T5EhJgARIgARIgARIgARIgARIgARIgATiQoACVlywJ+ZDH3zwQZk0aZK0aNFCPv7440smmZKSIpUrV5ZffvlFPv/8c6lTp05iguCsSIAESIAESIAESIAESIAESIAESIAEVAlQwFLFmdzOvv32Wylbtqzg89SpU6VNmzapQC5evCh169aVVatWySOPPCJvvfVWcsPi7EmABEiABEiABEiABEiABEiABEiABFwToIDlGhUvdEPg/fffl44dO0q+fPkEEVd58uQxt7355pvSs2dPKViwoPl6rly53LjjNSRAAiRAAiRAAiRAAiRAAiRAAiRAAiQgFLC4CdQJNGnSRBYvXiydOnWSCRMmyL///W8pV66cnDlzRmbPni333nuv+jPpkARIgARIgARIgARIgARIgARIgARIIHEJUMBK3LWN28z27dsnFSpUkHPnzsmSJUvk9ddfl3nz5knLli1l5syZcRsXH0wCJEACJEACJEACJEACJEACJEACJOBPAhSw/Llunh/1K6+8In369JHcuXPL6dOnzWd0JyxQoIDnx84BkgAJkAAJkAAJkAAJkAAJkAAJkAAJeIsABSxvrUfCjObChQtSrVo12bhxo5nT2LFjpVu3bgkzP06EBEiABEiABEiABEiABLxEYOHChdK0aVPJmTOn+cNx4cKFgw5v8ODBMmjQIClTpoxs2rRJsmfP7qVpcCwkQAIkkC4BCljcHFEhcPbsWZNGuH//fuP/66+/lptvvjkqz6JTEiABEiABEiABEiABEiABkQcffFAmTZokLVq0kI8//vgSJGimVLlyZfnll1/k888/lzp16hAbCZAACfiGAAUs3yyVvwb69NNPy6uvviqXX365/PTTT1K1alVZu3atXHbZZf6aCEdLAiRAAiRAAiRAAiRAAj4h8O2330rZsmUFn6dOnSpt2rRJHfnFixelbt26smrVKnnkkUfkrbfe8smsOEwSIAES+J0ABSzuBHUCGzZskJo1axqxCn/Zadu2rYnEeu2116RXr17qz6NDEiABEiABEiABEiABEiCB3wm8//770rFjR8mXL58g4ipPnjzm62+++ab07NlTChYsaL6eK1cuIiMBEiABXxGggOWr5fL+YH/99VcTbYV8+ueee06GDh0qCxYskObNm2eaj+/92XGEJEACJEACJEACJEACJOB9Ak2aNJHFixdLp06dZMKECfLvf/9bypUrJ2fOnJHZs2fLvffe6/1JcIQkQAIkEECAAha3hCqBYcOGGeGqZMmSsmXLFpNCCEP48vTp0+Xuu++Wjz76SPWZdEYCJEACJEACJEACJEACJPD/BPbt22fq0Z47d06WLFkir7/+usybN09atmwpM2fOJCoSIAES8CUBCli+XDZvDnr37t1SsWJFU/Nq6dKl0rBhw9SBHjt2zOTjnz592vzQxA9PGgmQAAmQAAmQAAmQAAmQQHQIvPLKK9KnTx/JnTu3+R0cn9GdsECBAtF5IL2SAAmQQJQJUMCKMuBkct+oUSNZtmyZdO7cWd59991Lpj527Fjp3r078+6TaVNwriRAAiRAAiRAAiRAAnEhcOHCBalWrZps3LjRPB+/i3fr1i0uY+FDSYAESECDAAUsDYr0Ie+884507dr1kmKRTjTOzic9evQwhSRpJEACJEACJEACJEACJEAC+gTOnj1r0gjRTAn29ddfy80336z/IHokARIggRgRoIAVI9CJ/Jjjx4+b9MDvvvtOpkyZYroOpmcIW8YPThR7X7lypdSqVSuR0XBuJEACJEACJEACJEACJBAXAk8//bS8+uqrpiYtSnyg0dLatWtNp3AaCZAACfiRAAUsP64ax0wCJEACJEACJEACJEACJEAC6RDYsGGD1KxZ04hVn3/+ufkDMyKxXnvtNenVqxe5kQAJkIAvCVDA8uWycdAkQAIkQAIkQAIkQAIkQAIkcCkBZDog2mrTpk2mO/jQoUNlwYIF0rx5c8mZM6cp5F64cGGiIwESIAHfEaCA5bsl44BJgARIgARIgARIgARIgARIIDiBYcOGGeGqZMmSsmXLFpNCCGvTpo1Mnz5d7r77bvnoo4+IjwRIgAR8R4AClu+WjAMmARIgARIgARIgARIgARIggUsJ7N69WypWrGhqXi1dulQaNmyYetGxY8dM3drTp0/LzJkzpWXLlkRIAiRAAr4iQAHLV8vFwZIACZAACZAACZAACZAACZBAcAKNGjWSZcuWSefOneXdd9+95KKxY8dK9+7dpWDBgpKSkiK5cuUiShIgARLwDQEKWL5ZKg6UBEiABEiABEiABEiABEiABIITeOedd6Rr166SL18+I07lyZPnkgsvXrwodevWlVWrVkmPHj3kzTffJE4SIAES8A0BCli+WSoOlARIgARIgARIgARIgARIgAQuJXD8+HGTHvjdd9/JlClTTNfB9AxF3G+++WZBsfeVK1dKrVq1iJQESIAEfEGAApYvlomDJAESIAESIAESIAESIAESIAESIAESIIHkJUABK3nXnjMnARIgARIgARIgARIgARIgARIgARIgAV8QoIDli2XiIEmABEiABEiABEiABEiABEiABEiABEggeQlQwEretefMSYAESIAESIAESIAESIAESIAESIAESMAXBChg+WKZOEgSIAESIAESIAESIAESIAESIAESIAESSF4CFLCSd+05cxIgARIgARIgARIgARIgARIgARIgARLwBQEKWL5YJg6SBEiABEiABEiABEiABEiABEiABEiABJKXAAWs5F17zpwESIAESIAESIAESIAESIAESIAESIAEfEGAApYvlomDJAESIAESIAESIAESIAESIAESIAESIIHkJUABK3nXnjMnARIgARIgARIgARIgARIgARIgARIgAV8QoIDli2XiIEmABEiABEiABEiABEiABEiABEiABEggeQlQwEretefMSYAESIAESIAESIAESIAESIAESIAESMAXBChg+WKZOEgSIAESIAESIAESIAESIAESIAESIAESSF4CFLCSd+05cxIgARIgARIgARIgARIgARIgARIgARLwBQEKWL5YJg6SBEiABEiABEiABEiABEiABEiABEiABJKXAAWs5F17zpwESIAESIAESIAESIAESIAESIAESIAEfEGAApYvlomDJAESIAESIAESIAESIAESIAESIAESIIHkJUABK3nXnjMnARIgARIgARIgARIgARIgARIgARIgAV8QoIDli2XiIEmABEiABEiABEiABEiABEiABEiABEggeQlQwEretefMSYAESIAESIAESIAESIAESIAESIAESMAXBChg+WKZOEgSIAESIAESIAESIAESIAESIAESIAESSF4CFLCSd+05cxIgARIgARIgARIgARIgARIgARIgARLwBQEKWL5YJg6SBEiABEiABEiABEiABEiABEiABEiABJKXAAWs5F17zpwESIAESIAESIAESIAESMDnBBo0aCArVqyQ+vXry/Lly309m86dO8vEiRPlkUcekbfeesvXc7GDv3jxotx0002ydetWeffddwVzpJEACYRHgAJWeNx4FwmQAAmQAAmQAAmQAAmQgIgRTRo2bOiaxYQJE6RTp06ur+eFGRNIFAFrw4YNUr16dfnDH/4g//rXv+SGG25InfiFCxekVq1asn79esmRI4ds3LhRypYtmyGYN998U3r27GmueeaZZ2T48OGutxL25z//+U/X1wdeuGzZMsG6WJs2bZq0bdtWrrvuOjO3nDlzhu2bN5JAMhOggJXMq8+5kwAJkAAJkAAJkAAJkECEBJJNwMqSJYshNnDgQBk0aFCE9CK/PVEErDvuuEMWLVok3bt3l7fffvsSMJs3b5aqVavKL7/8Irfeeqt88cUXYtci8OJDhw5J+fLl5cyZM3LjjTcK7r388stdw45UwMJrAhFx1n777Tcznh07dshLL70kffv2dT0WXkgCJPD/BChgcTeQAAmQAAmQAAmQAAmQAAmETcApYD366KPSo0ePDH0VKlRIcufOHfbz4n2j1wSsePPQeD4iqxB9Bdu1a5cRnYJZ//79ZejQoeZbo0ePlsceeyzodc2bN5cFCxYYgQvRUE4xyc14Dx8+LN99952bS80148ePl9dff938u1KlSrJmzZpLBLMxY8aY1Mg//elPAoHtiiuucO2fF5IACfxOgAIWdwIJkAAJkAAJkAAJkAAJkEDYBJwClleiksKejIsbKWC5gBTiJe3bt5cpU6YYEWvt2rXp3n3+/HmpXLmyiWT64x//KNu2bZPChQunuf7999+Xjh07mq+lF80V4vAyvPzrr7+W2rVrC8aWK1cu+eqrr6RkyZKX3HPq1CmTQogIsnHjxknXrl01h0FfJJAUBChgJcUyc5IkQAIkQAIkQAIkQAIkEB0CFLCiwzVZvH7//feSP39+IwC98cYb8vjjj2c49ZUrV0q9evUExdERafXJJ5+kXn/ixAkpV66c/Oc//5Hrr79etm/fbkSlaNnp06elSpUqsnfvXvOIDz74QO6///50H3f33XfLvHnzpGbNmvLll19Ga1j0SwIJS4ACVsIuLSdGAiRAAiRAAiRAAiRAAtEnEK6AhfpRgwcPNgOEGAEhAwLGrFmzZN++feb/gQXff/zxR5M69tFHH8nOnTvl7NmzkjdvXiMIoG7RnXfeme6EA2tFIU1s5MiRMnfuXMG/r7zySlNj6cknn5RmzZpd4qdo0aJy4MCBDIE+9NBDpoueGytRooQRPlDPCaJMRnbs2DFB6iWKmT/99NNm3Nbc1sBCShwKm0PwQSFx1IdCOlu1atUE477vvvsuGYIzte/TTz8V1KkKtNtvv10+++wz8+VXXnlF/vKXv1xyDZgixQ5rdfz48TS1q9577z3zfBjWoWDBgpniQ+rgP/7xD3Pd5MmTpV27dubfrVu3lhkzZph/Y13vuuuuTH1FcsG9995r9iIMwhv2b0aGwvC2gcH+/fulSJEikTye95JA0hGggJV0S84JkwAJkAAJkAAJkAAJkIAeAQ0BC3WPmjRpIjjUO80pYKHzHASqI0eOpDt4iDAQNIIV7HYKPS+++KJAfECkTjD729/+Jr17907zLW0B6/nnnxeMAymJELLgPz177bXX5KmnnjLfRoraLbfcknqpGwFr/vz5gjQ9RAylZy1atBB0y3N2yINglidPHvnhhx+CdvL7+eef5ZprrpFz584Zt/Dx8ccfX/IIpP1t2rRJWrZsKTNnzkzz/c6dOxvRD6mABw8edLUxIb6hKDpqSV177bWSkpIiq1evlnvuucfc36ZNG5k6daorX+FeBLGuT58+5naIgBAhs2fPnqE7iK5lypQx10DMsqmO4Y6B95FAshGggJVsK875kgAJkAAJkAAJkAAJkIAiAQ0B66abbjIiBIpcI80KogiihBChUqtWLROZU7FiRVNYG4IPolggUiCCCGliiEiCQAJ74IEHZPr06ZfM0Ao9pUqVEtQjuuyyy0w0U506dYzwAAHihRdeMCJPtmzZ5JtvvjEiiTWIbBBsMA5YsIL1GDdS19wY6jiVLVvWXIrC5M8991y6t0Eg2bBhgxE/wMlpmQlYixcvNhFlEKMgkmHcNWrUMKl14ApWkyZNMi4hAH744Ydp/NuC6LgHxcmdBmZ169ZN/dLVV19tRMGsWbOmfg1rBpEJnfhGjRolPXv2TOMD9aL27NkT9NkZcUQkmY24w7gxNoibdk/ky5fPzTKEdc2qVasE3H/99VezV1EHKyMB0j4EkYYQBLHHUAMLtbBoJEAC7glQwHLPileSAAmQAAmQAAmQAAmQAAkEEAilCyFEBSssOFMIISYhRa1x48ZB+bZq1So1cgcd3/785z+nuQ71kyDSoOMcDBFHgWmAVujB9yGMQYQIFJuc9ZWeeOKJ1M5yzodpFnFH/SSIHxDKtm7dGnTuEPIgusGGDBki6MTntIwELKRYIlURaXuIcJs9e7ZJlQw0CCkPP/yw+fKSJUvktttuS73k5ZdfNtFXEPUgRjkjtBBBhkgyrBvY/e///q8g7RCpmNbmzJkj//M//2P+u3nz5lQBEP9HzSrUv0pvbpm92JA6GBhphSLuHTp0yOzWsL9/8uRJufnmm434h72AFMJQUhUbNWpk9ilqdaEIPY0ESMA9AQpY7lnxShIgARIgARIgARIgARIggQACTgErMzjOLoVOAatLly7yzjvvBL396NGjJr0MEUSowQShK5gh/fDGG280UTGBxb1xvVPAyqg+EiK+EM0DkQLiUqBpClh///vfU2tGIeKrUqVKlzzPyQmRSsWLF09zTUYCFuqFoTYTUipRvyujqCREWK1bt86kGtqILDwIXQFRYwy2YMECadq0aerzIVxB8ELKJb63dOlS829n+iVSH5ECicgoiD+WH5yAL0Q82JgxY1JFtMz2kf0+/EGgQ0ohDGPDOKJliCLDMxDVBkMKIQS+UAyRg4h6QwQc6rzRSIAE3BOggOWeFa8kARIgARIgARIgARIgARIIIKAhYKEIOCJTgtmUKVOMqAJDgW5EY6VnNt0NUUao2+RMZbNCT+7cuU2aG6K+ghlS3FDsHOlwwWpGaQpYEOdQnB3CyF//+lcZMWLEJUMqXbq0IH0RwhrqPAVaRgKWFZgyEv6sP4gxqOsEgQxCmTWbJocC+ojEGj58uPnWL7/8ImCJ+leIuoJwNGDAgEvqYEEIhDiHKCwU6HfawoULUwWxzNY22FpBPHNG7WUkhGq8cJ1iIlJPEUmFyLRQrEePHvLWW2+ZWxA5mFndrFB881oSSHQCFLASfYU5PxIgARIgARIgARIgARKIIgGNGliIpEGdpGCG2lDDhg0z30IU0Q033JDubNDVECIDDKIPIrKsWaEH9aQQaZSeQYRBqh4ELkR9BZqmgAXfVmRClBnm54xQcnYBRDQVuu8FWkYCFuozZVS4PRgDiH9IPXQaoo4gNjnrYCEFEyIOIolQUwziWr169VL/D/EQz0bkFQQ6dCFEWqbTkP5nOwgiqgkdDd0axoh6ZOhYaQ3sICrVr18/qBtbxyzYNyEkQpBLzzA+cMBc0E0RTQXc1jtz+uzXr5+89NJL5kuo2VWgQAG3U+Z1JJD0BChgJf0WIAASIAESIAESIAESIAESCJ+AhoCFKB9ntJRzNCjsjvQy2E8//SQ5cuRId7C4DtfDkAYIwcVaZsXO7XXOKBsU3Q40bQELHfjQiQ8Glk7x5cknnzTCD6J8IHZAOAm09OaFCKlwo3sC542oq759+6apg4XC86jHZTsPosA9BCBnHSzUh0K3R1iwFEnU5EIBdlhGaZ3BFtymJuJ7qMUFkROiFuqFodZWsH2SUSdJZ8fLwOeh3hUiySC0QthEtBlqioVjaBzw6quvmltRUywj0Swc/7yHBBKZAAWsRF5dzo0ESIAESIAESIAESIAEokxAQ8AKJhTZYYciYL399tumyx7MLwIWUh2vu+46I/ygkLoV6xD9haigY8eOBa3pZfmkJ2D9H3t3AmVZWZ+L+1cNNN2oSAjIVRkFWoMgjkwCQQwtIohRQUWiXkSjRuX+vSSiQUFRGZTEBG8SIuq9V7gGp+XIqJFBBVGCiqJAGBvSBAiKgDRDd//Xd7SK7qarzj5Vb58e6jlrseyu+va7z3n21ytrv/n2d1rZN3v27N6w9s2MbbP1rq/tt99+qaGXXHJJ7bbbbr2fje6D1QqctippyT2v2ubvS+6DNVrWtJVg7bHNJVeXtawlv8WwFXmvf/3rO73FtoKuPVI5uidVe0+tFGrna6+2yqmVWsu+JlNgtXK1GbcVZ+3VHNu3VU721b5B8//8n/9T66yzTu9bLb0IEOguoMDqbmUkAQIECBAgQIAAAQLLCKzoAiv9CGFb4dTe83ivYa/Aau/jVa96VW9/r1b0tMKqrZxq5dDoKp8zzjhj7FG7Zd/3RCvLHvOYx/T2qGo57RHAyb5aidNWCrUVTm0frPaIZXuv7e9Lfutg+/mS+2A9+9nP7j1qd+CBB1b7NsJlX1dffXU97WlP6/24FVBtxVm/V1tZ1nLbtza2z9e+ya99q2Qr/Npm8z/60Y965VDbIH7ZIq5f9vJ+3zakP/nkk3u/agXdeeedN+7+aV3ym0VbbdYeHWyr6rwIEOguoMDqbmUkAQIECBAgQIAAAQLLCKzoAmuQTdzb42xnnXVWtX2c2je8LbnB9qr6CGHjbIVGKzbaqz1299KXvrT3WGFbldRKmv/8z//s/e/yXhN9rrZHVVs51I69/fbbey6TfY2uuGqPZbZvT3z+85+/1H5XLffiiy8e2wfr+uuv733rYVslNV451Yqxtll+K9nayrl/+Id/6Pv2ltznrH274RFHHDF2zE9+8pN67nOf2/smylZmtc8+3mb9fU9U1Svd2ubz7dUKp1bGbbLJJl0OHXfMH/3RH9Uvf/nLKZeKU3oTDiawmgoosFbTC+dtEyBAgAABAgQIEFgVBFZ0gdVWqbSN29sKm4m+Te/mm2+ubbbZpvfteO3bCL/5zW8uxZMqsNpjee3xvKOOOmpsc/mpXof2nttjhG0z9Pa4X3vErBUl7fHC9g2Mp59++rinmOhznXTSSb0VU+3V/ty+aXCyr7bxeHs0r5WCLaftOTW6/9Vo5pL7YLVH7dqKrPZqq6HaHlLLe40+dtiKp7aaAog+GgAAIABJREFUa6LXVVdd1ctp52lFWts4ftmCqu3VNfpNieNtfN/FoBVwz3nOc3ob0bf92do3ZY63OXyXvDamXc+2kq09Mtts2h5iXgQIdBdQYHW3MpIAAQIECBAgQIAAgWUEVnSB1U530EEH1Re/+MXemT/1qU/VYYcdttS7aIVGK61aydBebRXWi1/84qXGpAqspzzlKb1vvmvvqT32l3qN7vXVCrJWvLzxjW8c97Msec6JPlcrTLbeeuu68847e5uat03Tl3VZMqutWGpFYfs2wWVfo9862H7eVk21FW5L7n81On60kBod0wqbtv/VeCuhRh/ZbI9Ntvc73ib9bSVXW/XV9jab6BHBVi62byf893//93rc4x5XrfRqe4kN8nrggQd6e3614q29WnnXirGpvtr+YM2nvZbdsH+q2Y4nMB0EFFjT4Sr7jAQIECBAgAABAgRWkMAwCqxbbrmlnvGMZ/S+ta1tBN4er3v1q19dG264Ye9xrI997GO9b7lrr7aC6cwzz3zUp00VWIceemi1Pala0dK+IbCVKrNmzeqdb/311+89NjeZ15IbmrfSp638ad862FagLfko5LLZ/T7Xt771rV5p1R6rayXSK17xit5/rdhqr/nz59fll1/eK7fat/edcsop9fa3v/1RH6GtEmvvqz3uN/pacv+r0Z+N7oM1+vcDDjig94jkeK+WsdNOO/V+3fb9+pM/+ZPlDm3Wo3tk9dtI/Tvf+U7tvffevZz2OGZ7LHOQ15JfHLDjjjvWZz/72UdtQD9RXpsDy5sHbQVbK8OW3OtskPdlLIHpLqDAmu4zwOcnQIAAAQIECBAgMAWBYRRY7e21/Yf233//CTe+fvnLX94rl0YLpSU/Vr+iZ3Rsv03cW1HW9ldqq3SWfbVv0Wv7Vk3m1R4r22qrreqmm24aO7wVSa1QmujV5XO1lT/tUcS2QXy/V3t88XWve91yh7VyaXSVW1th1VZWtcfrlnyN7oM1+rO2AfrotwOOd+7RfaFaMfnpT3/6UcOaydOf/vTepvFt0/d2DcZbqTV6cFvBNprVVu+10q7ra9lvS+x63Oi4Y445pto8WvY1unrvz//8z6t9Y6YXAQKDCSiwBvMymgABAgQIECBAgACBJQSGVWC1U9577729x+va5trtG+zaaqCNNtqoVyi94Q1vqLbaZ7xXl6KnHduvwGpjWpnWHp9rj9W1DdZHy6ypFFgtd8lvXGx/b3s87brrrhPOt66fq1l95jOfqW984xvVNjsffayvrfJqBVLb36mVPE996lPHPd+HPvShaquf2mvZ/a9GD2qPc7YVRqMrtdq3Ara9pCZ6tZLune98Z28FW/NctoDcd999e9+i2IqlVpC1VW/9Xm21XvtcLa9twP6LX/yi9+hjl9eKKLAuueSS3mOJ7dX824pCLwIEBhNQYA3mZTQBAgQIECBAgAABAgQIBAVaMbnlllv2SrX2uF57THNNex1++OG9/dv22WefOu+889a0j+fzEBiKgAJrKMxOQoAAAQIECBAgQIAAAQLjCYx+Y2J7RPDnP//5uJu+r46CS35DZpdVdavjZ/SeCQxDQIE1DGXnIECAAAECBAgQIECAAIFxBdq3B7byqu139bnPfa63Sf+a8nrrW9/a2/OqPaI5+m2aa8pn8zkIDFNAgTVMbeciQIAAAQIECBAgQIAAgeUKtG9ibN+auM0226wxjxG2zflPPPHEagXdYYcdVptvvrmrT4DAJAUUWJOEcxgBAgQIECBAgAABAgQIECBAgMBwBBRYw3F2FgIECBAgQIAAAQIECBAgQIAAgUkKKLAmCecwAgQIECBAgAABAgQIECBAgACB4QgosIbj7CwECBAgQIAAAQIECBAgQIAAAQKTFFBgTRLOYQQIECBAgAABAgQIECBAgAABAsMRUGANx9lZCBAgQIAAAQIECBAgQIAAAQIEJimgwJoknMMIECBAgAABAgQIECBAgAABAgSGI6DAGo6zsxAgQIAAAQIE1kiB0047rd70pjfVYx7zmLr33nvXyM/oQxEgQIAAAQIrX0CBtfKvgXdAgAABAgQIEFgtBW699dZ6+tOf3iuv7r77bgXWankVvWkCBAgQILB6CCiwVo/r5F0SIECAAAECBFY5gQMOOKBGRkZqww03rC9+8YsKrFXuCnlDBAgQIEBgzRFQYK0519InIUCAAAECBAgMTeD000+vt73tbXXVVVfV0UcfrcAamrwTESBAgACB6SmgwJqe192nJkCAAAECBAhMWuD222+v7bbbrj74wQ/2Sqw3vOENAxdYt9xyy4TnX7BgQf3yl7+sTTbZpDbeeONae+21J/1+HUiAAAECBAYVePjhh+uOO+7oHbbDDjvUrFmzBo0wPiygwAqDiiNAgAABAgQIrOkCr3zlK2v+/Pn13e9+t/cI4WQKrHacFwECBAgQWB0ELrvssnre8563OrzVNfo9KrDW6MvrwxEgQIAAAQIEsgJf+tKX6pBDDqkrrriitwqrvRRYWWNpBAgQILBqCSiwVo3rocBaNa6Dd0GAAAECBAgQWOUF7r333tpmm23q0EMP7e17NfpqjxF+7Wtfq/ZY4DrrrNP7VsJ+r36PEM6bN6922223Xsz5559fW2yxRb9Iv59A4IEHHqgf/OAHvRE777xzrbvuurwmKcByknDjHMYz58kyZ9mSbrrpptpnn316oTfccENtueWW2RNIG1hAgTUwmQMIECBAgAABAtNT4MYbb6ytttpqwg9/4IEH1le+8pUpA7WCa7PNNuvlXHPNNbXttttOOXM6B9x///113nnn9Qjmzp1bs2fPns4cU/rsLKfE96iDeeY8WeYsW9K1115bc+bM6YW2/6fKpptumj2BtIEFFFgDkzmAAAECBAgQIDA9BdrG6pdeeumjPvwJJ5xQF154YZ199tm10UYb1fbbbz9lIAXWlAmXCnBjm/NkmbNsSTxznixzlgqsrGUqTYGVkpRDgAABAgQIEJimApPZA6sflQKrn9Bgv3djO5jXRKNZ5iwVWCyzAtk0K7Cynok0BVZCUQYBAgQIECBAYBoLKLBW/YuvdMldI5Y5SwUWy6xANk2BlfVMpCmwEooyCBAgQIAAAQIEogJWYEU5PaYV5FRgBTE9QhjFNDejnPbAynJG0hRYEUYhBAgQIECAAAECSQEFVlLTPkNJTSVBUtPcTGqam0lNm7hnNTNpCqyMoxQCBAgQIECAAIGggAIriGmVSxRTSRDltDowyGluBjF9C2EWM5SmwApBiiFAgAABAgQIEMgJKLByli3JjW3Ok2XO0txkmRXIptkDK+uZSFNgJRRlECBAgAABAgQIRAUUWFFOBVaQU4EVxFSuRjHNzSinPbCynJE0BVaEUQgBAgQIECBAgEBSQIGV1LQCK6mpJEhqmptJTXMzqWkPrKxmJk2BlXGUQoAAAQIECBAgEBRQYAUxrXKJYioJopxWBwY5zc0gpj2wspihNAVWCFIMAQIECBAgQIBATkCBlbNsSW5sc54sc5bmJsusQDbNHlhZz0SaAiuhKIMAAQIECBAgQCAqoMCKciqwgpwKrCCmcjWKaW5GOe2BleWMpCmwIoxCCBAgQIAAAQIEkgIKrKSmFVhJTSVBUtPcTGqam0lNe2BlNTNpCqyMoxQCBAgQIECAAIGggAIriGmVSxRTSRDltDowyGluBjHtgZXFDKUpsEKQYggQIECAAAECBHICCqycZUtyY5vzZJmzNDdZZgWyafbAynom0hRYCUUZBAgQIECAAAECUQEFVpRTgRXkVGAFMZWrUUxzM8ppD6wsZyRNgRVhFEKAAAECBAgQIJAUUGAlNa3ASmoqCZKa5mZS09xMatoDK6uZSVNgZRylECBAgAABAgQIBAUUWEFMq1yimEqCKKfVgUFOczOIaQ+sLGYoTYEVghRDgAABAgQIECCQE1Bg5SxbkhvbnCfLnKW5yTIrkE2zB1bWM5GmwEooyiBAgAABAgQIEIgKKLCinAqsIKcCK4ipXI1imptRTntgZTkjaQqsCKMQAgQIECBAgACBpIACK6lpBVZSU0mQ1DQ3k5rmZlLTHlhZzUyaAivjKIUAAQIECBAgQCAooMAKYlrlEsVUEkQ5rQ4McpqbQUx7YGUxQ2kKrBCkGAIECBAgQIAAgZyAAitn2ZLc2OY8WeYszU2WWYFsmj2wsp6JNAVWQlEGAQIECBAgQIBAVECBFeVUYAU5FVhBTOVqFNPcjHLaAyvLGUlTYEUYhRAgQIAAAQIECCQFFFhJTSuwkppKgqSmuZnUNDeTmvbAympm0hRYGUcpBAgQIECAAAECQQEFVhDTKpcoppIgyml1YJDT3Axi2gMrixlKU2CFIMUQIECAAAECBAjkBBRYOcuW5MY258kyZ2lusswKZNPsgZX1TKQpsBKKMggQIECAAAECBKICCqwopwIryKnACmIqV6OY5maU0x5YWc5ImgIrwiiEAAECBAgQIEAgKaDASmpagZXUVBIkNc3NpKa5mdS0B1ZWM5OmwMo4SiFAgAABAgQIEAgKKLCCmFa5RDGVBFFOqwODnOZmENMeWFnMUJoCKwQphgABAgQIECBAICegwMpZtiQ3tjlPljlLc5NlViCbZg+srGciTYGVUJRBgAABAgQIECAQFVBgRTkVWEFOBVYQU7kaxTQ3o5z2wMpyRtIUWBFGIQQIECBAgAABAkkBBVZS0wqspKaSIKlpbiY1zc2kpj2wspqZNAVWxlEKAQIECBAgQIBAUECBFcS0yiWKqSSIclodGOQ0N4OY9sDKYobSFFghSDEECBAgQIAAAQI5AQVWzrIlubHNebLMWZqbLLMC2TR7YGU9E2kKrISiDAIECBAgQIAAgaiAAivKqcAKciqwgpjK1SimuRnltAdWljOSpsCKMAohQIAAAQIECBBICiiwkppWYCU1lQRJTXMzqWluJjXtgZXVzKQpsDKOUggQIECAAAECBIICCqwgplUuUUwlQZTT6sAgp7kZxLQHVhYzlKbACkGKIUCAAAECBAgQyAkosHKWLcmNbc6TZc7S3GSZFcim2QMr65lIU2AlFGUQIECAAAECBAhEBRRYUU4FVpBTgRXEVK5GMc3NKKc9sLKckTQFVoRRCAECBAgQIECAQFJAgZXUtAIrqakkSGqam0lNczOpaQ+srGYmTYGVcZRCgAABAgQIECAQFFBgBTGtcoliKgminFYHBjnNzSCmPbCymKE0BVYIUgwBAgQIECBAgEBOQIGVs2xJbmxznixzluYmy6xANs0eWFnPRJoCK6EogwABAgQIECBAICqgwIpyKrCCnAqsIKZyNYppbkY57YGV5YykKbAijEIIECBAgAABAgSSAgqspKYVWElNJUFS09xMapqbSU17YGU1M2kKrIyjFAIECBAgQIAAgaCAAiuIaZVLFFNJEOW0OjDIaW4GMe2BlcUMpSmwQpBiCBAgQIAAAQIEcgIKrJxlS3Jjm/NkmbM0N1lmBbJp9sDKeibSFFgJRRkECBAgQIAAAQJRAQVWlFOBFeRUYAUxlatRTHMzymkPrCxnJE2BFWEUQoAAAQIECBAgkBRQYCU1rcBKaioJkprmZlLT3Exq2gMrq5lJU2BlHKUQIECAAAECBAgEBRRYQUyrXKKYSoIop9WBQU5zM4hpD6wsZihNgRWCFEOAAAECBAgQIJATUGDlLFuSG9ucJ8ucpbnJMiuQTbMHVtYzkabASijKIECAAAECBAgQiAoosKKcCqwgpwIriKlcjWKam1FOe2BlOSNpCqwIoxACBAgQIECAAIGkgAIrqWkFVlJTSZDUNDeTmuZmUtMeWFnNTJoCK+MohQABAgQIECBAICigwApiWuUSxVQSRDmtDgxymptBTHtgZTFDaQqsEKQYAgQIECBAgACBnIACK2fZktzY5jxZ5izNTZZZgWyaPbCynok0BVZCUQYBAgQIECBAgEBUQIEV5VRgBTkVWEFM5WoU09yMctoDK8sZSVNgRRiFECBAgAABAgQIJAUUWElNK7CSmkqCpKa5mdQ0N5Oa9sDKambSFFgZRykECBAgQIAAAQJBAQVWENMqlyimkiDKaXVgkNPcDGLaAyuLGUpTYIUgxRAgQIAAAQIECOQEFFg5y5bkxjbnyTJnaW6yzApk0+yBlfVMpCmwEooyCBAgQIAAAQIEogIKrCinAivIqcAKYipXo5jmZpTTHlhZzkiaAivCKIQAAQIECBAgQCApoMBKalqBldRUEiQ1zc2kprmZ1LQHVlYzk6bAyjhKIUCAAAECBAgQCAoosIKYVrlEMZUEUU6rA4Oc5mYQ0x5YWcxQmgIrBCmGAAECBAgQIEAgJ6DAylm2JDe2OU+WOUtzk2VWIJtmD6ysZyJNgZVQlEGAAAECBAgQIBAVUGBFORVYQU4FVhBTuRrFNDejnPbAynJG0hRYEUYhBAgQIECAAAECSQEFVlLTCqykppIgqWluJjXNzaSmPbCympk0BVbGUQoBAgQIECBAgEBQQIEVxLTKJYqpJIhyWh0Y5DQ3g5j2wMpihtIUWCFIMQQIECBAgAABAjkBBVbOsiW5sc15ssxZmpssswLZNHtgZT0TaQqshKIMAgQIECBAgACBqIACK8qpwApyKrCCmMrVKKa5GeW0B1aWM5KmwIowCiFAgAABAgQIEEgKKLCSmlZgJTWVBElNczOpaW4mNe2BldXMpCmwMo5SCBAgQIAAAQIEggIKrCCmVS5RTCVBlNPqwCCnuRnEtAdWFjOUpsAKQYohQIAAAQIECBDICSiwcpYtyY1tzpNlztLcZJkVyKbZAyvrmUhTYCUUZRAgQIAAAQIECEQFFFhRTgVWkFOBFcRUrkYxzc0opz2wspyRNAVWhFEIAQIECBAgQIBAUkCBldS0AiupqSRIapqbSU1zM6lpD6ysZiZNgZVxlEKAAAECBAgQIBAUUGAFMa1yiWIqCaKcVgcGOc3NIKY9sLKYoTQFVghSDAECBAgQIEBgOgj8+Mc/rr/+67+uK6+8su64446aPXt2PfWpT62/+Iu/qEMPPTRGoMCKUfaC3NjmPFnmLM1NllmBbJo9sLKeiTQFVkJRBgECBAgQIEBgmghccMEF9S//8i+1++6715Of/OS677776owzzuj97Ljjjqujjz46IqHAijCOhShdcp4sc5YKLJZZgWyaAivrmUhTYCUUZRAgQIAAAQIEprnALrvsUv/xH/9RN998c0RCgRVhVGBlGXtpCqwsKs+cJ8ucZUtSYGU9E2kKrISiDAIECBAgQIDANBfYf//966qrrqrrr78+IqHAijAqsLKMCiyeK0AgF6nAylkqsLKWqTQFVkpSDgECBAgQIEBgGgksWrSo2n+/+tWv6gtf+EIdccQR9YlPfKL+/M//vJNCK6gmes2fP7922mmn3pC239bWW2/dKdeg5QssWLCgLrroot4v99xzz5o1axaqSQqwnCTcOIfxzHmyzFm2pOuuu6522GGHXui8efNq0003zZ5A2sACCqyByRxAgAABAgQIECDwlre8pU499dQexMyZM+vjH/94vfWtb+0MMzIy0nnsaaedVhtttFHn8QYSIECAAIGpCtx55511+OGHK7CmChk8XoEVxBRFgAABAgQIEJguAm2vq9tvv73339e//vX653/+5zrxxBPryCOP7ESgwOrEZBABAgQIrCQBBdZKgp/gtAqsVe+aeEcECBAgQIAAgdVOoK2+aiul2kbuG2+8cd/37xHCvkTRAR4tynGyzFm2JJ45T5Y5y5bkEcKsZyJNgZVQlEGAAAECBAgQmOYCn/nMZ+qwww6rSy+9tHbeeecpa9jEfcqESwXY3DnnyTJn2ZJ45jxZ5ixbkm8hzHom0hRYCUUZBAgQIECAAIFpLvC6172uzjjjjLrttts6rcDqx6XA6ic02O/d2A7mNdFoljlLBRbLrEA2TYGV9UykKbASijIIECBAgAABAtNE4M1vfnOtv/76vW8I3GSTTartEdK+hfDMM8+sv/zLv6yTTjopIqHAijCOhShdcp4sc5YKLJZZgWyaAivrmUhTYCUUZRAgQIAAAQIEpolAe1Sw/feLX/yifv3rX9djH/vY2nHHHXvf1HTooYfGFBRYMcpekNIl58kyZ2lusswKZNMUWFnPRJoCK6EogwABAgQIECBAICqgwIpyKrCCnAqsIKZyNYppbkY57YGV5YykKbAijEIIECBAgAABAgSSAgqspKYVWElNJUFS09xMapqbSU2buGc1M2kKrIyjFAIECBAgQIAAgaCAAiuIaZVLFFNJEOW0OjDIaW4GMX0LYRYzlKbACkGKIUCAAAECBAgQyAkosHKWLcmNbc6TZc7S3GSZFcim2QMr65lIU2AlFGUQIECAAAECBAhEBRRYUU4FVpBTgRXEVK5GMc3NKKc9sLKckTQFVoRRCAECBAgQIECAQFJAgZXUtAIrqakkSGqam0lNczOpaQ+srGYmTYGVcZRCgAABAgQIECAQFFBgBTGtcoliKgminFYHBjnNzSCmPbCymKE0BVYIUgwBAgQIECBAgEBOQIGVs2xJbmxznixzluYmy6xANs0eWFnPRJoCK6EogwABAgQIECBAICqgwIpyKrCCnAqsIKZyNYppbkY57YGV5YykKbAijEIIECBAgAABAgSSAgqspKYVWElNJUFS09xMapqbSU17YGU1M2kKrIyjFAIECBAgQIAAgaCAAiuIaZVLFFNJEOW0OjDIaW4GMe2BlcUMpSmwQpBiCBAgQIAAAQIEcgIKrJxlS3Jjm/NkmbM0N1lmBbJp9sDKeibSFFgJRRkECBAgQIAAAQJRAQVWlFOBFeRUYAUxlatRTHMzymkPrCxnJE2BFWEUQoAAAQIECBAgkBRQYCU1rcBKaioJkprmZlLT3Exq2gMrq5lJU2BlHKUQIECAAAECBAgEBRRYQUyrXKKYSoIop9WBQU5zM4hpD6wsZihNgRWCFEOAAAECBAgQIJATUGDlLFuSG9ucJ8ucpbnJMiuQTbMHVtYzkabASijKIECAAAECBAgQiAoosKKcCqwgpwIriKlcjWKam1FOe2BlOSNpCqwIoxACBAgQIECAAIGkgAIrqWkFVlJTSZDUNDeTmuZmUtMeWFnNTJoCK+MohQABAgQIECBAICigwApiWuUSxVQSRDmtDgxymptBTHtgZTFDaQqsEKQYAgQIECBAgACBnIACK2fZktzY5jxZ5izNTZZZgWyaPbCynok0BVZCUQYBAgQIECBAgEBUQIEV5VRgBTkVWEFM5WoU09yMctoDK8sZSVNgRRiFECBAgAABAgQIJAUUWElNK7CSmkqCpKa5mdQ0N5Oa9sDKambSFFgZRykECBAgQIAAAQJBAQVWENMqlyimkiDKaXVgkNPcDGLaAyuLGUpTYIUgxRAgQIAAAQIECOQEFFg5y5bkxjbnyTJnaW6yzApk0+yBlfVMpCmwEooyCBAgQIAAAQIEogIKrCinAivIqcAKYipXo5jmZpTTHlhZzkiaAivCKIQAAQIECBAgQCApoMBKalqBldRUEiQ1zc2kprmZ1LQHVlYzk6bAyjhKIUCAAAECBAgQCAoosIKYVrlEMZUEUU6rA4Oc5mYQ0x5YWcxQmgIrBCmGAAECBAgQIEAgJ6DAylm2JDe2OU+WOUtzk2VWIJtmD6ysZyJNgZVQlEGAAAECBAgQIBAVUGBFORVYQU4FVhBTuRrFNDejnPbAynJG0hRYEUYhBAgQIECAAAECSQEFVlLTCqykppIgqWluJjXNzaSmPbCympk0BVbGUQoBAgQIECBAgEBQQIEVxLTKJYqpJIhyWh0Y5DQ3g5j2wMpihtIUWCFIMQQIECBAgAABAjkBBVbOsiW5sc15ssxZmpssswLZNHtgZT0TaQqshKIMAgQIECBAgACBqIACK8qpwApyKrCCmMrVKKa5GeW0B1aWM5KmwIowCiFAgAABAgQIEEgKKLCSmlZgJTWVBElNczOpaW4mNe2BldXMpCmwMo5SCBAgQIAAAQIEggIKrCCmVS5RTCVBlNPqwCCnuRnEtAdWFjOUpsAKQYohQIAAAQIECBDICSiwcpYtyY1tzpNlztLcZJkVyKbZAyvrmUhTYCUUZRAgQIAAAQIECEQFFFhRTgVWkFOBFcRUrkYxzc0opz2wspyRNAVWhFEIAQIECBAgQIBAUkCBldS0AiupqSRIapqbSU1zM6lpD6ysZiZNgZVxlEKAAAECBAgQIBAUUGAFMa1yiWIqCaKcVgcGOc3NIKY9sLKYoTQFVghSDAECBAgQIECAQE5AgZWzbElubHOeLHOW5ibLrEA2zR5YWc9EmgIroSiDAAECBAgQIEAgKqDAinIqsIKcCqwgpnI1imluRjntgZXljKQpsCKMQggQIECAAAECBJICCqykphVYSU0lQVLT3ExqmptJTXtgZTUzaQqsjKMUAgQIECBAgACBoIACK4hplUsUU0kQ5bQ6MMhpbgYx7YGVxQylKbBCkGIIECBAgAABAgRyAgqsnGVLcmOb82SZszQ3WWYFsmn2wMp6JtIUWAlFGQQIECBAgAABAlEBBVaUU4EV5FRgBTGVq1FMczPKaQ+sLGckTYEVYRRCgAABAgQIECCQFFBgJTWtwEpqKgmSmuZmUtPcTGraAyurmUlTYGUcpRAgQIAAAQIECAQFFFhBTKtcophKgiin1YFBTnMziGkPrCxmKE2BFYIUQ4AAAQIECBAgkBNQYOUsW5Ib25wny5yluckyK5BNswdW1jORpsBKKMogQIAAAQIECBCICiiwopwKrCCnAiuIqVyNYpqbUU57YGU5I2kKrAijEAIECBAgQIAAgaSAAiupaQVWUlNJkNQ0N5Oa5mZS0x5YWc1MmgIr4yiFAAECBAgQIEAgKKDACmJa5RLFVBJEOa0ODHKam0FMe2BlMUNpCqwQpBgCBAgQIECAAIGcgAI0A8MwAAAgAElEQVQrZ9mS3NjmPFnmLM1NllmBbJo9sLKeiTQFVkJRBgECBAgQIECAQFRAgRXlVGAFORVYQUzlahTT3Ixy2gMryxlJU2BFGIUQIECAAAECBAgkBRRYSU0rsJKaSoKkprmZ1DQ3k5r2wMpqZtIUWBlHKQQIECBAgAABAkEBBVYQ0yqXKKaSIMppdWCQ09wMYtoDK4sZSlNghSDFECBAgAABAgQI5AQUWDnLluTGNufJMmdpbrLMCmTT7IGV9UykKbASijIIECBAgAABAgSiAgqsKKcCK8ipwApiKlejmOZmlNMeWFnOSJoCK8IohAABAgQIECBAICmgwEpqWoGV1FQSJDXNzaSmuZnUtAdWVjOTpsDKOEohQIAAAQIECBAICiiwgphWuUQxlQRRTqsDg5zmZhDTHlhZzFCaAisEKYYAAQIECBAgQCAnoMDKWbYkN7Y5T5Y5S3OTZVYgm2YPrKxnIk2BlVCUQYAAAQIECBAgEBVQYEU5FVhBTgVWEFO5GsU0N6Oc9sDKckbSFFgRRiEECBAgQIAAAQJJAQVWUtMKrKSmkiCpaW4mNc3NpKY9sLKamTQFVsZRCgECBAgQIECAQFBAgRXEtMoliqkkiHJaHRjkNDeDmPbAymKG0hRYIUgxBAgQIECAAAECOQEFVs6yJbmxzXmyzFmamyyzAtk0e2BlPRNpCqyEogwCBAgQIECAAIGogAIryqnACnIqsIKYytUoprkZ5bQHVpYzkqbAijAKIUCAAAECBAgQSAoosJKaVmAlNZUESU1zM6lpbiY17YGV1cykKbAyjlIIECBAgAABAgSCAgqsIKZVLlFMJUGU0+rAIKe5GcS0B1YWM5SmwApBiiFAgAABAgQIEMgJKLByli3JjW3Ok2XO0txkmRXIptkDK+uZSFNgJRRlECBAgAABAgQIRAUUWFFOBVaQU4EVxFSuRjHNzSinPbCynJE0BVaEUQgBAgQIECBAgEBSQIGV1LQCK6mpJEhqmptJTXMzqWkPrKxmJk2BlXGUQoAAAQIECBAgEBRQYAUxrXKJYioJopxWBwY5zc0gpj2wspihNAVWCFIMAQIECBAgQIBATkCBlbNsSW5sc54sc5bmJsusQDbNHlhZz0SaAiuhKIMAAQIECBAgME0E/vVf/7VOP/30+v73v1/z5s2rDTbYoJ773OfW+9///nrOc54TU1BgxSh7QUqXnCfLnKW5yTIrkE1TYGU9E2kKrISiDAIECBAgQIDANBE46KCD6r/+67+q/e92221Xd9xxR5188sn1ox/9qM4999zae++9IxIKrAjjWIjSJefJMmepwGKZFcimKbCynok0BVZCUQYBAgQIECBAYJoI3H777fWEJzxhqU9777331jbbbFPbb799fetb34pIKLAijAqsLGMvTYGVReWZ82SZs2xJCqysZyJNgZVQlEGAAAECBAgQmOYCbeXVrbfeWldffXVEQoEVYVRgZRkVWDxXgEAuUoGVs1RgZS1TaQqslKQcAgQIECBAgMA0Fbj77rtriy226D0++OUvf7mTQiuoJnrNnz+/dtppp96QK6+8srbeeutOuQYtX2DBggV10UUX9X6555571qxZs1BNUoDlJOHGOYxnzpNlzrIlXXfddbXDDjv0Qtuej5tuumn2BNIGFlBgDUzmAAIECBAgQIAAgSUFDj300DrzzDPr0ksv7byR+8jISGfE0047rTbaaKPO4w0kQIAAAQJTFbjzzjvr8MMPV2BNFTJ4vAIriCmKAAECBAgQIDDdBN73vvfVhz70oTrllFPq7W9/e+ePr8DqTGUgAQIECKwEAQXWSkDvc0oF1qp3TbwjAgQIECBAgMBqIfCBD3ygjj322Prwhz9c733vewd6zx4hHIhryoM9WjRlwrEAljnLlsQz58kyZ9mSPEKY9UykKbASijIIECBAgAABAtNMYLS8agXWMcccE//0NnHPktrcOefJMmfZknjmPFnmLFuSbyHMeibSFFgJRRkECBAgQIAAgWkkcNxxx9X73//+Ovroo6v9eUW8FFhZVTe2OU+WOUsFFsusQDZNgZX1TKQpsBKKMggQIECAAAEC00Tg5JNPriOPPLL23Xff5a682mWXXSISCqwI41iI0iXnyTJnqcBimRXIpimwsp6JNAVWQlEGAQIECBAgQGCaCOy111514YUXjvtpFy9eHJFQYEUYFVhZxl6aAiuLyjPnyTJn2ZIUWFnPRJoCK6EogwABAgQIECBAICqgwIpyKl2CnEqCIKZCMIppbkY5FVhZzkiaAivCKIQAAQIECBAgQCApoMBKalo1lNRUEiQ1zc2kprmZ1LQCK6uZSVNgZRylECBAgAABAgQIBAUUWEFMq1yimEqCKKfVgUFOczOI6RHCLGYoTYEVghRDgAABAgQIECCQE1Bg5SxbkhvbnCfLnKW5yTIrkE2zB1bWM5GmwEooyiBAgAABAgQIEIgKKLCinAqsIKcCK4ipXI1imptRTntgZTkjaQqsCKMQAgQIECBAgACBpIACK6lpBVZSU0mQ1DQ3k5rmZlLTHlhZzUyaAivjKIUAAQIECBAgQCAooMAKYlrlEsVUEkQ5rQ4McpqbQUx7YGUxQ2kKrBCkGAIECBAgQIAAgZyAAitn2ZLc2OY8WeYszU2WWYFsmj2wsp6JNAVWQlEGAQIECBAgQIBAVECBFeVUYAU5FVhBTOVqFNPcjHLaAyvLGUlTYEUYhRAgQIAAAQIECCQFFFhJTSuwkppKgqSmuZnUNDeTmvbAympm0hRYGUcpBAgQIECAAAECQQEFVhDTKpcoppIgyml1YJDT3Axi2gMrixlKU2CFIMUQIECAAAECBAjkBBRYOcuW5MY258kyZ2lusswKZNPsgZX1TKQpsBKKMggQIECAAAECBKICCqwopwIryKnACmIqV6OY5maU0x5YWc5ImgIrwiiEAAECBAgQILDiBfbaa6+68MILBzrR4sWLBxq/qgxWYGWvhBvbnCfLnGVL4pnzZJmzbElWYGU9E2kKrISiDAIECBAgQIDAEATe8Y531BVXXNH3TG3Mb3/723r84x9fv/71r/uOXxUHKLCyV8WNbc6TZc5SgcUyK5BNU2BlPRNpCqyEogwCBAgQIECAwCoicNZZZ9X+++9fbeXVl7/85frTP/3TVeSdDfY2FFiDefUbrXTpJ9T99yy7W3UZybOLUrcxLLs5dR2lwOoqNbxxCqzhWTsTAQIECBAgQGCFCsybN6+e9axn1X/913/VEUccUR//+MdX6PlWZLgCK6vrxjbnyTJn2ZJ45jxZ5ixbkgIr65lIU2AlFGUQIECAAAECBFaywMMPP1x77rlnXXLJJbXTTjvVxRdfXDNnzlzJ72ryp1dgTd5ueUe6sc15ssxZKrBYZgWyaQqsrGciTYGVUJRBgAABAgQIEFjJAkceeWSdfPLJtcEGG/T2ydpyyy1X8jua2ukVWFPzW/ZopUvOk2XOUoHFMiuQTVNgZT0TaQqshKIMAgQIECBAgMBKFPj6179eBx54YG/fq6985Su9P6/uLwVW9goqXXKeLHOWCiyWWYFsmgIr65lIU2AlFGUQIECAAAECBFaSwM0339zb9+quu+6qd73rXb1VWGvCS4GVvYpKl5wnyw6W3/1u1e67dxg4xT2wBjhPpzezmg8yN7MXUIGV9UykKbASijIIECBAgAABAitB4KGHHqo99tijfvCDH9TOO+/c2/dqnXXWWQnvJH9KBVbW1I1tzpNlH8tjj636wAeqTjih6t3v7gs/ac8TT6w66qiqY46pauf0siF+eA4osMKggTgFVgBRBAECBAgQIEBgZQi0FVd/+7d/WxtuuGFv36vNN998ZbyNFXJOBVaWddIlQfZtrBFpLCe4jG1F1B57PDKgQ4k1Kc/R8mr0TBdf3HnF1xoxCcf5EJOyXJNBpvjZFFhTBFwBhyuwVgCqSAIECBAgQIDAihb46le/Wi972ctqZGSk2p8POOCAFX3KoeYrsLLcbmxzniz7WC5bLvUpsQb2HDA/d+VX/aSBLVf9j7RS36ECa6XyL/fkCqxV75p4RwQIECBAgACBCQVuvPHG3r5Xv/71r6t9++BHP/rRNU5MgZW9pG5sc54sO1gOUDIN5DlAbod3ucYNGchyjfv0+Q+kwMqbTjVRgTVVQccTIECAAAECBIYo8OCDD9buu+9eP/zhD2u33XarCy+8sNZee+0hvoPhnEqBlXV2Y5vzZNnRsmPZ1NmzY17Hd7dGDutsuUZ++vyHUmDlTaeaqMCaqqDjCRAgQIAAAQJDFDjiiCPq7//+7+sP//APe/tebbbZZkM8+/BOpcDKWruxzXmyHMCyQ+nUybNDzgDvao0d2slyjf30+Q+mwMqbTjVRgTVVQccTIECAAAECBIYk8OUvf7le8YpX9Pa9+sY3vlH77bffkM48/NMosLLmbmxzniwHtOxTPvX1VF51Bu9r2TnJwCagwFr15oECa9W7Jt4RAQIECBAgQGC5AhtssEHdfffdtd566/X2wOryOuWUUzqP7ZI3rDEKrKy0G9ucJ8tJWE5QQi247eq66qxP1joLf1tP3fF5NXPbvav+YIvfnUR5NRC2uTkQV9/BCqy+REMfoMAaOrkTEiBAgAABAgQmJ9BWXg36+s53vlN77bXXoIet9PEKrOwlcGOb82Q5Sctly6j3vL3q6f9Zi689r0Zq8RKhI1Xbzq36+SZVx3/ikZ/3+TbDSb6rNeowczN7ORVYWc9EmgIroSiDAAECBAgQIEAgKqDAinKWG9ucJ8spWC5bYr1w3ard13104HcfqPr2A8qrAanNzQHB+gxXYGU9E2kKrISiDAIECBAgQIAAgaiAAivKqcAKcioJpoj53ncsvbJq2RJr2fKqrdT6yClTPOn0ONzczF5nBVbWM5GmwEooyiBAgAABAgQIEIgKKLCinAqsIKeSYIqYZxxc9ZmvLb3CarTEWra8aj8/7MCqQ86c4kmnx+HmZvY6K7Cynok0BVZCUQYBAgQIECBAgEBUQIEV5VRgBTmVBFPA/NVNVX+3Y1Xb82rZsmr2SNX9S+yFNbYya6Tqf/y0aoPNp3Di6XGouZm9zgqsrGciTYGVUJRBgAABAgQIECAQFVBgRTkVWEFOJcEUMK84o+qrb3skYNkSa/Q3yz5W+LJ/rHrmIVM48fQ41NzMXmcFVtYzkabASijKIECAAAECBAgQiAoosKKcCqwgp5JgCpiX/mPVOUctHXDSPUuvvGorsf7qcUuP2ffEql3eMoUTT49Dzc3sdVZgZT0TaQqshKIMAgQIECBAgACBqIACK8qpwApyKgmmgGkF1hTw+h9qbvY3GmSEAmsQreGMVWANx9lZCBAgQIAAAQIEBhBQYA2A1WGoG9sOSB2HsOwItbxh9sCaAl7/Q83N/kaDjFBgDaI1nLEKrOE4OwsBAgQIECBAgMAAAgqsAbA6DHVj2wGp4xCWHaHGG+ZbCKcIOP7h5maWVoGV9UykKbASijIIECBAgAABAgSiAgqsKKdHCIOcSoIpYr73HVXHf+KRkGU3bF92Y/f3vL3qI6dM8aTT43BzM3udFVhZz0SaAiuhKIMAAQIECBAgQCAqoMCKciqwgpxKgilgnnhi1VFLbOK+bHk1Gr1siXXCCVXvfvcUTjw9DjU3s9dZgZX1TKQpsBKKMggQIECAAAECBKICCqwopwIryKkkmCTmMuXVpa8+pO7d5tbae8aPa8bI4iVCR6rmvKjqZ09YeqWWEqsvvLnZl2igAQqsgbiGMliBNRRmJyFAgAABAgQIEBhEQIE1iFb/sW5s+xt1HcGyq9QS45ZdeXXCCfXSxzy/fnrL3bXpyB2188gvapcN760D93xezZyzd9UGm//u4OUcZyXW+P7m5iTm5gSHKLCynok0BVZCUQYBAgQIECBAgEBUQIEV5bQCK8ipJBgQczkl1IJ3HVnbH3NuPbzokZVXb99uYf3FQfvU7Nmzlz6BEqszuLnZmarTQAVWJ6ahDlJgDZXbyQgQIECAAAECBLoIKLC6KHUf48a2u1W/kSz7CS3x+3HKpx/deFe98p8uGRs4UovrhJ0W1ktfPPfRBVYbpcTqhG5udmLqPEiB1ZlqaAMVWEOjdiICBAgQIECAAIGuAgqsrlLdxrmx7ebUZRTLLkoTl06nXXx9feibvxgLetJ6i+vdOy6suXPHKbCUWJ3Qzc1OTJ0HKbA6Uw1toAJraNRORIAAAQIECBAg0FVAgdVVqts4N7bdnLqMYtlBqc+Kqb8449/qm1fOHwva9QmL6tVbL5q4wFJi9YU3N/sSDTRAgTUQ11AGK7CGwuwkBAgQIECAAAECgwgosAbR6j/WjW1/o64jWPaR6vC4327Hf7v+4+4FY0Gv2Xph7fKExf0LLCXWhPjmZtd/xd3GKbC6OQ1zlAJrmNrORYAAAQIECBAg0ElAgdWJqfMgN7adqfoOZDkB0Xe/W7XHHo8MOOGEWvZbA//zNwtq5498e6mQ9+z4cP239apbgbW8Euvii6t2373vtVvTB5ib2SuswMp6JtIUWAlFGQQIECBAgAABAlEBBVaU07cQBjmVBH0wjz226gMfqFpOedWOPOdnt9VbTr98LOSx665Vxz3rgZoxMkCBtWSJdcwxVe2cXv6dh+eAAisMGohTYAUQRRAgQIAAAQIECGQFFFhZT6VLzpNlB8u2EmucFVHHn/2LOvXC68dCdn3KH9SrN7mj9/cJN3Ff3mknOE+Hd7nGDTE3s5dUgZX1TKQpsBKKMggQIECAAAECBKICCqwop5UZQU4lwdQwDz71krrshrvGQt6yx5b1Rw//++QKrKm9lTXuaHMze0kVWFnPRJoCK6EogwABAgQIECBAICqgwIpyKrCCnEqCyWM+vHBR7XDseXX/QwvHQv7hNc+oh278NwXW5FnHjjQ3A4hLRCiwsp6JNAVWQlEGAQIECBAgQIBAVECBFeVUYAU5lQSTx/z5f9xdL/n77y4V8L0jd68ffe8CBdbkWRVYAbvlRSiwVhDsFGIVWFPAcygBAgQIECBAgMCKEVBgZV2VLjlPlpO3PP3Sm+ror/xsLGCLP1yvznn7LnXeeecpsCbPqsAK2CmwVhBiOFaBFQYVR4AAAQIECBAgMHUBBdbUDZdMULrkPFlO3vLIL/ykvnj5LWMBL3vmk+r4A5+mwJo86VJHmpshyN/HWIGV9UykKbASijIIECBAgAABAgSiAgqsKKdHCIOcSoLJY77w5AvqujvuGws49oDt6lXP/m8KrMmTKrBCdsuLUWCtQNxJRiuwJgnnMAIECBAgQIAAgRUnoMDK2ipdcp4sJ2d5928fqh0/+LtHBUdfX/2L59ecjdZVYE2O9FFHmZshyN/HKLCynok0BVZCUQYBAgQIECBAgEBUQIEV5bQCK8ipJJgc5oXX3FGv//RlYwfPXHtG/ezYF9XChx5QYE2OVIEVchsvRoG1goEnEa/AmgSaQwgQIECAAAECBFasgAIr66t0yXmynJzl333r2vrbb10zdvCzN9+gvvy25ytXJ8e53KPMzSBmVSmwsp6JNAVWQlEGAQIECBAgQIBAVECBFeVUEgQ5lQSTw3zDZy6rC66+Y+zgN+6+Vb1v/+3MzclxKrCCbuNFKbCGgDzgKRRYA4IZToAAAQIECBAgsOIFFFhZY6VLzpPl4JaLFy+uZx13fv36tw+NHfyJQ55V+z/jSQqswTnHPcLcDGJagZXFDKUpsEKQYggQIECAAAECBHICCqycZUtyY5vzZDm45Q133lcv+NgFSx34vaP2ridvMNvcHJxTgRU0myjKCqwhQQ9wGgXWAFiGEiBAgAABAgQIDEdAgZV1VrrkPFkObvnlf7ul3vX5n4wduPHj1q3L3vvCGhkZUWANzqnACpopsIaEGTqNAisEKYYAAQIECBAgQCAnoMDKWbYkpUvOk+Xglu/7ys/qs5feNHbg3O02qX9+3XN7f+c5uOd4R7DMWbYkK7Cynok0BVZCUQYBAgQIECBAgEBUQIEV5VQSBDmVBINj7n/KxfWzW38zduC7931avXWvrRVYg1NOeIS5mQVVYGU9E2kKrISiDAIECBAgQIAAgaiAAivKqcAKcioJBsO8/8GFtcOx59bDixaPHfi5N+1Su279hwqswSj7jjY3+xINNECBNRDXUAYrsIbC7CQECBAgQIAAAQKDCCiwBtHqP9aNbX+jriNYdpX63bgf3nhXHfRPl4wdNGOk6spjX1SPWXdtBdZglH1Hm5t9iQYaoMAaiGsogxVYQ2F2EgIECBAgQIAAgUEEFFiDaPUf68a2v1HXESy7Sv1u3D9fdF195Kxfjh30R09cv84+Yo+xv/MczHOi0Sxzli1JgZX1TKQpsBKKMggQIECAAAECBKICCqwop0cIg5xKgsEw33bG5XXWlbeNHXTIzpvXR/50BwXWYIydRpubnZg6D1JgdaYa2kAF1tConYgAAQIECBAgQKCrgAKrq1S3cW5suzl1GcWyi9IjY3Y9/ts1/+4FYz846ZXPqIOfu5kCazDGTqPNzU5MnQcpsDpTDW2gAmto1E5EgAABAgQIEFj9Be6555467rjj6sc//nFdccUVdeedd9YxxxxTxx57bPTDKbCinFZgBTmVBN0xb7t7Qe1y/LeXOuBb79qztnnC4xRY3Rk7jzQ3O1N1GqjA6sQ01EEKrKFyOxkBAgQIECBAYPUWuPHGG+uZz3xm7bjjjjVnzpw67bTTFFirwSV1Y5u7SCy7W57zs/n1ltP/beyAx81au37y/rk1o+3k/vsXz+6e/Uay7Cc02O8VWIN5DWO0AmsYys5BgAABAgQIEFhDBBYvXtz7JCMjI73VVxtvvLECazW4tm5scxeJZXfL48/6RZ160fVjB+yx7Ub12TfuvFQAz+6e/Uay7Cc02O8VWIN5DWO0AmsYys5BgAABAgQIEFgDBRRYq89FdWObu1Ysu1se/E+X1GU33jV2wDv33qbeNfepCqzuhAONNDcH4uo7WIHVl2joAxRYQyd3QgIECBAgQIDAmiEwlQKr7XE10Wv+/Pm100479YZceeWVtfXWW68ZaCvpUyxYsKAuuuii3tn33HPPmjVr1kp6J6v/aVl2u4YPLVxUO51wUS14eNHYAf90yDPqj7fdaKkAnt08u4xi2UWp+5jrrruudtjhd9+YOW/evNp00027H2zkChFQYK0QVqEECBAgQIAAgTVfYCoFVnsEseur7bO10UZL3/R2PdY4AgRWjsAt91V99KdrL3XyDz/34XrsOivn/TgrgUEF2v+NO/zwwxVYg8KtwPEKrBWIK5oAAQIECBAgsCYLKLDW5KvrsxGYmsB3bxupL9yw1ljIRrMW1/uetXBqoY4mMEQBBdYQsTueSoHVEcowAgQIECBAgACBpQWmUmB5hHC4s8mjRTlvlt0sj/rKVfXVn9w2NviAZ2xSJ/3p0x91MM9unl1Gseyi1H2MRwi7Ww1rpAJrWNLOQ4AAAQIECBBYwwSmUmD1o2gF12abbdYbds0119S2227b7xC/n0DA5s656cGym+XeJ19Q199x39jgDx749Hrdrls+6mCe3Ty7jGLZRan7GJu4d7ca1kgF1rCknYcAAQIECBAgsIYJKLBWnwvqxjZ3rVj2t/z1bx+sZ37w/KUGfu3tz69nbLqBAqs/36RHmJuTplvugQqsrGciTYGVUJRBgAABAgQIEJhGAmeffXbdd999dc8999Rhhx1WBx10UB188ME9gf3226/WW2+9KWtYgTVlwqUC3NjmPFn2t7zg6tvrDZ/54djAddeeUVce+6KaufYMBVZ/vkmPMDcnTafAytKtsDQF1gqjFUyAAAECBAgQWDMFttxyy7rpppuW++FuuOGGar+f6kuBNVXBpY93Y5vzZNnf8m/Pv6b+7tvXjg187hZ/UF98627LPZBnf8+uI1h2leo2zgqsbk7DHKXAGqa2cxEgQIAAAQIECHQSUGB1Yuo8yI1tZ6q+A1n2JarXf/qyuvCaO8YGHr77VnX0/tspsPrTTWmEuTklvkcdrMDKeibSFFgJRRkECBAgQIAAAQJRAQVWlLPc2OY8WU5suWjR4nrWcefX3fc/NDbwfx3y7HrJM56owMpNQ5Yr2LLFK7CGgDzgKRRYA4IZToAAAQIECBAgsOIFFFhZY6VLzpPlxJbX3XFvvfDkC5ca9P2j9q4nbTBb6ZKbhixXsKUCawjAkziFAmsSaA4hQIAAAQIECBBYsQIKrKyv0iXnyXJiyy9dfkv9zy/8ZGzQJuuvW5e+54U1MjKidMlNQ5Yr2FKBNQTgSZxCgTUJNIcQIECAAAECBAisWAEFVtZX6ZLzZDmx5dFfubJOv/TmsUEvevomdeqfPXfcg3iamzmBbJJHCLOeiTQFVkJRBgECBAgQIECAQFRAgRXltAdWkFPhMjHmS/7+4vr5f/xmbNBRL35aveWPt1ZgBefgeFHmZhZZgZX1TKQpsBKKMggQIECAAAECBKICCqwopwIryKkkGB/z/gcX1vbHnlsLFy0eG3Tmm3epnZ/yhwqs4BxUYA0B0ybuw0Ee8CwKrAHBDCdAgAABAgQIEFjxAgqsrLHSJefJcnzLy264qw4+9ZKxAWvNGKkrj51b681cW4GVm4Ish2DZTmEF1pCgBziNAmsALEMJECBAgAABAgSGI6DAyjorXXKeLMe3PPXC6+r4s385NmC7J65fZx2xx4T4PM3NnEA2SYGV9UykKbASijIIECBAgAABAgSiAgqsKKdHCIOcCpfxMd/y2cvrnJ/fNjbgtTtvXh/+0x0UWMH5N1GUuZmFVmBlPRNpCqyEogwCBAgQIECAAIGogAIryqnACnIqCcbH3OUj367bfrNgbMBHX/mMOui5mymwgvNPgTUkTI8QDg96gDMpsAbAMpQAAQIECBAgQGA4AgqsrLPSJefJcvmW8+++v3Y9/l+X+uW33tvmq50AACAASURBVPXHtc0THqvAyk0/lkOybKexAmuI2B1PpcDqCGUYAQIECBAgQIDA8AQUWFlrpUvOk+XyLc+6cn697Yx/G/vl+rPWrh+/f27NmDGidMlNP5ZDslRgDRF6gFMpsAbAMpQAAQIECBAgQGA4AgqsrLPSJefJcvmWH/7mVfXJi28Y++Weczau/3vYTn3hefYl6jyAZWeqTgOtwOrENNRBCqyhcjsZAQIECBAgQIBAFwEFVhel7mPc2Ha36jeS5fKFDvqn79cPb/zV2C/f+cJt6137zOnHaX+2vkLdB5ib3a26jFRgdVEa7hgF1nC9nY0AAQIECBAgQKCDgAKrA9IAQ9zYDoDVZyjLRwM9tHBRbX/MufXAw4vGfvmZ//68esFTn9AXnmdfos4DWHam6jRQgdWJaaiDFFhD5XYyAgQIECBAgACBLgIKrC5K3ce4se1u1W8ky0cLXXnL3XXAJ7671C+ueN8+9QePmdmP0wqsvkLdB5ib3a26jFRgdVEa7hgF1nC9nY0AAQIECBAgQKCDgAKrA9IAQ9zYDoDVZyjLRwN99pIb631f/fnYL7ba6DH1nSP36oTOsxNTp0EsOzF1HqTA6kw1tIEKrKFROxEBAgQIECBAgEBXAQVWV6lu49zYdnPqMorlo5XedeaP68tX3Dr2i5c/68n1N696ZhdOK7A6KXUbZG52c+o6SoHVVWp44xRYw7N2JgIECBAgQIAAgY4CCqyOUB2HubHtCNVhGMtHI73gYxfUDXfeN/aL4w58ev3Zrlt20CwFVielboPMzW5OXUcpsLpKDW+cAmt41s5EgAABAgQIECDQUUCB1RGq4zA3th2hOgxjuTTSr+57sJ513PlL/fAb79i9tn/y4ztoKrA6IXUcZG52hOo4TIHVEWqIwxRYQ8R2KgIECBAgQIAAgW4CCqxuTl1HubHtKtV/HMuljb5z9e313z/zw7Efrrv2jPrZB15U66w1oz9mKbA6IXUcZG52hOo4TIHVEWqIwxRYQ8R2KgIECBAgQIAAgW4CCqxuTl1HubHtKtV/HMuljf7m/Gvq77997dgPn7flH9QX3rJbf8jfj+DZmarvQJZ9iQYaoMAaiGsogxVYQ2F2EgIECBAgQIAAgUEEFFiDaPUf68a2v1HXESyXlvqzT/2gLr72zrEfvnnPp9R79/ujrpz2wOos1X+gudnfaJARCqxBtIYzVoE1HGdnIUCAAAECBAgQGEBAgTUAVoehbmw7IHUcwvIRqEWLFtczP3he/WbBw2M//IfXPrv22+GJHTU9QtgZqsNAc7MD0gBDFFgDYA1pqAJrSNBOQ4AAAQIECBAg0F1AgdXdqstIN7ZdlLqNYfmI07/ffm/9yd9cuBTcJe/Zu574+NndMO2B1dmpy0Bzs4tS9zEKrO5WwxqpwBqWtPMQIECAAAECBAh0FlBgdabqNNCNbSemToNY/p7pVzfVZRd8rc7+0dV1T61Xly7arh5+3GZ16Xtf2MlxdBDPgbgmHMwyZ9mSFFhZz0SaAiuhKIMAAQIECBAgQCAqoMCKctpnKMg57UuCWy+vuuDEqmvPq6rFY7KLFo/Uzx+zc+3w2o9UPfk5ncWnvWdnqf4DWfY3GmSEAmsQreGMVWANx9lZCBAgQIAAAQIEBhBQYA2A1WGoG9sOSB2HTGvLq75W9aU3Vi18cHyttWZWveJTVdu9tJPotPbsJNR9EMvuVl1GKrC6KA13jAJruN7ORoAAAQIECBAg0EFAgdUBaYAhC267uq4665O1zsLf1lN3fF7N3Hbvqj/YYoCEaTT0VzdV3fjdqgd+U7Xu+lVb7r6U1bQtCdrKq0/vO3F5NTpNWol12DmdVmJNW88V8E+KZRZVgZX1TKQpsBKKMggQIECAAAECBKICCqwQ5+8f91p87Xk1ssTjXlUjVdvOrdrr3Z1KhtC7WbVjxnk0blmraVsSnHFw1bXndr+Gc/atOuTMvuOnrWdfmcEHsBzcbKIjFFhZz0SaAiuhKIMAAQIECBAgQCAqoMAKcK6Ax70C72rVjBjA6v6t9qnzzmv7P1XNnTu3Zs/u/o17K/vDP7xwUS14eFE98NDCeqD9b++/hfXAQ4/8eUHvz0v/bOY9t9Qhlx6wTAna79OMVP2Pn1ZtsPmEA5Uu/Ry7/55ld6suIxVYXZSGO0aBNVxvZyNAgAABAgQIEOggoMDqgDTRkBX0uNcU39WqefiAVgte+9U698o7JlVgLV68eDnF0cL6XWn0++KoVzAtWSItUTYtUTwtGPvz0mVTyxn73WjO78uqhYse2XR9kIvxyrUurI+tc+ogh/xu7Mv+seqZhyiwBpeb1BEKrEmxjXuQAivrmUhTYCUUZRAgQIAAAQIECEQFFFhT5Bzwca87nviC+skekygopvg2V4XDd7z4zbXx/As6v5VrH//8+vCMt9ZDi6o2eeKT6+HFI48URm3l0pIFVK9MeqSYevDhRZ3PsyoN/O9rnV3HrPPZwd/SvidW7fIWBdbgcpM6QoE1KTYFVpZthaYpsFYor3ACBAgQIECAAIHJCCiwJqP2+2PaJuR/t2PVUnteTZy3aPFI7fHAx+vW2ngKJ179Dt105I66aOb/qBkj3VcmTUcrK7BWj7mtwMpeJyuwsp6JNAVWQlEGAQIECBAgQIBAVECBNQXOK86o+urbBg74nw++pb60aM+Bj1udD5hsMbOmWc1aZ0atu/Zate7aM2rdJf48a53f/exJdXuddOvrasYApWhv83t7YA31n4cCK8utwMp6JtIUWAlFGQQIECBAgAABAlEBBdYUOC/9x6pzjho44NiHXlf/e+G+Ax+3Oh8w2Ufj0lZrzxj5fXm0Vs3qlUi/L5Pan1ux1CuVlvz5+GXT0uN+d/xYQTWas0TmzLVm1MjISP/LOOBjqeVbCPubhkcosLKgCqysZyJNgZVQlEGAAAECBAgQIBAVUGBNgXOSK7A+PPMddc7ae0/hxKvfoS9++F/rvQ+eMvAb/1+z3lzfX3fP2narLeoxs2c+snppiZJpdPXSUgXU71c5jf1unRnVCqS115ox8HsY+gEDbnZfh51T9eTn9H2bSpe+RJ0HsOxM1WmgAqsT01AHKbCGyu1kBAgQIECAAAECXQQUWF2UxhkziT2wuj7uNYV3tWoeOgmrxTVS5z/95Lp/5kY1d+7cmj179qr52VbEu7rqa1VfemPVwgfHT19rZtUrPlW13Us7vQOlSyemToNYdmLqPEiB1ZlqaAMVWEOjdiICBAgQIECAAIGuAgqsrlLjjFtBj3tN8V2tmocPaLVw633qG+v/We+zTLsCq33othLrwpOqrjl3mS8KGKma86KqP/6rTiuvRieD0iX3z4JlzrIlKbCynok0BVZCUQYBAgQIECBAgEBUQIE1Rc4V9LjXFN/Vqnn4gFYLXvvVOvfKO6ZvgTV6FdvqtZu+V7XgN1Wz1q/acveqDTYf+BorXQYmG/cAljlLBVbWMpWmwEpJyiFAgAABAgQIEIgJKLAClCvgca/Au1o1Iwawun+rfeq8885TYIWupNIlBFlVLHOWCqysZSpNgZWSlEOAAAECBAgQIBATUGCFKG+9vO4///ha94Zv1YyRxWOhbR+nkUk87hV6V6tmTMdH45QE2cvHM+fJMmepwMpaptIUWClJOQQIECBAgAABAjEBBVaMsubd9dt6zUc/XzuP/KIeN/LbumfxevXh/++tNWvjLXMnWZOS+jwapyTIXmyeOU+WOUsFVtYylabASknKIUCAAAECBAgQiAkosGKUvQJrj5O+s1TgLz64b82euVbuJNMoSUmQvdg8c54sc5YKrKxlKk2BlZKUQ4AAAQIECBAgEBNQYMUoFVg5yl6SkiALyjPnyTJnqcDKWqbSFFgpSTkECBAgQIAAAQIxAQVWjFKBlaNUYIUtFYJZUAVW1vPaa6+tOXPm9ELnzZtXm266afYE0gYWUGANTOYAAgQIECBAgACBFS2gwMoJe4QwZ6lwyVryzHoqsLKeCqysZyJNgZVQlEGAAAECBAgQIBAVUGDlOBVYOUuFS9aSZ9ZTgZX1VGBlPRNpCqyEogwCBAgQIECAAIGogAIrx6nAylkqXLKWPLOeCqyspwIr65lIU2AlFGUQIECAAAECBAhEBRRYOU4FVs5S4ZK15Jn1VGBlPRVYWc9EmgIroSiDAAECBAgQIEAgKqDAynEqsHKWCpesJc+spwIr66nAynom0hRYCUUZBAgQIECAAAECUQEFVo5TgZWzVLhkLXlmPRVYWU8FVtYzkabASijKIECAAAECBAgQiAoosHKcCqycpcIla8kz66nAynoqsLKeiTQFVkJRBgECBAgQIECAQFRAgZXjVGDlLBUuWUueWU8FVtZTgZX1TKQpsBKKMggQIECAAAECBKICCqwcpwIrZ6lwyVryzHoqsLKeCqysZyJNgZVQlEGAAAECBAgQIBAVUGDlOBVYOUuFS9aSZ9ZTgZX1VGBlPRNpCqyEogwCBAgQIECAAIGogAIrx6nAylkqXLKWPLOeCqyspwIr65lIU2AlFGUQIECAAAECBAhEBRRYOU4FVs5S4ZK15Jn1VGBlPRVYWc9EmgIroSiDAAECBAgQIEAgKqDAynEqsHKWCpesJc+spwIr66nAynom0hRYCUUZBAgQIECAAAECUQEFVo5TgZWzVLhkLXlmPRVYWU8FVtYzkabASijKIECAAAECBAgQiAoosHKcCqycpcIla8kz66nAynoqsLKeiTQFVkJRBgECBAgQIECAQFRAgZXjVGDlLBUuWUueWU8FVtZTgZX1TKQpsBKKMggQIECAAAECBKICCqwcpwIrZ6lwyVryzHoqsLKeCqysZyJNgZVQlEGAAAECBAgQIBAVUGDlOBVYOUuFS9aSZ9ZTgZX1VGBlPRNpCqyEogwCBAgQIECAAIGogAIrx6nAylkqXLKWPLOeCqyspwIr65lIU2AlFGUQIECAAAECBAhEBRRYOU4FVs5S4ZK15Jn1VGBlPRVYWc9EmgIroSiDAAECBAgQIEAgKqDAynEqsHKWCpesJc+spwIr66nAynom0hRYCUUZBAgQIECAAAECUQEFVo5TgZWzVLhkLXlmPRVYWU8FVtYzkabASijKIECAAAECBAgQiAoosHKcCqycpcIla8kz66nAynoqsLKeiTQFVkJRBgECBAgQIECAQFRAgZXjVGDlLBUuWUueWU8FVtZTgZX1TKQpsBKKMggQIECAAAECBKICCqwcZyuwXvPRz9cuM66qx9Vv655arz50xFtr1hO2yp1kGiUpCbIXm2fOk2XOsiUpsLKeiTQFVkJRBgECBAgQIEBgGgnce++9dfTRR9fnP//5uuuuu+ppT3taHXXUUfXqV786pqDAClHeenndf/5Hat0bvl0zRhaPhS6ukRrZdm7VXu+uevJzQiebHjFKgux15pnzZJmzVGBlLVNpCqyUpBwCBAgQIECAwDQRmDt3bv3whz+sE044oebMmVP/7//9vzrttNPqjDPOqEMOOSSioMAKMF71taovvbFq4YPjh601s+oVn6ra7qWBE06PCCVB9jrzzHmyzFkqsLKWqTQFVkpSDgECBAgQIEBgGgicddZZ9ZKXvKRXWr3mNa8Z+8St1Pr5z39eN998c6211lpTllBgTZHw1surPr3vxOXV6ClaiXXYOVZidSRXEnSE6jiMZ0eoDsNYdkAaYIhHCAfAGtJQBdaQoJ2GAAECBAgQILAmCLzpTW+qf/mXf6lf/epXtfbaa499pM997nO91Vff+973arfddpvyR12ywLr00kvrKU95ypQzp1PA+t94U61703c6f+QHtnxB/eYln+w8fjoPbCXBBRdc0CPYa6+9avbs2dOZY8qfneeUCccCWOYsW9L1119fu+yySy903rx5temmm2ZPIG1gAQXWwGQOIECAAAECBAhMX4Fdd921Fi5cWJdddtlSCG311fbbb1+nnnpqvfnNb+4L1AqqiV7z58+vnXbaqW+OAY8W2OLxI3X9EY+tGSMjnXkWLV5cW/3dvXXz3Y/sk9X5YAMJECCwhgsosFaNC6zAWjWug3dBgAABAgQIEFgtBNqeV2011DnnnLPU+22F05Oe9KT6yEc+Uu95z3v6fpaRAcqVvmEGLCXw+h3Xqf/9ssFXBb3+K/fX//3JQzQJECBAYBkBBdaqMSUUWKvGdfAuCBAgQIAAAQKrhUArsLbeeus6++yzl1tgHX/88b1vJOz3UmD1E5r879+588z6u31nDRzwzrMX1CmXTbDh+8CJDiBAgMCaIaDAWjWuowJr1bgO3gUBAgQIECBAYLUQ8Ajhqn+ZrMBa9a+Rd0iAwOoloMBaNa6XAmvVuA7eBQECBAgQIEBgtRBo+1u1DduX3cS9bezevpXQJu4r/zLO+M0tteFnX1Aj1X0/q8U1Unf92QW1aP0nr/wPsIq/AxtlZy8Qz5wny5xlS7KJe9YzkabASijKIECAAAECBAhME4H26OB+++3X+ybCV73qVWOf+sUvfnH99Kc/rZtvvrnWWmutKWss+S2E11xzTW277bZTzpxWAWccXHXtud0/8px9qw45s/v4aTyylQTnnXdeT2Du3Lm+hXCKc4HnFAGXOJxlzrIlXXvttdUem28vK7CytpNNU2BNVs5xBAgQIECAAIFpKtBu2n/0ox/ViSeeWNtss01vRdYnP/nJOv300+u1r31tREWBNUXGWy+v+vS+VQs77Gm11syqw86pevJzpnjS6XG4kiB7nXnmPFnmLBVYWctUmgIrJSmHAAECBAgQIDBNBO69997667/+6/r85z9fd911Vz3taU/rffPgq1/96piAAitAedXXqr70xolLrFZeveJTVdu9NHDC6RGhJMheZ545T5Y5SwVW1jKVpsBKScohQIAAAQIECBCICSiwQpRtJdaFJ9Xia85dZk+skao5L6r647+y8mpAaiXBgGB9hvPMebLMWSqwspapNAVWSlIOAQIECBAgQIBATECBFaPsBS247eq66qxP1joL76+n7vi8mjln76oNNs+eZJqkKQmyF5pnzpNlzlKBlbVMpSmwUpJyCBAgQIAAAQIEYgIKrBhlL8iNbc6TZc7S3GSZFcim2cQ965lIU2AlFGUQIECAAAECBAhEBRRYUU4FVpBTgRXEVK5GMc3NKKdvIcxyRtIUWBFGIQQIECBAgAABAkkBBVZS0wqspKaSIKlpbiY1zc2kZimwspyRNAVWhFEIAQIECBAgQIBAUkCBldRUEiQ1lQRJTXMzqWluJjUVWFnNTJoCK+MohQABAgQIECBAICigwApiekwriqkkiHJ6vDXIaW4GMUuBldXMpCmwMo5SCBAgQIAAAQIEggIKrCCmAiuKqSSIciqwgpzmZhBTgZXFDKUpsEKQYggQIECAAAECBHICCqycZUtyY5vzZJmzNDdZZgWyab6FMOuZSFNgJRRlECBAgAABAgQIRAUUWFFOBVaQU4EVxFSuRjHNzSinTdyznJE0BVaEUQgBAgQIECBAgEBSQIGV1LQCK6mpJEhqmptJTXMzqWkPrKxmJk2BlXGUQoAAAQIECBAgEBRQYAUxrXKJYioJopxWBwY5zc0gpj2wspihNAVWCFIMAQIECBAgQIBATkCBlbNsSW5sc54sc5bmJsusQDbNHlhZz0SaAiuhKIMAAQIECBAgQCAqoMCKciqwgpwKrCCmcjWKaW5GOe2BleWMpCmwIoxCCBAgQIAAAQIEkgIKrKSmFVhJTSVBUtPcTGqam0lNe2BlNTNpCqyMoxQCBAgQIECAAIGggAIriGmVSxRTSRDltDowyGluBjHtgZXFDKUpsEKQYggQIECAAAECBHICCqycZUtyY5vzZJmzNDdZZgWyafbAynom0hRYCUUZBAgQIECAAAECUQEFVpRTgRXkVGAFMZWrUUxzM8ppD6wsZyRNgRVhFEKAAAECBAgQIJAUUGAlNa3ASmoqCZKa5mZS09xMatoDK6uZSVNgZRylECBAgAABAgQIBAUUWEFMq1yimEqCKKfVgUFOczOIaQ+sLGYoTYEVghRDgAABAgQIECCQE1Bg5SxbkhvbnCfLnKW5yTIrkE2zB1bWM5GmwEooyiBAgAABAgQIEIgKKLCinAqsIKcCK4ipXI1imptRTntgZTkjaQqsCKMQAgQIECBAgACBpIACK6lpBVZSU0mQ1DQ3k5rmZlLTHlhZzUyaAivjKIUAAQIECBAgQCAooMAKYlrlEsVUEkQ5rQ4McpqbQUx7YGUxQ2kKrBCkGAIECBAgQIAAgZyAAitn2ZLc2OY8WeYszU2WWYFsmj2wsp6JNAVWQlEGAQIECBAgQIBAVECBFeVUYAU5FVhBTOVqFNPcjHLaAyvLGUlTYEUYhRAgQIAAAQIECCQFFFhJTSuwkppKgqSmuZnUNDeTmvbAympm0hRYGUcpBAgQIECAAAECQQEFVhDTKpcoppIgyml1YJDT3Axi2gMrixlKU2CFIMUQIECAAAECBAjkBBRYOcuW5MY258kyZ2lusswKZNPsgZX1TKQpsBKKMggQIECAAAECBKICCqwopwIryKnACmIqV6OY5maU0x5YWc5ImgIrwiiEAAECBAgQIEAgKaDASmpagZXUVBIkNc3NpKa5mdS0B1ZWM5OmwMo4SiFAgAABAgQIEAgKKLCCmFa5RDGVBFFOqwODnOZmENMeWFnMUJoCKwQphgABAgQIECBAICegwMpZtiQ3tjlPljlLc5NlViCbZg+srGciTYGVUJRBgAABAgQIECAQFVBgRTkVWEFOBVYQU7kaxTQ3o5z2wMpyRtIUWBFGIQQIECBAgAABAkkBBVZS0wqspKaSIKlpbiY1zc2kpj2wspqZNAVWxlEKAQIECBAgQIBAUECBFcS0yiWKqSSIclodGOQ0N4OY9sDKYobSFFghSDEECBAgQIAAAQI5AQVWzrIlubHNebLMWZqbLLMC2TR7YGU9E2kKrISiDAIECBAgQIAAgaiAAivKqcAKciqwgpjK1SimuRnltAdWljOSpsCKMAohQIAAAQIECBBICiiwkppWYCU1lQRJTXMzqWluJjXtgZXVzKQpsDKOUggQIECAAAECBIICCqwgplUuUUwlQZTT6sAgp7kZxLQHVhYzlKbACkGKIUCAAAECBAgQyAkosHKWLcmNbc6TZc7S3GSZFcim2QMr65lIU2AlFGUQIECAAAECBAhEBRRYUU4FVpBTgRXEVK5GMc3NKKc9sLKckTQFVoRRCAECBAgQIECAQFJAgZXUtAIrqakkSGqam0lNczOpaQ+srGYmTYGVcZRCgAABAgQIECAQFFBgBTGtcoliKgminFYHBjnNzSCmPbCymKE0BVYIUgwBAgQIECBAgEBOQIGVs2xJbmxznixzluYmy6xANs0eWFnPRJoCK6EogwABAgQIECBAICqgwIpyKrCCnAqsIKZyNYppbkY57YGV5YykKbAijEIIECBAgAABAgSSAgqspKYVWElNJUFS09xMapqbSU17YGU1M2kKrIyjFAIECBAgQIAAgaCAAiuIaZVLFFNJEOW0OjDIaW4GMe2BlcUMpSmwQpBiCBAgQIAAAQIEcgIKrJxlS3Jjm/NkmbM0N1lmBbJp9sDKeibSFFgJRRkECBAgQIAAAQJRAQVWlFOBFeRUYAUxlatRTHMzymkPrCxnJE2BFWEUQoAAAQIECBAgkBRQYCU1rcBKaioJkprmZlLT3Exq2gMrq5lJU2BlHKUQIECAAAECBAgEBRRYQUyrXKKYSoIop9WBQU5zM4hpD6wsZihNgRWCFEOAAAECBAgQIJATUGDlLFuSG9ucJ8ucpbnJMiuQTbMHVtYzkabASijKIECAAAECBAgQiAoosKKcCqwgpwIriKlcjWKam1FOe2BlOSNpCqwIoxACBAgQIECAAIGkgAIrqWkFVlJTSZDUNDeTmuZmUtMeWFnNTJoCK+MohQABAgQIECBAICigwApiWuUSxVQSRDmtDgxymptBTHtgZTFDaQqsEKQYAgQIECBAgACBnIACK2fZktzY5jxZ5izNTZZZgWyaPbCynok0BVZCUQYBAgQIECBAgEBUQIEV5VRgBTkVWEFM5WoU09yMctoDK8sZSVNgRRiFECBAgAABAgQIJAUUWElNK7CSmkqCpKa5mdQ0N5Oa9sDKambSFFgZRykECBAgQIAAAQJBAQVWENMqlyimkiDKaXVgkNPcDGLaAyuLGUpTYIUgxRAgQIAAAQIECOQEFFg5y5bkxjbnyTJnaW6yzApk0+yBlfVMpCmwEooyCBAgQIAAAQIEogIKrCinAivIqcAKYipXo5jmZpTTHlhZzkiaAivCKIQAAQIECBAgQCApoMBKalqBldRUEiQ1zc2kprmZ1LQHVlYzk6bAyjhKIUCAAAECBAgQCAoosIKYVrlEMZUEUU6rA4Oc5mYQ0x5YWcxQmgIrBCmGAAECBAgQIEAgJ6DAylm2JDe2OU+WOUtzk2VWIJtmD6ysZyJNgZVQlEGAAAECBAgQIBAVUGBFORVYQU4FVhBTuRrFNDejnPbAynJG0hRYEUYhBAgQIECAAAECSQEFVlLTCqykppIgqWluJjXNzaSmPbCympk0BVbGUQoBAgQIECBAgEBQQIEVxLTKJYqpJIhyWh0Y5DQ3g5j2wMpihtIUWCFIMQQIECBAgAABAjkBBVbOsiW5sc15ssxZmpssswLZNHtgZT0TaQqshKIMAgQIECBAgACBqIACK8qpwApyKrCCmMrVKKa5GeW0B1aWM5KmwIowCiFAgAABAgQIEEgKKLCSmlZgJTWVBElNczOpaW4mNe2BldXMpCmwMo5SCBAgQIAAAQJrvMA999xTxx13XP34xz+uK664ou6888465phj6thjj41/dgVWltSNbc6TZc6yJfHMebLMWbYkjxBmPRNpCqyEogwCBAgQIECAwDQQuPHGG+uZrPmsowAAFjpJREFUz3xm7bjjjjVnzpw67bTTFFiryXV3Y5u7UCxzlgosllmBbJoCK+uZSFNgJRRlECBAgAABAgSmgcDixYt7n3JkZKS3+mrjjTdWYK0m113pkrtQLHOWCiyWWYFsmgIr65lIU2AlFGUQIECAAAECBKaZgAJr9brgSpfc9WKZs1RgscwKZNMUWFnPRJoCK6EogwABAgQIECAwzQSmWmC1Pa4mes2bN69222233pDzzz+/tthii2kmnP24DzzwQP3gBz/ohe6888617rrrZk8wjdJYZi82z5wny5xlS7rppptqn3326YXecMMNteWWW2ZPIG1gAQXWwGQOIECAAAECBAgQmGqB1R5D9CJAgAABAquDwGWXXVbPe97zVoe3uka/RwXWGn15fTgCBAgQIECAwPIFLrjggnrBC17Qiad942DbvH3JlwKrE51BBAgQILAGCHz961+v/ffffw34JKv3R1Bgrd7Xz7snQIAAAQIECExKYP78+fXNb36z07Evf/nLa8MNN4wWWP0eIWyPa+y55569c37/+9+vzTbbrNN7NWj5Au1677TTTr1ftpUET3ziE1FNUoDlJOHGOYxnzpNlzrIlLfkoe9sPa5tttsmeQNrAAgqsgckcQIAAAQIECBAgMNUVWP0EW8E1Wlq1m4hNN9203yF+P4EAz9z0YJmzbEk8c54sc5bmZtYylabASknKIUCAAAECBAhMIwEF1up1sd3Y5q4Xy5ylkoBlViCb5t961jORpsBKKMogQIAAAQIECEwTgbPPPrvuu+++uueee+qwww6rgw46qA4++ODep99vv/1qvfXWi0i4cYgwjoXwzHmyzFkqsFhmBbJp/q1nPRNpCqyEogwCBAgQIECAwDQRaF8j3r5afHmv5NeMu3HITiieOU+WOUsFFsusQDbt/2/vzkO1qN44gD9lSYuISBkZ0ialZqhkpaGQ/iGmbWTWtUUsNM0EIRJKyyUzLZKMksgW/8glzVYrk8RKNFokM0kJIq2srEwNM4Sy+2MGkszrz9fredW58xkQxWae95zPM/fK/XbmjK/1tJ4pqgmwUiiqQYAAAQIECBAgkFTADw5JOe0zlJDTvZkQ0x5YSTHdm0k5fd9My5mkmgArCaMiBAgQIECAAAECKQX8IJZS00bZKTXdmyk13ZspNd2bKTXdm2k101QTYKVxVIUAAQIECBAgQCChgB/EEmJa5ZIU072ZlNMql4Sc7s2EmL5vpsVMVE2AlQhSGQIECBAgQIAAgXQCfhBLZ5lV4pnOk2U6S/cmy7QCaav5Wk/rmaKaACuFohoECBAgQIAAAQIECBAgQIAAAQJVExBgVY1WYQIECBAgQIAAAQIECBAgQIAAgRQCAqwUimoQIECAAAECBAgQIECAAAECBAhUTUCAVTVahQkQIECAAAECBAgQIECAAAECBFIICLBSKKpBgAABAgQIECBAgAABAgQIECBQNQEBVtVoFSZAgAABAgQIECBAgAABAgQIEEghIMBKoagGAQIECBAgQIAAAQIECBAgQIBA1QQEWFWjVZgAAQIECBAgQIAAAQIECBAgQCCFgAArhaIaBAgQIECAAAECBAgQIECAAAECVRMQYFWNVmECBAgQIECAAIGUAtu3b4+JEyfGZ599FqtWrYrNmzfHuHHjYvz48Sk/psHV+v333+Pee++N+fPnx5YtW6JNmzZx9913R01NTYOba7Un5B5MJ7x06dKYNWtWfPDBB/Hdd99Fs2bNonPnzjF27Ni44IIL0n1QCSpl3xPHjBkTa9asiV9++SWOP/74OPfcc+OOO+6Im266qQQC1Z3iM888E0OGDIkTTzwxsu+njsMnIMA6fPY+mQABAgQIECBA4AAENmzYEB07dowOHTrEOeecE9kPFQKs/QP26tUrPvnkk5gyZUruNmfOnNxu9uzZccMNN+y/gDN2C7gH090M/fv3j19//TWy39u1a5cHL1OnTo2VK1fG4sWLo2fPnuk+rIFXeu+99+KFF16Ibt26xWmnnRY7duzIv76zv8tC/yzAdtRP4Pvvv4/zzjsvD69+++03AVb9GJNdJcBKRqkQAQIECBAgQIBANQVqa2vz8kcddVS++urkk08WYO0H/K233oq+ffvmodWAAQN2n52FWl988UV8++230ahRo2q2rUHVdg+ma+fPP/8cLVq02KNgtrqldevW0b59+1iyZEm6DytppS5dusQPP/yQf5076idwxRVX5P/mNG/ePBYsWCDAqh9jsqsEWMkoFSJAgAABAgQIEDhUAgKsyqSzx16yVRhbt26NY445ZvdFc+fOzVdfrVixIi655JLKijlrDwH3YHVuiGzlVbbq5csvv6zOB5So6uWXXx5r166Nr7/+ukSzTjfV7BHX4cOH54bZKjYBVjrb+lYSYNVXznUECBAgQIAAAQKHTUB4UBl9165dY9euXfHxxx/vcUG2+ipb5fLUU0/FbbfdVlkxZwmwqnwPZI9onX766fnjgy+//HKVP63hlf/7778j+5UF1i+++GKMHDkynnjiiRg6dGjDm2yVZ5StEMwebb3//vvzEGvQoEECrCqbV1JegFWJknMIECBAgAABAgSOKAEBVmXtyPa8Ouuss+Ltt9/e44Iff/wxWrZsGQ8++GDcc889lRVzlgCryvdAtuH4vHnz4sMPP7SRez2shw0blofS2dG4ceOYNm1a3H777fWo5JJrr702su+Ty5cvzx8hFGAdGfeEAOvI6INRECBAgAABAgRKJZBtOtyjR4+K5py9cTDbvP3fhwCrIrp80/azzz47Fi1aVGeANXny5PyNhI4DF3APHrjZ/7vivvvuiwceeCAef/zxGDFiRNriJamW7XWVrRzKfi1cuDBmzJgRDz30UNx1110lEUgzzZdeeil/xDr7tydbhZUdAqw0tgdbRYB1sIKuJ0CAAAECBAgQOGCB7P9sv/nmmxVdd8011+Qb6AqwKuLa4ySPEB64WaVXCLAqldr/eRMmTIjx48fHpEmTYvTo0fu/wBkVCWSrr7I3jmYbuWcvvXDsX+CfFwlkqwH//fbG7DHC119/PTZu3BjHHnts/lZCx6EXEGAdenOfSIAAAQIECBAgcJACwoPKALP9rbIN2/+7iXu2sXv2VkKbuFfmWNdZ7sH62/37yn/CqyzAGjduXJqiquQCM2fOjFtvvTV/JPPiiy+mUoHAhg0b4swzz/y/Z1511VXx6quvVlDNKakFBFipRdUjQIAAAQIECBCouoDwoDLi7NHBPn365G8ivP7663dfdNlll8Xnn38e2SNHjRo1qqyYs/YQcA8e/A0xceLEGDt2bL7SJfuzI63AwIEDY/bs2bFp0yYrsCqk3blzZx74/feYMmVKvP/++/nj2CeddFL+EgzHoRcQYB16c59IgAABAgQIECBQT4Hsh4cdO3bE9u3b85UF/fv3j+uuuy6vlgU1J5xwQj0rN9zLevXqFStXrsz3wmndunW+Iuvpp5+O7BXxN954Y8OdeJVm5h5MAzt16tR8b6bevXvXufKqS5cuaT6oBFWylZZNmzaNiy66KE455ZTIwtXsLYTZhvijRo2Khx9+uAQK1Z2iPbCq61tpdQFWpVLOI0CAAAECBAgQOOwCZ5xxRnzzzTd1jmP9+vWR/XfHngLZni5jxoyJ+fPnx5YtW6JNmzb5mwdrampQ1UPAPVgPtDouufTSS/MVLfs6amtr03xQCapkjwpmv9atWxfbtm2LJk2aRIcOHWLw4MGR7eXkOHgBAdbBG6aoIMBKoagGAQIECBAgQIAAAQIECBAgQIBA1QQEWFWjVZgAAQIECBAgQIAAAQIECBAgQCCFgAArhaIaBAgQIECAAAECBAgQIECAAAECVRMQYFWNVmECBAgQIECAAAECBAgQIECAAIEUAgKsFIpqECBAgAABAgQIECBAgAABAgQIVE1AgFU1WoUJECBAgAABAgQIECBAgAABAgRSCAiwUiiqQYAAAQIECBAgQIAAAQIECBAgUDUBAVbVaBUmQIAAAQIECBAgQIAAAQIECBBIISDASqGoBgECBAgQIECAAAECBAgQIECAQNUEBFhVo1WYAAECBAgQIECAAAECBAgQIEAghYAAK4WiGgQIECBAgAABAgQIECBAgAABAlUTEGBVjVZhAgQIECBAgAABAgQIECBAgACBFAICrBSKahAgQIAAAQIECBAgQIAAAQIECFRNQIBVNVqFCRAgQIAAAQIECBAgQIAAAQIEUggIsFIoqkGAAAECBAgQIECAAAECBAgQIFA1AQFW1WgVJkCAAAECBAgQIECAAAECBAgQSCEgwEqhqAYBAgQIECBAgAABAgQOo8DixYujd+/e0aRJk1i7dm20atWqztFMmDAhxo8fH23atInVq1dH48aND+OofTQBAgQqFxBgVW7lTAIECBAgQIAAAQIECByxAjfffHPMmjUr+vbtG2+88cZe41y3bl107Ngx/vzzz1i2bFl069btiJ2LgREgQOC/AgIs9wQBAgQIECBAgAABAgQagMDmzZujbdu2kf0+d+7cqKmp2T2r2tra6N69e6xYsSKGDRsWTz75ZAOYsSkQIFAmAQFWmbptrgQIECBAgAABAgQINGiB559/PgYOHBgtWrSIbMVV8+bN8/lOnz49RowYES1btsz/vmnTpg3aweQIEGh4AgKshtdTMyJAgAABAgQIECBAoMQCvXr1infeeScGDRoUM2fOjI0bN0a7du1i+/bt8corr8TVV19dYh1TJ0CgqAICrKJ2zrgJECBAgAABAgQIECBQh8D69eujffv28ccff8SSJUvisccei4ULF0a/fv1iwYIFzAgQIFBIAQFWIdtm0AQIECBAgAABAgQIENi3wCOPPBKjRo2KZs2axbZt2/Lfs7cTnnrqqdgIECBQSAEBViHbZtAECBAgQIAAAQIECBDYt8CuXbviwgsvjFWrVuUnzZgxI4YMGYKMAAEChRUQYBW2dQZOgAABAgQIECBAgACBugV27NiRP0a4YcOG/IRPP/00OnXqhIsAAQKFFRBgFbZ1Bk6AAAECBAgQIECAAIG6Be6888549NFH47jjjoudO3dG586d46OPPoqjjz4aGQECBAopIMAqZNsMmgABAgQIECBAgAABAnULrFy5Mrp06ZKHVcuWLYsBAwbkK7GmTZsWI0eOxEaAAIFCCgiwCtk2gyZAgAABAgQIECBAgMDeAn/99Ve+2mr16tUxevTomDRpUixatCj69OkTTZo0yTdyb9WqFToCBAgUTkCAVbiWGTABAgQIECBAgAABAgTqFpg8eXIeXLVu3TrWrFmTP0KYHTU1NTFv3ry48sor47XXXsNHgACBwgkIsArXMgMmQIAAAQIECBAgQIDA3gJfffVVnH/++fmeV0uXLo0ePXrsPmnTpk3Rtm3b2LZtWyxYsCD69euHkAABAoUSEGAVql0GS4AAAQIECBAgQIAAgboFevbsGe+++27ccsst8dxzz+110owZM2Lo0KHRsmXLWLduXTRt2hQlAQIECiMgwCpMqwyUAAECBAgQIECAAAECdQs8++yzMXjw4GjRokUeTjVv3nyvE2tra6N79+6xYsWKGD58eEyfPh0nAQIECiMgwCpMqwyUAAECBAgQIECAAAECewv89NNP+eOBW7dujTlz5uRvHdzXkW3i3qlTp8g2e1++fHl07doVKQECBAohIMAqRJsMkgABAgQIECBAgAABAgQIECBQXgEBVnl7b+YECBAgQIAAAQIECBAgQIAAgUIICLAK0SaDJECAAAECBAgQIECAAAECBAiUV0CAVd7emzkBAgQIECBAgAABAgQIECBAoBACAqxCtMkgCRAgQIAAAQIECBAgQIAAAQLlFRBglbf3Zk6AAAECBAgQIECAAAECBAgQKISAAKsQbTJIAgQIECBAgAABAgQIECBAgEB5BQRY5e29mRMgQIAAAQIECBAgQIAAAQIECiEgwCpEmwySAAECBAgQIECAAAECBAgQIFBeAQFWeXtv5gQIECBAgAABAgQIECBAgACBQggIsArRJoMkQIAAAQIECBAgQIAAAQIECJRXQIBV3t6bOQECBAgQIECAAAECBAgQIECgEAICrEK0ySAJECBAgAABAgQIECBAgAABAuUVEGCVt/dmToAAAQIECBAgQIAAAQIECBAohIAAqxBtMkgCBAgQIECAAAECBAgQIECAQHkFBFjl7b2ZEyBAgAABAgQIECBAgAABAgQKISDAKkSbDJIAAQIECBAgQIAAAQIECBAgUF4BAVZ5e2/mBAgQIECAAAECBAgQIECAAIFCCAiwCtEmgyRAgAABAgQIECBAgAABAgQIlFdAgFXe3ps5AQIECBAgQIAAAQIECBAgQKAQAgKsQrTJIAkQIECAAAECBAgQIECAAAEC5RUQYJW392ZOgAABAgQIECBAgAABAgQIECiEgACrEG0ySAIECBAgQIAAAQIECBAgQIBAeQUEWOXtvZkTIECAAAECBAgQIECAAAECBAohIMAqRJsMkgABAgQIECBAgAABAgQIECBQXgEBVnl7b+YECBAgQIAAAQIECBAgQIAAgUIICLAK0SaDJECAAAECBAgQIECAAAECBAiUV0CAVd7emzkBAgQIECBAgAABAgQIECBAoBACAqxCtMkgCRAgQIAAAQIECBAgQIAAAQLlFRBglbf3Zk6AAAECBAgQIECAAAECBAgQKISAAKsQbTJIAgQIECBAgAABAgQIECBAgEB5BQRY5e29mRMgQIAAAQIECBAgQIAAAQIECiEgwCpEmwySAAECBAgQIECAAAECBAgQIFBeAQFWeXtv5gQIECBAgAABAgQIECBAgACBQggIsArRJoMkQIAAAQIECBAgQIAAAQIECJRXQIBV3t6bOQECBAgQIECAAAECBAgQIECgEAICrEK0ySAJECBAgAABAgQIECBAgAABAuUVEGCVt/dmToAAAQIECBAgQIAAAQIECBAohIAAqxBtMkgCBAgQIECAAAECBAgQIECAQHkFBFjl7b2ZEyBAgAABAgQIECBAgAABAgQKISDAKkSbDJIAAQIECBAgQIAAAQIECBAgUF4BAVZ5e2/mBAgQIECAAAECBAgQIECAAIFCCAiwCtEmgyRAgAABAgQIECBAgAABAgQIlFdAgFXe3ps5AQIECBAgQIAAAQIECBAgQKAQAgKsQrTJIAkQIECAAAECBAgQIECAAAEC5RUQYJW392ZOgAABAgQIECBAgAABAgQIECiEgACrEG0ySAIECBAgQIAAAQIECBAgQIBAeQUEWOXtvZkTIECAAAECBAgQIECAAAECBAohIMAqRJsMkgABAgQIECBAgAABAgQIECBQXgEBVnl7b+YECBAgQIAAAQIECBAgQIAAgUIICLAK0SaDJECAAAECBAgQIECAAAECBAiUV0CAVd7emzkBAgQIECBAgAABAgQIECBAoBACAqxCtMkgCRAgQIAAAQIECBAgQIAAAQLlFRBglbf3Zk6AAAECBAgQIECAAAECBAgQKISAAKsQbTJIAgQIECBAgAABAgQIECBAgEB5BQRY5e29mRMgQIAAAQIECBAgQIAAAQIECiHwP1hOW69M03PzAAAAAElFTkSuQmCC\" width=\"600\">"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## IK interactive 3D plot:  "
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-05-22T07:11:30.131206Z",
          "end_time": "2021-05-22T07:11:30.145892Z"
        },
        "code_folding": [],
        "trusted": true
      },
      "cell_type": "code",
      "source": "N = 4 # the number of links (N > 2)\nTH = np.array([0, pi/2] + [0] * (N-2))\nMinA = [-pi,  0] + [-pi/2] * (N-2)\nMaxA = [ pi, pi] + [ pi/2] * (N-2)\nBaseVec  = [0, 0, 0]\nStandVec = [0, 0, 0.5]\nLinkVec  = [1, 0, 0]\nL = [BaseVec, StandVec] + [LinkVec] * (N-1)\nTarget = TargetVec([2.0, 1.0, 2.0], L)\nV = FK(L, TH)\nmx, my, mz = Target\nscaler = 0.1\n\ndef click(event):\n    global TH, mx, my, mz\n    if event.inaxes == A10.axes:\n        mx = event.xdata\n        my = event.ydata\n    elif event.inaxes == A20.axes:\n        mx = event.xdata\n        mz = event.ydata\n    else:\n        pass\n    Target = TargetVec([mx, my, mz], L)\n    loop = 0\n    while True:\n        V = FK(L, TH)\n        J = Jacobian(V)\n        EE = V[:, -1]\n        Error = Target - EE\n        dTheta = pinv(J) @ Error * scaler\n        TH += dTheta\n        TH = angleLimit(TH, MinA, MaxA) \n        # TH = conv(TH)\n        if norm(Error) < 1e-4:\n            break\n        loop += 1\n        if loop > 1000:\n            break\n    \n    A00.set_data(V[0], V[1])\n    A00.set_3d_properties(V[2])\n    A01.set_data(V[0], V[1])\n    A01.set_3d_properties(V[2])\n    A0X.set_data(mx, my)\n    A0X.set_3d_properties(mz)\n    \n    A10.set_data(V[0], V[1])\n    A11.set_data(V[0], V[1])\n    A1X.set_data(mx, my)\n    \n    A20.set_data(V[0], V[2])\n    A21.set_data(V[0], V[2])\n    A2X.set_data(mx, mz)\n    event.canvas.draw()",
      "execution_count": 88,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-05-22T07:11:30.787490Z",
          "end_time": "2021-05-22T07:11:31.144927Z"
        },
        "code_folding": [
          0
        ],
        "trusted": true
      },
      "cell_type": "code",
      "source": "# Interactive 3D Plot: click Top view or Front view to change the target vector \nfig = plt.figure(figsize=(6,6))\nax = fig.add_subplot(221, projection='3d', proj_type='persp')\nfig.subplots_adjust(bottom=0.1, left=0, top=0.95, right=0.9, wspace=0.3, hspace=0.3)\nax.set_box_aspect([1,1,1])\nax.set_xlim([-1, N])\nax.set_ylim([-1, N])\nax.set_zlim([0, N])\nax.set_xticks([*range(-1, N)])\nax.set_yticks([*range(-1, N)])\nax.set_zticks([*range(N+1)])\nax.tick_params(axis='x', labelsize=6)\nax.tick_params(axis='y', labelsize=6)\nax.tick_params(axis='z', labelsize=6)\nax.set_xlabel('X', fontsize=8, rotation='horizontal')\nax.set_ylabel('Y', fontsize=8, rotation='horizontal')\nax.set_zlabel('Z', fontsize=8, rotation='horizontal')\n\nax1 = fig.add_subplot(222)\nax1.set_title('Top view(X-Y)', fontsize=10)\nax1.set_xlabel('X', fontsize=8, rotation='horizontal')\nax1.set_ylabel('Y', fontsize=8, rotation='horizontal')\nax1.set_xticks([*range(-1, N)])\nax1.set_yticks([*range(-1, N)])\nax1.tick_params(axis='x', labelsize=6)\nax1.tick_params(axis='y', labelsize=6)\nax1.set_aspect('equal')\nax1.axis([-1,N,-1,N])\nax1.grid()\n\nax2 = fig.add_subplot(224)\nax2.set_title('Front view(X-Z)', fontsize=10)\nax2.set_xlabel('X', fontsize=8, rotation='horizontal')\nax2.set_ylabel('Z', fontsize=8, rotation='horizontal')\nax2.set_xticks([*range(-1, N)])\nax2.set_yticks([*range(-1, N)])\nax2.tick_params(axis='x', labelsize=6)\nax2.tick_params(axis='y', labelsize=6)\nax2.set_aspect('equal')\nax2.axis([-1,N,-1,N])\nax2.grid()\n\nA00, = ax.plot(V[0],V[1],V[2]) # 3D view\nA01, = ax.plot(V[0],V[1],V[2], 'o', ms=4)\nA0X, = ax.plot(mx,my,mz, 'rx', ms=10)\n\nA10, = ax1.plot(V[0],V[1])   # Top view\nA11, = ax1.plot(V[0],V[1], 'o', ms=4)\nA1X, = ax1.plot(mx,my, 'rx', ms=10)\n\nax2.plot([-1, N], [0, 0], 'k-') # Front view\nA20, = ax2.plot(V[0],V[2])   \nA21, = ax2.plot(V[0],V[2], 'o', ms=4)\nA2X, = ax2.plot(mx,mz, 'rx', ms=10)\n\n\nfig.canvas.mpl_connect('button_press_event', click)\nplt.show()",
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<IPython.core.display.Javascript object>",
            "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.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(\n            '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\nmpl.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 = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(this.root);\n\n    this._init_header(this);\n    this._init_canvas(this);\n    this._init_toolbar(this);\n\n    var fig = this;\n\n    this.waiting = false;\n\n    this.ws.onopen = function () {\n        fig.send_message('supports_binary', { value: fig.supports_binary });\n        fig.send_message('send_image_mode', {});\n        if (mpl.ratio !== 1) {\n            fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n        }\n        fig.send_message('refresh', {});\n    };\n\n    this.imageObj.onload = function () {\n        if (fig.image_mode === 'full') {\n            // Full images could contain transparency (where diff images\n            // almost always do), so we need to clear the canvas so that\n            // there is no ghosting.\n            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n        }\n        fig.context.drawImage(fig.imageObj, 0, 0);\n    };\n\n    this.imageObj.onunload = function () {\n        fig.ws.close();\n    };\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute('style', 'box-sizing: content-box;');\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n    );\n\n    var resizeObserver = new ResizeObserver(function (entries) {\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * mpl.ratio);\n                canvas.setAttribute('height', height * mpl.ratio);\n            }\n            canvas.setAttribute(\n                'style',\n                'width: ' + width + 'px; height: ' + height + 'px;'\n            );\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    resizeObserver.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        return function (event) {\n            return fig.mouse_event(event, name);\n        };\n    }\n\n    rubberband_canvas.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    rubberband_canvas.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    rubberband_canvas.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\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\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.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,\n        0,\n        fig.canvas.width / mpl.ratio,\n        fig.canvas.height / mpl.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    var cursor = msg['cursor'];\n    switch (cursor) {\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\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.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.\nmpl.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\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                evt.data\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\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(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\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(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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 */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    var canvas_pos = mpl.findpos(event);\n\n    if (name === 'button_press') {\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, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.which === this._key) {\n            return;\n        } else {\n            this._key = event.which;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.which !== 17) {\n        value += 'ctrl+';\n    }\n    if (event.altKey && event.which !== 18) {\n        value += 'alt+';\n    }\n    if (event.shiftKey && event.which !== 16) {\n        value += 'shift+';\n    }\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, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\nmpl.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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(msg['content']['data']);\n    });\n    return ws;\n};\n\nmpl.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 = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / mpl.ratio;\n    fig.root.removeEventListener('remove', this._remove_fig_handler);\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.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.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'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.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 () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function () {\n    this.close_ws(this, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n    el.addEventListener('remove', this._remove_fig_handler);\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('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    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.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\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\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.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.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n"
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\" 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}