{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Tutorial 5c - Optimization Case Study"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "tags": [
                    "nbsphinx-toctree"
                ]
            },
            "source": [
                "### August 2024"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "This tutorial demonstrates how Optiland can be used to design an F/5 Cooke triplet starting from three (nearly) parallel plates."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 1,
            "metadata": {},
            "outputs": [],
            "source": [
                "import numpy as np\n",
                "\n",
                "from optiland import analysis, optic, optimization"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "1. Definition of initial system"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "We start with a system that consists of 3 (nearly) parallel plates, in which all surface have an absolute radius of curvature of 1000 mm. The center element uses glass type F2, while the first and last lens use SK16.\n",
                "\n",
                "We specify a maximum field of 20 degrees and an entrance pupil diameter of 10 mm. We will later specify a target focal length of 50 mm, which implies an F-number of 5.0 = 50 mm / 10 mm. We'll place the stop on the back side of the center lens."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 2,
            "metadata": {},
            "outputs": [],
            "source": [
                "class Triplet(optic.Optic):\n",
                "    def __init__(self):\n",
                "        super().__init__()\n",
                "\n",
                "        # Define surfaces\n",
                "        self.surfaces.add(index=0, radius=np.inf, thickness=np.inf)\n",
                "        self.surfaces.add(index=1, radius=1000, thickness=4, material=\"SK16\")\n",
                "        self.surfaces.add(index=2, radius=-1000, thickness=5)\n",
                "        self.surfaces.add(index=3, radius=-1000, thickness=4, material=(\"F2\", \"schott\"))\n",
                "        self.surfaces.add(index=4, radius=1000, thickness=5, is_stop=True)\n",
                "        self.surfaces.add(index=5, radius=1000, thickness=4, material=\"SK16\")\n",
                "        self.surfaces.add(index=6, radius=-1000, thickness=50)\n",
                "        self.surfaces.add(index=7)\n",
                "\n",
                "        # Define aperture\n",
                "        self.set_aperture(aperture_type=\"EPD\", value=10.0)\n",
                "\n",
                "        # Define fields\n",
                "        self.fields.set_type(field_type=\"angle\")\n",
                "        self.fields.add(y=0)\n",
                "        self.fields.add(y=14)\n",
                "        self.fields.add(y=20)\n",
                "\n",
                "        # Define wavelengths\n",
                "        self.wavelengths.add(value=0.4861)\n",
                "        self.wavelengths.add(value=0.5876, is_primary=True)\n",
                "        self.wavelengths.add(value=0.6563)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Let's view the starting point of the lens:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 3,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "image/png": 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",
                        "text/plain": [
                            "<Figure size 1000x400 with 1 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "lens = Triplet()\n",
                "fig = lens.draw()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "2. Initial Optimization Step"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "While technically not required, we will identify a lens starting point that satisfies the required focal length and minimizes the seidel aberrations."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "We first specify pickups on the surfaces to enforce symmetry in the design. The first and last lens surfaces should be equal and opposite. Similarly, the second and fifth, as well as third and fourth, should be equal and opposite.\n",
                "\n",
                "We define this as follows, using a \"scale\" factor of -1 and an offset of 0. The radius of curvature is defined as $R_{new} = R * scale + offset$, where $R$ is the radius of curvature of the reference surface."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 4,
            "metadata": {},
            "outputs": [],
            "source": [
                "lens.pickups.add(\n",
                "    source_surface_idx=1,\n",
                "    attr_type=\"radius\",\n",
                "    target_surface_idx=6,\n",
                "    scale=-1,\n",
                "    offset=0,\n",
                ")\n",
                "lens.pickups.add(\n",
                "    source_surface_idx=2,\n",
                "    attr_type=\"radius\",\n",
                "    target_surface_idx=5,\n",
                "    scale=-1,\n",
                "    offset=0,\n",
                ")\n",
                "lens.pickups.add(\n",
                "    source_surface_idx=3,\n",
                "    attr_type=\"radius\",\n",
                "    target_surface_idx=4,\n",
                "    scale=-1,\n",
                "    offset=0,\n",
                ")"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Let's define the optimization problem. We first define the focal length and Seidel aberration operands:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 5,
            "metadata": {},
            "outputs": [],
            "source": [
                "problem = optimization.OptimizationProblem()\n",
                "\n",
                "# Add requirement for focal length\n",
                "problem.add_operand(operand_type=\"f2\", target=50, weight=1, input_data={\"optic\": lens})\n",
                "\n",
                "# Add requirements for Seidel aberrations (1 to 5)\n",
                "for i in range(1, 6):\n",
                "    problem.add_operand(\n",
                "        operand_type=\"seidel\",\n",
                "        target=0,\n",
                "        weight=10,\n",
                "        input_data={\"optic\": lens, \"seidel_number\": i},\n",
                "    )"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Let's define the variables, which are the first 3 surface radii. Recall that the last 3 radii are picked up to these radii, so they do not need to also be specified as variables.\n",
                "\n",
                "Finally, we view the optimization problem info."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 6,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "╒════╤════════════════════════╤═══════════════════╕\n",
                        "│    │   Merit Function Value │   Improvement (%) │\n",
                        "╞════╪════════════════════════╪═══════════════════╡\n",
                        "│  0 │                 573580 │                 0 │\n",
                        "╘════╧════════════════════════╧═══════════════════╛\n",
                        "╒════╤════════════════╤══════════╤══════════════╤══════════════╤══════════╤═════════╤═════════╤════════════════╕\n",
                        "│    │ Operand Type   │   Target │ Min. Bound   │ Max. Bound   │   Weight │   Value │   Delta │   Contrib. [%] │\n",
                        "╞════╪════════════════╪══════════╪══════════════╪══════════════╪══════════╪═════════╪═════════╪════════════════╡\n",
                        "│  0 │ f2             │       50 │              │              │        1 │ 807.351 │ 757.351 │            100 │\n",
                        "│  1 │ seidel         │        0 │              │              │       10 │  -0     │  -0     │              0 │\n",
                        "│  2 │ seidel         │        0 │              │              │       10 │   0     │   0     │              0 │\n",
                        "│  3 │ seidel         │        0 │              │              │       10 │  -0.004 │  -0.004 │              0 │\n",
                        "│  4 │ seidel         │        0 │              │              │       10 │  -0.003 │  -0.003 │              0 │\n",
                        "│  5 │ seidel         │        0 │              │              │       10 │   0.001 │   0.001 │              0 │\n",
                        "╘════╧════════════════╧══════════╧══════════════╧══════════════╧══════════╧═════════╧═════════╧════════════════╛\n",
                        "╒════╤═════════════════╤═══════════╤═════════╤══════════════╤══════════════╕\n",
                        "│    │ Variable Type   │   Surface │   Value │   Min. Bound │   Max. Bound │\n",
                        "╞════╪═════════════════╪═══════════╪═════════╪══════════════╪══════════════╡\n",
                        "│  0 │ radius          │         1 │    1000 │        -1000 │         1000 │\n",
                        "│  1 │ radius          │         2 │   -1000 │        -1000 │         1000 │\n",
                        "│  2 │ radius          │         3 │   -1000 │        -1000 │         1000 │\n",
                        "╘════╧═════════════════╧═══════════╧═════════╧══════════════╧══════════════╛\n"
                    ]
                }
            ],
            "source": [
                "problem.add_variable(lens, \"radius\", surface_number=1, min_val=-1000, max_val=1000)\n",
                "problem.add_variable(lens, \"radius\", surface_number=2, min_val=-1000, max_val=1000)\n",
                "problem.add_variable(lens, \"radius\", surface_number=3, min_val=-1000, max_val=1000)\n",
                "\n",
                "problem.info()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "We then perform optimization. Here, we use the least squares optimizer in Optiland, which simply wraps the implementation in scipy.optimize.least_squares."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 7,
            "metadata": {},
            "outputs": [],
            "source": [
                "optimizer = optimization.LeastSquares(problem)\n",
                "res = optimizer.optimize(\n",
                "    tol=1e-3, method_choice=\"trf\"\n",
                ")  # Trust Region Reflective (trf) method supports bounds"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Let's view the optimization result. We see that there is a >99.99% improvement in the merit function."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 8,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "╒════╤════════════════════════╤═══════════════════╕\n",
                        "│    │   Merit Function Value │   Improvement (%) │\n",
                        "╞════╪════════════════════════╪═══════════════════╡\n",
                        "│  0 │               0.305589 │           99.9999 │\n",
                        "╘════╧════════════════════════╧═══════════════════╛\n",
                        "╒════╤════════════════╤══════════╤══════════════╤══════════════╤══════════╤═════════╤═════════╤════════════════╕\n",
                        "│    │ Operand Type   │   Target │ Min. Bound   │ Max. Bound   │   Weight │   Value │   Delta │   Contrib. [%] │\n",
                        "╞════╪════════════════╪══════════╪══════════════╪══════════════╪══════════╪═════════╪═════════╪════════════════╡\n",
                        "│  0 │ f2             │       50 │              │              │        1 │  50.01  │   0.01  │           0.03 │\n",
                        "│  1 │ seidel         │        0 │              │              │       10 │  -0.018 │  -0.018 │          10.63 │\n",
                        "│  2 │ seidel         │        0 │              │              │       10 │  -0.003 │  -0.003 │           0.26 │\n",
                        "│  3 │ seidel         │        0 │              │              │       10 │   0.003 │   0.003 │           0.31 │\n",
                        "│  4 │ seidel         │        0 │              │              │       10 │  -0.041 │  -0.041 │          54.12 │\n",
                        "│  5 │ seidel         │        0 │              │              │       10 │   0.033 │   0.033 │          34.66 │\n",
                        "╘════╧════════════════╧══════════╧══════════════╧══════════════╧══════════╧═════════╧═════════╧════════════════╛\n",
                        "╒════╤═════════════════╤═══════════╤═══════════╤══════════════╤══════════════╕\n",
                        "│    │ Variable Type   │   Surface │     Value │   Min. Bound │   Max. Bound │\n",
                        "╞════╪═════════════════╪═══════════╪═══════════╪══════════════╪══════════════╡\n",
                        "│  0 │ radius          │         1 │   26.7027 │        -1000 │         1000 │\n",
                        "│  1 │ radius          │         2 │ -998.564  │        -1000 │         1000 │\n",
                        "│  2 │ radius          │         3 │  -44.5965 │        -1000 │         1000 │\n",
                        "╘════╧═════════════════╧═══════════╧═══════════╧══════════════╧══════════════╛\n"
                    ]
                }
            ],
            "source": [
                "problem.info()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Before viewing, we call \"image_solve\" to move the image plane to the paraxial image location."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 9,
            "metadata": {},
            "outputs": [],
            "source": [
                "lens.image_solve()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 10,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "image/png": 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",
                        "text/plain": [
                            "<Figure size 1000x400 with 1 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "fig = lens.draw()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "3. Second Optimization Step - Remove Symmetry Constraint"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "In the second step, we remove the requirement that the lens is symmetric. We first clear all pickups."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 11,
            "metadata": {},
            "outputs": [],
            "source": [
                "lens.pickups.clear()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Now that we have a starting design, we will no longer consider the Seidel aberrations. Instead, we will optimize for a minimal RMS spot size for all fields and wavelengths as follows:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 12,
            "metadata": {},
            "outputs": [],
            "source": [
                "# Clear all operands\n",
                "problem.clear_operands()\n",
                "\n",
                "# focal length requirement\n",
                "problem.add_operand(operand_type=\"f2\", target=50, weight=1, input_data={\"optic\": lens})\n",
                "\n",
                "# RMS spot size requirement at (0, 0) field\n",
                "input_data = {\n",
                "    \"optic\": lens,\n",
                "    \"surface_number\": -1,\n",
                "    \"Hx\": 0,\n",
                "    \"Hy\": 0,\n",
                "    \"wavelength\": \"all\",\n",
                "    \"num_rays\": 5,\n",
                "}\n",
                "problem.add_operand(\n",
                "    operand_type=\"rms_spot_size\",\n",
                "    target=0,\n",
                "    weight=10,\n",
                "    input_data=input_data,\n",
                ")\n",
                "\n",
                "# RMS spot size requirement at (0, 0.7) field\n",
                "input_data = {\n",
                "    \"optic\": lens,\n",
                "    \"surface_number\": -1,\n",
                "    \"Hx\": 0,\n",
                "    \"Hy\": 0.7,\n",
                "    \"wavelength\": \"all\",\n",
                "    \"num_rays\": 5,\n",
                "}\n",
                "problem.add_operand(\n",
                "    operand_type=\"rms_spot_size\",\n",
                "    target=0,\n",
                "    weight=10,\n",
                "    input_data=input_data,\n",
                ")\n",
                "\n",
                "# RMS spot size requirement at (0, 1.0) field\n",
                "input_data = {\n",
                "    \"optic\": lens,\n",
                "    \"surface_number\": -1,\n",
                "    \"Hx\": 0,\n",
                "    \"Hy\": 1.0,\n",
                "    \"wavelength\": \"all\",\n",
                "    \"num_rays\": 5,\n",
                "}\n",
                "problem.add_operand(\n",
                "    operand_type=\"rms_spot_size\",\n",
                "    target=0,\n",
                "    weight=10,\n",
                "    input_data=input_data,\n",
                ")"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "We add the last 3 radii as variables, as well as the thickness to the image plane."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 13,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "╒════╤════════════════════════╤═══════════════════╕\n",
                        "│    │   Merit Function Value │   Improvement (%) │\n",
                        "╞════╪════════════════════════╪═══════════════════╡\n",
                        "│  0 │                4.21387 │                 0 │\n",
                        "╘════╧════════════════════════╧═══════════════════╛\n",
                        "╒════╤════════════════╤══════════╤══════════════╤══════════════╤══════════╤═════════╤═════════╤════════════════╕\n",
                        "│    │ Operand Type   │   Target │ Min. Bound   │ Max. Bound   │   Weight │   Value │   Delta │   Contrib. [%] │\n",
                        "╞════╪════════════════╪══════════╪══════════════╪══════════════╪══════════╪═════════╪═════════╪════════════════╡\n",
                        "│  0 │ f2             │       50 │              │              │        1 │  50.01  │   0.01  │           0    │\n",
                        "│  1 │ rms spot size  │        0 │              │              │       10 │   0.063 │   0.063 │           9.49 │\n",
                        "│  2 │ rms spot size  │        0 │              │              │       10 │   0.116 │   0.116 │          31.8  │\n",
                        "│  3 │ rms spot size  │        0 │              │              │       10 │   0.157 │   0.157 │          58.71 │\n",
                        "╘════╧════════════════╧══════════╧══════════════╧══════════════╧══════════╧═════════╧═════════╧════════════════╛\n",
                        "╒════╤═════════════════╤═══════════╤═══════════╤══════════════╤══════════════╕\n",
                        "│    │ Variable Type   │   Surface │     Value │   Min. Bound │   Max. Bound │\n",
                        "╞════╪═════════════════╪═══════════╪═══════════╪══════════════╪══════════════╡\n",
                        "│  0 │ radius          │         1 │   26.7027 │        -1000 │         1000 │\n",
                        "│  1 │ radius          │         2 │ -998.564  │        -1000 │         1000 │\n",
                        "│  2 │ radius          │         3 │  -44.5965 │        -1000 │         1000 │\n",
                        "│  3 │ radius          │         4 │   44.5965 │        -1000 │         1000 │\n",
                        "│  4 │ radius          │         5 │  998.564  │        -1000 │         1000 │\n",
                        "│  5 │ radius          │         6 │  -26.7027 │        -1000 │         1000 │\n",
                        "│  6 │ thickness       │         6 │   39.0959 │            0 │         1000 │\n",
                        "╘════╧═════════════════╧═══════════╧═══════════╧══════════════╧══════════════╛\n"
                    ]
                }
            ],
            "source": [
                "problem.add_variable(lens, \"radius\", surface_number=4, min_val=-1000, max_val=1000)\n",
                "problem.add_variable(lens, \"radius\", surface_number=5, min_val=-1000, max_val=1000)\n",
                "problem.add_variable(lens, \"radius\", surface_number=6, min_val=-1000, max_val=1000)\n",
                "\n",
                "problem.add_variable(lens, \"thickness\", surface_number=6, min_val=0, max_val=1000)\n",
                "\n",
                "problem.info()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Let's optimize the system, view the result and plot the lens. In this iteration, we use the generic optimizer in Optiland, which wraps scipy.optimize.minimmize."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 14,
            "metadata": {},
            "outputs": [],
            "source": [
                "optimizer = optimization.OptimizerGeneric(problem)\n",
                "res = optimizer.optimize(tol=1e-9)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 15,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "╒════╤════════════════════════╤═══════════════════╕\n",
                        "│    │   Merit Function Value │   Improvement (%) │\n",
                        "╞════╪════════════════════════╪═══════════════════╡\n",
                        "│  0 │               0.200164 │           95.2499 │\n",
                        "╘════╧════════════════════════╧═══════════════════╛\n",
                        "╒════╤════════════════╤══════════╤══════════════╤══════════════╤══════════╤═════════╤═════════╤════════════════╕\n",
                        "│    │ Operand Type   │   Target │ Min. Bound   │ Max. Bound   │   Weight │   Value │   Delta │   Contrib. [%] │\n",
                        "╞════╪════════════════╪══════════╪══════════════╪══════════════╪══════════╪═════════╪═════════╪════════════════╡\n",
                        "│  0 │ f2             │       50 │              │              │        1 │  50.009 │   0.009 │           0.04 │\n",
                        "│  1 │ rms spot size  │        0 │              │              │       10 │   0.018 │   0.018 │          16.38 │\n",
                        "│  2 │ rms spot size  │        0 │              │              │       10 │   0.03  │   0.03  │          45.81 │\n",
                        "│  3 │ rms spot size  │        0 │              │              │       10 │   0.027 │   0.027 │          37.77 │\n",
                        "╘════╧════════════════╧══════════╧══════════════╧══════════════╧══════════╧═════════╧═════════╧════════════════╛\n",
                        "╒════╤═════════════════╤═══════════╤══════════╤══════════════╤══════════════╕\n",
                        "│    │ Variable Type   │   Surface │    Value │   Min. Bound │   Max. Bound │\n",
                        "╞════╪═════════════════╪═══════════╪══════════╪══════════════╪══════════════╡\n",
                        "│  0 │ radius          │         1 │  26.0336 │        -1000 │         1000 │\n",
                        "│  1 │ radius          │         2 │ -95.5246 │        -1000 │         1000 │\n",
                        "│  2 │ radius          │         3 │ -25.2659 │        -1000 │         1000 │\n",
                        "│  3 │ radius          │         4 │  27.8951 │        -1000 │         1000 │\n",
                        "│  4 │ radius          │         5 │ 624.237  │        -1000 │         1000 │\n",
                        "│  5 │ radius          │         6 │ -19.6047 │        -1000 │         1000 │\n",
                        "│  6 │ thickness       │         6 │  39.889  │            0 │         1000 │\n",
                        "╘════╧═════════════════╧═══════════╧══════════╧══════════════╧══════════════╛\n"
                    ]
                }
            ],
            "source": [
                "problem.info()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 16,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "image/png": 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",
                        "text/plain": [
                            "<Figure size 1000x400 with 1 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "fig = lens.draw()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "4. Final optimization - Fine Tuning"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "As a last step, we will let the thicknesses between the lenses vary and re-optimize. Allowing the lens thicknesses to vary is generally unnecessary, as it offers very little corrective power."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 17,
            "metadata": {},
            "outputs": [],
            "source": [
                "problem.add_variable(lens, \"thickness\", surface_number=2, min_val=1, max_val=10)\n",
                "problem.add_variable(lens, \"thickness\", surface_number=4, min_val=1, max_val=10)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 18,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "╒════╤════════════════════════╤═══════════════════╕\n",
                        "│    │   Merit Function Value │   Improvement (%) │\n",
                        "╞════╪════════════════════════╪═══════════════════╡\n",
                        "│  0 │               0.200164 │           95.2499 │\n",
                        "╘════╧════════════════════════╧═══════════════════╛\n",
                        "╒════╤════════════════╤══════════╤══════════════╤══════════════╤══════════╤═════════╤═════════╤════════════════╕\n",
                        "│    │ Operand Type   │   Target │ Min. Bound   │ Max. Bound   │   Weight │   Value │   Delta │   Contrib. [%] │\n",
                        "╞════╪════════════════╪══════════╪══════════════╪══════════════╪══════════╪═════════╪═════════╪════════════════╡\n",
                        "│  0 │ f2             │       50 │              │              │        1 │  50.009 │   0.009 │           0.04 │\n",
                        "│  1 │ rms spot size  │        0 │              │              │       10 │   0.018 │   0.018 │          16.38 │\n",
                        "│  2 │ rms spot size  │        0 │              │              │       10 │   0.03  │   0.03  │          45.81 │\n",
                        "│  3 │ rms spot size  │        0 │              │              │       10 │   0.027 │   0.027 │          37.77 │\n",
                        "╘════╧════════════════╧══════════╧══════════════╧══════════════╧══════════╧═════════╧═════════╧════════════════╛\n",
                        "╒════╤═════════════════╤═══════════╤══════════╤══════════════╤══════════════╕\n",
                        "│    │ Variable Type   │   Surface │    Value │   Min. Bound │   Max. Bound │\n",
                        "╞════╪═════════════════╪═══════════╪══════════╪══════════════╪══════════════╡\n",
                        "│  0 │ radius          │         1 │  26.0336 │        -1000 │         1000 │\n",
                        "│  1 │ radius          │         2 │ -95.5246 │        -1000 │         1000 │\n",
                        "│  2 │ radius          │         3 │ -25.2659 │        -1000 │         1000 │\n",
                        "│  3 │ radius          │         4 │  27.8951 │        -1000 │         1000 │\n",
                        "│  4 │ radius          │         5 │ 624.237  │        -1000 │         1000 │\n",
                        "│  5 │ radius          │         6 │ -19.6047 │        -1000 │         1000 │\n",
                        "│  6 │ thickness       │         6 │  39.889  │            0 │         1000 │\n",
                        "│  7 │ thickness       │         2 │   5      │            1 │           10 │\n",
                        "│  8 │ thickness       │         4 │   5      │            1 │           10 │\n",
                        "╘════╧═════════════════╧═══════════╧══════════╧══════════════╧══════════════╛\n"
                    ]
                }
            ],
            "source": [
                "problem.info()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Let's optimize the system one last time with all variables to fine tune the system."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 19,
            "metadata": {},
            "outputs": [],
            "source": [
                "optimizer = optimization.OptimizerGeneric(problem)\n",
                "res = optimizer.optimize(tol=1e-9)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 20,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "╒════╤════════════════════════╤═══════════════════╕\n",
                        "│    │   Merit Function Value │   Improvement (%) │\n",
                        "╞════╪════════════════════════╪═══════════════════╡\n",
                        "│  0 │               0.110757 │           97.3716 │\n",
                        "╘════╧════════════════════════╧═══════════════════╛\n",
                        "╒════╤════════════════╤══════════╤══════════════╤══════════════╤══════════╤═════════╤═════════╤════════════════╕\n",
                        "│    │ Operand Type   │   Target │ Min. Bound   │ Max. Bound   │   Weight │   Value │   Delta │   Contrib. [%] │\n",
                        "╞════╪════════════════╪══════════╪══════════════╪══════════════╪══════════╪═════════╪═════════╪════════════════╡\n",
                        "│  0 │ f2             │       50 │              │              │        1 │  50.002 │   0.002 │           0    │\n",
                        "│  1 │ rms spot size  │        0 │              │              │       10 │   0.012 │   0.012 │          13.16 │\n",
                        "│  2 │ rms spot size  │        0 │              │              │       10 │   0.022 │   0.022 │          41.82 │\n",
                        "│  3 │ rms spot size  │        0 │              │              │       10 │   0.022 │   0.022 │          45.02 │\n",
                        "╘════╧════════════════╧══════════╧══════════════╧══════════════╧══════════╧═════════╧═════════╧════════════════╛\n",
                        "╒════╤═════════════════╤═══════════╤═══════════╤══════════════╤══════════════╕\n",
                        "│    │ Variable Type   │   Surface │     Value │   Min. Bound │   Max. Bound │\n",
                        "╞════╪═════════════════╪═══════════╪═══════════╪══════════════╪══════════════╡\n",
                        "│  0 │ radius          │         1 │  30.0189  │        -1000 │         1000 │\n",
                        "│  1 │ radius          │         2 │ -63.0945  │        -1000 │         1000 │\n",
                        "│  2 │ radius          │         3 │ -18.2466  │        -1000 │         1000 │\n",
                        "│  3 │ radius          │         4 │  31.338   │        -1000 │         1000 │\n",
                        "│  4 │ radius          │         5 │ 623.507   │        -1000 │         1000 │\n",
                        "│  5 │ radius          │         6 │ -16.4225  │        -1000 │         1000 │\n",
                        "│  6 │ thickness       │         6 │  43.5928  │            0 │         1000 │\n",
                        "│  7 │ thickness       │         2 │   4.21698 │            1 │           10 │\n",
                        "│  8 │ thickness       │         4 │   2.17393 │            1 │           10 │\n",
                        "╘════╧═════════════════╧═══════════╧═══════════╧══════════════╧══════════════╛\n"
                    ]
                }
            ],
            "source": [
                "problem.info()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 21,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "image/png": 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WU1JSEB4ejtDQ4XcLjvyMQkQfSyxmf7SuBFsv72Fr5h1svbyHrZl3sPUSIJG/8/pqwVKqbT+OdxyjgjVaGY2S+FLcW3gvTadHKiPpmhHxNNI1O68/T8eebq3binZLG1K0qbi74B6sSVuLJG3SFX+/prcGr5x9GVvrt0AlUVHLK7JFKS+dtR2P7zG73d53nfyuXC6Hv7lUIHFCi9ULyczMRHR0NKqqqi4pVkmN61BNWOQFDsQfEpLCCNRjTQTYenkPWzPvYOvlPWzNvGOyrle3tRsHWw/0TYwiqX6FRIFZMbPw9WnfpOn3rLCsIes9vV0z8ljb67ZhU+3HONt9llpVrUpdTf1QC6OKhlVTeqLjBF46+yK+aPocsapYPDztW7g+eyM0Mg0m4ntMPGDfQL0/h/sYE1qsNjY2oqurCwkJCWN9KAwGg8FgTCqI3dOJjuNucbqfdsoTcsJzsDZtLUoT5mNGzAwqWH0BicwSYUkapfa27KWCbWHiItw75T4sSFwIuUQ+rGauPc27qUg93nEc6aHpdBzq2rR1XrsLMHzHuBKrRqORRkk91NTU4Pjx44iMjKQbqT294YYbqBsAqVl98sknkZ2dTb1WGQwGg8Fg+De1X9tb0ydOj7QdpnWhkYpIlCSU4ra821ASX4JoVYxPH5OUEJA0/yf1n1AD/8KoQjxe/ASuSl01bIcAJ+fA1rptePnsS7Q8YVr0NPx20e+xOGkxnXjFGFvGlVg9fPgwli1b1vezp9b07rvvxt/+9jecPHmSDgUgtS2JiYlYtWoVfvrTnzKvVQaDwWAw/ECPracvtU+M+YlBv1wsx4yYmXig6EHatZ8dnu1zwUfGmBKBSsaeNpma6IQqUke6Ln090kLTvBrH+kH1+3it4jW0mVuxMHEhnpr9FD1+Zj8VPIwrsbp06dLL2kFs27YtoMfDYDAYDMZkwuFy4FTXSSF62rKP1oPy4JEZloUVKStp3ems2FlQSlU+f2y9TY8djZ9SkXqy8yQ0Mi1WpqzETzKeoeLSG0Gss+rwn8o38da5/8DkMGN12mrcVXA3FdaM4GNciVUGg8FgMBiBgwSI6g31tCHKk9o3O800vU669r+ScxO9jFXH+k0c727+Eh9UfoCDnQdoTSkZn/qL+c9TX1Rvx5g2GZvwavkr+PD8hyBx0+uzrsft+XcgXsN6W4IZJlYZDAaDwWAMMr0/1HYI+1v2UoHaYmqhJvnTo2fgq1PuRWlCKZ3s5K9aTiKQz3SfoWNPt9dth97eg+yQbNqNvyZ9LaJU3ltGVeoqadPUp/WfIEQegnum3EOF9kinXjECCxOrDAaDwWBMYshs+9Ndp3GARE9b9lOhSCKYpBN+SdJSd2q/GGqZ2q/H0WJqxubazdhUswn1hjrEqGJwXdZ1WJu6FpF8FJ1M6Y2dEhG9R9oP46WyF7GvdR8SNYl4bNZ3cV3mdX4pU2D4DyZWGQwGg8GYZDQaG6kwJel9EkU1OYzUi5TMt78uawMVqIFIjZPu/R31n2JT7SYcbT9CR6ouT1mB783+PmbHzoZELKEm995Mh3JxLuxq2kVFaln3GWqV9bN5P8fK1Kv6xqgyxhfsVWMwGAwGY4JjtBtwuP1wn0AlYlUikmJadBHuzL+LpvYLIgqoOAxEJPdA6wGa5v+8aRf1YyXTqp4tfQ7LkpePOIJL7ofc5yvlr9DIbHHsbPx5yf/DvIT5rLN/nMPEKoPBYDAYEwwSXSRRRaFrfz9Od52Ci3chRZuCeQnzUBI/D7PjZkMr0wbkeEhKvrKnkorJbXVb0WXtQmZoJh4ofJDWocap40YlxN+pehdvVLyObmsXliYvw3Pzfkr9VhkTAyZWGQwGg8GYAJCaTyFyup96nxocBipGSdTyydnfo137ydrkgB5Th7kDW+qEOtRqfRUdELA6fQ3Wp6+nTVqjiXh2WjrwesXreLfqXdhdNqzPuBp35N9Ja20ZEwsmVhkMBoPBGIeYHCbaQOQRqCT1TTr0SUTx1rzbaGp/SuTUgNdpWpwWfNawk9ahHmo7CKlIiiXJS/Gt6d+ixyQVj25saV1vHV4pf5lGaeUSBW7IvgG35t6GGLXvJmMxggsmVhkMBoPBGAeQDv3y7vI+z9OTnSdo/Sfpcifeow9Pf5hGUYk101iUHRDhTCKoOxt3UME6K2YWfjDnh3RYgC+O6UzXabxc/jJ2NX6GSGUUHiz6Om7MvgHaMXi+jMDCxCqDwWAwGEEKGV9KJkUJqf2D1HNUI9VgdtwcfHfW47RrP1mbMmYNROf152mEc0vtZrRb2pEakoq7C+7B2vR1SNIm+aTWdV/LXvzfqf/DSd0Jev9EAK/LWA+FhI1SnywwscpgMBgMRpBAIpJH248K0dOWfajprYEIIkyJmoobc26k4rQoumjUqfTR0G3tpk1SZOwpGbdKLK9Wpa7G+oz1KIwq8olwJhFjYuD/8tmXaGNWbmgefjn/V1iWsjwgjgWM4IKJVQaDwWAwxjC1T6YrkcgpMeU/3nEcDs6BOHU87dp/sOghGkUd60lLNpcNXzR9TqOo+1r2UUG6MHER7p1yHxYkLoRcIvfJ41idFvz3/H/xWvmraDY1Y178PPx16d+RKctEZGSkV0MBGF7C8whWmFhlMBgMBiOAdNm6sLdmDw62HaB+o922bmqGT6ykvj3jO7QJKS0kfcy9QYmQPtFxnDZKkSgnMfAviirC48VP4KrUVT4V0D22Hrx97i38p/JNOu6V3P9vFv0OeRF5Xg8FYFwBlx2i7hqIus5B1F0FUUc5RK0nAF0TgIcQjDCxymAwGAyGH7E6rTjecczteboPVfoqentBZAEdJ0o8T6dFT/NZdHK01BvqsblmE61DbTI10Qaum3Nvwbr09UgLTfPpY7WaWmgU9YPzH1BxfG3mddR+yhf1rpMecxdEumqIuqoEYerZeuoh4l10F14kAXgXhNMiKdxXgg4mVhkMBoPB8CGkKYh4ipJ0ORGox9qPws7Z6az7krhS3Jj6FSzLXI4odRSCBb1Nj0/qt9M61JOdJ6GRabEyZSV+kvEMZsTMpJZYvqSqp4rWo26r2waNTI3b8+6ggjhCGeHTx5nwcE6IdLVChJSK0SqgsxJxXecgsfbQXXjy2mliwMs0EDmt8ChSXiTtE6pc/HQ4C28DdrQhGGFilcFgMBiMUdJl6aJpfY/naZe1EwqJEsWxs/DN6Q9TaykysYkIWZLSDgZR5nA5sKdlN7Wb2t38JY1skuP8xfznsThpCZRSpU8fjzx3EmF+6eyL2N28m9blfnvGt7Eh6/oRj1idNFj1fWK0P0paBZGuBiLOQXfh5RrwUTngIjJg06ZBIbJDTKKo7WUQGdsAuRZQRQASKeB0go/JB1d4A1xTNgKhSeDsdmDHbxGMMLHKYDAYDMYI5tD3p/b3o7Kngt6eG56LdenraHPU9JgZF9krEcE2lpDHJ36lpA51e912aoVFJkl9a/ojWJ22BlEq30d7iQj+oukLvHz2RRq1zQzLwjOlz2FN2uoxdTUIOjgXoG+A2BMl7XTXlHZVQWRq79uND00WRGnGUvCzvwY+PA1wmCFuPwtx/R5IKjZD47KBV4aDj50KLmUOxB0VEJk7wauj4Jr7DXBTbwAfk4fxAhOrDAaDwWAMQ+QRGymP5+mR9iOwuayIUkbRMaZ35N+BufEliFZFIxhpNjZjc+1mmuYnk65iVbG0XpbUoWaHZ/stcktGrb5y9mW6djNiZuAPi/9I3QN8XVYwrrAZIOquHhApdYtTcpvLRnfhpSrwUdl041IXUHHKR+eAj8gExFKImo9AXLcHkvIPIWo6TNP7vDIMXOp8uOZ+HTZ9G9Sth6h45VVR4KZsgGvqjeCTZgNj3Lg3EphYZTAYDAZjCHpsOhxoPUgF6oHW/dT0Xi6W0xrOh4oeop6n2eE5Y961fylI9/6O+k9pFPVo+xHqOLA8ZQW+N/v7mB07229+pWQM7PtV7+H1itfompGSgqfn/hjTY6Zj0sBzgKGlL0LaFy0lm6GlfzdtvCBEU0rAzbgDHLkelU3T8vAIeqcNouajEJ/bRgWqqOlQvzhNmQdu6Q/BxUyhXf2Ssvcgq9wCiVQNLm8dnFf9HHz6YkAyviPYTKwyGAwGg+GOBJ7sOtknTonhPQ8eWWHZ1EqJWErNjJkJpVSFYIWY6RM7LOKH+nnTLlquQEawPlv6HJYlL/drbSip232z8g28c+5tmJ0WrEtfizsL7kZmWCYmLA4zRN3nB9eReqKkDjPdhZfIwUdmgY/MBld0K/hoEjHNoT9DMcSoWCJOGw9SYSqu290vThWhNHJKxSmJtoalQly1DZLT70Cy4ydU3HJZK2C/9h/oii5BeGzihPGlZWKVwWAwGJM2tV9nqBMM+Vv24XD7YTpBiviHlsbPw005N9PUfqw6FsH+PCp0FTTFTyZLdVm7aF3oA4UPYk36WsSp4/z6+I2GBrxS/go+rvkIEpEE12dtxG35t/v9cQMGqTM2tQk1pG4hKnaLU+gbIYJQh8yrY8BHZYFPmAGu8CtCXSmJkoalApeLYhPfUxI5JeK0fg9EjUScWtzidB64JT8Al7YAfGwh7d4XV38Kyb4/0UgrEbFcSimcq38NLv9aQB1JfWn5CeZLy8Qqg8FgMCYNxHD+YOtBOi2KiNQWUwukYilmRM/AfVO/RlP7uRF546Kmst3cjq11W2g3P7HKilREYnX6GqxPv5qa6fu7PKG8+yzt7N/RsANh8jDcO/U+fCXnJjp+dVxCIpqku/7CrnuSwrcZ6C68WAo+IkOoJZ1yfV+ElKbuSaf9cKDi9BgVpjSt33jQLU5DhLT+ku+DS1soiFMicnkOovq9kG59HOLyjyCy9oCLnQrXoieFTv6wZEx0mFhlMBgMxoTFyTlwuuu021JqH8q6y2h3ekZoBpYmLUVJwjwUxxZDFcSp/YGQyO9nDTtpHerB1gOQiWVYkrwU35rxCErjS/zeXU+iuIfaDuLFshepVVeSNhlPFn8PV2dc43OrK79FSYlZvkeEugWpmPiT9tRBRGpNyW6kk54I0ZgCcPnXuJudcsCHp3tf/0nEacvx/rT+UOKUpPXjivojsDwPUftpiEmKv+w9WufKh6XANesecFNuAB9bgMkEE6sMBoPBmFCQtDSJmhJT/sNth2Bymmjkb278XGzI2khFXbwmAeMFF+fCkfbDNIK6s3EHFayzYmbhh3N/hJUpK6CVhwTkGMhjEyN/UstL7K6IHytp2CKR6aDD5YCop3ZAhNRTS1oFkUXXb5YfnkZT9a7cte4IKWlwygHIwIaRRqbJY7ccG5DWP0jrV3m5VkjrL/6ekNan4vSCtdPVUnFKRKq4q1Lo5C+4Di5iNZU8d1x28vuCIHyHMRgMBoMxfIx2Aw61HRI8T1v3o8nYCIlIiunR03DXlLtp/Wl+RL7fut/9RbW+um/sKemqTw1Jxd0FX8Xa9LUBG0dqc9nw0fmP8Gr5y2g0NmJu3Fz8z9K/oiS+JDhcECw9gyKkg83ynXQXIhI9IpTLvqrvOknnQzrYB3fk4vT4gLT+gX5xmlIKbtETQlp/KHFKMHVAfPa/kJx5F+KmQ+BlanC5a+FY8Sz1UsU47+T3BUysMhgMBmNcQTrez3aX9UVPicm9i3dRMTc/YT4Vp7PjZkMj02C80W3tpk1SpJu/XFdOI8Kr0lZRP9TCqKKACUSD3UC7+t+oeB06mw4rUlbiF/N/iSlRUxBwOBck+nqIu49AMmCsKN3MHX27kTS5YJa/DPzs+/u8SaGJ821EkojT1hOD0/oO02BxStL68dOGFqcEmwFiYjF15l2IanbR4+Myl8Fx3T/A5awB5OPvvetPmFhlMBgMRtBDTO1JzSkRqIdaD8LgMEAr09JufeIbSoz5AxVt9DVWpxVfNn9BBSoR30SQLkpcRBu+iIG+XCIPaNPWGxWv4b2q9+DgHLg68xrcmX8nUkJSA2SW75neVNV/vfs8VB6zfJlasIEiDU7pi/qjpJGZgL9suQaKU5LWbzjgFqcaoeZ04XeFyOnlxCm9HzvE53cKKX7ayW8Bl1wK56rnaaqflh4wxr9Y/eKLL/Cb3/wGR44cQUtLC95//31s2LBhUOH3T37yE/zrX/9CT08PFixYgL/97W/IyckZ0+NmMBgMhvfG8qROc5/b87TeUE9tkaZGFeLWvNvoONOCyCnBWS85DEiT14n247RR6pP6T2ByGFEUVYQnip/EytSrqH1WIKnRn8fLZ1+mE6fI8ICbcm/Czbm3+n4iF2lg6m12NzVd4E1qbO3fLSRBqCFNmQfn9DthUMRDkzoDovDkfrN8f8E5IWo5MSCtvx8iuwm8TAM+pRQuIk5J5DRh+uXFqfv5ihr2Cyl+Mm3KogMXUwDXwsfhmnI9EB6Ak4AJwLj6lJtMJkyfPh333nsvNm7ceNH///rXv8af//xnvPTSS8jIyMCPfvQjrF69GmVlZVAqx0GXIoPBYExSSAMPSXuT6OmBlv040XkSLt6JJE0SShPm0dn1s+PmICQAzUT+hIju96rexa62XWg2NSFRk4hbcm+haf600LSAH8+pzpN46exL2NX4GWJUMfjmtIdxffZGGrUevVl+9QBvUs9Y0SoaUSTwEkV/lHT67X3jRS80yye+oTadDuqwCIj8IVSJOG09KaT06/dC3LBvsDhd4BanJHI6nPpR2sl/BuIz7wqd/L1N4EOT4ZpxFzjSKBU7BqUU45xxJVbXrl1Lt6EgUdU//vGPePrpp3HdddfR215++WXExcXhgw8+wC233BLgo2UwGAzG5Wg1tQqG/K37qPep3q6HRqqhovTx4scxL34ekkNSMN7R2/T4pH47TfOf6joFtVRNJ2Ktz3iGjm4NtKcr+b7c07IHL5e9iKMdR5EWko4fzf0x1qav867kgNhAGVsH1ZD2RUt7G/t308QKojRhJriim4RJTqTjPizl8mb5/uKy4rQErvmPCd368dO9a27qqRciqGTrLAevigCXfx1chTe6O/mD37s3WBlXYvVy1NTUoLW1FStXruy7LSwsDCUlJdi3b98lxarNZqObh97e3r4zObL5Ezplguf9/jgTBbZe3sPWzDvYevl3zYjlEplRT8aBHmjbj5reGirUpkRMwY3ZX6F1p4VRhYNS++P1tSCjW4kgJFOldrd8SdeINH79tPTnmKaehrioOGEUJi+UBASqMY2I5lfKX0aVvoo2bP16wW+xOGlxn2Aecr2dVrdZflXfjHviS0qjpXbjYLP8yGxqVC8IUrdZvvIyJQ3DeH1H/bkk4rTtFCQkrU/FKUnrG4Wu++S5cM77jjDGNH7GxeL0So9p7oSk/EMqUiXuTn5Xzho4lj7t7uR3i38y5CpArzM3wvUauH8gNNCFjzkpxCoRqgQSSR0I+dnzf0Px/PPP49lnn73odlLz6nK54E94noPBQD7ovH9SGxMMtl7ew9bMO9h6+XbNiAirNlTjaNcRHOk8gjM9p+HknYhVxqI4ajZuT78D06NmIFTWP/HIoBcmBY1H6NhTfTk+bfkEu1p30Saw7JAc3JdzP5bFL0OEIqJvvXokuoC9x6xOC7Y0bcF7de+i3dqOudFz8dvZv0NhhOAuoO/R0yip2NoNqe48pPoaSHvO920SQ1OfWT6nCIczPAO28Cy40lbCEZ4JZ3gmXCHJQ0chLTzg9jUN2OeSc0LWdRby5oNQNB+EvPUwxHYjOKkK9vhi2Gc8AFvCXDhiCgcfc68gvK8Eaa5S1u6AqupjKBp209tsyQvQu/w3sKavoBFa4f5MpIAR4+XvmMPhGKSBZDL/W2YZDIbJJVZHylNPPYXHHntsUGQ1JSUF4eHhCA0NDcAZhYg+Fj3DZlwWtl7ew9bMO9h6jX7NOiwdQuS0dT+dcERsj8h0qOLY2fh2+nfoONPUkLTg8Oj0Ec2mZuqFSpqTSE1qrCoWG7Kux7q0dcgKzx6z91iPrQdvnfsP3jr3Fm3gIqUHd+bchlxIhShp5av9qXtSX2rt6TPL58PTwEfmgMu/Gg73SFGaund3rIvdWyAcQK+4ZpyLTnuS1O0WIqekIcpmECKnSXPgKn0EDhI5TSCRUzk9Zq+P2+WAuOYzWoMqObeV+qi6kubAcdXP4cq/FlBHg3TGBEN3DDfC95jdbu+7Tn5XLve/C4VEIplcYjU+Pp5etrW1ISGhfzIJ+XnGjBmX/D2FQkG3CyEvcCC+rMgf7EA91kSArZf3sDXzDrZe3tsuHek6jDN1Z3Cg7QCdUS+CCPmR+VSwkeaoaVHTIJtgxuZkEMGnDTtomp+UNhBBvix5Ob43+ynMjp192QEE/n6PEZuv1878Hz6o/Rginsf1ylTc6YpB0skdEH3xf/1m+YqQfrP8nDUDzPLThzTLH8tPxKA1I+K07ZRgI0XspEjNKRGnUhWtDXWVfktoiEqc2Z+GH8nxk07+xoOQEKsp2snfDS46D675j8I1dSOdfjWi+w0AohG8xwbuG6i/gcN9jAkjVkn3PxGsO3bs6BOnJEp64MABfP3rXx/rw2MwGIwJAUl1V/Wc65sWdaz9KOycnUYTSc3pvVPvo1OOIpQRmGiQmk/ynMlUqc+bdsHusmNO3Fw8W/ocFapqf/l8XgoiOnvq++pIz7Ufw4u9Z7FNZIaW43BfrwE395oQEeIUBGnWiv4Z96SW1Ndm+f6Cc0HWcQbSc6cgbtgLcT0Rp71XFKcjRdReJnTyE8P+3kbwoUlwTb8dHGmUipkyPtZsgjGuxKrRaERVVdWgpqrjx48jMjISqamp+M53voOf/exn1FfVY12VmJg4yIuVwWAwGN7RZemiaX2hc/8AuqydUEiUKI4tplZHBeopmJ48fdgpvXFXh6qrwKbaj7G9bhu6rF3IDMvCA4UPYk36WsSpB/dJ+M0sf6AfqedSd54azR9WKvDv8AjsVsmRIJHjsdBibEhZBWXsFGqWbw+0iB4tNK1/xt2tT5qi9kFFxalSEKcl3xS69RNm+mZcKkHfAMmZ94RO/o4ydyf/tXARq6mUUtbJP8aMK7F6+PBhLFu2rO9nT63p3XffjRdffBFPPvkk9WJ94IEHaHHwwoULsXXrVuaxymAwGF7Ogz/RcVyInrbsQ2VPJb09NzwP6zPW07rT6TEzoJAoaH2cTkeahSZWtIlMctpatwWbajbR0oZIRSRWp6/B+vSrkReR5/vnS83ym4RO+0HepMQsv61/t5BEGhV1pc7HztzFeNFQhtPGemSHZeOnU+7BValXQSqW9TWgjytxOjCtb9UL4jRpDpxzvw59xDRochdDLFf57nHNXRCf/a8gUhv300gtl7MajqU/AJe53CdRWsYkFKtLly6lZ7mXgvzxeO655+jGYDAYjOFB/q6e7z1PhSmJoB5pPwqby4ooZTQVpncW3IW5cSWIUk3scZDEWuuzhp10qtTB1gOQiWVYkrwU35rxCErjS/pE4KiwmyDtLIOkpc2dvndvpMHpIrP8HHDTS/pT95FZsEsV2Fy7Ga+cfRl1LbWYFTMLfyp+AvMT5o+fEwZSC0ojp3v6IqekucsjTl1zv+5O68+ikVNyQmTX6aDxRRTVboL43FaIz7wD8fnPqAsCn7EUjmv+Ci537aBhBIzgYVyJVQaDwWD4hh6bDgdaD2J/y14aQSVd/HKxHDNjZ+GhoofoONOssOzxI4BGMTnrcPthWoe6s3EHFaxEAP5w7o+wMmUFtCOZmOUxyx8QIe03y2+CaqBZPhGiScXgpt0siFPScR+afJFZvtFhpJOvXq94jZZlEBH9TOkzKIqehvEhTssGpfWpOCWiPHkOXHMeFNL6VJz6IRNKO/l3CQK1cgvt5CcuAc6VPwNXcB2gifH9YzJ8ChOrjAkZJbpcBH64kC/pif5FzZg8EJP6E50n6LQoIk7Lu8vBg6fp49Vpa2gElUxTUvpDLAQh1fpqKlCJ5VS7pR2pIam4u+CrWJe+DonaxOHdCTHL7z5/QT2pO31vF/w1ebFMMMsnQrTwK+AiMqGXxUObPhNi9ZWb0DotnXiz4g28U/U2rC4rHct6V8FdSA/NQPCLU0/kdG+/OE2aDdecB4TIaVKxf8QpPQZe6OQnNahn/wuRpQtcVC5c879DhxaAOB4wxg1MrDImHC0tLXj5pRdHfT+z58zBypVX+eSYGIxAQ07Y6gy12N9CGqP24Uj7ERo1JMb0pGv/5txbURJXghj15IkqdVu7sa1uKx17Wq4rR5g8DKvSVtE61KlRhUOfnJITX1PH4BpStzcp6cQXuStDeVWkkKqPKwQ3ZUO/DRSxN7pgIpdDpwOUYZc9VuLXSlL95FhJOcLG7I24Ne92xKpjEZTitOOsIE5pzeleiCy6wIpTN6KOchpBJXWoIn09rfF1Tb8VHGmUii1knfzjFCZWGROOqnOVkMsVKJ5dPOL7qK6qQlNj/2xrBmO8zKA/1HawrzGq1dxKhc6MmBm4b+r9NHqaG5Eb8Fn0Y+0D+2XzF1T07WvZRwXposRF+Frh/ViQsLDf/9Vlh0hXOzhC6hGoVj3dhRdJwEekURHqyru6X5ASGyi3Wf5oKesqw0tnX8TOhh2IVEbi/sIHcGPOVxAyknIEv4rTciGtP0icygVxWvw1Ia2fNNvv4pSib6Rm/bSTv/0MeGWYu5P/RvCp81gn/wSAiVXGhONcVRWSkhKRnT14cow3dLS3U2cJBiOYcXIOnOo81ed5WtZ1hqb2M0IzsCxlOZ1FPyt2FjWsn0yQMa/EzYA0Sn1S/wmd3lQUVYQnip/EypjZiDC6I6WVP+9P4ROhygsjtnlFaJ8IJU03QnNT9iXN8n0RBSeNbUSkHmo7hBRtCr4/5ylcnXENdVwIFnFKhaknrW/pFsRpYjFcxfe5I6ezAVmA3mvmbmrUT9P8Dftocxbt5F/8PXCZK/zyOjHGDiZWGRMKMgiCCM28RYvG+lAYDL+ImkZjgztyuh+H2w7B5DTRdPbc+BJszNpIU/zxGmGi32SDpM5JHerm2o/RbGpBojwCt2mycbVDgvTWFojOPE1rFwk8REB4qjBGNGtlnzgll9DEBiRdTIYM7GjYgZfPvoQKXTkKIgvwywW/ogMGLjcBKzDitEKoN63ziNMuof42iYjTewMvTgkOM8RV2yEuexfi6p0A73J38v8FXO461sk/gWFilTGhOH++mqb5yDAIBmMiYLAb+lL7B1r2o8nUBIlIiunR03D3lHto9JT4fo6puBkrrL3obTuOT2o24+POwzjl6IaWB1YZzbjWYMBMWz1EsirwUW4bqMyl/aI0IjOwQusCH9t3zr2N1ypepa8nOcH467K/0WlYY9LUSZqROisgqts9tDiddU9/Wn8MpnSJqz9D+PE3oKz9VOjkTyyGc8VzQie/NghreBk+h4lVxoTifHU1oqOjoVCwFBBjfEKibWXdZ9yNUftxpus0XLwLqSFpWJC4EKUJpSiOnQ2NTINJATHL1zcKZvnulL2zqxK7DefxkcyJz9Uq2uK0wMHj17I4LI6cBnluPhWkDhIlDUkImqYaUlP8VuV/8GbFmzA4e7EiZSV+tfDXyI8sGCNxOiCtb+4UxGmiW5ySyGnyGIhTz/E1HYaEWE2RTn5zJxzhGXCSsaqFNwIRQeyEwPALTKwyJgyky7a2thYFU6aM+r7EYjGcTqdPjovBuBJNxibasU8EKomiEk/NEFkITe1/f/ZTNPI2bDul8YrdKBjjE0FK/Em7B5rlW6kgPanW4qPIOGyVcdCHy5GvSsW3k5ZhVd7NiApN7bsrDsFFq6mV+qO+X/0erae9KmEV7p1+H1IHHLP/xWnlgLT+ngHidBZcM+8eW3HqhpQekCYpSdm7EPXUgdfGw1V0E5wFG9EtT0ZEZCT928yYfDCxypgwNDc3wW63IyEhYdT3pdFoUFdX55PjYjAuhIjRI21HsL91LxWoDcYGSEQSFEYV4fb8OzAvfh4KIqdMvNQ+sYEytPR12osHdt4bmvt3o2b5OXSaUWPB1fjY1Y1NPadQb2pGrCoCG9LXYV3GemSFZSGYOa8/T+tRt9RugVqqwq15t+Gm7JshsogQob2yx+qoxClZ04FpfXMHeLFUiJzOuKs/rS8f4wh9bzMVp2Iy8rTtlLuT/xq4pvwRfOp8OhyB5ziA2H0xJi1MrDImDDU1NZDL5YiKGr2FjEarhc1mg9VqhVI5OUzSGf6dknRWd5YKU2LKf7LzFFy8E8naZFpz+u2E72B27OyRTUsKRhwWiHTnB0RIPVZQ1RA5BpjlR2YKtaRFN/XbQEVmwygW4dOGHdhc8zGO1u+kbgbLk1fge3N/RNcp2EX88Y7jtLP/y6YvEKuKpeNar8+6npZukAyQzqLznzil0dOB4nQWXDPucIvTOWMvTgkWXV8nv6h+HyCRC538C58Al8U6+RkXw8QqY8JQW1OL+Ph4n6SJtFotvdTr9UysMkZEq6mlr2v/YNsB9Np7oZFpMSduDp4ofoJ6niaHpGDcQs3y2yHuqIS68SRklmb3rPtzgL5hgFl+lNssvwjclI39DU4XmOWTWl2yXpuO/AJfNH0Ou8tOyyCeLX2OdserxzA9PRxIen9385d4qewlnOg8Tu3DflLyDNakre33cvWpOK2CqH5A5NTULojThJnBJ049nfzntgsjT6t3CJ386YvhvPrP4HLXA8rQsT5CRhDDxCpjQkDS/y0tzZg9e7ZP7o+UARB6e/WIi4vzyX0yJjZmhxlH20lqX5gYVdtbS833p0ZOxc25N6Mkfh4Ko6ZCKvaxcPE3xCy/u+aCCKnbm9TWS3eRU7P8dMGXtODaQVFSqCMva8VVoavAptqPsb1uG7qsXcgMy8IDhQ9ibfq64JzWNMQYWzIVi6T7z/eex7To6fjdoj9gUdIi3w1fIOKUrH/dJcTp9NvcNadEnAon2kEB54So9gvBC7XiYzqCliOR3uXPwDWFdPJPTos1hvcwscqYEDQ2NtL0Goms+gKVSkUjtL164cuYwRgqklapq6BTkYhAJdE0Eh2MV8djXsI8fH3aN2kUNVQ+TiJG5q6hpzfp6oYwy8+l0TA6ySkiE90IQ0R03LCzGu3mdmyp3YzNtZtRra9CpCISq9PX0LGnxIZrTOybRnByQhqmSONUm7mNTsX6wdwfYkbMTB+KU3e3PhljSsQpOSlInAnXtFuFyGny3OASp55jbz7ibpT6gJYjcJFZcJU8DG7qRvCRwV1nzAhOmFhlTAjq6+uowAwNu/y87eFCvixJdJUMGWAwBoosMmmIep627kePrQdqqRrFcbPx6MzHaP1pakhq8IotEukik5oGzLjvE6iW7kFm+RypJc1e1T+9iZrlx1xkAzXc5hci7j5r3EkF6sHWA5BL5FictITWc5KSCOmAkoBgptvajf9Uvom3z70Fk8OMNWlrcGfBXcgOzx6lOK0e3K1vbBPEacKMfnFK0vpBanxP6pNJip/WofbUgtfGwVV4Azgy8jR+etDYhzHGJ+PjrwODcQUa6usRGxvrU5GgVqtpGQBj8mJ1WnC0/WjfONPz+mqIIKKd+huzb6Aiqyhqmu9rEkeLVX9BlNR9XVcDEeegu/AyTd/EJi5zed91nnhY+sgsnzSWHW4/TKdK7WzcAYvTglmxxfjh3B9hZcqKcdVQ1mhsxGvlr+DD8x/S9P6GrOtxe97tiNckjFCcnoe44RLitOhmd1p/btCKU4qhBZKy9yA+/Y7Qya8IAZd/LVxrfw8+bQHt5GcwfAETq4xxj8PhQEtLC4p9VK/qQU0jqwaf3icjuCE1lNWGapxtK8OB1gM43nEMds6OOHUc9Tr92tSvYW78XIQr/Gg7NFw4F9Db6DbKHyBIyaWpvW83PjRJEKQZS8AX3ycI0ugcoV7QT9Guan01Fagk1d9uaacDDe4u+CrWpa8bd36xpKb2pbIX8WnDJ7Sk46tT7sVXcm5CmCLMO3FK3BHq9kBStxtxtbshMbvT+gnT4Sq8iYo7LrkkuMUpwdIDccVHQgS1bo/QyZ+9Co4F3wWXvRKQsoZUhu9hYpUx7iGNVaRelURWfYlGrUZXZ6dP75MRfHRaOgek9g+g29oFpURJU/ueFHV6aMbYpfaJWf5AIeq5TtLGLhvdhZcq3an6bHCp8wc0OGUFrBucpMc/adiOTTUfo1xXjjB5GFalraJ1qFOjCoO3NOISJy2H2w5R+ynyvkjUJOLxWU/g2sxroZSqhueUoKvpqzelkVNDC3iRmKbETTnXQp67AkgtDX5xSnBYIK4infzvQlz9KeBygE9fBOf6P4HLI538vim/YjAuBROrjAnRXCWTyRAeHu7T+yVlAEajkX5xjacvWsaV57ITH8z9tDFqH871nKO350Xk42oirDRTsSBjIZQyZYDN8pv7pjd5LKAEs/yW/t20cYIITZ4Lbvrt4KIFUYrQJMBXnedeYHVa8XnjLvz33H9xpOsw/ZyQRqOvFd6PBQkLg688YhhlC581foaXz76Isu4y5Ibn4mfzfoGVqSsvX1NLXr+eWoj7uvUHi1PX1BvApy4Al1IKTqaBQadDREREcE9jIvXNdbshISl+2slvBEdKFJb9CK4p17NOfkZAYWKVMe5pamxEdHS0z//wq9RqGrE1m819VlaMcZra11cLkdOWfTjacZQK1mhVNG2IurvgHurnGamMFAzbdTra/OM3s3zPSNGBNaXd5/vN8iVy8BHELD8bXNEt/b6kxAYqCLwoiQsCKY8gjVKf1H8Ck8OIgrACfHfWEzSSGq7w7UljICDvBxIRfrX8FdQb6unggf+39H/o+2PIE9U+cTqgW9/Q7Ban0+AifrI0rV968WtGGtKCFXJi3nLM3cn/Pi0n4SIy4Jr7dXBEcEeNoomMwRgFTKwyxr0QaWpqRm5ujs/vm0RWCQaDgYnVcYbOqqMpfRI5JRtJ9SskCsyMmYmvF30DpQmlyArL9k/EnJrltw2aby/UlVYNNstXRwup+4Tp4ApvFOpKiSANTx1klh8sEBFH6lA3125Cs6mZpsZvzb2Vmt6HOEOCP1I4BEa7Ae9UvYM3Kt6g5R/LUpbjp/N+jqlRU4cQp3WD0/q9TYI4jSuCa8oG8GkLhxan4wA6+pak+Mmmq6Hjbkn0lArUhJmsk58x5gTfX0QGwwt6dDpYrRZEx8T4TaySUgBGcEOmHZ3sPEGnRRFxSmomCTnhOVibtpYa8s+ImQGlL5s/nDahu34ob1Kb0JhHG2giMtxm+dcNjpJexiw/WNDb9PikXqhDPdV1ik7guir1KqxPX4/pMTNoV7wnGj2e6DB3UH/U96repQ10V2dcjTvy70JaaFq/ONXXD07rDxSn5LV0p/XHbb0m7eR/XxCorSfAy7Xg8q+Bfc1vqfBmnfyMYIKJVca4prlFqOeLjory+X17xqyamFgdNR0d7dD3+NYGrNXaijJbGc6YzuBI22FYXVZqLl8SX4Jb826jl9GqUZ7EENFCzfIvnHFfBVEPMcsXUrq8MkwQojH59Avf40vKR6TRbunxBJnItKdlNxWoXzZ/SbMXZMjB8wt+iUWJi30r+AMMmSr2ytmXaXRYLlHgxpyv4Na8W4X3CYmcnni9P63f20g9Z/n4IrjyrxXS+inzxq84JVj1EJd7Ovl3AxIZuKyr4Jj/HXBZK31mWcZg+BomVhnj3gkgJCQECrew9CUkpUkEK4usjg5S8/viCy/A5RKmII0UHjx6Zb1oUjehSdMEvVwPMS9Gcfxs3F/4AEoT5tFI6ohGXLocVHyKOyuhJXPuzU0Q69y1pRYhakiiaggjZvnZ4HLW9PuSkgYndfS4TpUSQXq66xQVcdvrtkNv1yM/Ih/fnvEdrEpdjSiV708GA8npzlO0s39X4y76XB4q+jpuiClBaMtxiD99Voic6hsEcRpXCFf+1UJaf7yLU4LTCnHVJ4IXavUnQid/2kI41/2BnliN++fHmBQwscoY17S2tCDSD1FVD2QqFhOro/fBJUJ10eLFiIuL87qZp9pUhYO6QzikO4hWWytUEhWKw4pRICtAx8EO3DL3NmRnD7Pxw9JzcYS0zyzfSXeRydRAVC71IuUyVwywgcqYcB6SzcZm2ii1ufZjWpMaq4qlZvfrMtYjK2x8j8UkAnxvy14qUo+2H0GqJhFPJ67CNXo9lJ/9abA4zVvvTuvPA1Tjr0HsIjiX0MlPUvwVH9GyFI64Eix9WujkDxnBIAMGYwxhYpUxbiG1cm1tbSgqKvKrWDWZmFj1BXK5nK7nlXDxLpzpOY19Xfuwv3M/uu3dCJOFoSSqBA9GP4ii8GmQiWVUjGyq/BinTp4cLFaJWb6+YWizfHNH3258aLLbLH8Z+Nn300ipKyIbOoccEZGR465ZyJumok8bdmBzzcfUGUElVWF58gp8f/ZTKI6dDck4r1V0ck5aZ/vy6f/FOUMtCsVa/N4ALK/ZDzEOCOI0d507rT9/YohTTyd/63EaQfV08pN6adfsB4SRp2QQBIMxTmFilTFu0em6adQuMtJ/jSqkDMBkEiyFGP6DNLmc0J3Avs69ONh1EAanATGKGCyIWYB5UfOQH1YAiWiwiCJJ96nJIeg9/V/wO05Dpq/tt4HqM8tXuRuassClLeyb3kSsoYY0yx/mnPvxKOCIdRepQ/2i6XPakEbsup4r/SntgCeCdbxj7a7Ghyf/gVdav0QLb8MCswVP6XsxKzQEfMZacEsXwEkjp0EwfcyHECu0vk7+7mrw6hihk584TLBOfsYEgYlVxriFRFUJ/har3d3dfrv/yYzZacZR3VHs69yHw92kQcqCJFUSVieswbzoecjSZg22luIckHdXQtl+DMr241C2n0CmRYiU2o9HQRQ/BTwxXZ9xJzh31/1YmeUHAyTyTEaFbqr9GNtqt6Lb1o3MsCw8WPQQtZuKVft24lvA6W2ijVC9tZ/hPx0H8IbcBYNYjNUuGf4QvQC5s9bSbn3nOHBd8BpjKyRlH0B85h2IW44Lnfx5V8O+6pd0slQwWp8xGKNhQr2jn3nmGTz77LODbsvLy0N5uWBjw5hYtLe3U/9TfzRXeVCqVLRBiOEbeh29ONR1iArU47pjcPAOKkpvSLmBCtQUdUrfviK7AcqOU25hegyKzlMQO63gxHLYoqfCmHU1rLEzsK2sBy55KG6//c4xfW7BQru5HVtqN2NT7Sac11dTh4Q16WuxLn098iLyxu80Nrc49XTrtxgb8HJoKN4NDQFUYlwXU4Lbpj+MpBjBIzWIrfdHhrWXTpISOvm/BEQScNlXwVH6LXDZq1gnP2NCM6HEKmHq1Kn49NNP+36WSifcU2S4aW9r8/mI1aEiq3a7HU6nk72XRghJOZ/Xnseppj/iXFUl7eovCC3AnRl3oTS6FHHKOFpvJzW1QHF+s1ucHodcd44a6LsUEbDGTodu+kNUnNqipgyyg0qwVWHf3r10eANxhpiMmB1mfNa4E5tqNuFQ20E6gWtJ0lI8MuPbKI0vvfyo0GCltxnieo/P6V7aBEeoiMvDC3Fx2BoBaGUa3Jl3C27KuQURyomV3u/v5P9USPFXbQdcdvCp8+Fc+ztweddMnHpbBuMKjMO/YJeHCIr4+PExs7ipx4LmDjNCbVKIJmgzhy/hOQ69vf3rdbalF2lJ8TDYXNDIxRD7IWKkVCjoJYmuhoaOv8k0Y52G/rxpF3535HdojWpBPgrwYPZDKIkuQYQ0hIpRZc3Ovsip1NxOf88emk5FaW/BbfTSQYzaL/PapqSk4IBYjMqKChTPno3JApljf7j9MK1DJULV4rRgVmwxfjj3R1iZsgJa+TgT7oYWtwn/7kHilIuZAmfmChyJSsaLvaexp+0g4qRh+E7hY7gucwPUxL1hIkE6+ev3CJ385aSTvxccGUSw5Ck6xhWhiWN9hAxGwJlwYvXcuXNITEykEbF58+bh+eefR2pq6iX3t9lsdPPQ29vb12lONn/ym+3nsK1M+IJmjIR0gJSTnqqgzTZEsGoVEmjdlyFyCTQKMULobRJoFWJ6Kfzs3pf8v1wCuXTokwW5W6ySJiutVhuwZ0YiuUTsjRbyHnY6HPQ97ovudplMNqz9qnqq8Ptjv8Ph9kOYEz0HsyrzcEdRDhLbaqA8/T5N74udZvBiGaxRU2DIWAtrzHQaQeWUQ9QYXmYtiMsAOUEtryjHzFmzRr1eZN39/dkfDdX6auqHuq1uK9ot7UgNScVd+Xdjbfo6OgLVQ6Cew4jXjExQIin9+r1Car9PnBbAlbEcriXz4UwpxRe6M3i5/CWcPred2mk9U/Is9X71RIuD+bUa9nqRTv62k1SgSs9+AJGxFVx4GpzFX6MClY/OHXgHmGyMh8/lRFgvbsD+gdBAFz7mpBGrJSUlePHFF2mdaktLC61fXbRoEU6fPn3J9CARsxfWuRJ6enpGbWJ+Je6dHY11mQqo1SqIJmkTiDfwPAez2ULXS6/vxYED+5GdPxUuqQomBwejjaOXJjsHo52DyeZAm0G4jf5s5+C8xOdCJgYVsFTwDrhUiDnoROl4+3ADpqXbkRqhRJjKvx+b7q4ubNu21Wf3R+yiLBaLT+5r9pw5yMkZ8MV5AcRM/pXql7CpYRMS1Yl4PuV2LKk9BLXjfUiOcnDKw2COKkRb/l0wRRXBEpEPXiKcEFDIR24E7gtJSUk4e/Ys2lpbIFcoR/UeMxiIVRkfVJ9JnU2Hz1o/w47mT1FlOIcQWQiWxi/FyoSrkBeWL9Sh2gGdPfBOBsNdM7GpDYrmg5A3H4Si5SCk+lp6uyMiB5bE+bDNfhT2hDngVJFwcA7sbNmBtz97AA2mBhSGF+G5mT/D3Oi59Lka9MI42/HIwPWS9jZAVfURVFUfQ9ZTA5cyEqasdbDkXANH7PT+jMIEdKiYCJ/LibZeDodjkAYabnBiNJDyrUknVteuXdt3fdq0aVS8pqWl4a233sJ999035O889dRTeOyxxwZFVklakdRC+jvtGxYWhuRwJX2sierp6OszMPIBIutFTkDO2DqxdErisGtJyZmmzcXDaHNRYWu0u2gJARGy9Db6MxG5wm097v1aLKE4fKgH/KEeej8RahkyotTIiNYgI1qNjCjhMjlCBZlk9K8jeY5kEEFhYSFCw0Y3XYaeXbtcEEsko26sOX3qFDo7OzF3bsmQ1kjvVr2Df57+B/1D+Z3wWbit5jAUZ56HIyIbn2IRYhfcjtDM2X1fwORfXyVwU1JTcejQIXR2dmFqYeEoz/JFQfGZtDqt+LL5C2rav791H339FiUuwgPTHsSChAWQSfz/RTKqNTO0QtKwt78pSnde2D86H1zWctioCX8poIkB+S3SHuRyGPFR9ft4o/J1dFg6sDhpCX5S+iymRU/DRIHvbYWm9n2E1G6BpOUYeLkGrpx1sK16Hlz6YkjEUgQuhzM+CKbP5UReL7vd3ned/C7JWvkbiUQy+cTqhZDFzs3NRVVV1SX3USgUdLsQ8gIH4kNBvoAC9VgTAc966bq7aVremzM/8rsqMaCSSRCjHb7Ye/2117Bo2QpEpOajptOEmk4zzneaUNFmxJYzbTDbhQi8VCxCSqQKmVTECptwXY0I9fA/9KRshXyAiRNBVtbopgiR4yclDMQ1YbRitercOXp54Xt1X8te/P7o7+jc9RvEkXi47gwiUQOuYAPs1/4dncpM7P/XP7EqJA1hPnyf05MPJw+Lk4PFJQMXEo8vT9cgMTOPrrdYLBp3n0kyset4xzEqUD+p/wQmh5EKtSeKn8TK1KsQrgjOhhq6ZuYOSN3ilNRcEs9PAhedBz5jKRxLfwgudT4Vpx48K9xl6cKbla/j7XNvw+qyYm3aOtxVcBcywjIxIbAZIK7YBMmZdyCq/QIq0smfuQKODf8Cl7MacNfdsm+BS8O+K/2/XgP3DdRaD/cxJrRYJdGp6upq3Hkns7SZaHR1dSE0NCwgH3hyMuOyW5EfH0K3CwVTu8FGxSsRsUTMkutbTreiWW/tK7UMV8v6RWyUGpkxwvWUIaKxRICTuuu21lYUFBQgWKnrrcMfDz+PL9sOYrYD+HV7C3LD1HAtfw72qTf2dSrznZ3geMDi5NFpcsDi4Po3JwfrwJ/7bueHuO3ifQdXsiYD7cCfyj+nJw4xIQrEXriFDvxZKOkIBisnspakDpVYTjWbmmnt6a25t9Kxp6QmNSgxtkJctxeSut2Iqf2SprEJHBlVm74YjiU/EMaXai/t59pgqMcr5a/g4/Mf0RrUjdk34Na82xCn9m4sb1DitEFcvcPdyb8NImK7ljofjtW/RlfcIoQnZDDhxWAMkwklVh9//HFcc801NPXf3NyMn/zkJzRCdeutt471oTF8THd3F2JjA2NqLpcrYLVYh/w/InTiQpV0m5cZNej/rA4Xarv6BSwRs+WtBipkL4zG9kdhBTEbmZCKs8cPUzEcDGJqIAZLD/659yd4u/1LxDqd+I3OhJzwpTgx9Vm8J8mDrsmB7soa6MwOdJvs6DLaYLDNxksfk264Sw9YUEhFUEnFUMmETem+JLeFKWV9t/dt0sH72Yx67Nu3DyVLVsEp19KTCLr1WnG4Tkevk2MaCGmsGyhmY7RyaKUc0mKtiA9V9olbrcL3orbH1kPHgm6u2YRTXaegkWlxVepVWJ++HtNjZkAcbLV5xjahGapuN0Qktd9d1SdOLYml4Jf8gI4wvZw49XC2uwwvlb2EnY07EC4Px9cK78eNOV9BqHycO27wHF0bSZm7k9+qBxdbCNfi77k7+ZOE5pdJXoPKYExqsdrY2EiFKYm6xcTEYOHChdi/fz+9zph4tatZA+fB+xGFQg6rdWixejmUMsmoorFyFOA/L1dQkeQRShfKJY9+Eg36efC+pIaURHD6fvfC3/HsL7r0fYt4HqEmEVKNL+APPT+GXcTjRp0Yxu6VeNK5CL2dGqjrJYhQtyJSI6dp+NRIFWYkh0HG23H68D7MmVmE2KjwQYK0T5hKxZCMMG3vgeNUqD/mQCI6sXDu0BFpu5NDh5EIWLeQ7dus9LZz7UYqbg22pkG/R46RRGIvjs4Ojtiq5dIres7uad5No6hfNn9J3wvzEubh+QW/xKLExVBK/TfgYuTi1J3W7xLKQOh0sLSFcCz+Ho0UcuoY6HU6REREXDZSSJ7rgdYDePnsizjYdhBJ2mQ8Wfw9XJ1xTXA9b2+hnfyn6DQpSdn7EBlawIelwjXrXnBTbwAfkz/WR8hgjHsmlFh98803x/oQGAGAdA8SwRooA3iSlrdafdNNP9xobGWrHv/56BMkxicjKlrYx5Py9ohZYq4/8D/4ofbhedrhKZXJqOjs+3/PAw6+C/p7SpcJcfbzSLDVIMxejXb+PKqkOuyPkeILmQyLXZFYnvAQwucuRaRWgQfVRJzKqDi/1FjcF453Yn6KCtHR/nvNiFCKi4tDXW0tFi5cNOQ+JJKaFK6i21CQ95VOp4NSE4ous2OQqG0jgpZGam0409xLr3si5B5IBPZCAUuitXZpLSpMu3CkaxeMjl4URBbg2zO+g9VpaxA5lFXXWGBs77ORopHTrkp6MxeZTSOmjkVPCjWn2gtS9FewniF+sDsaPsXLZ19Cua4c+RH5VJwvT14BiXh4zRVBia4GkjPvCSNPu86BV0WBm7IBLiJQk+Zc1huYwWBMYrHKmByQqCohUGKVeK2OJLI6EgZGY7uO8tBourCguMA/DVacAzJ9HTXnp1vPOXC6Kpx2deOASom3VSqUqeXgREC8OApxehVuT70DNyy92+tjIATiqzsuPh7Hjh4d9cQxlVyCVKUMqZGX9ysw2pzoGBihHSBu6/QN2Ne9Fxb5QYjkneAcoXDoZ8Kpn4XK2mT0nFPg05AaxIY2Dy5FcF9GaxWX9P/1CaaOwWn9C8XpwsfBpRFxGj9iN4OPaz6iNalNxkbMjZuLvyz7G70MttIWrwT92f8Kaf6mw+BlGnB56+BY+VNw6UuAIHFoYDAmGkysMsYder0gVokACwRymQyG3sD7OiYlJ/V14I8KnoeEeFz2VPWJUrmuCnL9eWo5dUYhx77QaOxXa3AqVg4H4hAu0aIoYjq+HjET08OnQcuF4L1338X05AUjP44ACBQSWSX+yKRm/XLDQHwFiaSSjdQaE4x2Az5t2IGamo9x3nUUKqkKVycvx7KktUhUTEWn0XmBqLXSMpADNd30Z4drcMtYpEbWX34wZJOYAlEaOaTDsUzrE6futH5nBb2Zi8wCn0rE6XfB0ZrT0U0A7LX34u1zb+E/FW+ix95DI6i/XPBLFEROwbjt5K/cTA37RTWf0/cxl7kcjuv+KXTyywPzd4jBmMwwscoYd+h79FCr1cP2ZxstMrkcNltgIqsDSUxIxNEjR+j0qaHs1YZC5DAJQpQI0m5BmMq6z0HqEMS2U6rG2agM7IuMwaHYSJx0dsLM2aGWqFEYXoi7w6dhWvh0pKpTB0W/2tuFSWthYd43wAQyskrs6kjZRmNjQ0DEKsHJObC/ZT821W7CF02f07rUufEleK70p1iWspwKVg+5cZdfJ9IANqiWlopaofygos2AL6s60Wm0w0XsFdyQUt8o7cV1tKlKE3ItJ5HYcwTh7Qch6/aI00xBnC54TEjrhyT4ZB3azG14s/INvF/9Hj0JuibzWtyRfwdSgtXN4HK47O5O/ncgPufu5E8phXP1L8HlXweog6R0g8GYJDCxyhh3kMENgRx9SiKrA82SA0V8giAiuru7keC+3gfnhKy3vj9K6k7ly4xCYxAvEsMRmgZbeDbKsvJxTKvAUVcPTpqqoHfoIYcN+eoC3BC+AkXh05Adkg2J6NLin5QSEEZkF+YpoA1AZJXUrUZHR6OpsdGvj0OEZYWuAptqP8a22q3otnUjKywbDxY9hDVpaxGr9t6pgpwckOY0sl3YlDcQIlSJy8JgUWuFuacdkZ1fIK31KKbYTiILDXT/81w8PuEKcAhXoVo9HSJxImL1CsTWKBDbaUFsaNOo7Lxqemvwf6f/Fztbd0ApUeLm3JtxS+5tiFINrsceF5389fuoF6rQyd8DLnYqXIueFDr5w5LH+ggZjEkLE6uMcYe+V4isBgohsmoLuI1UZGQkZFIpTG3noeJqIO8ZIEp7zkPMCQLaqYqGPTwbptQVsEdko1Ubj8O8Hid7y3Cy5yQ6bBUQ28TICcnBqvjVmBYxDfmh+ZCLhz+owGwy0Wkmw43wDsQTAwzU2hH3j3Pnzvnl9Wo3t1MvVBJFPa+vRqQiEmvS12J9xtXIDc8NyHMkrgmkrjVGYkRR736Iu9xp/Y6z9P+5iAzwBUtgTZ6Prug56OIjEdZrwzSDDfHDtPMiTWG0/OCCkoO4AWUI1YYztGmKRJOjFFH4RtE3sTHnBmhl42j+EnmPtJ+mXqikWUpkaAYflgLXrHvATbkBfGzw+hwzGJMJJlYZ4w5Dby+SkwMX5fBMySJd9X4dP2czQNRRDlHHWbrJ2svwqOs4VCeEqCYnUcIengVbZD4MWdfAHpFDxWmvRI5T+lM41XMSJ3q2obFZiKila9JRGlWKXFUeimOLoZGNvLbObDaPuKHNUwYQKKKio3Hy5Eno9XpaFjBazA4zPmvciU01m3Co7SDkEjmWJC2l3fwl8SXUzD4gmLsgrt8nCFPSENVRRm/mIzIEs/l5j4BLXQCEJtLbiWyOdm9IuvTdXsnOq5rYeRls6LU66amHRFsBedQuSNW1EDvjEO+6EymuEjTVReItXSdiQwxe2XmNCT11tAaVGvZ3VoBXRdKJa7STP5l08geZxy2DMckJwr8iDMZl4Hk6mSygkVW3WCWlAD4Rqy47RF1VEHWUQdQuCFMSFRPpG/pS+HxEJviYAtTFrUJ1rxxFq26DU5sMiCWwuWwo05Oo6QmcbHkT543nwYFDvDIe08Kn4ZbUW1AUXkTN1j1uAGrp6NZrNGK1rwwgQERFCenn1taWEYtVYrd0qP0QNtV8TIWqxWnBrNhiPD33R1iRsgJaeQCcKMzdEDfsg6hu9yXE6cNucXoZJToMrmTn5anL/ah6K14pfwn1xvNIVuVjmvb7UDuL0GFwoFlnRE1XJ9qNNphsV7bzuqhhTKuA4hLWZz6DNJiRTn4iUJsOgZepweWuhWP5M+AylrJOfgYjiGFilTGusNlttNtbFUCx6rFAsttsgDe1sjwH9NQLQpRs7WVC5LS7CiKORKkAPiQBfMwUuPKvBR87hQpUPioHkAnCofvwYRzesR0cZ8SphrepQK3orYCTdyJCHkHF6drEtbQpKlbpv4leFouVdtqPhECXAahUKqhUaurvmp/vXRq3uqcK71W+h11tn6HD0oHUkDTcM+WrdFZ9olaIWPoNi45261MbKRI9bT9Db+bD02mXvqP0YaFbf5Ti1Nuo8gfV7+O1itfQZm7FgsSFeLrkKcyMmdX3enq8aT1DAS5n59XcY8Hxhh609dpgcw72Zw1XyQZZdw0lbr228yKd/Oe2QHKadPLvcnfyL4Pjur+Dy1nLOvkZjIkkVh977DGv7/jpp5+mNXcMhi+xWARz/jGJrDoG1/YNwtRBo6Qk+uVJ44s6Kmh3PoFXhoGPLgCfOg+u4nsFURpTAKjCLykS9rbswUfdH+JA8gG8c/IdaKQaFIYV4d7Me2lTVIo6JWAC0GIxQ6Md6Rd74NwAPERGRqC9rW1Y+3ZZurCtbiutQ63QlSNEFoI1aWtoHerUqEL/rTEVp/1pfVH7GYjIqIfwNBoxdZR8U+jWH4PGHp1Vh/9UvkktqIwOI1alrcbdBXcjOzzHazuvoSARf4PVbeN1kai1orbLhIO1I7TzUosQ274HsrPvQVy5FSKnBVxyCZyrngdXQDr5x1njF4PBGJ5Y/eMf/4h58+YNOwW6e/duPPzww0ysMnyO1SJYSCmVyoBHVh0OO2A3CiLUncLvi5qaO+k+vEQBPjqXRkm5/GvAxQjRUmoPdAXRQzw6yQjOnQ07sLdlL03354TmIE+fh7VT1mF+9vzLduz7EzIUQaPRjq5mNYDNaWHh4WioF8oqLmVYTxqDiEDd37KPClIy7vRrU7+GAuUUxEbFXnZ06IjFKU3rDy1OXSVfd4vTFIwVTcYmvFr+Cj48/yE9ubg+63rcln87EjS+jSqT9Q5VyeiWHasdtZ1Xl9GKmXwFNkj2IEtyAEqREVVIxW7VTTgdtxKS8DTE9ioQd9aC2JCOPmFLxgKLRznml8FgBFEZwPvvv4/Y2OGlGQM1WYgx+bC4J0mRVK9f4HmIbTpIjS2QGZshNbUgtKcet/BHkfrem5CbmgfUlWZQIcrN+qoQKY0toLfBi4YbvU2Pz5t2UYFK5qY7OAcKowqpBdLylBVI0iThD7//HSJsEWMmVEljGZkIpRlhNLtfqwZOFJBa1bIzZwbVGXM8h+Mdx2ij1KcNn8LkMGJa9DQ8UfwkVqZehXBFeF9K2ydYeiBu8KT190LUdloQp2GpNJ3vmvuQkNYfQ3HqoVJXSTv7P6nfDq0shEZRb8q9ma7JWHJZOy/Syd9RBvHpbRCXvQdxbxNsmkQ0Jd2C3VGrUYlUKmi7eq1ob9LT650m+6ASaqnbWWGoCWIDI7akRGHcTt1iMCYAw/pWfeGFFxAWNnx/xX/84x8jrm9jMK4U4SNp+RGP0uQ5SCydkBIhamyhYtQjSoWfmyF29g8A4KQqONTx6CYNxImLEZG3UBClUbl9daXe0m3txq7Gz7CjYQcOtx0Gx7swI2YGHpnxbSxLXo54zeAJQqQWkDggjBXEtmt0pReBbbAieP5edXV1wa6xY3PtJrq1mFqQqEnErbm3Yl3GeqT60rCeitMBaX2POA1NBpe2EK45DwqR0/DgMMknUcsj7YfxUtmL2Ne6DwmaBDw667u4LvO6QYMMgo6eekiIOD39DsSd5eBVEdSo3z71BiClBEkiMTU/WDXErzpdHLpMdrRdUEvrKzsvUv7ARC2D4XuG9Y1/993ezQK/7bbbRno8DMZlIZOkLuv1yTkhNbf1CdGLRWkrRFz/F5FLHgKnNhFOTQIsiSVwahLhID9rE+h1ThEGF8fhjddew9X51yCsqGhEx91h7sDOxh3Y2bATxzqO0tuIndQTxU9gafJSRKtiLvm74RER0PcII2bHApsnmj3KyGogMclNqAqpwncOfhvV5irq/XlV6lVYl74e02NmQOwLayKrflC3/sXi9AGhWz9IxOlApwMSzX+x7EWUdZ9BTngOfjrvZ3R9pOIg7Yg3dUJc/qHQyd94ALxUJXTyL/sRbZiCZHglamQsbVyokm6+s/PqRyUT99fTXsL5IFrjR/s7BmOCMio3AGIhRNJmAwkN9X4cI4MxXBxWM2KlBqia9wtC1BMR9Vw3t0PE91vnuJQRcGgE8WlKWSYIU22CIEg1CeDlV67D9NQuklS4N7SYmrGjYSdN8Z/sPAGJSIqS+Ln4wZwfUp/OCGXEsFPa/p7INJzI6shLL/yvVk1OE071nMIx3VEc1x1Hq7UVokgRpnBT8PyCX9J6VKVU6SNxKnTri1pPucVpkiBOZ99PL4NNnHogY2BJdPnlsy+j3lBHrbj+tOT/YX7C/OCMBtqNEFduEbxQSSc/zwud/Nf+jQpVDOOz6087L4LF7rqEqBWEbVlLL71+oZ2XRi6I5gsjtTEDorXkutLfdl4MxkQVqzU1NbR5ateuXTQl68EzLYbYCjEYPsPlgKjlOBUH0rrdWFe7DzLeBnxCJJAILnUMFZ1EgFrjZtBoKI2KUjEaTyMwo4W8ryUSCRzOy7gBuGkw1LsF6qco6y6jU6JKEkrxTOlzWJy0GKFy70/mwkLDqFcqOTH0edPPMLC5R82OtKnNHzWrLt6FakM1juuO4ZjuGMp7y6nXbIIyAbMiZ2FmxCy0HGim1lNXpQ6VEB4G1t4L0vqnIOI58CGJgjgt/pq75jQ1oM1j3kIa996pehdvVLyObmsXjeQ/V/ocCqNHliXwKy4HxDWfCSn+c1shcpjBJc+Fc+XPhU5+DR1xEDSo5BKkRqrpdjkG2nm16a2oa9fB4JSgw2i/rJ0XGX3rGYPrMzsvBmMyiNU77riDCtN///vftC41KM/IGeMXYphPxKknetV4kH5h8XINuORSnIxYg055MgrmraFiNFBG3qRG9lKR1fP68zR6SrbKnkooJEosSFyA2/LuwMKkhaMePxkSGko/c+TkMJCWXR6Ivyz5nPt1etcw6LJ10cjpMd1xnNAdh8FpgEqioh6zD2Q/iJkRMxGv6q/3/VL7BfT6Hu/Eaf0+hFbugKL9yBDi9F53Wj8tqMWph05LB96oeAPvVL0Du8tGSyDuLLgL6aHpCCp4jn7OaYr/7H8hsnSDi86Da/6jcE3dKKz3OGegnZfQxKfo86UNiJ1XiAJRGjktg2AwJoVYPXHiBI4cOYK8vDz/HBFj8onT5mO0W3qwONWCSykFt+gJKhD4+GngIMaxV1+FRqOGMzSwHdRiiQQup6vvS+VczznsaPiUCtSa3ho6IWph4iLcV3g/Tav6skHF465BpkiNiVh1OGid8MhPTEdWBkCsu87oz/RFT+vN9RBBhOyQHDoIgURPc0NyLznuVKPRoPFy5RPEMH5QWv8kFadSTRy49EXgZ33VndYfH+LUQ11vHV4tfxkf13xMI/sbs2/AbXm3I0Z96brosYBav515hzZLkelt5KTANf12cGTkaezUcbXmwWjn1Wm0w8X1f/aIQ1eU9uI62rgLyhAimZ0XYyKI1Tlz5qChoYGJVcYoxak7tUrEqdMypDi9yAKK46iN0lhE+Mgf7xpLDY4dP0ZFaqOxkZrHL05agoenP4LShFIoJJdp/BoFWvfULM9AhEDjsNsv39R2JYZZBkC+hIkgpdHT7mNUqDp4B6LkUZgRMQM3pd6M6RHTESobXimFWqOBwWDoK1ESxOn+/rR+6wl35DRB8DmdeQ9cKfPQzYchIjJyTEouRsOZrjN46eyL+KxhJyKVkdT+7IbsGxESiNGww0XfAMmZ94Q61I4y8MpwcPnXwlV4I/iUUsAXjW8TnMvaeQ2ACFWd2X7RFDGP88Hpy9h5RVPnAxKdvSBay+y8GONFrP7v//4vHnroITQ1NaGwsLBvuo+HadOm+fL4GOMdpw2ilmMD0vqHBHGqCBHE6eLv0bo/Pq5oWP6kTqdj5LZVXqC361FlrMI5wzlUGc7hdORpWLosCDOEY1nKMjxZ/D3MiZsLWQDKEDzR1DETq+7IKvwQV+119NKGKBI5JRHUbns3jQZODZuKOzPupNHTkU7qCpPYkOmqArb/CLLmA/3iVBsvpPVn3iWk9Yk3rvv+edIw6iuf1QBAhPj+1n3Ufupw+2GkaFPw1Jwf0Olb/jp58hpzl9DJf5p08u8XOvlzVsOx5ClwWSuG3cnP8A4JFZ1CTeuUhEvvdyU7ryOXsPOSSUT99bTMzovhZ7z+1u/o6EB1dTW++tWv9t1G3oiswYrRJ06bjw5I6w8Up/PALfm+EDml4lQyIuF04QnSaDE6jbRZxyNOqw1VaLe10//TSrU07Zxnz8OsmGI8sO7BS6ad/QWJ8JFOfI+FVKAhtbq+imY7OScqDBU0ckoiqNXGatJPjzR1GhbHLsaM8JmYEjbFO6HFc5D1NkCuK4e8uwKK7grIuyuRaenAAhJhOhsDPmMxXDPuBE9OjCIyx32Kmazjp/WfUiP/yp4KTImcgl8u+DWWJS+DZASfK59jN9EGKRpBPb+TdtnxGUvhuOavQie/IoiivZOcYLDzitEqoFEE9u8qY3zh9bvj3nvvxcyZM/HGG2+wBivGAHHqTq02EXFqBa8IFSKnoxSnAyEnQuSkSDoKsWp1WXHeeJ5GS88ZqlBlPIdmizCVSilRIVubhfkxC5CtzUZOSA7ilMJ7fHP9JqRIUgIuVD0QsWp1W0iNhViVjUKskklR1SHV+H3171BmLIPFZUGINISm9tcmrqONUVGK4c1rJ+8teU8VFaV9wlRXCbFTiDo71bGwRebBkH0d9Oo0fHigBquv+zrSMzIwEbA6LXQU6mvlr6LJ1ITS+FL8bdnfMTtuztj/LSad/Oe/EARq5RaIHCZwSbPhXPkzmuqHdngTEBnBidd2Xhc1iV3BzkshGSBiB7sfxGjkUPA2qLQuqBWsVGQy4vU3b11dHT788ENkZ2f754gY40CcHulP6zcd7henqSRy+gMhrR9bOGpxOlTtJGG4ZQBkdGmtqbYvlV9lqEKDuYFaHJFUc4Ymg6aZv5J6ExWmSaqkS5rFk+gmGQ4wVqhUajo6dKzEqnIEHqs6qw6vV7yGNyvehDXSgjxXHjam3EDFaaY284rjY8XWbii6KyHv7o+YynprhVS+SAxHWAYVpqbU5bBH5sEWmQtOGdn3+2S9dAffhMU6NuUTvoSM5X373Ft4s/IN9Np7sTLlKvxq4W+QH5k/tgdGxhM3HkTY0dehrNkGkaULXFQOXPMegYtMlIoIMucBRlDaeV0oalv0FpxoZHZejFGI1eXLl1NHACZWJwlOK0RNR/rT+h5xqgwT0vpLfyhETkn3rp/Tj053iYlUIhnSd7PBVC8IU5rOr0KdqRZO3klFUbomHfmh+bg66Rpkh2QjVZ3qVZSURK0419iJVYVSQS2kxgIS0ZZJhx/NbjO34dXyV/B+1Xt03VbErAR/iMPtG+6gHfoXQTrwDY3u9D2JlArClAx48Iy8tUfkwhI/G/opt1Nhag/PBn8Fk39SLkIe32oZm/IJX9BqasVrFa/ig+r3wfEcrs28Frfn34lkbfKYHpeoo5xGUIndlEhfTx0UnEU3gy/6inCiOtZRXsa4svO6FB47r1a9BedbumDmZeg0epwQmJ3XZMJrsXrNNdfg0UcfxalTp1BUVHRR/eC1117ry+NjjJk49aT1D0PksgniNHV+QMXpRYfm8TkVi9BobhSipe46U5Lat3N2iCFGsjqZ1pmuiF+BHG0O0rXpNJI6Gkhk9cJpbYFEIVfQwQBjJVaHE81uNDTQbvSPaj6i/qd3FtyJm3NvRXdTN97a/ybdh7yXZD3V/cKURExJGt8hPDenKoaKUUPWNe5oaR6cISkj6hInQpWUL1ht40+sVuur8XLZS9hatxUamZpaT92cewvt8h8z9I3UZoqm+dvPCH8T8q+Fs2AjukLyEREZNe4cFBjjw85Lq5AgSua4yJv2SnZennKEyjYDdld10iEMw7HzulDcMjuvcShWiRMA4bnnnrvo/1iD1XgVp4cHpPWPuMVpuJDWJ7O3SVo/ZkrAxemFadD/1v4X20K34c2a/8BaLaR2E1WJtL50fvQCGjEl6WUilHyN0EQ4dmJVrpDD6bjyBC1/QD7TZILX5YTVi2f+jW312xAuD8dDRd/AjTk3CsMQrHo4a7diA78FOds/gMJQR8fh0jR+aDrskbnQpSyGPSKPilOXani1q8NFLpONWfnESDjecYx29n/Z/CXi1HF4ZMYjuD5rI9SywPvrUiw6atRPDfsb9tFoNpe9Gg7i4pG5ApAqhJO4ceSgwJh4MDuviY/XYnUso0sMH+CwCOK0L60/UJzOB7fsx+6a0ylj7nlIZpnvad5N55nvbt4NF+dCAhKwPnodpsVNpyJ1tNOhvCoDGPjXK8CQNPxYnQiSz/xQYvVsdxn+feb/8FnjZ4hTx+OxWY9jQ+Z1UFp6ID75FiSVmyGq240kzgkRYmGKng/D1NsEYRpB0vi+P6m4EBIRDnaxStL7XzZ9SaPSJztPIDM0E8+UPIvVaWsCYo12EQ4zxOe2UcN+cTXp5HeBT18Cx9X/Ay5vPevkZ4xbmJ3X+IV5RUwacepO6zcTcWoHr4oAlxJc4tSTzjnVdRKbajbhk/rttJkkPyIfj8z4NqbJp+Gzj3diSexSREYENh1KI6sD0keBRiq79LjXQIhV8YC6rqPtR/DCmX9jX+s+pIak4kdzf4z1oXlQnNsO8d4NEDcfAS+Wgk9dQGe61yoK8PrHu7Bx1g1D16z6EcllxuSONQ6XA1vrtuCVsy/jfO95TI+egd8v/gOdhHapRj+/QU4oaj4XIqiVmyCym8AlFsO14lm4CjawTn7GpMJXdl7nOwQ7L71l+HZeMQOuMzuvfka0EocOHcJnn32G9vb2iyKtv//97zHW/OUvf8FvfvMbtLa2Yvr06fh//+//Ye7cuZg84vRQf1q/+ehgcbr8GXdavyAoxOnAesfNtZuxpXYzGowNNAW6MesGrMtYj8ywTLoPmZxGGIszUo+X8FhBIptjldUgz1ssEmFv8x78u+z/cLzjOLLDsvGLggewStcB2ae/grjrHHiZGlzmcjiu/Su4rFWAKpz+vrO6GmOFRCwOOrFqcpjwfvX7eKPiNdqMtihpMX4w92nMiJkR2AMh3thNhwWBevYDiMyd4CKz4Sr9FlxTNgKRwueOwWCMzs7L6nBR54M2H9p5xbqjtUTcKmVB4K0cbGL1F7/4BZ5++mk6bvVCn9VgCGv/5z//wWOPPYa///3vKCkpwR//+EesXr0aFRUViI2dgNEBhxmiRnfkdJA4jaRpfdfyZwUj9Jj8oBKnBBI1JdFTEkUl6U+1VI0VKSvww7lPY1Zs8UXRJU/N6Fi9z8ZUrIrHRqwaHAZUy6vxaeenaGxpRKE2DX/SzsDS6kMQH98pvM9y1sBBIvQZSwGZ/1P7XjfGBUkdfbe1m1pPvV35FsxOC9amr8WdBXchKywroMch6qyE+PQ7kJS9C1FPHZ3o5Sq6CdzUG8DHTWOd/AyGjyFiMiVSTbfR2nm1G2ywOi5v5xWjlUMrdSEt1oH4MOWEsPPyWqz+6U9/wr///W/cc889CEZIZPf+++/vm7BFROumTZvoMX//+9/HhBKnnrQ+53CL0wVBLU49qc89LbupQN3d/CWt1yuJL8XP5v0CS5OXQHmZOkaPWBwTsUofc+zEqkgcmMgumYxUaaik06XICFTiTcuH8phuVeLHPUaU1nwJhKXARbrAc9eBTykZ1pjcsUIkEo9prTGh0diIV8++go9qPqQnYKRhinT3x2viA3cQvc1UnIrPvAdx2ynBFzn/GrjW/RF86vwxbZ5kMBje23m1DylqBTuvAzWCnZeTE7KRw7XzilAGn2bwIB1JpGLBAjLEMPggjRRHjhzBU089Neh4V65ciX379g35OzabjW4eent76SWJYvk7kmWyOVDeZkKIWXxJAUYm82jajyKk7QBCWg9A03USYs4BhyICPXFzYZj9FAxxpbCGZ/eLU9JP0iQ8j2CAfLiqDWXY2/4JDnbsgsnZizRtDm5Mvx8lMcsRJhfqT8+1ktfh0l6iLe0WtDsUqOqyQWs3B/AZAK1WKaQuCU419mAsqNW70O5UoqLDy+fNAxaLDSqzGLiExu+yt6LScATn9QdRaauGBU6EciKUWiy402zCPIsVclkSrLm3oSzlKlgiSX2z+86ajVc8hOZOKzo5NX3dlObAnmi02mUwmETDft3oF4Hh8p/J4VJnPIfNDW/iUOfn0MpCsS75NixPuI5e79ABHTr/vpckth5E1G1FVM2H0LYdAi+WoSdlObqXfh36pCXgPSNtmw2jehxfrtlkgK2X97A1G5oQhQQhCjWyotUXrRfVMnIVeixO6Ex2dJsdNGrbSiy9DFZUtBmo6CUTxzyn81K4cKc7XmS2OYY9gGc0DFdniXgvwzW//vWv0dzcTNPrwQY5rqSkJOzduxfz5s3ru/3JJ5/E559/jgMHDlz0O8888wyeffbZi24vr6hESIh/u17L24y4982KQbepYEWx+BxKxGdRKi7DdFE15CIXuvgQ7OcKsJ+bQrcqPhE8gvcsiCCSdUEWdoxuYnkXOEcYHPoZcOpngbPHjfXhTVoixW1I0h6GVHMOXZoO6GQuSHkSPbWh1GJDijkEFmsayrl0lPFpOMulQofQsT7scQIPiboa8qjPIdWeA2ePhL17ERw9swHe/539CtixUnwU10n2YKn4OCTgsIcrxIfcfGxzzYEBY2SBxWAwgh4pFavH6PUFV9+CKYlhfn9Mg8GA/Lxc6PV6hIaG+k6sEhW8fv16VFZWYsqUKRcNBXjvvfcwnsTqUJHVlJQUtLa1X3bhfBVZPX2uFgmWSoS2H6SRU3XnSYh5JxzKSBjiSmAg0dP4EljDcsZFLZnJYaCRpL3t23Gu9zSUEhVmRy/GvNirkB82HeIrjNi8HKRh7ssvPsfsOXOgDQmMZZWHI4ePUM/O5StWYiw4deokzpw+jRVXefH4PAe1qQmyjlPQ2U7hrLUKx0Q9OCMTwyUSIdXhQjGnQqEsFekhM+EInQJjSCY4T8TNzWc7P0NuTi5mzJw5omNvbmrCJ59+QqffKVWXnzrlaw4dOAhtSAgWL17iRQTHQE9UvYngcLwLRzq/xObGN1FrrESqJhvrkm/B7JglVxwrO2o4J0Jb9iKy5iNE1G+HxGmCKWoaujKvhS5tHRxq/9bqj3TNJitsvbxnsq6Zk+PRY3ZQb9hud3SUXNeZHOh236YzO2mt64UWWuEqKa1TjVAL/rORapn7OrmU0dsubMwiXt7b3vwXvf7Qw99GqMb/PQhEc8XHxV5RrHod433kkUeoE8CyZcsQFRUVVG+c6Oho2jXd1tY26Hbyc3z80PVhCoWCbhdCygf8PY0lfNcPseTEqxBxTvDqGKEhatYtcJIJUdG50IhEIJUrAaxsG0Ud6h7qh/pl0xd09GlpfCnunvpzLE1eetk6VG8I43pRIbMhK1KO8PDARoiaFQ4oFBIUJQsd7oGmt1aMDpkNeTFDP28yAlfeU9U3FapbV4bDtiZ8opBgv1IJg0QMrVyEWdIEfCtsKoriliA6esaw6prPSK1ICxWN+LlrbF04JjYjO0oBjSawr1udzIYoTciwj52cjOt0HCIiwob1+be5bPi45iNak0pcLObEzcHjs/9C67D9+reRdPI3H6VeqJIy0snfAS4yE9y8b8I+9QZII7NAcheByF94u2aTHbZe3jPR1owMJyA+rh7f1qHrT21UkA4MJ8r6fFwViA9VYlpS+JD2Vxq5GD09PZec+HW5Uspt7utqhSwgaz3cx/BarL700kt49913aXQ12JDL5SguLsaOHTuwYcOGvjc5+fnhhx9GsEHEqVGTBmX+VRDF5I2LyOnAM93TXaeoQN1e9wn09h7kReTj4enfombm0apov72px6Irnvy9GMsTM5fL2ff8xdbuweNKuyvgMNThsEKGPWo19mq0qNMAYk0I8pVJWB0yHbMTlyA3NHdEUT7aUT/GTUqjGmgg9X1k02A34J1zb9PuftLlvzxlBX42/xeYGjUV/kTUec4tUN+DSFcDXhsHV+ENQid//Ixx9TeEwZhocAMnZA21uYVop9GGgbbdkoETskIUmJESNuRggQj18CZkTcThTV6L1cjISGRlBdZqxRuIbdXdd9+N2bNnU29VUltLZqp73AGCCWK2bdbpoIiICKoI9eVoMjZRL1QiUusN9YhVxeK6rOuwLn09skmTlx/xiDV+LD6IJJI1VrOhe5uR3PhfZFn3I/Wtv0Nq6QBZgTMqLXZHJGJvlAqnI1PgBIdYRQxmRhbj1ogZKAqfBo1EQ9//xIx/pO8xOr3LNT7/+DmdLsh82CTQbm6n/qjvVb0HO2fH1RnXUPspMhzBbxhaqDgVEz/U1pPgFSHg8q+Fa83vqPMH6+RnMPwfnCHG/tTsf0ivVGEjDUwkde+B/MmN1vSL0KmJoVg2xAAAkpIngpVxabz+K04akn7yk5/ghRdegFodfMX6N998Mzo6OvDjH/+Y1jjOmDEDW7dupZ6wjJH7oX5a/wkVqMQQnvihkkjS92c/heLY2dQDNBB4Rn66xiKy6jbGDxjGdojLP4Kk7H2IG/cjVyTDcUUq9qUV44DEgSO2ZvS6TFBKRJgWXoB7I2ZiZsRMJCgTBolSX9hdkZOEUY16HeOItPSCuvqRUNtbg5fPvkw/AwqJEl/JuQm35N3qlwwChYysrfiIGvaL6vYAEhm47FVwzH8MXPZKQBrY2l8GYyJC/j4SI37BrN96SRFKNjKtaiAkyukRndmxWszPihpkB0UM+6M0cjoNizEGYvXPf/4zqqurqfhLT0+/qMHq6NGjGGtIyj8Y0/7jCVKHurdlL/1y/qLpc1qHWhJXgp/O+xmWJi+DKgBz3S8lVscixUHSOyJ/1++YuyGu+BgSMk2objetJyVG+weXP4Wf1n2BWq4BIttZZIdkY3XiesyMnIm8kDxI/exzStbdxQWHsb63OBwOWh40Uk51nsRLZ1/C5427EKWKwjemfRMbs2+AVuaHBj+HBeKqT2iaX1z9KeBygE9fBOf6P4LLuxpQ+r8zl8GYKJjtxGDffkURarYP/tsWqvQY7CuQGqnC7LSIi3xJY8a5wf54xOtvOU8tKGNinmWe6TqNTbQOdTutQ80Nz8M3p38La9JWI1oVM6bH5/F8G1WUb4SQ6Vl+mdduM0BcuRliEkGt2UU7+Pm0hXCu+S3K4vLw18pXsbfmNcSJ4rDauRp3LLoTobLA2kiJxZKgG1nqTcPAUA2UV/oc7GnejVfKX8bRjqNIC0nHD+f+COvS10EuGbnwHRLOBVHdl8LI04qPIbIZwCXMgGvZj2iZEEISfPt4DMY4x+Zwod14CfHpvq3DaKMeokONLiVCkwjOwqRQxF0wwpT8n0rOymomhFglJQCMiUWzsRmb++pQ6xCjisG1mddifQapQ81BsOARq2MhnGgZgK/SOXYTxFXbIS77gEbQRC4buORSOFf+jE4VqnGZ8PdTf8eOz/9IhdLzC36J9t3tEEvFAReqnsjqaNa8rwggwE1a5KSGbErl8LIATs6BbbXb8OKZF1BjrEFhVCF+s/C3WJK81LcnKqT+ueUYrUElZR4iUzu4iAy45jwEbupG8FHB85ljMAKFw8Wh02i/uDveYENbrxUtPWZ0mV3QWxyDfk8hFSOurxFJifz4kIs65EltKJkMxRi/sFdvkkK6mT11qMc6jtG0/vLkFfje7O9jdgDrUEcUWR0DsUq7ykezJk4rxNU7IT77PsTntkHkMINLmAnX0h/CVXAdEJpEm9f+dfqv9DWJU8fhxyU/oY1rJM3/b8v/Ijx8bGyzpFIJHPbBXxDjAY9/skp1ebFqcVrw3+oP8Gr5K2g1t2JO9Bx8b873URw326eNj6KuKiHFT6KopJNfEwvXlOuFTv6EmayTnzEh8YVNE4l4zkoOQWp0GOLcs+49W4hSOm4alBl+FqvEAYAMASA+psMhNTUVX375JdLS0kZxaAxfQyJHpA51U43gh+rknZgbNxfPlf4Uy1KWj0kdqjd46qOdYyRWvfacczkgrv1cSPFXbhZSvLFT4VrwmCBQIzLobp2WDvzf4V/i/er3ECYPw3dnPU7nxw9MOVssFsSOUZMgOUlwOMgM3xHi/iIJtPmV1Wqll5dqBO2x6fCfyv/grcq3YHQYsCp1FW7PuxMxiKH+hD75AiSd/Gc/gPj0OxC3ngAv19LouX3Nb2i5B/xcb8xgBNKmqa13cGe8r2yaBJ9Vnde+oYyJw7D+UhJz2S1btiAsbHgF/l1dXWNSV8i4RB1q9xlsrtmE7fXb0GMjdai5tFGE+KHGqMe2DtUbyB8ukpJ2jFVk1d3gdfkdXRDV7xG6+EkNokUHLjJbSPFOuZ4Oe/BAXouXz75EBZNCIsdDRd/Azbk3X3TSQF5Ds9kMpVI5ZmLVaDRhvGG1WOglse0aSIupGa+Wv0qjqeQ7dEPWBtyedwcStYl9X4qje+BeoZP/9DtCoxzp5M+6Co553waXfRUgC+6TQsbkxh82TR6LJmbTxBgpwz6tJ96ljPFbh0osdq7JuIamlXMi+gXTeEMml9ORcIHGdTlzeZ6DqPGQIFDLP6Q1iHx4Glwz7hIEauzUQSleo8OINypep4KJNG7dmX8nbs+/AyHykEs2CQm1l8oxi2jb7f0jib1lrL6WSDR6oFg9p6ukJwfb67fTbn7ij0pODsIVEaN/MFLmQTv536WXcNmpB6pz3R+ETn7V2JRwMBgemE0TY8KL1Yk4DWGi1qHuaPiURlFJF7NSoqR+qE8Wf4+OgQzGOlRvIQbv9jEQq5zLNTiySppkWo/TFD8dd2loBh+SANfUjeCmbByyBtHqtNKpRy+UvQCL00y9Ou+Z8lVEKC8vlkxG47BqL/0pVm32UZQB+NDz1RtoNFqlxInuE3ip7EXsbdmDeHU8Hp35GK7L2jD6shfayb8HElKHWvGRUOYRP02oQ55yPevkZwTUpskjPkknPLNpYkw0WMHUBKlD3VyzmfqhkjrUOXFz8Wzpc1iWvBxqWfANbhhtZNXhA+HkLSSyKRVLIGovcwvU9yHqqQWvjgFXcC21GeJTSqg36lCetf89/1/835l/oduqo04LXyu8nzZRDQeDW6yO1RAOsuY2d/3neAitEk/gBnMD9hj24Gj0Uby641VkhWXT2uxVaasgFY9iSIDnJOX0O32d/Dzp5J/9ALipN4KPZp38jMDaNJHNaBtcGqWWSwYJTmbTxBjvMLE6DiERqrLuMpri3163DTqbDjnhOfj6tG9gTdracVWH6i0Kubyvccbv8DykphbIu8ux0PYZZhx+BfIvGsArw8HlXw1Xwe/Bp82/ZJMMMdLfWrcF/zz1DzSbmrEmfS0eLHwQySEpXh2Gobd3TCOrxFSfNLURwT6sut0AqlXyWei0deKc4RwqDRX0sspQBStnhYgXIUWagj8u/jMWJCwYVcOUqLtaSPGTrbuanqT0dfInzmKd/AyvcLp4tOitglXTZURoD7NpYjAo7B09jiCNIbQOtWYz6gy1tA51fcbVtA41dxzXoXoDMXjX6/W+v2POAZm+ForuCipOhcsKSOyCUAyBCubw+ZBf/WtwGUuAy5jDEwH1WeNO/P3k33C+9zyd+PW7xX9Adnj2iA6tt7eXPu8Lp8UF8gSBYLVaoNF4P7nJlzrO5DRRMeoRppWGSujsQkNUtCIauSG5uDntFuSF5OLsrrMozCvCwsSFI3swY5tQh0wEassx8HINrT+1r/olnSzFOvkZI7VpIvsMZKBNE9lKoiMvEqHMpokxmRn2X9vm5mYkJib692gYF2EkfqgNO2gU9Wj7EVqHSmymnih+gqb7J0IdqjfI5QrYbKMrAyAep3Jd5SBhKtNVQcwJ9+vQJsMWlQ/9lDthi8qDNTwXL7+7DetmXY1p2dMvK1L3t+7D307+lUa+S+JL8ePSZ6i5/Ggg4lyr9cN4z2HimQBlsVhHJFY9kVVva1YdnAN1pjoqSM8ZKlFpOIcmcyN48FBL1MgOycGKuJXIDclBTkguIhWRg+rsjxmOUasbr7D2QlXxHuS1WyCmI28l4LJXwlHyv+ByVrNO/knKlWya+kToMGyaYrRyaCUupMdFIC5MdZFNE4PBGIVYnTp1Kv7yl7/gtttuG+6vMEZRh7qvZR8VqF80fQG7yz6h61C9QaEkYnX4ZQASSxeNkPZHS8sh662HiEgesRT28CzYI/JgyLqaXtoic8Ff0JVP5suT8KBMeunI5vGOY/jrib/QxrZp0dPx9+X/xOy42fAFuh4dNEEhVs0j+v3hfAcTIdtqbXWLUkGYnjdUw8E7IBFJkK7JQFFYIW5I3oic0FwkqZIuO1XKaDTS+4yI7Bewlx/YsEPwQq3aDqXLDi51Ph15y+Vfyzr5JzC+smkqTAylIjQ2dLBh/VA2TcwzlMHwo1j9+c9/jgcffBDvv/8+/vGPf9BBAQzf/tE8232WCtRtdVtpHWp2WDYeLHqI1qHGqmPH+hCDAqVCSScTXWTSz3OQGhqh6C6n4lS4rITU0kH/m5NpYIvIgyVpPnoKvwp7VD7sYVnUA/NKeIYQSIdIw5d3n8VfT/6Vdprnhufhj0tGXx95IbpuHVLTUjFWKNyWWWazYAXlPRevRa+jl6bxqTjtFQSqwWmg/xevjKfp/IXRC5AbmocMTQYUEkEwe1M6Qbjk3ymPHy5J8ZeTTv5ecHFFcC7+ProSlyMspYAJiXEMs2liMCapWP3GN76BtWvX4r777sOUKVPwr3/9C9dcc41/j24S0G5pxwct72NL3WbU9tYiSjn56lC9gVgRiTkHRK0nEWKqpZFSKk51lRA7BON6pyqGpvEN2ddRUUpEqjMkachO/eHgEasDa0Zr9Ofx91N/p1ZhaSHpeH7BL7EiZaVvZ8i7o7oGQy9CQ4b2YA1UZJWIb7N5ZIMBeHDokndha/tWNDTVU2FKoqiEEGkIckJysD5xPY2YEpEaKgsd9THre3ro6xUaGjq4k7/tZH8nv7EVfHg6XLPvF+zGYvLoSRA32qEAjIDZNA0VAWU2TQzGxMOrDoGMjAzs3LkT//M//4ONGzeioKCgb167h6NHj/r6GCcszx/6Od4//75Qh5q8jI7ZJOl+MgueMQCHmZruS+v2YGrFpyjGaUg+4cBDBEdYOk3f61IWu9P4+eBUvo36e8SqXCZDk7EJ/zr9TxoBJ9ZTPy75CT2x8Ndr1t3dTS9Dhzk9zh8QoUoGEphMJq8iW5U9ldhKGgLPb0ZXYhdkLTJkajMxJ2oOrTElwpREUf1Rq0em7pHx0PS+u88LEVTayV8FXh0NrmADXIU3gk8sZp38QQKzaWIwGJfC62/Yuro6vPfee7Te5rrrrrtIrDKGz9z4EmSpsrE+72qEKMYuchZ02E0QNR2GuG4PxPV7IGo+ChHnAK+KgjVmJrZ3LUHinKsRmjMffAAaXkh00yKx4F/n/4ktzVsQJg+jJxbXZ22E/DKuAL6gq6uTXg531LG/UKpUMA1j5CoR88Sua1vtVuqEEK4Ix/yo+TAfNeOuq+5CVGS0/w+W5+HoqkOppgWyF1dB3HxU6OTPXQ/7VT8HT9wc2AlhwHC4OMGi6cLueGbTxGAwholXn3KS+v/ud7+LlStX4syZM4iJmbh+noGApI11Wh00ssGzyyenOD10gTh1ChGw1AVwEYFBLiOzoe/uxsH//RfmyVIR4kehSiKDzZZmHNcdo81uZ5LOQNOmwUNF36AjOkc9/WiYdHZ0QKVW9zU5jRUqpZI2LQ1Fj02HT+o/wZbaLTjZeaIvU/DIzO+gNL4Erc1teHXfy5D4UCCKbb2QGpshNTZB5r4kP8vcl/c6LeD0UvCkk3/Dv9yd/JO3MdEfOF0ctWBq01tR09oDM29Ch8c3lNk0MRgMHzLsb481a9bg4MGDtATgrrvu8uUxMCYbdiNN6xNhSgSqqOWYW5zGgEubD9dVv6DilI/OHZyidTdVkUlOZvfcd19idBhxsuckjumO4rjuONpt7ZCKpMiQZ2Bqz1T86o7fIDYssI1u7e0dCA8b+250IpiNRqEBimBxWvB54y5sqduC/S37aWVqacI8/Gzez7EkeekgMe8RHN5YVxF7sYuEqKGp77rE0S+cOakSTk0iHCFJsMTNhj4hHPvONqPkpseRkDXVZ2swWRixTZNIhOiQwTZNJCJ6oQhlNk0MBsNvYpVMrzl58iSSk5O9fhDGJOdK4rTwK+DTFoKPyhlW/WBISAjMXtRPXm4sJ+lEJ9HTY7pjtDudA4dkVTLmRpVgZsQMTA0vRFNNE/ZV7EWUNgqBpq2tDSmp3k288gfkBKG5tRm7m3djW+0W7GraRQUrsel6vPhxrEy5ChHKoT1Nh3pFRU6rOzLaHw3tj442Q2Lr6duXE8vh1CbAqU2CLWYajBlr4dQm0s2hTQJHHnfA+6aiogKVkkNYn8oaFH1t00TS7lMTQrAsN7rPpilaI4OCsyIjMQYyKasLZTAYYyhWP/nkEz88PGPiitOD/Wn9luOCONXEUv9KV9FN4FOJOM0eUXML6fD2ptlnIG2WVhzVHaMClURRzS4ztFItpodPx8r4qzAjYgZilbEX1aySMaMjGzU6cixmM3UCGEubuHZrO12nPfbdOBNxBq98/jIyQjNwz5SvUku1JG3SpX+ZRFJ7G6Gp24Fl/B6kHzkOjb1TEKaWzv7dRFI4NfE0MmqPzIM5dVmfECWXLlW0V04OnZ2dtERprCZ+jYUIJU1H7Qa7X2yaiFeo7DI2TYJvqOsiP1EGg8HwFawynTF6bAZBnPZFTo9DxLsEcZq2AK6im0clTi8kJCQU7e3tw9rX7DTjlP4UjnULArXF2gIxxMgPzceG5A2YETET2SHZ1Hj+UhCxOhY1o62tgr1TVFTgIro9dh1O9pzCqZ6TVKQSiykRREhRpCDdmI7H1j+OWcmzhk7jGlshbj4mvP6tJyAml+ZOEOmvhAYiSxYcEWmwJM7rE6Lk0kU8hH04iY3U+WZn52Ci2zT132aFxTFYhDKbJgaDMZFgYpXhPTYDxI0HIKrfO7Q4nXYr+LQF4CN9I04vJCw8jEZWSUTpQtFEUvvnjedxrPsoTe1XGCrobcQiaWbETNwT8VUUhRdBIx1+U5vDbh8TsdrS0gK5XE7LHvyF0WnEmZ7TONFzkgrUenM9vT1FnYLiyNmYFj4NhWGFcJqc+KjiQ8QiRlhzczdErccFceq5NArimjbGJcyAa9Y94BNmolWciH+/9RHWzV/vd+FtsVjoQIBgL1fyhU1TXJgCRcnMponBYEx8mFhlDF+c9qX1TwjiVBsndOtPv01oiIrMCohnZVhYOPU+tVqtUKlU6LB2CHWnPcdxUneCTkJSSVSYFj4d92fdT6OnCaqEET+enYpVYYpTIGlubqLizpfNKFaXFWX6sr7IKRH2pE43ThlH1+srqV9BUfg0RMjd9ac8D4m5DZKecizgDyLy0yOQW2oh6qkT/lsRCp4IUxI9T5gBLmEmEEoGMPQfM+eOENOyAD/jibgnp4xNnS+zaWIwGAzfw/7yMYYWpw376ThKGjltPdkvTtMWwjX99oCK0wvRhmrRqmzF/1b9C+W2CjSaG2hqn6Tz1yauoxFUYjjvK6N+IlbJ5KxAQqLG9Y3NSM/K7kvxerrpPZLvQu3HD7iNd+/lcNlxpusMqlvO4azhNKpNlXDxToTJwlEQMg2L0lejIKQQ0fJYSOwGKHuroW7dCpW+Cip9NdS91ZA6BBeAGMhhNGbDlb8WfOJMKk75iIwr1pP2uQHA/7S1tlJP2kGTq3xo03Sh+Oy4IDrKbJoYDAbD9zCxygCsvRA37u9P67eSyCkHXhsvpPVn3Cmk9SMyx2zaDxFqZd1l+KDiPexq3YWe+B6E94ZjTsxc3JZ2K40Khsj8ky4nYjU8YuhOd1/YBDUTn8pOE2q6TDjfYUJNpxlV7QZ0mqYAhwEcLvfmHiFWNkGqqYZETbZaiMQO8C4VnKZMuMzrITalQutwQCNqhFq8G0rR60gSNyBRJEzLcvASnOcTcIBPQQW3FhV8Csr5FDTx0eCtYki6RAhXyRChbkWkpps26URo5IhUyxGhkQmXajkiyXWNHA53Z7k31lWjqfNNS08fsU1Tq96K+o4eGBytaPd4hg5l0yQWIVp7ZZsmsk5i1njEYDAYo4KJ1cksTj1pfRo55cCHJAhp/Zl30UvQqNnYftG2mlqo2fym2o9R21uLSHkkHW/au1+POWlzMCN3pt+PgUZWlaOLrJLaQypIO8308jy9bkJdtxlWd+SUNLukR6qREa3G4mQZ2mvOYcG8EjolzvMq9F3SKyIqALtdjai3lqHBVoZG21nYeDNkIgWSFXnIFq/CVJsEMzgzosS1CBd9hFBxA8QKYW66SRGLHk0mdJq1qNVmokebCYM6ldpF0cYqAKki4CqimQ8fhjo0ApkF06AzO9BtsqPbbEePyYEGnd79s+OijnOCFDPxweYuaBR6qGTi/k064Lp7Uw66XTTk/mQf8QXvTbPZDL1ej/T09JHbNAGIVEsRF6aiYvNCmybPRkQ4635nMBiMwMDE6mQRpw37+tP6baf6xSlJ68+8O2jEqcecf0f9p9hcuxlH2g9DIVFiefIyPDrju8iR5yA6Khqvl70Kg6HfpN7fYlWlVHkVJfWIUSJOyXUijDyQ2sOMKDVmpIRj48wkKk4zozVIDFf1CaCPPvwvWmN5rM4f3JBERBjp0PfUnJJN79DT4QVTlEm4TZWJuTYHZvS0QN2zE2Knmf6eSx4Ce3gO7Clz0RVxO+wR2bCHZ4OXC9FolXuLv8zz6z5jRWwkh6vnXLoelByf2e6iIpYIWp3Jjrq2Lmz/bA/S0vMglqtgcXK0tIFsBhtpNHIMuo1sdteVo7BKqWiQuBW57DDY8rF9Syc63tkxIpumcJUUxl49HSdNBlAwGAwGY+yZUGKVRFTq6oTGDw/PP/88vv/972NSYdW7xeneC8RpopDWn/VVeonw9KAQpwQn58T+1v3YXLMJnzftgt1lx5y4OXim5FksS1lOR9IKfo46un9UVDQaGxsCcmw2mw1KleqKUdLaLjNszguipDEabJyZiIxoDTJjNFSkhigv7/9JBB95H6emptKfu2xdVJzSjn3dCXTYOyGGCPkiLTY4OMzTW1Bs6ISSPw9eLIM9PJMKU13aCipIe+RJkEenQxQA8UXqLjUKKd1S3JUTXVEiNO9uw+r8GYiNixvW/bg4XhCubhFLos8DxeyF4pZstY16qNVizJuWOGKbJvIeYzAYDEZwMaHEKuG5557D/fff3/ezP21/gk6c9qX1T5EEsVucLoSr+F4hchqeFjTi1CPKynVnqUDdVrcN3bZuZIZl4f7CB7E2fS3i1JcWNpFRkThz5vSQ9lUjPRYieIx2IdpnJBu5bnXimDkStWft+EvZISpQh4qSzkwdECWN0SAxrD9K6i1tna2ocJ1FHX8SL+z9MxqcwjSnHCeP1SYjSi0WzLLaoNQkCRHS9IXQR2SjIzwHjtBUYEBjGXleDpMJ8jF93b1vsCJrp1VI6DYciMh8+63PMXdeCRYumhgeqwwGg8GYoGKViNP4+MslMycAlp4L0vqnBXEamuQWp/cFpTi9sA51c+0m1PTWIEoZhTXpa2ktal5E3rDEJ4msEvsqMnZVo9XS25wuHka7SxCbdk4QnDYXDHZy6f6Z/j8RpW5BauPc/+8a1EAzECkSkdztRF6SHBtnhgsRUhIpjdJAq/TtR6it7QSe2PF1nI2zIq3XgVKLFQ9ZeKTZQ+Hg49EhjkGdOBZHFNFwuOQAGQRFh0HpSVWpe7t4VCqp5/RFhDkhMdHr3/PUlvqzwYqMpSXlGtk5TKgyGAzGRGPCidVf/vKX+OlPf0pTqLfddhseffRR2qByuS9gsnkghuKeSI2/U4J/3FGFfVUdkAxooBkKLWdAgeM0Ch2nMNVxGunO8xCDp8LltGwazoR8G6dlRWgXxwGtIoDYWh5sI1/hCBZcsMAoPQaD9AAsknMQQQqNczoSneuhNubjUKcEh44QwXXwkvdBpI7L6aTr5XK50GLLxycfNsLKianYtDqHFkMkwKmRSxCiEEMrF6J1WrkY8VoZNHIxQhT9t5HLkAHXHeZebN+8Cbd/5U4kJV08WtRn7xFrD058/mN8r+tLyCDCryXFiI+cBaMmDQ55OLrcu5HRBMTufriW90QgkrUio2J9EYGePn3GiJ8z+T1/CdaG+np6okrGrI7mNfEcIysHGD5szbyDrZf3sDULzHoN3D8QGujCx5w0YvWRRx7BrFmz6Cz1vXv34qmnnqJTgH7/+99f8ndITeuzzz570e09PT30S96faMROxGrEkMkktPPag9rVi2zraeRYTyLXehJJdkGcdkliUamajt3KDahUTkO3rD+CTKrxgi2ezMMFHcrQjn3owglwcCAMeUjB3YjCLEhlKsCL8e3EO9Th4NzrJYGjm0OM1oWEKC0Vl0R4UpE54Dq5VElFXgo18uHhAM4Jo9kErVZLRbKnXtanOG1Qn34V/z33Av4QqsR0RSy+N/e3CNcKcnR4FZ6Xhuc5GAxGhIRoIbqCH+pwuPDkbjgYjUa6hmQSGJk85mvIH+XOzk7k5OTQz60v1ou823yxXpMBtmbewdbLe9iaBWa9yGhxD+RvqUzmxRf0CBluo3TQi1XSHPWrX/3qsvucPXsW+fn5eOyxx/pumzZtGh1V+eCDD1JBeqlxmUTQDvw9EllNSUlBeHi4z43FL+S+JWH0DRGu4CFtOgAJaYgiNaftZTStz4WlgsubD2fKt8Glzoc6PBUzALoFK0Q4VOgqsLluE7bXb0e3tQsZoZm4Kf0BrElbgzh1/KjOwOh6hYfTTu2XXzoFtcaF+fOnwF+QOfNEbMXGxg5qsho1PAfJmXdg/+KXeE5hxZYwNe7I3IhvFD/ps2EG/Wetor41GwtIVJesoVQmg0Yz/DG33kyt6urqwuo1a2gX/3hfr/EGWzPvYOvlPWzNArNepJTKA/ldoqEC8f0wIcTqd7/7Xdxzzz2X3SczM3PI20tKSmhdY21tLfLy8obch4jYoYQseYH9/aGQHvgrYk++CWlXhVBzSsQp6daf+3UqThEudIMTSFww+KpP+2k1tWJr3RbaLHW+9zwiFZFYnb4G62kdar7PpvOQ+/G8NrFxsWhsaPDr5B8SRSSPpVKrffcczn8G6c5n0dRdjm+nZKBRosIvSp7BqrTVPrn/y63ZWOBZN3Lpj9eKOCeQyG1KSqpP7n+s12s8wtbMO9h6eQ9bM/+v18B9A7XWw32MoBerpAaNbCPh+PHjgqiJjUVQ4rLBET0FfOk3wacvBMLGZp75SDE5TNjZsIM2Sh1uOwy5RI4lSUvx7ZmPoiS+xKcRwqEgr+vpU6foWaS/PlRWq9VnQpVMBpPufA7i2s/xecp0PJWehXBVNF5Y9Dtkh2f75HgnG+S1r6+rw9TCQjaulMFgMCYoQS9Wh8u+fftw4MABLFu2jDZakJ9Jc9Udd9wx6tSgv3DOfxQ9Ot24MiAnfqgHWg9QgbqrcRdsLitmx87Gj0p+jOUpK6CVCZ35gSA2No6KFTK1yF+vMRGrGrV6dHfSUwfp57+A5My7cEZm4W/z78E/Wj7DwriFeG7ezxDiNuZneE9rSwssFgumTi0c60NhMBgMhp+YMGKVpPLffPNNPPPMMzR1m5GRQcXqwHpUxijrUGuJH+pWdNE61Ax8berXqB9qvCZhTI4rzm0w393d7TexaiFidaR1luZuSPb8DpKjLwDKcHSv+gWeNp3G7ubP8EDRg7hv6tcgZs0Co6K6uhpRUVET366OwWAwJjETRqwSF4D9+/eP9WFMKNrMbX1+qOf11UIdatpqrMtYj/yIgjFPu5ITFCJSSXNNVlaWXx7DarEgLs5LIeQwQ3Lon5Ds+xNtpHIt+C4q8lbhif1Po8fWgz8s+RMWJi70y/FOJshJaUNDAxYtXjzm70UGg8Fg+I8JI1YZvqtD/axhJxWoh9oO0TrUxUlL8Mj0R1CaUAqp2P9WFt4Qn5CAzg7qiu8XSIqZNO8MC84F8ck3IP3yV4Cpg461dS14DNs7j+K5zx5EsjYZr6x+Fckh46s22VeQ+uLqqiqf3R85SSFlIIWFRT67TwaDwWAEH0ysMmgd6kFah7oZnzV+RutQi2Nn4+m5P8IKUocaxDWVCQkJqKyo8EuTFR3BarFAo71CGQDPQ1y1HZLPnoO4swKugg1wLv0hnGEp+J8T/w+vlr+C1Wlr6HqqpD60vxonkBpykvkgXqi+NJkmUfX8goLhn0wwGAwGY1zCxOokhQixyp5KajW1ldahdiI9NB33Tb2P1qEmaLwfqzkWJCQk0uENxH+VDIPwJcQgmdz35cSQqOkIpDufoeNvyYhb+z3/D3ziLHRbu/GDz76BYx3H8NjM7+LWvNsmbaqanESsWr1mrA+DwWAwGOMUJlYnGe3mdmyp3UyjqNX6KkQoImjUb136ehREjn0dqreQxhpyzCRq52uxajab6aVWe3FkWdRdDcmun0NS/iG4mAI4bnoDXNZKYm6H012n8b3dT8DhcuCvy/+O4thinx4Xg8FgMBiTCSZWJwFmhxk7G3fSKOqhtoOQiWVYkrwED09/GPMS5gVdHao3kHFwxG+1o6MDubm5Pr1vi1ushgyMrBrbId39W4iPvwxoYuG4+v+BK7wJEAtTOD6o/gC/Ovw88iLy8KuFv0GcerQDUxkMBoPBmNwwsTpBcXEuHGw7QAUqqUO1uqyYFTMLP5z7I6wM8jpUb0lKSkZV1Tmf36/ZYqGX2pAQwG6E5MDfIDnwP4BIAteSH8A1+35AJtSg2l12/ObIr/F+9XvYmH0DHp/1BG1OYzAYDAaDMTqYWJ1gVOoqaSc/sZwidahpIen46tR7sTZtHRK146MO1VuSkpNx9OgRauCvVCp9WgagVsggP/kKpF/+BrD2wDX7a3DN+w6gjhxk8fXk7idwTleJH839Ma7L2uCzY2AwGAwGY7LDxOoEqUPdWreFRlGr9FUIV4T31aFOiZwy7upQvSU5OZletre3IzU1dfR3yPOQGuqR2LQFix3bId3aBa7wK3AueeqikbhkzOxTe74HuUSBf638P0yNmjr6x2cwGAwGg9EHE6vjuA71s8ad2DSgDpX4oX5j+jcxP2H+uK5D9ZawsDCEhISiva1txGJVamyCsuUQVK3CJjW3IxlitKjzobn1bfBxRRe5Kbxe8Rr+fPxPmBU7C7+Y/0tEKINzrC+DwWAwGOMZJlbHWR0qEaabajdR4/7+OtSnsSJl5aSeMZ+amoLW1tZh7y8xtUHVehhKKk4PQmZsBg8R7JH5MKavgSVhDv57tBWJGflYfYFQtTgt+OmB57C9fhvuzL8L35z+MKRi9lFiMBgMBsMfsG/YccA5Tx1q3RZ0WjqRGpKGe6bci3XpE7cO1VtSU9NQVlYGu90OufzixiaJpQvK1sM0aqpsPQh5bz293RaRA3PKElji58IaVwxOEdr3Oz17/oP80LBB99NgqMfjXz6OZlMTfrngV1iZelUAnh2DwWAwGJMXJlaDlA5zh1CHWrsJ53rOIUxO6lBXY13GekyNnDrh61C9JTUtjabm29rakJKSArG1B8q2I31pfXlPNd3PHpYBS0IJdDMfhiV+Njhl5CUHApDZ86Gh/eJ1d9OXeHrfDxGpjMSLq15GVlhWwJ4fg8FgMBiTFSZWgwiSXibpfZLmJ+l+iUhC61AfKvoGrUOVSSZPHaq3hCtFmK5sQfzxPyHpeAPk3ZUQgYcjJIWKUl3RfbDGz4FLHTOs+zOZTPQyNCwUHM/hf0//C/88/Q/6ejxX+tyEsv5iMBgMBiOYYWJ1jHHxLhxo3U9T/KRhigjWGTEz8NTsH9AU82SuQ70sVj0dcSqq2wNx/R6IWk9hA3gYrGGwZy6GvuB2WIg41SaM6O49YlWskuC7XzyK3c276UnDvVPvhVgk9vGTYTAYDAaDcSmYWB1DXil/Ga+Xv4YuWxdSQ1Jxd8E9WJu+DknapLE+tODD0gNx/V6EVu6Eov0IRG2naeSUD00Gl7YAruKvocIWi3c/PYAbZn0FarV6VA9nNBrRq+jFw/u+gR5bD/645M9YkLjAZ0+HwWAwGAzG8GBidQwh6eX5sfNxfd4NKIouYnWoA7HoBkRO9/aJU4k2EVz6IvBzHgCXugAI77eqSiTR0B0H0dLSgqyskdeTdlg7sK17Kz6P/xwZ0gy8svRVJIcM9ldlMBgMBoMRGJhYHUNIJFWn0yEiIoIJVSJO6/dBVD9YnPJhqULkdM4DcCXPQzcfQtdLLL44Fa/RaBAbG4fm5mavxWq3rRt7Ovdgd8eXKO8thxRS5Lry8M+r/gmlVBipymAwGAwGI/AwscoYe3Fatwei9jMXiNMHwaXOHxQ55TkO0Okue7dZ2Vk4dvQoOI4bUtAORG/XY2/nXuzu2I0z+tO0oW1mxEw8mvcYUMXDaXMyocpgMBgMxhjDxCojMJi7BzVEidvP0Jv58DSazneVfF0QpxeMM/WWzMws7Nu7F11dXYiJubjz3+gwYn/XfnzZ8SVO6k7Q26ZFTMfDuQ+jNGoetDItvW1f9V444RzVsTAYDAaDwRg9TKwy/IO5a1Bav1+cptPIqaPkGz4RpxeSlJQEhVKJpqamPrFqdppxsOsgjaAe0x2lDgxTwwrxQPaDmB89H2Hywcb/DAaDwWAwggcmVhm+F6cketpRRm/mIzKoKHWUfNMtTpP9ehgk9Z+ZmYm6xlqYkoz4smM3jnQfhp2zIz80H/dkfpUK1ChFlF+Pg8FgMBgMhm9gYpUxMkydNK1P602JQO04O1iczntY6NYPDZwNl4tz4VDbIeyU78B+7X64zroQaY/EVMtUpFpToWnWwFxuwqf45Ir35XQ6kZjIRtkyGAwGgzHWMLHKGL44Jel8YsBPLt3ilIvIAE/S+vO+FXBx6qGq5xw21Xz8/9u7E+ioyruP4//sLElIgJAAJoGwRXZEq0nAAkIicHrQttQWF6gosvRFIfgGbEWBsmrpUY8HsbXAaTml6jlagRBBCEhLMCLkVSGyKGEzCwgJCUIImfue5wkzZsgCF8nMnZnv55xrZrkzc/k7M/nluf/7XMk6liWnL56W2NA4GdlmlAwMHSjtgtrd9PN269b9lm4nAAAwj7CK+l04fTWc7qo5KOrMV/pmW+sEMfTI6fSr4dQ9o49nLp6WrIIsySzYKIdKD0lESISkxqXJqM6jpVfrXkwFBgCAlyCswjmc2nfrnzlYK5ymSFXKMzXhNOzmTl96K6hT0W799iPZ8fkO+bQ4VwL9AmVwx3tlct8pktw+WQL9g9y2bQAAoGkQVn1VRckPu/XVyOl3h/TNttZdrobTGW4Pp/Y+1D0leyTz6EbZdnKrDqz9owbInDufk+FxIyQsOMyt2wcAAJoWYdVXVBTXGjndVSucdq3ZrT8oveZofTeHU+c+1I3y4bEsKblYInFhcfJY4nhJjkiW2zv2vO6E/wAAwDt4TFhduHChbNy4UfLy8iQ4OFhKS0vrrHP8+HGZMmWKZGdnS2hoqIwfP14WL14sgYEe889sonCqRk4P/xBO1QFRg2aJLT5ZJDRGrOLMxTP6ICk1inqo9KC0Co6Q1PhUGd1ptPRq01sMw9CnpwUAAL7DY1Lc5cuXZezYsZKUlCRvvfVWnfurq6tl9OjREhMTI7t27ZLCwkJ57LHHJCgoSBYtWiRer6JI/I/V2q1/9oi+2damW81u/UHPWi6cKmq3/vaT2TqgflL8iT7lqepDndTnKUlpnyJBAT/0oaqwCgAAfIvHhNV58+bpn6tXr673/s2bN8uBAwfko48+kujoaOnfv78sWLBAMjIy5MUXX9SjsV6lvNB5t74jnHYXI36QVN2bUbNbPzRarEb1oX6m+lALMmXbia36DFP9o/rL7Dvn6D7U8OBwd28iAACwCI8Jq9eTk5Mjffr00UHVLi0tTbcF7N+/XwYMGFDv4yorK/Vid/78ef3TZrPppSmp51ejhTf0OuVFEqB255+omU7K/+zXNc/RprvY4gfJlcEZUh17T91w2sT/BjO+Lj0imccyHX2osaGx8kjiozIyfqR0DP3hzFYN1cNUvaBRM3Ool3nUzBzqZR41c029aq/vigx07Wv6RFgtKipyCqqK/bq6ryGqp9U+alub6olVrQVNyTBsUl5eoS6Jn5/zAUP+F4ol5NtcCf42V0IKcyWwrEDfXhXZVS62v1sq7/gfudz+LrG1aPvDg6pExGI9nWcrz8r2omw95dSR8iMSFhQmQ2KGyH3th0tiq9tr5kOtUpt97kfVC/WjZuZQL/OomTnUyzxq5pp6VVWpEPFDBlJtlE2tvLzc+mF19uzZsnTp0kbXyc/Pl8TExCbbhjlz5sjMmTOdRlZjY2MlIiJCwsPDXfAXhZ9+LRVO9cjp1emk/M8drVmnbaLYugyVyrgUsamR05btRL31ml9drOjSlUuy/dR22VSQKZ8U79Z9qIM6DJJJfSfX6UO96XoxG8ANoWbmUC/zqJk51Ms8auaaeqljg+zUY13RPhkQEGD9sJqeni4TJkxodJ2EhIQbei51YFVubq7TbcXFxY77GhISEqKXa6n/wU39ofA//KFE7P9AmhfvcQqnRsIwqVLhNC5JpGXUD+uLddkMm3xWrPpQN8rWq32o/dr2l4w7Z8vw2BHSKqTVLXkdNRLriv833oSamUO9zKNm5lAv86hZ09er9rquqvWNvoZbw2pUVJRebgU1S4Ca3qqkpETatas5H/yWLVv06GjPnj3FigIOZYp/yf+JrfMwqR46SGyxKpzW2q3vAb4u+1ofyZ91bJMUf18st4XepvtQR3UaJbeFxbp78wAAgIfzmJ5VNYfq2bNn9U/VS6rmW1W6du2q51RNTU3VofTRRx+VZcuW6T7VP/zhDzJt2rR6R06toGrkcjlXdl4iIyM96q9FNR+qOkhKHc1/8NxX+uj91Lg0GdV5lPRp07emDxUAAMCXwurcuXNlzZo1juv2o/vVCQCGDBmi+x42bNigj/5Xo6wtW7bUJwWYP3++WJb/jfVqWMElPR/qDr2b/5Oi3TqQDu4wWJ7o9YSkdBgkwQFeNjUYAACwBI8Jq2p+1YbmWLWLj4+XzMxMl22Tt1N9qHtLPpONRzfIthPb5MKVC9K3bT95dmCGjIi7dX2oAAAAHh9W4TrflH2j+1A36T7UIj0H6rjEh3UfamxYnLs3DwAA+BDCKrTvLn53tQ91o3x1tQ91RFyqjOo0Wvq2pQ8VAAC4B2HVh6n5UHecqulD3V2YowPpoA6DZSJ9qAAAwCIIqz7bh7pRtp3YerUPta88O/B/ZXjcCIkIiXD3JgIAADgQVn3EUdWHWrBRNhVskiLVh9qyo4xLHCcjO42WOPpQAQCARRFWvdjZS2cdfaj5Z/MlLChMRsTX9KH2a9uPPlQAAGB5hFUv7EP9+Gofas7VPtSU9oNkwqDH9byo9KECAABPQlj1mj7UvTqgblV9qFUV0qdNH5k18Fl9RD99qAAAwFMRVj1Ywfmj+kCpTQWZjj7U33T/jYzsNEriw+PdvXkAAAA/GmHVA/tQNx/7UI+iHjh7QPehqqP4R3dWfaj96UMFAABehbDqIX2oO7/9WJ/2VPWhivhJSocUWZKyTAZ3HCwhASHu3kQAAIAmQVi1cB/qvtP79GlPPzrxke5D7dWmt6TfMUtS41UfaqS7NxEAAKDJEVYt2oeadWyTFF4olA4tO8ivu/9a96F2Cu/k7s0DAABwKcKqBZy7dE62nNyiR1EPnN0voUGhMiJuRM18qFH9xd/P392bCAAA4BaEVTfaeepjefurt2XPd5/qPtTkDsmyJGWpDO54L32oAAAAhFX32nFqh5ReLpUZA2ZKWvz9EtmMPlQAAIDaCKtuNPvOOVJeVi6RkZHi78+ufgAAgGuRkNwo0J+/FQAAABpDWAUAAIBlEVYBAABgWYRVAAAAWBZhFQAAAJZFWAUAAIBlEVYBAABgWYRVAAAAWBZhFQAAAJZFWAUAAIBleUxYXbhwoSQnJ0uLFi0kIiKi3nX8/PzqLOvWrXP5tgIAAODW8JjzfV6+fFnGjh0rSUlJ8tZbbzW43qpVq+T+++93XG8o2AIAAMD6PCaszps3T/9cvXp1o+upcBoTE+OirQIAAEBT8piweqOmTZsmTzzxhCQkJMjkyZPlt7/9rW4HaEhlZaVe7M6fP69/2mw2vTQl9fyGYTT563gL6mUeNTOHeplHzcyhXuZRM9fUq/b6rshA176mz4TV+fPny7Bhw3Rf6+bNm2Xq1KlSUVEh06dPb/Axixcvdoza1lZaWirV1dVNur2GYZPy8gp1Sfz8PKZ92G2ol3nUzBzqZR41M4d6mUfNXFOvqqoqpwwUFBQkTa28vNz6YXX27NmydOnSRtfJz8+XxMTEG3q+559/3nF5wIABcuHCBXnppZcaDatz5syRmTNnOo2sxsbG6naC8PBwafq/KPz0a/n78wG8HuplHjUzh3qZR83MoV7mUTPX1EsdG2SnHhscHCxNLSAgwPphNT09XSZMmNDoOmp3/s26++67ZcGCBXo3f0hISL3rqNvru0/9D3bFh0K1KLjqtbwB9TKPmplDvcyjZuZQL/OoWdPXq/a6rqr1jb6GW8NqVFSUXppKXl6eREZGNhhUAQAAYG0e07N6/PhxOXv2rP6peklVEFW6du0qoaGhsn79eikuLpZ77rlHmjVrJlu2bJFFixbJrFmz3L3pAAAA8PawOnfuXFmzZo1TT6qSnZ0tQ4YM0Y3Ar7/+usyYMUMfBadC7PLly+XJJ59041YDAADAJ8Kqml+1sTlW1YkAap8MAAAAAJ6PTmUAAABYFmEVAAAAlkVYBQAAgGURVgEAAGBZhFUAAABYFmEVAAAAlkVYBQAAgGURVgEAAGBZhFUAAABYFmEVAAAAlkVYBQAAgGURVgEAAGBZhFUAAABYFmEVAAAAlkVYBQAAgGURVgEAAGBZhFUAAABYFmEVAAAAlkVYBQAAgGURVgEAAGBZge7eAAAAALhXUFCQzEyf5bhsJYRVAAAAH+fn5yfBwcFiRbQBAAAAwLIIqwAAALAswioAAAAsi7AKAAAAyyKsAgAAwLIIqwAAALAsjwirBQUFMnHiROncubM0b95cunTpIi+88IJcvnzZab3PP/9cBg8eLM2aNZPY2FhZtmyZ27YZAAAAPjLP6ldffSU2m01WrlwpXbt2lS+//FKefPJJuXDhgrz88st6nfPnz0tqaqoMHz5c3njjDfniiy/k8ccfl4iICJk0aZK7/wkAAADw1rB6//3368UuISFBDh48KCtWrHCE1bVr1+qR1r/97W96UttevXpJXl6eLF++nLAKAADgoTwirNanrKxMWrdu7biek5Mj9957r9PZF9LS0mTp0qVy7tw5iYyMrPd5Kisr9WKnRmgVNZKrlqaknt8wjCZ/HW9BvcyjZuZQL/OomTnUyzxq5r31utFt9MiweuTIEXnttdcco6pKUVGR7mmtLTo62nFfQ2F18eLFMm/evDq3nzx5UkJDQ6UpGYZNKiouSHn5efHz84j2YbeiXuZRM3Ool3nUzBzqZR418956VVRU6J8qXDfKcKOMjAy1dY0u+fn5To85efKk0aVLF2PixIlOt48YMcKYNGmS02379+/Xz3HgwIEGt+HSpUtGWVmZY1HrXm+bWFhYWFhYWFhY5JYsJ06caDQvunVkNT09XSZMmNDoOqo/1e7bb7+VoUOHSnJysrz55ptO68XExEhxcbHTbfbr6r6GhISE6MVOjaaeOHFCwsLCxM/PT5qSajlQsxao1wsPD2/S1/IG1Ms8amYO9TKPmplDvcyjZt5bLzWiWl5eLh06dGh0PbeG1aioKL3ciFOnTumgOnDgQFm1apX4+zsPbSclJcnvf/97qaqqkqCgIH3bli1bpEePHg22ANRHPe9tt90mrqTeTFZ/Q1kJ9TKPmplDvcyjZuZQL/OomXfWq1WrVtddx9rNDLWC6pAhQyQuLk73qZ4+fVr3oarFbty4cfrgKjUf6/79++Vf//qXvPLKKzJz5ky3bjsAAABunkccYKVGSNVBVWq5dtTT3pSrkvnmzZtl2rRpevS1bdu2MnfuXKatAgAA8GAeEVZVX+v1eluVvn37ys6dO8VTqF5ZdSau2j2zaBj1Mo+amUO9zKNm5lAv86iZOd5YLz91lJW7NwIAAADw2J5VAAAA+CbCKgAAACyLsAoAAADLIqwCAADAsgirbrJw4UJ9Jq4WLVpIREREvescP35cRo8erddp166dPPvss3LlyhXxVa+//rp06tRJmjVrJnfffbfk5ua6e5Ms4+OPP5af/exn+iwg6sxr77//vtP96jhKNZVb+/btpXnz5jJ8+HA5fPiw+KrFixfLXXfdpc9Upz5bDzzwgBw8eNBpnUuXLump8Nq0aaPPbPeLX/yizlnyfMWKFSv0bCv2ScbVSVg2bdrkuJ9aNW7JkiX6c/nMM884bqNmzl588UVdo9pLYmKi437qVf8c9I888oiuifpe79Onj+zZs8crv/cJq25y+fJlGTt2rEyZMqXe+6urq3VQVevt2rVL1qxZI6tXr9ZvPF+kTvKgTvCgpuPYu3ev9OvXT9LS0qSkpMTdm2YJFy5c0DVRgb4+y5Ytk1dffVXeeOMN+eSTT6Rly5a6fuoXgC/asWOH/sW3e/duPY+zOvNdamqqrqPdjBkzZP369fLOO+/o9dXpnn/+85+LL1LzW6vA9dlnn+lfhsOGDZMxY8boE7Ao1Kphn376qaxcuVKH/dqoWV29evWSwsJCx/Kf//zHcR/1cnbu3DlJSUnRZ+xUfzgeOHBA/vSnPzmdsdOrvvfV1FVwn1WrVhmtWrWqc3tmZqbh7+9vFBUVOW5bsWKFER4eblRWVhq+5ic/+Ykxbdo0x/Xq6mqjQ4cOxuLFi926XVakPtbvvfee47rNZjNiYmKMl156yXFbaWmpERISYvzzn/9001ZaS0lJia7bjh07HPUJCgoy3nnnHcc6+fn5ep2cnBw3bql1REZGGn/961+pVSPKy8uNbt26GVu2bDF++tOfGk8//bS+nZrV9cILLxj9+vWr9z7qVVdGRoYxaNAgoyHe9r3PyKpF5eTk6CH96Ohox23qL6Lz5887RjN8hRpdViM6aheGnb+/v76u6oTGHT16VJ+auHb91BnfVCsF9atRVlamf7Zu3Vr/VO83Ndpau2Zql6Q65bOv10zt9Vm3bp0ehVbtANSqYWr0Xu0hq10bhZrVT+2iVq1MCQkJ8vDDD+tWOIV61fXBBx/InXfeqffQqlamAQMGyF/+8hev/d4nrFqUepPVDqqK/bq6z5ecOXNG/4Ksrx6+VoubYa8R9aufzWbTvYRql1rv3r31baouwcHBdfrJfblmX3zxhe4VVGfFmTx5srz33nvSs2dPatUAFehVy5Lqj74WNatLhSjV6paVlaV7pFXYGjx4sJSXl1OvenzzzTe6Tt26dZMPP/xQtxROnz5dtwx64/e+R5xu1VPMnj1bli5d2ug6+fn5Tk3jANw/+vXll1869cehrh49ekheXp4ehX733Xdl/PjxuncQdZ04cUKefvpp3Q+tDgjF9Y0cOdJxWfX3qvAaHx8vb7/9tj44CHX/yFYjq4sWLdLX1ciq+h5T/anqs+ltGFm9hdLT03UYbWxRuzduRExMTJ0jHe3X1X2+pG3bthIQEFBvPXytFjfDXiPqV9fvfvc72bBhg2RnZ+uDiOxUXVT7SWlpqdP6vlwzNbLVtWtXGThwoB4tVAf0vfLKK9SqHmq3tTr484477pDAwEC9qGCvDnZRl9XoFjVrnBpF7d69uxw5coT3WD3UEf5qz0Ztt99+u6N1wtu+9wmrt1BUVJQeNW1sUV/4N0L1gqndbrWPdld/patpY659g3o7VTP1C3Lr1q1Of1Wq66pOaFznzp31l1Pt+qneZ3V0qK/WTx2HpoKq2pW9bds2XaPa1PtNHWVbu2Zqaiv1i8BXa3Yt9RmsrKykVvW477779Pe3Gom2L2oUTPVh2i9Ts8ZVVFTI119/rUMZ77G6VNvStdPtHTp0SI9Ge+X3vruP8PJVx44dM/bt22fMmzfPCA0N1ZfVoo4eVa5cuWL07t3bSE1NNfLy8oysrCwjKirKmDNnjuGL1q1bp49iXL16tXHgwAFj0qRJRkREhNNsCb5MvW/s7yH1sV6+fLm+rN5nypIlS3S9/v3vfxuff/65MWbMGKNz587GxYsXDV80ZcoUPQvH9u3bjcLCQsfy/fffO9aZPHmyERcXZ2zbts3Ys2ePkZSUpBdfNHv2bD1TwtGjR/X7R1338/MzNm/erO+nVtdXezYAhZo5S09P159H9R7773//awwfPtxo27atnqlDoV7OcnNzjcDAQGPhwoXG4cOHjbVr1xotWrQw/vGPfzjW8abvfcKqm4wfP16HimuX7OxsxzoFBQXGyJEjjebNm+sPrfowV1VVGb7qtdde019WwcHBeiqr3bt3u3uTLEO9b+p7P6n3mX0ak+eff96Ijo7Wof++++4zDh48aPiq+mqlFjWVnJ36Qp86daqeokn9EnjwwQd1oPVFjz/+uBEfH68/e+qPZvX+sQdVhVqZD6vUzNlDDz1ktG/fXr/HOnbsqK8fOXLEcT/1qmv9+vV6UEt9pycmJhpvvvmm0/3e9L3vp/7j7tFdAAAAoD70rAIAAMCyCKsAAACwLMIqAAAALIuwCgAAAMsirAIAAMCyCKsAAACwLMIqAAAALIuwCgAAAMsirAKARXXq1En8/Pz0Ulpa6vLX3759u+P1H3jgAZe/PgAohFUAcFHgq28ZOnRoo4+fP3++FBYWSqtWrcTVkpOT9Wv/6le/cvlrA4BdoOMSAKDJAt+1PvjgA5k8ebJMnTq10ceHhYVJTEyMuENwcLB+7ebNm0tlZaVbtgEAGFkFABcEvtrLuXPnZNasWfLcc8/J2LFjTT3f6tWrJSIiQjZs2CA9evSQFi1ayC9/+Uv5/vvvZc2aNbp1IDIyUqZPny7V1dWOx6nb//jHP8pjjz0moaGhEh8frwPz6dOnZcyYMfq2vn37yp49e5qgCgBw8wirAOBCqvdUhcMhQ4bIggULbuo5VDB99dVXZd26dZKVlaVbDR588EHJzMzUy9///ndZuXKlvPvuu06P+/Of/ywpKSmyb98+GT16tDz66KM6vD7yyCOyd+9e6dKli75uGMYt+tcCwI9HGwAAuIjNZpNx48ZJYGCgrF27Vves3oyqqipZsWKFDpeKGllVAbW4uFiPkPbs2VP3wmZnZ8tDDz3keNyoUaPkqaee0pfnzp2rn+Ouu+5yjO5mZGRIUlKSfh53tR4AwLUIqwDgImq3f05OjuTm5upe1Juldv3bg6oSHR2td/OroFr7tpKSEqfHqd38te9X+vTpU+c29TjCKgCrIKwCgAuoXfYvv/yybNy4Ubp16/ajnisoKMjpuhqhre82NZLb0OPso7r13Xbt4wDAnehZBYAmlpeXJxMnTpQlS5ZIWlqauzcHADwKI6sA0ITOnDmjJ9RXB1SpA5mKioqc7g8ICJCoqCi3bR8AWB1hFQCakNrtf+zYMb20b9++zv1qCqmCggK3bBsAeAI/gzlKAMCS1EFTzzzzjF7cacKECXrKrffff9+t2wHAN9GzCgAWpqaTUkf5l5WVufy1d+7cqV9bTbMFAO7CyCoAWJRqHVBzqioJCQni7+/a8YWLFy/KqVOn9GUVWpnOCoA7EFYBAABgWbQBAAAAwLIIqwAAALAswioAAAAsi7AKAAAAyyKsAgAAwLIIqwAAALAswioAAAAsi7AKAAAAsar/B2pOPOFbaEI7AAAAAElFTkSuQmCC",
                        "text/plain": [
                            "<Figure size 1000x400 with 1 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "fig = lens.draw()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "We view the spot diagram to see the final performance of our system."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 22,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "image/png": 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",
                        "text/plain": [
                            "<Figure size 1200x400 with 3 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "spot = analysis.SpotDiagram(lens)\n",
                "spot.view()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "And we print the RMS spot radii for each wavelength and field."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 23,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "RMS Spot Radius:\n",
                        "\tField (0.0, 0.0), Wavelength 0.486 µm, Radius: 0.01444 mm\n",
                        "\tField (0.0, 0.0), Wavelength 0.588 µm, Radius: 0.01076 mm\n",
                        "\tField (0.0, 0.0), Wavelength 0.656 µm, Radius: 0.01108 mm\n",
                        "\tField (0.0, 0.7), Wavelength 0.486 µm, Radius: 0.02149 mm\n",
                        "\tField (0.0, 0.7), Wavelength 0.588 µm, Radius: 0.02054 mm\n",
                        "\tField (0.0, 0.7), Wavelength 0.656 µm, Radius: 0.02113 mm\n",
                        "\tField (0.0, 1.0), Wavelength 0.486 µm, Radius: 0.02128 mm\n",
                        "\tField (0.0, 1.0), Wavelength 0.588 µm, Radius: 0.02242 mm\n",
                        "\tField (0.0, 1.0), Wavelength 0.656 µm, Radius: 0.02256 mm\n"
                    ]
                }
            ],
            "source": [
                "print(\"RMS Spot Radius:\")\n",
                "\n",
                "fields = lens.fields.get_field_coords()\n",
                "wavelengths = lens.wavelengths.get_wavelengths()\n",
                "\n",
                "rms_spot_radius = spot.rms_spot_radius()\n",
                "for i, field in enumerate(fields):\n",
                "    for j, wavelength in enumerate(wavelengths):\n",
                "        print(\n",
                "            f\"\\tField {field}, Wavelength {wavelength:.3f} µm, \"\n",
                "            f\"Radius: {rms_spot_radius[i][j]:.5f} mm\",\n",
                "        )"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Conclusions\n",
                "\n",
                "- Starting from a simple system consisting of 3 (nearly) parallel plates, we designed a Cooke triplet. The triplet achieves an RMS spot size of ≈20 µm or less for all wavelengths and fields. We could have optimized the system to improve the performance further.\n",
                "- We optimized for minimal RMS spot size, but we could have instead chosen to optimize the wavefront or other performance metrics. All operand possibilities can be seen in the operands module.\n",
                "- This tutorial showed a typical example of optimizing an optical system from a simple starting point to a system with significantly improved performance. Lens optimization is complex and can be considered somewhat of an \"art\". With experience, the lens designer will learn how best to optimize lens systems to achieve target performance."
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": ".venv",
            "language": "python",
            "name": "python3"
        },
        "language_info": {
            "codemirror_mode": {
                "name": "ipython",
                "version": 3
            },
            "file_extension": ".py",
            "mimetype": "text/x-python",
            "name": "python",
            "nbconvert_exporter": "python",
            "pygments_lexer": "ipython3",
            "version": "3.11.1"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 2
}