{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Quasi-bound states in the continuum (qBICs) in symmetry-breaking\n",
        "\n",
        "dielectric metasurfaces\n",
        "\n",
        "Dielectric metasurfaces, composed of subwavelength nanostructures, have\n",
        "emerged as a transformative platform in nanophotonics due to their\n",
        "ability to precisely manipulate light while maintaining low optical\n",
        "losses. Within this domain, quasi-bound states in the continuum (qBICs)\n",
        "have garnered significant attention for their ability to support\n",
        "ultrasharp resonances with high quality factors. These qBICs arise from\n",
        "symmetry-breaking in the metasurface design, converting otherwise\n",
        "non-radiative modes into accessible, yet highly localized, resonant\n",
        "states. By carefully engineering the symmetry properties of these\n",
        "structures, it is possible to achieve angularly tunable optical\n",
        "responses, opening new avenues for advanced photonic devices such as\n",
        "spectral filters, sensors, and imaging systems.\n",
        "\n",
        "In this notebook, we investigate the angular response of\n",
        "symmetry-breaking dielectric metasurfaces supporting qBICs, as described\n",
        "in `ACS Photonics 2022, 9(11), 3642–3648.` [DOI:\n",
        "10.1021/acsphotonics.2c01069](https://doi.org/10.1021/acsphotonics.2c01069).\n",
        "Through simulations of the metasurface transmission spectra at varying\n",
        "incident angles, we analyze the impact of these angles on the spectral\n",
        "shifts of the qBICs.\n",
        "\n",
        "<img src=\"img/metasurface_qbic.png\" width=\"400\" alt=\"Schematic of the metasurface\">\n",
        "\n",
        "Tidy3D offers two approaches for simulating oblique plane waves in\n",
        "periodic structures:\n",
        "\n",
        "1.  Fixed in-plane $k$-vector with Bloch boundaries.\n",
        "2.  Fixed angle mode with periodic boundaries.\n",
        "\n",
        "While both methods yield identical results at the central source\n",
        "frequency, their behavior can differ significantly for frequencies away\n",
        "from the central one. Understanding these differences is crucial for an\n",
        "accurate simulation. More details are introduced in this dedicated\n",
        "[tutorial](https://www.flexcompute.com/tidy3d/examples/notebooks/BroadbandPlaneWaveWithConstantObliqueIncidentAngle/).\n",
        "In this notebook we will use the second approach as it is more\n",
        "cost-effective and easier to set up."
      ],
      "id": "f836b17f-257b-4082-919f-66bed3a8bd34"
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import tidy3d as td\n",
        "import tidy3d.web as web\n",
        "from tidy3d.plugins.dispersion import FastDispersionFitter"
      ],
      "id": "10e6fbfb"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Simulation Setup\n",
        "\n",
        "### Basic Parameters\n",
        "\n",
        "Define the simulation wavelength range from 700 nm to 900 nm."
      ],
      "id": "c9e52c04-e817-41cd-a8e6-63b775a1a737"
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [],
      "source": [
        "lda0 = 0.8  # central wavelength\n",
        "freq0 = td.C_0 / lda0  # central frequency\n",
        "ldas = np.linspace(0.7, 0.9, 201)  # wavelength range\n",
        "freqs = td.C_0 / ldas  # frequency range\n",
        "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))  # width of the source frequency range"
      ],
      "id": "c1d69821"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The metasurface consists of two elliptical amorphous silicon nanodisks.\n",
        "The geometric parameters of the metasurface are defined by the\n",
        "dimensions and orientation of its constituent elliptical nanodisks. Each\n",
        "nanodisk is characterized by its major axis diameter and minor axis\n",
        "diameter. The thickness of the nanodisks determines their vertical\n",
        "dimension. The rotation angle specifies the orientation of each nanodisk\n",
        "relative to a reference axis. Additionally, the periodicity in the x and\n",
        "y directions governs the size of the unit cell as well as our simulation\n",
        "domain. These parameters collectively determine the optical and physical\n",
        "properties of the metasurface. In this notebook, we use the parameters\n",
        "from the [paper](https://doi.org/10.1021/acsphotonics.2c01069)."
      ],
      "id": "a76273da-dccb-4337-83bf-3d6ff31de77f"
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "h = 0.126  # height of the silicon nanodisk\n",
        "dx = 0.226  # major axis diameter of the nanodisk\n",
        "dy = 0.152  # minor axis diameter\n",
        "px = 0.51  # unit cell size in the x direction\n",
        "py = 0.265  # unit cell size in the y direction\n",
        "alpha = np.deg2rad(38)  # rotation angle of the nanodisks"
      ],
      "id": "70a0f467"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Define Materials\n",
        "\n",
        "Pyrex, which has a constant refractive index of 1.47 in the visible\n",
        "range, is used as the substrate. For amorphous silicon, we aim to use\n",
        "the same refractive index as the original paper. We do so by\n",
        "discretizing the refractive index plot from the paper, saving the index\n",
        "data in a .txt file, and using\n",
        "[FastDispersionFitter](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.dispersion.FastDispersionFitter.html#tidy3d.plugins.dispersion.FastDispersionFitter)\n",
        "to fit it. As the plot shows, the fit of the dispersive refractive index\n",
        "is very good.\n",
        "\n",
        "Alternatively, one can use the refractive index data from\n",
        "[refractiveindex.info](https://refractiveindex.info) by conveniently\n",
        "using the\n",
        "[from_url](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.dispersion.DispersionFitter.html#tidy3d.plugins.dispersion.DispersionFitter.from_url)\n",
        "method from the\n",
        "[FastDispersionFitter](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.dispersion.FastDispersionFitter.html#tidy3d.plugins.dispersion.FastDispersionFitter).\n",
        "Tidy3D’s [material\n",
        "library](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/material_library.html)\n",
        "also contains amorphous silicon however the supported wavelength range\n",
        "is outside of the wavelength of interest in this case."
      ],
      "id": "54486fb1-ee8e-4fab-b82e-1b6dca0705c2"
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
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          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
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        },
        {
          "output_type": "display_data",
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          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:12:48 UTC </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Unable to fit with weighted RMS error under               </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'tolerance_rms'</span><span style=\"color: #800000; text-decoration-color: #800000\"> of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-05</span><span style=\"color: #800000; text-decoration-color: #800000\">                                           </span>\n",
              "</pre>"
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        {
          "output_type": "display_data",
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BWLduXYXjrrjiCvr06QPAY489xo8//ljqeEJCAtdffz3u7u4VXqPX2T/Yr1+/nm+++abU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VyT3HRHkiRJkiRJkmrDwFKSJEmSJElSZBhYSpIkSZIkSYoMA0tJkiRJkiRJkWFgKUmSJEmSJCky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\nu2q//vrr5ObmMnjwYPbee+9q27344ovk5+czfPjwKvv0k08+YfHixXTt2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          }
        }
      ],
      "source": [
        "n_pyrex = 1.47  # refractive index of the Pyrex substrate\n",
        "pyrex = td.Medium(permittivity=n_pyrex**2)\n",
        "\n",
        "# create a fitter from the refractive index file\n",
        "fitter = FastDispersionFitter.from_file(\"misc/amorphous_silicon_from_paper.txt\")\n",
        "\n",
        "# alternatively one can create the fitter object from a refractiveindex.io url\n",
        "# url = \"https://refractiveindex.info/tmp/database/data-nk/main/Si/Pierce.txt\"\n",
        "# fitter = FastDispersionFitter.from_url(url, delimiter=\"\\t\")\n",
        "\n",
        "# fit the data\n",
        "silicon, error = fitter.fit(max_num_poles=2)\n",
        "ax = fitter.plot(silicon)\n",
        "plt.show()"
      ],
      "id": "4c6c19d3"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Create the Nanodisk Structures\n",
        "\n",
        "To create the rotated elliptical nanodisk structures, we first define a\n",
        "function that takes the geometric parameters of the nanodisk and return\n",
        "the vertices of the ellipse. This can be done by noting that the\n",
        "boundaries of an ellipse can be described by\n",
        "\n",
        "$$X'(\\theta) = \\frac{b}{2} \\cos(\\theta),$$\n",
        "\n",
        "$$Y'(\\theta) = \\frac{a}{2} \\sin(\\theta),$$\n",
        "\n",
        "where $\\theta \\in [0, 2\\pi)$, $a$ and $b$ are the major and minor axis\n",
        "diameters. To rotate the ellipse by an angle $\\alpha$ counterclockwise,\n",
        "apply the rotation transformation:\n",
        "\n",
        "$$\\begin{pmatrix} \n",
        "X \\\\ \n",
        "Y \n",
        "\\end{pmatrix} \n",
        "=\n",
        "\\begin{pmatrix} \n",
        "x_0 \\\\ \n",
        "y_0 \n",
        "\\end{pmatrix} \n",
        "+ \n",
        "\\begin{pmatrix} \n",
        "\\cos(\\alpha) & -\\sin(\\alpha) \\\\ \n",
        "\\sin(\\alpha) & \\cos(\\alpha) \n",
        "\\end{pmatrix} \n",
        "\\begin{pmatrix} \n",
        "X'(\\theta) \\\\ \n",
        "Y'(\\theta) \n",
        "\\end{pmatrix}.$$\n",
        "\n",
        "Substituting $X'(\\theta)$ and $Y'(\\theta)$:\n",
        "\n",
        "$$X(\\theta) = x_0 + \\frac{b}{2} \\cos(\\theta) \\cos(\\alpha) - \\frac{a}{2} \\sin(\\theta) \\sin(\\alpha),$$\n",
        "\n",
        "$$Y(\\theta) = y_0 + \\frac{b}{2} \\cos(\\theta) \\sin(\\alpha) + \\frac{a}{2} \\sin(\\theta) \\cos(\\alpha).$$"
      ],
      "id": "79193ce8-19b6-4e5d-802d-9467cacaa7fe"
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [],
      "source": [
        "def ellipse_vertices(x0, y0, dx, dy, n, alpha):\n",
        "    \"\"\"\n",
        "    Generate N points along the boundary of a rotated ellipse.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    x0, y0 : float\n",
        "        The coordinates of the center of the ellipse.\n",
        "    dx : float\n",
        "        The length of the ellipse's major axis.\n",
        "    dy : float\n",
        "        The length of the ellipse's minor axis.\n",
        "    n : int\n",
        "        The number of points to sample on the ellipse boundary.\n",
        "    alpha : float\n",
        "        The rotation angle in radians. alpha=0 means the major axis is aligned\n",
        "        with the y-axis.\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    vertices : list of tuples\n",
        "        A list of (x, y) coordinates on the ellipse boundary.\n",
        "    \"\"\"\n",
        "\n",
        "    vertices = []\n",
        "    dtheta = 2.0 * np.pi / n\n",
        "\n",
        "    for i in range(n):\n",
        "        theta = i * dtheta\n",
        "        Xp = (dy / 2.0) * np.cos(theta)\n",
        "        Yp = (dx / 2.0) * np.sin(theta)\n",
        "\n",
        "        # Rotate by alpha:\n",
        "        x = x0 + Xp * np.cos(alpha) - Yp * np.sin(alpha)\n",
        "        y = y0 + Xp * np.sin(alpha) + Yp * np.cos(alpha)\n",
        "        vertices.append((x, y))\n",
        "\n",
        "    return vertices"
      ],
      "id": "3d349b87"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "With the above function defined, we can create each nanodisk structure\n",
        "as\n",
        "[PolySlab](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PolySlab.html)."
      ],
      "id": "eb697d8e-dfe5-467f-8106-d10893f11e6b"
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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pxhtv1OjRo2kpCyDqlZaWatasWXrwwQerXRu4msUo5vh0eTsky3Dw\nftYQVXQdL96QrZKN2SrPLqq2TSAQ0OTJk3X55Zfr1FNP5W8XANsRWKJBI7AEEC3WrVun5557Tv/+\n97+1c+fOqg8akqdlvLwVIWXAY0+RqBNmMKTiDdkqXJWh8j2FVR7r06ePbrjhBl1wwQVyuVw2VQgA\nB5eXl6dnn31WjzzyiLZv317lMU+bBMX0TZe7ZTzhVSNTnltktbws311Y7fFu3brp8ssv10UXXcQY\nzQBsQ2CJBo3AEoCdioqKNHv2bM2YMUOff/55tcfdqbHydW0uX/skxvhqAkzTVOm2vSpclaHS7fuq\nPNajRw89+uijOv30022qDgAOCAaDevHFF/XXv/5VmZmZBx4wJN9xKQr0TZc7hbENm4LyfcUqWZ+t\nop+yqo3R7Ha7NWHCBF1++eUaNWqUnE4mVQJQfwgs0aARWAKww8qVKzVjxgzNnDlTubm5VR4zfC75\nOzeTv1tzuZIPP4QGGq+yrAIVrNqhkg3ZUqVPRuPHj9fDDz+s4447zr7iADRpixcv1rXXXqsVK1ZY\n6wyXQ/7uLRTonSZnHEOVNEWmaaosI09FP2apeMMeKVj1sr5t27a67LLLdOmll6pt27Y2VQmgKSGw\nRINGYAmgvuzdu1evvPKKZsyYoW+++aba457W8fJ3ayFv+yQZTocNFSIale8rVv7XW1WyPtta53a7\ndd111+nWW29lggMA9WbLli266aab9Oqrrx5Y6TAU6J2mmONbyuFj2AqEhUrKVfzzHhX9kFltqBPD\nMDR69GhdfvnlOvvss+XxMMwNgLpBYIkGjcASQF3btGmTHn30Uc2YMUMFBQVVHnPEeOTv2lz+rs2Y\n4RuHVZqxT3lfbq4yVlhqaqruu+8+XXLJJXI4CLkB1I3CwkJNmzZN06ZNU1HRgclWvO0SFTuwHTN+\n47DKsgpU9GOmin/eI7M0WOWx9PR0/fGPf9RVV12lxMREewoE0GgRWKJBI7AEUFdWrFihBx98UK+/\n/rqCwUof0B2GvO0S5e/WQp7WCcyYihozQ6aK12Yp/+utChWVW+v79++vxx57TIMGDbKxOgCNjWma\n+u9//6sbb7xRW7dutdY7k/yKG9hW3jaJ9hWHBscsC6p4Y7aKfshS2c68Ko/Fxsbq8ssv15/+9Ce1\na9fOpgoBNDYElmjQCCwBRJJpmvrwww/14IMP6rPPPqvymCPgVqBXmnxdm8sZYAId1F6opFwFK3ao\n8PudUujAx6bf/OY3+uc//0krFQDH7Oeff9Zll12mRYsWWesMj1OxA1rL370FQ5fgmJTnFqloTaaK\nfsyUWRay1judTk2ePFl/+ctfdMIJJ9hYIYDGgMASDRqBJYBIKCkp0axZs/Twww9r9erVVR5zJfsV\n6JMu33EpXOAhospzi5T31RaVbsm11rVp00Yvv/yyhg0bZl9hABos0zT14osvaurUqQeGMTEkf/cW\nij2xtRx+vnBD5IRKylX0Q6YKv9upUGFZlcdGjBihv/zlLxozZowMg94oAI4egSUaNAJLAMciNzdX\nTz/9tB5//HFlZGRUeczTKl6BPunytEnggzbqVMnWXOUt3qTgvhJJ4QkNbrrpJt19991MZgCgxrKz\ns3XllVdq9uzZ1jp3WpziBreXOyVgY2Vo7MxgSMU/71Hhtxkqzy6q8ljPnj31l7/8Rb/61a/k9TID\nPYCaI7BEg0ZgCaA2tmzZokceeUQzZsxQfn7+gQcMydcpRYG+6XI3i7GvQDQ5odKg8r7crOKfsqx1\n/fv318yZM9W1a1cbKwPQEMyfP18XX3yxtm/fHl7hMBR7YisF+rZkrGXUG9M0Vbp1rwq/zVDp9n1V\nHktPT9e1116rKVOmMPQJgBohsESDRmAJ4Ghs375d9957r2bMmKHy8gOTnhhuh/zdWijQO03OOL79\nh32KN+zRvoUbZZaEJ3ry+/165JFHdOWVV9LSF0A1JSUluvXWW/Xwww9b65wJPiWM7CR381gbK0NT\nV5ZVoMJvM1S8fo9UKSFISEjQX/7yF1177bWKi4uzr0AAUY/AEg0agSWAmsjKytIDDzyg6dOnq7i4\n2FrvCLgV6J0mf/cWcnhdNlYIHBDML9G+zzaodMeB1injx4/XjBkz1Lx5cxsrAxBN1qxZowsvvFCr\nVq2y1vm7t1DcwLYy3E4bKwMOCOaVqPC7ndUm6GnWrJluueUWXX311fL7/TZWCCBaEViiQSOwBHA4\nubm5evjhh/Xoo49W6frtiPUotn8r+To3YyIdRCXTNFX47U7lf73Vmkk8LS1NL7/8skaNGmVzdQDs\n9vTTT+u6666zvoQzfC7FD+sgX/tkmysDDi5UUq7C73ep8NsMmaVBa32rVq1022236bLLLmPcZgBV\nEFiiQSOwBHAw+fn5+uc//6lp06YpNzfXWu8IuBXTr6X83VsQVKJBKNtdoL3zf1YwNxxKOJ1OTZ8+\nXVdeeaXNlQGwQ3l5ua677jo98cQT1jpP6wTFD+8oZwxhD6JfqLhcBasyVPj9Tqn8QIvLDh066K67\n7tKvf/1rOZ20EAZAYIkGjsASQGXFxcV6+umndf/99yszM9Nab3hdijk+XYGeqXSTQ4NjlgWVt2SL\nitYcOKdvuOEGPfDAA3I4CN6BpiI/P18XXHCB5s6dG17hMBR7chsFeqcxxi0anGBhmQr/t0OFa3ZZ\nPQkkqXv37rrnnns0ceJE/sYBTRyBJRo0AksAklRWVqYXXnhBf/vb37Rt2zZrveF2KNAnXYE+aXJ4\nGKMSDVvhml3KW7zJmrxg0qRJeumllxQIBGytC0Dd2759u8aNG6eVK1dKkgyPU4mju8jTMt7ewoBj\nFMwvUcE321X0U1aVyXn69eune++9V2eeeSaBPNBEEViiQSOwBJo20zT1yiuv6I477tD69esPPOBy\nKNAzVTHHp8vhc9tXIBBhJVtztfeTddbEBSeddJLmzJmj1NRUmysDUFdWrlypcePGafv27ZIkZ7xX\niWO6ypXERCVoPMr3Fqtg+TYV/7ynyvpTTz1VDzzwgIYMGWJTZQDsQmCJBo3AEmi6vvnmG/3xj3/U\nl19+eWClw5C/RwvF9GspZ4CxvNA4le0pVO6HPymUXypJateund5//3316NHD5soARNrcuXN1/vnn\nq6CgQJLkTo1V4ugucvj5Mg6NU3l2ofKXb1PJxpwq6y+44AJNmzZNbdq0sakyAPUt0nkPg0wAAOpU\nZmamrrjiCg0YMOBAWGlIvm7N1eyCvoof1J6wEo2aOyWg5P/rKVezGEnS5s2bdeqpp2revHk2VwYg\nkp588kmNHz/eCiu9HZOVNK47YSUaNVdyQIlndFHyxF7ytEmw1r/66qvq1q2b7r33XhUXF9tYIYCG\nisASAFAnysrK9Nhjj6lLly6aMWOGKhr0e1rFK+Xc3koY1lHOOK/NVQL1wxnjUfL47vK2D3/TvHfv\nXp155pl64YUXbK4MwLEKhUL685//rGuuuUahUHj4h8DxLZUw6jgZLi630DS4m8coaWw3JZ7VTc5E\nnySpsLBQt99+u3r06KG33npLdO4EcDToEo56RZdwoGmYN2+err32Wq1Zs8Za54jzKm5gW3nbJzEY\nO5osM2Qqf8kWFX6301r33HPP6bLLLrOxKgC1ZZqmpk6dqieffDK8wmEofkh7+bu1sLcwwEZmMKSi\nNZnKX75NZmnQWj9q1Cg99thjDIkCNFJ0CQcARK2NGzdq4sSJOv300w+ElS6HYga0VrPJfeTrkExY\niSbNcBiKO7Wd4ga1s9ZdfvnlmjVrlo1VAagN0zR1ww03WGGl4XYo8cyuhJVo8gynQ4HeaWp2QV/5\nuzW31s+bN099+vTRn/70J+Xm5tpXIIAGgcASAHDMCgoKdPvtt6t79+566623rPXeTslqNrmPYk9o\nRbc4oJJArzTFDWkvKRx6XHTRRZo9e7a9RQE4KnfccYcefvjh8B2XQ4ljusrbOuHwTwKaEIffrfhh\nHZU8sZfcqbGSpGAwqMcee0ydO3fWv/71LwWDwSPsBUBTxdUjAKDWTNOsMqh6SUmJpPAA7Elnd1fi\nqM6MUwkcQqBHqmIHtpUUvoC74IIL9N5779lcFYCauO+++3TvvfeG7zgNJY7uIk/LeHuLAqKUu3mM\nkib0UPxpneQIhCeh2r17t6688kqddNJJ+uKLL2yuEEA0IrAEANTK+vXrNWrUKP3qV7/Stm3bJEmG\n16W4we2VPKkXF25ADcT0SVfsSa0lSeXl5Zo0aZI++eQTm6sCcDiPPPKIbr311vAdh6HE0zvTshI4\nAsMw5O/STCnn91Xg+HTJER4iaMWKFRo8eLB+97vfKScnx+YqAUQTAksAwFEJBoP6xz/+od69e+vT\nTz8NrzQkf89UNbugrwI9U2U4GKcSqKmYfq0Uc0IrSVJpaakmTJigzz//3OaqABzMU089pT//+c/h\nO4aUMPI4edsxiSRQUw6PU3Ent1XK5D7ytE201j///PPq2bOn3n77bdtqAxBdCCwBADW2evVqDRo0\nSNdff72KiookSe4WMUqe1Fvxg9vL4XPZXCHQMMWc2EqBPumSpKKiIo0bN05fffWVzVUBqOz555/X\n73//e+t+/Gmd5OuYbGNFQMPlSvAp6cyuSjyzqxyxHklSRkaGzjnnHJ1//vnKzMy0uUIAdiOwBAAc\nUWlpqf72t7+pX79+Wrp0aXily6HYgW2VNKGn3CkBewsEGjjDMBR7Shv5e6ZKkvLz8zVmzBitXLnS\n3sIASJJee+01XX755db9+GEd5e/czMaKgMbB2zZRKZP7yN8r1Vr32muvqUePHpo5c6ZM07SxOgB2\nMkzeAVCPcnJylJwc/iY6OztbSUl0oQGi3fLly/W73/1O3377rbXO0zJeccM6yBXvs7EyoPExTVN5\nCzeq6McsSVK7du20fPlyNWtGMALYZcWKFRo0aJCKi4slSXGD2yvQM/UIzwJwtEoz8rRv4QYFc4ut\ndWeddZaeeuoptWnTxsbKANREpPMeWlgCAA6qqKhIN910k04++WQrrDQ8TsUN7aDEcd0IK4E6YBiG\n4oZ0kLdD+APe5s2bNXnyZJWXl9tcGdA0ZWVl6ZxzzrHCytgBrQkrgTriSY9TyqTe4Ul59g+HPnfu\nXPXs2VPPPPOMQqGQvQUCqFcElgCAahYtWqS+fftq2rRp1odDT9tEpZzXW4HuLWQYTKoD1BXDYSj+\ntE5yJfslSZ999pluuOEGm6sCmp6ysjJNnjxZW7ZskSR5OyYr0K+lzVUBjZvhciju5LZKPqeXXPuH\nHMrLy9NVV12lkSNH6ueff7a5QgD1hcASAGDJy8vTH/7wBw0dOlTr1q2TJBk+l+JHdlLimC5yxnpt\nrhBoGhxupxLO6CLD65QkPfroo3r55ZdtrgpoWm644QYtWLBAkuRKDihheEe+sAPqibt5jJLP6amY\nAa0lR/j/3YIFC9SnTx89/PDDCgaDNlcIoK4xhiXqFWNYAtFrwYIFuvjii62WJJLk7ZSi+EHt5PC7\nbawMaLpKtuYq94OfJFPy+XxavHix+vfvb3dZQKP30ksv6eKLL5YkGV6Xkif2ZCgUwCblOYXat2Cj\nyjLzrXUnnXSS/vOf/6hz5842VgagMsawBABEVFlZmW699VaNGDHCCisdAbcSRndR4qjjCCsBG3nb\nJCr2pPBEA8XFxTrnnHOUmZlpc1VA47Z8+XJdeeWV4TuGlDDqOMJKwEaupICSJvRQ3KntJFc4wvj6\n66/Vr18//fvf/2YmcaCRIrAEgCZsw4YNGjJkiO677z7rw56va3OlTO4jX3taQAPRINA3Xd5OKZKk\nrVu3avLkySorK7O5KqBx2rVrl8455xyVlJRIkmJPbitv6wSbqwJgOAwFeqcp5bzecreMkyQVFBTo\nkksu0YUXXqjc3Fx7CwQQcQSWANBE/ec//9Hxxx+vpUuXSgrPAJ5w+nFKGN5RDq/L5uoAVDAMQwnD\nOliTD3z++ee6/vrrba4KaHwqJtnZtm2bJMl3XIoCfdJsrgpAZa54n5LO6q7Yk1pbM4m/+uqrOv74\n4/Xll1/aWxyAiCKwBIAmZt++ffrtb3+r3/72t8rLy5MkudPilHJub/k6pthcHYCDMdxOJZ7RWcb+\nLxP++c9/6o033rC5KqBxueOOO7Rw4UJJkisloPihHZhkB4hChsNQTL9WSp7QU8748ISQmzdv1tCh\nQ3XPPfcwIQ/QSDDpDuoVk+4A9lqyZIkuvPBCbdy4MbzCkGL6t1ZMv5YyHFyUAdGuZNte5c79UZLU\nvHlzrV69Ws2bN7e5KqDh+/rrrzVw4ECFQiEZXpdSJvWSM85rd1kAjiBUWq68xZtVvG63tW7IkCH6\nz3/+o7Zt29pYGdD0MOkOAOCoBYNB3XfffRo8eLAVVjrivEoa30Ox/VsRVgINhLd1gtVFNSsrS1On\nTrW5IqDhKy4u1qWXXqpQKCRJih/cnrASaCAcHpcSRnRS/IhOMtzheGPRokXq27cvPRGABo7AEgAa\nuW3btmnUqFG69dZbrS4y3k4pSpnUS560OJurA3C0Yge0kTMhPGPxf//7X82ePdvmioCG7Z577tGa\nNWskSd4OSfJ2Sra5IgBHy9+5mZLP7S13ixhJUm5urs477zxdfvnlKigosLk6ALVBYAkAjdhbb72l\nPn36aMGCBZIkw+1Q/GkdlTCyExPrAA2U4XIofnhH6/7vf/977d69+zDPAHAoy5Yt09///ndJkuF1\nKW4w41YCDZUr3qek8T0U06+lte65557TCSecoBUrVthYGYDaILAEgEaotLRUf/jDHzRx4kTl5ORI\nklzNY5Q8qbf8XZpzMQY0cJ60OKtreGZmJl3DgVooKSmp0hU8bnA7OQNum6sCcCwMp0OxJ7VR0tnd\n5YjxSJLWrl2rU045RU888YSYwgNoOAgsAaCR2bFjh4YPH67p06db6wLHpyt5Qg+59ncjBdDwxZ7Y\n2uoa/uqrr+rNN9+0uSKgYbnnnnu0evVqSZK3fZJ8nVJsrghApHhaxivl3N7ydghP+lFWVqapU6fq\n4osvVmFhoc3VAagJAksAaEQWL16s/v3766uvvpIkGT6XEs/qpriT28pw8pYPNCaG26n4YQe6hl99\n9dXas2ePjRUBDcfy5curdgUf0p7eB0Aj4/C5lHB6Z8UNaS/tn2Dy5Zdf1qBBg7Rp0yZbawNwZFy9\nAkAjYJqmnnjiCZ122mnauXOnJMnVIkYpk3rJ2zrB5uoA1BVPepwCvQ90Df/jH/9oc0VA9KvoCl4x\nEV3coHZyBjw2VwWgLhiGoUCPVCWP7yFHTHjIh5UrV6p///765JNPbK4OwOEQWAJAA1dUVKRLLrlE\nU6dOVXl5uSTJ3625ks/uIWes1+bqANS12AGt5YwP/1+fNWuW3nvvPZsrAqLbAw88oO+//17S/q7g\nx9EVHGjs3KmxSp7YW+70OElSdna2xowZo7///e+MawlEKcPkfyfqUU5OjpKTkyWF/0gkJSXZXBHQ\nsG3evFkTJ048MPOhw1DcoPYK9Ghhb2EA6lVpRp5y5qyRJHXr1k3fffedXC6XzVUB0WfHjh067rjj\nVFRUJMPjVMrkPnLG0LoSaCrMYEj5S7eq8Lud1rpJkybphRdeUFxcnI2VAQ1fpPMeWlgCQAM1b948\n9e/f3worHQG3ksZ3J6wEmiBPepzVSuzHH3/U888/b3NFQHS66667VFRUJEmK6d+KsBJoYgynQ3Gn\ntlP8iE6SKxyHzJ49W6eccorWrl1rc3UAKiOwBIAGxjRNPfjggxo9erQ1wYY7LU7Jk3rJk8o3w0BT\nFXtSG2tSgTvvvFP5+fk2VwRElzVr1ui5556TJDnjvAr0TLW5IgB28XdupuQJPeSMCw+psmbNGg0Y\nMEBz5syxuTIAFQgsAaAByc/P1/nnn68bb7xRoVBIkuTvlaqkcd2YMABo4pxxXgV6hQOYnTt36h//\n+IfNFQHR5eabb7b+dsae1EaGk0shoClzN4tR8sRe8uyfoHLfvn2aMGGC7rzzTuu9AoB9+CsNAA3E\nunXrdMopp+j1118Pr3Aaij+to+IHteeiC4AkKaZfKxkepyRp2rRp2rVrl80VAdHh888/17vvvitJ\ncjWPkbdTss0VAYgGDp9LiWd2VeD4lta6e+65R2effbZycnJsrAwAV7gA0AB8/vnnOumkk7R69WpJ\nkiPWo+QJPeXv0tzmygBEE4fPpZgTWkmSCgoKdPfdd9tcEWA/0zR1ww03WPfjTm4jwzBsrAhANDEc\nhuJObqOE0zvLcIcjkvfff18DBw7Uhg0bbK4OaLoILAEgys2cOVOnn366cnNzJUmeVvFKmdRL7uYx\n9hYGICoFeqbKERseIuLZZ5/VTz/9ZHNFgL1ef/11LVu2TJLkaZsoT6sEmysCEI18HZOVfE5PORN8\nkqSffvpJp5xyipYuXWpzZUDTRGAJAFHKNE3de++9+s1vfqOysjJJkr9HCyWO7SaHz21zdQCileFy\nKHZAa0lSMBjULbfcYnNFgH1KS0sP/B8wwq0rAeBQXEkBJZ/TU56W8ZKkrKwsDR8+XG+99ZbNlQFN\nD4ElAEShsrIy/e53v9Ptt99urYsd2FZxg9vLcNCNDcDh+To3kyslIEl666239OWXX9pcEWCPZ555\nxurS6evSXK7kgM0VAYh2Dq9LiWO7ytelmSSpuLhYkyZN0iOPPCLTNG2uDmg6CCwBIMrs3btXY8eO\n1QsvvBBe4TSUcHpnxfRJZ8wtADViGIZiT2lr3b/55pttrAawR0FBge65557wHZdDsSe2srcgAA2G\n4XQofnhHxZwY7rFgmqb+/Oc/649//KOCwaDN1QFNA4ElAESRLVu2aNCgQZo3b54kyfC5lHR2d/k6\nMpspgKPjbZ0gT6twl7ZFixZZY/gBTcVLL72k3bt3S5ICvVLljPXaXBGAhsQwDMX2b6X40zpK+3s4\nPfHEEzrnnHNUUFBgc3VA40dgCQBRYsWKFTr55JOtmcCdCT4l/19PeVLjbK4MQEMVOL6ltfzII4/Y\nWAlQv0KhkB599NHwHYehQO80W+sB0HD5uzRX0lndZHickqR3331Xw4YNU0ZGhs2VAY0bgSUARIH3\n3ntPQ4cO1c6dOyVJ7rQ4Jf9fT7n2z1IIALXhaRUvV7JfUnim5G3bttlcEVA/PvjgA61du1aS5Dsu\nRc6Ax+aKADRknpbxSv6/nnLEhVtqf/PNNzrllFOshgYAIo/AEgBsNn36dE2YMMHqWuI7LkVJ47rJ\n4XPZXBmAhs4wDrQsKy8v1xNPPGFzRUD9qNyiONCH1pUAjp0ryR9uUNA8RtKBoZw+/fRTmysDGicC\nSwCwSSgU0g033KA//OEPCoVCkqSYfi0VP6KTDCdvzwAiw3dcMxn7vwB55plnlJ+fb3NFQN1atWqV\n5s+fL0lyt4yXOyXG5ooANBbOgFvJZ3eXt32SpPBkmaNHj9a///1vmysDGh+uiAHABqWlpbrwwgv1\n0EMPhVcYUtzQDoo9qQ0zgQOIKMPlUKBnqiQpNzeXiyo0etbYlZJiaF0JIMIMt1MJp3dWoNeBHgyX\nXHKJ7rvvPpmmaXN1QONBYAkA9ayoqEgTJ07Uf//7X0mS4XYo8cyuCnRvYXNlABorf49Ua4bTxx57\nzGrVDTQ2O3fu1KxZsySFJ6/ztE20tyAAjZLhMBQ3qJ3iTm1nrbv11lt1yy23EFoCEUJgCQD1KC8v\nT2eddZbmzp0rSXL4XUqa0EPeNon2FgagUXMG3PJ1biZJWrdunfUeBDQ2Tz31lEpLSyVJgd5p9FoA\nUKcCvdOUcHpn60vBv//977rmmmv4YhCIAAJLAKgnOTk5Ov300/XZZ59JkhwxHiWN78HYWgDqRcXk\nO1LVCUmAxqK4uFhPPfWUJMnwOuXv0szmigA0Bb6OyUoc00VyheOV6dOn69JLL1V5ebnNlQENG4El\nANSDXbt2afjw4Vq6dKkkyRnvVfKEHnIl+m2uDEBT4U4JyNMqXpL02WefaeXKlfYWBETYzJkzlZWV\nJUnyd28hw+20uSIATYW3TaKSxnaV4Q5HLC+99JLOP/98lZSU2FwZ0HARWAJAHdu6dauGDh2qb7/9\nVpLkTPIraXwPOeO8NlcGoKmp3MryX//6l42VAJH37LPPhhcchjXRFADUF096vJLO7i7D65Ikvfnm\nm5owYYIKCwttrgxomAgsAaAO/fzzzxoyZIjWrl0rSXI1j1Hy+O5yxnhsrgxAU+RpmyjH/vef119/\nne5qaDTWr1+vr7/+WpLkaZMgZyxfCgKof+7msUoe312OgFuS9NFHH2nMmDHat2+fzZUBDQ+BJQDU\nke+//15DhgzR5s2bJUnutDgljesmh89tc2UAmirDMOTrlCxJysrK0vz5822uCIiMV1991Vr2H8fY\nlQDs40oOKGl8Dzliw18QLlq0SCNHjtSePXtsrgxoWAgsAaAOLF++XMOGDdPOnTslSZ7WCUoa21UO\nj8vmygA0db5KYc6sWbNsrASIDNM0D5zLLoe87RJtrQcAXAk+JU/oIWeCT9KBa4OMjAybKwMaDgJL\nAIiwRYsWacSIEcrOzpYkeTskKXFMFwb/BxAVXM0C1gXUW2+9paKiIpsrAo7Nd999pzVr1kiSfO2T\n+HsLICo4Y71KGt9DruSAJGn16tUaOnSo1fsKwOERWAJABH388ccaPXq08vLyJEm+zs2UMKqzDCdv\ntwCig2EY8h2XIknKy8vT3Llzba4IODaVWwpXnNsAEA2cAbeSzu4ud4sYSdXHtwdwaFxBA0CEfPDB\nBzr77LOt1kr+Hi0Uf1pHGQ7D5soAoKrKoc4rr7xiYyXAsTFN0xq/0vC65GmdYHNFAFCVw+dS4lnd\n5W4ZL0naunWrhg4dqp9++snmyoDoRmAJABEwf/58nXPOOSotLZUkBY5PV9zg9jIMwkoA0ceV6Jer\nWbiL2ty5c7V3716bKwJq56uvvrK6V/o6JtOjAUBUcnicSjqzqzxtEyVJu3bt0ogRI7R+/Xp7CwOi\nGH/RAeAYLVy4UGeffbZKSkokSTH9Wir2pDaElQCiWsXkOyUlJXrrrbdsrgaoHbqDA2goDJdDiWd0\ntkLLHTt2aMSIEYxpCRwCgSUAHIMlS5borLPOsrqBB/qkKWZAa8JKAFHP1ynZWqZbOBqi8vJyvfba\na5IkR4xb7rQ4mysCgMMznA4lnt7ZGr5iy5YtGjlypLZv325zZUD0IbAEgFpasWKFxowZo/z8fEmS\nv2eqYk9pS1gJoEFwxnrlTg8HPPPmzdOuXbtsrgg4OvPnz1dWVpYkydcphTGjATQIFS0t3S3Df4PX\nr1+vUaNG8XcY+AUCSwCohe+++06nn366Ne6bv1tzxQ1qR1gJoEGp6EIbCoU0Z84cm6sBjs6bb75p\nLdMdHEBDYridShzTVe7UWEnSjz/+qFGjRmn37t02VwZEDwJLADhKP/zwg0aOHKns7GxJkq9ziuKG\ndCCsBNDgeNslWcvz5s2zsRLg6FWcs46AW65mMTZXAwBHx+F2KvHMrnI1D79/ff/99zrjjDOUm5tr\nb2FAlCCwBICj8PPPP2vkyJFWFzRvx2TFD+9ENzQADZIzxiNnkl9SuHttKBSyuSKgZjZs2KANGzZI\nkjytE/jSEECD5PC6lDS2m1wpAUnS//73P40ZM0b79u2zuTLAfgSWAFBDmzZt0ogRI5SRkSFJ8rZP\nUsIIwkoADZunVbwkac+ePVq1apXN1QA1M3/+fGu54hwGgIbI4XMp6axu1heIS5cu1VlnnaWCggKb\nKwPsRWAJADWwbds2jRgxQlu3bpUkedokKGHUcTKcvI0CaNg8rRKsZbqFo6GofK5WPocBoCFy+N1K\nGtdNzgSfJGnx4sUaP368ioqKbK4MsA9X2gBwBBkZGRoxYoQ2btwoSfK0jFfiGV0IKwE0Cp70OGl/\nQ/HKrdaAaBUKhaxz1ZnokzPGY3NFAHDsnAFPOLSM80qSPv30U02cOFElJSU2VwbYg6ttADiMPXv2\naNSoUVq3bp0kyZ0Wp8QxXWS4ePsE0Dg4vC65W4RnKV24cCEXRoh6q1at0p49eySFx68EgMbCGetV\n0tnd5YgNfxHz4YcfavLkySovL7e5MqD+ccUNAIdQWFios88+W2vWrJEkuVvEKPHMLjLcTpsrA4DI\nquhSW1RUpK+++srmaoDDozs4gMbMGedV0rjucgTckqQ5c+bo6quvlmmaNlcG1C8CSwA4iGAwqAsv\nvNC6cHcl+5U4tpscHpfNlQFA5FWetIRxLBHtrHPU2D+kAQA0Mq4En5LGdZfhDV97zJgxQ3/7299s\nrgqoXwSWAPALpmlq6tSpeueddyRJjlhPOKz0ElYCaJzcqbHS/qEuCCwRzYqLi7Vo0SJJkrtFLH+b\nATRariS/Esd0kZzhgabvvPNOPffcczZXBdQfAksA+IUHHnhATz31lCTJ8DiVNLYrA/oDaNQMp8Nq\nqbZs2TLl5ubaWxBwCF999ZU1a27llsEA0Bh50uKUMPI4a3K8KVOm6P3337e3KKCeEFgCQCX//ve/\n9de//jV8x2kocUwXuZIC9hYFAPWgYizAUCikBQsW2FsMcAiVZ7Jn/EoATYGvQ7LiBrWXFB626rzz\nztOyZcvsLQqoBwSWALDfxx9/rMsvv9y6nzCikzzptN4A0DR4Wh54v1uyZImNlQCHZk0K5TTCQxkA\nQBMQ6JmqmH4tJYUnBj3rrLP0888/21wVULcILAFA0ooVKzRp0iSVl5dLkuJObSdfxxSbqwKA+uNK\n9kuOcJ+zlStX2lsMcBCmaVrnpis5IMPJpQyApiNmQGv5ujSTJGVlZWnMmDHKzMy0uSqg7jBKdR3Z\nvHmzfv75Z5WWlqpt27bq2bNn1Bxn1apVWrdu3RG38/l8GjduXCTKBKLaxo0bNXbsWOXn50uSAn3T\nFeidZnNVAFC/DKdDrmS/yncXElgiKm3btk3Z2dmSJHcKw7UAaFoMw1D80A4KFZapdNterV+/XuPG\njdNnn32mmJgYu8sDIo7AMsKWLFmiP/3pT1q6dGmV9e3bt9fdd9+tiy66yPbjvPDCC3rssceOeIzU\n1FTt3LnzmGsFotnu3bs1ZswY7dq1S5LkOy5FsSe3sbkqALCHKyVG5bsLtWvXLmVkZCg9Pd3ukgBL\n5SDd1YyLcwBNj+F0KOH0zsp5d43Kdxdq2bJlmjx5st555x25XMQ7aFw4oyPonXfe0aRJkxQMBuV2\nuzVw4ED5fD59/fXX2rRpky6++GL98MMPuv/++6PiOH6/X2PHjj3k40lJScdUJxDtCgsLNX78eK1d\nu1ZSePy2+OEdZRiGzZUBgD3cKQEV719euXIlgSWiyv/+9z9r2UULSwBNlMPjVOKZXZX99hqF8kr0\n/vvv6+qrr9azzz7LdQwaFQLLCNm6dasuvPBCBYNB9ezZU++9957at28vScrPz9fFF1+sN998Uw88\n8IAGDhyo8ePH236c5ORkvfHGG7WqA2jogsGgLrzwQmvwfldyQAlndGY8LABNWuUQaOXKlTrzzDNt\nrAaoqkoLSwJLAE2YM+BR0thwaGmWlGvGjBlq3bq17rzzTrtLAyKGK/MIueeee1RYWCiXy6U33njD\nChElKTY2Vi+//LK17pZbbon64wCN3bXXXqt33nlHkuSI9ShxbFc5vHyHA6BpqxwCVW7NBkSDisDS\nmeCTw+20txgAsJkr0a/EMV0kZ7hV5V133aUXXnjB5qqAyCGwjIDS0lK99tprkqRx48apW7du1bYJ\nBAL6wx/+IElas2aNli9fHrXHARq7p59+Wk8++aQkyfA4lTS2q5wxHpurAgD7ObwuOeO9kpgpHNEl\nNzdXGzdulETrSgCo4EmLU8LI46T9PcGnTJmiL774wt6igAghsIyAxYsXa9++fZJ02DEhK3erev/9\n96P2OEBj9vnnn2vq1KnhOw5DiaO7yJXEhQ8AVKgIg37++Wfl5eXZXA0Q9u2331rL7mb83QaACr4O\nyYob2E6SVFZWpokTJ2rr1q02VwUcOwLLCKj8Aapfv36H3K5Hjx7y+XySpO+++y4qjrN9+3bNmzdP\n7777rr744gsrEAUao02bNuncc89VeXm5JCluUDt5WsbbXBUARJeK2ZdN06zy2QOwU9UJd5ghHAAq\n8/dKla9rc0lSZmam/u///k+FhYU2VwUcGwLLCFi/fr213K5du0NuZxiG2rRpIyncasHu42zfvl2t\nW7fW6aefrvHjx2vw4MFKSkrS6aefrkWLFh11fUA0Kygo0P/93/9p9+7dkiR/9xYK9Ei1uSoAiD7u\nX0y8A0SDKhPu0MISAKowDEPxQ9rLnRorSVqxYoUuv/xymaZpc2VA7RFYRsDevXut5cTExMNum5CQ\nIEm1askY6ePExsaqd+/eGjt2rEaNGqUWLVooFApp3rx5Gj58uB566KGjrlGScnJyDnnLzc2t1T6B\nY2Gapi699FKtWrVKkuROi1PcoEOH/gDQlP1ypnAgGlSciw6/W84A404DwC8ZTocSzugsx/6x+V95\n5RVNmzbN5qqA2mNK3AioaGptGIbcbvdht/X7/ZLCrb3sOs7w4cM1YcIEDRkyRC7XgVPANE29+eab\nuvrqq5WVlaUbbrhBXbp00fjx44+qzuTk5KPaHqhr/+///T+9/vrrkvbPCH5GZxlOvq8BgINxxHhk\neF0yS8q1Zs0au8sBZJqmfvzxR0mSK8VvczUAEL2cAY8SR3dR9jurpaCpW265Rb169dJZZ51ld2nA\nUeOKPQI8nvA3GKZpKhQKHXbb0tJSSZLX67XtOP/3f/+n0047rUpYKYWD0EmTJmn+/PnW826++eaj\nrhOIJu+8845uv/328B2XQ4mju8jhP3zgDwBNmWEYcsaFP3MwaD+iQVZWloqLiyVJzjifzdUAQHRz\nN49R/LCOksLZwYUXXqgffvjB5qqAo0dgGQFxcXHW8pFaTlY8HhsbG7XH6d27t377299Kkn744Qet\nW7fuqJ6fnZ19yNuGDRuOuh6gtr7//nv95je/se4nDO8odzMG6geAI3HGhr+43L59uzVRGWCXLVu2\nWMuOWLqDA8CR+Ds3U6BvuqTwMHETJkxQTk6OzVUBR4fAMgJatWplLW/fvv2w21Y83rp166g9jiQN\nGjTIWj7aCYKSkpIOeTvS2JtApGRnZ2vChAnKz8+XJMWc0FK+Tik2VwUADUNFKBQKhbRjxw6bq0FT\nVzmwdBJYAkCNxJ7URp62iZKkdevW6Ve/+pWCwaC9RQFHgcAyAnr27GktH66pdWZmpvWtRo8ePaL2\nOJLk8x3oblPRvRxoKMrLy3X++edbLXq97RIVc2LtwnsAaIoqWlhKVcMiwA5VA8ujH1YJAJoiw2Eo\nYUQnORPD1/YfffQRQ76hQSGwjIDBgwfL4Qi/lAsWLDjkdpUfGzZsWNQeR5J++uknazk9Pb1W+wDs\n8pe//EXz5s2TJDmT/Iof0UmGYdhcFQA0HJVbsRFYwm60sASA2nF4XUoc3UWGxylJeuihh/Tyyy/b\nXBVQMwSWEZCamqohQ4ZIkl555RVrNu9fmjFjhqTwWJSjR4+O2uMUFxfrxRdflCTFx8erX79+R70P\nwC4vvPCCHnvsMUmS4XWGJ9nxuI7wLABAZbSwRDSpMoZlDIElABwNV6JfCSOPk/a337jiiiu0bNky\ne4sCaoDAMkJuu+02SeFZDK+99lqZplnl8RdeeEGffPKJJOn666+X3++vto+VK1fqjTfe0BtvvHHI\nAXGP9Tg7duxQdnb2IX+OvLw8TZ48WZs2bZIkTZ06VW43MyqjYVi5cqWuvvrq8B1DShjVWa4EZhMF\ngKPloIUlokjFOegIuGU4uXwBgKPlbZuo2JPaSJJKSkp04YUXHjYXAKKBYf4y8UKtTZkyRc8++6wk\naejQofrVr34lr9er+fPna9asWTJNUwMGDNCCBQsUCASqPf+aa67Rk08+KUlatmyZTjzxxIgfZ8aM\nGbr66qs1ePBgnXTSSUpLS1NqaqpKSkq0cuVKvfLKK8rKyrL2/dFHH1UZz/JY5eTkKDk5WVJ4UpSk\npKSI7RtN2759+3TiiSdas9rHDmyrmD4MZwAAtWGapjJnLJNCpsaOHau5c+faXRKasNTUVGVmZsrd\nIlbJ5/Q88hMAANWYpqm9n6xTycZw46hx48Zpzpw5DJ2FiIl03kM/yQh68sknFRcXp0ceeUQLFy7U\nwoULqzw+duxYvfjiiwcNK+vrOK1bt1ZSUpIWLFhwyHEw/X6/fv/73+vee++NaFgJ1BXTNDVlyhQr\nrPR2SFKgd5rNVQFAw2UYhpyxHgX3ldDCErYqKipSZmampKotfwEAR8cwDCWc1kl7cr5XMLdY7733\nnv7xj3/o+uuvt7s04KBoYVkH1q9frzfeeEPr1q1TWVmZ2rRpo7POOksDBw487POee+45ffDBB5Kk\nadOmqWPHjnVyHNM0tXz5cn3xxRfavn27du7cKYfDoebNm+uEE07QmWeeWWctH2lhibrw7LPPasqU\nKZIkR5xXKZN6yeHl+xgAOBbZ765R2Y48xcfHa+/evXaXgyZq3bp16tKliyQp0CddcQPb2lwRADRs\n5dmF2vPWaqk8JJfLpUWLFumUU06xuyw0ApHOewgsUa8ILBFpq1at0sknn6ySkhLJYSh5Qg+5W8Ta\nXRYANHh7P1uv4rW7JUm5ublKSEiwuSI0RfPnz9eoUaMkSXGD2inQix4UAHCsin7M1L7PN0qS2rZt\nq//973/WdTpQW5HOexi1GkCDVTFJVElJiSQp9uQ2hJUAECFOJt5BFNi6dau1zAzhABAZvq7N5euc\nIin8N/7SSy+tNqEvYDcCSwANkmmauuqqq7R27VpJkrc941YCQCQ5fG5rOScnx8ZK0JRVnsXW4Xcf\nZksAQE0ZhqG4IR3kTAzPWTFnzhw9+uij9hYF/AKBJYAG6bnnntOsWbMkhQfhjx/ekRnuACCCDPeB\nj4l5eXk2VoKmrPK5Z7idNlYCAI2Lw+1UwqjOkjN8DXXTTTfp66+/trkq4AACSwANzrfffqupU6eG\n7zgMJY7qzCQ7ABBhlcMhAkvYpfK55/AQWAJAJLlTAoob1F6SVFZWpsmTJ9OrAlGDwBJAg5Kfn6/J\nkyeruLhY0v5xK1MZtxIAIo3AEtFg37591nLlVr8AgMjwd2su33Hh8Sw3b96syy67jPEsERX4qw+g\nwTBNU1dffbV++uknSZKnXSLjVgJAHTE8BJawH13CAaBuWeNZJoTHs3z77bf1+OOP21wVQGAJoAF5\n4YUX9J///EdSeNzKhOGdGLcSAOoILSwRDaxzz2HIcHLpAgB1weFxKuH046zxLG+44QYtW7bM5qrQ\n1PFXH0CDsHr1al1zzTXhOw5DCSOPk8PHuJUAUFcctLBEFKg49wzGrwSAOuVOiVHcqe0kHRjPMjc3\n196i0KQRWAKIeqWlpfr1r3+toqIiSVLsSW3kSYuzuSoAaNyYJRzRwAos6Q4OAHXO372FvJ2SJUmb\nNm3Stddea3NFaMoILAFEvXvuuUerVq2SJHlaJyjQh3ErAaCuVQ6IKk98AtSnisDSQWAJAHXOMAzF\nD+0gR5xXkvTSSy/p7bfftrcoNFkElgCi2tKlS3X//fdLCncHix/ekXErAaAeGE6H5Ai/39LCEnY5\n0CWcyxYAqA8Oj0sJwzta96+88kplZmbaWBGaKv7yA4hahYWFuuiiixQKhSRJcYPbyxnjsbkqAGg6\nKsYNJLCEXegSDgD1z9MyXoHe4V5tWVlZuuqqq2Saps1VoakhsAQQtW6++WatXbtWkuTtmCzfcSk2\nVwQATUtFSERgCTuUl5ersLBQEoElANS32JPayJnokyS99dZbevnll22uCE0NgSWAqDR//nz985//\nlCQ5/G7FD25PV3AAqGeO/RPvEFjCDgUFBdYygSUA1C/D5VDCiE7S/kuwqVOnauvWrfYWhSaFwBJA\n1Nm7d68uvfRS63780A5y+N02VgQATdT+L4roBgY7VAwJI1mnIgCgHrmbxyqmXytJ4Qn4Lrvssirv\nzUBdIrAEEHX+9Kc/Wd/e+bo2l7d9ks0VAUATtT+odDpp3Yb6V/m8IzMHAHvEnNBSrmYBSdK8efP0\n1FNP2VwRmgoCSwBRZc6cOXrxxRclSY5Yj+JObWtvQQDQhJkhAkvYp8p5R2IJALYwnA4lnNZJcoab\nut9www1at26dzVWhKSCwBBA1srKydMUVV1j3E4Z3lMPjsrEiAGji9mdEBJawQ5XzLkRgCQB2cSUH\nFDugjSSpqKhIF198sYLBoM1VobEjsAQQFUzT1NVXX63MzExJkr9XqjytEmyuCgCaOLqEw0Z0CQeA\n6BHonSZ3Wpwk6auvvtKDDz5oc0Vo7AgsAUSFWbNmafbs2ZIkZ6JPcSe1sbkiAIBJC0vYiC7hABA9\nDIeh+NM6ynCFY6Q77rhD3377rc1VoTEjsARgu+3bt+uaa64J3zGkhNM6yXBzcQwAtqOFJWzkcFS6\nVCGwBADbueJ9ih3YTpJUVlamiy66SKWlpTZXhcaKwBKA7f7whz8oNzdXkhTTr6XcLWLtLQgAEMak\nO7CZde6RVwJAVPB3by5Pm/DQXatWrdK0adNsrgiNFYElAFu9/fbbeueddyRJrmS/Yk5oZXNFAAAL\nXcJhs4pzz2TSHQCICoZhKH5YRxme8Pvzvffey6zhqBMElgBsk5eXp6lTp1r344Z2kOHkbQkAooW5\nvxtula65QD060MKSwBIAooUzxqPY/XMOlJSU6Pe//731mQGIFD59ArDNHXfcoW3btkmS/D1ayJMa\nZ3NFAIAqGMMSNqNLOABEJ3/3FnK3iJEkzZs3T7NmzbK5IjQ2BJYAbLFixQo9/vjjkiRHwG19QwcA\niCJ0CYfNaGEJANHJcBiKG9pBMsL3//znPys7O9veotCoEFgCqHfBYFBTpkxRKBSSJMUNbCeH12Vz\nVQCAamhhCZtZY1iSVwJA1HGnxCjQO12SlJmZqZtvvtnmitCYEFgCqHfTp0/X8uXLJUmeNgnydkq2\nuSIAwC+ZpimzPPzFkt/vt7kaNFWBQECSZJYHba4EAHAwsSe2kiPWI0n617/+pS+++MLmitBYEFgC\nqFfbt2/XrbfeGr7jNBQ3uL0Mw7C3KABANWZp0OoSnpKSYm8xaLKSk8NfaprF5TZXAgA4GMPtVPzg\n9tb9KVOmqLS01L6C0GgQWAKoV9dee63y8vIkSbH9W8sV77O5IgDAwYRKDgREFaERUN8qzr1QCS0s\nASBaedslydshSZK0evVq/eMf/7C5IjQGBJYA6s17772n2bNnS5KcSX4F+qTZXBEA4FBMAktEAauF\nZUm5zBADWQJAtIo7tZ0Mdzhiuvvuu7VhwwabK0JDR2AJoF4UFBToD3/4g3U/fmgHGU7eggAgWoWK\nCSxhv8rnnllKK0sAiFbOWK9iB7SRJBUXF+v3v/+9TGZMwzEgLQBQL+666y5t2bJFkuTv1lyetDib\nKwIAHE7lLuGMYQm7VD73Kp+TAIDo4++ZKlezGEnSRx99pNdee83mitCQEVgCqHOrVq3SI488Ikly\n+F2KPbmtzRUBAI7EpIUlokCVFpZMvAMAUc1wGIof2kHaP6fqn/70J+Xm5tpaExouAksAdSoUCumq\nq65SMBjuxhU7sJ0cPpfNVQEAjqTyJCcElrBL5XOPFpYAEP3czWMU6Bmeq2Dnzp267bbbbK4IDRWB\nJYA69eqrr2rJkiWSJE+rePmOo1shADQETLqDaEBgCQANT8yA1nLEuCVJTz/9tNasWWNzRWiICCwB\n1JnCwkLdfPPN4TuGFDeonQzDsLcoAECNVJ50hzEsYZfK555JYAkADYLD47SGAQsGg7r++uttrggN\nEYElgDrzyCOPaOvWrZIkf/cWciUFbK4IAFBTFa3ZPB6PAgHev2GPKi0sGcMSABoM33EpcrUIT8Dz\n4Ycf6sMPP7S5IjQ0BJYA6kRGRobuv/9+SZLhcSr2xNY2VwQAOBoVrdmSk5NpHQ/b0CUcABomwzAU\nN7Cddf/6669XeTnv46g5AksAdeL2229XQUGBJCnmhFZy+N02VwQAOBqhSoElYBdmCQeAhsuTFidv\nx/D7+Jo1azRjxgybK0JDQmAJIOJWrlyp559/XpLkjPcq0CvV5ooAAEerovstgSXs5Pf75ff7JdEl\nHAAaorhT2krOcE+NO+64Q3v37rW5IjQUBJYAIso0TV1//fUyTVOSFHtyWxlO3moAoCEJlQWt1mxt\n2rSxuRo0da1bh4eVCeaX2FwJAOBoOeO8CvROkyRlZWXpvvvus7kiNBSkCAAi6t1339Wnn34qSXKn\nxcnbIcnmigAARyu470Aw1KFDBxsrAQ6cg8G8EusLUQBAwxHTr6UMn0uS9Oijj2rDhg02V4SGgMAS\nQMSUlpbqL3/5i3U/7tS2TNQAAA1QMI/AEtHDOgeDpkKFZfYWAwA4ag6PS7EDwq3lS0tLdfPNN9tc\nERoCAksAEfPUU09p3bp1kiRf52ZyN4+1uSIAQG2ECCwRRSqfg5XDdABAw+Hv1kKu5PCYxK+//roW\nL15sc0WIdgSWACIiOztbd999d/iOy6HYk1rbWxAAoNboEo5oQmAJAA2f4TAUO7Cddf+6665TKBSy\nsSJEOwJLABFxzz33KCcnR5IU0yddzlivzRUBAGormFcsSXI4HEy6A9sRWAJA4+BtnSBP20RJ0vLl\nyzVr1ix7C0JUI7AEcMx++uknPfnkk5IkR8CtmOPTba4IAHAsKkKhNm3ayO1221wNmroqgeU+AksA\naMjiTmkr7Z/m4JZbblFhYaG9BSFqEVgCOGZ//etfVV5eLkmKPamNDLfT5ooAALVlmqYVWNIdHNEg\nJSVFsbHhcbFpYQkADZsryS9/j1RJ0rZt2/Too4/aWxCiFoElgGOyYsUKvfnmm5IkV0pAvi7NbK4I\nAHAszOJymWXhMaUILBENDMOwzkUCSwBo+GL7t5LhCTdyeeihh7R3716bK0I0IrAEcEzuuusuazl2\nQGsZhmFfMQCAYxZkhnBEoYpzMZRfIjNk2lwNAOBYOPxuBXqnSZJycnL02GOP2VwRohGBJYBaW7Zs\nmd59911Jkqt5jDWAMgCg4SKwRDSyzkUzHFoCABq2QO80q5XlP/7xD2sCV6ACgSWAWrvzzjut5dgT\naV0JAI0BgSWiETOFA0Dj4vC6FOgbnqx17969euSRR2yuCNGGwBJArXz11Vf64IMPJEnu1Fh52iTY\nXBEAIBIqz8JMYIloQWAJAI1PoFeqDK9LkvToo49qz549NleEaEJgCaBWKreujKF1JQA0GsF9xZIk\nn8+ntLQ0m6sBwjp27Ggtl+8ttrESAECkODwuxexvZZmXl6eHH37Y5ooQTQgsARy1RYsW6ZNPPpEk\nudPi5GkVb3NFAIBIME1TZXsKJUk9e/aUw8FHRUSHLl26yO12S5LK95+jAICGz98rVYYv3Mry8ccf\nV1ZWls0VIVrwKRTAUbvjjjusZWYGB4DGI1RYJrO4XJLUt29fm6sBDvB4POrevbskAksAaEwcbqdi\njm8pSSooKNCDDz5oc0WIFgSWAI7KZ599pgULFkiS3C3j5WlJ60oAaCwqB0EElog2FedkqLBMoaIy\nm6sBAERKoEcLOfzhVvRPPPGEdu3aZXNFiAYElgBqzDTNqq0rT2xtYzUAgEgr31NgLR9//PH2FQIc\nROVzsoxWlgDQaBhup2L6hVtZFhUV6e9//7vNFSEaEFgCqLF58+Zp8eLFkiRP6wR50uNsrggAEEmV\nQ6A+ffrYWAlQXeVWv3QLB4DGxd+9hRyBcCvLp556Sjt27LC5ItiNwBJAjfyydWXMia1srAYAUBcq\nQqB27dopMTHR3mKAX6gaWBYcZksAQENjuBxWK8vi4mI98MADNlcEuxFYAqiRDz/8UEuWLJEkedom\nypNK60oAaEzMsqCCe4slMX4lolOzZs3UsmX4YpYWlgDQ+Pi7t5AjxiNJeuaZZ7Rt2zabK4KdCCwB\nHJFpmrr77rut+7G0rgSARqc8p0gyw8sElohWFedmeW6xzGDI5moAAJFkOB2KOSH8xVRpaSljWTZx\nBJYAjuiLL77Q0qVLJYVbV7qbx9pcEQAg0iqPX8mEO4hW1rkZMsMhOwCgUfF3bS5HbLiV5fPPP689\ne/bYXBHsQmAJ4Igeeughazmmb7qNlQAA6krlLra0sES0YuIdAGjcDKdDgd5pkqTCwkI9/fTTNlcE\nuxBYAjisn376SXPmzJEkuZrHyM3M4ADQKFWEP7GxserQoYPN1QAHR2AJAI2fv1tzGR6nJOmf//yn\niouLba4IdiCwBHBYjzzyiEwzPKhZTN90GYZhc0UAgEgzTVPl2eHwp0+fPnI4+IiI6NS5c2f5/X5J\nVYcxAAA0Hg6PS/7uLSRJu3bt0syZM22uCHbg0yiAQ8rMzNS///1vSZIjzitvh2SbKwIA1IVQXonM\n0qAkuoMjujmdTvXq1UtSuIVlxZeqAIDGJdArVXKEG8s8/PDDCoWYaK2pIbAEcEjTp0+3mt/H9E6T\n4aB1JQA0RmVZBdYyE+4g2lWco2ZJuYJ5JfYWAwCoE85Yr3ydUiRJP/zwgz744AObK0J9I7AEcFCF\nhYV68sknJUmGxylft+Y2VwQAqCulO/Os5VNPPdXGSoAjq3yOllU6dwEAjUugb5q1/OCDD9pYCexA\nYAngoF566SXt3r1bkuTvkSqH22lzRQCAulKWEQ59kpKS1KNHD5urAQ5vyJAh1nJpBoElADRW7pQY\neVrHS5I+//xzLVu2zOaKUJ8ILAFUEwwG9Y9//CN8x2GExw8BADRKoZJya7blwYMHM+EOol7Hjh2V\nnp4u6UDYDgBonAJ90q3lhx9+2MZKUN/4RAqgmnfffVfr1q2TJPk6N5MzxmNzRQCAulK2K99artxy\nDYhWhmFY52pwb7GChWU2VwQAqCue1glyJfslSa+//ro2bdpkb0GoNwSWAKp56KGHrOWYPmmH2RIA\n0NCVZuyzlgks0VBUPlcZxxIAGi/DMBToG25lGQqF9Oijj9pbEOoNgSWAKr766it98cUXkiRPmwS5\nkgM2VwQAqEsVYY/f79cJJ5xgczVAzVQJLOkWDgCNmq9TihwxbknSjBkzlJOTY3NFqA8ElgCqqDwu\nSEzf9MNsCQBo6MzykMoyCyRJAwcOlMfDECBoGHr16qXExERJUunOfYffGADQoBlOhwK9wj3/CgoK\n9Mwzz9hcEeoDgSUAy8aNG/Xmm29KklzNAnK3jLe5IgBAXSrLzJdCpiS6g6NhcTqdGjRokCSpfE+h\nQqXlNlcEAKhL/u4tZLjDEdbjjz+usjLGL27sCCwBWGbMmCHTDF+4BnqnyzAMmysCANSl0kpj/xFY\noqGxzllTKtuZf/iNAQANmsPrkr9rC0lSRkaG3nvvPZsrQl0jsAQgSSorK9Pzzz8vSTK8Lvk6Jttc\nEQCgrlWM/edyuXTKKafYXA1wdJh4BwCaFn+PFtbys88+a2MlqA8ElgAkSe+995527twpSfJ3aSbD\nxdsDADRmZshU2a5wyHPCCScoJibG5oqAo3PiiSfK5/NJkkqZeAcAGj1Xkl/utDhJ0kcffaRNmzbZ\nWxDqFIkEAEmqMnCxv3uLw2wJAGgMyvcUyiwLSaI7OBomj8ejk08+WZJUlpUvMxiyuSIAQF2ruFY1\nTVMzZsywuRrUJQJLANq4caM+/vhjSZI7PU6uJL/NFQEA6lppxoGZlYcOHWpjJUDtWedu0LRmvAcA\nNF6+jskyvE5J0vPPP8/kO40YgSUAPffcc9ZkO7SuBICmoWzHgcCyYrZloKGp3Dq4dMdeGysBANQH\nw+WQv0tzSeHJd+bOnWtzRagrBJZAE1dWVqbnnntO0v7Jdjow2Q4ANHZmeUgl28OBZf/+/ZWSkmJz\nRUDtDBo06MA4llty7S0GAFAvKjeyqTy0GRoXAkugiWOyHQBoekoz9knl4fH+zjrrLJurAWovEAho\nxIgRkqSyzAKFiugaCACNHZPvNA0kE0AT9+yzz1rLdAcHgKahpFJLNAJLNHSVz+GSrbn2FQIAqDeV\nJ9+p6DGIxoXAEmjCNm3apI8++kiS5E5jsh0AaApM07S6zjZv3lwnnniivQUBx2js2LHWcsnmXPsK\nAQDUm8qT7zz33HNMvtMIEVgCTdiMGTOYbAcAmphgbrGC+0okSWeeeaYcDj4OomFr3769evToIUkq\n3bZXZjBkc0UAgLpmuBzyd2byncaMT6hAE1VWVqbnn39ekmR4nfJ1ZLIdAGgK6A6OxqjiXDZLgyrb\nlW9zNQCA+uDv0dxarjzUGRoHAkugiZo7d64yMjIkSf4uzZlsBwCaiIrA0ul06owzzrC3GCBCqoxj\nyWzhANAkuJIC1uQ7H374oTZv3mxzRYgkEgqgiWKyHQBoekIl5SrbmSdJGjx4sBITE+0tCIiQU089\nVQkJCZIILAGgKfF3D7eyZPKdxofAsg58+OGHuuyyyzRkyBCdfPLJOu+88/Tiiy+quLg46o5TX7Ui\numRlZenjjz+WJLnTYplsBwCaiNLte6VQeOxiuoOjMXG73Ro9erQkKZhTpGBeic0VAQDqg69jigxP\nePKdmTNnWnM0oOEzTH6bEZOXl6df/epXhxzstUePHnrzzTfVtWtX249TX7X+Uk5OjpKTw2MlZmdn\nKykpKaL7R8089dRT+v3vfy9JihvcXoGeqTZXBACoD3sXbFDxT1mSpNWrV1sTlQCNwUsvvaSLL75Y\nEp9vAKApqfz55uuvv9aAAQNsrqhpinTeU+ctLEtLS+v6EFHBNE1NnjzZCgAvv/xyffrpp/ryyy/1\nt7/9TX6/X2vWrNGYMWO0e/duW49TX7Uier3yyivhBUNMtgMATYRpmird31W2ffv26t69u70FARF2\n5plnyjAMSXQLB4CmxHdcirVsXeuiwavzwPK2227T6aefrldffVUlJY23a8arr76qDz/8UJL0//7f\n/9O//vUvnXbaaRo4cKBuu+02zZ07Vw6HQ5s2bdJdd91l63Hqq1ZEp61bt2rRokWSJE+rBDn8bpsr\nAgDUh/LdBQoVlUkKdwevCHaAxqJ58+Y66aSTJIWHPzDLgjZXBACoD56W8XL4XZKk//73vwoGef9v\nDOo8sAyFQpo3b55+9atfqWXLlrr22mv17bff1vVh6920adMkhVss3HTTTdUeP+200zR58mRJ4clO\ncnNzbTtOfdWK6PTaa69Zy5W/iQIANG4lm3OtZcavRGNlndtBU6U79tlbDACgXhgOQ96O4WvbHTt2\naPHixTZXhEio88ByxIgR1vhI2dnZevzxx9W3b1+ddNJJeuaZZ7RvX8P/ILFx40atXLlSknThhRfK\n6XQedLvf/va3kqSysjK99957thynvmpF9LKayDsNedszhigANBUlm3MkSX6/X8OHD7e3GKCOjB07\n1lquHNIDABo3uoU3PnUeWI4dO1arV6/W4sWLdckllygQCEiSli1bpquuukrp6em65JJLrC6qDdGX\nX35pLQ8ePPiQ2w0aNOigz6nP49RXrYhO69at0zfffCNJ8rZJlMPrsrkiAEB9KN9brPLdhZKk0aNH\ny+/321wRUDf69eunNm3aSJKKN2bLDIZsrggAUB/cqbFyxHokSW+88YbKyspsrgjHqs4DywqDBg3S\nCy+8oIyMDE2fPl39+vWTJBUWFurf//63hg4dqq5du2ratGnatWtXfZUVET/88IO13Llz50Nul5CQ\noBYtWlR7Tn0ep75qRXR69dVXrWW6gwNA01H88x5r+Ve/+pWNlQB1y+Fw6Pzzz5ckmcXlKt3e8Htz\nAQCOzDAM+TqFr3H37NmjefPm2VwRjlW9BZYV4uPjdfXVV2vFihVavny5pkyZovj4eEnS2rVrddNN\nN6l169Y655xz9N577zWIwVJ37txpLbds2fKw26anp1d7Tn0epz5qzcnJOeSN8TDtY5qm1TTecDnk\nbZtob0EAgHphmqaKf94tSYqJidG4ceNsrgioW5VD+eL1ew6zJQCgMakILKWqjXXQMNV7YFlZ//79\n9fTTT2vHjh167rnndMopp0iSysvL9fbbb+vss89W27Ztdccdd2jHjh12lnpY+fn51vKRulhVdImv\n/Jz6PE591JqcnHzIW8eOHY9qX4ic7777zmot622fJMN98PFLAQCNS3l2kYK5xZKkCRMmWH/fgcaq\nX79+6tKliySpZGO2zHK6hQNAU+BqFpAzwSdJeuutt1RUVGRzRTgWtgaWFfx+v9LS0pSenl5tEpgd\nO3bob3/7mzp27Kgbb7xRxcXFNlV5aBWtQA3DkGEYh9224ucrLy+35Tj1VSuiD93BAaBpqmhdKUkX\nXHCBjZUA9cMwDOtcN8tCKtmSa29BAIB6UblbeF5enj744AObK8KxsDWw3LJli+666y61b99eZ511\nlt566y0Fg0ElJiZq6tSpeumllzRmzBg5nU6VlJTowQcftMakiSYxMTGSwl2uSkpKDrttRcIfGxtr\ny3Hqo9bs7OxD3jZs2HBU+0JkmKZpBZaG1ylP6wSbKwIA1AfTNFW8PluSlJSUpNGjR9tcEVA/Kofz\ndAsHgKaD2cIbj3oPLMvKyjR79mydeeaZ6tChg+6++25t3bpVknTyySfr+eef144dO/T444/rt7/9\nrT744ANt3LhRl1xyiSRpzpw5Wr58eX2XfVhJSUnWcnZ29mG3rXg8MTHRluPUR61JSUmHvNXm58ax\n+/rrr7Vx40ZJkq9DsgxnVDSuBgDUsbLMfIXywl9QTpo0SR6Px+aKgPrRvXt39e3bV5JUsjlHodLo\nHxcfAHDsXEl+uVLCw9+89957ysvLs7ki1Fa9pRZr167VjTfeqNatW+vcc8/Vhx9+qFAoZE3Cs3Ll\nSi1ZskSXXnpptbEV27RpoxdeeEGDBg2SJK1ataq+yq6RijFyJFmh0MGUl5dr27ZtkqSuXbvacpz6\nqhXRpfI3S3QHB4Cmo/Ls4HQHR1NjTb4TNFWyKcfeYgAA9abimre4uFjvvPOOzdWgtuo8sFy4cKGG\nDx+url276sEHH1RmZqak8IQ7zz77rHbs2KHp06db34AezoknnigpPAt1NDn++OOt5WXLlh1yu5Ur\nV6qsrKzac+rzOPVVK6KHaZp6++23JUkOv1vu9Hh7CwIA1AszZKpkQ7i3RGpqqoYPH25vQUA9qzyU\nFN3CAaDpqDxbeMW1MBqeOg8s58yZo88//1xSeCzEK664QsuXL9fy5ct1xRVXWGMq1kSzZs3UqlUr\nxcXF1VW5tXLyySerRYsWknTY9L7yY2effbYtx6mvWhE91qxZo82bN0uSPO0SZTgOP9kSAKBxKMvY\np1Bh+MvHyZMnV5vYEGjs2rdvr4EDB0qSSrftVai4zOaKAAD1wRnnlSs53C38448/Vmlpqc0VoTbq\npUt43759NX36dO3YsUPPPvus+vfvX6v93Hbbbdq2bZumTJkS4QqPjcPh0GWXXSZJ+uyzz7Ro0aJq\n22RlZenpp5+WJA0ePLhW3awjcZz6qhXRY+7cudayt22ifYUAAOpV5e7gVtdYoImxhkIImSreGF29\ntAAAdcez/9o3Ly9PixcvtrcY1EqdB5a33nqrVq5cqauvvjrqWkZG0k033aTU1FRJ0nnnnadPP/3U\nemzt2rU666yztHv3brlcLj344IMH3cd9992nXr16qVevXlq9enWdHScS+0DDYQWWDkOeVswODgBN\ngRkMqXhjuDt4u3btdMopp9hcEWCPyZMny+EIX/JUDvEBAI2bt12itVy5EQ8ajjoPLCvPSt2YJSYm\n6t1331ViYqJ27dqlkSNHKi0tTe3atVO3bt20bNkyOZ1OPfXUU4e8aNixY4dWr16t1atXq6ioqM6O\nE4l9oGHIycnRF198IUnypMfJ4aE7IAA0BaXb9sosCc+KfMEFF8gwGA4ETVNaWpo1fmvZjn0KFtAt\nEACaAneLWBne8PUvgWXDVG+zhDcFAwYM0HfffaeLLrpIsbGx2rVrl7Zs2SKHw6EzzjhDixYt0uWX\nXx4Vx6mvWmGvjz/+WMFg+ILVQ3dwAGgy6A4OHFD5/wCT7wBA02A4DHnbJEqSfvrpJ61fv97egnDU\nDNM0TbuLaIyCwaAyMjJUVlam9PR0+Xy+Iz4nIyNDe/aEP0Qdd9xxNXpObY5TF/uoqZycHCUnJ0uS\nsrOzm0wLXLtcdNFFevnllyVJKef3kSvRb3NFAIC6FiouU9Z//icFTfXo0UPff/89LSzRpGVnZys9\nPV2lpaVyJvmVcl5v/k8AQBNQtG639n0aDiofe+wx/fGPf7S5osYt0nkPLSzriNPpVOvWrdWhQ4ca\nB4Dp6enWGJY1fU5tjlMX+0D0CYVC+uCDDyRJzngvYSUANBFFa3dLwfD30VdccQXBDJq85ORknXvu\nuZKkYE6Rynbl21wRAKA+eNskSPs/Br3//vv2FoOjRmAJNFLLli3T7t27JUnetrRkBYCmwDRNFf2Q\nKUnyer266KKLbK4IiA5Tpkyxliv+jwAAGjeHzy13i1hJ0oIFC1RQUGBzRTgaBJZAI1V5YGFPW2YH\nB4CmoGxnvoK5xZKk8847z+qWAzR1Q4YMUdeuXSWFx7EMlZTbXBEAoD5498/lUFJSovnz59tbDI4K\ngSXQSFUElobLIU/LeJurAQDUh6IfdlnLV155pY2VANHFMIwD/yeCporX7ra3IABAvfC0S7SWmS28\nYSGwBBqhjIwMrVixQpLkaZ0gw8l/dQBo7ELF5SrekC1J6tatmwYPHmxzRUB0ufjii+XxeCRJhT9k\nirlHAaDxcyUH5IgJv/e///77vPc3IKQYQCNUeUBhz/4m8ACAxq143YHJdq688kom2wF+ISUlhcl3\nAKCJMQzD6ha+bds2ffvtt/YWhBojsAQaocpN3b0ElgDQ6JmmqUIm2wGOqPJQCUy+AwBNQ+VGPHQL\nbzgILIFGJhgMWoMJu1ICcu5v/g4AaLzKduUrmFMkSTr33HOVkpJic0VAdBo6dCiT7wBAE+NtFS85\nwj1PPv74Y5urQU0RWAKNzLfffqt9+/ZJEpPtAEATUbmlGJPtAIdWbfKddUy+AwCNneF2yt0iVpK0\ndOlSlZSU2FwRaoLAEmhkFi1aZC270+NsrAQAUB9CJeUqXr9HUniynSFDhthcERDdLrroImvynSIm\n3wGAJsGz/9q4uLhY33zzjc3VoCYILIFGpnJg6UkjsASAxq54LZPtAEejWbNmmjRpkiSpPJvJdwCg\nKajcmKfyNTOiF4El0IiYpqmFCxdKkpyJPjn8bpsrAgDUpcqT7Xg8HibbAWpoypQp1jKT7wBA4+dO\njZX2f6dbcc2M6EZgCTQi69atU2bm/gvXdMavBIDGjsl2gNoZOnSounTpImn/5DvFTL4DAI2Zw+OS\nKyUgSfriiy8UDAZtrghHQmAJNCJVxq+kOzgANHqF32ZYy0y2A9ScYRgHWlkGTVpZAkAT4EkLN+rZ\nu3evvv/+e5urwZEQWAKNSJXxK5lwBwAatfK9xSrZmCNJOuGEEzR06FCbKwIalt/97neKiwt/Xir8\nfqfMYMjmigAAdYlxLBsWAkugEal403XEeuSM89pcDQCgLhV+t9Na/stf/sJkO8BRSkhI0BVXXCFJ\nChWWqfjnPTZXBACoSx4CywaFwBJoJLZv364NGzZIYnZwAGjsQsVlKvopS5LUtm1bnXvuuTZXBDRM\n1157rZxOpySpYFWGTNO0uSIAQF1x+N1yJvokhQNL3vOjG4El0EhUGb+S7uAA0KgVrs6UysPdV//0\npz/J7XbbXBHQMLVt21bnn3++JCmYU6TSrXttrggAUJcqGvdkZGRo/fr1NleDwyGwBBoJxq8EgKbB\nLA+p8Ptwd/CEhARdfvnl/7+9O4+Pqr73P/6eyb6TsO+7iIqIC6iooFBBVHCtuxVB/XnVqkWvVlHA\nam0vVqv31lZFrSgWFQQXFJRNBFlEFonsEPZAyJ6Zyezn98eQIZFEIds5M3k9H488PHPOmTmftJzJ\nOe/zXUyuCIhs48aNCy+71uf+wp4AgEjHOJaRg8ASiBIVX7a2xFjFNEsyuRoAQEMp35Yvw+2XJN1z\nzz3hSUMA1M6ZZ56pSy65RJLkPVAq32GnyRUBABpK5eHTCCytjcASiAJFRUXKzs6WFPoCZuIFAIhO\nhmHI9WOoBVhcXJx+//vfm1wREB0eeeSR8HLFOQYAiD72tATZU+IlEVhaHYElEAVWrFgRHjA4jgl3\nACBqeXcXK1DsliTdfPPNat++vckVAdFh+PDhOu200yRJ7h0FCpR5TK4IANAQbDZbeAi17du3Ky8v\nz+SKUBMCSyAKrFu3Lrwc1yrFvEIAAA3KWanlV+Vx9wDUjc1mO3pOGQqPEwsAiD6xLY/eM69fv97E\nSvBLCCyBKFA5sIzNSjavEABAg/HlOeTLLZMkDRs2TH369DG5IiC63HTTTWrbtq0kqXxTnoIev8kV\nAQAaQlzzo/fMBJbWRWAJRIGKL1l7WoLsCbEmVwMAaAjOSrMXVx5vD0D9SEhICI8La/iCKt9EN0EA\niEaxlQLLyo1/YC0ElkCEc7lc2rZtm6SqT4oAANEjUOqWJ6dQktS3b18NGTLE5IqA6HTPPfcoJSXU\nVdCVfVBGIGhyRQCA+mZPjJM9JU4SLSytjMASiHDZ2dkKBkMX03QHB4Do5NxwUArNraZHHnlENpvN\n3IKAKJWZmamxY8dKkoJOn9zbC0yuCADQEGKbhx5Obd68WR4PE61ZEYElEOGqjF/ZgsASAKJNwOkN\nd03t0KGDbrjhBpMrAqLbQw89pJiYGEmSc+0BGUHD5IoAAPWtonei3+/Xxo0bTa4G1SGwBCJc5Sbs\nsXQJB4Co41x7QAqEApM//vGPiouLM7kiILp16dJFt99+uyQpUOKWe1u+yRUBAOob41haH4ElEOEq\nAktbnF0xaQkmVwMAqE8BhyfcurJjx44aM2aMyRUBTcP48eMVGxuayNC5Zj9jWQJAlIllpnDLI7AE\nIlgwGAx/ucY2T2ZMMwCIMs61B6Qj3VHHjx+vhAQeTAGNoVu3bho9erQkKVDqoZUlAESZmPREKTYU\niRFYWhOBJRDBcnJy5HA4JB0dNBgAEB0CZR6Vbz4sKdRF9Y477jC3IKCJefLJJ8NDMDh+oJUlAEQT\nm92muKwkSaHA0jAYr9hqCCyBCMb4lQAQvRxr9odbVz711FOKj483uSKgaencufPRGcMdXpVvOWxy\nRQCA+lTR6KeoqEj79u0zuRr8HIElEMEqB5ZxBJYAEDX8JW65j4Qj3bt312233WZyRUDT9MQTT4Qf\nFjjXHJDhp5UlAEQLJt6xNgJLIIKFv1RtUmxmkqm1AADqj3PNfulIz6Snn36amcEBk3To0EH33HOP\nJCno9Kp8c57JFQEA6gsT71gbgSUQwbKzsyVJMRmJssXFmFwNAKA++IvLwxN8nHTSSbr55ptNrgho\n2h5//HElJiZKCk2ERStLAIgOsVlHA8sNGzaYWAmqQ2AJRCi/36/du3dLCgWWAIDo4PzhaOvKCRMm\nKDY21tyCgCauXbt2uvfeeyVJQZdPro2HTK4IAFAf7PExsieHerHs3LnT5GrwcwSWQITau3evAoGA\nJCkmLcHkagAA9cFf5JJ7e4Ek6ZRTTtENN9xgckUAJOmxxx5TcnKoJY5r3QEZvoDJFQEA6kPFvXRO\nTo7JleDnCCyBCFX5C5XAEgCig2P1/vDyxIkTFRPDcB+AFbRu3Vr333+/JClY7pfrJ1pZAkA0qLiX\nLigoUFlZmcnVoDICSyBC7dq1K7wck05gCQCRzlfgkmdnoSSpT58+uvbaa02uCEBljz76qFJTUyVJ\nzvW5CnppZQkAka7yvTStLK2FwBKIUFVbWDKGJQBEOufqfeHlSZMmyW7nMg2wkhYtWuj3v/+9JMlw\n++XKPmhyRQCAuqrcW5HA0lq4EgYiFF3CASB6eA+UyrOrSJLUr18/XXXVVeYWBKBa48aNU3p6uqTQ\nWJYBl8/kigAAdUFgaV0ElkCEqvgytSXGyh7PGGcAEKkMw1DZ8j3h1//zP/8jm81mYkUAapKVlaUn\nnnhCkmT4gnJ+v9fkigAAdRGTfrS3IoGltRBYAhGq4suU1pUAENnc2/Llz3dKkq644goNHTrU5IoA\n/JIHH3xQXbp0kSSVbzksX4HL3IIAALVmT4mXjjwnJrC0FgJLIAKVl5crNzdXEoElAEQywxeQY2Wo\nhVZsbKxeeOEFkysC8GsSExP117/+NfTCkBzLd8swDHOLAgDUis1ukz01dE9NYGktBJZABNq9e3d4\nmcASACKXc32ugkfGwLv33nvVq1cvkysCcDyuv/56nX/++ZIk7/5SefcUm1sQAKDWKu6pc3JyeABl\nIQSWQASqMuFOOoElAESigNMr5/pQa/lmzZppwoQJJlcE4HjZbDa9+OKL4ddlK/bICARNrAgAUFsV\ngaXT6VR+fr7J1aACgSUQgZghHAAin2PVXskfCjiefvppNW/e3OSKAJyIAQMG6Oabb5YkBYrdKt+U\nZ3JFAIDaqNwIiG7h1kFgCUQgAksAiGy+ww65t4ae4Pfo0UP33XefyRUBqI3nn39eiYmhGWYdq/cr\n6PGbXBEA4ERVvqcmsLQOAksgAu3duze8HJNKYAkAkcQwDJV9tyf8evLkyYqPjzexIgC11alTJ40b\nN06SZHj8cv6w3+SKAAAnqnJgWfleG+YisAQiUGFhoSTJFmeXLZbTGAAiiSenSL6DZZKkwYMHa9So\nUSZXBKAuHn/8cbVp00aS5PrpkPwlbpMrAgCcCHtibHi54l4b5iPpACJQQUGBJMmWGGdyJQCAE2EE\ngnKsDLWurJi0w2azmVwVgLpITU3Vs88+G3oRNORYseeX3wAAsBR7wtHAsuJeG+YjsAQiUMVTH3tC\njMmVAABOhCv7kAKlHknSHXfcoX79+plcEYD6cMcdd6hv376SJM+uInkPlJpcEQDgeNkSaGFpRQSW\nQAQ6GljG/sqeAACrCJb75FwTGt8uJSXlaIssABEvJiZGL774Yvh12fLdMoKGiRUBAI6XzW6TLT7U\nGIjA0joILIEI4/P5VFoaempvI7AEgIjh+H6fDG9AkvTYY4+pXbt2JlcEoD5dcsklGjlypCTJn+9S\n+ZbDJlcEADheFeNYElhaB4ElEGGKiorCy5UHBwYAWJf3YJnKN+VJkjp27BieVRhAdJk8ebLi4kJj\njDtW7lGw3GdyRQCA41HRGIgxLK2DwBKIMJWf+NAlHACszwgEVfZtTvj1//3f/yk5OdnEigA0lJNO\nOkmPP/64JMnwBFS2fLfJFQEAjkfFvTUtLK2DwBKIMJW/QG20sAQAy3NtOCh/Ybkk6aqrrgp3GQUQ\nnZ544gn16NFDkuTeViDPvhKTKwIA/JqK3otOp1Mej8fkaiARWAIRhxaWABA5AqVuOX4ITbSTmpqq\nV155xeSKADS0xMRE/fOf/wy/Lvs2R4Y/aGJFAIBfU3l+iMrDsME8BJZAhKk8pgaT7gCAdRmGodKl\nu6QjQcWf/vQndezY0dyiADSKoUOH6pZbbpEkBUo9cq49YHJFAIBfUrkxEONYWgOBJRBhqrSwpEs4\nAFiWZ2ehvHtDXUHPPPNM3X///SZXBKAxvfjii8rMzJQkOdcdkL+o3OSKAAA1sSXEhJcZx9IaCCyB\nCEOXcACwvqDHr7LvQpNt2O12vfbaa4qN5TsbaEpatWqlv/71r6EXQUOl3+bIMAxziwIAVKtyYyAC\nS2sgsAQiTJVJdwgsAcCSHN/vU9DlkyTdf//9Ovvss02uCIAZxowZo4EDB0qSfLllcm/NN7kiAEB1\n6BJuPQSWQIRxOp3hZVscpzAAWI0vz6Hynw5Jktq1a6c//elPJlcEwCw/b2FdtmKPguU+k6sCAPyc\nLe5ol3CXy2ViJahA2gFEmEAgEF622WwmVgIA+DkjaKh0SU749f/+7/8qPT3dxIoAmO3UU0/Vo48+\nKkky3H6VrdhjckUAgGNUurWufM8N8xBYAhGmypcneSUAWIor+6D8BaGn8ldccYWuvvpqkysCYAXj\nx49X165dJUnurfnyHig1uSIAQBWVGgMRWFoDgSUQYaoGliSWAGAVgTKPHN/vkyQlJyfr//7v/2gJ\nD0BS6Dvh1VdfDb8u/TZHRiBoYkUAgMpsBJaWQ2AJRBhaWAKA9RiGodJluyR/KICYNGmSOnfubG5R\nACxl+PDhuuGGGyRJgWK3nOsOmFwRACCsUjpGYGkNBJZAhAl/edoYwxIArMK9LV/e3cWSpL59++rB\nBx80tyAAlvTSSy8pIyNDkuRcc0C+fOevvAMA0ChoYWk5BJZAhDkaWBJWAoAVBBwelS3bLUmKiYnR\nlClTFBcXZ3JVAKyobdu2+tvf/hZ6ETRUumgHXcMBwAoILC2HwBKIMJVbWAIAzGUYhkoX75ThDX03\njx8/XmeffbbJVQGwsjvvvFOXX365JMlfWC7H6n0mVwQAsDFLuOUQWAIRpuLLk+7gAGC+8p8Oybs/\nNNvvWWedpSeffNLkigBYnc1m0xtvvKGsrCxJkmt9rrwHy0yuCgCaOFpYWg6BJRBhwl+edgJLADCT\nv8StspV7JUkJCQmaOnUqXcEBHJe2bdvqn//8Z+iFoVDXcB83yABgGjuBpdUQWAIRhi7hAGA+48jY\ncxWzgv/5z3/WKaecYnJVACLJb3/7W914442SpECpR2Ur9phcEQA0YXQJtxwCSyDCMOkOAJjPtT5X\nvkMOSdJFF12khx56yNyCAESkf/zjH2rbtq0kqXxjnjz7SkyuCACaJhtdwi2HwBKIMIxhCQDm8hW4\nwpNkpKam6t///rfsdi6pAJy4rKwsTZkyJfy6dPEOBT1+EysCgCaKFpaWw9U1EGEqgkrDMEyuBACa\nHiMQDHUFD4a+g1988UV17drV5KoARLIRI0borrvukiQFnT6VLdttckUA0LTROMgaCCyBCJOWliZJ\nMo6MmwYAaDzOH/bLX+CSJF122WUaO3asyRUBiAZ/+9vfwg8/3Nvy5d5ZaHJFANC0VJ74rOKeG+Yi\nsAQiTPjL0x+UEaSVJQA0Fu/BMjnXHZAkZWZmasqUKTyBB1Av0tLS9O9//zv8nVL6bY4CLp/JVQFA\n02F4jzYIIrC0BgJLIMJU/vKs/BQIANBwDF9ApYt3SkeeE7366qtq166duUUBiCoXXXSRHn74YUmS\n4far7NschgACgEYSpIWl5RBYAhGGwBIAGl/Zyr0KlLglSb/97W914403mlwRgGj03HPPqXfv3pIk\nz64iubfmm1wRADQNhpfA0moILIEIQ2AJAI3LvatQ5T8dkiS1adNGr776qskVAYhWiYmJmjp1qmJi\nYiRJZUt3yV9cbnJVABD9GMPSeggsgQhTJbD0MvEOADSkQJlHpYt2hl+//fbbat68uYkVAYh2Z599\ntiZNmiQpNMliydfbmWwRABoYgaX1EFgCEabyl2eQFpYA0GCMQFAl87eFuwg99thjGj58uMlVAWgK\nHn/8cQ0dOlSS5C90qey73SZXBADRjcDSeggsgQhTtYUlgSUANBTHqr3y5TklSQMHDtSf/vQnkysC\n0FTExMTovffeU5s2bSRJ5ZvyVL6d8SwBoKEEmSXccggsgQiTnp4eXmYMSwBoGJ5dRXL9eFCSlJWV\npf/85z+Ki4szuSoATUnr1q31/vvvy24P3bKVLclhPEsAaCCV760r33PDPASWQIRh0h0AaFiBMo9K\nFu8Iv546dao6duxoYkUAmqqLL75YEyZMkCQZvqBK5jOeJQA0BLqEWw+BJRBhCCwBoOGExq3cLsMT\n+n599NFHdfnll5tcFYCm7Mknn9Qll1wiSfIXuFS2nPEsAaC+VQy3ZrPZlJKSYnI1kAgsgYhTZdId\nZgkHgHrl+H6ffHkOSdJ5552n5557zuSKADR1MTExmjZtmlq3bi1JKt+YJ/f2ApOrAoDoUtEYKDU1\nVTabzeRqIBFYAhEnMzMzvGy4fSZWAgDRxbO7SK71uZJC37XTp09n3EoAltCmTRtNmzYtfBNdumSn\n/CVuk6sCgOgR9PglSc2aNTO3EIQRWAIRpkWLFkpISJAkBZxek6sBgOgQcHhUsmhn+PU777yjTp06\nmVgRAFQ1ZMgQPf3005IqxrPcxniWAFBPAo7QvTXXf9YRa3YB0WrHjh3avn27vF6vOnXqpNNPP71B\nmhXX5jhr167Vli1bfvWzk5KSNGrUqPoqFfXEZrOpU6dO2rZtW/hLFQBQe0fHrQw9WR83bpyuvPJK\nk6sCgGM99dRTWrJkiRYtWiR/fmg8y/QLu5pdFgBENMMXkOEOXQcSWFoHgWU9W7ZsmR588EH98MMP\nVdZ37NhREydO1J133mn6cd555x29/PLLv3qM1q1bE1haVEVgGXR4ZBgGY2wAQB04Vu+T71Bo3MoB\nAwbo+eefN7kiAKhexXiWZ5xxhvLy8lS+MU/x7dKV2L252aUBQMSq3BCIwNI6CCzr0ccff6zrr79e\nwWBQ8fHxuuCCC5SYmKgVK1Zo7969GjNmjDZt2qTJkydb4jhJSUkaOXJkjdsZu8G6Kr5EDV9Qhjcg\nWwKnMgDUhjunUK51oXErmzVrpg8++IBxKwFYWtu2bTVt2jRdeumlMgxDpd/sVGzzZMU2SzK7NACI\nSAGHJ7xMYGkdpBz1ZM+ePbr11lsVDAbVp08fzZkzRx07dpQkuVwu3XHHHfroo4/0wgsvaODAgbrq\nqqtMP05WVpamT59eqzpgrs6dO4eXA2Ue2QksAeCE+YvKVbo4NG5lfHy8/v3vf1f5fgUAqxo6dKjG\njx+vP/3pTzJ8QRXP26qsq07lmhAAaqFyC0uuBa2DSXfqyTPPPKPy8nLFxsZqxowZ4RBRkpKTk/XO\nO++oW7dukqQ//vGPMgzD0seBtVV+6sM4lgBw4oIev4rnbZXhDUiSHnnkEYZBARBRJkyYoEsvvVSS\nFCh2q2ThDhlBrv0B4EQF6RJuSQSW9cDj8ejDDz+UJI0cOVInnXTSMfskJSXpvvvukyRt3rxZq1ev\ntuxxYH2Vv0SDlZqvAwB+nRE0VDJ/uwIlbknS5ZdfrmeeecbkqgDgxMTExGj69Onq0aOHJMm7p1iO\n7/eaXBUARB66hFsTgWU9WLp0qcrKyiRJl112WY37DR8+PLz85ZdfWvY4sD5aWAJA7TlW7pF3X4kk\n6eSTT9a0adMUExNjclUAcOIyMzP16aefKi0tTZLkWper8u35JlcFAJGl4p46PT1dGRkZJleDCgSW\n9WDDhg3h5X79+tW4X+/evZWYmHjMe8w8zu7duzV37lzNmjVL33zzjYqKik64LjS+Dh06hJcDtLAE\ngONWvvWwXD8elCRlZGTok08+4cIUQETr3bu33n//fdlsNklS6eKd8h12mlwVAESOil6LtK60FgLL\nerBjx47w8i/9A7fZbOExJ7dv3276cfbv368uXbrosssu0zXXXKPBgwerefPmuvjii7Vo0aITrg+N\nJykpSa1atZJUdbwNAEDNfHkOlS7JkSTZ7XZ98MEH1Q6vAgCR5oorrtBzzz0XehEwVDxvqwIun7lF\nAUAEMAwj3MKSwNJaCCzrQUlJSXi5WbNmv7hvRSuO0tJS04+TkZGhfv36aeTIkRo+fLjatWsnwzC0\nePFiDRkyRH/5y19OuEZJKioqqvGnuLi4Vp+JY1V8mdLCEgB+XcDpVfG8rVIgNCHFX//6Vw0bNszk\nqgCg/jz++OO68cYbJUlBp1clX2+VEQiaXBUAWFuw3CcdmbCMwNJaYs0uIBq4XC5JoZaNcXFxv7hv\nUlKSJMnpPPFuGvV1nEsuuUTXXnutBg4cKLv9aGZtGIY+/fRT3XPPPTp06JD++Mc/qlevXrr66qtP\nqM6srKwT2h+106lTJ61evVpBp09GIChbDM8fAKA6hj+okq+2KniktdGtt96qcePGmVwVANQvm82m\nN998U1u3btWaNWvkO+hQ2dJdSruoa7i7OACgqkDZ0QZAFT1VYQ1NKrD8/vvvq3Srro2LLrpI7dq1\nq7IuPj5e0pGmxIHALw7c7/WGmhonJCSc8LHr6zgjR46s9j02m02jRo1Sjx49dPbZZ8vtduuJJ544\n4cASjePkk08OL/uLyhXXIsXEagDAmgzDUOm3OfLlhR7gnXPOOXr99de5eQcQlZKTkzVr1iydc845\nysvLU/nmw4ptnqzk09qYXRoAWJK/sDy83Lt3bxMrwc81qcDytdde05tvvlmnz/jss8+OCSwrZuWT\nQq0gK7/+uYoWj6mpqSd87MY6zqmnnqrbbrtNb7zxhjZv3qxt27apZ8+ex/3+wsLCGrcVFxerW7du\nJ1wTjnXGGWeEl/35LgJLAKiGa8NBubeGZsxt27atZs2aFe6FAADRqFOnTpo5c6YuueQS+Xw+lX23\nW7GZSYpvzwRjAPBz/vyjvVIr32PDfE0qsOzfv78cDkedPqN9+/bHrKs8Y/O+fft+MZXft2+fpNo1\nNW6s40jSwIED9cYbb0gKTdxzIoFlZmZmrY6JE1P5y9RX4FSSWppXDABYkGdvsRwr9kgK9VL4+OOP\nq/07DgDR5oILLtA//vEP3X333ZIhFX+9XVnXnKrY9ESzSwMAS/EXhIbeS09PV5cuXcwtBlU0qcDy\n7rvvDv3RrmennnpqeHnTpk01BomHDh0KTzpzyimnWPY4UtWu5BXdy2Et3bt3V2pqqhwOh/z5LrPL\nAQBL8Ze4VTJ/uxQaQ12vvfaazj33XHOLAoBGdNddd2n9+vX6xz/+IcPjV8m8rcocdars8TUPKwUA\nTYkRNMKB5RlnnMGQQRbDLB314IILLghPXrN48eIa96u8bdCgQZY9jiRt3rw5vNy2bdtafQYalt1u\nV9++fSVJ/gKnDMMwuSIAsIZguU/FX2yW4Q1Ikh566CHdcccd5hYFACZ46aWXdPHFF0sKjdNW8vU2\nZg4HgCMCpW4Z/tB3Yr9+/UyuBj9HYFkPWrVqFQ4G33///RpnAJ8yZYqkUFPjYcOGWfY45eXlevvt\ntyVJGRkZnLgWVtEt3PAFq8xuBgBNleELqOjLLQqUhr4TL730Uk2ePNnkqgDAHHFxcfrwww/DY8h7\n95WodEkOD7oBQKrSU5HxK62HwLKejB8/XpJUUFCgBx544JiLgDfeeEPz58+XJD3yyCNKTDx2/Jg1\na9Zo+vTpmj59uoqKihrkOPv27VN+fn6Nv0dJSYmuvfZa7dkTGvPr97//veLi4mrcH+b6+cQ7ANCU\nGUFDxfO3y3849ECvX79+mjFjhmJjm9QIOABQRYsWLTR37ly1aNFCkuTemi/n6n0mVwUA5vMVMOGO\nldkMHq/Vm/vuu0+vvvqqpNCkNTfeeKMSEhK0YMECffjhhzIMQwMGDNCiRYuqnaH0/vvv1z/+8Q9J\n0vfff6+zzz673o8zZcoU3XPPPTr//PPVv39/tWnTRq1bt5bH49G6des0ffr08CzfF198sb788ssq\n41nWVVFRkbKysiSFZhNngp66Wb16tc455xxJUsqZ7ZR6Tu0mWQKASGcYhsqW5Kh882FJUpcuXbR8\n+XK1adPG5MoAwBpWrVqliy++WC5X6CF32oVdlHxKa5OrAgDzFH2xWd69JYqLi5PD4VB8fLzZJUW0\n+s57aHJQj1555RWlpaVp8uTJWrZsmZYtW1Zl+5VXXqm333672rCysY7TsWNHtWrVSkuXLtXSpUur\n/fzk5GQ98MADmjRpUr2Glah/p512mmJiYhQIBOSjhSWAJsy5Zn84rMzKytLcuXMJKwGgkv79++uD\nDz7QqFGjFAwGVbZ0l+zJ8UrsQgMCAE1TRS/FU045hbDSgmhh2QB2796tGTNmaNu2bfL5fOrYsaMu\nv/zycEu4mrz99tuaN2+eJOnPf/5zeKyZ+j6OYRhat26dli1bpv379+vgwYOy2+1q2bKlzjzzTA0b\nNkwZGRkn9ksfJ1pY1r8+ffooOztb9pR4tbyV8UYBND3lm/NU+k2OJCkxMVELFizQ+eefb3JVAGBN\nb7zxhu6+++7Qi1i7Mq84WfGt08wtCgAaWcDlVf67ayVJd9xxR3geD9Refec9BJZoVASW9e+2227T\ne++9J0lqefuZsicx5iiApsOzp1jFc7dIhmS32zVz5kxdddVVZpcFAJY2ceJETZo0SZJkS4xV1qhT\nFNusbr3AACCSePYUq/jLLZKkv//973rwwQdNrijy1Xfew6Q7QISrPDiwL7/6meMBIBr58hwq/nqb\ndOTR6//93/8RVgLAcZgwYYLGjBkjSTLcfhV/sUUBl9fkqgCg8fjzmXDH6ggsgQg3YMCA8LL3QJmJ\nlQBA4/GXuFX05RbJH5QkPfHEE7r33ntNrgoAIoPNZtM///lPjRgxQpIUKPOo+MstCnoDJlcGAI3D\ne6BUkhQTE6MzzzzT5GpQHQJLIMINGDBAqampkiTv/hKTqwGAhhcs96n4i80y3H5J0u23365nn33W\n5KoAILLExcXpgw8+0Nlnny0pNPlEydfbZASCJlcGAA3L8AflPRhq7HPuuecqLY1xfK2IwBKIcHFx\ncRo0aJAkyX/YqaDHb3JFANBwDF9ARXO3KFDqkSRdeumlmjJlimw2m8mVAUDkSU1N1Zw5c9S9e3dJ\nkndfiUqX5IhpDgBEM+/BMikQ+p4bOnSoydWgJgSWQBSo/CXr3V9qYiUA0HCMQFDF87fLnxcac6hf\nv36aMWOG4uKYbAwAaqtVq1aaO3euWrZsKUlyb82X8/t9JlcFAA2n8j0zgaV1EVgCUaBqYEm3cADR\nxwgaKlm4Q949xZKkLl266IsvvqALDwDUgx49eujzzz9XcnKyJMm59oCcaw+YXBUANIyKe+bU1NQq\nc0LAWggsgShw6qmnqnXr1pJoYQkg+hiGodLFO+XZWShJatmypebOnas2bdqYXBkARI/+/fvro48+\nUmxsrCTJsWqvnD/mmlwVANSvoMcv/+FQb51BgwbRU8fCCCyBKGCz2cKtLAMlbgXKPCZXBAD1wzAM\nlS3JkXtbviQpKytL8+fPV69evUyuDACiz4gRIzR9+nTFxMRIkhzL98j10yGTqwKA+kN38MhBYAlE\nCbqFA4g2hmGobNlulW8+LElKT0/XV199pdNPP93kygAgel177bWaOnVqeDKzsqW7wt/DABDpKt8r\nE1haG4ElECWGDBkSXqZbOIBIZxiGHCv2qvxIy57U1FTNnTtXZ511lsmVAUD0u/nmm/Xmm2+GX5d+\ns1PlR1q6A0Akq7hXbt26tU499VSTq8EvIbAEokTHjh110kknSQo9NTIMw+SKAKD2nKv3y3Vk7LSk\npCTNmTNH5513nslVAUDTMXr0aP3zn/8Mvy5dtEPuI2MJA0AkCpR5FChxSwo1+KloSQ5rIrAEokhF\nk/ZguV/+wnKTqwGA2nGs2S/nmv2SpISEBH366ae66KKLTK4KAJqe//f//p9eeuml0AtDKlmwXZ5d\nReYWBQC1RHfwyEJgCUSRyl+6nt1cTAKIPM71uXJ+v0+SFBcXp48//pgLSgAw0UMPPaS//OUvoRdB\nQ8Vfb5Nnb7GpNQFAbXh2F4eXKw+pBmsisASiyKWXXqrk5GRJknt7gcnVAMCJcWUflGPFHklSTEyM\nPvjgA40YMcLkqgAAjz32mCZMmBB6ETRUPG+rvAcYMx1A5Ah6/PLsKZYknXXWWerUqZO5BeFXEVgC\nUSQlJUWjRo2SJAWKyuUrcJlcEQAcH9emPJUt2y1JstvtmjZtmq6++mqTqwIAVJgwYYIee+yx0IuA\noeIvt8h7sMzcogDgOHlyiqRgaJ6Hm2++2eRqcDwILIEoc9NNN4WX3duZzRGA9ZVvPayyJTmSJJvN\nprfffls33HCDyVUBACqz2Wx6/vnn9eCDD0qSDH9QxV9sli/PYXJlAPDrKu6NbTYb15kRgsASiDLD\nhg1TZmamJMm9o5DZwgFYWvmWwypdvDP8+l//+pduv/12EysCANTEZrPppZde0v/7f/9PkmT4giqa\ns5mWlgAsLeDyhoexuOiii9S+fXuTK8LxILAEokx8fLyuvfZaSVKwzCPfIZ56A7AmV/bBUFh55LnK\nK6+8orvvvtvcogAAv8hms+kf//iHRo8eLUkyvAEVz9ksz76SX3knAJjDs7MwfL1Jd/DIQWAJRKHK\nX8JMvgPAipxr9ofHrJSkV199VQ888ICJFQEAjpfdbtcbb7wRfshk+IMq/nKL3LuKTK4MAI7l3ha6\nJ46NjQ037oH1EVgCUeiiiy5S27ZtJUmenQUygnQLB2ANhmGobOUeOb7fJyl00zt16lTde++9JlcG\nADgRMTEx+te//qVx48aFVgQNlXy1VeWMoQ7AQgKl7vBYu8OHD1fz5s1NrgjHi8ASiEIxMTHhgYSD\n5f7weB0AYCbDMFS2dJdc63IlSXFxcfroo4902223mVwZAKA2bDabJk+erIkTJ4ZWGFLpgh1ybcoz\ntS4AqODecbTHYeUJamF9BJZAlKoyW/g2nnQDMJcRNFS6eKfKN4ZuYpOSkvTZZ5/pmmuuMbkyAEBd\n2Gw2TZgwQX/729/C68qW5Mj5Y66JVQFASMUQaUlJSRo5cqTJ1eBEEFgCUeqcc85R9+7dJUmeXUUy\n/EGTKwLQVBmBoErmb5N7a+jhSVpamubNm6dhw4aZXBkAoL784Q9/0Ouvvy6bzSZJcizfI8fqfTIM\nhiYCYA5/oUv+wnJJ0qhRo5SammpyRTgRBJZAlLLZbOFWloY3IPfOQpMrAtAUGb6AiudulScnNBFD\nVlaWFi5cqAsvvNDkygAA9e2uu+7StGnTFBMTI0ly/rBfjhV7CC0BmKJ80+HwMt3BIw+BJRDFRo8e\nLbs9dJq7NuRysQigUQW9fhV9sUXefSWSpDZt2uibb77R2WefbXJlAICGctNNN+njjz9WfHy8JMn1\n40GVLclhEkgAjSro8at8S2goonbt2mn48OEmV4QTRWAJRLFu3bpp1KhRkiR/vku+3DKTKwLQVATd\nPhV9vlm+g6Hvnc6dO+vbb7/VaaedZnJlAICGNnLkSM2ZM0fJycmSpPLNh1W6aIeMAEMUAWgc5VsO\ny/CFvnPuv//+8EMURA4CSyDK/eEPfwgvuzYcNLESAE1FwOlV4aeb5D/slCSddNJJ+vbbb9WjRw+T\nKwMANJahQ4fq66+/VkZGhqTQxBfFX29jXHUADc4IGuF736SkJN1zzz0mV4TaILAEotzAgQPD3S89\nu4rkL3GbXBGAaOYvdKlw9k8KFIUGOD/99NO1ZMkSdezY0eTKAACN7fzzz9eiRYvUokULSZJ3d7GK\n5mxSsNxncmUAoplnV6GCDq8k6Xe/+52ysrJMrgi1QWAJRDmbzaaHH344/NqVTStLAA3Du79EhZ9s\nDF8gDhgwQIsWLVLr1q1NrgwAYJZ+/fppyZIlat++vSTJd9Chwk828hAdQINx/Xj0nvehhx4yrxDU\nCYEl0ARcf/314YtE9+bDCnr8JlcEINqUbzmsoi+2yPAGJEmjRo3SwoULeaINAFDv3r21YsUKnX76\n6ZKkQIlbhbN/kvcg46sDqF++Qw75DjkkSZdffrl69eplckWoLQJLoAmIi4vT/fffL0ky/EGVbz5s\nckUAooVhGHKs3qfSxTulIzPAPvjgg5o5c2Z4sgUAADp06KBvv/1Wl156qSTJcPtV9PkmuXcUmFwZ\ngGji3JAbXq7c0xCRh8ASaCLuvvvucHjgyj4o40iwAAC1ZQSCKl20U84f9ksKDUHx97//XX//+98V\nExNjcnUAAKtJT0/X559/rrFjx4ZWBAyVzN8u57oDMgyuTQHUTaDMI8/OQkmhcdQvueQSkytCXRBY\nAk1EVlaW7rjjDklS0OGVJ6fQ3IIARLSgx6+iL7bIvS1fUmgGxlmzZunBBx80uTIAgJXFxcXp9ddf\n15///OfwOsfKvSpbuosH6gDqxPXTIenI18hDDz0km81mbkGoEwJLoAmpHCQ41+fyJBtArQTKPCqc\n/ZN8B0olSa1atdI333yjUaNGmVwZACAS2Gw2/fGPf9T777+v+Ph4SVL5xjwVz9uqoC9gcnUAIlHQ\n41f5pjxJoWvTm266yeSKUFcElkATctJJJ2nkyJGSJP9hJ60sAZww32GHCmf9pEBxaHbXiokUzjnn\nHJMrAwBEmptuuknz589XZmamJMm7p1hFn25UwOk1uTIAkca57kB48sf7779fiYmJJleEuiKwBJqY\nZ599Ntw03rFyr4xA0OSKAEQK964iFX66ScFynyRp8ODBWrZsmbp27WpyZQCASHXhhRdq+fLl6tat\nmyTJn+9S4ayf5CtwmVwZgEgRKPPIteGgJKlly5Z66KGHzC0I9YLAEmhi+vTpo9/97neSpECpJ9xs\nHgB+iSv7oErmbZX8oYcct956q+bOnRtuFQMAQG316tVLy5cv14ABAyRJQadXRZ/8JM++EpMrAxAJ\nHKv3SYHQcGcTJ05UWlqayRWhPhBYAk3QM888E24i7/hhv4Jev8kVAbAqIxBU6ZIclS3bHV739NNP\na+rUqUpISDCxMgBANGnVqpUWLVqka665RpJk+IIq/mKznD8y7jqAmvkKnHJvDU0C2bNnT911110m\nV4T6QmAJNEEdO3YMN5M33H651ueaWxAASwo4vSr6dFO4JXZsbKzefvttTZo0iVkXAQD1LikpSR99\n9JHGjRsXWmFIjuV7VLpwhwwm4wFQDcfKveHl559/XnFxcSZWg/pEYAk0UY8//riaN28uSXL+eJDB\nzQFU4c0tVeHMbPnyHJJCLV/mz5+vO+64w9zCAABRzW6364UXXtCUKVPCM4i7txeo8JON8pe6Ta4O\ngJV49pXIuzc0dMS5554bbqGN6EBgCTRRGRkZGj9+fOiFPyjn6n3mFgTAEgzDkGvDQRV9vjk8uU7/\n/v31ww8/aNCgQSZXBwBoKsaMGaNvv/1WHTp0kCT5C1wq/Dhbnr3F5hYGwBIMw5Bj5Z7w68mTJ9MD\nKMoQWAJN2L333hue3bd8y2H5i5iNEWjKDF9ApYt2quy73VIwNF7Y2LFjtWTJkvANIwAAjeXnD8wM\nT0DFX2yRc+1+xrUEmjj39gL580P3r1dddZUuuOACkytCfSOwBJqwhIQE/fnPfw69MKSySuN/AGha\nAqVuFX6yUe5toUHL4+Pj9frrr+uNN95gch0AgGlatWqlr7/+Wg8//HB4nWPVPpV8tU1BL+NaAk2R\n4Q/KsSp07xoTE6Pnn3/e5IrQEAgsgSbut7/9rc4++2xJknd3sTx7is0tCECj8+wtVsHHP8lfEHpK\n3b59ey1ZsoRZFgEAlhAXF6cXX3xR06ZNU1JSkiTJs6tIhbOy5S8uN7k6AI3N+WOugo7QHAx33XWX\nTj75ZJMrQkMgsASauIqBzSuULslR0OM3sSIAjcUwDDnXHlDxl1tkHDnvL7roIv3www8aMGCAydUB\nAFDVzTffrOXLl4eHNAoUu1X4cbbcOYUmVwagsfgLXXL+sF+SlJaWpgkTJphcERoKgSUADRo0SHff\nfbckKej0yrFiz6+8A0CkC3oDKvl6W6g7zZFhwB588EHNnz9frVu3Nrc4AABq0LdvX61evVrDhg2T\nJBm+oEq+Cv09M4KMawlEMyMQVMmineGx1l988UW1adPG5KrQUAgsAUgKzarWqVMnSVL55sPMwAhE\nMX9RuQpnZcuTUyRJSkpK0rvvvqu///3viouLM7k6AAB+WVZWlubMmaMnn3wyvM659oCK525RsNxn\nYmUAGpJrfa78+U5J0m9+8xuNGTPG5IrQkAgsAUiS0tPTNWXKlPDr0iU5CnrpGg5EE8Mw5NqYp4KP\nsxUodkuSunbtqu+++0633nqrydUBAHD8YmJi9Oyzz2rWrFlKS0uTJHn3lqhgxgZ595eYXB2A+uYv\ndMlRqSv4lClTZLPZTK4KDYnAEkDYb37zm/AkG0GHV44VzBoORIug26+Sr7ep7NscyR+UJA0bNkyr\nV6/WGWecYW5xAADU0lVXXaVVq1apd+/ekqSgy6eizzerbOUeGYGgydUBqA9G0FDJ4qNdwV944YVw\n70BELwJLAFW88MIL6tixoySpfFOePPt4Qg1EOu+BUhXM+DHcBTwuLk4vvPCCvvjiC2VlZZlcHQAA\ndXPyySdr9erV4THZJcm1LleFn2yUv8RtYmUA6oNrfa78h0NdwYcOHRpuZIPoRmAJoIr09HS98cYb\n4del3+ykazgQoYxAUI5Ve1X02SYFnaExvXr27Knly5dr3Lhxstu5DAAARIfk5GS99tprmjlzpjIz\nMyVJ/sNOFc7coPKth2UYTMgDRCJ/kUuO1fskSampqXQFb0K4UwFwjGHDhmns2LGS6BoORCp/qVtF\nn26Sc+2B8LoxY8ZozZo1Ouuss0ysDACAhnPNNddo/fr1GjRokKTQLOKli3aqdOEOBT08hAciSXVd\nwTt37mxyVWgsBJYAqvXCCy+oQ4cOko50Dd9dZHJFAI5X+bZ8Fc7YIF+eQ5KUkZGhDz74QFOmTFFq\naqrJ1QEA0LA6duyoBQsW6LnnnlNMTIwkyb29QAUzs+U9WGZydQCOl3PNfvnzQl3BL7nkkirDPiD6\nEVgCqFZGRkaVruElC3fIX1xuYkUAfk3QG1DJwh0qXbhDhi800cDAgQO1fv16/fa3vzW5OgAAGk9M\nTIyeeOIJLV26VF27dpUkBcs8Kvp0oxxr9ssI0kUcsDLPriI5j8wKnpqaqjfffJOu4E0MgSWAGg0f\nPlyPP/64JMnwBlQ8byvjWQIW5ctzqHDmBrm35UuS7Ha7Jk6cqMWLF9N1BgDQZJ177rlau3atbr75\n5tAKQ3J+v09Fn29SwOExtzgA1fIXlatk0Y7w67fffltdunQxryCYgsASwC969tlnNXz4cElSoNit\n0kU7GbQcsBAjEJRjzX4VfrJRgdLQjVenTp20ZMkSTZgwQbGxsSZXCACAuTIyMjRt2jRNnTo1PDSK\nL7dMBTM2yL29gGtbwEKCHr+Kv9oqwxuQJD3xxBO67rrrTK4KZiCwBPCLYmJi9P7776t79+6SqjbN\nB2AuX75ThbN/kvP7feHByH/7299q/fr1GjhwoMnVAQBgLbfddpvWrVun/v37S5IMT0AlC7arZN5W\nBZxek6sDYBiGShbtUKDYLUm67LLL9Mwzz5hcFcxCYAngV2VmZuqTTz5RSkqKJMn5w365dzEJD2AW\nwx+UY9VeFX6cLX++S5KUlpamt956S9OnT1ezZs3MLRAAAIvq3r27li5dqieeeEJ2e+h22LO7WAUf\n/qjyzXm0tgRM5Fy9X97dxZKknj176v333w9PnIWmh8ASwHE59dRTNXXq1PDr0oXb5S9iEh6gsXkP\nlqlg5gY51x6QjtxTXXbZZfrpp580evRoBiMHAOBXxMXF6bnnntOKFSvUp08fSaHx2ku/yVHxnM0K\nlLpNrhBoetw5hXKuOTrJzuzZs3kI38QRWAI4btdcc43Gjx8vSTJ8wdAkPB4m4QEaQ9AXUOmyXSr6\nZGO4m0xWVpbeffddzZkzRx07djS5QgAAIss555yj1atXa9KkSYqLi5MkefeXKv+jDXJtOMhM4kAj\n8Re5VFppkp2pU6fqlFNOMbEiWAGBJYATMmnSJF1++eWSpECJWyULd3AxBzQwz74SFXy0QeXZh8Lr\nrr/+em3cuFG33norrSoBAKil+Ph4Pf3001qzZk14bEv5gyr7breKPt1IjyKggQXdfhXP2ybDF5Qk\nPfXUU7r66qtNrgpWQGAJ4ITY7Xa99957OumkkyRJ3j3FKl3MzOFAQwh6/CpZvFPFczYrWBaaAbxN\nmzb6+OOP9eGHH6p169YmVwgAQHQ47bTT9N133+mFF15QYmKiJMl3yKGCGRvkWLNfRiBocoVA9Al6\n/Cr6YrMCJaHeQ1dccYUmTpxoblGwDAJLACesWbNmmj17trKysiRJ7m35KluSQ2gJ1CP3rkIVfPij\n3FsOh9eNHj1aGzdu5KkzAAANICYmRuPGjdOGDRs0aNCg0MqgIef3+1Q46yf58p3mFghEkaAvoOK5\nW+Q/HDqvTjvtNL333nvhybAA/iUAqJXevXvrq6++UkZGhiSpfPNhlX23m9ASqKOAy6vi+dtUMm+b\ngi6fJKlz586aN2+e3nrrLWVmZppcIQAA0a1Hjx5auHCh/vWvfyktLU2S5C9wqfDjbJWt3CPDFzC5\nQiCyGf6giudule+gQ5LUq1cvzZ8/P3xvCUgElgDq4KyzztKXX36plJQUSVJ59iE5Vu4ltARqwQgE\n5Vyfq4Lp6+XZUShJstlseuCBB5Sdna1LL73U5AoBAGg67Ha77rnnHv30008aMWJEaKUhudblKv/D\nH+XeUcA1L1ALRiA0eavvQKkkqVu3blqwYAFDHeEYBJYA6uS8887TnDlzlJSUJElyrc+Vc/V+k6sC\nIotnT7EKPtogx4o94QHHe/XqpSVLluiVV15RamqqyRUCANA0dezYUZ9//rnee+89NW/eXJIUdHhV\nMn+7ij7bJF+By+QKgchhBIIqmb9d3n0lkkLn18KFC9W+fXuTK4MVEVgCqLNBgwZp9uzZio+PlyQ5\n1+yXc+0Bk6sCrM9f4lbRl1tU/OWW8GDjKSkp+stf/qL169frggsuMLlCAABgs9l0yy23aMuWLbr3\n3nvDY+z5cstUOHODSr/NUdDtM7lKwNqMoKGShTvk2VUkSWrbtq0WLlyozp07m1wZrIrAEkC9uPTS\nSzVjxgzFxsZKkhyr9sr5Y67JVQHWFPQGVLZyjwo+/FHePcXh9bfddpu2bt2qxx57TAkJCeYVCAAA\njtG8eXO9+uqrWrNmjS666KLQSkMq35in/Ok/yvXTIRlBuokDP2cYhkoX75RnZ2jYo5YtW2rBggXq\n0aOHyZXByggsAdSbK6+8Uv/5z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          }
        }
      ],
      "source": [
        "# parameters for the first nanodisk\n",
        "x0_1 = -px / 4\n",
        "y0_1 = 0\n",
        "alpha_1 = -alpha\n",
        "\n",
        "# parameters for the second nanodisk\n",
        "x0_2 = px / 4\n",
        "y0_2 = 0\n",
        "alpha_2 = alpha\n",
        "\n",
        "# create the nanodisk structures\n",
        "n = 100\n",
        "nanodisk_1 = td.Structure(\n",
        "    geometry=td.PolySlab(\n",
        "        vertices=ellipse_vertices(x0_1, y0_1, dx, dy, n, alpha_1), axis=2, slab_bounds=(0, h)\n",
        "    ),\n",
        "    medium=silicon,\n",
        ")\n",
        "\n",
        "nanodisk_2 = td.Structure(\n",
        "    geometry=td.PolySlab(\n",
        "        vertices=ellipse_vertices(x0_2, y0_2, dx, dy, n, alpha_2), axis=2, slab_bounds=(0, h)\n",
        "    ),\n",
        "    medium=silicon,\n",
        ")\n",
        "\n",
        "# plot the nanodisk structures to verify\n",
        "ax = nanodisk_1.plot(z=h / 2)\n",
        "nanodisk_2.plot(z=h / 2, ax=ax)\n",
        "ax.set_xlim(-px / 2, px / 2)\n",
        "ax.set_ylim(-py / 2, py / 2)\n",
        "plt.show()"
      ],
      "id": "ca1f40bf"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Create the Substrate and Monitor\n",
        "\n",
        "Next we create the Pyrex substrate as a simple\n",
        "[Box](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Box.html)."
      ],
      "id": "00ed3143-14e7-4c3f-bc2a-3ae92b12857e"
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [],
      "source": [
        "# create the substrate structure\n",
        "inf_eff = 1e2\n",
        "substrate = td.Structure(\n",
        "    geometry=td.Box.from_bounds(rmin=(-inf_eff, -inf_eff, -inf_eff), rmax=(inf_eff, inf_eff, 0)),\n",
        "    medium=pyrex,\n",
        ")"
      ],
      "id": "bbf2c9fd"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "To measure the transmission spectrum, we add a\n",
        "[FluxMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FluxMonitor.html)\n",
        "below the nanodisks."
      ],
      "id": "6edb4785-a6d6-4479-9955-fb2823ff38c4"
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [],
      "source": [
        "# create a flux monitor to measure the transmission spectrum\n",
        "monitor_z = -1  # monitor z position\n",
        "flux_monitor = td.FluxMonitor(\n",
        "    center=[0, 0, monitor_z], size=[td.inf, td.inf, 0], freqs=freqs, name=\"flux\"\n",
        ")"
      ],
      "id": "29bfcc91"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Create Simulation at Given Incident Angle\n",
        "\n",
        "To facilitate parameter sweeping of the incident angle of the plane\n",
        "wave, we first define a `make_sim(theta)` function that takes the\n",
        "incident angle as input and creates a tidy3d\n",
        "[Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html)\n",
        "object. In this function, we will create a\n",
        "[PlaneWave](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PlaneWave.html)\n",
        "source with `angle_theta` set to the incident angle. Importantly, we set\n",
        "`angular_spec=td.FixedAngleSpec()`, which means we will use the fixed\n",
        "angle plane wave source instead of a constant in-plane wavevector\n",
        "source. When this is used, the boundary condition in the $x$ and $y$\n",
        "directions needs to be periodic instead of bloch. In the $z$ direction,\n",
        "we will simply use the PML boundary. If the simulations diverge, we can\n",
        "use the absorber boundary condition instead. When the absorber is used,\n",
        "it’s recommended to use a larger number of layers to effectively\n",
        "minimize the undesired artificial reflection.\n",
        "\n",
        "To visualize the simulation setup, we create a dummy simulation and plot\n",
        "it in 3D."
      ],
      "id": "495fd0f8-4c77-4332-bbfd-889f4ea81d62"
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "\n",
              "    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"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\" ></div>\n",
              "    <script>\n",
              "        \n",
              "        /**\n",
              "        * Simulation Viewer Injector\n",
              "        *\n",
              "        * Monitors the document for elements being added in the form:\n",
              "        *\n",
              "        *    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"{...}\" />\n",
              "        *\n",
              "        * This script will then inject an iframe to the viewer application, and pass it the simulation data\n",
              "        * via the postMessage API on request. The script may be safely included multiple times, with only the\n",
              "        * configuration of the first started script (e.g. viewer URL) applying.\n",
              "        *\n",
              "        */\n",
              "        (function() {\n",
              "            const TARGET_CLASS = \"simulation-viewer\";\n",
              "            const ACTIVE_CLASS = \"simulation-viewer-active\";\n",
              "            const VIEWER_URL = \"https://tidy3d.simulation.cloud/simulation-viewer\";\n",
              "\n",
              "            class SimulationViewerInjector {\n",
              "                constructor() {\n",
              "                    for (var node of document.getElementsByClassName(TARGET_CLASS)) {\n",
              "                        this.injectViewer(node);\n",
              "                    }\n",
              "\n",
              "                    // Monitor for newly added nodes to the DOM\n",
              "                    this.observer = new MutationObserver(this.onMutations.bind(this));\n",
              "                    this.observer.observe(document.body, {childList: true, subtree: true});\n",
              "                }\n",
              "\n",
              "                onMutations(mutations) {\n",
              "                    for (var mutation of mutations) {\n",
              "                        if (mutation.type === 'childList') {\n",
              "                            /**\n",
              "                            * Have found that adding the element does not reliably trigger the mutation observer.\n",
              "                            * It may be the case that setting content with innerHTML does not trigger.\n",
              "                            *\n",
              "                            * It seems to be sufficient to re-scan the document for un-activated viewers\n",
              "                            * whenever an event occurs, as Jupyter triggers multiple events on cell evaluation.\n",
              "                            */\n",
              "                            var viewers = document.getElementsByClassName(TARGET_CLASS);\n",
              "                            for (var node of viewers) {\n",
              "                                this.injectViewer(node);\n",
              "                            }\n",
              "                        }\n",
              "                    }\n",
              "                }\n",
              "\n",
              "                injectViewer(node) {\n",
              "                    // (re-)check that this is a valid simulation container and has not already been injected\n",
              "                    if (node.classList.contains(TARGET_CLASS) && !node.classList.contains(ACTIVE_CLASS)) {\n",
              "                        // Mark node as injected, to prevent re-runs\n",
              "                        node.classList.add(ACTIVE_CLASS);\n",
              "\n",
              "                        var uuid;\n",
              "                        if (window.crypto && window.crypto.randomUUID) {\n",
              "                            uuid = window.crypto.randomUUID();\n",
              "                        } else {\n",
              "                            uuid = \"\" + Math.random();\n",
              "                        }\n",
              "\n",
              "                        var frame = document.createElement(\"iframe\");\n",
              "                        frame.width = node.dataset.width || 800;\n",
              "                        frame.height = node.dataset.height || 800;\n",
              "                        frame.style.cssText = `width:${frame.width}px;height:${frame.height}px;max-width:none;border:0;display:block`\n",
              "                        frame.src = VIEWER_URL + \"?uuid=\" + uuid;\n",
              "\n",
              "                        var postMessageToViewer;\n",
              "                        postMessageToViewer = event => {\n",
              "                            if(event.data.type === 'viewer' && event.data.uuid===uuid){\n",
              "                                frame.contentWindow.postMessage({ type: 'jupyter', uuid, value: node.dataset.simulation, fileType: 'hdf5'}, '*');\n",
              "\n",
              "                                // Run once only\n",
              "                                window.removeEventListener('message', postMessageToViewer);\n",
              "                            }\n",
              "                        };\n",
              "                        window.addEventListener(\n",
              "                            'message',\n",
              "                            postMessageToViewer,\n",
              "                            false\n",
              "                        );\n",
              "\n",
              "                        node.appendChild(frame);\n",
              "                    }\n",
              "                }\n",
              "            }\n",
              "\n",
              "            if (!window.simulationViewerInjector) {\n",
              "                window.simulationViewerInjector = new SimulationViewerInjector();\n",
              "            }\n",
              "        })();\n",
              "    \n",
              "    </script>\n",
              "    "
            ]
          }
        }
      ],
      "source": [
        "run_time = 1e-11  # simulation run time\n",
        "\n",
        "Lz = 3  # simulation domain size in z\n",
        "\n",
        "\n",
        "def make_sim(theta):\n",
        "    \"\"\"\n",
        "    Create a simulation with the plane wave incident at an angle theta\n",
        "\n",
        "    Parameter\n",
        "    ----------\n",
        "    theta : float\n",
        "        The incident angle of the plane wave\n",
        "\n",
        "    Returns\n",
        "    -------\n",
        "    sim : td.Simulation\n",
        "        A tidy3d simulation\n",
        "    \"\"\"\n",
        "\n",
        "    # create a plane wave source\n",
        "    source_z = 1  # source z position\n",
        "\n",
        "    # create an oblique plane wave source\n",
        "    plane_wave = td.PlaneWave(\n",
        "        center=[0, 0, source_z],\n",
        "        size=[td.inf, td.inf, 0],\n",
        "        source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
        "        direction=\"-\",\n",
        "        angle_theta=theta,\n",
        "        angular_spec=td.FixedAngleSpec(),\n",
        "    )\n",
        "\n",
        "    # construct simulation\n",
        "    sim = td.Simulation(\n",
        "        size=(px, py, Lz),\n",
        "        grid_spec=td.GridSpec.auto(min_steps_per_wvl=25, wavelength=lda0),\n",
        "        structures=[substrate, nanodisk_1, nanodisk_2],\n",
        "        sources=[plane_wave],\n",
        "        monitors=[flux_monitor],\n",
        "        run_time=run_time,\n",
        "        boundary_spec=td.BoundarySpec(\n",
        "            x=td.Boundary.periodic(),\n",
        "            y=td.Boundary.periodic(),\n",
        "            z=td.Boundary.pml(),\n",
        "        ),\n",
        "    )\n",
        "\n",
        "    return sim\n",
        "\n",
        "\n",
        "# create a dummy simulation for visualization\n",
        "sim = make_sim(theta=np.deg2rad(20))\n",
        "sim.plot_3d()"
      ],
      "id": "7af92014"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Before running any simulations, we can inspect the grid around the\n",
        "nanodisks to ensure it’s sufficiently fine. This is crucial to capture\n",
        "the accurate resonant behavior of the metasurface. In this case, we use\n",
        "the automatic nonuniform grid of 25 steps per wavelength, which results\n",
        "in about 10 nm minimal grid size."
      ],
      "id": "c823747e-1434-40d3-a745-8c769d5edd4d"
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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kup0FGvHDbyptxEDTdQBEAMvn18HFq3XwvdWSn0sHwL4s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\nf2g6DhB2/pxUZU8Zr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          }
        }
      ],
      "source": [
        "ax = sim.plot(z=h / 2)\n",
        "sim.plot_grid(z=h / 2, ax=ax, alpha=0)\n",
        "plt.show()"
      ],
      "id": "28c64fa1"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Parameter Sweeping the Incident Angle\n",
        "\n",
        "We now proceed with a parameter sweep of the incident angle ranging from\n",
        "0 to 16 degrees. For demonstration purposes, we conduct 17 simulations\n",
        "at 1-degree increments. However, to generate a smoother result, similar\n",
        "to Fig. 2 in the paper, a denser sampling of angles would be required.\n",
        "\n",
        "To perform the simulations in parallel, we construct a dictionary of\n",
        "simulations and subsequently create a\n",
        "[Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html)\n",
        "object."
      ],
      "id": "1b42cb92-5ec3-4180-ae33-96b9f62afd18"
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"e87865b2a89e43f7a03a53b07142d932\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:12:59 UTC </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span> tasks.                      \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:13:12 UTC </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5.072</span> for the whole batch.                \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after    \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>completion.                                                        \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"77c8a9d1a4274f628c2b79335d4a6ad8\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:15:34 UTC </span>Batch complete.                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        }
      ],
      "source": [
        "theta_list = np.linspace(0, 16, 17)  # theta values for the parameter sweep\n",
        "\n",
        "# create a dictionary of simulations\n",
        "sims = {f\"theta={theta:.1f}\": make_sim(np.deg2rad(theta)) for theta in theta_list}\n",
        "\n",
        "# create and run a batch of simulations\n",
        "batch = web.Batch(simulations=sims)\n",
        "batch_results = batch.run(path_dir=\"data\")"
      ],
      "id": "05a4cf6e"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "After the batch finished, we can check the actual cost of running the\n",
        "batch, which can often be significantly lower than the maximum cost due\n",
        "to early shutoff of the simulations."
      ],
      "id": "131157e0-eda6-4541-a227-b3432db31e83"
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:15:39 UTC </span>Total billed flex credit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.329</span>.                              \n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "real_cost = batch.real_cost()"
      ],
      "id": "31d53f05"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Extract and Visualize the Transmission Spectra\n",
        "\n",
        "To extract the transmission spectrum of from each simulation, we can do\n",
        "a quick list comprehension."
      ],
      "id": "c5335a6b-3294-4005-89e6-538b4d41fdd2"
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [],
      "source": [
        "T = np.array(\n",
        "    [np.abs(batch_results[f\"theta={theta:.1f}\"][\"flux\"].flux.values) for theta in theta_list]\n",
        ")"
      ],
      "id": "4a2e2b5d"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Next, we plot the transmission as a function of wavelength and incident\n",
        "angle as a false-color map. Here we can clearly see the dispersion of\n",
        "the electric dipole (ED) qBIC mode. Compared to Fig. 2(a) in the\n",
        "referenced paper, the qBIC feature in our results appears slightly less\n",
        "prominent. This discrepancy comes from the difference in the silicon\n",
        "refractive index used, which has a slightly higher loss in this notebook\n",
        "compared to that reported in the paper."
      ],
      "id": "aee82bd4-c132-4df6-9057-70dca685666f"
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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NnDhRefPlkyR9MHy4FeE6VKBgQX01b56yZUv81bVj2zZtWr/e5e3X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\nfHz4tQsAQEZEkgUAAMAFIiIiNH3iRNUqW1bdXnhBf+/f7/CYSlWraur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          }
        }
      ],
      "source": [
        "# plot the transmission as a false color image\n",
        "plt.pcolormesh(1e3 * ldas, theta_list, T, cmap=\"hot_r\", vmin=0, vmax=1)\n",
        "plt.xlabel(\"Wavelength (nm)\")\n",
        "plt.ylabel(\"Incident angle (degree)\")\n",
        "\n",
        "# add text label and arrow in the plot\n",
        "x_point = 840\n",
        "y_point = 8\n",
        "plt.annotate(\n",
        "    \"ED-qBIC\",\n",
        "    xy=(x_point, y_point),\n",
        "    xytext=(x_point - 100, y_point + 3),\n",
        "    arrowprops=dict(linewidth=2, edgecolor=\"white\", arrowstyle=\"->\"),\n",
        "    fontsize=20,\n",
        "    color=\"white\",\n",
        ")\n",
        "\n",
        "plt.colorbar()\n",
        "plt.show()"
      ],
      "id": "6c74c487"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Final Remarks\n",
        "\n",
        "This notebook aims to demonstrate how to perform broadband simulations\n",
        "with plane waves at a constant incident angle. It only explores one\n",
        "metasurface configuration and one polarization. Different geometries and\n",
        "polarizations can be studied in a similar fashion."
      ],
      "id": "3334faac-2caf-49e6-8e4e-f80f2eded2e5"
    }
  ],
  "nbformat": 4,
  "nbformat_minor": 5,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    }
  }
}