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      "source": [
        "# Advanced Gaussian sources\n",
        "\n",
        "It can often be tedious to create easily usable customized simulation\n",
        "objects from scratch, as there are various details to consider. For\n",
        "instance, if one wants to create an easily-usable beam source from\n",
        "scratch, one must create functionality to automatically interpret the\n",
        "source plane into field coordinates, handle conversion for polar and\n",
        "azimuthal angles, handle different direction specifications, etc. This\n",
        "all becomes much more complicated to build than Tidy3D’s natively\n",
        "supported Gaussian beam. <br><br> Fortunately, we can take advantage of\n",
        "the fact that Tidy3D is open source to create complex Gaussian sources\n",
        "without needing to consider any of these extraneous functionalities.\n",
        "Namely, we use the Tidy3D\n",
        "[BeamProfile](https://github.com/flexcompute/tidy3d/blob/develop/tidy3d/components/beam.py)\n",
        "class to handle all extra usability considerations, so we only need to\n",
        "define the scalar field profile for z being the propagation direction.\n",
        "The BeamProfile object will automatically rotate the field amplitudes\n",
        "according to the geometry of the source plane and specified angles.\n",
        "<br><br> This is just one way in which we can take advantage of the open\n",
        "source nature of Tidy3D, and these principles can be applied to any base\n",
        "object class that Tidy3D provides."
      ],
      "id": "d845b41b-79e1-4fed-8759-a46ff507ec51"
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
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      "source": [
        "# Standard python imports\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "# Tidy3D import\n",
        "import tidy3d as td\n",
        "from tidy3d import web\n",
        "\n",
        "# Import base object\n",
        "from tidy3d.components.beam import BeamProfile"
      ],
      "id": "7ce19ff5"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Quasi Gaussian source\n",
        "\n",
        "Here we show how to create a Quasi-Gaussian mode in Tidy3D using our\n",
        "[CustomFieldSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.CustomFieldSource.html)\n",
        "object, based on [J. Tuovinen,\n",
        "1992](https://ieeexplore.ieee.org/document/138840). When a small beam\n",
        "waist (on the order of a wavelength or smaller) is required, this source\n",
        "is a better solution to the full-wave equation as opposed to the\n",
        "paraxial wave equation:"
      ],
      "id": "28b389c0-c1a5-425e-b19e-8e47f0866a57"
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        "<center>"
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      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$E(r,z) = \\frac{w_0}{w(z)}\\frac{1}{{F^{\\prime\\prime}}^2}\\exp{\\Bigl(-\\frac{(r/F^{\\prime\\prime})^2}{w(z)^2} - jkz - jkR(z)(F^{\\prime\\prime} - 1) + j\\phi_0}\\Bigr)$"
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        "</center>"
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    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "where:"
      ],
      "id": "640abf6a-4a3f-40fb-a39a-e3f673fb1b5f"
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      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\omega_0$ is the beam waist"
      ],
      "id": "9b55683f-0dd6-4db8-b7c0-918481467c1e"
    },
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        "</li>"
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    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$z_R=\\frac{\\pi n_\\epsilon\\omega_0^2}{\\lambda}$ is the Rayleigh length"
      ],
      "id": "9f0fc64a-7417-48d2-8e6a-6d6afb6e914e"
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      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\omega(z)=\\omega_0\\sqrt{1+\\frac{z^2}{z_R^2}}$ is the beam radius"
      ],
      "id": "0c3a5de4-f730-426a-ad36-a0af9d94d9b3"
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        "</li>"
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      "id": "54d01f58-3110-4bba-acd8-aa594ffdff27"
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      "metadata": {},
      "source": [
        "$R(z)=z(1+\\frac{z_R^2}{z^2})$ is the wavefront curvature"
      ],
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      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$k=\\frac{2\\pi n}{\\lambda}$ is the wavenumber"
      ],
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      "source": [
        "$F^{\\prime\\prime}=[1 + (r/R(z))^2]^{0.5}$"
      ],
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      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\phi_0(z)=\\arctan{\\left(\\frac{z}{z_R}\\right)}$ is the phase shift"
      ],
      "id": "569223db-1be9-4c9e-8e73-872dfb138dc8"
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        "</li>"
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    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<br> We then validate the field profile along the propagation direction."
      ],
      "id": "c3b5c703-3761-4cfa-b114-38048171fd18"
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [],
      "source": [
        "def QuasiGaussian(\n",
        "    size,\n",
        "    source_time,\n",
        "    center=(0, 0, 0),\n",
        "    direction=\"+\",\n",
        "    pol_angle=0,\n",
        "    angle_phi=0,\n",
        "    angle_theta=0,\n",
        "    w0=1,\n",
        "    waist_distance=0,\n",
        "):\n",
        "    freqs = [source_time.freq0]\n",
        "\n",
        "    class QuasiGaussian_obj(BeamProfile):\n",
        "        \"\"\"Component for constructing OAM beam data. The normal direction is implicitly\n",
        "        defined by the ``size`` parameter.\n",
        "        \"\"\"\n",
        "\n",
        "        def scalar_field(self, points, background_n):\n",
        "            \"\"\"Scalar field for OAM beam.\n",
        "            Scalar field corresponding to the analytic beam in coordinate system such that the\n",
        "            propagation direction is z and the ``E``-field is entirely ``x``-polarized. The field is\n",
        "            computed on an unstructured array ``points`` of shape ``(3, ...)``.\n",
        "            \"\"\"\n",
        "            x, y, z = points\n",
        "            z -= waist_distance\n",
        "            r = np.sqrt(x**2 + y**2)\n",
        "\n",
        "            k = 2 * np.pi * np.array(freqs) / td.C_0 * background_n\n",
        "            zR = np.real(w0**2 * k / 2)\n",
        "            wz = w0 * np.sqrt(1 + z**2 / zR**2)\n",
        "            inv_Rz = z / (z**2 + zR**2)\n",
        "            Fpp = np.sqrt(1 + r**2 * inv_Rz**2)\n",
        "            phi0 = np.arctan2(z, zR)\n",
        "\n",
        "            phase = -((r / Fpp) ** 2) / wz**2 - 1j * k * z + 1j * phi0\n",
        "            if np.all(inv_Rz) != 0:\n",
        "                phase -= 1j * k * (Fpp - 1) / inv_Rz\n",
        "\n",
        "            E = w0 / wz * 1 / Fpp**2 * np.exp(phase)\n",
        "\n",
        "            return E\n",
        "\n",
        "    QuasiGaussian_obj = QuasiGaussian_obj(\n",
        "        center=center,\n",
        "        size=size,\n",
        "        freqs=freqs,\n",
        "        angle_theta=angle_theta,\n",
        "        angle_phi=angle_phi,\n",
        "        pol_angle=pol_angle,\n",
        "        direction=direction,\n",
        "    )\n",
        "    field_data = QuasiGaussian_obj.field_data\n",
        "    field_dataset = td.FieldDataset(\n",
        "        Ex=field_data.Ex,\n",
        "        Ey=field_data.Ey,\n",
        "        Ez=field_data.Ez,\n",
        "        Hx=field_data.Hx,\n",
        "        Hy=field_data.Hy,\n",
        "        Hz=field_data.Hz,\n",
        "    )\n",
        "    QuasiGaussian_source = td.CustomFieldSource(\n",
        "        center=center, size=size, source_time=source_time, field_dataset=field_dataset\n",
        "    )\n",
        "    return QuasiGaussian_source"
      ],
      "id": "d83e7ea8"
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "freq0 = td.C_0 / 0.5\n",
        "\n",
        "QG_center = (0, 0, -5)\n",
        "QG_size = (5, 5, 0)\n",
        "QG_source_time = td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10)\n",
        "QG_w0 = td.C_0 / freq0 / 5\n",
        "QG_waist_distance = -5\n",
        "\n",
        "QG_source = QuasiGaussian(\n",
        "    center=QG_center,\n",
        "    size=QG_size,\n",
        "    source_time=QG_source_time,\n",
        "    w0=QG_w0,\n",
        "    waist_distance=QG_waist_distance,\n",
        ")\n",
        "\n",
        "G_source = td.GaussianBeam(\n",
        "    center=QG_center,\n",
        "    size=QG_size,\n",
        "    source_time=QG_source_time,\n",
        "    direction=\"+\",\n",
        "    waist_radius=QG_w0,\n",
        "    waist_distance=QG_waist_distance,\n",
        ")"
      ],
      "id": "02a069d5"
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [],
      "source": [
        "field = td.FieldMonitor(\n",
        "    size=(td.inf, 0, td.inf), name=\"field\", freqs=[freq0 * 0.9, freq0, freq0 * 1.1]\n",
        ")\n",
        "\n",
        "QG_sim = td.Simulation(\n",
        "    size=(5, 5, 15), sources=[QG_source], structures=[], monitors=[field], run_time=50 / freq0\n",
        ")\n",
        "\n",
        "G_sim = QG_sim.updated_copy(sources=[G_source])"
      ],
      "id": "f86e0d63"
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [
        {
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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\">10:30:40 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'gaussian beam profile test'</span> with resource_id         \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-a452fa16-4a8e-4fdd-b9c5-84d28e1ee130'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
              "</pre>"
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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\">             </span>View task using web UI at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a452fa16-4a8e-4fdd-b9c5-84d28e1ee130\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a452fa16-4a8</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a452fa16-4a8e-4fdd-b9c5-84d28e1ee130\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">e-4fdd-b9c5-84d28e1ee130'</span></a>.                                         \n",
              "</pre>"
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          "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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
              "</pre>"
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        },
        {
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          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
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              "</script>"
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        {
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          "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>"
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        },
        {
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          "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\">10:30:42 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. This assumes the FDTD solver runs\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for the full simulation time; if early shutoff is reached, the     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed cost can be lower. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed FlexCredit cost after a simulation run.                     \n",
              "</pre>"
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        },
        {
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          "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\">10:30:43 UTC </span>status = queued                                                    \n",
              "</pre>"
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        },
        {
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          "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>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
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              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
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              "<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\">10:30:53 UTC </span>status = preprocess                                                \n",
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          "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>"
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        },
        {
          "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\">10:30:57 UTC </span>starting up solver                                                 \n",
              "</pre>"
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          }
        },
        {
          "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\">10:30:58 UTC </span>running solver                                                     \n",
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            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"5bd9f090a95c4ef99a539afd2cfdd0c9\",\"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\">             </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91</span>%, exiting.                            \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>"
            ]
          }
        },
        {
          "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\">10:30:59 UTC </span>status = postprocess                                               \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"724bdcc8e93d43928072a8c52fd66883\",\"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\">10:31:01 UTC </span>status = success                                                   \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>"
            ]
          }
        },
        {
          "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\">10:31:03 UTC </span>View simulation result at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a452fa16-4a8e-4fdd-b9c5-84d28e1ee130\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a452fa16-4a8</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a452fa16-4a8e-4fdd-b9c5-84d28e1ee130\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">e-4fdd-b9c5-84d28e1ee130'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"9e3a8e5f545547eaae0eae587a1a1c06\",\"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\">10:31:05 UTC </span>Loading results from simulation_data.hdf5                          \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>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'gaussian beam profile test'</span> with resource_id         \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-72a9cf0e-a9c5-47d4-84d4-d3f60d73c210'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \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>View task using web UI at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-72a9cf0e-a9c5-47d4-84d4-d3f60d73c210\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-72a9cf0e-a9c</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-72a9cf0e-a9c5-47d4-84d4-d3f60d73c210\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">5-47d4-84d4-d3f60d73c210'</span></a>.                                         \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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"f03dd902d9ce44c69524b4f005ed8f3a\",\"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\">10:31:07 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. This assumes the FDTD solver runs\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for the full simulation time; if early shutoff is reached, the     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed cost can be lower. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed FlexCredit cost after a simulation run.                     \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\">10:31:08 UTC </span>status = queued                                                    \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>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"55e5a55c346247a68297294bee8fbd09\",\"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\">10:31:20 UTC </span>starting up solver                                                 \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>running solver                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"036a9c926fa94e04b3e7fc8adf0b42c2\",\"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\">10:31:22 UTC </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">91</span>%, exiting.                            \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>"
            ]
          }
        },
        {
          "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\">10:31:23 UTC </span>status = postprocess                                               \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"625b9589caff4b34a2f00c4e1e13fe19\",\"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\">             </span>status = success                                                   \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>"
            ]
          }
        },
        {
          "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\">10:31:25 UTC </span>View simulation result at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-72a9cf0e-a9c5-47d4-84d4-d3f60d73c210\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-72a9cf0e-a9c</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-72a9cf0e-a9c5-47d4-84d4-d3f60d73c210\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">5-47d4-84d4-d3f60d73c210'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"5b2d052aa38741189e786509f6548225\",\"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\">10:31:27 UTC </span>Loading results from simulation_data.hdf5                          \n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "QG_sim_data = web.run(simulation=QG_sim, task_name=\"gaussian beam profile test\")\n",
        "G_sim_data = web.run(simulation=G_sim, task_name=\"gaussian beam profile test\")"
      ],
      "id": "1377b342"
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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V///6668H1jN58uROfc999tnHbW1tLfs6XNd1P/74Y73MmDFjumVfzpgxQy9z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F7/iO75jp8bmeA7j0ms73/SjpelbHMBgMBoPBYNgtGAPyAjhz5gz83M/9HAAAvOMd74DFxcWL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ayhvSbAbSzfjcq24kWSZQSHxH809xzJh8d2krRj8HmR5Bgj66SSWfeyyXWqMFW2bgrArGmS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y9jcM0cqZpLIpq5kGAGiLGsZqs7r+XSLQYXuCjpvVS0dReKTOKx1FTM/YyGk6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\nzN9jjz0+c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mW001s2uUbnjdib+hOauKtOc6vJh6ZXUEa/UcMezSgfOZ2CJdujtqg7O2gX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jp0xG9GNBm8JPRUVoAuVtCoVCoTjjMAUfAvBhxdviEeWFK+TzxbCjsuZZLh7+ZikAN0aIWVsR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\n7rgjD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6TXCXbT1dJrsiO4/WlKOuKTWRsl1VFRtoXNQr74pddcFk3Hbjq9dJzctjPZk364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          }
        }
      ],
      "source": [
        "fig, ax = plt.subplots(1, 2)\n",
        "\n",
        "QG_sim_data.plot_field(field_monitor_name=\"field\", field_name=\"Ex\", f=freq0, ax=ax[0])\n",
        "G_sim_data.plot_field(field_monitor_name=\"field\", field_name=\"Ex\", f=freq0, ax=ax[1])\n",
        "ax[0].set_title(\"Quasi-Gaussian\")\n",
        "ax[1].set_title(\"Gaussian\")\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "8ad1338c"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Hermite-Gaussian source\n",
        "\n",
        "Here we show how to create a Hermite-Gaussian mode in Tidy3D using our\n",
        "[CustomFieldSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.CustomFieldSource.html)\n",
        "object. We then validate the phase change along the propagation\n",
        "direction.<br><br> In cartesian coordinates, where $x$ is the\n",
        "propagation direction, the OAM has field profile"
      ],
      "id": "a5b7e3d3-abb1-463c-a7c3-b2e7b650143b"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<center>"
      ],
      "id": "bfa3cdcd-0c5f-43d1-9872-46b92be23861"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$E_{l,m}(x,y,z)=E_0\\frac{\\omega_0}{\\omega(z)}H_l\\Bigl(\\frac{\\sqrt{2}x}{\\omega(z)}\\Bigr) H_m\\Bigl(\\frac{\\sqrt{2}y}{\\omega(z)}\\Bigr)\\exp\\Bigl(-\\frac{x^2+y^2}{\\omega^2(z)}\\Bigr)\\exp\\Bigl(-i\\frac{k(x^2+y^2)}{2R(z)}\\Bigr)\\exp\\Bigl( i\\psi(z)\\Bigr)\\exp( -ikz)$"
      ],
      "id": "a3f3ad87-bd9a-4346-8f6d-9a483fcfaf96"
    },
    {
      "cell_type": "raw",
      "metadata": {
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      "source": [
        "</center>"
      ],
      "id": "63468ab2-272b-4aed-a829-300445d7a9a3"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "where:"
      ],
      "id": "4268683a-305e-4e1f-82a1-c8477b98bd64"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "ffb79660-3e1c-42aa-87ef-aece35c70f25"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\omega_0$ is the beam waist"
      ],
      "id": "c2c7e0cf-9642-4e34-b0c5-a3a764c174b4"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "74852647-d7e0-4f81-914b-04f093ca9fc3"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "523d96fa-3693-4fbc-9bf3-1e421d568eec"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$z_R=\\frac{\\pi n_\\epsilon\\omega_0^2}{\\lambda}$ is the Rayleigh length"
      ],
      "id": "facf5ebe-6d1c-470a-be17-404608739e2e"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "6f836475-5bdb-4489-9856-74cb2a03324c"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "184e4c06-3b1e-4df2-8adb-36707c5ec6ae"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\omega(z)=\\omega_0\\sqrt{1+\\frac{z^2}{z_R^2}}$ is the beam radius"
      ],
      "id": "9a8b6b68-ee9d-44fe-96d4-fbbe1077c0f7"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "b3d8ce1d-0546-4548-b08f-29986d671d21"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "5c3cf87a-9d2d-4458-a41c-2513909663f7"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$k=\\frac{2\\pi n}{\\lambda}$ is the wavenumber"
      ],
      "id": "2cf28280-9d77-4c65-bd41-b95989955908"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "eb4c3a23-2edf-4cbf-a512-fde620c165b5"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "9b19f1f6-5074-4962-81c2-69d0c6fae4b0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$R(z)=z(1+\\frac{z_R^2}{z^2})$ is the wavefront curvature"
      ],
      "id": "4f29f4d8-158b-44f3-ad3b-809aabd35bd2"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "410696dc-a104-459d-b8be-60b1120d2f99"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "31534be2-1e9d-44c4-8d1c-c671effa0d25"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$H_l,H_m$ are Hermite polynomials of orders $l$ and $m$"
      ],
      "id": "2418c71d-d245-4fe4-809b-fea52d534847"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "c4626b63-5cca-4cb3-b8df-9c53ad0647fb"
    },
    {
      "cell_type": "raw",
      "metadata": {
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      },
      "source": [
        "<li>"
      ],
      "id": "ef045927-0861-4055-88df-30b47c77e49e"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\psi(z)=(l+m+1)\\arctan\\Bigl(\\frac{z}{z_R}\\Bigr)$ is the phase function"
      ],
      "id": "9783456e-3fb9-4a90-bacb-63e54657c3eb"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "2cfa70cd-973c-4dbe-b40d-8b1a49d31e91"
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [],
      "source": [
        "from scipy.special import hermite\n",
        "\n",
        "\n",
        "def HGM(\n",
        "    size,\n",
        "    m,\n",
        "    l,\n",
        "    source_time,\n",
        "    center=(0, 0, 0),\n",
        "    direction=\"+\",\n",
        "    pol_angle=0,\n",
        "    angle_phi=0,\n",
        "    angle_theta=0,\n",
        "    w0=1,\n",
        "    waist_distance=0,\n",
        "):\n",
        "    freqs = [source_time.freq0]\n",
        "\n",
        "    class HGM_obj(BeamProfile):\n",
        "        \"\"\"Component for constructing HGM beam data. The normal direction is implicitly\n",
        "        defined by the ``size`` parameter.\n",
        "        \"\"\"\n",
        "\n",
        "        def scalar_field(self, points, background_n):\n",
        "            \"\"\"Scalar field for HGM beam.\n",
        "            Scalar field corresponding to the analytic beam in coordinate system such that the\n",
        "            propagation direction is z and the ``E``-field is entirely ``x``-polarized. The field is\n",
        "            computed on an unstructured array ``points`` of shape ``(3, ...)``.\n",
        "            \"\"\"\n",
        "            x, y, z = points\n",
        "            z += waist_distance\n",
        "\n",
        "            zR = np.pi * background_n * w0**2 / (td.C_0 / np.array(self.freqs))\n",
        "            wz = w0 * np.sqrt(1 + z**2 / zR**2)\n",
        "            Rz = td.inf if np.any(z == 0) else z * (1 + zR**2 / z**2)\n",
        "            k = 2 * np.pi * np.array(self.freqs) / td.C_0 * background_n\n",
        "            psi_z = (l + m + 1) * np.arctan2(z, np.real(zR))\n",
        "\n",
        "            E = source_time.amplitude * w0 / wz\n",
        "            E *= hermite(l)(np.real(np.sqrt(2) * x / wz)) * hermite(m)(np.real(np.sqrt(2) * y / wz))\n",
        "            E *= np.exp(-(x**2 + y**2) / wz**2) * np.exp(-1j * k * (x**2 + y**2) / (2 * Rz))\n",
        "            E *= np.exp(1j * psi_z) * np.exp(-1j * k * z)\n",
        "\n",
        "            return E\n",
        "\n",
        "    HGM_obj = HGM_obj(\n",
        "        center=center,\n",
        "        size=size,\n",
        "        freqs=freqs,\n",
        "        angle_theta=angle_theta,\n",
        "        angle_phi=angle_phi,\n",
        "        pol_angle=pol_angle,\n",
        "        direction=direction,\n",
        "    )\n",
        "    field_data = HGM_obj.field_data\n",
        "    field_dataset = td.FieldDataset(\n",
        "        Ex=field_data.Ex,\n",
        "        Ey=field_data.Ey,\n",
        "        Ez=field_data.Ez,\n",
        "        Hx=field_data.Hx,\n",
        "        Hy=field_data.Hy,\n",
        "        Hz=field_data.Hz,\n",
        "    )\n",
        "    HGM_source = td.CustomFieldSource(\n",
        "        center=center, size=size, source_time=source_time, field_dataset=field_dataset\n",
        "    )\n",
        "    return HGM_source"
      ],
      "id": "00985353"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create and run example Hermite-Gaussian beam:"
      ],
      "id": "3b83b248-abb7-4194-a927-e76bf2882267"
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [],
      "source": [
        "freq0 = td.C_0 / 1.55\n",
        "hgm = HGM(size=(0, 4, 4), m=2, l=1, source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10))"
      ],
      "id": "03b80b0f"
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [],
      "source": [
        "sim_size = (5.1, 5, 5)\n",
        "sim_center = (sim_size[0] / 2 - 0.05, 0, 0)\n",
        "\n",
        "num_field_monitors = 61\n",
        "field_monitor_xs = np.linspace(\n",
        "    sim_center[0] - sim_size[0] / 2 + 0.1, sim_size[0] - 0.1, num_field_monitors\n",
        ")\n",
        "field_monitors = []\n",
        "for x in field_monitor_xs:\n",
        "    field_monitor = td.FieldMonitor(\n",
        "        center=(x, 0, 0), size=(0, sim_size[1], sim_size[2]), name=str(x), freqs=[freq0]\n",
        "    )\n",
        "    field_monitors.append(field_monitor)\n",
        "\n",
        "HGM_test_sim = td.Simulation(\n",
        "    center=sim_center,\n",
        "    size=sim_size,\n",
        "    structures=[],\n",
        "    sources=[hgm],\n",
        "    monitors=field_monitors,\n",
        "    run_time=1e-13,\n",
        ")"
      ],
      "id": "635e94c0"
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "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\">10:31:28 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'HGM test'</span> with resource_id                           \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-615f9919-06c5-477b-96b6-efff3295f438'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \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>View task using web UI at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-615f9919-06c5-477b-96b6-efff3295f438\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-615f9919-06c</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-615f9919-06c5-477b-96b6-efff3295f438\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">5-477b-96b6-efff3295f438'</span></a>.                                         \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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"e1c0ea5306b24a7991c6fc8ae5c18c87\",\"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\">10:31:31 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. This assumes the FDTD solver runs\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for the full simulation time; if early shutoff is reached, the     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed cost can be lower. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed FlexCredit cost after a simulation run.                     \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\">10:31:32 UTC </span>status = queued                                                    \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>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"748080fec5a7439bafaf84ec7bc1a32c\",\"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\">10:34:42 UTC </span>starting up solver                                                 \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>running solver                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"6ea8966bb17a406ba51a4ce4372c1b8f\",\"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\">10:34:43 UTC </span>status = postprocess                                               \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"0e8b00c5ca6c42ea8debc789abbb19c1\",\"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\">10:34:50 UTC </span>status = success                                                   \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>"
            ]
          }
        },
        {
          "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\">10:34:52 UTC </span>View simulation result at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-615f9919-06c5-477b-96b6-efff3295f438\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-615f9919-06c</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-615f9919-06c5-477b-96b6-efff3295f438\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">5-477b-96b6-efff3295f438'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"d0773e16a9b44ceeacb2847da042b0b3\",\"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\">10:34:54 UTC </span>Loading results from simulation_data.hdf5                          \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\">10:34:55 UTC </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Simulation final field decay value of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"color: #800000; text-decoration-color: #800000\"> is greater than </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">the simulation shutoff threshold of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-05</span><span style=\"color: #800000; text-decoration-color: #800000\">. Consider running the    </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">simulation again with a larger </span><span style=\"color: #008000; text-decoration-color: #008000\">'run_time'</span><span style=\"color: #800000; text-decoration-color: #800000\"> duration for more        </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">accurate results.                                                  </span>\n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "hgm_sim_data = web.run(simulation=HGM_test_sim, task_name=\"HGM test\")"
      ],
      "id": "252da090"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Display field in propagation direction:"
      ],
      "id": "16ff032e-00a5-4a3b-8206-ac54068847dc"
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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          }
        }
      ],
      "source": [
        "hgm_sim_data.plot_field(str(field_monitor_xs[0]), \"Ey\", f=freq0)\n",
        "plt.show()"
      ],
      "id": "e7a7168b"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "To see how the field evolves, run the following code to visualize along\n",
        "the propagation direction."
      ],
      "id": "ee0a9514-3913-4eac-b56f-9da97363da58"
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [],
      "source": [
        "import ipywidgets as widgets\n",
        "\n",
        "component = \"Ey\"\n",
        "\n",
        "field_slider = widgets.FloatSlider(\n",
        "    value=0,\n",
        "    min=field_monitor_xs[0],\n",
        "    max=field_monitor_xs[-1],\n",
        "    step=None,\n",
        "    description=component,\n",
        "    disabled=False,\n",
        "    continuous_update=True,\n",
        "    orientation=\"horizontal\",\n",
        "    readout=True,\n",
        "    readout_format=\".3f\",\n",
        ")\n",
        "\n",
        "\n",
        "def update_plot(x):\n",
        "    if x not in field_monitor_xs:\n",
        "        x = min(field_monitor_xs, key=lambda ll: abs(ll - x))\n",
        "    hgm_sim_data.plot_field(str(x), component, f=freq0)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "widgets.interactive(update_plot, x=field_slider)"
      ],
      "id": "ca0a9bf7"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Laguerre-Gaussian source\n",
        "\n",
        "Here we show how to create an Orbital Angular Momentum (OAM) beam in\n",
        "Tidy3D using our\n",
        "[CustomFieldSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.CustomFieldSource.html)\n",
        "object. We then validate the phase change along the propagation\n",
        "direction.<br><br> In cylindrical coordinates, where $z$ is the\n",
        "propagation direction, the OAM has field profile"
      ],
      "id": "d0823fd5-4866-48a3-bb7a-fa576c3d469a"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
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      "source": [
        "<center>"
      ],
      "id": "f66e9685-a033-4631-8285-7f4e92a489f6"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$E_{l,p}(r,\\phi,z)=E_0\\sqrt{\\frac{2p!}{\\pi(p+|l|)!}} \\frac{1}{\\omega(z)} \\Bigl(\\frac{r\\sqrt{2}}{\\omega(z)}\\Bigr)^{|l|} \\exp\\Bigl(-\\frac{r^2}{\\omega^2(z)}\\Bigr) L_p^{|l|}\\Bigl(\\frac{2r^2}{\\omega^2(z)}\\Bigr) \\exp\\Bigl(-ik\\frac{r^2}{2R(z)}\\Bigr) \\exp(-il\\phi) \\exp\\Bigl( i\\psi(z)\\Bigr)$"
      ],
      "id": "78cf2c28-2e16-4e72-b23b-bb7fa2a84728"
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    {
      "cell_type": "raw",
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        "</center>"
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      "id": "957cd55c-8e59-4658-b2e0-1edbe39a7648"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "where:"
      ],
      "id": "20c63b16-4433-41ca-a0ff-9a7f778345d2"
    },
    {
      "cell_type": "raw",
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        "<li>"
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      "id": "8febcf5a-afa5-423d-9af1-c774e4800a31"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\omega_0$ is the beam waist"
      ],
      "id": "7a6e45de-14d4-4072-979e-8867ed209eb2"
    },
    {
      "cell_type": "raw",
      "metadata": {
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        "</li>"
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      "id": "acfae13b-43d5-423e-887a-6853c71e032c"
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    {
      "cell_type": "raw",
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        "<li>"
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      "id": "2c06ab66-f928-4bb2-a395-b3f74da8a14b"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$z_R=\\frac{\\pi n_\\epsilon\\omega_0^2}{\\lambda}$ is the Rayleigh length"
      ],
      "id": "00e4798e-c6ab-472b-9422-0a6315ed1d68"
    },
    {
      "cell_type": "raw",
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      "source": [
        "</li>"
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      "id": "7eaf2ed9-13cb-4ef3-88d8-1970757dcb2d"
    },
    {
      "cell_type": "raw",
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        "<li>"
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      "id": "780ce788-7a5d-4d34-af45-a7a03dd846f5"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\omega(z)=\\omega_0\\sqrt{1+\\frac{z^2}{z_R^2}}$ is the beam radius"
      ],
      "id": "a957eff1-cfeb-4099-99e1-6ad43c1cdc3f"
    },
    {
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        "</li>"
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      "id": "de00b746-6a01-4545-9e8d-26856a58e6f4"
    },
    {
      "cell_type": "raw",
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        "<li>"
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      "id": "ce091ab0-f25d-4937-b1bb-14db9124cd77"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$R(z)=z(1+\\frac{z_R^2}{z^2})$ is the wavefront curvature"
      ],
      "id": "cad43fb1-07cb-4de1-a9a1-6c6fca8dd9b6"
    },
    {
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        "</li>"
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    {
      "cell_type": "raw",
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        "<li>"
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      "id": "16fcd3f3-6b49-44b5-8484-6466e5c8d017"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$k=\\frac{2\\pi n}{\\lambda}$ is the wavenumber"
      ],
      "id": "0d84eba0-3dad-469d-94b4-99a6b1ac6e9f"
    },
    {
      "cell_type": "raw",
      "metadata": {
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        "</li>"
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      "id": "359d8648-8f2d-4abe-b015-a065964aee35"
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    {
      "cell_type": "raw",
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        "<li>"
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      "id": "6565f24f-25e1-422f-bb21-c5b82dc96bbb"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$L_p^{|l|}$ is the generalized Laguerre polynomial"
      ],
      "id": "804a3dd9-74ea-4a87-8105-c026a228673c"
    },
    {
      "cell_type": "raw",
      "metadata": {
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        "</li>"
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    {
      "cell_type": "raw",
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        "<li>"
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      "id": "4b24bb3c-5174-478f-b10d-227d916682ef"
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    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\psi(z)=(|l| + 2p + 1)\\arctan\\Bigl(\\frac{z}{z_R}\\Bigr)$ is the phase\n",
        "function"
      ],
      "id": "56b9c458-f43a-481b-b044-5654138e770e"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
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        "</li>"
      ],
      "id": "8fde8a81-b619-480d-9d46-9eeb6e2d6851"
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [],
      "source": [
        "from scipy.special import factorial, genlaguerre\n",
        "\n",
        "\n",
        "def OAM(\n",
        "    size,\n",
        "    p,\n",
        "    l,\n",
        "    source_time,\n",
        "    center=(0, 0, 0),\n",
        "    direction=\"+\",\n",
        "    pol_angle=0,\n",
        "    angle_phi=0,\n",
        "    angle_theta=0,\n",
        "    w0=1,\n",
        "    waist_distance=0,\n",
        "):\n",
        "    freqs = [source_time.freq0]\n",
        "\n",
        "    class OAM_obj(BeamProfile):\n",
        "        \"\"\"Component for constructing OAM beam data. The normal direction is implicitly\n",
        "        defined by the ``size`` parameter.\n",
        "        \"\"\"\n",
        "\n",
        "        def scalar_field(self, points, background_n):\n",
        "            \"\"\"Scalar field for OAM beam.\n",
        "            Scalar field corresponding to the analytic beam in coordinate system such that the\n",
        "            propagation direction is z and the ``E``-field is entirely ``x``-polarized. The field is\n",
        "            computed on an unstructured array ``points`` of shape ``(3, ...)``.\n",
        "            \"\"\"\n",
        "            x, y, z = points\n",
        "            z += waist_distance\n",
        "            r = np.sqrt(x**2 + y**2)\n",
        "            phi = np.arctan2(y, x)\n",
        "            absl = np.abs(l)\n",
        "\n",
        "            zR = np.pi * background_n * w0**2 / (td.C_0 / np.array(self.freqs))\n",
        "            wz = w0 * np.sqrt(1 + z**2 / zR**2)\n",
        "            Rz = td.inf if np.any(z == 0) else z * (1 + zR**2 / z**2)\n",
        "            k = 2 * np.pi * np.array(self.freqs) / td.C_0 * background_n\n",
        "            psi_z = (np.abs(l) + 2 * p + 1) * np.arctan2(z, np.real(zR))\n",
        "\n",
        "            E = genlaguerre(p, absl)(2 * r**2 / wz**2) if p != 0 else 1\n",
        "            E *= (\n",
        "                source_time.amplitude\n",
        "                * np.sqrt(2 * factorial(p) / (np.pi * factorial(p + absl)))\n",
        "                / wz\n",
        "            )\n",
        "            E *= (r * np.sqrt(2) / wz) ** absl * np.exp(-(r**2) / wz**2)\n",
        "            E *= np.exp(-1j * k * r**2 / (2 * Rz)) * np.exp(-1j * l * phi) * np.exp(1j * psi_z)\n",
        "\n",
        "            return E\n",
        "\n",
        "    OAM_obj = OAM_obj(\n",
        "        center=center,\n",
        "        size=size,\n",
        "        freqs=freqs,\n",
        "        angle_theta=angle_theta,\n",
        "        angle_phi=angle_phi,\n",
        "        pol_angle=pol_angle,\n",
        "        direction=direction,\n",
        "    )\n",
        "    field_data = OAM_obj.field_data\n",
        "    field_dataset = td.FieldDataset(\n",
        "        Ex=field_data.Ex,\n",
        "        Ey=field_data.Ey,\n",
        "        Ez=field_data.Ez,\n",
        "        Hx=field_data.Hx,\n",
        "        Hy=field_data.Hy,\n",
        "        Hz=field_data.Hz,\n",
        "    )\n",
        "    OAM_source = td.CustomFieldSource(\n",
        "        center=center, size=size, source_time=source_time, field_dataset=field_dataset\n",
        "    )\n",
        "    return OAM_source"
      ],
      "id": "25b592c0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We will demonstrate this functionality by defining an OAM source that\n",
        "propagates in the $x$ direction."
      ],
      "id": "a1f2dabf-f792-480e-9a8e-0ddad5e1298c"
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [],
      "source": [
        "freq0 = td.C_0 / 1.55\n",
        "oam = OAM(size=(0, 4, 4), p=0, l=1, source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10))"
      ],
      "id": "8c146fdb"
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [],
      "source": [
        "sim_size = (5.1, 5, 5)\n",
        "sim_center = (sim_size[0] / 2 - 0.05, 0, 0)\n",
        "\n",
        "num_field_monitors = 61\n",
        "field_monitor_xs = np.linspace(\n",
        "    sim_center[0] - sim_size[0] / 2 + 0.1, sim_size[0] - 0.1, num_field_monitors\n",
        ")\n",
        "field_monitors = []\n",
        "for x in field_monitor_xs:\n",
        "    field_monitor = td.FieldMonitor(\n",
        "        center=(x, 0, 0), size=(0, sim_size[1], sim_size[2]), name=str(x), freqs=[freq0]\n",
        "    )\n",
        "    field_monitors.append(field_monitor)\n",
        "\n",
        "OAM_test_sim = td.Simulation(\n",
        "    center=sim_center,\n",
        "    size=sim_size,\n",
        "    structures=[],\n",
        "    sources=[oam],\n",
        "    monitors=field_monitors,\n",
        "    run_time=1e-13,\n",
        ")"
      ],
      "id": "7ad0b5c4"
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "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\">10:34:57 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'OAM test'</span> with resource_id                           \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-a790fed3-6e0d-4ed1-956a-fbabbbdf86c9'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
              "</pre>"
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          }
        },
        {
          "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>View task using web UI at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a790fed3-6e0d-4ed1-956a-fbabbbdf86c9\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a790fed3-6e0</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a790fed3-6e0d-4ed1-956a-fbabbbdf86c9\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">d-4ed1-956a-fbabbbdf86c9'</span></a>.                                         \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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"5a350ca41aa54d8e9d3872d5f9b30e6e\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
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          }
        },
        {
          "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\">10:35:00 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. This assumes the FDTD solver runs\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for the full simulation time; if early shutoff is reached, the     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed cost can be lower. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed FlexCredit cost after a simulation run.                     \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\">10:35:01 UTC </span>status = queued                                                    \n",
              "</pre>"
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        },
        {
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          "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>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"20fbd1da48464498acddb51217c701a5\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
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        },
        {
          "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\">10:35:23 UTC </span>status = preprocess                                                \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\">10:35:25 UTC </span>status = postprocess                                               \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\">10:35:34 UTC </span>status = success                                                   \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>"
            ]
          }
        },
        {
          "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\">10:35:37 UTC </span>starting up solver                                                 \n",
              "</pre>"
            ]
          }
        },
        {
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          "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>running solver                                                     \n",
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              "</script>"
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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\">10:35:38 UTC </span>status = success                                                   \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>"
            ]
          }
        },
        {
          "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>View simulation result at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a790fed3-6e0d-4ed1-956a-fbabbbdf86c9\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a790fed3-6e0</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a790fed3-6e0d-4ed1-956a-fbabbbdf86c9\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">d-4ed1-956a-fbabbbdf86c9'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"115e81d7844d4386a92297162050940a\",\"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\">10:35:39 UTC </span>Loading results from simulation_data.hdf5                          \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><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Simulation final field decay value of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"color: #800000; text-decoration-color: #800000\"> is greater than </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">the simulation shutoff threshold of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-05</span><span style=\"color: #800000; text-decoration-color: #800000\">. Consider running the    </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">simulation again with a larger </span><span style=\"color: #008000; text-decoration-color: #008000\">'run_time'</span><span style=\"color: #800000; text-decoration-color: #800000\"> duration for more        </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">accurate results.                                                  </span>\n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "oam_sim_data = web.run(simulation=OAM_test_sim, task_name=\"OAM test\")"
      ],
      "id": "fe8e24a8"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Display field in propagation direction:"
      ],
      "id": "1b4b0393-f078-4f7b-8d2e-d0b09f9a8082"
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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VwPHlc8aYY/9IHDhwYKl/UGdkZJhGjRp5265YsaJC31d15OTkmNNOO817zdKmL9ku4Bhj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\n4IEHtHjxYl1xxRV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          }
        }
      ],
      "source": [
        "oam_sim_data.plot_field(str(field_monitor_xs[30]), \"E\", f=freq0, val=\"abs^2\")\n",
        "plt.show()"
      ],
      "id": "73a77f3f"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "To see how the field amplitude evolves, run the following code to\n",
        "visualize along the propagation direction."
      ],
      "id": "3b2c2f92-de3b-4232-b807-091eea7d1977"
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {},
      "outputs": [],
      "source": [
        "import ipywidgets as widgets\n",
        "\n",
        "component = \"Ey\"\n",
        "\n",
        "field_slider = widgets.FloatSlider(\n",
        "    value=0,\n",
        "    min=field_monitor_xs[0],\n",
        "    max=field_monitor_xs[-1],\n",
        "    step=None,\n",
        "    description=component,\n",
        "    disabled=False,\n",
        "    continuous_update=True,\n",
        "    orientation=\"horizontal\",\n",
        "    readout=True,\n",
        "    readout_format=\".3f\",\n",
        ")\n",
        "\n",
        "\n",
        "def update_plot(x):\n",
        "    if x not in field_monitor_xs:\n",
        "        x = min(field_monitor_xs, key=lambda ll: abs(ll - x))\n",
        "    oam_sim_data.plot_field(str(x), component, f=freq0)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "widgets.interactive(update_plot, x=field_slider)"
      ],
      "id": "bfc9bf14"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Bessel Beam\n",
        "\n",
        "Here we show how to create an Bessel beam in Tidy3D using our\n",
        "[CustomFieldSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.CustomFieldSource.html)\n",
        "object. We then validate the phase change along the propagation\n",
        "direction.<br><br> In cylindrical coordinates $(\\rho, \\phi, z)$, where\n",
        "$z$ is the propagation direction, the Bessel beam has field profile"
      ],
      "id": "6b8b9991-07bb-4ac4-a93a-d12c663ef534"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<center>"
      ],
      "id": "518d27bb-cf27-4346-86e6-6524b25a5610"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$U_\\beta(r)=J_m(k_T\\rho)e^{im\\phi}e^{-i\\beta z}$"
      ],
      "id": "dd040cce-a5ec-44ff-910f-2e64fbd93cb4"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</center>"
      ],
      "id": "5412e5e4-8616-4d86-bfdd-26a8c23e4390"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "where:"
      ],
      "id": "b8665a49-26aa-4b00-89c5-710960894819"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "16bcd776-6f01-41f2-8453-abe77b7eead0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$k=\\frac{2\\pi n}{\\lambda}$ is the wavenumber"
      ],
      "id": "fa78b7fc-2a0b-42a1-97b9-3199582d58e0"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "8719e25a-3d78-4f04-9326-b24e99a7417f"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "12a9a150-f4bb-4db6-b379-038b07c1d0ab"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$J_m$ is the Bessel function of the first kind and $m^{th}$ order"
      ],
      "id": "a4403a44-566f-41a0-8d90-ed4a4acc151a"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "534f7de8-a21a-4840-aa8f-8183751cfede"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "d9a5dbcb-128a-4a9e-bc44-a3a22a552ca2"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$k_T=\\sqrt{k^2-\\beta^2}$"
      ],
      "id": "7999904e-7670-46dd-9471-1de8418728e4"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "c8b3bd6f-eea5-49b8-8ac5-a68a6b79cba0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<br> Source: Saleh & Teich, <i>Fundamentals of Photonics</i>"
      ],
      "id": "c724e0e3-d088-4070-88b6-bf9f11719d80"
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {},
      "outputs": [],
      "source": [
        "from scipy.special import jv\n",
        "\n",
        "\n",
        "def Bessel(\n",
        "    size,\n",
        "    m,\n",
        "    beta,\n",
        "    source_time,\n",
        "    center=(0, 0, 0),\n",
        "    direction=\"+\",\n",
        "    pol_angle=0,\n",
        "    angle_phi=0,\n",
        "    angle_theta=0,\n",
        "    w0=1,\n",
        "    waist_distance=0,\n",
        "):\n",
        "    if not isinstance(m, int):\n",
        "        raise Exception(\"Error: m must be an integer\")\n",
        "    freqs = [source_time.freq0]\n",
        "\n",
        "    class Bessel_obj(BeamProfile):\n",
        "        \"\"\"Component for constructing Bessel beam data. The normal direction is implicitly\n",
        "        defined by the ``size`` parameter.\n",
        "        \"\"\"\n",
        "\n",
        "        def scalar_field(self, points, background_n):\n",
        "            \"\"\"Scalar field for Bessel beam.\n",
        "            Scalar field corresponding to the analytic beam in coordinate system such that the\n",
        "            propagation direction is z and the ``E``-field is entirely ``x``-polarized. The field is\n",
        "            computed on an unstructured array ``points`` of shape ``(3, ...)``.\n",
        "            \"\"\"\n",
        "            x, y, z = points\n",
        "            z += waist_distance\n",
        "            rho = np.sqrt(x**2 + y**2)\n",
        "            phi = np.arctan2(y, x)\n",
        "            beta % (2 * np.pi)\n",
        "\n",
        "            k = 2 * np.pi * np.array(self.freqs) / td.C_0 * background_n\n",
        "            k_T = np.sqrt(k**2 - beta**2)\n",
        "\n",
        "            E = source_time.amplitude * jv(m, k_T * rho)\n",
        "            E *= np.exp(1j * m * phi) * np.exp(-1j * beta * z)\n",
        "\n",
        "            return E\n",
        "\n",
        "    Bessel_obj = Bessel_obj(\n",
        "        center=center,\n",
        "        size=size,\n",
        "        freqs=freqs,\n",
        "        angle_theta=angle_theta,\n",
        "        angle_phi=angle_phi,\n",
        "        pol_angle=pol_angle,\n",
        "        direction=direction,\n",
        "    )\n",
        "    field_data = Bessel_obj.field_data\n",
        "    field_dataset = td.FieldDataset(\n",
        "        Ex=field_data.Ex,\n",
        "        Ey=field_data.Ey,\n",
        "        Ez=field_data.Ez,\n",
        "        Hx=field_data.Hx,\n",
        "        Hy=field_data.Hy,\n",
        "        Hz=field_data.Hz,\n",
        "    )\n",
        "    Bessel_source = td.CustomFieldSource(\n",
        "        center=center, size=size, source_time=source_time, field_dataset=field_dataset\n",
        "    )\n",
        "    return Bessel_source"
      ],
      "id": "afdcd42f"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create and run example Bessel beam:"
      ],
      "id": "c96c796b-7738-4bc4-8b70-5b7bbb285c0c"
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {},
      "outputs": [],
      "source": [
        "freq0 = td.C_0 / 1.55\n",
        "bessel = Bessel(\n",
        "    size=(0, 4, 4), m=0, beta=0, source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10)\n",
        ")"
      ],
      "id": "2b651ae4"
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {},
      "outputs": [],
      "source": [
        "sim_size = (5.1, 5, 5)\n",
        "sim_center = (sim_size[0] / 2 - 0.05, 0, 0)\n",
        "\n",
        "num_field_monitors = 61\n",
        "field_monitor_xs = np.linspace(\n",
        "    sim_center[0] - sim_size[0] / 2 + 0.1, sim_size[0] - 0.1, num_field_monitors\n",
        ")\n",
        "field_monitors = []\n",
        "for x in field_monitor_xs:\n",
        "    field_monitor = td.FieldMonitor(\n",
        "        center=(x, 0, 0), size=(0, sim_size[1], sim_size[2]), name=str(x), freqs=[freq0]\n",
        "    )\n",
        "    field_monitors.append(field_monitor)\n",
        "\n",
        "Bessel_test_sim = td.Simulation(\n",
        "    center=sim_center,\n",
        "    size=sim_size,\n",
        "    structures=[],\n",
        "    sources=[bessel],\n",
        "    monitors=field_monitors,\n",
        "    run_time=1e-13,\n",
        ")"
      ],
      "id": "4a17a68b"
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "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\">10:35:41 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'Bessel test'</span> with resource_id                        \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-ae1f968e-ee90-4294-933d-5ed2c67c9fd0'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \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>View task using web UI at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-ae1f968e-ee90-4294-933d-5ed2c67c9fd0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-ae1f968e-ee9</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-ae1f968e-ee90-4294-933d-5ed2c67c9fd0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">0-4294-933d-5ed2c67c9fd0'</span></a>.                                         \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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"90685051060347dfb07be37dd4b044ff\",\"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\">10:35:43 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. This assumes the FDTD solver runs\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for the full simulation time; if early shutoff is reached, the     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed cost can be lower. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed FlexCredit cost after a simulation run.                     \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\">10:35:44 UTC </span>status = queued                                                    \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>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"f915d4ab59154409b66ece80f5da6b88\",\"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\">10:36:10 UTC </span>starting up solver                                                 \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>running solver                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"7e106d6a95a043558c4fea271ae871fd\",\"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\">10:36:11 UTC </span>status = postprocess                                               \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"957193baf3f8488f9f05b74ff6e2dd92\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
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          }
        },
        {
          "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\">10:36:16 UTC </span>status = success                                                   \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>"
            ]
          }
        },
        {
          "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\">10:36:18 UTC </span>View simulation result at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-ae1f968e-ee90-4294-933d-5ed2c67c9fd0\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-ae1f968e-ee9</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-ae1f968e-ee90-4294-933d-5ed2c67c9fd0\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">0-4294-933d-5ed2c67c9fd0'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
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              "</script>"
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        },
        {
          "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\">10:36:19 UTC </span>Loading results from simulation_data.hdf5                          \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\">10:36:20 UTC </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Simulation final field decay value of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"color: #800000; text-decoration-color: #800000\"> is greater than </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">the simulation shutoff threshold of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-05</span><span style=\"color: #800000; text-decoration-color: #800000\">. Consider running the    </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">simulation again with a larger </span><span style=\"color: #008000; text-decoration-color: #008000\">'run_time'</span><span style=\"color: #800000; text-decoration-color: #800000\"> duration for more        </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">accurate results.                                                  </span>\n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "bessel_sim_data = web.run(simulation=Bessel_test_sim, task_name=\"Bessel test\")"
      ],
      "id": "d6fe15b9"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Display field amplitude in propagation direction:"
      ],
      "id": "15a553df-b59f-45d6-a386-725237d99173"
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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          }
        }
      ],
      "source": [
        "bessel_sim_data.plot_field(str(field_monitor_xs[0]), \"E\", val=\"abs\", f=freq0)\n",
        "plt.show()"
      ],
      "id": "51390c90"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "To see how the field amplitude evolves, run the following code to\n",
        "visualize along the propagation direction."
      ],
      "id": "36c7c775-d540-4921-b1a1-e2e558426662"
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {},
      "outputs": [],
      "source": [
        "import ipywidgets as widgets\n",
        "\n",
        "component = \"E\"\n",
        "\n",
        "field_slider = widgets.FloatSlider(\n",
        "    value=0,\n",
        "    min=field_monitor_xs[0],\n",
        "    max=field_monitor_xs[-1],\n",
        "    step=None,\n",
        "    description=component,\n",
        "    disabled=False,\n",
        "    continuous_update=True,\n",
        "    orientation=\"horizontal\",\n",
        "    readout=True,\n",
        "    readout_format=\".3f\",\n",
        ")\n",
        "\n",
        "\n",
        "def update_plot(x):\n",
        "    if x not in field_monitor_xs:\n",
        "        x = min(field_monitor_xs, key=lambda ll: abs(ll - x))\n",
        "    bessel_sim_data.plot_field(str(x), component, val=\"abs\", f=freq0)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "widgets.interactive(update_plot, x=field_slider)"
      ],
      "id": "59c1f739"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Ince-Gaussian modes\n",
        "\n",
        "Here we show how to create Ince-Gaussian (IG) beams in Tidy3D using our\n",
        "[CustomFieldSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.CustomFieldSource.html)\n",
        "object. We then validate the phase change along the propagation\n",
        "direction.<br><br> In elliptic-cylindrical coordinates $(\\xi,\\eta)$,\n",
        "where"
      ],
      "id": "53d12e80-3c5d-46ef-8c13-686a3b238592"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<center>"
      ],
      "id": "0271b504-a3c6-4ad6-a276-435c1c4adf11"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$x=\\sqrt{\\varepsilon/2}\\omega(z)\\cosh\\xi\\cos\\eta$<br>\n",
        "$y=\\sqrt{\\varepsilon/2}\\omega(z)\\sinh\\xi\\sin\\eta$,"
      ],
      "id": "d3fd4d99-c58c-4dd9-89c6-f96c98c4bbab"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</center>"
      ],
      "id": "fcede6f7-8c42-4f96-81ed-1ba8aac92caf"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "the IGB has field profile"
      ],
      "id": "53a30691-fece-46ce-a41f-38431f9e5b86"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<center>"
      ],
      "id": "16b43df0-5c37-41d6-b8c4-8997aa8a196d"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$u_\\varepsilon(\\xi,\\eta,z)=\\frac{\\omega_0}{\\omega(z)}C_p^m(i\\xi,\\varepsilon)C_p^m(\\eta,\\varepsilon)\\exp\\Bigr[-\\frac{r^2}{\\omega(z)^2} + ik\\frac{r^2}{2R(z)}\\Bigr]\\exp(ikz)\\exp\\Bigl(-i\\psi(z)\\Bigr)$"
      ],
      "id": "403f22ef-71b0-498d-9500-3140498aee2d"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</center>"
      ],
      "id": "5a5c88de-fa52-4d4a-aca0-c2f858e90a62"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "where:"
      ],
      "id": "e742b973-ebf7-407d-bb8e-490d0af4d6cd"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "ef63ba90-d573-49ee-885c-5d4c2bf73d66"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$k=\\frac{2\\pi n}{\\lambda}$ is the wavenumber"
      ],
      "id": "77fd7b39-1e40-4161-8d83-b7e1340e3c2f"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "0c810fc4-fdbe-46c8-8b71-0a3db888c130"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "cca32950-5fd8-4a4b-8c7c-a31276f0dd38"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\omega_0$ is the beam waist"
      ],
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      "metadata": {},
      "source": [
        "$z_R=\\frac{\\pi n_\\epsilon\\omega_0^2}{\\lambda}$ is the Rayleigh length"
      ],
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      "source": [
        "$\\omega(z)=\\omega_0\\sqrt{1+\\frac{z^2}{z_R^2}}$ is the beam radius"
      ],
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      "metadata": {},
      "source": [
        "$R(z)=z(1+\\frac{z_R^2}{z^2})$ is the wavefront curvature"
      ],
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    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$z_R=\\frac{\\pi n_\\epsilon\\omega_0^2}{\\lambda}$ is the Rayleigh length"
      ],
      "id": "f4d1a3e7-de00-48e0-b530-45ce3214a1ae"
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    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\psi(z)=(p+1)\\arctan(\\frac{z}{z_R})$ is the phase function"
      ],
      "id": "0eca0409-25fb-4495-b1fe-58d4500fdf07"
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      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$C_p^m(\\cdot,\\varepsilon)$ is an Ince-Gaussian polynomial of order $p$\n",
        "and degree $m$ with ellipticity $\\varepsilon$. Note that $m$ and $p$\n",
        "must have the same parity with $m\\leq p$ and $\\varepsilon\\in(0,\\infty)$"
      ],
      "id": "40672255-2dd2-49f6-a5dd-fdf074f630f3"
    },
    {
      "cell_type": "raw",
      "metadata": {
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        "</li>"
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      "id": "733ccb86-f23c-4c3a-abc4-a56133c06e72"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<br> We also add a visualization option for the beam to ensure that the\n",
        "correct Ince polynomial is solved for."
      ],
      "id": "e2c0b210-904f-45b9-bc19-5a1351311176"
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {},
      "outputs": [],
      "source": [
        "from scipy.interpolate import RectBivariateSpline\n",
        "from scipy.special import gamma\n",
        "\n",
        "\n",
        "def InceGaussian(\n",
        "    size,\n",
        "    m,\n",
        "    p,\n",
        "    e,\n",
        "    source_time,\n",
        "    center=(0, 0, 0),\n",
        "    direction=\"+\",\n",
        "    pol_angle=0,\n",
        "    angle_phi=0,\n",
        "    angle_theta=0,\n",
        "    w0=1,\n",
        "    waist_distance=0,\n",
        "    num_sampling_points=501,\n",
        "    normalize=True,\n",
        "    display_profile=False,\n",
        "):\n",
        "    if not isinstance(m, int):\n",
        "        raise TypeError(\"Degree m must be an integer.\")\n",
        "    if not isinstance(p, int):\n",
        "        raise TypeError(\"Order p must be an integer.\")\n",
        "    if m < 0 or p < 0:\n",
        "        raise ValueError(\"m and p must be nonnegative.\")\n",
        "    if (p - m) % 2 == 1:\n",
        "        raise ValueError(\"m and p must have the same parity.\")\n",
        "    if m > p:\n",
        "        raise ValueError(\"m must be less than or equal to p.\")\n",
        "    if e <= 0:\n",
        "        raise ValueError(\"Ellipticity must be greater than 0.\")\n",
        "\n",
        "    freqs = [source_time.freq0]\n",
        "    L = max(size) / 2\n",
        "    N = num_sampling_points if num_sampling_points % 2 == 1 else num_sampling_points + 1\n",
        "    x = np.linspace(-L, L, N)\n",
        "    y = np.linspace(-L, L, N)\n",
        "    X, Y = np.meshgrid(x, y)\n",
        "    R = np.sqrt(X**2 + Y**2)\n",
        "\n",
        "    class IG_obj(BeamProfile):\n",
        "        \"\"\"Component for constructing Ince-Gaussian beam data. The normal direction is implicitly\n",
        "        defined by the ``size`` parameter.\n",
        "\n",
        "        from https://www.mathworks.com/matlabcentral/fileexchange/46222-ince-gaussian-beam\n",
        "\n",
        "        Copyright (c) 2014, Miguel A. Bandres\n",
        "        All rights reserved.\n",
        "\n",
        "        Redistribution and use in source and binary forms, with or without\n",
        "        modification, are permitted provided that the following conditions are met:\n",
        "\n",
        "        * Redistributions of source code must retain the above copyright notice, this\n",
        "          list of conditions and the following disclaimer.\n",
        "\n",
        "        * Redistributions in binary form must reproduce the above copyright notice,\n",
        "          this list of conditions and the following disclaimer in the documentation\n",
        "          and/or other materials provided with the distribution\n",
        "        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n",
        "        AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n",
        "        IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\n",
        "        DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE\n",
        "        FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\n",
        "        DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\n",
        "        SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\n",
        "        CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\n",
        "        OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\n",
        "        OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n",
        "        \"\"\"\n",
        "\n",
        "        def scalar_field(self, points, background_n):\n",
        "            x_p, y_p, z = points\n",
        "            z += waist_distance\n",
        "\n",
        "            wvl0 = td.C_0 / source_time.freq0\n",
        "            k = 2 * np.pi * background_n / wvl0\n",
        "            zR = np.real(np.pi * background_n * w0**2 / wvl0)\n",
        "            wz = w0 * np.sqrt(1 + z[0] ** 2 / zR**2)\n",
        "\n",
        "            def mesh_elliptic(f_m):\n",
        "                xi_m, eta_m = np.zeros((N, N)), np.zeros((N, N))\n",
        "\n",
        "                elliptic_complex = np.arccosh(\n",
        "                    (\n",
        "                        X[0 : (N + 1) // 2, (N - 1) // 2 : N]\n",
        "                        + 1j * Y[0 : (N + 1) // 2, (N - 1) // 2 : N]\n",
        "                    )\n",
        "                    / f_m\n",
        "                )\n",
        "                xi0 = np.real(elliptic_complex)\n",
        "                eta0 = np.imag(elliptic_complex)\n",
        "                eta0 = np.where(eta0 < 0, eta0 + 2 * np.pi, eta0)\n",
        "\n",
        "                xi_m[: (N + 1) // 2, (N - 1) // 2 :] = xi0\n",
        "                xi_m[: (N + 1) // 2, : (N - 1) // 2] = xi_m[: (N + 1) // 2, (N + 3) // 2 - 1 :][\n",
        "                    :, ::-1\n",
        "                ]\n",
        "                xi_m[(N + 3) // 2 - 1 :, :] = xi_m[: (N - 1) // 2, :][::-1, :]\n",
        "\n",
        "                eta_m[: (N + 1) // 2, (N - 1) // 2 :] = eta0\n",
        "                eta_m[: (N + 1) // 2, : (N - 1) // 2] = (\n",
        "                    np.pi - eta_m[: (N + 1) // 2, (N + 3) // 2 - 1 :][:, ::-1]\n",
        "                )\n",
        "                eta_m[(N + 3) // 2 - 1 :, :] = np.pi + eta_m[: (N - 1) // 2, :][::-1, ::-1]\n",
        "\n",
        "                return xi_m, eta_m\n",
        "\n",
        "            def C(e_coord):  # Even Ince polynomials\n",
        "                if p == 0 and m == 0:\n",
        "                    return 1 + 0j, [1 + 0j], 0j\n",
        "                if np.isscalar(e_coord):\n",
        "                    e_coord = np.asarray(e_coord)\n",
        "                shape = e_coord.shape\n",
        "                if len(shape) == 1:\n",
        "                    largo, ancho = (shape[0], 1)\n",
        "                elif len(shape) >= 2:\n",
        "                    largo, ancho = (shape[0], shape[1])  # largo = rows, ancho = cols\n",
        "                else:  # scalar or empty\n",
        "                    largo, ancho = (1, 1)\n",
        "                e_coord = e_coord.flatten(order=\"F\")  # MATLAB uses column-major order\n",
        "                e_coord = e_coord.reshape(1, -1)\n",
        "\n",
        "                if p % 2 == 0:\n",
        "                    j, N_c, n = p / 2, p / 2 + 1, int(m / 2 + 1)\n",
        "                    M = np.diag(e * (j + np.arange(1, N_c)), k=1)\n",
        "                    M += np.diag(\n",
        "                        np.concatenate(([2 * e * j], e * (j - np.arange(1, N_c - 1)))), k=-1\n",
        "                    )\n",
        "                    M += np.diag(np.concatenate(([0], 4 * ((np.arange(0, N_c - 1) + 1) ** 2))))\n",
        "\n",
        "                    ets, A = np.linalg.eig(M)  # ets = eigenvalues, A = eigenvectors\n",
        "                    index = np.argsort(ets)  # indices to sort eigenvalues\n",
        "                    ets = ets[index]  # sorted eigenvalues\n",
        "                    A = A[:, index]\n",
        "\n",
        "                    mv = np.arange(2, p, 2)\n",
        "                    N2 = np.sqrt(\n",
        "                        2 * A[0, n - 1] ** 2 * gamma(p / 2 + 1) ** 2\n",
        "                        + np.sum(\n",
        "                            (\n",
        "                                np.sqrt(gamma((p + mv) / 2 + 1) * gamma((p - mv) / 2 + 1))\n",
        "                                * A[2 : int(p / 2 + 2), n - 1]\n",
        "                            )\n",
        "                            ** 2\n",
        "                        )\n",
        "                    )\n",
        "                    NS = np.sign(np.sum(A[:, n - 1]))\n",
        "                    A = A / N2 * NS\n",
        "\n",
        "                    rr = np.arange(0, N_c)\n",
        "                    Rr, Xr = np.meshgrid(rr, e_coord)\n",
        "                    IP = np.cos(2 * Xr * Rr) @ A[:, n - 1]\n",
        "                    IP = np.reshape(IP, (largo, ancho), order=\"F\")\n",
        "\n",
        "                    dIP = -2 * Rr * np.sin(2 * Xr * Rr) @ A[:, n - 1]\n",
        "                    dIP = np.reshape(dIP, (largo, ancho), order=\"F\")\n",
        "\n",
        "                else:  # p is odd\n",
        "                    j, N_c, n = int((p - 1) / 2), (p - 1) / 2 + 1, int((m + 1) / 2)\n",
        "                    M = np.diag(e / 2 * (p + (2 * np.arange(0, N_c - 1) + 2)), k=1)\n",
        "                    M += np.diag(e / 2 * (p - (2 * np.arange(1, N_c) - 1)), k=-1)\n",
        "                    M += np.diag(\n",
        "                        np.concatenate(([e / 2 + p * e / 2 + 1], (2 * np.arange(1, N_c) + 1) ** 2))\n",
        "                    )\n",
        "\n",
        "                    ets, A = np.linalg.eig(M)  # ets = eigenvalues, A = eigenvectors\n",
        "                    index = np.argsort(ets)  # indices to sort eigenvalues\n",
        "                    ets = ets[index]  # sorted eigenvalues\n",
        "                    A = A[:, index]\n",
        "\n",
        "                    mv = np.arange(1, p + 1, 2)\n",
        "                    N2 = np.sqrt(\n",
        "                        np.sum(\n",
        "                            (\n",
        "                                np.sqrt(gamma((p + mv) / 2 + 1) * gamma((p - mv) / 2 + 1))\n",
        "                                * A[:, n - 1]\n",
        "                            )\n",
        "                            ** 2\n",
        "                        )\n",
        "                    )\n",
        "                    NS = np.sign(np.sum(A[:, n - 1]))\n",
        "                    A = A / N2 * NS\n",
        "\n",
        "                    rr = 2 * np.arange(0, N_c) + 1\n",
        "                    Rr, Xr = np.meshgrid(rr, e_coord)\n",
        "                    IP = np.cos(Xr * Rr) @ A[:, n - 1]\n",
        "                    IP = np.reshape(IP, (largo, ancho), order=\"F\")\n",
        "\n",
        "                    dIP = -Rr * np.sin(Xr * Rr) @ A[:, n - 1]\n",
        "                    dIP = np.reshape(dIP, (largo, ancho), order=\"F\")\n",
        "\n",
        "                return IP, A[:, n - 1], dIP\n",
        "\n",
        "            f0 = np.sqrt(e / 2) * w0\n",
        "\n",
        "            if z.any() == 0:\n",
        "                xi, eta = mesh_elliptic(f0)\n",
        "                Ince_eta, _, _ = C(eta)\n",
        "                Ince_ixi, _, _ = C(1j * xi)\n",
        "                IGB = Ince_eta * Ince_ixi * np.exp(-((R / w0) ** 2))\n",
        "            else:\n",
        "                Rz = z[0] * (1 + (zR / z[0]) ** 2)\n",
        "                f = f0 * wz / w0\n",
        "                xi, eta = mesh_elliptic(f)\n",
        "                Ince_eta, _, _ = C(eta)\n",
        "                Ince_ixi, _, _ = C(1j * xi)\n",
        "                IGB = (w0 / wz) * Ince_eta * Ince_ixi * np.exp(-((R / wz) ** 2))\n",
        "                IGB *= np.exp(\n",
        "                    1j * (k * z[0] + k * R**2 / (2 * Rz) - (p + 1) * np.arctan2(z[0], zR))\n",
        "                )\n",
        "\n",
        "            C0, coef, _ = C(0)\n",
        "            Cpi2, _, DCpi2 = C(np.pi / 2)\n",
        "\n",
        "            if normalize:\n",
        "                if p % 2 == 0:\n",
        "                    norm = (\n",
        "                        (-1) ** (m / 2)\n",
        "                        * np.sqrt(2)\n",
        "                        * gamma(p / 2 + 1)\n",
        "                        * coef[0]\n",
        "                        * np.sqrt(2 / np.pi)\n",
        "                        / w0\n",
        "                        / C0\n",
        "                        / Cpi2\n",
        "                    )\n",
        "                else:\n",
        "                    norm = (\n",
        "                        (-1) ** ((m + 1) / 2)\n",
        "                        * gamma((p + 1) / 2 + 1)\n",
        "                        * np.sqrt(4 * e / np.pi)\n",
        "                        * coef[0]\n",
        "                        / w0\n",
        "                        / C0\n",
        "                        / DCpi2\n",
        "                    )\n",
        "\n",
        "                IGB = IGB * norm\n",
        "\n",
        "            # interpolate 2D grid to points' coordinates\n",
        "            IGB = np.real(IGB)\n",
        "\n",
        "            shifted_points_x = x_p.reshape(-1) - np.min(np.abs(x_p))\n",
        "            shifted_points_y = y_p.reshape(-1) - np.min(np.abs(y_p))\n",
        "            IGB_interp = RectBivariateSpline(x, y, IGB)\n",
        "\n",
        "            sqrt = int(np.sqrt(len(x_p)))\n",
        "            square_x = shifted_points_x.reshape(sqrt, sqrt)\n",
        "            square_y = shifted_points_y.reshape(sqrt, sqrt)\n",
        "\n",
        "            IGB_recast = IGB_interp(square_x[:, 0], square_y[0, :]).T\n",
        "\n",
        "            # check profile\n",
        "            if display_profile:\n",
        "                plt.imshow(np.abs(IGB_recast).T, cmap=\"hot\")\n",
        "\n",
        "            return IGB_recast.ravel().reshape(-1, 1)\n",
        "\n",
        "        plt.show()\n",
        "\n",
        "    IG_obj = IG_obj(\n",
        "        center=center,\n",
        "        size=size,\n",
        "        freqs=freqs,\n",
        "        angle_theta=angle_theta,\n",
        "        angle_phi=angle_phi,\n",
        "        pol_angle=pol_angle,\n",
        "        direction=direction,\n",
        "    )\n",
        "    field_data = IG_obj.field_data\n",
        "    field_dataset = td.FieldDataset(\n",
        "        Ex=field_data.Ex,\n",
        "        Ey=field_data.Ey,\n",
        "        Ez=field_data.Ez,\n",
        "        Hx=field_data.Hx,\n",
        "        Hy=field_data.Hy,\n",
        "        Hz=field_data.Hz,\n",
        "    )\n",
        "    IG_source = td.CustomFieldSource(\n",
        "        center=center, size=size, source_time=source_time, field_dataset=field_dataset\n",
        "    )\n",
        "    return IG_source"
      ],
      "id": "0c701454"
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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+Yl4a5eVp8cWRyr/SMlaHoq46XyrP006UW1IoKX/rSD/xH9SNrvVGrn6rbnQt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\nnn7X8vK5NLSqZHQR3UmMExqT7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1VkehcVw8N7nvJzmqdZe2z07LXWqpHVu5du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oxjZQ2WdWmG3uXylwlXplTnVV3lPvO16YjZTHdmrkj20586IyRe+q9ej5U9CXJyGEEEIIIYTI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\nRU5ErkJggg==\n"
          }
        }
      ],
      "source": [
        "freq0 = td.C_0 / 0.532\n",
        "IGB_x = -1\n",
        "IGB_99 = InceGaussian(\n",
        "    center=(IGB_x, 0, 0),\n",
        "    size=(0, 6, 6),\n",
        "    m=9,\n",
        "    p=9,\n",
        "    e=2,\n",
        "    source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10),\n",
        "    waist_distance=IGB_x,\n",
        "    display_profile=True,\n",
        ")"
      ],
      "id": "034c3a6a"
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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W3liMrUDUu/Pa605RGI/JI114/nu4jILF/jhRvUq5jN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\nYII=\n"
          }
        }
      ],
      "source": [
        "IGB = InceGaussian(\n",
        "    center=(IGB_x, 0, 0),\n",
        "    size=(0, 6, 6),\n",
        "    m=4,\n",
        "    p=10,\n",
        "    e=2,\n",
        "    source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10),\n",
        "    waist_distance=IGB_x,\n",
        "    display_profile=True,\n",
        ")"
      ],
      "id": "ba07ab31"
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {},
      "outputs": [],
      "source": [
        "sim_size = (10.5, 10, 10)\n",
        "sim_center = (IGB_x + sim_size[0] / 2 - 0.1, 0, 0)\n",
        "\n",
        "num_field_monitors = 61\n",
        "field_monitor_xs = np.linspace(IGB_x + 0.1, IGB_x + sim_size[0] / 2 - 0.1, num_field_monitors)\n",
        "field_monitors = []\n",
        "for x in field_monitor_xs:\n",
        "    field_monitor = td.FieldMonitor(\n",
        "        center=(x, 0, 0), size=(0, sim_size[1], sim_size[2]), name=str(x), freqs=[freq0]\n",
        "    )\n",
        "    field_monitors.append(field_monitor)\n",
        "\n",
        "auto = td.AutoGrid(min_steps_per_wvl=40)\n",
        "\n",
        "Ince_Gaussian_test_sim = td.Simulation(\n",
        "    center=sim_center,\n",
        "    size=sim_size,\n",
        "    structures=[],\n",
        "    sources=[IGB],\n",
        "    monitors=field_monitors,\n",
        "    run_time=1e-13,\n",
        "    grid_spec=td.GridSpec(grid_x=auto, grid_y=auto, grid_z=auto),\n",
        ")"
      ],
      "id": "e74c7584"
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "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\">10:36:27 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'Ince-Gaussian test'</span> with resource_id                 \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-c04e44a2-cc83-4874-9150-a799d8bef6b0'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \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>View task using web UI at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04e44a2-cc83-4874-9150-a799d8bef6b0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04e44a2-cc8</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04e44a2-cc83-4874-9150-a799d8bef6b0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">3-4874-9150-a799d8bef6b0'</span></a>.                                         \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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"2b13234084d0478fbc814ce8b0cf20bb\",\"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\">10:36:29 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.586</span>. This assumes the FDTD solver runs\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for the full simulation time; if early shutoff is reached, the     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed cost can be lower. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed FlexCredit cost after a simulation run.                     \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\">10:36:30 UTC </span>status = queued                                                    \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>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"4eed76edaf664770ae5d35895e6819fc\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
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        },
        {
          "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\">10:36:45 UTC </span>status = preprocess                                                \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>"
            ]
          }
        },
        {
          "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\">10:36:56 UTC </span>starting up solver                                                 \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>running solver                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"03b34d4b610e4466868314f59d1ae180\",\"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\">10:39:31 UTC </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">70</span>%, exiting.                            \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>"
            ]
          }
        },
        {
          "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\">10:39:32 UTC </span>status = postprocess                                               \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"9a7af268cf03453b90f5ad9eeeaba9cd\",\"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\">10:40:25 UTC </span>status = success                                                   \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>"
            ]
          }
        },
        {
          "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\">10:40:27 UTC </span>View simulation result at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04e44a2-cc83-4874-9150-a799d8bef6b0\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04e44a2-cc8</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04e44a2-cc83-4874-9150-a799d8bef6b0\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">3-4874-9150-a799d8bef6b0'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"75515bf043a44bb082bbe66c82a685b1\",\"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\">10:44:20 UTC </span>Loading results from simulation_data.hdf5                          \n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "ince_gaussian_sim_data = web.run(simulation=Ince_Gaussian_test_sim, task_name=\"Ince-Gaussian test\")"
      ],
      "id": "2c552fd6"
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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icnISu+22Gw4++GDstNNOmDNnDubPn48bb7wRv/zlLzFv3jzjpihjUMcbABYv\nXoyDDz7YjID18Y9/HG9605ucec444wxce+21uOuuu3D11VfjS1/6Ej7zmc90va5hc+KJJ+Kcc87B\nggUL8Pzzz2OnnXbCoYceil122QVLLLEE/vKXv+CHP/whnnrqKQAqjans3Dr55JNxzjnnAADe/e53\nF9bL+upXv4qzzz4b++yzD7baaiustdZaWHbZZfHoo4/ikksuwf/+7/86ozydcsoppWl3Te9HXfbY\nYw9T3+jaa6/FbrvtVut7rVYLxx9/PC6//HK84x3vwNprr41Fixbh1ltvxU9/+lM89NBDmDVrlunT\n3/nOdzBr1ixsvvnm2Hjjjfve7ia57bbb8OyzzwIAdt5555Eqnk4IIaSCYStIhBBSl7vvvltutNFG\nzlPOsn8h90a3DhwppXzwwQflxhtvXGudURTJ733ve8HlXHzxxcbVUOffJptsIp9++unGl1GXJtfV\n6XQcB0SdfxMTE/Lmm28OLm/RokXy7W9/e+1lHXfcccHlfOc73yn93j777OPMX8eBI2Vz54yUw3Hg\nSCnl//3f/8l2u125/bNnz5bf/e53zfsiB46U3R/vuhx99NFmGVtvvbVctGhRcL4///nPcmJiQgLK\nyfenP/2pp/UNm4suuqhW2wCQp59+eumyDjroIDPvu9/97sL5jjrqqNr97eSTT57y/ajL/fffb5a5\n6667ls5rO3AOOeQQucwyyxRu37LLLit//vOf56Z/7nOfM8sbFQfO6aefbub95je/WbkdhBBCRgcW\nMSaEjA0bb7wxbrjhBhx66KGVNU9WWmklzJ49u5H1rrPOOvjTn/6Egw46qLQezEYbbYT/9//+X2Et\nhz333BM333wzDjjgAGd4bR8hBP7t3/4N1157LVZcccXGl1GXJtfVarXw4x//GGeffTY22mij0vXO\nmjUL7373u3H77bcXFvVdYoklcP755+NrX/uaM/JT0bxrr7128LMjjzwyNzpQEzR1zgyTnXfeGeee\ne64pABziFa94Ba6++mpsscUWtZY5iON98cUX4/TTTweghon+1a9+ZQpJ+2y77bamRkscx3jXu95l\nnAjjxF577YU//OEPpc6OlVZaCb/4xS9w1FFHNbLOddZZBxMTE6XzvPzlL8eVV16J448/vtYyh7Ef\n66+/PnbccUcAwDXXXIN58+bV+t7aa6+Nc845x6nlpFl++eXx29/+Fu985ztzw6aXXTuHxW9+8xsA\n6rp80EEHDXdjCCGEdMXo/aoQQkgJK6+8Mn784x/jxBNPxO9//3v89a9/xdy5cxFFEVZbbTWsueaa\n2GWXXbDDDjsERZ4NN9zQDN273nrr1V7vnDlz8Otf/xonnngi/vd//xd///vfMW/ePCy99NJYe+21\nsfvuu2P33XevDHC22mor/H//3/+HJ554Ar/73e9w44034rHHHkMURZgzZw5e8YpXYN999y0dFaSJ\nZdSl6XW9973vxbve9S6T4nb//ffj6aefxpJLLok111wT22+/Pd70pjdVijKAEo4+8YlP4Mgjj8Rl\nl12Gq6++Go8++ihefPFFzJkzB6utthq23npr7LnnnmbkKp9Wq4Vf/epX+NjHPoaLLroId911F557\n7jl0Oh0AKuC3mZiYMOdPlRDV1Dmz3HLLmXW++tWvrjwu66yzTu1trOLtb387dtttN5xzzjm4/vrr\n8dRTT2G55ZYzKXWvf/3rEUURbr31VrPOsoKo3R7vKjqdDn7961+bdKn3ve992GyzzUq/c8wxx+De\ne+/Fv/71LwDAueeei/e///1drXcU2HnnnXHHHXfg8ssvx2WXXYaHH34YnU4Ha6yxBnbaaSe85S1v\nMSPAlfGqV73KFK0uGwXtE5/4BN7//vfj0ksvxV//+lc88sgjmD9/PlZeeWVssMEGePOb31zr/BzU\nfnTDEUccgWuvvRadTgfnn38+PvCBD9T63j777IO77roLP/7xj3H77bdDCIFXvvKVOPzww7HqqqsC\nAC666CJ8+ctfxrx587DHHnvgkEMOMd/vti/vvPPO5tpaJQTZw9KvtdZahfM9/vjjpnD6Pvvsg9VW\nW61yOwghhIwOQkoph70RhBBCCCGETAWLFi3CeuuthyeeeALbbbcdbrzxxuB8P//5z/He974XAPDp\nT38aX/ziF6dyMwfCySefbEZx/MMf/jAyI98RQgipB1OoCCGEEELIjGHWrFn4xCc+AQC46aabcMMN\nNwx5i6aGTqeD73//+wBUMXiKN4QQMn5QwCGEEEIIITOK//iP/8Dqq68OAPjKV74y5K2ZGs455xw8\n8MADAICTTjppyFtDCCGkFyjgEEIIIYSQGcXSSy+NL3/5ywCACy+8EH/729+GvEWDpdPpGNFm3333\nxR577DHkLSKEENILLGJMCCGEEEJmHP/+7/9uip9feuml2HrrrYe9SQPjhhtuwPrrr48NNtgAp512\n2rA3hxBCSI9QwCGEEEIIITMOIQR+/OMfD3szpoQdd9wRF1988bA3gxBCSJ9QwCGEEEIIIcRjzTXX\nNENzb7rppkPeGkIIIYTDiBNCCCGEEEIIIYSMPCxiTAghhBBCCCGEEDLiUMAhhBBCCCGEEEIIGXEo\n4BBCCCGEEEIIIYSMOBRwCCGEEEIIIYQQQkYcCjiEEEIIIYQQQgghIw4FHEIIIYQQQgghZIS59957\nwQGkCYcRJ33R6XTw0EMPAQCWX355RBE1QUIIIYQQQgiQJAmee+45AMA666yDdrs95C0aT6SU2GGH\nHXDMMcdg//33H/bmkCFCAYf0xf33348NN9xw2JtBCCGEEEIIGWHuu+8+bLDBBsPejLHkvPPOw4EH\nHoiNN94Yt99+O5ZYYolhbxIZErRLEEIIIYQQQgghI8jixYtx/PHHAwDuuece/OAHPxjyFpFhQgcO\n6Yt58+ZhlVVWSd9FAMQwN4eQEWfY/WPY6x8GTf7ENbWsftuh6XYcx2c5SYPLaqJdm1hG0+3K/j7z\n1k/IKCKhr9lPPfUUVl555eFuzhjyrW99C0cddZR5v8oqs3HPPQ9g9uzZQ9wqMiwo4JC+eOaZZ7DS\nSiul71qYmTeMhNRDDLt/iBnaPxv6mZMNBWd9nweNt+M4CjhAYyJOA+dHE+dG49cH9vepXzUFHEIC\nSAAxAODpp5/GiiuuONzNGTPmz5+PjTdeD/PmPYfPf+FQ/PePfoeHHpqLT37yk/jyl7887M0jQ2Bc\n79oIIYR0w0wN5kgFvA2YlrC/E0LItOCUU07BvHnPYb31VsMxx7wTJ510OADgtNO+bgaSITML3rkR\nQgghhBBCCCEjxIMPPojTT/8GAOCkkw7HkksugXe9ew+86lUb46WXFuMzn/nMkLeQDAMKOIQQQgiZ\nudCtQgghZAT5zGc+g0WLJrHNNpvgnQfvDgCIoginnPpBAMDZZ5+NW265ZZibSIYABRxCCCHTm4YC\n9KHXMCIeo3MLw3ODADwPCCHNcfPNN+NnP/sZAOCUUz+IKMp+8/bYY1vsuedrIKXEf/3Xfw1rE8mQ\nGJ27H0IIIYRMIbwFGBUaDfzpKCKEkLFGSoljjz0WUkq8+c3bY7fdtsnNc8qpRyKKIlx66aW49NJL\nh7CVZFjw7o0QQggZFxicE1IO+wghZMy55JJLcPnllyOKIpx8ypHBebbaakMccsieAIBjjz0WcRxP\n5SaSIUIBhxBCCCGEEEIIGTJxHJu0qH//973w8pdvUDjv579wKJZaahZuvfVWk25Fpj8UcAghZAoY\nam0EPpEeGVgjo2l4G0MIIWT6cPbZZ+O2227D0ksvic9/4dDSeddaaw4+dvSBAIATTjgBCxcunIpN\nJEOGdz6EEEKmPxSxPPjzTwghhIwSCxcuxAknnAAAOPrjB2LNNVep/M6xx74Tc+asgEceeQTf/OY3\nB72JZATgHRwhhBBCyHSAQiUhhIwtp512Gh599FGsuuqKOOaYd9b6zvLLL4PPfu4QAMDJJ38RTz75\n5CA3kYwAFHAIIYSQmjAFihBCCCFNM3fuXJx66pcBAJ/73L9jueWWrv3dI47YF5tuug6ef34hTjzx\nxEFtIhkRKOAQQgghZIwZ71sZioKEEEJOPPFEPP/8Qmy22To47PC9u/ruxEQbJ5/8AQDA9753Ju66\n665BbCIZEcb7rocQQgipC9NLUvjTn4PnxvSC7UkIGSPuuusufP/73wMAnHzyBzAx0e56GW/db0fs\nsOPL0enE+OQnP9n0JpIRgndxhBBCCCHjDkULQggZS44//nh0OjF22vkVeMtbd+xpGUIIfOUrHwIA\nXHDBBfjTn/7U5CaSEYICDiGETGcY1E0f2JaEEELItOKaa67BhRdeCAD4ylc+CNHHb/1rX/syHHDA\n6wEAxxxzDKSUjWwjGS0o4BBCCCFdINL/yCjB2xlCCCHjhZQSxx57LADgwAN3xWtes0Xfy/zSl9+P\niYk2rrvuOlxwwQV9L4+MHrzjIYQQMnOY8S4W/uwPCop6hBBCuuH888/H9ddfj4mJNr705fc3ssyN\nNloLH/rQfgBUatbixYsbWS4ZHXgnRwghhBAyBBoTfWa8MEkIIePF4sWLcfzxxwMAPvTht2HDDdds\nbNmf+vR7sfzyy+Cee+7B97///caWS0YDCjiEEEIIIWR6QVGLEDLCfO9738O9996L2bOXwac//Z5G\nl73KKrNx/CffDQD4whdOwLPPPtvo8slwoYBDCCHTFQYwIwVTbAYNb2kIIYSMPvPnz8eJJ34GAHD8\nJ9+NlVee3fg6PvrRd2CddVbFvHnP4dRTT218+WR48G6HEELIFBEF/g2BGSts8Se/lBl7XvTKiPRn\nQggZM0499VTMm/cc1l13NXz0o/sPZB1LLTULJ510OADgtNO+joceemgg6yFTD39tCSGEDJiy4G58\nAz86ashIMOXC0/Tsz03B6wIhpIyHHnoIp5/+DQDASScdjiWXXGJg63rXu/fA1ltvgpdeWozPfOYz\nA1sPmVpm9q8sIYSQAdJNMMfArxS6Q6Yd4xXod+uyYX8mhJAQJ5xwAl56aTG22WYTHPyu3Qe6riiK\ncMqpRwIAzj77bNxyyy0DXR+ZGvjrSgghA2a8ArWm6PXnhT9LpB94/jRPP8eU7UEIIZqbb74ZP/vZ\nzwAAp5z6QUTR4K+Ru+++Lfbc8zWQUuLYY48d+PrI4OEvKyGEkIbp96dlCn6aZpyjhT/3pBeaOG+G\neO7NuH5OCBlVtIAipcRee22P3XbbZsrWfcqpRyKKIlx22WW49NJLp2y9ZDDwjo4QQqYjQwtcmvpZ\n4c8TIZUMtJ832QfZnwkhM5tLL70Ul19+uZPWNFVstdWGOOSQPQEAxx57LOI4ntL1k2bhLyohhJCG\naPonZfR/omZmehwpYvqcD4Poe6PfnwkhZBDEcWzSl/793/fCy1++wZRvw+e/cCiWWmoWbr31VpPG\nRcYT/poSQggZYfgzRbpl9M+Z0RZ6Bnn8Rr9tCCGkac4++2zcdtttWGqpWfj8Fw4dyjastdYcHP3x\nfwOgCikvXLhwKNtB+oe/pIQQQhpgDIO+KUwzG27Azp/62sz4mik8VwghpEkWLlyIE044AQBw9Mf/\nDWuuucrQtuWYYw7CnDkr4JFHHsHpp58+tO0g/cFfakIIIX0yFT8l/LkixGFsxaYp7stje5wIIdOB\n0047DY8++ihWXXVFHHvsO4e6Lcsvvww++7lDAACnnPIlzJ07d6jbQ3qDd8SEEEJIHwzcXcMAlEwJ\nU3lLyNtPQsj0Z+7cuTj11C8DAD772UOw3HJLD3mLgCOO2BebbroOnn9+IU466aRhbw7pAf6CEkLI\ndGNKA34GfWQU4bnSHTxehBDSNF/84hfx/PMLsdlm6+DwI/YZ9uYAACYm2jj55A8AAL73vTNxzz33\nDHmLSLfwF5sQQkgPRBjOT0jD65z27hb+zI8ao13AeCrhuUkImd7cfPPNAID/+MjbMTHRHu7GWLx1\nvx2xwQZroNOJcfvttw97c0iXjM6ZRAghhJCxpkyckJBTuCXDQ0AMfl8bFR4ppDTNlJwDhJCxYZml\nlxr2JjgIIbDMMksOezNIj/BXmxBCSJcM+6dj2OvPM9NdFSL9r995yFQz7L407PUTQggh4wUdOIQQ\nMkAYsJLpfg50u396/sE7FCIAyYDXQcYCIQBJRwwhZEjIBEhG7PeIl8SxhY8+CCFkOjHwmi6j8rPR\nYA2eaVsHZ7Bt1a+jZmSFrQGeD6O1z6PUlwkhhBBSB/5qEkIIIYQQQgghhIw4TKEihBAyxjBNZhg0\n5SRhsVeiYD8mhExjpBy9FCr+9o4tdOAQQgipCX8yyhit9JjBMIhCxNPxuA10nxpJ8WJfJoQQQsYR\nOnAIIYSMOaP79L7vQH6E6vMMUpQYnBNndM6N6ShUEUIIqcFIOnDIuMJHMIQQQmrAn4s6jE6QPn7t\nNTrHbrozqufGgLdrhMRQQgghpFdG9VecEEJIt8zoAKXPn7MZfeyqmSpxZTqJOPa+jM5+8baPEEII\nGWeYQkUIIaQCBn3doNOBRido74/psh9jz4wQGUcn5a1fWKCbEGKQUv0jpAF4V04IIWSaMDo/adNF\n9BjGfjS/zuGdF4Mo+tw7o9M/CCGEENIb/DUnhJABMTqBWz/wZ2L8GP82G3rfmRFul1Fl/M9fQggh\nZFAwhYoQQsg0oo8UDCFocbYYuohCSNOwjxNChsEojkLFa+HYwscchBAyHaBjYPoxxDYdBfFmFLZh\nZOj7XBi3271x215CCCFkaqADhxBCSAHjGkRNn0KoM53mCsHynCCEEEKmmieffBJ/+9vfsHDhQgDA\nTjvthFVWWaWrZSxcuBC33347nnrqKayyyirYcsstsfTSSw9ic8cCCjiEEELItKF/0Y3Ol+kGhVhC\nCBkqo5hCNSAWLlyI73//+7jhhhtw44034v7773c+v/LKK7HrrrvWWtZzzz2H448/HmeffTZeeOEF\nM33ZZZfFIYccgpNPPhnLLbdck5s/FlDAIYQQEmBcgz5Nj8Efa2SMHByOmRBCCBkP5s6di49//OPm\n/SqrrIKVVloJd911V1fLeeaZZ7DjjjvijjvuAABssskm2HDDDXHPPffg3nvvxXe+8x1cddVVuPba\nazF79uxG92HUGfc7dEIIIYQ0BN03I0hf9W94m5djCmtLsT8RQgAASerAGaV/A2KZZZbBxz72Mfzy\nl7/EPffcgyeffBLHHnts18s59NBDcccdd6DdbuOss87CXXfdhYsvvhj33HMP/vu//xutVgu33347\njjjiiAHsxWhDBw4hhAyAKb1xbzwgYdA3ExnlYLMZFw5TcsYPthkhhIwTc+bMwWmnndbXMq677jr8\n9re/BQAce+yxeN/73ud8fthhh+GOO+7A1772NZx33nm46aabsN122/W1znGCd+mEEEKmKfyJI30w\n9iO78fwnhBAyfpx11lkAgImJCXzsYx8LzvPxj38crVYLAHD22WdP1aaNBPx1J4QQQmzGNnDv/Sd9\nlN03mnHYRjIIeKtKCBlz5AikTPn/Rrje30UXXQQAePWrX41VV101OM8aa6yBV73qVQCA3//+91O1\naSMBfxUJIYRYTLefhTHdn7EVkUij9HwejOl5TwghZEbz7LPP4sEHHwQAbLPNNqXzbrvttgCA+++/\n3xmlarrDX3hCCCFkBjNOzhaR/kdIX1AgJYSQkeSee+4xr9dbb73Sedddd10AgJQS995770C3a5Rg\nEWNCCCEp01XTZyFUouG5MJ7oa9P4tV0zBbgJIWONlAMd+akfFixYgGeeeabw8xVXXHEKt0Y5cDQr\nrLBC6bz25/b3pjsUcAghpGGmzCHAp8iDQ4iRzg/P05v4Nq5uFgbFZUxXIZYQQkjTvOc97yn9XE7x\nvdDChQvN61mzZpXOu9RSS5nXTKEihBBCCCHDgwJtAN62EkLIdGaJJZYwrzudTum8k5OT5nWV2DOd\noAOHEEIIpn9gxNQZn3F132imxIUzQ5xYhBBCBoiUEHI070F+/vOfY++99x72ZhiWW24587rKVWN/\nvuyyyw5sm0YNCjiEEEIImUFQzCMYQ3GOEEKaZ9lll53yOjdlrLnmmub1I488Ujrvww8/bF6vtdZa\nA9umUYOPagghZBxhekUPdPmTN6xj3PV6u/8pH3f3jWa67AfpBt66EkLIdGXdddc1bpp//vOfpfPe\neeedAIDZs2c7ws90h7+ChBAy45m6nwJR4z9CZjw9iYeD6cd1+iz7bjk8NoTMcPQoVKP0b0QdiEII\n7LzzzgCAa665prAOzuTkJP70pz8BAF7/+tdP2faNAhRwCCGkQXijHqabAG+wASF/9qYb7HODoZc+\nSCGHEEJIvxxwwAEAgHnz5uG3v/1tcJ7zzz8f8+fPd+afKbAGTpfceuut+P3vf2/ef+hDH8Ls2bMb\nWfZzzz2HK664Ag8//DBmzZqFTTbZBLvssgtardaULoMQMpMYrKDRbzDH4aKbhwE2MP3q4DTXj5s4\nPwbfb6db+xFCpjVSAgnvZerynve8ByeddBL+9a9/4ROf+AR23HFHrL766ubzRx99FMceeywAYKON\nNsI73/nOYW3qUKCA0wWLFi3CQQcd5OTjvfOd7+xbwFm8eDE+//nP47TTTsNLL73kfLbGGmvgjDPO\nwP777z/wZRBCSJM0JRTo5QxFyBn5Qqd0FAEU+pqiSXFvqP22LiPfvwkhZPy45ppr8NRTT5n3N998\ns/OZds4AwAYbbIBXvvKVzveXWGIJ/PjHP8aee+6JBx54ANtuuy0+/OEPY+ONN8bdd9+N73znO3j8\n8cfNfBMTE4PepZGCAk4XfO5zn8M///lPCCEgG/rBT5IEBx98MC644AIAwFZbbYVddtkFL7zwAv7n\nf/4Hjz32GA444AD88Ic/xBFHHDGwZRBCxogxKGA8CJdHc0H6zH16T/fNGDCk/j2oc2Nw4trM7ceE\nEDLKnHDCCfjjH/8Y/Owzn/mM8/7II4/E9773vdx8b3jDG/Cb3/wGhx56KB599FGccMIJzuerrbYa\nfvrTn2KXXXZpbsPHBAo4Nfnzn/+Mr33ta1hmmWXw1re+Fb/61a8aWe6ZZ55phJfjjjsOp5xyivls\n/vz52GefffCnP/0JH/7wh7Hrrrti4403HsgyCCEzkebdG4MWCOi0GHFEyTklxzTYHnmXRv/9mP2W\nEEIGSJIWMZ4h7LTTTlhhhRVqzfuqV72q8LO9994b99xzDy644ALccMMNmDdvHlZeeWW89rWvxdvf\n/nYst9xyzWzwmEEBpwaLFy/GYYcdhjiOcdJJJ+GJJ55obLknnXQSAGC77bbDySef7Hy+wgor4Je/\n/CU23XRTLF68GCeeeCLOPvvsxpdBCCGEEEIIIYT0yxe/+MXGlrXccsvhkEMOwSGHHNLYMscdJs/X\n4Itf/CJuu+02bLvttvjP//zPxpb7hz/8wYhBH/nIRyACtun11lsPb33rWwEAF154Ya6+TRPLIISQ\nJpiq9BymAfXGwI6biLJ/TczX62bwvOgJ9ltCCCFkfKCAU8Ett9yCU045Ba1WCz/4wQ8aHc3p0ksv\nNa/f+MY3Fs6nP1uwYAGuu+66xpdBCGmG8QpQmr38T/W+9z9ccRf7P5U1ScagvpGhHzFmgEJOfYa9\n/ibobx+G0W+bpYE2nKI+N16/D4SQRpGJSqEapX8jnRpMypgOdy8Do9Pp4NBDD8Xk5CSOOuoobLPN\nNo0u/+9//zsAYJVVVsEaa6xROJ9dmVt/p8llEELGiHEK8KeAmR0UDfEnvCnxpWERZ+zPhyns38M6\nVmPfRoQQQsgQYQ2cEk499VT87W9/w3rrrYcTTzyx8eX/61//AgCss846pfOtvfba5vX999/f+DKq\neOaZZwo/s4eBI4TMTMY3IJs5o9g00kaDcszo5Y5rkeMxZNh9lkWNCSGEkN6ggFPAP/7xD1Mc+Lvf\n/S6WWWaZxtfx3HPPAQCWX3750vnsz59//vnGl1HFSiut1NX8hJBRp7lAfNiBoN4GBoMDZirSnUTU\niIgzc86H3tpkFPpss8wcIZYQMq5IPqQgjcEUqgBxHOOwww7DokWLcNBBB2HvvfceyHpefPFFAMCs\nWbNK57M/199pchmEENIt/degaZaBb8sYp671fWymslbNlNfFGaHboCk4x2ZUn+2GMe7fhBBCZhZ0\n4AT4xje+gRtuuAErrLACTj/99IGtZ8kll8Rzzz2HxYsXl863aNEi5ztNL6OKp59+uvCz+fPnY8MN\nN+xqeYSQHhmRIGOkAi+L3pwX4/j0fjoLKmjMidMoQoxYwccREp76oDm31Dj2Y0LIjCGRqnAwIQ1A\nAcfj7rvvxuc+9zkAqgbO6quvPrB1Lb/88pg7d25lStOCBQvM6+WWW67xZVSx4oordjU/IWSUmR6B\nXxEzJ32mHn2JbcMcJapPEYfnQZ7pJbwSQgghMxMKOB6XXHIJXnzxRSy77LKYN28eTjnllNw8119/\nvXl95plnYsUVV8TSSy+N//zP/+xqXeuttx7uuecePPTQQ6Xz2Z+vv/76jS+DEELqMqpBYH/UfHo/\naBfGiDisAIzAEN8YTSfOmDI9++34QbGKEEJIv1DAKWDBggX41Kc+VTnfV77yFQDAyiuv3LWAs+WW\nW+KKK67A3LlzMXfuXKy66qrB+exhv7fccsvGl0EI6Z+ZECCNyz4ySOqTURBvNH2IOPXPgxFIv+lK\nvOuufcah3zbTZ/tsx5FLkyOETBukVGlUo8SIbQ6pDwUcj2233RbHHXdc6Tx//OMfjQvngx/8IGbP\nnt3TKFV77LEHvvWtbwEArrjiChx88MHB+S6//HIAwFJLLYUddtih8WUQQsaARtwZIxSYD5jpK+LU\nb8OeAvdREm80dOLMCKZvnyWEEEKagwKOx+te9zq87nWvK53n+OOPNwLOcccd13NK0hvf+EastNJK\nePrpp/Hd7343KL489thjuPDCCwEAb3nLW7D00ks3vgxCCKliHJ7i98cIuDBIMRRxemL691tCCCFk\nZjGCj9qmDz/84Q9xyimnFI5kteSSS+KTn/wkAOCaa67BySef7Hy+cOFCvO9978NLL72EKIrw2c9+\ndiDLIITMBHq/3I9rEDiQ7R6lOjVNM4rumz4Zi3O39jkVYeAOrCHT/zb3eQ5P5/5NCBkeMh2FapT+\n0fE4ttCBM0C+/vWv484778Ts2bPxsY99LDjPxz72MVx22WW49NJL8alPfQq///3vseuuu+KFF17A\n+eefjwcffBAA8LWvfa2wdk0TyyCEjDAMKnpmpqZldB0Ij4N4QxfOjGCm9llCCCGkDhRwhky73caF\nF16IT3ziE/jBD36Aa665Btdcc435fPbs2fj617+Oww8/fKDLIISQEOP4FL93Zmga1TiINxq9rV0I\nOfUEgRptP9Qit9OvcPHgmKH9mBBCyIyAAk4P7Lrrrub17NmzC+f7wAc+gLlz52KppZYqXd7SSy+N\nM888E5/97Gdx8cUX46GHHsKsWbOw6aabYq+99qr8flPLIIRMV3oL0KdLENj4E33tiJryYL5eO06X\ndiuFbpxpzXR24UznfSOEFKBTqAhpAAo4PbDXXnthr732qpzv4x//eFfLXWONNXDooYf2ulmNLYMQ\n0h0zImBukjqOj6EF50N6ej+sNLlxct9MRwbQ7o1ej+qeH9NJTONw4oQQQkYYCjiEEDLKDCmwH0wB\n4C7EAnveBoJDPvUOMO7iTRcunPFu/ykuXNzLedFwfwX6bTOmURFCRgeRSIhRc+BQqB5bxvzujRBC\nSDkjcJkXUX9iQb/fHxQjWFx6xrnBGj0vRvAcm0qa6mcN9tcZdz4TQgghFdCBQwghxKGxoKlp0aWH\nArbO12s/0R/Fp/cDOpaN0c3yRu3YDomGBcC++u0gBNKh1ynqox8zjYoQQsiIQgGHEEJGlb4DvO6D\nspEVb/xlD1zEGT9qt11jbdPrcuzvNRDg1zwfxrPtB+wKGrSzrU/RFRjXditnOu4TIaQMSVGYNAYF\nHEII6RHa+wNMVapTA4FhOaPowhkFBuXcGZNjPbQRyMrp6Vo0lWmJQ3fjEEIIIdODGZ7wTQghI8oQ\n6qv0LUgNo05ND+tsdpSeJorGTmFb99VGg2zfqL/l19yv6rafKgGyTpsP2MU21fSxTpH+1z39nFMU\n6AkhhIwedOAQQsi0ZIoDtGEWGR64G2fYVB/bwbrBprJt+6lbMjNdHl23/bD7KtOpCCEzjUQCozYK\nFRlb6MAhhBAyegVQe6GL7ai3vyOyX03RUzsN4xhMs+M+QMZKvBnaNozAPgdgCi4hhJBeGM1fNUII\nGXEGevM9hOLFPTMKAaHNUFJDxiAQGxvxxl53D+uvsZ9DD5yHlT41Sn21z3SqKWMc+jYhhJAZBVOo\nCCFkhjPyBVC7ZVqPSpSn+YB2lNp2RItJj8Aw0121+yj21ylNeRvR84gQMjOQyeilUI3/7c+MZQR/\n0QkhhPROd5f1aSfeaIY+VPYI0dWxGMX97XKb+m77UTwGfTDK/bXHbRu6i6ohpst+EEIImTrowCGE\nkC6Z0TfdoxwM9kBjLpxeHRmVKRpTXUB4VOnSQVHh7hia+6qh9Kna16Bx6K9T5sTp0YUzAm4rQsiY\nI6EKGY8Uo7Y9pC5j8MtOCCEziL5qLgzYfTMOwaDNuA0t3QOV2167zUZ3HzPGYRtHiHHqrz1s63QR\n0qfLfhBCCJkaxujXnRBCCCGEEEIIIWRmwhQqQgjpghn7tLTRp/ndLKvP1IqpLJQ6tqkW4/QsR29r\njTYddNsPpL0bSp+a8jpADRznHtqr+1Q4FjMmhAwBKUeviDEZWyjgEELItGCA6VNDLQhsf6fHm58a\ngeF0GZHKoVa7NSfeiBrrk40JKv0H4uVtPoBAf6qGpO65v/ZzLjTQT4EpHpmqC3TbjaVASwghZDpB\nAYcQQkaFKQrwptZFNAjnTi+FSPsNDIcR0Jcfu1Fwg9URbcrm70/QqdEmoyoI9MDgnDdNO7D66KdA\n1202HVw401JAJoQQMhAo4BBCSE1GIWAOM8AUmKE8ze9m2c0FYo0EUaOSRjUg9023gk3d5fUu5Ixe\nMN47U53KNuj1TZ3gSgGEEDLSJMnopVDxkjm2jFPiOyGEkD6ZmtSpqR76uub6xmlUnhJE+l9/dO+c\naVq8mbLllyy3/DjW2J66rrk+3XXNum+66DONMD363aAZ3QcEhBBCRgn+qhJCSA0GfnPdU4DXXSA2\nePFmqgNDf901qNivvgP6uvSZPlW+7KrvdnHODFi4aWZ9vJUZ/eHie7g2dJue19U1usfjMFV1jAgh\nhJACmEJFCCHEZSTqaPRCzXSasRydqO66mxVvhoUQUZdpVRVtX9LmfaffVLV3raC/V5cQxkC8seky\n5Y2pVISQ6cIopFeTacEo/JoTQshIM5rW9gE9nR5b8UbTvwto4C6cPp7iT9W5OEzxxt6G7rZj+Ns8\nmgzTGReiy+0Z2Lk4SsdEMZq/NYQQQkaJ0fv1IoSQmcaAbfmDCQoijF5gaFOxXYMWKIaRatGA+2aq\nU6bq0Nj2DFKcLGrvobtvRqstXboUcWq232imuxJCCCHNwBQqQggZO6a+2Oug1l8VnA90mOlBptUA\n4dSaPgP63qkn3owq9VOqehuVaixTbwYs3gy2b2oGk1JVvz2n0yhmhJCRRY7gKFTj9ptHDBRwCCGk\nhHG3tDefOjXYoLBq/u6Dxt5FnPJlony5ZvmWiDPIkYhKj+ugxZtWD9+Ju/5GIyLOIOsf+YLdVIw8\nVcjgh4gPzd+bqEMRhRBCCKkLBRxCCBkmXQd5Axh1asDiTZPODr2sRgvcFq2rKVfGiKdc9NY+vYg2\nRd+vL+bY21p+DjQpCnSxrAH2Z3c9/Ql2ZjENu656659Ad8d4BFw4AyxUPpZuMEJIOQmAhP2aNAMF\nHEIImckMULwZZEpO/UBeMyRXRteEj9mg3DfdtVG/ok2d5XYn5vTk+Cho71EKnAfptgIGny7Xff8E\nunO2NS3iEEIIIePB6Ca8E0II8WjYfTMg8WaqC+HWX1/JPAXfH/iIVAOlpDhu7WPWsv5NBd2tq3wf\nRr19mmY0i1QPbDSxRvejh2WNuLOOEELI9IQOHEIIKWBcRzNpTrzpvybGVFIvfWOa1dvo4ZjXb6ep\nEm3K1l3tyCl34hS0d9cunEGcN12KhlPmtBoM3Tmmah7vGk4cunAIIUNHytErYszL4tgy/F90Qggh\nNWjwct2weDNqQ09Xb0vB50N34fSy/i6X1ZXrZhSotx2jdP4NhDEXbzTdXSuac+LU60N04RBCCBl9\n6MAhhJBhMEz3TSVTUQS1W4Ggu1GLqt043TkzRpLCYz9VbeJS51zobZSiem6cYodHUy6cJulCrOtR\nvBnVvgl0U+y4OSfOOEHXECGEkCIo4BBCyMhTszBpI6lTgxpyuslRi4C6QWNP6TWh5Qw8oGrKfdNr\nQN99+/RyHvQ39HQLjYs4XTFq6XdNiTfD6ZtA3bSqZkScen14tEakIoRME2QyeilUFInHFgo4hBAy\n1QzLdj8U8Wb4Ixd1LeJ0/TR/igP7xuveDDdNqbsRi6rbvSsRZ4ScG927bwqWUztNblB0N6pY/dpV\nQL/9jM4WQggh487oJEYTQsgIMfACxrVpyH3Tp3jTXe2KYY1cVLy+8u0PTA/MOzrnRBHd1r2pbiN9\n3Kaqjkr351kTK+2mrSP0f+vURG2XXmscTXV9o/rr63skOaChkalYC4cQQsjoQgcOIYRMJQO40Z8K\n8aYeo1D4trxeSncj4XRDPy6cJuqh9CLeFDPswrf1a6SE06oGm0rVPN2JgwHBqZZwM0zq1zEC+nTj\nNJJK1QNMpSKEFCEBJCN2fRixzSH1oYBDCCFTRdfiTQNBdB/izSCFm24Fgu5Fl+J6KeHgvl56zTil\nYPQi3vQq3IguzlXZhYBSL6BvQMSZsrau6fYJtkMvrpvu+mYv7d9d3+y3ILVNiRjXt4gzmkIfIYQQ\nQgGHEELGlEE6b5p+ot+vo6Po+9WBPVA/uO+3RkovQd9g3Dfdijd126cboaabZVSJOtVCTritR9Nx\nVUEj4s3U1TXyl1HveFcLOYMWcaoZbkHjcRKLCSEVSDky9dbI+EMBhxBCpoKG3Tf9iTf9pEzVF26m\nIg2neYdGddCmj/1oBFeDF2+aEG2qsNdRJubUE3LqiDjDcOH0WldpvNLjeitKXeyWq15ObyIOU6kI\nIYSMIxRwCCFk0AwjdaqHZTfhuhlW7ZTqoLEbh4YXEA7MhdOE+8abrYugfhSEm6r1Fok55YF9HyJO\nVwzAhZNrk27Em+ZT4/qlvpjTr5AzKBGHqVSEEEJGCwo4hBDi0ehoQyNVtLhX8aZZ4aZXYaBu7ZSB\nBPcjWQ+nznHsznXTS9v0Kg7USbXR21Mm5PTXzv4C+027KaKG+6Yvka6/1Di1Pb2LPHX6Zj0xp7h2\nlV5GTyJOXww3lYoQMg2QcvSKGJOxhQIOIYSMFINKnepFvGlGuGnKyVG0nO5dGvmn/b3WSgmLOHUC\nvn7cN3VdGfVdN3XaqGkXRze1U8qEnPJ2rhJx6qXM9SfU9Xrc3O816a4CmnVY+cvqr6ZRP26cgvbs\nO5VK718X14gGRJzhi8SEEEJGDQo4hBAyKEam7k23NTSAUSh2W5eqlJu6AX5lcD/wgsYBenZlNCPe\nTGXqTR2HRllbh0W4ckeHYurbudp9U0e86b6PTlW/rCvo9CvkTK2IQwghhAwfCjiEEDIIxla86V24\n6SY4HNRwxVVOjUGIOMXBX1Fw34X7psZ3exVvitqr+7bpVRSoLlYMlIs5vYg4vbitygP8MhGnl9Sp\n3sSbftPi+hHrqo5n7yIrUCbCTb2I06Vgx1QqQgig0qeSUaunxWvTuEIBhxBCmmaqixY3It4MboSi\nplwc3QwlXhQwhgPFHkQcoKZLow8nTo3UqV7Em96Fm6bdG6HldRfchwS7xtq471o4vRyv7sWbUXBW\nhZZX5aLq3i2nyafFhb9DEYcQQsj0gwIOIYRYNFrAuBZ1nC0F29TlUOFNuW6qRJupHvGmqpZKUZCf\nD/ABHRx2Wyul2qFRTi/nXZV4U9d1U9xeU9uO+XXm3TU2dvvUb+PeRZzuXDg1XVbOPlWJN1PtrLK3\nq4c0sQoXVVU6XNH3+hpRzsw8xSJOH+hzhilehBBCAAo4hBBCCCGEEELIYBjFUahGbHNIfSjgEEJI\nk3SVPjVs9019503/rpum3RzV9VOqnDhVqTbNOjS6pObIUxnl7pv6zpvhuKuK65ho6qXb+HVxunfh\n9ENVumH9YcMH767S1G3Pbtq9uK2A+qlw9vf6Gyp+BFw4TKMihBDSEBRwCCEkpe/0qTEXb5pNxxh0\n+k3R8vO1UIDeg/zKAH+QIo6hu9SaKvGmG+FmqtLhqocU97ejuP1CQl19EadapFPL7rONSwQ691j0\nVtNouGlxxW0FlIs53Qs5+XSq8Lx6nd73x0jE4UhZhIwxchSLGJNxhQIOIYRMOYMQbwYv3JQH86Pi\n3Ai7NvygrtqNUyTiBAK2PgveDsqZUS3c9C7aNN2euUC+chQqNyCvcuOUtW942c3eaJeLw/XEmyaF\nufLv9Ee34lvoe70JOT26ccasHg5FHEIImdlQwCGEEEyl+6bLNAvnw2bFm/6Em2YCwzrzlTlgyp0b\neTGnjpBTT8TJlpnbpi6CrG6GlC4Tb8qC+zrCTWHB6h4C/CLXVmjUoaL1OMF8qZhTLuSUu61qOq0C\nAX5zbVwt3lT107r9s8k+CZSMMlU5IlU9kRXoVsgJu3FGSsRpIJWKIg4hhMxsKOAQQmY8UzfyVNPi\nTd2gu3vhplvRpizo6/cpf9X3i4J997P6gX79IN8K2gaSStW9M6O8HavbuLQd+0y/qfp+aChw85lM\nSqeH2rd/ka5/V0WT4k0vjqomhblul1FPhCsWWe15i0asqqpjVTxPgYgDBIWceqlzdOIQQgoYxSLG\nZGyhgEMImdE0It7Uct/0KN705brpvn5GHeGmV7GmXwHApizYB/IBfx0hxw703e8NRsTpN7j3P6vr\nusmdAzWdWLl5GhABQm4L5/NAUG9/r6x9+xfpittWLW+w7aunV7vihivM2TQjwgFVqXFF63LbFKge\nNj5bVzZjP26cGiJOQwWNKeIQQsjMhAIOIWTGMvJpUwN03XT7NL/bJ/n9j1oVJvRE3vm84Cl+/ql+\nuZCTD/SzgDAsGnQn4vR27vUi3tQXbnobxai7+YByx5Q/j79NVe1bJeT05rQqpnb7diHeDEuU60eQ\nq9Mv6wg6VUJraF3djjrmrkevqzsRR623SDyZWidO+bYQQgiZblDAIYTMOKYuZQooTTvqM2Wqlzo3\ng0ix6XWkql6C/rLv2C4aMw158cYN4vKBYsiN049bww/yg+1eGeBX17upI9z04sDqNrAvc9LUWZ4v\nuOlpoWX7bqkyca2bts0od+Gobapo3x7athfhpglBrtu2bqpfmvkKhVZNoD/XKkgOdO3GKUmpAqoc\nMBUiTsPDitONQ8iII2Vfgx0MhAavQWRqoYBDCJlRNCbe9Jk21a/rpkq8KQvmunHb1AkKi7anMljs\nJnWj12bz708KlpPdx4QdG/mUKkC7ceqKOIX0KN6E27Q6uK8qgNtrSpW7jGybpYwH0tZlaW9FIp3d\nXnbb+iJOabsCwXSq8L70Lt7UFVeL2ja/jIb7pPpCKSExTn3gvy0WWvV7RdiZ04uQ05QbhyIOIYSQ\nqYQCDiFkRtCo62YQ4s2UCze9izZNBP12gF8Hke6jlEVDP6NeMFkZ8Ou5rQBSwvlOV8F+j0/cenNn\n5AP/Oo6Oes6Neu1VdW7USk0KxaBVXc7+TmBeW8jR3dcX6Gq3K1CvbWuKN+Vt1J8gV1+A7a4/Zssr\n75dCuKOAFSLtl3XEHHs/8qKrXo7ehux7QLWQU+LGAbqshUQRhxBCSLNQwCGETHumNmUKGIR4kw+M\n66dKdZtaUybY1BVqQgFhPzU2/GWEhACBVj6QtA63E5BXBvz6VRbcF7tx+hBxKgQYe9vVphYH+d0I\nN8UCQPftFnXlrsnmTYqGYc+lt6A7UccT3JyPTPAfbtdyEacLehRv6rSpPX/dedRng+mT9nJ66Zc5\narrmsvVlgktIyFGLDKXX5evj9FrkuLwWTYWIQwiZ/nAUKtIgFHAIIaQbKt03BU+4ByDcVIkpVcJN\ntwGhP5/6vHqI8qoAvyqIDAbQ3neSgqftueBRZOusI+ZoIcc0e2Befx5bJDDbWrkPoWNQFeRn3/Pb\nNDRvWNQpPp/K2q2JwL9lB9j+8RGRI/BUijqhblkq5Ojlesty2tAXcQIuHCDftg2LN2ViXB0hrts+\nWbdtq/plWfv5/dJ26uTauus0SPcyXT3CHNBTWhXQhRunRMShC4cQQkgXUMAhhExrpjZ1qh/xpnfh\nple3TZVoU+bMqAr266ZZ1aHsezrQ0mKACbzS7yS5p/JZ4KiDxqCYExRyqmqolAT8pfteHuQXBfj2\ntCIxoKwt7eNa1X5VbSfQXQqO9IoFhwLnUJsWiQKOIOB3t0AKnN9GxW6cUJsChek1Dn67dS/chEW7\n0DLC14eo8NpQPK0uoe9WtR9QT2ytLehUpMuVpVd1J+TY+1qeSjcKIg4hZMSQoAOHNAYFHELItGUk\nxZuGhJs6o0nVFW1Cy60TEBatI1vW4FI2stFvrGK51hDfeh4niEwFgFDgbweM6cL0TljL0/sAZ77a\nIk6Q7sWbsnYtFnRc8aAosHfPhWp3VYiqId6L5lHCitue9nrt9tTvfVFHb7fdpo44I5NKcS6cUuVT\nr13LxJtuhJuyPjoVbVqXUL0bKTKxrqgNART2zfSNs83dp0Jm/baekAPAup6UplYF3DjDFnHowiGE\nkOkLBRxCCKmiB/GmW9dNL8JNldumjmhTJtiEAsIykaZMYPLXEcIXh4pqpKQrAOAXT207AaR+bQs7\nQibOZ4kTuLcgERcG/XpaLii0xJ7aro10j7PlVIk3VnAfDOajwjb12zMsCuRdOfaysu3srg1tStsT\neVeO9AL9kFinBYFCISAgxIWEHFucy4s4QLgeTqhdexfk/M+r+qjfnvbrOu3Za1tW9Uu/3o3Tjk7/\ndAUSI7YW9E3zvYA4p/fNuKtCQlKBAGtvezav68rxhWGFJ8Z4bpziujgVIo69sYQQQogHBRxCCCmj\nVLzp33VTR7gZtGjTS4BfFthXpuPUTLcJHV0/yIdQP2N2YG0CTBNMti0xJ/2bugJsQccOGH1XTpl7\nw6mj4sRfoeLGeeqIN6Eg37x3XB35Ns23fz64D4kEddLi7OVVYX87144AINrhdgzML71gX7enL+gk\ntjgnY7f9ClxWdnuGRJxs3uJ2tdu0yHVTR7ix27NIUC3rm/r7lalUXaTAVfbLWn0SCPVLINw37eUI\nr02dfuoJryExp1lXTq9unBIRR29YnyIOXTiEjBBJov6NErw8jC0UcAgh05K+06cGkjJVFhAXB9Xu\n9OKn7vZ3wsFhPcGmKCAMBYOh7/nzBEe/KXFqlBF+sp4F5gkSs2SJ2BEFEiQ5UccWABwxJ+DK0dud\nE4PsJ/u5oN8NEp1jUND+oUA/JAL4gX6VaFPVnkWpNiEnRpl7I5gelWu3iewzr8i0DvYjWMJAgbij\nPw8JOkbMCYhztqPKFt7U9qg1CBEF21MRHqEqJMbpYxJyUvnCjd02vsvGb59Qe5a1ZVmf7LU/avIi\nSXmfVPOE+mWxOAfkRZ3EEVPC7hxfzLHbrcyVUzxyFVBLyBkBEYcQQsj0gwIOIYT4NJEyVdt1U+aG\ncEUbe1o/aTT9BPdlwaAdBJrv+TU3SgLFyAoqE3/YYYucGCBcB0DiCyzpZwkSR9SxA0eJCDoFSos5\ndpAoZeIIOXpfJBJIkZjUqqqUqjDlLg1f1KkSbvx2DbVpUXs6aTqB9nQPe7lrw3Y0lGEH6IDffkro\n0YJATtzxBDpb0PHFOd+V4ws5tsOqWJSzA/miNi13UvltnbVvuC1DgmpVWzbRJyNP5Cnrk4DXzhV9\nUr2O3c8sF1VIbDXLTdtJIg4KOiF3TrWYY6VilYw4p7fPF3KCaVWeGyecUuUJPz4ipywSQgiZ4VDA\nIYQQzYBdN2XCTR23TV5kKZqeT7sIBfb+d5x5A4G9ntcRb+AGilGhAGA5OmSBkFEjPklEPtBJTNBu\nOTRkNk0HhontuEHsBI46aFQijSXmIBNzbCHHWZ+XOqWObZKbrrCD4PouDT/Q15/77RsSbfwg3xdr\n/Hb12xTIB/OhoD+qEHSArK1sfIHHbjszj/CC/VTcsYUdUSLO6fPAceV4Qk66YC9Yz4s4arobxCvK\nCxWXtaduyyIBLuSu0W1pt2NRG0a5tnbbKtgnu9AL/H5pt7MRV7x2Dbdpvm8CYbeOL7oCqUMnnWa7\nc7ovau39HATEHPsccF12A3Dj6JV0KeIwjYqQEWEkR6Eate0hdaGAQwiZdvSUPtW466Y/4aaOaOPX\nuihy2YigI6A8sLeDejsY9ANBNU8q9sgIkPkg0Q/2Q26O2gVTZX5aVvTUDRB1UJlYzplExkFRRweN\nITFHz28LOUAm8BgHToEbJz9KVUYv4k2RS8MP9kOBflG7AsVBvm5X+zO37bobQlzjizl+u9nzlIkA\nOkVHQgXqidDvVfvl2jJ1TYSEOact9Tq8tgRgtSdQVLfKd93UEW6K2rFIeNPtaLeh3X5amBGyuE92\n0x9VmwSEBq9f+n3SmVbQL/U8RYJrNq1IqMvEm1BKJFAs5tR25aT7mh5Es0zfkZUTcppw49gbQjcO\nIYTMWCjgEEJIl+JN9QhTIVGmqK5MtdsmJNrYgbz6dl608VMufIdN6Ol9VTDoB4L2d/V2ANkT/aJA\nMepBZEsCT4v8p/dZcJggcQoUx848+r0t6BSKOSIVBtAprJWjvtMJuHGQC/h8isSbSLQLg30zX0XA\nr0WbkBCXC/RLxDc/oA8G/UXOKo+8W8OrbSPzAkAo+NfT/eDftKOMkAjlzMkJOZbzIpJAEnLglLUl\nEGzPopQpX7yJoolC4aYlJgrbUK2j5bShLbQJGTltZ/fLQfRJwO2XQRHH6pMAcv3SvPaEnSJRx0zT\n/dQTdJTY087EOBErQS8kwGoxJ523qPhxqPBxXsjRc4SEnOG7cQghhEwPKOAQQmY2AxJvfOHGnuYH\nec5njkjj18twU2dsAadMtAk9wfcFm8gRclqFwWCRQKOXBthP+/Vf4fzNjmW9gF/jjkYjc69N8C8S\nZ5oODu0A0hZ1tKATy8mgmBNjEjI9nlrIAeC4cmKkdVnSQNDM449SZe1H0XlQJt5EUTvnqPLbuSUm\nSkUb076WWOO2Yz0RTr3P9wcREHKkLdpYcWco+C8M/JF4hYzd9tPfrRLlYtkJuqvitM0qRRzABPu5\nfS9ImVLtlrVly7Rv2rZiAn5fNdPK+mj62u6fbtuqJdTpk70WMg71y1Cf9Ke7gmpYcLXb1nwWaF/1\nWd5FZ7tz9HcKxZx0ncaBk6ZDFo1iFRqtzP7crY9T7sahiEPINEfKEUyhIuMKBRxCyMylX/GmAddN\nXeGmKG3GXmcdF4ZaZv4JfrfBoP/k3og3lpBjpol8sNhLqJg4r7MbISmzoDFR0VQaBMosYJSJEXZs\nUaeDThrsxWhjAolIEGPSCRL1SFS2kKOWmQk+SFQB1SSZBAQQ6VGuTEpVksZbbuCfE+Fst0ZJwA8g\nF/T7wk2dNjbt6rWzbi8/8M/aTwRfF+Ldt4YEOPVap0YlaVqOdIQdN70qMaKOHfDroDuREYQWb0T6\nWkYqqEfmyElSkaaVtlmst7dwOHFXyLHbzxbijAgXcN1ExmXjOm7sNowwYdqvLScc91uoj/r9U/dL\nYbVn031StYP9WqbHxRNy0ve5fmn1SOe9JerUceoUCnae+8oefa6suLXtytFCjl6/xi90rT930yUr\nihz3K+LUgHVwCCFkekEBhxAyM+lHvBF+qFNPvAmlS/mfh4SbyJu/rFBtUepMMJiXxYJNUTCot80W\naYQQ1vvsWEXCF3LgvHeOb0Fz+A+YswDRmiayIFFaIVYCCSlNuJYG+vp9ghixCdptMaeFNmLRMQGi\nkJM5IUftR2REHURQqVVRWkA1nafIweESSLUpEG+UKJAVmM5EnBZaaAfbuiXbwXbO2jLv0siJcJYI\nYG11oB3L+5X0GtR3bKhDlpiA3wnsRTbdTLOD/YCYo8Q4V8iBhEmtMs4pRKbNWmg7Io5JqXGGDFfB\ntXCuBYF29MQb7aDS7dgSbUe4aWHCiDq6n+pp+jrQlu1cu7XRMmKNEW6s/uf3S79PhtqzrCmr+qXd\nJ9WhDPdLPY8t7CSh/3upkSGXTu2USEvYsdOz/JpIxoGjhZz0nAilV4XSqspr4zQk4tCFQwghMw4K\nOIQQkqNG2lRovoB4U8d1k39fLdyU1bTxhRs7GAy5bFSAX/z03g4Iq4JBNZ/Z03QeN7C3j1qljgZP\nrDHTrEBeB42QyqVs/U2QiTq+oBPLOCjmdEQHLTmBGJOIRQdCRIjlJARaiMWkCdLyKT6TafDfQYSJ\nQhHHJxj0+wVuvaAfAEKpNpmDo1i46UWgs9sz2I6FfcTfWbdwa9i9EZn3Zloq6tiCTiQEEkQQMkFk\nCTkiDcyFjBEhQkdMGkcOMAmICQgkiCXQEjBiTSSyNtP9Vos3jiMHfpHaknb0xJtIZAKNEEqc0e2n\nHTctTJi2a6Ht9FHdDuq90K0e7J+6b4b6ZST0NmfCa7Yf9ZoyL+Lo6VqYcYUd57WQjuBaJbZmNZGK\nHXRlYk6MTmVNJCFauWLlWsiBOV75afaxcFx2BbVxehNx7CNMCBk7pASSEevD1H7HFgo4hBDiUJFI\n4LlozGRLvKmqdRNKlyqqcVMk3NgpVL04MEKijQ4JQ4JNS0SFwSCQiTQRXKeNea0DINvB0UXNVDt1\nXEIikdmXs+BQpK9VEJl4Yk4sXUEnlhF0lZtEttBJRyESMkqFnAiRbCFBjEi0EGMSQkamboaumSKs\nGh31RBw/7QbOezuVyWl/3fbIO3Ds4F+LNC1MmPa2hZuWbBWKNiHnht1ukSPEWfVTumhLV5CzhTjV\nNhAC2ruQBfbCvFeHMxN0bHdOjE5OyDGOm1SIEVDOnJaYyIk4Ai2VAicjJALKlRQqcIx8O3Yj3kRi\nwnHdtMSEabsWJnLCjW4zAKafthFBCIE2hCPYtETWT+1+qduprF920yezdtOHRws3wmnnrA/mxR1H\ncPVEndgScbJhxFPxVXSQSBl00IUdWK2gKyfBpCXkuMKMP9y82idvyHnA69eRI+KUp1R1I+IQQggh\nCgo4hBBSQnnqVDq5B/GmzHVTR7jRwTsAE9Rr4cYO4u2n+Co4bBeKNlqksZ/gt7yn+GUBYST099Rn\n6r31usCFo5fjE3Le6OmuoKOCRjuQTKRALCWkFI6gY0QcCXTSQKmDCLFM0EILsYxV4JUKOZGI0EEH\nURpAdywHTtrQpq5Ktq2ZiFMmAGT77p8TrewcsMWAdB7jxCgQb+yUm37SbYpS4Iqm2dNDGLHGcia0\n0jcJJFpCmIC+BSXoROlKtEsjMqlVKsyNUqlGp0lBwHHkdNBBCxOAVLWJIIBYTqIF5bCKEEGF0okS\nbJDVQEHqyoB0a5/Y7ea/LhNvTHsJLdi0EaXijRZaW5hAG21HuNHt1UqFO91PW4E+2hYCtpAa6pt+\nv1Tb3Z0TJ+y+EY5Ao2fRfVP3S1/YiQNiqxJ0olTEcWvrdJCgnYqvWnTVYo5KfVT/xTJtX6tIuV8T\nKUKWBplLrUqFWWeUMsD04zI3TqjAcaWIU0nBvBVpVBSDCBkBpGS6I2kMCjiEEFIHr9YF4Lsn3GG1\ns89DYo3vwikWb0Kj09huG72+MveF7bbRqRc67SITblSA1xaRCfxawhVszJN94T6x1wFhWNyxHDnG\nmeMd2oJAsShFww4C9XTXeSMcUScTciRiqYLMjpRoyRZiKdPKNgIdSERSOEKO/q8jCkYoAhALoOUF\ncQkmVZ2ZaMIUNtZP8e16KjkHjhZn9Llh0vFa1nlhOa/QytxWUrdoXrzxXTe2g8N32tipN2o9eceV\nxnZsVNW/aVkBfroyI7rZh7SVhtlR+hcARCrmJEI7hpSYYws5nXQBkRDoQAXebdHOiTgq4FfHT4oW\nIglILdikxxSpCyeG106e6yLUdrbgqmvemHMpIN605YRx3bRl24isLdmGTqTSoo0+jrqfavGmFYX7\naDvK901h9cOyvlnlqgoJrLb7JrHmM31UasE17ceWqKP6p+uei63PACBGghZS51wqukqZQMs2kRFi\nlINO10WKMYlItAqEnNRdF0qtQlbsWDV/5sjJuXG080boYteZ68sVcQqgC4cQQkgNKOAQQoihTu2b\nYvEmX/OmXLzpxnXTwgTs+jbadaG2Mx2lpkC40cG7n3oReopvizYt6wm+nm6LNYAVMAImcNRHyX5v\nf6duGpWfNmVPk9Y8OkBUrwV8QSdOhRztyokl0Epf67/KnaLrqighJ4JAR0aIhDBuHIEoGyZbwBFx\ntPND6iMrklQcaJnip3Ywp7HPC/vcst1cWf0T6xxLhQHttLLbv0i8sYW7qpop0G1oiXVmmwOODT1/\nGdJq+wQqfQlIXQ5pEKwcOMJoZVJPl0BkKSiJUN9Ty4rQBtBJz4O2gBFxIqFcNkrkUs6OyKS5uK6d\n2LgjYtMG+nUZTt+2HVRp7SI7bapKvNGuG+2da4nIiDb6GLeEMG6bltU/Tf8FjKjj90/7dc6JU7Nv\nAtX907w2/VO4Yk76N5auoBMnInXhCMedA8AIOh2ZoC2U6CpNkeqkIBWyA4HIEXL84tZInXR2cevs\nBIQj2DmOHF/QDYg4+vzIXFz9uHAIIYTMdCjgEEKmHRKyQHxpGncYb/e1+75b8cYeWtiudeIXJgZQ\nWPC0SLjRNTOqnuJnQaH7BL8l3Cf3fkBop2v4AWIWKGbRXyhQdINDASBLkbLTM7L30kyPE1fQidNg\nMU4k2hDoJJ54IwEhoUQaqZ7sIxVb1Aa0g4GcGn4Ypa6MBJNp8JiNRGOn5Aj4EoiLK/Rk7htNJFrQ\nBar1+aBFnsh5JZx/dQre2sJNVYpNWeqUu0P6uKg0qWzUIiVEyFRMS6SqiRJJdRKJdB2+I6dTIuJE\nQqbpUWlBYrTS9y3ESMyRsV02InV0mGOvi9t6zglT3wSZ2Gb3c6df231dy2gl4s0SWr4RkfLZiQit\nVGTVx7oVZcKN30+z/pvvny3T/wR8MbZu3wTc/qmOrTDTfRFH9009ze+fmZCTunEioJO4Yk6cOnva\nQfeccuXomjnq/JEQiBCLGEJGJrVKIDKpVW5xa5i0Kl0XSbtxEkzm+ng3Io5f2Lg0lYouHEKmJ7aq\nPTKM2vaQulDAIYSQKkwQHXLfuE4JX8jpVrzxU6ayUYXytU508Gi7Luz0C+24CAk3Osgre4rfcpw4\nSOfPO2vsp/6ZS0fdGOSCRHNs6h16FeBbQxAHxRth1dkAYuGKOS39t6XEHJE6bBIj3ABCCkSJSpqw\n3TghEUePPqXScpAFbGkKh9TtqUUCGRkXjnHfFNw32YWs7Wn2+yy9ynXx6M/0EOFqP9y0qW7EG7s+\nSqjdbNGmbnua76YBuR5u2ogwRqSQgBRIhKqHEkFkgo7aYeOcsp04sdku7XiILGdFBCBOCxRH6dyZ\nwym2ilGrIeOtIsXICtICVkAOv/+7taoy+aylHDh2zZsuxZt2emz0+1akX2fCjRZXdT814is8Mbah\n/qmOBVDUR7P+aaVPiUzUiS0HnRJr0tpIIq1jJTLnHIBC95wSbtRyIinQQQLtoNOpVbrAtdlaWVzc\nWsoIsZhU55WYgK6Ho11iQD0RRx9VYb2vTKUqJeDWYV0NQgiZUZQ/+iOEEEIIIYQQQgghQ4cOHEII\nCVCdguWmsripML7jpj/3jR5VSD+5t4caVmuLCketsUessVOmipw3RWkY9l97pCn7ib7jwkHeqdNN\nEeNwgdS8C1kXODVP8yHQMsWLgVZL1bwxT+cTIIqEKoAr1dP6SKrp7sPtNJUhdc6olbWRCIm2bJud\nShArN4WYgJQxpGgFa+HYaVS5dBxR71lKFHjmEnLh2PNGzjRhva5OnVLbVu6+cabVcG2YosUCxlkD\nwHLaZE0QCTgunPy+K18MoMrPZscgX7NGF7fV6VPZMlrwHQ12vRI/xarIORGqX2SnT7VMCmSaImnX\nKPLq3tjumwntwElTpoDMgdOOYKVRZc6bVuQ64+r0Ud103RQzLuuj5rXVP7OUqswxF1spVnF6TnSM\ny0a751TqI4Bg+qPtxOnIJK1VJRBLdYbEiLPi1jKGXZRc6ELEIhudTCI2hckTkQBy0jhtInTnwlHH\nyU7Js71KfhqVPuBZGlW/MAWLkBHBzi8dFUZsc0h9KOAQQkaKKuFk2DekoaGD3fdRZUBeJd7YBYt9\n8caud6OFBFXfplWYNmWnYfj1M0LCTd1gEAjX2fADRLXP0nptHYuC5jb1btL3ppAtskKoej4dGLZl\nNpKNFmcSqc4oEakzJ0KWMhUbNUiYSCzyRBwpY7TSwCuBqr2hT9EEiQr4pBqZJsKESdeQXpqUHvHI\nTqPqPY3CRadM6fWEqKq1k1tmQbvUrnVTslxfxNHY74XwRqyqQFhf1ik1agj3ON333o51UvE9P9VN\nT/PTp3Ttm0i00JYTqWzTNn1Wizfqtdtn7f4KICjetMz7fF9tCVWhxk5/zIk4WgDroY+q46TIhgjP\n+qkj3niCTpz2UZUapa7vLRlOfQTUdUfVscrSH6WEU8cqllLVSBICsUyMbNZJa1YliIzAItLXEdL6\nNLoGDpSgpFOoICfVfolyEcfu07rmTXZcrM+C/Z/FjAkhhFRDAYcQMlS6LTZsz9+XmKOrS1au0K1/\noyhz36TTStw32edZ0WKnbkaJeOPXu1Fb5g45HOkAEPl6N379jEi4gWBIuLEDQRMYmv0MiDipWBPB\nd+BI89rGDhBNUKgDHzNdDw0u0yAs/VymQaDIAsUoSQOtdASqKBVzYt/ioVduiThJokbvQaIL7aqn\n4TIVxhLlF1BftUamitCCFIlV72YybUftvqkK3qpRglErP10kaOlCrKmA5KO2Ofuu+y6wLhkO3HUR\n4ZCQU/Qd+3Nnm0ywL5336nV3fdue3yzPrndiPnPdOTLg1pFdBtH26HNFxYvzZaSjtPB0ZIk4asQp\ngayfuv1THdx2BLSNqJP1Vz2fSOfxhZuqfpq5cPL91G9XW8BQx0xPF+l7PXqUFm3ygk6c6Fo3mXuu\nk6jt1865llCfRWmTRJFIRxSTxj0XJ2p/7DpWMSSQunE6yGxBkZxAJx11yq5nFWMSbTmBjlA1cHwR\nR6bXbS3WiLSGTua4sYqSB8Qc+1wJuXCKGHQh47Lf32E/LCGEEBKGAg4hZCg0MUrU1Iw0VQ/bfVMn\ndUp/x/6sLG0qJN7oINoWb3T6hV2s2H+K7wSGXiCoAz1fuPFTqfSRN0/1A8FglAaQOmhU+5wFBUFP\niHG3KKRV7DaRgBQqSNTfTdJlSqkK4MZSaW46bUqYEF3ARG0FIk4idZqKhBRQQ1mnwacQwgwtrket\nyYJzNUpRLICseHELRWlU9jnjB3l2mlVWMDdWyxF5ycUWZnTRXnVcVLqQ/qumSUd4MaMDidStlBYJ\nTkQ2n5QSSZpGZWueRsiR2fKEyIs0IdzUG1e80UO/AzDDR2vXRn7f1R7bnxWJL7aTRgft9nd8p40v\n7PjLDbnsgtOskcPMiGHpyHICmawjUsdcBKCdpj1qwTVCljIFZAJqSLxpeUKr02+RijoN9lPA66vp\nyF/6vFKiq3AEHT0UeKsFyy2nxFkRwYwUJwBIodKkzHZpx02aBhmlDjvl0FEKou/GgTWqnBlhS4sv\nsoO2ULfCZSJOK/2aLmwstVBj+k9UI5XKPlpu/2/SkWcTEoDq/m6G5qOoQ0iPSAkkdNiRZqCAQwiZ\nckZJeOmG3AhT3aalOKJOy4g3ZpQaE9Slf9OAT6dNhUaaApATb0zdmwLxpij9wnfjVAWC6jhkwWDL\nCwR1EOg6cdJpFU4NLVVIkb1PhAoStZiTfS4Qm2VnrSIFrHhJR1J5EUemwlA7LT0hUyEnSR0ACZR4\nIzPvhGlPKS2RDq4TI3SrFhqSugxbyFHv43QEpdQFgFZahydKXydIRKICYkSIRDZMsqoCI6yUj7Ta\nS4GIg1SciVI5Q1ijchkBzQ70ZXW/dsQWR8jR07K29cUb+3WiRR5I9R3I7DMjyUhzPABAz+W/to+1\nLbDpdtLT7Hbz20Xjp08BgE6fUscoOz8iRM4oYVEqvIpUFBW6DlXkiqa2uOoLrr7Y6gqzsrSvGq+h\nsIQOlPdV1RbpMRHWe6HFOBEQX2Xal9N0t1QgiT0hx0+BBJQwo1If1ZEVwnXjREm4AlIm4ljeswoR\nx4wyhsQcfJGmYQm0zPe16Kr7lX0Ohci7cLxthTuceL80+XvLoc0JIWT4UMAhhEwp4yrelKHdN6Hp\nfuoUoJ/KuykXkS/mWMOF2zVv9FN77boB0Ih4Y0/z0y90OpUfCAJa2MmCQTtIVPsqzdDi+r0mmKKT\niiaASqmAfnKvg710qil+a5apwy0dXghVDNVx22QiTiIzJ4IWaYSUaQAt9cP81MmTVlERalhuvcAI\nIh22OgomQZQNF26TF2lUAKema/dMYtaW7U2MRKq0m0QkEDJOw78EumivPmowwah2zpSLODrrRLtq\nIhWpmjYLCTpxF4GdHZrajhv1WVa02BZxEilN6ybIizcSCTpauhGOhJP+lw4FjRiJ1K+T1OHkCjeZ\neFMviA65owAYEQfIzlCdPmV/rs9nXVRan3Na1IlEmtoHGIFHn7sivarqflYm3uj+qoVYYfVX3Vdh\nvTf7UXDZdvtrNk2LrlqAtcVXJdIIKMOOat843UedEqVeqxRIJOq4AEhdN+m2azHHS4PMrDBuS9gi\njoSqO2SLOJGIAEwgxiR0SqQ69zMxVr+OkKT7pNx2ENm5IoS1XH1g9DHyXDiK8jSqUUP/hlPIIaQL\npKxnUSWkBhRwCCFTxviKN8X1b2z89Cl3CZn7BoAj7Nh1b7KCpyrIyzwf6q9drFhYwZ8J9GqIN7p+\nhp1+oepuZOKN77pRAZ/9dF/LJDpIzAeCdhBYNyDUzhcgCwhVcJqKLsiEHP2ZdtXEUqAtgI7eLqgR\nbXSwK6FTOtT6JZAGj+nnIpsu1CKzv9q5gyzYjmH7fQA1wtGkE/CpYK5jzoE4F7xlSOvpvqp3o6t5\nqPNCFUtOUkFGi1dapMiCSwE1yk5btrVRId10LbMIJfGkrqIsRUoqh076L7bEsjhNkbPvPyPrdQ3z\njYNbADdz2Oj39mtfuMnmycSbGLE5ElIk6CBW7ywhR7+3v2WnTyXWdP0+2EY9YIs3RZ9pwQawBE8j\nfGaYfmYJNrp/CevzzKETFm+0w67f/gro9pSQyNxrEvk+a14LVeNGpLKkEGm9KsCkQKr9lul7vQHp\nyVyQBllfxAGQOtdkKnm2ZRsd0YFM+xrEhBFmMldfC0gFVzuVqlsXjmZQqVNTAd04hBAyHCjgEEKm\nhPEVb/LUHfZZzVvuvvH/2qlTujhuhKzgqU650CNNAYBfsLjKeWMHgMqPEhZv/Cf47XR+HfipbS4O\nBHNP9Z3jEr7xl1I9iTeJLjITb/RTePu1dopA6JouqRgBaZ7q20JN1g7CBKhapMm3nXDzfJC5brqh\nyIlTlJJjUnacdJ84LZ4aQ+pRp4Ry4ahirxMmdSrGJICJnIgjodKp2ml9Hh2Wqu9IR8iJ02OkxRvl\nwMkEBXiHLPY+K8KvTRwSb4AsRcqvc2PcOpbrxpJnEIs4c96IBB10IJEgxiQSkf5NHTe2+0anT/nO\nG/V54rhyQm0Wono0uvIDZkaECvQfe7p+bYs2RshBJqzmnDcN91kgayfdpdT1Qr3uJK6QoyUA5XRT\n37Bl2UgoN066Fr0V2dIrRJwkSc9haYm30NeHVMSEVH0iFX6VCGo8d0bOzCppRUYoVaPJtUpdOGUF\nse3h6tV3xk/MoYhDCCFTDwUcQsjAmU7ijaaq/k2oRo7vvlGvXfeN/lynTjk1cZx3qrAuoJ+4Z7Uz\ndF2LKBUwukmbqiveaAeOLeCUBYF2PZwydE2VFpAWRc0EG1/EQbrfCdK6LekytAAkAEdlUKGfndvQ\nPX4x3TojFtUNysx8IuzCQfrEPxZqSOOWRDp8OVSdG6Het+WEI+LoWj2qJo4SPYR0x0YSliNHp0dF\nAGIpU99O2o91ypQQTspUZH1WhX8MbbFGfe7O59e4UfO6wo1KmdIijk6kSoLiTYJJ9amcTEUc26UT\nZ+/7DKa1o6rsOJSNBCZLTlVHWKmxLVr2ADK3XJl4E1nz+uvLLzxrN91vVR/USZCq77Yj15GDVBjs\nSH090X1YvdbuOfdGVR8UV8SRWqQR2mWXFSS3FGEAUVpHyq5rFaVCsYRMR5bLXDiAFNm5oJx6mQsH\nMnGEGD3NHBot4nlpVELUvy6MOhRxCKmBtv+OEiO2OaQ+FHAIIQNlOoo3muwJe370KRt/5Kn89y0X\njuW+0dN99409eg2QOSVsYUcXP9XDCgtb4EG5eOOnX4TEm6wGTnkQ6AeAUcFTfIMedSr9blQg4vR6\nHySt87FoESaFS9qCQfY6NCKSmp5PvbFTKYIpOfYTeCtMDrlwINL6NtqtIhJATqpUD0xCygQtoQqw\nRtAOgFYq3ERBIScxQo5MU8nS1DxppfPo88yy2PgFi+t70vIVQHx3jZ5mpqfyij2vL9rY6VKWlAOJ\nBB0xme5rXryx/2qXTfbPdd/kRqLy2qvMceO0Y/CzyOxfy7tmZsW0FS1kYon6fv8UiTe1+y1SLcUa\niUr3Xd3rbHdNIiXaQqADqUad8kSclqV42JWf7DRI7aLT1zqkVrMkrdWknHdKXJCWqNtChCStg2Nc\nONDuIO2wybtw1PrjdF8jxGkKVgw9clz2WTdpVN0xmqIPRRxCCJk6KOAQQgbG+Ik3WSA1aPz0KQBO\noKDfl7lvsuAq7L7RxU+zaUiLoZbXzrBr3qgn9SqACxUprhJvQgFg6KyQ1nxJRUGVKvEmkekTeZkV\nVE2sdaggMHMNyPRzPS+QpfS4oyBJJwB3xIRAgB56wl4W1EkkbqaIdthIIMEkIkwggRZsAMhJSD2i\njWipUqgyTc0QCRIRoy0nUoeAK+TEgKqxZIZCT0UamY2elBNwZL5vhNKAQtOKRS/XVWNPs48vACPY\nONNKhBs1PUYsJ427JkZHOTAcB06aQmW5b/Syi8Qbs80VaVSq+LR7buhta0m9H5E5g1rQdX8ETAaf\nZ24y88ksRcl+XUQ34bUzjLgn3hStQiLrvxFgRjTTX0qkTLcvE3F0PZwIwuyDXcfK1K4yKXb6GiOM\nmKM/T7TQHAnIRB9Dmfp1slSq1M+Wc+H49akiU3cq67OqRpk6VwRa8NOo6jjypisUcQghZGqggEMI\naZyBCTdVRTb8Ahv9LKsh/Po3alrLfe+JRjp9qht8941d/NR336jp+ZFr7NoZajuz2hn2dL/AaZnz\nRs1fLt4UIT0hRxdGBbK/SqwRRqBRdS785VhCTugftDijhB1H0IEqomvXYbGL3uqiuGqbrAC9IpCz\nRYGsbkaUE3GSZBKIJvIiDlQCSgsTiMUkRCpARGIiddokRsgxtZRkZF4LqJQrLd/oUZHy9ZnC4k2E\nemJOiFwKlS16iXKBTA8J7hce9kUb7bgx9YPS+aSMEaduJcd5gxhJ0oFJqbIdOV472W0l9LFO65dI\nJJBCSQRZlSHt3JhwhJsEiVWcW5pzzYgaqSihU4KkSTUT6ehIMKM8qb6cuk/0dGQuFb0dZkQxIR1f\njF1rCkK5Z3QfTqSo5cDRS/NFHL8fawEGeu2psKKEqqyYsSpdrfq2qQeEYheOqt+k0/2Qc+FoGUY5\nbcK1cOw0KlvQidJrduzUuMn3cbuOjRZ2Bk6gVtew4AhVhBRgPyEaGUZte0hdKOAQMs3pR0ypcxM2\nZS6bOoLLFIkyg0AEBJuq9Cl97P3AWde+cYqcwhVpqoisoA+wHDf++wYOuT7LEit9SqOFFFuwse+D\nEmueRArjvomlSsuILfeNhEAsdWCoPpN6HqmKrCZS1X2RUqZ/1fw6paeDxIgM2RDVsRIOrOGoHdHA\nFMnNCwGhQsZVIo5JrxMTiOUkRFqUWAqVGtISE1lYqoNJqOLYtphjpqcFWO20PedvWl9Hzx8iJOiU\n4QtcjrPJE2n0a9f9FDuijvO+QLjJuW48sUaLN8aRUyDe6PfO0O9Ign1YpkWnExEhSdOsElVeG3r0\noySVe6SMEAuJCDITJaUq5OuMzCTS4e2VDqMcJWlaoRYphBZ1YIuaAq00vSnNbDLXAi3e2A4eM+w3\nXBHHNom5+9o9uiaVEBI6fdJerj2CHJC55XwXTmytXAtYuelWGlXdjdX9o2j0uFAdnF5xzjF9rai9\noSUiTi/VxfuEQg4hhAwOCjiETCOaFlNGIgVqJESZqUmt0k95e/9+fitD0+zP/PQpn6KjrwWUIgFH\nek/w1bzh23k7ZSpB5qjR61HCizDCTWx9rqfHUokzSrDJHDl6WiyFJdCooFi/VmKNfvqvwrBOWji3\nI5WMEEvt9FBDVAOAPUS1cX2k4oA6BpkQYKfl6L8hQcc58J6II1MBppX+dCsxR6d0RJmQk6Z3qNpL\nVj0lmQ1Tr9rDrrXUMvOoVVr1mazzsgkBp6oWkJrHrQGUiTpx7ju2YKOXb4s2bmFiq64N3PZJksns\nM+2mKWgj47RI20nXQElElLqh0uUjMkO/S+9fR3QgZIRYdBDJCXSQQEAglknqpstG94plVncoVnYZ\nROllSY3ipIQQJWpIR7iwTyZhXqfqj8w+i4QWOJX7KUqdOLqwuD1WfFFfVu2RF2Lr4os3deP/SGTu\nG3d5Whzy51eOpkSIwnWkZbzz6wqkW40E/fxWDsjFM6x7CApHhJDpDAUcQsaYkRBYph0qKlLm/eLj\na7sk9L1vN8OLN0239+51nTP+bbAvZfnDfJsUDGRP8AGrwGkAHQpJK/DTwo3914g40MMOIyfeaHFH\nizS2eBOn7po4gXHnxKl4o6er78l0ugrBY5mk1VPUMNVZrRZrhCM5mQbslpPDEhXU/mlhp7hOjvPe\nE3H06xgddUxlBCF0kVVXyAE6llcrFWdgj35mpU0FUvkiUZDeVyO1LwrUyklEecCbeIGy47aRcZpm\nYx03r2C0Fmz0NC3OmPclwk1RweK8eJOd/TkHTkkalR76XYoYiYzQEZMQaTqbEm8idBAjSoXKSLTQ\nkYlJWxOpyBKZzqjypqLUUhJBb5ZUOVdRSPnIpklLxDHOFsAZKcruy7DSobI2KR6Hr6g/5+aznHV6\nXnu2XvSEbkQfTQSRk2mitO2mnrJ1Dnh7RigVq1/8324KOmTYSCkhRy6FiowrFHAIGTNmlGgzCu4b\nmeYvGOJCsUY/kXdHp/G/nwbyge8nMkarRxGobMjhEHbdDF2aV0i3CKot1iTp8nXx1Mi0jXSW6QR+\nsFwD6TzalSM9141ZB/LCjX7dkep7HeuBeubAcdOmfOdNLJWrxhZvOokSbyYTLd5IV7yRCWKZoIMk\nFW9UjZSO6KT71IEeptp23yRyUgk6lgAQEgVcYcDFFFFGKtBIPcpZFthrR44WcrQTRMhWmqqD9HuW\ngANXtNHOGeG7bLTDqiBMD6ULlVJy3yoDLgenLo79OjCql0lb8wQb/V0t2uh5yoQb5zvB9rG3JX2R\n9nmdRpUgCbpwjPCGFmLRAaR2c3QAAXSkdkoJQESITOXeBIgiy/aWrjR14phNskScRAhYik+65e4I\nT2p0q/R1Kv0hyVKTbJlHXQssBw7yfVodk/r9Wn+Wny+jWz2hF/0hVGDbT9nzP8vW5znrZPhcdefP\nXw/cmbpMn2qSaSTi2Nj3TRRzCCHjDgUcQsaAGSXaaPoSb0JBZ/dPL10XTlLbZeM/nU+QoIUoTW2x\n62ZkA+T6n/WCHm7YnyYEaofbKn1CnXMtSFMoNLKEl8RJScie2EcC5rUaDSkLgYzjxw7wrMBOv/dr\n3djCjXbWJKnjBsjcOEawcdw1Ao7LJgEmE9d5o8WbSUu8mUyFm8lUvIkRIxYddNK/OhCPMYmOmESS\nFsZN5KT6iyx4zwrjWgKCJwiE0nP0+ZZNTM8raQ1Jn4o5CZQAI4R21XTMsPYAIKRq/SQdsUp4ok1k\nCTb++V0m1HRb9yZEkcvBF3X8Y2TEG+mmVGUBtSvY6O9kAlp94SYUZOvjZDtvnPUWuHASESGWk6lL\nLRNvoEVR2QbQSf8C5lqmRRwApoKxJ+IkUAacROhpqq8mQnW7VqSPpYAUqt6NKp8sIaRAO9WCIqnT\nK3UR8/z4QrboERx1rGbfzqdMWq4db349XcIVd+1i5D66KHkIte7yYF6nR+amVwwRnnPWFYk1AGC5\nxYq3dAqZpiKOhmIOGRqj1q9GbHNIfSjgEDKCzEjBxqaWeNNt8OjPX3XDbM0fcNFUkblxWua9DvSU\nO0KJOoB+emsJPiKBkErQUa/1aDWRCQcFJFqhwAlpXRspcm4aIe0Cn9IEQQJZwVMTEyIVc4Sd/qRm\ndutiWK4bAFlZ0swSFAm3mCjgplT4T+RNcIawcGOnUEmJUtdNliKVCjhSp0ipzyb160QLNzIn3kyK\nSSPeKBlHjQLVEcppkzgOHLcIrpNOZf+1nsRnxyExx1S3mjpnLFFQZMFhmZij3TiA7bJx/6rmbFlO\nisi5oasjKIo+6zZVDqvuzOsHxXHuM1uscae7jhz9me2cKBJu7O3Qx0S1BwC4tXBk6oTStXD0iGHp\nl2G6hfSOt/OZK+IkUqQOnHR70uujEmvUF5NIIElgxBpA1XdJhICMVH/Xnyu9J3PjJOm1whVylCNH\nwhVlAS3GCpOAFYoB/P6tpxX1b50KKdPXMv1nBBuZX24Renmhec1yuwykkpCbxoiEsfPed+jUH4nK\nvhb0ElnV+Y2quS3TXMTRUMwhhIwjFHAI6ZMZL7Y0TaV401SdGZMc1NW3dODmpCxJ937XrY0Re0/r\nWybVQq09QUuLPMa2Xy8o1jecSRoiCaRZEyILmFRxT5k+aVcBnB6hxnzHSqNCop7UJwAglQunA6ig\nLhVx7HQKCTfYU+tVB0e7bnzxBmY+vR9WgAc3qFMBnSvcaNFGL9sVcfKuGz9lqqPTpaREJ5EqtUpK\nTCaJqXnTQYJJdBznzSQWG9eNWrcSb2J01Os0dSqRHdh1VmxBR58HbrCWf1pvvUEm5KiRijQqpUq7\nbCxxRnaMOCAQmaU5aVLWOeo7aeq4zGwRqAnKgtzQZ6E0FvU6X+TYF3fC04tFG2db0unZ8OFWnKvF\ntfRvjA5aaBs3lkSEWEw6Io75i+y1crhNAOggkS3lnEoAqa8jab+SAma0pQnzXpghxFuWy6YDgXaU\nTUvSf7FQ4k0sJVqpi04LOVGahaWzsez+rAXakDibayurn9tOGV+c1eKNXYjcd9dIa5py4kgj8Pgu\nnOy70izL2a60ZWTqmZNpUXJdnFyPLue2f+ycG3mhsLhfm7U66VOeMJQ718t+n3r5LXQqmJXPOkNE\nHE3dezkKPYSQYUMBhxBQhBkZGhZv6hUyLBJylEzhp1HV2QZd4NgWbhIBJ41KpXCo+iR69JoWWmao\n4Qh6mOEkdd2o+ifafRPpEVQACJnWr9CBnQ5uhHq6LgAzfHiZCyc9aDAlLQQcEUe5ctKhiPUTcSB7\nUp8eXy3u6KGOfexASgs2+rUt2vgBnR7uW4s2QFi40fNk6VKu68ZPmYqlGm1qEolTsHhSKHGmk6ZN\nafEmlpPp9haLN0nSQSw7qm1lJ1jzomyYaoPI5k1LyTrnlS/o2M4O20GjhR3nfUqMsNumX3dNvwRr\niBQJK95x9ecPf14s2lS6JkRexClKpbJdOC1M5EQcIxzI2BF2EpnKP7KVikJasI2QJAITIkKSGnNU\n+qTARJR340ikQk5aGycRErFQ6ZYtgfS16j8tIdER6mxoCTXalBZz9OUzQnap1mV2ioqi29cJdVz9\nEeayvt4xrpt8X7cdevaIdLbAo901SrDO0NPsMcC6CcIzYT0TbJx0vICIE0rtKzqn8oJu1bZN4UOM\nGSbi1IEja5GeKLIFEtIDFHDItIfizJjQp3hTp53LBR0VHBeSS6OKnSfvtgvHDrCr0qhEWgdHP6XX\ngXTdNCq95Wr5aaqUyNKolMOm2oWjdyJ3FFMRR6THKzET7V2XxrETCViVfcJP5+0ADsiCuOx1Jtro\nfbIDOv1XLd8O9tx0KduJ00m0A0cLNtlrXfNGp0wpx416tVgo142qfaNEGp1CJZEUijf5kY/yqVN5\ncaGo1kbm0LJFAnX8M+dNFkB6wo0+sIH39jJsfMFnWJQ6c3znkp9i5byvL/AoilK7sr6cF3GyVKoE\nHVPot4W2I+IItPIOHJG9TkSCNhIkqXsnkTI9X/Tw8anoIYCWFKlwk7lxWjIVZyKhxBmpHHStSKai\njbCEGzUthnLeddIUKpG6ckQq5uiaOEAm6gCZcBMF+nn+yGeiDfQ+wBVg9ChytnjTsfp7NiKd2j7f\nfWO7dnT9GyMMGzFIpuuzRZ3EcuPYU+Nc+pTq172lT3XnvvEpKihe/ttXTxCqEHEACjlDps49DkUe\nMko89thj+NGPfoTLL78c9957LxYsWIBll10WG2+8MfbYYw8cccQRWH311Ye9mWMJBRwytlCYmUb0\nKN70ew7o72c3PeEnkt0WM7YDORVYpzfqIquXoYd7Vu4clUaVpIkDdhpVlQtHLVd9y06j0mJNlQsn\ndnLB7HyO9H49ynxH+ihIKbMn8MhkHwHtugmNK5RhizXqfRbA2aKNH8RJuKNOAZlAY4K6gHCTjSqV\nr3XTgT9MeCdX78YXb5LUgaOmZS6bJB15Sk+TSJAknRriTXHBXnWe+UORZ84YO6XHfMcZBc1P6dOt\n5pI7nyvO8akgJN4UCzrl81aJPWHxLD22nnCraDkijrPMChHHeFAsB46UsRILxIQ5PxKRQMq2KkQs\nW8bh1pIttFN3oLoyCCSJQFuIVNBRYkwdIUenVglI83kstGCTiTmR3ect8Ua79SJrJKoQRX1eHbes\n3+t+7ou1+hrTUeZG46GxUyRt901iviuD7pu66VOmnzqOKsuFY/Vtv0C2nt/u++FzrMx90/9vX30n\nKlOqxp1e7oko+pBBcP755+PQQw/F888/70x/9tln8cgjj+CPf/wjvvrVr+Lss8/GfvvtN6StHF8o\n4JAph8ILcehBvCk9h7oJOnWAVijkBOYPBHNGAylx4agn61FaUyKtZ4JYuWHSEWqUsBMjSYvTqtok\nLRNYhFw4ANCBNGlUEtUuHBOqJirQk5CmKHDmqUlv55N0n5AXcvQxiyUcQSdbVh47aFPvXcFGB195\n542wgjmZCThJlnpRJdzY6VK61s0kOqXCTYI4WOtGbXtiRBtfvPHTpnzxJuS6qS9Y5IUF36ljf26E\nCE+gdL+vWze/7qkWcsr2uc683Yo1VelSeUFNL6Pl9G/jwkHbEXG0YJMN4a7bJYYUCSJMqJQpfX5Y\nKVW+GwdQDhKJCIlsoQWJthRoiSitZ9OdkKNEV/W9WACxkMZt44s5kdXHtaiD9DVkdcnrXvu+hCpK\nDmgRNxNt7dSpUN9vwn1jizbafWOnSdnuGzeNynWA9ee+UQR/+4r6Z8Ey8793mpoiDkAhZxoxFffk\nPFuQWQVnALfddhsOPvhgTE5OYrnllsPxxx+Pt7zlLVhjjTXw6KOP4sILL8RXv/pVPPfcc/i3f/s3\n/O1vf8PLXvayYW/2WEEBhzSIoDhD6tPjSFOF51hpkFlQuNH+jkxKbmx9unPhAJloo9KXMhcOpPqb\niARRKvJoF45Oo1K31WEXDqACqVjI9IY9ynbTLlyhh5OCGr1KAmow7PQr9thR/rsIWpTKhBy92ChN\nscj2s/ioZYFb+le6T+SLAjcdtPmOHMCtcSNRX7gJpUuFat1IJM4Q4UqkSQWcXMpUJuR0I97kBYR6\nqRT+99xj38oJD/5oSnmBRn+eF3KmSsSpK970467pxsWj8IUu1xllC7iKDqQRYXXa06QqNB1BDfUe\nZamVSjSI0cJE0I0TYxItMYE4XVYLMWK00JJttGWkXvcg5ESpgNtKRRvtytGCry3mRCI7CsIXdaT7\nWRn2NcBNocz6v74u2LVushSqsOMulDpVVPumF/dNsAaO577Rok7YfRM6FmFXjk/uN69uX8y56rzr\nBfzB4YFaIg5AIYcQUsh3vvMdTE6q+6Sf/exnjsNmlVVWwSte8QpsscUWOOigg7B48WKceeaZOOOM\nM4a1uWMJBRxCyNRRS7TR1BBvgjeyVTe3oc8tZ40l5AAqGKgWJuOgCyfdaBUsI0k/swudurVwEiAV\nbzIXjllmQS0ctfVpShWAOqlUSOWZFjIRpxVlNSUAkY5gpb7b0iGJzAI53ZR2oWKhFx3AnqyDtXTV\n7tN3S7QxKRBQgVoCN2AD8sWJE/Qu3CSpA8dOl7Lr3NiOG7Uf9VOmdHuXizf1nsK787nigu8QCVHu\nlQjUz7G/OyAhJ+T2yY5NeVBp+leQKvGmzjHPH29fyHEyEa1rgHLgRNmQ7wkgRQtJkqAl2pCIEWHC\nuHHUvkwgEokj3thpd35qVYSkayHHCDbpdCFcV07kiTla5AHSFEzPjQNkenHZ1dIWbNVxzAu6RdcB\n/X37WqAlkNB1oEn3je22MUJN6qKU0nLoeKJNWLyN3fMwIPDUc9rU6YvFDyzs9XRVD87ZJm87KegQ\nMuO5/fbbAQDLL7883vrWtwbnOeCAA7DMMsvghRdeMPOT+lDAIYQMjq4EG5sK8aamcFMVbLoBIuAL\nObn1FnzfCTqNUJMt166NoV04ekQq24WjPo9cFw5QOiKVWmw2KlVRKpVy4HhRpifiaIcNUtFKB09J\nOrywfl4bw659kT0dLzrajkThu24grCfnrmiTq4OhAzSZBYA6YLOLE+v56gg3SeqwsYUbqefUr636\nNtpxo/YrQZJMuk/iB+a6qcY938NDhudGpgJQJNr4/ac6SaabPpf/XrEIk48L7UuLlInZtnyh5xaK\nC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FTLCErcSWRiUqmkfi1ic463RDuVLNpGAGpDCTrqWuEKOUBaYUsqIacthAnqbRFY18zR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\nekqz+STtQ2P3S9PUTr83HqdM3QZxgGspVfU7HPvj+G+Bl4Ac4LUwJy7/v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M/9Z5zxLcYJ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\ngzfZ5tPaZKhag14h1humChYRLKXUKmm6X9ULSNMDGSu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LO75P64TnzPicE55NTdXS4dzX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U6yK/kQ7FqHqHBy5MobRiJ2mMP5ziEbx6CnwjFM8XqbW6iSlerwIGNFX30zDDSmI21UvSpU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\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GJgxMODpYc0yEm6SQZNKXgQjaRQYl92IaUsFhLAZoPsS+6XxvdBhMRrdd3/1BxMEbKhlY\n5uZ9c5oNqJ2Wyr6RyePD54TZAZypcJVOzR2QFfcGpmiVDr3PFN/2mHdJOlXCbwwd+wZr+ZQBOu14\n8FACVfjgGGN3LaGq4I1yjRC370Yd6wZVoNsYNmtQhrrz0gp86dg3WxZOLyXmC0zNviLxsT2+fn7e\na6+99trr09RHT6H6zu/8TvzSL/0Sfuqnfgp/9+/+XfziL/4i/tt/+2/45V/+ZXzf933fx16cvfb6\n5LWDVI9XzBjGYwvOXYM13LFzthevcNaKwp/Tyahq9Grng3PJyLiPMo+I1e2FLT9itdlf4PdGxqpS\nmTdZFUk7Twa1Zb/Gwmlj0lg4ieyesW5kLkozrtAr6jydAizAQsAgqGyV2Z9g7AKbVZ+LRSePp4J0\nX8BfuJnxnfvgjB0LZ7ZGkbhz6tmapPa/J6rSDmPjBANnMBbOyOAjg09m1DoMgiHZLeWIC29gmPhY\nnwpwlxX3WXCSgpNkLMjI3pAxGAMYCQkjJRwp4eDLeZMYN0PEiisSAYMQblRrA1+ETEZVGJphVIvs\n2q15Ac0z9HR6WQDnq68MuHnzFnhzB7y5h377BNwv0NmhPPZ27bTYuqoAyvxRAKZaWynOnM1L5ZSB\nKUNzDySYGTQxGZo2jqDDaPKf/+//exnQaZrsPsZlcXPlIi6fIoiv86LsBr0BfDpomBV3BbjPYttd\nEUxasGjBglzZHgzCiAEjJdxwwpdixxdRa9lHXkuNTNKnSCQNvEyCYSw1OpwO1Ng3iRv7Jtg2zNf3\nw3gc4E2/niYHb1bsmwK5a+bFUx5wyiYpO7mcbC7G6MtiJunFwRsDoY0xsq13gRMek05t2Tdb+VRR\nA3QbI7GBN70UVh0S7yVVbXm53q8ek/nf8AYoWXvcUPc+axCHu/PTFrw5MzCmOP/Bjumrc117T1uO\nb0aZS9zOSNnr45QirhX22uvD65PEiKeU8Hf+zt/B7/7dvxt/9a/+Vfy7f/fv8If+0B/CP//n/xy/\n//f//k+xSHt9Q2oHS153EejB2T5eATPn7Jt28dp+HxIqCeNiB2aqjAoN/GgXzZeNjLmbnVwv1/rC\n3H5uYI6iAGr35ptgF/uyagM6Dxy0JqJom23NCkBsgryn1vepVKwG8lRD4xiHB8Z8m7hV5QKO/hTY\nchjuQC6hsueGnOpUEm6ysXCOczYz43sB3WToTQbdzw62GABDzFBvFungo9qbpW68YZTZGnX3xake\nKGMCjQl6SKBDAR+AdFSkk3l/jIs1sgM3EKeOiQNkWRQnKXgrM+7oHvd0h4wJmRYAwKAjBhzxhX6J\noxzwpRqYUXSA+JaTmDA6eLMIWU9fQRyGCEGCgTMX0JJr00v399Dv+I6XSXu6vTX2zVffBr4yAEe/\nfYLeztD73ORTMZ4DG2Nqzg3EmeePB+D0Upw5VzYHJksz0rltFzQI2LdRqttFAiXzTcL3fM/zL9/p\nZJ93mnxsnB00C3Q2AKe4dC5LY+EszvqaxUDD+yy4XQS3ZcGdzrinCfe83u5GPeKIL3AjX0Dki3ps\nTEQ4JFoBsonCRNu3dwcvhy55ikay5KmD7z++L2JIDcTZ1sqs2f11ArxZFtA0+XY8rdk39xlyb+yb\nZTJgd84hn6LKvpmcdTMJkMUAk/CqDvbhNRPjAOp7lmQA1/G4/v6KdKoHjKpsCmv5lL1O/T0vGxgD\n5/Kpvnr26dYHJ84x1/xvVgwcnMun4tzXgzerNUnozn+NdbrXXs9bOxi2114fqz4JgBP1l/7SX8Lv\n+l2/C3/qT/0p/I//8T/woz/6o/gn/+Sf4E/+yT/5KRdrr1dWrwV0eR8j40/1ua9lzD6kqLu47au/\noA02jv0+LmR1HUWOmM21i/aegUPagJreB+cxI+NIotrOnD5lPTW6fXjgNCPjAkEiWsmoLI2qMYiE\n3OCY7HcAVqlUroSpTU/f0KzH92EqfbxvLPUi1jhOAhy8CQVMOhT+HjdlwBclY54TxntGOgroWEDH\npQIt1WeDqLFvREAHgUbyTfxOz4EcY+OwvQdQwRw6JODAoFHAo2I4CoZZMKRiDS2JGQ27vCR1PkvW\nsAkWZNzTHW7xLcz6FlkmCASJBoz0JWb+bnyp3wWpGcQ3oDJgZMJcTNYSEchFLR65qMtpCkEWhi4C\nTJ7SM81uJuwx2N/93Y9sPe9Y9/eg//ct0Le+Av7ft4GvboE3J+ibCXpv/iTBaKEh7jNwzFVGZd4m\nH9EH53Tq4qhdPuVR1HovkLkDbVmhWcECMNv2FB4uNAwGED7nmN7fg+5u/bGbQHtUts4KKUDJbCCO\nNhlV1m6bcLnUqSjuSsadznhLt3jLX+Fev8KidyiSwWCM/CUW+i0AAwcZsKgzcLo92gCOFl9vN2fg\njNm8b0YFHwA6sAE3iRtwE143QDvYRkIaMlS6zypuaJ2LxdFPDmKd3Az7tAB3M/Rugd4Z+yafGPOU\ncPIkrlPhyr6Z3E9rDumi++AEgJwuwAw9ExO4fAw7A26631cmTiedUqzZN0XW8impzwoAZ21grFpc\nHitn595t+tQ6gaqX5HaADdbnoBQJUejOQ9g+twNyYMBO/Vy1FwRbi5zZ1Mu06nPj3LojPHvttdde\nr7Y+KYADAH/sj/0x/Jt/82/wJ//kn8R//a//FT/2Yz+Gv/23//anXqy99nqW+joAKS9Z15KbtlTu\nBp60n/u/9WUXpR0Dx+O0bcY1AJsOxIGe+eDUi+MVlX39cyRRATBKer0wT92yJJhuxoAbBduFPkUb\n0ECcDEECr2RUxdk2PQsnfEojIQqIZWssnK0XzkPzYj14VVO2QMjhzaPhv2MR4qMAcyHMPvCnAhzZ\nk51Kwv0y4DCNGMeC4X5x49QMOiw+8x+No7Nv0BosGjYGDV3c9vlCc3scjJzEJhEZFJyamfGQOkkJ\nMUaGx34HIGeAoa2RBRkTTvJtzOUWIguYRxzSd0CTGKvJ9+lRBxwluX+JMW+iUa/+J0JYCiOXhLIQ\n5ATISUD3C+huAu5PoNu75t3yxRcPrK13qNvbc/DmqzvIVyfIm8XAkJNCg9F1MBaWJgJussW/T7M3\n55OxcA6H51m2ayVigNE0u3HxbOybxaOoT4oyxXMBMJCyAmL7GAOVpUW+fSnwPCBOzh7Bfmc/394Z\ngHM3G8A0CWQilMxYisdke2S9bQvY3ASzFtzThDt6gzv9Fu7LtzDlNxBdkPiIY1qQ0oCM76yghn1P\n22YTEQZSjIwOnBRLnkrF2Tdi4M1AoAODBruZI3e/H3HTW6oYSMMK4qDDaEskW0z6h9PUgCy/6f1S\n2Tf5BMz3A07TiGkZcCoD7gvjJIxTIfMAqt43jYFT5Z+A72/rVXEJtLmEN/TSqQBogLVxcZcAv4kW\nD3P5rRGynBkYA00eu14m971xY/ttfDjQzmkP+d/U43z8HjiTT63PV7o6s4onT9XJjwvytDgH9Mtk\nj2lFOr2WQMWUUHaD3L32ulpOoH5V9dEmZvZ69vrkAA4A/OAP/iD+7b/9t/ixH/sx/Nqv/Rr+2l/7\na0jpYS+JvfZ639pBlafXaxyrfml6qVT1wNlIqKAG4pCnA5GbY/YyqjMfnHrhfO6DQ1VK1S9TMHFC\nRrU+fl0ax6Dex0yuapNTqZKZeHYsnCIK5sbCITWDYfvutGbhoHnhvPP4XnhNzEpnoHp5HLwbOpVz\nFs4xFxznAcOdgI8ZfJQK4FA/8+9FAFQEKNlSp/oqZvZL1+K2I26cyJg4A4EGgEcHcJyBYzdjKAyk\nGJgwEHnT614UymCkuj5yuUcuJzAPPjYjBj5iJgNZFs1YdEAW3jBvws/DDGyzWAJPnlOVlundArqd\ngC/vgeOhebcwf7hc6c0bk0196yvgN/8f8K03wLduDbz5aobcWjKQzLZuOQGcAUBAhwI6mXSp+ppM\nk7GEXhrAub+32+SMjsm8VOSuQCZFuQfKZNtNeAnIIhiyVqDUmDhUwUGI2Lb13d+N9/bEyRn07a9a\nBDtQjaD1foHcO9tkIuRsht5ZOiPjTqpjUkRnnECw0IwJd5jkLab8BtPyFQCBJsHIX1RggEFI3lmn\nINJQ3G+YNy6d4qRIo4ISgGRAHYYNcBMVQGnOvm9moGPfxH4IwEC209QxyCbgfjbw5m6BvC3It8By\nlzDPCVMecJcH3OVg4AR4Y6DwXLSCoCWkSrQ+ilbmTQ/iP/H41gMzD7FvSjBuOjZOL28F+p/XBsb2\nOefHqO0kRTXAp8biNOCF2vdCA3T675mosUSDmRPMm0ioMpnopi1TP2+ENBhNinUp8bEu6wa8ufgc\nZQg9bIlPSFU2vNf71Z4etddee/X1KgAcAPje7/1e/Kt/9a/wEz/xE/iFX/gFlLIf7Pdq9RqBhL0e\nry2Q8aHV6PPaQJfwQYDWmHEANX2Jya7WzfzXLlYHVpTSgTVY++AwHvfBWc2ioqWKhNfB9sI9KPY2\na1ug1GZuG3DjzQGpS6eaPIrJk1mIKgsn/PDac66zcPqqSSa6YRyhp9DbAAYLx76bpeYkQmXgzExn\nLJxDz8K5E/AooKGA02wsmWgio0RANwLkBB0KtiaqlPM6EWnrxozGvFAmB3GchZMsStnYNwHgWBTz\nyOrNMGEkxogBCQMGHEHEfswRiGQUmSC6oMBuAFAoI8NMTs27g6pXUDWuLWwx68Wa2cOJke4EdJtB\nNzPo5r76jxCRAQ7f/d3vx8SZZ9DbN8Cbt6Bv/T/g22/PwJvylYE3+cRBXDFF2lEwAKAkoGMGIgJ+\nmkAOqmjOL+PT40XTyWQ5p9nYHGFc7OBNPjHyZNuGeApaWgiaBaqKARnAqe7PEDHgz8FB/a7f8u7g\n2DSB3nzbxvSrbwNfvbHfv7mHvp2gtzPktiCfgGUaMM0DcjH2zeTbgAE5PYijyCooKG6XvUDUbupA\nFBGDaUDCiAEDElIDcIh8Gw72TS+jkppAxaygpKDBGDiNdbM5IMQYiYBKgc7w9Vzq3+s+CJhsagXe\nTDYWb2fIbYbcK8o9YT4Z++Z+cfmUMO6KJXJN7gc0lw37xnftAJ8vs2065siV1dazb+Jn+93D7Js1\neNP8b8IP7JqB8UP+N3Z+SDWBKmRV7F43D/nfBDATY8EunB3870O3SsnBm+2QMQWriapsGGhgkC3j\n9arLC0b5QCCGwRfZSnvttddeez29PgqA8+M//uP40R/9UfzW3/pbH3zezc0Nfv7nfx4/8AM/gH/4\nD/8hAODw0jN+e+31DvWpfHC+TnUtqYmuiO63Ro6h7W8XtVrvQzoVMiqhYMbYmjPAwuPDXUbVAzUB\n1iQ2sKIyWjbgRvXL6XAEUq7SmmvbSFzoh5FxixHvQJyQLZEtc3HmkKi1LcXBm2DhAB71fYGFE1fl\nl0Cc+B51jLGh0HffTRDdkI3/0JkYD0VxYANw7phxzAkHdhDnNLoHh4AGAR0yMMwGtvQV8eHjCCoO\n4MTCRKx4Lg3E6b1xLsmrAnRjgNkAnBQMBQdxwgfHgByPB5eEo95g4CNG/gKZv4BwXu330bjFuBSV\narxa1AxZs8JNaxmLiiV0ucHz4b4gHWfwTQEdZvDQmTMD9v1Lhn75HcCXXz4NcJhn82e5vQXd3gLf\nfmOGxV/dQr91C/3qBPlqQf5KkO+MGRFeLQDAyaVUJKCDgu4L0s0C3M/A3QR8x/xyPj1Rwb65uzdg\nYFqA+wXi0imZCMuJkRc7fmSPn2dWjLlASoGKYBAD1xgAeTdOEdc+TU8f1+2Yvr018OYr98D56g76\nZkL5dka5BfI9Y54NqDt5VHZWxqIhmaIWFa62n2cUFCyrhpZoAPOAkb/AwEcc6Esc5YiREkYHNkdn\n4Iwr9k0DbxKLHZ+SmDxua3TSVwW4CuBjSvFz/5wYQ8AAnABv7iaLo7+dobcL5FawvAXm+4TTacT9\nMhr7piTc5YhTtzSuU9bqfxNpT6qoQFUbEzpj3vTSoke9vND54DzCvunlUzXSfcXAafLXYFEGOA/Y\nMb4HPOp3cMj/kozqIf+bXtpkDBs7d9EF9k2diNgwcESpStIqKNSNcfWRe8JYAj5J8UT202uuj51A\ntSdefbOrl3HutdeH1kcBcH7qp37qyc8lIvz0T/80fvqnf/oFl2ivl6k4Oe0Ax7vW+zKMVIv5rDyh\nIhL5Qz/zKfUUkKtP5Vi9dgOSXHxtnTVscalUL2yDGq4VYBEisCrU2TcqhESKTOpeNk/3wdkaGQMd\n/V25jqn531xe/q2RcW9mLECVUYV5cc/CMbPjxsIBWupUsHDiUpF03ejYmPkYwubXTVbWpGI9YAU0\nW4wAcRYRk26UaCYJp0I4JuBQGHesOOQBIwsOS8FwKgbipAIaChIvxpKJBao5vgUYR4sZJ8JZIpWq\nNZFxiwbTX69nGekGNhEbE4fcH6QyFZyFMziIMzDhSAmjjDjql5joS+RkJsbhg1MX2dlTRXNlKJkH\njtaULkvWMVbSkRl3ecCwCA5TQXor4JRBnEF8AmI8SvFo8QV0dw/98gvzxhkPxojYyl5yBi3hRXJv\n/iy3d8a8eXMP/eoe+v9OKN9aUN4olreE+T5hngaUwiiFQQ5wqZAtzyDgg0C/yMDdDPpiAm7vQMeD\nLcvNjX32c6ZS9f4yFRgwbxm9N8bQcmLM04B5tsuWXGI/Uyw54ZgzpGRACoAFEAVnMRCnGPhApwn0\nHY+Maz+m09TG9M0t8OYe+MokVJXR9EaxvGVM96OzTUacyoCTMKYSaUsG4hQJgE+RoZWFF8U0Yhy+\nNKle+gIjfYlRjxh1xJETRj8gDkwYmep2nMhkgQbeOGDp4E3t7PsKb6ksQCpw/Zz/Tc63swBOZwdw\nQlp3NwG3a/AmpFOne2Pe3Ll86r4kB2/sNhUDb+xeKouNQRAoEjomCs6ZInTt4Io16+ZdvG9EazJ9\nlU/Vv/nnKZ0bGEf1MqFeTrudtAgOjp2r6FH/m/U5rmOLdmBWSKeY9AIIY8BU2UQYV6bapnpw6Vox\nGIqE8g0HJT4nadPLLuvnMw577fV1qFcjodprr8fqOQGHjynJ+qbKv64ZFG//tnr8QPTFFlg40/kD\na/CG2kV3jdbuWDjhBZDcDyWYLuEJMBCQ48J6axiJNbgUc6vte6RqbByX9HHxpGF8SWgzuSQm8woQ\nR5uMighnLJyQh0lc2CugXSrVpdamxzdMjtWNaTQGBCQmkDNt2L97pC4JFKSM7I0XEM2k4i4DIxFG\nZhyYMeYB42yACQeIMgiIC4C5k7lEM3kADt4oMq2lOiuWQLF46Yi/DlmVOojTfdHY7aKxCZAv0ZqB\nMwQDx2VUR73Bgb9E5gkKQaHJJFW+jiVi4ElQtGDRgqK8Mqmd/XYqPh48WKT56QBmAbECXABksNwb\n2DBnj86egS+OoC9ugJujxWIP64SuuK9+JAF8vLkz8ObNBPlqgrwpWL5ykOHOAJBpHizaHLYtD6lU\nTxlOC3hU0BcbFs7xHjjemocRAE3f83xyqjdvmr/M7X31U5HbjHKnyCeuUdTTYp+5eFQ3EzCUgpwZ\npRBUCIeSMeaMlA3E4dlTv+4m4DvuQV/emO/QOK7HFXAAZ+lYJjGu99A3J+i3zUU5GE3LtwmntwPu\n70fcziPue6+XCuah+SJJyKgEmVoENYEx8AFF7f7A3+nsmxsTUTFh8M58dP+bYODErTIztofRXhuU\nHbgp0va1ul1pMxivr+3YN7MDPR4Xjiohc98bB7OadGrE7TLgrjDussmn7gtwKpZiNxX3A1Jj4QDG\nPOzTp3pQAzhn3lw7ZVTGTdxXCdXj7JuQufUeOD3r7pKB8UPNMWvkT3HzwNn437Afey/53zTQfS2f\nCjZNrPu0kRW3ivNG833bnp0vMjSfAOSsP4V3r5u99rpSit00eK/nqx3A2esFKtqCvfZ6Wm0vJ1cp\nGDi/IG3R4T39O+RTbQYy7sVZNcHCYVL3AljLqFLMfiIuos99cOJC2C66yZeH/H24zrZelVH14I22\nBk5JqteCkrM6YCwiRUuk2rJw4MsbDJxrMqqzMTeijlPwz31w7PtpveKIGN1gmkS07VwUJ3JDYFb3\nk0km6cgDBhakUzACMogEIANxSNRuubhxzACM2ZvI+XIjWfy50UwuBZhLa0yr+YUprdr3DYPr1vwM\nlb0AZzT4smPEQb9AphOElno427LdLD2sICPYN4pZrDG194Pfkn/WWJvs9ibFZD9ZQLMZCNP9DHxx\nAI4H4OYAJDd/3gI4fWMdRrK3E/TbE+TNgvJGkN8A05sB02nANA045QFzTijKLldRDMJQZ2Glk4DH\nDL4toMMCvplAxxE4DKDRTZYBi4D/Ld/94SDOmzegt2+M6fLm1oyBAxi4N8nXfJ+ql8oKwHHQKeWE\nQyoGSglDhKA5Y8wFaT4Bc7HUr++agNsT8KWP7Tiej6tIjVA3GZezgW5nyJsZ8m3b7sobxfyGcXo7\n4O7ugLfTEbfLiLcBWPgt5EJTcbNeVSxi/jfaAQFECUwjmEYkPmKgIw76BUaMGClhIMLgi5mCcYFz\nAPYM2Jbu3hELLQ4W9l17dnPxhTbj4cw3j3QHYObSd7NJ3G4XyLdzYyLdNTDLwJuE+5JwVwj32aVT\nzr6ZRTCJIEuTKKUqNroMmPfARhwdepZKXzVUC9fZN6Vj36z8bwK80eZNZsMY/5qB8TX/G6K0klP1\nBsaX/G8qK6cDZ1bsozh3dfKp+jp0r9mMhXOHavJi88tZmyQHy3Svvfbaa6/XXTuAs9dnVa+BhfMp\nfHB27x2r/kI9gJ2tB05cnPbFcDmSs3B62vlWRtUnfSRaexFswY1+djJYOK39QDPCjUbCwZu46A86\nvnQJVL2MygAZqmBSUThQ1Fg4gDFxqneDWnMQc8aXZFR1man5IvQNRIxBSMWYqMb7BioS6o9UqLIB\nRnZPGWKMOa1lHffq77nA6EYFXOVTAsoC3IxmQHRwVkTfXVQGgbNwljBUzdClQOcCFIFmhWaFFEsq\nUiHIRjoQjVFdz27pkJgwFkbSwcAWjBjoWNdXsKyKuokxMgoZA2cSxiiEoSRrsFm90SYk4vOmSsnA\nhjLjGFKzuxP4OxfQ7Qz6cgQdBxuLcTgfi7hfjF2iU4beLU3K8kaRbwnT3WBylmoma6lZ8RZMwEE6\nBg4rOJmMio8FepxB473RlIZk8dwANCLgv+M7309OlbNFnb99A3rz1hk498Z0uZ0hb0vzlpnMP2hy\nSQ4AzJIagEOKWSz5KQsbGyczbsqCcRHoMoPvC/huAX05gb4YfVzPE9GMnWIsLz1l4H4xNtDbgnJr\ngBgAzLcJp7sR96cRb6cDbpcRb5YRtyXhNjfA4i4beBMAzlwECwQzMjLlaogNoLK8BjpiwBEJo2+L\n5Le2zipggzXAHdu6bfu2u2qG7RezSaaICepgdN2vhgIs3T4XG0gFV53FBLRt7T7buLg8b7odcH9/\nwO1s43GbB9zmhLeZcVfIx8TG4pRtPIyB40lbvS8LBfuxARyr7472c1/9rtF/vUvsm+LKzGDf9ObF\nIZ/S7rgMbD2wpDJOtsyTuLaICPH6+9VZogFVcUwfKujrN26GzgOt5VMNxAvz4ssMnJhmiAmLDykG\nvRPH5qmmxUT8quRIr2lZ9tprr722tQM4e71Q7SycvdZ1zbz4vd7rKqsk5FPrC1hBR0vXfvaSagPU\nx4nb79aR4n3DvzL7BS5eFF+TkG2NjG35+n9aZ34ZBKHGwjEfA1tW1WbSTNqYN+GH81CEeABS0ayw\nj01iRdJoDsjlaPb9CtBaFxVk12/NJEhi0cCppuKYlCpRqgAOux8NAKhmjCpIUsACcBbgxkAZGpMx\nH6Kx7ulYGhKQUiVUGgycuUBngc7qDSsg2Rs0IQNMHphfTs6YYSIMypb84yBOwtJJ4VqCWMGChWYs\nOmJWxiSMVAhMjBQNso94ZMnYrL/Fiy8ONuRlwXFaMN4L0m1G+o4CupnBNwyMCXRIVwEcnW3c5CTm\nF3On1aj4dDdimgbczoeaBGRAhyUjhewis40NkSJNxpZKtwt4FGBYQEMkh3WNqAg0Z9C8QL/4wlKz\nnhI6IGJ+PffmLVPBm2+/rcbA+mY29tDtOsnIvFTssmUqxsCJM83IgkVsTJfCWEpCzoybecHhvmD4\njoL0HQX8xQK6SaBjsu+0TUTLAs1i29Nk4yr3inILLHeM+d4/fxpwd3KgYhlwmwe8zQbevC2E2+yA\nhcuFTDYkmMQAv4UWLJhQdKmAIIGRaKy3QQcMYAzEFVC150UjH6ACVfBBlVCEIEKQwtBigKYWhc4K\nDAJwsWOFGgMOuZzvb9ohHw6S4mQMHD1lyH2B3jeg8PTWwKy7eazgzducXDZFuC9YjcUsgkXF07i0\nsghTsEJgjKMe4GjfXc8ODX1t5VOxy2zZN/VWpVQtDbDJp5psCjDZZO9dtjIw9kmhCuBX9k1LoAI2\njCLqzjXbn2m9nglNPhVyqURaj+eNgbMG9AKoj8NG7/nWxpTqyPWAmS3vw6APd144ljy5gx/PWc8B\nJu3+N5++bB/8MAD1uUv18efs9TprB3D2+uzqc/SUecoyP/f3+hzHaVv90m9Bm97XBFhfdJ4zcAAl\nAiBQ4vbakFFRdwGNSPpA9cjpfXDiYjnYKfH+bWa1yageqgbedM2AyylUGUrRTFAHQClIm6lx6SRU\nqmvwppoaAyv6TT+53suoElnUcQVv3CNmIEIh+9y4wM9QkF8QLkJIpXnKDET1cSIDcWwst1cKGSqC\nlA144UVApwzcDM72YFDaNNdhVlykATgOYOgsBmIsClkAWayBLcW8Uopw7Um3Qbv9T9bYsPlWUFoB\ncda6LSCYD8pCI5KOmGgAKyHJaoutgFGAb6JsCVUeLz0XttSiPODLecDNacF4LBjfGvslHU3GRMmi\n0eui+PWyikIXhc5AmeBJTQnzyXxutsDHVCzaumgI5yy9KH5mb/54Uk8Py6ChgIYZzLQeNVFLzPJ0\nJ9zfQ49HA3GGAdWIGmj+RfNsBsHTBLq7b543nemyvJlR3hTk2146Zd4y98X8ZQDUiO74HgMzJpEa\n2x5snGVJOE4Zx1PGeFuQvhCko1wdV9u+AJkVMtm45nvGMg2YZ1seANXv5jaPuKssE8ZtYdw68+a+\nKO4zcJsF91lwkoKTZpzoZMAfGYCzjaFexU5XEOCcgyld0y1Kfgt2l93KQuBFgRMMQD2ViliQqIFV\nAwOUV2loq31tNoabTs42OYnJ226BfMfGvDmNuD0d8GY+4O0yVjDLgCwbj1NWA2+KSQ5NShbsFsIY\n5vBElRUXjMBIpuoB9QpwPNAThXzKHj/OvtnKp8L/pjecDvnrY8VYgzkho6rrk9r9tfjwHqgK+VTq\nJhp69k2AN+vx0HouQJzHOuTroXPs+fd5N/YNUXpQXvZQ9Ppee+21117Xawdw9nrBev0snM9JRvVN\nq9UMYH8BW7kM/jtvYOp9SKq650gwc0DeEJhJcKGtCWgvr1r7EXD3M6GxU4D4mWqUuDVeyW9rAIC0\nNQOrSFr3wOllVKSKUlkwl1k49v2oyqWUmoyqNXfnjJz4sZdRpQq+NPo+aZNRsRKKAzfFx3lRQdja\nJGKn/If/C3eNVktxMkYMcMgZYxakrNAlg48MmgrowEBiaERsd6VhxFocwHFpiM4GZpR7a7rLQijZ\nAJxckoE4aqwNY8CsPTIeK+38ioCTjyGvjx8KiBx83Rpgo2rysyyEZQAWTW5sS5iEcSoJX+YB98uI\nL6YFN0PG4ZAxjoLhUJBGM4CGR0MTN28fVUAWhmQgLwnL3Ix+Tzm5oa4xbyIVafHvDwRzRVESuUF2\nM0NNLGY8zS2liAFjbADmh3KagdMM+vLUTIEPB2NzUMfYEQFKBnIBTVMzCL6999tk4M1XE+SrjPyV\nS5TuR9xNfZqRMTqABuAEk4iKRdnPiTGLRXifinn+fJEX3EwZh/uM8e16XCmtZ4+1EKQQymIyrEtj\nCgAnB5NuPR67SoRKD94YYHGfBXel4CQZ95gw0YQZ91j0DlknZJkgmq+ei+I40y9pzzIxAA6+bRsL\nacgJQxaTxE0OY7CBNuy0E10ElKixkLp9rd/PNCvUwVEAKHe2ny13Zlh8f38w5o373gR4c+dMpNsY\nj8pCMiZSgZk5kzMh2/E5GIHUwPR6DniaT0tPIKq2WE9g32zlU6WTt9p4N98i1fDAaSbGVD3Q7J79\nHLA1MCY/3vb+N1VKhe58g3YuC0A+AB5y9k1vYr2VUMV5QDcSKhtTRYxmP74fWmbev7My+vr6Roh/\nXb/XXnu97toBnL1euF4GxPk6sEueq2IW66lx4p9bXbug3PQbVT5VmTIdC4eVABYUsfDTamS8kVEl\natRyDlkVmhdOZd5EolG9+DVwg525ER1GjZLd6Pvjgt+Mi93MdCuhClkB3PsGzQuHlJDd1Njez/AM\nZm9W/PMVtgcmf9yDNqLnMqoeqEpMSIrKpilq4yQOHJXu+7AQZkTjTzXZy96PVw1KGwOgFIaUjHEp\nSJOCjwK+ASgJ6GALQ9sXihqAkV0+UuUhgCwO3kxsgMbCmJfUpDXCyD526m9RlJp5tM+89xfbtUGD\nQHTx9VZiBdsyOCBnz7HlKaoo7suyCGFOkUxFOCXGKRHuCuPLxPiyJHyZE26WATep4HAqOAwFh1Qw\nDGJgCluaFwCIy9dUAREDqeZsn3XKA+bi4EVh3JWEqRBOvhxLB1wlAkYFsjIkAXFJYHKd3mzZ0rIg\nal5FgBkuL56YdXtvZsvjADqMQHJj4Esx8PNir7mfmkHwm8kMgj0xa37LuL8dcXdyYCCPuCupGgMD\nZoZrYBQAWKN/EsVRFBNbfPdNMoDslBOOqeA425iOPq7soFg/ruJsrZwN+JtL6sYz4d4//74klwYZ\neHPqgJuTe97cZcGpCE7FmDf3mHDie5xwixPeYtZ7LHKHopOd08AQGs+avdgu688I0MFuWbDaxseS\nkFmwLMnWI8eRQMEZ0CzghYAkoCFYSBvnFNHqJ9WzvACg3BvTK4yx7xcDb950vje3hXHb+d7c5+Z7\nMzvzpmxkHeYBQyv5VHjCxBGgl09dY9+Inv9cPXDi8RX2zWX5VCehwuMGxnEubiBOY1GFgTH3IA46\nsKabQAiz6t4Dp8mkgKEDbeI+baLp7Thvx7hmuh+MnbW/0Pn3sImD9ymb4tib+9dQu5/P6yjF0yaL\n9trrKbUDOHt9tvVcIM7nAga9NOvntY9DLNkKtNno/bkDb1Y+ADAQR92PRcQuXAdWlLKWUdUoVlrP\n/jZJVTymju3jF+YaF8i9kXFanbUfMjK2ZbV2wZgFyWReIBQY0sLeaPWx4UUV5Cycfqa5zuYCV6et\nqxGq2gV9ImsUCjXpQmIgKSF3MqraUKpggbF/kpBFN4OqN4M1KOyzwoPPgFuTXDwxqGTGMBcMkyBN\nChrUoqwHW/iehaM+hV5ZKBnQAshssqmyEPKSMHvs9BxNuKQqXSoa904y0D6Nxhu2zutCHLwRyQCy\nJVPBZ1UZlUVVaDFjWv0Cixyw6AGzJMzCmAc28KYAXw7AKRFuEuE+EW4L48uUcJMEBxZ8kQQDCY6p\nYGSpPkJbaWD4ndj3cemQMu6LsVBO7j8yR5y1A30BqycGRiGUpM3EmBJ4CUPwDjSQAs0FabYunicz\n+MUXI+hmADypCkNyAIcagAOs08PCePl+gb6dIbfZjZeB6U2YAx/wdiPHeZvt+wDGwJmlyQgJ1vyf\nmHBixY0QbgrjlAR3nAwYWwQjtxv5uF4bz7idSsIk5NHgDUA6CeHOk5Um0SoRMgDHwJtJC046454m\nTHTCiW4x6x0mfYtF7pDlHkUzVAWJBggt7pFVKtMjGCHFkYlYRkuEIxQml+Yx5mKeOYkTaOnXH0GK\nycd4AXS2/YsGvb6PhZeUSxLzZM/p5WT3y4i7PFQfoDc54U1mvO2YN3ed70143wSzBbDkqcpi7ORT\n1UwdLYHrEhhsQLcvu9/HsTBYi+pSokvJUz37JsfjTj4l9a+NSfGQgbEtk4M22tg3KwPjeg5p/luN\nvbiWT8V+2Mun2vG1mRcnkjNfIPbvzYSVZPhD6jmvQ3ag53rtwMtee+11rXYAZ6+PUK9fSvU+9a6A\nyqfwwdmWQHDNXPe11EOGiXUWluKyvHtdxxrYRjXHBT75axl2a6kdqCycbZx4ouYR0/vgrExFCSvw\nhpEMfMEavInqzYttJnftgyNutNyzcAKMKeqf7X4XMS69ZOCSjOpsnDcsHCZTUpTSzIwTE5I0Fs5A\nDFXF0r2nQM0TR6TCVmHi21hSZuxrNcBi0al60+ScMS4Z4+yR46MgjQpK6gyc7ZR6B+C45EUyTDKV\nzfdkWRJmj8yeC7v/iwEbkxh7YwnwRkItonVNZORqMCu6IMsMkWW13weTqnCGUoHQgkwLCjImOmDS\nI27kBpMOmCThyIxjMinTXSLcJOA2MW6S4iYBN2yPj2zeNAcWjN60DXy+zYd5bQUcNKRZBtjE/VyA\nRVFBq9hmBgYOrMhKzsA5Z/GJugF0WXBYDGQDgHQv4C8K6MvFDIEPCTgk8y3aGgP7hqkhyTllYC7V\nCLe8VeQ7wnyXcLofcHt/dDNcAwXuSwNv7hzAORVjMxVtDWoiS0E7EXASwoGBm8I4suLAjGPSOp4j\ny5ncREHV4DnGchEyMMzH8+S9eh8PPkmXrCQNuJk0Y8KM2cGbie6w6F1l3mS5x1LuIerx3AwkdY6H\nLrCYegM7impdd9kBx0WAxdlGozAGAgZJSKXJO9W9ccZSMGRBWmz/4uRAaYKfnrtty/evJiczkHWe\nbPtYPM6991fqQTYDb4C7rAZwObA1iY3LoqWCN4ODGoMfMxpoTDWBqV9PDdQ5Z47E8XArn9rGg/fs\nm+KMm559E/KpiA8PkN2GppdSXpbGMBgRIV6BfG2OOHHueKp8iur7ooI3zf+msUntNetjhLgZfann\nJ38vivdsaYqXJklecz0l3eolawdYvunff6+9Pl3tAM5eH6let5TqtbNPvmn1WOpFfd7KxLhduF5k\n4MCaGe1AHvP7EAxsjWCANds48d4sc+WL0y0v1/u13aj9nABkXxbxZSn1avqSDw7DzIyFqLJwQghh\nkiprPmwcnH3TNynU3QM1Tjya3b6IrHUXbWbGwcIZ2ACCnoVDRE2HA5gUwkGs8MNhYmtSEBHtbGAA\nqM5+hx/NXBKOORlAMIS8xeOsUwPj1v4v9iWkGMBgfjeEXAy8WYTNt6QknMpgLBgHb7KDN1kJWRWL\nAllc9qSC4vHOIZsy9s2CIvMawKmz8wVKBYUNvMmYMNARE46Y6Asc9YhTOeAgI44l4T4n3CTGzeAg\nQwKOiXBMhBtWHBIwkuLAycEGdTDxHIxTUJWChUQqC2ESk2wZCGHMgiKt3QwGzsLOwPH1sgVxqmdQ\nTrhZFhxm247HewEfndFxk0EjmextYAPdem2Gd81VkjMLdFLICcgnjwr3tKk7Z3W8mV2OUxK+vZg5\n8H1GB+BYBPUirY1IpAZiMHAohJEVRyYckhnkHhgPjuelsZx9/GYxwGZ2lOCU4WCNyYImZ5dMWjDr\ngolmLLRgphkz3WPRE7JOWPQOi9yjyISl3KPIXP1vSLlub0qCguwgjtr6830uC7kJsIE42UGcRIRU\n4ngTQ+/mxoVQiiA5iMPJJHnE5/uXRZBHkhUhZ8ayGBgKAHNJmHJyX6LBzJvdn+i2GHgTN4sNNxnZ\nLKUyb/r9KIWciKkDcXrAogccztk316qmc0FXx844/mTpDIvR2DdZZSOfahKqMDCOBCpg3cj31xHs\n7Mtg4QDNL20F2nTftT/XhHxqoLZ9N3Pj5ndTJVQda64eohUo6MH0a2zWWH4D/WNy4rGiFf/pkee+\nsqjwb0Lt4/16Kq7N9trrOWoHcPb6iPX1Y+K8JjNj1XLmg/MYMHXt74qyagI+dfWXklsKfT/j2C5s\nG7ATzxEEc6ddHOdudjeo5QMDi67jxKOBqLPBFABPu1gOEUCAT/3s67bC/yZ8FIAGBrR/5MybcxYO\nq7mSUIAYLq9gpup3ExKqa2lUMZb9BUXzX7DkqebD0JKlgoUT8q2YSTdmjqz8cNosOSH2FoBXrJGi\njEMp5t2RxXxfUjEWUDKZS3iUsMvf7PNiLI3FI8XuFwnvEpMUzZJcSmSSIpMxkYMbwFQMvFlULdYY\nggWLgTjOghDJrZVzsAoARDIIbNAcAyoG/mQ6YcANFgyY6R4nHDHQEUe9wVGOODqQc8gJNynhwCan\nOiTCkYFDAgZijKwYuTW0gwOI623JGBkKVEbRUkEHS/sxmZhWHxDA348JC6tLyBqjS5AczDBT3Kw+\npjnh6ADO8ZQxjAXDwdhSPIpJclJx1lTn0eSOsZoBKSHJYeSJkRc2k+B5qHKc+7xmdAR48zabVAkI\nAMUBHG3bb3IgYCSLtD8kYMjGzBmrRKUdR3os8tI4xmfMxQAbD2KqTJuQBE2asSBjogkLzyjIljKF\nBdnBm4LFDYud0aUZ4vKpelwIBg4Wu5GBHtnXJQBfp1SXL8Cbwf2m6rbhTLdcGIeBkbKe7VsUfl6b\nfSv2q/ACMnlW8rG3/SpMpe98/3qbIy4cuM8wVpJLyZaIDe/kSAaUs7MeN+wbapKiS8bFK4JX9/uQ\nScUxMO6LrNk3pbJsUOVpPfumB27iH4CLBsax7uJc2keJNxPjZgZP1M4Z/XYYP1ffn2DXhFTXz1sh\npQrj4pBO9ec9hlb2jYBcItsAns+FZfOhdS3p6iHZ1nODHu8jEXv9wMtrX7699vp61w7g7PWR6/lB\nnM+JhfOhMqrXBBi9hlqBNJ2Jcf17SG/ELmSVzOsjsUCUMZDU2ckAOQiKgQgL1nHiHBfYdQa0MYX6\n+5pEheRU+ocBtDAyDh+cJqNiFBTrQCr1pL0XETUGjjYWThH/HuxJVSCff8bFNCqgyagEkdBlDVTx\nJt+YKY2FI+B2+eZNWTwOPxwuNiKtUTAQJzhORQllMHbHgRmzJBy4YOSEkQVDcvNenDOq7LtEsxnf\n2+LCc+ddMkuq0dlhOmt+JY1NkcUazWgwF2TzsYEzITbxzqsZdh4qaFqNjrFUb6NMjKwTZhqRMOLE\nR4x6xAgDc8Yy4lhGHCnhwCaxOjAbY4TNCHpkrIC0a6atlpjj4IOo+92ogxFapSLV/8bBymMyTxVR\ndblUzBSyAz+EqZi3yk1OOCx22XAzGdB2GAtSEqR0mdXRtnWXuhXzPcqZkbOBQpMbL0di1l3pU4y4\nxlBHLDdgDBwDMnQlowpwdWQy8CsbI6cfxwApt2MYMqWQ1S3aIq9nj72e3dMnmDYzMhZazkAb0QJR\nY2SpFgNjNFcQkMi2JaahmmDHthWJZ0KCohkFBVkF2f13FgEmAQZRDEJIpZmvxzHC2CaEzISRBYsw\nEivGkpDC/6c28+f7VlE626emAHA81ezkoGgkcN1mA29uF5j3jZs4T1Iwq/GJistHE1KFuA18orpN\nBlgZ5sXBMrExWkuK1vvAZfnUln1Tur/FvrFm2xirMI7F7bchoWrAe1/bY32A+NUDh+I3zQenl1KF\nafFWPtUzZpp5cRsXM3+WKqGqgI+6hEqbcX9IjWP8Akz6OtTrBz32+iZXHIdeU+2EoM+3dgBnr69F\n1QjPTyCD2kGVl6v+wnKblhGeCNtGMWYhDcBw4IIBCLUZZ/RyqCajWjSSp3pTY5cYOUOH+sYiZjvJ\nAJSaRAVPo6rL3h5Ho68acbRuZIzWtJkHjrFwCApWPZNSBeMGaHKAAF8umRkLYcXOuSSjYv97NLiJ\nzK1nYKrvn4ggaF4q4t87mDjhh2PvSeDSaPlwMEmUkJOlHy2JcGDzGTkwV4PZlM1gduiMOXu2laCx\nBUR9mSRYPeQADrsPjPmnnMRvxdgbweLIflu0uHwqQ3rghhiJjw7gpLo+A6BjGuusewA6AgErkDGB\nsCAjYdE7TA7mJB4x6hEHfIFRDziWI8Yy4EgDRmK7MTmIQw7e9KwmG9caJR/AgypKB9rkFXgTjRu5\nX4w152VwY2kHcWrz714wEc19YMFNsnEZFzNZHiYxRkc1W5YzBlwwXIpwBQcaqyOYUlyBgbtsnjMB\nCrR0J+DeU7BCtpTFJC8BUhJ6PxVyNg6dsTlWEktv8i2dzAAbA8Ps/cO3xRg2MwBgoRmZTC6XybyS\nbL92ZkYw6yIlEKmBpxyeKIxCuT6HeVyBgoJin6GCBVIZOFkUczGQKpUApezYZPs3o6Rmxmz7lB3n\nwhCb0Qyct/tV7FM9S25yY2wAq30qfIlOZQ3emO+NM5QgK/AmAIxE7Dfbznv5lBkZU0s4j6HbHLeu\nsW/CMSrAvWDfFNENcNMzc7CKDc+xJv34DGxkk1r8vpNQuWTW1m7cN3ZmnMd6/5sAq7ZS3QZk2foJ\n75sGatk6NdCmgTdVuQgFa8ho28DFREVf8ZmX6pKkmcEweD227/Z4r9dRLwdovTYYYq+9vnm1Azh7\nfYJ6OSnVh7JoXgsLZ69WVJkb8XNHA+9/37E0ArzpZxqF4RezxsIJM+NEikLBvFEUCiNjbYwboipf\n2nrj2Ge3BJXwPABZ0xZSNCKGSq7LuzUyrj441rYZo0btMjmAHHuh7T9EXQKPAzJFyR6LLWdvZiwa\nUiz7Ww/i9DPagl5KZY2UiDEYNJo7seYLgLOGHEiC2vKRvVHMP3cuRE3SoISSzIPmwISZ7X5kNp+S\nzri3NzFl/05tHMPnohnQhgnt5FHTIZsK8OZUyFNx1E1oxcAbFCxY0BuVEiUkPoJ1BPgLX4ah/Y2G\n2rDF73rWTlu/BVkXQCf3O0lINCJhwMA3SBidnXPAqAeMMmIsA0ZKGGqzSyvmSN9YRVKRxc6rN6Lr\nhjTAZgZhpIRR2QEeNiBHIyLePVa8gT8V4CYRjmwR1QCqwfLgIBt3ko6LZqobYKCox5p3IFtLegpA\nwNbTXcRQe7oTAJPlaKmsqR6cCsPYRIyhuEzHQasGBjbQcTtuGVoBm0IZCxbMPFewBoDL65aVjCaq\nZ16A2mWWwNLFgpGj7GbF2o4LTINvU1zBApPzjVj8cxZlDG5OnUjBpQNI6xgrFnYml/g9MWrKHvr7\nAAGp7lNFzw2d1wCO71MFDuAYO+q0AW8C/CpYM9mus28ayBaeZD1Yvt6m/P4R9k1lVV0wLi7V+6p5\n35hEdC1orQwcbceGh6QxhFS9b0gD8EVj4tD6fFLlVB0TJ85h7Tjd9rHqlxPMmg68aee9kOH6eak7\njgJ+zrwAzuz1eL0k2+d1M4le87Lttdc3p3YAZ69PVK/XD+d9AJba7D3Td3pfGdUlH5xtPWcS1WsA\no3pjxurncEFOxQCUQj5F3cXxeRpVoi4Ku/fM6G5EVC996wyoUp1tXSWQ1Oaeq8cFabBvDLSJxkAu\nsHDQSanCD8eMjG0JioM2hMbCKWqAFQHVM4cJdUaWcO5/0xKKtDYUiey1icmSqcjimgsF+4cgnZGI\nOGOokHnKmDrEeEOVLRMAjjeZRzfTHd27xFKXgvGjdWvdsq2AJqEKECcMaC1WOeKzg3XTkoPmYv43\nc2XfCGZkY0X5PkaUMOAIDcAmZtRp9PXOYIxgCp8LZ05QN1uvpTb6teFHqWa1CwCit0gYwRt2TsKI\nEQckHTBoQpKhblmxXcXjCkb4J2RERH38ph2jBiQkHTDqgKMOKJq8iWVnMaGO3ymZyfJ9STh4OhYA\nA4C49+LoGAIX1lO/rqoxsqADB87X06mybpqXyqnY2M5aMGHBQot9V7SkINYGoCSNRrrtm3V5fExy\nBUqKmVCTAzcuhyq6VEmdhOcJGrMmUoccakOisW4PsSx13ZBAyJZ39b5dY5Ro7CAO399RUDRMhMX2\nQ2FQB97A2W1FLXXsqEASZyB1+1Q1vr2wrvr9qYKh0kAcwNePEKbSR6hfYN54XHjBeerUg+wbakBO\nD5RfqurbtGHf9Gy0PoEqjIsvSafC+yaYNyGfkm7bCv+bSwbGgAG4l86vtu31DE7qAJgGrvQJiHE+\nquc4CsZosKka+6YHbyog55+ruk5dDACoLlv/GG3SZAd3Prw+VUT66waBvpkVoPFeez1H7QDOXp+w\nXgbEeQ2gwmuqTzEekdmR+jQUlGcDjoC4CD0/G4b/xjaVCgBSEpTC9SK4dDOYMRNN1ORT3F1MB7Cz\n9cGx90dtt7rW0ZbzwncOI9yQUtVGgXoTU2PhZAUGJJs5VVn54VSWgwDMxsR5iIVT1BCdYOzE5XmM\n1JmMCgQhrSycaiyqjQmibmocyxXNUI2L6q4jg6mjalKqomaim5kwMToApyUKRXT7dva4f8/avGlL\nEbImtiUIzd5wmukrnIET5qrmz2FSNgcBKGHQI1IH3kRjPqgBOAnGoGHlVaNuy+XNOiJNqKBwrqa2\nIZ0pWKAqyJgAnfyzxwoUxX2iEYM2YMCWic+2r7Up9jVgI2EkY/oUPaCUEUWHysaJSPKJFUcHU0Y2\nOcfoG314ynA0nQGAkq7avt4o29hX1LGwbB2Fd0+/juailSVlQE7BSSyaG0CN555pdrNfG+NYd/X7\nuh/VJdC7H6NMyzmooiGV6bYLf59+3Qw41vWTMDrgNtT104Ns4XMlJBZVj6VuF71sz7a/sa5TAxZs\nIIsa6DgVl9T14E2yv4/OoLHULQejCx7dp/r9qe5HFcCx5/T7kzHYUGPULzFvVuwoOHADcplggDhh\nYLwGyu11rfptq9+uevZNgDSK5nnT/I16xo12PxvzKrxvKrBTQZwAZTvmZGc6vd0PKwtL2zbAvQcO\nnbONmkm+3Yd8qpdQEfpJhAB0xN6PgzVoLFOmFh9+6Vz5PmdjUgbo85ZKfUwD409Ru3Rqr72+/rUD\nOHt94nqdIM77vv6pfjifI8j0sb1+Hpr76//WkqDWgM455b7Jq0g8yYMFRWJ22i7kB1IsQVVHixNP\nLsGKC2daNRhUafA968aYGan5pmhjScXFPwgdE8caegJbg6cFA5mnhfNgwGrpWaQmzInvWtRjvsVl\nEXzOwiG0Wd2QSl2raLwfYuEA4a/A51IqAFBzSchC6Pd1axAJhRVLZd/oKiVooMaA6sGyS9UAnPBy\nQQUF7GZSrbmg+t/MHv9cmQJdo0kGcSAF00Z51ZgnP3WOOiI4MZXhsfKl0cqeyCiV4RGgw8KTSWjI\nzG7NR8XYORkCdkAnJFc9qGPL2YCctpWvGSICWTkVxvdaMGLEEQU3yHpElgOOOiBLwk1SZGEMTDim\nZgIcoA3QpzmFZ1QAOG1FrUxmu3XVABwDC7KG50wkPmldR5N4BLUzbu7pBMA8aGbcG0vGzaa3TCNb\nhs6LCmk9Lj5e8fpoxrfJNSGVC5YUgArahCn1KIfKbBrA1aQ35JX2mQqNbSJMfSkju/dSRm5ggdq6\nGpyzIg4uAMYYWvy4NVOML7n0x/Y3Y0f5ftTtV8bYWO9TWyB3C+D0+xIQ0epa2VKzp03F/tSDN9Xg\nHKj7CKP3KQJ69o0B5c3nZbvbB9eoB2+KNPZN0eZ9UwTuB4UNeLP2vRH3wol1I1AHBFsiWDMxbttI\nbEv99hXbC1MCa0ugqgbG3bmD6vdtEwYG5niKXyd3s/FDlZWaFXzHfnNj6niedOfFJtHSOqZNkorV\nfVtXe12rb6Z86rUu1157fTNrB3D22muvvfbaa6+99tprr7322usFykTxuyxxr+epHcDZ6xXU14uF\n81z1seLE+8+59Jnb3z3ms9P/XS2k+4OXkX3meOsHsK3e/wYAmBv1QMR1/Z7CohosHJuV7VkEAwGZ\n0GY3K7smWAbNo6B+blDktVmYPuRVJMRgNy2uM726gJ2dY7R8+x+UAR0QKR+DMgo1mVKYZCZVk0ep\nzQWvIsXVlp5JXZbV5tSCbRP67JihZSKQU/ETA6WsZVSApVsJ6KIXDmCpVNACSEI4MNXEpEQYBcis\nzvKImXit7A4GVmynS1Vn49W8W2ImPouxOyqzQyzB55R15dFRZV8wxsaII5IG08IkUqMzcEaYsTAQ\nLKFmLrz1jLhkLJyhWMQNk2kxg1wyg9xg5BRaPIJ6qUytkCWGzMq2uzUTB2jMm5jJ7b1VIjUr6YiB\njihkn5EpY9EFix6x6IhFE0ZKODBjKmEw2yKe4eskGBPx82Oz+D0LB2hmssGKyL5+LL7b1k/EdU80\nY6IJE+4BAAtNyGq3YC71Uqf+O2+rsm96Q9ouyTD8j3rWzYAjRrrBqEcAMLNpOWDUsW4TIxiDS4La\nMaH7XG3bRJjmLrBtcNFcWVpbJtF2uyq+PUUqVVRICEdWzNL2J5NThvzm8X0qjgWxLy1ClSEF2Dqa\nnHlj+9XT2De9fCoSwkI+FXHavaHvteq/dWMLNUZX3Z7iOCOK7GycS8bFBbFvSmXLBQunuC9WyNuC\nU1eTBC9sbysW5oqdh5WBcb8eyM9vQ3duCdnuUM95TeqbOqP+uPWeRhyG1KRQ90S7ljJVl/3SOfUT\nNpxbNsq7slO2TLqPXZ/C/+b1Mnj22muv56wdwNnrldTrBHHe6zM/sYzqKUbGX5cKwAZo99XImDcm\nxmwgDpFWGdWZ8XHng1MBDDQjSSaTk2R1SZVfKzW/HL9Q9xSq8N645v1TDTHd1LQlUZUqo4JmAMMZ\niGNaApeJOGiySJgpWzPMbH44BuqYf09Rk14EiAM8TI5m8tfDpVSd5AGwdK9SDLwatIkeVl44xIAW\niLDLFgiqDuSw+aCMAsysWHlBoGt2HukjemmOBmDiZrxZrKmbSgMIDNRx34su3jjpUOGQXhJjTTpb\nKlT1geFOAtJkENvl6k1To6Fc1P13IFjEEo8WWrDQjAWzgTlbA11vHvvtxzYFWYES8bv+OfAth4i9\nMV0MAKEjMi0mp6KMRQ+YdMSoA0ZNGAuvYrnXyWvxeLPNPKHpC8CsqElXej+SANbCpHihBROdsNCE\nRU1CFeCNaB/hfb4lx2j1IHVfNRKeBjMPdr+hhAGDAzYDjjjqDUYZcfC95kAjRjDGZJHvfVx5xF9f\nkv/UbUGARbXbFgYU6EXwAzDz337ssgpIYTtgfV9gVLj3TdufehC69756EMDB+XYbEqqiAd6Y1G2R\nZlrcL3/vDcMgDGAMG/lU7wHzmGFxLFsdTwdveu+bJpe67H2zXAFvIqUtzIs7WB19Kl1I7R5rlKn7\n3pHFF9AOwcCrZmjs64jP/W/6VKm1WXiTT3EH3vQGxpG2GImLts7XKVa2rE+rlzA1/lQmv6+xXi/4\n8lqXa6+9vrm1Azh7vaJ6GRDnQ+o1s3A+xfs8Vs+ZcPVQXTJkBIxpUh87MNNKwWwX/XERGxe8cTEc\nPjjNsFgxECFTAzBqQpN7SQDRgHQzrMpd43LOkgBQWRXVyBgNyCmU6zTzQAOg2Zk44YdTv1I/KmDY\nTDP7vGkiNQaNNg8cuPlNgDiRTBV/ujzezfcnEaE4IwcIVg5VFk6qJsuXQJwwNjbPnDBaHRjIDCRp\n49gakvh2D9fKY6WflZfWwC2ROOVNczRvUaSMsZs1T0iVWTEy48jmC9OMfCNBJ3yBzpkNbXmo8+NQ\nLJLOlscaYQNz5hWgM1Wj22CbAKhGyJZV5gwU6kCczoS332aEFgiNFcgpyMg4YqHJ/FzoiFE7Txft\nOWW+zT82nd9vPw80fr0vTO8XtNDiEd5zBW4CtLFxtbEQzeffEWt2Un/sYxoqwL01it762hzlBqOO\nOGLESAlHXoN3B98WEnXsMV4zK/oKr5bSMVoWAbKwg4qCLMlNtW1cAsjpx95WYxyrbGMPD6iiDQxJ\nYuupMaW0LtfKGLhbTu2OBbHttm3Wv8eFfekSeNOvf2M1GY+xgp2rxx3zZAuCoh2jtr+vbD5dJ09d\n9r65zrxRSPMkQqkeOP2WaZ8ZltINyKnbGoVptieQgWukfSRQ9ePfmzVXIAfn/jexrux5sjp/rRg4\nPfu0jhtBOxBnO7Yfk1/zEEDxGsCLpyzDU5fz68G++fTr5OtUinZ83WuvD60dwNnrlVUVdTzbO34K\nKdXHYOF8iIzqKUCLyZ8+nMljFzLr99nSzt+nwsSxNzGOe2PfrAEduITKqPrqxsRijJSNjCp5EtXA\nNktuTcc6nSpmT4HekLJLGdEGA5zJ0uDGsjR4093N+GqpTYA1FRkDDcaqgYNX24sAjQYoGDcmpVrE\nwZBOSmUoECqIExKEuLCXC28f37H/3tkv/RM1Fs5A7PIwWl2p9CCOqEWkD8QQkEWSK2GWMPPUNdNj\nswzXap101Jg4vaQipBO9dMo+g/1k2ICKRAbmHDlhZMKBm6nvoUtiivSckVG3nevMizDtDWNYj+yW\nBuicMRp6dk7InWAgRqEMoWJABhaXepzfW5z5soo+tojxDsihBRkTMo6Yg4WizkqJf3r5mBEpV7Ff\nb2Vbq3tt8pI6PrTeByJVKgCrkEkFaGPrO19von2fCylUSMe2kd+Mlu414IiDuiSqgjaMQ0oVuDsw\nY/TFHl1S1sydm/xvyxrbGjc3QCRS0shTpci3BfZtNNghnTE4GiAmWsU8ECGoSx7DgL0xC9v+1DNw\ngOv7VL/MPRMHiG1X/Ds0Gdg18GbLvgkgONV9Zg1u9BXLsN2pro1pL52qAJODTfkR8CagGe22w5BP\nFWRfnrIyvAb8PM7ry+k1iH+eQNXYN7G+tkBOk09FClWV+XbbWWLxxw3EAdp0mMkuydd1sHAur/MP\nqY8NWGyvIV4zsPKU+lDwZQdv9trrm1U7gLPXK63nZeO8ZinV51rvy7YRFKQXGheOxI1VGpU/ZgBC\nYDYPipQEqgyLEz+XUQUDh9HSkAiot34WO2aTgzlSZ5w79k2AMnFZFE0CR0Pg7BvBAkZy+dSChBEZ\nGRygjsuzLoE4ACytSNTBHpMVmMlNLOwaxImmoPRYlwLnMEQbRnKgxcbX3tJYOM74QXt9NJ4B4igI\nCKBHGMUbmwBvTJrT3vt9qmcRhDwnfEekNm5a06KsIU4VuEkgjMzewFvjHsDNYQPgjKwYyTx8KgMH\nW/bXhhWkcAlNgDjkXj2EuQCzsIE5VaZi7IbFvVJmbya3qVYBxKx8dGhA0QxSriCOqqBoBit3QM4C\nphGZTkg6VmYKhQyQ0qqJ3nqCVLaCM4LW24yBJvY+m/e88n5FcwVtxAGoLQgVFcyHup9dimGHRbD3\ncd8jDkgyYFSTRo0YcKCEY2qg3SEZOBfrPgCcgfrkNNsOKnNvw3Bp7BjqEreAXGPuDbw5MPljxehJ\nT0W5gg51W+p2ftuv/P174KYDbYItdYl18zg7ar0fAT2jxT2d3EvoHLyxT0xIK/bNEIANHnZYUT/Q\nVRCn/h6+HOF508AbA0ThoE1j4mQNEKcBTsH4aqlTamw0977RAHGwbFhtHRC6kSzbtt1i7NmZRz1w\nEwBNz8CpnlJ0Lp+KY21jhVriVGLx9+kZODH2WsGbnsnYJ1r1EfL0gcfcd61P7U/zkvVaQaKn1+e+\n/K+zFK9vZHdC0OdbO4Cz1yuu1wPivCQA9Nh7vxcD6BP44LwrY0dIkN7j7EFXTjlbWRVxUMutuSE3\nciENw8wG2hhgIxVE6CnulXkDu7AeyFgXs7SLXUJj4ESUeNDoL4F4sU6rQS01GZUQG8uAANAI6OKC\nrWSQmceRC7VGQlQBDPbZYnQbVq6SBwKqH07TIxiIw2Qj2o/rQ+BNXHavZvSjEVGbaVbVMxaOOlxl\nPwiECKJi5prdDPVTG8u2TOfP6/8eJsKi6nPr56+PBis5Q2BgqqyLY/IbA4cE3CTC4NuagTrA6KbL\nFt28NtsmaAOzahPfWANL13ROYoDOLBHVHJHajEWSATo6YhFbsQsC2MnuX9MYOiY/OkFgzJpCA7Kw\nt9kLWH0WW8UZXBnMi8GrLjPqmSsxZL1JcgArquLsmNx8nXzbDBYMESPRAKZxBbJcMk1vMc2yAp0u\nA0O8es/eeDgi0yMCPmHEQQ5IGNbmw7RmWh0SOXCHCt4cEzCQ4uiHuNEll3ZMUAfvmuFs7E8KuhDL\nbet26tZ7gDdDMVneXBRDJ1NKSpUBE9uzbVPtdwxCcUDnof2nb9L7510CHeO9zdTYgQuoeUdtQBCB\nHcvCVH0VG96xb2jjGXWJeSPquPOVc4TCTMoVTd619b1pfldyBt7EMmcU97zRZljs/Jtg38RvbCzW\nbLbVuKK3LF7LDnsD4x7ISd39NflUO9aaeXE1Pj6TT3WsU7GzhpJ2XjixnOtBfQlGzvvWNpr9vd/n\nHQGi55RPvWu9LvbNa4MY9tprr0u1Azh7vfL6vEGcl5ZSvQvL58FUq+5vn9r356GiLUhDuvr2K/lU\nf8FaL1Cd4eEsnDAzjgvmYN4kaiycAG9SXHT7hXWAPQCQmMAS79GSqIJlwHqeSBWATbAjStcsK4p5\n3TiIw9r2BAGQKdvsdgxHMHIcl2GlmhjDICz+3e2PqCCOAkjeYPKFqdeQT2wrvCrso1uqDZGlXcVW\nuWXh2Iw2DIhSQkEDUGrTeaVhk2t/WC3X00CfqDozDphkirj62gTrxgAc4MiEY1LcJMXBV+WRFQdn\n4AR4k7pmPmbHJRK7AOgKwDH2zVLvDRiciwE7U2lgzlzgbBzG7HSp5p0zrsCchW7MO8Z9bRgjMiYQ\nJ2SdKhsH4j4falatIsaqE1pWjJa+mnFygUhG0WzgjcwQyRCdITIhGgGiAUQjmA5gHpD4UIGWnjmz\n+oxOGhXL19ZZk2RVIIgGDHxEgqVrhTRqVEsTO+hl0OYxlpX97OuYbX0HeLdmXkkDe2Nb3Kz3WN91\nnQvhILa+ByGMYqybRIrBfaVSARay34XhMeAARUinNPYtdYbZ5W1e9fL+09g55yyd9j7NqyjeN6RG\nwbpROgfXgADwmgdMfyS8BByINkDDvu55klfcr02KAwg1MKeaFcs58yakXsG6CfZYdt+bXsJ35oET\ngGUHMl6auAgPnPi+7TgTLKTGvonH1+RTIaEK8+KQDsfxpQdvqoTKGafbc2Zv9t9+Jl9X19fLpXqI\nafL5s1Der971e+/gzV577fU+tQM4e30G9c0AcZ77cx+rd5FAVcbIhe/Sx+9e/SwtSMTOulk/7338\ncAJs6avHH2IWcuWBA9gFLWtl4XAH1GxlVGtfgp6V02ZRayMClwN0PgekIRfhyoZax7F3zJsLLByC\nVO8Hixy3ePGejRPeI6pDBW5YCUtcigvbhboADeVpII4ZEZtHRruM9+Xrh+0B7KTOoGuAMcYEuMTC\nAYIpIHWeVXogavX5Up/f39vjSx4r60aUNr9vz/e/X2DdWENPlYFxk+A3woHVHntDD1hDf0yKA4uD\nOLICAGMWvX2nkHxYAtcibA29N/XGtCFMyYCbKaECOFOxx8HQAZydU5oB7iwJiw6YdDCmDh0wYUDC\ngKXzsslgE2ExDMTpG2RIM4wlZ/M9EFOO+tQwcB1Wh+v4fXjSXKrtrPuWcbMyIY71yoODNwbaDNQA\nnFHjZkbMPXBz9BSxMCE+JupAmwButK7vAG1iXQ++zzUAJ4A7OVvfsc6zmPW5xXETFmFMQjj4Oh8F\nmISQSqSwEZKo3xugRwIXzqH1Wb7T9j45vSF0QBNAgC7nx1resGVinV1eT22f7N9vC960ddX7vqxl\nRFt51/pzFEXbMemyfEo7EOccvOkNlgO8aSbLxrrJDoNt/ZdqGqCWlgSn7oGj3TF7M57GNEtgSpWF\nFFB++P5sDeEJTXLXDI3X8qkqe4rzFZt8qjFwGnizMjFmOy73Zv2r9fNCzJttIt5rqQ8BlV6DyfLL\n1tf9+3360isTYnvt9T61Azh7fSZVDTye5d1eo5zqQ1g4wPlF93PIqK7Jop5bonXJ6Ph9znPUXcA2\n9k33Tp2EilkhspZRhXcJdxfQwcIhNNp73CKJiaQBOpUq35lY9iAO0LEYupSgMDMuWGpjljBWKUGB\nVCCnICPpAI0x67CZysSBs29EAGaPEo9pbYKSz6x7w2C/XV/RhwmwAlUG8lCFjKpcWXuXwBi4lGH9\nPKmyhtoMeKMVf9+Cj1yTkrgBaJ2EwYbJPTmoubv04E3f0N+kJpn6IjXw5siKm2TLcWDxxl5w4NIA\nHO4a+g3QqEooYiylRRhF7D6rgzfCFci5L2Tsmw7MMVaOveecCHOh6qEyCmMRwSiMSRNmZSRNmGkw\nRgAlZ9VYg5mFQZxAbgz8kBmw/a7fhq05GyBn2/G2th41sS62x5BgNCjEccZ1ulTP1onY7wBvauS3\nuhkx1mbEIyU3IQ55lN2HNM7WuQE3to7b4wMLRlYc/R4ARhYMLBhI1rKXbn2re7SoNuAmbgdfzycB\nUqHKzEjFm3o0f6otC8W2dzilCxDf8QO82cqDtkDF6n0CELuw//TPOTONpQbmrN+vAalNQvQwOw5w\nyRSAOET1DKbV53bHpCJbw+Jz8CZMlnvwJryjeuAmQBtj4izVGDxGtHrghN+TGxn3+0tUP449eLX1\nv6nSKWrm580E24DDSEe0z0Db1tBJqhzQsec0ydTWvDje432Bm4hYt8ftuPzwa+TBn59aL5lg9Vzg\nzOfLvtnBm732+txqB3D2erZ6ChPjw+v52DgfE8R5rSyc11hPkcr0tW2Q43fVA6fZrjjA07NwtMqo\novEeVFB8ZnQgxYIWJ149cKhdgAPdBXmVCHRJVF1kcV+RRKW0MTN2Zg35bLAZF8f2U9oFNBUMOvqY\nlYsgDgOAJKAHPLh2SHV3Mo+gYB9hs5xoUdgPrBqKz4WNQS+jWrNnLjNpArCJ30eM77a5kguz/azB\n/oh0Ia73DELSAdH6RyP5FPDmiwTcdODNl0lwkwy0AYCbVAzESQWHJNbUp+Lbkpz7UgBQITOcFbab\nEpZiYMoijKkkzMKYhHGTGFMhnISNhSOEE2tl4EyFMLPi5L4pY1HMxUxikxAGISRtEj6CyfLIxysk\nVazDqvnYpjcljI1FhnVjv12P12q7/YdUsH99mCAXrGUq9TW+TABchmXpUZV1A2PdHPWIEQOONJhE\nqouA367jHri5SQ7edMyqG7b12oN0ADAkqQlAl9a1Oq2pCNX1XISRC2OShLkwBknOumFwWbnRAFCX\nNTpYt90zxcDX6n2zkTcttNQ47Nwb8tYGvIA7s93YfyyRbViBz5fW33a984XtwtZZ960C3O6+i/rB\nR9W+D2k7RF2C8eN4FEbgfcT5Q+DNgnwWEX7p2BKPw2Q+gJq1cfH65/g6AdnEuEaEeDCPtv43jXHT\nwJk4lwzdc4KBE+bFwbRJLGfMGxtuA3GYFErBONTVufKlriSez8Pm+jHlfUGg516OT/m+nxt48/Vn\nMO311PrP//k/4//+3/8LAPgtv+W34Pf8nt/ziZfo86wdwNnr2evlgYbXAeK882c9AcR56eV5bh+c\nazIsVQcUur9dixNPHxBV3s8kUvW+6X+3vlfBSkKVkjrzhdDT0VsKlV9Mc4sTj8+Ii2+guyDHeRLV\niolzIU68p+QLsrEjUFAUSDQi2q14jwqUgiuYkzDaTDzJCsThmMGWtKLPizeGwgT3PEbqgJxttSSa\n8MO4Xj2QU9cTaHVZv5Ve9D4UMSvuLhXVi0KCnXGBlk9ISGQpQ5EwJCQYdICZO0ttqmJ5uHpREEai\n5n3TMW+OfA7e3CTBF87AMQCn4JAKDoPdD4M19syKlOQqgKNKKIUgwsiZsZSELIw5p9rgz5IwMePo\nDJuTMI5MOBVbSSMpJrFI61NRjORR1sJIxWf9xWR1/TppIIgno1Hz+NhGbW/HtjX06cHm/iF5Zm8I\nu22gLT2rWDJWwBHdOmca6/szRozOvBlxcPDm0CLA2SLAt8bEW08jk8XB163ihsWBOcFNyhWcO6SC\nITnz6B3Xcy4JOTMyJwwiGDkhZUWiBC7qrBs3Kfc1AQQLRZ0BZ+u9+sAAFh/uYG2xZyJ3yUr2b6qs\nkirT9HXQJ41ZZHxC0cHZWjVA3vyqLsTIxzYQ54KtgbE9hy4eV+pYhVRU28/XDZUbgKMaXjdPA28W\nLNXn5hJwAx+/ogvCZchSqBqzrJp0+zF7e0znbp+IBKoArqrMtjt/2LniXELVy6dWiX/USasCdO/8\n3uJ5scPHBEW/lOv0KV/u92TlPKUeA3Weu7m/dI64xo75VOybD/qszwi82YGbVh05+htb//2//3f8\nwT/4B/HmzRsAwI/8yI/gV3/1Vz/xUn2etQM4e71IvTwb59ODOC/lh/NUkOUp7/2Y1OldfHCeWv17\nvi9AIxWFeL8KQ13gHMSBXGDh0DUZ1TpOnOsMqUeL+zIOpEhMSKzgsk6iqk4rVUJi49HMYJ11oBlE\nZi7LzpQoitpMl7p+W+MV72GJKQbizB0Txxr3IQYVgMWYjy7LUCiUPAJcmgTsUiJMD+KotiDj99V0\nbxk3l0xEBaVKGQpybaxW69oBhwIDboLRFGNgXkQEaPgQedBvADgO3FjaUPNB6T1QbpJ4s2/gzRfJ\n/DCOqeA4NABnHLM19oOAk4KTMcAuyahUACkEKYSSDcTJJeGwJByFMS0DJhGT/RSX/xTFqTCSd2sD\nE4Zi3ikW0ewm3aXJ4Yjgnf2hMaR8Z8i0rJgwMZ7buO2kAwYdnNXkDCZnNQVQCZz7EF2qXkbXm+AW\nsn1ASGA8ibYNqKcB2bI3JtCg40XJ1IESjpxwSNdlcTe+foN5c8MNnLtxts1NrFtfv8NgAB0AW8es\n4CTg4fF1PBYxoC4L0pLqsYaLor8UC5+keGzZaX4fv2dA1Na3Epl/10ZuFAyTAG+yTsiYKsOprwDp\nRJf6OGEEq7GvBA3os/XbZFePndOupcSFeTqhgb7GFTw/u688cBy8EQBFIn3qYfBmoWUVDx5MpB60\nsc8J9k1pxxtPWBOXGRbNFXjfjmEc41kDuO/zqBpgU32OqE06pPq3YHw2+VSYGDO0sr5WLFMy8/7V\nGDuwBzQJlX1+x8KpzKFPU6/d6Pg1sm928Gavz7n+wl/4CxW82evDagdw9nrRelkg5/l8cT4miPO5\nVfjgPGRkvH3u+e9ebowuxYe3x5vGyq9YSbWLEwdSEhRP7EisNVFqa2ScnOFAaPR2IKRT1jRbIlVL\nogqmwrWIdYtKziBNlZpfsBirxlVOUGuh+kZbKYE6MCcAi0rpX8mpGogzgABmBMYhRBCK72ttf9FN\nAxWfGQycTk4VjeWVkJtH66EEmKILCqz5tJjqpTZPK2NbGpGwQOmmsr+ifeqZX70nRSJbVwbioII4\nIxNGZ2REApHJagRHFtykgqOzMI5Dwc2QcTxkjGNBGgTDWJBGBQ0KTgANl9gEaundGdBCkCIoC6Hk\ngmVOWHIyxkdJOOUBIwvGMtSmLpXeywdurG3gYax46hhw6n4pomObAiQg6YjB2UohqYmmPUCb0R+P\nLqxJFJ/dxrExzxzAuYLfNOaIJQRFNHXEUi9aULTzKdHWdNvrClg7AAeDLZuOOMCWcQve3HSG1CGX\n6mVxPevmJpV2c/DmOOYKzA2jII2+zyUFjw7QXVvH2Vh/shDKIuDESC69onktaREdIEpmSKzWZhf3\n0BE1Jk7474hLpooSCjVGGaExrTRYbCQVvMl6qqlh/bmZwBAaUVyWplogKEgOCodx+tlxnC6DOE8C\n8rQdQ5vheYPte8bN9uciBiBnMe8bk1BdB28Wms9BQTRQsMqh/PhakF3OGn43PQNnLakKk2573LbN\n3v+nNzAOz5s4h6Q4z1S/tXP5VJ8cFeyb1EmnUtIzAJGdUclka+eS1Pi5aguEXaq+mb9mbvw+8qvX\nABK8CxC1gzd7fVPrH/2jf4R/+S//JX737/7d+Na3voXf+I3f+NSL9FnXDuDs9VHqZYGO52HjvC/Y\n9BJ+OC/Jwnnf9z5/7vsZGVeT0rP30zo7/5TaNkzczUISN+8b+9kfuPcLdSycMDPu06hS0M47OVXE\niW9jX4HO/6aTT4URqEUdp+ozETfoOQvH0qjcBweWBqSwdVK2zJPuAsmkVnIRvKnbQwVxfJ6bGRI+\nGg5iiIYR6zZLJ9g3a1PjGNJYo8HUeax6g+JeNtW8J8oKvAkAR3SxqOqO5UVkUjKl4ijaDViLyYLc\nGHotH2rrJ2bCG3jjN4rHzcS23czvBsAKvBnGguEgSEcBjzDw5uAg4hBIH1qDLd7gZ4UsipSBMquB\nQLN56QzL4MBhcpleWgGHXFyqQf2btw/R5IwOsDFeJFUet7GWMjINEG1AYDBtkqYKiozENWY92D+j\ng199c8pd47mtBviFBEbdw8Qa8KyKLMMq7nlBRlYDc2Rz3DAAJxnQBL4I3hwvgjeWLPZlkgrg3CTB\nlx1wczNkHIeMw1jO160f8nh04GawjYo2X7qtXxiYNyp4BmjqnjQbU8cAGYGCPH3JwJmRFIWpJi15\nejyyrlkciex1PRuqjjsMiIgkpSIBhua6zpnNA4ljfCuKYo8HHVdnWfHXCaSCOI9VyKSMvWfHF+2M\nikmNDRjMMccc/bW62n6yGHAc8qnyCHizYLZjCS0VuOmjwe07XfFhctbf+u/nIHJvzh0R4m2NNAPj\nrf9Nz8q5Jp+Kc11idUCoZ9+gW4ZurLufLxn6byc+XmttgYDH/G+eSz71VABiB2/WtQM31+ubnEL1\nv/7X/8JP/dRPgYjwsz/7s/jxH//xT71In33tAM5eH62+zmycd/1uz2Fq/Fx13cfmHYGpd3y+yase\ne88nv93F6k2MAQdyREFMHQtn7X0T0oYAcXoWDlHzwYkLbsAvyOtznMnSJVGFKWzIqvpRUDVAw7wX\nMshntC0Bxc1kN+MgfbMFm7kM+RD8/aqEKNg5wArEURWMbGlUYZFCoApaRV8Q3zGAG6A1UMDT1tE1\n4+Lt70wK1jwoKmijC4pMxh6QxdkFMfaMgU3/VTQhIfxTxrPP8UDfM/ZNotYQD6QY2PxlDMhRv5lZ\ncXihAG5km4x1M94I0kHAB2/uDwAlMvBmoNV2qAKQx3ppVvBizT4fBDw5uyOxzaxzSzjimI3P61O3\ngP3CkCpbo4IAamavytwxqNTi5skMnvvxCbbNSAkj2KPVuXoEjb5BJAoQx/yTevndpW0H6MEbONsk\nGBTmYWI+JlzZFEVTjYGOZKXt+kxI62Xl5ml0YE+Z2oA3N25UvAVvvhwyjmPGzZBxOGSMo2A8ZgxH\nB2COAB98uxsISH7Pl9evZgUKQLNCZ1tT25QqdXPjwgVZbLmzOhPMx2rpgBrAJJuZCAMrslBr8s+O\nE840cbBitR+FJAgA61j3oRpV7oBhpDIFiGPj3kCcSxXGyuJQTQpQxrc/cmYJaQMdmey7kh9QYv+O\nbaZn/J0Df7qKCt+CNwtN1UdL3NPG3mt9LIrmP8DwKqGSvPbAQXvcs/0MTE0b8+IGbibuHpPW404D\ncUKui5V8KmRP3IE79XEH5FT2qfRMvM0+Q/rB4M1LS5++jiDADt7s9U2uv/gX/yK++uor/Pk//+fx\nh//wH/7Ui/O1qB3A2euj1+cA5HwMSdVjIM6nYuG8RIWMxWQam2XbMCQ+tLbeNwCA1YWtsyKChROg\nSyejIr9oHliRHeRJZElUDdAhBE/FAAFFEqzkJO2yPlUQx5ZxC+JsopiprMgUW/YNsP5dNFrssqsK\n3ihjqQ7O/mRv2AUMCBsDh7EyMxZtscVl2xSqNVFrOUxjUMVNcc6o2v7cp0r17JtoOgXWREnPHpBs\nkrNuxjvGlHVYsXmkGyNbLy41CaYU9eCN3SJlLNUmy/woIiJ8SNIZ2RaMB5NO8ejgzRHgA4FGAh0I\nGNi2xc5ciJyqpAJQFmhW6GyyK9sexeV/Z6vd1wF1j+NmkF5JDbw5st0PbLKbQc00GRiwqMn8Yp0E\nGJKIV8DNITUwxEAc+9xgK4WssMUft4a0rfe2rEWNFZQFyC4DsgQhWkVBzzUSXR3AGUxe1G1DxqKy\nvSuWNzyNDimkcW1Zj2yeRkdPmWqeN8a86cGbw7FgPBakoyAd1+vVVr6BczTQ2YqizbplArSisJZ0\npwqkIrY9ScEohJHF4+TXks3+Btg+mpxslxigKte8LFsKcHi1H2lu5wE2UBYAiBkS6XdUIGrsKyFB\negLT5lLFsYDg24dvA6U7yMU23ROZtqAN0I43xaVTRU16t6j5KV0Db4LRtzXFPotH92NwYwQa+yYA\nr950vrIpvXqQvgdxwsDY1k8w1hoo28fQ82pfanIpe//GyKHtPXcyKgYg5OzSGNf3O8kqnu/k/DHT\nox6rj82+eZ96XkDk5ZZ1B26eVooPn5R87voYy/NzP/dz+Gf/7J/he7/3e/G3/tbfevkP/IbUDuDs\n9cnq5YGcby6I867Vs3Auve9DPjh9msn7f/71s0gPFjy1ViBOvfi1JopAaxbORkYVjX1Q2Ldx4tz5\n4PQSKuvRm5Fxdb7RiLOOVJLLbCcDbqzRgimcGoizee7Z9/U573qB7CDO4lKtlSQCAHRoTTXIDC8d\n2HjIzBjoDY0bA0d9Jjy8cES1e39d3cfj/mI+cqeEutltb55CsiBi8qkiM4K5ZOt1ACmjaAZrxlN8\nFJqkYZ0KE6aiAdxsb6NHSkdDNbiRbRrVZFPjGryhA1uHPXCT2HhGsooxvAw1UoAF8FQjk+RsGksx\ntoaBIM5ocMlNUcXRwZBMQCEDLIoCowCF7TWjs3CiEhiqAUJyjVY/OJPl4Oa/BuKYwXMwcEaGA1ta\nga8Yv9jC/av6Oo7tJvxb4GCNgzeqWIQwF2AWYBTCXAgL2+/tNQzx5TUhTvPhCZbQ6HK4RAHckDOo\ngIFtXw453EiKAxePgbfbOBaMo3sZ9eDNsVunCAbOZt3WdaWg7DsSNzEQiRp4UczgOjmDK2Vr0g0E\n3m53VCWbPeOvsZ2oMjRoe7CAG/OG14snKIlmiMx+PLfLQGJ2yZAl4QWASoh9MtV9M86udQslVHDH\nAPl2jAt/G1Jj5cRoENnQFFjkdRyzt4BxHGtiuw3WTak3MfkUMuYwLKZcwZtFTwgTdPP2kQePEX18\nfQ/WrOWu633TgJwAb1J3rA+PqI6dyahAVqxHQvjehFx3LZ+KsTGAXRorjy+AN7DnB4cy5FYfku79\nFGmzXPG1uVYrFhNwcZ08Bgxs//4u8qkPrZeWTu2sm72+DvW///f/xk/+5E8CAH7mZ34G3/M93/OJ\nl+jrUzuAs9cnr5cDcj6cjfO5mhs/l0Trfb9H+Lf0rxUt1QC1X85ttHg1q7xwzah63qA8pXovAGUF\nxCUPpZdQtYvlxAIS7lKo1n4FvQ8O0DVU6GVI5LOwmyQqCkkVO+BhEcTVWwEFQmweN8GmqePVmRh3\nF071/SHI8byOibMFcQSKMZg4SlBiT6OC+VB4c9Ub00ZFM7X1p4hGK9g39W8+/26vlRod3t7v/ALQ\nZsE3DRTEWQNrBg4DUB1WEocLfSyoWxP2Ouo8i2K9GRhR/Yw6MIe77SS5B06kEPWGxUhYgTd0SL7B\n+LbvqAYBRnsYjP5AbH2vgak2wEnETHCFMI4Z6uBNFvv84jK4UQmLGJiyKJCUHAgg/13IcdQAGHHw\nVdUkIG5EbBIpxki0it0OD5nwBAIszWn08QoQZyU37DbcSFYSNGPerCYVykKYnHkzi4MthTweHZiK\nSaIW1cq6iO0w1mMviYvHAeIkck+juIUkjhRHjwcfIiJ8EPO8ORQMR12DNzcMOjBo9PU4MGjgNbIS\n25p7bWkmEIobTQFUFJQB8oQyTgpmNzV21l807u0Yow4EtI+pfkOdbqonAV2WxDbz3WCxqYrvP2yg\nDkZw7HvUfGIkvLwemmzoJk0C+on0vqiehQNB9bxpcMN2mdfeW7bNh3TK3X024M1CMwpyBW8y3D/L\nWTSXjjd9amKMlTgYXDTXsbO/CSogR0M9ltd/XQLVgOYRFSlTcS4ZulvsL/3+E/KpRFLZM7adtPtr\nXjiqqCmL/cHwqSycD/XpCJbT+zBuHgIEnovB86Hsmx282YGbvZ5Wf/kv/2X85m/+Jv74H//j+DN/\n5s986sX5WtUO4Oz1aurlQI8PY+O8tLnxx2LhvISM6pKRcZ9Epe859pdonbJBMx6jflYWToAsDMQ1\nBzGgFbxpMipiA2+KEhLZ+PRx4qkCOk2GA1gPnqQ1/pHMMzhokDB2IEuqs7Xr7+zwBzXAAvDtgxo7\nqr/vX0u03Y5OD4I4cS/EDrSwbYlKDchxmUO8aw/aRAXzJpKFgn0TYA42j+sy47J8SroL//4+gBxr\nPBfE6Fvb6zPmV9JQaCP96BvhWPd9Dx6gTg/YNVCnzXaHWTZRexHVjsxBm2jyU8fUSMbSAJOBN93q\nIQEgAjoYWyMVhRTBUAi5KIZigANgAI+ZCwd4EzK/Bl5Q93hkixY2VQXX7YEIGKh53ATr5sjAMRGO\n7htz8NhtwMCQIwcDp92GDWMgthsz64UzhshZNwbaHIQwO5Azii+LKGax7zKL7V8LdeyjbhvsI+HX\nkiP3jmGslq8trwE4YxKMqWBIJoczRpU2RtXB5VIjVyCuAnPJf/Z1a+s1GDH+8wAgF2P9xTbDTf5S\nvbcq+2INgLFvHfE76o6Fsak9tQKAsP1pMTaMcgVBewDUEt3aZWKNEVffiDclfrw3m/TgBLblhhrg\nVqA+OMYeKvU79cup1SC9Z/wF6yY7eFNQHgVvTEIVyVJr4Bs4l6hW4Mq9b3rj/UsGxoCzcCrvkpGQ\n0BsYx6bSM/2CfROSqTi+VC+ckFLVc5mes282/jcq9nnnRsbPr5UI1uRDtWXWXEugetd6bqDlJerr\nCN7swM37V+Nivr56+/YtvvWtb139+/swZ/7pP/2n+MVf/EV8+eWX+Ht/7+99yOLtdaF2AGevV1Vf\nNzbOxwBx3vc9t/WuMqqnLqeZFbeLfSEBaUHC1oi1MTeerWoqFdq9GAuHBGcyqmZiHLOkgky8mhmt\nHgUwU0oANbGqRsTWm7NwLiRR+QIimimswBtj4WzNi2P/qIlTXZHP/loik3h/vlwFcRRiAI4mb7XC\n+4YqkGOsALrIvu8lVD14E/P2PfumJk516VPtfS5f0jSj0cbEcQ4HoLnCSkrjaiwq6NM1Ck/1Wdr2\nwedZXBdew/1tTZGg5l7aHtfXkUmpus9WMR8cDHSRrZGcrRESrp4dVGV8aF4+vcdPAIvJwaZ+2+oB\nkGMkNg1r898DG4hTGTgsKzZLeAT13h19mfypB3AYiwM5kxBGIQx+n0gxCIFLpO60xLBFYrvb+Pc4\ntpKYuu+Lldwx9t1hxXDwMUwWxxxjXROm3KjYzKiddRPr+NJ6hQPFrSN3dhUBpA3o27AmgHMgxiSc\nl9GZABmfWtXMuILAC2J/qiBFF6sdQM5WRhVlfmZrGZVtGlxlVGFizKoQ3z6zCgbj+awammpT1h1X\n4uc4tsCW1gEcA28yyoPgTdbJTdHbsdUWN63A8TpOnRdZSKl6E+O+BWvm9HHrJVRrA2NyKdXW/ybO\nN6m738qnUgCiWw8cXoM3gD3W6uVG9XWP1ZZ1EyD81ec/ctzu62M0/U8Fhj4W++bTgTc762avd68/\n+2f/7IN/18dmTDf1f/7P/8Ff+St/BQDw1//6X8f3f//3v/ey7XW5dgBnr1dZLwvkfL1AnHcZq/dh\n4Vz93M3yXkuzulZPoUNfekbIMd63KvuGrZ+6JqOqj9HixMMTp/fBATovCpeUhKzDWDjJL+tHMPkN\nDchp58XGvAkgRwIPqM1M34BtZpOVoR2zh5RrogyRmWr2II7qYA2aqgE4miDEZnTrQE4P4pyvmzWA\nY+/TwJvcYJsz8KaPDrf36sCWJ2wXCq0x6g95U6xf04E8V7af7a8tgvuRZZH1fa2tgdAFqY0tDK2a\n/dBXUD5na/Qgo73lmrER22mAHv1bJiIUZ6PAZ+mBBn4kOpdMteQmS236Ipl/DIAar159gcg8XAYS\nZ6dtARzy5ClCUTYARwiTMEZhl0oxTnX/ie9l2+DcMRmASEKzCtmiY1Pt8XZo42+rJrlL9gkvEW+M\nEaDcJbCmB+i26/WJB6jtNfHZz1cgxBAlypWPEt+/GrPtnLFnDxyYeSKDJ/bTh47zwcIhvw8WjilX\njXGTVRB+OPHRZcvQ2xxXcmXgBHAjKJQdwHkYvAk5VH98CPBGtTFG7ffn0s3+2NLew4+z1EmoPIEq\naapyzd4HJxg3ASiuUqioZ+Jo3Yf6/T3OTT37JmrFsGFAyxNXKtbn2Yf6tEtMyhjL96l38b95V/nU\nuy7TDt5crx242etd66/8lb+C3/iN38Af+AN/AH/tr/21T704X8vaAZy9XnW9DJDzYWycTwnivOtn\nPCWRqq/HWDjvW8be4bNZXPvM9UVhld0EaKGtUfugy4hOz2GeM1ZrGZWzcSoTp8WJE9yzgGF+s13f\nVi/E4WyBJxgZMw0omL2J6Oj5HQunjkmwZvTCLLmX+kw5KQexB2BA4ECOgzdMacXIEVKIJgzQysZJ\nVVZFVfJwyQvH1k8ANyF32II3vYzqwuxsgDgbA2P7vtcv7IO7Qji/wDTpR2MdbJe5Lo+apMiMl2N5\nYvZ5sw36c8SjnwGTK6j0IE4zyT6f0vafL4E4XYXvtD0XF9kavTywgjZ0ztiInxlhzmxNNNginAN4\nNKVXA29uUgfesDqAY5HbwcC5SQXHZHKuZu4sXaJON9YRlx2R2eIMHGGMkjAVRSLGIAAVF5507AEu\nHpVdULfDRFrlVPZdO/bNZphj16/ADc5lcf34V0lcXQf9m1G82fnK2673YAvFxtRtXHUb8m2qvynW\nQLXAt9O6bs/BDvv7uyDbxo/bfostm60eNjsPMyHzOIvpkC0LxwhI4XtEMAfdBKhAiDDEUF04rthn\nXT6m2DeXCt4sWJApY8FkP18BbyTiwLtjwQqE6hahSjWxNjK+dPYJ4KYxcRhDCGfDj6mCMw2sGbpt\n9Ix1g5D6GdMuAEYAK7Pinn3zXPKoD32Xh8yh+7G/BoQ8FSh4innxh7z/h9TXBbzZQZvnL71wWfBa\n6ud+7ufwJ/7En3iW9/qlX/ol/MIv/AKYGT/7sz+LYdihhpeofVT3+izq5YCc9wdL3nV5ngPEeQkp\n1Tv56GA9W2mvd0r6FVDoobJo2gu/v/TZZ/0w1Yb6oaJrWoNORhXXneFH0TNyYhZ0cI+RuMAmUEuh\nQvM4sHhfM1JlaUbG5oOTHLwZQTQbiHOhOQggB2rj2rNugAbeXPLCYR4gsoCZrZGBHegFjFwZODcO\n3ggOvbzK31t8BjkRo6h6k7Ye575ZfAi8EQgKNV+bnn3T/25bT0mTslobO/fgTVu+S348zVhX/PtE\n/93Amib5CRBC/TEAS+9SghaCFnszzS6DiqSpbGhfZy3S6lqz3w9s/W7948dn13vMoRpsu3wD3bYb\n3jhDx7w5cANvvvS47ZskDuLYeFtyk5n/jmzR6onN4LlvOmN5VQmlGHhThJGFMefkZsuMQRLui7oM\nxQCAtuO2jTS+1yIEUlRqN/UsB2qsnO2uH6yqLShX/75VynRIXk0OAwDW83Xq6zzeWEWNKuQbmopC\nMyAFkAxIYYhw264ccqvHNtj2F2a+PaAo/t17oAN+r7F/UfOG6hkl71oBwF+qS1Kq5PIpJoFU/ykD\ncViB3K2XLTW/DXuTYRaU+v0yCgoZB2cL3giWi+BN0Xx2rBQCoOes0QbeXGbeVFib2i2ReZwNOp4Z\nGLNDqs0fbe1/E/HhAwUzZy2Tsn2hMe4uMW/603d8zXfxRXqoLm0tj/nefGhdksS+0+s/Efvm04A3\nz78udvDmm1ff+Z3f+WwJUREV/kf/6B9FKQW/9mu/dvaceZ4BAG/evKl//77v+z78jt/xO55lGb4J\ntQM4e31W9fxAzsdl47w0iPPk938iC+fa+z72OYriXJuemn7Ovll/7vkl0qVEqmugzWNATi1XEgV+\nR+qzmA/EiVdfj/q75lkANLlKtJwDA1xMlhJGxgS70E86ri7+aYMwxdhWM9EzWYU82IyJZDAPNY4c\nDBRvOAy0YSwdiDMTMEAgxsFB0gECRUKCePSveNrNNlGmLXMVGqzAm0JrOAfACrwJ42J7PzMwfgy4\nWcvOunHZXPSrG2yKtk8r6hlPanHFCjNILUIQDrBG/b6BN+HZEo9ztvU1JIIUu3G25pwGA3EwGHij\naDIcBSMi7LXG6giQZdPsG1sjsD2t4NEGbOgACHGGRmWrbcYoksW20j/zvkHzvqmeN868cfDmy1Rw\n4zcAFrs9lJreNKRiHjK8TsaJdaVq41QKoxRGzuYtlYpiIAafrfaIDHewrD5uX4wFKD3j6BIpBu0o\nb8DX5SnQxsZqrKwAXUjU1pP7FtUB5o5dE1V8HWZfr0WhOW4G3mgmB29sPBYJYItW21yJpC7fXiNi\nu3Q/VyBHA4g895naVuyL1/x1bNw8oaqb6Kj7sL3Ykuq6v7WzaTxmgDKgcalZ7Oyizg2jc4niQ8cS\nIACcDBdPrcCbrJMbFq/BG5FldaxcSX8JKz+oZpjeewOtl3KbJkgUAP1lA+PE5ABN879ZmX6jk/Ft\n5FM9++7MvHhrkoYmEY5iVpQLh9Q4jlzaG7ZMroe8cNprngJwXIr5fsf48Wdm3zwGVryUbGpn3ez1\nda2c7Vj9K7/yK/iVX/mVB5/767/+6/jhH/5hAMBP/uRP4md+5mdeevG+NrUDOHs9W50lv7wnKPKk\nz3pFQM77gDjAhy37u4I4H+Kv8zBQc0mi1acmeZx1f8GMAq5yquulPuteG1J8OP20T6Ja/b5j3NjP\nax8ci3LlMx+cuLBO9YLczSPRkqiITEI11MjZBKYRiQaU6oMTc9jWLIXBsC3MZlz0fHY4fk9k6JRI\nrkNOyhBkFE0AoTKoehCnfo4CQoqkkSJGteGKn6O2cqQt6+aS5409dw3e9H97/2rvHXP29nPplihg\nHTNFVVVrmDmYDu3WGuZoohuIMxTGwDa4uSQMWcCLghMZ84adJcLRJDt/ZGBv+qk1WA7W6MVm3zry\nYGuoUGVrFI8Bz8pnkhtxJselqswUtGhqY+B0MeHJ/G1uuMmmgnlzkwpuBmfgDBmHoWAcM4ZBkAZp\n0dhOq4tDhzoIFayTkhkpsRkHL4LECeE3FZcltu2ZyKaCKugArGYMtTp698yjM+AXa1ZVUfYbQR1M\nGUSgmaDjBpBjBZGYGTFgoE4kjK0+pFufi0Bnvy0KnQFZgLIQSjYQKxdGEa6SskUIS10+bO7tC/Xg\njUVqawdQ6mr/amySgj4Ou20TT2VfngPwaylVqiBOpoxBh4sgDjs0JNB6XFm954VjSc/g24I3BQsE\nS9gZG2BzAbxZfe8NjifdYlTwpgI5a4Zk9RjrjuW9gbF5npmHWETbBzNsZagN1ImB3sA4zI17b6YA\nas7kU9Q8suryi/3+cjD7Zqx7Vt9mUAIUfKiuS6FKPdpefe0F9uhz1EU253u+9+sFb3bg5nMsxbXp\ng09XL7E8v/f3/t5Hn/Mf/sN/wDzP+K7v+i78nt/zewAAv/N3/s4XWJqvb+0Azl4vVm2W73MDct4P\nxIl6eqz3u4MjT339U0Ccd2XhtPc5l1E95XUAVj4K/WtW+vgqi7h8ARoXpoomaanvJeuf+1p9bPWI\nMRkV0EWJX/DBieaS0NJ92B8Da9PUPkXaGDg+L6uMASNS9UgwKZUgN8YN+EG202OziPXvhNq0FbXZ\nkBalfTLgBgbiCI31LC4kGNzcONg4jNYMyIV122blHwZvtpIp2Vzcx6vte6xlUduyYOL1pcfKR0ib\niWtE3UZDFsuZVZFUkT31aPHI6ZEJWRQLExZVLEIYiLBQeLYw5mLbf8qChZOBFks0+YCy0zcAY9yE\nnCaMb2OZg23j4I2xNhS6KMSb/S1bIzxk7LtiBTAZAyP2oTXgFsUA4ODjGrwBjmxpUwc2EOeYFMcN\neHMcbHs6HjLGoWA89NHbAk5w899u3ThyYuwTBS8CTlxNmWnpGsfYv5Ugyp5ABNQspNi/O+oE+fft\nGTgBAItuAY8GdOVgvfiYStwKgRYFJwdvCP5ZDRpTZ+M8tD4reDPZ+iwTIAs38CYnLL49LcLInblz\nuwGL4UGNgSNAEXW2WGwHtm3nAEU34OVDTdqlJKZ+0xGIM/LcxJgaaNODOLF9XQNxRMMF7HK63dYv\nS0nq98nOwCmRP+XgTdaTgTcB2OhyBt6IZJwV2bXJNQbHw3KzkE4NjVlJI5IOLpltwM3aa+nc/2Zr\nYNzHhxvwc25i/C6eNyLnx4AtW3UlzXvovTbHcPvd+XF89fMWqHkEfHhIPvUY++Y5pVPfBPDmYwI3\n7yPd3OvzrH/wD/7Bo8/5bb/tt+F//s//id/3+34ffvVXf/UjLNXXr3YAZ68Xr2vU5Wf9jPcAUK7X\n+7NxYlk+FojznPUYC+cxGdVjgFC6APrY7/313u6v/x5qEpsd1PrcC8u/uVBVpY6/0ypYOD3VnBjv\n5IMTRq0hQQgwh9CAm2ZeaakkyaEc7tKoiOZKxVddj21MiPYmx/G3cw+cNQAW49kMkQWiiy8ro0S8\neAymAz4JY2PigCsbJ0C5bbKQfXI0XU9j3djPzcvHwJ3OsLmCONcu+LYeTGufCnXWgejis/Qjsmaf\nGxckFRRQZTRkUQxMhp2QNcuJgEGAqbJU2AysJSGVJmlI7Oyb3lzUvzOJglWAkQI5sG1uq/PRjnWz\nYWrIQiu2Rpj/hnlvsDaKkjf4TXKTQ17TrTNGYxtE1HiwcAZSDAyMpBW8ObDgwOJ+NwbeHA/WDI9D\nweGYMRwCvFHwaIyVywAOwBmQYh5BvLSG1IbBU6rEAJbM5EyoDoThxkIJ5lF8n0tbS/UNdgDI2FUm\nkVuUMAbDqjAyJ6Ssxqjy9C9JAnBs9wIcOgnVwKAi6/Wp5ouDLL4+HYw7GXhTZkaeGHlJWHLC7LdF\nGLMkTIUxSYtWX3y9ZiVkVSz+JRcfj0UURRSLCixnqRjoQRkKsfhsbcybs+NGt5IunWeMteMswX4f\n1Qbi+It7QtQKxGGws2/YPXHiOeefV/d9Cv5GruBvQQA4CzK5TCqYNw7axK1nKYrk8+axYx0GiGNe\nY+cG8ZcYS8xDJ4HdxoebCXyVT3W3AHOImoSqATnn8eFbM3D7/Fh15+ybhyr2r3Pw5mGmzlPkU/KI\njOl9fGyeq95HOvU6wZvPD7jZQZu99nq52gGcvT5qfV6snPcHcj4WiPOSLJznroeMMPuyWfZzudTa\nwLMlnPSXCL3fRlylV7BGLl/sBnjT++CUgkd9cAZq5pKJAHIvkSRtxrVFifusLEYwpeqXkGiA0PDk\n9fi0Cy8x9gXJmZRKIQbe1C8fH4K1rICswVKPHq/Ai15ZRmrg2yXWzSXgBkAFbwxgOve/Ob8AjC+z\nMXpANF1h1hqsm2Kz9VhQaEBBwqIejy4hcVM3nnbgTcKgWjEQYa6AHCEVW4ttvacqj7CyJlPVzbmd\nfUPZ5FXqG08vLaoGtxvmjUyEPJE1+wtjWRLmkpDdMwVABW8WodV96YELbftFN4LVdHt06dTorJvR\nbwcWHFlwTGJmxYN53owuoargzVGQjqjgDQ0EJFxgpgBaFDQDnIDSyeZUS20ui5CDLeLfRZCVnWUE\nRDqysJqs7AobQRRQ6n2NDPgYfZxSx6pKpBiEkYqNc7DwiCqa6YCcM3IAX5/UNsftuiwdEDc38GaZ\nE6Z5sFseMJeEU27gzSxxD8xiyxwsnABwsigWMfBxUfGxsnSmjDD4NfCmYNmwcARY7Wfvd/wXLX5M\nZNuvg41YAZoe4MlQZQjYj6vkLmmb99wcQzJlB2+ah8018KZ0wE3pkqe28ikDo+QiiANcB2/a8dkA\n9wDhEw1IMPZN0sigaseMYNjEMaUaGaM3Nb4eH96DnFylVO139nMDQS+vq83kBpqRt/18LjdcP3+9\nrq4BMg/6Lj3gf3PpvPYc7Jv39b15Sr3Le3zTWDc7cHO5tvvZXnt9SO0Azl6fpD4/IOf9ZVVPMxX+\nMBDn2ue8K4jTP/8hM+NeRnVpXQaDRIAz5k0096QFHl5dE5fOl1995jBOfu1CNExH23P9vmfiCAFJ\nr67CiBPvGTj2+/UsaEio6kU2Io2K6vtw95yYcQ02Tu+D08CbEUIZzD5DLICE3OmSpKEbv0u13Q56\n5lQvpTofhPrGKxDHmi2ubBwAZ7PBUStp1ANyqR64sdf14E3//PPveH3/6JgF/b03sqwLBozIyJUF\nVU1GlUACVJtpUo+xVgzSvGJaMhJ8HC4viUmXinm+ZGelLACPnkzFBmxoN+YV3Mh2C+ZNBW/mhGUZ\nMOcBc06YJGFyCdcijbGxVK+U3r/n4m5laWkbdsDovxsJOLBgpAByjH1jZsVmWAzAZFM9eHMAaCTQ\nYLd+oEiMYURCUFbIrH5UiEYZVboU3jSZxcAlJYyiWEhtWf09k9ryFt+Hw8S3rgcyfxgSY1EZs4rq\n/aCMRRWzJNtnS5Nz1YZYyMA4kQrekF810dDkU5UZ+JR1mVMFb0454VT8JoyTgzgnZ+BMBZgKYRbF\nXIDZNVQVvBHFIoJFBQsyFlqw0FyNfAssfalnpbSNtUe0Hz5HhbdN/ywCVxCnrUlUNs45iGO/L5B2\nPEE718TnAFixbkIuFceQAG8kANvKuOsTp7rUre33xoXja3e8qeDNlePs1oC+97+JSPFE3ICbjo1p\nIPHa/4agGCr7Zu1/A2AdHX7FuPhDqn+3Jl8OLPJlus0PBVaealz8PvU0M+aPAd48LwiyAzd77fX1\nqh3A2euT1seUV30YkPPybJyX8sR5FzbQtee/y3tvgR8DiLh+h37Gt2/UBWYsG4BCD85sZwrXrBs6\ne6ziKT/vMLncS6bqjGfng9OAm+Zb0Lc/rRnuk0aMRj84Cyfp4FKekFBNYNjMdEipnlKXmpJ1NRaO\nwRAdsEEFCrMSJZdICDGAZQXi2OtSZeOwcp01X4F1m6bLPn1tUhx/t7+Vs9e2pZaLj/u6lELVN2pV\nPqUjEgqETHJBylh8O2Q1YIphUe/WNFnLWf0qiq1rKv6NicDFXx9mJGG46/4zxT2YpBBSFgzFJVaj\nNf7EPlver2YBpPj94iDGQshzMG8MuJlL3BizM3Dm8E3RBuIs4kbMAtRodLT9KdhCPSuggjfOvrHf\nCUYWJLbHw+C3g62/5JIpHgG+IdBotLQK4GykRRhgC4WQ3zijRQUpA0MRlCIYRZBZsLBgZEYSk3YN\nYiBT2OUMZJK3ROQJVashNdYMGy4bLJyQx7GQy8fsSGVgrDXhRArM60VXwWo9AhfWpbTnagbU12NZ\nGHkxCdw8GxBnwE0H4AjjLrODOOQ34FQIkyhOGQbi+IFwLoqpAjdr5k2wb4KV0pgpW2Petj+1x11q\noBaALJ/uHIRfy6msCpiSMTuogJHs/ODHkQCE2WGd/ngC4KLcsmCBkN9rGJMvbR9H873ZRqVfYt+s\nv0ObNHgIMLfi+hymAUwDEg3OwGn+N0lTY1sGa6+yMTe+N2jnkTinXPK/2VYP4jx0Wt8eI6WLqre/\nx9msMfUuvbaPeVdasyml+/kpaVJPbfDXnnhPAFQuvO9LSac+N/BmB25eT7UryL1+6Id+CL/tt/02\n/OAP/uCnXpTPtnYAZ69XUy/Nynk+IOfzA3Eee59rUqrHTInPP//y++g7jJt4ooo9bpcyDcShevHZ\na/prLGp/8ekfS/3PTyyy6eL2c5VSNRlVXGCvDCuxBnIGIiRiN7e0JjHRWEEc5gUMgYqAMXzwBddW\ncqUIJk6BEIPCGyKkVMG6oRE9iMNI52wcoDZgfV1i3GxlUnX5+qatly1UOv3jUeK2LflzVBxlcQBH\nFigNJh+hxWbIdXIGQAITYwE7baN+AQRfwECaSxdZ9vdeRlalfN4YmRku45AtnalkT2eaWzoTMbDO\nLTbQRgUG3uRmcrssyZg3LrM5lWReKQ7gGEuDMLvkpklt1mycLW07vmFtKik8OeDgjUccVxDHb540\nBaB53hxgQOlAoAOD+jftYrctUp2r6JEdjdVsYFDJgpTaZw0kSCQYibGQsXEWxYr1lkiR0X5G/10p\nTH/NiJr8e8++r04OYBnzisFl8E2hmaMXYYylQIp/90XAAeBQty7DVNrXoQpQMkMKY1kYuaQqgZsr\n62bAqTDuizFvTsK4ewC8ORWtDJxJBHMAOFowYcZCC+YN+8aAjXNQY70lxPe5BtC7Nwzhyiu7TVmB\nHsjZsnGCfcPgs+S5S8ePTEtl6MXxylhFZQ3edODt5fjvNgFz6TrgsWNusG3aY0ufityprf9NAPcV\niEEDcd7V/yZ+Z5/dLVOoSS+APNqdCw1UXB/PrsmlpPvZpMxaH69e/0jDHg5GD4Ml1+VTD9VLSade\nB3jz+QA3O2iz14fUL//yL3/qRfjs6+X0K3vttddee+2111577bXXXnvttddeez1L7QycvV5dvbSs\n6sOZOO8np3rq574EC+cpXjhPfY9LPjhPWa6eii8ozf+A5OJMn6DFV1ePi26GPUyM2/JRd3O2jS/e\nyu7hgWpR4vHzNomqMW/I+QRAmE82Fk4fI06dkXHS1EwvMbiJ8YhEkeC01LF+fFnX6VSXksJs7Hwm\nmhojR7CAMbpPDC6ycJTaa0IGQS692lZPq79kUBy1TSvp6fe92fFD37nKHjYsmeZ947PxmlE0gbDY\nrLkyFpqaTAxYsXBEFOHNYSybbtsCuZSAnSFmVVJ4toSJsCVFZWEcCmNIgmEoYFYMg1Q/i626KGRX\nxePCczaz4mBsTGLSqVMx9s3JpVzG3HC/FGfhZJdRZVUUQTUx7jlwfaxxS6FqzICh3jdGDLvBdzBw\nqiQsNdkUJQIGRo1L7xg4NuzGwoHYgpnpMUDF3jclY/ikrG1ZWMESfiEm+QJ830L7HkXXY7rakiQS\n45w9VNftRv6pg/kxKSqbytaLsW+GQZoELcXxfL0e1aPILTXMWFSLcJPBiTFwpsLV9+a+mO/Nfce+\nmZ19cyrqHjgmmwKAWQSTFixazrxvFpqqfKrJCbOlMVX5lB0QQ7a5llFtjx+ljlPPkm3HgcbSjHNC\nMHGUBOLStDiOBBMn3md1fAhPrO7YUVweVapBuBsza2PbbJOnrh8/z5mg22PmJb+cXt4a8ikiMzIm\npDMD4z6J0PymaO1xg8cNjGPbItJqXvwhVb3k1I5nPdtGN15Z7+p9s/YQWh/jHzMjfuj378Mi+dTs\nm08tm9qZN6+3tLt+3WuvD60dwNnrVddLyqo+JZDzFBAHuL5szwXirP/+PDKqx0q0ING6IbDPiUZP\nccn/xp7T7q2pbnTxXk6l3T0JHjQyBoKGvgYEtnKp3ry4B2rgr2QoEluKUR8bm+rFPGPQhMF9cBgm\noyqUIbQguexnq955lwuyx5KsQkbFCigViwMGoGAUCvnUWkq1bcCu1TXgpjcoXj9/HR0eKVLSNWCX\nvns0nHphWaKJK5pBaqCNuMdQriCVLVM1W67yi7FuYNHktOhdhSSDHwy0CYmaIjNq3PUi4uBNwZIY\nYxIMOTkIYgBF77Fk79F9TiEsJSELYymMLIwpZFPufXMSxuRRTAHeWMMPzLIGb7JLqFTX8gsbR2oS\nDsQ23BJyBu7lHPBobW3SDUaNDF9JpphAgz+pB3HYwB3SUl+jrKDkgFKyz6lyLW6+U4maD071ner2\nv/U24KsxgCv/YuYf00AcbECckGQqPFpcpca2j1kwpIK0NP+RxHGM1tXxphQD8Yrw1fV4EluXBtgY\nCGfAjUunimIS2H0FcAST2D6zQDDrgrkDbxZMWGhayadEFwduYh/sz1lPP64IZKX62x6jttKqHsip\nceNkz6zntk4GeT2VrpmRBzAQ4E0JeZhLdXr5lK2LPnXrcj12Hq2yKVh0uP0ugXnrfzNiQLJ/xBg8\nfaoH9VMnr+0NjMODqTcwBnDVMH67H9fvUv3fNj93Zv+qveQY2I5OhAXYc/13m0mVrfRttQxXxvpd\nTIffJcnqqWDCh4A3n4ts6iWBmx202Wuv11c7gLPXZ1Evycp5HiDn+UGcx573GLj1FBDnqYlUjy0j\n0MbPQAL3uPCL92DeXIsSb+a3fWPbsQf8YjOas0sa/n72OyEuYLW+l/cPV3uXPokqosTr3zrWxBbM\nsd9RvUAPc1iuniJUPXLsEt89Eyg5iLNAaISSgHmEyFIbpK2fTVse3lywPd6Q9SwcIYDiZzCKLkgY\n7eJclwriqIqlZQF1APlClPilVCkAtcGqz7t2gX8J4Llw0V+9KDRd/L7NzLgZmhZn4EBRQRyh0ceh\nsXZEFUUHFE0omiDegIqDhBZF7ffJVlBR4CaxN/yMAwsWMfPdoyQMxT1kyAEclovmpBosHmfwBJtn\nKglZ+SxiOhg4s6CLnDbwZhYz6y3i/jf+GWHV0kO0hABpArBs2zfgbACgYw5p9e/Z+nGQd6o1PnyD\nrhC7sXjQfxApTlpfX81ZOwZC8xEJtsIWaA021rlhc0Hb761vDVZfMP6imWUUVUgyIC6zx5czYxBb\nh2MxIK422Jv12IysYx1aRHkW9nXJXUS4gTezJ04FcBNsm5MnTp2KYC7qfjcFkwaA48ANmu/NQhOy\nTsiYkPVU47UbOLo1Lx5ANDaGyYVjvbEmuT6uTJuzRrr4eyYUNKZNgCsErobqYXB87qO1Bn1r0pQD\nM6VjJwZ4E8ybAH37JLt3qZ5dWsdn4w8UPzfz4s6QHuFxZmxLS66j6nkT54Wh2577fW1rYFyZn7wG\ne7f7hy071Z8reBOeTH1qYz/WF9hql0yMte4nm+NVHDNROnPpR84/PUtn43/zPuybp3rfvF7w5nUD\nNztos9der7t2AGevz65eipXzYUDOtpl+vs97iqQKuDwe7wPiXKq4eH9fGVWfRBXPExInxohfzgcI\n4DN99bPtQnIF1KCZx/YXqfZ3eAqVNYxK1hxWGdUj1yXknW4f3Rp1KYkKWF+Q17/BZ2BrIhWDlTYy\nqhEZZoipMbPJMBAHqICLLQe3Zgjrbcee03+5h5lWsQ5sfBcwjSganzkCukDJYLeiqA0YAE+s2rzn\nBbZNyKL6vz+2TGF+eamafCqazdH/UnApbkwgIDXwpmiu5IvsY6o1qnhBxtHye3SE6AFZ1IAaTjXW\neqkgjjX5AFAYlvzEikkURybMyYCcWQQjmwxpYDUQZ2NK2r6/bcv1s8RAoanY587CWKpMyu4BB3DK\nmnkTRsbGvOlmz4kqqLqtkHVQ16jF4zBTfVKJQqXFa79P9fsdPyDlCObQtqIh1daFQolQqD+W2LcT\nfxzrVGDR44taotdI3NK4SJF8fdryXfjcbh1mMVBvcRZPD8DNzpqaxFg39nMP3KxZNz3jBgAWWlAo\nY0EDb0pNZfIo7Q606Y8hdny2fcf5IfWYfc3IGARj1Dx28FQ/T6BAKeK110AOO8hzqXrWTU2i6hKm\nADTmjW5vTzHFfZy1eklCxTSA2caMeQCBkdDkU4MOxsBxA+OqJARWjwPMqbIpdDyw/jyzWbZLRsXr\nZT/f32IyI1g3kUDVM80aexWV+dqbGPf371KPGRhfq3dh35z//dOAN5+KdbMDN59fvUYJ1StbnL3e\noXYAZ69nq0sXPi/6eS/EyvnY0qqnSqoefc5V8ORdY8TfnYXzpPd1+ksfJS4oSBjOZk4rfbu7t4aL\nvOlCvQits+j+uuqBowbaKJuMSj0OJb6OSjfTeOECGGhNWkSJr3/uJFRkHhuM8BJx7wNpDJyQUbFy\nlVERGIlGb3gsfYmVATaGCLqG+9L+dX4R93CDYi+Es1C4yiIU4mwpcfCGkRQoBFAP3nWyh7P378CX\n3s/mqfT5PrlkeyEf4E3IpxgDxJvZaEB7FsHak2GduCUO3gTrKNFY45cLHVC0YNQRRUcUFSyaUNST\nnfy2+Ia5JMJBFEsiA286IOfEbLHcHsmdKpCnK6DEltcAyfDSyR4L3gAAA20WtWZ/9iGdxJZrFkUW\nk0xlMRCil0MAQMIFHdUTqpdd9PvJWdqbeKO5zSQGKrCzotQB9jt//Vb68U7L6M1ngDdFjDsQEp6i\nxoYLHxDh+HvPrIKBZ6w4smJhsvUnXGPVY/1FxXoMr66ibT0uwrY+1CRvBsQ1r6JTgSeIBWADnLKx\nbYJ1M2nBpHnlcwMAGXkF3IjLpuKxaul8YYIdw85E7BOVBgMkOobJ9TF+2n5cAtQPMOcCkGNjtwb0\n4zPO5JQoBkj1rD5ds2/6379v9SlT298Tpco+Ik8RJLJ71mBVUgVp2DlhwSALplv426wZZe14EJLF\n96nYh3rJFNAmOcR/X8+lwbzpEF3pfh8/273U+8seaC1BsP97yNrq894DFLl0/tiCDM8J3rx21s1L\nADc7aLPXXp9f7QDOXi9WW8nHi37WC4A5H1Na9ZTPetJzngjiPCcL59p7Vt8EAmIceiPj/nkAjOGh\nbcZPVb0xo3rB2S5A17+z57eZxtWtY+EArVE8G6Mrv9+yD1Y0d4ScgqqRcbtob8ycuKgf4GbGTr1P\nNHrzlbxJGJ1IkyOZ2BgEWEuptuaf12RW9btdWL8hpTJcy0yNBSafYgUKLUi+/mJL3jKugHbxvm6k\nnsCoufI+16qCNAaTofky2dL1UpD4rsa0KT6Gxe1YpX4PwYJSvYgWLBgx4oiRDih6xKIjjmXEIoKb\nlKoc5ujDvAhwTAaq3CTFgcnBGwMBRopYbj6LDr4ovwkARxwEcCBnUSALOWBjnxef37NujDnUMBQT\nDFEHNK6BlyibmW+m4bY+yAFTm80PiaJmB3NGiwCnAYYcsQDMBtZkWUuoYoGKQLN2N0BLB7bKet/t\nm8tLFQ1n/7MdNwzIUmg1N84gDNwYVHavq8fZxzyrYhB1BhUsVl24epUA50f2WJa1qbWtu6Uyp4I1\nZcCNsWxQI8JnEY8IN7nUhKUCNxkZGZN9FzKmTUgEg6nSS6aiiBKg2fefAX0TGWySHqS4ysK5ug7W\nf2M/NhGxgTkbIAdoLJ3t+/SgbxgwV2+b+rcL0qkeJDhrRp9Au7xQMQ7sMrPwwOGQUKGZ0bPBOtX/\nJjGQmDBs5LS9nKpXGvYGxvbZLUL8UqmaKXJllfZ/q/tQ7Fe9700HxqI3NT7HXC8dJ6IEZSU/tfd7\nGmByTT71KLvrwnv1r3/sd9de/9TXfchzrT4MJNmBm7322quvHcDZ66PU5wzmPI+06uOxcZ4Cxlx6\nn/5178LCqf4H1efGgJjeELkHbhQFosGkWL+vQKGqENLa88nq793sYTWYbRen1QxWCOwyKqSg8Zhp\nKrBuZJ9yXbRNogIaOAP0gI15dESjt2XhUFzoa8JAAwYdDUCg7LPTBiwQSfUs8UGr23XPvNkCN0/2\nLGo2IBdBHHWJQKFl1YAB8JZ+856bxmt7kd5fnLfEmsvyvvOxN9aSNYACdsaWbsw0exZObHvb7Rva\nGAKRo0NYIC5lSxiw4ISRbrBgxhE3WDDiqAcsZcQsCYukCqBMhXEzEA5sDIoD2+ORCQcmjOwAjgM5\nA4U06AK+AWvM8gpgcIlWADRKmIqBNgBWcqnsLJyQG8b2TRROFuT7ljd3DtjoplNr+xZWjLZSCEnM\naBkAOCs0AZq1oZUQYIClUaH7kv5mK/CmOICTAc0E8QQu6byAVv5XiP3b33K7zGgAb7CQtAOEGTZO\niTrWjQCFFQsDC5sUbmRgZsJIBvjEugv2TWxRT1l/se6yrNlSjwE3CzImmt2c2GRSAdrY5537wzRA\n41y+wmSMNcZQ95t+f+HOC2e731wyse/35y1DonTngwBzlLgeR+iKhGoL+q6+j4M59jzBFrzZevw8\nxExcJW5dkI71xsVECURcfW8AVONixljlU0kHY1ei+d8EG6f3RquAPpqBMbDelragzVXTYmnS4Ph5\nzZBrEqkeEA0JVWO1NlZOPS50qZD9sdZ8b1626X+MffMur1/9/pHlfjnJ1PuP19cFtNn6b31TS1Ev\nu/ba64NrB3D2+uj1uYI5HwvIeSob511BnKf44az/dp5K9a4snPP3u+yf0keJA1g9Vg3PCk8DChkE\nwrfC5Que/DKItNnHmNn3JByCoRX17eXK1fEjRa0lrvfs7Ju4WDfjYo8X9wZwcB8choES0QyILlCM\nK1BCsJyBOKBujK+AOqvlvLK+HwNxQOY1YXIBrGfSLzBlGvumNY9b+nxUQbdd6cPNYSRnBasmos+V\nzi8IWyRyqjG/9rt0YRxKbTShQKEMVkYmdl+iCQuOWHjCqEcsuMFBj1j0gEUHHMWW34AbwoEZxwQc\nGDgkYGRgIMIxKRIFkGPeGCHFu8TgUG/+Iz3KpFshyVmzbYA1cGOgRIAWVuGxoUogdgBDW9PWAx/F\nmSeNQcLI6lHYJWEQgRSpAI4sZH5R3JgD9sayNoUKmVRWZ+codFHoDMhi71MWQsmMUjx+u1uGnpUk\n6GQd3RhVUBfxcxuLUnd23xehyEJIrMjsXjcCZAdyRgfeBlIMRJZ+5ft2L5/q118Fj0Cb9QaXwIW5\ntAF98yOMm4lOWDCZz42eIFhM+vcIUNrvCwaiCxIGCDFI04rJApyDFLG/bOuibGbDitlWRMYbA8iy\n4ALIsfFbg0S2hs6BG1VZHVcugTfPVZfAm2Al9WBPSF9ZjVVkfEBC739TDbhpDd6sgf+exbk2LH5K\nbUEcIM55zf+mNynuAdG1PNlOBuvJEl3db+uagfE1GewamHk59s1TXnf29xcBb765wM0O1uy118vX\nDuDs9UnrU4A5nx7IeR42zkuAOB/io3NJXtOnmMT7hw9Ob2Tcnq+rC8cmj+pmCWEXnKUaMcZzqDZS\nl2RU6EGcWB6ftVxdAD8A6sQFd0vqcTZCXJijsXGqBwI6Bg7B48RDRuWJVBhB5DIHJBevOIVfYcku\nlFYgDtC25Utslmv1FBDHzEZHAzfgzRatZ9e3QE7feMUyXQOVmp/O4xgaIQGE6pUk/bJv3rc2Wx1w\nczWlrbugFclmzqxAxoREIzJNWHCPAUdMfMRRv8SsN5j0iIPaqfOgI46SDMApjEMiHAphZGdvlAbm\nDBz+Ny2+O2bXYxvOvo03GZVLe0RX/jYNwFFPm9Lqe9M3XOyflQiwAClnnwhBHdARtc/dyn9sGUwy\nNqgBK8xcl9lScmwkIQCJgoqCsr331shY/ctpVkgFb1DBm5wZyzIgl2TR252Zc7t1BtLRjGpL3Cqi\n5z93xxFU8IyQ1LyMRibMDrIN4XvDbj7r682izAGmy1tTNMTFm+HcgW1FjW2zOPNmEV153CwO3Ew0\nYaEZM+6RaUHW5m/Ts1Ieq/44wRihZOCr+VwNq2a5+rpc2Ge24P1qXXbgio3qGkiqwGt3LOuZbwCg\nG+DfxlHO3j++9xoYPpdVPW1sHmDcXAFv+shwANV8np2xN8BAnASq2xbhnHnTGxgDW/bm04GbSFSM\n9KnKwAmJYyefCoZqZeB05sXBxAE6yWUcQ+o5dQ3iSMfEqcvzQMrgFmB7TCb7EPvmfaVTHyqZej8w\n4v0AjOcGPnbQ5nVVTDS8qnpty7PXk2sHcPZ6NXVxFvElPueTAznPx8Z5DAB7Kohz7TVPYeFcew+b\nAU612RZYjPbWB0fcuHI9i9fkD+LAjOjlW/FYa7uw7xI3OhmVxsxmxwg4W+aN+eO2tsE6dOF35xGx\n8MYv6PTW0oSMiomRdEAhSzNRjA5hcQUu7LP44rrugZx3uVh7DMQBAshJbSbd1xlvPutS0wWs2Tjr\ncVt/t9hOLhU5cBQNKcUM/gXQ51oDumX41GXWNcgUvhqWWjVZs0kDBj4iqQE6AeSMOAAAjnrELAcc\ndMSpMI4l4ZDY5TcGCoxM7oPTJBUtar5bJmeOiDb5TzBxwtsmC2pCFhC+LW1f2W6/idrRJhLAU/jt\niK3vXqo1qhpjhM2/JRFjEEbKqQOczDya2PbtQcSSpwrAIyz6eLDvAkZdABU0z5tszJs8OXizJCw5\nIZcWvZ2lJTgt0jxlwtOmedloZd40XxtFiSQxdbhYo3G2QU9qoGoWu1/Y2BMjm3/JSLDo924/pksb\nHvr11oNqBtqEN9Giliq1aA/czJhpwkwzZrrHoidkTBBZzmRR6229bdv9MTjA8hDnCDnQ0THWeNNE\nx369Zpms951+H7f3v8yMieeyxvtIA6X9eNOzclZjeOW9e8ZN/9xL4M32GHhJbtq+98Oyqca8SVVu\nBqCCOUmdd6POwCGqTK3++L81MLb3aOy4qOt+N91jIVBSu2fzh+v/VhMY68RFJyuu8qmNbGrzOe28\nG9Ms6+W6dp55SO70ENjyPpKs1wvefLOAmx202WuvT1c7gLPXq62XZuc8l7zq/Zfz3YCc9/XGeQqI\n80Hvv7lAfqqMSvxxwoDwc5D6KJ7fZi0UcXHpkoVOyx/Prf4ZRcFsUioRMjZAPHHLDJCzXuLJ1XsY\nRBJVsG4qE8fvTVJFNovvMirzThiRkCEoYJI6Q436vQ0wu+aHU8e8Y+M8pVYXXyHNcq+ZFKeGDjyJ\nzyhb5k3fSF2QOqzHi9fv2z3egjhNZuWN2JXvt22++sZr9ZleAgGhQMGV2SCa298lV5BSaEHRCeyM\nnIGOWOgOA90AACZ8gZGOOOoNjnrAqQwYJeFIyQEcA3NSJ6FKHP4YulqyfpsPNs0aENAK2ASAYyCP\nOVX072HNoTVtydtEUgKLJYsVB4eSAzYBMNlju5/IjZcLG0vsAnYxFGsSUxFwUsii4GQL0B8C1Hda\nFUCLSaakEPKcjHmTE5Yl4ZQHzCVhKski1D12O8yAQ5oENIlSCcZNB9jEbVFBUfFjhnt7KExKpeTs\nOI9+FltfszTG3P+fvXOLtaXL6vp/zKr1nUZsCdJGjJIQ0ly8m6iEGCMdu8EIBroT5dZEMcZECR2D\nPoiK3EzHhIQIdrcJDxofmiDEC0TwAdsECVEkLQ8gGtQIhjYN0kDLrfucVTWHD2OMOcecNeuy1l77\n7H3OmePL+fZatWrVqnvV+NV//MeoShyi/W0mUIzTNjvr63OMCnAqf5sg/jZP6Tcw8VP991HMPCWY\nWO/n/jzu9/MFpKS8rzNldUwNYvK012HnVqwBFvO4IUipqIEcGSZQeHV6G+VSaTwPindO3gtw01Df\n2LzW49k/OUdrG3FYOae2EMcASgrL/NeOQSuftZDh24+9a5hjoIaInfJGSxjh4I2VTPnyKfavAV+C\nXDwMsfc6b+zm0XehArBpYNw678s4223e19Q3R65nt4Y3LyK46dCmR49XKzrA6fFCxPOCOQ+jyjkG\nco5M+1YQZ8/QeE2FU5dRMc+IlJ8M27RlvGVC7p8UJ9l2koNnrwkzMxW4Ize3E6v/TfA3s1IeFWeS\nxFIhjs2ywZtafh4PlFEthutnkuhlI+NCjRNIn/xLGdUZKtPngECD/EUQr4hGKVXLDweonjQfKBmy\nqJU9BlNmLJMvKZtaufmunpYDltzlG3EzL7XphoBiX8nrsU5Gg0KXIc9jNX4NbCi1Lm6rb2wflLk9\ng2jQUhVtN84RM08JMhE9w0xPcaYThvAEIz0BADyj38CIJ3hGvwkfoSd4jV/Da1pidYojThRwoiG3\nkQ/mg5Of1BfzltQl2b/FFDmmJJk5YrIki8uSQ1l+gpmpBjP5DgEhMkIQ8BF0HkYCJpLuS89m1VkR\n8JQIgZZrz5uKz5HwWpwxzxHjFBEGgThhkNKqusuWHWtxDpgnMSyWsqkB53kQcDMJvPmo/YsBzxTi\n2L9cPkZJ4WJwp1C+KLw5c2pGndUEbKUu4kk1UMAIwrMYMrxJCfn69rJ1YqoFK9vy8OjMEWdMeIYp\nqW0mPMWZnuIZ/wam+BSRpWQqt/7Ox7VXgVgZD6lXU72fZyP5Rmc4P4zyOHvBrDCzOvb99OqSJgtK\n5uN2LgnNa5H/Lftbg5uW307x+soEtgQ6pfom0MkZPNv55YSRrfuU4Bzt5ZXAvanV6nJar9qsW4j7\niNw6M+ZglulZuW825C/BTdTSQymTDFpCJcdOUXKM/JDET88eqxTz1ugeZn/9PrXlT7SlvtmDNzVA\neFh482qAmw5tbhPaV/WhZ6PHSxId4PR44eI+Yc6tVTmXg5y7q3HuG+Ic+V0rzfHtnCXxrkFOTjCi\nthEHcjlIfiqIVKYQIWarDMKktfzyG0g3pabEoZnTU0u21Rtz+1V/X1KXn3h5eiv8U1IyopI+c2Uy\nYO1ApTJ62NPZIN2oMGKmEyYtWQp0QmQ1/URdbtRWnxQlURdE2t/9slclVeCYQE79m2k6VcLVSrY8\njIqEXArF20/JgRIAtpQ1PpG1ZDekrlnVPo+IaGUlmDHTSVoy04iZT5jj0zTezJMsD88Kep5hiE8x\naUvhgZ5gDE9wJvHKGcMTnPiJtCLn13DiE17jMbcYnikpPoIpY9xu5hMngTdywzepemRKKVWGNi1P\nE/F4kRQTFJCMhaN42ExRAGP2ZVKlSRT4mGuf8rqzZNBKFucYMM0DxmHGOEYMISIExjBESVZD3qm8\nQmCeCTGq580srdmfTQPOMeBZFHDzdA74aAx4Ogu0eZb+SScuQEyBpaRMS5QMnMSowEvgiWjbZkxq\nfl17BBELXBiRy2EGhVe5sxAW24sX56oM12aFNhPm1Ab8rNBm4qeY8BRT/KjCG1HcyL6Wj7EaIgw0\nJhUIqUrO7+tN7zJLrt3+LvO8VE7IMjWSc8LivFKrX1qdoGw5CLEAOQBcidXyXNICN2vQprUMW+HV\nesVwg76N0inR2pySKjHQIPuMnr8Hcb+BlchauWzqTEgZ6njfGx9r5VORCcSEGG3+leIHWfJiPdTq\nG19KZb44yD44Bm/sGpt85qyEqrGOM6wRA+OsqjlWPnVEfbMVd4E3j0F1cysQct/QpgObHj0ef3SA\n0+OFjpbM/GbTvoEq53KQc1yNc18Q5+j4XoUDuJvxhpmxhfnfeB8cb2Rs2ghrJc6awJrixnedmSLA\ngZKpqdX5zzFgJsYQWdU4+vS/uPmFgBxrsxrzX++Fs+WJI8uc64Dqkim7eSd/Q2//QBghChx7djvy\nSRVI80KFgwOlVJdCnIXyxqap07HEi2jIIMdt77KV8Eo7Xw9EWQxBDdi09jvv6bEGanRtl8OdQiFA\nlExgG6/2cMqJ4URnjIiYIZ4jA86YhxEzT5jjUxCHlFgzz6qQmEFacjXRM8z8VAAOPUGgE0Z6ghFP\ncAqvw4mfYMCIE7+G0Uou2EowslImr0cPZjjBGg8fyiLDMmy9BJDCn4DIA0ADAjOkA5P8AhBEAaBd\n0oymSXKZIU5kKerLRsLy2+cYcAoRp3nAOM9SbhWiTrMEOIAcW7MeX+cYFAAF9bgRePN0zoqbZzHg\nI7OAm49GwrMZeBaljToAPJutNbfAm8n/5TkpXyZEnEmMgGeS8jjbd82cO3WFE4yj/iYCwWw75X3Q\ngHG5rQwSzTRjpgkTTQnazHxWaPM0KW3m+LTYt2z/to5QAm6kxNL2qwRw3L4+sBxT9X5u+3pKvimm\n97FWtZhywpkcM6KamsvuIGbqNp8hAxaO6biPDkLZfBKHxflETNlLgu5hkP1+q0zqSPLaOg+2IPHa\n+Sf/G/JfXb9mYmweOKksFq4LIUq1TfG7d3gCb+VT9tpHnL2BcanCicjlxumhCCOpc1jXqle52vnH\nd0YEGtCvug60PJtKZc516pvHA29eTnDToU2PHi9WdIDT44YhOokytlUbt477UOfcQpVzHyBnb5pr\nn29J2O17ba+by1Q49lswbsKSoJgPjniPSCLijYxz6VTuiGF7lm8lbk8Rc9mJJogKbeYo5UrzbDe6\nAWGIqQ6J4RPnfNNrER0YgvudVtQeB0kmj8rYWJPBkQLOiKmMasSIWbs/tVQ4Xs206Eql67mGIls3\nZKtP1FNihbQAzGXitZyWSxLj1Ey8iGQZYpwQwijDG/tY7elB/qk9MtipFTYGbeTJeH5ybol5HZLM\nRoz8RJQ2OGMigTgRZ8w0YaYnmPgpBusEpN44MZ5d8iqgwEqsAp0whScYaMQZr5MuNfS6ZHo60Akj\nRplXB1vyCnClg4ZryB8ZEXUJg4Utt00/EiOy9O4qTsvR1ieroW+GN/Y32vGAoGoWMfl9EgLOKgc4\nhZj+DdOghr8x+UF5VUEyFjcVjkEcDsmk+Kn+zQCH8NGkwIG+l45OgMCbZ7O1VedUNuXhzTNMmGnG\nmZ5hwpS2daySUivvSfsO5X2nuZ0ARMrbycCQIBzdlxTaxJg7Ss38FDFOWdnlHhIQDQJuwoiBnsi+\nolBwwKnwYRl4xMCnxT5el6X6fceAb4I4lPclD3UIptQJ2pntrOffCF9KW4eBW/nMjv/cgtuDHECA\n7mIaiMW06mGtWLv+rUHiLfWNfa9W3+QCKaQy1wBVbSVvM6e89KWz8Of/HHt3ApEJFAEmSrBQ1gNQ\nt+5L6lNvWqzHmV0LrXNjhjb5umrKG5mWO24VTtbdp7x6Ns1DwxvtEvXNpb43i+lcAW8eO7jpSpuX\nK0zl9pjikc1OjwuiA5we9xx1svH8gM59wpwXDeTsQZxLS6lqFc7yO3NSWpS/K4kBqwJAlnBORsZ5\nqfPTbbk55fQEUWr48xPEpQKHMAeDNwFEjBglqYxzkC45DZPI1LFD/9o07fMjUYAc74Hg/g6BUktn\nK6Oa9Yn6jKmAD6bCETXJkIHKAaXNkXFWPy/ATSjKKFodr1LyhogYJ8AlXXk+xuY+mrq7OFDT8vbw\npSJJZYMMcDy88Em3TxSTlwejULTMNCFylYDjjIlULZFeT4g0Fk+RbdknfgYiLYdR02NRT3xEk+8R\nQRNx8zvaUwh51QSAlGT78CBr5JMoieikR9SY79CsNIIZch6O+mQ+AKZyG+Q4mwfrcEV4EqDwhvAs\nMF7TnVwMmlkNkCMGhTbWeacuCzHoOsWyVfk5Bpy1w5QZFlvJ1NMIPIvA05nwLDKexWxiLK24c1vu\nM0c8i214c8aztF2lNO68SDib+5hL3GX/GQqA5reRTFMBkXaRapVI+UTV/FW84mYMorQZ6QkCTjjR\n6xKwGa2Mx6mFbP/2ijSvovGqrQIGclzd1yIHVfwBoBPAZ2n7vZGE54TdJ+5ynm+BnASLUZ6HPLhZ\nAwD1taoe1hoPyNft1riF+q9S3xhAA5DKp8xDaXTlU6SKugzwOakuy/nYTpvWrjcxEsJK+VR0ZYpx\nFiWqwZuox12+hubXMxPMlyOXKXMBcop5IH+dXlfTpHnbUN8cAQhrsLD8jfuCN9cBjscMbjq06dHj\n5YgOcHo853gYoHNrmHNXVc51IGe/rGptmreEOPXnRTnCym+VS5LLqOxpbOGFo+lG3UrcoI0pcuxJ\nokEWU+DEQMkDZwhRvHBoxjwHDKbAqWbPPDpk/jPQkffVk/eVm2vvg1M8dXW+B/mJLLm/GTgMPCLS\nSdfhAFIVzow5lS0QhdLQWFZcocJJ8+TeG3hZliXUMMZtQxVm1PtCOX5O3nwC55+cy9LGbFJdJzSW\nLGHAmp+N7/xiwEbWdcDIo1uHQ/q2JVlA9jDJ2zGXKEVmVVEwZkzqXiIw5xxUPTGck9nszGedxiRK\nsjjpmowpUY90RqQJpMqcAPUz4ZDey3ZZngOTV0lat+seE6l8DBneJJiWusWcEJlx4lHWfQQigiTq\nHPXpvB5Dg7YsD4RzYPk7CEh5LRBOBnASvGHx9zHlDczo2y+PxKSKgMnB19QinIGnURLNMwNPtWTq\nHMXv5tksZsXPtI+4lUs9dV2ePLw5kyipzngmZUwQVcwMVVQlpUm5LgNngGj71942sukVf9WQ2Hvb\nGAA3r5UQxlQeZe2pR4j6RsrvRLl14tfSvg0AI4a0b9f7tYUk4dmyOzb+P6lyiBFBWroZKSbAMrOc\nr9idi2TZbZ1Mi98tYQ6ceqUCOVgC5lpts6faWLteHYk0Hxvqm9RC3IFWg8dWZkewzlOl4oaSqk1/\nT/+2jbDztSaydIUTRSgnH5y0hhLEcd+P5n8TMM/BKd60fbhCG1OxTq4Uue5CJfPDxX7jvW/k86X/\njS+fOqq+yZ+31TcvGrx5rODmYaGNbduu9ejR45bRAU6PB47nD3QeE8y5DOTsq3FsmvcBcfKw9VKq\nlgrH7mNbZVQ2D1ET+5RwstwyJgUOUKhvUttep8CRG1RV4GjrZoE3EZGCthWXmeGZUJuR1hJ0AzkA\nihvivWjdoIusnlSFo09lU2rgNTdDghM21FQ4AkLWO0EZoNmCOMtYJkqL9eKmWewr1Y02m8Ig3bzb\nsT2s7t91smTYxcoWDNyMfGoqbWy5RwxqQDvolDTBpZw+5t/MT5zzPsaIfELyMmH1MsGECR+zhDna\nrSr5maiyIyrYSU+a+ZwS1UgBxNLxKvDTYp3U3YNKhU+Z3PilIetcRidEnBEM3pjSgudkDi4lVRHM\nI2YMmOOAmRgzBzmOQsAUtItTIEyBMar65hQZp0A4BeCkO8gYGCNBvG/0b4D8BdodtuTJvxy3GeJA\nFTjia3VmaWNu4MaGm9rmrFnmVJRNaemUghsxDxbj4JkmnPmjiDjLdlS4YooZv74tqU/rdkOxYd+r\nk9Ya6Nn3AwIovIbamHgkV2oHBTc8YuQRA0Y1oxaz3DHNT96vqQI4zX1bk/GZ5wxwSM2FUSpzZj4n\nkAOS/WGQnTTtn6lDnpZbFmWXaX26BJ9OOt7yvFJ+Zx0sL6NdIrUW16hv0n+UFX+yNcZ87naG5LXn\nmQf4e2HgBpAlJ+1ExZHAhYSHF10Sc2dGp8IB1HMKmDloJ6pcVmXAxsqnmPMDE3bwRubHP2BZwpa1\njmZH1DfPE948RnDz8kGbY93tXtXoGKvHraIDnB6PLJ4v0LkvmHP/IOf5QZzWeHUplcxVu5xqOZ1c\nRuV9cPLS5YQjDTNoU5ROcXpyCEhnnYkIY/LAkbkhYlAg9f6IkvwERq0Qj5GKDh7ZALK1DO278gIU\naCmJdaLKPgj5xp9A0sZYy6hEXZMTBv/ku+WF4+/jmedViLMVvmRBX6T5l8/cUlH5nfw6q24E5pyL\n9cBOJ+ATJfnrkiVVptSGxAnoIKttRj031ODGOgcJTNBSB1NB1SocXVjfRShilL9sMCeqkuOcYM6Z\npFPVTKWqQ1Qe2d+kXk9yDGkKw0vPkjyeM4htbEe/DgOdQHzW9RWTEXbEnNRcTFEgAUYwoii9WOEN\nBcw8YGLGiQOmSBgD8CwAp0B4bWCcAjBqS+2TmhOftCW6tNzW8kCFOECZuKYn+7quM8DJ/0SJA2dI\nLDBncuBmcgCnbtNtZsUzJjwjKZnyBsKpFE7Lmgy01OUfHtqYIsOvcx/52JmbqpGBRqcsC0U3qVaJ\n1Gv8WoI2r2Es9udBzxkyj2VnrDoMfGczbOlkNnLIncyY5XxBtq9PpdcJnwW8KMQRLYepUGStJSNg\nXl7zyv32DMaAgLE4r7TPUdvqm7VtsRUL35uj6hs1Ly48cNIZKgNiGb5OaoKeZ+rS3VZ4xWdkPaNz\nVnbqWMX4Cd7ErD61EqpJ4U0CN5yPw/RwBKbCWV4Xl143WZcDlOVTrdbhfjtulU49PLy5DHg8RrXN\nw0CbDmx69HiI6ACnxyMPf3F4cWDOtaqc4yBnX41zK4hzpJTKz/OeCmfQ2//BbU8xMZ6rm8FlK/GZ\n2d1wZh8N+S2UChy2VqniCSC2H6LEmZ0CR36ruhEunibbE0uVo2/cqFssPA/cU1mgBDnkUoKcGlgy\nES9S4ZS/eQHE8evdgRzZjnF5U19MtwVvtvfPBcTRZEnWwKnosBOS9iCkzi9WJgUANkad6Fqrbkt0\nTQXVXP4EA4MCBlMsDNoW+oQZr2WYw68DAEw0JaCTYA7lEh37K78xL5IU/wTbA4DsrbMEQV4lEsIJ\nAWoMDQN9MxgnBFW1eTXOTFIeJqbZUp5z5oATjxg44BQDThRwCgJCByKcZlHejAEKcGQ+DN4MJJ+J\n743oQdplIvJ3LpQ4UJNkATezgzapPTgzZlPaRHFpkelkcJMAG7nSN8pqqaSUWjESXlu/dWvp1j7c\n2qcN2BiIJBIIGRolUqOWSNXQZgTlfZpKYGP7cn102VLk/VlaqzMDgyArDAja7jwigDCxnNkCESae\nAXJJOZ9FOaZHpoF2xixeNqqaiw56bXXuEzBk62tlnBoo2/ptLq1Xoy3PNS1w04o19Y0vn0olVGqW\nbuVrRYdB5NJZwqJSdDH3spxmyG+ITMunoDCHOJXzxqAlbSzdqAqFqHZ5m2NI172ZvQJHoKkddxH5\nvalbfQtxVhhsqlig9L8BsnrGzll5eFmeuA5V9pP/Pdiz9xt7n0kcBx+PTW3z/KFNBzbXhh1rPXrc\nIjrA6fECxfNT51ymiNmZ1hWqnMtBDtBKltemcwuI0yqlOqLCkeFSRiXJgZdnZw8cmV7ZSlxKqEjV\nA2Xd/uSAzsQBQ2S9EXfrSiGO3PyiuAmun2J6oOO7dKSpHSyn8smslFBpOZWWlG2VUQm8KVU4vvTA\nOjWbEsercIAMcY7CHL+/tJKtch3UUviI9s1d9hPxS0pULrVBq0DDAt541U1q8QzzAwma6IriZnDw\nZghaZkJZtWDbJS0Fy5yl8oH0hJoxcUgJ8MQCD848Y8ZrAGTYmc6Y+XULmCPlS6IIYS1lMlBj/ist\nlY4HC3VXL9s2tj4jTwg0IiBiIFXfkLQcNzXOzOdkwpqMjumECRMCBfVYOWHkAQMPONGAMRJONAjA\nUZAzpr+6VSn/I0JS4fgObGm53LpOaqdoUBaYIyeYc7bXCm1m5qS2mRBTK+vUshtTAW6sA5QobqRk\nygCOdRNLKhyOiFz6uGR1RlCAekrln/Z5Mb4rETRVx0Cj7KGVefXIAnBGHvN6F4xTQBvbh0cylQcS\nxLHYgmRsCkUQRmZMLOc5AzaBBB0zyzLOqoQ00B4Q8wZUAM+cPcuyOiUW0MOgb/a8yeeGVD6lKsJW\nua783FKJkc5HOH4dXYM3RekiLY3S82cKlJ3huE03n7FsXCo6UJXzsQy2FV0P1wSPFNAQi3J0CLpO\nIlkTOcBdfwze2DVLFDjWicopcGBdqCh54DA4+8shH59eBevLpsz/Zq98SpZnXX1zpHTqrvDmZQU3\nHdr06NGjA5weL3DcvzrnoVU5tyqtagKbG0Mc+zwiqtfNUoVTen2E4nf9a0tx61biuYRq6YEzsxig\njmRPHQkUtVTJjCBngIlAQbrk1HJ1MzO2m+D8RNsgT/kUZas71aIjVTXcDDC9BD+1M9YyKtn+OcG0\npGntyWXyF3IQZzlOG+bUN86WNJXJ1sqN8sZv2d/8z7omDfCdXoon3toOvAVvDOvYehtIcNfoEl8D\nN5b0Di7Bkt9uLUOGcrOah76W1DjipyRqkQGTrqszoqpzZjxj6XrkYY7vaMWQDkUGVZgE5shnAVF9\ndey48smvL1OTdWoKnDGrn0ghTpgLNQ5hSL8ZEDDjVHgLDXTCUxJfIVm/g8IFXddR1u8phAQVZJuK\n+kZAGWRfPgBw5Gk/J5gj61Qgw5z+RVU+CVwwlY1AG2cYres4knZ/4jmBG+Y5lbRFPmOOT+V1PEM6\nQ01FxzSJkGa+dY4OYUznMF+GY0BywEkATgVtvBnxiAEnPiVd2YnCAtrYawNitv+m48rmh8onuuzW\n8QAIJCMBAswMYik5nJlBzJiJ08YJiICaXE+wjm1ZgWLgArAyIikMLY9tNSpGAGOAlUutXWfWymIW\nwxuwZ+uauHd9te2W3rtplebFpR9ZXnZTT7a9iNZUaEC5vaI+jEgPCAgKYZAeWEQgmRgHlP5tsi6y\nR5uco1SJYw8zqq5vBk2j+2fHofklZd+kUlkTq0Tel1HVPlB5/o4DmccGb15NaNNhTY8eL0J0gNPj\nJYn2k/9bxn3AnNuDnMshTj3doxAnf67GlpUapzltnosyKkL2wamNjCNnM8VsskjuhtOUOCYjh7tR\nDSAGBmY1MmYgBjCxPM2MhLlK4/2NsHnfFOVTnP9ZR4+01q0spLHe/a+ItF7SG0nOsg+Otdcty6hK\nM2Nr4+tbiqffOaCy2QI7OWYA2d9oCXFsfW1Npy5tyAmeDcvLmpMlU98USp0GvLHSEgBNeJPLe0gT\n4GXZSauEw9Q3AGGOnKDOzIwYKJX7zPoYPKtDBryGUy7rKUyQl+qQkZ4IcFDjYYEOAdFgnbKyqG3l\nvRdO5CkrcGIE0Vge9hGqxJFOWDZ9K+0JeJrWuSAdB3SgsIEa4GzO615mMZer+VK1lt+Q9xqy96Zq\nMn8WZk4KG1PXRIqp7MsAmJVx+Nbd4vkj5w1rEW5KJt/GO8Yz5vgsqW+4ob6Rra/7p3rWJK8h/SvL\nlz2b0t8GtBl5xMleIyS1TQ3F8v4r54gxZBBg+22hwMmbu9h3rXyKkfsghZivkIZXZrCcT1Q5M0Fv\nCK1TmQEFTcozUDaQrHsA5zIqW2/pV9jP8/b1eA3eXBqta2pLfQNsmxfbtEwRmQFO3ghBIZstI1Wg\nrQ4riapfA0jXFiKAmJMKJyiYAQAmlmvZoqTVw5uQrmEzB6SW4cjXyKR8S0otD3Qq/znE4pphWMeX\nT7WX1Z2zqmtO+u6DwJsXA9x0YPNyxlaJ6UPEI5udHhdEBzg9bhZywSnvXm5RgnR93F/J1a1gzv2A\nHJu3tfKl/eFHIM6aH05S4Wwsk5VRlXM9F0/4rAdGNpjNxqdTBXEAuzHl9NRxIFXhKMRBkqEL0AnV\nzbPMV1k+ZVJ0Vs+A2v/mklssn3wlX5b0JDcU68uShllT7JaZse/kFTjfJNcqnEu8cHKUEMdi78m3\n/L7/fFk+lZ7Wuyfa/nMzLTZFSIB4TuT1lJ+NA0jwxkp9LAn28CarRcoyn9aSWDLDRG7/Iy3zyTAH\nEI+Wk5bsmXrkzIMoSFQ9IubH6j/DAnKkZfmcIM5MJwQt9SH12JhsZnRGY0QCDqXh9CTvFOIwzwjh\nlI9TkqPKK0akTMa2Q9k620BECEOCEIFKHyLbbgGEIY4pqbVthDTbClcN4KQn9vkJP1PEBCn7srbW\npliaUncvfbqPGdGV2mRw40rTnBLAt/K28ikPb/z5N0FFGlN778G99gbEsp+XShsr+xtY9l3ztalL\npKw0rdhnq/01e97k/XXvjJ/K05ICkUFBzoHmeE4k58984goLiCOmuUEVivlYzVoTpCMQmAplnY1r\nKhxQmbDc6n5g1X9oA96k93AlX2nY0ry4Lp9KXe/sXOQMpYGl4rIe5iMmOIYEWALJeSYwywMCVeFE\nhThA+/FMeugAg0D5QUb5UCMPMwPjvQ5ULQPj8n15va7VNzLP7dKpo/DmtmbF9wNvXixo04FNjx4v\nQ3SA0+Neo3VBejiocz8lV/UyXrN8l5ZXHUmk19Q4R31xtiBOa5xWZ6q0btwTXfmrz4A5FD44Mtd2\n62hGslzebEKUEbmLTS6hKv8FLRmAZL8QiJMMIKuOIB7imE9A1OTdGxubAav3wNkzNrZP5Qlt+bv5\neXVOn2dgs4xK/CiWZsZbsOY6kCPRgnXt6S+H+X9ALlHIn7tkqfKhMMNi30bZl0wBWWljvkKWDJvq\nxl7XPi21MgpwpXHI79mAIVEy/5x1xNlUOTH7t5wU5px5xoQBJx5TNyvrklSrcoIqZAICZhoxxQAK\n0pls5iEdyjEChKVvjhw1EzhGBBrBURFqOGHmqVAa2HpPrw+UBBFcJ7BgJXCqTkiGrnm4335A+QSe\nkVsRM6yFtVPTqJm5eNZkOGPT2fLOqLt31X5CtfImAQkKIBoRaMQQXkMICm/ohCE8SeAm0CkBnIGy\nysagjS9B21LbjA42mjm030+9akzmc8fzxu2rEVI6Rbq/JlqgEIfBYNLSHMi5h5kRSZSArFuTE4aX\ncqigpXiAnpv0v4jqOOeswknn/CqOPrDYjv1prO3zfpg/N6XhCRH7c1YoPrdztnxuf49HBi6sbcIN\nomQVjvnfRL1mBFcy7KeTFDdRrnsClOWflVCVHRwVTqf5yKo4C29gnFRvzv+mLp/y4dU35fAlPLgV\nvHlRwU2HNj169LgmOsDp8dzjFsDj7vF41TlHVTn3ocY5CnFqPxybX++Js6XCkS5UuYzKplMbGUti\nwfAtww3asP7ypDed2cBYOlBN0XnMhJAgDpNaSDb8a+qbYfMjyCVUSPDGbnzTd3e0qMUTWgjI0fv2\nIhEInBMK/8Tbl1F5dU2a5oYK576jVvuU8+/LFIbyNbIfjiyDlSzkJ95p+ZANXa10QaaDUrmA7MVi\nSfEQXBkVXCmbS5D9iwLggDFq1UIy3iWDhvovQNtvS6vrmRkjk3RTQsQMUeVIG+eTQpwZZ3qGgU+i\ntCJRXBGegsKAiaVVObkn/wAQ45SWPZ9rcqewiCkl0RxlX7GxvOrNJ1O1H0hSRSW1VFZX2LiFggdh\nMZ28/RtP7jl3nDO/n5aPhvcBsqjLMerwT/qzEsfAjcCuYh61RGoIr6n65oQxvCYdo+iJKm/EjHik\n12WAw6atyeBmzdvmRCGV9mWlGFy5XwkXh7X9s15WBx6ZpLyPWE53dl7MRjkZ4uR1ZUm8bCkpAw1J\nhQOaC6A8FypCLaPiDDli2idUhWPAHscg8C2jBW+8+sabF6flqcqn/N+lB06l5ttm+AD0+gIrv/UK\nUPlHMHN71m3BSTEKIJdQadg1bI5mVBy0E1VW3+SHHfZgwz/8sHK7rHSVefSNBEplbN1tant5l8cv\nkM8Hl8Kb+1DdXApQXgxo87iAjZx7e7HO8urTo8f10QFOjwePx6HSuX91zqXLdCnI2f6NdTXOpRBn\n67utz1oqnNQSm7KpsffBaRkZs5ZHpSeJ0RQQuoTMqFU4Qf/J4gvEYcoKnPpmOJnYxtL7RhKd0v+G\nOZdUxTQP2yCnXltmhJleVz44a92oZswKS5Y3ai2lzV3UN2tRb98aKtXlUntPwxfTd2vB+04AWbFk\nr0l9WAKVMKeGNz4xNpCTk+Ryw+VtSynJmUn2RUtkZzaPHGAg2f8GIgU4jIlYu6MxzlFQx8wRZw4Y\nEDFi0PbXo5jL0skpGIAQ5Gk6AEx6CBMCcuekKW0DM4wtyl64WucKMvIythOsBUCsyt5k2FCMG3Bs\n+9a+GC3gUgxfOQ+u+Zr47ycYpOBmea4MWiI1FvBmIGn1bQDHWn9bFykACdxYJ6ktcHNyZVKnUO6b\nAXkfbe2b9X6ZltOdeyi9l/+bRbwBGiZT6Wh3Ixgs4KYKJ/vlCLxZrHstn6rfS3nelNZvAfzvAG/W\n9qdSSbaiMNvYF/1+3iyfqvxvgNIDJ08H7vMctcE0qs8iIZdP6V/W7mGANk0Ep9+MAHz3KcCuWw7e\nsHWbEvXNlN5r23BkxZY1BJiiPbzI5Y3ye0v/G/nN2andltC1BWZapVP1OPXvbI2zN/yxgZtXBdo8\nP++eHj1e7egAp8ejjIdV6dyPOueYYqbxvYMgx35jG+IANUZozdcWxGn54fhxfClVpDKxy9OfF2VU\nxY1vw8h4jnJzy9VTRLsxnlXxMFBW4QQO2v43JojDLMoXAzl5nnJCZPBmjmU5VQZIlYydy9tFK/lq\nhbWaJfd4moiKZDsovJkx7ZZRyQD9XkOFc9/h4dAyiWon3cWw6kk30N5nZHgGXmkY5V8pVAumaEAJ\nbwzmWHJcl1PlsKfepsSRfcqSHkA7t0Bg4kAlyBEfJsagipyBTJEjyzBwlDI/w1QUcOZnBeiMtmT6\nxyCO7WySdE2V8knUOIUSym2jpaolQ9NyONJ30+sD27OMI+rAJayxYS2QhOL1EjYtyqoa8MbmzaDU\nGrwZ6QkCTjjR63DiJ6krGoBkTCwaHIE2px3FzSmUUNGX+RGgxsW8UN7UJX6ynJzGCUSYdB/Mn8CV\n3YkXWFCQY/tvUDw0V3ihBSn8Oi6GOWhj24PYlH+yP26B/lvHKuxx6jE/XvuclBWB5n9TmBcjqzuJ\n2uvKwhROAJedn9SriA0KQ/xv6vMbKVyTeW1Mv7pW+bIp2dYZ3qSHGzGrWFNZ8kYHqpaJMbCthiuV\nOtu+N+X6qtV6D6e6edzQ5uGBTYc1PXo8XHSA0+OFiIdV6dxWnXOtKud2pVXH1Dj1dLYgjo1XQ5x6\nHro3owAA/IBJREFUWpacEkn51ODmw7wxIubixrF4MmhPEU0RwblUYGJogp2VOIEBiiTqG4U4TPmm\nuL4htpth60hlChy7MS46eqBKqHjtWfl6WCcqM6n0HjiWOMwpmWuXUbWnW0KV51FGtRb3dZzW245c\n0uuTKnKAxsCNJM2clA6Ag0BuuqksiaBeFbLNbXsNChMpSIvmoOVwHuQEEkUXMSOAFSxKF7SzbXeW\njlAe3oCBiQApTBGz3zEIxDEvEjkexwLi+GVYU617eLMdM0rPmY1pJAhT/mhKSNN+cBwCyW8Pqtoz\nSGWfVSqPFhBagTemKEqGxa5sysMbK5k68ROc8FpS3AAozIlPCBgpYAy5o5T53JxCWSp1CiW4GS7Y\nHwvIDd0Xdd8MRLkMx22DAD1Xwk+HCmgj7/20717ukPdHRxxXx7mfqOGeDdsqn6Lqn30/l4qtQ5st\nlmNVbLbdvALHtvvMy3UVIMooAADL2RwwKIR0rbIHDQZvTH0jr/P1aeY8D1YSWneg8i50kcREHAAK\n02IHXffUN3WsjXN3ePPw4Ob+9ucObF702Hqw16PHpdEBTo8XNh4G6twPzHn+IGddjbNVUrUGcbbm\noaXCkemYSie3E7ebRplDLv6xKW60dr9uI578SBTcTEygCFCgXEIFcd0JmozXTzvtZliml0umvP+N\nlU+ZKkOWx5XbYD8tBtrlVOkfh5S0envjVhmVzPfsphM2n4xux1y9PraP3yURS8oPN89RoUX9+xGc\nuk8lOFFDOPfa+1J47Y4luKbeSa2v6wTM2ANL0s2snXpUuWUwJzBhsP2SgHOEtAHW8pazTmMmATCk\nT8nlJ04gnvOMVxAn0ycAERgogsl7Ukxg3lY6FItEAUv4uv2d9rbdVtAsfnelxOWuZrRrPjv190tF\nkrYG992mvOqGTgjaUt3gjXWVeg2mwBmbqpu1cikBOd6rCWpgnMGN7YurfipOiRMMCJiapno9byQK\nZZtoXrzPr8vt2i5tWU8s7xvQ2G8cG6/yZ9oonwIAM+Wur13JE8d1CltX8Umwbiu7doDU44ZZr4+5\nFK6+Jtn1Kk3LfWwPGVhLqFpdp7wCxx5+2LUyApjjsgOVGRjL75f+N3X5VCuig6a1+uYu8OZa1c19\ng5v72ccfDth0UNOjx+OPDnB6vFTxfEuvWhfY66DONaqcS0DOJWqcvZKqvXKqPRVO8r2pyqhAIyLP\n+sSvNDK27ir+5nOKYh6by1nkBvUcVfXAOpfWQlwhDpmSoroxlrXRfqo5O5AzpQ4eVHrfpOUs/7Zi\nYWjcGkeVONZOvA5KpVX6JDkpE2I1zt1uBI+AuqPfZ46SyNhfzABO6W+kCFLzZUCSClLoRmAMQEoy\nDOREB1fqLMo+87FmDOuTsFAkSTp9/RK5EipJvKXN7xRtCANB1TgRCEGGBQWLumCatQ0Az4C29q4h\nTiR9qk0KOGkGhxlmS8wxZsNitgmnJZJJVf41rdKRZWnU8jy28LSq4sh+1pruXuxNt04M/T7m10te\n3qy+IYQEb/y/EU9S2ZQpbwzenPS2yeBNAjghK2+ss9SoypuRDNaUiptUzocMbtb2QVnW/Fl0A2pg\nUz/l9VusMF4vYA1gpTqWxMtr/Us+2a6VWe1tdKtEcOsctPbZlvpmq3wKAEIy6h6SKnLPB6c5byiV\nN3l47j41s25/LLcjg9L1Sua3LN+16xRDFDfmdVOAm1hDHXuvZcmwByKlgXFE2S2uDu9h1VLfyGeX\nw5tbqm5eLHDTgc2rEN3Lucet4nnVoPTo0aNHjx49evTo0aNHjx49evS4MroCp8dLHc/fDPnuJVaX\nllX5p0drapxblFNtqXBs2rUKxz73ZVQMKRepfXCkbCYvk+9ENXHEHAPmwEkybvX8XoGT2qRGMYMM\nOkHzLEGEGnmWTzbTmuBcEmVmxbN7wjkzIXf9cAoc5PIqAIUyZ+uBS0h1MrmEquhCVBkZpya/zgfH\n1lcdtylfyGVUWVnVLrM7GlkhMUNcYWZECog8F/4UosaJ6u0hhWFieC3bLmoZEwFJoSNPvMXfiKUG\nTfYVghYIUFOV46P2IAnu6bl5jqRxYZ/JByGVVHGltqH8KD744UgqHFkXAZGlP1WkiJFPor7hGYwT\nZppAnMs8mOTzgFFLqfK81R3A8uvcPapWI2RPkFK9cI1y5toolR2Vuqby4LDhVrLBPOv6ysWXMq58\np14nIZyyH477b6CTtgnPnaZes15Tum621DemvPGeN6a+MaNi3xmtpbwpdhPKJTayHspY81UolIH6\nntM/Tq+z9wkX5938Wr3JdNuU6gu/Ddqt39diexzb1vez763735QGxnX47ndrUXcjFHWTljypaTEh\nb9MZ+fo0Bq/CEW8jKxOm6vF9fZ3K5VKlaXFuG26d83R/QLsDlesBqf+ykqYoj1pR5uxt+0vUN/fp\nd3ON8uZFV910tU2PHi9HdIDT44YR0a4EfzxCr+frm3M3mHOtP85WSdU+yLkO4qx9py6jWs5r7YPj\nkoVGJypmqdmfAiUfnFnvlGdt32xmxoGBc0qipYyK5RfV9FNugIs1kMALpZvjLE9XUAMUn8lyUkqQ\nrAyrlMyvh2tGlcKbGQft0lWHfD7rNALA+Yb0Lj44rXK+NYPrvemIt4oAPZPaS8cxARaAuRKVppkz\nn3UNCNazMqpJUU2AyP5l6rIPhCDdVUgTINJyhKBlT+IvYaUKgntqIGOx9CeyFVJCnIjsRSIb0QCR\nlEgMhEx5HMSJhAQPpZwvKAQcMOrePiNgwEmPiDOIpFG1lVEBQIwRgQTeGJQovF4gPi8GboikZMhg\njYc6BnMI9nrI0/BlKPeUUFuS6H1X2AEDK9PI8CC3Lw6uhCMiIsZzCXJc+Y+tE/G5CYvyKbEklvbR\nI49QjJPgjZXuDWpWPFiXqYBUOmX/RjoOb2pwY5EhYQ4DMbKe3DAYqPSgRs6ZAp0z1prYp+e5+9Ck\n6ysiYqLJJfEOiKUU37dp99uyKNpqb+9GEp+HXefFZdECkB5Y1v43xXcTyFGIzhntHIl6aZNxKWWI\nJg80CFY1GWHt3IEpUoI4VmplUZ+r/HXKw5t2+VQJcaQTle4vVQeqBOWcgbEsS9v/5pLyqaPw5j79\nbh4O3HRg8yqH3T8+pugVXS9udIDT4zlE65T1eKHO/QCd62HOpf44R7xx1kHOUo1ziRKnGA8NFY7z\n+DCfHBTfyUbG5VNgTURSh6nsgzPpTa2Am6zCCfqPYCYEAQOJ4YAwE+0g5C5h2Yy4fLrJQHFjnNuJ\n57VmBsamDvLT2wuCdDYhNnCjYKZInEsjY0Z0fkLl9twCletPOeeVm72lCmctWmow/7Q2JdU6/wIm\nApgDZjon9ZGsgyl5wYAskYryNJpCeho9gxOsSdCGS6gTwlKFY0lzCWGWQpk6arNY+77ga8YYypbO\ngCRsBOlGxNrqnvW7Awn0k6fzosCZeMagKpyZzxjoBOYZsxqtEmeDVaZBlVljCW9Sp6VTAW4CnUCq\nMiESSEQ0pP0r4ISQ3i/VCKE6f+15cO1FVnC4p/wk2Io1gTTMYFAXgK6Pc4Y2LK+JzwghYOZJvqNw\nyx8jhSqpUt8EGpL6xroPWQI/gjDq+h2IEoQx02KDNQEKbwKKzmfWItx8b2rz2y19pKybcng2Vs/n\nI+suNOk+mVrdczaCN+NaOZ/GBG5m7QAYwZhpgqlvJjoj6vq2dS/re4b3P0mgNiX0+2qcbXjjxrPP\n9bAiVddde70uPaCOGRhbODelah7da2RYA9gxLqrPWbtJTQqcKS0YMBJjUh83d1rSaeZ32RcpAxy7\nRp1VLXou1De5fbg96GD1wak7UKWHJxVUTb/ttplXxdXqm9vDm+cHbm4HPp4ftOmwpkePVyc6wOnx\nQLF2oXl4sHP/QOfuMOeWIOeIGmcP4tjvZONQ19qX2yUYNo5oK8TI2EppaiPjiGyyaE+f5yhdfZYl\nVHJzSozchcrdCksFD4n5LMmcG8TxAMfAjYEZD20saTJpe+5OVSZW9pn/ezR8J6qWkTFpGVVa9xs3\np1ufL4dniFcbENflcevTgNv2CrWSImLGbG2vEfT1oCqbc95UHvZxwEwTwKNNHCG11o2pxS+xfFFA\noZlUSzeovEvbDxjGg9VhYQi5tMFypaNHvyVcpvqxp+sMSeYN7A2kQIfk6GfSsittJy+gYMCMGWVb\n42yoGj2kUcjgMz2vrPHgJtCIISlNZNiADHQCBF4E9kAnJIDTMnK1dZ+Hb6+xOhkUtQenz7y6I7+f\nFSjMmPmcvhcgSpuZzxAdjgDByGcgQtZTVPDoVBel4shAzgDCgCEpcPJ/Mg4paM3LL7CG9HwCGUe3\nrbWvt+5ntXl2q/OXP+vaWvIGxvbaymBMpTFFO/9xMnP3aospmuKCMUc5l545YuaICQJxZsyYMGMm\neTVhwowzZlXhRJzTcT7jrNBsKgBajFOCOMBSlVHH8rxh6o76ocUxFU7bzHjZfWqrfMobGAMoIJ4M\nb0N5brxmPcekawPJ9YTASYXjy6WQfiNvb6+6KQBeuq7oAwWUZsUGcVJZMZddqAzm2bWV5czszKsz\nUC3L5DKQX4tanbNcV7eDN48T3DwfaPNiABubx6716NHjltEBTo9HFo9PrXO/QOe6Ov9bgpxtNc6y\nbGatrMaPV5dypFIIp8IhGlCXUQU3v3bjOGGWp8SkyUewJIXwGnwbcU4qnElLqEKxGPZr5Q2yzk21\nzryihhKUqduypmfGBnf0aagl6wuI09wCywgg7UAV0h5S++BYgg8gtxTnSgVTrf/LQlZcLoUaSjDX\niMUNZfG0PJezMEfEOKkaKgi4sfGBJsRhHnVYhjjy2QBEldmkv7rxbYdLvXrRhDhsvx1lXr3Kps7X\n9kBcUnzVw01twVmRwWwJv3apQvZCsnbygaScJ5VBGbCBbN/AosLxP+vhTSoX0nbZA04J3Az6N3DA\nwCcMGDHymGDNwAYyDFTkRBZwEKdBI+pEN1Y38Knjke98ZMiGFdvQrH8nRI6YVScCADMpYGCFNgpi\nZp5sBoA4AeEE88eReR2cF86QwI0vmyGFVsW2gEI2S7IdqEllUPZvRXjXGm6bzZL1NXDDXH62Bm/O\n0YMbUXlMBm30rylvDN6cFdckeEMZ3tg6njFleMaqeLKytnhOx3eMEwzeHE2cTQGYX5efXXPN3eo+\nVX9eR2BT4lz+uy1wb0ocZlnK3CXRHhmUJz7Pm1vQxsasr1EtcOO94QwwR85gz7xvymK5pf+N/GZZ\nPuXVV2vqm/S+AX724c0OALwYEF4/rf24f2jz+IHNY5+/Bw49jz+qeGzz0+NwdIDT4wWIxwV17gfo\nXKfKuWRejoCcS0uqDnnirA6fFTjkMipfTlH74IjUP6Qnh6kcwD2VtptVYgZZ0q6LwUH8b+R3WktW\nLrUHN16mnhQ4nJ+ecvpOfp2VOvqb7kK5BQEM3uT3YmRch7r5LIebATIv1Q5b4UseTNkjeYWtIXkK\n3tpPyv3QP32FAzEREVPKTIgCiHVYuWD6Zf/d/FpMQAe8Bj/eMYiTTKsriGN7RUqaOCfmUmbnltW9\n9on1UYUVqSSJ3MIFEIhYFUQ6HmeFiCWUphJI/jQ8gMgdX1yqCtbgzYgnGOiEkRXkKLgR017xfAmq\nR5F5y3iDEsDIMMPzm01zV7f27HgwYGPOG96LY2ZBNpFPBVwAgMBORaPqPcGzH/UzA1Lwk9d/6YVS\nl08V67qAOLadymVK3jWN4UvPkmygbfuNqbWAsoW0je/3L3bDc4LOydPElDcCbNCEN6a8OXNMZVMe\n3jyjZw14I3+jAhx7HeOkpWpl2ZQvp/KxZ36e3/vht7/WZ5P4rMYBAA/x8q/v/34N6FPrcIaUbiaI\no+obVeHMi5OdXT8Y5pHTWhNJ07DxcGFy+0hRRmX7i6luFOjZMZe0b1q+aObUaVnR3rZI8zTnhzBV\n6dSt4M2twM1jhTYd1PTo0WMvOsDp8YLG2gXk+YOd2wOd+y2x2gI5l6hxak8VX15zRIXjwY8vo2Ja\n98Gxm80pEuZgZVRy92w3p2eWUpqAXEojPyyPuO1JN3GZPPkltdG9WbEHOEmB40qoZnczbd/xT8/h\npnsk/PbxRsbmewK335Gqcy6N5nf8MKk3Q+01sf5b9VN0VfGkXmOjU+Cc1w/XKq+REg0BeiMigNfw\nTNfjKBQwl8uQSG1YM+2oNVLRNnjUhJgUBql3ifzl8um3/kar3AVYJtd+XzkaViCSFl29kPLnut0d\nXMjjZsAjZVkuMTWFCUKCNyM9QVDlzYmfyDCMOPFrCdyIVbKUDI1aADRSEKCFsoQolQVRLv0o5y+v\nJx85AWVVrnFSArBCOlGIBJxY/Vl4xqRzB0Bhg0IWGrJhOb0OHuJEnMX8Wc8m9bqpo2Vs24qW6qhY\nRgV/gzv9DJT3E+h50LybfGS4Ve5bc3G+cf420StvTIkj/iZnLZsScONLp0R5M5Opb8qyKQ9vogIb\nU+BY6dTMUwI5MkxLqkwFVV3L9s4beamLNZmAqq2bo9fYvfIpP17LzPiayObSAmqS+gZaXglbWgO4\nS/WNfWIgx6LGBb6U11+XTIUzMXCuPOMM9kX31/vf5FcZxBSeNxvqm1bp1Lrn2vK1W7KVdfsYwM3t\noc3jBTaPdb569OjRAU6PlyweXq1zW6BzfyVWeyDnEohTT7duN930TVE4YGbGjLBI1msfHGb/5FBK\npQa9YRbjWCBE8cYJgLYPl1viCOERlkTZJ7aGpS9RvlmuzUFLs8j8dBMoFUG+fColXzCFzgWZfSME\nS+UbyLT+Wdf5gRuuI+OZaohQJ6lbXhQe3vgbdC2hQgB4QvS7UblLVfMwIyjsGei0UONEvXyZQuvE\n0r+JwYhRWq1HljbOzNLamSEmwzEidYLiIEtLTIhqTCuAj4vSmFYsylwS8Mvbf7FcB/eBdQNV12rd\nVgeFpLgyQOE9b0x5U8Ob1/g1DJA22SNC6rQ0gqTjEmWfFzHsLQFOep1Kt1x5ldt16vVg+5e0fPcA\nRwx2RX1DGFhsiAnZH2iy8hbZqTBp6SDodQniME4KHmcEOsFK9AwcF6U0zv9mDejswRpbxlZ7em+c\nHbQ7mSm7TIHjKbLfp+y9Jeg2rKW6MXPiBG+YpYQq/Y04Iya/m2eYqpIpgTYTqdoGuWzK4I2BGXm/\nBW9KQ/RtH5vGecNfQ+/4QGSrfGrt+nhUhRMdgBFQLyc7U9yIcbps89QhT9V2qYwXgEkD5bzB2iWv\nPOUtfru6PtkDhGxgLB2tvDJ10vlI7cSR/W8iWPyoKMMbdhDHxxFT6rXh2/DmOtXN/YKbVwHYPLb5\neTmjvDPq0eNu0QFOj1cgHhbqLG9kr4m7lVhdA3La313PuPc8ceT1UoXjP/ctpfNNZPbBkXKKIDeh\nIT9NBICJGCESKDDIMqPkAplvhyNT0bo3J5olvLG/6SYZACu8YbibbwARlAwiSxUOu5IrlK9hCcB6\neA+c9mflp7I+r7nh3PuOPQVfS8Qa/hWuDEuYxRmgk2xfXzrV2KUiIgYaAYYqdqyk7qRJ5YgTPdHf\nHLWsKoIxIvKAEyQROoWAGEn/5kR6IOAUcieoGcDgQI7BisSLrGV5oyQGqEFf3vYMfcoNBXtucyeI\nsbrG3Xlj5Zizkio7hn1pkIEJ6UKl5rw0pLKpGt6cMKY22acQEriRNtlq2ht8CVVpzFurcVqRfW98\nwqogB5JcDoP6g0TGQAJyKMZk8kwpyYcrq4v6V/xuAp0QFfzNfBbVRTVbtn72QspFwkImY8m6BzdR\nZ0mb3RXuIQOJX01OzmVdmOk1UO5P9j773XACxkmBs6K62SuZOtN5U3XDVlhVwZtcQjUVvjdJiVHA\nG9t//Tn+gBnxgeR2qxvepddYK5IDkPym0me8Py07tn0ZVUQF8ckNgymp3DVJ5jwpbjzI8ftH+s3G\n9al+sJDeqzrL1DdT2l84QZxJt7i8VtNqU9q41uH2KEWGH1ffXAtvbqG4uR6W3BbcPB5o81jmo0eP\nHneJDnB6vKLxMFDnoWDOkd9d9apZgJmccdefeZPbupTK1DbLaQ9YK6OqfXB8zf4UCWOQG1LAWohr\nQmT/1IggEmnJjHQE8jfKdStxWRcugYKAGwMzc2ornksazCAyqXBWyqfa22b78yNRth4fFJrc6EaN\n44VPwd1NOhjgWVOTEcDZ7T1W1jL5XUqUN5C22UymLDohkBinBpxSog4AM51wwmuIOr0TnwTe0ACO\n+pejABtNtk2NMxAwsJZQIYMcYlFxpe5C+rf2KElLXIGbQoWDDHE83MulQ1ldxvp+YQC6c9O9UJSg\n7CJl3h7idyNlU9nvJsObk1PdjPp3oAxuxpA5iHVdCshsI6R5aM8nWwkQ8n5vqhuGbIeZRUUXgoBR\n8zQKuTZF/wRA4d2oieXIpwT8pNTQ1kXM+TIAulDRaCHbKVMrr7YTU2pOx/4EucHyEIfceQGuBM3v\nV0uvG07fSYq/CtxM0ZeXlqqbGYwzzxepbqxFu6lszLTYDKJjNKAzSecpNhXOWbZogrcBmzK759St\nx4cvMyyGX7lP+FiAepIHBrN53uiqMPXNZL9MYsCffW/y9Qlon3cM4szVtWnmqmwqwZxSfTNHpI5k\nyXPK4I0BUZTmxL58qhUtj5tjCp7bqHyOfn89brc/Pjyweejf79Gjx31GBzg9bhdszx9d3LRj033H\n84U6t4c5wBGgs6XK2VLjbEEcP701iJOnlVU4g5UEMVSuXZZR1T44kwM4s92QarZofjjnqC3C0yyW\ntTcMTioLUQG5zK5Y5pxs5oScUulDXUJl5QxREypfPmWKG4Ym+Jqo5/V+GcWpS6nuHgPudsM3IO+L\nlrTlUO2LJu32FHfSvWgsII50VRIVBSMKzEGE9BkKqawqt7uVfWWgE2ZN5QcewDxixoAIgTQRIYGJ\nqL4RAxHGUIKciQXyiYkxJ68kbzDcihrc5JIg219yiYskTTnZszKi5TRjocTZi9xZKSB3W8rqm9QO\nXM15zfPGlDcGbESBgwxzFNwMgQpIY/Am0D68AUpoA7eeQqAEcgJRUrHM8qFAHAD+fBx5SNs6Ykyl\nH7kdtKhwgqbDuQfdZZFdQewoYf197SBmyphkmi7nkwElxJGh+Ugn0CIxz6Vl5X40cYbDgKwXAzq5\nsxQKrxuvuvFeN2d6tgA3zDF73cBgzVnBuZZJQX2rgCa8kaV08AY4AH/9eeN2sa5Yu2z7R4oY2NRw\nbt9DhnnMnDxuGNYVKh/bM9TrCNl7zcBN1qGZpbkZqbuHC9Q4LzSuTbUC52zKmwXMyfDYDMQnu87q\nMeTVr/I7DTCzo75ZzvO61vDYePcFbl4GaNNhzQsRXN739ehxl+gAp8f9xtoF7YUBO/X838983wbm\nAJd45uyBnEsgTvvzxu9VKpw8D3l+izIqUqNMSCJyYtZyGXvinJMgayFOEB8ANQUB9Em+3XSP1c0y\nmDZKY+x9fnIuAIfSjbCNb4DGFDqWZKUSCPc+iQlc4p7KS1wif0nyXoe0Fd9XbuzedC626fq+tTk9\n3f7ALIoFjIBuWQ9xWFtlM0eEMEqiQCEDHAi8MUPV3A57AvMTNToWNc7AIyIzRgRwZAwUMBMhcsAQ\nkEp0PMghouShRKrYkmXj1fbQgNtn2CVWaX8xlUmpvrF9MrfOzu8NUB2N2uPDOuysq2/G1GUqABgp\nOOVNCW/sPVEuFwoVwJHfzZ9triN9HSDcg3Q9hUAKbfQDHdsMqZmBwdRxFBLEyVqj3HLd/vMqnO3k\nsDRPZ93PoL9h28hMZWeISbopbkxtkZdQzzNcQq68vpY38v7c4OGfeX+lc51T3GQwaCVToqMw1c2k\nJVO7JsUGa/SvqW7MrJh5RvbAmXK7cJlTWbccE4Qi0EXnjhQHzlsPGRFcLMWyPFYVn7DyODnHSDlU\nuc0F7gkEGsg0WnJtmqHHkwPHVhUMlNem+qFC2Uoe+WFHsa/ocL0SzjTn/R7qf+PKp+Q3bXhDMeOO\nr+OlU7eBNw8FbR4G2DzeY6NHjx7PLzrA6fEwsXXhe9Rw5/5VOrcxQT5eZrVlRgwsgcsRiLOlwmHE\ndPfpVTiMgLqMyp4GzjQh8km70UTMHMDWElVX10yEcwQosBiems9AMYtys0wkBsfmhbNWGpMSblhi\nbqar+Ukm4GTpqRsIpyeoPqEvEjQHb2L6PXeju3XDei9PIrciHNgP5Wm6bH8IrHMJnZ8vK5szVY6H\nOIQIYum0FaNCmwrkRD4j0EmmV3jkzBj5hJlOiIgYMCNyxIwBE2vDbCbMxDhxSOVBHuQEkmTKfHA8\nzAEOwIlif8ngzvaXOvHmtL+IasKnUKl80LX03YN6fjt5w+M0rGiNbWbFucuUNy1uwRtbfntt/jfe\nG2d13mwfgBQpMmW/GBluY2WIY2Vv5jUT7XeYiuUI2nY9aFeqyGcBwwr6SNV97a44M0ByOxStSxpF\nWHeeAPHBmUm0PDaXk9+1FRpHlh0mMmMIzoyWlUlxex219h+DwIyciANAC9xsmRSvtQZfAzeMOalu\nPMgxgGMeN9aNynveLI3P7dyxdh26HxXOrULOI0M6V5sKK+rDhMGpbvw5fo4iHpv1ocIUsXSshpVT\nyXC7VM3u2uTDrlMZ3vh9hUpDa/Z+OLXZtd937JyzbB9eK2zW1DdbpVN3gTe7ZvsXXeNeNGjzEoEa\njvnG5xUOu598TPHIZqfHBdEBTo/HFy+caud+oc7d1Tn7qpxL1DhtiAPUvjg1xGl/txy/LqOa+YwR\nkozPNOuNo0uCoyTYQPbO0BQDAKUbZus6FElMRAfoU05e+nf4JZL5K8FNkqzHPF4yjYwuUY/+Blt+\ny8qnsgQfyC1cDebE9PraOHqTuTbeMglrjNPYjotSKoU48gU//oxsbmrreJJUnK3N8xLkEAXtlCIg\nB4CUe9AJA4lfx6yKnFRWRVNqk21lVYPCkhMNWjolICeAK88XzoCi0Sq71SbbtrfMW94fzKQ3Ypl8\nSxmDPd/OyZP8l0sadreJa5FcgBxXPpWGJfjhXmvpGBm0gSy3hzdegTNU4GZLgWMAxukzEsiZITcj\nE2QaBEpdwAatoNIO8ApmUcy37TMVmgIwSTmVYODNdedL8aLbBjNNCAqPpeypPN+VE5EOQ4iyLjmW\n+0/YOKwTxK2gTb3fAEtw431uJkRR3DifmzM9PQxusuImJ+cGb3wCn88djfWa9r0S3rTPGUifWYnl\nkdhSfG6ZHK9ODzOi248KKKFKLJk7TtcPgXKixPJlVDMzSFU4xKLWAmT714cG6xJH+5xQ/Xr72tS6\nLnl4c46kJVScFTluv7HzjhgXe/VZfs3Iqhy/3pvrz4Oae4Y3zxPcPB9g8xLAmkesmuvR42WMDnB6\nvDjxQql21m6/7hZ3gznXg5x9iAPUahw/nqluWiocOJNjU+HUZVTWTtwUOBNIW4j7pEZKMIj1qb49\n8nZPPZk1IWQBOWZZQdS+zbObYyCDmzIp19928CZ398g30964lp3yQvQpBm4yxAGgfgSlkbO/qY0r\nr/e8cY6AgPVoJ2I2zCBOATaSkSnglTx1SV3at91DalPpGMjxaq5I2hqaTkmVYyDHPHIG7VhlZVUz\nZum6xEFUOWCMrCoUK6UiwsCSiOcn4eqrVJUK1eGfjNtfn4B7VUWdgDPnTjAzZf8nv919UmXvt8La\nY8s8O8DR6K5DBhmQW6lb2U9ABjZ+HWSTZ9261IY39plfL/Je1qslsQGyzzCgLZgVzEJblqt6DhBP\nIiKBN2ttnveSeAEUAZGiKiHkeFOdl743F52ImV1ZEC/Pd4YwfdkUpfWZlTuL+bDvO9iXlHz6d9LX\nAIr9ZmbxuJkUNrV8biZ+uupxUyhsUKoqDNT413lJ6+Q2uIWT9bIFb2zYEvzigjKq9WtOK1g9kuSb\nEQPc9aixr9jWh1PgmBpLyqTEB8crcKaos68QH0ENriHnE8DMiWUbm99WcQzIxTDt6/UZ3ZfZ+QcK\nWWVD+VoUsTQv5lQMhRlzu32460Ll15+tly31zWK9XwBvbqO6eezQ5gWFHR3S9OjxaKIDnB4vRzxq\nuFPP223m5/pSq2Mg5y4QZ7UsqwGIImJqKS7jzNKFypVReW+KCREnhEKFAwBnmOmsPumWx/VAJO1C\nJaUxMZZeFCQLByAnn17matDGbpqtjbh1/UB67Uob9EZZzCyz+maufE7M98Q6D5n3yVaZjNw8N9p2\nN96vrf/DceGxk7chYOVU+b3f7kMBciRRKcEOc1V+x5OAG2SDXgAYKCLSOYGcnJackj8OcxS4gxEz\nJpxwwsBjAjmDAzmztc9O5VQCcxJEwHaZEFCVylXgJoJTYu6TcC1YkXJBREyUO8JE9aK4rkV8G2QQ\nggAQXa7g0IJXYJkiJ6TPynXQgjd1VzekccjBmwxxCKxdnIS5GhwCZ1cQU9zMa9NG9sFZW+atyClt\nTGVUE00gDphpAni0EXUhDTLkfXwgAU9SopnX22Xld0vQZ/uMqX8m3WdMcWPgZqYJZzwrDIpFlVa2\nBDdzYoMyrYS8DW/cZ+kcNaiKLq8Lf5z798X140ZJbA1+966D9bXJSqT8fEWKIJ4x6C1yhNkTA4pw\npJRKy6gIooaZVTVmKhxAHijMadXIsMgAAqXjxMAlkfnmlNel5nIgn2fsYUHRiUoN0w3qTIVqqyyf\nEp3WpKXKZfmUX8clxCvX6Vrp1K3gzX2Cmw5sNDqguddgbB7SPXpcFB3g9Hj549GVZN0/0DkGc7ZB\nzhrEAUrVxB7EWSul8koLU+Ew8ndMgcKImpCI+SqzdKMa9EZ00EyZVDZOlGYhQxzkJ5+De96awYKu\nEQ9u3Gv/pFP+UoI2AJAVFf4pp1PjOKBj6hu2J+3FP4U4yMtuqoC4MJT0nT+WT0JbT9OX28ni+I1v\nvb1bSVkuh5Bpl98Zmt+1+S6MkMkNd/uUqXIASKtxCgnkRC2bGnBGxAkzpCRmoFPyx5kwYcTYBDmB\nxfJ2rH1hiDfLqGQ+82sDcwAW4CbCkickeGOGsx7izOJqkvaHlifFmuJqq+POmmKlHkpUEgcPIExZ\nYsNb8KYGogJq6LAPgP0c+XPFgQgYMOO8OY6dg7zvVqSAmc8gCphxBsHgjc4Mu1smU5dxVCWRdDcL\nnIGflaSBHQBr7C8xvS+hjYd8ts8AaIIbMyg+09ND4MaXScnitE1o18ssvafQgHJXWQc3/vv+fH/r\nqL3WiocEkI5kcj4ZwDwj6nnFn5/ME4Y4IpDBerGtnjkikDxICCDpoBYoqXAQMpDRiSWIQ7LjIZB6\nJCn4sY539XVpsWxcKkNnvSbVKtCzez8lJc4S3uyVT/lzzNZ15Si8OVoy9eJCm0cOQjqo6dHjhY8O\ncHq8utG6iD0I1Lk90LkM5qyDnCMlVVu/1YI4raekpsJhymbGVtIw81k9TbICZ2BpGDxz7uwhZVPZ\nLDK1EY/iUxC1u04kTazYlcSsJIfp3tuekCu4yTfNOUH38MaeVfsuIJbA2y3xpAk8u2Gmvtkqn7Jk\n3tabX9drHULqbbLuTVCPHFePia2kDKjLI9w4VVK327nMXrtkz5cASavsUIAcpij7EmkBDMXCH6cG\nOdKVacDI0lZ7RMAZESOTggpKChyvxAFK5YqFlVsYrPGvDdzk15zgjZnOWjIetduW+HOci6SqXk93\n6153+9hTKdXjrhmJ33f4MipCqcKxTmcJNlcQJzKDVck0MiWQkyCOGqlnn61ypbT2E/MmYYgvEjMn\nwJfGaYAbMyie+KOr4MYbE9cJeCsRXwsPXVrHed0R7e4RC6jBK0obD21WFaC6LRmzqr3Uj8ugReWD\nY2VUMZVeZbv9CLmO1CocQLyaZpOZ5cUQ434tGxxgijQzu1bze2wrcPx1yT9M8A8SDN5M0TxwSvXN\nhO3yqbSPcHsfWazXxutiwVc+X9vX9gHL5eDm/qDNIwQiHdL06PFSRwc4PXr4eBRQ57ZAZw3CLGMb\n5OyVVJXj+dKCEuL4eVpT4TDaZVTWjSpqcmMqHEA8MUJ0Wpvkemrzy/q00/uarJd9MHJ5lP3NCpxs\nNApkaGPKG3ldep3UXYhMfZOTs331jZVPGajxT89tve55WdTbMEdM+z/bU+IrooY4a+OUnx/bx2uZ\nvk1LPHIiAo3ifZPUOBNCUuUsjY4N5AwY1SNHQM6MQRIwbbNNsE5Htt/kddMCOEBOyGPa1hK+0xQr\nkBTFDSfjWdvXZ0jyPaNKvNN6mIvkisiXgswATivz1r65r3EbW12Hfc7ZxJgT0cifFblqI/nktXW1\nk6jyyufXRlIU6CK0VDh6InHnpzy+zHPAqHq+gQc5YhTeBMh5BpDkHGz7SbkgrX0kKrQxsGcqCYN7\nABApbrYEl/eyr9eKG3sv63V5PBXraXE9tOM0KzENrLbCXx8W5/6jsQKR88MAr1gpS3z9KjcVjoxn\nXfCGpPaUatsA771GLJ45psIBkEyt11Q4CLLUVkJVHxg2h3ItkRJNu66guibJkLzPcHW81dcke4Cw\n7EbF1b+YwOBa+dRR9c3aPpS382Xw5taqm/uBNo8IjnRQ88KE+WT16HGL6ABnI37t134N73//+/F/\n/s//wQc/+EEwMz7xEz8Rn/VZn4VP/dRPvfnv/eIv/iJ+4Ad+AB/4wAfw5MkTfOqnfire/OY347XX\nXnuu0+hRxYNDndsAnctAzv1AnLXvAOZFkFuKt8qoBoySyPCsZS8x+dCEyAhB1TSuX691oBqpfPpp\nDgTW5hWN5HKpwOHyplmHT/rabpa9J04aHl0JjT0BZYM0++qb6P9yfm/rt2Uw2Qrzslh7amqqojWI\nc0Tt4SFO67PV762Zj27cpOayKtlnpOX4jBDE+4aDJBvZH+eEoB4nTBETzguQc4Yk5wOPCm4E4aSu\nR9gHOIBXWDiVVY3naNa/oqawfd0n5ewBnkuqlgnRvLl+y3GjAtLcTWfQZfFwxkyFI6lBr18+46Qu\nR2UQWh44HojWJs9puB+/ojZH0xTr2tVc5qrkjDEnNQYjYKZzgjTW2aqGOLbOBxoV3owQVYYZKlPa\nJ6iAN6153d4/arCXAI6qb7bAjcGaGtzUIPfaBDdB+cII2FZTWIxbf28zrpwnD21ahvmyD4diu5sK\nJwJJgbWmwgGAiIAJM7SQExMYxJy9mSIQAhwxygeI+STZ9Uh2D06lU9LlrPaX2r4uZcNrOVY9vJmi\nL51CUt9EQJFw+aDAl0+l9QlU14plR7z10qlbw5tj4Oa20OaRAJIOanr06OGiA5xGvPe978V73vMe\nvP/978c0Tc1x/vgf/+N417vehT/0h/7QnX/vox/9KP723/7bePe7343zuazbf8Mb3oBv+7Zvw5d9\n2Zfd+zTuGozlTTuAq5/kP+pYu5g+F7Djf/vy3zsGctpqnNZ3k9qiaXDsJDBuuL+p9gmSf5qbnoqj\nLKOS54VS6kKg5IETIO1crRwqcJlZMksHKhMViOGxjruxi2Z4k6FNdK+BXC5lhsW+/a9Am2XbX0va\n1rwsLEFLBrZw5TRoKzFaN8k+aVt8zhFXewg0tvtetJ7IL41P96J14+/2rahKnBjBdEKMMZVVRTov\n/HEGnJogZ1YnFevdZN2ODOi0lsme3xfzlhK/nCoJrMup+uQ8byRpd6orl5j7bZ6X/SiY3Q9m1iRX\nyjIIWXETWbeUf0+sZUPlk8WwYt7h4U2ZhOZjif1xZQmqQR7kTkysx5Al2PZfWpaNxKteZ+kcg1Mq\npYoQmMPky24iBjJjW4U3xIv9A0Aa5sM+8/tIDfT8vpG9kHJJHYAFuIkwWHNGdADH9hlrAV4n2pdE\nCV7k3F6UUl2oojs0rkFkAzPI528TuMC9T/Pjrin19SbtFwQwgm5X8/MJSYWTVFj+OgUBe4EIky5H\nYMJMDDO0Ln1vSogjpw215a6uR7MeTwQUEKcVa9ek2nttis68OJkYSyfHWVVdk55vWuVTtr1iY7+p\nYeD9wZvnrbZ5YFDSQU2PHj0ORAc4jXjf+96HH/mRHwEAfNzHfRze9KY34Y1vfCOICD/6oz+KH/qh\nH8IP//AP47M+67Pwfd/3fXjLW95y9W/N84w/9+f+HL7v+74PAPBH/sgfwWd/9mfj13/91/E93/M9\n+Lmf+zm8/e1vx4c//GF85Vd+5b1N4z5jDez4eGkgz3NX61yvzjkOcq5T49QQZ6uUqoA2vozKFDla\nRiVJzKgJV1bhyJKTqm/gvG/EVYAJGIhSB6ohWHtiFDfcayUgtWmkvbdk0lQ3jOx5U7cArlv/Hi2d\nihAzUlNhFEmZe1K6VzqVAU+7nAocDxyr7f3h4cOSB3s3NcuqRJ0TC38cWb8CcmacU2kVIWCgE4L7\nj1Am6T5BbxkDp8SHPMTJJRq+VCF53uCcQF1dOmXb3CdLog4ojy9/OmXMbp/SfYGidNCBL9shTWJR\nwBtRJqSGbgX03II4za3ES/WAJaE2LCIDUri/zBneHI1CabKWNLrSqIgIeN8bPw7Z+pZjzmBPQEBw\nig1gCW/29o21/cJK6CY6J8gEoAluGKXPTYy+TfjUVFNYLIzJ61KkjTiiqCn2zcZnt4m4CnFkRuW9\nnMEMwkn3Og/voOBmwCltDyulAlCYWgc+YTI4RKLXWXg5KcSJTBiDlk0FLZuKZUdE7/NzyTXJSnjt\neuO91+p/E3LpVNrPNsqnWuqb+mHBXeDN9vbfhzd3338eEJh0WPNKhX+A8Vjikc1OjwuiA5yV+N2/\n+3fja77ma/AlX/Ili/KjH/iBH8Db3vY2/MZv/Abe/va343/8j/+B3/JbfstVv/Oud70rgZev//qv\nxzd8wzekz775m78Zf+bP/Bn80A/9EP7aX/trePOb34xP//RPv5dpPHTsJY4vNOB5rlDncnXOPshZ\nV+PcBeKA8lPb+gmpNzNON5l8xoiT6m9GSbBVhQMAxNnclrg2P2jfOLtKK1nSajf07X2BfJMsf3nx\nJNS3/vVlUx5J1V2HknGtlkj4FsC5ZGrWUhoHZ6pEPik0kIetKW+aQUHh2WWX9GYZ3cpN8Vr53O6s\nNZ7+tyMWapzktaPrMBjs0LIqUmWXgZxgLccV5MyYEDhgwKlK0Mu/W8vk14VPzu0zAzfJ58nKpvS1\nT9BrpZVNp4Q40lUHNKa/e2HtkCNTUjMwif5BVC6U4I13QWlBHJleaz3kz4qyKQWiVobIqmTz6gLv\nHZDVOFnVxFQCqsXypfXdVqpZch9xBuhUQBzSc5N1MrM25VY+FDAs9o3AoTi/tSIpsyhvwxrmRcyy\n7XWfjDpfBm7S3xWfmyW8fbg4osKo4+h1v34ocA3ESfCOTqmUajaVT2M6gaWUyi1Q2gPqiFGVbFGO\nEY6MgXIZb1LdAEXHtTVz77LtvFfglF5rpr45O/UNczYvntVvK3W6U3DszYsNIDfXexPU3ALe3Ce4\neaDj4BWENf5e4tL7ih49emxHBziNeMc73oE/+Af/IMaxvXo+93M/F+985zvx1V/91fi///f/4l/8\ni3+Bv/gX/+LFv/Ps2TO8853vBAB81md9Fr7+67+++Pz1r389vuM7vgNvfOMb8fTpU3zTN30TvuM7\nvuPm03gR4qUDPIsE4j6AzmUw5xjIaZdU+e+tJ+klxLFx06YlgDBgocKhrCCY6IyBpU30iAEzz6mc\nJRApmQn5L7RlN0SBw1Ek6tLel5yp5dZ6yXMv77PaxqsEvOIm30yvK2+24I0tr/e2kARt2QrYtkOr\nq0z9fvfmVSGOf1/GtvrmSFJ2bRxvN5z3M3k3ZT+TCDAN+jcKsEFMYMeDnMhnBJwQaMCEMwIGUVpo\n0i4zVZdQBTcX7eTFkiUAC3Bj5XFr6gq/zYHtY7ZW4kT1/YmF+kb+DRB/jkjslDaU2iHDxgFgvz7a\nmnYQR/yk1g8mD27q8o9UmggHdtI8ZlgT2QBOLq1a/o7z8VhJBm37BAV+erpYQJyg5TUJkFmaTkPa\nF2y/kPGHw/tFvU8c2R9sGt7npga4MU6NYx84ck24tBTv9mAotGxfsFZqWV5v2g8KdESJBsRhPe5r\neDcAhR9OHlfK2mqwk8q9/PZmYAgyopVNRRYgaiVTdj2ageKatNWZrX6Q4B8i+HbhXv1p6hsp3VXv\nrWSUfk6wZvmAoGw1X5dO7SmrjpdM3Re4ec7w5BWANR3IXBd9vfW4VXSA04g//If/8O44b3vb2/DV\nX/3VAIAf+7Efuwrg/Nt/+2/xoQ99CADwVV/1VWJ4WMXv+l2/C29961vxXd/1Xfje7/1efOQjH8HH\nfMzH3HQaL0O88IDn3lU6Xr2wMyubIOdYpyq7YSOUwCbXN60oeHhON96mwpGbxQxyzMx4wgwzlgXU\n84YCQiIuEaytwxFJTFq1hTgDajyp6pt000xuXvI+VSttvHmkjGtlKLlkKr8+Dm/MtLg2Jl2DN/4G\nu37S3k7gWjfAQ9HJpd7v8jYaqvdI29i/XrtZrwHfmjrrWGypcFBMU2dMk/Mpq3HU5NhakEcKBcgJ\nCCAS+DNASqqCdnkqknXI0/itMJWFzJkDOE5NldQX6Sn49jaX9Tqr4iYmg9blmoiILOqRerjsI2Jk\nbGVUBlMYosKJLGdPUwbYkT/pVkieJLBcmZv+HU3vm6Qc0L+qWmPkRDQpckyNo1PgCuTYsbMXpirw\n60FeTCCKCDgh4gy28xQFRI4YVJkR/PkLATPOCeYAl+8Trf3BkmrmNsCxc6JvC76turn/hLJe93tK\nO9/BSuZzSCC9VSpXnhuG9H75O9Wxn3+wCXGySk+nU0EcXbhVEFRMlwHQAHBEZAJT0OsPtIwXRRmv\nqdYK/xusX5Nk3WQIaj9p1yT/EGGtdFe8b8wsfZKyTafwi9W+swVMlp81rjfVfvH8VDfPCaK8ZLCm\nA4YePV6M6ADnynjy5El6/dGPfvSqabzvfe9Lr7d8dN7ylrfgu77ru/Drv/7r+A//4T/gzW9+802n\n8SrEC2mwfC8qnctAziVqnNZ3lsm6zMOqVwGZciB/5suoIs96wzkh6FPRycqmIGqelow96txmA2PZ\n9vnmOS1A+T0uXxcKAs7lHEl5o8PsBjry8bIp73/Sgjfmf+KTtr0no/6vRdE9xiVMuQW1v5Eeiu/J\nej6WmFnU82GmoreBOMBWOVUNcZilzC6EUTxCNPEWBcaoIMQBHARVhZ1BNCSjWvLrxSstaHlMRJ6L\np/Rp+zhoI+snl8lZ2Zz3vDF4U3cXM4iTpz8DyEa7eS3N+k/+GzBk+AEBmlGTyKjFHaTwJhBSi2Rb\nlsHWPKk/TloH68qBuvSjgDgGaiD+HXYsJUWOm1dZntLAOP0GyXnC1o39XZRzVO9jWo6zwjrxRiEM\nsA5m8tqUIA7acN4n9vYHWQ/WBWm5Lxi0se3u1Tap01x1DqiP/31446DrAqK3/WrK99U5pvEbR8ol\nMzSx37B5Wlf6tc5Dy3NG+aDA/WA6B4iqRmLWstwIAzcrEMfe70AcRsBAAabGMZWbqXEYvPC/iUlJ\nun1NAkrlZ+qMmK49chwZvJndNciuPxOyebHAwqV5sazFvH/ZumwrO22dXwNvtsHN5YqbewQqLwGs\n6YCmR4+XIzrAuTLM5BgAPuVTPuWqafyX//JfAAC/7bf9Nvz23/7bV8f7/b//96fXP/mTP1nAl1tM\n41WOFwrs3BToHAM516hxjkGcdUDEPCNSkHavlfrG6vV9IjqTFHVYKVUtY2eWJ5/2BJQAsHrk2M3z\nllR96YPDKen0T0O9AicmaCOdco6WTR2FN96g1NZlDW7aIbDEJ0FL5VQb1BwBK2l/cRCnTgZTgrgB\ncY7+3n40nsaTJMCk3WbE7HjQblVjmqdIQRO9oYA5osxpA5wj98Ye2Mgclsm6T8hTmUyVrDcmWhiE\nLxInDzgMFFBE5JDAiKlpGA7W2AJFMWDNw/U39TtqM6XLtb38Nbjxx5Lv4Ob9cExZYKVfMp3sf2PL\n5duHJ9+bhvqsLg1J36FcwiIgZ1A/FNv2EWz7ZYI70mCaaAlwbPUZKlgrq2tBmwLMOIhn878Gbspl\nvi7hXIc3jXV54Df2juXW9eHy6R27lukPAk6RF3A6BnGAJbBpQZw0XgDznJRxDCBG3ZsU5MAeKiCX\nTe1dk4Aahrprj1PgRDDOHNMDBOl4aCqvade8eHm8lCq3+4Q3D6q2eYFBTQc0jzdMLdejxy2iA5wr\ngpnxLd/yLQBE3voFX/AFV03nZ37mZwAAn/RJn7Q5nv/cvnPLaezFL//yL69+9uEPf/iiab0o8UKA\nnZsAnfsBOfX4e8m6v/lNJVQoy6hmnCXpZillCTyICkcVOBNmBBBmLaUyiJNKNgBY/plumOG6fVTb\n1vtrrPngeAWOKW9MdWMQRzpN8a5hcYTzPXFto1ttgbfKpepYbrPyybT/fG/vXkuwymnpfCSJ/0YH\nmpX9wk9zP46XU9WqLxuWQY5CHIoJ2FgCD1UpGcwp1ssFnbl85zCZu5zE1wl7UmBELZ1pbOeio5vb\nPqa+ySqPnHyZDw5ZwsYBUVsjy/pQbxiI7w0TY/IQBwJEvQlrOkbcTtTqTGXAxr+2simDN7WHh0sr\nEzRll26aEkeW25UkNfYLv75tOvpCtoF523BY7AeiVMoKHGDKipz097p9waCNzZPtB1uKO/vuZfCm\nrbhpzl9DdeOHb8GbtD7StNtA+BpguzXu8ryRr3EtiCNjnGW7Bi19M0bn5/kKiBOZkxJHyqUoeUkZ\nyDE16AxeeLLV1ySZ1/K6ZPCzfojQKt21tvSmvsntw+2cU5sXt4FxS+G1Bm9eCHDzggGbDml69OjR\nAc4V8e53vxs//MM/DAD4ki/5Evze3/t7r5rOr/7qrwIQo+Gt8J/bd245jb34rb/1t140/sscj9pr\np7g5vRTm3B/I2YM4i99AlKejqSuSmHsSliqcySVQIKRyKnv6GTlq6uVunKHJqd5sm8fAvLJta8+B\nrMDJbY0jBNwwuFDdcHrqOekt8jq8sVbhBm+8Sakvn7GWwHtlSj5a2+uihGltO1XTYoNmHLMxtE9y\nGtHeL4CjXdTyuPs34YsErp4/BiYtSTLjUiL910jigZzIHw2v+ihKE1wy31LdLBP0/W0o0zylv8nI\nWP8LRIi6r5Ju5bkloYkEIpHaOAEOiLkAObYaLVoqghLgmGIgl4MYvPFKHUlKM7ABTIGj/1EusPLA\nai+KY6gCj7Pulx7kyPLp+Y1FxRWhx8eB8p/lumgAGdRJ9DKR9qobe+//Xhrb32sn42vrtwVuCkh8\n4Ny0Nd1WrM2LnY8k/HJ4eBsWZZV2aWrCuNoXZwXiRDBG3S8YhIGC7u8CcgLLMZX+ggr/GzE1Xr/f\naKk/64cIdeluBGO264/64BTgJr2vAOHqg4LbwZvnCm5eAGDTIU2PHj22ogOcC+OHfuiH8Df+xt8A\nAPzO3/k78a53vevqaX3kIx8BgEWb8jq8345955bT6HG7eDTKnathznGQc9QfZxviuBu3LRUOqxLH\nlVPNNCHwgElLqIiDlFOxntb0xhnuxnlUdYE87SQ1ZmVd4ryNYrUd6/Ipex2TGkBuW32SaTfNTFHV\nNxMmmHnkEt6Yea3BmyOtgf06tmglS8ukqoy7lCvVN+9ecVNAGafI2ZpWaXhtsTV/R27Gy/26BjnM\n2ReDKDTVGMCUP3dBvEzyFvt2I2oljlfk1El7+cTbTcMdO5ZsJoVRGkdaiZuRccScStyi+nMERMxM\nYsbLkkwa7LQNNyhCTYo2Lg3BtYJx81x31IDVVDm+i5spDWbzgUHZPhxAMgb2nafqshBbJ6uqNdsf\ndF8xkAOGAj33Ha4VbAPAJcxrecwU7ytwl+Z5Yx/YBjd7x0MbnK+Pu5zv1jG8Bm62zkG3KZMs10Oz\nhDCBnFo1kmY+lVUGKGKIKLe1jw2II3vjiBEDwCMiWPymVI0jpYp2JXRtxKEQR0uqWtclma1agZNV\noBObHg3rvmvI6hsp2Z0SCPXgUBZvC4xdCm8eGNw8UmjTQc2rE/Yw4lHFY5ufHoejA5wL4id/8ifx\n1re+FefzGR/7sR+Lf/kv/yU+4RM+4erpfczHfAx+5Vd+Bc+ePdsc7+nTp8V3bj2NvfilX/ql1c8+\n/OEPX+0B1KNHjx49evTo0aNHjx49evQ4Fq8MwPnRH/1R/Jt/82+an33GZ3wGvuRLvmTz+//rf/0v\nfM7nfA5++Zd/GU+ePMH3fu/34jM/8zPvNE+vf/3r8fM///O7JU3+87pU6hbT2IuP//iPv2j8Hst4\nUGVOekp/jRIHWHtau19OdUSFk6dvyoHUXhYDIqKUUVEu+5gxgVj8cGbtGANA1TfQJ6LWhUeenEci\nffI5g1TCzjIzqdSnJVf3T0tS6YaWSkX4p5+5gMPKpsRgWZ56RoqYtGxKJOxnNY/M6hsplcpto1uG\nxbFoHd54Ck7lU25y5Qvt7i3tco/d0pyFgkVVBJTnzYxyy6ffedtvTbvdVeYWkZU4i3loKHHsPXuD\nWs6mtBKqAPPzvPJUq/7N2Hhivae6KGe5XE/SXSqbf4NyNyrSoycZ6pIcW1E/JS258P5RacXoAmUD\ncICIVUFDvjkVwLx6VsvqHa/CYW0j3jZirb08cgmVamsonxki5qIDFa889S/mqVbEOBUH6Tq3kjmm\noVAJ2kLl/SGrb/zne78bi+297nNTf3fd72UvtpSWG0ovjVY5kyxvPtdYeZJ/77/bOvccVeSsqpio\nPG68GmepwgGAWJRTBYwwY2MApanxYmbTj+frE88YcMplVMQYWLq9jQiIqm4LIJCWUQUgXZNMhbN3\nXZLlSUuwuCaZErRlnG/qVV8+JerOWhGYS6nWlIDPR33z4qtuusqmR48et45XCuB84zd+Y/OzL/zC\nL9wEOB/4wAfw5je/GR/84AcxjiO++7u/+yZdnD75kz8Z//N//k/87M/+7OZ4/vNP/uRPvvk0bhcR\nbaOL28ikX8ZoXdjvDercU1nVuidH6YmzXnYlN9F12QljLoal8ikOYBL5d6ABM7sb7MKHYEwWxoEJ\nDHIgR275CTnzDJTXe6x0rql9OJbQRpcAZqrqy6YYMXneRC2j8q3CGbGAN77blDcx9mVTaze9HtQY\nuClBzlCM5yHE0dKqotzND6OxTEJ1HaT37GFOXpPNaT+XOA5yWom8faNIQi+8R1+0A69KEloeJ2kW\nG9tL2okvt5f4R2UIFEn2OXH4EciYjgFoB7cK4qTlBaVjwWCOgZyZy3NXcPuINzJOxxLnEhBvxjq5\nUqpcEsLFMQZI0jwnpFP+a5kX+3WyGFaPz3nctA9URtzeB+ku+0PtiVTDmdY+cFnJ1Fbsf3fvfCMR\nVs8/HtjU556LzztphOozPf/4a0c633A9PlBDHBsu8MZAzll/auW6hxmMEwJFDKzQpmjcFjHyKOcT\nSMe3EYNchxCKaxLACeZsXZeA8tpUX5fsmuSN8xNc0uNlxhlWPtXqPmXrdNtDqgZoa0DxAcDNA0Gb\nDml67IVdyx5TPK656XFJvDIA5zM/8zPx9V//9c3PPuMzPmP1ez//8z+Pt7zlLfiZn/kZDMOA7/iO\n77i661Qdv+/3/T68733vwy/8wi/g53/+51fbgP/4j/94el0bJt9iGvcfl1xQO+ypbwTuBejcSZWz\nYSbZhDRZjVM+3V73wjEVTuGDg5ASUlMUzDinm/PAAyZMBcSJ9uS8ummeATUv5uQx0DRvRQls7H2d\nTFraKDfLarOsHT/STTPFAt60WoXX3aYugTe16iYnUqUhr40v4w7FNHajTpzcsGAeIwpAkqeCS6bS\njT4tE1W6J265HT4prj5yXihrajO6MsnY8rPZU1oUICEZnlYJrz7Lt05UNiwqlAoImDEhqFG4mBkH\n9Zcxu28ALEfaAAIzMBAKr5uyDbLMTFIONA4nrxqw9wZuzIzVvHAM3kzI3dzMEByQrnOF+oZEAWE9\n4AofmcaxU6sLivVc7ect1VjzeOGGAmcnWmBm35z4+SWp7eWoziMb0Lh17rnLecfCbyvGDPLnHgrN\nc09er8ByHUa3f06pKxW5rlTptyGtx8sHBkgQhzkmJU5ExMAjAsk1Y9AHC+k6xEG9cC67LukcN69L\nXgFq16LkfaMAV84H8rfVfcrW8RIq7gNGiSW82Qc3j19t00FNjx49HkO8UgDn0pKnX/qlX8LnfM7n\n4Kd+6qdARPgn/+Sf4Iu+6ItuNk9vectb8K3f+q0AgPe97314+9vf3hzv3/27fwcA+NiP/Vj8sT/2\nx24+jccVRy7CrxbkuVegc5Uq55giZ6nG2YI45fTSODw3u1FFPiNQSAmp/MIZA07y9F3LqQJJgikp\nBCeQA4gqBxC4015KXry2m1X/rB9AAW5MdRMVMMn7XB7l4U3dKrxlWOzLpup1v/XUe7WT0kopQ7jw\nuIrkE88ZwJjBDGWgU8CcolV2DXPqJLl9LmglAZeaobZVYz4RCcV+auOlfbtlhrz1ewcTk3WVRTlO\nS6Hgjb/955KgBTmO4I4jnhfAc80AHKpli6oUAKSEatEGWb+7FbZUdetj/9d30cmlIJaI5hIjr76x\nYy23P57T5/m3l5Csta6XJTrL/WV32/O6emM56ja0uxWwuf7YWTcgPnrese/c9bxjkQyrq3MP0+yu\nFyXIiXFKMGgP4kCNja07lZ9NKt8sIE6kkJU4CEmNI6/luBFwk69Ls02XBYYa/mi1Etc5TX/r65Lv\netgq37XjJEN2K6dy7zf270vhzb2Bm3uENh3U3CVa26WvT0bjQVGPHlfGKwNwLo1f+ZVfwZ/6U38K\nP/ETPwEiwrd/+7fjz//5P3/T33jLW96CN7zhDfjQhz6E97znPfiyL/syUPUY+gMf+AC+53u+B4CU\netUGxLeYxosXRy/aLyfouTegczHM2Qc5RyGOTc8ubilZJvcUkBTc6A3xbH4T7obb3zTLd0MhYQ/q\ngWBPPG2u5OvZo6dcSq7+xlQeVAzTxNg6TfmSKe93s9cqPA+b0g11ub7zOmolUYFORQJl733iVDwR\nd0/DL0mmCv8Wyk9spVV1mVRdDnPqG50VBYr9/o464kgyUn63hDn22vs4HYmjgGcZW99bK+mI8J2o\nUlKmxwvpe6/CSeVGlX9UhHTOgfpHRY6Qflxlu/DczU1LFQ+UUMnSld3cPLgx1Q1re3NTFFhSauve\nShOto1tLfZPXTdmBqrn+jsK4C7fpdb4u2/v3LaOtmmyAGg9vLoDFvnyzdd65BuCYssx8ntJ5Bfm8\nE/lcgJwYzwhhTMdGxLQBcSI4tRaX7lT+crfwxnHwhnlO6hxT3zAGgTgYBaYiJEVOVuHka9OMfCz5\nvdWUqdXcLq5NVr7r4Y1dk+w4MfVN3X2qpb5pXYPa58BLVTePB9x0YLMVz0/x16NHj2PRAU4jfuM3\nfgOf//mfj/e///0AgH/4D/8h/vJf/ssXT+fd7343PvShD+F1r3sdvuZrvmbx+ZMnT/B3/s7fwVd/\n9VfjP/7H/4hv/MZvxDd8wzekz3/t134NX/7lX46nT59iGAZ83dd93b1M4+WNvYvOywF47gXoJHn6\nJSAHqNfpFsTZGo8R5Qn2hgrHqwrsO5EiwKLEmbREBIzihhnIpVVl8rDcX0pI4Z9y5nmx8ODGVDfm\ncZPsJDdahZtZcYxTdeNcz1fLXyIg0AiiAQONJczRBColV/DJlDPnXayP7YiNm/mUEDSATiupypDu\nKMxZqru2ypH2opmEVPfxnodfk0i31T7Hxq/D4FIBt8grguRYGRDgy6j88QKcS8UAAGAsIE4uPRQv\noBFB/KM449bCeNWpcixsGFCq2WQ+8/DagHXNx8N7SgEo4I33vvHmxXX5lP/bVhrsb99L9oEWbDwS\nzX26Brg3un7VXjZ+WA2I/XfWwE3rnCPTGO58zgEyvAGg229OsEQ80qzENgikUUUOgkGJGRETglft\n6Hm2VI9G11pczI11BoAAhLq0So8nMzyHmhsXpZiIGGgUeMohqW5a16b2uqnhTakAtWFWvttSgdqD\nhBKkt4+TVqzD80tUN1cAgRtDmw5sOpTp0eNFjg5wGvFX/+pfxQ//8A8DAD7t0z4NH/rQhwooUsen\nfMqnNNU57373u/FTP/VT+LiP+7gmwAGAd7zjHXjf+96H7//+78c3fuM34vu///vxpje9Cb/+67+O\nf/Wv/hV+7ud+DgDwbd/2bfj0T//0e5vGqxkvJ+DxNyZ3hjlXqXKOQZyjKhxfsiA36EtVAaCeGwSA\nTgBbd6oTJprSDXMqn6KyJKq9JL6EqpSMZ+8NB4/cU08zifSlHWZWHBETvKk7TV0Kb0KQU7i8Pokk\nP4zp6XegUwFuLIEihJQcpPKGtG7anakW66cyXwVEiePLVjzQmVkMQpuqnIZnRfJB8qCoAjnABSUt\n1bwe/vyC+/zdaV+ZhPiSrbaBcU48fRlVWqcImMnAzQmk+2NbtSZJZunXEZNXhykDrIsO4PpV8bHz\nDbs15aGNKWzqUhDv42Hf9PDGm4JbYmrHn50f1sqn8vqL1ft6no8ntUAb3hyBLofVXXcEOnvgpu4g\nVRuhb6ltAvy5J59fZA+67nxjkbqMVeccQlRIGVNBH9GgSpO87Wdd2lZJFZniMx1nEWZuHGAd3Sa9\nzJ2AOC0gjnnxiPrmhIgZA50Q9JonneAy+KphDih3itvbF2oFKJCvTWacX5fwtkoMDXrZby7VNxUA\nrd4fhzcXnP+6yuYO0eHMYwwpQ+7R4zbRAU4j/vf//t/p9X//7/99tXuVxZvf/Oary6uGYcA//+f/\nHH/rb/0tvOc978H73//+pPwBgDe84Q341m/91lVvm1tNo0crjpxqHzfkuReYswtynNbcvnoA4pji\nJn1Hh2VflXxTa6qCBG0guh57Hylg5JMmdQNEgZOhBaduQuvLUnhnJPXNEtqk15Qhzuzk6R7abLUJ\nvwbepCSogjeFGseBmwEGfBTiKMyRqbtSKt7fr736qFgPvg025XVANOQn5E6Vs1liVRmQJijRKK86\nAnL2vE+aceCwaU9nq4X1etLaBDSIVYJeKpN8aRdhkOPD1E0ImFWVZgo1EDDglCBOLvUQeGPvl34d\nDuAo0AHK0qm6hHexLM501f56aGNlIB7c1GoCAE144yGpP5byv63ykHI7roMeH+vbuCzVGoppbimx\njkK+pXG1g5o716X83Ta4Wb7PwCEN31D4FQDHAZvW+ebIuQbI55uBTtX5RuYqldna+VVBjoxnbcZn\nIKIoqboE4sh8j5sQJ+h2CApEA0K6jkUKCeQIoJZrk41XX58S1FmJGtoArpxXS3jtmuQfJhTn2GL/\nn3f3vyW8qT5vDj+YtnZocyA6AujRo0cHOM34iq/4CrzpTW86PP6nfMqnNId/1Vd9VSqh2orXve51\n+Af/4B/ga7/2a/EDP/AD+Nmf/Vk8efIEn/Zpn4Y3v/nNeO2113bn4RbT6HFNvDiQ52Yw57Aqp1Tj\nrKkHWt+r24ozqjIq9R8YyN3sUoY4A50w0bl9swxIaRXW5fu+PGihvqmgjQ3z8MJulM3vxhQBvk24\nwZt2p6lj8CaEk66HsUioBvW9GXBK4KaGNj6BqpOqQ0oB9utoCbLSey3rcboK+HIHWVchJWBrBqRp\n3VCpblgrr1pI/Q/Bm0bSfSipuNy0c3ksrP+eV6q1jiODnfK6VChEnBFIzb35nBRqdXJp6puIOcGe\ngCD7B2WAQ1X54QLiGFRCYx7T0rd9peryxBrcWCc3AMlXqoak9pfZ/YWpDuqSqTxHa/Najr+3nf37\nEriVZX/tUtK138mRv7NVmrcEfq3xWqBmHdwYHK4/r9U2XmkzkJyf7Hxz9bkGEYPLw+18C6AA55Gl\npDZQUL+xkCCmTCdoZ6kIBFwMceS3p02Ik36L7Nhyvm8IC5Bj64AxOBVOeW1qXafWrlGXKEHtfOxL\nCm06rdKytD1Wjomr4E2HNhodzPTo0eN4dIDTiK/4iq+4yXS+6qu+6qLxP+ETPgFf+qVfeqffvMU0\netw61i7MDwd2buabswtztiDOtgonJeuW3BvkoFlujH1pCICBS4jTulnORsWDzl17G5TJZpUQV4AC\nQAI3terG/G5SS3CFN6024TFO6RfLWIc3A6mixsqlNJFa/MWpADeWSAX4J+LV350n46UCxz395ZxE\nAEggLa0jV2Y145xgTFSPnEtATrHNGiDn2FPitWR5S0GzNb08D9vfya9ln2/93nrnNvmem447VsB2\ndFnZhxwjreTSl3oEGjDglI6VutTDYI5FDXEAJMCzutwNA3CZtxLa1MmomYH78jxvCm6gpgVvTOXm\nE9VWecgRcLO6rVvDC2iTP1nf3nuxBIw2T1twfK1caqtUiihkPy1XIgUgAeKW2qaGxPW5pj7PANvn\nGn+eAVQthjHtI8RSchQpHyPmIxN1HhP0S+epsxwbF0Ic+4xJjrEWxAl0Soq3mc5JCSf9D8MC5Mi6\nKGEOkK9RMr9tVV7+vK0EbT1Q8NeoUvVY+uC0YqlKO3BcrE7sdsDi8QObDmd66Lnj0bWhemzz0+No\ndIDTo8eDReui/jBQ5yZAh+OdIY7/jqlwct19VuHYU9WIiGBPRkleG8QBgMjSDScCiDSnhGJGebNc\nLEa1XbzKxj5f+DAUfgLL0imfUO7Bm5ycB+zBG1tnBm+sZGowJQ6yImctmbLE3K+P8unvcl+I4OqJ\n+HoSThyaiUU0eGOgC7nDmKzDaQFyYjwvFThY98lpQZzLnh5fEu77e9NyCWHdPn1Zagise0bpz7l1\nIRNBE+LkcpYBjChgT5NJQihATisBN0gkc72SiB84dfiSRPvrFW57iagssx1zGZJaeaJPTO8P3izB\nzULlaJ9tbO9L4oghvPx2Hq9VLlWbEx8BNwZt5HtLcGPnnFudZwzwDUn5IutsQHmeSTBH1XwGcsAC\nTaRTla2XpW/XZRDHPovpGBMvnXMBcfxx5kuqmIYFyAGwgDnpNza2a7vEtzxe6uuSgc4Ea+6kvrkS\n3twA3DxOYNMhTY8ePZ5fdIDTo8ejiqX64iHi6nKrImHxsQVx/O8eU+HYuBFaEgKk8hCDOPWNcqBB\nbmcLBUE7AYqNG30PbVrGqD6htJIpm+cteJNvfmt4g/Q6JVoVvAm67DW8sZIpS6pGPq0mVPl99jaR\ndbO+7/m1JknUoMqKAZHbZTBemVOrcmY6K1SYU0mVNyBddJLhuQQFzgsp7TeQpHldiXMreNMGN60k\nIx1LBexcHhtAO1kv1GryIxDLGVUxYdLtORYQh2xbk4HLmAEoQoJ9BnJkv8hqCtg0Gj5JRUnMwVNF\n8/hywAZYqtr8MSafq8qt6GCWyxNTonoBvLkI3ABpe7e2tQ1bBzmy1lprp4ytfWO7FMvDm1a5VKtU\nKpViVuDGoA2AVXAjptfr5xidk4vOMba9g/NWiggY2Pm9OA8YU+QI5I9SUgsAZOW1No2z7vfHlDhw\nv+5VbzFO+r0McUKQhweEmEoWWR8+1CDHtquHOQBWrlO1Gqk8juprVAveeHNvr76x+WjFUnnjPjsK\nb648xz4+WNNBTY8ePR4+OsDp0eNRx8MDnatgTlONswZxlioceY00fkpc1U8lMIpSKgCIhHSjPJiZ\nsf6ugRxZBktChqTEqaPZYclBG68CyMPKG+JaDbAGb+onnXXSZclWoDGZFfuSKRkzJ1Me3gw4IXBW\n4th/kmiVCZWHOEVJTGOfK2/oAyIY4AFRhf8R6mnSgDkzpqTKMSNa4oCIc1HyQJBEzHvk2G9HKpVZ\na6VVkmjl7c4NoLOanF8aO/DGhq9DHGA/WS9LcQzSkEs4ZWqyjmX/URWUqmrsWCIKIB60xPCUlD11\nm3nbN+TnhmJ/8B2ELumCVKgHquSxTjxlecrjS8a/HNzk33Hvr4U3zVjCmfVtfmR6fpx9AA7k7bA4\nj6yobvw5pTYm9iboBm1kGtvgZuSxAMMe2Fx+jsnnF1kbLGAEAnUiDIyUsB+syhRCbs1dQRyZXllO\nZeodUOsYzN/agzhEonCLBqRVjVODHJlECXPqdcK0vp8cUYMW1yZ/XNRgs3FNaivT1oBPYz6vADeP\nA9p0UNPjtsEsYPcxxSObnR4XRAc4PXq8UPGwQKd4qrw78j7EyZGfJPsSkXSDaDfTZrTq27XqFShA\nII4ocM7pJploKEEOZoEEGzeW7BI4r7KReSqTSpvPlhogg5t4CN7kcElW+qeJVBhTkuWfiO/BmxHj\nQnFTdxfKaoplklXPX14/Bm04lzeAnKFomWQFCk2QY4ocK62yTjKLde3KqmzPKRQ4CzVOfoqekjsA\n6pbkluk28GZ31N2Evl0eBXjvFFdm4ZbNe+IkILMCckyRY1AnprIT11XIJewpeffQxnmXbKkp6ohu\nXbeOKxneUAgU4GWlc1lxbGH1WFuCm6UnzSa82VDfLKazuc1bX/CKHf/7298r4U1ZMrWlujGD4gSG\nddzaBL02Jfbg5rbnF/nUyqjIreOg5xcAi3OMQRuvxgEhgU6dGGbWblG6PBFnBD02RCM1KRgNBQQu\nYx3isK4zU/kI+IxNkCPLVMIcG2axpRCsr1WtEkM7RtIDhQvUN8vP1ryb7gZvHh7adGDTo0ePFyc6\nwOnR44WOtZuO+wU7h0HOTiLS8hbYUuHIb5dPHFNelG7gBeKAgBlzAXLmBIf2b9bKJ4/r0MZ/vqUI\nOAJvWr43RUmD+VJAfW0KBY5X4bThzYBxNbGy1zIfRxIsiQLesGADGyYqJHOpEVXOxHMT5Mw0Fd4V\n1knGq3BsO6fyOYjHy57RcV0KsWVwLF9ofLaWdF9ZGrAeSxVH+qk0/36YvkhJqh1fTm3jQA5Y1nOs\nkniZblbmzPa+AjfecLalAjEFz1pwlQD67XAE1pTjZmhj07pccXOkg9jRbWznlnK9LM6TNcRZ24ea\n589l1CWXR+BN8rlZUd2s+WgB2ATDAw/Nc4usHbro3GLgJjjZWQTl4QpzJgYCRQCjgv0J6fbWgK4e\n/1ZOJZ85dYxuOik5LFUwl0IcuNLFwZUz2t9ZHyIEyPFp1ylZJiul8l26tve/o4rQJbw5rr5Z/Oae\nMu3AefFhoU0HNj2eb8gd0UODyh4vS3SA0+OGwW09Hu3fqPW4dbRuTm4PdQ6XV20oDVqlVCB/85xB\nTSmPD8nAWKZ4bjzpDAXIAconm15NwLx8sujVAH5efKIpn5c3x/4G2ZdR7cOb/NqbFpuxaAY5ZeId\nFNqksoYqwbKSqQDS10tw4xMrm5OjJXOpEIgyvAkKcwjmtmKqnLAAORMmBJbSKSltOxedZFI5BEqI\nBmRFzozJNkZTjWMQR05T5XrfhDnph+7phn9TkdE+jsv9Riejy2XLY/uN7G8Gb3Tf4jLBty43tl/J\nr7iyGysrwRLQrJXyyLgG3Y4lgvVxVkLSlWOuUtrk77vvbUCb7W1/TWJ68Dx7k/2pLGHbgzd2/qi9\nbvZUN95HS35VxvelUmvgxs4tGeLY/O6fW/x5JS+nnVvEhjsgYsSQ1DgCScYC4sg15ZTUN8kfTZcX\nUM8a84DS0idyptx1lzsf/hrlIQ4AgdBO7WZKJ9kv83XKjl2DO7Z/HFW2ta5VR1ShNRitr0st9c1d\n4c3DgJsObHr06PHyRAc4Pe4/rmmb16HPPcT9Qp2iTOBQtEoCSlNOU+HUHansaWpS21hUTzrFFye2\nb5CB5o0mryR3tfeG//xIOccxeFMlXXDlLC4Js6fkSRWRUqWcaPmn4y14M2BoJlcESoahR56S5/Wj\npVQsWhkPc5iDYpe5ADmzmRMTFPEEzCzdqCY6JzUOyD8VnzEj7zmCh8THQjoVuX2geu0hDlK5kW3v\nY8qsu8ZVHd6KKOdR9iOZd/OJgnaZyiVQwR1DQDK1dYbhGQBAjxNfkjOk4XVcUjq1XJLWspSKtnJ4\n25MjH0v7Spvd5PPCEES5fo27+/ZuTLMBe1vwJqRuUu2SKfm89LgxGOxVN1YqZR3NvI/WHhQ2IHzN\neSWVUDGndRxAiEQO5JgiR88K6fwvECdCIQ2bx5a+NzUMZfBvihlTBdamxkBLjSPHXw1xZF3rGHYd\nqkCOXcdMXZj9p7JScHbXo5a6rXW9ainZio5TtXKtgqE2LMcFnlAb8Ob5gJsOanr06PHyRwc4PR5n\nXAN9gA5+Lo7bQp3N0qoNpUGrlApOheOHISWizrwYDuQ4lYXdlM+YJQl1MGcrCo+OtWRSb4j9/F3S\n/WYZrszB+d4ULX1zypQ8b2SRBwQaYH4U9oTcl01ZkmXgZi3BymVUaa4215WFjSXPwZcwRxIugqRU\nimu0dEpau09JZWMqK1PjwMyqCWB9Km5Jz8xnBDqlsiorqbKW4zrBTYiz7DRzt1hL6leTeV8qc818\npGXLMEfCFDAGLB2wcSocP26hukF5DK4a5+55uqxEvc5bCWQL0tTjHzdardZta11vLct9qbCuitzi\n20cBbip4488lBm9aJVO16sYrbgAoHBaD69FAsAM3g8IL29/tvHLJOUXOIQRmMyuW40nOKaJdmQqA\nLyVJE+CO7YCRRkypO9ugKhyBxExD8uZihVfeDycdL5VqrzW3NcQBi5eOeU8RDemBg1zvMsiplXP+\neiXra1/JtlXOK8P9A4aGV1TjwcLF58TnDm8e0/H4CsZF9+m9dIhxfWrTo0cdHeD0eLmiq31uEP6m\n6MrEbE2Nc0EplUwn6k103rRJieONKYFCjWM3xAnkuBIQe6Lpy6fS7DW6T9m8ybDyZjgvRQY39t0t\neLNXOrXwrXBAJ5VA2FNcoPC9CSrJz+UN6/BmBDXBzaUQx5ItoBS/GMyhAuQQZs6lVeARSWXj1DgA\nChPStZIqW/8RZ1jpQ2AA4bQBcZY3/oVh6bUgxU+vgjiHjb/XPtq6AebZTT/DoLycE/Jxpsuavluq\na2jV42b/XHApyNnzm9kGNBbH230Xv722bW4M8i6NxbmzUuc1f4eyd1YL3rT8bqw9eKtkastDS+fk\nqnOKv9RunVPq84l/b+eUyIwRGQ6DIwzPI0H6EeAJgQKAUwY76pNVl1LNrGoc8uo1U/75hwkyl/Vc\ntyCOf808CzTS8t8EcvSBRA1z7He9CkfWp5mYV/5NO8pQ+2ytQ5ufzn654QEYiluCmw5r7iU6UejR\n44WMDnB69LjkAvbKwZ7rYc7dIM5SlZOnGxc3xmlKrmQqfS5fSje3fvrN+S5UAMub11KmXip16htj\nG38N3uTYLp3yXaesdKrsEhSSkWgeLz8lz5+sJ1p1kpXKqvQ9bez7Bs6iJkg1M6lBDiik8gdZl1mN\ng9QhRpMmm6aV/MDg3VlnTMojYE/PcZIW83ECwkmTl3MxQ+IJ498D91FKZRDnLmU07QSonr+wHI99\n6QWhBCNwx+CkwxrghgFf0nht7IGd9jFx97KNo8njxaCtipbi6lp40456/Q3F+aKp3jsIb1LpFE4I\nNIgCx5VMWbmUnUsAFKqbESEp+YbG+QQoofDe+YSZ07iRgUhZiQPI+8CkUBcKbAic1rd2l3MlVFnB\nIh5rVkplKpyhUUoVOGi3w6BwubymXAJx7FqWHio4kGOlVbJOfBkkEtCx2Lp2tR4y2N9LynpbpVPL\n37tveNNhzUXRIUyPHq9cdIDTo8clceRC+dJCnrIs40hcA3EkSkPjWoWzeLopPyZPMRdS9ex/AyA9\n6VzO63o3Gg9t7H3LUDV9Vr1fgzd18mXDTGnjS6da6puQPHCWpVMBoeg2ZWqcPXgTQIska3eLU6XY\n4RLm1CAHHN2Tc0m/shpHvHEKlQ1rGQE5gGfzmJ6Qm/pplsQuAIiT7AuqzLFpmdpmvZRKzUvvqMaw\nBOZaiLNMgNbmZ3s+m2ct9k5CAJBVPPk4CzDAc1H49ZaUTddP4/JE8NLt5tQVV2yrW6kMFr9LNVTL\naqkWvKk9bwze1GbFi79aNmV+N75kqi7BBFCobny5VCDC0CiXCnTZuSRfaQTmGMiR36ZC5ZcgjlPN\nGcyJHBBIPLhAQEyAe0gqnAHArOo/K6UyFU5ggGkoHyYU5VQt2NuAOPo9+ePUoXq9mtMwD3PK6xaw\nVNzU0Srptdce3iyjUuBsllHdF7x5xaFNhzAvfTzGLlSPa256XBId4PTocetYuxC/NGDnMpBzKcQ5\nWkpVQBx7jzzMbopTWZVX92zcLNalUfXwVptj+3ypupGprJXs+NdefQPkLkAGdFrqmzSuK50KKUnJ\nWhwPb8IBeCPj2bxB5+dIGZWpO0i3lSZgKEEOEDbVOEl1YwAPeR+Y6IyBTi4hkjKrmYGBkpXpJsQJ\nGBEx3RvEaSUvl4KB66HA2nF5IHGrv7+TMDanU5//0vHql/0oBL42qavPK0fHlbhkW61tp7sqr5al\nU7lD2B68CSF3ldqCN96s2Pvd+JIp6y5lNsUANlU3BnAAXHUuqc8jelVI3zGYYyocGxbAiEQCjyHd\nqbLfWS6lqlU4sj5zKZVX4aR1XXSjKlWiPvJndh3w21M/R74Ged+bJszxIAjbSrbWdctfs9YeMqw9\neABax/59wJtXANx0ONOjR48bRwc4PXo8r2hdxF9oqFOrZtbjOMTRwZulVHEd4jSGpRti/b21rjlr\nHXHk9XpXnLyMx1Q3ZdTKm7b6xj6v1TfBnsgvYE5olk7ZWK2Eq35K3vLC2QrvWSHzJFs9QsCKJFZI\nsGRLjWMTCkRJfTNRbhMeKYOdmRXzaWkU7gPiALsg50jSsmnyfSiOHW/t6bvubivzer1KyM0XtdbT\ncr6P/dZwaL1uT+vYNI5PL8fedK/e3ivwxp8LroU3a2bF3u/GOkwNPKRyKVPdAChUNyOFTQjsoc3R\n8wjrsRjBAuArVQ6YEsRhwJVTmRcaZXzDAaA54exahTMbKKkMja1LlDc0TuveSYDqUqrkXaMgZ3HZ\ndyAnXdtqlU4Nc9LEo66D8nhqPWiw6bQeKlxeOnX7ssWXEtx0UNOjR4/nFB3g9OjxkPHCq3X8TdiO\nz8VaMlNAnCOlVNXTz+rmtzXMbohlivs3ji0z4xra7LUzLt+XsfCtQPn3qPrG5PbH1Tda6uCTrQMJ\nVyqp2klEWQgMIvtSBwazmI2aX8WeGsciutIHnzQlc2OZqWRwPBMwGIhJT7qDcBiOmDFdB3EQsWVs\nfCkguLM6Q6M5jR2/GfleHcfLIvenddtYTv/yxI+Aq5RUW3HJNr8I5GzAG6o+W4M3dZtw32lqzay4\n5XczYkjgRqCNlVBl1c1A6+CmdQ7ZWg9pnRqQMa8bAzlw5xGFOIQ8HrOdcQwmk2EciLozXKTCketN\nVs3YeMAemPcgx97X2zkt9Eqpb6nM8bF1Ddt62NDyZVuWS6353vgf6fCmw5oelwbzI9xtHtv89Dgc\nHeD06PEYY+8s/ygBzzFFTjN5bUCcvVKqwmcA2L0hPnKhqkur1pQ2i2Eb4CaZJxdPz/1sexVONi4+\nor7xMn9gqb6RtbQsnSqemO8kXbkV8P76A8SvYqAMc4gdyLHfVDWOTbJW44jqhqT7iutSJaqcgAmT\nl/rkp+LIXapmOqfOMtYeeMDYhDhMETFOTYgj21O3rVNy3TX2IM5hwLMANg21yy7UWTcqvrSz1C1i\nLznOsV7itZiGK23JIz3fRHIT5Dg4A9h6X5oV22ehNifWc0QL3vhOU2tmxbXfjZVMWbmU+WYBKFQ3\nA62Dmxr87p9D5Pwh42YYHBTWAHrucBCHkUuqFHlUpVSsXjjWpeq4CseuH4FDgiZkw+HLqgC4kqhi\nm6+AnPoatVDlAMVneQ1tlFFtPFRYU4jWn/nvSOwfMy8luHl0mXaPHj165OgAp0ePFzGO3lw8d9Bz\nfxAntz/egDhAW5GDfDO8Ok8rN95HlDataWz57DSNi1G9P6i+yVNcV9/UpVOl90078aqTrpyMrQe7\n8SJTGp+JV0GOgBp7Zi5qHFBALqnSNroKVrwvDgAEHjDjnBVaDvaYCXLyhFj8nREVBoUw6vabCogD\nmBrHfnEJclpdiI7E1UqcDWiz3MdLONM6BlpJ4UOAm/zj8mcL5PDKuSYnzLbcvpuVH7NRvnkA6NzV\nsHjLqNiXVLbgTQijTsMrcLSjlDcsxnqnqdqseM3vplTeoFTgKAQe6dj5o1TfrK1XpPEj5/NHIN3S\n+l5gTYY49lmkbHisVwwEVeMECIAJGyocRi6zOqrCkVNULu7aAhQ1yJFh9TooYU57PfkSreX0F6+b\nCtJSlbPue/OSwpsOZ3r06PGCRwc4PXq8zPEgJVr+hnY9bgdx9KsbEvU8zkpr8hrebEIbm7ft77Vi\ny7j4UvUNAPc37KhvAF865Use1pIvn3glpUxLOECkpQtu7SQVjiVktAlyjLkYzAlgzLov+JKqstW4\nrB/vjRNIYY4qdWbtoGQdqqzNeFbjyPKbAkcWdIRYKWtyoz4WCzUOUICc5wJxDoOboTFsCWqWx8Le\n57jo8yOxrbapP2srEWqj1/L4hfvMj+/PMzbC7RRWrViHN23VjQzLSpvinODLo1b8btbMimu/m7WS\nKVPdmOJmoHxeCYSifOrSc8faecPG9SDHIA7gYI1BHMbCD4e5rcLZ8sIxsEGVCgeEApj71uItQ2Ov\nmGleD3b3RxttG+bsw81yvJapfgveNB9O3Klk6jmCmw5mejziYEg5aI8et4gOcHr0eBWjvtG5F6Cz\nr8ZplhRsQpxSer68Gd5Q5NjkD3oXLMddL4/ai/IGfKm08a+Pdp4qjIt31Dd16dTRBIzgErGtNsDV\n/pMTE9u+2yAnBMLM+Vbfq3FmEsAR2JdUaatx2QgpyZpZlTiUfXEk0ZKES57ES+kU0wxEKblijkDI\nT6Rbvjh5P1xRcijEkVm68U3aHcANrY67rtrZAz+L2bsC5JRmr9VnlcogH3Nr0GYxgTSdchoDgLka\ndhnIuXYbF+e4FXBjr73qpva6kWktzYov9bsZ9TgaVY3jS6a86sZMzq1USuaRxJh847wB5PLMvKT1\nSsnrJEKhrx5ckT30yWtvBhcQR04sKPxwDHmYobH3whHFTluFI2AHhQpHAIq0FQeQWotDHybk80MF\nd1eihisZyuVhLZhj+8aROFLeexd48yhUNx3W9OjR4xWODnB69OhR1orcNK5U46xCHMBMjZN/ADzY\nsQk0QM6BWKv934M2rd9qJ8UO0HgQo4BG3m+rbwDzusnf2VPf2Pva9+YIvGm1AZbptcPSZFlXlL7H\nLO9EmSOlDjM7kEPSUSowMLnSqlKNQyDEXFIFKQsjU+ZASqqka5UocQgDZn1tJVVEAyKfgQCQN/fU\nkirzxUlP5S3ZUXjjy3OKjmjAxSBnV32zo5LJUcKbNrhpQ5s14FN/1np/bWyVgJgXiB93C5bWQK1W\nLpReIgJx0nQLOHT7hHMf3ACtcil/nvDlUva9W5VM+S5Ta6qbAMIQ8p6RwO/GOcOWcu+cYWu81Tpc\n1h+qo4gWEIeFCoOhgEfVPTKdsiNVIE7lVJeqcAD3AIFrEOjmkMIKRMFyPAdW9mDOmoK0jq0HD0sP\nt/uAN/cEbjq06fECBzMjPrJ9+HHNTY9LogOcHj165HhAkHMNxJF5LSYig/xkLrpC7UObS8FQ01/E\nJ2i+bfiO+gaQsqnkg+Mg0BH1Te17U8ObMayDmxbEsci+N6XjimcbDHlqH5FhTqAS5EihnPz2HDlD\nHUhC5dU4BqomTXzsv4kmWXIOqaSKOCBqSZVX4RCCqG2cGgcRKZljxCXIge/m4pMtt7DAIZBzV3jj\nAUD5vjXOEtgcUepcqsa5OjZWRQ1j/Hwty1gExPgkOhnPNiBOGRXEUWVVe3a3S+YuBTd5+FJ1Y5B3\noDGNd2mL8COqG+su5VU3Bm6KEioHbgZqQ5u184U/V8gakMitw1G0DhfwUpdglRCH0hbGQRWObGd5\nv1ThJL+cSoUjyxMLFc6aofF2GDSpBjtwU8Mci2PXs+3r2P3Bm3sAN48s4e3Ro0ePxxAd4PTo0WMZ\nDwRytiGOzZpX2mSQUzylb/gM7MWan80S2Kx3vrF5qqNOzGyYgZza+yb44QpyAAU1Tn2T24ivq2+8\ncXHte7MHb+pELBkaryx57XMRreTCmQIbzPGqnBrkMAMhCDIJkcXkmMQPZ+YoPkDJJFkUOVIWcVyN\nQzQg4pzUOBQGEJ8RQsDMExhzgjdRvXSKsirYPheKfbLVseoWLcMviS3I0oQ8B+DN2jTrFseXhLU8\n9tP3gKblK7I13nLe9pV4R8ZZ/W4FcS41KJbvrKturCzKK24AXKW6kY5TIaluaq8bMykeKJdLmdIm\ndZrS5ds6V9hxcMm5IsqKSACYkUFOMivm+nsZ4jCy5w0DydDYtxWvVTjMAVHNiWsVjhmh1yoc217l\nX3fNoao0sDA5BpbXjvJ9wSoSCK7X3L4K59i17Bi8eTDFTQc3PXr06LEaHeD06NGjR48ePXr06NGj\nR48e9xCs//XocYvoAKdHjx7r8QBKnIWxcVLh5O/4zlSmeGkpcWovja1YL5NaKm62DFh9bHpaaFmE\nn46VT8l3y/Ip6z7ly6dyWZUMsd8syqfgyqec941/qr73RN1UO8DyCftWDHAdqVgUOTaM9ek6q3nx\nHHlViROsGw20VbA8E9flJS2ZYPXIyeVU6Qm7llNFzM1yqtrcmFhVOBzB9qS6KqeSiOnJe1ni5/Y7\nV1J1fyHHQcsb6to44rVxF/WNfd+rcFrzcInp+Npn2/45O9tlo4wKWCmDu6PypiiRQkAIYkYcUgnV\ntlmxqG2GVDY1aLGUlU2Z341p/kYKRWvwWnmTzxW6RE6dU6tuFr43B84TZOoayJFlRW52aKVudbDz\nhLw2pY6UTakXDkiVL6rgS+qcZRmVnTOPlFEl1R0GsH42u/KpUi0GFB3TGvtx2zfNf27L2FDc7OSA\n9f6+dj27u/qmK2969OjR4yGiA5wePXrsxwOBnCXEse/UEMdiKG9WL5jd/Zvc7e9s+Yb4qMuo7lI+\nlaAN+x5VZfmU7zzlu8e04E2dlNUJWZ3EHYlBSyM0rxI/C1kgSdZYfW4CJX+cwKQthCW5IwU+gYGB\nCTMLyJFljxiJMCnACSBMWk4VmSElVAGBxQ9HfHGkXIpplrIqnEEUMLMAhYgJRAExTpLUsZRZeV+c\nvP1Lk+MS5DS8cSyuAjrHTU0N4uRx6uMGTeCTTVrLabegkMGXa0BOC9ysJZ5HOr+tddtpj7MGje6Y\nkFbgBrBzwXaHKape1x2mvNcNgN0W4QJsQmoRvuZ3442KR8rnhxa48SbGa+eI3dbhWPoGJcCrXyQu\nQU5g87HJE80Qx+oZpZxq4YUDSuebu5ZRpXJQdxzUx0yGuWW55TZQaQ/f9HE7cO7dKv1tmvUvyq62\nQEoHNz169OjxkNEBTo8ePY6Hv8m6KcwpE9P0cwcgTp6dHZizG1vQpjWdVuKcE9kj6psC3pAzND6o\nvsmeNyvmxYaAKHvfJEUOcnLWgjcjLZMy74OxTM6WYXtLgjgAmMTPgpGTtUClKmdQFU5kMSA1aONB\njj21H3jQz6L4/bA8I585YEJMvjiBpPPOzFNa7zOf07qPrH44DV8cewoe49mpcJaqnLpbFZAPk3zo\nmDKnsf/U+13DA2od4mQVjvxuWIE4ft7yZ3uqtcJjyoalBHbPF2o9tpLbLXDTgjtrHXfK8Wrvj/K7\nF8Vi29QQtw1ubFgyKXbnhMENa3ndAA7gbPjdjBhAHJLfTcuoeA/cDKrIGzaUNv4cArTPD+W5gQo0\nkK1eOMMcD3L0te1h1jrcIE5kUhiz9MIxKMR8nQpHjjRR4dixmaA6AYGDzp83Md7aj2rz7K2HA24d\n0fpn21F77DTADXABvLkxuOnQpscrFKYY7NHjFtEBTo8ePa6Lm6ty2mqcbYiTx1+WNdVJZa0SWC+N\nKqe/Nb8NQ1jKpU3pfZHAAc3OUy6ZOKq+oWRinOFNrb6pS6eoStBKs9L15MwDH2AJcLYUOZaYRc2o\n2ICNgzkJ4MCUN1pCtQJyBjUxtvfEASMDE7K5KSEq0BkxY8CEGcG2BQeMOGGi3KUqalLny6oS3OFY\nGBwDWDU5Nh0AI+6DnGLnycbHKVIplt/X/HdbarRhAWa88XINcsp5sD8Hyg9vcOjvlZasmYlvgZv2\n93YUCFuxW07WUt9td5jaMiq2cikDOgNO8lpv2QJOCDSkcqkBAnSsXMobFY8IIKJkVLwHbupzQgAw\nhLYSz58XgBLkAPvnBPsOgHSWN5ATyHekyt9j+59CnDEAUyQQMQYlp0xWhiXSHtPMXKrCqVuKAwqU\nEGFtxPc6UiXTc9qAO/XwRslw8fEFx137Ny8tmergpkePHj0eU3SA06NHj7tF62bsTlBnCUYWEAdo\ngBygfbO7BnR2nsJvJa9VQtfs7OOettt7n9Blzxp7Sn+5+iYDHyr+Uf2+Kp3agzdDWCZoPjmT93m7\n75VTDfp5UuHASqSoKK2amdPrkYEplUzps+vIGEGYooAcQD4fmDEzY2IWtQ1LMjcgZCXOwh9nxITJ\ntRsfEHnWJ/C+rEraki/ajQOrHjmphKoqqQDmpHrJ+8YKyGmpceyzIko1mgc5hdKmAjkyHMV4xc9V\n3hu+tbEflqd1medOs8TpoBpHYru86ibgZjfa4MbeX+Jz0yqXarUGl184IXAo2oMbuAkIhc9NDW4C\npDW4gZsWzB0c+E1twlGqbPywPFx2pJY6b60KKOhOGNnGyyCHkNU4FtHWcKXEyWVUOn8MbTEu572b\nqHCgXjtOheNLDdc6UtWx6+20WQZ8bde0xnd24c0NwU2HNj169Ohxs+gAp0ePHreP+mbtYqCzVOM0\nW4wDm8oEmZUjShoXKze1S7PSOmEdNpM2mYYrk2qobwgZ3MhT+GFTfZN8YOzbFJrqGyudEjDjIU4J\nb+pkbSAqkjSfoPm1sdcy2NZyVuFwUuHIOwE6A8svWPmUQBv3d1CYQ4xZFThTRFLkeJAzMyOwmB0T\nCCNLUjvzjAmDtB5H9scx02Pzx8klSOdmWZXMtyR7iFmNc1lZ1Q7IaUWR3C3VaFsgRz7w08pbx/vi\n+GNn4YOzAmqubcW99v012LKm0Fl+dmlJJFbW7Vpsl0vl4R7YjO4csV4uteVxA2DT5+YacGP+NvI6\nq23y+SCPC5TApqXK2zsPAPlckE3rkUzMa5BTr/UJGeJwpc6xUiqT8Fgp1S1UOPIb+l4nThQRGJuG\nxqUKB1jzYKqXlUCNfbLed9fW9kFA1Pjd3e8fiQ5sevQoQs5Dj+24eGzz0+NodIDTo0eP+4+rgU6p\nxll0qAI2kq4LbkAP3NAuABKOqQ78E3f7Tm1cbFBHPs8QB8Cm+iZ74OTSKesu49U3BnO8aTGtwJuh\nUt3I+Iz6Kbw3NIUbLstcr7tcwJagjSY0UjKVgQ5DSqXM3HgYWKGNvmdgZvHJATLMWQc5+h4R1rEq\nIBsdr/njEAcFN6FZViXLIqVVCFmNEzEtlDf7ahxbo419uQVGDux3JXy5rFvbloHqXVQ3a/PZji31\nzRa4Aa6CN8Ch9XpL1Y3vLtUql2p53AAofG5a4IaQO0sNtAQ3dg6w4aa6O3IOAJbngaPnAFtTdg7w\n+NGrbjzImZkwOAlOhNy4TvqdwWGeyITBXI9dKdVRFY68WlfhAABb2ZR+N6tvKuhZHO/Lfc7gzqYP\nTn2924S3O7FmnLy41l0Bbjqs6dGjR4/nGh3g9Lhh7DedbEWzDWuPlzsuMkPeKakqPrjgCfpFXTdc\nNKe7rr4BfGK3bBsOmOdNqb4BsKu+yZCnLJ1K/hVOfZNVNGXi1oI3qZxKVTe1Nw6AIpnz7/dSYOvm\nktU33sC4hDlWLmVP663Eao5SXgW4EqvDIIcwIWDgiJkDpLn40h9nr6zKInmtIGLW5V/zxkm7mHsS\nvwlxgINQYbnmL4ErdYepEv6sP/G/q+qmjJUEc0NxcySW5SoXJr6L7+XpSuzDGwE1bdXNVrlUqyW4\n/OLS58Z3ljoKbvxxX5RUwl6X4NZD20uVNxZeiWfqGd95KuOYfH73EIeAdJxBXxMIxKUfDiGXUh1V\n4QTKrcFbKhyZ17hQ4bTaigMojutNFU6rZNJFUwl6V8XbXVU3Hdr06HFRMBj8yI6bxzU3PS6JDnB6\nPHhch33a0WHQCxiHzJDbEMfHYtsfvMHdfwJpT1ipGObLJlpRGxfbsCPqGwCHvG/q8KVTI2WQ47tO\nZaiTyyVa8KZO3oaNpC1BHXtivLEpbXNHHcnADWAKnAx0JmYMg8EbyrBm4KTAmR2waYEc+UcIUZ6Z\nB1DRscqMjr0/ji+rmugspRKuWxXS8ooiB0DhjxOjjBMw6hP+KUGc5CVDy12/LKkCjpdLtIDNsPN5\nVg3sjbf327eJNlgpS7uW89wq6zoi+Nu+j16WcNbzI+GO3QvgjYCbbdWNbwnuPW4AXAVufEepgaTL\nnHldLX1wOB33dnzXx/61x33qUuXWNAFF56mJ/TyQlkLZxMszNus5w/vh+FKqy1U4UnoY1Njcq3Bk\nvsOuCsegTsvQOEOdQd/bWpB1Uy5du5TY4pL7nf37rKNKnp7yvahxy3vta369R48et4sOcHq8VHHk\nAtUhzyONJFNYiyXEKb6+B3Q2xs3T34mV5Lb19H352br6xv6a+iZBm0p948PGlmktU/FcIpX9LsgN\n9x1m7Gl1DW98++BUTmFPzV3yZtMCyjIKoCylYDcgaiIQXYITiZwSJ5dbSOmUlFJ5VQ4AzCQwJ3vl\n1CBHDI9nEgg0R07drCZTLa2UVZVqnHN6gm4KKYM3smxCw3xJVdTPA8YNiGO2rLUaR75ZbtO2+mtt\nnOOAZn2/fv7RVvgs52UF6DR8e1rTlONxzdj8yHrL670Fb7zfTQiqsnElU741uHndeNVN3RLcSqXk\nl9s+NwZtBeJkQ2KvuKnBzdYxv+hK5+HByjFfn3XZfSDHtGyRLEajQn0zQ25M03tmjEGArI1vahxm\nZOmOKnqslOouKhzGgNnKqZwKR5Z72FXh+P1lYapfHPf+gy0VTvuccLuEfOfa16HNo42HhTI9evR4\nqOgAp8crF1sXvA53Hjh21TjrT8YXkzp8Y7N183q5+qb2vfDDvfpGhpWdp9IvOPVNOTdl+VThgZOw\nTwY7Mq1SQWPqm5CUOfkJfCuR8x2pfCKXAU79dD6XOmyFlU9EfSFlU2z2FQXMGRTijE6VYybGpryZ\nSQBPQFuRc45AiEAIQEjKnIDAlMqqiOdNNY73xqkXMup+FHEWPx1MCDilcbNHRvkkPkObDHHa4YBB\nNY7fT8rP1oavw5kW9DnyvbtGsxzLrd+t0qnav6d4D6Dw03Elb8AyyV4DOznK7bDpeVPBm9qoeK1k\nysObE58KxQ2AhermFI6DG6+0M2+blg9Wfazbce43y+Fj3dYcyfFuzEW+awVTeSpMyAQHAnGCuybM\nLFqVQScUDU5DSqluocLxc2nnAwAKdrQrlYJYU+F4eFgoxioVji+l2lfh1HH8GrgfHdw85uhw5uUK\nAch9m/a4TXSA06OHi6MXzA567jkOqXEsrr2RvdBDoFWC0iifWIyzor7xScFShVOqKFrmxWZQDFhy\n1e48Vc5vqb5JJVUe8KzAm2EjmQuUCxy8V4b85vKYYtc6Jurn5okRmZowJ7UVh6pt9HszA8GVV3lF\njpVPEevTfJLx56iJXlVWBUJTjZMWThOv4jSRPjsD2uY54qwlGEjfNxWOLH9O5HzytwUF/f6wHF6q\nuvbHX3m/cix5uPg8gnmtS8++T451/KrHz+NYorwGdbbz1nrdbpVN1cqbGt4cKZkynGOKGwBJdXOi\nsFoulSFO9rixYTKOHLMjlWqb1nHeOsaBC4/ztM4ysGFZ6YgEBD0oUgmVk+Wo3sZNIZda2nxaKdVR\nFU6rpCMgFCocMzMG5gzdIWbl4lkWMSflnPytO1LJejh4rVmocDzqquN4eWU3Jr4uOkDp0aPHY40O\ncHr0uCKe94X9lQRGuxDHYl9Bc2zc9nfb6pvtqDtPyTdtell9U7xHVuYAaJoXl3PnSqgq9U3dear2\nvvHqG0I2LSV1mrCn7y14M7qETn67hDZEnF7X5VR5BWVoMyAbmzITIkkLcZA8afcwh1hUOaLA0d+I\nprIR+EJRlocCi6cGm/KGpK046+csnWy8GgcRhTdOBjavFSVVBdCxlQAAfAZDPE4k95qAcEqeOP67\nLYjTXFUVnGmpagwc1MP892VYW8VT71tb+/h9llWtJbqt4bE6lm0cD38ykImqeNC/bnhWTaiaQt/v\nmSXXsKtW3pifVV02dQTenFSJY/bFJxqS4gbAqurmFPbBjSlufClVhjjchDZZfZeve7vHOADYsQyn\n2lF05kFOZjWCRkYsIU7epnre0INHlDbbKpy5CWtoUUYFKsGhNzOea5WW7iekoIcwpH1sW4VT71dH\nvHCOxA0NxV8ReNMBTY8ePV7U6ACnR48XIC7xd3mp4jDEWYsb3dQ2/C+WSfMS2shnw2pS7c2LLax8\nqjkbVfeptTD1je88taW+MXiTXjeeyHsTY/80Pnvi+OSPdVk2ZzP52KSOVCSvo8KcoAmgKXNGYkws\nu4XBK4M5ISqACtknZ2Yk/5tz9GocATmyTpFMjhFECRAAhTOjjGcP7FvgpoY4AGY+i+KCojz5p6Fo\nL+zhQGo5DAU5TZjiQE1TAVJDnLzPhcW+5r/fBjoPqcRpqW9aSpohfbZsGW5/YwFq5iW8QQTTNszx\nv7+2bYptQNmY3BL8o/DmxK8VfjemvBlAOIWg0CIblI+hVN2Mqsbx5VIJ6FAGN3Z81+BGjvEltPGK\nO1kPx45vGVcigBTMGiTOIGdmOVfJsSHlTQZxiASyegVPIDm2SVFHrcKp96AAXG1mnJcjH09WRjXr\n51ZGlfYJB26WILDuSFUpbghammUQZ0uFcw/xksObDm16PFToFeehZ6PHSxId4PTo8QKG3YS8MiDn\nucf16hsLn1Db+/Yv5cSgLp3yZVbrc7ksn1obd0t9I79ZlkfJdzhN1+CNlVjJcrXBTZ5mecMSKAOb\nPExGjszwLYY9zImqsiGQdqyxEipZaxSQFDeRBeQEVoNiHbdW4wCUhkmeJGlc3gb2GB9LiANXruMg\njpVXyLN98cDxyp3yCT0A75+xorbZ8lUytYcHNiXUKdtcy2sHDBe/WYIdP04r7gp1FsCGGuqaBqSx\nyJBmCWiCfs/gjI0v8GYu4Y3CHDMxlu2UZiDPXuUx5LeNzL6aGPvPdPt4o/IteCMOONJh6uRMik/B\nFDhehZO9bk4rqhuDN8vW4UtwI1Bn+5iW5Vwe10B5bLNC5Mj2Tv/PUjqZ4KiHOLJBBK7oqp85T9+X\nT62FqW98GdW1eZN1o6phju2TBnKsjCoP2zYzrqMwMG+WUgH3DnJeYnjTwU2PHj1epugAp0ePFzhe\nCWXOnVU4l0aVrDbUN1tRJ9kyxSXIWUuKm52DUuq39L/ZnhdaJF5r4dU39t4bFXvljS+n8ImeV/PY\nNGQ+yv10qOaH3fDIAnQi+yf17rUDOfL7kkoRKYxh8b/JUxZUhcDyOaB5kA1TAhPJPezWbcARqSDM\nQZxIpgI5iWpAE39ClGGWzCq8CRzANADsFDeWkDqI47aGrLfaFHcBBYclLFiow3Jreg90gvtc1say\npKoGObvKrwMwJzaAjUWtVvDgJoEa8mqcOX9GeXzxLonpc9s+jDl1EAKNC5iTQI4zii1ATrm05WI4\nWOPNyvNROxTdprQ4KpVNeeXNGryx4yaXT8FBHDiIs1Td2OcCbLxx8Tq4WTueZbO1E2KbR8M1Uu5k\n7wWuBlpCHAYnQ3NTqKQKKg9JkVU4BnN8GdVanm7nB1Ho7CfzgnKHBGLyb1vRp7y2blRWRuWVOB5O\ntsqockcqoGWcfV0p1ZXxEsKbDm169OjxskYHOD16vETx0ipznjvEWapvis8Waoh2+ZSNm6e5Uhq1\nkxhfE3dZXQZpbDqlYbG8zuqfZbLnwY1P+taW0mTFOdmz35KMbIolyLHUxn4lkHSnsjXp1TjJ9ya6\nrBDyecr4rH7DQZyoayECqexp4FETrjGtkIg5QRvmGaxthgME/lgplZTktFqFL9eM35dqeGPGuH48\nD208QJDv2/sMajygSaUhFcjxZXx1C3s/XhFX5ks1uIkO0kSDMtbly3vcmIIGcwY8ajLroY4HOi2Y\nE3WbrIGctdx2TX1TfKaQTaBNdqoaWIyOzbCYOCTPGyubquGNlVC14E1W36zDm1p1Yx3nDOqsHcst\ngLN+LLut6uBNAjdYQhywKQFZxzUwS+l3bRvsaVDM92sLSMi5ZJ32iOrm7moXAzvNOaA1Vc5WydTB\ncqrWsm9dEF4yeNPBTY/HGdwoqXzo6MfKixod4PTo8RKGv4F5aWDObovxajyLi0jG7UHKVqwBnVbC\nfOuo/W9aa8mXEwWnuKk7zmwlfH5JWp1qANE0sZZQWBpu6VVk8fbwihwoGrH5EkNjX9hQL41CGg9x\nIrSVuSoF1GwjRpnxGC3ZJIACIg/6PmAguXRGVdxYtxopmcpthgkDwJOoZFSF471w1g7NlurGq21C\nGHUp2+DGQxuvACGEAtQEDGlfIy7Bjff8SNu5cXzcZV+tk+RUOsUogIx8VoIc+74fHnnWUqiszPFA\nh0lgzgwxm7ZxDeTM+ttpu2xsIwBNWJPeY7nuRYUzYGRR4IwYFeYMqVV43SJ8TEBGSqYAFGVTLbPi\nLXgzrqhuEsypjuOjHacs7FiWEbVTlCpmWhAn8hJL+IKlQNmw/CHDjhszMzYj4zragPZYtMqoliqc\nDYizBWIeCNJswZRb3Zt0YNOjR49XLTrA6dHjJY+1m5u1m6db3gzdCzy69Eb00qeRcPNd+Y3cOgQ3\nLKcbKWK4I8ThneRTEqusdLl2u6+VUtSdqYBtPGbtxFMCSIAHOTafU2SMRNkM0I27nXkLpBlsikHT\nIFXbSFtyEsYDBpN0vBq1FGKggMiM0ZVJDDwiqrrGutUYqCGOAKZmKUVtYpxKKnZUNzYsaLtyAzcD\njbvQxgMbe+0hTfJi4jwP9pn8LdcnNfbPLa8cHx7UAGVZlDd59BDHYI/3x4mmoMGcQQ/l9x7ozJjA\nqqywde5BTsQZA8akxok453msSl+K9VAt85r3jVffJH8rzp/Z0BGEoMqbgOqvzsct4c24obppHcOy\njFvbVsZl9aYyiLMXtwQ1vHONiODN811LfVOX/q21ur8+BrTKqF60uOQ60sFLj1cpGI/PxPhxzU2P\nS6IDnB49XtF4HjdPL21J1wOElA9F2DPZoEafAEDMqbzCh/lKEJa+M8d+U1wdAFGiDBtP3veicHip\nphM5p8GWAIbiKX5+gj8GgTiBHKxh6WiTIAxyGVjyx3CfQ0s6BhXlDDJT4Cjr0Sr2BpL1PiAgcoS1\nHk5qFWJNvkVZM5OVJUVd5rBaRpVmvfK/2YI3gU4FwLHhA04J3Aw4NaGNDbfvWXt6X1IV/LJV4Mb+\ntkqnarhzNDKEq5Q1ts+lv7mcqTmMIuw/gS9zgj4zzogs26AGOXk65pUzA3HSSrpTCXFk4YvwptNr\n3ley7dV3SDvMBYNtqr5RW2MQia34oKbkQ7C/5ldj0/V+NgJvBHBiE94YsF2DNwJ3StXNGnxtHcM2\nnoc4R2MN8kTeB0BRj2/mNq+X4VYUd+wcVhtpP984WCrl44HLoDqM6dGjh8U8z/jP//k/4wd/8Afx\nEz/xE/jgBz+IX/iFX8Bv+k2/CW984xvxlre8BV/8xV+M173udQ89qy9sdIDTo0ePew9xNnjsEOeI\neuCOHXcwNxNgSUSDez2k11KSkz9fnbYadJrpJ4FVbSJhUIO0ZIEJ+hyaSjWOfpbnInvT2HT8Wsga\nmevDkkEDOa0EkJwUIijUsU+kDCQvh4Cb7Jtk1jaMXJZlnWpGyuvOkmBSqMMEbTMs3xfvjAw8GKK4\nSQk8sh+KlVHVq6b2xTBFTgEDduCNlXBZNyODMAGnBG5GtuH6HmMBbGpYY3Nv87QAN1S+T9tuZZvW\nx3srwYvF6/y5KSh8wi1gpkzApSwqIjInoONhzsxnBIQFyJnpnCAbaTPoAN0vApoQx3cJK5azgja+\nfCqvC6eGKrZBhmTpH5V7UoBBnbwNzIDY/Kk8gPFd5uT7UiIl+7Z9nqy5F0bFFpfAm2vDwExM7ym9\nj9X+Y+PIMUwJ7NRwJyIPZ/Aq1xDgsw11IuaFGod3VDLXlk9thR1LjxWSPNb56tGjx8PEG97wBnz4\nwx9ufvYjP/IjeO9734uv/dqvxXvf+1589md/9vOduZckOsDp0aPHc4lHBXGuNkWecSnEkVbTjTIp\nRFF2IGLAoNoawSMRsyZ3QzG+qFCCfisb+Qr04ARhDNwkoEGSrLB+I5KAnJYqJ0I+8woWD0DEs4JS\nyZMlvgAKn4vIMhGvrEmvmVaf4NfhyzAM3Jh3BmDD8jPrZIQKJHhiJqgCseT7xLL+yCe8CnWsnIMo\ntyEmJu1kk0HHDIMdQSHAgBkKDXT+RRkTtWortxeWz5btw1ueNjW8Me8kgzfW2ciAzcBmhzuiVtqI\n4sN1M6tgDRG59zl5DCsAZ+0wqsdrJck+uc5G1rLfWFIY9TNW2OTVOVImZUl4hjkzJkSKsCPFQM5E\nZwGkrIk4QaZLWIU41v5d5nc9OV9rp54No6vSNM6d5WR7Z2ADZEDjTcQLFZuNg6y+8cP999M8umnU\n0KYFcY6GP3YTaFFV3AKwJLhCaTwgc87IWUkT4RR0XH/fAHT+PDZ+x3RaxXQbVEf1Wwmae0XYsjta\nNs+WZZiL92m8u5ZZLdqJP77o8KZHj2NxiQLwRY9f/dVfBQC88Y1vxBd/8RfjT/yJP4FP/MRPxC/9\n0i/h+77v+/Cud70LH/jAB/Cn//Sfxr//9/8ef/SP/tEHnuMXLzrA6dGjx3OLRwVxnmMYrAGQTWzT\n66Eoq4nqtyLfE8VO7YkTFcUEUyoQgVhUKJLQZFjDlMuoDFSYCkc8J3JZkaVRXoVDICnXstekeiFN\nvCaoJ43OSxPi2JP1Avq094M6XTmSvpjpae2jEZBhTt2K2I/rgQ2YFWtIu+EASm2H5XUOSe5n/WzA\njAmBBkQ+q8npOY/rvW4QFB5U3jeVYbH/F1IXI1HdAJDuRU6FM/Ipl1BBOhyJ+mYAJb8V04MMq8Am\nuGFEKF6X6z0P2G9VXwGdLKjSm1pKvk1ZdaM3vQ7qJLWGQh27KWZETNrK3fY9AzkAEriJFBUIyjqf\nCRj0dwXIyXhEUdpOa/v3+rTlj+PVJaa6HK1s4V6vQ3LrOSmeDMx4EEPLNbpmRF5/dy0EkPrubgJX\niLw+0MZdTtCDG3tv0MUUM/Xf2UGeyISZs/omQo7JVB6FclrFP2Q4wyym5qa+qcunzP/G7zcRLPAP\nsVDcmL+SvZblav+t4z6UODmuKLG6h+jwpkePHq341E/9VLzzne/EW9/6VoRQXiff9KY34fM+7/Pw\nuZ/7ufjIRz6Cd7zjHfiRH/mRB5rTFzc6wOnRo8dzjZcT4sSsJnCgwCd47LqXWDIJsr5J2hFHgY2V\nggxsBqtRtQRWxDPocCt54UKFM7n7auL8hL6lwjF0I+NQSpILgYwlduwW0BJLpl2Io42dEsiZkcsz\nWuGTQADN5K9c+3m8cni5ny0AD20bp5bdcAizLV89XVXgXBNrrecL9Y2iF1HgZC8bgzcDToXPzYhR\nVTiKfHhcBTc1tDFgY5BAynpsvhywKeZ3uVyXKHBsO6XSKQf8mEn/yjRyWR9jpgwyo2I3D3JAEDNp\nyok28Zx2eOYo1rE6XkAESMqmasWMQZw16CbL7MqmVhQ56fM1iONWm1fj1J8V411wOrUSSF8WuRhH\nlzWghDhbceSYXYM3s5YpCrShrKhhOT5nHQcApmjvOX9WDdtT39TlU159I8sg4Cb5JPFcqGuS4oYz\nHEyvOa5CnYvjEatvOrzp0aPHWvz4j/84TqfT6ud/8k/+SXzRF30RvvM7vxP/6T/9J/zsz/4sPumT\nPuk5zuGLHx3g9OjR47nHywBxEoRBOwn34xQgx/ngrJVRRc5JvChftHsOi7pgYoiqwpQhamjsVTim\nOplTlqwZmWWixWN1P6ySqqTInaq8700EMEIgTvpthTcmXDBQEpENUuFMT33UZRCmK2glgjbcfy9y\nCXhaZRh++o8lvPomv7fXuZuRlUwBgO9m1II3Vi5l+GZMpToZ3IwUCmhTlvBkzOA/s/cWLYDgj29G\n6ccElAocv4vae1F5QdUylGGOU0MFVefUIAdQKKSqEjAUztj0BdTAlFfIrd8DA2Y8zTp8vlVCfmHE\nxnqz8F3mTD1TH7feF2sgp2LR9Sm+UUvoKtNkdzpoH6vA8ngFSnBjwz20sfKquVLezPa6ADf5+8B6\n6VTL++Ya9U10Y8vvtcup6vIpeb0stWLWf+51Wz3jEfDe/vawYKfDmx49Lg874zymuK8jeQveWHzm\nZ34mvvM7vxMA8NM//dMd4FwYHeD06NGjx4FYlj4da5ls40eShDSV0pAoKOy1eXHUKhxJKLMKZ4IY\n75oXDgCkzlTIKpyUuXkgcwXEYc7jGLixQiD7vyXorL/fAjl53ByE9pP9Gs7UiaBX4Vjil30xypKK\noswCJQSySL/DBqgynMrj5C/UapJrb8qSB07Vrr5oRZ11NNkXRzfIQCeYSfEWvPGqmxFUKG6s45Ep\nbVrQJqlxvAKkUofUr6slzetKV10yxTZli+5Dth1JyGeyqwq6DRP/g3m6EMBR9n0iVS1IS+YRg8BO\nAiaYQkZve/iM6NZvav2uxyXBuoa57VNAp+1zAPMM0Potljcr98oiD2b8Ohsog640D7B9ldL7wsOK\nqnOD+j6B2so5Xevp/6m0sHE85OVYbtuW4saDG9vGdtwKwKEC2Hjljb0HnPImitIwq3A4q3CijceY\n9K/8i5ggf2fMC/WNs79O7ehNfZNa2rO89kobATSzriMDNftmx/u6JlufjweYPKZ56dGjx4sb3uT4\nyZMnDzcjL2h0gNOjR48HiZdBhVNGu4zKXnv4I0mitJSWNtZaIMXQpDKrcEBS9kEImGjCyCOslGry\nP89ANr3U7wEKgLIfznQQ4kSSp/QDQd9bW23RhRjskCf7pEmmVwDl15YEShmST/RLzw2Zg2VCuEgM\nUZZsFGUYCm7S035UIIdz4muf+fbDGQxx8bd+DQDs/DLMKyNy+8n8midGKsWp1Df581J9QxgQrC21\nMyw2s+I8Zlbe1PCmpboZgqpyXOmUGehuwRp/BB8p5RmohGf2HSubEsEHg5y5LdnZQkEOoDCBgUiM\nEeKFAzMMb0CcQJwgaUzrZQBTVCNpU9vMeXto+/fAWKhwWvDGe10B+VgX+Cr7yICxAH4FvHHQ1Mod\nzYg8ct42zChKIFnXKcGglgwTpZ6sQwO/cpyUEMeOUwI7NY+HrcvjVD4/fqy2wI0vmZrss+heMxUl\nUzZP18KbunRqwoyZ5kJ9M+MM874pC6xyeZVX3yRFzsox7tU3rfDDr/bNeU4txDu86dGjx63iX//r\nfw0AeO211/B7fs/veeC5efGiA5wePXo8WNgN4eMAObVVJ3JCWHyWO1GlJ6jcTuiKSa2ocMCQ5+ME\nmBfOjDMGnDDzWb0oAmacAZzEl4GnAhJJ2ci8hDjV0sWoyocViMMMcJCtMmg6aLBDoA0wBEnERiu1\ngJRwGcghTZaJSX1voH43lJLvnPxn9cBifVXJoaU2dXcbgTa5DMPDG3tS31Lf2L+JlyUY2TPDlWI4\noFO0vEZ+Eh/dU/i83TPIOaLUyV2Lhqb6phV5vNwe3HeYqpU3Ht6MREl1U0CdCtzUwKY01c1vto4C\nW3pT32TPm7LEx37ZXEmClfywqmwgR4pKd/SzpJlBJFLFjqjUginaICVSgQJY1W8tFU5AzCDHqaSu\n6Spk8MaX5AAQYMB6XCGKITMRrGzKq25YO6ul9UWUjMiZDG4YvsmEawjmh5UbUcu8ZCVdAVn1tGCQ\n1atv7nKc2jHKbpzkdYOl6saAbH7NToGTPW8ijsEbKwcTBY5s2wlzKp2aacKEKQMbkr8zn8EGclyn\nKVPfpLKohvqmBW2sfGoJau7YrepAXHut7dCmR4/bBIOLhz6PI+T4/rVf+zX88i//8upYH//xH3/T\nX/3u7/5u/NiP/RgA4M/+2T+L17/+9Ted/qsQHeD06NHjweNaNc7azeVdgdDa/Bwpo0o35w0Vjrwu\n4U16Qs/ATOfUESc95UXERGeMfFKIA4w0ZogjI2FUxUEL4rAmg61yqsiMGMjBHfkokibClNU4gQQC\nBQDWFIsYSVkzEKtKQstxFObAGSkDWUWx18m9bYyak0EbZuAm4vjTfEsWDdBYIsjQpC9NO7tgiCrC\nAxsuuxy5v7GZqB2LLRiYHWygiptSfQMAXq9j/wCksqnSrHgd3tTgpgVt9syMfRgEtChhDFT94T7n\nsuuZQRz7bqgBj4IPKaeS4WIRTlJySHzIz8b8h8gl7jJ8SIfPVvkLa/+y/H59H5H/BNyIAka+TZSh\nCum+a7tFYbytw/NqKyFOVlTJZwbFYnWMkq4na6c+O/C6FXaM6s8twKqHNmvHaFbRlSVTM3NxHNuy\nszuGJwdtbHhLedOCN6LAmRKMmXFGJP3rSqesbEqWN6ZhBm9q9U3L+2a5j6ztP7dP8Px1snXNrK91\nHdr06PFqxZd/+Zdvfs58u3PCz/zMz+Arv/IrAQCvf/3r8c53vvNm036VogOcHj16PIrwN41bAObI\nzeX9l2dlFU76TY6aLG0rcQzWAHAKnDmpc8z3ZiYtAmHxOlmFOG46SaGhECdyRGQpmdEfB5P7B2Ag\nAkfWYQQmSfqYRI1DqnqYiTCQzhcxJs1rRx0/EDCZ6gYGBDgBAmNHWcGRwU4rihzVldP4p/yy3iUp\ntKf1Nk75VL9MClvdawTyyFP8DHQsKZQUz1I9e4pm6bd/am9P7O3zNCx1qZlXk7faC+eaMPVNno68\n9i2qgbK7VB63VN6k4fCdkJZqm7Jz0npENy5zHjeSqEsC5W3oS6tqiCMTyMsRiXX/FxDimyxbQ3i4\n96bL2SujyuvFgGg7vKE5I4NdQTMzmAOYZkQ2M/IZ5mnFFGU4xISZSfcYXR6BNayKmLRSKtIlx6oW\n4MFOCAwslHNB1UkCWpfAFdBjE9g8Pt0mSNvJhpVKnAxtvNpmqb7Jxygj+9yIyiZDq1p14xU6dsxG\nLD1v5ChswxsZWsKbiLMc3XyGL5tK8MYBnQx11r1vWuqbzfKpG3WgOnq97NGjR4/7jl/91V/FF37h\nF+IXf/EXAQDf/u3fjk/+5E9+2Jl6QaMDnB49evTo0aNHjx49evTo0eMewjrgPcZ473vfi8/7vM+7\n19/46Ec/ii/4gi/Aj//4jwMAvumbvglf+qVfeq+/+TJHBzg9evR4dPGongg2fXD0I1culXv3bJsZ\nA0hqGxvOCOrlAYDPAJ0OqXBC1R1HlAByWo8s5q5WTiX6Akptic0TJ6rqwsqkYpAn9MkEtVLiBAIm\nEMZUzsGq2ijVOFZaBS4VOdDXYNrRKtnatHVt7/PTfFnO/NTfhucn+VJ6ktQ1XpVTlVNNEYWHhj3F\nn1wJBkOe3NtNWO5cM8M61uQn9GZ0uv6Ufa+T0ZqBcUhai+tUOq0IldbCl0/l+blefWOfJ2UMleVU\nRNnjxR82W9Pacw4xRU75/v4jlc5YKRWZGkf2FVH5TAgUMKlB+YwZAWIqLF21BsyQHToEwiwSJP0F\naqpwzNdK2q5b+WNZ+lgfn16NA1x2bNrPyjLbe3Kv94/PUi2XS6ai/6vqGlm67bIpKc/KFsTWcWqy\nI1VNi73vzRH1zaxqR+9vU/jhVN43y9bhbv8o9sKdblWP6VrYo0ePlzJ+82/+zTf3ufExTRO+6Iu+\nCD/4gz8IAPjrf/2v4+/+3b97b7/3KkQHOD169OhxQeSkuyyjsjIKn5AXXjfAKsRh5PGOQJyAQUuv\nhmK60ZJFDuqJox43FDAyiScFBS2T4qJkKirEmdWQWEqlKIGcoKVT8heYZ/UvISmzGEMJc3wpFdDu\nZnQJwJFlyasyt/5eJoq+rXgus1iape4ZoFoi6EuomKTkAgAm0gSQsgFq6lrjyimKlsOu9OKaiDyn\nfUxK5obtLxydLjjBPfkd+esZATMniGO8gDlv4yXirH/DT6v8zNfYH0lZj6y9Zbv32ybDtg2JQjr+\nI4krkcGb0uVmxsxnBBpAPGPCJDCHZgTW0i0GAg2YvBG5vYx24CixVYjDClwjDMhqc3EHcqz0kfh2\nx6bNGlB639j71rHpjcStXCq9ZvXGsWMVcowatAFQQJuyhCoDmwkMZk6eNxGs5VKMGROmVDolHacm\n0s5TG/Ammxgfhzf1mtovn3psBqc9evS4VZiD3qsWMUa8/e1vT12n/spf+Sv4lm/5lgeeqxc/OsDp\n0aNHj0a0fXTaKerS3NgSWx2G7JHRgjgRZwScNiEOGSBSSAMqk4BIESNGMEcMNCrQ0RbLzGCEpHKQ\nbjwCZ0yBwwTMxBiIEryZtY04mf8NoJ2LzOAUCdjMTAnmlOa3GerY+HBrcd/IuFz7zUTRJYU5USwV\nNz5J9KobRhvenGOGN5YIylP7ORkXJ+8MVd/MOCf1Te1/UwOd1r7TXn7x1zEAsKeNME8VU9SwEhZN\n6WENi6TtthgB20awhFtMbfOGsXUaKIMWIiogjgzbT0Hr7ZnmEXnb2mvbjhkG8AL8+GG59bv7vWqO\nvAn1NdHyL6qPf29WLPvCWXx3SDRAs74XeDAptKGknpNNNQAVxIn2MmbgypBjNIIqRZ1sRwG/WTln\nx+Zdj0tZ1vy6VsTl1+1j0x+PXm1jx+dCmaMTNYPx2u/GzJ+9303dKtx73sTkgSPgxTpOzZiSabGH\nN4XnjR7T8tl21ynzvknDivFW1DebcPeyfZdgx36PHj16PN9gZvylv/SX8N3f/d0AgL/wF/4C/tE/\n+kcPPFcvR3SA06NHjx4pVjQEqYxK3xYqHMC3FW+VUvnkTgagCXEIAYFOBcRhCiCOGOiUEj/JvaUF\nsv5w7kxEVo6lTZR5wIgBjIiBB0moYOUsATMTBiJMxBgTvFF9UbCkT5LEoDBnpjLRC2SGxRno5E5G\nVCSJRScjl1jU5TqxyjmsXbENL7vduETf3q8khkVr4giYYawlhLXyxneumRLEmXQLC8yZ+YyoT/OL\nJ/LO4NT2j2xmvAQ37Paz1J74gJlxhEIeLb0xzYetX2vXTsxa7ld1boIZaFs7bkn+oyqZbLv5bZI6\nR/myqgN5YqnCKcENo9y+LXjjoc/iM2aYzwBz9hsw4+mivTtMLTWnjkNrcMcbUNfDivcJwC5VODPO\nCmoCIgdMdE7nACulku9niBMpJOAqgEZBmyrjzIhcShpZIewSts7Eh49Lf0zaZ4tteODY9MflYphT\n2tTQxtQ2GfJkxY1NpwVufLmUgRszKzZQtt5tKqtxDN4kBU4FZxgzYpwWyhu/H5SlU7EYnqOGua/e\nk/kePXq83PGOd7wD//Sf/lMAwBd/8RfjH//jf1yUYve4PjrA6dGjx0sX99uBSvBHnYDb+7KUqvTD\nIf2eva8hjkz9jNTCGAGDKnOkK00A05B/zzAKQbrpcMSAU4I3I4+pOxJxwAhrtTwkv40RhEk7VSUF\njkEbJpAm+UOwxC/DHABVG2oPdJYqHXsts6wyIrSTxLS2XbLok8E8rFGu4RLDugzDFDce3OSuNWXn\nGvPOMOWNwRvzIJppSolf1Kf4kc/6d2qqb2zb+X2mDhledzmbk4IjdbnSjkaDQgL7/wDo3iPvA7N1\njc/rjgTiTODkeTRIzyTZNW3bExYgB9A200CSYQTa96RpbVeu3ntwY5P38IYbiXwaB7nde4QJ1hNW\nS+ss+RZRO2n2AG4r/Of1uaBW4TCCQoMpL7ieA5KqLg3zShzrgBXSucSUczEA8yzA1UCOPz4HB1vr\n47LVHv7oMWmRt+ESxNn7reOSV6BNAjrIx2epwCnbg3vFTV0uFSkmr5s11U0CO/q+aBWuMMcfs62y\nKb/dF23F/f6wVzrpv1fBtB49ery4ka9Qjyfu8wzzN//m38R73vMeAMDb3vY2vPe978Uw3Kbku0cH\nOD169OixGkUZVaXCKUP8cG4FcXwyN7MAHWk5LGocmU6EtQ1nVehE0pSdQwI5VlZl8yVtpiNGBBAH\nWGnVzAJsZlK7XFXlhAbMIcIiASye8FdQB0DxHSsss+G728HdZSw8NzgPbyWGKdFfSQyzl0YuwZhg\nhsVteDPTpFtdYI08yS+TwfJJ/bxI7EytVRphi3pmSGvItDSzW2vSjlrWXUilOOJ/EtP+AQYmyEV+\nAjBywETy3ifaA6wNt3yJ1NjWWnN7kCPqJae4cdvu0hvBpZLKKTXSNuXFNk0G0g7sTGy4ZpnQmxLD\nl9B49U3pW5TL39Jy8bHEuz6m5YwwgkngzcznPLKtNwdxGNqKnkcxE+cBI+SvoLh8LJkiZ54plzrq\ndjJoU8NWf0wCJdQBLj8mbRtYFCVUjWNSxi+Py1TqGJfbeuIM5uz4lDnkwuPGIF3ezhnc+HKpNa8b\nr7qpS6Z8uZRt38vgzZrvTVff9OjR4+WNv/f3/h6++Zu/GQDw+Z//+fhn/+yfYRw7crhl9LXZo0eP\nHhdHVuEABmpKiAN4hUUJceRD995BHLAAGCJJ8L0ahzBIeUSlxiFNQuTzEuQwYk70eUyvZxAGHkVt\nw4QBA2aQJH4gDOppY8Bm0NeBOCWDsuwl1LHEEVgqb0w66zHYpcli7ZsClOUZ+X1ZgrGVGNbeGb5j\njZmeet+MpMBx8EZgzpSe1hdP6l1iV5RbwJfcicqGSPYrplkBT1ZvkKIF66VkST/4LMAOEaBJFBwN\niBOYAArqWyO/DnXLYV23QeGDbS+BmLbP5Z2VbD8sFDn7G9OrCgol1QLO5O1s4GY5TllCs5bUWxmN\nT+hNmVaXT3nAZp3E1krgFk9Tq2M6UgDiBAQg0CnBOOaAuQFxyu/a/Il/1cRBusrpdhJvm7IE0pRy\nSWVTHJdL0Crb8e7HpM2TbS8gH5P2eqskrt7GprLJJXEC5uR3bMvMeUv7bVwpbmpw0yqXaqluaniT\n9oEK3hT7ywq8afneNOHNrvrmOtDTfXB69OjxvOKDH/wgvu7rvi69/6//9b/iD/yBP7D5nb//9/8+\n3va2t933rL1U0QFOjx49ehRR+uCsq3DyeHVnquSHIRNYQhxgkbQxizqGaFhV49iT/UKNgwxztkAO\nKQQI9h8HTDRjxJBUOWEF5gTOvhkpKdQFtNf5KT+7p/xUdbrJr9F4vblVuP16r9ymTv4N2vgn+bVi\nY63V8ETn5Hcje0Bswhspo5rS6xretLoXpfe6j6XxCUXiD0IGC2yG1icgKTzGAuLI9EcEQzEMMLQ7\nERQaGaxzKqsWzNGm2LbiE8SxbX1UhxPdeC0wl0Cc224e3gCmtLHPTEdTJvZ75rWFEqNo/Z7Lp1ol\ncD7WtqUd05EA4pj2GfuMqnOEbefIczpOTY1jsNXWvsGcybCug62ixLFjMsNW264yr6WCDnBKnIPH\nI9A+Jo8oqezz1vZd26527Bhcbaltao8bAzh3BTeLEkgHa/wxfTm8cbFXWtWjR48XOph4tWz34eL2\nYHeey2vlT//0T+9+5//9v/938/l42aMDnB49erxUcR/+N0dKqVoQZ62cKifq0DIV/a7LgWeIOmNL\njRMseVCY0wI5Yowsf2dMGHhEwOCUOPKXEJowh9KnS6ADoIA6QIY2ltCXXjn5ZsE/5Q872yxWNxn1\nk/86KbRxfGLYgjZHEn5veOo71QDI7yt445N+n+i1jG8L7xTdVyIF9aWZFbhoGQ6dMTCyegPIcM9B\nHGsnzxzgW8vLllVlhkIAAzkzCx6oYQ6A8nW1rXLCn1uMbwVzuS09rPHbrX7t1Rg2fp3gryX3LQ8U\nA3GlYa35oJTJvW2bluLCb0sApaJOu8vNmDBgLCCOHbsGbnIZpPxuLoEUAGsgB8Cmcm4NtnrQCnjl\nTVZU5Xnb345rx+QWiPOva4VNa3vaa9um9n1/jGaXo6zAse2bShltSndU3PjtXB/TtWExcATetJO5\nrpbp0aPHixqf+ImfiP/23/7bRd/5Hb/jd9zT3Ly80QFOjx49eiyiVOEsIkEcuwFfV+IsVRYlgCie\nwsPKanJpzV5ZlX2XaHCoRV8ruBEFjkIcGjDglFQ5azDHXhHn1x7oWEhyL5+lsipNIGXN5Kf+rfdp\nOhtJY0uxUX+2luwfSQxb5Rd1p5o62ZffccMU3PjWwtFeV8n/IlzSb3DPlBsimhEPlQGnBHGADHIM\nBkbtQCaoTNrJi5Ijl9ENPMCccxjmiZS3VbEtHQxAo4QKOk6od+Jq+9bbbG2b+u0nU8vbUMbjPM7K\ntmypMpLR9Mb2TBDHbatafdNSUTW36QGIY8cuY8aAE5jkd4K+NuXcjDMGOiFgwqjmxhPlI1WA7GWw\n1baPP+ZuB1S5GGagpt6eCbpuHJfRDY0J4KxDG6+2uRbc2G/sgZv0uiqFau0ju/DmnkqnevTo0eN5\nxziO+IzP+IyHno2XPjrA6dGjx6sZzDtmDxulVECjnAoou1MtIQ6lz/MspLAyqpTYKcjRsqqWIid/\ndanMaalyAKSk0CtzAoYMdNKw/J8HOgAS1JElluRR5sPBABtmSWMqtbF5Xq770Ngescr+6wTHKzJk\nnR5L8n1i6Mtr6kTfl154xY38VtmlZq1sKid6dSK2NLRmyrDPEsGIMwKdCogDIKlxCDGDGxL1hiSq\ncwJ0Ymbty+houR3TsBLoeEjjS6ha2zFtwxa02diWR7cj3Hhb27MGN7UqY4aY1c44p6S+VlHVib7M\nV6268dt0xaDcQZzAYlJDMP+qAYwo4AYzAqniBnM6Fu28YObZdjyOPBYwpwVb/bYV0JtfF743a9tx\nY/tdux3z9pPtBmBzOxqskd/S798B2ti2O6q4Kbb5Yl9Yqm78+3uHNyvbpEePHo8rGPk806PHXaMD\nnB49ery6cQuIAyx8cUqI4+6xK6ECkd3Yu1RqDeRADW2dqiZ9pVLmRCCBn1qVE4GmMsfDHABNoAOg\ngDoWW3DHJ//ldxrrncvh9ZP+1nCfEJZ/l2UXa4lh/RR/q72wQQDZrmWyH+M5JXhr8MYncrLrlUm/\nL62zTkayDBniWPIPVemEBG7GDG50u418SoocU+H4bVmrrert6eFca7vV77dKGOvyqdZ2s226tj39\n+zTuzjZtldO0tumR7ZmXZblNF2C2gjjEajwe5ZhlqOIG4lU10Iio29NADmHAjDOCKudkm4QEdFqw\n1W/DxTY9ejwePBZb2661XWtQk7YpttU1QIY1aXtbaSJyx7A1aCPbY6m2se1mahs/nn22Wy6Hcpzy\ns7k5fh5YlVNeA2969OjRo8crGR3g9OjR46WKBWS5c+xAHKChxtnuUJUSwbWyKqANcrS8xhLB5J/i\nSqygHjurMIcCkFqT5zIrSdhKoCOzkRU66b1+lj8v4Y4Nt2EWRckG++f/WIyb1/4yiTEwk8dZJvUA\nisTehq+WXXCZ4NfJoE/y2T1V9yVTPtm38qk0h41Sm6zGCotEcA3i2HbN6yyrrRgziIYEckyR8//b\nu/N4J6q7j+Pfu7BeZFcQVCwIuFusK9atLrhg0YK2tlKt4r608rLulha01laf1rr1qVZ8ibttlVrF\npT5q3asWFxSXWhdERBGQVYGb8/yRO8kkmUlmJrMl+bx98fLeZHJmkpnJzfnmd84UV1llH9fiGujY\n94U9BHDaRyWBjnE/95xCgMKqmnwn336ftU8kOXb2s797G05jD26sqoyMWVdSjVE+jOvYuuJOuC3I\nyS7b3HEuNmeDzebW3D7NhbDNtgo607H/bEGOPWy1rn5WqXrO2k/N2caL9ntpEFfNuWjfX67702Xf\nWfcVhDNlwhp7u/ZzNLts4T61Hl98vjpV29iXtW53u83aguLlCpfxXnWTfXzA8IbqG6BmWHWkacJ8\nW7WLAAdAY6tYhSM5hThSUbWBpyFV+c/cxcOqZAtoCh5nC3IKh2NlCjpext55cwhzZNYp09ScC3Ok\ndbkOu1XRYXUYpXwlTX6oR2GoYykOd9SUva10uaKf7XNuOHQgS/aAy9UbrA9EJZ3Fok6hdVvu/pDm\nyvBadWPcPrjlDr98UKeiCg57h7+pKTvcJrv+tXIaNmcFOU5VVpJLKKeWbEVPUaBj/7+1rJ1TR9+p\nusq9mqpweIpU2NG3/9/e2c/97tThD7hf3cK4cpVUjvvVKZhtkjKZdR3nYz6EzWSylTcFc1t1BDnF\n1XNN9v1nSs9Npwo6SSXnbbXnoqX4nLTvy3Lno/2xJedk7nUtra4pbLe94Dx0Gh6V+7kotMn+373a\npnC50uoZf1U3hY9NIryhkwYA9YUABwCMrcflqjDEkRyCnDJDqrLNlxlWlW2wYDOMsao08kNgisMc\nq12rMkcqDXOkdblKAElqMtnqC3t1jlRYgWF1GrPtF4Y61v0W945ifpnijmFBEFAyoXFLx6vnfOnm\n7EtV1HlscukoGutKTvlOnb1yw61zb7XhNFdGcSfQraPvNgQj97QLrlKWPyasYK+po4IjdzQ1ZS/t\nnbFVYjjNf5Sx3VdcxZF9XEvBPrPvr4IwztoX1pWLPIQ3bre7ffPoFOBkb3fv8Bfcbu+IO4Q21u2V\nArlMbt9526f2bSjZt7ahksUhjmzndD7IyQ9va2rq+GdaCgLX4nPTep0r7dvsbYXno9dz0X7+ljsX\n7a+FVBjsOJ6PttfMfk5ay9nDGnsQk2/TpXLGYXhUwbo8TEpcuC7n/ZtocJNdibflAAB1iQAHACw+\n58TJPUzeJziWnIMct6FV9mWcwhwpPwTC6vwVhzmSCjt5DtU59kAnu4wtwHHoOFrsVQEyxdUapSGP\npIIhWE6sOVvKsTqClsKOdWmnMLtMaafeWq6aCU7dhteU6+g5X2q+qG/W0eHPaF1B1UZxpVWuisqq\nsiqqyrEPmZPycyDl2iiqmHKrtLJzqtQoDnicOO1Xpw6/fVl7CJe/r3wYl/0942nfugU3ueVt4U3p\nPDiW7GA36/bS/WobUtVxtbCOF60j1Cmc38pxvxadm/agTlLp/rWdj1Gei1LR+VhmX2V/t7+Gheek\n9foVLG/bf/b7iwObwscUhjwFj/NYbeNWZVW638sENxLhDQDlr40JVI8AB0DdqWoenIrVOPlApnid\nUuVqnOwqylTkZBuxGs091qq2cfr8Xjw/Tr5tyZovJTeBqlTQebeqc6xAJ3t/vtNoPTbbpkOA49BB\ndAp47Mva+y9uVRxOXOfgKOoQFi/v1DH0+g1+cUfQbbhF+aobp+oFh0osW37oNBFubjhdUaVVbsic\nCqtyCius1uUqPOyBTkZFIZwKwxm3jr+lUgBQiRXOWPx0/AvvKw3krMe4Dalx27eVAjmrnSz7vrVX\nYnT8UHCJeFsYq8Iqq5L5rXKBa2H1nKR8dY6s87YowHEJXMM8F7OvSun5WBp2VD4fC+5zC12KHuMU\n2JR9fBVDpIq31b3iprAdb8FN0WOcENoAAGwIcADASZjVOFJHkFMY/jgFOVZlRvaOgoY7lpXtsQ4d\nLtv9TvPmSHKszpFUWKEjh3DGXqlT1AG0dyLt3ZGCjqfcO/uVOo/lJv8zLh0qP51Ct2/wK82T4bXq\nxm0IlX2C63yI09zRnrVgPrix5kXq2JDCyo3c/s4U7LumXMfZ3uEvDHSsZSUPAZyNnzlTilUKAIpD\nmuz9pfvaqVLDKbSxlq0UytkDuXxbzvu18LYsx/2abbz0ynNF+9Y+v5VT9Vy2/UzuOCmpoHPYx9bW\nFe8/p/PRa4jjHqa6V8ZlHPatW2VNwe+O57S3wKbSfU7DpJyHxrk/L3s7+QVCqrqpMrxh/hsAqD8E\nOADgxlOII1WsxpHkNqwqu5ryQY7T8Krs7fZNzXYKrcCmYwNy95WEOQ5DsNwCnVyVjsp0Am2dyILl\nCgKedSpmdRg9dGU6lnPpONq+6Xf75rzct/hOHUL7cs6hTfbRzt/uuwc39m1zC3Ek9yFV9uPCqp7K\nBTlNzbKuSpZdJlMSxDkHOpK9w5+/wtla1+CtOKwLqnifVgrksrd7r9TwctWh0isOuYU35aovCm8v\nV01l7dvcMeB01TlZ52177tzMNuOtgq7kfCwKW4vPxyD70zGEKx7eWOF8tN9eLqwpbrtSlY1bu+VC\nm9JlS6vnnNrK3+kluHF4XOlKyt8PoKYUT8IPVIMAB0BdCu1y4p4nOJacghz3apzSx1WsyJEcq3Jy\nd7nMmWN/XHGYk22meILkjk6uFeh0hAKSwwSotvlLyn7Db9bZnltetQGAUyfab8ew3Lf4zp3Ews6e\nt6qb4u3M73OnECe/jxxCnPwTzW23fQhOU1OL2jtuKw5zsk04BzrZtvLBW3FHv7g6IxcOFO1TL9zC\nD6eQxnqOTo8PMrSmcjBXPpQr3X5/+7ajYcfJyu1BjnWb/dy0nkvJPpZ9jq2MbR0OFXARnYvWcy74\nvUzlins4V7jPsu24hEA+Q5uSx3sIbpyP1fLBTbZtwhsAQPgIcADAiwCXG5dcgqSCahzrcVL5IEdy\nrcpRvsOfva9ws6023cIc+/1Wm06BjtVpzG+bCjou5cId+3aGyTHAqdAxzP4cfK6M8sMtisMbt85a\nfp97CXGybRY1UVS1UXxbuY5+wb52GebWVLTtxm3flVR2lFdcoZFvxjmkyd/v3Kn2EtoU3p7fx+X2\nr7eKqnKde+d9a5/gWHIPcjo2wtO56Ri22t4TsvcVbmvY52L2OXg/H4vv8xPYeFvGb2gj+Q5uJB/h\njYeILMTwhuFTAFCfCHAA1K3QqnByDQYPcSSHIVWSjyBHcqvKKQ5z3IdZWf8vDXOKH5e/yT6Bcr7D\nb+9sWR33suFO0XNyY68KqLSsxXkYh/eOYblAprgzWLysr6qbkuDOWsY9xOlYUem8OHYuQY61PW5h\njqSiyo3ikMC2j9VSErAUbEJTs+f9ZW2X4+0V5hop/t0ttMm2VTmcc9u/lfdt/jHu8vtWchlSlV1Z\nyf320Ka0AqfwvtxtfsJWVd5fxRU6YZ2P2d89DrMqCfG8LJe24Mbl8QUPJGwB6lk6r0LF+06tIsAB\nAD8ChjiSS6BUZZBjv99axl5ZUfjYwsqA0u0r7RDmfrYHK8o4Bi32IR7ZdeYrMtqLPri4Drvx0Eks\n15EM0jF0mrS0XMe+dJkK4Y1x+Nnh+fup1sgub6vG6Fgu35F3COlyAV57Qehm7+AXB232YXbFCo+B\n4GP7K1VtSP4rN8oNs6kUzlW+glj+MdkHOByPLlefc9u/hfusMPjJt2l/AVTUZrnzt/z5WM25aK3L\n/T6HOWTKBClugYvj/T5Dm9LHVJqYuLDd/IJu4WN6whuqbwCgfhHgAKhroVfhSFWHOJKcgxzH6gyp\ncpAjFYc5bkFO9r7Cp5K/vajTWKE6p1ilYKdgWYeOndMQHK/BQKXOXvHvfic6rTRXhmNnslwHuGB/\nB+nkZx9X3Pdzm/Daeg5uHXzHQMf2HJyuTlT8+nqdC6dch99L9Ya1zbmfQ6qq8nalqaJtcXsuJftX\ncq20klyrcdzCVi/nptfz0eu5WG55p3U7P7ZcoFI+3Cm9zXv4E0pwIznu7/JhCZU3ACTTlFHGYVh5\nkkzIH40RHwIcAAiiihBHcgmWXKszCtspDXIkt6ocp7lOnKtyfIQ52SfgWXFH0nU5j9/4e31cNcMv\nKlXoZJWZ78bLc3EJcQrbdw5xpML95yfIyS9k3xbbj7ZAJ78lHvZhwP2XX2/5oEbyXpURNKArHxp4\nDG+K7y/ax4UhjlR+H1uNlRnyVHQ1uqai94qSoVAe9mXQc7HcY92q/sotUylc8RcAhVtxk11f+sIb\nqm8AoL4R4ACoe5FU4XhWPsSRXKpxpLLDqqTCDkil4VXlJz12rhQoy+3lTKDv4Nph9NU59BYCuHcC\ny4c33iqvijv41vpKO/j2dZcbdlNuSJ3fgM4p2AlL0ImNi28LMrGtc3hT4TLwfgKOAPtYcp+YPLtd\nzqsqd57Hxev56LZs6W2Vl/ET3HhdR3bBiMIbAAACIsAB0BAiG0olVVWJI5XZNg/DqvKbUvytunuQ\nk11naScxf7+981E6+bDbhLUlkylbt8fQiQw6ZKPS3Bnehl64hzfFnTxvVyUr3p/uHfzCZd0DuPIT\nXVeYb6XwCUTC6/5zuz3c6iovl4Ev2h6HF6Zk0nKPIY5UaQik8772uh/TdD663VZueJTbOpzbibvq\nxqW9kkaovgEaSXYK4+BzxUWD94taRYADoGG4VkFU3XB1w6mkCiGOVHFYVXYziitqJKtj6LaM2/Cq\n/DLlwxz7sn5CnSh4H7rh3vGrNNdN6e3ewxv77e7HYH6/Og5/sd1WfrLqoisWFQdwLmFO7v4E9qWf\noTdS+aqLYNVVkq8JqXPb4XE/u4Q4krXf8udq8X4uHhaVf4xzaFd85Tj77Umfj+73eazQiTK4kQhv\nAACpRoADoOEkN6TKuXrGUjZgKluNU9hmaZBTWI3jtExxkOPcjvP67Mta3DqQTsv44aVyIEjn0Ouk\np9WGN/b7K3XurfU5de4lOXbwy1XjlFwO3uEKU07VGV72ZZiqGYJTKbgpbqdchVVxG/4nsA26nyW3\nahyp8lxWbhVY9sc4iep8LL9csNDGvU0vw6Wc11tdcOPSZunGeGjHP8IbAGgcBDgAGlLo1TieqnAs\nYVfjOLdZaViVtYzk3pm3L2Nfzrmz4jw/T+lj3Zfxq3wbHjr81QY3TtvksTPlP0gsraZyC3GkyhUa\njhUbFfa/k8iCOM+d9vL7p7oKq+r5D3Gs7Smtxsm2Vxi2egla03E+Sm7njp/Qznn5KoIbyTW88R6M\nxBNuOiG8AdLPKBNb9SPqHwEOgIYWajVOHCGO5FKN49ym+7AqqVyQk90G96ocS2G7xR9Owu8gVua9\ngxhaeFMQEFTRmfLZsS++z31uHPt2u1ThVAhzcvd5uJx4EOU+2IYxNK54HdVWWGXb876vgw2bK626\nkioPf3Q/J9NzPpZbv5/gLivJqhuXdh0bDDdoIbgBgMbk/2szAAAAAAAAxIoKHAANL9k5caKowlFJ\nu04T4hZXc1jLSc6VOFJpBYbz8KribbEL63sDD0NwPH7DX244RsUqhSqrGIJXZkhe58Sx31epEsd+\nm8XtWIiS3wmNvQ6bKm0j2DC5IAr2dcn5663iqvR+90ocqVKFnBTu93jBz0kp5sobKYTqGx/HCNU3\nQEMzJqOMSddVqCKakgsxIMABAIUY4vgaRiV5CXGkMhMbS6EPp3Jf1nlYVfFjLM5zo0QbAFQ3LKPS\nlWuKfvc5cbEnrsGcUwjnbU4c58c6BzmS97lRgsx946RSSFbNBLjBwpviRv0Onyp/The06znEkaod\n8pim8zF3v885cbKcO0GpDW9CRngDAI2NAAcAwhZyiCNVU43jHLQ4V+NIfoMcS/BApzrhdRB9hDe+\nOvTFyzq8Th4nubW2y0+II3mdI8XrPEdyXS5MfkIbp+X9VFl5XUdlThU8xedNuX1dKMgk5Nl1OIes\nXiYyrlbQyakrP959f/k9VmIPb0L8mpvwBqhNRiaFkxjzflKrCHAAoENyExpL6QhxJL9BTn7b3IdZ\nFbcRNf8dxLjCG+s2v53m0hBHKr5MvHOIk92+0mqcwscXb2u8HX9vx4X3Sg2/4U3ZoVOeq6zKhQh+\nQpxKgZ3kN8iR0n1OVt4OwhsAACwEOACQGlGGOCppu3woUz7IsTg91kt1TtiCdRC9zKERRjVGZZUr\nMyodG5VDHMl5eI373EVlhvbVyBWM/FdapYGXEEfyMj9O7nYPYU7YvHzbHH5wI0UT3iR/nFB9AwCQ\nCHAAoECyVThSsAoN+zrdh2SUq8aRygU5LQ63e3lsxzIhBzp+ypD9DMnwO+dNdlucOlWVtq/KfWyt\n28NwKqm0KsNtaE3lSaij7vgHr9JIdo4j//vbb2DnPpeN+0Tkpcta63aoqErFOWkpP9Gn76obKZnw\nhuobAB2MMjIV3tsArwhwACBKEYQ4FUOmACGO5H9YVfFjLZWG10Q9DjySK9eEFt744KEKp1KI47RM\npTlS3Pef23ML0vkPp8Pv/cpFPsOb0FUf4uQW8zA3jn1ZKe3npCVoxY0UXXgTEPPeAAAiQoADAFGr\nsRBH8jesyq0N93aiEeSb/aDhTfU8dOi9Pi5AiJNdX/kgR/K6/8J/fYJOhhssvHFqPKzqG58ChziS\nlyBHiu+c9D48LWjFjSXK8Cb5oVMAANgR4ABAHAKFOBWaLHeJcclDiCP5r8aRCjtc3sMcKb5LTxcK\n4bLD9sfF1ZmXKuxD22IBQxzJeViV/TGWqDv+0VzByEvJehyBnbWecEI7yd/cOMWPs8Q/GbVdtcGN\nlMrwhuobAEWy16BKWyDM+0utIsABgCKhzoNTFW9zpQSb2LjyOrwNv/Ae5tjbdFJSIVJ1R9rvkAyH\n22Ke5NZ7h14KWokjuV8WvtxcKG77I2gI4Gf/hnXp6SBDp8LtRAcZSuX8OKm6YY/W48spGHoX2rlQ\nOVSrqupGqovwBgAAJwQ4ABCXJCY1lqoKcaRK1Th23jqN5dYTjiDf7HsLb8KtvvG4b8teXazS452r\nMcK8WlGUV3IKfvlpr8Plihfy81wiDPdcQxwpjKvJed6MGEMb7+sLHt54Q3gDAEgvAhwAiFMEQ6mk\naufEkbyEOJLXagt/VTnhCfHqNb7Cm3A57svAQ6mkSpeEd9unXqpyouB1Qt3qw5ukytk9DqXyGdyF\nNewxXGEGN1K14Q1DkgAkw0Q+WTwaBwEOAMTNd4gTwlAqyWOIo7Lr8hfkSNF3HKvtIIbxgaqaNqqt\nsPIyqbHFXzVO7v4AVTl+VR/aWKoIbxIM7fwLEuJYojwn/V8mN5SqGymk8IbqGwBAuhHgAEBNiCvE\n8bauYBOhFnfu/HQe/XcMpUqdQ5f7UtCRr7YiI0iIIwW/3LTfYMfvN5FBghtvjwsqjGE61VThOLch\nVVMtJ/kPdIKdl1KIwY2UbOVNROFNesNDAECSCHAAwEHkExlHNJRKii/EyTXneY6cYsE7f16EFd6U\nl96S6CBXKfJfYdXxuIheB2+dfL/HUXqrb8IKcaSg+zLac1IKcbhUrsGwjr30nssAapsxGRkT/fur\nH4TEtSvege0AgCqE2MHw/O2396EtUU5m60flbfEX3kT/IcfH6+ZzKJifeWKKH5fk/vS+/hCuNOaL\n93PCW1seBTmerYfWzHlpF154w9ApAEA9oQIHAJKSZBWO5HliXL/VOFLwS0tXI9QhGVabZTt/0XaM\n/VeB+Z0Xxb0Sx/5YKb796S9s8BveuC2cjuob+7od97u1nQGuSJb+89ISVqjVsUgNDp0CUH+yUxin\nI0xH7SPAAYCa4iNMSSjEkYLOkRNMKN/qp6RKwZOyHXm/vF1muvg1DnOfhhXaVG4vjfu42kms/bUV\n13kZrOonqfAmjccFAADOCHAAIEkRVuFIUYQ4kt8OZ9idxtA7h76HTkXR4XOpnom8CsdSuRqnuD07\nP/s1+JCeCMKbyKpDOo6dgOd22f0ecE6ckmZCrsqpbqhWuOFN5CKuvmFuCgCAGwIcAKg5YX5r38Fz\niFPd+oN0/KufwyPBypsqO/Ll2/Z+VarspngJcaQgl5aOfp6VasIbf6ruPNs791UEtHGEOJLz6xbP\neSn5DkM9rpPqGwBpYpSRiWGSeDQGAhwAcBH5lahyKwrSyQt5KJUUIMSR521wXWWkHf/gbYdSfeO7\nIx9WFU65TfJyxTB/1TjR8vaBN54rjnnakAAPChiIVgxxFKxdxTXxcTRVN5FXrzD3DQAgQVyFCgAa\ngOdOTaDLaKfxW2wP2xRlJzWuTl6A+V68X90pyW8Lva8/UHjj1lYUw+aqOBaqDyPSem6mIbxJ42sD\nAEB5VOAAQBoErsKRkq3EsW9LWr4TqC68CXUITfHtEc53VMp9n3irxJGqGVYVjL/QKHClSGqqbyxR\nVOHY21aw9kMXzZAp/whvAMTHyMRU2egH1YS1Kg1/zQEAaRN4ouAkP6B4XH/g8Ca5YSVltyvgh0L/\nV3+KsiLHf/uVtz9FH5ajrMIJ4ypskQvw3uDzuI5l4t8YKuuYwBgAUA4VOABQ8yKYD0cKWIljbY88\nb1P1UnQFm0odvBRV4UhBrkTkFLIErc4JHghVFd5EcdWxUDr2VVSxRXwlueDiqZBi6BQAoFEQ4ABA\nGbFNZCzF1rmPJ8SR4ukshhfeJF99U4Uqr0rkfUiVk/jmyvFWNZTgVcfKieqKVLmF4p+EvHL7ATRo\n5Q2A+mWUUSZlnyN4V6tdDKECgLoQYacnlMt4hzW8KqNA7cXRcffayQvYGayuo1r5+advfH6eMZlI\nt68Whq2Yjv/KL5T0JORVthf5MZjeYxwAAC+owAGANIl9iI1HVVXi2Nk7UH6rBaKTrg58lBPaVmii\nqkqcaPgLbhKovgm1OiOEycADT0Jul8C5GWD/pOu8BQAXJiNjkryyoxPeP2sVAQ4AVBDrMKqq+Ov8\n+X5eoYU4lpi+Da9q6JSUpm/tqzsWvR0f/ufFiU5o4U1gIbcZQkAb/nAqJzEf87GEN0Hn44mvk0Mg\nBQCoJPlPZwCAEEU8f0SKh9k4imt7/XbyouoUhnhlpiSHVPkfMlVh2SgvGx+6kF73WjlXqbwBAMAz\nKnAAAAAAAIhAdgazGgnVkXpU4ABA2sR8xZNAVTjWvzTzsH3pHT4V5Xr9VeHEWYkT9/qqFuRcDeH8\n9nzOpv21jG37Uv46AADgEQEOAHhQWyX7MXZW0tpBTOt2haDi1YiqvdS2U5MxBCvB2w8+fKqqdhNW\n8yFOwO2K9b2Y+W8AACnDECoAQHWT44Y+uXEVfHQKQ+swBe3kpfWKY2XYQ5YwJjmuPhSq7vHp7TSH\ncDUquxo9R0seGmh/pTTAAtAwjExtVZci1VLy1xwA0q+2vvmNeWLQNHwwCT28ScFzCiqCKpySVXRU\n5fj9UBr0caU8PD4Nx6WTkCo7fJ2zaXgt0rANAADUMCpwAADhSPJb/rrsGJavwqhYNeVpf4RT6RH/\nN4vVr6/qQDby4TUhV+FINXuOBt9XVRwnDJ8CAKQQAQ4A+FDVUKPY+e8AVv38rE5anJ1EvxUgYVbf\nxDzhdDQiCAoi42NfVxUq1U4g6PucjfscrTLcI9wAUPsyMmpPeiOK8N5aq2rlExsANJ6EwoFQOkxR\nV2TUypWwKqlyH1fcV55fn1p4HWthG5MR6JyN49xJNLyh+gYAUH+owAGAupZgdUUU3/TH0iFs1KAg\nzZU4PvdJheMkFZ1mT5NYR7xPoqrGSTxYTXr9AJBnTPomMU7BX0EElNZPagCQWqno/EUs1OcYRqVM\nCG2Evt9i+ZY+hA98vl63dH3AzErhNqVw6FzVk5CH0bkIsSquEd5nAQDwiwocAEizUC41Hexb/NDn\n+7F37Lx845+yb6vSKvx5mdJUiRPgGEj40uTh874/QpvDSvJelRPBeZrY0CmJ4VMAgFQjwAEAuIps\n0uaYwxnvHaW0dd5D4vvqQ2kIcaIJb1LVaQ4loI0IASoAhCKNQ6jSWEkKb5L+dAYANSlVnUBPUvbB\nIUaRDJ1qiA8+GSV33DTu8erM++tRe+9NhWp9+wEAiBIBDgCkXcJhQeN0qBIKDSru35CqSgJ/+xfn\n61JFaJS2bzcTVKvnbPXbzfApAEB9YwgVADSM4MNiIhtKFTE6SUV8D6WyWB3jqL73iSd8qXw8VNiO\nKDr4aR5GBQComlFGGSpLERIqcAAgINPxXzwrI4jwK5J90/D7IaPwh1bFfaWtWuXvda+18DLx6hsA\nAGoAAQ4ANJTgnZxa6hD639ba7/x5fs6hhR3VBDkhBkEen08tHb9hqZXnnIrtZPgUAKAGMIQKAOBZ\nrQ6lqn0hXxUq8FAqJ8UBilO7tR+QRcrXMCp/x0Laz9lwwgyOLwBplsKrUKFmEeD4tGLFCr3//vu5\n30eOHKlOnTqF1v6XX36pBQsWqEuXLhowYIBaWloSaQNACqVkroz66xB6/FBVA8On0rFvYvyQGuoH\nYj5cx41KFAAA/GEIlU9HH320ttlmm9y/+fPnh9Luk08+qf333189evTQ0KFDNXjwYPXt21fHHXec\nFixYEFsbABpB9R3VWOf/8SGN2+RJEuFQrX8b6GP7a/a4CEl9P/8whuHV8+sDIGnGZGRMe6r+qa7/\nLtQ3Ahwf7rrrLv31r38Nvd1rrrlGe+21lx555BEZYzRkyBCtv/76WrZsmW688UZtvfXWeuWVVyJv\nA0Aw9d05Ki9Nzz1N21Izaj3EqSe+QgT/+y1t50faticujfq8AQDhIMDxaNGiRTrttNMkSTvttFNo\n7T7xxBM644wzlMlkNHr0aL3zzjt6//339emnn2rWrFnq37+/Fi9erLFjx2rFihWRtQGgRoT2TXF9\nddyDd4pqafgUk/XmJFF9k4pjoDppOTbC2476eh8DAKASAhyPTj/9dH322Wf64Q9/qL333ju0ds86\n6yxlMhkNHDhQf//73zV06NDcfQcccIBuu+02SdJHH32kK664IrI2ACCopDuFSa+/5tVSFY7JRLS9\nNfQa5ATb5qTPl6TXX6IOgjkA6ZYddJ5J2T/UKgIcD2bOnKk77rhD/fv3DzUAefnll/Xiiy9KygZE\nffr0KVlmv/320y677CJJ+tOf/hRJGwAaVXid1qQ6ZdWttxY77d74fl1qIcSphW2sEbV5vgIAAAKc\nCpYsWaKTTz5ZknTFFVeof//+obV933335X4eN26c63LWffPmzdPLL78cehsAakxKvzGOs3OW1kmU\na1odBiQ1d4z4PreD77O4X5vw11d/xysAAJUQ4FTwk5/8RAsWLNA+++yjH/7wh6G2bQUpbW1t2nLL\nLV2Xs8+5Uxy+hNEGgOrVXEcxInEEK+G076Pzl6rArEE7rXUYLqVBXO9bqX1/TNW5DaBuGdNxJar0\n/OMqVLWLAKeMWbNm6eabb1bXrl31hz/8IfT23377bUnSkCFD1NTU5Lrcpptumvv5rbfeCr0NAI0s\nmo5xVB221HYEwxByZzLQa5XGoCTybUrhc45RlOdUdIFube6zun7/AgDEojXpDUirZcuW6YQTTpAk\nXXTRRdpss81CX8eSJUskSX379i27nP3+pUuXht5GJdY6nPhtC0DjMDJqknuw7LctxMRkpKaUfL9T\nRXhTs8eMMVKZL2RKZVTt93HWaxXW+WpvEwAAhIcAx8VZZ52ljz76SFtvvbV++tOfRrKOlStXSpK6\ndetWdjn7/cWXAQ+jjUoqhUMAEuC7k1dO9R1AN2F0DBOdO6PGh1gEDtHSEOKkqRqoxo8Dr8IIXaMP\nblJ0XACAB0bWsCWgegQ4Dh599FFdf/31ampq0h//+Ed16tQpkvW0tLRIktrb28suZ7+/tbVwl4XR\nBgBELUiQwzf4bqwPgREHLEmGOFV+0G28Yye8ENb+2tX1+dogoRwAoL40TE9+8eLF+vjjjx3v69mz\npzbZZBNJ2eqUSZMmSZJOOukk7brrrpFtU48ePfT5559r9erVZZdbtWpVwWPCbqOSxYsXu963dOlS\nDR061Fd7ANIouiocu+JOntVBjK/zxzdgviQR4sT6LSXHQzmVwpyaC20AAKhxDRPg3HbbbTr99NMd\n7xs3bpzuvffe3HLvv/++evTooaOOOkpz5swpWX7RokW5n99++22tWLFCra2t2nzzzX1t08CBA/XB\nBx+4BkuWBQsWFDwm7DYq6dOnj6/lAcTE+gY5tKFU8aMDGL2qh8XEGeKEEN7UxTEVaIhktCFsOl5X\nAjcAtSc7nTvvXwhHwwQ4/fr101ZbbeV435AhQ3I/r1mzRlK2Eme33Xar2O6YMWNy7duDHS+22GIL\nPf/885o/f75Wr17tOo/NO++8U/CYsNsAAAAAAADp1jABzpFHHqkjjzyy4nLlgh7LwoULc2HNiBEj\n1KlTp0BVKqNHj9ZNN92kdevW6bnnntPee+/tuNxTTz0lSWpqatIuu+wSehsAwhHmVZcQBZ/ffjFH\nRl4cVThM8Ii4JHBup6OCCUAijEnhJMa8J9WqlFwnND2OPPJIzZkzp+y/4447Lrf8Qw89pDlz5ujJ\nJ5/0va5x48blJiGeMWOG4zJr167VHXfcIUnaZZddNGjQoNDbAICstH24aEARdSxD6TyaTP5f2FL3\nwRbpkhHvTwAAEOBE6p133tGcOXM0d+5cx/s32GADHX300ZKkm2++Wc8880zJMr/4xS9y89ecffbZ\nkbQBAPWvHjt/CT6nsAKXkAOhuqpyCBTm1eNxDgAALA0zhCoJhxxyiN566y316tVLS5cudVzmkksu\n0UMPPaT58+drzJgxuvDCC7XXXntp5cqVmjFjhm666SZJ2UqbQw89NLI2ANSwQBOeuonnalSpV4fD\np0If4mcFL0GGVqWi4sbjNtThsVBb0nCsAEBwRikcQsWftppFgJOwgQMH6sEHH9T48eP19ttv69xz\nzy1Z5rDDDtMtt9wSaRsAUL9S9qGp3tg/lJYLcyL+8FpX1TdVIYQti0AOAFDDCHACGDhwYG6i486d\nO7suN2LECLW2tqpnz55l29t666318ssv67bbbtMDDzygefPmqUuXLhoxYoS++93vav/996+4TWG0\nAQBZdAARUNq+YQQAAKgjTcbwVQSCW7Jkifr27dvxW4vEFXjQ4BK7ClVoQ6gs9RTgBAgVkvzT6Htf\n+ttX9XiltGDVNzUyhCrwuV0P53AUE2Ynsz+pEEPjMpLaJUmLFy8OdOXeWrXHHnvoySefVEtLT7U0\nd096cwqsXbtIRut07733aty4cUlvDnyoh7/uAJAaiX1ID71TUi+VFDUW3iAm9XJ8oxYQ3gAAwkKA\nAwBAmkQcINGZbBS1HlLVT/UNAABhYQ4cAICLWp8Lp9Y7sPCCQAoAkGomfVeh4m9n7arlT+YAAIQr\nhG/oTcd/8fH/oZAPbh5VeTyEcixUtQ3p6jB4V6vbDQBAtKjAAQCUUatVOHQAG0GkkxeHyMjU5eTR\nAIDKslE+n0sQjlr8VA4AcML8DomzBwppr3JJ+/bVuvS8vrXWaai17QUAID4EOAAQsvR03MJSax2q\nWtteBFFr51lV20s4Wz0uHw4AqAMMoQIA1JEqwpsQ5jtJTrChbgztaRS1MhSS8BVA/TEpnMQYtasW\n/poDABLHB48gAoc6VFyUFTws4zgGAAC1iwAHAOpJQ3f86ZwHwRCP8Lm9pslXaaVZ2rcPAIDkMYQK\nAOBRrQzDQL2KNQBJWxhqbU8TQ958S9u+BNBgMpLak96IIrwv1io+iQNABKhqiFuV397X9Pw3luCv\nQTq2H9FLa5VLWrcLAIB0IcABAPhARwvJqD5k4tjNStvrkLbtAQAgvRhCBQCocenuANbKlZ7SvJ31\nVCGU5tcZ4aqn4xZANbgKFcJDBQ4A1JvI53tI04eQNG0LEEOnPZTzOy3nTVq2AwCA2kAFDgAgAKvj\nVQffA6R1/htjAkxYW91E02msDqGKAVVhAmMAicsofYE17421qg4+eQMAGk8aPwzVh/oMTDhWSiX9\nmiS9fgAAag8BDgCgCkl0wuj4NYrEwqSGqdpI6lziHAYAIAiGUAFARNI4HCUa1Q3bQfqk4ditz0qg\nrKpf30DD69xw/gJApIwRwTXCwl9sAKhHdVtBEPIHoLTOf1OVcF6jdD431L7G6MRw/gAAokCAAwAI\nQRydstrt+NGZ8yfc16t2j5v4xPUaxbwv6jbIBgA0KoZQAQBCEuVQDDrhSUhiKFUth121vO3RD6Xi\nHAbQmLJ/G2r57wPShAocAECIouikNXDHLwUVBHGGErUdgMQskmOjgc81AABqAAEOAAAAAABAyjGE\nCgDqVahXqvGjRq5qk4LqluiEuw/ScFWqepPe1zSK85fKHgCNjKtQITw18AkbAFB7wvigkgmpnWgw\n3Cdc0byeAY6fug72vArzvEvoHGY/AgDqEBU4ABCh9H7LHodqvslPb3DTqKI8lgnD0qjaShzOYQDI\nSV2onLbtgVdU4AAAIhSkExdDxy91H6Rqg+n4L+w2EVDkx3HQc7GxwxuOaQBAVKjAAQBEzOrMVfrO\noLE7feGLbi4iq4NabUUOHd1a4PX8tS8LAACiQIADAPUssYmMnTR2564eh9MFfU7xBDfpP95q65hI\n/+sJAOkUfvUqGhdDqAAASLOUD/fyO6yKD7EhS/nxkQheEwBAnaICBwDQWKrs3BFAOCs3rKoRXrNG\neI4AA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          }
        }
      ],
      "source": [
        "ince_gaussian_sim_data.plot_field(str(field_monitor_xs[0]), \"E\", val=\"abs\", f=freq0)\n",
        "plt.show()"
      ],
      "id": "2fd0071b"
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {},
      "outputs": [],
      "source": [
        "import ipywidgets as widgets\n",
        "\n",
        "component = \"E\"\n",
        "\n",
        "field_slider = widgets.FloatSlider(\n",
        "    value=0,\n",
        "    min=field_monitor_xs[0],\n",
        "    max=field_monitor_xs[-1],\n",
        "    step=None,\n",
        "    description=component,\n",
        "    disabled=False,\n",
        "    continuous_update=True,\n",
        "    orientation=\"horizontal\",\n",
        "    readout=True,\n",
        "    readout_format=\".3f\",\n",
        ")\n",
        "\n",
        "\n",
        "def update_plot(x):\n",
        "    if x not in field_monitor_xs:\n",
        "        x = min(field_monitor_xs, key=lambda ll: abs(ll - x))\n",
        "    ince_gaussian_sim_data.plot_field(str(x), component, val=\"abs\", f=freq0)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "widgets.interactive(update_plot, x=field_slider)"
      ],
      "id": "7062542c"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Hyper-geometric Gaussian modes\n",
        "\n",
        "Here we show how to create a Hyper-geometric Gaussian (HGG) beam in\n",
        "Tidy3D using our\n",
        "[CustomFieldSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.CustomFieldSource.html)\n",
        "object. We then validate the phase change along the propagation\n",
        "direction.<br><br> In cylindrical coordinates, where\n",
        "$\\rho=\\frac{r}{\\omega_0}$ is the normalized radial coordinate and\n",
        "$Z=\\frac{z}{z_R}$ is the normalized longitude direction (the direction\n",
        "of propagation), the HGG has field profile"
      ],
      "id": "4748ae94-cd6e-4abb-83c9-a4e0b92fd351"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<center>"
      ],
      "id": "559e7861-b574-45e0-a277-ab789c3927dd"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$E_{p,m}\\Bigl(\\rho,\\phi,Z\\Bigr)=\\sqrt{\\frac{2^{p+|m|+1}}{\\pi\\Gamma(p+|m|+1)}}\\frac{\\Gamma\\Bigl(\\frac{p}{2}+|m|+1\\Bigr)}{\\Gamma(|m|+1)}i^{|m|+1}Z^{\\frac{p}{2}}(Z+i)^{-\\Bigl(\\frac{p}{2}+|m|+1\\Bigr)}\\rho^{|m|}\\exp\\Bigl(-\\frac{i\\rho^2}{Z+i}\\Bigr) e^{im\\phi} {_1}F_1\\Bigl(-\\frac{p}{2},|m|+1;\\frac{\\rho^2}{Z(Z+i)}\\Bigr)$"
      ],
      "id": "ab962d4b-5145-421b-9e45-febd61ffb8f8"
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      "metadata": {
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      },
      "source": [
        "</center>"
      ],
      "id": "6021c671-a7b0-4ebb-b7bc-dc617b633008"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "where:"
      ],
      "id": "76da733b-5fe7-4c03-acb5-a9ea0c99db06"
    },
    {
      "cell_type": "raw",
      "metadata": {
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      },
      "source": [
        "<li>"
      ],
      "id": "2f0e8c2b-0913-4928-87a4-2ca0b361d8b4"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\omega_0$ is the beam waist"
      ],
      "id": "5e955edf-55bc-479f-8b68-a1eea52d8497"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "968bc32e-5f3f-4d1b-b2d9-ab26298c94df"
    },
    {
      "cell_type": "raw",
      "metadata": {
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      },
      "source": [
        "<li>"
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      "id": "5357306c-40ab-4007-82a4-68e3fc34322a"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$z_R=\\frac{\\pi n_\\epsilon\\omega_0^2}{\\lambda}$ is the Rayleigh length"
      ],
      "id": "57d28ece-9e81-477d-bc32-525b3f75eaab"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "0704d0ef-ed87-4c03-9966-9b05ac55b393"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "<li>"
      ],
      "id": "8222f7fc-2e1b-4c72-aae7-039e9d25ce4d"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$m$ is the rotational index"
      ],
      "id": "c15c423f-0ba2-4831-b057-1ce0e2ddb4f0"
    },
    {
      "cell_type": "raw",
      "metadata": {
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      "source": [
        "</li>"
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      "id": "27a5f3b8-ab9c-415a-a76f-873313110ec4"
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    {
      "cell_type": "raw",
      "metadata": {
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        "<li>"
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      "id": "d37c42b7-0c67-46ff-a0ca-9ccbe264d903"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$p\\geq-|m|$"
      ],
      "id": "c7e60a12-5eec-4dac-97ad-3a438b825ed6"
    },
    {
      "cell_type": "raw",
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      "id": "fef348ec-43d1-4bea-9430-ace5d08eb9e7"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "$\\Gamma(x)$ is the gamma function"
      ],
      "id": "d6aa4980-9579-4a6f-9275-79fcb3e01f89"
    },
    {
      "cell_type": "raw",
      "metadata": {
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      "source": [
        "</li>"
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      "id": "416e077d-9285-48b3-a6ad-f4629d33a75c"
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      "metadata": {},
      "source": [
        "${_1}F_1(a,b;x)$ is a confluent hypergeometric function"
      ],
      "id": "227572a7-c166-4262-8add-26ef2bb3fe8b"
    },
    {
      "cell_type": "raw",
      "metadata": {
        "raw_mimetype": "text/html"
      },
      "source": [
        "</li>"
      ],
      "id": "58f59975-f348-4d8b-9381-c24be19f000c"
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {},
      "outputs": [],
      "source": [
        "from scipy.special import hyp1f1\n",
        "\n",
        "\n",
        "def HGG(\n",
        "    size,\n",
        "    p,\n",
        "    m,\n",
        "    source_time,\n",
        "    center=(0, 0, 0),\n",
        "    direction=\"+\",\n",
        "    pol_angle=0,\n",
        "    angle_phi=0,\n",
        "    angle_theta=0,\n",
        "    w0=1,\n",
        "    waist_distance=0,\n",
        "):\n",
        "    if p < -np.abs(m):\n",
        "        raise Exception(\"Error: p must be greater than or equal to -|m|\")\n",
        "    freqs = [source_time.freq0]\n",
        "\n",
        "    class HGG_obj(BeamProfile):\n",
        "        \"\"\"Component for constructing HGG beam data. The normal direction is implicitly\n",
        "        defined by the ``size`` parameter.\n",
        "        \"\"\"\n",
        "\n",
        "        def scalar_field(self, points, background_n):\n",
        "            \"\"\"Scalar field for HGG beam.\n",
        "            Scalar field corresponding to the analytic beam in coordinate system such that the\n",
        "            propagation direction is z and the ``E``-field is entirely ``x``-polarized. The field is\n",
        "            computed on an unstructured array ``points`` of shape ``(3, ...)``.\n",
        "            \"\"\"\n",
        "            x, y, z = points\n",
        "            z += waist_distance\n",
        "\n",
        "            r = np.sqrt(x**2 + y**2) / w0\n",
        "            phi = np.arctan2(y, x)\n",
        "            abs_m = np.abs(m)\n",
        "\n",
        "            E = source_time.amplitude * np.sqrt(\n",
        "                2 ** (p + abs_m + 1) / (np.pi * gamma(p + abs_m + 1))\n",
        "            )\n",
        "\n",
        "            Z = z / (np.pi * background_n * w0**2 / (td.C_0 / np.array(self.freqs)))\n",
        "            if np.all(Z) == 0:\n",
        "                return E * r ** (p + abs_m) * np.exp(-(r**2) + 1j * m * phi)\n",
        "\n",
        "            E *= gamma(p / 2 + abs_m + 1) / gamma(abs_m + 1) * 1j ** (abs_m + 1) * Z ** (p / 2)\n",
        "            E *= (Z + 1j) ** (-(p / 2 + abs_m + 1)) * r**abs_m * np.exp(-(1j * r**2) / (Z + 1j))\n",
        "            E *= np.exp(1j * m * phi) * hyp1f1(-p / 2, abs_m + 1, r**2 / (Z * (Z + 1j)))\n",
        "\n",
        "            return E\n",
        "\n",
        "    HGG_obj = HGG_obj(\n",
        "        center=center,\n",
        "        size=size,\n",
        "        freqs=freqs,\n",
        "        angle_theta=angle_theta,\n",
        "        angle_phi=angle_phi,\n",
        "        pol_angle=pol_angle,\n",
        "        direction=direction,\n",
        "    )\n",
        "    field_data = HGG_obj.field_data\n",
        "    field_dataset = td.FieldDataset(\n",
        "        Ex=field_data.Ex,\n",
        "        Ey=field_data.Ey,\n",
        "        Ez=field_data.Ez,\n",
        "        Hx=field_data.Hx,\n",
        "        Hy=field_data.Hy,\n",
        "        Hz=field_data.Hz,\n",
        "    )\n",
        "    HGG_source = td.CustomFieldSource(\n",
        "        center=center, size=size, source_time=source_time, field_dataset=field_dataset\n",
        "    )\n",
        "    return HGG_source"
      ],
      "id": "1da2da24"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create and run example HGG beam:"
      ],
      "id": "3c4b729e-509d-4949-bd38-1911e405893a"
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {},
      "outputs": [],
      "source": [
        "freq0 = td.C_0 / 1.55\n",
        "hgg = HGG(size=(0, 4, 4), p=1, m=2, source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10))"
      ],
      "id": "926b8683"
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {},
      "outputs": [],
      "source": [
        "sim_size = (5.1, 5, 5)\n",
        "sim_center = (sim_size[0] / 2 - 0.05, 0, 0)\n",
        "\n",
        "num_field_monitors = 61\n",
        "field_monitor_xs = np.linspace(\n",
        "    sim_center[0] - sim_size[0] / 2 + 0.1, sim_size[0] - 0.1, num_field_monitors\n",
        ")\n",
        "field_monitors = []\n",
        "for x in field_monitor_xs:\n",
        "    field_monitor = td.FieldMonitor(\n",
        "        center=(x, 0, 0), size=(0, sim_size[1], sim_size[2]), name=str(x), freqs=[freq0]\n",
        "    )\n",
        "    field_monitors.append(field_monitor)\n",
        "\n",
        "HGG_test_sim = td.Simulation(\n",
        "    center=sim_center,\n",
        "    size=sim_size,\n",
        "    structures=[],\n",
        "    sources=[hgg],\n",
        "    monitors=field_monitors,\n",
        "    run_time=1e-13,\n",
        ")"
      ],
      "id": "396a8eed"
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "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\">10:44:27 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'HGG test'</span> with resource_id                           \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-a751ede0-30f5-4edb-a19e-9fe9618853f8'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \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>View task using web UI at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a751ede0-30f5-4edb-a19e-9fe9618853f8\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a751ede0-30f</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a751ede0-30f5-4edb-a19e-9fe9618853f8\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">5-4edb-a19e-9fe9618853f8'</span></a>.                                         \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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"96b82ab135194099b84bd3a1588b4961\",\"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\">10:44:30 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. This assumes the FDTD solver runs\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for the full simulation time; if early shutoff is reached, the     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed cost can be lower. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed FlexCredit cost after a simulation run.                     \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\">10:44:31 UTC </span>status = queued                                                    \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>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"ca3a746b57874f8b9873beb93115d027\",\"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\">10:44:40 UTC </span>status = preprocess                                                \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>"
            ]
          }
        },
        {
          "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\">10:44:45 UTC </span>starting up solver                                                 \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>running solver                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"7d787e63f92f430d9e99bf21ee6eb18b\",\"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\">10:44:46 UTC </span>status = postprocess                                               \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"726289666a6a48e9a8f0b3abdae5a874\",\"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\">10:44:49 UTC </span>status = success                                                   \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>"
            ]
          }
        },
        {
          "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\">10:44:51 UTC </span>View simulation result at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a751ede0-30f5-4edb-a19e-9fe9618853f8\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a751ede0-30f</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a751ede0-30f5-4edb-a19e-9fe9618853f8\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">5-4edb-a19e-9fe9618853f8'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"c3d4c00965a34e21a5f204cf8eae3087\",\"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\">10:44:52 UTC </span>Loading results from simulation_data.hdf5                          \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\">10:44:53 UTC </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Simulation final field decay value of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"color: #800000; text-decoration-color: #800000\"> is greater than </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">the simulation shutoff threshold of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-05</span><span style=\"color: #800000; text-decoration-color: #800000\">. Consider running the    </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">simulation again with a larger </span><span style=\"color: #008000; text-decoration-color: #008000\">'run_time'</span><span style=\"color: #800000; text-decoration-color: #800000\"> duration for more        </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">accurate results.                                                  </span>\n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "hgg_sim_data = web.run(simulation=HGG_test_sim, task_name=\"HGG test\")"
      ],
      "id": "f363bb98"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Display field in propagation direction:"
      ],
      "id": "cc61dd5a-9638-4598-acee-63b29384c9ca"
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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          }
        }
      ],
      "source": [
        "hgg_sim_data.plot_field(str(field_monitor_xs[30]), \"Ey\", f=freq0)\n",
        "plt.show()"
      ],
      "id": "b288a5ca"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "To see how the field evolves, run the following code to visualize along\n",
        "the propagation direction."
      ],
      "id": "cfcf4248-c35e-4ab5-9da7-afb86011b1ec"
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {},
      "outputs": [],
      "source": [
        "import ipywidgets as widgets\n",
        "\n",
        "component = \"Ey\"\n",
        "\n",
        "field_slider = widgets.FloatSlider(\n",
        "    value=0,\n",
        "    min=field_monitor_xs[0],\n",
        "    max=field_monitor_xs[-1],\n",
        "    step=None,\n",
        "    description=component,\n",
        "    disabled=False,\n",
        "    continuous_update=True,\n",
        "    orientation=\"horizontal\",\n",
        "    readout=True,\n",
        "    readout_format=\".3f\",\n",
        ")\n",
        "\n",
        "\n",
        "def update_plot(x):\n",
        "    if x not in field_monitor_xs:\n",
        "        x = min(field_monitor_xs, key=lambda ll: abs(ll - x))\n",
        "    hgg_sim_data.plot_field(str(x), component, f=freq0)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "widgets.interactive(update_plot, x=field_slider)"
      ],
      "id": "b3a2b366"
    }
  ],
  "nbformat": 4,
  "nbformat_minor": 5,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    }
  }
}