diff --git a/DREAMS/DREAMS.yaml b/DREAMS/DREAMS.yaml new file mode 100644 index 00000000..f575f82f --- /dev/null +++ b/DREAMS/DREAMS.yaml @@ -0,0 +1,52 @@ +--- + +### Leopold Figl SBIG camera +object : instrument +alias : INST +name : DREAMS +description : + DREAMS is a 0.5m telescope operated + by the Department of Astrophyhics at the University of ANU. + +properties: + temperature: -40 # deg + pixel_scale : 2.48 # arcsec / pixel + plate_scale : 206.265 # arcsec / mm + +effects: +- name : seeing_psf + description : Schoepfl PSF + class : SeeingPSF + kwargs : + fwhm : 5.00 # [arcsec] +- name : skycalc_average_atmo + description : atmospheric properties for a default skycalc run + class : AtmosphericTERCurve + include : True + kwargs : + filename: "TER_atmosphere.dat" + rescale_emission: + filter_name: "!OBS.filter_name" + filename_format: "filters/{}.dat" + value: "!OBS.sky.bg_mag" + unit: mag +- name: dreams_static_surfaces + description : telescope and camera optical surfaces + class: SurfaceList + kwargs: + filename: LIST_DREAMS_mirrors_static.dat + +- name: filter_curve + description : transmission curve for filter + class: FilterCurve + kwargs: + filter_name: "!OBS.filter_name" + filename_format: "filters/{}.dat" + minimum_throughput: !!float 1.01E-4 + outer: 0.05088 + outer_unit: "m" + +- name: fits_headers + description : FITS headers + class: ExtraFitsKeywords + include: True diff --git a/DREAMS/DREAMS_InGaAs.yaml b/DREAMS/DREAMS_InGaAs.yaml new file mode 100644 index 00000000..2e8077e9 --- /dev/null +++ b/DREAMS/DREAMS_InGaAs.yaml @@ -0,0 +1,64 @@ +--- +### Princeton DREAMS InGaAs DETECTOR +object : detector +alias : DET +name : DREAMS_InGaAs_detector +description : base configuration for Dreams camera + +properties: + image_plane_id : 0 + temperature : -60 + dit : "!OBS.dit" + ndit : "!OBS.ndit" + width: 1280 + height: 1024 + x: 0 + y: 0 + bin_size: 1 + +effects: +- name: full_detector_array + description: THe full DREAMS detector array list + class: DetectorList + include: True + kwargs: + filename : FPA_array_layout.dat + active_detectors : "all" + +- name: qe_curve + description : Quantum efficiency curves for each detector + class : QuantumEfficiencyCurve + kwargs : + filename : QE_InGaAs.dat + +- name: exposure_integration + description: Summing up sky signal for all DITs and NDITs + class: ExposureIntegration + +- name: dark_current + description : SBIG dark current + class: DarkCurrent + kwargs: + value: 67.00 + +- name: shot_noise + description : apply Poisson shot noise to images + class: ShotNoise + +- name: detector_linearity + class: LinearityCurve + kwargs: + incident: [0, 57143, 999999999999] + measured: [0, 57143, 57143] + +- name : readout_noise + description : Readout noise frames + class : BasicReadoutNoise + kwargs : + noise_std : 75 + +- name : detector_binning + description : Binning the detector frames + class : BinnedImage + kwargs : + bin_size : "!DET.bin_size" diff --git a/DREAMS/FPA_array_layout.dat b/DREAMS/FPA_array_layout.dat new file mode 100644 index 00000000..8fcbc105 --- /dev/null +++ b/DREAMS/FPA_array_layout.dat @@ -0,0 +1,23 @@ +# name : DREAMS 1280SCICAM +# author : Anjali Shivani Reddy +# sources : https://github.com/Astrogirlanajli/DREAMS/blob/main/5240-0001%20Scicam%20FPA%20Drawing%20mm%20v1.pdf +# date_created : 2024-05-04 +# type : detector:chip_list +# x_cen_unit : mm +# y_cen_unit : mm +# x_size_unit : pix +# y_size_unit : pix +# pixel_size_unit : mm +# angle_unit : deg +# gain_unit : electron/adu +# +id x_cen y_cen x_size y_size pixel_size angle gain +1 -8.015 12.95 1280 1024 0.012 0.0 4.3 +2 8.015 12.95 1280 1024 0.012 0.0 4.3 +3 -8.015 0.000 1280 1024 0.012 0.0 4.3 +4 8.015 0.000 1280 1024 0.012 0.0 4.3 +5 -8.015 -12.95 1280 1024 0.012 0.0 4.3 +6 8.015 -12.95 1280 1024 0.012 0.0 4.3 + + + diff --git a/DREAMS/LIST_DREAMS_mirrors_static.dat b/DREAMS/LIST_DREAMS_mirrors_static.dat new file mode 100644 index 00000000..2374a591 --- /dev/null +++ b/DREAMS/LIST_DREAMS_mirrors_static.dat @@ -0,0 +1,10 @@ +# name : mirror_list +# outer_unit : m +# inner_unit : m +# angle_unit : degree +# temperature_unit : deg_C +# description : A list of optical surfaces in the telescope and camera. M[1-2] are the telescope mirrors. +# +name outer inner angle temperature action filename +M1 0.5 0.0 0 -40 reflection TER_mirror.dat +M2 0.5 0.0 0 -40 reflection TER_mirror.dat \ No newline at end of file diff --git a/DREAMS/QE_InGaAs.dat b/DREAMS/QE_InGaAs.dat new file mode 100644 index 00000000..dc1b3997 --- /dev/null +++ b/DREAMS/QE_InGaAs.dat @@ -0,0 +1,2110 @@ +# action : transmission +# wavelength_unit : um +# +wavelength transmission +0.8010318882867862 0.47089420439103236 +0.8014842434347645 0.48637536025609485 +0.8019365985827428 0.4782511781493827 +0.8023889537307212 0.4820753360496684 +0.8028413088786994 0.4801019014406843 +0.8032936640266778 0.4951879706049592 +0.8037460191746562 0.4854655975193126 +0.8041983743226344 0.4779761523419514 +0.8046507294706128 0.48708141997460186 +0.805103084618591 0.4954502240424059 +0.8055554397665694 0.4903882986383811 +0.8060077949145478 0.4798940500624708 +0.806460150062526 0.4914403608191411 +0.8069125052105044 0.4919116092563264 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0.0 +1.7509776990412675 0.0 +1.7514300541892456 0.0 +1.751882409337224 0.0 +1.7523347644852023 0.0 +1.7527871196331806 0.0 +1.753239474781159 0.0 diff --git a/DREAMS/README.md b/DREAMS/README.md new file mode 100644 index 00000000..dc1da135 --- /dev/null +++ b/DREAMS/README.md @@ -0,0 +1,5 @@ +# DREAMS Telescope in a nutshell: + +The Dynamic REd All-Sky Monitoring Survey (DREAMS) is a cutting-edge 0.5-meter infrared telescope strategically situated at the Siding Spring Observatory, part of the Australian National University. DREAMS is pioneering in its application of Indium Gallium Arsenide (InGaAs) detectors, which, despite having a higher noise profile, offer a cost-effective alternative to the traditionally used mercury-cadmium-telluride (HgCdTe) detectors in infrared astronomy. The telescope is equipped with the advanced Princeton Infrared Technologies 1280SCICAM, enabling high-sensitivity observations across the near-infrared spectrum. + +DREAMS is designed to push the boundaries of wide-field time-domain astronomy in parallel with other surveys such as Palomar Gattini-IR and WINTER. As a southern sky near-infrared time-domain survey, DREAMS is uniquely positioned to contribute to a range of astrophysical phenomena significantly. These include detecting and characterising Fast Radio Bursts (FRBs), studying variable stars such as RR Lyrae, and advancing multi-messenger astronomy by providing crucial infrared observations that complement data from other wavelengths and messengers. diff --git a/DREAMS/TER_atmosphere.dat b/DREAMS/TER_atmosphere.dat new file mode 100644 index 00000000..a471871f --- /dev/null +++ b/DREAMS/TER_atmosphere.dat @@ -0,0 +1,359 @@ +# date_created : 2023-03-21 +# location : Sidling spring +# wavelength_unit : nm +# emission_unit : ph s-1 m-2 um-1 arcsec-2 +# action : transmission +# Details : http://www.gemini.edu/sciops/ObsProcess/obsConstraints/atm-models/trans_30_10.dat +# +wavelength transmission emission +1161.0 0.924793 0.1 +1161.5 0.939469 0.1 +1162.0 0.935235 0.1 +1162.5 0.940330 0.1 +1163.0 0.967153 0.1 +1163.5 0.963672 0.1 +1164.0 0.962931 0.1 +1164.5 0.968273 0.1 +1165.0 0.949592 0.1 +1165.5 0.934222 0.1 +1166.0 0.940428 0.1 +1166.5 0.953383 0.1 +1167.0 0.959292 0.1 +1167.5 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0.1 +1335.0 0.904685 0.1 + + diff --git a/DREAMS/TER_mirror.dat b/DREAMS/TER_mirror.dat new file mode 100644 index 00000000..bd8459df --- /dev/null +++ b/DREAMS/TER_mirror.dat @@ -0,0 +1,22 @@ +# author : Anjali Shivani Reddy +# Assumption: Assuming that telescope has reflectivity of 85% +# date_created : 2024-04-02 +# status : Dreams mirrors +# type : mirror:reflection +# wavelength_unit : um +# +wavelength reflection +0.4 0.85 +0.5 0.85 +0.6 0.85 +0.7 0.85 +0.8 0.85 +0.9 0.85 +1.0 0.85 +1.1 0.85 +1.2 0.85 +1.3 0.85 +1.4 0.85 +1.5 0.85 +1.6 0.85 +1.7 0.85 \ No newline at end of file diff --git a/DREAMS/Test_codes/Galaxy.py b/DREAMS/Test_codes/Galaxy.py new file mode 100644 index 00000000..7287ea2f --- /dev/null +++ b/DREAMS/Test_codes/Galaxy.py @@ -0,0 +1,67 @@ +# Extragalatic +import os +import pytest +import numpy as np +from astropy.io.fits import HDUList +from matplotlib import pyplot as plt +from matplotlib.colors import LogNorm +import scopesim +import synphot +from scopesim import Source +from astropy.io import fits +from scopesim_templates.extragalactic import galaxy +from scopesim import rc +from scopesim.source.source_templates import star_field +import scopesim_templates as sim_tp +from scopesim.optics.fov_manager import FOVManager + +PLOTS = True + +if rc.__config__["!SIM.tests.run_integration_tests"] is False: + pytestmark = pytest.mark.skip("Ignoring DREAMS integration tests") + +cmds = scopesim.UserCommands(use_instrument="DREAMS") +cmds["!OBS.dit"] = 1000 +cmds["!OBS.ndit"] = 1000 +cmds["!DET.bin_size"] = 1 +cmds["!OBS.sky.bg_mag"] = 14.9 +cmds["!OBS.sky.filter_name"] = "J" +cmds["SIM.sub_pixel.flag"] = True +dreams = scopesim.OpticalTrain(cmds) +dreams["detector_linearity"].include = False + +print("scopesim package loaded successfully.") +from scopesim_templates.extragalactic import galaxy +src = galaxy("kc96/s0", z=1.5, amplitude=17, filter_curve="J", pixel_scale=0.01, r_eff=2.5, n=4, ellip=0.5, theta=45, extend=3) + +dreams.observe(src) +print("yessss anjali") +hdus = dreams.readout() +dreams.readout(filename="gal.fits") +# Observe the source +dreams.observe(src) + +# Readout and plot +hdus = dreams.readout() + +plt.subplot(122) +im = hdus[0][1].data +plt.imshow(im, norm=LogNorm()) +plt.colorbar() +plt.title("Observed Galaxy Field") +plt.xlabel("X Pixels") +plt.ylabel("Y Pixels") + +detector_order = [2, 1, 4, 3, 6, 5] +plt.figure(figsize=(20, 20)) +for plot_number, hdu_number in enumerate(detector_order, 1): + plt.subplot(3, 2, plot_number) + plt.imshow(np.log10(src.fields[0].data), origin="lower") + plt.colorbar() + plt.title(f"HDU {hdu_number}") + +plt.show() + + + + diff --git a/DREAMS/Test_codes/GaussianDiffractionPSF.py b/DREAMS/Test_codes/GaussianDiffractionPSF.py new file mode 100644 index 00000000..cad84dcf --- /dev/null +++ b/DREAMS/Test_codes/GaussianDiffractionPSF.py @@ -0,0 +1,68 @@ +import os +import numpy as np +from astropy import units as u +from matplotlib import pyplot as plt +from matplotlib.colors import LogNorm +from astropy.convolution import Gaussian2DKernel +from scopesim.utils import quantify +from scopesim import rc +from scopesim_templates.stellar import star_field +from scopesim.optics.fov_manager import FOVManager + +# Set plotting flag +PLOTS = True + +# GaussianDiffractionPSF Class +class GaussianDiffractionPSF: + def __init__(self, diameter=0.1, **kwargs): # Default diameter is 0.1 m + self.meta = {"diameter": diameter, "z_order": [242, 642]} + self.required_keys = {"pixel_scale"} + self.valid_waverange = [11610.0 * u.angstrom.to(u.micron), # Min wavelength in microns + 13330.0 * u.angstrom.to(u.micron)] # Max wavelength in microns + + def update(self, **kwargs): + if "diameter" in kwargs: + self.meta["diameter"] = kwargs["diameter"] + + def get_kernel(self, pixel_scale): + wave_min = 11610.0 * u.angstrom.to(u.micron) # Using J band min wave + wave_max =13330.0 * u.angstrom.to(u.micron) # Using J band max wave + wave = 0.5 * (wave_max + wave_min) # Average wave + wave = quantify(wave, u.um) + + + diameter = quantify(self.meta["diameter"], u.m).to(u.um) + fwhm = 1.22 * (wave / diameter) * u.rad.to(u.arcsec) / pixel_scale + + sigma = fwhm.value / 2.35 + kernel = Gaussian2DKernel(sigma, mode="center").array + kernel /= np.sum(kernel) + + return kernel + + def plot(self, pixel_scale): + kernel = self.get_kernel(pixel_scale) + + size = kernel.shape[0] + arcsec_extent = size * pixel_scale / 2 + x = np.linspace(-arcsec_extent, arcsec_extent, size) + y = np.linspace(-arcsec_extent, arcsec_extent, size) + + plt.figure(figsize=(8, 6)) + plt.imshow(kernel, origin='lower', extent=[x[0], x[-1], y[0], y[-1]], cmap='plasma', norm=LogNorm(vmin=1e-6, vmax=1)) + plt.colorbar(label='Intensity') + plt.title(f"Gaussian Diffraction PSF (Diameter = {self.meta['diameter']} m, J Band Wavelength)") + plt.xlabel("X [arcseconds]") + plt.ylabel("Y [arcseconds]") + plt.gca().set_aspect('equal', adjustable='box') + plt.grid(False) + plt.show() + +# Define the pixel scale for DREAMS +pixel_scale = 2.48 # Arcseconds per pixel for DREAMS + +# Instantiate the GaussianDiffractionPSF class +gaussian_psf = GaussianDiffractionPSF(diameter=0.5) + +# Plot the Gaussian Diffraction PSF +gaussian_psf.plot(pixel_scale) diff --git a/DREAMS/Test_codes/LMC.py b/DREAMS/Test_codes/LMC.py new file mode 100644 index 00000000..8c02e732 --- /dev/null +++ b/DREAMS/Test_codes/LMC.py @@ -0,0 +1,54 @@ +#cluster in the LMC +import os +import pytest +import numpy as np +from astropy.io.fits import HDUList +from matplotlib import pyplot as plt +from matplotlib.colors import LogNorm +import scopesim +import synphot +from scopesim import Source +from astropy.io import fits + + +from scopesim import rc +from scopesim.source.source_templates import star_field +import scopesim_templates as sim_tp +from scopesim.optics.fov_manager import FOVManager + +PLOTS = True + +if rc.__config__["!SIM.tests.run_integration_tests"] is False: + pytestmark = pytest.mark.skip("Ignoring DREAMS integration tests") + +cmds = scopesim.UserCommands(use_instrument="DREAMS") +cmds["!OBS.dit"] = 1000 +cmds["!OBS.ndit"] = 1000 +cmds["!DET.bin_size"] = 1 +cmds["!OBS.sky.bg_mag"] = 14.9 +cmds["!OBS.sky.filter_name"] = "J" +cmds["SIM.sub_pixel.flag"] = True +dreams = scopesim.OpticalTrain(cmds) +dreams["detector_linearity"].include = False + +print("scopesim package loaded successfully.") +src = sim_tp.stellar.clusters.cluster(mass=10000, distance=1800, core_radius=500, seed=9002) + +dreams.observe(src) +print("yessss anjali") +hdus = dreams.readout() +#dreams.readout(filename="Han.fits") +plt.subplot(121) +wave = np.arange(3000, 11000) +plt.plot(wave, dreams.optics_manager.system_transmission(wave)) +plt.subplot(122) +im = hdus[0][1].data +# detector_order = [2, 1, 4, 3, 6, 5] +detector_order = [1, 2, 3, 4, 5, 6] +plt.figure(figsize=(20, 20)) +for plot_number, hdu_number in enumerate(detector_order, 1): + plt.subplot(3, 2, plot_number) + plt.imshow(hdus[0][hdu_number].data, norm=LogNorm(), cmap="hot") + plt.colorbar() + +plt.show() diff --git a/DREAMS/Test_codes/Lc.py b/DREAMS/Test_codes/Lc.py new file mode 100644 index 00000000..3e37bb18 --- /dev/null +++ b/DREAMS/Test_codes/Lc.py @@ -0,0 +1,54 @@ +#cluster in the LMC +import os +import pytest +import numpy as np +from astropy.io.fits import HDUList +from matplotlib import pyplot as plt +from matplotlib.colors import LogNorm +import scopesim +import synphot +from scopesim import Source +from astropy.io import fits + + +from scopesim import rc +from scopesim.source.source_templates import star_field +import scopesim_templates as sim_tp +from scopesim_templates.stellar import cluster + +from scopesim.optics.fov_manager import FOVManager + +PLOTS = True + +if rc.__config__["!SIM.tests.run_integration_tests"] is False: + pytestmark = pytest.mark.skip("Ignoring DREAMS integration tests") + +cmds = scopesim.UserCommands(use_instrument="DREAMS") +cmds["!OBS.dit"] = 1000 +cmds["!OBS.ndit"] = 1000 +cmds["!DET.bin_size"] = 1 +cmds["!OBS.sky.bg_mag"] = 14.9 +cmds["!OBS.sky.filter_name"] = "J" +cmds["SIM.sub_pixel.flag"] = True +dreams = scopesim.OpticalTrain(cmds) +dreams["detector_linearity"].include = False + +print("scopesim package loaded successfully.") +src = cluster(mass=1000, distance=50000, core_radius=500, seed=9002) + +dreams.observe(src) +print("yessss anjali") +hdus = dreams.readout() +dreams.readout(filename="Lc.fits") +#plt.subplot(121) +#wave = np.arange(3000, 11000) +#plt.plot(wave, dreams.optics_manager.system_transmission(wave)) +plt.subplot(122) +im = hdus[0][1].data +plt.imshow(im, norm=LogNorm()) +plt.colorbar() +plt.title("Observed Star Field") +plt.xlabel("X Pixels") +plt.ylabel("Y Pixels") +plt.grid() +plt.show() diff --git a/DREAMS/Test_codes/cluster.py b/DREAMS/Test_codes/cluster.py new file mode 100644 index 00000000..e238512e --- /dev/null +++ b/DREAMS/Test_codes/cluster.py @@ -0,0 +1,118 @@ +import os +import pytest +import numpy as np +from astropy.io.fits import HDUList +from matplotlib import pyplot as plt +from matplotlib.colors import LogNorm +import scopesim + +from scopesim import rc +from scopesim.source.source_templates import star_field +import scopesim_templates as sim_tp + +PLOTS = True + +if rc.__config__["!SIM.tests.run_integration_tests"] is False: + pytestmark = pytest.mark.skip("Ignoring DREAMS integration tests") + + +class TestLoads: + def test_scopesim_loads_package(self): + dreams = scopesim.OpticalTrain("DREAMS") + assert isinstance(dreams, scopesim.OpticalTrain) # Corrected syntax + print("scopesim package loaded successfully.") + + +class TestObserves: + def test_something_comes_out(self): + print("Starting observation test...") + + # Setting the width to 10000 arcsec makes the field fill the image. + # A with of 700 works as well, but covers only a fraction of the + # middle two detectors. + src = star_field(10000, 10, 20, width=10000) + + cmds = scopesim.UserCommands(use_instrument="DREAMS") + cmds["!OBS.dit"] = 8 + cmds["!DET.bin_size"] = 1 + cmds["!OBS.sky.bg_mag"] = 14.9 + cmds["!OBS.sky.filter_name"] = "J" + cmds["SIM.sub_pixel.flag"] = True + + dreams = scopesim.OpticalTrain(cmds) + dreams["detector_linearity"].include = False + + dreams.observe(src) + + hdus = dreams.readout("dreams.fits") + + print(f"Observation completed. HDUList type: {type(hdus[0])}") + + if PLOTS: + plt.subplot(121) + wave = np.arange(3000, 11000) + plt.plot(wave, dreams.optics_manager.system_transmission(wave)) + + plt.subplot(122) + im = hdus[0][1].data + plt.imshow(im, norm=LogNorm()) + plt.colorbar() + plt.title("Observed Star Field") + plt.xlabel("X Pixels") + plt.ylabel("Y Pixels") + plt.grid() + plt.show() + + detector_order = [2, 1, 4, 3, 6, 5] + plt.figure(figsize=(20, 20)) + for plot_number, hdu_number in enumerate(detector_order, 1): + plt.subplot(3, 2, plot_number) + data = hdus[0][hdu_number].data + med = np.median(data) + std = np.std(data) + vmin = med + vmax = med + 5 * std + plt.imshow(data, origin="lower", norm=LogNorm(vmin=vmin, vmax=vmax)) + plt.colorbar() + plt.show() + + @pytest.mark.slow + def test_observes_from_scopesim_templates(self): + print("Starting scopesim templates observation test...") + src = sim_tp.stellar.cluster(mass=10000, distance=2000, core_radius=1) + + dreams = scopesim.OpticalTrain("DREAMS") + dreams.observe(src) + + dreams.cmds["!OBS.dit"] = 10 + hdus = dreams.readout() + + assert isinstance(hdus[0], HDUList) + print("Observation from scopesim templates completed.") + + if PLOTS: + im = hdus[0][1].data + plt.imshow(im, norm=LogNorm(), cmap="hot") + plt.colorbar() + plt.show() + + @pytest.mark.slow + def test_saves_readout_to_disc(self): + print("Starting test to save readout to disk...") + src = sim_tp.stellar.cluster(mass=10000, distance=2000, core_radius=1) + dreams = scopesim.OpticalTrain("DREAMS") + dreams.observe(src) + dreams.readout(filename="GNANU.fits") + + assert os.path.exists("GNANU.fits") + print("Readout saved to GNANU.fits.") + + +def run_test_and_plot(): + test_observes = TestObserves() + test_observes.test_something_comes_out() + + +# Run the test and plot as soon as the module is imported +if __name__ == '__main__': + run_test_and_plot() diff --git a/DREAMS/Test_codes/ellip.py b/DREAMS/Test_codes/ellip.py new file mode 100644 index 00000000..7004683b --- /dev/null +++ b/DREAMS/Test_codes/ellip.py @@ -0,0 +1,55 @@ +#Elliptical Galaxy +import os +import pytest +import numpy as np +from astropy.io.fits import HDUList +from matplotlib import pyplot as plt +from matplotlib.colors import LogNorm +import scopesim +import synphot +from scopesim_templates.extragalactic.galaxies import elliptical +from astropy.io import fits + + +from scopesim import rc +from scopesim.source.source_templates import star_field +import scopesim_templates as sim_tp +from scopesim.optics.fov_manager import FOVManager + +PLOTS = True + +if rc.__config__["!SIM.tests.run_integration_tests"] is False: + pytestmark = pytest.mark.skip("Ignoring DREAMS integration tests") + +cmds = scopesim.UserCommands(use_instrument="DREAMS") +cmds["!OBS.dit"] = 1000 +cmds["!OBS.ndit"] = 1000 +cmds["!DET.bin_size"] = 1 +cmds["!OBS.sky.bg_mag"] = 14.9 +cmds["!OBS.sky.filter_name"] = "J" +cmds["SIM.sub_pixel.flag"] = True +dreams = scopesim.OpticalTrain(cmds) +dreams["detector_linearity"].include = False + +print("scopesim package loaded successfully.") +src = elliptical(half_light_radius=11500, pixel_scale=2.48, filter_name="J", amplitude=17, normalization="total", n=4, ellipticity=0.5, angle=30) +dreams.observe(src) +hdus = dreams.readout() +dreams.readout(filename="ellip.fits") +plt.subplot(122) +im = hdus[0][1].data +plt.imshow(im, norm=LogNorm()) +plt.colorbar() +plt.title("Observed Galaxy Field") +plt.xlabel("X Pixels") +plt.ylabel("Y Pixels") + +detector_order = [2, 1, 4, 3, 6, 5] +plt.figure(figsize=(20, 20)) +for plot_number, hdu_number in enumerate(detector_order, 1): + plt.subplot(3, 2, plot_number) + plt.imshow(np.log10(src.fields[0].data), origin="lower") + plt.colorbar() + plt.title(f"HDU {hdu_number}") + +plt.show() diff --git a/DREAMS/Test_codes/field.ipynb b/DREAMS/Test_codes/field.ipynb new file mode 100644 index 00000000..f082fb55 --- /dev/null +++ b/DREAMS/Test_codes/field.ipynb @@ -0,0 +1,624 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "LKOlMK9pT1wu", + "outputId": "892bca39-8580-4249-8579-7a5161b33618" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Requirement already satisfied: scopesim_templates in /usr/local/lib/python3.10/dist-packages (0.5.2)\n", + "Requirement already satisfied: numpy>=1.26.3 in /usr/local/lib/python3.10/dist-packages (from scopesim_templates) (1.26.4)\n", + "Requirement already satisfied: scipy>=1.11.4 in /usr/local/lib/python3.10/dist-packages (from scopesim_templates) (1.13.1)\n", + "Requirement already satisfied: astropy>=5.3.3 in /usr/local/lib/python3.10/dist-packages (from scopesim_templates) (5.3.4)\n", + 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"base_uri": "https://localhost:8080/" + }, + "id": "Mczzz3KcUzL0", + "outputId": "0748f1e7-7361-4346-cc74-00e3cc967baa" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\u001b[32mimf - sample_imf: Setting maximum allowed mass to 1000\u001b[0m\n", + "\u001b[32mimf - sample_imf: Loop 0 added 1.09e+03 Msun to previous total of 0.00e+00 Msun\u001b[0m\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Downloading file 'filter_systems/etc/index.yml' from 'https://scopesim.univie.ac.at/spextra/database/filter_systems/etc/index.yml' to '/root/.spextra_cache'.\n", + "100%|██████████████████████████████████████████| 609/609 [00:00<00:00, 135kB/s]\n", + "Downloading file 'filter_systems/etc/V.dat' from 'https://scopesim.univie.ac.at/spextra/database/filter_systems/etc/V.dat' to '/root/.spextra_cache'.\n", + "100%|██████████████████████████████████████| 3.18k/3.18k [00:00<00:00, 804kB/s]\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "src.fields\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "hQvqPUhqVjUZ", + "outputId": "583b2ac8-7abe-40a5-bbeb-182ba3bede4e" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "[\n", + " x y ... masses spec_types\n", + " arcsec arcsec ... solMass \n", + " float64 float64 ... float64 str7 \n", + " ------------------- -------------------- ... -------------------- ----------\n", + " 0.7047941071430335 -0.34193400839906835 ... 0.023450818028910993 M6V\n", + " 3.017163801660643 -1.531947677274888 ... 0.5030213194041789 M1V\n", + " 5.545342770168751 -0.5059378004225308 ... 0.6887993545486397 K5V\n", + " 0.04337484405135695 0.47394950595035895 ... 0.16592467519086804 M5V\n", + " -0.1695198026107141 2.689008599028229 ... 0.4981528843145076 M1V\n", + " 2.903227971744357 -0.42880293404815345 ... 0.030385458123976427 M6V\n", + " 2.9147725521817955 1.4290979035892837 ... 0.12048133658240405 M5V\n", + " 2.1879322601012166 1.7393082707150282 ... 0.33768446357534043 M3V\n", + " -0.5711617098260228 -5.393018142881724 ... 0.8167460590486888 K2V\n", + " ... ... ... ... ...\n", + " 1.4678772515789662 -0.17251949373959752 ... 0.6961978840502374 K5V\n", + " -2.9862656254225963 0.5421006937620638 ... 0.12278256100621125 M5V\n", + " 3.157740384424968 3.0596228361838076 ... 1.1792543689064683 F8V\n", + " 2.358628131504372 -1.557299020469622 ... 0.012963210764621674 M6V\n", + " 1.4521739653435157 -0.851382522869428 ... 0.117485467623293 M6V\n", + " -0.4565704589836154 0.18085670454520986 ... 0.26443896759352503 M3V\n", + " -4.2880207051930626 4.243801810096584 ... 0.48208630286109483 M1V\n", + " -1.0717398664268987 3.7082294509014195 ... 0.08623356844839875 M6V\n", + " 2.1224836756915306 1.1488760649099696 ... 0.05865254767345462 M6V\n", + " -4.886571147953505 1.7463696161882218 ... 0.3244795598952535 M3V]" + ] + }, + "metadata": {}, + "execution_count": 11 + } + ] + }, + { + "cell_type": "code", + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.plot(src.fields[0][\"x\"], src.fields[0][\"y\"], '.')\n", + "plt.xlabel(\"X [arcsec]\")\n", + "plt.ylabel(\"Y [arcsec]\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 714 + }, + "id": "EimFNanwVrDD", + "outputId": "75ba5c44-4072-4889-bb18-6f94171222c7" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Text(0, 0.5, 'Y [arcsec]')" + ] + }, + "metadata": {}, + "execution_count": 12 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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C/5koi6FMSCxefVC7LTJRyJOKxQwS/QwRXSSLqw/RfSChS6QUiRZdscLpuhIZVZ/oLcZobznrukKI1z35+v7Y+OFp5fZ9fVMrRG2YqMlbJiQCAF6rbcATU4e7/l4mCnlSUSBSZorkgRYdRLwhoUukDIkWXbFC57oSkWczGfwaE2H9kV33hg9Ph/4u64dkmrxZ8JjIitqjmFtR5NpvoijkfXRTWSAmQ67adF2oe4EWHUS8IaFLpATJILpigZfrineezWTYYkyEgHTbugeC/bD+QCOmjsgP3ZdkmbxVvsEBE9r3jonC17bVY/mWepgADANYWDUspReXicxVm64L9XBIhkUH0X2gYDQiJUjXYJJkvi4mMnnibaWMZRCZCtl1y3h6/SFLoNescYNQWz0JKx+8GbXVkxIiYtjCSUY4927F1vqQS4ZpAs9sPBL3oKFIAxGTAQrAspPvz8L4kj5xE7npMI6I8CCLLpESJNPWcDRJ5utKFitlvK0/4nU7IVrgE13dSmWN9hnwfO+SwaKfLlbQZOjL7ky6jCMiPEjoEilBsoiuaJPs15UsW4zxFpD8dR/4/Bye2XQk6K9qBC2bPMkkWKQ5fQGsXTAB5YW5ER8r3tk+0sVdKdF92Z1Jp3FEhAcJXSJlSBbRFW2S/boSbaVMFOy6x5f0wbSRBWhouojsTB9mvLg9aQWLauHkVeQ6HSudAxFjRaL7sjuTTuOICA8SukRKka6iK12vK13g70+yC5ZoLpwSuQiLlxU0XpkQkn1Bm66QNZ0wTNPFCa2bcf78efj9frS0tKBXr16Jbg5BEElIY0sbCZY4sGrXcduiIpq+leS72T2I9TgiEoOuXiOhK0BClyC6F5Tb1Eqy9UesFhWNLW2YWLPZZumrrZ6UFNdNRBdanKYfunqNXBcIgkhJoiHIyKJnJRn7I1ZuPeS72b0g97DuC+XRJQgi5Vi16zgm1mzGnOU7LLlsvUC5Ta10t/5IhjzRBEHEHhK6BNHNkSVST+bk6m6CTLftiSjWkWz9yrcnFv2RbNfLk4hiJARBxB9yXSDSkmTzM/RKvNov26oGkHTb1zxOgmzLJ2e02x7vaOxYugWEM17E9iyaXBrV/khGNwgRyoRAEOkPBaMJUDBa6pMKE6wT8Wq/LBjHBwASsZNMATqqIKI1C8ZLc9w6tT2RfR2tfg3nGlTtWVg1DM9sPBJxdDoFehEEEWt09Rq5LhAph9N2qI6fYbJtp/LtiaefpMwyGgDivp3vFdWWc2t7R1htZ0v9WC75Y+UmEe54UbVnxIDeqK2ehJUP3oza6klhi/5EuIUQBEHIINcFIqVws165RVInm7VXbM8DFcVxiwRXlYuVWXSTLUBHtuXc2NLmaeudiUT2dROxKw0aKzeJcDMHOLUnGtHp0bzeVHdDIggisZBFl0gZdKxXTpHUyRZVLmvPq7X1EJofM6EpWkZ9ABZVlaZMgA4rz8vaxq6H3X+fAce2x9PqGKvAp3AzB8Q6ECtax49Gdo3uQrLtVBFEskAWXSJl0LFeOdWU317XlFR5M6WuAybwUGUxXt3aEJcSs7PGDcK5tm9Rs/EwAiawdNNhLJlZhtrqSSkboKPrihDvYLRYBD6pxjsAbK9rcrSCsvbsbmgGDGDM4NyI2yM7frjXq1qYxsLingxEYrlOtp0qgkgmSOgSKYOuMFFNsMlW81zVnrkTizF3YnFchGZjSxuWbjwcEoVMTNRWT8L4kj4xO28skLkiLF5zENmZGRhblGfrR6dFUayIRdJ6cbxv+eRMKBDMTfR4yVIRDpFcb3cq6KArVGViuLstCAjCK+S6QKQMXrZDxW1tr7+PB07tkbU/FqRT0JDKQv7oyn3Kbe9Z4wZFJfgq0bDxAkDbPcerK0+8t8ZTsaBDOH2kex9UbhzxfobJRYJINciiS6QUkW6HJlvezES3J9ms3JEguxaGk5UrnUqDerGCevkub3E0ADx4SzHmVhRbrIqRBIzJfp8Ii3skhOs+oHMfnKy28XyGyUWCSEVI6BIpR6TCJNmETSLbk2piQkQUSPy1iMRz2zsc4ReN33gRPbrfFUWWCeCVrfVYUVsflQIjTuIpEQvBcO9DuO4DOvfBSQyPL+mDJTPLLH0Yi2eYXCSIVIWELkF0cxJtVQ4XlZWxtnoS9hxrxiOv7wWvDbxYueIdGKT6jVM7VL+ZMWoAVu85Gfre9FEFSvcenUWOTGQBQaGzeM1BmCZC/exV/OiIp3guBGNplVWhcx90xHCs80F3J59pIr0goUsQRNJZud1wszLOGjcIFy59F5alOpLt2XCsXqrfnLv4LZZuOixth+o3pf17Yu3ek5bjr9t7Co/fOQwAbKJZZ5Hj5hIi4kX8JJN4irVV1gm3++AkhuOVDzqd3JyI7gUJXYIgUg4nKyOb5MOxVEe6PRuOcFP9pmbjYaWlVPWbXQ3N0s9f21aPFVvrpaLZbZHDRNbi1QcREP7mM2Cx6ALexE8yiadYW2XdcLsPqvEcr8VCqrs5Ed0XEroEQaQMbCu/rf07GLAKLAY/yXu1VOsGBqncCcIRbtIKdRILKt8O1XnGFeVKj7V8S72je4GbqwYTWa/VNmBF7VEEzK4sIQDCFj/JJJ5ibZWNBP7+iGn/4rlYSFU3J6J7Q0KXIIiYEc3yrbxLgRORTPJuosHNrSEc4Sb7zcKqYVjaWcRD1g7VecoLc22BSQ9UFGP51nrLOcMpi53vz8ITU4djbkWRTeikQyaUaFplWQquaI/7aI25SEg1NyeCMEwzVq7rqcn58+fh9/vR0tKCXr16Jbo5BJGyhBNgpaKxpS1UBMEJNslHkvJo1a7jNtEwa9wg7D/RjOkvbrcE+2QYBmqrJ9muo7GlzbNwE3+jaofbeVbtOo7q1UGfTQNA9ZRSqWiurZ4EALZ+VV1TJERzwRPN46kKMEQiuqOZgks27qM55mJFtO83QcjQ1Wtk0SUIIuqEE2DlhMonV2Th5GGux9PdphdFJxOPPE6+kKbUsUKNaCnTsXSKv5EFJj2z8QgWTS7FM5uOJKQsdrRzr778h7qQ/3Ikx1O1KxKLZbRTcHnxv00WSyvl2iWSDRK6BEFIicQqoxtgtXj1QZT274nywlzH4zlF/vMs3XgY00bK02kB+pMwLxpE8cgjc5OI9kTvRTCr+n3EwN6orZ4U97LY0RZ+L2+pw5KNh0P/Dvd4scoJG+3AsGQK1tOBcu0SyQiVACYIwoaq3KgusvKtPsMePBYAMP3F7a7HZ36IrFyyigAgLX3a2NKG/9h/0lPJW4bKmiwm5o/kHDLCuQdOZXPz/fEvix3N8rSNLW2o4USul+OJZWtjVTY32mWLY31/ok06lRQn0gey6BIEYUFmldG1vDJ0A6yAYHoqHasPv5V/sf1bzPv1bptw9gGOFlYRHWubNCsCgLULJoT6I9JziIRrGQsnMCkawWAq6380LZL1Ta3SYgiye84js7BXDu0XE0tpLALDkiVYT4dUs0AT3QMSugSRIJI1YENmlWGW1xoP2/CyCbp31uXSfKxe8pWy79TcU4bqzspcQDDwask9ZVKfVZXLg84k7JThQOccPsMqxHTueyRb4OEIIzf/znAqtLHjRkv4qdxXFlWVKo+nWjDUVk+KWaYCWf9H+qwni/+tG8mULi4RJOs7vbtDQpcgEkAyB2yoBIWu5ZVHFmBV2r+nNHuBV6sPExR7jjXDNIExRbk2kfv2gVOOIld3ElaJR7dzAMF+2/LJGcwaN0j7vhf3zbHlCTbgbLnkcRJGXidjpzbrWJ6jZZEURZTPCIrc+ZUlyt/sPiYvoNHQdDGmlmy+/5P5WY8FqWSBjibd7T6nEiR0CSLOJHvABhMUkVhenSgvzEVNlKw++f4sTB1h/52TK4EPwPNzRmH04FxP5xTFo25eXxNd5Xl17ntjSxt2H2u2h6A5uydr4XUydhurTkKSXwxEy8rlRUSxTBkiYj7icNuk05dOpZpb2zvS1vKXKhboaJHs7/TuDgldgogz8SrZGQnRtLyqjh/LKlIqAcpE9dQRBTE7h6qq2TuHvnS9707i2TThOEbcBGU4k7HTWN3yyRlXIRkLK5eOiFJlyhADCMNFty9V/Td92faI06MRyUMqvNO7M5R1gSDiTLQjs2MFs7xGI+JbjHoHIM0CEA1UWRKenDoctdWToiIqVOf4yzuuwdoFE2z31wDw/Luf2b7P3/dw/YkbW9rw8/UfY8IS5wwN4UTEq8ZqdqbPVUiqxGA4GSi8oro/z80eFbP7L+tLWf8BsJVjjkefeEX2zBJyUuWd3l0hoUsQcSaVUgbNGjcItdWTsPLBm8MWiZGmKvOKatKZMiI/an2sEjDPvfMZDp/+2nJ/2dfEjAE+WK2LTkUxVGOE9e0rW+tdxVM4k7FqrLa2d7gKyUSmmlJd65givawh4R5f7Eux/2RjJhnTb8X7mU11Uumd3h0h1wWCSACx3rqPZuRvMlWK0iHcyG8v/RbyYxYssMwft7Z6EmqrJ+G12gYs33pUWvLh+TmjLC4UOZkZ0nP9/d3XY8RAP1rbO9DY0mYrZKGb0izcflFlEZClXOOFZLxTTYV8m00TY4vyYhr976Uv+f7LzvRhxovbXfskkdH75G8aHt01CC8VIKFLEAkiUgEpmwiTLfI3Ub5rXiedcPpt1rhByM7MwKMr91k+Z9dX1DcbK2rlIjfDMDB6cJcobGxpw86Gs9LznDjbhp++9ZGtbW4WYJmgDHcyFscqE3p8WWQTXdkl+O/ESmzyzwDzF2ZtMRBMPyerBhctvPQl339ufZLoZ5j8TcOnuwXhpQokdAkixVBNhLGyxERiXYqnVU9sp+6kE0m/jS3Ks6UBY9enW1HNLUPEitqj0rbJUpAxpo9Sl0GO1mRcObQfDKPLJYNZs2ORWkyE77OQawj3dxPBIifbFt+O8SV9onJOGawvmT+rzjPi1CextqbqPMtU9IFIN0joEkQK4TQRerXE6Ex60bAuzasoxoqt9Qggur5rokUv3Ha69ZtTP2355Izl3wasItatoppbhogHKorwytZ6aduOn21VXtO6vafw+J3DbCIqmtvhuuONicH9J5rx9oFTuLEoD1f1uiLstoh9psruxspBOx0/Gn0SzjOiWmzE0pqq285YW+IJIt6Q0CWIFMJpIvRiiYkkB6iudUk8x0MVQzC3oigqE6aTRc9rO536zamf3jl0GouE9FqGEbR0Au4V1QDnDBFTRuQDAFbU1lvFsgFl1gOGU9qyaG2H52RmWCy6fNtEfvLbfVi956Ttc1kBinCqxskIpzSw1z6JtgU2VtZUr+0kf1MinaCsCwSRQjhFe+tG/uqmfYokal52jhW1R/Hl+W/0L1bz2CbsVj2+nW5pklT9BkDZTz/57T488OvdtmMFOnPdMtyyVrhliGBtM7jvmCaw/kCjo9hzSlsWjZRWq3YdxwwhxzI79owXt1ui9PefaJaKXLEtupH+sj4zYK2nISsHzROtPol2ZolYRe+H085Ypf8jiHhDFl2CSCHcthV1LDG626ORWJdk5wiYwPRl21Fzj9xy1tjShg8azsIwDIxxqFqmY9HTscjyyPpte12TtJ/+6+MvlMJNlWLKyV/WbZu4cmg/i5I3AazYWi8tTMHa4Ja2LJLtcLd8v6K1UBVkx7dld0OztsVR1WdO5aBFotUnsbDARmJNVVnE08HvNtquN4nMbJFMbegOkNAliBRDZyI0lZva+pNeJL56snME2yUXMKxcqxg1LxOlsmMbCLoNBEx3i6yq/KooSFX9dObCJek1i/65urjdz/qmVtvdDCDoCvJqbX3o3iysGoYRA3rbjhFtkaOz0OBF441FeY7fzTAMQFFNbndDM+4q199al5WDlhGtPomVP6s4FiP1p091v9tou94kOrNFsrShu2CYprj51L05f/48/H4/Wlpa0KtXr0Q3hyA8IfquVleVYv6tJdLviZOe6iXb2NIWlnXJKZvAygdvDkXDN7a0YcKSzdIqW9uqb5eeU9Z+mUV2zvIdtt+yTAU+A1g0uRRlA/1KASE7T2n/nrh72Xbbd1/94RhcV+D3bKHRKd07sWazTZTVVk8CAK174+V+67RXbI8Iax9rk8pHl793smPGSgDYFlYGUBPBecJ9RnTQ9adXjRFRMKea363utSXqeOGQDG1IB3T1Gll0CSJNkPmuLtl4GDCA+ZVWscssYrsbmgEDGMPldBUJNx3VrHGDUNq/J6Yv2y5Nv8WQWSyBLn9XL8EybpZMwBq0tmTjYQBqAaE6zz2jB1iE2z2jB+CzL1sx79e7QyJaR6DpiBg3a5zOvYlmcJGsPdNHFWDd3lO29jER//idw3Df+MH4oKEZY4tycVWvK2xtWTKzDItXH0SAO1fADKYJi2axAvac8MPCMLuCCMMhVvlTdYPIvGbASCWi7XqTDHmCk6EN3QkSugSRJqi2lJduPIybi/Ns2/WRpORyg7dS1tzjvGWqygfrM2AJqBKtnm6TtijIVD6tgLtPqPjZP/7ZSItwe7/+LJZsOKx1PL6PRBGjEnXREKqq/grHT1DWnsfvHGb5t0zEP3DLEEt7xGPm9LgMj7y+1/J5AMBrtQ14Yupwz9csQ+o/DvdUZCLx8K+Mhz99shPta0uGvkqGNnQn0irrwt/+7d/CMAzL/0pLSxPdLIKIC0wwirAgMD6aPRaR+Awxeh6AY+aBfH8Wau4ps0bNdwojJph0ovFl8FkP1i6YYIvW5/EaLV9emIsHbhmCq3pdgZqNh21/dzueSnA9/85n0u/HIgreqW91slUw95PtdU0AEGpfY0sbqldbx1f1moOu42vM4FzpGF5RezQqYxNwzlyiSyRj0guqtmZn+iz3RszW4AOwcPKwtLAORjsTRawyW6RaG7oTaWfRvf766/Ff//VfoX9fdlnaXSJBSMn3Z6G6qjS0Hc/Db9dXrzmI52aPjMnWmUpA11ZPcqxQxbtSGAYwujPrQjTylPKWTN7CKxKuRaW+qdWWZgsI+gI7HU9lyX5953EM7pttczeJNk59y5fUdQoMVLle7D7WbLsu0wT2HGsOBYyprPQP3lJsK5IR6Pxtbk7kFtRIA7NiXb3Mra3TRxVgxovbbX0+a9wgnGv7FjUbDyNgAks3HUbv7MvTIsAp2nl9kyFPcDK0obuQdirwsssuQ//+/RPdDIJICPNvLQGMoLsCC0iTCY6Wtm89b52Fm8xfV0Dn+7NsEfa6x9MJ6KpvakXl0H6orZ6EhqaLOHDyHJ7ZeETpV8qO5XZsJ1/gLZ+cUQoNlagDgvdvWrm6jG8ksOv56sIlZaYDPlDLBFAtcalwEnyqGGf2sRg0+eAtxZhbUYx8fxbmVhTbimQYBvDI63s9+T87EYnIiLd/Jd/Wi+3fhvzAAWufA8FxY3oU4JG4YMQzPVa0/YuTwV85GdrQHUg7ofvpp5+ioKAAV1xxBcaPH48lS5Zg0KDUX9EShC7zK0swrbwADU0X8dmZr/Hkuo9s3+mdlSm1agHBbWhx4tJNhaPje+ZlclSJyAOfnwtZiN3apvr7+JI+oX5S+ZXOGDUAa/ee1AoWk2WYcBMacyuKsXxrvT19WKcFc/RgaPWVbp+K1ycuhDIMA81t7fbFEWBL9eUk+MYW5dmObSCY31YWNPnK1nqsqK0P9a/oW22a4Ve+UxGuyEiEf2W+PytoZZdUw2N9bsL0LMAjSXFF6bGIVCGtfHRvuukm/PM//zM2bdqEl156CfX19bjlllvw9ddfK39z6dIlnD9/3vI/gkh1mP/k94ZfbfN5ZIJDrNoFQOp36ObPu/9EM5ZvrcP+E82OvmeNLW34h/Ufe/JtzPdnYVGV3c/+mU1H0NjS5to2t7/zfq+y767ec9IWLCbzFZ01bhB+MXuk7fMO08T6A42Ofq7VkusDgIdf34sJS9z7ivcXnbBkM17+Q530e7Lrg9E1CbB7lZudKf29IQwktyp9NfeUhY7tQ9D9Id+fpQya5O8NPzZ/MXukY+W7eJMI/8pQpghJv7E+9+p7HImffix9/Aki2qSVRbeqqir03yNGjMBNN92EwYMH47e//S0eeOAB6W+WLFmCn/3sZ/FqIkHEFSY4WNomH6ylUZlVy2kb2sly939+d8SWZusf/2ykbVtYzFsqnsNJJJQN8Ns+07Viedlm1imE4JQB4NQ5eXnjp9cfws83HFJavER3Ex43K6aXlHKy6zNN4IU5o5CX0yN0rxpb2uzW2E6/aR43X1eWXm5XQzPGFeWivDD4e5WVHrDeG35sJluEerz9K1Vj0wdrkRIvvseRuGBEy6WIIOJBWgldkd69e2Po0KH47DN5FDMALF68GI899ljo3+fPn0dhYWE8mkcQcSHSssCqrdqL7d/aigCs3nMS940fjPLCrhKs+08020SueA6nSVB2fh+6Ar2cRJCXbWYnAcazovYo5lYUWdq8/0SzNPMCw03Uz68sQYH/Cjy6cp/yGLK+ckopJ/r4qvpitFBuOd+fheoppSHhzbalZe0WxxbQ5fqiSl8XcvUQcuay9kRSoS8RPqMsO0Uszyl9Bgxg7YIJoQUE4E2AR+KCofNbcm0gkoW0cl0QuXDhAurq6pCfn6/8To8ePdCrVy/L/wgiHdEpC8zDb0PLtmqPNrVKj/VBQ3Pov1ftOo7pL25Xnlk1sfKprdj5+eaxQC+3bWTdbWYmkBZNLrV895Zr+9raxgpZ6F4jg99ul6XuGluU55j+TNZXxX1zpN8V2wg49wXfnlW7jluCGRdNLnUUKMz9Y8snZywuFGJ6MX5re9a4Qdi2+HY8dMuQ0DU7CVjRzUaVASIeKb8ScU7ZvVsys8wicvnv6qShi8QFw+235NpAJBNpZdF9/PHH8f3vfx+DBw/GqVOn8NOf/hQZGRm49957E900gkgY0ai+JbMU7T/RLDsdxhYFJ18nv0Ig2BbZxCprb+XQfpbIKRNdFlI3K5bb38XzLaoqxYgBvUOiUlaqky9k4XSNPOx3qvsh3gMDADoDsbz6gaqKbcj6QmwPH/hlIugPPW2kcwYImQuFiGiRzvdn4YmpwzG3okjLAukUPBbPlF865wT0ggi9EAt3iUiO6fRbqvxFJBNpJXQ///xz3Hvvvfjqq6/Qr18/VFRU4P3330e/fuGXdiSIVCaa1bdEoVFemCsthcusTKptdQPAg5XFmDuxWGpZlYmHWeMG2sSkzJ9ThervsvM9s/GIpea80wLAyXdyxugBtrK4ABwFmcwVQHY/mHg929ouvd55FUOkIpYX1Y0tbfiP/SftAWoCOgJFx78ZALIz7ZuI0UixlAhhpTrna9vqsWJrfUy27GORjiqSY6p+S5W/iGQirYTuG2+8kegmEN2QZA64UFXfUgVUeZ30xFK4/Faqrl+hW3s7TBOv7zxh+y5vtQwXHYHktABwu0axLO72uibX84n3wMkCrfJ0mFtR5FoQQpYOTYaOQNH1b77YLnrlRodECCvVvV++pT7qqdBSDS9+1QQRa9LaR5cgYo3oo/fyljrHsqnxRlUWePnWo3j7wKmotJOVwhXFqxe/Qr69op+qym+VWS0jQTclk8rv0e0axd9FWn5Wx0WAHV4l4vcca3YUuQaXcsxnAPdXFLm2S+wHH+wiPJbCMxEpv2TnfKCiOKlSoSUSHb9qgogHhqkqYdNNOX/+PPx+P1paWigwrRvixTrb2NJm899kxDrK2Es7f77+Y2n1LSA+0dCNLW2efABX7TpusQQtrBpmS73lA7Bt8e1RETLi+X4+8wbP/eHlGiM53/a6JsxZvsP1eysfvBlFfbNt49MH4G/vvg5Pvfmx9HesPZVD++G1bfUh66TuOOH7YcsnZyLuV680trRhz7FmBEwTY4vy4mJB5K8ZkPt0864wqUgy71oR3RddvUZCV4CEbvfFazocN9ERqwnOazudBHks2xkJonC0id/Jw1A20B+1iderGI/W+bIzfWht79C+Drd7CQTHxLbq2239xv+dDzgDggL4+TmjQqnGZOfxOk72n2jGfx36Alf3ugJ3DL86Lv0az5RWKvEXjYVTMpGMacJIeBOAvl5LKx9dggiXcKK23fwSYxEME047RX+5eLQzUkQ/Vd5P9sDJc7Ycr+FYYNlECXiLkA9nkhV/k+/PUuaZdULm+zh9VAHW7D0ZCtYzzWDqtVnjBoWKNkx/cXvo78y314egvzYTY1NHFITOE2lw109+u88SpLj3+Dn845+NdO+oCIh25gWn++wk/uJdTCKWJCKbhRvJKLyJ5IaELkEgvIndTUDGwicxXAHCJt/dDc348Rt7Yx60Ew2LCztGTmZGyOpZ1DcbP1jxfkQTLz9RAl1Zy3QmTd1Jlr9+maCtHNovbAEhy8ywhhOVfOq1fH8WWts7bBkrTAD33lSI748YYKmIxtocSXDX/hPNjoVEvKI7llTPxu6GZuRd6W0sOt1nHfEXi+wIiSCZ0oQ1trRh9zFr8ZlkEN5E8kNCl0hrdCfJcCd2i6Xx83N4ZtORmEYZRyJA8v1ZuKs8C63t38U0GjoaFhdRjALBYz1QURzRxCuKFMBaZnfxGnnqNdlvVd93ykvLJuZf3DsyouvghdT2uiZlAFS+P0u58/DGjhN49PZrlWnIwq1GtrPhrLTNHzQ0exa6XsYSC7wU+4It7Lz4GTsJ2WQSf5Hi9n5MljRhsvcBI1X7nogfJHSJtMXLJBlJOhwmOsaX9MG0kQVR3bKUbXlHmrYnllur0djqlIlRdqxXa+ttYsYHeX5WGW75XgMm8Nq2ejwx5Tqt34rfl12/SEen8tUVEI0tbfig4SwMw8AYoVwv4C5G8v1ZeKCiGMuFgMQAuqqnye5ZbfUk1FZPchwnsmfsxqI8+0Wjq5CILtHaNvf6ezchq0orpjsGk4VoFJKJB6r3AYPy8xJukNAl0pJwJsloCMBoblmqJqJEtDPS7WOZxUV1TCcxGjCBhyqL8erWhpC7SADAjBe3a1nrcjIzHP8OACu21EuLWagso/z3dQonZBgGxhTlagmIVbuOY9Hqg6F/GwCqp5RifmVJ6DOVGAGC1t7ivjm4v6IYK7bWWxYITCA43TOnUrKqZ6y2epJjIRHVsXYfa4bJZUvwajmtb2rVLsMcye6OzGUpYOqPwUTj1QUg0T7HTs8U5ecldCChS6Ql4W4vJotvnZtQj2c7vW4f61gqnY7pFOSXYRiYO7EYU8vybQFWOta61vYO1+tllk5Zzlw3y+hXFy7Z2m4YgGFaA7/y/fYqaLKFAC9ygaAle8mGw4AJzL+1S+yKx9ryyZlQ1gTWvzX3qIV1ONvTTs+YUyERkVW7jltElwGg5p6gH7OXdukUrdC5Lh0rZijIb9n2pPMX1Q2iE3F6P4rvm3hmPVBZ0J+bPQpjiuw7HAQhklp7LUTUaWxpS6oCB9Ei0sT8icZJRMST/SeaUS0R3KrxwkSCU+J+lYhnxxSPweCPJQuw0ukf2bgQcRon91cUSwshHPj8HCYs2YxHV+4LZjUwuv5WM7MM2xbfLk2cz1xeZJP1BwpfVwBYuvGw7R6wYwHqMsOyBP4690yGqi8PnDwHQF1IhIeNBf5WmgiWqQZga9fCycNQ39QqHX+y67hn9ICwikjoFDtobe+IeXEI1ftZ9blYwGbVruOW30TDBcDpHLFAdl+XzCzDXeUFJHIJLcii241J5zQtyeBbxiPbmnUiEUEgopVGtLQx3CzjbpZKr2V3szN9uNgesBwr3P5h42Lx6oOQFaP1GZCOE75vRMvowqphqNlw2CrWTGAZl5eWndsL5y5+q/ybyuoMOPevKKrZdTER7GV7Ot+fhUWTS7Fk42HL589sPIJpmiJEtS3Nrs9rWjnZ2BPLMOvitmsS62dU9X5WfR5OEB3fbp33Y6LSjSXSfYJy9qY+JHS7KcmYHzHaJNq3jKHamuUn6VgEnXltIz95LppciqWbDkt9HnUFpaqtugKB/V42yUTSP7LcskBwe2vtggk2C6Stb6pK8Yt7RwImMKYoFx80nJX2k2k6i1u3Lean3vxI+VuvW/he3Ud0KRvot33mJQpe5W7gAyw+sQC00srJ+jRWbj6xfEZV7+fS/j2V7+1wg+i8uAAkMuNEItzK0tkY1J0godtNSacUOU4k2ufWaWuWTdKxDDrz0kZ+8ly68bDU4gkA00dFtmWoKxDcJplI+qe8MBc1kjaIIlfWN0s2BC2YrE05PeSvUUOyra9zbbIxw+MmqHT6N1oL3Uitmqyt1WsOhhYdBoAl95S5BiiK76tEiBLVGIzUCqi63l0Nzcp+8BpEx8bFXeUF0CVZ0o3Fg+5gDOoukNDtpnSnF1YicduaBdT+lPEKOpOmzUJQqMkKhK/bewqP3zksonbpBGLpTDKR9I+OUHbLAPHEmg+xZsF4W8ozwwBGD5b7poa7xfw/7xyK0YPytER9NNxHdPBi1VSJP9bWPceaYXZaycXfu72vEilKxDEYDcGtut5xRbnKftANootk8ZxsLmGxpLsYg7oDJHS7Ken4wkpGXyq3rdl4vEzDTQq/sGpYyCcyVu0zFXbLeE0y4fhhim06cbYN995YiNd3ngDQJW5Uxw1nixkA/vH3n2DJzLJQwFkk1xbNha6OeHITf/n+LEwd4ZwNxel99VptfVKIElVRkezMDC3ffIbqessLndPS6dyLSBfPyeISFmvIGJQ+kNDtxqTTC8urFSVeolhnazaWyecjSQo/a9wg3FycZ0mhBET+sm9sacOvauvxaqc4YRXP7q/oyl2rm5Q/3Puo+zuxb0QMAI+u3Gvpn0VVpY5jT3eLWQyYi6aVMtoLXSfxJBV/q9UV6FQ4uQmIKd+A4HiJtyhRFRV5dOU+z9Zd1fW6vbfjsQuUaJeweJCOxqDuimGass3J7sv58+fh9/vR0tKCXr16Jbo5hAaNLW2hnKGMDMNAbfWksKxLsWqjamt21a7jNiEVjXZ57ZfGljbp5Mm3jxfB4aDK5ADYg/Tc+sXNz5UXsvy/t3xyRuv+878BYCvz7EPQXUG8Fh+AbYtvd5wQdfr0r97Yg3X7Gm2/XfngzVpWXR0xr7rn0WR7XRPmLN9h+/yhW4bgianDk/74XpA9czxOz1+8SNTOl+y8ybgLJxKPZ4QID129RhbdbkwqvGR08FqNKxG+fE5bs5VD++Fvp12HJ7ko+2i0y+v2v8pKEy3Lv1uQlQnrNTsl5XeKPheF7IxRA7B278lgflvuXOLv+Ot6eUsdajYehimIYb7M83/sPxlyV+BxSv3F4P1SA50p53he3lInFbm6VkrdxVw8LHPFfXNsPswAsKL2KOZWFEV8fqn1H8DciiIA8X3Pue0AJNrHM1FZBGTnBRC1tsTyHncH63W6Q0K3m5JOaVO8+FIlW4BBuJWKdIimj1k0XvY65XHFa1Yl5f9/H3wuvY+7G5ptApgvRSs7vXjOl/9QZ8kNKwsQBCAVuUCX/7WTVTnfn6W0LDe2tKFGyE3LqLimr3TxJp4nGq4C0SLfn4UHbynGK2JFOdO6IAhXrDhtMUfyngu3Pfwi5pHX90bV7ScSGlvabGV/q9fEflyo/JZN033BqUM6zWVEbCCh2w1JlbQp4fpROvlSxTrAwMvkGK1KRU7tWDS5NLTVzvdLIqz54ZRoVf3mX3fYqzFlGAbgcnwZBuf7qxKZohh2qlq2aEqpo1WZ5eLlA/3EfKgqh7Laz4LVsFg7ZJN8YV62NIvGa7UNcd/KZ8ytKMYKIWCMv9eyXMVlA/za41O26xDJey5S8cR2cC5c+s6Tj2csfc6f3/ypbaFnmsCeY82OgYCRovJbFglnYZ8qcxmRWEjodkOSzaopw+tEo7u9HssAA69tjkalIp12LKoqxYgBvUP9kigLiNj3PgAV1/ZF7adNCEB+zW5bwQz22zGD7emXRET3BdMEpi/bjpp7giJR9lPRZeCdQ18qj1/TmWeXt1bxVuWACVslNcCaD1W21c9+y55T1ST/yn2jpe2KlqtAODg9dzq5inXGp7jrEO57LpriyYvbj85zKRO0ur97fYd8ByLcKB1dUa4KLOUtukB4C/tUmMuIxENCtxuS7GlTwp1o2N+CpXbPKtP5xCLbRDhtjkalIp12PLPxSCgAJtEWEJXlzelesN+sP9CIp9cfsv39yanDMWVEfui3oqCaPqoA6/ae6irZO3mYzWprIri9v/bhCVKhvKiq1LLFvm7fKeU16ugG2Xd0nkH+O6pJvr4zP7OI6CrAIwbefdBwFoZhYMxg7+PQLV+ueK91chXLxqeb0MrJzJAe0y2jSTTEk6zSodv33Z5LmaCtHNpP63mub2qVntdAMDjWK14Wy6pFDoCIDQ7JPpcRyQEJ3W5IsqdNCXei0Sm1y4h2gEE4bVbdBy+Viry2Q6edsXZrEPte514Et4Lz8fMNh2yTGi9yAbmgevzOYaF/1ze1yq2lAC62B2xW50VVpZhfWRL6nko0RAL/DG6va1JalfnnVDXJFysmeVUgGy9abIUvoH6GZOjkyxXvtU6uYvE5Uom+4CI3GNzX2t4hPd7F9oDjGFe158DJc1rZLvj3kG7/uT2XKiH87OxyrfeO6pqquQWcLuEsliuH9rOUzWbfi9TgkOxzGZEckNDtpiRzDt1wVuk6pXZjSbiWhWjfB7d2uP09Wm4NsRDLXiY1lZhubGnDVxcuSau+sSCy8SV9HO+Jjq8xD7Mqr91zUlpWWbRIq46/4LYSm2iUWa8f/M1u2zkMRRELUbTYfDgRDBzSeYYi2Ylxck8RnyPZeapXH7S030BQxMnG+oGT5/CDFe87ivFFk0stAYlAcGdkWrlz+Wsx4MtEsG1ufaDKHPFV66XQsyQTtD7D0Hrv2NyGDPsCThevi3qnd0o0DA7JPJcRyQEJ3W5MtK2a0SKcVbpbqd1YX2cklgWv98FJRLq1w6uvpK7I4YmlD3Akk5poueStl6yIBxDMy5qTmaGs2iYTDeOKcrGjvtn23SenDsfYoly0tndgSll/zPv1blupYNEirRJaL713FD+4ebDSep2d6cOMF7dbngMDwN9Pvx53DL9a2lc6mTCcXB6ArvH41YVLYW/589fB5yrmt7nfPnAKLO27eB6ZQF+68TAWTSnFMxuPWNxWVEGAfBu/unDJ1kanlIXsefyg4ay0LbsbmnFXub7YZ2Pzkdf3hkSpTNCOHuxcKY1vY2FeNtYsGI+L7QFkZ/rQ2t5hCWzUxcuiPl6uUsk6lxHJAQldIinxKmjcSu3Gg3hYFnREpFs7vPhKBkzgtW31eGLKdaHPnIR2PCY21aTmpV0mgmPj76dfj95ZmRhTlIstn5yxJfvX7WMA0uIc3wXMkPj0GRLfXIXILBvot30mE1qiyJIJwJJ+PT35iYv4DKDpwjdSUSSOR9H1wYu/JLuv40v64OYhedjV0IxxRbk4fPprTFiy2bIoUQXr8QQAjBjQG7XVkyxuKzquO7qV1sTrn32jfEH36Zdfu4pKNqZ2NzTjx2/stfnZqzKouD3vYhvFDCDhZJTQXdRTsBiRDJDQJZIWL6t09vKVldoFgla6eCWMj9U5vIhIt3Z48ZVcsaUecycGy/O6CW3VxOZm0YqUcNoVQFAEji/po0z15qWPxcl/YZXdeihiQm4tVQUq8oJTtFDLkG37i0FSMksiw0DQxUNWwlY2Hg0D8JlQZtHQQbyXYnQ++28fgudRVagDgAOfB/1q+Ta4WSNVPtxTbsi3/Ft2/W/stKe9A4BfvPMZnt/8mauozPdnIe9K+TM0YqBVtOv4ucvaKGYACWchqruop2AxIhkgoUukDXyidlZql7fSpXoy8VhbR/L9WXigothmzWLuHwBchbZKLP/4jb1obf8uVBAhkqh+EZ0FgNuE67SFz4R63pXOPsfi5C+zsIqoJn2ZAA1wglPMwys7jQ/W4DXVYkAMFAKCW+3n2trx5LqPlEn9ZX1mmsALc0YhL6eH666GzAK//0SzZbHq1H/Pc+fZ8skZaWnpZzYdwbSRXX61OtZI1Rh++2AjNnzYGOo31Q7IQ5XFWLG1Xvo3HVHpNFa9LqTDKdKii05bKFiMSAZI6BJpRb6/q9RuolNpRZt4WEfurwhO0rLtZx2hzSa2xasPWgKvWN+fu/htsLRu5+deo/pleGmXasJVpaJibWRbyTqplHhrq+1YBmBoWjxnjRtk6y8g2Je8yFUx+6ZCR+srux9LNx0OWWOrOwOU7iqXZ3/g+1U1HkdrLF5UJWFlYlWGD7CcZ9a4QcjOzMCjK/fZ2ivuJrhZI52C4/h3iOr6504sxtyJxXj67UNYf9BaxllHVKrGKuB9ZyqcIi3RhoLFiERDQpdIW9LNPywe1pF8fxZq7lGfw7a1LfFbnDVuEHJ6XIZHXt9r+bzDNG0BVibcA97cMjjobPOzdqkmXFUqKuYS4GWxpHKD8KErDZZq0hfz2S7dZC8swdrh5qf6xo4TePT2a5XW1w7TtIho0+ws1GAC828tUQq57ExfKGBv4jV9sfXTptDfJ1zjnn5LVaIYMh9mwJYhg7kk8T619U2tGJSXLRV1j67ci5MtbZYMA27WSKfczR2mifUHGjF1RL5jYOfGDxttxzXgnseXPz8bJ+HuTMneGWJe6XhYWClYjEgkJHSJtCUd/cPiYR3xdA6F0pJVKFNZlpyi+nWC70JWZM5flW3zixZj1YSrSu/0s7uvx5NvfmT5LlssAZAK8Ndq7dvWAPDI7SUhgSwTuK/V1mN5pzXdZwDzKoqVljiWQYAFJ8lEL59xRLUYkB1/6cbDoe1+mUgSMzvwbP20CROWbHa00qv8pWVjic+Ry7skqdwxZowaYEvjZsIq4HUJ7g7ZczcDwNPrD+HnGw5hycwyqd+symXABDDjxe1aQpWNk0h3ptzySpMAJdId96UlQaQobKLOMIJ2uUitF40tbdhe14TGlrZoNtMzLDI9lhOU7ByyIB0WTCX7/ZKZZfB1mkR9RjAPrCxoSlXIQDXBq/qfWf3EwKXq1Qctv5HdR9lYWXJPGb533dWha2BkGAYOfH4OE2s2Y87yHZhYsxmrdh0PHVsWsQ8Az22us3yXsWrXcUys2YxXOJeRgAms2Fov7y8EfW/n31qC2upJWPngzVj38ATbd/lFnez6FlWVwpCcgPfJnjVuEGqrJ2HZnFH427uvw5o9J11dJkw43ycmusVrkn22dsEEzBo3qFN0FuAuLo+tbHys23sKP7v7eul5l248jMaWNk/PsdhvPGw8ArA9K7JrFH+n+x5x2pnyAp8uLx7vEIJIFsiiS6Q10bKAxjI3bKoQjoWcFyHL3q3DzNEDsGbPyS4fXUUhA0Df9URWLITHRFceU6f7qBorOtkUmIVNFbHP9wdvjRMLDFi+C2s2BQPAg7cMwdyKIovvMTvOg7d0BkEheG0Lq4ZZRCGfR9VyfRus7iSAtQrYlk/OSF0xnHByEXLyQRU/Ky/MVZ5DNT5yszOlBUECAJ5++xA2ftjo6Tl2c2OQXaeTn6/T72REujOlGvOxqoAY68qKBOEVErpE2hOpf1i0g9pSdSLw4iPc2NKGRautwVgmgLV7T+J/TCxCZoaBKy7PwO2lVynFjO4Ev/tYs6sIMwy9+ygbK6IAdhLgOZkZrr6zvMj5VW2943dFf2he5DJkacZYwFrvrMsBwCZ0WEq1sgF+/HD8YPz6j8csx2RVwPjfesFnIOTLKxvnqkWFl0Xpwc9bbJ9lGAbGFOWiuqpUKuD54DAvz7HKjcFJcPJZYB55fW9E+YXD9c1XBiG2fRtarEVz4U4GASIZIaFLEC5EM6gt0okg0SJZ10L+q1r59n3ABF7b1hD693ObPwtF+ovoTPCrdh23CWoZnze3ITcnM+z7KApgVWnZpUKGBJbrlYeJnMaWNryq6Cepz63El9mphG/ABBatPmhpqzTbguT8rF++arVXO9Oh4pq+lkIZKt9qmSVUV8At3WQXssyKPb+yBDBhC34U8fIchyM4WRaYC5e+iyiINNydKccgxCgt3BmqIMNUzXJDpA8kdAnChWgFtUVqGU4Wa4mbGHEScCJipL+I0wTP+lOHZzYdwZoF46NyH/P9WZgxaoAl8f6fXH+1LeWXzwB+dFsJXny3zpJOjYmc7XVNUhF5V1k+HqwstgV9yYo/vH3glKsQdc22IPkN80OuUQhFA8APJwxGrysuw3Ob62x/2/ppk8XfWDXOw124qYK9RgzoHfrvaSMLbKnZRLze/3AFp9s41umDcHamVEGWschGowoyfK22AU9MHR72cQkiUigYjSBciFZQWyRBJV4DsxKJTpJ6ERYoJEMVOOPlPB2miRNn26JyHxtb2rB270nLZ7/78LR9kjdhEblA0P2gcmg/AIqgLAP4X3cNR3lhrmNbWQDbP6x3tlgCdouttBSx0MaFVcOUqc2A4O//efsxu8g1gHm3FCvz7/KwaxAD+nQo7pvjGHwHqCucMXwGwrr/4QZyyX4XSR/onlMWhCgLsIw0G43sngDAitqjSfmeIroPZNElCA2iEdQWiWU4lXIC6ySpF+FTYUV6HjbZiqf/8Rt7lemgGDrWNZXlSgyAkrWNdz9w2woXxxyAUP5aXb9ZA0D1lFI8s/FI6Bw/um0Ilr1XZwvWCmECBf4rwnJZMEzgrhH5eFVIseYDbNboSHY3tnxyxnpe2EWr0/h4sLI4VNbaiVi4CrFjivcxWi4EIrJ3V+/sy6Oejzvfn4UHbynGK2JlRYnLDUHEExK6BKFJpEFtQDA3KouMZ7lQ65taQ8dXEY5I3n+iGTsbzuLGojxc1euKuPn2ukWcywjXhWDJzDJLyViWNxeAsjpbbfWkUEYBHtE1ZFFVKcoG+G191tb+nbQ99908GP/yx2Nd91bIzsBfJxM7lUP7OQpvNubEgDOdXvUhWFhh1rhBmFZegIamizjw+bmgpdbhACaAPx79SuMMdgIALrYHgveFyyZhIihOmatNJAs3WZYN3lLOEMehD8A8TYELxMZVyHIfJZkhYrV4Fd9dscrHPbeiGCuERU6q5y4nUh8SugQRB8RJ86GKIejTM1M78tlrIMxPfrvP4kPKiMaErWPl4ifSAyfPhSyKPgOYckM++uRk4l/eP6ZVCtfp3Hxku1hMQFWdTSYkZBZGFrXP99mqXcdRrQh++837x2Cia+t/fmUJemfZLWdv7TsV8h31GcCiyaUoG+h3vGZVwJkKnxHMQcsyWrDr/cGK9y0ixOj8P6LgWrnjBKaPzMe6ffbqXk4wUVPUN9si5ExYrZXR3t1QBeqpUqqxv6vGsTSwas1B9L0yE1mZl4W1YLTdR8mNjKcojMbCXXbMWFdvJAivkNAliBgjmzRXbD0KSKLhnbYtda0w+080S0Wu7nmc8GLlYhPp+JI+IYtidqYPre0dKO6bg7+YVOLJoqQ6N4tsF5FVZ5MJCbegLtZnfa/MVOa8BThRZwbTc91cnGcTWm/tP2XJBBDgMgOo+jMcn+eAGbSsuh3HBFBW4MfBky22z7/+Rm65XjZnFD4+dR7L3quz/W3h5GHKQDt+keEmiJxEqI5Ilo0V3orvNo5VYvqBX+8GEN6CUXUfWWaOdBGF8ajeSBBeIKFLEDFGt+SpqhjC7mPNME0TY4vytKwwOxvOOv5dZ3uUFxrsGiLxKcz3Z1kKD8iEglcLm9u5ddOT6fi7dphmSOTo0GGauHvZdgBd11rUN1uZxcDpmsLxeZYJelUE/oen7PloAeCdw2cs/s7MFWLqiAKl2B+Ym6U+lwE0XfgGjS1tFmu8KIjcRKjNJcEA7q8oCv3dbazojCW3Plfdq3AEusriHC2i6Wesc6xEp0AkCBESugQRY1QCAxpWKd6CyPxP3axINxblOf5dlqaKn5hkBQjYlny4PoVu4sJN3Lwm+P3pnlsnPVk4QVciOqLoF/eOdPSNBYLXtP5AI6aOyA+1lQk73bbygl68t6Lwf6CiyBY8xMPcK56fPcriFmIqLoR9LJ6LjZ1HV+6zWeOd7olKULL7+tq2eizfUo/lW+vxam09lswsQ2FetuNY0fEP1ulz8TdeBbpO9TcdnIQl/w7RfX+o0NnNSZYUiATBQ0KXIGKMaoID7CVP+a1bMeDGhF4C9vLCXNwzeoDUfUGWpkoMwOIDqCznj8Cn0C21mswfMjszA2M7RftyiRjzGZC6IYiTvsoKrtpKfnLqcHwXMIP94HplQQExY9QArNt7Shl812GagOksiBlPrz+En284ZCtPXNq/J6Yv267Me7tw8jCMGNg7JOjFe/tARTHuryi2BL8BsAUPiQRMoM+VPSx9OLYozxYUZyDoI81QVQZzssZ7DVJbsbXedly3fMm6/sE6fc5+41WgR7qtz8b5wZMtSj9/sby0CaA6zAIOOtcX7QqSBBEtSOgSRBzwWvJUJcJ003A9fucwrNl70pbuas2C8SELkmxiErMEyGA+hT50+WS64SQuVP6QzPr3QIU9LysAzKsYonRD0LEmqdo0ZUR+MH2VZnoDE8C6vaewZsF47GpoxtPrD9m+4zOCIlDccr9taD+898kZ6fWLIqG8MBc191gXTKK4Zcju7fKt9Vixtd5m1XPLkCETgfn+LNTcUxbKbMHcGmRZI3Jz7PlsVeLVS5CaShSzrA+qRaSXgCmxz/k28b/xItAjDQJTuduIY+aDhrO2fjcB7G5oxl3l0csBHk4fEEQ8IaFLEBHgxR9NNcGZEjWl8hEU85GqqG9qtVlgxQAllcB00nc+A1hwWwmWvVcXFMabDqN39uWu25Nu4kJl6QyYwKu19bY2+QDM9eCXqUJM98Ys7V5dGpjAmjoiHz/fcMj220VVpTa/VJbqy2lrfM+xZkugna5FULVQMmHvF/6Y2Zk+rD9wGitqjyJgOgdI6bZFNZYPnDxnS/PmRYQ6ieLxJX0c2+bFsir2j8yfVkegR8N31c3dhh8zhiEr3xB0QfKKzvVFq4IkQUQbEroEESaR+qM5/Z5N+GKOWJnVTEYkE9PCycPwzKYjFt9KRsAElnHVvrxsT6rEhZs/ZMAEHqosxqtbG5Tix6s1SZbubW5FkTJjgIgovFnf5vuzsGhyacjtwYegyJ1f2VXemLVHTPUl45HX92LfiXO4v6LY0l9ufe0UTCXrF/6Y5YW5mFtR5CoCvZSuXTS51JJtAghmpphWXhC2CLUFpcG6w+DWT14sq6rv8n3gJNCj5buqk4Hjkdf34sKl71A5tJ/dvcQARg/27hOsswDxskghiHhimKqogm7K+fPn4ff70dLSgl69eiW6OUQSwjIhPMr5HQJBsVNbPUnrxd7Y0oaJNZttIlP8fWNLmzRHrI7IWLXruG3SkQWPyL7T2NIWsmCpfBR5Vj54s7QIgxf+Y/9JPLpyn+1znwFsq74dABwrmon9CQCLp1hFps6923+iGdNf3O4aOMb/dmHVMJQN8Ft8Jg0DqO4UueL92l7XhDnLd0ivVSZk+EAiXYGp2uL2Mk51js0LN1XbVNf7N1OHY1xRbijlXDhtenlLXTAvcYwCoFTXJOuDyqH9sLuhGTCC6e1YQKDOs67bFtk4F2HHd8t04hX2XnBbAFFqMSIe6Oo1sugSCSMV09A4paNysiCK16prgcz323PEulmHdKtuAc5WVibI3PRepNuTrL2D8rKlQo9t+7N2ydCxGurcOyYMdEWuAeB7w/uhZsNhuz+kGTw/AEvA0KLJpRiQa78OA8DP7r4eT677yPY35nJwru1b7SIjfGaCFVvqtXO1qp5Lt9K15y5+G3LFENv2L388Jj0X78/sNeUc+/vSjV2V3iIJgJKdy0nQ2wIoVx/EgkkleLHTrYd93y0LhBdkVtM/GzcQK3eekB4/2jltdazgkfogE0S0IaFLJIRUTEPj5h+nEnwqy084/myRpunij8NP6l78Kw0ErZVuPpxO51P1DZ+9QLbt74Ssupgqs4NIhmEgO9Nn+44PwH+/eXCo6pmICeB3H3+pbFOHaYasjYC1QIQNAxgxwO/ociAeS0fU3TbsKkwty1fmauXvjcoC6FaCONQ22Nv25flvsPHD08r2QfIb3bEcrQAo1TOqetZUubFfeLeriAb7/iv3jba5AEWyOBR9ho+fvYhVu04o3yUkPInuDgldIu6kahoaJ/84leBTXWtt9SRtfzZeiISTpqu0f09Lrk6v1c1k7fRiJfJiFWPZC8JJoO81swP/nZ/PvAGt7R1S8TKuOA/+nMvx3DufabeF4YN+oQfTRChjgEyUG/CWx9itOpj4HT5nMtA1Vkv793QtQawSvw1NF/HhqXOu1y7+BrCPZVUxDZkfqhcRqXpGf3HvSOWzplvEo8M0Me/Xu21uMpH6rub7rQVY2OLT9LD4DJdU3IlLR+g+6ENCl4g7yZKGxuuLQlXt6TkhmT6P07XqbCtahIgBPHxbiec0XdOXbUfNPUEL1X99/AWefPMjy9/DLT2s64ss2+It7d9TKixZ9gIv/r66AUGye/ezadcjNycTYzoDdGTW6x+/sddTBgYGC+xzyqwgfp/PGMC7HKgC5VWWwXDynsqa2GGa2NXQrPQbZh+rxG92ps+1gIlIdqZP+dyIxTSk5/Z4r1TnkuU95oMOZ4yS56p2ao4P1hR/4SK7dz4TeGHOKIweLH8XRYNU3IlLR+g+eIOELhF3kiENjaxQQtkAv6PoVVk37yovUJ5H51pl6cUAyWRmBrdGq27oj99/9IV2mi4TwUTx7L9FdBYZXrc/mfj86sIlqZV0+ovbUT25VJm9QBfZC1/mlyy7d9NHFeCnb31k+e3k6/tjA7fNbkJeKMOJ24b1w/zKktD5e2dfHso3q8JnwGaFYy4HJ862ScW2AWvpW55w856KZBgGxhXlKlPOOaWiM9G1yBILmIwe1Bv7TpyTnv9ie0BpMRWLafyqtl56XpkgVqF6RmV5j1l/N7a0Ye1eZ5Era38A1hR/4aJyncjL6RFTS24q7sSlG3QfvENCl4g7trRABrCwSq/wQDSQvSiWbAj6TeoG+Ohu2zul3HFblauEyO8+PI21D0+wbe87pely0jPRXmSI1yUTQ6YJ1Ai+qgbsYs/J6i5WfgqYQPWag9hefbvNItzY0obCvGy8ct9o1DddRHHfbMuWcsAEFnUuBnR5qLIYy7fU265ty5Ez+NMxA0N9eq7tW8f+9wFYu2BCyMonZhF4oKJYOg5MIFT6dtHkUpQN9CMnMwOt7R3IycwIK70cj9EpvssLc/HgLcW2UsE6+t9E0IK/bfHtuG/8YHzQ0IyxRbkoL8wNZrcQMnroWEx5l4pXJUIXkFeXUyE+N/yiQ1VqeJ7injC/8hEDeyM704cZL26PyYI+EcaCZNmJ6+7QffAOCV0iIcwaNwjnLn6Lms4I8qUbD6N3lnvhgWjgZMnSWR17tW7KxLHOqry4b44tiAXosgrJtvfdypaK+GAXl5Eguy7DAAxTInaFfxtGsFIcw20hsPtYs1RAv7HzOGbfOEgaOR86l+T8XvAZwNyJxSjMzba4ggDB+/PI63vhM2CzEIuw3MghkfuHOkuwWsCUF8ywnM+0B7iJgX06eU9tbTO77sfcimLXUsEqWDW/8SV9LFX5Wts7UF1VGsrZzLfRzWLq5FIROq9HSxfrApkFXyw1LCtJDQDLfzgG1xX4Ud/Uiqt6XRGzvLKJyFmbDDtxBN2HcCChSySExpY2LN0kj9KO9arUzZIVi9WxKI51VuX5/ixUV5WGrM0Mt5eaWLbUh84teOF7BoC1D0+I2F+QR3Zdpgk8Pf16PPnmR45uAAGzq7yxzkJAlQL8F+98huc3fyaNnA+1KdwL5K7p//zuCNY4+GgGTDiKXMAq7htb2mxWbnYcvmCGDrqBfWwRtv5Ao610MV9u2mm3gOHrXJSJfxar+cnchkYMsJYx/qDhrKOIZS4VbgFhsupyImysscOYsI416ZhWHGvH0WY8+Jvdrq400SDaqcN4ZDspOuKaAqRiTyIWOakOCV0iISRy+yXfn4UHKoqVVpl4rI6VZVE/t5ZFnV9ZAnRavHXzoAL2SXDLJ2dsVdZqOEtiLK8rwzBwx/CrcXmGPX0XD9/vOuNjbFGe0tLpFDkfDUxAKxDJDV7c1ze1yv1gDeDaq67EfRMG47VtDdrH7jBNnDjb5uhDDrBczfbSxeJzMGvcIGRnZkiLejw5dTimjMiXjjO+mp9sAfPMxiOW4glMCKtgz0B5oeBDC/mC7uHOSmGq3SK3sSYNQu28OPEzVjqZXRvLsBJpMRUVsUgd5rST4iSuKUAqfsRykZOOkNAlEoJKEGVn+rC9rinmFoH7K4ot25EMWVBQLMj3Z2GRxFr7zKYjmDbSWhZ1/q0lmDaywPZS23+iGTsbzuLGojypYOUnQfZilFVZi/Z1qawNTkJJ7HeVuMjO9Fl+N+8W+X0E1JHzDKNTJZudx54xegDW7DkZkbXXq0sES4XV2NKGry5ckgcTmsD//Hdv/sOMH7+xF63tapHH0LUSjS3Kkz63UzoDv1TjjFn66r684CgqVbmqfQAWTbFbfsUJ/639p2zPFBD0E2YWWtHq6LYVrOobAJbPHqgosvkxe1m8J4M1VGcnhX+vuBURcdqhS4brTWVischJV0joEglBFQXPgjdibRHI92dhphAJXnltXyz90xFxe3mUDfDbPlOlUBJfaj/57T5L2+8ZPQD/+GcjbccTJxOnLdxowIK+VFvmMqFkwBqMBcj9RwMAZry4HUtmlgHoyrNqAJhzUyHe2GlPmi9GzvPMHDUAj985zGL1Xrv3pOcsC/z5FlYNwzMbu3xOJ1zTB1s/bVL/yATe2ndKOwWZiAHg4UkleOm9o1K3hoAZ7CeVyOOpHNoPz84uh88wlCmqtnxyxtI/hmRhKI4zp4p0gLslHwCenzMKU0fYLdPi9QzoLR/fzA1DVRDDTeSrLGj8Z0DQd5dvvm5O31W7jocCK9luSyKsoV522sTUh5HmeCbrLxErSOgSCUOs8MNHKMfaZ1cW7LLts6+ifh4ndFMoiew/0WzbNl+95yTuGz/YtTAEq+oUCyuKW4ECJkoWTS61VNECgMOnv7a0nc+SMO83uy3VwBavPmjZNjYBrNr5ORZVlVpEJm9JLu3fE3cv225p77q9p3Df+MEwYeLL8984ijE32PlmjRuEaeUFFvEzYclmxxRcYl944d4bCzHhmr74b9ddjRNn27D7WDNe295g+U7ABF7bVo+SflcqxYWO8BB9WQFrwJoMt2qCADB9VNcOhsq6OnqwdceisaUNr9XWh4Qla3N2Zob0HCynr8rqqLMVLLOgidZNGxo3VsweYiKYDjAR6aJ0A51kqQ9FIsnxTBDRhIQukVDYRLG9rimuPrvR9hEOZxvOKerd6eW/s+Gs9HgfNDRbotrFyaR69cFQ6d5IrCiya/VSmlgsfiAG/7hZigLsRxwdpokRA3orA3/ePtBou44O08T0F7drW3Blbgk+BK2NvAWUjWnWTwsmlWAZVxrW8nuN6lpO7Vm58wRe33nCVtVMZPmW+tC9B7oWDEyk6ggPVe5Wp2dGJ1fvur2n8Pidw0L9JqYV44UwILcQszb/xW1DpOeoripVFijhA+4iedfIfKxNOPcPEAy8k/1ud0Mz7ioPvz3ReCepXFhU99UHuMYSUHosIt6Q0CWSgninTInm+bxsw4mTj1PUu+rlr6o0xbddFSlusYyu8W41EgVrdVUp5t9aopy8djc0w8RZrQpcstKvMhEqE5wGEBK34vU0trQp8616cVMw0ZUqLYDgpP7fbx6MUy1tGHg+y1WMibCMA0s3endbEIWt28/5e88IAHittgG3lfbTEh46z4zM/9XNb1n00RV3Wngh7GQh7jBNvChZUDw8qQTzby1BY0tbTN4xvJ+q7vH5fjIMed27Px79ShpIqCNgnd5JqoUq+0zHuq0aCzrluyk9FhFvSOgSSUG8U6ZE63xetuFUk49u1DujvDDXVmkKAB78ze6Qe8LZ1nZXgcG2tJ+Ycl1Y12qiM3+rAUwrL4i4fO6Bz8/BhCkPHIOLqJNrBQB6VkVdTBO496ZCrOz0B/71+8dCf2N+0vtPNFu2olX8cHwRppUXoHfW5TZrt4muEsIjBvbGxfZvsXbPKaz/sLEr32sUrmdF7VFMHdFfKTzEgEenZ0blKuOGl2wbTvdSZR2vuCbYBvGZ91qoRiYQxWt2y10s+82iqlLp+VbuPI5Hbr/GIkZ/VRssWKHjYiJ7J8l8lAEo30sqVO9PnSwuTu9eClAjYoFhqpJRdlPOnz8Pv9+PlpYW9OrVK9HN6XY0trTFNWVKpOfbXteEOct32D5f+eDNNv/UiTWbbWKCT6v08pa6kHWP9/lU8c6h03jg17stnxlAaIuaF02q1Es+ANsW36517apr9RnAturbseWTM6HJy01ky/7OLEJiNSndTAZinzNkfR+uy4AqVyzj4dtK8OIf6rQtxUwc8YuWxVWlwaAqAxgzuCtrgXgNToiWZ9m9ZzxUWYySflfahMfO+rPSgEfZM6Ma38/OLpdm2WD3VBznqutcPKUU8ytLlH9nWRlE67j4jAHBohzML1rXhUe2kzFtZIH0mp2smqp+mjVuIF7fecJ2Xjam+WA1Htn1qZ7TZXNG4dGVe23PgTieZcdUEcn7U/yt1wA1EsWErl4jiy6RVMQ7ZUqk59PdhnOzVK3adTw0SRsAFk4e5jr5ZmXaH19+i5pN5M/PHoUxRbn4VWfwDo+bj6V4rTLRGTCDxwiVS61twPKtR5XHyTAM3F9RZGtLh2niYnvAYu3RFbmsz3UT3U8fVeA5lZiq3TzL3pP74qoImPZ8vEs2Hg6NKcMIiqqyAX5Hn0gDwf9jcosktv38VeslPPL6XmUbVmypx7bFt1v8m788/42tJDIf8Kjjsxm0mhqetrjz/Vn40a0ltn5cuuEwbi62W5V9BjCvYgjmVhQh35+F3lmXO1oKczIzPBeqUe1kHDsrv2ZV1UIAeE1SXa7DNDHxmr54Y5c9awgb02IQIP9bXReTgGnfLVG5gOi+E9h36ptaLf/WQQzk8xKgRlkbCC+Q0CWICNB1gXASxLKJVJZPV8StwhsQ/FufK3sg358lzR3sxTcu399ZqW2jc6W2FbVH5YUPALzQGbgFILQFKx5nfEmfUC7Whx0EGv+7n8+8wbYtu2hyKcoG+m1+hyzDB99GVTCXWLlL1u5YwPsoL9lwGA/fVuIqGAFIrWtftV5yLiGMrhK97HdvHzgl/S4f8MjjlC3Byxb3ql3H8eIf7IuFAIDpL25HTaegKe3fE7samjGuKNdyLJl/aSRpsAC168vKHSc8+Zo2trRJF0k+A8p+UgXqup1vXuezzgeGyVL7qSy6uu+EaAlOLwFqlLWB8AoJXYKIEN3URF4mMh2ris3nEPYtajHxPV8aOBy/5Pm3lgAGLNbn75fnh/7u5g974dJ3IQubbDLmrbC5Oa3K4xgGsOC2ElRc0y90ffyWcMBESJAbRtClYMI1fVHcN8dTSdfnZo+yBQSpMmVMKeuPTR+edrz+/zFhMH7zx2OehfKL79Xh3hsLQ1Y/VmBDFIyqgDgDahcQmbBRBTyOLZILVKfxrVvFyc232ewUNOcufhvKO8wWImUD/CErPp/14j/2nww7DRZDtZNhAniwYghera3Xep5Ule/mVQxx7CfVglZW3EYMgpwxsgALq0pD39EpfKH7Toim4PQSoEZZGwivkNAlpJD/kzd0XCC8TGS6VhVZqd9wEt97YX5lCfYdP4eNH56GCWDdvlNYt+8Ult4TDD5SWZlNdAqVtm9DQtlnAA9xW888ThZr0wReeq8Og/KCFmAnq5dpAi+8W4cX3q0LWXp1fHR9RrCylwjfhxfbv0VD00WM7bQsrtp1XCqCGb/54zHMHtdZ3AJdrgdumIDFh1PlA6yqVMW7sWw42IgNH54O/UZM3wUEAx5HD+qNPcfPhT4rK+hlSV8nvh+cxpbb87Fq1/Fg6WCXfugwTUve4UCnxRuwWhR1sl4wFk52Dkhz2smYW1GEuRVFWs+Tqtrf3Ioiy7nEY8gWtPMqizF3YrHlu2I+XgBYu+8ULn0XwIt/PgaAXuEL3XdCNAWnl+BgytpAeIWC0QQoGI38nxIBL5B0AtGcCDdARHdxs/9Es634AhAcK7+YPRKnWr4JFW6QIW4fOwW/uAlH9lsA2sFarIKZW1qvh24ZgiemDnc/oADrfyffWN63VHS5GFeUix31zVrXwfebjrh74d5RtkwYsv5XBoVVlaJ39uWe3w9OKa1yMjNsAYgq3BYoqoBGJ1jAl9v49xosKoMfzz4DeKCiGPdXFGs9p27P9dsHTinH25sPT9DKiMDOo/Me0Amw9Yruuyua70sidaFgNCIsyP8pMUTD0soIJ8DOy+JGVbAiYAKPrtwXspoOzM3CI6/vtViYfLALFScrEPPHVBV2YL8dX9JH6VIg+82IAb2xdsEETF+2XWpFFC1tKlTBb/n+LLws8TVlBMygr+/ciqKuIL5t9Vi+pV5L5LLr4PPP6uTthUQoyvpf5YJS02nV5C2qbu8H2dgC4Og3CwTvwYzRXem6fAYw+8ZBWLnjuNLy22Ga2NXQrC1ymSVQZ/zPryyxVL0TFwY64lC818u3BtOF6SwW3J5rJ5uVyrdaxMt7wIsVVhfdd1c035dE+kNCl7BA/k+JI94ZJxheFjeNLW3ocZnP8XgBE1i66TDWLphg8wleOHlYyL+S4bbt2Nreodyq53/LT37bPjuDFxTVyNhvRJ9l/u9uE7aqBC2fJmvppsPK3wP250oMFHTDLf+syLyKIRgzOFdr2zdYyMAuQGWn4It96FTMq+7M5sCOJRW5BrB2QdAK+fidw0LC8PUdx139jccV2a9RBu+jKraRL6YiilhxXHgtzgBY73W0jAljFX7Vwb+5i1yv74H6plZUDu2nrEYYC9zuBUHIIKFLWOgu/k/kg9yF2+KmsaUNu481Y/tnTVi584SWGAuYwN3LtmPxlFLLRLjlkzMWYWNIAmpElME4sP+WTX7jS/rABPDiu3W24LyFk4eF0iGJ2RjcqjoBziVomSjQEZ4GgOzM4KLB7fuisBOLHbhl4GAWal0rXMgvdYNVrKui9A+cPIcfrHjfJva8BP6J5WN5CyQvDM3O/vjx7degI2Dil384asvosGRmGRavPij1f/4f4wfjzhvyQ/dZ5t8dMIPFVEr6Xelo4fRanEHVJ9EwJuT7s7D0njJbWrh7Rg/QsubqtitRrm3kUkeECwldwoLORJjqIrE7vTB17lVOZoZNSPFbuk6R8AaAP7n+avz+oy+k31my4TDOX/wWE6/tiy/Pf2PLB2qYcK2eZQvGEXKnyli16zheeq8uJIoWTApmaDhw8pwlEE6M2HfDrQQtEwUHP29xPZYJYPqy7ajpDOJzSgFmIljY4fIMH158ty5oNd94GL2zLg9VsbLkH+48mAm7hVp323d+ZQnQeR5egAKw3Is/GzfQ4u/Miz2dFHhAl2/tibNtoUIZDJVYfm7zZ7b0b/w1tn8XwJNvfmQ716//eAzDC3qFct2q2rh8S33oXOJ1sfOoxOE7h77AU29+JO2TgyflY+PAyXPK/Lu6sHv7Xx9/gaYLl3B76VXavrm6JZ4T4dpGLnVEJFAwmgAFowVRBQWkukiMRQBFsqJzr2TWSb7ggE6Al8olQUQl5FQVzUR0A1VU99gpSEl3LKuqTrFzeA2M49u2atcJaXWsUBsBm4+tOHb5PgJg+W/ZgkdnISTr9/0nmrF861G8feC09DeAtaqXk++0Wylat6pwsufXbYEm/uYf1n/sWAhEdl2AOmhPhSwY0Ok6ooEXw4RbkJduJchotzOW5yVSFwpGIyJC5v+ku6pOZotvd/FB1rlXMuukzwDWLBiP8sJcx5RdPB2miREDg8FdsmwMDJVPpaqimQgbk40tbdhe16T8ruoe/78PPldej66FKCczQ/q5Abgm+FcFXXWYZijYzq2wg/hHceyKz22+P8uWT7e6qhTzby1xXQjx94QXEzrZHWS+07sbmqUib8FtJbZFlXg/nAINxT5wqiSm+k3fnj0cvi2/LtY/i6pKUbPhsKtLT4ZhSIMBVW2KBl4NE27WfpX1O1JrtFs7u4tLHREbSOgS2uiIxGS3+CbjCzNaCwP+ODr3SvadgAlcbA96NnrZdmaT4uIpdr9OEXZMVUUzpzGjM75U7f7XHccd26UjNE40t0k///vp14faIc2X2rnFrkppxpdtNtD13zwqi67T2FWVrz3/zbd46b06pbBU9bNOdgeZu1O+Pwt3lWfh5Lk2Wz7al947itL8Xo7jlWXfeOfQl3j+3c9s6en4xdLZ1nbtMcv6aOlG+Zg1jKB7jVjU5OUtdcF8vp394+Taw7uPyIIBZW2KBuFu9zsFeeX7s7Bosj2n8DMbj2BauXMlx0jaGYsMD0T3gYQuoY2bSEwFPyr2wuQncZ0I+1hZqKO1MBCPs6jKXhRBnEjd7ifrq+o1B0PCwgBwy7V9UftZk0Wssn4R/TpFZGVrnSx5PLrjy80C6AQLDlOh8vTqnZVpOz/fb6YJ9M66XCoSbOcAsGzOKOz//BxWbKl39I/lA9IYbgsewB6kB1izJ6j6+YOGs44icllniWfVc1I20G/7rKMzus1pLNqqvHVax2WLJaesDOy4/Jh1CgQ0zWDZ6rycHqHF3Mt/qLPcQ6f++Lu7r8c1V/W0WEdlY9NNuIXzDorV7pXqHoZ7XN12UkoxIlxI6BLauK2qU8ktgBcgDNlkEksLdbQWBrLjPLPxCBZNLsUzm44oLSD5/izMGDUAq/ecDH0mVslik8ueY80wzWClMOY+oJpw5t9agmkjg/lGD5w8FyoewdpwVa8rQlkPVGNmd0Mz7iq3HtfLd1m739h5HL945zPtvmTWbBWnzn1j+8yAvYJaaf+elrFlAli8+mCXuZb7rSEReKMH52LqiALMnVhs6+dzF79FTadlmA9IA+QLHpnoU2mz7Eyfsp9fq23Aitqjil8GGZjrnPJJVk43wzAwpihX+W6RWaV9nQJ0dGfQGr9Yclra8K45Tm1iGAYswr2xpS2US1iH3JxM2zPiNdOHKPIfvKUYczWKTMRq9yrax/VyPEopRoQDCV3CE06r6kS5BXixdoj+eybkZWmXzAxGwsfSQh3pwoCl/Tpy+rz0OCMG9nbMcdnY0oa1e09aPlu39xQev3OYTRBPHWFPP6Wz/Tm+pI8lyf6WT86ERInK8gwAP35jL1rbv7PkI/3qwiXpdx9duRcnW9qC1mRYx8M1V12pbKOIjhuALDfuw5NK7IFQaw7avifzsTUBPFgxBCtqj0p3GMR+Zm1gh2FjsrR/Txw/e1G64FlwWwmWvWfNKazaPr/YHghm4ZD4Ey/fetTVD5VlkVAtBrd8csbyb963WfVukbrYAMjL6eHoEy2Dd83RQjhufVOrXBDbvwoDwCOv75UukHUFm0zkv7K1His0ikxEst3v9E6NthsBuSUQsYaELuEZ1Us6ES8srxZXlbhk/nZAl3h4dnZ5TC3UkSwMdKLKmVhQtTXWFngxmElmeV664TBm31hoy8/LLyrEbWkRE8E0ZjBhK0+7qKpU2b5r+mWj7sxFaQouGaot7mXv1aEwL9viw+rFYyLzMsO2w6ASGqp7pqrw1mGaqLi2H3plX24pXysrgZxhGDjw+bmgkJYcTOeSTADVXLEFHlmQmGFY08vJxqvbc6IKEJQhe752H2t2TOvGPw8q/+/qKaWYVl6APceacba1HT99S55azOtzpRpzuscUrcet7R1obGlz/I3OO1W2KInExYvcEohYQkKXiCrxfGGFs/UvDRSCvCyqzzBiaqEOd2HgFlWue5xYWuBlk2VhXrbUMvf6zhNSAdthmthzrNlm0VIhK0/7zMYjWFxVGlzICN//7EzQH7Xy2r5Y+qcjwuovIChO2bhz8vdUbY8ve6/OssNQvfpgyJ1BFBrKNijazO6naFkHgKavL+HV2npH8RsOpgnsOdZs2wVQBT+6LazcnpPW9g6tdsn88dmCUYX4PIht8QH40aQSlA0I+q1OHVEgtTB7XUAy0ZiTmaG0vuseM9+fpR3wKXunLl5zENmZGRhblGfb6Ymmixe5JRCxgoQuEXXi9cIKxyIpmzRVZWlHD1b7DUYCb/kIZ2HgJKaenDocU0bkax0nVhZ41QLklftGK1NsyS4nwzAQME1t4aWyaI4Y2BvrHp6AdXtP4bXtDbbvbPm0CV+e/0ZLMKgqbrFx5+TvKftMtsgyAdvuAlu82YSWQ1YMVjkOQCgdG8try9+fOTcV4tHbr9Wq5qaLadqt0jKXCN2FlZvLlFPwmQHgwcpiTC3Lt1g0w10w8m1hFvBl79ZZXJ4iWUCKonHyDf2x8eBpWzt1jykVr6sPorR/T1sxCdVi5NGV+2AYnanpOl2EGPtPNFsCL5MxCJno3pDQJVKWcC2Sskmzd/blIQHDl5Z1E6Jet+tUlg8vE4JTSVxdkcuIhQVetQCZ9+vdrtvfYuqxsUV5WinO2G/F8rQ+A/iP/Sfxxq4Tjsf4oKFZq4IUS3MlugqEYwnPMAz8xW1DsOzdOsfviYs3cTtaVQQDBrCz/myX24cBPHxbCV7k0ooBwOs7TmBwXg6mjSzQ7mvuFFLf1JMtbfhxzd7QOJ8xagDW7j1pE7leFlb8Alp87mokpW8Zf3f39ci8rKufnHYYGG7ZI9jnrOwx0CXwaqsneV5A8hZcUZRuONhVlENMVxbuwjgAYPqL21Gjka+WYZpdLkLzbw2KXZULVbIGISeaZM4xn86Q0CVSlkgsklKrM5tFDI3vwvt2XbSyLLDrFtN+LbmnLKyXZ7Qt8Drb60bn/xGFD596jFndHqgoxoqt9Y4iWZZ+i23/O1UbY4wtcha5/AR1+PTXlr8ZhrVYhI5OZNH/bx9odP2uTETz90yVsixgwpJRwzSBFxSieunGw7h5SB7mdfa1TrgW2z3Y8skZyyJRzBcstgOd3xOzH6gQxYHquSvt39NWsMQAMGKg37IYYM/dmgXjlTsMLNDNqU2v7zim3FHis5UETBOD8rKVRU7ErApO48dAV7YJ3WdWx+WGD350S823dONhTBtZAABKi7hhIC65yVNJOCZ7jvl0hoQukdJEwyIZjgB1+g0gL7cazeAvdt3vHPoCX56/hDuG69e0jzU62+smgIcqhuDV2npp6rEvz3+D12rrsdxF4PqMoMXOn3V5yIeQCYxHXt+r1d7Ka/s69p04QYlWY8PsCqjKycxwFStAsD9OnG3Dq7X1ru2T5crlkeU19Qqz8LECCJXXdOVKll1PhmGEdg/EZ1DHBSIAYFdDM67qdYWnwKjZNw7Cyh3HbVknKof2Q3lhLpbeU2YR3UvuKUNre4f0ubvYHkB1lb3AiZt1Xsyjq/ot7xfLEAWOLKuCE3y2CV3y/VnK6m1O+Wr3HGvGw5JnKICgX7UJB7eiKLnAOJFKwjEVcsynMyR0iZRHxyLptPIPR4C65RoVX76NLW0429ouzSEaruVjyydn8NSbwejuF979LC4vel0Litv2eoZhYG5FEeZWFIUE0lv7TmHCks3ac6TRuSXO+oDv79wceRooGT/5k6HKawTsxRNE2MTPhI3Oed3KwfKMGNDb8e+6Fezc4H0st3za1PW58D3egs0Qn0Gd9jy9/hB+vuGQp8Co1yXV7cQKarJsACoXp+NnW23He6CiyNYONh7e2n9KKXJ5n+i3D5ySbumLAue1zmBAXcJ5X6zadRxLJcGYTsfL9wdTCn5+rs1xIaB0c4B7kGEkpJpwTKUc8+kICV0i7YlFHXVV9gYmcoGul++5i9+Ggt34qk2RBH8l4kXv1YLCix+nYgAmTPzb+8eU2+o8PgP42bTrkZeTiSsu91n8fvk+8CL+Pm9uQ3lhLhpb2ixWZJ8BVFzT1/UYGYaB7EyfY7o38ftu5WD574rjUFxsMIudLF3YnddfjQ0fnrb83gBw382D8S/vH9NyURDhLdgyQq41q+2pxMTdcKdxqxscJ8uMIIpw2fgDgosYET5PLfsOe3adeH7OKFy49J2leIUMvgLd8q3uFn2GF19fNjacSjbrHE+sdCj+RhWcqSPII3E7SDXhmIyl57sTWkL3scce83zgv/mbv0FeXp7n3xFENIlVHXXZbx6oKMIrwsQVytHb+W8moJ6fPSpUZSwcvL7odSeVxpY2fNBwFoZhYIxQESoSYV05tB+enV0OX2c2C9HXUpeACVxzVU8cP9uKR1aqg2DGl/SxpYGaVNoP7xw+YzumaULaFtGyqWL6qAKcaG7TErlPTh2OsUW5oZRYYmW6Gwp64eNT56WiArAvNh6oKEbfK3tYFlILbitBxbX9QgU6Nn5ojdg3Afzm/WOonlKK7Msz8OSbH2m0vAtmwZYFhgHBsVnav6ftd6YJ/OUd19gq1bE0cmI6Mp3FitOz6pbdxKnQRMBEKB8y/+yq8CFYFU4ZGCi0mbl46A59nWwquin9dI/H4Csdqqq88TtZOu/PSN0OVIaGr1ovueYJTgSxynBD6KEldJ999lmMHz8emZmZ7l8GUFtbi0ceeYSELpFwYllHXfwNAKwQtiJlEzWLgI/kJefFQqA7qYgR1AYQqnIViQVFdn6x6pwuzHqqKspgIFjGFpDfn3eWbLb95tDp83hJyETghbV7ToZEnhM+AN+ZpiX6X7yGD0+dD13HwqphlvskW2yIFkETwC//cBR/Pn4wAHWwkIlgsY6Hby+R/BUYMcCPD0+1KPuE9bEYSMWOrfJT7tezh/SZeOT1vbhw6btQLmK2IBODLnn+8vZrMPsmecYSnewmbkLay3hQ+QKL+NDlGiE7vwF5SWg3UapaiK5ZMF76nvCancXJPSzfn4Unpg63uCGF01Yvu1GicGTjTVWJLhmgohiJQ9t1Ye3atbjqqqu0vtuzp301TxCJQLXyj1YddfE34qr9zhuutqQHYrCJPdyXsa6FQHdSaWxps201mwgKJZUrgO72pOz8v7h3pGdhyXxDnQSFCWsZWv7+rNpl9+8EgJferQtrC58RAPB/fv+J6/d+dFuJLRuBChPBAhjTygtC7dfdymcLEMdgoc52f/LFBenfbrm2Lw6ebFH+dldDMwCr/7I4dmSYZud2t7DIMRGsqAaza9fDKZsCAFwrsRoD+mNeJ8OACC9EfQYwe9wgPHrHNUpfYJ8BPDd7FArzsrD+wGmsqD1qcY1QuVR4tfypFqIX2wNxsyTqvj9VbZVZ9Z1gwnF3QzN+/MbelPDXjXaGG0IPLaH72muvwe/3ax/05ZdfxtVXXx12owgiWsj8BU0EA7liseKXBWHJMBH5y1jHQqCaVNYfaMRUzqqj2kYNmJC6AkQ6AcN0Dli68/qr8fuPvlBmN3D6raxvmfiREYDcf5Sh6+srWjRZ+jRWirhsgB/L3nP3Qw5dh2mtMKbrd6wTLMT43Udf2D6bVNoPL/2hznFb/en1h7SyS4g89eZHqLmnDL+YPRKPrtxn+Rvf/wEzWNRAlk2B9bPKeudl94F/hp79r0+wo/6src0+wOJKonrmVIvPMUW5+KDhrNR/v7Z6EmqrJ9mO57Vsr9NCdHxJn6SyJKrGcTiL/3x/FvKuTC1/XSL+aAndH/7wh54OOmfOnLAaQxCxoHJoP4uQiYbIdIKt2p18AIHovIzdLASqSUWMeFdtvfu4fJjhbL2pJuDCvCzMqyiWpg/zGcBdI/JtIoz5hjLR7eT6IPatkzXUqfytYQBrF0zA+oONWLGlPiS0VO4AL9w7Cn2u7BHqM7fofzf+8+MvkJuTadnKd7puWbCQzGLpJFInlvTFuxJfZhG3y5AtHkwESxyve3iCa18EALxW24Anpg73ZL3zuvvAfrerQS5y1z48wZLbmf+NiPiMbPnkjDI4rcuKWWA7Xr5fv2wv+77TQjSZLImqcRzue5kCvQg3PGdd2LVrFwKBAG666SbL5zt27EBGRgbGjh0btcYRRKQ0trTh7QOnErLid7PAub2MnQLIdIPLnLZneZEAyMXPoqpSxzRSbsgm4OmjCix+qrdwOVudKqL5YPW/PXfxW8d8ptmZvlCSfqd7MX1UAeZXlqDAf4XUynixPYAnplyHuROLsbuhGTCArMt9mPeb3baCF2KAoZPFT0f0rtt3Cuv2ndLayv/x7dfY8imLOwyfN7eh+WI7vjj/DZ7fbLcu+wxgXJF7NgjxN8zvnLkesPvY3hHAk+uswW4mgjmEebGjEt7Ltx7F3Iqi0LjTsd6FE/ijWgjNqyz2nJ+atdUp4wFDZcUMx481lXxAZ40bhOzMDNvzpnovO73vKNCLcMOz0H344YexcOFCm9A9efIkli5dih07dkStcURqkizVapyi+uOx4rcFTEiEgKp/nALIvEYsswlw/YFGPL3+kOVvvD+nbD52y+Gqg1NO3YAJbPvsKyy/bwzqmy5iXFFuSFiIAj0AYMaL20PBbEs3KfKZGsCdN1xtEdOLJpcqLchr957EfeMHS8W1qgCAzwBmjhqAdXtPSSdXWZqn+qZWVA7tF9qqdizfK8CyAGRnZqD5Yrv0O89t/kyaT5lfnBw+/XUo77CMRVWlKC/M1fZdFavZAVYr9tsHTkl/Z3T6H/C7LDJMWDM86FrvvIo+qS+/AZQN8Icdxa/jU62yYoYb/JlMlls3BuXJ379sMcvQed+lksgn4o9nofvxxx9j9OjRts9HjRqFjz/+OCqNIlKXZKlWE2n+yGghi/x3exm7VV0LJ2I535+FqSPy8fMNh5QiIZbbf07uHB2mGcqHy48ZZr1kFbv46312drljtDwfABgwEbL8ynKhBsyuADanfL9iv6/be8pWshiwZyKoKuuPTR+etmWdqG9qxZ3X98fGD+3BiqrrEi1gsu+oxoPTM8FK986vDGZh4MftgZPn8MzGI8rFmmjx5M87ZnCu1Fr7cWMw04WbxhcDR/P91pzBPkNeOc7rYluW4YH1d7jvsZzMDK3vyQRsd9iOZyn2RPiKeWKQbMAMBi3KxncqiXwivngWuj169MAXX3yBIUOGWD5vbGzEZZclR/2JZcuW4X//7/+N06dPo7y8HM8//zxuvPHGRDcr7UmmajUqa4qX/JHRQDbhhhvAtedYM061tIXthuG2xRfr7b/GljZ8deGSsiQwYJ/IWts7bH6ewW1/I6xqYE6WQ6fgIKeodpYTlSEGPoqiu3r1QVsKqWjCjwd+/Hl9JphwGF/SB9PKCzwt1vhjVE+xl9nVTee25J4yyzlYlS/+HbN042H0zro8tHg4eLLFIoQfqCjG/RXFSms7o3JoP+kAYdZ0r++xE81t0s9F4S8TsNHcjk+WHTYRnfiBnB6X2W6JGKRJEG54VqZ/8id/gsWLF+PNN98MZWI4d+4cnnjiCfy3//bfot5Ar6xatQqPPfYYfvnLX+Kmm27Cs88+izvvvBNHjhzRTo9GhEcyVatRWUTiKXLDtW5L82saQX8+mTYwDHm6NIYqcb4Y0a0qnxqNSVK0crJAJZm1zzSBdw59gT+/uUh5H0cPtm6vs8j4SGBjtahvNr5qvYSmC99gbFEe8v1ZynYc+PwcfrDi/a50UzcWulopTagzPEQD5p/8D+s/xqudeZ0NA/hhZ25dkbGahUuYc4uu5YyNnQG97d918ssFgn25dsEEi7VYZZF2WjwEzGCu4RVb61Fzj7XSmfhMOhVwCJjAa9vq8cSU6yzXpnouWE5qkQzDwF/cNiQk9J0ErNN2vO5z6eUdFG9BrBM/8NNpw6W/jeXzQ6Qfhml6GzInT55EZWUlvvrqK4waNQoAsG/fPlx99dX4z//8TxQWFsakobrcdNNNGDduHF544QUAQCAQQGFhIR599FFUV1e7/v78+fPw+/1oaWlBr169Yt3ctKKxpc0WYZxhGKitnpQQS8KqXcdtFpFouFHoTAiR9gXfdlZYQPWgGgC2L75dOeHKJjqdCTBabiiyvjAA/P3067HhYCO219mj3QFg6T1dbeX7gt9ib2xp8+zvqsIHYNGUUtRs6KpkxxfNEMfTwqphlu/GAp8BTCq9Cu8c+lLv+wBuHdYP7x5xz5rAWPngzRhf0kf5d3EcLJpcirKBfsfxryokwTAM4O7yfLy1r7ErZVjnOFc9q/+x/6Sr64YTvs5zqJ5J2TgVf79t8e0WX20DQHVVKebf2lV4Q3UcnxGshLd278nQ3x6eVIL/eWep5bdu7xbVcynzC3d6B/Hf95LhIdo0trRJ4wcAYNmcUbYFvtP7juhe6Oo1zxbdAQMG4MCBA/i3f/s37N+/H1lZWZg7dy7uvfdeXH755RE1OlLa29uxe/duLF68OPSZz+fD9773Pfzxj3+U/ubSpUu4dOlS6N/nz5+PeTvTlWSLfo1FgIKu+IvUus23venCN44TvBiww1C5kpT27+nqYuLFDUVVNtipL0wAf7POufQsOx/LsFDTuR3NtqpZvzNL47yKYqzYWh/Kebpw8jCMGNgbB06ek6YOE2EFHfivmQhaC7MzMyyBZEV9s/GrWntgWzS5qywf/+uu4fjy/DeOQtdnAJNvCPr6Bkx4Erk6mT/EccD7O1dPCeYH5oWZ+Buz87u8Rdw0gXX7GmEAeOiWIZjbWS1sz7FmBEwTY4usVTXZcxcJAdYYDv6ZdLIwst//18df4KdvfWS5tiUbDwMGQouv14TqiIy/u/t6WyDgsnfr0OuKyzH/1hKtd4vquTzX9q3FXUNV/pddryhs+YV0vF3OnOIHRg/ORQ2XQ9kHuzsLQbgRllNtTk4OHnrooWi3JWKamprQ0dFhK1Zx9dVX4/BheYT2kiVL8LOf/SwezesWJFv0azQDFLyIv2gEk/BpisJJU6YS27saml1FuK5QdyobzCjumxNWcQF2PgBYuumwbSLmJ3eGzwAeqhgSSkkFAMfPtrpudd553dUYXtBL2scm7EFJjS1teLW23uMV6eMD8L/uGh4SJE6IwXeux+4cS7JMEeKCxSlzgAmEfG/5IDtZOj8TwN/ffb1tcWMCWFEbTCGmsiq6penydR7HbXypLLr8s8Pn6310pd1V6Kk3P5Kep2bDYQzonYXC3CxbWWYgeD3+rMul17B042HcPCRP692iei5rNh62BWyqyv+yEtr8uUQ6TBO7G5qRd6U9c0gsXBucjCTJNqcQqUdYQvdf/uVf8PLLL+Po0aP44x//iMGDB+P//t//iyFDhuDuu++OdhtjyuLFi/HYY4+F/n3+/PmEu1+kOuka/erFShtN63a4acpUYluWJ1Wc8HWEulvZYD747sFbivGKRAA4YQChQC+3yZ0RMIFXa+tDFkImktxE0O8+/gK/+/gLR0HOiw/dcrwqnM7Dl4J1y8MaDj+6tQQV1/azZYqQLVgqh/bTCvpzC7LzAQgoVhsBM2jJVQk9VV8/Pf16lPTrGSrMYHErmTwMX7VeChX58FpeN+/KTFRPKcXSDYctvt+qbjAR9KE3DPl35lUMwdiiPGkRjQCgXHyKQVeqkuaqQEnZO8iphDbDAEKFOUSXi1i5NjgJ2nSdU4j44FnovvTSS3jqqafwV3/1V3j66afR0RFMEZKbm4tnn302oUK3b9++yMjIwBdfWCsqffHFF+jfv7/0Nz169ECPHj3i0TwixfFqpY2mJSKcNGUqsS3mSZVN+DpC3als8O6GZtxV3vXduRXFWKHY0lXS6dypO7kz+MWHV0Hq9lVWPlmnqILKt5r5dS7dZLdGPzd7VKjoxM/XfxyTzAy//MNR/Pn4wRZLrmrBsq36dswYNQCr95x0Pa4JdZBQAMDfviVPPxnsR1O5iFQ9d3cMvzp0Dapnbe7EYmV5XdmzI7oPzL6xEK/vPOF67aE+UIh8tsNQXWXPQKFafALAw0JBCdlzuXDyMNtYcir/K9shMoxgiW3mHmAClkUHf/9j6dpAgjZ1SdbsHkAYQvf555/H8uXLMX36dNTU1IQ+Hzt2LB5//PGoNs4rmZmZGDNmDN555x1Mnz4dQDAY7Z133sEjjzyS0LYRqU84VtpovrjFY3n19RUn+2dnl8PX6QfnFPWt8pt0ckn48Rt70dqunqB5q7TPAKbckI+3DzZajmGa1pK/4uRes8lu0QW6Kqhtr2tCTmZGWG4TBoC7RxbgzX2nbL99ev0h2zENRQEJWfU2wwCmjSwAENy25i2Od5UHP29saZNugXtFdu0yNxXVgmXPsWas3esucnVQifZ5FcXIVuSczc70Id+fZRPb00fJy+YCCKV6Y8+LKm2aiMw16Y2dJ6SLrAWTSvCiRoo0A0GfUgDYXteEaeUFgGm/72zxKbPgL1p9EDk9Lgu5k8ie6d7Zl2uX/1W9x9gxv2q9hEde3+t4XYnKpkMkJ8mSP1+FZ6FbX18fyrbA06NHD7S2tkp+EV8ee+wx/PCHP8TYsWNx44034tlnn0Vrayvmzp2b6KYRaUCq+ovx6bK8RFg7fTffn4Wae8ps1kBAbvVxskoDwIYPG5XWcllatIdvK8EL79rL2N5a2i9UZMKn2Ep2wwTwH/sbUV1Vimc2HbEFJ9mstCbw+J3D8Pidwyxj4x/W262YARN4rbYBK2qPBjMOGMCPbhuC7MwMvH3gFApzs7Cz4azndocskDu6LJALbgsKMv5YMjcV1fFkltZocVNxHnY1nMUrW+uxXOHv/M6hL3DgZAvWCBblNXtP4vE7rYUiwpls3fIMBxD0+V6+9aglN3JhXja2Vd+O3Q3NoS1+GYYBnLv4bSj7AWvXtsW3294hs8YNwqXvOvDUm/Yx88jrey3XJIpXr+8l1fd1YgIA552sZLbsEdEnmfLnq/AsdIuLi7Fv3z4MHjzY8vmmTZswfLg85108mTVrFs6cOYOnnnoKp0+fxsiRI7Fp0yZbgBpBhEu8ttcimTDYbw9+3hL0ZeX+xlv5VC+lxpY27D7WbKtKJBOvpf174u5l221tkFl9nKzSOu4UltROBjCptB/+cPhMcMvVAG4d2g/vHu7KOhCJSOswTYwY2BtrFozH//vgc/zrjuPK7wbQZX3mXQJUAWvLa492lb81IRXsIgaA8kI/9p1osf2NpTtbKliPX3zPelwDsPXr//ndEfu5OkWVrCyyDJ8BzB7nbZt/R31XWjmVy8Nzm+X9IhYNCGey5f2SWQYJmYvE1BH9sYK/X+gqLnJXeQFa279TZ2owYXn+AiawePVBPDdnlDRDSV6O2o3O7Zq8vpdU35dZfKePKlCWu+ZJdsseEX2SKX++Cs9C97HHHsPDDz+Mb775BqZpYufOnVi5ciWWLFmCFStWxKKNnnnkkUfIVYFIaSKZMPjfynDaym5sacOvautDhQZEZC8wVSlPn0shCxE3q5QtbZUJvHv4DB6+LRhclZ3pw3SJ4A4XH4DaT8/gpT/oVfH67MzXrtXUGF4T3jOxIXMjeKiyGHMnFivTuPEYBkKlpAFg/4lmqf/tM/eU4f8bGxxvspRbfG5c3k0jUrwU/uD7UDXZrj/QiKmSIjH7TzRjEVfQwUQwcwJvwWfXdaJZXY0QCFp31ywYj8+b22w5X2WLhADsFlqGqmSyeN5YCwi2gN3V0IxxRbkoL8y17VaIpIJlzwu6hobubsFOhXLVnoXuvHnzkJWVhb/5m7/BxYsXMWfOHBQUFOAXv/gFZs+eHYs2EkTKI3sZql6QkUwYssAiN9hLSYy8d/ouj6qU56KqUq0Xv9gPqt+ohONL79Xhz8cPdqxs5YZMYAUALHvP3dLKeHLdR/jpmx+FxIuqX7zy5NThGFuUqyyIsWJLPaaW5Wv5IwdMa87lRf9+QPq9//nvB/HpFxcwt6LY5jbyeXMbAqaJ7MwM7D9xDv16XYHS/j0x48XIFhk+AD+7+3qc+foSntv8meN3DQBjirqqprmVk+WLXGz55Iy0apkJYEDvLEuu5C2fnMGjEn9VWVW8JTPLUHOP1RL6o9uGKK31zLrL+98ydyDVQlX2/PHPDxB8TnIyM9Da3hG2+FIttJ2OlcyWPa9iVNfQQBbs5MufLyOs9GI/+MEP8IMf/AAXL17EhQsXqLQukbLEYzUuexkCzqVIw50wdh9rdhV7BhBKAyWmsnL6rQ/AA51pu3hkwUJVN/QPJdBnyPray0RR3DdHmZ5JFZ2vy9I/LUNL23fwZ12GhasPOlpc//KOa/DcO58pA7iqVx9Eaf+eKC/M1c5YoMJnAFNG5DtahwNAyJLteu+NYIAXALxz6DQOf3FB+V3mOzuvohj3VxRjfEkf5W5BOAF/st8/+eZH8BnO35UVDcj3Z2GRJKMBYC9yAYe2GoY1f7XsmfAZwKxxAy2ZDthitLZ6UkgoZ2f6sLNBXvUv1DbYrbv8wuLAyXN4ZuMRpYBwq0AXjvgKd6GdrJY9r2JU9/rTzYIdCckeu+JZ6La1tcE0TWRnZyM7OxtnzpzBs88+i+uuuw5/8id/Eos2EoSSSIRqpKtx3VLA4stw8eqDlsT14gsykglDp6L3gkklKO3f05JxYXtdk1JIBf0vB+GNXcfxytZ6rKitt/RVY0ubbUv99x99gcaWNkdBWzm0n71vhBy8PE7pmdjL1amylRP/89+DFj43wZZhGJh94yAU9M5SnscEcPey7VhcVRpxxoLZnBXNScTrXq1pBkXxzNEDbAFequ8v31qP5VvrMefGQryx64S0DREarS2/Z/7XfNcaRjAl24gBvUPBiPz4AoCyAX5P5xExDGD04NzQc/3VhUvSaw2YkPois8Xo+JI+Fl9yHcR3APvf+JI+mFZeIBUQsgp0bsfVIdyFdjJa9sIRo7rXn8wW7ESQzKnhPAvdu+++GzNnzsRf/MVf4Ny5c7jxxhuRmZmJpqYm/NM//RN+9KMfxaKdBGEjEqEa6Wo8klLAXkuRepkwxhbluYq1ZZ1bqXy7VdZQnxF0QeArkIl95fbCV/X1L+4dae8bE3j67Y/xN3ddJ73e+ZUl0vRMsswO//J+g6eKYYBzv/kM2Ko17TnWjIcVqZjEIMBweGPXcZQX+jFr3KCwRbyICYRlZdYJNGMuIF58bWWYJrBsziiYZpcAzfdnSfLcDsL4IXkYW5QXsatI9eRSW5YRL5ZqtuByq+Smwqn4jOxZ0M0R7Sa+xAW7Km/1V62XbIsLkWSz7IUjRnUNDclqwSbs+Lz+YM+ePbjlllsAAP/+7/+O/v3749ixY/jNb36D5557LuoNJAgZKvHU2NKm9XunF2A0z81ehjw+wPaZrBRpbfUkrHzwZtRWT9IW8MzHT+fB5tvNxHWGYYTa+FBlMbZV346yAX7HvpJeI7dFruprmPZ+AID1B09jwpLNWLVLnuVg/q0l2Lb4dkvfNLa0YXtdU+haivpm489vHoxXfzgGd5Xlh7Z1MwwDowf1du0b1i6Da1/ABOq+vBC6z/n+LIwenIu7yuTFaEzh9+HA3yN+TPzvPy1DhIeOOj4DWPvwBKx88GYsmFTi/gMHMjp3G+4qL8DUEQXKBdPrO47j0ZX7MGHJZmz55IxlDKswwN1f7vOajYdRvVoojWt0TZJOLhX8givcqnleRZLsufN63FW7jmNizWbMWb4DE2uCz5z4LmBi/5HX94a+4wSzREdD5PLPdTjI+sitn8XrVxkadL9HJB7PFt2LFy+iZ8+eAIDf//73mDlzJnw+H26++WYcO3Ys6g0kCBmRbhtFshrXsWDyFpJFk0ttFkjAvRRpuFtBYvDQroZmPL3+kPS7fLudrDFOfSVzGQiYwIwXt4dcFGwWIgMwYWL2jYPwuiRtlwn9VEqilU9WrvR/3TXckrN3/JLNyv7LMAxLFD0P77oBOJfo9SFoDWc+lqzilFcNJFr7mdWRPw5fgCMcDACP/cm1qLy2H377wef4N4dUatLfd/ZzeWFw6/8HK/SD+ERUz4NjFgsEXYK2Lb4dtdWTsP5Ao3LMV08pxbTyAjy/+VNLzmHZoU0TeGHOKOTl9EB2ps8WEOgD8PycUZaiK7J3i8y3nP88HJEkPneyMeB0XKddLfYuEPMEx9MPNRqBXuHujulappPNgk3I8Sx0r7nmGqxbtw4zZszA7373O/z1X/81AODLL79Er169ot5AgpDhJFR1fGd1X4CyYzmdWym6EJzUFlYNC72sI31BOl0nLwSv6nUFfr7hkFYUt0xc6/QVS0c0fdl2ac7QRZO70jaxQLhHV+5zvD6dhYtsshbLlYp5S/9jv3rbnq9U1dreofR7dNuaNhAMmJo1bpDFx/JXtfWeK57x90i2Le4DsHbBBACw9L8uzOD1j7//FP/3Pz/FvIpi7d/93d3XIy8n0yL0dC2afPCUD8CPOtPEqZ4Hp0p8gDWX8dQR+fiHDYek4nLEgN4AgJUarhjMsszaI3sOpo4osPxG9ryosi+suG8MsjMvD/sdoCrCkp3pw8X2gONx3Rbs+f4s5F2ZGD/UaAZ6hStGdQ0NyeybSgTxLHSfeuopzJkzB3/913+NO+64A+PHjwcQtO7KKqYRRCxQiS8vVb/cXoBOKXZk5wbgKLpME3hm4xFMKy+wBJwwvATWqYK7ZL9XBWl5sSLpTBYyYchHlS+qKsXA3llKn1YRH9zz8OqIKjGyff/n9oILQDCbwuwbu4K/nHw+Vef8yzuuwbVX9cSYoi5xxN/n+yuKsWJrvScxeuf1VzuKyACAi+0BjC/pg5mj1VkeVFZF/qOAGQw+0/FNNQFcc1VPjC/pY/lc11fWBDDnpkKs3BkMcHvpD3UY1CfbdjxdDHS5y7gFLtY3tSoza7C2qxZ04Vr6Glu+sdybe0YPwB3D5W4vDN1Fu/i866Czq5UoP9RoB3qRGO3eeBa6f/qnf4qKigo0NjaivLw89Pkdd9yBGTNmRLVxBOGEzJrBSm0CelYA1QvQzaIgm8icMhcwVC9rL9t0srZVrzkY2raU/V50Z3Cz9njpK4abMHxm4xH8dNpw7fPp5OH1EoDErLumwq+RiVxeXCyaXKodVMYyMji1mflQe8l1vOHD03h5Sx3mV5a47mSosjxkGAZ+Om24tLysiNguZpFc9l6dRRyKlmaWv/VEcxtmjSvEKkWGBobPAFbuOOFapY/hlifZRJe7zKxxg1wDF2XjxkBw3I0Y0Fv5fOiIJplA/cc/G4n7xg/GBw3NGNtZhMGJeORonde58JL1D5C4TAoU6EVEE89Ct6WlBZmZmTbr7TXXXIPLLgsrLS9BhA0/6ciEpkxY6lhJdCwK4oTntrUKqBO+e9mmk1bA4v6t+j1rL7t+nb7wYmVWWY4ZHaaJry60Ox4D6Mr0IObh1TmnWK5URJbxAgDm3FiI+qZWvLXvVCg/qpiX1OneehEAlUP7ufpsiizdeDi0E8Bfr6/THcZpoWUgmC2icmg//PTNjz1Zk30A1iwYj/LCXBTmZUsFj1slPhmGATxQUWxz4+gwTexuaAaMZpimibFFeVoWdgZbzLAiDPNvLcG0kQWWxfD2uiYU983BkpllWLz6oCU7hInggqy2elLYYs5JoJYXugtcIPY5WsU2PlQxBHMriqTHToQfaqIENpGeeFams2fPxve//30sWLDA8vlvf/tbvPXWW9iwYUPUGkcQXtCxAuhaSaQpdgyg6cI3jil23ESubpCN0zadzoSvKn+qSjAv64twEq2zcqgnzrZZgljY9d9eepWy2AIQrAI2RVKy1QnZRDy0f09p8QAfYMlh3PlPrNx5wpY+S9ZGUez6DOC52aMsrgpuiwOVuwVLlyULzguYsAQNnrv4LWo6U74t3XgYvbMulwb98dchsyYbBjBz1ADHhcHF9qAUlG/He0ulZQD4++nX447hVwOArdS0AeDRlXsti4uae7pchhZNLg0Vf1AhK8IgCnL2t5/dfT2efPMjy+/DXRyz70VDoOq+E8LJIy5r46u19ZjLFYORVSuMt8ikQC8iWnhOL7Zjxw5MmjTJ9vltt92GHTt2RKVRBBEOzAqgSvfiJS2YeCxmaXt05T5lih1mJZXx5NThyjRhXlPgiG1j+T5Fnl5/yNJWWYJ5cduY9YXX9G18mqIZL25Ha/t30ntRXpiLebfIg51YFTAvExpLP/Tl+W9gdl5NY0sblkrEkM8IBoiJfcf6wg0TwIO3DLGkYFs0uRR3dVpaxX6YULMZL2+xByCpUs6tXTABj95+jfTcPgMWN4Glmw7b7h0QFG+ylFN8irLti2/HC/eOwrI5o7C9+nY8fucwzBo3UH5eBPOn7j/RjO11TQBgSR21+1izq8gVm3N5hi8knMSUdoD1XpgIWmjZuCsb6Hc+GQc/ZlXuPqLIBeSLYzEFFw+fAiuStIU8Ou8Et3apcGtjuMeNBfn+6KUqI7ovni26ly5dwnfffWf7/Ntvv0VbW3i57ggiWjhZAbxaTvmiAI+8vtfVl1DluuAm4MLZphOvc8snZ6QuA3xb3QK3+L6QCRhVCjXAHoTHyqGuWTAeuxqaMY7zSVQFZOn45PLItsx9RtDvUHadP5t2PQrzslHcNydUprXpwjeu2R9CxwYwdUR/9OmZ2WVN3XQYvbMvD+XytSwkTGDJhsM4f/FbTLy2b6iv6ptaLWnH+EUAACyVWF2XzOwqees0jmeNG4TszAzbNYnR9HeV21OzifD5U/n+ZVbSVbuOo3r1Qcc+E0WuCbWv+1etl2zp3ICghXb9gUYU981WBhKqdjg6TBN7jjXjVEubo7sPfxydxXHl0H4AgF/V1oes0j4DWHCb3N2GBcnp4vZOiMRyrNoROvD5ORT1zaaytkTa4Vno3njjjXjllVfw/PPPWz7/5S9/iTFjxkStYQQRLqpttnACHPL9WcjNsQfByASyamuYFyky+C1/VZCYbIuSv04mGGT5Q1lb3Vwe+BRpMgGjSqH2gERYdpgmXqttwIrao9KsFTX3cH6mcPbJlV27asucZQ2QXedTb34UctNYNLkUZQP9GJSXrewTo/P/MEEUQDB9F2C3hDstJJa9V4dl79WFjsm3YcRAe9ATn8OUrwrGcBvHY4vylEKGz2ig43Yg/oldb2n/nrZcviIGgAdvKcYrEj9cma97Y0ub8l6ocuICwWds7YIJUncZw4BlkerGc7NH4a7yrnRhqkXFa9vqsXyLdbEWMIEX35PnD77YHvDsZhDNRTtPvj8LiyQZKZ7ZdAQDcrOimu2AIJIBz0L36aefxve+9z3s378fd9xxBwDgnXfewa5du/D73/8+6g0kkpdw/MMSSbgBDgdP2q1IKoHsJlJEZH6DYnolXV/ZfH8Wpo7It+XMZW0Vr59PMJ9hGFg4eRh2H2uWZgRgli7Abr19tdaejsoHhEQu+55b1grd/pk1bpBr8YAbi/Kwo/6s7XPWFubn6TOAyTf0t5UK9hnA8vvG4OS5NkumAtkpmRA4qLA2qtrwzCZ10BNvdQXsz5rTOHYSMtNGdrlZOPWhUwnfDtPErga5y8Lfd+bVNU1gTFHQQr1C8MNVPTvsuqrXHFSm/pJhmkEheVd5AVrbv7ME6imvT/K3DMMItZmhWhy+ssUq3hnM953/eoZh4MDJc/jBivc9Z1CI5qKdp2yA3QWkwzTR3NpuC4ikbAdEquNZ6E6cOBHvv/8+nnnmGfz2t79FVlYWRowYgVdffRXXXnttLNpIJCHxSH0TC7wGOKj8PRdOHuboisCLFKdju20Tet2idBNBqgTzB06eC6ZhUggDZumSRfYHzGC54Fe3NoTO+UBFkZYlD+jybZZZsVXX7mad3tlwVv4HgYAJbPzwtPTzeb/erZ1WLDvThxqXICkRp2p6PKpnTTaOG1vasPtYMy58863j+QC1iGMWdpZ9QsRnAMUS4WMA+N51V9va72VxybsLHTn9NZ7b/Jmi97rghZgYqKdi8vX9sfHD05agN1V1QtmiwaktCycPCxVHYf/mny0xM0Q4RoJIsxJIq7cB+OlbH9lELmU7IFIdT0L322+/xfz58/Hkk0/i3/7t32LVJiLJiXXqm1jjJYJYZfUaMbB3xO3Q2X4MZ4uSVSkTfWMBtRWeWZtk8JYulSVp7sRizJ1YbBHQbpY8t6IXTtc+vqSPYyozrxZB6ecav2VCQFVFze23MlcQftEoe9YWrzmI7MwMjC3Ks1j/mcuJqh2yKnhiqrJ5XJqp3tmXK/2+H/j1bvsJDODL89/YxpfXxWVwZyILowe34YV3P3MUrDLfVT5QT8UGYXFjGAj53YrIrJ8y2K7HrHGDLCnNVEU+xMwQXokkK4Ht3iM43i3+7uhKLScjkh29eO0Gptquo0iqtz9Z8CR0L7/8cqxevRpPPvlkrNpDpADRrlqTzMQycXmsKhOphFM4bgCybXG3bXOGOJE+IKQvskXBrz4YKg/Mcuk6XTub6F/Y/Bn+TUjJpVtEQobub/lUaC//Qe6bqcKpmt7i1QdDi0apSDKD2T/4e8j600nkyixzTmKJt67qVLMzTeDuTh9mPi0YYPXDZXlsdQSvajFTdUN/3De+SMt3VYeACeX7iwURqjAAPFgZXOjJAjW/unDJsZBKuEaCSEWQWyAgn1pOJJIdvXjtBqbqriMj1dufTHh2XZg+fTrWrVuHv/7rv45Fe4gUIJbiL9lWsJFuEUZ6bK/nV1nbWfCQrhuALD8sw2sZVBaU9srWeqyorceSmWUozMu2R8GDC/wyg4n7F00utWwDy6595U553lneV9IHYNaNwXKzTvz5zYMwaVg/PPib3a6WRCZymRXRDSbeRwzojexMH1rbO/BBw1mpte+12gY8MXW4a7U5nYwabrmJVTscXemyvCtHE8GFCy/gwpm4Z40bhHNtQVcEs/OePjypBI/fWSr9vpdKeSJeMyMAwfase3hCyOqpylNtQF0MJBwjQbREkFMgoOqdHsmOXrx2A1N91zHV259seBa61157Lf7u7/4O27Ztw5gxY5CTY13t/vjHP45a44jkJFbiL1lXsLFMXK5Kws+Lfd6yFuisFqVCZW2XBQ+p3ADY/eSjz0W8uH/IgtLWLBivVfRixMDeoVRgsv5xC0rjBTsA17K0//r+cby+4zhmOBRREMe7jhWRF5viOJexovZoyIVgycwyZXYEdg9zMjOUldu+C5iufsAiFsFmOFeFA+QizgSwu6EZd5XbC0voTtzMR54d2wTw0ntH8YObByt91GeMGoDVe+SlkJ1QWS+d8mNXV5WGRK4sTzXDBOAzg8Uynnrzo4iMBLEQQV7e6ZHs6MVrNzDW54m1QaY77ZrGA89C99VXX0Xv3r2xe/du7N5t9dMyDIOEbjch2uIv2VewXoRdJMdWif0tn5wJu6JbhmFgXFGulhtAtMW86oV9sT0gLcHKw2eLUPXPosl29waegAn0ubJH6PeWrBOAJX0Y/5t1e0+F0r1dbP821C/ZmZfb+kcnbRtv/RXHuUxEilvpKqMqi+hfulHtl/rMpiOAgVBAlNsisrGlzeLryyypLBMDn63DB2BeZTEK87Lx5Dp78YVzbcGSz+FO3F5/t/9EM9bsdRa5zLqqKzZzMjOkn/+PCYMx/9aulHhuC54AgJJ+PSM2EsRKBOm+AyLZ0YvlbmC8zhMPg0y8+qm74Fno1tfXx6IdRAoSTfFHK9jw3A5kUeKyibS8MFc5wfLWCTG1WaQ4vbCL+mbjkTuuwXPvyCPrxcwWsv55ZtMRS/EFEVbZi5VtlmWdUOUePnG2DXlXZuK6Aj/uGN7f0g7ez1TsczFtm5v1l21t8x+zPnLyvZVF9MvoMM3Q1j/rN6dF5O5jzbbzmQDmTizC6EG5Ieu4aGV/at1Htt899eZHuDzDJy1PLJu4RUuZavxcbP8Wy7fW4caiPIvbgCoYj4l03jdaV2y2tndIP7/z+nzLv1UFY8TrHV/SJ6JFpUp4h+N6IaLzTo9kRy+WrmDxOE+8DDLx6qfugmehSxCxgFaw4bkdyF58KsuM7PNYWydUL2zeQq2CZbZgKbN2S/xZO0wTIwZ0uTcc+PxcyKeXiQ4xul2czMcJuVMZj67cG3J/cAvoE/v2y/PfSLNeqMa5mJKKTWqydG4A8Jd3XINrrroShmG4uk34YLc2O40fU2E+/tW2Bvzz9gZLPzLy/fZiKYC1Sp7bxK3qW97y7wNQXui3ZH24Z/QAPH7nMOWCwGcAfzvtOvTJ6WHJa60rNnXfTVs+OWP7LRuDsqDNcEWLSnirXC9iQSQ7QLF0BYv1eeJpkIlXP3UHwhK6n3/+Od566y0cP34c7e3tlr/90z/9U1QaRnQvnFawyRagFivCdTuQoZpI+c/3n7AWh2CZD6JtnZBZUSfWbHYN9uKrtKm+ahiwuDcU9c3GgNwsNLe246dvfaRleVEJB75fdCzr7H9OiwfVOBdTUrE2yqyEhgE8985nIUuwEyGrr5AT12n8jC3KU1omnfpx1rhByOlxmS16ny9PzMYBC8Zjlna3UrusQaYB7Dl+znL81XtOYmRhb+l4MhB0vXjqzY9DldrmVhRb7pcbOtY1meXdZwQrtqmqHYZLshgFIhHrsXQFi+V54t338eqndMez0H3nnXcwbdo0DBkyBIcPH8YNN9yAhoYGmKaJ0aNHx6KNRDchERbHZCIct4NwWbXrOBZJyvyaAJ5/51P8fOYI5W/DXXiYnTJA5cvIApp8BrCwahgAuJaZ5f8oRryLv1NZXnQi9XUt6zpbmypLjWxSE62ERuc1h/xn1U2Gga48qHxOXB/cC57U3KP2n3ayYI0Z7Lwoy/dnSf3NZVk4OkwTuxuarQFeigtu+tqewkscAyZgyfzh5T1SObQfnp1dDp9hSKsdqtLAfd7chqkj1EGdbqhKf0fyPuguhoNYQC4FqYlnobt48WI8/vjj+NnPfoaePXti9erVuOqqq/CDH/wAkydPjkUbiW4EP9kne4BaLPDidhAurF9VrNx5Ao/eca30HOEsPHQCyDIMA39x2xC8+G4dAmYwcOqrry+5bsubCPqKAlBGvPPncCo9yxdOME3YrHM6lnXV1ibLPsCf0+0eSv1zFSmqZJjo2s7m03QFTGDppsPonX258t7xpax//MZeyzX5DKDpwjchayyPmxBQPdOyLBw+I3i9bmMAAEYU+vFARTFWbK13XQR4yfhQ39SKg5+3hCziqjGvWiw98vpeXLj0XViLc9lzUzbQj+K+OY5FYbwcM1qGg+4knsmlIPXwLHQPHTqElStXBn982WVoa2vDlVdeib/7u7/D3XffjR/96EdRbyTRPYmXP1S8X9Ju53NzO/CSdF92TrfocCYexWOHs/DQCSDjt9d5d4EVW+uVuUcZTGiqromJD93Ss2zy2vLJGVSvOdiV1soEDp/+2tWaoxI8P35jL062tKFsgF9538RxIQ1cU1irVRz4/BzGl/SxpenSuXf5/mAp69b27yyBdqZpL1jBt79yaD9bSjiGWxYOsc9PNtvzu4oMystyzXssIrPE833PC0IeVb8xgS+62ZjQe0bE94HsuVnSWWLaZwAzRg3A2r0nPQnWWBkOutOuG4NcClILz0I3Jycn5Jebn5+Puro6XH/99QCApqam6LaO6NbEwx8q3i9pnfOJEx//b900Y07nlFUc41H1cTgLD9VvBvizLFvBqjKpD1UMwfLao1KxKwpN2VhhKcJ0S8/ygUq8YmGCpbZ6kmNeXyZ4xG3/gAks2dAlVMT7piqHLLNy/ujWEvzyD0elWSZEntl0BNNGFuA1oRwzoL9o5PM4P/L6XpvvcuXQfhGlv2OZMUr797T1ubgoko3b42fbHNsvWxjwY1z2fDhlslD1W+XQftIFiFM/h1OtMGDCkidYV7DGwnDgJp67k6WXSF48C92bb74ZtbW1GD58OKZMmYKf/OQnOHjwINasWYObb745Fm0kuimx9oeKt2uEzvnEiY+33IgTdtgWVaHiGI9TH4ez8Dh4ssX2mQGEtsOdRF2GYWBuRRHmVhRhz7FmnG1tR15OJgbmZtnEq5N/czjUN7UqfXzHl/RR3i8mVGRBWQw+uK21vQM5mRn2MsBrDmJb9e22ErgBE3jpD3VYVFWKr75ux/KtR0PtVPkl725oxvKt9bZ2+DoD+XTI92chN0feJyt3HsfzncFx/PXx45IXPGIuYxPBLX5V+/msGp+d+Vqar1cFCwhbf+B0qHAJP8b3n2i2+KoztxmdQEkRVWEJVT87vQ+8VnjTEayxMBw4iedwFuUEEQs8C91/+qd/woULFwAAP/vZz3DhwgWsWrUK1157LWVcCANa8ToTS3+oeOfudTufbOLjLTderUVO5xQrjgFQ9rFKpOiUI166UV4aV5zc3dJPTR3hfj+iOVZ0RIGTUBkzONfRxaDDNDF92XZpDl12rNe21eOJKdehtH/P0HfZ35ZuCLp5iL+T5eOFIW9HxTV9tVwonPoEgDQPMj8uxSpr1VWlqK2eZPP/lbVRLBrSdOEbybfU/Oi2ErS2d4QWTGKga7UkIFMVzMja42UhCAQtxLLvO70PWLVCp4wjIsxNRUUsDAeq5yQ709ft4iuI5MWz0B0yZEjov3NycvDLX/4yqg3qTnRH36ZwiJU/VLxTxbidT6eUrIhbe53OKfar7taqyv9SRHU9KktpNISql7Hitsic1xncxBca0PE3Zemz3G6lKfx/kRVb6jG1LB87G87ahbDieA9VFuPVrQ0WISPLhAAAtZ822QLK3FKjuW3rM8SCFyExy1w4TKBsoN/xOD4Dtj5XpT4TP/MBmHxDf7z0Xh2WvVsn9SdW5t1FUCC/9F5d6N4vrBqGEQN629Ki8diCGhEUufMrSyRn0Xv/qLrnpuI87Kg/a/mMuak4jf9oGw5U4rm1vSOuRgSCcIIKRiSI7phRQIdoWLh1jyGbmB6oKAqv4Rq4WVRUFY9U6FhkvFpx+L4DIB2jtdWTtCqoqfwxxUh6Mf1UPMa/KOgeqCjG/Z35VcW/PVQxBHMrimw+hyqhcuDkOdQoLNmA3ZdYRQCwWHLd8AGYO7EYcycW24TMAxXFNveFAIJV4aY6lCfm30mrdh3XFrluBS+WbjyMBZPkApAxu7MQB2Adl9VVpcFKb9x3DQN4sGIIpo7oj4vtAWRn+jDjxe02d5DS/j1RXij3CWdUXNsXL/2hLlTueGHVMMyvLNEyTHgRkk7PplNmFB+AP795kE3o6grJaD9jsmtubLEHEXa3AkBE8qAldPPy8vDJJ5+gb9++WgcdNGgQtm7disGDB0fUuHSGSt7aiYaF2+sx2Ev6tdoGrKg9GnaeTV2cJkJV4QIRnwE8N3sUxhTZ83l6PSegTqM0r6I4ojGqmsiBrvKrPgO4P4aLC0Ae3CcKuuVb67Fiaz2qq0otxRUCJvBqbT3mVhTZ8vRWV5Vi0eROCyesJXllcWI+AM/PGYWBuVkWEQaoxa/K4iiz6M6rLLb4LPPcL6TeYjy9/hB+vuGQYy5bWfo2GbJxWdw3R5o5IwBg2Xt16oMBeGPXcTx6xzUWX09WIEPm6rGi9ijKBvbC2KI8ZV7bu5dtx+KqUkwbWSDtcwPA1k+buqztnW4i1/TLcSxowS8OvSzUVc+mUxaRJTPLMLYoL6mEpGx3iPLNEsmCltA9d+4cNm7cCL/fr3XQr776Ch0depN2dyVZqtskC9GwcEdyDBaoEu65vaCyqKjGxF/cOsSyjfrzmTfgrnL9JPROFm6nNEorttZLxYCbLyCPaiKvHNoPr22rx/It9Vi+tR6vxmhxIVv4yAQdEBRPTLTydJgm9hwTChcgmO6JbZkzy1/ZAPl2vA/AknvKQsUDRBEwfVQB1uw56RhYBgBPTh2OsUW5NqEMAH1yelj+Ld53VREINt5luWzd0rexdqrGZb4/C9VVpaGME3x/uFmGAybwzqEv8NSbH1n63en7LO2ZLFczY8nGw0DnWODTmRkA5t0it3zzJYcZHaaJ17YFF0iiCPeyUJe9D1S7IWsXTAgFWCa7kKR8s0SyoO268MMf/jCW7eh20IrXSjQs3OEeI1ms66oxMWvcIPz5+MFhTRhOFm5xYSASADBn3CC8vvO45XMdX0DxumTf5S2M4tZyNPBSnIAhs5QCwNmL7Y4WV9MMiuS/nXadzYLJIv/56xLL4c540e6iIGvjdwET5YW5WCQRj/x9kd13AEoF3WGaOHG2zdEvWdpngmuHjPmVJYAJi+X7L24bgmXvOlt0AeBvPGRYYATMrrRkKleLpRsPY1v17dhefTv2HGuGaQJjioL351VJKjYZPgNYvkVeoCLSxXK+P8u2WyBmEQm3aEQsERdX8XJFIggntIRuIKB6/RORQCveLqJh4Q73GImwrqusrF7Kw+qcw8nC7Rb8lmEYmHBNH5vQ1VkEuPlJq7aWpy/bjpp7omPZdStOIBP5KgGcm5XpWqghYAJPvfmx5TMDQZEpEyHsnsr8WE0Atw+7Cu8c/tLyOROzBf4rbMfrME2sP9CIcUW50nRlYrU3sZ18yreHOv1d+cArWX5gk3PtcGL+rSWYNrIgNK7rm1q1hG64sLRkaxdMwN3Lttv+HjARym7AMnqwMcsLTBG+AMn9FUXStG18G8JdLK/adTzoQoOu3QLxmUi2YOZkaw9BMCgYLcHQijdINCzckQRexcO6HvKFPdkSsjTJJoRojQk3S3Vx3xzXNEqyiH2nErCA3oSnSsVkInpuI04LmPElfULuEyu21Fui60UrYIZhYExRbnAL3iHITIYJ4A9HzjhO+Kq+EEUu0Lld3ulPLuPp9YeU6crc2slXTVteezSUo9ctP3C4QVCyrfnH/mQo/s/vP7H9ln3XbbHB4DOLVN3QHxs/PC39O0McswsmlWDZe3UWyzxfgCQ704fjZy+GVXjFDVmmimc2HsG08q5dlGQLZk629hAEDwldImmIhoVb9xhOabNYCqH9J5rR2t4RlRzHOiVFAW+BLG6EY6k2ADx/rzWgyJLg31CXgAWCEx6f+zNgAtWr7S4JIQuhpE+i5TbitvDJ92fhiSnX2bIU9M66XPqb+beWAEZXQQGjs8PcCpRt+PA0/uX9Bnxv+NXSaxLb6YaqUhxD9icvxQcA6zXxY1S28AlH0KnuTeXQfvin//xE6qe+7L06R4u0AdhcLhpb2rBJELlA0EIKANvrmqQFO1567yiquaIqvOuAGJTIngmjU4WbsLt9eEHHlSpZ3K0YydYeguAhoUvEDZ20X9GwZrodQ2V9qK2ehONnW23iK9JtODdfWDGoJVrbfm5CT1b9ywTQ58oeUncKpxKw7Pu7jzVLj3n3su1YKrgkMB9DWQqtAyf1A95UNLa0oTAv21YG2M2P0GmxNL+yBNPKu7bgAWDljmN4brPzNvyT6z7CU+s+QnVVaVAwC7C++H8ffI5/3XFccoQuNLQwAOs2+89n3oC6Ly/gFYetdifEQgaqlFiq51v2N1U/i8dfWDUMNRucLekmgBfmjEJeTg/LsWTjEQCONbViYs1mpZVYVlRFlrHDBOAzg+cePTi4kIvUFU1ngZqTmSEtDpKoYGYKriaSGW2he+rUKRQU6Ed6EwRPMvlvqawPuxuaXa2u0bLQ8IhBLdHc9nMSbV4mp3y/ugQsb7UxHVQYf01iXlTRJUDcqvWKbLyNL+mjPQ6dFkvi3+69aTCe36y2NjJMdEX8i0UEVBZ/EVkeYhn8Njsv0lZoBFr5Oi2U4tf+48BJFPXNlo4pp351K0LBb8fXN7Wicmg/i8D8QFIwQ3a9owfnhq5ze10TivvmYNtnTdLvv77zROi/Va47sqIqUt9yAHk5XYvDWO9EsP7km+Hr9ONNlPVU120sHpVAqdooIaItdK+//nosW7YMc+bMiWV7iDQk2fy3VALPSUBEsg3nVLc+wzDwZ+MGYiU38UZ6PhGVaBMnJ7fJUkcYqypXAV3XxOdFZfl6Vd8NJ+BNNd5K+/eM2jiUpe7SLde6dONhR39LJ2aMHoAbi/Mc3Rx8gC1CH7C7i8ju00OVwYITb+07ZVt8vL7jBN7YeSIkVJmofPvAKZu7CuvXL89/I/1baf+eFrcgVo7XRLBdfECiYRiQIVqsRcEt/5Ua2fEY7H7nZGbExXKpWqCqxkrADI6r3lmXJ8yA4OY2plrwRFOYJpNBJRnprosAbaH7D//wD5g/fz7Wrl2Ll19+GXl5ebFsF5FGJJv/lsr6oCqVCkQ2mcnOt3DyMIwY2BsHTp7DUkmAU7y2/WaNG4RzF79FTaffqdNkqWO1yfdnKYO2DACfffk1nnrzI4vwkeXrdbt+pwlNNd7eOfSlchwCwAcNZ2EYBsZwlkHZpKA6N194xClwikX8O/lbqli79yTuGz8YtdWTsP5AI55ef8j2nefnjArl6+VpbGnDZ19ecHR9eHVrA+ZOLEbZQL/077yI5RcsIixobnntUekuwPQXt8Ps7L9FVaWo2dBV6cxE0K+bLUDGDM619aXRmbJNtFiLbgUy5txUiDd2nrCNtzULxuPz5jYETBNji7rmN/F+zxg1AOv2nop5WkjZAtVprCTagACoF9Wqxee5i99aitRE00XMqT+6o+DrzosAbaG7YMECVFVV4YEHHsB1112H5cuX4/vf/34s20akCcnov6XjH8jwMpl5SRvW2NKGH6x4357iClCeL9ov6MaWNizddFjbbUIn2O/YV63Sc5kAnnzTnhc1gGA6q1dr67WzZThNaLLxZgB4/t3PbMdiJXvnLH/fUqxh5ugBWLv3pGVSqBzaD7uPNSutl/n+LDwxdTjmVhSF+kdmGRXHvlP2C1tfmV0p2MYV2QUg28IX4S2mDCeru9MuBCug4WTB9iFYhEUlqvkMD7zI5du2u6EZd5VnhSzm/CS9aHKpLVBUZ8HgM4BHb78W5QN72xZsh09/bRMClUP72cbaur2nbG4h8cLpvgDJGwCmWnzypZxj4SIm64/uKPiSbVc13ngKRisuLsbmzZvxwgsvYObMmRg+fDguu8x6iD179kS1gUTqo+u/lYh2iW0QE/l7mczcXqA6/n6A2iIXzRc0E8xnW+2FEFg+1qkj8pUuD04i9HXBDcONDMPA3Ioii0B06m+3Cc3mkgFr+iyGD8DCycNsQssEsHrPydC/AyZQveZgKKJeRJxM+f4RMzVEY+wzi6dh2EWuyi9S9OlUwfumyvLmsu+cvdiuPF6GYeCBiiLtwDfVcZjHAgsqZBZctgsiPgeqBY7BuSQsnDzM4ge8u6EZMIBCoSwzEwLPzi6XjrWL7YGIgyVFdIN1nTJ0JNKA4NT+gydbbN+XCfZou4iJ/dFdBV+y7arGG89ZF44dO4Y1a9YgNzcXd999t03oEoSMVCqO4STkVITzAlW9mGUWuWi+oG3pkWAXG0+vP4SfbzikJaZ5/8WdDWc9tUWW8ks8rjhx6kxo/Hj7qvWSLfcrEFxQ5OZkaglAp+1+/tyyNouZGmTb0ZqeC13tEdrkM4CfThseSlMnHl9lATQMwDDtabkASN0x2HeyMzOUbbthYC9MHZGvFfgGoGshIrRr9OBc2+Ju0eTS0FY3YH8OVCnLGpouWgSyAaDi2r6o/bQpVMJZvMdBv3UjLrtRXhax/Ng+8Pk5Wwo0AKFgvHi9Z90qMMrcs350W0mwtHmU+lbHoJKugs9tkZSMu6rxxJNKXb58OX7yk5/ge9/7Hj766CP062d/qRKEinAEZKoQzgvUi6U7Wi9omR+jAbl1RUdM62YLEPEZwHOzrfl6VceVRerr9Bsbb40tbcoFxVv7T3lruIAqEMopu4CI23a0DgEzWJXtp29+bEthpjo+vz2vEuG8O8aeY802/1UZ+0+0YPqL2zFzVJf7hwq+PLGsZLG4uJNVLOOfA6cFNe8mZALY+mlXRgbZQsZnAANzY78bFc4ilo2n8SV9LBXntnxyJpQ2LV7b8uFWYKy4ph8G5WVHtW/dDCrpKPh0FknJuqsaL7SF7uTJk7Fz50688MILuO+++2LZJoJIOcJ9gepauqP1gpZNOiaA52ePwunz39iCm5zEtJdsATzsZXxXeZd7Bm+RAOwCR5z4vewQqF7yAJT5Wafc0B+/++iLUDYKMd2WKNQjsbirghUH5mZZ8hYzWDYBWbebsKcwk7lyzOvMriCzpMsQM2Usqip19Cs2O31Zl983BvN+vVv5vedmjwqNA/F+ykojs5K4YsUy/jnwGsTF4+s8BxC8hzNe3G4pJuN1N0rHHSHSRSy/oHPyH48VOhUY3SoURnOnz2lRmW6Cz8t7J5V2VaONttDt6OjAgQMHMHDgwFi2hyBSkkheoDqW7mi9oFWTzpiioLvEzzcc0hbTbuLhz28ehH993178gBc3gN2V4t4bC7Umfi87BLKX/Pa6JqUA++/ji/Dk96+zWMrEvuevIVKxopqELlz6zpL+bV7FEMytKLK0R4aYwqxyaD/84t6RgAmLOH/7wCmYnJVWN13b0o32ADIRlulChQGExh1gv58qS3TV9V2LEKfngBeZOlbzDMPAK/eNtghzJhxqqyd59snVdUeI1iL2V7X1tnviddcnnGBXt/a7vbvivdOXToLP63snnXdVndAWuv/5n/8Zy3YQREqjqsIVTaLxgnabdLyI6RwHP80Mw8D/N2YgXt9xXCmqAXvJYBPBZP66VZ/cJmZZFTSGKtuBz4CtWEA8tkRlk5B4XgCWYKo9x5rxsMT/OGB2pTCTCS4AtqwJrC900rWxRYmb2HUMTHRJdJvvz8KiqlIsEazuv/voC9fnTHbNquA6oDMwsWoYjkr8paPhIuRkaYvGIraxpQ2v1tZLrys706flsxtusKtO+1nlv10NzRhXlGvL8RzvdF/pIvjS0RUjFlAkGUFEiKoKVyyIxgvaSbR5EdOt7R3Sz31GV8ECtwlQVaIV6NpGVk38bhOzThYMsdCD0fk9r9aQWG6JsvOqrufz5jZlCjOZ4Fq85qC08plqy1uazUBwHzAAlA3w48NTLdquLKYJVwFZNsBv+8wt64FsC7969UE8d+9ILP/hGKzZcwobP2wM9eO8iiHoc2VmKFBNRFc48GLNq6Ut0kWs0g/22r6hbBJO4jXSYNdwi0W4/Y1wJt1cMWIFCV2CCJPGljbXvKrJipto02m7TAD5EEzkzyw2qvzBTBCoSgabAF6YMwp5OT2kE6fbxKw7cbP27W5oDkX6q67dzeoUyy1Rp+uZf2sJzn/zLV58N1iGmJ/spH6uGkLUMV2bJEOBAeDl+8bgg4azeHTlPq1r8gGuAlJmdTcQtFIC9nvS2NKGlTuPS0U83y4DXVXgAIQCuGQsnOxeWleWHcKrpS2SRaz0WTSCAXc676ZoBLuq2q9abJX274mrel2R0HRf6VA4Ip1cMWIFCV0iqUnWF5FTtoF0SFejg8qaICs9y/rCJgiqSqXHZhHvKqux28TsZeLO92fhrnJvQkZldeKvNZpj1+l63tp3KiRyDSO4Bc/aphJAMosuj1O6tqYL39jEbABB6+zYojztDBKLqkq1+kUmWqcv224r6jFDI8sDfwxWBc7N13zEwN6Ox5IJuWc2HcGiqlI8s/FIXCxtsmfx/ooiLBdyGaueAZUP84GT57R2p5zGusr1Zfqy7XjwluKEpftKJ0tyurhixAoSukTSEu8Xka4wccs20J18pLxYE6SCYOMRLK4qtVRIMjpFy/Rl20Ppz2rusd57lYBruvANGlvalL5ruv6Kbu1evPogcnpcFioXLKI7dmUWSdkYPPi5PeF+hmGg9rMzWPZuXegzs7NPWSAa83MVC1YAwSIYFveDTgEcTro2H4CvWi8hO9OHeRXFWLG1PuR28he3DcGxpotYf7Ax5AO8qKoU08oLXO/FB4q8zCbsRT34f+ugUwVO51lWLUJGDOgddraGcJD5c78q5DJWXU++PwuLJttLd/NjSYXbWFf1r4nwyn9Hg+5aOKK7QkKXSEri/SLyIqqdLEDd0UfKacuSF21KQTCwN7Yvvj3kPjAwNyskcoGuSmD8vRctWEykPbpynyX4iLdwTR9VoOWvKCK1SAF45PW90uPojl1xzPEWSf64rEyzyI9uG4Jl79XZPuctYqt2HbcUSVg4ucvaWzm0H/Yca4ZpdmU/0BFlWz45Y3NdMDv7g+EzgmWd+/TMtFQxe5DLGiHme60c2s8m8g1WHi0G8FXgFk0uteXo1X2WnQKC4m1pE8/nxX+zbKDcH9rJuqoz1tmzKjMOeC3/HS3StXAEIYeELhE14rVVG+0XkdPLmrWFvyaVNdGpAEJ3Q7ZwqBzaT+pvyQTBXeVBa+HrO45Jt6t3NzRbXAyYBWvPsWZLvlk+JRSzqGVn+qQlXlX3mMfJ4ieb2HXGrmzMiRZKdlzVwqp3dqa80EFnn8qKgzyz6Qimjeyy9k4dYb/e+qZWAPLcuqpywuK/AyawYutRgOu3gBm0ME4d0d927YtWH+xqPyfyxwzO1cruIMPpd2Khj6WbDody9D58WwkmXtNP2woby4AgXYu/Ci87LuFE8LuNddbeyqH9sHbBBMsClh3fS/nvaEHZCroXJHSJqBBtN4N4vohUL2u+9Cl/TaqJjc+r2p1RLRzWLBhv/zJnsHt5S13QhUGhTlTGvVMtbcqUUONL+iiDspzuMY94v0VEEaszdnUKGDhtrfsAFPfNlgpw5vuqumbVYlHnGdYtvAB0Fl6QnH9XQ7PjMcTFQ809dmsgs9Cv23vKYrFn/1YFzK344RhkZ15uCYy0LAZM4KX3juIHNw/2JCydBGW4BgBdi78bulblcAS701iXjaeae5zz6cYLylbQvSChS0RMLNwM4vkiUgkJJoAA+zXFK9I1WYPxnFAtHHY12FOJsRRTb+07ZfMP5GEZEXicAgJFYamyyi7felQrKp3PzvDjN/YqRSy7X26BSDoFDHhrtyi0AwAe/M1uzBg1wCLuFlWVhiqiefFT1n2GvZQr9nVehLjz0eNyn6uVVlXWNzvTZ8mf+/idwyzPIPu3LGDOBLDjaDOemDo89JmTRVKsBucmLGWCMhwDgCqbi8riH833gtf3muo9DcirG/K7LInOEEDZCroPJHSJiImVm0G8XkTiy9oHYEpZf7x98LTle+I1efG/C0ewJjIqOBKBrRJY44pylcKrxkHksmsXrWROIlcUliwoSyw+oLIEqyxyd5UXoLX9O+kCTJZiasTA3tKxa/MxlrSFt3azhPvTX9weslQGzGCZXVXxBJkIUfkp6z7DqmMysS3eAwA2P+on133kVivC4n7B+l4W/S8+g+zf7xw6bfsuEFy8zq0ocrW+Z2f6Il68RxrE6EasXLm8+hWrqg6qxhPbZUkG4u1DTSQGErpExMTSzSBeLyL2smZb2aLIBcK/pnCtOomKCg43YwBDZeVRFZBobe+QWvcMA3h00jW4Y/hVtpRlqi30J6cOx5QR+dI+khUfEBHvsaovZLmBZSmmaqsnKe8XP+aWbz1q+7tYUKG1vcO2He9UPEGs1ufkp+zF+iu7fmZJFS2uAKR+1Ca6dLzs3i+qKrVYVA0AD95SjLkVxa7j/ye/3afMwBAQ+pQtgMSsFK3tHZ4W77JnIdIgRjeSyadUfE+TDyyRTJDQJSImnfydeHcFnnCvKVzBmqio4HAzBiyaXIqygf7QRK+yxqtEojT9kAk8t/kzvPDuZzZRsO3TJlvbMwxDKXIB+eRrICioeZGjs50PACYn0T5oOKt9v3hRBATHnEzbiC4RX124pC0eZAK9MC/b0crmZP01AFRXlWL+rUG3CJUlVXWduTmZrgFsQOd5pgRTj/FFHEwAr2ytx4raeseF4v4TzY5pxmQLGVlWClUKtc++/BpNF77B2KK80PWqFkPRCGLk2y36JCfzOzad5gQi9SGhS0SFdPB3CsdKGM4xdQSrrCJUPCwiTu1lf8/JzLAJQOZfy+e8VVnj2eeNLW0ha6HTNr4oCl7eUidNq7WwyrmClWryVY1bZZDitvpgnlghSEhEVvlLFEUPVNgT5jOmjyqwuUQwYe6U71Yl0F+5b7T0PKzKmOgLK6Z4W7LxMGAg5APshE6lMBEDwLqHg1X1ZFvf/LWoFoo7FXl3ga7S1KqFjAlrVgpxTAYAPPnmR6G21twTzCQi+tIu4twTIg1iFLO5iD7JIsnk058OcwKRHpDQJaJGqvs7qbbbwhW5Tsd0E6xbPjlj+bcBxMUiomrvgc/P4Qcr3g+KLUlEO8OEPeetDJkVjAWpyAKJeLGt8ucdMaC36/WpJl9ZW1XC45Ut9aF/i0FCPCaC95FZH2UC9NXaemVg1rq9p3Df+ME2MeYzg+WRVeWKVQK9vrP/RC62d2WPZcd7+u2PpW1auvGwpYCATFjpVApTFRBgbXGyhjotFG8sypNeI2Afs25WeD4A8dE39lpukomgv+3Ppl8v7SfePaG2ehLeOfQF/mbdR7bvsUUGoF6IidlcTEUYXzJW+kr1OYFID3zuXyGI7gGbaDI681hFY7tNPKYPwAMVRY6/keUqNQyEtsxjiawPFlYNC+YZZWLLxYfQBPBfH3+B7XVNaGxps/1dGqSz5iC+PP8Nxpf0CZWR5WGLg/qmVsfcsbrXKAbEMOsy317ZvRsrZH5wwkTQ+siOqSqF+mBlsfRFrErFFQCQl9PD1UWDhw8GFD8Xt/In1mzGeomPOmsvW3Cw785ZvgMTazbjibUH8R/7T2L3MXub+UphKx+8GWsXTHBsC+t7WdCa00KxvDAX94weIP0bfz9W7TqOv3xjn+ux8/1ZyLtSnq84AODM+W+k5wK6rM8AMKTfldLv8IsMILgQY31UWz3JIlTF/l6163jobyorvuz5ixTZs0IQyQxZdAmCIxbbbWKgm5uvoUoQxatqj9gHKpcOH4CA/WMAwFNvfhQq9ypep+r6pi/bjnm3FOP+imJH/z6n3LHhoCpuwRLdL6wahppOP86dDc2ejs1bCFXW8rkTi3FTcR7m/Xq3zVVFlanCSdTLLIMLJw9Da3uHJfDKZwD3c4sunWCo/7+9uw+Poj73x/+eRBKSQBIeAgkKJGAhcgoYKGBAEdRToFhr9WdRWxVOa6kKfn1oIfFYFK0SaI9ttfS0By3a08NDr0u056h49AiWhyBSIEotoNJAEBY0BTYSYiLJ/P5YZp2d/czT7uzOw75f1+V1SbKZ/ezs7M4999yf+6M8tyiwWrW9Cau2R4IvUZb63SOnYi4wzGo4Jw8rEd49WDDduETl3751MW6tHowl6/firb/Hvl+dsoydB08KX2cWxHdN9LLLWQCuvKg/ntpwQLdVmlEvZKPleK2Woyh3TuyUSCVT3uDFrDGRGQa6RBqput1m1JdXzQszlrX7QDSedXdW4/CJNsxfvVt3opHodeoFDjKAFZsj9a91148U9tvUBnHa3rF2iQKImuf3RCeoWVmVa0jffBz8xxnxxYAU2yZL1F9X6S6gDXKVThXq5WmzJPNaZCD2YuXdI6diJlyp35sVmxvxzLmLLtFkNe1rUQJBvRpahehXy9bvjyl7mDysBL+86WJAhnBFQb0LrFEXFBu88oh+hd2xXRPkKq9B29tX8dTNVZg5Kn7RF+WYq1m3Jxp0SwCWXD8Sowf2iixo8fwe4UWfeingZCZnmQWyVr8zEu0Ao1ebn65OMETJYKBLlAZ2Mi5em7Fs1C5s9MBeaO04GzNZShtDaCezKZPP9LKHyi3mLTVThW2znMy6i94XGV9kEc2CXAD4u07tK85t52f/uz9mRSt1f10AmLhkQ9zz/MetY5CXcx5+u+lAdHlaIBJcLF2/D8V53UwDFGW/KLXVeq9HCVjW3VktvACRECmvmDOpwvRixYj6eFevgqcOuNTZxmQu+BqbW4Wv9XuXDsHYweIsuXZBEjX1ctOyDAzsnYfWjk6Ewm1xFxV6C4UketzqddzIwhc1vla+MxLpAKOdCKn32WagS17GQJcCxUuzjtXsnrS9NmPZaDza2frqXq1AJJDZ8sEn+PbTB2IySS/cOTFmZr+acov56tHi1+1U1r3+w/g2ZU6SEb+i1dL1+/DkzVUo75uPnYfiV4sDgO8+t1N3m0pNc35OdkybKxGrS/Yq/Xi1nQZuGj8I86+8MC5gamxujWSaVbXbauq2bQrleP/tnw/ErIKnBFyn2j6PKatYct3IhC/49FY7VBaL0NuutvWb+rukrCgPM0dFumCIFt1Qar+vGT0g+llQgmHttq12TNDruAFEyoa++ev66PObfWfY7QAj6kqhxd645AeSLJtNLcksLS0tKCoqQjgcRmFhodvDIRu8Xj+2dkdT3MnVS+Nzivp16smWJGypmRqzKICWulVZKoTCbZhYt8F0cl2qSACG9++BfcdPJ7UNdX9bbbAUCrfF9KM12s4j3/gnXDWiP/7rrUNYvvGAsMZa+xm7c8rQ6GPVamdUoji/m7CVmyiDDcR388iSgK01VwBAQhd8Zp+3ULgtZrvaoBJA3D4Q7U/lWFaPTbuflBZ0et9NenXi2ucSLbIhen4Rq2NX1B9oxs0rtsf9XLmACPJ3GPmD1XiNga4GA11/svsl7hbtydXpbXslm/3O4ZO62VrF6tsvQfXQPgiF27ByayNWbGqMe7wEoL72ipS8Hr0TuUiWBMybeiGe3PCh4+Nwws3jB2Jw34K4jOiscYNiAj7p3P1nO1/6yucIQNxnTK98QXlv3zl8EjsOnsS48l7R/rhW9zkAfH9yBR742ggbo41l9fNmdkGg7IPG5lbh+B+ceRFmnmtDaOXiIksCXrgz0jNY77vrFzeOjmuzp0fZ32bsXGzrjUtvyWmidLMar7F0gQLBrZXE7ErVRDevZbP1lvVVqGfvNza3Ys6kCgzsnY8fa3qNyoBhCYOI1YBfr860dkYlICFuWdjJw0rwq40f2qpLBYDqIb2xvTG+Z6uTVr19OObf6vpL7S1tIJIhPdPxuWGJhEL5HMmQhd0y9BY20ctS6k3wE/386U2NMbXBdpl93pRj5R+n2w3fH2UfFORkC3//k5f34vFX9kYWxsgyr11WuozUXa+/Yl2WJBmu5KdQJjxaYackyqg2n8hPGOhSIHihU4Ei3ZnVRJcZTiWjyUrabgNKIHTjuIHCbUmiZqo67AT8Zh0clFpLdUCgPfH/4PIh6F2Qg6+U90K/wu6RVdM2NcbMwN/29y9W67LSxcEpnbKMl98NRTON6mNB6ZxghTqQEn3GFkwfjmWvxk7AAiA8JrfUTEXNjMqYGl1lO7PGXRAfsCN1bfW0x4rRe6P0aW5sbtXdXpeMuNdlRJl0KZoEqEyOW3LdyJiV14BIGcS63Ue+mDApxy5MYsbOxbbX5goQJYKBLgVCWVFeTBsmtzoVuJFZ9WI2W9jLdcZwjDr/i24D6tuiXTKw5u3DccGGJMFwNryaUcAPQHjxYXYi165CZfb4B742AjNHluHaX9fr1v7ayWgmS8k0io5D0TLTIuoexdoLg3+5tBzXXDwA11wce1Egaj+mHJNzLx+qmzFf/fZh3f67ThIdK5IUWXWuC/HvhYxIMDl5WIntbhPZkoRrqwZEa3TVRJMA1d9d2l7CMoAXVEGu8rOadearESZK2aYS5DPYJb9hoEuBsHZHU7QNk3Su12i6b927lVn1UjZbzSgoFAVCXQC+f9mQaL9hSYpMtEq21+jKrZHevHoXH6IMl9EFi1lGrLWj03CJ5F/dVIV3PwpHX2eWFGl7NefScvz3O0ex5BXrWUErjAL+uutjM4ZxFxoAivO6Rf8dXfzkXE21ug+vssgGYH5Mzp08VJgxF2V7tf13rTK6s7JyS2N8Wzk5srRy74LcuO4hSvZ1S81Uw9Z4IgumD8fcy4fi1urBcXXryj6pHtpH+FnRW1xFS5aBXYdOYuao4JdFEdnFJYDJ9+La4MiRk2O6l6g0yqymknapWrf77qopLZf0FsVQy5YkzLm0HAunV0YCLjmS9VMvdWpEtM0sCVixqTHu4sPo2LC6nKreUqiicUTHg8jiCEP7FcTceh7aLxKMXTM6fsECI1dWxi4LLQGYObIs7nFKwK9dQnbWuEGor70Cv7qpCstvrsKLd8UuzasEeNrX+PTmLyYOKotsqLe96f1PTI9J0bEx8oIi4djtfobMlstdsbkx7m+yzt09qB7aB4dPtul+lmeNG4Rf3nix5bEsezXyXaQsLqG3T0T7Q3Qs6ZXypGJaeTqXFiZKFWZ0yfe8cuvezcyqaMJR/YFmT3RgENGb6AIAS1/dFxNEKT1jB/XOR2tHp+5rEm3zXy4tjwtqzI4NK8eTWcZXPQ41GcB/NxyNeY1KMKnOiFr1xr5P4ra//q+huMysEvCr96v6boMy2c+o5EB57X85GD+xToaqv6uqHle7up1Z/brVz5DRdt45fDJmFTPtazVaTEJpM1bz/J6436vHcTT8WdzvRRPFgNj9Z7fmVa8EqO6VfXGZ97Hlzk8SM/sseKnTC5EeBrrke6kKMO1+ibu9oplyS90vtxpFJ31hSYOMmDZLRv11RQH/M5rb1GbHhnCxAdWELCslKuqVtOat2h0T1Cp15GpK8KBXN2unLrRLjrTlembzQVsBv94KXOr9pRxbZpRtqzOUVo/L715aEX3PRJ8ho+0oQap2V3XKMnYdOoleBZGlbPUWk1DeW9H+Vy8qsVQw6axmRiUuGdJbtzxBYbfziuhzUpzXLbrscBYiyxGn4nvG6LvVL98zRAx0yfdSEWAm+iXuZmY1FG7DzkMnY070VuuE3crMqGsRP275DCdaO0z/RkbkVrnea9IGEnaPDeV4UmcF1TPbrd5BKCvKQ6+C+OyhUkcuWwy+pXPdIJSlZbV/q5UlRcoX5kyqsBzw663ApV01zE5tqrI8LWDt4kA7hu9rlh022w4AYZCq7EPlgkNZwOHF3UfjjgnRhRYAPHljFa4+V1ait9rcqAuKo+UJTl/sao/pdHVDKCvKw8IZlXETBwFxVw03O70Q6WGgS4Hg5Bd/spPK3Misqp9Ly+xWvZuZGaNxG5Fhvb9uIsfG5GElMWlVdXmBKOuqF6jqZcQWzBgeDVy1gZZ2V8gyMOr8YiyYPhx16/eZ1mKqe7Sq30ejZW+1S71mnZuYNWZwL8OJUQBw9xVD8eSGA3E/P9PxRd7ayi1w7Rie2XwQcyZVxPyN0XZEfX6ByDEty4i5+Htx91Hhwgd675e6LMDsDlKi30WJ3EFKdVC5dkdTNMiVEJlYN2vcIEslLkRewUCXAsOpL34nan7T2YHBLNNmlC10YpyJZoO1tZR2SZL157Z7bIjqOJVjoOlEbB2tBOAHU4bE1NeqxyQKMGeNGyTsOqAXROXnZMXU9ZqREcm4Ke9jKNyGgb3zhcGdcGY/gN4FucKJUdqxXXlRf/xq4wHD8hCz4NDqZ85sO6ISj2tGl+HFhlDcts90dMW1LbNyd8jqY7SZaKPj1ItlAKKLj6Xr9+GSIb092+mFSISBLpGGE1/i6Zwgp5dpA8w7MCQ7zt9uOhDNMmpP0EYnd71aSqskCfjoZBvmr96dkuBA7xg40/F5JDhXPVYGsHzjASzfeACS6mfqMYkyfKLgu6woD9+sOh/P7zoS/dm1VQPQ2tFpO+vdJUey3u981BgtW1DGpA7wrB7vm97/JOaiRDpXtzp6YK+kg0OrYzDbzh2XD8XyN2Ozy//9TvzkPKPPs5WMrJ2srVkQm+jFZqrLjfQugK79dT3qrhvp6nwEToIjOxjoEmk4UfObzoyH3uSpJ2+swtjyXobjTmacv/3zgZiep+oTtHbVM20ArFdLKSLqIKCuG9Q+txMnPtExcG3VAHzvuZ2G41b/rksGap/fg4Lc8zD2XNsqM6FwG17YfSTmZy/uPopbqwcL32Oj4FcCMH/17rgxafeTleNd9J5JMqK1sckGh3Y+c8p2dh48CUjA2HMLiqzd0YRfvxlfQiGanKfetihosnIHwMpjrASxoi4WXig30lvdUJb1u2qkgxez3+RtDHSJBJKt+U1nBwa957raQk/WRMcZCrehTjDzvFOWsfPgScOT+85DJy1nJyUANV+rxKjzi5GfkxW97Z6OjLn6GFAWELCbge5CZBKU1ROy3usSrZ71gylDsHxjfGCnJhqvaD+ZHe962T31dpINDu185rQXUgunV+qWdmRLEuZMqoiZnGe3E0Si9N7PnQdPonePVuw5EhZ2cEh1uZFV37u0AitUPZPVr0HbVSMdvLjcOXkfA10iHYnW/CoZosnDStKW8UgmME/kb/V6kWZJAAx6iW56/xNhj9IsACtuG4u2ji7MX7M7ZsnTZev3Y0vN1Lhx6dWyOtnlQjkG9GbjW2X1hGyUYdeuntXY3CoMdP/flRfiS/17Yt6q3cLn0AuijI73dN2hSDRLKmrZpri2akBMMG60Hafr00X7TQJw95rdhsdTKsuNrIjrwgHrpR+p5JWe6eQvXBmNyEHaFZk2vf9J2rIeZUXiVchS8bd6q3/dOH4gBvbKE656lp+TJSxZkBApRbjyolL07pETNzlNtDKWkolWrzJ1bdUAfPPX9cLVsJKl93p1FqkSsrLCl+h16a2epbe63I3jB2Hs4F7C8ar7wVqlBHMLZ1R6YvU9veyy3ophL+4+KlzJK9mVDI1WX1No30/lhGtWcqKUhIjove9OBZ6iSWgAos/p5nuf6tdOwcSMLpFDMum2mrbkQTn3rNp+GGvePhzTpzQLkbZEehOqZERWQyvO74bJw0osZw61pQXqRv1dMlCzTr/XrhG9mk1RicfkYSV4+d0QfvLy3rjtJJoFs5phNyo7CYXb8L1LK/AfmkUiFk6vtHVrXntrf+H0Soy6oDitNZlaRi3b1HXbCr2MX6JZarv9qtXv5z9a23Uz7QoZMMxQprosSnQBIAN46sYq9OmR6+p7n86SMAoOBroUFaSZrG68lky7raaeFKS+Fav0Kb1jyhAsfzPSdmrpq/uwcEal7gQqJVDYUjPV1olMudX90rtHhf1ndx06iZmjrO97o5pNvQB05qgyPP7K3vjAa/pwLHs1vleuFUa38NXHtjbYb+3oxG83HRAGfACw7NX9uObiAZbGEQq3xQVzy14Vl5Eky+rnVZ1d1vYhnjVuEC6pMF+ZTJFI0JRov2rl/QyF20wnEVoJtlO5YIRRL2EvfI/NGjcIlaU9sePgSYwr74XRA51f+piChYEuAQjWTFa3Xksm9pYsK8pD7x7iAH/5mweiZQhdcqTWduH0ymjwp6UEComcxGWdZrx2evSKAjtRhwLtePQCplnjBuGai+N75SZDWzt504SBqB7SB0dPfYalr4qDWzXRsr96AebvtuhPQnIy4LH6ebWSXba7MpmdYy2RftXa/VtWFFlpbMkr8RPQAETvfljZv4nOIbCyXS9nTYN0rqL0YKBLgbrl7uZr8foJIlWE7c0gnpA26oJibKmZGpcFBmIDBbsn8a+U944rFZCAmBWtFOrgA/hicYdkAjujpZ+ttBWzQlQ7uWr7YazaftjyNtT7+Ld/PtcDGeIWcM9saYz7+yzA0Qs3q59X0eP0sst2L5SsHmt2+1XrBWQjzy8SbkNCpNZYKeNxM3hL1xLDdgXpXEXpw0CXAnXL3e3X4tUThBP0sn+iAH/B9OFxGUYlyCorysPVo/PQ2nHWsYuCsqI81F0/ErXP70EXIgHZkutHxm1PmxEFIgGj3qQyO4GdEjClKuNkFGhZod7Hv92k3wO5rChP97luHD8wugKcE8e21c+r3c+1E9lO7fFu1K96YO88tHZ0IhRui5Yo6AVkuv1pEf9YN78/UpUxTobb3+/kTwx0KVC33L3wWrx4gkiWWfAmCvCL87sZBrJOXxSYbU9vNrn2/9W+N7nCdoeCVGWc9AIkI8okrVHnf3GL36gHshIw6LXFWv32Yax6+7CtVfDsvibt5zUUbsOJ1g5Lk/ucqs3XO95Fd2xaO87im7+uj3nswN75ugFZ9dA+MdvJAuJaowUpeHNyvoQXvt/JfxjoUqBuuQfptaSb3gnJavCmDfCtBLJmFwV6ZQZmk9NE7GZEsyRgzqQK63+g8xxOBS3Ksa1krfUoGXW97giNza3C2mV19lr7OcqSIvXO2qxjZWlPvPxuKLqogFEGW3t8RSeWqeq2tZ9XvX6udkoF7DI63kUlKpPqNsQ9dt2d1YYBmWgxkiAGb07f3eD3OyWCgS4BCNYt9yC9lnQxOiGZBW9GGZtkstt6ZQaJnjDNMqISIr1Yu+TEe4Um07LKStZLObZXbjmIFZv/Hg081SvImR3zevth4YxK3QuV5tOfYf7qhpjHd8pyXIcDvYsg7fH1zarz8cLuI19MLJsRP3ZRBj5LirS50nYASCaTrt33Zse7+pgWLSSit5Kd9nhSbyeIwVuq7m7w+53sYqBLUUG65R6k15JqZicko+AtVfWoRmUGiZ4wtdkgCQDOZSrVfXGTOYFGs66qfWKnZZWVfVhWlIc5l5Zj5AWFCLd9juK8HFutn0TZ2oUzKjF38lBhlwDlYsaorlRN1NlB283i+V1Hoo9XOnJoJ5YJF4aQgT49coVZ6kQy6aJ9b6eXs52V7KxcwAQpeEv13Y0g7CNKDwa6RB6X6p7AVjJYoowTgJTVo5qVGVg9YWr3nejWs/r/ndrP0SWMTUolEsl6iYIzu+MVBVZGAXdccIz4ulKFNigUdbPQEr2fdrLjBTnZthfo0Nv3dno5m91KtxOQBS14Yz0teUWgAt3y8nIcOnQo5mdLlixBTU2NSyMiSk46ekZaOSGJAiO927ZmAagocLcyw13NyglTW/pQM6MScy8fGhdQONkpQQmelGHL+CJwBRBXb3zg49O29qGTt4PV+8HKds3qSoFIna860NNrU6Ylej+t1mMq7502yDXLpBtd4NnJsAYxG+sE1tOSVwQq0AWARx55BLfffnv03z179nRxNESJS1WNm+j2tJUTkjZATCRjIwooAZjOcBeVGZgF09rShyXr9wESMHfyUMPHJrOf9YKnlVsb8fTmxrh6YxGjfZiq28FWt6tXV5olAd+7dAjmXFpuWn4AAJO/1BdbP/yHaQBkt5MGEDmG1t1Zbbpiltnxm8nZWKfwIoC8IHCBbs+ePVFaWur2MIiSloqgRi9zmcgJySxAFs2y1waUtev2CGfz681wNwp4zCYUAcDS9ftwzegBpsFYovtZr9fqik2NMVlePVkSsGCGeGUsO2227ErkosXKMaO3P5b+f6MA6L+fakZBpF4d75kOo74UX2yXGcfU40UAuS1wgW5dXR0effRRDBo0CDfffDPuvfdenHee/stsb29He3t79N8tLS3pGCaRKadr3Mwyl4mckPSCHVFALeotKgpG9Wa4h8JtkAVhoui5KkvFd3K6ZGDl1kY88LUR0Z85uZ9FwdO/XFqOFZvNb98r41u6fh+K82JXxlK/RjWjwDjZcVsJ+syOGSs1rMnQC6SbT38WXbzBSDoyjqmusSciY5Kst0i8Dz3xxBMYM2YMevfujfr6etTW1mLOnDl44okndP/m4YcfxuLFi+N+Hg6HUVhYmMrhEplau6MpLkhItEa3/kAzbl6xPe7nq2+/xNYytWYn7lC4Laa3KBAJHNfdWR1X16ntz6o8VjsDXy8Trfdcv7hxdFw7rOhzAthae0Xc9p3az8o+0Ou1aoV6H4heo5oEoO5657pdpCLoS9V2gdj3TjqX7lZakamPEzeCzXTU2BNlqpaWFhQVFZnGa57P6NbU1GDp0qWGj9m7dy8qKytx3333RX82atQo5OTkYO7cuViyZAlyc3OFf1tbWxvzdy0tLRg4cKAzgydKkpMZp2Qyl0qgsOejcHRpX70Tt14pgF5vUQCGmUSjTLTec2VJku5kti4grizB6cyeNtMZU2+sCsb0qLPaZh0oZERKQJzodqHNoCcTHIpqwVNBee92HTqJeat2x5XBnDrzuekxmwqpXCWPiKzzfKB7//33Y/bs2YaPGTJkiPDnEyZMwNmzZ3Hw4EEMHz5c+Jjc3FzdIJjISYkGDk4FCYnenta7ba534k6kt6hRkKkXzO48eBJjy3sJn2vM4F4x/WzV9IL7dARj2nrj/JwsHD7RhrvX7Na9AKnoWxBXl6vVJccH78lYu6Mp2vs2kYyxXseLVCkrykOvgta4fdQpy6hbv09YA57qYDOVfWRThWUWFESeD3RLSkpQUlKS0N82NDQgKysL/fr1c3hURPZ45Ram3cylaFa7mt7M/ER6i4rqbwH9lbzuXrMbS64bqftc0VXEtjbi6U2N6ELiK545QdTWLBRuQ2tHJxbOqMSy9eJlcMuK8lAzozLSNUJHloSkJ6QptAs8yABqnreeMbbT8cJJevW6bgWbXu4jKwpovfIdReQ0zwe6Vm3btg3bt2/H1KlT0bNnT2zbtg333nsvvvOd76BXL+M2M0Sp5LVbmHYyl2a3zfVO3HYCarMTrBI41z6/J2aRAnWD/3V3VmPHwZMYV94rpq1UWVEe5kyqwKgLigEZtlYQSzVt1rRmRiVGXVAc3Z/1B5qjgcjcy4cCUmSimvb9kBJcNELPXw6eiLvkkAH839+O45bqcoTCbfjLwROQJAljB8fvTzsdL5wkusBaMGN43D5LV7Dp1a4OeqvBeek7ishJgQl0c3NzsWbNGjz88MNob29HRUUF7r333pj6WyI3+PEWpqKibwEkSbzCl3ZxAC0rAbXVi4BZ4wahIPc8zFu1O+bvtT1qtYFyqrNURrd6zX6nzZrWrd+HJ2+6GO8eORUNztRjnjt5KK4ZPSCm5EGSgDGCYDMZkiQJf77oT++h4fAprNt1JDpuUVmDXqmFqLzCyq1yO7fTRRdYxXnd0hJsisbptT6yep+3X9w42rffUURmAhPojhkzBm+99ZbbwyCK4+VbmGqiE3X0tvkrsbfNsyTghTsnmjblN2PnImDs4Ph6XG2PWnWgDFhbojjRukSjINoswNbLmmo7RRi1gEt23+sZO7iXMFCVATy/60jcz7QT4fRKLbTHvJWLkEQuVLQXWOkINs2WT/ZKsGhn8qYXv6OIEpHl9gCIgk65hZl9LlPmlVuYamt3NGFS3QbcvGI7JtVtwNodTdHfzZ08FLUzKqNfFtmShCXXjXQk0FIuAtS0J9hQuA31B5oBIG4/fvfSCuEEpIPNZwyDaIXodSvPFwq36Y5bLzMWCrfp/u6dwyej29XLmopox5xqZUV5qLt+JKyOUMnUqs29fChqv1YZfW9Fi4no7T+FlcfYeU3VQ/sIM+va99rK+6/dhlPjTDW9z5syedPL31FEiQpMRpfIy7x2C1PNSvnA3MuH4pqLBzg+frM6Rm2mbOH0SvzixtHIOndyBoBntjTqZqKMslSi112zbo+wD6uWURAtQxb+7trl9dHtLpxeadpJQTTmdJk1bhAqS3vi2l/XC8tW1LQT4ZQM+TWjB0RLLbTHjJVMvtVsv5MZeUC8HLWRnYdOJnTb340OB0afNy9/RxElg4EuUZp46RammtWAIlXj1zvBigJR5Xa4OggxCpSNfid63eqgzmhCjlk5imi2v7q8Ytmr+1HztUrh5DI1o8xaqgOl0QN7oWa6cbcH7UQ4q6UGBTnZcbXf2oDeSslPojXYdpej1tu/yoRCLbOLEyvjTtX7axTQevU7iigZDHSJMpwbNcSixQSszt4HYoMQoxO30e/02pap6WXmzDLR6t/ptbgadX4xttZcgZVbG/Efmxqjv9N2YBAFHulqBTXygiLd3/2/Ky/EjeMHmZYjaANFZezaIFcb0OvtYyDSkaIgJzvhTgGiY0t0HBhlZpXXq/2zLMl4kqaV/ZTq95cBLWUSBrpEGS7dbZCsnsTNAlF1EGJ04tb7nfZ16y1HrBfwWw2w83Oy4pY+Vm/36c2NMduVJOCai/XbcKWzXZ1e140sICbIBazdGRD1Zc4CsO7OamHNt3Yfb3r/k+hyyKJxWe0UoNdz1877r3ch9uSNVbh69ADd5zbbT15rR0jkdwx0iSht9XnatlpKXazoJK4NRLW09baJ3OYVBVKigF9v+1YDbL0LifoDzcLMolGwls52dZve/ySukFgCsOT6+L69Vu4MCDOpAM50dEGPsh/jFqIQBJlW70QYZYutXvDpXYgdMZmEZrafEn1/vbKqmVfGQaRgoEtEANJzO3PnoZPxbatkYNehk5g5Kv651YHou0dOCVcPS/Y2r/p1iwJ+J24j611IJFI2UpCTLfx5fo6zTXREt+YlAC/eJW4rZ+XOQDJlMnoZ1CzA9qp3oXAbBvbOx7o7q3Gmo8vyctTa17tQUMO8bP1+w4UxzPZTIvvIK6uaeWUcRGoMdIkobWSdKfxGM/uVQLR6aJ+4WfxWb/PayTKpA1/hpCUby+HqbVc9JqPlf0VaOzqFPzfKiiZCOFnP5HnM7gwkUyajFwCqg1UgdkU5EVEwVj20T8wYrb63ohpmK9lXswlh6pUAzRZm8Uqpg1fGQaTFQJeI0uYr5b3j2mpJiCzNa4Vywtx56CRk+QQA8UQvdaCRTJZJ71b7yi0H8cDMiyxtQ0TUNs1o8pkiFG7DP063x9eXAvhHaztC4TbHgopEs69mgaIS5O08eBKQIgtUWKEXJCvZZaudDJwMxvT2UX5OlmnAbRpQKx8Uk4bGXll50SvjINJioEtEaVNWFFmMQJ2tEtV76lHaOSnnUwmIC5zNeuXaCWz0lrN9esvfMefS8oRO4KI65WWv7seWmqmG21MHchK+mIyljG/eqt2O3i5O5STFTe9/ktDFh51WdKL32elgTLSPrq0aEJ18mMj7YfeY9crKi14ZB5EWA10ij0n3ZA7R86VyDIlOfBPVjCr/r1enmWxgU1aUh9svq8B/aDojmE0YM/K7LY26q7lZvT0tA8iSgW9cXIYXG0Ix43LydnEqJikme/EhyoRafZ9TEYwZddhI5P2we8ymu2uKHq+Mg0iLgS6Rh6R7ModTq0PZlcjEN6O+uk/dXIXeBbmWeuWaBTbaIH/OpRV4WrP6GgC8e+RUTG2n6G9F/35mS2zQDEQCdaMx6ZVQqINcRacs607uS4TTkxRTcYtb2C4M8fvUbjBm9YJP2UeiLhp2X1six6xXVjXzyjiI1BjoEnlEuidzOLU6VLrotXPKAjBmcC9Hsl16FxpWZtdr//abVefjhd1HYrY1sHe+MFj/3uQKw/1rZXELtXmrduN0+1nhBYrb7Z9SkVVV3md1SYiMSImEdh9oM7CtHZ3C2mazi07RfnTitSWaGU1H1xQrvDIOIgUDXSKPSPdkDidWh0qnsqI8LJxRibpX9sXU6JrV+FrNMhldaJjNrhf97fO7jkQfq2xr3Z3VwoUK5kyqMH3tRj2FtWQYr0rmZvunVN3injysJGYRCb19oIzBqE7Y7KJTbz869dqYGSVyDgNdIo9I92QOvdWhtMGuVyaUrN3RhKXrvwhyb54wEPOv+FLCdZ1aRhcaiTT51+qUZZzp6Eo4EFKCn5ffDeEnL+81fbzZqmSJZuudyAinIpCzc6Foti+MtgXA8G+dem3MjBI5w9kO40SUMCUblC1F+gmlejKH9vkAfDGj/9y/vTKhRLR07Nq3P3L0OZRgVk0JZs3eG9HfainbmjVuELbUTMXq2y/Blpqpthe3mDmqLO65RM9tZVUydfBmxdodTZhUtwE3r9iOSXUbsHZHk+W/1SorivRGdrodmpreRZrZvhBtS6n5tbIfnX5tRJQ4BrqUkULhNtQfaEbIZLnOdEsmCEr0+dbdWR3TqlNGpHXVr26qSssYrHAiSDNjFswavTeiv71+zPm620omEBI915LrRmLp9cYXSXYCQRG9LKhXPkN2LhTN9oWyLe3nYtP7nyS9H/3Oq9+dRHpYukAZxwt1ikbSfcuytaMzrt1Vlwz06ZHrmYxUuso6rKzspbdPRH/7w2nDU1JnqTdOu6uSLZg+HI3NrdHfG/HDggBWywas1NLq1fxuqZmasW20vP7dSSTCQJcyCpepjOeHRu9GgYnTXQSSudDQ/m0qL1pE2zZ7PnUg+O6RU1i6fp/loMXp4yRV3R+s7nOzoNgosM/EyWL87iS/YqBLGcUPWal080ujd1FwwQyTfcr7+u2n3xIGLQCEAaiTx4kT75sTC50YBcVmgX2mTRb7y8ET/O4kX2KgSxnFD9lLN3g5Q6UNXpzuIpCJ9C74Vm5txNObG3UDUCeOEyfet3QsdOKXC8B0UPa3Fr87yQ8Y6FJG4clLnxczVEaZP71g7eV3QxhX3gutHZ2uLYrgdXqt5VZsajRdLCSR40R9sZLsXZV0LnTi5QvAdBF1PAEiM9n53Ul+wECXfCfZ2j6evLwvFG7DzkMnY1a60gYvequFqXvMmmX23F4lzC2iC75/ubQcKzbHLk/sxK1p7cXKwhmVCd9VCYXb8NK7R9O60IlRYJ8Jx49ej+inbq7CzFED0j8gIpsY6JKvOFWT6cXsJUWo32MtdfCiDdZEjDJ7mV7fq73gA4CnNzfGdOBI9ta0KPu6bP1+LJxeiWWv7rd1V8XouMg61x3BybGbyZTjR6/ca8zgXu4NisgG9tEl3/B6H09Knt5tUoU2eFF62z448yLdbYr67frtWBL1LnWqn6l8Ljzc9P4nMT+XkPytab0yhVEXFNvqF210XCh9hOtM+gg7yW/HTzLSvZANkdOY0SXfYMeE4DNaSlfvBKusFvb4K3t1AyFtZs9Px1IqJl6Fwm1YuaURK85lcJX1D9S7RJIQ7cJgtB2jW/dGkz/t3FXROy5+PPMifG1UmaU+wk7y0/HjBJZ7kZ8x0CXfYMcEb0hlXaLeJKknb6zC2PJelhcAUIiC41C4DSdaOyAhvbe6E5GKiVeiEgDRtUWXDMPAzcqte6cmfwqPCwD9i7rHPV866mkz8buI5V7kVwx0yTfYMcF9qa5L1HuPrx5tPulFnXXKz8nCmY6uuOyTevwSEA12vXosiTKHyUy8MisNUTMK3Oy0CHMiG6g9LpT3bd6q3ZaOQ6ePW34XEfkHA13yFd5Cc0+6+tYm8x6bZfTU45cRCXqeMskWu0kvw53oxCuj0hAJkXKFLtk88De6da/8Xp05dSIbqBwXOw+exN1rdls+DlN13PK7iMgfGOiS7/AWmjvSWZeo9x4nc/tZLzvap0euZ48nvcwhgISyiXot2bIALLl+pOXATe/W/btHTkVXXEtVxr93D3vHYSqPW34XEXkfA10issTtusRkbz/rZUebT3+GULjNswGLXuYwkWyiNnDOkoDvXToEcy4tj8m+2t1OtiRhwfThWLp+X8oz/naPQ7ePWyJylyTLOg0oM1RLSwuKiooQDodRWFjo9nCIPGXtjqa4TGI6eoeGwm2YVLchLljZUjPVVhClHr90rtBTKWHwYx/URDPcoXCbI7fc1dtpbG7FzSu2xz1m9e2XoHpon4SfQ8TucZjscZsJC0MQ+Y3VeI0ZXaIAc/oE7VZdolO3n5Xx7zp0EvNW7XZ8ydh0spvh1h4LTrxO7XbSlTm1exwmc9xmysIQREHFQJcooFJ1gnajLtHJ289lRXnoVdAa11LLT31Q7U6wSkewlu5OBHaPw0SO23RNwCSi1OHKaEQB5PeVm7Srfjm9OpMSOKulu24zmZXNzLoeaJ8nXceCslKd1RXPvM7OfiYib2JGl3yDdXLW+XnlJr3so5NlE273QU3FxDq9QD3dx0KQOhFwIhuR/zHQJV9gnZw9fj1Bm90qdjKIcqveOJHb4aL6WquBul+PBS9w+4KIiJLHQJc8j3Vy8cyy2349QWdC9tHua0w2w+3XY8FN6s8XF4Yg8jcGuuR5fr4NL5JsCYbV7LYfT9CZkH208xqdynD78Vhwi97nK5GJbCy1InIfJ6OR53lh4pBT1u5owqS6Dbh5xXZMqtuAtTuabP293YlFZUV5qB7axzcnWqcnnXmRndfo5GQovx0LbnBq4l6yn3Micg4zuuR5Qbn16kQJRtCy2yKZkH20+hozIcPtJU58vlhqReQtDHTJF4IQ/DhxEs2UwMeN2tl032q28hqDcpHnF058vjLhYpTITxjokm/4vW2REydRBj6pYbXu2Y26yyBc5PmFE5+vTLkYJfILSZZl7QJBGc3q2slEiVi7oynuJJpIm7RQuM13gY9XJ+eEwm2YVLchLjDZUjM1ZpxscZc5kv18OfU5JyJ9VuM1ZnSJ0sip7JzfstteDhKt3GoW1V3WPr8HBbnnYezgXr56L8hcsp8vZuGJvIOBLlGa+S1ITZbXJ+dYudUsCoa7AMxbtdtzgTulnpW7E5n2OSfyKrYXI6KUcrJFVipYafclanGnSKQFVSjchvoDzbbbVpH7Mrl1GI9b0vLDMcGMLhGllB8m55jdatZOUtKyM6vey2UcZMzrdydSicctafnlmGBGl4hSyi+LQJgtqDBr3CBsqZmKX91UlfACJk4tSOAUP2RjvMTrdydSxWvHLbnPT8cEM7pElHJBmZxTVpSHq0fnobXjbEItqLzUY9XpbIxXu2o4yQ93J1LBS8cteYOfjgkGukSUFkGanJNo4O6VQMnuLXizINYvtzCTpS1hyZKABTOGB+a41uOV45a8w0/HBEsXiCgjJXvb3qzUQe9vvFDGYecWvNnkKz/dwnTCrHGDsGD6cEiIvNal6/cFfkKaV45b8g4/HRPM6BK5KBNu93qRmxlIq9ngVB4bVrMxVjK/frqF6YRQuA1LX90H5SVbnZDm9896UMqPyDl+OSYY6BK5JFNu93qNF2bOm5VxpPrYsLrUrZUg1qlbmEogWJCTjdaOTs8GhIkE9kH5rAep/Iic4YdjgoEukQu8EGxlKq9nINN1bFjJxlgJYq0GzUbUgaDCqwFhRd8CSADUh5BRYM/POpG7GOgSucDrwVaQeX0SRTqPDbNsjNUgNplbmNpAUOHVgHDT+5/E/FsCDAN7ftaJ3MVAl8gFXg+2gsyJDGQqpfvYMKsdtRrEJnoLUxQIKpwMCJ2okVWCcvVwJQmYPKxE928y9bPu95pkCg4GukQu8HqwFXRenkSRzmPDau1oKuvwRIGgwqmA0KkaWVFQ3iXDMBjPxM96UGqSKRgkWRasZ5nBWlpaUFRUhHA4jMLCQreHQwEXCrd5MtgKGj9ml1J9bITCbZhUtyEu07ilZqori1dol1dWAsJkAyQnX2cy28qUz7qXjisKNqvxGjO6RC7yw4xVv/NrdinVx4aXakfVGfb8nCyc6ehyLCB08nUmk53NlM+6l44rIoCBLhEFGGe86/Na7WiqAkGnX6eXy168wGvHFRFXRiOiwLKzAlim8dPKRslIxetMZFW8TJEpxxX5BzO6RBRYzC4Z81t2MtFaa7+9Tr/j/iYvYaBLRIGViTPe7fJL7WiytdZ+eZ1Bwf1NXsGuCxrsukAUPJky4z2oOJOfiLTYdYGI6Bxml/yNM/mJKFGcjEZERJ6m1FqrsdaaiKxgoEtERJ7GmfxElCiWLhARkedxJj8RJYKBLhER+QJrrYnILpYuEBERpVEo3Ib6A80IhdvcHgpR4DGjS0SuSLT5P5GfJdsPOFPw+4GcwkCXiNKOJ/v08WrA4NVxpVIo3BY97oHIin0PrPsrJg8ryZh9YAW/H8hJDHSJKK14sk+fdAcMVoPXTA1k2A/YHL8fyGms0SWitDI62QeRW/WYegFDqsaxdkcTJtVtwM0rtmNS3Qas3dHkiXF5CfsBm8u07wdKPQa6RJRWmXSytxr8pUI6AwY7wWsmBzLsB2wuk74fKD0Y6BJRWmXKyd7tzGU6AwY7wWumBzKzxg3ClpqpWH37JdhSMzUjSjbsyJTvB0of1ugSUdq53fw/HROh3K7HVAKGB9b9FZ2ynNKAQQle1a9XL3hN57i8iv2Ajbn9/UDBwkCXiFzh1sk+XROh7AR/qZKugMFu8MpAhszwYoCcIsmyLJs/LHO0tLSgqKgI4XAYhYWFbg+HiBwUCrdhUt2GuOBzS83UlJxU1+5oigv+vHar2snsdijcxuCViNLCarzGjC4RZYx0lxN4PXPpdHabWTgi8hpORiOijOHGRKiyojxUD+3juQDQ7clyRETpwECXiDIGZ3R/IZPbfBFR5mDpAhFlFK+XE6SLFybLERGlGjO6RJRxvFpOkE7MbhNRJmBGl4goQzG7TURBx0CXiCiDsVMCEQUZSxeIiIgIoXAb6g80s/MGBQozukRERBkuXSsGEqUbM7pEREQp5PVMKXsqU5Axo0tERJQifsiUpnvFQKJ0YkaXiIgoBfySKXVjxUCidGGgS0REjvL6rfp08cvqc+ypTEHG0gUiInKMH27Vp4ufVp9jT2UKKt9kdB977DFMnDgR+fn5KC4uFj6mqakJM2fORH5+Pvr164cf/ehHOHv2bHoHSkSUofxyqz5d/JYp5YqBFES+yeh2dHTghhtuQHV1NZ555pm433d2dmLmzJkoLS1FfX09QqEQbr31VnTr1g2PP/64CyMmIsosnNQUj5lSInf5JtBdvHgxAODZZ58V/v61117D3/72N/zf//0f+vfvj4svvhiPPvooFi5ciIcffhg5OTlpHC0RUebx0636dOLqc0Tu8U3pgplt27Zh5MiR6N+/f/Rn06ZNQ0tLC9577z3dv2tvb0dLS0vMf0REZJ/fbtUTUfD5JqNr5tixYzFBLoDov48dO6b7d0uWLIlmi4mIKDm8VU9EXuJqRrempgaSJBn+t2/fvpSOoba2FuFwOPrf4cOHU/p8RERBx0lNROQVrmZ077//fsyePdvwMUOGDLG0rdLSUrz99tsxPzt+/Hj0d3pyc3ORm5tr6TmIKHVC4TY0Nreiom8BAyQiInKEq4FuSUkJSkpKHNlWdXU1HnvsMXz88cfo168fAOD1119HYWEhRowY4chzEFFqsPcqERGlgm8mozU1NaGhoQFNTU3o7OxEQ0MDGhoacPr0aQDAV7/6VYwYMQK33HIL3nnnHfzv//4vHnzwQdx1113M2BJ5GHuvEhFRqvhmMtqiRYvw3HPPRf9dVVUFANi4cSOmTJmC7OxsvPTSS7jjjjtQXV2NgoIC3HbbbXjkkUfcGjIRWcDeq0RElCqSLMuy+cMyR0tLC4qKihAOh1FYWOj2cIgCLxRuw6S6DXG9V7fUTGWgS0REQlbjNd+ULhBRMLH3KhERpYpvSheIKLjYe5WIiFKBgS4ReQKXSSUiIqexdIGIiAyFwm2oP9DMThhE5DvM6BIRkS72OCYiP2NGl4iIhNjjmIj8joEuEREJGfU4JiLyAwa6REQkVNG3AFlS7M+yJQnlffPdGRARkU0MdImISIg9jonI7zgZjYiIdLHHMRH5GQNdIiIyxB7HRORXLF0gIiIiokBioEtERGQRF88g8heWLhAREVnAxTOI/IcZXSIiIhNcPIPInxjoEhFlGN5+t4+LZxD5E0sXiIgyCG+/J0ZZPEMd7HLxDCLvY0aXiChD8PZ74rh4BpE/MaNLRJQhjG6/M2Azx8UziPyHgS4RUYbg7ffkcfEMIn9h6QIRUYbg7XciyjTM6BIRZRDefieiTMJAl4gow/D2OxFlCpYuEBEREVEgMdAlIiIiokBioEtEREREgcRAl4iIiIgCiYEuEREREQUSA10iIvKUULgN9QeauTQxESWN7cWIiMgz1u5oQu26PeiSgSwJWHLdSMwaN8jtYRGRTzGjS0REnhAKt0WDXCCyVPED6/7KzC4RJYyBLhEReUJjc2s0yFV0yjIONp9xZ0BE5HsMdImIyBMq+hYgS4r9WbYkobxvvjsDIiLfY6BLRESeUFaUhyXXjUS2FIl2syUJj1/3ZS5XTEQJ42Q0IqIACoXb0Njcioq+Bb4KFGeNG4TJw0pwsPkMyvvm+2rsfuDX44IoUQx0iYgCxu+dC8qK8hiEpYDfjwuiRLB0gYgoQNi5gER4XFCmYqBLRBQg7FxAIjwuKFMx0CUiChB2LiARHheUqRjoEhEFCDsXkAiPC8pUkizLsvnDMkdLSwuKiooQDodRWFjo9nCIiBISCrexcwHF4XFBQWE1XmPXBSKiAGLnAhLhcUGZhqULRERERBRIDHSJiIiIKJAY6BJRSoTCbag/0Mw+nURE5BrW6BKR47gCExEReQEzukTkKK7AREREXsFAl4gcxRWYiIjIKxjoEpGjuAITERF5BQNdInIUV2AiIiKv4GQ0InLcrHGDMHlYCVdgIiIiVzHQJaKU4ApMRETkNpYuEBEREVEgMdAlIiIiokBioEtEREREgcRAl4iIiIgCiYEuEREREQUSA10iIiIiCiQGukREREQUSAx0iYiIiCiQGOgSERERUSAx0CUiIiKiQGKgS0RERESBxECXiIiIiAKJgS4RERERBRIDXSIiIiIKJAa6RERERBRIDHSJiIiIKJAY6BIRERFRIDHQJSIiIqJAYqBLRERERIHEQJeIiIiIAomBLhEREREFEgNdIiIiIgokBrpEREREFEgMdImIiIgokBjoEhEREVEgMdAlIiIiokBioEtEREREgcRAl4iIiIgCiYEuEREREQUSA10iIkqJULgN9QeaEQq3uT0UIspQ57k9ACIiCp61O5pQu24PumQgSwKWXDcSs8YNcntYRJRhmNElIiJHhcJt0SAXALpk4IF1f2Vml4jSjoEuERE5qrG5NRrkKjplGQebz7gzICLKWAx0iYjIURV9C5Alxf4sW5JQ3jffnQERUcZioEtERI4qK8rDkutGIluKRLvZkoTHr/syyoryXB4ZEWUaTkYjIiLHzRo3CJOHleBg8xmU981nkEtErmCgS0REKVFWlMcAl4hcxdIFIiIiIgokBrpEREREFEgMdImIiIgokBjoEhEREVEgMdAlIiIiokDyTaD72GOPYeLEicjPz0dxcbHwMZIkxf23Zs2a9A6UiIiIiDzBN+3FOjo6cMMNN6C6uhrPPPOM7uNWrlyJ6dOnR/+tFxQTERERUbD5JtBdvHgxAODZZ581fFxxcTFKS0vTMCIiIiIi8jLflC5Yddddd6Fv374YP348fve730GWZcPHt7e3o6WlJeY/IiIiIvI/32R0rXjkkUdwxRVXID8/H6+99hruvPNOnD59Gnfffbfu3yxZsiSaLSYiIiKi4JBks5RnCtXUhDvPTwAADl1JREFU1GDp0qWGj9m7dy8qKyuj/3722Wdxzz334NSpU6bbX7RoEVauXInDhw/rPqa9vR3t7e3Rf7e0tGDgwIEIh8MoLCw0fxFERERElFYtLS0oKioyjddczejef//9mD17tuFjhgwZkvD2J0yYgEcffRTt7e3Izc0VPiY3N1f3d0RERETkX64GuiUlJSgpKUnZ9hsaGtCrVy8GskREREQZyDc1uk1NTThx4gSamprQ2dmJhoYGAMCFF16IHj164H/+539w/PhxXHLJJejevTtef/11PP744/jhD3/o7sCJiIiIyBW+CXQXLVqE5557LvrvqqoqAMDGjRsxZcoUdOvWDcuXL8e9994LWZZx4YUX4oknnsDtt9/u1pCJiIiIyEWuTkbzIqvFzURERETkDqvxWuD66BIRERERAQx0iYiIiCigGOgSERERUSAx0CUiIiKiQGKgS0RERESBxECXiIiIiALJN31000XpttbS0uLySIiIiIhIRInTzLrkMtDV+PTTTwEAAwcOdHkkRERERGTk008/RVFRke7vuWCERldXF44ePYqePXtCkiS3h5MWLS0tGDhwIA4fPsxFMgKI72+w8f0NNr6/wcb3N3GyLOPTTz/FgAEDkJWlX4nLjK5GVlYWLrjgAreH4YrCwkJ+0AKM72+w8f0NNr6/wcb3NzFGmVwFJ6MRERERUSAx0CUiIiKiQGKgS8jNzcVDDz2E3Nxct4dCKcD3N9j4/gYb399g4/ubepyMRkRERESBxIwuEREREQUSA10iIiIiCiQGukREREQUSAx0iYiIiCiQGOhmuMceewwTJ05Efn4+iouLhY9pamrCzJkzkZ+fj379+uFHP/oRzp49m96BkiPKy8shSVLMf3V1dW4Pi5KwfPlylJeXo3v37pgwYQLefvttt4dEDnj44YfjPquVlZVuD4sStGnTJnz961/HgAEDIEkSXnzxxZjfy7KMRYsWoaysDHl5ebjqqqvwwQcfuDPYgGGgm+E6Ojpwww034I477hD+vrOzEzNnzkRHRwfq6+vx3HPP4dlnn8WiRYvSPFJyyiOPPIJQKBT9b/78+W4PiRK0du1a3HfffXjooYewa9cujB49GtOmTcPHH3/s9tDIAf/0T/8U81ndsmWL20OiBLW2tmL06NFYvny58PfLli3Dk08+id/85jfYvn07CgoKMG3aNHz22WdpHmkAyUSyLK9cuVIuKiqK+/krr7wiZ2VlyceOHYv+7N///d/lwsJCub29PY0jJCcMHjxY/vnPf+72MMgh48ePl++6667ovzs7O+UBAwbIS5YscXFU5ISHHnpIHj16tNvDoBQAIL/wwgvRf3d1dcmlpaXyT3/60+jPTp06Jefm5sqrV692YYTBwowuGdq2bRtGjhyJ/v37R382bdo0tLS04L333nNxZJSouro69OnTB1VVVfjpT3/KMhSf6ujowM6dO3HVVVdFf5aVlYWrrroK27Ztc3Fk5JQPPvgAAwYMwJAhQ/Dtb38bTU1Nbg+JUqCxsRHHjh2L+SwXFRVhwoQJ/Cw74Dy3B0DeduzYsZggF0D038eOHXNjSJSEu+++G2PGjEHv3r1RX1+P2tpahEIhPPHEE24PjWxqbm5GZ2en8PO5b98+l0ZFTpkwYQKeffZZDB8+HKFQCIsXL8Zll12Gv/71r+jZs6fbwyMHKedS0WeZ59nkMaMbQDU1NXGTGLT/8UQYHHbe7/vuuw9TpkzBqFGj8IMf/AD/9m//hqeeegrt7e0uvwoiUpsxYwZuuOEGjBo1CtOmTcMrr7yCU6dO4Y9//KPbQyPyFWZ0A+j+++/H7NmzDR8zZMgQS9sqLS2Nm8V9/Pjx6O/Ifcm83xMmTMDZs2dx8OBBDB8+PAWjo1Tp27cvsrOzo59HxfHjx/nZDKDi4mIMGzYMH374odtDIYcpn9fjx4+jrKws+vPjx4/j4osvdmlUwcFAN4BKSkpQUlLiyLaqq6vx2GOP4eOPP0a/fv0AAK+//joKCwsxYsQIR56DkpPM+93Q0ICsrKzoe0v+kZOTg7Fjx+KNN97AtddeCwDo6urCG2+8gXnz5rk7OHLc6dOnceDAAdxyyy1uD4UcVlFRgdLSUrzxxhvRwLalpQXbt2/X7YhE1jHQzXBNTU04ceIEmpqa0NnZiYaGBgDAhRdeiB49euCrX/0qRowYgVtuuQXLli3DsWPH8OCDD+Kuu+5Cbm6uu4MnW7Zt24bt27dj6tSp6NmzJ7Zt24Z7770X3/nOd9CrVy+3h0cJuO+++3DbbbfhK1/5CsaPH49f/OIXaG1txZw5c9weGiXphz/8Ib7+9a9j8ODBOHr0KB566CFkZ2fjpptucntolIDTp0/HZOMbGxvR0NCA3r17Y9CgQbjnnnvwk5/8BF/60pdQUVGBH//4xxgwYED0IpaS4HbbB3LXbbfdJgOI+2/jxo3Rxxw8eFCeMWOGnJeXJ/ft21e+//775c8//9y9QVNCdu7cKU+YMEEuKiqSu3fvLl900UXy448/Ln/22WduD42S8NRTT8mDBg2Sc3Jy5PHjx8tvvfWW20MiB8yaNUsuKyuTc3Jy5PPPP1+eNWuW/OGHH7o9LErQxo0bhefa2267TZblSIuxH//4x3L//v3l3Nxc+corr5T379/v7qADQpJlWXYryCYiIiIiShV2XSAiIiKiQGKgS0RERESBxECXiIiIiAKJgS4RERERBRIDXSIiIiIKJAa6RERERBRIDHSJiIiIKJAY6BIReVB5eTkkSYIkSTh16pTbw0nYm2++GX0dXOWJiNKNgS4RUYp0dnZi4sSJuO6662J+Hg6HMXDgQPzrv/6r4d8/8sgjCIVCKCoqSuUwU2rixIkIhUL41re+5fZQiCgDMdAlIkqR7OxsPPvss3j11VfxX//1X9Gfz58/H71798ZDDz1k+Pc9e/ZEaWkpJElKeAwdHR0J/60TcnJyUFpairy8PFfHQUSZiYEuEVEKDRs2DHV1dZg/fz5CoRD+9Kc/Yc2aNfj973+PnJwcW9v6xz/+gZtuugnnn38+8vPzMXLkSKxevTrmMVOmTMG8efNwzz33oG/fvpg2bRoA4L333sPVV1+NwsJC9OzZE5dddhkOHDgAIFJeMH78eBQUFKC4uBiTJk3CoUOHotv805/+hDFjxqB79+4YMmQIFi9ejLNnz0Z/f+rUKcydOxf9+/dH9+7d8eUvfxkvvfRSoruMiMgx57k9ACKioJs/fz5eeOEF3HLLLdizZw8WLVqE0aNH297OZ599hrFjx2LhwoUoLCzEyy+/jFtuuQVDhw7F+PHjo4977rnncMcdd2Dr1q0AgCNHjmDy5MmYMmUKNmzYgMLCQmzduhVnz57F2bNnce211+L222/H6tWr0dHRgbfffjuaRd68eTNuvfVWPPnkk9Hg+Pvf/z4A4KGHHkJXVxdmzJiBTz/9FH/4wx8wdOhQ/O1vf0N2drYDe46IKDmSLMuy24MgIgq6ffv24aKLLsLIkSOxa9cunHeecZ6hvLwc99xzD+655x7Dx1199dWorKzEz372MwCRjG5LSwt27doVfcwDDzyANWvWYP/+/ejWrVvM3584cQJ9+vTBm2++icsvvzxu+1dddRWuvPJK1NbWRn/2hz/8AQsWLMDRo0fx2muvYcaMGdi7dy+GDRumO87Zs2fj1KlTePHFFw1fDxGRk5jRJSJKg9/97nfIz89HY2MjPvroI5SXl9veRmdnJx5//HH88Y9/xJEjR9DR0YH29nbk5+fHPG7s2LEx/25oaMBll10WF+QCQO/evTF79mxMmzYN//zP/4yrrroK3/rWt1BWVgYAeOedd7B161Y89thjMeP47LPPcObMGTQ0NOCCCy4wDHKJiNzCGl0iohSrr6/Hz3/+c7z00ksYP348vvvd7yKRm2k//elP8ctf/hILFy7Exo0b0dDQgGnTpsVNOCsoKIj5t9lEsJUrV2Lbtm2YOHEi1q5di2HDhuGtt94CAJw+fRqLFy9GQ0ND9L89e/bggw8+QPfu3TnJjIg8jRldIqIUOnPmDGbPno077rgDU6dORUVFBUaOHInf/OY3uOOOO2xta+vWrfjGN76B73znOwCArq4uvP/++xgxYoTh340aNQrPPfccPv/8c2FWFwCqqqpQVVWF2tpaVFdXY9WqVbjkkkswZswY7N+/HxdeeKHutj/66CO8//77zOoSkecwo0tElEK1tbWQZRl1dXUAIrW3P/vZz7BgwQIcPHjQ1ra+9KUv4fXXX0d9fT327t2LuXPn4vjx46Z/N2/ePLS0tODGG2/EX/7yF3zwwQf4z//8T+zfvx+NjY2ora3Ftm3bcOjQIbz22mv44IMPcNFFFwEAFi1ahN///vdYvHgx3nvvPezduxdr1qzBgw8+CAC4/PLLMXnyZFx//fV4/fXX0djYiPXr1+PVV1+1t6OIiFKAgS4RUYr8+c9/xvLly7Fy5cqYOtq5c+di4sSJtksYHnzwQYwZMwbTpk3DlClTUFpaamm1sT59+mDDhg04ffo0Lr/8cowdOxYrVqxAt27dkJ+fj3379uH666/HsGHD8P3vfx933XUX5s6dCwCYNm0aXnrpJbz22msYN24cLrnkEvz85z/H4MGDo9t//vnnMW7cONx0000YMWIEFixYgM7OTus7iogoRdh1gYjIg6x2XfALdl0gIjcwo0tE5FELFy5Ejx49EA6H3R5KwjZv3owePXrErAxHRJQuzOgSEXnQoUOH8PnnnwMAhgwZgqwsf+Yl2tracOTIEQBAjx49UFpa6vKIiCiTMNAlIiIiokDyZ4qAiIiIiMgEA10iIiIiCiQGukREREQUSAx0iYiIiCiQGOgSERERUSAx0CUiIiKiQGKgS0RERESBxECXiIiIiAKJgS4RERERBdL/D7BdMPcojb1hAAAAAElFTkSuQmCC\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "import astropy" + ], + "metadata": { + "id": "AMWfW90EdEPh" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "from astropy.table import QTable\n", + "import astropy.units as u\n", + "import numpy as np\n" + ], + "metadata": { + "id": "SoLqfFxudNWf" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "pip install astropy astroquery matplotlib\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "RpwXcCvXk91v", + "outputId": "c12107ad-736e-48e8-aee0-c1b8591e87a6" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Requirement already satisfied: astropy in /usr/local/lib/python3.10/dist-packages (5.3.4)\n", + "Collecting astroquery\n", + " Downloading astroquery-0.4.7-py3-none-any.whl.metadata (7.2 kB)\n", + "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (3.9.0)\n", + "Requirement already satisfied: numpy<2,>=1.21 in /usr/local/lib/python3.10/dist-packages (from astropy) (1.26.4)\n", + "Requirement already satisfied: pyerfa>=2.0 in /usr/local/lib/python3.10/dist-packages (from astropy) (2.0.1.4)\n", + "Requirement already satisfied: PyYAML>=3.13 in /usr/local/lib/python3.10/dist-packages (from astropy) (6.0.1)\n", + "Requirement already satisfied: packaging>=19.0 in /usr/local/lib/python3.10/dist-packages (from astropy) (24.1)\n", + "Requirement already satisfied: requests>=2.19 in /usr/local/lib/python3.10/dist-packages (from astroquery) (2.31.0)\n", + "Requirement already satisfied: beautifulsoup4>=4.8 in /usr/local/lib/python3.10/dist-packages (from astroquery) (4.12.3)\n", + "Requirement already satisfied: html5lib>=0.999 in /usr/local/lib/python3.10/dist-packages (from astroquery) (1.1)\n", + "Requirement already satisfied: keyring>=15.0 in /usr/lib/python3/dist-packages (from astroquery) (23.5.0)\n", + "Collecting pyvo>=1.1 (from astroquery)\n", + " Downloading pyvo-1.5.2-py3-none-any.whl.metadata (4.7 kB)\n", + "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.2.1)\n", + "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (0.12.1)\n", + "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (4.53.1)\n", + "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.4.5)\n", + "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (9.4.0)\n", + "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (3.1.2)\n", + "Requirement already satisfied: python-dateutil>=2.7 in 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(from requests>=2.19->astroquery) (2024.7.4)\n", + "Downloading astroquery-0.4.7-py3-none-any.whl (5.3 MB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.3/5.3 MB\u001b[0m \u001b[31m9.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hDownloading pyvo-1.5.2-py3-none-any.whl (910 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m910.8/910.8 kB\u001b[0m \u001b[31m9.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hInstalling collected packages: pyvo, astroquery\n", + "Successfully installed astroquery-0.4.7 pyvo-1.5.2\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import numpy as np\n", + "from astropy.table import Table\n", + "import matplotlib.pyplot as plt\n", + "from astroquery.simbad import Simbad\n", + "from astropy.coordinates import SkyCoord\n", + "import astropy.units as u\n" + ], + "metadata": { + "id": "-fUNm7w7lIXJ" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "import numpy as np\n", + "from astropy.table import Table\n", + "import matplotlib.pyplot as plt\n", + "from astroquery.gaia import Gaia\n", + "import astropy.units as u\n", + "from astropy.coordinates import SkyCoord\n", + "\n", + "# Define the query for Gaia\n", + "query = \"\"\"\n", + "SELECT TOP 1000\n", + " source_id,\n", + " ra,\n", + " dec,\n", + " phot_g_mean_mag,\n", + " bp_rp\n", + "FROM gaiadr2.gaia_source\n", + "WHERE CONTAINS(\n", + " POINT('ICRS', ra, dec),\n", + " CIRCLE('ICRS', 75.0, -65.0, 5)\n", + ")=1\n", + "\"\"\"\n", + "\n", + "# Execute the query\n", + "job = Gaia.launch_job(query)\n", + "result = job.get_results()\n", + "\n", + "# Convert the results to an Astropy table\n", + "star_table = Table(result)\n", + "\n", + "# Display the table\n", + "print(star_table)\n", + "\n", + "# Plot the star field\n", + "plt.figure(figsize=(10, 10))\n", + "plt.scatter(star_table['ra'], star_table['dec'], s=10, c='white')\n", + "plt.gca().invert_yaxis() # Invert y-axis to match astronomical convention\n", + "plt.gca().set_facecolor('black') # Set the background color to black\n", + "plt.title('Star Field of Dorado Constellation')\n", + "plt.xlabel('RA (degrees)')\n", + "plt.ylabel('Dec (degrees)')\n", + "plt.show()\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "uUnEhR9ClNDp", + "outputId": "31f08023-3207-48e6-dc82-14f08867fb28" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + " SOURCE_ID ra ... phot_g_mean_mag bp_rp \n", + " deg ... mag mag \n", + "------------------- ----------------- ... --------------- ------------\n", + "4662919794243475840 72.7660842539151 ... 21.10991 --\n", + "4662919003978495488 72.82551465050375 ... 16.21827 1.8037281\n", + "4662923505095502080 73.24361411726106 ... 20.848244 -0.29154396\n", + "4662915018242323840 73.15924806671195 ... 20.814703 0.23135567\n", + "4662918007537116288 73.01395758290441 ... 20.276127 0.86989784\n", + "4662937386430040960 72.18974073577743 ... 18.685677 0.89114\n", + "4662925253162516224 73.02975371282093 ... 18.94579 1.2791443\n", + "4662874847410814976 68.77607885434055 ... 16.293564 0.9358797\n", + "4662924222356262528 73.23873690368688 ... 17.773794 -0.1875019\n", + "4662930338390336768 72.94207524304505 ... 20.27316 0.47165298\n", + " ... ... ... ... ...\n", + "4662941956284055168 72.52602339970234 ... 19.662247 0.27460098\n", + "4662923779974132608 73.16113089160135 ... 20.56335 0.4067192\n", + "4662922027635655552 72.8926365632069 ... 19.772848 0.2648239\n", + "4662942402952360960 72.48492768762556 ... 18.885538 1.049612\n", + "4662914502852743808 73.11497486280486 ... 20.085327 -0.017742157\n", + "4662929037015853824 72.73728251686379 ... 21.115808 --\n", + "4662906222147998976 69.20045755557811 ... 19.598658 --\n", + "4662917182905118976 73.0811393979387 ... 20.7303 0.40285492\n", + "4662918179344862592 72.96356054194248 ... 19.981756 0.073246\n", + "4662841484104750720 69.87093736591488 ... 20.877447 0.87417984\n", + "Length = 1000 rows\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "import numpy as np\n", + "from astropy.table import Table\n", + "import matplotlib.pyplot as plt\n", + "from astroquery.gaia import Gaia\n", + "import astropy.units as u\n", + "from astropy.coordinates import SkyCoord\n", + "\n", + "# Define the query for Gaia\n", + "query = \"\"\"\n", + "SELECT TOP 1000\n", + " source_id,\n", + " ra,\n", + " dec,\n", + " phot_g_mean_mag,\n", + " bp_rp\n", + "FROM gaiadr2.gaia_source\n", + "WHERE CONTAINS(\n", + " POINT('ICRS', ra, dec),\n", + " CIRCLE('ICRS', 90.0, -75.0, 5)\n", + ")=1\n", + "\"\"\"\n", + "\n", + "# Execute the query\n", + "job = Gaia.launch_job(query)\n", + "result = job.get_results()\n", + "\n", + "# Convert the results to an Astropy table\n", + "star_table = Table(result)\n", + "\n", + "# Display the table\n", + "print(star_table)\n", + "\n", + "# Plot the star field\n", + "plt.figure(figsize=(10, 10))\n", + "plt.scatter(star_table['ra'], star_table['dec'], s=10, c='white')\n", + "plt.gca().invert_yaxis() # Invert y-axis to match astronomical convention\n", + "plt.gca().set_facecolor('black') # Set the background color to black\n", + "plt.title('Star Field of Mensa Constellation')\n", + "plt.xlabel('RA (degrees)')\n", + "plt.ylabel('Dec (degrees)')\n", + "plt.show()\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "teaFHYJDmH8O", + "outputId": "48a550f6-69fe-4ba5-92f3-81364ef49be0" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + " SOURCE_ID ra ... phot_g_mean_mag bp_rp \n", + " deg ... mag mag \n", + "------------------- ----------------- ... --------------- -----------\n", + "4650814927136960000 85.85262033910165 ... 20.839825 0.73988724\n", + "4650808085281396608 86.39271577504434 ... 20.62958 0.49964714\n", + "4650808394493643008 86.49425140095568 ... 20.585037 0.30471802\n", + "4650809871987381248 86.65624210169915 ... 20.470694 --\n", + "4650805272060164608 87.11597358981999 ... 19.857107 1.1211338\n", + "4650806577730105216 86.88168555052404 ... 18.912148 0.33413315\n", + "4650810013700362368 86.51761427553822 ... 20.93511 0.7413807\n", + "4650810249919557632 86.4551981957551 ... 19.72775 0.12936592\n", + "4650804756660599424 87.11455398622944 ... 20.894976 0.027791977\n", + "4650811388085230464 85.9027602275617 ... 20.83379 0.7212105\n", + " ... ... ... ... ...\n", + "4650814063847213440 85.99411322749931 ... 19.473928 0.824728\n", + "4650811211999103744 86.05100513744152 ... 18.745077 1.1922779\n", + "4650813307932913792 86.03532637051946 ... 19.063814 1.199173\n", + "4650821318049429376 85.7117272002812 ... 20.923588 1.0083065\n", + "4650817744635035264 85.58089699125316 ... 20.13649 0.6758671\n", + "4650806886963681792 86.70888882008953 ... 20.72311 0.5260372\n", + "4650802415919396736 87.23960985565544 ... 20.661968 0.5091858\n", + "4650817160519216768 85.3036841820232 ... 19.507359 0.5188885\n", + "4650809837602302464 86.71935700292266 ... 18.667803 1.2366505\n", + "4650820493414018688 86.02989258830004 ... 20.192488 0.17674828\n", + "Length = 1000 rows\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "from scopesim_templates.stellar import star_field, star_grid\n", + "\n", + "field = star_field(n=400, mmin=15, mmax=25, width=20, height=20, filter_name=\"Ks\")\n", + "grid = star_grid(n=400, mmin=15, mmax=25, separation=1 , filter_name=\"Ks\")\n", + "\n", + "plt.figure(figsize=(14, 7))\n", + "plt.subplot(121)\n", + "\n", + "size = np.log10(field.fields[0][\"weight\"])**2\n", + "plt.scatter(field.fields[0][\"x\"], field.fields[0][\"y\"], s=size, marker=\"o\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 617 + }, + "id": "Mtz9oAyYmu5o", + "outputId": "7a86eefd-bd6f-4fd9-f5b2-49c36208e2c3" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 30 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [], + "metadata": { + "id": "tsRbG1pAnTch" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file diff --git a/DREAMS/Test_codes/inst_pkgs b/DREAMS/Test_codes/inst_pkgs new file mode 120000 index 00000000..c25bddb6 --- /dev/null +++ b/DREAMS/Test_codes/inst_pkgs @@ -0,0 +1 @@ +../.. \ No newline at end of file diff --git a/DREAMS/Test_codes/star_1.py b/DREAMS/Test_codes/star_1.py new file mode 100644 index 00000000..55ac0556 --- /dev/null +++ b/DREAMS/Test_codes/star_1.py @@ -0,0 +1,63 @@ +import os +import pytest +import numpy as np +from astropy.io.fits import HDUList +from matplotlib import pyplot as plt +from matplotlib.colors import LogNorm +import scopesim +import synphot +from scopesim import Source +from astropy.io import fits + + +from scopesim import rc +from scopesim.source.source_templates import star_field +import scopesim_templates as sim_tp +from scopesim.optics.fov_manager import FOVManager + +PLOTS = True + +if rc.__config__["!SIM.tests.run_integration_tests"] is False: + pytestmark = pytest.mark.skip("Ignoring DREAMS integration tests") + +cmds = scopesim.UserCommands(use_instrument="DREAMS") +cmds["!OBS.dit"] = 10 +cmds["!DET.bin_size"] = 1 +cmds["!OBS.sky.bg_mag"] = 14.9 +cmds["!OBS.sky.filter_name"] = "J" +cmds["SIM.sub_pixel.flag"] = True +dreams = scopesim.OpticalTrain(cmds) +dreams["detector_linearity"].include = False + +print("scopesim package loaded successfully.") +x, y = np.meshgrid(np.arange(100), np.arange(100)) +img = np.exp(-1 * ( ( (x - 50) / 5)**2 + ( (y - 50) / 5)**2 ) ) +# Fits headers of the image. Yes it needs a WCS +hdr = fits.Header(dict(NAXIS=2,NAXIS1=img.shape[0]+1,NAXIS2=img.shape[1]+1, CRPIX1=img.shape[0] / 2, CRPIX2=img.shape[1] / 2, CRVAL1=0, CRVAL2=0, CDELT1=0.2/3600, CDELT2=0.2/3600, +CUNIT1="DEG", CUNIT2="DEG", CTYPE1='RA---TAN', CTYPE2='DEC--TAN')) +# Creating an ImageHDU object +hdu = fits.ImageHDU(data=img, header=hdr) + +# Creating of a black body spectrum +wave = np.arange(1000, 35000, 10 ) +bb = synphot.models.BlackBody1D(temperature=5000) +sp = synphot.SourceSpectrum(synphot.Empirical1D, points=wave, lookup_table=bb(wave)) +src = Source(image_hdu=hdu, spectra=sp) +src.shift(10, 10) +dreams.observe(src) +print("yessss anjali") +hdus = dreams.readout() +#dreams.readout(filename="Han.fits") +plt.subplot(121) +wave = np.arange(3000, 11000) +plt.plot(wave, dreams.optics_manager.system_transmission(wave)) +plt.subplot(122) +im = hdus[0][1].data +detector_order = [2, 1, 4, 3, 6, 5] +plt.figure(figsize=(20, 20)) +for plot_number, hdu_number in enumerate(detector_order, 1): + plt.subplot(3, 2, plot_number) + plt.imshow(hdus[0][hdu_number].data, origin="lower", norm=LogNorm()) + plt.colorbar() + +plt.show() diff --git a/DREAMS/default.yaml b/DREAMS/default.yaml new file mode 100644 index 00000000..3c319132 --- /dev/null +++ b/DREAMS/default.yaml @@ -0,0 +1,44 @@ +--- +### default observation parameters needed for DREAMS simulation +object : configuration +alias : OBS +name : DREAMS_default_configuration +description : default parameters needed for the DREAMS simulation + + +packages: + - DREAMS + +yamls : + - DREAMS.yaml + - DREAMS_InGaAs.yaml +properties : + airmass : 1.2 + declination : -31.273 + hour_angle : 0 + pupil_angle : 0 + dit : 8 + ndit : 1 + filter_name : J + sky : + bg_mag : 14.5 + filter_name : J + +--- +### default simulation parameters needed for DREAMS simulation +object : simulation +alias : OBS +name : LFAO_simulation_paramters +description : RC simulation paramters + +properties : + random : + seed : 9001 + + spectral : + wave_min : 1.17 + wave_mid : 1.42 + wave_max : 1.67 + + computing : + preload_field_of_view : False diff --git a/DREAMS/filters/H.dat b/DREAMS/filters/H.dat new file mode 100644 index 00000000..7a445e31 --- /dev/null +++ b/DREAMS/filters/H.dat @@ -0,0 +1,367 @@ +# source : Generic_Bessell.I SVO +# wavelength_unit : angstrom +# download_date : 2020-05-23 +wavelength transmission +14900.0 0.90802 +14905.0 0.958796 +14910.0 0.913225 +14915.0 0.849135 +14920.0 0.884093 +14925.0 0.915954 +14930.0 0.928744 +14935.0 0.949936 +14940.0 0.945656 +14945.0 0.927238 +14950.0 0.900331 +14955.0 0.895292 +14960.0 0.898208 +14965.0 0.900709 +14970.0 0.943867 +14975.0 0.955807 +14980.0 0.932836 +14985.0 0.944357 +14990.0 0.954788 +14995.0 0.954577 +15000.0 0.970904 +15005.0 0.985127 +15009.9 0.986479 +15015.0 0.973983 +15020.0 0.96211 +15025.0 0.957062 +15029.9 0.942257 +15035.0 0.916619 +15040.0 0.893669 +15045.0 0.906644 +15049.9 0.93975 +15055.0 0.973944 +15060.0 0.987869 +15065.0 0.993428 +15069.9 0.986808 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b/DREAMS/filters/H_block.dat @@ -0,0 +1,8 @@ +# source : Generic_Bessell.I SVO +# wavelength_unit : angstrom +# download_date : 2020-05-23 +wavelength transmission +14900.0 0.0 +16700.0 0.0 + + diff --git a/DREAMS/filters/I.dat b/DREAMS/filters/I.dat new file mode 100644 index 00000000..2fbe0590 --- /dev/null +++ b/DREAMS/filters/I.dat @@ -0,0 +1,29 @@ +# source : Generic_Bessell.I SVO +# wavelength_unit : angstrom +# download_date : 2020-05-23 +wavelength transmission +7000.0 0.0000000000 +7100.0 0.0240000000 +7200.0 0.2320000000 +7300.0 0.5550000000 +7400.0 0.7850000000 +7500.0 0.9100000000 +7600.0 0.9650000000 +7700.0 0.9850000000 +7800.0 0.9900000000 +7900.0 0.9950000000 +8000.0 1.0000000000 +8100.0 1.0000000000 +8200.0 0.9900000000 +8300.0 0.9800000000 +8400.0 0.9500000000 +8500.0 0.9100000000 +8600.0 0.8600000000 +8700.0 0.7500000000 +8800.0 0.5600000000 +8900.0 0.3300000000 +9000.0 0.1500000000 +9100.0 0.0300000000 +9200.0 0.0000000000 + + diff --git a/DREAMS/filters/J.dat 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