IK_BWS_FABRIK_CCD.ipynb

IK_BWS_FABRIK_CCD.ipynb

{
  "cells": [
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Inverse Kinematics: Backward Shift, FABRIK, CCD "
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-03-28T06:14:52.771045Z",
          "end_time": "2021-03-28T06:14:53.275097Z"
        },
        "execution": {
          "iopub.execute_input": "2021-03-09T19:28:06.847Z",
          "iopub.status.busy": "2021-03-09T19:28:06.829Z",
          "iopub.status.idle": "2021-03-09T19:28:06.867Z",
          "shell.execute_reply": "2021-03-09T19:28:07.034Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "%matplotlib notebook\nimport numpy as np\nimport matplotlib.pyplot as plt",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-03-28T06:14:53.277860Z",
          "end_time": "2021-03-28T06:14:53.327655Z"
        },
        "execution": {
          "iopub.execute_input": "2021-03-09T19:28:06.922Z",
          "iopub.status.busy": "2021-03-09T19:28:06.898Z",
          "iopub.status.idle": "2021-03-09T19:28:06.936Z",
          "shell.execute_reply": "2021-03-09T19:28:07.040Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "class Arm:\n    def __init__(self, _ax, _ay, _length, _angle):\n        self.ax = _ax\n        self.ay = _ay\n        self.length = _length\n        self.angle = _angle\n        self.bx = self.ax + self.length * np.cos(self.angle)\n        self.by = self.ay + self.length * np.sin(self.angle)\n\n    def backward(self, tx, ty):\n        theta = np.arctan2(ty - self.ay, tx - self.ax)\n        self.ax = tx - self.length * np.cos(theta)\n        self.ay = ty - self.length * np.sin(theta)\n        self.bx = tx\n        self.by = ty\n        \n    def forward(self, baseX, baseY):\n        theta = np.arctan2(self.by - baseY, self.bx - baseX)\n        self.ax = baseX\n        self.ay = baseY\n        self.bx = baseX + self.length * np.cos(theta)\n        self.by = baseY + self.length * np.sin(theta)\n    \n    def shift(self, dx, dy):\n        self.ax += dx\n        self.ay += dy\n        self.bx += dx\n        self.by += dy",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-03-28T06:14:53.331391Z",
          "end_time": "2021-03-28T06:14:53.443964Z"
        },
        "code_folding": [
          10,
          14
        ],
        "trusted": true
      },
      "cell_type": "code",
      "source": "N = 8  # the number of link\nOX = 0 # offset x\nOY = 0 # offset y\n\nbws = [] # Backward Shift\nfab = [] # FABRIK\nccd = [] # CCD\nfor i in range(N):\n    linkLength = 1 - i * 0.05\n    initTheta = np.pi / 2\n    if i == 0:\n        bws.append(Arm(OX, OY, linkLength, initTheta))\n        fab.append(Arm(OX, OY, linkLength, initTheta))\n        ccd.append(Arm(OX, OY, linkLength, initTheta))\n    else:\n        bws.append(Arm(bws[i-1].bx, bws[i-1].by, linkLength, initTheta))\n        fab.append(Arm(fab[i-1].bx, fab[i-1].by, linkLength, initTheta))\n        ccd.append(Arm(ccd[i-1].bx, ccd[i-1].by, linkLength, initTheta))\n        \nbwsX = []\nbwsY = []\nfabX = []\nfabY = []\nccdX = []\nccdY = []\nfor i in range(N):\n    bwsX.append([bws[i].ax, bws[i].bx])\n    bwsY.append([bws[i].ay, bws[i].by])\n    fabX.append([fab[i].ax, fab[i].bx])\n    fabY.append([fab[i].ay, fab[i].by])\n    ccdX.append([ccd[i].ax, ccd[i].bx])\n    ccdY.append([ccd[i].ay, ccd[i].by])\n        \nfig = plt.figure(figsize=(5,5))\nax = fig.add_subplot(111)\nax.axis([-1,N,-1,N])\nax.grid()\nax.plot(bwsX, bwsY, color='tab:blue')\nax.scatter(bwsX, bwsY, color='tab:blue')\nax.plot(fabX, fabY, color='orange')\nax.scatter(fabX, fabY, color='orange')\nax.plot(ccdX, ccdY, color='magenta')\nax.scatter(ccdX, ccdY, color='magenta')",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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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 * this.ratio;\n    var y = canvas_pos.y * this.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    fig.cell_info[0].output_area.element.one(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\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 / this.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 (event) {\n    var fig = event.data.fig;\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\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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\" width=\"500\">"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
            "text/plain": "<matplotlib.collections.PathCollection at 0x7fd0044d9d00>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-03-28T06:14:53.475509Z",
          "end_time": "2021-03-28T06:14:53.515760Z"
        },
        "code_folding": [
          1,
          24,
          50
        ],
        "trusted": true
      },
      "cell_type": "code",
      "source": "# Backward + Zero shift\ndef Backward_Shift(arm, _tx, _ty):\n    tx = _tx\n    ty = _ty\n    for i in reversed(range(N)):\n        arm[i].backward(tx, ty)\n        tx = arm[i].ax\n        ty = arm[i].ay\n    \n    dx = OX - arm[0].ax\n    dy = OX - arm[0].ay \n    PX = []\n    PY = []\n    for i in range(N):\n        arm[i].shift(dx, dy)\n        PX.append(arm[i].ax)\n        PY.append(arm[i].ay) \n    PX.append(arm[N-1].bx)\n    PY.append(arm[N-1].by)\n    \n    return PX, PY\n\n\n# FABRIK: Backward + Forward\ndef FABRIK(arm, _tx, _ty):\n    tx = _tx\n    ty = _ty\n    for i in reversed(range(N)):\n        arm[i].backward(tx, ty)\n        tx = arm[i].ax\n        ty = arm[i].ay\n    \n    baseX = OX\n    baseY = OY\n    for i in range(N):\n        arm[i].forward(baseX, baseY);\n        baseX = arm[i].bx\n        baseY = arm[i].by\n        \n    PX = []\n    PY = []\n    for i in range(N):\n        PX.append(arm[i].ax)\n        PY.append(arm[i].ay)  \n    PX.append(arm[N-1].bx)\n    PY.append(arm[N-1].by)\n    \n    return PX, PY\n\n\ndef CCD(arm, _tx, _ty):\n    tx = _tx\n    ty = _ty\n    for i in reversed(range(N)):\n        targetTheta = np.arctan2(ty - arm[i].ay, tx - arm[i].ax)\n        endTheta = np.arctan2(arm[N-1].by - arm[i].ay, arm[N-1].bx - arm[i].ax)\n        dTheta = targetTheta - endTheta;\n        for j in range(i, N):\n            linkTheta = np.arctan2(arm[j].by - arm[i].ay, arm[j].bx - arm[i].ax)\n            linkDist = ((arm[j].bx - arm[i].ax)**2 + (arm[j].by - arm[i].ay)**2)**0.5\n            arm[j].bx = arm[i].ax + linkDist * np.cos(dTheta + linkTheta)\n            arm[j].by = arm[i].ay + linkDist * np.sin(dTheta + linkTheta)\n            if j < N - 1:\n                arm[j+1].ax = arm[j].bx\n                arm[j+1].ay = arm[j].by\n    \n    PX = []\n    PY = []\n    for i in range(N):\n        PX.append(arm[i].ax)\n        PY.append(arm[i].ay)\n    PX.append(arm[N-1].bx)\n    PY.append(arm[N-1].by)\n    \n    return PX, PY\n    ",
      "execution_count": 4,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-03-28T06:14:53.519782Z",
          "end_time": "2021-03-28T06:14:53.662213Z"
        },
        "code_folding": [],
        "trusted": true
      },
      "cell_type": "code",
      "source": "def motion(event):\n    mx = event.xdata\n    my = event.ydata\n    Mouse.set_data(mx, my)\n    \n    BX, BY = Backward_Shift(bws, mx, my)\n    BLine.set_data(BX, BY)\n    BDot.set_data(BX, BY)\n    \n    FX, FY = FABRIK(fab, mx, my)\n    FLine.set_data(FX, FY)\n    FDot.set_data(FX, FY)\n    \n    CX, CY = CCD(ccd, mx, my)\n    CLine.set_data(CX, CY)\n    CDot.set_data(CX, CY)\n    \n    plt.draw()\n\nfig = plt.figure(figsize=(5,5))\nax = fig.add_subplot(111)\nax.axis([-1,N,-1,N])\nax.grid()\n\nBLine, = ax.plot([],[], linestyle='-', color='blue', alpha=1, label='BackWard')\nBDot, = ax.plot([],[], marker='o', color='blue')\nFLine, = ax.plot([],[], linestyle='-', color='orange', alpha=1, label='FABRIK')\nFDot, = ax.plot([],[], marker='o', color='orange')\nCLine, = ax.plot([],[], linestyle='-', color='magenta', alpha=1, label='CCD')\nCDot, = ax.plot([],[], marker='o', color='magenta')\n\nMouse, = ax.plot([],[], marker='x', ms=20, color='red')\n\nplt.connect('motion_notify_event', motion)\nplt.legend(loc='lower right')\nplt.show()",
      "execution_count": 5,
      "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 (fig.ratio !== 1) {\n            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n    if (this.ratio !== 1) {\n        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n    }\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 * fig.ratio);\n                canvas.setAttribute('height', height * fig.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'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.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 / fig.ratio,\n        fig.canvas.height / fig.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 * this.ratio;\n    var y = canvas_pos.y * this.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    fig.cell_info[0].output_area.element.one(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\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 / this.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 (event) {\n    var fig = event.data.fig;\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\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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WNBrcXW/uPW75ptvvnnuu+++9n8Qbr311nWGtd4s7sADD2x/vvUmcq3vpPfiw4LeC8WBGV4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYMX999xzT7beeuv26hNOOCH/8R//sc6drR93f/S7sH/1V3/Vfjf3XnxY0HuhaEFnFHXVdagEmNfxvzwyrq1UbRlbXXVlBJhU55VxtaAzrqWpFvRSwYr7FyxY0P7TZq2P4447LhdddNE6d7b+zNqkSZPanz/yyCPz7W9/u+KrrH+ZBb0njANCvDR0ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBivtXrFiRpzzlKVm0aFG22WabtN6UYezYsYPu/s53vpOjjjqq/bl/+Id/yGc+85mKr2JB7wlUzRAvjZpgFZfrWhGq5jJda4JVXK5rRagulmnbBVqFLbpWQOpiia5doFXYomsFpC6WWNC7QBuCLRb0IUB+9CX+5m/+Jl/72tfa/+eZZ57Z/lNqa3/cf//97d8/b/2t9NbH97///fYbj/Xiw++g90JxYIaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKlhj/7x587LXXnvlT3/6U3tX67vkrXdyf/TPrF177bU5++yzc8cdd7Q//4IXvCBXXHFFjVdY/1ILes8o1wjy0tCVEWBSnVddGQEu1ZllbHXVlRFgUp1XxtWCzriWplrQSwVr7m8V7le84hVp/U76+j6e//znt39PvfVj8b36sKD3SnLNHC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsIv9CxcuzL//+7+33539lltuyQMPPND+ffStttoq++yzT1o/Cn/00Udn1KhRXaSve4sFvaecj4V5aejKCDCpzquujACX6swytrrqyggwqc4r42pBZ1xLUy3opYIN2m9BZw7LS0NXRoBJdV51ZQS4VGeWsdVVV0aASXVeGVcLOuNammpBLxVs0H4LOnNYXhq6MgJMqvOqKyPApTqzjK2uujICTKrzyrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFG7Tfgs4clpeGrowAk+q86soIcKnOLGOrq66MAJPqvDKuFnTGtTTVgl4q2KD9FnTmsLw0dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlyqM8vY6qorI8CkOq+MqwWdcS1NtaCXCjZovwWdOSwvDV0ZASbVedWVEeBSnVnGVlddGQEm1XllXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACX6swytrrqyggwqc4r42pBZ1xLUy3opYIN2m9BZw7LS0NXRoBJdV51ZQS4VGeWsdVVV0aASXVeGVcLOuNammpBLxVs0H4LOnNYXhq6MgJMqvOqKyPApTqzjK2uujICTKrzyrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFG7Tfgs4clpeGrowAk+q86soIcKnOLGOrq66MAJPqvDKuFnTGtTTVgl4q2KD9FnTmsLw0dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlyqM8vY6qorI8CkOq+MqwWdcS1NtaCXCjZovwWdOSwvDV0ZASbVedWVEeBSnVnGVlddGQEm1XllXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACX6swytrrqyggwqc4r42pBZ1xLUy3opYIN2m9BZw7LS0NXRoBJdV51ZQS4VGeWsdVVV0aASXVeGVcLOuNammpBLxVs0H4LOnNYXhq6MgJMqvOqKyPApTqzjK2uujICTKrzyrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFG7Tfgs4clpeGrowAk+q86soIcKnOLGOrq66MAJPqvDKuFnTGtTTVgl4q2KD9FnTmsLw0dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlyqM8vY6qorI8CkOq+MqwWdcS1NtaCXCjZovwWdOSwvDV0ZASbVedWVEeBSnVnGVlddGQEm1XllXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACX6swytrrqyggwqc4r42pBZ1xLUy3opYIN2m9BZw7LS0NXRoBJdV51ZQS4VGeWsdVVV0aASXVeGVcLOuNammpBLxVs0H4LOnNYXhq6MgJMqvOqKyPApTqzjK2uujICTKrzyrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFG7Tfgs4clpeGrowAk+q86soIcKnOLGOrq66MAJPqvDKuFnTGtTTVgl4q2KD9FnTmsLw0dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlyqM8vY6qorI8CkOq+MqwWdcS1NtaCXCjZovwWdOSwvDV0ZASbVedWVEeBSnVnGVlddGQEm1XllXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACX6swytrrqyggwqc4r42pBZ1xLUy3opYIN2m9BZw7LS0NXRoBJdV51ZQS4VGeWsdVVV0aASXVeGVcLOuNammpBLxVs0H4LOnNYXhq6MgJMqvOqKyPApTqzjK2uujICTKrzyrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFG7Tfgs4clpeGrowAk+q86soIcKnOLGOrq66MAJPqvDKuFnTGtTTVgl4q2KD9FnTmsLw0dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlyqM8vY6qorI8CkOq+MqwWdcS1NtaCXCjZovwWdOSwvDV0ZASbVedWVEeBSnVnGVlddGQEm1XllXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACX6swytrrqyggwqc4r42pBZ1xLUy3opYIN2m9BZw7LS0NXRoBJdV51ZQS4VGeWsdVVV0aASXVeGVcLOuNammpBLxVs0H4LOnNYXhq6MgJMqvOqKyPApTqzjK2uujICTKrzyrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFG7Tfgs4clpeGrowAk+q86soIcKnOLGOrq66MAJPqvDKuFnTGtTTVgl4q2KD9FnTmsLw0dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlyqM8vY6qorI8CkOq+MqwWdcS1NtaCXCjZovwWdOSwvDV0ZASbVedWVEeBSnVnGVlddGQEm1XllXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACX6swytrrqyggwqc4r42pBZ1xLUy3opYIN2m9BZw7LS0NXRoBJdV51ZQS4VGeWsdVVV0aASXVeGVcLOuNammpBLxVs0H4LOnNYXhq6MgJMqvOqKyPApTqzjK2uujICTKrzyrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFG7Tfgs4clpeGrowAk+q86soIcKnOLGOrq66MAJPqvDKuFnTGtTTVgl4q2KD9FnTmsLw0dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlyqM8vY6qorI8CkOq+MqwWdcS1NtaCXCjZovwWdOSwvDV0ZASbVedWVEeBSnVnGVlddGQEm1XllXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACX6swytrrqyggwqc4r42pBZ1xLUy3opYIN2m9BZw7LS0NXRoBJdV51ZQS4VGeWsdVVV0aASXVeGVcLOuNammpBLxVs0H4LOnNYXhq6MgJMqvOqKyPApTqzjK2uujICTKrzyrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFG7Tfgs4clpeGrowAk+q86soIcKnOLGOrq66MAJPqvDKuFnTGtTTVgl4q2KD9FnTmsLw0dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlyqM8vY6qorI8CkOq+MqwWdcS1NtaCXCjZovwWdOSwvDV0ZASbVedWVEeBSnVnGVlddGQEm1XllXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACX6swytrrqyggwqc4r42pBZ1xLUy3opYIN2m9BZw7LS0NXRoBJdV51ZQS4VGeWsdVVV0aASXVeGVcLOuNammpBLxWsuP+QQw7JzJkzK65etezKK69Ma1+vPizovZJcM8dLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFay4v25BHz16dO64445su+22FV+h8zILemejblZ4aXSj1nmPrp2Nulmhazdqnffo2tmo2xXadiu3/n266soIMKnOK+NqQWdcS1Mt6KWCFffffvvtWbJkyXpXz5kzJyeccEJ7zWGHHZbLLrusYnq1ZRb0ak51V3lp1BWrtl7Xak51V+laV6zael2rOXWzSttu1Drv0bWzUTcrdO1GrfMeXTsbdbPCgt6NGr/Hgs4bV36Ft7/97TnrrLPa67/85S/nVa96VeW9VRZa0Kso1V/jpVHfrMoOXaso1V+ja32zKjt0raLU3Rptu3PrtEvXTkLdfV7X7tw67dK1k1B3n7egd+dG77Kg08IV81esWJHtt98+d911VzbaaKP84Q9/yIYbblhxd7VlFvRqTnVXeWnUFau2XtdqTnVX6VpXrNp6Xas5dbNK227UOu/RtbNRNyt07Uat8x5dOxt1s8KC3o0av8eCzhtXeoXLL788hx9+eHvta1/72nzpS1+qtK/OIgt6Ha3qa700qlvVWalrHa3qa3WtblVnpa51tOqt1baeV9XVulaVqrdO13peVVfrWlWq3joLej2voVptQR8q6Q6v8+pXvzpf+cpX2qt++MMf5tBDD+35k1nQe07aDvTS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBXuwf/Hixdlqq63abyLX+jH33/72txk1alQPkteMsKD3nNSCzpDqqisowET7Xx4ZV/+foLpyAkyy/yzQlRFgUi3ojGtpqgW9VLAH+88///z2j7W3Pt71rnflQx/6UFeprQK+vo+7774706ZNay+ZPXt2dtxxx65ex01rCixdujSzZs1q/5vTp0/P+PHjJeqBgK49QBwkQlddGQEu1ZllbHXVlRFgUp1XxvW2227Lrrvu2g6fP39+Jk+ezLyQqbUELOi1uJjFL3jBC9o/1t76uPXWW7PTTjt19UJ1vut+7rnnZvPNN+/qddykgAIKKKCAAgoooIACzRZYsGBBTjrpJAt6nx2jBX2YD6T1Xe8ddtghrXdx33fffXPNNdd0/UQW9K7p3KiAAgoooIACCiigwBNKwILen8dtQR/mc/noRz+ad77zne2n+PznP583vOENXT+RP+LeNV3RRn/sqohvnZt11ZURYFKdV8a1laotY6urrowAk+q8Mq7+iDvjWppqQS8VLNy/yy67ZM6cOdlggw3S+h3xpzzlKYWJ697um8QxtL4hjK6MAJPqvOrKCHCpzixjq6uujACT6rwyrr5JHONammpBLxUs2MPJOwkAACAASURBVH/jjTdmn332aSccd9xxueiiiwrSOm+1oHc26maFl0Y3ap336NrZqJsVunaj1nmPrp2Nul2hbbdy69+nq66MAJPqvDKuFnTGtTTVgl4qWLD/zW9+cz772c+2E771rW/lqKOOKkjrvNWC3tmomxVeGt2odd6ja2ejblbo2o1a5z26djbqdoW23cpZ0Bk5XXUdDgHmNS3ojGtpqgW9VLDL/cuWLcu2226be++9N1tssUV+//vfZ+zYsV2mVdtmQa/mVHeV/+Wxrli19bpWc6q7Ste6YtXW61rNqZtV2naj1nmPrp2Nulmhazdqnffo2tmomxUW9G7U+D0WdN540Fdofcf8pS99aftzp512Ws4++2z8SSzoDLGXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtjl/pe//OW5+OKL27t/+tOfZs899+wyqfo2C3p1qzorvTTqaFVfq2t1qzorda2jVX2trtWt6q7Utq5YtfW6VnOqu0rXumLV1utazanuKgt6XbGhWW9BHxrnNV7l/vvvz9Zbb52HHnooU6dOzezZs4fkKSzoDLOXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtjF/hkzZuSUU05p7zzrrLNyxhlndJFSf4sFvb5ZlR1eGlWU6q/Rtb5ZlR26VlGqv0bX+mZVd2hbVareOl3reVVdrWtVqXrrdK3nVXW1Bb2q1NCus6APrXf71Q444ID85Cc/yZgxY3LHHXdkm222GZKnsKAzzF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLdWYZW111ZQSYVOeVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLdWYZW111ZQSYVOeVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLdWYZW111ZQSYVOeVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLdWYZW111ZQSYVOeVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLdWYZW111ZQSYVOeVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLdWYZW111ZQSYVOeVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLdWYZW111ZQSYVOeVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLdWYZW111ZQSYVOeVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYJf7FyxYkC9+8Yv55je/mdtuuy33339/Nttss2y33XaZPn16jj322Oy3335dpg++zYLeU87Hwrw0dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwS72f/3rX88pp5yShQsXrnP3S1/60nzjG9/oIn3dWyzoPeW0oDOcuuoKCzDx/pdHxrWVqi1jq6uujACT6rwyrhZ0xrU01YJeKlhz/wUXXJDXve51WbFiRbbccst2UT/wwAOz6aab5p577ml/N/3b3/52Nt5447SKfC8/LOi91Hw8y0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VrLF/7ty5ee5zn5uHHnooBx100GNFfLCIhx9+OE960pNqpHdeakHvbNTNCi+NbtQ679G1s1E3K3TtRq3zHl07G3W7Qttu5da/T1ddGQEm1XllXC3ojGtpqgW9VLDG/he+8IX5wQ9+kM033zytst7630P5YUFntL00dGUEmFTnVVdGgEt1ZhlbXXVlBJhU55VxtaAzrqWpFvRSwYr7582blylTprRXn3nmmXnf+95XcWfvllnQe2e5epKXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKlhx/wc/+MG8973vba++5ZZbsvPOO7f/devd21vv6N76HfTWu7iTHxZ0RtdLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFay4/4gjjsill17afvO3Vin/6le/mrPOOis333zzYwlPf/rTc+KJJ+atb31rNtpoo4rJ1ZdZ0Ktb1VnppVFHq/paXatb1Vmpax2t6mt1rW5Vd6W2dcWqrde1mlPdVbrWFau2XtdqTnVXWdDrig3Negv60DinVb5/+9vfZvfdd2+/a/s555yzzleeOnVqvv/972ebbbap9XStAr6+j7vvvjvTpk1rL5k9e3Z23HHHWvkuHlxg6dKlmTVrVvuTrb9hP378eKl6IKBrDxAHidBVV0aAS3VmGVtddWUEmFTnlXFt/fWoXXfdtR0+f/78TJ48mXkhU2sJWNBrcXW/uPWd80WLFmWDDTZov4v7Jptsko9+9KM59thjM2nSpHZhbv0I/Pe+9732i+y///750Y9+lNGjR1d+0VGjRlVee+655w75m9RVfjgXKqCAAgoooIACCiigACrQ+jXbk046yYKOKtcPt6DXN+tqx9ixY/PII4+0944ZMyZXX3119t133zWyWn8b/cgjj3yspLf+DvrLX/7yyq9nQa9M5UIFFFBAAQUUUEABBZ7QAhb0/jx+C/oQnUvrd8qXLFnSfrW//uu/zte+9rVBX7n1BnKtH3FvfbS+u37xxRdXfkJ/xL0yVU8X+mNXPeV8LExXXRkBJtV5ZVxbqdoytrrqyggwqc4r4+qPuDOupakW9FLBivu33nrr3HPPPe3V559/fl7zmtesc2fr9z/uuuuubLfddrnjjjsqvkLnZb5JXGejblb4xiXdqHXeo2tno25W6NqNWuc9unY26naFtt3KrX+frroyAkyq88q4+iZxjGtpqgW9VLDi/tabs91www3t1T/4wQ/y/Oc/f50799tvv1x77bXt31dv/X8Me/VhQe+V5Jo5Xhq6MgJMqvOqKyPApTqzjK2uujICTKrzyrha0BnX0lQLeqlgxf2ve93rct5557VXX3bZZTnssMPWufPRMj9x4sQsXry44it0XmZB72zUzQovjW7UOu/RtbNRNyt07Uat8x5dOxt1u0LbbuXWv09XXRkBJtV5ZVwt6IxraaoFvVSw4v4vfelL+du//dv26s9//vN5wxvesM6dm2++eRYuXJiddtopt956a8VX6LzMgt7ZqJsVXhrdqHXeo2tno25W6NqNWuc9unY26naFtt3KWdAZOV11HQ4B5jUt6IxraaoFvVSw4v5W4W79HvqyZcva3z1vfRd9sI+ZM2fmkEMOaX/q7/7u79L6c2i9+rCg90pyzRz/y6OujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXipYY/+pp57a/u5566P1Lu6td3Nf/ePBBx/M9OnT8/Of/7z9b19//fXZZ599arzC+pda0HtGuUaQl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXipYY/+9996bvffeu/3O7K2/i976MffWn1KbNGlSZs+enX/5l3/JvHnz2omnnHJKPve5z9VI77zUgt7ZqJsVXhrdqHXeo2tno25W6NqNWuc9unY26naFtt3KrX+frroyAkyq88q4WtAZ19JUC3qpYM39c+fOzdFHH53/+Z//WefO1u+qz5gxI+PGjauZvv7lFvSecj4W5qWhKyPApDqvujICXKozy9jqqisjwKQ6r4yrBZ1xLU21oJcKdrF/yZIl7R91v+iii9L6D0brndq33HLLHHDAAXn961+fQw89tIvUzlss6J2NulnhpdGNWuc9unY26maFrt2odd6ja2ejbldo263c+vfpqisjwKQ6r4yrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsEH7LejMYXlp6MoIMKnOq66MAJfqzDK2uurKCDCpzivjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFWzQfgs6c1heGroyAkyq86orI8ClOrOMra66MgJMqvPKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEu1ZllbHXVlRFgUp1XxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXKozy9jqqisjwKQ6r4yrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsEH7LejMYXlp6MoIMKnOq66MAJfqzDK2uurKCDCpzivjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFWzQfgs6c1heGroyAkyq86orI8ClOrOMra66MgJMqvPKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEu1ZllbHXVlRFgUp1XxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXKozy9jqqisjwKQ6r4yrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsEH7LejMYXlp6MoIMKnOq66MAJfqzDK2uurKCDCpzivjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFWzQfgs6c1heGroyAkyq86orI8ClOrOMra66MgJMqvPKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEu1ZllbHXVlRFgUp1XxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXKozy9jqqisjwKQ6r4yrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsEH7LejMYXlp6MoIMKnOq66MAJfqzDK2uurKCDCpzivjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFWzQfgs6c1heGroyAkyq86orI8ClOrOMra66MgJMqvPKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEu1ZllbHXVlRFgUp1XxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXKozy9jqqisjwKQ6r4yrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsEH7LejMYXlp6MoIMKnOq66MAJfqzDK2uurKCDCpzivjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFWzQfgs6c1heGroyAkyq86orI8ClOrOMra66MgJMqvPKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEu1ZllbHXVlRFgUp1XxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXKozy9jqqisjwKQ6r4yrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsEH7LejMYXlp6MoIMKnOq66MAJfqzDK2uurKCDCpzivjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFWzQfgs6c1heGroyAkyq86orI8ClOrOMra66MgJMqvPKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEu1ZllbHXVlRFgUp1XxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXKozy9jqqisjwKQ6r4yrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsEH7LejMYXlp6MoIMKnOq66MAJfqzDK2uurKCDCpzivjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFWzQfgs6c1heGroyAkyq86orI8ClOrOMra66MgJMqvPKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEu1ZllbHXVlRFgUp1XxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXKozy9jqqisjwKQ6r4yrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsEH7LejMYXlp6MoIMKnOq66MAJfqzDK2uurKCDCpzivjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLhUZ5ax1VVXRoBJdV4ZVws641qaakEvFWzQfgs6c1heGroyAkyq86orI8ClOrOMra66MgJMqvPKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEu1ZllbHXVlRFgUp1XxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXKozy9jqqisjwKQ6r4yrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKdWcZWV10ZASbVeWVcLeiMa2mqBb1UsMb+UaNGVVp98MEH56qrrqq0ts4iC3odreprvTSqW9VZqWsdreprda1uVWelrnW06q3Vtp5X1dW6VpWqt07Xel5VV+taVareOgt6Pa+hWm1BHyrpJBb0IcQewpfy0mCwddWVEWBSnVfGtZWqLWOrq66MAJPqvDKuFnTGtTTVgl4qWGP/owX9lFNOyamnnrrOnRMnTszTn/70GsnVlvod9GpOdVd5adQVq7Ze12pOdVfpWles2npdqzl1s0rbbtQ679G1s1E3K3TtRq3zHl07/tYOxQAAIABJREFUG3WzwoLejRq/x4LOGz/2Co8W9Pe9730588wzh/CVV72UBZ0h99LQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFa+y3oNfAatBSLw3msHTVlRFgUp1XxrWVqi1jq6uujACT6rwyrhZ0xrU01YJeKlhjvwW9BlaDlnppMIelq66MAJPqvDKuFnRdOQEm2X8W6MoIMKkWdMa1NNWCXipYY78FvQZWg5Z6GTOHpauujACT6rwyrhZ0XTkBJtl/FujKCDCpFnTGtTTVgl4qWGP/owV95513zvLly3PHHXdk7Nix2WqrrbL//vvnta99bQ499NAaifWW+jvo9byqrvYyripVb52u9byqrta1qlS9dbrW86qzWts6WtXX6lrdqs5KXetoVV+ra3WrOist6HW0hm6tBX3orCv9mbWXvexlOe+887LxxhvXfrJWAV/fx913351p06a1l8yePTs77rhj7ddww0CBpUuXZtasWe1PTJ8+PePHj5epBwK69gBxkAhddWUEuFRnlrHVVVdGgEl1XhnX2267Lbvuums7fP78+Zk8eTLzQqbWErCg1+IqW9z682lHH310XvCCF+Q5z3lONtpoo9x7772ZOXNmZsyYkYULF7Zf4OCDD87ll1+ecePG1XrBqn9nvRV67rnnZvPNN6+V72IFFFBAAQUUUEABBRQYGQILFizISSedZEHvs+O0oA/hgTzwwAPZZJNNBn3FP/zhD3nxi1+cm266qf35T3/603nzm99c6+ks6LW4XKyAAgoooIACCiigwBNWwILen0dvQe+jc/nNb36TKVOm5OGHH84zn/nMtH4vpM6HP+JeR6t3a/2xq95Zrp6kq66MAJPqvDKurVRtGVtddWUEmFTnlXH1R9wZ19JUC3qpYI/3H3nkkfnud7/bTr3rrruyzTbb9OwVfJO4nlGuEeQbl+jKCDCpzquujACX6swytrrqyggwqc4r4+qbxDGupakW9FLBHu9/29velo997GPt1Ouvvz777LNPz17Bgt4zSgs6Q6mrrkMgwLyE/+WRcW2lasvY6qorI8CkOq+MqwWdcS1NtaCXCvZ4/xlnnJGPf/zjFvQeu5JxXhqMrq66MgJMqvPKuFrQdeUEmGT/WaArI8CkWtAZ19JUC3qpYI/3H3HEEbn00kvbqa3veG+77bY9ewW/g94zyjWCvIx1ZQSYVOdVV0aAS3VmGVtddWUEmFTnlXG1oDOupakW9FLBHu5vvUlc68+vLVu2LM94xjPSeuOGXn5Y0Hup+XiWl4aujACT6rzqyghwqc4sY6urrowAk+q8Mq4WdMa1NNWCXipYcf+3v/3t9p9RGzt27KA71v4za5/4xCfylre8pWJ6tWUW9GpOdVd5adQVq7Ze12pOdVfpWles2npdqzl1s0rbbtQ679G1s1E3K3TtRq3zHl07G3WzwoLejRq/x4LOG7df4WlPe1r7O+PHHXdc9ttvv/b/PWHChLT+/uBVV12VGTNmZOHChe21Bx54YK644opssMEGPX06C3pPOR8L89LQlRFgUp1XXRkBLtWZZWx11ZURYFKdV8bVgs64lqZa0EsFK+5vFfLf/e53HVe3Cvy5556bTTbZpOPaugss6HXFqq330qjmVHeVrnXFqq3XtZpT3VW61hWrvl7b6lZ1VupaR6v6Wl2rW9VZqWsdreprLejVrYZypQV9iLRnzpyZ1v9cc801af2uees754sWLcpGG22U7bbbLvvvv39OPPHE9nfXqQ8LOiPrpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuFRnlrHVVVdGgEl1XhlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKU6s4ytrroyAkyq88q4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS7VmWVsddWVEWBSnVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpzixjq6uujACT6rwyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLdWYZW111ZQSYVOeVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcqjPL2OqqKyPApDqvjKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUp1ZxlZXXRkBJtV5ZVwt6IxraaoFvVSwQfst6MxheWnoyggwqc6rrowAl+rMMra66soIMKnOK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuNQn1MwuW5T86c5k2eJk3EbJhpOTcZMQ3CeUKyI4eKiuDLaujKsFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUkf8zK5cmfzxquRX5yR3fiNZ+cjjmKPGJJOPSXY6NdnykGTUqJ5Bj3jXnknVC9K1nlfV1bpWlaq3zoJez2uoVlvQh0q6D17Hgs4cgpeGrowAk+q86soIcKkjembv+1lyzWuS/72lM+DGuyT7XZBsumfntRVWjGjXCl8/tURXRlZXxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqSN2Zu++PPnRMcnyJdXxxk5MDrok2fqw6nvWsXLEuhbLlAXoWua3rt26Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aASx2RM9v6zvkV0weW8z89OblvcvLQRskGi5NN70w2fHBN3FZJf+Gs4u+kj0hXbgwrJ+tamarWQl1rcVVebEGvTDWkCy3oQ8o9vC9mQWf8vTR0ZQSYVOdVV0aASx1xM9v6nfNLd338x9pXJplzSHL5G5OfvixZMfZxzNHLk70vSV74uWTnq5JHfwV946nJS24u+p30EefKjWCtZF1rcVVerGtlqloLLei1uIZssQV9yKiH/4Us6MwZeGnoyggwqc6rrowAlzriZvYPVyY/eP4qsNufm8y4ILlzamfAyb9M3vCa5Ok3tdfetOmV2eNFh3T9vnEjzrWz4JCs0JVh1pVxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlzqiJvZHx2fzL8omf3C5FOXrPpx9qofrR97P/2YZNcrcuG1x+cDP7wwF1yQ7NnF+8aNONeqhvA6XRlgXRlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKWOqJlt/Z3zizZNfrNb8sFZ9cr5o8Stkv6e6Vm+/c3Z9PX3ZcXoSbnkkuSwmu8bN6JcufGrnaxrbbJKG3StxFR7kQW9NtmQbLCgDwlzf7yIBZ05By8NXRkBJtV51ZUR4FJH1Mz+75zkO7sk75hd7cfa18U6eXby0d0y5W1zMu/3UzJxYjJrVr3vpI8oV278aifrWpus0gZdKzHVXmRBr002JBss6EPC3B8vYkFnzsFLQ1dGgEl1XnVlBLjUETWzC65PPvX25MNXloO965BM+9pZueE309pZU6cmN9d437gR5Vqu2bMEXXtGuUaQroyrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FJH1My2voN++C3J9ceXgz3vwkyZv2v7O+iPflx5ZXLIIdWiR5RrtS95SFbpyjDryrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLnVEzezCRcmWG675p9S6pFs5enkmP+lP+f3SSY8lHH98cuGF1QJHlGu1L3lIVunKMOvKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEudUTN7Jwku/TOqvW983mrxY0Zk9x3XzLp8c6+zhcbUa69Iy1O0rWYcNAAXRlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKWOqJm9PsnzemfV+u3zG9aKmzMnmfL4T71b0HvHXSlpRM1rpa94aBbpyjhb0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLnVEzew1c5P9K7Tnipxrfwe9te2665Jpq943br0fI8q10xc7hJ/XlcHWlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXOqImdl7r0m+dWRy8h968jvoy5JsluTBtej9Djo3i1WSR8y8Vvlih3CNrgy2BZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FJHxMze84PkyhclKx9JPnlx8tNji8Fa7wV3wlopY8cmCxf6O+jFuAUBI2JeC75+aquujKwFnXEtTbWglwo2aL8FnTksLw1dGQEm1XnVlRHgUhs/s3d+K5l1TJIVyfxdkvdemzy8UTFY66+pzVwrxXdxL2YtDmj8vBYLMAG6Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS230zP72a8lPXplkZXL13yT/en5Pfrx9dpLdBiH376Bzc1g1udHzWvWLHIZ1ujLoFnTGtTTVgl4q2KD9FnTmsLw0dGUEmFTnVVdGgEtt7Mz+z7nJ9X+/CuZLn02ueGOSUcVQi5NMT3LTWklTpyY335yMqvgSjXUtFmQDdGV8dWVcLeiMa2mqBb1UsEH7LejMYXlp6MoIMKnOq66MAJfayJmdd3bys9OT5WOT91+d/GaQv602Olk2Khn3SHW7Vjlv/bD8FWttmTgxmTUr2XPP6lmNdK3+5Q3bSl0Zel0ZVws641qaakEvFWzQfgs6c1heGroyAkyq86orI8ClNm5mZ38omf2e5I87JO+9IXlwi4E4GyfvfmFy6cXJBUmmVuBr/Vj7iYN857xVzi+5JDnssAohqy1pnGu9L2/YVuvK0OvKuFrQGdfSVAt6qWCD9lvQmcPy0tCVEWBSnVddGQEutVEze9Pbk7lnJT97SXL2JckjTxoIMzU5fvvkoksf/9TBSVo/AN/67vjY1Xa0/pTaJUk+N8gbwrWWtX6s/fzz633n/NH4Rrly49XzZF17TtoO1JVxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlxqY2b2hjcmv/5c8vX3J994z6C/b77ib5KDfpv85CcDvXbaKZn94+RJ9yYrFyU3zEv+7yXJV7+TPLLaj8G3/pTaMcckp56aHHxw9d85X/sVG+PKjRaSrCvCakFnWGNBh2ALYy3ohYBN2m5BZ07Ly1hXRoBJdV51ZQS41EbM7E9OTH5zQfIv/5388vCB5XxUsvzsZLcZydy5A62mTUuuuSYZPXrg5xYtSu66K3nwweTJT0623bba3znvdCKNcO30RfTh53VlDkVXxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqX0/s7OOTW75UfLunyX3bTcQYsPkT99JnnNiMn/+wE+/+MXJpav9uDsnuWZy37sOFUSPX0fXHoP+JU5XxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqX09sz98UXLVkuSjlyfLJgxE2CG553vJ1IOShQsHfvrEE5PzzuPs1pfc167DQ9KTV9W1J4wDQnRlXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACX2pczu2JFcsVByZf3Sb7yySRr/2z6yuSIUbntU8keeyaLW38fba2PM85IzjqLc+uU3JeunR66AZ/XlTkkXRlXCzrjWppqQS8VbNB+CzpzWF4aujICTKrzqisjwKX23cy2yvn39ko++I7kuv8z6JvB5YPJjX+VHHhg8tBDA21axbxV0Ifzo+9chxOjh6+taw8xV4vSlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXGpfzezyh5OL90v+8avJPc8e+EW3/qrat5LLRycveUmyfPmaS0aNSr70paT1o+3D/dFXrsON0cPX17WHmBZ0BnO1VAs6TtzVC1jQu2Jr5iYLOnNuXsa6MgJMqvOqKyPApfbNzC5fmpzzsuQdFyZLJw38gp+a5MbkP3+cvOIVycqVay4ZMyb5xjeSI4/krOok941rnYduwFpdmUPSlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXGpfzOzDi5O3vis55xPJyrEDv9gDk1yZ/N8ZyT/8w8BPjxuXzJyZ7Lcf51Q3uS9c6z50A9bryhySroyrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKHfWaX3pcc/e3k8tcM8vvmK5PTRyWfTN773uSDHxzoMGFC8tOfJlOmcEbdJA+7azcP3YA9ujKHpCvjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLjUYZ3Z++9J9v598ps9B36BY1YkXx2d/J/klFOSGTMGLtlkk2T27GTyZM6n2+Rhde32oRuwT1fmkHRlXC3ojGtpqgW9VLBB+y3ozGF5aejKCDCpzquujACXOmwzO/vOZP8JyeLNBn5xT16aXDc+mZIcd1zyX/81cMlWWyVz5yatkt6PH8Pm2o8YPXwmXXuIuVqUroyrBZ1xLU21oJcKNmi/BZ05LC8NXRkBJtV51ZUR4FKHZWa/emfymqcmj4wb+IU9e2Hys82yYnxy6KHJrFkDlzzzmau+cz5+POdSmjwsrqUP3YD9ujKHpCvjakFnXEtTLeilgg3ab0FnDstLQ1dGgEl1XnVlBLjUIZ/Zt9yTfKr1luyj1vqiVibH3p5c/Iz2n0/bc89VJXztj732Sq69Nhk7yHvJcUr1k4fctf4jNnKHrsyx6cq4WtAZ19JUC3qpYIP2W9CZw/LS0JURYFKdV10ZAS61pzO7bFHypzuTZYuTcRslG05Oxv3lT6a1/mb5oQ8kVw/yM+mjHkk+PDt5xx5ZvDiZOjX53e8Gfs2HH55873vJ6NGcR6+Se+raq4caATm6MoeoK+NqQWdcS1Mt6KWCDdpvQWcOy0tDV0aASXVedWUEuNTimf3flckvrk/mXpIs+m7ylN8lGz646oFHjUkmH5Nsclpy+N7JPYP8TPoGS5JLbklePC0LFiQ775zce+/Ar/eVr0y+8hXOodfJxa69fqARkqcrc5C6Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS+1qZlcmuSrJp+5PvvvkZMVqP28+enmy9yXJCz+X7HxVMnd6ctZ/J8smDPwitrg9ufreZKdpuf32ZPfdkwf/0u1XX3z66cknP8kZEMlduRIPMsIydWUOVFfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCptWf2Z0laf7L8lgrPtPHdyf+2ft987Z9JX5ns+Z3ksu2SzfbIz3+e7LdfsnTpwMwPfzh55zsrvFafLant2mfP36+PoytzMroyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLrTWzlyc5JsmSkudZkZzwvuRfX5Vs/Oz88IfJi16U9hvDrf4xalTyb/+WnHRSyWsN395arsP3mI17ZV2ZI9OVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcauWZbX3nfHphOR+7NDnjiCzZ/a5sePzcXPxfo3LCCcmKFWt+fa03gWv97fOXvpT7uunkyq70g4ywfF2ZA9WVcbWgM66lqRb0UsEG7begM4flpaErI8CkOq+6MgJcaqWZbf3O+a4Vf6x9XY86elny6e2TTe9przju81fmv64+ZMDqcePS/q76gQdyX/NQJFdyHYoHGWGvoStzoLoyrhZ0xrU01YJeKtig/RZ05rC8NHRlBJhU51VXRoBLrTSzVyZ5fg+e4V2HJDvPbAddeO3xOeGzF64ROmFCcv31q/7MWtM/Krk2/YschufXlUHXlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXGqlmT0+yUU9eIbnXZi8+YR20PJHxmTT19+XB/+86u+kT5qUzJ6dbL99D16nDyIqufbBczbtEXRlTkxXxtWCzriWplrQSwUbtN+CzhyWl4aujACT6rzqyghwqR1ndlGSTZM80oNnaP0Jtn/d9LG/kz7ljDmZ9/spGTMm+cMfks0268Fr9ElER9c+ec6mPYauzInpyrha0BnX0lQLeqlgg/Zb0JnD8tLQlRFgUp1XXRkBLrXjzM5JsksPX/+sKcm289qB095zXW74zbT2v77yyuSQgb+S3sMXHtqojq5D+zgj5tV0ZY5SV8bVgs64lqZa0EsFG7Tfgs4clpeGrowAk+q86soIcKkdZ/b6JM/r4et/YFqy4w3twEe/g97618cfn1y45q+k9/BFhz6qo+vQP9KIeEVdmWPUlXG1oDOupakW9FLBBu23oDOH5aWhKyPApDqvujICXGrHmYW+g75s+dhs9oaFj/0OeuvH3O+7b9Xvoo+Ej46uI+GLHIavQVcGXVfG1YLOuJamWtBLBRu034LOHJaXhq6MAJPqvOrKCHCpHWe2l7+DPmZZMmOz9u+gD/Yu7nPmJFOmcF/rUCZ3dB3KhxlBr6Urc5i6Mq4WdMa1NNWCXirYoP0WdOawvDR0ZQSYVOdVV0aAS600s8C7uB/yoSszc+6av3R+3XXJtFW/kt74j0qujf8qh/4L0JUx15VxtaAzrqWpFvRSwQbtt6Azh+WloSsjwKQ6r7oyAlxqx5ldkWT/JNf14Bn+8nfQZ8+fmt3ecXOSUWuE+h30HhiP8IiO8zrCv37qy9OVkbWgM66lqRb0UsEe7H/b296Wj33sY48lXXnllTkEeKtYC3oPDmuQCC8NXRkBJtV51ZUR4FLXO7NLk+yd5JYevP7k2clHd8vihyZm+gdn5abf7rlG6NixycKF/g56D6RHdIT/jGWOV1fG1YLOuJamWtBLBQv3/+IXv8jee++d5cuXW9ALLYdru5cGI6+rrowAk+q8Mq6t1HXa3pNk9yR/7MFrb7A4ec/0LN76VznmU5fkil8eNiDUd3HvgfMTIMJ/FjCHrCvjakFnXEtTLeilggX7V6xYkX333Tc33HBDttxyy/zxj6v+W4bfQS9AHYatXhoMuq66MgJMqvPKuK6zoP/8Lz/W/udBXnf08mTF2OoP1Crnpx+T2ZvckxNnnD/gO+ePBvl30KuTPpFX+s8C5vR1ZVwt6IxraaoFvVSwYP/ZZ5+d008/Pc95znNyzDHH5CMf+YgFvcBzuLZ6aTDyuurKCDCpzivjOmhBv2xCclySR9Z+zZXJiz6dHHRBMuOC5M6pHR9q5eRf5vIDvpwP3/zizJx78IDfOX80YOrU5Oabk1Fr/kp6x/x+XuDMMqejq66MAJNqQWdcS1Mt6KWCXe6fP39+dt555yxevLj9HfOrrroq73//+y3oXXoO5zYvY0ZfV10ZASbVeWVc1y7oL57z4jzp/3vSIC+2Inntm5LDPr/qc7t9JFnwjtzyxuTZc5LVv5++LCszc+J9uWD84nxjyVPy4NL1/2HziROTWbOSPdf8lXTuCx6iZGeWgdZVV0aASbWgM66lqRb0UsEu9x911FH5zne+kxNPPDHnnXdezjzzTAt6l5bDvc3LmDkBXXVlBJhU55VxXb2g7/653bPDZTtk1FrvrJ7Ry5K3HpXs8f1VD7Hn2clzTssb35h87nPJk5Nsm1X/+8Ekd/3lf1d54lY5v+SS5LCBv5JeZXtfr3FmmePRVVdGgEm1oDOupakW9FLBLvZfeOGFOeGEE7Lppptm3rx52WKLLSzoXTj2yxYvY+YkdNWVEWBSnVfGtV3Ql/w5i/dbnC1mbzHwRTZ4MPnA85LJc1d9bp9/TZ51cv76r5P//M+ByzffPGn9z7x5nZ+39WPt558/8r5z/uhX7sx2noFuVujajVrnPbp2NupmhQW9GzV+jwWdN17jFR544IFMmTIl99xzT77whS/kpJNOan/e76AP8UH08OW8NHqIuVqUrroyAkyq88q4ZnGyYvcVGf2b0QNfYJO7ko/slky6b9Xvju93QVbs8Kocfnjygx8MXP7MZyazZycbbJDMnJmcc86q744/strvsrf+lNoxxySnnpocfPDI+p3ztUWcWWZmddWVEWBSLeiMa2mqBb1UsOb+k08+uV3M999//1x99dUZ9Zd3nOlFQW/9nfP1fdx9992ZNm1ae8ns2bOz44471nx6lw8msHTp0sxq/YJikunTp2f8+PFC9UBA1x4gDhKhq66MAJA6Pxm/7/iMun+Qd2bb4WervnM+dnlWZlQenvb/snzrl+Wgg56Um24aM+Bhdt99RX70o4fSKuCrfyxalPz+96Py4IPJk5+cbLPNykxa/6+kA1/o8ET6zwLGXVddGQEm9bbbbsuuu+7aDm+9P9bkyZOZFzK1loAFvRZX2eJWIW8VuDFjxuRnP/vZY/+BaKX2oqA/WvarPOW5556bzVs/5+eHAgoooIACfSawya2b5MB3H5gxy9Yu2yuTvS9OTj++/cStcn7tBu/KnSum5bTTDs3dd2804CvZbbc/5swzr8noQb4J32dfto+jgAIKDKnAggULHvtpXgv6kNKv98Us6EN0Fg8//HD22GOPzJ07N2eccUbOOuusNV7Zgj5EB+HLKKCAAgr0tcC2s7bNXp/aK6NWrv2d85XJ0R9OTnh3+/lXZHR+ssGZmf/wnnnTm56f++6bMODr2n//u/K2t93Y11+vD6eAAgoMl4AFfbjk1/+6FvQhOpdHC/j222+fOXPmZGLrrWFX++hFQfdH3IfoMNd6GX+cjXHXVVdGgEl1XnvjOvbDYzP2Q2MHvlP7qEeSv/+75ODz2y+0ctTYPHTQ5bl72fOy117jc/+AH4Nfmb//+0fy6U8v682DjcAUZ5Y5VF11ZQSYVH/EnXEtTbWglwpW2N96p/bdd989re+if/Ob38zRRx89YFcvCnqnR2kV+O2226697Fe/+lWe9axnddri5ysI+IYwFZC6WKJrF2gVtuhaAamLJbp2gbZygewWAAAgAElEQVT2llcl+X+D5Ix5KHnnC5MpV6/65OgnJYddk1/ft2ee+9xkyZKBe9797uSDH+zBM43gCGeWOVxddWUEmFTfJI5xLU21oJcKVtj/+te/Pv/2b/+WZzzjGfnnf/7nQXdcdNFFufjii9ufe8973pOdd965/a9bfy997e+2V3jJQZdY0LuVW/8+L2NdGQEm1XnVlREoSF2e5MAk1w2SMeGB5J/3TJ56e/uTK0ePz6i/ujE/+80u2X//5KGHBu45++zktNMKnucJstV/FjAHrauujACTakFnXEtTLeilghX2v/a1r835rT+m2sXH7bffnqc97Wld7By4xYLeE8YBIV7GujICTKrzqisj0GXqA0l2T3LHIPs3v33Vn1HbcHH7k8uzQZYddmOumT01L3pRsrxV7Ff7aP1RlAsuSF7V+k68Hx0F/GdBR6KuFujaFVvHTbp2JOpqgQW9KzZ8kwUdJ04s6EOAPIwv4aXB4OuqKyPApDqvXbj+OsneSRYNsvdZP07ePT0Zu6L9yWWZkB9O+EwW/OnVec1rNsiKVf/2Yx9jxiTf+lbykpd08RxP0C3OLHPwuurKCDCpFnTGtTTVgl4q2KP9/g56jyCHIcbLmEHXVVdGgEl1Xmu6XpXk8HbzXutjZXLAl5NTT3zs3185buP899iz8+3Ld8+MGXtk5Vrv7j5uXDJzZrLffjWf4Qm+3JllBkBXXRkBJtWCzriWplrQSwV7tN+C3iPIYYjxMmbQddWVEWBSndcarv+e5O/bf8R8YDl/+buTYz78+L//pM3y5xfclJPfvChf+UrrvVnW/NNrEyYkN9yQ7LJLjdd3aVvAmWUGQVddGQEm1YLOuJamWtBLBXu034LeI8hhiPEyZtB11ZURYFKd14qub09y1iBrRy1P3vSKZN+LHv/k+K2SI2/NaWdMyGc+M3ZAOZ80KZk9O9l++4qv7bI1BJxZZiB01ZURYFIt6IxraaoFvVSwR/st6D2CHIYYL2MGXVddGQEm1Xmt4HpMkm8Msm7cn1f9vvkzb3z8kxtObpfz1560Yc4/v/Wt9jW/c77FFsmcOcnmm1d4XZcMKuDMMoOhq66MAJNqQWdcS1Mt6KWCPdpvQe8R5DDEeBkz6Lrqyggwqc7relwfTjItyS8GWTNxQfKR3ZPNfv/4Jyc+Iznilhzx0vG59NKBe3bYYVU533BD5iyfKKnOLHPSuurKCDCpFnTGtTTVgl4q2KD9/pk15rC8jHVlBJhU51VXRmAdqQuS7Jbk7kE+v9WtyT/vkYxf+vgnn/ycrHjx7Bxw0Nhce+3APVOmrMjNN4/O2NZPvPtRJOA/C4r41rlZV10ZASbVgs64lqZa0EsFG7Tfgs4clpexrowAk+q86soIDJL6yyT7JlkyyOd2uSJ5x2HJ6NU+t8luefj5N2WPPUdn7tzByvmC3HDDxEycOGHIvoSR/EL+s4A5XV11ZQSYVAs641qaakEvFWzQfgs6c1hexroyAkyq86orI7BWautH01+aZPnar7YyecGM5G9PXfMTm03L4v2uyc5TR2f+/IFPuM8+d+dd77o+hx9+eCa03rrdj2IB/1lQTDhogK66MgJMqgWdcS1NtaCXCjZovwWdOSwvY10ZASbVedW1SGBRkjuTLE6yUZLJSSatlfjZJKet48+over05MWfXnPDlodkwW4/aJfze+8d+HSvfvXyHHfcd9ufsKAXnd4am/1nQe8sV0/SVVdGgEm1oDOupakW9FLBBu23oDOH5WWsKyPApDqvutYWaL2J+lVJzvnLu7A/slrCmCStd2dvfUP8kOT/Z++8w6woz/f/2SJVULFGMMaYiKtADCLGqIAF1Ghi0BBjYokl0WBi7I1YokaN/owagyWaWGL5StS1ohSlKFEBAWmLJNixgwoIKyy7v2uWBXb3nOXMnPfcu+fAPdflH5l5nvud+TxPzrs3M/MOpwN/SzNCcRWcMRB2f6rhwa8dzNvffIbu3WHx4tS8c8+FP/5xGSNHjrRBT1y4dSf4tyDHQOvkzNVcNQQ0qjboGq6hqjbooQQLKN8GXVMsT8bmqiGgUXW/mmsiAlOA44BZMbLarYSlkWNvtLVeBpf2hu2jl9LrbdsdwczNHmGPPaCy3jpxqyP+/Gc47zxwz8Zgn0WIuWYBLUaKucaAlEWIuWYBLUaKDXoMSC0QYoPeAtBbakgbdA15TxrmqiGgUXW/mmtsAqPq7o6nW+Qtrsimn8BVu8Am0XLu9bZv/IIJNfex336wYkXDQ0VFcMcdcNJJq/a7Z+PCThZnrsl4xY0217ikksWZazJecaNt0OOSat44G/Tm5d2io9mga/B70jBXDQGNqvvVXGMRiO6c92liBfZYAsB2r8GVvaC00UpxO/6KJz76OwMHQnV1Q7HiYnj4YWqPrd7cs3GBJ4sz12S84kaba1xSyeLMNRmvuNE26HFJNW+cDXrz8m7R0WzQNfg9aZirhoBG1f1qrhkJRO+cd4/5WHtTYm0Wwd83gcZPvHc9g3tm3sAJJ0BNNE69Lfq2+ahR0C96l73e5p7NWLGsAsw1K2wZk8w1I6KsAsw1K2wZk2zQMyJqkQAb9BbB3jKD2qBruHvSMFcNAY2q+9VcMxIYA+yfMSpzwJB+sMu42rhaL77DCdzw0j85++zU1Nat4eWXYbfdUo+5ZzOjzibCXLOhljnHXDMzyibCXLOhljnHBj0zo5aIsEFvCeotNKYNuga8Jw1z1RDQqLpfzTUjgUHAwxmjMgfsOQxOP2pN3Oz3u7HrudOBoga5G28M06bBjjuml3TPZkadTYS5ZkMtc465ZmaUTYS5ZkMtc44NemZGLRFhg94S1FtoTBt0DXhPGuaqIaBRdb+a6zoJRN857wTU/5RatsiiT6vd3gnarf1+Wr8rxzCuYu0z7J06QUUFbLVV04O4Z7MtwLrzzNVcNQQ0qu5XDVcbdA3XUFUb9FCCBZRvg64plicNc9UQ0Ki6X811nQRmA7vmkNG1ZdB5zhrBYS8P4qibh9X+786dYfZs6NjRRjKHxGNL+bcgNqpEgeaaCFfsYHONjSpRoA16IlzNFmyD3myoW34gG3RNDTxpmKuGgEbV/Wqu6yQwEdgzh4wu7w07TlojWLWyhE6nLOSrlR1ZtAiid88zbe7ZTISyO26u2XHLlGWumQhld9xcs+OWKcsGPROhljlug94y3FtkVBt0DXZPGuaqIaBRdb+a6zoJiO+gR2OXnTubOe+XMWZM6ort6c7NPeue1RDQqLpfzVVDQKNqg67hGqpqgx5KsIDybdA1xfJkbK4aAhpV96u5rpNALt9BL1kBt23e4B30aOzeF7/CpDd6M2gQDFv1tPs6N/dsJkLZHTfX7LhlyjLXTISyO26u2XHLlGWDnolQyxy3QW8Z7i0yqg26BrsnDXPVENCoul/NNSOBnwCPZIzKHNBoFffVCavvoJeUwMKFfgc9M0hNhH8LzFVDQKPqftVwtUHXcA1VtUEPJVhA+TbommJ50jBXDQGNqvvVXNdJ4EOgG7AgB5zqfQd9tdqKqlI2P3UBi5etWhkuWiSurGzdY7lnc1CLNBLmaq4aAhpV96uGqw26hmuoqg16KMECyrdB1xTLk4a5aghoVN2v5tokgbHAwcBXOWDUZQZc06PxJ8+pv4p7NMorr0Dv3jboOSCeWMK/BYmRxUow11iYEgeZa2JksRJs0GNhavYgG/RmR95yA9qga9h70jBXDQGNqvvVXNMSuA44H6jJAZ/WS+DiPrDD1BSxxt9B9x30HPDOUsK/BVmCy5BmruaqIaBRtUHXcA1VtUEPJVhA+TbommJ5MjZXDQGNqvvVXBsQqAYGAY82waUVsDwBs8icnzkQuo9OSZrxbjd6XDCd1bfVS0thwQK/g56Abk5D/VuQU5xrxMzVXDUENKo26Bquoao26KEECyjfBl1TLE/G5qohoFF1v5rrGgLRiu29gP+mYRJ9n/xpoHI0nLoNvBe9mJ5hix5rP/X4tHfOl1S2p88V45n6Vs81Il7FPRNQ7XH/Fmj4mqu5aghoVG3QNVxDVW3QQwkWUL4NuqZYnozNVUNAo+p+NddaAtOAfYElaXhsA7wavYt+H7x0HNTUQEVfGHUaTB4I1aVrk6JPqfUqhwNvgbJxKe+cR4GROR94QzmjZ/ZvMJi/g67pxbiq/i2ISypZnLkm4xU32lzjkkoWZ4OejFdzRdugNxfpPBjHBl1TBE8a5qohoFF1v5ordwEnA9Hj7Y23yLQ/D7x1J0z8Verx5dvy3BsP8I2Ft7Lj9q/BZvNTvnNePyl6rP342+5pcOc8Ot6tG0yfDkVFmevhns3MKJsIc82GWuYcc83MKJsIc82GWuYcG/TMjFoiwga9Jai30Jg26BrwnjTMVUNAo+p+3cC5/hq4owkGZwHXA3NvgcmnpQZttAnXz5nNOZdsW7uaXN+ycZzWfygDe5VTWrJyTXz0KbXyyQO5ZfRgxkV33mnowtu3h/Hjoefap93XWRT37Abes5rLl6m6XzVozVXD1QZdwzVU1QY9lGAB5duga4rlScNcNQQ0qu7XDZRrJbA3MCXN9UdPrD8I/ASo+AtMPTs1qFUnLnzpda75yxYpxzq0XUTnzebToc1iFld2YP5nndd857xxcGTOy8uhf8On3W3QNW1prubaAgQ0Q3ru0nC1QddwDVW1QQ8lWED5NuiaYnnSMFcNAY2q+3UD5DoPiL41vjDNtW8KvAx0BWb+Cab/ITWo9Zac8vRc/n5XFNxw22IL2HJLqKjIzDV6rP2ee+LfOV+t6J7NzDabCHPNhlrmHHPNzCibCHPNhlrmHBv0zIxaIsIGvSWot9CYNuga8J40zFVDQKPqft3AuD5ed2e8Ks119wBeAtoB0y+BmVekBrXZhp/c+zqPPN4x5dg3vwmzZkHr1jBuHAwduuru+Mq1T7sTfUpt4EAYPBj69o33znnjgdyzG1jPai632VTdrxrU5qrhaoOu4RqqaoMeSrCA8m3QNcXypGGuGgIaVffrBsT1IuDqJq73eODuumNTz4eKa1MCa9p25oCb5jJmXOTgG249esCrr1JrwOtvixbB/PmweDF06ACdO2f+znmmirhnMxHK7ri5ZsctU5a5ZiKU3XFzzY5bpiwb9EyEWua4DXrLcG+RUW3QNdg9aZirhoBG1f26AXCN7pYfVLcae+PLLQZuAU6pOzD59zD3r6nmvN327HHZHF59rU3KsX33hbFjoTjSaobNPauBbK7mqiGgUXW/arjaoGu4hqraoIcSLKB8G3RNsTxpmKuGgEbV/bqec/0Q6AXMT3Od0Y3wscAedccmngr/uz0lsLr9tyg7ZxZz/9cq5dhhh8GTT2oYNqXqntXwNldz1RDQqLpfNVxt0DVcQ1Vt0EMJFlC+DbqmWJ40zFVDQKPqfl2PuY6vu3MerdjeeNsBmAx0qjvw0i/hzXtSwla2L2P706Yzf36jZ9eB445btchbc2/uWQ1xczVXDQGNqvtVw9UGXcM1VNUGPZRgAeXboGuK5UnDXDUENKru1/WUa/T98nNrP0+euv0IKAdWP5L+4s/gnYdS4lZs3IOtfzmVzz5LfXb9jDPghhs07DKpumczEcruuLlmxy1TlrlmIpTdcXPNjlumLBv0TIRa5rgNestwb5FRbdA12D1pmKuGgEbV/bqeca0Gfgo8kua6ioA/ARfWOzZ+ILz3WEpwZftebHnMKyxZkmrOL7sMLr1Uwy2Oqns2DqXkMeaanFmcDHONQyl5jLkmZxYnwwY9DqXmj7FBb37mLTaiDboGvScNc9UQ0Ki6X9cjrovq3jf/b5pril4fHw4cUO/YmEPgg2dTgpe024ctjx5HZWWqOf/rX+F3v9Mwi6vqno1LKlmcuSbjFTfaXOOSShZnrsl4xY22QY9LqnnjbNCbl3eLjmaDrsHvScNcNQQ0qu7X9YTrNGBfYEma69kGmAR0qTtWXQ3PHwgfj0kJ/rz1/mx19HOsWNHwUFER3HsvHHOMhlcSVfdsElrxY801PqskkeaahFb8WHONzypJpA16ElrNF2uD3nysW3wkG3RNCTxpmKuGgEbV/boecI0WajsRiB5vb7xFpv15YPUab5E5H70vfPqflNCPSw9h258PZ+XKhoeiz6c9/jhEK7bnw+ae1VTBXM1VQ0Cj6n7VcLVB13ANVbVBDyVYQPk26JpiedIwVw0Bjar7tcC5ngqkfhlt1UWdBUSLxa3eInM+sjcsfDXlot9lINsf8yg1jRaVKy2FMWNgn300nLJRdc9mQy1zjrlmZpRNhLlmQy1zjrlmZpRNhA16NtT0OTboesZ5M4INuqYUnjTMVUNAo+p+LVCu0afTItOc6rVX3S2/v26xuPrm/NnvwufTUy547vKj6XrCAyn7W7eGl1+G3XbTMMpW1T2bLbl155mruWoIaFTdrxquNugarqGqNuihBAso3wZdUyxPGuaqIaBRdb8WINc3gT2ABWnOfVPgZaBrvWPVVTC8Oyyak5IwbfEv+e6pd6Xsb98eXnsNdtxRwydE1T0bQq/pXHM1Vw0Bjar7VcPVBl3DNVTVBj2UYAHl26BriuVJw1w1BDSq7tcC4/oE8BOg0SJutVfRvc6ct6t3TVXLYfgusGReyoVO+PhU9jnz1pT9m20GM2fCtttq2ISqumdDCabPN1dz1RDQqLpfNVxt0DVcQ1Vt0EMJFlC+DbqmWJ40zFVDQKPqfi0grkOAq5o43+OAaLG4+ltVJTy1Myx9OyVp5Nunc9BFN6Xs32YbqKiATaM78Xm6uWc1hTFXc9UQ0Ki6XzVcbdA1XENVbdBDCRZQvg26plieNMxVQ0Cj6n4tAK7R6uwDgOfSnGv0qfJbgFMam/Ol8OROsGx+StKjFedx5JV/Ttn/jW/ArFnQrv4deA2eIFX3bBC+JpPN1Vw1BDSq7lcNVxt0DddQVRv0UIIFlG+DrimWJw1z1RDQqLpf85zrh0AvINVnQ2Skx9a9j17/MpYvgqe6QmWUvHaLFmi/e/KlnHjDZSkXveuuMG0aRKu25/vmntVUyFzNVUNAo+p+1XC1QddwDVW1QQ8lWED5NuiaYnnSMFcNAY2q+7WFuC4C3gOWABsDXYCOjc5lPHAQEK3Y3njbAZgMdGp0oHIhPN0Vvvo0xZzfPP4qfn/7hSlSe+0FL74I0ffOC2Fzz2qqZK7mqiGgUXW/arjaoGu4hqraoIcSLKB8G3RNsTxpmKuGgEbV/dqMXKNb2NEd76HAY8DKemOXAAOBwUA/4AbgHKDRd8lrMw4DHgcaG+rKj1e9c778sxRzftUz1/OH+6IPozfcDj4YnnlGw0Cl6p7VkDVXc9UQ0Ki6XzVcbdA1XENVbdBDCRZQvg26plieNMxVQ0Cj6n5tJq4VbSFayG1WjPGiO+nRHfbGWxFwBRAtFtd4W/o+PL0LrPgixZxf9OhQrnkkcv4Nt5//HO6PvpdeYJt7VlMwczVXDQGNqvtVw9UGXcM1VNUGPZRgAeXboGuK5UnDXDUENKruVz3Xg0sOpvXPWsOXAWO1Ap4C+qfR+PIdeHpXqIqel1+7RTfff3//ndw8/KSUpN/+Fm6+OeB8WjDVPauBb67mqiGgUXW/arjaoGu4hqraoIcSLKB8G3RNsTxpmKuGgEbV/arlusm8Teh7SV+Kvoxuf2e5bV33vnn0nnrjbfE8GN4DVi5tZM6LOPkf/+Kfz/8iJeXii+Hyy7M8lzxIc89qimCu5qohoFF1v2q42qBruIaq2qCHEiygfBt0TbE8aZirhoBG1f0q5DpiJPv9fj86vtN49bcEY0YrtX8ObJQm54vX4dnvwsplKeb8F7cO48EXf5KSdMMNcMYZCcbPw1D3rKYo5mquGgIaVferhqsNuoZrqKoNeijBAsq3QdcUy5OGuWoIaFTdrzquU66fwt4X7x0+wGMV0K8G2nWBjerM/mczYUQvqP6qkTkv5ogby3ls0o8a7C8qgrvuguOPDz+dllZwz2oqYK7mqiGgUXW/arjaoGu4hqraoIcSLKB8G3RNsTxpmKuGgEbV/arjuvDAhXT+T+fwAfYcBqcfBUUl0GUgbH0AvHo61KxIMec/uHY4z74WfZtt7RZ9Pu3RR+Hww8NPJR8U3LOaKpiruWoIaFTdrxquNugarqGqNuihBAso3wZdUyxPGuaqIaBRdb+KuH60jNbbtqa4OgcfFy+ugts7QbvFTZ5sNSXsf+VoxlVE32hbu5WWwqhR0K/hbs1FN5Oqe1YD2lzNVUNAo+p+1XC1QddwDVW1QQ8lWED5NuiaYnnSMFcNAY2q+1XDtXJKJW12b5M78WvLoPOctHora0rZ949jeem/DR+nb90a/vMf6Nkzd6eRD0ruWU0VzNVcNQQ0qu5XDVcbdA3XUFUb9FCCBZRvg64plicNc9UQ0Ki6XzVcK8dX0qZvDg365b1hx0kpJ1tTA8fc8i8e+M8xDY61awdTpkDXrprra0lV96yGvrmaq4aARtX9quFqg67hGqpqgx5KsIDybdA1xfKkYa4aAhpV96uGa3PeQZ/xbjd6XDAdWPUpt002gZkzoUu6z7JpLrdZVd2zGtzmaq4aAhpV96uGqw26hmuoqg16KMECyrdB1xTLk4a5aghoVN2vIq65fAe9ZAXctvk630Hvd+WY2vfPt9oKKiqgUyfNdeWDqntWUwVzNVcNAY2q+1XD1QZdwzVU1QY9lGAB5duga4rlScNcNQQ0qu5XHdecr+K+jlMd9vIgjrltGJ99Bu3ba64pX1Tds5pKmKu5aghoVN2vGq426Bquoao26KEECyjfBl1TLE8a5qohoFF1v+q4TrluCntfmoPvoA/pB7uMW+eJVq0sodMpC3lieMf1asX2dBftntX17MiRI2vFBwwYQNu2bTUDbWCq7ldNwc1Vw9UGXcM1VNUGPZRgAeXboGuK5UnDXDUENKruVx3XpT2XsvmczcMG6DIDrumx+vXydWqVnTub7nuXMWxY2JD5nu2e1VTIXM1VQ0Cj6n7VcLVB13ANVbVBDyVYQPk26JpiedIwVw0Bjar7VcN15f4rKRlTEibeeglc3Ad2mBpLp/fFrzDl7d4sXAgdO8ZKKcgg96ymbOZqrhoCGlX3q4arDbqGa6iqDXoowQLKt0HXFMuThrlqCGhU3a8CrocDTwTqRub8zIHQfXRsoegO+pz3y5g9G8rKYqcVXKB7VlMyczVXDQGNqvtVw9UGXcM1VNUGPZRgAeXboGuK5UnDXDUENKru1xxz/RnwUBrNw4A3gVkxxoseaz/1+Nh3ziPFFVWlbH7qAhYv68grr0Dv3jHGKdAQ96ymcOZqrhoCGlX3q4arDbqGa6iqDXoowQLKt0HXFMuThrlqCGhU3a855HoicFeqXtXAKkofLYUaIFrrbShQDqysFxt9Sq1XORx4C5SNi/XOef2RolXcj7p51cvnvoOew5puQFL+LdAU21zNVUNAo2qDruEaqmqDHkqwgPJt0DXF8mRsrhoCGlX3a464/g74W6rWh7t/yCYvbJK6IvYiYD4w4TL47CHYbP46v3Oe6SxXfwe9tBQWLPA76Jl4+XgqAf8WaLrCXM1VQ0CjaoOu4RqqaoMeSjBm/qJFixg+fDiTJk1i8uTJzJ8/n08++YToh3zTTTdll1124Qc/+AEnnXQSm28euApwE+dkgx6zWAnDPBknBBYz3FxjgkoYZq4JgaULPw+4LvXAJ90/4T9X/KfpT1ZNvRAqrgk+gRnvdqPHBdOJbrsPGoRXcQ8mumEK+LdAU3dzNVcNAY2qDbqGa6iqDXoowZj5o0ePpn///hmjt9hiC+677z4OOuigjLFJA2zQkxKLF+/JOB6npFHmmpRYvHhzjcepyag/ApelHl3ZeyVPXfAUFDfxTekpZ8OcvwQODksq29PnivFMfatnrdaYMfg76MFUN0wB/xZo6m6u5qohoFG1QddwDVW1QQ8lGDM/Mugnnngi++23H7vvvjvbbbcdX/va16iuriYyzg8//DCPPvooK1eupFWrVrV32nv06BFTPV6YDXo8TkmjPBknJRYv3lzjcUoaZa5JidWLj+6aR3fPG2+7wbIXlzFy9MjaIwMGDGj4iPvk02HuzSlp1dVFFBdHL6rH2yJzPvCGckbPXPWPvd26wfTpUFQUL79Qo9yzmsqZq7lqCGhU3a8arjboGq6hqjbooQRj5kfGu6Rk3d/Ifeyxxxg4cGCt4hFHHMEjjzwSUz1emA16PE5JozxpJCUWL95c43FKGmWuSYnVxUfvm0fvnTfedl61Uvuyr5YxcmQagz7xN/C/21LSKt7fmWNvuYe7TzmRbttlXuo9eqz9+NvuWXPnvH17GD8eeq66kb5eb+5ZTXnN1Vw1BDSq7lcNVxt0DddQVRv0UII5zi8rK2POnDlEj7pH76jncrNBzyXNtVqeNMxVQ0Cj6n7Ngmu0Unu0Ynvj7ZvA60ApteuJpBj0l0+EN1KXeZ/57q5856JpVFeXEi313rdsHKf1H8rAXuWUlqxd6j36lFr55IHcMnow4yr61r5zHm2ROS8vhxhvTWVxsfmX4p7V1MRczVVDQKPqftVwtUHXcA1VtUEPJZjj/F69evHqq6+y8cYbs3jx4pyq26DnFOcaMU8a5qohoFF1vybkGn3j/OhaH91w2w6YC7RZtTuF69RfwVv3pww29a3d6DnkVWpfVq/bWreG7baDj+YvovNm8+nQZjGLKzsw/7POtd85r79Fj7Xfc8+Gced89XW7ZxP2bMxwc40JKmGYuSYEFjPcXGOCShhmg54QWDOF26A3E+g4w1RUVNC9e/fa99Ajox69h57LzQY9lzTXannSMFcNAY2q+zUB18eB6K2jxuZ8G2Ae0C7978Chm95L6fxHUwaaOK8Xe17ySgNz3qEDzJgBX/86jBsHQ4euuju+st4306NPqUVvPw0eDH37rv/vnDcG555N0LMJQs01AawEodo5FmcAACAASURBVOaaAFaCUHNNACtBqA16AljNGGqD3oyw0w21dOnS2k+uPfnkk1x77bV89NFHtWH/+te/OOaYY3J6djboOcW5RsyThrlqCGhU3a8xuY4CDgaqG8VHX8F8A2h4Y3vNHfQ9Kq9m25WRCW+4TZi7F/v88cUG5rxTJ6iogK22ahi7aBHMnw/RQ1SRge/cef3+znmmirhnMxHK7ri5ZsctU5a5ZiKU3XFzzY5bpiwb9EyEWua4DXoLcL/77rs54YQTmhz5nHPOqTXrRQmX5o0M+Lq2Dz74gN69e9eGzJgxgx133LEFrn79G7KyspLx0WpNQJ8+fWjTpu6Z1/XvUpv1isxVg9tcM3MtfrGYVoe0omhlw+XRazapoXJGJWyRqhFx/WpEf7apjh5fb7iNq9iXfleObWDOt966hqlTK9l008zns6FHuGc1HWCu5qohoFF1v2q4zps3r/bp3Wh799136dKli2YgqyYiYIOeCFdugpsy6Lvtthu33XYbe+65Z1YDJTH0d955Z+1CdN5MwARMwATWEthk7ib0ubAPxSvXviMeHV3RdgWjbxnN8s2Wp8W117JL2ar6tZRjo2ceQP+rRzfYv+WWX3Lzzc/Tpk3j2/OuhAmYgAmYgAk0H4FPP/2Uk08+2Qa9+ZDHGskGPRam3AZ9/vnntd8+j7bokZ3oX6+GDRtGeXl57V3tG2+8kcMOOyzxoDboiZE5wQRMwATWEOjwVgf6nd0vxZxXta7iub89R+WWlam0qqv5/leXsGX1zJRjw6cdzKHXPdNgf5cui/nLX56nVSuDNwETMAETMIGWJWCD3rL8mxrdBj2P6hK9d3788cfXPtr+j3/8g1/+8peJzs6PuCfClbNgP3aVM5QNhMzVXDUEmlCdC232bEPRV40ea29TQ+WkSkj3RlB1Na1e6E/JwpdSRB9/9Uf8+C/RKnNrt549VzJ+/HKKG96cb9bLLMTB/FugqZq5mquGgEbV/arh6kfcNVxDVW3QQwnmOP+oo46qvZvevn372ndBNttss5yN4EXicoaygZAXLjFXDQGNqvs1Ddc3gV2jR5oaHYvuck+pO9Y4rboaRu0FCyamCP77lSP56V8fbrB/v/1g9GhszrNoa/dsFtBipJhrDEhZhJhrFtBipJhrDEhZhHiRuCygNUOKDXozQE4yxAMPPMAvfvGL2pT777+fn//850nS1xlrg54zlDboGpTmaq7NQKDREO8DOwFfNtpfCkSLsfdMc0qROR+xB3wWufeG2/0TjuaYWx5osPPww+Gxx5r/0taXEf2HuaaS5mquGgIaVferhqsNuoZrqKoNeijBHOePGjWKAQMG1KpeddVVXHjhhTkbwQY9ZyhtJDUozdVcm4FAvSE+Bb4FfNFo2BJgHLB3E+b82d3g8xkNDtbUwN3jj+fEv9/dYP+xx8K99zbvZa1vo/kPc01FzdVcNQQ0qu5XDVcbdA3XUFUb9FCCOc6vv8L7X//6V373u9/lbAQb9JyhtJHUoDRXc20GAnVDfM6q98oXNhoyej88+gb6/unMeRUM7wGLKlLM+R1jTuaUf9zRYP9vfws339x8l7S+juQ/zDWVNVdz1RDQqLpfNVxt0DVcQ1Vt0EMJ5jj/0EMPZfjw4bWqY8aMoV+/fjkbwQY9ZyhtJDUozdVcm4EAsKTOnH/caLhofbgngHQf0ahaDs90g8X/TTHnQ0cN5nf3DK23v4aLLiriT39qnstZ30fxH+aaCpuruWoIaFTdrxquNugarqGqNuihBGPmR3fGf/azn9GmTZsmM2644QbOOuus2uPf+MY3iP5PU1oavQiZm80GPTccG6t40jBXDQGN6gbfr9GX0qLH2uenMefDgJ+k4R6Z86fL4Ms3Usz5jc+ewVn33dDAnP/pTyu46CJ/Ry1XHbzB92yuQDbSMVcNWHM1Vw0BjaoNuoZrqKoNeijBmPmR4V68eDFHHnkk++yzT+33zjfeeOPafTNmzKhdEG7ChAm1aq1ateLpp5/mwAMPjKkeL8wGPR6npFGejJMSixdvrvE4JY3aoLkuB7oCb6Wh9i/gmHTmvBKe2hmWvp1izq996lwu+L9rG5jz3/zmNa6/vitt27ZNWhrHN0Fgg+5ZYVeYqwauuZqrhoBG1QZdwzVU1QY9lGDM/Migv/12wz/w0qV26dKFf/7zn/Tv3z+mcvwwG/T4rJJEejJOQit+rLnGZ5UkcoPlWlX3ubS5aWjdBpySzpwvhae6wtL3Usz5nx6/iIv/vfYZ9qKiGs4881X69Jlfu9CnDXqSrlx37Abbs7lDmFbJXDWAzdVcNQQ0qjboGq6hqjbooQRj5s+bN4/Ro0fXvldeUVHBRx99xIIFC2ofed96663ZbbfdOOyww/jpT39Ku3btYqomC7NBT8YrbrQn47ikksWZazJecaM3SK7VwG5Aw4XXVyGLnk4/Iw295UvgqZ2g8oMUc37pI5dxRfmla/YXF8OwYV9RWvps7T4b9LjdGC9ug+zZeGiCosw1CF+TyeZqrhoCGlUbdA3XUFUb9FCCBZRvg64plidjc9UQ0KhucP0amfM9gclpeF4JDElnzhfVmfOPUsz5RQ9dxTVPrv38ZbRMyHPPwR57LGPkyJE26IK23eB6VsAwnaS5akCbq7lqCGhUbdA1XENVbdBDCRZQvg26pliejM1VQ0CjusH1a19gfBqWFwHpVlmvXAhPd4Wvoo+kr92i75yfc///4y/PnL1mZ6tWEC0d0qsXbHBcNe2ZVtVsNbDN1Vw1BDSq7lcNVxt0DddQVRv0UIIFlG+DrimWJw1z1RDQqG5Q/XowMCINxzOBv6TZX/npqnfOlzf8OHpkzk+/96/8beTv1iRFa8C9+iqUla3atUFx1bRmk6pmqwFuruaqIaBRdb9quNqga7iGqtqghxIsoHwbdE2xPGmYq4aARnWD6deBwGNpGEaLwUWLwjXeKj+GJ7vCis8bHInM+Sn/vI07nl+7ilyHDjBjBmy//drQDYarpi3XqWq2Gujmaq4aAhpV96uGqw26hmuoqg16KMECyrdB1xTLk4a5aghoVDeIfv0F8EAaftH++9LsX/r+qu+cr1iUYs5PuuNO7hp30pr9m20Gc+bAVls11NkguGpaMqOq2WZElFWAuWaFLWOSuWZElFWAuWaFLWOSDXpGRC0SYIPeIthbZlAbdA13TxrmqiGgUV3v+/XXwB1p2B0BPJJm/5fvwNO7QtWSBgera4o4/ta7uW/CcWv2b7MNVFTAppum6qz3XDXtGEvVbGNhShxkromRxUow11iYEgeZa2JksRJs0GNhavYgG/RmR95yA9qga9h70jBXDQGN6nrdr78H/pqGW/Qu+jNp9i95E4Z3h6ovG5rz6iKOHvogw14+as3+6HH22bOhqa9grtdcNa0YW9VsY6NKFGiuiXDFDjbX2KgSBZprIlyxg23QY6Nq1kAb9GbF3bKD2aBr+HvSMFcNAY1qwfZr9PT5e0B0o3tjoAvQsR6jaFX2q9Mwi1ZxH5tm/6L/wjPfgZXLUsz5T276N+WTj1yzf+ed4bXXIFq1vamtYLlq2iynqmabU5xrxMzVXDUENKruVw1XG3QN11BVG/RQggWUb4OuKZYnDXPVENCoFlS/1tSZ66F1C76trMekBIgWghsMTAAuTsOrN/ASUNzo2BcV8ExPqK5scGBldTE//ks5T0390Zr9u+8OEydCcWONRpIFxVXTWjJVs9WgNVdz1RDQqLpfNVxt0DVcQ1Vt0EMJFlC+DbqmWJ40zFVDQKNaMP06BYhe/56VJYcewNQ05vyzmTCiF1R/lWLOD73uKUZMP2TN/n794LnnMpvzKKFguGaJsyXTzFZD31zNVUNAo+p+1XC1QddwDVW1QQ8lWED5NuiaYnnSMFcNAY1qQfTrqLq74w1fDY8PpCswEyhtlPLZNBixJ1Qvb3CgamUJB/15BM/POmDN/h/9CB5/PP6QBcE1/uXkVaTZasphruaqIaBRdb9quNqga7iGqtqghxIsoHwbdE2xPGmYq4aARjXv+zW6c94HyNacbwu8CTR+X3zBZBj5fahZkWLO9/vT87z4ejToqu3YY+Hee5Pxz3uuyS4nr6LNVlMOczVXDQGNqvtVw9UGXcM1VNUGPZRgAeXboGuK5UnDXDUENKp53a/RO+fdAx5rj5B1XQovvwXtu8BGdavIffISjO4DNVUNoK6oKqXvlWN56b97r9n/29/CzTcnZ5/XXJNfTl5lmK2mHOZqrhoCGlX3q4arDbqGa6iqDXoowQLKt0HXFMuThrlqCGhU87pfxwD75+C6h/SDXV+ELgNhy31hyllA/RXmYHnVRuz9xwlMfmOPNQNedBH86U/ZjZ/XXLO7pLzJMltNKczVXDUENKruVw1XG3QN11BVG/RQggWUb4OuKZYnDXPVENCo5nW/DgIezsF17zkMTl/7DfPGil+taMX3Ln2JaW/3XHPoz3+G887Lfuy85pr9ZeVFptlqymCu5qohoFF1v2q42qBruIaq2qCHEiygfBt0TbE8aZirhoBGNW/7NfrOeaeUG93ZQSiugts7QbvFKfmVK1rTa8hkZs3vtubYbbfBKadkN9TqrLzlGnZZeZFttpoymKu5aghoVN2vGq426Bquoao26KEECyjfBl1TLE8a5qohoFHN236dDeyaw2u+tgw6z2kgWFMDR974MOWTj6zdX1QE998PRx8dPm7ecg2/tBZXMFtNCczVXDUENKruVw1XG3QN11BVG/RQggWUb4OuKZYnDXPVENCo5m2/TgT2zOE1X94bdpyUIjjj3W70uGA6xcVFtZ9RO+yw3IyZt1xzc3ktqmK2Gvzmaq4aAhpV96uGqw26hmuoqg16KMECyrdB1xTLk4a5aghoVPO2X5vhDvpqogdcNYaL/9aPfv1yxzhvuebuEltMyWw16M3VXDUENKruVw1XG3QN11BVG/RQggWUb4OuKZYnDXPVENCo5m2/5vId9JIVcNvmad9Bj6gOnzmIQ/40rPYR91xtecs1VxfYgjpmq4FvruaqIaBRdb9quNqga7iGqtqghxIsoHwbdE2xPGmYq4aARjWv+7WZVnGvWlnCS50Xsu/+dd9JzwHqvOaag+trSQmz1dA3V3PVENCoul81XG3QNVxDVW3QQwkWUL4NuqZYnjTMVUNAo5rX/ZrL76DvMm6dAM8cPZsb/lmWM8h5zTVnV9kyQmar4W6u5qohoFF1v2q42qBruIaq2qCHEiygfBt0TbE8aZirhoBGNa/7tQbYBEj9Olp8GF1mwDU9IMPj63td9gojJvemY45uouc11/j08jLSbDVlMVdz1RDQqLpfNVxt0DVcQ1Vt0EMJFlC+DbqmWJ40zFVDQKOa1/36a+COgOtuvQQu7gM7TM0oUnbubB4dXUZZjm6i5zXXjDTyO8BsNfUxV3PVENCoul81XG3QNVxDVW3QQwkWUL4NuqZYnjTMVUNAo5q3/XoJcEXANUfm/MyB0H10RpEVVaVsfuoCRo/tSO/eGcNjBeQt11hnn99BZqupj7maq4aARtX9quFqg67hGqpqgx5KsIDybdA1xfKkYa4aAhrVvOzXW4DT0lzvxsCSGByix9pPPT7WnfNIbdjLgzjq5mHMno3voMfA29IhedmzLQ0lB+Obaw4gppEwV3PVENCo2qBruIaq2qCHEiygfBt0TbE8GZurhoBGNe/69WEgWr298dYLmAhEa70NBcqBlfWCok+p9SqHA2+BsnEZ3zmvL9/vyjFM+G8/FizA76Br2iynqnnXszm9upYTM1cNe3M1Vw0BjaoNuoZrqKoNeijBAsq3QdcUy5OxuWoIaFTzql/HAgcA1Y2u9VvA60Bxvf0vXwcv/BMqO0CbxbDZ/Ca/c74ucjPe7UaPC6YzaFARw4bljnFecc3dZeWFktlqymCu5qohoFF1v2q42qBruIaq2qCHEiygfBt0TbE8aZirhoBGNW/6dTqwO1DV6Dq3Ad4E2tTbP/2PMPOyYCBLKtvT54rxTH2rJ2PGQL9+wZJrBPKGa+4uKW+UzFZTCnM1Vw0Bjar7VcPVBl3DNVTVBj2UYAHl26BriuVJw1w1BDSqedGv7wA7A8saXWP0ibU3gE71zfklMDN19bjqmiKKi6LvssXbInM+8IZyRs/sT7duMH06FGX4FFs85VVRecE1yQkXUKzZaoplruaqIaBRdb9quNqga7iGqtqghxIsoHwbdE2xPGmYq4aARrXF+/Vz4BvAF42uL7pjHj3W/vV6+6ddBLOvTgHx5ifb87ObH+Qfv/oV3bablRFU9Fj78bfdU3vnvH17GD8eevbMmJYooMW5Jjrbwgo2W029zNVcNQQ0qu5XDVcbdA3XUFUb9FCCBZRvg64plicNc9UQ0Ki2aL9WAjsAHza6tlLgVaBHvf1Tz4OK61IgzPvom+x8TgVV1a2AGvqWjeO0/kMZ2Kuc0pK1q8hFn1IrnzyQW0YPZlxFX6JV5CJzXl4O/fvnnm2Lcs395eSVotlqymGu5qohoFF1v2q42qBruIaq2qCHEiygfBt0TbE8aZirhoBGtcX6NVoILnqs/b+NritaCG4UsH+9/VPOgjk3pAD474ffYpdzZ9WZczj2WJgyBWbNgg5tF9F5s/l0aLOYxZUdmP9ZZxYv67hGI3qs/Z57cn/nfPUALcZV0yZ5pWq2mnKYq7lqCGhU3a8arjboGq6hqjbooQQLKN8GXVMsTxrmqiGgUW2xft2z7rNpjS/rIeCn9XZOPh3m3pxy8XPe78qu58+kujq63Q6XXQaXXgo1NTBuHAwduuru+Mp6n2IrLYWBA2HwYOjbN7fvnDc+wRbjqmmTvFI1W005zNVcNQQ0qu5XDVcbdA3XUFUb9FCCBZRvg64plicNc9UQ0Ki2SL8eBjyd5noiH/7bevsnDob/3ZoSOOu9MnpcOH2NOb/2Wjj33FS9RYtg/nxYvBg6dIDOnXP3nfNM1WgRrplOaj05braaQpqruWoIaFTdrxquNugarqGqNuihBAso3wZdUyxPGuaqIaBRbfZ+PRn4R5pr+QNQf3H2V34N8+5ICZz+Tne+c+G0NR9Fv+UW+M1vNGxCVJuda8jJFliu2WoKZq7mqiGgUXW/arjaoGu4hqraoIcSLKB8G3RNsTxpmKuGgEa1Wft1CHBVmuuITHt9L/7yifDGXSmBU9/6Dj2HTKk159En0e69F445RsMlVLVZuYaebIHlm62mYOZqrhoCGlX3q4arDbqGa6iqDXoowQLKt0HXFMuThrlqCGhUm61fo8fXT09zDdHj7k/W2/+f4+Ctf6UEvvpmT3r9YVKtOS8uhmHD4MgjNUxyodpsXHNxsgWmYbaagpmruWoIaFTdrxquNugarqGqNuihBAso3wZdUyxPGuaqIaBRbZZ+HQYcleb8ewOv1Ns/4efw9oMpga/M24PvXfJyrTkvKYGnn4aDDtLwyJVqs3DN1ckWmI7ZagpmruaqIaBRdb9quNqga7iGqtqghxIsoHwbdE2xPGmYq4aARlXer88D0XfGo8+q1d++DcxZ8yo5vPhTeOffKRc5Ye5e7PPHF2sDo1XYx4yBffbRsMilqpxrLk+2wLTMVlMwczVXDQGNqvtVw9UGXcM1VNUGPZRgAeXboGuK5UnDXDUENKrSfo3WctsDqGp07l8D3gDa1O0ffwS8V55ygS/M2Yc+V4yrNeetWsGECdCrl4ZDrlWlXHN9sgWmZ7aagpmruWoIaFTdrxquNugarqGqNuihBAso3wZdUyxPGuaqIaBRlfXr28DOQGWj894EeAvYtG7/uMNh/hMpFzdmdj/2/9OY2v1t2sCkSdCtm4aBQlXGVXGyBaZptpqCmau5aghoVN2vGq426Bquoao26KEECyjfBl1TLE8a5qohoFGV9OtCYAdgUaNzblv3WPvX6/aPPRTeH55yYaNnHkD/q0fX7m/fHl57DXbcUXP9KlUJV9XJFpiu2WoKZq7mqiGgUXW/arjaoGu4hqraoIcSLKB8G3RNsTxpmKuGgEY15/0a3TH/BvBRo/PdCIi+kLb6LvjzB8GHI1Mu6tnpAzjkzyNq93fsCLNmQZcummtXquacq/JkC0zbbDUFM1dz1RDQqLpfNVxt0DVcQ1Vt0EMJFlC+DbqmWJ40zFVDQKOa036N3jWPHmuf1+hci4HoafU+dftHHwAfR6vHNdyemvoDfvj/nq7d2akTVFTAVltprlutmlOu6pMtMH2z1RTMXM1VQ0Cj6n7VcLVB13ANVbVBDyVYQPk26JpiedIwVw0BjWpO+zVaEG5ymvOMFmf/SbSSezU8tz98Ei381nB7bPLhDLzhsdqdkSl//XXYdPV76ppLl6rmlKv0TAtP3Gw1NTNXc9UQ0Ki6XzVcbdA1XENVbdBDCRZQvg26plieNMxVQ0CjmrN+/QHwTJpzHAoMrjPno/vCp9En0xpuD088gkE3PVK7M3qcPTLn7dpprre5VHPGtblOuIDGMVtNsczVXDUENKruVw1XG3QN11BVG/RQggWUb4OuKZYnDXPVENCo5qRfTwDuTnN+lwKX1ZnzUXvDgpdTgh56eRA/u3lY7f5vfnPVO+fRqu2FvuWEa6FDEJ2/2WrAmqu5aghoVN2vGq426Bquoao26KEECyjfBl1TLE8a5qohoFEN7tcLgWvSnNspwG115nzk92DhpJSg+178Ocfeen/t/l12WbVae2mp5jqbWzWYa3OfcAGNZ7aaYpmruWoIaFTdrxquNugarqGqNuihBAso3wZdUyxPGuaqIaBRDerXG4Ez05zX4UD0Onn0zvmIPeCzaPn2tVtNDdz7wnH88vZ7anfuvjtMnAjF0WJy68kWxHU9YaC6DLPVkDVXc9UQ0Ki6XzVcbdA1XENVbdBDCRZQvg26plieNMxVQ0CjmnW/Pgj8PM057QX8p86cP9sTPn8txZz/c9wJnHzHP2v39+kDY8asX+Y8uq6suWrKvF6pmq2mnOZqrhoCGlX3q4arDbqGa6iqDXoowQLKt0HXFMuThrlqCGhUs+rXUcBBQE2jc+oKzI72VcEz34UvZqaY89ufP4Xf/DN69h0OPhieSbewnOZSm1U1K67NeoaFO5jZampnruaqIaBRdb9quNqga7iGqtqghxIsoHwbdE2xPGmYq4aARjVxv0ZPq++5yoM32L4GvAG0qoLhPWBRRYo5HzpqML+7J1rWHX7yE/h39Pm19XRLzHU95aC4LLNVUPVTHxqq5mquKgIaXRt0DddQVRv0UIIFlG+DrimW/3g0Vw0BjWqifn0TKAO+anQu0ffKo2Mdq+DpbrD49RRzftOI0znzXzfV7v/lL+GuuzTXky+qibjmy0kXyHmYraZQ5mquGgIaVferhqsNuoZrqKoNeijBAsq3QdcUy5OGuWoIaFRj9+un0XfQgMWNzqMtMBfYZjkM3xWW/C/FnF8//CzOfeD62v2//S3cfLPmWvJJNTbXfDrpAjkXs9UUylzNVUNAo+p+1XC1QddwDVW1QQ8lWED5NuiaYnnSMFcNAY1qrH5dCuwAfNzoHDYCpgJdl8PTZfBl9Iz72i1arf3PT57HhQ/9uXbnBRfA1VdrriPfVGNxzbeTLpDzMVtNoczVXDUENKruVw1XG3QN11BVG/RQggWUb4OuKZYnDXPVENCoZuzX6F3zaPG3ht4bok+ijQO+VwlP7QxL304x51c9cSF/GHZV7f4rr4QhQzTXkI+qGbnm40kXyDmZraZQ5mquGgIaVferhqsNuoZrqKoNeijBAsq3QdcUy5OGuWoIaFTX2a/VwB5Aw8+YQxHwCPDDyJzvBEvfTTHnl5dfzGWPXF67/8Yb4fe/15x/vqr6d0BXGbPVsDVXc9UQ0Ki6XzVcbdA1XENVbdBDCRZQvg26plieNMxVQ0Cjus5+jT6lNjLNuNFX0k5aCk/uBMvmp5jzSx7+I1c+dglFRfD3v8PJJ2vOPZ9V/Tugq47Zatiaq7lqCGhU3a8arjboGq6hqjbooQQLKN8GXVMsTxrmqiGgUW2yX48D/pVmzMuAC5esunNe+UGKOR8y7EqufmJIrTm//344+mjNeee7qn8HdBUyWw1bczVXDQGNqvtVw9UGXcM1VNUGPZRgAeXboGuK5UnDXDUENKpp+/U84Lo04/0mel59ETzVFSo/TDHn5z/4Z657+jyKi6G8HH70I805F4Kqfwd0VTJbDVtzNVcNAY2q+1XD1QZdwzVU1QY9lGAB5duga4rlScNcNQRyqLoIeA9YApWllTz3+nNUtatiwIABtL21LZydZqyBwP99Dk92ha8aLucerdZ+1v3Xc+MzZ1FSAiNGwAEH5PB8C1DKvwO6opmthq25mquGgEbV/arhaoOu4RqqaoMeSrCA8m3QNcXypGGuGgKBqjXAWGAo8Biwcq1edXE1H3zvA7bce0taXdcqdaC9gecjc/5t+Cr6IPraLTLnp9/7V/428neUlsLYsbB3FL+Bb/4d0DWA2WrYmqu5aghoVN2vGq426Bquoao26KEECyjfBl1TLE8a5qohEKAarcIevVM+KwuNMmDyQhi+EyxfkGLOT7trKLc+N5hWreCll6BnzyzGWA9T/DugK6rZatiaq7lqCGhU3a8arjboGq6hqjbooQQT5E+ZMoVnn32WF154gZkzZ/Lxxx+z0UYbse222/L973+fk046iX333TeBYrJQG/RkvOJGe9KISypZnLkm47UmehQQPZ7+ZfL8mi0WUPTyCzDlBFjxeYo5//Wdt3Pn2F/Tti28+iqURWbeWy0B96uuEcxWw9ZczVVDQKPqftVwtUHXcA1VtUEPJRgzv2/fvowfPz5j9LHHHsudd95Jq+j2VI43G/QcA62T86RhrhoCWahGd877ZGfOoQb+sC+UTUgZOHqs/aQ77uSucSfRvj3MmAE77JDF+a3HKf4d0BXXbDVszdVcNQQ0qu5XDVcbdA3XUFUb84Vc8gAAIABJREFU9FCCMfO/9a1vMW/evNq75YMGDaq9U/71r3+dlStX8tJLL3H99dczf/6q7wsfffTRPPDAAzGV44fZoMdnlSTSk0YSWvFjzTU+q9rI6J3z7lk+1r56qC4z4JoeULR27OqaIk64/S7ufeF4NtkEZs+GbbdNeG4bQLj7VVdks9WwNVdz1RDQqLpfNVxt0DVcQ1Vt0EMJxsw/7LDDOO644zjyyCMpiZY9brR9+umn7L333sydO7f2SHS3PdePu9ugxyxWwjBPGgmBxQw315igVoeNAfZPmJMufEg/2GXcKs9fA0OGXcHVT/yBzTeHOXNgiy1yMMZ6KOF+1RXVbDVszdVcNQQ0qu5XDVcbdA3XUFUb9FCCOcx/6qmn+OEPf1irePrpp3PTTTflUB1s0HOKc42YJw1z1RBIqDoIeDhhTrrwPYfB6UetOTLj3W7s//+mM29eER075kB/PZXw74CusGarYWuu5qohoFF1v2q42qBruIaq2qCHEsxh/pIlS+jQoUOt4qGHHkpk2HO52aDnkuZaLU8a5qohkEA1+s55p4afUkuQ3TC0uApu7wTtFq/Z/8t/jeGu4f0oqvfoe9b662mifwd0hTVbDVtzNVcNAY2q+1XD1QZdwzVU1QY9lGAO8xcuXMjm0XOkUHsn/Yknnsihuu+g5xRmPTFPGhqy5pqA62xg1wTxmUKvLYPOc9ZEDXt5EFsdMYx+/TIlbrjH3a+62puthq25mquGgEbV/arhaoOu4RqqaoMeSjCH+eXl5RxxxBG1iueeey7XXnttDtVt0HMK0wZdhXONrifjBIgnAnsmiM8Uenlv2HHSmqiqlSWc9MxC7nnAz7g3hc79mqmpsj9uttmzW1emuZqrhoBG1f2q4WqDruEaqmqDHkowR/nV1dXstddeTJwY/aUNkyZNolevXonUo0fY17V98MEH9O7duzZkxowZ7Ljjjon0HZyeQGVl5ZpP6PXp04c2bdoYVQ4ImGt8iEUVRbTZPYd91+gOenQm3S6YxXOTdvB76E2Uxf0av1+TRpptUmLx4s01HqekUeaalFi8eHONxylpVPSFqe7do0/AwLvvvkuXLl2SSjheQMAGXQA1G8noM2vnnHNOberAgQN59NFHE8sUJXhBNPrW+hZejjkxYyeYQD4SKF1ayiHHHEJxdXH46ZWsgNs2b/AOeiTa++JXOO7MxWy33ZLwMaxgAiZgAiZgAibQ4gSir0idfPLJNugtXomGJ2CDngcFGTduHAceeCBVVVVstdVWTJ8+na233jrxmdmgJ0bmBBNYbwj0urYXnf/TOfx6Gq3ivlqw7NzZnHjGx+y00+fhY1jBBEzABEzABEygxQnYoLd4CdKegA16C9dl1qxZtd87/+yzz2jdujUjRoygb9++WZ2VH3HPCltwkh+7CkaYVsBcE3CthlZ7taJkRkmCpCZC630HfXXEiqpSNj91AeMmtGLnnWvCx1gPFdyvuqKarYatuZqrhoBG1f2q4epH3DVcQ1Vt0EMJBuS/+eab7LPPPrz//vuUlJTw73//u/bxdtXmz6xpyHrhEnPVEIipGj1x/h3gjZjx6wrrMgOu6QGNPqcWreL+i1uHsWABfge9CX7+HchB/5mtDmIaZfesBre5mquGgEbVi8RpuIaq2qCHEswyPzLl0Z3zN954g+jR9LvvvpvjjjsuS7V4aTbo8TgljfJknJRYvHhzjcFpHhCtJZmLp85bL4GL+8AOU1MG7nflGLbq1o9hw2Kc0wYa4n7VFd5sNWzN1Vw1BDSq7lcNVxt0DddQVRv0UIJZ5Efve0SPsc+eHX28GP72t79x2mmnZaGULMUGPRmvuNGeNOKSShZnrhl4PQ8cAixPExc96b4yAe/InJ85ELqPTkma8W43elwwnTFjivwd9HUgdb8m6LeEoWabEFjMcHONCSphmLkmBBYz3FxjgkoYZoOeEFgzhdugNxPo1cN88cUX7L///kyZMqV21zXXXMP555/fLGdhg67B7EnDXDUE1qH6d+BUIN3r4H8A9quA46vhvV0zn1r0WPupx6e9c76ksj19rhjPio17Mn06JPhQROZx17MI/w7oCmq2Grbmaq4aAhpV96uGqw26hmuoqg16KMEE+UuXLmXAgAFMmDChNmvIkCFceeWVCRTCQm3Qw/g1le1Jw1w1BJpQPRO4Mc2x6Atr9wIHT4aR34fqFVDRF0adBpMHQnXp2qToU2q9yuHAW6BsXMo751FgZM4H3lDOS2/2Z/x46NmzWa+y4Abz74CuZGarYWuu5qohoFF1v2q42qBruIaq2qCHEoyZv3z5cn74wx8ycuTI2ozf//733Hhjur+yYwpmEWaDngW0GCmeNGJAyiLEXBtBqwZ+AIxIA7MNMBb41iQYuTfUrGgQtHxxJ4bcdhen7v0AO27/Gmw2P+U75/UTosfaj7/tHuZ+0pPycujfP4sCbmAp7lddwc1Ww9ZczVVDQKPqftVwtUHXcA1VtUEPJRgz/8gjj+TRRx+tjY4ecY/M+bq+W96qVSt22mmnmOrxwmzQ43FKGuVJIymxePHmWo/TUiC6g/16GnZbANG6bm1egVH7QE1VQ3NetRF7XvIy097uyQUX1PDBtDEcutOtDOxVTmnJ2hfVo0+plU8eyC2jBzOuoi/duhVxzz2+cx6vW8H9GpdU8jizTc4sToa5xqGUPMZckzOLk2GucSglj7FBT86sOTJs0JuDMtG7m42+W5Rh3O2335633norp2dng55TnGvEPGmYq4ZAneo7wHeBhWlGKQOi5SwWT4DR/VLM+VcrWtH7kleY8e5u/OMfcMIJsHTpMv7yl1cZN3oLPnijmnYbLWFxZQfmf9aZZSs6En3pcfBg6NvX75wnqat/B5LQShZrtsl4xY0217ikksWZazJecaPNNS6pZHE26Ml4NVe0DXozkbZBbybQLTCMJw0NdHMFouUqDgC+SsP4UOAJ4NMX4bn90przXhdPYtZ7PXjwQTjqqFUa9bl+73sDWLiwLYsXQ4cO0Lmzv3OebTe7X7MllznPbDMzyibCXLOhljnHXDMzyibCXLOhljnHBj0zo5aIsEFvCeotNKbvoGvAe9IwVwmBaMG3E4Do3fPG2znAdcBH4+H5/aGm4TfVKle0pteQyVR80I2HH6b2rvjqzf0qqZYfcddgTflHpWih1bZt2wpH23Ck/VugqbW5mquGgEbVBl3DNVTVBj2UYAHl26BriuXJ2FxzTuAi4Oo0qtGbMncAJ0XmfCw8f2Bac95zyKu8/sGuPPUUHBJ9K73e5n7NebVsIjVI/Y9K5iomoJH3b6y5aghoVG3QNVxDVW3QQwkWUL4NuqZYnozNNWcEorvlRwKPpVFsBYwC+gAfPg9jBqSY82XL2/Ddi6bwv4/LGD0a+vVL1XG/5qxa/ocPDcoUVfesBrS5mquGgEbV/arhaoOu4RqqaoMeSrCA8m3QNcXypGGuOSFQCfQGZqRR2wx4FdghMufPwZiD0prz71wwjTcXdGXsWNh77/Rn5X7NSbVsIjUY06q6ZzWwzdVcNQQ0qu5XDVcbdA3XUFUb9FCCBZRvg64plicNcw0m8CHwHeDjNErfqvuM2sbA+6Ng7MEpL6Yv/aotPS58jXc/+zYTJkCvXk2fkfs1uFo2kRqETaq6ZzXAzdVcNQQ0qu5XDVcbdA3XUFUb9FCCBZRvg64plicNcw0iMLnusfVlaVQOBEYAxZE5fwbGHtakOX/v828zeTJ067bus3G/BlXLJlKDb52q7lkNdHM1Vw0Bjar7VcPVBl3DNVTVBj2UYAHl26BriuVJw1yzJjAMOLqJldp/C9xcpzx/OIz7YUrgl1+1o/v50/lwyY5MnQpdu2Y+E/drZkbZRJhrNtTi5ZhtPE5Jo8w1KbF48eYaj1PSKHNNSixevA16PE7NHWWD3tzEW3A8G3QNfE8a5poVgT8Cl6XJjFZq/xswuO7Ye0/B+MNTzXllO3Y9fyafLtuBGTNgh+j99Bib+zUGpCxCzDULaDFTzDYmqIRh5poQWMxwc40JKmGYuSYEFjPcBj0mqGYOs0FvZuAtOZwNuoa+Jw1zTUwgumv+f2myNgKeBvqvNudPwPgfAzUNgpdUtmfX82bx+YrtmTULunSJfwbu1/iskkSaaxJayWLNNhmvuNHmGpdUsjhzTcYrbrS5xiWVLM4GPRmv5oq2QW8u0nkwjg26pgieNMw1NoEq4Ht1K7I3TuoIRO+jf7vuwLvl8EL0zbWG5nxxZXt2OXc2X9Z8nTlzYKutYo9eG+h+TcYrbrS5xiWVPM5skzOLk2GucSgljzHX5MziZJhrHErJY2zQkzNrjgwb9OagnCdj2KBrCuFJw1xjEfgU6AF8kCZ6e2A6EJn0aHvnEXhxUIo5X7RsY8rOrWB5SRdefx06dYo1coMg92tyZnEyzDUOpexizDY7bpmyzDUToeyOm2t23DJlmWsmQtkdt0HPjps6ywZdTTiP9G3QNcXwpGGuGQlE5vv7wJdpIvcFxtat1B4dfnsYTPhZGnPegbJzZ1PdepU577jazGccvGGA+zUhsJjh5hoTVBZhZpsFtBgp5hoDUhYh5poFtBgp5hoDUhYhNuhZQGuGFBv0ZoCcL0PYoGsq4UnDXNdJ4HEgelJ9ZZqok4A76+1/+yGYEL2g3vCx9i+WdmTncyso3XjbWnPerl32zN2v2bNbV6a5arhGqmarYWuu5qohoFF1v2q42qBruIaq2qCHEiygfBt0TbE8aZhrkwSuA85LczRaqT06dna9Y2/eDy8dm9ac73T267TrtA0VFdCmTRhv92sYv6ayzVXD1QbdXHUENMr+LTBXDQGNqg26hmuoqg16KMECyrdB1xTLk7G5piVwAnB3miOlQDlwWH1zfh+8dFyKOf/8y03oes4cNtl6G2bOhFatwlm7X8MZplMwVw1XG3Rz1RHQKPu3wFw1BDSqNugarqGqNuihBAso3wZdUyxPxubagEC0Unsf4KU0XNoDrwC71jv2xj3wcuTmGz7W/tmSTdnpnNfZ+utbMW0alEbGPgeb+zUHENNImKuGqw26ueoIaJT9W2CuGgIaVRt0DddQVRv0UIIFlG+DrimWJ2NzXUPg87qV2t9Nw6Rz3Urt9Vden3cXvHJiSvDCJZvx7bPn8o2dtmDSJCguzh1j92vuWNZXMlcNVxt0c9UR0Cj7t8BcNQQ0qjboGq6hqjbooQQLKN8GXVMsT8bmWkugAtgTWJyGR29gAlD/Lvj/7oSJv0oJXrC4U+2d867dt+DFF3Nrzm12NL1qrjquZqtj67lLw9ZczVVDQKNqg67hGqpqgx5KsIDybdA1xfJkbK48A/wIiB5vb7z9Ariv0c7//p2aSacQrRVXf/t08eZ8+6y59PxeJ0aNyr05t9nR9Kq56riarY6t5y4NW3M1Vw0BjaoNuoZrqKoNeijBAsq3QdcUy5PxBs71ZuD3Ka+Qr4JyJTCksTm/lZpJg1PM+SeLtuBbZ/+XvftuyvDhGqY2O+aqI6BT9m+shq25mquGgEbV/arhaoOu4RqqaoMeSrCA8m3QNcXypLEBcx0M3Jrm+kuAh+q+f17/8NxbqJl8Woo5//iLLfn2OXM58OBNeeQRDc/Vqu5XDV9z1XD1PyqZq46ARtm/BeaqIaBRtUHXcA1VtUEPJVhA+TbommJ5Mt4AuVYDBwJj0lx7W+BFoGejY6/fTM2rp6eY84++2IpvnfVffnRER+6/X8Oyvqr7VcPYXDVcbdDNVUdAo+zfAnPVENCo2qBruIaq2qCHEiygfBt0TbE8GW9gXJcA3wHeSHPdW9et1L5Vo2NzbqJmyhkp5vzDz7euXa39Z8d05I47NBwbq7pfNZzNVcPVBt1cdQQ0yv4tMFcNAY2qDbqGa6iqDXoowQLKt0HXFMuT8QbE9c26O+PR59Qab5Fpnwi0anSg4i/UTD07xZx/8Nk2tXfOT/z1xtwcvcfeTJv7VQPaXDVcbdDNVUdAo+zfAnPVENCo2qBruIaq2qCHEiygfBt0TbE8GW8gXMcCBwHL01zvEUC6d8dnX0fNtPNSzPn8z77GTmfN5bTfb8y112r4NaXqftXwNlcNVxt0c9UR0Cj7t8BcNQQ0qjboGq6hqjbooQQLKN8GXVMsT8YbANe/A6c2sVL7H4Ar0jCYfS01085PMefvLexc+1j7uee34/LLNezWpep+1TA3Vw1XG3Rz1RHQKPu3wFw1BDSqNugarqGqNuihBAso3wZdUyxPxus517OAG9JcYzFwLxB957zxNutqal67KMWcv7ugCzud8zqXXNaOCy/UcMuk6n7NRCi74+aaHbc4WWYbh1LyGHNNzixOhrnGoZQ8xlyTM4uTYYMeh1Lzx9igNz/zFhvRBl2D3pNGgXJdBLwHRIu+bQx0ATrWu5ZopfZDgWfTXF8bIHrkfc80x2ZcSc2Mi1PM+dufbsdOZ8/lz9e14YwzNMziqLpf41BKHmOuyZnFzTDbuKSSxZlrMl5xo801LqlkceaajFfcaBv0uKSaN84GvXl5t+hoNuga/J40CohrTZ2xHgo8Bqysd+7Rt8sHAtG3zXsDvYA5aa5tc2BanaFvfHj6H6mZeVmKOX/rk+3pes4c/vq3NpxyioZXXFX3a1xSyeLMNRmvJNFmm4RW/Fhzjc8qSaS5JqEVP9Zc47NKEmmDnoRW88XaoDcf6xYfyQZdUwJPGgXCdQpwHDArxvlGZr2+eV+dUgZEOtEd9BRzfgk1M69IMedvfvwNys6r4O93tuG4aPwW3tyvmgKYq4ZrpGq2Grbmaq4aAhpV96uGqw26hmuoqg16KMECyrdB1xTLk0YBcB1Vd3f8y4BzjR53fwKI3j1vvL12MTWzrkwx5/M++iZl51bwr/tbcdRRAWPnMNX9mkOY9aTMVcPVBt1cdQQ0yv4tMFcNAY2qDbqGa6iqDXoowQLKt0HXFMuTcZ5zje549wFCzPk5wHVNXOe0i6iZfXWKOf/fhzuy6/mzGfZwKw4/XMMoG1X3azbUMueYa2ZG2UaYbbbk1p1nruaqIaBRdb9quNqga7iGqtqghxIsoHwbdE2xPGnkMdfonfPuMR9rb+oyvrYCXpsKrTaGdl1go3oryU09n5qKa1PM+dwPvk33C2byxFOtOCj6dnoebe5XTTHMVcM1UjVbDVtzNVcNAY2q+1XD1QZdwzVU1QY9lGAB5duga4rlSSOPuY4B9s/B+Q3pB7uMo6aohKIuA2GnwfDe09S8fn2KOX/9/Z3oftEsRo4spV+/HIydYwn3a46B1smZq4arDbq56gholP1bYK4aAhpVG3QN11BVG/RQggWUb4OuKZYn4zzmOgh4OAfnt+cwOL3hS+TRzfmiRtIV83dmtz/MYOzYUvbaKwfjCiTcrwKovsurgep//DBXKQGNuH9jzVVDQKNqg67hGqpqgx5KsIDybdA1xfJknKdco++cd2piNfakp1xcBbd3gnaLm8yc9V4ZvS6dzoQJpfTsmXSA5ot3v2pYm6uGa6Rqthq25mquGgIaVferhqsNuoZrqKoNeijBAsq3QdcUy5NGnnKdDeyaw3O7tgw6p/swOvzvw2/ynYtfZ+LEUnbN5Zg5PP3VUu5XAVSbSA3UOlX3rAavuZqrhoBG1f2q4WqDruEaqmqDHkqwgPJt0DXF8qSRp1wnAnvm8Nwu7w07TkorOPO9brT+8XS+vVPjh95zOH6OpNyvOQLZSMZcNVwjVbPVsDVXc9UQ0Ki6XzVcbdA1XENVbdBDCRZQvg26plieNPKUazPeQY8I1Ow/hqJt8nBVOBtJTYOaa7NwtUHXYfbcpWFrruaqIaBRtUHXcA1VtUEPJVhA+TbommJ5Ms5Trrl8B71kBdy2+TrfQf+4zSC2OmKYBkYOVd2vOYRZT8pcNVxt0M1VR0Cj7N8Cc9UQ0KjaoGu4hqraoIcSLKB8G3RNsTwZ5zHXHwOP5+D80qzi3lh1ZXUJJUctbPid9BwMnWsJ92uuia7SM1cNV7M1Vx0BjbJ/C8xVQ0CjaoOu4RqqaoMeSrCA8m3QNcXyZJynXGcBvYDKHJxf3XfQMykt6TubjTuXZQpr0ePuVw1+c9VwtUE3Vx0BjbJ/C8xVQ0CjaoOu4RqqaoMeSrCA8m3QNcXyZJyHXMuBnwJVOTi3LjPgmh6pHz1PI/3mTq+wQ6/eORhUJ+F+1bA1Vw1XG3Rz1RHQKPu3wFw1BDSqNugarqGqNuihBAso3wZdUyxPxnnG9Urg4hydU+slcHEf2GFqLMHpX59Nj318Bz0WrPUsyL8DuoKarYatuZqrhoBG1f2q4WqDruEaqmqDHkqwgPJt0DXF8qSRR1wHAQ+nOZ9ioFXCx90jc37mQOg+OtYFrqgq5Y2eC+jarWOs+JYKcr9qyJurhmukarYatuZqrhoCGlX3q4arDbqGa6iqDXoowQLKt0HXFMuTRh5wjd4zj54sn5HmXDYGXgKWA8cB0bvpmbbosfZTj4995zyS+/fEQRx0+TA65rc/t9nJVPssj/t3IEtwMdLMNgakLELMNQtoMVLMNQakLELMNQtoMVJs0GNAaoEQG/QWgN5SQ9qga8h70mhhru8APYEFac7j60D0dHqnumM1wDhgKBC9p76yXk70KbVe5XDgLVA2LtY75/VHvOzFMVx2i7+DrumG/Ff174CuRmarYWuu5qohoFF1v2q42qBruIaq2qCHEiygfBt0TbE8abQg1/HAAOCrNOfQF3geiB5vT7dF30mfDwsev4jNS8phs/nr/M75uq5yxrvdWNB7Ov32K9LAyKGq+zWHMOtJmauGa6Rqthq25mquGgIaVferhqsNuoZrqKoNeijBAsq3QdcUy5NGC3G9HfgNEN0Vb7wNrrtLnunUXvwpvPPvTFHrPL6ksj0nPjCeh0b1pCj//bnNTlC1m07274AIrA26DKx7VoPWXM1VQ0CjaoOu4RqqaoMeSrCA8m3QNcXyZNwCXCMDfmuacSODHO0/JcY5vTAI3k23olyM3LqQyJwffWs5f7y9Pz2jx+wLYHO/aopkrhqukarZatiaq7lqCGhU3a8arjboGq6hqjbooQQLKN8GXVMsTxrNyLUa2A+IHm1vvLUGogXX94lxPi8cCe8+mhI48X970K71Urptl3klueix9lPvuYfLbupJ//4xxsyTEPerphDmquFqg26uOgIaZf8WmKuGgEbVBl3DNVTVBj2UYAHl26BriuXJuJm4LmsLuwHvphlvi7rF4LrEOJfxR8B70QpxDbfRMw/gvGdHs3x5DVtUj+O0/kMZ2Kuc0pK1K8lFn1IrnzyQW0YPZkFJX+65p6hg7pyvvlr3a4weySLEXLOAFjPFbGOCShhmrgmBxQw315igEoaZa0JgMcNt0GOCauYwG/RmBt6Sw9mga+h70mgGrl8bQNv928KXacbqAbwCtIlxHuN+DPMfTwkcMb0/104ayXPPQU0NjBsHQ4fC6GcWsc0m8+nQZjGLKzvw0aLOHHhIRwYPhr59KYh3zhtfrPs1Rp9kEWKuWUCLmWK2MUElDDPXhMBihptrTFAJw8w1IbCY4TboMUE1c5gNejMDb8nhbNA19D1paLl+7T9fY4/r96BoZZoV2AYBw2KOP+5wmP9ESvCz0wdw47QRPPtsqs6iRTB/PixeDB06QOfO5P13zjPRcL9mIpTdcXPNjlucLLONQyl5jLkmZxYnw1zjUEoeY67JmcXJsEGPQ6n5Y2zQm595i41og65B70lDx/XtE96m60NdKSKNOb8SGBJv7OqxP6T4/adSgodPO5hbK57hySfj6awPUe5XTRXNVcM1UjVbDVtzNVcNAY2q+1XD1QZdwzVU1QY9lGAB5duga4rlSUPAtRqqBlZR8kRJqjkvBaLF1w+PN2712MMofv/plOCnpx3CP+cN55FH4umsL1HuV00lzVXD1QbdXHUENMr+LTBXDQGNqg26hmuoqg16KMECyrdB1xTLk3GOuS4F9gBmp9HtUPe+eVm8MavH/IDiD55JCX5q6g+4/72nefDBeDrrU5T7VVNNc9VwtUE3Vx0BjbJ/C8xVQ0CjaoOu4RqqaoMeSrCA8m3QNcXyZJxDrm8D0ffEF6bR3AGYAmwab7zqMYdQ/EHqi+VPvHoYD3/yJPfeG09nfYtyv2oqaq4arjbo5qojoFH2b4G5aghoVG3QNVxDVW3QQwkWUL4NuqZYnoxzxPV54BBgeareyr4rKXm+BIrjjVX93EEUfzQyJfjxV3/Ek188zp13xtNZH6Pcr5qqmquGqw26ueoIaJT9W2CuGgIaVRt0DddQVRv0UIIFlG+DrimWJ+MccL0F+C1Q01CrhhreOOwNth22LW3bto01UPXoARR/PCol9rHJhzNi2WPcemssmfU2yP2qKa25arjaoJurjoBG2b8F5qohoFG1QddwDVW1QQ8lWED5NuiaYnkyDuT6a+COVI2a4hqmDZ7GOwe+w4ABA2IZ9JWj+1Py8egUsfJJP2ZsdTk33RR4rutBuvtVU0Rz1XC1QTdXHQGNsn8LzFVDQKNqg67hGqpqgx5KsIDybdA1xfJknCXXKqAfMCFNfhuofLqSEYtH1B6MY9BXjjyAkk+j5+Qbbg9PPIJXNnqE667L8jzXszT3q6ag5qrhaoNurjoCGmX/FpirhoBG1QZdwzVU1QY9lGAB5duga4rlyTgLrp8CuwHz0+RuBUyFZZstY+TIVe+RZzLoVSP3p/TTMSli/37lSKa2f5irrsriHNfTFPerprDmquFqg26uOgIaZf8WmKuGgEbVBl3DNVTVBj2UYAHl26BriuXJOCHXacDeQPQ5tcZbtIL7S0AriMt15bP9KFk4LkXqoZcHMWvTYVx+ecLzW8/D43JdzzHk/PLMNedI1wiarYatuZqrhoBG1f2q4WqDruEaqmqDHkqwgPJt0DXF8qSRgOtDwC+AlWlyjgYeWLs/DteqZ/tRmsa8SfQNAAAgAElEQVSc/99LRzFvm/9jyJAE57aBhMbhuoGgyOllmmtOcTYQM1sNW3M1Vw0Bjar7VcPVBl3DNVTVBj2UYIL8jz/+mIkTJ9b+N2nSpNr/FixYUKtw/PHHc/fddydQSx5qg56cWZwMTxpxKAGRWW7qUfM/A+c11Fkn1+pqqkbsR+ln41MGf/A/P+O97R/k3HNjntcGFuZ+1RTcXDVcI1Wz1bA1V3PVENCoul81XG3QNVxDVW3QQwkmyC8qKmoy2gY9Acg8C/WkkaEg1cDhwFNp4kqBx4EfpB5rkmt1NStG9GWjz15MSbp/wtF88u0HOOOMPGuSPDod96umGOaq4WqDbq46Ahpl/xaYq4aARtUGXcM1VNUGPZRggvz6Bn277bajrKxszSJYNugJQOZZqCfjdRQkes98d2BOmpiOwESga/r8tFyrq1n+TB9afZG69Pu/XvgFi7vfx+DBedYgeXY67ldNQcxVw9UG3Vx1BDTK/i0wVw0BjaoNuoZrqKoNeijBBPmXXnope+yxR+1/W2+9NW+99RY77LBDrYINegKQeRbqybiJgrxZZ84/S3N8R2AKEJn0JrYUrq1bs3z4PrRaFK0i13C794Vjqfzuvfw6+qa6t3UScL9qGsRcNVxt0M1VR0Cj7N8Cc9UQ0KjaoGu4hqraoIcSDMi3QQ+Al0epnozTFOM54BBgRZpjA4BngOJ1F7EB1wMPpPj5A2m9+OWUpHte+P/snQm4lVP7xp/TadacShrRIGmgAZUUMtOfPmVISOZCETL7kKFEmWkg8xDRgEqRIcoQCfU1Sklzp0HjOf/rXtnHPvvsvd/x2ft997nXdblw9rOetdbvWfvd637X1Ety274kl14aoE4R4Kqwv+oEh1x1uFKgk6seAR3PfBaQqw4BHa8U6DpcvXqlQPdK0EN+CnQP8AKUlT/GMcEYLiL9RSQvTpAGiMij9oKXzzU3V04qNljKbPu2QMa8PJGXPr9YShz7olyIk+GZbBFgf7WFybERuTpGZjsD2dpG5ciQXB3hsm1MrrZROTIkV0e4bBtToNtGlVJDCvSU4i5YGAV6GuH7WDR/NKJg9haRMXHgYrZ8NPZy2AdvuH70kRyzdZBUz15QSJy/OPMS2e+EMdK9u32ftOSJ2Fp9gM8BLbLss1pk2Wd1yJIrueoQ0PFKga7D1atXCnSvBD3kp0D3AC9AWfljLCJ7RKSDiHwTJzBlRGSGiBzlLGh/b9smOeOOlBrFFxYS56M+vUyqnjZSzj7bmU9aU+xo9QE+B7TIss9qkWWf1SFLruSqQ0DHKwW6DlevXinQvRL0kN9vgY57zpOlP//8U9q2bWtM5s2bJ4ccgpO6mLwS2LFjh8ycue8+7o4dO0rp0qW9ugxX/jUipY8uLVmrC18jmFcjT3bM2iFygMMm5ebK3g/bS7ldP8YV55VPeUpOOw33tzE5JVDk+6tTYDbtydUmKBdmZOsCmo0s5GoDkgsTcnUBzUYWcrUByYXJ4sWLpVmzZibnihUrpHbt2i68MIvfBCjQ/SbqwJ/fAj3ZPeux1Ro5cqTsv//+DmpLUxIoTKDioorS4bYOUnwXLjQvmDY22CgzB88UKemQXG6uHLPlZqlefFGBjNhz/sKMy2VlrUvkyCPXOnRKcxIgARIgARIgARIggWgC69atkz59+lCgB6xbUKCnMSAU6GmEz6I9E6j1WS1p9XgrycorOHOeJ3myovMK+eH6H5yXAXGeM1Cql1hcSJw/P/1yWVO/lzRvvt65X+YgARIgARIgARIgARIoQIACPZgdggI9jXHxW6BziXt6glkUl10Vv7O4FH+0uGRJjDjPypPdD+yWvTfsdR4MLGuf3E7K7f6pkDh/bvqVcsh5w6VDBy5rdw62YI6i2F+9MrOTn1ztUHJnQ7buuFnlIlcrQu4+J1d33KxykasVIXefc4m7O27auSjQtQkn8e+3QLdqCgR8nTp1jNnChQulYcOGVln4uQ0CRepAGOjjM0VkchwwJURkgoicbANarElurmwdd0Rccf70J1dL017DpFOnIra33wVGO1mKVH+1A8QnG3L1CWQcN2Srw5ZcyVWHgI5X9lcdrjwkToerV68U6F4JeshPge4BXoCyFpkfja0icqSI/C8O/IoiMkdE3LzzgTh/p6WU2zOvgGPsOYc4396ku/Tte5SUKYPj4Jm8Eigy/dUrKIf5ydUhMAfmZOsAlgNTcnUAy4EpuTqA5cCUXB3AcmBKge4AVgpNKdBTCDu2KAr0NML3sejQ/2jkiAguAIAALyciOMCzQgwgbAlvLSKb4oCDKP/+n7xOuUKcv91Cyu39uZA4f2paX9nd/Bw5+OAcOemkkyjQnbJNYB/6/uoTB7/dkKvfRP/1R7Y6bMmVXHUI6Hhlf9XhSoGuw9WrVwp0rwQ95KdA9wAvQFlD+aORJyKfishTIjJeRKK3jGeLCO4Xv0ZEOonIlH+Wte+OA/1UEZkoIsVcBCR3j2x5q6WUz51fSJw/OfU6Ofrah2TVKhQuFOgu8CbKEsr+6mP7tVyRqxZZ3oOuRZZ9VocsuZKrDgEdrxToOly9eqVA90rQQ34KdA/wApQ1dD/GmO3uJSIFdXF8ori/fHUC2DeLyMMuA5G7R3LeaiEVcn+JI85vkBNveUzq1/9bpkyhQHdJOGG20PVXvwEo+SNXJbBCga5Fln1Whyy5kqsOAR2vFOg6XL16pUD3StBDfgp0D/AClDVUP8ZT/5kd3+YBIGbLx4rIhS59QJy/2Vwq5P1aSJyPmNJfTrtjmOD8wlBxdYkiHdnIVYc6uepwhVey1WFLruSqQ0DHK/urDlcKdB2uXr1SoHsl6CD/F198IYsWLcrPgbsHBw4caP6/ffv20qdPnwLeLrnkEgferU15irs1IzcWofnRwMx5RxHxIs5xTtvMf/aju4EFcf5GM6kgvxUW51MHyFl3PyoHHbTvo9BwdcMhjXnIVQc+uepw5bOAXPUI6Hjms4BcdQjoeKVA1+Hq1SsFuleCDvJDcL/00ku2c+ThGGsfEwW6jzCjXIXixxhdqZnNZe2JMBX/5zC5Gi455u6Rza8fLhWzFhQS58On3CTn3DdE6tb996NQcHWJIp3ZyFWHPrnqcKVAJ1c9Ajqe+SwgVx0COl4p0HW4evVKge6VoIP8FOgOYIXINBQ/xjNE5HgfoMIPDo5zmow4byoVsxYWEuePfXyzdB/8sNTG6fFhe/HhlEMA7EPRXwPAyWkVyNUpMfv2ZGuflRNLcnVCy74tudpn5cSSXJ3Qsm9LgW6fVSotKdBTSTvNZXEGXScAofjROFdE3vGh/fDzlkM/uXtk02uHSaViBS9QxwKRx6bcKhc8/KAcgMPoYlIouDpEEQRzctWJArnqcIVXstVhS67kqkNAxyv7qw5XCnQdrl69UqB7JRii/BToOsEK/I8G7jmvEnOVmlsUuIJtQ5x70hP527NLNr3eVCpl/3v2AkyNOP94kPQcOliqV4+fOfBc3TJMcz5y1QkAuepwpUAnVz0COp75LCBXHQI6XinQdbh69UqB7pVgiPJToOsEK/A/xrjJrKmPbYe/Jjb8QZxj5rz44gLG+2bOb5NLHntAquDFQYIUeK42EATRhFx1okKuOlwp0MlVj4COZz4LyFWHgI5XCnQdrl69UqB7JRii/BToOsEK/I/xbBE5yse2fyMibS387dklG19tIpVLLCkszqfeIb0fv08qVUruI/BcfUSaSlfkqkObXHW4UqCTqx4BHc98FpCrDgEdrxToOly9eqVA90owRPkp0HWCFfgfY4UZ9JzqObJm+R+yc+tWKVWunFSvV1sqVK2wD3AScT5syp1y+RP/lQr/mCaLSOC56nQnda/kqoOYXHW4UqCTqx4BHc98FpCrDgEdrxToOly9eqVA90owRPkp0HWCFfgfYx/3oOdl58qcuy+WI+u/LsWz9+YD3bM3W+asPltKH3651P/rCqlccnkB2FjWPmzq3XLlk/dIuXL24hB4rvaaETgrctUJCbnqcKVAJ1c9Ajqe+SwgVx0COl4p0HW4evVKge6VYIjyU6DrBCsUP8Z+neJ+1Fsi1/VwBNKI82n3yNVP3S1ly9rPGgqu9psTGEty1QkFuepwpUAnVz0COp75LCBXHQI6XinQdbh69UqB7pVgiPJToOsEKxQ/xn7dg357J5HDPrMN0ojzT+6Va5++S0qXtp3NGIaCq7MmBcKaXHXCQK46XPksIFc9Ajqe+SwgVx0COl4p0HW4evVKge6VYIjyU6DrBCsUP8Z5ItJMROZ7YFB7nshDzUWy7PmAOB8762o5f9jTUrKkvTzRVqHg6rxZac9BrjohIFcdrhTo5KpHQMcznwXkqkNAxysFug5Xr14p0L0SDFF+CnSdYIXmx/gLETnWJYNSW0Xu7Chy0A+OHCxcc7g0vO4nySpmU9VHeQ8NV0dE0m9MrjoxIFcdrhTo5KpHQMcznwXkqkNAxysFug5Xr14p0L0SDFF+CnSdYIXmx7iTiNhfnf4vLIjz/meLNJvmCuDcqjOk5cko3FkKDVdnzUq7NbnqhIBcdbhSoJOrHgEdz3wWkKsOAR2vFOg6XL16pUD3SjBE+SnQdYIVih/jV0Wkp4v2Y1n7VRc7njmPLmnWynPlmIFvOS48FFwdtyr9GchVJwbkqsOVAj29XHNzc2Xr1q2Sk5Mju3btkr17/729Q69m4fYMZmvXrjWNqFatmhQrVizcDQpI7ck1fiCys7OlbNmyUqlSJSnt9LAfEaFAD0gHj6kGBXow46JSKwp0FazBP8wM16zVEJEdMe2/TUQWish7IhI95iousvv03VLssFMku+l023vOE9HFFWzbT9vw7z3pNsNAwWMTlEMzcnUIzKY5udoE5cKMbF1As5HFiuuWLVtk5cqVkocDRZhsEwAvsEUqU6aMZGU53+Jlu7AiZEiu1sGuWLGi1KxZ01Gfo0C35poOCwr0dFBPU5kU6DrgrQY5OqU68NpBRL6Mse8YtdwdAn6liGwRkfIiUktk0aJfpMFvTR0Uktx0cZNf5JAjmjjyF3iujloTHGNy1YkFuepwhVey1WGbjGs8cQ6hidk6JmsCe/bsMUbFixe3NqaFbQLkWhhVhEnkE6za2H///W0zpUC3jSqlhhToKcWd3sIo0HX4B3rwOFZELo5pN647w+q7col5zJ85W5r+cZRvwObX/kaadmzryF+guTpqSbCMyVUnHuSqw5UCPfVcsZR44cKF+TPn5cqVkypVqphltJwNto4H+GFLAFKFChW4xN0amS0Lco2PCdtONm3aJGvWrMk3OOSQQ6SkzetzKNBtdb+UG1Ggpxx5+gqkQNdhH9iBOcYH1UVkZ0y73xSR7slZLPqeM+g6vSX9XgPbX9OPxlMNyNUTvqSZyVaHbSKuEJdY2o4EcV67dm0KcwchoJB0AMuBKbkmhwWBvn79emNUo0YN81LNTqJAt0Mp9TYU6KlnnrYSKdB10Ad28HiMiHwd0+bOIjLdmkPO+hwpO7mKFM/2fiDQ7j3F5e/T13MPujX2lFgEtr+mpPV6hZAr2eoR0PGcqM9irIAl7kh169aV/fbbT6cCGeqVQlInsOSanOuOHTtk6dKl+S/W6tSpYysQFOi2MKXciAI95cjTVyAFug77QA7MR4lIn5j2lhGRdSJS1h6HWUPOlWNqvWPPOIkVT3H3jNBXB4Hsr762MD3OyFWPO9nqsE3EdcmSJbJz504za964cWPOnjvETyHpEJhNc3JNDgqH6C1YsMBsTcHydixzt5Mo0O1QSr0NBXrqmaetRAp0HfSBGzxu+ufU9l0x7YXW7mafwY8fTpYWG0+3nyGBJe9B94zQVweB66++ti59zshVjz3Z6rBNxBUDdhw8hQPOGjZsqFN4BnulkNQJLrlac3Xz3aVAt+aaDgsK9HRQT1OZFOg64AM3eMRZbHNi2tpFRKY4aP+urbJ+bAOpWvYvB5kKm/5vzeHS4LqfJKuY82tmAsfVE4ngZCZXnViQqw5XeCVbHbYU6DpcKSTJVYeAtVcKdGtGYbGgQA9LpHyoJwW6DxDjuAjU4PE5EbkqppJY0o5zQ3B6u520a6tsGNtQqpRdbcc6oc3WHfvJikNnSpN2R7ryEyiurloQzEzkqhMXctXhSoGeeq5uBvl6tQyfZwp0nZiRqzVXN99dzqBbc02HBQV6OqinqUwKdB3wgRmYbxCRA0Rkd0w7x4tIV5tt35UjG8Y2kioxM+d5eSJZDibBIc4X1HhPWp2OqXt3KTBc3VU/sLnIVSc05KrDlQI99VzdDPL1ahk+zxSSOjEjV2uubr67FOjWXNNhQYGeDuppKpMCXQd8YAbmrUXku5g2niIiH9psN8T5yw2lSpl/79JETojz1368WdrWmiQNq823dIZl7XvavuR65jxSQGC4WrY4XAbkqhMvctXhSoGeeq5uBvl6tQyfZwpJnZiRqzVXN99dCnRrrumwoEBPB/U0lUmBrgM+EAPzp0Xk2pj24WYcnNpuZ2n7rhzZ+HJDqRxHnL8w9ym5Ysg1kpebJz9O/Uz+/ukpaXPAewWuYMNVat/+dbaUaX6NtOhynKs957HRCQRXnS6TVq/kqoOfXHW4UqCnnqubQb5eLcPnuSgLyWXLlslBBx1kgjZmzBi55JJLfAtgUeD66aefSufOuA9XZMaMGdKpUydH/Nx8dynQHSFOmTEFespQp78gCnSdGKR9YI4J79pxlrZPEpHTrNucuyNHNr2CPeeFZ85fmPu0XDHk6kJOcE/62t9Xyo4tW6R0+fJSrW4tx/ecW9Us7VytKhjSz8lVJ3DkqsOVAj31XN0M8vVqGT7PboRktDCL12LcRX/ggQfKMcccI5deeqlj4ZYqil4E+jXXXCPPPPOMqeqPP/4ozZs3L1DtaK733HOPDB8+3Hx+7LHHysyZMxM2ce/evVKpUiXZunWrtGjRQubOnZsqHI7LoUB3jCxjM1CgZ2xoCzeMAl0n2GkfmLfEr1lM23A72kTr9ubu2CSbX2kklcuuLWCMZe0jf3xaLn+ksDi39uqPRdq5+tOMwHkhV52QkKsOVwr01HOlQPfGXEOgx9aod+/e8vzzz0t2dra3yvqc24tAf+ONN+T88883NXriiSekb9++CQX6iSeeKN99t29PX6lSpWTz5s3m3/HSt99+K23atDEf9evXT0aMGOFzq/1zR4HuH8uwe6JAD3sEHdSfAt0BLAemaR2Y4wXyDTGVLffPqe0lkzcimTgfNe9Z6fPQlQ4o+G+aVq7+NycwHslVJxTkqsOVAj31XCnQvTH3KtCvvvpqwWxyJOXl5cmGDRtk1qxZ8thjj8maNftWu911111y7733equsz7m9CPQ///zTrBJA6t69u7z55psFahfhipnw+vXrC2bG8YIC/8YMOmbS4yUwGzBggPno7bfflv/85z8+t9o/dxTo/rEMuycK9LBH0EH9KdAdwHJgmraBOW5BqyMie2Iq+5GInOxFnD8nfR66wgEBHdO0cdVpTmC8kqtOKMhVhysFeuq5UqB7Y+5VoN99992CJdzx0i+//CKtW7cWPG8qVKgg69atkxIlSnirsI+5vQh0VKNBgwayePFiqVmzpqxatSquQJ8+fbp069ZNKlasKO3atZMPP/xQ7r//frn99tvjtuTss8+W8eNxnY3IX3/9JdWrV/exxf66okD3l2eYvVGghzl6DutOge4QmE3ztA3MsT1rXkwlcZ3avt+hhGnfzHlDqVwWJ8j9m7Csfcz856T34PSLcw7KbXY+F2Zp668u6hqmLOSqFy2y1WGbiCsFujfemgIdNTv33HPlnXfeMZWMt1fbW+295fYq0LF0H4fLIaEfQrBHUoTrAw88IEOHDpVTTz1VOnbsKIMGDZKTTz5ZPvoIsxOFU7Vq1cyLjMaNG8tvv/3mrYHKuSnQlQGHyD0FeoiC5bWqFOheCcbPn5bB46MiclNMfSqICLaSJ1nanlSc//KC9H6gjw4kF17TwtVFPcOWhVx1IkauOlzhlWx12FKg63DVFugDBw40AhXpm2++kbZt2xZoyJIlS+S9994TiL158+aZWWMkzBwfffTR5pC5U07BHazW6eeff5bnnnvO+MIYcufOnWYZOoRz165dzXJxCOBIsiPQ4QN7zVFHpOjZ7xdffNHUD2nUqFECwR5JEa5nnHGGfPnllwKhDoGOpe3ly5eXjRs3FtqT/+uvv8phhx1mXFx++eVm334keeUUXdelS5eaWX8ccoe99IsWLZL169dL7GoIfOeGDRsmb731lrEpXbq0HHrooea0+8suu8ws1ecp7tb9sihYUKAXhSj/00YKdJ1gp3zwiFVf9eIsbZ8mIickbqMR5682kMpl1hcwwsz5i7+8IJcGSJxzUK7TV8mVXPUI6HlO+TNWrymB8kyBrhMObYEePYOOfdsHHHBAfkMgFA8++GDLhvXs2dPMVBcvXjyuLfZ140UATkpHexKliy++WCBUI8lKoGP/OIQ9lqkXK1ZMnnzyScGe+2jRfMghh5j/hWiNzKbj/1EPzIRj/zn6LsQsXk5gqTtEPw6Da9WqVYGq4uXCVVddZf728ssvC9qN5AenaIE+Z84c8wIg9oT4aIGOJfsnnHBCwll8vDTp37+/WQ2AxGvWLLtxRhtQoGd0eAs2jgJdJ9gpHzw2FZFfYtrSTUT2rXiLm3L/3iA5rzaSSmULi/OXfhspl9x3mQ4cD15TztVDXcOUlVx1okWuOlzhlWx12FKg63DVFOhYon3kkUea7wROJp89e3aBRmBWtmnTpkbkdenSxcweV6lSxRwyt3DhQnnqqadk/vz5Jk+yQ+Ywmzt69Ghjh5lhnKiO/d4Qw2vXrjXlYpl9y5YtbQt0zChjWTrELPbNjx07Vs4777xCQahTp46ZrceLBuxHjyRwnTp1qpn9L1mypDm5HTPQHTp0MDPqmJmGwI1OEOSvvvqq+dPy5culbt265r/94BQt0HElHFYrXHTRRdKjRw/z0uT33383J8ujzXv27DEvE3744QdT/kknnWReTKCtsHv66adl2rRpJqbgg0SBrvP9DItXCvSwRMqHelKg+wAxjouUDh4fEpFBMZWoKCLYTh7/RbgYcf5aQ6lUZkOBjJg5H7twpFx8b/DEOQflOn2VXMlVj4Ce55Q+Y/WaETjPFOg6IfEq0OOd4r5p06b8U9xXr15tDojD4WgQzdFp27ZtkpOTY0R1vIQT4bFsHOISd6uvXLnSiO7o9P7778v//d//mT/h3vXJkyebe8TjJYwra9eunf9Rohl02EGUYsl52bJljbiHcI2XLrjgAnn99dfNR6hf5GR3cP3vf/9rTq5v3769fPHFF8bm1ltvlYcfflhwGNy7775bwGW9evWMAMa/UbdI8oNTtECH39gl+dEVwbVx1113nfnTFVdcYbYNxKbolyL4jAJd5/sZFq8U6GGJlA/1pED3AWIcFykbPP4hIvVFZG9MJWaISKf4bUsuzkfLxffu2+sVxJQyrkFsvGKdyFUHLrnqcIVXstVh60WgY9Xz+oILsnQqGSCvVauKFCtmXSGvAj1ZCVgWjqXUN9xwg9m77CZhNh370bGMHUIZJ6JHJ4jyr7/+2ghpzLrXqlXLdjHxBDp8YDYfQhlCf+LEiUZgJ0rPPvts/rJ3CPXILDu4QtRPmTJFbrnlFnnoIcxYiPF35plnyv77729m9yMpIszx/5jZxoy9k2TFKVqgH3/88fLJJ58kdI+VDHg5UaNGDcHed7CNTVj+j1UDkTZQoDuJVubZUqBnXkwTtogCXSfYKRs8NhGR2ANIe4jIG/Hblbt9neS83jj+zPn/XpSL77lYB4hPXlPG1af6hsUNuepEilx1uMIr2eqw9SLQoYMCfFuVCjBcPx51HlrCMjQFOgqtXLmymQUfPHiwWeqdLO3evdscErdlyxYjyCMJe6Fxn/qdd95pZqUjCcvQcegbZtpj94DbgRor0Fu0aGGWpKMsiNOPP/5Y8LdkCVfJYZk+Eu6Dx7J8JCwThwjH0vYPPvjAiHIkHA5XtWpVU2fkbdIEgyWRV155xQhzpJEjR5pD2BIlp5zgJ9mBdtHlYO955CVHv379ZMSIEQnrga0EkfZSoNvpcZlrQ4GeubEt1DIKdJ1gp2Tw+ICI3BFTf6w4w8viOEvb92xdJ1vfjC/OX138ovS8K9jiHC1NCVedLhFor+SqEx5y1eHKZ0Hqudq5Zo0CPXFcvAr0ePeg4/mCfdM46Oyxxx4zYvW4444zy9zLlClToDIQmzitHLbY87xr166ElcVyeux/jiTMAp944onmf7EHPXKiut1eGC3Q8RIBM/RYco+D3bB/PPratEQ+IbQxw48D4Q4//HCztxsJB7AdccQRkpWVZT7D3vpIatasmeDEecy+X3nllebP+Hfk1HbM4jds2NA3TrECHfvGcT99vISXEpFT8zGLH3lpEM8Wn+PgPSQKdLu9LjPtKNAzM65xW0WBrhNs9YH57yKCQ1ljl7Z/LiIdCrdpnzhvJJXKbCzwYW5elkCcX3RXLx0QPntV5+pzfcPijlx1IkWuOlzhlWx12HIG3RnXVM2gxxPo0TV94YUXzD5mpNgZcCzLxl7v7777zlbjYmfJ33zzzfwl5RD/dq9jixQWLdCjKxDvOrhkFcR+8vHjxxcQ4zjxHTPQWC4O0Y7l/pGEFw0Q5xdeeKGZOUeKLCvHgW047T46eeUEX9Ez6Hh5Ejl9PrZduHYN18oh4a72yCnt8dofLeYp0G114Yw1okDP2NAWbhgFuk6w1QePjUTkfzF1v0BE9h1MWiBBnG97s5FUjCPOX1s6Vnrese+KkTAkda5hgKBQR3JVgEoRqQP1H6/sszp4KdCdcQ2KQMcMPZahQ2TiADUcpBZJmJ2NCFQc9IZZbJwwjhlpnHiO2WcknGa+YsUKM1sbfU1atEC3EpPx6EULdFynNmnSJDPbj3oDedoAACAASURBVNnrzz77LOHhdbG+sEpgwIAB5s84tO6ss84yp6Pj/nAsVcfMeLRAx0ntOLE9cio6ZtjRZszGd+/eXdCu6OSVE3zF3oOOVQLxEvbR4+A7JAhwvEBJlMA8cngeBbqz72emWVOgZ1pEk7SHAl0n2KqDx3tF5J6YemNVF5a2xxxWk0ycv7FsrFxwe3jEOVqsylWnK4TCK7nqhIlcdbjyWZB6rnaWuPOQuMRx0VjiHlva0UcfLZiVRsK+cSz3xlJy7NHGEncIwsj1YvFqWr58ecGhZLEC3c8l7rjDHC8FIJyx/71x48by6aefFri3PRFFrACILBm/6aabZMiQIWYfN/ZzYwUBXjxEC3RcoRYRyHhJ8P3338s555xj3GPm/dprr80vyg9OTgQ6l7jrPcMy2TMFeiZHN6ZtFOg6wVYbmC8VkQYikhtT769w90nBv+3Zuka2vdlYKpbZVOADLGt/8/excv6gcIlzDsp1+iq5kqseAT3Pas9YvSqHwrOXGfRQNDBNlUyFQId4jSxjx7VrOIAtWtRGH6IWi2HBggX5J8DHCnTMykPk+3VIHJbQv/baa2bfNbhg2TlmhjG7nSxB0EdeOuD+cPiI7F/HXnMcBBct0OErsioA+7ix9x6z8Eg//fSTYI96JPnByYlAd3JIHJbw44UCEmfQ0/QFDkixFOgBCUQqqkGBrkNZbfB4iIgsiakzto+/VPBvu3LWyN9vxxfnb//xsvS45UKdhit7VeOqXO+guydXnQiRqw5XvlRKPVc7M+h6tQq/Z22Bvn37diOi8czBDDVmwrOzs82MOmbWkbDvGUvC46X+/fvL448/bj6KFej4W4cOHeTLL780V4GhL0TuIbcTmUT3oOPAOoh1sMHBbxCfaEOyhKXeWPJdvHhxU1+ccI4l7BDcuAc+VqBjnzfajWvoMIMOIQ6Rj+XukaX9KM8vTnaXuKPM6P3wuGYt9mA/2OBudlyzhhPvKdDt9LbMtqFAz+z4FmgdBbpOsFUG5neKyP0x9a0qInhuRy1tz1RxzkG5Tl8lV3LVI6DnWeUZq1fd0HjmDLpOqLQF+sCBA2Xo0KGm8tjnjcPUkKKvSDvttNPM/u/YhDvDsTc9cuVaPIE+YcIEs+cbqV27djJ58mSpWLFiXFgYV9auXTv/s0QCHQYvvfSSWZoOPtgXP336dHM9WqL04IMPym233WY+hnCFsMV+8ueeey6uQMf1ZBDxmEnHvny0Ee3AHvbo5BcnJwL9iSeekOuuu85UI/bk/EjdcPAflu9HEmfQdb6fYfFKgR6WSPlQTwp0HyDGceH74HGxiOBguNil7bNFpM2/FYA43/F2I6lQZnOBWmFZ+zurXpXuA/edGhrW5DvXsILwud7k6jPQf9yRqw5XeCVbHbYU6DpcvQp0CDjc/x2dduzYYWazsXwbs8pImD2fPXt2geXbZ5xxRr4wx2nhuGoMghWzsuPGjTMHm0Hsbtq0SdauXRt3Bh2++/TpI6NGjTLlYAYdwrd9+/ZGGGNG+ttvvzUHtkFoRx8yl0ygwxeuboNvLKHHlWnY84573eMlzOJjNj86DRs2zFz9Fm8G/ccff5SWLVsWsMeLjBtvvLGQez84ORHoOCgPS/Wx9B4Jp+NfddVVZkUADuvDVXdTpkyRNm3aCK5sQ6JA1/l+hsUrBXpYIuVDPSnQfYAYx4Xvg8eDRGRZTEGX4pft37/t2LRado07NK44H/fn63LuTfGXtukQ0PHqO1edaobOK7nqhIxcdbjCK9nqsKVA1+HqVaDbqRVOccdp7bEngkPsQdT+/jvuZy2cINZxfRpm2HGwWrwZdOTC7PMNN9wgmJWGmE6UYvNbCXT4wSwxXhzAb6tWrWTatGlSqVKlQkXg/nb8Hf00kmbNmmX2z8cT6OCOJe2bN/87aYEXGBC9sckPTk4EOsrHXvTjjz9ecAZAvIRY4mVC5Bo2CnQ734TMtaFAz9zYFmoZBbpOsH0dPA4SkYdi6llNRFb/u7Q9mTh/d/Xr8p8bwy/OOSjX6avkSq56BPQ8+/qM1atm6DxToOuETEOglyxZ0ojPpk2bGnGNWeREM89Ywv3www+bpd0Q4ZhpxwnnWNp+/fXXm3z4/2QCPUIGe7mxpBynr2PZOEQ1TlPHtWm4q7xbt24F6mFHoMM3fGKlAPxBQE+dOjXuMvrOnTubspHQftw3jv3k8QQ6bMAGLyCQypUrZ1YKYH9+vOSVk1OBHvn9xSoA7JVfvHixlCpVyrxw6NWrl3lpMXPmTEGbkSjQdb6fYfFKgR6WSPlQTwp0HyDGceHb4BEvVZuISPTLalxZiqXtrfcVbMT5u42lQumcAjXJzc2Sd9e+If/p312nkWnw6hvXNNQ9yEWSq050yFWHa2RQi+WfSJhlinfAkl7pmeuZAl0ntm4Euk5NMssruVrH080Bj8jTqBH2VYpZbh99poB1ibTQIkCBrkU2gH4p0HWC4tvAvJ6IxK5Ku1JEnt1X7+0bVsue9xpLhTKFxfn7696Qs2/IHHHOQblOXyVXctUjoOfZt2esXhVD6ZkCXSdsFJLkqkPA2isFujWjsFhQoIclUj7UkwLdB4hxXPgyeMQZJsNinNfApqV9S9u3r18le95vEnfmfPz6t+Sc6/+j07g0evWFaxrrH9SiyVUnMuSqw5UvlVLP1c0gX6+W4fNMga4TM3K15urmu8sZdGuu6bCgQE8H9TSVSYGuA97zwPxXEWkaZ2n79yLSUmTrulWS98GhUr70lgINwLL2CRvfkq79Mk+cc1Cu01fJlVz1COh59vyM1ataqD1zBl0nfBSS5KpDwNorBbo1o7BYUKCHJVI+1JMC3QeIcVx4HjzWEZE/YhzjhpWnLMT5prela99uOo0KgFfPXAPQhiBWgVx1okKuOlz5Uin1XN0M8vVqGT7PFOg6MSNXa65uvrucQbfmmg4LCvR0UE9TmRToOuA9Dcz7i8jjMfWquU+wb133h+RNPCzuzPmknLflzGsyV5xzUK7TV8mVXPUI6Hn29IzVq1boPXMGXSeEFJLkqkPA2isFujWjsFhQoIclUj7UkwLdB4hxXLgePP4sIs3jLG3/SSSn2h9SbFITKVd6a4ESsax98tZxcsZVZ+s0JkBeXXMNUBuCWBVy1YkKuepw5Uul1HN1M8jXq2X4PFOg68SMXK25uvnucgbdmms6LCjQ00E9TWVSoOuAdzUwzxWR2iLyZ0ydrhPJuS2xOP9w2zg5/crMF+cclOv0VXIlVz0Cep5dPWP1qpMxnjmDrhNKCkly1SFg7ZUC3ZpRWCwo0MMSKR/qSYHuA8Q4LlwNHvuJyJMxzmqJbPrmDyn+ceGZ8725WfLR9vfk9Cu66jQigF5dcQ1gO4JWJXLViQi56nDlS6XUc3UzyNerZfg8U6DrxIxcrbm6+e5yBt2aazosKNDTQT1NZVKg64B3PDCfKyJHFl7anjNjlRRb3LjQsnaI8yk7xsupfc7SaUBAvTrmGtB2BK1a5KoTEXLV4UqBnnqubgb5erUMn2cKSZ2Ykas1VzffXQp0a67psKBATwf1NJVJga4D3tHAHEvbDxSRvwrW5e/LN8veY2pJuVLbCnywN7eYTN3xnpxSxMQ5B+U6fZVcyVWPgJ5nR89YvWpknGcucdcJKYUkueoQsPZKgW7NKCwWFOhhiZQP9aRA9wFiHBeOBo9XichzBZ3sPXCP/H1fJSlXurA4n7brPTm5d9GaOY/QccRVJ7QZ6ZVcdcJKrjpc+VIp9VzdDPL1ahk+zxToOjEjV2uubr67nEG35poOCwr0dFBPU5kU6DrgbQ/MvxeR1gWXtudl5cn2+4+Q/er/WKBymDmfvud96XLJGTqVDoFX21xD0JYgVZFcdaJBrjpcKdBTz9XNIF+vluHzTCGpEzNytebq5rtLgW7NNR0WFOjpoJ6mMinQdcDbGphjaTvuN19TsA67Tn1USva8qZA4n7H3fTnx4qIrzjko1+mr5EquegT0PNt6xuoVn7GeucRdJ7QUkuSqQ8DaKwW6NaOwWFCghyVSPtSTAt0HiHFc2Bo89hGRUQUz51ZdLsVG1C8sznMnyIm9TtOpbIi82uIaovYEparkqhMJctXhypdKqefqZpCvV8vweaZA14kZuVpzdfPd5Qy6Ndd0WFCgp4N6msqkQNcBbzkwnyMibQuWnZe1V7KGNBapuTj/Ayxrn5k1QTpfSHHOQblOXyVXctUjoOfZ8hmrV3RGe+YMuk54KSTJVYeAtVcKdGtGYbGgQA9LpHyoJwW6DxDjuEg6eMTS9hoisi4mY9f7RbrfWVCcF5sonS84VaeSIfTKQblO0MiVXHUI6Hlln9VhS4Guw5UCnVx1CFh7pUC3ZhQWCwr0sETKh3pSoPsA0alAv0REXorJVG2xyOMNCojzL7InynHnU5xHk+KgPA39VafIIuGV/VUvzGSrw5YCXYcrBTq56hCw9kqBbs0oLBYU6GGJlA/1pED3AaITgT5LRNrFZMjaKzLsEJHqy80HWNb+ZcnJ0rH7yTqVC7FXDsp1gkeu5KpDQM8r+6wOWwp0Ha4U6OSqQ8DaKwW6NaOwWFCgpylSv//+u4wYMUImTZok+O9SpUpJgwYNpHv37nLNNddI2bJlfa8ZBbrvSI3Dtb+tka9f/UKyt4o0atNEqrerJRXqVhCpJiIbYso8+x6R/9ybL86/KvmRHNu9i07FQu6Vg3KdAJIrueoQ0PPKPqvDlgJdhysFOrnqELD2SoFuzSgsFhToaYgURPmFF14omzdvjlt648aNZfLkyXLwwQf7WjsKdP9w5u3Nk0VD50qVV3dIlfltJCu3eL7zvGJ7ZGeFjVJ6ExR6VDpgocijjfPF+axSH0mHcynOE0WFg3L/+mu0J3IlVx0Cel7ZZ3XYUqDrcKVAJ1cdAtZeKdCtGYXFggI9xZH68ccfpV27drJ9+3YpV66cDBo0SDp37iz4oXzjjTfkhRdeMDU69NBDZc6cOcbGr0SB7g/JpWN+lQNvKy6lVje07zBrj8hjh4hU+1325BaTb8p8JO27UZwnA8hBuf3u5cSSXJ3Qsm9LrvZZObUkW6fE7NlToNvj5NTKjUD/9NNPzVjQbhozZoxccgkOuSmYTjzxRPnkk0/MH+Fv+vTptlx26tRJPvvss7i2xYsXl0qVKslhhx0mp59+ulx++eVSuXLlhH5Rr5deij18RyQrK0vKly8vBx54oLRt21Z69eolJ5xwQtL6RXO56667pH///sa+QoUKUqxYMfPf8It03HHHCewTpT179shFF11kxtpIRx11lHz88cdSsWJFW4zCYESBHoYo2asjBbo9Tr5Z4YGJBwgeeDNnzpRjjjmmgO8hQ4bIzTffbP527733Ch5IfiUKdO8kF97/nTS8v7Fk7XT44uTY0SJXXWbE+eyyU6TdOcl/lLzXNPweOCjXiSG5kqsOAT2v7LM6bCnQdbimS6BjjFevXj1B+RHhumzZMqlbt65lQ5MJ9NjMNWrUkPHjx8vRRx8d128igR7PGNs6X375ZSlZsmRcX34J9N27d8v5558v48aNM+W0b99ePvzwQ/PCIJMSBXrmRJMCPYWxxIw43hoiXXnllfLss88WKh0P1sMPP1x+/fVX84byr7/+khIlSvhSSwp0bxgxc17/6jrOxTmKLbVV9tzeSb5r/rAc1ZXi3E4kOCi3Q8m5Dbk6Z2YnB7naoeTOhmzdcbPKRYFuRcjd514F+tVXX23OIkqWateubWa1o9NDDz1kVmVC7Obl5QlE6QMPPCC33XabZUOiBfq8efMK2O/atUuWLFlihPQHH3xgPqtSpYosWLBA9t9//0K+owU6ZqgxY460d+9ec+bSl19+KcOHD5cdO3aYv/ft21eeeOKJuHX0Q6Cj/ueee25+3dHWiRMnyn777WfJJWwGFOhhi1ji+lKgpzCWt99+uwwePNiU+PXXX5vlNfFS5CGLz6ZMmSJduvizFJoC3X2wsed8V+1Fzpa1xxS3q+YCKbGikWRl71uOxZScAAflOj2EXMlVh4CeV/ZZHbYU6DpcvQr0u+++W+655x7HlWvatKn88ssv0rVrVyPQIaaxXRITPlYpWqAjb6J08cUXy9ixY83HGKvecssthUyjBfrSpUulfv36hWzwEgBjYPRBrChdsWKFHHDAAYXsvAp0vATo1q2bOdcJCePp999/X8qUKWOFJJSfU6CHMmxxK02BnsJYduzYUT7//HPz1m7Tpk3moRQvzZo1y+xTR8ISdyx19yNRoLun+L+Hf5CGtx7h3sE/ORc9PFca3NzSs5+i4ICDcp0okyu56hDQ88o+q8OWAl2HazoEevQKzbfeessI9B49epgGfvPNN/mrNxO12K5Anz9/vlnliXT22WfLu+++60qgI9Nll10mo0ePNvlff/11Oe+88wr58iLQ0b/xsmLq1KnG76mnnmrqW7p0aZ3AB8ArBXoAguBTFSjQfQJpx021atVk3bp10qJFC5k7d27CLBs3bjTLh5CwLAcPWz8SBbp7iuubz5Kq8wqeF+DG27rms2T/H737cVN22PJwUK4TMXIlVx0Cel7ZZ3XYUqDrcE2HQO/Xr588+eST5sCz1atXm4Zhr3hOTo5ce+215rNkya5A37ZtW/7hxRC8kZnpaN92ZtBh/9RTT5nl7UiPPPKIDBw40DeBjnqeeeaZMmPGDOPzrLPOkrfffjvhXnednpB6rxToqWeuVSIFuhbZGL9YZhNZUoNTMLH/JVnC6e14wOAQDsyo20kQ4MnSn3/+mf8WFcuLDjnkEDtui7zN1uVbZP+mVQpcpeYWCq5gWzd/g5Srl1kHk7jlkSwfvjM4SBEJq08y+a23Br9EPslVhza56nCFV7LVYZuIK/YJY78wzr/hOME5ewj0rVu3mowYy0VOG0/mCTPFkRPNsXISy9ztJuw1x550TABdeumlMnLkSJMVM9QvvviiVK1aVVauXJn0PKPjjz8+/xR3xD5Rwgx68+bNzcdXXHGFPPPMM4VMUYfIMvjFixfHXeKOTDiHCS8PkB599FG54YYbCvmK5nLnnXfKgAEDCnHNzs42f8Mp7ji1fsuWLXLGGWfIF198Yf5+zjnnyGuvvebbeU5245IOO/BGfwATO4cDoo7I06xZM1NdbDVAX2JKPwEK9BTFYO3atVK9enVTGpYdRa55SFQ83nyuWbPGLCWKPbAjUZ7IVRN2moQHeLzDPezkLWo2xb7dK2fef45vzZ5w5zjJbRV/e4NvhdARCZAACZAACbggAEGHCYWyZctKzZo1XXhgFqcEICYx44uEfd233nqrbReTJk2Snj17GnvsOz/22GPNf+MFN5Z4I73yyivmirRECYIWh7chYRVnogRBDbGL9Oabb8pJJ51UyBQH3GHJOhKuFk4kFNHO559/3tjhADrUITbZ4RK58g0ns7/66qtm5SmW/CNh/zleBCTaUmobckgMMRGHa5yxOmb9+vW2ao0XO3369DG2FOi2kKXEiAI9JZj3dfrIQwr3MEbeLiYqHrbIg7fXixYtslVLCnRbmBwblfh0r5z2uH8CffIN78ruTvve+DKRAAmQAAmQQJAI2BLoebmStWtDkKqtXpe8klVEsvbdve13ihaivXv3NrPfiRK2S+KfSMKYEqsycVo6JnQiM/aYycfM6KpVq4z4hQhOlKIFekSoR2wxI4tVFdhuGVn9CeGP2fl4yY5Axw1FWCGK85hwp/nPP/8c98ozJwIdbYUQ/+GHH0y1sKcdy+jtrGDwO57p8keBni7y/pdLge4/07geUzGDziXuOsFc+d4yaXBhE9+cL3r9V6nVtfCppr4VkCGOuKxVJ5DkSq46BPS8ss/qsPW0xH3HWik2vvCp2zo1DYbX3P9bLVL6X2GcqFZel7hbtTZ6CfyGDRukVq1agqvEsIcbJ6tHJ8xSDx061Oy9xjL3yPlGsWVEL3FPVn6jRo3kpptuMkvpEwnfREvcwQVCHzP7WK4eGbOOGDEif6l7bNlOlrhH54U4xwuJoiTO0X4ucbf69oTncwr0FMUqFXvQrZrCQ+KsCMX/PGdZjpQ/pKw/e9Czd8uWRX9LhfoV3FWmCOXiwVA6wSZXctUhoOeVfVaHradD4nasFXl337a9IpPOWWNboONwNiTMDtsRidGnlVvxjL6G7emnn84Xtz/99FP+XuKID/wNBxMjwRZ3rMdL0YfEWZWPW4Yefvhh6dChQ1zT6EPikvnCtWq4pQh72RMlJ6e4YxVp5Io4XO2GW5OK2n5qHhJn1XvD8zkFegpjxVPcUwjb56J4irvPQG2446DcBiQXJuTqApqNLORqA5JLE7J1Cc4iGwW6Q64pEuhO7kHHXeKzZ882B7dhv3e8hM+w9D3ZocPJTnHHzDf2KWO5+X//+19TTqlSpcw+c1y1FpvsCnTse8bp8vDlh0DH3nusJoic8dSwYUMzWx/vfnWHkQ+NOQV6aEJlWVEKdEtE/hnwHnT/WKbaE+9BTzVxMYecTJkyxRSMg2gityCkviaZVSK56sSTXHW4wivZ6rClQHfINWACfeHChdK4cWPTiETXlEU+w1J3JOSBcI1Ndq9Zw+n0rVq1Mn6wOmDZsmUSOaQt4jNaoH/88cdmbzwSbiZCPszkf/311+Zv2PuOg+0SnaHkZAYdp7hPmzbNHBI3fvx4479p06YCH0XlUGQKdIff6QCbU6CnMDi33XabPPjgg6ZEPJzw5jNewh6iQYMGmY/wcIt3SqabanOJuxtq+/Lk7c2TXbUXSanVhX/Y7HrdWfN/UnJFA8nKzrKbpUjbcVCuE35yJVcdAnpe2Wd12HoS6Hm5IjvtnRKtU/s0eC1V1dYhcam6B/3222+XwYMHOwJxxx13yH333Vcoj12BjoyPP/649O/f3/jAKeyXX355AX9W96CDD06dj5z0PmzYsHx/sRVzKtBhj/34OMTuo48+Mu6OOOIIc/1apUqVHLEKozEFehijFr/OFOgpjCWWIUVE+ZVXXmmufohNeHDharVff/3VPExw1RruIvUjUaB7o7h0zK9S/+o6krWznGNHeaW2yrJnVshBl/p32JzjSoQsAwflOgEjV3LVIaDnlX1Wh60nga5TpYzwmgqBjr3W2GeNQ9ecJORZsmRJoRlrJwIdwvfUU081xfbr109wyFt0shLosMUefcz+r169WipWrGjqFO8AOzcCHf7Rt3Gt3IwZM0zVsLx/6tSp5l76TE4U6JkTXQr0FMcysswdV0Fgb8wxxxxToAZDhgyRm2++2fzNyT4kO82gQLdDKbnNwvu/k4b3N3Yk0iHO/3fHAml0RyvvFShCHjgo1wk2uZKrDgE9r+yzOmwp0HW4pkKgY0b4hBNOyBfJOLgtWcK94JipRoLoxXLw6OREoOOqtcid7VdddZU888wzjgU6MuAKtL59+5q8WIIfewJ9pK6dO3c2Nji9PjJzH334XmR5PNqEtkUSluOffPLJ8tVXX5k/4fMPP/wwo7fLUaDrfKfT4ZUCPcXUcT9j+/btzds9vMnDsnc8fPD/ONgCy4WQcJXFt99+G/deSLdVpkB3S65gPsykH3hbcVvL3bGsfdUDezhz7gI9B+UuoNnIQq42ILkwIVcX0GxmIVuboByaUaA7BGbTPBUCPTJLnZ2dbe45r149+Yn6GzdulBo1agjuNMc966NGjXIt0DF5hMPikB544AEzjo1OdmbQYb9z5045+OCDTf3Lly9v9rPHzqK7nUGP1Gfz5s3mRcZ3331n/oQto9jznuxgOpthDqQZBXogw+KqUhTorrB5yzRhwgSz/yZyDUesN4jzSZMmSYMGDbwVFJObAt0/nNiTvvjRH6XyK39LlfltClzBlpe9W9Y3/VY2XVhGDrmxBfecu8TOQblLcBbZyJVcdQjoeWWf1WFLga7DVVugb9++3YhtzBBj5juyjNuqNaeccoo51wizz1haHn3wqt0Z9OXLl0vr1q3Nqe5ImHRq2bKlK4GOTNH72TFDjmvXopNXgQ5f69evNxNhOMke6ayzzpJx48YJVrJmWqJAz5yIUqCnKZZ4yA0fPtwIcQjnkiVLGkGO0yex5Kds2bK+14wC3XekxuHa39bI1699LtlbsqTRUU2k+tG1eM+5D6g5KPcBYhwX5EquOgT0vLLP6rClQNfhqi3QX375ZenVq5ep/BNPPJG/TNyqNS+88EL+neOvvfaanH/++flZogV6RMhGPkR7IHJxrzj2m+O/kS688EJ55ZVXChVrdwYdGfGy4aCDDjLnLeHcJYyN8QIhkvwQ6PD1119/mSXuCxYsMK67d+8uYIAVCJmUKNAzJ5oU6JkTS8uWUKBbInJlwMGjK2yWmcjVEpErA3J1hc0yE7laInJtQLau0SXNSIGuw1VboHfp0sVcJ4a91xjXRa4xs2oNZr1xJ/jevXsFs+nYjx1J0QLdyg8+79Gjh7z00ktxl4o7Eejw9fDDD8utt95qisWp9JFbjPD/fgl0+Fq5cqXgHCgcSId08cUXy5gxYxJe8WaHQ9BsKNCDFhH39aFAd88udDkp0HVCxsEjueoQ0PHK/kquOgT0vLLP6rClQNfhqinQITLr1q0rKAMHw3355ZeOGnH88cebJfGYOcaYEIIdKZlAx4sAnJlUp04dc7AxZu8hdBMlpwJ9y5Yt5kT6DRs2SLVq1cxe9MgqUj8FOuoL36j7ihUrTPXjHXLnCGjAjCnQAxYQD9WhQPcAL2xZKdB1IsbBI7nqENDxyv5KrjoE9Lyyz+qwpUDX4epGoOvUJLO8kqt1PCnQrRmFxYICPSyR8qGeFOg+QIzjgoNHctUhoOOV/ZVcdQjoeWWf1WFLga7DlUKSXHUIWHulQLdmFBYLCvSwRMqHelKg+wCRAl0HIrmSa8oI6BREEanDFV7JVoctBboOVwp0ctUhYO2VAt2aUVgsKNDDEikf6kmB7gNECkkdiORKrikjoFMQRaQOVwr01HN1M8jXd33NHwAAIABJREFUq2X4PFOg68SMXK25uvnuIg+ud0bC3vzatWtbF0QLdQIU6OqIg1MABbpOLDgwJ1cdAjpe2V/JVYeAnlf2WR22nEHX4UohSa46BKy9UqBbMwqLBQV6WCLlQz0p0H2AGMcFB4/kqkNAxyv7K7nqENDzyj6rw5YCXYcrBTq56hCw9kqBbs0oLBYU6GGJlA/1pED3ASIFug5EciXXlBHQKYgiUocrvJKtDlsKdB2uFOjkqkPA2isFujWjsFhQoIclUj7UkwLdB4gUkjoQyZVcU0ZApyCKSB2uFOip5+pmkK9Xy/B5pkDXiRm5WnN1893lHnRrrumwoEBPB/U0lUmBrgOeA3Ny1SGg45X9lVx1COh5ZZ/VYcsZdB2uFJLkqkPA2isFujWjsFhQoIclUj7UkwLdB4ic6dWBSK7kmjICOgVRROpwhVey1WFLga7DlQKdXHUIWHulQLdmFBYLCvSwRMqHelKg+wCRQlIHIrmSa8oI6BREEanDlQI99VzdDPL1ahk+zxToOjEjV2uubr67XOJuzTUdFhTo6aCepjIp0HXAc2BOrjoEdLyyv5KrDgE9r+yzOmw5g67DlUKSXHUIWHulQLdmFBYLCvSwRMqHelKg+wCRM706EMmVXFNGQKcgikgdrvBKtjpsKdB1uFKgk6sOAWuvFOjWjMJiQYEelkj5UE8KdB8gUkjqQCRXck0ZAZ2CKCJ1uFKgp56rm0G+Xi3D55kCXSdm5GrN1c13l0vcrbmmw4ICPR3U01QmBboOeA7MyVWHgI5X9ldy1SGg55V9VoctZ9B1uFJIkqsOAWuvFOjWjMJiQYEelkj5UE8KdB8gcqZXByK5kmvKCOgURBGpwxVeyVaHLQW6DlcKdHLVIWDtlQLdmlFYLCjQwxIpH+pJge4DRApJHYjkSq4pI6BTEEWkDlcK9NRzdTPI16tl+DxToOvEjFytubr57nKJuzXXdFhQoKeDeprKpEDXAc+BObnqENDxyv5KrjoE9Lyyz+qw5Qy6DlcKSXLVIWDtlQLdmlFYLCjQwxIpH+pJge4DRM706kAkV3JNGQGdgigidbjCK9nqsKVA1+FKgU6uOgSsvVKgWzMKiwUFelgi5UM9KdB9gEghqQORXMk1ZQR0CqKI1OFKgZ56rm4G+Xq1DJ9nCnSdmJGrNVc3310ucbfmmg4LCvR0UE9TmRToOuA5MCdXHQI6XtlfyVWHgJ5X9lkdtpxB1+FKIUmuOgSsvVKgWzMKiwUFelgi5UM9KdB9gMiZXh2I5EquKSOgUxBFpA5XeCVbHbYU6Dpc/RDou3fvlnHjxsmHH34os2fPljVr1khOTo5UrFhR6tWrJ23btpVu3brJ8ccfL8WKFUvakO+++874mj59uqxYsULWrVsnpUqVkmrVqskRRxwhXbp0kR49ekilSpUK+bnnnnvk3nvvLfT3kiVLmrrgn4YNG0rr1q3lxBNPlI4dO+pAFRE/uKpVLiCOKdADEggfqkGB7gPEsLigQNeJFAeP5KpDQMcr+yu56hDQ88o+q8OWAl2Hq1ch+f7778uAAQNkyZIllhVs1KiRDBs2TE4//fRCthDj/fr1E/izSmXKlJH+/fvLHXfcIfjvSEok0BP5a9KkiRH05557rlWRjj/3ytVxgSHMQIEewqAlqDIFeubE0rIlFOiWiFwZcPDoCptlJnK1ROTKgFxdYbPMRK6WiFwbkK1rdEkzUqDrcPUiJB988EG5/fbbJS8vz1QOs9Jdu3aVww47zMxwb9iwQRYsWCATJkyQqVOnmlnlFi1ayNy5cws05ocffjCi/c8//zR/x6z7+eefL+3bt5caNWrIrl27BGPCadOmyXvvvSfr1683dsjXsmXLuAJ99OjR0qZNG/MZ6rd582ZZu3atzJkzRyZOnCjz5s3Lz9e7d2954YUXLGf3nUTAC1cn5YTZlgI9zNErWHcK9MyJpWVLKNAtEbky4ODRFTbLTORqiciVAbm6wmaZiVwtEbk2IFvX6CjQddAl9epWSL788svSq1cv4xvLz998803p3LlzwrIgiG+44QYjrqMFOpbDQ2RHxPltt90md911l1nWHi9t2bJFhg4dKoMHDzZiO5FAnzFjhnTq1ClhffDSAMIcS+iRBg4cKI888ohvEXDL1bcKhMARBXoIgmSzihToNkFlghkFuk4UOXgkVx0COl7ZX8lVh4CeV/ZZHbacQdfh6kZIrlq1SrBcfdu2bVK2bFkjlDFrbpVQ1muvvSY9e/bMNz377LNl/Pjx5v+xRP3uu++2cmM+nzlzptSpU0cOOuigfPvoJe5WAh2ZIBCxHx375ZG+//57s8/dj+SGqx/lhskHBXqYopW8rhTomRNLy5ZQoFsicmXAwaMrbJaZyNUSkSsDcnWFzTITuVoicm1Atq7RJc1Iga7D1Y2QxGwzZrGRhgwZIjfddJOrys2fP1+aNWtmlqBj6TsOiMvOznblC5mcCnTkefrpp+Xaa681ZXbv3t2sBPAjueHqR7lh8kGBHqZoUaBnTrQ8toQC3SPABNk5eCRXHQI6XtlfyVWHgJ5X9lkdthToOlydCkmIaewLx37u/fbbTzCbXqFCBVeVg7B/9NFHTd6RI0fKZZdd5spPJJMbgb59+3apVauWbNq0yawGwL9LlCjhqR7I7JSr5wJD6IACPYRBS1BlzqBnTiwtW0KBbonIlQEHj66wWWYiV0tErgzI1RU2y0zkaonItQHZukaXNCMFug5Xp0ISs96HH364qcwpp5xirlZzm3CI27fffmuyr1692gh/L8mNQEd5OKBu8uTJpuivv/5ajjrqKC/VMHmdcvVcYAgdUKCHMGgJqkyBnjmxtGwJBbolIlcGHDy6wmaZiVwtEbkyIFdX2CwzkaslItcGZOsaXdKMngR6rojsO/i76KSqIpL8ynFXQhJ7yC+88EKTFwe6PfDAA66Z4n5y3KF+4IEHysqVK137iWR0K9DvvPNOuf/++42bsWPHykUXXeS5LhTo1ggp0K0ZhcWCAj0skfKhnhToPkCM44KDR3LVIaDjlf2VXHUI6Hlln9Vh60mgrxWR6jr1CqzXNThe3bp2ToXkiBEj5PrrrzeOhw8fLtddd511IXEscDBbxYoVzSc4mA0HtHlNbgX6448/bu5V99qm6Po75eq17WHMT4EexqjFrzMFeubE0rIlFOiWiFwZcPDoCptlJnK1ROTKgFxdYbPMRK6WiFwbkK1rdEkzUqA75Kok0DFjfscdd5jKeNk3jhnz2rVrGz8dOnSQzz//3GEDC5u7Fehox+WXX24cYiYdd7t7TRTo1gQp0K0ZhcWCAj0skfKhnhToPkCM44KDR3LVIaDjlf2VXHUI6Hlln9VhS4HukKuSQM/EGfTHHntMBgwYYACjff369XMIu7A5Bbo1Qgp0a0ZhsaBAD0ukfKgnBboPECnQdSCSK7mmjIBOQRSROlzhlWx12FKgO+SqJNAzcQ86ZswHDx5sAL/yyiv5e+wdEi9gToFuTY8C3ZpRWCwo0MMSKR/qSYHuA0QKSR2I5EquKSOgUxBFpA5XCvTUc7U1yOchcQkD41RIZuIp7qeddlr+afRz5syR1q1be+7ITrl6LjCEDmx9d2PahTyNGjUyf12xYkX+NokQNj+jqkyBnlHhTN4YCnSdYHNgTq46BHS8sr+Sqw4BPa/sszpsPc2g61QpI7w6FZK4B7169eqybt06X+9BHzVqlPTu3dsTUzd70HEPOk6R37x5s2kP7kEvXry4p3ogs1OungsMoQMK9BAGLUGVKdAzJ5aWLaFAt0TkyoCDR1fYLDORqyUiVwbk6gqbZSZytUTk2oBsXaNLmpECXYerGyE5cOBAGTp0qKnQo48+mr9/22kNf/75Z2nWrJnJ1rJlS3MnenZ2tlM3+fZuBPpTTz0lffv2NT7OO+88ef31112XH53RDVdfCg6REwr0EAXLoqoU6JkTS8uWUKBbInJlwMGjK2yWmcjVEpErA3J1hc0yE7laInJtQLau0VGg66BL6tWNkMQJ7FhmjNlnzDpDWB966KGWtUdZ2MPes2fPfNuuXbvKBx98YP7/vvvuyz8h3soZTn3HKfAHHXSQa4EOgdiqVSvZsmWL8TF37lxp0aKFVdG2PnfD1ZbjDDKiQM+cYFKgZ04sLVtCgW6JyJUBB4+usFlmIldLRK4MyNUVNstM5GqJyLUB2bpGR4Gug853gQ6HY8aMyV+SjiXvb731lhx33HEJy/rll1/M/elr1641QjiSVq9ebWbP//rrL/OnO++804j0kiVLxvW1bds2M3uP695mz55t8kaSkxn0iRMnyqWXXmqW6iMNGjQo/6A4P8JAgW5NkQLdmlFYLCjQwxIpH+pJge4DxDguOHgkVx0COl7ZX8lVh4CeV/ZZHbZc4q7D1YuQxIz3XXfdlV+xk046STAj3qRJE6lUqZJs2LBBFi5cKJMmTZKPPvpI9u7da2aoowU6MmMG/owzzsgX6fXr15cLLrhA2rdvb/a779q1SzBrP336dBk3bpwR+Ug//PBDQoE+evRoadOmjbHDvvmcnByTD4fATZgwQebNm5dfb9yB/txzz0lWVpZvkL1w9a0SAXdEgR7wADmoHgW6A1hhN6VA14kgB4/kqkNAxyv7K7nqENDzyj6rw5YCXYerVyH57rvvyo033ijLli2zrGDTpk1l2LBhAiEfm5YvXy7XXnutEfNWCcvqsQ/+1ltvlVKlSuWbR8+gW/nA54cddphZVn/OOefYMXdk45Wro8JCakyBHtLAxak2BXrmxNKyJRTolohcGXDw6AqbZSZytUTkyoBcXWGzzESulohcG5Cta3RJM1Kg63D1Q0hihvudd94xV5VhhnrNmjVmX3eFChUEs+FHH320dOvWTTp37mw5S438mCWfMWOGuUZr/fr1Zrk7ZtKPPPJII+579OhhfMemRAK9RIkSxr5ixYrSuHFjc40a/HTo0EEHKk9xt8WVAt0WplAYUaCHIkz+VJIC3R+OsV44eCRXHQI6XtlfyVWHgJ5X9lkdthToOlz9EOg6NQu3V3K1jh8FujWjsFhQoIclUj7UkwLdB4hxXHDwSK46BHS8sr+Sqw4BPa/sszpsKdB1uFJIkqsOAWuvFOjWjMJiQYEelkj5UE8KdB8gUqDrQCRXck0ZAZ2CKCJ1uMIr2eqwpUDX4UqBTq46BKy9UqBbMwqLBQV6WCLlQz0p0H2ASCGpA5FcyTVlBHQKoojU4UqBnnqubgb5erUMn2cKdJ2Ykas1VzffXeRp1KiRcY4zCmrXrm1dEC3UCVCgqyMOTgEU6Dqx4MCcXHUI6HhlfyVXHQJ6XtlnddhyBl2HK4UkueoQsPZKgW7NKCwWFOhhiZQP9aRA9wFiHBccPJKrDgEdr+yv5KpDQM8r+6wOWwp0Ha4U6OSqQ8DaKwW6NaOwWFCghyVSPtSTAt0HiBToOhDJlVxTRkCnIIpIHa7wSrY6bCnQdbhSoJOrDgFrrxTo1ozCYkGBHpZI+VBPCnQfIFJI6kAkV3JNGQGdgigidbhSoKeeq5tBvl4tw+eZAl0nZuRqzdXNd5d70K25psOCAj0d1NNUJgW6DngOzMlVh4COV/ZXctUhoOeVfVaHLWfQdbhSSJKrDgFrrxTo1ozCYkGBHpZI+VBPCnQfIHKmVwciuZJrygjoFEQRqcMVXslWhy0Fug5XCnRy1SFg7ZUC3ZpRWCwo0MMSKR/qSYHuA0QKSR2I5EquKSOgUxBFpA5XCvTUc3UzyNerZfg8U6DrxIxcrbm6+e5yibs113RYUKCng3qayqRA1wHPgTm56hDQ8cr+Sq46BPS8ss/qsOUMug5XCkly1SFg7ZUC3ZpRWCwo0MMSKR/qSYHuA0TO9OpAJFdyTRkBnYIoInW4wivZ6rClQNfhSoFOrjoErL1SoFszCosFBXpYIuVDPSnQfYBIIakDkVzJNWUEdAqiiNThSoGeeq5LliyRnTt3moIbNWok2dnZepXIQM8U6DpBJdfkXMFn4cKFkpeXJ6VKlZKDDz7YViC4xN0WppQbUaCnHHn6CqRA12HPgTm56hDQ8cr+Sq46BPS8ss/qsE3EdfXq1bJx40ZTaPXq1aVq1ao6FchQrxSSOoEl1+Rcc3JyZOXKlcaoUqVKUrNmTVuBoEC3hSnlRhToKUeevgIp0HXYc/BIrjoEdLyyv5KrDgE9r+yzOmwTcd2xY4csXbo0v1AI9AoVKphZuaysLJ3KZJBXCkmdYJJrfK7gsnXrVsGLtb179xqjOnXqSLly5WwFggLdFqaUG1Ggpxx5+gqkQNdhz8EjueoQ0PHK/kquOgT0vLLP6rBNxnXVqlWyefPmAgVDnHO5u71Y7NmzxxgWL17cXgZa2SJAroUxQZRjWXsklSlTRurVq2f7ZRoFuq2ul3IjCvSUI09fgRToOuw5eCRXHQI6XtlfyVWHgJ5X9lkdtsm4YsC/fv16Wbt2rU7hGewV7MAWCWKJqw78CTa5WnNEf6tbt64UK1bM2vgfCwp026hSakiBnlLc6S2MAl2HPweP5KpDQMcr+yu56hDQ88o+q8PWDtddu3aZ5bPbtm0T/DeW0zIlJwBGkRcb1apVcySWyDYxAXKNzwarWiDMy5cvL/vtt5/jF0IU6MH81lGgBzMuKrWiQFfByiuAdLCSK7kqEdBxa0fs6JSc+V7JVifG5EquOgR0vLK/6nClQNfh6tUrBbpXgiHKT4GuEyz+aJCrDgEdr+yv5KpDQM8r+6wOW3IlVx0COl7ZX3W4UqDrcPXqlQLdK0EH+bFM7Pvvv5fZs2ebf+bMmSPLli0zHnCgQ+S/Hbh0ZEqB7giXbWP+aNhG5ciQXB3hsm1MrrZROTIkV0e4HBmTrSNcto3J1TYqR4bk6giXbWNytY3KkSEFuiNcKTOmQE8ZapHOnTvLp59+GrdECvQUBsLnovij4TPQf9yRK7nqENDxyv6qwxVeyVaHLbmSqw4BHa/srzpcKdB1uHr1SoHulaCD/J06dZLPPvvM5KhcubK0bt1aZs2aZQ5goUB3ADJgpvzR0AkIuZKrDgEdr+yvOlwp0MlVj4COZz4LyFWHgI5XCnQdrl69UqB7Jegg//PPPy/lypWTtm3bSoMGDUzO+vXry/LlyynQHXAMmil/jHUiQq7kqkNAxyv7qw5XCnRy1SOg45nPAnLVIaDjlQJdh6tXrxToXgl6zE+B7hFgALLzx1gnCORKrjoEdLyyv+pwpUAnVz0COp75LCBXHQI6XinQdbh69UqB7pWgx/wU6B4BBiA7f4x1gkCu5KpDQMcr+6sOVwp0ctUjoOOZzwJy1SGg45UCXYerV68U6F4JesxPge4RYACy88dYJwjkSq46BHS8sr/qcKVAJ1c9Ajqe+SwgVx0COl4p0HW4evVKge6VoMf8FOgeAQYgO3+MdYJAruSqQ0DHK/urDlcKdHLVI6Djmc8CctUhoOOVAl2Hq1evFOheCXrM76dAxz3nydKKFSukXbt2xmTq1KnmYDom7wR27twp33zzjXF01FFHSalSpbw7pQchV51OQK7kqkNAzyv7rA5bciVXHQI6XtlfdbjioOouXboY50uXLjWHVzOlnwAFeppj4KdAz8rKSnNrWDwJkAAJkAAJkAAJkAAJkEDYCMyePVvatGkTtmpnZH0p0NMcVgr0NAeAxZMACZAACZAACZAACZBAEScwYcIEOeOMM4o4hWA0nwI9Jg579uyREiVKeI7OmDFj5JJLLrH046dAt1rijqUrHTt2NHX66quvpE6dOpb1o4E1gT///NPcbY+Et481a9a0zkQLSwLkaonIlQG5usJmmYlcLRG5NiBb1+iSZiRXctUhoOOV/VWHa/T2V+xHb9CggU5B9OqIAAV6Bgl0q8hDwEdEOb6QtWvXtsrCz20QIFcbkFyYkKsLaDaykKsNSC5MyNUFNJtZyNYmKIdm5OoQmE1zcrUJyqEZuToEZtOcXG2CSrEZBXoc4L/99pvnMGAWtWLFipZ+/JxBtyqMX0IrQu4+J1d33KxykasVIXefk6s7bla5yNWKkPvPydY9u2Q5yZVcdQjoeGV/JVcdAsH0SoGe5rhQoKc5AD4Uzx8NHyDGcUGu5KpDQMcr+6sOV3glWx225EquOgR0vLK/kqsOgWB6pUBPc1wo0NMcAB+K54+GDxAp0HUgkiu5poyAXkF8xuqwJVdy1SGg45X9lVx1CATTKwV6muNCgZ7mAPhQPH80fIBIIakDkVzJNWUE9AriM1aHLbmSqw4BHa/sr+SqQyCYXinQ0xwXCvQ0B8CH4vmj4QNECkkdiORKrikjoFcQn7E6bMmVXHUI6HhlfyVXHQLB9EqBnsK4LFq0SL744osCJd50002yfv16qVq1qgwdOrTAZ6eccooccMABvtWQDzffUBZwRK7kqkNAxyv7K7nqENDzyj6rw5ZcyVWHgI5X9ldy1SEQTK8U6CmMy4svviiXXnqp7RJnzJghnTp1sm1vZciHmxUhd5+TqztuVrnI1YqQu8/J1R03q1zkakXI/edk655dspzkSq46BHS8sr+Sqw6BYHqlQE9hXNIt0FPYVBZFAiRAAiRAAiRAAiRAAiRAAiTgkAAFukNgNCcBEiABEiABEiABEiABEiABEiABDQIU6BpU6ZMESIAESIAESIAESIAESIAESIAEHBKgQHcIjOYkQAIkQAIkQAIkQAIkQAIkQAIkoEGAAl2DKn2SAAmQAAmQAAmQAAmQAAmQAAmQgEMCFOgOgdGcBEiABEiABEiABEiABEiABEiABDQIUKBrUKVPEiABEiABEiABEiABEiABEiABEnBIgALdITCakwAJkAAJkAAJkAAJkAAJkAAJkIAGAQp0Dar0SQIkQAIkQAIkQAIkQAIkQAIkQAIOCVCgOwRGcxIgARIgARIgARIgARIgARIgARLQIECBrkE1pD63bt0q33//vcyePdv8M2fOHFm2bJlpTb169fL/O6TNU6n277//LiNGjJBJkyYJ/rtUqVLSoEED6d69u1xzzTVStmxZlXIz0emaNWsK9D30v/Xr15umXnzxxfLiiy9mYrNT0iZ8rz/66CP5/PPP5eeffxawLlGihBx44IHSrl07ueyyy+TYY49NSV0ypZCcnByZPHmyeU5+++23snLlSlm7dq38/fffUqlSJTnssMPktNNOM2yrVq2aKc1OaztuvvlmGTJkSH4dZsyYIZ06dUprncJUeFZWlq3qHnfccfLpp5/asqVRQQLr1q2T0aNHy/vvvy+LFy+WjRs3mu9/nTp1pGPHjnLOOefIMcccQ2wWBPC9/uyzzxxx4vPAES7ZtWuXvPzyy/L222/Ljz/+KBs2bDDjglq1akn79u3liiuukKOPPtqZU1r7RoAC3TeU4XfUuXPnhD/KFOiF4wtRfuGFF8rmzZvjBr9x48ZmAH/wwQeHv3OkoAXJBo8U6O4DgMH2zJkzLR1cdNFFMnLkSClZsqSlLQ1Epk2bJl26dLFEsf/++8srr7wiJ598sqUtDRITwACydevWsmfPHgp0lx2FAt0lOJvZIHSuvvrq/BfL8bJ17dpVxo8fb9Nj0TVzKtCLFStmJkkgLpmsCaxYsUJOP/10mTdvXlLj/v37y6OPPip2nx3WJdPCLgEKdLukioBd9AOxcuXKZjA0a9Yswcw6BXrBDoDBImYet2/fLuXKlZNBgwYJXnBg9uyNN96QF154wWQ49NBDzQwbbJiSE4j+AcBsQ5MmTWTKlCkmEwW6+96DFR2YycFs+bnnnmtmyuvWrSt79+4132/8+GL2F+n888+X1157zX1hRSgnBHrv3r3N975Vq1ZmhqxmzZqSm5srf/zxh7zzzjvy7rvvGs546YHnQPPmzYsQIf+aCqaYyQHD6tWrmxUgSJwxc8Y48oyFiMQKr0Rpv/32k4MOOsiZ8yJuPXbsWLn00kvN9x99FIw7dOggVapUkdWrV5tn8IQJE6RixYpmxpIpOYGlS5fKtm3bkhr98ssv0qNHD2ODl6WR8QLZJieAl5xHHnlkvjjH79KAAQMEk0pbtmyRL774wowLIvwfeeQRGThwILGmmAAFeoqBB7m4559/3gjJtm3bmmXaSPXr15fly5dToMcELrLaoHjx4mZ2MnbJGpZhYjkm0r333it33XVXkEMfiLrdfffd0qZNG/NPjRo1zJaKyCCRAt19iM444wzp1auXdOvWTbKzsws5wpJMLGdbuHCh+Qz9mcvdrXlDeMfjGZ0TM2Vnn322+ROWto4bN87aMS0KEXj88ccFMzl44QmeDz74oLGhQHfWWSICHc/ae+65x1lmWick8Ouvv8oRRxwhO3fuNM/OiBCPlwHLirlKyZ/OdMsttwjEIxKWavfs2dMfxxnuBb9D//nPf0wrMXbF1rfY37LvvvvOfLZ7927BhB1eimK8y5Q6AhToqWMdypIo0AuHDbM4eImBdOWVV8qzzz5byAhv0Q8//HDBDzcebn/99ZfZ28NknwAFun1WXi0nTpwoZ555pnFz3XXXyfDhw726ZP5/CGAlyG+//SZY6o496kzOCGApJvbzYyUXBDn2RuOlJxIFujOWFOjOeNm1PvHEE+WTTz4x33H85uPfTLoEMMbCSjCs/sLEEsZYPPPHHnPMlj/22GPG+IMPPsj/7Y/NjZfK7733nvkzlsJjTMuUOgIU6KljHcqSKNALh+3222+XwYMHmw++/vprOeqoo+LG9qGHHjJL35Gw9MrOftVQdhKlSlOgK4GN4xbip3z58uYT7EuDYGfyhwC2CmE2AoNILB9kckYAL47QHyOraDDzS4HujGHEmgLdHbdkufDyDS/hkNA3sTqBSZ/A1KlT5aSTTjIFXXLJJTJmzBj9QjOkhL59+8pTTz1lWoNDY5s2bRq3ZVjWPnToUPMZDkLFVi6m1BGgQE8d61CWRIFeOGw4iRVLgrBPb9OmTQmX/WB/L/apI2HFdGwjAAARzUlEQVSJe2RQGcqOkIZKU6CnDjpOb42cNA5BhLfqTN4JYDatWbNmZh86hDpW3zDZJ/DWW2+ZPabYxwshVK1aNSOCKNDtM4y2pEB3xy1Zrvvuuy9/C9v8+fPNag8knN6O7UPou7zFwX/uONQUh28iTZ8+3ZwFwmSPAG4euv76642xnRl0PDcw1q1QoYK9AmjlCwEKdF8wZq4TCvTCscUgET+8LVq0kLlz5yYMPn6g8eOMhMO5MNhksk+AAt0+K6+WWMaG5WxIeGse2dfn1W9RzI+DI7HsEvtQwRFLL5G4R9JZb8CAEDOTOGALh2726dPHOKBAd8Yx2joi0CEicVAUTr3GvtIDDjjAvEzGTCSFjjO+WHGE21pw+Bt+83HIJr73P/30U74jnKWCFSA33ngjD4x1hjeuNVZ8oc/iEDMsc8dYgaeM2weLrVY4ZwpXheL8GVxnF7sH/YcffjAHc+LMBB4ea5+tn5YU6H7SzEBfFOgFg7pjxw4pU6aM+aOdpcBY1oofETzoMKPOZJ8ABbp9Vl4ssZcPh8HMnj3buMEsL2Z7mewTePHFF80JzonSTTfdZAbtHETaZ4o7eCHMIRxxqnCEHQW6fYaxlnb63//93/8J+jMEJ5M1AYhv/FbhhT1ObY8sHY6XE3t4P/74Y3OjBpN7Ai+99JJ5mYSELYf333+/e2dFNCdeyuOaYNw8hAMOb7jhBmnUqJE56+PLL780p7hjS1bLli3lww8/NC9EmFJLgAI9tbxDVxoFesGQ4c0jrlBBwtJLXKmWLOE0cpx+iR9mq/smQ9c5lCtMga4M+B/3+CGGgETCCdm4GozJGYFEAh2DGxwimeicCmelFB1rCHJsJcKszvfff2+2CUQSBbr7foBtWWeddZaccMIJ5kR8vEDGbxpm0NBP169fb5wfd9xxgj2+PNjUmjVeZGAmslSpUuYU90qVKgnOn8GKJCwJxu8+trhB5CDhhRO2yOHebiZ3BNB/sawdacGCBUZYMjkngGvqhg0bJqNHj5a8vLwCDjB2xSn5eFGK5wZT6glQoKeeeahKpEAvGC6cKIwlVUjYA4W7T5Ml2CLPIYccIosWLQpV7NNdWQp0/QhgYI4TiLHcFS+esCwTP8xMzghgOTbuPkfCjATuPMaWFsxS4LuPa8Jw3R2TNQEsqcSLDezfj7fdggLdmmEiC/RTCMh4CVsxTj31VMHSViTc5IAbHZiSE8AWAZwxgYQXSni5hBVz0QmrlPD9j4h03IMeueaKfJ0RwHO2Xr165r55rkx0xi7aGten4SwPrFLCJFK8hCtvceghVosypZ4ABXrqmXsqEQNpP95q48TLyBKhZBWiQC9IhzPonrqvo8wU6I5wOTbGgUa4sxf7JjH7g6WXmDlj8o8A9p1j7ymWFo8aNcrWM9e/0sPpKSLA8XITMzyxszcU6HpxXbJkidn3j5ck2KP6v//9T6+wDPEc2caG5px33nny+uuvx20ZnreRa6owu467qJmcE4i+HeeZZ56Rq666yrmTIp4D2y5PO+00mTlzpnmphLMRsEXr4IMPFmzj/Oabb+S///1v/tYiXMkWOVSuiKNLafMp0FOK23thFOjeGXrxwD3oXug5y0uB7oyXE+ulS5ea/ZKrVq0yP9CY0cHydib/CWArDGbTITSxmqZy5cr+F5IhHnFSO/byQiC+//77Zjl2bKJA1w02ZnonTZpkCsFhh9wvnZx3zZo1zUGGSNgb3atXr4QZateubZjWqVPHHNDH5JwArgTDizu8VP7zzz/5PHWO0Gxpw9Y2JGzPwkvk2AStgWvsZsyYYbZjYGVN8+bNXZTGLG4JUKC7JZfGfBjEeE34UbFzCAxn0AuT5inuXnufvfwU6PY4ObWCKMfMOWbLMLOLH+hkg0qn/mlfkABOdcZhPEivvvqqXHDBBUSUgMCVV14pzz//vJnJeeCBB+JavfPOO/mzj3feeWf+tVa4HpB7Jb13rZtvvlmGDBliHOHgSCxzZUpMoG3btvnXJ37yySdy/PHHJzTGYZxff/21EZd42c/kjADu4o70x27dugmeBUzOCGCv+f777y+4WhV797GHP1HCYXF4kY+EQ+Qwk86UOgIU6KljHcqSKNALh433oKemK1Og+88Z1wNiGTtmIJCefPJJufbaa/0viB7zCeCwLcxEIA0ePFgGDRpEOgkIYNsVZiHdJKwKwe8VkzcC2Pc/dOhQ44QC3ZollgbjJSfSlClTpEuXLgkzRcQ8XiThtGwmZwRwJsITTzxhMiW7v9uZ16JljdUemKBDsjroOHrF6CmnnJJ/hkLRIpa+1lKgp499KEqmQC8cpttuu00efPBB8wHehic6oTl6rxT290YG6aEIfAAqSYHubxA2b95sZndwKjYS+idOaWXSJRB9wvuIESOkX79+ugWG2DsFevqDF7nXGzXBgVy1atVKf6UCXAOc59O7d29TQ6s90Zi5xEn5VjOXAW5u2qqGQ83QF3EOEFYxYiUYDuhjckYAL+nBD8lqFQKuWcNNBEjY+jJhwgRnhdHaEwEKdE/4Mj8zBXrhGGNWISLKsSQT19PEJpwwigNhcBIxTs3FKZl+HO6X+T3u3xZSoPsX7e3bt5sXRFiyhsS7Y/1ja+UpWvBgP1+nTp2ssvDzJAS4B12ve2DbC65fgxjCNgPcRsCUnAAEN2YkwQyz55hFj5dwY0bku3/ZZZfJyJEjidYBAcyYd+3a1eTAgWW4GYPJOQGMTXEOCq4GxPkSy5cvT/iiY+LEiYKtQ0h4sYwXzEypI0CBnjrWoSyJAj1+2CLL3PEGFydhYm9ZdMIePuzlQ8I1FRhUMjkjQIHujFciaxy4hR/ZyMCRgxt/uGJmHKc2ly5dOqFD7NkbMGCA+RzPUpyKzVkfb/wp0N3xw+wXrlFL1P9ir1nDIVKRvuuuxKKT65prrjGz50g4xR3PheiEmUiMGebOnWv+zK0DzvsGrqWLnHz/3XffyZFHHuncCXMYAjgHJXLbAJ6nGKPGJtzugv3nke1wXAWa+s5DgZ565oEtEfd04w7P6ITTHvGGuGrVqvn70iKfY0/KAQccENj2aFYMJ1q2b9/e3HmMa1aw7L1z587m/9944w1z0BESlrLhYJPy5ctrVicjfKPvRd8Vj6VY2A+JBNZ9+vQp0E471wRmBBiPjcAytnfffdd4wRJ3zDzgcLhEqWTJkqbfMiUnAMGNgTf4YiCD+87xLMDf5s2bZw6Ei6xYAFOcjI0755m8EaBAd8cP/RWzvOiveKGM/y9TpozgOfvpp5+alWD4rUdCf542bZo5zIzJmgCWXbdu3dqczI4XILj6C1epYXkwngUPP/ywRA73vfrqq+Xpp5+2dkqLfAIQi1ilsHPnTrMyEUyZ3BNAX2zVqpVgZR0SXuDjJPfINWvYuolxQuSmgRNOOME8D5hSS4ACPbW8A11a9F5JOxUt6ss1MSPRs2dPs1QoXoLIwaAc98kyWRNwuv8Up5EyWRNIJsbj5a5Xr55g9QJTcgKR1UVWnHC10ujRo5MeHmXlg5//S4AC3V1vsNtfIeCx/Bpbs5jsE8B2NlwLGP2SOTY39qrjRQi3u9nnCksww4sNpEceeST/xb0zL7SOJgDBff7555sXdMkSXurjtHxeD5r6/kOBnnrmgS2RAt15aLB/Z/jw4UaI40AdzJRBkJ977rnSt29fKVu2rHOnRTQHBbpO4CnQdbhify4GOXhRicE5lghjBhJL3mvUqCEtW7Y0B+t0796dzwEfQ0CB7g4m9kDjn1mzZpkrFjEwx8tlrPrAvdzt2rUzs2ix27XclVY0c23bts0sdYegwXYWnNRevXp1swIM59VglR2TcwLg99VXX0l2draZ1cXeaSbvBPB7NWrUKHM6+/z582XTpk1mBQhWxuI6OyyFx0snp2MI7zWjBxCgQGc/IAESIAESIAESIAESIAESIAESIIEAEKBAD0AQWAUSIAESIAESIAESIAESIAESIAESoEBnHyABEiABEiABEiABEiABEiABEiCBABCgQA9AEFgFEiABEiABEiABEiABEiABEiABEqBAZx8gARIgARIgARIgARIgARIgARIggQAQoEAPQBBYBRIgARIgARIgARIgARIgARIgARKgQGcfIAESIAESIAESIAESIAESIAESIIEAEKBAD0AQWAUSIAESIAESIAESIAESIAESIAESoEBnHyABEiABEiABEiABEiABEiABEiCBABCgQA9AEFgFEiABEiABEiABEiABEiABEiABEqBAZx8gARIgARIgARIgARIgARIgARIggQAQoEAPQBBYBRIgARIgARIgARIgARIgARIgARKgQGcfIAESIAESIAESIAESIAESIAESIIEAEKBAD0AQWAUSIAESIAESIAESIAESIAESIAESoEBnHyABEiABEiABEiABEiABEiABEiCBABCgQA9AEFgFEiABEiABEiABEiABEiABEiABEqBAZx8gARIgARIgARIgARIgARIgARIggQAQoEAPQBBYBRIgARIgARIgARIgARIgARIgARKgQGcfIAESIAESIAESIAESIAESIAESIIEAEKBAD0AQWAUSIAESIAESIAESIAESIAESIAESoEBnHyABEiABEiABEiABEiABEiABEiCBABCgQA9AEFgFEiABEiABEiABEiABEiABEiABEqBAZx8gARIgARIgARIgARIgARIgARIggQAQoEAPQBBYBRIgARIgARIgARIgARIgARIgARKgQGcfIAESIAESIAESIAESIAESIAESIIEAEKBAD0AQWAUSIAESIAESIAESIAESIAESIAESoEBnHyABEiABEiABEiABEiABEiABEiCBABCgQA9AEFgFEiABEiABEiABEiABEiABEiABEqBAZx8gARIgARIgARIgARIgARIgARIggQAQoEAPQBBYBRIgARIgARIgARIgARIgARIgARKgQGcfIAESIAESIAESIAESIAESIAESIIEAEKBAD0AQWAUSIAESIAESIAESIAESIAESIAESoEBnHyABEiABEiABEiABEiABEiABEiCBABCgQA9AEFgFEiABEiABEiABEiABEiABEiABEqBAZx8gARIgARIgARIgARIgARIgARIggQAQoEAPQBBYBRIgARIgARIgARIgARIgARIgARKgQGcfIAESIAESIAESIAESIAESIAESIIEAEKBAD0AQWAUSIAESIAESIAESIAESIAESIAESoEBnHyABEiABEiABEiABEiABEiABEiCBABCgQA9AEP6//TqmAQAAQBjm3/Vs7KgDUngQgQABAgQIECBAgAABAgQIOOg2QIAAAQIECBAgQIAAAQIEBgIO+qAEEQgQIECAAAECBAgQIECAgINuAwQIECBAgAABAgQIECBAYCDgoA9KEIEAAQIECBAgQIAAAQIECDjoNkCAAAECBAgQIECAAAECBAYCDvqgBBEIECBAgAABAgQIECBAgICDbgMECBAgQIAAAQIECBAgQGAg4KAPShCBAAECBAgQIECAAAECBAg46DZAgAABAgQIECBAgAABAgQGAg76oAQRCBAgQIAAAQIECBAgQICAg24DBAgQIECAAAECBAgQIEBgIOCgD0oQgQABAgQIECBAgAABAgQIOOg2QIAAAQIECBAgQIAAAQIEBgIO+qAEEQgQIECAAAECBAgQIECAgINuAwQIECBAgAABAgQIECBAYCDgoA9KEIEAAQIECBAgQIAAAQIECDjoNkCAAAECBAgQIECAAAECBAYCDvqgBBEIECBAgAABAgQIECBAgICDbgMECBAgQIAAAQIECBAgQGAg4KAPShCBAAECBAgQIECAAAECBAg46DZAgAABAgQIECBAgAABAgQGAg76oAQRCBAgQIAAAQIECBAgQICAg24DBAgQIECAAAECBAgQIEBgIOCgD0oQgQABAgQIECBAgAABAgQIOOg2QIAAAQIECBAgQIAAAQIEBgIO+qAEEQgQIECAAAECBAgQIECAgINuAwQIECBAgAABAgQIECBAYCDgoA9KEIEAAQIECBAgQIAAAQIECDjoNkCAAAECBAgQIECAAAECBAYCAYW6ve8xRSlPAAAAAElFTkSuQmCC\" width=\"500\">"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-03-13T03:40:42.221300Z",
          "start_time": "2021-03-13T03:40:42.214212Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "_draft": {
      "nbviewer_url": "https://gist.github.com/15d0b847d88cf3c2b8011ff3368c89ad"
    },
    "gist": {
      "id": "15d0b847d88cf3c2b8011ff3368c89ad",
      "data": {
        "description": "IK_BWS_FABRIK_CCD.ipynb",
        "public": true
      }
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3",
      "language": "python"
    },
    "language_info": {
      "name": "python",
      "version": "3.8.5",
      "mimetype": "text/x-python",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "pygments_lexer": "ipython3",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
    },
    "nteract": {
      "version": "0.28.0"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 4
}