{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Compact on-chip optical switch design optimization using DBS\n",
        "\n",
        "Note: the cost of running the entire notebook is larger than 1\n",
        "FlexCredit.\n",
        "\n",
        "The direct binary search (DBS) algorithm is an iterative optimization\n",
        "algorithm often used in image processing and has been adapted for use in\n",
        "photonic design.\n",
        "\n",
        "The steps in a DBS are typically as follows:\n",
        "\n",
        "1.  **Initialization**: Starting with an initial design, usually a\n",
        "    binary representation of the photonic structure where each element\n",
        "    (pixel or voxel) is either one material or another.\n",
        "\n",
        "2.  **Evaluation**: Simulating the optical performance of the current\n",
        "    design using methods like finite-difference time-domain (FDTD)\n",
        "    simulations.\n",
        "\n",
        "3.  **Modification**: Adjusting the design by flipping the state of\n",
        "    specific elements (from one material to another) based on certain\n",
        "    criteria, such as improving performance metrics like transmission\n",
        "    efficiency.\n",
        "\n",
        "4.  **Iteration**: Repeating the evaluation and modification steps until\n",
        "    a satisfactory design is reached or a certain number of iterations\n",
        "    have been completed.\n",
        "\n",
        "This process allows for the fine-tuning of photonic structures to\n",
        "achieve highly specific and efficient optical characteristics. The DBS\n",
        "algorithm is valued for its relative simplicity and effectiveness,\n",
        "especially in scenarios where gradient-based optimization is\n",
        "challenging.\n",
        "\n",
        "This notebook demonstrates the design of an on-chip optical switch based\n",
        "on the phase change material Ge$_2$Sb$_2$Te$_5$ (GST) using the DBS\n",
        "algorithm. The design region is a square of 900 nm by 900 nm discretized\n",
        "into 9 by 9 pixels with a size of 100 nm. The 3 by 3 pixels at the\n",
        "center of the design region is GST. Other pixels can be either silicon\n",
        "or silica. The goal is to optimize the materials at each pixel such that\n",
        "the best switching performance is obtained. That is, we want to achieve\n",
        "the highest transmission possible when GST is in the amorphous state\n",
        "while the lowest transmission possible when GST is in the crystalline\n",
        "state. The notebook follows the work\n",
        "`Yin, K.; Gao, Y.; Shi, H.; Zhu, S. Inverse Design and Numerical Investigations of an Ultra-Compact Integrated Optical Switch Based on Phase Change Material. Nanomaterials 2023, 13, 1643.`\n",
        "[DOI: 10.3390/nano13101643](https://doi.org/10.3390/nano13101643).\n",
        "\n",
        "<img src=\"img/optical_switch.png\" width=\"450\" alt=\"Schematic of the optical switch\">\n",
        "\n",
        "`Tidy3D` is a powerful tool for photonic design optimization due to its\n",
        "fast speed and high throughput. Besides DBS, we have demonstrated\n",
        "particle swarm optimizations of a [polarization beam\n",
        "splitter](https://www.flexcompute.com/tidy3d/examples/notebooks/ParticleSwarmOptimizedPBS/)\n",
        "and a [bullseye\n",
        "cavity](https://www.flexcompute.com/tidy3d/examples/notebooks/BullseyeCavityPSO/),\n",
        "genetic algorithm optimization of an [on-chip\n",
        "reflector](https://www.flexcompute.com/tidy3d/examples/notebooks/GeneticAlgorithmReflector/),\n",
        "and CMA-ES optimization of a [waveguide\n",
        "S-bend](https://www.flexcompute.com/tidy3d/examples/notebooks/SbendCMAES/).\n",
        "Furthermore, we also have a growing list of gradient-based adjoint\n",
        "optimization examples including\n",
        "\n",
        "1.  [Mode\n",
        "    converter](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd3InverseDesign/),\n",
        "\n",
        "2.  [Waveguide\n",
        "    taper](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd5BoundaryGradients/),\n",
        "\n",
        "3.  [Metalens](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd7Metalens/),\n",
        "\n",
        "4.  [Waveguide\n",
        "    bend](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd8WaveguideBend/),\n",
        "\n",
        "5.  [Multiplexer](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd9WDM/),\n",
        "\n",
        "6.  [Y-branch](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd10YBranchLevelSet/),\n",
        "\n",
        "7.  [Light\n",
        "    extractor](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd12LightExtractor/)."
      ],
      "id": "f118a15f-881c-4570-bd40-2aae1a389ec6"
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import tidy3d as td\n",
        "import tidy3d.web as web"
      ],
      "id": "d057751a"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Simulation Setup\n",
        "\n",
        "The simulation wavelength range is 1535 nm to 1565 nm."
      ],
      "id": "68226b34-7847-4d77-8c9f-8e44af2edfa1"
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [],
      "source": [
        "lda0 = 1.55  # central wavelength\n",
        "freq0 = td.C_0 / lda0  # central frequency\n",
        "ldas = np.linspace(1.535, 1.565, 11)  # wavelength range\n",
        "freqs = td.C_0 / ldas  # frequency range\n",
        "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))  # width of the source frequency range"
      ],
      "id": "a5c93107"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "For simplicity, we will use the silicon and oxide media directly from\n",
        "the [material\n",
        "library](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/material_library.html#).\n",
        "The GST has two states: the crystalline state with a higher loss and an\n",
        "amorphous state with a lower loss. Since our wavelength range of\n",
        "interest is relatively narrow, we use the `from_nk` method to define the\n",
        "material responses of GST in two states. It’s important to note that the\n",
        "defined refractive index is strictly accurate only at the given\n",
        "frequency."
      ],
      "id": "7001c429-da29-40ba-8ec9-46beb5c41343"
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "Si = td.material_library[\"cSi\"][\"Palik_LowLoss\"]\n",
        "SiO2 = td.material_library[\"SiO2\"][\"Palik_LowLoss\"]\n",
        "\n",
        "aGST = td.Medium.from_nk(n=3.98, k=0.0244, freq=freq0)\n",
        "cGST = td.Medium.from_nk(n=6.49, k=1.054, freq=freq0)"
      ],
      "id": "07e1449c"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The straight waveguide has a width of 400 nm and a thickness of 220 nm.\n",
        "The size of the pixels in the design region is 100 nm by 100 nm. There\n",
        "are 9 by 9 pixels in total but the 3 by 3 pixels at the center are fixed\n",
        "to GST. In the current version, we only support `Nx`, `Ny`, and `N_gst`\n",
        "being odd numbers."
      ],
      "id": "5c8b3188-f314-4361-88e7-a15a9a97aa0c"
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [],
      "source": [
        "w = 0.4  # width of the waveguide\n",
        "t = 0.22  # thickness of the silicon\n",
        "l = 1  # length of the waveguide in the simulation\n",
        "Px = Py = 0.1  # pixel sizes in the x and y directions\n",
        "Nx = 9  # number of pixels in the x direction\n",
        "Ny = 9  # number of pixels in the y direction\n",
        "N_gst = 3  # number of pixels for GST\n",
        "buffer = 0.8  # buffer spacing"
      ],
      "id": "61c79e35"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Now we want to characterize a design by a parameter vector\n",
        "$(x_1, x_2, ..., x_n)$, where $x_i$ represents the material at the i-th\n",
        "pixel and takes the value of either 0 (silica) or 1 (silicon). Due to\n",
        "the symmetry, we only focus on symmetric designs. Since the GST pixels\n",
        "are fixed, we have a total of\n",
        "`(Ny * Nx - N_gst * N_gst) // 2 + Nx // 2 - 1 = 39` tuneable pixels.\n",
        "That is, the length of the parameter vector is 39 in this case.\n",
        "\n",
        "For easier structure construction, we define a helper function\n",
        "`parse_to_2d` that takes the parameter vector and parses it into a 2D\n",
        "array representing the design. With that, we define another helper\n",
        "function `create_design` to define the structures in the design region\n",
        "as well as the input and output straight waveguides."
      ],
      "id": "3ebf6872-8093-4765-99b9-dff79316ffb5"
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [],
      "source": [
        "def parse_to_2d(array_1d, Nx, Ny, N_gst):\n",
        "    # ensure Ny, Nx, and N_gst are odd\n",
        "    if Ny % 2 == 0 or Nx % 2 == 0 or N_gst % 2 == 0:\n",
        "        raise ValueError(\"Nx, Ny, and N_gst must be odd numbers.\")\n",
        "\n",
        "    # calculate the number of changeable elements in the top half (including the middle row)\n",
        "    num_elements_half = (Ny * Nx - N_gst * N_gst) // 2 + Nx // 2 - 1\n",
        "\n",
        "    if len(array_1d) != num_elements_half:\n",
        "        raise ValueError(f\"1D array must have {num_elements_half} elements.\")\n",
        "\n",
        "    array_2d = np.zeros((Ny, Nx))\n",
        "\n",
        "    idx_1d = 0\n",
        "    for i in range(Ny):\n",
        "        for j in range(Nx):\n",
        "            # skip the fixed center\n",
        "            if (Ny - N_gst) // 2 <= i < (Ny + N_gst) // 2 and (Nx - N_gst) // 2 <= j < (\n",
        "                Nx + N_gst\n",
        "            ) // 2:\n",
        "                continue\n",
        "\n",
        "            # Fill up to and including the middle row\n",
        "            if i <= Ny // 2:\n",
        "                array_2d[i, j] = array_1d[idx_1d]\n",
        "                idx_1d += 1\n",
        "\n",
        "                # Mirror the element to the symmetrical position, but not for the middle row\n",
        "                if i < Ny // 2:\n",
        "                    array_2d[Ny - 1 - i, j] = array_1d[idx_1d - 1]\n",
        "\n",
        "    return array_2d\n",
        "\n",
        "\n",
        "def create_design(pixels):\n",
        "    # parse 1d parameter vector to 2d array\n",
        "    pixels_2d = parse_to_2d(pixels, Nx, Ny, N_gst)\n",
        "\n",
        "    # define geometry at each pixel\n",
        "    geo = 0\n",
        "    for i, row in enumerate(pixels_2d):\n",
        "        for j, pixel in enumerate(row):\n",
        "            if pixel == 1:\n",
        "                geo += td.Box(\n",
        "                    center=(l + Px / 2 + Px * j, (Ny - 1) / 2 * Py - Py * i, 0), size=(Px, Py, t)\n",
        "                )\n",
        "\n",
        "    # add input and output waveguides\n",
        "    geo += td.Box(center=(0, 0, 0), size=(2 * l, w, t))\n",
        "    geo += td.Box(center=(l + Nx * Px + l, 0, 0), size=(2 * l, w, t))\n",
        "\n",
        "    # define structure from geometry\n",
        "    design = td.Structure(geometry=geo, medium=Si)\n",
        "\n",
        "    return design"
      ],
      "id": "babde23c"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "To test the functions, we define a parameter vector of all 1s. This\n",
        "should define a design that is all silicon besides the 3 by 3 pixels at\n",
        "the center for GST. The plot confirms that it’s working correctly."
      ],
      "id": "be90d7a5-35e2-44e2-9c99-c2e0d0f746b8"
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABSwAAAHeCAYAAACR/kXlAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90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\n"
          }
        }
      ],
      "source": [
        "pixels = np.ones((Ny * Nx - N_gst * N_gst) // 2 + Nx // 2 - 1)\n",
        "design = create_design(pixels)\n",
        "design.plot(z=0)\n",
        "plt.show()"
      ],
      "id": "ea81bfe0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Now we can define a function to create a\n",
        "[Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html#tidy3d.Simulation)\n",
        "given a parameter vector and the state of the GST."
      ],
      "id": "ca78a1f3-7eea-48d5-a6b0-78d7de6409e9"
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [],
      "source": [
        "def make_sim(pixels, gst_state):\n",
        "    # create silicon structures\n",
        "    design = create_design(pixels)\n",
        "\n",
        "    # add a mode source as excitation\n",
        "    mode_spec = td.ModeSpec(num_modes=1, target_neff=3.5)\n",
        "    mode_source = td.ModeSource(\n",
        "        center=(l / 2, 0, 0),\n",
        "        size=(0, 4 * w, 6 * t),\n",
        "        source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
        "        direction=\"+\",\n",
        "        mode_spec=mode_spec,\n",
        "        mode_index=0,\n",
        "    )\n",
        "\n",
        "    # add a mode monitor to measure transmission at the output waveguide\n",
        "    mode_monitor = td.ModeMonitor(\n",
        "        center=(Nx * Px + 1.5 * l, 0, 0),\n",
        "        size=mode_source.size,\n",
        "        freqs=freqs,\n",
        "        mode_spec=mode_spec,\n",
        "        name=\"mode\",\n",
        "    )\n",
        "\n",
        "    # create the GST pixels\n",
        "    if gst_state == \"c\":\n",
        "        gst = td.Structure(\n",
        "            geometry=td.Box(center=(l + Px * Nx / 2, 0, 0), size=(N_gst * Px, N_gst * Py, t)),\n",
        "            medium=cGST,\n",
        "        )\n",
        "    elif gst_state == \"a\":\n",
        "        gst = td.Structure(\n",
        "            geometry=td.Box(center=(l + Px * Nx / 2, 0, 0), size=(N_gst * Px, N_gst * Py, t)),\n",
        "            medium=aGST,\n",
        "        )\n",
        "    else:\n",
        "        raise ValueError(\"gst_state can only be 'a' or 'c'.\")\n",
        "\n",
        "    # define simulation domain size\n",
        "    Lx = 2 * l + Nx * Px\n",
        "    Ly = Ny * Py + 2 * buffer\n",
        "    Lz = 10 * t\n",
        "\n",
        "    # simulation domain box\n",
        "    sim_box = td.Box.from_bounds(rmin=(0, -Ly / 2, -Lz / 2), rmax=(Lx, Ly / 2, Lz / 2))\n",
        "\n",
        "    run_time = 1e-12  # simulation run time\n",
        "\n",
        "    # define simulation\n",
        "    sim = td.Simulation(\n",
        "        center=sim_box.center,\n",
        "        size=sim_box.size,\n",
        "        grid_spec=td.GridSpec.auto(min_steps_per_wvl=15, wavelength=lda0),\n",
        "        structures=[design, gst],\n",
        "        sources=[mode_source],\n",
        "        monitors=[mode_monitor],\n",
        "        run_time=run_time,\n",
        "        boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
        "        medium=SiO2,\n",
        "        symmetry=(0, -1, 1),\n",
        "    )\n",
        "\n",
        "    return sim"
      ],
      "id": "be2b454c"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Visualize the simulation in 3D to check if the setup is correct."
      ],
      "id": "1b4a46fe-718c-4398-9f4a-6336c6d2b050"
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "\n",
              "    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"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\" ></div>\n",
              "    <script>\n",
              "        \n",
              "        /**\n",
              "        * Simulation Viewer Injector\n",
              "        *\n",
              "        * Monitors the document for elements being added in the form:\n",
              "        *\n",
              "        *    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"{...}\" />\n",
              "        *\n",
              "        * This script will then inject an iframe to the viewer application, and pass it the simulation data\n",
              "        * via the postMessage API on request. The script may be safely included multiple times, with only the\n",
              "        * configuration of the first started script (e.g. viewer URL) applying.\n",
              "        *\n",
              "        */\n",
              "        (function() {\n",
              "            const TARGET_CLASS = \"simulation-viewer\";\n",
              "            const ACTIVE_CLASS = \"simulation-viewer-active\";\n",
              "            const VIEWER_URL = \"https://tidy3d.simulation.cloud/simulation-viewer\";\n",
              "\n",
              "            class SimulationViewerInjector {\n",
              "                constructor() {\n",
              "                    for (var node of document.getElementsByClassName(TARGET_CLASS)) {\n",
              "                        this.injectViewer(node);\n",
              "                    }\n",
              "\n",
              "                    // Monitor for newly added nodes to the DOM\n",
              "                    this.observer = new MutationObserver(this.onMutations.bind(this));\n",
              "                    this.observer.observe(document.body, {childList: true, subtree: true});\n",
              "                }\n",
              "\n",
              "                onMutations(mutations) {\n",
              "                    for (var mutation of mutations) {\n",
              "                        if (mutation.type === 'childList') {\n",
              "                            /**\n",
              "                            * Have found that adding the element does not reliably trigger the mutation observer.\n",
              "                            * It may be the case that setting content with innerHTML does not trigger.\n",
              "                            *\n",
              "                            * It seems to be sufficient to re-scan the document for un-activated viewers\n",
              "                            * whenever an event occurs, as Jupyter triggers multiple events on cell evaluation.\n",
              "                            */\n",
              "                            var viewers = document.getElementsByClassName(TARGET_CLASS);\n",
              "                            for (var node of viewers) {\n",
              "                                this.injectViewer(node);\n",
              "                            }\n",
              "                        }\n",
              "                    }\n",
              "                }\n",
              "\n",
              "                injectViewer(node) {\n",
              "                    // (re-)check that this is a valid simulation container and has not already been injected\n",
              "                    if (node.classList.contains(TARGET_CLASS) && !node.classList.contains(ACTIVE_CLASS)) {\n",
              "                        // Mark node as injected, to prevent re-runs\n",
              "                        node.classList.add(ACTIVE_CLASS);\n",
              "\n",
              "                        var uuid;\n",
              "                        if (window.crypto && window.crypto.randomUUID) {\n",
              "                            uuid = window.crypto.randomUUID();\n",
              "                        } else {\n",
              "                            uuid = \"\" + Math.random();\n",
              "                        }\n",
              "\n",
              "                        var frame = document.createElement(\"iframe\");\n",
              "                        frame.width = node.dataset.width || 800;\n",
              "                        frame.height = node.dataset.height || 800;\n",
              "                        frame.style.cssText = `width:${frame.width}px;height:${frame.height}px;max-width:none;border:0;display:block`\n",
              "                        frame.src = VIEWER_URL + \"?uuid=\" + uuid;\n",
              "\n",
              "                        var postMessageToViewer;\n",
              "                        postMessageToViewer = event => {\n",
              "                            if(event.data.type === 'viewer' && event.data.uuid===uuid){\n",
              "                                frame.contentWindow.postMessage({ type: 'jupyter', uuid, value: node.dataset.simulation, fileType: 'hdf5'}, '*');\n",
              "\n",
              "                                // Run once only\n",
              "                                window.removeEventListener('message', postMessageToViewer);\n",
              "                            }\n",
              "                        };\n",
              "                        window.addEventListener(\n",
              "                            'message',\n",
              "                            postMessageToViewer,\n",
              "                            false\n",
              "                        );\n",
              "\n",
              "                        node.appendChild(frame);\n",
              "                    }\n",
              "                }\n",
              "            }\n",
              "\n",
              "            if (!window.simulationViewerInjector) {\n",
              "                window.simulationViewerInjector = new SimulationViewerInjector();\n",
              "            }\n",
              "        })();\n",
              "    \n",
              "    </script>\n",
              "    "
            ]
          }
        }
      ],
      "source": [
        "sim = make_sim(pixels, \"c\")\n",
        "sim.plot_3d()"
      ],
      "id": "3cc1dae0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Optimization\n",
        "\n",
        "The objective function is defined as the contrast between the\n",
        "transmissions when GST is in the amorphous and crystalline states. To\n",
        "evaluate it, we need to define two simulations with the same parameter\n",
        "vector but a different GST state, run the simulation in parallel,\n",
        "extract the transmission, and calculate the difference."
      ],
      "id": "1ea35873-eaad-44ba-aa78-85a0596745b3"
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [],
      "source": [
        "def objective_function(pixels):\n",
        "    # define two simulations\n",
        "    sim_a = make_sim(pixels, \"a\")\n",
        "    sim_c = make_sim(pixels, \"c\")\n",
        "    sims = {\"a\": sim_a, \"c\": sim_c}\n",
        "\n",
        "    # define and submit a batch\n",
        "    batch = web.Batch(simulations=sims, verbose=False)\n",
        "    batch_results = batch.run(path_dir=\"data\")\n",
        "\n",
        "    # calculate transmission\n",
        "    sim_data_a = batch_results[\"a\"]\n",
        "    sim_data_c = batch_results[\"c\"]\n",
        "\n",
        "    t_a = sim_data_a[\"mode\"].amps.sel(direction=\"+\").values\n",
        "    T_a = np.mean(np.abs(t_a) ** 2)\n",
        "\n",
        "    t_c = sim_data_c[\"mode\"].amps.sel(direction=\"+\").values\n",
        "    T_c = np.mean(np.abs(t_c) ** 2)\n",
        "\n",
        "    return T_a - T_c"
      ],
      "id": "0fff13aa"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We start the optimization using the parameter vector of all 1s. The\n",
        "objective function is evaluated to be just above 0.8."
      ],
      "id": "d1a20f49-9bfb-4189-b52c-83be771694d2"
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Initial objective function is 0.814."
          ]
        }
      ],
      "source": [
        "initial_obj = objective_function(pixels)\n",
        "print(f\"Initial objective function is {initial_obj:.3f}.\")"
      ],
      "id": "3e1751f4"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Since the DBS algorithm is pretty straightforward, we don’t need to make\n",
        "sure of any external libraries. We can define the DBS optimizer\n",
        "directly. In the optimization, we flip the value of elements in the\n",
        "parameter vector one by one. If the flip leads to an improved objective\n",
        "function, we keep the flipped element. If no improvement is found, we\n",
        "revert back to the original value. One iteration ends when all elements\n",
        "of the parameter vector are flipped once and this can be done for\n",
        "multiple iterations. We can implement different termination conditions.\n",
        "For example, if no improvement is found or the improvement is smaller\n",
        "than a certain threshold between consecutive iterations, the\n",
        "optimization stops. Or if the objective function reaches a certain\n",
        "threshold value, the optimization stops. In this example, we simply\n",
        "monitor the improvement and terminate the optimization if no improvement\n",
        "is found within one iteration."
      ],
      "id": "f377867b-fd79-46f7-b279-6ae6276c9a71"
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [],
      "source": [
        "def direct_binary_search(pixels, iterations):\n",
        "    num_of_eval = 0  # number of objective function evaluations\n",
        "    best_score = [initial_obj]  # best objective function values\n",
        "    print(f\"The initial objective function is {initial_obj:.3f}.\")\n",
        "\n",
        "    for i in range(iterations):\n",
        "        print(f\"Iteration {i + 1} starts.\")\n",
        "        improvement = False  # keep track of if there is improvement within one iteration\n",
        "\n",
        "        for idx in range(len(pixels)):\n",
        "            # flip the current element\n",
        "            pixels[idx] = 1 - pixels[idx]\n",
        "\n",
        "            # Evaluate the new solution\n",
        "            current_score = objective_function(pixels)\n",
        "            num_of_eval += 1\n",
        "\n",
        "            # if better, update best solution, else revert change\n",
        "            if current_score > best_score[-1]:\n",
        "                best_score.append(current_score)\n",
        "                improvement = True\n",
        "                print(\n",
        "                    f\"A best objective of {current_score:.3f} found after {num_of_eval} evaluation(s).\"\n",
        "                )\n",
        "\n",
        "            else:\n",
        "                best_score.append(best_score[-1])\n",
        "                pixels[idx] = 1 - pixels[idx]  # revert change\n",
        "        if not improvement:\n",
        "            break\n",
        "\n",
        "    return pixels, best_score"
      ],
      "id": "c3d89f9e"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "For simplicity, we only demonstrate the optimization for 1 iteration in\n",
        "this case. We tested more iterations and found that the second iteration\n",
        "only improved the performance very mildly. The third iteration showed no\n",
        "improvement at all. Within the first iteration, we improve the objective\n",
        "function by about 10%, which is quite significant."
      ],
      "id": "2c538c97-0592-4d7d-9be4-80bf50851130"
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The initial objective function is 0.814.\n",
            "Iteration 1 starts.\n",
            "A best objective of 0.834 found after 1 evaluation(s).\n",
            "A best objective of 0.860 found after 2 evaluation(s).\n",
            "A best objective of 0.864 found after 6 evaluation(s).\n",
            "A best objective of 0.871 found after 7 evaluation(s).\n",
            "A best objective of 0.872 found after 8 evaluation(s).\n",
            "A best objective of 0.883 found after 9 evaluation(s).\n",
            "A best objective of 0.899 found after 10 evaluation(s).\n",
            "A best objective of 0.916 found after 11 evaluation(s).\n",
            "A best objective of 0.918 found after 13 evaluation(s).\n",
            "A best objective of 0.922 found after 18 evaluation(s).\n",
            "A best objective of 0.924 found after 24 evaluation(s).\n",
            "A best objective of 0.927 found after 26 evaluation(s)."
          ]
        }
      ],
      "source": [
        "pixel_opt, best_score = direct_binary_search(pixels, 1)"
      ],
      "id": "9c1b8bd0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Plot the best objective function as a function of the number of\n",
        "evaluations."
      ],
      "id": "82df2b1f-264c-4e72-a3df-e4068fc7d06e"
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABKwAAANdCAYAAAC5zuR7AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90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\nrAAAAAAAAOBSSFgBAAAAAADApfw/NLvFGrS4vmoAAAAASUVORK5CYII=\n"
          }
        }
      ],
      "source": [
        "plt.plot(best_score, c=\"red\", linewidth=2)\n",
        "plt.xlabel(\"Number of evaluations\")\n",
        "plt.ylabel(\"Best objective function\")\n",
        "plt.show()"
      ],
      "id": "a4163bce"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Final Design\n",
        "\n",
        "After the optimization, we can inspect the final design more closely. We\n",
        "rerun the simulations with an added\n",
        "[FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html)\n",
        "so we can visualize the switching behavior better. We didn’t have a\n",
        "[FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html)\n",
        "during the optimization to minimize unnecessary data download."
      ],
      "id": "3fe8922d-be2f-455c-85e4-7424997684fb"
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [],
      "source": [
        "sim_a_opt = make_sim(pixels, \"a\")\n",
        "sim_c_opt = make_sim(pixels, \"c\")\n",
        "\n",
        "# add a field monitor to visualize field distribution at z=0\n",
        "field_monitor = td.FieldMonitor(\n",
        "    center=(0, 0, 0), size=(td.inf, td.inf, 0), freqs=[freq0], name=\"field\"\n",
        ")\n",
        "\n",
        "sim_a_opt = sim_a_opt.copy(update={\"monitors\": sim_a_opt.monitors + (field_monitor,)})\n",
        "sim_c_opt = sim_c_opt.copy(update={\"monitors\": sim_c_opt.monitors + (field_monitor,)})\n",
        "\n",
        "sims = {\"a\": sim_a_opt, \"c\": sim_c_opt}\n",
        "\n",
        "batch_opt = web.Batch(simulations=sims, verbose=False)\n",
        "batch_opt_results = batch_opt.run(path_dir=\"data\")"
      ],
      "id": "146e83f6"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Visualize the final design."
      ],
      "id": "ed1a1ab0-50da-44f2-9a6c-72e2a5e614ad"
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0EAAAOsCAYAAACMJ72FAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90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\nK1Yr9B+iAAAAAElFTkSuQmCC\n"
          }
        }
      ],
      "source": [
        "sim_a_opt.plot(z=0, monitor_alpha=0)\n",
        "plt.show()"
      ],
      "id": "b281f2d4"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Plot the transmission spectra for the final design with GST at two\n",
        "states. A clear switching with \\>20 dB contrast is confirmed."
      ],
      "id": "5570d807-42ec-4026-b803-9d2babbd28eb"
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABKkAAANdCAYAAABf5y8/AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90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\n"
          }
        }
      ],
      "source": [
        "sim_data_a = batch_opt_results[\"a\"]\n",
        "sim_data_c = batch_opt_results[\"c\"]\n",
        "\n",
        "t_a = sim_data_a[\"mode\"].amps.sel(direction=\"+\").values\n",
        "T_a = np.abs(t_a) ** 2\n",
        "\n",
        "t_c = sim_data_c[\"mode\"].amps.sel(direction=\"+\").values\n",
        "T_c = np.abs(t_c) ** 2\n",
        "\n",
        "plt.plot(ldas, 10 * np.log10(T_a), c=\"blue\", linewidth=2, label=\"On\")\n",
        "plt.plot(ldas, 10 * np.log10(T_c), c=\"red\", linewidth=2, label=\"Off\")\n",
        "plt.xlabel(\"Wavelength (µm)\")\n",
        "plt.ylabel(\"Transmission (dB)\")\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "id": "a0322bdb"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Finally, plot the electric field norms to see the energy flow. When the\n",
        "GST is in the amorphous state (on state), the waveguide mode is\n",
        "transmitted with little loss. When the GST is in the crystalline state\n",
        "(off state), the transmission is cut off nearly completely. The result\n",
        "confirms that the optimized design functions very well as an optical\n",
        "switch while maintaining an ultra-compact footprint."
      ],
      "id": "72c75477-557b-432e-8795-7bbdbec40ad8"
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABeYAAAGgCAYAAADPS7c8AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90\nbGliIHZlcnNpb24zLjExLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlcelbwAAAAlwSFlzAAAd\nhwAAHYcBj+XxZQABAABJREFUeJzs3XecE3X+P/DXJNneYJfdpfemCCIgAoqgIBbsiNhRsYB69rOd\nDblTLHjniaLi+VNETw/9CooiKgdyICpFQJDe6wLbYHuSmd8faTOfJDOZ3SSbZF/Px2MhszPzmc9M\nsslnPnl/3h9JURQFREREREREREREREQUFZbGrgARERERERERERERUVPCjnkiIiIiIiIiIiIioihi\nxzwRERERERERERERURSxY56IiIiIiIiIiIiIKIrYMU9EREREREREREREFEXsmCciIiIiIiIiIiIi\niiJ2zBMRERERERERERERRRE75omIiIiIiIiIiIiIoogd80REREREREREREREUcSOeSIiIiIiIiIi\nIiKiKGLHPBERERERERERERFRFLFjnoiIiIiIiIiIiIgoitgxT0REREREREREREQUReyYJyIiIiIi\nIiIiIiKKInbMExERERERERERERFFETvmiYiIiIiIiIiIiIiiiB3zRERERERERERERERRxI55IiIi\nIiIiIiIiIqIosjV2BYiIiIiIiIiIouHEiRP4/PPPsWLFChw6dAjV1dVQFAX5+fn497//rdn2wIED\nmDNnDtasWYPi4mLU1tYCAM4++2w8/fTTjVF9IiJKIOyYJ6ImYcOGDfj++++xa9cuHDlyxNv47tix\nI8477zyceuqpjV3FqHj99dexcOFCAMBzzz2Hfv36Nck6EBEREVFsO378OBYtWoTly5ejqKgIJSUl\nyMrKQn5+Pk477TScf/75aNOmjakyf/nlF1x++eU4fPiw3zqxrA8++AATJ05ETU2N37bNmjUzddxw\nkGUZo0aNAgC0bNkSs2fPbpJ1ICJKJOyYJ6KEpSgK5syZg6effhpbtmzR3bZz586YPHkyrrvuOlgs\niZvla926dfj6668BAPfcc0+TrQMRERERxabDhw9jypQpmDlzJux2u+62F110EV544QX06dPHsNza\n2lpcddVVATvlRVu2bMGECRPgdDpDrnekybKMRYsWAQA6dOjQZOtARJRI2DFPRAnpxIkTGDduHBYs\nWBDS9jt37sSNN96I999/H5999lmjRMEQERERETVlP/zwA6666iqUl5eHtP0333yDb7/9FtOmTcP9\n999vWPb+/fsBAOnp6XjkkUfQp08fZGVlAQBSU1O9286ePdvbKd++fXs8+OCD6NKli3ebwsJCs6dG\nRETkhx3zRJRwTpw4gaFDh2LdunXe3yUnJ+O8887DOeecgzZt2kCSJBw6dAhLlizBwoULvUNUFy1a\nhDPPPBPLly9n5zwRERERUZT83//9H8aNGweHw+H9XadOnXD55Zejb9++aNGiBY4fP45t27bhq6++\nwsqVKwG4orgfeOABHD16FH/729+Clr9p0ybv4/vuuw/PPPNMSNu+/vrruPTSSxtyakRERAGxY56I\nEs5tt92m6ZQfOXIkZsyYga5du/pte//992PPnj24++67velV/vjjD9x8882YO3dutKpMRERERNRk\nbdu2DTfffLO3Uz45ORmvvPIKJk2aBJvNv9viqaeewoIFC3Drrbd6U9M8//zzGDhwIC677LKAx6is\nrPQ+7ty5s259zGxLRERUX5KiKEpjV4KIKFy+/PJLTWN87Nix+PjjjwM26NWcTiduvvlmzQRGn376\nKa6++mq/badOnYply5YBAKZNm4YePXp48y0uXLgQ+/fvh8ViQefOnXHJJZfgjDPOCNPZuWzatAkL\nFizApk2bUFpaCqvVioKCAuTn56Nv374YMWIEMjIyNPs888wzWL16NdavX499+/YBAAYOHIj8/Hy/\n8v/xj38E/BJj06ZNWLZsGXbv3q2ZgKtt27Y4++yzMXLkSFit1qD1DkcdPLZs2YJvv/0WmzZtwrFj\nx5Camop27drh3HPPxbnnnqtbDyIiIiKKLaNGjcL3338PALDZbFiwYAFGjhxpuN+uXbtw1lln4eDB\ngwCAgoIC7Nmzx5tyZt26dXjooYcAuFJX7tq1CwBw0kknoXXr1kHLXbt2LYqLiwEAgwYN0rStc3Nz\n8Z///KceZwlUV1fjm2++wYoVK7B7925UVlYiJycHBQUFaNWqFc455xwMHDhQM+dVUVERrr/+eiiK\ngv/+978AXGl3zjzzTL/ye/TogTfeeMPv9+Xl5Vi+fDlWrVqFw4cPo6ioCDU1NcjLy0Pv3r1xwQUX\noHfv3kHrHY46qK/BDz/8gMWLF+PAgQM4ceIE8vLycMopp+CSSy7BySefHPwCEhElGoWIKIEMHjxY\nAaAAUDp37qycOHEi5H2rqqqUHj16ePfv169fwO3GjBnj3WbFihXKxo0blT59+nh/J/6MHTtWqaqq\navC5HT58WBk9enTQ43h+UlJSlKlTp2r2Pf/88w338/ysXLlSs++3336rFBQUGO7XtWtX5fvvvw9a\n/4bUwWPr1q3KxRdfrLtvz549lcWLFzf4ehMRERFR5K1evVrTlpsyZYqp/RcuXKjZ/4033vCuW7x4\nccjtz1B/CgsL63Wen376aUht6hYtWijbtm3z7rdr166Q69a/f3+/41533XWK1Wo13Peyyy5Tjh49\nGrDuDa2DxzvvvKO0bNky6L6SJCljx45ViouL63WNiYjije9rWCKiOLd161asWLHCu/yXv/wFmZmZ\nIe+flpaGJ5980ru8Zs0arF+/XnefTZs2YciQIbrbzZkzBzfddFPI9QikqqoKw4YN86bb0VNbW+uN\nBgqHQ4cO4ciRI4bbbd++HRdeeCG+/PLLsB1bbenSpTjjjDMwf/583e02b96MUaNG4fPPP49IPYiI\niIgofGbNmuV9nJub641wD9WoUaMwbNiwgOXFii+++ALXXHNNSG3qY8eOoaKiImzH3rFjh3ciWz3z\n5s3DmWeeGfLEu2YoioLbbrsNd9xxhzf1ULDt5syZg8GDB+PYsWNhrwcRUaxhjnkiShhLlizxPk5J\nScG1115ruoxx48Zh4sSJ3rySP/74I/r06RN0+7vvvhvV1dUoKCjAjTfeiNNOOw1paWnYvn073n33\nXWzbtg0A8Nlnn2HZsmU466yzTNcJAN577z1s2bIFACBJEi666CKMGDECbdu2hc1mw5EjR3D48GGs\nX78e3333nd/+zz33HO655x68/vrr3vWTJ09Gv379/Lbt1q2b3+8sFgsGDBiAoUOHolWrVsjPz0d2\ndjaKi4uxcuVKfPrppygrK4PD4cCtt96KrVu3Ijc3N2x12LNnDy6//HKUlpYCALKysjBmzBgMHjwY\n+fn5qKmpwbp16/Dhhx/i4MGDsNvtuPnmm3HqqafqpsQhIiIiosalbsNfffXVSEtLM13GzTffjB9/\n/BEAsHr1alRUVCAzMxOnnnqqN0XOrFmz8OGHHwIAHnzwQVx44YVBy3v88cexatUqAMDMmTPRsWNH\n77qUlBTT9XviiSeguLMIt2zZEjfeeCP69u2L3NxcVFVVoaioCAcPHsTixYvx888/a/Zt2bIlvv/+\ne8iyjPPPPx8AUFhYqEnB6ZGdnR3w+IWFhTjvvPPQq1cv5Ofno7CwEIqiYM+ePVi4cCG+/vprKIqC\nrVu34uGHH8bMmTPDWoe//e1v+Ne//uVdPu200zBmzBicdNJJSE9PR1FRERYtWoRPP/0UdXV12Lp1\nK2666SZ88803epeViCj+NWq8PhFRGN1+++3eYZBDhgypdznnnHOOt5wbb7zRb706lQ0A5cILL1SO\nHz/ut11lZaUyaNAg73Z33nlnves0btw4bzkzZszQ3ba2tlbZvXt3wHUTJkzwlrNgwYKQjn348GGl\npKREd5ujR48qZ511lrfsadOmBd22PnW49NJLvfuMHDlSKSoqCrhdRUWFcsUVV3i3HT9+fEjlExER\nEVH01dXVKRaLxdt2mz17dr3K2bZtm6Z9vmzZMr9tnnnmGe/6mTNn6panTsH4+++/16tOHqWlpd6y\nWrVqFTRdjMexY8eUiooKv9/b7XZvOR06dAj5+Lt27VJkWdbdZtGiRUpGRoYCQElOTg5ax/rUYefO\nnYrNZlMAKElJScq7774bdNvffvtNk+7nf//7X0jHICKKV0xlQ0QJQz00tCFR0l26dPE+Pnr0qO62\n7du3x5w5c5CVleW3Lj09HS+++KJ3+Zdffql3nWpra72PL774Yt1tk5OT0aFDh3ofS1RYWIjmzZvr\nbtOiRQt88skn3kl2582bF7bjb926FV999RUAoFOnTpg7dy4KCgoCbpuRkYGPPvoIbdu2BeCawFd9\n7YiIiIgodhQXF0OWZe9y586d61VOp06dIEmSdzmW0qCo26L9+vVDixYtdLfPy8vTTDbbUB07dtRc\nm0DOPfdcPPHEEwCAuro6LFy4MGzHf+211+BwOAAATz/9NCZMmBB02759++Ktt97yLntGOBARJSp2\nzBNRwvCkOQGAZs2a1bscdSd0SUmJ7rZ33HGHbsN5yJAhSE5OBgDs37+/3nVSp9P5+9//HlKeyGhr\n06YNevfuDcCVn19xD9dtqG+++cZb1p133ml4o5KWlobLLrsMAFBTU4PVq1eHpR5EREREFF5iW7u+\nbXir1aoJlDFqw0dTQUEBWrVqBcCVJvN///tfI9cosFGjRnkfr1mzJmzletLRWCwW/OlPfzLc/pJL\nLvGmM1q+fHnY6kFEFIuYY56IEoanAxxwRXrUlzqqxSiH5IABA3TX22w25Obm4vDhwzh+/Hi96zRx\n4kS8+eabOHbsGF599VV88sknGD16NAYPHoz+/fujV69esFqt9S4/FLIsY9myZfj555+xbds2lJeX\no7q6WtMBv2fPHgBARUUFKioqAo4kMEs90uD//u//vBP8qo/reez535PbH2jYFyJEREREFDmpqama\n5YaMdKypqQlabmOSJAnPPPMMJk6ciIqKCpx99tno168fRo4cidNPPx0DBgzQ5LCPlMOHD+Obb77B\n+vXrceDAAVRUVMBut3vXV1VVabYNh9LSUm+7PCkpCePGjfOu02vLe0ZRHDhwICz1ICKKVeyYJ6KE\nkZeX533ckOGrxcXFAcsMJCcnx7A8T4d5Q6LcW7VqhSVLluDWW2/Fr7/+ioMHD2LmzJneiZlycnIw\ncuRIjB8/HhdffLHhcFWzPv74Yzz66KOmOrnLy8vD0jGvvjH49ddfTe9fVlbW4DoQERERUfiJbe36\ntuFPnDihCcwxasNH25133gmLxYK//OUvOHr0KNasWaOJSm/fvj2uuOIKTJw4ET179gzrsYuLi/Hg\ngw9i9uzZmrRBesrLy8NybHWq0draWtMpcsJVDyKiWMVUNkSUMNq3b+99/Ntvv9W7HLGRHCt69eqF\nX375BT///DOeeOIJDBs2DJmZmQBcjdbPP/8cl156KYYMGRLWKPGXXnoJ119/vekyPbkkG6qioqJB\n+4d6A0JERERE0ZWTk6NJX1PfFCpi6sJwzrcULrfffjv27t2Lzz//HJMmTcJpp53mnZ9p7969eO21\n19CrVy889thjYUsJefz4cQwdOhSzZs0y1SaOlXZ8uK4DEVGsYsQ8ESWMoUOH4uWXXwYA7NixAzt2\n7NBM5BqKffv2YfPmzd7ls88+O6x1DIczzjgDZ5xxBgBXFP66devwzTff4N1338WePXvw888/Y/To\n0VizZk2D09vs2LEDTz75pHe5oKAAo0ePRq9evVBYWIj09HRNCqHHH38cGzZsaNAxReqbtalTp6JX\nr16m9lfn5yciIiKi2HLWWWdh/vz5AIBvv/0WjzzyiOky1JHYBQUF6NGjR9jqF06pqam48sorceWV\nVwJwpY9ZtmwZPv/8c3zwwQeora3Fiy++iIKCAjz44IMNPt5f//pXbNq0ybs8bNgwnH322ejcuTNy\nc3ORkpLivV/Yu3ev7sSs9aFux7dv3x7/+te/wlo+EVG8Y8c8ESWMs88+G6mpqd78kv/85z/x2muv\nmSrj9ddf90ZmJCcnY9iwYWGvZzhZrVb069cP/fr1wwMPPIBBgwZhw4YNWL9+Pb799luMHj26QeXP\nmTPHm3ty1KhR+OKLL5Cenh50+yeeeKJBxwtEPWohJycHF198cdiPQURERESN4/zzz/d2zC9evBi/\n//47evfuHfL+VVVVePfdd73L6klMY116ejpGjRqFUaNGYdy4cRgxYgQAYNq0aWHpmP/kk0+8j+fM\nmYOrrroq6LaRmGi1devWSEpKgt1ux5EjRzBkyBDdewkioqaGqWyIKGHk5ORg/Pjx3uU333zTVE7y\n3377TdORf8MNN6BFixZhrWMkZWRkaCZUCpTOJykpyfs4lJz327dv9z5+6KGHdBvShw4dwh9//GFY\nptk6DB8+3Pv4/fffN9yeiIiIiOLH+PHjNZHVEyZM0ExKauTBBx/U5KZ/4IEHwlm9qDn33HPRtm1b\nAMDBgwf98u1brVbvPFKhtKHr6uqwb98+AEDnzp11O+UB4LvvvjMs02wd0tLSvCN9a2pq8PHHHxvu\nQ0TUlLBjnogSyqOPPurtPHY4HLjsssuwdu1aw/3++OMPXHLJJd5Jo9LS0vDYY49FsqqmzJw5M6Qc\njeqJUgNNAKuejLWoqMiwPHVexwMHDgTdTpZl/OlPfwqpgW62Dpdeeql3kt1ffvkFU6dONdwHAEpK\nSjB79uyQtiUiIiKixpGVlaVJX7Ny5UqMHTvWOwpWz+TJk/H22297l6+44gr069cvIvWsrz/++ANf\nfPGF4XYVFRUoKyvzLlss2u4aSZK880sdPXrUsN2tvhcoKipCbW2tbh3//ve/G9bRbB0AaAKnHnvs\nsZACeQBg0aJFWLlyZUjbEhHFK3bME1FC6dSpE2bMmOFdPnz4MIYMGYK//OUvAScvPXz4MJ577jkM\nHDhQ0/E8ffp0dOvWLSp1DsW0adPQuXNn/OUvf9HkwPeorKzEG2+8obkx6du3r9926pz7n3zyiWE0\n0kknneR9/Oijj2Lx4sV+22zcuBGjR4/G559/HsqpmK5DTk4OHn30Ue/y448/juuvvz5gLntFUfD7\n77/jz3/+M7p27coIeyIiIqI48Oijj+Lcc8/1Ls+bNw+9e/fGxx9/7Bec4nQ6sXjxYpxzzjl49tln\nvb9v3769JqVNrDhy5AiuvPJKDBgwAO+++y6OHDnit82GDRswZswY77m2b98eubm5ftt17doVAFBb\nW2sYgJKUlITu3bsDcN0rjB07Fnv37tVsU1NTg3/9618YOnQoTpw4EdL5mKkDANx8883o2bMnAKC4\nuBiDBw/GK6+84jciAADKysrwySef4Nxzz8XIkSOxZ8+ekOpERBSvJIXTXBNRAnr++efx5JNPQnyL\n6969O1q3bg1JknDo0CFs2bLFb5vnnnsOTz31VNCyr7rqKm8n9IoVKzBo0CDdurRt2xYHDhyA1WqF\nw+Go1/n07NkTW7Zs8S4XFhaiS5cuyMzMxNGjR7F161ZUVlZ61/fq1Qu//fabJm0MAGzdulUzGVaL\nFi3Qu3dvTYqaf/zjH94G9/79+9GtWzdNxFL79u3RqVMn2Gw27Nq1Czt37gQANG/eHLm5udixYwcA\nYNeuXejYsaPfuZitA+CKyL/88svx1Vdfacpq1aoVunXrhrS0NJSVlWHbtm0oKSnxrh8xYgR++OGH\nQJeUiIiIiGJIcXExLrvsMr9c5ykpKejatSvy8vJw/Phx7Nq1C+Xl5ZptOnTogG+++QYnn3xy0PKf\nffZZTJ48GYBrNOptt90WdNsLLrjAO6Hs77//jlNOOaW+p4UlS5bgnHPO0fyuU6dOaNWqFZxOJw4e\nPOhNOePx+uuv45577vEr689//jNeeeUV73KXLl3Qrl077wSuPXr0wBtvvOFd/+KLL2pGAVutVnTt\n2hWFhYWoqKjAH3/84W3nDx48GCtWrADgyvv/7bffBjwfs3UAgC1btmDQoEGaEQGSJKFLly5o2bIl\nZFnGkSNHsGPHDs29mVFefCKiuKcQESWoOXPmKC1btlQAhPRTWFiofPLJJ4bljhkzxrvPihUrDLdv\n06aNAkCxWq31Ppe///3vSk5OTkjn0alTJ2Xr1q0h1T/Qz8qVKzXbz5w5U5EkSXefrKwsZdGiRcqw\nYcO8v9u1a1fY6qAoilJbW6vceeedIT+fLVq0UD744IN6X3MiIiIiiq6amhrl7rvvVmw2W8htvtGj\nRyuHDx82LPuZZ57x7jNz5kzdbc8//3zvtr///nuDzunIkSPKVVddZdie9vzce++9iizLAcvas2eP\nkp2dHXTf/v37a7avra1Vzj33XMNjjhgxQvntt9+8y+eff37Q8zFbB4/NmzcrJ598csjP66hRo5Q9\ne/bU/8ITEcUBprIhooR11VVXYceOHZg2bRoGDx7sjeJQs1gsOOOMM/Diiy9ix44dmslTY8n999+P\nXbt24eWXX0bv3r0DbtOpUyc8++yzWL9+vW4anlmzZuH+++/X5HrXc9ttt2HBggUB83Wmp6fjmmuu\nwfr16zXDj42YrQMAJCcn46233sLPP/+MsWPHevPOq1mtVgwYMAD//Oc/sWPHDtx0000hl09ERERE\njSslJQXTp0/Hpk2bcO+992pGUKoVFBTghhtuwNKlSzF//nwUFhZGuaahy8/Px5w5c7Bu3Trcdddd\naNmypd82KSkpGD16NBYtWoTXXnst4FxRgGvk6rJlyzBq1KiA9zai5ORkfPvtt5g8eTIKCgr81p98\n8sn45z//ie+++w6pqakhnY/ZOnj06NEDa9euxXvvvYczzzzTb2Qv4LpW48ePx7Jly7Bw4UK0b98+\n5PKJiOIRU9kQUZNx/Phx7N27F0ePHoWiKMjPz0f79u0DdvDqWb16NQ4dOgQAOOuss9CsWTPd7Rct\nWoTq6mpYLBZcdNFF9a2+hid9TUVFBTIzM9G5c2e0atXKVBkOhwNbtmxBUVERqqurvcNGhw4dGvSa\nHDhwANu2bYPD4UBhYSG6du2KtLQ07/oVK1aguLgYgCuNjHpduOrg4XQ6sW3bNhw9ehTV1dXIzc1F\njx49THX2ExEREVFsO3r0KIqKilBSUoKsrCwUFBR4U1OasXPnTm8KxpNPPhmtW7cOuu3atWu9OdAH\nDx6MjIyM+p9AALt27cLBgwehKAry8vLQrVs32Gw2U2VUVVVh69atKC8v987ZlJ2djYEDBwbcXlEU\nbN26FUVFRUhPT0ebNm009w9VVVX46aefALhSTQaar6qhdRD33b17N0pKSmCz2dCyZcuAaTCJiBIZ\nO+aJiIiIiIiIiIiIiKKIqWyIiIiIiIiIiIiIiKKIHfNERERERERERERERFHEjnkiIiIiIiIiIiIi\noihixzwRERERERERERERURSZm/a7CTpx4gRWrVqFX3/9FYcOHQLgmpV93LhxYT/Wnj178M0332D/\n/v1ISUlBt27dcPHFFyMrKyuqZRARERERxTNZlvHHH3/g119/xW+//Ybq6moAwBNPPIHOnTuH9Vh2\nux3ffvstVq5ciZKSErRo0QKDBw/GyJEjYbVao1YGEREREcUXdswHMWXKFHz66afYtGkTZFnWrKuo\nqAhrx/yJEydw33334f3334eiKJp1GRkZeOmll3DXXXdFvAwiIiIionh26NAhXHfddVi1ahUqKir8\n1t92221h7Zj/8ccfcdNNN2Hv3r1+63r06IHZs2djwIABES+DiIiIiOIPO+aDWLhwITZu3IjMzEz0\n798f/fr1w9///vewH8dut+Oyyy7D4sWLAQAjR47EsGHDUFlZiTlz5mDHjh24++67cfz4cTz22GMR\nK4OIiIiIKN6Vl5djyZIlsFgsOPnkkzFw4ECUlZVh7ty5YT/W8uXLcf7556O2tha5ubm4+eab0alT\nJ2zZsgUffPABtmzZghEjRmDZsmXo3bt3xMogIiIiovgkKWJ4NQEAvvvuO7Ru3Ronn3wyLBYLampq\nkJaWBgCYMGEC3n333bAc54UXXsATTzwBAHj11VfxwAMPeNfV1NTgyiuvxIIFC2CxWPDbb7+hT58+\nESmDiIiIiCjelZeXY82aNRgwYIA3leP06dPxpz/9CQCwYsUKDBo0qMHHsdvt6NmzJ3bu3Im2bdti\n+fLlaN++vXf9pk2bcOaZZ6K0tBT9+vXDqlWrIElS2MsgIiIiovjFyV+DGDVqFE455RRYLJG7RNXV\n1XjppZcAAMOHD9d0qANAamoq3n//faSlpUGWZTz33HMRKYOIiIiIKBHk5OTgnHPOifj8SrNnz8bO\nnTsBuAJj1B3qAHDSSSfhr3/9KwBgzZo1mD9/fkTKICIiIqL4xY75RrRw4UKUlZUBACZNmhRwm4KC\nAowZMwYA8PXXX6OysjLsZRARERERUeg+/fRTAEB+fj6uuOKKgNvcdNNNSE1NBQD85z//iUgZRERE\nRBS/2DHfiBYtWuR9fO655wbdbsSIEQBcaWmWL18e9jKIiIgosciyjNLS0nr/iBPfE5GPLMtYunQp\nAGDo0KGw2QJP25WZmYmBAwcCgHcuqHCWQURERETxjR3zjeiPP/4AABQWFqJFixZBt+vVq5ffPuEs\ng4iIiBJLeXk5cnNz6/1TXl7e2KdAFLN27dqF6upqANo2diAnnXQSAODAgQM4fvx4WMsgIiKipuOX\nX37BU0+Px6xZsxq7KhRGgUMzKCr27NkDAGjXrp3udm3btvXbJ5xlGCktLQ26zuFw4MCBA8jJyUF2\ndnZEc/ITERHFI1mWvZ1p7dq1CxoZS0TxYe/evd7H6jZ2IOr1e/fuxSmnnBK2MkLBdjwREVH9xFIb\nXpZl3HHHHVi/fj2s1tkYPHgwunXr1mj1ofDhnWEjOnHiBADXEFU96vWefcJZhpHc3FxT2xMREVFg\nO3fuRKdOnaJ6zG1bZ6NZM/12AgCUlVWgW/cbolAjovimbktnZGTobhusDR6OMkLBdjwREVHDNUYb\nXu3TTz/F+vXrAQBOp4xnnnkGH3/8caPVh8KHYRGNqKamBgCQnJysu11KSorfPuEsg4iIiBJXs+x0\nNM/JMPxplp3e2FUligu1tbXex0lJSbrbqtvo6v3CUQYRERElPrvdjqeffhoAcO6IfgCAf//731i3\nbl1jVovChBHzjSg9PR3Hjx83bGCrO9LT07U3zeEow0hJSYnuuq5du7qXLAAkU2XXX7SOkyhi8Xop\nYSzL6PzCeaxYEYvPKVFjM/u3Hq33BgWAazLV7OzsKB1TRZZdP6FsR0SG1G3p+rbBw1FGKBqnHS+W\nIy4Hjw2TYqV9I8VK/Fr96yHFzDmEU6KdU7g+d+PjuiTma7JxKEqsttnCVy/NOSoO7To4I3ZcoRZo\n1Da82//7f/8P27dvR3Z2Bv7976cx/qYX8O23v+DJJ5/EV1991Wj1ovBgx3wjys7OxuHDhw0ncVIP\nWc3Kygp7GUaaN28e4pYSotVZGDON9nghxeD1Cmu/vMH5JWS/fAw+p0SNzeTfemO8NTRKDmdFcf2E\nsh0RGVLfnBu1wdUTKav3C0cZoWiMdrxfO92vzRL8ODHTxo+Zdlb96yHFzDmEU6J17Ibrczc+rgs7\n5puCSAXf6X+OKErk3+8aax6W6upqPPfccwCABx+6Gnl5OXhuyq349ttfMH/+fPz0008YMmRIo9SN\nwoPvjI3Ik59KPflTIOr1nTt3DnsZRERElMA8EfOh/BCRoS5dungfG7XB9+3bB8B1Q9+xY8ewlkFE\nRESJ7c0338SBAweQn98M9913FQCgX7/uuOqqYQCAJ554AgqDa+IaO+Yb0SmnnAIAKC4uxoEDB4Ju\np84b1atXr7CXQURERAlMVkLsmGejnigUrVu39k6q+ttvv+lu61nftWtXpKamhrUMIiIiSlzHjx/H\nCy+4ouUfe/x6ZGX50tlNfu5WWCwW/Pjjj/j+++8bq4oUBuyYb0SjRo3yPv7uu++CbudZl5WVhcGD\nB4e9DCIiIkpgSojR8jGbr5Qo9px//vkAgJ9++gkVFRUBtzl06BDWr18PALjgggsiUgYRERElpldf\nfRXFxcfRrl0B7rzzUs26Hj3aY/x4VzuCUfPxjR3zjeicc85Bq1atAADTp0+HHGAI+c6dOzF//nwA\nwJgxY5CSkhL2MoiIiCiBMZUNUdjdcMMNAIDKykq8/fbbAbd57bXXvG3z66+/PiJlEBERUeI5duwY\npk17CQDw1FM3ITU12W+bp54ej+TkJKxevRpffPFFtKtIYcKO+Qh64YUXcP/99+Pxxx8PuD4pKQnP\nPPMMAGDNmjV4+OGHNd9yFRcX45prroHdbkdycjKefvrpiJRBRERECYwd80SmbN++Hbfddhtuu+02\nzJkzJ+A2F110Ec466ywAwNNPP40ffvhBs/6zzz7DtGnTAACXX345Bg4cGJEyiIiIKPFMnToVFRXV\n6N69HW4aH3jEXPv2hZg40RVJ/+STT8LpdEazihQmksLxDgH9/PPP+OSTT7zLTqcT06dPB+DK0T5y\n5EjvupSUFLz44ot+ZfTs2RNbtmxBTk4OysrKAh5HURRcd9113mN1794dZ599NiorK/HNN9+gvLwc\nAPDBBx/gpptuilgZ9VVaWurNjwlY4T9bdmRIUTpOwpBi8HqF863H6PwS8W0uFp9TosZm8m9dQbTe\nGxQAroZySUkJmjdvHvEjqj+fj217H82bZRrvU1aBFt1uBhC9ehJFwgsvvIAdO3Z4l//44w+sWLEC\nAHDppZciPz/fu+68887DuHHjNPsvW7YMQ4cOBQA89NBDeOWVVwIeZ9++fRg0aBAOHjwIADjzzDPR\nqVMnbN68GatWrQIAdOvWDStWrEBeXl7EyqivSLXj/drpfm2W4LFhMdPGl2Ilfq3+9ZBi5hzCydrY\nFQizcHWixcd1SczXZONQYjb9YPg6hjXnqDi064TjRO56RL8NDwD79+9H166dUVtrx7///TTGXn1O\n0G2LikrQvdv1qKyswfvvv4/x48dHpY4UPrbGrkCs2rBhA1577bWA6zZu3IiNGzd6lzMyMgJ2zIdC\nkiR8+OGH6NmzJ15++WVs3boVW7du9a7v0KED3njjDYwePTqiZVCCiYdO22jWMZzHClcnfzw8R01e\nPN48xGojnRpVqNHwjJinBDFv3jz88ssvAdd9+eWXmuXMzEy/jvlQtWvXDitXrsTdd9+NL7/8EsuX\nL8fy5csBADabDePGjcNrr72m26EejjIoTGKi07BhdUiMjs/6dzJH6vwj1+kX3g71xnj+pbhsLzcO\nJYzt9IY815Ht1Nd7TTOaO1RTpkxBba0dfft2xZirhuluW1iYi3vvuwovPD8bzzzzDK655hqmr44z\njJgPYuPGjSHPbJycnIy77rrL7/ezZs1CSUkJUlJSMGnSJMNyqqqq8OOPP2Lfvn1ISUlB9+7dMWjQ\nIEgmOvDCUYYZjJiPUez0jRx2zDch8Xij0cQ7Vhkx76WJmN/0r9Aj5k+aAIAR8xTfvvzySxw5ciSk\nbU855RQMGjRI87uioiJ89dVXAIA+ffqElELm8OHDWL16NUpKStCiRQucfvrpaNGihal6h6MMMxgx\nLx48Fj732THftDrmw4sd87EtnB3zDdF4r2dzHfNNOWK+ffv22Ldvn2G0vEdZWQVatbwCdrsDa9eu\nxamnnhqFWlK4sGOeGoQd8zGKnb6Rw475JiQebzRio8HfaNgx76XpmN84M/SO+V63A2DHPFFTwI55\n8eCx8LnPjnl2zNcfO+ZjGzvm2TEfKk/H/A8/TMPwYX1D2qdZ84tRUVHNjvk4xFQ2RERERIlMVkJM\nZcNYDSIiIiKimBBqG57iGjvmiYiIiBKZIrt+QtmOiIiIiIganxLiPFEU19gxT0RERJTIQm3Us2Oe\niIiIiCg2KEr4UulSzGLHPBEREVEik5XQ0tQwlQ0RERERUWxgKpsmgR3zRERERIlMDjFing1/IiIi\nIqLYwFQ2TQI75omIiIgSGTvmiYiIiIjiCyPmmwR2zFNcUqAdbi9BaqSaxCgxD5kkXh9LAwpv4h8M\nftcy0urzXIXxOQpXTruIXbeGvJYTUWNdjyb+vhDjJFmGFEKjPpRtiIgiKTHb+OH7bJYko7KsYTuW\nljOMZYVeR+PzFbZvwLVWdNoyZuvhLdM9d0t99/erRwNfS+GqBwWn6MzX09DnT3OcBrS9zb4O9M7J\nHPFvP5zvKwnKVMQ8U1LGK3bMExERESWyUCeO4uRSRERERESxwUzEPJvxcYsd80RERESJjKlsiIiI\niIjiigQZUthGLFCsYsc8ERERUSILNdpGZqgNEREREVFMYI75JoEd80RERESJTFFC63RnKhsiIiIi\notgQahue4ho75omIiIgSGVPZEBERERHFF0bMNwnsmCciIiJKZOyYJyIiIiKKL0qIbXiKa+yYJyIi\nIkpkihJampoopbI5duwYZs+ejW+++QZ79uxBTU0N2rdvj759++Kaa67BkCFDIElS0P0PHTqEt956\nCwsXLsSBAweQkZGBk046Cddffz2uuuqqqJwDEREREVFEKYqrc54SGjvmiYiIiBJZDEXMz549G/fd\ndx9KSko0v9+7dy+WLVuG6dOn47333sMtt9wScP+FCxfi2muvRWlpqeb3W7Zswdy5c3HBBRfg888/\nR3p6esTOgYiIiIgo4kJtw1NcY8c8URMkIXgkokiBGEFpUT2O5IeExXiTBGLmOQlE+zwFu3YhPl+N\nPgFk+J77hl7Xpsz/b19PJP9eTbzP6ERZA4iB13YjkUOcOCrCk0vNmDEDd911FwDglFNOwYMPPojB\ngwcjJycHR48exYoVK/DRRx9BCfI8rV+/HmPGjEFlZSXat2+PF198EUOGDEFpaSlmzpyJN954A99+\n+y1uuOEG/N///V9Ez4WIghM/P/w/i8X39eCfIcZlxaLIfSZKUlLEylYaKSpTkoJfL8ngWurta0Q8\nX71jKfW85wlWv/qfV2jn25Drkoii+do2aoqaoVdvo9eQppwG3rOrX0+N9T7RZHHy1yaBHfNERERE\niSwGIubXrFmDe++9FwBw5ZVX4pNPPkFSkq+DqVWrVujTpw/uvPNOyEHqcf/996OyshLZ2dlYunQp\nOnToAABo3749pk+fjpycHDz//PP44osvsGDBAlx44YUROx8iIiIioogyNfkrO/DjFb9KJSIiIkpk\nno75UH4i5N5774XD4UCbNm3wwQcfaDrlRRaLf/N03bp1WLx4MQDggQce8HbKqz311FPIzc0FALz6\n6qthqjkRERERUSNQGr8NT5HHjnkiIiKiRKbAl85G7ydCgTa///47li9fDsDVQZ+ZmWm6jC+++ML7\n+Lrrrgu4TWpqKq644goAwJIlS1BWVma+skREREREMUCSFUiyHNIPA+bjFzvmiYiIiBKZIof+EwHz\n5s3zPr7yyivrVcYvv/wCAMjLy0P37t2DbnfmmWcCABwOB9asWVOvYxERERERNTpZBpzO0H4obrFj\nnoiIiCiRhRItH+oEsfXw66+/AgByc3PRtWtXrFy5EjfffDNOPvlktGnTBn379sWkSZN0O9I3b94M\nAOjSpYvusTp37ux9vGnTpjDUnoiIiIioETCVTZPAyV+JiIiIElk9Jn81SgPTvHnzkA+/a9cuAECH\nDh3w/PPP46mnntJM8Hrw4EGsW7cOb731Fv785z/jxRdfhCRJmjKOHDkCAGjZsqXusVq1auV9fPTo\n0ZDrSEREREQUUyIYOEOxgxHzRERERImsHhHznTt3Rm5ubtAfMzyd/Nu2bcNf/vIX5OXlYcaMGdi+\nfTv27t2L//znP+jZsycA4OWXX8bUqVO11ZdlVFdXAwDS0tJ0j6VeX1FRYaqeREREREQxQ1EYMd8E\nMGKeiIiIKJHVI2I+nJzuvJcVFRXIyMjA0qVLvR3xANCuXTucd9556N+/P3bu3IkpU6ZgwoQJKCgo\nAAAoigJFcX1pIEbSi9TrZd6kEBEREVG8itFO9xMnTuC3337D4cOHkZmZiU6dOqFnz56G7XSPAwcO\n4Pfff0dZWRkKCwtx+umnIzMzM8K1jl3smKeEoAhTUEsI7Q0hYRi+AQqDYyT1n77+G70kTAaovdbh\nG3Rj+JxJERrgE87JDk3VsT7nE7yumqsX5JwU3WOavA5mX3PqXRvruSZTGvQuGtZJRK2hHxZGQz2b\n6MRIoQ6DVW2zc+dONGvWLCyHz8jI8D6+/fbbNZ3yHs2aNcNTTz2FW265BdXV1Zg3bx5uv/12AIDV\nakVqaipqampQU1OjeyxPZD2AJt3AJ4opivD+E+KNe8CiErzNLxm0gSxS/W/fFb82vd5ntfbzUtxX\nj/85WHXXS0KbUbteb5054jnovQzNnK8e/XMDPOfnd01MXSOd44ehTR2uaxHpsvVez0bXoSH18N/X\nzDU3uA/Xqbepv0mhTvp/+xRTFPh/hjainTt34tFHH8VXX32F2tpazbq2bdviuuuuw4svvhh0/127\nduGuu+7CwoULvUE3AJCeno4JEyZg6tSpSE9Pj1j9YxU75omIiIgSmSKH9mWJaptmzZqZyiOvJy8v\nD9u3bwcAjBgxIuh26nVr1671K+PAgQOGeePV682m3CEiIiIiihlK7ETMz58/H2PHjvUGyfTt2xfd\nunUDAOzYsQNr167FtGnTgnbMb968GUOGDEFpaSkkScLQoUPRqlUrrF+/Hps3b8brr7+OX3/9FYsX\nLzZMXZlo2DFPRERElMiUECPmIxSRc9JJJ+GXX34BAOTn5wfdTr2utLRUs65Hjx44cOAAdu7cqXus\n3bt3ex8HiswnIiIiIooLMTL56/LlyzFmzBjU1dVhwIABeP/999GrVy/NNocOHcKnn34acH+n04kx\nY8agtLQUubm5+PrrrzFo0CDv+jfeeAP33HMPfvnlFzz88MN44403Ino+sYb5AoiIiIgSWT0mfw2n\nAQMGeB+Xl5cH3U69Ljs7W7OuX79+AFyN/v379wctw/MFgCRJ6Nu3b32qS0RERETU+ExN/hqZdnxt\nbS1uvfVW1NXVoUePHli0aJFfpzwAtGrVCvfff3/AMj788EP88ccfAIB//OMfmk55ALj77rtx4403\nAgDeeecdTaBNU8COeSIiIqJEJofaqI9Mg/6yyy7zTga1fPnyoNup1/Xp08evDI/PP/884P6yLOOL\nL74AAJxxxhlo2bJlvetMRERERNSoQu2Ul+VI9cvjP//5D7Zu3QoAePXVV/2CZ0Lx4YcfAnB13l97\n7bUBt3nwwQcBAA6HA5988kk9axuf2DFPRERElMgaOWK+bdu2uPTSSwEAb731VsA88Q6HAy+88AIA\nICUlRdMRDwBnnnmmt7P+5ZdfDhh5/84772Dfvn0AgEmTJoX1HIiIiIiIokpBo7bhAeC9994D4GrP\nX3jhhab3r66uxtKlSwG45pOy2QJnVO/bt683qObbb7+tZ23jEzvmiYiIiBJZI3fMA67O9KysLBw5\ncgTnnHMOfvzxRyjunPYbNmzA6NGjsWrVKgDAI488gjZt2mj2lyQJr776KiwWCw4cOIBRo0Zh3bp1\nAFwN/unTp+O+++4DAAwcOBA33HBDxM6FiIiIiCjiFDn0nwiw2+34+eefAQDDhw/3joD97bffMGfO\nHHz++edYs2YNZJ0Jajdt2gSHwwEAOO2003SP50lDuWHDhjDUPn5w8lciIiKiRObNPRnCdhHSrVs3\nfPHFFxgzZgw2btyI4cOHIyUlBVarFVVVVd7t7rzzTjz77LMByxgxYgTefPNN3HPPPfj111/Rt29f\npKWloba21ntDcNJJJ2HevHmwWBh7QkRERERxTGncyV83b96MmpoaAMCpp56KhQsX4k9/+hO2bdum\n2a5ly5Z48skncffdd/uVsXPnTu/j9u3b6x7Ps764uBhlZWVo1qxZA88gPvCuhYiIiCiRKUroPxE0\nYsQIbNy4Effccw/atm2Luro6VFVVISsrC6NHj8bChQvx1ltv6Xaq33nnnVixYgXGjh2LnJwcVFdX\nAwB69OiB5557DqtXr2ZueSIiIiKKfyHPE+ULrjl+/DhKS0uD/pihTj+5fPlyXHTRRdi2bRtOO+00\nXHPNNTj//PORnp6Ow4cP45577sFtt93mV4Y6/WROTo7u8dTrjx8/bqqu8YwR85SQFJ2ZLyRIUaxJ\nhEjmzkE8Z4slxftY8Rv25NQsKdCu15ZkFF0ZvHNFkoy+F7QarA8TyWm8jS5fPY3OSarHd6Hi9Q+6\nnfp51DxJqvPTHeIWbP9gDM7V71pE6fmkRiL8HUXpbVZ8//I/rHa9+MkgKU7VusaLRom4UNPURCEi\np02bNnj99dfx+uuvo66uDnV1dcjMzDRVxoABA/Cf//wHAFBZWYmUlJSg+SqJiIIybIvqqf++xm1g\nNW37yWpJ1d1a3W70b+MLy4oj6L7+9NujkqR+D9bW2SLZdLYFLBZhveraitfK6Nr5n7OPLJ6vsK0i\nrK8PT9199dQue66FZ9n7v3c7q3Z7mDv/+tK9bgbPvd6+/tvqtxdDve8JdFy9+yyjOorX1Uw9zPCv\nh9HzGbwefnWOUCoTamT1iJg/++yzDYoMvTx15/jcuXORmZmJ//znP5pc84cPH8aYMWPw008/4V//\n+heGDx+uSSmpHhmbkuLrhwokNdX3GafeL9ExYp6IiIgokSlK4Hzy4k+EI+ZFycnJpjvlRRkZGeyU\nJyIiIqLEU4+I+XBKTk7WLL/88st+E8C2bNkSX3zxhbdNP3XqVM16dWe83W7XPV5dXV3A/RIdO+aJ\niIiIiIiIiIiIYkWowTWqqPqlS5eipKQk6I8ZWVlZ3scpKSkYP358wO0KCgpwxRVXAAA2btyIw4cP\nByyjsrJS93gVFRUB90t0DDEiIiIiSmQxMPkrERERERGZoMgG6Wj9ZWdno3nz5mE5vHqy1s6dOyMt\nLS3otr169fI+3rNnj3fOp3bt2nl/v3//ft3jedanp6cjLy+vXnWOR+yYJyIiIkpkMZRjnoiIiIiI\nQiCjUdvn7du3R1ZWFk6cOGGYOlK93uHwzdlx8sknex//8ccfumVs2rQJANCzZ09IJudVjGdMZUNE\nRESUyEIdAsuOeSIiIiKi2FCPVDbhJEkSzjnnHADA3r17IeuMrt29e7f3cevWrb2Pc3Nz0adPHwDA\n4sWLg+5/4MABbN26FQC8x2wq2DFPRERElMjYMU9EREREFF9CnfhVloEINeOvueYaAEB5eTm+//77\ngNvY7XbMmzcPgCvKvlOnTpr1V199NQBXxPzy5csDljFz5kzv47Fjxza43vGEHfNERERECUyRlZB/\niIiIiIgoBiho9OCaq6++2ps//u6778bBgwe1VVQU3H///di3bx8A4P777/cr4+6770Zubi4AYOLE\niX6T0K5cuRIvvfQSAGDUqFE444wzwn0aMY055k1wOBywWq1hzXVUXV0Np9NpuF1SUhJSUlJCLjcS\ndSUiIqI4pCiun1C2I0pAiqKgsrISmZmZYSvT4XCgrKwspG1zcnKQlJQU0raRqCsRERHFIVOd7pFp\nx1utVnz44YcYNmwYduzYgVNOOQW33HILevTogdLSUsyZMwerV68GAJx33nm49957/cpo1qwZ3n33\nXVx11VXYsGEDTj31VNxyyy1o3bo11q1bhw8++ADV1dUoKCjAW2+9FZHziGXsmDewbds2vPzyy/j6\n669x+PBh2Gw2dO3aFddccw0efPBBZGRkNKj8008/HRs3bjTc7vrrr8fs2bMbta7UyBryJYukHRxj\nkZJV68SNtXnDFJ1ZwBVhW8lgEI4k6a3XrtPf1hy9cxDP11jwelokW9B1gZaD0a9v6NsA2udIvY//\n/uG7DoGYeT5DPbdw70vh1DjPg/j8y4pD2KJWu726noncKR3qxFH886EEM2vWLLz99ttYtWoV6urq\nkJqaikGDBuHuu+/GVVdd1aCyV61ahcGDB4e07eLFizF8+PBGqyuFQ+jtmIa1Ya26ZSXZtPdz4uee\novgCvsTPQL9l4T1f0rQZxcAxsd2n/aJJ3Qa2WJKDrnOtF5aFsqyq7Y2upV67zymcr6Roy5Jl4Xro\nLEl+H5CB28Gec/Vfdj2vnnPzXAPJ/XyL21nc5XvKkYTXRTAKtM+bX7soyAe9+HwHu38IdAz/snTu\nN4TXglgf3ftOoY7ia0O8L20QnSaT3/2vWA+dczCzbWIyDkglgSL7v1k3gtNOOw3//e9/MX78ePzx\nxx949dVXNettNhvuuOMOvPrqq7BaA79fXXHFFZgzZw7uuOMO7N+/H1OmTNGsP/XUU/Hxxx/7pcFp\nCtgxr+OLL77ADTfcgKqqKgCub4rq6urwxx9/4Omnn8asWbOwaNEitG/fvsHHstlsuhHxqampMVNX\nIiIiiiNKiNE2ifzlBDUpDocDY8eOxdy5c72/y8jIQGVlJZYsWYIlS5bg1ltvxbvvvhuW0aU5OTmw\n2YLfVulFy0e7rkRERBQnFMRM+3zAgAFYv349Fi9ejP/97384fPgwUlNT0bNnT4wePTqkvsYrr7wS\n559/Pr788kusXbsWZWVlKCwsxLBhw3DOOefAYmma2dab5lmHYN26dbjuuutQVVWF7t27Y8mSJait\nrUVFRQVmzJiB1NRUbN++HaNHj0ZdXV2Dj3f99dejoqIi6M+7774bM3UlIiKiOMLJX6mJefjhh70d\n3XfffTeOHDmCiooK7Nu3DzfccAMA4L333sPzzz8fluPNnz8fx44dC/pz5plnxkxdiYiIKE4osdWG\nt1qtGDlyJCZPnoy3334br732GiZNmmQqADgjIwPXXnstXnzxRbz99tt47rnnMGLEiCbbKQ+wYz6o\nhx9+GDU1NcjJycGiRYswbNgwWK1WZGRkYOLEiXjvvfcAABs2bGj0HEjxVFciIiKKMnbMUxOyZcsW\nTJ8+HQBwww03YPr06cjPzwcAtG3bFh9++CEuuOACAMDzzz+PQ4cOsa5EREQUe5wy4HCG9kNxix3z\nAWzbtg0//PADAGDSpElo27at3zbXXnutd2biN954I6r1U4unuhIREVH0KbIS8g9RvJs5cyacTick\nScJzzz0XcBvP76uqqjBr1qxoVk8jnupKREREUcbgmiaBHfMBqHM8jh07Nuh2nnVbt27F5s2bI12t\ngOKprkRERNQI2KinJmTevHkAgH79+gWdQOz000/3Drv2bN8Y4qmuREREFGUxlsqGIoOTvwawevVq\nAK4JV0899dSg2w0aNEizT8+ePRt8bIfDAUmSgs5kLGrMusYTCU19siztd3BJtnTvY3E2eL/lBsxw\nLwnHVc9EL85Kb7RvQ+idg3i+RsR6WyTfhG42S7JmndWindBZ75yC1THU+ikhzHKvLsupOIKuU5TA\nZUlS8Pclo+fTDL1zDlY37/owPtcUGxryvDnlOmFZLFv9ekrg10eoDXY26inOnThxAtu3bwcADBw4\nUHfbM844A3v37sXatWshy3KDc5sqioITJ04gIyMjpHZ8Y9Y1loW1zd6gtom5fc21g0K7zwMAi6S9\nXU+2ZmiWxc9IWbF7H4ttPadcq38wWdUWFM9feFokoV5WVRvYKrSHbUJ72GLR7qtuS7sOpb5f0L9W\nYrtQ3Q60qK4FAMiy9rhOSWwLB29jiu1LTx099fM8/1b3dfEse87N879nvRXa31vc5Vm8v7dqt1MC\nv75kyVUv2X0f4Kmn7D4Xxb3ec58gq85D/VrxlBPKOr1rLi4rkrCt8Hq1Cq8zsSx1fcW/Mb/2oV4T\nxuBtRSxLfSy/dQZ1NqynKeqyEridSsGZ6XRnMz5uJW6rrgG2bNkCAGjfvr1uw7pjx47exw2NQv/u\nu+/Qvn17JCcnIykpCQUFBbj00ksxZ84cOJ3BGwmNUVciIiKKI4yYpybC0y4GgM6dO+tu62kbV1dX\nY+/evQ067q233orU1FTk5OQgKSkJHTt2xIQJE7B27dqYqysRERHFB0UJPSUlxS92zAdw7NgxAPBO\nvhRMQUGB93FxcXGDjnno0CHs27cPSUlJUBQFR48exVdffYWrr74a55xzDoqKihqtrqWlpUF/ysrK\nTJVFREREUaYoof8QxTF1G9eobaxeX1JS0qDjbtu2DYqiICMjA4qiYM+ePXjvvffQv39/PP30041a\nV7bjiYiI4hTb8E0CO+YDqKysBACkpaXpbqdeX1FRUa9j9enTB9OmTcPq1atRXFyM2tpaVFRUYMGC\nBTj77LMBAP/73/9w4YUXorbWf/hhNOqam5sb9McowoeIiIgalyvaJoQftukpznnaxYArzaOehrbj\nU1JScNNNN+HLL7/Evn37UFNTg4qKChw5cgRvv/02CgoKIMsypkyZgqlTpzZaXdmOJyIiilMc9dok\nsGNeh2Jwh6peL0n1y4f48ccf48EHH0S/fv2Qm5sLAMjIyMAFF1yAxYsX46abbgIA/Pbbb3jjjTca\nta5EREQUh9iopyZC3cY10zauT8720047DR988AEuueQStG3b1ltGfn4+7rjjDqxevRpt2rQBAEye\nPBkHDx5stLoSERFRHOLkr00CJ38NIDMzE6WlpaiurtbdTr0+MzMz7PWwWCyYPn06vvzyS5SVlWH2\n7Nl48MEHo15XvSGzZWVlMRFtk5CTu4bxCxRxEpokiy/yShYn7DGYoEY94Y/RhEx+E6VqJnMymPy1\nARN2GZ9DAya0FeqlnuA12aL920qR6ve+oJ7IVXx+GkJ9/WsVbcSdeoIwowlWAePn3gzDSaTUE9NC\nfxIp/7KDrw/ntQ0nSxx+Zx4r11Jv8i7XemGiN9VnR0I3Zzn5KzUR6jZuY7fj27ZtixdeeAE33XQT\nampq8H//93+45557ol7X2GzHa9+bTbXjwzjZvJkYtUhN7mpcdvA2POD/uedUfLf3FuEzz7AeqmOJ\nbTGROMGruj1sE9dJ2slfxclgJeF6WYXJYPWIbUgn1JPfasuRJe1ksOLksOp6iJPuBpv8VayrdxJY\nYXJXz7JVXHY/XxZ4Jnt1L7sne01Skt3/eyaJdf2tONztYad7clUnXM91nVSnqa/nejjc564+D821\ngjBRruq1ILbxZL9txclfnarH+hOliu16kUWnWSKbuVVWxMXQJ2w1mszVzGSwxu3U2GhPi2K1Xk2C\nDLbPmwB2zAdQUFCAffv2Bc3r7nH48GHvY6PckPWVlZWF4cOHY+7cuVi/fj1kWdZEykSjrs2bNzdX\naSIiIooZnlQ1oWxHFM/Ucyqp276BHDp0yPs4Uu34iy++2Pt43bp1mnXRqivb8URERHFKYTR8UxB/\nYXlR0LNnTwDAvn37YLfbg263c+dO7+OTTjopYvXxNMCdTqdfXslYqysRERHFGKayoSaie/fu3gCW\n7du3627raRtnZ2d7U86EW/Pmzb31KS8v16yLtboSERFRbFFkJeQfil+MmA9g4MCB+Oijj1BXV4fV\nq1dj0KBBAbf76aefvI9PP/30iNXHEyVjs9mQlZUV03WNloRIXRPFXP+SMMwy2ZbtfWwmjYjxccSh\nycKyKv2JUbqOSKayUTNKwSHW0yJeSyn4xMtiuhh1WUlSumadTTXM16YaehtsWLFDGI5rV6p865Ta\ngI8zrb7ovCz4HgNAjcVXV6cS/Eu+YCxCahtZJx2O0TBWz3Bc73oleGofo9Q26u1DSdFDsU9veL3f\nkH5hKLpTrhOWVem1FO17spJIyW1k908o2xHFsbS0NPTu3Rvr1q3DihUrgm6nKIp3/cCBAyNWn0OH\nDkGWXX9YeXl5MV3XiBLavH7teFNtvvDFlUUqPY3ZNqzYXtYrK1XK0SwrUvA2lF2u0qwTyxI/Ix2S\n9jNSb18xXY3N4mvX2sTUNcKyJ42Ld1lMB2PiOfZPweJbdqBWu62YnkbR1kutTtafZNlzP+C5LsHS\nV1q8KW2EdD2Kti41UpDjuf9UMpRmAIAOaAkASLW6jlvhcD3fNe60RbXuNrzdfZ/geT043P9rXh+S\n7/qI1zHUNDeB91URm1Li7a/Reh1imhsxtY02HY3w92sitU28pp+hBMGI+SaBEfMBXH755d7Hn3zy\nScBtFEXBf/7zHwBAnz59Ipafsbi4GEuWLAEA9O/f32/i1liqKxEREcUeRttQU3LFFVcAADZt2oS1\na9cG3OaHH37A0aNHAWjb0uE2Z84c7+NAneqxVFciIiKKMZ4c8xz1mtAYMR9A+/btcfnll2Pu3Ll4\n5513MGnSJPTo0UOzzZtvvokdO3YAAO67776A5VRVVUGWZUiShIyMDNP1qKurw4QJE7zpa2655ZaI\n1ZWIwm/YiFM1y+qIeaukjTRSTzJlUXxRHZJmckrfB64sRkgpvignWTXZlzqKJcXiGimxfNGm0E6A\niBIDI+apCbnjjjvw0ksvoaqqCg8//DAWLlwIq9X3uVpbW4vHHnsMANCiRQvceOONfmU4HA6UlZUB\nANLT05Genu63jaIofgEzamvWrMHTTz8NwJXSJlCnejjqSkThl9siWXe9JwLb6n4LSJICT7Qrudvu\n4igRm/CBm4TgoxUAIAXHXQ+KW+puR0QJxkzEvMLO+XjFiPkgXn75ZeTk5KC6uhrnnHMOPv30UxQV\nFWHnzp2YPHmyt4N7yJAhGD9+fMAy+vXrh6ysrKC5ICdMmIDLLrsM7777LpYvX44dO3agrKwMO3fu\nxKxZszBgwADMmzcPADBs2DDcdtttEasrERERJTAlhB+iBNCqVSs899xzAIBFixZh9OjRWLZsGQ4c\nOIBFixZhxIgRWLNmDQDglVdeQXZ2tl8ZP//8M/Lz85Gfn+/tXFerqKhA69atcccdd2DOnDlYsWIF\ndu3ahQMHDmD58uV4+OGHceaZZ6K8vBySJOH1118POAlrOOpKRERECUpRQv+huMWI+SC6du2KuXPn\nYuzYsTh06BCuueYav21OP/10zJ07VxPZYkZVVRW+/PJLfPnll7rbjRs3Du+8807Q40SjrhREFPPE\nN4RFyKmYbmnmfeyfs1vMMR88L7eYr0/MCSnmZ5d08nMa5ZMUczOq+eUzj+DTItYjSZWfshKlmnVO\nRZvbUlE9D+K10Ls2gYj5rzXR9KrsjuroeU8ORFlxIlvW5ijNkHyjemRNWb7Xg+68AAZtAXVOS1nS\nvsYcYk55iHnCVflChdz6ftsq4vrg+emN6OUybwgzuVPJ3PMgvl/VCjlb7XK1Ztnh9P1NKgbRavEs\n1DQ1TGVDieKhhx7C0aNH8dJLL2HhwoVYuHChZr3VasXzzz9f74AVSZJQVFSEmTNnYubMmUG3a9as\nGWbMmBGwbR6tujYGw7mg/HKwq+b7aMAcQ8YaJ098Q8oW2/CZ0M5V4JffWxW5XWfR5lBXz0cEAA5J\n2061WYLPMSTmgU+yCHMlwXesZGEepSRFzDGvPSebrF3Wu5Zim8AhRKrbVXnl7Rbt+fmdv5CDvkY+\n7n0szkljFXLqe17jnrp62pie/PnievFvwtNW97Tfff+7fu9pz3ra8Z72TLrcAQCQm+LKae8ZtZPk\ndB0nSba6z9VVD7u7jW13v04cqnax+nmw++Xj9z3fdqVGs85hIk+8IjyXhnNFCdurn29xW5FRznld\nOjnnzeaUF1+/kbqfoCZCATiNQeJjx7yO4cOHY8OGDZg+fTq++eYb7Nu3DykpKejevTvGjRuHW2+9\nFTZb8EuYkZGBjIwMZGYGngzm//2//4fx48fj22+/xW+//YZDhw7h2LFjSEtLQ9u2bTFo0CDceOON\nGDBgQMTrSkRERAmKqWyoCZo6dSouv/xyzJw5E7/++itKSkrQokULDBkyBHfeeSf69u0bdN+kpCTv\nZK2B0lFmZGSgqKgICxcuxA8//IAdO3bg0KFDqKqqQrNmzXDSSSdhxIgRuP7665GTk+O3fzjrSkRE\nRAmK+eObBPbUGigsLMSUKVMwZcoU0/uuXr1ad31qaiouuOACXHDBBfWtnkZD6kpERESJSZFDi7Zh\nRA4lmkGDBmHQoEGm9zvjjDNw7Ngx3W3y8/Nxww034IYbbqhv9TTqW1ciIiJKUArYMd8EsGOe4oLx\nkNj4SCkTPiaH1/oNg23hfSwbDAtUpOA9Nf6pa0JPbSOmRbEoBucUxs+jhqQSEetpVU3UarVoh/mm\nWXO1+6quj1XRPifqcsU0NYGI+yuqIcROi2ryV1VqlwzFFbWXq7RCoU07ksepyksXLEWd1cTfmVMo\nxKHq8RPXORUxtY2Qnkb1GrULqWwcwuvXKQxpVg+ZNUrbZPS3ECvEv7N4F87rLr5f2aza4fMOIZVN\nrVTmWxBf34mUq5ER80REREREcSXU4BqKb+yYJyIiIkpgjJgnosYVPKc8AEiqfNaRzDHfkMAMc/Uy\nG0ATfHsxt3merM0xbxfm6VEHMNRK2jRMdZL2y2kxB7s6mEO8VklSqmY5WUnTLKcovvVJsjZQJQXa\nc7D5Pf/aL8YtqoAsWQhWUYQvze2K9vzrVNejTsihXyvkvq+xaOeh0dTZpg0EsUriObiWPTnlxaAJ\nT/CH/2tOcm8fONjFE0QiS+5c80JASrr7byUryV2O+7XjOYoniKZOdv3G7g4gcgo55wGgTlHlkRfO\nz66ad8cvmEqYb6sW2usoqRsTwmka5oHXyVevuy4A9bHE4BzDv2dF/dAgp7yJHPRm89UnHjG4KD6C\nohqVwlQ2TQE75omIiIgSGSPmiYiIiIjiS6hteIpr7JgnIiIiSmCKElpmnkTK3kNEREREFM8URYHC\niPmEx455ik+NllM+csNrI0kcBttCzvc+9s+zHfobvzgM0z+nvHa9VbIEXRdO/oNGhSGyOq8fo3qJ\nu6rzrqc5tPmsM+WcoPUQ62RV1Vo9zNShGsJqUw05TfJ7+/Y9b+rPbnV+9mYW17Dj9tY8tErXDjOu\ndQZ+3oNdDaNXiV1oQNSpyhe/9E+zap8xhywOU/Yt1zllYZ3+sjp/vZi73mhoqpm/hXCK5N9GohGf\nI3HOAZtF+zdZYz2uWa6UiryPE3kwraKEmMqG7X4iIiIiotjAiPkmgR3zRERERImMqWyIqBH5BUgI\nX5paJPUtafSCYBqSz97MvmZy24vlil8wFyRpc7uLgRC1su9r5jpZm2O+WpU3HNDmoxeJQQIpsjbI\nJ1nSBnikqZ5Dm1XY16I9J6sQ5aIXbyV+Yez3hbzf+fs+yGpkIae8rD3/WilLs3xc8l3bNKlSs84G\n7fnaFNf5JrmDZtIsrmWHu8LViutY4qT0nu2TJE/ud9d6pye3vPv8PDnmPctWd674vBTX8+C5Zk73\n8cSPb4s3l717O/hT161WqtGsq5F8eeNrFW0OebtcpVl2yNpc/kkW33W3CtdNjD1xQvsaVIS/FXVu\neFnY1kzOeb/c9mZyzhscxyhPvPrvP5z56qNJXa/w1ok55w0pMI6Io7jHjnkiIiKiBMbJX4mIiIiI\n4oupVDbswI9b7JgnIiIiSmDMMU9EREREFGecgOIw3oziGzvmKT74jXGMz1zv4lDeaEm2aoeytkr2\nDTEUAyQVEz0zkiTmkNeu98tBr1q0CNuG89qIZYv1SlJtYDRdgV++er+yfI+PVGuH42VL2uHG6uG3\n4nVOtlix+b+H/ernVG2XZvMNFfV8cd7tnEIA/kOZvfVVPU5x53LvP6qN3zXR7BNknUP1YnEK9fd/\n/oShxaoc89WytnWRn+oalrv7xyMAgK5Z2rJK63zLlQ5tuTXCiMcaR/AhzmKdG/Lajxfi32g8aMjz\n4BD2LRPmfai0lGrXW/aolsS/9gQKH5cl108o2xERhZukveW0CMtWS6pv0waklwkns/Uwl65GTN8Q\nnM2qbUu2zdBeO7vwUVXjtKkei20x7Wei+JmpXkwSGtPJQjqaVJuQrkbVsEwRLoVNWBZT2YjtdjWx\neSu25Rx+569+LLYZtel46oT15U7f/ZJdPqxZJ7ZzPUuedlaK1YL00lbIS7Fqjq0I26e6r1NZnavi\nhzP3AQAswutHEbppPNfsWNZ+1/+e7ZI927vI3tQ2imbZM+eUU/JdIIfkS+1jQbXmeEmKb1lShFQ1\nQuoaqyUFpcd85aZK2QhGTEcjCalMxNQ2UFTLQvokRUh7IqbBUaeNUSTttpIwRFBMz6LbHDKRQidQ\n2ZpdTaWu0W+nmilLfL8ySrGjdxwzjNPgaF8P6reKBLxNCw1zzDcJ7JgnIiIiSmBMZUNEREREFF8U\nhe3zpiAqHfNOpxNr1qzBkiVLsGrVKhw5cgRHjx5FTU0N8vPzkZ+fj27dumHYsGEYOnQomjdvHo1q\nERERESU+RYKihBANH8o21OSUlpZi6dKl+PHHH7F9+3YcOXIEx44dQ2pqKvLz81FYWIgBAwZg2LBh\n6NevH6zW0KOBiYiIiCgIRsw3CRHtmN+wYQNmzJiBjz76COXl5QG32bFjh/fxq6++CovFgqFDh2LS\npEm48sorkZSUFHA/Snx6qU0aKyWMnxgZbmsk2aYdUtgu03fTLI4KM5pbRD3cVHwWjIamqtOn+Key\n0T+wovt60O4rpmlJEfoI0qzBj2X0jPqVbfGVtS9Zu7c1SXtg9ZBhWRiPl2qzoEWa6y25U2bg42nS\n5tS4VuS6xwurh+OqS1Y/n+oRu7rPcwhDBY1S1+iVbxX2zXIPhy5Idf3fJ6dKs77M7vscOG7XXuNS\nYbnKoS27TvatF4c/CyOYDV/7ag0ZTtmY2WX0hovHC73nSRzSn16j/RssryvULB9VpfmqE16XiTRi\nlhHzZJbdbscXX3yBGTNmYOnSpZBl/RfHp59+CgDIycnB9ddfj4kTJ6J3797RqCoRERFRQlLQhNP4\nNCER6Zhfvnw5nnjiCSxdulTze0mS0LZtW+Tm5iIvLw8pKSkoLi5GSUkJDh48iKqqKsiyjB9//BE/\n/vgjCgsL8cADD+D+++9HSkpKkKMRERERUTDsmKdQ1dbW4p///CemTZuGoqIizbqMjAy0atUKeXl5\nyM3NRU1NDUpKSlBcXIwDBw5AURSUl5fjzTffxJtvvomhQ4fi+eefx1lnndVIZ0ONRvgGWhJyQ6tz\nygNAks33JamYa7uxNCSPsvn89MFHmaRatME13bOFvPFCMuxqVYBClVNbD3WwAuD/Zbb6y3ub8Bym\nCkEt6UIvQqoqUEXcNskvUKf+vUzix1SNcI7VTkm1TnvgWll7ne3CtSut853Ufps2H72Yj9+Xy91F\nggSrJKGF+6XtyXfuCR7yXFvPEWX3+uPuEUaeoAO/3PDCceyy012+EvB/D8X7v7scd451WZVrXYZD\n9VjM1+4rT8xHbrVo+2XSLM0g23x/0zlyC+/jWqlGs22tpA2+gSIs682BJdTRKW6gl/vdZF541cvZ\nePodM2Ur4qJ+nnjNtn6NNHM55/XKMjNHRoOYDBBSFNWzLJ6P4vcKSEihtuEpvoW1Y37nzp149NFH\n8dlnn3l/d+qpp+KKK67A4MGDccYZZyAnJyfgvk6nE+vXr8fPP/+MRYsWYf78+SgqKsJjjz2Gt99+\nGy+++CLGjh0bzuoSERERJTwFoaWy0RuZRIlvzpw5ePTRR7Fr1y4AQGpqKi6++GKMGDECgwYNQu/e\nvYOmqSkrK8Mvv/yCFStW4IsvvsD69evxv//9D0OHDsVVV12Fl156CZ06dYrm6RARERHFNwVMZdME\nhLVjfty4cVi1ahVycnJw++2346abbgp5GKvVasVpp52G0047DZMmTUJZWRnmzJmDt99+G6tXr8bV\nV1+NVatWoX///uGsMhEREVFCU2QJimHIF0LahhKTp60NAP3798edd96Jq6++OmhAjahZs2Y4//zz\ncf755+PZZ5/F77//jlmzZmHmzJn47LPPsHv3bqxcuTKSp0BERESUWBgx3ySEtWM+KysLf/nLX/DQ\nQw81eALXZs2a4fbbb8ftt9+OefPm4dlnn4XC5EpNmDB0yW9oVmwMe41V6ZZmmuWTs33v7o4G/FnZ\nDIamisvqIbINGcYKaCM7xRzzSRbtcqZNO9StdWaF93G1XTu8Wnyb8Tsnoez05Drv46OV6Zp1a1MK\nNMvq4cWyEJmalwIku0cr92tWiUCSLL7nbXuF61hpqa5zq3IE/htQ51FXD++tFp549Xbq5ylVFRyZ\npPNnJivalZVC+UmqDr904e+1V45rmOupLU8AAE479ZBm/fFDviGzlVXaocXbS5tplk84tNGc6mHb\n4pBl8bVv9IqUG2liTEsD/1aiQX/GgegRh/QfEuZ5KC7Wtk12q3LMV/oNkQ1v3RqTooSWn5LNrKZL\nURT07dsXzz77LC677LIGl9e7d2+8/PLLeOKJJzBt2jT89NNPYaglERERUdMRahue4ltYO+YXLFgQ\nkVzwl112GS699FLY7fawl01ERESUyBQlxFQ2jfTlEzW+Pn36YM2aNZDCPDt18+bN8de//hW1tbVh\nLZdinfaLToukveVU55QHgBRrlvexVchHH6vM5JHXyyFvJM2i/UJ5QG65ZrnGqb22FXbfsphjvtqp\nrYcYoKDeOtWqDdFMF5YzbA7tetVyqhAQY7Nql8UrJ/kF8viWrRbtcW027fK+Um0O/hrVOdrFnPoG\nn3En7L59/ytcqwrhYnlzzLt/nZ8qoY1iwcnZde56uI4tpojzBBNlJbmepwqLa7tap6fOiuZ/xT3x\nttMdMlsnucqvdf/vyRPvyVVucb/WPK85q/tqO93rFf/M7Jr9AhFf68mSNhCpUCmETS70LjtVkQ2l\nyomg5bq2NejfUV0+RRED9bSLivDKklX5P8Tz9t82eD2EmKyI5pz3Y+Ij2Uznrf/7V3RCso1y2fvl\n0Vd9HiiKA02SIoXwovNsG9mqUOSEtWM+khO0SpKE5ORk4w2JiIiIyIupbMhIpNvYkbxHICIiIkpE\nnPy1aQhrxzxRpEh+Xxdrv22V4iS6prHkoKVm+fT8Eu9jMT2HUcSkpBPF4p/2RVivCjmQxPADA2Y6\njJKStN+oZzXXRuodOODLmbtPSD+TLkT1JAvnkCKsd6rq1TxVe5z26dp6HKkN/pbbJtWONtnVAACb\n6toU1fg6M1JVdWmV6k6h445KSlZd+2Apg9TRT2V12rrUqKKK1FFR2aprWaOKvBJT8ViFr+gdwutI\nnWImP1kbldJ5kOu6tTnFlcKn+jfNamw5nOd9nCXse2qbI5plMdVNnSriySlETjllc6998ZyjxRKl\n8AcxYi0eiM9ZjRDhtitJ+/ddVJ2qWU6rauZ9XCaJf5+JE+HLVDZERERERPFFQWijXim+sWOeiIiI\nKIExlQ0RERERUZxhxHyTEPWO+V9++QVLlizB9u3bcfz4cTidgfOcebz00kvo3LlzlGpHRERElFhk\nWYIcwqijULahpquiogLffPMNVq1ahaKiIlRVVUHRGWbRpUsXvPjii1GsIcUKcaSr1aodrZRqa6ZZ\nzrD4RsbFS455kVHuZDW9fN6iHDlPs9x78DHNsrNC+zdYd8JXj5oK7a1+nTBa0inkoLeqRkwmJ2tH\nfaZmapeTs4RRsVm+59ySLlwLmzDS2T/JvHYx3fcakFo306wr+U+RZvnwIe1rSz3yVRwVXCeMnJSF\nt6/mqnNuK2nPt9yufc48oyg9I1Nzkxzok1TnzdTtGYla5/5ctbtXeE41xT06Ntt9qpXu31c7pIB1\n87zX2tzdN54c8w64/vfkmLfCVWCa4rousuS6Hk73durXnvpxipKmOV6W4pvbQJa0z3UWtNumWC1I\nS/I9Z5sdB7yPj+OoZluHMBoxSShLnI9BvSQLLxxxWzFfvaTKK6+Xfz4QRZ2fXtL2V0lCL6kilCXW\nU5033S/XvXBtxRzr6vcV8Th+dZYi13vrl/s9QsRpbmS5TrUU+ntsIlEUdsw3BVHrmN+6dStuuukm\n/PLLL6b2e+yxx9gxT0RhVdGng/extVrbIITQqHEKKXfqxAaUKr2MU5gYC9UmK9a/NQDAoSonSTWJ\nlybVSAPSjlhXH0BttTbfrzrVjDXJ12i0pNZBdtfLDMfKQ9rya30N9vyMGs26NqceBwAcyHQ9L3Ud\nteudqhv4GiGVEPZuNF03oqaGqWyood555x088sgjKC8vN97YrX///hGsERE1Vd9X+SYU3Zp0WLMu\nWVJ3gmp7+cTJX8XPvBR1+krZfCfgetthb/LBSsnVrna6i3R6Vrir4G11m/1CvLgFAKDWUuo6jjD5\nq01yte9tcjPXcSUHkvNCf9/2cBbn+h4LHdNJUo5mOc1mQ3VzX7s/RT7ufZyJOs22sqpj+nhx/SdF\nJmoqQh31CnDu13gWlY75Y8eO4eyzz0ZRkesb7qSkJHTp0gXNmzeHxaL/oZeVlRWNKlIsUn9lKn5D\nLkTTWPxyA8c+/9nQ9TXkm+qWSr5mufsIVbSJQ+hoNjiMutpSsnAOVuF5ShYaXOrk5xaTDVG/eqo+\nesSwErHsOu3r5cQ+Xx7y4lptHVOE96QkoWPeKhStzuFuEzrLU4WO+hYpqsgNocp2xXfcY9W++lar\n2sLqgKMWydpGsjoXfJLqxkJdv5xMV4d3XqtjGNhG21BWVMVZVd9VVB2y4GheBgCgosLXma8o+q/f\nLift0yyn5vnqZCvUPh+1G1wRLo72rvqt3K59vVY5fRe9IFV73gO6a8+jRYY2wknzenYowjqD5kus\nRidEKGBEMvs3GQPE51Cu1C7nb9a2IfZWaefbyK72LR8WPlfEiE8ljpu7TGVDDTFz5kzceeed3uXc\n3Fx07NgRaWlpOnsBPXv2jHTViIiIiBKWa/JXts8TXVR6M1977TUUFRUhOTkZL730EiZMmIDMzMxo\nHJqIiIioSYvljnlFUTRpDW22+PuiPZHJsoynnnoKANCnTx/MmDEDQ4YMaeRaUcwTgk/EAJpkSful\nTip894VWRfySVP/baKP0DvEuXUgxYm2pDUiwCl9QJ6sCWTKcwhfKDm0aEb9gHHVZwpf1kpiOJkn7\nnEqpquVUYV2akJ4oRVhO147iRJZq4vZCbbBGRusDSDnmq7ijSPgSXfXacyrmIubVqW/E4JpmQkCM\nuK/Dva8ndY3nafAc0xM57ynVcyRPMRb3bywGI2KT3UEEzdwR8cmSK9jIk27GKruuvc0dk1+Jckio\ngxWu7WxK4FQ26t8DQJ41O2gdnMLJb3TsQapc4V0+IR/xPpYVbcCM+r2gVpb9gk0URXud1elpxCA1\nMR2NuK8mHY1f+hn9dMqa9DMGUWtGaXHUJEl7ncV0PLr1MmiihfO90O+cG9A8NBNcKJ6D2UDGRMUR\nrYkvKq/0FStWAAAef/xx3HfffeyUJyIiIooSRZEgh/DTGB3z1113HZKSkrw/FRUVhvts3rwZd955\nJzp27Ijk5GQ0a9YMgwcPxvTp0+FwOAz3p9Dt3LkTRUVFsNlsmD9/PjvliYiIiKLEE1wTyg/Fr6iE\nJXkioUaOHBmNw1FCElPZ6H+nlAjfroZzkpU2adqJkTRpYYQIGL/sUuIsLGrC17eKXYhGqNX51l+M\nxDE6rl6aDf8ZkoJvC6BNni/3oQT9dFn+h1WCrrdK4jrt9Ui2qCchCh61k6qZuMr3e3WKmvQkYRIu\nm28f9eRd6sibtFzXPjkd6pB8kjY/pJo6KsqSVo7j3mAlX6SVOEmkIuTiTGslnHv/Qt+CEClV+psr\ntVJNjitqJCdJ+7rJS/adQ8tsbaedXCukMqnTj4BRC+vbRATfcvxSzIR+iqYYpvaJA0JgFpziRG/C\n9upoMTMT98UbRZFCGgYb7Ub9vHnz8Mknn5ja5+OPP8aECRNQU+Obi6K8vBw///wzfv75Z3zwwQdY\nuHAhcnNzdUqhUHna8D169EC7du0auTZERERETYcih9aGp/gWlbvQbt26AQCqqqqicTgiIiIicvNM\n/hrKT7SUlpZi0qRJAICuXbuGtM9PP/2Em2++GTU1NTjllFOwePFi1NTU4PDhw5gyZQqsVitWrVqF\nMWPGQOG437Do2LEjkpKS2IYnIiIiijIFsdeGp/CLSsT8LbfcgpkzZ2L+/PkYNWpUNA5JjeC880Yg\nKSnZeMOQ+b4ZFCd7lYRcleIkfbpR3vEijO+uXbIKNcsH81X57MTZTMVLZyJi3m9uRL1zEMs1Oq7e\nU2rmuACwn59cieJQ22713jesbxOR/Jo7Ed7PokTJ1f5tn0jV5uZt0UY7QmbQCd8T16nmHM06pyx2\nRNb/fcNur8P3339X7/0bypOqJpTtouX+++/HoUOHcO211yI9PR3bt28PaR+73Y6CggIsXrwYLVq0\nAAAUFhbiySefRFpaGh5++GEsWbIEc+bMwdVXXx3p00h4KSkpuOaaa/Dhhx9i48aN6NWrV2NXiSKk\nsLAQFr9hk/VjsWjb6Uk27Xtvuk07filV8r3fWoScy5HUkJzMehOCmy1Xd3Jxoai5K45rli1CenZL\nqur+KVW4llaD59euGrFZrR2eJ2vT00PWprrX1FO4bYNVmCfakiXc12UI949pquXkPZpVimKHNc+3\nvnP2Cc36aruvbDHHvPgZ53+roQR8DAB2WcwF7mJxP7JatNs73RGunjo4FIu7HE8uetdyrXu5yl0X\nz2X0DEKudQb+XLa6/07SFVc+/iTF9TeXbnGdf7Z7DoA6Z3PUSIdRKzs19XbVyfccO4UXml01ctsi\n3IRVCE9+paUUEny/U7/+xVHs6uXcFhbIijASVrELy6rRxn73d2Le+Pq30/z6EjTL4nuSufdJKQbb\n8eaDF4K/p4nXXb9s/eOK8wRon39tBgBF1g6TjdTdvSzLKCo6GKHSQ2AqTU3svdYoNFGJmB88eDD+\n9Kc/4a233sLXX38djUMSERERETyRNKHkp4xOfRYsWIBZs2ahefPm+Pvf/x7SPr/88gtWrlwJAHjo\noYe8nfJq9913H1q2bAkAmD59evgq3MRNnToVHTt2xM0334ySkpLGrg4RERFRkyDLrhSyofxQ/IpK\nxDwAvPbaa8jLy8OYMWNw5ZVX4uqrr0b37t2Rnp6uu1/r1q2RnBzOKGyKT+K3tIrOEmAwoX1cakgU\ngJg6uq5YFRFiFWY/N/F1nZgG3y8tvvjtrma9UCnhuJL4JJoJoBID+YV6WZN89crPqhK21Y+usei9\nuMR1YqSOqmyxFHVeePVeFlUEjlUVYWZN1pZgSVI9p+oC1Dnwm7ne8pPkFGDYadoKJPsijNS5xq2V\nK2DJdr0HJ9Wocsw7hONbhJzyvTpqlpX+fXyPhZE1eXu/AeDLMV9YrX1O1FFISUL++eoS4WPMzJ+J\niUEZrg2CF+73ejVTjWi2o2KwzSZGpZkhztXgtGvfKI7Xal9rNUJ+foekjvBKwA8Ot1iKmD9+/Dju\nuOMOAMDLL7+MwsJCgz1c5s2b530cLBLeZrPhiiuuwIwZM7B8+XIcPXoU+fn5Abel0LVu3Rr//e9/\nMX78ePTq1Qt33303hg8fjpYtW8JmC34rkZKSglatWkWxpkRERESJw5PKJuSNKS5FrWNekiSMHTsW\nS5cuxb///W/8+9//Dmm/lStXYsCAARGuHREREVFiUkIcBhuNyV8ffvhh7N+/H2effTZuvfXWkPfz\nRMsXFhaiY8eOQbcbPHgwZsyYAVmW8dtvvzGFYpi0b98ekyZNwp133omnnnoqpH369++PVatWRbhm\nFA/E1AZ+qQ9UkRviF65GE3M3JB2Nf1nhSU+jd35mjysL+zrrxPdpMdDFt2yRhOCbJKFe4mHtqudB\nm1HEL3WNfz18yxahYDF4QbIJM7X7TXKvkzajRrtvRrYQGFIrlK2pR9BVrrJVRTmc2i/664Qv/j1l\nJbvPJS1buGCeMt2paBx17lQ27nKqa10BMSfcqXeO2z3dMq7tHN6UN9pUOBnuVDWp1hRNPVLdaYqa\nJbt+0cod+9g8Sca2FAlFNa79qlSBNSfsvgtSJQeuPwDIwmvMCW2UgwSL4d+ptyzFYbCsLVud2sRc\nyhST/IJ1Qm8PGaWqMVOW/nG011jxi4gzU5j+av9rqz628L5iEOmkLcvg/Yv8mUplQ/EqKqlsAODt\nt99Gnz598N///jdahyQiIiJq8mQTP5G0aNEizJw5EykpKXjnnXdM5V3dsmULAKBz586623Xq1Mn7\nePPmzfWrKGkcP34co0aNwnXXXYcTJ04Y70BEREREDRZaKsrG6bw/ePAgWrRoAZvNBpvNhvHjx4e0\n3+eff47Ro0ejbdu2yMzMRJcuXXDrrbdizZo1Ea5x7IpKxPyqVaswadIkKIqCgoICXHPNNejTpw+a\nN29uOMlQ165do1FFinni60SMpkmAyV8NvvVvyLftTuEbdVuOqlwzk6y6dgi+LqyRCwbfG6qPJWaQ\n0Z8bSLNBRoowyZCQ6sL/uMHLFj8QxbLUaXL80ncECUSwqAJ01JFOFvHdO9jlUp+7J0WNU4b0v7Xa\nzYp96WOk7BTtPu79LGnqaCjtYSRhEmFl51Ht+qL/+R4X5mjWoX2u639rBgCgeatSbd1UwTQWIaWR\nIgsTP/lNBIzgDF7rei91028x4XxLaqy3txh5W1VfezGiR67Rvh4ya7R/38lW7Sx5ViVqAwcbVX0i\n5svKynS3bd68uak6VFRU4LbbbgMAPP744+jRo4ep/Y8dOwYAKCgo0N1OnRqnuLjY1DEosIceesgb\nWDNkyBBcfPHF6NixI9LS0nT3M/saocQltjUtkvbDXD3hqwRxnf57lxzGDye91GpiJL8e/wh4ceLQ\n0CetFNv/ycIk52L7C6plv3Vi2WJka5KvMSmmbpSShHsJscGl2l6yCRN+JgmN1GShMZckRKOrIugV\nMXpeiK63CVlxLcm+xrfwMvNbFqlHCdirtMe1CA1fTwrHtOau49W5J5MvKskE4EsN52l6eyLePRHw\nNU7XcrU7or7K/X+lu83riWyvdZ+/ZzLWUmcNACBFdrVfrO7Xh81931TpsLqP5/q/Y74TaVYZ7dJd\n2xXV+i6CU3VKdrv2/GpVkep1wvCJMku5ZlmBHPKIEqO0geLrXVHd4EjiMcLYLtW/zxYnsA1fhLwY\nBW+GmX3F6Hr/6yyOchHWa/7exeOGHkFvOMpBOK6kapc21dj6UNNRNoZJkyZp2tpOp35Hit1ux3XX\nXYfPPvtM8/udO3di586d+PDDD/Hyyy/j/vvvj0R1Y1pU7kjfeustKIqC0047DYsXL0ZOTo7xTkRE\nTUzbNm0BaDuXLdbAnfGS8O4d7GZDPSLU1ty9Udu2QKY297ZUoRqjnKYq3KEA+/cb1l10IKeT9hfq\nmzBJ6MyxRjpOl6hpq0+OeaPIdLNDyB977DHs3r0bPXv2xOOPP25qX1mWUV1dDQCGncHq9RUVFaaO\nQ/5qamrw/vvvAwBefPFFPPLII41bISKiGHXx6NEoKvV0zFvc/7vWORRPahrX74065ivdHfPVDldD\nvsYd7ePpQPV0xHu+uLK4OzST3UGPWe4vQzplObFx/nzT5yLnHfEtCOllUizVmuVMCHmOiChsFBmQ\nnbHXMf/RRx/hyy+/RKdOnbBr166Q9rn33nu9nfK33XYb/vznP6NVq1ZYt24dHnnkEaxYsQIPPPAA\n2rVrhzFjxkSy+jEnKh3z27ZtA+CKkGKnPBEREVEUhTrENUIROUuXLsWbb74JSZLwzjvvIDk52Xin\nIIy+EAhrzlnCrl274HA40KJFCzz88MONXR2KU2IEpUWIIFdHyVtNZlq1NiBs1j96N3hZxpH5qohx\nwy2Db2EUUWzJTRV2ELZXh0HLiv62Ak2txKh3caimsF4dyS5ZhXXi6Yo55UUOVcCGLEbyCkULHyc2\n1ehOKdkgUl+8PHWqDmiLEPlZIeQ+d1fR6e6j3n8sG/uLc7CjIllTtOdMPIH/nsB0u7u4Ovf51bkj\nTevcz5Hd3RHvye/ueV1Y3H8fnrP0dMh7lu3ukaRH3bPdN0tOwtFaK1qmunPhq56bFNWIimSH9lrV\nqIarOiRtHngnhLzwAXLOB1tnljpyW1GE16SJkSd+5Rr+lUYt43NUGOWnNxNBr59/HtBLjOgfiS+s\nF8pSNK+f2OucjoZYjJg/cuQI7rvvPgDAm2++iQsvvNBwn7Vr1+Ltt98GAEyYMAEzZ870rjvrrLOw\naNEi9OvXD5s3b8YDDzyA0aNHIzU1NVhxCScqHfPZ2dkAgDZt2kTjcNQU+Q0pa6w3rwZ0CIQz/Y7w\nKVcrNGqtzVOCbmviHsW/YS2eg17D22/8rHBg8WZCb1lYZ6pjRtjUanQ9xPWqSZRkh1CPuuA3S36H\ncQAWT6oaVXtGHQmveSy2gdSZfdTpdVTtmbojvoWSP7TXv9qe4X2cYvNtV9i+Es4SVySMJTv4R4ZS\no214H9+kbZTVqSYJS0vVDoFNK9Dua0nXnpxmJLbBsGz/15H+5qbotdHN/P2GNa1NFN/rYqtNGJBF\neB2mVWiHX6eK/Qia9AlxcIL1pMpIZbidx86dO9GsWbMGH7u6uhoTJkyAoii47bbbMHToUNNlWCwW\npKWlobq6GjU1NYbH88jMzDR9LNLytOFbtWplmH6SiIiIiMIp9iZ/veuuu1BcXIwbb7wRI0eODGmf\n6dOnQ1EUJCUl4W9/+5vf+rS0NEyePBnjxo3Dvn37MHfuXFxzzTXhrnrMikrH/Jlnnon58+djx44d\nGDJkSDQOSURERESoX475Zs2ahSVH+FtvvYXt27cjPz8fzz//PBwOh9826i9TnU4nHA4HJEmC1er7\n4iQ/Px979+5FUVGR7vHU61u0aNHg+jd1rVu3RqdOnbB3717Y7XYkJSU1dpUoIWjfj9RR8hbFIBF4\nA4h5sPW+kFWEHOtGkfl60bqyGH2K4Oeol+ceAKTcDO0vau3Csu89VqkV3m8dBt/QqiPdhehyKVX4\n208RI+hVy+KXeH5BLUK9xHPQiZgXSalCPVX1loS0jUjWf/+Sqmp9C07tl8Bynfa146hxnaPT4Ylg\nVyBBQaZNmPvGU5w3lY1rucb9cpLcKSq8udTdofU2q/b6Wt2BGL7/3fu7//dcYrv7QY03Nz1gVyRv\nrJRV9bpOUgVQ2YRgKoti5otYMwFRZiaDMsco6tsc9fMtRpsb5GP3+3uPrU7VUOhdS/388/plmctl\n79q7qTMTMR+NMaOfffYZPv/8c+Tl5eHVV18NaR9FUTBv3jwAwPDhwzXzQalddtllSElJQW1tbZPr\nmI9K6Mvtt9+Oli1b4rXXXoPdbjfegYiIiIjCQoYU8k+4lZe7RsgcPXoUBQUFSEpK8vt57733vNs3\na9YMSUlJ6NWrl6acnj17AgB27Nihezx1nsuTTjopXKfRZEmShCeffBLl5eV49913G7s6RERERE2G\novgCbIx+Iq24uBh33303AGDatGkhB8Ds3r0bx44dAwAMGjQo6HYpKSno168fAGDVqlUNrG18iUrE\nfF5eHr755htccskluPTSSzFz5ky0bds2GoemBOX/zXOsfJsarXqYm9G8Wha+EMtWTZ4nzp5tlO9A\nHVFhFSJ+xHyT4nq9tBuykHPEKSw7nMGXZTECyoA6kscvWaWwrXg5xOtj99XDKkQmaXJVAlDs+nlV\nbM3ceSJV6VrUj3XTuKjT16gijRS7r77q1DrNmmknbsp2qKJmUnz7W9IkWNLc0UCp6tlnheMLyxl5\nQgoRVTSUVQhYsog5QFOE6Kck1Xqj9EkiM2mNTKWjMfm33pC3hnCmq4lWJgq/XEtROmyydgKy1DTt\ncopF+3qwJFgO0WBcjfrQtgs3i8WiiXwPRJZlb5SUZ1ubTdtEPf300/Hdd9/h6NGj2LlzZ9DJaX/6\n6SdvOaeddpqpuu7duxejRo0ytU99dejQAQsXLozKsRrq1ltvxd69e/HAAw/A6XRi4sSJfs8PkT4x\nN7SwrOpQsDTgA9PoLUwvUt21vyoq1KAwM9H3kkFh2ihSg/PPydIuVwnpvSRV+86vLW2Q30/d/hQj\n5DOFibfThdy/qrlDFKHdIokR8tVCnZ3C9amxB18n0LQRIUTJZwujC9JSoMumira3C2kWj9dqlj3N\nHM+kjDaLAptFRmaS6xp7Rj545hPwXPpa9+Svnsh3T+09r59ki9W9nyenvKd8uPcLXHXPLYYwT6vf\n57/6aklBHov8Y9zFFKJirnf1TYmwrZBz3n9fvfSk+q9fMxHyRttq/57F49Y/gt4vEl0JPeemmCfe\nDDPHabjgOeeNRzU04F4sQecYUhDezKwN8ac//QlHjhzBueeei/Hjx4e83+bNm72Pu3Tporttp06d\nsGLFCuzatQu1tbVISTF4304QUWlVv/rqq9i7dy9GjhyJ2bNno1OnThgyZAh69OiB9PR03X0feugh\ntGvXLhrVJCIiIko4oQ6DjcTkUk8//TSefvpp3W1uu+02/Otf/wIAlJWVBcwNf/nll3tzUn766ad4\n/PHH/bax2+344osvALgmksrLyzNV17q6OmzZssXUPvUVKKVPLNq3bx+mTZsGAOjTpw/+9Kc/YcqU\nKRg6dChatmyp20Hfvn17PPjgg9GqKhEREVFCqU80/PHjx1FaWhp0fX1SVX755Zf497//jdTUVLz1\n1lum9j169Kj3cbA0NuJ6WZZRUlKCVq1ama5rPIpKx/zHH3+M1atXa363dOlSLF261HDfG264gR3z\nRERERPUUapqaSKSyCZcBAwZg8ODBWLFiBaZNm4Zbb73Vr3H/yiuv4MiRIwCAe++91/QxCgoKMGPG\njLDU10hOTk5UjtNQRUVFeO211zS/O3LkCD7//HPDffv378+OeQpIjJrUTMRtKre1WK6WIpmLM9Tm\nQjbaVht9rxeBKwbMm4m2FynuCZm9+4pRo3bfl35StXbUmF8NxVGg6lGJYg75DG3EvJIlRO6nChH0\n6m1rhWhzMbK1Rrtes1qI+hd3lZKEURBpqoj5TG0AoJIhRNAL1NdSqhbqnKxdRpU7Il72RLTLsFoU\npFtdEeEW4Wo73NfW5j4dizv62eLJGa9NMe+tiy83vPv3nnNx/++JlPdcJckdkO6J4nYqrh+Hu2PP\nqQR+jfsPEPZdd1nSRrnLYtS7GOWuWm5YhLzraMG2FRnlOjdF509SMorc13sPM/hT1533IqpR7+Gk\nvh7xeg6NR0HoOeY9zj77bP0yTf6tlJWVYeLEiQCAJ598Et26dTO1f0VFhfdxqs5nBeCaBDbQfoku\nKh3zrVu39uYUMqupDF0gfX6NTqPt4yA9gdgoN8fc9aiUKrW/yFJ1ZghDNf1S24jUaWDESDmxcWwT\nhsHqpWLRS1UDAOL8FHWqZcOhuWKKHfU5iOl2DF474vVR3QChRnsDJNWIdQ5+bSWbBZYs182EeuIq\nzTXV/B0ET6mjvh6S6piKauKq5GThmqlSfFjUx09PgpTtvslRD2sWhykL19gqrLeq6yfuK0wwJk44\nBvUwZTElhjjBmCic/Yxm3ofElDvhKtdv3/rvalx2jHbSquslNiyF9xhruvZGOklMZRPBSQZjSWOm\nsgmnf/zjHzj77LNRXFyMYcOG4bXXXsPgwYNRVlaGd955B88//zwA4LzzzsOVV15puvzs7GzvjQe5\npKSkoEOHDvXat3Xr1mGuDREREVHTEa388XoeeOABHDp0CL169cIjjzzSoLKM+vXM9vsliqh0zH/5\n5ZfROEzE7N+/HwsWLMD+/fuRkpKCbt264aKLLkKGwbfujXGcaNWViIiI4oMcYrRNLEfMA8DAgQMx\ne/Zs3HzzzdiyZQsuuOACv23OPPNMzJkzpxFql5h69+6N3bt3N3Y16k1RFCxbtgwrV65ESUkJWrRo\ngcGDB+OMM86IueNEq66NQbzR9ssxr3kcvvchSQk9qt1vX2HZKPq+IdH2muMY7S2k+lKc2rRYUpUq\nx7wYvGAwj5SkDipI0gbXKGlCjnkx5ZheoIQQVKHUifnag9dTEXPMW8TAEOGZUkVj+kXIi1H+AnVE\nsnRcG6lpSRKOK3mq6s4Z784xn2Z1BKqmN1Ld4o5TkbzPs+vaWL3leXLPK5rjeK6Qp4a+CHhP3aFZ\nlt37ywogKwpq3bnwVTE6mrgmp/DNvBPqiHlZWKcNPFIUMSretyz7rQseER+IJvreMHogfNEFuocy\njHoPfk660fQhlK3dNHJtNjPvlQ1hlHNe89kR48EjkeL6Gza3z9KlS3HKKaeE5fgLFy7E+++/D0mS\n8M477yBJ+GwIhTpFZXV1tc6W2vWBUlsmKs7cpKOiogIPPvgg3n33Xb8PgqysLLzyyiu44447YuI4\n0aorERERxRcFkncCOqPtGoPVavVO+moUKXPVVVfhtNNOw2uvvYbvvvsOBw4cQHp6Ok466SRcf/31\nuPXWWw0nm6WmYfXq1bjpppvwxx9/+K0bMGAAZs2ahZNOOikmjhOtuhIREVEcUWA6Yj47O7teeeQD\neeCBBwAAEydOxJAhQ+pVRosWLbyPPSkngykqKgIAWCyWsJ1DPIjZjvmtW7ciOTkZHTt2bJTj2+12\nXH755Vi0aBEAYPjw4Rg2bBgqKyvx2WefYffu3bjzzjtRXl6OP//5z416nGjVNfr08rPpR97EA7N1\nbkjqmypFmPwjTTUs3SqkWxFT24jUKUuShLeQlGTtsviNql5niZiqxi5MjCd+HqlfAxaDSfTEdDXq\nFDx+68TUNsKBxRQ7dar0NUYRFGJKHbVkG6RM9/VLTtL83leAan9ZeD3UqXKKqtP8qEN2rKpIICHw\nSf28alLLJNuATHf0kZiqKMj+QIAIJruqvn7pR4Tr4pcSyRr4MeAfkiQ+X3qdfA0ZKmcmVY3pYzWk\nXvXf1Y9RWqdYJFxnS6p22SYk+o1ktFEsUUKMtmmsVDZvv/023n777ZC379KlC/75z39GsEbUENXV\n1diyZQu6dOmCLIMI1Uj57bffMHz4cFRUVCAjIwPjxo1Dp06dsGXLFsyZMwerVq3C0KFDsWLFCtO5\nUsN9nGjVNZaI773qvPKRfVduQOkmct83JNe9UQSpX3tCjGRXtyENTtcvX7u6bLG9JeYFNkolqCa2\n/5OE+wXxnJyaUG7tOvFzSmxDpqjOP12bY96wzumqCHsxna7N71l1/euuj1WSYZUUSO62tlXyRLy7\n/nfIlgB7q4u3uMvTRsp7Ius9X5zb3TntHe4CPFHvde4Pebv7/kBWPMuunyqnq/xqp+88alXX2S7c\nVzgk332FQ4iQl6G973IKy7LiW/aLpjfMKS8Kvt7UvbH/iz3kXcV7dv86hx713ZD89GLgQrSi2o34\n1asBjUn/snQ2jvX8i2ES6jxRkVJSUgLA1VZ/5513dLf9+OOP8cknnwAAXn31Ve98Tz169PBus3Pn\nTt0ydu3aBQDo0KGDYT560fvvv4+5c+ea2qe+brnlFlx22WVhKy9mO+avvfZaHDp0CHv37oVNzGMd\nBX//+9+9Hd0vvfSSpkP7ueeew+WXX47vvvsOjz32GC688MJ6DxUJx3GiVVciIiKKP7ISYiqbRs5h\nGQuqq6uxfPlypKen1zsyCHDdyPzzn/9Ebm5uvSaijWcbNmzAwIED8dRTT+G5556L+vGdTieuv/56\nVFRUoKCgAEuXLtXcFN5///0YPnw4iouLMX78ePz000+Ndpxo1ZWIiIjij4LY+A5CFoMCA1AUBU73\nfHzq7Tt16oS8vDwUFxfj559/Drp/XV0d1qxZA8A1WtCsDRs2YN68eab3q4+zzjorrOVFpcf7v//9\nr/ebllAcOHAAGzduRG1tLXbu3Inu3btHsHb+ampqMHXqVACuGY3FKPO0tDTMmjULnTp1QnV1NSZP\nnlyvfKbhOE606kpERETxKdZT2cSSAwcO4LzzzkOXLl2wfft2v/V79+7Fueeeiw4dOniDIgIpKSnB\n5MmT0aVLl7jumC8tLdU9T5Esy9525rJlyyJVLV2ffPIJNm3aBAB45ZVXNB3dANC/f39MnjwZDz30\nEFasWIGFCxfi/PPPb5TjRKuujc0vQt4vx7wUdNuG8ItcNbWvVoPqZSLa3rRkIbJbHZ3ekNF9fqNi\nheM0hBh0J0Yvqy6+4hCeQyHXu1/EvLpss7mQk1WR/MnaOoojQSVhMnmrRYHFIntf2VaLkCPe6Yl8\nd/GMYvN0uHn286wXnzlvhLy7QE+wu2dAao17gxrZ3SkGT8S8Arus4LjddYQq1fWsVY1GqBMi2x0W\ndcR8nWadUxFzzDuEZXWOebEzT7+HUTcK3qB30lSktsG26shtBU5xpXbRYLiq5lCRzE8vlhWlSTTN\nRciL52AmI0DTbKMqIQbXRMqBAwd0n2On0+mNbL/uuuvwwQcfAIAmraTFYsEll1yC999/H4sXL8bR\no0eRn5/vV9aXX36JmpoaAMDll19uuq5nn302HA6DTAph0r9//7CWF5WO+UceeQSrV682vZ/NZkNu\nbm4EaqRv4cKFKC11pf646667Am5TWFiIK664Ah9//DG+/vprVFZWmp5gNRzHiVZdiYiIKD6FOnGU\n2cmlmqK6ujrs2LGjsasRNTt27MDYsWPrtW9hYWGYaxMazzDq3NxcjBs3LuA2EyZMwOOPP466ujp8\n+umn9e6Yb+hxolVXIiIiij+NncrGzLxNkiQFzXZy991344MPPkBdXR2eeeYZvPnmm5r1tbW1mDx5\nMgCgdevWuOKKK0zX9dJLL8Wll15qer9YELOpbNq3b48pU6ZoJgqIFnVk0Lnnnht0u5EjR+Ljjz9G\ndXU1fvrpJ5x33nlRP0606kqNT+/beKMce9VOIce8Orej0RfVerkcxUgUIWekkizmmA/+liOJeR/9\nki8KZal7kIy+qfeLplF9wIh58cU6ip+DViFqQn1sp3AxHToXV4xiSEny5QVNVUfsBIn2EXPda+oU\n+LiSRbWPeHybkFfeI8nmq4+ZfO3isvq6ib1/YkSX3vOlty5gHdVzEUBfQ3Kqm4lKMdu2alC96r+r\nf1lxEKki/A1Kydpr5zclge4FSpxeakbMUzRZLBace+653hGd0aQoChYvXgwAGDp0KJKTkwNul5OT\ngwEDBuCnn34yNSIgnMeJVl3jjdnIdL08yw0py+y7od4nRkOi7Q0/ifzaW9ag6/yay3rfxort8nBO\nqi225cRzUNVLbNJKBrnCFTHSv77EziW/eaLcFXNXR4ICC3yR9FaLa72nCed5DdjcueYd7u2SvDnl\nXdt7Ts9zWrI7p7znrD3rPYHvNe6o90qnK0q0CrWu48D1fHlyzFe4Q+trVFHy1bKvbV4naaPg7aoo\neaeYY14Rc8o7hWXfkyZG05tlLho7fO02RSfM3X+2gdAj6g1PR7edKt7fGUXqq97P4qENT4EpsZHK\npqEGDBiAW265Be+99x5mzJgBm82Ghx9+GK1atcL69evx0EMPYcOGDQBcIwjTxPlTElxUOuYXLlwI\nuzixo6C2thY7duzA+++/jw8//BBt27ZttG87Nm7cCMAV6RNoiIVHr169NPuY7ewOx3GiVVciIiKK\nT4yYp/rq27cvDh06ZLhdWVkZfv75Z0ydOhXbtm3D6NGj0aFDB8P9wm337t2orKwEAMM5lXr16oWf\nfvoJe/fuxYkTJ0xNVBuO40SrrrHIP7VN+MpSMzs5oros8/sGF9W3VrPpa9TUu5qZ3NUsi4lOfpMd\nmWGrt9+XByHUQwIs7sleLRbF93v4+mo9HfZWdwe91dshb9Fs7+WphlPbQe+J/al1f3BXuzvka6Vq\n126Ka+Jbp6LAqSioc/fk16nyPtepUtI4LNq+GnVnvNgRrwjflvhP8OpUrROfQLNPaOh/PZGaDNWv\nRnqTJgfYQD35s3+gnf4LS/tlobht6B31Rl9wsOM+drna8KE9P7HejJ8xYwaOHDmC+fPn4/XXX8fr\nr7+uWW+xWPC3v/0N1157bSPVsPFEpWM+Ly8vpO06dOiAc889Fx07dsSUKVPw4IMP4r333otw7fzt\n2bMHANC2bVvd7dq1a+e3T7SPE426elLlBFJWVmaqLCIiIoquUBv17Jgnkc1mQ8uWLQ23a9myJXr2\n7Ikrr7wS/fr1w0MPPYRBgwZh0KBBUailj7qNa6ZtvHfvXk0QSzSOE626sh1PREQUn0Id9RoPkpOT\n8dVXX+Gjjz7Ce++9h7Vr16K8vBwFBQUYNmwY7r33XgwePLixq9koYjKVzaOPPooXX3wRH3/8MV5/\n/fWo50M/ceIEABhGo2RmZvrtE+3jRKOujZHnv6Ei9a2vueF0scPurNb+Qh1NI0xmBKdBhIj62hql\nIBEjYvyGgfoosjARmF9ZOvUwer7FVCCW4MN8/esYfEIq/7LE40jBlwNt64nyUUf7BEtjIkw6FXQf\nyRl4G7FuNtU6zcRhFt810bvO4t+GVVjW9PiJ45KFsvzS4uit07nGgH4aGLPvE2Y2N5N+xnRqmzC9\nvzUkRY6RCBZt6rgGL5emQkFoUTTx+QlHsSQ7Oxv33Xcf7r33Xrz77rtR75hXt3Ej2TYOx3GiVdd4\nbMfHAjE6tSHRuPWPAQ7H0WKQ0Yexuk1p9mKF7YM+1AhVsaEROFLe2+Ty/l67naf56jfpsPALz6Xx\nTiLrbl87JFdUu2eiVkVKc2+vQFEAh3tHpyra3am6R5CFtrmsjnoX1vkvB6lkwDMyEs4IeTMTi9a/\n4Sr2DzSkHyKcZVFiUGAicKYRGvI2m82bHcUS4oil66+/Htdff31E6lNeXo4TJ06gWbNmmraTWWvX\nrsXmzZtx2mmnoUePHmGsYWCNdeusKyMjA126dEFtbW29ItEbyjMTcLBcjx4pqtnpPftE+zjRqisR\nERHFJ1mRQv4haqhTTz0VALB169aoH1vdxo1k2zgcx4lWXYmIiCg+xUMb3mazwWazhdwxH0lTpkxB\nu3bt8NZbbwVc/9577+Hiiy/GF198oVvO7Nmzce211+Krr76KRDX9xGTEPODKOQ8AqampUT92Wloa\njh8/7q1DMOqGcX0mJwjHcaJR15KSkqDrysrK0LlzZ1PlERERUfQoCC1ujBHzFA6N3YYX6xFMQ9rG\n4ThOtOrKdnz9hDNfdXTfW+PgndxoBLJmVGyYyw69oJC2krzbeULePf8rmlK8geqeiHdFGyIfLCLW\nL4LeE3HvXra4Q+1tDle3jk1yfcknucuXJAmSBNjce8iq0ZJWxTdC1iKMorTAt07Mi+6/rDM80a+z\nMHw55o1HtUSnkzCcUe2MkCd/ZlLZ8PVj5I8//sDXX3+N4cOHN3ZVNGKyY76srAx79uxBQUFBo0wc\nlZ2djaKiIhw/flx3O/VQ0uzs7EY5TjTq2rx5c1Pbx4J4TTkTKUlW4SZO3fpzisMPhe4bvxahqpEj\ntiKdwr5WYZZ6Z/APC0kW9hXLEnuVNMNcDZ5v8ZxkVb0UId2OeFy/eXacwZf9jqOTzkUKsK3nGqiv\nhVimd3tx/yD7KMG20WlEW9TpbyTfNdFrLBo+f6pl8bqI6WfE51PRWydeY7+KqY4jrNJ7bQei9zLz\nm/hJpxvU9D2KUC8z72+6s9E5dVYGKstEY89k0WHj9z4hLDbRjwZFkXydAAbbETXUunXrAAADBw6M\n+rHVbdxIto3DcZxo1TUe2/FERETkmSeqsWtBkRZzHfOyLOORRx6B0+nEk08+CavVxKztYdKpUyds\n27YN+/bt091Ovb5Tp06Ncpxo1ZWIiIjik4zQIubNZGNNdKWlpfjrX//q93tP9HGw9eJ2Tc2BAwfw\n8ssvIy8vD3fffXfUj69u44baNpYkyXQgUDiOE626xiIxsrUhfQ7hjWyvf1kx02/SkB6cYMEc4SYG\nuegx+r5YPN1w1VsMMDG6rO7JXDzpJCTZ/b87tsLzxbfTPaeW07OsuJfdJ+oJIPDEQsiy9gJ4ljxT\nQ6W4g1vSkKLZ3+KORrFKEqyShFT3nGJWVZCUOj7DIQRrOKQk72OLpO0ykoSAEUnS9tdI6uAUMUm+\nyYjecMWiNIzwHBjObSY+ZxbNkrkj620f+ogARuLHL9dbC5+/RBeVjvl58+bh6NGjutsoioK9e/di\nwYIFWL16NQYOHIi0tDS8++67Abe//PLL0aJFi0hUF6eccgq+++47HDt2DAcPHkTr1q0DbueJCAKA\nXr16NcpxolVXIiIiik+hRtswIsenpKQETz31VL3XJ4pjx45h7ty5httVV1djy5Yt+PDDD1FRUYEH\nHngAX3/9dcBt8/Pzcdlll4W5pi7t2rVDTk4OysvLNW3fQDzrO3XqhPT09KgfJ1p1JSIiovikMGK+\nSYhKx/yUKVOwevVqU/v8+uuv+PXXX4Ou79u3b8Q65keNGoVXX30VAPD9999j/PjxAbf77rvvAABZ\nWVkYMmRIoxwnWnWlxqc0IJYxzSoMY7bX+R477MI6gygWdeiCJOxrESMEhE8RMbWN5rhCWQ6HsCys\nd6rDPMym5FBvX6ddZxPKEiMMxGOp610nXkvhHIyurbg/oI380aQREl4PdapjqY+j+r1i13kNWX3r\nJHWUkFMGatzXKElnBJN4bn7XQp1GR3xdCBEfescRiWWJz5dehIjfOhOvIzH9jhFTkSoNqZeJwxhW\no/En8DFNeB9R6rSvebFhqx8daTbnUOxSQsxPyYgcEu3evRu333676f2mTZsWdF3//v0j1jEPAOed\ndx4+++wzLFu2DNXV1QFzsh89ehRr164FAJx//vmNdpxo1TWeJGIEfEPqYTF6XxbbQer2sbDOL+ue\nXlvGL0Wh0BZpyKh2v2j04CkO/ZoifichnKOq7d2g51C8DxHr7D2g51iS607NG+HuqrgnYFx2R6o7\nvJHzrv/t3v8tmjr7tQS9OeNdyzb3/55I+Ayru1vH/TQ53PeNSRbXT2aSq3yLKoJdfekcTl+EPAA4\nJd+E1A7hXskpRNBbhIh5RXWfJft1N+k/K+L9ribS2yB8PpzpCnUjzHUj4gPuEFq5CF+EfCjHovgg\no3EndqXoiMO77sg799xz0bJlSwDA66+/DjnAkLjdu3d7Z+i98sorkZKS0ijHiVZdiYiIKD55IuZD\n+Wnq2rdvj99//z1sPwsWLGjsU2pyrrvuOgCuvOz/7//9v4DbvPnmm3C4O96uvfbaRjtOtOpKRERE\n8UdWJDhD/KH4FZWI+Z9++ilgh3FDRLJzOSkpCU8//TTuuusurF69Go8++iheeukl77eOpaWluOaa\na2C325GcnBx0KPNLL72EI0eOIC0tDVOmTInIccJVVyIiIkpMjJgPXXJyMk455ZTGrkbM6N+/P6qr\nq8NapsUS2bigyy+/HP3798fq1avx+OOPo3///jjjjDO867///nu88MILAFwR6EOHDvUrY/fu3Zg+\nfToAYPjw4bj44osjcpxwlBEP/HPKy0HXR/L7wcbKZa9IDbgPVgwi0+tqtcvqyHaz37aqQ47FUZ+1\nwnEaklJJjEb3G/2oemiTgq4D4B/Jri5bHI2bpI0K91Onigyv09ZRcQqvYXFAgSxBli3eyFbFfe0l\nd4S6wx0Rb3e6ns9a2fO/6/d1noh5Ice8Z/SxIuSg9ww2dQfCI9XmyVnvKrfKXd8ki4Qki4TsJP9Y\nfIcqf72nPh52xddNZFNFzwOAUxIj6LXXWVJFzIvv9n7vBeKIB4ivd/VIbXGNTnS9yGiErQ4zEfEB\n16qOpR8RD+jFzcZqBLxYL/E51WpIn2DTjB5RwDmgmoKodMwnJycbbxRjJk6ciP/+97/47LPP8Mor\nr+Drr7/GsGHDUFlZifnz56O0tBQA8NZbb6FLly4By3jvvfewZcsW5OTkBOyYD9dxwlFGbNJ5CxLe\n8MUGr/EHaONrSGoas9IlIZVNdY3vsZiCRByqKlLfUIuNYXFfm9Dwtuo0KMQUMXopYwBtqhSHwbX0\na7SryrYJDUCj9B3iOapvXGqEtDg1YlqN4NdWsjuhVLj2l5JV26nTumgaPkLjRPU8KurroTqmOq2H\nmOJD/SdjSVYtpCcBFe7XS6rqhkZsHIo3MFU6KZLEIaDJwnMg3kjKQmodTb0Nnq9wtmHNNIjNpLpp\nSEM7km30GL0BgN6wZuFvUK7RrncI0SThTJkQy5hjnupLkiSkpqY2djVMkSQJ//73vzF48GAUFxfj\nzDPPxAUXXIBOnTph8+bNWLRoERRFQbt27fDee+8FLGP//v2adDyBOubDcZxwlEFERESJSVEk7+TR\nlLii0jEfjyRJwscff4yePXti2rRp2LRpEzZt2uRd37ZtW0yfPr3BOTLDcZxo1ZWIiIjiDzvmqanp\n1q0bfv75Z9x+++1YsmSJ30S0o0ePxttvv43WrVs3+nGiVddY4hc1qwqwUYwixMN4XFP7moh6D2dk\nvs0vTFgoXRzRog5cMaiI3/fv2qTj2nU1Ndpl8Qs7vUAJv6AWIZBFb+4hMahHDHwQAzZqVedfVaVd\nl5UVvI4AUFWpKkcYIeAIfDE919CpWOBUJDicrro7xWq6O9Zq3BHzNe7tqtzLnngZT8S9BZ6Ie8+y\ne71wfJt7RbL7utS5nweLOxrek2M+3T2XlCeXPQDUqq5tklP7/Nmc6oh57UgDu9CFZBWWtTnmBX7z\nHuj/XWlG05iJrheZ7tcMvkMk88SbiYo3jr6vPzPvlfoR8iaPa6Ysg/kmEoWM0CPmE/MK1M/vv/+O\nzz77zO/3W7du1V0vbhct7JjXkZSUhClTpuDRRx/F4sWLsW/fPqSkpKB79+4488wzDYfiPvrooygu\nLjaMNGroccJVBhERESWi0FLZRHYIBlF0de3aFYsXL8bWrVuxcuVKlJSUoEWLFhg8eDA6duyou2+n\nTp3w8ssvAwBOP/30iB0nnGUQERFRYlE4B1S9zJo1C7Nmzar3+mhjx3wIMjMzcckll5je75ZbbonK\nccJdRizy+4bcoO8gmmliGoe5d+cMJUP7ixOq6BoxisXonV8dqWIVIhVswhdA4nq9J06ch0Iv/Yy4\nbHYOC/UXVWKd/KKHhGXx+qhTtNQK6VyE1DWKPXg9FQBytjuVjSqCRf1YNxWQqmh1KhvFroo0qfM9\ntldoy5IdvmVbiq/eSXkylOPueqlPXQxSqNGeu7NUWFYFHlmFFJ/WLDF1jfD3ro7isQivA8M3gwZE\nXoRrW6Bh/Z3hTCkTre9ojVJCRUq1kPe0Snvt7LLwupcMUnclCEbMU1PWvXt3dO/e3dQ+bdq0wcMP\nPxzx40SijFgktuP9c8yrH4cx+rIBud3N1sJUhGlD7lMqKjSLUpUYMa9qf4ntYzHaXHjTV1TLkpBC\nUhIi8xWb0I2gF4gmRJ9LtULEvE49JaHtKzbrxNzvkiqyX6qs1G4bvIau7StU2wvtCdkuXCtPZLv7\nNeaUJThkC6rdkeYW4WieVHo17lzu1e62bbXTE0kPdznuungi5d2n77kMnqvhKd3zlEnCdhb49rdI\nElKsrg3V2TJtmoEJ2utsVTUYLYq2TWcVIugdkvZ+Tx3JLl4H/799/fzkknr7MDb5jehFrkcyT3wk\no+DNEOsRqdSPRuWGMxo/XingHFBNQVg75seOHYuLLroIN954I2zih3UDrFu3Ds888wyeeuop9O/f\nP2zlEhERESW6UIfBJvpX2kb27t2LUaNGReVYHTp0wMKFC6NyrFCsXr0af/3rXzF58mT06dMnbOU6\nHA7MmjULCxYswJw5c8JWLhEREVGiU8DAGTPGjx+PQYMGha28cLaJ9YS1Y37Xrl249dZb8fzzz+Ph\nhx/GuHHj0KxZs3qVJcsylixZghkzZuDzzz+Hoih48sknw1ldIiIiooQX6sRRTX1yqbq6OmzZsiUq\nx3I4HMYbRZGiKJg7dy7mzZuHq666CpMmTcLw4cNN5btVKykpwaeffopp06Zhx44dDKwhDTFKUoYv\njLchg8Qa2ncRqah3RTKICtU7rrBKOn5c+4sqIfe7Kse8YmYULKDt/RFGgaJSGzEv+U2+7quHIjyJ\nkvh+VyPkbxej3tVzvFu10ceSOKLWLox8U0e6J2lzzEviKGHRCd/2SpU2Yl6pEzd2VdIzQNAhW+CU\nJW/OeMn9xHkiXT2DWWtlbaR8tfvSVHsi5t2XwvOa8ES+e6Lbgw2e9VwWz5X0vHdbJdePzf0atKpe\ni+qoaLFYi2rko0XI5S4ui9HV2mVx9LRwIEXWXa+oovUlo7+5MDZhIpUnviER8VIDRqMq4nWOqqYe\n9tEwSsjpKAkAevfujd69ezd2NUwLa8f8P//5T9x///1YuXIlJk6ciPvuuw8XX3wxrrjiCgwaNAhd\nunTR3b+8vBwrV67EDz/8gI8++gj79+8HAOTk5OCJJ56I2rcVRERERImCEfOhKSgowIwZM6JyrJyc\nnKgcJ1R9+vTBiy++iOeffx5z5szBnDlz0L59e1x33XUYOXIkTj/9dGRnZ+uWsWPHDqxYsQJffPEF\n5s+fj7o6V0/WwIED8fe//z0ap0FERESUMEJNR0nxLawd80OGDMEvv/yCjz76CE899RR2796Nzz//\nHJ9//jkAoEWLFjj55JORl5eH3NxcpKSkoKSkBCUlJdi7dy+2bNmiySOVkpKC2267Dc8++yxatGgR\nzqpSnBMjSyS/SJPG+lYxRt41hSiWNIuQ1Pt4ZdBtTV1KMdJGjBAQ1+ttK9ZD/ATSWxZzZJrJRydu\nanQ9xPUO37LsEOpRJ2yrCtTxO4wDcGS6f6nO8akKNAn2WKQOilCcgX9fVpam2afa7vs4SLH5dipM\nr4Rc7drRkhQ8wlOp0UYhVRZrX3N1db4Kp6Vqy0lL0e4rKUJEU61qWS/PPhDgdaS/uSl6gSqm8tM3\nuCb1O26DjxW9Q9WX+DqsqdY2c2rFHPNNpCuaOeZDk52djYkTJzZ2NRpFcnIyHnnkEdxyyy145pln\n8K9//Qt79+7F1KlTMXXqVEiShJ49e6Jdu3bIzc1Fbm4uamtrUVxcjJKSEmzcuBHFxcWaMjt37ozn\nnnsO1113Xb0j7ylRiHmlhWVVFK8cwZzC4Yxy9y87+PayqfsDg23LT2iXa+3CsqqN5TD5GaeKXFdq\nhBzz4rZCDnqo0thKFqHB5Nd2dugvq98vxHaf0ET0m7+pwhfa7lfnGr+wd60qXyS/UqE9P1mooqdN\nbXHnbne4c8xX2LXn7qmd0z0irc79C09zxfe/qxy7O/RdfOas3gh4XyQ84LtUnkvsCDAvm/pyqstV\ngjwWidfRL0JeiOSWVFHu4t+RpNQ/gl5RxIa4LGwael50c5Hr9Y+QNzpWQ6LgzRCPE9kIer051Yze\nC83cwzeNRisnf20awj75qyRJuOGGG3Ddddfh66+/xowZM7Bw4ULIsoxjx45h6dKlhmV07doVd955\nJ2655Rbk5eWFu4pERERETYaC0G512O6n/Px8vPnmm5g8eTLee+89vP3229i1axcURcGmTZuwadMm\n3f2tVisuuugiTJw4ERdccAEsYgcdEREREYWEqWyahrB3zHtYLBZccskluOSSS3DkyBH8+OOPWLp0\nKVavXo2ioiIcPXoUdXV1aNGiBfLz89GtWzcMGzYMw4YNQ69evRhZQ0RERETUCPLz8/Hoo4/ikUce\nwfr1673t+O3bt+Po0aM4duwYUlNTkZ+fj5YtW6J///7edjyDasiY9mtApzrCMoq3gGZyyhtHvYcn\nP71RnZSSSuEX4ujM4CNKDanzt9eIo0CFUHWb8KWbapSsJOSFD5DAPPQ6GWwrjpSDOoJezD+fLETM\ni6NXVeforNA+R866wF8yWm2yuyhX51mFQ9IU7Y2Ydz+wK9qq1cnaSPk69/Npl53u/T256j055131\nsHkj513LfoHn7nKSJCBJUrwvBadqLhn1pXIIrxVZMfM3aWbUqDhiOnx/8Gb+no0F/1K5IRHy8ULv\nWpoamd7gshgywoj5piFiHfNqBQUFGDt2LMaOHRuNw1FTJL6px+PnYQSHY6UIjVpnqW+opl/bwuja\n6TVGwnkORl/OqY8lNqzFaoj3P6oNFGEkrmwwL5Rf+0CdNkZoXMpOYUilKo2GX/olCyDbJbF6sKgW\nNE1EMYtQCGluklr4VrTqLNxwVahu9NJUHw2OZFirkgEAcqXqYol/csJQ45yThAZtsmo5W8itLAy1\ndmwt1Syrhw9bhHMTR2L6PfdmxuaKq01kYjIU1vQ1YSwrHo4r0EwKJ2YuEubAq67VplSqEV4v6gkH\nw3tDF1tkSJBDuPmVY+VJppghSRJOPfVUnHrqqbj33nsbuzoUp/Qme3WtV3WICvtaDN6XzKWJMaLT\ngWQmDY5R57pfah8TXxCUaD/oxPaXOvWL3zoDms9UoW2miGlxdFJfSkKnvZQk1CNZaMwlCZOJqu9b\nhHsYv1SQQl+7U5VWUrIKqRKt+o189T2BvUp7XHudMAGqxXU9rO7MkG1bHEfbvHIkWTIBALI77Yqn\nQ83hTWXj+n2NUzsJrGfS2Ep3m7fS4VqudrjqXOO+QVG8HfWSu3x3h727cZTsHqWUm+T6Pz/FifwU\np/e41ap7k1rVFzF1QoNa3flsU7RdRlZJuyxOBqt+fZtJLxOItuO2/n83fuX6pcUV/1bUx4r/kV9G\nqWsM37N07/FNvDca3Kjpv88mbjtdT6jzRBHw/vvvY+7cuVE51i233ILLLrssbOVFpWOeiIiM7T/g\nmvBa/emr7oiWklSd9OK7d7A2o6osa6WrsDbFOyC1yNBsphRX+Y6TneJbUecEcjoZVd1Pm/JdmmUp\nI9m3kCV0zDtddyH7ra1NH4eIjDGVDRERUWTN//prFJV4OuY9HeeudQ53R32dO0jHv2Pe9b+nY77K\n/QVDldgxX+yady/F3TludXco29yR82k2V1u/MM31vy3fDghTjYXCUlzgWxCimGot5ZrlCtQiM88g\nfz8R1YsCyS/4jwLbsGED5s2bF5VjnXXWWWEtjx3zRERERAks1GGwTWQeLSKKMjFKUhYmeZcl37L/\n9I760apmItmN6KZcaEDEvNG++sfVrqsr0XbQWJO16y1pqiCOFP3Idb/3fFVuE1lIZeMURqQ564IP\nufVMiOqtY4r2/K2ZQnS2NlYEijqiXhyiKHyYOaq0q+21QYaNBihKpA4qdji15dTZhah+d1nOo66e\n9LRsV+d165bHtWW6O9wd7lQ4dnc5nhF9J+yu/4/bXd0ySRZPahrXfk53h77T/WRlWFMBAKnudEGe\neniWmyW7ftEq3fX7crsV1RYLimrcXwCoRj54Ov0BwK5oZ7fNUg2/TRGH4gov5xOWYkghRpX7R9BD\nWA4+NNnv7yqsI7XFRfUvhEh9YRJaMbWNcTS+uqzQ31fCOYFrJCPkG/Q8KeJ7JxumCkKPmG/qV+vs\ns8+GQ5xMPEL69+8f1vLYMU9xwi8Xic4SICXgu1JDPpiswge5QxXoIAmNZ+PJ4VVpYMRRrX5Pk9iY\n1ilWTEcpCRsHb2f7E4e56tSrptImbCukoxHOwaL34hLXialtVGWLpVit6mGfquNZfFtaVY1pvxsx\nVTS9pn2oKcy9YLVAGdpXW/VkVTiN+qbnmxXe/eRq3+9l4TNPXU8AkHrla5aV/n18j5OStdvO/sb1\nIMcVSV96KFWz3qoqOyVVG7Ujy8ILx8yfiV8j3Gj74IVLDXjTieqUKjEYcOGX1skEcTIkp137eqio\n04aJiSlynVJ0Gm+NLdRhsBwqS0REREQUG2TmmA/ZpZdeiksvvbSxq1Ev7JgnIiIiSmCKElo0PCPm\niYiIiIhiB5vniY8d80REREQJTIYU0sSunPyViCJBTPUgpnZQp8EINSVGfbdXE1PM6KWckPwmuAw9\n1YO4r389gpdlEc7Pb8RkCrTLyarJX4VUNrAKKTjEg6kncHVqh5hZ/IZUibOvq0ZuCjnNLdqBkJDS\nbMKysEOaamRlstBdIQx9qzyuPYtqu68spzhyVVgWRyyqR/CJo/nssvj8u1jcKWms1dqTdMqeVDTu\nVDbu9Cd2WTsJbK0cOMd8jdN1hDr3/w738N8K2TVytNT9/Djd0yUnubt10mtc9TlcbfPuX5OroNY9\n1FUzv68qpZTeJMriBMzWAJO9hprqySIZdT+JE0WrVwmjc4XR1Q0ZXa73t2/EMFVLmJpWiqI/ebG5\nssxeq+DPr7nUNexiNssVMc/2eaJjxzzFCbHRrd/Aj25uiAgRGx8N+FS3CLsm56l+YRVzyAg7611L\n8YPXL1GgXtoXgzwiRuvre1wA1ft964+eSNfdVrx24sHU662SuE7biHGo0q6IKTjUVXaocheqh64l\nqe6K0pO0KTiSbb7Gmjotjjr1TprFtY/9YC2Sf/wNwUg23/EdRdWQJdeETvYTvjrLQsofRUgpU7dk\nm7Z+J6p95adob8COLXPdZFT0cJ1DUVWmZr1NdQ4trRWadZn52tQ2ZoT1baL+/QLGEuH9LGKEm4Fa\n7d9Fdq12MrJUq7YHw6b4bv4b8h4b6xgxT0REREQUXxTw64ymgB3zRERERAmMOeaJiIiIiOKLwhzz\nTQI75ilsvv9+EcI5s6B65nFJ0kY5WoRxm+IwVnHW8njUkJnWRfn5J2mWW5+8y7dgE66d3+CE0CPm\n/aqs9ykihKIbHtc/dD34cQzCPrejs+56ih+t9m8z3iiIsL5NRPAtR9J77Yf1QNE5TCQ5TwhDz7fm\naJaP7SnQLP98ZKf38ZYTizXrHI5SzXJDhkg3dqxLqBNHseFP1HQVFRUhXB8EYjs9NVn7IZmbKkwQ\nL/lGL1qhHVVnlKom1BQacUvWXqvLBycL64U3bofveijO4OsAg3a72E63CctJwv1DqqpbIdUgVY0w\nchLpQj6eLNVo1kLt+de+sxQLjlV6l3ceb6FZrx69KqaysSvBR6sCQIrF94tUq/biGO3rUedNVSNp\n9nO6i/OU6inNU0ydO5VNrfs5s3u3D3wgTwqbKqnKtZ17lO5xxXXtj9W50s2USyVIU6q8KWRsii8N\njUXyPVb/HgCSdBrJmRbtazADzZEC34jWOvieH1nRjmRU/72WFstIsWhHyYrpWpywq9ZpnxNZ+NsX\n91UfS9xXgX5aGPX2/vfk2n3FeuiVZaQh6WrC+V4Yzn4IU+cvnIMs+0a+OpyV2m2V2nofx5xGbsOD\ngTNNATvmKU6IH7xC7kah8RC5N+bwMfryIJzndKC6RvsLdWe8Q/wA1C9LXS1JuNHya6QnCzk11Y18\ns52NfjcTqg9J8aZELFvIR3mgONv7eF+VtnGpbpQDQJKwbBWKVt8A2IRUNilCo77K6bseYoNeXW65\n3bddtarq6qetRbL2nNKsvoavOuWNJr2O5HodlO9JRrajXLO/uh1oTVPV+ZAFte7qVFT4bpwURf/1\nW31EeP2uKPKdR6H2hiyzpTuVTY6rEuWHta8bT95NAKhVsjXremRrnxBLhnBc9VPgEL9IMmhoxerb\nSIS+BIjaFwBhJD6HYupSq5AUV7x0surmKpE7d0IdBst+eSIiIiKi2MFUk4mPHfNERERECYwR80RE\nRERE8UWGBDkRhjWTLnbMExERESUwTv5KRFElppwQ0lnUKdWa5RrJlwbDKglpTuKEUcodNQusxhu5\nVUnaa+U8rB0F66zQvnHXnfDVo6ZCe6tfV6dNGeN0autsVY30TE7WPmepmdrl5CztsjXLl3LEki5c\nC5NpM6V032tAKj6uWVd50IbaKl8BNmFka7KkSkEidGbZDFPZ+PatlbWVVI9mBXyDKj0jU3OTXCPw\nrFbFvd61veT+xtt7qd1V8JRW405540lZY/QFeZ3ius5lljIAQCVcafc8o/5s/7+9+46Pouj/AP65\nSy+QAIHQi4BU6VVAkCIoKFWaFKWIjQcFFHksz49HRR4pdiyAikgRFJAiUlQElN5rAKWGAAlppCd3\n8/vjcpvdvZ5cz+fNKy/uMrOzszuXu9m52e8UhpGK0htC/IQiAkEoQB4MrxshC18jf80KKO8gvqkr\nOu86jfIu3UoaZZjAJoG1kK1NKNpWVm427iry6lH0ugnRBiAIYYp0oVG+dwTK7mzUq9LUdzrqRL4q\nXXZXpI0wOHqTbWWvI9Xxq8tSvQSthraxFm7HXNn2ppkry5k8FY3AF6IguJq9fXjybW4JxD19+nSs\nXr0aeXl5tjMTERERkdMIFMWotPbDfj+pnT17FlOmTMGJEyc8XRUiIiKiUsXePjy/wvBtbpkxv3Pn\nTsyfPx8VKlTAqFGjMGHCBDRt2tQduyZfpvhqUP0NufJbbZ98I3LjCMhNTaLi+flfixba0ZvMHrF+\nq5RGFrNcHb85QBVj3SRdNqVAo55eYIPQ2/89YlCQchZPmXLK10uZCkVfElbQKWfAhGgs1xkAAlXp\n8njuwaqY8reyQxXPk3Itz5CqFlpUx6phRfVPzy96mw60Es9enk8eKlzeJtlphjyJCTG48Y9y1lR6\nQVHdooOKZnPEhuZBX94wMyZHNrNKfUtdgOoFffVsDcXz27lFs5/uiVDO9uoxzjArJzDScL7a6pSv\n1yvXo6XHoQHKmSbJ55UzfDJVawbkydpXp3oN6fSOvfY9dRuh1k1vFhqN7w3LqtssR/X3fCkjXPH8\nompx2HRxU1aWeraU750PSxjKhoorMzMTH330ET766CO0adMGEyZMwIgRI1C2bFnbGxMRERFRsdnb\nhyff5paB+apVq+Lw4cO4c+cOPvzwQ3z44Ydo164dJkyYgOHDh6NMmTLuqAYREQAg8sQV6fGNVOXt\nmFAN/Kq/XAhWpcsHisNUXwjcqt/AsYodvgEACAwsKjM/p2gAXVEX4+PWVR3bBwBd62oIyVO+/ZeR\nDVrLF63Vq47JXoFtqyjLlw38I1g5ABofWQ4AUC3D0C7Zl5W3LV8/XnSMoaptUb5Y1SMqVbj4KxVX\nmTJlEBkZiYyMDBw6dAiHDh3C1KlT8fjjj2P8+PHo0qWLp6tIRKVMr/CisYPg/MqKtHBZv1w9+ShH\nNUFDPdgVKet/71dNarJHs4LK0mSx5MJ+dl7hJJD8wgRj1J7Awv9PByXAIRWSAAAh2ixDeTBMNjKG\nMTFOlAkSqYbnqjAs9gqokCw91qgmJeVrlBNssrVahKUU9ftzC4ryZyBXkbeAPQ0ih+gFoLPzz4Z/\nXb7LLQPzGzZswJ9//olFixZhzZo1yMrKwoEDB3DgwAG89NJLePzxxzFhwgR06tTJHdUhIiIiKjU4\nY56Kq0GDBkhISMCqVauwaNEiHDhwAFlZWVi6dCmWLl2Ke++9F+PHj8fYsWMRGxvr6eqSl1DfcaTT\nKQfycgpSlfllg6m+EmNeYxIo3UpeB2LKq+m1yoHVk3urK57n6JSX8xmyOyizVDHks1V3lRWo3vPl\nuUNVd4GGq55HBConboTLnocGKuscqJrUYhpiXlkRreLu3DRlWYHKOyMrh6peW7JjzFcNxAdrrd9j\nnSKbtHJdfV5VJ0svlDHhs0MDgaxgNC5rGCgPLdxXiFYVP7/wbyOxcF/phfNNcnXGOhfGpFcFldYU\njugXQHneAwtjwxsH5o3rF+RrDAUHFJ7tACmf7IsL2eMsjXJSTB6ypMfq2OV3obwjuIquGgryiybO\nVEZF6XGIKm+WbD0JAMiCsn3l9QMAnex41fHZdao76K3FkbcV290kxrzQm32sLtdcurV9mea1P268\nzbwlisfuHfEHTM6Pol7eUUd3E3Agxjz78T7LbYu/durUCZ06dcKHH36I5cuXY9GiRTh27BgyMzPx\nzTff4JtvvkHDhg0xfvx4jBkzBpUqVXJX1cgHqDv4GpMPRNUsWlJIw03F84OJbaTH6k65IwJVkT1M\nQtmYdLQtpzlKvqCTRvX6CFKFn4m8rewgVY0s6hTWiMhSpKk/+EzD8yifhwcXhcVJzFSGzbiapXyL\nzZb1pU27FkFISTcsgNQqOlP6bQVZ+fKwORcLQ3SEFc5Ezyowf4Eo/4Y9W1d0zrJVDS/Pp5VdbIYG\nFF0ABVm5BlXPSspUlS+bPIMrUF50B+8zJF49EgEAaNlceXHQoPKdonJVoWqOxys/K+4WKC8682QX\nZfmq0DXq176tV6T6GN1F6wMhZtRnxlM1zlW1cUK28kUbn6X8e8/WpUqPhSje3SG+QEBjsgiepXxE\napGRkZgwYQImTJiAEydOYNGiRVi+fDlSUlJw/vx5zJgxA6+99hr69euH8ePH4+GHH0ZAQPEHIomI\niIioKMY8+Te3LP4qFxUVheeeew5Hjx7FoUOHMGnSJCmUzblz5/Dyyy+jevXqGDRoEH7++WfodMW7\n/YqIiIiIimbM2/NDZE2zZs3w8ccf48aNG1i2bBkeeOABAEBBQQHWr1+PRx99FDVr1sRrr72Gv//+\n28O1JSIiIvJd7MOXDm4fmJdr3bo1Pv/8cyQkJGDJkiXo0KEDACA/Px/r1q1D3759UatWLbz++uu4\nevWqJ6tKRERE5JPYqSdnCw0NxahRo/DHH3/g3LlzmD59OipWNIQvuHHjBmbPno369evjwQcfxIoV\nK5CXl2ejRCIiIiJSE3b+kO9yWygbayIiIjBu3Dj06dMH06ZNw6pVq6S0+Ph4vPPOO5gzZw4ef/xx\nzJ49G3Xq1PFgbYmIiIh8Bxd/JVdq0KAB5s6di169emH8+PG4fv06AEAIgZ07d2Lnzp2YOnUqZsyY\ngcmTJyMw0CsuP8il1PGblaHC8gsyYYnWs/PGJI7EkC/pttZi0KvPx6HkJorn6hBu8rCJWTplWp7q\n29d8VXwEecjJQI3y7zQ0QBXKMTBEmS4L9ajOG2Qj9KUj1CEdckzi6Gtkacq8uaqN1SEOU/KK6pUY\npty4QBXrUooxX/hclx2AjDQ9dMIYy91QtjHcpvHcGveYkG34PzVMX1heYbkwxq5X/q8p3DK4sPwg\nEVS4H6H430hI/xv3bzgevey1mY+iL0z1sBylQB33O1co48Tf0t5CpmwtgCh9TFFe1UKxuRplSEF1\nbHedKoa+TpZuEn9e9b7iUGx3VVnWYr+XJKa8Or/1GOqmrG1ryv6AJyWLR198to7XJD/DFXPiTCnh\n8Z6xTqfD5s2bsXjxYpPQNffffz8iIyOxY8cO6HQ6rFq1Chs3bsTPP/8s3TpLpYXqTdwk1rOHIm+V\noNPuTln6VMXzM+lF9Va/z9t645d32tWtEKDRWMxrSLecpo4Tr2Yt9rF62wBV1hDV9c65u8qFiORs\ntahJ2bILkWuqeNYByvW5FJ16vaqDXyC0uFwYWj1fH2F2f/IY77dzDAlVcgwHlycLEi8vWd6eOsX+\nYZE8LUP2p2Wp3MLfWCwDKFrMCgDy9MoO7Ok0Q3vcumkIa5alihOfml8Ukz49X3mOU1TPs1RhwvNk\nF13qhbTUK9w70umxexEeMzQOh/F2Xtxv9d+dL7LWTupBhmTVVfltpCie5+lkg0MeukhxBy7+Sq5y\n69YtLF26FIsXL8aFCxek30dERODRRx/Fvn37cPnyZdy6dQtTp07F2rVrsWPHDoSEhFgplYiIiIjs\nXSeKfJvHRhUvXbqE119/HTVr1kT//v2xceNG6HQ6REVF4YUXXsDJkyfx559/YuvWrbh8+TLeeOMN\nlClTBpmZmXjmmWc8VW0iIiIiHyPs+sc582QPvV6PLVu2YPDgwahevTpmzJghDco3b94cCxcuREJC\nAlauXIl//vkHO3bswMMPPwwA2LNnDz7//HNPVp+IiIjIJwiGoywV3DpjPi8vD+vWrcPixYvx66+/\nQsimHLZr1w7PPPMMhg0bhvDwcMV2NWrUwH//+18MHDgQbdu2xdmzZ5GQkIAqVaq4s/pEREREPocz\n5skZrl69iq+++gpfffUVrl27Jv0+PDwcQ4cOxTPPPIP27dsrttFoNOjRowd69OiB559/HgsXLsRv\nv/2GKVOmuLv6RERERD5FD/bPSwO3DMyfPXsWixYtwrJly5CUlCT9vkyZMnjiiScwadIktGjRwmY5\nLVu2RP369XHu3DkOzBMRERHZgTHmqbgKCgqwYcMGLF68GFu3boVeXxTyqUmTJpg0aRJGjx6N6Oho\nm2UNHTpUmk1Pfk4V700dJ1inV8adloeVLklsd2dyPE68/fk1Gssx5W3V43y6MqSBOoRbjixOX45O\nFRtc9VwdN13+NEgV+y5Yq6xHaKAyPUQWezFEtW2g6tTYCn0ppx6QUoclLDA5fvljoUpTZs5Tpafp\nimKu5wcpF6zWqEJJGJ9pCo9FQAudEEjKUe5LqPKHFp6n9DxDelawTpHPSB0zPqCwhCBtgCqf8v+i\n2PfKGPXawjCwOtlx6DRF50OrWudAfrzquOA6fa7ieTZSkVZQdOL1AZbj1TsSU16d3zTWuwOx3R2I\nKa/eV0liypvWw/6Y8uaeKzlWltW8bgoLXKLY9n4cctIW9s/9n1sG5kePHo3Dhw9Lz1u3bo1JkyZh\nxIgRiIyMdKisiAhD7GX5hQH5J3mHRN0ZUndWPEZY7niYoz4Od8krSFc8v5Yh6zyp8goHgmdrVB1r\ndfx1rboTazXGvK1zY3+9rMW2B5QXG7bifasvs9T55WXdzlaezer5yteHXnYM6vNcoAeSClfsSss1\nHxc9THZlY7xQCSlcySrfwlfp8uqGBBRtrz4nim0spMkvftR/g+r201pZ2Eun2vZugeH57RzD/yfS\nwhTpKXlFZWcWqC+ylGXnFKjPa1Gl1RdzJXnt+wr136gvKEk7qAcZUguUF48p2luK5/myGPNe87ni\nApwxT8V17NgxDB48WHoeGhqKIUOG4JlnnkGnTp0cKot9eCIiIiL7MUxN6eC2UDYREREYMWIEJk2a\nhDZt2hS7nBUrViArKwsNGjRwYu2IiIiI/JMQ9i1Y7IffTZGTNGzYEE8//TTGjh2L8uXLF6uMJk2a\n4OjRoyYhK4mIiIjIVNE6UOTP3DIwP2vWLHTp0gVly5YtcVn33nuvE2pEREREVDroYeuG56J8RHLV\nqlXD77//jm7dupW4rLCwMLtCV5IfEspwFXrVcyhC27gvlE1JwuY4sq1jYW6UeQt0ysv165nKc6e+\nYzJXX3QrYZ7qzt5sKMOz5GuUYUPktHpVqBoRrHgenBekeB6mKapnoOrW1RBVGBx1KBtrN/epvzDW\nQ31npPr4iz7JcvTK488RyuPP1Sifp2tSpcdh2kxFWiCUxxsoDMcbJAy/z9XpIQp0SMkzlJkqsgz1\n1yg/WUNFqKH8wvOlizCk6wo/gaUQNBqd4nmAMISaqRho+GIzojCUUHZhOB7j68B4d6j0f+H2xhtZ\nNcLCyVbfySx7HapDL2k1ytek+u85RxTdqa218drXQfkatBZSRh0GxyTsi5VwNdbKNUe5bfFD19ji\nWGgX7whdU6JwNDZZDzlUGgkHZsxz+N53uWVgvm/fvu7YDfkzda9M46k36ZJdLHjq2848nbJzmZCX\nJT1WfzCrO7zWmISqUZ0fdXqArJOnTnMmk/AzJmFWLO/bVr3Um8ovLtRhM8qKbIv1UNcpT69D9W6G\nWYj5sniLBbKLpkBRdFEQVPj2nZxv3GdRu8lbVCfr4EQLQ4iYs7/dRJVw5QVGrs58u1s6G7ZeJeoL\nRXkcT/Vf750AZYsdu6PcNl/295+nig+aL6w/18meF6g70jY6pY78LTiTK/82/I3JBbqqQ5+hvat4\nnqW/o9xeL78o99/Ov70LR7nzDCQnJ0Or1SIqKqpEIZfu3LmD8PBwhIWF2c5MDqtSpQrXdCIiskNe\n+ZtSSL2Awi8B1APzKOzLFxgHux3sakamGt6Py4UY+s5phbHqc6QBesNz4xcW+YWDysYBTnlMd53s\ni4lcjfJaMUf2uZyrGnjPV33BUaB3LLQrEdnP3nWiyLd5x+o6REREROQSxlA29vy4wt9//43PP/8c\nw4cPR506dRASEoIKFSqgXLlyKFOmDB566CGsWbPG7vL++usv9O/fH2FhYYiJiUF4eDjq1KmD119/\nHRkZGa45CCIiIiIiNzLOmLfnh3yX22LMExEREZH7eTqUzZQpU7B582bF78qVKwedTof09HRs374d\n27dvR9++fbFmzRqrs98/+ugjvPTSS9ICouXKlUNmZiYuX76Md955B6tWrcIff/yBatWquehoiIiI\niIhcT4BrQJUGHJgnIiIi8mPesPirRqNBr169MHHiRPTs2RPR0dEAgFOnTmHGjBn4+eefsXnzZkyY\nMAHLly83W8bWrVvx4osvQgiBzp07Y9GiRWjYsCHy8/OxdOlSTJ48GX///TceffRRHDx4EAEBAWbL\nISL3Uody1OuVof/k4T5KEvfdFnXIRUfe89T1sr6tY8egKFtVboEqnvftfGWYRHn4Q0AZNz5Xm6NI\ny4NqW42yHXSyGN7qcxWkDVU8DxbKL1BDRFF6UIEyXGIIlPHpA1Vlq8OZyUP6qUPWCdWJVx9/nux5\nnur41OcjR6O8wypHn1a0X1U88wCN6hgKnwdoDMeagcLPm8KqG1/T6vNojGsvHaMqkpteijVvCA8j\nxWAvzHcn17B9dHBo4f41heWp/saMsephmUYU1S0EyvaVx4ZXx9fP1yoX8M5VnUf568iRGPKGdMvx\n3B2JKa9+7khMeXU9bMWUt8WReO7eGlPddfViGCRb7J1cQ76NA/Pkm0xizrsrJrO3vC061uHX6ZWx\nAJO0idJjvY0PRGudCdOY8gE20rVmHwOAVrhxsa8S7EtdT+NiTABwV5umSKuhDVFuKzs/ASJQlVZU\nrqW1COQXGHlQXdTKttFpZPEjZZ1j4wzTq7o7QFYFxfY62d+UpYtN9WJd1uhUhRTIOnQ61fHdyVO+\nxtSx4OVx8tULlaljisuPHQD0GsudctP1FXyjc6j+O/N1zjzv6jbNhvJvMleXrnhusgChnxKw79PL\nVePyHTp0wH/+8x+0bdvWJK1p06bYsGEDevXqhd9//x0rVqzAzJkz0bRpU0U+vV6PqVOnQgiBmjVr\n4ueff0aZMmUAAEFBQZgwYQK0Wi3Gjx+Po0eP4ptvvsH48eNddERERERERK7lyOKvrpSbm4v9+/fj\n3LlzSEhIwJ07d1CmTBk0atQIPXv2ROXKlR0q6+eff8bx48eRmpqK2NhYdO3aFffff78Lj8C7cWCe\niIiIyI8JIUxmGVrK5wqvv/661fSAgADMmDEDv//+OwBg27ZtJgPzu3fvxpkzZwAAL7/8sjQoL/fk\nk0/irbfewuXLl/HFF19wYJ6IiIiIfJYr14CyR2pqKgYNGoS9e/ciJyfHbJ6goCA89dRTmDdvntn+\nuZzx7tibN2+apLVr1w7fffcd6tev75S6+xIOzBMRERH5MXsXhfLkjJzatWtLj2/dumWSvmHDBunx\nwIEDzZah1WoxYMAAfPDBBzh06BASEhJQpUoVp9eViIiIiMjV7L3r1VUyMjKkiTPBwcF44IEH0LFj\nR8TExODWrVv48ccfERcXhy+//BJHjx7F77//joiICLNlbd68Gf3794dOp0NsbCzGjBmDKlWq4Pjx\n41i1ahUOHDiAbt26Yd++fahRo4Y7D9PjODBPPkEd2kOjDsjnqa8R3RZCR83B2HaqcA0ZSJKVZD28\nhzrWn5xGY3/oGkO65RActmKKajWWt9VbqaOzqesRJIrC1WQiRZGWrVN+KGllcUIDNcpYjvLYlfIw\nN/LXuqVwNQCgE0XhiuShi+S/NzZHsiYBIQXKMDvy8uTxPOWvj5KEG9LJYn7Kw8sAQIHqWNSvQXl8\nygJVKBuTvEKdXvTasBVfUs2RmJCOUP+dkHWOxeZUvhfk6pVxT/N0mar8+fInjlfORwjYF6bGk2fg\nypUr0uPy5cubpB89ehQAUK1aNasLu7Zr1w6AYfb/sWPHODBP5BXU7+Pqvqb8s9t1n5HCgVBwpjHl\nrX8WKT/bbeR1oGx1OMo72jvKdFUMb3l/Lk9kKdLyVc8L9JZjzKsZY6kbBanijAdqivqVwao0eV8Z\nAAJUQxCBqvCO1vpJwkYfMl8W6lEdQ9/W8efoi8LdBRUoz3uAVhljPr/wfBj778Y+fkBhPHZj/914\nLOprV2NvRUix4HWFzwtjyxe2hRRyr/CaM6vw93fzDec0W2c4Hzk6XeEx6AqPtfD/wv63MRRkgSI8\nZNEx5qtCZMpfR/lCOUu2QKjCaZrEhZfFZy9BTHn19o7ElDe3L+vbWq+HNY7EX/fWGPLu4xthQ72J\np2fMA0BERASmTp2K559/HrGxsYq0WbNm4YUXXsAXX3yBgwcP4q233sKcOXNMyrh79y6efPJJ6HQ6\nNGzYEH/88QcqVaokpU+cOBE9evTAjRs38Oyzz2LTpk0uPy5vwtEBBxjjMztTXl4ecnJybP7k51vu\nKLmrrkREROR7jDPm7fnxlGXLlkmPu3TpYpIeFxcHAKhTp47VcuQz78+dO+ecyhFZUFBQYNePq8JE\nERERkf/SO/DjCuXLl8f58+fx3//+12RQHgACAwPxySef4J577gEAfPXVV2bHIj/99FMkJRkmh37+\n+eeKQXkA6NSpE6ZPnw7AMLP+0KFDzj4Ur8aBeRv++ecfPPfcc6hVqxZCQkIQHh6O5s2b491330V2\ndrbtAmxo1aoVwsLCbP489dRTHq8rERER+Z7iDMynpqYiJSXF4o8z/fnnn1i+fDkAw4x3c4s/JScn\nAwBiYmKsliVPd3Y9yfds2LABffv2RaVKlRAYGIjKlStj4MCB2LFjR4nL3rdvH4KCguz6+eOPPzxa\nVyIiIvJFQlorytaPK4SHh6Nq1apW8wQGBuKhhx4CACQmJpoNSfn9998DABo2bIiuXbuaLWfSpEnS\n49WrVxe3yj6JoWys2LBhA0aOHInMTMOt7xqNBgUFBThx4gROnDiBpUuXYvv27U6Jf6TVahEUFGQx\nPTg42GKau+tKREREvkMU/rMnn5Fx5ovFvE66ALh16xaGDRsGIQSCg4Px2WefmeTR6XTSglOhoaEm\n6XJhYWHS44yMDCs5yZ/p9XqMHz8e33zzjeL3t27dwvr167F+/XpMnToV8+fPd8r+AgKsh0jRWAl9\n6O66EhERkW/w9B2txVFQoAwxlpqaimPHjgEAHnzwQYvb1ahRA/Xr18eFCxekuPalBQfmLTh58iSG\nDx+O7Oxs1K1bF1988QUeeOABZGVlYdmyZZg+fTri4uLQr18/HDp0yOqguj1Gjx5t0iH31rqSTEkG\nJtwYn16vijGfpU+VHjsS288WdcxMdYxIeUx6dfx5W2U5EvzYkTrbijuurqdWFWMzWBNmMW+ARhlT\nU56uhTo+v2OvB3V++XN52UIW1954TrWaAKRr0xTb52iKBrCsxRi1RB1731rcf5PXmCreoDwePaB8\njerVMSFtxJuUt6+19RLId1iL+6luf50qfmyBThknVb3+hr/y1sVfs7Ky0L9/f8THxwMAFixYgFat\nWpnk02q10Gg0ds0Ikt8+q9XyxtDS6o033pD61aNGjcKbb76JOnXqIC4uDv/+97+xYcMGLFiwADVq\n1MCLL75Y4v3t3LkTnTt39om6uoPttaFU7+OyZNt9uJL8XSvLtra+kWmfwfqXL/LPJlvrJqmP0VpM\ndXUfPgPKGPMmfShZ/ny9Kqa6Kja4yWekKp69oo6qYwrUZqieF8WVz9Wo0jTqGPPKvnSAVvnckbV4\n1H1WvXxdInUMfVU8fnU7yOsZoLXeLze+xo3tbuzjCylWvIFxfS3130AglJPujOVoCodnpHWpCjcL\ngeH8ltUa6phVYNhPRuEAWE5hu+cWHqMxpryxT22MxS/vY8tj8JusVSA7r+o0veqcm25btA9HrzNt\n9eutpZnGr7e2rf0x5R2NC++qNaqodLJ3nShP27NnDwAgMjLSZH2n06dPS4+bNGlitZxGjRrhwoUL\nOHv2LIQQVic2+BMOzFswffp0ZGdno2zZsvjtt99Qs2ZNAEBUVBReeOEFREdHY/To0Thx4gS++OIL\nvPDCC6wrESn88etxxXP5wHyQxvKiWYGi6AJFfnEi7+ipF0GVL2glv/CSP44MUMZyI6LSwd6Fo+R5\n/vnnH0RHR7usTnl5eRg0aBD2798PAJg5cyaef/55s3k1Gg3CwsKQlZWFrKwss3mM5KH7IiMjnVdh\n8hmXLl3CvHnzAAADBw5UrF/QpEkTrFu3Dt27d8cff/yBN998E6NGjbIZIol1JSIiInfT6YECO7/r\nMXbj09PTrYZzLFeuXMkrJvPTTz/h1KlTAIABAwYgMFA5zHzt2jXpcfXq1a2WZYzwkZmZiTt37pSa\nPg+nEplx8eJFbNu2DQDw7LPPSgPdcqNGjULjxo0BGBYy8BRfqisRERG5n4CA3o4f+SzX6OholCtX\nzuJPSeh0OowcORJbt24FADz//POYPXu21W2MC07dvHnTar6EhASTbah0+fLLL5GXZ5j5++6775qk\na7VavP322wCAu3fv4ttvv3Vr/eR8qa5EpUlyUp7Vn5SkAqQkFSDtDpB2B7h7J9DsT8adYGTcCUZm\ncqjiJ/tOhOJHna7+yb1TFrl3ynr6tBCRBwg7/xk98MADKF++vMUfZ7p9+7Y0sSY0NBT/+c9/TPLc\nvXtXemxr0ow8vTSFpOSMeTPWr18vPX788cct5hsyZAj++9//4ty5c4iLi0ODBg3cUDslX6qrM9m8\nRdYX2Jq+6MTbdoTqlsO8gnTpsSO3/RnSi27902hsxVRVhYGRfRdo6zZfW+nW2D6G4t9iqK5XnrZo\npnuwVvlBE6Kxf7amfGZ7PopmhFoMtWPl5SMPtxMse1wgisJ4JIkkxTY6veXbTs2x1faOcOQ2V0du\ncbWVbiuMkafYCvPkjbzlXNoKZaNX36aveG35wo2ixVOcGfOuotfr8dRTT+HHH38EADz11FP4+OOP\nbW7XqFEjXLp0CX///bfVfPL0Ro0alayy5JN++uknAEDz5s0t9nc7d+6MqlWr4saNG1IMd0/wpbqW\niOrNRWhU/XhH+mVO7PI78p7nSLfc4fdSK2WrP9dyRJrVdHkIEnUYnHx9tjKvyWekrC9o43Ndp1WG\nYinQFn2+BqrS1KEdA7XK5xqh7FMGaOwPu6ruQ8rDquhUx68OwaJ+rpGFK1LXWX0+jHe0Gs9/jjBc\nWxmvE4zherQaQ3pA4d2wxmPTFYaWCRCG4ZhQEVm4XWEom8Lyg0Rw4f+G7VIKrxEK9LrCcnSK8vI0\neYr6Gs+H8U5b+XHYG65G3cczOY8m/faiNilp6BpH+vHOCl1juyzv6PNS6aCH98aYz8vLw5AhQxQh\nKevVq2eSz7hOFACbYbXla2vKt/N3vnf17waHDx8GAISEhKBFixYW83Xs2NFkm5JydEVlT9aViIiI\nvJ/egR9Xe/bZZ6VwHSNGjMDixYvtih/ZoUMHAEBycjLOnj1rMd+ff/4JwNDxb9mypRNqTL4kMzMT\n586dA1D0mrHEmH7kyBGnLWbsCF+qKxEREbmfcXKNPT9Gu3btQnJyssUfZ9Dr9Rg9ejR2794NAJg0\naRKeffZZs3nDw2VrkOTmms1jJB+Ml2/n7zgwb4axk1yrVi0EBFieFVqnTh2TbYprx44duOeeexAU\nFISgoCBUrVoVgwYNwrp16xQLmXlDXYmIiMh3GL/0t+fHlaZOnYovv/wSADBo0CB8++23di/QOnDg\nQOnx8uXLzebJzs6W7iTs3r07oqKiSlZh8jlxcXHS6/iee+6xmtfYN87MzFTEPy2OKVOmoGLFitBq\ntShbtixatGiBadOmWb3Dw1N1JSIiIt9gbzhKvezO37Jly7osHKXRM888g9WrVwMAhg8fjoULF1rM\nW7ZsURiu9PR0i/nU6fLt/B0H5s24c8ew2n3FihWt5qtUqWghReM2xRUfH49Lly5BCAGdToeEhASs\nW7cOgwYNQo8ePXD79m2P1TUlJcXiT2pqqkNlERERkXvphf0/rvLGG2/g/fffBwD069cPq1atMlkc\nypqmTZuiV69eAIAPP/wQ//zzj0meN998U1rsatq0aU6oNfmapKSiMG3yvq858jUIStqPP3LkCJKS\nkiCEwN27d3H8+HEsWLAAjRo1woIFCzxaV/bjiYiIfFNxZsy72tSpU7Fo0SIAwGOPPYZly5ZZnWgj\nn3xw9epVq2Ub08uVK4fo6OiSV9ZHMMa8GcZFBsLCwqzmk6fLFzRwRJMmTTBmzBh069YNtWvXRqVK\nlZCWlobdu3fj3XffxV9//YWdO3fikUcewZ9//omQEGW8O3fU1dkLRLiCrdjAfhGDvgQx59Wx8OQx\nJm3F8rMVg88ajeq7P3l8dpsx5p34vaG1Y3A0TqBJ3HxZzGqdVnlrVp5WuWCJtWOyVEd766eO0Wir\nLHXcTUUcdwsx5q3FlS/JmgBqjsSINEl3YluTdyhJu+lUMeXV8Xb9Oa68nHomjbV8rjB//nxpAcvW\nrVvjgw8+wK1btyzmDw8PN9v3+OCDD9ChQwfcvXsXXbp0wezZs9GxY0ekpqbiyy+/xJIlSwAAQ4cO\nlQbxqXSRLxTmSN+4OAuMBQYG4rHHHsOQIUPQsmVL1KpVC2FhYbh06RLWrVuH2bNnIy0tDdOmTUNw\ncDBeeOEFj9TVO/vx6r6mrH9oq8/uUDx6W30Ta2Upt7X1WaTsB9nqkyn7U1bL1ljuw5vbVh7/W93X\nU8eUN/mMlD23dbzyePQAoNcWyB4rY5AHalX1EMp6aFUx5TWKNamsr2lkLXa4SSx0vboe6r6w5Xaz\nFGPeWD8ptrwmUPHceGzG/43pRTHoC/8vLE8r/T6gMH/hc2H+tawvfH3oC19zxnrqhfK58dj0Fs6P\ntTjy1mLIy/dRlO68taGsrWFkeg1rf/vZKsveNFeX7S3k72++Umd/IeCeUJP2kk+06d27N1avXm1z\nok2jRo0QEBAAnU6HY8eOWc17/PhxAIYJOaUJB+atsHVLtzzdnvio5nz//fcmv4uKikK/fv3w8MMP\nY+zYsVi+fDkOHz6Mzz77DC+++KLH6kpERES+x9OLv3799dfS48OHD5tdGEpu2LBhWLVqlcnvGzdu\njPXr12P48OG4ceMGnnzySZM8/fv3x9KlS0tcZ/J9jvSNi6NNmzbS4q1y9evXxyuvvIKBAweiU6dO\nSExMxMyZMzF06FCLM+NdXVciIiLyPe4INWmvOXPmSBNtunXrhnXr1plMHDYnPDwcXbp0wc6dO/Hr\nr79Cp9OZDcN98uRJ3LhxAwDQp08f51bey5WagXmdTof8/HyzaQEBAYrVgSMjI5GSkmJzFeDs7KIZ\nC5GRkc6pqKpeCxcuxKZNm5CWlobvvvvOZGDeHXW1tkBEamqqzbiYRERE5DmenjFfuXJlh0JmVKhQ\nwWJa9+7dcfr0aSxatAjbtm1DfHw8wsPD0ahRIzzxxBN49NFHnVBj8jY6nc7ihWlAQIA06UTex/V0\nP75+/fqYPXs2Jk6ciIyMDKxbtw6TJk0yu0/244mIiEhNDwdCTbpw/P7jjz/GzJkzAQD3338/Nm7c\naPNuP7knnngCO3fuRHx8PFavXo0RI0aY5Pnggw8AGPp1w4YNc0q9fUWpGZj/7LPPMHnyZLNp/fv3\nlxYLAwzx2q9du2b1NmsAinRbMd6Lq2zZsnjwwQexfv16HDt2DHq9XhG/yR11ddYCEUREROR+np4x\nv2PHDqeWV7FiRfz73//Gv//9b6eWS96rdevW0u3Nahs3bkS/fv0AKPu4jvSNY2JinFBLUwMGDMDE\niRMBGO4WkXNXXdmPJyIi8k3Czsk1rvT1119jypQpAIC2bdtiy5YtDk8SePLJJzF37lycP38e//rX\nv9CgQQO0atVKSl+yZIl0h+348eNRt25d5x2ADyg1A/OBgYEWb7MIDg5WPG/YsCGOHDmCq1evIj8/\nXzGbXk6+8FjDhg2dV1kV422vOp0OGRkZitWJva2uRERE5F08PWOeqKQCAwPN3vYMQDFhpUGDBtBo\nNBBC4O+//7Za5qVLlwAYZqBXr17deZWViYmJgVarhV6vN7lrxNvqSkRERN7F3Qu7qp0+fRoTJ06U\n7lqsU6cOXnnlFavbTJ06Fffee6/id4GBgfjhhx/QuXNnJCUloV27dujevTuqVq2K48ePS7HnW7Zs\nifnz57vkWLxZqRmYf+aZZ/DMM8/Ylbddu3ZYsWIF8vLycOTIEbRv395svr/++kt63LZtW6fU05yE\nhAQAhhdzmTJlvLqu3kq+wJ9PLgRbYqqFowqy7M5rdcEaCwshWWJ9gVDLC8WWlPVFahxdTsVyPQs0\ngRbTzD23xJ5FdexfFFa+qKv5xwbOOw/mONKeJVlUiAsSeQvPtIPpInjqhd2UC85513JKriOEgN6O\nXr23xLAkUjt06JBd+cLDw9G4cWOcPn0a+/bts5p37969AAyz8V21/lJiYiL0esP7jHrmurfV1Vs4\nuii31X69rT6B1b6Jelvr/Rj554/tPo+1xWGVX0CpP8fydJkW92t4XlS2eluT5+oFXGXpQrVwqno/\nGtWCrUK2rXo/6kVmtVplf1m9+GuArD9t61xa6/epF3e1tRis8vht9ZPN94O1Jou/Gp8bF3M1PDee\nA01he6vzaaXFZbWKfCaE+qn1xVYtLaZqbUFXk9eYjcWNrV9vKJkuLGttoVQb+3VgoVhbHLn+Lem+\nrCsd/VSyzLD4q32fi67oxaekpECnK/rbW716tc1thg8fbjIwDwD33XcfDh48iEmTJmHnzp3Yvn27\nlBYcHIwxY8Zg/vz5Lgkv6O1KzcC8I/r37y/Fcl+1apXZwW4hBNasWQPAsGKwq261SE5Oxs6dOwEA\nrVq1MumMe1NdiYiIyPsI2DfYxWF58gcDBgzA6dOncfLkSZw5cwaNGzc2ybNr1y7cvHlTyu8qa9eu\nlR63bt3aq+tKRERE3sXTM+br1auHzz77zKFtzA3Ky9N+//13/PPPPzh+/DhSU1MRGxuLjh07lurQ\nexyYN6N27dp47LHHsGHDBnz55Zd47rnnUL9+fUWeL774AhcuXAAAKd6SWl5eHvR6PTQajV2rFavl\n5+djwoQJuHv3LgBDXCZX1ZWIiIj8kx72zbnivCzyB08//TTmzZuH3NxczJgxAxs3blSk63Q6aQGz\nqKgojBkzxmw5BQWG2bNarVYRLsde586dw+uvvw4AKFOmDAYOHOiyuhIREZH/sTccpatUrlzZ7sgj\njrjnnnu4+LyM82JF+Jm5c+eibNmyyMrKwoMPPogff/wRd+7cwdWrV/HOO+9IC8m2b98eTz31lNky\nmjVrhrCwMMTGxppNnzhxIgYPHoxvvvkG+/fvx5UrV5CRkYGrV69ixYoVaNeuHdatWwcA6NKli7R4\nlCvqSkRERP7J2Km354fI19WsWVMazN60aROGDh2KU6dOITMzE4cPH0bfvn2lEI+zZ89G+fLlTcrY\ns2cPgoKCEBQUZDaWakZGBho0aIBXXnkF27dvx9mzZ5GSkoLMzEycPn0ab7/9Ntq1a4ekpCQAhr66\nfLFXZ9aViIiI/JMxHKU9P+S7OGPegnvvvRfr1q3D448/jvj4eAwZMsQkT6tWrbBhwwaLi1HZkpGR\ngbVr1ypuczVn8ODBWLJkCQIDzTeXO+pKREREvklA2BU/3tHYzkTe6s0330RCQgK++OILrFmzRgrp\naKTRaPDqq6/iueeeK1b5Go0G58+fx9y5czF37lyL+cLDw7FgwQJMmjTJY3UlIiIi3yQK/5F/48C8\nFd27d8epU6fw0Ucf4eeff8a1a9cQEhKCe++9F8OGDcPEiRMRFBRkcfuQkBCEhIQgNDTUbPqSJUvw\nxBNP4JdffsHRo0eRkJCApKQkhIWFoXr16ujQoQNGjRqFjh07uryuRERE5J/snQ3PGfPkLzQaDT7/\n/HMMHDgQX375JQ4cOIDk5GTExMTg/vvvx3PPPYcuXbpY3d44mcXcpJaIiAhcvHgRW7ZswY4dO/D3\n338jISEBWVlZiI6ORqNGjdCjRw+MGzcOlStXdmldiYiIyD8ZFn8lf6cR9kyhIrIgJSVFdlttAACN\ntexeQeMDdbRJ49gxaKC8qNQGREiPTVeOV654b31leVsfE5ajZWk0tiJpuevuDp3tLFYV1dPWMWmK\nET1M2PlRbLmddHbkARz/yLdxrCbngnfr+LeS/h0Vj/XXNKB+XQuhqqfsuWtnowgYz1FycrJbFjeS\nfz53KvsCgjTmJwnI5Ysc/Jn+CQD31ZOIPMdd/XiTvrdJP7b40VVL1K+32Re1pgR1dmi/yv5TcGBZ\nq7nl/Ub1Z6Tp8wLFc73iufp6QJlXTaORz/dTXXdoAq3kBbRaVbrs3KrPla1zZ61foFcdg7XzYZJm\nZz/ZWPeieiqfG8+F8bn0v5QvQJkfjh1/cVk9bzaO3XZfTJ7Xen/R3vPs+H4du87xlno4cn3mUD1K\nMNTr+DFYY+P1IN+X+u/XoTGLknB/Hx4whLq7du0aWkeMQPmgmnZt81vq+9AhD8eOHUPz5s1dXENy\nJs6YJyIiIvJjxgjy9uQjIiIiIiLPszccpTE3+SYOzBMRERH5MYayISIiIiLyLcLOPjz5Ng7MExER\nEfkxezv1XFyKiIiIiMg72Du5hnwbB+aJiIiI/Ji+8J89+YiIiIiIyBsIhposBTgwT0REROTHBPQQ\nGjtizLts4SwiIiIiInIEZ8yXDhyYJyIiIvJjjDFPRERERORbHIkxz1687+LAPBEREZEfMwzM2xPK\nhl16IiIiIiJvYG8fnnwbB+bJL2mg8XQVXEuoBk801o9XvaCfXp8rf2ZjX8p0xxYH1FkuVn0IttpM\no3Vgvw5wYugG4VAdi3M8dtbVwjFZbzvZNurGMcfWa05YPj6PtTW5j4dCoth8fxLK96TSstipKOzW\n25OPiKjUUH9WOdT/sPZ+ab0ca2HDNCZ1UH5u6fQ5Nupl/34de8+3/5jUXUS9SZ9fVQ9dgTJdcQ60\nVtIcY3renf+ZZzynxn1pCutv7FoLTYFqC0O6+rhMnhfzPJTkfBm5MsydM8suSR+mJPUo2TF4ar/k\nK+wNR0m+jQPzRERERH5Mr9FDb0en3p48RERERETkejroUWBlsiP5Bw7MExEREfkxfeE/e/IRERER\nEZE3ELyjtRTgwDwRERGRHxN2Dsyz409ERERE5B3sveuVfBsH5omIiIj8GGPMExERERH5FsHFX0sF\nDswTERER+TE9dNDYEZ9SzxiWRERERERewd5wlAbCdhbyShyYJyIiIvJjws74lIIdeiIiIiIir2Bv\nH558GwfmiYiIiPyYXqOHxo74lIxhSURERETkHQR0vKO1FODAPBEREZEfYygbIiIiIiLfwhnzpQMH\n5skvaKDxdBU8S9gIP6CeBSkK7C/aamgD531ImO5Fq8rgAwNGDtVRmbekr2H7QlA48UPd1mtOPcCn\nKTo+mzW1Wbb9Sv17Qwl4T1gTdkZLiou/EpFHaZz3Wezvn+tCWH8f1jvQhy+ZAMWzkjWhsk9o0s1T\nlS0/BxrV9YB6W41Gdb3gAFvn2hnUn6vGfRYdl77w98rtLB+XfcdbkvPij9zR1kWceH3spHqzf+e7\nhEZv9x2t3nLlRo7jwDwRERGRH9MLHTR2fHGo94UvQImIiIiISgHD0q/sn/s7DswTERER+THOmCci\nIiIi8i0MZVM6cGCeiIiIyI8ZBuZtz7Zhx5+IiIiIyDsIoeMdraUAB+aJiIiI/JgovBHWnnxERERE\nROR5js2YZ5R5X8WBeSIiIiI/xlA2RERERES+xd67Xsm3cWCeiIiIyI8JoYMQWrvyERERERGR59l7\n1yv5Ng7MExEREfkxQ4fedqeeHX8iIiIiIu/AxV9LBw7MExEREfkxAR0E7Jgxz1tliYiIiIi8guGu\nV/bP/R0H5olKIVGihUHc9Y1t6fpm2HKL2B5MM1XCc6fRFD0WnlhExpH6Wz8/JXutk/285O/VI69X\n7yeghxCMMU9E7qGBxkYO+/s2tsvyRur30uL05cwTIt9GjgCn7ctdrH4+2Wh+9baaEpxrV3wGGuun\n0SjrZWtfls6JvcdnqTukrgc5nz39Lafsx419NncdE5kShcFsyL9xYJ6IiIjIj+khYF8oG36xQURE\nRETkDbj4a+nAgXkiIiIiPyaEDsKOWae8VZaIiIiIyDvYe9cr+TYOzBMRERH5McNsG4ayISIiIiLy\nFY6FsuGdr76KA/NEREREfkwIOwfmOSOHiIiIiMgrcPHX0oED80RERER+TMDOUDaMYUlERERE5BVE\n4Zx58m8cmCciIiLyY5wxT0RERETkY4T9MeYZyMZ3cWCeiIiIyI8JYd9sGyHYpSciIiIi8gaGdaJ4\nR6u/48A8ERERkR8zLBtlTygbzpgnIiIiIvIGeqGDXl/g6WqQi3FgnnySxo4BhlJNY+v8cPCl2Jw1\no9RmGxl5uK3srqenuPL8aF1Ytqvwb5tMGW6BtWNgnqFsiMjD/LOP78h7q/W+h633aa/vtgGAzdmf\nAdIjhz+XXHT8Jf18dNbnq60v0DWakr1+ikPjk/1lz/CWCRCe6+9x5rejROH0GvJvHJgnIiIi8mNC\n2HchZG8+IiIiIiJyLeFAjHnyXRyYJyIiIvJjhhlaDGVDREREROQrDAPz9k6c4VpRvooD80RERER+\njKFsiIiIiIh8jZ4TZ0oBDswTERER+TEOzBMRERER+RYhBPvnpQAH5omIiIiIiIiIiIi8hABjzJcG\nHJgnIiIi8mMCArDjNljB2JRERERERF5BQDCUTSnAgXkiIiIiP2bvTBvOyCEiIiIi8hKCM+ZLAw7M\n25CXl4fjx4/jwIEDSEhIAAC0adMGAwYMcPq+bt++ja1bt+L69esICQlB/fr18dBDDyEkJMStZRAR\nEZH/4MA8lVaZmZk4fPgwjh49iuzsbADAmDFjULVqVafv6+zZszh48CCSk5MRExODjh07om7dum4v\ng4iIiPwDY8yXDhyYt2DevHn44YcfcOzYMeTm5irSxo8f79SB+ezsbMyYMQMLFy6ETqdTpJUrVw4f\nfPABxowZ4/IyyI8IVTgCje1F/9xOXceSsHV8ztyXs5S0Tt7Ypn6HnSDyF/a+lvmaJ993584dvPrq\nqzhw4ABOnz5t0i/u1q2bUwfmz58/jwkTJmD37t0mab1798aiRYtQo0YNl5dBTiAf/NBoPVQJ9fuw\nY/WQD+BoPHYMJaWzkhZgdUvfG8CydqyOMJwXTxy/I2E2fPc16X2897XurNc0GejB/rn/48C8BevX\nr8f+/fsRFBSE1q1bo3Xr1vjyyy+dvh+dTofBgwdjy5YtAIAOHTqga9euyMzMxLp16xAfH4+xY8ci\nNTUV//rXv1xWBhEREfknb5wxn5KSghs3biAiIgLVqlVDUFCQ2/ZN/i0xMRGLFy8GAISHh6NVq1YA\ngD179jh9X+fPn0fHjh2RnJyMwMBAPPLII6hTpw7i4uKwbds2bN26FR07dsT+/ftRrVo1l5VBRERE\n/scbZ8zrdDokJCQgNTUVsbGxqFixoqer5PP4laUFL7/8Mvbu3Yu7d+/i0KFD+PDDD12ynw8//FAa\nUP/vf/+LvXv3Ys6cOfj4448RFxeHBx98EAAwdepUnD171mVlEBERkX8S0Nv942rr169H+/btUb58\neTRt2hR16tRBhQoVMGHCBNy+fdvl+yf/FxMTgy+//BLHjh1Deno6du/ejWHDhjl9P0IIjBgxAsnJ\nyYiOjsbevXvx008/4YMPPsCWLVuwfft2hIaGIj4+Hk8++aTLyiAiIiL/5E19+MzMTLz88suoUqUK\natSogfvuuw+VKlVC48aNXTKJuTThwLwF/fv3R4cOHVwamz03NxezZ88GANx///144403FOkRERH4\n7rvvEBISAp1Oh//+978uKYOIiIj8lyhcOMqeH1d67bXXMHDgQBw4cADBwcFo1KgRqlSpgrt372LJ\nkiW47777EBcX59I6kP+LiYnBxIkT0bx5cwQEWA97URJr167FkSNHAADvvvsu2rRpo0jv3r07/v3v\nfwMAduzYgV27drmkDCIiIvJXwoE+vOvC9yYlJaF169aYN28eEhMTERMTg8aNGyM8PBxnz57FpEmT\nMHLkSAhvDCHsAzgw70Hbt2/HnTt3AADPP/+82TxVq1bFwIEDAQAbNmyQFq5yZhlERETkz/QwxPy0\n9eO6gfnVq1dLEwkee+wxXLt2DWfOnMGNGzewceNGREVF4fbt23j00UdN1vYh8kYrV64EAJQtWxZj\nx441m+fZZ59FYGCgIr+zyyAiIiJ/ZW8f3rWx/YcNG4a4uDgEBwdj8eLFuHXrFk6fPo2EhAQ888wz\nAAx9lDlz5ri0Hv6KA/MetGPHDulxjx49LObr2bMnACArKwt//vmn08sgIiIi/+XpGfP5+fl49dVX\nAQANGzbE6tWrUalSJSm9X79+UkzwCxcu4PPPP3dJPYicafv27QCAzp07IywszGyemJgYtGzZEgCw\nbds2l5RBRERE/snTfXgA2Lx5M3777TcAhtDZ48ePh1ZrGEouW7YsPvvsM2m88d1330VSUpLL6uKv\nODDvQadPnwYAVKpUCbGxsRbzNW3aVHp85swZp5dBRERE/kzvwI/z/fbbb7h06RIAYPr06WbDBA4Z\nMgQNGzYEACxZssQl9SBylqtXryI9PR0A0KxZM6t5mzdvDgC4dOkSsrKynFoGERER+TMBT/bhAUiT\nZ6KiojB58mSzeV577TUAwN27d7F69WqX1cVfBXq6AqXZ5cuXAQA1atSwmk+ebtzGmWXYkpKSYjEt\nOTlZ9sx98aQYucpBXnnCnFgpm0V55QkoGT88JKKSc/QPw11/SEX70etdvziT6e71ADR25HPN+di0\naZP0+NFHH7WY79FHH8W5c+dw8uRJXL16FTVr1nRJfYhKSt6XttUHr169OgDDQq+XL19G48aNnVaG\nPTzRjzcpyfYvvJC31LEk9fCWY3AmD3yGupSz2sjfzgvZ4up1gYrPiZ8l8n6pqo8qTPbjqvc7H+nD\nu0h+fj62bt0KwBChIzw83Gy+Bx54AFFRUUhLS8OmTZvw3HPPubOaPo8D8x509+5dAEBkZKTVfGXK\nlDHZxpll2FK+fHk7c3rrhwMREZF3SE9PR4UKFdy6T9OLl5Llc9Tx48cBALVq1VKEsFFr27atYhsO\nzJO3Ms50Bwy3cVsjT5f3wZ1Rhj18rR/vNUPJXlOR4uMafEREzuO5Przn3swvXLggrVEp76erabVa\ntG7dGr/99pvU7yf7MZSNBxlf4MHBwVbzyW/5Vi/c6owyiIiIyJ95NpTN+fPnAQC1a9e2mk+ebtyG\nyBvJ+9LmQjPJWeqDO6MMIiIi8meeDWUj74/b24+/ceMGMjIyXFIff8UZ8x4UFhaG9PR05OXlWc2X\nm5ur2MbZZdiivM1VqaCgAPHx8YiKikLZsmWlRSC8WWpqKu655x4AwD///IPo6GjPVojchm1ferHt\nSy9vaHu9Xi/NjrUVssI1hPJ2YDukpqZaTS9XrpzdZRlDadiauSsv01r4DSJPCw0NlR470geXb+eM\nMuzBfjz5C7Z96cW2L7083fae78M7vrBrenq61X50cfrwgGP9+NTUVJtRPahIqRmY379/PzZu3Gg2\nrXHjxhg5cqSba2S4LfXWrVs2b0mVp8tD0jirDFts/eFWrFjRofK8SXR0tENvTOQ/2PalF9u+9PJk\n27v71lelAoe3MF4EWWLvQH9BQYE06GhrQFE+cSAzM9Ou8ql0+Prrr3Hr1i2zaY8//jjq1q3r1vo4\nElpGPmtM3gd3Rhn2YD+e/BHbvvRi25denmp7z/bhHZ8J/8ADD1hNd2Syjrw/zn6865SagfmDBw/i\nnXfeMZvWv39/jwzM165dGxcuXMC1a9es5pOn16lTx+llEBEREblCQEAANBoNhBDQ6XRW88rTAwNL\nTReV7PDhhx9ajFnatGlTtw/M16pVS3psbx9co9EotnNGGUREROR/OnfujMTERIe327Fjh1PrIe+P\nsx/vOqXmbHXo0AFvvfWW2bQGDRq4uTYGTZo0wfbt25GYmIibN2+icuXKZvOdOHFCsY2zyyAiIiL/\nEhUVZTWEhTWpqalOC2uh0WgQHh6OzMxMZGVlWc0rT+ftryQ3btw43Lhxw2xavXr13Fwbw6B6ZGQk\nMjIycOrUKat5jek1a9ZUvK6dUQYRERH5nxUrVhRrO2eHgpT3OdiPd51SMzDfpk0btGnTxtPVUOjV\nqxc++OADAMD27dsxevRos/m2b98OAIiIiMD999/v9DKIiIjIv2i12mLf7uvs24SrVq2KCxcuWBxY\nNZKnV6lSxal1IN/2r3/9y9NVUNBoNOjevTs2bNiA3bt3Iy8vD8HBwSb5UlNTcfjwYQBAz549nV4G\nERERkZEr+vBG9vbjg4ODPRz+x/d4/wo/fqxnz55SXMdPP/3UbKyna9eu4aeffgIADBgwwCSukzPK\nICIiInKVRo0aAQAuXrxoNa7lhQsXpMeNGzd2eb2ISmLYsGEADLPTVq5caTbP4sWLpTUWjPmdXQYR\nERGRKxj78ICyn26OMb1+/foMZeMgDsy70IcffojXX3/dYmz74OBgvPHGGwAMi9MaHxulp6dj5MiR\nyMvLQ2BgIN58802XlEFERETkKsY79dLT0xWh9dR27doFwLC4VMuWLd1SNyJzrl+/jjlz5mDOnDn4\n/fffzeYZNmyY9AXS9OnTcfbsWUX6gQMHMGvWLABAp06d0KtXL5eUQUREROQKVapUkdao3L17t8V8\nqampOHnyJAAwQkcx8GsMCw4fPox169ZJz+ULGRw+fBivv/669DwkJMRkQBwAPvvsM8TFxSEqKgqv\nvfaa2f08//zz2LFjBzZs2IB33nkHmzdvRrdu3ZCZmYmffvoJt2/fBgB88sknuPfee11WBhEREZEr\nDBo0CK+++ioAYOnSpViwYIFJnrS0NOnuvt69eyMiIsKtdST/smzZMsTHx0vP9+7dq0jbuXOn9Lxt\n27bo0aOHYvvLly9j5syZAIBp06bhwQcfNNlHQEAAVqxYgS5duiApKQlt2rTB448/jjp16uDcuXNY\nu3Yt8vLyULFiRSxdutRsPZ1RBhEREZGrDBo0CPPnz8f+/fsRFxdndo3O5cuXS2OmgwYNcncVfZ5G\nWLunuBRbvHgxJk6caFfeiIgIZGRkmPy+YcOG0sB8amqqxe1zc3Px+uuv46OPPpJuVTWqVKkSPvro\nI5u3rjqjDCIiIiJXGDx4MNauXYuQkBDs27cPLVq0UKSPHz8eX331FQDgr7/+QseOHT1QS/IXHTp0\nwP79++3KO2XKFGm9JqM9e/agS5cuAAwD8/PmzbO4/dGjRzF27Fhppphc+/btsXTpUrMXsc4ug4iI\niMjZrl27hnvvvRc5OTno0aMHtmzZgqCgICk9Pj4eLVu2RGJiIlq0aIEjR45Ao9F4sMa+hwPzFhw7\ndgybNm2yK29wcDBeeeUVk99//vnnSEpKQmhoKKZPn26znJSUFOzYsQPXrl1DSEgI7r33Xjz44IMO\nxWdyRhlEREREznT58mW0a9cOiYmJiIqKwsyZM9GxY0ekpqZi0aJFUp/r2WefxcKFCz1cW/J1Cxcu\nxNWrV+3K27lzZ/Tr10/xuytXruCzzz4DADzwwAN45JFHbJazd+9eHDhwAMnJyYiJicH999+P1q1b\nO1RvZ5RBRERE5EwLFizAtGnTABhC1UyZMgVVq1bF8ePH8e677yI+Ph6hoaHYuXMn2rdv7+Ha+h4O\nzBMRERGRyx05cgSPP/44/vnnH7PpkyZNwqeffoqAgAA314yIiIiIiCx5++23MWvWLBQUFJikxcTE\nYNmyZejTp48Haub7ODBPRERERG6RmZmJ77//Htu2bUN8fDzCw8PRqFEjPPHEE2jbtq2nq0dERERE\nRGacO3cOy5Ytw7Fjx5CamorY2Fh07doVo0aNQoUKFTxdPZ/FgXkiIiIiIiIiIiIiIjfSeroCRERE\nRERERERERESlCQfmiYiIiIiIiIiIiIjciAPzRERERERERERERERuxIF5IiIiIiIiIiIiIiI34sA8\nEREREREREREREZEbBXq6AkTm6HQ6bNu2DVu2bMH169cRGhqKBg0aYNiwYWjYsKFX7cdddS0N8vPz\nceLECRw4cAAHDhxAQkICAKBPnz548cUXnbovvV6PHTt2YPPmzbh+/TpCQkJQv359DB06FE2aNHFb\nGQTk5uZi//792Lt3L65fv46EhATo9XpUrlwZHTp0wKBBgxAZGem0/en1evz666/YvHkzrl27huDg\nYKndmjZt6rYyyODKlSv49ddfERcXh4SEBKSmpqJMmTJo2LAhHnroIbRv395p+xJC4Pfff8emTZtw\n9epVBAYGol69enj88cfRvHlzt5VBROTPUlJS8MMPP+D48eNITU1FbGwsunbtij59+iA4ONir9uOu\nupYGmZmZOHz4MA4cOIBjx44hJycHADBv3jzUrl3bqftKT0/H2rVrcfjwYSQnJ6NSpUro1KkT+vXr\nh9DQULeVQYbzuGfPHpw8eRIJCQlITExEeHg46tWrh549e6J169ZO3V9mZibWr1+PAwcOICkpCTEx\nMWjfvj369++PiIgIt5VBBmfOnMHu3btx5coVJCQkoKCgADExMWjZsiUeffRRlCtXzmn7ysnJwcaN\nG/HXX3/h9u3bqFChAlq3bo1BgwahTJkybiuDyOkEkZf5559/RPv27QUAkx+tViumTZsmdDqdV+zH\nXXUtDcaPHy9CQ0PNnsvx48c7dV9Xr14VnTp1MrsvjUYjJk+eLPLz811eBgnx9ttvW2x3409UVJRY\ntGiRU/Z3/fp10aVLF4v7eu6550ReXp7LyyAh8vLyRL169ay2PQDRuXNncfHixRLvLyEhQXTv3t3i\nfiZMmCBycnJcXgYRkT9btmyZKFu2rNn3yAYNGojDhw97zX7cVVd/988//4hmzZqJgIAAs+fy6NGj\nTt3f2rVrRYUKFczuq3bt2mLPnj1uKYOE6NChg8V2N/5069ZN/P33307Z3y+//CIqV65sdj9Vq1YV\n27dvd0sZJMS2bdtElSpVrLZ9aGioePPNN50yHrJr1y5Rq1Yts/uJiYkR69evd0sZRK7AgXnyKklJ\nSdJATXBwsJgyZYr44YcfxNdffy26desmvXFOnjzZ4/txV11Li06dOomgoCDRsmVLMWnSJPH555+7\nZGA+NTVVNGrUSAAQgYGB4oUXXhBr1qwR33zzjejZs6e0z4kTJ7q0DDIYP3689GVG165dxezZs8Xq\n1avFjz/+KGbMmCHKlSsnnc8FCxaUaF9paWmiSZMmUrs999xzYs2aNWLp0qXioYcekvbz1FNPubQM\nMsjOzhYAxH333SeeffZZMW/ePLFy5UqxevVqMW/ePNGuXTvpfFauXFncvHmz2PvKyMgQLVq0EIDh\nS9Onn35arF69Wnz77bfikUcekfYzYsQIl5ZBROTPVqxYITQajQAg6tatK/73v/+Jb7/9VkybNk2U\nKVNGABDly5cXcXFxHt+Pu+paGhw9elQAEOHh4aJz585i6tSp4vHHH3fJwPymTZukgeAaNWqIt99+\nWyxbtkzMnDlT6jNGRkZa3aczyiAD43kMCwsT/fv3F/PnzxfLly8XH3/8sejdu7eiH3fp0qUS7Wvn\nzp0iODhYKu///u//xLJly8Sbb74pKlWqJACIkJAQsXv3bpeWQQZff/21CAgIEO3btxcvvPCCeO+9\n98SyZcvEJ598IiZPniyioqKcdi1/6NAhER4eLgCIChUqiNdee00sW7ZMvPXWW6JatWrSddmWLVtc\nWgaRq3BgnrzKs88+Kw3Sqd8U9Xq9GDNmjPQG/+eff3p0P+6qa2lx7tw5kZ2dLT03Dto5e2D+pZde\nkso19634xIkTpfTffvvNZWWQwcSJE8XIkSPFmTNnzKZfu3ZN1K5dW/oCrCSd+pdffllqlx9//NEk\n3fg3DUBs27bNZWWQgU6nE1euXLGa57333pPO55QpU4q9rzfeeEMqZ/ny5Sbp8r/pDRs2uKwMIiJ/\nlZSUJA3EtGrVSqSlpSnST5w4ISIiIqQZtJ7cj7vqWlqkpaWJY8eOiYKCAul3c+fOdfrAfEZGhoiN\njRWA4Y6GpKQkRfqFCxdE+fLlBQDRsmVLodfrXVIGFYmOjhazZs0yOY9Gn332mfQ66NevX7H3k5ub\nK+rUqSN9mRIfH69Iv3btmjS4Wr9+fbN3LTujDCoSHx8v7ty5YzE9NTVVMcnm0KFDxdqPTqcTzZo1\nEwBExYoVxT///KNIv3XrljRZsmrVqiIrK8slZRC5EgfmyWvcvn1bBAYGCgBi1KhRZvOkpaVJs1j6\n9u3rsf24q66lmSsG5lNSUkRISIgAIIYMGWI2T2ZmptQh79Gjh0vKoCLJyck28/zwww/Sa+G9994r\n1n7S09NFWFiYACAGDBhgNk9WVpaIiYkRAETXrl1dUgY5Rq/XSxfQLVu2LFYZWVlZIjIyUgAQffr0\nMZsnNzdXVK1aVQAQ7du3d0kZRET+7D//+Y/0WX3gwAGzed555x0pT3FDhThjP+6qa2nmioH5999/\n3+bkh08//VTKs2nTJpeUQUXsuZvROHNeq9WKxMTEYu3n66+/ltpk9erVZvMsX75cyvPdd9+5pAxy\nzPbt20t8Dbdu3TqpjC+//NJsns2bN0t5PvnkE5eUQeRKWhB5iZ9++gkFBQUAgHHjxpnNU7ZsWQwe\nPBgAsH37dqSnp3tkP+6qKznXpk2bkJubC8Byu4WHh2Po0KEAgJ07dyIpKcnpZVARexYEevDBB6XH\ncXFxxdrP5s2bkZ2dDcByu4WFhWH48OEAgN27d+P27dtOL4Mco9FoUKVKlRKVsXXrVmRkZACw3G7B\nwcEYOXIkAGD//v24du2a08sgIvJna9asAQA0a9YMbdu2NZtn/Pjx0Gg0ivye2I+76krOZWyHWrVq\noWfPnmbzjB49Wlq011rbl6QMKhIbG2szj/E86/X6Yvfjje1Qvnx5DBw40GyeIUOGICoqSpHf2WWQ\nY2rWrCk91ul0xSrD2A6hoaF44oknzOZ5+OGHUa1aNUV+Z5dB5EocmCevsWvXLgBAUFAQOnbsaDFf\n165dAQB5eXnYv3+/R/bjrrqScxnbTavVonPnzhbzGdtNp9Nh7969Ti+DHGMcDAcM5704jO2m0WjQ\npUsXi/mM7abX6/Hnn386vQxyTHJysnQRZ2nwxBZjuwHAAw88YDGfsd0AYM+ePU4vg4jIX925cwdn\nzpwBAHTr1s1ivtjYWDRs2BAA8Mcff3hkP+6qKzlXbm6udC3VtWtX6UsTtTJlyqB169YATNvNGWWQ\n4/Lz86XHQohilbF7924AQOfOnREYGGg2T3BwMO6//34A5tvNGWWQYw4ePCg9Nv5NOcrYB2/Xrh3C\nw8PN5tFoNFL//K+//pImUDqzDCJX4sA8eY2zZ88CMMxgCA0NtZivQYMG0mNjx9rd+3FXXcm5jO1W\ntWpVlClTxmI+e9q+JGWQY7Zv3y49btKkSbHKMLZbbGwsoqOjLeazp+1LUgbZ79SpUxg0aBCys7MR\nHR2N119/vVjlGNstOjra6swue9q+JGUQEfmr06dPS48bNWpkNa9xsDsuLg56vd7t+3FXXcm54uLi\npBm39rbblStXkJWV5dQyyHG//vorAMPkGnk/yV5Xr17F3bt3AdjfbqmpqUhISHBqGeSYX375BdOm\nTQMAdO/eHb169XK4jPT0dFy/fh2A/e2Wn5+PCxcuOLUMIlfjwDx5DeMbpvEWIkvk6fHx8R7Zj7vq\nSs7Ftvc9ubm5mD17NgAgJCRECg/lKLa9dzt9+jT69OmDPn36oGvXrqhXrx7uu+8+7Nq1Cz169MDB\ngwdRo0aNYpXNticici35+52975PZ2dm4c+eO2/fjrrqScxWn3YQQiu2cUQY5Zs+ePfjtt98AAD16\n9EDFihUdLqM47QYU9d2cVQZZtmTJEgwZMgRDhgxB9+7dUatWLTz88MNITU3FxIkTsXHjxmKVy7an\n0sL8PTxEHmCM32vp9iKjiIgIk23cvR931ZWci23ve6ZNmybNWHjppZdQvXr1YpXDtvduKSkp2Lp1\nq8nvW7ZsiUmTJuGee+4pdtn2tlt4eDg0Gg2EEMVue2tlEBH5K+NMVED5GWiO+jPSkYE6Z+zHXXUl\n5ypJuzmzDLJfWloaxo0bByEEAgMD8e677xarHLa99zt69Ch+/PFHk9+PHTsWU6dOtdl/toRtT6UF\nB+bJaxjjz1mK+WYUFBQkPc7Ly/PIftxVV3Iutr1vWbJkCT799FMAQJs2bTBr1qxil8W2925NmzbF\nli1bABjukrh8+TJ+/PFH7N69G0OHDkW/fv2wcuVKREZGOly2ve1mzJOfn1/strdWBhGRv5K/39l6\nnzQuqgkY3u/dvR931ZWci23vW3Q6HUaMGCFNrpk1a1axY4yz7b3fhAkTpDU70tPTcezYMaxcuRJf\nfvklvvnmG3zxxRd48sknHS6XbU+lBQfmyWuEh4cjNzcXOTk5VvPJF4K09a2nq/bjrrqSc4WHhyMt\nLa3EbV/SMsi2jRs34plnngEA1K5dG+vXr1d0lhwVHh6OO3fulLjtS1oGmRcdHY0+ffoofjdlyhR8\n+umneOGFF7Bp0yZMnjwZX3/9tcNlG2fp2Go3nU4nDcCba/uSlkFE5K/ksyFtDWaU5DPSGftxV13J\nudj2vuXpp5+WJlw88cQTmDlzZrHLYtt7vxYtWqBFixaK382aNQuDBw/G77//jnHjxqFWrVp48MEH\nHSqXbU+lBWPMk9cwLqaYmppqNZ88PSoqyiP7cVddybnY9r7h999/x9ChQ1FQUIDKlStj+/btNmMC\n2sK2903PP/88Hn30UQDAsmXLcPv2bYfLYNsTEbmW/P3O1vtkWlqa9Lhs2bJu34+76krOxbb3HVOn\nTsVXX30FAHj00UfxzTffQKPRFLs8tr1vKleuHFauXInQ0FAIIfDee+85XAbbnkoLDsyT16hXrx4A\n4MqVK1bzydPr16/vkf24q67kXGx777d371489thjyMnJQUxMDHbs2CGd85IwlnH16lUIISzms6ft\nS1IGOa5v374ADLPRjx075vD2xna7fv06dDqdxXz2tH1JyiAi8ld169aVHtvbP4qJiXH4C0xn7Mdd\ndSXnKk67hYSEKNYmckYZZN2bb76J999/HwDQs2dPrFmzxq4wgNbIrwPsbTeNRqNob2eUQY6LjY1F\nu3btAAAHDhxwePuaNWtKIUIdufaWt7czyiByNQ7Mk9do1qwZAOD27dtWV8E+dOiQyTbu3o+76krO\nZWyD9PR0XLx40WI+e9q+JGWQeUePHsXDDz+MjIwMREdHY9u2bWjSpIlTyja2QWZmJuLi4izms6ft\nS1IGOU4eV76goMDh7Y1tkJ+fj5MnT1rMZ0/bl6QMIiJ/1bBhQ2ng4+jRo1bzGtPvu+8+j+zHXXUl\n56pVq5Y0g9VWux05cgQA0LhxYwQEBDi1DLLsvffew1tvvQUA6NKlC3766SeEhISUuNyoqCjUqFED\ngP3tVrt2bUX/0RllUPEY/+aKs/ZSUFAQGjZsCMD+ditfvrziTmtnlEHkahyYJ69hnBUJAJs3b7aY\nz5hWvXr1Yg18OGM/7qorOZej7VapUiW0bdvW6WWQqdOnT+Ohhx5CWloaypQpg19++QUtW7Z0WvmO\ntluFChXQoUMHp5dBjjtz5oz02HhR5QhH261s2bLo0qWL08sgIvJXoaGhUuzgHTt2SGttqB06dAiJ\niYkAgEceecQj+3FXXcm5NBqNtBbNrl27kJGRYTbfxYsXpYkz6nZzRhlk3ieffIIZM2YAANq3b4/N\nmzcrYnuX1MMPPwwAOHjwoPR3qXbz5k3pzkpz7eaMMshxxslMxb3zxNhuZ8+exeXLl83mSU9Px19/\n/aXI7+wyiFxKEHmJgoICcc899wgAokGDBiInJ8ckz+7duwUAAUC89tprHtuPu+pammVnZ0vnb/z4\n8U4pU6/Xi4YNGwoA4p577hFZWVkmeQ4cOCA0Go0AIKZNm+aSMkjpwoULonLlygKACA8PF7t27XLJ\nfpo0aSIAiFq1aomMjAyT9MOHDwutVisAiClTprisDLLfrVu3RMWKFQUAUaNGDaHX64tVTqtWrQQA\nUbVqVZGWlmaSfurUKREQECAAiEmTJrmsDCIif/Xdd99J/bZFixaZzTN06FABQAQHB4urV696bD/u\nqmtpNhIRqwUAABoqSURBVHfuXOkcHz161Cllbtq0SSpz7ty5ZvM8/fTTAoDQarXizJkzLimDlL76\n6ivpuqdVq1YiJSXF6fvYs2ePzevqV155Rcqzb98+l5RBjlm/fr10Pl988cVilXHy5Enp9fX888+b\nzTN79mxpP1u3bnVJGUSuxIF58irff/+99IY4dOhQxeDH4cOHRfXq1QUAUbFiRYsf+mPGjBG9e/cW\nI0aMcOl+nFEGWVacgfkJEyaI3r17i8GDB1vMI+8gDBgwQKSmpkppJ06cELVr1xYARLly5URiYqLL\nyiCDq1evipo1awoAIjQ0VPz666/FKmfSpEmid+/eYsCAARbzyC/G+vXrp/i7PHXqlPRlW1RUlLh1\n65bLyiCDxYsXi6VLl4qkpCSTNL1eL7Zu3SoaNGggne9ly5aZLWfy5Mmid+/e4pFHHrG4r+3bt0sd\n8t69eyv2ee7cOXHvvfcKACIyMlJcv37dZWUQEfkrnU4nmjdvLgCIsmXLih07dijS5syZI72fT506\n1WwZe/fuFYMHDxaDBw8WGzZscNl+nFEGWefowPyJEyektl+5cqXFfF26dBEARFhYmPjpp5+k3+v1\nevHpp59Kn9Pjxo1zaRlk8P3330uTEu677z6zfTpb/v77b6ntFy9ebDHfo48+KgCIoKAgsWLFCkXa\nt99+KwIDAwUAMWjQIJeWQQZvvvmm2Ldvn9lJM9nZ2eLzzz8XERERAoAoU6aMiI+PN8mXkJAgtf2H\nH35ocV+jR4+Wviz74osvFGlr164VISEhAoB48MEHXVoGkatwYJ68zrRp06SOXJkyZUTnzp1F8+bN\npU5SeHi4+PPPPy1uX6tWLQFAxMbGunQ/ziqDDH755RfRu3dv6adXr17Sua1evboizdLgq3EQLyoq\nyuq+XnvtNansyMhI0blzZ9GyZUup3UJDQ8Xvv//u8jKoqINsrp3N/bz88stmyzHOZI+IiLC6v//8\n5z/S/iIiIkSnTp1Eq1atpHYLCQlRXKC7qgwSYuzYsVIHuXLlyqJFixaiR48eomPHjqJ8+fLSOdZq\nteKdd96xWE7r1q0FABEQEGB1f/KZMOHh4eL+++8XrVu3lu5wCAoKEps3b3Z5GURE/urvv/8WlSpV\nkt4nW7ZsKfr27St9AQ9AdO3aVeTm5prdfs2aNTZnMztjP84qg4pMnz5dGmAbPHiwuO+++6Tz2LNn\nT0Xad999Z7L99u3bbc5mFkKI+Ph4RRvdd999om/fvtLECACidevWZu9qdGYZJERiYqIICgqSztkD\nDzygaGdzP+aujQ4ePCiVYWk2sxBCJCUlKSZsNGrUSPTr18/kd8nJyS4tgwyMA9nlypUTTZs2FT17\n9hT9+/cXnTp1EpGRkdL5LFeunPjjjz/MlnHhwgUp3xNPPGFxX+np6aJFixZS3nr16om+fftK138A\nRO3atUVCQoJLyyByFQ7Mk1datmyZNPvQ+BMQECAefvhhce7cOavb2jswX9L9OLMMEmLRokWKc2jt\nx9Lgq70D80IIsWrVKtGoUSNFuVqtVvTq1UucOnXKrjo7o4zSrkePHna3u/Ei2Rx7B+aFMFz4N27c\n2KTdevToIU6cOGFXvZ1RRmm3Z88eMWnSJOkOE/VPZGSkGD58uDh48KDVcuwdmBfCcLdL06ZNFfvR\naDSiW7du4siRI3bV2xllEBH5q/j4eDFkyBDFgB0AER0dLV599VWz4R+N7B2YL+l+nFkGGRjvQLDn\nZ8aMGSbb2zswL4RhQHjUqFHSwKC83zBlyhSRmZlps77OKKO0u3btmkN9eADi66+/NinH3oF5IYRI\nTU0VEyZMEGFhYYpyw8PDxdNPP2021KAryiAh5s+fL3r06GHyN2T8qVixovjXv/5ldaDb3oF5IYTI\nyMgQkydPVgz6A4YJUWPGjLHrbg1nlEHkChohhACRl/r7778RHx+PkJAQ1KtXDxUqVLC5zR9//IHs\n7GyEhIRIizu5Yj+uKKM0u379Ok6dOmVX3sDAQPTs2dPk93v27EFGRgaCgoLQo0cPu8q6dOkSrl27\nhpCQENStWxcxMTEO1dtZZZRWhw4dQlJSkt35y5cvj3bt2pn8/s8//8Tdu3ctvjbMuXz5Mq5du4ag\noCDUrVsXFStWtLseziyDgOTkZNy4cQO3b99GcHAwYmNjUbduXWi1tteo37t3L9LS0qDVavHQQw/Z\ntb8rV67g6tWrCAwMRN26dVGpUiWH6+yMMoiI/FVycjJOnz6N1NRUxMbGonnz5ggJCbG6TXx8PPbu\n3QsAaNasGe69916X7McVZZR2O3bsQGpqql15GzZsiKZNmyp+d/v2bezatQsA0KhRIzRp0sRmOWlp\naTh58iRSUlJQsWJFNG/eHGFhYQ7V2xlllFbZ2dnSovf2atu2LWrVqqX4XUpKCn799VcAQL169dCi\nRQub5WRkZODEiRO4c+cOKlSogGbNmiEyMtKhujijDDK8Dq5evYqEhASkpaUhMjIStWvXRt26dW1u\nm5mZiS1btgAAatWqhbZt29rcJisrCydOnEBiYiLKly+Ppk2bIioqyqE6O6MMImfiwDwRERERERER\nERERkRvZnopGREREREREREREREROw4F5IiIiIiIiIiIiIiI34sA8EREREREREREREZEbcWCeiIiI\niIiIiIiIiMiNODBPRERERERERERERORGHJgnIiIiIiIiIiIiInIjDswTEREREREREREREbkRB+aJ\niIiIiIiIiIiIiNyIA/NERERERERERERERG7EgXkiIiIiIiIiIiIiIjfiwDwRERERERERERERkRtx\nYJ6IiIiIiIiIiIiIyI04ME9ERERERERERERE5EYcmCciIiIiIiIiIiIiciMOzBMRERERERERERER\nuREH5omIvNiPP/6I4cOH47PPPvN0VUrkzJkzGD58OKZMmeLpqhARERERudwrr7yCCRMm4OLFi56u\nSol89tlnmDBhArZt2+bpqhAR+R2NEEJ4uhJERGQqPT0d9evXx+3bt3HgwAG0bdvW01UqNr1ej2bN\nmuH06dP4/vvvMXToUE9XiYiIiIjIJVauXImRI0eiWbNmOHbsGDQajaerVGw7duxAr169ULt2bZw7\ndw4hISGerhIRkd/gjHkiIi81e/Zs3L59G4899phPD8oDgFarxX/+8x8AwIwZM5Cbm+vhGhERERER\nOV9OTg5mzpwJAJg1a5ZPD8oDQM+ePdGlSxdcvnwZ77//vqerQ0TkVzhjnojICyUkJOCee+5BTk4O\n9u3bh/bt23u6SiUmhEDDhg1x/vx5LFiwAC+99JKnq0RERERE5FTz58/H9OnT0bRpU5w8edLT1XGK\nrVu3ok+fPihTpgyuXLmCcuXKebpKRER+gTPmiYi80KJFi5CTk4OGDRv6xaA8AGg0GowZMwYAsHDh\nQvB7YSIiIiLyJ3q9Hp9++ikA4Mknn/RsZZyoV69eqFq1Ku7evYulS5d6ujpERH6DA/NERF5Gp9Nh\n0aJFAIDRo0d7uDbONWrUKGg0Gly8eBHbt2/3dHWIiIiIiJzml19+waVLl6DVajFy5EhPV8dp5Mfz\n+eefe7g2RET+g6FsiIjskJKSgn/961/Iz89H/fr18dZbb5nNJ4TA1KlTkZCQgIiICHzyyScICwtz\naF9btmzBI488AgA4f/486tevbzbf8ePH8e677wIAPvzwQ8TGxprNt3fvXnz44YcADDPxy5QpI6Ul\nJiZi8uTJAIDp06ejTZs2SE9Px/Lly6Vbb1u2bIkxY8aYLPR0+PBhbNiwAVevXkV0dDQeeeQR9OrV\ny+bxtW/fHgcOHMCwYcOwatUqm/mJiIiIiIpr48aN+OmnnwAAEyZMQIcOHczmi4uLw9y5cwEADzzw\ngHSnpyMGDx6MtWvXomvXrti5c6fFfJ9++imOHj2Kxo0bY+rUqRbzzZ07F3FxcWjTpg2eeeYZRdra\ntWvx888/IyoqCvPnzwcAXLx4EWvXrsX169dRuXJlPPLII2jRooViO51Oh40bN+Lw4cNITU1FgwYN\nMHToUFSqVMnqsR06dEha92rXrl3o0qWL1fxERGQHQUREdpkzZ44AIACIL7/80myed999V8qzePHi\nYu1n2rRpAoCIiYmxmm/Lli3Svi5cuGAx38qVK6V8iYmJirRLly5JaevWrRO///67KFeunPQ740+d\nOnXElStXhBBC5OXlidGjR5vkASBGjhwpCgoKrNb7xRdflI5Pr9fbeVaIiIiIiBx39+5dUb9+fQFA\n1KhRQyQnJ5vkycnJEc2bNxcARMWKFcWNGzcc3o9Op5P60TNnzrSat3///gKA6NGjh9V8Xbt2FQDE\n4MGDTdJmzJghAIjY2Fih1+vFjBkzhEajUfTNNRqNeOWVV6Rtzp07J+69916TPnx0dLT49ddfrdYl\nPz9fhIeHCwDizTfftJqXiIjsw1A2RER2euWVV6QZ4VOmTMGZM2cU6fv27cMbb7wBABg2bBjGjx9f\nrP388ccfAOD22PLnz59H3759UadOHcybNw9Lly7Fiy++iJCQEFy6dAmPPfYYhBB48sknsWrVKowb\nNw5LlizBwoULcf/99wMAVqxYgQULFljdT8eOHQEASUlJOH36tMuPi4iIiIhKr8jISKxatQrBwcG4\ndu0axo0bZ5Jn+vTpOH78ODQaDb755htUqVLF4f2cOHECKSkpAGBxVr6rvPPOO5g7dy4GDx6MDz74\nAHPnzkXbtm0hhMB7772Hr776Cjdu3MADDzyAzMxMvPLKK/j0008xdepUREREIDU1FYMHD8bt27ct\n7iMwMBBt2rQBAKt3AxARkf04ME9EZCeNRoNly5YhNjYW2dnZGDZsGLKzswEAaWlpGDFiBAoKClCn\nTh188cUXxdpHfn4+jh49CgBo3ry50+puj1mzZmHkyJE4ePAgpk2bhjFjxuD999/H8uXLARhC5zz7\n7LNYv349du3ahSVLlmDcuHF49tlnsWvXLnTu3BkAsGDBAuh0Oov7kd9Ou2/fPpceExERERFRq1at\n8L///Q8AsH79enzyySdS2oYNG6TnL774ohRS0lHyfq06fIwrpaamYs6cOfj555+xZs0aTJkyBdOn\nT8fevXvRrVs3AMDs2bPx/PPPo379+jh79iz+97//4bnnnsP8+fOxfft2aDQapKam2owf37JlSwDA\n/v37IRgVmYioxDgwT0TkgNjYWCxbtgwajQanTp3CSy+9BAB4+umncfnyZQQGBmLlypWIiooqVvmJ\niYnSoHZMTIzT6m2PChUq4JNPPoFWq/xoGDx4MOrVqwcA+OKLL/D666+bzAIKCAjAtGnTAAA3b97E\niRMnLO5Hflw3b950VvWJiIiIiCx68cUX0a9fPwBFM+SvX78uzaBv1aoV5syZU+zyExISpMfu7Mfn\n5ubihRdeQO/evRW/DwgIwKuvvgoA+Pvvv7F582asXLlSsd4UYLibtUePHgAMi9daU7FiRWmfycnJ\nzjoEIqJSiwPzREQO6tWrF1555RUAhoHqESNGYPXq1QCAt99+u0QhaBITE6XHFSpUKFlFHTR8+HCT\nBV6NjLetAsDYsWPN5jEuBgUYFs+yJDo6Whr8lx8vEREREZErff3116hWrRpyc3MxbNgwjBw5Enfu\n3FGEuykuY782NDQU4eHhzqqyXSyF0JRfl/Tq1Qs1atQwm69du3YAgLNnz1rdj/z6hP14IqKS48A8\nEVExvP3229Ks8VWrVgEAevbsKQ3YF1dmZqb02N0d+vvuu89imrETXr58eVStWtVqHsAQ2scSrVaL\n0NBQAEBGRkZxqkpERERE5LCYmBgsX74cWq0WcXFx2L17NwBg4cKFqF+/fonKNvZrIyIiSlxPR4SF\nhVmse3R0NAICAgBYD5NpnAmfnp5uNUSN/Nju3r1bnOoSEZEMB+aJiIohMDBQcatrQEAAvvrqK2g0\nmhKVKx/cNi4e5S7q21rlAgMD7c4DGGLlW5KXl4esrCwA7r8rgIiIiIhKt65du2Lo0KHS80ceeQSj\nR48ucbnly5cHYH2CiiuULVvWarqxj24tnzGPXq+3ulZUamqq9Nh4vEREVHwcmCciKoaCggLMnDlT\neq7T6bBw4cISl2ucrQLAb+M2yo9LfrxERERERK529OhRrFu3Tnq+e/duXLx4scTlGvu1BQUFSE9P\nL3F53ujOnTvSY/bjiYhKjgPzRETF8Oabb2Lv3r0AimI3/u9//8OOHTtKVG65cuWkhWPlC0iVhLXZ\n655w48YN6XHt2rU9VxEiIiIiKlUyMjIwfPhw5ObmokaNGihXrhzu3r2LESNGlLjPXKtWLenxzZs3\nS1pVAIZBfm9iPK7o6GibM/WJiMg2DswTETno119/xf/+9z8AwKRJk/Dbb7+hUaNGEEJgzJgxJVoI\nSaPRoHPnzgCAgwcP2r2dtUH8a9euFbs+rnDgwAHpcZcuXTxYEyIiIiIqTZ5//nmcP38eAQEBWLFi\nBRYvXgwAOHTokOJu2OKQ92sPHTpk1za2BvCvX79eojo5m7Efzz48EZFzcGCeiMgBiYmJGDVqFPR6\nPZo0aYL3338f4eHhWLVqFUJDQ5GQkICxY8daXTTJlq5duwIAjhw5YvfMnT/++MPs74UQ+PHHH4td\nF1fYt28fAKBBgwaoXLmyh2tDRERERKXB8uXL8e233wIw3P3auXNnDBo0CM888wwAYMGCBdi6dWux\ny69Vq5Y0a37//v12bXPx4kXcvn3bbNqxY8dw5cqVYtfH2bKysnDy5EkARdcrRERUMhyYJyKykxAC\nY8eOxc2bNxEWFoZVq1YhLCwMANCsWTPMmzcPALBlyxZ88MEHxd5P3759AQA5OTmK2eXWzJkzx+RC\nIicnB1OmTMGRI0ek37l7QVlzdu3aBaDoOImIiIiIXOnixYt49tlnARgGlV9//XUp7f3330fTpk2l\nvv6tW7eKvZ9HHnkEQFF/15bc3FyMGzfOpI9++fJlxYK03hCz/q+//pJC6zz88MMerg0RkX/gwDwR\nkZ0WLFiALVu2ACjqwMs9//zzGDBgAADg1VdfVQyIO6Jx48ZSOJvvvvvOrm0qV66MPn36oHHjxnjs\nscfw8MMPo1q1avj4449x//33S/n69++P8ePHF6tezvDXX3/h0qVLAICnn37aY/UgIiIiotIhLy8P\nw4cPx927d1GhQgV899130GqLhkJCQ0OlCTe3bt3CmDFjin33q7F/e+zYMZw5c8Zm/qpVq2Lr1q2o\nW7cuevfujbFjx6JHjx5o0KABTp8+jebNmwMAfvvtNwwfPhxr164tVr2cYcWKFQAMYWwaN27ssXoQ\nEfkTDswTEdlBHndy0KBBmDRpktl8S5YsQfXq1aULgIyMjGLtz3hL7ffff4+8vDyb+ZcuXYru3bvj\n7Nmz2LhxI3755RekpqbiySefxI4dO/DQQw8BAM6ePVviBWpLYtmyZQCA7t27o0GDBh6rBxERERGV\nDjNnzsThw4cBAF999RWqV69ukqdJkybSHa/btm2T7oR1VIsWLdChQwcAkMLmWNOoUSMsXboU+fn5\n2LZtG7799lv89ttvCAkJwdKlS/H1118jODgYOp0O33//PU6dOlWsepVUdna2FB7TeJ1CREQlF+jp\nChAR+YLc3Fypc92nTx+L+cqXL49t27bh+PHjAIDbt28jMjLS4f09/vjj+Pe//42rV6/ihx9+wMiR\nI63mj42Nxa+//orz588jLi4OAQEBaNmyJapUqQIA2Lx5M3bu3AmNRoNOnTpJ21WsWBErV64EALRt\n29Zi+WPHjkWHDh0QERFhMU9AQIBUVuvWrU3S7969i++//x4AMG3aNKvHQ0RERERUUrm5uWjSpAkW\nLVqEihUr4rHHHrOY9+mnn0aZMmWQmZmJ4OBg6PV6xcx6e02dOhVDhw7FsmXLMGvWLISEhFjNP3Lk\nSPTv3x+7d+/G7du3UalSJXTp0kXqd585cwb79+/HPffcIw36A8DgwYNRr149hIeHWy3/888/R0FB\nAdq1a2cxT/fu3bFo0SIAhj692po1a5Ceno6aNWtiyJAhVvdHRET204iSrFBIREQus2LFCjzxxBPS\nrazqTvIvv/wixXe8cOEC6tWr54lq2u3tt9/GG2+8gV69emHbtm2erg4RERERkUt07NgR+/btw0cf\nfYTJkyebpA8YMAA//fQTevTo4dG7We2h0+nQqFEjXLhwAStWrMCIESM8XSUiIr/BUDZERF5qxIgR\naN++PeLi4qSYjr4qLS0NCxYsQEBAAObPn+/p6hARERERucyCBQsAAO+++y6ys7M9XJuSWbZsGS5c\nuIAOHTpg+PDhnq4OEZFfYSgbIiIvpdFo8N133+HQoUOoWrWqp6tTIunp6Vi4cCFiYmJw3333ebo6\nREREREQu07FjR/zwww9ISUlBUlISatSo4ekqFVtsbCwWLVqELl26QKPReLo6RER+hQPzRERerF69\nel4fosYeNWrU4AwbIiIiIio1Bg8e7OkqOIUxdCYRETkfQ9kQEREREREREREREbkRZ8wTEfmoFi1a\nYOXKlQCAypUre7g2RERERERkjxdeeAH9+vVDtWrVPF0VIiLyII0QQni6EkREREREREREREREpQVD\n2RARERERERERERERuREH5omIiIiIiIiIiIiI3IgD80REREREREREREREbsSBeSIiIiIiIiIiIiIi\nN+LAPBERERERERERERGRG3FgnoiIiIiIiIiIiIjIjTgwT0RERERERERERETkRhyYJyIiIiIiIiIi\nIiJyIw7MExERERERERERERG5EQfmiYiIiIiIiIiIiIjciAPzRERERERERERERERuxIF5IiIiIiIi\nIiIiIiI34sA8EREREREREREREZEbcWCeiIiIiIiIiIiIiMiNODBPRERERERERERERORGHJgnIiIi\nIiIiIiIiInIjDswTEREREREREREREbkRB+aJiIiIiIiIiIiIiNzo/wFMMqZjNYviTQAAAABJRU5E\nrkJggg==\n"
          }
        }
      ],
      "source": [
        "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 2), tight_layout=True)\n",
        "sim_data_a.plot_field(\n",
        "    field_monitor_name=\"field\", field_name=\"E\", val=\"abs\", ax=ax1, eps_alpha=0.4, vmin=0, vmax=70\n",
        ")\n",
        "sim_data_c.plot_field(\n",
        "    field_monitor_name=\"field\", field_name=\"E\", val=\"abs\", ax=ax2, eps_alpha=0.4, vmin=0, vmax=70\n",
        ")\n",
        "ax1.set_title(\"On state\")\n",
        "ax1.set_ylim(-1, 1)\n",
        "ax2.set_title(\"Off state\")\n",
        "ax2.set_ylim(-1, 1)\n",
        "plt.show()"
      ],
      "id": "6955f0bc"
    }
  ],
  "nbformat": 4,
  "nbformat_minor": 5,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    }
  }
}