{
"cells": [
{
"cell_type": "markdown",
"id": "80074018",
"metadata": {},
"source": [
"# Photonic crystal waveguide polarization filter"
]
},
{
"cell_type": "markdown",
"id": "37a27f2a",
"metadata": {},
"source": [
"Polarization control is one of the central themes in integrated silicon photonics. Different polarization modes not only allow for more information-carrying channels but also enable a wide range of applications given their different characteristics. For example, waveguide TE modes usually have better confinement and thus they are less prone to sidewall roughness. TM modes, on the other hand, have a larger penetration depth into the top and bottom claddings, which makes them suitable for sensing applications. As a result, integrated silicon photonic filters that selectively transmit or block certain polarization are very useful. \n",
"\n",
"This notebook demonstrates the modeling of a compact TM-pass polarization filter based on photonic crystal waveguide. The photonic crystal is an air-bridged silicon slab with periodic air holes arranged in a triangular lattice. It is possible to achieve a TM-pass but TE-block device within a frequency range by utilizing bandgap engineering and index guiding mechanism. The design parameters adopted from [Chandra Prakash and Mrinal Sen , \"Optimization of silicon-photonic crystal (PhC) waveguide for a compact and high extinction ratio TM-pass polarization filter\", Journal of Applied Physics 127, 023101 (2020)](https://aip.scitation.org/doi/abs/10.1063/1.5130160) are optimized for the telecom frequency to have a ~-0.5 dB TM transmission and ~-40 dB TE transmission. \n",
"\n",
""
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "a172f231",
"metadata": {
"execution": {
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"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import tidy3d as td\n",
"import tidy3d.web as web\n",
"from tidy3d.plugins.mode import ModeSolver\n"
]
},
{
"cell_type": "markdown",
"id": "2bcbebc6",
"metadata": {},
"source": [
"## Simulation Setup "
]
},
{
"cell_type": "markdown",
"id": "565a299c",
"metadata": {},
"source": [
"This device is designed to work in a wide frequency range from 1480 nm to 1620 nm."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e2bda8ee",
"metadata": {
"execution": {
"iopub.execute_input": "2023-03-27T20:36:53.746928Z",
"iopub.status.busy": "2023-03-27T20:36:53.746613Z",
"iopub.status.idle": "2023-03-27T20:36:53.767979Z",
"shell.execute_reply": "2023-03-27T20:36:53.767412Z"
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"outputs": [],
"source": [
"lda0 = 1.55 # central wavelength\n",
"freq0 = td.C_0 / lda0 # central frequency\n",
"ldas = np.linspace(1.48, 1.62, 100) # wavelength range of interest\n",
"freqs = td.C_0 / ldas # frequency range of interest\n"
]
},
{
"cell_type": "markdown",
"id": "c7862239",
"metadata": {},
"source": [
"Since the photonic crystal slab is air-bridged, we only need to define two materials: silicon and air. The frequency dispersion of the silicon refractive index in the frequency range of interest is quite small. Therefore, in this notebook, we model it as non-dispersive and lossless. "
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "65537c56",
"metadata": {
"execution": {
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"iopub.status.busy": "2023-03-27T20:36:53.770150Z",
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"shell.execute_reply": "2023-03-27T20:36:53.787098Z"
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"outputs": [],
"source": [
"n_si = 3.47 # silicon refractive index\n",
"si = td.Medium(permittivity=n_si**2)\n",
"\n",
"n_air = 1 # air refractive index\n",
"air = td.Medium(permittivity=n_air)\n"
]
},
{
"cell_type": "markdown",
"id": "ebfa2951",
"metadata": {},
"source": [
"For the photonic crystal to work as a filter, the geometric parameters need to be carefully chosen such that bandgap lies within the frequency range of interest. The design process would require the calculation of band structures. In this notebook, we will skip the band structure calculation and only model the optimized device. For band diagram simulation, refer to the [photonic crystal slab band structure calculation notebook](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/notebooks/Bandstructure.html).\n",
"\n",
"Define the geometric parameters for the photonic crystal as well as the input and output straight waveguides."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "f2d41dc3",
"metadata": {
"execution": {
"iopub.execute_input": "2023-03-27T20:36:53.789734Z",
"iopub.status.busy": "2023-03-27T20:36:53.789553Z",
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"shell.execute_reply": "2023-03-27T20:36:53.806370Z"
}
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"outputs": [],
"source": [
"a = 0.42 # lattice constant\n",
"t = 0.75 * a # slab thickness\n",
"r = 0.3 * a # radius of air holes\n",
"w = 0.73 * a # width of the photonic crystal waveguide section\n",
"\n",
"N_holes = 11 # number of holes in each row\n",
"N_rows = 7 # number of rows of holes on each side of the waveguide\n",
"L = N_holes * a # length of the photonic crystal waveguide\n",
"\n",
"D = 0.4 # width of the input and output waveguides\n",
"\n",
"inf_eff = 1e3 # effective infinity of the model\n"
]
},
{
"cell_type": "markdown",
"id": "9fd085a2",
"metadata": {},
"source": [
"To build the device, we define the silicon slab, input and output straight waveguides, and air holes. The air holes are systematically defined using a nested for loop. Due to the mirror symmetry of the device with respect to the $xz$ plane, We only define the air holes in $y>0$. Later, we will define the symmetry condition in the simulation."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "fae873ee",
"metadata": {
"execution": {
"iopub.execute_input": "2023-03-27T20:36:53.808914Z",
"iopub.status.busy": "2023-03-27T20:36:53.808745Z",
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"shell.execute_reply": "2023-03-27T20:36:53.832361Z"
}
},
"outputs": [],
"source": [
"# define the silicon slab\n",
"si_slab = td.Structure(\n",
" geometry=td.Box.from_bounds(\n",
" rmin=(-L / 2, -N_rows * np.sqrt(3) * a / 2 - w / 2, 0),\n",
" rmax=(L / 2, N_rows * np.sqrt(3) * a / 2 + w / 2, t),\n",
" ),\n",
" medium=si,\n",
")\n",
"\n",
"# define the input and output straight waveguides\n",
"si_wg = td.Structure(\n",
" geometry=td.Box.from_bounds(\n",
" rmin=(-inf_eff, -D / 2, 0),\n",
" rmax=(inf_eff, D / 2, t),\n",
" ),\n",
" medium=si,\n",
")\n",
"\n",
"# systematically define air holes\n",
"holes = []\n",
"for i in range(N_rows):\n",
" if i % 2 == 0:\n",
" shift = a / 2\n",
" N = N_holes\n",
" else:\n",
" shift = 0\n",
" N = N_holes + 1\n",
"\n",
" for j in range(N):\n",
" holes.append(\n",
" td.Structure(\n",
" geometry=td.Cylinder(\n",
" center=(\n",
" (j - (N_holes) / 2) * a + shift,\n",
" (w / 2 + r) + (i) * np.sqrt(3) * a / 2,\n",
" t / 2,\n",
" ),\n",
" radius=r,\n",
" length=t,\n",
" ),\n",
" medium=air,\n",
" )\n",
" )\n"
]
},
{
"cell_type": "markdown",
"id": "e441c407",
"metadata": {},
"source": [
"A [ModeSouce](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.ModeSource.html?highlight=modesource) is defined at the input waveguide to launch either the fundamental TE or TM mode. A [FluxMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FluxMonitor.html) is defined at the output waveguide to measure the transmission. In addition, we define a [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldMonitor.html) to visualize the field propagation and scattering in the $xy$ plane."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "043af5cf",
"metadata": {
"execution": {
"iopub.execute_input": "2023-03-27T20:36:53.835394Z",
"iopub.status.busy": "2023-03-27T20:36:53.835222Z",
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"shell.execute_reply": "2023-03-27T20:36:53.854308Z"
}
},
"outputs": [],
"source": [
"# simulation domain size\n",
"Lx = 1.5 * L\n",
"Ly = 2 * N_rows * a + lda0\n",
"Lz = 7 * t\n",
"sim_size = (Lx, Ly, Lz)\n",
"\n",
"# define a mode source at the input waveguide\n",
"fwidth = 0.5 * (np.max(freqs) - np.min(freqs))\n",
"mode_spec = td.ModeSpec(num_modes=1, target_neff=n_si)\n",
"mode_source = td.ModeSource(\n",
" center=(-Lx / 2 + lda0 / 2, 0, t / 2),\n",
" size=(0, 4 * D, 5 * t),\n",
" source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
" direction=\"+\",\n",
" mode_spec=mode_spec,\n",
" mode_index=0,\n",
")\n",
"\n",
"# define a flux monitor at the output waveguide\n",
"flux_monitor = td.FluxMonitor(\n",
" center=(Lx / 2 - lda0 / 2, 0, t / 2),\n",
" size=mode_source.size,\n",
" freqs=freqs,\n",
" name=\"flux\",\n",
")\n",
"\n",
"# define a field monitor in the xy plane\n",
"field_monitor = td.FieldMonitor(\n",
" center=(0, 0, t / 2),\n",
" size=(td.inf, td.inf, 0),\n",
" freqs=[freq0],\n",
" name=\"field\",\n",
")\n"
]
},
{
"cell_type": "markdown",
"id": "a5c609d5",
"metadata": {},
"source": [
"For periodic structures, it is better the define a grid that is commensurate with the periodicity. Therefore, we use [UniformGrid](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.UniformGrid.html) in the $x$ and $y$ directions. In the $z$ direction, a nonuniform grid can be used. "
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "34ea04d9",
"metadata": {
"execution": {
"iopub.execute_input": "2023-03-27T20:36:53.857146Z",
"iopub.status.busy": "2023-03-27T20:36:53.857001Z",
"iopub.status.idle": "2023-03-27T20:36:53.875015Z",
"shell.execute_reply": "2023-03-27T20:36:53.874421Z"
}
},
"outputs": [],
"source": [
"# define grids\n",
"steps_per_unit_cell = 20\n",
"grid_spec = td.GridSpec(\n",
" grid_x=td.UniformGrid(dl=a / steps_per_unit_cell),\n",
" grid_y=td.UniformGrid(dl=a / steps_per_unit_cell * np.sqrt(3) / 2),\n",
" grid_z=td.AutoGrid(min_steps_per_wvl=steps_per_unit_cell),\n",
")\n"
]
},
{
"cell_type": "markdown",
"id": "99bc4945",
"metadata": {},
"source": [
"Since the TE and TM modes share different symmetry with respect to the $xz$ plane, we can selectively launch them by setting the appropriate symmetry condition. The simulation for TE incidence is done by setting the symmetry condition to `(0,-1,0)` while the TM incidence corresponds to `(0,1,0)`. \n",
"\n",
"For this simulation, we set a relatively long run time of 20 ps to ensure the field decays sufficiently such that the simulation result is accurate. "
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "5f2deae1",
"metadata": {
"execution": {
"iopub.execute_input": "2023-03-27T20:36:53.877016Z",
"iopub.status.busy": "2023-03-27T20:36:53.876873Z",
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"shell.execute_reply": "2023-03-27T20:36:53.907982Z"
}
},
"outputs": [],
"source": [
"# define the te incidence simulation\n",
"run_time = 2e-11 # simulation run time\n",
"\n",
"sim_te = td.Simulation(\n",
" center=(0, 0, 0),\n",
" size=sim_size,\n",
" grid_spec=grid_spec,\n",
" structures=[si_slab, si_wg] + holes,\n",
" sources=[mode_source],\n",
" monitors=[flux_monitor, field_monitor],\n",
" run_time=run_time,\n",
" boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
" symmetry=(0, -1, 0),\n",
")\n"
]
},
{
"cell_type": "markdown",
"id": "1cdcd5fd",
"metadata": {},
"source": [
"To quickly check if the structures, source, and monitors are correctly defined, use the `plot` method to visualize the simulation."
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "82aa2672",
"metadata": {
"execution": {
"iopub.execute_input": "2023-03-27T20:36:53.910507Z",
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"outputs": [
{
"data": {
"image/png": 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LEl/84hfFtm3bhGmaoqamRuzcuVPcddddIplMlrT9t3/7N3HOOedMtLvsssvEww8/PPH33t5ecc0114hoNCoATKTbT02xL/L9739/or/a2lrxW7/1W+LEiRMlba6//noRDoenfb4777xTyHzVn3nmGfHOd75TBINB0draKv74j/9YPPjgg9PiGRsbE7/5m78pEomEAFA23f6yyy6bNV3+zjvv9IzJC9d1xRe+8AWxevVqYRiG2LZtm/j3f//3ae2K2w+OHDlS8vvZYpvpeL3yyivi6quvFuFwWESjUfGhD33I89oiFh5FCI/5HoIgCIJYotCaGEEQBLFsIREjCIIgli0kYgRBEMSyhUSMIAiCWLaQiBEEQRDLFhIxgiAIYtlSVZudOefo7u5GNBqtqKI4QRAEsfAIITA6OorW1tayxbuBKhOx7u7uJVOolSAIgihPZ2dniQP8TFSViEWjUQDAH//h7yMYPOVDZNmFLfoAYGhAcZBW3AZeH9Ohaws7crNsjpF0wQY+EVZh6Kd/plcIgYFkoT6hqSuIhxfn8kimHeTtwsFviGuLMmqm83EKOh8F6Hycwu/5sB2BwVShbqVMuNlsHl/68lcn7tnlqCoRK57sYNBEJBwCAORtDkUFmFIQLUUBTL1Q2JZzAS6AWFSHsYAiZtkcadtFfPx82RyIB07vF5ULgZMpF+GwDlNTkLMFmMoQDVVm7VEpoxkXqq6hNqQg7wjYQkFdVAU7jV9UOh+noPNRgM7HKSo5H5YjkLY1MAVgTD5WGYGu6sSOvM3huICmAkGTwdALQpa3MWf/JFksm2Nw1IWuKqiPa6iPa9BVBYOjLiz79MRQ/ILarkB9VEVdTEMsyJDKcoxm3NMSA1D4gqayHLEgQ11MQ31Uhe0WYuOnqToanY9T0PkoQOfjFEvhfEylakVssoCZ408QmloqZAtdVnLyBVEXKzxNMaXw79N1YUz9ghafpqIh9bR+USd/QYtPt4bOTusXlc7HKeh8FKDzcYqlcD5moipFzHYwTcCKTBUyzhfmwpjpgihyui6M2b6gRU7XF3WmL2iR0/VFpfNxCjofBeh8nGIpnI/ZqEoR42JmASsyIWQAXI55vzDKXRBFFvrC8PqCFlnoL2q5L2iRhf6i0vk4BZ2PAnQ+TrEUzkc5qlLEmDK7gBXRVAZDKwjZyNj8XRgyF8SpOBfmwpD9ghZZqC+qzBe0yEJ9Uel8nILORwE6H6dYCufDi6oUMV0yJ1NlCjRWmHqcjwvDzwVRZL4vDL9f0CLz/UX18wUtMt9fVDofp6DzUYDOxymWwvmQoSpFzA+MKaiJzP3CqOSCmIhhni6MSr+gRebri1rJF7TIfH1R6Xycgs5HATofp1gK50OWqtonVkQIuYQNLsTEhud4kGE47aJ/RKAmovraYGjbHMNpF5qqIBZicFzg1PZqeWIhhuExF/1JBzVhFbqPL5kQAsNjLhxXoCasAooCy/Efg2kwhFyBkXShr3DQ35csnXUxluOIBBhMg1UUAxSFzsc4dD5OQedjnCV4PqJBFUIIcACQ0DQ/O5yqU8RQSO7wgotiliKHpiqIBFRYDkcqw2FoitTOc84By+EwdQZDU8Z32lc+zA+OX9jpPIfhAh5lxQAUPoPlCDAFiARUuAJwrcqfjlRVQTjAYLkCIlu42GVwXAHbFQgHGFRVQW4OMQCg8zEOnY9T0Pk4xVI6H5k8h8tlz4eAQyJWnoaYjlhU92xnOwJ5m+MXzosjHj69O/MJgiBWCsm0i/ufHUbIYAgGZr+XFkfEliXfd1WKmK4p0mWkXK4gHlZRG63KQ0UQBDEvaCrDaI6PV0eaPiQrrElycAHU+qhLSYkdBEEQxIJjaAq0WZI9pibV+FnPJBEjCIIgFhxFAWoi07MW55oVSiJGEARBnBaUKen3eZvPScAAEjGCIAjiNFLcR6YxYDDlwnIqFzCARIwgCIJYxpCIEQRBEKeN4hqYw4H6mApDm1tlDxIxgiAI4rQgpiRxmDqbc4kqEjGCIAhiwRECGB6bnsQx11qLJGIEQRDEgmM5As4sWYhThcz2IWQkYgRBEMSCI0ShuPJsWYiThWzEhwsAiRhBEASx4Bga86zEMZF+L1k0GSARIwiCIE4DMhXsgYKQJXwUXCcRIwiCIJYUfvzPSMQ88GPORhAEQZxeqlLE0jm5RUPb5rD8uLMRBEEQp5UqFTGOUY/sF2vcotvPsJYgCII4vVSliIUDDKns7EJm2RyDowVbcVnzTIIgCOL0U5V2xeGACqYWhAwAoqFTmTBFAdNVBbEQQ94WixUmQRAE4UFVihhwSrgmC9lkAauLqXBcACARIwiCWKpUrYgBpUJmOQJ5R0wIGFMUkIARBEEsbapaxIDxEZgjkBufNjwlYARBEMRSpyoTOyZj2Rx559SIK52llHqCIIjlQlWPxKaugaWzfMZkD4IgCGJpUrUiNlXAmKJMS/YwjaofqBIEQSxpqlLEbJsjbbtTkjgKTBaykCug+qimTBAEQZxeqnKoMZKZWcCKREMqYkGGsRyH41KGIkEQxFKlKkdiWhkBKxINqXBcAYtEjCAIYsmybEZi99xzD3bs2IFYLIZYLIYLL7wQP/3pTyvqKxGWS6MPBwsuowRBEMTSZNmIWFtbG/7mb/4Gr7zyCl5++WVceeWV+NCHPoS3337bd19+ivr6cRglCIIgTi/LZjrxAx/4QMn/P//5z+Oee+7B888/j23bti1SVARBEMRismxEbDKu6+KHP/wh0uk0LrzwwsUOhyAIgvBA+EgvkPV8BJaZiL355pu48MILkcvlEIlEcP/992Pr1q2zts/n88jn8xP/T6VSpyNMgiAIYgqWIxAwBIDySzSjGRfpnHzlpGWzJgYAmzZtwq5du/DCCy/gpptuwvXXX4/du3fP2v7uu+9GPB6f+Glvbz+N0RIEQRBFhBAYHnPBywzJRjMuUlmOcEBempaViBmGgQ0bNmDnzp24++67cdZZZ+HrX//6rO1vv/12JJPJiZ/Ozs7TGC1BEARRxNAYHFfgZGpmISsKWCzIEA7Il/1bVtOJU+Gcl0wXTsU0TZimeRojIgiCIGaCMaAmrCKZ5TiZckv26k4WsGhIRXJUvt9lI2K333473v/+96OjowOjo6P43ve+h8cffxwPPvjgYodGEARBSKDrDPWagsFRd0LIioXXiwLml2UjYv39/fjYxz6Gnp4exONx7NixAw8++CDe/e53L3ZoBEEQhCSGzlAfBQZHXfQMOQBQsYABy0jE/vVf/3WxQyAIgiDmAUNnMDU+YUYcDlaenrGsEjsIgiCI5c9oxkXOFgjoChQFsyZ7yEAiRhAEQZw2Jidx1MU01EdV2GWyFr0gESMIgiBOC+msOy2Jo7BGVrmQkYgRBEEQC47jCozlZs5CnCpkwoeQkYgRBEEQC47tCkQCs2chThaykbR87UQSMYIgCGLB0VUF4WD5NPqikDk+zIhJxAiCIIgFR9ab0dAZEj72jJGIEQRBEEsKXV+hBYAXgwq3LhAEQRCngWVTsWM+sW05rxohBCxn5avYd5/Zs9ghEERV81sXb1nsEJYtVTkSG8m4sDyEjI973/hJ9SQIgiBOL1UpYppaqKI8m5BxUdir4LgChlaVh4ggCGJZUJV36ERYhT6LkBUFzHYFasIqWFUeIYIgiOVBVd6iFUVBXWy6kE0WsPqo6itDhiAIgjj9VGViBwCwcSE7mXIxOOqiLgqkMnxCwAydVUVSRzl0lWFjcw3aaqOIBHS4nGNoLIdD/Ul0D49V1Gd9NIiNzTVoiAahqwxpy0bPcBr7eoaRsx3f/WmMYUNzAu11hRg5FxhO53G4fwQnhiqLsTYSxBnNCTTEQjBUhozloGdkDPt6RpC1bN/9qQrDhuY42uuiiAYNCA4MZ/I4MpDE8cFURTHWhAM4ozmBxngIhqoiazvoHUljX/cw0hXEyBQF65sS6KiPIhY0IASQzORxpD+JoxXGGA+aOKO1Bo2xEAKaipztoDeZwb6eYYzlLN/9KVCwrjGG1Q1xxIMGAGAkk8exwRSO9Kcg4P/7Gg0Y2NRSg6Z4CAFdQ8520Z/KYF/PEFJZ/zECwNqGONY0xJAImYACJDMWjg+mcLg/WXGldmJ2qlbEgFNCNph0MJgqlDlpiBUErNqpiwTxri2rEDL0kt9HAgY66mM4NpjCc/t74Aq5TE8FCnaubcSm1tqS3wcMDXWRgrA9e6DblzjWhAN41+ZViASMaTG210VxYmgMz+zrgsPlYgSAs1c3Yltb3bQYayMBnNFSg+cO9KLzpPxNPRY0cNmWdsSCpTGGAzraaiPoaUrg6b1dsFz5Mjvb2+txZnv9hLV7McaacAAbm2vwwqFeHB1ISvcXCRi4bPMqJMKB0hhNHa01EWxsqcFTe08gZ8vHuKW1FmevbgCbNB8fMDQkwgFsaE7glcP9ONg3LN1fyNBx2ZY21EZKYwwVY2yuwZN7u3w9ZJzRXIN3rG2EOi1GExua4nj12AD2dQ9J9xfQNbxrcxsaYsFpsbckwjijpQZP7DmBdN7/QwYxO3S3JqYRCRi4clv7NAGbzOr6GC48o0W6z3PWTBewyZi6indtXoX6aHDWNpMJGTqu3NY+TcAm01YbwaWbV0nHuKOjYZqATUZXVVxyRiua42Gp/gK6hqvO7JgmYJNpSYTxri2roECumsHWVXXY0dFQImCT0VSGi89oxaqaiFR/hqriym3t0wRsMo2xEC7f2j7re05lY3MN3rG2qUTASmJkDBdsaMbq+phUfxpjuHJb+zQBm0x9NIgrt7aVCFI51jbEcd765lnbM8Zw7tomrG9KSPXHFIYrtrZPE7DJ1IQDuHJbB3SVbrvzSVUfzYksRA7Ux1QYWvmsxWph59omGJp32ZfV9TGpm2VNOIAtq2YXsCIqYzh/fbNUjOesaURA955IaK2JSN0sYwED21bNLmBFGFNw/vpmKdE5a3VD2QeBIk3xMNY3xT3bhQwd2zvqPdsBwPnrm8EU76/39o56RMs8CBSpiwRxRkuNZ7uAruKcNY1SMZ67rgmahOhsa6tDPGR6tkuEA9gqcZ3pKsPOtU1SMe5c2yj1XdjcWlNWZIvEggbObJc7h4QcVStiU5M4TJ3NmOxRbQSNwjSXLDJPqusbvW/QRWrCAdRFyo/GDFVFR518jBskYlzXFAdjciONaNBAUzxUto2qMKyRHGkAcsdxbWNc6qYPFKfZysdYWGOSPzfrGxOebVbXx6VHGgFdQ1td1LPdOgmBLyITY0ddFKYuV5tPV1WphyDZERsArJOIkZCnKkVMTBGw4hoYm5K1KFvZYyVRG/F+4p1MXdT76bNOcopwor3HE21NJDDrVNXM7+8dY62HcE5vX77PeNiE5mPaqDbsfdy9jsv09uU/UzRoSI0yiiTCpqeIyoxGJuP1mUKGLjWaLRIO6J4jdL/n2itGQ1XLThlPJaCrZafBCX9UpYiNpKcLWJHJQjacduEjJ2BFIPukX0SVmLJSJUc4E+09ql377k9iLcdvn14CpfnsjzHmeSx9f26Pc+k3RsD73Pjt0+szVRKjV7V039e4R3u1gjUuvzEQs1OVR9KZRcCKFIVMUxVYTnWpWDrnL3NKJtPKbzZWOlc+1d5vjGN579T9jM8YvVLE/caYsWzPTE/fxzFfPsYxn/3Zrou8R4ai/xg9zrXlgPt4knQ5R8ajzzGP4zKtvce5zlkOHFc+Ri6E57kh5KlKEUuEvNPomaKgJqJCkczIWimcHMsh4yNNWWYvlp/9Wo7L0TuSLtsmmc1j1Mcenq55jpFzjp7h8jGmLRvD6Zx0n/MeoxDo8ojRcgp7omSZ7xhl+nQ5R29SPsaekYznXiyZz1HS3mPbh4DwtTVkIJWB7UP0iPJUpYjJVuJQFAWGVl0iJiDw5vGTUm1ztoN9Pd77aI70p6Q3ju7tHpLaM/VG56BUf5bjYo/EXp/jg6PSorO/dwRZiY3ZbxwfkOrPcTl2d3nH2D08hsFUVqrPI/1JqQ3Fbx6XO44u53ir0/u66E9l0OPxEFLk2GAKIxnvY/7m8UGpTcKcC7zZ6X3Mh9I5dJ4clYqxe3gMg6Pex/zNEyelR4xvSB5zQo6qFDE/VNlADABwsG8Yh/pGyrZxXI6n93bDcrwFhwuOJ/ee8KzI0T08hjclxenoQBJ7PcTJ4RzP7O+W2gArIPDk3i7PUWhfMo1dR+XE6cTQGN7y+Dycczx7oEe6gsXT+7o82w6msnj5cJ9Uf73JNF472u8Ro8ALB3uRzOal+nx2f7fnQ8twOocXD/ZK9Tc4lsWrR7w/z8tH+jA0Jvcg8vzBHox4PLQkM3k8d6Bbqr+RdA4vHur1FNtXj/T5Gv0S3lR1xQ5idp4/2IOhsRy2t9cjYJReJn3JNF463IdkRu6mBhRuCD97/Sh2rm1C+5S06uJo6e3Ok75KB71ypA8j6Rx2zLAfqz+VwSuH+zDkY0pvLGfhZ68fw861jWivi5Zs7rVdF/u6h/Fmp9yooMjrxweQzORx9upGhAOlMZ4cK4iNzJN+kbRl48E3juKcNU1YUx8r2RbguBwHeofx+rFB6UoqALC76yRGsxbOWds4bc/YcDqHlw/7u/HmbAcPvn4U56xtxLqGWEkmqcM5DvaO4PVjA74qqezrGcZozsbOtY2IBUszOUcyebx6pE96BAgUrrmH3jyGs1c3Yn1TvCR5g3OOQ/1JvHZ0ALaPSiqH+pMYyzs4d23jtM3jqayFV4/2+Z7KrFb8ZIaTiBGzsr93GAf7RlAXDSJi6nCFwNBYrqK6d0Bh0f/JvScQNHTURwLQNYZ03sFgKuvrpjuZQ/1JHO5PoS4aQDRgjPvA5ZCqMMasZePpfV0I6Brqo0EYGkMm72BwNOvrpjuZo4MpHB1MoT4SRDQ4HmM6j5TkyGYqOdvFcwe68drRPtRFgzA1FVmrEGOlay2dQ6PoHBpFbSRQEAkhMJKxpKb7ZsJyXbxwsAevHe1HQzQIU1eRs10MpLK+hGEy3cNj6B4eQ004UNj8LASSWcvX2uNkbJfjpcO9eP3YAOpjQQTGYxxMZX2VAZtMXzKNn+w6gkQ4gETQABQFqUze18PUSsVx5R7+LJtjJCN//EnEiLJwITCQykBuAk2OrGWjc2j+6scJCAyOZn2NaLzI2Q5ODMmtm8gyOJbF4Nh8xujO+5P90FhOekpOBstxPRMj/DKczlUsXDNhuW7FBa1nYySd85yurDZsVyCddWFEZ5cdy+YYHHU9t0lMhtbECIIgiAVHVxWM5ThGZxllFQVMVxUkwvKb8EnECIIgiAVHUxVEAgyp7HQhmyxgdTF/W5toOpEgCII4LYSDKjSVI5UtrN1GQ+o0AZN1SyhCIkbAUNWKF7KnEjJ0KAqQyTsVmRRORWMMAUOD5bhS6fwyBA0dbBnEqLJCjPNhpKgyhqChwXFdX75g5QjqGlSVIZO35ydGhSFoanBcXpFB6kwEdA2aypDNOxUnD02GKQyhBYixmoiGClOFqSyH5QjkHVGxgAEkYgSA6955BobTOezpGsIRH2aKRQK6hu3t9VhdH5uoDm67LjpPjuHNzgGM+SzBBACraiPYtqoeddHAxIU9ks5jX8+wLzPFIoam4sy2eqxtjE3cNByX48TQGN48PlBRNmNLIowz2+pRHwtOxJjKWtjfM4T9PSO+BVJXVWxrq8W6xgSCxqkYu4fH8EbnoK8tDUWa4mGc2VaHxlhoIh1/NGvhQO8w9vUM+xYfjTFsbavD+qb4xLYGl3P0jKTxxvHBihIu6qNBbG+vR3M8NJGOP5azcLB3BHu7h32Lj6owbFlViw1NiYltDXy88sebxwcrSq6pjQSwvb0BLYnQRDp+Jm/jYN8IdncNwfWZucoUBZtba7GhOSFlhbPSiIZUWI5Azi5cf5UKGAAoQlSPX3YqlUI8Hsc9X7kDcYnK6pYjkLM4rru0BrVlMmpWEscHU3hmf7f0za02HMAVW9un7SUrYrsuntzb5VlKajLnrWsu613VPTyGJ/d0Sd/c4kGzYPJpzlwN3XE5ntnf5atk0kwO0JPpS6bx+O4T0mn5RSPS2W5oLud4/kAPjg7Ku0pvb6/Hjo6GWf8+mMrisd2d0qPwkKHjqjPbp+3TKsI5x4uH+zw3yk9mc2stzlnTOOsNbGgsh8d2H5cePQZ0DVdua0fNLCafXAi8eqQP+3rkH4Q2NNXgvHVNs1r1jKTzeHR3p7SrtKGpuGJru7QB7EpgaNTBD58aRsBgMDRlYgqxeJuJBdnECA0AkqNZ3HTr55BMJhGLlbfCocQOooSO+hjeIWlqaOoqLtvaNquAAYXRxbs2t0k/bW5ZVetpvthaE8F56+VMDXW14Lg7m4AB427Im1YhEZKzEdnYXFNWwIDCCOjCjXLO1+q4K3C5Y6Qyhgs3tqBe0kZkbUO8rIABQH0siIs3tUr1xxQFl29tm1XAgEIl/vPXN6NJ0vm6rTaKnWubyj6B10YCuHRzm1R/AHDZ5rZZBQwofI5z1zVLO183x8O4YENzWa+5RNjEZT7cuS/dJO9gvhKZvAbWUqshFpw52UMWEjFiGhtbahCTEJ1tq+qkvJ50leGs1eVvqEDhCXV7u3c7oGBCWO5mVWRza+20ShkzoTGGc9Z4v7fGGM7yEIciHfUxNMTKG1MCwBktCSk/KsYYzlnr/YDBFAVnS3wWoPBA0CpxQ1/XKHe8maJIPwTtlPgsANAYC6FDwphyTUMc9TE5cXiHD2dnGeoiQaxr9I5xVW0EzQk5kV+J2DMkcURD6pyEjESMmAZTFHQ0eH8hV0u0KdJWG/H0ZWqrjUi7AgOQctxd0yDvCtycCHuaRLbURKRdgQFIuTv7OY6NsZDng0NT3LtNyftLHUdvB+Yihaof5UW5IRb0ZQwpdRx9OGnHgoanOWYiHJhWPqrs+0tca2vq5a/HlQbnwHB65izEuQgZiRgxI/Ey00ZAIaPRz41SZQxRjxtbPOTPVdqrPVMUX467Mu0TIX+L8HGJ9v4/93wfR5kY/Tk2e7X3ur6m9+fd3ve58TrXPq4dQO44+o1xJWE5HFqZLMTJQpbOyQvZshGxu+++G+eddx6i0SgaGxtx7bXXYt++fYsdFuGD+TYEWAiDgWp0LZBdy/HX59KnGs/1YqKMezSWWwMtClk6J5/tuWxE7IknnsDNN9+M559/Hg8//DBs28Z73vMepNPyWW+EPF7FaS3X9WWeyTn3tOfwm0LuZQ3ChZD2MTsVg1eMPvuTeP+Uzz692vs9jiMS7ZM+CwF79Slr63Lq/WVinOdzPc/XDgCM+IxxJWFoilQljmhIRTggL03LRsR+9rOf4YYbbsC2bdtw1lln4b777sPx48fxyiuvLHZoK5JjEqncxwbkC+SeGBrz3EtzYmjMl837sQGJGH2kpHcPj3luVu4eHkPex2bh+Y6xP5VB2tPzLIOsJb8RV+pcD8qf6+F0zvMhaDDlzw1BLkb54ziatXDSY7/YcDonJfB+3t9PjCsNPyPfcKAKaicmk4VNubW1tYscycpjf8+w1Ahmd9cgchI3S8fleP2Ydx18y3GlTTEP9yel7C32dA0hLbHZ2uUcuyRidDiXdmzuPJmS8uHaJ3m8Oed47Uh5A0ugMAL1Mros0jNub+LFob4R6Y3Mr0rEKCDwqqS5aH8qI3XzPzqQknYyeOWonGmojBknUNjPdrjPu1DAiaFR9CVp9mg+WZYixjnHLbfcgosvvhhnnnnmrO3y+TxSqVTJDwD42d8t64GzUug8OYpXJL+4OdvFY3s6ywqZ7XI8ta9LuiLG7q6T2N9bfiNq9/CYtCuw7RZiLDf16bgcz+zrlr5J7+8dxp6uk2Xb9CXTeO5Aj1R/Lud4Yndn2ZGJyzmeO9grXW3iyEASbxwv/0AwOJrF0/vknIu5EHhiz4myYss5xwsHe9EreZPuPJnCqx5iMpzO4am9XVL9CQg8uedEWQsULgRePiJvTtkzksZLh3rB+ez3gWQmjyf2nJCu0PLUvi7PUSAhz7IsQ3HzzTfjrbfewtNPP1223d1334277rpr2u9H0i5iUeFZ5iSddWFXiYiNpHPY2z2EQ/3+yk4NjeXwk11HsL2jHmvqYxMp6o7L0Tk0ijeOD/o20XzpUC96h9PY2lZXsik0lc1jb/cwDniI3FSSmTz+364jhbJTDfGJFHnH5egaHsMbxwd8r529erQfvckMto2XdCoymrWwr3cY+7uHfZWdSuUs/HTXUZzZXoe1jfGJ0lgu5+geTuONzkHf/lRvdg5gIJXBme11aIiFJq73sZyFA70j2Ns95KvsVDpv42evH8HWVXVYN6nsFOcc3SMZvNk54NuLbE/XEAZHCw7iTZNKY6XHSzrtOTHkq+xU1nbwszeOYet42aniJveJslOdg7595/b3DhdczjtKS2NlLBuH+5J4+8RJX4apedvFQ28cx5bWGmxsrpHax0jMzrIrO/XpT38aDzzwAJ588kmsXbu2bNt8Po98/tScdiqVQnt7Oz535+2IR0Nl63WNZlyMpF2EAwy/cXntii479cMX9s9L4VoFCkKmBkVR5q0orK6qCOqFAsXzVbg2bOhQ2HzGyBDUNVjzWBQ2ZOhgTBkvADz3wrUaYwgZCxPjfBXXVcdjdLiQLuHkRdDQoTEFGcvxXd9wJtRiAeD5jFHX8Evnb5yXvpYqU8tOeeGn7NSyuTMLIfCZz3wG999/Px5//HFPAQMA0zRhmtP3lyRCKixX4GTKnVHIRjMuUlmOSIBB9eEwulyZr8rrAgLp/Pw5NgOF6cBK7exnwysxwi+2y2G785t15ifzUwaH84qKHJdjvmN0OcfoPMc4X0JTxBULEOM8PVRUK8tGxG6++WZ873vfwwMPPIBoNIre3sKaSDweRzDorw6ZrjPEAioGR91pQlYUsFiQwTQYctbcn94IgiCIhWHZJHbcc889SCaTuPzyy9HS0jLx8/3vf7+i/gydoT6qwh4fkXEhSgRsckVlgiAIYmmybEZiC7F0VxAyYHDURc9QYUhPAkYQBLF8WDYitlAYOoOp8QlztnBw2QxOTwsKFNRFA4gEDLhcYGgsO+d1r4CuoT4agKaqyORtDI7m5py8UBcJIho0wLnAUNrfRtqZY1RRFwlC11RkLQeDqeyckxdqIwHEAgY4gJGx3JzXqAxNRUM0CKMY42jWV5bcTNSEA4gHDQgAw+m856ZlzxhVFfWxIExNRc4uxGj72NA+E4nxGIFCZZBKzEIno6sM9dEgArqGvONiIJWd8zpsPGgiETahoFD5oxKzUEKOqhex0YyLnC0Q0BXkndmTPaqRDU012N4x3W6lZySNVw73+S4dFDJ07FzbiLa6aMnxzdsu9nSdxO6uId9uyGsb4jiro2FamnJ/MoOXj/T5vnkEdA071zaioy5W4iFlOS72dg/j7RODvjMaO+pjOHt1wzS/sMHRLF4+3Od7z5Cpq3jH6iasaYhOpHsDhQST/T1DePP4Sd+C21YbwTlrmqYVQD45lsUrR/oxILFpezKGquLsNQ1Y1xgvcS9wXI6DfSN4/diAb8FtSYTxjjVNSIRLk7VG0jm8cqRfen9aEY0VLII2NCWgTXJPcDjH4b4kdh3r9y24TbEwdq5rnGZbk8rm8eqRfnRJbCwn/FHVw47Ja2B1MW3aGlk1c/76ZlywoXnGSvUtiTDee9aakv1RXsSDJt5/1hp01MemPSCYuoqz1zTiXVvafBWjfceaJlx0RuuM+2wa4yG8Z/tqtPjwbooEDLz/rDVY0xCfZoJoaCp2dNTjiq3tYIr812Z7ewMu3bRqRsPL+mgQ79negbZaeZuTkKHjvTvWYF1TvETAgMKIYltbPa48sx2ah+3NZLauqsNlW9pnrOBfFwni6m0dvixtArqG9561Ghuba6bZ72gqw+bWWly9vQOGKj9tf0ZzDa7c1jFNwIDCyOyqMzuwoSkh3Z+hqnjPjtXY3FpbImBAQdzOaKnBe7av8WW7s7YhjivPnNlVOhY0cfnWdmxqpQpD803VithMSRxTkz2W2Ra6eWNDUwIbm8u7K+sqw6WbVnn6bwEFi5N3bVlV1gEaKIwGdnTUS8W4pj6GLavK3xA0leGSTasQ1L0nHBQouHTTqrIO0EDBc0zGPBMAVtV4fx7GGC46oxURyQ2vF29q9XTJboyFpM0cm+JhnONhYsmYggs2NJd1dZ7MRRtbPNvWRYI4b32zVH/1kSB2SphYnreuCbWS/l/v3NjsafKZCJt45wY55+tEKIB3bmj2nMF5x5pGKaNUQp6qFLF0bvYsxMlCNjzmotp0TIGC7ZJCEjA0bGopL3YAsLYhJn0D3NxaK/WEvl3SXdnQVE+xA4D2+ihqI3I3wDOaExMVNcoh42YNFB4Itq6q82zXWhORHv2ua0pICaPsQ4PGGLa3e8fYEAuhRcIpGgDWNMSkfMK2d9RPGxnPBGNM6tqtCQfQXidnoNlWG0G9h3kmAJzZXjdtZDxjjIoifcwJOapUxMqn0ReFzHEFLKe6VKwuEvBldikzFbbKx3SZpjJP+/Z40PRldinz/m21cjdeoHCzbK0pH2PY0D2f9CezSuL9fcWoKFjlISaGpvqaEm6VECc/MQJAm0efKmNojsvH2JwIe46G/MbodW4UeB/ryTTGQr4czInyVOWRDAe80+gNnaEmrFbdlKLfOm5hj+k3ANJTZadiKD/K8RtjxPQeNcl8jpI+Pab0/MYYMnSoHmttfmMMm+VjjPjsz9BUzzUiv316HaewoUmNcIporFAWqhwRj+Myrb3HuQ7o6rR1tXIwRfE8N4Q8VZmdKOtVo+sMxvxWPFry+M0Yk8mCc8tUAJ+xvUfRZd/9STyI+O3Ty/fM8dkf59wzmcj35/Y4l35jBLzPjd8+vT5TJTF6OU/4vsY92vs9L5XEQMxOVY7E/ODjIXBFMDTmL21epmq538rmXu2H0zlwHzeBk1Ix+ktz94oxmcn7MvgcSuc9txf4PY5en3s0a/mqmzmSyXvefOf7XGcs25fBZzpvexY49nuuvY6j5boY9eGCkLfdOe9jJE5RZbdowousZUuZJBY52DcyL22KDKdznp5ZluOiU9IPCgAO9Xq//+H+ZFnPqMmM5iz0Jcvvm3I59+Xie0jCUPFIf1K6EnvGstE9XH7flIDAYR/WO4clzuOxwZS0eOdsF50nvR2jD/m4fmTaHj8p785tu67UefRzjR/ul29brfhZxiERI6bxyuE+qSf0zpMpKXPB4XGvMi8453jpsJzZ5WtH+qWsWXqGx3BU4iaUylrY7WF0WYhR4MWDvVKbsncdG5Cq9N6fykjdfNOW7Wl0WeSlQ71SVVDelPR7OzmWxb4ebx+3nO1Iu0q/cqRPalrt7RMnpfzeRtJ57O7yvs5s1/U04yzy6pEBqe/Cvu5hqY31ozkLb3Z6X2crEdnJEy4ERtLyMwQkYsQ0UjkLj+0u74Z8fDCFZ/bJORcDBcv6co7NluPiyb1dGEjJTfWkLRuPvn0c6dzsMXYPj+GpfXKuwADw+vEB7ClzE7RdjmcOdEtXhsjZDh59q7PsVFNvMo0ndsu7Au/uOok3O2evGuK4HM/u78YJyZGq5bp45O3OsqWbBlJZPL77hHQBgP29w3jtaP+sI1uXc7x4qBdHB+RGgQ7nePSt42VF4uRYFo/u7pQeqR7uT+Llw72zTktzzvHqkT4c7JMzYHUFx6Nvd5Y13BxJ5/Do28fn3VpouWA5HLZd/vxwUdij67WuOZmqTOwgvBkczeLHrx7BGS01aKuNIBLQ4boCQ+ksDvUlfZfPERB46VAvjg6kcEZzAvXR4ETtxO7hMezrGfZt1jiczuHHrx3GxpYE2mtjiAZ0cFGonXi4L4nOIe+pqqm8erQPxwdT2NhSg4ZYELqqImvZ6BlJY1/3sG8PrWQ2j5/sOoINzQl01EXHaycKjKTzONyf9DXlWOSN4wPoPDmKTS01aIiFYGgqcpaN3mQGe7uHfNe2HMtZ+H+7jmJDUxwd9VHEg+ZEjEcHUjgiKTaT2d11El3DY9jUUoOmeLgQo+2gbySNfT3Dvj250paNn71+FOsa41jdEEM8aEJAIJmxcGwwhcN9Sd8ly/b1DKNnJI1NLbVoiodg6hosx0FfMoN93cO+y6rlbAcPvXEMaxtjWFMfQzxsQoGCVDaPY4OjONQ3UtWVgBRFwXDaha4pMPTp46eigNmuQMJHEXYSMWJWbNfF2ycG8fYJuSksGQZSGd91+MrhcI49XUNlR1B+GRzLYvCAv8X/cricY1/3EPZJTKnKMpzO4fmD8iNhL7jg2N87XHa07JdkJo8XD8lND8vAhcDBvhFf609epLKW9BS2DMV1Rj9rjdWCoSlwuYLBURf1UZQI2WQBq4+qyOZ8bFlYiGAJgiAIYjKKAtREVOhqQcis8anFqQI20yitHCRiBEEQxGlBURTUxU4JWd7mcxIwgESMIAiCOI2wcSHTGDCYcmE5lQsYQCJGEARBLGMosYPAWR0N6EtmfJsKTsbQVLTXRZEYr0o+mrXQOTSGrM9svsnUR4NoSYQR0DVYjouB0ayvjdjTYlRVtNVFUBMOQAEwmrNx4uQo0nOIsTYSRGsijKChwXYLrsDdw2nfmXJFdJVhVW0UteEAVKYglbPQNTQ2pwoPNeEAWmsiCI3HODiaQ/fwWMWZchpjaKuNoDYSgMoYxsZjnItTdTxkYlVNBGFTh8M5To7mcGJorGLHb1VhWFUXQV0kAI0xpPM2uobGfGccTiYWNLCqJjLucs5xcqwQo2xa/1SKRZrrot5V8lcSE2n0HKiPqUhl+IzJHrKQiBE4s70eZ7YXMt6eO9Dj2w15S2sttnc0TKvMvXMtx57uIbx+bNDXTT1s6rhoYysaZ6hePpLJ47kDPb5LB53RXIOz1zRAn2Lz8o41jaf2Nfm4qQcNHRduaJ7RdmQ0a+G5gz2+szDXNcbxjjVN04rsvmNNIw71jeCVw/2+HJsDuoYLNrTMWLV9LGfhhYO9vh9cVtfHcO66pmlWNO9Y24TDfUm8dLjXV11AQ1Nx/vpmrK6fbo2SsWy8eLDX93aOttoIzls/3dD1nDWNODqQwkuHemH52KulqwznrmvGusbpxqA5y8FLh/tw/KS/rRItiTAuWN/iu1D0ckcIgZMpXrIGVhdTcDLlVixkNJ1ITFATDuDd2zukjQWBgrvyO9Y2zWgtwVjBafjiTXLGgkBBwN6zY/WMAgYAiZCJd5/ZgYaY/NPr9vZ6nLe+eZqAFWJUsLm1FpdubpPuL6hreO/21bP6ZkWDBq7a1o7muLyr9JbWWly4sXXGKvFMUbCxuQaXb2vztBkpYuoq3r199ay2I5GAgSu2tvmyENnYXINLNq2a1UttXVMcV23r8KzGX0RXGd59ZseMAgYUKvu/a0vbrH+fibUNcVy2pX1WO6E1DTFcdWaHtPO1yhiuOrNjRgEDCp56l25ehfU+XKXb62K4fEt7FQoYMDw2PYmDTUn2sDw2RE+FRIwoQVdVXLypFQq8b5bN8bCU4eTq+hjWz3ITmMqFG1s8/cw0leHijaukbpb10SB2SBhottVGsKlFzjr+/A3eT9DquGOzjG9UTTiAs1d7OzE3x8NS5pkAcO7aJk/PNcYYLtzYKuXOHQsYUm7R9bEgtnfIxXjOmkYkPB6YmFJwlQ5KeNyFDR3nS7hF10YCnm7WRc7qaECdhCnmueuaPC1bgMLo+J0bmqVMPlcaliPgzJKFOFXIvCp7lLx2vgMllj+xoCllHLi1Te5mJdu2NhJEk+ToJRzQ0VHvbXYpe9MvtPUWMdljAwBBQ8PaBm/x3txaK31T29Ra6zkaCxs61ki8L1AYsW2QGEVsaq2FKjl6OaOlxrNtQFelH2x0VcUZzQnv922tkfb1Wt8U93QQ11WGjRLvCxTWCWVczjc0J6QeGlYiQgjUhGfPQpwsZCMZqp1IzBEvd2WmKGj0MaUXC5qeIyw/Dr6Ad4wA0OSjz5Cpe45e/Mfo3V6mTZGArnqOXmabip39/b2Po0ybIrqqot4jWaEhFvZldikzNevnXKuMeU5JF0qj+YlR4lz7PDcrCUNj0D3WuybS71X5kSqJGDEjAQ8HX0NTpZ/MZfsMGv7yjLz6UxXm+6k3qJcXWv8xek+DzbbGNGsMp/k4yrbx097rM0zrz/BuH/R7HD2Ok9/zEpA47n7PzUpC9nbBFAWJsPz1QSJGzIiX/YTlcGn/rYnXeGSE5X0YNBZjKIcruC9jSpkYcj5jlPlMlqS3lWyf/o+jd3u/fc53jDLtfffpcdzn+3oEIGUfRBQqe8hCIuZBtbqI93lYonDBPc0rJ5PO2RgrY5sCAP0eRpPT2kuksMu0KZKz3bKWJAAw4DtG7xR2PzHarothD/dtvzH2Jb3P44BEmyLFfV7l6Je03JloL/H+fq4fzgUGytimAAUnBz8O4n0S2xXms/g1UaAqRSydk3R1tbnU09VKI5O30TnobWMiY5JYZG+PdwX3/lRG2t4+ZztSflR+YtzfM+S5n20onZO+WVqOK1XNfK+PGA/0jnjuFUvlLOlN4Y7LparC7+sZkt5Hd6Q/6emZlbVsaRsal3Op6vr7e4elRefYyZSn9Y/luDgyIBcj5wL7e0Y82x3oHfE9O0CUp0pFjGPUI/vFsjmG066vYe1KgHOOZw/0SG2qPT6YkhKS3mTBi0uG5w70eE5vcS7w/IEe2BI3g+7hMRyQuAEOjmbx9gk5q5TnD/ZI2du/eKhXqt1AKiNlJTOczuFNSWfnFw/2Imt5+7O9fLhXqqrKUDqHtzq93zuVtfDa0QGpGF8+3FfW1LTIa0cHpCqWpLIWdh3zfu+xnIVXj0g6Ox/tl3KVfrNzECMZ7wewdN7Gq5LO14QcVSli4QBDKju7kFl2oQyKpiowtOoRsYxl47HdJ6SmRYo8u78He7tnf0o/MpD05Vw8ksnhkbeOz3rjyFkOntx7wlcVhxcP9eKtzsFZn9KPD6bw6Nud0iWORnMWHn7zGEZmqWySt108tbfLl+Hlq0f78PrxgVlLGJ0YGsPP3zouXQ0jbdl4+M1jODnLlK/luHh2fzcO+fC9erNzEK8e6Zt1JNEzksbDbx6Tdi7O2Q4efuvYrG7etuvihYO92Ccxii+yp3sILx3qnTXG/lQGD795XHptynJc/Pyt47N+JxyX4+UjfXjLh+fegd5hPHegu2odnucbRYjqsRpNpVKIx+O45yt3gKkGUlmOWJAhOslFtChguqogFmLI2wLXXVqD2ujKzSo61DeC/lQGxwZGfZU1mkwsYGB1QwyJkAlFOeVm67eEVRGmKGiri6I5HkLQ0Au1E1MZHB1I+SprNJlIwMCa+hgSYRNMUTCas3B8cHTWG70XChS01UbQXBNGaDzGwdEsjg6kKr5BFfZ4xVATKdROHM3a6BxKzXqjl2FVTaRQO9HU4YzXdzw6mJJK6JiJoKFjTUMUdZEgVKZgLGfjxNCYr4efqbTWRNCaCCMc0OG4HINjORwbSFacCBHQNaxpiKEuEoSmFmLsGh5D70jlMTbHw1g17nLuuAJDY4VznfXpSF7E0FSsbYijPhqQ3te3XBkadfDDp4YRMJjUwCA5msVNt34OyWQSsVj5ii0r987sQVG4Ulk+8f/JAlYXU1H4jq98jZ8Ph+BUzsKbEtNNsnAhcHwwheM+RjNejOUsX0/MXggIdA6NonPIe/1QlrRl4+2uk/PWHwB0DY/5rj9Yjqxlz6uTNlCY9p1Lceep5GwHe+fRSRsoTIvPpUj2VCzHxb6eIezrwYoXsYWkakUMKBUyyxHIO2JCwApVEVa+gBEEQSxnqlrEgPERmCOQswuCdUrACIIgiKVOVSZ2TMayOfLOqRFXOkvprwRBEMuFqh6JTV0DS2d5yRoZQRAEsbSpWhGbKmBMUaYle5hGdQ9UmaJgdX0MbbVFN1uBk2NZHO5PVpx1GA0Y2NCcQH0kCF0rOO72DKdxqD9ZkUOuAgWr66Noq4siGjDAucBQOofD/cmKsw4jAR3rGxNoiAVhaCoyeQc9I2kc7h+R2ps2Ex11MbTXRREN6gVfpXQORwZSFVdwCBk6NjQn0DgeY9Zy0DuSxqG+pC/Dx8m01UbQUR9DLGhACCCZyePIQKrirMOgro3HGIKpq8hZDnqTGRzsG6k4M7K1JoLV9THEQ4VCzcm0haODSfRUmHUY0FWsb6pBUzyEgK4iZ7voH4/RazP0bDTHw1jTEEM8ZEJRgGTGwvHB1Lwm1xCnqEoRs22OtO1OSeIoMFnIQq6A6qOa8koiFjRw6aY2JMJmye8bYkFsbq3F3u4hvHqk35dj87a2euxoryupXl4TDqCtNoqtq+rw9L4uX6WsIgEdl25qQ22ktKp7fSyIM1pqcLB3GC8d7vPl2LyptRbnrG4oKW5cEwZW1Uawta0Wz+zr9lUmKmjoeNfmVdOqutdHg9jYXIMjA0m8cKDX19aGDU012Lm2saTCek24cIPf2laHZ/d3+7qpB3QNl2xqnWaDUx8NYn1TAscHU3juQI+vrQ1rGuI4f31zqZ9aGGipiWDrqjo8f7AHJ3xkdRrjPnetU0w86yJBrGuKo2toDM/s97f3qr0uhnduaJ5WJLolEcbWtlq8eLAXR31kx+pqwZ+tva7UIqguEsS6xjh6R9J4en+X1AZ4Qp5lNdR48skn8YEPfACtra1QFAU/+tGPKupnJDOzgBWJhlTEggxjOQ7Hrb4MxaCh46ozO6YJ2GQ2t9bivPVN0n1ua6vH2asbZrXfCAd0XHlmO+LB2d9zMoam4qptHdMEbDIbmmtw4cYW6Rg3tdTi3LVNs1bnDxk6rtjaXvY9J6OrDFef2VHWlmRtQ9yX8/X6xjgu2NA8q0VIQNdw2ZY2NMTkLD9UxnDltvayPm4d9TG8a4u883VHfQwXlzEENXUVl25ahRZJexemKLhiW/s0AZvMqtoILt8q73y9qiaCSzbNbghaMIddhfZab886oDAjcNmWtmkCNpnmRBhXbG2Xdr4m5FhWRzOdTuOss87CN77xjTn1o5URsCLRkIpIgMGuQhF7x5pGT+8voGBX3yhxs4wFDOxo9zan1FUV52/wduYFgHNWN0g56a5piJe9+RUJGTrOXu3tAK2pDO/cICeMOzoaPP3JAKC9LorV9eU3dAKFqa+d67wfHFRWiFHGnfvMtjrUePiTAYXRyXoJ80xdVXH+Ou9zyJiCCza0gEnc0De31nr6kwFAYyyEMySMKVWF4fwNzVKCd/76ZmgSHiIbmxNShq51kSC2tMk5iBNyLCsRe//734+//uu/xoc//OE59ZMIy6XRh4MFl9FqIqCr6CjzNDkVmZvG+uaEtAFiYyzkeVPVVYY1kq7AAHBGs0SMTXFpA8SacMDTUJEpCtY3zW+Maxvi0D3ciIvEggZaarxvqjKuzkVkYlxdH4Mp6RUWNnUpl2xZd+VCW+8Y2+siUg9pQMEjTMZB3F+M8m0Jb5aViM0Xfor6+nEYXQnURoJgTP4z10e8n5BlnqL9tK8JB6Sejv28v+8YPT53ImRKCw4A1EW9R0N+Y6zziDEWMKSMHIvURgKeU2H1Ep+jtH35GIO6JjXiLhILGp4iOt/Xo64yT7ftyYQMHWFTTkQJb1Z0Ykc+n0c+f8p7KZWavxJGK5XZ1jFmba95t/fdp0f7+e6v0Mbflgovx2i//amMQVVY2QQP2ZFiEcPj3PjtDwB0TYFbpvC8/3NT/oFJ5vqa3qdaNnlC9+n27XUuNZ/neiKGvHcFf8KbFT0Su/vuuxGPxyd+2tvbFzukJU9Gwr6jpL3EF1HGEsRPn75jlLAakWkzmXS+fAxpn/3lbNczQ9HvcUzP83F0XO5ZkNf/uSnfPms5vrJLOefIepwbmWu2pL3Huczbju/tIX5jWAn4KTUv6/kIrHARu/3225FMJid+Ojs7FzukJc/J0ayvFOBuiVRuP4VdOefo9TCdHE7nfN0E5j1GIdAzUr79WM6S8qEq4tUfIPc5SvocLt8+ZzvSJqQApNL2/e7X6vaI0XY5Bn1U8O9PZT0fBub7OHIh0OfDVXpwNFvxPrnljOUIyJimjGZcpHPyDwUrWsRM00QsFiv5IcrDhcBuySrqtutir4TZ5aG+pLToHOxLSm0yffuEXIyOy6Uqrh8dGMWopOgcHUh5jnIASJlIAgXhlvk8nYOjs3qYTeX4YArJbN6znXSMQkjF2D08hsFROdHpGR6T2pD+pg/ngbckYhxIZaQ3cPenMlKV6/24I8ge85WGEALDY27ZkfVoxkUqyxEOyEvTshKxsbEx7Nq1C7t27QIAHDlyBLt27cLx48cXN7AVxp6uIc+NqJxzPLe/R8oV2OEcT+3r8qx2MTialXa93d87jKMe1vFcCLxwqFfKFZgLjqf3dXk+IQ+nc3j5sJwr8JGBJA72jXi2e+lwP5IZb8EREHh6X7fnlF4yk8eLh3ulYuwcGpWyLHntaL90BZRn9nd7TsGN5iw8d0DOAqh3JC1143/j+IC0OD27v8fTVTqTt/Hs/m6p/gZSWbwmce3u7jpZtZU7DI3BcQVOpmYWsqKAxYIM4YD8OuOyErGXX34Z55xzDs455xwAwK233opzzjkHd9xxxyJHtrIQEHhyTxfe6hyc0SE3mcnjkbc7ffloDY5m8fCbx2Z8SuecY3/PMB5567ivtYVn9nfh9WMDM1ZpSGUtPLa7E0cH5J2Lh9I5PPjG0RkrcnAucKhvxJdzMQC8cLAHrx7pm1Ecx3IWHt/TiYN93qPZIslsHg++cXTGaTsuBI4OJPHQm8d8TQm/cqQPLx3qnfE1GcvGU/u6fHlzjeUsPPj6MXQNzXyzPjaYwkNvHPNlJvn68QE8f6AbuRnW0HKWg2f3d/vys8tYNn72xlF0npz5QejE0Bh+9sYxqRF3kd1dJ/HMvq4ZBTxnF1yqZYRupcIYUBNWYc8gZJMFzG/d2qp1do5LpNlajkDO4ive2fm7z+yZ9W+GqqK5JoyIqcPlAkPp7JxchgGgNhxAfTQIXWVIj9f8q7ROHVDIiGtORBAN6HCFwPBYzldpqJlIhANoiAZhqAyZ8Zp/MqPO2dAYQ3MijFjQABcCw+k8+pMZX2W7phIPmmiIhWBqDFnbQd9IxndCyWRUxtAcDyEWKtROHMkUYvSTWDGVWNAo1E7UVOQcF33JjNTIeNYYFYamRAjx8U3kyayF3pEMeIWO5EDB8bspHkJgPMb+ZAajc4iRKQqa4iEkQiagAKlMIcZya3W/dfGWit9vOTDZ2RlCzFh4fbKAkbMzMW9Yrjuv7spAYcQzVGEB4ZmwXT7rE3WljKRz0utPMjic+6oVKEMym5da95LF5XzcBXreukQq6y/BxQtX8HEX6HnrEmM5a07COpVC4k+64qLEKx1DZ6iPAoOjLnqGCg+vlYzAiiyr6USCIAhi+WPoDKZ2ao9gOFi5FJGIEQRBEKeV0YyLnC0Q0BUoCmZN9pCBphOXEVk3iz3Z0vWrLcEtCKr+yugQBLHCcNLA0Culv6vdCWhyTgGnk6lJHEVvx5Mp17Mw+0zQSIyYV5ii+L4IvZjNGqVSFChS1dP9MN/2GgqUee9zucQoU31fluUQYzWRzk7PQiyskc2ctSgDjcQI/No7N6E/lcGe7iH0VrAYrTGGTa21WDvuZgsU9gEdH0xhd9dQRdUJ6iNBbFlVi+ZEGIamwnE5Bkaz2Nc9VNE+G1VhOKM1gXUNccRCJpiiIJ2zcfzkKHZ3nawoO7ImHMDWVXVoSYRh6iocznFyNIt9PSMVJZowRcHG5hqsb4ojPh5jJm+j8+Qo3u4aqig7Mh4ysXVVHVprIgjoKlzOcXIshwM9w74MH4soULChOYH1TXHUhAJgTEHGstE1NIa3T5z0lZJeJBYwsLWtDqtqIggYGjjnGBrL40DfMA73y2+RmMz6pgQ2NCVQGzbBGEPOctA1PIa3TpysKIkjEjCwdVUt2mqjCI7HOJzJ42BvEof6RirKMl3TEMfG5gTqJf3pljuOK5DOcSTC6rQkjsnJHidTLnRF/niSiBHQVIbWmghaayLY3zOMlyQ3ygKFL/cVW9un+WZFAwa2tdVjXWMCj+85gSEfjs1nttXjrCneXprK0JIIoyURxuG+JJ4/2CN94wgbOi7f2j7N5DMc0LFlVS3WNsbx5N4TGPCRlr+ptRbvWN1YUvFfYwxN8TCa4mEcG4zi2f3d0k+VAV2b0XAzZOqFB4TGOJ7a2yVVPaLIhqYanLeuscQGR2UMjbEQGmMhrG6I4+m9XdKu0oam4oot7aifYkMTMnRsbK7BmoY4ntnfNev+sJlY0zBu8jkpRsYY6mNB1MeCWNMQx1N7T3hulC+iqwyXbWmb5u0VMDSsb0pgdX0Mzx/swTEfAt5eG8VFZ7SWFExmjKEuEkTdhiDWNsbwxO4TsCT3D2qM4dLNq6R87lYStisQCcyehThZyNJ5qp1IVMgZLTXY3u5tDgkUbhhXbpsuYJMJGoWbc1DSv2l9U2KagE1lXVMc56xplOpPVdiMAjaZgK7i8i1t0pYfq+tjOHdtU1nLmtX1MZwrYWAJFEZgl29tK+sYbWgqLtvSJu18vaomggs2NJf1cWurjeCdG+VMSAHgss1t0wRsMrrKcOmmVdLO103xMC7c0FLWVqclEcZFZ6ySjvGSTavKmlNqKsNFG1ukna/rI0Fcsqm1bMX/xlgIl26Wj/HCjS1VJ2BAwbEgHCyfRl+cWnR8mBGTiBHTOLOtFmEJ0dncWoeoxI0/oKs4q6Pes53GGM5ZLSdOm1prpFyTz2hNlBWwIoamSjk7M4XhHWvlYtzYXINaCZ+p9U0JT+8voHADlnlvBYq0gK5piEu5c69piKMx7t1OZQw718q9t9eDQJG22ojUTb+tNirVjjGG8ySPz851TVKGrs2JsJQ7d3M8jA6JdisRWW9GQ2dI+NgzRiJGTIMxhtUN3l+0dY3yX8bV9THPZIq22oi0KzBTFKxt8HZOXifRpkh7bcTTD6slEZJ2BQaAtRIO1H5iLKxtlV8FaIyFfBlJysUof65l3r82EpB6uCgida59XI814YCnkWUsaPgy0JSJUeZYE4Cur9ACwItB9RTlKqXG4wajq8zXjVJTGaLB8jd/Pzc1mfYKFMRC8n0yxjyn62p8OPgCcp/J9+f2+Ex++/M614U2/j53jUeMvvuTOY6h+Y3Rj1tzob3McfR3bghvqlLEbFtukVgIAcupThVTPNLkvf4+E16p937T3r36UypI91c8prf8fmyZ95eYUStt7/ECv/3JpIv7Pd+ex9FnirrccfTb53z3J3EcKTV/3qlKERvJuLA8hIyPe99UUX3kEry8tSzH9bQEmQznwjO12W+NPa/2XHBPu42peH1uWc8xP+3n+3OnfKaQyxS79VsQ1/M4LkCMfj93yuPa8HteZM71XAoLEzNTlSKmqQoGR2cXMi4Km+4cV8DQqvIQ4fhJ72K1fvZC9SbTnmnSXUOjvqxYZGKUaVOkP5Xx3C/WPZye0Z5mLu9//KR8SvrQWM7zYaB3JOPLikUqRh8p6amshWGP4skDqQyyM9iqzOX9O32c60ze9nSMHhrL+tpTNt/XIyFHVd6hE2EV+ixCVhQw2xWoCauY52IRy4KjAynPmxAAvN15UmojM+ccrx8b8GyXtR0pp2ig4Pcks6+rsJFZIkYhsEsiRst18bak83VfMo1uiY3Z+7qHPE0ki+w65u1H5XIu7TQ8OJqVEogDvSPSN/RdEp5ZXAi8ftz7eAMFR4EjHgaoQMFBXMZcFAB2HRuQ2mcoc00ABeE+2Dvi2e7YQApDY/PnjkBUqYgpSsHHZqqQTRaw+qjqK0NmpdCfyuCFg3KOu2nLxlN7yzs2c87x3MFeaeuV148NeI7wTo5l8Zyk427OdvDk3hNlxZYLgZcO9Ulvdn6rcxBHPMw2R9I5PL1PLkbLdfHEnhOeYvvKkT5pe4+93UM40Fv+gSCVtfDU3i6p/hzO8fieE56jp9ePD0ibpR7qG8GervJmm2M5C0/s7ZLaNM4FxxN7TnhOIb99wvv8FTk2mPI028xYNp7Yc0Jq07iAwJN7T/ieliZmp2ordrBxITuZcjE46qIuCqQyfELADJ1VVVJHznKwr2cYu7tO+qpd1ptM42evH8HZqxuxqiZSknTQO5LGa8cGfFXrKHzJu3BGcwZbV9UhHDiV0Zi3XezvHcbbnSelq0wAhamrn47H2F4bKdn305/MYNfxft9Gn8/u70ZfMoNtbaV75fK2i4N9IwVXbB9To0NjOfx01xGcs6YB7XXRknqRg6NZ7Do2gD4f1ToA4MVDvehPZbG9vb5kT53tujjUl8Qbxwd9uVQnM3n8v11HcPbqBqyuj5VsAD45lsUbxwelRp6TefVoHwZHs9jeXleSDWi7HEf6k3j9+ICvsmWjOQs/feMIzupowNqGeEmMw+kc3jw+6MuRHADeOD6Ak6NZ7OhoKNnI7bgcRwdTeP3YgK+yZem8jZ+9fhTbO+qxvikOXa3MR4soUPXOzlwIDCYdFB+CG2IFAQOWnrPzQlWx//Frh6WnYcphqCpiIQOKUljk9pP4MRuxoIGArsFyOZLp/JyckIHC1oB40ITClPEYK3eULhIJGAgZGmyXI5nJz8kJGShs+o6HTDCmYCxnz8lReqFiVMdjVFmhBqXsdGg5wqaOsKnDcTlGMtac3JqBQrWWeMiApjKkc/acXK+LhAwdkYAOh3Mk05avh6mZYApDImTg/WevnVtgS7yK/WRnZ0PzztAkZ2fCF/MhYEBhWmxw1N+Ixov5dga2XY5BHyNDGebbGdjhHCeXeIwu575G2DKk83ZFBYRnwxV8Xh3EgcLU4XwIdhG+ADFWG9W36DOJiSxEDtTHVBha+axFgiAIYmlRtSI2NYnD1NmMyR4EQRDE0qUqRUxMEbDiGhibkrUoW9mDIAiCWByqck1sJO3CMEsFrMjkrMXhtItIgDKHwqaOSMCAyzlG0nlfWXczoSoMibAJXWXI5G3flRZmjNHQEQka4KIQo6z/1GwwhSERNmCoKjKWg1R27uuGQUNHLGiAC4FkOi/tPzV7jAoSIROGpiJrOUjOR4y6hljQhIDASCZfkaHpZBQoSIRNmJqKnONiZB7WfwK6NpFtmcrm55xApEBBPGwioKnIOy5G5iGByNTVQgIRFCSz+XlJICJmpipFzHEFWmcQsCJFIesfEbCc6h2NraqN4KyOhpJirS7nODY4il3HBnxnzRmqirNWN2BtY7ykWvxo1sJbJwYrcvFtSYRx1uqGEisTzjk6h8bw2tF+34kCusqwvb0BG5pLU5/HchZ2d3nvvZqJxlgI56xuLPHi4lyga3gMrx7t951woTKG7e112NBUU1L1P5O3sbtrCPt6yu+9mon6aBDnrG4ssVvhQqB7OI1dR/t9CyRTGLa11eKMlloEJsWYtRzs7R7Cnq4h30JRGw7g7DWNaEmUZtz1DI/htWMDUhv0S2NUsKW1FptbaxEwTt0Kc/b4dpMT/rabAIUixOesaUBzIlxSS7EvmcZrRwfmPWGHqFIRS4RmF7AiTFFQE1GRylSniO3oaMD29ukeYCpjWNcYR2sijEd2d0o/WYcNHVdt75jRfywaNHDhxlY0xkJ4XnKjNQBsXVU3ozkmYwyr62Nojofx+O5O6WzEgK7hqjM7ZqwSHwkYOH99MxpjITy7v1v6BnxGc03Bk2pKcVjGFLTXRdGcCOHx3SfQL7nR2tBUXLWtY0bjyZCp49x1TWhOhPCU5AZhAFjXGMcF61umFRZmioK22gia4yE8ta9Leg+YrjJcubVjRgPNoKHhnDWNaE6E8cRuuQ3CANBRH8PFG1tm9PZqqYmgIR7Cs/u6pfeAqYzhiq3THaCBwnVwVkcDWhJhPPZ2p/TMw6qaCC7ZtGpGA82meBjv2R7Ecwd7cVRyozUhR1WuiclW4lAURWpPw0qjoz42o4BNJmBouGzzqrKuvEUUKLh0yypPA831TQlsaa2VirG1JuLp7mzqKi7dsgqG5GbSSza1etqcrGmI4cz2Oqn+GmOhGQVsMrqq4l2b2zw9wopcfEarp3NyW23U0x27SG0kgAvWN5etjK+pDJdsakXYlPNRu2BDS1kHaKAwgt65Ts5cNB40ceEsAjYRI2O46IxWKaNUADhvXVNZB2igcP7O3yDnfB0JGLh4FgErwhjDhRuafdvQEOWpShHzQwWOI8ueszvkboCRgIGNLQnPdh31USnnYgA4s71eShhlXJiBwubUTRLC2FoT8bypFdm6qg6G5i2MZ61ukLLnMHUVW1d5C2NjLCRta7+5pQZBCfPOszoapJyLdVXFtjbvGGvDASmHY6Dw0CLjSbejQ+6a0Mangr2IBQ2sb0rIhIi1DXEpX7HtbfWehqpAQch2SH6/CDlIxIgSasIBRCWfZgGgo877htVeF5Xuz9BUNCVCZdtEAoavp9kOifeXaVNEU5mnmAR0DY2x8p/D7/v7OY6MMazyiFFXGZoT8hUd5vtcM0VBe235GJnC0OrRZjJttRFPz672WvkYC+2937+tTj7G1kRISpSrGT+Z4XQkiRL8CBgAzylCANJTPBPtPfr03Z+HozRQyecu36ff/sIB3dMUdL4/dyRg+DJ+NHXVcwTq+zh6tA+Zmq8bvqYyhMzyU7N+Y/Q67gFdkxqZF2GMSU/NriQcV26N1rI5RjLyGackYkQJgvvLxpKrLu63T4+/+47Ru43fEqJezSs5jl4x+D+O89sf4H2c5v04VhCj5/Xj9zh6DAoW4jiuRGxXIJ0tL06WzTE46kJT5R+uSMSIEoZ91lGUSWse9umf5NXniM8YZWrTDafnt89kNg/uYz9dMuO9N8lvjF7tR7OWL4PP0Zzluf9uvo9jOm/7MvjMWY7n1o8Rv8cxUz5Gy3F9beWwXRejPh3HVwK6qmAsxzE6yyirKGC6qiAR9jGyna8AiZXBWM5Cf1Iu3RsAjkjs7TosYWhYZDRneaab52zHl+XHkX7v9/ezRy1j2ej18PWy3cJeNVlkjuPR/qT0U3/edtHl8f5cCBzz4dgsFeNASlq8bddF56B3Srys95ds2+MnU9Li7XCOYxLXr8yxKXJ0IDXnzdTLEU1VEAkwpLLThWyygNXFVCg+prlJxIhpvHykT2pvTF8yjaMSN8GBVEb6RvTy4T6pdq8c6ZOqyjE4msWhvhHPdsPpHPZLbmR+5Ui/lJjsOtYvVfFiOJ3Dvp4Rz3apnIW93XIbmV89KncOXz8+iJyH0SVQcBPwMrAECgL/1gk55+vXjw1IVS15s3MQGYmRTjpn461O7/fO2a60q/RbxweRlai2sbvrJEYlNq1nLQdvHJdz3V6JhIMqYsFSIZsqYH7WaYEq3ezcl8xgVMayngOcK/jfVw5B1xd/07OrWMiEekt+91ZGhSr8LVR7MZzO4am9XbhkU+ushn39qQye3CPnCgwALxzohcbYrNlrLud46VCv9AgrlbXwxJ4TuHTTqpKqFZM5OZbFE3tOSD/1vnK4D4bKsKYhPuPfOed45Ug/jkuOXsZyNh7b3YnLNreVVISYzHA6h8d3n5D2ztp1dACGpmLDLCniXAi8fmxAemSZtcZj3NqG0Cwp+alsHo/tPiG96ffNzkEYmorNZbY2vNk5iH09cg8NluPi0bc7ccXW9hKT1MmM5iw8vrtTupTX3u4hmJqKM8vsh9zTNYS3u+QE2Xb5RIyzJYJk8jYe33NixhJU331mzwyvkMdAHh1K6b3huDgAC+X3PZ4ubJthaCwExgQYAxxXQV+SYXBUgAsFiiLgCo7u8Usi42PJoCpNMf/yzj9EyGNTK3BKxFoaM0tIxEqFI5RZNe8iNtG3oWPrqlq01UYRDujgnGNoLI9D/SM41JesaEqkoz6GM5oTqIsEoakMWaswNbi7a6ii+oRBXcOWVXVor4sgEjDAOcdwJo/DfUkc7BupaNG9rTaCM1pq0RAtxJizHfSMpLG7a6ii2n8BXcXm1jp01EcRHY9xJGPhyEAS+3tGKjJ/bK2JYFNLDRpiIegqQ9520TOSxp6ukxX5Uxmqii2ratFRHyvUd+QCyWweRwdS2Nc9XJH5Y1M8jM2tNWiKh6CrKvK2i75kGnu6hyryndNVhs2ttVhdH5vIMExlLBwbTGFv91BFNT0bYiFsaa1BUzwMQ1NhOS76Uxns6RqSrqIyGY0xbGqpwZqGGGIhE0xRkMrmcXRgFPu6h+ZcL3M2CiK2v+R3x8UZS0rEevpPiVjxdy4vjLpMwy3Zk5vJ5PGXd31ZyhSTRKwMy13EhBDYkzuBVUYd4qr8nqWZUKDM+zw+U5Q5OwxPhmKcH5ZLjADmNc75jhFYmGM5E8tNxDgHbEedyE7VVA5NO3Wc/IhYVU4nVgsn3VHce/JRcAhsC7Tj3PB6bAm0QVf8n/aF+CLO9w2DYpwfKMb5oxoTOLwoCpiiCBg6h+sqcFwGoFTIZCERW8G4gsMWDjgEXskcwqvZw0ioYZwXWo9zQuvQrtf7ygIiCIKYC1wArlsQMF3jUBSMCxevWMiWXXbiN77xDaxZswaBQAAXXHABXnzxxcUOackTVAzUahFEWQCjbgYPpl7HV/r+F1/uewBPjL6NpOt/7p8gCMIvjlMqYEU0TUBTC0LmOCs4O/H73/8+br31VnzrW9/CBRdcgK997Wt473vfi3379qGxUa4i9krjnwcewQlr5tRnIQQccJjj14SmqIipIQghYAkHx6wBHLX68b/Jl+Y83UgQBFEOzpUZBazI5BGZ6y7gPrHrr78eTz75pN+XzQtf+cpXcOONN+LjH/84tm7dim9961sIhUL4t3/7t0WJZynQaZ3EsDOGjJuf9pPlFgxFhY7SFHRFUWAyHTVaGAk1DDE+3fjPgw/jrp4f4IGRF3DcGqjK0jgEQSwQSiGBo9wKxuQRmSy+H7mTySSuvvpqrF69Gh//+Mdx/fXXY9WqVX678Y1lWXjllVdw++23T/yOMYarr74azz333IK//1LGVHRE1Mo8ipiiIKyYCDMTjnAnphsfG30Lq/Q6nB/eiHeE1iGqylmpEARBzARThJS1VVHIZPEtYj/60Y8wMDCA73znO/j2t7+NO++8E1dffTU+8YlP4EMf+hB0fWGqMw8ODsJ1XTQ1NZX8vqmpCXv37p3xNfl8Hvn8qb1HqVRhkyoDB4PMfg0FgAIdWRhS7RcWFzZcUVoVQAGf+JkruqIgrgYghMAYz2Nv/gS67AEcyB3Dpxoun3P/BEEsDDosMNhTfpcFlsB9q4AKhgAYBJhExqauysdd0eJHQ0MDbr31Vtx666149dVXce+99+KjH/0oIpEIPvKRj+BTn/oUNm7cWEnX88rdd9+Nu+66a9rvTWUMIcW7wKSjqHAUHavUPQiri5/8IMDBndKNrCaysBQXhjJ3EXOEQJq7yAsBHQq2mkFcFanF5eEQGtVdc+6fIIiFgYEjgNJ6nu3IgC+R3L00D6FfOQeaYkNTvAXKlWhTZE4r+D09PXj44Yfx8MMPQ1VV/MIv/ALefPNNbN26FV/60pfw+7//+3PpvoT6+nqoqoq+vtLaen19fWhuntlC/Pbbb8ett9468f9UKoX29nZAKFInV0CBK1S4QoezQFUx/CAUF+6Upy0BBXkuMDrLSIwBCCmzF9QUQiAjXKSFCwVAnOm4KlyLS8O12GZGJ+qYObQ8RhBLFgYXfMqDuSN0cMhXg19IXKFDQIGA3L0XPmaWfIuYbdv43//9X9x777146KGHsGPHDtxyyy34zd/8zYmd1ffffz9++7d/e15FzDAM7Ny5E4888giuvfZaAIVado888gg+/elPz/ga0zRhmtN3rGecIELC8ZyftVwDrlDBoYIvgUROAQXulAu1VQ8iVyYBI8NdqAqDOcntVggBCwJjvLCHLKCo2BmsweXhBpwXrEGInfqsi1+nhCAIbxRMzdPj0JaMiBXiUCb9zB++78wtLS3gnOM3fuM38OKLL+Lss8+e1uaKK65AIpGYh/BKufXWW3H99dfj3HPPxfnnn4+vfe1rSKfT+PjHP+6rHyEUZO0gwvrYrEKWc0xYjgFDs8bXxBZ/OhHg0Kasif1t8xpAzPxkc8LO4eaefYAoZARNTBeCQwdDu27iqnANLgkl0KoXxT4//kMQxHKhsM5fOktjLKHpRHt8DKZI5yMs4Ejsq1/9Kq677joEArNnwyUSCRw5csRv15782q/9GgYGBnDHHXegt7cXZ599Nn72s59NS/bwIqRl4IoE0nYYEX10mpDlnAByTgCmloOqCOiKDV3xtllYaIQiwERpBWymsIk6clPRFBuAQA4uRl2nMF2oanhfKI7LwnFsN0OTbA8W//MRBFEZCgTYlHUkbVw6lgK6ok9MJsokoSk+ynX5FrGPfvSjfl8yr3z605+edfpQFoUBQT2LtB3GqB1HSM9MCFneMZBzAghoOWjMhcN1ZEQMWAprYnDhqKWLt5oThiJmnjLIiSw0RYMrBN4RjE2bLswWOiUIYpnD4E4bc2VEfMlMJ2ZEYGJZZnqk0/FzW1r8hZ5FQmUcYT2NtB1Gxg4hpGdguacEzNQsuHxpDMUrpUUL4DN1G7BWD6FFp31eBEGsPKpWxIBSIUvlC0kpRQFbCSiKgotCdYsdBkEQxIKxvIca84DKODR2ap3JUFeGgBEEQVQDVTkSM3UVYbNQWSRt6RDQETJc2C6DzaOIB3NgCmC7DJarYnVDDPEyiSynC1c4GJ6yYatGi0OdY8Heg70jc3o9QRBzY0NzYm4dCAfIlT6ANwbiwBIp5p3MGdg/pMJQAV2ipJRjy2cnVvVILG3pSFs6woaNRDCPRDAPhytIZgPglPBAEASx5FkaMn26EQJjeRVpS0PYyCOk2xAC0BhHPMCRzAUxkjUR1vMQgkG4Nri7+NOMXDgAL02x564FZY4lpxgc70YEQSwYc76/CAfgU/ZfuRYwD+Xo5gPhKhBCQAgOISRi8uGgUZUilrUYFKEhpGcQVHMl514FEDUspPIRpFwNpuYgnx1Eni/+ZmcBDpWXXuw2y8OZ44A6rNDmZoJYTPKZ7Bx74MCUuqqFG9vSmGzL50MQfA2EYoFLbHYW4jTVTlyuZN0AGiIOwoYAML0slakCCWZhOBuEK1SYwXqYgcW/0bvCQcZNlfxOV2NzXhNLp1PejQiCWDAaQrG5dSAcID/FHNesXTJrYiYzoTANCgOYxJqY4qO4xNL4hKeZkG4jYqoo95RiaEAsYCFr61BUHUxd/EUyIRggSk8ZUw2wOV6oS6EuJEFUM0ydYzEFwQA2ZWOzaiwZEVNUHYqiQFGYlKeYXKMCS2OseZoJ6HJrQBoTUpk0BEEQxOJQlSLmB6Ys/giMIAiCmBkSMYIgCGJJ4SM5kUSMIAiCWHi4kFvn4gIYs+SLS5CIEQRBEAuO7TI4vLyQcQEkswG4Hu0mszRSV04zgjtwJbYhcK6CuxrymQHk3CWwT0xwqLx0L4jF8lCUue4Ty3k3Ighiwcil57hPTHDAmXKPcnnBd2oJkM+HALEayawOReShq9NvwEIAyXwYLhcI6WPSfVeliBVTPT3bodBO1Uyo2uIneHDBwd3SbEmmBsHmeKHaMjvoCYJYMFRtjlZJggNTXN+hBZeMiKmuCV3l4IIjZUUQN9Mlmd9cAKl8CK5QEQ+kkfPxXF2VIgZFBWO6dzPBoAgVmhGDbi6NAsDCKRUcTZv7ZufFL6hFENWNbibm1oFwADGlIIMZWzL7xDRhgDEVsYCDtGUglY8gEcyPCxswmgvAFQpqgnnoqopcXt7Mc2nINEEQBLHiURQgHsxBYwIjWROWw5DMBuBwZULU/EIiRhAEQZw22LiQqUxgJBeAzVnFAgaQiBEEQRDLGBIxgiAI4rQxOY0+EchBZxwjWRO2W5kckYgRBEEQpwUxLmDFNTBD4yVrZJUI2dJIXTndCBec297NOCtsv7BSsJfAXiouOBS3dD+J4zLwOabRGkjP6fUEQcwNe65OT2IGP7F8asmk2DtWAJy7SFkaOIC4OQZV4eDjy2BR00YqF8Jw1kDcTAPkJ1aeosOoZzsoEILDdfJw1bma1s0dITjYFFNMLhjEHC9U3Yd3D0EQ84/rzFFsBAfcKe4cSnbJiJjrKOMVOxgSgTFozC2pj6gAiJljSObDSOZCUFx5Va9KEVOYBlWdboY5FQ4GpqowQw0IBBb/Ru8KB2lnpOR3hpaYuynm6IhnG4IgFo6WcGJuHQgHyA2U/i7QsGT2ieXHvc3iQRsBXcNs0lOjOkhmNaRyEem+l4ZMEwRBECsaXeXQWPnKR5PT72UhESMIgiAWHFlvRqYAEUM+B4FEjCAIglhSKPJF7EnEvJD1wCEIgiBOP1UpYjlbbrHT4UrFG/AIgiCIhWdppK6cZjK2jrG8grAx+14x22VI5QwYKodwbXB38bMTuXAAXppGy10LijI3KxUGx7sRQRALxpzvL8IB+JS9Va4FzPHeMF8IV5nY2iSzvakk/96DqhSxoJpDOh+F4A5C+vQFRJurSOUjYLChKg7y2UHk+RIwxQSHOmWfmM3ycOY4oA4rc91pSRDEXMhn5roPdYbNztzFUplsy+dDEHwNhGKBw3sjs6DNzuUJGhyq4SBthaAwrWREZrsMo1YQmsoR1h3YXIMZrIcZWPwbvSscZNxUye90de5+Yul0yrsRQRALRkMoNrcOhAPkh0p/Z9YumX1iJjOhMA0KA5hEtXrFRwGGpfEJTzeKgojpQlEcpC0TisIQNmzYLkMyZ0JjAvFgHi5nUIQCRdXB1MV3dmYwUK+F5r1fXqWXAUEsFZhqzLEHA1iAe8N8oag6FEWBojC5zEMf6YlVffcqjsDSlg7bZbBdNi5gOTAFEoNegiAIYjGpahEDMDECs9yCHXY8mAWjrHqCIIhlwdJY9VtEiiOwIllbX8RoCIIgCD9U9UjMdhlGssU1sCyyto60VRCxcun3BEEQxNJg2YzEPv/5z+Oiiy5CKBRCIpGYc3+lAlZYAwsbNsKGjbR1SswIgiCIpcuyGYlZloXrrrsOF154If71X/91bn05LvIZHSqzETXSBSue8b8F1Dy4ZmIsH4CpulAVG/nMAHLu4u8TWyjCS8DwkyCqmVx68f0KF5J8PgTurgJXHLgy+8S4fAGGZSNid911FwDgvvvum3NfaSuMWJgjFsiCzWAaFzZsKFAwagUQ1G2omglVW/wU+4XCltlBTxDEgqFqwcUOYUFR3cJWJgWFNHsvFEqxL5DP55HPn9qknEoVNvVqKpAI2WDK7FOGkYAAhwvb1aAZMehmYMHjXSwWv6AWQVQ3uplY7BAWFE0YUJha2OzMJB6afZTLWjZrYpVw9913Ix6PT/y0t7cDKHjVyKTRB3UHmswBJwiCIBaFRRWx2267bXwX9+w/e/furbj/22+/HclkcuKns7MTgD+vGm0JVOogCIIgZmZRpxP/4A/+ADfccEPZNuvWrau4f9M0YZpmxa8nCIIgljaLKmINDQ1oaGhYzBAIgiCI04APdxVpz0dgGSV2HD9+HENDQzh+/Dhc18WuXbsAABs2bEAkElnc4AiCIIiy2C6DoXqn16ctHRlbfqVr2YjYHXfcgW9/+9sT/z/nnHMAAI899hguv/xyf50JF5x7V+QQnEFwwLFSsFfwXioD6cUOgSCqGnvxnZ4WFMcKgAuBVE5DIpieNbEuYxlI2xpCmvy+3GUjYvfdd9+87BEDMOEw6tkOCoTgcJ08XHXlbkbUfXj3EAQx/7jOik4Uh+so0JmNjG0imQsibqanJdhlbBMZ20RIz8IV5CdWFoVpUFXvhA8OBqaqMEMNCARW7o0+PTqy2CEQRFXTEk4sdggLSl41oKoa4pqNsbyBUSs+Ue4PKEwhZh0dEdNG2ACSjrw0rWz5JwiCIJYMGhNIBPNwuIJkNgAuMFGrtli71i8kYgRBEMRpQ1f5hJANpkNzEjCARIwgCII4zegqh66eyksI6pVbX5GIEQRBEKeVtKXDclUYqgsFYmJqsRJIxAiCIIjTxuQ1sEQwP22NzC9VmZ0I2RR7AQjBIFwb3F252YkM8t49BEHMPyv5/gIAwlUghEDGYsg5GsJGHiHdhhCAxjjiAY5kLoiRrIl4IOurvEdVipgQDrjrfZAEVyE4kM8OIs9XsinmCt9pSRBLnHxm5e5DBQqmmLazDjnHQMTIIKjmwCcV71ABRA0LqXwEIxkdzMf9tipFTFE0MNXwbgcGRWgwg/UwAyv3Rp9OpxY7BIKoahpCscUOYUExmQkOAyHDQSQgAEzfp2uqQIJZSOaCyNrypQSrUsSgyLqLsoIljKqDrWBLFl6llwFBLBVkHqqXM4qqQ2McIYOXvfcaGpAI5tGdXYG1EwmCIIjli6w3o65yREz5lHvKTiQIgiCWFBrzTrwrQiLmgR8PHIIgCOL0UpUi5nC5jy1EwQOHIAiCWJpU5R16LG96ihMXwGjegMAsxjcEQRDEolOViR0MDoYzQcTMNPQZnEaFAJL5MGwXCOl55DMDyLkreZ/YyjX8JIjlQC698veJcXcVuOLAhbe7s+DyBRiqUsQiZg6CmUhZEcTNdEkhSi6AVD4EV6iImlkIoULVTKjayl0csyWqlxAEsXCoWnCxQ1hQVNcsbFmC7PYm+RmwqhQxxlREQzaSWRWpfASJYB66ygtTiLkAXKGgJpgHoMJyVWhGDLoZWOywF4yVXfCGIJY+uplY7BAWFE0YUJgKhQFMJvNQoexET5gCxIM5aExgJGvCchiS2QAcrkyIGkEQBLG0qVoRA04JmcoERnIB2JyRgBEEQSwjqlrECIIgiOVNVYsYF0AyG4DLFSQCOeiMYyTrnX5PEARBLA2q9m5dFLDiGpih8ZI1MhIygiCIpU9VZidy7mIko8MRQNwcg6pw8PFlsKhpI5ULYThrIKxnIQTgWCnYK3gvlYH0YodAEFWNvXKdngAAjhWA4C6EYoPLZB4K771kRapSxMbyAZgBhpg5Bo25JfURFQAxcwzJfBij+SBCeh6uk4errtzNiLpCSfYEsZi4zsqe+XEdBUJwCAgIiX2pgpydy8OhoSZkQ1c1zHYIalQHwxkNjjBhhhoQCKzcG316dGSxQyCIqqYlnFjsEBaUvGqAqToYY1Alsr8l9kNPsLLlfxYipncaPVOAqGlBwcqt1EEQBLHcqUoRk/WqURTQnjGCIIglTFWKmB98lPAiCIIgTjMkYgRBEMSSQtbzESARIwiCIE4Djis3rWW7DGN5U7rfqsxOhJBN8wSEYBCuDe6u3OxEBnnvHoIg5p+VfH8BAOEqcDhDxmKIBWa/39guQzJnQlXktzRVpYgJ4YC73lmHgqsQHMhnB5HnK9kUc4XvtCSIJU4+s3L3oQIFU0wGCxnLAIONkD69eITNC9ZYqmIhrI9J912VIqYoGphqeLcDgyI0mMF6mIGVe6NPp1OLHQJBVDUNodhih7CgmMyErjEw5iDjhKAwDWHDnvi77TKMWkFoKkc8YGMsLS9NVSliUGTdRRkURYGi6mDqyt0vxqv0MiCIpYLMQ/VyRlF1KIqCkOFCUx2krYLTc9iwJ6YQNSYQD+bBFOYrLZzuXgRBEMRpozgCS1s6bJfBdtm4gOXAKtjSRCJGEARBnFaKIzDLVQEA8WC2IgEDKMWeIAiCOM0UR2BFsrZecV/LQsSOHj2KT3ziE1i7di2CwSDWr1+PO++8E5a1stNSCYIgVhq2yzCSLayB1YczCBs20paOtFWZkC2L6cS9e/eCc45/+qd/woYNG/DWW2/hxhtvRDqdxpe//OXFDo8gCIKQwOEKxvJGyRrY5DUyACVZizIsCxF73/veh/e9730T/1+3bh327duHe+65pyIRE9yBK+G5xrkK7mrIZwaQc1fyPrGVa/hJEMuBXHrl7xNz3TaM2iZ01UbUSENwoHgbDqh5cM3EWD4Azm0ILl+AYVmI2Ewkk0nU1taWbZPP55HPn9rflUoV9kMpsin2KLRTNROqtnJT7G2J6iUEQSwcqhZc7BAWFNU1YXMdGuOIB7KFNPophA0bChSk7SDgyI/GlqWIHTx4EP/wD//gOQq7++67cdddd03/g6KCMe/5V0UwKEKFZsSgm4FKw13y0MoiQSwuuplY7BAWFE0YYIqCsGlDU2e/90YCAgpz0J+Vr524qIkdt9122/ioaPafvXv3lrymq6sL73vf+3DdddfhxhtvLNv/7bffjmQyOfHT2dm5kB+HIAiCmAVd5VJ7mMOGjZC+TEZif/AHf4AbbrihbJt169ZN/Lu7uxtXXHEFLrroIvzzP/+zZ/+macI05RWdIAiCWBj8eDMG9GWyJtbQ0ICGhgaptl1dXbjiiiuwc+dO3HvvvWBsWewOIAiCIBaQZbEm1tXVhcsvvxyrV6/Gl7/8ZQwMDEz8rbm52Xd/wkeOhqwHDkEQBHH6WRYi9vDDD+PgwYM4ePAg2traSv4m/CjSOGNWADEhPMucZG3Nl8MoQRAEcXpZFiJ2ww03eK6d+cFxgZGMjlggM6uQZSwDaUtFULfhWCnYK3gvlYH0YodAEFWNvXKdngAAjhWA4C6EYoMrElt6hMRG3nGWhYjNN2EjDYfXIJkLIm6mpy04ZmwTGdtEUMtDBYfr5OGqK3czoq5Qkj1BLCaus7JnfFxHgRAcAgJCYl+qnxm2qhQxQ1MRCtoYyZoYteIlFgBpS0fW0RExbRgqYLk6zFADAoGVe6NPj44sdggEUdW0hBOLHcKCklcNMFUHYwyq6i1iErUoJljZ8l8GXeVIBPNwuIJkNgAuMFGEMmzYvut3EQRBEKefqhUxoFTIBtMhEjCCIIhlRlWLGFAQMn3S8DboY6c4QRAEsbhUvYilLR2Wq8JQXSgQE1OLBEEQxNKnqkVs8hpYIpiftkZGEARBLG2qMjsRQmAsryJtaQgbeYR0G0Jg3CaAI5kLYiRrIqznIQSDcG1wd+VmJzLI1ykjCGL+Wcn3FwAQrgIhCun1Min2fsoqVaWIZS0GRWgI6RkE1Rz4pH11KoCoYSGVjyDlajA1B/nsIPJ8JZtirvCdlgSxxMlnVu4+VKBgiin4GgjFAof3RmZBm53Lk3UDaIg4CBsCwPQq96YKJJiF4WwQrlBhButhBlbujT6dTi12CARR1TSEYosdwoJiMhMK06AwgMnsE/NRgKEqRSyk24iYKsotCRoaEAtYyNo6FFUHU1fuIhmvzsuAIJYMTDUWO4QFRVH1cY9IJmfJ4sO3pSoTO2S9ajQmStLvCYIgiKVFVYqYH5iyckdgBEEQyx0SMYIgCGJJ4cdhi0SMIAiCWHC4kFvn4qLg+SgLiRhBEASx4Ngug8PLCxkXQDIbgOvRbjJVmZYmuANXYhsC5yq4qyGfGUDOXcn7xFau4SdBLAdy6ZW/TwxiNZJZHYrIQ1en34CFAJL5MFwuENLHpPuuShErpnp6tkOhnaqZULWVm+Bhy+ygJwhiwVC14GKHsKCorgld5eCCI2VFEDfTJZnfXACpfAiuUBEPpJHz8VxdlSIGRQVjunczwaAIFZoRg27Kz9EuN1Z2wRuCWProZmKxQ1hQNGGAMRWxgIO0ZSCVjyARzI8LGzCaC8AVCmqCeeiqilxele6b1sQIgiCI04KiAPFgDhoTGMmasByGZDYAhysTouYXEjGCIAjitMHGhUxlAiO5AGzOKhYwgESMIAiCWMaQiBEEQRCnjclp9IlADjrjGMmasN3K5IhEjCAIgjgtiHEBK66BGRovWSOrRMiqMztRuODc9m7GGQQHHCsFewXvpTKQXuwQCKKqsVeu0xMAwLEC4NxFytLAAcTNMagKBx9fBouaNlK5EIazBuJmGiA/sfIUHUY920GBEByuk4errtzNiLoP7x6CIOYf11nZk2Kuo4xX7GBIBMagMbekPqICIGaOIZkPI5kLQXHlVb0qRUxhGlR1uhnmVDgYmKrCDDUgEFi5N/r06Mhih0AQVU1LOLHYISwoedUAFA3xoI2ArmE26alRHSSzGlK5iHTfVSliRCkbmhOLHQJBECscXeXQWPnKR8X0+3SWTDEJgiCIJYSsNyNTgIghn4NAIkYQBEEsKRT5gRiJmBeyHjgEQRDE6acqRSxnyy0FOlypeAMeQRAEsfBUZWJHxtYxllcQNmbfK2a7DKmcAUPlEK4N7q7c7ESCIIiFRLjKxNYmme1NJfn3HlSliAXVHNL5KAR3ENKnLyDaXEUqHwGDDVVxkM8OIs9XrikmQRDEQpLPhyD4GgjFAof3RmZBm53LEzQ4VMNB2gpBYVrJiMx2GUatIDSVI6w7sLkGM1gPM7DCt9QTBEEsECYzoTANCgOYRLV6xUcBhqoUMSgKIqYLRXGQtkwoCkPYsGG7DMmcCY0JxIN5uJxBEQoUVQdTV66zM0EQxEKiqDoURYGiMLnMQx/pidUpYuMUR2BpS4ftMtguGxewHJgCiUEvQRAEsZhUtYgBmBiBWW7BDjsezIJRVj1BEMSyYNnkj3/wgx9ER0cHAoEAWlpa8NGPfhTd3d1z7rc4AiuStfU590kQBEGcHpaNiF1xxRX4wQ9+gH379uG///u/cejQIfzKr/zKnPq0XYaRbGENrD6cQdiwkbZ0pC0SMoIgiOXAsplO/P3f//2Jf69evRq33XYbrr32Wti2DV33LzqTBay4BjZ5jQwADJVWxQiCIJYyy0bEJjM0NITvfve7uOiii8oKWD6fRz5/KjU+lUoBACzHRT6jQ2U2okYagp9K4gioeXDNxFg+AFN1oSo28pkB5FzaJ0YQBFEJ+XwI3F0FrjhwZfaJcUe672UlYn/yJ3+Cf/zHf0Qmk8E73/lO/PjHPy7b/u6778Zdd9017fdpK4xYmCMWyIIp02dUw4YNBQpGrQCCug1VM6FqlGJPEARRCapb2MqkoJBm74XiI8VeEcJHfY955rbbbsMXv/jFsm327NmDzZs3AwAGBwcxNDSEY8eO4a677kI8HsePf/zjWT/wTCOx9vZ2/NUdt6K1VnhmIaZyBmyX4QNnHkJ8BZtiEgRBLCTJnIGH962BobrQJTY7J8fyuOXPvolkMolYLFa27aKOxP7gD/4AN9xwQ9k269atm/h3fX096uvrccYZZ2DLli1ob2/H888/jwsvvHDG15qmCdOc7uAcMXJgirezc1B3IMSyGqwSBEFUFYt6h25oaEBDQ0NFr+W8oOaTR1qy+PGq0ahSB0EQxJJlWQwzXnjhBbz00ku45JJLUFNTg0OHDuEv/uIvsH79+llHYQRBEMTKZ1nsEwuFQvif//kfXHXVVdi0aRM+8YlPYMeOHXjiiSdmnC4kCIIglhZ+si9kPR+BZTIS2759Ox599NHFDoMgCIKoENtlUntv05aOjC0/vloWIjbvCBecz26IOdGMMwgOOFYKtjLdd4wgCILwxrEC4EIgldOQCKZnzQzPWAbStoaQJr8vtypFrOgw6tkOCoTgcJ08XDV7GiIjCIJYebiOAp3ZyNgmkrkg4mZ6WoJdxjaRsU2E9CxcQX5iZVGYBlX1XkvjYGCqCjPUgADtEyMIgqiIvGpAVTXENRtjeQOjVnyi3B9QmELMOjoipo2wASQdeWlaFokdBEEQxPJHYwKJYB4OV5DMBsAFJoquhw17on6tH0jECIIgiNOGrvIJIRtMh+YkYACJGEEQBHGa0VVeUn4qqFcmYACJGEEQBHGaSVs6LFeFobpQICamFiuBRIwgCII4bUxeA0sE89PWyPxSldmJkE2xF4AQDMK1wV3KTiQIgqgE4SoQQiBjMeQcDWEjj5BuQwhAYxzxAEcyF8RI1kQ8kPVV3qMqRUwIB9z1PkiCqxAcyGcHkedkikkQBFEJ+XwItrMOOcdAxMggqObAJxXvUAFEDQupfAQjGR3Mx/22KkVMUTQw1fBuBwZFaDCD9TAD/qvlEwRBEIDJTHAYCBkOIgEBYPo+XVMFEsxCMhdE1o5I912VIgZF1l2UQVEUKKoORpYsBEEQFaGoOjTGETJ42XuvoQGJYB7dWaqdSBAEQSwhZL0ZdZUjYsqn3FN2IkEQBLGk0Jh34l0REjEP/HjgEARBEKeXqhQxh8t9bCEKHjgEQRDE0qQq79BjedNTnLgARvMGBGYxviEIgiAWnapM7GBwMJwJImamoc/gNCoEkMyHYbtASM8jnxlAzqV9YgRBEJWQz4fA3VXgigMX3u7OgjvSfVeliEXMHAQzkbIiiJvpkkKUXACpfAiuUBE1sxBChaqZUDVaHCMIgqgE1TULW5Ygu71JfgasKkWMMRXRkI1kVkUqH0EimIeu8sIUYi4AVyioCeYBqLBcFZoRg24GFjtsgiCIZYkmDChMhcIAJpN5qFB2oidMAeLBHDQmMJI1YTkMyWwADlcmRI0gCIJY2lStiAGnhExlAiO5AGzOSMAIgiCWEVUtYgRBEMTypqpFjAsgmQ3A5QoSgRx0xjGS9U6/JwiCIJYGVXu3LgpYcQ3M0HjJGhkJGUEQxNKnKrMTOXcxktHhCCBujkFVOPj4MljUtJHKhTCcNRDWsxACcKwUbCW3uEETBEEsUxwrAMFdCMUGl8k8FN57yYpUpYiN5QMwAwwxcwwac0vqIyoAYuYYkvkwRvNBhPQ8XCcPV80uWrwEQRDLGddRIASHgIAQ3iImyNm5PI7QUB9woDIDMx5OBYiaHMkcYHETltqKvCpvDUAQBEGcwlJ1CMUAhwoOb4FyIW9CXJUi5nIVw9npzqJTEQJwuYLHDqyGqblgytyrdjiuAoczaIxL++tU8ppycKHAdhkUCOgqh8zm+EpeU45icWUBBbrKpY5tJa/xgs5HATofp6DzcYr5Oh8uV5DKG1AAqWOTzarSMValiDFFgEnMywooECgkgWQsFbGABY1VfmFkbQ1ZR0NIdxDU5WuDGWrhtRlbQ0jx99qpOFzBWN6AxgQipu3ry6YxBamcAS4URE2r4i+qGC+u7HDF9zE1VBejeYPOB+h8nIqBzkeRpXo+HEWBgsK9V5EQV0VitFakKkVMgQCTeboCwFQgEcgjbRkYyxsVb4ZOWzpyjoaoaSNs+J+a1FULKhNIWzpUJirqw3YZxvIGDFUgHsxJHYPSGACN5TGSNZG2jIr6KGaFcqGgNlTZsaxRc0hmA3Q+6HxMQOfjFEvxfBiqC0UpjMJkjokfEaM8cgmUKSWq/Kbfpy0daUtH2KjsgihSfH2xPz/YLsNI1oTGKvuCFtFVjkQwD4cr4182+ddO3dZQaWWUqSXD6HzQ+QDofBRZiucja/sbL3EhfwJIxCSp9MKYrwuiSCVf1Pn6ghap5Is6X1/QInQ+TkHn4xR0PgostfORsXW4XO7AOlyBI2hNzBOpFE4x/gMOIXgh/T6QQTIXxEjWRDyQLXuxFS4IDWEjj5Buw0fWaFlCeh5CcIzlDQjBy15stsuQzJlQGUcskIUCzEscGuOIB3jJsZjty88FkMwF4XIF8UAWGuPzEgOdj1PQ+TgFnY8CS+l8uBwYdoKwXQVGmRhcrsDmKgB5Aa1SEeOAxF6FwmXAwF0LfNLmu5ieRzIfwUjWQMwcg86mb8zL2IHCwqaeQVDNgcvv3ZMiqOYhtADS+QAEdxDSp2/GtnnBakZVLMT0MYBj5i0FFaICiBoWUvkIRjI64ubYtMXsgsFoBK4QiJlJqHDn/VjQ+ShA5+MUdD5OsRTOh8kcMJjggsF2BXQ2PVHEFQw2V6FAQCMR84IBEsZsEAoABUw1pnngJFQbyZyGUSs+7QknbenIOAbCpoWwIQB4p/NXQkQVUJiDtBWCwrSSJ07bZRi1gtBUjnjABlMWJgZTBRLMQjIXRMpOlDxxcgGkckFwMCSCWeiqhoW65Oh8FKDzcQo6H6dY7PPBFAaVCUBwuEIFuAJdPaWUhRGYBgUChurAZfIrXVUqYnLOoaKwqwEAm/YEpSpAIphHMhtAMhecmMdOWzoyto6IaSNsuFjoZceI6UJRHKStgnNq2LAnpkgKc/x5MBnBngOGVjgWI1kTqVwI8WDhqTeVGy+uHMxDV4GFPBZ0Pk5B5+MUdD4KLP75YICiQGcCjivgCga4CgzNhTM+hVgQMBfM56Jk1YrYfFBcPE1mAxjJmtBVDstV521RVJbie6UtHbbLYLts3hapZSkuZo9kTYxkCy7Y7jwtUstC5+MUdD5OQeejwFI5H4bmwnJUuEJB3lHBhTJJwPz3V1UiVkzmyOYtufZQChsPlTzUMpujFZHHWDYIADDUPBzkkZR7i3kkDztvIj2ehVQTzGI0fbpjABSeRzJTmI6IBvLIZE+/wSidj1PQ+ShC52MihkU4H65gyGYKM1rFPWAWV1GY6QJ0xYE76YEimysEJJOApwg/lRaXOSdOnEB7e/tih0EQBEFI0NnZiba2trJtqkrEOOfo7u5GNBqVWhNbSFKpFNrb29HZ2YlYLLaosVQKfYbFZ7nHD9BnWCospc8ghMDo6ChaW1vBPOYYq2o6kTHmqeqnm1gstugXzFyhz7D4LPf4AfoMS4Wl8hni8bhUO6rYQRAEQSxbSMQIgiCIZQuJ2CJhmibuvPNOmObCbLI8HdBnWHyWe/wAfYalwnL9DFWV2EEQBEGsLGgkRhAEQSxbSMQIgiCIZQuJGEEQBLFsIRFbAnzwgx9ER0cHAoEAWlpa8NGPfhTd3d2LHZY0R48exSc+8QmsXbsWwWAQ69evx5133gnLOu21hebE5z//eVx00UUIhUJIJBKLHY4U3/jGN7BmzRoEAgFccMEFePHFFxc7JGmefPJJfOADH0BraysURcGPfvSjxQ7JN3fffTfOO+88RKNRNDY24tprr8W+ffsWOyxf3HPPPdixY8fE/rALL7wQP/3pTxc7LGlIxJYAV1xxBX7wgx9g3759+O///m8cOnQIv/Irv7LYYUmzd+9ecM7xT//0T3j77bfx1a9+Fd/61rfwp3/6p4sdmi8sy8J1112Hm266abFDkeL73/8+br31Vtx555149dVXcdZZZ+G9730v+vv7Fzs0KdLpNM466yx84xvfWOxQKuaJJ57AzTffjOeffx4PP/wwbNvGe97zHqTTi1CYsULa2trwN3/zN3jllVfw8ssv48orr8SHPvQhvP3224sdmhyCWHI88MADQlEUYVnWYodSMV/60pfE2rVrFzuMirj33ntFPB5f7DA8Of/888XNN9888X/XdUVra6u4++67FzGqygAg7r///sUOY8709/cLAOKJJ55Y7FDmRE1NjfiXf/mXxQ5DChqJLTGGhobw3e9+FxdddBF0XV/scCommUyitrZ2scNYsViWhVdeeQVXX331xO8YY7j66qvx3HPPLWJk1U0ymQSAZXvtu66L//zP/0Q6ncaFF1642OFIQSK2RPiTP/kThMNh1NXV4fjx43jggQcWO6SKOXjwIP7hH/4Bv/d7v7fYoaxYBgcH4boumpqaSn7f1NSE3t7eRYqquuGc45ZbbsHFF1+MM888c7HD8cWbb76JSCQC0zTxyU9+Evfffz+2bt262GFJQSK2QNx2221QFKXsz969eyfa/9Ef/RFee+01PPTQQ1BVFR/72MekvHQWEr+fAQC6urrwvve9D9dddx1uvPHGRYr8FJV8BoKohJtvvhlvvfUW/vM//3OxQ/HNpk2bsGvXLrzwwgu46aabcP3112P37t2LHZYUVLFjgRgYGMDJkyfLtlm3bh0Mw5j2+6Lv2bPPPruoQ3q/n6G7uxuXX3453vnOd+K+++7ztFA4HVRyHu677z7ccsstGBkZWeDoKseyLIRCIfzXf/0Xrr322onfX3/99RgZGVl2I3lFUXD//feXfJblxKc//Wk88MADePLJJ7F27drFDmfOXH311Vi/fj3+6Z/+abFD8aSqrFhOJw0NDWhoaKjotZwX3F7z+fx8huQbP5+hq6sLV1xxBXbu3Il77713SQgYMLfzsJQxDAM7d+7EI488MnHj55zjkUcewac//enFDa6KEELgM5/5DO6//348/vjjK0LAgMK1tNj3H1lIxBaZF154AS+99BIuueQS1NTU4NChQ/iLv/gLrF+/ftksrHZ1deHyyy/H6tWr8eUvfxkDAwMTf2tubl7EyPxx/PhxDA0N4fjx43BdF7t27QIAbNiwAZFIZHGDm4Fbb70V119/Pc4991ycf/75+NrXvoZ0Oo2Pf/zjix2aFGNjYzh48ODE/48cOYJdu3ahtrYWHR0dixiZPDfffDO+973v4YEHHkA0Gp1Yj4zH4wgGg4scnRy333473v/+96OjowOjo6P43ve+h8cffxwPPvjgYocmx+ImRxJvvPGGuOKKK0Rtba0wTVOsWbNGfPKTnxQnTpxY7NCkuffeewWAGX+WE9dff/2Mn+Gxxx5b7NBm5R/+4R9ER0eHMAxDnH/++eL5559f7JCkeeyxx2Y83tdff/1ihybNbNf9vffeu9ihSfPbv/3bYvXq1cIwDNHQ0CCuuuoq8dBDDy12WNLQmhhBEASxbFkaCxcEQRAEUQEkYgRBEMSyhUSMIAiCWLaQiBEEQRDLFhIxgiAIYtlCIkYQBEEsW0jECIIgiGULiRhBEASxbCERIwiC+P/buWOVBcEwDMMPDbWEbtEZuBQ4hKuHUOfR3Ck4hlsH4NooTgmC4CIN4SwEQUsHEDTIv/2H8H28cF+j07PdvArCLCIGADCLiAEAzCJigEGfz0fr9VpZlv0/67pO8/lcdV17XAa4xQ+AAaOqqtLhcFDXdYqiSHEca7/f63w++54GOEPEAMOOx6Nut5t2u52GYVDf91osFr5nAc4QMcCw7/erzWaj1+ul+/2u7XbrexLgFN/EAMPGcdT7/dY0TXo+n77nAM5xiQFG/X4/JUmiOI4VRZHyPNcwDFqtVr6nAc4QMcCo0+mk6/Wqx+Oh5XKpNE0VhqHKsvQ9DXCG14mAQU3TKM9zFUWhIAg0m81UFIXattXlcvE9D3CGSwwAYBaXGADALCIGADCLiAEAzCJiAACziBgAwCwiBgAwi4gBAMwiYgAAs4gYAMAsIgYAMIuIAQDMImIAALP+ABsnzd45c4ogAAAAAElFTkSuQmCC\n",
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