ADSP_11_Complex_S_and_S.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AsJyFbr_bhFU"
      },
      "source": [
        "<center>\n",
        "    <img src=\"https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/adsp_logo.png?raw=1\">\n",
        "</center>\n",
        "\n",
        "### Prof. Dr. -Ing. Gerald Schuller <br> Jupyter Notebook: Renato Profeta\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1j2dnI2FbhFZ"
      },
      "source": [
        "# Complex Signals and Filters, Hilbert Transform"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "hide_input": true,
        "id": "24bp8R0vbhFa",
        "outputId": "58cab6b6-8f3d-4334-9f1f-0682d934e8cb"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/_f1rULreCok\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "%%html\n",
        "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/_f1rULreCok\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oM7WBqMjbhFd"
      },
      "source": [
        "Imagine we would like to know the precise, **instantaneous, amplitude of a sinusoid**.\n",
        "\n",
        "Just looking at the function this might not be so easy, we would have to determine the maximum or minimum, and depending on the sinusoidal frequency this might take some time, during which the amplitude also might have changed. But if we have a **complex exponential** with samples\n",
        "\n",
        "$$\\large\n",
        "x(n)=A \\cdot e^{j \\Omega n}= A \\cdot cos(\\Omega n)+ j A \\cdot  sin(\\Omega n)\n",
        "$$\n",
        "(we know x(n) but not A)\n",
        "\n",
        "We can easily determine the amplitude A only knowing one complex valued sample x(n) by taking the magnitude of this complex exponential,\n",
        "    \n",
        "$$\\large\n",
        "A= \\sqrt{\\Re(x(n))^2+\\Im(x(n))^2}=\n",
        "$$\n",
        "\n",
        "$$\\large\n",
        "=\\sqrt{((A \\cdot cos(\\Omega n))^2 + (A \\cdot sin(\\Omega n))^2)\n",
        "}$$\n",
        "\n",
        "Observe that this computation of A is independent of the time index n, so it can be done at **every time instance**.\n",
        "\n",
        "So if we not only have the sine or cosine function in itself, but both, we can easily compute the instantaneous amplitude in this way. This means, instead of just having the sinusoidal function, we also have the **90 degrees phase shifted** version of it, to compute the amplitude. The problem is, if we only have one part (e.g. the real part) how do we get this 90 degrees phase shifted version?\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "hide_input": true,
        "id": "wOPJroWxbhFd",
        "outputId": "42501d28-d6b4-4114-e0fc-464933fba52c"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/uEaEv2qY5vM\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "%%html\n",
        "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/uEaEv2qY5vM\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vKoBmyJbbhFe"
      },
      "source": [
        "For example, look at the sine function. It already consists of 2 complex exponentials,\n",
        "\n",
        "$$\\large\n",
        "sin(\\Omega n)=\\frac{1} {2j} (e^{j\\Omega n} - e^{-j\\Omega n})\n",
        "$$\n",
        "\n",
        "we just have one exponential too many. If we look at it in the Fourier Domain, we see that one exponential is at positive frequencies, and the other is at negative frequencies. If we could remove one of the 2 exponentials, for instance at the negative frequencies, we would have reached our goal of obtaining a complex exponential for amplitude computations. So what we need is a filter, which **attenuates the negative frequencies**, and leaves the **positive frequencies unchanged**!\n",
        "\n",
        "So how do we obtain such a filter? First we formulate our requirement in the **frequency domain** (the DTFT domain):\n",
        "\n",
        "\n",
        "$$\\large\n",
        "H(\\Omega)=\\left \\lbrace \\substack { 1 \\textrm{  for } \\Omega > 0 \\\\ 0 \\textrm{  for  } \\Omega <0 }  \\right \\rbrace\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "hide_input": true,
        "id": "GZgdpK52bhFf",
        "outputId": "95adbd3a-90d1-499b-a3ba-9e75dae089de"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/ZDnIH8Ns0GQ\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "%%html\n",
        "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/ZDnIH8Ns0GQ\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wt7xiszfbhFf"
      },
      "source": [
        "We could multiply our signal spectrum with this  frequency domain formulation (which is often not practical), or in the time domain convolve with the **impulse response** of the resulting filter obtained with **inverse DTFT**,\n",
        "\n",
        "$$\\large\n",
        "h(n)=\\frac{1}{2\\pi}\\int_{0}^{\\pi}1\\cdot e^{j\\Omega n}d\\Omega =\n",
        "$$\n",
        "\n",
        "for $n\\neq 0$ this becomes\n",
        "\n",
        "$$\\large\n",
        "=\\frac{1}{2\\pi}\\left(\\frac{1}{jn}\\cdot e^{j\\pi n} -\\frac{1}{jn}\\right)=\n",
        "$$\n",
        "\n",
        "$$\\large\n",
        "=\\frac{1 } {2 \\pi} \\left( \\frac{-j} {n} \\cdot (-1)^n + \\frac{j} {n} \\right)=\n",
        "$$\n",
        "\n",
        "$$\\large\n",
        "=\\left \\lbrace \\substack{\\frac{j} {\\pi n}\\textrm{ for n odd }\\\\\n",
        "0\\textrm{ for n even} }  \\right \\rbrace\n",
        "$$\n",
        "\n",
        "For n=0 this inverse DTFT integral becomes\n",
        "\n",
        "$$\\large\n",
        "h(0)=\\frac{1}{2\\pi}\\cdot \\pi=\\frac{1}{2}\n",
        "$$\n",
        "\n",
        "\n",
        "Hence the resulting impulse response of this one-sided filter becomes\n",
        "\n",
        "$$\\large\n",
        "h(n) = \\frac{1} {2} \\cdot \\delta(n) + \\left \\lbrace \\substack{\\frac{j}  {\\pi n} \\textrm{for n odd}  \\\\  0 \\textrm{ for n even } }  \\right \\rbrace\n",
        "$$\n",
        "\n",
        "This is now the **resulting impulse response** (time domain) of our **filter which passes all the positive frequencies and attenuates the negative frequencies**.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mkEjG8-AbhFg"
      },
      "source": [
        "Here we can see that the first part with the **delta function** represents the **real part**, which is the signal itself (signal convolved with the delta impulse), except for a factor of 2. The second part represents the imaginary part of our one-sided signal (pos. frequencies). Multiplying both parts with this factor of 2 for simplicity, we obtain the following structure,\n",
        "<center>\n",
        "    <img src='https://github.com/GuitarsAI/ADSP_Tutorials/blob/master/images/Lecture11-1.PNG?raw=1' width=\"600\">\n",
        "</center>\n",
        "\n",
        "\n",
        "where the **Hilbert Transformer**\n",
        "$h_H(n)$ is\n",
        "\n",
        "$$\\large\n",
        "h_H(n)=\\left \\lbrace \\substack{ \\frac{2}  {\\pi n} \\textrm{ for n odd }  \\\\   \\textrm{ 0 for n even }}  \\right \\rbrace\n",
        "$$\n",
        "\n",
        "(See also: Oppenheim, Schafer, “Discrete-Time Signal Processing”). The x(n) is our real valued signal. Observe that only this part, which creates the imaginary signal part, is the Hilbert Transformer. We can use it to construct a filter that suppresses the negative frequencies.\n",
        "\n",
        "This means, we take our **original signal** (the sinusoid) and **define it as our real part**. Then we take the **Hilbert filtered signal**, filtered with the above $h_H(n)$, and define it as our **imaginary part**. Then both together have a **one-sided, positive only spectrum**! That also means, our Hilbert transform filter is our **90 degrees phase shifter** that we where looking for!\n",
        "\n",
        "You can also imagine, if the real part is a $cos$ signal, then the Hilbert Transformer generates the $j\\cdot sin$ part."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "hide_input": true,
        "id": "EmcjlO0_bhFh",
        "outputId": "cc2ee346-324c-4c7a-c568-5f353a0b20fe"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/t6FXEhn4x04\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "%%html\n",
        "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/t6FXEhn4x04\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P18JZUQubhFi"
      },
      "source": [
        "#### **Python example**: Plot the Hilbert transformer for n= -10 ..10:\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "hide_input": true,
        "id": "0Bbaz6pFbhFi",
        "outputId": "b7e17be8-1792-4df1-a324-775032f505a1"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/JiJIKy_GmbQ\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "%%html\n",
        "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/JiJIKy_GmbQ\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "esyLXPVUbhFi",
        "outputId": "2088011e-dcd7-446b-e80d-5deadcf3bdca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 527
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-2-979b862d1462>:11: MatplotlibDeprecationWarning: The 'use_line_collection' parameter of stem() was deprecated in Matplotlib 3.6 and will be removed two minor releases later. If any parameter follows 'use_line_collection', they should be passed as keyword, not positionally.\n",
            "  plt.stem(np.arange(-10,10),h,use_line_collection=True)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "/* Put everything inside the global mpl namespace */\n",
              "/* global mpl */\n",
              "window.mpl = {};\n",
              "\n",
              "mpl.get_websocket_type = function () {\n",
              "    if (typeof WebSocket !== 'undefined') {\n",
              "        return WebSocket;\n",
              "    } else if (typeof MozWebSocket !== 'undefined') {\n",
              "        return MozWebSocket;\n",
              "    } else {\n",
              "        alert(\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",
              "\n",
              "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
              "    this.id = figure_id;\n",
              "\n",
              "    this.ws = websocket;\n",
              "\n",
              "    this.supports_binary = this.ws.binaryType !== undefined;\n",
              "\n",
              "    if (!this.supports_binary) {\n",
              "        var warnings = document.getElementById('mpl-warnings');\n",
              "        if (warnings) {\n",
              "            warnings.style.display = 'block';\n",
              "            warnings.textContent =\n",
              "                'This browser does not support binary websocket messages. ' +\n",
              "                'Performance may be slow.';\n",
              "        }\n",
              "    }\n",
              "\n",
              "    this.imageObj = new Image();\n",
              "\n",
              "    this.context = undefined;\n",
              "    this.message = undefined;\n",
              "    this.canvas = undefined;\n",
              "    this.rubberband_canvas = undefined;\n",
              "    this.rubberband_context = undefined;\n",
              "    this.format_dropdown = undefined;\n",
              "\n",
              "    this.image_mode = 'full';\n",
              "\n",
              "    this.root = 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_device_pixel_ratio', {\n",
              "                device_pixel_ratio: fig.ratio,\n",
              "            });\n",
              "        }\n",
              "        fig.send_message('refresh', {});\n",
              "    };\n",
              "\n",
              "    this.imageObj.onload = function () {\n",
              "        if (fig.image_mode === 'full') {\n",
              "            // Full images could contain transparency (where diff images\n",
              "            // almost always do), so we need to clear the canvas so that\n",
              "            // there is no ghosting.\n",
              "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
              "        }\n",
              "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
              "    };\n",
              "\n",
              "    this.imageObj.onunload = function () {\n",
              "        fig.ws.close();\n",
              "    };\n",
              "\n",
              "    this.ws.onmessage = this._make_on_message_function(this);\n",
              "\n",
              "    this.ondownload = ondownload;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_header = function () {\n",
              "    var titlebar = 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",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
              "\n",
              "mpl.figure.prototype._init_canvas = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
              "    canvas_div.setAttribute('tabindex', '0');\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",
              "            'z-index: 2;'\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(\n",
              "        'style',\n",
              "        'box-sizing: content-box;' +\n",
              "            'pointer-events: none;' +\n",
              "            'position: relative;' +\n",
              "            'z-index: 0;'\n",
              "    );\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",
              "\n",
              "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
              "        'canvas'\n",
              "    ));\n",
              "    rubberband_canvas.setAttribute(\n",
              "        'style',\n",
              "        'box-sizing: content-box;' +\n",
              "            'left: 0;' +\n",
              "            'pointer-events: none;' +\n",
              "            'position: absolute;' +\n",
              "            'top: 0;' +\n",
              "            'z-index: 1;'\n",
              "    );\n",
              "\n",
              "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
              "    if (this.ResizeObserver === undefined) {\n",
              "        if (window.ResizeObserver !== undefined) {\n",
              "            this.ResizeObserver = window.ResizeObserver;\n",
              "        } else {\n",
              "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
              "            this.ResizeObserver = obs.ResizeObserver;\n",
              "        }\n",
              "    }\n",
              "\n",
              "    this.resizeObserverInstance = new this.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",
              "            /* This rescales the canvas back to display pixels, so that it\n",
              "             * appears correct on HiDPI screens. */\n",
              "            canvas.style.width = width + 'px';\n",
              "            canvas.style.height = height + 'px';\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 (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
              "                fig.request_resize(width, height);\n",
              "            }\n",
              "        }\n",
              "    });\n",
              "    this.resizeObserverInstance.observe(canvas_div);\n",
              "\n",
              "    function on_mouse_event_closure(name) {\n",
              "        /* User Agent sniffing is bad, but WebKit is busted:\n",
              "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
              "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
              "         * The worst that happens here is that they get an extra browser\n",
              "         * selection when dragging, if this check fails to catch them.\n",
              "         */\n",
              "        var UA = navigator.userAgent;\n",
              "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
              "        if(isWebKit) {\n",
              "            return function (event) {\n",
              "                /* This prevents the web browser from automatically changing to\n",
              "                 * the text insertion cursor when the button is pressed. We\n",
              "                 * want to control all of the cursor setting manually through\n",
              "                 * the 'cursor' event from matplotlib */\n",
              "                event.preventDefault()\n",
              "                return fig.mouse_event(event, name);\n",
              "            };\n",
              "        } else {\n",
              "            return function (event) {\n",
              "                return fig.mouse_event(event, name);\n",
              "            };\n",
              "        }\n",
              "    }\n",
              "\n",
              "    canvas_div.addEventListener(\n",
              "        'mousedown',\n",
              "        on_mouse_event_closure('button_press')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'mouseup',\n",
              "        on_mouse_event_closure('button_release')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'dblclick',\n",
              "        on_mouse_event_closure('dblclick')\n",
              "    );\n",
              "    // Throttle sequential mouse events to 1 every 20ms.\n",
              "    canvas_div.addEventListener(\n",
              "        'mousemove',\n",
              "        on_mouse_event_closure('motion_notify')\n",
              "    );\n",
              "\n",
              "    canvas_div.addEventListener(\n",
              "        'mouseenter',\n",
              "        on_mouse_event_closure('figure_enter')\n",
              "    );\n",
              "    canvas_div.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",
              "    canvas_div.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",
              "\n",
              "mpl.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",
              "\n",
              "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
              "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
              "    // which will in turn request a refresh of the image.\n",
              "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_message = function (type, properties) {\n",
              "    properties['type'] = type;\n",
              "    properties['figure_id'] = this.id;\n",
              "    this.ws.send(JSON.stringify(properties));\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_draw_message = function () {\n",
              "    if (!this.waiting) {\n",
              "        this.waiting = true;\n",
              "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    var format_dropdown = fig.format_dropdown;\n",
              "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
              "    fig.ondownload(fig, format);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
              "    var size = msg['size'];\n",
              "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
              "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
              "        fig.send_message('refresh', {});\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.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",
              "\n",
              "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
              "    // Updates the figure title.\n",
              "    fig.header.textContent = msg['label'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
              "    fig.canvas_div.style.cursor = msg['cursor'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
              "    fig.message.textContent = msg['message'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
              "    // Request the server to send over a new figure.\n",
              "    fig.send_draw_message();\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
              "    fig.image_mode = msg['mode'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.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",
              "\n",
              "mpl.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",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Called whenever the canvas gets updated.\n",
              "    this.send_message('ack', {});\n",
              "};\n",
              "\n",
              "// A function to construct a web socket function for onmessage handling.\n",
              "// Called in the figure constructor.\n",
              "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
              "    return function socket_on_message(evt) {\n",
              "        if (evt.data instanceof Blob) {\n",
              "            var img = evt.data;\n",
              "            if (img.type !== 'image/png') {\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",
              "                img.type = 'image/png';\n",
              "            }\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",
              "                img\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",
              "function getModifiers(event) {\n",
              "    var mods = [];\n",
              "    if (event.ctrlKey) {\n",
              "        mods.push('ctrl');\n",
              "    }\n",
              "    if (event.altKey) {\n",
              "        mods.push('alt');\n",
              "    }\n",
              "    if (event.shiftKey) {\n",
              "        mods.push('shift');\n",
              "    }\n",
              "    if (event.metaKey) {\n",
              "        mods.push('meta');\n",
              "    }\n",
              "    return mods;\n",
              "}\n",
              "\n",
              "/*\n",
              " * return a copy of an object with only non-object keys\n",
              " * we need this to avoid circular references\n",
              " * https://stackoverflow.com/a/24161582/3208463\n",
              " */\n",
              "function simpleKeys(original) {\n",
              "    return Object.keys(original).reduce(function (obj, key) {\n",
              "        if (typeof original[key] !== 'object') {\n",
              "            obj[key] = original[key];\n",
              "        }\n",
              "        return obj;\n",
              "    }, {});\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.mouse_event = function (event, name) {\n",
              "    if (name === 'button_press') {\n",
              "        this.canvas.focus();\n",
              "        this.canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    // from https://stackoverflow.com/q/1114465\n",
              "    var boundingRect = this.canvas.getBoundingClientRect();\n",
              "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
              "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
              "\n",
              "    this.send_message(name, {\n",
              "        x: x,\n",
              "        y: y,\n",
              "        button: event.button,\n",
              "        step: event.step,\n",
              "        modifiers: getModifiers(event),\n",
              "        guiEvent: simpleKeys(event),\n",
              "    });\n",
              "\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
              "    // Handle any extra behaviour associated with a key event\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.key_event = function (event, name) {\n",
              "    // Prevent repeat events\n",
              "    if (name === 'key_press') {\n",
              "        if (event.key === this._key) {\n",
              "            return;\n",
              "        } else {\n",
              "            this._key = event.key;\n",
              "        }\n",
              "    }\n",
              "    if (name === 'key_release') {\n",
              "        this._key = null;\n",
              "    }\n",
              "\n",
              "    var value = '';\n",
              "    if (event.ctrlKey && event.key !== 'Control') {\n",
              "        value += 'ctrl+';\n",
              "    }\n",
              "    else if (event.altKey && event.key !== 'Alt') {\n",
              "        value += 'alt+';\n",
              "    }\n",
              "    else if (event.shiftKey && event.key !== 'Shift') {\n",
              "        value += 'shift+';\n",
              "    }\n",
              "\n",
              "    value += 'k' + event.key;\n",
              "\n",
              "    this._key_event_extra(event, name);\n",
              "\n",
              "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
              "    if (name === 'download') {\n",
              "        this.handle_save(this, null);\n",
              "    } else {\n",
              "        this.send_message('toolbar_button', { name: name });\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
              "    this.message.textContent = tooltip;\n",
              "};\n",
              "\n",
              "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
              "// prettier-ignore\n",
              "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
              "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
              "\n",
              "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
              "\n",
              "mpl.default_extension = \"png\";/* global mpl */\n",
              "\n",
              "var comm_websocket_adapter = function (comm) {\n",
              "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
              "    // object with the appropriate methods. Currently this is a non binary\n",
              "    // socket, so there is still some room for performance tuning.\n",
              "    var ws = {};\n",
              "\n",
              "    ws.binaryType = comm.kernel.ws.binaryType;\n",
              "    ws.readyState = comm.kernel.ws.readyState;\n",
              "    function updateReadyState(_event) {\n",
              "        if (comm.kernel.ws) {\n",
              "            ws.readyState = comm.kernel.ws.readyState;\n",
              "        } else {\n",
              "            ws.readyState = 3; // Closed state.\n",
              "        }\n",
              "    }\n",
              "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
              "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
              "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
              "        var data = msg['content']['data'];\n",
              "        if (data['blob'] !== undefined) {\n",
              "            data = {\n",
              "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
              "            };\n",
              "        }\n",
              "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
              "        ws.onmessage(data);\n",
              "    });\n",
              "    return ws;\n",
              "};\n",
              "\n",
              "mpl.mpl_figure_comm = function (comm, msg) {\n",
              "    // This is the function which gets called when the mpl process\n",
              "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
              "\n",
              "    var id = msg.content.data.id;\n",
              "    // Get hold of the div created by the display call when the Comm\n",
              "    // socket was opened in Python.\n",
              "    var element = 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.on(\n",
              "        'cleared',\n",
              "        { fig: fig },\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "};\n",
              "\n",
              "mpl.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",
              "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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",
              "\n",
              "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
              "    fig.send_message('closing', msg);\n",
              "    // fig.ws.close()\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
              "    // Turn the data on the canvas into data in the output cell.\n",
              "    var width = this.canvas.width / this.ratio;\n",
              "    var dataURL = this.canvas.toDataURL();\n",
              "    this.cell_info[1]['text/html'] =\n",
              "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Tell IPython that the notebook contents must change.\n",
              "    IPython.notebook.set_dirty(true);\n",
              "    this.send_message('ack', {});\n",
              "    var fig = this;\n",
              "    // Wait a second, then push the new image to the DOM so\n",
              "    // that it is saved nicely (might be nice to debounce this).\n",
              "    setTimeout(function () {\n",
              "        fig.push_to_output();\n",
              "    }, 1000);\n",
              "};\n",
              "\n",
              "mpl.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",
              "\n",
              "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
              "    var fig = event.data.fig;\n",
              "    if (event.target !== this) {\n",
              "        // Ignore bubbled events from children.\n",
              "        return;\n",
              "    }\n",
              "    fig.close_ws(fig, {});\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (el) {\n",
              "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
              "};\n",
              "\n",
              "mpl.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",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
              "    // Check for shift+enter\n",
              "    if (event.shiftKey && event.which === 13) {\n",
              "        this.canvas_div.blur();\n",
              "        // select the cell after this one\n",
              "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
              "        IPython.notebook.select(index + 1);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    fig.ondownload(fig, null);\n",
              "};\n",
              "\n",
              "mpl.find_output_cell = function (html_output) {\n",
              "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
              "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
              "    // IPython event is triggered only after the cells have been serialised, which for\n",
              "    // our purposes (turning an active figure into a static one), is too late.\n",
              "    var cells = IPython.notebook.get_cells();\n",
              "    var ncells = cells.length;\n",
              "    for (var i = 0; i < ncells; i++) {\n",
              "        var cell = cells[i];\n",
              "        if (cell.cell_type === 'code') {\n",
              "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
              "                var data = cell.output_area.outputs[j];\n",
              "                if (data.data) {\n",
              "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
              "                    data = data.data;\n",
              "                }\n",
              "                if (data['text/html'] === html_output) {\n",
              "                    return [cell, data, j];\n",
              "                }\n",
              "            }\n",
              "        }\n",
              "    }\n",
              "};\n",
              "\n",
              "// Register the function which deals with the matplotlib target/channel.\n",
              "// The kernel may be null if the page has been refreshed.\n",
              "if (IPython.notebook.kernel !== null) {\n",
              "    IPython.notebook.kernel.comm_manager.register_target(\n",
              "        'matplotlib',\n",
              "        mpl.mpl_figure_comm\n",
              "    );\n",
              "}\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div id='0d6fcd21-9811-4cea-b85f-7f5dfec00c64'></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "%matplotlib inline\n",
        "#The above code is only for jupyter\n",
        "#notebook for interactive graph\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "h=np.zeros(20);\n",
        "n=np.arange(-9,10, 2);\n",
        "h[n+10] = 2/(np.pi*n)\n",
        "\n",
        "plt.figure()\n",
        "plt.stem(np.arange(-10,10),h,use_line_collection=True)\n",
        "plt.xlabel('Sample')\n",
        "plt.ylabel('Value')\n",
        "plt.title('Part of Imp. Resp. of Hilbert Transform')\n",
        "plt.grid()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G31UUIGIbhFj"
      },
      "source": [
        "Here we see that we have negative indices. If we want to obtain a causal system, we need to shift them to at or above zero using a suitable **delay**, hence the Hilbert transform involves some **delay**. Hence to make the imaginary and real part to fit to each other, we have to **delay the real part accordingly**.\n",
        "\n",
        "This type of complex signal, with a 1-sided spectrum, is also called an “**analytic signal**”.\n",
        "\n",
        "Let's take a look at the frequency response of our filter. Since we have included a delay, our phase should be our **90 degrees (pi/2 Rad) phase shift** plus the linear phase from the delay. Hence our phase curve should hit the phase axis at frequency 0 at $\\dfrac{pi}{2} Rad$, for which we would like to zoom in to this part $\\left(\\dfrac{pi}{2}+\\Omega*d\\right)$.\n",
        "   "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "hide_input": true,
        "id": "Eoa6meAqbhFj",
        "outputId": "b5117218-ca04-45b4-fd86-97f5de75fae9"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/n_D4xXQahQQ\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "%%html\n",
        "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/n_D4xXQahQQ\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "uznzLLTKbhFj",
        "outputId": "bfed7e8f-cf33-4c12-eb21-bbca8d8fdeb8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 602
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Frequency Response\n",
        "\n",
        "from scipy.signal import freqz\n",
        "import numpy as np\n",
        "from matplotlib.ticker import FuncFormatter, MultipleLocator\n",
        "\n",
        "w, h_response  = freqz(h)\n",
        "\n",
        "fig=plt.figure(figsize=(8,6))\n",
        "fig.suptitle('Frequency Response', fontsize=16)\n",
        "plt.subplot(2,1,1)\n",
        "plt.plot(w/np.pi, 20 * np.log10(abs(h_response), where=abs(h_response) > 0), 'b')\n",
        "#plt.ylim((-0.001,0.001))\n",
        "plt.ylabel('Amplitude (dB)')\n",
        "plt.xlabel('Normalized Frequency')\n",
        "plt.grid()\n",
        "ax = plt.gca()\n",
        "ax.xaxis.set_major_formatter(FuncFormatter(\n",
        "   lambda val,pos: '{:.0g}$\\pi$'.format(val) if val !=0 else '0'\n",
        "))\n",
        "ax.xaxis.set_major_locator(MultipleLocator(base=0.2))\n",
        "plt.subplot(2,1,2)\n",
        "angles = np.angle(h_response)\n",
        "plt.plot(w/np.pi, angles, 'g')\n",
        "plt.ylabel('Angle (radians)')\n",
        "plt.xlabel('Normalized Frequency')\n",
        "ax = plt.gca()\n",
        "ax.xaxis.set_major_formatter(FuncFormatter(\n",
        "   lambda val,pos: '{:.0g}$\\pi$'.format(val) if val !=0 else '0'\n",
        "))\n",
        "ax.xaxis.set_major_locator(MultipleLocator(base=0.2))\n",
        "plt.grid()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eXiTEsRhbhFk"
      },
      "source": [
        "Here we can see that the phase curve indeed would hit the $\\dfrac{pi}{2}$ Rad (90 degree) mark at the phase axis. We see that the magnitude plot only reaches about 0 dB attenuation at about frequency $0.08\\cdot \\pi$ and reaches higher attenuations at frequencies below about $0.05\\cdot \\pi$ and above about $0.95\\cdot \\pi$. Hence it is only a working Hilbert transformer within this frequency range.\n",
        "\n",
        "If we want to plot the frequency response of our **entire filter** (not just the Hilbert transformer part), which **passes only the positive frequencies**, we first need to construct our resulting complex filter, and then plot the frequency response on the **whole** frequency circle. First we need to create the correspondingly delayed unit impulse as the real part:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "EhfWdhYCbhFk",
        "outputId": "92a96e49-dda2-4fd2-95aa-46e3c73edcbe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.-0.07073553j, 0.+0.j        , 0.-0.09094568j, 0.+0.j        ,\n",
              "       0.-0.12732395j, 0.+0.j        , 0.-0.21220659j, 0.+0.j        ,\n",
              "       0.-0.63661977j, 1.+0.j        , 0.+0.63661977j, 0.+0.j        ,\n",
              "       0.+0.21220659j, 0.+0.j        , 0.+0.12732395j, 0.+0.j        ,\n",
              "       0.+0.09094568j, 0.+0.j        , 0.+0.07073553j, 0.+0.j        ])"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "# construct a delayed impulse to implement the\n",
        "# delay for the real part:\n",
        "delt = np.zeros(20)\n",
        "delt[9] = 1\n",
        "#delt =\n",
        "#0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
        "#Then we need to add our imaginary part as our\n",
        "#Hilbert transform to obtain our complex filter:\n",
        "h = np.zeros(20);\n",
        "n = np.arange(-9, 10+1, 2);\n",
        "h[(n-1)+10] = 2./(np.pi*n);\n",
        "hone = delt+h*1j\n",
        "\n",
        "hone\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bn25frSebhFk"
      },
      "source": [
        "Observe that this is our first complex valued filter!\n",
        "\n",
        "Its frequency response, including negative frequencies above $\\pi$, is:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "s9og5XD-bhFl",
        "outputId": "16216627-9818-4f37-84a7-540f7859a9aa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 602
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Frequency Response\n",
        "\n",
        "from scipy.signal import freqz\n",
        "import numpy as np\n",
        "from matplotlib.ticker import FuncFormatter, MultipleLocator\n",
        "\n",
        "w, h_response  = freqz(hone, whole=True)\n",
        "\n",
        "fig=plt.figure(figsize=(8,6))\n",
        "fig.suptitle('Frequency Response', fontsize=16)\n",
        "plt.subplot(2,1,1)\n",
        "plt.plot(w/np.pi, 20 * np.log10(abs(h_response), where=abs(h_response) > 0), 'b')\n",
        "plt.ylim((-40,10))\n",
        "plt.ylabel('Amplitude (dB)')\n",
        "plt.xlabel('Normalized Frequency')\n",
        "plt.grid()\n",
        "ax = plt.gca()\n",
        "ax.xaxis.set_major_formatter(FuncFormatter(\n",
        "   lambda val,pos: '{:.0g}$\\pi$'.format(val) if val !=0 else '0'\n",
        "))\n",
        "ax.xaxis.set_major_locator(MultipleLocator(base=0.2))\n",
        "plt.subplot(2,1,2)\n",
        "angles = np.angle(h_response)\n",
        "plt.plot(w/np.pi, angles, 'g')\n",
        "plt.ylabel('Angle (radians)')\n",
        "plt.xlabel('Normalized Frequency')\n",
        "ax = plt.gca()\n",
        "ax.xaxis.set_major_formatter(FuncFormatter(\n",
        "   lambda val,pos: '{:.0g}$\\pi$'.format(val) if val !=0 else '0'\n",
        "))\n",
        "ax.xaxis.set_major_locator(MultipleLocator(base=0.2))\n",
        "plt.grid()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "knxHGWzMbhFl"
      },
      "source": [
        "Here we can see that we have indeed a **passband** at the **positive frequencies** between 0 and $\\pi$. Observe that the passband is at about 6 dB (above 0dB), because we multiplied our filter by a factor of 2 to make it simpler.\n",
        "\n",
        "The negative frequencies appear between $\\pi$ and $2*\\pi$ on the frequency axis, and we can see that we get about -30 dB attenuation there, which is not very much, but which we could increase it by making the filter longer. This also gives us a good indication of how well our filter is working!\n",
        "\n",
        "The Python function “remez” also has an option for a Hilbert transform filter. We get a similar design with:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "UnNBTXmEbhFl",
        "outputId": "0885ff62-a9dd-45e9-8eda-4d2de519c37d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 602
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import scipy.signal as sp\n",
        "b=sp.remez(21, [0.03, 0.47],[1], type='hilbert');\n",
        "\n",
        "\n",
        "# Frequency Response\n",
        "\n",
        "from scipy.signal import freqz\n",
        "import numpy as np\n",
        "from matplotlib.ticker import FuncFormatter, MultipleLocator\n",
        "\n",
        "w, h_response  = freqz(b, whole=False)\n",
        "\n",
        "fig=plt.figure(figsize=(8,6))\n",
        "fig.suptitle('Frequency Response', fontsize=16)\n",
        "plt.subplot(2,1,1)\n",
        "plt.plot(w/np.pi, 20 * np.log10(abs(h_response), where=abs(h_response) > 0), 'b')\n",
        "plt.ylim((-40,10))\n",
        "plt.ylabel('Amplitude (dB)')\n",
        "plt.xlabel('Normalized Frequency')\n",
        "plt.grid()\n",
        "ax = plt.gca()\n",
        "ax.xaxis.set_major_formatter(FuncFormatter(\n",
        "   lambda val,pos: '{:.0g}$\\pi$'.format(val) if val !=0 else '0'\n",
        "))\n",
        "ax.xaxis.set_major_locator(MultipleLocator(base=0.2))\n",
        "plt.subplot(2,1,2)\n",
        "angles = np.angle(h_response)\n",
        "plt.plot(w/np.pi, angles, 'g')\n",
        "plt.ylabel('Angle (radians)')\n",
        "plt.xlabel('Normalized Frequency')\n",
        "ax = plt.gca()\n",
        "ax.xaxis.set_major_formatter(FuncFormatter(\n",
        "   lambda val,pos: '{:.0g}$\\pi$'.format(val) if val !=0 else '0'\n",
        "))\n",
        "ax.xaxis.set_major_locator(MultipleLocator(base=0.2))\n",
        "plt.grid()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hf4kueVpbhFm"
      },
      "source": [
        "Observe that the specified passband does not go all the way to 0 and 0.5. The further away the passband is from these edges, the less ripples we will have in the passband, and the **more attenuation** we will have for the **negative frequencies**!\n",
        "\n",
        "Observe that this design now has a +90 Degrees ($\\pi/2$) phase shift at frequency close to zero. This is a phase difference of 180 Degrees from our previous design with the rectangular window, and results from a sign change of the coefficients.\n",
        "\n",
        "Let's look at the resulting **one sided complex valued filter** at the whole frequency circle again, in iPython:\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "9gW_YVONbhFm",
        "outputId": "2f2213d6-2b45-4589-c820-f2c786ad7cf0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.-8.35889141e-05j, 0.+7.28072838e-02j, 0.+7.11334936e-05j,\n",
              "       0.+6.79343477e-02j, 0.-7.21513298e-06j, 0.+1.10111613e-01j,\n",
              "       0.+2.67809302e-05j, 0.+2.01516354e-01j, 0.-8.96356182e-06j,\n",
              "       0.+6.32971502e-01j, 1.+0.00000000e+00j, 0.-6.32971502e-01j,\n",
              "       0.+8.96356182e-06j, 0.-2.01516354e-01j, 0.-2.67809302e-05j,\n",
              "       0.-1.10111613e-01j, 0.+7.21513298e-06j, 0.-6.79343477e-02j,\n",
              "       0.-7.11334936e-05j, 0.-7.28072838e-02j, 0.+8.35889141e-05j])"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ],
      "source": [
        "#Delay for the real part:\n",
        "delt = np.zeros(21)\n",
        "delt[10] = 1\n",
        "#The complex filter:\n",
        "honeremez = delt + 1j*b\n",
        "honeremez"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "5BL5TlHMbhFm",
        "outputId": "516a27e6-25ea-4683-9663-07a3dd4fc127",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 602
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAroAAAJJCAYAAABF+5SuAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3xT1fsH8E+StuluoXTSUqDsvacMWWXIFFFEBUXxi/pVv+Dip4i4AAUcOFEBByouEBGBygbZUPYeLVBaoED3SJPz++N4MtokzbhZl+f9evWVNrnJOU9u0jx57jnnKhhjDIQQQgghhMiM0tMdIIQQQgghxBUo0SWEEEIIIbJEiS4hhBBCCJElSnQJIYQQQogsUaJLCCGEEEJkiRJdQgghhBAiS5ToEkIIIYQQWaJElxBCCCGEyBIluoQQQgghRJYo0SXkNla3bl0oFAqrP++//76nu0mcZG4/q9VqJCYmYvjw4Vi1apWnu0gIIS7h5+kOEEI8r3v37mjQoIHZ25o1a+bm3hBXMd7PeXl5OHDgAFauXImVK1fif//7H+bPn+/hHhJCiLQUjDHm6U4QQjyjbt26yMjIwOLFizFhwgRPd4e4iKX9XFFRgf/973/46KOPAAC7d+9Gx44dPdRLQgiRHg1dIISQ25Sfnx/effddhIeHAwD++OMPD/eIEEKkRYkuIcQmYpznhQsX8Pvvv6NPnz6oWbMmFAoFNm3apN/u5s2bmDFjBtq0aYOwsDAEBwejZcuWePPNN1FcXGz2sSsqKvD++++jZcuWCAwMRHR0NO6++24cPnwYS5YsgUKhqFJxfu2116BQKPDaa6+ZfcxNmzZBoVCgd+/eZm/PysrClClT0LRpUwQHByMsLAwdO3bERx99hIqKiirbT5gwAQqFAkuWLMH58+fx4IMPIi4uDmq1GikpKXjllVdQVlZm8fnbt28fxo8fj3r16iEwMBA1a9ZE69at8fzzzyMjIwMAsHjxYigUCqSmplp8nKysLPj7+yMoKAi5ubkWt7NVYGAgGjZsCADIyckxu8369esxatQoxMfHIyAgADExMRg5ciR27NhhdvvTp0/jkUceQb169aBWqxEaGork5GQMGTIEixcvNtnWeP/m5ubiySefRJ06daBWq5GcnIz//e9/uHnzpsX+7969G2PGjEFCQoK+b0OHDkVaWprZ7R3djzqdDgsXLkT37t0RGRkJf39/xMTEoHXr1vjvf/+LCxcuVLlPRUUFvvzyS/Tu3Rs1a9aEWq1GvXr1MHnyZFy8eNFiTIQQCTFCyG0rOTmZAWCLFy+2edunnnqKAWAdOnRgY8eOZb169WJbtmxhjDF29OhRlpSUxACw+Ph4NnDgQDZ06FAWGxvLALA2bdqwW7dumTyuVqtlI0aMYABYQEAAGzBgALv33ntZ3bp1WWBgIHviiScYADZ+/HiT+82YMYMBYDNmzDDb340bNzIArFevXlVu27x5M6tRowYDwOrWrcuGDRvGUlNT9dcNGDCAlZeXm9xn/PjxDAB75plnWHh4OEtOTmZjxoxh/fr1Y0FBQQwAGzFihNm+vPPOO0ypVDIArFGjRmzMmDFs6NChrGnTpibPf2lpKYuOjmYKhYKdPHnS7GO9+uqrDAB7+OGHzd5uTnX7uWHDhgwAmz59epXbpk6dygAwpVLJOnXqxO655x7WuXNnplAomEqlYosWLTLZ/vDhwyw8PJwBYI0bN2ajRo1i99xzD+vatSsLDQ1lrVu3Ntl+8eLFDAAbNmwYS0lJYZGRkWzEiBFs5MiR+v3RuHFjdvXq1Sp9W7hwof55bdu2LRs7dizr1q0bA8AAsNdee63KfRzdjw8//DADwAIDA1m/fv3Y2LFjWWpqqv65W758ucn2+fn5rHfv3gwACw0NZb169WKjR49mjRs3ZgBYVFQU279/v9n9QQiRDiW6hNzGHEl0VSoV+/3336vcXlxczFJSUhgA9sorr7CysjL9bUVFRWzs2LFmE7SPPvqIAWCxsbHs2LFj+us1Gg2bPHmyPmmRKtG9cuUKi4qKYgqFgn3yySdMq9Xqb7t+/Trr06cPA8Bmzpxpcj+RIAFgL7/8MquoqNDfdvjwYRYSEsIAsH/++cfkfr///rs+QVq2bFmVfh49etQk7pdffpkBYE8//XSVbcvLy1lcXBwDwPbt22c2bnOs7edjx44xlUrFALA9e/aY3LZw4UIGgDVo0IAdPHjQ5LbNmzezsLAwFhAQwE6dOqW/XiSEb775ZpW2iouL2ebNm02uE4kuANalSxeWm5urv+3mzZv6xPW+++4zud+hQ4eYn58fUygU7JtvvjG5bfXq1SwgIIABYOvWrTO5zZH9mJGRwQCwxMREduXKFbPPYUZGhsl1999/PwPA7rrrLpaTk2Ny23vvvccAsIYNG5q0TwiRHiW6hNzGRAJk6cc4SRTbPvLII2Yf69NPP9V/sJtTUFDAYmJimJ+fH7tx44b++gYNGjAA7NNPP61yn5KSEn1iJ1Wi++KLL+or0+ZcunSJ+fv7s+joaKbT6fTXiwSpffv2JtcL//nPfxgA9vrrr5tc36ZNGwaAzZs3z2x7lV2+fJn5+/uziIgIVlhYaHLbDz/8wACwrl272vRYgrlE99atW2zt2rWsSZMm+i8nxrRaLUtISGAA2N69e80+7jvvvMMAsKlTp+qvGzx4MANgc7XSONE9cOBAldsPHTrEFAoFUyqV7OLFi/rrJ06cyACwUaNGmX1cceShf//+Jtc7sh93796trzrb4tixY0yhULCEhASWn59vdhvxPP3xxx82PSYhxDE0RpcQgu7du2P8+PFVfgYOHFhl29GjR5t9jD///BMAcO+995q9PTQ0FB06dEBFRQX27NkDALh8+TLOnDkDAHjggQeq3CcwMBBjxoxxKCZLqutn7dq10bBhQ1y7dg2nT5+ucvtdd90FhUJR5fqmTZsC4DEJ2dnZSE9Ph1KpxMSJE23qX0JCAkaPHo28vDx8++23Jrd9/PHHAICnnnrKpseq7OGHH9avoxsZGYnU1FScPn0a3333Hd544w2TbQ8cOICsrCykpKSgffv2Zh9PjH/+559/9Nd16tQJADB58mSsXbsWpaWlNvWtdevWaNOmTZXrW7ZsibZt20Kn02HLli3668W4cEurhYjne+vWrdBqtVVut2c/NmnSBGFhYVi9ejXeeustnD9/3mosq1evBmMMgwYNQlhYmNltzD13hBDp0Tq6hBA8+uijNi8vVrduXbPXnzt3DgDw4IMP4sEHH7T6GNeuXQMAXLp0CQBQq1YthIaGmt22Xr16NvXLVqKfPXr0qHbba9euoVGjRibX1alTx+y2YuUC48QuMzMTABAfH4+IiAib+/j000/jhx9+wMcff4z//Oc/AIBDhw5h27ZtiI2NtfhlozrG6+heu3YNW7duRUFBASZPnoyGDRvqk1TA8DydPXvWbEJoTOxPAHj++eexbds2/P333xg4cCD8/f3RunVr9OzZE/fdd5/F5cus7ed69eph//79+tcLYEhELd0vJSUFAN8fubm5iImJMbndnv0YFhaGxYsX4+GHH8Yrr7yCV155BfHx8ejSpQsGDhyI+++/3+T1K567r776Cl999ZXFuADT544QIj1KdAkhdgkKCjJ7vU6nAwAMHDgQsbGxVh8jOTlZ8n5Z6o+l60ePHo2QkBCrjxEVFVXlOqXS9QfCunTpgk6dOmH37t3YvHkzevXqpa/mTpo0CQEBAQ49buUvNHl5eRg5ciQ2btyIMWPG4NixYwgODgZgeJ7i4uKsrgIB8C8qQnBwMNLS0rBnzx6sWbMG//zzD/755x/s3bsX8+fPxxNPPKGPxV5MwmXf7d2Pd999N/r164eVK1di69at2L59O5YvX47ly5fj1VdfRVpaGlq2bAnA8Ny1adMGrVu3tvq4nTt3diwAQohNKNElhEgiKSkJJ06cwMSJE22uONauXRsAcP36dRQWFpqt6ppbtgmAPtkrKCgwe7tYsstcP0+fPo0XX3wRHTp0sKmfjhJVwytXriAvL8/uqu4DDzyAjz76CK1bt8bSpUvh5+enr/BKISIiAsuWLUOTJk2QkZGB+fPn45VXXgHAnyeAJ/tLliyx+7E7duyor95WVFRgxYoVeOihh/DJJ59g9OjRuPPOO022tzYcQLwGEhMT9dfVrl0bZ8+exblz59CiRYsq9xFVVbGUmxQiIiJMjlhcvHgR//3vf/H777/jqaeewubNmwEYnrvu3bvrT8ZBCPEMGqNLCJHEoEGDAAA//fSTzfdJTExE/fr1AQDff/99ldvLysrw888/m72vSJKPHz9u9nYxFleKfjoqLi4OrVu3hk6nw6JFi+y675gxYxAfH48VK1bgrbfeQlFREUaOHImEhARJ+xgdHa1PbufOnYtbt24B4IlqrVq1cOzYMRw9etSpNvz8/DB69Gh9ZTg9Pb3KNocOHcKhQ4eqXH/06FHs378fSqUSPXv21F8vxrhaSsLF892jRw/4+bmmppOUlISZM2cCMI1JvMZWrlxp8xhlQohrUKJLCJHEpEmTkJycjJ9//hkvvvii2UprdnY2vvjiC5Prnn32WQD8BBAnTpzQX6/VavHcc88hKyvLbHt9+vSBUqnE2rVr9ZU0gB/e/vDDD/Hrr7+avd/zzz+PyMhIzJ8/H/PmzUN5eXmVbc6fP4/vvvuu2phtMWPGDADAyy+/bLZPx44dM5us+/v7Y/LkyaioqMDcuXMBOD4JrTpPPPEE6tSpg7y8PMybN0/f/owZM8AYw8iRI7Ft27Yq99NqtdiwYQN27typv+6TTz7ByZMnq2ybnZ2NvXv3AjA/dIUxhsmTJ5ucHCIvLw+TJ08GYwx33323vlIKAM888wz8/PywYsWKKvtq3bp1+PzzzwEAzz33nD1PhVkHDhzAsmXLUFJSUuU2cTY545jatm2Lu+++GxcvXsSoUaPMHpUoKirC0qVLLZ6kgxAiEU8u+UAI8SxH1tE9f/68xW2OHDnC6tatywCwyMhI1rNnT3b//fezESNGsGbNmjGFQsFiY2NN7qPVatnQoUP1J4xITU1l9913H6tXrx4LDAzUr6VbeXkxxhh75pln9Gv79u7dm40aNYqlpKQwf39/9tJLL1k9YUStWrUYABYTE8P69OnDxo0bx+666y79WsCdO3c2uY9YlsrScyWWyTLXz7feeospFAoGgDVp0oTde++9bNiwYaxZs2ZWHzMnJ4ep1WoGgLVq1crsNrawZT8vWrSIAWBhYWEma9k+//zz+uW/mjdvzoYPH87uu+8+1rt3bxYZGVllabjWrVszAKxevXps6NChbNy4cWzAgAH6kzH06dOHaTQa/fbGJ4yoX78+i4yMZCNHjmSjRo1iNWvW1K83W3ktWsYY+/zzz/UnjGjXrh27//77Wffu3fXPtbUTRtizH5cvX84AsKCgINa9e3d23333mZz8ISAggP31118mj5Ofn8/69u2rv71jx45szJgx7J577mEdO3bUr/N7/Phxi/uEEOI8SnQJuY1Jnegyxj/g33nnHda1a1cWGRnJ/P39WXx8POvYsSN7/vnnq5xQgTF+coh58+axZs2aMbVazaKiotjw4cNZenq61QRSp9OxefPmsaZNm7KAgABWs2ZNNnToULZv3z6rZ0ZjjCeR06dPZ+3atdOf+CAxMZF169aNzZgxgx06dMhke2cSXcYY27FjBxs7diyrXbs28/f3ZzVr1mStW7dmL7zwQpWTDRjr3LkzA8A+//xzi9tUx5b9XFFRoU+8X3rpJZPbtm/fzsaNG8eSk5OZWq1mYWFhrFGjRmzEiBHsyy+/NFkXedWqVWzy5Mmsbdu2LDo6Wv+89u7dm3399ddVzjhn/LxdvXqVPf744ywxMZEFBASwpKQk9vTTT5sk3pXt3LmTjR49msXFxTE/Pz8WFRXFhgwZUuVEEYIj+/HKlSts9uzZbPDgwaxevXosODiYhYeHs2bNmrEnn3ySnThxwuxjabVa9v3337PBgwez2NhY5u/vz6KioliLFi3Yww8/zJYvX17l+SCESEvBmITTWAkhRGJLlizBww8/jPHjxzs0KcqXnTp1Ck2aNEFERAQuX76sXxFBTm7n/UsIcT0ao0sIIV7q1Vdf1Y9dlWOSSwghrkbLixFCiBdZuXIlfv/9dxw9ehS7du1CXFwcXnjhBU93ixBCfBJVdAkhxIvs378fixYtwrFjx9CvXz+sW7cOkZGRnu4WIYT4JBqjSwghhBBCZIkquoQQQgghRJYo0SWEEEIIIbJEiS4hhBBCCJElSnQJIYQQQogsUaJLCCGEEEJkiRJdQgghhBAiS5ToEkIIIYQQWaJElxBCCCGEyBIluoQQQgghRJYo0SWEEEIIIbJEiS4hhBBCCJElSnQJIYQQQogsUaJLCCGEEEJkiRJdQgghhBAiS5ToEkIIIYQQWaJElxBCCCGEyBIluoQQQgghRJYo0SWEEEIIIbJEiS4hhBBCCJElSnQJIYQQQogsUaJLCCGEEEJkiRJdQgghhBAiS5ToEkIIIYQQWaJElxBCCCGEyBIluoQQQgghRJYo0SWEEEIIIbJEiS4hhBBCCJElSnQJIYQQQogsUaJLCCGEEEJkiRJdQgghhBAiS5ToEkIIIYQQWaJElxBCCCGEyBIluoQQQgghRJYo0SWEEEIIIbJEiS4hhBBCCJEln0p0t2zZgqFDhyIhIQEKhQIrVqwwuZ0xhldffRXx8fEICgpCv379cPr0ac90lhBCCCGEeJRPJbpFRUVo3bo1Pv74Y7O3v/POO/jwww/x2WefYdeuXQgJCUFqaipKS0vd3FNCCCGEEOJpCsYY83QnHKFQKLB8+XKMGDECAK/mJiQkYOrUqXjuuecAAHl5eYiNjcWSJUtw3333ebC3hBBCCCHE3fw83QGpnD9/HtnZ2ejXr5/+uoiICHTu3Bk7duywmOiWlZWhrKxM/7dOp8ONGzcQFRUFhULh8n4TQgghhBD7MMZQUFCAhIQEKJWWByjIJtHNzs4GAMTGxppcHxsbq7/NnFmzZmHmzJku7RshhBBCCJHexYsXkZiYaPF22SS6jpo2bRqmTJmi/zsvLw916tTB+fPnERYW5vL2NRoNNm7ciDvvvBP+/v4ub8/d5B4fIP8Y5R4fIP8Y5R4fIP8Y5R4fIP8YKT5pFRQUoF69etXmarJJdOPi4gAAOTk5iI+P11+fk5ODNm3aWLyfWq2GWq2ucn3NmjURHh4ueT8r02g0CA4ORlRUlGxf+HKOD5B/jHKPD5B/jHKPD5B/jHKPD5B/jBSftEQb1Q0z9alVF6ypV68e4uLisH79ev11+fn52LVrF7p27erBnhFCCCGEEE/wqYpuYWEhzpw5o//7/PnzSE9PR82aNVGnTh08++yzePPNN9GwYUPUq1cP06dPR0JCgn5lBkIIIYQQcvvwqUR37969uPPOO/V/i7G148ePx5IlS/DCCy+gqKgIkyZNwq1bt3DHHXdgzZo1CAwM9FSXCSGEEEKIh/hUotu7d29YW/ZXoVDg9ddfx+uvv+7GXhFCCCGEEG8kmzG6hBBCCCGEGKNElxBCCCGEyBIluoQQQgghRJYo0SWEEEIIIbJEiS4hhBBCCJElSnQJIYQQQogs+dTyYoQQQrxXaSmQnQ3k5ADl5fy60FAgJgaIjgYCAjzbP3vodMDNm0B+Pv8pKAAYA5RK/hMUBNSowX/CwoBqzkLq1RjjMd66xWMuLubxa7U8rpAQHmNoKN+Pvn722vJyHufNm0BeHlBRweNlDFCrgYgIIDwcqFkT8KVl+BkDbtwAsrKAwkL+fgwI4PsuJgaIjfXt16mjKNElhBDikKwsYOVKYONGYP9+wOjElWZFRwNNmgDNmvGf1q2BNm14YuEJjPEYjhwBDh/ml+fOAZcuAZcvG5L16qjVQHIyULeu4adpU6BFC6B+fZ4Ye4PCQuDkSeDECcPliRPAqVNAWZltj6FUAnFxQGIi/xGxNmvGL2vUcGkINhP7VsR4/LjhMivL9seJjub7tk4dftmkCdCyJdC8OU+GPeXqVWDfPv6+27cPOHYMuHiRf0mxJCyM76NevYC+fYE+fXz/S4stKNElhBBiM60W+OMP4P33gc2bq96uVvPKkVrNq0cFBfxDWasFrl3jP1u3mt6nfn2gXTugbVvDT1yctP3OzeWJbOWfW7es3y8oiCfioaE8ydPp+E9REa8IlpfzJPHUKf5j7v7Nm/OkV/w0bQokJbmmulY5wTP+uXTJ+n3Vap6ohoQAKhWPlzEea0EB/9Hp+ONnZQG7d1d9jNhYwxeZ5s0Nl7VqSR8rAGg0/AtW5YT2xAneX2siIoDISJ7sKRT8p6yMV7fz8nis4jW7d2/V+ycnG/Zpy5b8skkT/jxKhTF+lEQktCK5tbYva9XiSbhazV+fBQU8hoICvs927wbefZdXeR94AHjqKaBePen67G0o0SWEEFItxoBVq4CpU4HTpw3Xd+4M3HUXv2zbFoiKqprA6XQ8obxwgScix4/zCmp6OpCZyauo584Bv/xiuE9cnCHpbdOGJxUJCfx6PzOfXDodUFjoj0OHeGKQkcHbOXqUV7tycszHpVIBjRoZkpWGDXkSmpTE27I23IIxoKSEP3ZGBo/vwgXg7Fne5rFj/Pa9e6smSiEhPClq2pT/1K9vqJLGxvJD5uYSYTGk4vp1nuyI5+7sWZ7wnTzJK7eWiKq68U/jxvy5DQqyfD/R9rVrvN1Ll3gF8exZ/jyLimJODv/ZuLFquyLxbdqUV0gTE4HatfkQAUuVxYoKfjj+2jX+3BrHe+oUv6yoMH9flQpISTHE2bQpv2zQgCf0KpXlWBnjr9mMDP4azcgAzp/ncR4+zBP9jAz+8+efpm2K11OLFrytOnX46ykqynJbBQX8MS9f5u+vI0f4a/fIEb6vK1Mo+H5r1w5o3x5o1YpX1xMTzQ+3KCvjz9u+fXzfrFrFv4DOnw98+CEwcSIwfTrfH3JDiS4hhBCrMjOBxx8H1qzhf9eowf9+4gn+AV4dpZInMzVr8g9mY7m5POE9cIBXqg4c4Mladjbw11/8x5hCAQQH82qVWm1IEoqK/AEMttqP5GRD5U1cNm7seAVO9KVePfMVMa2WJxdiWIT4OX2aV0lFhc4clYofag4OFuNl/VBSMgjFxX7Q6az3q3KCZ5zQ1qzpWKwA34+xsfynffuqt+fn80qqSPKPHePJ2oULPFHdtIn/mBMYCISH+0GrHQB/fx5jWRmvrFYnNNQ0TpHQpqQ4t2/FGOw2barefuOGYcjL0aP88vBh3l/xZe7nnyvfyx9+fkMRHq5AUBCvRpeV8bG01oaOKJU8JpHUtm/Ph/2Ehdkej1pt+FL1wAO87TVrgAULgLQ04PPPgR9+AObN40mvnMbyUqJLCCHEopUrgQkTeBUxIACYMgX4v/+z70PWmqgoPl6wb1/DdUVFwKFDPOk9cIAnEJcvA1eu8OSxqIj/mH88hjp1FEhK4pW15s35T9OmPCFyJ5WKV4gbNgRGjTJcr9GYVkJPnOBfJkSltLycx3nrlvHQCgUAQ3k5NBSIj+fJXP36hh+R4Hli4l94ONCpE/8xVlTEYxTV9VOnDBXhnBz+ZaW0FCgtVQAwX1aOjOQVS+NYGzTg+7V2bfcnZjVrAj178h+BMf46Nf5Sc+GCYd9qNEBFhRI3bph/zIgIXlmvW9d0qEuTJvwLj5T8/YGhQ/nP1q3A888Du3YBjz0G/PorsHSpc1+KvAkluoQQQqpgDJgxA3jjDf53x47Ad9/x5NHVQkKArl35jzGtlh/GLSw0jI0FeNIdGKjBP/+swYgRA+Hv5TNs/P0N1ceRI01vExVq8VNczBNmnU6Df/7ZgqFDeyI21l/ScaCuFhJiqERWptHwOPPzgdxcDTZv3o4ePbojMNAfAQH8i1BkpPnhKt5GoTAMPxk40PQ2nY7H9/vvG9CxYx9UVPD4AgJ4tTU6mj9PntCjB7B9O/DBB8DLL/NKb+fOfCx+kyae6ZOUfOClQwghxJ20WmDyZOCLL/jf//sfMHu255cHU6kMh84r02iAgIBqjun7AIWCV0Yrz+jXaIDMzELEx8trpry/v2FYS+3awKVLeWjTRl4xAnz4QWQkEB1dimbNvC8+lYofrenXDxg2jI/37tKFDx2q/IXT13jJoieEEEK8gVbLx/B98QX/cP78cz5hxdNJLiHE9Vq14qsydO/OxxunpgI7d3q6V86hRJcQQggAftj86aeBH3/kFaeffgImTfJ0rwgh7hQTA6xdC/TuzYeVpKZanjTpCyjRJYQQAgB4803gk0/44fOlS4G77/Z0jwghnhASwpcg69WLj58eNoxPtPNFlOgSQgjBihXAq6/y3z/6CLjnHo92hxDiYSEhwO+/85UtsrKAESOsn3nNW1GiSwght7mzZ/kSYgCfePbEEx7tDiHES0RE8NUXoqL4SU988X8DJbqEEHIbKy0FRo/mE0+6dQPmzPF0jwgh3iQlhZ+1UKkEvv4aWLbM0z2yDyW6hBByG5s5k5+ZrFYt/gHmbcseEUI8r3dvfqIYAPjPf/jJPnwFJbqEEHKb2rcPePdd/vsXX/CF7gkhxJxXX+Vnvbt1C3j4Yb5Kiy+gRJcQQm5D5eXAI4/wdXPvvZdPNCGEEEv8/fnZEYOCgPXrgR9+8HSPbEOJLiGE3Ibeew84dIhPMlmwwNO9IYT4goYN+WmCAWDqVD6239tRoksIIbeZq1eBt97iv8+dC0RHe7Y/hBDf8dxzQKNGQHa2YUlCb0aJLiGE3GZmzOBnPGrXDnjoIU/3hhDiS9RqvtY2wC9PnPBsf6pDiS4hhNxGjh4FFi7kv8+fz5cMIoQQe/Tvz8+WptN5f1WX/sURQsht5P/+j384jRzJT+9JCCGOePNNfrrwn38GDhzwdG8so0SXEEJuEwcPAitX8g+nt9/2dG8IIb6sZUtg7Fj++yuveLYv1lCiSwght4nZs1UAgDFjgCZNPNwZQojPmzkTUKmA1auBHTsUnu6OWZToEkLIbeDixVD89hv/IBLLAxFCiDMaNAAmTOC/v/OOd6aU3tkrJ3388ceoW7cuAgMD0blzZ+zevdvTXSKEEI/65ZdGYEyBESP4IUdCCJHCCy/w4VB//qlERkaYp7tThewS3WXLlmHKlCmYMWMG9u/fj9atWyM1NRVXr171dNcIIcQjrlwBtm2rDYCquYQQaTVqBNx9N/9961bvO4+47BLd+fPn47HHHsPDDz+MZs2a4bPPPkNwcDAWLVrk6a5VodEAy5crcPhwlKe7QgiRsS+/VEKrVaJ7dx06dPB0bwghcvPaa8CqVRUYN+64p7tShZ+nOyCl8vJy7Nu3D9OmTdNfp1Qq0a9fP+zYscPsfcrKylBWVqb/Oz8/HwCg0Wig0Whc2t85c5SYPt0PLVs2xpQprm3LU8Rz6Orn0pPkHqPc4wPkHWN5ObBwIf9XP2mSBhqN7OobAOS9DwH5xwfIP0Y5x9eoEVCvngZpae6Lz9Z2FIwx5uK+uE1WVhZq166Nf/75B127dtVf/8ILL2Dz5s3YtWtXlfu89tprmDlzZpXrv//+ewQHB7u0v9euBWHSpP5gTIFPP01DfHyxS9sjhNx+tm1LwNy5HVGjRikWLlwHf3/Z/MsnhNzGiouLcf/99yMvLw/h4eEWt5NVRdcR06ZNw5QpU/R/5+fnIykpCQMGDLD6xEnlp590SEtT4ezZ3pg40eXNuZ1Go0FaWhr69+8Pf39/T3fHJeQeo9zjA+Qd47vv8iXFUlMvYPDgfrKLT5DzPgTkHx8g/xgpPmmJI/DVkVWiW6tWLahUKuTk5Jhcn5OTg7i4OLP3UavVUKvVVa739/d3y4569NEKpKUB333nh7ffVkCGr30A7ns+PUnuMco9PkB+MR4/DmzfDvj5MQwYcAH+/imyis8cue3DyuQeHyD/GCk+6dqxhawGawUEBKB9+/ZYv369/jqdTof169ebDGXwJkOGMERElCI7W4E///R0bwghcvLtt/wyNZWhZs0y6xsTQogMySrRBYApU6bgiy++wNdff43jx49j8uTJKCoqwsMPP+zprpkVEAD06XMRAPDFFx7uDCFENnQ64Lvv+O8PPKDzbGcIIcRDZJfo3nvvvZg7dy5effVVtGnTBunp6VizZg1iY2M93TWL+vXLAACsWQPQcr+EECls3gxcvAhERPAjR4QQcjuSXaILAE899RQyMjJQVlaGXbt2oXPnzp7uklW1axehfXsddDrg11893RtCiByIYQtjxgCBgZ7tCyGEeIosE11fNHo0r7j89JOHO0II8XnFxcDPP/PfH3rIs30hhBBPokTXS4wezcfQbd7MT9dJCCGO+vNPoLAQqFsX6N7d070hhBDPoUTXSyQnA126AIwBv/zi6d4QQnzZihX88p57AIXCo10hhBCPokTXi9x7L79ctsyz/SCE+K7ycuiXKhwxwqNdIYQQj6NE14uI6sv27cClS57uDSHEF23cCOTlAbGx/CgRIYTczijR9SK1awNigYjVqz3bF0KIbxLDFoYPB5T0H54Qcpuz6xTAt27dwvLly7F161ZkZGSguLgY0dHRaNu2LVJTU9GtWzdX9fO2MWQIsHMnT3QnTfJ0bwghvkSnA37/nf8+cqRn+0IIId7Apu/7WVlZePTRRxEfH48333wTJSUlaNOmDfr27YvExERs3LgR/fv3R7NmzbCMBpg6ZcgQfvn330AZnbGTEGKHXbv4qi1hYcCdd3q6N4QQ4nk2VXTbtm2L8ePHY9++fWjWrJnZbUpKSrBixQq8//77uHjxIp577jlJO3q7aNMGiI/nH1ZbtgD9+3u6R4QQX/HHH/xy8GBArfZsXwghxBvYlOgeO3YMUVFRVrcJCgrC2LFjMXbsWOTm5krSuduRQsE/pL76ig9foESXEGKrtDR+OWiQZ/tBCCHewqahC9Uluc5uT0wNHswvxRJBhBBSnRs3gH37+O/9+nm2L4QQ4i3smowGALm5ufpE9uLFi/jiiy9QUlKCYcOGoUePHpJ38HbUrx/g7w+cPs1/Gjb0dI8IId5uwwZ+wpmmTfkKLoQQQuxYXuzw4cOoW7cuYmJi0KRJE6Snp6Njx4547733sHDhQtx5551YIda1IU4JDwfuuIP/vm6dZ/tCCPENYtgCDXcihBADmxPdF154AS1btsSWLVvQu3dv3HXXXRgyZAjy8vJw8+ZNPP7445g9e7Yr+3pb6dOHX27e7Nl+EEJ8AyW6hBBSlc1DF/bs2YMNGzagVatWaN26NRYuXIgnnngCyn9XJP/vf/+LLnQaHsn07s0vN2/mhyPpfPWEEEvOnQPOnwf8/IBevTzdG0II8R42V3Rv3LiBuLg4AEBoaChCQkJQo0YN/e01atRAQUGB9D28TXXsCAQGAlevAidOeLo3hBBvJqq5XbvyNXQJIYRwdp0gUlGprFj5byIdtZp/aAHApk0e7QohxMutX88vabUFQggxZdeqCxMmTID631XIS0tL8Z///AchISEAgDI6jZfkevcGNm7kwxcmT/Z0bwgh3ogxYPt2/rsY8kQIIYSzOdEdP368yd8PPPBAlW0eeugh53tE9MRYOxqnSwixJDMTyMri43M7dPB0bwghxLvYnOguXrzYlf0gZnTuzIcwZGcDp04BjRt7ukeEEG/zzz/8sm1bIDjYs30hhBBvY9cYXeJegYE82QVomTFCiHki0e3WzbP9IIQQb2RTRXfUqFE2P+Bvv/3mcGdIVb16AVu2ANu2AZMmebo3hBBvQ4kuIYRYZlNFNyIiQv8THh6O9evXY+/evfrb9+3bh/Xr1yMiIsJlHb1dderEL42ebkIIAQAUFgIHD/LfKdElhJCqbKroGo/PffHFFzFmzBh89tlnUKlUAACtVosnnngC4eHhrunlbaxjR3554gRQUEBrZBJCDPbsAbRaICkJSEz0dG8IIcT72D1Gd9GiRXjuuef0SS4AqFQqTJkyBYsWLZK0cwSIjeUfYowB+/d7ujeEEG+yYwe/pGouIYSYZ3eiW1FRgRNmTtV14sQJ6HQ6STpFTIklg/bs8Ww/CCHehcbnEkKIdXadMAIAHn74YUycOBFnz55Fp38HkO7atQuzZ8/Gww8/LHkHCR++sHw5JbqEEAPGgF27+O9duni2L4QQ4q3sTnTnzp2LuLg4zJs3D1euXAEAxMfH4/nnn8fUqVMl7yAxjNOlCWmEECErC7h+HVCpgFatPN0bQgjxTnYnukqlEi+88AJeeOEF5OfnAwBNQnOx9u355blzQG4uEBXl2f4QQjwvPZ1fNmnC19wmhBBSlVMnjAgPD6ck1w1q1AAaNOC/U1WXEAIYEt02bTzZC0II8W42JboDBw7Ezp07q92uoKAAc+bMwccff+x0x4gpGr5ACDEm1s9t3dqz/SCEEG9mU6J7zz334O6770azZs3w4osv4ueff8b27duxb98+/P333/jwww8xZswYxMfHY//+/Rg6dKjkHX3rrbfQrVs3BAcHIzIy0uw2mZmZGDJkCIKDgxETE4Pnn38eFRUVkvfFE0SiSxPSCCEAVXQJIcQWNo3RnThxIh544AH8/PPPWLZsGRYuXIi8vDwAgEKhQLNmzZCamoo9e/agadOmLuloeXk57rnnHnTt2hVfffVVldu1Wi2GDBmCuLg4/PPPP7hy5Qoeeugh+Pv74+2333ZJn9xJjNMVH26EkNtXYSFw5gz/nSq6hBBimc2T0dRqNR544AE88MADAIC8vDyUlJQgKioK/v7+LuugMHPmTADAkiVLzN6+bt06HDt2DH///TdiY2PRpk0bvPHGG3jxxRfx2muvISAgwOV9dKWWLfllRgaQlwfQ2ZYJuX0dPsyXF4uPB2JiPN0bQgjxXnavuiBEREQgwouyrR07dqBly5aIjY3VX5eamorJkyfj6NGjaNu2rdn7lZWVoaysTP+3WElCo9FAo9G4ttP/tmN8aUloKFC7th8uX1YgPb0C3boxl/dNCrbG58vkHqPc4wN8L8Z9+5QAVGjdWgeNRlvt9r4WnyPkHqPc4wPkHyPF55r2quNwouttsrOzTZJcAPq/s7OzLd5v1qxZ+mqxsXXr1iE4OFjaTlqRlpZW7TaxsV1w+XIsfvzxKG7duuD6TknIlvh8ndxjlHt8gO/EuGpVKwD1EBJyBqtXH7f5fr4SnzPkHqPc4wPkHyPFJ43i4mKbtvNoovvSSy9hzpw5Vrc5fvw4mjRp4rI+TJs2DVOmTNH/nZ+fj6SkJAwYMMAtS6dpNBqkpaWhf//+1Q4B2bpVif37AaAFBg9u5vK+ScGe+HyV3GOUe3yA78X49tsqAMDIkfUxeHC9arf3tfgcIfcY5R4fIP8YKT5piSPw1fFoojt16lRMmDDB6jb169e36bHi4uKwe/duk+tycnL0t1miVquhVqurXO/v7+/WF6It7YnZ1UePquDvr3J9pyTk7ufTE+Qeo9zjA3wjRq0WOHKE/96+vR/s6a4vxOcsucco9/gA+cdI8UnXji08muhGR0cjOjpaksfq2rUr3nrrLVy9ehUx/87OSEtLQ3h4OJo1843qZ3VatOCXR47wiSgKhWf7Qwhxv/PngeJifja0hg093RtCCPFuDp0Z7datW/jyyy8xbdo03LhxAwCwf/9+XL58WdLOGcvMzER6ejoyMzOh1WqRnp6O9PR0FBYWAgAGDBiAZs2a4cEHH8TBgwexdu1avPLKK3jyySfNVmx9UaNGPLm9eZOf454Qcvs5cYJfNm4MqHzrwA4hhLid3RXdQ4cOoV+/foiIiMCFCxfw2GOPoWbNmvjtt9+QmZmJb775xhX9xKuvvoqvv/5a/7dYRWHjxo3o3bs3VCoVVq1ahcmTJ6Nr164ICQnB+PHj8frrr7ukP54QHAwkJwMXLvAPO4mK4YQQHyISXRdOXSCEENmwu6I7ZcoUTJgwAadPn0ZgYKD++sGDB2PLli2Sds7YkiVLwBir8tO7d2/9NsnJyVi9ejWKi4tx7do1zJ07F35+sllYAoDhw0182BFCbi+U6BJCiO3sTnT37NmDxx9/vMr1tWvXtrqMF5EGJbqE3N4o0SWEENvZneiq1WqzSzqcOnVKsollxDJKdAm5vVGiSwghtrM70R02bBhef/11/RkpFAoFMjMz8eKLL+Luu++WvIPEFCW6hNy+rl8HcnP5740aebYvhBDiC+xOdOfNm4fCwkLExMSgpKQEvXr1QoMGDRAWFoa33nrLFX0kRho35pfnzwNGZy4mhNwGTp7kl0lJfHIqIYQQ6+yeqRUREYG0tDRs27YNhw4dQmFhIdq1a4d+/fq5on+kkthYICQEKCriqy+IxJcQIn9nz/LLBg082w9CCPEVDi9JcMcdd+COO+6Qsi/EBgoFkJICHDrEP/Qo0SXk9iES3ZQUz/aDEEJ8hU2J7ocffmjzAz799NMOd4bYxjjRJYTcPijRJYQQ+9iU6L733nsmf1+7dg3FxcWIjIwEwM+UFhwcjJiYGEp03UB8yFGiS8jthRJdQgixj02T0c6fP6//eeutt9CmTRscP34cN27cwI0bN3D8+HG0a9cOb7zxhqv7S0CJLiG3K0p0CSHEPnavujB9+nQsWLAAjY0GhzZu3BjvvfceXnnlFUk7R8yjRJeQ209BAXDtGv+dEl1CCLGN3YnulStXUFFRUeV6rVaLnJwcSTpFrKtfn1+eOwfodJ7tCyHEPc6d45dRUUBEhGf7QgghvsLuRLdv3754/PHHsX//fv11+/btw+TJk2mJMTdJTgZUKr6O7pUrnu4NIcQdRKIrvugSQgipnt2J7qJFixAXF4cOHTpArVZDrVajU6dOiI2NxZdffumKPpJK/PyA2rX57xcverYvhBD3yMzkl3XrerQbhBDiU+xeRzc6OhqrV6/GqVOncOLf89A2adIEjeh8lG5Vpw7/4MvMBLp08XRvCCGuJr7UJiV5th+EEOJLHD5hRKNGjSi59SDxYUcVXUJuD6KiW6eOZ/tBCCG+xO5E95FHHrF6+6JFixzuDLGd+LATH36EEHmjRJcQQuxnd6J78+ZNk781Gg2OHDmCW7duoU+fPpJ1jFhHiS4htxdx9IYSXUIIsZ3die7y5curXKfT6TB58mSk0OKObkNDFwi5fZSXG1ZYoTG6hBBiO7tXXTD7IEolpkyZUuVUwcR1qKJLyO3j8mWAMUCtBqKjPd0bQgjxHZIkugBw9uxZsyeSIK4hEt1r14CSEs/2hRDiWsbjcxUKz/aFEEJ8id1DF6ZMmWLyN2MMV65cwZ9//onx48dL1jFiXWQkEBoKFBby4Qu0AAYh8kVLixFCiGPsTnQPHDhg8rdSqUR0dDTmzZtX7YoMRDoKBT9pxMmTfOweJbqEyFdWFr8UJ4ohhBBiG7sT3Y0bN7qiH8QBcXGGRJcQIl/iPR4f79l+EEKIr7F7jG6fPn1w69atKtfn5+fT8mJuFhfHL7OzPdsPQohrife4eM8TQgixjd2J7qZNm1BeXl7l+tLSUmzdulWSThHbiOoOJbqEyBsluoQQ4hibhy4cOnRI//uxY8eQbZRdabVarFmzBrVpAJlbiQ89GrpAiLzR0AVCCHGMzYlumzZtoFAooFAozA5RCAoKwoIFCyTtHLGOhi4Qcnugii4hhDjG5kT3/PnzYIyhfv362L17N6KNVi0PCAhATEwMVCqVSzpJzKNElxD5KykB8vL475ToEkKIfWxOdJOTkwHw0/0S70CJLiHyl5PDL9VqICLCs30hhBBfY1Oiu3LlSgwaNAj+/v5YuXKl1W2HDRsmScdI9cR4vWvXgIoKwM/uxeIIId5OjM+Ni6OzohFCiL1sSo1GjBiB7OxsxMTEYMSIERa3UygU0Gq1UvWNVCMqClCpAK0WuHoVSEjwdI8IIVITR2xoIhohhNjPpuXFdDodYmJi9L9b+nFVknvhwgVMnDgR9erVQ1BQEFJSUjBjxowqy5wdOnQIPXr0QGBgIJKSkvDOO++4pD/eQqUC/t0tNHyBEJmiiWiEEOI4nzjYfeLECeh0Onz++edo0KABjhw5gsceewxFRUWYO3cuAH7CigEDBqBfv3747LPPcPjwYTzyyCOIjIzEpEmTPByB68TF8UOblOgSIk/ivR0b69l+EEKIL7Ip0f3www9tfsCnn37a4c5YMnDgQAwcOFD/d/369XHy5El8+umn+kR36dKlKC8vx6JFixAQEIDmzZsjPT0d8+fPl3WiW6sWv8zN9Ww/CCGuId7bRgvdEEIIsZFNie57771n04MpFAqXJLrm5OXloWbNmvq/d+zYgZ49eyIgIEB/XWpqKubMmYObN2+iRo0aZh+nrKwMZWVl+r/z8/MBABqNBhqNxkW9NxBtONpWZKQKgBJXr2qh0XjfihjOxucL5B6j3OMDvDvGa9f4ezwiwvH3uDfHJxW5xyj3+AD5x0jxuaa96igYY8zFfZHcmTNn0L59e8ydOxePPfYYAGDAgAGoV68ePv/8c/12x44dQ/PmzXHs2DE0bdrU7GO99tprmDlzZpXrv//+ewQHB7smAAl9/nkr/PVXPdxzz0mMG3fC090hhEhsxoyuOHgwBs88sx933nnR090hhBCvUFxcjPvvvx95eXkIDw+3uJ1TY3RFjqxwcM2bl156CXPmzLG6zfHjx9GkSRP935cvX8bAgQNxzz336JNcZ0ybNg1TpkzR/52fn4+kpCQMGDDA6hMnFY1Gg7S0NPTv3x/+/v5233/XLiX++guIimqAwYPrV7v9pk0KbNigQPfuDAMGMMmXK7p5E1i6VIlbt4BevRi6dCl3Kr7qlJcDa9cqcPCgAnXqMNx9N0NIiOTNVJGWpsDq1QqUlQG9elUgJGQNUlNdE6PAGLBmjQIbNyqgVgODBjF06+b676mlpRrMnn0IpaXtEROjxIgROtSv/qXmtNxc4M8/FcjJUaBnT4ZOnaR/vQoajQbr1qVBoUjFyZP+SEpiGDGCSb5kn04HbNyowKlTCowYobNpJYXXX+cn4unduxUGD27pULvO/p/xBXKPUe7xAfKPkeKTljgCXx2H/o1/9dVXeO+993D69GkAQMOGDfHss8/i0Ucftetxpk6digkTJljdpr7RJ2pWVhbuvPNOdOvWDQsXLjTZLi4uDjliZfV/ib/jrExXVqvVUKvVVa739/d36wvR0fbEqgs3b6rg72/9zHTTpwNvvmn4+7//BewYfl2t9euBMWOAGzcM140ercR99ylc8nxmZADDhwMHDxqumzkT+PFHoFs3SZvSKy8HHn4Y+P57w3VffqlC69Zd0a2bP2JjXfOaycsDHngAWLXKcN2cOcBjjwGffOK6NZSzs4F771Vhy5Yu+utmzFDh3Xf568dVfv2Vx3bzpuG6UaOAJUuAsDDp28vLA6ZP74YjRwL117VowZ/vf8+V4zStlr8/Vqzgf7/8sgq//Qb072/9fuL9FBvrB2ffQu7+v+YJco9R7vEB8o+R4pOuHZswO02fPp2FhISwl156if3+++/s999/Zy+99BILDQ1l06dPt/fhbHbp0iXWsGFDdt9997GKiooqt3/yySesRo0arLy8XH/dtGnTWOPGje1qJy8vjwFgeXl5TvfZFuXl5WzFihUm/bbHN98wBjDWv7/17fbuZUyh4NvedZfh9yVLHGq2ioMHGQsL44/ZvDljY8cy5u/P/+7VK5OVlTkWnyW5uYzVqcMfPyqKsQcfZCw5mf8dHs5YerqkzTHGGNPpGHvoId6GSsXYY48xNmUKY0FBun/j1LKyMunbLS9nrF8/3m5AAGOTJjF2//2GffjYY7xvUissZKxNG95GYKCGPfKIlvXsyf8GGPvsM+nbZIyx1av58wsw1rQpYyNH8rgBxvr0YczM298pZWWM3XGHlgF8X95zD2M1a/L2mjRh7MYNadp59VX+mGo1Yy1a8N+TkvjzbE14ON/25EnH23b2/4wvkHuMco+PMfnHSPFJy9Z8ze5Et1atWuz777+vcv3333/PoqKi7H04m1y6dIk1aNCA9e3bl126dIlduXJF/yPcunWLxcbGsgcffJAdOXKE/fjjjyw4OJh9/vnndrXla4nuqlX8Q7BdO+vbiQRl3Dj+98yZ/O/EROZ0cqbVMtahA3+83r0ZKy3l1//5J2N+fjwJ/OknjXONGNHpGBs+nLeXksJYZia/vrDQEGfTps7HVdnXXxuS3NWrDdfv2VPOgoLKGcDYK69I2yZjjM2YwdsNCWFs1y7D9b/+yphSyW9bulT6dh95hD92dLSOffzx36y8vJzpdDxGgDE/P8YOH5a2zZwcxmrU4I//wAOMaf592fzzD48f4M+HlN5+mz9ucHA527WLvw8zMxmrXZtf/8QTzreRlWVI1r/7jrGiIsMXM2vxlJcbvlhcu+Z4+3L/gGVM/jHKPT7G5B8jxSctlyW6ERER7NSpU1WuP3nyJIuIiLD34WyyePFiBsDsj7GDBw+yO+64g6nVala7dm02e/Zsu9vytUR3xw7+IZicbHmb8+f5NkolYxcv8utKShiLj+fXf/WVQ03riQQwLIyx7GzT2156qeLfypWOlZQ4146wdq2hurl/v+ltubmMxcTw2996S5r2GGPs5k3GoqP54779tult5eXl7Pnnd+v7dPq0dO2eOcMrgABjP/xQ9fbXX+e3xcbyPkpl505DgrV+vcbkNWr8ReOOO6StJouKedu2PMkztnSpoSKakSFNe5mZjAUF8cd99tm9Ju/DjRsN75tDh5xr5/nn+WN172647vvvDe9dS89hdrZhPzhTyZb7Byxj8o9R7vExJv8YKT5p2Zqv2XRmNGMPPvggPv300yrXL1y4EOPGjbP34WwyYcIEMJ6UV/kx1qpVK2zduhWlpaW4dOkSXnzxRZf0x5uIFdaMx8VW9ssv/LJXLyAxkf8eGAiIOXgff+x4+4wBb7/Nf3/55aqL2r/0kg5RUSW4eFGBpUsdb8e4vf/7P/77k08Cbdua3l6zJjBvHv/9nXeAggLn2wSABQuAa9eAJk2AqVOr3t6tWxb699ehvBx47TVp2gSAGTOAsjI+jvPee6ve/sILQOPGQE4O76NUnn+eX44fD/ToYfo+Uyj42O7gYGDbNmDNGmnaPHEC+OYb/viffYYq41HHjgV69+bPh1TP8fvvAyUlQPfuOvTqdcnktt69+bhgnQ54913H2ygtBcRiMNOmGa4fMQIICeFjzXfvNn9f8b6OjORnQiSEEGIfuxNdgE9Ga9GiBR599FE8+uijaNmyJb744gsolUpMmTJF/0NcLyqKXxYU8IlS5vz0E78cM8b0+vHjAaUS2L8fOH/esfY3bwZOngRCQ4Ennqh6e3AwMHToWQDAe+/xRNUZmzYB+/bxBME4aTB2//08+cvLA774wrn2AJ6oiCRyxgzAaKlmPYUCeOMNfgrsZcuAy5edb/fSJf5YADBrFsyuOKBW8z4BvI8lJc63u3cvsHUrn+BmPHnRWJ06wH/+w393Jgk0Nn8+vxw+HOjUqertCgV/HgDg2295cu+MggLgyy/57y++qDP7/Irvyj/95PhJWdLSgPx8oHZtYNAgw/VBQcCwYfx3sZ8rE22K9zkhhBD72J3oHjlyBO3atUN0dDTOnj2Ls2fPolatWmjXrh2OHDmCAwcO4MCBA0hPT3dBd0llkZGGBMh4hrpw6xawZw//fcQI09uio3nVCuCz3B0hKlXjxlmeDd+vXwZCQxmOHuUVQGeIxTYefNDymaKUSkPVdcECXpFzxvff82punTrA6NGWt2vXjlfNKyqcq5ILH33EH6t3b6B9e8vb3XMPXxng2jXT1SAc9cEH/PLeew1HAMx59lmeDG/caLryhSNyc3k1FwCee87ydl26AJ078+dlyRLn2vz+e56ANmoEDBhg/htYx458v5aVOd6eOKJy9938tWls1Ch+mZZm/r6U6BJCiHPsTnQ3btxo08+GDRtc0V9SiUrFk13AfMVp3z5+Wa8eYG6VNZG4OZLolpYCf/zBf5840fJ2oaEVGDmSJxKiuuyI69eB337jv1d3VucHHuCJ94ULwD//ON4mAHz3Hb/8z3+qX8ZLLLn17bfOJdhaLX8MAKjuZIN+fsDkyYZ2nZGfD/z8M//9mWesb5uUxKuvgOE5ctQvv/BksnXr6peGe/xxfrlwoXNHCEQV9dFHqyaggkLBbxd9tJdGA/z+O//d3Jek7t355bFjQFFR1dvF0AWjk0ASQgixg0NDF4h3EdUec4muGPvXsaP5+951F7/cs8f+8awbN/IP59q1gQ4drG87ejTP+n75hSdxjvj9dz48o02bqmNzKwsKMlTLnKlyZmXx4RIAHyNanSFDgPBwPuzAmQR761bedmQkMHhw9duLvm3eDFx04uRZK1fyhLNx4+r3KcAr+QDwww+O71dxf/F41Z0UYswYPiTm3DngwAHH2svJ4c8VYL1KDxiS+V27+LrC9ti/nw+hqVHDfAIfH8/fPzod37YyqugSQohz7E50S0tL8e6772Lw4MHo0KED2rVrZ/JD3M/ahDQxbMHcmEeAV+Xq1uVJyo4d9rW7ciW/HDas+uSkb1+GyEieKGzfbl87gqiMjRxp2/YiCfvpJ8eTsJ9+4lXD7t3581SdwEBD/0Ty5ghx37vv5uNwq1OnDtCzJ//9xx8db1dUOe+9t/p9CvAkPDKSj0neutWxNi9fBrZsMbRbnZAQYOBA/rt4Tdhr+XKeXHbsyI92WJOQwLdjzPSEHbYQz0mPHpYnk4n3prkJaVTRJYQQ59id6E6cOBHvvPMOkpOTcdddd2H48OEmP8T9rFV0RaJrqaILGBIkkWzYgjHgzz/570OHVr99QIChMmlpPKI1xcWG+9n6MrvzTp6E5eYangd7iRirq/oZE8naH384dmidMcOQkMoTCK0R24o+26uoCFi3jv9uS8IJ8CRcTKhavdqxdtes4TF37swTdluI14A4y5i91q7ll5XHrVfXnr3PrXhPifeYOeK9ae41ShVdQghxjt0nDl21ahVWr16N7mJwGfG4iAh+Wfm0z9ev80PoAJ9QY0nPnnwikD2JbmYmP0Tu58cnYNmib18+jGD9euCNN2xvCwA2bOBjgpOTgVatbLuPnx/Qrx8fLrF2LZ/IZI/iYkNFTlQQbdGrF08AL17kK1I0aWJfu0eOAFeu8OEX1hKkykQft2/nw1DsPVXu5s18aEjdukDTpva1+803/Dl+5x372gQMybU9z/GQIbxCeugQf56Tkmy/r1ZrGI7Sr59t9+nbF3jlFT6ZkjHbqt06nWHyZY8elrcTia65oQviPS3e44QQQuxjd0W3du3aCHPFyeaJw0JD+WVhoen1587xy9q1DduYIz6Ed+/ms9ltIT7A27Xj4yVt0bevoZ3KSXl1RGIyYIBtSYaQmsovRQXPHlu28PGqderwMau2Cg42PKciibOH6Gvv3nwohK1SUoAGDfg+dGQuqKiY9+9v33Mstj90iCfo9tBqDe2KfWWLqCjDShT2fEED+LjeW7f4WGpbR1u1a8f3xfXrwKlTtt3nxAm+EkpwsPUx5eK1df581SE24j1t7f1LCCHEMrsT3Xnz5uHFF19ERkaGK/pDHFBdolu/vvX7N2jAH6OszPYPcTHO1p7CfnIyT8a0WvuTE1FZtafCCRiSp127+KQge4gk1d7kWtzH+DEcbddeIl5H2jVOdO1Rq5Yh6bR3WMq+fTwZjIiwPrzGHPFaEJPKbCW+BPTuXf0qGkJAgGEsra1L5Ikl19q0qXryC2MJCfzxKyoMR2AEMUGUaguEEOIYuxPdDh06oLS0FPXr10dYWBhq1qxp8kPcT3wIVl41wdZEV6kEWrbkv9u6HqojiS5gGOZgz8S3wkLDYV17E92kJB6/Tmf57FOWiISmTx/77gcYDolv2WLfRLiKCsNza+thdWOir/auV5yTAxw9yhN6R+IV97F3oqHYvmdP25NOwZGx5YDhuRFrSNvqjjtM718d8V6qbqiNSsW/BAKG96xAFV1CCHGO3WN0x44di8uXL+Ptt99GbGwsFPaWuojknK3oAnz90h07+IdzdctoFRUBhw/z36tb87Syjh2BRYv42bdstXMnTwDr1LF9spKxLl34c7Fzp+3VytJSQJzzxN6xvQD/4hAczL98nDgBNG9u2/2OHOFjg8PDgWbN7G+3a1fD49gzTld8CWja1LGJT+I52rnTvvuJ7UW/7XHHHTwxP3mSJ+qVTz9tiVhb2tJKJJaI1/quXbZtf+gQv2zduvpt69cHTp/mwxfuvNNwvfjySokuIYQ4xu5E959//sGOHTvQ2pb/3sQtqqvoVrd8EmCoOokPZ2uOHuUTcmJj+Tqg9hCHp/futX1Sj0iGREXNXl268Elw9iRhBw7wxf5jYmxbVqwyPz++Du2WLTwxsjXRFX3s1MnySQysiY/n1cGMDJ68inHR1RHJW+fO9rcJGBJdexNsZ9qtUYM/r0eO8FhtWf0jK4v/KJV8SIE9xPanTvFhPtUt+2ZrRRcwfBm1VNGloQuEEOIYuz9KmzRpgpKSElf0hThIqoouYNvQBVHNFcMd7NGiBR+PeOMGr17ZQlRWrZ0G1xrjaqOty32JhLNLF/vH51Zu19YKYOV2HSXua8/wEFHRtbfKKYgEW6ezfSm37GyekCsUtp2cwhwxycvWM46Lam6zZnw9XnskJPDkWqsFjh+3vu316zyhBmx7n1hKdKmiSwghzrE70Z09ezamTp2KTZs2ITc3F/n5+SY/xP3MVXQ1GsMZsmxJdMWHcVYWnxxkjaj6OpLoqtWGCpetwxdEEmNvBU5o3Zq3e+MGcOaMbfcRCaejFU7j+9pTSRZJsTOJrhgGYGu7xuOXnYnX3uELItbmzflQDUeIRNfWM6SJ15wjibVCYfuRjyNH+GW9erZVY8VRF+NElzGq6BJCiLPsTnQHDhyIHTt2oG/fvoiJiUGNGjVQo0YNREZGokaNGq7oI6mGuYpuZiZPYAIDgbi46h8jLMyw3dmz1rd1pqILGJIMc+uGVpafb+iPo6NlAgIMfbVlaAZgSK4drTQChurokSN8zG91ior4eF7A/hUIjInKt60TC8+c4StSBAbyiru72pXiORZffuyt6Dp6dEC8jsR7wBLxhcrWZenMVXSLiw1HIKiiSwghjrF7jO7GjRtd0Q/iBFHtMU50c3L4ZUKC7YfeU1L44eSzZy0nH4wZPuRtPXFDZWK8qkjqrBFJU1KSc2eHatGCV/OOHOGn1bWmtNSQqDiazAN8/eIaNXiF/OTJ6hP1Y8f4ZWwsHxvsKJGsXrrE14uNjLS+vfEXF2vLYNnarqhmVkds50xyLRLd8+dti1UMOXD0tWtrRVd8OUtJse1xa9fml9eu8YmXfn6m72d7h1kQQgjh7E50e1k5DdYRWz/hiKREtcd46ML16/yyVi3bHyclhS/3ZK2ie/Uqf2yFwrFVAQDDWbeqG+cIOD9sQRDJ1NGj1W974gSvhteoYVs13BKFgif127bxpK66RFeKxA/gyV5SEh+6cuRI9ZP4xHNi64Q5S0S/bZ2sJUW7NWoYJt+lp1tfMqy01DAu3N6z1Qnii091/+rsTXSNV2a8eROIjja8n0NCHJuYSAghxIGhC5UVFBRg4cKF6NSpE63E4CHmKrqOJrqA9URX3FanDj9FrSNEknH2LD/lrDUiGXKmsgrYV20UbbZo4fhEtMrt2pJgi745m3Aat2tLvKKS7OgXFyExkZ/4oaKi+hOPlJfz5bQA5xN78dqo7gjB6dP8iESNGjyRdETDhvwyKwuwNifXnomgAK/gipFf4r1L43MJIcR5Die6W7Zswfjx4xEfH4+5c+eiT58+2GnvIppEEqKiW1bGJ6EBrkt0RUXMliXLLElI4B/eWm3144FFMtSokePtAVWrjdZIVVkFDEmrLYmucYLtLFsrj8btOptgKxS2J9inTvGEODzccNjeUSL5rC65FolwkyaOf4GpWdOQeFo7OaS9FV3A8F4V711acYEQQpxnV6KbnZ2N2bNno2HDhrjnnnsQHh6OsrIyrFixArNnz0ZHZ2bQEIcZfxCKKpCrEl171ua1RKEwVHWrG74gEl2RzDgqIYEf0tdqq0+IPFVZlTLBFo9R3aSpigo+fhhwvqJr3G518RrH6mzVXLw2xGvFEuNE11EKheWlwIQbN/h4YcD2ii5QNdGlii4hhDjP5kR36NChaNy4MQ4dOoT3338fWVlZWLBggSv7RmwUEMB/AEMVyJlE9/Jly6sEiIquPR/g5ohkw9rh5pISwxJpzia6xmOKq0uuxe1SJLriMc6f57PoLcnL4887IE3CaeuEvzNn+FGAkBDHzjpXmSeeY1Htd0eiC5hfCsyY+KIYH8/PjmcrqugSQoj0bE50//rrL0ycOBEzZ87EkCFDoFKpXNkvYqfKS4w5kujWqsUfhzHLh2WlqOgChmRDVBOttRURYV8clojk3NqJKrRaQ+wNGjjfZnQ0ryQzZr1dkRzFxPB4nSW+tFy9WvVEIsaMkz8pJjyJdqs7GYiIV4rnWHwJOneOV6gtEbHauuSXJdVVdO0dnytQRZcQQqRn80fbtm3bUFBQgPbt26Nz58746KOPcF38RyYeV3lCmiOJrkJhGC8pzupUmRRjdAHDaXUzMy1vYzxswdnD24Chz9aSsEuXeLIUEMCHO0jBlnalqpQLERGGmfzubNe42mntLHRSvY4APgkuMJBXpq2Nm71wgV/aM27WnOq+MInKfFKSfY9LFV1CCJGezYluly5d8MUXX+DKlSt4/PHH8eOPPyIhIQE6nQ5paWkoMF7birhd5SXGHEl0AX64FQCuXKl6W3m5fWdbsyY5mV/amuhKobpKnPFtycnSLelU3aFuQNrET7AlXpH8SdWu+AKTn2/9DHtSxqtUGpJXS8MXCgv52FnA+SEa1e1P8d4R7yVbUUWXEEKkZ/dHeUhICB555BFs27YNhw8fxtSpUzF79mzExMRg2LBhrugjsUHlim5uLr+UMtHNzORVuqAgflIDZ4hk4+JFvmatOeKkDVIc3gY8U1m1tV1HD3dbY0uiK/okElRnBQcbXkOW2i0pMby+pEqwxZchS6d4Fl/QIiIcP92wYPy8mqtaS53oUkWXEEIc51TNqnHjxnjnnXdw6dIl/PDDD1L1iTjAuKJbUWGopkmZ6IpkISnJ+aEE8fGASsUPN2dnm99GVHulSsJEUpWRwcfimuOKyqo9CbavV3SNH8tSvGJ4QWio6YkSnCG+OF26ZP528VqSYsKdGJJQWGh6khZBqkRXPDZVdAkhxHGSHJxVqVQYMWIEVq5cKcXDEQcYV3Rv3uSVJoXCsAi9rawluiIhtfcD3Bw/P8N4YEvDF8RYR2fXWRVq1+anuNVoDI9dmacSXakm+RmrLtFlzJDoSvVlwpZ2jZ9jKcZeA4bXiKX9KmWiGxJi+GJp7kuauM7es+qJRFccjaGKLiGEOI9OLCkTxhVdURGqUYMnlPawlujm5PBLZ4ctCCLpcFeiq1IZxgZbSjpdkXAaJ7rmDnXrdIaE051DF27cMFQNxfMiheoSe1d8mUhM5JfuqOgChiRWvCeMUUWXEEK8ByW6MiES3aIixyeiAYYPZ3OrLjhaqbLE2oS0khLD5CGpEl2g+olErkjCRLW0oMAQk7ErV/hEP5XKkLBJoboEWyTXcXGOn87ZHHsqulKxtaJr70oIloj3QOWKbmmpYdiQo4luXh4/6lBUxP8OCXG8n4QQcrujRFcmxAkjysv5jHfAsUk3YkktaxVdqRJdaxVdkWgHBfF1aKUiEklz8Wk0hhilqvwBPAbxnJlb/kqMfU5MtL8Cb43Yl2VlhjN1GXNFwgkYkk5zzzFgqLpKWUU2TnTNJfXiOZZqv4qjGpUTXfG3Wm3/sCHj9ZPz8/l7GTC8twkhhNiPEl2Z8PfnlxoNr4YCjlXpRBUqP7/qmbzEh7jUQxfMJX/GwxakGscJWK7EAcC1azxJUqmkOUGFMfG8WhvTKcXYZ2OBgYYvCeaSTpFwSlXlFKw9x8bXS/WFCTAkusXF5pN6Vw1dqByjeJ7j4ux/3apUhvdxSQl/LwOG6wghhNjPZxLdYcOGoU6dOggMDER8fDwefPBBZFU6vn7o0CH06NEDgYGBSEpKwjvvvOOh3rqfcUVXJKj2nH5UCA83JMiVkyOpK7oisTM3zlHq8bmCtSRMXBcTI90aupXbNRerKxI/wVqCLfX+rNzm9euGqqQxV8QbFGRYwaHy8AXGpH89Wdqfjo7PFcR7triYKrqEECIFn0l077zzTvz00084efIkfv31V5w9exajR4/W356fn48BAwYgOTkZ+/btw7vvvovXXnsNCxcu9GCv3Ueqiq5CYXlCmtQV3ehofnntWtXbPJnouiLh9HS77phcKNSsaRiCcfWq5XaljtfSON2iIj52FuBfYqRQXUXX0URXvGepoksIIdKQcESga/3vf//T/56cnIyXXnoJI0aMgEajgb+/P5YuXYry8nIsWrQIAQEBaN68OdLT0zF//nxMmjTJgz13D6kSXQCIiuITiYwnTul0hqRFqgRFJLrmkiG5JbqWxnQCpoe7pWbLcnFSt6tU8ngvX+ZtGE+wKyszTNaSOsFOTAQOH6668oL4IhUYKN3ELkv7U0wEFa9texknulTRJYQQ5/lMomvsxo0bWLp0Kbp16wb/fzO8HTt2oGfPnggw+lRITU3FnDlzcPPmTdSwMDOkrKwMZWVl+r/z/53JpdFooBElFRcSbTjblkqlBKBCaakOhYUMgApqtQ4ajYUzI1gRGakCoMT16xXQaPjMnmvXAK2WP9c1amhga3etxcfHj/r/u/C+BoGBhtsuXuR9iIvTQqOxcOo0B0RF8Tazsxk0mgqT2y5f5s9hTIx9z5st+zA6mj92VlbVx87K4rFGR0sbKwDExop2qz52drYfAAWiogz72RxHXqOxsSpcvqzEpUsVaN3a8Ng8CfWHvz9DaGiFza8jW8TH8+cxM9M01itXFAD8EB3NUFFRYfa+9sZYqxZ/zJwc09fRjRv8+Q4Pd2xfBgbyfVJQUIHychUABRQK6/vHFlL9n/Fmco9R7vEB8o+R4nNNe9XxqUT3xRdfxEcffYTi4mJ06dIFq1at0t+WnZ2NepWmj8f+W3bJzs62mOjOmjULM2fOrHL9unXrEOzIIFcHpaWlOXX/06frA2iJjIwslJcXAWiMq1cvYPXqw3Y/VnFxBwC1sWPHcURF8TWiMjLCAPRBWFgZ0tLW2P2Y5uJjDPDzG4qKCiWWLduA6OhS/W3Hj3cHUAtXruzH6tVm1jpzUHGxH4AhKChQ4Lff1iIw0JB07trVEkB9FBaewerVx+1+bGv78MqVBAAdcfz4Daxevd3ktpMnewKogUuX9mL1agszuBx082YKgBbYty8Lq1fvN7ktM3MAgCCcObMdq1ffqvax7HmNKpWdAcQhLe0IFArDbMNTpyIB9EJERAn++su513xlBQVNADTG3r0ZJq/7vXtjAXSBv38eVq/ebPUxbI3x2rVAAKnIzmZYtWq1fkz34cNtAdTB1asnsHq1hfMRW1Fe3gtAJLZs2YO8vFYAQrB37z8oKLhp92OZ4+z/GV8g9xjlHh8g/xgpPmkUV54xb4FHE92XXnoJc+bMsbrN8ePH0aRJEwDA888/j4kTJyIjIwMzZ87EQw89hFWrVkHhxLT8adOmYcqUKfq/8/PzkZSUhAEDBiDckfW57KTRaJCWlob+/fvrq9OOyMzkn7S1aiUgMZFXf5o0ScbgwfZPqf/zTyW2bwfi45th8GD+3K9fz5/jpKQADB482ObHqi6+mBgFsrKAVq36oG1bw/X/93/8pdm/f1vceWcbu2OwhDEgOJihuFiBNm1STU7Q8O23KgBA9+4pGDzY9jW3bNmHoaEKzJ0LaDRRVZ6/p5/msQ4Z0h6dOjlXuavs1i0FliwBlMraGDzYMEZBpwPy83m7I0d2s7rygiOv0ZUrVdi7F4iObonBg5sbtctfR8nJgXa9jmxx6pQSP/8MhIfXNXndX7/O22zQINxim/bGWF4OPPYYUFGhRNeug/89UgB89RV/DXXu3ASDBzeyO4Z331Xh7FmgRYuO8Pfnj9WrV1e0a2f3Q5mQ6v+MN5N7jHKPD5B/jBSftMQR+Op4NNGdOnUqJkyYYHWb+kaZSK1atVCrVi00atQITZs2RVJSEnbu3ImuXbsiLi4OOZWmQIu/46wMQlSr1VCr1VWu9/f3d+sL0dn2xGF/rVYJMRIjJESl/7C0h5i9XlBguH9eHr8uOlrhUD8txRcdzdfMvXHD32TSjRgfHBPjJ/lknLg4PgY5N9cfjRsbrhdjOWvXdux5s7YPxVjjnBzT548xwzjPxETpYxUJbHa2Ev7+hrmnubmGyU61a/vb1K49r1Gxhu+1a6bPpRjDGh9v2h8piIlmN2+aPrZ4LUVHV9+mrTH6+/OTtBQWAoWF/vpxzuL/blSUY68hcRBJo/HT75+gINv2jy3c/X/NE+Qeo9zjA+QfI8UnXTu28GiiGx0djWgHZ23odHz8mxhf27VrV7z88sv6yWkAL583btzY4rAFORFDkzUaw/Jijk5GE2uv3jQ6WioSXeNF7aVgbuUFxgzJiUi6pSQSXUuL/bty9YO8PD7RSOybW7cMk46knpxl3G7lWMV3who1+MkN3NWuK59j8VqpfPY58dpydIKYJRERPNEV7w3AsIavoyc5Ea8LWl6MEEKk4RPLi+3atQsfffQR0tPTkZGRgQ0bNmDs2LFISUlB165dAQD3338/AgICMHHiRBw9ehTLli3DBx98YDIsQc7EF5vycudXXRDfC4wX3ndnomv8IS8OCUupuiTMFQlnRIQhoTQ+8CDajIyEyWQ8qYhVF27dMrwujPvgilgBzyS64rWSm2t6vSsTXcB8ouvod2taXowQQqTlE4lucHAwfvvtN/Tt2xeNGzfGxIkT0apVK2zevFk/7CAiIgLr1q3D+fPn0b59e0ydOhWvvvrqbbG0GGB+eTFH59KJapRxouvMaYWtMZfoiopcQIDjMVhjbmmokhJDjK5I/hQK88mfK5NrgO9L1b9H0I0rna5OdMXjVj6hgivbtVTRdXbJL0vMJbriKIijFV3xeqflxQghRBo+sepCy5YtsWHDhmq3a9WqFbZu3eqGHnkf4zOjSVXRdefQBeO1dI2HLUh5+l/BXMVatKlSSR+jEBPDT3dsLlapTzksKBQ86crN5fEaxgrzS1cluuaeY8CQdLoiXlHRvXULqKgwnLTCXRVdrdbwZcnZoQtU0SWEEGn4REWXVE/KE0ZYq+i6Y+iCOPTsivG5gPlKnHEi74rk2lK7zo7ptIW5/emq5E8wjpUZLSQhYndFvMbDBdwRqzi6Id4bxhOAnU10CwoM11FFlxBCHEeJrky4q6LrzqELrkp0zSV+7kw4zSXY7k50Xd2ueNyKCsPkSON2XVE19/MzPK7xOF3x2pK6ilz5i4t4foODHU9OxXvWOGmmii4hhDiOEl2ZcEVFt6CAJyqA6xIUcbjZeFyl+N0VE9GA6iu6rmKtouvKdt05uVAICTGMDXZnu5VfT2Vlhuqoq4cuODs+FzC8Z41fI1TRJYQQx1GiKxOuWF4MqHpYVuqKblgYvzQ+VOvJiq6nEl13V3RdtT8FhaJqvIy5PtEVrxlR0TWujErdpqWKrtSJLlV0CSHEcZToyoSUy4v5+/OKHGCoUrkqQRGJbmGh4TpXJ7rWKrqeGkLgygTbnesim2tXxFtUxCdsGd8mtcoVXfG6CgoyVJil4o5EV6mE/vTChBBC7Ef/QmVCyqELQNUkxR2Jrpi05OrJaJ5KOL2pouuJRFe0qVK5Ztk4oGpFVxwpEK8zKVWejObsGrpA1TG6NGyBEEKcQ4muTJibjOZMMlF5Qpqrhy4wxit+gPvG6ObnA/+eYM9jQxc8kXC6q93K8bpjZQtLFd3QUOnbcscYXRq2QAghzqFEVybEB2JZmWGheSkqujdv8sf890zLkidGwcGGpEdU39w1RlenMyRC7hi6IJ47T6324M4xuubadceXCXdWdF05dIEquoQQIg1KdGVCfCCKqijgXKIrKmDFxaYTeqROGBQKQ1si6RSJrjOHgK0JDDR8MTBXbXQVb1lezB2Twsy1685YRVvurOhKsQSfOAoj3sdU0SWEEOdQoisT5j4QnUl0xX1LSw0f4KGh0k/oAaquvCCSE1euCGCp2uiOiq67lxerHGtpqeGsW54auuAqIlEUK4+I15I7KrqlpaZ9cETl9yxVdAkhxDmU6MpE5UQ3IMC52dqBgfyypMT1CUrlRFckKa6asAR4Jgmr3KZO554qZ+V1dEWbxtV0V3DXhEZjYrUQ8RoSrylXxCm+iInVJESiK947jqic6FJFlxBCnOPn6Q4QaVSu/DhTzQUMH9alpa4fz1l56IKz6wDbwhNJmGizuNiwOoZYacKdFV2xP8PCXLt0lSeeY09UdAH+nFKiSwgh3ocqujJR+QNRykTXnRVdxjxT0XXH0AXjLwp5eYY2AwKcS46qY5xwumt8rvHjV36O3ZnourKia7zf8vJck+jS0AVCCHEOJboy4cqKrjsTXY3GsOSXKxNdT1Qb/fwMh9bz8tyz3BZgiFWr5RVOdyW6npiMZqmi66ohGsbJPFV0CSHE+1CiKxMqlWmy5GySaJzounKJJuPHLSgwJCiA+yq6Wq0hRndVOW/dck8VGeDJk0iYbt2SZnUAW3jD0AVXv3bFF5eSEqroEkKIN6JEV0aMPxSlrOiKdXlddXjdeIyuSFBUKtdWs4yTMOPl09xV5TSu6Lo60VUoTBN7Ea+7hy54coyuqyq6xidqoYouIYR4H0p0ZcT4Q9EVia6rqkvmKrqurOYCpkmYSMACAwG12n3tumPMqmBuuTg5J7piHVpXV3TFe6KsTJpE18+P/1R+fEIIIY6hRFdGKNG1nXh+SkpcnwwZM07+RDImDn+7kjvHXFduU5xVz52JbkmJ6ZnvfKWiC5i+d6miSwghzqFEV0aME1FnP9iNK4DuTHRLSvjvrk50jZMwkYi5upoLmCZiol1XrrgguHO5OEE8n1otUFFhSARduWyc8eumtNS1y4sBrkl0jd+7VNElhBDnUKIrI8bVH2c/2N1Z0TU3RtfVia5Iwtyd6HqqXePEXlSw3ZXoinbdEa9xEl1c7NrlxQDXJLrG+4UquoQQ4hxKdGXEOBF1Nonx9NAFV1b9AO9IdEVi5M52S0ulS8iqY/z4xs+zK6uUKpUh1uJi11d0zb2OKNElhBDvQYmujBh/KPp6ouuuim5p6e1V0XXH/hT8/AxnXnNnvMYrL3iioutsfMZJOQ1dIIQQ51CiKyOuGLpQUuK+RPd2GLpgPEvfU2N03ZXoAqZfKES77kp0jb84uXqMrpTL8FFFlxBCpEOJroz46tAFUW1zZ0XXU5PRPF3RvR3iFatYXLtmuM7VFV1ROQakTXSpoksIIc7xq34T4it8dTKaSEyKity36oI3jNF1V4UT8FxF1/jIQEUF/91dFd2rV/mlSuW6qrl4Do1POkIVXUII8R6U6MqIr1Z0xYd5RcXtNRnNE+16auiCcSLorkRXVHSDg01Pjy0lEYtYI1ipND3hgyOooksIIdKhoQsy4quT0URiYJzo3g4VXU+N0fVEvJ5IdEXy6cqqaOWKbmCg80k1VXQJIUQ6lOjKiHEi6uzQBXeeMOJ2T3TdPUbXE0MXjBNdVydv4rUj2nS2wmqNuUTXWZToEkKIdCjRlRFXVHSNl01yx9AFcVpcWl5MWp5edUEkggEBrhtGIPh6okvLixFCiHQo0ZUR4w90qSajAYYZ5a6u6AKGBf5p1QVpecvQBXeeZlm8bn0t0aWKLiGESIcSXRkRlTpAuoouYFqNcwXjRES0dTtMRnPXGcqM2/V0Rdedia5oU6VyXVuVJ6NJnehSRZcQQpzjc4luWVkZ2rRpA4VCgfT0dJPbDh06hB49eiAwMBBJSUl45513PNNJDxGJE+B8oujnZ0gQPJHoumvoAmCoIt8OFV1PjdEViaAnEl2q6BJCyO3L5xLdF154AQkJCVWuz8/Px4ABA5CcnIx9+/bh3XffxWuvvYaFCxd6oJeeYZzoSjEOsvJEIrkmuu6sNno60b2dhi7IIdGlii4hhDjHpxLdv/76C+vWrcPcuXOr3LZ06VKUl5dj0aJFaN68Oe677z48/fTTmD9/vgd66hnGia4UjCekAZToStnu7ToZTa6JrlSn/wVME11XDrsghJDbgc+cMCInJwePPfYYVqxYgWAzWdCOHTvQs2dPBBh9eqempmLOnDm4efMmatSoYfZxy8rKUCYyDgB5/x5jvXHjBjQajcRRVKXRaFBcXIzc3Fz4O3mcsrDQDwAv5ebmOt/3gADD4wFAUZEGubn2PYbt8fG28vIYAAXKyyuQm8sc6LXt/Pz8UFGhQG6uDoASFRXaf3+3jz37sLRUAcAPRUXs3+RIgdJS18daXs7bLSjQoaxMAUCBwkLb9qdzr1EVAKX+OVapGHJzK+zuvz0YUwJQ6V9LjFXfpqMxiudVUCp1yM3VOtZxfV8AgPchN9ex12TVx5Tu/4y3knuMco8PkH+MFJ+0Cv6dccxYNZ+fzAfodDo2cOBA9sYbbzDGGDt//jwDwA4cOKDfpn///mzSpEkm9zt69CgDwI4dO2bxsWfMmMEA0A/90A/90A/90A/90I+P/Vy8eNFqDunRiu5LL72EOXPmWN3m+PHjWLduHQoKCjBt2jTJ+zBt2jRMmTJF/7dOp8ONGzcQFRUFhasX/AQfW5yUlISLFy8i3NmlEryQ3OMD5B+j3OMD5B+j3OMD5B+j3OMD5B8jxSctxhgKCgrMztsy5tFEd+rUqZgwYYLVberXr48NGzZgx44dUFca4NehQweMGzcOX3/9NeLi4pCTk2Nyu/g7Li7O4uOr1eoqjxsZGWl7EBIJDw+X5QtfkHt8gPxjlHt8gPxjlHt8gPxjlHt8gPxjpPikExERUe02Hk10o6OjER0dXe12H374Id58803931lZWUhNTcWyZcvQuXNnAEDXrl3x8ssvQ6PR6MeGpKWloXHjxhbH5xJCCCGEEPnyicloderUMfk7NDQUAJCSkoLExEQAwP3334+ZM2di4sSJePHFF3HkyBF88MEHeO+999zeX0IIIYQQ4nk+kejaIiIiAuvWrcOTTz6J9u3bo1atWnj11VcxadIkT3fNKrVajRkzZlQZPiEXco8PkH+Mco8PkH+Mco8PkH+Mco8PkH+MFJ9nKBirbl0GQgghhBBCfI9PnTCCEEIIIYQQW1GiSwghhBBCZIkSXUIIIYQQIkuU6BJCCCGEEFmiRNeDPv74Y9StWxeBgYHo3Lkzdu/e7ekuVcuePs+aNQsdO3ZEWFgYYmJiMGLECJw8edKNvbWfM/tk9uzZUCgUePbZZ13XQQk4EuPly5fxwAMPICoqCkFBQWjZsiX27t3rht7az574tFotpk+fjnr16iEoKAgpKSl44403qj93uhfasmULhg4dioSEBCgUCqxYscLTXZKc3GOUe3yAb34u2EPu8QG+FyMluh6ybNkyTJkyBTNmzMD+/fvRunVrpKam4urVq57umkX29nnz5s148sknsXPnTqSlpUGj0WDAgAEoKipyc89t48w+2bNnDz7//HO0atXKDT11nCMx3rx5E927d4e/vz/++usvHDt2DPPmzfPKE7HYG9+cOXPw6aef4qOPPsLx48cxZ84cvPPOO1iwYIGbe+68oqIitG7dGh9//LGnu+Iyco9R7vEBvve5YC+5xwf4YIyMeESnTp3Yk08+qf9bq9WyhIQENmvWLA/2yjpn+3z16lUGgG3evFl/XZMmTRgAsz8LFiyQPAZrHI2voKCANWzYkKWlpbFevXqxZ555xuR2X4/xxRdfZHfccYfVx/WWGO2Nb8iQIeyRRx4xuW7UqFFs3Lhx+r+9JTZ7AGDLly83uc4X47BG7jHKPT6h8ueC3GKUe3yMeX+MVNH1gPLycuzbtw/9+vXTX6dUKtGvXz/s2LHDgz2zTIo+5+XlAQBq1qypv+7XX38FAKxfvx5XrlzBhQsXoFQq8fPPP+Oxxx6TMALrnInvySefxJAhQ0zua8zXY1y5ciU6dOiAe+65BzExMWjbti2++OILk228IUZH4uvWrRvWr1+PU6dOAQAOHjyIbdu2YdCgQfptvCE2KcglDmvkHqMc46v8uSC3GOUeH+D9MVKi6wHXr1+HVqtFbGysyfWxsbHIzs72UK+sc7bPOp0Ozz77LLp3744WLVror8/JyYGfnx+6d++OuLg4XL9+HTqdDj169HDr2VUcje/HH3/E/v37MWvWLIvb+HqM586dw6effoqGDRti7dq1mDx5Mp5++ml8/fXX+m28IUZH4nvppZdw3333oUmTJvD390fbtm3x7LPPYty4cfptvCE2KcglDmvkHqPc4jP3uSCnGOUeH+AbMcrmFMDEuz355JM4cuQItm3bZnL94cOH0ahRI/2L/+DBg4iJiamSrHijixcv4plnnkFaWhoCAwMtbufLMQL8H1mHDh3w9ttvAwDatm2LI0eO4LPPPsP48eMB+G6MP/30E5YuXYrvv/8ezZs3R3p6Op599lkkJCT4fGyVySUOa+Qeo9ziM/e5IKcY5R4f4BsxUqLrAbVq1YJKpUJOTo7J9Tk5OYiLi/NQr6xzps9PPfUUVq1ahS1btiAxMdHktkOHDqFly5b6vw8ePGjyt7s4Et++fftw9epVtGvXTn+dVqvFli1b8NFHH6GsrAwqlcqnYwSA+Ph4NGvWzOS6pk2b6g9PAd6xHx2J7/nnn9dXdQGgZcuWyMjIwKxZs/SJrjfEJgW5xGGN3GOUU3yWPhfkEqPc4wN8J0YauuABAQEBaN++PdavX6+/TqfTYf369ejatasHe2aZI31mjOGpp57C8uXLsWHDBtSrV6/KNocOHTJZqeDgwYMeWbnAkfj69u2Lw4cPIz09Xf/ToUMHjBs3Dunp6VCpVAB8O0YA6N69e5WlY06dOoXk5GT9394QoyPxFRcXQ6k0/TeoUqmg0+n0f3tDbFKQSxzWyD1GOcRX3eeCr8co9/gAH4zR7dPfCGOMsR9//JGp1Wq2ZMkSduzYMTZp0iQWGRnJsrOzPd01i6rr84IFC1ifPn3020+ePJlFRESwTZs2sStXruh/iouLGWN8RnxwcDD7448/9PdJTExkH3zwgXsD+5e98ZlTedUFOcS4e/du5ufnx9566y12+vRptnTpUhYcHMy+++47xph3xWhvfOPHj2e1a9dmq1atYufPn2e//fYbq1WrFnvhhRcYY94VW3UKCgrYgQMH2IEDBxgANn/+fHbgwAGWkZHhU3FYI/cY5R4fY9Y/F+QQo9zjY8z3YqRE14MWLFjA6tSpwwICAlinTp3Yzp07Pd2lalnr84wZM1hycrL+b1hYXmTx4sWMMcZOnTrFALCMjAz9fQYNGsQiIyPZtm3b3BWSCXviM6dyoiuXGP/44w/WokULplarWZMmTdjChQv1t3lbjPbEl5+fz5555hlWp04dFhgYyOrXr89efvllVlZWxhjzvtis2bhxo9n32/jx430qDmvkHqPc42PM+ueCHGKUe3yM+V6Min87TQghhBBCiKzQGF1CCCGEECJLlOgSQgghhBBZokSXEEIIIYTIEiW6hBBCCCFElijRJYQQQgghskSJLiGEEEIIkSVKdAkhhBBCiCxRoksIIW6yadMmKBQK3Lp1CwCwZMkSREZGurTNCRMmYMSIES5tgxBCvBUluoQQnzNhwgQoFArMnj3b5PoVK1ZAoVB4qFf2u/fee3Hq1CmP9kEk35V/XnnlFY/2ixBCpODn6Q4QQogjAgMDMWfOHDz++OOoUaOGZI9bXl6OgIAAyR7PmqCgIAQFBbmlreqcPHkS4eHh+r9DQ0OrbKPVaqFQKKBUUo2EEOIb6L8VIcQn9evXD3FxcZg1a5bV7X799Vc0b94carUadevWxbx580xur1u3Lt544w089NBDCA8Px6RJk/RDClatWoXGjRsjODgYo0ePRnFxMb7++mvUrVsXNWrUwNNPPw2tVqt/rG+//RYdOnRAWFgY4uLicP/99+Pq1asW+1Z56ELdunXNVleFixcvYsyYMYiMjETNmjUxfPhwXLhwQX+7VqvFlClTEBkZiaioKLzwwguw9SzvMTExiIuL0/+Ehobq+7dy5Uo0a9YMarUamZmZKCsrw3PPPYfatWsjJCQEnTt3xqZNm6rEVqdOHQQHB2PkyJGYN2+eSazmhlQ8++yz6N27t/5vnU6HWbNmoV69eggKCkLr1q3xyy+/6G8X1ej169ejQ4cOCA4ORrdu3XDy5EmTx/3jjz/QsWNHBAYGolatWhg5ciQA4PXXX0eLFi2qPBdt2rTB9OnTbXreCCHejRJdQohPUqlUePvtt7FgwQJcunTJ7Db79u3DmDFjcN999+Hw4cN47bXXMH36dCxZssRku7lz56J169Y4cOCAPsEpLi7Ghx9+iB9//BFr1qzBpk2bMHLkSKxevRqrV6/Gt99+i88//9wk8dJoNHjjjTdw8OBBrFixAhcuXMCECRNsjmnPnj24cuUKrly5gkuXLqFLly7o0aOH/rFTU1MRFhaGrVu3Yvv27QgNDcXAgQNRXl4OAJg3bx6WLFmCRYsWYdu2bbhx4waWL19ux7NaVXFxMebMmYMvv/wSR48eRUxMDJ566ins2LEDP/74Iw4dOoR77rkHAwcOxOnTpwEAu3btwsSJE/HUU08hPT0dd955J95880272541axa++eYbfPbZZzh69Cj+97//4YEHHsDmzZtNtnv55Zcxb9487N27F35+fnjkkUf0t/35558YOXIkBg8ejAMHDmD9+vXo1KkTAOCRRx7B8ePHsWfPHv32Bw4cwKFDh/Dwww878nQRQrwNI4QQHzN+/Hg2fPhwxhhjXbp0YY888ghjjLHly5cz439r999/P+vfv7/JfZ9//nnWrFkz/d/JyclsxIgRJtssXryYAWBnzpzRX/f444+z4OBgVlBQoL8uNTWVPf744xb7uWfPHgZAf5+NGzcyAOzmzZv6diIiIsze9+mnn2bJycns6tWrjDHGvv32W9a4cWOm0+n025SVlbGgoCC2du1axhhj8fHx7J133tHfrtFoWGJiov65Mkf0KSQkxOTn+vXr+uchPT1dv31GRgZTqVTs8uXLJo/Tt29fNm3aNMYYY2PHjmWDBw82uf3ee+81idV4HwrPPPMM69WrF2OMsdLSUhYcHMz++ecfk20mTpzIxo4da9L3v//+W3/7n3/+yQCwkpISxhhjXbt2ZePGjbMY/6BBg9jkyZP1f//3v/9lvXv3trg9IcS3UEWXEOLT5syZg6+//hrHjx+vctvx48fRvXt3k+u6d++O06dPmww56NChQ5X7BgcHIyUlRf93bGws6tatazJ2NTY21mRowr59+zB06FDUqVMHYWFh6NWrFwAgMzPTrpgWLlyIr776CitXrkR0dDQA4ODBgzhz5gzCwsIQGhqK0NBQ1KxZE6WlpTh79izy8vJw5coVdO7cWf84fn5+ZmMzZ+vWrUhPT9f/iHHPAQEBaNWqlX67w4cPQ6vVolGjRvp+hIaGYvPmzTh79iwA/rwb9wMAunbtatdzcObMGRQXF6N///4m7XzzzTf6dgTj/sXHxwOAfr+kp6ejb9++Ftt57LHH8MMPP6C0tBTl5eX4/vvvTSrChBDfRpPRCCE+rWfPnkhNTcW0adPsGiZgLCQkpMp1/v7+Jn8rFAqz1+l0OgBAUVERUlNTkZqaiqVLlyI6OhqZmZlITU3VDy2wxcaNG/Hf//4XP/zwg0kCV1hYiPbt22Pp0qVV7iOSYWfUq1fP7FJnQUFBJuOECwsLoVKpsG/fPqhUKpNtzU1gs0SpVFYZP6zRaEzaAfjQg9q1a5tsp1arTf423i+ir2K/VDfZb+jQoVCr1Vi+fDkCAgKg0WgwevRom+MghHg3SnQJIT5v9uzZaNOmDRo3bmxyfdOmTbF9+3aT67Zv345GjRpVSdKcdeLECeTm5mL27NlISkoCAOzdu9euxzhz5gxGjx6N//u//8OoUaNMbmvXrh2WLVuGmJgYk9URjMXHx2PXrl3o2bMnAKCiogL79u1Du3btHIjIvLZt20Kr1eLq1av68cOVNW3aFLt27TK5bufOnSZ/R0dH48iRIybXpaen65NW48lvojLuiFatWmH9+vUWx9z6+flh/PjxWLx4MQICAnDfffd5zUoYhBDnUaJLCPF5LVu2xLhx4/Dhhx+aXD916lR07NgRb7zxBu69917s2LEDH330ET755BPJ+1CnTh0EBARgwYIF+M9//oMjR47gjTfesPn+JSUlGDp0KNq2bYtJkyYhOztbf1tcXBzGjRuHd999F8OHD8frr7+OxMREZGRk4LfffsMLL7yAxMREPPPMM5g9ezYaNmyIJk2aYP78+fqTU0ilUaNGGDduHB566CHMmzcPbdu2xbVr17B+/Xq0atUKQ4YMwdNPP43u3btj7ty5GD58ONauXYs1a9aYPE6fPn3w7rvv4ptvvkHXrl3x3Xff4ciRI2jbti0AICwsDM899xz+97//QafT4Y477kBeXh62b9+O8PBwjB8/3qb+zpgxA3379kVKSgruu+8+VFRUYPXq1XjxxRf12zz66KNo2rQpAFT5YkQI8W00RpcQIguvv/66/nC10K5dO/z000/48ccf0aJFC7z66qt4/fXXHR7iYE10dDSWLFmCn3/+Gc2aNcPs2bMxd+5cm++fk5ODEydOYP369UhISEB8fLz+B+Bjhrds2YI6depg1KhRaNq0KSZOnIjS0lJ9hXfq1Kl48MEHMX78eHTt2hVhYWH6pbSktHjxYjz00EOYOnUqGjdujBEjRmDPnj2oU6cOAKBLly744osv8MEHH6B169ZYt25dlRNQpKamYvr06XjhhRfQsWNHFBQU4KGHHjLZ5o033sD06dMxa9YsNG3aFAMHDsSff/6JevXq2dzX3r174+eff8bKlSvRpk0b9OnTB7t37zbZpmHDhujWrRuaNGlSZWwxIcS3KVjlQVKEEEKIxJYsWYJnn31W8gqzFBhjaNiwIZ544glMmTLF090hhEiIhi5UotPpkJWVhbCwMJ86lSghhHizkpISMMaQn5/v6a6YuH79On755RdcuXIFd999t9f1jxBiHmMMBQUFSEhIsHq2RqroVnLp0iX9RBJCCCGEEOK9Ll68iMTERIu3U0W3krCwMAD8ibM0s1lKGo0G69atw4ABA6osXSQHco8PkH+Mco8PkH+Mco8PkH+Mco8PkH+MFJ+08vPzkZSUpM/bLKFEtxIxXCE8PNxtiW5wcDDCw8Nl+8KXc3yA/GOUe3yA/GOUe3yA/GOUe3yA/GOk+FyjumGmtOoCIYQQQgiRJUp0CSGEEEKILFGiSwghhBBCZIkSXUIIIYQQIkuU6BJCCCGEEFmiRJcQQgixk9yXoP/l2C+495d7kV9GJ9Agvk1Wie6nn36KVq1a6ZcG69q1K/766y9Pd4sQQm47J66fkG2SxBhDryW90PWrrqjQVXi6Oy7x3s738NPRn/DtwW893RVCnCKrRDcxMRGzZ8/Gvn37sHfvXvTp0wfDhw/H0aNHPd01Qgi5bRzKOYSmHzfFmJ/HeLorLlFaUYqtmVux89JO7Li4w9PdcQmNVgMA+PP0nx7uCXHGtwe/xfbM7Z7uhkfJKtEdOnQoBg8ejIYNG6JRo0Z46623EBoaip07d3q6a4QQctu4mHcRAJB2Lg25xbke7o30dEyn/33VqVUe7InrMPChGRvOb0BReZGHe+MaF/MuYtSyUdhwfoOnu+ISF25dwEMrHsKwH4fpv7jcjmSV6BrTarX48ccfUVRUhK5du3q6O4QQctsQSZKO6bDmzBoP90Z6Ij5AvhVPkcyXactkmwj+ceoPLD+xHC9veNnTXXGJgrICAMCNkhv45+I/Hu6N58juFMCHDx9G165dUVpaitDQUCxfvhzNmjWzuH1ZWRnKysr0f+fn8zFlGo0GGo3rvwGJNtzRlifIPT5A/jHKPT5A/jG6O75yTbn+9z9O/oExTV0/hMGdMZaVGz4zjl47itPXTqNuZF2XtunufajTGarWf5z8AwPrD3R5m+6OsbS8FACw69IuZN3KQnRItEvbc3d8ZRrD63TliZXoVrubS9tzd3y2tqNgMps6Wl5ejszMTOTl5eGXX37Bl19+ic2bN1tMdl977TXMnDmzyvXff/89goODXd1dQgiRnV15uzDr/CwAQIgqBN+0+AYqhcrDvZJOkbYI4w6P0/89qfYkDI4e7MEeSe/ZE8/iQukFAECUfxS+bPYlFAqFZzslsZVXV2JR1iIAwDN1nsGdNe/0cI+kda74HKacmgIASFQn4qOmH3m4R9IqLi7G/fffj7y8PISHh1vcTnYV3YCAADRo0AAA0L59e+zZswcffPABPv/8c7PbT5s2DVOmTNH/nZ+fj6SkJAwYMMDqEycVjUaDtLQ09O/fH/7+/i5vz93kHh8g/xjlHh8g/xjdHV/5yXLgPP+9SFuEGi1r4I46d7i0TXfGeLPkJnDY8HeGOgODB7s20XX3PpyeNR3gBU/kanKR2CERrWNbu7RNd8d4atcpIIv/fjnksuz24YHsA8Ap/vulskto0rUJ6teo77L23B2fOAJfHdklupXpdDqToQmVqdVqqNXqKtf7+/u79QPP3e25m9zjA+Qfo9zjA+Qfo7viU6lMq7drzq3BnSnuqZa5I0aVxjS+TRmbUM7KERIQ4tJ2AfftQzEOOUIdgbyyPKw9txYdEju4vF3AfTEqlYZpSuvOrQOUgL/K9e166n247vw6/Dfmvy5v113x2dqGrCajTZs2DVu2bMGFCxdw+PBhTJs2DZs2bcK4ceOqvzMhhBBJGK9KAMhvwpbxZLQ6EXVkOWFLjGoc2ICPzZXbPgRMX6f5ZfnYflFey3BVfh+uOi3PFUKqI6tE9+rVq3jooYfQuHFj9O3bF3v27MHatWvRv39/T3eNEEJuGyJJahnTEiqFCkevHcWFWxc82ykJGScQQxsNBSC/ZcZEjHc1ugsAsPPSTlwvvu7JLknO+AsLAPx5Sl7JvIjPX8krn5subEJheaEnu+QRskp0v/rqK1y4cAFlZWW4evUq/v77b0pyCSHEzUSSFBUchW5JfKa3nJII4zncQxoOAcArnnKa2y2SpKTwJLSJawMGhr9Oy+tMo+J1GqGOACC/iqeIr3Z4baTUSEG5thx/n/vbw71yP1kluoQQQjxPJEkKKPQVQTkd+hYJhAIK3FnvTgT7B+NywWUczDno4Z5JRx+jQmGSzMuJ+GLSt35fqBQqnLh+AmdvnPVwr6Qj4lMqlIZ9KKMvnLaiRJcQQoikRJJk/AErpzNsiUReqVAi0C8Qfev1BSCvJMI4SRJfVtacWSOrM2yJ12mNwBrokdwDgLySeZP3YSN5HnmwBSW6hBBCJCU+SBUKBZpFN0NyRLKsJmwZVzsBwzhWOR36Nk6SOiZ0RK3gWsgry5PVGbaMv7DIsWptfGSlV3IvhPiH4ErhFb7s2G2EEl1CCCGSMk6SFArD8AW5TNgyrnYCwOCGfP3VXZd24VrRNY/1S0rGSZJKqdLHKJd9CJi+TsVrVE4TtozjU/up0T+Fz1mS05EHW1CiSwghRFLGSRIgvwlbxmN0ASAxPFE/YWvNmTWe7JpkjJMkAPKseDLD67RxVGPUr1FfVhO2jI+sAMBdDeV35MEWlOgSQgiRVOUkSW4TtowPeQsiEZRLElE5SRqQMgB+Sj8cv34c526e82TXJFPlyMO/iaBcKp6V34eiKr/n8h7kFOZ4rF/uRokuIYQQSVVOkuQ2YavyGF3AkOiuPbNWFhO2KidJkYGR+tM4y2EfAkZHHv7dj3KbsFX5yEp8WDzax7fnS8WdkddScdZQoksIIURSlZMkALJaZqzyGF0A6FS7k37ClhzOsFU5SQLkN3yh8utUbhO2zL0P5bYPbUGJLiGEEEmZS5LEYdOdl3b6/IStymN0AUClVGFQg0EA5FHxtPZlZeOFjbKYsGU8RheAyYQtOUy6q3xkBTBUrdedXYdybblH+uVulOgSQgiRlLkkKTE8Ea1jW8tiwpa5MbqAvJYZM5ckGU/YWn9uvae6Jhm5VzzNxdchoQNiQmKQX5aPbZnbPNU1t6JElxBCiKTMJUmAfBJBc2N0AT5hS5xhy9cnbJlLkownbMmi4omqr1Nx5GH35d0+P2HL3JEVpUKpj1EORx5sQYkuIYQQSZlLkgD5TNgyN0YX4BO29GfY8vEkwlySBMhrwpa512lCWALaxbcDAJ+fsGXpfXi7LTNGiS4hhBBJWUqS5DJhy9wYXUEuy4xZSpLkNGGr8hhdQb/MmI8PX7B0ZKV/Sn/4K/1xKvcUTuee9kTX3IoSXUIIIZKylCTJZcKWpTG6gCHR9fUzbFlKkuR0hi2LRx4aGY48+PKELUvxhavD0TO5JwDfT+ZtQYkuIYQQSVlKkgB5LDNmaYwuADSp1UQWZ9iylCQB8pmwZW6MLmCYsFVQXuDTE7YsHVkB5LMPbUGJLiGEEElZS5LEhC1fPsOWpTG6AE+a9EmED1c8rSVJxhO2rhZddWu/pGTpdWo8YcuXJ91Z/bLyb9V684XNKCgrcGu/3I0SXUII8TI3Sm5gb9ZeT3fDYdaSJDlM2LI2RhcwrVr76oQta0mSmLDFwPDXad+dsGVpjC4gj4qntSMrjaIaoWHNhtDoNEg7l+burrkVJbqEEOJlxv46Fh2/6Ijdl3d7uisOsZYkAb4/YcvaGF1AHhO2rCVJgDxm7ld35MFP6efTE7ZsfR/66hdOW1GiSwghXuZy/mUAwC/HfvFwTxxTXZLk6xO2rI3RBeQxYavaJEkGZ9iyNEYXkMeELWtHVgDTIw9if8sRJbqEEOJltEwLwHfHB1aXJPn6hC1rY3QFuVStLSVJcjjDVnWvU19fZqy6+Hok90BYQBhyinKw/8p+d3bNrWSV6M6aNQsdO3ZEWFgYYmJiMGLECJw8edLT3SKEELtU6CoAAMevH8f5m+c93Bv7VZck+fqErerG6AKGCVt7Lu/xyTNsVZckyeEMW9bG6AK+P2GruiMrAaoADEgZAMB3v1TbQlaJ7ubNm/Hkk09i586dSEtLg0ajwYABA1BUVOTprhFCiM20Oq3+d1+sJlWXJAG+PWGrujG6QKUJWz54hq3qkiRA/hVPX5+wZcv7UA6T7qojq0R3zZo1mDBhApo3b47WrVtjyZIlyMzMxL59+zzdNUIIsZkYugD4ZqWlukoZ4NsTtqoboyv4chJhS5IkzrB1Mvckztw4466uScbaGF1BPwTFF9+H1RxZAYBBDfkJXPZm7cWVgitu6Ze7+Xm6A66Ul5cHAKhZs6bFbcrKylBWVqb/Oz8/HwCg0Wig0bj+XOyiDXe05Qlyjw+Qf4xyjw/wvhiNK7obL2zEzaKbCA0Idfjx3B2fRmtox1KbSijRt15frDy1EitPrETLWi2da9ONMYo2lFBabW9g/YF4Y8sbWHtmLYpKixCgCnC6TXftQ5EkVVRUWGwzSBmEO5LuwMaMjVh5fCX+2+m/TrXp7hgrtHyIENMxi22m1k/F+7vex+rTq1FWXmY18a+Ou+Mrr+CTBBVQWGwzSh2FDvEdsPfKXqw6uQoTWk9wuD23/5+xsR3ZJro6nQ7PPvssunfvjhYtWljcbtasWZg5c2aV69etW4fg4GBXdtFEWprvHRaxh9zjA+Qfo9zjA7wnxuKSYgA8kSrXluPdX99F54jOTj+uu+I7mc3nRly8eBGrV6+2uF1SSRIA4Pu936NtfltJ2nZHjEcLjwIAiouLrcanYzpE+EUgrzwP83+Zj1ZhrZxu2137UKfjFd2NGzaipr/lYlE9TT1sxEZ8s/MbpFxPkaRtd8WYeTETAHDq1CmszjO/HzU6DQKVgcgpysGCXxegYXBDp9t1V3zpN9IBANevX7f6Om3AGmAv9mLRtkWIuRzjdLvuiq+4uNim7WSb6D755JM4cuQItm2zPht02rRpmDJliv7v/Px8JCUlYcCAAQgPD3d1N6HRaJCWlob+/fvD39/f5e25m9zjA+Qfo9zjA7wvRr9TfkAF0DO5JzZlbMLViKsYPHiww4/n7vj2b90PZAN169TF4EGW+92moA0+XvAxzhSfQfue7REbGutwm+6MMSwzDDgDhIaEVrtfhrPh+ObQN7gRdQOD+/nOPmTpvKLbr28/xIXGWdyuQW4DLPp8EY4VH0OPvj0Qpg5zuE13x/jbqt+AG0DTJk0xuKvlfTOwbCBWnFyBvJg8DO7pO/vw+qHrQCYQGx1r9XUadyUOPy7+EUdKjqDvgL5Q+6kdas/d8Ykj8NWRZaL71FNPYdWqVdiyZQsSExOtbqtWq6FWV92p/v7+bv3Ac3d77ib3+AD5xyj3+ADviVGM0R3RZAQ2ZWzCX2f/gp+fX7VjQqvjrviUSn54V6VUWW0vuWYy2sW3w/4r+/F3xt+Y0GaC0227I0alisenVCqrbWto46H45tA3WH12Nd4b9J7TbbtrH4qhC+oAtdX2msc1R8OaDXH6xmlsurgJo5qOcrptd8Uo3k9+Kj+r7Q1rPAwrTq7AmnNr8EbfN5xu113xqVQqANW/TjsmdURcaByyC7Ox88pO9Kvfz6l23RWfrW3IajIaYwxPPfUUli9fjg0bNqBevXqe7hIhhNhNjNHtU68PQvxDkFWQhfTsdM92yg62TGQSfHHCli3r6Ar96/f3uTNsGa+CYW0ik+CrS8XZ+jr11QlbtsanVCh9etJddWSV6D755JP47rvv8P333yMsLAzZ2dnIzs5GSUmJp7tGbJRxKwOHcg55uhuEeJSo6Ab7B+urKz6VCNowm10Qy4z50hm2bFlHV4gIjPC5M2wZnyXLlmRe7MPVZ1b71Bm2bFmVAADiQuPQMaEjAPjUUnG2LBEnGCe6vrbcX3Vkleh++umnyMvLQ+/evREfH6//WbZsmae7RmzU79t+6PhFR2TmZXq6K4R4jKjoqpQqfRLhS5UWeyq6vniGLVvW0TXma1VrER9gW5IkzrCVXZjtU2fYcuTIg1zfh/3q94O/0h9nb57FqdxTru6aW8kq0WWMmf2ZMGGCp7vm08oqyqrfSCJZBVko15bjj5N/uKW9/LJ8pH6Xio93f+yW9gixhajoqhQq/dmndl/ejatFVz3ZLZvZso6u4Itn2LJ1HV1BfFnxlTNs2VvRDVAFoH9KfwC+sw8B+yqeYh+mnUtz62eiM2ytWANAmDoMvev2BuA7X8hsJatEl0jvt+O/IeTtECw+sNgt7YlTn7rrjbb78m6sO7sOr2x8xWTtT0I8ybiimxCWgLZxbfkZtk77xmFTeypJgFG17LRvVMvsGaML8DNsNajZwGfOsGXvGF3AcJY0X9mHgH2v07bxbREXGofC8kJsydji6q5JwuH3oQ9VrW1BiS6xavfl3dAyLb488KVb2hMf8BvOb0BRuetP3SyS21ult/DPxX9c3h4htjCu6AKmp8v1BfaM0QV8b8KWvQkEYHS6XB+oeNpb0QVMJ2xlF2a7pF9Ss6fiqVQoMbjBv0cefOV9aEfFGjD8n9mauRV5pXku65e7uSzR1Wg0uHjxIk6ePIkbN264qhniYiLx3HlpJ64XX3d9e/9+wJdpy7Dh/Aa3tQf4zj8vIm/GSYZKyRNdUWlZe3atTxx5sDcR9LUJW/YkSMKQRoZxut4+YcveMbqA6YSt1actn5zAm9j7OjUeL+8LE7bsjS+lZgoaRzVGha7CJ4482ErSRLegoACffvopevXqhfDwcNStWxdNmzZFdHQ0kpOT8dhjj2HPnj1SNklcTCSCOqbDmjNrXNpW5X/+7vjAMz7Vqi98wBL5M35Niopux9odER0c7TMTtuwZoyv40oQtRyq6PZN7IjQgFDlFOV4/YcuRii7gW/sQsL/i6WsTthz5QuaLk1+rI1miO3/+fNStWxeLFy9Gv379sGLFCqSnp+PUqVPYsWMHZsyYgYqKCgwYMAADBw7E6dPef3iKuDcRNG5LtOfqb83GFd1j147h/M3zLm1PuFp0Fa9seMVt7RHfIcapA4aKrvGELV/4AHLo0L4PTdiyN0EC+IStASkDAHj/PnRkjC7ge0vF2fs69bUJW468D8WXldWnfWupOGskS3T37NmDLVu2YPfu3Zg+fTpSU1PRsmVLNGjQAJ06dcIjjzyCxYsXIzs7GyNGjMDWrVulapq4kHEiuObMGpMPYVe25af0w6X8Sy5fU9dccu0O3xz8Bm9tfQvT1k9zS3vEdxi/D0RFF/Ctcbr2jtEFfGvCliMJBOA7FU9HK7q+NmHLoSEoPjRhy5EvZHfUuQPh6nBcK76GPZflcQReskT3hx9+QPPmzavdTq1W4z//+Q8eeeQRqZomLmScCLp6wpZxW72SewFw/T8T46TCHe0JheWFAPiXB18Yc0ncx2TogtKQ6IoJWydzT+LMjTOe6JrNHE0EfWXCliMJEgB9Vd7bz7DlyBhdoNKELS/fh4BzRx58YcKWI/H5q/yRmpIKwPu/kNnKLasu5OfnY8WKFTh+/Lg7miMScmciaNzW8MbDAbhvuERieCIAYOOFjfok1B3t5pXlYfvF7S5vj/gOSxVdkwlbXp5EODJGF/CdCVuOJvJxoXHokNABgHefYcvRii5gNMbTB5YZc6TiaTxha93Zda7qmiQc/ULmS1VrW7gk0R0zZgw++ugjAEBJSQk6dOiAMWPGoFWrVvj1119d0SRxEZGQtYlrA8C1iadxJWto46EAXL/agxiK0Ty6OepF1kO5thzrz613WXuCyWoPXp60EPeyVNEFfO/Qt71Jkq9M2HIkQRL0VWsv3oeOjtEFDBO2ztw44/UTtm6XISj2xjeo4SAooMCB7AO4nH/ZFV1zK5ckulu2bEGPHj0AAMuXLwdjDLdu3cKHH36IN9980xVNEhcRCdmgBoOgUqhcOmHLOPmrE1EHbeLauHyRfP16pUanWnXHPy/jsc7urHzcKr2FdWfX+cTSOLcr8ZpUQFHlA0p8wG66sMmrJ2w5MkYX8J0JW44mEIChar3u7DqvPcOWMxVd4wlb3rwPAccrnuKzwtsnbDn6hSwmJAadancC4DtLxVnjkkQ3Ly8PNWvWBACsWbMGd999N4KDgzFkyBBabcHHiA/dqKAo3FHnDgCuSwSNK1lKhdIt35r1Z6BSqEzac/lqD0axnrh+AudunnNpe8Kza55F6nep+OnoT25pj9jP+KxolRlP2Pr73N/u7prNnEoEfaBa5miCBADt4tshNiQWheWF2JrpnZOyHR2jK/jCPgQcf536yoQtZ96HvjT5tTouSXSTkpKwY8cOFBUVYc2aNRgwgH9Dv3nzJgIDA13RJHER4w9dV//zsnQ2KFdO2DKu6Paq2wsh/iHIKshCena6S9qr3K7gruEL4oxFvx6nIUTeqvL7wJhCofCJ8XOOjtEFTCdseesZtpxJIIy/xHvrPhTxObL/AMP/7i0ZW5Bfli9Zv6TmaMXTVyZsOfOFTLxG/z73N0orSiXtl7u5JNF99tlnMW7cOCQmJiIhIQG9e/cGwIc0tGzZ0hVNEhcx/tAV/7w2nt/oktPzVq5kdUzoiFrBtZBXluey1R5Em35KPwT6BaJf/X4A3DcJLlwdDsB9wxfE/vSVM2zdjqxVdAGjw6ZnvPewqTOJoPGELW89bOrMGF3AMHzBW8+w5Wx8vjJhS4ojD976ZQVwLr42cW2QEJaAIk0RNl/YLHXX3Molie4TTzyBHTt2YNGiRdi2bRuUSt5M/fr1aYyujzH+0G1SqwnqRdZDmbYM689LP2GrciVLpVS5fJH8ym2665+X8dhngI+5dOdqD75yhq3bkbWKLmCYsJVdmI0DVw64s2s2c3SMruDtE7acSSAAvlScN59hy9n4AN8YvuBMxdMXJmw5c2TF+OiRN+9DW7hsebEOHTpg5MiRCA0N1V83ZMgQdO/e3VVNEhcQk6ZUChUUCoVLTw9orpLl8uESldoUifXuy7txteiqS9o0brd5dHOk1EhBubbcLWMujYdMuLMSUaGr8PnDX9YsP74cnb/sjNO5zs9BqK6i6wsTtpxNlLx9wpYzCRLAJ2z1qsvXCvfGJMLZ+ADfmLDlzOvUFyZsOf0+bOjdRx5s5ZJEV6vV4quvvsL999+Pfv36oU+fPiY/xHcYj2EF4NIJW8ZJtTAgZQBUChWOXz/ukglblatntcNro21cW7eu9qB/Tt0wTtedp3Q2NmjpICS9l+TSpeI86bvD32H35d34dO+nTj9WdRVdwPurZc5UkgA+YUucYcsbJ2xJUfEUVWtv/LIiRXxiwtbVoqvYm7VXqq5JyukhKN7+PnTyyErf+n2hVqlx/tZ5nLh+QsquuZVLEt1nnnkGzzzzDLRaLVq0aIHWrVub/BDfYbwqAQD0qtsLwf7BLpmwVTmpBoDIwEj0SOZL1bkiETRXPXPHbFNzY5/dstqDUUXXnWfY2nN5D64XX3fbh7pWp8XMTTPdtjKB+JImRXzVVXQBw5GHPVl7vHLClg7OJUrGZ9jyxkTQ2QQJMFStvfEMW1LEZzxhyxv3IeB8Qi/+d6edS/PKI1bOxhcaEOozS8VZ45JE98cff8RPP/2EZcuW4f3338d7771n8kN8h0iM/JR+AIBAv0D0r98fgPSJYOWkWnDlt2Zz1TPRnisnbBknMz2TeyLEPwRXCq/gQLZrx1waT74D3Lfag3ie3fXPck/WHry2+TU8uPxBtxw2Fc/r6RunnR5zaUtF1+QMWy488uAoKRNBb6yWSVHxbFCzARpFNUKFrgJp59Kk6pokpIgP8KGKp4NHHsSErWJNsVdO2HL2yArg/fvQFi5JdAMCAtCgQQNXPDRxM3eOmzVX0QUM35pdcXpec8l1x9odER0c7dIJW8bJjNpPjf4p/355cHHiKdq9s+6dvD03/fMSz/O6s+tQri13eXtiVZDswmy3nGFLyjPd2VLRBYzGz3nhqValSJTEhC1vPMOWFGNYAe8dviBVfGLC1v4r+5FVkCVF1yTl7OvU2ydsSTKp8N8vnNsyt+FmyU1J+uVuLkl0p06dig8++MDtg5e3bNmCoUOHIiEhAQqFAitWrHBr+3JkrrokDpvuurQL14quSddWpWqj0DiqMerXqO+S0/OaS66VCqU+RndNgtN/4Lk4aRHtDms8DID7zrAlnueC8gK3rPbg7kl3Uo59tqWiCxi+ALrry4M9pEiUjCdseVsiKFnF898kwtsmbEkVn7dP2JLkyIMXT9hydowuANSvUR9NazWFlmm9eqk4a1yS6G7btg1Lly5FSkoKhg4dilGjRpn8uEpRURFat26Njz/+2GVt3G7MVZdMJmydke6wqaUPeIVC4bLKh6XhEq5cXQKoGqt+zOXlPcgpzHFJm8btNq3V1K1n2DJOBH0t8bSpPaPE2tlF8vWTMqup6BqfYWtLxhaH23MFqRIlb11mTIoECfDeM2xJFR/g3Ye+pXidevOELcnehz5+ljSXJLqRkZEYOXIkevXqhVq1aiEiIsLkx1UGDRqEN998EyNHjnRZG7cbS8mnKxJBa4dsjcfrSfmt2VJS0b9+f/gp/Vw2YatyrPFh8Wgf317yLw/W2nXngucmh/bd8M9S7FfAPWfYMk6sNToN0s46PubS0pevykxOk+2msda2kipREu/7LRlbvGrCllQJhPFScd6UREgVH2A0YetsmtctFSfFkQdvnrAlxRhdwPBlZfXp1Sb/63yFSxLdxYsXW/0hvsNS8umKCVvWDtn2Su7lkglbltqMCIxAjzquW+3B3FJq7qh8mFvtwdVn2Kr82KdyT0my3qw1lU+x7OrDpqK9OhF1ADi3Dy2NVTfHWydsSZUoNajZQH+GLW+asCXVGFbAO8fpShmfyRm2MrxrwpbcK55SxdctqRsiAyORW5KL3Zd3S9E1t/KrfhN5KysrQ1mZ4Vtmfj4/5KjRaKDRuP4UqaINd7TlCJGQMR0z6WObmDaIDo7GteJr2HRuk/4bbWX2xFdWzveDUqGssr0SSvSt1xcrT63EyhMr0bKWNKeS1lQY2qnc5qCUQdh4YSNWnVqFJ9o/YfkxHNiHFdp/K47McL+B9Qfi9S2vY+2ZtSgqLUKAKsDmx7OV+OLCdAxdE7rqz7C15+IetItvZ/Y+zr5Gjb8ItY1riwPZB7DyxEo83elphx7PFmUa08rRHyf/wIMtHrTcR4livKvBXfhk3yf489SfKCsvc+gDRv8+QNX3QWW9k3rDX+mP0zdO42j2UTSKamS+f27+PyNeZzqtzuk2B6UMwsnck1h5YiWGNxxucTt3xqj/v8Gcb69f3X76M2xl3MhAQliC+TbdGJ+1/8WOGJQyCF+lf4WVJ1bizjp3WtzO3a9TnY4nglqt1qk2B9TjVfltmdtwNf8qagTVMLudu+PTf34z5nSb/ev1x8/Hf8bvJ35Hh7gOZrdxd3y2tuOyRPeXX37BTz/9hMzMTJSXm06U2L/f9bOgbTVr1izMnDmzyvXr1q1DcHCw2/qRluY91QpjN2/xWZb79+4HKk18bqFugY3FG/Fx2scorl1s9XFsie9QwSEAQElRCVavrlqBSypJAgD8sPcHtM1va0v3q3XmEh+WkHEuA6tLTdsMKQ0BwCds/frHrwhSBVl9LHv2YfZVfij9yOEjWH2Zt6tjOkT6ReJW+S3M/2U+WoW1svnxbJVfyL/I7dqxCzdDbqJFUAvsLN+J9/96H/fF3Wf1vo6+Rst1hvd/YzTGARzANzu/QYPrrluZZe9NvkB9sDIYxbpirDm9Br+v+h3+Sn+r93M0xhs3bwAAQnNDEagMxNXiq1jw6wI0DG5o92MdyOdHLIoLi82+DyprFtwMBwsPYv4f8zEsZpjVbd31fyYri8+wP37sOFZfc66aXrOgJgBg5fGVWKVcVe2XB3fEeOTaEQBATnaOTfuoOg2DG+JU8Sm8u+Jd9I/qb3Vbd8SXWZIJANCUaySJLyYvBgDwy6Ff0E/Tr9ohLe56nYrPt3379kFx2rnqdaI6EZfKLuHd397FHTXusLqtu+I7e/ksAOD8+fNO78eEIv4FbNn+Zeha3NXqtu6Kr7jYet4huCTR/fDDD/Hyyy9jwoQJ+P333/Hwww/j7Nmz2LNnD5588klXNOmwadOmYcqUKfq/8/PzkZSUhAEDBiA8PNzl7Ws0GqSlpaF///7w97f+IewJ07OmAyVAl85d0K9eP5Pbio8XY+PyjTiuPY7Bgwebvb898QWcDwDOAhHhEWYfr01BG3y84GOcLj6NDr06ICYkxvHA/rVu7TrgOtCoYSMM7mXaJmMM7332Hs7cPANVIxUGN3Y+RmHB9wuAAqBtm7YY3MLwuMPYMHxz6BvciLqBwf3Mt+cM9Vk1oAF63NED7ePb4+rBq9j5506cUZyRZB+aU1ReBPDvMJgyZAp+/OpHHC8+jh59eyBMHeZMOBblH80HMoCOiR1xIvcEcopyENo8FH3r9TW7vbMxzsyeCRQD3Tt1xyn1Kaw4uQK3Ym5hcE/796HyrBI4B9SIrGFxnxg7s/sMDv59EOf9z7tsH9rr61+/BvKAFi1aYHB7517H/bT9MPf9ucgry0Ns21h0TOhodjt3xnh+z3ngMpCQkGDTPqrOgfADmLllJjKDMr1iHx6+ehg4CQSqAyWJr2d5T8x/bz5yynNQvzOfxW+Ou1+nM7NnAiVAp46dMDBloFOPNSZwDObvnI8rYVe8Yh8CwMa/NwLXgJT6KRjcx7n92Km4Ez58/0NcKL2Alne0RFJ4UpVt3B2fOAJfHZckup988gkWLlyIsWPHYsmSJXjhhRdQv359vPrqq7hx44YrmnSYWq2GWq2ucr2/v79bE093t2crMcZH7a+u0r/BjQbDT+mHUzdOIbMgEyk1Uyw+ji3xKZT8G7Wf0s/stsk1k9Euvh32X9mPvy/8jfFtxtsbThVMwceiBfgFmG1zSKMh+GDXB1h7bi3uaXGP1ceyZx+KM0cF+gea3GdYY57orj67Gu8Nkv7kKmL8p9ifQ5sMBf4E9l7Zi9yyXMSFxlm8r6OvUaXOUIFrEdsCDWs2xOkbp7Hp4iaMauqaVVjEaynALwCDGw7G4vTFWHtuLQY2sv5h5miM4n0SGBCIYY2HYcXJFVhzdg3e7Pumw3239D6obHjT4Xju7+ew9eJWlOhKEK62/AXdbf9n/i2O+fs5356/vz8GpAzAL8d+wZpza9AtuVu127s6RqWKv6ZVSpUkbQ1rMgwzt8zEhvMboFVoEegXaHFbd8Tn58dTA4VCIUlbNfxroHfd3lh7di3WnV+HVvHWj1a563UqxiJb+v9vj2GNh2H+zvlYc3YNlCql1TH27opPVM79Vc63Fx8Rjy6JXbDj0g6knU/D4x0et7itu+KztQ2XTEbLzMxEt278n1FQUBAKCvg6nQ8++CB++OEHVzQJACgsLER6ejrS09MB8HJ9eno6MjMzXdam3FmbIGYyYUuCQfi2LJQv9Xqz1c1wN55kIOWELUvPa/8Uvki+qyZsVZ7o5I4zbBmvgKBSqly+dBtg+lrSt+fCNYqN9+eghoMAAPuu7MOVgiv2P5aNJ4wQjM+w5S3rXEo5mQnwvmXGpFyVAOBj1/UTtrzgDFtSxwd454St/2/vvOOjqNM//tnd7G4S0iEhgfRCLwm9SgmkgIh6thNPLOepPxUR1LNzigp4qCh6KnjYTuXsBwiEEEF6SSD0lgAJPYSShNRNMr8/lpnMJltmZuc7Ozt+36/XviC7s/PMM9/Zmef7fJ8iZxk1NSZsseMoh34AFLmXkoCIoRsZGcl5bmNjY7Ft2zYAVsOTZEHl/Px8pKWlIS3NGr85Y8YMpKWl4ZVXXiEmU21U1lfimTXPyFaT0dVDV06jRUihfDbLXK4i+a4y3G+Iu4FL2Np9TsZqDw7Oa5A5CDfE3QCAUMtjO005SHfY4pejMegMNqVqSFV74F9LSnTY4o9nZEAkt7wupdqD0IYRfLRuCKqtw5acBhK7nwnJZJvUiEFu/YCW+8zGko24WndVtv26g5zXqdFgRGZSJgD1VNBgJ5xy/Q7ZMcw7nodaS60s+1QCIobu2LFjsWzZMgDA/fffj6eeegrjx4/HnXfeSbTG7ejRo8EwTJvX559/Tkym2lhxdAXmb52PJ1Y9Icv+7JXB4sNe+L+X/O52hy0hnqwBnayxuXK153VlVJgMJoxPtCaHyFoz2IlckmXG7Mnl17kk0WGLX+pLr9NjZNxIBJoCcaH6AgrOFsguD7C9lpTosNX6vLozhmI9uoD6OmzJbSiprcMWSY+nGjpskdAvITRBdR22ZF95UJnXmvPoyqRfn459EB0UjdrGWqw/uV6WfSoBEUN30aJFePHFFwEAjz32GJYsWYLu3bvjtddew0cffURCJOU6NRZrFuKOMztQVl3m9v5ceTy7tO+CpNAkNDQ1uN1hS4gny6Y9rwz1bQWFSxC4eTmTy8r7/aT7kwchctkOW1UNVdhYslFWeTYydQbodDpFiuTLaXgKktfqvPJXHsQWyZfi0WU7bJVVlyH/bL4oeSQgYSgp2eDEFXIbSIC1w5bJYFJFhy0S+gHkO06KRe7rNCs5CzrosOfCHpyqOCXLPt2BnTDJpZ9Op1PV71AoRAxdvV7PBbMDwF133YX3338fTzzxBEwm+WuDUlrg6qSCkSXm0lUMq06nk80QFNr6VE6jRYhRwbXnPStfe15nclPapyAlLMXaYUvmIvn25PI7bJG4edmbLBFvsdza8Ewh22Gr9XntF9UPkQGRqLZUi27PK8WjazN5UEGXNBKGEjt5WHt8rcc7bJEw5ANMARgTb60x62mPIAn9gJbf4aqiVarosCX3ykMH/w4YEj0EgLpWHkiEoMjdpZQksl3Fe/fu5Yov79271+mLQg5+4o+shqCThy7/wndn2VRo69OMpAzZ2vMKMSr4CVty3bxcySVleDrsdEeww5a9cc1Odi9hy6XMVoZnSvsULmGLRIet1udVr9NzMZdix1CKRxcgH2stBhKGkk3Cloc7bJGIYQXU47UmpR+bsFVeU66KhC2tJ93JHaMLWFcefH18UVJRggMXD8i2X5LIpn1qairKy8u5/6elpSE1NbXNi00Uo5CBHw8pR3tee8lLrZErYUto61ObhC03vVdCjQq5l75dyeXa88occ+mw2sP1hK1jl4/JnrBlb1w7BrTUQ11VJH+1B3sGvadin8V6PqR4dAHr5EEtCVtyL5kCtglbnjYEOQNJ5kVRdsK5qXSTRxO2SHl0+QlbajIEZV15SGlZefB0wpbcMboA4G/0b1l5UMHqkRBku4pPnDiB8PBw7v/Hjx/HiRMn2ryOHz8ul0iKHfjLQXIkbAkxBM0+Zi5hy52blxCjmkWuMmNCwyVYo0W2ag8ujBl+wtauc/J1EnQkl5+wJffNy5GnnmT4gjPDk0TClr3zOi5xHIx6I4qvFIuaPEj16HYM6IiBnaVXe5ATEkumgHoStjgDSWb9EkMTuYStnKIcWfctBlIxuoC6PJ4kDHo1JWyRmHAC3ldmTDbt4+LiuB99XFyc0xeFHHyPLuC+ESHUuySH0SLmAc96PtxN2BIaLiF3wpaQag9szKVchiDDMNwDzFm1B7lvXo489ay83OO5ssdc2rtuR8SOQKApkEjClr3xDDQHYnT8aADixlDo5MseaikzRmLJFFBPwhYpjydAPnFSCCT1YxO2Cs8X4nTladn3LwYSIRpqStgiNeFk9dtyagsu16qrCZg9ZLuKly1bJvhFIQf7gA/xDQHg/s1SqPEpR8KWmCXbLu27yJKwJTRcgl/tQY6blxBjhlS4hCO57GRlQ8kGVNYLa60oSK6DyURaVBqiAqJwreGa6IQtV9gri2cymJCZTKbOpcPYZwljKHTyZQ92AphbLP/kQQwklkwB9SRscQYSQY/nymMrPZawRSpGF1BXwhYpg15q2JLckJpwxoXEoVdELzQzzR5deRCKbNrffPPNNq9bbrmlzd/si0IO1pgZnzheloQtocZnZEAk+kf1ByD95iV2yZYzItxYahdjVMi55CZELmtY55/NlyVhy6ZDmR25/A5bucXyJWw5mkzYlIqT2WhxdC2R8pY5lHfd8NxYulFwtQehky97qCVhi9SSKaCOhC2SHs9hMcMQbA72aIctkvoB6ikzRipEY2zCWFUkbJGacALqSn51hWxXcXNzM/das2YNUlNTsWrVKly9ehVXr17FypUr0a9fP6xevVoukRQ7sAZUqG+oLAlbYoxPdw1BsUk4XJH8Iukxl6x+QuKC5UzYEmLMyJ2wZdOhzFGnO5lbLPPl2ruGSMVcOrqWSCVsOfLQJ4clo2v7rqLa87rj0bXpsOXBRBFSS6aAOhK2SMXoAtaErazkLACe81qTjNEFeB22Tni2wxYpg97f6I+xCWMBePZ3SMqjC7SM4eqi1TZOFDVCZLo2ffp0vPfee8jMzERQUBCCgoKQmZmJd955B9OmTSMhknIdvgElx4xLjPHJypOasCXWo8uv9iA1YUuMfnImbAlNvJPTe2UTuuCo0x2BDlvOjPpxieNgMphEJ2wJltlKT1IJW86MU7G/QzGTL3uwY7jimOcStkg+YPkJW57qsEXa4+lprzVp/diErRpLjUcTtkiGaKgp1pqEfkNjhiLUNxSXay9j2+ltsu9fTohcxcXFxQgJCWnzfnBwME6ePElCJOU6/AeuHB22xBif/Tv1dythS6xHV44i+ZLDJRSKfeba88qQsCXEo0uiw5YzIzDAFIBRcdcnDwQ6z9kzFkk8gJwZ8+wYrjq2StDkQWp5MRZ28nD8ynEcuXRE0j7cheSSKeB5Q5BkjC5g22HLEwlbJA1Adr9qMgRJejw3n9rssYQtkiFEPnqflpUHlZcZI2LoDhw4EDNmzMCFCy1JSRcuXMAzzzyDQYMGkRBJuQ7/gdulfRckhyVLTtjiP5SFPHTdjbmUUlbJ3aV2sUYFN3ko+d2thC2hctOi0hAZEIlrDdewsdS9ag98j64jbyGJDluuwjRIxOsJMTzlTNhyZsyzk4eLNRex88xO1/uSWF6MJcAUIKnag5yQfMACvMmDhzpskfZ4hrcL5xK2PGFEkNYPUEfCFskQDTUkbJGecHpLmTEiV/GSJUtw7tw5xMbGIjk5GcnJyYiNjcWZM2fw73//m4RIynVaP3C5ckMSbpY2HkCBD113jBYpsYnZKdYOW/ln83H+2nnxMkUaFXIlbAmVK2d7Xv54OnuAyZ1k4GpcWXliErbckZkWaa32IFfCFr9sm70JBL9IvpAxdCdGl8XTZcZILpkCLQlbnuqwRTJGl8WTHk/SMbpAS8LWyasncfDiQWJynKFYCIqHDEGSIUSAdeVBr9Njf9l+lFwtISJDDohon5ycjL1792L58uWYNm0apk2bhhUrVmDfvn1ITk4mIZJyndaeLHcStlyVo7KHOwlbUrLNIwMiuYQtKTGXUpaJPRX77G7CllDjmp+wJWe1B0de5KSwJHTr0E1UwpYrnF1Lcte5FPI7EWO0uFN1gZPHVnso2eiRhC3SD1hPJ2wp6fH0RIctJfSz6bDlqaQ7wiEa7Bh6KmGL9IQzzC8Mw2KGAfB87W5nELuKdTodMjIyOEN3/PjxRGe/FCutvUHuJGy5Kkdlj0BzoORqD1I9We54PiSFS8jQYUuMXLkStoQa13InbAkx3GSvGezKi9xFnskDX5Yzedkp1snD7vO7cabyjKD9uePR9XTCFuklU8CzcbqkY3QBz3bYIm0Asni6zBhpg35I9BCPJmyRDiEC1JF05wpi2ldXV2PlypX4+OOP8f7779u8KORobVS4E3MpJHnJHlLLjEn1ZLFGy5riNaJjLqV4dPkdtgrOFoiSJ0VuoDlQloQtUaXiZCwzJsRwk7s9r6triZ08yNFhS4hHN6JdBAZ1tuYnuJo8yOHRBdRhCJJ8wLKTB08kbCnh8fRkwpYS+gGe77BFOkTDR+/Dhdd5MtZaiQnnbyd+Q42lhpgcdyByFe/evRvJycn485//jMcffxyvv/46pk+fjhdeeAELFiwgIZJyHXtGhdSldiHlqOzByhObsGWvm5UQ+kX1k5ywJcWjK0eHLanVHtxqsSwmXELGDltCDLfhMcMRbA4WnLDlUqYL45qfsOV2BQ2BsexCf4dyeHQBzyZskV4yBTzbYUuJGF1AvrAlsSgRowu0JGw1MU0eSdhSwqBXQ6w1Sf16RfRCbHAs6hrrsO7kOmJy3IGI9k899RQmTZqEK1euwM/PD9u2bUNJSQn69++P+fPnkxBJuY69wvX8DltiErakenRT2qdwCVtrT6wVLU+sJ0uv00suki+kFa893L15Sa324E7Clhjjmt9ha0Ope+15hRhuRoORW3mQM25WiXAJobHs/JjLusY6l/tz16PLT9jKPydPqTihKPGABTzntVbK4zk2YSzMBjNKKkpwsFy5hC2l9AM8bAgqEKLBJmztK9uH0opSYnLsocSEk7/yIEdjIxIQuYoLCwsxc+ZM6PV6GAwG1NfXIyYmBm+99RZeeOEFEiIp17FnzEQGRGJApwEAxHk+2H3poBN9w2Mv/JVF4uVJ8WRJLXMi1XvGJmwVnCvAuWviEraamWbOEBAqNyksieuwJaVUHCDOuOZ32HL35iXUcJO1xbKAa4mr9uBmwpZQj25qZCo6BXZCjaUGv590XO1BLo+u0WDkVh48tfRN2iPIXjNKd9hSIkYXANqZ2nEdtsTcS91FqRhdQB0rDyQNen7CltKGoBIhRAAv9KxopcdKxTmDiPZGoxF6vXXXERERKC21zmKCg4Nx6tQpEiIp13FkVEgpN+RO4Xp+e0ChMZfuyBuXOA5GvRFFl4tEJWxJ9Z7xE7ZWF4lra+1u7LNi4RK8ih1uVXsQaLixkwchCVuCZTo5v2y1hyamSfLkAbD16Dp7oAit9iCXRxdo+d2vKtbmA5bfYev3UvdLxQnFEx5PJY0kJfXjJ2xtP7OduDw+SoVoSHH8yIFSE84x8WPg5+OH01WnUVKnvjJjRK7itLQ07NxpjbMbNWoUXnnlFXz99deYPn06evXqRUKkDR9++CHi4+Ph6+uLwYMHY8cO5essegpHRoWUhC13PKwj40ZaE7ZqylBcWyxKnpTWp4HmQElF8t3xnnFLbkXSku7EyuVulhITtsSGaXAdtq4ex5l66YanUMMtvF04BkcPBuB+zKXgznMpLZ4IybKuX0N6nd6lB4y/TOto8iCXRxew7bBV3lDu9v6EosSSKbt/TxiCSsXoAi337i2nt6CqUVqHS7EoZQACth22VhZ7xhBUyuO5rmQd6pvlaVIjBKVCiPyMfkhPTAcA7Kx0P8dCboho/+abbyIqKgoA8MYbbyA0NBSPPvooLl68iEWLFpEQyfHf//4XM2bMwKxZs7Br1y707dsXmZmZKCsrIypXLTgyFqUkbLnjYeVXe8ivEBYf6O4DXkqslzvGNX/Z1NJsES5TokdXbIctR3KFnl9+wlZ+pfQYTzFyZYubFXjtskZETnGOzQRElCwRE8L0xHSu2sOh8kN2t5EaN24PfoetgkppFUKkoNQDFrD1lim1bKqkxzM+JB49w3uimWnG7qrdxOUByuoH2FZdURKlQjR6hvfkErb2Vu0lKouPUhNOAHh84OP4KPsjpIelE5clFtmvYoZhEBERgaFDhwKwhi6sXr0alZWVKCgoQN++feUWacM777yDhx56CPfffz969OiBjz/+GP7+/liyZAlRuVJpam7CtcZrsu4PaPuQlJKw5W4rUvbmJdRIcnfJljVaNpRsEJyw5Y4xz++wdaD6gODvSfXo8jtsuVUzWEy4RIq4MXRXLtee93iu04QtVwit4MFWeyivLcexmmOSZIm5hgJMAS1F8h38Dt393bWGNQTdGUOxKLVkClgnD74+viipKMGpOmVC45SK0WVhfxdKTVaUjNEFeB22Lu7HxYaLisgElDPodToddy9VdMKpUAgRAGQmZ+LBtAcRZgwjLkss4t1YLmAYBsnJyThw4ABSUlLk3r1TGhoaUFBQgOeff557T6/XY9y4cdi6davd79TX16O+vmUpobLSWg7LYrHAYhHupZPCN/u/wczcmUj1S8Utlltk2ael6foxN6PN8WclZWFJ4RKsOLoCb6W/5XJfdQ1WQ8OgN0g6F+PixgEAimuLUXqlFLGhscKOnWl77EKIC4xDl7AuOHr5KFYdXYU/df+Ty++wRkpzU7MkmdnJ2VhSuAT5FfmCv19X32LAMU0MLBAuNzMxE98f/B7LjyzHyyNeFnWs9Q3W69ygEz6eGQlWr/yha4dwseoiwgPDRckEgAZLAwBAD71LuT3CeqBzYGecqTqDvOI8ZCRmiJYHiLuWxieOxw+HfkBBZYGka4D7nQg8r1mJWcgpzsHyI8sxfdB0t45dCJmJmXhp3UvYe20vqmqrEIhAt/fpiuZmqwEh9XclBiOMGB03GquLVyO/Uvjv0B0am6wTKYZhFJGXmZCJeZvnYVflLpv7BykaGq2/WR2jU0S/QJ9ADO08FJtPb0Z+ZT7uttxNXCbQsvLQ2NhIXM/MxEz8K/9fyK/MR0NDA1FZLOzzrampSZFxZGUoIUuMHNkNXb1ej5SUFFy6dElxQ7e8vBxNTU3o2LGjzfsdO3bE4cP2i8LPmTMHr776apv316xZA39/fyLHyVJSVYJLtZeQb8lHzpocWWZdZ8+dBQAcOngIK8tsl4Gamprgo/NB0ZUiLP5pMTr7dna6L9Y70mRpwsqV0paUUvxTcKzmGN5d8S7Gtx/vdNuSUmsQe9HRIqyskCavm6EbjuIoFv++GH4n/FxuX1tvzdTesmkLTvmK9wZFXI0AYI1LWrNmjSAPSGVjS23hnNXixt3H4gMddCi8UIj//O8/ombPB69ZyxPV19aLGs9oczRO15/Gu8vexYjQEYK/x1J4qRAAUH6xXJDcHqYeOIMz+Nfaf6ExWlrbzHPnrZUwDh44iJXnncvsXG39HeRX5iM3V3xS2pk6a/wy08QI0s+v3npdbj61Gd8t+w4BPgE2n5eesibvFh0twsqr7i/lMgyD9sb2uGS5hPf+9x76BfVze5+uqLpmjSXdvn07rh2Qb8XKEbF11km01DEUS8mp6/eqY0VYWUV+ub2JaUKAIQBVTVX48H8fontAd6Lydl+xhkhcvnxZ8r1fLIlNidiMzSioLFBkDIGWCcv6desRbhI/iRdDfXM9TDoTyi3l+HT5p4j3iycqDwDKLlpDNvft3YeVp5ULC1Fq/GpqhDWokN3QBYC5c+fimWeewUcffaRI8pk7PP/885gxYwb3d2VlJWJiYpCRkYGgoCCissc1jcP8d+ejoqECHXp3wJDYIW7v89PvPwUqgL69+2JC2oS2n1d9iryTeajuXI0Jg9t+zmdf2T7gMOBn9sOECc63dUR+u3y8vvl1lJpLXe7jh+U/AJeBHt17YMIQafL8T/pj2TfLsL9uP7Kys1wakYbDBqAJGD1qNLq27ypa3g0NN+Cdd9/BhYYLiOsfh16Rrq/3C9cuAPut/79x4o2iZf7ryr+w4+wONMQ1YEKq8PMUUBIAFAGBAYGixvNPxj/hvZ3v4WzAWUnXwZldZ4BTQFRklKDvNx1tQu4PuTjUeAjZ2dmSlk8/+e8nQCWQ2icVE/o6lzmweiDef+99nKg9gR5DeiA+LF6UrEPlh4DDgNlkFnx+FpQtwOFLh4FkYEIP2+8s/d9S4ArQs0dPTBgk7XfQmsnMZCzZuwQXgi9gQrY8+3SGf6k/UA8MGzoMw2OGE5fX42oPLPrXIhyuPoz+I/qjY1BH119yg+UrlwOXgK5dumLCCPLnEwCyG7Lx/aHvUd6+HBPSycqsOFABlADhHcIl3/vFElsWi68+/Qp7q/Zi+OjhCPYPJi5Tt1cHMED62HREB0UTl5denY5VxatwNeIqJowkf14XfrMQqAJSU1MxoRd5eRaLBbm5uRg/fjyMRiNxeewKvCuIGLr33nsvampq0LdvX5hMJvj52XrWLl8m0+qvQ4cOMBgMuHDhgs37Fy5cQGRkpN3vmM1mmM3mNu8bjUbiA2U0GjEuYRx+PvIzck7mYGTSSLf3yS7FmIwmu8c/qesk5J3Mw+rjq/HMiGec7ktvsBqJBr1B8rm4scuNeH3z6/it5Dc065ph9ml7rtscu4/9YxfC6MTRCDIHoaymDHsu7uHarjqCXdrxNflKkhlqDMWo2FHIPZGL3JJcpMWkufyO3uf6edVJO6+Tuk7CjrM7sKp4FR4e+LDg7+kMVoPRR+8jSu6NXW7Eezvfw5rja6A36MXHM1+fa5gMwsY1MyUTZoMZJ66eQHFFMbqHi/deNcO6dG42ml3K7BTSCYM6D8L2M9uxtmQtHu34qChZUn4nk7pOwuEth7H6+GpM6TvF5jM5fgetubHrjViydwlyjufAx8eHeOwlq4PRh/x9FABSwlPQo0MPHCw/iHWn1uEvqX8hKo89fz4Gcb8ld5iYMhHfH/oeOcdzMD+LbOMltjyoXq9XTL/UTqmIDYpFaWUpNp/djMndJxOXycbomk2u7xNyMDFlIlYVr0LOiRzMGjuLuDw2hFzOe4kQlLCfWDlCIBKhvGDBAixatAhLlizBxx9/jHfffdfmRQqTyYT+/fsjLy+Pe6+5uRl5eXlccpzakKsoP4urRBYxCVvuJGqxpEamItQn1Nphq8R5hy05knD4CVtCyozJITM72drLXGjGsLvnlU0uctVhSy65w6KHwV/vj/Lacuw860a1B4Fy25naYUyCNWFLqZrBXKKmyFJxQIt+Yip3cCWxjrUtki93MhoAjIkbA6POiJMVJ3HwIvkOW0omwbCwHSCVKDOmdFUCwBrjqYc1YYt0hy1PjJ9Op+PupUqVilMyaRJoeVZsP7Md5TXky/0prZ9aIXIVT5061emLJDNmzMDixYvxxRdf4NChQ3j00UdRXV2N+++/n6hcqWQlWesH7jq/C+eqxHXYsocroyI5LFlwhy05Hrh6nR79g/oDcG20yGFYA+JKVMkhk715bT69WVC1B3fPK9thq9pS7bTDllxyjQYj0oKsnmqxLZYB4RUQ+CjdYpkdw3Un14nusCXlvA6LGYYQ3xBcqr3Upki+XL8DPu1M7dA7oDcAZbqkKVnWiGVCktXQzTmeQ7zDlpJ1dFna+7dH13bW8Copv0MxeMpAYiecSpWKU7IMHgDEBMUg3jcezUyz6EZDUlBaP7Uim/bV1dVEtxfKnXfeifnz5+OVV15BamoqCgsLsXr16jYJamqhY0BHpPhbk/bkqCEopvWpUobngCBr++EVx1Y4vXnJ5cnKTrF22Np1bhfOVp11uq0cMpNCkxBtjkZjcyPWFK9xub2755VfJF+pTnf8MRSLlLJmrH6bSjfhSu0V6TIFjmvfiL5ob2yPGksN1p9cL06WhPNqUyquldFCwqML8MZQopdcDJ54wA6JHoIAQwAu117GttPbiMryhEcXaBlD0pMVTxlIo+NGw6Qz4VTlKewv209UFv9ZpOSEZUCwMmMIeGbCqUZku4qTk5Mxd+5cnDvn2CvJMAxyc3ORnZ2N999/Xy7RbXj88cdRUlKC+vp6bN++HYMHDyYmSw7kvHkJeejye4s767AlxRNnj76Bfa0dtq4cx5FLRxxuJ5dhHdEugovNdTV5kKs4vxhDUA5Dhj9ZEer5cEduv6B+1moP5wtFt+eV0ggkITQBPcJ7oIlpEjR5cChT4LjqdDpu5UHs71DqeeXGsNU1Q8KjC4DTb8upLbhcSyZPgsUTHkEfvQ/SAq+vPChkCCrt8WTHMO9EHmoswjLOpeApA8nP6Ic+gX0AkJ+QsWMIKGvQs8+K1UWruecPKTwRgqJGZNN+/fr12LlzJxISEjB48GA89thjeOONN/D222/jpZdewq233opOnTrhgQcewKRJk/Dss8/KJdrrYW9eYtrzOkLIQ5ftsFVWXYb8s46LyLvbwIHFz+CHUbGjADhfcpPTkyXE48k38t2VyY6hvZjL1shhyKQnpnMJW4fL7ZfOk1NusE8wBne2Thg9bQiSksmfcIpZNpV6XtmVh70X9uJURUtpO1Ie3Y7mjujRwTp5yCnKkXXfrfHUA5b1lpE2kjzl0Y3zjUNMUAzqGuuw7sQ6YnI8aSAp5bXm3/+VnLCk+KegvV97XK27ii2nthCVRWN0rch2FXft2hU//vgjjh49ijvuuANnzpzBDz/8gMWLF2P9+vXo3LkzFi9ejJMnT+L//u//YDDIexP3ZhL9ErkOW64Stlwh5KFrNBi59rzOHgjutuTlw8ZAOjNa5Gx9ynXYKs51OHmQ2orXHt0DuiPYHGxtz+siYUsOTzm/Pa/QB4K7BhQ7hqINXYmGILfyIGDyIIfMPgF9YDaYcfKquIQtqee1g38Hrj0vf+WBlEcXaEnYUsqIUNoj2C+wH/Q6PfaV7SOasKV05zAWnU7HxbGSNOY9aSCxToOtp7fiUs0lYnL4k1klDXqDzuAwbEluaIyuFdm1j42NxcyZM/HLL79g9+7dOHz4MDZt2oSFCxfixhtvpAauHfQ6PZeU5u7NS6gRxbYjdPbAYx/gYrLJHcEaSZtKN+Fq3VX78mQ0rG0StkrsJ2xJbcVrDx+dD8YnWhtiuLp5yeUpZw1BodeMuxMJdgxFV3uQaAjyE7Z2nNkh6rtSZPoafDE6bjQA5WKfuTHkTQBJeXSBloStVUXiJw9i8NQDNtAnEEM6WycPJI0IT3l0AdsJJ6mELU8aSOGmcPSO6E08YcvGo6vwhCU7ybXjRw48eZ2qiT+29ipCrpuXUCNKSMKWnJ6lpNAkdOvQzWnCllwGIGCbsOXIEOQ/6OU05l0ZSXIZ9PyELUeTBznl9o3oi86BnUUnbEm9jnz0PshKljYBlCpTirfMHcOUHcO843lctQeSHt0h0UMQ6htKPGHLkx5BrlQcQa+1p2J0AWupOD8fP5yqPGVt6kMATycxKTmGgPKGYEZiBgw6Aw5ePIgTV04Qk+OplQe1QQ1dlZAenw6TwYTiK8U4eumo5P0INWaEJGzJ7VlyFTcrpR6pEHmOErZsPLoyGBVZiVnQQYfd53c7TdiSy6DnJ2wJibl0V65NtQcR3jI5DEGl4oLZycqWU1sEV3twxzDt07EPooOiUdtYi3UnrTGXJD26/MkDUSPCgzGe7BiSTNjypKfMz+iHsQljAZDzWns6iYlfX55UwpanYnQBINQvFMNjrR0DSf4OqUfXyh9bexURaA7EqDhrwpY74Qtiwg2Eejzl8iy5irmU+wGfnmidPDhK2LKJ0ZVBZni7cAyOtiZsOav2IKdBL6lmsBu68pfaBVd7cOM6ykq2tnHec2GPTcIWKZnxIfHoGd7TOnkoFpaw5c51a2/yIGesuj2Elhd0B096BHuF90JscCzRhC1Pe8rY3yEpI8nTSUyDOg3iEra2ntpKRIanYnRZhIQPuosnVx7UBDV0VYQcNy8xD3hWnqOYS7kNz+Exw50mbMltWAeYAjAm3tphy945ldujC7TcvJzFXpGoLrHy2ErX1R5kiLkemzCWS9g6VH5I0Hfc0ddRwpYr3En4E2sIytXpjp08yBmrbg928kAyYcuTMZ5S60yLwdOeMjapkFTClqeTmAx6A7JTrsexEpqQeTJGF2jpUrruxDpUN5DpK+Dp61Qt/LG1VxnszXlj6UZBHbbsIcaocNVhS27D02gwIjPZcbYpiSVbZw88vmEo142AvXk5S9iS87yKSdiSQ247Uztu2dQThqBQ3AnT4NeZFpKw5e51m56YDl8fX5RWlOLAxQOyxqrbo71/ewyNtrZEJ7X07WmPID9Rk0TClqc9ZbHBsUQTtjwdowu43x3RFZ6M0QWA7h26IyEkAfVN9cg7kUdEhqdXHtQCsdHduHEj7rnnHgwdOhRnzljjFb/66its2rSJlEivJynMdcKWK8QYFfxSNc48niQMT3tGC4kkHNbw3FiysU3CFgn9+nZ0nbAlp1ybDluukuBkkiv2AeSuJ5k1WvgJWy5luuEVHRozVFTClruhBv5Gf27lYcXRFcQ9ugD5pW9Px3iOiW9J2CLRYUsNnjJ7FTvkwtPjBwCZSZkw6Aw4cPEATl49Kfv+PRmjC0jPeRCDGq5TNUBE+x9//BGZmZnw8/PD7t27UV9vrWNaUVGBN998k4RIzeBOkXxAvDHjzPNBwvDMTs522GGLhOGZGJqI7h262+2wRUI/ITcvUrHPSrV0ZicPm0s3C0rYctdw6x3Rm0vYElrtwR2vqNiELTljn3899qusZf0cwVV7IJSw5WmPID9hi8TStxo8ZewYkuiw5WmPPNAqYYuAIejpGF2g5V5KqlScp1ce1AKR0X399dfx8ccfY/HixTAajdz7w4cPx65du0iI1AzuFMkHxBszzhK2SBie/ISt1kYEqbJKjgxBUtntrm5ecsvNSrZWe9hzYQ9OV552uJ1ccsUmbMlR7YGLfRYZLiHVWBQTpytHqAErb8upLSivKXd7f67oFdGLaIctT8d4AmS91mrwlA2JHoIwvzAiHbbUMH4A2YQtT8foAsDo+NHwN/rjTNUZ7LmwR/b9q+E6VQNEtD9y5AhuuOGGNu8HBwfj6tWrJERqBlcJW64Qa8w4S9giZXg6WvomZnhel9c65pKUfukJLe157SVsyS23g38HDI1xHXMpp1ylqz2I9Xy4ey2JSdiSQ7+4kDj0iuiFZqYZ56+dd3t/rtDpdIoYgp70JJFM2FKDp8ygN7TU7pbZ4+lpjzwL+7v/7cRvsidseTpGFwB8fXwxLnEcAO2uPKgBIqMbGRmJoqKiNu9v2rQJiYmJJERqBn57Xik3LynGjCPvFSnD01G1B1KG57CYYQg2B6O8ptwmYUuOVrz2aGdqhzEJ1ycPKki6IyFXzMqDHB7PsQlj4evji5KKEhy4eMDl9u5eS/yELVfVHuQKNWDHkIWkR5cvj0TClhpiPGODY9GnYx8iCVtq8ZSRmqyoYfwAa8JWfEg86pvq8duJ32Tdt6djdFmU8Fp7ehw9DRHtH3roITz55JPYvn07dDodzp49i6+//hpPP/00Hn30URIiNYU7Ny8pxgw7a27dYYuU4ekoYYuUYW00GO3GXJLMbndWZoxI0l1KS7UHRwlbciY5sQlbl2ovYfuZ7U63lWNC4W/0F1UkX45rSWj4gmyxz60NXYIeXcA6eSCVsKUajyChzH21eMpIJWypwSMPSAtbEgp/cufJcWRXHraf3o6L1Rdl3bcaVh7UABFD97nnnsPdd9+N9PR0XLt2DTfccAP++te/4uGHH8YTTzxBQqSmYBO2XHXYsoeUhy4/YYvfYYuUx9NRwhbJ1qf2jBaS2e3OErZInFd+hy2X1R5kOL9i2vPKJVdMoqYc1xJX7cFFwpZcEzR28sBC2qNLMmFLNTGevFJxciZsqcVTFuoXimExwwDIG76glvEDyCVsqcWY7xzUGWmRaWDAYFXRKln3rZbr1NMQ0V6n0+HFF1/E5cuXsX//fmzbtg0XL17E7NmzSYjTHEI7bNlD6kPXnueDpMeTvXnxO2yRbH2anZLdJmGLpH7OErZIyBVSJF9uA1uot0yuCQU/Yety7WXnMmW4loQmbMk1QeNPHgDyHl2A3NK3WoyIwZ0HE+mwpSZPGYkyY2oZP4BcwpaqjHmNrzx4GqIjbDKZ0KNHDwwaNAgBAQEkRWkOqWXGpD502Zslv8MWSY8nm7DF77BFsvWpvQ5bcrbitYfDpDtC59VVkXy5PeZswtbeC3udJmzJZdjzE7ZcxVzKoavQhC0Ssc8AeY8uQC5hSy0xnga9QfDKgxjU5Clj7zNydthSy/gBtglbcnqt1RJeA7Q4flYXrYalySLbftV0nXoS2bS/9dZbBb8ornHVntcRUr12bMIWv8MWSY8nP2GLfQCRLpTfuswYSQ8y0HLzap2wReq88hO2Dl482OZzufUVmrAl57gKTdyQuzmGs4QtOScQ7OQBIFtHl4VUhy01GREkvNZq8pT1CO/BJWzJ1WFLTeMHkEnYUpMxP7DTQIT7h6OyvhKbT22Wbb9qWnnwJLKNcHBwsOAXxTVCOmzZQ6oRxU/Yam14KuXxJN36lF8kv9ZSSzQmGLBtz8tP2CJ1XvkJW/a8VyST4AR5POUoa8bzfDiLuZRL1zEJY+Dr4+s0YUvOCUSYXxhmjZqFW7vfiq7tu7q9PyEQMQRVtCxMImFLTZ4yEh221DR+QMvKw7bT22RL2FJTeIZBb0B2irVUnFZXHjyJbNp/9tlngl+keOONNzBs2DD4+/sjJCSEmBwlkHrzcsd75tDwJOXxTLFN2CLt0WUTttjJA2n9bDpsHbUT+0wiCc6J4Umi45aQ9rxyjitbJN9Ze16GYbgHtbsy/Y3+SE9IB+DYEJR7AvHKqFfw4x0/KhK6ANjWmZYrYUtNRgSJDltq85TxJytyJGypafwAa8JWamQqGDCyrTyozZgn6bVWi2feU6hjhGWioaEBt99+u2ZKmInNNrV5wEt4SLZO2CJteCaEJqBHeA8uYYt069PWCVukPbqA/TJjSlSX2Hxqc5uELRLjySZs1TbWYt1J+wlbpKo9OGyxzLSEicjZHMORp4X0hIk0/A5bciRsqaG1amvkTvZRm6dM7oQtNS3rszgr2SgFtYVnZCRlwEfvg8Plh1F8uViWfartOvUURLRPS0tDv3792rz69++P4cOHY+rUqVi3Tv62k6+++iqeeuop9O7dW/Z9ewJXHbZaw3/ASzEW+Qlbvx79lXgoAWA7i1XC8OQbLUoYKPyErVMVpwCQNYz4CVv8UnE2cmWu9uCoxTInV+ZQDVcPPH48tBznmJ1wOkrYIj0hJA2/w5Ycy6b8jlNqMSLYa1SuDltq85T5+vi2rDzI4LVWmxEItPwOc4pyZEnYUpsxH+wbjJGxIwHINyFT28qDpyAywllZWTh+/DjatWuHMWPGYMyYMQgICEBxcTEGDhyIc+fOYdy4cfjf//5HQrxmcNVhqzVyPODtejwJPsDZm9fKYythabYQl5eemM4lbO27sM8qj6BhzU/Y4kJCCBv0Sld74MuzW+1BZsM+MzkTep0e+8v2o+RqSZvP+cvvcpxjVwlbSkwISSNnnK4aPbpyd9hSo6dMzjJjalvWB1oStirqK2RJ2FJbeAag/ZUHT0Fkjbi8vBwzZ87Eyy+/bPP+66+/jpKSEqxZswazZs3C7NmzMXnyZBKHIJj6+nrU19dzf1dWVgIALBYLLBb5ynw4gpXhSFZWYhZWF63G8iPLMX3QdKf7qrO0VGdobmqWdPyZiZl4ad1LWHt8LRJDrO2addBJPheu9BsYORAhviE2y+xSj10IRhgxOm40Vhevxi+HfwEA6KF3S57LMUzKwuZTm7H8yHI82PdBNDQ2AAB0jPTz6oysxCzM2zwPq4pWoa6+jjPAOC8I4/hY7eFKv5HRI+Hn44fSilLsPrsbvSNsV1Qam6yGJ9PMyKJvoE8ghnYeis2nN2PZ4WV4pP8jNp/XNfB+B43NsOhcy3SlY3ZyNvaV7cPyI8txR/c7bD6rt1jvH6TGUw5c6Tc2diyXsHXs4jHEh8RLl8XztjVaGmHxUeacuNJxQtIE/KvgX1h2eBmyErPsbiMU1oBoampSbMxd6Tc+fjwAa4ets1fPIrxduHRZ18dQrt+sYLkudMxMysR/9v0Hyw8vx/DOw92S1WCx3of1Ovfu/2JwqV9iJp7G01h/cj2uVF9BgMm9sqzspLOxqVEV9gwpea4gYuh+9913KCgoaPP+XXfdhf79+2Px4sX485//jHfeecflvp577jnMmzfP6TaHDh1Ct27dJB3rnDlz8Oqrr7Z5f82aNfD395e0Tynk5ubafd+v3g+ANebyu2XfIcDH8YVf29SSDJS7JhdmvVn0cTAMg/bG9rhkuYRf9v4CACg5WYKVK8U1rmiNI/0AoLdvb2ys28j9vX7deoQZw9yS54zY+lgAwIaSDQCAa5XX3NYPcKxjYG0gAGBt8Vr8vOJn7C+3Zu+fP3deFrmtaWKaEGAIwOXay1jwwwJ0D+gOADhZehIAUHysGCurxMt1NoY9/XsivzIfC35dgD91/JPNZxcvWbOk9xTuQbuT7UTLtUdSUxI2YzO+2PoFYi/E2nx2rfEa9/81OWtg1BsF79eRjqHXrB3LVhxZgeW/LrfxTh89dxQAcKr0FJHxlBNnY9jNvxsOVB/A/P/Nx4TwCZJlsCszALB27Vq0M8gz5kJxpGOHyg4AgJ8P/IyJzES3luUvX7ZOzHfv2g1TsUnyfqTgbAwT/BJwovYE3vr5LYwJGyNZRvFZa4xoSYn7934pONIxqioKAPBd4Xe4of4Gt2ScrrM2DmpsbFRcR0f6MQyDSFMkzjecx1s/vIUhIUPcklNbZ7UJtmzagrN+Z93alxicXaNyUlPjuGMlHyKGrq+vL7Zs2YLk5GSb97ds2QJfX18AQHNzM/d/Z8ycORP33Xef020SExMlH+vzzz+PGTNmcH9XVlYiJiYGGRkZCAoKkrxfoVgsFuTm5mL8+PEwGu0/kBdcXIBD5YfAJDGY0NPxA+hq3VXAuhqPidkTYTJIuwHfqr8Vi3cvRkmddVk4OSkZE8ZKe/AJ0e/K/ivYuKzF0M0Yl4GIdhGS5AmhZ0VPLPpwEZph9cqEhYZhwgQ3HuwudGQYBm9/+DZOVZ6CbzdfdLnYBTgLxEbHuiXXGTc23oilB5bicvhlTBhjlfHzip+By0D3bt0xYZhwuULG8FTBKeTn5OO44XgbneZ+MReoBgb2H4gJXeXRN7YsFl9++iUO1BzA6PHWRByW8ppy4HolsEkTJwlatnOlY2ZzJv753j9xufYyQnuHYkTsCO6zTes2AReApIQkTBhPZjzdRcgYHtx6EC+sewGlvqVuXZd1jXXAXuv/MzMyEWQmfx8FXOs4tnEs5r87H5csl9B5QGekdkyVLOuNsjeAGmBA/wGY0EWZMRcyhtv8t2Hulrk40+6MW2O48beNQBmQmJCICeOUu6Zd6Ti8bjjeXfAuTtefRreh3ZAYKv3Zf6j8EHAYMJvMxO7DrREyhrcZb8MH+R/gQvAFt4/LdNQENAIjR45ss9JGAiH6yQm7Au8KIobuE088gUceeQQFBQUYOHAgAGDnzp349NNP8cILLwAAcnJykJqa6nJf4eHhCA+XvgTjCrPZDLO5refTaDQqMlBC5E3qMgmHyg8h50QO7km9x+E+9JaWB7qvyVdyzOCkrpOwePdi7m+TweT2uXCm341db4Rep+eWA31NvkTPfXKHZPQM74kDFw8AAHwMPrLIc6bjxJSJ+LjgY+Qcz0F0ULR1ewO5a2xS10lYemApVhevxlsZbwEAGJ11GcvkI208nel3U/eb8ETOE9h6ZisqLZVo79+e+4ydUJiNZtn0Te2UirjgOJRUlGDj6Y02HcX0hpbfgdkkblXDkY5GGJGdnI2v932NnBM5GJPU1ltm9FH2niEFp2PY7Sa8sO4FrDu5Dg1MA9qZpHliG9ESI202yTfmQnE4hkYjxiWOw7Ijy7Dm+BoMjB7otiyT0f17o1icjeHk7pMxd8tc5B7PBfTWe4wU9PrrTUtkujeKxZGOHYwdMCJ2BNafXI81J9bgiYgnJMswGKzPRx10qhrDm7rdhA/yP8Dq4tXw8fFxa+WBxL1XCErZT0JlEIlQfumll7B48WLs2LED06ZNw7Rp07Bjxw4sXrwYL774IgDgkUcewfLly2WVW1paisLCQpSWlqKpqQmFhYUoLCzEtWvXXH9ZxTjqsNUaftUFd4LP2YQtFtJJNvxqD0rIA1q1WlUgW56fKEKy1TELW+1hX9k+rj0vySQ4fsJWTnGrag8E5DqrM02qqoWjMmOky+IpBb/DljsJW+yEFVBXog8gX7KPGhOZAGvCVgf/Dm4nbKlVP0C+MmNqTLgDgBvibkA7Yzucu3YOu8/vdmtfaqsO4imIjfCUKVOwdetWXL58GZcvX8bWrVtx9913c5/7+fkJCl0QwyuvvIK0tDTMmjUL165dQ1paGtLS0pCfny+rHKVx1GGrNaxBodfp3bqw/Y3+GBPf4rFSwhBkH0AekaeAYc122CqtKOXqXJLUM8wvDMNihgFoMQSltocWiqMyY6Tk8icP/Ex/UgZ9ZrL9DlveXl6MhT95cKfMGL+8mNqMCFY/dztsqdVI4peKc6fMmNpKb/FhHT/rT67HtQbpTiw1llADALOPGRlJGQDcL/dHqy5YIap9Q0MDTp8+jdLSUpsXKT7//HNr04RWr9GjRxOTqQRCiuQD8nqylDYE+R5WJTxjQ2OGItQ3VDF5/A5brMeT9Hn1VIvl1u15SckdHT8afj5+OF15GvvK9rWVJ7PhaW/yYCPPi8uLscjRYcvGo6syI0KuDltqNZIAecqMqVm/ru27Iik0CQ1NDVh7fK3k/ajamJdp5YHW0bVCZISPHTuGkSNHws/PD3FxcUhISEBCQgLi4+ORkJBAQqTm4TwtTm5ecnqy2FkzoIynqndEbzwx6Ak8OfhJ+Bn9iMvjTx6U8sSxY8h6IUjL5drznshDjaWGuOeR7bB1pe6KTYctUnL9jH5IT7ROHvieD5IhGvbqzWrFowvI02FLjXV0+cix9K1mIykjKQMGncGtDltq9VgDzsOWxKDm8IwJKdYktB1nduDCtQuS90M9ulaIaH/fffdBr9djxYoVKCgowK5du7Br1y7s3r0bu3btIiFS89jrsNUaOT1Z8SHx6Bne07o/BTxVOp0O72e/jwVZC4jLYrmjp7UeaqfATorI408eAPKe5J7hPREbHIu6xjqsO7GOuOfRZtn0mDIeT3v94Ul2nmMfsPwOW1ry6Pr6+GJc4jgA0o0INcfoAvJ02FKzkRTiG4KRce512FK7gSTHyoOajfmowCj0j+oPAFhVtEryfmiMrhUiI1xYWIhPPvkE2dnZSE1NRd++fW1eFPHYtOd1cPOS25P16IBH4efjh8GdB8uyP7UxuetkbHlgCxZmL1REHpuwxULaMNLpdC3eq6MrZG/Faw97S24kPZ6s52Pb6W3WsmIg69G1l7ClJY8uIGz1yBlqjtEF5EnYUrORBLi/9M0ZSCo05AF5ErbUHJ4BOE5+FYPaJyxKQUT7Hj16oLy8nMSu/9DY817xkTvp57FBj6Hq+SquDbHW0Ol0GBozVHIZJSkonnTXhdfSmaCnk4VN2OK35yXp8YwJjkHfjn1t2vOS1NNm2VSh2GelYScP209vl5SwpeYYXcA6TqyO7nqt1agf0OLxlJqwpXYDyexjxvgkayc4qWOo5vAToGUM1xSvQUNTg6R90BhdK0RGeN68eXj22Wexfv16XLp0CZWVlTYvijRYoyXveB5qLbVtPifxwNXKw1st2JQ1U6LaQ/wY+Pn44VTlKew5v4e4XJuELdYQJOxJbmN4EvTotpbHMIwiEwgliQ6Kdithi7+UrNYHrFweT7UaSV3bd0ViaKLkhC3OQFKpIQ+4H2utdmO+f6f+6NiuI6oaqrCpdJOkfahdR6Ugov24ceOwbds2pKenIyIiAqGhoQgNDUVISAhCQ0NJiPxD0DuiN2KCYlDbWIt1J9e1+VxrS6hahE3YApQZJ37C1rlr5xSR27rMGGlDkJXHVnsgLW9Mwhj4G/1xuvI09l7YS9yw9gTuhC+o3aMLWBO2fPQ+OFR+CMevHBf9fTXH6ALuJ2x5g4HEeuV3ntkpKWFL7d5OvU7P6Sg1fIHG6FohchWvW7cO69atw2+//WbzYt+jSMPVzUsrheu1jEFv4MYw0ByoiEx+uAR7DErIYxO2SBuCgzoPQgf/DrhadxVbTm0hLs/Xx5crFbfi6ArNeXSBlsmDlIQttcevAtaELbaNsxRD0Bt0dCdhS+0xukBLwhYDRlLCljcY8+6uPHiDjkpARPtRo0Y5fLVv3971DigOcVQkHyC/ZEuRhznpczAnfQ7uT71fEXltDF3CBlnrhC3ShqBBb+BKxa04uoJ4YwzA1ojQ4u/OnYQttXs7WdxZ+lZ7jC4AjIobJTlhy1sMJHcMQW/wdo5PGg+j3oijl47i2KVjor+vdq+1UihyFVdVVWHRokUYNGgQrbrgJvwOWwcuHrD5TIueJS3SOagznhvxHNr7KzPpiwmOQZ+Ofbi/laj2wH8AKWEI8hM1lUgO41d7OH/tvFWehn537iRsqT1+lcWdDlveoCM/YUvs0rc3xOgCtisPYhO2vMGYDzIH4Ya4GwBIM+a9QUclIKr9hg0bMHXqVERFRWH+/PkYO3Ystm3bRlKk5vE3+mNswlgAbW9eWvQsUeSBNQQBZVss/3rsV0U8rGy1h4MXD3JF8knK4ydsbT1tbY6htd+d1Dhdb/B2Au4lbHmL11qqx9NbDCR3Era8xdvpqLW6ELzBa60Esl/F58+fx9y5c5GSkoLbb78dQUFBqK+vxy+//IK5c+di4MCBcov8w+GozBj16FIcYdPpTolqD7yEraqGKuJy+TGXy44uIy4PaDEiWKNAa787NmHrcPlhUQlb3hC/CtjWmRbttfYSHaUmbHmLEchP2BI7ht5izLP3mQ0lG1BZL65qlbdcp6SRVftJkyaha9eu2Lt3LxYsWICzZ89i4UJlivH/kWCNli2ntuBSzSXuferRpThicOfBaO9nDZUw6o3E5fETtlhIG4LsAyGnKAcA+aRMpZP8lEZqwpa3eDsB2zrTYhK2vMVr3SmwE/pF9ROdsOUtRiAgfeXBW7ydKe1TkBKWAkuzBbnFuYK/5w1l/pRC1qt41apVePDBB/Hqq69i4sSJMBi0deNXC2yHrWamGTnFOdz71KNLcYRBb8D8jPn4U/c/YWjMUEVk8msGs8eghLxqi7U1L+nfAVvtgUWLvzspRoQ3xK+ySE3Y8iYdpYQveIsRCEhP2PImY56f/CoUfpk/b9CRJLJqv2nTJlRVVaF///4YPHgwPvjgA9ohjRBOW61qzLNEkYf7Uu/DD3f8gABTgCLy2CVFFtKGYLcO3ZAQktAij/DvwKA3IDs5m/tbi2X9pHTY8hZvJyC9w5Y3ea2lJGx5kxEoNWHLW8IzgJbn/cpjK20MWGfwW3F7w2+RJLJexUOGDMHixYtx7tw5PPzww1i6dCk6deqE5uZm5ObmoqqqSk5xf2jYm9eqY6u4ZB/q0aWoCTZhi0XJag+AMr8DpTvdKY2UhC1viwuUUmbMm3Qc0GkAItpFiErY8iYjEJDmtfYmY35k3EgEmgJxofoCCs4WCPoO9ei2QET7du3a4YEHHsCmTZuwb98+zJw5E3PnzkVERARuuukmEiL/cLAdtq7UXcG209ZKFtSjS1EbWjc8M5IyOL20OMGUkrDlTd5OQFrCljd5raV02PImIxBo+d3/fvJ3VNULc6h5U3iGyWBCRlIGAOHGPI3RbYH4Vdy1a1e89dZbOH36NL799lvS4v4w8JdNlWq1SqGIxcbQVcDwHBU/Cv5Gf6s8BX4HIb4hyE6x/g6jg6KJy/MEYhO2vCl+FbB22BKbsOVtOor1eHqTEQi0Stg6Lixhy1uNebGTFcB7dCSFYtobDAbcfPPNWLZsmVIiNU/rmxf16FLUxqDOgzA0eigGdBqAIHMQcXm+Pr4Yn2iNuVTqd/D1rV9j7yN7MbCzNksnik3Y8iZvJ4ujko2O8DavNVsqTmjClrcZgQAvYUvgyoO3hWewjq2CcwU4V3XO5fY0RrcF77mKKW1gi+TvL9uPkqslihTmp1DEYNAbsOXBLdjx1x2KPTRv6moNj1LCsGbl9O7YWxFZnkBshy1vil9lYb3Wa4rXCErY8jYdxSZseZsRCNg6foQkbHmbMd8xoCMGdrJOplceW+lye+rRbeGPrb2XE+YXhmExwwAo1/qUQpGCkh6Fe/vei3cz38W8cfMUk6l1xCx9e5u3E2hJ2KqsrxSUsOWNXmspY+hNBhI/YWvXuV0ut/e28AxAXJkxGqPbgvdcxS44efIkHnzwQSQkJMDPzw9JSUmYNWsWGhrE9b/2Nrg6l0dXtIQuUI8u5Q+Mj94H04dMR7cO3Tx9KJpBTMKWt8WvAuI7bHmjjmIStrzRCOQnbAlZefBGY5593ucez0V9Y73TbalHtwXNaH/48GE0Nzfjk08+wYEDB/Duu+/i448/xgsvvODpQyMKe/Nad3KdIq1WKRTKHw8xHba80dsJiCsz5o1e6y7tuyA5LFlQwpY3GoGAOK+1N4ZnpEWlISogCtcarmFDyQan29IY3Ra86yp2QlZWFj777DNkZGQgMTERN910E55++mn89NNPnj40ovQI74G44DjUNdZxNy8tFq6nUCieRWjClrfFr7KI6bDlrTpyxrwLj6c3GoFAy8pD/tl8lwlb3mjM26w8uPgdUo9uC5q2iCoqKhAWFuZ0m/r6etTXtywBVFZWAgAsFgssFgvR42Pl8P+VwoTkCfio4COsKV4DwHpzUuLYhSCHfmpH6zpqXT9A+zrKoV9mYiZe2/AacopyUF1XDZPBZHe7Bos1XEzp+5C7Ovrp/TAydiR+O/kblh1ehmmDpjncljUiGhsbFdNRrjFcsH0BVh5bifqGeocGUGOTNbGZaWa8agzDzGEYEDUA+efyseLICtzX9z7Hshqvy2CU+93LMYZZiVn49+5/Y8XRFXhr7FsOvbX8sM1GSyMYvevSgO6i9H1UqBzNGrpFRUVYuHAh5s+f73S7OXPm4NVXX23z/po1a+Dv70/q8NqQmyus9p89OlR2AADUWGoAABcvXMTKla6zMpXEHf28Ba3rqHX9AO3r6I5+zUwzgn2CUdFQgXd+eAd9AvvY3a6opggAUF9X75H7kDs6xjfEAwC+2vYVksuTHW7X2Gg1BDf8vgFHzUcly5OCO/pZmi3w1fviQvUFLPxxIVL8U+xuV1ZWBgDYt28fVp71rjFMYVKQj3ws2bQEEWciHG5XcNXaYezqlauKX6fu6NfY1AgfnQ+KrxTj058/RWffzna3q2is4P6/etVqRcMXlLqP1tTUCNpO9Ybuc889h3nznGdPHzp0CN26tSSenDlzBllZWbj99tvx0EMPOf3u888/jxkzZnB/V1ZWIiYmBhkZGQgKIl+eyGKxIDc3F+PHj4fRaJS0j7GNY/H2u29zhm7nqM6YMGGCnIcpGTn0Uzta11Hr+gHa11Eu/SYzk/Hl3i9xqf0lTBhn/x6TfzYfOAr4+/kreh+SQ8fkS8lY8skSHKw5iJHpIxFoDrS7nW6/DmgGxowZg4SQBHcOWzByjWFWfRZ+OfILKiIqMOEG++Pz8X8/BiqB1L6pmNDHu8Yw8lwkvv3sW+yv3Y/0jHSYfcx2t6s+WA2cBNq3b6/YdSrXGP772r+x9sRaXOt8DRMG2z/2suoyYL/1/xMnTrS7jdwofR9lV+BdoXpDd+bMmbjvvvucbpOYmMj9/+zZsxgzZgyGDRuGRYsWudy/2WyG2dz2h2A0GhV94Lkjz2g0Ij0hHcuPLrf+7aPssQtB6fPpCbSuo9b1A7Svo7v6Teo6CV/u/RKrildhQfYCu9sYfKzJsHq93iPn0h0de0b2REpYCo5dPob1p9bj1u632t2OjWE1G82K6+juGN7U9Sb8cuQXrD6+GrPTZ9vf6Lrzz8fg43VjODBmICIDInH+2nlsO7cN4xLH2d1Ob7CGbRj0Bq8bw0ldJ2HtibVYXbwaz4541u427O9QB53X6SdGjhBUH6EcHh6Obt26OX2ZTNZYsTNnzmD06NHo378/PvvsM+j1qldPNtjqCwAtL0ahUMggpMOWN1Yk4MNl7jspM+atlSUAcC2rnSVseWOiFotep7cpu+kIbyyhxsLqt7F0IyrqKuxu4836yY33XcUOYI3c2NhYzJ8/HxcvXsT58+dx/vx5Tx+aIrCZmAAtL0ahUMggpMOWN9aY5cMvyu+ow5Y36xgZEIkBnQYAgMNScd5uJPENXX7jBD7ebMwnhSWhW4duaGxu5JLQW+PN+smNZs5Abm4uioqKkJeXh+joaERFRXGvPwLRQdHo27EvAOrRpVAo5HBVZsybvZ2AsA5b3u61dlVmzNuNpHGJ42AymFB8pRhHL9lPFvTWEmosrmoGe7t+cuKdV7Ed7rvvPjAMY/f1R2Fy18kAgGBzsIePhEKhaJWJXawPWEcdtry1xiyLkA5b3q4jO4aOOmx5u5EUaA7EqLhRAFxPyLx1DNmVh5XHVtpdefB2/eSEngEN8czwZ/Be1nv4+4i/e/pQKBSKRunSvgtSwlIcdtjydm8n4Npb5u1e635R/RAZEOmww5YWjCR+CIo9vD08Y3jMcASbg3Gx5iJ2ntnZ5nNv109OvPcqprQhwBSAaYOnITIg0tOHQqFQNIyzZB9vjl9l4Sdsnb9mm+fBXyX0Vh31Oj0mJDvusKUFI4m9RjeUbLCbsOXtxrzRYERmciYA+79Db9dPTugZoFAoFIoonC2beru3E7AmbA3sNBCAVUc+7LI+4N1GBDuG9hK2tGAkJYUloWv7rmhsbrS78uDt4RmA85UHLegnF957FVMoFArFI/ATtgrOFth85u3xqyyOjAi+UejNRsS4xHEw6o12E7a0YiTxjfnWaMGYz07Ohg467D6/G2cqz9h8pgX95IKeAQqFQqGIwmQwYXzSeABtDUEtxOgCLUbSmuI1NglbfA+2NxsRgeZAjIq3n7ClFSOJnazYW3nQQnhGeLtwDI4eDMDOyoMG9JML776KKRQKheIRHJUZ00KMLgCkRaVxCVsbSzdy7/NDF7zdiHBUZkwrRtKI2BEIMgfZTdjSmjGv1cmKHNAzQKFQKBTROOqwpYUYXcBxhy2teHSBljJjrTtsacVIMhqMyEyyJmy1mZBpLDwj93gu6hrruPe1op8cePdVTKFQKBSPwE/Y4nfY0kqMLmDfW6aVGF0ASA5L5hK2+B22tGQkOYrT1Yox37djX3QO7IwaSw1+P/k7975W9JMDegYoFAqFIglnHk8tGElswlbR5SIuYUtLHl3AvjGvJSOJn7B1tuos975WwjN0Op3d36FW9JMD77+KKRQKheIR+MumbMKWVmJ0AWvC1uj40QBajAgtxegC9kvFaclICm8XjkGdBwGwTdjSkjHPhqD8euxXbuy0pJ+70DNAoVAoFEnwE7bYDltaidFlae3x1JpH117CltaMJHvhC1oKz0hPSIfZYMaJqydwuPwwAG3p5y7auIopFAqFojj2OmxpKUYXaDGS2A5bWorRBawJWxlJGQDajqEW9ANaJitrj6/lEra0ZMy3M7XDmIQxAFqMeS3p5y70DFAoFApFMq07bGkpRhdo22FLax5doG2ZMa0ZSamRqegU2AnVlmouYUtL4RlA25UHrennDtq4iikUCoXiEVp32NJSjC6LjTGvsRhdwFoqjt9hS2tGEj9hq3UIilauU1a/TaWbcKX2iub0cwd6BigUCoUiGX7C1q/HftVcjC7QYkSsKlqFxuZG7n2tGBER7SJsEra0aCS1XnnQWnhGQmgCeoT3QBPThDXFazSnnzto5yqmUCgUikfglzfSWowu0JKwVVZdZtNhS0tGBN/jqUUjqXXCliaNeTYE5dgKTeonFXoGKBQKheIWrLdsY+lGXKm9AkBbRhK/w9byo8u597XktWbHcO3xtai11ALQlpHET9jil+HS0hiyZcZWHWtZedCSflLRzlVMoVAoFI/AT9jKKc4BoC0jCWjbHENLhjxgm7B14uoJANozkvhjyHk8NWQGDYsZhhDfEFyqvYRtp7cB0N7vUAr0DFAoFArFbViPIGvoas1IYhO2zlSdAaA9A0Kn03Gl4li0pqNNwlbd9ZUHDV2nPnofZCVnAWhZedDahEwKmrqKb7rpJsTGxsLX1xdRUVH4y1/+grNnz7r+IoVCoVDcgjUirjVcA6A9I4mfsAVoy0BiYScrLFozkvgJW6uLVgPQ3nXK/g43lmwEoD39pKCpMzBmzBh89913OHLkCH788UcUFxfjtttu8/RhUSgUiuZhE7ZYtGYkAbaGoBYNiPTEdJgMJu5vLerIGoL7yvYB0N51mpWcBb1OjyamCYA2J2Ri0dRV/NRTT2HIkCGIi4vDsGHD8Nxzz2Hbtm2wWCyePjQKhULRNPyELUDbRhKgPQMJAAJMARgTP4b7W4tGUmuvtdau0w7+HTAkegj3t9b0k4Jmz8Dly5fx9ddfY9iwYTAajZ4+HAqFQtE8NoagBo0kNmEL0K4BwR9DLerIJmyxaPE6ZcuMAdqckInFx9MHIDd///vf8cEHH6CmpgZDhgzBihUrnG5fX1+P+vp67u/KykoAgMViUcQTzMrQqtdZ6/oB2tdR6/oB2tdRKf3GxY+DDjowYKBjdIqeT6V0zE7Kxr8L/w2dTpv6ZSRkcP9vamzSpo6JGfju4HfWPxjlfvdK6vfCby8AsBq6WtOvtTxX6Bi2mJxKee655zBv3jyn2xw6dAjdunUDAJSXl+Py5csoKSnBq6++iuDgYKxYscLhrO0f//gHXn311Tbvf/PNN/D393dfAQqFQvkD8ezRZ3G05igGBA3AS4kvefpwZGd7xXbMOTEHvnpfLO2z1NOHQ4S/H/07imuLsbjHYoQaQz19OLKz/vJ6LChdAACY0GEC/hb9N88ekMwwDIOHDj6Ecks5Yn1j8X639z19SESoqanB3XffjYqKCgQFBTncTvWG7sWLF3Hp0iWn2yQmJsJkMrV5//Tp04iJicGWLVswdOhQu9+159GNiYlBeXm50xMnFxaLBbm5uRg/frwmQyy0rh+gfR21rh+gfR2V1O/NTW/iHxv+gcldJuP7274nKouPUjrWWmqR8U0GUsJSsGTSEmJyWqPkGFY3VKOyoRJRAVFE5bRGKR3La8rReUFnMGDw+IDH8U7GO8Rk8VFyDB9f9TgW7V6E3hG9UfDXAqKyWJS+j1ZWVqJDhw4uDV3Vhy6Eh4cjPDxc0nebm60FofmGbGvMZjPMZnOb941Go6IPPKXlKY3W9QO0r6PW9QO0r6MS+j0x5AkcrziOv6b91SPnkrSORqMR2/66jdj+hcgnfV5DjCEIaRdCVIYzSOsYFRyFoTFDseXUFhgMBsWvUyXG8NYet2LR7kUI9QvVpH6sHCGo3tAVyvbt27Fz506MGDECoaGhKC4uxssvv4ykpCSH3lwKhUKhyEuYXxi+uPkLTx8GheKUe3rfgy2ntiA5LNnTh0KEjKQMfPunb5EWmebpQ/E4mjF0/f398dNPP2HWrFmorq5GVFQUsrKy8NJLL9n12FIoFAqFQvlj8siAR5CVnIX4kHhPHwoRdDod7up1l6cPQxVoxtDt3bs3fvvtN08fBoVCoVAoFJWj0+mQEJrg6cOgKID2iuRRKBQKhUKhUCighi6FQqFQKBQKRaNQQ5dCoVAoFAqFokmooUuhUCgUCoVC0STU0KVQKBQKhUKhaBJq6FIoFAqFQqFQNIlmyovJBdsRubKyUhF5FosFNTU1qKys1GRHJq3rB2hfR63rB2hfR63rB2hfR63rB2hfR6qfvLB2Gmu3OYIauq2oqqoCAMTExHj4SCgUCoVCoVAozqiqqkJwcLDDz3WMK1P4D0ZzczPOnj2LwMBA6HQ64vIqKysRExODU6dOISgoiLg8pdG6foD2ddS6foD2ddS6foD2ddS6foD2daT6yQvDMKiqqkKnTp2g1zuOxKUe3Vbo9XpER0crLjcoKEiTFz6L1vUDtK+j1vUDtK+j1vUDtK+j1vUDtK8j1U8+nHlyWWgyGoVCoVAoFApFk1BDl0KhUCgUCoWiSaih62HMZjNmzZoFs9ns6UMhgtb1A7Svo9b1A7Svo9b1A7Svo9b1A7SvI9XPM9BkNAqFQqFQKBSKJqEeXQqFQqFQKBSKJqGGLoVCoVAoFApFk1BDl0KhUCgUCoWiSaihS6FQKBQKhULRJNTQ9SAffvgh4uPj4evri8GDB2PHjh2ePiSXiDnmOXPmYODAgQgMDERERARuvvlmHDlyRMGjFY87YzJ37lzodDpMnz6d3AHKgBQdz5w5g3vuuQft27eHn58fevfujfz8fAWOVjxi9GtqasLLL7+MhIQE+Pn5ISkpCbNnz3bZO12NbNiwAZMmTUKnTp2g0+nwyy+/ePqQZEfrOmpdP8A7nwti0Lp+gPfpSA1dD/Hf//4XM2bMwKxZs7Br1y707dsXmZmZKCsr8/ShOUTsMf/+++947LHHsG3bNuTm5sJisSAjIwPV1dUKH7kw3BmTnTt34pNPPkGfPn0UOFLpSNHxypUrGD58OIxGI1atWoWDBw/i7bffRmhoqIJHLgyx+s2bNw8fffQRPvjgAxw6dAjz5s3DW2+9hYULFyp85O5TXV2Nvn374sMPP/T0oRBD6zpqXT/A+54LYtG6foAX6shQPMKgQYOYxx57jPu7qamJ6dSpEzNnzhwPHpVz3D3msrIyBgDz+++/c+9169aNAWD3tXDhQtl1cIZU/aqqqpiUlBQmNzeXGTVqFPPkk0/afO7tOv79739nRowY4XS/atFRrH4TJ05kHnjgAZv3br31VmbKlCnc32rRTQwAmJ9//tnmPW/Uwxla11Hr+rG0fi5oTUet68cw6teRenQ9QENDAwoKCjBu3DjuPb1ej3HjxmHr1q0ePDLHyHHMFRUVAICwsDDuvR9//BEAkJeXh3PnzuHkyZPQ6/X4/vvv8dBDD8mogXPc0e+xxx7DxIkTbb7Lx9t1XLZsGQYMGIDbb78dERERSEtLw+LFi222UYOOUvQbNmwY8vLycPToUQDAnj17sGnTJmRnZ3PbqEE3OdCKHs7Quo5a1K/1c0FrOmpdP0D9OlJD1wOUl5ejqakJHTt2tHm/Y8eOOH/+vIeOyjnuHnNzczOmT5+O4cOHo1evXtz7Fy5cgI+PD4YPH47IyEiUl5ejubkZI0eOVLS7ilT9li5dil27dmHOnDkOt/F2HY8fP46PPvoIKSkpyMnJwaOPPopp06bhiy++4LZRg45S9Hvuuedw1113oVu3bjAajUhLS8P06dMxZcoUbhs16CYHWtHDGVrXUWv62XsuaElHresHeIeOPopLpPwheeyxx7B//35s2rTJ5v19+/ahS5cu3MW/Z88eREREtDFW1MipU6fw5JNPIjc3F76+vg6382YdAeuNbMCAAXjzzTcBAGlpadi/fz8+/vhjTJ06FYD36vjdd9/h66+/xjfffIOePXuisLAQ06dPR6dOnbxet9ZoRQ9naF1Hreln77mgJR21rh/gHTpSQ9cDdOjQAQaDARcuXLB5/8KFC4iMjPTQUTnHnWN+/PHHsWLFCmzYsAHR0dE2n+3duxe9e/fm/t6zZ4/N30ohRb+CggKUlZWhX79+3HtNTU3YsGEDPvjgA9TX18NgMHi1jgAQFRWFHj162LzXvXt3bnkKUMc4StHvmWee4by6ANC7d2+UlJRgzpw5nKGrBt3kQCt6OEPrOmpJP0fPBa3oqHX9AO/RkYYueACTyYT+/fsjLy+Pe6+5uRl5eXkYOnSoB4/MMVKOmWEYPP744/j555/x22+/ISEhoc02e/futalUsGfPHo9ULpCiX3p6Ovbt24fCwkLuNWDAAEyZMgWFhYUwGAwAvFtHABg+fHib0jFHjx5FXFwc97cadJSiX01NDfR629ugwWBAc3Mz97cadJMDrejhDK3rqAX9XD0XvF1HresHeKGOiqe/URiGYZilS5cyZrOZ+fzzz5mDBw8yf/vb35iQkBDm/Pnznj40h7g65oULFzJjx47ltn/00UeZ4OBgZv369cy5c+e4V01NDcMw1ox4f39/Zvny5dx3oqOjmffee09Zxa4jVj97tK66oAUdd+zYwfj4+DBvvPEGc+zYMebrr79m/P39mf/85z8Mw6hLR7H6TZ06lencuTOzYsUK5sSJE8xPP/3EdOjQgXn22WcZhlGXbq6oqqpidu/ezezevZsBwLzzzjvM7t27mZKSEq/Swxla11Hr+jGM8+eCFnTUun4M4306UkPXgyxcuJCJjY1lTCYTM2jQIGbbtm2ePiSXODvmWbNmMXFxcdzfcFBe5LPPPmMYhmGOHj3KAGBKSkq472RnZzMhISHMpk2blFLJBjH62aO1oasVHZcvX8706tWLMZvNTLdu3ZhFixZxn6lNRzH6VVZWMk8++SQTGxvL+Pr6MomJicyLL77I1NfXMwyjPt2csW7dOru/t6lTp3qVHs7Quo5a149hnD8XtKCj1vVjGO/TUXf9oCkUCoVCoVAoFE1BY3QpFAqFQqFQKJqEGroUCoVCoVAoFE1CDV0KhUKhUCgUiiahhi6FQqFQKBQKRZNQQ5dCoVAoFAqFokmooUuhUCgUCoVC0STU0KVQKBQKhUKhaBJq6FIoFIpCrF+/HjqdDlevXgUAfP755wgJCSEq87777sPNN99MVAaFQqGoFWroUigUr+O+++6DTqfD3Llzbd7/5ZdfoNPpPHRU4rnzzjtx9OhRjx4Da3y3fr300ksePS4KhUKRAx9PHwCFQqFIwdfXF/PmzcPDDz+M0NBQ2fbb0NAAk8kk2/6c4efnBz8/P0VkueLIkSMICgri/g4ICGizTVNTE3Q6HfR66iOhUCjeAb1bUSgUr2TcuHGIjIzEnDlznG73448/omfPnjCbzYiPj8fbb79t83l8fDxmz56Ne++9F0FBQfjb3/7GhRSsWLECXbt2hb+/P2677TbU1NTgiy++QHx8PEJDQzFt2jQ0NTVx+/rqq68wYMAABAYGIjIyEnfffTfKysocHlvr0IX4+Hi73lWWU6dO4Y477kBISAjCwsIwefJknDx5kvu8qakJM2bMQEhICNq3b49nn30WQru8R0REIDIyknsFBARwx7ds2TL06NEDZrMZpaWlqK+vx9NPP43OnTujXbt2GDx4MNavX99Gt9jYWPj7++OWW27B22+/baOrvZCK6dOnY/To0dzfzc3NmDNnDhISEuDn54e+ffvihx9+4D5nvdF5eXkYMGAA/P39MWzYMBw5csRmv8uXL8fAgQPh6+uLDh064JZbbgEAvPbaa+jVq1ebc5GamoqXX35Z0HmjUCjqhhq6FArFKzEYDHjzzTexcOFCnD592u42BQUFuOOOO3DXXXdh3759+Mc//oGXX34Zn3/+uc128+fPR9++fbF7927OwKmpqcH777+PpUuXYvXq1Vi/fj1uueUWrFy5EitXrsRXX32FTz75xMbwslgsmD17Nvbs2YNffvkFJ0+exH333SdYp507d+LcuXM4d+4cTp8+jSFDhmDkyJHcvjMzMxEYGIiNGzdi8+bNCAgIQFZWFhoaGgAAb7/9Nj7//HMsWbIEmzZtwuXLl/Hzzz+LOKttqampwbx58/Dpp5/iwIEDiIiIwOOPP46tW7di6dKl2Lt3L26//XZkZWXh2LFjAIDt27fjwQcfxOOPP47CwkKMGTMGr7/+umjZc+bMwZdffomPP/4YBw4cwFNPPYV77rkHv//+u812L774It5++23k5+fDx8cHDzzwAPfZr7/+iltuuQUTJkzA7t27kZeXh0GDBgEAHnjgARw6dAg7d+7ktt+9ezf27t2L+++/X8rpolAoaoOhUCgUL2Pq1KnM5MmTGYZhmCFDhjAPPPAAwzAM8/PPPzP829rdd9/NjB8/3ua7zzzzDNOjRw/u77i4OObmm2+22eazzz5jADBFRUXcew8//DDj7+/PVFVVce9lZmYyDz/8sMPj3LlzJwOA+866desYAMyVK1c4OcHBwXa/O23aNCYuLo4pKytjGIZhvvrqK6Zr165Mc3Mzt019fT3j5+fH5OTkMAzDMFFRUcxbb73FfW6xWJjo6GjuXNmDPaZ27drZvMrLy7nzUFhYyG1fUlLCGAwG5syZMzb7SU9PZ55//nmGYRjmz3/+MzNhwgSbz++8804bXfljyPLkk08yo0aNYhiGYerq6hh/f39my5YtNts8+OCDzJ///GebY1+7di33+a+//soAYGpraxmGYZihQ4cyU6ZMcah/dnY28+ijj3J/P/HEE8zo0aMdbk+hULwL6tGlUChezbx58/DFF1/g0KFDbT47dOgQhg8fbvPe8OHDcezYMZuQgwEDBrT5rr+/P5KSkri/O3bsiPj4eJvY1Y4dO9qEJhQUFGDSpEmIjY1FYGAgRo0aBQAoLS0VpdOiRYvw73//G8uWLUN4eDgAYM+ePSgqKkJgYCACAgIQEBCAsLAw1NXVobi4GBUVFTh37hwGDx7M7cfHx8eubvbYuHEjCgsLuRcb92wymdCnTx9uu3379qGpqQldunThjiMgIAC///47iouLAVjPO/84AGDo0KGizkFRURFqamowfvx4GzlffvklJ4eFf3xRUVEAwI1LYWEh0tPTHcp56KGH8O2336Kurg4NDQ345ptvbDzCFArFu6HJaBQKxau54YYbkJmZieeff15UmACfdu3atXnPaDTa/K3T6ey+19zcDACorq5GZmYmMjMz8fXXXyM8PBylpaXIzMzkQguEsG7dOjzxxBP49ttvbQy4a9euoX///vj666/bfIc1ht0hISHBbqkzPz8/mzjha9euwWAwoKCgAAaDwWZbewlsjtDr9W3ihy0Wi40cwBp60LlzZ5vtzGazzd/8cWGPlR0XV8l+kyZNgtlsxs8//wyTyQSLxYLbbrtNsB4UA1BEoAAABBFJREFUCkXdUEOXQqF4PXPnzkVqaiq6du1q83737t2xefNmm/c2b96MLl26tDHS3OXw4cO4dOkS5s6di5iYGABAfn6+qH0UFRXhtttuwwsvvIBbb73V5rN+/frhv//9LyIiImyqI/CJiorC9u3bccMNNwAAGhsbUVBQgH79+knQyD5paWloampCWVkZFz/cmu7du2P79u02723bts3m7/DwcOzfv9/mvcLCQs5o5Se/sZ5xKfTp0wd5eXkOY259fHwwdepUfPbZZzCZTLjrrrtUUwmDQqG4DzV0KRSK19O7d29MmTIF77//vs37M2fOxMCBAzF79mzceeed2Lp1Kz744AP861//kv0YYmNjYTKZsHDhQjzyyCPYv38/Zs+eLfj7tbW1mDRpEtLS0vC3v/0N58+f5z6LjIzElClT8M9//hOTJ0/Ga6+9hujoaJSUlOCnn37Cs88+i+joaDz55JOYO3cuUlJS0K1bN7zzzjtccwq56NKlC6ZMmYJ7770Xb7/9NtLS0nDx4kXk5eWhT58+mDhxIqZNm4bhw4dj/vz5mDx5MnJycrB69Wqb/YwdOxb//Oc/8eWXX2Lo0KH4z3/+g/379yMtLQ0AEBgYiKeffhpPPfUUmpubMWLECFRUVGDz5s0ICgrC1KlTBR3vrFmzkJ6ejqSkJNx1111obGzEypUr8fe//53b5q9//Su6d+8OAG0mRhQKxbuhMboUCkUTvPbaa9xyNUu/fv3w3XffYenSpejVqxdeeeUVvPbaa5JDHJwRHh6Ozz//HN9//z169OiBuXPnYv78+YK/f+HCBRw+fBh5eXno1KkToqKiuBdgjRnesGEDYmNjceutt6J79+548MEHUVdXx3l4Z86cib/85S+YOnUqhg4disDAQK6Ulpx89tlnuPfeezFz5kx07doVN998M3bu3InY2FgAwJAhQ7B48WK899576Nu3L9asWdOmAUVmZiZefvllPPvssxg4cCCqqqpw77332mwze/ZsvPzyy5gzZw66d++OrKws/Prrr0hISBB8rKNHj8b333+PZcuWITU1FWPHjsWOHTtstklJScGwYcPQrVu3NrHFFArFu9ExrYOkKBQKhUKRmc8//xzTp0+X3cMsBwzDICUlBf/3f/+HGTNmePpwKBSKjNDQBQqFQqH8Ybl48SKWLl2K8+fP09q5FIoGoYYuhUKhUP6wREREoEOHDli0aJGsraQpFIo6oKELFAqFQqFQKBRNQpPRKBQKhUKhUCiahBq6FAqFQqFQKBRNQg1dCoVCoVAoFIomoYYuhUKhUCgUCkWTUEOXQqFQKBQKhaJJqKFLoVAoFAqFQtEk1NClUCgUCoVCoWgSauhSKBQKhUKhUDQJNXQpFAqFQqFQKJrk/wGLMmVKuNqMNgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "#Observe the sign change\n",
        "#compared to hone above.\n",
        "#Now look at the frequency response\n",
        "#for pos. and neg. frequencies:\n",
        "\n",
        "\n",
        "# Frequency Response\n",
        "\n",
        "from scipy.signal import freqz\n",
        "import numpy as np\n",
        "from matplotlib.ticker import FuncFormatter, MultipleLocator\n",
        "\n",
        "w, h_response  = freqz(honeremez, whole=True)\n",
        "\n",
        "fig=plt.figure(figsize=(8,6))\n",
        "fig.suptitle('Frequency Response', fontsize=16)\n",
        "plt.subplot(2,1,1)\n",
        "plt.plot(w/np.pi, 20 * np.log10(abs(h_response), where=abs(h_response) > 0), 'b')\n",
        "plt.ylim((-40,10))\n",
        "plt.ylabel('Amplitude (dB)')\n",
        "plt.xlabel('Normalized Frequency')\n",
        "plt.grid()\n",
        "ax = plt.gca()\n",
        "ax.xaxis.set_major_formatter(FuncFormatter(\n",
        "   lambda val,pos: '{:.0g}$\\pi$'.format(val) if val !=0 else '0'\n",
        "))\n",
        "ax.xaxis.set_major_locator(MultipleLocator(base=0.2))\n",
        "plt.subplot(2,1,2)\n",
        "angles = np.angle(h_response)\n",
        "plt.plot(w/np.pi, angles, 'g')\n",
        "plt.ylabel('Angle (radians)')\n",
        "plt.xlabel('Normalized Frequency')\n",
        "ax = plt.gca()\n",
        "ax.xaxis.set_major_formatter(FuncFormatter(\n",
        "   lambda val,pos: '{:.0g}$\\pi$'.format(val) if val !=0 else '0'\n",
        "))\n",
        "ax.xaxis.set_major_locator(MultipleLocator(base=0.2))\n",
        "plt.grid()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AIouLPcZbhFn"
      },
      "source": [
        "Here we can see that we have again only about -30 dB attenuation in the stopband, which is now for the positive frequencies, because of the sign change of our remez filter.  We obtain more practical filters, with more attenuation in the stopband, if we change the corner frequencies to more above 0 and below 0.5 in remez (increasing the transition bandwidth).\n",
        "\n",
        "Also observe the equi-ripple behaviour in the stopband, which is what we expect from remez."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FD5XAZGFbhFn"
      },
      "source": [
        "## Example for the Measurement of the (Instantaneous) Amplitude"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "duKy1W2-bhFn"
      },
      "source": [
        "We can now test our application example of measuring the Amplitude of a sinusoid with our Hilbert transform design. We saw that the lower end for the passband of our design is at normalized frequency of about 0.05. Hence we test a sinusoid of that frequency,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "hide_input": true,
        "id": "6SNKCLrRbhFn",
        "outputId": "c299aac6-58ea-48a6-cb6b-35bb08eecf8e"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/w9X0D2fD0-g\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "%%html\n",
        "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/w9X0D2fD0-g\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "ntf5pY5XbhFo",
        "outputId": "a9eb1b09-944b-454e-e824-a29d611f3c01",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "x = 2*np.sin(np.pi*0.05*np.arange(0, 40))\n",
        "plt.figure()\n",
        "plt.plot(x)\n",
        "plt.grid()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OXLhanCNbhFo"
      },
      "source": [
        "Now we can filter it with our filter which passes only positive frequencies “hone”, an creates a complex valued signal xhone:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "DFeyxP4EbhFo",
        "outputId": "043b3e42-3914-4d07-9d21-57dc7863fd12",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "xhone = sp.convolve(x, hone)\n",
        "plt.figure()\n",
        "plt.plot(np.real(xhone))\n",
        "plt.plot(np.imag(xhone),'r')\n",
        "plt.grid()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rM9vIZoUbhFp"
      },
      "source": [
        "Here we can see that we get indeed a 90 degree phase shifted version, the red curve, about between sample 15 and 45.\n",
        "\n",
        "Now we can compute the magnitude of this complex signal “xhone” to obtain the amplitude of our sinusoidal signal,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "zL5OHNqpbhFp",
        "outputId": "bfdc6b1f-5374-433f-add4-f796606c9b6b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure()\n",
        "plt.plot(np.real(xhone))\n",
        "plt.plot(np.imag(xhone),'r')\n",
        "plt.plot(np.abs(xhone))\n",
        "plt.grid()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DUDKLJ7zbhFp"
      },
      "source": [
        "We see that between about sample 15 and 45 we obtain the **amplitude** of our sinusoidal signal with about **10% accuracy**, which roughly corresponds to the -20dB attenuation (corresponding to an attenuation factor of 0.1) that our filter “hone” provides. This also hints at the fact that we can improve the magnitude estimation by having a filter with a **higher attenuation** at negative frequencies.\n",
        "\n",
        "Also observe that this only works for sinusoids inside our\n",
        "passband!"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VJPutdeNbhFp"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.5"
    },
    "livereveal": {
      "rise": {
        "height": "90%",
        "width": "90%"
      },
      "scroll": true,
      "theme": "sky",
      "transition": "zoom"
    },
    "colab": {
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}