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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Broadband polarization beam splitter using anisotropic metamaterial\n",
+ "\n",
+ "Polarization beam splitters (PBS) play a vital role in polarization diversity circuits to mitigate the strong polarization dependence of silicon nanophotonic devices. Among the various PBS structures, asymmetrical directional couplers are predominantly employed due to their superior overall performance. Notwithstanding, engineering an on-chip silicon PBS that offers a compact footprint, low loss, exceptional extinction ratio, and particularly, a broad bandwidth, all at once, remains a formidable challenge. The working bandwidth of directional couplers is inherently limited. \n",
+ "\n",
+ "Metamaterials offer an innovative method of manipulating optical responses and regulating light flow. Subwavelength grating (SWG), an anisotropic metamaterial (AM) formed by a one-dimensional array of deeply subwavelength nano-strips, exemplifies these characteristics. SWGs demonstrate strong anisotropy and flattened dispersion, making them extremely useful for polarization manipulation.\n",
+ "\n",
+ "In this notebook, we present an ultra-broadband PBS design that makes effective use of AM. The design is based on the research work `Xu, H., Dai, D., & Shi, Y. (2019). Ultra-broadband and ultra-compact on-chip silicon polarization beam splitter by using hetero-anisotropic metamaterials. Laser & Photonics Reviews, 13(4), 1800349.` [DOI: 10.1002/lpor.20180349](https://doi.org/10.1002/lpor.201800349).\n",
+ "\n",
+ "The design comprises three SWG sections symmetrically arranged to form a hetero-anisotropic slab, with two AM[100] sections sandwiching a central AM[010] section. The design also utilizes an adiabatic taper structure at the input/output ports, which serves as a converter between the standard channel waveguides and the SWGs. The design goal is to have the TE mode transmitted to the through port while the TM mode will be coupled to the cross port.\n",
+ "\n",
+ "\n",
+ "\n",
+ "For more examples utilizing SWGs for on-chip applications, please check out the [waveguide bragg gratings](https://www.flexcompute.com/tidy3d/examples/notebooks/BraggGratings/), [broadband polarizer](https://www.flexcompute.com/tidy3d/examples/notebooks/SWGBroadbandPolarizer/), and [exceptional coupling for waveguide crosstalk reduction](https://www.flexcompute.com/tidy3d/examples/notebooks/ZeroCrossTalkTE/)."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "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",
+ "from tidy3d.plugins.mode.web import run as run_mode_solver\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Simulation Setup\n",
+ "\n",
+ "We will focus on the broadband capabilities of the designed PBS over a 200 nm spectrum, ranging from 1450 nm to 1650 nm. This range encapsulates the S-band, C-band, and L-band frequencies."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "lda0 = 1.55 # central wavelength\n",
+ "freq0 = td.C_0 / lda0 # central frequency\n",
+ "ldas = np.linspace(1.45, 1.65, 101) # wavelength range\n",
+ "freqs = td.C_0 / ldas # frequency range\n",
+ "fwidth = 0.5 * (np.max(freqs) - np.min(freqs)) # width of the source frequency range\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The three materials utilized are silicon, silicon oxide, and SU8. Both silicon and oxide are readily available in the [material library](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/material_library.html). In contrast, SU8 is modelled as a non-dispersive medium."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "si = td.material_library[\"cSi\"][\"Palik_Lossless\"]\n",
+ "sio2 = td.material_library[\"SiO2\"][\"Palik_Lossless\"]\n",
+ "\n",
+ "n_su8 = 1.58\n",
+ "su8 = td.Medium(permittivity=n_su8**2)\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Determine the geometric parameters. The thickness of the silicon layer is recorded to be 250 nm. The input and output single mode waveguides each have a width $w_{in}$ of 450 nm. The width of the [100] anisotropic metamaterial (AM[100]) $w_{100}$ is 650 nm. The junction between the single mode strip waveguide and the AM region takes on a taper structure, incorporating $n_{tp}=$10 grating periods. The periods $p$ for both the AM[100] and AM[010] are set at 250 nm. The duty cycles $f_{100}$ and $f_{010}$ are set to 0.7 for both metamaterials, with an option for fine-tuning later.\n",
+ "\n",
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "t = 0.25 # silicon layer thickness\n",
+ "p = 0.25 # pitch of the swg\n",
+ "w_in = 0.45 # input waveguide width\n",
+ "w_100 = 0.65 # width of the AM[100]\n",
+ "n_tp = 10 # number of periods in the taper region\n",
+ "f_0 = 0.7 # initial duty cycle for the anisotropic metamaterial\n",
+ "inf_eff = 1e3 # effective infinity\n",
+ "buffer = 0.6 * lda0 # buffer spacing\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Mode Analysis\n",
+ "\n",
+ "To gain insight into the operational mechanism of the PBS design and to assist future design optimization, we start with a mode analysis. The effective refractive indices of the SWG AM are procured via the effective medium theory. The subsequent formulas elaborate on this:\n",
+ "\n",
+ "1. The ordinary refractive index, denoted as $n_o$, is governed by the formula:\n",
+ " $$\n",
+ " n_o^2 = f \\cdot n_{Si}^2 + (1 - f) \\cdot n_{SU8}^2\n",
+ " $$\n",
+ "\n",
+ " Here, $f$ represents the SWG duty cycle, $n_{Si}$ stands for the refractive index of silicon, and $n_{SU8}$ indicates the refractive index of SU8.\n",
+ "\n",
+ "2. The extraordinary refractive index, denoted as $n_e$, is demonstrated as:\n",
+ " $$\n",
+ " \\frac{1}{n_e^2} = \\frac{f}{n_{Si}^2} + \\frac{1 - f}{n_{SU8}^2}\n",
+ " $$\n",
+ "\n",
+ "3. The refractive index tensors for various configurations, specifically the anisotropic metamaterial [100] and [010], are depicted as such:\n",
+ " $$\n",
+ " n_{[100]} = \\text{diag}(n_{[100]}^{xx}, n_{[100]}^{yy}, n_{[100]}^{zz}) = \\text{diag}(n_e, n_o, n_o)\n",
+ " $$\n",
+ " Similarly,\n",
+ " $$\n",
+ " n_{[010]} = \\text{diag}(n_{[010]}^{xx}, n_{[010]}^{yy}, n_{[010]}^{zz}) = \\text{diag}(n_o, n_e, n_o)\n",
+ " $$\n",
+ "\n",
+ "In this context, $n_o$ and $n_e$ are the ordinary and extraordinary refractive indices respectively. \n",
+ "\n",
+ "By applying the aforementioned refractive index tensors, a mode analysis is conducted on the effective mediums."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "
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+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "n_si = si.nk_model(frequency=freq0)[0] # refractive index of silicon\n",
+ "\n",
+ "# calculate effective refractive index tensors\n",
+ "n_o = np.sqrt(f_0 * n_si**2 + (1 - f_0) * n_su8**2)\n",
+ "n_e = np.sqrt(1 / (f_0 / n_si**2 + (1 - f_0) / n_su8**2))\n",
+ "\n",
+ "# create effective mediums\n",
+ "n_o_medium = td.Medium(permittivity=n_o**2)\n",
+ "n_e_medium = td.Medium(permittivity=n_e**2)\n",
+ "am_100_medium = td.AnisotropicMedium(xx=n_e_medium, yy=n_o_medium, zz=n_o_medium)\n",
+ "am_010_medium = td.AnisotropicMedium(xx=n_o_medium, yy=n_e_medium, zz=n_o_medium)\n",
+ "\n",
+ "# create waveguide structures\n",
+ "n_010_example = 5 # use 5 periods for the AM[010] region width as an example\n",
+ "am_010_waveguide = td.Structure(\n",
+ " geometry=td.Box.from_bounds(\n",
+ " rmin=(-inf_eff, -n_010_example * p / 2, 0), rmax=(inf_eff, n_010_example * p / 2, t)\n",
+ " ),\n",
+ " medium=am_010_medium,\n",
+ ")\n",
+ "\n",
+ "am_100_waveguide_left = td.Structure(\n",
+ " geometry=td.Box.from_bounds(\n",
+ " rmin=(-inf_eff, -n_010_example * p / 2 - w_100, 0),\n",
+ " rmax=(inf_eff, -n_010_example * p / 2, t),\n",
+ " ),\n",
+ " medium=am_100_medium,\n",
+ ")\n",
+ "am_100_waveguide_right = td.Structure(\n",
+ " geometry=td.Box.from_bounds(\n",
+ " rmin=(-inf_eff, n_010_example * p / 2, 0), rmax=(inf_eff, n_010_example * p / 2 + w_100, t)\n",
+ " ),\n",
+ " medium=am_100_medium,\n",
+ ")\n",
+ "\n",
+ "# create box structure\n",
+ "box = td.Structure(\n",
+ " geometry=td.Box.from_bounds(rmin=(-inf_eff, -inf_eff, -inf_eff), rmax=(inf_eff, inf_eff, 0)),\n",
+ " medium=sio2,\n",
+ ")\n",
+ "\n",
+ "# create a simulation for the mode solver\n",
+ "mode_solver_sim = td.Simulation(\n",
+ " center=(0, 0, t / 2),\n",
+ " size=(buffer, n_010_example * p + 2 * w_100 + 2 * buffer, t + 2 * buffer),\n",
+ " grid_spec=td.GridSpec.auto(min_steps_per_wvl=25, wavelength=lda0),\n",
+ " structures=[box, am_010_waveguide, am_100_waveguide_left, am_100_waveguide_right],\n",
+ " run_time=1e-12,\n",
+ " medium=su8,\n",
+ ")\n",
+ "\n",
+ "# create a mode solver\n",
+ "mode_solver = ModeSolver(\n",
+ " simulation=mode_solver_sim,\n",
+ " plane=td.Box(\n",
+ " center=(0, 0, t / 2), size=(0, n_010_example * p + 2 * w_100 + 2 * buffer, t + 2 * buffer)\n",
+ " ),\n",
+ " mode_spec=td.ModeSpec(num_modes=6, target_neff=n_si),\n",
+ " freqs=[freq0],\n",
+ ")\n",
+ "\n",
+ "# plot the mode solving cross section\n",
+ "mode_solver.plot()\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "To ensure accuracy in our process, we execute the server-side mode resolving and subsequently illustrate the mode properties. Utilizing the `TE (Ey) fraction` as a reference, we can discern that the initial two modes align with the first TE modes. Similarly, the third and fifth modes correspond to the first TM modes."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
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+ "
0.977042
\n",
+ "
0.895539
\n",
+ "
\n",
+ "
\n",
+ "
3
\n",
+ "
1.55
\n",
+ "
1.877063
\n",
+ "
0.0
\n",
+ "
0.979590
\n",
+ "
0.932494
\n",
+ "
0.854730
\n",
+ "
0.600598
\n",
+ "
\n",
+ "
\n",
+ "
4
\n",
+ "
1.55
\n",
+ "
1.848565
\n",
+ "
0.0
\n",
+ "
0.040660
\n",
+ "
0.707929
\n",
+ "
0.921683
\n",
+ "
1.215862
\n",
+ "
\n",
+ "
\n",
+ "
5
\n",
+ "
1.55
\n",
+ "
1.768686
\n",
+ "
0.0
\n",
+ "
0.950798
\n",
+ "
0.789337
\n",
+ "
0.875877
\n",
+ "
1.052148
\n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " wavelength n eff k eff TE (Ey) fraction \\\n",
+ "f mode_index \n",
+ "1.934145e+14 0 1.55 2.266313 0.0 0.983015 \n",
+ " 1 1.55 2.266243 0.0 0.982896 \n",
+ " 2 1.55 1.960053 0.0 0.008933 \n",
+ " 3 1.55 1.877063 0.0 0.979590 \n",
+ " 4 1.55 1.848565 0.0 0.040660 \n",
+ " 5 1.55 1.768686 0.0 0.950798 \n",
+ "\n",
+ " wg TE fraction wg TM fraction mode area \n",
+ "f mode_index \n",
+ "1.934145e+14 0 0.858241 0.817122 0.656644 \n",
+ " 1 0.857676 0.817317 0.655516 \n",
+ " 2 0.677583 0.977042 0.895539 \n",
+ " 3 0.932494 0.854730 0.600598 \n",
+ " 4 0.707929 0.921683 1.215862 \n",
+ " 5 0.789337 0.875877 1.052148 "
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "mode_data = run_mode_solver(mode_solver, verbose=False)\n",
+ "mode_data.to_dataframe()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot the field profiles for the initial two TE and TM modes. These results reproduce Fig. 2b in the cited [study](https://doi.org/10.1002/lpor.201800349). The TM0 and TM1 field profiles demonstrate coverage over both the AM[010] and AM[100] regions. In contrast, the even and odd TE super-modes are primarily concentrated in the AM[100] region, indicating a much smaller coupling strength."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# plot the mode profiles\n",
+ "fig, axes = plt.subplots(2, 2, figsize=(8, 4), tight_layout=True)\n",
+ "mode_solver.plot_field(mode_index=2, field_name=\"Ez\", val=\"real\", vmin=-30, vmax=30, ax=axes[0, 0])\n",
+ "axes[0, 0].set_title(\"Ez of the TM0 mode\")\n",
+ "mode_solver.plot_field(mode_index=4, field_name=\"Ez\", val=\"real\", vmin=-30, vmax=30, ax=axes[0, 1])\n",
+ "axes[0, 1].set_title(\"Ez of the TM1 mode\")\n",
+ "mode_solver.plot_field(mode_index=1, field_name=\"Ey\", val=\"real\", vmin=-30, vmax=30, ax=axes[1, 1])\n",
+ "axes[1, 1].set_title(\"Ey of the odd TE mode\")\n",
+ "mode_solver.plot_field(mode_index=0, field_name=\"Ey\", val=\"real\", vmin=-30, vmax=30, ax=axes[1, 0])\n",
+ "axes[1, 0].set_title(\"Ey of the even TE mode\")\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "We can calculate the coupling length for TE and TM modes using the formula $L_c = \\frac{\\lambda}{2(n_{eff}^0-n_{eff}^1)}$, where $n_{eff}^0$ and $n_{eff}^1$ denote the effective indices of the initial two modes. The results demonstrate that the coupling length for TM mode is approximately 7 μm, whilst the coupling length for TE mode is several orders of magnitude larger. Consequently, by designing the coupling region to roughly 7 μm, we can effectively couple the TM mode to the cross port. Conversely, the TE mode is directed solely to the through port, which results in the realization of the PBS functionality."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "The coupling length for the TM mode is 6.95 μm.\n",
+ "The coupling length for the TE mode is 11132.14 μm.\n"
+ ]
+ }
+ ],
+ "source": [
+ "# calculate TM mode coupling length\n",
+ "n_tm0 = mode_data.n_eff.sel(mode_index=2).values[0]\n",
+ "n_tm1 = mode_data.n_eff.sel(mode_index=4).values[0]\n",
+ "print(f\"The coupling length for the TM mode is {lda0/(2*(n_tm0-n_tm1)) :.2f} μm.\")\n",
+ "\n",
+ "# calculate TE mode coupling length\n",
+ "n_te0 = mode_data.n_eff.sel(mode_index=0).values[0]\n",
+ "n_te1 = mode_data.n_eff.sel(mode_index=1).values[0]\n",
+ "print(f\"The coupling length for the TE mode is {lda0/(2*(n_te0-n_te1)) :.2f} μm.\")\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Design Optimization\n",
+ "\n",
+ "For the final design configuration, it is crucial to pinpoint the exact coupling length that promotes the maximum coupling of the TM mode to the cross port. The determination of the coupling length is reliant upon the number of grating periods in the AM[100] region, i.e. $n_{100}$. Similarly, the width of the coupling region is governed by the number of grating periods in the AM[010] region, i.e. $n_{010}$. A parameter sweep of both aspects will be conducted to search for the optimal values. The duty cycles for both AM[100] and AM[010] are held at a constant 0.7 in this scenario to guarantee the minimal feature size. However, these values are open to precise adjustment at a later stage.\n",
+ "\n",
+ "To start the parameter sweep process, we define a `make_sim` function. This function processes the design parameters and returns a Tidy3D [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html#tidy3d.Simulation). "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def make_sim(mode_index, n_100, n_010, f_100=f_0, f_010=f_0):\n",
+ " \"\"\"\n",
+ " Constructs and returns a simulation object given the design parameters.\n",
+ "\n",
+ " Args:\n",
+ " mode_index (int): The index of the mode to excite in the simulation. mode_index=0 for TE and mode_index=1 for TM.\n",
+ " n_100 (int): Number of SWG periods in AM[100].\n",
+ " n_010 (int): Number of SWG periods in AM[010].\n",
+ " f_100 (float, optional): Duty cycle for AM[100].\n",
+ " f_010 (float, optional): Duty cycle for AM[010].\n",
+ "\n",
+ " Returns:\n",
+ " td.Simulation\n",
+ " \"\"\"\n",
+ " \n",
+ " l_c = p * n_100 - (1 - f_100) * p # coupling region length\n",
+ " l_tp = p * n_tp # taper length\n",
+ " y_0 = n_010 * p / 2 + (1 - f_010) * p / 2 + w_100 / 2 # y coordinate of the input waveguide center\n",
+ "\n",
+ " # create the swg structures in the coupling region\n",
+ " am_geos = 0\n",
+ " for i in range(n_010):\n",
+ " am_geos += td.Box(\n",
+ " center=(l_c / 2, (n_010 - 1) * p / 2 - i * p, t / 2), size=(l_c, p * f_010, t)\n",
+ " )\n",
+ "\n",
+ " for i in range(n_100):\n",
+ " am_geos += td.Box(center=(f_100 * p / 2 + i * p, y_0, t / 2), size=(p * f_100, w_100, t))\n",
+ " am_geos += td.Box(center=(f_100 * p / 2 + i * p, -y_0, t / 2), size=(p * f_100, w_100, t))\n",
+ "\n",
+ " am_structure = td.Structure(geometry=am_geos, medium=si)\n",
+ " \n",
+ " # create the waveguide taper structures\n",
+ " vertices = [\n",
+ " (-inf_eff, y_0 + w_in / 2),\n",
+ " (-inf_eff, y_0 - w_in / 2),\n",
+ " (-l_tp - (1 - f_100) * p, y_0 - w_in / 2),\n",
+ " (-(1 - f_100) * p, y_0),\n",
+ " (-l_tp - (1 - f_100) * p, y_0 + w_in / 2),\n",
+ " ]\n",
+ "\n",
+ " taper_in = td.PolySlab(vertices=vertices, axis=2, slab_bounds=(0, t))\n",
+ " taper_out_bottom = taper_in.rotated(angle=np.pi, axis=2).translated(x=l_c, y=0, z=0)\n",
+ " taper_out_top = taper_out_bottom.translated(x=0, y=2 * y_0, z=0)\n",
+ "\n",
+ " taper_geos = [taper_in, taper_out_bottom, taper_out_top]\n",
+ " taper_structure = td.Structure(geometry=td.GeometryGroup(geometries=taper_geos), medium=si)\n",
+ "\n",
+ " # create the swg structures in the taper regions\n",
+ " taper_widths = np.linspace(w_in, w_100, n_tp + 2)[1:-1]\n",
+ " taper_am_geos = []\n",
+ " for i in range(n_tp):\n",
+ " taper_am = td.Box(\n",
+ " center=(-l_tp + f_100 * p / 2 + i * p, y_0, t / 2), size=(f_100 * p, taper_widths[i], t)\n",
+ " )\n",
+ " taper_am_geos += [\n",
+ " taper_am,\n",
+ " taper_am.rotated(angle=np.pi, axis=2).translated(x=l_c, y=0, z=0),\n",
+ " taper_am.rotated(angle=np.pi, axis=2).translated(x=l_c, y=2 * y_0, z=0),\n",
+ " ]\n",
+ " taper_am_structure = td.Structure(\n",
+ " geometry=td.GeometryGroup(geometries=taper_am_geos), medium=si\n",
+ " )\n",
+ "\n",
+ " # add a mode source as excitation\n",
+ " mode_spec = td.ModeSpec(num_modes=2, target_neff=n_si)\n",
+ " mode_source = td.ModeSource(\n",
+ " center=(-l_tp - buffer / 2, y_0, t / 2),\n",
+ " size=(0, 4 * w_in, 6 * t),\n",
+ " source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
+ " direction=\"+\",\n",
+ " mode_spec=mode_spec,\n",
+ " mode_index=mode_index,\n",
+ " )\n",
+ "\n",
+ " # add a mode monitor to measure transmission at the through port\n",
+ " mode_through = td.ModeMonitor(\n",
+ " center=(l_c + l_tp + buffer / 2, y_0, t / 2),\n",
+ " size=mode_source.size,\n",
+ " freqs=freqs,\n",
+ " mode_spec=mode_spec,\n",
+ " name=\"through\",\n",
+ " )\n",
+ " \n",
+ " # add a mode monitor to measure transmission at the cross port\n",
+ " mode_cross = td.ModeMonitor(\n",
+ " center=(l_c + l_tp + buffer / 2, -y_0, t / 2),\n",
+ " size=mode_source.size,\n",
+ " freqs=freqs,\n",
+ " mode_spec=mode_spec,\n",
+ " name=\"cross\",\n",
+ " )\n",
+ "\n",
+ " # add a field monitor to visualize field distribution at z=t/2\n",
+ " field_monitor = td.FieldMonitor(\n",
+ " center=(0, 0, t / 2),\n",
+ " size=(td.inf, td.inf, 0),\n",
+ " freqs=[freq0],\n",
+ " interval_space=(2, 2, 1),\n",
+ " name=\"field\",\n",
+ " )\n",
+ "\n",
+ " run_time = 1.5e-12 # simulation run time\n",
+ "\n",
+ " # construct simulation\n",
+ " sim = td.Simulation(\n",
+ " center=(l_c / 2, 0, t / 2),\n",
+ " size=(2 * l_tp + l_c + buffer * 2, n_010 * p + w_100 * 2 + 2 * buffer, 10 * t),\n",
+ " grid_spec=td.GridSpec.auto(min_steps_per_wvl=25, wavelength=lda0),\n",
+ " structures=[am_structure, taper_structure, taper_am_structure, box],\n",
+ " sources=[mode_source],\n",
+ " monitors=[mode_through, mode_cross, field_monitor],\n",
+ " run_time=run_time,\n",
+ " boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
+ " medium=su8,\n",
+ " )\n",
+ "\n",
+ " return sim\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The simulation setup is relatively complex due to the SWG structures. To validate the correctness of the setup, we construct a sample simulation and render its 3D visualization."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ " \n",
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "sim = make_sim(mode_index=1, n_100=30, n_010=5)\n",
+ "sim.plot_3d()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Visualize the grid to ensure that it's refined enough to resolve the small features."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "ax = sim.plot(z=t / 2, monitor_alpha=0)\n",
+ "sim.plot_grid(z=t / 2, ax=ax)\n",
+ "ax.set_xlim(0, 1)\n",
+ "ax.set_ylim(0, 1)\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The purpose of this notebook is solely for demonstration, thus, we will only be exploring a limited parameter space. For a more extensive exploration, a similar procedure can be adopted.\n",
+ "\n",
+ "Prior to initiating a [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html) of simulations, it is important to get an estimate of the potential FlexCredit cost. This helps users by keeping them informed about possible expenses associated with the simulations and protects against accidental misuse of credits."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
09:06:41 Eastern Standard Time Maximum FlexCredit cost: 12.125 for the whole \n",
+ "batch. \n",
+ "
09:07:46 Eastern Standard Time Total billed flex credit cost: 5.630. \n",
+ "
\n"
+ ],
+ "text/plain": [
+ "\u001b[2;36m09:07:46 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mTotal billed flex credit cost: \u001b[1;36m5.630\u001b[0m. \n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "batch_results = batch.run(path_dir=\"data\")\n",
+ "_ = batch.real_cost()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Result Visualization\n",
+ "\n",
+ "Let's now move towards visualization of our results. We begin by extracting and plotting the transmission at the central frequency as a function of both $n_{010}$ and $n_{100}$."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def cal_transmission_at_freq0(mode_index, n_010):\n",
+ " \"\"\"\n",
+ " Calculates the transmission at the central frequency as a function of n_100 for a given mode index \n",
+ " and n_010\n",
+ "\n",
+ " Args:\n",
+ " mode_index (int): The index of the mode for which transmission is calculated. mode_index=0 for TE and mode_index=1 for TM.\n",
+ " n_010 (int): The number of periodic elements along the y-direction.\n",
+ "\n",
+ " Returns:\n",
+ " tuple[list[float], list[float]]: A tuple containing two lists:\n",
+ " - `cross`: Power transmission values to the cross port.\n",
+ " - `through`: Power transmission values to the through port.\n",
+ " \"\"\"\n",
+ " cross = [\n",
+ " np.abs(\n",
+ " batch_results[f\"mode_index={mode_index}; n_100={n_100}; n_010={n_010};\"][\"cross\"]\n",
+ " .amps.sel(mode_index=mode_index, direction=\"+\")\n",
+ " .sel(f=freq0, method=\"nearest\")\n",
+ " .values\n",
+ " )\n",
+ " ** 2\n",
+ " for n_100 in n_100_list\n",
+ " ]\n",
+ "\n",
+ " through = [\n",
+ " np.abs(\n",
+ " batch_results[f\"mode_index={mode_index}; n_100={n_100}; n_010={n_010};\"][\"through\"]\n",
+ " .amps.sel(mode_index=mode_index, direction=\"+\")\n",
+ " .sel(f=freq0, method=\"nearest\")\n",
+ " .values\n",
+ " )\n",
+ " ** 2\n",
+ " for n_100 in n_100_list\n",
+ " ]\n",
+ "\n",
+ " return cross, through\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# hex codes of the colors used for plotting\n",
+ "colors = {\n",
+ " \"TM_cross\": \"#dc0154\",\n",
+ " \"TM_through\": \"#f5a67a\",\n",
+ " \"TE_cross\": \"#aaa3f0\",\n",
+ " \"TE_through\": \"#3130bc\",\n",
+ "}\n",
+ "\n",
+ "\n",
+ "def plot_transmission_at_freq0(cross, through, n_010, mode, ax):\n",
+ " \"\"\"\n",
+ " Plots the transmission values for cross and through ports at the central frequency as a function of n_100\n",
+ "\n",
+ " Args:\n",
+ " cross (list[float]): List of transmission values for the cross port.\n",
+ " through (list[float]): List of transmission values for the through port.\n",
+ " n_010 (int): Number of periods in the AM[010]\n",
+ " mode (str): Input mode type (e.g., \"TE\" or \"TM\").\n",
+ " ax: Matplotlib Axes object on which to plot.\n",
+ " \"\"\"\n",
+ " ax.plot(n_100_list, cross, color=colors[f\"{mode}_cross\"], linewidth=2, label=\"Cross port\")\n",
+ " ax.plot(n_100_list, through, color=colors[f\"{mode}_through\"], linewidth=2, label=\"Through port\")\n",
+ " ax.set_title(f\"n_010={n_010}; {mode.upper()} input\")\n",
+ " ax.set_ylim(-0.05, 1.05)\n",
+ " ax.set_aspect(aspect=5)\n",
+ " ax.set_xlabel(\"n_100\")\n",
+ " ax.set_ylabel(\"Transmission\")\n",
+ " ax.legend()\n",
+ " ax.grid()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The outcome replicates a portion of Figure 3 from the cited [paper](https://doi.org/10.1002/lpor.201800349). It is evident that the optimal outcome is achieved with $n_{100}=30$ and $n_{010}=5$."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "for n_010 in n_010_list:\n",
+ " fig, axes = plt.subplots(1, 2, figsize=(8, 5), sharex=True)\n",
+ "\n",
+ " # TM\n",
+ " cross_tm, through_tm = cal_transmission_at_freq0(1, n_010)\n",
+ " plot_transmission_at_freq0(cross_tm, through_tm, n_010, \"TM\", axes[0])\n",
+ "\n",
+ " # TE\n",
+ " cross_te, through_te = cal_transmission_at_freq0(0, n_010)\n",
+ " plot_transmission_at_freq0(cross_te, through_te, n_010, \"TE\", axes[1])\n",
+ "\n",
+ " plt.tight_layout()\n",
+ " plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Next, we generate the transmission spectra plots for both TE and TM input simulations."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_spectra(sim_data):\n",
+ " \"\"\"\n",
+ " Calculates the power spectra for the through and cross ports \n",
+ " from simulation data.\n",
+ "\n",
+ " Args:\n",
+ " sim_data: td.SimulationData\n",
+ "\n",
+ " Returns:\n",
+ " tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:\n",
+ " - Power spectrum for mode_index=0 at the through port.\n",
+ " - Power spectrum for mode_index=0 at the cross port.\n",
+ " - Power spectrum for mode_index=1 at the through port.\n",
+ " - Power spectrum for mode_index=1 at the cross port.\n",
+ " \"\"\"\n",
+ " return (\n",
+ " np.abs(sim_data[\"through\"].amps.sel(mode_index=0, direction=\"+\").values) ** 2,\n",
+ " np.abs(sim_data[\"cross\"].amps.sel(mode_index=0, direction=\"+\").values) ** 2,\n",
+ " np.abs(sim_data[\"through\"].amps.sel(mode_index=1, direction=\"+\").values) ** 2,\n",
+ " np.abs(sim_data[\"cross\"].amps.sel(mode_index=1, direction=\"+\").values) ** 2,\n",
+ " )\n",
+ "\n",
+ "\n",
+ "def plot_spectra(sim_data, mode, field_component, field_vmin, field_vmax):\n",
+ " \"\"\"\n",
+ " Plots the spectra and field distribution for a given simulation result.\n",
+ "\n",
+ " Parameters:\n",
+ " sim_data: Simulation data object.\n",
+ " mode: \"TE\" or \"TM\".\n",
+ " field_component: Field component to plot (e.g., \"Hz\", \"Ez\").\n",
+ " field_vmin: Minimum value for field plot colormap.\n",
+ " field_vmax: Maximum value for field plot colormap.\n",
+ " \"\"\"\n",
+ " # extract spectra\n",
+ " te_through, te_cross, tm_through, tm_cross = get_spectra(sim_data)\n",
+ "\n",
+ " # choose the correct data based on mode\n",
+ " if mode == \"TE\":\n",
+ " through = te_through\n",
+ " cross = te_cross\n",
+ " title = \"TE input\"\n",
+ " elif mode == \"TM\":\n",
+ " through = tm_through\n",
+ " cross = tm_cross\n",
+ " title = \"TM input\"\n",
+ " else:\n",
+ " raise ValueError(\"Invalid mode. Use 'TE' or 'TM'.\")\n",
+ "\n",
+ " # create figure\n",
+ " fig, axes = plt.subplots(2, 1, figsize=(5, 7))\n",
+ "\n",
+ " # plot spectra\n",
+ " axes[0].plot(\n",
+ " ldas,\n",
+ " 10 * np.log10(through),\n",
+ " color=colors[f\"{mode}_through\"],\n",
+ " linewidth=2,\n",
+ " label=\"Through port\",\n",
+ " )\n",
+ " axes[0].plot(\n",
+ " ldas, 10 * np.log10(cross), color=colors[f\"{mode}_cross\"], linewidth=2, label=\"Cross port\"\n",
+ " )\n",
+ " axes[0].set_title(title)\n",
+ " axes[0].set_ylim(-50, 2)\n",
+ " axes[0].set_xlabel(\"Wavelength (μm)\")\n",
+ " axes[0].set_ylabel(\"Transmission (dB)\")\n",
+ " axes[0].legend()\n",
+ " axes[0].grid()\n",
+ "\n",
+ " # plot field distribution\n",
+ " sim_data.plot_field(\n",
+ " \"field\", field_component, \"real\", vmin=field_vmin, vmax=field_vmax, ax=axes[1]\n",
+ " )\n",
+ "\n",
+ " # adjust layout and display\n",
+ " plt.tight_layout()\n",
+ " plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The results show a great PBS performance."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# plot TE simulation results\n",
+ "sim_data_te = batch_results[\"mode_index=0; n_100=30; n_010=5;\"]\n",
+ "plot_spectra(\n",
+ " sim_data=sim_data_te,\n",
+ " mode=\"TE\",\n",
+ " field_component=\"Hz\",\n",
+ " field_vmin=-0.5,\n",
+ " field_vmax=0.5,\n",
+ ")\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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rxaBBg+Dn54cDBw4gPT0dY8eOhUwmw3//+18bREwIIYRUjcPXrOfPn4/XXnsNbdq0Mbl827ZtOHfuHH7++We0a9cOjz32GN577z0sW7YMKpWqlqMlhBBCqs7ha9aVSUxMRJs2beDr6yvOi4uLw+TJk3H27Fm0b9/e5HZFRUUoKioSp7OzswEAarUaarW62vHot61JGbXJ0eIFKOba4GjxAo4Xs6PFC9TfmGvj89b5ZJ2RkWGQqAGI0xkZGeVut3DhQsyfP99o/rZt2+Ds7FzjuOLj42tcRm1ytHgBirk2OFq8gOPF7GjxAvUv5vz8fAtGYppdJutZs2Zh0aJFFa6TnJyMli1bWi2Gt99+GzNmzBCns7OzERgYiNjYWLi7u1e7XLVajfj4ePTv3x8ymcwSoVqVo8ULUMy1wdHiBRwvZkeLF6i/MeuvvFqTXSbr119/HePGjatwnbCwMLPK8vPzw+HDhw3m3b59W1xWHoVCAYVCYTRfJpNZ5CS0VDm1xdHiBSjm2uBo8QKOF7OjxQvUv5hr47PaZbL29vaGt7e3RcqKjo7GBx98gDt37sDHxweA7nKHu7s7WrVqZZF9EEIIIdZkl8m6Kq5fv44HDx7g+vXr0Gq1SEpKAgA0a9YMrq6uiI2NRatWrfCf//wHH330ETIyMjB79mxMnTrVZM2ZEEIIsTcOn6znzJmDH3/8UZzWt+7etWsX+vTpA4lEgs2bN2Py5MmIjo6Gi4sLnnvuOSxYsKDWY2WM1fo+CSGEOD6HT9YrV67EypUrK1wnODgY//zzT+0EVAHN2V1Q3ziLZioOwp0rYH5NwUkc/r+AEEKIlVGmqEXa9ItAZgZCAWj3/IQCiQy8TwgkAeGQBISDd21g6xAJIYTYIUrWtYQJWoAJhjO1agjpFyGkX4T62GZw7t6QBLSEpEkE+IaB4HiH72COEEKIBVCyriUcL4EydjJUOQ9xYtufiPJ3A+5cBivIEddh2Xehyb4Lzfm9gMIFkiYRkDaJBO8bRpfLCSGkHqMMUMs4pSsypA3RofNASKVSsMwMaNNSoE27AOH+dUDfCK0oD9rLR6G9fBSQKXWJO7A1eL9mlLgJIaSeoW99G+I4DpyXP3gvf8gi+4AV5UF7KwXaW8m6+9va4v5m1YXQpp6ANvUEIHeCJDAS0qAo8D6hdKmcEELqAUrWdoRTuEAa1gHSsA5gGhW0GZegvX4G2lvnAU3xoCKqArHGzTm5QRLcFtKQduA8/cBxnG0/ACGEEKugZG2nOKkc0iatIG3SCkyrhjb9ErTXT0N7KxnQ6Ib2ZAU50JzfB835feA8fCENbQ9JcFvwztXvu5wQQoj9oWTtADiJDNImEZA2idDVuNNSoL2apLtULmgBACzrNtRJW6E++S9432a6xN2kFTipY/XPSwghxBglawfDSeWQBrWBNKgNWFE+NNdPQ3s1CcK967oVGIOQcRGqjIuATAFpUBQkYR10j4LRZXJCCHFIlKwdGKdwhqx5V8iad4WQcx+aqyegTU0Cy3uoW0FdBM3lI9BcPgLO3RvS0A6QhLSjy+SEEOJgKFnXEbxbQ8jbxIC17gfhzlVoUk9Ae+NMyf3t7LtQn/wX6lPbwPs3hzS0IySNW9JjYIQQ4gDom7qO4TgeEt8wSHzDwDo+Du2NM9BcOQ7h7lXdCoxBSLsAVdoFQO4MaUhbSEM7gG8QYNO4CSGElM9qybqoqIiGoLQxTqaANKwjpGEddZfJU49Dm3oCLD9Lt4IqH5oLidBcSATn6QdpaAfdY2BKF9sGTgghxIDFkvWWLVvwyy+/YO/evbhx4wYEQYCLiwvat2+P2NhYjB8/HgEBVHuzFd6tIeRR/cFaPwrh9hVoUo9Be+McIGgAACwzA+oT/0CdtBWSgBaQhHaAJCDcxlETQggBLJCs//zzT8ycORM5OTkYOHAgZs6ciYCAADg5OeHBgwc4c+YMtm/fjvfeew/jxo3De++9B29vb0vETqqB43lI/JtB4t8MTFUAzbVT0KaegHD/hm4FJkB767yuIxa5E/jA1nDX5tFY3IQQYkM1TtYfffQRli5disceewy8ia4vR44cCQC4desWvvjiC/z888947bXXarpbYgGc3KmkNXnWHd1l8qtJJYOLqAogXD6CrgA0/34JLrQ9JCFtaShPQgipZTVO1omJiWat17hxY3z44Yc13R2xEt7DB/J2A8CiYiHcvqxL3DfPAVrdZXLk3of69HaoT28H7x0MSUg7SANbg1M42zZwQgipB6g1ODGgu0zeHBL/5mDqQqiunsLd4zvRQCgZylO4ew3C3WtQH9sMiX8LSELaQdI4HJyEeksjhBBrsNiQTRcvXsTvv/+O1NRUAMDff/+NXr16oXPnzvjggw/onqcD4mRK8CHtcUwZAenAVyFrGwvO3adkBUEL7a1kqPavRcGfC1F08HdoMy6DCYLtgiaEkDrIIjXrP//8EyNHjgTP8+A4Dt9++y1eeukl9OnTB+7u7pg3bx6kUilmzpxpid0RG+CcPSFr1RvSiF5gD9OhuZoE7fVTJfe31UXQph6HNvV4qdHA2oLz9KduTgkhpIYsUrP+4IMP8NZbb6GwsBBff/01Jk2ahIULF2LLli3YvHkzli1bhpUrV1piV8TGOI4D3yAA8g4DoRz8FhR9x0MS2h6QljxTrx8NrHDrMhRu+Rzqc7sh5GXaLmhCCHFwFknWKSkpeP7558FxHJ577jmoVCrExMSIy2NjY3Ht2jVL7IrYEY7nIfFrBkW3p+D05NuQ93gGksYtAV4irsOy7kB9chsKNy1G4Y7/QXPlOJi6yIZRE0KI47HIZfC8vDy4ubkBAHieh5OTE5ydS1oJOzk5oaiIvqDrMk4qMzEa2EkI9/Q/0hiEO1egunMFOLoJksBISMM6gvcJAcdZrOkEIYTUSRZJ1hzHGdyXLDtN6heD0cByH0B7NQma1CSw3Pu6FbRq3XjcV5PAuXhBGtYBkrCO4J09bBs4IYTYKYska8YYWrRoISbo3NxctG/fXuwkhVqC11+8awPwrftBGtkXwv0b0KaegObaKUBdCABgeQ+hPr0D6jM7daOBNe0MSUA4uFKX0gkhpL6zSLJesWKFJYohdRjHcZA0CoKkURBkHQZCezNZNxpYxiUAzGA0MM7JHdKmnSBp2pnG3iaEEFgoWT/33HOWKIbUE5xEBmlwFKTBURDyMqFNPQ7N5WNg+ZkAAFaQDfWZnVCfTYCkSStIw6PBNwqmWyuEkHqLejAjNsW7eOouk7fqAyHjEjSXDkObdh5gTDeoyI0z0N44A75BAKQtukMS1AachE5bQkj9UuNvPS8vL7NrPA8ePKjp7kgdxfG8bmjOgBYQ8jKhuXwEmktHgKI8AIDwIA2qg7+BO7kN0vDukDbtDE6utHHUhBBSO2qcrD/99FPx/f379/H+++8jLi4O0dHRAHQDffz777949913a7orUk/wLp6QR/WHLLIvtNdPQ3PhAIQHaQCKL5EnbYX67C5Im3WBLPwRcE6uNo6YEEKsq8bJuvT96uHDh2PBggWYNm2aOG/69On48ssvsX37dhoak1QJJ5FCGtoekpB2EO5dg+b8PmhvngfAAHURNMl7obmQCGnTzpBG9KRHvwghdZZFe6P4999/MWDAAKP5AwYMwPbt2y25K1KPcBwHiXcIFD2fhXLQK5A07QTwxb8ztRpoLiSi8K9PoDqyEUJ+lm2DJYQQK7Bosm7YsCE2btxoNH/jxo1o2LChJXdF6ine3RuKLk9C+cTrkIb3APTDcgpaaC4dRuFfS6BN2gI5U9k2UEIIsSCLNqudP38+XnjhBSQkJKBr164AgEOHDmHr1q347rvvLLkrUs/xzu6QdxgIWaveUKfsh+ZCIqBRAYIGwqVDeAQ8tKddIW3dB5zcydbhEkJIjVg0WY8bNw4RERH4/PPP8ccffwAAIiIisG/fPjF5E2JJnNIF8raxkLXsAXXyPl3S1qohgQAhZR8KUo/phvZs3g2cVGbrcAkhpFos/sBq165dsXr1aksXS0iFOIUL5O3iIGvZA0Wnd0Fz6RB4MEBVAHXSVmguHISsbSwkwW1o4BBCiMOp8bdWXl6eVdcnpCo4pSsk7QZgvzIKXHBbALo+AFh+JlSJv6Jo23Jo7161aYyEEFJVNU7WzZo1w4cffoj09PRy12GMIT4+Ho899hg+//zzmu6SkEoV8gpIOz8J5WPTwPs3F+cLD26haPt3KNr/C4S8TNsFSAghVVDjy+AJCQn4v//7P8ybNw9t27ZFp06dEBAQAKVSiYcPH+LcuXNITEyEVCrF22+/jZdeeskScRNiFt7TD8o+46BNvwjViS1gWbcBANrrp6G9dR6yiJ6QRvSi+9mEELtW42QdHh6O33//HdevX8f69euxd+9eHDhwAAUFBWjUqBHat2+P7777Do899hgkEhr2kNiGxL85lL5Nob1yFKpT8UBRPqBVQ31mJzSpxyHrMAiSxhE0WAghxC5ZrIFZUFAQXn/9dbz++uuWKpIQi+J4HtJmXSAJaqNL0hcOAkwAy8uEau9q8AEtIO/wOHg36hOAEGJfqFksqXc4uRPkHQZB+djL4H2bivOFtAso/OdzqE7vANOqbRghIYQYomRN6i3ewweKvuMh7/EMOCd33UxBA82ZnSj85wto0y/ZNkBCCClGyZrUaxzHQRrUBspBr0LasidQ/Aw2y72PooQVKNq/Dqwgx8ZREkLqO0rWhADgZArI2w+AcsA08N7B4nzt9VMo+PtTaC4dBmOCDSMkhNRnlKwJKYX39IXi0Rcg7/IkoO9TXF0I1ZGNKNr+PYSsO7YNkBBSL1k8WWdmZmLbtm34+eef8dNPPxm8LO3q1auYMGECQkND4eTkhKZNm2Lu3LlQqQxHXDp16hR69uwJpVKJwMBAfPTRRxaPhdQdHMdD2rQTnAa9BklIe3G+cO8aCrd+WdwATWPDCAkh9Y1F+wb/66+/MGbMGOTm5sLd3d3gmVWO4zB27FhL7g7nz5+HIAj45ptv0KxZM5w5cwYTJ05EXl4eFi9eDADIzs5GbGwsYmJisHz5cpw+fRrPP/88PD098eKLL1o0HlK3cEoXKKKfgja0PVRHNoLl3tcNxXlmJ7TXT0PeeSgkPiG2DpMQUg2MMbCc+9CmX0SQOsPW4VTKosn69ddfx/PPP4///ve/cHZ2tmTRJg0YMAADBgwQp8PCwpCSkoKvv/5aTNarV6+GSqXCDz/8ALlcjsjISCQlJWHJkiWUrIlZJH5NoXzsZajP7oImea/u2ezsuyja8R2kzbpA1i4OnExp6zAJIZUQ8jIh3L4M7e0rEG5fASvIBgCEQmr3bVIsmqxv3bqF6dOn10qiLk9WVhYaNGggTicmJqJXr16Qy+XivLi4OCxatAgPHz6El5eXyXKKiopQVFQkTmdn6/5T1Wo11OrqP4Or37YmZdQmR4sXsF7MXKu+kAZEQHtsE9jDNACA5tJhaG4lQ9L+cfAB4dUu29GOs6PFCzhezI4WL2B/MTNVPtidVLA7VyDcSQVyH5hcTw4NNPfTwDVqUq391Mbn5RhjzFKFDRs2DM888wxGjhxpqSKr5NKlS+jYsSMWL16MiRMnAgBiY2MRGhqKb775Rlzv3LlziIyMxLlz5xAREWGyrHnz5mH+/PlG89esWWPTHyPEDjCGQM1tNFPfhBQlv8YzJA2QIg+GiqN+xgmxBY4J8BRy0UCbhYZCNtyFPJTXgbAWPB7ybngoccMD3h05vAtYNbsbzs/Px+jRo5GVlQV3d/fqf4AKWLRmPWjQILz55ps4d+4c2rRpA5nM8Etr8ODBZpUza9YsLFq0qMJ1kpOT0bJlS3H61q1bGDBgAEaMGCEm6pp4++23MWPGDHE6OzsbgYGBiI2NrdF/hlqtRnx8PPr37290fOyRo8UL1F7MLO8htMc3g92+DADw0z6An7YAkrZx4ILaVqmfcUc7zo4WL+B4MTtavIBtYmZ5DyFkXATLuAR29yqgUZlekePBNQwE5xMKzicU0gaN4c9L0cgCMeuvvFqTRZO1PkkuWLDAaBnHcdBqtWaV8/rrr2PcuHEVrhMWFia+T0tLQ9++fdG9e3d8++23Buv5+fnh9u3bBvP0035+fuWWr1AooFAojObLZDKLnISWKqe2OFq8QC3E7OkD1nc8tFdPQnX8b0CVD6gKoD2yAfyNs5B3HgLe1fRtlvI42nF2tHgBx4vZ0eIFrBsz06oh3LkKbVoKtOkXwXLulbsu5+ELiV8zSPyagvcJBSeVl7tuTWKujf8fiyZrQbDMDXpvb294e3ubte6tW7fQt29fdOzYEStWrADPGz6NFh0djXfeeQdqtVo8oPHx8QgPDy/3fjUh5uI4DtLQdpD4N4Pq+N/QXjsFABAyLqJwy+eQtY2FtHlXcBx1aUBIdQl5mbrknJYC4fYVoLy++xUuuuTs3xwSv2bgnNxqN1Arsmiyrm23bt1Cnz59EBwcjMWLF+Pu3bviMn2tefTo0Zg/fz4mTJiAmTNn4syZM/jss8+wdOlSW4VN6iBO6QpF96ehDW4L1dFNYPlZgEYF9bHN0F47DXnXJ8G7m/cDlJD6jjEBwv2b0N46D21aClhmOY9WcTz4RkG65OzfHJyXf539YWzxZL17924sXrwYycnJAIBWrVrhzTffRM+ePS29K8THx+PSpUu4dOkSmjQxbMWnbzfn4eGBbdu2YerUqejYsSMaNWqEOXPm0GNbxCokjVtC6RMCddK/0Fw6DKC4M5UtX0LWuh+kEY+A42lcd0LKYhoVtBmXdAn61nmgKM/0ikpXSPxbQBIQDolfU3D6ngbrOIsm659//hnjx4/HsGHDMH36dADA/v378eijj2LlypUYPXq0JXeHcePGVXpvGwCioqKwd+9ei+6bkPJwMiXknYdAEtQGqsN/guU+AAQN1Ke2QXPjDBRdh4H38rd1mITYHCvMLU7OydBmXALK6RmQb9AYksYtIQkIr9O154pYNFl/8MEH+Oijj/Daa6+J86ZPn44lS5bgvffes3iyJsSeSXzDdJ2pnN4BTcp+gDGwh2ko/PcrSCN7Q9aqDziJQ9+JIqTKhNwH0N48B+3NcxDuXgdg4ulhiQwS/2aQBBQn6Dp077m6LPpNceXKFTzxxBNG8wcPHoz/+7//s+SuCHEInFQOefvHIAlqDdWhP8Cy7gBMgObMLmhvJutq2Q0a2zpMQqxKyLoD7Y2z0Nw8C/Yw3fRKSldIG0dA0rgleN+m4KSO1QLe2iyarAMDA7Fjxw40a9bMYP727dsRGBhoyV0R4lAkDQOhjJsK9dkEaM7t1nVZmpmBwm3LIW3VCwh/xNYhEmIxjDEImbehuXEG2utnwLJNj1bHuTWCpEkrSJq0At+wcb28vG0ui/cNPn36dCQlJaF79+4AdPesV65cic8++8ySuyLE4XASKeRRMZA2aYWiQ7/rWrgyAZqzCcDNZLgKjWwdIiE1wrLvIkx9C5pty6Ap5/lnvkFjXYIOjKQnJKrAosl68uTJ8PPzwyeffIJff/0VABAREYF169ZhyJAhltwVIQ6LbxAAZexkaM7thvpsAsAEIOs2uuIOtOd2Q9qmL7UYJw5DyHsI7bVT0Fw7BZaZgaYAUOYxaL5RMCSBkZAEtgLvQv1bVIfFW7c8+eSTePLJJy1dLCF1CieRQtbmUUgaR6Do4G9gWbfBg0E4twtFGRcgjx5BtQ5it1hRPjTXT0N77SSEu9dMrsN7B0MS2FpXg3b2qOUI6x5qikqIDfENAqCMm4KiU9uhOb8XPADhwS0Ubl0GWfsBkDbrWqU+xgmxFqbVQJt+AdrUJGjTzgOCcffRXIPGOJ8jQWTsU5C7N7RBlHVXjZN1gwYNcOHCBTRq1AheXl4VfrE8eGB6eDJC6jNOIoWk9aNITL2PrrLbQO59QKuG+uhf0N46D0XX4fToCrEZIes2NJePQXP1BFCUb7Scc/eBNKQtJMFR0CrccP2ff9DayTojT9VnNU7WS5cuhZubm/ieagGEVE+2xBXSmKHA2R3QXDwEABDSL6JgyxdQdBsOSQ3GyyakKphGBe3109BcOgLh/g3jFZSukIa0gzSkLThPf/F7X2sn41jXRTVO1s8995z43pzexAgh5eOkcsg6DYakcQRUh34HK8gBivJQtPsnSFt0h6xdLDgJPX9KrEPIugPNpcPQpJ4A1IWGC3kJJE1aQRraHrxfM2oEWcsses/6+PHjkMlkaNOmDQBg48aNWLFiBVq1aoV58+ZBLi9/eDJCSAmJf3MoB7wM1eE/dP0kA9BcOADt3VQoeowC70b3A4llMCZASLsAdcoBCMVjs5fGefpBGtYR0pB24BTONoiQAIBFn0B/6aWXcOHCBQC63syefvppODs7Y/369XjrrbcsuStC6jxO6QJ5z2ch6/gEwOt+V7OH6Sj8dxk0N87YODri6JhGBfWFgyjc/CmK9qwyTNQSKSShHaCInQTlgGmQhXenRG1jFq1ZX7hwAe3atQMArF+/Hr1798aaNWuwf/9+PPPMM/j0008tuTtC6jyO4yBr0Q0SnxAU7VsLlnMPUBdBtW8thBbRkLUbQP2LkyphRXnQXDgI9YWDgMqwwRjn2gDS5t0gDetQb0azchQW/StnjEEQBAC6LkYff/xxALpuSO/dM92bDSGkcrynH5RxU6A6shHaaycBAJoLiRAepkHRYxS1FieVYgW5UJ/fq2u8qDVsCMb7NoU0PBoS/3BwPHX5aY8smqw7deqE999/HzExMdi9eze+/vprAEBqaip8fX0tuStC6h1OpoA8egQ0PiFQH/sbEDQQ7l5D4b9fQf7IaEgaUf/7xFi5SZrjIQlqA1lETxqy1QFYNFl/+umnGDNmDDZs2IB33nlHHNDjt99+E/sKJ4RUH8dxkDXrAt4rAKp9a8Dys8AKslG04zvIOw+FNKyDrUMkdoKpC6FO3gvN+f2GSVoihTSsE6QtHwHvSl1/OgqLJuuoqCicPn3aaP7HH38MiYSa+RNiKZKGTaCMnYKi/Wsh3L0KCFqoDv0OIfsuZG370+hF9RjTaqC5eAjqcwmGnZhIpJA26wJZRE9w1GmJw7Fosr5x4wY4jkOTJk0AAIcPH8aaNWvQqlUrvPjii5bcFSH1HufkCkW/56E+/rfYiYomeQ9Y7gPIuz1F4wHXM4wxaNPOQ318C1ju/ZIFvESXpFv1prYNDsyiP79Hjx6NXbt2AQAyMjLQv39/HD58GO+88w4WLFhgyV0RQgBwvATyToMh6/g4oO9F6sYZFO38Hqww18bRkdoiZN9F0e4fodrzs0GilgS3hXLQq5B3fJwStYOzaLI+c+YMunTpAgD49ddf0bp1axw4cACrV6/GypUrLbkrQkgpshbRUPT6DyDVdTwk3L+Jwu3fQsh7aOPIiDUxrRqqU/Eo3PIFhPSL4nzeOwTKuClQdB8J3rWBDSMklmLRZK1Wq6FQKADoHt0aPHgwAKBly5ZIT0+35K4IIWVIAsKhjHlRvB/Jcu6jKP4bCFm3bRwZsQbt7Sso3PIFNGcTxBGwOGcPyHs8A8WjL4Bv0Ni2ARKLsmiyjoyMxPLly7F3717Ex8djwIABAIC0tDQ0bEjdIxJibbyXPxT9XwLn1ggAwApyULj9O2jvXbdxZMRSmLoIqsMbULTzf2A5xZe8OR7SyD5QDnoV0qA2NKBSHWTRZL1o0SJ888036NOnD0aNGoW2bdsCADZt2iReHieEWBfv4gllzIslNStVAYp2rYD2zlWbxkVqTnvnqq42ffmIOI9vFATlgGmQR/UHJ6XxF+oqi7YG79OnD+7du4fs7Gx4eZU8v/fiiy/C2Zn6lSWktnBKFyj6TUDR3tW6Pp81KhTt/hGK3mMh8Qm1dXikiphWA/Wp7dCc3weA6WZK5ZC1i4O0WRd6VK8esPj/sEQiMUjUABASEgIfHx9L74oQUgFOpoCi93/A+7fQzdCoULT7J2jvpNo2MFIlLPcBirZ/C835vdAnat47GMrHXoaseTdK1PVEjWvWHTp0wI4dO+Dl5YX27dtXeK/k+PHjNd0dIaQKOIkMip6jUbRvDYS0C7qEnfAjFH3GQeITYuvwSCV8NA+g2fENoC7SzeAlkEX1hzS8B/XhXc/UOFkPGTJEbAE+dOjQmhZHCLEwTiKD4pFSCVurRtGen6B89AXwXgG2Do+YwAQttElb0FZ1SZzHuTaEoscz4BvQ/1l9VONkPXfuXJPvCSH2Q5ewx6Bo78+653HVRSjctRLK/i+CL245TuwDK8pH0b61EO5cEedJgtpA3mUoOJnShpERW7LadZTc3FxkZ2cbvAghtsNJpFA8Mhp8oyDdjKI8FO1aCSGf/jbthZCZgcJ/vxITtQAOfPtBkHd/mhJ1PWfRZJ2amopBgwbBxcUFHh4e8PLygpeXFzw9PY0anRFCah8nlUPReyw4D92QtSzvIYoSVoKpCm0cGdHeOo/C+G/A9L3OKVxwVNESkqad6blpYtlHt5599lkwxvDDDz/A19eXTjBC7BAnd4KizzgUbf8WLO8hWNZtFO3/BYre/wHH0+h4tqC+dBjqo5sAVtzau0Fj8N1GIithv40jI/bCosn65MmTOHbsGMLDwy1ZLCHEwnhndyj6jkfhtuWAKh9CxkWoj/8DeacnbB1avcIYg/r0dl2XocUkQW0g7zocGma7uIj9sehl8M6dO+PGjRuWLJIQYiW8W0Moeo4BimvTmosHob6QaOOo6g9WPAZ56UQtbdkT8u4jaXhTYsSiNevvv/8ekyZNwq1bt9C6dWvIZIYnXFRUlCV3RwipIYlPCOSdh0J16HcAgPr43+DdGkHi39zGkdVtTKuBKvFXaG+cLZ7DQdZxEGQtom0aF7FfFk3Wd+/exeXLlzF+/HhxHsdxYIyB4zhotVpL7o4QYgHSsA4Qsu9Ck7wHYAxFB9ZBGTcVvCs1CrUGplXrHs1KS9HN4CWQdx8JaWBr2wZG7JpFk/Xzzz+P9u3bY+3atdTAjBAHImvbHyz7LrS3kgFVAVT710IR8yI4iUW/Iuo9plGhaM/Puv7aAUAihaLns3Qlg1TKon+J165dw6ZNm9CsWTNLFksIsTKO4yHvNhyF/34FlvsAwoNbUB//G/LOQ2wdWp3BtGrDRC2VQ9HrP5D4htk2MOIQLNrArF+/fjh58qQliySE1BJO7gTFI6OB4tq05tJhaFKTbBtUHcG0Gt2lb32ilil0/bNToiZmsmjN+oknnsBrr72G06dPo02bNkYNzAYPHmzJ3RFCLIz38oe802CoDv0BAFAd2QC+QQB4Dxo1r7qYIECVuL7kHrVUrkvU+p7kCDGDRZP1pEmTAAALFiwwWkYNzAhxDNKwjtDevQbtlWO6QT8Sf4Wy/yS6f10NjAlQHf4T2htndDMkUt2lb0rUpIosehlcEIRyX5SoCXEc8o5PgHP3BgCwh+lQn9lp44gck/pkPLSpxUMD8xIoHhlDl75JtVh9QNTMzExr74IQYmGcVAZF9AiA031FaJL3QHv3qm2DcjDqi4d0j8MBAMdB3v1pSAJa2DYo4rAsmqwXLVqEdevWidMjRoxAgwYN0LhxY2p4RoiD4Rs0hqxNjG6CMagSfwNT04Af5tDcSob62F/itKzjE5AGRtowIuLoLJqsly9fjsDAQABAfHw8tm/fjq1bt+Kxxx7Dm2++acldEUJqgTSiJ3jvYAC6EbpUx/+xcUT2T3v/JlT714mDckgjekHWvKuNoyKOzqLJOiMjQ0zWmzdvxsiRIxEbG4u33noLR44cseSuCCG1gON5yLs9BUgVAADtlWPQZly2cVT2S8jPhmrvz4BWDQCQBEVB1ra/jaMidYFFk7WXl5c4kMfWrVsRE6O7hMYYs1oDs8GDByMoKAhKpRL+/v74z3/+g7S0NIN1Tp06hZ49e0KpVCIwMBAfffSRVWIhpC7iXRtA3n6AOK06sgGsOBmREkyrgWrfGrCCHAAA7x0Cebfh4DirNw0i9YBFz6Jhw4Zh9OjR6N+/P+7fv4/HHnsMAHDixAmr9WrWt29f/Prrr0hJScHvv/+Oy5cv46mnnhKXZ2dnIzY2FsHBwTh27Bg+/vhjzJs3D99++61V4iGkLpI07VRyOTz3AYRzu20ckX1hjEF1dBOE+7rKCufsCcUjo+lxN2IxFj2Tli5dipCQENy4cQMfffQRXF1dAQDp6emYMmWKJXcleu2118T3wcHBmDVrFoYOHQq1Wg2ZTIbVq1dDpVLhhx9+gFwuR2RkJJKSkrBkyRK8+OKLVomJkLqG43jIOw9F4dYvAUEL4cIBuCpa2Tosu6G5dEj3XDoASGRQ9BwDTuli26BInWLRZC2TyfDGG28YzS+dUK3pwYMHWL16Nbp37y72npaYmIhevXpBLpeL68XFxWHRokV4+PAhvLxoZCFCzMF7+EDaqjc0Z3YCTECEKhWMCbYOy+a0d69BfexvcVre5UnwDQJsGBGpiyx+jebixYvYtWsX7ty5A0Ew/EOeM2eOpXcHAJg5cya+/PJL5Ofno1u3bti8ebO4LCMjA6GhoQbr+/r6isvKS9ZFRUUoKioSp7OzswEAarUaanX179fpt61JGbXJ0eIFKGarat4duHYSyLkPTyEPmouHwbXoZuuozGKNY8xU+dDs/wUo/tHCt+gO1riVRfbhMOdEKfU15tr4vBxjxc8XWMB3332HyZMno1GjRvDz8zMYIpPjOBw/ftyscmbNmoVFixZVuE5ycjJatmwJALh37x4ePHiAa9euYf78+fDw8MDmzZvBcRxiY2MRGhqKb775Rtz23LlziIyMxLlz5xAREWGy/Hnz5mH+/PlG89esWQNnZ2ezPgchdZGnNhudi84DAFSQYr9TFDRcPbw3yxjaqi7CR5sJAHjIu+GYoiUYDQ1c7+Tn52P06NHIysqCu7u7VfZh0WQdHByMKVOmYObMmTUq5+7du7h//36F64SFhRlc2ta7efMmAgMDceDAAURHR2Ps2LHIzs7Ghg0bxHV27dqFfv364cGDB1WqWQcGBuLevXs1+s9Qq9WIj49H//79jQY6sUeOFi9AMdcGdeJ64NZZAADfPBqStnE2jqhylj7G2osHIZzcqpuQO0HafzI4J8t9UTvaOQHU35izs7PRqFEjqyZri/4cfvjwIUaMGFHjcry9veHt7V2tbfWX3vWJNjo6Gu+8847Y4AzQddgSHh5e4f1qhUIBhUJhNF8mk1nkJLRUObXF0eIFKGZrYm37o+jWOUjAIFw+DHl4N/BujWwdllkscYyFB7egPh0vTiu6PQWJe8OahmaSo5wTpdW3mGvjs1r00a0RI0Zg27ZtliyyQocOHcKXX36JpKQkXLt2DTt37sSoUaPQtGlTREdHAwBGjx4NuVyOCRMm4OzZs1i3bh0+++wzzJgxo9biJKSu4Zw9cU3qr5sQtFCf2GrbgGoR06hQdOBXQND1HSEN7wFJ45Y2jorUdRatWTdr1gzvvvsuDh48aHI86+nTp1tyd3B2dsYff/yBuXPnIi8vD/7+/hgwYABmz54t1oo9PDywbds2TJ06FR07dkSjRo0wZ84cemyLkBq6KvNHmDQbKMyF9lYytBmXIfFrauuwrE59Mh4s5x6A4v7T28baOCJSH1g0WX/77bdwdXXF7t27sXu3YacJHMdZPFm3adMGO3dWPnRfVFQU9u7da9F9E1LfaTkJJJEx0B7dAABQnfgHyrip4Pi622OX9k4qNBcO6CYkUsijR1DHJ6RWWPQsS01NtWRxhBA7xwVHgb9yGMKDNLDMDGivn4Y0pK2tw7IKpi6C6uDv4rQsKha8e/Xa1hBSVXX3JzAhxOo4joesbUm/4eozO8EE64wDYGvqpK1geQ8B6Pr9loZH2zgiUp9Y/PrNzZs3sWnTJly/fh0qlcpg2ZIlSyy9O0KIjfG+YeC9QyDcvQqWcw/aqychDetg67AsSptxGZpLh3UTEhnkXYfRAB2kVlk0We/YsQODBw9GWFgYzp8/j9atW+Pq1atgjKFDh7r1x0sI0eE4DrKoGBTt+B4AoD67C5KQtuB4iY0jswymVUN1ZKM4LWs3ALybdR7TIqQ8Fv1p+Pbbb+ONN97A6dOnoVQq8fvvv+PGjRvo3bu3RZ6/JoTYJ4lPKHhfXUtwlvsA2lTzeit0BJrkvWC5uk6a+EbBkDbvYuOISH1k0WSdnJyMsWPHAgCkUikKCgrg6uqKBQsWVNp9KCHEscmiYsT36jMJYFqNDaOxDCHnPtRni59s4XjIOw+my9/EJix61rm4uIj3qf39/XH58mVx2b179yy5K0KInZE0CgIf0AIAwPIzobly1MYR1YxujOq/AEH3o0Ma3h28p5+NoyL1lUWTdbdu3bBv3z4AwMCBA/H666/jgw8+wPPPP49u3RxjZB5CSPXJ25TUrjXJ+xy6Zbj2xlkIGRcBAJyzB2St+9k4IlKfWbSB2ZIlS5CbmwsAmD9/PnJzc7Fu3To0b96cWoITUg/wDRqD92sOIeMiWN5DaG+egzSoja3DqjKmLoL6eMkY1bIOg8DJjMcKIKS2WCxZa7Va3Lx5E1FRUQB0l8SXL19uqeIJIQ5CFtETRcU1Uk3yXkgCWxsMl+sINOf3gRXoxrDnA1pA0qSVjSMi9Z3FLoNLJBLExsbi4cOHliqSEOKAeN8wcF66QT6EB7cg3L1q24CqiBVkQ31edzsPHA95+0EO92OD1D0WvWfdunVrXLlyxZJFEkIcDMdxkLXsKU6rkx2rX37V6R2ARtdQVtqsM3h3xxj6k9RtFk3W77//Pt544w1s3rwZ6enpyM7ONngRQuoHSVBrcM6eAAAhLQVC1h3bBmQmIes2tFeO6SakCshaP2rbgAgpZpFkvWDBAuTl5WHgwIE4efIkBg8ejCZNmsDLywteXl7w9PSEl5eXJXZFCHEAHC+BNLy7OC1eVrZzqqStAGMAAFmr3uCULjaOiBAdizQwmz9/PiZNmoRdu3ZZojhCSB0gbdoJ6jM7AXUhtFeTwKL6g3Nys3VY5dJmXIaQdgGA7lGt0j82CLE1iyRrVvxLtHfv3pYojhBSB3AyBaTNukCTvAcQtNBcOQZZZB9bh2USYwzqU9vEaVlUf3BSmQ0jIsSQxe5ZU2tJQkhZ0mZdAOi+GzSXj4AJgm0DKoeQfhHC/ZsAAM7DF5I6OiY3cVwWe866RYsWlSbsBw8eWGp3hBAHwLt6gfdvDiH9AlheJoSMi5AEhNs6LAOMMd3l+mKy1v2o/29idyyWrOfPnw8PDw9LFUcIqSOkzbpAla67F6y5dNjukrWQcRnC/RsAAM7DB5JA6gCF2B+LJetnnnkGPj4+liqOEFJHSAJagHNyByvIhjYtBUJeJngXT1uHBcBErTqyL9WqiV2yyFlJ96sJIeXheAmkTTvpJhiDRv8csx0Qbl+BcO8aAIBz94YksLWNIyLENIska31rcEIIMUXStBNQ/KNee/mI3YzGZVSr5qlWTeyTRc5MQRDoEjghpFy8swckAS0BAKwgB9q0FBtHBGjvXhX7LefcGkHigKODkfqDfkYSQmqFtFln8b3m0hEbRlIcw/kD4ntZq95UqyZ2jc5OQkit4P2al/QXnnEJrCDXZrEIuQ+gvXUOAMA5uUESHGWzWAgxByVrQkit4Hi+pLMRJkBz/ZTNYtFcOCj2AS5t3hWcxGIPxhBiFZSsCSG1RhrSTnyvvZpkkxiYuhCay0d1ExJpcS9rhNg3StaEkFrDe/iA8/IHAAgPbkHIvlfrMQhXkwBNEQBAEtIOnIJG1iL2j5I1IaRWla5da64l1e7OGYNw6aA4KaORtYiDoGRNCKlVkqAo6Af30F49Wav9NHhrM4G8TAAA79cMvIdvre2bkJqgZE0IqVW8szt43zAAAMt9IPbLXRuCNBnie6pVE0dCyZoQUuts0dCM5dxDAyEHgK4TFN6/ea3slxBLoGRNCKl1ksBWgEQGANBcO10r3Y8KV0+I76VNO9OAHcSh0NlKCKl1nEwJSeMI3YQqH0L6RavujwlaXStwAOB4SEPbWXV/hFgaJWtCiE1IQkp6DdPcOGvVfWnTUoCiPAAAFxAOTulq1f0RYmmUrAkhNiHxawZI5QAA7a1kq14KFztBAcCHdrDafgixFkrWhBCb4CQycSQuqAog3Em1yn6E/CwI6RcAAAWcHJxvU6vshxBromRNCLEZSWAr8b3WSpfCtanHxX7A0ySNqGEZcUh01hJCbEbi3wIoHkRDc/McmCBYtHzGBGiuHBen06TeFi2fkNpCyZoQYjOcTAGJ/nnnwlwI969btHzhdipY7gPdvnybopBXWLR8QmoLJWtCiE1JmrQW31v6UrimVIcrfEh7i5ZNSG2iZE0IsSlJ43CAlwAAtDfOWayvcKZRlyR/mQJcQLhFyiXEFihZE0JsipM7lfQVnp8J4cEti5SrTUspGQqzSSS44h7TCHFElKwJITYnDYwU31vqUri21PCb0pC2FimTEFuhZE0IsTlJ41YAVzxs5s2zNb4UzlQF0Kbpnq2G0hW8T1hNQyTEpihZE0JsjlO6gPcOAQCwnPtg2XdrVJ72xhmguEc0aXAUOJ6+6ohjqzNncFFREdq1aweO45CUlGSw7NSpU+jZsyeUSiUCAwPx0Ucf2SZIQki5JE1KdZBys2aXwjVXT5aUG0yXwInjqzPJ+q233kJAQIDR/OzsbMTGxiI4OBjHjh3Dxx9/jHnz5uHbb7+1QZSEkPJImkSI77U3k6tdjpCfBeHOVQAA59YQfIPGNQ2NEJurE8l6y5Yt2LZtGxYvXmy0bPXq1VCpVPjhhx8QGRmJZ555BtOnT8eSJUtsECkhpDy8ixc4L38AgPDgFoS8zGqVo712CoDunrc0uC244nvhhDgyqa0DqKnbt29j4sSJ2LBhA5ydnY2WJyYmolevXpDL5eK8uLg4LFq0CA8fPoSXl5fJcouKilBUVCROZ2dnAwDUajXUanW149VvW5MyapOjxQtQzLXBWvFy/uFgD9MBAKrrZyBp1rXqsZXqCIU1jjSKtb4fY2uqrzHXxuflmKV6ILABxhgGDhyIHj16YPbs2bh69SpCQ0Nx4sQJtGvXDgAQGxuL0NBQfPPNN+J2586dQ2RkJM6dO4eIiAiTZc+bNw/z5883mr9mzRqTPwoIITXnKuQjuvAMAOA+747jypZV2t5FKED3wtMAgCzeBYeVkZVsQUjN5efnY/To0cjKyoK7u7tV9mGXNetZs2Zh0aJFFa6TnJyMbdu2IScnB2+//bbFY3j77bcxY8YMcTo7OxuBgYGIjY2t0X+GWq1GfHw8+vfvD5nM/jtpcLR4AYq5NlgrXsYYNFtvAXkP0ZDl4LGYvuDkTmZvrz2zA8J53XuvNj0xsHk3q8dsLY4WL1B/Y9ZfebUmu0zWr7/+OsaNG1fhOmFhYdi5cycSExOhUBh2zt+pUyeMGTMGP/74I/z8/HD79m2D5fppPz+/cstXKBRG5QKATCazyEloqXJqi6PFC1DMtcEq8TZpBU3KfoAx8HcuQxpqXp/ejAnQ3NDVqsHxUIS2B2ciNjrG1lffYq6Nz2qXydrb2xve3pUPZff555/j/fffF6fT0tIQFxeHdevWoWtX3b2u6OhovPPOO1Cr1eIBjY+PR3h4eLn3q2tCq9VWeP9CrVZDKpWisLAQWq3W4vu3NEeLF7D/mOVyOXh67rdcksDiZA1dq3Bzk7Vw7zpYcaM03q8pOCdXa4VISK2zy2RtrqCgIINpV1fdH2fTpk3RpEkTAMDo0aMxf/58TJgwATNnzsSZM2fw2WefYenSpRaNhTGGjIwMZGZmVrqen58fbty44RCtVB0tXsD+Y+Z5HqGhoQaNHkkJvmEQoHABivKgTb8AplGDk1Zec9GWalgmDW5nvQAJsQGHTtbm8PDwwLZt2zB16lR07NgRjRo1wpw5c/Diiy9adD/6RO3j4wNnZ+dyk4QgCMjNzYWrq6tD1K4cLV7AvmMWBAFpaWlIT09HUFCQXf6YsDWO5yFp3BLaK8cArRrajIuQluowxRSm1UBzXdcwDRKZwTPbhNQFdSpZh4SEmOxTOCoqCnv37rXafrVarZioGzZsWOG6giBApVJBqVTaXSIxxdHiBew/Zm9vb6SlpUGj0Tjcfb3aIm3SSpesAWhTkypN1tr0C4CqAICuJzROZtzehBBHZn/fZA5If4+aHuki5tBf/rbH++n2gvdvDih1t7W0t5LBCipubast1b0ojbBF6iJK1hZElzSJOeg8qRzHSyAN66ibYAI0xbVsU5iqENpbxc9rKVzA+zWrhQgJqV2UrAkhdknatDMA3Q8bzeWjYIJgcj3tjdOAoNFtExwFjpfUVoiE1BpK1qRcCQkJkEgkyMrKsnUo5QoJCcGnn35q6zCIFfCuXuD9dbVklpcJIeOi0TpMq4H67G5xWkKXwEkdRcm6nuI4rsLXvHnzbB2iQxo3bhyGDh1q6zDqDGmzLuJ7zeUjRss1Fw+B5T0EAPC+TcE3aFJrsRFSm+pUa3BivvT0dPH9unXrMGfOHKSkpIjzXF1dcfTo0SqXq1Kp6uXzw1qtlu5FW4EkIByckxtYQQ60t1Ig5GeDd9Z198tUBVCf3VW8Jgd5uwH0f0DqLKpZ11N+fn7iy8PDAxzHGczTdzADAElJSejSpQucnZ3RvXt3g6Q+b948tGvXDt9//z1CQ0OhVCoBANevX8eQIUPg6uoKd3d3jBw50qDbV1M10FdffRV9+vQRp3NycjBmzBi4uLjA398fS5cuRZ8+ffDqq68abJefn4/nn38ebm5uCAoKqnSs8j59+mDatGmYNm0aPDw80KhRI7z77rsGj/09fPgQY8eOhZeXF5ydnfHYY4/h4sWSy7ArV66Ep6cnNm3ahFatWkGhUOD555/Hjz/+iI0bN4pXKBISEir7ryAV4HgJJGGddBNMgPZKyQ9I9bk9JY9rhbQF38B4PHtC6gpK1qRS77//Pj7++GMcPXoUUqkUzz//vMHyS5cu4ffff8cff/yBpKQkCIKAIUOG4MGDB9i9ezfi4+Nx5coVPP3001Xa74wZM7B//35s2rQJ8fHx2Lt3L44fP2603ieffIJOnTrhxIkTmDJlCqZOnWqQWE358ccfIZVKcfjwYXz22WdYsmQJvv/+e3H5uHHjcPToUWzatAmJiYniCG+lu5LNz8/HokWL8P333+Ps2bP4/PPPMXLkSAwYMADp6elIT09H9+7dq/SZiTFp005AcY1ZfX4fVKe3Q3v/JjQpB3Qr8FLIomJsGCEh1keXwa2k8N9lYAW5RvMZAJkgoJDnYY0LdpyTK5RxUy1a5uzZs9G7d2/wPI9Zs2Zh0KBBKCwsFGvRKpUKP/30k9ife3x8PE6fPo3U1FQEBgYCAH766SdERkbiyJEj6Ny5c6X7zMnJwY8//og1a9bg0UcfBQCsWLECAQHGtaeBAwdiypQpAICZM2di6dKl2Lt3Lzp27Fhu+YGBgVi6dCk4jkN4eDhOnz6NpUuXYuLEibh48SI2bdqE/fv3i8l29erVCAwMxIYNGzBixAgAuufrv/rqK7RtW9KoycnJCUVFRRUOEkOqhnfx1PVodjMZUBdBc2YXNGd2iculLaLBu1i+n39C7AklaythBbnlduSgT9KOMpB4ZGTJmMD+/v4AgDt37oh9swcHBxsMvJKcnIzAwEAxUQNAq1at4OnpieTkZLOS9ZUrV6BWq9GlS0kDIw8PD4SHhxutGxUVJb7XX86/d+9eheV369bN4P5mdHQ0PvnkE2i1WiQnJ0MqlYqDwQBAw4YNER4ejuTkZHGeXC432DexHnnX4VDxm6C9cQZgpR7hkjtBFtnbdoERUksoWVtJeSP+MABMEMBZsWZtaaW7xNQnOKHUM68uLi5VLpPneaOuYSsarczc+ABdjEI5z+RakpOTEzVoqiWc3AmKHk9DyIuD5uIhXctwdSHkHR6v0njXhDgqStZWUt6laEEQkJ2dDXd3d7vst9oSIiIicOPGDdy4cUOsXZ87dw6ZmZlo1UrXx7O3tzfOnDljsF1SUpKYeMPCwiCTyXDkyBGxBp+VlYULFy6gV69eNY7x0KFDBtMHDx5E8+bNIZFIEBERAY1Gg0OHDomXwe/fv4+UlBQx/vLI5XLqRtSKeBdPyNvFQdbmUUCrpkRN6o26mS2ITcXExKBNmzYYM2YMjh8/jsOHD2Ps2LHo3bs3OnXStezt168fjh49ip9++gkXL17E3LlzDZK3m5sbnnvuObz55pvYtWsXzp49iwkTJoDneYvUZq9fv44ZM2YgJSUFa9euxRdffIFXXnkFANC8eXMMGTIEEydOxL59+3Dy5Ek8++yzaNy4MYYMGVJhuSEhITh16hRSUlJw7969al8tIBXjJFJK1KReoWRNLI7jOGzcuBFeXl7o1asXYmJiEBYWhnXr1onrxMXF4d1338Vbb72Fzp07IycnB2PHjjUoZ8mSJYiOjsbjjz+OmJgY9OjRAxEREWLDtpoYO3YsCgoK0KVLF0ydOhWvvPKKwbCpK1asQMeOHfH4448jOjoajDH8888/lY6SNXHiRISHh6NTp07w9vbG/v37axwrIYSAEbNkZWUxACwrK8toWUFBATt37hwrKCiotBytVssePnzItFqtNcK0OHuKNzc3l3l4eLDvv/++wvUqi7l3797slVdesUKE5jF1vqhUKrZhwwamUqlsFldVOFq8jDlezI4WL2P1N+aK8oOl0D1rYrdOnDiB8+fPo0uXLsjKysKCBQsAoNJL0YQQUtdQsiZ2bfHixUhJSYFcLkfHjh2xd+9eNGrUyNZhEUJIraJkTexW+/btcexY+eMYVxd1AUoIcTTUwIwQQgixc5SsCSGEEDtHyZoQQgixc5SsCSGEEDtHyZoQQgixc5SsCSGEEDtHyZoQQgixc5Ss67mMjAy8/PLLCAsLg0KhQGBgIJ544gns2LHD1qHVioSEBHAch8zMTFuHQggh5aJOUeqxq1evokePHvD09MTHH3+MNm3aQK1W499//8XUqVNx/vx5k9up1epKB7RwBDQiFiHEUVDNuh6bMmUKOI7D4cOHMXz4cLRo0QKRkZGYMWMGDh48KK7n5eWFr7/+GoMHD4aLiws++OADAMDXX3+Npk2bQi6XIzw8HKtWrRK3YYxh3rx5CAoKgkKhQEBAAKZPny4u/+qrr9C8eXMolUr4+vriqaeeKjfOlStXwtPTExs2bBC3iYuLw40bNwzW08ejVCrRuXNng3gA3WhgpT/HxIkT0bdvX/EzchyHcePGVft4EkKItVDNup568OABtm7dig8++AAuLi5Gyz09PQ2mFyxYgA8//BCffvoppFIp/vzzT7zyyiv49NNPERMTg82bN2P8+PFo0qQJ+vbti99//x1Lly7FL7/8gsjISGRkZODkyZMAgKNHj2L69OlYtWoVunfvjgcPHmDv3r0Vxpufn48PPvgAP/30E+RyOaZMmYJnnnlGHIKydDz9+vXD77//jgkTJiAoKEhMyAAwb9488XNIJBIMHjwYw4cPR0pKCtzd3eHkRGMkE0LsDyVrK7nZeSY0GZkmlzFBQCZvnYsaUj9PNDmyqNL1Ll26BMYYWrZsaVa5o0aNwvjx4w2mx40bhylTpgCAWBtfvHgx+vbti+vXr8PPzw8xMTGQyWQICgpCly5dAADXr1+Hi4sLHn/8cbi5uSE4OBjt27evcP9qtRpffvklunbtCgD48ccfERERgcOHD6NLly5YvHixGI8gCJg6dSqSkpLEePRGjx5t8DlSU1MBAD4+PkY/UAghxF7QZXAr0WRkQnvrgcmXkF7+spq+yvuBUBZjrEqfp2PHjgbTycnJ6NGjh8G8Hj16IDk5GQAwYsQIFBQUICwsDBMnTsSff/4JjUYDAOjfvz+Cg4MRFhaG//znP1i9ejXy8/Mr3L9UKkXnzp3F6ZYtW8LT01PcX2Xx6HXq1KkKn5oQQuwD1aytROrnWe4yJgjgrFizNkfz5s3BcVy5jcjKMnWpvCKBgYFISUnB9u3bER8fjylTpuDjjz/G7t274ebmhuPHjyMhIQHbtm3DnDlzMG/ePBw5csTqtduqfg5CCLEHlKytpLxL0YIgIDs7G+7u7uCtlLDN0aBBA8TFxWHZsmWYPn26URLLzMysMHFGRERg//79eO6558R5+/fvR6tWrcRpJycnPPHEE3jiiScwdepUtGzZEqdPn0aHDh0glUoRExODmJgYzJ07F56enti5cyeGDRtmcn8ajQZHjx4VL6WnpKQgMzMTERERZsdjilwuBwBotdoK1yOEEFuiZF2PLVu2DD169ECXLl2wYMECREVFQaPRID4+Hl9//bXRJeTS3nzzTYwcORLt27dHTEwM/vrrL/zxxx/Yvn07AF0Lbq1Wi65du8LZ2Rk///wznJycEBwcjM2bN+PKlSvo1asXvLy88M8//0AQBISHh5e7P5lMhpdffhmff/45pFIppk2bhm7duonJu3Q8/fr1w2+//YY///xTjKc8wcHB4DgOmzdvxsCBA+Hk5ARXV9dqHE1CCLEeumddj4WFheH48ePo27cvXn/9dbRu3Rr9+/fHjh078PXXX1e47dChQ/HZZ59h8eLFiIyMxDfffIMVK1agT58+AHStyb/77jv06NEDUVFR2L59O/766y80bNgQnp6e+OOPP9CvXz9ERERg+fLlWLt2LSIjI8vdn7OzM2bOnInRo0ejR48ecHV1xbp160zG06ZNG6xcuRL/+9//xHjK07hxY8yfPx+zZs2Cr68vpk2bZvbxI4SQ2kI163rO398fX375Jb788sty13n48CHc3d2N5k+ePBmTJ082uc3QoUMxdOhQk8seeeQRJCQkVDnWYcOGlXuZvHQ8pW81lFZeo7p3330X7777bpXjIYSQ2kI1a0IIIcTOUbImhBBC7Bwla2L3xo0bRwNtEELqNUrWhBBCiJ2jZG1BVe0VjNRPdJ4QQqqKkrUF6IeLrKzLTEIAQKVSAQAkEomNIyGEOAp6dMsCJBIJPD09cefOHQC6Z4I5jjO5riAIUKlUKCwstGkPZuZytHgB+45ZEATcvXsXzs7OkErpz48QYh76trAQPz8/ABATdnkYYygoKICTk1O5Cd2eOFq8gP3HzPM8goKC7DI2Qoh9omRtIRzHwd/fHz4+PlCr1eWup1arsWfPHvTq1Uu8fG7PHC1ewP5jlsvldlfjJ4TYN0rWFiaRSCq8FymRSKDRaKBUKu0ykZTlaPECjhkzIYRUxOF/3oeEhIDjOIPXhx9+aLDOqVOn0LNnTyiVSgQGBuKjjz6yUbSEEEJI1dWJmvWCBQswceJEcdrNzU18n52djdjYWMTExGD58uU4ffo0nn/+eXh6euLFF1+0RbiEEEJIldSJZO3m5iY28Cpr9erVUKlU+OGHHyCXyxEZGYmkpCQsWbKEkjUhhBCHUCeS9Ycffoj33nsPQUFBGD16NF577TXxsZjExET06tULcrlcXD8uLg6LFi3Cw4cP4eXlZbLMoqIiFBUVidNZWVkAgAcPHlTYgKwyarUa+fn5uH//vkPcT3W0eAGKuTY4WryA48XsaPEC9TfmnJwcANbt8Mjhk/X06dPRoUMHNGjQAAcOHMDbb7+N9PR0LFmyBACQkZGB0NBQg218fX3FZeUl64ULF2L+/PlG88uWRQghhAC6pO3h4WGVsjlmh30fzpo1C4sWLapwneTkZLRs2dJo/g8//ICXXnoJubm5UCgUiI2NRWhoKL755htxnXPnziEyMhLnzp1DRESEyfLL1qwFQcCDBw/QsGHDGj0fm52djcDAQNy4ccPkGNH2xtHiBSjm2uBo8QKOF7OjxQvU35gZY8jJyUFAQIDVHsu0y5r166+/jnHjxlW4TlhYmMn5Xbt2hUajwdWrVxEeHg4/Pz/cvn3bYB39dHn3uQFAoVBAoVAYzPP09Kw8eDO5u7s7zMkMOF68AMVcGxwtXsDxYna0eIH6GbO1atR6dpmsvb294e3tXa1tk5KSwPM8fHx8AADR0dF45513oFarxfsR8fHxCA8PL/cSOCGEEGJPHPo568TERHz66ac4efIkrly5gtWrV+O1117Ds88+Kybi0aNHQy6XY8KECTh79izWrVuHzz77DDNmzLBx9IQQQoh57LJmbS6FQoFffvkF8+bNQ1FREUJDQ/Haa68ZJGIPDw9s27YNU6dORceOHdGoUSPMmTPHZo9tKRQKzJ071+gSu71ytHgBirk2OFq8gOPF7GjxAhSzNdllAzNCCCGElHDoy+CEEEJIfUDJmhBCCLFzlKwJIYQQO0fJmhBCCLFzlKzNtGfPHjzxxBMICAgAx3HYsGGD2dvu378fUqkU7dq1M5g/b948o+E9y/bKVlhYiKlTp6Jhw4ZwdXXF8OHDjTp5qc2YTQ1JynEcpk6dKq7Tp08fo+WTJk2ySswJCQkm48nIyDBYb9myZQgJCYFSqUTXrl1x+PBhg+XVPc7WiHfhwoXo3Lkz3Nzc4OPjg6FDhyIlJcWgHHs7xvZ2LpsTszXP5er87RUVFeGdd95BcHAwFAoFQkJC8MMPPxiss379erRs2RJKpRJt2rTBP//8Y7CcMYY5c+bA398fTk5OiImJwcWLFyvdt7Vi/u6779CzZ094eXnBy8sLMTExRn9748aNMzrGAwYMsEm8K1euNIpFqVQalFGTY1wTlKzNlJeXh7Zt22LZsmVV2i4zMxNjx47Fo48+anJ5ZGQk0tPTxde+ffsMlr/22mv466+/sH79euzevRtpaWkYNmyYzWI+cuSIQbzx8fEAgBEjRhisN3HiRIP1zB1DvLoxp6SkGOxP3ykOAKxbtw4zZszA3Llzcfz4cbRt2xZxcXG4c+eOuE51j7M14t29ezemTp2KgwcPIj4+Hmq1GrGxscjLyzMow56OMWCf53JFMVvzXK5OvCNHjsSOHTvwv//9DykpKVi7di3Cw8PF5QcOHMCoUaMwYcIEnDhxAkOHDsXQoUNx5swZcZ2PPvoIn3/+OZYvX45Dhw7BxcUFcXFxKCwstEnMCQkJGDVqFHbt2oXExEQEBgYiNjYWt27dMihnwIABBsd47dq1NokX0PVkVjqWa9euGSyvyTGuEUaqDAD7888/zVr36aefZrNnz2Zz585lbdu2NVhmal5pmZmZTCaTsfXr14vzkpOTGQCWmJhok5jLeuWVV1jTpk2ZIAjivN69e7NXXnmlSvGZYk7Mu3btYgDYw4cPy12nS5cubOrUqeK0VqtlAQEBbOHChYwxyx1nS8Vb1p07dxgAtnv3bnGevR1jezuXq3OcrXUumxPvli1bmIeHB7t//36564wcOZINGjTIYF7Xrl3ZSy+9xBhjTBAE5ufnxz7++GNxeWZmJlMoFGzt2rU2ibksjUbD3Nzc2I8//ijOe+6559iQIUOqFF9Zlop3xYoVzMPDo9zlljzGVUU1aytasWIFrly5grlz55a7zsWLFxEQEICwsDCMGTMG169fF5cdO3YMarUaMTEx4ryWLVsiKCgIiYmJNotZT6VS4eeff8bzzz9vNLjJ6tWr0ahRI7Ru3Rpvv/028vPzrRKvXrt27eDv74/+/ftj//79BjEeO3bM4BjyPI+YmBjxGNriOJcXryn64VkbNGhgMN9ejrGevZ3L5sSsZ+tzedOmTejUqRM++ugjNG7cGC1atMAbb7yBgoICcZ3ExESD4wfohvvVH7/U1FRkZGQYrOPh4YGuXbta5RibE3NZ+fn5UKvVRudyQkICfHx8EB4ejsmTJ+P+/fs2izc3NxfBwcEIDAzEkCFDcPbsWXFZbR/j0hy6BzN7dvHiRcyaNQt79+4Vx9Yuq2vXrli5ciXCw8ORnp6O+fPno2fPnjhz5gzc3NyQkZEBuVxuNICIr6+v0T3Z2oq5tA0bNiAzM9No0JXRo0cjODgYAQEBOHXqFGbOnImUlBT88ccfFo/Z398fy5cvR6dOnVBUVITvv/8effr0waFDh9ChQwfcu3cPWq1WHBZVz9fXF+fPnweAWj3OlcVbliAIePXVV9GjRw+0bt1anG9Pxxiwv3O5qsfZ1ufylStXsG/fPiiVSvz555+4d+8epkyZgvv372PFihUAdOepqfNYf/z0/1a0Tm3HXNbMmTMREBBgkOwGDBiAYcOGITQ0FJcvX8b//d//4bHHHkNiYiIkEkmtxhseHo4ffvgBUVFRyMrKwuLFi9G9e3ecPXsWTZo0qfVjbMCq9fY6CpVcctFoNKxTp07s66+/FueZc0n54cOHzN3dnX3//feMMcZWr17N5HK50XqdO3dmb731ls1jjo2NZY8//nil+96xYwcDwC5dulSVkKt06b60Xr16sWeffZYxxtitW7cYAHbgwAGDdd58803WpUsXxpjljrMl4i1r0qRJLDg4mN24caPCMmx5jE2x5blcnopitua5bE68/fv3Z0qlkmVmZorzfv/9d8ZxHMvPz2eMMSaTydiaNWsMtlu2bBnz8fFhjDG2f/9+BoClpaUZrDNixAg2cuRIs+O1ZMylLVy4kHl5ebGTJ09WWO7ly5cZALZ9+3abxssYYyqVijVt2pTNnj2bMWbZY1xVdBncCnJycnD06FFMmzYNUqkUUqkUCxYswMmTJyGVSrFz506T23l6eqJFixa4dOkSAN0QniqVCpmZmQbr3b59u8LhPWsj5mvXrmH79u144YUXKi27a9euACB+Lmvr0qWLuK9GjRpBIpGYHCZVfwxr8zhXFm9p06ZNw+bNm7Fr1y40adKkwjJseYxNseW5XJ7yYraHc9nf3x+NGzc2GGYxIiICjDHcvHkTAMod7rf0eayfV946tR2z3uLFi/Hhhx9i27ZtiIqKqrDcsLAwNGrUyCbHuCyZTIb27dsbnMdA7R3j0ihZW4G7uztOnz6NpKQk8TVp0iSEh4cjKSlJ/IMvKzc3F5cvX4a/vz8AoGPHjpDJZNixY4e4TkpKCq5fv47o6GibxrxixQr4+Phg0KBBlZadlJQEAOLnsrakpCRxX3K5HB07djQ4hoIgYMeOHeIxrM3jXFm8gO7RkGnTpuHPP//Ezp07ERoaalYZgG2OsSm2PJfLU17M9nAu9+jRA2lpacjNzRXnXbhwATzPiz/UoqOjDY4foBvuV3/8QkND4efnZ7BOdnY2Dh06ZJVjbE7MgK719HvvvYetW7eiU6dOlZZ78+ZN3L9/3ybHuCytVovTp0+LsdT2MTZg1Xp7HZKTk8NOnDjBTpw4wQCwJUuWsBMnTrBr164xxhibNWsW+89//lPu9qYuKb/++ussISGBpaamsv3797OYmBjWqFEjdufOHXGdSZMmsaCgILZz50529OhRFh0dzaKjo20WM2O61tRBQUFs5syZRssuXbrEFixYwI4ePcpSU1PZxo0bWVhYGOvVq5dVYl66dCnbsGEDu3jxIjt9+jR75ZVXGM/zBpfQfvnlF6ZQKNjKlSvZuXPn2Isvvsg8PT1ZRkaGuE51j7M14p08eTLz8PBgCQkJLD09XXzpL9XZ4zG2t3PZnJgZs965XNV4c3JyWJMmTdhTTz3Fzp49y3bv3s2aN2/OXnjhBXGd/fv3M6lUyhYvXsySk5PZ3LlzmUwmY6dPnxbX+fDDD5mnpyfbuHEjO3XqFBsyZAgLDQ1lBQUFNon5ww8/ZHK5nP32228G53JOTo5YxhtvvMESExNZamoq2759O+vQoQNr3rw5KywsrPV458+fz/799192+fJlduzYMfbMM88wpVLJzp49a5FjXBOUrM2kfxSk7Ou5555jjOkeP+jdu3e525tKfE8//TTz9/dncrmcNW7cmD399NNG98IKCgrYlClTmJeXF3N2dmZPPvkkS09Pt1nMjDH277//MgAsJSXFaNn169dZr169WIMGDZhCoWDNmjVjb775JsvKyrJKzIsWLWJNmzZlSqWSNWjQgPXp04ft3LnTqNwvvviCBQUFMblczrp06cIOHjxosLy6x9ka8ZoqDwBbsWIFY8w+j7G9ncvmnhfWOper87eXnJzMYmJimJOTE2vSpAmbMWOG0b3UX3/9lbVo0YLJ5XIWGRnJ/v77b4PlgiCwd999l/n6+jKFQsEeffRRk5+ttmIODg42WebcuXMZY4zl5+ez2NhY5u3tzWQyGQsODmYTJ040+CFdm/G++uqr4veEr68vGzhwIDt+/LjFjnFN0BCZhBBCiJ2je9aEEEKInaNkTQghhNg5StaEEEKInaNkTQghhNg5StaEEEKInaNkTQghhNg5StaEEEKInaNkTUg9MG/ePLRr187WYYg4jsOGDRuqvF1KSgr8/PyQk5Nj+aBKuXfvHnx8fMrtM5qQ2kbJmhALWb58Odzc3KDRaMR5ubm5kMlk6NOnj8G6CQkJ4DgOly9fruUoa5elfyS8/fbbePnll+Hm5maxMk1p1KgRxo4da9a47oTUBkrWhFhI3759kZubi6NHj4rz9u7dCz8/Pxw6dAiFhYXi/F27diEoKAhNmza1RagO6fr169i8ebPRmNPWMn78eKxevRoPHjyolf0RUhFK1oRYSHh4OPz9/ZGQkCDOS0hIwJAhQxAaGoqDBw8azO/bty8AYNWqVejUqRPc3Nzg5+eH0aNH486dOwB0I4Q1adIEX3/9tcG+Tpw4AZ7nce3aNQBAZmYmXnjhBXh7e8Pd3R39+vXDyZMnK4z3+++/R0REBJRKJVq2bImvvvpKXHb16lVwHIc//vgDffv2hbOzM9q2bYvExESDMr777jsEBgbC2dkZTz75JJYsWQJPT08AwMqVKzF//nycPHkSHMeB4zisXLlS3PbevXt48skn4ezsjObNm2PTpk0Vxvvrr7+ibdu2aNy4sTjPVM39008/RUhIiDg9btw4DB06FP/973/h6+sLT09PLFiwABqNBm+++SYaNGiAJk2aYMWKFQblREZGIiAgAH/++WeFcRFSGyhZE2JBffv2xa5du8TpXbt2oU+fPujdu7c4v6CgAIcOHRKTtVqtxnvvvYeTJ09iw4YNuHr1qlh75Hkeo0aNwpo1awz2s3r1avTo0QPBwcEAgBEjRuDOnTvYsmULjh07hg4dOuDRRx8tt1a4evVqzJkzBx988AGSk5Px3//+F++++y5+/PFHg/XeeecdvPHGG0hKSkKLFi0watQo8TL//v37MWnSJLzyyitISkpC//798cEHH4jbPv3003j99dcRGRmJ9PR0pKen4+mnnxaXz58/HyNHjsSpU6cwcOBAjBkzpsJa7N69e80aYtGUnTt3Ii0tDXv27MGSJUswd+5cPP744/Dy8sKhQ4cwadIkvPTSS0b3qLt06YK9e/dWa5+EWJTVhwohpB757rvvmIuLC1Or1Sw7O5tJpVJ2584dtmbNGnFoxR07djAA4lB+ZR05coQBEIcRPHHiBOM4Tlxfq9Wyxo0bs6+//poxxtjevXuZu7u70ZCCTZs2Zd988w1jzHgEtaZNm7I1a9YYrP/ee++JQ1ampqYyAOz7778Xl589e5YBYMnJyYwx3UhbgwYNMihjzJgxzMPDQ5wub+Q2AGz27NnidG5uLgPAtmzZYvKYMMZY27Zt2YIFCwzmmSp/6dKlLDg4WJx+7rnnWHBwMNNqteK88PBw1rNnT3Fao9EwFxcXtnbtWoOyXnvtNdanT59yYyKktlDNmhAL6tOnD/Ly8nDkyBHs3bsXLVq0gLe3N3r37i3et05ISEBYWBiCgoIAAMeOHcMTTzyBoKAguLm5oXfv3gB092gBoF27doiIiBBr17t378adO3cwYsQIAMDJkyeRm5uLhg0bwtXVVXylpqaabMCWl5eHy5cvY8KECQbrv//++0brR0VFie/9/f0BQLxEn5KSgi5duhisX3a6IqXLdnFxgbu7u1i2KQUFBVAqlWaXX1pkZCR4vuTrztfXF23atBGnJRIJGjZsaLR/Jycn5OfnV2ufhFiS1NYBEFKXNGvWDE2aNMGuXbvw8OFDMfEGBAQgMDAQBw4cwK5du9CvXz8AusQZFxeHuLg4rF69Gt7e3rh+/Tri4uKgUqnEcseMGYM1a9Zg1qxZWLNmDQYMGICGDRsC0LU4L3uvXE9//7i03NxcALr7zV27djVYJpFIDKZlMpn4nuM4ALr76JZQumx9+RWV3ahRIzx8+LDScrVarVn7Mmf/Dx48gLe3d6X7JMTaKFkTYmF9+/ZFQkICHj58iDfffFOc36tXL2zZsgWHDx/G5MmTAQDnz5/H/fv38eGHHyIwMBAADFqT640ePRqzZ8/GsWPH8Ntvv2H58uXisg4dOiAjIwNSqdSgYVV5fH19ERAQgCtXrmDMmDHV/pzh4eE4cuSIwbyy03K53GTyrI727dvj3LlzRvNv375tMH3lyhWL7A8Azpw5Y/TYHSG2QJfBCbGwvn37Yt++fUhKShJr1gDQu3dvfPPNN1CpVGLjsqCgIMjlcnzxxRe4cuUKNm3ahPfee8+ozJCQEHTv3h0TJkyAVqvF4MGDxWUxMTGIjo7G0KFDsW3bNly9ehUHDhzAO++8YzLxA7rGXQsXLsTnn3+OCxcu4PTp01ixYgWWLFli9ud8+eWX8c8//2DJkiW4ePEivvnmG2zZskWsgevjTk1NRVJSEu7du4eioiKzyy8rLi4OiYmJRsk/IyMDCxYswJUrV/D7779j1apVePjwIc6fP1/tfQFAfn4+jh07htjY2BqVQ4glULImxML69u2LgoICNGvWDL6+vuL83r17IycnR3zECwC8vb2xcuVKrF+/Hq1atcKHH36IxYsXmyx3zJgxOHnyJJ588kk4OTmJ8zmOwz///INevXph/PjxaNGiBZ555hlcu3bNYP+lvfDCC/j++++xYsUKtGnTBr1798bKlSsRGhpq9ufs0aMHli9fjiVLlqBt27bYunUrXnvtNYP7ysOHD8eAAQPQt29feHt7Y+3atWaXX9Zjjz0GqVSK7du3G8xv3bo1Lly4gMjISLz77rv4/vvvIZfL8cYbb1R7XwCwceNGBAUFoWfPnjUqhxBL4BhjzNZBEELqhokTJ+L8+fNWe9xp2bJl2LRpE/79918AuuesN2zYgKSkJIvvq1u3bpg+fTpGjx5t8bIJqSq6Z00IqbbFixejf//+cHFxwZYtW/Djjz8adK5iaS+99BIyMzORk5Nj1S5H7927h2HDhmHUqFFW2wchVUE1a0JItY0cORIJCQnIyclBWFgYXn75ZUyaNKnW9m/NmjUh9oSSNSGEEGLnqIEZIYQQYucoWRNCCCF2jpI1IYQQYucoWRNCCCF2jpI1IYQQYucoWRNCCCF2jpI1IYQQYucoWRNCCCF2jpI1IYQQYucoWRNCCCF2jpI1IYQQYucoWRNCCCF2jpI1IYQQYudoPGtCCCFWU1hYCJVKVeXt5HI5lEqlFSJyTJSsCSGEWEVhYSGc3BoAmoIqb+vn54fU1FRK2MUoWRNCCLEKlUoFaAogaz0KkMjM31CrRsaZtVCpVJSsi1GyJoQQYl0SGTiJ3OzVmRVDcVSUrAkhhFgVx0vA8RLzN2BVWLeeoGRNCCHEqihZ1xwla0IIIVbFcVVM1gIl67IoWRNCCLEqTsKDk1SlZk1dgJRFyZoQQohV8VW8DM6qUguvJyhZE0IIsaoq37OmZG2ErjUQQgghdo5q1oQQQqyKatY1R8maEEKIVXE8D46vwoXcqqxbT1CyJoQQYlVUs645StaEEEKsSlezrkqyppp1WZSsCSGEWFWVO0XhqGZdFiVrQggh1iWRVKlTFEY9mBmhZE0IIcSqqnrPukq18HqCbgwQQgghdo5q1oQQQqyKatY1R8maEEKIVfG8BDw9ulUjlKwJIYRYVVUf3apSByr1BCVrQgghVkWXwWuOkjUhhBCromRdc5SsCSGEWBUl65qjZE0IIcSqqtqDGUc9mBmhu/iEEELqlA8//BAcx+HVV18V5xUWFmLq1Klo2LAhXF1dMXz4cNy+fdt2QVYRJWtCCCFWxRV3N1qVV3UdOXIE33zzDaKiogzmv/baa/jrr7+wfv167N69G2lpaRg2bFhNP1qtoWRNCCHEqvSPbpn/ql5qys3NxZgxY/Ddd9/By8tLnJ+VlYX//e9/WLJkCfr164eOHTtixYoVOHDgAA4ePGipj2lVlKwJIYRYVdUSdRVH6Cpl6tSpGDRoEGJiYgzmHzt2DGq12mB+y5YtERQUhMTExBp9ttpCDcwIIYRYVXVbg2dnZxvMVygUUCgUJrf55ZdfcPz4cRw5csRoWUZGBuRyOTw9PQ3m+/r6IiMjw+y4bIlq1oQQQqyK57kqvwAgMDAQHh4e4mvhwoUmy79x4wZeeeUVrF69GkqlsjY/Wq2hmjUhhBCr4ngOXHECNnd9QJeE3d3dxfnl1aqPHTuGO3fuoEOHDuI8rVaLPXv24Msvv8S///4LlUqFzMxMg9r17du34efnV8VPYxuUrAkhhNgld3d3g2RdnkcffRSnT582mDd+/Hi0bNkSM2fORGBgIGQyGXbs2IHhw4cDAFJSUnD9+nVER0dbJXZLo2RNCCHEqjiOA8dVoWZdhXUBwM3NDa1btzaY5+LigoYNG4rzJ0yYgBkzZqBBgwZwd3fHyy+/jOjoaHTr1q1K+7IVStaEEEKsiit1H9ocrArrmmvp0qXgeR7Dhw9HUVER4uLi8NVXX1l8P9bCMcaYrYMghBBS92RnZ8PDwwPNXloDicLZ7O20Rfm49M1oZGVlmXUZvD6gmjUhhBCrqm4DM1KCkjUhhBCr4jkOfBXuQ7Mq3rOuDyhZE0IIsSqqWdccJWtCCCFWRcm65qgHM0IIIcTOUc2aEEKIVfF28OiWo6NkTQghxKo4XveqyvrEECVrQgghVmXtHszqA0rWhBBCrIrnUcXL4FYMxkFRsiaEEGJV1Bq85ihZE0IIsSqOq2KypsvgRuhiAyGEEGLnqGZNCCHEqqi70ZqjZE0IIcS6qnjPGnTP2ggla0IIIVZFDcxqjpI1IYQQq6pqD2ZVWbe+oGRNCCHEqqhTlJqjZE0IIcSqqLvRmqNkTQghxKroMnjN0e8XQgghxM5RzZoQQohVUWvwmqNkTQghxKqogVnNUbImhBBiVXTPuuYoWRNCCLEqGsij5ihZE0IIsSoJz0FSpfGsKVmXRcmaEEKIVfFVTNYCJWsjlKwJIYRYVVVr1pSsjdFz1oQQQoido5o1IYQQq6Kadc1RsiaEEGJVlKxrjpI1IYQQq5LygLRKrcGtGIyDomRNCCHEqqhmXXP0+4WQUhISEsBxHBISEmwdCrGwGzduQKlUYv/+/bW+b7VajcDAQHz11Ve1vm97oH90y9wX9WBmjJI1qZe++uorrFy50tZhVMuaNWvw6aef2joMAIAgCPjoo48QGhoKpVKJqKgorF271qxt09PTMWvWLPTt2xdubm7l/kjKz8/HsmXLEBsbC39/f7i5uaF9+/b4+uuvodVqzY51wYIF6Nq1K3r06GH2NpYik8kwY8YMfPDBBygsLKz1/duahOMh4avwogGtjdARIfVSecm6V69eKCgoQK9evWo/KDPZU7J+5513MHPmTPTv3x9ffPEFgoKCMHr0aPzyyy+VbpuSkoJFixbh1q1baNOmTbnrXblyBS+//DIYY5gxYwYWL16M0NBQTJkyBc8//7xZcd69exc//vgjJk2aZPZns7Tx48fj3r17WLNmjc1iII6LknU9lpeXZ+sQ7A7P81AqleB5+tOozK1bt/DJJ59g6tSp+PbbbzFx4kT89ddf6NmzJ958881Ka70dO3bE/fv3ceHCBcyYMaPc9fz8/HD69GnEx8fjzTffxEsvvYQ//vgD48ePx08//YRLly5VGuvPP/8MqVSKJ554osqf01I8PT0RGxvrsFd0aqIql8Cren+7vqBvpDri1q1bmDBhAgICAqBQKBAaGorJkydDpVIBAFauXAmO47B7925MmTIFPj4+aNKkibj9V199hcjISCgUCgQEBGDq1KnIzMw02MfFixcxfPhw+Pn5QalUokmTJnjmmWeQlZUlrhMfH49HHnkEnp6ecHV1RXh4OP7v//6v0vjN2a6oqAhz585Fs2bNoFAoEBgYiLfeegtFRUVG5f3888/o0qULnJ2d4eXlhV69emHbtm0AgJCQEJw9exa7d+8Wh+7r06cPgPLvWa9fvx4dO3aEk5MTGjVqhGeffRa3bt0yWGfcuHFwdXXFrVu3MHToULi6usLb2xtvvPGGWZdrN27ciEGDBon/h02bNsV7771nsG2fPn3w999/49q1a2LsISEh5ZY5btw4cb2yr3nz5lUaU2XxqtVqTJkyRZzHcRwmT56MmzdvIjExscLt3dzc0KBBg0r306hRI0RGRhrNf/LJJwEAycnJlZaxYcMGdO3aFa6urgbzQ0JCMG7cOKP1+/TpI54TQMl58euvv2L+/Plo3Lgx3Nzc8NRTTyErKwtFRUV49dVX4ePjA1dXV4wfP97kedm/f3/s27cPDx48qDTmuoSSdc1Ra/A6IC0tDV26dEFmZiZefPFFtGzZErdu3cJvv/2G/Px8yOVycd0pU6bA29sbc+bMEWvW8+bNw/z58xETE4PJkycjJSUFX3/9NY4cOYL9+/dDJpNBpVIhLi4ORUVFePnll+Hn54dbt25h8+bNyMzMhIeHB86ePYvHH38cUVFRWLBgARQKBS5dulRpgx5zthMEAYMHD8a+ffvw4osvIiIiAqdPn8bSpUtx4cIFbNiwQVx3/vz5mDdvHrp3744FCxZALpfj0KFD2LlzJ2JjY/Hpp5/i5ZdfhqurK9555x0AgK+vb7nxrVy5EuPHj0fnzp2xcOFC3L59G5999hn279+PEydOwNPTU1xXq9UiLi4OXbt2xeLFi7F9+3Z88sknaNq0KSZPnlzhcVi5ciVcXV0xY8YMuLq6YufOnZgzZw6ys7Px8ccfA9Bdds7KysLNmzexdOlSADBKQKW99NJLiImJMZi3detWrF69Gj4+PuK8e/fuVRibnpubGxQKBQDgxIkTcHFxQUREhME6Xbp0EZc/8sgjZpVbHRkZGQB0ybwiarUaR44cqfT4m2PhwoVwcnLCrFmzcOnSJXzxxReQyWTgeR4PHz7EvHnzcPDgQaxcuRKhoaGYM2eOwfYdO3YEYwwHDhzA448/XuN4HEVVEzAlaxMYcXhjx45lPM+zI0eOGC0TBIExxtiKFSsYAPbII48wjUYjLr9z5w6Ty+UsNjaWabVacf6XX37JALAffviBMcbYiRMnGAC2fv36cuNYunQpA8Du3r1bpfjN2W7VqlWM53m2d+9eg/nLly9nANj+/fsZY4xdvHiR8TzPnnzySYPPw1jJsWCMscjISNa7d2+j/ezatYsBYLt27WKMMaZSqZiPjw9r3bo1KygoENfbvHkzA8DmzJkjznvuuecYALZgwQKDMtu3b886duxY8UFgjOXn5xvNe+mll5izszMrLCwU5w0aNIgFBwdXWp4pFy9eZB4eHqx///4G5wEAs14rVqwwiCMsLMxoH3l5eQwAmzVrltlxrV+/3uC4V6aoqIi1atWKhYaGMrVaXeG6ly5dYgDYF198YbQsODiYPffcc0bze/fubXB+6M+L1q1bM5VKJc4fNWoU4ziOPfbYYwbbR0dHm/w/SktLYwDYokWLKv6AdURWVhYDwCb+tJ9N/e2k2a+JP+1nAFhWVpatP4LdoMvgDk4QBGzYsAFPPPEEOnXqZLS87LiwEydOhEQiEae3b98OlUqFV1991eA+7cSJE+Hu7o6///4bAODh4QEA+Pfff5Gfn28yFn0Nc+PGjRAEwezPYM5269evR0REBFq2bIl79+6Jr379+gEAdu3aBUB3uVMQBMyZM8fovnN1xsg9evQo7ty5gylTpkCpVIrzBw0ahJYtW4rHp7SyjZh69uyJK1euVLovJycn8X1OTg7u3buHnj17Ij8/H+fPn69y7GXl5eXhySefhJeXF9auXWtwHsTHx5v1iouLE7cpKCgQa9ml6Y9TQUFBjWMuz7Rp03Du3Dl8+eWXkEorvkB4//59AICXl1eN9zt27FjIZDJxumvXrmCMGTV069q1K27cuAGNRmMwXx+DuVcy6gp6dKvm6DK4g7t79y6ys7PRunVrs9YPDQ01mL527RoAIDw83GC+XC5HWFiYuDw0NBQzZszAkiVLsHr1avTs2RODBw/Gs88+Kybyp59+Gt9//z1eeOEFzJo1C48++iiGDRuGp556qsIGW+Zsd/HiRSQnJ8Pb29tkGXfu3AEAXL58GTzPo1WrVmYdj8qUd3wAoGXLlti3b5/BPKVSaRSjl5cXHj58WOm+zp49i9mzZ2Pnzp3Izs42WFa6XUB1TZw4EZcvX8aBAwfQsGFDg2VlL5Wbw8nJyeR9Wf2jSaV/fFjSxx9/jO+++w7vvfceBg4caPZ2jLEa7zsoKMhgWn/uBwYGGs0XBAFZWVkGx1ofQ3V+ODoyugxec5Ss65mafIF+8sknGDduHDZu3Iht27Zh+vTpWLhwIQ4ePIgmTZrAyckJe/bswa5du/D3339j69atWLduHfr164dt27YZ1OTKxlTZdoIgoE2bNliyZInJMsp+WdpKeZ+xMpmZmejduzfc3d2xYMECNG3aFEqlEsePH8fMmTOrdKXClM8++wxr167Fzz//jHbt2hkt19//rYyHh4d4Dvn7+2PXrl1gjBkkn/T0dABAQEBAjWI2ZeXKlZg5cyYmTZqE2bNnm7WNPlma84NJr+xn0ivv/7e8+WV/IOhjqOw+e10j5bkqdTeqpWRthC6DOzhvb2+4u7vjzJkz1do+ODgYgO6Z19JUKhVSU1PF5Xpt2rTB7NmzsWfPHuzduxe3bt3C8uXLxeU8z+PRRx/FkiVLcO7cOXzwwQfYuXOneJm6PJVt17RpUzx48ACPPvooYmJijF76mm/Tpk0hCALOnTtX4f7MrdmUd3z088oen+pKSEjA/fv3sXLlSrzyyit4/PHHERMTY/LSbVVrZXv37sUbb7yBV199FWPGjDG5jr+/v1mvdevWidu0a9cO+fn5Rq2xDx06JC63pI0bN+KFF17AsGHDsGzZMrO3CwoKgpOTE1JTU00uz8nJMZp3+/btasdZEX0MZRvlEVIZStYOjud5DB06FH/99ReOHj1qtLyyS38xMTGQy+X4/PPPDdb93//+h6ysLAwaNAgAkJ2dbXT/rU2bNuB5XrwUaupxFP0XtqnLpXrmbDdy5EjcunUL3333ndG6BQUFYsv2oUOHgud5LFiwwKg2Wvrzubi4GD2aZkqnTp3g4+OD5cuXG3yGLVu2IDk5WTw+NaWvmZWOUaVSmeye0sXFxezL4unp6Rg5ciQeeeQRsUW5KdW5Zz1kyBDIZDKDGBljWL58ORo3bozu3bsbxHH+/Hmo1Wqz4i5rz549eOaZZ9CrVy+sXr26Ss/By2QydOrUyeTfBwAkJiYa9Cp29uxZXLx40SKXzcs6duwYOI5DdHS0xcu2Z/ToVs3RZfA64L///S+2bduG3r17i481paenY/369di3b5/Bo0VleXt74+2338b8+fMxYMAADB48GCkpKfjqq6/QuXNnPPvsswCAnTt3Ytq0aRgxYgRatGgBjUaDVatWQSKRYPjw4QB03Tnu2bMHgwYNQnBwMO7cuYOvvvoKTZo0qfARHnO2+89//oNff/0VkyZNwq5du9CjRw9otVqcP38ev/76K/7991906tQJzZo1wzvvvIP33nsPPXv2xLBhw6BQKHDkyBEEBARg4cKFAHSP0Hz99dd4//330axZM/j4+IiN1UqTyWRYtGgRxo8fj969e2PUqFHio1shISF47bXXqvvfZqB79+7w8vLCc889h+nTp4PjOKxatcpkwujYsSPWrVuHGTNmoHPnznB1dS23s4/p06fj7t27eOutt4x6FYuKikJUVBSA6t2zbtKkCV599VV8/PHHUKvV6Ny5MzZs2IC9e/di9erVBpeG3377bfz4449ITU01eC78/fffB6BLkACwatUqsR2A/jL3tWvXMHjwYHAch6eeegrr168v93OUZ8iQIXjnnXeQnZ0Nd3d3g2WZmZno168fxowZg+zsbHzxxRdwc3PDmTNn8M033+Cll16q8rEpT3x8PHr06GHUZqCuo3vWFmCTNujE4q5du8bGjh3LvL29mUKhYGFhYWzq1KmsqKiIMVby6Japx7sY0z2q1bJlSyaTyZivry+bPHkye/jwobj8ypUr7Pnnn2dNmzZlSqWSNWjQgPXt25dt375dXGfHjh1syJAhLCAggMnlchYQEMBGjRrFLly4UGHs5m6nUqnYokWLWGRkJFMoFMzLy4t17NiRzZ8/3+gRjx9++IG1b99eXK93794sPj5eXJ6RkcEGDRrE3NzcGADxMZ2yj27prVu3TiyvQYMGbMyYMezmzZsG6zz33HPMxcXF6PPNnTuXmfOntn//ftatWzfm5OTEAgIC2FtvvcX+/fdfo3hyc3PZ6NGjmaenJwNQ4WNcvXv3LvcxrLlz51YaU2W0Wi3773//y4KDg5lcLmeRkZHs559/NlpP/1hbamqqwfzyYit9vPT/JzX5HLdv32ZSqZStWrXKYH5wcDAbM2YMmzRpEnNzc2MNGjRgs2fPZps2bWJubm4sNjbWIIayjy6W93el/z8v/ThiZmYmk8vl7Pvvv6803rpC/+jWzN+PsDlbk81+zfz9CD26VQbHmBWu9RBCiJ2ZMGECLly4gL1794rzQkJC0KdPn1rpAvTTTz/FRx99hMuXL1utpby9yc7OhoeHB97+8yiULuV33lNWYV4uFj7ZCVlZWUZXQuorumdNCKkX5s6dK/bKV9vUajWWLFmC2bNn15tEXRrds645StaEkHohKCgIhYWFNhsi8/r16wb9qNcn1k7WCxcuROfOneHm5gYfHx8MHTrU6AmOwsJCTJ06FQ0bNoSrqyuGDx9utVb/1kDJmhBCiFVJ+Kom7KqVv3v3bkydOhUHDx5EfHw81Go1YmNjDUYWfO211/DXX39h/fr12L17N9LS0jBs2DALf1LroXvWhBBCrEJ/z3rB38ehdHEze7vCvBzMGdSh2ves7969Cx8fH+zevRu9evVCVlYWvL29sWbNGjz11FMAgPPnzyMiIgKJiYno1q1blfdR26hmTQghxKpq+561vh8C/RCsx44dg1qtNnhEsWXLlggKCqp0KFd7Qc9ZE0IIsarqPmddto98hUJhcvCY0gRBwKuvvooePXqIYyZkZGRALpcb9Tnh6+trdle7tkbJ2kyCICAtLQ1ubm71rhN+Qkj9wBhDTk4OAgICqtRLXGX4KiZr/ahbZfv8nzt3LubNm1fhtlOnTsWZM2eMBtlxdJSszZSWlmY3g0UQQog13bhxA02aNLFYeRKOg6QKlRz9ujdu3DC4Z11ZrXratGnYvHkz9uzZYxC/n58fVCoVMjMzDWrXt2/fhp+fn9lx2RIlazO5uekaR1y8dEl8TwhxXJyJtrWsBlfNTJVX03ItXWZ55enLysnJQfNmzSz+HcdzHPgqxKtf193d3awGZowxvPzyy/jzzz+RkJBgNBRwx44dIZPJsGPHDrF75JSUFFy/ft1h+mmnZG0m/aVvd1dXuJtxIpv7h1TRH2NtlGmtcqvyRWKteC2xr5rurzb2Wxf/v611/jjC36Wt/38Ay4+3LQEgqUKRVR1odurUqVizZg02btwINzc38T60fkhXDw8PTJgwATNmzECDBg3g7u6Ol19+GdHR0Q7REhygZE0IIcTBff311wCAPn36GMxfsWIFxo0bBwBYunQpeJ7H8OHDUVRUhLi4OJOj2tkrStZVxDiu0l+pHGNm1x6q8ivaWr/MLRmruWWWLqsq5VZWdmVllV5endpuZepSrdEacVb1PLJUefoybXmum/O9YY3yKirTEleNzMHznNhozNz1q8Kc7kKUSiWWLVtWpbHQ7Qkla0IIIVZV3QZmpAQlayvQ/1qt7Bdy6eVVqRGa2r6y+aa2LzuvonjNjdWSjV5qUrZYJhPKWYE3KrN0GAJjJQ1iGKB/yzFmUCZX6j0rLrN02foyhVKFl34ghuNMx8oxoaQ8E/GaPGSspEwx1jLlGqmo3FLvSx96g/+vsmVzxo/72LLGX9Xtyqt9m/P3U7YcU+8ristSNW9z4jNVtjVr2dVtYEZKULKuImtcOq0N+rgtnWgrUvZQlS3e3C99MemZSHyA7g+7bDLlmGA6SXG8mAT15QqMiXlJKB0SGDh9+aUSHydoDD+k/scZYLJswCDvGfwQMCi3TLz6aVYmAZr6AaA/DiXbmpGoq6DUxwQrfTyMVjTeHwfD/8uy5YrvwRmdI2IZ5SS/8s5ZU+FVdHqX/TzWaL1dVrV/xFTyA7R02RWFY/Sjzop4rmoNzGjQLWOUrAkhhFiVte9Z1weUrK3EUr9WS9dorFF+TVR06cxUePp5RjU0UzUFJhhdUjVVS9XP58urlRnVSrTgeF0ZHPjiurO+HMOGKgI48JyufI43UZsUa6/F/0kmYi6PvnZdYS21EjzHicek3MuGHG9WTazaKiq/EhWdI4DheV/ecTLnilHpsmv6t1RZjb26/5/lbcJxZcqs6FhX4fzT77Pc2xsWRpfBa86uBvIwZ0xSU9avX4+WLVtCqVSiTZs2+OeffwyWM8YwZ84c+Pv7w8nJCTExMbh48aK1PgYhhJBSJFzVX8SQXSVrc8YkLevAgQMYNWoUJkyYgBMnTmDo0KEYOnQozpw5I67z0Ucf4fPPP8fy5ctx6NAhuLi4IC4uDoWFhbXxsaqFMcOKW+UbCCWv8lax4K/V0o1dSr/E5RXsqsL7aMX3bkvfc+ZM1B4FVvJi0NVUtUJxTb9s7aL0sSl+lXtPuwx9+ZUSj4e+/Nq58lFejcXg/9pUbaucGhjHlf8S1zFqjMCXv48KanqVnY5VOYSmzj+juKtQqzZ1TlcrzrLnXjWJ/59ljqf4t1KGqbgFxozaORiUTeyaXY9nXXZMUlOefvpp5OXlYfPmzeK8bt26oV27dli+fDkYYwgICMDrr7+ON954A4Bu+DRfX1+sXLkSzzzzjFmx6MdlvZ2RATcPjwrXtURvVZZqnGWqbEswp4Vr2dbVemLjKv33j6AtLrPMF1rpxmC8RGywpRV/xBQnyOKCdI1YdBe3xYZgpRuc6WPjpcXf5DwEicygXH2ZAtOVx3GcWK6+5TanVekDKHNQuJKYOR4COIPGa+JqpY6D2Bq8nC9d3bEsSXplj2tZ1bmsaa2e0szZV2VFmt0KHTDZwKrCsk1ehxcqLKvKDbYqiLOiJxGAMg0GTTw1YOp8KXuulC67wr/B4mVZOTnw8/Wt9jjSZem/N39OTIGzq/ldmObn5uDZ6HCLxVEX2FXNuqyyY5KakpiYaDBGKQDExcWJY5SmpqYiIyPDYB0PDw907drVYcYxJYQQR1bb41nXRXbbwMzUmKSmZGRkwNfX12Be6TFK9f9WtI4pRUVFKCoqEqf146pWpdeg6iqv4U2Vnp/Vb1fFGobJ50nLNAwzXGg6Bg48UE4tUKw5VNoorLi2yfEAM2wMxhgrecyKMV1DMHDgih+K5k1dCjd4zxeXz8RyeQ7QsjKPbzEGAVz599BK18QYA2z4HVOVWnV554Wl+hmv6PIyK1NjrPKfTHnnfan/iyo/N1y2zGqUVV4DtvL2xYE3Krd07bf0I36MAdA3NKusUZ8ZDc3EBo76tpE1aOhoDmpgVnN2W7PWj0n6yy+/2GT/CxcuhIeHh/ii4TEJIaR6qIFZzdllstaPSbpr165Kx1T18/PD7du3DeaVHqNU/29F65jy9ttvIysrS3zduHGjOh+lfEYdYFj+V23pe1alG6yV3mfZ/Rp1DsFMv9fNKLl3Vvalb2QlPqZl4iUwVlxj4EvK0z/KxQRA0OqmBa2uPK7kF7e+4Zf+pWXQNTDTl2vQQUg5jcvEe94lH0lfq2YwrGEbNczRx1kBw1qSYXklsVVWAzbvPqw5tWp9n9dm1YZNNMozVZY4Xeb8qmhfZRtvlW0IZrAfVrKNcTllzrnSsZezjemdGPYcZ1BembLKxmlugy2TcZoRY9lGYZVf2SuJ25yyawtXXLM292XpUb/qArtK1owxTJs2DX/++Sd27txpNCapKdHR0dixY4fBvPj4eHGM0tDQUPj5+Rmsk52djUOHDlU4jqlCoRDHUjV3TNUqJ9wyX4LVTdimvgTK68HIVNIu+4VcNg79F4Y+uZZeLCY+QVvyKqexlFCcULUCM2jFbfAFpP9SEzS6l1ZV8l7QGn1Z6svTCswgYRv8CCj7OQWNYQIvFR8AsUGYPmGzskmslLJf6rqZJZc3jZO+7t/Sva7BRHIASiXq0uWZatNW6vaIOQM2lP7xZnJ1Ez/CxPllz7OySbqick2UUd1GcKZbQJffSE8fW0VM9SBn6qkEPX2yM0imJn+QVa1coORHaOl9Gf0tl9eiv+z+LNjqvrronnXN2dU968rGJAWAsWPHonHjxli4cCEA4JVXXkHv3r3xySefYNCgQfjll19w9OhRfPvttwB0v+heffVVvP/++2jevDlCQ0Px7rvvIiAgAEOHDrXJ5ySEEEKqwq6StTljkl6/fh08X/KLsnv37lizZg1mz56N//u//0Pz5s2xYcMGg0Zpb731FvLy8vDiiy8iMzMTjzzyCLZu3QqlUmn1zwSgzCXZch4XMfEr2ajvZ5RTGxPLNhz8Qf9Ikr4Ug0eGSjVSM3isCTBoVFO21zD9tK5Hr1I7KlWO7vGR4mZbvBQMnFhD1deoOcaghe4XN88Arjhurrjmq6sBCwBf/CgKx+vWYSWfT2CAgFKXSsHAMw4QGDi+zAD2+vJ0B1JXu+alRo9Vla0Jm7x3Vubzlj7u4r/MsCzGmOlLe6Zq1aXPh1LllXxuZtQAp9ye4MqcD/rt9Uo3Miodg9FlYP1iE+eXOA3Dc6zs5yyJVSg57sXnmu59xY+lld7eVLnlNaoydSunwtqmqTIrabRVaU9ypcstXU5xuaUb2pU+BGX/dgEUNwarJF79pInGcWVr7LXRmItH1fr7tqtLvnbCrpK1OY98JyQkGM0bMWIERowYUe42HMdhwYIFWLBgQU3CI4QQUg00RGbN2VWyrqu0Qqlfr6VqtUY1WkDsr7q8frANiLWfkqoRB0Aw0YEIUPLLVvdrGiW1uuJOSXThCcWdhvDi/svWDnlOv0tevAfJ6WvDxTHo7rMqdMt4CVhxLAIDtIyBh+5HFBMYJFxxTV1fnlZTEpfAiTVrfa0fum5PwIrv46mLA+SLXyiu9cv0x4gJ4LSaUseLB5NIxc/PIBHLE68AFJelr5Xor0ZwpT9vKRxK1ao5DoLADK4m6I5ZSe1a7GClTGM3caF4DI1H7+JgWCOqqFOVkmNW8n9ftmalO3acWHsz6JxGjKu4Blj26o1YDoqPU0m54pUgE7V1rsz25fUDX+HjRZU08CtdozR1NcHko1BlyyyOtbz7w2VrvgJjkHAlfb6bbNNQ6u+E6ffN/T97fx5t21WW+eOfOefqdneae26f3EtaCAkhHY3RKmxIGYYNohZaKIpIoWWhpcShyFcFyqYoO0BLESkLu6Elg59KqYWMotBBiUbA3BASAyFA+pvbnmaf3a5mzt8fc861195nn3vPufeeNGS/GXvcnL3Xnmuutdda73ze93mfV5VzKzbJYUPlVt+sfMtUfic4awlXdc47abPSrfO3mbN+AqwwlO0Wx26KykNaCF1xSPbGNVhHbz+3NcTVh+oYI7kkVI0vAIpKTNcIO44P7XqHWHW0Rgb2ISIDEKokhXmnLV14WyjnYMF+X+egJ0LhMkAIiWE0jieB2WMCJW2o2Ta1kCPyTZGNHKJTBRMBoBWIqDyvnlwGUPjz5BzjyCN4Znk1DK5BWMdjykWEXUj4v7HR/Mr5rjjqqrOuymq68fy592e/cOP4Yy3D1tV5+bEqdrZFV+DmtcHpVxZvlqykSketJ8aa+ljcEFZ311YlLK+NGVvIga11h43pgw3zM4V1lmx0hNNqjauhen+djM1ViKmh6slUUHV8iRhbPG9coDA6j6XzU+UYm4Wrx9IKkzb5+1QWP9Nqzv1Cr3ouzmpnCNlPW1w9EW5RSfvazvYzG7eZs57ZzGY2s5ntqEmxPbQ8I4NvtJmzvkB2phKUQlsylb9gBRVUO0nKkoBQJTIrEZXxS2wbwvblTWOlMDKwiJhRYwuvd63xeSM7TkAFVWejhiZCaQzRKJTtUF1hDIX2etmjm0l4NFzko/HcXChSi4IckatwIeu08CFOg9LC6W4bYilLtCmKFJGn9riVcgjdjiuDUd1ypg2pHiElJe18lbGQQfiwepFWkJM9R8YRFW1ZjD1feWFGsQktkJb9ZsPW2iHhPC2RopGBi5f731GMlZJV9ctVNRSuR+VpY+VaMsBC+lE4vRqNsPuYEiGZej1NoGFG5XOTY1Wvq7F6dL+dO8PVyI29LM0YUvdqclVoOYaqxxBxeahj6H+0P8rfx/++bCBXmdG/1fK0SvpgMpoA23AGxlA9h5M2GaXY/ClQmevEuPb8jMrz/Pmo7mNDeuFM41ejDEZPbQU7ObZPC+yUyW3mrGdh8I02c9Yzm9nMZjazHbVZzvr8beasL4CdTdhhWFglLyUEgXTIQxeIfDDK86rAlTlFaBFQaEOmIZ+ABFJ58oqGIh0jThkZIIIIEcQlkk0LUxJWlIDQAwSF/V6RIvKhRXhCYnRoxyICZcfItSHTppyL7WxlEVkwiYazQaXcypHDpEIbReFQdVqYEgiFEgJpSWZaSqRHnHmKyPp2roVF5whZ5oot4jflMYLFfTYHLmyFlysD8zlmUbjvBrixdJljzvQI+ZdnXII0AuV/Y3+MRTZOEiIA4ZB2Jf+d6xHqDOWohKYkHunCHo+bFypA6NyhazWW46/mrA2gcONVUXWV5CdkidKF0WhkSXgrJi5XyaQwjdmA+MsyNzEqiPOItYpcpRi954/Vo+oy6lIpYTJGbkia+qiSNyU3QZJbtA3CNlDqyJdo3RcLTeavYeyYJ8ed/Nse/5nQb6V8axuovewCN/0QN6J294zYlBhXifjM7OlhM2d9nrYVBaZ+bmk3oRQkgSpJSiLtlw9FIQNMEANgVEymrRMaFroSBpNjJDWRDZ3zcOFmFWGMhrhVhjuHhaZwzwcbIhZEQF1ROkU5WB+FzaKac7ABxmi0sTXSuTYMcutklTQoIVHSECmJcGFmUaTOoWXlGGAXEYWRpM5Z9zONkqPVc2EMubaOMgDnWDN01zZPEWGEiGrWATh2rg/dFsaQ5qYk30RKYaSxj8pKiLQM01dJTirECEGWawpjFyRVR1Zoy1ovHGuoXET4FpmMyE6GEdvZh9QzPVqUKJzTL1lS7kcp8jEnZoKoHNe4sfy/3n0YQ8l4F9V0xiRD3Tt+lxLwjnoa210bMFWnWC4CtF18bUJamnSsvunJmAsoHXYlZbOJecdfdVSi4gSnhlLLMUdh/2oIfEOonikLlKnjVea/iVOdtgjw6QnjUl5nYm1X//bNb84US7fnxzhypxy77sbn7hrVuO+MLbIqcz5ro5oLZDOC2fnbzFnPbGYzm9nMdtRmYfDzt5mzfgKsm2kbmg0sCgmdgpYcdsqQqlGR/VdIdGiRbFpo+pkPV43CxYWxyFYUqUXn+cCuoIORIlvuUGyh7fZe7cubjgIbyi4yRNrF5BkiCDGBC4O7sHOk7Oo7LVw43EHPSAlig9XrTrsA9HOBGQzxtdU1IW1YXEhMGDPIDauDjHqoSm1sJe1YmYZ0WFALIhgC+RAz6CGCEJTCyAATxui4RVgMIYjJtWCIINOaYW6PrhlLlJQkgUSkuT0nRkNqw44GyvmaILFIP7cEM4lNFRhGJJ+BI5zNhaJMGVRRkVEhhIkLZ6cO69hz7cPgStj0RSAFsXQh2CBG5qMWrKLIHAp2yFAqilzbVIMLLUuHiDINGnstYIoRea5ae+vGKsPZMhornytLuaHUYS60QcgA4fXdfdrAw3AfWjcaKSSaEQIu8ZwLJZTa5564VEWLRW7RuruwPRnO1p6PNvP/uwH9uaiDRa0jjYCqlcQyren1+mVoPgxDwjC0vwsVtF7+pu5gHcFuWhh5smzrvO0MpVZASUqsEs02HWdszOnhexiPXDwRHa6E2B5/bearN9rMWZ+HbbUJwcluSj1UFEYxHyvLns4G0G+j+11MniIbc/Z9FVFowyDXdDJNNy3QxhBKSS0QFFLQzzQiDAiKFAbr6G4bPegiai3E4n5SbVgd5GQalM7p9YcUBuqBgDihnWu6q6eZ013U6uOEx79Is9HgeD+jaC5R1BfJW/vYte8g+crjfOnEGisDzdH1AXsPXESGpHf0S+yuhexKBPtW7ufS517DA4+dpvfAvZg8I6g1uOH5V1Osr/Lp5ZwTyUGOdlJqh57DRXMx/3zHHQDUA8WVu2tcec11fPKfj3BJ2EWtPU5+8nGuv2gRISVH7n+Y4OLLMa29XP2v/g3JoM0d9z3Ccr/gdC9jeZBxyXOfz+fu/jSH5xN21QKWagEvvOoSUCF3fuoTcOpRMJoXXP88slPHuOt4GzO3h9X6ftYGBTfccCOfvftOVgf24R8Hkuuuv4Fuqnnkvs+wL8yRvWVeeOXFIAPu+PRdAOjGbnTS4qZrr+LOT32KYXM33dT+flc87zqMgXs/82lakaQRSm6+/hq0irn7jk8h0h5iYEP9L7jmORy5+15MWMckTbIg4TnPu55Awh1HjtB3i5Ebb7iRVBvuPfJpkkDSND3EsMeN1z2PI5/5l9J5majOjddfh8hT7rj7XoZRi0FheO611wPwmTvvdMcpiJTgxhtv5I4jRwiFQWb9ckyAO+/6jE3RBDHXv/ArADhy5AiZgUFuQ/7Pv/4G7vr0nUghCCTUQ8lN118HQnLkjjsQOgNdcNPznwdGc+TOuzFS2eNVIdffeBN33nGE3KVEtDFcf8ONGGP49F2ftm0TJbzwxhvt/u+806Zf3PHeeP11HLnzToxQICWZUNxww430ej0+97nPO2dt2L//APsPHOBf7rkboXOkgEaScPVzr+L48ROsLJ8qc+yXPuswQggeP3EKpF2otOYXmZufZ/n0abK8sFUWUrG4axdpmlLkGYG0i5VGLbHO3nePA5tOGUuFyDN6Jh+yrgrqnOmpM8bgN6NQuJCq/OKGhjXGLyp3kA2OcEm8rW8/s3GbOettWqfTGalQbdFZn1hpUw8Uc7GiqWOMzJDdNcSpk+juGuQZYbPPIO6S1fqsNqCdgqnPsby8wumVFQIpyBYSLrroIFmu+cKjD9I6/XmKU4+zoDT7mjGfffxe8oV9DC7ucWogOHjFVQxXT/HZBx5mkGv2NiKuvPLZ9ApIjz1CK28jTz3E/PLD1A/s5fSxFdLmGuw6gMhDFvYdJMsy1jo9TnZTHlsdIFq7MUHAcJjTihVGhOhhD5MNEXlK0VmFPEcXGbq7jum2EXmAxpDmmiLN6aQBnbTAaIOObVo0c5EEERhMlmIGXUxX2Qd6bx0z6EOzsA8aY/PwmVvU9LOCTpozyLUlr7nzLoocowtEnqIHXRu5GA4w6QCTWTSqNaT5KArRy0ZIze7DksaEzso8uohr6H7PosN6NU9sx/P56kFmc+Fpod2DE4dKXelWkSHyzJKBiszONxgRuwpjkWau7VyE8EIwFln78TCeRGcdon2/kid2f2JG+eWijACMPxRH6mV6LJcudGH5EM6MU58rBXP8Lh3m9SQ6IyQC43L+RekIMbZDmHFjaWPQjHd187l146JCJU6slpVV/zUai7d9SZ77aPNbc8yyPKPX69sFgNE2x18UnD59GqS9FkUQMjc/z7HHH6c7sNyFOI5Y3LWLU6dOceL4cQJlOQpXPefZCAz3ffbe8vfYu3cPF190EV/84hcYpjkIQRhGXPGcq1hZWWG13S7P6b79B5BSsrx8upxjHCckcQRa2yiO0WV0bkwf3ndqkwqERKtwQ2e68jfHRreUFHQ6nS2ere3ZDFmfv82c9Tbti1/8Io1Go+KoJx8F41eZEYLb7zlBIw7YXQ8Z7mkwJ3PU+nGy+4+gO2voYUbQaiHndxPsP8TyguFEJ6cvYx5ZWWd1vUscSIKLF0jqDYIgIEuHdB97kPz4IygErfkG6XIbYwTqYkGuNZ20YL2fcXR9SC+1D969w4x+YUlmIs/QnTX6x08xVIL05GmKrCBszoMnUQlJpg3tYcGpzpCwM0CoCDHIyZuxDQkOephhH4oc01lDZylSW8emO6ug5zBAqjXFMKeXFfTS3DojKVxNOKS5hkhbZz3sk/dChJLkgyFBXqmThpL01ssLBrmmlxV0hzlp7pyrZ287trUe2NC3HnQxg66TNDUuilGQae1IdHYfgZN99GF/zwQ3gx5ojUn7Fq3o8TBsYXDo0I6ljVukuOtEGO3CvYVjqltnbZuXjBCYJ24JR6zKta0iKLxTwzlGd5xWQa6woWshrGPVo9rmaggcKHuaUHGO9u/KmP5862KiK8roNzDVr3h29dgNMEEsm1zgToTIPQK2ywU/xTLoPX3sDe+bLT3sTWXYTWVBN5l39e6f+gQ4y/6HgyGD1BIxC63p9Xqsra2xvLJShtnTNKMoCnq93ogN7sYNhGXxlRoHRrtFUZXFLm2kQQi0CkvFudxfFlgiphAQKZsn7na7Zz9x52BWY2J7289s3GbO+hxsc0c9sirT9P986lHqrYjL989x2WKN+SDDrBzjxMf/mfZjbbJOSuviFguXH2CuyNBzl3O6n3L30VN88rMnyLOCIFT0Uhv2vXQhYVexxvq997B6/6M8eHrAl+ohRTNk/soujau+EiVqHD+9wj997nH++XPHGPRzrjq0gFjqkkQBlyMQww75qaOcuvsBakdPc/L0KtFFq7RUQDi/14bFpKI9LHhotc/dj65xUq4ig4ildMBSI2JPLcB4p5wO6T1+kmKYkcz3KU4fI11ZRScGM2fZ7cvtIXNJyOlOSppr8mZUouqBe4qYYZ+822UgDUJJ0rUO0aCPdM4VISmMoZcWdNKCtX5GrZPS7mfkviRF54isZ5FFv43prNnfpd+1r8zmVoda08kKlvsZ3aygPcxR2IehNobMeTWRD9G9DsVajogSdG8doQKUMSV6AUlaWNZ8e5izNszRxtDJCnab0D5oi9TmqvMhIu2j+12ElDaSMOwjwprLtdrIgcZVBeSGQAkKDXkxcrYekYvconTr/NWU3sujBQ6M/tXV/LWwbwhduFdeXu8lg7jsQjVy1HrKfWAXI4XdvER9Ew7PwS3NSDe+5FaMosYIxOjh7VG1MdY5jQ2oR+I5jEqdBNPvVCFcuHWaoy6PVY829ruZMpa3qpPp9/uYPBsbb22tTa/XsxwLaVdAWV7wufvuszMVNlysMXS762U1gc9o+781tsOcEdJF+iTGVUqMH4f9TLhyssnfyjvsnbYZsj5/mznrc7YRUirfmUYSMbC+3EMXmhONyNY8G40ZdOk83mb9sXUG3RShJMniOs1BD2MsKjvVGdJe7pOlOWEU8PjagMOLdavoVOQMV9ZZP9ah83iXVSloHWgSL63TzAYEMuaRB7/EJ+59jPXlHsN+zueVAPVZrr5ogasOJgidkff6tE91ebyd0e70aMQRjfUVZNojUoJ1YUPWq92UTiflZDsljCDWOakrKzN5jskyTDok6w4o0gwVKHQ6IB8MMWFuQ7iFJYJlWjPINFlh/zUutJv7B7pDhUWWI7VE5/koF+tOq64gWK0tek1zX2NMiTKNLjBZatG+cupueYa/9AsNqZtXWhiyXEMw0WZQAEUG2RByV1KVpeMbCAlSlipoaWGPz6KZ0QNSFLnNPxa5DS0XOYYAk40/1K1qnD1QHyLWE46xLE9z50yY3KHg6U86P4Y/j9WtvFPbtMzIzass9XIha9iYXxx7+Jdh7wmn586ZqTjXMV/uHJSuDCURU5uVjL4znaRVKosZUarvyfKAz2JV3XcEaZqxurpK7hdxQJ5l3H//50mHg3IBIIzh4YcfGs1X2N9qmOUMs7x8z1TGBsqWltK48yymk9ls6sE6YCOVTTEg7X1yBrKaA+Q+WcEFpsrNbAdt5qx30tx9MFg7hQr2sd5NLSIyBj3sM1gbsrY+ZC3TJMt90rUupm9zRsPcIsZ+e5Vs0CFPmqx0l+hlhcs/5qTrPYarQ1Y61nEEsSJd64DOUVJQFJrO2oDO2oC02yWIJA9Gq+yuS4KLaphsSN4fcPp0l8e7q+hMoxZiBqdXCFdP8sBnPsXJImZ1kLHcTRn0MtTyKlEtYZDYsHF5s+epHW8wRA8zdBJRDFKKQTqW1y2lOLWtkdYlwhs9NEyh0XmBKTRFoTE+dusYsUZIGxouDLnWZR7OOyKBRXYWdaY2PF9ojKiErEuxFshybdF9rsmNIXBz8RKJUoDQBbrILWserPNWgc3dClWy5wsMqS4cE3xcTKYUwylD3oVlRrtFhNE2MW2wUpmFi9NaxGnQesIpClzud4Q2y3MohM2pu65lZpPH8kg+VjghD7PRYYsRCcpUnP3kXGyXLVHOa4yRPCF9OhpTuPXG+Iiy8m+Jyiroesyzj3UBE+57YsNihArSLtG2sIzx1dVVBv1B5QuSBx96mKIoRgcIrKwss7yyPFL/dSdl0OuOZHg3g/LSd2Ubd9CTVu1BfTanXR6E/32E2hhx8BsKUdas+6+KJwRXzwhmF8JmzvqcbDNU7W+YUR5OY0i7bcL6PHnWKIU9yHOG7ZSVVNPONXu7KWk3o0hzDJAXht6wIO2skg86mDyn08vIilH+M++nbgz7QJlvp6Tdoe1YFVrkOexlDNqrZL02/UaDfjOnNyxAOEScFwxWh7S7KYWBudUh6VqXYuUEw4X9PJbNc7KbstbPGPYy0kcfJ4oVB6/cXZYmteM57r3/Sww66xT9ITovKIYZOs3t8XgHh9cYd2jROTHvLPwZm2YijEGGVq0siCyqdjllyxS234+UJJQSkac2r6xC9KCPyQsIFAQRQkpEGIGK6A3yMuc9cOIoAIEvtQr8eEPMsI8ZYtFrnkMEqJAcMEGMCSLSoQ2De9U3n/MOhBNFyQeYLLTzG/YtAc4fYxBgpAIVUOSGvAAjfYjYIJVXZzNI160M4xy/y1lbswsRqxWvQYVOxWv8nHqEaRXpzMhRG2OJfa5MywiBUaETt7GD+JyndfZ2UaOkIJSWDU5hBWjKCLMQIJQVfTEaowKMDCncWFUhFAmOVW7dTiDt+RsjUJUHMRLesflZr5w3qu1V0gnAGOisrXD/2gpG5yiHgNMs40sPPOBizCOk73keRgWAcPf16Jqtlr+VndRgQ/tUI33C3y7EpqUNqu1OhSnGS9iEtIKDQoKLrhjsI6ZwyxMprEa97VBWySG4yQpHvpNCgDTl+fDHsuPOcZth8C83X/1DP/RD/NzP/Rx79uw55zG27awfeOAB/v7v/56HHnqIXq/Hnj17uOGGG7j55ptJkuTsA3yZ21gPXXdTyiBEqGDDGlYG0j7cBARSIkM5ajsp7UNGhTFFNkAEAbIq6yMkMlSoWJH07PsylKhgFLYTQqACQRDXMUVGECpUKAhdmFRIiVASFSlqA4tWg1gR1GJEXEMEETURkgSSUAlUKIlbC9RadaQonFQjzGUdLnnWxdx3ch0h/wUoEFMYIkKOHupSCEIlkXJUb+17bE+aDC0LF9cX26igVKgCkNKPCYF3FmkOeeqIUgVIiQhCRBgiggh0iFGhZVoDWWFG+W4hrHOVEEpJILHhaqeCZgpZhr2Rgc0hC4WRoSVGad/D2jZOkXh0no+ad+gCo209uggCRBi63Ld1OoXWaAzCiFKdTUnXDEQIFMICtUkPDGV7UiMD25hFqBGhzP8WjJyZME6dzVRIZT60D87xWza0d6hFuZk9NuVOh0eX3vGXV8EYonbqdtI2rJlkbQtXU62kdTwjtDruhMrmFH7MSgSg3K1zRBpLOtu9axcHDh7k7rvvJs8zMBAGIfv37mFlZYVut1N+UQURhSPpVRfg1T34e6CMblTmV07AfcsgKCrpg7FNyryET2tU0h3ec0tRhsj9gt2T5LQjEQih8J5eTJAfwThkLcr9laRAwZarW87FnskEs5MnT/Le976XV77ylXzd133dOY+zZWf9x3/8x/z6r/86//zP/8y+ffs4ePAgtVqN5eVlvvjFL5IkCd/93d/Nm970Jp71rGed84Se6jbtgt5Mf9dbWJ8jSgLCRLlwnEV2USNkbkUAirAZEiYBMlAIIYiloBYFhI05hJSoqE49VoTKr4ElQT0hnotYcGHwqBURNpOSuBJIQa0Zkw0LhAqotWKWFuq0GjXr6IIQFYUs7mnQWGhwsjcgWUiI5pvEew7y3K/8OpJHHueB5S7ztYg4CWjtXSKqJYTitEWfQmDSoUWstQYytqIqMgyQUYCKgjIUKoUgCqRFYEqgjSAJpZXilE5n3J9nKex3ARlYtGmksnlcqayz1k7vXEmiwL2U6+5jbB5d+j7bUkAQIKIEEScIIuesjaszNaVARiAFgbIoMQrseCYdjlhdPl+pAoxDrYVbRBQ6LxdpVu/cjqWUsAuHwsmx+gPw5TVS2fGkxbgeCfurzXdrU9LmGZW0DntscSOVG8+xgKUCE9i/80oo3v3r0bkng405CSeAIowuFxBG2Jy8zwFrRg9h5RYQgZeRnWRq+xx1Kf7jhG4mHbULVfu5mXJBoV3p15Twtz+HDu5W+0Pb/6kgRzFCxfZeNigl2bt3D2mW0u11yyjZFc95Dlpr7vvcfSWinZubZ67V4vHHH7eELmMdYBRIssyWI44ds9upL08rmfMj/2svKVFh0lciCAKDMfbc2ZpyVS4cqmsX43Znu/tZQpmRaiz6V5bSVaZYRfQ7aX69tZ3tn462vLzMH/7hH/LYY49RFAXD4ZC//du/5ZprruHVr3413/RN30Sz2UQpxYEDB/iu7/ou9u/fv6Wxt+Ssb7jhBqIo4vu+7/v4sz/7Mw4dOjT2+XA45Pbbb+dP//RPecELXsC73/1uXvnKV27/SJ9mNu6kxQhVm3Ei0P7LLqLWirlyX5MosA8WObeLPc/bR7KQkHZT5i5qMXfpAdTSfqSE+STk2fuaLF+yjzxbIggDrju0wP5mbJ1H0mThSvs7zB1Ypz4XY6KQ1iUHMMkcg0xw+PBhXq5q3HHfI6x0U5538QIvuv55hIFiMDxGHDcIdy1y8Mo9HNqzwP2n14gu2kN8+HKKuX2sppq5UHCwFXPZ3gZr/ZT9F82jwojFYZe5WBEqEFGMiBJkIkgWWxTDjGi+QTg3hyk0MqkDNpTZSgLqoWK+HqK1oZWEhIEgUZJ6aAUkhJKoWkxQt5GasNVANufJw5qth1ZxmQcOlRWL2dWIaCYBjVARBwKRDTGpwmRDjNGoJEHWWqj5JXR3HTqSIqyRFh3XEMRgtLFCI5GiFSmaoX18rissuUxrCEKEUoi4hqy30FGdwVDTzTSZESXpLhCCeqjItKEeKhIlkIO+VU9TCqEz+4CNaxDVoTaHCWuYqM7AoXxtRiVIcSCJA0EtkOTaECuB1Jl1YB4FC2WjDmEdrSIyGRGoiFwotHtoB847BEoQSUkksRrz+cAq4nk0piIrhGI0JgjRYWKjD9qrafkFiSBUkASCKLAPFFFGNLyamiqdv9e/10FUasKP7qDRIiLAEJocIyTSL242OH/HFxCuNEmFo4+NqbxGqFcWKbKwizgvqGJzxHaBo2UAxoaXc22viaJyL9dqCfv27ePkyZPk6QChC+Io5JrnXsVjR49y4vhx9wgQHLzoYnIjOHbiZFk2hVRIqciHqX9U2Kq4qneqlmH56ISQGEK3PnEZeWEvST3mfK3jFwJUmZozIwb9hOKbcOeymsbbCXumyI1+13d9F5/4xCe45pprSrW8l770pfzcz/0cv/Ebv8E//dM/MRwOKYqCz3/+87z73e/mC1/4wpbG3pKz/q//9b9y6623bvp5HMd8zdd8DV/zNV/DL/7iL/Lggw9uaedfPnbmC+ui/U2WmjGHl+qE7sEq602aF+8lSGLywZBkaZ7GgT3I5gISqEeSw3sXWB4Y2p0etTjg0l11rr70EHO1iO6po4S799LsDziwd5GLFue4f6VNuLhg84uZYGlpN1cWBe3VVdr9jEsWa+ypRwwN6CGYIEI25qntWaR50W4aUYDYvQs5t4gJElevXJAEkvkoYG8rYf98ggojorWAehjYvF8QIuIElCZs1FBxSNRqIGoNwjwF7AM6UIJapAilJA4VSkAjkCUii5QsIZZUAUHNfS+JMSoqc6aFsTk76XKZSSCJA0ktUkSBQBbWiRntyoec3KmIa5iwhqw1MANLAssnWlCFSpIEyjozJci0tFKgTnpThJFFwWEEYYwWAbnJyQtDVoxC84Gy+W5Z2AVAKLBEtzyDoijzyyKM0EGECWN7zlVI7jql+f7hAIGAUNg5SWHT7yLPJ5CwsvKnKhgR26SohKxHRPFA2HNu69AzS3SrOFifOzfG5rx9h7PCWLTn3eYYshZO3MWH07UumWIWSStyH0Y3Lic/JSSsEGWqQAht/3VFRuVG4Jjkvk5/xLrfwE6vCLGMicVMQ5M+J1zJo0/bTIjxcUVVlMQt4lvNJqiQYydOlt/btWuJ/Qcv4rP3/gupc9gqUFz6rGexsrzM+tpKuW0ttmH4NE0rcxZlpKBwoX1fRgd2vh5CaIyLSkweY2Xh47t/7XDnDMH2ctZPT1cNt99+Ox/5yEd40YtetOGzt73tbWN/nzp1ir1793LixAn27t171rG35KzP5KgnbWlpiaWlpS1v/3SzQ4cO0Wq1pn7mkfXkzf3Sr6gzFwXsaURctqfGnMhRuxJy3bH1ydmQaH4X/bCO2HOYeNdeaGkO1BdZ2HWcE6dOEkjBFfvmObhnF2lhWNWS2t6LURgWZU6rntCoRxSLeylEgBTQjAKCZsSh+Rq9RsSeZszeZkgnB9EBVISst2hctJvGRXuoqYBsbg8kLYyKyhV7pCwi3jufcGAhQQQhRT+wqBoDcR0ZJYggJ5proosc1Wgi6y3QBTK3CFkKaCYBcSBphgohnfNWtiNZKAUitygHFZTImriGCWNynKpYRaXMOkVl0WugCIWwtcZFipVHc04xTqyzjmrIRgvWB9a5YkaORlrHXw+URZ1KUhiNKByqdnlvpEPWtUZJIktLdrtzYNixlLDOWhQZFENMliK1Ld9CSqtdriLrqIOQXCiKSqc0e95cWF5VnDVAqS3uNLulAhligsh1MQNw8p2ePyFsPjjw59uhaZtLd95TCNuRTEU2dCpD8sISFgttQ/A+56mkRYbSFBatOuc/FlZ1+X2DLEVZ8sI6lgKD8omdSr5baNvJDSFd7bhEVCNZDg3aNMZ4O1IjJrpzTTppXYwEYyrbGSFG5C2D5UeYUY55AxHLjXnGcjK/KaPnghSglEIqaX/LIGBhYQFd2FI+kQ/AGA5fdIBASY4dP2HHUBFxrUYcJwy1KNF6VZHMz85GKNx1LahEJ3wCo2ru95EB7R1SMHum2E033cSzn/3sLW27e/duXvayl6EnCSWb2DmzwU+cOMGJEyc27Oj5z3/+uQ75tLBdu3YxNze34f0qsWzSWb/oiph6qGhEir2NgIbIkHWJDLUV6MhTZK0BjUV0bZ6F1kF2DQt6mWZ3/RDFFRejhGCxFpAowYISXHLT9SSX70IO1jG9NcxwwPPCGqY+T7rnCi4aFBgVkkZLLDbrFMYQKUGj2WBRQ6H209DzyMUW9Yv3E8/Ps3RRRi9oYWpzZEGdUNqH/Hwt4lIVsFhP2LunRaECOoOEuUghioxgcQ9yYQ+6IwgOPweMJkgSgoOXWsGUE7YvdT1QNOsRu+she5oRkZIsJCERBfXQameTadsSs9FCLe4FqQjSGqa2QD+39edD1w87CWwufFct5EAzZrkZ04olotNBDwdAC1MU1rEmDURrF7qxZNteri3TG1j50lBZZB5Jye56xFwimYskwWCVZlhDDDs2P6kCZGvR5vp7Cl3fRSfVdLOCfmboWe9IEigiJdhVs2HZQayQ/dPItIcZRFBr2BKnWgOdtNC1eXR9kSJZoJNq+rkmzQ3K8aVCCY1AUQ9A9ZaRQYIcrNl+355wF4SYqI6OGuRBTG9gr59ACoaFduFWQexy8LVQEOocMexBMbRjOfUzhEQHsQ3LA5kKGQxtWVuqDRHW0YZCEAoQ+dDqiWd9FwK3uXjPBjcyQAuL9r3GeebK94QQSGlGeWqMbUOa9hBpzzrpIh9JZ+LGk0HZrMYLx2TFKHqgfL92M0LmuAWJJdO5zyqlZVJIlLLRGyFcFEEqGk27OFdSECcJQsCepSV0WrfXurQ5+l0Lc9RrsY1yiIA4jpFRjauvvsaifzNKnV111VV2t4yiJ3v27Gbv7qWyWYyfo087lguyinyoYbxs0Zsl/Y14DqJsD6s3qO75MkYjA4Io2uTJd34mGSH+rW7/dLS//du/3db2H/rQh7a87bad9R133MFrXvMaPvvZz1JtYO6F5su6xGewVSo8AItwo8AiGctsdUgobiCltKVNcd12vJIKKSzSjFwoVRtTsp2FJ0AJe/MaFSKSBiJKiMIaJm4gw4A5GdpuUknCfJRUECQkUrB78WKCYRvZT5BzIUZrDi/E6PqidSBxiwxJvO9inrt0kH6mWU81WWEotObya5/HfKxokBIt1zEq4tDB/RSLLXzXLREltuRq5aRDmor52OasF5KQSElqoT1ZobJIFIAwts41SixprQNZEFMMrQNLC/swjaRAOkRtxwwIdA7FOBlMxDVkcw4d1zGBPcZBsUzmyFK+8UIUCBqRRdaySK3jKXKb/1YBIsLm5hst9EqBjpsMU12GrTNtytB8LVQlek0CgegOXKlWy9ZTS8seN2GMViEmiOnnhlRr8grnQTlUHQfWKQqXOxe51WK3F5xlQpswQYcJae57cxtwYjPeKSgXSg8wFsEVw1KuEqfAbaQlk2kXYs5KVO10yR1zXzhyWimdWrie2kZTPlqk6yDmEL6PGHhEXNVv8eFv2/TDh5i9EpoaZY5dnX2hx1XPCgzKiDHcWIsjLrv0UisYYzRJbFMrVz37CrQj4Qm3CNh34AC79x/A9/32dvkVV9hDEaOc//79+zc41VqtRq1WG93fwvJY4jguO99N6nJvsLOhdGNK+CyFKEvptviVJ81s/f3WZ7GdbZ8pJsykGsFZ7LrrruPyyy/nTW96E/v27dtwUr9cmeDtdpv5+XmOHzu2AVlPa2JfPasPrqW2FaQU7KoFJOSItIvqnIQ8swhEhfZhGzVI60v0Ms2gsGjN6wLXKiSjWGjU+glE1rPNIACUQod1irn9DI1kmFviU2FGaSnvQBZjiRyuI4ZdZG+lZIqapIWOG5iogQ5iOqlV9xoUFhX5yOFirGhGkpooUGtHbchSj5oKlISiMEbX5jnBHGtDzdowY5DblqE+2rCvERArQahTwhP3o9dOoXtty+auNVCLe8j2P5euSFhPNe20YH2Y03MqaM3ILgCaseSShkC1jyHXT5CffKz8DdTiXqgvoGvzFHP7WU01q4OCLyz3Gea+05bi0oUa87FkIVHEneOIrI/sr5Eff7gkmAVL+9ENi9KP6TqdVDvFMkMvKwiVIFaKxZqiFkhakSRZedBGQfrrdkJBhAhjitZeTNxEhzVWM+hlti2qlzmNlGW4764pEmmQaRcx7FpCmCdySVu/rBtL6KjBQAvWhnrUJtKMHE2kBI1QEqKRaRfZXxvpwMvAcgNUiKnNU8jQScHa67CsQXfXUKQEjUDYhUNh0TAOwRmP1oIIncyTOynWKhoGR1Bz12UtlMh8aMdLe1Tjz0YGNoeuInRUL9u1ps7pC7cQ8ccZ+3x8pdFF+fKLmwpSNTIgN75Ryriz9rKlfmwlXblb1Vn72mo/tj9+FaERmzrrDePqotKYY5xR74V3kMou8ExVt2D8+VNF1lIIpNkasl5bX2f/vn2sra1NjSBu1/xz876HjtLaxnjr7TbPedbBCzaPJ8Muu+wyvvqrv5r3vOc9xG6RCDZX/aIXvYgvfelL2xpv28j6S1/6En/2Z3/GFW61+Uy3aY4axskUjVCWdaO2X7JEyAAdNRFBjjGun7W0oh1eECICjJFlnW3s0LlHIyaM3VPKOmuPtIGxvKSCEsX4kqTSoaoQEzfwHZWMCkekEyijJ0rY3LVElD2ohcsbetaw0COkZ98PwWiO3HU3y6ZON9OspzntYYEUNlzcjBR76yENVSB7q3DiAdutK+2DlMh6Czl3iuLxIX0Rs54VPLQ6oJMWZA6mLdUidtVDmpFkRfaR3WXM+rJ1sIXVyg6W9iPnl9C1RdrJY7SHBSv9nMfWB+SFKXPf3cUarVAyHyvC5Qcx7dO22Up3zc4nSggu6qBri+j6SY72DetDqyluG3dgGeWh4mArohlLoqyHWn0M3VmzDU+MLqMGZuEgujZPXytO93P6udVIz7UhCQT10C5kluqKMB9aB9tbxqSDETs9iNFRDd3cQyYD+rmhMyys83FP8VhZhJ4oSSvEhq3TPmKwblEnlI6aIKao77ItMAtDlhuGjuUO2CiREERK0lCFQ/wDyPpl3tuoAFRsmeTJPJnxoeqRgwUbQVLO8deUGemmZ/2RU6nk4o2KyIKYvIDMWIKgd9a+lDCQEOmMm1yLzxLtlyk7xz8QEmNkCTuNu979v5Rb20XAmEP0pVWTJWoVgtk02xYy2nQQ7TqWbVQfc1QCq/luKvXK1V7n/i1/zwNTO7VcQPPlctvZ/uluDz74IEEQ8K//9b/mL//yL8sSraIoeOihh7Y93rZTAy996Uu56667tr2jZ7L5VXM15Ge8o3REHrsKt0IWMApZeocbeEGR6kXs0Ws5TlhKV5ZjVL6nJsYwnvgjgxGq8qt3X3/pwldSOMcvcaQVF5b3DycZlPMfkZ0CUBFUjilwxK0kUJYlLW3JjyVg2bCz1wEXQYwIY4RTB8uMse0s85GEpxC2djuUNmUg0oFVGxt0HcvZPaACW4pkooS+izh0soJhRQwlEILIjSPzAfTWrKPur49Kt1RoyWBRjaFRdFNNe5jTSQv6WeEWVrbuNgkkYZEhhh10exndWUX31svmDiKMMVGdFEU/dwuZQe7afRZlGXYobX7ZouoOutPG9DquA9jIoWkVMnR5/W6m6aY5vbSwY5lKaZRrIiKyPmR92zXNO393XVmhGKyj1pYnkDnEWSVc2Z6g9reTmUPY2hPMvDMQ5Np2e/Kqc56tPqZ1rgtLTsszm7cuXGh9ov5ba4co3W/nXz5ybnfqUaTtumZ7X5+ZDFZVUcPNXjPuuC+UTSLhrdhWiGzT9+UW3mfRg9hJk+fwerqbEIIPf/jDXHzxxdx000186lOfOq/xto2sf/d3f5fXvOY13HPPPTzvec8jDMOxz1/+8pef14Se6rYZkj6TeblDr9xll7+W8Vzes04Nq6o+JoXN0ZpKAwLvOG3tkpODrOQHR47RKYO5mktjrJP2Y5RrfB8C8ytr5Z316HZRJdAWZbhRiVEezLjthZCO2eMWI+54jFDlvCMlqYeGQNiQfhyIktksdFHKUoowQtbqyHoTHdXIEeSFLsOTtjZVELq66DgQJEpYOc9hH5M6lO/KymSjhQ4tAWvYKUp5UbBO2pZsSWJlc8yy23VOrA/pEC9kIxNbC11EDfpD24a0l1k0bLShFopyIZIokL115KBD3lu3vbSLHBHVSrZ1EdYYpPb7nbQo0bkskSKESpSOVaQ92+YzzxFKImjaMisZMHR9uVPnsP2CJnDI0LPeyYbgcvJ60C+vHRHjQs6q7Bfuc9XlWNJfB05pT2cuV12U+WUrxlJ1/CPRGduLe6MJcLrpBRgnZOOR30R99ViHLsd0VxWMKRyjvKxTnkC/AvdnBUyayj1Rdv6qmHaRqbPmm8/XIV4Ah+rR9Rn3cY6O/1ztmZizNsbQbDb58z//c9785jfz1V/91bz3ve/l3/ybf3NO423bWd9+++38wz/8A3/zN3+z4bNnEsFsO047crEor1/tHSQO0VZzvB7RVsks3gJPUHNjGBnYm1Lqsff8De/HqJZ1jCF8qbDc3spxeZQvZIUAJJCK8Tyja1ZvJZOkdT5Cgs5L523D9Ba9RwikkETK0IpkidSjAGTaKfPusjmPaMxZ4Y2khQ5r6LhFN7WOCGAuCdDGMq6TQLFUC6iHgjDrIfIBOs8RUYRa2OuY5XMUrb0UtQU6mWVv54VFwLsSK6c6lwS0IsViZJCdUzZP7RyZJajNI+cWob7AoL6L9UFBJ9N00pyisIzgKFTsb8a0nKiK6pxCDlbRa6cxw4EbK0Ht2mPz5/UF1tw47UHu+AmGQArqgaIV2zRBKxDIlRXot9G9DiYbugVNbMvskhY6maPnmOTdrCg7kHmEnwSSWiBJlEF0e8i0j/GlX1IiotjWeoe2Fn2obd7c50OlkzcNpI0+REoQKwFZBlVxFhVgRIAJXUmaisoyrbJ0iXK3dqEkrbCKSLOKkxdlL2YfTveRH527RjC+HM0tIu38LFGtRNQ+R+uctr02jcv06DGvXQ2BV8G0FiDNqLlGSdiaDH9X/3+K0/UIfduoujpehcHu1xdCWG33LY0rZBm5eiLNl+VtZ/unu1UXHG9/+9u55ppreP3rX8+rXvWqcxpv2876R37kR3j1q1/Nz/7sz7Jv375z2ukzzUaIeHSDQSUsVZVNFNKxbO1bSowIQsBIXKA6xkT9afm/bt9VacMNN8GG78ux93xJrUYgHePfo2pRCU3avrp6tOAoQ+MRN9z0QtYz62w9ScmzkpNAEKeW6CayHnKwXqIzXZu3RLdkjuUipJtZZ7TatznWUAkakWJ3LaAVSaKsS3B6EdNbQ/e7Fp1FCbK1QL7rMEV9F2vDgt3tjLVhVpZa1UPJrlpIM1Jc3JCozklkd5lid2ydrC6QrUXk/BKmuYvBrstYHRSsDTWNVUtQK4wNVx+er7FYU8zHirnecVT3NHrtFMXpx+25CiLCg5eg6wvoxhInabGeFqwOck50UwptCJ2a2+H5hLnIlZGdXkD2VtHddXSvbasGogSx9zA6saVfx4eCXqbppnYR4c9RPbTnqB5K6soQrB0tSWpm0LWM6CgpKwFM1GClsEh9UGjygrKcKZSCVqRIHNEx6J5CZn2L1LPh6HqIG2inyNaXCYPCof5SBc062Xoo7TWgBFG6bku2iswSzACkREfNkWhMWKOdanctWfTv75NGaMl4kZIEw7bVhjd61FjDqYGZLSJLXbkHz2jbyFlfENtiWN5M1JHP7Im1yfTJq1/9ai6//HK+9Vu/9ZzG27azPn36NG984xuf0Y56u6Hw0lFv+GDK6rvynhTOSWLKMSYGZrPsTnXVrQRlaZ0dtxKKN0WpAW2mNkKwzFfpVgll3nNDKF1iqIwjR2zbTx05Qi+3OcbqwsGLfMR5r8yh2ppmUyJrHLJu64C+q7FeG9iHbyChHgYsJsoi63yAWj2KGdh8rtEFIoyR9SbF/DI6mWc9NxzvZC7kbBFGEijmooBGJDlRl6jeCqLfRp94CD3sg9YWWTfnob7AcGGV9aGmk2kebQ8su9kh4m4zoRlbgllreBrZX0N3VilWrbCFUAHqdB9Tm8PU5lmhQSctWE9zlntWVzyQNmKw1oxoRpJGIAhWH7X56l7HOlghbbOVx9uYZA6dtFhOBYPcssk7rmdyIAT1yC4ePLJW68ddbn9g+3JLiVABur6AiRrWIWrleo/7kitXPoh1inEgSZRADVbLMjJfSmakwkQ114ksYShji9RzUwqr+OswKfkG2MhINihD9P7a8oIx9t+Ybm7KxiuFy+tL4SRZpYv6DNe56ZrnMCaGUt5kDp2eJX9dbn7WuPK52xhnbTslVtUa8TNYGb4XG5XMrE74ExcOf6YtG6aJndx8883cddddfO5zn9v2eNt21t/2bd/G3/3d33H55Zdve2fPVPMr86rerRHS+uqq7F/FpBAlWakke02MUfYIHvt7fAycIpN3tNVtvb/GiFHO2pedlGOwAY6XEYIKIcnm2x1dyCNzF06X2NyrD6VLRprSXgQD7UKgKrJzUAEmsXrZqQjop5YMNsw1EiddGipiJWiGEpV1EYM2urNq88xFPmJcx00rOJJp2sOC5b4tHysK7bTKJY1IutD1CYuq105TrJ2yBLUoRiQNG7pu7GJ5YJnky/2Mk13rVEJlc+e1yCLPuhkiVh4jXzmB7q5hBn0btm60IKpjavOkUZPTqxmn+mnJJg+koBnZGu16aB216i1jVo5RdFbHwulWkc0Kq/S0Ym2YuRy6JbpFUhJFlpxYCyQ1WSD767aEbNhHZ04hLLLtQr02eYpikBekuUWveWHrxwV2geUdta1FH45KyPCkRWV/xyDGBLF10oUNW5d1wZWwtb0OsES1MZaYWxirwI0VkcOYo/b5aollqIdSIPO0JBqO5a1htDA1Gxe51ZptqCAjd89NDTOfxdlVu3VN298Glrnf3xZD5Vuttd58fk8MleuZFAY/m3zo0tKSrcffpm3bWT/72c/mzW9+Mx//+Me59tprNxDM/tN/+k/bnsSXswlXdlX9e3yD0c2yIaTN+Gp0qrj9xPbTbr6zjlEZq8w3uwdGNZReDcVP7lP4ufj8+1ho3XV3QjhHPZKpLAU5hBXPKP+VFklpGZLlTg/c5U6TQBEGjrmtpHUama07LslIKkDUGtYxhjUGhQ3pZhU9cKWsAErdOf1aIBBpH93v2RIrsAS1MLJEt7CGDusMXI23738dSIvokkBSU7IkqGlHKiNNrfBGECKd5KkJa7bEKrNOOvNkNykcW96Nk/UsY3vYx2SpJajFVmxGxIkl3wmLgq2D1WWpn81XK4tclW1uQmHHML5zmOtEZgIreapFQJY7ZrX7+QI1LlEaKpDGiZdUc8zK9+P2ZVYh1f7NArtI852vAkd4s1UFRSWtIsproayScF2/dKUAWgibn/aOIFAg0E5UJStrn0WpU17J+57NyU7cpxN8tI3mF65y2iLg7M70QvHNn6o+7plEMDtw4ACPP/546bCvvfZaPvShD5VKdKdPn+bmm2/eNr9r28uq3/3d36XZbPKxj32M3/zN3+Sd73xn+XrXu9613eGm2m/91m9xySWXkCQJL37xi/nkJz95xu0/8IEPcNVVV5EkSXliqmaM4S1veQsHDhygVqtxyy23cP/991+QuW7HznT9TXOy0xxr9a1zXRVvGGPKIqG6XRVce3Q/qf1s/EsGU8eU0j5MA0lZ+132UBbShvRcWRSuxEoHEcNKntszpGOX4/QvUQydFrh1+iKMLeM6blrHGDdsrtTlS32TjnooacYBSWAdrSxSK+7iJDNFYB2i7a7VQMdNBgX0s4K0sGzrWDryVqSYiwOrB+5Loob9sgEIUYRM6ohaq0SvQ1dTXbjyslhZYlkzVFa4RBhE2kdmQ0zuHI8KkHENUW+BI+ANc0j1qIOVFDZPXQ8cSz4YX9BYRTDLbhdJvcwF6zApS7Q0VdUzW1ttz7e06mdFZpEwLuztBFBwoWqjIisJaky56FNClISySErLdveoWmtXCSBABKBCkKFF/DLEqGDUuQrKHuGBH1P5RiKjhiRlqVa1tekFCPueix/x8z6Xkq0dz4E/AejaL6i28zoX267v2AmbXOg9+OCDZFl2xm22YttG1g888MC2d7Ide//7389tt93Ge97zHl784hfzrne9i1tvvZX77rtvamjhH//xH3nVq17F29/+dr7pm76JP/mTP+EVr3gFR44c4XnPs6IIv/zLv8xv/MZv8Ad/8Adceuml/OzP/iy33nor9957L0mS7MhxVJ3ZZjf3Bmd7FoddOs+xMOHmN5on8Wy+gUXC4yh4WiidEq1tuiOhKrWwYgyl33TDDWN5fq/PjDGu8UM6eqAGrtZbhfSNKklJg2LE0I0DR05zL7VulcbK2mHHtC8aS5ikRRE3OdHNLUEt0/SyAiUhVorddUtOa8gC2VtBrYTo9T3o1IabZdJAzu0iX7qENGqxNtQkawPWBhYRK2kd42ISMp8oDtVBdk8ju4sULe2IbgVyfgnVWoDWbtJ9z3EEtYJ4dVCGrZtRwK5ayFyimIsUS2bdjjVYJ99bhzwrFdRMbc7m4JPddDJNL9Ps7WcU2kYt5uOQWmjD381IEvdOOyGUng0PY0PCxjl8EzfpEpHqERHM/v7WydbcOY+UJEg7Nq/sHaP7zU2YOFJhSKHiUv/b1lOPLHTKWqFy2uKFW0AUrruUR8EuvaLDGlqosjY7rXAffN1/KKEmrEAL2QA5XHf9pjdxzpvcN5NM8PI+YKMDKUvCzmEBUOWQbDq/s4zrhVGq3JbxdtoTPJfqmBPj73Q4XLA91H8uvnq7vuPJtHOJHFywX+jxxx/nl3/5l897nHe84x28/vWv57WvfS1XX30173nPe6jX67zvfe+buv2v//qv87KXvYyf+Imf4LnPfS4///M/z4033shv/uZvAvameNe73sXP/MzP8C3f8i08//nP5w//8A85evQoH/zgB897vtNss0buGzoRjX04Ef7e4ShQ6Ty3eJNOWzTYcSoIukRGI5a77WQkxnQtRl/Wo4dz9b1zser3JuQUjRkPRfp63+nD6LK15uTYvqyn0Lha3xFZanKHwmiMb4U5MZ4xVaRlyiYPQBlFsHQDjwgr39dFGcKeZpPHNnYdGT0iXPm3HBmwOrdpl68PY271ujxb6HcncpI+ulM6+mk2JYrkyxS3Yn7aTwQx63wc6BnP75MQYvb9rLfz2q5t13c83WzbyPr7v//7p77/0EMP8clPfpKf/MmfPOfJpGnKHXfcwZvf/ObyPSklt9xyC7fffvvU79x+++3cdtttY+/deuutpSN+4IEHOHbsGLfcckv5+fz8PC9+8Yu5/fbb+Xf/7t+d83yn2TRHvZnzth9OPjiehFxNJddcvuXqSoUYf3iLM63UK1Z90Nx55EjlOyB1XoYkhRfS8PtXoa2lVaHTyLYO0YdmfetJi/IgKDJk7zTCqWeZIrcyqEGCbixiogZDAk4Pcoa5oZcW5MaULOkTSUAzskxy0V+FU49iBl3bXCWMEfUWorFAsSulWyjW04JH2gN6mdUDTwJZIuJmKDkle1Y2tbNMfuzhMgyuFtdR8+vo+iqdhzqspwXtYcHR9SGp86676xELSUAzksxFilr3GHKwblXU2sv29EUxak8fnVhkvVI8RN8xwNuuXCuSgsV6QM2VgMWiQK6fsOdI297cwuts1xcwYR2tItqpdrXVlOdaSQiltGx7AaLIkGnX/WY+Ju16aYd1m19G2s5ouMUIFhUIVw8dyFFFgSwyql2xSpOBDcQ7ZTbffrQw4+0w7VhOYtTYtpoiTyHrc9O1zx2/zifzyZukf85mZ7yfz2DnFALfpp1tEfREM8CfKDsX37FTJoRgfX2dJEnKCEqn06HdbgOU/27Xtu2sV1ZWxv4uioIvfelLfPazn+Xd7373OU3C26lTpyiKYkNZ2L59+zaluh87dmzq9seOHSs/9+9tts00Gw6HDIfD8u+tnOBt38RbdNRjBPCz7WMKQt/sK6aae56Ws6447DPtz0z8XR2/3Ldwc5+EbkKWje+NUDaEChQ+d2qck5YQYvv/esch80GZhxW+b7VjDZsgQSdzDApbzmRlOAs0VrvbM8nnIolK1xGDdeSwQzHsYwqNCEIrglKbwyRzdApJO81Zd61LvRDKQhKy4ARV5iKJXD5d6ombIsfriatdB9D1BYr6IsudnLVBTjvNGeYFgbC65HvqIXOuQUrQW4GVYxTdNfSwjxDSdiBrzlO09lHEc3QyzYleWi4cAlcK1UoCFuOAmsiRg1VbDre+jMmGGKmQzXnL/I6bDON5eplhmDpRFheBrrkFUawktUAQ9FdGJVWulaZRASZuliVVvRyKzJDrgsKYMq8cB5JA2vyyNHmFpT2RNlGxdfzC9b7GhqSL3G5XEt6cRxLgct7C9sCu5KttDsgpBMqKc6rK4U6UKm52Z41zN4TdshoC1xXBlS1aNUQ9tayz3HAKAXUiyuU1wG0EaxvPoCeICQ6joNt2toeNz904jseaYng7F9+xU2aMGetpbYzhhhtuGPv7XMLg23bWf/EXfzH1/V/8xV/kgx/8ID/4gz+47Uk8Fe3tb387//k//+cN75/rqvpsNs1RP20IkecaHRDSsrf9A0gICiwC8WFhT0wSULYJDaRwRKlRzrR8kKnAEaZicoRt9uC1v6VECkMtVONM8jxFFA5xBmFZd0zctKgzajDMnOxmYVG5DKzG+XwSUA+sQ7OLhz4mT8EUlsAVRpagljTRcYt+IUr97twJoHh03ggtglXDdVtTPehiUtcSs96w5WOufWknt9rmlpVudcSTWFJ3giWJMsh+BzHswLBra7Pd+TSuTEtHDXqZoZcXZAX00sISAZGOEGjrn2U+gLRrNbu1J5W5KhDH/M4MDB3b3jtqIx06d7+ZLDKLfLNBBZUrx/zGsb6la8u5sZWkv6pUJeui3IJTmEruXCqEDsoyrbHrzV1rZ+Jp2EtRjD1Uxx6u20Cmjl+3qe3ULf5UY1Pb32jrz06/rWdQe3vrW9/K2972tgs5tQtuf/d3f7cj427bWW9mr3rVq/iFX/iF8xpj9+7dKKU4fvz42PvHjx8vO5ZM2v79+8+4vf/3+PHjHDhwYGyb66+/ftO5vPnNbx4Lr7fb7Q0XzlPOzmGlPIaupw1ZNgEYv/m34pA3HXYsVKAqD0/h8sL25dGCYDzcKT2L3Hd4kgrhy80CV4YU1sgKSiEWr8suBCSBZSPXAlGKcKC1fUBHCdIxpXXcxCRNchWSp0UZxkwCy2ROAkkjqISa064VGQFEENowetJANufIk3lSGTod8KIMM9dDK6Ayl1hRljAfIIbWyXp9cxFGZTjeJC16OfQzTT81paOWEuqhFT6pBxI5aI8cdbdt0bCyxD0TxpioRq5CesNReiDVhgBbEhcKS94LdI7M+sisj0m9lGuMcKVURkXkiLI0rnAlX4EwJblRSayj9m0982Hl948BZaMqSHLHas8rF4/ycqIOnQW+/MsTFN3FZhAIp41vAuyxTraELEvCxssLtTEbHOdZHd6ZyGsTIfatIF4P2kf6CZtHraaZv1+qf59xZzsEPKbadol4bttHHnlkrEXmNFQN5+Y7dsq++qu/ekfGvWDO+q677hqD+udiURRx00038dGPfpRXvOIVgFWB+ehHP8oP//APT/3OzTffzEc/+lF+7Md+rHzvIx/5CDfffDMAl156Kfv37+ejH/1o6Zzb7Taf+MQn+KEf+qFN57JZuGUnbKtI9EKh+nNRIdzMaVfH3MxuuPFGF64zZUkNUxCPkZb97fsJ55UkX+A0zUMliHQ6asvo0FpZqx01MKGTpSxU2Yt7mI+IW1aBy/Z1jnunRz2inUOq9prWtQVSFXOsY9tX2o5Y2uVxbS/uVqxIij6yt4I8VUf3u5h0YKVOG3NQXyDffSldE7I2LJhrp3TSnEwb6qFiPg6YSxSHWhHBYNUywHur5McbTmFMEew/DI0FisYSy2qetWFBe1Aw17GOTwrB4fmEZmTbe871T9jceW8V3W1jBj03nxZ69yXo+iIDVePxTlbKkxbGEEpJK1bsa9iWo1Fu+3mr9eOY1CqeyVrDhdEbFPMH6RtFPzesDYtS/tP3u46VZDFRqHxge69nQ0Q+GP1eYa1MW2RBzfap1pR19R49V1vMBo58N3Yd+Quw8n559VRz4d7K7nKTqHrciUkxYoL7xYKoCrfos3XyOsNCGD/mGQhVYxGA6aRQL6BkGDlof+ts6TZ/AlD42TqeTdseYG5ubkv9rM/FdzzdbNvOepLMBXb18r/+1//iG7/xG8c+f8c73rHtCd1222285jWv4QUveAEvetGLeNe73kW32+W1r30tAN/7vd/LRRddxNvf/nYAfvRHf5Sv/uqv5td+7df4xm/8Rv70T/+Uf/7nf+a9730vYG+EH/uxH+MXfuEXuPLKK8vSrYMHD5Y/6pNpF4xQ9gTln3weu2rV59G0h9Ndd945yllj3MN0nLVmRS8EuXbKVIYxZSblULWSEOSuFWPhhC9cvS9SuYe/zaGu52ZMMhPsg9fqUVvRkaBzypZ9ZX2b0/XIMYgpWssudA2n+3nZqUsbS+KqR4rlulVAU4M2sr+GOf0Yut8DUyBrTURzHpIW2UKPdmo7az22PnTjGOaigLkkYC5WLMcG2Vu2EqVrpylWT9nyozAiON3H1BfQ9V2cyAPWB5rlQcqqk15NAklnvkYzlMwlkmT1UegsW3LawOuk15CNFuzrUdQX6ebweCej7crQ/DhzScC+piXMqf6qVTxbOWYbiGiNqLesSEzcJJ87TS/T9HLN+kCTOhTbiAIiJxQzH2EXRNkQ8kHZtAXpF1dOlpSg/K38deQbvvjfviSlVVnt1WqEykV54w3Xu7crRMhNtLur8rkSMOdxW06G2qcRy0rdgkruWlSPyR/PhIpatdJi0kZHcDZUffaysAtu54ist2Nn8x1PhL3uda/jXe96F61Wa0vb/8f/+B/5uZ/7OXbv3n3WbbftrO+8886p77/whS/kxIkTnDjhNJDP0Ql953d+JydPnuQtb3kLx44d4/rrr+fDH/5wSRx4+OGHkRVW51d+5VfyJ3/yJ/zMz/wM/9//9/9x5ZVX8sEPfrCssQb4yZ/8SbrdLj/wAz/A6uoq/+pf/Ss+/OEP71iN9VbtSWF+b8UmUO8ZN62UIG1mGoM0YlyfuPIgKsORE0NUHzj+Ya3AhsDHCEo+5z0uS1lqkRvKOs/AIb5Q2dCs76FtCteWMQgQQTgKpRsY5tr20XbCKoGy6mCxE2hRaReRWmRe9HujxUMQgZPw7OWaXm41wLvDnNzlQ31XrFhJ5GAFOWhbR91exvTWXeg6sMS5sEYexKx3rETp2iCjmxUEUpaRhziwva/prVKsnkZ3lkdSp1ICLZdjFvTyglO9lE5akOWaMLC5am0MoRDIbGAbagzWrfSqE2ZRYQSmAUIyzA39XDPIDauDjNy4ft5SEUVOXSwfWkSddm2v8WHfKsMFIcbU8ap1QydL6ntTSwnKQKRsxy+reJc5ZF7Jeft/ZTCS9xRggnhENqtGdTYx37Sm2ORS9jr59lrdmvPxQ2mXu65e05s155nYaeX/PRFz+mLDh/I3uxONcBqCTwYbfLOawDNtv007m+94Iuz9738/P/qjP8rzn//8s267vr7Oe9/7Xt7ylrdsaWxhdqKz+pehtdtt5ufnOX7sGK35+anbbDdMve2GIJPjn8GpVseeXje7ybhbEJGotgqEcUc97QzceecR27ZwEl2X4/l8tSB34U//cANGrF8hbL4661eYvyPkYVRgtbJlyLAw9DK9oXGEkjAXKSIJMushu8u2oUXuSoiixBKwogZ5Y7dzsprTvawU46iH0imESZYijeyvIQbrmO4qeu2ULUtTIcEeywDXtcUxNHyqZ515LAWHFmrMJ4r5SFFfexizeoJi7RSmu45OB8gosU1ELrkG3dxLxwTcd6rP8iCjPcjICmMbdSQhV+2us6umiAZr8OBnKFZPUHQ66DQjbDYQc4uoXfvRFz+PdqFYHRZ87mSHblYwzDTzNcts31uPuXQhIuivILvL6NUT5McfsddGEBDsuRg5vwddX2A1XKSTFqwNc0507XEFQrC/GdOMJY1Q0srbyIEjzQ0Htp92GCPjBN3cYxF6ELM20KXwCVhnHUpBM7RKbDJPEYV1/D5GboLI9QYPyYSy/a0d3+GGG28cD5tXCInlNe2cvEaQun7pPg3jzS+ElBTEkpGISz6w12H1Opa28YgvQczceNXr2V/TnjApmAjtw8aoAWxKiqvej5P3or/NPV+jzPNPpA+MCkFI1tbX2b9vH2tra1sKP5/N/HPzxCMPbGu8drvN3kOXXrB5PFH2kpe8hC996UvceOONBEFAGIY897nP5U1vehPve9/7+Id/+AcGgwFaa+699156vR6PPvrolsa+YDnrmV04O5ec8o7bFlr/nWmpMo6uTfngqTptgWVaa2HGdJglwmk+F6WkqNUPd1tJS1BCBWRCkReGzPg2jCCVlaRUyhKnYnLb6CGzJURGhhAG2HaMjbKvc8fJgaa5cejVPrgbkUXD9UAgO8uOyNWBbGg7YTldct3ai67N09OK9UFG2+W7k0ASSUkzVuxKAuYSSZR2MGunbCOS4QCKHFlvIRvzqIUliuZeuiakPcxZG2T0s2LMUe+uhSzEiijtILsrZOsrVuM8d9Ki9RZqfjeitYueCeikOSv9rHTU0imx+e5jZWOU9WWKzqolqLm+5aIxh47r6GSOzqAoa8ZTV84mS0lYS3YT3c6oY9iwb9n2YWyZ+1ENHSTloijNbalepGTZ8CUOBMqpr+Ebh/jfXdl6bC0D+pm2DUOcA1ofFpYIqASBlKggRubDUQjdaNAudywDlBTowkY8BNOVzLyTG5Mxrd4bfgEgJBpBoXXpqP0iwueqlXBhfSYcqB8HH1L3/z96KIwpJHohHUBIUTrtKsrWjqHvy+SEn/cT0dLzGWR//Md/zHvf+16OHj2K1prBYMDv/u7v8uEPf5jPfe5z3HLLLczPz6OU4ju+4zv43u/93i2PvSVn/bKXvYy3ve1tfMVXfMUZt1tfX+fd7343zWaTN7zhDVuexNPJLlTo+lyIWuc79k7a5LSrjT9uuOHGkaZ4hWg2Zj6/57BAVd7UknoqEqWeUOb3raISIQ2NdCQlG1L1W0XK5z4FibYkJytP2ht1ZBISE7csCzyssTK0/bOr8ptKCOZjSS2stK4crFvWtZMWFXGCqLXIFy+mqO9ifViw4Hpod9KCwhPLkoBnzccsJArVOYXcJShWTmJ6bSvKkjRQ80uopf1kB65hJZcs9wuKEx2LqrWVKF2shexrRFy1OyEerKDWjpFFXfT6KjodIKQk2HeYYO9FmMWDLDcPszwoON5JCU53S1LYofkaB5oxu2qKi1QX1T6OWV6kWFlEt0+DVIikQXT5tRTNPejmbnZ34XQ/Y6WfsZ4WKAHNKOCSxYT52LbmDE/Nl724TTqwTPlaA2pzFLsOk4YNOplmuW8dfqEphW9qgWB3TTkSYMfxCxybXCmK2iImqqOjOquDYgyZFy6mXUibfpETF6nwJDQj3PUkp4bCN/SF9s7xTKFwV4JWddRjHztSmRyr2R7PT3vSZbnLifS1/WDyPlKlzPBkakobYxupbGI7+dywpVvbIZg9PQO+hw4d4ud//ufH3nv44Ye55JJL+Ou//mu+4Ru+4ZzH3pKzfuUrX8m3f/u3Mz8/zzd/8zfzghe8gIMHD5IkCSsrK9x77718/OMf50Mf+hDf+I3fyK/8yq+c84Rm9tS3aSSzqk0+mO6884h11hOh8IlRx9oJei7v6DseWRejnLU36boyqYDMiLL0J688cW0o0+aqIz0qIxJZvxzLSAWOTa6DhLXUkGqL1oZurEBaFrntsAWqcwIx7MGwYxGxLmyIt9agmFumSOboZZrjndwh64JcG1dbrVhpxszFlsgljn0Rvb6MHti8t4hqyOZp1Pxp8mMp7ULSHhR8YblHJy3ItaYRKlpxwHI9or8QEQ3XkZ3T5A88gOmtU6QpQkmCtQJ1souZW6FdP017WHCyl/Hw2oDcIcR+M2a5HrGQKI7LPrLjBF7Wl9HtFVASkTQIewpdW0Q3FjnaN6wPC9rDnE5auF7cks5cTDNSNENJuPLICFlnQxt5iGtQm0PPr5AFCb3csDYoXOmWIQ6kq4UXLMTS1rB7ZJ0NrceSChP7bmgJnQqyNsDzr7sBEGS60pQExhjjAjDGqnoJITewwb1teKd6/Rkzijc7JGxcnbZ31JPtNsv/1dPC86O40mRo298TJTJmPDqFkaOwuHuriuirU516LDtlTwDB7Klqhw8f5tZbbz1jqfBWbEvO+nWvex2vfvWr+cAHPsD73/9+3vve97K2tgbYFeLVV1/Nrbfeyqc+9Sme+9znnmW0mZ3NLuQCd1sL1LPdIFsMmU3t0Ts+EMCGvLV14tZp+xpd4VQlxhjk1dAgwoZThaKA0lGXrbax12jgWjsGMKr3rSJ0H750jnpQWJGP1HXqyrWxYixQNhGRWRc56KB7bUgH1hGFMUJK2ykqqjPIDd3M5qo7aUFWaEIl0caKtNQcQU0O1slXT2A6axQD20QkWIgRUlmmtFF00pzTrod2f5hTGIhb0rbDVJKwyCwjffU42fIp8p5VY1NxRLAbRGhJc51Uc7KXcaKbcnxtgDaGWqSgGRMpR3brrmLWTlKcPkaxvkLRHyKjECWUOzY7p5XegFP9jPYwJ9eaJFC2f7l0TVaG65j2KYr2ipVxLXJkvYlUIQIowho9x5I/0UlJ3Q+3kATIyHYxk1kPMWgjncPXg26ZaiCsgbDRlE5aMMyNU3OT9DKDkgYlXEhdWkdsnWOOKHJ73akAZICKQ4xz7CVvwhiEssjceE9XhtAri0YjRtekDGx0x6nw+bH8YqEMgedDu/ishsAdmvaoOisMxlS6jQlLtBQuWjDp6IXRtixNKnD5coBMV7+rEIUenQsAE2LO3AT0/OwZ7KwB/uZv/ua8x9hyzjqOY1796lfz6le/GoC1tTX6/T5LS0sbelo/U+1sAiNPhp2P9kE1PHzWbRlHH2fTKJ4MiY3kGs2IMV5aFZXIUc/qskRGYWyWcUQSFnZWZa9j6dSuiswi9IrjNw6loWwP5hxbNuYRGlhEbR2+DadL40rGTDHKXQppa7TjGjoI0SIg17okGNlDsIIsSSCJA0moBGLoZDx9j2llEZ6IE9vCMowZupKmtNBo7UPyuBI0y0wXeR+RD9DpoNJSUyIDhYhtD20TJqQDM9ZDWwrhlNQUocKNNUAPbZtPnVlnIAPlHL4rtSqs+tkwL0jzopxToOwxhgJENrROetAd9QgHl/8OyJyYSt8rqeUa5STKpHA9ObIUkQ4sMu+t23Gi2LbRdCHqXFOqsA1yTRQY968YZ3cbXTpqdIEQLobjFov+svWOWuNS3GN0LUrnU94jZpzwpR1JzfpEOwGNcIs0V1ftHXVl4YCUYCI35ojsNqamZiph5arDxS96NRi7IKwS27SD+YEUrgd98cQ5xWe4s74Qds7Mgvn5efbv3z9z1BfYNtVGeIotAmDjXM/kn304+4zjlTeomXhVdugdq1SUDSQQFIzQtHST8Q7a91GWHoWUzt4yyFFh6ai1DMiLcVEJJa2Drr4o8hET2DkeEdeQtbotGQqSMn9aOFTlnXQ9UjTDgFi5muEit05fShtCjxJErYmstxBJE8KaDe+6ScWhpBYHzNVDGnHAXBw4B+vL0DQyCgmSmKBeI2haTXETNdBBQpabMrQah5JmYseYiwISJYkkmDyzddVYFKdqcTknwhq5DBi6nt6FASkFUaCIA0U9VERKWA3wfIBJ09ECCxCOCW6CiKE2pE63Pcu1k5s1ZeelQAinST6w0YthH5Ollr1fZHh5UW3sGANHChzkBcOicAslXw1gkago7ELLo9LSYVadnvFO0rG5sddEVdyjzFk7ZDxy3N7Jjn5/+6qQwtxcyL3eup/PaOGnzSiq47/v2ep2R7qcO7ntwy4mrnGDm0tlHmOPkqrG+U6aJ+Rt9fVl4qz//u//nle/+tXcfPPNPPbYYwD80R/9ER//+Me3PdaMDT6zkW0iljDWpGAiFD5JZpnmj19w403jvbjPUu96RiQ/wYw17iFWIqHKg8iXxighUDorH4hWm9rnqW0dsyepDURUEsp8KQ/gunzZ0G6NrOyfLftrYw95nbQsozxusqZDBoWtQ758qEsnVAtt+LsZKeYLK6YiB+voQ3tse06wKmEL+y3hrTbPsaGinRas9nMuGbjSLyW5ZDFhLlK0Ikmy9iiytx/dvohi5bA9XWGESOpw6Bp0czdtHVJfT1nuj8huXpv84rmIxURRL3qoxYzi4CKma8lusrWAml+C1m7y3ZfR0Yq1YUF9ZcD6cKTGtqsWsFQPuaRukN1lZH8Xeimyfb0BEYaopQNWja25h8d1k7WhrfdecgIv9VCVx9WMJLW1R5Hd0xQrJ9DddeuUapZ8V1x0DWk8z9pQs6tjSXy9TKMEpdDLXGzDu0qIUT9vnY9CxsZLlGYEYUAurFPzIexICZRHqB5RF/m4k66QwTJtSLVVzRu4jmo2NWCvEekJk24uwsndGhUgVEQR1TFCkOaafm7K61uJkTIcWGRONkBWeRdGQ5iAVBRalETLwoAQxn3fIN297sl6JthZzYlzVTB7Otuf/dmf8T3f8z1893d/N3feeWfZGGptbY3/8l/+Cx/60Ie2Nd6Ms/9laE8ECp/cx3b7z57JIW/lRt3OMY4RdMxEdyQp7QPb/7nJYUj3EkK4rk1BifTHxqugdv895eq7bbjZltbkuoK0/Hfcw15IZQVVZODqeYc2x8lonNG87MNbSYEOa5ggRoShDaGHEaYoLAPbOZTCGJQr04orTUSSwLa1TAtjj6/cgY1iiCCyNehRHYrM6qG7/HYSSEIpyByTG3DphhyUQjZa9lVrIOtz1tmmfdsxTVCyppPA1a87jfNAClvb7lTpRJQgfCTPIVATJPRziz6bsWQ+DmlFith5xqwY9feWphh31P4n82WEhUWmwgmMFMaUjUm0J2ZNCPmUJVwVRFs4B2kdJeQFYymV0fcK66jzzMnnDi2PAr8IdY7fLx61nw8lqhY6txyMzL5KVG3sQtPPw3MvfMtZPwcbaUinX/QX0qoIfquvp7n9wi/8Au95z3v47//9v49FoL/qq76KI9W2wVu0GbKe2aa23d63XkVp0u48cqRkgXsJyDuP3DG2zY033MCRijqeEZIbndb86H3BjTfeCMAdd94JxrLGtYHrb7iRT9955xgR56abbkQbuOfTd9ruWqbgRtfj+Mhdd9v9BBFGxdx4w/UcueMOUhWTFpYc9Nzn27nec9edlpkcSL7yRTdhUBz59F1WT3zYAeCm513Fkc/cXaJqHbe47HnXo6TgniNH6Aw1Utp5FsbwmbvupBkpFrI1RH+NF1x9BXfce78N7aoQ2Whx/VccROicO44c4ZSx5U0HrrwGbQyfv/sukkCSLSQs1hQveP41HPnMPcjuMqZjyVw3XnU5ZCl33PMAspuQN05y4DnXAvC5uz9Ne5gTSMlCEnDt9Tdw16fvZFeiaDFEPHIPNzxrH+iCI/d9CTW3ilxY57qXXI4wmjvv+GdWh4aH21Y69VlXXcu9d93JUiPiVCNiVa/wguc8CxOE3HHXvZi0j5CKF7zwJky/yx3/8nnM4kU8Lhc40c3Yf+U1fP7uu5DSln4NFxJe/MIb6WaaI5+5B7V+Er12kusv3o0e9Ljzs19ALe5Fr4acHgquvPY6Pnf3p1kbFLQHOVIKrrr2Ok6stDnxhUdYSBRNkXMo7HPgwAE+/8hRiizDqJCgPscVlxxm9fFHWCsCsrDOyV5Oa2kvBsH6yjo1pyUvgpxGo05vmCIGlqQoMdRjMAzRMiQTPgwvyLS2JYtGlOhY+HtL59ZRO016ESVl5MiH0EsnW9gIiKqSN3VuF0Vpv4x42Z7uIYSjUH7qFg3K5bDL7xttUww+nD6zC2r33XcfL3nJSza8Pz8/z+rq6rbHmznrJ8nOVv50Qfd1FpLZmYhxUxGwfzCYjf2u5bRAuNiIhKsLASNGHZBG+6uwaytypNU67MkZC8eyFe6B6BtACLTr0lXJSbruS0bFGKeAhQqcLrU7FqcBaftNSyIFMhtYtOlqvn2LRxPGTvmsjonqpJqx0rEosKi4EUobMg4U9UBAf2DbThqNiCIgQkR1KzpSX0QUKTpuMuwV5IUNo9dDRT1STlfc6Xf310Ya505QRbUW0EGInFunaOxibVgQ9WzDDt+icy6WNFzzj2YoaSqNaJ9Gt5fR3RrowrYOTawIyjCeRwC9XNDJClYHuWP/G4T0c5OIUycxpwMroLJ2CpOltsWnR+phhI4bnFrNeHx9gFkfsjzIyl7VgYTQhX3FoG1V1E4fo4iHFMMhxdppGzkQkqEu6Ge2Z/lyP2O5n1EPFZ20YHWQMY+TLO2ukJ14DC2H9L50P8NOG9VcoLb/MOLgEoPlY5wu6qzR5f5TfXbrGkYbVh57gKV6yK5EEbQMjUsu54uPPE7xyD2Y4YA4jnneFZfw6CMPc1LNcyI5yLFOSrDvMEv1mIcefIBQCnbXQ15weBdLBw/zuQcfo3Xis+SnjyL7XS5eqNPp9hjO70NfkbBmIjqyiVSKo6fXGGrNfBSwf76BqccsKg2DHqK7zPD4Q1YKNggI9h7C1A2Fiunm0Ek17aHVtfdNWmoqJJIKlQ0R66fRWlNEcxRhg6KolJBdSDOTyfItbP80t/379/OFL3yBSy65ZOz9j3/841x22WXbHm/bzvo1r3kNr3vd66auGGb2BNtOKA9tU+R/ctGxnfXH5ELAy46O/q6yb7c4H+eoJVZwwi5EJsJqUpZMcqS0THKnglZ9RljHL8pSG4UlBdncpQuHlmS3wDn80JaRad/k0I0lR7rkwpPfYFR2U5YQKSuh6ZqRICQFwkZaMYRKoI0gCayyV4CxIdR8CEVWMo9FaMPWEpv/HiJItabnmN1+IREpq6YWKUHgWOAiz5xWeoHxDPUwQocx/UyjpM2FDnJNUeiywXRZQiYEpt9F99aRgE4HrjtVMTr/yvabHuQpg1zTTXP6WUES2DIsKR0ZDIUocopBH4Z98l4fneXooZujOzeZk4Id5Jqs0KQuLJ9p7eQ8bTtUvb5CsVajaK/Y2nFA5HvL/ugGQZYblgcZspeRa816LyWSgmYoXejaho712ml0dx1dr1OstdCrpxHzNXJjaKc5w/aAblrwxROrJIGk24i47tASBmi31xh88XPkxx7CdPvsftYBjp1Yod06hYr3sSYarActHl7t8cBjx+gNC/bOxextxhxoxpyqFbYT2umjpI/cj84KZKgIL7oMuXQRem4vj6URJ3t28bI+zAmVZC4KePbuGktJQNA7jXnobstJuHSNvLWHbre7tRttu/YMZIO//vWv50d/9Ed53/vehxCCo0ePcvvtt/PjP/7jW9YDr9q2nfXa2hq33HILz3rWs3jta1/La17zGi666KJt73hmT6ydTwnXee+73PFmE/Ao2pHGJj2++5oNeW8cQ7jyrKqjFk4ZyjYuqDLKKx2anJiKdiVfRowK0IQQ1lG7HK+UVBqIVPLSpaP2KmphyWi2c3aIH8tstuQghxh1Ph5xUAFGBK5lZESOJAjiske0RBBKiVaGSCpCJWyTjDwd6VTnmY0YBLZNqACMikhzSAvrYJUUruHGiN2eKEEsBWIwAIfOjdajxYSK7DiFQRlItWVd58a42uFKmZwCM+haUpmUkDrFMa0RUoJS9jhlQC/v00sL+mnB0C0kyvywLlAyQOgMk/bJB0Oybh+jNTovysYiBsiceE1R6FLStTCgtXGCIBqRD9HdNfR6Dd1ZZbjWIQlC9KA/WpgEAVlqWOlnZO0BRmu6/YxapNitQ4Qv2cuGFKePkXe6BI0EvW8e012D5l4KbeinBcvtASfX+jx4qksSKLJCc6rdZagfJaYgP3WUzqMnGZxe4/89eIywUaN5sUbpAi3h1KmTfOoLp3l8rc8wK1jr1wFohAoR59Bvk596jNX7H0WnKUESs1BvIZvzoJdYTwuOd4Y8ujrgRHtAPQrYOxfzrIWEAkNQpBQnj1KkKcmhq3aU6/JMUTCr2k/91E+htealL30pvV6Pl7zkJcRxzE/8xE/w7//9v9/2eNt21h/84Ac5efIkf/RHf8Qf/MEf8Na3vpVbbrmF173udXzLt3zLrJRrG7aTofDtjj0WCp9GmBobfBwRb+vGKpH7OIL2r2q1lqk46aqVMqSV95QQ05uFjNVkj8hkRobWuTIiE1VLfKSwoVPj6mIDsCVWOrctF8FpQNvSLxPZOmYdRK40ilE/ZqwueaQE9VASSEMkQaQDR3izzt6oyPbijuoUUYNeZrW2h4UN+QfKqoOFSlALLatcDDolM11kfbRrV2XiOiZpQRBi4ibdvKCT5oRZYcloxtbbxoEbSxRWM33YwXTWrENyinEA2ml4dzKNEoJ+ZmgPcvLCEAeWeR8pi9BDnVN01tDrEeiCot9DBsoylVWIiLA11gY6aUG7n6E6KR3HBtduASCKlDBIMIMept8l7/XJewm60OT9IVGRuxprU5ZrDXLNMCso4sD9rm4hkQ/R3XV6x07T04bOY6foLrfBGOp7V2DYRbhmICuDAV843kHlq+SFRi+3ASvUUizVybtrcPJBTt/zBdLVji0xa3fRuxYwhRWr6eaaLzz0eT7/wAq60ERxwKO7aly1u8mliz2ancdY/fxDnLr3KJ1jHYQQtA40AFjSBRma092Ue754mvXVPkWu6e23VQCLtRCR9MlPPMra5x7g6D89SJ4WBElANN+kNbcIuw5xdH3I3Y+1+dKxNusrA8I4YHFXjWv3tdhTDxDZkNXPP0Q+GHLgeetbv4fPxZ6ByFoIwU//9E/zEz/xE3zhC1+g0+lw9dVX8zu/8ztceumlHDt2bFvjnVMcdc+ePdx2223cddddfOITn+CKK67ge77nezh48CBvfOMbuf/++89l2GekbdXRXQin7suUt7WPilrY2P+f2wxG41T36dNZVQTtUHQVSUtE6ahtmHv0KvdQddTVY3NdvWwbRatWhhAlqvbiERad2/+s4pPLe5vConUYlcl4yUsZlsjaM5u1GZ1rH/YOJMgiK1F1iVqlLOuFcQphlrlLWWdbjqOcdKp0NcjahoNNNhyFwB3D3QSx6+0duXGsIyy0a0HpkLqt9c7KGmSTj/qD2/1KkGHJKrb/uo5m2IVN6MrkAuGOrcgw6cC+8sKJevgFk83zF+740lyXtcB6xH5yCyOswEuRo7MCXWhMocvwPIay05YGCmxI3LhxyuvHaCgyirQg6w7IugPy/pCsM6DotRmsnCaVIcPc0Es1q72UE0ePcfyRR1nrZbR7Ge1hwfHVde656076jz1A/1Sb7okea4+v8+gjJ+iudzG5TZPkWrM+yBl0U3rrKf1uRreX0ssLu4gzhrzXJ10f0m8PGbSHpN2cfGAbjRhsSH/Qzxh2Bww7bdJBztD1U0cXmEGXrNOlvzygszZkuGqPy/9+g1yz1k/pdzL660MGnZReLyP1Ij3GkHUHpO0+xkc/dsqeQWzw4XDIm9/8Zl7wghfwVV/1VXzoQx/i6quv5l/+5V94znOew6//+q/zxje+cdvjnlfS8/HHH+cjH/kIH/nIR1BK8Q3f8A3cfffdXH311bzzne88n6GftvaU7VFdsXOa4nk56c3IaxsnMomivW1GXPMv4f9/s1C7dxQ+dF0qn00ZUowkIZVNa1N2apoY0yJ0WTpt6/RN6Th9cL8U+NAF0jiNc11UEL8bQwXOueJKh0YlXtUysEBY+VRRZDb0XUHBBJYwZ5nuNo/uHWNVzUtKW/vry3/IbemQyXNKfWonPuPJd0NHTMu1y1czWkQF0jbCsCIdNoxusnTkWHG8BFf2po11atowpvIGo5IoX5dvXJjaFNMf4l78ZFrHX5vd0GAM64OULzx6guF6F53mFGlGf+U0n/nMPZwaijJVMEgL2idO0Tm1yjAt6KW2yQhC2mPqtkm9k22nZOs9dGoFbvyVmhWabJiTZxl5lpOlTkTGXXU6K9CZbQuaaYPOC3t8wpX3GUORaYpsgM6G6EJTeA5BkUGakvdTGzXJNWla2N/ObZMVmt6wIBsWZP0eWZqTO015f47z/pCsXxFj2Sl7Bjnrt7zlLfz2b/82l1xyCQ888ACvfOUr+YEf+AHe+c538mu/9ms88MADvOlNb9r2uNsOg2dZxl/+5V/ye7/3e/yf//N/eP7zn8+P/diP8V3f9V1l39G/+Iu/4Pu///vPafXwVLedyKXsVDj8XMbdrA3ftm2Tm23UIlNsyEWf0VEL//8OPeKgsP9bF1OFF4yooFZs/haj0TJwiH60T2NKrpQLg1sVqQDGlc/AOXyJCSJLAAssqzwvKDt9+Q5HNkQMUmeIrAcmGQlhOIKa7YEcYYKEHFGW7BhXqiOh1NsuTIVcVuToPMdkaZkTFkHopEVrIAN0kJDmlizlUuYupO4Ib/2eDaPnQ9tvusis9naU2Jro0IbnPakMYJAbchdKjwLLAk8CW0cuUqswptMcGbk5CYGIYruQ0BpkOFqEiJGATejqq62jHm9yIaRERQG60Fb6VAXkjK6bMWfvJD3H6v+FoB6HLLXmWV+3rTrDRkK0uIfdl11BW4IpnLZ8WTA+5f5x51jISoSo0BTDFJMNLQcgUDQiRRgHiEyiAoWSciTQpQKCRo1oLqLRtqg2akQENUsqtCkUQRBJVFxHCEUUB9RdTTxao52CngTXUU4io9CeZxWSFVmpLW7MOMvbnyqhzguvzWyKfeADH+AP//APefnLX84999zD85//fPI856677iolY8/Ftu2sDxw4gNaaV73qVXzyk5+c2knka7/2a1lYWDjnSc1suj3R2uPecW97n+exKjaMctGTddtla02nIW7fmxA5qY41VvpVyYsL2+TAP+Sr4WoYZ5MLaUlnZQi8GsLHCqJoF8I12E5LmBGL3B4HpRZ02WWpSlITtr2nkbYnt9aUamy+r7LXyQ6UAFfCJYqM0dLAWRA68pZyCxM7r7KLmRClYxwh4Yk5AQSBdfpg/xWqTEt4JyuEIHDjhK5ntGDEZCwdgXNuNhIRIMjLEDtYRx0HkiiQBMo56yrCkgohFTJUyDBASI0IFATBGHfQn28fEfGv8neTijiJmFtoEs3VMaEinm8SL+3jkiuv4pGTpznWcb3PA8XCsw7ZhVD3BPVI2XK7JKa1/yAnVk+RLMQUuSW7BbXYHm+Ro6QVeFlsxNRaMXmaE0QBUS2wvx+AiojnG9R31cj7VoglWYiJWnWMVAhtNdrjJCRvJBRxRFwPma+F1lkDUgWoKKSRBOjckCzEdh5hjBGSUEniUBKEkqjeIowCgkiVXbuMVAS1yGq/y5112s8kBbNHH32Um266CYDnPe95xHHMG9/4xvNy1HAOzvqd73wnr3zlK0mSzeXpFhYWeOCBB85rYjO7MHYhUPvk98/ovLd5k02i6cmZSrGRNGYYv5n9g2BD45FKzbZH8oW2jk4zXqctJxx1lU0uJlG1H9vpN3u1KTtmZXFRjmnLxwS26YIxgTsePQrN+/y3kCX72zLURydGYXXOUc4JWa9uP1Y2XG0V1mzdukagpCrDrlYBTZQorGwogXeMbu7SMQFie4+LMLZjGsaIeAqLYCNpc9+BWwRgjEWeSiLCEBlaxypCq8pmsNeU7zwWh4qo0tjE11qPnWsVIIOAIInRRUEQR4gg3lDhIIRASjHqF+3GMkIhw4ignhC1GtYpBoqg1UI25jBh7A+dKBA0k4CwkWCMRuqQuXpIM1bMq5yLL7qEdqdLbfc8AFEYcMPzLuNYt09eaAJhiYCHL9rL0b6gs7KKVJJ98wn1UFmkGybU9i4yXBuVStX2zhPNN8FpF9RCRXM+Bikocs3uuZilVkQ9VDY5H0WErTr13XWMMUSt2H4/SjBCESrJQj1ivRFT5IaoFlCvh0Sl7qkibDZASIvGd9J8SGE72z9NrSgKoigq/w6CgGazed7jbttZf8/3fM957/TL3XYSAZ8L2vXbXqhQ+xlD5Vuo065+X1ZQX/U9qDg7Y0Y1ukaPyT6ObcgIRVf3YxAlGix8TpkRWxtG6W+L92zv7FH7wAqqdgQ13z9bO0c9lnMtc9528EBSNo8Yz33bXLUJHAtchhgk2ujxuQkIhQ0xR8p2mFISRFHYB3sUOSnOuGSUe2lJoUK0djXerod2KKWTC3WNRCqLERHYhiRCBcj6HCZKEEkXLQM0OaGUhNL1mg6UDYFHilpoJUcDD5jjGqq1YGu9m/PIpI6oNWzteGFRrhTQjBR5I2T/QkLRiGjFAc1IVX5vY4+v0SIymniXdZDBsEA2Wi5FYJ1jpASNQGIc+vTypWaIrV2vzRHv30900UGSTo7KMoKl/ZjGAiZqgAgIhGAuDrh8b5Pm/jmM0RRJm4taCfNxAOToqElR38XCVZfSaK8TxyGLl19E++HjrAcBkbKqcPHcfq48fDH/8tl7UQIWk5Cbn3OYxT37uPezn2XhOTewtLiH3Z1V9i7Ms7reJlvYjwkSgkywrxnzb67Zz1o/Iys0Fy/U2N+M2JUEmDQm2HMxC1dD2LCLqrBRI7nsKpjfg1Eh+5sx1148z95WzFo/ox4p9s7FLCYBSoIJa8w/9wrIhpC0ynttR+wZJIpijOH7vu/7iGO7ABoMBvyH//AfaDQaY9v9+Z//+bbGnSmYPUXsvEqtdmgf5zyPszjszeY9RiITU+ZbZfb6vzc5HuNIOkDJ+B77vOrrx/avR72z/fiV8i9TJYQhxp5BYyFZKmjdo+ANB+yaP8igDNNOizR4x+9Jb8aH1V3Zl3Cdw3w5Gk7cxeYqncylE2SxOt6SSEnX37la2iZsrjqMrahKrYHIQ0RcK5OcSmLRrxsrcrrgoWshKtwBy8hpeScNZJQga02rLa6CUqccYcPFDa8H7v5NAkU1vG+7dNXQeY5oWF6MiDqIOLH1535OUhIGksQYK87iQ+rYRZwJQmRjzjYlmVtEZxmiOW9V7IIIIxXKIdrdw80TqwAAKuZJREFUzYhdu2oYrekPI+aSwNbI+0qCIEIu7CWMa4RhgJpfIt41pBPXCCQ0ooBmI2Y+CWjPW2fajALbUz1QdtHY2k0gFcFgN4cO70MdO8FpWScPIgJtuPjSZ3HlsyM+/8CDZIVmbzNiz1yduVpMo6tQczX07iXy/Qfs5ZTUUQevoGjsoqgtcmWSstjLODTIGGS2Xeh8HHJoV43FRBIOYqR+vu2uduAiitZe1judjdfphbBnUOnWa17zmrG/fVvp87WZs36G2RMpc7pVq5ZkAWOxcB/+HvOIZ5x/pV7bmf9f78Cq3y/z02XEwjtq/3CZCKlX8uCmklMfgWqX63Z5QZg+XSPslr7W2ziGtKl8R3niFaIMWUsXIi0XPFJaYpoMrPNXQYn4YVS6JLGEuXqoHHPbsdONrkB4O5ZtAmJzn3ZBEaIxZamXr6lOAkMSKNfru5L2dGQykTSQtQai1rChWeWak4gchEQCSaBIC0MzCqgHqmwKMnauZWgdf6Fti05d2HFd6Fq5MHzkmopoY4/VNhpRo/OgYmRzDtVaQDYXkHkOUR3CqFwwSWmIpGA+CdmVhBgDw2aNxXpEEgXIwJ7jxvwu6hcfQve6BEogm3PM7TVEC/sYHNhH0CsokhqL9YTa1c8BIA4ES7taGOCKK65kv7oY2VtFZn3UcI1DS/s51Fgk2/tsVlPN2rAgLQzXX3MVgFvUSBqhoNEPkb0GLM1RrDQRUllC4J6L0Y0l8mSBop3SGuSsDXKGhSZWVm700HzCfCyJhi1U2Ic8Re87TNHcQ7vd3nixXgB7JuWsf+/3fm9Hxp0566exnSsBbKth8c2Gnfzapuh69McmA02MWQl724GnCbJMfsk7Tlk60FGDj3Gm97RhPNPcpsbNpuE6Uyll8vuapqZm/YxjNjsykSqdoShZ5ChL3hor/XKI2Nd4h66eOgyEC4ODNAWhVICxIfkwwajCirJEDad+lowWKFg0XAskoTE0I3scDdc1S2DAi7IEMToBwtj2iE5aFr3HTYtgBZbhLAWNSFILJEraVp1etlQiMCpELu4l2L3fhsGXulY73TPUsakJr5fdjBQXz8XkczFxIKgHyu5XOQGbuIlYFARzKeHFl2PSAaqt7fyASAoakWWj72vGZLkhDATzSQDzdaLkAPOJJNmzyHy6As0Gz7q6ac93mEDSwgjJvkuuZF5ErKeaw72cgbEph12X7aURSlqRYt70QOdcun8XqnmdbZyRDUEX7L74ckzcIFs6wGIu6GWafq7ZvbSrjI6kUhIJwd65GnGuEaKFyCNIYksyDBIwmkQJTKToZrq8HONAEEq7ODFCYsIEYQzBkkP7MqCIGhgVoY0hUoJWFBBKSaY1ofQd0lxkRgY2/F051ztmzyBkvVMmzLTCxJltsHa7zfz8PMePHaM1P7+l72zXiZ4P4j2fXNNm+z3TkNO+sp05bLbPsTF8HvVMN3qlCQjOWRsz3uhDT0xrjExWRaq+VGiTmmq7oXTCKsK2QpyoD/bjjzTFHdLO+hsZ10JatOnGLZzwyKiV4ajeO5A2Z62EsK0edW41wYddO2+jnQiKddaZim2o1dja6n5mWyb6ntq+P3cTJ1Wap672e3yOxomrDOtL9DPbXzmrHLBH/0oIGqEtLZODNVT7uGOrM2pyEsS20UlYQ6uQXqZZ7hdOaEU7ZCyoBZLFCHt8OrdNSvKB7VDleAQmqqHjFr3GPjqpZljosiVlYarzE7bjViRJTIpqHytbZBovE6tCTJig4xaDwtDNDKuDgkzblp++/3gtlCwG2inG9ZC9VVuCV2Rl+Z2JahTzBxkQ0M81nXTkbIWwi6ayN7oeIrJeee5trX6Ari+SIRnkthd61VlH0qYfgsGqK7cb2NaaQtiISn0REzXIZMRpd27Twpa3KWEXSLtqFqHLtIdaP47QOUVrHzpu0W632bd/P2tra2Up7vmYf26uHPm/zLUaZ/+C/956l8Ubb7lg8/hysBmy3kHbLvI9nxD1+ZDaNtuvEJs77GnR6O3MYdvHWnbe0oyj9vHPt3oKqiHq0lGfaTU/RmIT4/lpsXFB4PdR5qur6m/V/Rhtc8wVpC5waFyOD+pLuZTRFfUzBUZgUJXuZFb/2zgVtLJ/sfCdyHw3MqxoilsMeedqN3aLEhVCENk5uXpx39+5ar5RidA2xG3CxEYMdKW0zhjbLEMGpIUtd1PSPoSUlOXcALRQKKlsf+cqZ0AGtjwtSDAycDXNAmNE6ZTKOQnf69vtXgZWLz0fYtw8y9/A6FIbXkmohYJIWw6Bz8lLbBTHK7GZIMRrzPsGLL6OP1SCQtqFR2FGnAm/UDTG2HNLHVRkhWQq14idO1R1q0J3jiXGLfRC56SjMpduAptuMIZSh94ev03LeG5BeT4Dy3jfkaZAM7ugNnPWM5vZzGY2s501U1HY2+r2MxuzmbPepp0L8t1RxDmxHz/Gdm2zPPZ20fW57HP64OMSlaKCrqrv+/fKeRs25JI3lO1ChVA2EfKulmltmPAo5O7D7EJYIRSPrqshcDnxuxtR4btP6q0LOUaK87lv//+jV4U8JyzZqWSaq2DELK+MI4RFl8J9z+c9lRN8KRucSIUxfl6O9OZaWcJIZCSSopQtrYbBy7mV4X1ZRkJKlO5SCGCsqIpjkBssmgy8FnsZ+pAjRO2uA1Mh1HkiXqAEkRZj16sdb8Sk94pz9gcMRlEad76ELgikJDJQKImRxtaqC1GiWjD2GggiKBKQLm0gg9ExYpX2QmXPU2Gqcxr9xlooZCBBKzsfd979P15v3VuZUnHRCRGAMf57Hu3HaNecRgmLrrUZXUfl+fX3u5uv/413yoyu6LlvcfuZjdvMWc9sZjOb2cx21vQ2kfV2tn2G2MxZP0F2Pqj3ibRpyL4ErVuY+gUThJmo1Z4qKVqWUYlyftMY2mNfYUQqA0pUuimJrVLW5GusN9tFFVWX+WrDWC7co+tRVEBsOLYxlF5OQ4zG9PMBhAxAuPF9R7GJnLqvzS6VLh26kqPBR6jTaXIb5Wu/AydgYs9ZmWM2uPptRjlwf504trvNp+vRuQssIq7mb30uuDqvSQUzm5uVpXpdFaULY/uNh8YiflUpp/OIX1XOo49GCDvRsWiJMJpASlC2hK6KSH3O3rLwFRhLvEOr8eujwqoW+HMuSmU7f31YMR0bmhIqRFSjR1iUL4QcjwqZYnSd+miD27edqO1m5juXKbcjNUZ49NGZwpEYxhH9jtnMWZ+3zZz1OdhO1yqPh07PLew+Oc7GjcZZyVvZ/07fzxvsLKSX6tymHeq06VYdtT/OMWLZVJp7xVELUWnj6L8y+o5/sJch8Mnz7LXMN9Rt2/itFKBdrXZ1/DIEXp2nCzmP6pGD0vH64xcudKoqT33/8B7zA0KWjt8wGtdUwur+Ya+FdT4+BO4d2Vg/dBVY4tLkWBVNcO/MRKXETYqNY1k9cUYhet8JzJ1PJRSBtCFfy3h3Cybhu5SJioOS5e9ZLpp8gbguEEAgA4wSrie5GVuAVY9FBJENQ1fD6ZXfw9bFb0wvVc+7NrZ+XYjRL15ej9MWjxOa8uU5cvu1GvVu3lD+7sL/fo6gVu5jIvy9U881UxSYYusOeDvbPlNs5qxnNrOZzWxmO2vPIG3wnbKZsz5HO1d0fS7lXNXvbXdfm+6nGmaeQt6q7v+ppng2OZ+tnMqSUFYh15y9XGukVlat4YYxLpgb332FCnqvbuSZT5Xwd3XsDbuegtZh4roRcnwePpw9QTDTCNRmSL1E58aixWozFB9Sr4wnhECJEbOwJLBVfxJfzgTjYXBXR+y/Z0oUPZrrWHjezUOoYAx1liH6yu58+FwxKqPz44WTaBKsMtvkT280GFt+FqjQlryN/Q72R7XlW7o8lrHOb2JcnMdHNjar9R+zidTPGYVBNrk2TWVf00iPykcYYPzG2enSLa23GQafOetJmxXXzWxmM5vZzGb2FLenjLPOsow3velNXHvttTQaDQ4ePMj3fu/3cvTo0bN+97d+67e45JJLSJKEF7/4xXzyk58c+3wwGPCGN7yBpaUlms0m3/7t387x48fPe847oRp2pn2dy/7KHs5TB51AdZus5Le77wvRkvNMr3I7sxFVe/3syZcQG1H1BpvIO3pZ0UlUPb6/TVD1tH2UkxAb8pvTxqyOPTZuOdfKOE7GdBpS98jKv6pIfXxursTK56kr+e/R8VH2w/blXyVpqWKl/Ksfz8usinGZVj+mR8FjPX+r50iNtM/H8s5GI5wqm2+vGcqRgIiSPspRIRCW56ySry4n7nkMZpTrHjuu0XnyJDrjyXT+34nIxiiSMXpN7W1cjXRVm9VMkfKddm3qiliNH98ev3BldxuvzXKcHTaji22/ZjZuTxln3ev1OHLkCD/7sz/LkSNH+PM//3Puu+8+Xv7yl5/xe+9///u57bbbeOtb38qRI0e47rrruPXWWzlx4kS5zRvf+Eb+6q/+ig984AN87GMf4+jRo3zbt33bBZn3uTrRJ3p/23LaF3jfW7UzztFvY6Y/v6bZmG+szv2sLTwrTm8TRy2mvM5KXiu/XAlhwtj4k0cvprw39nD1BzjFZIVENuYoqnMdO9bKCdvE+U867PGw/wSZbmzcjU5hjDlfmWfpT3wYXrr68eprYpEp3PfKum9ZcVDGbP47nGHRNGm+d7lGYFxIf+zlFycTv0dJmnOLpannzk/pbJrYVWLihKOevCXGFwmich9MkdLdaTN6lLfeymumDb7BnjI56/n5eT7ykY+Mvfebv/mbvOhFL+Lhhx/m8OHDU7/3jne8g9e//vW89rWvBeA973kP//t//2/e97738VM/9VOsra3xP/7H/+BP/uRP+Lqv+zrAdkV57nOfyz/90z/xFV/xFTt7YDOb2cxm9gy37aLlGbLeaE8ZZD3N1tbWEEKwsLAw9fM0Tbnjjju45ZZbyveklNxyyy3cfvvtANxxxx1kWTa2zVVXXcXhw4fLbabZcDik3W6PvWDz0Pe5oM4no3HHWRH2Du57MzvTnKpI+ky7HUPRE2h6DFFPrNjHO3ZNaQoyMa/pnbbGw6VTz88Egqui6g2bVl5+/LEQ/rQxNwmBT47n0dxUmzbHsZCu2DDehvB8Oc54yL8asp20aaHhcrtqSmICwY4hfhcK99EEr6g2ifhH/chH4fSx/9/sOnQvG2qeRNgKJo6vGinxL68AN/XcbdqophI52SQiMw1V+/NazsFfP5ug6h0Phfs66+28ZjZmT1lnPRgMeNOb3sSrXvWqTbuunDp1iqIo2Ldv39j7+/bt49ixYwAcO3aMKIo2OPzqNtPs7W9/O/Pz8+Xr0KFD53dAM5vZzGb2TLXthMC3W+b1DLEnzVn/8R//Mc1ms3z9/d//fflZlmV8x3d8B8YYfvu3f/tJmd+b3/xm1tbWytcjjzyype+dCxnrXBH2+eSQz5cEdrb9bnX8M213tkOrgrfqvDacl6320p3IU/s5bK5YNkLUWyKw+elMItgtjH822wwZbfb9ybcnv19F1dXfSG7y/9vuqc5G4tvGjTwiH+XQx/PgYhNC3caxxjkImyF1Ufl8Omr1CLuoIGxjNt7HZepfTCc8jueQz8BvmDgXWy0jrHIBNgj0TCM+7rB5UZTtvGY2bk9azvrlL385L37xi8u/L7roImDkqB966CH+9m//9oy9THfv3o1SagOz+/jx4+zfvx+A/fv3k6Ypq6urY+i6us00i+OYOI7P5dAAntD65Ceq5nu7+z2b9Og5L1KmPden7WerDnqTOU1nf4/vfHKhsNk+x0lhm4fAp+1nWgj8bPKrojL/zeZ8xjHPEBadnNsZbco4UohN0gmVuRg7uECO6r+n7at6Lje71IStX/b10aXy18Q209jVNvS9cXM/V98f3JhNrssznJ9NF3ZTztnk4sl/9UxNa6oLSX9uzkpgm9lT1p40ZN1qtbjiiivKV61WKx31/fffz//9v/+XpaWlM44RRRE33XQTH/3oR8v3tNZ89KMf5eabbwbgpptuIgzDsW3uu+8+Hn744XKbmc1sZjOb2Q6aF0XZ8mu2qJi0pwwbPMsy/u2//bccOXKEv/7rv6YoijKnvGvXLqLItrZ76Utfyrd+67fywz/8wwDcdtttvOY1r+EFL3gBL3rRi3jXu95Ft9st2eHz8/O87nWv47bbbmPXrl3Mzc3xIz/yI9x88807zgTfDuLdcZS7ycr/Quz7THZebTu3CLw3hLy39KXtIeoNX59E1JvYBgQ8gaqrX50Wvt3w1hOMjLZy/W5KqNtkW4Mo0fW09qWT+x9XSt+4j+ocq0jTI16P0IEx1bHRPiZIhWdB1VOnssXrYYNNmceYitzk5psca7nvKfPyEZ+NJVvjxLUdtVkjj/O2p4yzfuyxx/jLv/xLAK6//vqxz/7u7/6Or/marwHgi1/8IqdOnSo/+87v/E5OnjzJW97yFo4dO8b111/Phz/84THS2Tvf+U6klHz7t387w+GQW2+9lXe/+907fkwzm9nMZjYzZv2sL4AJY55ARY+nsbXbbebn5zl+7NgZ8+jT7FzUys7Vdpo4dj77mjb2+ZDrNg62fVS9XUQNm+R8typmwXRUfV772eLYU9HfGUVbzn5uJkl1m+VEp6FX2Lyl6TSBmenjXpixJsfxW50pX+3JW7B1cuG27Qy/7ZmOd9qcpnbzEuMRh7X1dfbv28fa2tq2n3PTrHxu/v/exVyjtvXvdfvs+7c/dsHm8eVgTxlk/eVs2yWAjbFKt8uyPU9i21b7UV8o8ty5tAM9p8XMGcLesHXHOXX/W2i4MG2f297XFh31tsY8w3hbteo1MxnKPdN8jBk5Fu94tsp+9/vd8rb+kCfurel136J02NMabojKdmOLAFPpjb5hrtPTIVua+ybHeaZzNY2UuNm+xxq17BR2M9sMg5tZGHzSZs56ZjOb2cxmtqM2C4Ofv82c9TatWk+5nVXouba63CrSndzXBQ0vXwDbyrhbPUebnv8topWpqmHnQmbb5n7PdZ9b3U/1dz/T2GPn7wxjjrfjPHNI3Da4UOMI+wyNYSbHlBPUqDOeG49gHWnMbyrkmdML06IL1WOs7lLIMx/v1DlWSsSmf+HsJXtjm0+ZY3WeW71P7Hcq6nybpirOXfPhrDZrkXne9pRVMJvZzGY2s5nNbGbWZsj6PGxyFbod9Djt+2fbz5OJequ2U7nlJ3vc7Yx9LiVN5yIQMzUKcIZxtkPi287Y0xDotO+PvVcRH5k27maodgOfYHI/m4xbItENe9rCmBPz2mxuY2NUPhlpmW8UXNnqdXA+czzbeJv9LtsZ77xsVrp13jZD1udgVUnLqfKWE3a2vsxbGXuzh/BWx97quGcac9rYF2q+T9S42x17s/HPZDv94NvqPCbns9UH/BN9rW7nt9/u9brVMScX0VsZd6tjbmU8n+7a6utCzrE6z52yp4rc6IMPPsjrXvc6Lr30Umq1GpdffjlvfetbSdN0bLvPfOYz/Ot//a9JkoRDhw7xy7/8yzsyn+3YDFnPbGYzm9nMdta225xjh3LWn/vc59Ba8zu/8ztcccUV3HPPPbz+9a+n2+3yq7/6q4AtN/v6r/96brnlFt7znvdw99138/3f//0sLCzwAz/wAzsyr63YzFlv0Xw5+vr6+pM8k5nNbGYz2xnzz7cLLr/xFAmDv+xlL+NlL3tZ+fdll13Gfffdx2//9m+XzvqP//iPSdOU973vfURRxDXXXMOnP/1p3vGOd8yc9dPB/EV85RVXPMkzmdnMZjaznbX19XXm5+cv2HhGF5htOODtbHu+tra2xq5du8q/b7/9dl7ykpeUEtcAt956K7/0S7/EysoKi4uLT9jcqjZz1lu0gwcP8sgjj9Bqtaa38ztPa7fbHDp0iEceeeTLSrHny/G4Zsf09LEvx+PayWMyxrC+vs7Bgwcv7LjnWGfdbrfH3j/fboiT9oUvfIH/9t/+W4mqAY4dO8all146tp2Xrz527NjMWT/VTUrJxRdfvOP7mZub+7J5qFTty/G4Zsf09LEvx+PaqWO6kIj6fO3QoUNjf7/1rW/lbW9724btfuqnfopf+qVfOuNYn/3sZ7nqqqvKvx977DFe9rKX8cpXvpLXv/71F2S+O2kzZz2zmc1sZjPbUTPaYIrtIGubM5+MHmyGqn/8x3+c7/u+7zvjmJdddln5/0ePHuVrv/Zr+cqv/Ere+973jm23f/9+jh8/Pvae/3v//v1bPoYLbTNnPbOZzWxmM9tRM4XenrN22241erBnzx727NmzpbEfe+wxvvZrv5abbrqJ3/u930PK8Qrmm2++mZ/+6Z8myzLCMATgIx/5CM95znOetBA4zOqsnzIWxzFvfetbL2g+5qlgX47HNTump499OR7X0/GYfM56O6+dsMcee4yv+Zqv4fDhw/zqr/4qJ0+e5NixYxw7dqzc5ru+67uIoojXve51/Mu//Avvf//7+fVf/3Vuu+22HZnTVk3MWmTObGYzm9nMdsJ8i8yH3nUbc7WtLy7a/SHP+rF3XPAWmb//+7/Pa1/72qmfVV3hZz7zGd7whjfwqU99it27d/MjP/IjvOlNb7pg8zgXmznrmc1sZjOb2Y6Yd9YP/tqPbdtZX/Lj75r1s67YLGc9s5nNbGYz21EzRYHehoToTsmNPp1t5qxnNrOZzWxmO2rGbLPOepM2ns9kmxHMZjazmc1sZjN7itvMWe+QZVnGm970Jq699loajQYHDx7ke7/3ezl69OgZv/e2t70NIcTYq1rIDzAYDHjDG97A0tISzWaTb//2b99QF7hT9lu/9VtccsklJEnCi1/8Yj75yU+ecfsPfOADXHXVVSRJwrXXXsuHPvShsc+NMbzlLW/hwIED1Go1brnlFu6///6dPIQxe/vb384LX/hCWq0We/fu5RWveAX33XffGb/z+7//+xt+oyRJxrZ5Mo9rK9fQpD3VfyeASy65ZMNxCSF4wxveMHX7p+Lv9P/+3//jm7/5mzl48CBCCD74wQ9ekPmc7b58Mp8ZMCrd2s5rZuM2c9Y7ZL1ejyNHjvCzP/uzHDlyhD//8z/nvvvu4+Uvf/lZv3vNNdfw+OOPl6+Pf/zjY5+/8Y1v5K/+6q/4wAc+wMc+9jGOHj3Kt33bt+3UoZT2/ve/n9tuu423vvWtHDlyhOuuu45bb72VEydOTN3+H//xH3nVq17F6173Ou68805e8YpX8IpXvIJ77rmn3OaXf/mX+Y3f+A3e85738IlPfIJGo8Gtt97KYDDY8eMB+NjHPsYb3vAG/umf/omPfOQjZFnG13/919Ptds/4vbm5ubHf6KGHHhr7/Mk+rrNdQ1V7OvxOAJ/61KfGjukjH/kIAK985Ss3/c5T7Xfqdrtcd911/NZv/dbUz89lPlu5L5+sZ4a3mbO+AGZm9oTZJz/5SQOYhx56aNNt3vrWt5rrrrtu089XV1dNGIbmAx/4QPneZz/7WQOY22+//UJOd4O96EUvMm94wxvKv4uiMAcPHjRvf/vbp27/Hd/xHeYbv/Ebx9578YtfbH7wB3/QGGOM1trs37/f/Mqv/Er5+erqqonj2PzP//k/d+AIzm4nTpwwgPnYxz626Ta/93u/Z+bn5zf9/Mk+rrNdQ5P2dPydjDHmR3/0R83ll19utNZTP3+q/06A+Yu/+Ivzns/Z7ssn85mxtrZmAHP/f/4Bc+yXfnjLr/v/8w8YwKytre3o/J5ONkPWT6Ctra0hhGBhYeGM291///0cPHiQyy67jO/+7u/m4YcfLj+74447yLKMW265pXzvqquu4vDhw9x+++07NXXSNOWOO+4Y26+UkltuuWXT/d5+++1j24PtXuO3f+CBBzh27NjYNv//9u49Joqr/QP4l7Y7IKWgEcpqlUttMNWWYKElK7HtWxupGqX9w9qqUCLeWml+vPFN0Rhv0dZGjVpJJG0i2iCptVeatt6FFK22QSFeaEmlSC8KaioXI7DtzvP7g7Avy3LZYfa4y+v3k5zIzJyZc46zu0/OzJw5YWFhSE5OVtqWvjQ1NQGAyyw8Pbl16xaio6MxevRopKWl4eLFi85t/tCuvj5D3Q3G82S327F3717Mnz+/z4l1/P08dTWQ+njyvfTVb0ZXukM3nMgVg/Ud0tbWhtzcXLz66qt9jhtMTk7Gnj17cPDgQeTn56O2thaTJk1yTtFZX18PTdPcAn5kZKTLW3i87caNG3A4HM7ZZzwpt76+vs/8nf8aOaZKuq4jJycHKSkpeOyxx3rNN3bsWBQUFKC4uBh79+6FruuYOHEi/vjjDwC+b1d/n6HuBtt5AoAvv/wSjY2Nfb4P2t/PU3cDqY8n30tf/WZ0xcvg5nHolpcUFRVh8eLFzuUDBw5g0qRJADoeNnv55ZchIsjPz+/zOFOnTnX+HR8fj+TkZERHR2P//v3IyspSU3kCACxduhQXLlzo8/4u0PHuYJvN5lyeOHEiHn30Ubz//vtYv3696mr26274DO3atQtTp07tcypHfz9Pd5OBvhuc/os9ay+ZOXMmKisrnSkpKQnAfwN1XV0djhw5YvhtPEOHDkVcXBwuXboEoGPWF7vdjsbGRpd8DQ0NSmeECQ8Px7333tvjbDS9ldvb7DWd+Tv/NXJMVbKzs/H111+jpKTE8FSoFosFEyZMcDlHgH+0C3D/DHU3mM4TANTV1eHo0aNYsGCBof38/TwNpD6efC999ZvRVec4a48Tx1m7YbD2kgceeACPPPKIMw0ZMsQZqH/55RccPXoUw4cPN3zcW7duoaamBiNGjAAAJCYmwmKx4NixY8481dXV+O2331x6Ed6maRoSExNdytV1HceOHeu1XJvN5pIf6Ji9pjN/bGwsrFarS57m5mb88MMPStvSlYggOzsbX3zxBY4fP+426bwnHA4Hzp8/7zxH/tCurrp/hrobDOepq927d+PBBx/E9OnTDe3n7+dpIPXx5Hvpq98M8jJfP+H2v8put8vMmTNl1KhRUllZKVevXnWm9vZ2Z77nnntO8vLynMvLli2T0tJSqa2tlZMnT8rzzz8v4eHhcu3aNWeeJUuWSFRUlBw/flzKy8vFZrOJzWZT3qZ9+/ZJYGCg7NmzR6qqqmTRokUydOhQqa+vFxGR9PR0Wb58uTP/yZMn5b777pMtW7bITz/9JGvWrBGLxSLnz5935nn33Xdl6NChUlxcLOfOnZO0tDSJjY2V1tZW5e0REXn99dclLCxMSktLXc7R7du3nXm6t2vdunVy6NAhqampkTNnzsgrr7wiQUFBcvHiRb9oV3+focF4njo5HA6JioqS3Nxct22D4Ty1tLRIRUWFVFRUCADZunWrVFRUOEeIeFKf7r8Z/X0vRXz3m9H5NPjF/8yT31bO9zhd/M88Pg3eDYO1IrW1tQKgx1RSUuLMFx0dLWvWrHEuz549W0aMGCGapslDDz0ks2fPlkuXLrkcu7W1Vd544w0ZNmyYBAcHy0svvSRXr169I+3Ky8uTqKgo0TRNnnrqKTl9+rRz2zPPPCOvvfaaS/79+/dLXFycaJom48ePl2+++cZlu67rsmrVKomMjJTAwECZPHmyVFdX34mmiIj0eo52797tzNO9XTk5Oc7/g8jISJk2bZqcPXvW5bi+bFd/n6HBeJ46HTp0SAD0WPZgOE8lJSU9ft466+1Jfbr/Zoj0/b0U8d1vRmewvvDvOVK3PNPjdOHfcxisu+GsW0REpETnrFvn/u8VPBCoebxfS7sd8e/t46xbXfBpcCIiUopPg5vHYE1EREp1BGsjU2QyWHfHYE1EREp1Dskykp9ccegWERGRn2PPmoiIlBLd4D1r9qzdMFgTEZFaRt/3zXvWbhisiYhIKaMzaXHWLXe8Z03kQ7t27cKUKVOUl3Pw4EEkJCRA5+VF8gFD7wU3+DDa3YLBmshH2trasGrVKqxZs0Z5WS+88AIsFguKioqUl0XUHafINI/BmshHPv30U4SGhiIlJeWOlJeZmYkdO3bckbKIuhKHGE7kisGayKTr16/DarXinXfeca77/vvvoWma22xWXe3btw8zZsxwWffss88iJyfHZd2LL76IzMxM53JMTAw2bNiAjIwMhISEIDo6Gl999RWuX7+OtLQ0hISEID4+HuXl5S7HmTFjBsrLy1FTUzPwxhINgK7rzvvWHiVeBnfDYE1kUkREBAoKCrB27VqUl5ejpaUF6enpyM7OxuTJk3vd78SJE855z43atm0bUlJSUFFRgenTpyM9PR0ZGRmYN28ezp49izFjxiAjIwNdX/0fFRWFyMhIlJWVDahMIvIdPg1O5AXTpk3DwoULMXfuXCQlJeH+++/Hxo0be83f2NiIpqYmjBw5csDlLV68GACwevVq5Ofn48knn8SsWbMAALm5ubDZbGhoaIDVanXuN3LkSNTV1Q2oTKKBEl0guueXto3kvVuwZ03kJVu2bME///yDTz75BEVFRQgMDOw1b2trKwAgKChoQGXFx8c7/46MjAQAPP74427rrl275rLfkCFDcPv27QGVSTRQugPQHWIg+brG/ofBmshLampqcOXKFei6jsuXL/eZd/jw4QgICMDNmzf7Pa6jhwkQLBaL8++AgIBe13W/9/fXX38hIiKi3zKJvIlPg5vHYE3kBXa7HfPmzcPs2bOxfv16LFiwwK1X25WmaRg3bhyqqqrctjU0NLgs//rrr16pY1tbG2pqajBhwgSvHI/IU3wa3DwGayIvWLlyJZqamrBjxw7k5uYiLi4O8+fP73Of1NRUnDhxwm19cXExPv/8c9TU1ODtt99GVVUV6urq8Oeff5qq4+nTpxEYGAibzWbqOERGGbsE3pHIFYM1kUmlpaXYvn07CgsLERoainvuuQeFhYUoKytDfn5+r/tlZWXh22+/RVNTk8v66dOnY9OmTRg3bhy+++477Ny5Ez/++CMKCwtN1fOjjz7C3LlzERwcbOo4REbxMrh5AdJ1bAcR3VGzZs3CE088gRUrVgDoGGedkJCA7du3e7WcGzduYOzYsSgvL0dsbKxXj03Um+bmZoSFhaHk+acRYvF88NGtv//Bv45+h6amJoSGhiqs4eDBnjWRD23evBkhISHKy7l8+TJ27tzJQE0+oYtA1w0k9iHdcJw1kQ/FxMTgzTffVF5OUlLSgF/AQmSaQyABBgIw71m7YbAm8iOlpaW+rgKR1+kOHXoAp8g0g8GaiIiUEoM9aw7dcsdgTURESjFYm8dgTURESvEyuHkM1kREpJSIwYk8+DS4Gw7dIiIi8nPsWRMRkVK6Q6DD894yXzfqjsGaiIiUEodA4Pl9aD5g5o7BmoiIlOoI1nwa3AwGayIiUoqXwc1jsCYiIqVE1yEBAYbykysGayIiUoo9a/MYrImISCnRDd6zNjAm+27BcdZERHTXaW9vR0JCAgICAlBZWemy7dy5c5g0aRKCgoIwevRobNq0yTeV7ILBmoiI1HLoEAMJd+B1o2+99RZGjhzptr65uRlTpkxBdHQ0zpw5g82bN2Pt2rX44IMPlNepL7wMTkRESukOgW7gFaK64svgBw4cwOHDh/HZZ5/hwIEDLtuKiopgt9tRUFAATdMwfvx4VFZWYuvWrVi0aJHSevWFPWsiIlJKHGI4qdLQ0ICFCxeisLAQwcHBbttPnTqFp59+GpqmOdelpqaiuroaN2/eVFav/jBYExGRUrqI4QR0XJLumtrb203VQ0SQmZmJJUuWICkpqcc89fX1iIyMdFnXuVxfX2+qfDMYrImISCmHiOEEAKNHj0ZYWJgzbdy4scfjL1++HAEBAX2mn3/+GXl5eWhpacGKFSvuZPO9gvesiYhIKYd0JCP5AeD3339HaGioc31gYGCP+ZctW4bMzMw+j/nwww/j+PHjOHXqlNtxkpKSMHfuXHz44YewWq1oaGhw2d65bLVaPW+ElzFYExGRXwoNDXUJ1r2JiIhAREREv/l27NiBDRs2OJevXLmC1NRUfPzxx0hOTgYA2Gw2rFy5En///TcsFgsA4MiRIxg7diyGDRs2wJaYx2BNRERKdb207Wl+FaKiolyWQ0JCAABjxozBqFGjAABz5szBunXrkJWVhdzcXFy4cAHvvfcetm3bpqROnmKwJiIipQZ6GdwXwsLCcPjwYSxduhSJiYkIDw/H6tWrfTpsC2CwJiIixXSDPWsjY7LNiImJgfRQVnx8PMrKyu5IHTzFYE1EREo5YLBnrawmgxeDNRERKeUQgcPARB6q7lkPZgzWRESklEOM9ZY5Q6Y7BmsiIlKKwdo8vsGMiIjIz7FnTURESvGetXkM1kREpJRu8DK44hkyByUGayIiUoo9a/MYrImISCk+YGYegzURESnVEayN9KwVVmaQYrAmIiKl2LM2j8GaiIiU4j1r8zjOmoiIyM+xZ01EREoJAN1gfnLFYE1ERErxMrh5DNZERKQUHzAzj8GaiIiUYs/aPAZrIiJSij1r8xisiYhIKfaszePQLSIiIj/HnjURESnFWbfMY7AmIiKleBncPAZrIiJSqhW6oYfG7IZeoXJ3YLAmIiIlNE2D1WpFUf2fhve1Wq3QNE1BrQanABFebyAiIjXa2tpgt9sN76dpGoKCghTUaHBisCYiIvJzHLpFRETk5xisiYiI/ByDNRERkZ9jsCYiIvJzDNZERER+jsGaiIjIzzFYExER+bn/B34beSZzoRIHAAAAAElFTkSuQmCC",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# plot TM simulation results\n",
+ "sim_data_tm = batch_results[\"mode_index=1; n_100=30; n_010=5;\"]\n",
+ "plot_spectra(\n",
+ " sim_data=sim_data_tm,\n",
+ " mode=\"TM\",\n",
+ " field_component=\"Ez\",\n",
+ " field_vmin=-50,\n",
+ " field_vmax=50,\n",
+ ")\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Finally, we determine the polarization extinction ratio (PER) specifically for the TM input scenario."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "_, _, tm_through, tm_cross = get_spectra(sim_data_tm)\n",
+ "\n",
+ "per_tm = 10 * np.log10(tm_cross / tm_through)\n",
+ "\n",
+ "plt.plot(ldas, per_tm, c=\"red\", linewidth=2)\n",
+ "plt.title(\"Polarization Extinction Ratio (PER) for TM Input\")\n",
+ "plt.ylim(0, 50)\n",
+ "plt.xlabel(\"Wavelength (μm)\")\n",
+ "plt.ylabel(\"PER_TM (dB)\")\n",
+ "plt.grid()\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Final Remarks\n",
+ "\n",
+ "This notebook demonstrates the design process of a broadband PBS based on SWG AM. The result shows low loss and large bandwidth. However, ideally we would like to have a flat polarization extinction ratio. As demonstrated in the referenced paper, this can be achieved by further fine-tuning the duty cycle of the AM[100]. We don't demonstrate this part in this notebook and leave this part for the readers as an exercise. Readers are encouraged to explore additional opportunities to optimize the design by introducing apodization or using inverse design optimization, for example."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "applications": [
+ "Passive photonic integrated circuit components"
+ ],
+ "description": "This notebook demonstrates how to model a broadband polarization beam splitter (PBS) based on anisotropic metamaterial in Tidy3D FDTD.",
+ "feature_image": "./img/pbs_swg_am.png",
+ "features": [
+ "Mode analysis",
+ "Parameter sweep",
+ "Anisotropic material"
+ ],
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "keywords": "integrated photonics, polarization beam splitter, PBS, subwavelength grating, SWG, anisotropic metamaterial, waveguide, Tidy3D, FDTD",
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.0"
+ },
+ "title": "Broadband Polarization Beam Splitter in Tidy3D | Flexcompute"
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/Autograd23FabricationAwareInvdes.ipynb b/Autograd23FabricationAwareInvdes.ipynb
index ace1fb3d..1c41185a 100644
--- a/Autograd23FabricationAwareInvdes.ipynb
+++ b/Autograd23FabricationAwareInvdes.ipynb
@@ -5,7 +5,7 @@
"id": "e2c5f771",
"metadata": {},
"source": [
- "# Fabrication-Aware Inverse Design (FAID) of a Wavelength Division Multiplexer\n",
+ "# Fabrication-aware inverse design (FAID) of a wavelength division multiplexer\n",
"\n",
"This notebook extends the [Adjoint Optimization of a Wavelength Division Multiplexer](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd9WDM/) by incorporating fabrication awareness into the design process. Specifically, we integrate a differentiable computer vision model from [PreFab Photonics](https://www.prefabphotonics.com/) into the topology optimization loop to predict and optimize the manufacturability of photonic device designs. This approach, known as *fabrication-aware inverse design* (FAID), results in devices that are inherently more robust to fabrication variations.\n",
"\n",
@@ -178,9 +178,9 @@
"id": "e12a92cd-ca91-4981-8168-da4bcd7bb156",
"metadata": {},
"source": [
- "## Sim Setup\n",
+ "## Simulation Setup\n",
"\n",
- "Then we set up our basic simulation for the FAID optimization.\n",
+ "Here we set up our basic simulation for the FAID optimization.\n",
"\n",
"We have an input waveguide connected to a square design region, which has `n=4` output waveguides. \n",
"\n",
@@ -382,7 +382,7 @@
"id": "27386dd2-e686-4fd0-8210-20bac15dc422",
"metadata": {},
"source": [
- "### Solving modes\n",
+ "### Solving for Modes\n",
"\n",
"Next, we want to ensure that we are injecting and measuring the right waveguide modes at each of the ports.\n",
"\n",
@@ -669,7 +669,7 @@
"id": "d120bf86-54c3-4af2-b3eb-33726288d008",
"metadata": {},
"source": [
- "### Define design region\n",
+ "### Define Design Region\n",
"\n",
"Next, we define the design region as a pixelated grid of permittivity values that get generated from our optimization parameters.\n",
"\n",
@@ -951,9 +951,9 @@
"\n",
"With our simulation fully defined as a function of our parameters, we are ready to define our objective function.\n",
"\n",
- "In this case, it is quite simple, we simply measure the transmitted power in our `num_freqs = 4` output waveguide modes for each of the `num_freqs = 4` design frequencies.\n",
+ "In this case, it is quite simple. We simply measure the transmitted power in our `num_freqs = 4` output waveguide modes for each of the `num_freqs = 4` design frequencies.\n",
"\n",
- "Our objective when looking at waveguide `i` will be to maximize power transmission at frequency `i`. To reduce cross talk between waveguide `i` and frequency `j != i`, we will subtract the average of the power transmissions for all of the other ports.\n",
+ "Our objective when looking at waveguide `i` will be to maximize power transmission at frequency `i`. To reduce cross-talk between waveguide `i` and frequency `j != i`, we will subtract the average of the power transmissions for all of the other ports.\n",
"\n",
"Our overall metric will then be the average"
]
@@ -1035,11 +1035,11 @@
"id": "218ac455-3626-4399-a11d-1ba288fe63bf",
"metadata": {},
"source": [
- "### Total Objective function\n",
+ "### Total Objective Function\n",
"\n",
"Then we write an `objective` function that constructs our simulation, runs it, measures our metric, and subtracts our penalty.\n",
"\n",
- "> Note: due to current limitations of the autograd support in tidy3d, when running broadband simulations, one must have only a single output 'port' in the forward simulation. Therefore, we split our problem into one simulation per output waveguide, and then run these in parallel using `web.run_async()`.\n",
+ "> Note: due to the current limitations of the autograd support in tidy3d, when running broadband simulations, one must have only a single output 'port' in the forward simulation. Therefore, we split our problem into one simulation per output waveguide, and then run these in parallel using `web.run_async()`.\n",
"\n",
"> **For FAID:** We set `use_predict=True` and `use_penalty=False`.\n"
]
@@ -1087,7 +1087,7 @@
"id": "94fa67f3-31e2-444c-b2d2-9aea353eef10",
"metadata": {},
"source": [
- "### Differentiating the objective\n",
+ "### Differentiating the Objective\n",
"\n",
"Finally, we can simply use `autograd` (`ag`) to transform this objective function into a function that returns our objective function value and our gradient, which we will feed to the optimizer."
]
@@ -1269,7 +1269,7 @@
"\n",
"Let's visualize the results of our optimization.\n",
"\n",
- "### Objective function vs Iteration\n",
+ "### Objective Function vs Iteration\n",
"\n",
"First we inspect the objective function value as a function of optimization iteration number. We see that it steadily increases as expected. "
]
@@ -53702,14 +53702,6 @@
"metadata": {},
"outputs": [],
"source": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "60b5fb7b-d554-4179-a75c-ab979bef3777",
- "metadata": {},
- "outputs": [],
- "source": []
}
],
"metadata": {
diff --git a/docs/case_studies/pic.rst b/docs/case_studies/pic.rst
index 43d70b56..dcbcff9e 100644
--- a/docs/case_studies/pic.rst
+++ b/docs/case_studies/pic.rst
@@ -41,3 +41,4 @@ Passive photonic integrated circuit (PIC) components form the backbone of many o
../../LNOIPolarizationSplitterRotator
../../IntegratedVivaldiAntenna
../../KerrSidebands
+ ../../AnisotropicMetamaterialBroadbandPBS
diff --git a/img/pbs_swg_am.png b/img/pbs_swg_am.png
new file mode 100644
index 00000000..f529e1fd
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diff --git a/img/pbs_swg_am_top.png b/img/pbs_swg_am_top.png
new file mode 100644
index 00000000..3a67512c
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