{
"cells": [
{
"cell_type": "markdown",
"id": "0cf39405",
"metadata": {},
"source": [
"# Broadband bi-level taper polarization rotator-splitter"
]
},
{
"cell_type": "markdown",
"id": "e3f37fcb",
"metadata": {},
"source": [
"**This notebook contains large simulations. Running the entire notebook will cost about 30 FlexCredits.**\n",
"\n",
"A polarization splitter-rotator (PSR) is a key component in silicon photonics that is used to manage the polarization state of light. It is a critical component in silicon photonic integrated circuits, enabling more complex and versatile photonic devices and systems. As the name suggests, the PSR has two main functions:\n",
"\n",
"**Splitting**: It separates incoming light into its TE and TM components. This is useful because it allows each polarization to be processed separately, which can be important for certain applications.\n",
"\n",
"**Rotating**: It can convert light from one polarization to another. For example, it can convert TE-polarized light to TM-polarized light, or vice versa. This is important because it allows the light to be correctly interfaced with other devices that might require a specific polarization.\n",
"\n",
"In another case study, we have introduced a [compact PSR](../notebooks/PolarizationSplitterRotator.html), which has a small footprint but narrow bandwidth. In the present study, we delve into the exploration of a broadband PSR. This device employs a bi-level taper to transition the TM0 mode input light into the TE1 mode. Subsequently, a long adiabatic coupler transforms this TE1 mode into the TE0 mode. Conversely, the TE0 input light primarily passes through the PSR with minimal alterations. The broadband PSR demonstrates superior bandwidth and insertion loss compared to the compact design, marking a significant improvement. However, it's worth noting that this enhanced performance comes with a trade-off in terms of size. The broadband PSR has a considerably larger footprint, with a length longer than **0.5 mm**, which causes a difficult simulation in conventional numerical tools. For Tidy3D, even such a large 3D full-wave simulation is fast.\n",
"\n",
"The design is based on `Wesley D. Sacher, Tymon Barwicz, Benjamin J. F. Taylor, and Joyce K. S. Poon, \"Polarization rotator-splitters in standard active silicon photonics platforms,\" Opt. Express 22, 3777-3786 (2014)`, [DOI: 10.1364/OE.22.003777](https://doi.org/10.1364/OE.22.003777).\n",
"\n",
"\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 [90 degree optical hybrid](https://www.flexcompute.com/tidy3d/examples/notebooks/90OpticalHybrid/), 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": "8d1a8953",
"metadata": {},
"outputs": [],
"source": [
"import gdstk\n",
"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"
]
},
{
"cell_type": "markdown",
"id": "413e6b41",
"metadata": {},
"source": [
"## Simulation Setup"
]
},
{
"cell_type": "markdown",
"id": "94b310dd",
"metadata": {},
"source": [
"The simulation wavelength range is from 1500 nm to 1580 nm."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "7f7d6cae",
"metadata": {},
"outputs": [],
"source": [
"lda0 = 1.54 # central wavelength\n",
"ldas = np.linspace(1.5, 1.58, 101) # wavelength range of interest\n",
"freq0 = td.C_0 / lda0 # central frequency\n",
"freqs = td.C_0 / ldas # frequency range of interest\n",
"fwidth = 0.4 * (np.max(freqs) - np.min(freqs)) # frequency width of the source"
]
},
{
"cell_type": "markdown",
"id": "c729fe1e",
"metadata": {},
"source": [
"In this wavelength range, silicon and silicon oxide have minimal dispersion. Therefore, we use a constant refractive index for both. "
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0da6e324",
"metadata": {},
"outputs": [],
"source": [
"# define silicon and silicon dioxide media from material library\n",
"si = td.Medium(permittivity=3.47**2)\n",
"sio2 = td.Medium(permittivity=1.44**2)"
]
},
{
"cell_type": "markdown",
"id": "3d3e4044",
"metadata": {},
"source": [
"Define geometric parameters. The parameters are indicated in the figure below. In addition, we add a side wall angle to mimic realistic fabrication and see if this will degrade the device performance. \n",
"\n",
""
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "a6c80d2a",
"metadata": {},
"outputs": [],
"source": [
"L_blt = 100 # length of the bi-level taper\n",
"L_ac = 300 # length of the adiabatic coupler\n",
"L_s = 5 # length of the straight waveguide between the bi-level taper and the adiabatic coupler\n",
"L_t = 30 # length of the top waveguide taper after the adiabatic coupler\n",
"\n",
"w_1 = 0.45 # input waveguide width\n",
"w_2 = 0.55 # waveguide width at the center of the bi-level taper\n",
"w_pes = 1.55 # width of the widest part of the partially etched slab\n",
"w_3 = 0.85 # waveguide width at the output of the bi-level taper\n",
"w_4 = 0.2 # waveguide width at the beginning of the bottom waveguide\n",
"w_5 = 0.65 # top waveguide width at the end of the adiabatic coupler\n",
"w_6 = 0.5 # output waveguide width\n",
"gap = 0.2 # gap size of the adiabatic coupler\n",
"\n",
"t_pes = 0.09 # thickness of the partially etched slab\n",
"t_si = 0.22 # thickness of the silicon layer\n",
"\n",
"inf_eff = 1e5 # effective infinity\n",
"\n",
"sidewall_angle = 10 * np.pi / 180 # side wall angle"
]
},
{
"cell_type": "markdown",
"id": "c334bcd2",
"metadata": {},
"source": [
"Define the partially etched slab structure."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "e4af6ae6",
"metadata": {},
"outputs": [],
"source": [
"# define the partially etched slab\n",
"vertices = [\n",
" (0, w_1 / 2),\n",
" (L_blt / 2, w_pes / 2),\n",
" (L_blt, w_3 / 2),\n",
" (L_blt, -w_3 / 2),\n",
" (L_blt / 2, -w_pes / 2),\n",
" (0, -w_1 / 2),\n",
"]\n",
"\n",
"partially_etched_slab = td.Structure(\n",
" geometry=td.PolySlab(\n",
" vertices=vertices,\n",
" axis=2,\n",
" slab_bounds=(0, t_pes),\n",
" sidewall_angle=sidewall_angle,\n",
" ),\n",
" medium=si,\n",
")"
]
},
{
"cell_type": "markdown",
"id": "eb211d2d",
"metadata": {},
"source": [
"Define the waveguide structures using `gdstk`. For structures with bending parts, using `gdstk` is easy and convenient."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e9cdeabb",
"metadata": {},
"outputs": [],
"source": [
"R = 300 # bend radius\n",
"theta = np.pi / 30 # s bend angle\n",
"\n",
"# define a gds cell\n",
"cell = gdstk.Cell(\"device\")\n",
"\n",
"# define the top waveguide using a path\n",
"top_wg = gdstk.RobustPath((-inf_eff, 0), w_1, layer=1, datatype=0)\n",
"top_wg.horizontal(0)\n",
"top_wg.horizontal(L_blt / 2, w_2)\n",
"top_wg.horizontal(L_blt, w_3)\n",
"top_wg.horizontal(L_blt + L_s)\n",
"top_wg.segment((L_blt + L_s + L_ac, (w_5 - w_3) / 2), w_5)\n",
"top_wg.horizontal(L_blt + L_s + L_ac + L_t)\n",
"top_wg.arc(R, -np.pi / 2, -np.pi / 2 + theta)\n",
"top_wg.arc(R, np.pi / 2 + theta, np.pi / 2)\n",
"top_wg.horizontal(inf_eff)\n",
"cell.add(top_wg)\n",
"\n",
"# define the bottom waveguide using a path\n",
"bottom_wg = gdstk.RobustPath((L_blt + L_s, (-w_4 - w_3 - 2 * gap) / 2), w_4, layer=1, datatype=0)\n",
"bottom_wg.segment((L_blt + L_s + L_ac, (-w_3 - 2 * gap - w_6) / 2), w_6)\n",
"bottom_wg.arc(R, np.pi / 2, np.pi / 2 - theta)\n",
"bottom_wg.arc(R, -np.pi / 2 - theta, -np.pi / 2)\n",
"bottom_wg.horizontal(inf_eff)\n",
"cell.add(bottom_wg)\n",
"\n",
"# define the waveguide tidy3d geometries\n",
"wg_geos = td.PolySlab.from_gds(\n",
" cell,\n",
" gds_layer=1,\n",
" axis=2,\n",
" slab_bounds=(0, t_si),\n",
" sidewall_angle=sidewall_angle,\n",
")\n",
"\n",
"# define the waveguide tidy3d structures\n",
"wgs = [td.Structure(geometry=wg_geo, medium=si) for wg_geo in wg_geos]"
]
},
{
"cell_type": "markdown",
"id": "e61f0135",
"metadata": {},
"source": [
"Define source, monitors, and simulation. Here we will define a [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html) that launches the TE0 mode into the input waveguide. Two [ModeMonitors](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeMonitor.html) are added to the top and bottom waveguides to monitor the transmission. A [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html) is added in the $xy$ plane to visualize the field distribution."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "72a73176",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"run_time = 15e-12 # simulation run time\n",
"\n",
"Lx = 510 # simulation domain size in x\n",
"Ly = 11 # simulation domain size in y\n",
"Lz = 9 * t_si # simulation domain size in z\n",
"\n",
"x0 = 250 # simulation domain center in x\n",
"y0 = -0.5 # simulation domain center in y\n",
"z0 = t_si / 2 # simulation domain center in z\n",
"\n",
"# define a mode source that launches the TE0 mode\n",
"mode_spec = td.ModeSpec(num_modes=2, target_neff=3.47)\n",
"mode_source_te = td.ModeSource(\n",
" center=(-lda0 / 2, 0, t_si / 2),\n",
" size=(0, 4 * w_1, 6 * t_si),\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 mode monitor at the top waveguide output\n",
"mode_monitor_top = td.ModeMonitor(\n",
" center=(x0 + Lx / 2 - lda0, 3.2, t_si / 2),\n",
" size=mode_source_te.size,\n",
" freqs=freqs,\n",
" mode_spec=mode_spec,\n",
" name=\"mode_top\",\n",
")\n",
"\n",
"# define a mode monitor at the bottom waveguide output\n",
"mode_monitor_bottom = td.ModeMonitor(\n",
" center=(x0 + Lx / 2 - lda0, -4.2, t_si / 2),\n",
" size=mode_source_te.size,\n",
" freqs=freqs,\n",
" mode_spec=mode_spec,\n",
" name=\"mode_bottom\",\n",
")\n",
"\n",
"# define a field monitor to visualize field intensity distribution in the xy plane\n",
"field_monitor = td.FieldMonitor(\n",
" center=(0, 0, t_pes),\n",
" size=(td.inf, td.inf, 0),\n",
" freqs=[freq0],\n",
" interval_space=(2, 2, 1),\n",
" name=\"field\",\n",
")\n",
"\n",
"# define simulation\n",
"sim_te = td.Simulation(\n",
" center=(x0, y0, z0),\n",
" size=(Lx, Ly, Lz),\n",
" grid_spec=td.GridSpec.auto(min_steps_per_wvl=12, wavelength=lda0),\n",
" structures=[partially_etched_slab] + wgs,\n",
" sources=[mode_source_te],\n",
" monitors=[mode_monitor_top, mode_monitor_bottom, field_monitor],\n",
" run_time=run_time,\n",
" boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
" medium=sio2,\n",
")\n",
"\n",
"# visualize the simulation\n",
"ax = sim_te.plot(z=t_pes)\n",
"ax.set_aspect(\"auto\")"
]
},
{
"cell_type": "markdown",
"id": "bc157aec",
"metadata": {},
"source": [
"We can also visualize the cross sections at different $x$ positions of the bi-level taper."
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "fee64d30",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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8qFOnTkrxLFmyhADQv/71L9qxYwf9/PPPFc43JyeH7OzsqHfv3kJPmtzcXHJwcCB/f3+t3OG9Zs0aAkDDhg2jjRs3Unh4OAGgBQsWqFwP5e8RCQ0NFe5R2LBhAwUEBJChoSH9+uuvonoXLlwgY2Nj0Z3PJiYmFBQUpFacH374ITVv3lzp/gEAZGpqSv3796d169bRnDlzyNLSkqysrOiVV16hHTt2EFXyHVK0q3yvuor+Hjp06EDvvvuuWjEz9XFiUOHWrVsUHh5O9vb2ZGxsTK1ataIpU6Yo3eCmKjHQ8+6pHh4eZGRkRA4ODjRp0iTRj97Nmzdp7Nix5O7uTiYmJtS0aVPq3bs3HTt2TKgTHx9PgwcPJqlUShKJhKRSKY0YMYKuX79eaezqTieTyWjx4sXk6elJxsbGZGNjQ126dKHo6GilrpebNm0iHx8foV6vXr3o6NGjwufZ2dkUEhJCTZo0UesGt127dgnza9q0aaU3uJWnTmIgIjpz5gy9+uqrZGpqSlKplKZPn06HDx9WiqeoqIjeeecdsra2rvIGt7feeouaNGlCf//9t6h8//79BIAWL15cZVzq+Prrr6lt27YkkUjI3d2dVqxYofQDXFFiKC4upk8//ZQcHR3J2NiYfH19KS4uTuVyTp06RQEBAWRiYkL29vY0ZcoUKiwsVCvGixcvCjeovQgARUREUGhoKJmampKTkxOtXr2a1q9fT2ZmZvT+++8TaSkxXL16lQCIvjdMO/SoNo7vGGMNXt++fSGVSrF161ahTE9PD1FRUZg7d26tL3/atGk4efIkLly4wL2StIyvMTDGquXLL7/Erl27dDbs9jfffIP58+dzUqgF3F2VMVYtfn5+Fd53UdtsbW01GiKcaYaPGBhjjInwEQNjTGv4kmXDwEcMjDHGRDgxMMYYE+FTSSrI5XLcvXsXTZo04R4PjNVzRITHjx9DKpVWOsBkRUpKSjS6iC6RSESjAzdEnBhUuHv3br0ZSI4xpp47d+6gRYsWGk2jyWiyCo6OjsjIyGjQyYETgwpNmjQBnv+hlR9nnzFWvxQWFsLZ2Vn43mpCcaRQ0XMwVMnOzoZMJuPEUJvWrFmDpUuXIjs7G506dcKqVauERxGWt3HjRmzZskUY/bRLly748ssvRfXHjBmD7777TjRdcHAw4uLi1I5JcfrI0tKSEwNjL4manPY1MjJSa3oi0tm9G3VJo8Qgl8vx66+/4tSpU7h16xaePn0Ke3t7+Pj4IDAwUOPTL7t27UJERATWr18PPz8/xMTEIDg4GNeuXRONR6+QkJCAESNGICAgACYmJli8eDGCgoKQkpKC5s2bC/X69euHzZs3C+9VPamKMcYUNEkMjYFaYyUVFxfjq6++wrp16/Do0SN4e3tDKpXC1NQUjx49wp9//om7d+8iKCgIkZGRePXVV9VauJ+fH3x9fbF69WrgeeJxdnbG1KlTMXPmzCqnLysrg42NDVavXi0MXzxmzBjk5+eLHmivqcLCQlhZWaGgoICPGBir52ryfVVMa29vr9aFa7lcjgcPHjT43wa1LuG3adMGly9fxsaNG1FYWIjExET89NNP2LZtGw4ePIjbt28jPT0dPXv2xPDhw1WO81+eTCbDhQsXEBgY+H/B6OsjMDAQiYmJagX/9OlTPHv2DE2bNhWVJyQkoFmzZmjbti0mTZokPKO2IqWlpSgsLBS9GGONh5GRkdovTZw8eRIDBw6EVCqFnp6e0g4rESEyMhJOTk4wNTVFYGAg0tLStNw6zamVGI4cOYIffvgBAwYMqHDFuLq6YtasWUhLSxMeKl+Z3NxclJWVwcHBQVTu4OCA7OxstYKfMWMGpFKpKLn069cPW7ZsQXx8PBYvXoxff/0V/fv3r/QxiwsXLoSVlZXw4h5JjDUuEolE7Zcmnjx5gk6dOmHNmjUqP1+yZAlWrlyJ9evX49y5czA3N0dwcLDwnG5dUesagyaPzTMyMoK7u3tNYlLLokWLsHPnTiQkJIh6BwwfPlz4v5eXFzp27Ah3d3ckJCSofGg7AMyaNQsRERHCe0UvB8ZY42BoaKjWM8bVeY73i/r374/+/fur/IyIEBMTg9mzZ2Pw4MEAgC1btsDBwQH79u0T/ZbVtWr1SiopKcHly5dx//59pUc+Dho0SK152NnZwcDAADk5OaLynJwcODo6VjrtsmXLsGjRIhw7dgwdO3astG6rVq1gZ2eHGzduVJgYjI2N+QI1Y42YRCKplcRQmYyMDGRnZ4vOeFhZWcHPzw+JiYkvV2KIi4tDeHg4cnNzlT7T09NTe8VJJBJ06dIF8fHxGDJkCPD8wk58fDw+/PDDCqdbsmQJFixYgMOHD6Nr165VLiczMxMPHz6Ek5OTWnEx3UlLS8PZs2d1HUaNhISEKF3zYvWfkZGRWolBcYG6/HXI6uxcKk6Z1+R0em3RODFMnToVoaGhiIyMVGqQpiIiIjB69Gh07doV3bp1Q0xMDJ48eYL33nsPABAeHo7mzZtj4cKFAIDFixcjMjISO3bsQMuWLYWVZ2FhAQsLCxQVFSE6OhpDhw6Fo6Mj0tPTMX36dLzyyisIDg6uUays9n333XdYsGCBrsOokb179wo7OuzlYWhoCEPDqn8OFV1ay59qrqun1tUVjRNDTk4OIiIiapwUACAsLAwPHjxAZGQksrOz4e3tjbi4OGHet2/fFnUhW7duHWQyGYYNGyaaj2KjGBgY4PLly/juu++Qn58PqVSKoKAgfPHFF3yq6CVw5coVXYdQY1euXOHE8BKSSCRqJQbF71H5URGq8/uiOGWek5MjOqORk5MDb29vjeenTRonhmHDhiEhIUFrF5g//PDDCk8dJSQkiN7//ffflc7L1NQUhw8f1kpcrO41lMTAXj5GRkYaHTFoY1QENzc3ODo6Ij4+XkgEhYWFOHfuHCZNmlSjedeUxolh9erVCA0NxalTp+Dl5aXUffWjjz7SZnyskXj8+DEyMjJ0HUaNcWJ4OWl6xKCuoqIi3LhxQ3ifkZGBS5cuoWnTpnBxccG0adMwf/58tG7dGm5ubpgzZw6kUqnOjzo1Tgzff/89jhw5AhMTEyQkJIhuI9fT0+PEwKpFMf7Vy+769esoLi7WeMROpluGhoYa37ymjqSkJPTu3Vt4r+gWP3r0aMTGxmL69Ol48uQJJkyYgPz8fPTo0QNxcXE6H6BP48Tw+eefIzo6GjNnzqzW2OeMqdJQ9rTlcjmuXr2Kzp076zoUpgGJRKJWYtB0oL7XXnut0vGV9PT0MG/ePMybN0+j+dY2jX/ZZTIZwsLCOCkwrWooiQENrC2NRW0NifGy0vjXffTo0di1a1ftRMMarYb0Y9qQ2tJYKE4lVfVS5zpEQ6BxK8vKyrBkyRIcPnwYHTt2VMqgy5cv12Z8rBEgogb1Y9qQ2tJYVGccpIZM48Rw5coV+Pj4AA3ogiHTrXv37uHRo0e6DkNrODG8fNQ9TVQfn8cgl8sRGxuLsWPHam2eGieGEydOaG3hjKEB/pDeu3cPubm5sLOz03UoTE1GRkZqHTHUx8Sgr6+PDRs2aDUxaO0K8q1btyod44ixily+fFnXIWhdQ0t2Dd3LfvG5a9euwgPPtEHjI4bevXur7LJ179493Lt3T6vB6ZwsD5BpbzRFplr61SRYm+k6Cu26/uc59O6u22ENGg1ZzR+spe6PfvnRpOuLzMxMHDp0CMuWLUNAQAC8vLzg5eWFN954o1rz0zgxlB/Do6ysDDdv3sSNGzcQGxtbrSDqrTv7gCZ8o1Jta172G0L9dB2Fdpk+OADc5lFW68Tj4hrPQt2Lz/XxVBIA7N+/H3h+p3VKSgquXLmCY8eO1V1iWLFihcryb775BqtXr8bIkSOrFQhrnMrKynQ+xHBtyMrK0nUITAPq3vmszecx1ERgYCA++eQTpYcAmZmZwc/PD35+NdvT0to1hr59++LSpUvamh1rJO7fv49nz/7RdRhad/duVr097cCU1dajPWtLUlISWrZsCTy/vqvwzTffYNSoUTWev9YSw/Hjx0VjgjCmjoa6Z11aKsPDhw91HQZT08t28Vkmk6FJkybA80cY37x5EwAQEBCA+Pj4Gs9f41NJb731llJZTk4Ozp07h969e4s+37NnT40D1CnnIUANh9ZllYvbcg27z+k6itoxONsVIV1CdB1Gw1dYCGBajWahbnfV+nIqqXXr1jh//jyaNGmCJ0+eoKCgAADQpEkTrdwTpHFisLKyUlnWpk2bGgdT70hsAAknhtr0+x83kP9U11HUjot/ZiDkTRtdh9HwSap+JGdV1D0a+Oef+nHac+rUqRg/fjxatmyJjh074ttvv8Xq1atx6tQprTxETePEsHnz5hovlDGFhtzfvyG3raGpjcQwd+5cREdHi8ratm2Lv/76q1oxvuj9999H06ZNcf36dYwfPx7Dhw9Hq1atcO/ePa3cT6ZWYiAijYebZawqDeXhPBXhxPDyUPdUkqZHDJ6enjh27JjwXpuD8L142v7QoUPYu3cvZDIZhg8fXuN5q3Xx2dPTEzt37oRMJqu0XlpaGiZNmoRFixapHcCaNWvQsmVLmJiYwM/PD+fPn6+0/u7du+Hh4QETExN4eXnh4MGDos+JCJGRkXBycoKpqSkCAwORlpamdjys7qSkpOg6hFqVlpaGkpISXYfB1FBbF58NDQ3h6OgovGprmBRDQ0OEhoZi5MiRMDCo+ak1tRLDqlWrsGzZMjg6OiIsLAxLly7F9u3b8dNPP+Gbb75BREQEunXrBm9vb1haWqr9vNJdu3YhIiICUVFRuHjxIjp16oTg4GDcv39fZf3ffvsNI0aMwLhx45CcnIwhQ4ZgyJAhosH8lixZgpUrV2L9+vU4d+4czM3NERwczF/Qeqih71GXlZXh6tWrug6DqaG2uqumpaVBKpWiVatWGDlyJG7fvl1rbdAmPdLgVr7Tp09j165dOHXqFG7duoXi4mLY2dnBx8cHwcHBGDlyJGxs1L/Y5ufnB19fX2EYDblcDmdnZ0ydOhUzZ85Uqh8WFoYnT57gl19+EcpeffVVeHt7Y/369SAiSKVSfPLJJ/j0008BAAUFBXBwcEBsbKzah1iFhYWwsrJCQUFBjR/4zSr20UcfYdWqVboOo1Z99913CA8P13UYDVpNvq+KaX/44QeYmVU9LsvTp0/x9ttv486dO6JlGRsbw9jYWFT30KFDKCoqQtu2bXHv3j1ER0cjKysLf/75p9DVtL7S6IRXjx490KNHD60sWCaT4cKFC5g1a5ZQpq+vj8DAQCQmJqqcJjExUXhmqkJwcDD27dsHPH/QdnZ2NgIDA4XPrays4Ofnh8TERK2ce2Pa0xAHzyuvMbSxIVD3GsOzZ88AAM7OzqLyqKgozJ07V1T24l3JHTt2hJ+fH1xdXfHDDz9g3LhxWou9NujscUS5ubkoKytT6lrl4OBQ4VX77OxslfUVQyoo/q2sjiqlpaUoLS0V3hcW1nxQLlY1f39/GBsb486dO7oOpVa0a9cO7u7uug6DqUHd6weKOqqOGKpibW2NNm3a4MaNGzWMtvY1jufUVWHhwoVK3cpY7Vu4cKGuQ2AMqEZisLS01Pi0VVFREdLT07UyZEVt09qQGJqys7ODgYEBcnJyROU5OTlwdHRUOY2jo2Ol9RX/ajJPAJg1axYKCgqEV0Pdg2WMqaY4lVTVS5NeSZ9++il+/fVX/P333/jtt9/w5ptvwsDAACNGjKjVtmiDzhKDRCJBly5dRON6yOVyxMfHw9/fX+U0/v7+SuOAHD16VKjv5uYGR0dHUZ3CwkKcO3euwnni+WGgYg+gOnsCjLGXW210V83MzMSIESPQtm1bvP3227C1tcXZs2dhb29fq23RBp2eSoqIiMDo0aPRtWtXdOvWDTExMXjy5Anee+89AEB4eDiaN28unHL4+OOP0atXL3z11VcICQnBzp07kZSUhK+//hoAoKenh2nTpmH+/Plo3bo13NzcMGfOHEilUgwZMkSXTWWM1WPqdkXVpLvqzp07axiV7micGPr06YNevXohKipKVJ6Xl4ehQ4fi+PHjas8rLCwMDx48QGRkJLKzs+Ht7Y24uDjh4vHt27ehr/9/BzUBAQHYsWMHZs+ejX//+99o3bo19u3bhw4dOgh1pk+fjidPnmDChAnIz89Hjx49EBcXBxMTE02byhhrJDS9xtDQaXQfA553KbW1tUX37t2xfft2mJubA8/P40ul0noz+mBN8H0MjL08tHEfw5UrV9S6t+Dx48fw8vJq8L8N1brGcOzYMWRnZ+PVV1/F33//rf2oGGOsDr1sz2OobdVKDE5OTvj111/h5eUFX19fJCQkaD8yxhirI5wYxDS+xqAYZdXY2Bg7duzA/Pnz0a9fP8yYMaM24mOMsVqn7p3PnBgqUP6SxOzZs9GuXTuMHj1am3Exxlid4YvPYhonhoyMDKV+uEOHDoWHhweSkpK0GZvOKJIfD43BWP2n+J5q2I9GpKSkRK0jhsYySrPGvZIag5s3b/IYN4y9ZNLT09GqVSuNpikpKYGbm1ulY6mV5+joiIyMjAbdBZ4Tgwr5+fmwsbHB7du3VT7juiEpLCyEs7Oz0qBgDRG3tWEqKCiAi4sL8vLyYG1trfH0JSUlVT6E7EUSiaRBJwXo+s7n+kpxU52VlVWD/1IpNKahQLitDdOLN8NqwsTEpMH/0GtKZ2MlMcYYq584MTDGGBPhxKCCsbExoqKi1Hr4xsuO29owcVtZTfDFZ8YYYyJ8xMAYY0yEEwNjjDERTgyMMcZEODEwxhgTaTSJYc+ePQgKCoKtrS309PRw6dIltabbvXs3PDw8YGJiAi8vLxw8eFD0OREhMjISTk5OMDU1RWBgINLS0mqpFeqpTkxz586Fnp6e6OXh4SGqU1JSgilTpsDW1hYWFhYYOnQocnJyark1FVuzZg1atmwJExMT+Pn54fz585XWfxm3pYImbY2NjVXaluVv4KqvbT158iQGDhwIqVQKPT097Nu3r8ppEhIS0LlzZxgbG+OVV15BbGysUh1N/1YaPWoktmzZQtHR0bRx40YCQMnJyVVOc+bMGTIwMKAlS5ZQamoqzZ49m4yMjOjKlStCnUWLFpGVlRXt27eP/vjjDxo0aBC5ublRcXFxLbeoYtWJKSoqijw9PenevXvC68GDB6I6EydOJGdnZ4qPj6ekpCR69dVXKSAgoA5apGznzp0kkUho06ZNlJKSQuPHjydra2vKyclRWf9l3ZZUjbZu3ryZLC0tRdsyOztbVKe+tvXgwYP0+eef0549ewgA7d27t9L6N2/eJDMzM4qIiKDU1FRatWoVGRgYUFxcnFBH0/XHiBpNYlDIyMhQOzG8/fbbFBISIirz8/OjDz74gIiI5HI5OTo60tKlS4XP8/PzydjYmL7//vtaiL5q1Y0pKiqKOnXqVOHn+fn5ZGRkRLt37xbKrl69SgAoMTFRiy1QT7du3WjKlCnC+7KyMpJKpbRw4UKV9V/GbamgaVs3b95MVlZWFc6vPrf1ReokhunTp5Onp6eoLCwsjIKDg4X3mq4/RtRoTiVVR2JiIgIDA0VlwcHBSExMBJ4PQZ6dnS2qY2VlBT8/P6FOXatJTGlpaZBKpWjVqhVGjhyJ27dvC59duHABz549E83Xw8MDLi4udd5WmUyGCxcuiGLR19dHYGBghbG8jNsS1WwrABQVFcHV1RXOzs4YPHgwUlJShM/qa1uro6rtWt3119hxYqhEdnY2HBwcRGUODg7CEL2KfyurU9eqG5Ofnx9iY2MRFxeHdevWISMjAz179sTjx4+F+UokEqXRK3XR1tzcXJSVlWnUxpdxW6KabW3bti02bdqE/fv3Y9u2bZDL5QgICEBmZiZQj9taHRVt18LCQhQXF1dr/bEGmhi2b98OCwsL4XXq1Cldh1Rryrf12bNn1ZpP//79ERoaio4dOyI4OBgHDx5Efn4+fvjhB63HzGqXv78/wsPD4e3tjV69emHPnj2wt7fHhg0bdB0ae0k0yGG3Bw0aBD8/P+F98+bNqzUfR0dHpV43OTk5cHR0FD5XlDk5OYnqeHt7VzN6zZRva2lpqVZisra2Rps2bXDjxg3geVtlMhny8/NFRw0vro+6YmdnBwMDg0q3TXkvw7ZUpTptLc/IyAg+Pj6ibYl62NbqqGi7WlpawtTUFAYGBjVef41RgzxiaNKkCV555RXhZWpqWq35+Pv7Iz4+XlR29OhR+Pv7AwDc3Nzg6OgoqlNYWIhz584JdWpb+ba2b99eKzEVFRUhPT1d+OHo0qULjIyMRPO9du0abt++XWdtVZBIJOjSpYsoFrlcjvj4+ApjeRm2pSrVaWt5ZWVluHLlirAt62tbq6Oq7aqN9dco6frqd115+PAhJScn04EDBwgA7dy5k5KTk+nevXtCnVGjRtHMmTOF92fOnCFDQ0NatmwZXb16laKiolR2cbS2tqb9+/fT5cuXafDgwTrv9qdOTH369KFVq1YJ7z/55BNKSEigjIwMOnPmDAUGBpKdnR3dv39fqDNx4kRycXGh48ePU1JSEvn7+5O/v3+dt4+ed0E0Njam2NhYSk1NpQkTJpC1tbXQLbOhbEuqRlujo6Pp8OHDlJ6eThcuXKDhw4eTiYkJpaSkCHXqa1sfP35MycnJlJycTABo+fLllJycTLdu3SIiopkzZ9KoUaOE+oruqp999hldvXqV1qxZo7K7amXrjylrNIlh8+bNBEDpFRUVJdTp1asXjR49WjTdDz/8QG3atCGJREKenp504MAB0edyuZzmzJlDDg4OZGxsTH379qVr167VWbtUUScmV1dXUdvDwsLIycmJJBIJNW/enMLCwujGjRuiaYqLi2ny5MlkY2NDZmZm9Oabb4oSa11btWoVubi4kEQioW7dutHZs2eFzxrKtlTQpK3Tpk0T6jo4ONCAAQPo4sWLovnV17aeOHFC5fdU0b7Ro0dTr169lKbx9vYmiURCrVq1os2bNyvNt7L1x5TxsNuMMcZEGuQ1BsYYY9XHiYExxpgIJwbGGGMinBgYY4yJcGJgjDEmwomBMcaYCCcGxhhjIpwYGGOMiXBiYA3Kt99+i6CgoFpfTlxcHLy9vSGXy2t9WYzVNU4MrMEoKSnBnDlzEBUVVevL6tevH4yMjLB9+/ZaXxZjdY0TA2swfvzxR1haWqJ79+51srwxY8Zg5cqVdbIsxuoSJwZW72zZsgW2trbCsyUUhgwZglGjRlU43c6dOzFw4EBR2WuvvYZp06YpzWfMmDHC+5YtW2L+/PkIDw+HhYUFXF1d8fPPP+PBgwcYPHgwLCws0LFjRyQlJYnmM3DgQCQlJSE9Pb2GLWasfuHEwOqd0NBQlJWV4eeffxbK7t+/jwMHDmDs2LEVTnf69Gl07dq1WstcsWIFunfvjuTkZISEhGDUqFEIDw/Hu+++i4sXL8Ld3R3h4eF4ccxJFxcXODg4NOgnBLLGiRMDq3dMTU3xzjvvYPPmzULZtm3b4OLigtdee03lNPn5+SgoKIBUKq3WMgcMGIAPPvgArVu3RmRkJAoLC+Hr64vQ0FC0adMGM2bMwNWrV5WeBCaVSnHr1q1qLZOx+ooTA6uXxo8fjyNHjiArKwsAEBsbizFjxkBPT09l/eLiYgCAiYlJtZbXsWNH4f+KB8d7eXkpld2/f180nampKZ4+fVqtZTJWXzXIZz6zl5+Pjw86deqELVu2ICgoCCkpKThw4ECF9W1tbaGnp4e8vLwq511WVqZUZmRkJPxfkXxUlZXvnvro0SPY29ur2SrGXg58xMDqrffffx+xsbHYvHkzAgMD4ezsXGFdiUSC9u3bIzU1Vemz8qd/bt68qZX4SkpKkJ6eDh8fH63Mj7H6ghMDq7feeecdZGZmYuPGjZVedFYIDg7G6dOnlcr379+PPXv2ID09HQsWLEBqaipu3bolnKaqrrNnz8LY2JgfKs8aHE4MrN6ysrLC0KFDYWFhgSFDhlRZf9y4cTh48CAKCgpE5SEhIViyZAnat2+PkydPYu3atTh//jy2bt1ao/i+//57jBw5EmZmZjWaD2P1DT/zmdVrffv2haenp9o3koWGhqJz586YNWsW8Pw+Bm9vb8TExGg1rtzcXLRt2xZJSUlwc3PT6rwZ0zU+YmD1Ul5eHvbu3YuEhARMmTJF7emWLl0KCwuLWo0NAP7++2+sXbuWkwJrkLhXEquXfHx8kJeXh8WLF6Nt27ZqT9eyZUtMnTq1VmMDgK5du1b7ZjrG6js+lcQYY0yETyUxxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAtCIhIQF6enpISEjQdShMxwYMGIDx48frZNkzZ86En5+fTpbdkHBiYBpZu3YtYmNjdR1GtezYsQMxMTG6DkOgp6en8rVo0SKlullZWXj77bdhbW0NS0tLDB48GDdv3lR7Wb/99ht69OgBMzMzODo64qOPPkJRUZFSvdLSUsyYMQNSqRSmpqbw8/PD0aNH1V7OmTNncOTIEcyYMUPtabRp2rRp+OOPP/Dzzz/rZPkNhR4Rka6DYC+PDh06wM7OTunIQC6XQyaTQSKRQF+/fu5vvPHGG/jzzz/x999/6zoU4HlieP311xEeHi4q9/Hxgaenp/C+qKgInTt3RkFBAT755BMYGRlhxYoVICJcunQJtra2lS7n0qVL8Pf3R7t27TBhwgRkZmZi2bJl6N27Nw4dOiSqO2LECPz444+YNm0aWrdujdjYWPz+++84ceIEevToUWWbhgwZguLiYhw+fFjj9aEtYWFhuHfvHk6ePKmzGF56xDRWVFSk6xB0xtPTk3r16qXrMKolJCSEXF1ddR2GAABNmTKlynqLFy8mAHT+/Hmh7OrVq2RgYECzZs2qcvr+/fuTk5MTFRQUCGUbN24kAHT48GGh7Ny5cwSAli5dKpQVFxeTu7s7+fv7V7mcnJwcMjQ0pG+++abKurXpxx9/JD09PUpPT9dpHC+zRp8YMjMzaezYseTk5EQSiYRatmxJEydOpNLSUiIi2rx5MwGghIQEmjRpEtnb25O1tbUw/Zo1a6h9+/YkkUjIycmJJk+eTHl5eaJlXL9+nd566y1ycHAgY2Njat68OYWFhVF+fr5Q58iRI9S9e3eysrIic3NzatOmjVpfenWmKykpocjISHJ3dyeJREItWrSgzz77jEpKSpTmt3XrVvL19SVTU1Oytramnj17Cj8erq6uBED0UiSJEydOEAA6ceKEaH4//PADde7cmUxMTMjW1pZGjhxJmZmZojqjR48mc3NzyszMpMGDB5O5uTnZ2dnRJ598Qv/880+V62Dfvn00YMAAYRu2atWK5s2bJ5q2V69eSrFXliQ2bdpEAOjbb78VlS9YsIAA0IEDB6qMqyqKxPD06VMqLi6usJ6vry/5+voqlQcFBZG7u3ulyygoKCBDQ0P67LPPROWlpaVkYWFB48aNE8o+++wzMjAwECUQIqIvv/ySANDt27crXZZinf3999+i8qioKFK1D6r4bmVkZAhlrq6uFBISQidOnKAuXbqQiYkJdejQQfi7+umnn6hDhw5kbGxMnTt3posXLyrNNz8/n/T09Gj58uWVxssqZqjrIxZdunv3Lrp164b8/HxMmDABHh4eyMrKwo8//oinT59CIpEIdSdPngx7e3tERkbiyZMnAIC5c+ciOjoagYGBmDRpEq5du4Z169bh999/x5kzZ2BkZASZTIbg4GCUlpZi6tSpcHR0RFZWFn755Rfk5+fDysoKKSkpeOONN9CxY0fMmzcPxsbGuHHjBs6cOVNp/OpMJ5fLMWjQIJw+fRoTJkxAu3btcOXKFaxYsQLXr1/Hvn37hLrR0dGYO3cuAgICMG/ePEgkEpw7dw7Hjx9HUFAQYmJiMHXqVFhYWODzzz8HADg4OFQYX2xsLN577z34+vpi4cKFyMnJwX/+8x+cOXMGycnJsLa2FuqWlZUhODgYfn5+WLZsGY4dO4avvvoK7u7umDRpUqXrITY2FhYWFoiIiICFhQWOHz+OyMhIFBYWYunSpQCAzz//HAUFBcjMzMSKFSsAABYWFhXO87333sOePXsQERGB119/Hc7Ozrhy5Qqio6Mxbtw4DBgwQKibl5eHsrKySmMEADMzM5iZmSnFvnbtWhAR2rVrh9mzZ+Odd94RPpfL5bh8+TLGjh2rNL9u3brhyJEjePz4MZo0aaJymVeuXME///yDrl27isolEgm8vb2RnJwslCUnJ6NNmzawtLRUWg6en5JydnausH2//fYbbG1t4erqWuW6qMyNGzfwzjvv4IMPPsC7776LZcuWYeDAgVi/fj3+/e9/Y/LkyQCAhQsX4u2338a1a9dEpy+trKzg7u6OM2fO4F//+leNYmm0dJ2ZdCk8PJz09fXp999/V/pMLpcTvbBX06NHD9Ee6P3790kikVBQUBCVlZUJ5atXryYAtGnTJiIiSk5OJgC0e/fuCuNYsWIFAaAHDx5oFL86023dupX09fXp1KlTovL169cTADpz5gwREaWlpZG+vj69+eabova8uC6oklNJ5Y8YZDIZNWvWjDp06CDaG/7ll18IAEVGRgplo0ePJgA0b9480Tx9fHyoS5cuVa6Hp0+fKpV98MEHZGZmJjoq0vRU0r1796hp06b0+uuvU2lpKfn4+JCLi4vSHrWqIylVr6ioKNF0AQEBFBMTQ/v376d169ZRhw4dCACtXbtWqPPgwQOV64aeH60CoL/++qvCNuzevZsA0MmTJ5U+Cw0NJUdHR+G9p6cn9enTR6leSkoKAaD169dXur569OihcntpesQAgH777Teh7PDhwwSATE1N6datW0L5hg0bVB6l0vOjqXbt2lUaL6tY/bxKWAfkcjn27duHgQMHKu1N4fmFwReNHz8eBgYGwvtjx45BJpNh2rRpor2V8ePHw9LSEgcOHACe770AwOHDh/H06VOVsSj2nPfv3w+5XK52G9SZbvfu3WjXrh08PDyQm5srvPr06QMAOHHiBABg3759kMvliIyMVLp4XH5dqCMpKQn379/H5MmTYWJiIpSHhITAw8NDWD8vmjhxouh9z5491ep5Y2pqKvz/8ePHyM3NRc+ePfH06VP89ddfGseu4OjoiDVr1uDo0aPo2bMnLl26hE2bNintUW/fvh1Hjx6t8lX+IvOZM2fw8ccfY9CgQZg4cSIuXLiADh064N///jeKi4sBQPjX2NhYKT7FelXUUaWq6V+ctri4uNrLAYCHDx/Cxsam0jrqaN++Pfz9/YX3iu6nffr0gYuLi1K5qr8RGxsb5Obm1jiWxqrRnkp68OABCgsL0aFDB7Xqu7m5id7funULANC2bVtRuUQiQatWrYTP3dzcEBERgeXLl2P79u3o2bMnBg0ahHfffVdIGmFhYfjmm2/w/vvvY+bMmejbty/eeustDBs2rNIePupMl5aWhqtXr8Le3l7lPO7fvw8ASE9Ph76+Ptq3b6/W+qhKResHADw8PHD69GlRmYmJiVKMNjY2yMvLq3JZKSkpmD17No4fP47CwkLRZwUFBdVswf8MHz4c27Ztw4EDBzBhwgT07dtXqU737t1rtAwFiUSCDz/8UEgSPXr0EJJeaWmpUv2SkhKgXGIsr6rpX5zW1NS02stR0EYnxxd//PHCzlX501iKclV/I0RUrR0a9j+NNjFoSp0vRUW++uorjBkzBvv378eRI0fw0UcfYeHChTh79ixatGgBU1NTnDx5EidOnMCBAwcQFxeHXbt2oU+fPjhy5IjoSKV8TFVNJ5fL4eXlheXLl6ucR2XnjOtSRW2sSn5+Pnr16gVLS0vMmzcP7u7uMDExwcWLFzFjxgyNjsBUefjwIZKSkgAAqampkMvlSsn6wYMHal1jsLCwqPS6Bl7YHo8ePQIANG3aFMbGxrh3755SXUWZVCqtcH5OTk6iuuWnf3FaJycnZGVlVWs5AGBra6tWIleoKIlU9LdQUbmq+eTl5cHOzk7tWJhYoz2VZG9vD0tLS/z555/Vml5xge3atWuicplMhoyMDKULcF5eXpg9ezZOnjyJU6dOISsrC+vXrxc+19fXR9++fbF8+XKkpqZiwYIFOH78uHCqpyJVTefu7o5Hjx6hb9++CAwMVHop9ujd3d0hl8uRmppa6fLU3QuraP0oymp6gVIhISEBDx8+RGxsLD7++GO88cYbCAwMVHlKozp7kFOmTMHjx4+xcOFCnD59WuUNcr6+vnBycqrytWzZsiqXpzgtojh60tfXh5eXl5CcXnTu3Dm0atWqwgvPeH7fiaGhodL0MpkMly5dgre3t1Dm7e2N69evKx11nTt3Tvi8Mh4eHsjIyKjw88ePH4ve5+TkVDq/msjIyEC7du1qbf4NXaNNDPr6+hgyZAj++9//qvzSVXVIHBgYCIlEgpUrV4rqfvvttygoKEBISAgAoLCwEP/8849oWi8vL+jr6wuH7Yq9wxcpvoSqDu0V1Jnu7bffRlZWFjZu3KhUt7i4WOhhNWTIEOjr62PevHlKe9kvts/c3Bz5+fkVxqTQtWtXNGvWDOvXrxe14dChQ7h69aqwfmpKsRf5YowymQxr165Vqmtubq7RqaUff/wRu3btwqJFizBz5kwMHz4cs2fPxvXr10X1qnON4cGDB0rLe/z4MWJiYmBnZ4cuXboI5cOGDcPvv/8u+ju9du0ajh8/jtDQUNE8/vrrL9y+fVt4b2VlhcDAQGzbtk30w7x161YUFRWJph82bBjKysrw9ddfC2WlpaXYvHkz/Pz8qjy69Pf3R15eXoXXhV7cySEioUectu+xLSgoQHp6OgICArQ630ZF11e/dSkzM5McHR3JzMyMpk2bRhs2bKC5c+eSp6encC+CoueEqp5Lit4WQUFBtHr1apo6dSoZGBiQr68vyWQyIiLau3cvNW/enKZNm0Zr166llStXkq+vLxkZGVFiYiIREX388cfk4+NDs2fPpo0bN9KCBQuoefPm1KJFC9G9DuWpM11ZWRkNGDCA9PT0aPjw4bRq1SqKiYmhiRMnUtOmTUXtmjNnDgGggIAAWrZsGa1atYrCw8Np5syZQp3JkyeTnp4effHFF/T9999TfHw8UQX3MSjWnZ+fH8XExNCsWbPIzMyMWrZsKbrXQ3EfQ0XrtzK5ublkY2NDrq6u9NVXX9Hy5cvJx8eHOnXqpBTPkiVLCAD961//oh07dtDPP/9c4XxzcnLIzs6OevfuLfTKys3NJQcHB/L391fquaWpqKgo6tSpE82ePZu+/vprio6OJldXV9LT06Nt27aJ6hYWFpK7uzs1a9aMlixZQitWrCBnZ2eSSqV0//59Ud0X7y1RuHDhAhkbG5OPjw+tW7eOPv/8czIxMaGgoCCluEJDQ4X7HjZs2EABAQFkaGhIv/76a5Vtys7OJkNDQ9qwYYNSWwGQVCql6OhoWrNmDb3++utkZWUlbI/r168TvXAfQ3mqbgbMyMhQuiGPnt/gBoBu3LhRZcxMtUadGIiIbt26ReHh4WRvb0/GxsbUqlUrmjJlitINbqoSAz3vnurh4UFGRkbk4OBAkyZNEv3o3bx5k8aOHUvu7u5kYmJCTZs2pd69e9OxY8eEOvHx8TR48GCSSqUkkUhIKpXSiBEjhC9LRdSdTiaT0eLFi8nT05OMjY3JxsaGunTpQtHR0UpdLzdt2kQ+Pj5CvV69etHRo0eFz7OzsykkJISaNGmi1g1uu3btEubXtGnTSm9wK0+dxEBEdObMGXr11VfJ1NSUpFIpTZ8+Xeji+GI8RUVF9M4775C1tXWVN7i99dZb1KRJE6Wbtfbv308AaPHixVXGVZkjR47Q66+/To6OjmRkZETW1tYUFBQkJNry7ty5Q8OGDSNLS0uysLCgN954g9LS0pTqqUoMRESnTp2igIAAMjExIXt7e5oyZQoVFhYq1SsuLqZPP/2UHB0dydjYmHx9fSkuLk7tdg0aNIj69u0rKlNsxz179pCbmxsZGxtTYGAgpaamkqenJzVr1oz++OMPIi0lhrCwMOrRo4faMTNlPFYSY0xrTp06hddeew1//fUXWrduDbxwI2hd/NRkZ2fDzc0NO3fuxODBg2t9eQ1Vo73GwBjTvp49eyIoKAhLlizRyfJjYmLg5eXFSaGGuLsqY0yryo/YWpdUDVnONMdHDIwxxkT4GgNjjDERPmJgjDEmwomBMcaYCF98VkEul+Pu3bto0qQJD8TFWD1HRHj8+DGkUmm1HitbUlICmUymdn2JRCIaMbgh4sSgwt27d+vN4HKMMfXcuXMHLVq00Gia8iPMqsPR0REZGRkNOjnoPDGsWbMGS5cuRXZ2Njp16oRVq1YJT4wqb+PGjdiyZYsw8F2XLl3w5ZdfiuqPGTMG3333nWi64OBgxMXFqR2TYlCyO3fuKI29zxirXwoLC+Hs7FzpYIIVURwpqHoORUWys7Mhk8k4MdSWXbt2ISIiAuvXr4efnx9iYmIQHByMa9euoVmzZkr1ExISMGLECAQEBMDExASLFy9GUFAQUlJS0Lx5c6Fev379sHnzZuG9JhsdL4zCaWlpyYmBsZdETU77SiQStaYnokoHtmwoNOquKpfL8euvv+LUqVO4desWnj59Cnt7e/j4+CAwMFDj0y9+fn7w9fXF6tWrhfk7Oztj6tSpmDlzZpXTl5WVwcbGBqtXrxZGrhwzZgzy8/NFzzLWVGFhIaysrFBQUMCJgbF6ribfV8W0NjY2al2fkMvlyMvLa/C/DWpdqSkuLsb8+fPh7OyMAQMG4NChQ8jPz4eBgQFu3LiBqKgouLm5YcCAATh79qxaC5bJZLhw4QICAwP/Lxh9fQQGBiIxMVGteTx9+hTPnj1D06ZNReUJCQlo1qwZ2rZti0mTJuHhw4dqzY8x1jhJJBK1X42BWomhTZs2uHz5MjZu3IjCwkIkJibip59+wrZt23Dw4EHcvn0b6enp6NmzJ4YPH65y7P/ycnNzUVZWBgcHB1G5g4MDsrOz1Qp+xowZkEqlouTSr18/bNmyBfHx8Vi8eDF+/fVX9O/fv9InbJWWlqKwsFD0Yow1HkZGRmq/NHHy5EkMHDgQUqkUenp6SmcyiAiRkZFwcnKCqakpAgMDkZaWpuXWaU6tawxHjhyp8mlIrq6umDVrFj799FPRg0Jqy6JFi7Bz504kJCSILgINHz5c+L+Xlxc6duwId3d3JCQkqHxeLwAsXLgQ0dHRtR4zY6x+kkgkap9K0sSTJ0/QqVMnjB07Fm+99ZbS50uWLMHKlSvx3Xffwc3NDXPmzEFwcDBSU1N1enFbrSMGTR6RZ2RkBHd39yrr2dnZwcDAQOnxfjk5OXB0dKx02mXLlmHRokU4cuQIOnbsWGndVq1awc7ODjdu3KiwzqxZs1BQUCC87ty5U2X8jLGGw9DQUK2jBUNDzfrr9O/fH/Pnz8ebb76p9BkRISYmBrNnz8bgwYPRsWNHbNmyBXfv3q3RNVJtqFavpJKSEly+fBn3799XyqCDBg1Sax4SiQRdunRBfHw8hgwZAjzPxvHx8fjwww8rnG7JkiVYsGABDh8+jK5du1a5nMzMTDx8+FB4KLoqxsbGGvdcYow1HEZGRsJjYitTnRvoKpKRkYHs7GzRqXArKyv4+fkhMTFRdPajrmmcGOLi4hAeHo7c3Fylz/T09Co9l19eREQERo8eja5du6Jbt26IiYnBkydP8N577wEAwsPD0bx5cyxcuBAAsHjxYkRGRmLHjh1o2bKlcC3CwsICFhYWKCoqQnR0NIYOHQpHR0ekp6dj+vTpeOWVVxAcHKxpU1ktOXPmTKMbHvmbb75Rup7G6g+JRKJWYlD8vpW/DlmdnUvF71dNrrPWFo0Tw9SpUxEaGorIyMga/6GHhYXhwYMHiIyMRHZ2Nry9vREXFyfM9/bt26IMvW7dOshkMgwbNkw0n6ioKMydOxcGBga4fPkyvvvuO+Tn50MqlSIoKAhffPEFHxHUI7/++it++eUXXYdRp/744w8EBQXpOgxWAUNDQ7VOEynudSjfNV/xG9RQaJwYcnJyEBERobW9nw8//LDCU0cJCQmi93///Xel8zI1NcXhw4e1EherPVeuXNF1CHXuypUrnBjqMYlEolZiUOyolh8VoTo7noprqTk5OaJT3Tk5OfD29tZ4ftqk8QmzYcOGKf1gM6aJxpoYWP2laXdVxagIild1EoObmxscHR0RHx8vlBUWFuLcuXPw9/fXavs0pfERw+rVqxEaGopTp07By8tLqV/vRx99pM34WANTWlqKv/76S9dh1DlODPWboleSthUVFYl6RGZkZODSpUto2rQpXFxcMG3aNMyfPx+tW7cWuqtKpVKhQ46uaJwYvv/+exw5cgQmJiZISEgQjS+ip6fHiYFV6q+//tKog0JDkZqairKyMrUucLK6J5FI1EoMmo7HlJSUhN69ewvvIyIiAACjR49GbGwspk+fjidPnmDChAnIz89Hjx49EBcXp/MB+jRODJ9//jmio6Mxc+ZMrXbdYo1DY91zLikpwY0bN9C2bVtdh8JUqM5dzep47bXXUNlwdHp6epg3bx7mzZun9WXXhMaJQSaTISwsjJMCq5bGmhgA4PLly5wY6qnaOmJ4WWn86z569Gjs2rWrdqJhDV5jTgyNue31XW3d+fyy0riVZWVlWLJkCQ4fPoyOHTsqZdnly5drMz7WwDTmH8fG3Pb6rjGNnKoOjRPDlStX4OPjAwDCk9QYU0deXh4yMzN1HYbOcGKov9S9xqDB42vqjFwuR2xsLMaOHau1eWqcGE6cOKG1hbPGpbH/MN68eRNPnjyBubm5rkNh5ajbXVXT0VXrgr6+PjZs2KDVxKC1K8i3bt2qdPA7xhp7YiAipKSk6DoMpsLL/qCerl27Ck/C1AaNjxh69+6t8sr8vXv3cO/ePa0Gp3OyPEDW+Prc15b0q0mwNtN1FLp17cpZdPNureswGhZZzR+spe6ppPp4xIDno0gfOnQIy5YtQ0BAALy8vODl5YU33nijWvPTODGUH8OjrKwMN2/exI0bNxAbG1utIOqtO/uAJqa6jqLBcCg9iVA/XUehW5Ls/cBt3d681OA8Lq7xLIyMjNQ6GqiviWH//v3A8zutU1JScOXKFRw7dqzuEsOKFStUln/zzTdYvXo1Ro4cWa1AGrO0GzfwUMUw5g0NPwAJuHr1qtrPRX+Zubq6VvoMlPpG3SOG+nLXfmBgID755BP0799fVG5mZgY/Pz/4+dVsD0xrnXL79u2LqVOnamt2jcqen35CevpNXYfB6sDdu/ewadNmXYdR6/r27YOwsDBdh6E2da8f1JcjhqSkJLRs2RJ4fn3X1dUVeL6DfurUKWzdurVG89faxefjx4+LxgRh6iEi3L17V9dhMKZVWVlZug5BI5qOrqprMpkMTZo0AZ4/2/7mzf/tWAYEBIhGa60ujY8YVD3QOicnB+fOnUPv3r1Fn+/Zs6fGAeqU8xDghTHXa0PmnTvYklBSq8tgrK7ZpeciIia0bhZWWAhgWo1moW531X/++adGy9GW1q1b4/z582jSpAmePHmCgoICAECTJk3w6NGjGs9f48RgZWWlsqxNmzY1DqbekdgAktpNDH9cPYP8p7W6CMbqXP7th8jJk9XN40wlNR+xVt1TSfXlGsPUqVMxfvx4tGzZEh07dsS3336L1atX49SpU1pZ5xonhs2bG/750brU2Pv2s4br8uXLeP3113UdhlrUPU2kyRHD3LlzER0dLSpr27atVp5H8v7776Np06a4fv06xo8fj+HDh6NVq1a4d++eVu4nUysxEFGjGVWwrnFiYA3VlStXXqrEoM4Rg6ankjw9PXHs2DHhvTYH4XvxtP2hQ4ewd+9eyGQyDB8+vMbzVuvis6enJ3bu3AmZTFZpvbS0NEyaNAmLFi1SO4A1a9agZcuWMDExgZ+fH86fP19p/d27d8PDwwMmJibw8vLCwYMHRZ8TESIjI+Hk5ARTU1MEBgYiLS1N7XjqGicG1lC9TH/btXXx2dDQEI6OjsLLzs6uVuI3NDREaGgoRo4cqZWHQamVGFatWoVly5bB0dERYWFhWLp0KbZv346ffvoJ33zzDSIiItCtWzd4e3vD0tISkyZNUmvhu3btQkREBKKionDx4kV06tQJwcHBuH//vsr6v/32G0aMGIFx48YhOTkZQ4YMwZAhQ0SD+S1ZsgQrV67E+vXrce7cOZibmyM4OBglJfXvAq9MJmuUj7lkjcPLlBg0HRKjsLBQ9CotLVU537S0NEilUrRq1QojR47E7du367hl1aNHGgwXePr0aezatQunTp3CrVu3UFxcDDs7O/j4+CA4OBgjR46EjY2N2gv38/ODr6+vMIyGXC6Hs7Mzpk6dipkzZyrVDwsLw5MnT/DLL78IZa+++iq8vb2xfv16EBGkUik++eQTfPrppwCAgoICODg4IDY2Vu1DrMLCQlhZWaGgoACWtdgr6cqVK+jYsWOtzZ8xXTIxMUFRUVGtP860Jt9XxbQ//vgjzMyqHq/l6dOnGDZsmFJ5VFQU5s6dKyo7dOgQioqK0LZtW9y7dw/R0dHIysrCn3/+KXQ1ra80OuHVo0cP9OjRQysLlslkuHDhAmbNmiWU6evrIzAwEImJiSqnSUxMFJ6ZqhAcHIx9+/YBzx+0nZ2djcDAQOFzKysr+Pn5ITExscLEUFpaKsr4hYU1H3tFHZcvX66T5TCmCy/T40zV7a6quEZw584dURIyNjZWqvviXckdO3aEn58fXF1d8cMPP2DcuHFai7026OxxRLm5uSgrK1PqWuXg4FDh6ZXs7GyV9bOzs4XPFWUV1VFl4cKFSr0H6kKPHj20cjNKfffXX3+huLjm49k0JE2bNhXuVm3I7O3tdR2CWtTtrvrs2TMAgKWlpcZHJ9bW1mjTpg1u3LhR7TjrSuN4Tl0VZs2aJToSKSwshLOzc60v19XVtVH8OPTp00fXITBWKXUvLNfkzueioiKkp6dj1KhR1Z5HXdFZYrCzs4OBgQFycnJE5Tk5OXB0dFQ5jaOjY6X1Ff/m5OSIBvDKyclRGhX2RcbGxioPBRljjYO63VWr6pn5ok8//RQDBw6Eq6sr7t69i6ioKBgYGGDEiBE1jLb2aW2sJE1JJBJ06dJFdCpFLpcjPj4e/v7+Kqfx9/dXOvVy9OhRob6bmxscHR1FdQoLC3Hu3LkK58kYY7XRXTUzMxMjRoxA27Zt8fbbb8PW1hZnz559KU6v6fRUUkREBEaPHo2uXbuiW7duiImJwZMnT/Dee+8BAMLDw9G8eXMsXLgQAPDxxx+jV69e+OqrrxASEoKdO3ciKSkJX3/9NQBAT08P06ZNw/z589G6dWu4ublhzpw5kEqlGDJkiC6byhirx9S9xqDJE9x27txZw6h0R+PE0KdPH/Tq1QtRUVGi8ry8PAwdOhTHjx9Xe15hYWF48OABIiMjkZ2dDW9vb8TFxQkXj2/fvg19/f87qAkICMCOHTswe/Zs/Pvf/0br1q2xb98+dOjQQagzffp0PHnyBBMmTEB+fj569OiBuLg4mJjww1EYY6pp2iupodPoPgY871Jqa2uL7t27Y/v27cKDzXNyciCVSuvNIFM1UVf3MTDGak4b9zGoe2/B48eP0aFDhwb/21CtawzHjh1DdnY2Xn31Vfz999/aj4oxxuqQpnc+N3TVSgxOTk749ddf4eXlBV9fXyQkJGg/MsYYqyMv24N6apvGJ8wUo6waGxtjx44dmD9/Pvr164cZM2bURnyMMVbr1O2uyomhAuUvScyePRvt2rXD6NGjtRkXY4zVmbq4we1lonFiyMjIUOqHO3ToUHh4eCApKUmbsemMIvnV1ZhJjLHqU3xPNexHI1JcXKzWj35jGdpF415JjcHNmzfh7u6u6zAYYxpIT09Hq1atNJqmpKQEbm5ulY6lVp6joyMyMjIadBd4Tgwq5Ofnw8bGBrdv31b5jOuGRDEuVPnRIhsibmvDVFBQABcXF+Tl5cHa2lrj6UtKSjQa6kIikTTopABd3/lcXyluqrOysmrwXyqF6owW+bLitjZML94MqwkTE5MG/0OvKZ2NlcQYY6x+4sTAGGNMhBODCsbGxoiKimoUQ3FzWxsmbiurCb74zBhjTISPGBhjjIlwYmCMMSbCiYExxpgIJwbGGGMijSYx7NmzB0FBQbC1tYWenh4uXbqk1nS7d++Gh4cHTExM4OXlhYMHD4o+JyJERkbCyckJpqamCAwMRFpaWi21Qj3ViWnu3LnQ09MTvTw8PER1SkpKMGXKFNja2sLCwgJDhw5FTk5OLbemYmvWrEHLli1hYmICPz8/nD9/vtL6L+O2VNCkrbGxsUrbsvwNXPW1rSdPnsTAgQMhlUqhp6eHffv2VTlNQkICOnfuDGNjY7zyyiuIjY1VqqPp30qjR43Eli1bKDo6mjZu3EgAKDk5ucppzpw5QwYGBrRkyRJKTU2l2bNnk5GREV25ckWos2jRIrKysqJ9+/bRH3/8QYMGDSI3NzcqLi6u5RZVrDoxRUVFkaenJ927d094PXjwQFRn4sSJ5OzsTPHx8ZSUlESvvvoqBQQE1EGLlO3cuZMkEglt2rSJUlJSaPz48WRtbU05OTkq67+s25Kq0dbNmzeTpaWlaFtmZ2eL6tTXth48eJA+//xz2rNnDwGgvXv3Vlr/5s2bZGZmRhEREZSamkqrVq0iAwMDiouLE+pouv4YUaNJDAoZGRlqJ4a3336bQkJCRGV+fn70wQcfEBGRXC4nR0dHWrp0qfB5fn4+GRsb0/fff18L0VetujFFRUVRp06dKvw8Pz+fjIyMaPfu3ULZ1atXCQAlJiZqsQXq6datG02ZMkV4X1ZWRlKplBYuXKiy/su4LRU0bevmzZvJysqqwvnV57a+SJ3EMH36dPL09BSVhYWFUXBwsPBe0/XHiBrNqaTqSExMRGBgoKgsODgYiYmJwPMhyLOzs0V1rKys4OfnJ9SpazWJKS0tDVKpFK1atcLIkSNx+/Zt4bMLFy7g2bNnovl6eHjAxcWlztsqk8lw4cIFUSz6+voIDAysMJaXcVuimm0FgKKiIri6usLZ2RmDBw9GSkqK8Fl9bWt1VLVdq7v+GjtODJXIzs6Gg4ODqMzBwUEYolfxb2V16lp1Y/Lz80NsbCzi4uKwbt06ZGRkoGfPnnj8+LEwX4lEojR6pS7ampubi7KyMo3a+DJuS1SzrW3btsWmTZuwf/9+bNu2DXK5HAEBAcjMzATqcVuro6LtWlhYiOLi4mqtP9ZAE8P27dthYWEhvE6dOqXrkGpN+bY+e/asWvPp378/QkND0bFjRwQHB+PgwYPIz8/HDz/8oPWYWe3y9/dHeHg4vL290atXL+zZswf29vbYsGGDrkNjL4kGOez2oEGD4OfnJ7xv3rx5tebj6Oio1OsmJycHjo6OwueKMicnJ1Edb2/vakavmfJtLS0t1UpM1tbWaNOmDW7cuAE8b6tMJkN+fr7oqOHF9VFX7OzsYGBgUOm2Ke9l2JaqVKet5RkZGcHHx0e0LVEP21odFW1XS0tLmJqawsDAoMbrrzFqkEcMTZo0wSuvvCK8TE1NqzUff39/xMfHi8qOHj0Kf39/AICbmxscHR1FdQoLC3Hu3DmhTm0r39b27dtrJaaioiKkp6cLPxxdunSBkZGRaL7Xrl3D7du366ytChKJBF26dBHFIpfLER8fX2EsL8O2VKU6bS2vrKwMV65cEbZlfW1rdVS1XbWx/holXV/9risPHz6k5ORkOnDgAAGgnTt3UnJyMt27d0+oM2rUKJo5c6bw/syZM2RoaEjLli2jq1evUlRUlMoujtbW1rR//366fPkyDR48WOfd/tSJqU+fPrRq1Srh/SeffEIJCQmUkZFBZ86cocDAQLKzs6P79+8LdSZOnEguLi50/PhxSkpKIn9/f/L396/z9tHzLojGxsYUGxtLqampNGHCBLK2tha6ZTaUbUnVaGt0dDQdPnyY0tPT6cKFCzR8+HAyMTGhlJQUoU59bevjx48pOTmZkpOTCQAtX76ckpOT6datW0RENHPmTBo1apRQX9Fd9bPPPqOrV6/SmjVrVHZXrWz9MWWNJjFs3ryZACi9oqKihDq9evWi0aNHi6b74YcfqE2bNiSRSMjT05MOHDgg+lwul9OcOXPIwcGBjI2NqW/fvnTt2rU6a5cq6sTk6uoqantYWBg5OTmRRCKh5s2bU1hYGN24cUM0TXFxMU2ePJlsbGzIzMyM3nzzTVFirWurVq0iFxcXkkgk1K1bNzp79qzwWUPZlgqatHXatGlCXQcHBxowYABdvHhRNL/62tYTJ06o/J4q2jd69Gjq1auX0jTe3t4kkUioVatWtHnzZqX5Vrb+mDIedpsxxphIg7zGwBhjrPo4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDa1C+/fZbBAUF1fpy4uLi4O3tDblcXuvLYqyucWJgDUZJSQnmzJmDqKioWl9Wv379YGRkhO3bt9f6shira5wYWIPx448/wtLSEt27d6+T5Y0ZMwYrV66sk2UxVpc4MbB6Z8uWLbC1tRWGEFcYMmQIRo0aVeF0O3fuxMCBA0Vlr732GqZNm6Y0nzFjxgjvW7Zsifnz5yM8PBwWFhZwdXXFzz//jAcPHmDw4MGwsLBAx44dkZSUJJrPwIEDkZSUhPT09Bq2mLH6hRMDq3dCQ0NRVlaGn3/+WSi7f/8+Dhw4gLFjx1Y43enTp9G1a9dqLXPFihXo3r07kpOTERISglGjRiE8PBzvvvsuLl68CHd3d4SHh+PFocVcXFzg4ODQoB8ExRonTgys3jE1NcU777yDzZs3C2Xbtm2Di4sLXnvtNZXT5Ofno6CgAFKptFrLHDBgAD744AO0bt0akZGRKCwshK+vL0JDQ9GmTRvMmDEDV69eVXrgi1Qqxa1bt6q1TMbqK04MrF4aP348jhw5gqysLABAbGwsxowZAz09PZX1i4uLAQAmJibVWl7Hjh2F/yueD+zl5aVUdv/+fdF0pqamePr0abWWyVh91SAf7clefj4+PujUqRO2bNmCoKAgpKSk4MCBAxXWt7W1hZ6eHvLy8qqcd1lZmVKZkZGR8H9F8lFVVr576qNHj2Bvb69mqxh7OfARA6u33n//fcTGxmLz5s0IDAyEs7NzhXUlEgnat2+P1NRUpc/Kn/65efOmVuIrKSlBeno6fHx8tDI/xuoLTgys3nrnnXeQmZmJjRs3VnrRWSE4OBinT59WKt+/fz/27NmD9PR0LFiwAKmpqbh165Zwmqq6zp49C2NjY352MGtwODGwesvKygpDhw6FhYUFhgwZUmX9cePG4eDBgygoKBCVh4SEYMmSJWjfvj1OnjyJtWvX4vz589i6dWuN4vv+++8xcuRImJmZ1Wg+jNU3/GhPVq/17dsXnp6eat9IFhoais6dO2PWrFnA8/sYvL29ERMTo9W4cnNz0bZtWyQlJcHNzU2r82ZM1/iIgdVLeXl52Lt3LxISEjBlyhS1p1u6dCksLCxqNTYA+Pvvv7F27VpOCqxB4l5JrF7y8fFBXl4eFi9ejLZt26o9XcuWLTF16tRajQ0AunbtWu2b6Rir7/hUEmOMMRE+lcQYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkQ4MTDGGBPhxMAYY0yEEwPTWEJCAvT09JCQkKDrUNhL4s6dOzAxMcGZM2fqfNnPnj2Ds7Mz1q5dW+fLfllxYmAVWrt2LWJjY3UdRrXs2LEDMTExug5DsG7dOoSGhsLFxQV6enoYM2ZMhXXz8/MxYcIE2Nvbw9zcHL1798bFixdV1v3555/RuXNnmJiYwMXFBVFRUfjnn3/Uikkul2PJkiVwc3ODiYkJOnbsiO+//15l3atXr6Jfv36wsLBA06ZNMWrUKDx48EDN1gPz5s2Dn58funfvrvY02mJkZISIiAgsWLAAJSUldb78lxIxVgFPT0/q1auXUnlZWRkVFxdTWVmZTuJSR0hICLm6uuo6DIGrqys1bdqU+vXrR4aGhjR69GiV9crKyiggIIDMzc1p7ty5tHr1amrfvj01adKErl+/Lqp78OBB0tPTo969e9PXX39NU6dOJX19fZo4caJaMc2cOZMA0Pjx4+nrr7+mkJAQAkDff/+9qN6dO3fIzs6O3N3d6T//+Q8tWLCAbGxsqFOnTlRaWlrlcu7fv09GRka0Y8cOteKqDXl5eSSRSOjbb7/VWQwvE04MVSgqKtJ1CDpTUWJ4GdS3xPD333+TXC4nIiJzc/MKE8OuXbsIAO3evVsou3//PllbW9OIESNEddu3b0+dOnWiZ8+eCWWff/456enp0dWrVyuNJzMzk4yMjGjKlClCmVwup549e1KLFi3on3/+EconTZpEpqamdOvWLaHs6NGjBIA2bNhQZduXL19Opqam9Pjx4yrr1qY33niDevbsqdMYXhaNKjFkZmbS2LFjycnJiSQSCbVs2ZImTpwo7PVs3ryZAFBCQgJNmjSJ7O3tydraWph+zZo11L59e5JIJOTk5ESTJ0+mvLw80TKuX79Ob731Fjk4OJCxsTE1b96cwsLCKD8/X6hz5MgR6t69O1lZWZG5uTm1adOGZs2aVWX86kxXUlJCkZGR5O7uThKJhFq0aEGfffYZlZSUKM1v69at5OvrS6ampmRtbU09e/akw4cPEz3fwwUgeimSxIkTJwgAnThxQjS/H374gTp37kwmJiZka2tLI0eOpMzMTFGd0aNHk7m5OWVmZtLgwYPJ3Nyc7Ozs6JNPPhH9GFVk3759NGDAAGEbtmrViubNmyeatlevXkqxV5YkNm3aRACU9iYXLFhAAOjAgQNVxqWJyhJDaGgoOTg4KB2NTZgwgczMzITtmJKSQgBozZo1onpZWVkEgL744otKY1izZg0BoJSUFFH5jh07CACdOnVKKGvWrBmFhoYqzaNNmzbUt2/fKtv7//7f/6PXXntNqdzV1VXleujVq5doh0Tx97Zr1y6aO3cuSaVSsrCwoKFDh1J+fj6VlJTQxx9/TPb29mRubk5jxoxR+ff+n//8h/T09Ojhw4dVxtzYGer6VFZduXv3Lrp16yacv/Xw8EBWVhZ+/PFHPH36FBKJRKg7efJk2NvbIzIyEk+ePAEAzJ07F9HR0QgMDMSkSZNw7do1rFu3Dr///jvOnDkDIyMjyGQyBAcHo7S0FFOnToWjoyOysrLwyy+/ID8/H1ZWVkhJScEbb7yBjh07Yt68eTA2NsaNGzeqvCinznRyuRyDBg3C6dOnMWHCBLRr1w5XrlzBihUrcP36dezbt0+oGx0djblz5yIgIADz5s2DRCLBuXPncPz4cQQFBSEmJgZTp06FhYUFPv/8cwCAg4NDhfHFxsbivffeg6+vLxYuXIicnBz85z//wZkzZ5CcnAxra2uhbllZGYKDg+Hn54dly5bh2LFj+Oqrr+Du7o5JkyZVuh5iY2NhYWGBiIgIWFhY4Pjx44iMjERhYSGWLl0KAPj8889RUFCAzMxMrFixAgBgYWFR4Tzfe+897NmzBxEREXj99dfh7OyMK1euIDo6GuPGjcOAAQOEunl5eSgrK6s0RgAwMzODmZlZlfXKS05ORufOnaGvL778161bN3z99de4fv06vLy8kJycDADo2rWrqJ5UKkWLFi2Ezytbjrm5Odq1a6e0HMXnPXr0QFZWFu7fv6+0HEXdgwcPVrqcZ8+e4ffff69yu6pj4cKFMDU1xcyZM3Hjxg2sWrUKRkZG0NfXR15eHubOnYuzZ88iNjYWbm5uiIyMFE3fpUsXEBF+++03vPHGGzWOp0HTdWaqK+Hh4aSvr0+///670meKQ3zFEUOPHj1Ee6D3798niURCQUFBoj251atXEwDatGkTERElJycrnQYob8WKFQSAHjx4oFH86ky3detW0tfXF+3tERGtX7+eANCZM2eIiCgtLY309fXpzTffVNozVawLquRUUvkjBplMRs2aNaMOHTpQcXGxUO+XX34hABQZGSmUjR49mgDQvHnzRPP08fGhLl26VLkenj59qlT2wQcfiPamqRqnku7du0dNmzal119/nUpLS8nHx4dcXFyooKBAVE/VkZSqV1RUVIXLquyIwdzcnMaOHatUfuDAAQJAcXFxRES0dOlSAkC3b99Wquvr60uvvvpqpe0NCQmhVq1aKZU/efKEANDMmTOJiOj3338nALRlyxalup999hkBULl3rnDjxg0CQKtWrVL6TNMjhg4dOpBMJhPKR4wYQXp6etS/f3/R9P7+/iq3/d27dwkALV68uMJ42f80il5Jcrkc+/btw8CBA1Xu+ejp6Ynejx8/HgYGBsL7Y8eOQSaTYdq0aaI9ufHjx8PS0hIHDhwAAFhZWQEADh8+jKdPn6qMRbHnvH//fsjlcrXboM50u3fvRrt27eDh4YHc3Fzh1adPHwDAiRMnAAD79u2DXC5HZGSk0p5p+XWhjqSkJNy/fx+TJ0+GiYmJUB4SEgIPDw9h/bxo4sSJovc9e/bEzZs3q1yWqamp8P/Hjx8jNzcXPXv2xNOnT/HXX39pHLuCo6Mj1qxZg6NHj6Jnz564dOkSNm3aBEtLS1G97du34+jRo1W+wsPDqxVHcXExjI2NlcoV67W4uFj0b0V1FZ/X9nJerKPKw4cPAQA2NjaVxqOO8PBwGBkZCe/9/PxARBg7dqyonp+fH+7cuaPUO0sRQ25ubo1jaegaxamkBw8eoLCwEB06dFCrvpubm+j9rVu3AABt27YVlUskErRq1Ur43M3NDREREVi+fDm2b9+Onj17YtCgQXj33XeFpBEWFoZvvvkG77//PmbOnIm+ffvirbfewrBhw5R+pF+kznRpaWm4evUq7O3tVc7j/v37AID09HTo6+ujffv2aq2PqlS0fgDAw8MDp0+fFpWZmJgoxWhjY4O8vLwql5WSkoLZs2fj+PHjKCwsFH1WUFBQzRb8z/Dhw7Ft2zYcOHAAEyZMQN++fZXq1HZ3S1NTU5SWliqVK7pZKhKj4t+K6r6YQGtzOSiXrCtCRFXWqYqLi4voveI75ezsrFQul8tRUFAAW1tbpRiqs/PT2DSKxKApdf7QK/LVV19hzJgx2L9/P44cOYKPPvoICxcuxNmzZ9GiRQuYmpri5MmTOHHiBA4cOIC4uDjs2rULffr0wZEjR0RHKuVjqmo6uVwOLy8vLF++XOU8yn+BdKWiNlYlPz8fvXr1gqWlJebNmwd3d3eYmJjg4sWLmDFjhkZHYKo8fPgQSUlJAIDU1FTI5XKlZP3gwQO1rjFYWFhUel2jIk5OTrh3755SuaJMKpUK9RTl5bfrvXv3hGsFlS3nxIkTICLRD2Vly1EVU9OmTVUeTSgofpjVSfoK5WNSqOjvpqLy8slIEYOdnZ3asTRWjeJUkr29PSwtLfHnn39Wa3pXV1cAwLVr10TlMpkMGRkZwucKXl5emD17Nk6ePIlTp04hKysL69evFz7X19dH3759sXz5cqSmpmLBggU4fvy4cKqnIlVN5+7ujkePHqFv374IDAxUein26N3d3SGXy5Gamlrp8tTds6po/SjKyq+f6kpISMDDhw8RGxuLjz/+GG+88QYCAwNVnqaozl7hlClT8PjxYyxcuBCnT59WeYOcr68vnJycqnwtW7asWm309vbGxYsXlZLcuXPnYGZmhjZt2gj18Pw03ovu3r2LzMxM4fPKlvP06VNcvXpVaTkvzr958+awt7dXWg4AnD9/vsrluLi4wNTUFBkZGSo/f/z4sVJZTk5OpfOsLkUM5S+4M2WNIjHo6+tjyJAh+O9//6vyD7yqw9zAwEBIJBKsXLlSVPfbb79FQUEBQkJCAACFhYVK5zW9vLygr68vHIo/evRIaf6KL5eqw3UFdaZ7++23kZWVhY0bNyrVLS4uFnpYDRkyBPr6+pg3b57SD9CL7TM3N0d+fn6FMSl07doVzZo1w/r160VtOHToEK5evSqsn5pS7Bm+GKNMJlM51IG5ublGp5Z+/PFH7Nq1C4sWLcLMmTMxfPhwzJ49G9evXxfVq+1rDMOGDUNOTg727NkjlOXm5mL37t0YOHCgsHfu6ekJDw8PfP3116IjmHXr1kFPTw/Dhg0TygoKCvDXX3+J1sfgwYNhZGQkWndEhPXr16N58+YICAgQyocOHYpffvkFd+7cEcri4+Nx/fp1hIaGVtoeIyMjdO3aVeX3DgASExNFdyOnpKQgLS1NK6eeyrtw4QL09PTg7++v9Xk3OLq++l1XMjMzydHRkczMzGjatGm0YcMGmjt3Lnl6egr3Iih6JanquRQVFUUAKCgoiFavXk1Tp04lAwMD8vX1FXpK7N27l5o3b07Tpk2jtWvX0sqVK8nX15eMjIwoMTGRiIg+/vhj8vHxodmzZ9PGjRtpwYIF1Lx5c2rRooXoXofy1JmurKyMBgwYQHp6ejR8+HBatWoVxcTE0MSJE6lp06aids2ZM4cAUEBAAC1btoxWrVpF4eHhQm8UIqLJkyeTnp4effHFF/T9999TfHw8UQX3MSjWnZ+fH8XExNCsWbPIzMyMWrZsKbrXQ3EfQ0XrtzK5ublkY2NDrq6u9NVXX9Hy5cvJx8eHOnXqpBTPkiVLCAD961//oh07dtDPP/9c4XxzcnLIzs6OevfuLfTKys3NJQcHB/L399fKHd4///wzffHFF/TFF1+QRCIhHx8f4f0ff/wh1Pvnn3/o1VdfJQsLC4qOjqY1a9aQp6cnNWnShP766y/RPP/73/+Snp4e9enTh77++mv66KOPSF9fn8aPHy+qp9g2mzdvFpUrehVNmDCBNm7cKNz5vH37dlG927dvk62tLbm7u9PKlSvpyy+/JBsbG/Ly8qq0R5LCsmXLyNjYWGUPL1NTU/L396fVq1fTl19+SU5OTmRlZUVNmzal9evXE73w91a+t19F31fF31L5HnxvvPEG9ejRo8p4WSO7we3WrVsUHh5O9vb2ZGxsTK1ataIpU6Yo3eCmKjHQ8+6pHh4eZGRkRA4ODjRp0iTRj97Nmzdp7Nix5O7uTiYmJtS0aVPq3bs3HTt2TKgTHx9PgwcPJqlUShKJhKRSKY0YMUJpuIPy1J1OJpPR4sWLydPTk4yNjcnGxoa6dOlC0dHRSl/MTZs2kY+Pj1CvV69edPToUeHz7OxsCgkJoSZNmqh1g9uuXbuE+TVt2rTSG9zKUycxEBGdOXOGXn31VTI1NSWpVErTp0+nw4cPK8VTVFRE77zzDllbW1d5g9tbb71FTZo0ob///ltUvn//fq11b1R001X1Kv+D/ejRIxo3bhzZ2tqSmZkZ9erVq8K/yb1795K3tzcZGxtTixYtaPbs2aIunVRJYigrK6Mvv/ySXF1dSSKRkKenJ23btk3lcv78808KCgoiMzMzsra2ppEjR1J2drZabc/JySFDQ0PaunWrqNzV1ZVGjhxJEydOpCZNmlDTpk1p9uzZ9PPPP1OTJk0oKCiISEuJIT8/nyQSCX3zzTdqxdzY6VFtHLMxxtgLxo0bh+vXr+PUqVNCWcuWLfHaa6/VyUCNMTExWLJkCdLT02vUuaSxaBTXGBhjuhUVFSWMElDXnj17huXLl2P27NmcFNTE3VUZY7XOxcVFZ0NeGxkZ4fbt2zpZ9suKjxgYY4yJ8DUGxhhjInzEwBhjTIQTA2OMMRFODIwxxkS4V5IKcrkcd+/eRZMmTXgkRsbqOSLC48ePIZVKKx2huCIlJSWQyWRq15dIJKLh5RsiTgwq3L17t96MRMoYU8+dO3fQokULjaZRZ4jy8hwdHZGRkdGgk4POE8OaNWuwdOlSZGdno1OnTli1alWFQwZv3LgRW7ZsEUZJ7dKlC7788ktR/TFjxuC7774TTRccHIy4uDi1Y2rSpAnw/A+t/INaGGP1S2FhIZydnYXvrSYURwomJiZqnR0gImRnZ0Mmk3FiqC27du1CREQE1q9fDz8/P8TExCA4OBjXrl1Ds2bNlOonJCRgxIgRCAgIgImJCRYvXoygoCCkpKSgefPmQr1+/fph8+bNwvvKxotXRfEHYmlpyYmBsZdETU77Ghsbq50YdHWjXl3S6D4GuVyOX3/9FadOncKtW7fw9OlT2Nvbw8fHB4GBgRqffvHz84Ovry9Wr14tzN/Z2RlTp07FzJkzq5y+rKwMNjY2WL16tTDM8ZgxY5Cfny968L2mCgsLYWVlhYKCAk4MjNVzNfm+Kqa1tbVV6/qEXC7Hw4cPG/xvg1pXaoqLizF//nw4OztjwIABOHToEPLz82FgYIAbN24gKioKbm5uGDBgAM6ePavWgmUyGS5cuIDAwMD/C0ZfH4GBgUhMTFRrHk+fPsWzZ8/QtGlTUXlCQgKaNWuGtm3bYtKkScJzZytSWlqKwsJC0Ysx1ngYGRmp/WoM1EoMbdq0weXLl7Fx40YUFhYiMTERP/30E7Zt24aDBw/i9u3bSE9PR8+ePTF8+HCVD4opLzc3F2VlZXBwcBCVOzg4IDs7W63gZ8yYAalUKkou/fr1w5YtWxAfH4/Fixfj119/Rf/+/St9HOPChQthZWUlvPjCM2ONi0QiUfuliZMnT2LgwIGQSqXQ09NTOpNBRIiMjISTkxNMTU0RGBiItLQ0LbdOc2olhiNHjuCHH37AgAEDKsyYrq6umDVrFtLS0tCnTx9tx6lk0aJF2LlzJ/bu3Su6CDR8+HAMGjQIXl5eGDJkCH755Rf8/vvvSEhIqHBes2bNQkFBgfB68UlVjLGGz9DQUK2jBUNDzS7LPnnyBJ06dcKaNWtUfr5kyRKsXLkS69evx7lz52Bubo7g4GCdX8dQq5WaPCPVyMgI7u7uVdazs7ODgYGB0vNdc3Jy4OjoWOm0y5Ytw6JFi3Ds2DF07Nix0rqtWrWCnZ0dbty4gb59+6qsY2xsrPEFasZYwyGRSIRHx1amsjMPqvTv3x/9+/dX+RkRISYmBrNnz8bgwYMBAFu2bIGDgwP27duH4cOHa7QsbapWr6SSkhJcvnwZ9+/fV3pm8KBBg9Sah0QiQZcuXRAfH48hQ4YAzy/sxMfH48MPP6xwuiVLlmDBggU4fPgwunbtWuVyMjMz8fDhQzg5OakVF6tccXGxrkNotPT19XkHppYYGRmplRgUF6jLX4eszs5lRkYGsrOzRafCrays4Ofnh8TExJcrMcTFxSE8PBy5ublKn+np6WmUUSMiIjB69Gh07doV3bp1Q0xMDJ48eYL33nsPABAeHo7mzZtj4cKFAIDFixcjMjISO3bsQMuWLYVrERYWFrCwsEBRURGio6MxdOhQODo6Ij09HdOnT8crr7yC4OBgTZvKysnPz4eNjY2uw2i0XnnllXpx/rkh0vSIofx1yKioKMydO1ejZSp+v2pynbW2aJwYpk6ditDQUERGRio1SFNhYWF48OABIiMjkZ2dDW9vb8TFxQnzvX37tqgL2bp16yCTyTBs2DDRfBQbxcDAAJcvX8Z3332H/Px8SKVSBAUF4YsvvuA9LS1Q3FjIdCM9PR1PnjyBubm5rkNpcAwNDdW6fqC416H8za8N7fdF48SQk5ODiIiIGicFhQ8//LDCU0flLxj//ffflc7L1NQUhw8f1kpcTNmVK1d0HUKjRkRITU2Fr6+vrkNpcNS9sKzNm18V11JzcnJEp7pzcnLg7e1do3nXlMYjTg0bNqzSHj6s4bp8+bKuQ2j0eBvUjtrqrloZNzc3ODo6Ij4+XigrLCzEuXPn4O/vr7XlVIfGRwyrV69GaGgoTp06BS8vL6Xuqx999JE242P1CB8x6B5vg9qh6K6qbUVFRbhx44bwPiMjA5cuXULTpk3h4uKCadOmYf78+WjdujXc3NwwZ84cSKVSoUOOrmicGL7//nscOXIEJiYmSEhIEI0voqenx4mhgSIivsZQD3BiqB0SiUStxKDpeExJSUno3bu38D4iIgIAMHr0aMTGxmL69Ol48uQJJkyYgPz8fPTo0QNxcXE6H6BP42c+Ozo64qOPPsLMmTOrNfb5y4DHSlJ2+/ZtuLq66jqMRs/e3h7379/XdRj1ijbGSnrzzTfVSgzPnj3D3r17G/xvg8ZHDDKZDGFhYQ02KTDVeE+1fnjw4AFycnK01vmD/Y+RkZFWrx+87DT+dR89ejR27dpVO9GweosTQ/3B20L7eBA9MY2PGMrKyrBkyRIcPnwYHTt2VFpRy5cv12Z8rJ7g3jD1x+XLl0V3y7KaU/dHX8Mz73VCLpcjNjYWY8eO1do8NU4MV65cgY+PD8A3PDUqvJdaf/C20D5td0WtS/r6+tiwYYNuE8OJEye0tnD2cpDJZPjrr790HQZ7jhOD9qnbXbX82HD1RdeuXbF69epKx5nThNYe7Xnr1i0sXbpUeBpbgyDLA2SajabYEKWlpsJC8g/wcu5QNThZGX+irDhXrbF9GgVZzR+spe4RQ308lYTng4UeOnQIy5YtQ0BAALy8vODl5YU33nijWvPTODH07t1bZV/ee/fu4d69ew0rMdzZBzQx1XUUOleUeh6hfrqOgv2fUuReXMc9kxQe13zEX3WvMdTXI4b9+/cDz2+oS0lJwZUrV3Ds2LG6Swzlx/AoKyvDzZs3cePGDcTGxlYrCFa/ZWVm6ToEVk5WVhYnBi1St7tqfUkMgYGB+OSTT5Se9WBmZgY/Pz/4+dVsT07jxLBixQqV5d988w1Wr16NkSNH1iggVv9kZXFiqG+ysrLQuXNnXYfRYKh7xKDpg3pqS1JSElq2bAk8P42vuPn0m2++walTp7B169YazV9rd6n17dsXly5d0tbsWD2SlZWp6xBYOZystetlu49BJpOhSZMmAAAvLy/cvHkTABAQECAalK+6tHbx+fjx46IxQRoE5yFAA77tXR0FBQXYcOgDXYfByrmYW4CJX4bqOoz6obAQwLQazULdU0n15YihdevWOH/+PJo0aYInT56goKAAANCkSRM8evSoxvPXODG89dZbSmU5OTk4d+4cevfuLfp8z549NQ5QpyQ2gKRxJ4Yr11KQ/1TXUbDyLv6Zgaf/GMPMzEzXoeiepOa9s9Q9Gvjnn39qvCxtmDp1KsaPH4+WLVuiY8eO+Pbbb7F69WqcOnVKK9eeNE4MVlZWKsvatGlT42BY/cN95usnIkJKSgo/tEdL1O2uWl+OGN5//300bdoU169fx/jx4zF8+HC0atUK9+7d08q9DBonhs2bN9d4oezlwYmh/rpy5QonBi2pjSOGuXPnIjo6WlTWtm1brd0s+uLZmUOHDmHv3r2QyWQYPnx4jeetVmIgIo3HIWcNAyeG+ou3jfaoe41B01NJnp6eOHbsmPBenceHVoehoSFCQ7V3zUmtXkmenp7YuXMnZDJZpfXS0tIwadIkLFq0SO0A1qxZg5YtW8LExAR+fn44f/58pfV3794NDw8PmJiYwMvLCwcPHhR9TkSIjIyEk5MTTE1NERgYiLS0NLXjYf+HiPjHpx7jbaM9tdUrydDQEI6OjsLLzs6u1tqgTWolhlWrVmHZsmVwdHREWFgYli5diu3bt+Onn37CN998g4iICHTr1g3e3t6wtLTEpEmT1Fr4rl27EBERgaioKFy8eBGdOnVCcHBwhQ8i+e233zBixAiMGzcOycnJGDJkCIYMGSIazG/JkiVYuXIl1q9fj3PnzsHc3BzBwcEoKSlRd52w5+7cuSP0dmD1DycG7dE0MRQWFopepaWlKueblpYGqVSKVq1aYeTIkbh9+3Ydt6x6NHqC2+nTp7Fr1y6cOnUKt27dQnFxMezs7ODj44Pg4GCMHDkSNjY2ai/cz88Pvr6+wjAacrkczs7OmDp1KmbOnKlUPywsDE+ePMEvv/wilL366qvw9vbG+vXrQUSQSqX45JNP8OmnnwLPu1s6ODggNjZW7XNv/AS3/zlw4EC1b6lndSMnJwfNmjXTdRg6pY0nuP30008wNzevsv6TJ08wdOhQpfKoqCjMnTtXVHbo0CEUFRWhbdu2uHfvHqKjo5GVlYU///xTuAehvtLohFePHj3Qo0cPrSxYJpPhwoULmDVrllCmr6+PwMBAJCYmqpwmMTFReGaqQnBwMPbt2wc8f9B2dna2aKx6Kysr+Pn5ITExscLEUFpaKsr4hYU1H5SrIbh58yZsbGyQn5+v61BYOfr6+rC2tsb169cbfWLQBnVPEynq3LlzR5SEjI2Nleq+OFxFx44d4efnB1dXV/zwww8YN26c1mKvDbVzJUQNubm5KCsrU+pz6+DgUOFV++zsbJX1s7Ozhc8VZRXVUWXhwoVKvQfY//pKT506VddhMFbr1O2u+uzZMwCApaWlxkcn1tbWaNOmDW7cuFHtOOsKP7gZwKxZs1BQUCC87ty5o+uQGGN1qC6GxCgqKkJ6ejqcnJy0Gntt0NkRg52dHQwMDJCTkyMqz8nJgaOjo8ppHB0dK62v+DcnJ0e08nNycpRGhX2RsbGxykNBxljjoO6DejTpbvrpp59i4MCBcHV1xd27dxEVFQUDAwOMGDGihtHWPp0dMUgkEnTp0kU04JNcLkd8fDz8/f1VTuPv7680QNTRo0eF+m5ubnB0dBTVKSwsxLlz5yqcJ2OMKU4lqfNSV2ZmJkaMGIG2bdvi7bffhq2tLc6ePQt7e/tabYs26OyIAQAiIiIwevRodO3aFd26dUNMTAyePHmC9957DwAQHh6O5s2bY+HChQCAjz/+GL169cJXX32FkJAQ7Ny5E0lJSfj6668BAHp6epg2bRrmz5+P1q1bw83NDXPmzIFUKsWQIUN02VTGWD2m6cVndezcubOGUemOxomhT58+6NWrF6KiokTleXl5GDp0KI4fP672vMLCwvDgwQNERkYiOzsb3t7eiIuLEy4e3759G/r6/3dQExAQgB07dmD27Nn497//jdatW2Pfvn3o0KGDUGf69Ol48uQJJkyYgPz8fPTo0QNxcXEwMTHRtKmMsUZC3Tuf68uw27VNo/sY8LybnK2tLbp3747t27cLfX9zcnIglUrrzSBTNcH3MTD28tDGfQypqalq3Vvw+PFjtG/fvsH/NlTrGsOxY8eQnZ2NV199FX///bf2o2KMsTpUG9cYXmbVSgxOTk749ddf4eXlBV9fXyQkJGg/MsYYqyOKXklVvWprELz6RuNWKkZZNTY2xo4dOzB//nz069cPM2bMqI34GGOs1tXGxeeXmcaJofwlidmzZ6Ndu3YYPXq0NuNijLE6o+5posZyKknjxJCRkaHUD3fo0KHw8PBAUlKSNmPTGUXy4zGTGKv/FN9TDfvRiBQXF6t1NFBcXFztZbxMNO6V1BjcvHkT7u7uug6DMaaB9PR0tGrVSqNpSkpK4ObmVulYauU5OjoiIyOjQXeB58SgQn5+PmxsbHD79m2Vz7huSAoLC+Hs7Kw0WmRDxG1tmAoKCuDi4oK8vDxYW1trPH1JSUmVDyF7kUQiadBJAbq+87m+UtxUZ2Vl1eC/VArVGS3yZcVtbZhevBlWEyYmJg3+h15TPLoqY4wxEU4MjDHGRDgxqGBsbIyoqKhGMRQ3t7Vh4raymuCLz4wxxkT4iIExxpgIJwbGGGMinBgYY4yJcGJgjDEm0mgSw549exAUFARbW1vo6enh0qVLak23e/dueHh4wMTEBF5eXjh48KDocyJCZGQknJycYGpqisDAQKSlpdVSK9RTnZjmzp0LPT090cvDw0NUp6SkBFOmTIGtrS0sLCwwdOhQ5OTk1HJrKrZmzRq0bNkSJiYm8PPzw/nz5yut/zJuSwVN2hobG6u0LcvfwFVf23ry5EkMHDgQUqkUenp62LdvX5XTJCQkoHPnzjA2NsYrr7yC2NhYpTqa/q00etRIbNmyhaKjo2njxo0EgJKTk6uc5syZM2RgYEBLliyh1NRUmj17NhkZGdGVK1eEOosWLSIrKyvat28f/fHHHzRo0CByc3Oj4uLiWm5RxaoTU1RUFHl6etK9e/eE14MHD0R1Jk6cSM7OzhQfH09JSUn06quvUkBAQB20SNnOnTtJIpHQpk2bKCUlhcaPH0/W1taUk5Ojsv7Lui2pGm3dvHkzWVpairZldna2qE59bevBgwfp888/pz179hAA2rt3b6X1b968SWZmZhQREUGpqam0atUqMjAwoLi4OKGOpuuPETWaxKCQkZGhdmJ4++23KSQkRFTm5+dHH3zwARERyeVycnR0pKVLlwqf5+fnk7GxMX3//fe1EH3VqhtTVFQUderUqcLP8/PzycjIiHbv3i2UXb16lQBQYmKiFlugnm7dutGUKVOE92VlZSSVSmnhwoUq67+M21JB07Zu3ryZrKysKpxffW7ri9RJDNOnTydPT09RWVhYGAUHBwvvNV1/jKjRnEqqjsTERAQGBorKgoODkZiYCDwfgjw7O1tUx8rKCn5+fkKdulaTmNLS0iCVStGqVSuMHDkSt2/fFj67cOECnj17Jpqvh4cHXFxc6rytMpkMFy5cEMWir6+PwMDACmN5GbclqtlWACgqKoKrqyucnZ0xePBgpKSkCJ/V17ZWR1Xbtbrrr7HjxFCJ7OxsODg4iMocHByEIXoV/1ZWp65VNyY/Pz/ExsYiLi4O69atQ0ZGBnr27InHjx8L85VIJEqjV+qirbm5uSgrK9OojS/jtkQ129q2bVts2rQJ+/fvx7Zt2yCXyxEQEIDMzEygHre1OiraroWFhSguLq7W+mMNNDFs374dFhYWwuvUqVO6DqnWlG/rs2fPqjWf/v37IzQ0FB07dkRwcDAOHjyI/Px8/PDDD1qPmdUuf39/hIeHw9vbG7169cKePXtgb2+PDRs26Do09pJokMNuDxo0CH5+fsL75s2bV2s+jo6OSr1ucnJy4OjoKHyuKHNychLV8fb2rmb0minf1tLSUq3EZG1tjTZt2uDGjRvA87bKZDLk5+eLjhpeXB91xc7ODgYGBpVum/Jehm2pSnXaWp6RkRF8fHxE2xL1sK3VUdF2tbS0hKmpKQwMDGq8/hqjBnnE0KRJE7zyyivCy9TUtFrz8ff3R3x8vKjs6NGj8Pf3BwC4ubnB0dFRVKewsBDnzp0T6tS28m1t3769VmIqKipCenq68MPRpUsXGBkZieZ77do13L59u87aqiCRSNClSxdRLHK5HPHx8RXG8jJsS1Wq09byysrKcOXKFWFb1te2VkdV21Ub669R0vXV77ry8OFDSk5OpgMHDhAA2rlzJyUnJ9O9e/eEOqNGjaKZM2cK78+cOUOGhoa0bNkyunr1KkVFRans4mhtbU379++ny5cv0+DBg3Xe7U+dmPr06UOrVq0S3n/yySeUkJBAGRkZdObMGQoMDCQ7Ozu6f/++UGfixInk4uJCx48fp6SkJPL39yd/f/86bx8974JobGxMsbGxlJqaShMmTCBra2uhW2ZD2ZZUjbZGR0fT4cOHKT09nS5cuEDDhw8nExMTSklJEerU17Y+fvyYkpOTKTk5mQDQ8uXLKTk5mW7dukVERDNnzqRRo0YJ9RXdVT/77DO6evUqrVmzRmV31crWH1PWaBLD5s2bCYDSKyoqSqjTq1cvGj16tGi6H374gdq0aUMSiYQ8PT3pwIEDos/lcjnNmTOHHBwcyNjYmPr27UvXrl2rs3apok5Mrq6uoraHhYWRk5MTSSQSat68OYWFhdGNGzdE0xQXF9PkyZPJxsaGzMzM6M033xQl1rq2atUqcnFxIYlEQt26daOzZ88KnzWUbamgSVunTZsm1HVwcKABAwbQxYsXRfOrr209ceKEyu+pon2jR4+mXr16KU3j7e1NEomEWrVqRZs3b1aab2XrjynjYbcZY4yJNMhrDIwxxqqPEwNjjDERTgyMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxsAbl22+/RVBQUK0vJy4uDt7e3pDL5bW+LMbqGicG1mCUlJRgzpw5iIqKqvVl9evXD0ZGRti+fXutL4uxusaJgTUYP/74IywtLdG9e/c6Wd6YMWOwcuXKOlkWY3WJEwOrd7Zs2QJbW1thCHGFIUOGYNSoURVOt3PnTgwcOFBU9tprr2HatGlK8xkzZozwvmXLlpg/fz7Cw8NhYWEBV1dX/Pzzz3jw4AEGDx4MCwsLdOzYEUlJSaL5DBw4EElJSUhPT69hixmrXzgxsHonNDQUZWVl+Pnnn4Wy+/fv48CBAxg7dmyF050+fRpdu3at1jJXrFiB7t27Izk5GSEhIRg1ahTCw8Px7rvv4uLFi3B3d0d4eDheHFrMxcUFDg4ODfpBUKxx4sTA6h1TU1O888472Lx5s1C2bds2uLi44LXXXlM5TX5+PgoKCiCVSqu1zAEDBuCDDz5A69atERkZicLCQvj6+iI0NBRt2rTBjBkzcPXqVaUHvkilUty6datay2SsvuLEwOql8ePH48iRI8jKygIAxMbGYsyYMdDT01NZv7i4GABgYmJSreV17NhR+L/i+cBeXl5KZffv3xdNZ2pqiqdPn1ZrmYzVVw3y0Z7s5efj44NOnTphy5YtCAoKQkpKCg4cOFBhfVtbW+jp6SEvL6/KeZeVlSmVGRkZCf9XJB9VZeW7pz569Aj29vZqtoqxlwMfMbB66/3330dsbCw2b96MwMBAODs7V1hXIpGgffv2SE1NVfqs/OmfmzdvaiW+kpISpKenw8fHRyvzY6y+4MTA6q133nkHmZmZ2LhxY6UXnRWCg4Nx+vRppfL9+/djz549SE9Px4IFC5Camopbt24Jp6mq6+zZszA2NuZnB7MGhxMDq7esrKwwdOhQWFhYYMiQIVXWHzduHA4ePIiCggJReUhICJYsWYL27dvj5MmTWLt2Lc6fP4+tW7fWKL7vv/8eI0eOhJmZWY3mw1h9w4/2ZPVa37594enpqfaNZKGhoejcuTNmzZoFPL+PwdvbGzExMVqNKzc3F23btkVSUhLc3Ny0Om/GdI2PGFi9lJeXh7179yIhIQFTpkxRe7qlS5fCwsKiVmMDgL///htr167lpMAaJO6VxOolHx8f5OXlYfHixWjbtq3a07Vs2RJTp06t1dgAoGvXrtW+mY6x+o5PJTHGGBPhU0mMMcZEODEwxhgT4cTAGGNMhBMDY4wxEU4MjDHGRDgxMMYYE+HEwBhjTIQTA2OMMRFODIwxxkT+P8K/ZfcvC0FBAAAAAElFTkSuQmCC",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(3, 1, figsize=(4, 7), tight_layout=True)\n",
"\n",
"for i in range(3):\n",
" sim_te.plot_eps(x=i * L_blt / 2, freq=freq0, ax=ax[i])\n",
" ax[i].set_xlim(-1, 1)\n",
" ax[i].set_ylim(-0.1, 0.3)"
]
},
{
"cell_type": "markdown",
"id": "abaa2ce9",
"metadata": {},
"source": [
"## Mode Analysis "
]
},
{
"cell_type": "markdown",
"id": "5abca817",
"metadata": {},
"source": [
"We can intuitively visualize the mode evolution alone the device to see physically why it functions as a PSR. This requires us to perform mode analysis at different $x$ positions. First, let's perform the mode analysis at the input waveguide ($x=0$) and solve for two modes. \n",
"\n",
"As expected, the first mode is TE0 mode and the second mode is the TM0 mode. Note that the grid looks a bit coarse. If a finer resolution for the mode profile is needed, either use a finer grid or use Tidy3D's [waveguide plugin](https://www.flexcompute.com/tidy3d/examples/notebooks/WaveguidePluginDemonstration/) for the same analysis. "
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "9a1b4c64",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
19:23:52 CEST WARNING: Use the remote mode solver with subpixel averaging for \n",
"better accuracy through 'tidy3d.web.run(...)' or the deprecated \n",
"'tidy3d.plugins.mode.web.run(...)'. \n",
"
\n"
],
"text/plain": [
"\u001b[2;36m19:23:52 CEST\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Use the remote mode solver with subpixel averaging for \u001b[0m\n",
"\u001b[2;36m \u001b[0m\u001b[31mbetter accuracy through \u001b[0m\u001b[32m'tidy3d.web.run\u001b[0m\u001b[32m(\u001b[0m\u001b[32m...\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m\u001b[31m or the deprecated \u001b[0m\n",
"\u001b[2;36m \u001b[0m\u001b[32m'tidy3d.plugins.mode.web.run\u001b[0m\u001b[32m(\u001b[0m\u001b[32m...\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m\u001b[31m. \u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mode_solver = mode_solver.copy(\n",
" update={\"plane\": td.Box(center=(L_blt + L_s, 0, t_si / 2), size=(0, 3 * w_3, 5 * t_si))}\n",
")\n",
"mode_data = mode_solver.solve()\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 3), tight_layout=True)\n",
"mode_data.intensity.sel(mode_index=0).plot(x=\"y\", y=\"z\", cmap=\"magma\", ax=ax1)\n",
"mode_data.intensity.sel(mode_index=1).plot(x=\"y\", y=\"z\", cmap=\"magma\", ax=ax2)\n",
"\n",
"mode_data.to_dataframe()"
]
},
{
"cell_type": "markdown",
"id": "891c6fc0",
"metadata": {},
"source": [
"Lastly, mode analysis at the end of the adiabatic coupler section shows the first mode as the TE0 at the top waveguide and the second mode as the TE0 at the bottom waveguide, which indicates that with an appropriate choice of coupling length and gap size, the TE1 mode on the top waveguide will be converted into the TE0 mode at the bottom waveguide. The TE0 mode launched in the input waveguide however stays as TE0 throughout the device. \n",
"\n",
"For a more detailed analysis, please refer to the [reference](https://doi.org/10.1364/OE.22.003777). "
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "55b0c905",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
\n",
"
\n",
"
wavelength
\n",
"
n eff
\n",
"
k eff
\n",
"
TE (Ey) fraction
\n",
"
wg TE fraction
\n",
"
wg TM fraction
\n",
"
mode area
\n",
"
\n",
"
\n",
"
f
\n",
"
mode_index
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
\n",
" \n",
" \n",
"
\n",
"
1.946704e+14
\n",
"
0
\n",
"
1.54
\n",
"
2.629170
\n",
"
0.0
\n",
"
0.992861
\n",
"
0.850431
\n",
"
0.815151
\n",
"
0.189577
\n",
"
\n",
"
\n",
"
1
\n",
"
1.54
\n",
"
2.481675
\n",
"
0.0
\n",
"
0.983950
\n",
"
0.776126
\n",
"
0.820265
\n",
"
0.187840
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" wavelength n eff k eff TE (Ey) fraction \\\n",
"f mode_index \n",
"1.946704e+14 0 1.54 2.629170 0.0 0.992861 \n",
" 1 1.54 2.481675 0.0 0.983950 \n",
"\n",
" wg TE fraction wg TM fraction mode area \n",
"f mode_index \n",
"1.946704e+14 0 0.850431 0.815151 0.189577 \n",
" 1 0.776126 0.820265 0.187840 "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mode_solver = mode_solver.copy(\n",
" update={\"plane\": td.Box(center=(L_blt + L_s + L_ac, 0, t_si / 2), size=(0, 5 * w_5, 5 * t_si))}\n",
")\n",
"mode_data = mode_solver.solve()\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 3), tight_layout=True)\n",
"mode_data.intensity.sel(mode_index=0).plot(x=\"y\", y=\"z\", cmap=\"magma\", ax=ax1)\n",
"mode_data.intensity.sel(mode_index=1).plot(x=\"y\", y=\"z\", cmap=\"magma\", ax=ax2)\n",
"\n",
"mode_data.to_dataframe()"
]
},
{
"cell_type": "markdown",
"id": "8d603044",
"metadata": {},
"source": [
"## Run a Batch Simulation "
]
},
{
"cell_type": "markdown",
"id": "ed81f5e5",
"metadata": {},
"source": [
"We also want to investigate the TM mode as input. To do so, we only need to define a new [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html) and set `mode_index=1`. Then a simulation is created by copying the previous simulation with the sources updated. To run both the TE and TM input simulations simultaneously, we made a simulation batch. "
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "56499f75",
"metadata": {
"execution": {
"iopub.execute_input": "2023-08-18T17:08:57.985486Z",
"iopub.status.busy": "2023-08-18T17:08:57.985342Z",
"iopub.status.idle": "2023-08-18T17:08:59.309346Z",
"shell.execute_reply": "2023-08-18T17:08:59.307367Z"
}
},
"outputs": [],
"source": [
"# define a new mode source that launches the tm mode\n",
"mode_source_tm = mode_source_te.copy(update={\"mode_index\": 1})\n",
"\n",
"# define a new simulation and update the source\n",
"sim_tm = sim_te.copy(update={\"sources\": [mode_source_tm]})\n",
"\n",
"# define a simulation batch\n",
"sims = {\n",
" \"TE input\": sim_te,\n",
" \"TM input\": sim_tm,\n",
"}\n",
"batch = web.Batch(simulations=sims)"
]
},
{
"cell_type": "markdown",
"id": "aed077f2",
"metadata": {},
"source": [
"Submit the simulation batch to the server."
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "29dde0cc",
"metadata": {
"execution": {
"iopub.execute_input": "2023-08-18T17:08:59.350785Z",
"iopub.status.busy": "2023-08-18T17:08:59.350621Z",
"shell.execute_reply": "2023-08-18T17:17:15.063215Z"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "9e06999f3e854db6a5e40c3ecf9a1bf3",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Output()"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n"
],
"text/plain": []
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"
19:23:56 CEST Started working on Batch containing 2 tasks. \n",
"
TE input: status = running ━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━ 57%-:--:--\nTM input: status = running ━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━ 57%-:--:--\n
![\"Schematic](\"img/bilevel_PSR.png\")
\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 [90 degree optical hybrid](https://www.flexcompute.com/tidy3d/examples/notebooks/90OpticalHybrid/), 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": "8d1a8953",
"metadata": {},
"outputs": [],
"source": [
"import gdstk\n",
"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"
]
},
{
"cell_type": "markdown",
"id": "413e6b41",
"metadata": {},
"source": [
"## Simulation Setup"
]
},
{
"cell_type": "markdown",
"id": "94b310dd",
"metadata": {},
"source": [
"The simulation wavelength range is from 1500 nm to 1580 nm."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "7f7d6cae",
"metadata": {},
"outputs": [],
"source": [
"lda0 = 1.54 # central wavelength\n",
"ldas = np.linspace(1.5, 1.58, 101) # wavelength range of interest\n",
"freq0 = td.C_0 / lda0 # central frequency\n",
"freqs = td.C_0 / ldas # frequency range of interest\n",
"fwidth = 0.4 * (np.max(freqs) - np.min(freqs)) # frequency width of the source"
]
},
{
"cell_type": "markdown",
"id": "c729fe1e",
"metadata": {},
"source": [
"In this wavelength range, silicon and silicon oxide have minimal dispersion. Therefore, we use a constant refractive index for both. "
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0da6e324",
"metadata": {},
"outputs": [],
"source": [
"# define silicon and silicon dioxide media from material library\n",
"si = td.Medium(permittivity=3.47**2)\n",
"sio2 = td.Medium(permittivity=1.44**2)"
]
},
{
"cell_type": "markdown",
"id": "3d3e4044",
"metadata": {},
"source": [
"Define geometric parameters. The parameters are indicated in the figure below. In addition, we add a side wall angle to mimic realistic fabrication and see if this will degrade the device performance. \n",
"\n",
"![\"Top](\"img/bilevel_PSR_2.png\")
"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "a6c80d2a",
"metadata": {},
"outputs": [],
"source": [
"L_blt = 100 # length of the bi-level taper\n",
"L_ac = 300 # length of the adiabatic coupler\n",
"L_s = 5 # length of the straight waveguide between the bi-level taper and the adiabatic coupler\n",
"L_t = 30 # length of the top waveguide taper after the adiabatic coupler\n",
"\n",
"w_1 = 0.45 # input waveguide width\n",
"w_2 = 0.55 # waveguide width at the center of the bi-level taper\n",
"w_pes = 1.55 # width of the widest part of the partially etched slab\n",
"w_3 = 0.85 # waveguide width at the output of the bi-level taper\n",
"w_4 = 0.2 # waveguide width at the beginning of the bottom waveguide\n",
"w_5 = 0.65 # top waveguide width at the end of the adiabatic coupler\n",
"w_6 = 0.5 # output waveguide width\n",
"gap = 0.2 # gap size of the adiabatic coupler\n",
"\n",
"t_pes = 0.09 # thickness of the partially etched slab\n",
"t_si = 0.22 # thickness of the silicon layer\n",
"\n",
"inf_eff = 1e5 # effective infinity\n",
"\n",
"sidewall_angle = 10 * np.pi / 180 # side wall angle"
]
},
{
"cell_type": "markdown",
"id": "c334bcd2",
"metadata": {},
"source": [
"Define the partially etched slab structure."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "e4af6ae6",
"metadata": {},
"outputs": [],
"source": [
"# define the partially etched slab\n",
"vertices = [\n",
" (0, w_1 / 2),\n",
" (L_blt / 2, w_pes / 2),\n",
" (L_blt, w_3 / 2),\n",
" (L_blt, -w_3 / 2),\n",
" (L_blt / 2, -w_pes / 2),\n",
" (0, -w_1 / 2),\n",
"]\n",
"\n",
"partially_etched_slab = td.Structure(\n",
" geometry=td.PolySlab(\n",
" vertices=vertices,\n",
" axis=2,\n",
" slab_bounds=(0, t_pes),\n",
" sidewall_angle=sidewall_angle,\n",
" ),\n",
" medium=si,\n",
")"
]
},
{
"cell_type": "markdown",
"id": "eb211d2d",
"metadata": {},
"source": [
"Define the waveguide structures using `gdstk`. For structures with bending parts, using `gdstk` is easy and convenient."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e9cdeabb",
"metadata": {},
"outputs": [],
"source": [
"R = 300 # bend radius\n",
"theta = np.pi / 30 # s bend angle\n",
"\n",
"# define a gds cell\n",
"cell = gdstk.Cell(\"device\")\n",
"\n",
"# define the top waveguide using a path\n",
"top_wg = gdstk.RobustPath((-inf_eff, 0), w_1, layer=1, datatype=0)\n",
"top_wg.horizontal(0)\n",
"top_wg.horizontal(L_blt / 2, w_2)\n",
"top_wg.horizontal(L_blt, w_3)\n",
"top_wg.horizontal(L_blt + L_s)\n",
"top_wg.segment((L_blt + L_s + L_ac, (w_5 - w_3) / 2), w_5)\n",
"top_wg.horizontal(L_blt + L_s + L_ac + L_t)\n",
"top_wg.arc(R, -np.pi / 2, -np.pi / 2 + theta)\n",
"top_wg.arc(R, np.pi / 2 + theta, np.pi / 2)\n",
"top_wg.horizontal(inf_eff)\n",
"cell.add(top_wg)\n",
"\n",
"# define the bottom waveguide using a path\n",
"bottom_wg = gdstk.RobustPath((L_blt + L_s, (-w_4 - w_3 - 2 * gap) / 2), w_4, layer=1, datatype=0)\n",
"bottom_wg.segment((L_blt + L_s + L_ac, (-w_3 - 2 * gap - w_6) / 2), w_6)\n",
"bottom_wg.arc(R, np.pi / 2, np.pi / 2 - theta)\n",
"bottom_wg.arc(R, -np.pi / 2 - theta, -np.pi / 2)\n",
"bottom_wg.horizontal(inf_eff)\n",
"cell.add(bottom_wg)\n",
"\n",
"# define the waveguide tidy3d geometries\n",
"wg_geos = td.PolySlab.from_gds(\n",
" cell,\n",
" gds_layer=1,\n",
" axis=2,\n",
" slab_bounds=(0, t_si),\n",
" sidewall_angle=sidewall_angle,\n",
")\n",
"\n",
"# define the waveguide tidy3d structures\n",
"wgs = [td.Structure(geometry=wg_geo, medium=si) for wg_geo in wg_geos]"
]
},
{
"cell_type": "markdown",
"id": "e61f0135",
"metadata": {},
"source": [
"Define source, monitors, and simulation. Here we will define a [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html) that launches the TE0 mode into the input waveguide. Two [ModeMonitors](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeMonitor.html) are added to the top and bottom waveguides to monitor the transmission. A [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html) is added in the $xy$ plane to visualize the field distribution."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "72a73176",
"metadata": {},
"outputs": [
{
"data": {
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ePXuwaNEijB07Ftdffz0A4Msvv8Sdd96Jq6++GgMHDoTD4cA777wDjUaDq666CgDw5JNP4uuvv8bEiRPRp08flJSUYNGiRejVq1erU1v4s90NN9yADz74ADNnzsS6detw7rnnwul0Yvfu3fjggw/w3//+F2PGjEH//v3xyCOP4KmnnsL555+PK6+8EgaDAT/88AOysrKwcOFCoOEf+jfeeANPP/00+vfvj/T0dM+gi8Z0Oh2ee+453HTTTRg/fjymTJnimdKkb9++uPfeezsdPwA455xzkJSUhOnTp+Puu++GJEl45513fCYWo0ePxvvvv485c+Zg7NixMJvNuOyyy3zu9+6770ZpaSkefPBBLFu2zGvdiBEjMGLECKCDz9T16tULs2fPxp/+9CfY7XaMHTsWK1aswIYNG7B06VKv25Lz5s3DP/7xDxQUFHjm1fvd736Hs88+GzfddBN27tzpeaOE0+nEE0884XWs8ePHIzc3F/3790dRURHefPNNVFVV4ZNPPmnzzR9GoxEXX3wxvvjiCzz55JPN1q9evRpTp07FBRdcgL179+LNN99EbGwsPv/8c4wdOxaXXnppu78bX+x2u2eeSKIuJ9zDb4m6k8OHD4tp06aJtLQ0YTAYxGmnnSZmzZol6uvrhWg0pYmvaU9EwxQmgwcPFjqdTmRkZIjbb79dlJeXe9YfPHhQ3HzzzaJfv37CaDSK5ORkcdFFF4kvvvjCU2bt2rXi8ssvF1lZWUKv14usrCwxZcoUsXfv3lbr7u92NptNPPfcc+L0008XBoNBJCUlidGjR4snnnhCWCwWr7J///vfxZlnnukpN378eLFmzRrP+qKiIjFx4kQRFxcnAHimN2k6pYnb+++/79lfcnKymDp1qjh27JhXmenTpwuTydTs/NzTYbTlm2++EWeffbaIiYkRWVlZ4sEHHxT//e9/m9WnqqpK/P73vxeJiYkCQKvTm4wfP77F6UkaT9nRUU6nUzzzzDOiT58+Qq/Xi9NPP13885//bFbOPd1LQUGB1/KysjIxY8YMkZKSImJjY8X48eN9XqP33nuvOO2004TBYBBpaWni97//vThw4IDf9fz3v/8tJEkSR44c8SxzT2nyzDPPiLy8PGEwGEROTo748MMPxcMPPyxiY2PFE088IUSjGDaddqelmI8fP16cfvrpXss+++wzAUDs27fP73oTRQq++5WIiCKC0+nE0KFDcc011+Cpp54CGt4okZOTg7fffhs33nhj0OswefJkSJLkub1L1JXwmToiIooIGo0GTz75JF5//XVUVVWF/Pi7du3CJ5984kkoiboaJnVERBQxrr32WpSVlfk9r10gDRkyBA6Hw+/5JIkiDZM6IiIioijAZ+qIiIiIogB76oiIiIiiQMQldYWFhbj++uuRkpKCmJgYDB8+vMXJKN2++uorjBo1CgaDAf3798eSJUualXn99dfRt29fGI1GjBs3Dt9//30Qz4KIiIgotCJq8uHy8nKce+65uOiii/DZZ58hLS0N+/bt8/kKHreCggJMnDgRM2fOxNKlS7F27Vr84Q9/QI8ePTyzqrsnAF28eDHGjRuHl19+Gfn5+dizZw/S09P9qpuiKDh+/Dji4uL4kmciIiJqkxAClZWVyMrKanMC7kCIqGfq5s6di2+++QYbNmzwe5uHHnoIq1at8nqn5nXXXYeKigqsXr0aADBu3DiMHTsWr732GtCQoGVnZ+Ouu+7C3Llz/TrOsWPH8Oqrr6K6uhpOp7Pd59YWvV7vCbiiKLDZbAE/Rlu0Wi20WjXPr6+vD8oreFojSZLXa4ccDkez116FAuPhwnioGA8V4+HCeKgYD5U7HrIsIzY2Fn/84x9x9OhR9OrVK+jHjqieuo8//hj5+fm4+uqrsX79evTs2RN33HEHbrnllha32bRpU7NX5+Tn52P27NlAw3sZt27dinnz5nnWy7KMvLw8bNq0qcX91tfXe71DUggBjUaDAX3TERejaXG7jrI5BCw1rndgJsTK0GtD3xuoCIFTla466LUSEmLDc3feUqPA5nD9zyAlToYchp5RxkPFeLgwHirGQ8V4uDAeKnc8hAAcDX1AcXFxITl2RCV1Bw8exBtvvIE5c+bg4Ycfxg8//IC7774ber0e06dP97lNUVERMjIyvJZlZGTAarWitrYW5eXlcDqdPsvs3r27xbosXLiw2XsN586dC51GRqwxsF+bza6gosaJGL2rEdTYgFiDDL0udI1CEQKnrE7otDIMWgl1dgGnIiEuNvAJbGsqa5xQhASzUUa9Q6DWJiElXhPShsl4qBgPF8ZDxXioGA8XxkPVOB5OBbA5XIluqB7biqiBEoqiYNSoUXjmmWdw5pln4tZbb8Utt9yCxYsXh7wu8+bNg8Vi8XyOHj0alOPY7ApOVjqh00hITdAiNUELnUbCyUonbHYlKMdsyt0g7U6B1DgNUuK1iI+RYa1VUFkT+FvNLamsccJaqyA+RkZKvBapcRrYna66KSHqxmc8VIyHC+OhYjxUjIcL46FqGo+kuNAmtYi0pK5Hjx4YOnSo17IhQ4bgyJEjLW6TmZmJ4uJir2XFxcWIj49HTEwMUlNTodFofJbJzMxscb8GgwHx8fFen0BrfAG4/5qQJdfPoWqYTRuk+6+7uFhNSBtm4wbp/utOr5ND2jAZDxXj4cJ4qBgPFePhwnioWoqHNsRZVkQldeeeey727NnjtWzv3r3o06dPi9vk5uZi7dq1XsvWrFmD3NxcoOGBxdGjR3uVURQFa9eu9ZQJB18XgFuoGmZLDdItVA3TV4N0C1XDZDxUjIcL46FiPFSMhwvjoWotHqF+pC+ikrp7770X3333HZ555hns378f7777Lt58803MmjXLU2bevHmYNm2a5/eZM2fi4MGDePDBB7F7924sWrQIH3zwAe69915PmTlz5uCvf/0r/vGPf2DXrl24/fbbUV1djZtuuink54g2LgC3YDfMthqkW7AbZmsN0i3YDZPxUDEeLoyHivFQMR4ujIfKn3iEUkQldWPHjsVHH32E9957D8OGDcNTTz2Fl19+GVOnTvWUOXHihNft2JycHKxatQpr1qzBGWecgRdeeAFvvfWWZ446NLwg+s9//jPmz5+PkSNH4scff8Tq1aubDZ4IhfZcAMFqmP42SLdgNUx/GqRbsBom46FiPFwYDxXjoWI8XBgPVaQldIi0eeoimdVqxcKFC9ErLRbJ8boO7aOjF0B7G1Gw9tWeRhSsfQWyETEend8X46FiPFwYDxXjoeqO8bA5BApP2vDIY4/DYrEE5dn8piKqpy7SybLc4ckUO3MxBeovrs427kD9xdWZxh2ov7gYDxXj4cJ4qBgPFePhwnioIrGHzo1JXTvV2ES7L4RAXACdbZiB+mutsw0zEH+tdbZhMh4qxsOF8VAxHirGw4XxUEVyQgcmde2jKAqcCtp1IQTyAuhowwxk9zs60TAD2f3e0YbJeKgYDxfGQ8V4qBgPF8ZDFekJHZjUtZ/JIPl9IQTjAmhvwwx0g3Rrb8MMZIN0a2/DZDxUjIcL46FiPFSMhwvjoeoKCR2Y1LWfRpb8uhCCeQH42zCD1SDd/G2YwWiQbv42TMZDxXi4MB4qxkPFeLgwHqquktCBSV3HtHUhhOICaKthBrtBurXVMIPZIN0YDxXj4cJ4qBgPFePhwnioIiEegcSkroNauhBCeQG01DBD1SDdWmqYoWiQboyHivFwYTxUjIeK8XBhPFSREI9AYVLXCU0vhPowXABNG2a9XQlpg3Rr2jBD2SDdGA8V4+HCeKgYDxXj4cJ4qCIhHoHApK6T3BeCzSFw0uqEVkbILwB3w9TKwEmrEzZHaBukW+OGGeoG6cZ4qBgPF8ZDxXioGA8XxkMVCfHoLCZ1RERERFGASV0nue+567USUuM1cLRzHrtAcD8D4VCA1HgN9NrgvMS5LY27zIP5EufWMB4qxsOF8VAxHirGw4XxUEVCPDqLSV0nNH2I0hCklwa3pulDrQadHJSXOLel6TMQwXqJc2sYDxXj4cJ4qBgPFePhwnioIiEegcCkroNaGhUTqHfL+aOlUUqBetefv1p6qDWUDZPxUDEeLoyHivFQMR4ujIcqEuIRKEzqOqCtYc6huBDaGnYeqobZ1iilUDRMxkPFeLgwHirGQ8V4uDAeqkiIRyAxqWsnpyL8GuYczAvB33mEgt0w/R12HsyG6e88QoyHivFwYTxUjIeK8XBhPFRdKbFjUtdO1fXC73lrgnEhtHdiyGA1zPbOIxSMhtneiSEZDxXj4cJ4qBgPFePhwnioukpix6SuHWRZhqad89YE8kLo6EzfgW6YHZ0YMpANs6MzfTMeKsbDhfFQMR4qxsOF8VB1hcSOSV07xeqldk9EGIgLobOvbglUw+zsTN+BaJidfXUL46FiPFwYDxXjoWI8XBgPVaQndkzq2kFRFEgdnFm6MxdCoN7F19mGGahXt3SmYQbqXXyMh4rxcGE8VIyHivFwYTxUkZzYMakLoY5cCIF+uXJHG2ag38XXkYYZ6JcrMx4qxsOF8VAxHirGw4XxUEVqYsekLsTacyEEukG6tbdhBuvlyu1pmIFukG6Mh4rxcGE8VIyHivFwYTxUkZjYMakLA38uhGA1SDd/G2awGqSbPw0zWA3SjfFQMR4ujIeK8VAxHi6MhyrSEjttWI/eBTkVwOYIQNAkCQkxMsqrnSipEEgyazzP6wkhUF7lhMMpkGTSAJIUmGP6EB8ro7zKiRKLA0kmDXSNGn91rRNVdQrMRhkGvRy0Ohj0MmKdAhXVrnM2xaiN325XUF7thFYjIT5WhsMJAEGoB+PhwXioGI8GjIcH46FiPBq0EA+7Q0AJcY7HpK4dnE4nFAHU2QI3CaPZqIHNocBao0CvdTVKm0NAllzrnAJwBvB4vsQ0NLjqegV6JyDLgMMpYHcKmIwyNBopoOfsi0YjwWSUYXMKiFpXI1QUwOZQYNDJ0Gsl1NtFcBpkI4yHC+OhYjxUjIcL46FiPFRN4+FUmNRFtBMnTuCKc1MxqLc53FUhIiKiCGapduLfG8tCekwmde3gdDphNspIjuPXRkRERK0z6EM7dIEDJYiIiIiCwBHY19W2iUkdERERURCIEI+GZVJHREREFATuASyhwqSOiIiIKAgCPC1em5jUEREREUUBJnVEREREUYBJHREREVEUYFJHREREFAWY1BERERFFASZ1RERERFGASR0RERFRFGBSR0RERBQFmNQRERERRQEmdURERERRgEkdERERURRgUkdEREQUBZjUEREREUUBJnVEREREUYBJHREREVEUYFJHREREFAWY1BERERFFgYhO6p599llIkoTZs2e3Wm758uUYPHgwjEYjhg8fjk8//dRrvRAC8+fPR48ePRATE4O8vDzs27cvyLUnIiIiCp2ITep++OEH/OUvf8GIESNaLfftt99iypQpmDFjBrZv347Jkydj8uTJ2LFjh6fM888/j1dffRWLFy/G5s2bYTKZkJ+fj7q6uhCcCREREVHwRWRSV1VVhalTp+Kvf/0rkpKSWi37yiuv4JJLLsEDDzyAIUOG4KmnnsKoUaPw2muvAQ29dC+//DIeffRRXH755RgxYgT+3//7fzh+/DhWrFgRojMiIiKiqOeoBkq+dn1O/QA4q0N6+IhM6mbNmoWJEyciLy+vzbKbNm1qVi4/Px+bNm0CABQUFKCoqMirTEJCAsaNG+cpQ0RERNTVacNdgaaWLVuGbdu24YcffvCrfFFRETIyMryWZWRkoKioyLPevaylMr7U19ejvr7e87vVam3XeRARERGFUkT11B09ehT33HMPli5dCqPRGNa6LFy4EAkJCZ5PdnZ2WOtDRERE1JqISuq2bt2KkpISjBo1ClqtFlqtFuvXr8err74KrVYLp9PZbJvMzEwUFxd7LSsuLkZmZqZnvXtZS2V8mTdvHiwWi+dz9OjRAJ0lERERUeBFVFI3YcIE/PLLL/jxxx89nzFjxmDq1Kn48ccfodFomm2Tm5uLtWvXei1bs2YNcnNzAQA5OTnIzMz0KmO1WrF582ZPGV8MBgPi4+O9PkRERESRKqKeqYuLi8OwYcO8lplMJqSkpHiWT5s2DT179sTChQsBAPfccw/Gjx+PF154ARMnTsSyZcuwZcsWvPnmmwDgmefu6aefxoABA5CTk4PHHnsMWVlZmDx5chjOkoiIiCjwIiqp88eRI0cgy2oH4znnnIN3330Xjz76KB5++GEMGDAAK1as8EoOH3zwQVRXV+PWW29FRUUFzjvvPKxevTrsz+0RERFR9HI4pZAeTxJCiJAesYuyWq2YOXMm5k0fheH9eCuWiIiImnBUA2VbAQBlNTr844cszHn4GVgslpA8xhVRz9QRERERRQuNrIT0eEzqiIiIiKIAkzoiIiKiIHAqoU2zmNQRERERBQFvvxIRERFFAa0mtGNRmdQRERERRQEmdURERERRgEkdERERURTocm+UICIiIgoHa60NpdYalFfXo6K6DhW19VAU9bk5HeqQjWIAQLXdCLsjLaT1Y1JHRERE1Iqaejt+OlKKgyWWVstJEHBKriRPUQRC/couJnVERERETYiqWjgKjuGArMOPFXVwhjxFaz8mdURERERN1BaWQvlxP3oAMBoNOBwXhxOmWDjlyB2OwKSOiIiIqJHy6jrsOVKKYUJAkWWk1tYhtbYOtVoNjprNOBpnRpVeH+5qNsOkjoiIiKhBqbUWX+08igyn620QDlmGQ5YhCQGDU8HACgv6Wa0oNRpxJC4OxaZYKJIU7moDTOqIiIiIXE6UV2P97mNwKs1f7yUkCfUaDSAEtEIgs6YWGTW1qNFpcSQuDsfMJjh0Yam2B5M6IiIi6vastTZs2OM7ofMiSXBIEhyyDFkIxNodGFJWjgEVFpTG6mGPl1FpVGCqlaGzh6r2LkzqiIiIqFuzOxV8vfsY7M42EromFElCnVYLCAGdoiCrsgbaSh0gJJRLOmzTBK3KPjGpIyIiom5LCIEfDhTBUlPf8Z1IEuyyDEBA71AgAZAFIEKcZTGpIyIiom5rf3EFCkpbn1S4VQ29dFohICSgKkZBvV6gtl6B5AxkTdvGpI6IiIi6pVNVtdhysLhD28pCQO90QgJgl2UcMZtwIs4Ac8xhQAJqbBrYSgJe5VYxqSMiIqJux6ko+HbvcSiiHW+KaNorp9PhSLxr5GudVgs96mF2z24iAUqI5ylmUkdERETdzu7jZbDW2vwqKwsBndMJGYBDlnA8NhZH4uNQEhMDESFz1IFJHREREXU31fV27Dh6qs1yEoAYhwMCQK1WiyNxrrdJ1OjCPCFdC5jUERERUbey7VAJHG3MR+eQJdhkGWVGA47ExaEoNhaKHDm9cr4wqSMiIqJu40RFNY6ctLZZrig2Fl9m93TNQ9dFhPgRPiIiIqLwcCoKthws8quscE8s3IUwqSMiIqJuYe+Jcr8HR3RFXSsFJSIiIuoAm8Pp1+CItsQZ9UgyGZFkMiAh1gBNo+fsJGctYqpKAQAVtXr8WhbavjMmdURERBT19p0oh83Z8Vc89MtIxIjeqYjVtzLy1SEBigEAoECHUI+rYFJHREREUc3uVLDrRFmHts1MNGFU33QkmYwBr1egMakjIiKiqLa/qAL19vb10mkkGbkDe6BPanzQ6hVoTOqIiIgoajmcCnYWtu9ZOp1GxvghvZCRYOrUsYUI7f1XJnVEREQUtfYXV6DO7vC7vEGnwUVDs5Fijun0sW1ODpQgIiIi6jSHomBnof/P0pn0OvxmWG/Ex+gDcnwJIiD78RfnqSMiIqKoVFBiQa3N7ldZnUbGRcOyA5bQAYBWZlJHRERE1CmKEO3qpRvXvwcSYgwBrYNdCW2axaSOiIiIok5RRTWq6vx7e8SgrOSgjHLl7VciIiKiTtpXVO5XudS4GIzqkxaUOug1SlD22xImdURERBRVquvsOFZW1WY5g06D8wb1hCwHKR0K8RslmNQRERFRVNlfXOFXubP7Z8FkaOW1X10MkzoiIiKKGk5F8Sup65lsRq9kc0jqFCpM6oiIiChqHD1V1eZkwxpJxuicjJDVKVSY1BEREVHU8GeAxNBeyYgzBm4+ukjBpI6IiIiiQkV1HUqsNa2WMRl0GNozJWR1CiW+JoyIiIiiwr6itp+lG3NaBrSaIPVpaU1A+gWunysdgOZUcI7TAvbUERERUZfnUBQUlFpbLZOVZEav5LiQ1SnUmNQRERFRl3eirAp2p7PVMmcGaZLhSMGkjoiIiLq8tnrpeqfEI9FkDFl9wiHikrqFCxdi7NixiIuLQ3p6OiZPnow9e/a0ud3y5csxePBgGI1GDB8+HJ9++qnXeiEE5s+fjx49eiAmJgZ5eXnYt29fEM+EiIiIQqHe7kRheetvkBiWHZ2DIxqLuKRu/fr1mDVrFr777jusWbMGdrsdF198Maqrq1vc5ttvv8WUKVMwY8YMbN++HZMnT8bkyZOxY8cOT5nnn38er776KhYvXozNmzfDZDIhPz8fdXV1ITozIiIiCoYjp6xQhGhxfa9kM5KivJcOACQhWvkWIkBpaSnS09Oxfv16XHDBBT7LXHvttaiursYnn3ziWXb22Wdj5MiRWLx4MYQQyMrKwn333Yf7778fAGCxWJCRkYElS5bguuuua7MeVqsVM2fOxLzpozC8X3wAz5CIiIg6Y80vh1udyuSSM/oixRwT0jqVVTqw7KtTmDVnPiwWC+Ljg587RFxPXVMWiwUAkJyc3GKZTZs2IS8vz2tZfn4+Nm3aBAAoKChAUVGRV5mEhASMGzfOU6ap+vp6WK1Wrw8RERFFluo6e6sJXVaSOeQJXbhEdFKnKApmz56Nc889F8OGDWuxXFFRETIyvF/3kZGRgaKiIs9697KWyjS1cOFCJCQkeD7Z2dkBOCMiIiIKpEMnLa2uP71X9D9L5xbRSd2sWbOwY8cOLFu2LOTHnjdvHiwWi+dz9OjRkNeBiIiIWneotLLFdRkJJqTHx4a0PuEUsW+UuPPOO/HJJ5/g66+/Rq9evVotm5mZieLiYq9lxcXFyMzM9Kx3L+vRo4dXmZEjR/rcp8FggMFgCMCZEBERUTCUV9ehoqblAY+n92z50a1oFHE9dUII3Hnnnfjoo4/w5ZdfIicnp81tcnNzsXbtWq9la9asQW5uLgAgJycHmZmZXmWsVis2b97sKUNERERdS0Fpy7de42P0yEw0hbQ+4RZxPXWzZs3Cu+++i5UrVyIuLs7zzFtCQgJiYlwPOk6bNg09e/bEwoULAQD33HMPxo8fjxdeeAETJ07EsmXLsGXLFrz55psAAEmSMHv2bDz99NMYMGAAcnJy8NhjjyErKwuTJ08O49kSERFRRyhC4HArt14HZCZBkqSQ1incIi6pe+ONNwAAF154odfyt99+GzfeeCMA4MiRI5BltZPxnHPOwbvvvotHH30UDz/8MAYMGIAVK1Z4Da548MEHUV1djVtvvRUVFRU477zzsHr1ahiN0T9vDRERUbQpsdagxmb3uU4jychJSwh5ncIt4pI6f6bN++qrr5otu/rqq3H11Ve3uI0kSXjyySfx5JNPdrqOREREFF6HSlq+9do3PR4GnSak9YkEEfdMHREREVFrHE4FR061dus1MaT1iRRM6oiIiKhLKSyvgt2p+FyXYo7pNpMNN8WkjoiIiLqUQ6Utv+VpQGZSSOsSSZjUERERUZdRb3fieHmVz3V6rQZ9UuNCXqdIwaSOiIiIuowjp6xQWhhU2S89AVpN901tuu+ZExERUZdT0Mqt19MyuucACTcmdURERNQlVNXZUGqt8bku2WREYmxkvd7T5gjt8ZjUERERUZfQ2gCJvhE42bA/c+8GEpM6IiIiinhCiFbf9donLfIGSOi0oX1NGZM6IiIiingl1hpYa20+12UmmhCr14W8Tm1xOEN7PCZ1REREFPH2FlW0uC4nNfJuvYK3X4mIiIi81djsOHrS92vBNJKM7FRzyOvkDz1vvxIRERGpDhRbIOC716tXihk6jSbkdfKHFNqcjkkdERERRS5FUbC/lVuvkTjqNVyY1BEREVHEKiyvRo3N7nOdQadBVmJsyOsUqZjUERERUcTae6K8xXV9UuIhy0xl3PhNEBERUUSy1tpQZKlucT1vvXpjUkdEREQRaV9Ry710ZqMeqXHGkNYn0jGpIyIioohjczhxoLjlN0j0TYuHFOrhpRGOSR0RERFFnL0nymF3tvxKhhzeem2GSR0RERFFFLvTiV3Hy1pcn2yOQXyMPqR16gqY1BEREVFE2VdUAVsrL07NSYsPaX26CiZ1REREFDEcTgW7Ck+1uF6ChD6pcSGtU1fBpI6IiIgixv7iCtTZW+6ly0w0IUavC2mdugomdURERBQRHE4FOwtbfpYODaNeyTcmdURERBQRDpZYUNvCK8EAQCPLyE4xh7ROXYk23BXoimqdtdhVu8tr2ZCYIYjRxIStTkRERF2Zw6ng12MtP0sHANkpcdBpNCGrU1fDnjoiIiIKu18LT6GmlV46cNRrm5jUERERUVhV1tqw81jrz9KZDDpkJphCVqeuiLdfCQBQZ3eisKwKdQ4Hkk1GJJuMMOjYxU1ERMG3taAYilBaLTMgMwmyzNeCtYZJXTdWWWfDsbIqHDtViRJrTbP1ZqPeleCZDUg2xSDZzESPiIgC61hZFQrLq1otI0sy+mXwtWBtYVLXjQghUF5dj2NllThWVoXy6rpWy1fV2VBVZ8ORRs+tmgw6pJhjkGQyINlsRLI5BkYmekRE1AEOp4KtBcVtluudGgejjilLW/gNRTlFUVBaWYujp6pwrKwS1fWtP4Talup6O6rr7c0SPVePXsPHZIRRz0uLiIhat+t4GarqbG2WG5iZFJL6dHX8lzcKOZwKTlRU4+ipShSWV7X6/rxAcCd6R8sqPcti9TqvJC/ZbEQMEz0iImpQXl2HX4+2PoUJACSZjEiNM4akTl0d/5WNEnV2BwrLXL1xJ8pr4GzjgdNgq7HZUVNmx7FGiV6MXtfwfJ7rtm2y2YBYvuqFiKjbsTmc2LC70K9/qwZkJkKSOEDCH0zqurDKOhuONdxW9TXQIdLU2uwoLLOjsEx9IDZGr0Oy5/k814eJHhFR9BJC4Lt9J1Dpx21XnUZG3zQOkPAXk7ouxD3Q4WhZJY6dqkJFTesDHbqCWpsdhTa718gno07rleSlmFy3bvmXGhFR17f7eLnX4zqtyUlPgE7DKXX9xaQuwimKgpLKWhw75UrkqtuYbTsa1NkdOF5eheO+Ej2T+pxerIGJHhFRV1JiqcH2QyV+lx/YgwMk2oNJXQSyOxUUlVfhaMPcPcEe6NAV+Er0DDqNa/4891x6ZiNMBh0TPSKiCFRZa8PGvcchIPwq3zs1HgkxhqDXK5owqYsQdTYHCsurcPRUJYoqwj/QoSuotztxoqIKJyrURE8jy4jVa6HXamDQaaDXNp9DTwIgyxIkSYIsAbIkeT5Sw++S3LCsoaxrnau8JEmuZWgoIzcsa7yPRusl2fsY7n0w+SSi7qK8ug7rfj2KWrvD722G9UoJap1CwRHif8qZ1IVRZa3rjQ5HyypR2gUGOnQFTkXx6+HbSCD5SAqbJZpyQ5KIRolmo/XNEs3GvzdJVD2JbLNEtXkiykSViAKl1FqLr3Yehc3p/12n7OQ4JJm6/jQmTqd/vZKBwqQuhIQQKKuua3g1V3QMdKCOExBwCoF2/H8u4vlKVL0Sy8aJquSdWMpNe0ndvzf9uVEvqlrWO3mV0SgR9dqH7KobGn6X5UZ1ca1v/DsTVaLOOVFehfW7C+FU2tdldXp21++lAwCNJrT//2BSF2SKoqDYWut6NdepKtR0g4EO1H1FY6LarEe0UXLaeFmgelmb9aA2JKJyQyIqyXKj43qvlxoSVV/r1YSbSSoFn93pxM7CMuw8dgqKaF9vVVaSGSnmmKDVLZoxqQsCu1PBifIq10uKy6ra1eVMRJFFEQIQAtHUir16SD0Jozv5bJK8Nv7dZy9ro9/d26Npoqr2gHolqr4S3CbrXc/Ays0SXiaqkUlRBA6UVODnIydR147n5xob3is14PUKF95+7aLq7E4UnqzAMQ50IKII55WoRkm26pUg+khUm95a976d7+vWe0Mi6elxbZRoNk54PY8D+P8sqtcjB57HBZonzV1Fnc2B8up6VNTU4WCJtVOPFmUmmJAaHz29dBF/+7WgoAAbNmzA4cOHUVNTg7S0NJx55pnIzc2F0dj1H2psy9ZDJThc5US53vW+OqdQYLMr2FGtgUbow109IqJuSRFCvc0XNYmq2kPpShh93FqXADT0aIaaAFBrc6A2gI8VDc+Onl46ANCGeN5kv5O6pUuX4pVXXsGWLVuQkZGBrKwsxMTEoKysDAcOHIDRaMTUqVPx0EMPoU+fPsGtdRhV1tkgV9tRI/hsHBERBY8iFCjuu3fR1K3agj6p8UhPiA13Nbo0v3LIM888E6+++ipuvPFGHD58GCdOnMDWrVuxceNG7Ny5E1arFStXroSiKBgzZgyWL1/eqUq9/vrr6Nu3L4xGI8aNG4fvv/++1fLLly/H4MGDYTQaMXz4cHz66ade64UQmD9/Pnr06IGYmBjk5eVh3759naojERERBYZWljGqb3q4q9Hl+ZXUPfvss9i8eTPuuOMOZGdnN1tvMBhw4YUXYvHixdi9ezdOO+20Dlfo/fffx5w5c7BgwQJs27YNZ5xxBvLz81FS4vu1It9++y2mTJmCGTNmYPv27Zg8eTImT56MHTt2eMo8//zzePXVV7F48WJs3rwZJpMJ+fn5qKtr533/LvSMAxERUVcxrHcqYg26cFejy5OEaOdY4yAbN24cxo4di9deew1omBIkOzsbd911F+bOndus/LXXXovq6mp88sknnmVnn302Ro4cicWLF0MIgaysLNx33324//77AQAWiwUZGRlYsmQJrrvuOr/qZbVaMfPxhyCbazAsS4vE1FNe62NrevKZOiIionaKj9HjtyNzoJFD/ABakJVVOrDsq1OYNWc+LBYL4uPjg37MDn+DJSUl2LFjB37++WevT2fYbDZs3boVeXl5agVlGXl5edi0aZPPbTZt2uRVHgDy8/M95QsKClBUVORVJiEhAePGjWtxny2SJfxsqcQLOwrwt58q8XOJDXYlonJiIiKiLmVMTmbUJXTh0u7Rr1u3bsX06dOxa9cuuDv5JEmCEAKSJMHZiTnZTp48CafTiYyMDK/lGRkZ2L17t89tioqKfJYvKiryrHcva6mML/X19aivr/f8brVaAUWBSauBVkjYW2bHvnI7kowaTBlqwmBODkNERNQuvVPi0SPJFO5qRI12p8Y333wzBg4ciG+//RYHDx5EQUGB13+jxcKFC5GQkOD5uJ8lFABsioAAoJMlZJg0MOn4rB0REVF76DUaDo4IsHb3Lx08eBD/+te/0L9//4BXJjU1FRqNBsXFxV7Li4uLkZmZ6XObzMzMVsu7/1tcXIwePXp4lRk5cmSLdZk3bx7mzJnj+d1qteLBV55Bjd2JOK0GZ2ZpcWaGAekmjatATUfOmIiIqHs6Z2AWTEYOjgikdvfUTZgwAT/99FNQKqPX6zF69GisXbvWs0xRFKxduxa5ubk+t8nNzfUqDwBr1qzxlM/JyUFmZqZXGavVis2bN7e4TzSM6I2Pj/f6oN6Bi9JS8MgZ/ZF/Wqya0BEREZHfTu+Vip7J5nBXI+q0u6furbfewvTp07Fjxw4MGzYMOp13lj1p0qROVWjOnDmYPn06xowZg7POOgsvv/wyqqurcdNNNwEApk2bhp49e2LhwoUAgHvuuQfjx4/HCy+8gIkTJ2LZsmXYsmUL3nzzTaDheb/Zs2fj6aefxoABA5CTk4PHHnsMWVlZmDx5cvsqd7IK/fulw6Cxs2OOiIioAzISTBgRZW+OiBTtTuo2bdqEb775Bp999lmzdZ0dKIGGKUpKS0sxf/58FBUVYeTIkVi9erVnoMORI0cgNxolc8455+Ddd9/Fo48+iocffhgDBgzAihUrMGzYME+ZBx98ENXV1bj11ltRUVGB8847D6tXr+4WrzUjIiKKFDF6Hc4dmAVZ5rPowdDueer69u2LSy+9FI899lizEaXRzGq1YubMmcgdl46EJDtqYgu91nOeOiIiopZpJBm/GZaN9Pju8SqwcMxT1+6eulOnTuHee+/tVgldY1mJJmRmAMVyOQDA4VRQa3NAWydDRPdr+YiIiDpEp5ExfkivbpPQhUu7k7orr7wS69atQ79+/YJTowg3MDMJ/fvqsKvW+40Sg2P6o75WwtGyShwrq0J5dTtfQUZERBSFDDoNLhqajRRzTLirEvXandQNHDgQ8+bNw8aNGzF8+PBmAyXuvvvuQNavy5AAJJmNSDIbMaJ3GqrqbDhWVoVjZVUosdTANbMdERFR9xGr12HCsN6Ij+HjSaHQodGvZrMZ69evx/r1673WSZLUbZO6psxGPQZnJWNwVjLq7E4cL6vCsbJKHC+vhlMo4a4eERFRUGUmmHB2/x6ciy6E2p3UFRQUBKcmUcyo0+C0jASclpEAh1PBCUs1jp2qRGF5FertfBCPiIiiR0KMAaNy0pGVxHnoQi1gbyw9ceIE3nnnHTz44IOB2mVU0mpkZCfHITs5DooiUFpZg2NlVTh6qhLV9fZwV4+IiKjdtLKMRJMBp6UnoF96gtfUYxQ67U7qbr75Zp/LDx8+jO+//55JXTvIsoSMBBMyEkwY1TcdFTX1ngSPAy3aT6/VID5GD7NBB6NeC4NWA42G/2MhIgqWWL0WSSYjzEYdZIlzz4Vbu5O68vJyr9+dTicOHjyIXbt2YdGiRYGsW7ciSRKSTEYkmYwYnp2K6jq7ZyQtB1o0Z9RpkWw2uj4m1yfWoIXE/6kQEVE31e6k7qOPPvK5/I9//CNWrFiB2267LRD16vZMRp1noEW93YnC8kYDLZTuNdDCK4EzG5FiMiJGzwSOiIiosYA9UzdlyhQ8/fTTgdodNWLQaXBaegJOS3cNtCiy1OBYWSWOlVVG3UCLGL0OySZDQwIXg2SzAbF6jpwiIiJqS8CSup9++glnnnlmoHZHLdBqZPRKNqNXshmKkomTlbU4VlaJo2VVqKqzhbt67RKr1yHZbHAlbyYjkpjAERERdVi7k7o5c+Y0W1ZcXIyVK1di4sSJXutffPHFzteQWiTLEtITYpGeEIszGw20OHaqEmURNtDCpNchuWFy5mST6zZqjD5gf1MQERF1e+3+V3X79u0+l48dOxYlJSUoKSkBGh78p9DxNdDiWMNAi+IQD7QwGXSexM09kMEYIQlcibUGX+8+Fu5qEBEFjFGrRZLZiESTAcmxBqTFx0LLkf/dUrv/pV23bl1wakIBZTLqMCgrGYMaBlocr6jCsVNVOF5eBUcAB1qYDDqkmGM8z8ElmWNg1GkCtv9AE0JE3XOIRNS91dudsNTWA6Wu32P1OpzRJw190+I5zUg3ExndJxRUBp0GOWkJyEnzHmhRWFaJunYkOGaj3msKkWSzEYYITuCIiLqjGpsdm/Ydx+7jZRidk46MBFO4q9RtiRDPRuZXUnfJJZfg8ccfx9lnn91qucrKSixatAhmsxmzZs0KVB0pgJoNtKhqGGhxynugRZxR73r+rVESxwSOiKjrKK+uwxc7jmBIVjLO7JvOx6LCwOYIbVbnV1J39dVX46qrrkJCQgIuu+wyjBkzBllZWTAajSgvL8fOnTuxceNGfPrpp5g4cSL+9Kc/Bb/m1GmyLCE9Phbp8bE4s086LDX1qHc4kWQyQq9lAkdEFA12HS+DzeHEWf0y+fquEAt1Iu1XUjdjxgxcf/31WL58Od5//328+eabsFgsQEOFhw4divz8fPzwww8YMmRIsOtMQSBJEhJNxnBXg4iIguBAiQU2h4JzBmVBy8QuZELdP+L3M3UGgwHXX389rr/+egCAxWJBbW0tUlJSoNNxbjHqGlLMMZh45mlQFAGnIqAIBU5FwClEo2UCTqcCRQBORXH93qiMojTfxrNOCDgb1isNy90/81VvRBROR8sqsX7nMVwwpBd0HB0bEvZIvP3qS0JCAhISEgJbG6Ig02pkJMYawnJsNekTcArFk/QpTnfyp0BRoP7cLGlsSCYb9tM0afTss1FC6VWm8fpQP71LRBGhyFKNzftP4NyBWXzGLgQi8vYreYvRxGCUeVS4q0FdjCxLkCE1dMeH95lFpUnPYtNk0tkoOVQUpWEdfPdsNqxv2mvp9Np/0x5Nd4Lq2icRhc7hk1akxcVgUFZyuKsS9UI9RSuTOqJuSJYkyBr3X5DhTTCFUHswvXsf3ckimvdCNu3t9EomFa8EtGlvpWsZ1GSzSW8nUXew7VAJUswxSI2PCXdVKICY1BFRWEmSBI0kIRIe8RFCQAih9kz6eH6yI89hNk4g23wOs9E6PodJwaIIgQ17CvG/I/vCqGMqEC0YSSKiBpIkQZIkyAB0kXCbXFHgFGjxmUk1WYTv5zCdSqNeyib/dfdq+rpdLtBwe1zxJJ58DjP61Njs+HbvcVw4JBuyzOfrokG7k7rp06djxowZuOCCC4JTIyIiAgDIsgwZ7twyMp7DbHzr290z2Wxwjs/eSnePZqPb4F5lfI8aV2+vc6BPMJyoqMbeonIM5vN1UaHdSZ3FYkFeXh769OmDm266CdOnT0fPnj2DUzsiIooI7ucwI2Ggj/sWuc+eS9E0gfR+ZtJr9LhXstikt9PXs51R+hzmz0dK0Sc1DjF6Tk/W1bU7qVuxYgVKS0vxzjvv4B//+AcWLFiAvLw8zJgxA5dffjnnrCMioqCSJAlaSQIi7jnMRslio9vYvp7DVG9tw/s2eAeew6yzOzv1/KXdqWD7oVKcMzAroN8NhV6HnqlLS0vDnDlzMGfOHGzbtg1vv/02brjhBpjNZlx//fW44447MGDAgMDXloiIKII0fw4z9ByKAmuNDeXVdSivrsfRU5WosdnbtY+CUgv6ZyYiPT42aPWk4OvU3zknTpzAmjVrsGbNGmg0Gvz2t7/FL7/8gqFDh+Kll14KXC2JiIjIJ60sI9lsRL+MRIw5LQOXjToNZ/ROa/frwLYcLIai8HnFrqzdSZ3dbse//vUvXHrppejTpw+WL1+O2bNn4/jx4/jHP/6BL774Ah988AGefPLJ4NSYiIiIWqTVyBiWnYpJo09D/8wkv7crr67D/uKKoNaNgqvdt1979OgBRVEwZcoUfP/99xg5cmSzMhdddBESExMDVUciIiJqpxi9DuP6ZSIrIRYb9x73a9Twj4dL0TslDsZQvwqBAqLdUXvppZdw9dVXw2g0tlgmMTERBQUFna0bERERdVJ2ajwu1Grw9a5jcCitj9a1O53YWXgKo3IyQlY/Cpx233694YYbWk3oiIiIKLL0SDRhwrDe0GvbHs2xt6gCdTZHSOpFgRUBA8KJiIgo2FLjYvA/w3rD2MYwXaeiYNfxspDViwKHSR0REVE3kWgy4rxBbb8wYF9ROertzpDUiQKHSR0REVE3kpFgwsg+aa2WsTsV7DnB3rquhkkdERFRNzOkZwp6JptbLbP7eDlsDvbWdSVM6oiIiLoZWZKQ2z8LJkPLr/a0O53Ye6I8pPWizmFSR0RE1A0ZdBpcMLgXZKnlVGDX8TLYneyt6yqY1BEREXVTyWYjhmWntLje5nDiQLElpHWijmNSR0RE1I0NyUqG2ahvcf2+onIIP95GQeHHpI6IiKgb02pkjG7lDRLWWhuKrTUhrRN1DJM6IiKibq5Xshk9k1oeDbvvREVI60Mdw6SOiIiIMDono8VBE0dPVaLGZg95nah9mNQRERER4mL0OL1Xss91AgL7i9hbF+mY1BEREREAYGjPlBbnrttfbIGiKCGvE/mPSR0REREBDYMmTu/le4qTWpsdhWVVIa8T+Y9JHREREXmclp6AWL3v3rq9vAUb0SImqbPb7XjooYcwfPhwmEwmZGVlYdq0aTh+/Hib277++uvo27cvjEYjxo0bh++//95rfV1dHWbNmoWUlBSYzWZcddVVKC4uDuLZEBERdU0aWcbQnr6frSuyVMNSWx/yOnVVNkdojxcxSV1NTQ22bduGxx57DNu2bcO///1v7NmzB5MmTWp1u/fffx9z5szBggULsG3bNpxxxhnIz89HSUmJp8y9996L//znP1i+fDnWr1+P48eP48orrwzBWREREXU9/TISEaPT+lx3kG+Y8FuoJ22WRARPE/3DDz/grLPOwuHDh9G7d2+fZcaNG4exY8fitddeAwAoioLs7GzcddddmDt3LiwWC9LS0vDuu+/id7/7HQBg9+7dGDJkCDZt2oSzzz7br7pYrVbMnDkT86aPwvB+8QE8SyIiosizq7AM2w41v6tl0uswaUw/yJIUlnp1FWWVDry77hTuum8+LBYL4uODnztETE+dLxaLBZIkITEx0ed6m82GrVu3Ii8vz7NMlmXk5eVh06ZNAICtW7fCbrd7lRk8eDB69+7tKeNLfX09rFar14eIiKi7GJCZCINO02x5tc2OUr5hwi8OZ2iPF7FJXV1dHR566CFMmTKlxez25MmTcDqdyMjwfr1JRkYGioqKAABFRUXQ6/XNEsPGZXxZuHAhEhISPJ/s7OyAnBcREVFXoNXIGJLl+9m6Q6Xs6PBHqG+Ghi2pW7p0Kcxms+ezYcMGzzq73Y5rrrkGQgi88cYbYanfvHnzYLFYPJ+jR4+GpR5EREThMrBHEvTa5r11h09WwsE569qk14b2FrXvpyBDYNKkSRg3bpzn9549ewKNErrDhw/jyy+/bPUedGpqKjQaTbORrMXFxcjMzAQAZGZmwmazoaKiwqu3rnEZXwwGAwwGQ6fOkYiIqCvTaTTon5GInYWnvJbbnU6cKK9Gdkpc2OrWFYT6scOw9dTFxcWhf//+nk9MTIwnodu3bx+++OILpKT4ngDRTa/XY/To0Vi7dq1nmaIoWLt2LXJzcwEAo0ePhk6n8yqzZ88eHDlyxFOGiIiIfBuQ6fu59oJSjoKNNGHrqWvKbrfjd7/7HbZt24ZPPvkETqfT88xbcnIy9Ho9AGDChAm44oorcOeddwIA5syZg+nTp2PMmDE466yz8PLLL6O6uho33XQTACAhIQEzZszAnDlzkJycjPj4eNx1113Izc31e+QrERFRd2U26pGVZMbxcu+3SRSWVaHe7vQ5mILCI2KSusLCQnz88ccAgJEjR3qtW7duHS688EIAwIEDB3Dy5EnPumuvvRalpaWYP38+ioqKMHLkSKxevdpr8MRLL70EWZZx1VVXob6+Hvn5+Vi0aFHIzo2IiKgrG5iZ1CypU4TA0bJK9M/w3ZNHoRfR89RFEs5TR0RE3ZWiCHy87QCq6+1eyzPiY5E3vE/Y6hXJyiodWPbVKcyaw3nqiIiIKELIsoQBmUnNlhdba1BdZ/e5DYUekzoiIiJqU7/0BJ9vkTh0kgMmIgWTOiIiImqTUa9F79TmtxAPlVaGpT7UHJM6IiIi8stAH7dgK2rqUF5dF5b6kDcmdUREROSX1DgjkkzGZsv52rDIwKSOiIiI/CJJEnLSEpotP1RqhcLJNMKOSR0RERH5rU9a81eD1djsKLXWhKU+pGJSR0RERH6L1euQmWBqtryAt2DDjkkdERERtYuvW7BHTlbC4VTCUh9yYVJHRERE7ZKdaoZG8k4h7E4nCpu8SoxCi0kdERERtYtOo0GvFHOz5RwFG15M6oiIiKjd+vq4BXu8vAr1dmdY6kNM6oiIiKgDshJjoddqvJYpQuDwSfbWhQuTOiIiImo3WZbRx8drw/YVVUBwzrqwYFJHREREHeJrFGxFTR1KK2vDUp/ujkkdERERdUhqnBFmo77Z8n1FFWGpT3fHpI6IiIg6RJIk9E1rfgv2yEkram2OsNSpO2NSR0RERB3mK6lThMDBYvbWhRqTOiIiIuqwhBgDks3GZsv3FVdAUThgIpSY1BEREVGn+BowUV1vx/GK6rDUp7tiUkdERESd0ic1DhKkZsv3FZWHpT7dFZM6IiIi6pQYvQ6ZibHNlh8vr0JlrS0sdeqOmNQRERFRp/l6bRgA7OnGvXUOJbTHY1JHREREnZadYoZGbp5W7D9R0W2nN3E6QztQhEkdERERdZpOo0F2srnZcqdQsPt4WVjqFG4aTfPnDIOJSR0REREFREu3YPeeKEed3Rny+nQ3TOqIiIgoIHokxsKg0zRb7lAU7DnR/XrrePuViIiIuiRZln3OWQcAe46Xw+boXr11vP1KREREXdaAzCSfy+1OJ/ac6F4jYbUhzrKY1BEREVHAxMfokZlg8rlu9/Ey2J3dq7culJjUERERUUANzEz0udzmcGLP8e7VWxdK2nBXgIiIiKJLz2QzYvQ61Nrszdb9euwUctITYDLowlK3oHJUA2VbXT/X6ABnRkgPz546IiIiCihZljGghd46h6Jg26GSkNepO2BSR0RERAHXLyMBEnyP/jxy0ooTFdUhr1O0Y1JHREREARer1yE7Ja7F9VsOFsGphPjlqFGOSR0REREFxcAevm/BAoC11tbtpjgJNiZ1REREFBTp8bGIj9G3uP6XIydR42MwBXUMkzoiIiIKCkmSMKRnSovrHYqC7/cXQRGhfZ1WtGJSR0REREGTkxYPk77l6UsKy6uwq/BUSOsUrZjUERERUdBoZBlDe7XcWwcAPx4uRbGFo2E7i0kdERERBdVp6QmIaaW3DgA27jnO5+s6iUkdERERBZVWI2Noz+RWy9TZHfhmz3EonOakw5jUERERUdD1z0iEUdf620lLrDXYWlACwYETHcKkjoiIiIJOq5ExpI3eOgDYW1SOzQeKoChM7NqLSR0RERGFxIDMROi1mjbLHSiuwMa9hXDwVmy7MKkjIiKikNBpNBjWxkhYt6OnKrF+5zHYnc6g1ytaMKkjIiKikBnUI6nVt0w0VmSpxuc/H+F0J36K2KRu5syZkCQJL7/8cptlX3/9dfTt2xdGoxHjxo3D999/77W+rq4Os2bNQkpKCsxmM6666ioUFxcHsfZERETkiyzLGHNapt/lK2rq8MWOI1i/6ygstfVBrVtXF5FJ3UcffYTvvvsOWVlZbZZ9//33MWfOHCxYsADbtm3DGWecgfz8fJSUlHjK3HvvvfjPf/6D5cuXY/369Th+/DiuvPLKIJ8FERER+dIj0YTeqfHt2uZYWRVWbSvA5v0ncKjUgoqaek5/0kTrY4vDoLCwEHfddRf++9//YuLEiW2Wf/HFF3HLLbfgpptuAgAsXrwYq1atwt///nfMnTsXFosFf/vb3/Duu+/iN7/5DQDg7bffxpAhQ/Ddd9/h7LPPDvo5ERERkbdRfdNxvKyqXYMhBAT2F1dgf3EFAEAjyYiP1UOriYw+Kp2oQ7qzDABQZTPA4UwL6fEjKqlTFAU33HADHnjgAZx++ultlrfZbNi6dSvmzZvnWSbLMvLy8rBp0yYAwNatW2G325GXl+cpM3jwYPTu3RubNm1iUkdERBQGJoMOw7JT8OPh0g7vwykUlFfXBbReHkJAqwg42pEw6lGPWMkGAKixywj1rCwRldQ999xz0Gq1uPvuu/0qf/LkSTidTmRkZHgtz8jIwO7duwEARUVF0Ov1SExMbFamqKioxX3X19ejvl69d2+1Wtt5NkRERNSawVnJOFhigbXWFu6qNJNZU4szS0tRaozBkXgzSmNiICQp3NVqVdj6K5cuXQqz2ez5rF+/Hq+88gqWLFkCKQK+tIULFyIhIcHzyc7ODneViIiIoopGlpHbPwtyBPy735ROUWBwKuhZXY2zi4px0bFC9KuwwOBwhLtqLQpbUjdp0iT8+OOPns+3336LkpIS9O7dG1qtFlqtFocPH8Z9992Hvn37+txHamoqNBpNs5GsxcXFyMx0jazJzMyEzWZDRUVFi2V8mTdvHiwWi+dz9OjRgJw3ERERqVLjYzCqb3q4q+GTAFCr1cImyTDb7Bh2qgwTjhZiZEkpUmrrgAh7nVnYbr/GxcUhLi7O8/utt96Kyy67zKtMfn4+brjhBs8giKb0ej1Gjx6NtWvXYvLkyUDDc3lr167FnXfeCQAYPXo0dDod1q5di6uuugoAsGfPHhw5cgS5ubkt1s9gMMBgMATkXImIiKhlA3skobSyFodPRuajTooso06WASGgUxT0qaxCdlU1rHodDsfHodBkgl3T9psygi1inqlLSUlBSor3LNM6nQ6ZmZkYNGiQZ9mECRNwxRVXeJK2OXPmYPr06RgzZgzOOussvPzyy6iurvYkggkJCZgxYwbmzJmD5ORkxMfH46677kJubi4HSRAREUUASZIwrn8myqvrIvL5Og9Jgl2jgV0IaIRAQr0NZ5SewuCyChwzm1AcpwcMAKSGbr4Qz7gSMUmdvw4cOICTJ096fr/22mtRWlqK+fPno6ioCCNHjsTq1au9Bk+89NJLkGUZV111Ferr65Gfn49FixaF6QyIiIioKZ1Gg/MH9cR/fz4c+e98lSQ4JQlOWYbU0HvXz2JFjhWwGXSo1wvU1Wvxoz20vXeSEBF2QzhCWa1WzJw5E/Omj8Lwfu2bMJGIiIj8c7SsEht3F0IJc3qSXVmFUSWlqNX62f8lBHSKAyaHExKAMhjwnn4gZj/+LCwWC+Ljg587RMZsfUREREQAspPjcOHQbGjlLpSiCAGtENApAookoEiAIgNaEdoexy70jREREVF30CPRhAnDekOvDf/gg9ZIQsDgdCLG6YQsBEpMMSjIsuOn0+pwLN2Oeim0aVaXe6aOiIiIol9qXAz+Z1hvfLnzGGpt9nBXR+XplXP1wtVpNThqNuNonBn1eoHe0ikAQE2sAqUytLeQmdQRERFRREo0GfG/Z/TBz0dOYX9xeVjr4h4QoRECTknCyRgjDsfF4YQpFs6GW8V61Htto5VDe/uVSR0RERFFrBi9DuP6Z2JQj0RsP1yK4+VVIT2+RlGgUxRIAGwaGYfMcTgWZ0aFXg9E2JswmNQRERFRxEs0GXHR0GwUW6pRYq1FeVUdymvqUVUX3HnttELAYtBH1CTDLWFSR0RERF1GRoIJGQkmz+92pwKnEoRn1yprIBfEQfRIRWpqIlIlCaPb2sZRDU2FBQBQXqPDzjIOlCAiIiLyi04jQxeMzrPkOCB5cPu2kTSAxnVLVquRQn53llOaEBEREUUBJnVEREREUYBJHREREVEUYFJHREREFAWY1BERERFFASZ1RERERFGASR0RERFRFGBSR0RERBQFmNQRERERRQEmdURERERRgEkdERERURRgUkdEREQUBZjUEREREUUBJnVEREREUYBJHREREVEUYFJHREREFAWY1BERERFFASZ1RERERFFAG+4KEBEREUUFrQlIv8D1c6UD0JwK6eHZU0dEREQUBZjUEREREUUBJnVEREREUYBJHREREVEUYFJHREREFAQ2R2iPx6SOiIiIKAiEECE9HpM6IiIioiDQaaWQHo9JHREREVEQOJyhPR6TOiIiIqIg4O1XIiIioiig5+1XIiIioq5PCm1Ox6SOiIiIKBowqSMiIiKKAkzqiIiIiKIAkzoiIiKiKMCkjoiIiCgKMKkjIiIiigJM6oiIiIiiAJM6IiIioijApI6IiIgoCjCpIyIiIooCEZfU7dq1C5MmTUJCQgJMJhPGjh2LI0eOtLrN8uXLMXjwYBiNRgwfPhyffvqp13ohBObPn48ePXogJiYGeXl52LdvX5DPhIiIiCh0IiqpO3DgAM477zwMHjwYX331FX7++Wc89thjMBqNLW7z7bffYsqUKZgxYwa2b9+OyZMnY/LkydixY4enzPPPP49XX30VixcvxubNm2EymZCfn4+6uroQnRkRERFRcElCCBHuSrhdd9110Ol0eOedd/ze5tprr0V1dTU++eQTz7Kzzz4bI0eOxOLFiyGEQFZWFu677z7cf//9AACLxYKMjAwsWbIE1113nV/HsVqtmDlzJuZNH4Xh/eI7cHZERETUXZRVOrDsq1OYNWc+LBYL4uODnztog34EPymKglWrVuHBBx9Efn4+tm/fjpycHMybNw+TJ09ucbtNmzZhzpw5Xsvy8/OxYsUKAEBBQQGKioqQl5fnWZ+QkIBx48Zh06ZNLSZ19fX1qK+v9/xutVqh0WhQVaegrNIRgDMmIiKiaGWpdsKphLbfLGKSupKSElRVVeHZZ5/F008/jeeeew6rV6/GlVdeiXXr1mH8+PE+tysqKkJGRobXsoyMDBQVFXnWu5e1VMaXhQsX4oknnvBa9sADD2Dz3nr8fNgOABACsDkEhBDQa2XIMuBwCtidAjqNBK1G6uC30T5Nj6kogM2hQJIk6LUSpBBUo+kxgebfTbAxHirGQ8V4uDAeKsZDxXi4BCMeDqeApaabJHVLly7Fbbfd5vl91apVAIDLL78c9957LwBg5MiR+Pbbb7F48eIWk7pgmTdvnlcPoNVqxeuvvw5ZAox6GUIIlFc54XAKJJk00OnUq6661omqOgVmowxTjCao9ayudaLax7F0dqC82gmnIiHJrIEUxJZptyuw1jmh1UhIMsmeYxn1ru+oqs7Z7DsKNMZDxXioGA8XxkPFeKgYD5dgxcPuEJDgDEKNWxa2pG7SpEkYN26c5/e0tDRotVoMHTrUq9yQIUOwcePGFveTmZmJ4uJir2XFxcXIzMz0rHcv69Gjh1eZkSNHtrhfg8EAg8HQbLlGBrQa4JRVgSKA9AQt9E0uNn2cFlqNE9ZaBVqNgrjY4DTMyhonamwCiSZNs2PotRrotBJOVjphrVGQEq+BHISGabMrsNQqMOhkH8eQkJ4o4ZTVCUutglSt1Oy7CgRFCMajAeOhYjxcGA8V46FiPFyCHY9Q9HQ2FrbRr3Fxcejfv7/nk5CQgLFjx2LPnj1e5fbu3Ys+ffq0uJ/c3FysXbvWa9maNWuQm5sLAMjJyUFmZqZXGavVis2bN3vKtIcQAqesTtidAqlxmhYvsrhYDeJjZFhrFVTWBD5Tr6xxXWTxMXKLF5leJyM1TgO701VnJcBjYmx2BScrndBppBYbvSy51uk0rv9B2OxKQOugMB4ejIeK8XBhPFSMh4rxcImUeARSRE1p8sADD+D999/HX//6V+zfvx+vvfYa/vOf/+COO+7wlJk2bRrmzZvn+f2ee+7B6tWr8cILL2D37t14/PHHsWXLFtx5550AAEmSMHv2bDz99NP4+OOP8csvv2DatGnIyspqdQBGS2psos0LwC1YF4I/DdItWA3TnwbpFqyG6W+DdGM8XBgPFeOhYjxcGA8V46HqKoldRCV1V1xxBRYvXoznn38ew4cPx1tvvYV//etfOO+88zxljhw5ghMnTnh+P+ecc/Duu+/izTffxBlnnIEPP/wQK1aswLBhwzxlHnzwQdx111249dZbMXbsWFRVVWH16tWtzn/niyzLcCrw6wJwC/SF0J4G6RbohtmeBukW6IbZ3gbpxni4MB4qxkPFeLgwHirGQ9UVEruImqcuklmtVjz33HPISDIgLVHf7u070pgCvY+ONKZA76OjjSnQ+2A8XBgPFeOhYjxcGA8V46Hy97u0OQQKT9rwyGOPh2yeuojqqYt0iqJAI3fsqcfOZviBaNSd/YsrEI26s39xBaJBgvHwYDxUjIeK8XBhPFSMhyqSe+yY1IVQRy+EQDRIt442zEA0SLeONsxANUg3xsOF8VAxHirGw4XxUDEeqkhN7JjUhVh7L4RANki39jbMQDZIt/Y2zEA3SDfGw4XxUDEeKsbDhfFQMR6qSEzsmNSFgb8XQjAapJu/DTMYDdLN34YZrAbpxni4MB4qxkPFeLgwHirGQxVpiR2TujBp60IIZoN0a6thBrNBurXVMIPdIN0YDxfGQ8V4qBgPF8ZDxXioIimxY1IXRi1dCKFokG4tNcxQNEi3lhpmqBqkG+PhwnioGA8V4+HCeKgYD1VL8XCGOMcL22vCyMXd6Ky16l8YoWqQbq6GCZysdOKU1Yn4WBmnQtQg3dwN85TViZOVTqTEAdYaJWQN0o3xcGE8VIyHivFwYTxUjIeqaTwcikBg34HRNiZ1EaDphRDKBunmbpilVidOWp3QaRCyBunmbpgnLQ6ctLr+vEmLD12DdGM8XBgPFeOhYjxcGA8V46FqHA9FESG/Hcrbr0RERERRgEldBGj8DES4HrZ0PwOh10pIjdfAoSAoL3FujfsZCIcCpMZroNcG5yXObWE8XBgPFeOhYjxcGA8V46FqHA9zjBzy269M6sKs6UOt4RhF0/ShVkOQXuLcmqYPtRp0clBe4twWxsOF8VAxHirGw4XxUDEeqqbxMBk1vP3anbQ0SimUDbOlUUqBfolza1oapRTolzi3hfFwYTxUjIeK8XBhPFSMh6qleGhC+3gjk7pwaWvYeSgaZlvDzkPRMNsadh6qhsl4uDAeKsZDxXi4MB4qxkMVymlk2sKkLgz8vQCC2TD9nUcomA3T33mEgt0wGQ8XxkPFeKgYDxfGQ8V4qCIpoQOTutBr7wUQjIbZ3okhg9Ew2zsxZLAaJuPhwnioGA8V4+HCeKgYD1WkJXRgUhdaHb0AAtkwOzrTdyAbZkdn+g50w2Q8XBgPFeOhYjxcGA8V46GKxIQOTOraR5ZlOJWOXYydvQAC0TA7++qWQDTMzr66JVANk/FwYTxUjIeK8XBhPFSMhypSEzowqWu/6nrR7gshUBdAZxpmoN7F15mGGah38XW2YTIeLoyHivFQMR4ujIeK8VBFckIHJnXtoygKNDLadSEE+gLoSMMM9MuVO9IwA/1y5Y42TMbDhfFQMR4qxsOF8VAxHqpIT+jApK79YvWS3xdCsC6A9jTMQDdIt/Y0zEA3SLf2NkzGw4XxUDEeKsbDhfFQMR6qrpDQgUld+0l+XgjBvgD8aZjBapBu/jTMYDVIN38bJuPhwnioGA8V4+HCeKgYD1VXSejApK5j2roQQnUBtNYwg90g3VprmMFukG6Mh4rxUDEeLoyHivFQMR4ukRKPQGFS10EtXQihvgB8NcxQNUg3Xw0zVA3SjfFQMR4qxsOF8VAxHirGwyVS4hEI2nBXoCtzXwinrE6crHTCoFVQZxchvwDcx7LWKrA5BOodImQN0s3VMF2DSE5aHAAAh4KQNEg3xkPFeKgYDxfGQ8V4qBgPl0iJR2cxqfOTaOgWtjsV1NQ5vNbF6AVqKhXYHYBeK0Eji2Zlgk0jA7IkUFXn+gsjPkZGXX1wX+bsS6wesNS46pAQK8PhVOBwBvdFyk0xHirGw4XxUDEeKsbDhfFQBTIeTkXAPbWt6MSEy+0hiVAdqYs7duwYsrOzw10NIiIi6mKOHj2KXr16Bf04TOr8pCgKjh8/jri4OEiNuqStViuys7Nx9OhRxMfHh7WO5I2xiVyMTeRibCIXYxO5WoqNEAKVlZXIysqCLAf/VjJvv/pJluVWs+z4+Hg2sgjF2EQuxiZyMTaRi7GJXL5ik5CQELLjc/QrERERURRgUkdEREQUBZjUdZLBYMCCBQtgMBjCXRVqgrGJXIxN5GJsIhdjE7kiJTYcKEFEREQUBdhTR0RERBQFmNQRERERRQEmdURERERRgEldE6+//jr69u0Lo9GIcePG4fvvv2+1/PLlyzF48GAYjUYMHz4cn376qdd6IQTmz5+PHj16ICYmBnl5edi3b1+Qz6Jr+frrr3HZZZchKysLkiRhxYoVXuv9+Q7LysowdepUxMfHIzExETNmzEBVVVWrx62rq8OsWbOQkpICs9mMq666CsXFxV5ljhw5gokTJyI2Nhbp6el44IEH4HCE9hU+4bRw4UKMHTsWcXFxSE9Px+TJk7Fnzx6vMsH6Hv2J6c8//4zzzz8fRqMR2dnZeP755wN49pHtjTfewIgRIzzzYuXm5uKzzz7zrGdcIsOzzz4LSZIwe/ZszzLGJnwef/xxSJLk9Rk8eLBnfZePjSCPZcuWCb1eL/7+97+LX3/9Vdxyyy0iMTFRFBcX+yz/zTffCI1GI55//nmxc+dO8eijjwqdTid++eUXT5lnn31WJCQkiBUrVoiffvpJTJo0SeTk5Ija2toQnllk+/TTT8Ujjzwi/v3vfwsA4qOPPvJa7893eMkll4gzzjhDfPfdd2LDhg2if//+YsqUKa0ed+bMmSI7O1usXbtWbNmyRZx99tninHPO8ax3OBxi2LBhIi8vT2zfvl18+umnIjU1VcybNy8I30Jkys/PF2+//bbYsWOH+PHHH8Vvf/tb0bt3b1FVVeUpE6zvsa2YWiwWkZGRIaZOnSp27Ngh3nvvPRETEyP+8pe/BOnbiCwff/yxWLVqldi7d6/Ys2ePePjhh4VOpxM7duwQgnGJCN9//73o27evGDFihLjnnns8yxmb8FmwYIE4/fTTxYkTJzyf0tJSz/quHhsmdY2cddZZYtasWZ7fnU6nyMrKEgsXLvRZ/pprrhETJ070WjZu3Dhx2223CSGEUBRFZGZmij/96U+e9RUVFcJgMIj33nsvaOfRlTVN6vz5Dnfu3CkAiB9++MFT5rPPPhOSJInCwkKfx6moqBA6nU4sX77cs2zXrl0CgNi0aZMQDcmmLMuiqKjIU+aNN94Q8fHxor6+PsBn3jWUlJQIAGL9+vVCBPF79CemixYtEklJSV77eOihh8SgQYOCcOZdQ1JSknjrrbcYlwhQWVkpBgwYINasWSPGjx/vSeoYm/BasGCBOOOMM3yui4bY8PZrA5vNhq1btyIvL8+zTJZl5OXlYdOmTT632bRpk1d5AMjPz/eULygoQFFRkVeZhIQEjBs3rsV9kjd/vsNNmzYhMTERY8aM8ZTJy8uDLMvYvHmzz/1u3boVdrvda7+DBw9G7969vfY7fPhwZGRkeMrk5+fDarXi119/Dcr5RjqLxQIASE5OBoL4PfoT002bNuGCCy6AXq/32u+ePXtQXl4e8HOPZE6nE8uWLUN1dTVyc3MZlwgwa9YsTJw4sdm/EYxN+O3btw9ZWVk47bTTMHXqVBw5cgSIktgwqWtw8uRJOJ1Or0ABQEZGBoqKinxuU1RU1Gp593/bs0/y5s93WFRUhPT0dK/1Wq0WycnJrcZOr9cjMTGx1f36Om7jenUniqJg9uzZOPfcczFs2DAgiN+jPzFlfIBffvkFZrMZBoMBM2fOxEcffYShQ4cyLmG2bNkybNu2DQsXLmy2jrEJr3HjxmHJkiVYvXo13njjDRQUFOD8889HZWVlVMRG63dJIurWZs2ahR07dmDjxo3hrgo1GDRoEH788UdYLBZ8+OGHmD59OtavXx/uanVrR48exT333IM1a9bAaDSGuzrUxP/+7/96fh4xYgTGjRuHPn364IMPPkBMTExY6xYI7KlrkJqaCo1G02yUS3FxMTIzM31uk5mZ2Wp593/bs0/y5s93mJmZiZKSEq/1DocDZWVlrcbOZrOhoqKi1f36Om7jenUXd955Jz755BOsW7cOvXr18iwP1vfoT0wZH0Cv16N///4YPXo0Fi5ciDPOOAOvvPIK4xJGW7duRUlJCUaNGgWtVgutVov169fj1VdfhVarRUZGBmMTQRITEzFw4EDs378/KtoNk7oGer0eo0ePxtq1az3LFEXB2rVrkZub63Ob3Nxcr/IAsGbNGk/5nJwcZGZmepWxWq3YvHlzi/skb/58h7m5uaioqMDWrVs9Zb788ksoioJx48b53O/o0aOh0+m89rtnzx4cOXLEa7+//PKLV2Ncs2YN4uPjMXTo0KCcb6QRQuDOO+/ERx99hC+//BI5OTle64P1PfoT09zcXHz99dew2+1e+x00aBCSkpIC+C10HYqioL6+nnEJowkTJuCXX37Bjz/+6PmMGTMGU6dO9fzM2ESOqqoqHDhwAD169IiOdtOuYRVRbtmyZcJgMIglS5aInTt3iltvvVUkJiZ6RrnccMMNYu7cuZ7y33zzjdBqteLPf/6z2LVrl1iwYIHPKU0SExPFypUrxc8//ywuv/xyTmnSRGVlpdi+fbvYvn27ACBefPFFsX37dnH48GEh/PwOL7nkEnHmmWeKzZs3i40bN4oBAwZ4DRc/duyYGDRokNi8ebNn2cyZM0Xv3r3Fl19+KbZs2SJyc3NFbm6uZ7176PrFF18sfvzxR7F69WqRlpbWraY0uf3220VCQoL46quvvKYAqKmp8ZQJxPe4efNmMWjQIHHs2DHPsrZiWlFRITIyMsQNN9wgduzYIZYtWyZiY2O7zfQMc+fOFevXrxcFBQXi559/FnPnzhWSJInPP/9cCMYlojQe/SoYm7C67777xFdffSUKCgrEN998I/Ly8kRqaqooKSkRIgpiw6Suif/7v/8TvXv3Fnq9Xpx11lniu+++86wbP368mD59ulf5Dz74QAwcOFDo9Xpx+umni1WrVnmtVxRFPPbYYyIjI0MYDAYxYcIEsWfPnpCdT1ewbt06AaDZx/1d+/Mdnjp1SkyZMkWYzWYRHx8vbrrpJlFZWelZX1BQIACIdevWeZbV1taKO+64QyQlJYnY2FhxxRVXiBMnTnjt99ChQ+J///d/RUxMjEhNTRX33XefsNvtQf9OIoWvuAAQb7/9tqdMIL5H9zVQUFDgWdZWTIUQ4qeffhLnnXeeMBgMomfPnuLZZ58N6vcRSW6++WbRp08fodfrRVpampgwYYInoROMS0RpmtQxNuFz7bXXih49egi9Xi969uwprr32WrF//37P+q4eG0m4/sdNRERERF0Yn6kjIiIiigJM6oiIiIiiAJM6IiIioijApI6IiIgoCjCpIyIiIooCTOqIiIiIogCTOiIiIqIowKSOiIiIKAowqSMiasPf/vY3XHzxxUE/zurVqzFy5EgoihL0YxFR9GFSR0TUirq6Ojz22GNYsGBB0I91ySWXQKfTYenSpUE/FhFFHyZ1RESt+PDDDxEfH49zzz03JMe78cYb8eqrr4bkWEQUXZjUEVG3UFpaiszMTDzzzDOeZd9++y30ej3Wrl3b4nbLli3DZZdd5rXswgsvxOzZs72WTZ48GTfeeKPn9759++Lpp5/GtGnTYDab0adPH3z88ccoLS3F5ZdfDrPZjBEjRmDLli1e+7nsssuwZcsWHDhwIABnTUTdCZM6IuoW0tLS8Pe//x2PP/44tmzZgsrKStxwww248847MWHChBa327hxI8aMGdOhY7700ks499xzsX37dkycOBE33HADpk2bhuuvvx7btm1Dv379MG3aNAghPNv07t0bGRkZ2LBhQ4eOSUTdF5M6Iuo2fvvb3+KWW27B1KlTMXPmTJhMJixcuLDF8hUVFbBYLMjKyurw8W677TYMGDAA8+fPh9VqxdixY3H11Vdj4MCBeOihh7Br1y4UFxd7bZeVlYXDhw936JhE1H0xqSOibuXPf/4zHA4Hli9fjqVLl8JgMLRYtra2FgBgNBo7dKwRI0Z4fs7IyAAADB8+vNmykpISr+1iYmJQU1PToWMSUffFpI6IupUDBw7g+PHjUBQFhw4darVsSkoKJElCeXl5m/t1Op3Nlul0Os/PkiS1uKzpFCZlZWVIS0vz42yIiFRM6oio27DZbLj++utx7bXX4qmnnsIf/vCHZr1kjen1egwdOhQ7d+5stq7pLdODBw8GpI51dXU4cOAAzjzzzIDsj4i6DyZ1RNRtPPLII7BYLHj11Vfx0EMPYeDAgbj55ptb3SY/Px8bN25stnzlypX497//jQMHDuCPf/wjdu7cicOHD6OwsLBTdfzuu+9gMBiQm5vbqf0QUffDpI6IuoWvvvoKL7/8Mt555x3Ex8dDlmW888472LBhA954440Wt5sxYwY+/fRTWCwWr+UTJ07E888/j6FDh+Lrr7/GokWL8P333+Odd97pVD3fe+89TJ06FbGxsZ3aDxF1P5JoPJaeiIiaufrqqzFq1CjMmzcPaJinbuTIkXj55ZcDepyTJ09i0KBB2LJlC3JycgK6byKKfuypIyJqw5/+9CeYzeagH+fQoUNYtGgREzoi6hD21BERtVOweuqIiDqDSR0RERFRFODtVyIiIqIowKSOiIiIKAowqSMiIiKKAkzqiIiIiKIAkzoiIiKiKMCkjoiIiCgKMKkjIiIiigJM6oiIiIiiAJM6IiIioijw/wGZWPLGaBLORwAAAABJRU5ErkJggg==",
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