{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "80074018",
   "metadata": {},
   "source": [
    "# Photonic crystal waveguide polarization filter"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37a27f2a",
   "metadata": {},
   "source": [
    "Polarization control is one of the central themes in integrated silicon photonics. Different polarization modes not only allow for more information-carrying channels but also enable a wide range of applications given their different characteristics. For example, waveguide TE modes usually have better confinement and thus they are less prone to sidewall roughness. TM modes, on the other hand, have a larger penetration depth into the top and bottom claddings, which makes them suitable for sensing applications. As a result, integrated silicon photonic filters that selectively transmit or block certain polarization are very useful. \n",
    "\n",
    "This notebook demonstrates the modeling of a compact TM-pass polarization filter based on photonic crystal waveguide. The photonic crystal is an air-bridged silicon slab with periodic air holes arranged in a triangular lattice. It is possible to achieve a TM-pass but TE-block device within a frequency range by utilizing bandgap engineering and index guiding mechanism. The design parameters adopted from [Chandra Prakash and Mrinal Sen , \"Optimization of silicon-photonic crystal (PhC) waveguide for a compact and high extinction ratio TM-pass polarization filter\", Journal of Applied Physics 127, 023101 (2020)](https://aip.scitation.org/doi/abs/10.1063/1.5130160) are optimized for the telecom frequency to have a ~-0.5 dB TM transmission and ~-40 dB TE transmission. \n",
    "\n",
    "<img src=\"img/phc_polarization_filter.png\" width=\"500\" alt=\"Schematic of the polarization filter\">\n",
    "\n",
    "For more integrated photonic examples such as the [8-Channel mode and polarization de-multiplexer](https://www.flexcompute.com/tidy3d/examples/notebooks/8ChannelDemultiplexer/), the [broadband bi-level taper polarization rotator-splitter](https://www.flexcompute.com/tidy3d/examples/notebooks/BilevelPSR/), and the [broadband directional coupler](https://www.flexcompute.com/tidy3d/examples/notebooks/BroadbandDirectionalCoupler/), please visit our [examples page](https://www.flexcompute.com/tidy3d/examples/). If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. FDTD simulations can diverge due to various reasons. If you run into any simulation divergence issues, please follow the steps outlined in our [troubleshooting guide](https://www.flexcompute.com/tidy3d/examples/notebooks/DivergedFDTDSimulation/) to resolve it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a172f231",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n",
    "from tidy3d.plugins.mode import ModeSolver\n",
    "from tidy3d.plugins.mode.web import run as run_ms"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bcbebc6",
   "metadata": {},
   "source": [
    "## Simulation Setup "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "565a299c",
   "metadata": {},
   "source": [
    "This device is designed to work in a wide frequency range from 1480 nm to 1620 nm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e2bda8ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "lda0 = 1.55  # central wavelength\n",
    "freq0 = td.C_0 / lda0  # central frequency\n",
    "ldas = np.linspace(1.48, 1.62, 100)  # wavelength range of interest\n",
    "freqs = td.C_0 / ldas  # frequency range of interest"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7862239",
   "metadata": {},
   "source": [
    "Since the photonic crystal slab is air-bridged, we only need to define two materials: silicon and air. The frequency dispersion of the silicon refractive index in the frequency range of interest is quite small. Therefore, in this notebook, we model it as non-dispersive and lossless. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "65537c56",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_si = 3.47  # silicon refractive index\n",
    "si = td.Medium(permittivity=n_si**2)\n",
    "\n",
    "n_air = 1  # air refractive index\n",
    "air = td.Medium(permittivity=n_air)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebfa2951",
   "metadata": {},
   "source": [
    "For the photonic crystal to work as a filter, the geometric parameters need to be carefully chosen such that bandgap lies within the frequency range of interest. The design process would require the calculation of band structures. In this notebook, we will skip the band structure calculation and only model the optimized device. For band diagram simulation, refer to the [photonic crystal slab band structure calculation notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/Bandstructure/).\n",
    "\n",
    "Define the geometric parameters for the photonic crystal as well as the input and output straight waveguides."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f2d41dc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 0.42  # lattice constant\n",
    "t = 0.75 * a  # slab thickness\n",
    "r = 0.3 * a  # radius of air holes\n",
    "w = 0.73 * a  # width of the photonic crystal waveguide section\n",
    "\n",
    "N_holes = 11  # number of holes in each row\n",
    "N_rows = 7  # number of rows of holes on each side of the waveguide\n",
    "L = N_holes * a  # length of the photonic crystal waveguide\n",
    "\n",
    "D = 0.4  # width of the input and output waveguides\n",
    "\n",
    "inf_eff = 1e3  # effective infinity of the model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fd085a2",
   "metadata": {},
   "source": [
    "To build the device, we define the silicon slab, input and output straight waveguides, and air holes. The air holes are systematically defined using a nested for loop. Due to the mirror symmetry of the device with respect to the $xz$ plane, We only define the air holes in $y>0$. Later, we will define the symmetry condition in the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fae873ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define the silicon slab\n",
    "si_slab = td.Box.from_bounds(\n",
    "    rmin=(-L / 2, -N_rows * np.sqrt(3) * a / 2 - w / 2, 0),\n",
    "    rmax=(L / 2, N_rows * np.sqrt(3) * a / 2 + w / 2, t),\n",
    ")\n",
    "\n",
    "# define the input and output straight waveguides\n",
    "si_wg = td.Box.from_bounds(\n",
    "    rmin=(-inf_eff, -D / 2, 0),\n",
    "    rmax=(inf_eff, D / 2, t),\n",
    ")\n",
    "\n",
    "# get the union with both silicon geometries\n",
    "si_geometry = si_slab + si_wg\n",
    "si_structure = td.Structure(geometry=si_geometry, medium=si)\n",
    "\n",
    "# group all air holes as a geometry group\n",
    "holes = []\n",
    "for i in range(N_rows):\n",
    "    if i % 2 == 0:\n",
    "        shift = a / 2\n",
    "        N = N_holes\n",
    "    else:\n",
    "        shift = 0\n",
    "        N = N_holes + 1\n",
    "\n",
    "    for j in range(N):\n",
    "        holes.append(\n",
    "            td.Cylinder(\n",
    "                center=(\n",
    "                    (j - (N_holes) / 2) * a + shift,\n",
    "                    (w / 2 + r) + (i) * np.sqrt(3) * a / 2,\n",
    "                    t / 2,\n",
    "                ),\n",
    "                radius=r,\n",
    "                length=t,\n",
    "            )\n",
    "        )\n",
    "holes_structure = td.Structure(geometry=td.GeometryGroup(geometries=holes), medium=air)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e441c407",
   "metadata": {},
   "source": [
    "A [ModeSouce](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html) is defined at the input waveguide to launch either the fundamental TE or TM mode. A [FluxMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FluxMonitor.html) is defined at the output waveguide to measure the transmission. In addition, we define a [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html) to visualize the field propagation and scattering in the $xy$ plane."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "043af5cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# simulation domain size\n",
    "Lx = 1.5 * L\n",
    "Ly = 2 * N_rows * a + lda0\n",
    "Lz = 7 * t\n",
    "sim_size = (Lx, Ly, Lz)\n",
    "\n",
    "# define a mode source at the input waveguide\n",
    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))\n",
    "mode_spec = td.ModeSpec(num_modes=1, target_neff=n_si)\n",
    "mode_source = td.ModeSource(\n",
    "    center=(-Lx / 2 + lda0 / 2, 0, t / 2),\n",
    "    size=(0, 4 * D, 5 * t),\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "    direction=\"+\",\n",
    "    mode_spec=mode_spec,\n",
    "    mode_index=0,\n",
    ")\n",
    "\n",
    "# define a flux monitor at the output waveguide\n",
    "flux_monitor = td.FluxMonitor(\n",
    "    center=(Lx / 2 - lda0 / 2, 0, t / 2),\n",
    "    size=mode_source.size,\n",
    "    freqs=freqs,\n",
    "    name=\"flux\",\n",
    ")\n",
    "\n",
    "# define a field monitor in the xy plane\n",
    "field_monitor = td.FieldMonitor(\n",
    "    center=(0, 0, t / 2),\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    freqs=[freq0],\n",
    "    name=\"field\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5c609d5",
   "metadata": {},
   "source": [
    "For periodic structures, it is better the define a grid that is commensurate with the periodicity. Therefore, we use [UniformGrid](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.UniformGrid.html) in the $x$ and $y$ directions. In the $z$ direction, a nonuniform grid can be used. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "34ea04d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define grids\n",
    "steps_per_unit_cell = 20\n",
    "grid_spec = td.GridSpec(\n",
    "    grid_x=td.UniformGrid(dl=a / steps_per_unit_cell),\n",
    "    grid_y=td.UniformGrid(dl=a / steps_per_unit_cell * np.sqrt(3) / 2),\n",
    "    grid_z=td.AutoGrid(min_steps_per_wvl=steps_per_unit_cell),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99bc4945",
   "metadata": {},
   "source": [
    "Since the TE and TM modes share different symmetry with respect to the $xz$ plane, we can selectively launch them by setting the appropriate symmetry condition. The simulation for TE incidence is done by setting the symmetry condition to `(0,-1,0)` while the TM incidence corresponds to `(0,1,0)`. \n",
    "\n",
    "For this simulation, we set a relatively long run time of 20 ps to ensure the field decays sufficiently such that the simulation result is accurate. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5f2deae1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define the te incidence simulation\n",
    "run_time = 2e-11  # simulation run time\n",
    "\n",
    "sim_te = td.Simulation(\n",
    "    center=(0, 0, 0),\n",
    "    size=sim_size,\n",
    "    grid_spec=grid_spec,\n",
    "    structures=[si_structure, holes_structure],  # note: the order of the structures is important\n",
    "    sources=[mode_source],\n",
    "    monitors=[flux_monitor, field_monitor],\n",
    "    run_time=run_time,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    symmetry=(0, -1, 0),\n",
    "    medium=air,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cdcd5fd",
   "metadata": {},
   "source": [
    "To quickly check if the structures, source, and monitors are correctly defined, use the `plot` method to visualize the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82aa2672",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_te.plot(z=t / 2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "407055b0",
   "metadata": {},
   "source": [
    "To further investigate the grids, we overlay the grid on top of the structures and zoom in on a small area. The grid looks sufficiently fine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "27380ab5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "sim_te.plot(z=t / 2, ax=ax)\n",
    "sim_te.plot_grid(z=t / 2, ax=ax)\n",
    "ax.set_xlim(-0.5, 0.5)\n",
    "ax.set_ylim(0, 1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "287ae5bc",
   "metadata": {},
   "source": [
    "Lastly, we use the [ModeSolver](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.mode.ModeSolver.html) plugin to visualize the mode profile launched by the mode source. The mode field confirms that we are launching the fundamental TE mode at the input waveguide. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a66f5a30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:41:16 CEST </span>Mode solver created with                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #808000; text-decoration-color: #808000\">task_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'fdve-8d3acacf-34fc-431f-b3c3-0463cbba7daf'</span>,              \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #808000; text-decoration-color: #808000\">solver_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mo-89d61a69-7b93-4518-b8bb-2e6fd59310e4'</span>.              \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m14:41:16 CEST\u001b[0m\u001b[2;36m \u001b[0mMode solver created with                                          \n",
       "\u001b[2;36m              \u001b[0m\u001b[33mtask_id\u001b[0m=\u001b[32m'fdve-8d3acacf-34fc-431f-b3c3-0463cbba7daf'\u001b[0m,              \n",
       "\u001b[2;36m              \u001b[0m\u001b[33msolver_id\u001b[0m=\u001b[32m'mo-89d61a69-7b93-4518-b8bb-2e6fd59310e4'\u001b[0m.              \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f739a86f01664b479fced8b86cfd071d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "614323d3174f4326a53ad640c758fe74",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:41:23 CEST </span>Mode solver status: queued                                        \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m14:41:23 CEST\u001b[0m\u001b[2;36m \u001b[0mMode solver status: queued                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:41:25 CEST </span>Mode solver status: running                                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m14:41:25 CEST\u001b[0m\u001b[2;36m \u001b[0mMode solver status: running                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:41:30 CEST </span>Mode solver status: success                                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m14:41:30 CEST\u001b[0m\u001b[2;36m \u001b[0mMode solver status: success                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c611ad8215a346dda7d1d7ea1c09d893",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA98AAAEWCAYAAAB/iyTlAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQAAnMFJREFUeJztnXl8FEX6/z89k0wSIAeBkEPCJcp9iYoBBRQU0WVFWA9EOURYFVwx66q4KoeueKwKqwjqCuhPIooCHriwiAKLHEqAL6DCAgsCkgQ5kpBAkslM//6o6k56JpP0XElm8nnzmlfT3dVdTzUzH6q6nnoeRVVVFYQQQgghhBBCCAkalro2gBBCCCGEEEIICXc4+CaEEEIIIYQQQoIMB9+EEEIIIYQQQkiQ4eCbEEIIIYQQQggJMhx8E0IIIYQQQgghQYaDb0IIIYQQQgghJMhw8E0IIYQQQgghhASZiLo2gBBSvygpKUFZWZlX19hsNkRHRwfJIkIIqRuoh4QQIqAeBgYOvgkhOiUlJWjb9iLk5p7x6rqUlBQcPnyYAksICRuoh4QQIqAeBg4OvgkhOmVlZcjNPYMjh5ciLq6RqWsKC8+jTds7UVZWRnElhIQN1ENCCBFQDwMHB9+EEDfimkQjrkmMucJOZ3CNIYSQOoR6SAghAuqh/3DwTQhxx+k0L5oUV0JIOEM9JIQQAfXQbzj4JoS4o6riY7YsIYSEK9RDQggRUA/9hoNvQog7TtWLN5sUV0JIGEM9JIQQAfXQbzj4JoS4Q7ciQggRUA8JIURAPfQbDr4JIe5QXAkhREA9JIQQAfXQbzj4JoS4Q3ElhBAB9ZAQQgTUQ7/h4JsQ4o7qhbiqFFdCSBhDPSSEEAH10G84+CaEuKGoTigmRdNsOUIICUWoh4QQIqAe+o+lrg0ghNRDNLcisx9CCAlXgqyHv/76K+6++240a9YMMTEx6NatG7Zv366fV1UVzzzzDFJTUxETE4PBgwfjwIEDgWwhIYSYg/1Dv+HgmxDijlP17kMIIeFKEPXw7Nmz6NevHyIjI/Gvf/0LP/30E1555RU0bdpUL/PSSy/hH//4BxYsWIBt27ahcePGGDJkCEpKSgLdUkIIqR72D/2GbueEEHcYUIMQQgQ+6GFhYaHhcFRUFKKiotyKv/jii0hPT8eiRYv0Y23bttX/rqoq5syZg6eeegq33HILAOD9999HcnIyVq5ciTvvvNPb1hBCiO+wf+g3nPluoLRp0wYzZsyolboefPBBXH/99bVSV01cddVVeOyxx6o8N3DgQIwbN652Daqv0K2INCCoh+5QDyvhgx6mp6cjPj5e/8yePbvKW3/++ee4/PLLcdttt6FFixbo1asX3nnnHf384cOHkZubi8GDB+vH4uPj0adPH2zZsiW47SYNltrSxJtuugkTJ04Mej01YbfbkZ6ejjfffLPK87X5f0S9h/1Dv+Hgm+gMHDgQiqJU+enYsaNP9zx8+DD++c9/4sknnwywtb7x+OOPY968ecjNza1rU+o3qiqiVJr6+O5W9MILL0BRFEydOlU/VlJSgsmTJ6NZs2Zo0qQJRo4ciby8vAA0ihDzUA+Jjg96eOzYMRQUFOifadOmVXnr//3vf5g/fz4uueQSrFmzBg888AD+9Kc/4b333gMA/d8mOTnZcF1ycjL/3UitEmhN/O677/Dvf/8bjz/+eBCs9Y7IyEhkZmbib3/7G5dz1EQt9Q/DGbqdEwMtW7as8g19fHy8T/ebO3cu2rZti2uvvdZf0wLCLbfcgri4OLz55puYNWtWXZtTf6kFt6IffvgBb731Frp37244/sgjj2DVqlVYtmwZ4uPjMWXKFIwYMQLfffedT/UQ4ivUQwLAJz2Mi4tDXFycieJOXH755Xj++ecBAL169cLevXuxYMECjB071meTCQkGgdTEl19+GYMGDUL79u0DYZrfjB8/Hk888QSysrJw77331rU59Re6nfsNB9/EQHx8PO6+++6A3Mtut2PJkiW4//77A3K/QGCxWPCHP/wB77//PmbOnAlFUerapPqJN4EyfAioUVRUhNGjR+Odd97Bc889px8vKCjAu+++i6ysLFx33XUAgEWLFqFTp07YunUrrrrqKq/rIsRXqIcEQFD1MDU1FZ07dzYc69SpEz799FMAQEpKCgAgLy8Pqampepm8vDz07NnTq7oI8ZdAaeLJkyexatUqLFiwIABWBYaEhATccMMNWLx4MQff1RHk/mFDgG7nxCsuXLiAjh07omPHjrhw4YJ+/MyZM0hNTUXfvn3hcDgAAJs2bcKpU6cMa9UAYOzYsYiOjsbPP/9sOD5kyBA0bdoUJ06c8Mqm6dOnIzIyEr/99pvbuUmTJiEhIcHgRnT99dfjl19+wa5du7yqp0Hhw5qewsJCw6e0tNTj7SdPnoybb77Z7buRnZ0Nu91uON6xY0e0atWK6xtJvePbb7+FoihYsWKF27msrCwoiqJ/b6mHIUwQ1zj269cP+/fvNxz773//i9atWwMQwddSUlKwbt06/XxhYSG2bduGjIwM/9tGSAA5cuSIR9f0yi/3Vq1ahfLycoMeqqqKa6+9FklJSTh58qR+vKysDN26dcPFF1+M4uJir+wZO3YsmjdvDrvd7nbuhhtuQIcOHQzHrr/+emzatAlnzpzxqp4GBdd8+w0H38SAw+HAqVOn3D6a4MXExOC9997DwYMH8de//lW/bvLkySgoKMDixYthtVoBAJs3b4aiKOjVq5ehjrlz5yIpKQljx47VB+pvvfUW/v3vf+P1119HWlqaVzbfc889KC8vx0cffWQ4XlZWhk8++QQjR45EdHS0frx3794AQDfm6lC9EFbVuwBDS5cuxY4dO6o8n5ubC5vNhoSEBMNxrm8kdUFNejhw4ECkp6djyZIlbtcuWbIEF198sT5Aoh6GMD7ooVkeeeQRbN26Fc8//zwOHjyIrKwsvP3225g8eTIA6DExnnvuOXz++efYs2cPxowZg7S0NAwfPjwIjSXEMzVpYlJSEv7f//t/hs/ChQsRHx+PpKQk/T6bN29Gs2bN9JdMgPiuL1y4ECUlJQYPoenTp+PHH3/EokWL0LhxY6/sveeee3D69GmsWbPGcDw3NxfffPON2yx+7969oaoqNm/e7FU9DYog6mFDgYNvYmDfvn1ISkpy+/z5z3/Wy/Tp0wePPfYY5s6di//85z/45JNPsHTpUsyePRuXXnqp4V6JiYlu694SEhLw7rvv4ocffsALL7yAw4cP49FHH8Xw4cN9cmdq3749MjIy8MEHHxiOr1q1CmfPnsU999xjOH7RRRfBZrPhp59+8rquhoLidHr1AcwFGDp27BgefvhhLFmyxDAAIKQ+UpMeKoqCu+++G19++SUKCgr063777Tf8+9//NugZ9TB08UUPzXLFFVdgxYoV+PDDD9G1a1c8++yzmDNnDkaPHq2Xeeyxx/DQQw9h0qRJuOKKK1BUVITVq1dTQ0mtU5MmNm7cGHfffbfhs337dhQVFRleCO7btw9t2rRxu3/btm3xyiuvYMWKFViyZAm2bduGl19+GQ8//DD69+/vtb3XXXcdWrZs6aaHH374IZxOp5vGtmvXDgCoh9UQTD1sKHDNNzHQpk0bQ5oTjZYtWxr2Z8yYgS+//BJjx45FUVERBgwYgD/96U+GMqdPn0bTpk2rrOeGG27AH//4R8yaNQuffPIJoqOj8dZbb/ls95gxY/DAAw/g0KFDuPjiiwGImaf09HQMGDDArXzTpk1x6tQpn+sLe1TVfJRKWc5MgKHs7GycPHkSl112mX7M4XBg48aNeOONN7BmzRqUlZUhPz/fMPudl5enr30kpLYwo4djxozB7Nmz8cknn2DChAkAgI8++gjl5eWGjh31MITxQQ+94Xe/+x1+97vfeTyvKApmzZrFoHikzjHbR9R4//338eabb+KVV14xBJo8ffo0LrrooiqvmTRpEpYvX46HHnoIzZs3x8UXX6wHJPQWi8WC0aNH4x//+AfOnTuH2NhYAEIP+/bti7Zt2xrKaxpNPayGIOthQ4CDb2KgcePGbmsSq8Jms2HhwoW44oorEB0djUWLFlUZrEet5of397//HZ999hl27dqFrKwstGjRwme777jjDkydOhVLlizBM888g4KCAnz55Zd45JFHPNrF4ELVEKRoloMGDcKePXsMx8aPH4+OHTvi8ccfR3p6OiIjI7Fu3TqMHDkSALB//34cPXqU6xtJrWNGDzt27IgrrrgCS5Ys0QffS5YswVVXXeUWxZd6GKIwui8hAMz3EQFg165duP/++zFq1ChkZma6na9OD999911cfPHFOHDgADZv3oyYmBifbR4zZgxefPFFrFixAmPGjMH+/fuRnZ1dZbA3zSbqYTVQD/2GbufEZ7Q1NCUlJThw4IDb+WbNmuHs2bMer9+5c6ceVMN1QOYtTZs2xe9+9zt97eUnn3yC0tJSj26b+fn5aN68uV91hjVBCqgRGxuLrl27Gj6NGzdGs2bN0LVrV8THx2PChAnIzMzEt99+i+zsbIwfPx4ZGRmMdE7qLWPGjMGGDRtw/PhxHDp0CFu3bnXTHuphCMMAQ4R4xdmzZzFy5Ehceuml+Oc//+l2viY9XL9+vR601V897Ny5M3r37q27nn/wwQew2Wy4/fbbq7QbAPWwOoKohxs3bsSwYcOQlpYGRVGwcuVKw3lPgfxefvllj/ecMWNGQPLSBxIOvolP7N69G7NmzcL48ePRq1cv3HfffYY1j4CYETp79qzbcQAoLi7G+PHj0blzZ0yaNAkvvfQSfvjhB79sGjNmDP773//ihx9+wJIlS9CrVy906dLFrdyvv/6KsrIydOrUya/6whotlYTZTwB57bXX8Lvf/Q4jR45E//79kZKSguXLlwe0DkICyZ133gmr1YoPP/wQS5YsQWRkJO644w5DGephCFOHekhIqOF0OjF69Gjk5+djxYoVaNSokVuZjh074vDhw1Ven5OTg4ceegg33HADfve73+HRRx/FL7/84pdNY8aMwTfffIOcnBxkZWXh5ptvrnIZkGYT9bAagqiHxcXF6NGjB+bNm1fl+ZycHMNn4cKFUBRF95T0RJcuXQzXbdq0ySu7Ag3dzonX2O12jBs3DmlpaZg7dy4OHz6MK664Ao888ggWLlyol8vIyICqqsjOztZzNms8/vjjOHr0KLZu3YoOHTpg3bp1GDt2LHbu3ImoqCif7Bo6dCiaN2+OF198ERs2bPD4Jiw7OxsA0LdvX5/qaRDUolvR+vXrDfvR0dGYN2+eR/ElpL7RvHlzDB06FB988AFKSkpw4403us2cUA9DGLpZEmKamTNnYs2aNfjXv/7ltqZaIyMjA//85z/xv//9Tw9ypjFx4kQ4nU68++67sFqt6NKlCyZMmIC1a9f67A4+atQo/PnPf8bDDz+M//3vf9XqoaIoXOZWHUHUw6FDh2Lo0KEez7vG/vnss89w7bXXun2HXImIiKhXcYM4+CYGCgoK3KJCamgui8899xx27dqFdevWITY2Ft27d8czzzyDp556Cn/4wx9w0003AQCuvvpqNGvWDF9//bWhs/nNN9/gzTffxPTp0/XAW4sWLcLAgQPx9NNP46WXXtLLatEwjxw5UqPtkZGRuPPOO/HGG2/AarVi1KhRVZZbu3YtWrVq5Zbyh1TCqXohrpzpIeGJGT3UGDNmDP7whz8AAJ599lm38tTDEIZ6SAiAmjVxz549ePbZZ9G/f3+cPHnSraymmzfffDMiIiLw9ddfY9KkSfr5RYsWYdWqVVi8eLEexO3111/H3Xffjfnz5+PBBx/UyyqKggEDBri9wK+KpKQk3HjjjVi2bBkSEhJw8803V1lu7dq16NevH5o1a1bjPRssPuhhYWGh4XBUVJTPL5Y18vLysGrVKrz33ns1lj1w4ADS0tIQHR2NjIwMzJ49G61atfKrfn/g4JsYOH78uFsqGo27774bO3bswPPPP48pU6YYIlc+8cQT+OyzzzBx4kT8+OOPSEhIgM1mw+jRo7Fs2TI9UuW5c+dw7733olevXoY84ddccw0efvhhvPLKKxgxYoS+vre4uNgtaFF1jBkzBm+88QYGDRqE1NRUt/NOpxOffvopJkyYwIAa1cFoloTUqIeVGTZsGJo2bQqn04nf//73buWphyEM9ZAQADVr4unTp6GqKjZs2IANGzZUWQYAkpOTcdNNN+Hjjz/WB9/Hjx/HI488gmHDhmHs2LH6NaNHj8ann36Kxx57DEOHDkXbtm1RVFQEAFXqmifGjBmDL7/8ErfffnuVA7+CggL8+9//xptvvmn6ng0SH/QwPT3dcHj69OmYMWOGX2a89957iI2NxYgRI6ot16dPHyxevBgdOnRATk4OZs6ciWuuuQZ79+7Vo9/XNhx8Ex0zbw8vu+wy2O12t+NWqxXff/+92/GHH34Y8+fPx7p16zBo0CDExsZ6nLV59dVX8eqrr+r7P/30E06dOoXFixebbQJsNhsA946xxueff478/HzD21NSBXSzJA0cM3pYGYvFgoiICAwbNsxj/mXqYYhCPSTElCYOHDiw2ijmlXn00UcxcOBAHDhwAJdccglatmyJ/Pz8Ksu6xn3ZuHEjFEXBk08+aaouoGY9XLRoEZo1a4a77rrL9D0bJD7o4bFjxwypaP2d9QaAhQsXYvTo0R7/v9Wo7MbevXt39OnTB61bt8bHH3+sZyipbRhwjQSVdu3aYcKECXjhhRe8vvbbb79FRkaGR/egqnjnnXfQpEkTj2/CXnzxRUyZMsWrt6UNEtWLYBqc6SEEK1euxG+//YYxY8Z4LEM9DFGoh4QEnGuuuQY33HCDYWmNWb799lvceeed6Natm+lr3nnnHbRr1w5XX3212zm73Y5XX30VTz31lF9pzRoEPuhhXFyc4ePv4Ps///kP9u/fj/vuu8/raxMSEnDppZfi4MGDftngD5z5JkFn/vz5Pl03efJkTJ482VTZL774Aj/99BPefvttTJkyBY0bN66y3JYtW3yypcHBmR5CTLFt2zbs3r0bzz77LHr16oUBAwZUW556GIJQDwkJCv/61798uq661FKuLF26FLt378aqVaswd+7cKpfYREZG4ujRoz7Z0uCoB3r47rvvonfv3ujRo4fX1xYVFeHQoUMel0/UBhx8k7DgoYceQl5eHm666SbMnDmzrs0JfeqBuBISCsyfPx8ffPABevbs6ZVLeDChHgYY6iEhIcuoUaPQpEkTTJgwgUtsAkEQ9bCoqMgwI3348GHs2rULiYmJeoC0wsJCLFu2DK+88kqV9xg0aBBuvfVWTJkyBYBY3jBs2DC0bt0aJ06cwPTp06sNQlobcPDdQDETLTeUCER7vF3jGdZ4k5+R0X1JiOOPfixevLjeDLo1qIcBhnpIGhjh1Ec0uwa9OsLpefhNEPVw+/bthmDOmZmZAICxY8fq/88uXboUqqp6HDwfOnQIp06d0vePHz+OUaNG4fTp00hKSsLVV1+NrVu3IikpySvbAgkH34QQdxwO8TFblhBCwhXqISGECIKoh2YC9k2aNMmQns4V1xclS5cu9cqG2oCDb0KIO3SzJIQQAfWQEEIE1EO/4eC7BpxOJ06cOIHY2FjmQSUhiaqqOHfuHNLS0mCxmExwQDdLUgXUQxLqUA9JoKAeklCHelg3cPBdAydOnHBLDk9IKHLs2DG0bNnSXGGn6sWbTYprQ4F6SMIF6iHxF+ohCReoh7ULB981EBsbK/9mAcA3myQUUQE4K32XTcA3m6QKqIck9KEeksBAPSShD/WwLuDguwYqXIkUUFxJKOOdW5wTUM2u1eGanoYC9ZCEC9RD4i/UQxIuUA9rFw6+CSHu8M0mIYQIqIeEECKgHvoNB9+EEHcoroQQIqAeEkKIgHroNxx8E0LcYSoJQggRUA8JIURAPfQbDr4JIe7wzSYhhAioh4QQIqAe+g0H34QQdyiuhBAioB4SQoiAeug3JjOqE0IaFJpbkdmPF8yfPx/du3dHXFwc4uLikJGRgX/961/6+YEDB0JRFMPn/vvvD3QLCSHEHEHUQ0IICSmoh37DmW9CiDuqKj5my3pBy5Yt8cILL+CSSy6Bqqp47733cMstt2Dnzp3o0qULAGDixImYNWuWfk2jRo28qoMQQgJGEPWQEEJCCuqh33DwTQhxJ4huRcOGDTPs/+1vf8P8+fOxdetWffDdqFEjpKSkeHVfQggJCnSzJIQQAfXQb+h2TghxRxNXsx8AhYWFhk9paWmN1TgcDixduhTFxcXIyMjQjy9ZsgTNmzdH165dMW3aNJw/fz5oTSWEkGrxQQ8JISQsoR76DWe+CSHuqF6s1VFFufT0dMPh6dOnY8aMGVVesmfPHmRkZKCkpARNmjTBihUr0LlzZwDAXXfdhdatWyMtLQ27d+/G448/jv3792P58uU+N4cQQnzGBz0khJCwhHroNxx8E0Lc8cGt6NixY4iLi9MPR0VFebykQ4cO2LVrFwoKCvDJJ59g7Nix2LBhAzp37oxJkybp5bp164bU1FQMGjQIhw4dwsUXX+xbewghxFfoZkkIIQLqod/Q7ZwQ4o4TXrgViUu06OXap7rBt81mQ/v27dG7d2/Mnj0bPXr0wNy5c6ss26dPHwDAwYMHA91KQgipGR/00CwzZsxwy+7QsWNH/XxJSQkmT56MZs2aoUmTJhg5ciTy8vIC2z5CCDFLEPWwocDBNyHEnVpe0+N0Oj2uEd+1axcAIDU11e96CCHEa4Ksh126dEFOTo7+2bRpk37ukUcewRdffIFly5Zhw4YNOHHiBEaMGBHI1hFCiHm45ttv6HZOCHFDdapQTYqm2XIa06ZNw9ChQ9GqVSucO3cOWVlZWL9+PdasWYNDhw4hKysLN910E5o1a4bdu3fjkUceQf/+/dG9e3dfmkJInaJACXodKtjBCSbB1EMAiIiIqDK7Q0FBAd59911kZWXhuuuuAwAsWrQInTp1wtatW3HVVVd5XRchhPhDsPWwIcDBNyHEnSDmcTx58iTGjBmDnJwcxMfHo3v37lizZg2uv/56HDt2DF9//TXmzJmD4uJipKenY+TIkXjqqad8aAQhhAQAH/SwsLDQcDgqKsrjUpwDBw4gLS0N0dHRyMjIwOzZs9GqVStkZ2fDbrdj8ODBetmOHTuiVatW2LJlCwffhJDah3m+/YaDb0KIO0EMqPHuu+96PJeeno4NGzZ4dT9CCAkqPuih2ewPffr0weLFi9GhQwfk5ORg5syZuOaaa7B3717k5ubCZrMhISHBcE1ycjJyc3N9aQkhhPgHA675Ddd8E0Lc4ZoeQggR+KCHx44dQ0FBgf6ZNm1albceOnQobrvtNnTv3h1DhgzBV199hfz8fHz88ce12UJCCDFHEPuHGzduxLBhw5CWlgZFUbBy5UrD+XHjxrkFqLzxxhtrvO+8efPQpk0bREdHo0+fPvj++++9sivQcPBNCHGHg29CCBH4oIfeZH+oTEJCAi699FIcPHgQKSkpKCsrQ35+vqFMXl5elWvECSEk6ASxf1hcXIwePXpg3rx5HsvceOONhgCVH374YbX3/Oijj5CZmYnp06djx44d6NGjB4YMGYKTJ096ZVsg4eCbEOIOB9+EECKoRT0sKirCoUOHkJqait69eyMyMhLr1q3Tz+/fvx9Hjx5FRkaGv60ihBDvCaIeDh06FM899xxuvfVWj2WioqKQkpKif5o2bVrtPV999VVMnDgR48ePR+fOnbFgwQI0atQICxcu9Mq2QMLBNyHEDVVV9YiWNX4YUIMQEsYEUw8fffRRbNiwAUeOHMHmzZtx6623wmq1YtSoUYiPj8eECROQmZmJb7/9FtnZ2Rg/fjwyMjIYbI0QUif4ooeFhYWGj6fUsmZYv349WrRogQ4dOuCBBx7A6dOnPZYtKytDdna2IWilxWLB4MGDsWXLFp9t8BcGXCOEuOPNG0vOfBNCwpkg6uHx48cxatQonD59GklJSbj66quxdetWJCUlAQBee+01WCwWjBw5EqWlpRgyZAjefPNNb1tACCGBwQc9NBuAsiZuvPFGjBgxAm3btsWhQ4fw5JNPYujQodiyZQusVqtb+VOnTsHhcCA5OdlwPDk5Gfv27fO6/kDBwXeYURs5Zc0SjNyz4d6+egMH3ySMqVUdUYJfl1KLP8Gw1j1PBFEPly5dWu356OhozJs3r9o1kIRUR33qN7kSCD0J9/bVO3zQw2PHjiEuLk4/bDYGhit33nmn/vdu3bqhe/fuuPjii7F+/XoMGjTIp3vWBXQ7J4S4wzXfhBAioB4SQojABz30NQBlTbRr1w7NmzfHwYMHqzzfvHlzWK1W5OXlGY7XddBKDr4JIe6oqncfQggJV6iHhBAiqEd6ePz4cZw+fRqpqalVnrfZbOjdu7chaKXT6cS6devqNGgl3c4JIW6oTvExW5YQQsIV6iEhhAiCqYdFRUWGWezDhw9j165dSExMRGJiImbOnImRI0ciJSUFhw4dwmOPPYb27dtjyJAh+jWDBg3CrbfeiilTpgAAMjMzMXbsWFx++eW48sorMWfOHBQXF2P8+PHeGRdAOPgmhLjDNd+EECKgHhJCiCCIerh9+3Zce+21+n5mZiYAYOzYsZg/fz52796N9957D/n5+UhLS8MNN9yAZ5991uDGfujQIZw6dUrfv+OOO/Dbb7/hmWeeQW5uLnr27InVq1e7BWGrTTj4JoS4w84mIYQIqIeEECIIoh4OHDiw2nSNa9asqfEeR44ccTs2ZcoUfSa8PsDBNyHEDbpZEkKIgHpICCEC6qH/cPBNCHFH9eLNJgMMEULCGeohIYQIqId+w8E3IcQdp/yYLUsIIeEK9ZAQQgTUQ7/h4Lueo0Dx8UIz1wUq01zVvy7ddpc3XypqfhPm1u4a2xPcthiQ7fH238ZMu+sLqlOFavLNptlyhAQan/URMKmRgK/a4pdt3lcGwB+NMetDqPrcrlDSP1eoh6Q+Y/o3Wa3mVa9zgf/dO433NdFPrLlfWHUbgqdZ1eimyX5iKOoi9dB/OPgmhLjDN5uEECKgHhJCiIB66DccfBNC3FHlx2xZQggJV6iHhBAioB76DQffhBA36FZECCEC6iEhhAioh/4TqIWyhJBwwunlxwvmz5+P7t27Iy4uDnFxccjIyMC//vUv/XxJSQkmT56MZs2aoUmTJhg5ciTy8vIC0SpCCPGeIOohIYSEFNRDv+HgmxDihpbH0ezHG1q2bIkXXngB2dnZ2L59O6677jrccsst+PHHHwEAjzzyCL744gssW7YMGzZswIkTJzBixIggtJIQQmommHpICCGhBPXQf0y5ne/evdvrG3fu3BkREfRqJyQkCWJAjWHDhhn2//a3v2H+/PnYunUrWrZsiXfffRdZWVm47rrrAACLFi1Cp06dsHXrVlx11VXeVRYEqIeENDAYYMgj1ENCGhjUQ78xpX49e/aEoihQTSZLt1gs+O9//4t27dr5ZRwhpG7w5o2lVq6wsNBwPCoqClFRUdVe63A4sGzZMhQXFyMjIwPZ2dmw2+0YPHiwXqZjx45o1aoVtmzZUi8G39RDQhoWvuhhQ4F6SEjDgnroP6ZfPW7btg1JSUk1llNVFV27dvXLqIaE//kZvcxrqFQu7+FaxbvVCKrbr0vua8ddctAq+nnV5bhSqZ2WimMG4yyG84Gz2cV2vaB7OVWpPm9lFZUBCK18j6oTUB3mywJAenq64fj06dMxY8aMKq/Zs2cPMjIyUFJSgiZNmmDFihXo3Lkzdu3aBZvNhoSEBEP55ORk5ObmetmK4EE9rB0Ck78WqErrzGlk9fcQVdekPdYaznu+j2edckX8WD09hZr1zsVGD+Wr1r4abAxB/XPFFz1sSFAPa4ca9dBkP9Fwnxr7VFYPx7V7Va1/qosuVGiQw2XfuFU1LVNd+oaicrlvrdJ2V5v9tbXiKbnarOE+CtV1TKlUpspKq9dF6mF4Y2rwPWDAALRv396tQ+yJ/v37IyYmxh+7CCF1iC9vNo8dO4a4uDj9eHWz3h06dMCuXbtQUFCATz75BGPHjsWGDRv8MbnWoB4S0rDgTI9nqIeENCyoh/5javD97bffenXTr776yidjCCH1BB/W9GjRy81gs9nQvn17AEDv3r3xww8/YO7cubjjjjtQVlaG/Px8Q2cuLy8PKSkp5u0PItRDQhoYXOPoEeohIQ0M6qHfMNo5IcSN2o5m6XQ6UVpait69eyMyMhLr1q3Tz+3fvx9Hjx5FRkaG/xURQoiXMLovIYQIqIf+43W4SVVV8cknn+Dbb7/FyZMn4XQan+zy5csDZhwhpG5QVX1Jkqmy3jBt2jQMHToUrVq1wrlz55CVlYX169djzZo1iI+Px4QJE5CZmYnExETExcXhoYceQkZGRr0ItuYK9ZCQ8CeYehhOUA8JCX+oh/7j9eB76tSpeOutt3DttdciOTkZSo2BbgghIYdTER+zZb3g5MmTGDNmDHJychAfH4/u3btjzZo1uP766wEAr732GiwWC0aOHInS0lIMGTIEb775prctqBWoh4Q0AIKoh+EE9ZCQBgD10G+8Hnz/v//3/7B8+XLcdNNNwbCHEFIPCGZAjXfffbfa89HR0Zg3bx7mzZvn3Y3rAOohIeEPAwyZg3pISPhDPfQfr9d8x8fH12l+xnnz5qFNmzaIjo5Gnz598P3333ssu3jxYiiKYvhER0fXorWEhCaqqnj1aahQDwkJf6iH5qAeEhL+UA/9x+uZ7xkzZmDmzJlYuHBhraeL+Oijj5CZmYkFCxagT58+mDNnDoYMGYL9+/ejRYsWVV4TFxeH/fv36/t15QYVlPyMQBU5aavPd6jAUumcsWzlMsZ7oMp915yHTrXccFyV+xXH7YbjKuzajbQKoCiR8q8Rciv2Lfq+trUYjpu1UbdNyympOl3KOaspJxMbuuWn1G5u/LcJ5XyPfLNpDuphYAiUPrrdr0Z9BKrSSGPV1efBrSmXbE066in3bGU858z1sO+hfJV5aqu53jU3rwJ3rdTzAOua6aJXIah/bjZQD01BPQws3uuih/5iNfmwXftSWh/L4qGvZbGIPpnV5bzikg9cy9ftdIr+nkPvD4p+n8NZZjjvVLX9Unm9HZDXQNE0WvYHLVHSJpvcF7ZYLXJfMdqonfdko6Zpuo1Ou7TJ2Ket2K/o27pqpFv/UPYL3XXRtf9oPO/6b18fdFCDeug/Xg++b7/9dnz44Ydo0aIF2rRpg8jISMP5HTt2BMw4V1599VVMnDgR48ePBwAsWLAAq1atwsKFC/HEE09UeY2iKPUmRREhoYKqeiGu9ef/hFqHekhI+EM9NAf1kJDwh3roP14PvseOHYvs7GzcfffdtRpQo6ysDNnZ2Zg2bZp+zGKxYPDgwdiyZYvH64qKitC6dWs4nU5cdtlleP7559GlSxeP5UtLS1FaWqrvFxYWBqYBhIQQ3rgLNWS3IuohIeEP9dAc1ENCwp9g6uHGjRvx8ssvIzs7Gzk5OVixYgWGDx8OALDb7Xjqqafw1Vdf4X//+x/i4+MxePBgvPDCC0hLS/N4T80jpzIdOnTAvn37vLItkHg9+F61ahXWrFmDq6++Ohj2eOTUqVNwOBxITk42HE9OTvb4ADt06ICFCxeie/fuKCgowN///nf07dsXP/74I1q2bFnlNbNnz3b7RyKkweFUoDKaZY1QDwlpAFAPTUE9JKQBEEQ9LC4uRo8ePXDvvfdixIgRhnPnz5/Hjh078PTTT6NHjx44e/YsHn74Yfz+97/H9u3bq71vly5d8PXXX+v7ERFeD38DitcB19LT0xEXFxcMWwJORkYGxowZg549e2LAgAFYvnw5kpKS8NZbb3m8Ztq0aSgoKNA/x44dq0WLCakfaHkczX4aKtRDQsKf2tLDF154AYqiYOrUqfqxkpISTJ48Gc2aNUOTJk0wcuRI5OXl+d+oIEA9JCT8CaYeDh06FM899xxuvfVWt3Px8fFYu3Ytbr/9dnTo0AFXXXUV3njjDWRnZ+Po0aPV3jciIgIpKSn6p3nz5t4ZFmC8Hny/8soreOyxx3DkyJEgmOOZ5s2bw2q1uv2nk5eXZ3rNTmRkJHr16oWDBw96LBMVFYW4uDjDh5CGBqNZmoN6SEj4Uxt6+MMPP+Ctt95C9+7dDccfeeQRfPHFF1i2bBk2bNiAEydOuM0I1Reoh4SEP77oYWFhoeFTefmGPxQUFEBRFCQkJFRb7sCBA0hLS0O7du0wevToGgfrwcbrwffdd9+Nb7/9FhdffDFiY2ORmJho+AQLm82G3r17Y926dfoxp9OJdevWISMjw9Q9HA4H9uzZg9TU1GCZSUhYoEq3IrOf+sZ//vMf3H333cjIyMCvv/4KQOSg3bRpU0DroR4SEv4EWw+LioowevRovPPOO2jatKl+vKCgAO+++y5effVVXHfddejduzcWLVqEzZs3Y+vWrabvTz2sGeohIebwRQ/T09MRHx+vf2bPnu23HSUlJXj88ccxatSoal+E9enTB4sXL8bq1asxf/58HD58GNdccw3OnTtnuq5Aa6jXTu9z5szxqaJAkJmZibFjx+Lyyy/HlVdeiTlz5qC4uFiPbjlmzBhcdNFF+j/qrFmzcNVVV6F9+/bIz8/Hyy+/jF9++QX33Xdf0G0NeGqxGlLm6Cm63I4b00ZYLBF6GoYI17QMMn2Dlp7BikjDeYuHdzUOaKkkRHqGclW80XLIlBFljmJx3HFBbs/L8+K4KssrSiSslsbCNmsjuRXpSmzWxgYbIxTNVmm7h6+yE1qKCJneQqY301JKaDZq58u19BdyvyINRnlFijS3NGR2w76WYkL/F9bLuz4/Wd71u1APUk544y5U39zOP/30U9xzzz0YPXo0du7cqb9hLSgowPPPP4+vvvoqYHVRD32jtvVRS4dlTJ8jU+joaWiM+xY97aE87jE1ozFVmW6Bi266lte0q6It7vrqmjLMoWuNMUWOq87p1+vaYyzvel1FKh2j7mn1a/uA0y3tjpZiR9V1zzWFTujpnyu+6KFrMK6oqChERUVVec3kyZNx8803Y/DgwXjuuef049nZ2bDb7Rg8eLB+rGPHjmjVqhW2bNmCq666qkZ7qIf1Xw9dCV6KMffUra5purQ+VqQlxrC1WZoAAKIUsY1W5b4qcqNHqkY9cyhCF0ojSgAAJYro711QC8S+U/w+7I4iUa5cDITs5WLf4XTqfS5FphqzajZFyLojYsW+VdpkEQOwGCVe2tjYYKNVNaYasytC70oVzUZpiyq2ZU6xtTsvGLZav9HhLKvQSi39GIypdfV/CrdUjNq/jYsOehAa7d+0PqQc80UPjx07Zhgge9JCs9jtdtx+++1QVRXz58+vtuzQoUP1v3fv3h19+vRB69at8fHHH2PChAk11hUMDfUp2nldcccdd+C3337DM888g9zcXPTs2ROrV6/Wg2wcPXoUFkuFCJ09exYTJ05Ebm4umjZtit69e2Pz5s3o3LlzXTWBkJAglKP7Pvfcc1iwYAHGjBmDpUuX6sf79etn6NgGAuohIeGPL3qYnp5uOD59+nTMmDHDrfzSpUuxY8cO/PDDD27ncnNzYbPZ3Fwqk5OTkZuba8oe6iH1kJBA4oseBnKZhjbw/uWXX/DNN994fd+EhARceuml1S4xqUwwNNTrwXdNfvKtWrXyyRCzTJkyBVOmTKny3Pr16w37r732Gl577bWg2kNIOOJ0KnCadJ80W6622L9/P/r37+92PD4+Hvn5+QGti3pISPjjix6amek5duwYHn74YaxduxbR0dGBMdYF6qGAekhIYKjL/qE28D5w4AC+/fZbNGvWzOt7FBUV4dChQ7jnnntMlQ+Ghno9+G7Tpk21uRsdDodPhhBC6g+h7HaekpKCgwcPok2bNobjmzZtQrt27QJaF/WQkPDHFz00M9OTnZ2NkydP4rLLLtOPORwObNy4EW+88QbWrFmDsrIy5OfnG2a/vQkkRj0khASSYPYPi4qKDDPShw8fxq5du5CYmIjU1FT84Q9/wI4dO/Dll1/C4XDoHkCJiYmw2cTSiUGDBuHWW2/VX8Q9+uijGDZsGFq3bo0TJ05g+vTpsFqtGDVqlCmbgqGhXg++d+7cadi32+3YuXMnXn31Vfztb3/zyQhCSP0ilN3OJ06ciIcffhgLFy6Eoig4ceIEtmzZgkcffRRPP/10QOuiHhIS/gRLDwcNGoQ9e/YYjo0fPx4dO3bE448/jvT0dERGRmLdunUYOXIkADELc/ToUdOBxKiHhJBAEsz+4fbt23Httdfq+5mZmQDEkpYZM2bg888/BwD07NnTcN23336LgQMHAgAOHTqEU6dO6eeOHz+OUaNG4fTp00hKSsLVV1+NrVu3IikpyZRNwdBQrwffPXr0cDt2+eWXIy0tDS+//HK9TYFBCDFPKA++n3jiCTidTgwaNAjnz59H//79ERUVhUcffRQPPfRQQOuiHhIS/gRLD2NjY9G1a1fDscaNG6NZs2b68QkTJiAzMxOJiYmIi4vDQw89hIyMDFPB1gDqISEksASzfzhw4ECo1UyXV3dOwzXVYeV12r4QDA31evDtiQ4dOlQZMIS44HMUXzPRe92jm2sRLCO0SOaWqEpRLEVE8UiI/WjICJLavlNso1Rxj0gZcdLiEonTrgpXMruM8nhBRo4sjiiQ27MAgPOO0+K8/QwAoKRMi5arRTuPgi1SRquMFGlJGlnFeo7GEOlXGqsiimWMHmEzwmCbhlNGhNRsK4WIYl5iEdEqS5ULcl9Gs4QWzfK83BqjWpY7S+HQI6Ebo1tqUXy1KJdwiSxsOtqlRg1RL2sDp6rAaVI0zZarLRRFwV//+lf85S9/wcGDB1FUVITOnTujSZMmtWYD9dBIjdF79YLV66PbffzQR00bLRZj9gerzKSga6aHrA9a1HItkrge9Vyej1S0CLtSoyCjCEs9jZCRd7XzrroKVOiYQxHaUi7rsitlcltqOG9XS6RNxijnrrZ6ygJRrkXxVTXdk5rnlOWcZbr+KapoZ0XkdHP6p6H6qH91Ef28LvXwtddeg8ViwciRI1FaWoohQ4bgzTffNH099bDhUFO/0XVrsVTooN4vlJlloq2ir9VIEX2veKfoizVVRYTxZtLFt1mU0JYmkcbvfXG5+F0WlInf99lSoQ9nZR/rrEX0AwssuQabKrIplKKibyg0UsuCEx0pbGsc0ULYBrEEo6lT9Bubyr5t0yhxXbzNIssbbSyyCxtPlwrNOl0m9O4sROT1Aqvos563iD5siUP0ae1VZKZwOrVsD8Znr8uYx35g6BHK/UNfCIaGej34dk2foaoqcnJyMGPGDFxyySU+G0IIqT94k6+2Pub5BkTu12BHrqUeEhL+1KYeugYGi46Oxrx58zBv3jy/7ks9JIQEgnDoH/pCIDXU68F3QkKCW0ANVVWRnp7u99Q+IaR+EMoB16699tpqg/588803AauLekhI+EM9NAf1kJDwJ5T10BeCoaFeD76//fZbw77FYkFSUhLat2+PiIiAebETQuoQJ7xwKzLrUlxLuAbisNvt2LVrF/bu3RvwPLTUQ0LCH+qhOaiHhIQ/oayHvhAMDfVaDQcMGOBTRQ0F02sbdQK71ltbv2O1aOsWjfs2SxNEKWKdgrbGW1tH3UQVa33iZNkmci1PbKSoI0aul7G6LMmzyyV7FxziwDm7WBNUaBf3PQuxDudURCNDW+3lYu2Pw1EobYzW13onRKQDAJo7UwEATaWtcZE2o03SGLmrLxeUpuBCuWaTMLJIs02ubSxSigEAxYpYy1Mi266t7yxTiuR9LVDkunJtHbhDX6oo1jJZ5M/JqRptqXnNj4e1jx7QviPBXDMUzIAas2fPxvLly7Fv3z7ExMSgb9++ePHFF9GhQwe9zMCBA7FhwwbDdX/84x+xYMGCGu/vKXfrjBkzUFRU5JWtNUE9DBAmY2FUlDerj3I9tcU1FkaUro0RLjEwbIqMdaEIrYiWuhilamu4RR12RayDLlWM66wjIe4b5YyS14vrYmTdNou4PspikfVruqpIGys0xCHFo1weKJXrCsucYo3iBbn+ukTaUCrXgNtljAtt/WGUHiND6JpDcRhsL5E6WKqItY5lqoyBoQiNLpcxMhTFquufU675djo1/YM8DllWbF31D6qrztXf2BcaoRyAknpINF2sQItbYdE1QtNIq+z7aLGAGsk13k0htqkyH/3FceJ73i1eaE3XZmIN97kSoXu/FAvd/F+x0MPjcvvreanRZeJ6h0XGm7AKLbJrW0fFd1ORNkVYpTZbRWygJhDr0JvJ9egpNtFPvKiRqKOlMAHtGgsbWzcWOhcbLTRs72nR39xTIGw7VCjaBmEC7KqMrSEPaHrokM9KcVrc1nhXoD1zc/26UCKU9dAXgqGhHno2Rj7//HPY7XbTN/3qq69w4cIFnwwihNQ9qgyoYebjrbhu2LABkydPxtatW7F27VrY7XbccMMNKC4uNpSbOHEicnJy9M9LL73kV5vuvvtuLFy40K97ANRDQhoawdTDuoJ6SAjxhXDUQ1/wR0NNDb5vvfVW5Ofnm77pnXfeiZycHJ8MIoTUPdqbTbMfb1i9ejXGjRuHLl26oEePHli8eDGOHj2K7OxsQ7lGjRohJSVF/8TFxfnVpi1btiBavrX3B+ohIQ2LYOphXUE9JIT4QjjqoS/4o6Gm3M5VVcW4ceMQFRVl6qYlJSU+GRPWVLNYHzDvru6eMsLoTqm7VVZyrwQq0kjYlBg3d/M4VewnRIiyiTI9Q2KUsClJfrea2aRbpSLT38gf1XmH2J4rF9v8MnH9qRJho61Eut9I75syq3DdOW89JfblS/MIa7SeWkxzN0+2CBtbRAu3o+bR4p4JNmFDbITYNrKqst1aijFhy+kyUf43acOZUunqWSpdPMtdUxeJjSrdMlWLQz+lpcDQzylaih0NmYJHTzFRcW1V1Og+Xodul06Yd5bSyrlGuo2KijKlGQUFwuU/MTHRcHzJkiX44IMPkJKSgmHDhuHpp59Go0aNqrqFAddcslrE3e3bt+Ppp5+u8fqaoB6ax/tlOBo1LcdxRab58pBSR3et1FLWWGyVtFF8p7TlODEQL3ninAkAgFgI38VYq9CgaKu4V74UrhycMliipWhsIt3XYyPEdbGRwsbGERZ5H1HeJrcRVbidl8vffpmUkhK5LS4Xv7pzdtGecw7Zfqd8Pi6PqQVEWxKiIuV95PUO0YZzqrC1UHfXtxruo1ZSA03XND1UXJcAuKbYcXMnl+X8XH6j364WluH4oof1Beoh0dL/mZlv09OQSQ2wOrV0rjJdl0wplhItvulXtRIvUpp/fI+47oMVAIC0L8TxqGPJwgK59OW81KricrFfJN3aixWhw1rfValkq/Z37VykLKu5xMdaxL2ayqWSqbKb0ClWfNcuS88DACQNExrvvPt2AECT2/8fAOC3A2KZY+4FmSZS9hP1NJAW4/8v5qi+/xfKhLIe+kIwNNTU4NvbBeWjR4/2e5aKEFJ3+LKmJz093XB8+vTpmDFjRrXXOp1OTJ06Ff369UPXrl3143fddRdat26NtLQ07N69G48//jj279+P5cuX12hPfHy8Yd9isaBDhw6YNWsWbrjhBlNtqg7qISENi1Be40g9JIQEklDWQ18IhoaaGnwvWrTIp5uT6vAtkJBrcAf3mR4ZzEIPMCQDVSjizWCUEotGTvG2UAuwFm81zngnydnl9EbinVX7JuLtYbe03wAADjnTXVIq7q0F2DhdKurIK5EBNuSUTrRV7KNYfIGL1BYAgELrcQDAedkim7Ux4iDOaTPerRqLa7XAGS1jxOxycrQIhNEsStimBdCIjhIzOVY5E77nRBIA4KBVBkvSn6doqzY745QR2rQZHqdFbB1yNtuhlMMiA4MoMsiR66yaqrrs67NxMNTldeChOsCpwnw0S9muY8eOGTpVZmZCJk+ejL1792LTpk2G45MmTdL/3q1bN6SmpmLQoEE4dOgQLr744mrvGWy9oh4GkBo8gjzjqo/ydh70UddDi9AsixJp8AYCKs14qwkAgHjpIZRkE9/jtMbiXj0SxIzGd78JTdlZ9F8AQIJykbheBiaKl7rXPEbU3Ux6EsVFVu21Y5OaU3nmu0zOZLt6FxXahbacljM0lgvieFm50Kh8iPgJ+eqvAICMJi0BAP2ShO3/ly+ew4liY/AjuGiUqweQqjphsZTLonLmWgaBc9c/48y4x5nwmqgHgdd80cP6AvUw9NC8OHz3HKoJzeukskeL07B1Sg8XhyJ+73Z5vFT2lfLt4nd9+GRTAEDSWx8BAL5fKjprm35rDQA4UCjKHysWfbU8iMBsZxUxG33OmQsAKCkXHnCldrF1OCviAmh/P192WuzLPtiFiLPiXtYUAEBOkZhlP1okvOgOFgrt/rFQ2HL1SeGdd0XxRwbbtbZobdPaqrXd6eLto1bqu1U8w+D224Lp2eMtoayHvhAMjWPuB0KIG7682YyLi/NqRmPKlCn48ssvsXHjRrRs2bLasn369AEAHDx4sMbBNyGEBJKGNtNDCCGeoB76DwffASR4byk9rzVxXctoVVxnvOW6Rpk2wqbGIFqu72skyzSRaxHjbdoab/GqKi1GzKK0jhPpZ5q2F7PL2gs+xwXxJrPpWTF3HX9WziCdayJtEfsOuW6muFzUd+q8eNuYK9NGaERYYxDvFOeaNRJltbU7rRuJN5DpjcQb0NRYEd4/vqnYj24q3kzqt5SPq3WRsF1bZ1TiFLNRZU7R1lJ5vNQp6rPLZ1PmkmLCodjhlKmFrPJtqD4r5DaDLaiY8QnO2p9grnUUbzbNl/UGVVXx0EMPYcWKFVi/fj3atm1b4zW7du0CAKSmplZ5vmnTplBMzqKeOXPGtK2kbqlZU6tf621x0cPKsTA0byBt/WCMU8zYNFKNa7XjbFqcCVGjNkPtkDO92n0SncJrxzXdjaZhKVFCN5pL75y4SLGNtYmtzeqQtqt6h6VM6tO5MmFLoV1qqPQ6ypXeRY2ssl3nRd3lZcKWIos2U2ScXU+Q1xXJGZ8Sh9S/ctF2O4RNdotMq6h5AFnK4VTFOS3mhevW9NpvSW2s2faXYOphMKAeNkz0GXOtT6J/BbTfonHGW1WdcMpZZO2cQ/6+7RB9q1K5LVJFX0iLn6NAatAF8cJ9wSyhPXtLxEz2SWUvAKC4/KS4T7noi5U7ZJ/KKVM0anqi2yH7S5X6Taosa5dlyx1idvy81POzykEAwK9y7fc+6ekY5RBeSI3PCz38MKcNAKDrf8VMuRZDqLBMlW2zG9paKlMsas/CoduqeQeUu82Gu/cHnVojxKYe65xZQk0PfSHYGsrBNyHEjWC+2Zw8eTKysrLw2WefITY2Frm54j/r+Ph4xMTE4NChQ8jKysJNN92EZs2aYffu3XjkkUfQv39/dO/evcp7zpkzxysbCCHELKE200M9JIQEi1DTQ18ItoZy8E0IccMJBU6Tnhxmy2nMnz8fADBw4EDD8UWLFmHcuHGw2Wz4+uuvMWfOHBQXFyM9PR0jR47EU0895fGe3gb9IYQQswRTD4MB9ZAQEixCTQ99IdgaysF3HWPWrVIv7ymVjodAa1a5jZSukTanDVHSXUhzVWwcKe4RJw6jmU24+yRHC9ebpCThLhR5iYz4J/0II84LF5zIs8I10XZCuIJbcoypyM6VC7/LU9J9s8kFzd3T6HYeaYlBE4hzCZoLfJRw1UmLEbZclCBsaZYqAgpFpUn30qbiXop0V9eC9CT9KsqfkXUWyEBF5+xaugtx/YVy8SxKpGu8TZXu6dKNyY4L+jP1GHjNJVhehfuR9m8YOm6Xqmo+vpG3cZDUGi5IT0/Hhg0bvLupB0pKSlBWVmY4xki7wSdQKcYqbugpEKVWX02BKDU39Ar38wiIJTlRqtAnmyr2oxWjLjaRklIRIE38jm0W0UYtRVm81LMWModYmr5kRuhFS7lkJqmxXKYTL/ajYoWORMiUjkoEIKUF5TIrU+k5YVNBgagjoVjcPFqus9FcQO1OTd9iDLZptmq2a21pItMGaTp43iHquaAan005hMaXKyVwyGeoKFXrn+nAawEOPBlMHQ2mHtYm1MPQwmPgNe1LprvFGpd8uN1HTwuo3beij6KdK3eK37jWh7Q7hU5dsIggZVYtWKUM/mg/L/tUZVr6RnFcC+RbZBFLCMutmnt51e7ZmuW6jXowOHcqnoOmOVoATZu0UWxtVmFDlFV8txspwpYmcmmRXfpCHysSGlZULrbnpLt5oUW4tV9AoeFZONRSw7Oq/PwqAq9VvxyxApfzHoSjPvULNcJFD30hUBrq0+B73bp1WLduHU6ePAmn0/gFWrhwoS+3JITUI5yq4kU0y/r1ZrO4uBiPP/44Pv74Y5w+fdrtvMMR2DX41ENCwhvqoXmoh4SEN6Gsh74QDA31evA9c+ZMzJo1C5dffjlSU1NNL0hvsJh9Pq4zOT7O7ChyllUPLCT/ia0y6FkkIhGlaCnAxDWN5bcgVs7wxEeKL1KinG1ulCrfSLZpYbTpgnxTelrMLisR4i1hokO8JTwvgwL9VipmUeK04EDyzWqEGm24X4QSjUbS7jg5850oZ+Gby1mjxBbi3tGtZDtbyjdOzURgDcQY01s1ShVvMBN/E22JL4mWbRXXF4pJKRTJZxElAxxFypkk7blZEaE/U0cNQZ5qnvnRgqHIf9Oa3pDWQaod1Qu3IrWeuRU99thj+PbbbzF//nzcc889mDdvHn799Ve89dZbeOGFFwJaF/WwbqkpEKUekNI1MCUiK7yCpJdLFOTWoumjnC2OENvGEXLWWAZKi44QWmPTArRFivs1lSnFUqPFbIo2492yqdDHhGQ5450ibWpm9NpRrBaoDjm7Lr2Lok/LVIq5Qmuj8soN7dVSkhXaRftiS6QHjwygFq1rvF22RXo/RVgMbdXaHuUQz6JEPhPtWVnVyIogdvKZOl2etSvBDjxZG1APzUE9rGU8zIBrM9uugddcgx+qKIfDpfthd1TtbanfQwZttKuiz1VmF94xcRFCK8rlvS2yH2RFpOE+mn7o9/XUrVGUKtrnqWjV99bq1mzRbCuRjS4sFzOYRYroVxZZhL4WQ6QwK1FF/7HMKbw67XqwuDJ9q7oErKuY8fYUaM3cjHd9JpT10BeCoaFeD74XLFiAxYsX45577vGpQkJI/SeU3Yq++OILvP/++xg4cCDGjx+Pa665Bu3bt0fr1q2xZMkSjB49OmB1UQ8JCX+oh+agHhIS/oSyHvpCMDTU68F3WVkZ+vbt63VFRMPDmkbT5wWuswwW1xlxOTtr0WZwoc3yRMJmlTM7ckZHm/VorK8HFG/ymjQSsy0RLWSOnTTjzDdkqjFEyTrkOpqoYvG2MP6MnG2W62q02RabnGW2lhu/flZE6OcayzWJ8ZHi2vjG4l5R0gRrmpzpTksU22YJYhvjMpve4hdDW2LPSVuskbLtFsOzsJXLmW+Hcc28BZH6M9Xfsspnrs3neJr5caemNY2+rXkMJKHsVnTmzBm0a9cOgFiLo6WBuPrqq/HAAw8EtC7qoY8EeEasplgY7vtWXRM175YI+bvTNEhbJx1tMa71biw1KUpb8y3TOMZYtdgZonyiTCGmrfHWZryj28l6NQ3TvHZi5SJxqxWKdGNTzolrLU2ld1EjsU3Q0gDJ9Zb5ZTZZt9VgS5Sc+dZs1WzX2hJtMbZVa3uEw2J4NlZ9nbe1mmdaU+wLP6kDDyAN6qE5qIfBwePab72AtzPgdr2U9mt1nQHXPFX0FGRWoR3lMv2globQ7hSxgJzlwgvxvEXE4ymF0K5ytdRwH9fUZoHA0721ukvlzLZmW76M7VOgCG+kIrnG+7wqZrxL9ZlubStTjVWa8Rb1lFeqU7pRBmjGuz6u9dYIZT30hWBoqNnRgs59992HrKwsnyojhIQGKhSvPvWJdu3a4fDhwwCAjh074uOPPwYg3l4mJCQEtC7qISHhD/XQHNRDQsKfUNZDXwiGhno9811SUoK3334bX3/9Nbp3745Iuc5N49VXX/XJEFI1ntY06ufdZryNs7LajEWEvnbZCqt8O6pFp7TJmZ0obYZHznzHNBZv95QEETFXTZSzzPI6XLgg69b2xVtG66liw/WNI+S6RRk5XJtl0WblNSyIdJtt0q7V7mVtKr+yzYRNaC6iWKrNxBYxMoK6nIVXEqLl9UWGtmlt1dquPQvt2VjlLHcEKmZ+LC5ruV2fuSdCcc2jU9Ufoamy9Ynx48fj//7v/zBgwAA88cQTGDZsGN544w3Y7faA6xP1MDh4mwWixvu5eKtYEVFpxlt6u8gykVIDZLBzyGXRsMm1jjHamm+r+OJr99G8Z5pIr504WS4uTnjt2FpIbUmR2pXWTGw1DYuVxyOsQLk28y10C1Fy7bX8sdmK8sW9C8S944rssu4ogy3WkgiDrZrtWlu0tmlt1dsun4X2bCrHvnD1sjJP6GV90KAemoN6GFxcfxtmo6BrM+CQfZDKEcWdMB6D0ziLrG3L5WxvuVXMItstYlsq10mXKs0BVKyXvuCUs8gOMbtc5hD9wsqzxmJrnDHW21h5Zlj+XVU0DwCn4Vqtfdq9tbpc0derW+Rab5wCAJRoNrqt7S6t0ubKs936DL52zE2/QjequSdCWQ99IRga6vXge/fu3ejZsycAYO/evYZzDK5BSHgQym5FjzzyiP73wYMHY9++fcjOzkb79u3RvXv3gNZFPSQk/KEemoN6SEj4E0w93LhxI15++WVkZ2cjJycHK1aswPDhw/Xzqqpi+vTpeOedd5Cfn49+/fph/vz5uOSSS6q977x58/Dyyy8jNzcXPXr0wOuvv44rr7zSlE3B0FCvB9/ffvutTxURQkIHh6roedrNlK1PHDt2DOnp6fp+69at0bp166DURT0kJPyhHpqDekhI+BNMPSwuLkaPHj1w7733YsSIEW7nX3rpJfzjH//Ae++9h7Zt2+Lpp5/GkCFD8NNPPyE6OrqKOwIfffQRMjMzsWDBAvTp0wdz5szBkCFDsH//frRo0aLKayoTDA31Kc+3xvHjxwEALVu29MsIUjPuwWw8lbMathqay3QELIjQXKvlbyLSxa3SJoPxRMTIFFmx4gvtjI/XKpEXykBsZXZZTgQMUhqL45GNhOtPtNUh76/VJ93OXW1UrPo5rax2bWQjaUtj6VYu69JcNdU4aZvmdi5deyzS9oiYQkPbtLZGWjT3fHGZ9my04Evac4Pi+dm6ErSAQ7WIN2t16tuanjZt2uDqq6/G3XffjT/84Q9o2rRprdRLPax73FI0ugSgrHzeoh3TlpNouiiLWF1csrWlKtFy6Yruli7vo2uWy/KdqEZia20q9bJpY7FNFJqlNhfu52qsDLwWEQGUy1RiUcKNXNHyJRdfkPc6L+9dZqgrWl9Oo+mY1WBrtMuym0iXtlp1uVMMz6ayVlf3TCvvh0OUWw3qofdQD4OPRzd0tx+fXPKmaEs7NDd0OyAHR6oiXar1ZSViyYDDKVywLYrQL7t06dbczUss+QCAYqvIf1zuvCDLXZD74nqnW7AyF3dzfVledf0lraxL69wCrpUb6tJsKbVqAdZOGtpidxoDqjmdmnu5ZqvRzb1yUDWPbuYhHFCtJoKph0OHDsXQoUOrvpeqYs6cOXjqqadwyy23AADef/99JCcnY+XKlbjzzjurvO7VV1/FxIkTMX78eAAiK8OqVauwcOFCPPHEEzXaFAwN9TrgmtPpxKxZsxAfH6+P/hMSEvDss8/C6Qy9QQYhxB1tTY/ZT31i+/btuPLKKzFr1iykpqZi+PDh+OSTT1BaWhrwuqiHhIQ/1ENzUA8JCX980cPCwkLDxxf9OXz4MHJzczF48GD9WHx8PPr06YMtW7ZUeU1ZWRmys7MN11gsFgwePNjjNa4EQ0O9nvn+61//infffRcvvPAC+vXrBwDYtGkTZsyYgZKSEvztb3/z2RjiPTXNwuqzO6iY3dFmeIzzsxVx1KyK+E/Sot06Un5N5CyMjkyHg2h5XAuuEiXKK/Iyq5xlscpgGRZZv2ugMgWWSjaohmu1e2n31uvS6rbZjFsNabvWFr1tsh7XZ6A9G8XFRks1AZ5q+jcIRUJ5jWOvXr3Qq1cvvPTSS1i/fj2ysrIwadIkOJ1OjBgxAgsXLgxYXdTD+knNgSorfrNaADGLy5pUbU/XIk2/rJqOyXL67LDYj9RmnyOEPlqjpIZFS+2KkZrVSHjpqJq3jratNPOtyq3SKMZwrXYva1SpoS6tbk+2aba7tsk1cJP2LHTPH/2ZVKeD2myaxyIhC/XQHNTDuqXG2VRV+71XlFNd/6LNjqvawEL8rp2uM5jy914iO2faTLkeBM1sIDKXGeKq2uAahE2zX58t122WKdSc52U5cbxMt9E4q19hq/Q0cvFS9CVNWCjPaJvFFz2s7LYNANOnT8eMGTO8qjc3NxcAkJycbDienJysn3Pl1KlTcDgcVV6zb98+U/UGQ0O9Hny/9957+Oc//4nf//73+rHu3bvjoosuwoMPPkhxJSQMUGG+D11f/6tRFAXXXnstrr32WjzwwAOYMGEC3nvvvYB2NqmHhIQ/1ENzUA8JCX980cNjx44hLi5OPx7lOpkXAgRSQ712Oz9z5gw6duzodrxjx4564nFCSGijQtHfbtb0qW9rHDWOHz+Ol156CT179sSVV16JJk2aYN68eQGtg3pISPhDPTQH9ZCQ8McXPYyLizN8fBl8p6SkAADy8vIMx/Py8vRzrjRv3hxWq9WrazwRSA31evDdo0cPvPHGG27H33jjDfTo0cMnIwgh9Qunl5/6xFtvvYUBAwagTZs2eP/993HHHXfg0KFD+M9//oP7778/oHVRDwkJf6iH5qAeEhL+1JUetm3bFikpKVi3bp1+rLCwENu2bUNGRkaV19hsNvTu3dtwjdPpxLp16zxe40owNNRrt/OXXnoJN998M77++mvd8C1btuDYsWP46quvfDKC+E5FhMiqccool6oeJVKFKterOPUyciv9QxxynZ9Tu7VdrofRggtoayPLRCRIlMjjdhkJslRbryjv51TkfRVDParLz1KFs5INiuFa7V7avfW6tLo1W6xyTaK2JkfarrVFb5vq0nbNBlU1buUace05VkVN/wahiKoqUE2u6TFbrrZ47rnnMGrUKPzjH/8IeoePelg/qSnDgFrp9+yEFinXde2hQNciTb8cLjqmaYQmOVKzysqFFjlKpYaVyPXbF6Rmnb8g98VWjZD/HVda862d08pCXqvdS7u3VpdWtyfbNNtd2+S2GlP/P8JVo6vTwfo27Awc1ENzUA/rFtfYDe4FtPMV8276NS5ZWrR10do6aS3aucUi401YZFYbi4hHEWkVWRy8jnauGKOdK5XWgmvrpytsNNpfEW/HaLNmm0VuIyzR0sYYuR8jbfQx2rniOdp5ZfurI5TXhgdTD4uKinDw4EF9//Dhw9i1axcSExPRqlUrTJ06Fc899xwuueQSPdVYWlqaIRf4oEGDcOutt2LKlCkAgMzMTIwdOxaXX345rrzySsyZMwfFxcV69POaCIaGej34HjBgAP773/9i3rx5+mL1ESNG4MEHH0RaWlpAjCKE1C3evLGsb13uo0eP6gHzgg31kJDwh3poDuohIeFPMPVw+/btuPbaa/X9zMxMAMDYsWOxePFiPPbYYyguLsakSZOQn5+Pq6++GqtXrzbk+D506BBOnTql799xxx347bff8MwzzyA3Nxc9e/bE6tWr3YKweSIYGupTnu+0tDQGziAkjPEmZU59S61TWx1NDeohIeFNMPVw/vz5mD9/Po4cOQIA6NKlC5555hk9121JSQn+/Oc/Y+nSpSgtLcWQIUPw5ptvmu44Ug8JIYEkmHo4cOBA3fO0KhRFwaxZszBr1iyPZTQtrcyUKVP0mXBvCYaGmhp87969G127doXFYsHu3burLdu9e/eAGEaMVLj0ya2H74LmulORgkFeJd1kylUnyuUX26G7SYptmVO47pQ5xLb8gtiq54TbkFJQIApqeWukS6RyrkjsnxPpHdRi4apjPy9TUTis8v5afdKl0cVd26k69HNl0n1Su1a7l3ZvRdal122TqcfsZdrNDLZrbdHaprVVa7v2LLRnU665oioV7+3cnq0HKlyU6tsciHlUmA8cVF8DDAUL6mH9Rf/NKcZ9zV268nl9SY7m9ijdAB2aJuh6JbalmiaVRxiOl8v7aPpWIsudl+VKz4tt9FmhTZazwtURjYWeKhbp7qkt64mwAuXSBVPTtzNSe+W1Dnkv7d5aXVrdZS62abZqtmttsbu0Vdtqz6KqZTcen6nL+XAimHrYsmVLvPDCC7jkkkugqiree+893HLLLdi5cye6dOmCRx55BKtWrcKyZcsQHx+PKVOmYMSIEfjuu+98aUrAoR7WHR7dzN0GC64pAzU37gi39FsWPS2X0b3cahEBsiKtYobRZmkCAIi2iAjWTdAcAFBsPQsAuCC3pY5CAECZdPFWHEY3dKdqzJVcMe6qqp9ldDfXbLQowjbdzVyzUbrCR1mFjTGWpgCAxhDbIquYHS1xShudQm/t0kaHs1RuNfdzzR1dLq1U7RXpyfSUavJZ6/8EVacpc/23CyU3dPYP/cfU4Ltnz57Izc1FixYt0LNnTyiKUuWbCUVR4HCE3/pXQhoawXyzOXv2bCxfvhz79u1DTEwM+vbtixdffBEdOnTQy/g72xNMqIeENCx80cPCwkLD8aioqCoj/A4bNsyw/7e//Q3z58/H1q1b0bJlS7z77rvIysrCddddBwBYtGgROnXqhK1bt+Kqq67yvjEBhnpISMMilD0j6wumBt+HDx9GUlKS/ndSe2izCIpSdWD6ikBqTsO+FijHIQNElEMG6IEDDm12V59lFvcudZmxuVAs3iLG5Yu3gBbXVCEXxHGczpdb8dbQcbZcXi86GsXl4o1qxayMZqPdcDsn7CiTNpVIm7RrNVsanxVvIi2yLsSIt6uK9p99TMW6DwBwStu168+7zPxoM+zlTu15ydkv+dZVf26qXX+mnp65J0JxJiiYbzY3bNiAyZMn44orrkB5eTmefPJJ3HDDDfjpp5/QuLF4U12fZ3uoh8HHLdCOG1on3lzCDu03qOsiyuFQxG+7XHqy2GUZu9QAfWbbxTPogl3qmRa8TN6npFxcV1QujhfKcoWFQpNiTp4TFjcR2mXVPIhKpTdPrDgPqxXQBinSwwenxTlHrri27KRquLdWl1a3Zotum7RVs11ri9Y2ra162+WzKFcchvs41PIKHfRa12rwGKrHMz++6GF6errh+PTp0zFjxoxqr3U4HFi2bBmKi4uRkZGB7Oxs2O12DB48WC/TsWNHtGrVClu2bKkXg2/qYe1hPqCahsV4XRVB1TzPdMuAalYtoJqY6Y6SM96NFDF73MQZDwCIV8Xs8ll5ne7R44KrZ6ACD/uKUjENLttV0X7XoHBG211nvBtZmgkbIb6nTZ0J4rwi9LPIKjyLzlvkbL1FmwHXtsaAbNBmwmGBE9qMNwz2Q+8fas9B87rS3bIMzyWUZsI58+0/pgbfrVu31v/+yy+/oG/fvoiIMF5aXl6OzZs3G8oSQkKTYL7ZXL16tWF/8eLFaNGiBbKzs9G/f38UFBTU69ke6iEhDQtf9PDYsWOIi4vTj1eX13bPnj3IyMhASUkJmjRpghUrVqBz587YtWsXbDYbEhISDOWTk5ORm5vrbTOCAvWQkIYFZ779x+uAa9deey1ycnLQokULw/GCggJce+21dCuqEW22wNOMTU3nBa6zra6zEdp6PG122SG3dsWOMpl3S1v/VyIXPBfL2ZFz8njRedFZaHZSvBW0nThpNEJLmaPNypwQ21JZrKBYvFUssIv7FctZmTJHxexTZRwo188VSxu0a7V7xZ6UM9+NRV0Vs0dyFj3G2MEpP1km2xJvaJvWVq3t2kyR9mzsivG5OWF3W+PonoYnUPEf636mPJhulq4UyFgCiYmJAODTbE+vXr1MB8XYsWOHqXJmoB76iMuMhv+3M8bEqJhdcXjYd8Ch/cb1GXBRRtMgbXZY88I5L+NFFNs17xnRhlKIWZEL8rpCef5MmZiV+a24EQAgKk/UkyDLR53PBwBYzsrYGY3kLI7VAlXeSz0v9ee00L3SXHE8Py/GcG+trkK7nOGW3zvNNs1WzXatLa7eSFrbtZgX+oy31EFVdVTzTF2ffYB1rIbUPcHEFz2Mi4szDL6ro0OHDti1axcKCgrwySefYOzYsdiwYYOP1lIPw41gzHgDYn2366xxhD7TLfpc2uxxtCL6UNp66SbOWLFVhQbFRYjrS8vFrHOJRazxLlOkt46eskybaZc2BeBnrXi4d4RcCx4FYWMjp7AtIUKuES8XbYp0iucRKcsXyxnwEpf72R1aajOBwwnXee1K6cjkxssZcL1N0NJA1r/Ra0MYfAdbQ70efKuqWqVBp0+f1l1GCSGhTW25WTqdTkydOhX9+vVD165dAQC5ublez/ZUzvFYUlKCN998E507d9ZzzW7duhU//vgjHnzwQVNtMgv1kJDwJ9huljabDe3btwcA9O7dGz/88APmzp2LO+64A2VlZcjPzzfoYV5eHlJSUjzej3pICAkWDcHtPNgaanrwPWLECAAiaMa4ceMMM1oOhwO7d+9G3759fTIirDE7w6NH4ZVRvfW13uJNmzar6ro+xm0rZ2cdMvKiPnMht3bVjlI5U1GizzKLOs/JF3YFdlHnmQvizWdSjphljjxy0tAmfVZGrsMuPSHud+ak+E/21HnxBvVMmbhfYZm47rxTzjShxPAIytUSnJd2F8qZHO1a7V6NToo6m1nFW9WocjFraimQEdnl7JH2vM/nWAxt0dqmtbVYTr5rz0J7NnaXWTGHWq4/U9cZcPeZnqrXgrvNBJmdGaqDGR/VizebmnneuFlqTJ48GXv37sWmTZt8MVNn+vTp+t/vu+8+/OlPf8Kzzz7rVubYsWN+1aNBPawfeIqJobr8BjUvFS1KrQN2PR6GHTJyuLZ1amu6hVacl14xmufOOW3Nt9SOMuWCPC7ud7ZUXJcTKbY2S4zBttIy8d9ufKGcAY8V24hoOQMeoQfORbmUyNJz0gOoQGirNuN9XOpiTolV1q0abCmzXDDYqtmutUVrm+YBVOrUZszLDM9Ge1YO2PVn6BYDw4PHTijGvHDFFz30B6fTidLSUvTu3RuRkZFYt24dRo4cCQDYv38/jh49qncCq4J62EDwesbbdRtRxRpvl2jmcsa7CcS66QS5XjpWrpduEim0KUJ6IUbI/qSWKUbTDt1jUI8UXoMuVP4h6f1oT0WrvrfuuShtiZDPIdpqnBm3lQv91GbA9fXq2uS0xbUvV+HBoWWIUFy8VnXz/ZwBr4/Uth7WBcHWUNOD7/h48QNUVRWxsbGIianoUNhsNlx11VWYOHGiT0YQQuoXTph3ftfKeeNmCYi8i19++SU2btyIli1b6sdTUlJ8mu3RWLZsGbZv3+52/O6778bll1+OhQsXmrbRE9RDQhoOvuihWaZNm4ahQ4eiVatWOHfuHLKysrB+/XqsWbMG8fHxmDBhAjIzM5GYmIi4uDg89NBDyMjIMB37gnpICAkkwdTD+kgwNNT04HvRokUAgDZt2uDRRx+tMxeiefPm4eWXX0Zubi569OiB119/HVdeeaXH8suWLcPTTz+NI0eO4JJLLsGLL76Im266qRYtJiT0UFUFqmrSrchkuYryKh566CGsWLEC69evR9u2bQ3nfZ3t0YiJicF3332HSy65xHD8u+++Q3R0tIervIN6SEjDIZh6ePLkSYwZMwY5OTmIj49H9+7dsWbNGlx//fUAgNdeew0WiwUjR440pF00C/WQekhIIAmmHtZHgqGhXq/5rjwVX9t89NFHyMzMxIIFC9CnTx/MmTMHQ4YMwf79+90CfADA5s2bMWrUKMyePRu/+93vkJWVheHDh2PHjh36+tK6xtuUOjUFFnJKl26n5jatu1YK/8UyJQal8th5hww+Zhf3LowQ29PS1TuvRHypEn8TgTUaHSioXDVk9gWUnBXlC84KN6Wcc2J7Qrp6/1Yq7psv3c6LVGGLXb1gaKndeQFFSoksa7w2NkLsWxVxD6cMmBZfLO4R3VRsrTEXKj8u/PZbvKEtWtsKNbdzmWPnvEM8t1LpplSmSLdLaatDtcMpn5v2jM0HGgq9FDvBfLM5efJkZGVl4bPPPkNsbKy+jjs+Ph4xMTF+z/ZMnToVDzzwAHbs2KF3vLZt24aFCxfi6aef9tLa6qEeVk3NuuYJDwEn9WU5cldfzePdshztN+xQy1GuyOUyikjnpaWdKVFl0B0ZnKxI6uI5zVVbBivT0iKWqiKgUIHUs5MlMniPRbMt0nBdfplM4VgkBiixNmGTzeqQbVL1DkuZdH0/pwdUE9uTpdpWurjLjGQnSxwGWzTbNFs1G7S2FLnoYIl02yxzeTblaqn+3JwubqTeL7sxpuJxx7e5kmDqaDD18N133632fHR0NObNm4d58+Z5eWcB9bDu9dBXPOqnB3dzj/fR3c+t8r4V7ud6cDKL0D2rdMWOtIilLTEQ3mxxMqVYolUcbxEtNCjOJmw5VSK++UWKWBJ4XpVpuxwiEGuZQxzX0nU5VZmuSwtQpuuG599xxf8rmuZoAXEh720x1KW17byWUky60EdaRJ82tZG2JFJsT5ZIl3m5DMdhkal6LZr+if0Ii+xnq+UVLvyq7KNrz1j/v8qTIniXgqw+9RMb2sx3MDTU1OD7sssuw7p169C0adMaI8AFMnKmK6+++iomTpyI8ePHAwAWLFiAVatWYeHChXjiiSfcys+dOxc33ngj/vKXvwAAnn32WaxduxZvvPEGFixYEDQ7CQl1ghnNcv78+QCAgQMHGo4vWrQI48aNA+DfbM8TTzyBdu3aYe7cufjggw8AAJ06dcKiRYtw++23e2dsFVAPCWlYhHJ0X+oh9ZCQQBLKeugLwdBQU4PvW265RQ+gUTkCXG1SVlaG7OxsTJs2TT9msVgwePBgbNmypcprtmzZgszMTMOxIUOGYOXKlR7rKS0tRWlpqb7vmj6pOlSoPsz0mLx3DYGF9EBCqnjrZpFv6LQZC7sMClSmRKNEkYE1VPHPHyWDkEVZhe02GWwi2iLebDayireEcQflLLCWpkvOvpwrEd+N06Xi7WJeibj/8QvGWZnTMh1YgUzjUF5mnPkud1xAge2sLCtmhRqfl8FAZMoHh0xrcUHO2jeTs+uxZ0Q7o6NEHVar+MX/UihsP3FBpv0pEbYXlMm3tHYxU3RePq8S/TmJrTY7X66WGmbNgErBPeoo0FAw34SqMJ8BxFsrVBMROPyd7bn99tsD0rGsCuph7WHWM0j7SlX8Fo26qM1KOOTW4ixFudQUu/xv8II24yNnqiPlrHN0mZyxjtRmvMXWKgcZ5dI75oxFBKSMkOUdMq2N5mGULwOt5crgaLEy3U0jqVU2GdTHolR0WMr0NGdaGkix1VKKnZYB1k5dEO38rbzYYItmm2ardr98MemEQqmD5xzSG0rq3gU5e2VXzxvu43CWVtI/OevkEuTIfSY89Dx/XAmmHtYG1EN3QlEPa8JToDX9vFvANYtbei6rTEMWCbFuP0pum8jZ4yQ5431pvKjr6ubiGVx5mwjM+/0y0ef67pQIsHegUPwijhWL55aHMwCAM0oOAKDIIbSqRAbPLbWLbbnjHFSnDEJpEXVHyL5oVKSYwY6OkMHgrMKzIVFNBQAkQ6QtTW8svpeXxAlb++m25hhs3XRKzO5rXkol50V952XbS+TWrnkCVUpt5pRBefVnqnupGr1W3QOv1UelMEeo66EvBFpDTQ2+K7sS1ZVb0alTp+BwOJCcnGw4npycjH379lV5TW5ubpXlPaUrAoDZs2dj5syZ/htMSAgj3myae5EUDm82vYF6SEjDgnroGeohIQ0L6qH/eL3m+9ixY1AURY9O/P333yMrKwudO3fGpEmTAm5gbTNt2jTD29DCwkK3/MWBwdu1jXJfTyXhmmKs+rXf2sxFKc7B4vKGziJnVeQyPzhVbZZZHC92iLd+xy+If/NIue5aO+86K3NWzqqcLhHlTpYIG3Kc+QCAQkW86dTW5WiUOYpRiJOyrFg3juIEAECJI1Le2yptETZpa8G12SNtTbhd2nZazkL9JlP2aOuS8svE8ylwiEbr65QU8fa2VD1neG5O1V7jWm/3tY6OKs8Heq1jMAi1N5tNmzat1t2xMmfOnAlYvdRDPzGbitEN7benXV792m/tt6tpnlOJgF2fVbEa7qFpr1Pe3FGqxYWQHj3F4h5npedOinKpwbIyaNoi1zZeEPe5INPZxMg15I00TyO5jZD1V575Lpc2lMlJlPNye6Fc/OWc9NzRZq61uqPR2GDb4SJhq7bevESWLywXNhZK/StSxKzTBch1mtLzR3tWQgddY194udbbW+pBrhrqoTmoh4EhWB6UFRj7gID7rLhF6pHVKfqDkfK45iGZECl+z22S8gEA6gN3AQD6xK4EALRb9QsAYMcx8YJjb6Hoqx06lwYAOF4sUpflWE4DAH6LOgoAKFSOAwCKS8vhlLpjlekaG9nENXE28f1KUlsBAFJlGrSWTcRM98ViQhtd40T/7bL0PFH+ZqGLzrvvELavzxK2FTSRbbMY2mqVfWGL/n+E8RkZn2H16+79pT6t/Q41PfSFYGuo14Pvu+66C5MmTcI999yD3NxcDB48GF27dsWSJUuQm5uLZ555xmsjzNC8eXNYrVbk5eUZjleXfiglJcWr8oDITWwmPzEh4UyoremZM2dOndRLPSQk/KEemoN6SEj4E2p66AvB1lCvB9979+7Vo719/PHH6NatG7777jv8+9//xv333x80cbXZbOjduzfWrVunrytyOp1Yt24dpkyZUuU1GRkZWLduHaZOnaofW7t2ral0RYQ0ZEItmuXYsWPrpF7qISHhD/XQHNRDQsKfUNNDXwi2hno9+Lbb7fqbv6+//hq///3vAQAdO3ZETk5OYK1zITMzE2PHjsXll1+OK6+8EnPmzEFxcbEe3XLMmDG46KKLMHv2bADAww8/jAEDBuCVV17BzTffjKVLl2L79u14++23g2pnldTgXmk2NY+rmzmkm6G2pwUWKtezF7gE3LBY3dwrNZzlqrxW/PuWyIBDZ2W6L81dUsYd0pskvTJRKtMznJNpawrtwqXxNIQL9xmLWEt1vly4GZU7Sgz1lztKcN4hzp2JaITKDSs7HyvvKdwmT0UaXaCiLNJ1XrZJmoALsk3F5cYAa4VOo7t5sXS3LIFMzePibulwlqJcXuN0DbjmIeBQTdToPlSH7paqar76euAV6sahQ4ewaNEiHDp0CHPnzkWLFi3wr3/9C61atUKXLl0CVg/1sHoClXJMv4++LMfVxa/6wGuqYgzAVi7T3QCAXXMX1HRNEfdyyHQypXLpSaFDuE1qy3TKZZ3lcAm8qOuj2LeXi+u0IJE26cIYZdFS/Ij7Wav4v8Ghapos05o5xT3LnKLuC7I9JTJFY6lMiWOHaJ/mEvkbhL5py3ac8nmWWkrk9cWyrUKrK/RPBBhySO0rd5a5BZr0OtCax4BD9S/FmF4H9dAU1MP6itV0yYq0jFIHZUAxuzxebBdf8FyZlmvLUeEp0O13nwIACkvFv/8vRSL42REZNPdXGXj3bKlcKuMU2nPeck7eX2pNFYFstb9r57Sy2jLBczK45dlSobG/WqXLvAwSd+GIsKX1e+K6uKXC1j2nUwxt0dqmtVVru1N1XUJoBu2Zh+rw0zOhroe+EGgN9XqRQpcuXbBgwQL85z//wdq1a3HjjTcCAE6cOIFmzZp5bYA33HHHHfj73/+OZ555Bj179sSuXbuwevVqPWjG0aNHDQLft29fZGVl4e2330aPHj3wySefYOXKlfUmhyMh9RUVCpwmP2rQ16d5x4YNG9CtWzds27YNy5cvR1GReKHyf//3fwEPCEQ9JCT8oR6ag3pISPgTynroC8HQUEU1k/enEuvXr8ett96KwsJCjB07FgsXLgQAPPnkk9i3bx+WL1/ukyH1lcLCQsTHx0O8xTL/JfI40+NxAb/LDLWHlBEVM9lacB5jmghF7mvHrRbx1jHCEiX3oxApg1dEyNQ6NkUGm4CYbdaC9UQ7RTmbdJCIlFurrEubPXHIt4GlMKbr0t5KFkOkD9NmtS/YRXCCkjKxdThEcB+rNQ7RNpEiIiZSbBtZxX/YjdFU7KtiBjxa1dJgRBpsssjnptlkl7NSWiCiEouwrQRypgfiTWiZKn5Memq2SjPeAFDuLIVDzpZ5mvHWjtcUaM30jI+Hn6b3Mz0qAAcKCgoQFxdXbUnt+/5Ch2mItkabunuJowRP7J9t6v61QUZGBm677TZkZmYiNjYW//d//4d27drh+++/x4gRI3D8+PGA1UU9NIfpme8a9NHtPn7oo8WiaaTQwQiLltZQaqVMuaPppEXuWzy8s1Zkndpss56yR9VSmMl6ZBAfq6anWnpIVGiYpq1ObcZHm42XOlauzUZBSyUptg6Z/kuflfYw+6zd1+mSktKhp1OsmOkGKnTQ6Sz3W/80KnTMO/1zK0Y9rBbqYfDwVQ9roka9dNNJF330oIuKpmGaDlpseh9R6xdGWmX/zyrSeDVSRN8r3in6Yk0h+mDNbOK6plEydWKk0aJiISXIl+kMC2SQ29NO0fc6azkFADiH30T5chFs90KZ6C+WlZ+FQwbltUqbbBHClhib2DaOECnGYpEkbHE2F7ZZRPl4m2hngk20v7GLjeekjdps/OkyoXdnpbdmgQwGd14VNpU4hAeRXdpld16o6Be69Q+lFtfYD3TRvxp0L/CePg1LD30hGBrqtdv5wIEDcerUKRQWFqJp06b68UmTJqFRo0ZeG0AIqX+E8pqePXv2ICsry+14ixYtcOrUqYDWRT0kJPyhHpqDekhI+BPKeugLwdBQrwffAGC1WlFeXo5NmzYBADp06IA2bdr4ZAAhpP4RytEsExISkJOTg7Zt2xqO79y5ExdddFHA66MeEhLeUA/NQz0kJLwJZT30hWBoqNdrvouLi3HvvfciNTUV/fv3R//+/ZGWloYJEybg/PnzPhlBCKlfqF5+6hN33nknHn/8ceTm5kJRFDidTnz33Xd49NFHMWbMmIDWRT0kJPyhHpqDekhI+BNMPWzTpg0URXH7TJ48ucryixcvdisbHW3OJd4swdBQr2e+MzMzsWHDBnzxxRfo168fAGDTpk3405/+hD//+c+YP3++T4Y0GFzXc+hrd2qK7qtdblw/4pTr6xS59lkrryrGiNzauhSL5QLKZGRbq74uPF+ck/v6+nC5PkiLjq7oaxK1Nd/GSMIOl/WD5Q7xn61dRjUvd1wwHFdluYpHU4oyu1j/7XTKSMNWsfamyJorbROuaxEu6zLdbFOMUeFVLXKnZqNL5HJtTaNDj2RuN9jhVMvdo5rr9/awtkdvmMm13vUoLGQov9l8/vnnMXnyZKSnp8PhcKBz585wOBy466678NRTTwW0LuqhOVy/+x7XNHrMCqH9hlxiY5jUR8h11YrURVWJgMMp7uWwCG3Uop5ra8F1TbEY13pXrJ90jdNhNZ53Wftdcdy4xluxGPW1Mq765XTZ19rrttZb1xzjmm/XiOT62m+n8XpN91z3AWelNY3GqOZ+61+FkVUf107XwfCWemgO6mHd4rnfqJXQfvfllXcNVMSDkHElLKK/dsEiMybIGEEn7DJWUJkY6ES4RFTXskGUKlpGBRFXp9QitiVO0dcrK5dbuY66on9Yrt9L+7t2rsQu+3laPzFC3LNIrtE+KW2MLpM2lpq0UdpWKmMAlTnEVosB5BoLyOEsq2Ktt2vWh5pi/oQewdTDH374AQ5Hxf9be/fuxfXXX4/bbrvN4zVxcXHYv3+/vq94jB3jG8HQUK8H359++ik++eQTDBw4UD920003ISYmBrfffjvFlZAwIJRTSdhsNrzzzjt4+umnsXfvXhQVFaFXr1645JJLAl4X9ZCQ8Id6aA7qISHhTzD1MCkpybD/wgsv4OKLL8aAAQM8XqMoClJSUryryAuCoaFeD77Pnz+vp26oTIsWLehWREiYEA4BNVq1aoVWrVoFtQ7qISHhD/XQHNRDQsIfX/SwsLDQcDwqKgpRUVHVXltWVoYPPvgAmZmZ1c5mFxUVoXXr1nA6nbjsssvw/PPP+5R7uyYCqaFeD74zMjIwffp0vP/++7pf/YULFzBz5kxkZGQExChCSN0Sam6WmZmZePbZZ9G4cWNkZmZWW/bVV18NWL3UQ0LCH+qhOaiHhIQ/vuhhenq64fj06dMxY8aMaq9duXIl8vPzMW7cOI9lOnTogIULF6J79+4oKCjA3//+d/Tt2xc//vgjWrZsac7IKgi2hno9+J47dy6GDBmCli1bokePHgBEovHo6GisWbPGawMIIfUPbwJl1IO+Jnbu3Am7Xaxb3bFjh8e3pIFeC0Q9JCT8oR6ag3pISPjjix4eO3bMkOe7pllvAHj33XcxdOhQpKWleSyTkZFheLHXt29fdOrUCW+99RaeffZZk1a6E2wN9Xrw3bVrVxw4cABLlizBvn37AACjRo3C6NGjERMT45MRhJD6RajN9MydO1cX9vXr19davdRDQsIf6qE5qIeEhD++6GFcXJxh8F0Tv/zyC77++mssX77cK9siIyPRq1cvHDx40KvrXAm2hvqU57tRo0aYOHFioG0JK7yO7qsXNK6k0KP7qlpUc2N0dO18RWRI10i8LhF4HZZK56qO3qu43aN63KN/a1tjxHU9KriMDukeidcOh+OcvEZEk7TLaJOlMhK7om8DbasxMmXV5cxF9dV3AxTdvC6iY6pQoHr6zlZRtq7p1asXcnJy0KJFC7Rr1w4//PADmjVrVit1Uw+9p0Z99PTbcNPHqssr+u9WO6DppJapoVTXDIfTXSMN93LRS/fjxn3XqOWeyrlSXbRzt+OuWuOmPa66VnU5V73zfL2r9lVc67XuVRhT9XHXYvVgLpl6aB7qof/oUctNZ4Uwmy3HbijnUCuyF2hRu+0Qa/PLLKIvpmXB0bcy+4PVpS/mbqJRQ1wzyWgZeLR6tX0tC06FrRV/dzhFRHSn3SX6ebmIxF5ssUlbq7axJlt1G2X2B6dLH7Zy1gfteI1ZHwKU7aY+6KBGbejhokWL0KJFC9x8881eXedwOLBnzx7cdNNNPtWrEWwN9WnwvX//frz++uv4+eefAQCdOnXClClT0LFjx4AZRgipO1SYf7NZH/5LSEhIwOHDh9GiRQscOXIETmfthT2iHhIS3lAPzUM9JCS8CbYeOp1OLFq0CGPHjkVEhHGYOmbMGFx00UWYPXs2AGDWrFm46qqr0L59e+Tn5+Pll1/GL7/8gvvuu8+HmisItoaamy6sxKeffoquXbsiOzsbPXr0QI8ePbBjxw5069YNn376aUCNI4TUDZpbkdmPN2zcuBHDhg1DWloaFEXBypUrDefHjRsHRVEMnxtvvLHae44cORIDBgxA27ZtoSgKLr/8crRr167KTyChHhIS/gRTD4MB9ZAQEiyCrYdff/01jh49invvvdft3NGjR5GTk6Pvnz17FhMnTkSnTp1w0003obCwEJs3b0bnzp39aWLQNdTrme/HHnsM06ZNw6xZswzHp0+fjsceewwjR470yRBCSP0hmAGGiouL0aNHD9x7770YMWJElWVuvPFGLFq0SN+vKTjH22+/jREjRuDgwYP405/+hIkTJyI2NtZLy7yHekhI+BNqAdeoh4SQYBFsPbzhhhugenDDd11//dprr+G1117zoZbqCbaGej34zsnJwZgxY9yO33333Xj55ZcDYhQhpG4JZoChoUOHYujQodWWiYqKQkpKilf31WbHs7Oz8fDDD9dKZ5N6SEj4E2oB1wDqISEkOISiHvpCMDXUa7fzgQMH4j//+Y/b8U2bNuGaa64JiFGEkLpF9fIPABQWFho+paWlPte/fv16tGjRAh06dMADDzyA06dPm7520aJFtdLRBKiHhDQEfNHD+gL1kBASSEJZD30hGBrq9cz373//ezz++OPIzs7GVVddBQDYunUrli1bhpkzZ+Lzzz83lCWEhB4OVXzMlgWA9PR0w/Hp06djxowZXtd94403YsSIEWjbti0OHTqEJ598EkOHDsWWLVtgtVq9vl8woR4SEv74oocNEeohIeEP9dB/FNWTY70HLBZzk+WKosDhcNRcsJ5TWFiI+Ph4iJRdgU8h4jGVhFvBmsq5pLPxdF9DqgUPKW9Mpu3S8JS+psYUC/KrZ0irobfTQ3tMpv3x3mYX2/SC7uVMp9KpqMycTUF7Q6gCcKCgoKDGPIva931Kq2mIskSbunupswRvHJ2NY8eOGe4fFRVV41ptRVGwYsUKDB8+3GOZ//3vf7j44ovx9ddfY9CgQaZsqi2oh8HFtD7qF3gq7/7vZE4jq7+HqLKm70BtvDCq/rtlWu/0CzykOKtSo/xLJVb9vYNB7eihmfuHG9TD4FKjHprUP8N9auxTWT0cN4e79lSdkktVHYZ9qKqxbygqN9iqKFaX/dqyWcMZtFSL1MPwxuuZ79pMWUEIqRtU1XzfWSsXFxcXFHFt164dmjdvjoMHD9a7wTf1kJDwxxc9bIhQDwkJf6iH/uNTnm9CSHjjRI3z+YayweT48eM4ffo0UlNTg1wTIYS4U5/0kBBC6hLqof94HXCNEBL+BDOPY1FREXbt2oVdu3YBAA4fPoxdu3bh6NGjKCoqwl/+8hds3boVR44cwbp163DLLbegffv2GDJkSOAbSgghNRBMPZw9ezauuOIKxMbGokWLFhg+fDj2799vKFNSUoLJkyejWbNmaNKkCUaOHIm8vLwAtpAQQswR7DzfDQEOvgkh7qgVrkU1fbxdmrR9+3b06tULvXr1AgBkZmaiV69eeOaZZ2C1WrF79278/ve/x6WXXooJEyagd+/e+M9//lPj+nFCCAkKQdTDDRs2YPLkydi6dSvWrl0Lu92OG264AcXFxXqZRx55BF988QWWLVuGDRs24MSJExgxYkRg20gIIWYIoh42FOh2TghxI5huRQMHDkR1cR7XrFnj5R0JISR4BFMPV69ebdhfvHgxWrRogezsbPTv3x8FBQV49913kZWVheuuuw6ASH3TqVMnbN26VY8qTgghtQHdzv2HM9+EEDfMvtX0JvAGIYSEIr7oYWFhoeFTWlpqqq6CggIAQGJiIgAgOzsbdrsdgwcP1st07NgRrVq1wpYtWwLbUEIIqQH2D/3H68H3ddddh5kzZ7odP3v2rP5WlhAS2ji9/DRUqIeEhD++6GF6ejri4+P1z+zZs2uux+nE1KlT0a9fP3Tt2hUAkJubC5vNhoSEBEPZ5ORk5ObmBqJ5AYN6SEj4w/6h/3jtdr5+/Xrs2bMHO3fuxJIlS9C4cWMAQFlZGTZs2BBwAwkhtY+qqtW6hruWbahQDwkJf3zRw2PHjhlSL5qJWTF58mTs3bsXmzZt8s3QOoZ6SEj4w/6h//i05vvrr7/GH//4R1x11VX44osv0KZNmwCb1XBQa4hGoECRBWv6AjuM91UUDxU6qjhodIDw/rdSw7stlxt6arOKCh8VxaWM3p4q7QdU1d8VFF68n/NRTGr6t65PeBOlsqFHs6QeBg/T+qhf4Km8u254p5GAJ0cxs3LgZmsA8F9TvJyX8KMjFUr654ovehgXF2cYfNfElClT8OWXX2Ljxo1o2bKlfjwlJQVlZWXIz883zH7n5eUhJSXF9P1rC+ph8PD0G6q5nyg1TWqeoZSud+b6gd7qmOffvYv2VNNP1P6u6Icc8rjxHp76gYGz2ZVq9NPs4DQEdZH9Q//xacSSmpqKDRs2oFu3brjiiiuwfv36AJtFCKlLVC8/DRnqISHhTTD1UFVVTJkyBStWrMA333yDtm3bGs737t0bkZGRWLdunX5s//79OHr0KDIyMnxtUtCgHhIS3rB/6D9ez3wr8s1ZVFQUsrKy8Nxzz+HGG2/E448/HnDjCCF1A99smoN6SEj4E0w9nDx5MrKysvDZZ58hNjZWX8cdHx+PmJgYxMfHY8KECcjMzERiYiLi4uLw0EMPISMjo95FOqceEhL+sH/oP14Pvl3995966il06tQJY8eODZhRhJC6heJqDuohIeFPMPVw/vz5AEQKxsosWrQI48aNAwC89tprsFgsGDlyJEpLSzFkyBC8+eab3lVUC1APCQl/2D/0H68H34cPH0ZSUpLh2MiRI9GxY0ds3749YIYRQuoO4S5kds1Sw4V6SEj4E0w9NBOQKDo6GvPmzcO8efO8vHvtQj0kJPxh/9B/vB58t27dusrjXbp0QZcuXfw2iBBS9/DNpjmoh4SEP9RDc1APCQl/qIf+41O0c0JIeKNWBJ43VZYQQsIV6iEhhAioh/7DwTchxA0VKpym3YqoroSQ8IV6SAghAuqh/3DwXc/x9YureHWZp7y2/uHPj87tWj3/t6d8jcFpQ1U0BDHhm00SCvisj1B8+OL6pzEe84r7ddPa//E1BP1zhXpI6jNmf5PV9wvN6Vugv97e6EnN/cKq21AXP8lw1knqof/4lOebEBLeOL38EEJIuEI9JIQQQTD1cMaMGVAUxfDp2LFjtdcsW7YMHTt2RHR0NLp164avvvrKy1prHw6+CSFuqKrq1YcQQsIV6iEhhAiCrYddunRBTk6O/tm0aZPHsps3b8aoUaMwYcIE7Ny5E8OHD8fw4cOxd+9ef5oYdOh2Tghxg9EsCSFEQD0khBBBsPUwIiICKSkppsrOnTsXN954I/7yl78AAJ599lmsXbsWb7zxBhYsWOB95bUEZ74JIW44ZUANsx9CCAlXqIeEECLwRQ8LCwsNn9LSUo/3P3DgANLS0tCuXTuMHj0aR48e9Vh2y5YtGDx4sOHYkCFDsGXLlsA0Nkhw8E0IcUNFRVCNGj91bSwhhAQR6iEhhAh80cP09HTEx8frn9mzZ1d57z59+mDx4sVYvXo15s+fj8OHD+Oaa67BuXPnqiyfm5uL5ORkw7Hk5GTk5uYGsMWBh27nhBA3vJnB4UwPISScoR4SQojAFz08duwY4uLi9ONRUVFVlh86dKj+9+7du6NPnz5o3bo1Pv74Y0yYMMEPq+sXnPkmhLhh+q2mFyknNDZu3Ihhw4YhLS0NiqJg5cqVLnWreOaZZ5CamoqYmBgMHjwYBw4cCFzjCCHEC4Kph4QQEkr4oodxcXGGj6fBtysJCQm49NJLcfDgwSrPp6SkIC8vz3AsLy/P9JrxuoKD7zBFrQd/2K7QJZhrHIuLi9GjRw/MmzevyvMvvfQS/vGPf2DBggXYtm0bGjdujCFDhqCkpCQQTSOkbpRDdRo+XvdgVPd7UP9qB675JuFAneheLehJXbchWO2qr9SmHhYVFeHQoUNITU2t8nxGRgbWrVtnOLZ27VpkZGT4VW+wods5IcQNp+qFW5GXUz1Dhw41uBZVRlVVzJkzB0899RRuueUWAMD777+P5ORkrFy5EnfeeadXdRFCiL8EUw8JISSUCKYePvrooxg2bBhat26NEydOYPr06bBarRg1ahQAYMyYMbjooov0NeMPP/wwBgwYgFdeeQU333wzli5diu3bt+Ptt9/2rlG1TMjMfJ85cwajR49GXFwcEhISMGHCBBQVFVV7zcCBA92Std9///21ZDEhoYsvb3m9iWbpicOHDyM3N9cQvTI+Ph59+vSp99EraxPqISG1B2e96jfUQ0Jqj2Dq4fHjxzFq1Ch06NABt99+O5o1a4atW7ciKSkJAHD06FHk5OTo5fv27YusrCy8/fbb6NGjBz755BOsXLkSXbt2DWibA03IzHyPHj0aOTk5WLt2Lex2O8aPH49JkyYhKyur2usmTpyIWbNm6fuNGjUKtqmEhDwqAKcXZQERzbIy06dPx4wZM7yqV4tQGYrRK2sT6iEhtYcvekhqD+ohIbVHMPVw6dKl1Z5fv36927HbbrsNt912m5c11S0hMfj++eefsXr1avzwww+4/PLLAQCvv/46brrpJvz9739HWlqax2sbNWpU7xfeE1LfCGY0S+If1ENCahdGO6+/UA8JqV2oh/4TEm7nW7ZsQUJCgi6sADB48GBYLBZs27at2muXLFmC5s2bo2vXrpg2bRrOnz9fbfnS0lI391lCGhqqqnr1AXyPZlkZrSMUitErawvqISG1iy96SGoH6iEhtQv10H9CYuY7NzcXLVq0MByLiIhAYmJita6od911F1q3bo20tDTs3r0bjz/+OPbv34/ly5d7vGb27NmYOXNmwGwnJBSpqzebbdu2RUpKCtatW4eePXsCEGvJt23bhgceeCBg9YQy1ENCahfO9NRfqIeE1C7UQ/+p08H3E088gRdffLHaMj///LPP9580aZL+927duiE1NRWDBg3CoUOHcPHFF1d5zbRp05CZmanvFxYWuq1lJSTcCaa4FhUVGXI2Hj58GLt27UJiYiJatWqFqVOn4rnnnsMll1yCtm3b4umnn0ZaWhqGDx/uVT2hBvWQkPoJO5u1D/WQkPoJ9dB/6nTw/ec//xnjxo2rtky7du2QkpKCkydPGo6Xl5fjzJkzXrmi9unTBwBw8OBBj+IaFRXFtaqkwaNlaDRb1hu2b9+Oa6+9Vt/XOjNjx47F4sWL8dhjj6G4uBiTJk1Cfn4+rr76aqxevRrR0dFe1RNqUA8bFoyKHToEUw9J1VAPCamfUA/9p04H30lJSXr4+OrIyMhAfn4+srOz0bt3bwDAN998A6fTqQumGXbt2gUAHpO1E0IEwXyzOXDgwGrXASmKglmzZhmi0DYEqIeE1E8401P7UA8JqZ9QD/0nJAKuderUCTfeeCMmTpyI77//Ht999x2mTJmCO++8U49k+euvv6Jjx474/vvvAQCHDh3Cs88+i+zsbBw5cgSff/45xowZg/79+6N79+512RxC6j1O/d2muQ+pPaiHhNQu1MP6C/WQkNqFeug/IRFwDRBRKadMmYJBgwbBYrFg5MiR+Mc//qGft9vt2L9/vx6t0maz4euvv8acOXNQXFyM9PR0jBw5Ek899VRdNYGQkMEp/5gtS2oX6iEhtQf1sH5DPSSk9qAe+k/IDL4TExORlZXl8XybNm0Mrqzp6enYsGFDbZhGSNihKipUxeyaHr7ZrG2oh4TUHtTD+g31kJDag3roPyEz+CaE1B6qF+5CFFdCSDhDPSSEEAH10H84+CaEuOGEEwrdigghhHpICCES6qH/cPBNCHGDqSQIIURAPSSEEAH10H84+CaEuOFUnFBMrunhm01CSDhDPSSEEAH10H9CItUYIaR2KffyDyGEhCvB1MONGzdi2LBhSEtLg6IoWLlypeG8qqp45plnkJqaipiYGAwePBgHDhwIYOsIIcQ87B/6DwffhBA3vMviyDebhJDwJZh6WFxcjB49emDevHlVnn/ppZfwj3/8AwsWLMC2bdvQuHFjDBkyBCUlJYFoGiGEeAX7h/5Dt3NCiBtOOKDAYbosIYSEK8HUw6FDh2Lo0KFVnlNVFXPmzMFTTz2FW265BQDw/vvvIzk5GStXrsSdd97pVV2EEOIv7B/6D2e+CSFuqHoyCTMfppIghIQvvuhhYWGh4VNaWup1vYcPH0Zubi4GDx6sH4uPj0efPn2wZcuWgLWPEELMwv6h/3DwTQhxw6k4vfoQQki44osepqenIz4+Xv/Mnj3b63pzc3MBAMnJyYbjycnJ+jlCCKlN2D/0H7qdE0LcEG5F5t7N0a2IEBLO+KKHx44dQ1xcnH48KioqKLYRQkhtwv6h/3DwTQipAm8CZfDNJiEknPFeD+Pi4gyDb19ISUkBAOTl5SE1NVU/npeXh549e/p1b0II8Q32D/2Fg+8aUFVtvQLXLZBQRXx3K77LNeNUHTC7KkWUJQ0B6iEJfUJHD9u2bYuUlBSsW7dOH2wXFhZi27ZteOCBBwJWD/EN6iEJfUJHD8MJDr5r4Ny5c/JvfHtDQptz584hPj7eVFlvUkQwlUTDgXpIwoX6oodFRUU4ePCgvn/48GHs2rULiYmJaNWqFaZOnYrnnnsOl1xyCdq2bYunn34aaWlpGD58uFf1kMBDPSThQn3Rw9mzZ2P58uXYt28fYmJi0LdvX7z44ovo0KGDx2sWL16M8ePHG45FRUXV63SMHHzXQFpaGo4dO4bY2FgoilKnthQWFiI9Pd1tLVmoE47tqk9tUlUV586dQ1pamvlr4IBq8s2myjU9DQbqYfAJx3bVpzbVNz3cvn07rr32Wn0/MzMTADB27FgsXrwYjz32GIqLizFp0iTk5+fj6quvxurVqxEdHe1VPSTwUA+DSzi2Cahf7apverhhwwZMnjwZV1xxBcrLy/Hkk0/ihhtuwE8//YTGjRt7vC4uLg779+/X9+v691gTHHzXgMViQcuWLevaDAOBWEtWHwnHdtWXNpl9o6nhhBNm3+Y7+da/wUA9rD3CsV31pU31SQ8HDhxYrcunoiiYNWsWZs2a5dV9SfChHtYO4dgmoP60qz7p4erVqw37ixcvRosWLZCdnY3+/ft7vE5RFD1GRijAVGOEEDeCmcdxxowZUBTF8OnYsWOQWkIIIf7BvLaEECLwRQ8LCwsNn9LSUlN1FRQUAAASExOrLVdUVITWrVsjPT0dt9xyC3788Uf/GhlkOPgmhLihqg6vPt7SpUsX5OTk6J9NmzYFoRWEEOI/wdZDQggJFXzRw/T0dMTHx+uf2bNn11iP0+nE1KlT0a9fP3Tt2tVjuQ4dOmDhwoX47LPP8MEHH8DpdKJv3744fvx4wNocaOh2HkJERUVh+vTpYZcvNBzbFeptCrbbeUREREi5CJH6R6j/xjwRju0K9TZxGQ6p74T6b6wqwrFNQOi3yxc9dF3fbqbtkydPxt69e2ucnMnIyEBGRoa+37dvX3Tq1AlvvfUWnn32WVN21jaK6k18eUJIWFNYWIj4+Hgkx/eDRTH3bs6pliOv4LsqxbUqgZ0xYwZefvllxMfHIzo6GhkZGZg9ezZatWoVsHYQQoi/+KOHBQUF9WI9JyGEBILa1MMpU6bgs88+w8aNG9G2bVuvbb3tttsQERGBDz/80OtrawO6nRNC3FBVp1cfwLxbUZ8+fbB48WKsXr0a8+fPx+HDh3HNNddUSttCCCH1B1/0kBBCwpFg6qGqqpgyZQpWrFiBb775xqeBt8PhwJ49e5Camur1tbUF3c4JIW4E061o6NCh+t+7d++OPn36oHXr1vj4448xYcIE340mhJAgQLdzQggRBFMPJ0+ejKysLHz22WeIjY1Fbm4uABGRPSYmBgAwZswYXHTRRfoEz6xZs3DVVVehffv2yM/Px8svv4xffvkF9913n1d11yYcfBNC3FBVB1SYy5OoBdTwNW1GQkICLr30Uhw8eNDrawkhJNj4ooeEEBKOBFMP58+fD0CkYKzMokWLMG7cOADA0aNHYbFUOG6fPXsWEydORG5uLpo2bYrevXtj8+bN6Ny5s1d11yYcfBNC3NBSSZgt6w9FRUU4dOgQ7rnnHr/uQwghwaA29ZAQQuozwdRDM2HI1q9fb9h/7bXX8Nprr3lVT13DNd/1nDNnzmD06NGIi4tDQkICJkyYgKKiomqvGThwoFse5fvvv7+WLHZn3rx5aNOmDaKjo9GnTx98//331ZZftmwZOnbsiOjoaHTr1g1fffVVLVnqHd60a/HixW7/JtHR0bVorXcEc03Po48+ig0bNuDIkSPYvHkzbr31VlitVowaNSpIrSHhAvWQelgXcM03qW+EgxYC1EOAetgQ4eC7njN69Gj8+OOPWLt2Lb788kts3LgRkyZNqvG6iRMnGvIov/TSS7VgrTsfffQRMjMzMX36dOzYsQM9evTAkCFDcPLkySrLb968GaNGjcKECROwc+dODB8+HMOHD8fevXtr2fLq8bZdgHDLrvxv8ssvv9Sixd7igGryA3jnVnT8+HGMGjUKHTp0wO23345mzZph69atSEpKCk5TSNhAPaQe1g3B00NCfCHUtRCgHlaGetjAUEm95aefflIBqD/88IN+7F//+peqKIr666+/erxuwIAB6sMPP1wLFtbMlVdeqU6ePFnfdzgcalpamjp79uwqy99+++3qzTffbDjWp08f9Y9//GNQ7fQWb9u1aNEiNT4+vpas852CggIVgJrQuKvatEkPU5+Exl1VAGpBQUFdm0/CGOqhgHpYe1APSX0kHLRQVamHGtTDhgdnvusxW7ZsQUJCAi6//HL92ODBg2GxWLBt27Zqr12yZAmaN2+Orl27Ytq0aTh//nywzXWjrKwM2dnZGDx4sH7MYrFg8ODB2LJlS5XXbNmyxVAeAIYMGeKxfF3gS7sAsba5devWSE9Pxy233IIff/yxNsz1CboVkfoG9VBAPax9qIekPhHqWghQD12hHjYsGHCtHpObm4sWLVoYjkVERCAxMVEPv18Vd911F1q3bo20tDTs3r0bjz/+OPbv34/ly5cH22QDp06dgsPhQHJysuF4cnIy9u3bV+U1ubm5VZavrr21jS/t6tChAxYuXIju3bujoKAAf//739G3b1/8+OOPaNmyZW2Y7RVOOKGYjWbJ1DqkFqAeVpSnHtYu1ENSnwh1LQSoh5WhHjY8OPiuA5544gm8+OKL1Zb5+eeffb5/5XU/3bp1Q2pqKgYNGoRDhw7h4osv9vm+xHcyMjKQkZGh7/ft2xedOnXCW2+9hWeffbYOLasa8bbSbCoJiivxHephw4N6SIg71MKGCfWw4cHBdx3w5z//Wc9X54l27dohJSXFLUBDeXk5zpw5g5SUFNP19enTBwBw8ODBWhXY5s2bw2q1Ii8vz3A8Ly/Po/0pKSlela8LfGmXK5GRkejVq1e9zW3tTW5G5rUl/kA9pB5SDwlpOFoIUA+rg3oY/nDNdx2QlJSEjh07Vvux2WzIyMhAfn4+srOz9Wu/+eYbOJ1OXTTNsGvXLgBAampqoJtSLTabDb1798a6dev0Y06nE+vWrTO85atMRkaGoTwArF271mP5usCXdrnicDiwZ8+eWv83MYuWx9Hch3ltie9QD6mH1ENCGo4WAtTD6qAeNgDqOuIbqZ4bb7xR7dWrl7pt2zZ106ZN6iWXXKKOGjVKP3/8+HG1Q4cO6rZt21RVVdWDBw+qs2bNUrdv364ePnxY/eyzz9R27dqp/fv3rxP7ly5dqkZFRamLFy9Wf/rpJ3XSpElqQkKCmpubq6qqqt5zzz3qE088oZf/7rvv1IiICPXvf/+7+vPPP6vTp09XIyMj1T179tSJ/Z7wtl0zZ85U16xZox46dEjNzs5W77zzTjU6Olr98ccf66oJVaJFs4yJaqM2im5n6hMT1YbRLEmtQD2kHtYm1ENSXwl1LVRV6qEG9bDhwcF3Pef06dPqqFGj1CZNmqhxcXHq+PHj1XPnzunnDx8+rAJQv/32W1VVVfXo0aNq//791cTERDUqKkpt3769+pe//KVOv/ivv/662qpVK9Vms6lXXnmlunXrVv3cgAED1LFjxxrKf/zxx+qll16q2mw2tUuXLuqqVatq2WJzeNOuqVOn6mWTk5PVm266Sd2xY0cdWF09mrhG21qpMVFtTH2iba0orqRWoB5SD2sT6iGpr4SDFqoq9VBVqYcNEUVVVfoEEEIAAIWFhYiPj0eUrSUUxdyqFFV1orTsOAoKChAXFxdkCwkhpHagHhJCiIB6GDgYcI0Q4oY3ESoZzZIQEs5QDwkhREA99B8OvgkhblBcCSFEQD0khBAB9dB/OPgmhFSBN4JJcSWEhDPUQ0IIEVAP/YWDb0KIG3yzSQghAuohIYQIqIf+w8E3IcQN1Yu3ld6UJYSQUIN6SAghAuqh/3DwTQhxQyRBMCeaTJhACAlnqIeEECKgHvoPB9+EkCpwAFBMlqW4EkLCGeohIYQIqIf+wsE3IcQNsU7HnLjyzSYhJJyhHhJCiIB66D/msqQTYoJx48Zh+PDh1ZZZv349FEVBfn5+UG0ZOHAgFEWBoijYtWtXUOsCgDZt2uj1BbtttYPTyw8hpDLUQ+ohIURAPaQekgo4+CYBY+7cuVi8eLG+P3DgQEydOtVQpm/fvsjJyUF8fHzQ7Zk4cSJycnLQtWvXoNf1ww8/4NNPPw16PbWG6vTuQwgxQD2kHhJCBNRD6iGpgINvEjDi4+ORkJBQbRmbzYaUlBQoitn1Ir7TqFEjpKSkICIi+KsrkpKSkJiYGPR6agvVyz++MG/ePLRp0wbR0dHo06cPvv/++wC3gpC6g3pIPSSECKiH1EOzeNs3XLZsGTp27Ijo6Gh069YNX331la9NqzU4+A5B3n//fTRr1gylpaWG48OHD8c999xT5TVHjhyBoihYunQp+vbti+joaHTt2hUbNmwwlNuwYQOuvPJKREVFITU1FU888QTKy8v185988gm6deuGmJgYNGvWDIMHD0ZxcTEAo1vRuHHjsGHDBsydO1d3tzly5EiVbkWffvopunTpgqioKLRp0wavvPKKwaY2bdrg+eefx7333ovY2Fi0atUKb7/9ttfPbfHixW7iv3LlSoPQz5gxAz179sTChQvRqlUrNGnSBA8++CAcDgdeeuklpKSkoEWLFvjb3/7mdf2hRXDdij766CNkZmZi+vTp2LFjB3r06IEhQ4bg5MmTgWoAaSBQD6mHwYduliQ0oB5SD4NP8PTQ277h5s2bMWrUKEyYMAE7d+7E8OHDMXz4cOzdu9fn1tUKKgk5zp8/r8bHx6sff/yxfiwvL0+NiIhQv/nmmyqvOXz4sApAbdmypfrJJ5+oP/30k3rfffepsbGx6qlTp1RVVdXjx4+rjRo1Uh988EH1559/VlesWKE2b95cnT59uqqqqnrixAk1IiJCffXVV9XDhw+ru3fvVufNm6eeO3dOVVVVHTt2rHrLLbeoqqqq+fn5akZGhjpx4kQ1JydHzcnJUcvLy9Vvv/1WBaCePXtWVVVV3b59u2qxWNRZs2ap+/fvVxctWqTGxMSoixYt0m1v3bq1mpiYqM6bN089cOCAOnv2bNVisaj79u3z+IwGDBigPvzww4ZjixYtUuPj4w3HVqxYoVb+GUyfPl1t0qSJ+oc//EH98ccf1c8//1y12WzqkCFD1Iceekjdt2+funDhQhWAunXrVsO9XNsWihQUFKgAVCBCVRBp6gNEqADUgoIC0/VceeWV6uTJk/V9h8OhpqWlqbNnzw5Gs0gYQz2kHgaL2tJDQgIF9ZB6GCxqQw+97Rvefvvt6s0332w41qdPH/WPf/yj7w2tBTj4DlEeeOABdejQofr+K6+8orZr1051Op1VltfE9YUXXtCP2e12tWXLluqLL76oqqqqPvnkk2qHDh0M95g3b57apEkT1eFwqNnZ2SoA9ciRI1XWUVlcVbVqgXMVoLvuuku9/vrrDWX+8pe/qJ07d9b3W7durd599936vtPpVFu0aKHOnz+/Sjs81W1WXBs1aqQWFhbqx4YMGaK2adNGdTgc+rEOHTq4iUF4iavVyw/UY8eOqQUFBfqnpKSkyjpKS0tVq9WqrlixwnB8zJgx6u9///taaCUJN6iH1MNg4I8ecvBN6grqIfUwGAS7f+hL3zA9PV197bXXDMeeeeYZtXv37oFqdlCg23mIMnHiRPz73//Gr7/+CkC4zIwbN67GtTIZGRn63yMiInD55Zfj559/BgD8/PPPyMjIMNyjX79+KCoqwvHjx9GjRw8MGjQI3bp1w2233YZ33nkHZ8+e9asdP//8M/r162c41q9fPxw4cAAOh0M/1r17d/3viqIgJSUlaC7Kbdq0QWxsrL6fnJyMzp07w2KxGI6Fo4u0tuZK5HE0/2nSpAnS09MRHx+vf2bPnl1lHadOnYLD4UBycrLheHJyMnJzc4PVNBLGUA+ph8HAVz1MSUmBzWarG6NJg4d6SD0MBsHuH/rSN8zNzQ3JviTzfIcovXr1Qo8ePfD+++/jhhtuwI8//ohVq1YFtU6r1Yq1a9di8+bN+Pe//43XX38df/3rX7Ft2za0bds2qHVHRkYa9hVFgdPp3VoSi8XilnPQbrebqisQ9YcC0dHROHz4MMrKyry6TlVVt//Yo6KiAmkaIR6hHlIPg4Gvemiz2RAdHR0kqwipHuoh9TAYsH8YODjzHcLcd999WLx4MRYtWoTBgwcjPT29xmu2bt2q/728vBzZ2dno1KkTAKBTp07YsmWLQYC+++47xMbGomXLlgCEqPTr1w8zZ87Ezp07YbPZsGLFiirrstlshreTVdGpUyd89913hmPfffcdLr30Ulit1hrb4w1JSUk4d+6cHgAEQK3keAw1oqOjERcX59UnPj7e7ZgncW3evDmsVivy8vIMx/Py8uRbVUK8h3roHdRDc/iihxx4k7qGeugd1ENzBLN/6EvfMCUlJST7khx8hzB33XUXjh8/jnfeeQf33nuvqWvmzZuHFStWYN++fZg8eTLOnj2rX/vggw/i2LFjeOihh7Bv3z589tlnmD59OjIzM2GxWLBt2zY8//zz2L59O44ePYrly5fjt99+08XZlTZt2mDbtm04cuQITp06VeWbwD//+c9Yt24dnn32Wfz3v//Fe++9hzfeeAOPPvqo7w/GA3369EGjRo3w5JNP4tChQ8jKyjLknSS1g81mQ+/evbFu3Tr9mNPpxLp16wxub4R4A/XQO6iHhIQv1EPvoB7WPb70DTMyMgzlAWDt2rX1vi/JwXcIEx8fj5EjR6JJkyZ6CoeaeOGFF/DCCy+gR48e2LRpEz7//HM0b94cAHDRRRfhq6++wvfff48ePXrg/vvvx4QJE/DUU08BAOLi4rBx40bcdNNNuPTSS/HUU0/hlVdewdChQ6us69FHH4XVakXnzp2RlJSEo0ePupW57LLL8PHHH2Pp0qXo2rUrnnnmGcyaNQvjxo3z6ZlUR2JiIj744AN89dVX6NatGz788EPMmDEj4PWQmsnMzMQ777yD9957Dz///DMeeOABFBcXY/z48XVtGglRqIfeQT0kJHyhHnoH9bB+UFPfcMyYMZg2bZpe/uGHH8bq1avxyiuvYN++fZgxYwa2b9+OKVOm1FUTzFF3sd5IILjuuuvUhx56qMZyWjTLnTt3Bt+oekBV0SyDTThEs6xNXn/9dbVVq1aqzWZTr7zySrfUHIR4C/WwaqiHhDQ8qIdVQz2s31TXNxwwYIA6duxYQ/mPP/5YvfTSS1WbzaZ26dJFXbVqVS1b7D2KqrpEGCAhwdmzZ7F+/Xr84Q9/wE8//YQOHTpUW/7IkSNo27Ytdu7ciZ49e9aOkXXIwIEDsXnzZthsNmzZsgXdunULan1dunTB//73P5SUlODs2bNISEgIan2EkAqoh9VDPSSk4UA9rB7qIalrGO08ROnVqxfOnj2LF198sUZhbYgsWbIEFy5cAAC0atUq6PV99dVXemTMuLi4oNdHCKmAelg91ENCGg7Uw+qhHpK6hjPfhBBCCCGEEEJIkGHANUIIIYQQQgghJMhw8E0IIYQQQgghhAQZDr4JIYQQQgghhJAgw8E3IYQQQgghhBASZDj4JoQQQgghhBBCggwH34QQQgghhBBCSJDh4JsQQgghhBBCCAkyHHwTQgghhBBCCCFBhoNvQgghhBBCCCEkyPx/nRjzRbPWivMAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x300 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define mode solver\n",
    "mode_solver = ModeSolver(\n",
    "    simulation=sim_te,\n",
    "    plane=td.Box(center=mode_source.center, size=mode_source.size),\n",
    "    mode_spec=mode_spec,\n",
    "    freqs=[freq0],\n",
    ")\n",
    "mode_data = run_ms(mode_solver)\n",
    "\n",
    "# visualize mode fields\n",
    "f, (ax1, ax2, ax3) = plt.subplots(1, 3, tight_layout=True, figsize=(10, 3))\n",
    "abs(mode_data.Ex.isel(mode_index=0)).plot(x=\"y\", y=\"z\", ax=ax1, cmap=\"magma\")\n",
    "abs(mode_data.Ey.isel(mode_index=0)).plot(x=\"y\", y=\"z\", ax=ax2, cmap=\"magma\")\n",
    "abs(mode_data.Ez.isel(mode_index=0)).plot(x=\"y\", y=\"z\", ax=ax3, cmap=\"magma\")\n",
    "\n",
    "ax1.set_title(\"|Ex(x, y)|\")\n",
    "ax1.set_aspect(\"equal\")\n",
    "ax2.set_title(\"|Ey(x, y)|\")\n",
    "ax2.set_aspect(\"equal\")\n",
    "ax3.set_title(\"|Ez(x, y)|\")\n",
    "ax3.set_aspect(\"equal\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36381b65",
   "metadata": {},
   "source": [
    "The TM incidence simulation can be made simply by copying the TE simulation while updating the symmetry condition to `(0,1,0)`. Then a simulation batch consisting of both simulations is defined. This way, both simulations will be running in parallel on the server, which will substantially save the total simulation time. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f67374c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# copy the te simulation to make the tm simulation\n",
    "sim_tm = sim_te.copy(update={\"symmetry\": (0, 1, 0)})\n",
    "\n",
    "# define simulation batch\n",
    "sims = {\"TE\": sim_te, \"TM\": sim_tm}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "947ba4e5",
   "metadata": {},
   "source": [
    "Submit the simulation batch to the server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3d61016a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "89f9d0f00e5a48269c79610bc96c02ea",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:41:39 CEST </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> tasks.                      \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m14:41:39 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m2\u001b[0m tasks.                      \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:41:42 CEST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.747</span> for the whole batch.               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m14:41:42 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.747\u001b[0m for the whole batch.               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>the Batch has completed.                                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7764bf30d9ea49b9a07a08c4f021ecd9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:43:31 CEST </span>Batch complete.                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m14:43:31 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7b3265847f05465a8ac481c47b4cecc5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "batch = web.Batch(simulations=sims, verbose=True)\n",
    "batch_results = batch.run(path_dir=\"data\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d035558",
   "metadata": {},
   "source": [
    "## Postprocessing and Result Visualization "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c8eb58b",
   "metadata": {},
   "source": [
    "After the batch of simulations is complete, we first visualize the field intensity distributions in both cases. As expected, the TE mode is blocked and the TM mode transmits through the photonic crystal region. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2652b899",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get individual simulation data from batch result\n",
    "sim_data_te = batch_results[\"TE\"]\n",
    "sim_data_tm = batch_results[\"TM\"]\n",
    "\n",
    "# plot the field intensities in the te and tm cases\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(9, 4))\n",
    "sim_data_te.plot_field(\n",
    "    field_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\", ax=ax1, vmin=0, vmax=4000\n",
    ")\n",
    "sim_data_tm.plot_field(\n",
    "    field_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\", ax=ax2, vmin=0, vmax=4000\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "904169bf",
   "metadata": {},
   "source": [
    "To quantify the filter performance, we plot the transmission in both simulations. The result shows a good transmission (about -0.5 dB) for the TM mode and a low transmission (about -40 dB) for the TE mode. That is, the designed filter functions well while being very compact in size. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7a4d9dd4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T_te = sim_data_te[\"flux\"].flux\n",
    "T_tm = sim_data_tm[\"flux\"].flux\n",
    "\n",
    "# plot the transmissions in the te and tm cases\n",
    "plt.plot(ldas, 10 * np.log10(T_te), label=\"TE\")\n",
    "plt.plot(ldas, 10 * np.log10(T_tm), label=\"TM\")\n",
    "plt.xlim(1.48, 1.62)\n",
    "plt.ylim(-50, 0)\n",
    "plt.xlabel(r\"Wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Transmission (dB)\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d03118e9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components",
   "Photonic crystals"
  ],
  "description": "This notebook demonstrates how to model a photonic crystal waveguide polarization filter in Tidy3D FDTD.",
  "feature_image": "./img/phc_polarization_filter.png",
  "features": [
   "Mode analysis",
   "Parameter sweep"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "photonic crystal, waveguide filter, polarization filter, Tidy3D, FDTD",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.12"
  },
  "title": "Photonic Crystal Waveguide Polarization Filter | Flexcompute",
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "08793066c42a45258d23478c2271017d": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_fd260a0395c34fc5a906e6f08725654d",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">3.5/3.5 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m3.5/3.5 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "185d692d7b5d41b4a4f1120225780b22": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "23effc1700f142fc8e4d4c6dd4e51ff6": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_2d385e94357b4c8c81510eaf720385f5",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">3.5/3.5 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m3.5/3.5 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "2b346afa8d5b464ea8bb5d96bcc87d80": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_f386c9f347d04678bacff99d615548b9",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">result.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">372.6/372.6 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">27.4 MB/s</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mresult.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m372.6/372.6 kB\u001b[0m • \u001b[31m27.4 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "2d385e94357b4c8c81510eaf720385f5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "35c314f0bbef45478c5ce2b26a7ec069": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "5bb1fba0699642c98d656b89044aba20": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_f4fcec9b1f154c11b92ee0a407a9f7a0",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">3.9/3.9 MB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">27.3 MB/s</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m3.9/3.9 MB\u001b[0m • \u001b[31m27.3 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "715a05d084ad4e9abad3b464060d61c4": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_185d692d7b5d41b4a4f1120225780b22",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">3.5/3.5 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m3.5/3.5 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "a567bf84bb5d4b60a5efae31f1a9cb60": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_c614bd4628db42a39c8d7cc4e165dc04",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">mode_solver.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">3.7/3.7 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34mmode_solver.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m3.7/3.7 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "bf35a1d776ca48f0b8c0856caac02722": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_bfe6a667327b42d29d3e3803c1c4fe98",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">3.9/3.9 MB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">25.7 MB/s</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m3.9/3.9 MB\u001b[0m • \u001b[31m25.7 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "bfe6a667327b42d29d3e3803c1c4fe98": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "c614bd4628db42a39c8d7cc4e165dc04": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "d932ab44d79e417e984bc57d0f8a3b2b": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_35c314f0bbef45478c5ce2b26a7ec069",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">TE: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nTM: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "TE: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nTM: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "f386c9f347d04678bacff99d615548b9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "f4fcec9b1f154c11b92ee0a407a9f7a0": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "fd260a0395c34fc5a906e6f08725654d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}