From bd6c8c98abed53c67a39a20ad4a17ef7d0340488 Mon Sep 17 00:00:00 2001 From: Tobin Ford Date: Thu, 12 Dec 2024 14:44:39 -0700 Subject: [PATCH] IEC-63556 chamber improvements --- docs/source/_autosummary/pvdeg.diffusion.rst | 8 + docs/source/_autosummary/pvdeg.humidity.rst | 6 - docs/source/_autosummary/pvdeg.spectral.rst | 8 +- .../source/_autosummary/pvdeg.temperature.rst | 16 +- docs/source/_autosummary/pvdeg.utilities.rst | 30 +- docs/source/_autosummary/pvdeg.weather.rst | 6 - pvdeg/chamber.py | 67 +- pvdeg/decorators.py | 83 +- pvdeg/degradation.py | 261 ++- pvdeg/humidity.py | 2 +- pvdeg/spectral.py | 39 +- testing-setpoints/63556.png | Bin 0 -> 19430 bytes testing-setpoints/IEC-61215-MQT-11.csv | 8 +- testing-setpoints/IEC-61215-MQT-12.csv | 11 + testing-setpoints/standards_testing.ipynb | 1760 ++++++++++++++++- tests/test_degradation.py | 22 +- .../3 - Spectral Degradation.ipynb | 332 +++- .../Chamber Irradiance.ipynb | 165 +- .../tutorials_and_tools/Chamber.ipynb | 654 +++++- 19 files changed, 3182 insertions(+), 296 deletions(-) create mode 100644 testing-setpoints/63556.png create mode 100644 testing-setpoints/IEC-61215-MQT-12.csv diff --git a/docs/source/_autosummary/pvdeg.diffusion.rst b/docs/source/_autosummary/pvdeg.diffusion.rst index 7e20b0e3..6e2e3fb7 100644 --- a/docs/source/_autosummary/pvdeg.diffusion.rst +++ b/docs/source/_autosummary/pvdeg.diffusion.rst @@ -19,6 +19,7 @@ pvdeg.diffusion :nosignatures: + pvdeg.diffusion.esdiffusion pvdeg.diffusion.module_front @@ -35,6 +36,13 @@ pvdeg.diffusion + .. autofunction:: esdiffusion + + .. _sphx_glr_backref_pvdeg.diffusion.esdiffusion: + + .. minigallery:: pvdeg.diffusion.esdiffusion + :add-heading: + .. autofunction:: module_front .. _sphx_glr_backref_pvdeg.diffusion.module_front: diff --git a/docs/source/_autosummary/pvdeg.humidity.rst b/docs/source/_autosummary/pvdeg.humidity.rst index b7f29c8f..c2a5fe81 100644 --- a/docs/source/_autosummary/pvdeg.humidity.rst +++ b/docs/source/_autosummary/pvdeg.humidity.rst @@ -31,10 +31,7 @@ pvdeg.humidity pvdeg.humidity.module pvdeg.humidity.moisture_eva_back pvdeg.humidity.psat -<<<<<<< HEAD pvdeg.humidity.rh_internal_cell_backside -======= ->>>>>>> development pvdeg.humidity.surface_outside @@ -135,7 +132,6 @@ pvdeg.humidity .. minigallery:: pvdeg.humidity.psat :add-heading: -<<<<<<< HEAD .. autofunction:: rh_internal_cell_backside .. _sphx_glr_backref_pvdeg.humidity.rh_internal_cell_backside: @@ -143,8 +139,6 @@ pvdeg.humidity .. minigallery:: pvdeg.humidity.rh_internal_cell_backside :add-heading: -======= ->>>>>>> development .. autofunction:: surface_outside .. _sphx_glr_backref_pvdeg.humidity.surface_outside: diff --git a/docs/source/_autosummary/pvdeg.spectral.rst b/docs/source/_autosummary/pvdeg.spectral.rst index bfb180fc..fd55f3d6 100644 --- a/docs/source/_autosummary/pvdeg.spectral.rst +++ b/docs/source/_autosummary/pvdeg.spectral.rst @@ -19,7 +19,7 @@ pvdeg.spectral :nosignatures: - pvdeg.spectral.get_GTI_from_irradiance_340 + pvdeg.spectral.calc_full_from_irradiance_340 pvdeg.spectral.poa_irradiance pvdeg.spectral.solar_position @@ -37,11 +37,11 @@ pvdeg.spectral - .. autofunction:: get_GTI_from_irradiance_340 + .. autofunction:: calc_full_from_irradiance_340 - .. _sphx_glr_backref_pvdeg.spectral.get_GTI_from_irradiance_340: + .. _sphx_glr_backref_pvdeg.spectral.calc_full_from_irradiance_340: - .. minigallery:: pvdeg.spectral.get_GTI_from_irradiance_340 + .. minigallery:: pvdeg.spectral.calc_full_from_irradiance_340 :add-heading: .. autofunction:: poa_irradiance diff --git a/docs/source/_autosummary/pvdeg.temperature.rst b/docs/source/_autosummary/pvdeg.temperature.rst index b79495ee..5e628c02 100644 --- a/docs/source/_autosummary/pvdeg.temperature.rst +++ b/docs/source/_autosummary/pvdeg.temperature.rst @@ -20,12 +20,10 @@ pvdeg.temperature pvdeg.temperature.cell -<<<<<<< HEAD pvdeg.temperature.chamber_sample_temperature pvdeg.temperature.fdm_temperature -======= + pvdeg.temperature.fdm_temperature_irradiance pvdeg.temperature.map_model ->>>>>>> development pvdeg.temperature.module pvdeg.temperature.temperature @@ -50,7 +48,6 @@ pvdeg.temperature .. minigallery:: pvdeg.temperature.cell :add-heading: -<<<<<<< HEAD .. autofunction:: chamber_sample_temperature .. _sphx_glr_backref_pvdeg.temperature.chamber_sample_temperature: @@ -63,13 +60,20 @@ pvdeg.temperature .. _sphx_glr_backref_pvdeg.temperature.fdm_temperature: .. minigallery:: pvdeg.temperature.fdm_temperature -======= + :add-heading: + + .. autofunction:: fdm_temperature_irradiance + + .. _sphx_glr_backref_pvdeg.temperature.fdm_temperature_irradiance: + + .. minigallery:: pvdeg.temperature.fdm_temperature_irradiance + :add-heading: + .. autofunction:: map_model .. _sphx_glr_backref_pvdeg.temperature.map_model: .. minigallery:: pvdeg.temperature.map_model ->>>>>>> development :add-heading: .. autofunction:: module diff --git a/docs/source/_autosummary/pvdeg.utilities.rst b/docs/source/_autosummary/pvdeg.utilities.rst index 05aef05c..f92a5979 100644 --- a/docs/source/_autosummary/pvdeg.utilities.rst +++ b/docs/source/_autosummary/pvdeg.utilities.rst @@ -27,24 +27,19 @@ pvdeg.utilities pvdeg.utilities.get_kinetics pvdeg.utilities.get_state_bbox pvdeg.utilities.gid_downsampling -<<<<<<< HEAD pvdeg.utilities.kj_mol_to_ev - pvdeg.utilities.meta_as_dict - pvdeg.utilities.plot_water_2d - pvdeg.utilities.quantile_df -======= pvdeg.utilities.linear_normalize pvdeg.utilities.merge_sparse pvdeg.utilities.meta_as_dict pvdeg.utilities.new_id pvdeg.utilities.nrel_kestrel_check + pvdeg.utilities.plot_water_2d pvdeg.utilities.quantile_df pvdeg.utilities.read_material pvdeg.utilities.remove_scenario_filetrees pvdeg.utilities.restore_gids pvdeg.utilities.search_json pvdeg.utilities.strip_normalize_tmy ->>>>>>> development pvdeg.utilities.tilt_azimuth_scan pvdeg.utilities.ts_gid_df pvdeg.utilities.write_gids @@ -119,13 +114,13 @@ pvdeg.utilities .. minigallery:: pvdeg.utilities.gid_downsampling :add-heading: -<<<<<<< HEAD .. autofunction:: kj_mol_to_ev .. _sphx_glr_backref_pvdeg.utilities.kj_mol_to_ev: .. minigallery:: pvdeg.utilities.kj_mol_to_ev -======= + :add-heading: + .. autofunction:: linear_normalize .. _sphx_glr_backref_pvdeg.utilities.linear_normalize: @@ -138,7 +133,6 @@ pvdeg.utilities .. _sphx_glr_backref_pvdeg.utilities.merge_sparse: .. minigallery:: pvdeg.utilities.merge_sparse ->>>>>>> development :add-heading: .. autofunction:: meta_as_dict @@ -148,13 +142,6 @@ pvdeg.utilities .. minigallery:: pvdeg.utilities.meta_as_dict :add-heading: -<<<<<<< HEAD - .. autofunction:: plot_water_2d - - .. _sphx_glr_backref_pvdeg.utilities.plot_water_2d: - - .. minigallery:: pvdeg.utilities.plot_water_2d -======= .. autofunction:: new_id .. _sphx_glr_backref_pvdeg.utilities.new_id: @@ -167,7 +154,13 @@ pvdeg.utilities .. _sphx_glr_backref_pvdeg.utilities.nrel_kestrel_check: .. minigallery:: pvdeg.utilities.nrel_kestrel_check ->>>>>>> development + :add-heading: + + .. autofunction:: plot_water_2d + + .. _sphx_glr_backref_pvdeg.utilities.plot_water_2d: + + .. minigallery:: pvdeg.utilities.plot_water_2d :add-heading: .. autofunction:: quantile_df @@ -177,8 +170,6 @@ pvdeg.utilities .. minigallery:: pvdeg.utilities.quantile_df :add-heading: -<<<<<<< HEAD -======= .. autofunction:: read_material .. _sphx_glr_backref_pvdeg.utilities.read_material: @@ -214,7 +205,6 @@ pvdeg.utilities .. minigallery:: pvdeg.utilities.strip_normalize_tmy :add-heading: ->>>>>>> development .. autofunction:: tilt_azimuth_scan .. _sphx_glr_backref_pvdeg.utilities.tilt_azimuth_scan: diff --git a/docs/source/_autosummary/pvdeg.weather.rst b/docs/source/_autosummary/pvdeg.weather.rst index 4922b8be..1dd72fc9 100644 --- a/docs/source/_autosummary/pvdeg.weather.rst +++ b/docs/source/_autosummary/pvdeg.weather.rst @@ -23,10 +23,7 @@ pvdeg.weather pvdeg.weather.get pvdeg.weather.get_NSRDB pvdeg.weather.get_NSRDB_fnames -<<<<<<< HEAD -======= pvdeg.weather.get_anywhere ->>>>>>> development pvdeg.weather.get_satellite pvdeg.weather.ini_h5_geospatial pvdeg.weather.is_leap_year @@ -79,8 +76,6 @@ pvdeg.weather .. minigallery:: pvdeg.weather.get_NSRDB_fnames :add-heading: -<<<<<<< HEAD -======= .. autofunction:: get_anywhere .. _sphx_glr_backref_pvdeg.weather.get_anywhere: @@ -88,7 +83,6 @@ pvdeg.weather .. minigallery:: pvdeg.weather.get_anywhere :add-heading: ->>>>>>> development .. autofunction:: get_satellite .. _sphx_glr_backref_pvdeg.weather.get_satellite: diff --git a/pvdeg/chamber.py b/pvdeg/chamber.py index 7533816b..b3ca40de 100644 --- a/pvdeg/chamber.py +++ b/pvdeg/chamber.py @@ -478,10 +478,6 @@ def __init__( length=None, width=None, ): - # f = utilities.read_material() - # f = open(os.path.join(DATA_DIR, "materials.json")) - # self.materials = json.load(f) - self.absorptance = absorptance self.length = length self.width = width @@ -521,11 +517,6 @@ def setEncapsulant(self, pvdeg_file: str, key: str, thickness: float, fp: str = self.diffusivity_encap_pre = material_dict["Do"] self.solubility_encap_ea = material_dict["Eas"] self.solubility_encap_pre = material_dict["So"] - - # self.diffusivity_encap_ea = (self.materials)[key]["Ead"] - # self.diffusivity_encap_pre = (self.materials)[key]["Do"] - # self.solubility_encap_ea = (self.materials)[key]["Eas"] - # self.solubility_encap_pre = (self.materials)[key]["So"] self.encap_thickness = thickness def setBacksheet(self, pvdeg_file: str, key: str, thickness: float, fp: str = None ) -> None: @@ -606,7 +597,7 @@ def setAbsorptance(self, absorptance: float): class Chamber(Sample): - def __init__(self, fp: str = None, setpoint_names: list[str] = None, **kwargs): + def __init__(self, fp: str = None, setpoint_names: list[str] = None, setpoints: pd.DataFrame=None, **kwargs): """ Create a chamber stress test object. @@ -619,7 +610,14 @@ def __init__(self, fp: str = None, setpoint_names: list[str] = None, **kwargs): """ super().__init__() - self.setpoint_timeseries(fp, setpoint_names=setpoint_names, **kwargs) + + if setpoints is not None: + if setpoints.isna().any().any(): + raise ValueError("self.setpoints dataframe contains NaN's, may break simulation results, remove the nan's to continue") + + self.setpoints = setpoints + else: + self.setpoint_timeseries(fp, setpoint_names=setpoint_names, **kwargs) def setpoint_timeseries( self, fp: str, setpoint_names: list[str] = None, **kwargs @@ -627,13 +625,18 @@ def setpoint_timeseries( """ Read a setpoints CSV and create a timeseries of setpoint values """ + self.setpoints = setpoints_timeseries_from_csv(fp, setpoint_names, **kwargs) def plot_setpoints(self) -> None: """ Plot setpoint timeseries values """ - self.setpoints.plot(title="Chamber Setpoints") + fig, ax = plt.subplots(figsize=(12, 6)) # Adjust the width (12) and height (6) + self.setpoints.plot(title="Chamber Setpoints", ax=ax) + + plt.show() + def calc_temperatures( self, air_temp_0: float, sample_temp_0: float, tau_c: float, tau_s: float @@ -667,12 +670,12 @@ def calc_temperatures( "setpoint_irradiance_340" in self.setpoints.columns and "setpoint_irradiance_full" not in self.setpoints.columns ): - # gti calculation is very slow because of integration print("Calculating GTI...") # should this be setpoint irradiance full, it is not a setpoint - self.setpoints["setpoint_irradiance_full"] = spectral.get_GTI_from_irradiance_340( + # this may be misleading + self.setpoints["setpoint_irradiance_full"] = spectral.calc_full_from_irradiance_340( self.setpoints["setpoint_irradiance_340"] - ) # this may be misleading + ) print('Saved in self.setpoints as "setpoints_irradiance_full') self.sample_temperature = sample_temperature( @@ -696,10 +699,20 @@ def calc_water_vapor_pressure(self): self.air_temperature.to_numpy(dtype=np.float64), self.setpoints["setpoint_relative_humidity"].to_numpy(dtype=np.float64), ) + + name = "Water Vapor Pressure" + index = self.setpoints.index + self.water_vapor_pressure = pd.Series( - res, index=self.setpoints.index, name="Water Vapor Pressure" + res, + index=index, + name=name ) + # self.water_vapor_pressure = pd.Series( + # res, index=self.setpoints.index, name="Water Vapor Pressure" + # ) + def calc_sample_relative_humidity(self): """Calculate sample percent relative humidity""" res = humidity.rh_at_sample_temperature( @@ -732,14 +745,11 @@ def calc_back_encapsulant_moisture(self, n_steps: int = 20): permiability = utilities.kj_mol_to_ev(self.permiability_back_ea) res, _ = humidity.moisture_eva_back( - eva_moisture_0=self.equilibrium_encapsulant_water.iloc[0], - sample_temp=self.sample_temperature, - rh_at_sample_temp=self.sample_relative_humidity, - equilibrium_eva_water=self.equilibrium_encapsulant_water, - # pet_permiability=utilities.kj_mol_to_ev( - # self.permiability_back_ea - # ), # kJ/mol -> eV - pet_permiability=permiability, + eva_moisture_0=self.equilibrium_encapsulant_water.iloc[0], # 33100 nans + sample_temp=self.sample_temperature, # no nans + rh_at_sample_temp=self.sample_relative_humidity, # 33100 nans + equilibrium_eva_water=self.equilibrium_encapsulant_water, # above + pet_permiability=permiability, pet_prefactor=self.permiability_back_pre, thickness_eva=self.encap_thickness, # mm thickness_pet=self.back_thickness, # mm @@ -747,7 +757,6 @@ def calc_back_encapsulant_moisture(self, n_steps: int = 20): ) self.back_encapsulant_moisture = pd.Series( - # res, index=self.setpoints.index, name="Back Encapsulant Moisture" res, index=self.setpoints.index, name="Back Encapsulant Moisture" @@ -830,6 +839,10 @@ def sample_conditions( pandas dataframe containing [sample temperature, sample relative humidity, equilibrium encapsulant water, back encapsulant moisture, relative humidity internal on back of cells] """ + + if self.setpoints.isna().any().any(): + raise ValueError("self.setpoints dataframe contains NaN's, may break simulation results, remove the nan's to continue") + self.sample_temperature = sample_temperature( self.setpoints, air_temperature=self.air_temperature, @@ -854,7 +867,7 @@ def sample_conditions( ).T return sample_df - def gti_from_irradiance_340(self) -> pd.Series: + def full_from_irradiance_340(self) -> pd.Series: """ Calculate full spectrum GTI from irradiance at 340 nm @@ -863,7 +876,7 @@ def gti_from_irradiance_340(self) -> pd.Series: gti: pd.Series full spectrum irradiance using ASTM G173-03 AM1.5 spectrum. """ - self.setpoints["setpoint_irradiance_full"] = spectral.get_GTI_from_irradiance_340( + self.setpoints["setpoint_irradiance_full"] = spectral.calc_full_from_irradiance_340( self.setpoints["setpoint_irradiance_340"] ) diff --git a/pvdeg/decorators.py b/pvdeg/decorators.py index b5927399..469bc0b0 100644 --- a/pvdeg/decorators.py +++ b/pvdeg/decorators.py @@ -3,6 +3,9 @@ Private API, should only be used in PVDeg implemenation files. """ +import functools +import inspect +import warnings def geospatial_quick_shape(numeric_or_timeseries: bool, shape_names: list[str]) -> None: """ @@ -34,7 +37,7 @@ def geospatial_quick_shape(numeric_or_timeseries: bool, shape_names: list[str]) * Note: we cannot autotemplate functions with ambiguous return types that depend on runtime input, the function will need strictly return a timeseries or numeric but not one or the other. - Parameters: + Parameters ----------- numeric_or_timeseries: bool indicate whether the function returns a single numeric/tuple of numerics @@ -43,7 +46,7 @@ def geospatial_quick_shape(numeric_or_timeseries: bool, shape_names: list[str]) shape_names: list[str] list of return value names. These will become the xarray datavariable names in the output. - Modifies: + Modifies --------- func.numeric_or_timeseries sets to numeric_or_timeseries argument @@ -57,3 +60,79 @@ def decorator(func): return func return decorator + +# Taken from: https://stackoverflow.com/questions/2536307/decorators-in-the-python-standard-lib-deprecated-specifically +# A future Python version (after 3.13) will include the warnings.deprecated decorator +def deprecated(reason): + """ + This is a decorator which can be used to mark functions + as deprecated. It will result in a warning being emitted + when the function is used. + """ + + string_types = (type(b''), type(u'')) + + if isinstance(reason, string_types): + + # The @deprecated is used with a 'reason'. + # + # .. code-block:: python + # + # @deprecated("please, use another function") + # def old_function(x, y): + # pass + + def decorator(func1): + + if inspect.isclass(func1): + fmt1 = "Call to deprecated class {name} ({reason})." + else: + fmt1 = "Call to deprecated function {name} ({reason})." + + @functools.wraps(func1) + def new_func1(*args, **kwargs): + warnings.simplefilter('always', DeprecationWarning) + warnings.warn( + fmt1.format(name=func1.__name__, reason=reason), + category=DeprecationWarning, + stacklevel=2 + ) + warnings.simplefilter('default', DeprecationWarning) + return func1(*args, **kwargs) + + return new_func1 + + return decorator + + elif inspect.isclass(reason) or inspect.isfunction(reason): + + # The @deprecated is used without any 'reason'. + # + # .. code-block:: python + # + # @deprecated + # def old_function(x, y): + # pass + + func2 = reason + + if inspect.isclass(func2): + fmt2 = "Call to deprecated class {name}." + else: + fmt2 = "Call to deprecated function {name}." + + @functools.wraps(func2) + def new_func2(*args, **kwargs): + warnings.simplefilter('always', DeprecationWarning) + warnings.warn( + fmt2.format(name=func2.__name__), + category=DeprecationWarning, + stacklevel=2 + ) + warnings.simplefilter('default', DeprecationWarning) + return func2(*args, **kwargs) + + return new_func2 + + else: + raise TypeError(repr(type(reason))) \ No newline at end of file diff --git a/pvdeg/degradation.py b/pvdeg/degradation.py index 7c9b85c5..55cf4441 100644 --- a/pvdeg/degradation.py +++ b/pvdeg/degradation.py @@ -13,7 +13,8 @@ from . import spectral from . import weather -from pvdeg.decorators import geospatial_quick_shape +from typing import Optional +from pvdeg.decorators import geospatial_quick_shape, deprecated # TODO: Clean up all those functions and add gaps functionality @@ -862,33 +863,70 @@ def _gJtoMJ(gJ): return MJ +# new version of degradation def degradation( - spectra: pd.Series, - rh_module: pd.Series, - temp_module: pd.Series, - wavelengths: Union[int, np.ndarray[float]], + spectra_df: pd.DataFrame, + conditions_df: pd.DataFrame = None, + temp_module: pd.Series = None, + rh_module: pd.Series = None, Ea: float = 40.0, n: float = 1.0, p: float = 0.5, C2: float = 0.07, C: float = 1.0, -) -> float: +)-> float: """ Compute degredation as double integral of Arrhenius (Activation Energy, RH, Temperature) and spectral (wavelength, irradiance) functions over wavelength and time. + .. math:: + + D = C \\int_{0}^{t} RH(t)^n \\cdot e^{\\frac{-E_a}{RT(t)}} \\int_{\\lambda} [e^{-C_2 \\lambda} \\cdot G(\\lambda, t)]^p d\\lambda dt + Parameters ---------- - spectra : pd.Series type=Float - front or rear irradiance at each wavelength in "wavelengths" [W/m^2 nm] - rh_module : pd.Series type=Float - module RH, time indexed [%] - temp_module : pd.Series type=Float - module temperature, time indexed [C] - wavelengths : int-array - integer array (or list) of wavelengths tested w/ uniform delta - in nanometers [nm] + spectra_df : pd.DataFrame + front or rear irradiance data in dataframe format + + - `data`: Spectral irradiance values for each wavelength [W/m^2 nm]. + - `index`: pd.DateTimeIndex + - `columns`: Wavelengths as floats (e.g., 280, 300, etc.). + + Example:: + + timestamp 280 300 320 340 360 380 400 + 2021-03-09 10:00:00 0.6892 0.4022 0.6726 0.0268 0.3398 0.9432 0.7411 + 2021-03-09 11:00:00 0.1558 0.5464 0.6896 0.7828 0.5050 0.9336 0.4652 + 2021-03-09 12:00:00 0.2278 0.9057 0.2639 0.0572 0.9906 0.9370 0.1800 + 2021-03-09 13:00:00 0.3742 0.0358 0.4052 0.9578 0.1044 0.8917 0.4876 + + conditions_df : pd.DataFrame, optional + Environmental conditions including temperature and relative humidity. + + - `index`: pd.DateTimeIndex + - `columns`: (required) + - "temperature" [°C or K] + - "relative_humidity" [%] + + Example:: + + timestamp temperature relative_humidity + 2021-03-09 10:00:00 298.0 45.0 + 2021-03-09 11:00:00 303.0 50.0 + 2021-03-09 12:00:00 310.0 55.0 + 2021-03-09 13:00:00 315.0 60.0 + + temp_module : pd.Series, optional + Module temperatures [°C]. Required if `conditions_df` is not provided. Time indexed same as spectra_df + + rh_module : pd.Series, optional + Relative humidity values [%]. Required if `conditions_df` is not provided. Time indexed same as spectra_df + + Example:: + + 30 = 30% + Ea : float Arrhenius activation energy. The default is 40. [kJ/mol] n : float @@ -907,58 +945,183 @@ def degradation( ------- degradation : float Total degredation factor over time and wavelength. - """ - # --- TO DO --- - # unpack input-dataframe - # spectra = df['spectra'] - # temp_module = df['temp_module'] - # rh_module = df['rh_module'] - # Constants - R = 0.0083145 # Gas Constant in [kJ/mol*K] - wav_bin = list(np.diff(wavelengths)) - wav_bin.append(wav_bin[-1]) # Adding a bin for the last wavelength + if conditions_df is not None and (temp_module is not None or rh_module is not None): + raise ValueError("Provide either conditions_df or temp_module and rh_module") - # Integral over Wavelength - try: - irr = pd.DataFrame(spectra.tolist(), index=spectra.index) - irr.columns = wavelengths - except: - # TODO: Fix this except it works on some cases, veto it by cases - print("Removing brackets from spectral irradiance data") - # irr = data['spectra'].str.strip('[]').str.split(',', expand=True).astype(float) - irr = spectra.str.strip("[]").str.split(",", expand=True).astype(float) - irr.columns = wavelengths + if conditions_df is not None: + rh = conditions_df["relative_humidity"].values + temps = conditions_df["temperature"].values + else: + rh = rh_module.values + temps = temp_module.values + + wavelengths = spectra_df.columns.values.astype(float) + irr = spectra_df.values # irradiance as array + + # call numba compiled function + return deg( + wavelengths=wavelengths, + irr=irr, + rh=rh, + temps=temps, + Ea=Ea, + C2=C2, + p=p, + n=n, + C=C + ) - sensitivitywavelengths = np.exp(-C2 * wavelengths) - irr = irr * sensitivitywavelengths - irr *= np.array(wav_bin) - irr = irr**p - data = pd.DataFrame(index=spectra.index) - data["G_integral"] = irr.sum(axis=1) +# @njit +def deg( + wavelengths: np.ndarray, + irr: np.ndarray, + rh: np.ndarray, + temps: np.ndarray, + Ea: float, + C2: float, + p: float, + n: float, + C: float +) -> float: - EApR = -Ea / R - C4 = np.exp(EApR / temp_module) + R = 0.0083145 # Gas Constant in [kJ/mol*K] - RHn = rh_module**n - data["Arr_integrand"] = C4 * RHn + wav_bin = np.diff(wavelengths) + wav_bin = np.append(wav_bin, wav_bin[-1]) # Extend last bin + + # inner integral + # wavelength d lambda + irr_weighted = irr * np.exp(-C2 * wavelengths) # weight irradiances + irr_weighted *= wav_bin + irr_pow = irr_weighted ** p + wavelength_integral = np.sum(irr_pow, axis=1) # sum over wavelengths - data["dD"] = data["G_integral"] * data["Arr_integrand"] + # outer integral + # arrhenius integral dt + time_integrand = (rh ** n) * np.exp(-Ea / (R * temps)) - degradation = C * data["dD"].sum(axis=0) + dD = wavelength_integral * time_integrand + degradation = C * np.sum(dD) return degradation +# @deprecated("old double integral degradation function will be replaced 'pvdegradation' in an updated version of pvdeg") +# def degradation( +# spectra: pd.Series, +# rh_module: pd.Series, +# temp_module: pd.Series, +# wavelengths: Union[int, np.ndarray[float]], +# Ea: float = 40.0, +# n: float = 1.0, +# p: float = 0.5, +# C2: float = 0.07, +# C: float = 1.0, +# ) -> float: +# """ +# Compute degredation as double integral of Arrhenius (Activation +# Energy, RH, Temperature) and spectral (wavelength, irradiance) +# functions over wavelength and time. + +# .. math:: + +# D = C \\int_{0}^{t} RH(t)^n \\cdot e^{\\frac{-E_a}{RT(t)}} \\int_{\\lambda} [e^{-C_2 \\lambda} \\cdot G(\\lambda, t)]^p d\\lambda dt + +# Parameters +# ---------- +# spectra : pd.Series type=Float +# front or rear irradiance at each wavelength in "wavelengths" [W/m^2 nm] +# rh_module : pd.Series type=Float +# module RH, time indexed [%] +# temp_module : pd.Series type=Float +# module temperature, time indexed [C] +# wavelengths : int-array +# integer array (or list) of wavelengths tested w/ uniform delta +# in nanometers [nm] +# Ea : float +# Arrhenius activation energy. The default is 40. [kJ/mol] +# n : float +# Fit paramter for RH sensitivity. The default is 1. +# p : float +# Fit parameter for irradiance sensitivity. Typically +# 0.6 +- 0.22 +# C2 : float +# Fit parameter for sensitivity to wavelength exponential. +# Typically 0.07 +# C : float +# Fit parameter for the Degradation equaiton +# Typically 1.0 + +# Returns +# ------- +# degradation : float +# Total degredation factor over time and wavelength. +# """ +# # --- TO DO --- +# # unpack input-dataframe +# # spectra = df['spectra'] +# # temp_module = df['temp_module'] +# # rh_module = df['rh_module'] + +# # Constants +# R = 0.0083145 # Gas Constant in [kJ/mol*K] + +# wav_bin = list(np.diff(wavelengths)) +# wav_bin.append(wav_bin[-1]) # Adding a bin for the last wavelength + +# # Integral over Wavelength +# try: +# irr = pd.DataFrame(spectra.tolist(), index=spectra.index) +# irr.columns = wavelengths +# except: +# # TODO: Fix this except it works on some cases, veto it by cases +# print("Removing brackets from spectral irradiance data") +# # irr = data['spectra'].str.strip('[]').str.split(',', expand=True).astype(float) +# irr = spectra.str.strip("[]").str.split(",", expand=True).astype(float) +# irr.columns = wavelengths + + +# # double integral calculation +# sensitivitywavelengths = np.exp(-C2 * wavelengths) +# irr = irr * sensitivitywavelengths +# irr *= np.array(wav_bin) +# irr = irr**p +# data = pd.DataFrame(index=spectra.index) +# data["G_integral"] = irr.sum(axis=1) + +# EApR = -Ea / R +# C4 = np.exp(EApR / temp_module) + +# RHn = rh_module**n + +# data["Arr_integrand"] = C4 * RHn + +# print("arr integral", data["Arr_integrand"]) +# print("wavelength integral", data["G_integral"] ) + +# data["dD"] = data["G_integral"] * data["Arr_integrand"] + +# print(f"delta degradation ", data["dD"]) + +# degradation = C * data["dD"].sum(axis=0) + +# return degradation + + # change it to take pd.DataFrame? instead of np.ndarray @njit def vecArrhenius( poa_global: np.ndarray, module_temp: np.ndarray, ea: float, x: float, lnr0: float ) -> float: """ - Calculates degradation using :math:`R_D = R_0 * I^X * e^{\\frac{-Ea}{kT}}` + Calculate arrhenius degradation using vectorized operations. To eliminate the irradiance term set the irradiance sensitivity to 0. + + .. math:: + + R_D = R_0 \\cdot I^X \\cdot e^{\\frac{-E_a}{kT}} Parameters ---------- @@ -972,7 +1135,7 @@ def vecArrhenius( Activation energy [kJ/mol] x : float - Irradiance relation [unitless] + Irradiance sensitivity [unitless] lnR0 : float prefactor [ln(%/h)] diff --git a/pvdeg/humidity.py b/pvdeg/humidity.py index ed26697e..b8bcfe9f 100644 --- a/pvdeg/humidity.py +++ b/pvdeg/humidity.py @@ -1009,7 +1009,7 @@ def _calc_qss_substeps( return moisture -@njit +# @njit def rh_internal_cell_backside( back_eva_moisture: Union[float, np.ndarray], equilibrium_eva_water: Union[float, np.ndarray], diff --git a/pvdeg/spectral.py b/pvdeg/spectral.py index 9eb9ab1f..129ce058 100644 --- a/pvdeg/spectral.py +++ b/pvdeg/spectral.py @@ -6,7 +6,7 @@ from numba import njit, prange import numpy as np import pandas as pd -from pvdeg.decorators import geospatial_quick_shape +from pvdeg.decorators import geospatial_quick_shape, deprecated @geospatial_quick_shape( 1, @@ -140,10 +140,18 @@ def poa_irradiance( # Deprication Warning: pvlib.spectrum.get_am15g was depricated in pvlib v0.11.0 # will be removed in v0.12.0, currently pvdeg should be using v0.10.3 -def get_GTI_from_irradiance_340(irradiance_340: pd.Series) -> pd.Series: + +@deprecated("utilizes a deprecated pvlib function, this will be updated in a new pvdeg version") +def calc_full_from_irradiance_340(irradiance_340: pd.Series) -> pd.Series: """ Calculate the Global Tilt Irradiance of a module with 37 degrees of tile from irradiance at 340 nm. + This method assumes we are at a mid latitudes, and our solar spectrum matches ASTM G173-03 AM1.5 reference spectrum. + + .. math:: + + \\text{GTI} = \\frac{ \\text{Irradiance}_{340} }{ \\text{Spectrum}_{340} } * \\text{Total Reference Irradiance} + Parameters: ----------- irradiance_340: pd.Series @@ -159,29 +167,10 @@ def get_GTI_from_irradiance_340(irradiance_340: pd.Series) -> pd.Series: wavelengths = am15.index.to_numpy(dtype=np.float64) spectrum = am15.to_numpy(dtype=np.float64) - gti = _GTI_from_irradiance_340( - irradiance_340=irradiance_340.to_numpy(dtype=np.float64), - wavelengths=wavelengths, - spectrum=spectrum, - ) - - return pd.Series(gti, index=irradiance_340.index, name="GTI") - - -# this is very inneficient -# we probably dont need to integrate here -# according to the spectrum, we know that the ratio of 340 to full spectrum is the same compared to the refenece so this is just a proportion calculation -@njit(parallel=True, cache=True) -def _GTI_from_irradiance_340( - irradiance_340: np.ndarray, wavelengths: np.ndarray, spectrum: np.ndarray -) -> np.ndarray: - gti = np.empty_like(irradiance_340) spectrum_340 = spectrum[120] # 340nm at 120th index + total_reference_irradiance = np.trapz(spectrum, wavelengths) # numba? - for i in prange(irradiance_340.shape[0]): - scaling_factor = irradiance_340[i] / spectrum_340 - scaled_irradiance = scaling_factor * spectrum - total_irradiance = np.trapz(scaled_irradiance, wavelengths) - gti[i] = total_irradiance + scaling_factor = irradiance_340 / spectrum_340 + gti = scaling_factor * total_reference_irradiance - return gti + return pd.Series(gti, index=irradiance_340.index, name="GTI") \ No newline at end of file diff --git a/testing-setpoints/63556.png b/testing-setpoints/63556.png new file mode 100644 index 0000000000000000000000000000000000000000..7b9595940e56e1b9377357eaaecb9cb994a22650 GIT binary patch literal 19430 zcmcG$Wmr^E<1b1(bW3-4H%OPH0wO6T-HjkQlr$&~-3SUucQ?|V(kUGhQfKj=|2_Af z=bq=>`{jJ#8Df~dX3yGd{c=ZYsw-lmk)pxD!C@*Z$-M@Tb#QR-VGtDXorok39e99u zd#xw~S2jYv2Yx`Zl2((3gR6)`zcWP!KchM;>AAtdVRb!y!S^{8S-`=m_$tduYkM0X zW}r4}OkcKN-Clh-E*2O6!kEe*sU3k);LV%N`<@XuH?c_dXM7?}q$TR!01j>)uSBjA z!Al!%p={$L)9uzyj=Z}}&{CAFy@9$n*d2PG-TOHQS8vB;EJg(LgM=^xm zWnHb9MN+(}=cwpGt7E8ryH?x%oNXz2&Mb5h&!EKFz$}W;QN_NZ(;<@M|NW#y_g6tw zekVaUn@Ji&RFBt+PB9F&cUNtX0$<&-SYTiO{aQ5~i^5`&%&D1XIa%&3 zT=Gu38BzNCn^M-R;6+}0X1}g*Y$3_}izN1UZo>kW1BndVKLhT6u=ge89l4#hG9fqT zYpIL$koz7~ET_ue-HZkZvgwxbQ~6)#*i7U{mYDne{WEPQc=vDrr{%wkz3phe5$;fQ zBEjR<+cFY~57m&>9-?>bt@BJ-eiP(gOD^lS-O(xBrokNszXW)k6kSxGlMPxIG?@;%c?F97(tFf4H%7>p&*ze+YDTeH4GU zH&LLLKr3${vEY3$S7EtOZ9_XGzTbr{$^KxaT9>3QI&gQn==6Hm$1&4%w#=w7wvjqUpT3-iRCg7riR3A$|&lFj&GP+k;UTT8(CIhg11;doBBXJLnTdYOJk*EvEUM z83U&;ogvxNWkv?AZkd(u2VZJ%A*Xcq9tZIXKi-`WJJkJV3~l&$dwF*E_;A%W9D@DA z+Sq4{P=pID-(j)V^`Qt~Y)wJsIhXNL$-A~?ztbL~iR`9_fBWyrxJVo>zDeFIA2^AU zJ)C`Qi%1C`%ProUnf2%Ro%I-aA6=`s$}CQhJG5#DVuwDkEZUMU)eyWcb2@u!vuIC-v zYpq9(`*Mq?W-R0)kxpyP5WHEq#$pjJ{rfO7M;v(3`-{l}IMdGZnDg5o0Ym7QeFsu` zBdG!^{6Ye7wS0@k?_(t&ypJPfHJw97Q6Q`@1MS$B$dC^uA8+E8p50P!X1C!YGymyU zuV4HAqYQ76uqr4_3#Xd4^Q04s4|HHklk5+n8j#c*T_58I#g6*jHvhRg_RCs1tvEVm3B4 zR}H}t{P7&&`v-diq%0Hy%(t=9);O%+Pl~m^y^M}R!&$@)&W3Y#tgXnj`@?%e1ur8u z$=#j2?WcVYVYzivAHqh0c}kMD_+A~kVt79GC(sqB@x1>x4<8GC*&%>`1^ZPgol;vN({8VK% zO6j!c%&3uh!0)&;Cj$05_MdMnI$hqi`h|lFRha0VU&Z-R)A0v8@||I!6?ayh@0(8x zxxt1oSlt_|e6Jjx_HdqdZa&8);XXpYZ?@ClM?SM?HFLynpjB(tIU4nGXfCHlKW!p> zChc%eELTsPjC!6zO!`;j56a0tj=J0wb>+WY9bM3~CUaz;SuHpFET^WQF8dyf?9cwZ zO75h4lS&rz5}OkKrDmyqO&3Bi+;PYU>WGbOgWIyEBhiwyOy;HwJdE7|w*bCKfgGXN z0+KjhG8zo2e0)lWxnGl;_-g%blPUwL~Rh+Djpn z-fgs$Z0vJGi$sO26{@9Kq;$i{sN$9lQL_`SoqOdqrK-y)&-Y5uTsy|lEcjCBosr0s^V-@*mGgIO8IA@sPUE9Q75yfHl_I6^)i5f z{3n0DlZ?D1a_uJq9`&(d{^JZPrg(E#~&Mmlv z8K>Jm$ssS^>E${Syao9;WHe?!dPW?Lq>}CtgW!10Lplt8EIvC!TyZ(N&nDSRQiw_C z_-~=yHm~I@HHWnh*{l_+ITHfWQh3wjI-e1ssQsYZ3q(*sBSRRtw{y>xnUxriCO|`I zCK$;hc?sc!f8FkL&B5P>R~?U|^rZx>nDElnAq6&*g*K@I5|BMPH$2R*WZWSUC3G0c z@pA{87_{F0H0#EZn%$PVILtG+jW12xFEnv%N2E&xG|$Tq!p)W5W;^42EOItl*9rW1 zcj;ap)@8VXAG*1{gvYkl8yY&JpgE?g{Tu4e`ls)WE=91khuV^$AO|LUHS?hVt(J7x zZ4Eub@G~v=TSAAggwSd;^B*QO-Q>4Je53vM6H@d8!TRC18|hOR{ER-Ft{fHN<436o z3g-A7(>oiKk?4I!B9=qMHcE;1K@Ks4_`##Wz7yD?5pKnv8VY7#?$u>uOnmJfNv*CE zE7%C3qz($r{5pb~!{+MLOZf%3gKGBfAJ$S~Xx)l-I&nVIs(hC${_g7;Rl%CS2a=dn z=w5Ysvgv%Mw?v41HrFyYR%%d}?BLXPUwd8QW0^=_|IU~s7@L4I>__`zXA5rENW*x2 zH9Rvhf2Ga!deh9DV`k`E_mOXd1jK(i*HC3vtITbYBVS&Mkiv| zjhI!Y#;?+h&xIDt0dAt_?x?HCoX>@Q9>G8?1xf7X|5)=9-35h0gx1YE+oGrhvBvNt z(s&1qnTXE=8w+)Hk0{nFMP#$ zuFSOLVi9COrt|X+N0+oCdqda%1n~cN^yB{*NBKYeB)WF#ootsSNfk5YPsRU?eGdiB zH{v9JS=_jUh>*3dT(yWC&23ny|EfRT|JjzxHzM4nUHrPoASr-8)Oi%f)5Y(wFlF$G z3gS)v4RNcX_5RY}9Dv=lFif%!cIR>VnxWSG{zdiv)GdDp9>#aje)QG|{?9Z`jHvl) z*%#ny5zFnNl(Q$K+QL!n_jrG0+4G5T8!YFiGsJEutI`1Vik?sFzVor;eRhn4$@3`k zaJ%xDI{ia84Q&3Y07RyIVbe`r33&XynEGoZLu~lF&JT-~;8?;V!?AA~RD3>X7PwMK z4s+$EmH^$_P{ygH38thuwd#o@{{l1D5(SIg`r+@-0B`^+z{d&!nhVd^Xb(ax)ctAv z+PU@aOl1;a-SduTRNe+!PYjFXgc-GqVC+k8$I~qUi>S1 z;!I%EkGAg;Ygd#&$u>rO6qT>3$Ql|6sx8y6`7ZKsy)g_%u;(D~noYAD=R*|X5md9} zEf4P5&G}ALSg%JU&cmKYz}ck|;ZU@wjY2HBjiCM9D#!aQKyxB}ys+tKUqd_lYW; zJasGnO+En3t5sPJTZk=?^YtEMzM9+yV^4mMhBN!N)vp0^onn<~!`XDeJ8ucj0*-aJ zY4BLQEZq2#wNaZ`>{fPm?pB-_r+^7s>1enNy!CrDIB9dV*|nvebhp^LUf2`k-3Iep zFytAwAec}@L3R0N0g;A*+^v9tth+WnKHT=?XG_mF`?$@Qbsh?_U6<{LWdGKXymtqX zYKWBLzpIn69sPcWG$j zeIdOjk2{i&3BK8ORP~B8H)0`y9vxVD(U<7Pl6)ubIA*?+YC@6kvR1yh(PP#l&9)dF52GMpylMJnWYfI%TT z)MV>N-)|oKGwLBInCU>782A@MCL{`01-Dvd4nn#>K`H+n}4 zH9t0N18!bejgaHo9tr}aMoz;$zWzs&My@IdlU}65{w)q)QU{UauymApMb`*azSLvqM9mTrHv0Zu;ADG-tP%96j_zde3XPdt-% zqJvkbIIa9AC33;5Ei~xOZeHBx zL!b$>YV_az*)%|DB5kCsIpXO%VAL086KSYRY#EHC68-o1So><&~|ThYNUpGTLiE0+EB60#OF9roUB=suO5d_DiYiX!=u;U!3z?td;P@4tKyc zCsbC-%tO`8ELDGpiU8pZmd=Yj_ID@C4jPD)BTL#)Dq_R@St8YyXBsE6O>Fb|^<3~( z;8-Qr@Q{GcB0g7VrL9V}ByyCDl=Yvg=YK9_^0@<%`E&}Q zMA+7{)%oiSy}9??bitV@Xvq4p9zcpykNQO?M<{)IoJP5+WDEe=Yb_JOoCI83=&t~5 z0z7DzKGg0toK%bC5*77lYa6^!)WUVWu~x`!FfuxQe3Tm;GNtLXuuJHaaJJNG8g;pp zbf;KX&F`>!g3a?0F%4Sm1}u7&LX8qAS;wY)aai60Q)Jz{Hh(;)m_SzT<8DPZ2)c3` z1O-9i-*c0~?4G%>c+OJVK-h{(;kQY=0W_6$AD5N(4#N7ne)~ymD@5Z| zs`)XV$ZkFY*BN%w6eFkX6r#e_qHX(3mGLn4eSlyvQLb}KetR2?&KYm_-9e3+<4OrJ{v#o2DOhO!CS##i&ItZ9%8Ila zDq+k$?BH{~FLImuxG5@6Zv56WKoyD|#89g8!~Z}t(d|Yf1V>s{YRrkd-4+v!iYC{Uh`>AKjRynf3}#?o4x$35J4a2Dq949(0^{sFoIWD=j1s&)M2$NzSE8+wBMr~`qlBfO~Jv_OFpvn{6gcd7Zyez|4!3x4(%s?#o2F< z@955XyRJeHO)rp^9P^@B{e(+2>4Sz+IM)OePWiran`N{|B4K;cw8O@}hbfROH&o+s2m&}jE zNEs7}fnp1z$-N-d5KE?As?ylf*yl`Lp&N5qVJwAc%5V_D+3Yt`W6E@S@z>$p<=t^g z7V9Q2#$*-MX>R->H1m{mGyD%qT?oxAFqYI;UG+2;_IZCro_8<_*c~l3@JeEI32P#X zU(T7+?ru^hn##O^Y@^1!=GDDx_+oleY@kUp)A5c@FE%}YKPO$(2 zCdoq)>2*+PHWL46bz;Anz{k`Pa=*#w?(TM>3#AtqW3s$&=~6Qj5+gYF09;_FyA!aT z!nsYyBJ$=tVo+j&v9XNn))( zaItuWquHu?qYw~Fk5}4OQp9~Kwd$QstpKy(mGT3Be;NgvNtMyMjj{labVX#FGE8wYhQ^To$TBxN2c z21LnRn`ypW?oJj#0Un0A<%NVU=N?fD9%Q(mXw*{&;hv0D;UoyebBPJ>NPd5D!_Af# zX1^42VN3SLjhw?H4e^U0F;%q<8|djCJI&5<-<#kiWrNp7Qdm1?bpIkFT>|Nhn_-;% z2juk6a4e*8eoVd413MYZ(-{17HE|&qR@LH;67)Safy8%nbBWCzmTih~`y2ygw3FG@ zZ}HTMQpxy2V739W35%vLh%y3@fizk+b6;MnEO%ljS~%3MeswI%{3C#yxYOdsq!Mnn z^I}|j2YxZl?dGb(u-#s>{3=DXD`4e7qrQwXJf&dLpE(`z$ZO8&Nfj{=A8Q~SPZ3;#?xm~{@C5YII5#_Sim;01Zk`>q3q z`ltd7{hjaE=CVWxJr*R|5j(3rnjt1smM3Q#DbgW{;;Mw4Wua>7+p#i~Om4%wFCb)` z@*mU)kASdTaFW4+p=quO z$!JdDcfS~VHxS>67CE7+k_+BTqOd!sO7_PNsAeNJa(peutQM>%IIQ+4BtFsVrG1Nx zG_8X1%CpgqtEQtywo=VpIE83pnzo7;WV3XknoM62wmb6MUBq{CG*4gP@!-qu3JU2{ zd!yf#e;1){`G~`Q?-E3XyLKAFeQgx7;QY7C<3b)`XVuW(Tf|?j6J60e`1;%Ss{eG< zM)>*eAj*h9K!=}Jfh%Egq%i08onh4d9a0uY%g)Z#I07W{!^45Nfx@lDU&osfiQ6oW zx;d2hNadKnn%6XOE8m(a6m<^AqtA6bkCF)yv=-e;)(lN^k+V+MV-IW@ZO-Di#g{JX zq_8K@W9LuDpT?+u(o>*+I85&(?{b8GyC>B#ek2~6SdqqODr!h(H?rky*~CL#jLAFy zG(sQnOc-BFXv8+&-Vu zhPTG}C4S5*cq8_6{)yWtu%159a|}E)7yhSsG>q0s2Z=oKBHc;`LXQi-A{w5EPe4x; zkw%0`h=ZoSnMzUTJrL{{E;t8GyL$AKu2(77dh3D=6p(MR8@75RN=1OIjsPUwTv}Y;$r6IxAah)*9J=!3Rh~lZkCqmJ z*e8Xle^u6?*4|~NL~r9WtIn_a2Dfi@(=IRWPGrByMdFP#dh9m~+@QDpzPmYZDHw9G zqag9K0UG*pDjl8nu-bD-7b`vDk&_3k*J3pru;HjeZGQBu8x9`qiKx*xSrRtx7fQVJ ze6oEv9T>UE)LJY}&Q7XOkL?tz)D%9e4|XvaQyRVMv>)!y5HsmsQRsuKUCaAgs~{0s z6?=Q@^qcd|_<#Y30kAT5T%T^dCm}{3&#LP8a;3lL`W!5`*020G+D3L8v)BXUc<3}e zDJUG4IF?mIpu?@qJ+1j6vVCEx0q#%+aX9PEcDN=yKVt*TQGksSZn_Xs)`mOmbzo-9 zzSfqf7?<1$CVhY{1cmlB&h-#9(==No*(a>OIRANeAOoT}kw9EPb1Gd2ninUvd9zXi z?K-M5wlQ96qMtMhky%*n-sHDI!696P4gztm)SOWjhQi?d_o}21eARrj!53zBZ~H_V zm`qIkM>=+E{D_5K;U}V#g15?Xe}R%3CkjCiapILT@XW@s)+R?#Np6*?mC*Yml`KN{ zt^reLFRZt_JzsMzzpK6=3&*c334!o zcBO$mb@z;vQT}?)y1;px#-}!#8J0ITkOG4o05QeOKy4* z@|g8U1lAvZ? zIZ*sd`5Z=~eXIJd)U5}9sS7R*f{XZD3wbiU&Ws?w7ZD+LHv}>YSCORm%xWgpf z+GP936?Qrzj6`l6**u%a147XwILp$`!hYRwpZzy7$1+~SG6#Z>f}h)wp5dZ|<4D?N zmG!X}qtQJdN_zH*;$<9JO!iRrdFQcf6+QOF1fC>xk)N%I0zah$=eu5K*Ga|OvtV#O zzV}I1C-)>S@9H-&Xs=nW7m9lP@m5I=#>%7|(s<0yQ2K-AB~7dk$1gYmOJ9-II(NJHB^95tWs%F9Kpqj~bzAn{z}#z4#a2Z-Q{WlcrTm7za{Mp1cI>N4M-E%+vPR?H zB))A~-p=_|pUY#(P5^IEr3#l6yAYIhsd-B7h94i3hs)aBLk0J)8c0>B($oBWCKR}S zqT$%Dd>~9RWKbC15UDK^V-f=;vM%$vBZ8nnAvVt(Oi)hYVt-cS(&|CAmTr}Gv-_)w z;H#vQcU`uT4m2?_f1^`Vms<#sWC$IhGF>8hD9XqW*C>|4j5mSTc)?##uqoO1$6Ft+ z%`rVN8PD*N)G`^)yScM4&ilBF*=dTq{SiAqUG~gInc#_aYPxoZ2-(k_a1UclvCchi zDke%knN7GB+haM&rV@gUGrR**_M$EkLe@+56?Ft05Zg1WpWN_-IYs%Q5i#G%8u3G5RiNT5_oj;o~U_=mp%(XO_ZM8nY$L>T#KTBezn z{g=gBj%otOe8>$Uj#-MHPfJS4N(H4TVRueNZj9h2UG7(`4I?O+S56vA;?|OCj`Ujpi_xI zi$j_InAjPtjXcBAGz<)+z9ox_3QRTOeN9^ z?Paks0a|5Zxu%)J*pRhDGgmzcDj5Sbxie_HFi^ z<)5Tii>27+P6t0xNBE26GwixCOW!5DS@I-b_eISA+HMH{I91DIPBaw#Nof({YEP#* zM{Nex_7iUtAs-I*F=E|gZd_LCBA;w&PhT# ze%8nFuGMe`_gGpJNX)kuBsk)vKOWQx5sFVTuaOh6V8HeDQJF`4Cu&}>8k9p8aCtC~ z%-cbuy;j)AQN_8XI?oD@YgfDy#b}u!NXN6l?dpu?D({7t+~&ja+tm z^upP?p0xLgc-4L8F?C<(zHa)Vv(;n($ylhd6LZ@hO4tIMe<3FOvF)30GNEX^*J2@) zeC2n*!D3ugh@(8LwjP&hU2*Qh90`O++!U)1-XY-7pCS=*OlO~*e^sh4@DysO#3(ED z0s^hyT=vy`C>CyA_CVm@_K#1x^3@$ZQ-*LEp7Wbh{jK`YaRWDtw^j6rclaO8Jh@5P zj1KAHG#5VuiLn;9siPI+CM?;arIs$@YHTe$a*;9r3mjX9LHLm$zwp@fX#I*PGvipn zDD_t`-@fj@_BBDnMUcuSD8%Jqf%dPn&5HO43z-wUa>-F3oN|&r;^`EvaSsMFnm7U* z2NU2VhFX^|tU43C2K>>VV{u#Q%IC&Oui%m7$CYTC!p8M0is!@EdQKoX=hF5umXjvG zoTGyehvotao+EwTH0fofZ~jvLMkXvW*SuZ?4Mk8K2Vqcfd-RluKe(iy`4ex&UU#G@ zgjOFf?Q1Usss5oUrV8?bp)thYx0S6Cdl9lhPfkddPR(v;Ja<5V0?o{ShxFPPmqadU ziYLa)%TBMD!5zyZkrDOkmz!>IB^Y}EQ&B|)hqJVqc4EmU(Gi*tUrfnO`k)->Ta4)yR>8k>VwAq-&W zXRaMW5*LXyI99WQXg+D4XyR2n-~pa7EPH*9orj6wb zfE8I*bbIMQ3Dzqtuhj>9ku`iS>NDsXn)@)8%P~(KJyji#CoJmM^vDQclLx@)>N7|} z;}nj)1^Gw{U0Gi{?6p+Z^>r=h02fZfxYbmVSUW{AkmO2dXDiwH=UBrrSkEM)zLs9r zdzFmU=O88w{FX!!w)3>~dIWs6qL5L$5VjwhL&5yl;*6*b@p}c|w@~cghWTW7DEocz zPfF_80nf5Ty(|fk(Ny`ai-@gEi$qrR#|889&-9=HzR_4!J=?w8J{2l}iJ4)m*ObZK z!OrGwlZ+9f-tN|hx3YM#PfHlet0^O`T8WW za{-(!Ck+;!Gt0$yl3e~S_xlg#AUy?aE7~6$%+hI}jNcq43}ZA~b$8;2=bd{}f&+Sa zu05Z2AQswfPZ4veQoRefj{` z!tmH0K|KT$RH6l&j54gCY2FMz9VI$(5XUnTjILJ;${NU%^-3RAKXz72|P8c5Vi=$Q#K_GUXjliEpq! zU^I>hyFQN!{wek<*|n%styeym{4#m-SqG(ng76d>ZQRhTc3^A35jwQ)RS8Ri{ zMLd>>tyuZgl*8_dO@=3WW65n4){~oku-mVUREy7qFsGibjne~S1p|K4kubIa5bNj< zEFETdicCcs`mZBj^GRN>B03G2DYHMl$NM%Qx-KUcWXsAX`be1bq^E*czs`}q0kMT1 zb86Kn21u7E{dasOZCz^oW4=-(Em|uS_&2_n2a#LZDdLmKr3S++Oj+zXnJ(u;X13`c zFXx|XKUn&=m}kqtQI@%{i zbY>9+_(;WYgE9XjpKGrz1BbR7?=8CzSPNRrdeEx=JLDc~@37o#%eue48q{o(3L(}Q zxjbClk`4MBe!9*<4JSEQZK~P~B0;H6tv9^}NfN?ejSV`uN~9l_oSaJ}%7&L@y$f?O z+NOc`@|io7=)1FG3;r|Hmd!*JIg|U<#_kZrC$IzJ0G~)eWb7$s;j@{bIDwSxf&)mW zt$ww&%Ut)Hi*^^ROQ+eg483xbpgIOOoC#oSrvY@~WB1xLF`v_@5tiluPkG6Dqc85N zHop=CNVM`4FsppdEuGZ(*KU-=RHx`oo-m33!MlL_zX8>pq_1m4^gqu?APV!=@O6GX z8(@lh;}2MIH^p{)-6XV`0$@SoMHj-`5VV4XK$IZa)!YV2APrQxY$%{!bYe#(>%i|wUh*w22Rwc(euL}&J2v?W{RJcXJ{l1x`yfPc z#p`f^VbI^zyfR_l{TItO*zCIiqvQssbpdXbM0o#WIhJP4P_n)Uk6EJ~4tZ>7TJOSB zCO8Ly-?O}iM0bg6X~qAx)SbTqThLoG>ee(((m(hyU6w3|JYePHRSFnviqMMRQ$D&s zno>gFxN!z=uj2zW*i-e#o6=2h7?9D6jawS0=wF5Jbd`wig#+&AOI-ccC24p?=1+ud$(}~4G$YERtH1%Toc>FJT>qFVV5h$} z!iAHc%}sOh-6u%Fc9+#tE;~ zLF_%U<-}fz-SH9xSibVBvXCPufHQXM1|lHKulc11Q5>XH2?gk;d=pX{+FvwM{6vls ztG)xN|MyUaC9iK8o~ib_IQF(sYVszKTRklw(>MX?fT)!gfIXKfi%pJ74I5q~iTyfE zZQf*_ZEYI8%{(4T;ZqcUcAdx<^0AW`0b%iaN=t(h_ zPWNxHyjKxFfIMGmQ;4kp4`v>Vi>bcOC%C4 zKTO4<|3^&&M*?laqZj6yeD$Z`t1)Su z1sKmC>GHSbHDp4L?8^mmINzNOTv1y8Hn{Dif~<_U9eWDEGn2jw7_QnmA;s?plWkfe zq1i7$X6VWMuPni-`<F&Rv2yQ_ z?oArZ;ZgjBdz07xj9O#=>7w1Ssj*beA$H>@GVhT$KaDds4)UYREtOHSV^%)wb4=FQ z>FO~u=7S8+gxGEzozLxIUBP)!rW6zlbHtlHKeOPOp74e08I_u3Ln6$zpELkndr&S>;<^(O0vR#5@BWSLkufNZbCE4r zjm2a9?u0*7l6r9}DEE4XfM3s+$f!Wu2|j6gYcfH5W**u=vV&eSr_ZXSNROGmM?4^_ zocIwnbh=!Z(A75SDPuAOQg}-)eH50zKC@J2`hKIXq{RO-$kq1w?|&$GE{3OI1)ZL> zHH*wo6Ty?<;DLJUH;u{4id~LJz{aU>QKD5+R!;bc^O6Y-_B%KkM3-p!7}ZjE-w%Oa z6^(wz0d>Gylqk$PGBFZBC{~g0@UN^LkObJ2IJ2pX3VUZ5`~+Y(!3w>GlRcK+QMe{N$4jZdL(MA5cNn5M%xBjA^fcA%(b9 zJx7LbBiIjAKj>57X}-BcP{h93_&`AUg8#$m?q_yAUWe~4(DdbZu9C|B)R?hW9jeMx zbF)71wVuHI>=F9{DH+aypX;e)*qnaGe*oJ#i3R#%ymjz!x94;oY!PX zejtgZDX>0;PGSDLznkh{qSk+YePR1nkiX{E7bVkw0@_}jGO-HZ zW{J`=4S%U;h$>6x@C?>7z=V)dbn&5KKY})s2+L~ETer9npJBQGyE;DR*rGsx&hAVq zV7tk&g;{nY7DdE$`9$hxoVQ1_z@NEtY#kdDUEJge`MGsONyWLSy%M8+_?$O?u zXMpPtkK>sm#$es*8eF=S*=7LcCEJ6Geq&O`jam|%TrGu ztnm$?X?`MUjid5AuS!Ld%6a2@Lv?fb!efb`x+Eg5`G&JA{e>Y)c_>wg zmXy+Oo>EzW)_>-i7FQ-f9zp7!r|{_9?RF6W?!a>OF-UiK7-Igp1C6s-J9QDDNG3VF z^E(aI%8^0tQFahn~uEeohP3#T(BNZm__@>28R*C4SaVSJ~`!Z2VMy zi2dR6p5zIrd;{H)SOex}aEuvdSL~P0dN*M9nfMPnr{W1@G}WXmhuc?eGdg( zgp4UeDSUi~@D(yX==V2Gt9xjD1&TX}JQNsdh2u~dxo8`@0Nm*!jI|p!CL)ItH-ajc zjw;ag{;Lt=VBnr?vLfx;A_WNbF#4@KBr~z z8%iBRpXkx0V}3t8fk$Oy8O@}HkW_}epjQyy6(1}-f;&$Umnm|^Rs2r*YnBv2Br#Ln z^$mqF5vD`5gV&GQU*`7s>v^;yByvtn>L$m7Fk|OCPP*wO#}*?ou~k)MRta!J7P9k= z0#mlIM`K8r*jj1`E}k}=^L6~K@=^4Nd^&a_Q@Jr~xc&Qohq|qFo7Nu!lz#YIk&(h& zT9nD?YRT5_>c_a@9Ajd1E1SxSAtHL(j#Ab>ZVn{L zUn_rrLnDpxdc2p%T@Z@=GZ$565sDEUY$?yooyGqmEodCohv5|*Hy=cP`n3A~CcxT; zpXYP|Cc@8)8q)(Ew-F~^^E_SeG4qVKDA9z$aHZ+s;Nf==A%X88^-QJ6`mEm%k#`sr;8@^5-J!zf9}T*V;h?;8+nSNPWSZ* z2$9#pA2@iV15zO-=5-`)PqCWnHjLX>^ED$Y;9=gt7ZTf5Q&irz*srqq_0ciN%g}*y z5ba35Zk+iR(eY)hmSK|Yk%&aS*T|mW6fnmW)s2G0B}Y>sG8BFT`ST>ExE(`E9ZAHe{Twg3e6nDT2r z@oo7y3-jE;0NlerIS~@TC{f~bgoe%Fmr^h|<--5NXN!4n-m<@>O$$^ub+aR?WDr5! zzYhg0|5;2nyTNYI26RlDY`^MLIU4)h2$Ufxu2D2$0O%bMt(c>G6AORiQE4jOp^GFOmer5 zz~*x zNKU>cSry%$C}}%bv@z2w;MnXqRi9=!nobk&`#)!YOFgT3JyKNq&@W{vl3gV|+VgSJ z#4KMY)K57V@qSc+ZXjz{^$Y``gLUFfn?ytvi>1Qt57qaJmGUh}IHFMsI6CtMa z4tqGu&EJ7IQd$EW2`S9fYlC*x1tG}N+dRzOQuq(Ivgn$+vNF$8d-1e{V|=saY8n49 zBf`fa7Mfqx&{g(_U9U^*Q>Sm`lc4lpJ$ih&^FvU(5n4`UUgv(#j>@OlId3D^^b z*3yueHb{D@(C2n^AzpQmmCz?xb$j|#5e8U5DZiT0H+70CzZ+Mr{Qex4hQEd+Mr>6M zujoAmuXJ>c7|uEVs8}2+Zz}<+g)W~YXfx66cQLM5dARp2OAzz|dBM1eR@k}9K)hn& z6_P4Lcx{@5Z!J5YlSQ55Z&k3Vs{uhapO1wP82ohSFs(f9Ec$b{7yowiTw{Q||LY^d z>{D^10n`tMOY4?xYwhQ0YcQ?^y-!T^`f7n`QK1=}yn^19AIQ!Naw55jTsJ6@-r2l?Wf+hD*?tRr|_ml<)S`Sg+(b ztLNe`228*Om>nA&_grNhd+E-ds3X92c;5iDh!ODVZ8fo(jDR5Xf&EhbxJwO8tISYj z2LuLLaQ~a=xIVPU<fgz7zl z+b9h3h+~iX4={Y~KW#s6LX*DSYE}8dx>aA8VV?$)Vo$eb5OKVfPoC`3A&9j@`Jl3f zD>nRbM$anJGY3s!lGo=O8$qR-7}2hT`HX%w{sI|UGeA_Y4=ac7jV3Ow^k|F`N{zs+ z14KC4hKDO`qxf+DfEmtSg^O5-yYLm8kC;#81Qf>UQd3gA=O61gV)09dJj-G%J&<3K zcEbqVotlu97KpoxxXFI9RiBZW`ZRtl|i)))bJ@gwfBfN~aO=!I>(+j#_UWSuptTVnG`S7lBZT z5N<>{FWxrud|c|izD?Vz)w8zp^DOMEV4HD3d~ZzN@YD#-S_DA#JD_9lhd9y74A3J7 zLIzfC-|@5v3pVXaaA(wZiu$8-Y-X=aA6+^{v4XC95$G>?Bjd=_>0iwh=5nEQv{P>P zcpl7+H(#$uRc7pp^S?03b6jrLL;4hElOq$V+U9>BZHLuwxNAEr`+-ZWex$ABDhMtQ z`S$9VD>DiOlN1I*D4zl=q6<-uCIwLQ6MijSEinm1*pa4)9XD%jTUjl;qfrP7o|hrk zp!ZF{3I!py&Y3~x*6#QxNaB)L3Z~;WKSM?nF}h#Z`<$v~j}BgGB*wL8=Zw9yUZ;@_ zQ!smUE5-=H2RR>Vxov&X{q=#=ll&dXJc@*UPx~VQA^p7XVg!YC zc6g1wzs$ie0$s4DW*BXtwexEFLWF$NB)5WW*VF9`mi=!Xo=U@dSD?%k1=r|+VG}Xo z3~o131t{*Pbo_Iu6l10rXq31*9AU1NzH4hGa7PpAb2+*_`fmYS2Bi7BPYMyoav$8U z5?qcdNf#A}hoM4+3Ry-4V!QHUjy?8RZ%t~Iij7OSteP4uV?!1zR?OQgwZ{?7&Rpzh zZC)h*@tM1gSrKLm4(CTmxEAN;ynfgp?W;DgUW@awjG3YLhaJuN*v`4Rw?>T`nS1WJ zN6aSGzFb@3-0TO%ix*EbEqJBWTx`c))@$hgoF4(zd!xW{KODoe@Z9Pmn%AFF;}r-MTzcH#*ZKG zG-%L3qVW`0qo+mx`EdnW_J?b)z1Df?p@-x<{PN2$PWkfX9aq4;HR*Hk;6bN*_wEu2 zc%*QTb?VfSNIh_C68UX1i`dI9{rdGwd)Ay{qXP2)%msh68r{d*MGjQkm=bDE&|60~ z%DwmAdsuMQX{VhgJ&)-@4;>KIhnClKQ46q*7>~>#&mLmbW5G>nM-uZ&z(Eh z+mZ_1@g!PkY)LW_E8!-A0MkSx>#~9nQM#W=WXLImz9K|=9ZVi#H;8M=3 z0CQagkV3-wh&$mq5Pkx~$mXFoAf&f+>C#f*3E8E+0qjE?f-Z8jH0P$UE5x5rdvU+X zO6XfBy5I(zwisk|j%ub|M%mH&9bxnqWF0hzL+tXjGuW_3^TBFA9Q% z&=bT22(CiFlWR^&&=dbLh1671xCYO}dHgw&1VmxF0m7|;R-l1lel(yeS&5Z!BM@pM zl2t;Lo7pf9WU`>usG|LFp5Tj44-y{Omk?1hRQwT$8G%6gGkA#RBM6MF7lmOLD5MA` z0*t0sA;YY|&gZ_-(r8!y`{5XB7TlJ8vjTI4+6~x;j}jDO3LOQA81ZB!R>Dmp?<0>q zBHEhjm&PSkv7%Z|8-eif!w-wwuVcrKavU}*F2wX)fxK*g1B;+0s&xYW$^OX>#AM@Y z<6M9S#eAYcN0Ko2jY&dW37|bOF=+Tb|NQe3gN_NqwK*2kh}1ID&M1&PANN?IL0KsPo7UoTxHp%&uIdJQ!`-n^&?7_65VM%;9 zuph@_x&X)WEV}&EQ%_0bm;{ZSLT$zrR zYK9~OHWSB^EfDHt66`2ph1(KatZ-ZMgeX|MNoR8}T)0p=PH^=l*{v4{u(gS~x%ARY z(>jd8BI$%1pKsE~8OIz19DjOt{Qh}K(h0Z4l3lFLZHXzy{67r&8DD>QQAq#*002ov JPDHLkV1ma7l_&rJ literal 0 HcmV?d00001 diff --git a/testing-setpoints/IEC-61215-MQT-11.csv b/testing-setpoints/IEC-61215-MQT-11.csv index d3244dc7..e863080a 100644 --- a/testing-setpoints/IEC-61215-MQT-11.csv +++ b/testing-setpoints/IEC-61215-MQT-11.csv @@ -2,9 +2,7 @@ step_length,step_divisions,temperature,temperature_ramp,voltage,voltage_ramp [m],[unitless],[C],[C/min],[V],[V/min] 1,1,25,0,0,0 60,60,-40,-1.09,0,0 -60,60,-40,0,0,0 -120,120,85,2,100,0 +50,50,-40,0,0,0 +120,120,85,1.041666667,100,0 40,40,85,0,0,0 -120,120,-40,-2,0,0 -60,60,-40,0,0,0 - +60,60,25,1.041666667,0,0 diff --git a/testing-setpoints/IEC-61215-MQT-12.csv b/testing-setpoints/IEC-61215-MQT-12.csv new file mode 100644 index 00000000..c4fc7cae --- /dev/null +++ b/testing-setpoints/IEC-61215-MQT-12.csv @@ -0,0 +1,11 @@ +step_length,step_divisions,temperature,temperature_ramp,relative_humidity,relative_humidity_ramp +[m],[unitless],[C],[C/min],, +1,1,25,0,0,0 +60,60,85,60,0,0 +1200,1200,85,0,85,0 +60,60,0,85,0,0 +5,5,-40,-8,0,0 +30,30,-40,0,0,0 +5,5,0,8,0,0 +5,5,25,5,0,0 + diff --git a/testing-setpoints/standards_testing.ipynb b/testing-setpoints/standards_testing.ipynb index d45e7cf3..3a745a41 100644 --- a/testing-setpoints/standards_testing.ipynb +++ b/testing-setpoints/standards_testing.ipynb @@ -6,7 +6,9 @@ "metadata": {}, "outputs": [], "source": [ + "import matplotlib.pyplot as plt\n", "import pvdeg\n", + "import pandas as pd\n", "import os" ] }, @@ -14,7 +16,18 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## UV Preconditioning Test (MQT 10)\n", + "## Accelerated Stress Testing\n", + "\n", + "The following procedures are defined in IEC 61215-2 - *\"Terrestrial photovoltaic (PV) modules – Design qualification and type approval, Part 2: Test procedures\"*.\n", + "\n", + "WARNING: This material is copyrighted and we may not be able to share it publicly as it is paywalled by IEC." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**UV Preconditioning Test (MQT 10)**\n", "\n", "The following UV preconditoning test (MQT 10) specified in IEC-61215. The test requires irradiance between 280 nm and 400 nm does not exceed 250 $\\frac{w}{m^2}$. Significantly, we need to accumulate 15 $\\frac{kWh}{m^2}$ over the duration of the test. \n", "\n", @@ -23,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -34,18 +47,162 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + "

Chamber Simulation

\n", + "\n", + "
\n", + "

\n", + " \n", + " Setpoints Dataframe\n", + "

\n", + "
\n", + "
\n", + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
setpoint_temperaturesetpoint_irradiance_280-400
0 days 00:00:0060.0250.0
0 days 00:01:0060.0250.0
0 days 00:02:0060.0250.0
0 days 00:03:0060.0250.0
0 days 00:04:0060.0250.0
.........
2 days 11:55:0060.0250.0
2 days 11:56:0060.0250.0
2 days 11:57:0060.0250.0
2 days 11:58:0060.0250.0
2 days 11:59:0060.0250.0
\n", + "

3600 rows × 2 columns

\n", + "
\n", + "
\n", + "\n", + "
\n", + "

\n", + " \n", + " Setpoints Plot\n", + "

\n", + "
\n", + "
\n", + "

Setpoints Plot

\n", + " \"Setpoints\n", + "
\n", + "\n", + "
\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "mqt_10.setpoints.head(5)" + "mqt_10" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "mqt_10.plot_setpoints()" ] @@ -54,16 +211,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Thermal Cycling Test (MQT 11)\n", - "\n", - "This test uses the thermal and voltage cycling test specified in IEC-61215. Currently, voltage is not used for any of the chamber test calculations by pvdeg. It is just included in the csv for the sake of completeness. \n", + "**Thermal Cycling Test (MQT 11)**\n", "\n", - "*THE VOLTAGE SETPOINTS ARE WRONG, THE CURVE SHOULD BE SHIFTED BCK, SEE IEC-61215*" + "This test uses the thermal and voltage cycling test specified in IEC-61215. Currently, voltage is not used for any of the chamber test calculations by pvdeg. It is just included in the csv for the sake of completeness. " ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -78,14 +233,74 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ - "
" + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax1 = plt.subplots(figsize=(12, 6))\n", + "\n", + "# Plot temperature on the primary axis\n", + "mqt_11.setpoints[\"setpoint_temperature\"].plot(ax=ax1, color=\"blue\", label=\"Temperature\")\n", + "ax1.set_xlabel(\"Time\")\n", + "ax1.set_ylabel(\"Temperature (°C)\", color=\"blue\")\n", + "ax1.tick_params(axis=\"y\", labelcolor=\"blue\")\n", + "ax1.legend(loc=\"upper left\")\n", + "\n", + "# Create a twin axis for voltage\n", + "ax2 = ax1.twinx()\n", + "mqt_11.setpoints[\"setpoint_voltage\"].plot(ax=ax2, color=\"red\", label=\"Voltage\")\n", + "ax2.set_ylabel(\"Voltage (V)\", color=\"red\")\n", + "ax2.tick_params(axis=\"y\", labelcolor=\"red\")\n", + "ax2.legend(loc=\"upper right\")\n", + "\n", + "plt.title(\"Chamber Setpoints: Temperature and Voltage\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Humidity Freeze Cycle (MQT 12)**" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "path = os.path.join(pvdeg.CHAMBER_DIR, \"IEC-61215-MQT-12.csv\")\n", + "\n", + "mqt_13 = pvdeg.Chamber(\n", + " fp=path,\n", + " setpoint_names=[\"temperature\", \"relative_humidity\"],\n", + " skiprows=[1]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" ] }, "metadata": {}, @@ -93,21 +308,39 @@ } ], "source": [ - "mqt_11.plot_setpoints()" + "fig, ax1 = plt.subplots(figsize=(12, 6))\n", + "\n", + "# Plot temperature on the primary axis\n", + "mqt_13.setpoints[\"setpoint_temperature\"].plot(ax=ax1, color=\"blue\", label=\"Temperature\")\n", + "ax1.set_xlabel(\"Time\")\n", + "ax1.set_ylabel(\"Temperature (°C)\", color=\"blue\")\n", + "ax1.tick_params(axis=\"y\", labelcolor=\"blue\")\n", + "ax1.legend(loc=\"upper left\")\n", + "\n", + "# Create a twin axis for voltage\n", + "ax2 = ax1.twinx()\n", + "mqt_13.setpoints[\"setpoint_relative_humidity\"].plot(ax=ax2, color=\"red\", label=\"Relative Humidity\")\n", + "ax2.set_ylabel(\"Rh (%)\", color=\"red\")\n", + "ax2.tick_params(axis=\"y\", labelcolor=\"red\")\n", + "ax2.legend(loc=\"upper right\")\n", + "\n", + "plt.title(\"Chamber Setpoints: Temperature and RH\")\n", + "plt.tight_layout()\n", + "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Damp Heat Test (MQT 13)\n", + "**Damp Heat Test (MQT 13)**\n", "\n", "This test is defined in IEC-61215. It is an $85 \\degree C$, 85% relative humidity test for 1000 hours." ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -122,14 +355,65 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmwAAAGzCAYAAACSFUtCAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAABI8klEQVR4nO3deXiNd/7/8dc5JznJyXYiESJks2uaopQJRrSMMK2ti1JVVNGiugzKb0otVa2lo9UOZtqilq6jTFdVpa2lllbNTBnK2FqUsSRIRCSf3x/95h4nC6HInXg+rivX5dznvj/3+37nzn1e7vvc5ziMMUYAAACwLWdpFwAAAIDzI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7AB1wiHw6HBgweXdhmW3bt3y+FwaMqUKaVdSpm1cuVKORwOrVy5srRLAXCFEdiAMm7nzp0aMGCAqlevrsDAQIWFhal58+Z64YUXlJWVVdrl2d7hw4f1yCOPqG7duvJ4PKpUqZKaNGmiJ554QidPnrzo8dasWaMxY8bo+PHjl7/Yy2j//v0aM2aMvvvuu9IuBUAJ+JV2AQAu3Ycffqi77rpLAQEBuu+++3T99dfrzJkzWrVqlYYNG6bvv/9ef/nLX0q7TNs6evSoGjdurIyMDN1///2qW7eujhw5on/84x+aMWOGHnroIYWEhFzUmGvWrNHYsWPVu3dvhYeHX5nC/0/Lli2VlZUlt9t90cvu379fY8eOVUJCgho0aHD5iwNwWRHYgDJq165d6tatm+Lj4/X555+rSpUq1nODBg3Sjh079OGHH5ZihfZw6tQpBQcHF/ncq6++qr1792r16tVq1qyZz3MZGRmXFISuJqfTqcDAwNIuA8BVwCVRoIyaNGmSTp48qVdffdUnrOWrWbOmHnnkkULTFy9erOuvv14BAQFKSkrSJ5984vP8nj17NHDgQNWpU0cej0eRkZG66667tHv3bp/55syZI4fDoVWrVmnIkCGKiopSeHi4BgwYoDNnzuj48eO67777VKFCBVWoUEHDhw+XMabIbfnTn/6k+Ph4eTwepaam6l//+lehef7973/rzjvvVEREhAIDA9W4cWP9/e9/L7KmL774QgMHDlSlSpVUrVq1Ynu4c+dOuVwu/eY3vyn0XFhYWKEwtG7dOrVr105er1dBQUFKTU3V6tWrrefHjBmjYcOGSZISExPlcDjkcDis3uW/j3DBggWqU6eOAgMD1ahRI3355ZeF1r9p0ya1b99eYWFhCgkJUevWrfX111/7zFPUe9hatWql66+/Xlu2bNHNN9+soKAgVa1aVZMmTfJZ7qabbpIk9enTx6pzzpw5kqQffvhBd9xxh6KjoxUYGKhq1aqpW7duSk9PL7aXAK4szrABZdT777+v6tWrFzozdD6rVq3SokWLNHDgQIWGhurFF1/UHXfcob179yoyMlKStGHDBq1Zs0bdunVTtWrVtHv3bs2YMUOtWrXSli1bFBQU5DPmww8/rOjoaI0dO1Zff/21/vKXvyg8PFxr1qxRXFycnnnmGX300UeaPHmyrr/+et13330+y7/++us6ceKEBg0apNOnT+uFF17QLbfcon/+85+qXLmyJOn7779X8+bNVbVqVY0YMULBwcF6++231blzZ/3tb39Tly5dfMYcOHCgoqKiNHr0aJ06darYfsTHxys3N1fz5s1Tr169ztu7zz//XO3bt1ejRo301FNPyel0avbs2brlllv01VdfqUmTJrr99tu1fft2vfHGG/rTn/6kihUrSpKioqKscb744gu99dZbGjJkiAICAvTnP/9Z7dq10/r163X99ddb2/vb3/5WYWFhGj58uPz9/TVr1iy1atVKX3zxhZo2bXreWo8dO6Z27drp9ttvV9euXfXuu+/qiSeeUHJystq3b6969epp3LhxGj16tPr376/f/va3kqRmzZrpzJkzSktLU3Z2tvW7/emnn/TBBx/o+PHj8nq95103gCvEAChz0tPTjSTTqVOnEi8jybjdbrNjxw5r2ubNm40kM336dGtaZmZmoWXXrl1rJJnXX3/dmjZ79mwjyaSlpZm8vDxrekpKinE4HObBBx+0pp09e9ZUq1bNpKamWtN27dplJBmPx2N+/PFHa/q6deuMJPPYY49Z01q3bm2Sk5PN6dOnrWl5eXmmWbNmplatWoVqatGihTl79uwFe3Lw4EETFRVlJJm6deuaBx980CxcuNAcP37cZ768vDxTq1atQtuamZlpEhMTze9+9ztr2uTJk40ks2vXrkLrk2QkmY0bN1rT9uzZYwIDA02XLl2saZ07dzZut9vs3LnTmrZ//34TGhpqWrZsaU1bsWKFkWRWrFhhTUtNTS30u8rOzjbR0dHmjjvusKZt2LDBSDKzZ8/2qXHTpk1GknnnnXfO0zkAVxuXRIEyKCMjQ5IUGhp6Ucu1adNGNWrUsB7fcMMNCgsL03/+8x9rmsfjsf6dk5OjI0eOqGbNmgoPD9e3335baMy+ffvK4XBYj5s2bSpjjPr27WtNc7lcaty4sc968nXu3FlVq1a1Hjdp0kRNmzbVRx99JOmXGwM+//xzde3aVSdOnNB///tf/fe//9WRI0eUlpamH374QT/99JPPmP369ZPL5bpgPypXrqzNmzfrwQcf1LFjxzRz5kzdc889qlSpksaPH29dwv3uu+/0ww8/6J577tGRI0esGk6dOqXWrVvryy+/VF5e3gXXJ0kpKSlq1KiR9TguLk6dOnXS0qVLlZubq9zcXH366afq3Lmzqlevbs1XpUoV3XPPPVq1apX1+y9OSEiI7r33Xuux2+1WkyZNiux/Qfln0JYuXarMzMwSbROAK4/ABpRBYWFhkqQTJ05c1HJxcXGFplWoUEHHjh2zHmdlZWn06NGKjY1VQECAKlasqKioKB0/frzI9zAVHDP/BT82NrbQ9HPXk69WrVqFptWuXdt639eOHTtkjNGoUaMUFRXl8/PUU09Jkg4dOuSzfGJiYlGbX6QqVapoxowZOnDggLZt26YXX3zRupz66quvSvrlPV2S1KtXr0I1vPLKK8rOzi7x+7uK297MzEwdPnxYhw8fVmZmpurUqVNovnr16ikvL0/79u077zqqVavmE6Klwr/n4iQmJurxxx/XK6+8oooVKyotLU0vv/wy718DShnvYQPKoLCwMMXExBT55vzzKe6skznnZoCHH35Ys2fP1qOPPqqUlBR5vV45HA5169atyLNIxY1Z1HRTzE0H55O/zqFDhyotLa3IeWrWrOnz+NyzhCXlcDhUu3Zt1a5dW7feeqtq1aqlBQsW6IEHHrBqmDx5crEfgXGxH/9xJZXk93w+U6dOVe/evbVkyRJ9+umnGjJkiCZOnKivv/76vDdxALhyCGxAGXXbbbfpL3/5i9auXauUlJTLNu67776rXr16aerUqda006dPX7EPgs0/e3Wu7du3KyEhQZKsy4L+/v5q06bNFamhoOrVq6tChQo6cOCAJFmXkcPCwi5YQ8EzWwUVt71BQUHWzQlBQUHatm1bofn+/e9/y+l0Fjp7eSkuVGdycrKSk5P15JNPas2aNWrevLlmzpypp59++levG8DF45IoUEYNHz5cwcHBeuCBB/Tzzz8Xen7nzp164YUXLnpcl8tV6EzM9OnTlZube8m1ns/ixYt93oO2fv16rVu3Tu3bt5ckVapUSa1atdKsWbOsAHWuw4cPX/K6161bV+RdpOvXr9eRI0esy5KNGjVSjRo1NGXKlCK//eDcGvI/8624gLt27Vqf9wLu27dPS5YsUdu2beVyueRyudS2bVstWbLE56NUfv75Zy1cuFAtWrSwLon/GsXVmZGRobNnz/pMS05OltPpVHZ29q9eL4BLwxk2oIyqUaOGFi5cqLvvvlv16tXz+aaDNWvW6J133lHv3r0vetzbbrtN8+bNk9fr1XXXXae1a9fqs88+sz7243KrWbOmWrRooYceekjZ2dmaNm2aIiMjNXz4cGuel19+WS1atFBycrL69eun6tWr6+eff9batWv1448/avPmzZe07nnz5mnBggXq0qWLGjVqJLfbra1bt+q1115TYGCg/t//+3+SfvmA2ldeeUXt27dXUlKS+vTpo6pVq+qnn37SihUrFBYWpvfff1+SrBsK/vjHP6pbt27y9/dXhw4drIB0/fXXKy0tzedjPSRp7NixVl1PP/20li1bphYtWmjgwIHy8/PTrFmzlJ2d7fN5ar9GjRo1FB4erpkzZyo0NFTBwcFq2rSpNm/erMGDB+uuu+5S7dq1dfbsWc2bN08ul0t33HHHZVk3gItHYAPKsI4dO+of//iHJk+erCVLlmjGjBkKCAjQDTfcoKlTp6pfv34XPeYLL7wgl8ulBQsW6PTp02revLk+++yzYt8/9mvdd999cjqdmjZtmg4dOqQmTZropZde8vkw4Ouuu04bN27U2LFjNWfOHB05ckSVKlVSw4YNNXr06Ete94ABAxQUFKTly5dryZIlysjIUFRUlNq2bauRI0eqYcOG1rytWrXS2rVrNX78eL300ks6efKkoqOj1bRpUw0YMMCa76abbtL48eM1c+ZMffLJJ8rLy9OuXbuswJaamqqUlBSNHTtWe/fu1XXXXac5c+bohhtusMZISkrSV199pZEjR2rixInKy8tT06ZNNX/+/At+BltJ+fv7a+7cuRo5cqQefPBBnT17VrNnz1ZqaqrS0tL0/vvv66efflJQUJDq16+vjz/+uMgPGAZwdTjMpbwLGABw0RwOhwYNGqSXXnqptEsBUMbwHjYAAACbI7ABAADYHIENAADA5rjpAACuEt4yDOBScYYNAADA5ghsAAAANscl0QLy8vK0f/9+hYaGXvCrWwAAgD0YY3TixAnFxMTI6Sx/56MIbAXs37//snxPHwAAuPr27dunatWqlXYZlx2BrYDQ0FBJv/zCL8f39QEAgCsvIyNDsbGx1ut4eUNgKyD/MmhYWBiBDQCAMqa8vp2p/F3kBQAAKGcIbAAAADZHYAMAALA53sMGAOcwxujs2bPKzc0t7VIAFODv7y+Xy1XaZZQKAhsA/J8zZ87owIEDyszMLO1SABTB4XCoWrVqCgkJKe1SrjoCGwDolw/N3rVrl1wul2JiYuR2u8vt3WZAWWSM0eHDh/Xjjz+qVq1a19yZNgIbAOiXs2t5eXmKjY1VUFBQaZcDoAhRUVHavXu3cnJyrrnAxk0HAHCO8viVNkB5cS2f9ebIBAAAYHMENgAAAJsjsAEALruVK1fK4XDo+PHjpV0KUC4Q2ADgGrV79245HA599913l33sZs2a6cCBA/J6vSVepnfv3urcuXOJ57+S9dtRQkKCpk2bVtploJQQ2AAAl53b7VZ0dPQ1/Sbxksj/oOar6cyZM1d1fbg8CGwAUARjjDLPnC2VH2PMRdX67rvvKjk5WR6PR5GRkWrTpo1OnTolSXrllVdUr149BQYGqm7duvrzn/9sLZeYmChJatiwoRwOh1q1aiXpf2e6xo4dq6ioKIWFhenBBx/0eaHPzs7WkCFDVKlSJQUGBqpFixbasGGD9XzBS6Jz5sxReHi4li5dqnr16ikkJETt2rXTgQMHJEljxozR3LlztWTJEjkcDjkcDq1cufK8211c/Rfa7vwzc2+//bZ++9vfyuPx6KabbtL27du1YcMGNW7cWCEhIWrfvr0OHz5sLVeSvuTl5WnixIlKTEyUx+NR/fr19e677xbqy8cff6xGjRopICBAq1at0s6dO9WpUydVrlxZISEhuummm/TZZ59Zy7Vq1Up79uzRY489ZvUnv28NGjTw6cu0adOUkJBQqO4JEyYoJiZGderUkSTt27dPXbt2VXh4uCIiItSpUyft3r37vD1H6eFz2ACgCFk5ubpu9NJSWfeWcWkKcpfs8HzgwAF1795dkyZNUpcuXXTixAl99dVXMsZowYIFGj16tF566SU1bNhQmzZtUr9+/RQcHKxevXpp/fr1atKkiT777DMlJSXJ7XZb4y5fvlyBgYFauXKldu/erT59+igyMlITJkyQJA0fPlx/+9vfNHfuXMXHx2vSpElKS0vTjh07FBERUWStmZmZmjJliubNmyen06l7771XQ4cO1YIFCzR06FBt3bpVGRkZmj17tiQVO06+4uq/0Hbne+qppzRt2jTFxcXp/vvv1z333KPQ0FC98MILCgoKUteuXTV69GjNmDGjxH2ZOHGi5s+fr5kzZ6pWrVr68ssvde+99yoqKkqpqanWOCNGjNCUKVNUvXp1VahQQfv27dPvf/97TZgwQQEBAXr99dfVoUMHbdu2TXFxcVq0aJHq16+v/v37q1+/fiXaN861fPlyhYWFadmyZZKknJwcpaWlKSUlRV999ZX8/Pz09NNPq127dvrHP/7hsy/AHghsAFCGHThwQGfPntXtt9+u+Ph4SVJycrKkXwLJ1KlTdfvtt0v65YzUli1bNGvWLPXq1UtRUVGSpMjISEVHR/uM63a79dprrykoKEhJSUkaN26chg0bpvHjxysrK0szZszQnDlz1L59e0nSX//6Vy1btkyvvvqqhg0bVmStOTk5mjlzpmrUqCFJGjx4sMaNGydJCgkJkcfjUXZ2dqFailNc/Rfa7nxDhw5VWlqaJOmRRx5R9+7dtXz5cjVv3lyS1LdvX82ZM6fEfcnJydEzzzyjzz77TCkpKZKk6tWra9WqVZo1a5ZPYBs3bpx+97vfWY8jIiJUv3596/H48eP13nvv6e9//7sGDx6siIgIuVwuhYaGlrg/5woODtYrr7xiBbH58+crLy9Pr7zyinW2bvbs2QoPD9fKlSvVtm3bi14HriwCGwAUwePv0pZxaaW27pKqX7++WrdureTkZKWlpalt27a688475Xa7tXPnTvXt29fnjMzZs2dLdCNA/fr1fb7xISUlRSdPntS+ffuUnp6unJwcK9hIv3wpd5MmTbR169ZixwwKCrLCmiRVqVJFhw4dKvG2lsSpU6dKvN033HCD9e/KlStL+l/YzZ9WsL7z9eXkyZPKzMz0CWLSL+8Za9iwoc+0xo0b+zw+efKkxowZow8//NAK4VlZWdq7d+/FbH6xkpOTfc6abd68WTt27FBoaKjPfKdPn9bOnTsvyzpxeRHYAKAIDoejxJclS5PL5dKyZcu0Zs0affrpp5o+fbr++Mc/6v3335f0y5mvpk2bFlqmNPj7+/s8djgcF/1+vQs5efKkpJJt97n15J9lKjgtLy/votf94YcfqmrVqj7PBQQE+DwODg72eTx06FAtW7ZMU6ZMUc2aNeXxeHTnnXde8AYBp9NZqIc5OTmF5iu4vpMnT6pRo0ZasGBBoXnzz1zCXux/NAIAnJfD4VDz5s3VvHlzjR49WvHx8Vq9erViYmL0n//8Rz169ChyufwzLrm5uYWe27x5s7KysuTxeCRJX3/9tUJCQhQbG6uKFSvK7XZr9erV1mXYnJwcbdiwQY8++uglb4fb7S6ylvPNX7D+ypUrX3C7f43z9SUiIkIBAQHau3evz+XPkli9erV69+6tLl26SPolUBW8AaCo/kRFRengwYMyxlihsyQfc3LjjTfqrbfeUqVKlRQWFnZRtaJ0ENgAoAxbt26dli9frrZt26pSpUpat26dDh8+rHr16mns2LEaMmSIvF6v2rVrp+zsbG3cuFHHjh3T448/rkqVKsnj8eiTTz5RtWrVFBgYaF02PHPmjPr27asnn3xSu3fv1lNPPaXBgwfL6XQqODhYDz30kIYNG6aIiAjFxcVp0qRJyszMVN++fS95WxISErR06VJt27ZNkZGR8nq9hc7Knau4+i+03b/G+foSGhqqoUOH6rHHHlNeXp5atGih9PR0rV69WmFhYT7vnyuoVq1aWrRokTp06CCHw6FRo0YVOruXkJCgL7/8Ut26dVNAQIAqVqyoVq1a6fDhw5o0aZLuvPNOffLJJ/r4448vGMJ69OihyZMnq1OnTho3bpyqVaumPXv2aNGiRRo+fLiqVav2q/qEK8DAR3p6upFk0tPTS7sUAFdRVlaW2bJli8nKyirtUi7Kli1bTFpamomKijIBAQGmdu3aZvr06dbzCxYsMA0aNDBut9tUqFDBtGzZ0ixatMh6/q9//auJjY01TqfTpKamGmOM6dWrl+nUqZMZPXq0iYyMNCEhIaZfv37m9OnT1nJZWVnm4YcfNhUrVjQBAQGmefPmZv369dbzK1asMJLMsWPHjDHGzJ4923i9Xp/a33vvPXPuy9ChQ4fM7373OxMSEmIkmRUrVlxw+4uq/0LbvWvXLiPJbNq0qdh6i6q5JH3Jy8sz06ZNM3Xq1DH+/v4mKirKpKWlmS+++KLY9eTXdPPNNxuPx2NiY2PNSy+9ZFJTU80jjzxizbN27Vpzww03mICAAJ++zZgxw8TGxprg4GBz3333mQkTJpj4+PhCdRd04MABc99991m/w+rVq5t+/frZ+vXvfH+n5f3122HMZX4DQRmXkZEhr9er9PR0ThMD15DTp09r165dSkxMVGBgYGmXU6p69+6t48ePa/HixaVdiq3Ql9J3vr/T8v76zQfnAgAA2ByBDQBgS88884xCQkKK/Mn//DfgWsEl0QLK+ylVAEXjkqj9HD16VEePHi3yOY/HU+ijM1D+XcuXRLlLFABgSxERERf8eirgWsElUQAAAJsjsAEAANgcgQ0AAMDmCGwAAAA2R2ADAACwOQIbAOCyW7lypRwOh44fP17apRSye/duORyOEn1J+tUYp6TGjBmjBg0aXJV1Xcq6e/furc6dO1uPW7VqpUcfffSK1nUtIbABwDXqSgaOZs2a6cCBA9aXyZdEwRd8OymqttjYWB04cEDXX3996RR1FQ0dOlTLly+/qGUWLVqk8ePHW48TEhI0bdq0y1zZtYPPYQMAXHZut1vR0dFXfb05OTny9/e/KutyuVylso2lIf8bJi4Gn6F3eXGGDQCKYox05lTp/FzkF9C8++67Sk5OlsfjUWRkpNq0aaNTp05Jkl555RXVq1dPgYGBqlu3rv785z9byyUmJkqSGjZsKIfDoVatWkn639mksWPHKioqSmFhYXrwwQd15swZa9ns7GwNGTJElSpVUmBgoFq0aKENGzZYzxe8JDpnzhyFh4dr6dKlqlevnkJCQtSuXTsdOHBA0i+X3ObOnaslS5bI4XDI4XBo5cqV593u/DOEb731llJTUxUYGKgFCxZccLsLys3NVd++fZWYmCiPx6M6derohRdesJ4vrrZzz1Dm5eWpWrVqmjFjhs/YmzZtktPp1J49eyRJx48f1wMPPGD19ZZbbtHmzZvPu50FzZs3TwkJCfJ6verWrZtOnDhhPVfUWawGDRpozJgx1mOHw6FZs2bptttuU1BQkOrVq6e1a9dqx44datWqlYKDg9WsWTPt3LnTpwfnXhLNzc3V448/rvDwcEVGRmr48OEq+MVJ514SbdWqlfbs2aPHHnvM6uGpU6cUFhamd99912e5xYsXKzg42Ge7wBk2AChaTqb0TEzprPv/7ZfcwSWa9cCBA+revbsmTZqkLl266MSJE/rqq69kjNGCBQs0evRovfTSS2rYsKE2bdqkfv36KTg4WL169dL69evVpEkTffbZZ0pKSpLb7bbGXb58uQIDA61g0qdPH0VGRmrChAmSpOHDh+tvf/ub5s6dq/j4eE2aNElpaWnasWNHsWdWMjMzNWXKFM2bN09Op1P33nuvhg4dqgULFmjo0KHaunWrMjIyNHv2bEklP0MzYsQITZ06VQ0bNrRC2/m2u6D8sPXOO+8oMjJSa9asUf/+/VWlShV17dq12Nr2799vjeF0OtW9e3ctXLhQDz30kDV9wYIFat68ueLj4yVJd911lzwejz7++GN5vV7NmjVLrVu31vbt20u0vTt37tTixYv1wQcf6NixY+rataueffZZ6/dSUuPHj9fzzz+v559/Xk888YTuueceVa9eXSNHjlRcXJzuv/9+DR48WB9//HGRy0+dOlVz5szRa6+9pnr16mnq1Kl67733dMsttxQ5/6JFi1S/fn31799f/fr1kyQFBwerW7dumj17tu68805r3vzHoaGhF7VN5R2BDQDKsAMHDujs2bO6/fbbrVCQnJwsSXrqqac0depU3X777ZJ+OaO2ZcsWzZo1S7169VJUVJQkKTIystClPbfbrddee01BQUFKSkrSuHHjNGzYMI0fP15ZWVmaMWOG5syZY30J+1//+lctW7ZMr776qoYNG1ZkrTk5OZo5c6Zq1KghSRo8eLDGjRsn6ZdLbh6PR9nZ2Rd9mfHRRx+1trEk212Qv7+/xo4daz1OTEzU2rVr9fbbb6tr164lrq1Hjx6aOnWq9u7dq7i4OOXl5enNN9/Uk08+KUlatWqV1q9fr0OHDikgIECSNGXKFC1evFjvvvuu+vfvf8FtzcvL05w5c6ww07NnTy1fvvyiA1ufPn3UtWtXSdITTzyhlJQUjRo1SmlpaZKkRx55RH369Cl2+WnTpmnkyJFWj2fOnKmlS5cWO39ERIRcLpdCQ0N9evjAAw9Y73esUqWKDh06pI8++kifffbZRW3PtYDABgBF8Q/65UxXaa27hOrXr6/WrVsrOTlZaWlpatu2re6880653W7t3LlTffv2tc5oSNLZs2dLdCNA/fr1FRT0vzpSUlJ08uRJ7du3T+np6crJyVHz5s3/V7K/v5o0aaKtW7cWO2ZQUJAV1iRZL9C/VuPGja1/nzp16pK2++WXX9Zrr72mvXv3KisrS2fOnLnoOzIbNGigevXqaeHChRoxYoS++OILHTp0SHfddZckafPmzTp58qQiIyN9lsvKyvK5/Hg+CQkJPmeeLrWHN9xwg/XvypUrS/pf0M+fdvr0aWVkZBT6IvX09HQdOHBATZs2tab5+fmpcePGhS6LXkiTJk2UlJSkuXPnasSIEZo/f77i4+PVsmXLi96m8o7ABgBFcThKfFmyNLlcLi1btkxr1qzRp59+qunTp+uPf/yj3n//fUm/nPk694U1f5nSUPBmAIfDcdEv8EUJDv7f7+nkyZOSLm6733zzTQ0dOlRTp05VSkqKQkNDNXnyZK1bt+6ia+nRo4cV2BYuXKh27dpZAe3kyZOqUqVKke/NCw8PL9H4RfUwLy/Peux0Ogv1NCcn57zjOByOYqedO/aV8sADD+jll1/WiBEjNHv2bPXp08daP/6Hmw4AoIxzOBxq3ry5xo4dq02bNsntdmv16tWKiYnRf/7zH9WsWdPnJ/9mg/z3rOXm5hYac/PmzcrKyrIef/311woJCVFsbKxq1KhhrSNfTk6ONmzYoOuuu+6St8PtdhdZy8WoXLnyBbe7oNWrV6tZs2YaOHCgGjZsqJo1axY641XS2u655x7961//0jfffKN3331XPXr0sJ678cYbdfDgQfn5+RWqrWLFir9qu/NFRUVZN3JIUkZGhnbt2nVZxs7n9XpVpUoVn0B79uxZffPNN+ddrrge3nvvvdqzZ49efPFFbdmypcjL1uAMGwCUaevWrdPy5cvVtm1bVapUSevWrdPhw4dVr149jR07VkOGDJHX61W7du2UnZ2tjRs36tixY3r88cdVqVIleTweffLJJ6pWrZoCAwOty4ZnzpxR37599eSTT2r37t166qmnNHjwYDmdTgUHB+uhhx7SsGHDFBERobi4OE2aNEmZmZnq27fvJW9LQkKCli5dqm3btikyMlJer/eSPqLjQttdUK1atfT6669r6dKlSkxM1Lx587RhwwafgFdUbcVtQ7NmzdS3b1/l5uaqY8eO1nNt2rRRSkqKOnfurEmTJql27drav3+/PvzwQ3Xp0sXn0u6luuWWWzRnzhx16NBB4eHhGj169BU5o/rII4/o2WefVa1atVS3bl09//zzF/yQ5ISEBH355Zfq1q2bAgICrJBaoUIF3X777Ro2bJjatm2ratWqXfZ6ywPOsAFAGRYWFqYvv/xSv//971W7dm09+eSTmjp1qtq3b68HHnhAr7zyimbPnq3k5GSlpqZqzpw5VhDx8/PTiy++qFmzZikmJkadOnWyxm3durVq1aqlli1b6u6771bHjh19Phri2Wef1R133KGePXvqxhtv1I4dO7R06VJVqFDhkrelX79+qlOnjho3bqyoqCifM3gX40LbXdCAAQN0++236+6771bTpk115MgRDRw48JJr69GjhzZv3qwuXbrI4/FY0x0Ohz766CO1bNlSffr0Ue3atdWtWzft2bPHeh/ZrzVy5Eilpqbqtttu06233qrOnTv7vG/wcvnDH/6gnj17qlevXtZl5C5dupx3mXHjxmn37t2qUaOGdcNLvr59++rMmTO6//77L3ut5YXDXI43EJQjGRkZ8nq9Sk9PL/RGSwDl1+nTp7Vr1y4lJiYqMDCwtMspVb1799bx48e1ePHi0i4F14h58+bpscce0/79+30+Xqag8/2dlvfXby6JAgCAUpGZmakDBw7o2Wef1YABA84b1q51XBIFANjSM888Y30lUsGf/M9/K0+SkpKK3d78b3AobyZNmqS6desqOjpaI0eOLO1ybI1LogWU91OqAIrGJVH7OXr0qI4ePVrkcx6PR1WrVr3KFV1Ze/bsKfIjOKRf7n7lk/+5JAoAgO1ERERcU18gnv9NFUBRuCQKAOfgogNgX9fy3yeBDQD0v095z8zMLOVKABTnzJkzkkrv2zpKE5dEAUC/vACEh4db38sYFBTE1+MANpKXl6fDhw8rKChIfn7XXny59rYYAIoRHR0tSZflC8kBXH5Op1NxcXHX5H+mCGwA8H8cDoeqVKmiSpUqFXu3HoDS43a75XRem+/mIrABQAEul+uafI8MAPu6NmMqAABAGUJgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbK1OBLTc3V6NGjVJiYqI8Ho9q1Kih8ePH+3y32MmTJzV48GBVq1ZNHo9H1113nWbOnFmKVQMAAPw6Zepz2J577jnNmDFDc+fOVVJSkjZu3Kg+ffrI6/VqyJAhkqTHH39cn3/+uebPn6+EhAR9+umnGjhwoGJiYtSxY8dS3gIAAICLV6bOsK1Zs0adOnXSrbfeqoSEBN15551q27at1q9f7zNPr1691KpVKyUkJKh///6qX7++zzwAAABlSZkKbM2aNdPy5cu1fft2SdLmzZu1atUqtW/f3meev//97/rpp59kjNGKFSu0fft2tW3btsgxs7OzlZGR4fMDAABgJ2XqkuiIESOUkZGhunXryuVyKTc3VxMmTFCPHj2seaZPn67+/furWrVq8vPzk9Pp1F//+le1bNmyyDEnTpyosWPHXq1NAAAAuGhl6gzb22+/rQULFmjhwoX69ttvNXfuXE2ZMkVz58615pk+fbq+/vpr/f3vf9c333yjqVOnatCgQfrss8+KHHPkyJFKT0+3fvbt23e1NgcAAKBEHObcWyxtLjY2ViNGjNCgQYOsaU8//bTmz5+vf//738rKypLX69V7772nW2+91ZrngQce0I8//qhPPvnkguvIyMiQ1+tVenq6wsLCrsh2AACAy6u8v36XqTNsmZmZcjp9S3a5XMrLy5Mk5eTkKCcn57zzAAAAlDVl6j1sHTp00IQJExQXF6ekpCRt2rRJzz//vO6//35JUlhYmFJTUzVs2DB5PB7Fx8friy++0Ouvv67nn3++lKsHAAC4NGXqkuiJEyc0atQovffeezp06JBiYmLUvXt3jR49Wm63W5J08OBBjRw5Up9++qmOHj2q+Ph49e/fX4899pgcDscF11HeT6kCAFAelffX7zIV2K6G8v4LBwCgPCrvr99l6j1sAAAA1yICGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzZSqw5ebmatSoUUpMTJTH41GNGjU0fvx4GWN85tu6das6duwor9er4OBg3XTTTdq7d28pVQ0AAPDr+JV2ARfjueee04wZMzR37lwlJSVp48aN6tOnj7xer4YMGSJJ2rlzp1q0aKG+fftq7NixCgsL0/fff6/AwMBSrh4AAODSOEzB01M2dtttt6ly5cp69dVXrWl33HGHPB6P5s+fL0nq1q2b/P39NW/evEtaR0ZGhrxer9LT0xUWFnZZ6gYAAFdWeX/9LlOXRJs1a6bly5dr+/btkqTNmzdr1apVat++vSQpLy9PH374oWrXrq20tDRVqlRJTZs21eLFi4sdMzs7WxkZGT4/AAAAdlKmAtuIESPUrVs31a1bV/7+/mrYsKEeffRR9ejRQ5J06NAhnTx5Us8++6zatWunTz/9VF26dNHtt9+uL774osgxJ06cKK/Xa/3ExsZezU0CAAC4oDJ1SfTNN9/UsGHDNHnyZCUlJem7777To48+queff169evXS/v37VbVqVXXv3l0LFy60luvYsaOCg4P1xhtvFBozOztb2dnZ1uOMjAzFxsaW21OqAACUR+X9kmiZuulg2LBh1lk2SUpOTtaePXs0ceJE9erVSxUrVpSfn5+uu+46n+Xq1aunVatWFTlmQECAAgICrnjtAAAAl6pMXRLNzMyU0+lbssvlUl5eniTJ7Xbrpptu0rZt23zm2b59u+Lj469anQAAAJdTmTrD1qFDB02YMEFxcXFKSkrSpk2b9Pzzz+v++++35hk2bJjuvvtutWzZUjfffLM++eQTvf/++1q5cmXpFQ4AAPArlKn3sJ04cUKjRo3Se++9p0OHDikmJkbdu3fX6NGj5Xa7rflee+01TZw4UT/++KPq1KmjsWPHqlOnTiVaR3m/Bg4AQHlU3l+/y1RguxrK+y8cAIDyqLy/fpep97ABAABciwhsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACb8yvtAuxqw18fVrDHXdplAACAEjiVdaa0S7iiCGzFuOm/7ykswFHaZQAAgBLIyDalXcIVRWArxvoq9yjYE1DaZQAAgBI4lZUtaVZpl3HFOIwx5TuSXqSMjAx5vV6lp6crLCystMsBAAAlUN5fv7npAAAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwObKVGDLzc3VqFGjlJiYKI/Hoxo1amj8+PEyxhQ5/4MPPiiHw6Fp06Zd3UIBAAAuI7/SLuBiPPfcc5oxY4bmzp2rpKQkbdy4UX369JHX69WQIUN85n3vvff09ddfKyYmppSqBQAAuDzKVGBbs2aNOnXqpFtvvVWSlJCQoDfeeEPr16/3me+nn37Sww8/rKVLl1rzAgAAlFVl6pJos2bNtHz5cm3fvl2StHnzZq1atUrt27e35snLy1PPnj01bNgwJSUlXXDM7OxsZWRk+PwAAADYSZk6wzZixAhlZGSobt26crlcys3N1YQJE9SjRw9rnueee05+fn6FLpEWZ+LEiRo7duyVKhkAAOBXK1Nn2N5++20tWLBACxcu1Lfffqu5c+dqypQpmjt3riTpm2++0QsvvKA5c+bI4XCUaMyRI0cqPT3d+tm3b9+V3AQAAICL5jDF3WJpQ7GxsRoxYoQGDRpkTXv66ac1f/58/fvf/9a0adP0+OOPy+n8Xw7Nzc2V0+lUbGysdu/efcF1ZGRkyOv1Kj09XWFhYVdiMwAAwGVW3l+/y9Ql0czMTJ8wJkkul0t5eXmSpJ49e6pNmzY+z6elpalnz57q06fPVasTAADgcipTga1Dhw6aMGGC4uLilJSUpE2bNun555/X/fffL0mKjIxUZGSkzzL+/v6Kjo5WnTp1SqNkAACAX61MBbbp06dr1KhRGjhwoA4dOqSYmBgNGDBAo0ePLu3SAAAArpgy9R62q6G8XwMHAKA8Ku+v32XqLlEAAIBrEYENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbI7ABAADYHIENAADA5ghsAAAANkdgAwAAsLkyFdhyc3M1atQoJSYmyuPxqEaNGho/fryMMZKknJwcPfHEE0pOTlZwcLBiYmJ03333af/+/aVcOQAAwKXzK+0CLsZzzz2nGTNmaO7cuUpKStLGjRvVp08feb1eDRkyRJmZmfr22281atQo1a9fX8eOHdMjjzyijh07auPGjaVdPgAAwCVxmPzTU2XAbbfdpsqVK+vVV1+1pt1xxx3yeDyaP39+kcts2LBBTZo00Z49exQXF3fBdWRkZMjr9So9PV1hYWGXrXYAAHDllPfX7zJ1SbRZs2Zavny5tm/fLknavHmzVq1apfbt2xe7THp6uhwOh8LDw4t8Pjs7WxkZGT4/AAAAdlKmLomOGDFCGRkZqlu3rlwul3JzczVhwgT16NGjyPlPnz6tJ554Qt27dy82bU+cOFFjx469kmUDAAD8KmXqDNvbb7+tBQsWaOHChfr22281d+5cTZkyRXPnzi00b05Ojrp27SpjjGbMmFHsmCNHjlR6err1s2/fviu5CQAAABetTJ1hGzZsmEaMGKFu3bpJkpKTk7Vnzx5NnDhRvXr1subLD2t79uzR559/ft5r2QEBAQoICLjitQMAAFyqMhXYMjMz5XT6nhR0uVzKy8uzHueHtR9++EErVqxQZGTk1S4TAADgsipTga1Dhw6aMGGC4uLilJSUpE2bNun555/X/fffL+mXsHbnnXfq22+/1QcffKDc3FwdPHhQkhQRESG3212a5QMAAFySMvWxHidOnNCoUaP03nvv6dChQ4qJiVH37t01evRoud1u7d69W4mJiUUuu2LFCrVq1eqC6yjvtwUDAFAelffX7zIV2K6G8v4LBwCgPCrvr99l6i5RAACAaxGBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOYIbAAAADZHYAMAALA5AhsAAIDNEdgAAABsjsAGAABgcwQ2AAAAmyOwAQAA2ByBDQAAwOb8SrsAuzHGSJIyMjJKuRIAAFBS+a/b+a/j5Q2BrYAjR45IkmJjY0u5EgAAcLFOnDghr9db2mVcdgS2AiIiIiRJe/fuLZe/8EuRkZGh2NhY7du3T2FhYaVdji3Qk8LoSWH0pDB6Uhg9KexSemKM0YkTJxQTE3OFqysdBLYCnM5f3tbn9Xr5wykgLCyMnhRATwqjJ4XRk8LoSWH0pLCL7Ul5PtHCTQcAAAA2R2ADAACwOQJbAQEBAXrqqacUEBBQ2qXYBj0pjJ4URk8KoyeF0ZPC6Elh9KQwhymv978CAACUE5xhAwAAsDkCGwAAgM0R2AAAAGyOwAYAAGBzBDYAAACbu6TA9vLLLyshIUGBgYFq2rSp1q9fbz13+vRpDRo0SJGRkQoJCdEdd9yhn3/++YJjvvPOO6pbt64CAwOVnJysjz76yOd5Y4xGjx6tKlWqyOPxqE2bNvrhhx8uOO7KlSt14403KiAgQDVr1tScOXMuantKWu/AgQN9xli3bp1Vb2BgoKpVq6YKFSr49OTo0aPq0aOHwsLCFB4err59++rkyZM+60hMTJTT6ZTT6VTFihU1adKkQj2pUKGCNU/t2rUv2LtGjRopKSmp3PakU6dOcjgcPj+BgYHlticLFiyQ1+uV0+mUw+FQSkpKkdsaGRlp9S0uLu6C21ivXj3VrVv3ivYkJiZGlStX9lk+v97o6Gj5+fnJ399fwcHBPseS8/XknXfeUZ06deRyuRQYGCiXy6XOnTsX2Y+C+4nD4dDBgweL3Ea3263g4GC53e4yt4+MGTNGoaGhcjgccjqdql69uhYsWFCoJ9fSsaQkPbnWjiUvvPCCgoKCrJ5ER0frySefVE5Ojs+22nU/uZTccKGebNu2TTfffLN1nKpevbpPTyRpzpw5F72flDTDFBzkorz55pvG7Xab1157zXz//femX79+Jjw83Pz888/GGGMefPBBExsba5YvX242btxofvOb35hmzZqdd8zVq1cbl8tlJk2aZLZs2WKefPJJ4+/vb/75z39a8zz77LPG6/WaxYsXm82bN5uOHTuaxMREk5WVVey4//nPf0xQUJB5/PHHzZYtW8z06dONy+Uyn3zySYm3pyT1dunSxUgy48aNs8YIDAw0oaGhZvHixeauu+4yHo/HREdHm9WrV1s9adeunalfv775+uuvzVdffWVq1qxpunfv7rOOkJAQc9ttt5kBAwYYl8tlAgICzKxZs6yehISEGKfTaR577DFz8803m/DwcOPn51ds7z788EPjcrlMWFiY2bRpU7nsicfjMR6PxyxfvtykpaWZuLg4s3v3bp96y1tPfvOb35ixY8ea6tWrG4fDUej3Hxoaatxut+nZs6e5+eabTWRkpHE6ncVu49KlS42fn58JCAgwX3311RXpydSpU43L5TIul8ssXrzYWv7JJ580Xq/XtGvXzkRHR5uUlBQTExNjmjRpYh1LiutJ/vhPP/20ufvuu82tt95qHA6Hufnmmwv97sePH28kmVtuucXExcWZXbt2mQMHDpjc3NxC2/jcc88Zj8djkpOTTWhoqHnmmWfK1D7idDpN69atzYIFC8ygQYOMy+UyDofDvP/++1ZPrrVjSUl6ci0eS+666y6zaNEi8/DDDxs/Pz8TERFhRo4cafv95FJzw/l6YowxO3fuNK+99pr57rvvzO7du82SJUtMpUqVrJ4YY8zs2bNNWFiYOXDggPVz8ODBYveTkmaYgi46sDVp0sQMGjTIepybm2tiYmLMxIkTzfHjx42/v7955513rOe3bt1qJJm1a9cWO2bXrl3Nrbfe6jOtadOmZsCAAcYYY/Ly8kx0dLSZPHmy9fzx48dNQECAeeONN4odd/jw4SYpKcln2t13323S0tJKtD0lrbdJkyamcuXKVr1nz541TqfTtG/f3urJ3LlzrXrzeyLJbNiwwRrn448/Ng6Hw/z000+ma9eu5vrrrzcVKlQw2dnZVk8aNGhg6tSpY/XkhhtusGrJ70nNmjWL7d3w4cNNvXr1fHpX3nrStWtX4/V6fXpy7n5S3npy7jp69eplKlSoUOj336pVK+tvIb8nKSkpxW5j/t/Oudt4uXuSv3z+33r+8iEhIWbcuHHWsSS/3ilTphhJ5o033ii2Jx06dCh0LKlYsaJJSEjw6cfkyZPNihUrjCSze/fuYo8l+TXm9+PcbSyr+4gxv/zdxMbGmj59+lyzx5KS9ORaPpbk9yQ5Odm0aNHC9vtJfr0Xkxu2bNly3p4U57HHHjMtWrSwHs+ePdvaT4pyqRmmoIu6JHrmzBl98803atOmjTXN6XSqTZs2Wrt2rb755hvl5OT4PF+3bl3FxcVp7dq11rSEhASNGTPGerx27VqfZSQpLS3NWmbXrl06ePCgzzxer1dNmzb1GbdVq1bq3bt3ice90PYU59xx88dITU21ltmzZ4/y8vKUmZlp9aRjx45WvXXr1lVERIQCAwPVuHFjqydr1qyR0+nUunXrtHbtWgUGBqply5Zyu91W7RkZGdq2bZu+++47HTx4UD///LNVS35PIiIirFpSUlJ8erd27Vq1bdvWp3flrSdJSUk6efKk4uPjdf311yskJEQffPCBVWt560nBfbxSpUqF/nbS09ML7SfBwcHWfKmpqdqwYYNPT9q0aeOzjZezJ+cunz+u0+lU06ZNdfLkSVWuXNk6luTXu3fvXsXFxWnx4sUKDw9X48aNrWNJmzZt5HQ6i+xH1apVdfToUZ9+nDtPamqq8vLyNHz4cK1evVrSL8eS++67z6oxf9xzt7Es7yNpaWk6cuSIIiIirJ5ca8eSkvTkWj+W3HTTTdq+fbtSU1NtvZ+c+zu8mNywdu1a61iSL//vfN26dUWud8eOHfrkk0+UmprqMz1/P4mNjVWnTp30/fffW8+VNMNcyEUFtv/+97/Kzc1V5cqVfaZXrlxZBw8e1MGDB+V2uxUeHl7k8/lq1KihihUrWo8PHjxY7Jj5z+dPO9+4cXFxqlKlygXHzcjIUFZW1gW3pzjnjps/RmxsbKF6MzIyfHpy7rgej0cej8enJ5UqVVJERITVy9OnT/vUVrlyZaWnp0uStm7dKkk6cuRIoXnOnj1rradChQo+vcuv/dxayltPGjZsqNdee01LlizR/Pnz5Xa79dZbb+nHH38slz0pWFdAQEChdRw/frxQ37Kzs61tjIqKkjHmqvXk3OULbq8k5eTk+BxL8uepXLmy9u/fr0qVKln9qFixovz8/BQREaFjx44VqikwMFDZ2dk+/ahcubKqVKmimTNn6m9/+5t++9vfyuVyqVWrVvr2228VFxcnr9dr1Xhun899XFb3kR9//FGZmZnq06ePNc61diwpSU+u1WNJs2bNFBgYqJdeeklOp1Pjxo2z9X5S1DIlyQ0HDx60jiX58o8lBded35NatWrpt7/9rcaNG2c9V6dOHZ/9JC8vT82aNbP2k5JmmAsplbtEly9frsGDB1/2cV9//XVNnDjxso97NVypnowaNeqyj3m1XGpPGjdurPvuu08NGjRQamqqmjVrpoCAAM2aNUvStdmTC3nxxRcv+5hXw6/pR506dTRgwAA1atRIkZGRatKkiZo1a6Y//elPev311zVy5MjLXO3VcaGerFixQvPmzVNYWJiSkpJKPG55/rsprifX6rHkrbfe0rfffqs+ffooOztbU6ZMKfG4Zbkn55Pfk4ULF+rDDz/06UlKSorPfrJo0SJFRUVZ+8nlclGBrWLFinK5XIXu+vz5558VHR2t6OhonTlzRsePHy/y+eJER0cXO2b+8/nTLse4YWFh8ng8F9yekoybP8a+ffsK1RsWFubTk3PHzcrKUlZWls+4Z8+e1dGjR61eBgYG+tT2888/y+v1SpLq1asnSYqMjCw0j5+fX7G9y6/93FrKW08K1n748GFVqVJFO3bsKJc9KVhXdnZ2oXWEh4cX6ltAQECx23ile3Lu8gW3V5L8/f19jiX58/z888+KiYnRoUOHiuxJhQoVCtV0+vRp6wukL3QsadKkibWfnFvjuX0+93FZ20e++OILdejQQW3btlVCQoLPOq61Y0lJenKtHktiY2N13XXXKTY2VlWrVtWYMWMUFRUlyZ77SVHLlCQ3REdHF3ssKbju/J50795dzz77rMaMGaPc3Nwia/P391fDhg2L3U9Kuo0FXVRgc7vdatSokZYvX25Ny8vL0/Lly5WSkqJGjRrJ39/f5/lt27Zp7969hT5q4FwpKSk+y0jSsmXLrGUSExMVHR3tM09GRobWrVv3q8a90PaUZNz8Mb788ktrmfj4eDmdTgUHB1s9ef/99616t23bpqNHj+r06dP65ptvrHE///xz5eXlqWnTpkpJSdHp06f15ZdfWrcPL1u2TF6vV3Xq1FGDBg2sP7L8WvJ7cuzYsWJ7l5KSomXLlvn0rrz1pKj95NSpU9bl8vLWk4L7+KFDhwr9/r1eb6H9JDMzs9htzB/33G28nD05d/n8cfPy8rR+/XqFhITo0KFD1rEkv974+Hjt3btXnTt31vHjx4vsSVH92L9/vyIiInz6Udyx5LvvvrP2k3NrzB/33G0sa/vIypUrdeutt+q5557T0aNHC+0j19qxpCQ9udaPJcuWLVPNmjWVk5Oj+Ph42+4n59Z7MbkhJSWl2GNJ06ZNi113Xl6ecnJylJeXV+Tzubm5+uc//1nsflJULSVS4tsT/s+bb75pAgICzJw5c8yWLVtM//79TXh4uHUL64MPPmji4uLM559/bjZu3GhSUlJMSkqKzxi33HKLmT59uvV49erVxs/Pz0yZMsVs3brVPPXUU0XenhseHm6WLFli/vGPf5hOnToVuiW2Z8+eZsSIEdbj/I/1GDZsmNm6dat5+eWXi7yd+HzbU9S4Beu94447jCTz9NNPW2MEBgaasLAws2TJkkK3WOf3pF27dqZhw4Zm3bp1plGjRiYqKsrnFms/Pz8TEhJiOnbsaB566CHjcrlMYGCgz0dYhIaGGqfTaf7whz+Y1q1bF7rFumfPnqZVq1ZW7z766CPjcrmM1+s13333XbnsSWBgoBkzZoz56KOPTGpqqgkODjYBAQHm+++/L7c9GTZsmFm0aJGpXbu2cTgc5p133jGbNm2yehIWFmbcbrfp3bu3ad26daGP9ejZs6fp1KmTtY2ffvqpz8d6XImenPuxHkuWLLGW/+Mf/2jCw8NNu3btTJUqVUyzZs1MTEyMadq0qXUsye9J48aNzWOPPWZq1aplfaxH/vjvv/++GTBggHE4HKZx48Zm06ZNZtOmTdaxpG/fvmbatGmmTZs2pmrVqmbQoEHG6XSazz77zKo7fxsnT55sPB6PueGGG0xoaKiZOHFimdpHXC6X8ff3N/379zd/+MMfjL+/v1mxYoU5cuTINXssKUlPrrVjicvlMvfee6/54IMPzJAhQ4zL5TJRUVGmR48ett9PLjU3nNuTVatWWceSfPPnzzdvvfWW2bJli9m5c6d56623TExMjNUTY4wZO3asWbp0qdm5c6f55ptvTLdu3UxgYKC1n5S0lgu56MBmjDHTp083cXFxxu12myZNmpivv/7aei4rK8sMHDjQVKhQwQQFBZkuXbqYAwcO+CwfHx9vnnrqKZ9pb7/9tqldu7Zxu90mKSnJfPjhhz7P5+XlmVGjRpnKlSubgIAA07p1a7Nt2zafeVJTU02vXr18pq1YscI0aNDAuN1uU716dTN79uyL2p7ixi1Yb35QzR9j7dq1Vr1ut9tUrVrVeL1en54cOXLEdO/e3YSEhBiHw2EaNGhgTpw44bOO+Ph443A4jMPhMJGRkebZZ58t1BOv12vNU7NmTZ/e5dd+bu9uvPFGU69evXLbk6ZNmxqn02kkGbfbbVq2bGm+/fbbct0TPz8/67b9c3/O3U8qVKhg9a1atWo+25hf+7nbWLduXav2K9WT6OhoExUV5bN8fr2VKlUyTqfT+Pn5GY/H43Msye+Jw+Ewbrfb9OnTx+pJ/vhF9UOSNX5+P51Op/F6vaZVq1bm888/L1R3/jb6+fmZoKAg4+/vX+b2kdTU1CJ7kZqa6rOPXEvHkpL05Fo7ljz66KMmICDASDIOh8PExsaaZ555xgoVdt9PLiU3nNuTsLAwn2OJMb+EyRtvvNGEhISY4OBgc9111/n0JL9v+bVXrlzZ/P73v/fZT0pay4U4jDGm5OfjAAAAcLXxXaIAAAA2R2ADAACwOQIbAACAzRHYAAAAbI7ABgAAYHMENgAAAJsjsAEAANgcgQ0AAMDmCGwAAAA2R2ADAACwOQIbAACAzf1/GIBdOTX+oQUAAAAASUVORK5CYII=", + "image/png": "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", "text/plain": [ - "
" + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax1 = plt.subplots(figsize=(12, 6))\n", + "\n", + "# Plot temperature on the primary axis\n", + "mqt_13.setpoints[\"setpoint_temperature\"].plot(ax=ax1, color=\"blue\", label=\"Temperature\")\n", + "ax1.set_xlabel(\"Time\")\n", + "ax1.set_ylabel(\"Temperature (°C)\", color=\"blue\")\n", + "ax1.tick_params(axis=\"y\", labelcolor=\"blue\")\n", + "ax1.legend(loc=\"upper left\")\n", + "\n", + "# Create a twin axis for voltage\n", + "ax2 = ax1.twinx()\n", + "mqt_13.setpoints[\"setpoint_relative_humidity\"].plot(ax=ax2, color=\"red\", label=\"Relative Humidity\")\n", + "ax2.set_ylabel(\"Rh (%)\", color=\"red\")\n", + "ax2.tick_params(axis=\"y\", labelcolor=\"red\")\n", + "ax2.legend(loc=\"upper right\")\n", + "\n", + "plt.title(\"Chamber Setpoints: Temperature and RH\")\n", + "plt.figtext(0.45, 0.01, \"85, 85, for 1000h\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## DH+UV - IEC 63556\n", + "\n", + "200 W/m2, UV40 kWh/m2 \n", + "IEC61215-2, DH200h, 85℃/85%RH, 200h (MQT13 twice for 2000 hours total)\n", + "\n", + "UV irradiation of 200W/m2 applied during 85℃ " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" ] }, "metadata": {}, @@ -137,46 +421,209 @@ } ], "source": [ - "mqt_13.plot_setpoints()" + "path = os.path.join(pvdeg.CHAMBER_DIR, \"IEC-61215-MQT-13.csv\")\n", + "\n", + "dh_uv = pvdeg.Chamber(\n", + " fp=path,\n", + " setpoint_names=[\"temperature\", \"relative_humidity\"],\n", + " skiprows=[1],\n", + ")\n", + "\n", + "# apply irradiance at 85 C\n", + "dh_uv.setpoints[\"setpoint_irradiance_full\"] = dh_uv.setpoints[\"setpoint_temperature\"].apply(lambda x: 1600 if x == 85 else 0)\n", + "\n", + "dh_uv.plot_setpoints()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Thermal Cycling including UV - TC + UV - IEC 63556\n", + "## TC+UV - IEC 63556\n", "\n", "IEC 61215-2 MQT 11 combined with IEC 61215-2 MQT 10. This just has the temperature setpoints of MQT 11 with the irradiance turned on at 1600 $\\frac{w}{m^2}$ when the temperature is above $0 \\degree C$. The times the irradiance is turned on are shown in yellow on the plot below.\n", "\n", - "*WHAT HAPPENS WITH RH HERE, WE CANT CALCULATE because no RH SETPOINTS IN THE CHAMBER*" + "this is full spectrum, not uv, this is a stand in and partially representative of the 200 W/m^2 on 280-400 nm. " ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "path = os.path.join(pvdeg.CHAMBER_DIR, \"IEC-61215-MQT-11.csv\")\n", "\n", - "processing = pvdeg.Chamber(\n", + "tc_uv = pvdeg.Chamber(\n", " fp=path,\n", " setpoint_names=[\"temperature\"],\n", " skiprows=[1],\n", ")\n", "\n", - "processing.setpoints[\"setpoint_irradiance_full\"] = processing.setpoints[\"setpoint_temperature\"].apply(lambda x: 1600 if x > 0 else 0)\n", - "processing.setpoints[\"setpoint_relative_humidity\"] = \n" + "tc_uv.setpoints[\"setpoint_irradiance_full\"] = tc_uv .setpoints[\"setpoint_temperature\"].apply(lambda x: 1600 if x > 0 else 0)\n", + "# processing.setpoints[\"setpoint_relative_humidity\"] = 0.3" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + "

Chamber Simulation

\n", + "\n", + "
\n", + "

\n", + " \n", + " Setpoints Dataframe\n", + "

\n", + "
\n", + "
\n", + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
setpoint_temperaturesetpoint_irradiance_full
0 days 00:00:0025.01600
0 days 00:01:0025.01600
0 days 00:02:0023.8983051600
0 days 00:03:0022.796611600
0 days 00:04:0021.6949151600
.........
0 days 05:26:0027.1052631600
0 days 05:27:0026.0526321600
0 days 05:28:0025.01600
0 days 05:29:0025.01600
0 days 05:30:0025.01600
\n", + "

331 rows × 2 columns

\n", + "
\n", + "
\n", + "\n", + "
\n", + "

\n", + " \n", + " Setpoints Plot\n", + "

\n", + "
\n", + "
\n", + "

Setpoints Plot

\n", + " \"Setpoints\n", + "
\n", + "\n", + "
\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "tc_uv" ] }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAioAAAGdCAYAAAA8F1jjAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAABQ70lEQVR4nO3deXxTZb4/8E/27umetNBCy9KWTRBHxIVBZVhkHB2948bMFa8XHQd+M4iKogLKeEUcx/U6bndE546Keq/oVRFFNjdARZGtLRTK3nRv0zVJk+f3R3pOG9pClyTnJPm8X6++XpCcnn5zkibfPs/z/T4aIYQAERERkQpplQ6AiIiIqCdMVIiIiEi1mKgQERGRajFRISIiItViokJERESqxUSFiIiIVIuJChEREakWExUiIiJSLb3SAQyUx+PBqVOnEB8fD41Go3Q4RERE1AtCCDQ0NCAzMxNabc/jJiGfqJw6dQpZWVlKh0FERET9cPz4cQwePLjH+0M+UYmPjwfgfaAJCQl+PHM9gP8GsB1Amx/PKzEAmATgdwDMATg/BU93rxUXgBoAyfA+16EoHB4DwMfRF3xfouCx2+3IysqSP8d7EvKJijTdk5CQ4OdERQCIgvcXNxBTSob28ye0f1Ho6um1ooP3VyyUPxzD4TEAfBy9xfclCr6zLdvgYloiIiJSLSYqREREpFpMVIiIiEi1Qn6NChERKUcIgba2NrjdbqVDIZXR6XTQ6/UDbh3CRIWIiPrF6XSirKwMzc3NSodCKhUTE4OMjAwYjcZ+n4OJChER9ZnH40FpaSl0Oh0yMzNhNBrZdJNkQgg4nU5UVlaitLQUI0aMOGNTtzNhokJERH3mdDrh8XiQlZWFmJgYpcMhFYqOjobBYMDRo0fhdDoRFRXVr/NwMS0REfVbf/9Kpsjgj9cHX2FERESkWkxUiIiISLWYqBARUUSZOnUqFi5cqHQYAffQQw9h/PjxSocxYExUiIiIQojT6Qzqz5N65SiFVT9EYc7jAV79eixO1sX19TsBtMC7SZ3O/4EFjfKPQwNgxuhSTMq1KfLzqcPcuXOxdetWbN26Fc888wwAoLS0FI2Njbjnnnvw5ZdfIjY2FtOnT8dTTz2F1NRUAN5RmLFjx0Kn0+H111+H0WjEI488gptuugkLFizA//zP/8BiseC5557DrFmzAABbtmzBpZdeio8++ghLlizBgQMHMH78ePzXf/0XxowZI8f01VdfYcmSJfj++++RmpqKX//611i5ciViY2MBAEOHDsWtt96KgwcP4v3338c111yD1157Dffeey/Wrl2LEydOwGq1Ys6cOVi2bBkMBgNee+01PPzwwwA6Nv1bvXo1pk6dipycHPz444/yaEtdXR2SkpKwefNmTJ06VY573bp1ePDBB7Fnzx589tlnmDJlClatWoWXX34ZNpsNI0eOxNKlS/Ev//IvAX3OmKgQhbmvSgbhkY8nKx1GxFu/NwffLHlT6TACSgiBFpcyHWqjDbpe9XF55plncODAAYwZMwYrVqwAABgMBpx//vn493//dzz11FNoaWnBvffei+uuuw6bNm2Sv/f111/H4sWL8e233+Ltt9/GHXfcgbVr1+LXv/417r//fjz11FP43e9+h2PHjvmUbN9zzz145plnYLVacf/99+PKK6/EgQMHYDAYcOjQIcycOROPPPIIXn31VVRWVmLBggVYsGABVq9eLZ/jiSeewLJly7B8+XL5tvj4eLz22mvIzMzEnj17MG/ePMTHx2Px4sW4/vrrsXfvXqxfvx6ff/45AMBsNqO8vLzX1/S+++7DE088gdzcXCQlJWHlypX45z//iRdffBEjRozAF198gd/+9rdIS0vDz3/+816ft6+YqBCFuT0n0wAAozKqcGn+8T58pxvekYhohPaIirKPQwjgha3jcao+DtWNUUiJaw16DMHS4nJj1LJPFfnZ+1fMQIzx7B9pZrMZRqMRMTExsFqtAIBHHnkEEyZMwKOPPiof9+qrryIrKwsHDhzAyJEjAQDnnHMOHnzwQQDAkiVL8NhjjyE1NRXz5s0DACxbtgwvvPACdu/ejQsuuEA+1/Lly/GLX/wCgDfZGTx4MNauXYvrrrsOK1euxJw5c+Q1MyNGjMCzzz6Ln//853jhhRfk3iOXXXYZ7rrrLp/HIsUCeEdd7r77bqxZswaLFy9GdHQ04uLioNfr5cfZVytWrJDjdjgcePTRR/H5559j8mTvHz65ubn46quv8NJLLzFRIaL+K7IlAwCuPOcQ7pj6Ux++0wWgCkAKgP63v1ae8o9j3Z5cHKk2o8iWjIuGn1IkBurZTz/9hM2bNyMuruv06KFDh+REZdy4cfLtOp0OKSkpGDt2rHybxWIBAFRUVPicQ/pgB4Dk5GTk5eWhsLBQ/tm7d+/GG2+8IR8jhJA7/xYUFAAAzjvvvC6xvf3223j22Wdx6NAhNDY2oq2tDQkJCX1+/D3p/DNLSkrQ3NwsJy4Sp9OJCRMm+O1ndoeJClGYKyrzJir5GTUKRxK58q01OFJtRmFZSlgnKtEGHfavmKHYz+6vxsZGXHnllVi1alWX+zIyMuR/GwwGn/s0Go3PbdLUk8fj6dPPvv322/HHP/6xy33Z2dnyv6X1KpJt27Zhzpw5ePjhhzFjxgyYzWasWbMGf/3rX8/486QGbEII+TaXy9XtsZ1/ZmNjIwDg448/xqBBg3yOM5lMZ/yZA8VEhSiMtbp0OFyVCAAosFYrG0wEy8+oxvp9OfLoVrjSaDS9mn5RmtFo9Nnt+dxzz8X//u//YujQodDr/R//9u3b5aSjtrYWBw4ckEdKzj33XOzfvx/Dhw/v0zm/+eYbDBkyBA888IB829GjR32OOf1xAkBamncquKysTB4J2bVr11l/3qhRo2AymXDs2LGATvN0h+XJRGGspCIRbo8WSTGtsCRwh1ulFGR4k8TCshSFIyHAu55jx44dOHLkCKqqqjB//nzU1NTgxhtvxHfffYdDhw7h008/xS233NLlg74/VqxYgY0bN2Lv3r2YO3cuUlNTcfXVVwMA7r33XnzzzTdYsGABdu3ahYMHD+KDDz7AggULznjOESNG4NixY1izZg0OHTqEZ599FmvXru3yOEtLS7Fr1y5UVVXB4XAgOjoaF1xwAR577DEUFhZi69atPmtdehIfH4+7774bd955J15//XUcOnQIP/zwA5577jm8/vrr/b42vcFEhSiMSR+M+dZqcGNb5RRYvdNuB8uT0ObmE6G0u+++GzqdDqNGjUJaWhqcTie+/vpruN1uTJ8+HWPHjsXChQuRmJjol71qHnvsMfzpT3/CxIkTYbPZ8OGHH8Jo9K6XGjduHLZu3YoDBw7gkksuwYQJE7Bs2TJkZmae8Zy/+tWvcOedd2LBggUYP348vvnmGyxdutTnmGuvvRYzZ87EpZdeirS0NLz11lsAvAuF29raMHHiRCxcuBCPPPJIrx7Hn//8ZyxduhQrV65EQUEBZs6ciY8//hg5OTn9uCq9pxGdJ6pCkN1uh9lsRn19vV8XEQH1AP4O4GsAgWh0YwBwIYBbAZgDcH4Knu5eK8ov4ASAP390Af7+1TjcctEeLL9yWx+/Wx2PYeCUfxweDzD2oblochqx4c53MMJS14+zBONx9P59qbW1FaWlpcjJyen3rrjhTupHUltbi8TERKXDUcSZXie9/fzmiApRGJNGVKSpB1KGVtuxmHk/p3+I+oSJClGYEqJTomJlxY/S8tufg3BfUEvkbwFNVNxuN5YuXYqcnBxER0dj2LBh+POf/+xTFiWEwLJly5CRkYHo6GhMmzYNBw8eDGRYRBGhsiEatc1R0Go8GGGpVTqciJffPqpVxBGViDF16lQIISJ22sdfApqorFq1Ci+88AL+8z//E4WFhVi1ahUef/xxPPfcc/Ixjz/+OJ599lm8+OKL2LFjB2JjYzFjxgy0toZv90aiYJCmGHJS6xFlUKatOXWQRrUKyziiQtQXAS14/+abb3DVVVdh9uzZALylUm+99Ra+/fZbAN7RlKeffhoPPvggrrrqKgDAP/7xD1gsFrz//vu44YYbAhkeUVgrsknrUzjtowZ57YmKzR6H2iYTkmIdCkdEFBoCOqJy4YUXYuPGjThw4AAAb6vgr776St5ZsrS0FDabDdOmTZO/x2w2Y9KkSdi2rfsKBYfDAbvd7vNFRF1JHWm5kFYd4qNcyEr2vl+F0zqVEC8cpQDzx+sjoInKfffdhxtuuAH5+fkwGAyYMGECFi5ciDlz5gAAbDbvlufS/ggSi8Ui33e6lStXwmw2y19ZWVmBfAhEIUv6MMznQlrVyJenf0J/nYrUOr65mY0EqWfS6+P07Qf6IqBTP++88w7eeOMNvPnmmxg9ejR27dqFhQsXIjMzEzfffHO/zrlkyRIsWrRI/r/dbmeyQnQaR5sWJRVJADiioiYFGdXYsH9oWIyo6HQ6JCYmyhvwxcTEyHvdEAkh0NzcjIqKCiQmJkKn6/9eTAFNVO655x55VAUAxo4di6NHj2LlypW4+eab5a2ny8vLfTZ+Ki8vx/jx47s9p8lkCvgGSESh7lBFIto8WiREOZBhblI6HGpXEGYlytJ7+Om7BRNJEhMT5ddJfwU0UWlubu7Sflin08k7S+bk5MBqtWLjxo1yYmK327Fjxw7ccccdgQyNKKxJC2nzM9g6X02kEuViWzLcHg102tBe36HRaJCRkYH09PQed+ClyGUwGAY0kiIJaKJy5ZVX4j/+4z+QnZ2N0aNH48cff8STTz6Jf/u3fwPgfZFL+wyMGDECOTk5WLp0KTIzM+UNm4io76QS2FGs+FGVIcl2RBtcaHEZUFqVgOHp9UqH5Bc6nc4vH0hE3QloovLcc89h6dKl+MMf/oCKigpkZmbi9ttvx7Jly+RjFi9ejKamJtx2222oq6vDxRdfjPXr13PvCKIBkEdUrFyfoiZarbdMeddxC4psKWGTqBAFUkATlfj4eDz99NN4+umnezxGo9FgxYoVWLFiRSBDIYoo0ohKPkdUVKcgoz1RKUvGL8cdVjocItXjXj9EYaayIRpVjTHQaARGsnW+6khVWOFQokwUDExUiMKMVFGSk1KPGGObwtHQ6bg5IVHfMFEhCjNFnPZRNamV/sm6eNS3GBWOhkj9mKgQhZlCLqRVNXO0E4MSGwB0JJVE1DMmKkRhplDe44cjKmolPTdSdRYR9YyJClEYcbk1cut8jqiol/TccJ0K0dkxUSEKI4crE+Fy6xBvcmJwUqPS4VAPpPVDhZz6ITorJipEYUQqeWXrfHUrOK2VPhH1jIkKURgpbJ9KkEpgSZ2Gpthh0rehxWXAsZp4pcMhUjUmKkRhhKXJoUGnFXKZchEbvxGdERMVojAiTf1IUwukXgVWrlMh6g0mKkRhoroxChUNsQCAPAtHVNQuX2qlzxJlojNiokIUJorb16cMSalHrImt89WOrfSJeoeJClGY2C9V/HAhbUiQmr4dr0lAQ6tB4WiI1IuJClGYkP4y5/qU0JAY40CG2dvrppijKkQ9YqJCFCaKWJoccqTnqpCJClGPmKgQhYE2twYHyr2t8zmiEjrkBbUsUSbqERMVojBQWmWGs02PWKMTWUkNSodDvSRvTsgSZaIeMVEhCgNSiWuetQZa/laHjAJrRyt9j0fhYIhUim9pRGGAHWlDU05qPYz6NjQ5jThRy1b6RN1hokIUBtiRNjTpdQIjLbUAOsrLicgXExWiMCCXJrPiJ+Sw8RvRmTFRIQpxdc0mlNXHAQBGMlEJOfncnJDojJioEIU4aVO7wUl2JES5FI6G+mqUvOcPR1SIusNEhSjEdXSk5WhKKMprH1E5Wm1Gk0OvcDRE6sNEhSjESVMGUqkrhZaUuFakxzcBAIrLOapCdDomKkQhTm6dzxGVkCU9d+xQS9QVExWiEOb2aOS/wlmaHLqk544daom6YqJCFMKOVCeg1aVHtMGF7GS2zg9VBSxRJuoRExWiECb9BT7SWgudVigcDfVXvjyikgLBp5HIBxMVohAmrWkYxWmfkDYsrQ4GnRsNDiNO1MYpHQ6RqjBRIQphRe2bEeaz0VtIM+gEhqd7W+lLzykReTFRIQphUrO3fJYmhzx5nQoX1BL5YKJCFKLqW4w4WefdcZcjKqGvQO5QyxEVos6YqBCFqOL2CpFBiQ0wxzgVjoYGSuqlwhEVIl9MVIhClNzojaMpYUF6HkurzWhx6hSOhkg9mKgQhSip4ocdacNDWnwLUuOaIYSGrfSJOmGiQhSipIW07EgbPgo4/UPUBRMVohDk8XSsUWHFT/iQnkuWKBN1YKJCFIKO1SSgxWWASd+GoSl2pcMhP5HWqezniAqRjIkKUQiS1qfkWWug17HnergoYCt9oi6YqBCFoEJW/ISlYel10Gs9sLeaUFYfq3Q4RKrARIUoBBWVMVEJRya9B8PS6gBwJ2UiScATlZMnT+K3v/0tUlJSEB0djbFjx+L777+X7xdCYNmyZcjIyEB0dDSmTZuGgwcPBjosopAmdS/NZ8VP2JE71JZxQS0REOBEpba2FhdddBEMBgM++eQT7N+/H3/961+RlJQkH/P444/j2WefxYsvvogdO3YgNjYWM2bMQGtrayBDIwpZDa0GHK9JANCxPwyFD6kvDhMVIi99IE++atUqZGVlYfXq1fJtOTk58r+FEHj66afx4IMP4qqrrgIA/OMf/4DFYsH777+PG264IZDhEYWkA+3NwKwJjUiKdSgcDflbR4kyp36IgACPqPzf//0fzjvvPPzmN79Beno6JkyYgFdeeUW+v7S0FDabDdOmTZNvM5vNmDRpErZt29btOR0OB+x2u88XUSSRd0xmR9qwNKp96udwpRmtLrbSJwpoonL48GG88MILGDFiBD799FPccccd+OMf/4jXX38dAGCz2QAAFovF5/ssFot83+lWrlwJs9ksf2VlZQXyIRCpjjQlwI604SktvgXJsS3wCC0Olied/RuIwlxAExWPx4Nzzz0Xjz76KCZMmIDbbrsN8+bNw4svvtjvcy5ZsgT19fXy1/Hjx/0YMZH6cTPC8KbRdDy3hZz+IQpsopKRkYFRo0b53FZQUIBjx44BAKxWKwCgvLzc55jy8nL5vtOZTCYkJCT4fBFFis6t8ws49RO2WPlD1CGgicpFF12E4uJin9sOHDiAIUOGAPAurLVardi4caN8v91ux44dOzB58uRAhkYUkk7UxqPRYYRR50Zuap3S4VCASCMq3JyQKMBVP3feeScuvPBCPProo7juuuvw7bff4uWXX8bLL78MANBoNFi4cCEeeeQRjBgxAjk5OVi6dCkyMzNx9dVXBzI0opAkTQWMsNSydX4Yk1vp27yt9DUahQMiUlBAE5Wf/exnWLt2LZYsWYIVK1YgJycHTz/9NObMmSMfs3jxYjQ1NeG2225DXV0dLr74Yqxfvx5RUVGBDI0oJBW1TwVwx+TwNjy9DjqtB7XNUSi3x8BqblY6JCLFBDRRAYBf/vKX+OUvf9nj/RqNBitWrMCKFSsCHQpRyOuo+OH6lHAWZfBO7R2sSEahLYWJCkU07vVDFEKK5IW0HFEJd1KfHK5ToUjHRIUoRDQ59Dja3jqfpcnhT15QyxJlinBMVIhCRHF5MoTQIC2+GSlx3Asr3I1iiTIRACYqRCFDmgLgtE9kkKZ+DlUmwtHGt2qKXHz1E4WIIlv7QlpO+0QEa0ITzNGtcHu0KKlgK32KXExUiEJEkbwZIUdUIoFG01HdVcgFtRTBmKgQhQAhOpq9ceonckj9coq4ToUiGBMVohBwsi4ODa0mGHRu5KbWKx0OBYk0osLKH4pkTFSIQoA07TMsrQ5GvUfhaChY5F2Uy7yt9IkiERMVohAglaiO4rRPRBlpqYFW40F1UzQqG2OUDodIEUxUiEKANPSfz9b5ESXa6MbQVDsArlOhyMVEhSgEFNq4GWGkKrBKjd9SFY6ESBlMVIhUrsWpw5Gq9tb5HFGJOB0LajmiQpGJiQqRyh0oT4ZHaJEa14z0+Balw6Egy7eylT5FNiYqRConr09hR9qI1NFKPwlOttKnCMRXPZHKSV1JmahEpkGJjYiPcsDl1uFQJdepUORhokKkctKQPzvSRiaNpmN/pyKbReFoiIKPiQqRignB0mTqeO6LypioUORhokKkYjZ7LOpboqDXejA8vVbpcEgh0mjafiYqFIGYqBCpWGGn1vkmts6PWPLmhJz6oQjERIVIxaT1KflcnxLRRlpqodEIVDbEo6oxWulwiIKKiQqRirE0mQAg1tSGIcneXbPZSp8iDRMVIhXrGFFhohLpCjKqAABFNpYoU2RhokKkUq0uHQ5XmgFw12Rih1qKXExUiFSqpCIRHqFFUkwr0uOblQ6HFCatU+KePxRpmKgQqZQ87WOthkajcDCkuFHtUz8Hy1PgcvMFQZGDiQqRSnV0pOX6FAIGJTYgzuSA061DaVWi0uEQBQ0TFSKV6uhIy/UpBGi1QJ61HEBHfx2iSMBEhUiFhOg0osLSZGpXkCElKlynQpGDiQqRClU0xKC2OQpajQcjLGydT1757SMq0mgbUSRgokKkQtLQfm5aPaIMboWjIbWQRlSKOPVDEYSJCpEKSSWo7EhLneVZKwAANnscaptMCkdDFBxMVIhUSBpRKeBCWuokzuREdnsr/UJO/1CEYKJCpEJFcmkyExXylW9tb6XPBbUUIZioEKmMo02LQ5WJADj1Q11J5eqs/KFIwUSFSGVKKpLQ5tEiIcqBDHOT0uGQyoySNyfk1A9FBiYqRCpT1Gl9Clvn0+mkzQkPlCehja30KQIwUSFSGekvZbbOp+5kJ9cjxuiCo02PI9UJSodDFHBMVIhUpqM0mQtpqStvK31vEst1KhQJmKgQqUxHaTJHVKh70iJrKaklCmdMVIhUpLIhGlWNMdBoBEZamKhQ96SydXaopUjARIVIRaT1KTkp9Yg2snU+da+AJcoUQYKWqDz22GPQaDRYuHChfFtrayvmz5+PlJQUxMXF4dprr0V5eXmwQiJSnUI2eqNekNaonKqPQ32zUeFoiAIrKInKd999h5deegnjxo3zuf3OO+/Ehx9+iHfffRdbt27FqVOncM011wQjJCJVkoby2eiNziQhyoVBiQ0A2E+Fwl/AE5XGxkbMmTMHr7zyCpKSkuTb6+vr8fe//x1PPvkkLrvsMkycOBGrV6/GN998g+3btwc6LCJVkvZvyedCWjoLabE1p38o3AU8UZk/fz5mz56NadOm+dy+c+dOuFwun9vz8/ORnZ2Nbdu29Xg+h8MBu93u80UUDpxtWpRUeJN5libT2cgLajmiQmFOH8iTr1mzBj/88AO+++67LvfZbDYYjUYkJib63G6xWGCz2Xo858qVK/Hwww/7O1QixR2uMsPl1iHe5MTgpEalwyGVk5LZQpYoU5gL2IjK8ePH8ac//QlvvPEGoqKi/HbeJUuWoL6+Xv46fvy4385NpCRpN9x8ts6nXpCmBw/YkuD28AVD4StgicrOnTtRUVGBc889F3q9Hnq9Hlu3bsWzzz4LvV4Pi8UCp9OJuro6n+8rLy+H1Wrt8bwmkwkJCQk+X0ThQF6fwoW01AtDU+yIMrShxWXAUbbSpzAWsETl8ssvx549e7Br1y7567zzzsOcOXPkfxsMBmzcuFH+nuLiYhw7dgyTJ08OVFhEqsXSZOoLnVYgzyJ1qOU6FQpfAVujEh8fjzFjxvjcFhsbi5SUFPn2W2+9FYsWLUJycjISEhLw//7f/8PkyZNxwQUXBCosItWSS5NZ8UO9lG+twU8n0lFUlowrxpYqHQ5RQAR0Me3ZPPXUU9Bqtbj22mvhcDgwY8YM/O1vf1MyJCJFVDdGoaIhFhpNx1/JRGcjjb7tZ4kyhbGgJipbtmzx+X9UVBSef/55PP/888EMg0h1pKH7Icl2xJraFI6GQoU0+sapHwpn3OuHSAWk9SlcSEt9UdBeonyiNgH2VoPC0RAFBhMVIhUokjvSciEt9Z45xolMs7fnTjFHVShMMVEhUgGOqFB/ScltEdepUJhiokKksDa3BgfLva3zR3FEhfpISm4LOaJCYYqJCpHCSqvMcLp1iDU6MTipQelwKMTkc3NCCnNMVIgUJu3VkmetgZa/kdRH0ihcsS0ZHo/CwRAFAN8WiRRW2N7orYCN3qgfhqbUw6hvQ7PTgOO18UqHQ+R3TFSIFNZ5M0KivtLrBEZaagFw+ofCExMVIoVJpckFrPihfpJeO0xUKBwxUSFSUF2zCWX1cQC8a1SI+kMuUWblD4UhJipECpLWp2Ql2xEf5VI4GgpV0ogKExUKR0xUiBQkd6TlaAoNgDSicrTajEYHW+lTeGGiQqQgaU2BtGcLUX8kxzpgSWgCABTbkhSOhsi/mKgQKUheSMvSZBqgfKu0ToULaim8MFEhUojbo5E3kmNpMg1UgdyhlutUKLwwUSFSyJHqBDja9Ig2uJCdzNb5NDAF3JyQwhQTFSKFSOtT8qw10GmFwtFQqMvvVPkj+HKiMMJEhUghRWydT36Um1YHo86NRocRJ9hKn8IIExUihUiLHlmaTP5g0AkMT5da6XOdCoUPJipECunYjJALack/8jPY+I3CDxMVIgXUtxhxss47PM/W+eQvBSxRpjDERIVIAVJZ8qDEBpijnQpHQ+GCJcoUjpioEClA7kjLhbTkR1I/niPVZjQ79QpHQ+QfTFSIFNCxxw/Xp5D/pMa1IjWuGUJocKCcrfQpPDBRIVKANDSfzxEV8jNpcXYhG79RmGCiQhRkPq3zOaJCfiZNJxZxnQqFCSYqREF2rCYeLS4DTPo25KTalQ6HwozUl6eQJcoUJpioEAVZEVvnUwBJo3SFZSlspU9hgYkKUZAVytM+XJ9C/jc8vQ56rQcNrSacqo9VOhyiAWOiQhRkHaXJXJ9C/mfUe+RW+txJmcIBExWiICviiAoFWOedlIlCHRMVoiBqaDXgeE0CADZ7o8CRRuv2c0SFwgBbF/Zg36lGVDTEIiEqDedml0GjUToiCgdSWXKGuRGJMQ6Fo6Fwlc8SZQojTFR68NLWk/i/nwYDGIxnbtiIq8YfUjokCgNcSEvBIG1OWFplRqtLhyiDW+GIiPqPUz89yEo2yf/+3x9GKhgJhRNpcWM+F9JSAKXFtyAltgUeoWUrfQp5TFR6cM+Modh412EAwDclg1DXbDrLdxCdndw6nyMqFEAaTUcyzMofCnVMVM5gWJoL+dYatHm0+Gz/EKXDoRDn8XSsURnFERUKMHaopXDBROUsZo05AgBYtydX2UAo5J2ojUeT0wijzo2c1Hqlw6Ewx80JKVwwUTmL2eNKAQBflwxCfbNR4WgolEl/2Y6w1EKvY29zCqzOvVTYSp9CGROVsxieXo+Rlhq43DpsKOT0D/UfO9JSMA1Pr4NO60FdcxTK7TFKh0PUb0xUeuGKsd5FtZz+oYGQK364kJaCIMrgRm5qHQBO/1BoY6LSC1eM9U7/fHlwMOpbOP1D/SO1M+eICgWL1P2YC2oplDFR6YWRlloMT6+Fy63DRk7/UD80OfQ42t46nyMqFCwsUaZwENBEZeXKlfjZz36G+Ph4pKen4+qrr0ZxcbHPMa2trZg/fz5SUlIQFxeHa6+9FuXl5YEMq184/UMDUVyeDCE0SI9vQkpcq9LhUIQo4OaEFAYCmqhs3boV8+fPx/bt27Fhwwa4XC5Mnz4dTU1N8jF33nknPvzwQ7z77rvYunUrTp06hWuuuSaQYfXL7PZE5YsDg2FvNSgcDYUaac+VfG5ESEEkTTMeqkxEq0uncDRE/RPQvX7Wr1/v8//XXnsN6enp2LlzJ6ZMmYL6+nr8/e9/x5tvvonLLrsMALB69WoUFBRg+/btuOCCCwIZXp+MtNQiN60OhysTsbFwCH49oUTpkCiEyBU/nPahILIkNCMxphV1zVEoqUjEmEFcH0WhJ6hrVOrrvU2ukpO9f13u3LkTLpcL06ZNk4/Jz89HdnY2tm3b1u05HA4H7Ha7z1cwaDQdoyqc/qG+4kJaUoJG49tPhSgUBS1R8Xg8WLhwIS666CKMGTMGAGCz2WA0GpGYmOhzrMVigc1m6/Y8K1euhNlslr+ysrICHbpMWqey9cBgNHD6h3pJCG5GSMphh1oKdUFLVObPn4+9e/dizZo1AzrPkiVLUF9fL38dP37cTxGeXb61BrmpdXC26bGpKDtoP5dC28m6ODQ4jDDo3Mhl63wKMi6opVAXlERlwYIF+Oijj7B582YMHjxYvt1qtcLpdKKurs7n+PLyclit1m7PZTKZkJCQ4PMVLBoNMKu9p8rHuzn9Q70j/SU7PL0WRr1H4Wgo0uR3GlFhK30KRQFNVIQQWLBgAdauXYtNmzYhJyfH5/6JEyfCYDBg48aN8m3FxcU4duwYJk+eHMjQ+k2a/tlyIAuNDk7/0NlJFT9cSEtKGGmphVbjQU1TNCobopUOh6jPApqozJ8/H//85z/x5ptvIj4+HjabDTabDS0tLQAAs9mMW2+9FYsWLcLmzZuxc+dO3HLLLZg8ebKqKn46G5VRjaEp9Zz+oV6ThtxZmkxKiDJ07NZdaOM6FQo9AU1UXnjhBdTX12Pq1KnIyMiQv95++235mKeeegq//OUvce2112LKlCmwWq147733AhnWgGg0nZq/cfqHeoGbEZLSpCRZGt0jCiUBn/rp7mvu3LnyMVFRUXj++edRU1ODpqYmvPfeez2uT1ELKVHZXJyFJkdAW9FQiGtx6lFabQbA1vmkHGnakZU/FIq4108/jM6sRnayHY42PTYXc/qHenagvXV+alwz0uJblA6HIpQ0msfKHwpFTFT6wWf6h83f6AwKy1IBcDSFlCVV/pRUJMHZxrd9Ci18xfaT1KV2U1E2mp2c/qHuFdm4PoWUl2luQkKUA20eLQ5VJiodDlGfMFHppzGDqjA4yY5Wlx6bi4LXHZdCC0dUSA00Gt9+KkShhIlKP3n3/vE2f1u3l9M/1JUQHSMqLE0mpbFDLYUqJioDIK1T2VSYjRYnt1AnX2X1CahviYJe68Hw9Fqlw6EIJyXLhSxRphDDRGUAxg2uxKDEBrS4DNjC6h86TZHNAgAYllYHE1vnk8K4OSGFKiYqA+BT/bM35yxHU6QpLPMmKtwxmdRgpKUWGo1AVWMMW+lTSGGiMkBSorKxcAhaXZz+oQ5SolLA9SmkAjHGNgxN8bbSL+Y6FQohTFQGaHxWJTLNjWh2GrClmNU/1EGa+sm3ckSF1CHfynUqFHqYqAyQRgPMYvM3Ok2rS4fDlVIPFY6okDrI61S4OSGFECYqftAx/ZPN6R8CABwsT4ZHaJEc24L0+GalwyEC0DGiws0JKZQwUfGDCVkVyDA3oslpxBcHBisdDqmA9BdrvrUKGo3CwRC1k0b3SiqS4HLzhUmhgYmKH2i1wKwx7c3fOP1DAIrKpESF61NIPQYnNSDO5ITTrcNhttKnEMFExU+k6Z/PWf1D6NQ6n6XJpCIaTafpH1b+UIhgouIn52aXw5rQiEaHEV8dHKR0OKSgzq3zR2VUKRwNkS/u+UOhhomKn2i1wExO/xCAioYY1DZHQ6vxYHg6K35IXQrYSp9CDBMVP5o9zjv9s2H/UDjaeGkjlfQBkJtWjSiDW+FoiHxJ66aKWKJMIYKfpn40Mbsc6fFNaHAY8dVBVv9EKmlIvSDDpnAkRF3lWb0bZJbbY1HTZFI4GqKzY6LiR77VP9z7J1JJixTzrRUKR0LUVZzJhSHtrfSLuE6FQgATFT+Tqn827B8KJ6d/IlKRPKJSrnAkRN2TW+mz8odCAD9J/ey8oeVIi2+GvdWEr0tY/RNpHG1aHGrvT8GpH1Krjg61HFEh9WOi4mc6rcDM0d7pn49Z/RNxSiqS0ObRwhzdCmtCg9LhEHWrY88fjqiQ+jFRCQBp+uezfZz+iTTSHir51mq2zifVkhKVA+VJaGMrfVI5fooGwPk5NqTGead/vjmUqXQ4FEQdFT/sSEvqlZXUgBijC842PY5Um5UOh+iMmKgEgE4r2PwtQkkVPwXsSEsqptUCeVY2fqPQwEQlQK5oT1Q+2z+Uu5RGkI7SZI6okLoVsJU+hQgmKgFyfk4ZUmJbUNcchW2c/okIlQ1RqGqMgVbjwUgLW+eTuhVwc0IKEUxUAkSvE5jB6Z+IIg2hD021I9rYpnA0RGcmbU7IEmVSOyYqATS7vfrn0305nP6JAPL6FE77UAiQ1qicqo9DXTNb6ZN6MVEJoEk5ZUiObUFtcxR2HOb0T7jrKE3mtA+pX0KUC4OT7AA4/UPqxkQlgPQ6gRmjjwBg87dIsL9MqvjhiAqFho4OtUxUSL2YqATYFfL0z1A2VgpjzjbgUKW3H0V+BkdUKDQUZEglylynQurFRCXALsg9haSYVtQ0RWNHaYbS4VCAHK4ywuXWId7kxKDERqXDIeoVafSPUz+kZkxUAsygE5g+6ggAVv+Es8KyKADeSgq2zqdQIU39FJcnw+3hC5fUiYlKEFwxrmP6h28G4amozFs1UcBpHwohQ1LsiDK0odWlx5HqBKXDIeoWE5UguHDYSSTGtKKqMQY7Sq1Kh0MBUGjzJirsSEuhRKcVcpkyF9SSWjFRCQJO/4Q/aUSFC2kp1Eh9f4psXFBL6sREJUhmjfV2qV2/N4fTP2GmutGFigY9NBqBPLbOpxCTz80JSeWYqATJRcNOIiHKgarGGHx3hNM/4aTI1gQAGJJsR6yJrfMptHBzQlI7JipBYtR7ML29+Runf8JLYZk3Ucm31iocCVHfSSMqJ+viYW81KBwNUVdMVIJIav72Cad/woqUqLDih0KROcaJTLO390+xLUnhaIi6YqISRBcPP4n4KAcqG2Kw82i60uGQn0hTP1xIS6GqY/qH61RIfVSRqDz//PMYOnQooqKiMGnSJHz77bdKhxQQRr0Hvxh1FACwbs9QZYMhv2hze3CwvBkAUMCpHwpR+RlcUEvqpXii8vbbb2PRokVYvnw5fvjhB5xzzjmYMWMGKioqlA4tIGbL0z9D4PEoHAwN2OGqJjjdArFGDwYnNSgdDlG/5Mslypz6IfXRKx3Ak08+iXnz5uGWW24BALz44ov4+OOP8eqrr+K+++7r9XmanW3QO3tfcWHUaaHXefO0NrcHTrcHWo0GUQZdp3Nq0NdLZNC5YdAJAIDbo4GjTQcNBKKNbgDAxSNOIM7oRLk9Fl8fisHEIW4AZ49br9XCqPfG6/EItLZ5zxdj7Iiv1eWGR4g+xavTamDSex+zEAItLv+ct+u19D7GaIMOmvYe8442N9we/5w3Sq+DVus9r7PNg7Y+ZoEaaBBt7Dhvi9MNAQGTXgdd+3ldbg9cbt/z7jruHUUZYXGgta3za0UAMADQI8bYcWurSweP0MCoc0Pf/jppc2vgdOvQVzHGjteNdN7uXn99FW1ok7cBcLTp4Pbo219/3sfu8eC0x9o7Ufo2aNv/NHK2adHm0UKn9cDUfl4hgBZX389r0ruh03ofs8utgcutg1YjEGVwy8c0O73PRV9+n7t7jrqet+/xnu09AgBanDoInL6OreM11d3j0Gs93T5H3b1OTjc0tR4AUFSWhMbWOmi1He9LfI/w6u97RG90dy27+4zyx3kNOi0M7ed1ewQcbe6evr1H3T1HPX1GnUlzLz+zFU1UnE4ndu7ciSVLlsi3abVaTJs2Ddu2bev2exwOBxwOh/x/u90OADj/PzZCa4rp9c9+/qZzMXucd5PAT/eVY/6bP2BSTjLevn2yfMzFq3JR0zSyT49pxVVf4V8n7wcAfFtqxY2vXIkR6TXYsOh/AAAmvQea9jfV3/09C0D3j/N0f7p8BO78hTeWkspGTH/qCyTHGvHD0l/Ix9z86rfYUdq3dRK/u2AI/nz1GABATZMTEx/5HABw5LHZ8jGL3tmFdXtsfTrvFWOt+NucifL/Ry37FACw88FpSInzNkd75KNC/Pf2o306b9fnaDNqmpz47M4pGGmJBwA8v7kEz2w82KfzjkiPw4ZFP5f//6v//AoHKxrx1rwLMHmYt2zzrW+PYdkH+7r9/l3HozFq2b92uT05tgU/LP1v+f83vzoLO0oz8fxNGzB7nLe3zqf7hmL+m7/o8r1nc+Sxl+V/L3rnUqzbk9vt66+vdj74D6TEtQIAHvloBv57+8/wp8t34s5f7AQAlFQmYfpTv+nzeT+7812MtHgTu+c3T8AzGyfidxfsw5+v/hoAUNMUhYmPdL2GZ/PWvA8xeViZ99/fFmDZBxfjirGH8bc5n8vHjFp2f5/P291zNCnnFN6+/SP5mItX3Yiapug+nfds7xEA8Kv//DUOVvRtGqa756in119PWlwGjHloJDq/L/E9wmug7xE96el9vLvPqL7q7jlacdVo/OvkoQCAb0trcOMr2/t83u6eo+4+o87G42ju1c9TdOqnqqoKbrcbFovF53aLxQKbrfsX/cqVK2E2m+WvrKysYITqV3Eml9IhEBERhQSNEH0cr/OjU6dOYdCgQfjmm28weXJHBrx48WJs3boVO3bs6PI93Y2oZGVloayyGgkJvd9U6+xTP/Vodr4KYDt6MzUj6c2wbm2TERevuglNTiPe+PcxmJA96Kzn5dTPmc+r1LDu1L9sQUWDA2/8+zFMyN6CjteKC0A1gGTEGDv+HgitqR8XHG21cHtSodfqQ3jqx4VmZz2AZADGnk7ThfqmfjpeU909joFM/QDAA+9djLW7RuIPU6uw4LIrAXjfT/ke4cWpnw7+mvqx2+3ISEtBfX39GT+/FZ36SU1NhU6nQ3l5uc/t5eXlsFq7795qMplgMpm63B5j1Ps8KX2h7/SC8D2ngPeDp3/dRnVa4fMmIUmKdWLaqOP4YNcwbCqqwUXDh/TpvFqtptvH2vmXsz80msCcF0C355Xe/Px9XqNeC+MABws7vyFJOv+CA0BtkxMVDd6kedxgR/tzLT3fbfB+sLSh84dK5w85iV4noNcNrKNtd+ft6fXXFya9tFah43FrtRjweY16D4zwfePVaAZ+XoNOwNDNtYwxSs9F/14XPT1HA423p+eoc9LSofNr6syPo6fnqLvXiWTs4Cqs3TUSJRUmxBh16O7jge8RHXrzHtEf3V3Lnj6jBnpeXQ+fJX3R3XPU02fU6dp6+bMVnfoxGo2YOHEiNm7cKN/m8XiwceNGnxGWcHTF2CMAgE/2VMPTx78YSB2KbN4qn6xkE+KjWMJFoS0/Q6r86fqHIJGSFC9PXrRoEV555RW8/vrrKCwsxB133IGmpia5Cihc/XzkScQaPThV78CuE3VKh0P9UFjmXchdYI1VOBKigStob6V/rMaIRgf3rCL1UDxRuf766/HEE09g2bJlGD9+PHbt2oX169d3WWAbbqIMblxe4G1bvW53mcLRUH8U2byJSn4GExUKfUmxDlgTvF2Wi229q8YgCgbFExUAWLBgAY4ePQqHw4EdO3Zg0qRJSocUFFeM9U4dfLLXBgXXNFM/SVM/HFGhcJGf4S0fl/avIlIDVSQqkWpqXhNijFqcrGvBTyfqlQ6H+qDN7UGxlKhwRIXChLSTsrR/FZEaMFFRUJRB4LJ8b1OndXs4/RNKjlQ3w9HmQbRBh+zkKKXDIfKLAnnPHyYqpB5MVBQ2e2wqAODj3WWc/gkh0vqUPGu83JuBKNQVtE/9FNuaWY1IqsFERWFT85IQbdDhZF0L9pzk9E+okCt+MuIVjoTIf3JS62HUedDocONkXYvS4RABYKKiuGijDpflpwMAPub0T8goKpPWp/S+GzKR2hl0AsPTnQCA/e3JOJHSmKiowBVjvRtPrdvD6Z9QIVX85FuZqFB4KcjwdluWknEipTFRUYFL89MQZdDieE0L9p7kXzFqV9/ikofF86yc+qHwIicqNr4XkTowUVGBGKMel+Z5p3/W7eX0j9oVtQ+JD0qMhjnaoHA0RP6Vb5USFY6okDowUVEJTv+EDrnRGxfSUhiSRlSOVDfJOw8TKYmJikpclp8Ok16Lo9XN2HeKQ65qJrfO5/oUCkMpcW6kxRsgBOSmhkRKYqKiErGmTtM/rP5Rtf2s+KEwl9++LQSnf0gNmKioyKyxVgCc/lEzt0fggFTxw6kfClOj2reFKGSJMqkAExUVubzAAqNeiyPVzShkaaAqHatpRovLDZNei6Ep3OOHwpO0IzhLlEkNmKioSJxJj6kj0wBw+ketpL8w86zx0LF1PoUpaeqn0Gbn6C4pjomKyswex+ofNZNKkwu4kJbC2LC0aBh0GjS0trGVPimOiYrKXJafDqNei8NVTSgu57Cr2hRyfQpFAKNei2FpcQA4/UPKY6KiMvFRBkwZ0T79s5vTP2rD0mSKFFJVGzvUktKYqKjQ7HHe6p+POf2jKg2tLhyv8Q6Ds9kbhbv89u0huLCflMZERYUuL7DAqNPiUGUTDlY0Kh0OtZOaX2WYo5AYY1Q4GqLAkkZUCjmiQgpjoqJCCVEGXDIiFQDwMad/VENen8KNCCkCSOuwjlQ1ocXpVjgaimRMVFSq894/pA5SaTI70lIkSIszISXWCI8ADlZw+oeUw0RFpaaNssCg0+BgRSMOsvpHFaTS5HwmKhQBNBpNx/QPO9SSgpioqJQ52oCLh3unf9btsSkcDXk8Ql6jUsCpH4oQXFBLasBERcU4/aMex2ub0eR0w6jXIieVrfMpMuSzRJlUgImKik0fZYVBp0FxeQNKWP2jKOkvypGWOOh1/LWhyCCV4ReWNbBVAimG77gqZo4x4CJ5+oejKkpiozeKRMPT46DTalDf4oLN3qp0OBShmKio3BVjOP2jBlIbcZYmUyQx6XUYlsadlElZTFRUbvpoC/RaDYpsDThcyekfpUhNr0ax4ocijDSKuJ+VP6QQJioqlxhjxIWc/lFUk6MNR6ubAQB5HFGhCNOx5w9HVEgZTFRCwOyx0t4/LFNWgrSLdXq8CSlxJoWjIQouqUNtEUdUSCFMVELAL0ZZodNqUFhmR2lVk9LhRBx2pKVIVtA+9XO4qgmtLrbSp+BjohICkmONuHBYCgBO/yhBXkjLHZMpAlkSTEiKMcDtEWyTQIpgohIi2PxNOVJpcgFLkykCaTQaeUEtW+mTEpiohIgZo73TP/tO2XG0mtM/wSKE4IgKRTx5nQoX1JICmKiEiORYIy7ITQbAvX+C6URtCxocbTDoNBiWFqd0OESK4OaEpCQmKiGE0z/BJ/0FOTw9Hga2zqcIVdBp6oet9CnY+M4bQmaMtkKrAfacrMex9r4eFFhSSSZ3TKZINsISB60GqG12obLBoXQ4FGGYqISQ1DgTLsj1Vv98spejKsEgdaRlaTJFsiiDDrntU5/sUEvBxkQlxMzi9E9QcSEtkZe0zxUX1FKwMVEJMTPbp39+OlGP4zWc/gmkFqcbpe0VVtw1mSKd3EqfIyoUZExUQkxavAnn53irfzj9E1jF5Q0QwjvllhbP1vkU2aQRlULuokxBxkQlBM2Wp39YphxI8kJaTvsQySMqhyob4WhjK30KHiYqIWjGGCs0GmDX8TqcrGtROpywJc3F57PihwgZ5igkROnR5hE4VMGmkxQ8AUlUjhw5gltvvRU5OTmIjo7GsGHDsHz5cjidTp/jdu/ejUsuuQRRUVHIysrC448/Hohwwk56fBR+NrR9+oeLagNmPzcjJJJpNBrkS+tUbFynQsETkESlqKgIHo8HL730Evbt24ennnoKL774Iu6//375GLvdjunTp2PIkCHYuXMn/vKXv+Chhx7Cyy+/HIiQwo40/fMxE5WA8LbO974ZcyEtkdcodqglBegDcdKZM2di5syZ8v9zc3NRXFyMF154AU888QQA4I033oDT6cSrr74Ko9GI0aNHY9euXXjyySdx2223BSKssDJzjBUPfbgPPx6rw6m6FmQmRisdUlgpq2+FvbUNeq0Gw9JjlQ6HSBVYokxKCNoalfr6eiQnJ8v/37ZtG6ZMmQKj0SjfNmPGDBQXF6O2trbH8zgcDtjtdp+vSGRJiMJ5Q5IAAJ/s5aJaf5P+YhyWFgeTXqdwNETqkC+PqDBRoeAJSqJSUlKC5557Drfffrt8m81mg8Vi8TlO+r/N1vMH78qVK2E2m+WvrKyswAQdArj3T+BIfzGy4oeoQ54lHhoNUNXoYCt9Cpo+JSr33XcfNBrNGb+Kiop8vufkyZOYOXMmfvOb32DevHkDDnjJkiWor6+Xv44fPz7gc4aqWWO8icrOo7Uoq2f1jz9JIyr5XEhLJIs26pCT4p0K5YJaCpY+rVG56667MHfu3DMek5ubK//71KlTuPTSS3HhhRd2WSRrtVpRXl7uc5v0f6vV2uP5TSYTTCY23wIAqzkKE4ckYefRWqzfa8MtF+UoHVLYYGkyUffyM+JxuKoJRWUNuGREmtLhUAToU6KSlpaGtLTevTBPnjyJSy+9FBMnTsTq1auh1foO3kyePBkPPPAAXC4XDAYDAGDDhg3Iy8tDUlJSX8KKaFeMzcDOo7VYt6eMiYqftLrcOFzZCKCjyoGIvPKtCVi3x8bKHwqagKxROXnyJKZOnYrs7Gw88cQTqKyshM1m81l7ctNNN8FoNOLWW2/Fvn378Pbbb+OZZ57BokWLAhFS2LpirHf06fujtSi3tyocTXg4WN4IjwCSY41snU90GqmvUCErfyhIAlKevGHDBpSUlKCkpASDBw/2uU8IAQAwm8347LPPMH/+fEycOBGpqalYtmwZS5P7KMMcjXOzE/HDsTqs32vDzRcOVTqkkFdok/qnxEOj0SgcDZG6SNOhJRUNcLk9MOjY4JwCKyCvsLlz50II0e1XZ+PGjcOXX36J1tZWnDhxAvfee28gwgl7V7D5m18VsiMtUY8GJ0Uj3qSHyy1wuJKt9CnwmAqHgVnticp3R2pQwemfASsq40Jaop54W+lLOylznQoFHhOVMDAoMRrjsxIhBLB+H5u/DYQQQi675IgKUfekbSUKWaJMQcBEJUzMZvM3vyi3O1Db7IJOq8Hw9DilwyFSJWlEpYgdaikImKiEiZljvNU/35bWsGPkAEh/IeamxiLKwNb5RN0p4OaEFERMVMJEVnIMzhlshofTPwMir0/htA9Rj/Is3hGVigYHqhv5hxEFFhOVMCLv/bOb0z/9VdSpNJmIuhdr0mNISgwAoJj9VCjAmKiEESlR2VFajSr+ldMv0lA2O9ISnVlB+4La/Zz+oQBjohJGspJjMHaQd/rnU07/9JmjzY1D7X0h8rlrMtEZyQtqOaJCAcZEJcxcweqffiupaITbI2CONsCaEKV0OESqJpUocxdlCjQmKmFGKlPedqiai9z6qLB9IW1BBlvnE51NQfuIyoHyRrS5PQpHQ+GMiUqYyU6JwZhBCfAI4LP95UqHE1KKyqSFtFyfQnQ2WUkxiDXq4GzzoLSKrfQpcJiohKFZYzj90x/SXHsB16cQnZVWq0Fee3Ucd1KmQGKiEoak6Z9vDlWjpsmpcDShQQghV/xwRIWod6R+Q0Ws/KEAYqIShoamxmJURgLcHoHPWP3TK5WNDlQ3OaHVACMtHFEh6g12qKVgYKISpmaPa5/+2ctEpTekjrRDU2MRbWTrfKLeKLCyRJkCj4lKmJrVvvfPNyVVqGvm9M/ZyDsmc9qHqNekNSpl9a18n6GAYaISpnLT4pBvjUebR+Czfaz+OZvOpclE1DvxUQZkJUcD6PgdIvI3JiphTFpU+zGrf86KC2mJ+oeN3yjQmKiEsSva16l8XVKF+maXwtGol7PNg0OVjQDYOp+or+R1KhxRoQBhohLGhqXFIc/SPv2zn4tqe3KoshEut0B8lB6DEqOVDocopMiVPxxRoQBhohLmuPfP2XVeSMvW+UR9I/VSKbY1wO0RCkdD4YiJSpibPc5b/fNVSRXqWzj90x1pyJrTPkR9l50cg2iDDo42D45Us5U++R8TlTA3PD0eIy1xcLkFPufeP93az4W0RP2m02owUmqlz8ZvFABMVCIA9/45M+7xQzQwozK4oJYCh4lKBJC61H55sAr2Vk7/dFbV6EBlgwMats4n6jeWKFMgMVGJACMt8RieHgen24ONhZz+6ay4fTRlSHIMYk16haMhCk358tQPR1TI/5ioRIgr2lvqf7ybZcqdSXPqUoklEfWdVPlzsq6Fi/bJ75ioRAip+dsXByvRwOkfmfQXIBfSEvWfOdog9yAq5gaF5GdMVCJEniUeuWmxcLZ5sLGwQulwVEOaU2dpMtHA5Ms7KXOdCvkXE5UIodFo5L1/WP3j5XJ7cLDc2zp/FKd+iAZE7lDLEmXyMyYqEUQqU95yoBKNjjaFo1FeaVUTnG4P4kxsnU80UNKoJBfUkr8xUYkgBRnxyEmVpn9Y/SP95ZdnjYdWy9b5RAMhrfMqtjXAw1b65EdMVCKIRqPBFWO91T+c/un4y4+N3ogGbmhKDEx6LVpcbhytaVY6HAojTFQijLRJ4ZbiSjRF+PSPvJCWFT9EA6bXaZEnLajlOhXyIyYqEWZURgKGpMTA0ebBpqLIrv4p4ogKkV/Jjd9Yokx+xEQlwninf1j9U9vkhM3eCgDI44gKkV/IrfQ5okJ+xEQlAkllypuLK9DsjMzpn8L2aZ/s5BjEsXU+kV/IJcrspUJ+xEQlAo3OTEB2cgxaXR5sLqpUOhxFFMkdaTntQ+Qv0u/T8ZoWdsAmv2GiEoE0Gg1mRXj1T0dHWk77EPlLUqwR1oQoAMCBcq5TIf9gohKhpOmfTUUVaHG6FY4m+KTS5FFcSEvkV9Li9P1s/EZ+wkQlQo0dZMbgpGi0uNzYUhxZ1T9tbo/81x5Lk4n8Sxql5IJa8hcmKhGq894/H0fY9M+R6mY42jyIMeqQnRyjdDhEYaVjc0KOqJB/BDxRcTgcGD9+PDQaDXbt2uVz3+7du3HJJZcgKioKWVlZePzxxwMdDnUyq9P0T6srcqZ/2DqfKHBGdRpRYSt98oeAJyqLFy9GZmZml9vtdjumT5+OIUOGYOfOnfjLX/6Chx56CC+//HKgQ6J25ww2Y1BiNJqdkTX9w460RIGTkxoLo06LJqcbJ2pblA6HwkBAE5VPPvkEn332GZ544oku973xxhtwOp149dVXMXr0aNxwww344x//iCeffDKQIVEnvnv/2BSOJnjYkZYocPQ6LUZY4gCwnwr5R8A6XZWXl2PevHl4//33ERPTdR3Atm3bMGXKFBiNRvm2GTNmYNWqVaitrUVSUlK353U4HHA4HPL/7Xb+IgzEFWMz8MqXpfi8sBwPf7hP6XCCYuexWgAcUSEKlHxrAvadsuPvX5Zi++FqpcMhP7j23MEYM8isyM8OSKIihMDcuXPx+9//Hueddx6OHDnS5RibzYacnByf2ywWi3xfT4nKypUr8fDDD/s95kg1PisRgxKjcbKuBau/PqJ0OEFj0GmQzxEVooAYN9iM//3hBL49UoNvj9QoHQ75wYTspNBIVO677z6sWrXqjMcUFhbis88+Q0NDA5YsWTKg4LqzZMkSLFq0SP6/3W5HVlaW339OpNBoNHjpdxOxfq8NApGz8O28IclIiDIoHQZRWLruvCw42tyob2F32nAxIj1OsZ/dp0Tlrrvuwty5c894TG5uLjZt2oRt27bBZDL53Hfeeedhzpw5eP3112G1WlFeXu5zv/R/q9Xa4/lNJlOX89LAjBlkVixTJqLwE23U4bYpw5QOg8JEnxKVtLQ0pKWlnfW4Z599Fo888oj8/1OnTmHGjBl4++23MWnSJADA5MmT8cADD8DlcsFg8P5lu2HDBuTl5fU47UNERESRJSBrVLKzs33+HxfnHTIaNmwYBg8eDAC46aab8PDDD+PWW2/Fvffei7179+KZZ57BU089FYiQiIiIKAQptr+92WzGZ599hvnz52PixIlITU3FsmXLcNtttykVEhEREalMUBKVoUOHQoiuCzXHjRuHL7/8MhghEBERUQjiXj9ERESkWkxUiIiISLWYqBAREZFqMVEhIiIi1WKiQkRERKrFRIWIiIhUi4kKERERqRYTFSIiIlItJipERESkWoq10PcXqeOt3W7385ntAFoBuAC0+fncktb2n6MJ0PkpOLp7rbgAuNv/H6rPbzg8BoCPo6/4vkTBIX1ud9e5vjONONsRKnfixAlkZWUpHQYRERH1w/Hjx+UNi7sT8omKx+PBqVOnEB8fD43Gf38B2O12ZGVl4fjx40hISPDbeSMNr6N/8DoOHK+hf/A6+gevo3ckpaGhAZmZmdBqe16JEvJTP1qt9oyZ2EAlJCRE7IvIn3gd/YPXceB4Df2D19E/Iv06ms3msx7DxbRERESkWkxUiIiISLWYqPTAZDJh+fLlMJlMSocS0ngd/YPXceB4Df2D19E/eB17L+QX0xIREVH44ogKERERqRYTFSIiIlItJipERESkWkxUiIiISLWYqPTg+eefx9ChQxEVFYVJkybh22+/VTokxTz00EPQaDQ+X/n5+fL9ra2tmD9/PlJSUhAXF4drr70W5eXlPuc4duwYZs+ejZiYGKSnp+Oee+5BW5vvHkpbtmzBueeeC5PJhOHDh+O1114LxsMLiC+++AJXXnklMjMzodFo8P777/vcL4TAsmXLkJGRgejoaEybNg0HDx70OaampgZz5sxBQkICEhMTceutt6KxsdHnmN27d+OSSy5BVFQUsrKy8Pjjj3eJ5d1330V+fj6ioqIwduxYrFu3zu+PN1DOdh3nzp3b5bU5c+ZMn2Mi/TquXLkSP/vZzxAfH4/09HRcffXVKC4u9jkmmL/Dofre2pvrOHXq1C6vx9///vc+x0T6dewXQV2sWbNGGI1G8eqrr4p9+/aJefPmicTERFFeXq50aIpYvny5GD16tCgrK5O/Kisr5ft///vfi6ysLLFx40bx/fffiwsuuEBceOGF8v1tbW1izJgxYtq0aeLHH38U69atE6mpqWLJkiXyMYcPHxYxMTFi0aJFYv/+/eK5554TOp1OrF+/PqiP1V/WrVsnHnjgAfHee+8JAGLt2rU+9z/22GPCbDaL999/X/z000/iV7/6lcjJyREtLS3yMTNnzhTnnHOO2L59u/jyyy/F8OHDxY033ijfX19fLywWi5gzZ47Yu3eveOutt0R0dLR46aWX5GO+/vprodPpxOOPPy72798vHnzwQWEwGMSePXsCfg384WzX8eabbxYzZ870eW3W1NT4HBPp13HGjBli9erVYu/evWLXrl3iiiuuENnZ2aKxsVE+Jli/w6H83tqb6/jzn/9czJs3z+f1WF9fL9/P69g/TFS6cf7554v58+fL/3e73SIzM1OsXLlSwaiUs3z5cnHOOed0e19dXZ0wGAzi3XfflW8rLCwUAMS2bduEEN4PG61WK2w2m3zMCy+8IBISEoTD4RBCCLF48WIxevRon3Nff/31YsaMGX5+NMF3+gesx+MRVqtV/OUvf5Fvq6urEyaTSbz11ltCCCH2798vAIjvvvtOPuaTTz4RGo1GnDx5UgghxN/+9jeRlJQkX0MhhLj33ntFXl6e/P/rrrtOzJ492yeeSZMmidtvv92vjzEYekpUrrrqqh6/h9exq4qKCgFAbN26VQgR3N/hcHpvPf06CuFNVP70pz/1+D28jv3DqZ/TOJ1O7Ny5E9OmTZNv02q1mDZtGrZt26ZgZMo6ePAgMjMzkZubizlz5uDYsWMAgJ07d8Llcvlcr/z8fGRnZ8vXa9u2bRg7diwsFot8zIwZM2C327Fv3z75mM7nkI4Jx2teWloKm83m83jNZjMmTZrkc80SExNx3nnnycdMmzYNWq0WO3bskI+ZMmUKjEajfMyMGTNQXFyM2tpa+Zhwv65btmxBeno68vLycMcdd6C6ulq+j9exq/r6egBAcnIygOD9Dofbe+vp11HyxhtvIDU1FWPGjMGSJUvQ3Nws38fr2D8hvymhv1VVVcHtdvu8kADAYrGgqKhIoaiUNWnSJLz22mvIy8tDWVkZHn74YVxyySXYu3cvbDYbjEYjEhMTfb7HYrHAZrMBAGw2W7fXU7rvTMfY7Xa0tLQgOjo6QI8u+KTH3N3j7Xw90tPTfe7X6/VITk72OSYnJ6fLOaT7kpKSeryu0jlC3cyZM3HNNdcgJycHhw4dwv33349Zs2Zh27Zt0Ol0vI6n8Xg8WLhwIS666CKMGTMGAIL2O1xbWxs2763dXUcAuOmmmzBkyBBkZmZi9+7duPfee1FcXIz33nsPAK9jfzFRobOaNWuW/O9x48Zh0qRJGDJkCN55552wSiAo9Nxwww3yv8eOHYtx48Zh2LBh2LJlCy6//HIFI1On+fPnY+/evfjqq6+UDiWk9XQdb7vtNvnfY8eORUZGBi6//HIcOnQIw4YNC3aYYYNTP6dJTU2FTqfrsuK9vLwcVqtVoajUJTExESNHjkRJSQmsViucTifq6up8jul8vaxWa7fXU7rvTMckJCSEXTIkPeYzvcasVisqKip87m9ra0NNTY1frmu4vpZzc3ORmpqKkpISALyOnS1YsAAfffQRNm/ejMGDB8u3B+t3OFzeW3u6jt2ZNGkSAPi8Hnkd+46JymmMRiMmTpyIjRs3yrd5PB5s3LgRkydPVjAy9WhsbMShQ4eQkZGBiRMnwmAw+Fyv4uJiHDt2TL5ekydPxp49e3w+MDZs2ICEhASMGjVKPqbzOaRjwvGa5+TkwGq1+jxeu92OHTt2+Fyzuro67Ny5Uz5m06ZN8Hg88pvf5MmT8cUXX8DlcsnHbNiwAXl5eUhKSpKPiZTrCgAnTpxAdXU1MjIyAPA6At5S+AULFmDt2rXYtGlTl2muYP0Oh/p769muY3d27doFAD6vx0i/jv2i9GpeNVqzZo0wmUzitddeE/v37xe33XabSExM9FmpHUnuuususWXLFlFaWiq+/vprMW3aNJGamioqKiqEEN7SxuzsbLFp0ybx/fffi8mTJ4vJkyfL3y+V5E2fPl3s2rVLrF+/XqSlpXVbknfPPfeIwsJC8fzzz4d0eXJDQ4P48ccfxY8//igAiCeffFL8+OOP4ujRo0IIb3lyYmKi+OCDD8Tu3bvFVVdd1W158oQJE8SOHTvEV199JUaMGOFTVltXVycsFov43e9+J/bu3SvWrFkjYmJiupTV6vV68cQTT4jCwkKxfPnykCmrFeLM17GhoUHcfffdYtu2baK0tFR8/vnn4txzzxUjRowQra2t8jki/Trecccdwmw2iy1btviUzTY3N8vHBOt3OJTfW892HUtKSsSKFSvE999/L0pLS8UHH3wgcnNzxZQpU+Rz8Dr2DxOVHjz33HMiOztbGI1Gcf7554vt27crHZJirr/+epGRkSGMRqMYNGiQuP7660VJSYl8f0tLi/jDH/4gkpKSRExMjPj1r38tysrKfM5x5MgRMWvWLBEdHS1SU1PFXXfdJVwul88xmzdvFuPHjxdGo1Hk5uaK1atXB+PhBcTmzZsFgC5fN998sxDCW6K8dOlSYbFYhMlkEpdffrkoLi72OUd1dbW48cYbRVxcnEhISBC33HKLaGho8Dnmp59+EhdffLEwmUxi0KBB4rHHHusSyzvvvCNGjhwpjEajGD16tPj4448D9rj97UzXsbm5WUyfPl2kpaUJg8EghgwZIubNm9flzTrSr2N31w+Az+9XMH+HQ/W99WzX8dixY2LKlCkiOTlZmEwmMXz4cHHPPff49FERgtexPzRCCBG88RsiIiKi3uMaFSIiIlItJipERESkWkxUiIiISLWYqBAREZFqMVEhIiIi1WKiQkRERKrFRIWIiIhUi4kKERERqRYTFSIiIlItJipERESkWkxUiIiISLWYqBAREZFq/X8II7CzEvyoXwAAAABJRU5ErkJggg==", + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", "text/plain": [ "
" ] @@ -191,18 +638,1259 @@ "fig, ax = plt.subplots()\n", "\n", "# irradiance = processing.setpoints[\"setpoint_irradiance_full\"]\n", - "temperature = processing.setpoints[\"setpoint_temperature\"]\n", + "temperature = tc_uv.setpoints[\"setpoint_temperature\"]\n", "\n", "# ax.plot(irradiance, label=\"full spectrum irradiance\")\n", "ax.plot(temperature, label=\"temperature\")\n", "\n", "ax.axhline(y = 0, linestyle=\"-.\")\n", - "for idx, value in processing.setpoints[\"setpoint_irradiance_full\"].items():\n", + "for idx, value in tc_uv.setpoints[\"setpoint_irradiance_full\"].items():\n", " if value > 200:\n", " ax.axvspan(idx.total_seconds(), idx.total_seconds() + 60, color='yellow', alpha=0.3)\n", "\n", - "plt.legend()\n", - "uv_tc = processing" + "plt.legend()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## HF+UV - IEC 63556\n", + "\n", + "200 W/m2, UV40 kWh/m2 (we will approximate by using 1600 w/m^2 full spectrum for now) \n", + "IEC61215-2, TC50 (MQT 12) \n", + "\n", + "UV irradiation of 200W/m2 applied above 0℃ " + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "path = os.path.join(pvdeg.CHAMBER_DIR, \"IEC-61215-MQT-12.csv\")\n", + "\n", + "hf_uv = pvdeg.Chamber(\n", + " fp=path,\n", + " setpoint_names=[\"temperature\", \"relative_humidity\"],\n", + " skiprows=[1],\n", + ")\n", + "\n", + "# apply irradiance when temperature above 0 C\n", + "hf_uv.setpoints[\"setpoint_irradiance_full\"] = hf_uv.setpoints[\"setpoint_temperature\"].apply(lambda x: 1600 if x > 0 else 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "hf_uv.plot_setpoints()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Standard test sequence\n", + "\n", + "![63556](63556.png)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
setpoint_temperaturesetpoint_relative_humiditysetpoint_irradiance_full
0 days 00:00:0085.085.01600
0 days 00:01:0085.085.01600
0 days 00:02:0085.085.01600
0 days 00:03:0085.085.01600
0 days 00:04:0085.085.01600
............
50 days 06:55:000.030.00
50 days 06:56:006.2530.01600
50 days 06:57:0012.530.01600
50 days 06:58:0018.7530.01600
50 days 06:59:0025.030.01600
\n", + "

72420 rows × 3 columns

\n", + "
" + ], + "text/plain": [ + " setpoint_temperature setpoint_relative_humidity \\\n", + "0 days 00:00:00 85.0 85.0 \n", + "0 days 00:01:00 85.0 85.0 \n", + "0 days 00:02:00 85.0 85.0 \n", + "0 days 00:03:00 85.0 85.0 \n", + "0 days 00:04:00 85.0 85.0 \n", + "... ... ... \n", + "50 days 06:55:00 0.0 30.0 \n", + "50 days 06:56:00 6.25 30.0 \n", + "50 days 06:57:00 12.5 30.0 \n", + "50 days 06:58:00 18.75 30.0 \n", + "50 days 06:59:00 25.0 30.0 \n", + "\n", + " setpoint_irradiance_full \n", + "0 days 00:00:00 1600 \n", + "0 days 00:01:00 1600 \n", + "0 days 00:02:00 1600 \n", + "0 days 00:03:00 1600 \n", + "0 days 00:04:00 1600 \n", + "... ... \n", + "50 days 06:55:00 0 \n", + "50 days 06:56:00 1600 \n", + "50 days 06:57:00 1600 \n", + "50 days 06:58:00 1600 \n", + "50 days 06:59:00 1600 \n", + "\n", + "[72420 rows x 3 columns]" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = pd.concat([dh_uv.setpoints] * 2) # this is only 100 hours by default\n", + "b = pd.concat([tc_uv.setpoints] * 50) # 50 cycles TC + UV\n", + "c = pd.concat([hf_uv.setpoints] * 10) # 10 cycles HF + UV\n", + "\n", + "repeat_twice = pd.concat([b, c] * 2) # repeat two times\n", + "\n", + "# combine all\n", + "iec_63556 = pd.concat( \n", + " [a, repeat_twice]\n", + ")\n", + "\n", + "# reset index\n", + "iec_63556.index = pd.timedelta_range(start=\"0 days\", periods=len(iec_63556), freq=\"min\")\n", + "\n", + "\n", + "### CALCULATION DOES NOT WORK IF RH IS 0, gives NaN dew point\n", + "### realisititally, RH will neverbe 0, should we approximate with a very low RH, ex. 0.1\n", + "### or should we use a normal indoor rh like 30 or 40\n", + "### the test sequences never specify 0 RH, only that there is no active RH control\n", + "### does this mean we can use a default in these cases\n", + "iec_63556[\"setpoint_relative_humidity\"] = iec_63556[\"setpoint_relative_humidity\"].apply(lambda x : 30 if x == 0 else x)\n", + "\n", + "iec_63556" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# we must fix the nans\n", + "iec_63556[\"setpoint_relative_humidity\"].plot(title=\"rh setpoints : contain nans\")" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# must fix the nans so they do not propigate through our simulation\n", + "# lets use a placeholder value of rh = 30 %\n", + "iec_63556[\"setpoint_relative_humidity\"] = iec_63556[\"setpoint_relative_humidity\"].apply(lambda x: 30 if pd.isna(x) else x) \n", + "\n", + "iec_63556[\"setpoint_relative_humidity\"].plot(title=\"rh setpoints : nans fixed\")" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "# define chamber with created setpoints df instead of providing file containing setpoints\n", + "chamber_63556 = pvdeg.Chamber(setpoints=iec_63556)\n", + "\n", + "# use water parameters\n", + "# add test sample parameters\n", + "chamber_63556.setEncapsulant(\"H2Opermeation\", key=\"W001\", thickness=0.5) # eva\n", + "chamber_63556.setBacksheet(\"H2Opermeation\", key=\"W003\", thickness=0.25) # pet\n", + "\n", + "chamber_63556.setDimensions(0.1, 0.1)\n", + "chamber_63556.setAbsorptance(0.98)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "chamber_63556.plot_setpoints()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "chamber_63556.calc_temperatures(\n", + " air_temp_0=chamber_63556.setpoints[\"setpoint_temperature\"].iloc[0],\n", + " sample_temp_0=chamber_63556.setpoints[\"setpoint_temperature\"].iloc[0],\n", + " tau_c=15,\n", + " tau_s=10\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "chamber_63556.plot_temperatures()" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
setpoint_temperaturesetpoint_relative_humiditysetpoint_irradiance_fullAir TemperatureWater Vapor PressureDew Point
0 days 00:00:0085.085.0160085.00000049.35371681.111387
0 days 00:01:0085.085.0160085.00000049.35371681.111387
0 days 00:02:0085.085.0160085.00000049.35371681.111387
0 days 00:03:0085.085.0160085.00000049.35371681.111387
0 days 00:04:0085.085.0160085.00000049.35371681.111387
.....................
50 days 06:55:000.030.00-28.5752810.012822-40.824643
50 days 06:56:006.2530.01600-26.3292940.016129-38.130547
50 days 06:57:0012.530.01600-23.8250750.020709-35.364591
50 days 06:58:0018.7530.01600-21.0792800.027048-32.557339
50 days 06:59:0025.030.01600-18.1074890.035822-29.719125
\n", + "

72420 rows × 6 columns

\n", + "
" + ], + "text/plain": [ + " setpoint_temperature setpoint_relative_humidity \\\n", + "0 days 00:00:00 85.0 85.0 \n", + "0 days 00:01:00 85.0 85.0 \n", + "0 days 00:02:00 85.0 85.0 \n", + "0 days 00:03:00 85.0 85.0 \n", + "0 days 00:04:00 85.0 85.0 \n", + "... ... ... \n", + "50 days 06:55:00 0.0 30.0 \n", + "50 days 06:56:00 6.25 30.0 \n", + "50 days 06:57:00 12.5 30.0 \n", + "50 days 06:58:00 18.75 30.0 \n", + "50 days 06:59:00 25.0 30.0 \n", + "\n", + " setpoint_irradiance_full Air Temperature \\\n", + "0 days 00:00:00 1600 85.000000 \n", + "0 days 00:01:00 1600 85.000000 \n", + "0 days 00:02:00 1600 85.000000 \n", + "0 days 00:03:00 1600 85.000000 \n", + "0 days 00:04:00 1600 85.000000 \n", + "... ... ... \n", + "50 days 06:55:00 0 -28.575281 \n", + "50 days 06:56:00 1600 -26.329294 \n", + "50 days 06:57:00 1600 -23.825075 \n", + "50 days 06:58:00 1600 -21.079280 \n", + "50 days 06:59:00 1600 -18.107489 \n", + "\n", + " Water Vapor Pressure Dew Point \n", + "0 days 00:00:00 49.353716 81.111387 \n", + "0 days 00:01:00 49.353716 81.111387 \n", + "0 days 00:02:00 49.353716 81.111387 \n", + "0 days 00:03:00 49.353716 81.111387 \n", + "0 days 00:04:00 49.353716 81.111387 \n", + "... ... ... \n", + "50 days 06:55:00 0.012822 -40.824643 \n", + "50 days 06:56:00 0.016129 -38.130547 \n", + "50 days 06:57:00 0.020709 -35.364591 \n", + "50 days 06:58:00 0.027048 -32.557339 \n", + "50 days 06:59:00 0.035822 -29.719125 \n", + "\n", + "[72420 rows x 6 columns]" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "chamber_63556.chamber_conditions(\n", + " tau_c=15, \n", + " air_temp_0=chamber_63556.setpoints[\"setpoint_temperature\"].iloc[0]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "res = chamber_63556.sample_conditions(\n", + " tau_s=15, \n", + " sample_temp_0=chamber_63556.setpoints[\"setpoint_temperature\"].iloc[0]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Calculate Degradation in the chamber using double integral\n", + "\n", + "We want to scale this to 1600 w/m^2 across the full spectrum" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1002.8734035484464 w/m^2 full spectrum (reference)\n", + "1600.0 w/m^2 full spectrum (scaled to relative 1600 w/m^2 to approximate UV irradiance of 200 w/m^2/nm @ 280 nm - 400 nm)\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import pvlib\n", + "\n", + "# full wavelength irradiance in W/m^2 for reference spectra\n", + "reference_spectrum = pvlib.spectrum.get_am15g()\n", + "\n", + "print( np.trapz(reference_spectrum) , \"w/m^2 full spectrum (reference)\")\n", + "\n", + "scale_factor = 1600 / 1002.8734035484464\n", + "scaled_spectrum = scale_factor * reference_spectrum\n", + "\n", + "print( np.trapz(scaled_spectrum) , \"w/m^2 full spectrum (scaled to relative 1600 w/m^2 to approximate UV irradiance of 200 w/m^2/nm @ 280 nm - 400 nm)\")" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "# create a datetime index from the timedelta index\n", + "base_date = pd.Timestamp('2023-01-01')\n", + "datetime_index = base_date + chamber_63556.setpoints.index\n", + "\n", + "data = np.zeros((chamber_63556.setpoints.shape[0], len(scaled_spectrum)))\n", + "\n", + "# create an empty dataframe\n", + "spectra_df = pd.DataFrame(index=datetime_index, data=data, columns= scaled_spectrum.index)\n", + "\n", + "# get the mask, this will have the wrong index because it was created from the timedelta index series\n", + "mask = chamber_63556.setpoints[\"setpoint_irradiance_full\"] == 1600\n", + "mask.index = spectra_df.index # fix the index (entries already correspond 1:1)\n", + "\n", + "# full the dataframe\n", + "spectra_df.loc[mask] = scaled_spectrum.values" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
wavelength280.0280.5281.0281.5282.0282.5283.0283.5284.0284.5...3955.03960.03965.03970.03975.03980.03985.03990.03995.04000.0
2023-01-01 00:00:007.547752e-231.963478e-219.077118e-212.498740e-191.905884e-187.248931e-182.943861e-175.641390e-171.159389e-153.965565e-15...0.0123160.0123620.0124530.0122540.0119810.0117860.0118580.0117620.0115030.011334
2023-01-01 00:01:007.547752e-231.963478e-219.077118e-212.498740e-191.905884e-187.248931e-182.943861e-175.641390e-171.159389e-153.965565e-15...0.0123160.0123620.0124530.0122540.0119810.0117860.0118580.0117620.0115030.011334
2023-01-01 00:02:007.547752e-231.963478e-219.077118e-212.498740e-191.905884e-187.248931e-182.943861e-175.641390e-171.159389e-153.965565e-15...0.0123160.0123620.0124530.0122540.0119810.0117860.0118580.0117620.0115030.011334
2023-01-01 00:03:007.547752e-231.963478e-219.077118e-212.498740e-191.905884e-187.248931e-182.943861e-175.641390e-171.159389e-153.965565e-15...0.0123160.0123620.0124530.0122540.0119810.0117860.0118580.0117620.0115030.011334
2023-01-01 00:04:007.547752e-231.963478e-219.077118e-212.498740e-191.905884e-187.248931e-182.943861e-175.641390e-171.159389e-153.965565e-15...0.0123160.0123620.0124530.0122540.0119810.0117860.0118580.0117620.0115030.011334
..................................................................
2023-02-20 06:55:000.000000e+000.000000e+000.000000e+000.000000e+000.000000e+000.000000e+000.000000e+000.000000e+000.000000e+000.000000e+00...0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
2023-02-20 06:56:007.547752e-231.963478e-219.077118e-212.498740e-191.905884e-187.248931e-182.943861e-175.641390e-171.159389e-153.965565e-15...0.0123160.0123620.0124530.0122540.0119810.0117860.0118580.0117620.0115030.011334
2023-02-20 06:57:007.547752e-231.963478e-219.077118e-212.498740e-191.905884e-187.248931e-182.943861e-175.641390e-171.159389e-153.965565e-15...0.0123160.0123620.0124530.0122540.0119810.0117860.0118580.0117620.0115030.011334
2023-02-20 06:58:007.547752e-231.963478e-219.077118e-212.498740e-191.905884e-187.248931e-182.943861e-175.641390e-171.159389e-153.965565e-15...0.0123160.0123620.0124530.0122540.0119810.0117860.0118580.0117620.0115030.011334
2023-02-20 06:59:007.547752e-231.963478e-219.077118e-212.498740e-191.905884e-187.248931e-182.943861e-175.641390e-171.159389e-153.965565e-15...0.0123160.0123620.0124530.0122540.0119810.0117860.0118580.0117620.0115030.011334
\n", + "

72420 rows × 2002 columns

\n", + "
" + ], + "text/plain": [ + "wavelength 280.0 280.5 281.0 281.5 \\\n", + "2023-01-01 00:00:00 7.547752e-23 1.963478e-21 9.077118e-21 2.498740e-19 \n", + "2023-01-01 00:01:00 7.547752e-23 1.963478e-21 9.077118e-21 2.498740e-19 \n", + "2023-01-01 00:02:00 7.547752e-23 1.963478e-21 9.077118e-21 2.498740e-19 \n", + "2023-01-01 00:03:00 7.547752e-23 1.963478e-21 9.077118e-21 2.498740e-19 \n", + "2023-01-01 00:04:00 7.547752e-23 1.963478e-21 9.077118e-21 2.498740e-19 \n", + "... ... ... ... ... \n", + "2023-02-20 06:55:00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n", + "2023-02-20 06:56:00 7.547752e-23 1.963478e-21 9.077118e-21 2.498740e-19 \n", + "2023-02-20 06:57:00 7.547752e-23 1.963478e-21 9.077118e-21 2.498740e-19 \n", + "2023-02-20 06:58:00 7.547752e-23 1.963478e-21 9.077118e-21 2.498740e-19 \n", + "2023-02-20 06:59:00 7.547752e-23 1.963478e-21 9.077118e-21 2.498740e-19 \n", + "\n", + "wavelength 282.0 282.5 283.0 283.5 \\\n", + "2023-01-01 00:00:00 1.905884e-18 7.248931e-18 2.943861e-17 5.641390e-17 \n", + "2023-01-01 00:01:00 1.905884e-18 7.248931e-18 2.943861e-17 5.641390e-17 \n", + "2023-01-01 00:02:00 1.905884e-18 7.248931e-18 2.943861e-17 5.641390e-17 \n", + "2023-01-01 00:03:00 1.905884e-18 7.248931e-18 2.943861e-17 5.641390e-17 \n", + "2023-01-01 00:04:00 1.905884e-18 7.248931e-18 2.943861e-17 5.641390e-17 \n", + "... ... ... ... ... \n", + "2023-02-20 06:55:00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n", + "2023-02-20 06:56:00 1.905884e-18 7.248931e-18 2.943861e-17 5.641390e-17 \n", + "2023-02-20 06:57:00 1.905884e-18 7.248931e-18 2.943861e-17 5.641390e-17 \n", + "2023-02-20 06:58:00 1.905884e-18 7.248931e-18 2.943861e-17 5.641390e-17 \n", + "2023-02-20 06:59:00 1.905884e-18 7.248931e-18 2.943861e-17 5.641390e-17 \n", + "\n", + "wavelength 284.0 284.5 ... 3955.0 3960.0 \\\n", + "2023-01-01 00:00:00 1.159389e-15 3.965565e-15 ... 0.012316 0.012362 \n", + "2023-01-01 00:01:00 1.159389e-15 3.965565e-15 ... 0.012316 0.012362 \n", + "2023-01-01 00:02:00 1.159389e-15 3.965565e-15 ... 0.012316 0.012362 \n", + "2023-01-01 00:03:00 1.159389e-15 3.965565e-15 ... 0.012316 0.012362 \n", + "2023-01-01 00:04:00 1.159389e-15 3.965565e-15 ... 0.012316 0.012362 \n", + "... ... ... ... ... ... \n", + "2023-02-20 06:55:00 0.000000e+00 0.000000e+00 ... 0.000000 0.000000 \n", + "2023-02-20 06:56:00 1.159389e-15 3.965565e-15 ... 0.012316 0.012362 \n", + "2023-02-20 06:57:00 1.159389e-15 3.965565e-15 ... 0.012316 0.012362 \n", + "2023-02-20 06:58:00 1.159389e-15 3.965565e-15 ... 0.012316 0.012362 \n", + "2023-02-20 06:59:00 1.159389e-15 3.965565e-15 ... 0.012316 0.012362 \n", + "\n", + "wavelength 3965.0 3970.0 3975.0 3980.0 3985.0 \\\n", + "2023-01-01 00:00:00 0.012453 0.012254 0.011981 0.011786 0.011858 \n", + "2023-01-01 00:01:00 0.012453 0.012254 0.011981 0.011786 0.011858 \n", + "2023-01-01 00:02:00 0.012453 0.012254 0.011981 0.011786 0.011858 \n", + "2023-01-01 00:03:00 0.012453 0.012254 0.011981 0.011786 0.011858 \n", + "2023-01-01 00:04:00 0.012453 0.012254 0.011981 0.011786 0.011858 \n", + "... ... ... ... ... ... \n", + "2023-02-20 06:55:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2023-02-20 06:56:00 0.012453 0.012254 0.011981 0.011786 0.011858 \n", + "2023-02-20 06:57:00 0.012453 0.012254 0.011981 0.011786 0.011858 \n", + "2023-02-20 06:58:00 0.012453 0.012254 0.011981 0.011786 0.011858 \n", + "2023-02-20 06:59:00 0.012453 0.012254 0.011981 0.011786 0.011858 \n", + "\n", + "wavelength 3990.0 3995.0 4000.0 \n", + "2023-01-01 00:00:00 0.011762 0.011503 0.011334 \n", + "2023-01-01 00:01:00 0.011762 0.011503 0.011334 \n", + "2023-01-01 00:02:00 0.011762 0.011503 0.011334 \n", + "2023-01-01 00:03:00 0.011762 0.011503 0.011334 \n", + "2023-01-01 00:04:00 0.011762 0.011503 0.011334 \n", + "... ... ... ... \n", + "2023-02-20 06:55:00 0.000000 0.000000 0.000000 \n", + "2023-02-20 06:56:00 0.011762 0.011503 0.011334 \n", + "2023-02-20 06:57:00 0.011762 0.011503 0.011334 \n", + "2023-02-20 06:58:00 0.011762 0.011503 0.011334 \n", + "2023-02-20 06:59:00 0.011762 0.011503 0.011334 \n", + "\n", + "[72420 rows x 2002 columns]" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spectra_df" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
relative_humiditytemperature
2023-01-01 00:00:0085.00000085.0
2023-01-01 00:01:0081.66053786.045333
2023-01-01 00:02:0078.67406887.02325
2023-01-01 00:03:0075.99478687.938098
2023-01-01 00:04:0073.58403088.793944
.........
2023-02-20 06:55:0026.113443-27.223452
2023-02-20 06:56:0032.657592-27.165785
2023-02-20 06:57:0036.905242-25.905
2023-02-20 06:58:0042.088819-24.548441
2023-02-20 06:59:0048.266644-23.087711
\n", + "

72420 rows × 2 columns

\n", + "
" + ], + "text/plain": [ + " relative_humidity temperature\n", + "2023-01-01 00:00:00 85.000000 85.0\n", + "2023-01-01 00:01:00 81.660537 86.045333\n", + "2023-01-01 00:02:00 78.674068 87.02325\n", + "2023-01-01 00:03:00 75.994786 87.938098\n", + "2023-01-01 00:04:00 73.584030 88.793944\n", + "... ... ...\n", + "2023-02-20 06:55:00 26.113443 -27.223452\n", + "2023-02-20 06:56:00 32.657592 -27.165785\n", + "2023-02-20 06:57:00 36.905242 -25.905\n", + "2023-02-20 06:58:00 42.088819 -24.548441\n", + "2023-02-20 06:59:00 48.266644 -23.087711\n", + "\n", + "[72420 rows x 2 columns]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# create dataframe from chamber simulations\n", + "conditions_df = pd.DataFrame(\n", + " data={\n", + " \"relative_humidity\":chamber_63556.sample_relative_humidity,\n", + " \"temperature\":chamber_63556.sample_temperature,\n", + " }\n", + ")\n", + "\n", + "# update index, same as above timedelta->datetime\n", + "conditions_df.index = spectra_df.index\n", + "conditions_df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pvdeg.degradation.degradation(\n", + " spectra_df=spectra_df,\n", + " conditions_df=conditions_df,\n", + "\n", + " p=0.5, # default\n", + " Ea=38,\n", + " C2=0.07, # default\n", + " n=0, # ignore RH for nowe\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Simple Calculation Compared to Miami\n", + "\n", + "How can we calculate degradation in the chamber, and degradation in miami\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "weather_db = 'PSM3'\n", + "weather_id = (25.783388, -80.189029)\n", + "weather_arg = {'api_key': 'DEMO_KEY',\n", + " 'email': 'user@mail.com',\n", + " 'names': 'tmy',\n", + " 'attributes': [],\n", + " 'map_variables': True}\n", + "\n", + "weather_df, meta = pvdeg.weather.get(weather_db, weather_id, **weather_arg)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def calculate_vapor_pressure(temp):\n", + " \"\"\"Calculate the saturation vapor pressure using air temperature.\"\"\"\n", + " return 6.11 * 10 ** (7.5 * temp / (237.3 + temp))\n", + "\n", + "def calculate_relative_humidity(dew_point, air_temp):\n", + " \"\"\"Calculate relative humidity.\"\"\"\n", + " avp = calculate_vapor_pressure(dew_point) # Actual Vapor Pressure\n", + " svp = calculate_vapor_pressure(air_temp) # Saturation Vapor Pressure\n", + " rh = (avp / svp) * 100 # Relative Humidity\n", + " return rh\n", + "\n", + "actual_rh = calculate_relative_humidity(chamber_63556.dew_point, chamber_63556.air_temperature)\n", + "\n", + "actual_rh" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pvdeg.degradation.arrhenius_deg(\n", + " weather_df=weather_df,\n", + " meta=meta,\n", + " # calc rh outdoor?\n", + " \n", + " temp_chamber=chamber_63556.air_temperature, # must call calc_temps before this\n", + " I_chamber=chamber_63556.setpoints[\"setpoint_irradiance_full\"],\n", + " rh_chamber=actual_rh,\n", + "\n", + " Ea=80, # sample arrhenius activation energy for a polymer\n", + ")" ] }, { @@ -215,7 +1903,7 @@ ], "metadata": { "kernelspec": { - "display_name": "fem_diff", + "display_name": "deg", "language": "python", "name": "python3" }, @@ -229,7 +1917,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.14" + "version": "3.9.19" } }, "nbformat": 4, diff --git a/tests/test_degradation.py b/tests/test_degradation.py index d9428e99..0454a01c 100644 --- a/tests/test_degradation.py +++ b/tests/test_degradation.py @@ -131,12 +131,26 @@ def test_degradation(): data = pd.read_csv(INPUT_SPECTRA) wavelengths = np.array(range(280, 420, 20)) + + # convert to expected format + spectra = data["Spectra"] + spectra_df = pd.DataFrame(spectra.tolist(), index=spectra.index) + spectra_df = spectra.str.strip("[]").str.split(",", expand=True).astype(float) + spectra_df.columns = wavelengths + + conditions_df = pd.DataFrame( + index=spectra_df.index, + data={ + "relative_humidity": data["RH"], + "temperature": data["Temperature"], + } + ) + degradation = pvdeg.degradation.degradation( - spectra=data["Spectra"], - rh_module=data["RH"], - temp_module=data["Temperature"], - wavelengths=wavelengths, + spectra_df=spectra_df, + conditions_df=conditions_df ) + assert degradation == pytest.approx(4.4969e-38, abs=0.02e-38) diff --git a/tutorials_and_tools/tutorials_and_tools/3 - Spectral Degradation.ipynb b/tutorials_and_tools/tutorials_and_tools/3 - Spectral Degradation.ipynb index 91c048f0..dce03564 100644 --- a/tutorials_and_tools/tutorials_and_tools/3 - Spectral Degradation.ipynb +++ b/tutorials_and_tools/tutorials_and_tools/3 - Spectral Degradation.ipynb @@ -32,22 +32,7 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_40480\\1750438778.py:2: DeprecationWarning: \n", - "Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),\n", - "(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)\n", - "but was not found to be installed on your system.\n", - "If this would cause problems for you,\n", - "please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466\n", - " \n", - " import pandas as pd\n" - ] - } - ], + "outputs": [], "source": [ "import os\n", "import pandas as pd\n", @@ -66,9 +51,9 @@ "output_type": "stream", "text": [ "Working on a Windows 10\n", - "Python version 3.11.7 | packaged by Anaconda, Inc. | (main, Dec 15 2023, 18:05:47) [MSC v.1916 64 bit (AMD64)]\n", - "Pandas version 2.2.0\n", - "pvdeg version 0.2.4.dev83+ge2ceab9.d20240422\n" + "Python version 3.9.19 (main, May 6 2024, 20:12:36) [MSC v.1916 64 bit (AMD64)]\n", + "Pandas version 2.2.3\n", + "pvdeg version 0.4.3.dev22+g0ef212c.d20241017\n" ] } ], @@ -101,7 +86,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -201,6 +186,218 @@ "SPECTRA.head()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Convert To Expected Format**\n", + "\n", + "Since the original version of this tutorial, the expected inputs for the spectral degradation function have changed, we must convert the previously loaded inputs to the expected form. \n", + "\n", + "We will created the desired spectra dataframe and conditions dataframe in the following cell." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
280300320340360380400
timestamp
2021-03-09 10:00:000.6892150.4021560.6725890.0267550.3397720.9432470.741140
2021-03-09 11:00:000.1557570.5464370.6895800.7827660.5049820.9335720.465200
2021-03-09 12:00:000.2278210.9056500.2638720.0572300.9905800.9369940.180034
2021-03-09 13:00:000.3741940.0358310.4052370.9578220.1043990.8916960.487553
2021-03-09 14:00:000.4032120.6473170.6981120.0633600.8680300.6869390.416581
2021-03-09 15:00:000.7461340.8382590.8390970.1348490.5484540.6060190.101388
2021-03-09 16:00:000.4629110.0323000.5794190.3702470.5205980.5665950.672994
2021-03-09 17:00:000.1735030.8139710.8662740.3441680.6677450.6899450.143764
2021-03-09 18:00:000.3699190.8874100.0823970.0853350.6335600.1955460.374416
2021-03-09 19:00:000.1497640.7994750.6171050.1562690.3227450.7293110.606430
\n", + "
" + ], + "text/plain": [ + " 280 300 320 340 360 \\\n", + "timestamp \n", + "2021-03-09 10:00:00 0.689215 0.402156 0.672589 0.026755 0.339772 \n", + "2021-03-09 11:00:00 0.155757 0.546437 0.689580 0.782766 0.504982 \n", + "2021-03-09 12:00:00 0.227821 0.905650 0.263872 0.057230 0.990580 \n", + "2021-03-09 13:00:00 0.374194 0.035831 0.405237 0.957822 0.104399 \n", + "2021-03-09 14:00:00 0.403212 0.647317 0.698112 0.063360 0.868030 \n", + "2021-03-09 15:00:00 0.746134 0.838259 0.839097 0.134849 0.548454 \n", + "2021-03-09 16:00:00 0.462911 0.032300 0.579419 0.370247 0.520598 \n", + "2021-03-09 17:00:00 0.173503 0.813971 0.866274 0.344168 0.667745 \n", + "2021-03-09 18:00:00 0.369919 0.887410 0.082397 0.085335 0.633560 \n", + "2021-03-09 19:00:00 0.149764 0.799475 0.617105 0.156269 0.322745 \n", + "\n", + " 380 400 \n", + "timestamp \n", + "2021-03-09 10:00:00 0.943247 0.741140 \n", + "2021-03-09 11:00:00 0.933572 0.465200 \n", + "2021-03-09 12:00:00 0.936994 0.180034 \n", + "2021-03-09 13:00:00 0.891696 0.487553 \n", + "2021-03-09 14:00:00 0.686939 0.416581 \n", + "2021-03-09 15:00:00 0.606019 0.101388 \n", + "2021-03-09 16:00:00 0.566595 0.672994 \n", + "2021-03-09 17:00:00 0.689945 0.143764 \n", + "2021-03-09 18:00:00 0.195546 0.374416 \n", + "2021-03-09 19:00:00 0.729311 0.606430 " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# convert to expected format\n", + "spectra = SPECTRA[\"Spectra\"]\n", + "spectra_df = pd.DataFrame(spectra.tolist(), index=spectra.index)\n", + "spectra_df = spectra.str.strip(\"[]\").str.split(\",\", expand=True).astype(float)\n", + "spectra_df.columns = wavelengths\n", + "\n", + "conditions_df = pd.DataFrame(\n", + " index=spectra_df.index,\n", + " data={\n", + " \"relative_humidity\": SPECTRA[\"RH\"],\n", + " \"temperature\": SPECTRA[\"Temperature\"],\n", + " }\n", + ")\n", + "\n", + "spectra_df" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -212,28 +409,108 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.496994351804118e-38" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "degradation = pvdeg.degradation.degradation(\n", + " spectra_df=spectra_df,\n", + " conditions_df=conditions_df\n", + ")\n", + "degradation" + ] + }, + { + "cell_type": "code", + "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Removing brackets from spectral irradiance data\n" + "Removing brackets from spectral irradiance data\n", + "arr integral timestamp\n", + "2021-03-09 10:00:00 2.193695e-45\n", + "2021-03-09 11:00:00 1.833548e-46\n", + "2021-03-09 12:00:00 1.508690e-34\n", + "2021-03-09 13:00:00 4.256451e-47\n", + "2021-03-09 14:00:00 1.041473e-82\n", + "2021-03-09 15:00:00 5.746285e-189\n", + "2021-03-09 16:00:00 2.430948e-62\n", + "2021-03-09 17:00:00 1.440645e-46\n", + "2021-03-09 18:00:00 2.196529e-64\n", + "2021-03-09 19:00:00 1.433768e-103\n", + "Name: Arr_integrand, dtype: float64\n", + "wavelength integral timestamp\n", + "2021-03-09 10:00:00 0.000358\n", + "2021-03-09 11:00:00 0.000287\n", + "2021-03-09 12:00:00 0.000298\n", + "2021-03-09 13:00:00 0.000258\n", + "2021-03-09 14:00:00 0.000338\n", + "2021-03-09 15:00:00 0.000412\n", + "2021-03-09 16:00:00 0.000275\n", + "2021-03-09 17:00:00 0.000309\n", + "2021-03-09 18:00:00 0.000311\n", + "2021-03-09 19:00:00 0.000284\n", + "Name: G_integral, dtype: float64\n", + "delta degradation timestamp\n", + "2021-03-09 10:00:00 7.861213e-49\n", + "2021-03-09 11:00:00 5.263019e-50\n", + "2021-03-09 12:00:00 4.496994e-38\n", + "2021-03-09 13:00:00 1.099005e-50\n", + "2021-03-09 14:00:00 3.519596e-86\n", + "2021-03-09 15:00:00 2.369241e-192\n", + "2021-03-09 16:00:00 6.696099e-66\n", + "2021-03-09 17:00:00 4.452817e-50\n", + "2021-03-09 18:00:00 6.827920e-68\n", + "2021-03-09 19:00:00 4.071628e-107\n", + "Name: dD, dtype: float64\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\tford\\AppData\\Local\\Temp\\2\\ipykernel_26040\\2414568496.py:1: DeprecationWarning: Call to deprecated function degradation (old double integral degradation function will be replaced 'pvdegradation' in an updated version of pvdeg).\n", + " degradation = pvdeg.degradation.degradation(spectra=SPECTRA['Spectra'],\n" ] + }, + { + "data": { + "text/plain": [ + "4.496994351804118e-38" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ "degradation = pvdeg.degradation.degradation(spectra=SPECTRA['Spectra'],\n", " rh_module=SPECTRA['RH'],\n", " temp_module=SPECTRA['Temperature'],\n", - " wavelengths=wavelengths)" + " wavelengths=wavelengths)\n", + "\n", + "degradation " ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "deg", "language": "python", "name": "python3" }, @@ -247,12 +524,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" - }, - "vscode": { - "interpreter": { - "hash": "14c04630f1cd445b2532d35c77825134bfcafda47af70d0b9c2b5023b1f357a5" - } + "version": "3.9.19" } }, "nbformat": 4, diff --git a/tutorials_and_tools/tutorials_and_tools/Chamber Irradiance.ipynb b/tutorials_and_tools/tutorials_and_tools/Chamber Irradiance.ipynb index 5592d535..6eabb515 100644 --- a/tutorials_and_tools/tutorials_and_tools/Chamber Irradiance.ipynb +++ b/tutorials_and_tools/tutorials_and_tools/Chamber Irradiance.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 17, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -146,19 +146,19 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "0 days 00:00:00 0.000000\n", + "0 days 00:00:00 0.0\n", "0 days 00:01:00 1096.460463\n", "0 days 00:02:00 1096.460463\n", "0 days 00:03:00 1096.460463\n", "0 days 00:04:00 1096.460463\n", - "Name: GTI, dtype: float64\n" + "Name: GTI, dtype: object\n" ] }, { @@ -173,7 +173,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjoAAAGzCAYAAAAmH71NAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA+SElEQVR4nO3deXRTdf7/8Ve6pWvSsrSlrBUd9hEFKQUURyplcQXBapVFBEZZBhAXRimgYhVcUET4MTMCKrgwM+6CVkBwoCAiIAIiKlAW2yrQBlAotJ/fH5j7JbSFoi2B6/NxTs4h935y7/u+ubl95SY3cRhjjAAAAGwowN8FAAAAVBWCDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2Czh/cJ598IofDoU8++cSa1q9fPzVo0MBvNeHcUNZ+4HA4NH78eL/Uc64bP368HA5HlS2/rOfquaBBgwbq16/faccdPHhQd955p+Lj4+VwODRixIgqrw2QCDrnpdmzZ8vhcJR5e+CBB85aHSUlJXrppZeUlJSkatWqKSoqSn/605/Up08frVy58qzVUZ4VK1Zo/PjxKigo8HcpZ8ThcGjo0KH+LsP2PB6PJkyYoIsvvliRkZEKCwtT8+bNdf/992vPnj3+Lq9SffDBB34PqI899phmz56tu+66Sy+//LJuv/12v9ZzOiNHjtSll16qatWqKTw8XE2aNNH48eN18ODBUz5u4sSJcjgcat68eZnzV6xYoQ4dOig8PFzx8fEaPnz4aZeJ3yfI3wXgt3v44YeVmJjoM628J1dVGD58uKZNm6brr79e6enpCgoK0pYtW7RgwQJdcMEFatu27VmrpSwrVqzQhAkT1K9fP0VHR/u1Frv45ZdfFBR0/h82vv/+e6WkpCgnJ0e9evXSoEGDFBISoi+//FL/+te/9Oabb+qbb77xd5mV5oMPPtC0adP8GnYWL16stm3baty4cX6r4UysXr1al19+ufr376/Q0FCtXbtWjz/+uD7++GMtW7ZMAQGlzxPs2rVLjz32mCIiIspc5rp169SpUyc1adJETz/9tHbt2qUnn3xSW7du1YIFC6p6k/6wzv8j1h9Y165d1bp1a7+sOy8vTy+88IIGDhyomTNn+sybMmWKfvzxR7/U9VuVlJSoqKhIoaGh/i6lQg4fPqyQkJAyD7aHDh0q90D7e50v/TmVY8eOqUePHsrLy9Mnn3yiDh06+MyfOHGinnjiCT9VZ1/5+flq2rTpacedat8+m/73v/+VmtawYUONHj1an332WZkv5EaPHq22bduquLhYP/30U6n5f//73xUTE6NPPvlELpdL0vG3/gYOHKiPPvpInTt3rvwNAW9d2VV5n6Wo6Pvpp7Nt2zYZY9S+ffsy1x0bG2vd977VtmzZMg0ePFjVq1eXy+VSnz59tH///lKPX7BggS6//HJFREQoKipK3bt318aNG0uN+/rrr9W7d2/VrFlTYWFhatSokR588EFJxz8vce+990qSEhMTrbf2tm/fbtU4dOhQzZ07V82aNZPT6dTChQvL/RzE9u3b5XA4NHv2bGtav379FBkZqZycHF1zzTWKjIxU7dq1NW3aNEnShg0bdNVVVykiIkL169fXvHnzzqjHXt6aXnvtNT300EOqXbu2wsPD5fF4rBq+++47devWTVFRUUpPT5ckffrpp+rVq5fq1asnp9OpunXrauTIkfrll19KreOtt95S8+bNFRoaqubNm+vNN98ss5aT96sdO3bo7rvvVqNGjRQWFqbq1aurV69eVp+9vPvA8uXLNWrUKNWsWVMRERG68cYbywzFCxYsUMeOHRUVFSWXy6XLLrusVP9WrVqlLl26yO12Kzw8XB07dtTy5ctP28///Oc/Wr9+vR588MFSIUeSXC6XJk6caN0/kz6W5ZVXXlGbNm0UHh6umJgYXXHFFfroo4+s+b/nuVqR2vr162ftkye+ze1VUlKiKVOmqFmzZgoNDVVcXJwGDx5c6rlpjNGjjz6qOnXqKDw8XH/5y1/KfF6ezLv/btu2Te+//77Pc/FU+7YkzZ8/X61atVJYWJhq1Kih2267Tbt37/ZZ/tl6HkqyPrNW1tvhy5Yt07///W9NmTKlzMd6PB5lZWXptttus0KOJPXp00eRkZF64403Trlub6/eeOMNTZw4UXXq1FFoaKg6deqkb7/91mfslVdeqebNm+vLL79Ux44dFR4ergsvvFD//ve/JUlLly5VUlKSddz8+OOPK96E8xBndM5jhYWFpV411KhR46ysu379+pKOH4h69eql8PDw0z5m6NChio6O1vjx47VlyxZNnz5dO3bssJ7AkvTyyy+rb9++Sk1N1RNPPKGff/5Z06dPV4cOHbR27VrrQPPll1/q8ssvV3BwsAYNGqQGDRrou+++07vvvquJEyeqR48e+uabb/Tqq6/qmWeesfpSs2ZNq57FixfrjTfe0NChQ1WjRg01aNDgjD/PU1xcrK5du+qKK67QpEmTNHfuXA0dOlQRERF68MEHlZ6erh49emjGjBnq06ePkpOTS73dWFGPPPKIQkJCNHr0aB05ckQhISGSjp+hSE1NVYcOHfTkk09a/xfz58/Xzz//rLvuukvVq1fXZ599pqlTp2rXrl2aP3++tdyPPvpIPXv2VNOmTZWZmam9e/eqf//+qlOnzmlrWr16tVasWKG0tDTVqVNH27dv1/Tp03XllVdq06ZNpfaLYcOGKSYmRuPGjdP27ds1ZcoUDR06VK+//ro1Zvbs2brjjjvUrFkzjRkzRtHR0Vq7dq0WLlyoW2+9VdLx/7uuXbuqVatWGjdunAICAjRr1ixdddVV+vTTT9WmTZtya37nnXckqcKfEaloH8syYcIEjR8/Xu3atdPDDz+skJAQrVq1SosXL66UV+8VqW3w4MHas2ePsrKy9PLLL5daxuDBgzV79mz1799fw4cP17Zt2/T8889r7dq1Wr58uYKDgyVJGRkZevTRR9WtWzd169ZNX3zxhTp37qyioqJT1tikSRO9/PLLGjlypOrUqaN77rlH0vHnojcQl7Vve2u67LLLlJmZqby8PD377LNavny51q5d6/N2dFU9D48dO6aCggIVFRXpq6++0kMPPaSoqKhS+1dxcbGGDRumO++8Uy1atChzWRs2bNCxY8dKnYUPCQlRy5YttXbt2tPWI0mPP/64AgICNHr0aBUWFmrSpElKT0/XqlWrfMbt379f11xzjdLS0tSrVy9Nnz5daWlpmjt3rkaMGKG//vWvuvXWWzV58mTddNNN2rlzp6KioipUw3nH4Lwza9YsI6nMm5ckM27cuFKPrV+/vunbt691f8mSJUaSWbJkiTWtb9++pn79+qeto0+fPkaSiYmJMTfeeKN58sknzebNm8utt1WrVqaoqMiaPmnSJCPJvP3228YYYw4cOGCio6PNwIEDfR6fm5tr3G63z/QrrrjCREVFmR07dviMLSkpsf49efJkI8ls27atVE2STEBAgNm4caPP9LL6YYwx27ZtM5LMrFmzrGl9+/Y1ksxjjz1mTdu/f78JCwszDofDvPbaa9b0r7/+utz/k7JqGzJkSKmaLrjgAvPzzz/7jPXW8MADD5RazsljjTEmMzPTOBwOn761bNnS1KpVyxQUFFjTPvroIyOp1H5w8jaUtY7s7Gwjybz00kvWNO8+kJKS4vN/NHLkSBMYGGitu6CgwERFRZmkpCTzyy+/+CzX+7iSkhJz0UUXmdTUVJ9l/fzzzyYxMdFcffXVpWo60SWXXGLcbvcpx5yoon0cN26cz3Nw69atJiAgwNx4442muLi4zG0x5vc9Vyta25AhQ0xZh/tPP/3USDJz5871mb5w4UKf6fn5+SYkJMR0797dp/a///3vRpJPneWpX7++6d69u8+08vbtoqIiExsba5o3b+6zH7z33ntGksnIyLCmVdXz0Jj/25e9t0aNGpU6NhhjzPPPP2/cbrfJz883xhjTsWNH06xZM58x8+fPN5LMsmXLSj2+V69eJj4+/pS1eHvVpEkTc+TIEWv6s88+aySZDRs2WNM6duxoJJl58+ZZ07zbHhAQYFauXGlN//DDD0sd2+yGt67OY9OmTVNWVpbP7WyaNWuWnn/+eSUmJurNN9/U6NGj1aRJE3Xq1KnU6WVJGjRokPXqUJLuuusuBQUF6YMPPpAkZWVlqaCgQLfccot++ukn6xYYGKikpCQtWbJEkvTjjz9q2bJluuOOO1SvXj2fdZzJ5b0dO3as0GcGTufOO++0/h0dHa1GjRopIiJCvXv3tqY3atRI0dHR+v7773/zevr27auwsLAy5911112lpp049tChQ/rpp5/Url07GWOsV48//PCD1q1bp759+8rtdlvjr7766gr15sR1HD16VHv37tWFF16o6OhoffHFF6XGDxo0yOf/6PLLL1dxcbF27Ngh6fg+cODAAT3wwAOlPg/kfdy6deu0detW3Xrrrdq7d6+1nxw6dEidOnXSsmXLVFJSUm7NHo/njF65VqSPZXnrrbdUUlKijIyMUp83qazL0H9rbV7z58+X2+3W1Vdf7fOca9WqlSIjI63n3Mcff6yioiINGzbMp/bKukT85H37888/V35+vu6++26f/aB79+5q3Lix3n///VLLqIrnYdOmTZWVlaW33npL9913nyIiIkpdIbV3715lZGRo7NixPmeMT+Z9O9HpdJaaFxoaWuG3Qvv372+dzZWOP4ckldqmyMhIpaWlWfe9296kSRMlJSVZ073//j3HpnMdb12dx9q0aeO3DyNLUkBAgIYMGaIhQ4Zo7969Wr58uWbMmKEFCxYoLS1Nn376qc/4iy66yOd+ZGSkatWqZZ2+3rp1qyTpqquuKnN93ve1vU/I33uF2W99C+lEoaGhpQ5ubrdbderUKfXHzO12l/mZpIoqr96goKAy32bKyclRRkaG3nnnnVLrLSwslCQrYJz8fyMdPzCWFVZO9MsvvygzM1OzZs3S7t27ZYwptY4TnRxMY2JiJMmq77vvvpN06v9b737St2/fcscUFhZayz6Zy+U6o4N6RfpYlu+++04BAQGVEqYruzavrVu3qrCw0OczdSfKz8+XVP5+UrNmzXL7fCZO3re962vUqFGpsY0bNy71QeGqeh66XC6lpKRIkq6//nrNmzdP119/vb744gtdfPHFkqSHHnpI1apV07Bhw065LG+QO3LkSKl5hw8fLvdFzMlO9xzyKm/b69atW2paWY+3E4LOH0xxcXGVLLd69eq67rrrdN111+nKK6/U0qVLtWPHDuuzPBXhfRX+8ssvKz4+vtT8yr6suawDS3mvtMvrW2Bg4BlNPzEInKnyDoROp7PUGYPi4mJdffXV2rdvn+6//341btxYERER2r17t/r163fKMx5nYtiwYZo1a5ZGjBih5ORkud1uORwOpaWllbmOyuiLd7mTJ09Wy5YtyxwTGRlZ7uMbN26stWvXaufOnaUO+ic7W30sb91VXVtJSYliY2M1d+7cMuef6gxFZaroH/nynK3nYY8ePXT77bfrtdde08UXX6ytW7dq5syZmjJlis93Lx0+fFhHjx7V9u3b5XK5VK1aNdWqVUvS8bOoJ/vhhx+UkJBQoRoquk1n89h0riPo2FRMTEypD9YWFRWV+SSrbK1bt9bSpUv1ww8/+ASdrVu36i9/+Yt1/+DBg/rhhx/UrVs3Sccv3ZSk2NhY61VUWS644AJJ0ldffXXKOn7L2wPeV0cn9877CvN8sWHDBn3zzTeaM2eO+vTpY00/+e1N7/+P9yzJibZs2XLa9fz73/9W37599dRTT1nTDh8+/Ju/pNG7D3z11Ve68MILTznmxFfbZ+Laa6/Vq6++qldeeUVjxow55diK9rG8OktKSrRp06ZyA5n025+rZ1Jbec+Fhg0b6uOPP1b79u1PGTZO3E+8zz/p+NvIVXEmwLu+LVu2lDrDu2XLljN6AVWZjhw5opKSEuts2e7du1VSUqLhw4dr+PDhpcYnJibqb3/7m6ZMmaLmzZsrKChIn3/+uc/baUVFRVq3bp3PNFQuPqNjUw0bNtSyZct8ps2cObPSzujk5uZq06ZNpaYXFRVp0aJFCggIKPWHaubMmTp69Kh1f/r06Tp27Ji6du0qSUpNTZXL5dJjjz3mM87LexlyzZo1dcUVV+jFF19UTk6Oz5gTX5V4v0vmTP7o1q9fX4GBgaV698ILL1R4GecC76u2E/thjNGzzz7rM65WrVpq2bKl5syZ4/NWR1ZWVpn/v2Wt5+RXglOnTv3N+1nnzp0VFRWlzMxMHT582Geedz2tWrVSw4YN9eSTT5b5jbKn+w6nm266SS1atNDEiROVnZ1dav6BAwesrymoaB/LcsMNNyggIEAPP/xwqbMrJy7vtz5Xz6S28p4LvXv3VnFxsR555JFSj/FecSRJKSkpCg4O1tSpU33WV96l1L9X69atFRsbqxkzZvi81bNgwQJt3rxZ3bt3r5L1ehUUFJR5DPrnP/9p1SfJ+iqGk2/NmjVTvXr19Oabb2rAgAGSjr9FlJKSoldeeUUHDhywlvnyyy/r4MGD6tWrV5Vu0x8ZZ3Rs6s4779Rf//pX9ezZU1dffbXWr1+vDz/8sNIuP9+1a5fatGmjq666Sp06dVJ8fLzy8/P16quvav369RoxYkSpdRUVFalTp07q3bu3tmzZohdeeEEdOnTQddddJ+n4K/Tp06fr9ttv16WXXqq0tDTVrFlTOTk5ev/999W+fXs9//zzkqTnnntOHTp00KWXXqpBgwYpMTFR27dv1/vvv69169ZJOv4HUZIefPBBpaWlKTg4WNdee+0pv0zP7XarV69emjp1qhwOhxo2bKj33nvP+qzC+aJx48bWl5vt3r1bLpdL//nPf8p89Z2Zmanu3burQ4cOuuOOO7Rv3z5NnTpVzZo1O+1X019zzTV6+eWX5Xa71bRpU2VnZ+vjjz9W9erVf1PdLpdLzzzzjO68805ddtlluvXWWxUTE6P169fr559/1pw5cxQQEKB//vOf6tq1q5o1a6b+/furdu3a2r17t5YsWSKXy6V333233HUEBwfrv//9r1JSUnTFFVeod+/eat++vYKDg7Vx40bNmzdPMTExmjhx4hn18WQXXnihHnzwQT3yyCO6/PLL1aNHDzmdTq1evVoJCQnKzMyU9Nufq2dSm/e5MHz4cKWmpiowMFBpaWnq2LGjBg8erMzMTK1bt06dO3dWcHCwtm7dqvnz5+vZZ5/VTTfdpJo1a2r06NHKzMzUNddco27dumnt2rVasGBBlXylRXBwsJ544gn1799fHTt21C233GJdXt6gQQONHDmy0td5ok8++UTDhw/XTTfdpIsuukhFRUX69NNP9d///letW7fWbbfdJun413nccMMNpR7vDYAnz5s4caLatWunjh07atCgQdq1a5eeeuopde7cWV26dKnSbfpDO7sXeaEyeC/VXb16dbljiouLzf33329q1KhhwsPDTWpqqvn2228r7fJyj8djnn32WZOammrq1KljgoODTVRUlElOTjb/+Mc/fC5B9da7dOlSM2jQIBMTE2MiIyNNenq62bt3b6llL1myxKSmphq3221CQ0NNw4YNTb9+/cznn3/uM+6rr74yN954o4mOjjahoaGmUaNGZuzYsT5jHnnkEVO7dm0TEBDgc6m5TrqE+0Q//vij6dmzpwkPDzcxMTFm8ODB5quvvirz8vKIiIhSjy/r0lJjyr68tiwn1+b9P5o/f36pseXVYIwxmzZtMikpKSYyMtLUqFHDDBw40Kxfv77MS0n/85//mCZNmhin02maNm1q/vvf/5a5H+ikS3P3799v+vfvb2rUqGEiIyNNamqq+frrr0vtZ+Xts+Vdzv/OO++Ydu3ambCwMONyuUybNm3Mq6++6jNm7dq1pkePHqZ69erG6XSa+vXrm969e5tFixaV2Y+T7d+/32RkZJgWLVqY8PBwExoaapo3b27GjBljfvjhhzPu48mXl3u9+OKL5pJLLjFOp9PExMSYjh07mqysLGv+73muVrS2Y8eOmWHDhpmaNWsah8NRqs6ZM2eaVq1ambCwMBMVFWVatGhh7rvvPrNnzx6fOidMmGBq1aplwsLCzJVXXmm++uqrUnWW51SXl5e1bxtjzOuvv271rlq1aiY9Pd3s2rXLZ0xVPA+//fZb06dPH3PBBReYsLAwExoaapo1a2bGjRtnDh48eLpNLXfdxhy/pL9du3YmNDTU1KxZ0wwZMsR4PJ7TLrO8XpX11Rdnuu2nOh7agcMYG38CCecE7xd/rV692q9XiQEA/nj4jA4AALAtgg4AALAtgg4AALAtPqMDAABsizM6AADAtgg6AADAtv7wXxhYUlKiPXv2KCoqqtJ+URgAAFQtY4wOHDighISEUr/3d6I/fNDZs2fPaX/YDwAAnJt27typOnXqlDv/Dx90oqKiJB1vlMvl8nM1AACgIjwej+rWrWv9HS/PHz7oeN+ucrlcBB0AAM4zp/vYCR9GBgAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtvWH/1FPr8wFmxUaHunvMgAAQAUc/vlghcYRdH41d2WOApzh/i4DAABUQMmRnys0jqDzq/SkeqoW4/Z3GQAAoAIOHzqojCmnH+cwxpgqr+Yc5vF45Ha79d2ufF1Qu6a/ywEAABXg/ftdWFgol8tV7jg+jAwAAGyLoAMAAGyLoAMAAGyLoAMAAGyLoAMAAGyLoAMAAGyLoAMAAGyLoAMAAGyLoAMAAGyLoAMAAGyLoAMAAGyLoPMrh8PfFQAAgMpG0AEAALZF0AEAALZF0AEAALZF0AEAALZF0AEAALZF0AEAALZF0AEAALZF0AEAALZF0AEAALZF0AEAALZF0PkVvwABAID9VFnQWbZsma699lolJCTI4XDorbfe8plvjFFGRoZq1aqlsLAwpaSkaOvWrT5j9u3bp/T0dLlcLkVHR2vAgAE6ePCgz5gvv/xSl19+uUJDQ1W3bl1NmjSpqjYJAACcZ6os6Bw6dEgXX3yxpk2bVub8SZMm6bnnntOMGTO0atUqRUREKDU1VYcPH7bGpKena+PGjcrKytJ7772nZcuWadCgQdZ8j8ejzp07q379+lqzZo0mT56s8ePHa+bMmVW1WQAA4HxizgJJ5s0337Tul5SUmPj4eDN58mRrWkFBgXE6nebVV181xhizadMmI8msXr3aGrNgwQLjcDjM7t27jTHGvPDCCyYmJsYcOXLEGnP//febRo0aVbi2wsJCI8ls253/WzcPAACcZd6/34WFhacc55fP6Gzbtk25ublKSUmxprndbiUlJSk7O1uSlJ2drejoaLVu3doak5KSooCAAK1atcoac8UVVygkJMQak5qaqi1btmj//v1lrvvIkSPyeDw+NwAAYE9+CTq5ubmSpLi4OJ/pcXFx1rzc3FzFxsb6zA8KClK1atV8xpS1jBPXcbLMzEy53W7rVrdu3d+/QQAA4Jz0h7vqasyYMSosLLRuO3fu9HdJAACgivgl6MTHx0uS8vLyfKbn5eVZ8+Lj45Wfn+8z/9ixY9q3b5/PmLKWceI6TuZ0OuVyuXxuAADAnvwSdBITExUfH69FixZZ0zwej1atWqXk5GRJUnJysgoKCrRmzRprzOLFi1VSUqKkpCRrzLJly3T06FFrTFZWlho1aqSYmJiztDUAAOBcVWVB5+DBg1q3bp3WrVsn6fgHkNetW6ecnBw5HA6NGDFCjz76qN555x1t2LBBffr0UUJCgm644QZJUpMmTdSlSxcNHDhQn332mZYvX66hQ4cqLS1NCQkJkqRbb71VISEhGjBggDZu3KjXX39dzz77rEaNGlVVmwUAAM4nVXXZ15IlS4ykUre+ffsaY45fYj527FgTFxdnnE6n6dSpk9myZYvPMvbu3WtuueUWExkZaVwul+nfv785cOCAz5j169ebDh06GKfTaWrXrm0ef/zxM6qTy8sBADj/VPTycocxxvgxZ/mdx+OR2+3Wtt35apBQ09/lAACACvD+/S4sLDzl523/cFddlcvBr10BAGA3BB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBJ1f8QMQAADYD0EHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkHnVw5+7AoAANsh6AAAANsi6AAAANsi6AAAANsi6AAAANsi6AAAANsi6AAAANsi6AAAANsi6AAAANsi6AAAANsi6AAAANsi6AAAANsi6PzKIX7sCgAAuyHoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoePELEAAA2A5BBwAA2BZBBwAA2BZBBwAA2Jbfgk5xcbHGjh2rxMREhYWFqWHDhnrkkUdkjLHGGGOUkZGhWrVqKSwsTCkpKdq6davPcvbt26f09HS5XC5FR0drwIABOnjw4NneHAAAcA7yW9B54oknNH36dD3//PPavHmznnjiCU2aNElTp061xkyaNEnPPfecZsyYoVWrVikiIkKpqak6fPiwNSY9PV0bN25UVlaW3nvvPS1btkyDBg3yxyYBAIBzjMOceArlLLrmmmsUFxenf/3rX9a0nj17KiwsTK+88oqMMUpISNA999yj0aNHS5IKCwsVFxen2bNnKy0tTZs3b1bTpk21evVqtW7dWpK0cOFCdevWTbt27VJCQsJp6/B4PHK73crJ/Ul146pXzcYCAIBK5f37XVhYKJfLVe44v53RadeunRYtWqRvvvlGkrR+/Xr973//U9euXSVJ27ZtU25urlJSUqzHuN1uJSUlKTs7W5KUnZ2t6OhoK+RIUkpKigICArRq1aoy13vkyBF5PB6fGwAAsKcgf634gQcekMfjUePGjRUYGKji4mJNnDhR6enpkqTc3FxJUlxcnM/j4uLirHm5ubmKjY31mR8UFKRq1apZY06WmZmpCRMmVPbmAACAc5Dfzui88cYbmjt3rubNm6cvvvhCc+bM0ZNPPqk5c+ZU6XrHjBmjwsJC67Zz584qXR8AAPAfv53Ruffee/XAAw8oLS1NktSiRQvt2LFDmZmZ6tu3r+Lj4yVJeXl5qlWrlvW4vLw8tWzZUpIUHx+v/Px8n+UeO3ZM+/btsx5/MqfTKafTWQVbBAAAzjV+O6Pz888/KyDAd/WBgYEqKSmRJCUmJio+Pl6LFi2y5ns8Hq1atUrJycmSpOTkZBUUFGjNmjXWmMWLF6ukpERJSUlnYSsAAMC5zG9ndK699lpNnDhR9erVU7NmzbR27Vo9/fTTuuOOOyRJDodDI0aM0KOPPqqLLrpIiYmJGjt2rBISEnTDDTdIkpo0aaIuXbpo4MCBmjFjho4ePaqhQ4cqLS2tQldcncjBb10BAGA7fgs6U6dO1dixY3X33XcrPz9fCQkJGjx4sDIyMqwx9913nw4dOqRBgwapoKBAHTp00MKFCxUaGmqNmTt3roYOHapOnTopICBAPXv21HPPPeePTQIAAOcYv32PzrnCex3+zryfVCeW79EBAOB8cM5/jw4AAEBVI+gAAADbIugAAADbIugAAADbIugAAADbIugAAADbIugAAADbIugAAADbIuj8il+AAADAfgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6v3I4+LUrAADshqADAABsi6ADAABsi6ADAABsi6ADAABsi6ADAABsi6ADAABsi6ADAABsi6ADAABsi6ADAABsi6ADAABsi6DzK34AAgAA+yHoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLo/MrBj10BAGA7BB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbBB0AAGBbfg06u3fv1m233abq1asrLCxMLVq00Oeff27NN8YoIyNDtWrVUlhYmFJSUrR161afZezbt0/p6elyuVyKjo7WgAEDdPDgwbO9KQAA4Bzkt6Czf/9+tW/fXsHBwVqwYIE2bdqkp556SjExMdaYSZMm6bnnntOMGTO0atUqRUREKDU1VYcPH7bGpKena+PGjcrKytJ7772nZcuWadCgQf7YJAAAcI5xGGOMP1b8wAMPaPny5fr000/LnG+MUUJCgu655x6NHj1aklRYWKi4uDjNnj1baWlp2rx5s5o2barVq1erdevWkqSFCxeqW7du2rVrlxISEk5bh8fjkdvt1g8/7lV8jWqVt4EAAKDKeP9+FxYWyuVylTvOb2d03nnnHbVu3Vq9evVSbGysLrnkEv3jH/+w5m/btk25ublKSUmxprndbiUlJSk7O1uSlJ2drejoaCvkSFJKSooCAgK0atWqMtd75MgReTwenxsAALAnvwWd77//XtOnT9dFF12kDz/8UHfddZeGDx+uOXPmSJJyc3MlSXFxcT6Pi4uLs+bl5uYqNjbWZ35QUJCqVatmjTlZZmam3G63datbt64kySF+7AoAALvxW9ApKSnRpZdeqscee0yXXHKJBg0apIEDB2rGjBlVut4xY8aosLDQuu3cubNK1wcAAPzHb0GnVq1aatq0qc+0Jk2aKCcnR5IUHx8vScrLy/MZk5eXZ82Lj49Xfn6+z/xjx45p37591piTOZ1OuVwunxsAALAnvwWd9u3ba8uWLT7TvvnmG9WvX1+SlJiYqPj4eC1atMia7/F4tGrVKiUnJ0uSkpOTVVBQoDVr1lhjFi9erJKSEiUlJZ2FrQAAAOeyIH+teOTIkWrXrp0ee+wx9e7dW5999plmzpypmTNnSpIcDodGjBihRx99VBdddJESExM1duxYJSQk6IYbbpB0/AxQly5drLe8jh49qqFDhyotLa1CV1wBAAB781vQueyyy/Tmm29qzJgxevjhh5WYmKgpU6YoPT3dGnPffffp0KFDGjRokAoKCtShQwctXLhQoaGh1pi5c+dq6NCh6tSpkwICAtSzZ08999xz/tgkAABwjvHb9+icK7zX4ef+uE9xNWJO/wAAAOB35/z36AAAAFQ1gg4AALAtgg4AALAtgg4AALAtgs6vHPwCBAAAtkPQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQAQAAtkXQ+ZXD4e8KAABAZSPoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLo/MohfuwKAAC7IegAAADbIugAAADbIugAAADbIugAAADbIugAAADbIugAAADbIugAAADbIugAAADbIugAAADbIugAAADbOmeCzuOPPy6Hw6ERI0ZY0w4fPqwhQ4aoevXqioyMVM+ePZWXl+fzuJycHHXv3l3h4eGKjY3Vvffeq2PHjp3l6gEAwLnonAg6q1ev1v/7f/9Pf/7zn32mjxw5Uu+++67mz5+vpUuXas+ePerRo4c1v7i4WN27d1dRUZFWrFihOXPmaPbs2crIyDjjGhz81BUAALbj96Bz8OBBpaen6x//+IdiYmKs6YWFhfrXv/6lp59+WldddZVatWqlWbNmacWKFVq5cqUk6aOPPtKmTZv0yiuvqGXLlurataseeeQRTZs2TUVFRf7aJAAAcI7we9AZMmSIunfvrpSUFJ/pa9as0dGjR32mN27cWPXq1VN2drYkKTs7Wy1atFBcXJw1JjU1VR6PRxs3bixzfUeOHJHH4/G5AQAAewry58pfe+01ffHFF1q9enWpebm5uQoJCVF0dLTP9Li4OOXm5lpjTgw53vneeWXJzMzUhAkTKqF6AABwrvPbGZ2dO3fqb3/7m+bOnavQ0NCztt4xY8aosLDQuu3cufOsrRsAAJxdfgs6a9asUX5+vi699FIFBQUpKChIS5cu1XPPPaegoCDFxcWpqKhIBQUFPo/Ly8tTfHy8JCk+Pr7UVVje+94xJ3M6nXK5XD43AABgT34LOp06ddKGDRu0bt0669a6dWulp6db/w4ODtaiRYusx2zZskU5OTlKTk6WJCUnJ2vDhg3Kz8+3xmRlZcnlcqlp06ZnfZsAAMC5xW+f0YmKilLz5s19pkVERKh69erW9AEDBmjUqFGqVq2aXC6Xhg0bpuTkZLVt21aS1LlzZzVt2lS33367Jk2apNzcXD300EMaMmSInE7nWd8mAABwbvHrh5FP55lnnlFAQIB69uypI0eOKDU1VS+88II1PzAwUO+9957uuusuJScnKyIiQn379tXDDz/sx6oBAMC5wmGMMf4uwp88Ho/cbrd+2rdf1WOi/V0OAACoAO/f78LCwlN+3tbv36MDAABQVQg6v+IXIAAAsB+CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2CDgAAsC2Czq8cDn7tCgAAuyHoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLoAAAA2yLo/IofgAAAwH4IOgAAwLYIOgAAwLYIOgAAwLYIOgAAwLYIOgAAwLYIOgAAwLYIOgAAwLYIOgAAwLYIOgAAwLYIOgAAwLYIOgAAwLYIOr9y8GNXAADYDkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkEHAADYFkHnVw5+7AoAANsh6AAAANvyW9DJzMzUZZddpqioKMXGxuqGG27Qli1bfMYcPnxYQ4YMUfXq1RUZGamePXsqLy/PZ0xOTo66d++u8PBwxcbG6t5779WxY8fO5qYAAIBzlN+CztKlSzVkyBCtXLlSWVlZOnr0qDp37qxDhw5ZY0aOHKl3331X8+fP19KlS7Vnzx716NHDml9cXKzu3burqKhIK1as0Jw5czR79mxlZGT4Y5MAAMA5xmGMMf4uQpJ+/PFHxcbGaunSpbriiitUWFiomjVrat68ebrpppskSV9//bWaNGmi7OxstW3bVgsWLNA111yjPXv2KC4uTpI0Y8YM3X///frxxx8VEhJy2vV6PB653W4VFhbK5XJV6TYCAIDKUdG/3+fMZ3QKCwslSdWqVZMkrVmzRkePHlVKSoo1pnHjxqpXr56ys7MlSdnZ2WrRooUVciQpNTVVHo9HGzduLHM9R44ckcfj8bkBAAB7OieCTklJiUaMGKH27durefPmkqTc3FyFhIQoOjraZ2xcXJxyc3OtMSeGHO9877yyZGZmyu12W7e6detW8tYAAIBzxTkRdIYMGaKvvvpKr732WpWva8yYMSosLLRuO3furPJ1AgAA/wjydwFDhw7Ve++9p2XLlqlOnTrW9Pj4eBUVFamgoMDnrE5eXp7i4+OtMZ999pnP8rxXZXnHnMzpdMrpdFbyVgAAgHOR387oGGM0dOhQvfnmm1q8eLESExN95rdq1UrBwcFatGiRNW3Lli3KyclRcnKyJCk5OVkbNmxQfn6+NSYrK0sul0tNmzY9OxsCAADOWX47ozNkyBDNmzdPb7/9tqKioqzP1LjdboWFhcntdmvAgAEaNWqUqlWrJpfLpWHDhik5OVlt27aVJHXu3FlNmzbV7bffrkmTJik3N1cPPfSQhgwZwlkbAADgv8vLy/vJhVmzZqlfv36Sjn9h4D333KNXX31VR44cUWpqql544QWft6V27Nihu+66S5988okiIiLUt29fPf744woKqliG4/JyAADOPxX9+33OfI+OvxB0AAA4/5x336MDAABQ2Qg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtgg6AADAtmwRdKZNm6YGDRooNDRUSUlJ+uyzz/xdEgAAOAec90Hn9ddf16hRozRu3Dh98cUXuvjii5Wamqr8/Hx/lwYAAPzMYYwx/i7i90hKStJll12m559/XpJUUlKiunXratiwYXrggQdKjT9y5IiOHDli3fd4PKpbt64KCwvlcrnOWt0AAOC383g8crvdp/37fV6f0SkqKtKaNWuUkpJiTQsICFBKSoqys7PLfExmZqbcbrd1q1u37tkqFwAAnGXnddD56aefVFxcrLi4OJ/pcXFxys3NLfMxY8aMUWFhoXXbuXPn2SgVAAD4QZC/CzjbnE6nnE6nv8sAAABnwXl9RqdGjRoKDAxUXl6ez/S8vDzFx8f7qSoAAHCuOK+DTkhIiFq1aqVFixZZ00pKSrRo0SIlJyf7sTIAAHAuOO/fuho1apT69u2r1q1bq02bNpoyZYoOHTqk/v37+7s0AADgZ+d90Ln55pv1448/KiMjQ7m5uWrZsqUWLlxY6gPKAADgj+e8/x6d36ui1+EDAIBzxx/ie3QAAABOhaADAABsi6ADAABsi6ADAABsi6ADAABsi6ADAABsi6ADAABsi6ADAABs67z/ZuTfy/t9iR6Px8+VAACAivL+3T7d9x7/4YPO3r17JUl169b1cyUAAOBMHThwQG63u9z5f/igU61aNUlSTk7OKRuFM+PxeFS3bl3t3LmTn9aoRPS1atDXqkFfqwZ9Pc4YowMHDighIeGU4/7wQScg4PjHlNxu9x96h6kqLpeLvlYB+lo16GvVoK9Vg76qQico+DAyAACwLYIOAACwrT980HE6nRo3bpycTqe/S7EV+lo16GvVoK9Vg75WDfp6ZhzmdNdlAQAAnKf+8Gd0AACAfRF0AACAbRF0AACAbRF0AACAbRF0AACAbf2moDNt2jQ1aNBAoaGhSkpK0meffWbNO3z4sIYMGaLq1asrMjJSPXv2VF5e3mmXOX/+fDVu3FihoaFq0aKFPvjgA5/5xhhlZGSoVq1aCgsLU0pKirZu3Xra5X7yySe69NJL5XQ6deGFF2r27NlntD1VWe++ffuUnp4ul8ul6OhoJScnq379+j51fPnll7r88svldDoVGRmpiIiIUn09VS30tXRf33rrLTkcjlK38PBw+nqKeidOnKh27dopPDxc0dHRZdaRk5Oj7t27KywszLqdvL+eahvpa9l9LWt/DQ0Npa/l1Lt9+3YNGDBAiYmJCgsLU8OGDdWtW7dSdXB8/f19HTdunIqKinzGlLW/rly58oxqqVTmDL322msmJCTEvPjii2bjxo1m4MCBJjo62uTl5RljjPnrX/9q6tataxYtWmQ+//xz07ZtW9OuXbtTLnP58uUmMDDQTJo0yWzatMk89NBDJjg42GzYsMEa8/jjjxu3223eeusts379enPdddeZxMRE88svv5S73O+//96Eh4ebUaNGmU2bNpmpU6eawMBAs3DhwgpvT1XW26VLF3PxxReblStXmvHjxxtJJikpyarD7XabmjVrmvT0dNO7d29TvXp1ExISYv7+979bfT1VLfS17L66XC4jyXz88cemT58+JiEhwcyfP9+sXLmSvp6i3oyMDPP000+bUaNGmbCwsDLraNy4sUlJSTE33XSTqVmzpnG5XKZfv35WX0+1jfS1/L5KMrNmzfLZX5cvX05fy6l3wYIFpl+/fubDDz803333nRk9erSRZFJTUzm+VmJf3377bRMbG2vuueceaxnbtm2zjq8//PCDdSsqKjqjWirTGQedNm3amCFDhlj3i4uLTUJCgsnMzDQFBQUmODjYzJ8/35q/efNmI8lkZ2eXu8zevXub7t27+0xLSkoygwcPNsYYU1JSYuLj483kyZOt+QUFBcbpdJpXX3213OXed999plmzZj7Tbr75ZpOamlqh7anKejdt2mQkmdWrV1t1XHvttcbhcJjdu3eb4uJi43a7TVhYmMnPz7f6ev/995tGjRpZfe3UqVO5tdDXsvsaFxdnJJlly5aVu7/S1/LrnTVrlgkMDCxVR/Xq1Y3D4TDffPON1dfp06cbl8tl1q9fbySZ2267rdxtpK9l9zUhIcFIMq+88kq5+yt9PXW9bdq0Me3atTOJiYlWHRxfK6feSZMmWX015v+Cztq1a39zLZXtjN66Kioq0po1a5SSkmJNCwgIUEpKirKzs7VmzRodPXrUZ37jxo1Vr149ZWdnW9MaNGig8ePHW/ezs7N9HiNJqamp1mO2bdum3NxcnzFut1tJSUk+y73yyivVr1+/Ci/3dNtTnsqoNzs7W9HR0WrdurVVR9++fRUQEKBVq1YpICBA1atXl9vt1oYNG6y+pqamasuWLYqLi1O9evV86vf21VsLfS27r+3bt5ck9ezZU0ePHtWTTz6pd955R9L/7a/0tXS9XseOHVNxcXGpOmrXrq2oqCjt3LnTZ3/1eDwqLi5WvXr1tGLFCvp6hn313v/b3/6mo0eP6rHHHtOLL74oY4y1v9LX8vvqrSMhIUHVqlWz6uD4+vv66lVYWGj19UTXXXedYmNj1aFDB+v4WtFaKtsZBZ2ffvpJxcXFiouL85keFxen3Nxc5ebmKiQkRNHR0WXO92rYsKFq1Khh3c/NzS13md753mmnWm69evVUq1at0y7X4/Hol19+Oe32lKcy6s3NzVVsbKyk/+ur94noHVNcXKzi4mKfvnqX6a3B4/FY07x9PfH/g76W7mtCQoLq1aunoUOHKjg4WFdeeaVuuOEG68lIX0+93AMHDpQ5/sT1lbe/7t+/v8y+ejwe+lpOX+Pi4lS7dm0NGTJEwcHBuvnmm3X33Xdr6tSp1nz6Wv5yvXV88MEHGjx4sDWd4+vv66skffvtt5o6dapPXyMjI/XUU09p/vz5ev/999WhQwef42tFaqlsQVWy1NNYtGhRlSz3pZdeqpLlni+8fX3hhRcqdbl262tYWJji4+N14YUXyuFw6PHHH9eePXs0efJkXXfddaXG09eq4e1rZX8I0Y59rV27tho1aiSHw6H7779fhw4d0uTJkzV8+PBSY+mrrx9++EGSdNVVV2ngwIG/eTkcB3zt3r1bXbp0Ua9evXz6WqNGDY0aNcq6f9lll53y+Ho2nNEZnRo1aigwMLDUVVR5eXmKj49XfHy8ioqKVFBQUOb88sTHx5e7TO9877TKWK7L5VJYWNhpt6cq642Pj1d+fr6k/+vrnj17tG/fPmtMYGCgAgMDffrqXaa3BpfLdcr/D/pauq9l7a9JSUn69ttvfbaFvpa93KioqDLHn7i+8vbXmJiYcreRvpbd1/L21127dunIkSP09RTL3bNnj9LS0uRwONS/f3+feRxff19f//KXv6hdu3aaOXNmuev0OvH4WpFaKtsZBZ2QkBC1atXK54xMSUmJFi1apOTkZLVq1UrBwcE+87ds2aKcnBwlJyeXu9zk5ORSZ3mysrKsxyQmJio+Pt5njMfj0apVq37Xck+3PVVZb3JysgoKCrRmzRqrjpdeekklJSVKSkpSSUmJ9u3bp8LCQv35z3+2+pqVlaVGjRopPz9fOTk5peo/sRb6WnZfy9pf161bp1q1aln7K30tv96goCAFBgaWqmP37t06cOCA6tWr57O/ulwuBQUFKScnR+3ataOvZ9jX8vbXmJgYbd++nb6WU+/u3bt15ZVXqnXr1mrdurWWLFniUwfH19/X11atWmnWrFkKCDh9jPAeXytaS6U7008vv/baa8bpdJrZs2ebTZs2mUGDBpno6GiTm5trjDl+eXm9evXM4sWLzeeff26Sk5NNcnKyzzKuuuoqM3XqVOv+8uXLTVBQkHnyySfN5s2bzbhx48q87C06Otq8/fbb5ssvvzTXX399qcv0br/9dvPAAw9Y972X6d17771m8+bNZtq0aWVepneq7SlruZVVb5cuXcwll1xiVq1aZSZMmGAcDodJSkqy6nC73aZGjRrm9ttvN7179zY1atQwTqfT/P3vf7f6emItbdu2NV27dvW5/JG+lu5reHi4mT59utm8ebO5+eabTXR0tHE4HCYjI4O+nqLeHTt2mLVr15oJEyYYp9NpQkJCzIQJE8zq1autOho3bmw6d+5sevXqZWJjY43b7Tb9+vWz+nriNrZt29b06tXL5zJo+lq6rxEREeapp54yGzZsMLfccoupVq2acTqd5s4776Sv5dS7a9cuc+GFF5pOnTqZXbt2mRkzZhin02meffZZjq+V2NcTLx/3mj17tpk3b57ZvHmz2bx5s5k4caIJCAgwL7744hnVUpnOOOgYY8zUqVNNvXr1TEhIiGnTpo1ZuXKlNe+XX34xd999t4mJiTHh4eHmxhtv9GmCMcbUr1/fjBs3zmfaG2+8Yf70pz+ZkJAQ06xZM/P+++/7zC8pKTFjx441cXFxxul0mk6dOpktW7b4jOnYsaPp27evz7QlS5aYli1bmpCQEHPBBReYWbNmndH2lLfcyqh379695pZbbjGRkZHG5XKZpKQkU7duXZ861q9fbzp06GBCQkJMRESECQsLK9VXby2STM2aNX1qoa+l+zp27FjTpEkTEx4ebqKiokxsbKyJiIigr6ept2/fvkZSqVtwcLBVx/bt203Xrl1NaGiodTu5r95tlGSio6N9tpG+lu7rM888Y1q2bGkiIyNNeHi4qV69ugkPD6evp6h31qxZZfZUEsfXKuqr1+zZs63jq8vlMm3atPH5SoSK1lKZHMYYUzXnigAAAPyL37oCAAC2RdABAAC2RdABAAC2RdABAAC2RdABAAC2RdABAAC2RdABAAC2RdABAAC2RdABAAC2RdABAAC2RdABAAC29f8BDDBNHz+Z6VYAAAAASUVORK5CYII=", + "image/png": "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", "text/plain": [ "
" ] @@ -183,7 +183,7 @@ } ], "source": [ - "gti = pvdeg.spectral.get_GTI_from_irradiance_340(chamber.setpoints[\"setpoint_irradiance_340\"])\n", + "gti = pvdeg.spectral.calc_full_from_irradiance_340(chamber.setpoints[\"setpoint_irradiance_340\"])\n", "print(gti.head())\n", "gti.plot(title=\"Full Spectrum Irradiance Calculated from 340 nm\")" ] @@ -347,7 +347,18 @@ { "data": { "text/html": [ - "
\n", + "\n", + "
\n", + "

Chamber Simulation

\n", + "\n", + "
\n", + "

\n", + " \n", + " Setpoints Dataframe\n", + "

\n", + "
\n", + "
\n", + "
\n", "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
setpoint_temperaturesetpoint_relative_humiditysetpoint_irradiance_340
0 days 00:00:0025.050.00.0
0 days 00:01:0090.030.00.55
0 days 00:02:0090.030.00.55
0 days 00:03:0090.030.00.55
0 days 00:04:0090.030.00.55
............
33 days 07:56:0085.085.00.55
33 days 07:57:0085.085.00.55
33 days 07:58:0085.085.00.55
33 days 07:59:0085.085.00.55
33 days 08:00:0085.085.00.55
\n", + "

48001 rows × 3 columns

\n", + "
\n", + "
\n", + "\n", + "
\n", + "

\n", + " \n", + " Setpoints Plot\n", + "

\n", + "
\n", + "
\n", + "

Setpoints Plot

\n", + " \"Setpoints\n", + "
\n", + "\n", + "
\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "chamber" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "f, axs = plt.subplots(nrows=1, ncols=3, figsize=(12,3))\n", "\n", @@ -145,9 +301,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating GTI...\n", + "Saved in self.setpoints as \"setpoints_irradiance_full\n" + ] + } + ], "source": [ "chamber.calc_temperatures(\n", " air_temp_0=25, \n", @@ -159,9 +324,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Chamber and Sample Temperatures for First 200 Minutes')" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plt.plot(chamber.air_temperature.values[:200], label=\"chamber air temperature\") # inital air temperature\n", "plt.plot(chamber.sample_temperature.values[:200], label=\"sample temperature\")\n", @@ -192,7 +378,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -225,9 +411,203 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
setpoint_temperaturesetpoint_relative_humiditysetpoint_irradiance_340setpoint_irradiance_fullAir TemperatureWater Vapor PressureDew Point
0 days 00:00:0025.050.00.00.025.0000001.58660313.799419
0 days 00:01:0090.030.00.551096.46046331.1855681.37894211.721883
0 days 00:02:0090.030.00.551096.46046336.7825011.89539716.501222
0 days 00:03:0090.030.00.551096.46046341.8468162.49477820.827960
0 days 00:04:0090.030.00.551096.46046346.4291973.16712224.738060
........................
33 days 07:56:0085.085.00.551096.46046385.00000049.35371681.111387
33 days 07:57:0085.085.00.551096.46046385.00000049.35371681.111387
33 days 07:58:0085.085.00.551096.46046385.00000049.35371681.111387
33 days 07:59:0085.085.00.551096.46046385.00000049.35371681.111387
33 days 08:00:0085.085.00.551096.46046385.00000049.35371681.111387
\n", + "

48001 rows × 7 columns

\n", + "
" + ], + "text/plain": [ + " setpoint_temperature setpoint_relative_humidity \\\n", + "0 days 00:00:00 25.0 50.0 \n", + "0 days 00:01:00 90.0 30.0 \n", + "0 days 00:02:00 90.0 30.0 \n", + "0 days 00:03:00 90.0 30.0 \n", + "0 days 00:04:00 90.0 30.0 \n", + "... ... ... \n", + "33 days 07:56:00 85.0 85.0 \n", + "33 days 07:57:00 85.0 85.0 \n", + "33 days 07:58:00 85.0 85.0 \n", + "33 days 07:59:00 85.0 85.0 \n", + "33 days 08:00:00 85.0 85.0 \n", + "\n", + " setpoint_irradiance_340 setpoint_irradiance_full \\\n", + "0 days 00:00:00 0.0 0.0 \n", + "0 days 00:01:00 0.55 1096.460463 \n", + "0 days 00:02:00 0.55 1096.460463 \n", + "0 days 00:03:00 0.55 1096.460463 \n", + "0 days 00:04:00 0.55 1096.460463 \n", + "... ... ... \n", + "33 days 07:56:00 0.55 1096.460463 \n", + "33 days 07:57:00 0.55 1096.460463 \n", + "33 days 07:58:00 0.55 1096.460463 \n", + "33 days 07:59:00 0.55 1096.460463 \n", + "33 days 08:00:00 0.55 1096.460463 \n", + "\n", + " Air Temperature Water Vapor Pressure Dew Point \n", + "0 days 00:00:00 25.000000 1.586603 13.799419 \n", + "0 days 00:01:00 31.185568 1.378942 11.721883 \n", + "0 days 00:02:00 36.782501 1.895397 16.501222 \n", + "0 days 00:03:00 41.846816 2.494778 20.827960 \n", + "0 days 00:04:00 46.429197 3.167122 24.738060 \n", + "... ... ... ... \n", + "33 days 07:56:00 85.000000 49.353716 81.111387 \n", + "33 days 07:57:00 85.000000 49.353716 81.111387 \n", + "33 days 07:58:00 85.000000 49.353716 81.111387 \n", + "33 days 07:59:00 85.000000 49.353716 81.111387 \n", + "33 days 08:00:00 85.000000 49.353716 81.111387 \n", + "\n", + "[48001 rows x 7 columns]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "chamber_df = chamber.chamber_conditions(tau_c=10, air_temp_0=25)\n", "chamber_df" @@ -235,9 +615,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "f, axs = plt.subplots(nrows=1, ncols=3, figsize=(12,5))\n", "\n", @@ -263,9 +654,179 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Sample TemperatureSample Relative HumidityEquilibrium Encapsulant WaterBack Encapsulant MoistureRelative Humidity Internal Cells Backside
0 days 00:00:0025.00000050.0000000.0000830.00008350.000000
0 days 00:01:0025.39892642.4028500.0000710.00008349.475518
0 days 00:02:0026.16963655.6004230.0000950.00008348.706962
0 days 00:03:0027.21725368.6771560.0001200.00008347.825648
0 days 00:04:0028.49283880.7594860.0001450.00008446.900538
..................
33 days 07:56:0085.56670883.1702360.0004280.00042883.170236
33 days 07:57:0085.56670883.1702360.0004280.00042883.170236
33 days 07:58:0085.56670883.1702360.0004280.00042883.170236
33 days 07:59:0085.56670883.1702360.0004280.00042883.170236
33 days 08:00:0085.56670883.1702360.0004280.00042883.170236
\n", + "

48001 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " Sample Temperature Sample Relative Humidity \\\n", + "0 days 00:00:00 25.000000 50.000000 \n", + "0 days 00:01:00 25.398926 42.402850 \n", + "0 days 00:02:00 26.169636 55.600423 \n", + "0 days 00:03:00 27.217253 68.677156 \n", + "0 days 00:04:00 28.492838 80.759486 \n", + "... ... ... \n", + "33 days 07:56:00 85.566708 83.170236 \n", + "33 days 07:57:00 85.566708 83.170236 \n", + "33 days 07:58:00 85.566708 83.170236 \n", + "33 days 07:59:00 85.566708 83.170236 \n", + "33 days 08:00:00 85.566708 83.170236 \n", + "\n", + " Equilibrium Encapsulant Water Back Encapsulant Moisture \\\n", + "0 days 00:00:00 0.000083 0.000083 \n", + "0 days 00:01:00 0.000071 0.000083 \n", + "0 days 00:02:00 0.000095 0.000083 \n", + "0 days 00:03:00 0.000120 0.000083 \n", + "0 days 00:04:00 0.000145 0.000084 \n", + "... ... ... \n", + "33 days 07:56:00 0.000428 0.000428 \n", + "33 days 07:57:00 0.000428 0.000428 \n", + "33 days 07:58:00 0.000428 0.000428 \n", + "33 days 07:59:00 0.000428 0.000428 \n", + "33 days 08:00:00 0.000428 0.000428 \n", + "\n", + " Relative Humidity Internal Cells Backside \n", + "0 days 00:00:00 50.000000 \n", + "0 days 00:01:00 49.475518 \n", + "0 days 00:02:00 48.706962 \n", + "0 days 00:03:00 47.825648 \n", + "0 days 00:04:00 46.900538 \n", + "... ... \n", + "33 days 07:56:00 83.170236 \n", + "33 days 07:57:00 83.170236 \n", + "33 days 07:58:00 83.170236 \n", + "33 days 07:59:00 83.170236 \n", + "33 days 08:00:00 83.170236 \n", + "\n", + "[48001 rows x 5 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "sample_df = chamber.sample_conditions(\n", " sample_temp_0=25,\n", @@ -277,9 +838,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAABIcAAAH+CAYAAAAGZG41AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOydeXgUVdaHf93ZCVkIhHSCAaJECcomaCaIIkM0KCI4yJoZFhHG0YwiIyh+LBrQKCIGEI0bm8KgjMg44KAsIioYCJvAIJthJ2FNQvaku78/kq50dVd1V3VXdd/qPu/z9AOpunXr1N3r1Lnn6MxmsxkEQRAEQRAEQRAEQRCEX6L3tgAEQRAEQRAEQRAEQRCE9yDlEEEQBEEQBEEQBEEQhB9DyiGCIAiCIAiCIAiCIAg/hpRDBEEQBEEQBEEQBEEQfgwphwiCIAiCIAiCIAiCIPwYUg4RBEEQBEEQBEEQBEH4MaQcIgiCIAiCIAiCIAiC8GNIOUQQBEEQBEEQBEEQBOHHkHKIIAiCIAiCIAiCIAjCjyHlEEEQBEEQBEEQBEEQhB9DyiGCIAiCIAiCIAjCI2zfvh0DBw5EQkICdDod1q1bxztvNpsxc+ZMxMfHIywsDOnp6Th+/DgvzbVr15CZmYnIyEhER0dj/PjxKC8v9+BTEITvQcohgiAIgiAIgiAIwiNUVFSga9euWLx4seD5uXPnYuHChcjLy0N+fj7Cw8ORkZGB6upqLk1mZiYOHz6MTZs2Yf369di+fTsmTpzoqUcgCJ9EZzabzd4WwpuYTCZcuHABERER0Ol03haHIFTDbDbjxo0bSEhIgF7Phl6Y+h/hL7DY/wDqg4T/wGIfpP5H+AuO+p9Op8NXX32FwYMHc2kTEhLwj3/8Ay+88AIAoLS0FHFxcVi2bBlGjBiBI0eOoFOnTti9ezd69uwJANi4cSMefvhhnDt3DgkJCZLkoj5I+AtS58BAD8rEJBcuXEBiYqK3xSAIj3H27FncdNNN3hYDAPU/wv9gqf8B1AcJ/4OlPkj9j/A3pPS/wsJCFBUVIT09nTsWFRWF1NRU7Ny5EyNGjMDOnTsRHR3NKYYAID09HXq9Hvn5+XjssccE866pqUFNTQ339/nz59GpUyc3n4ogtIOzPuj3yqGIiAgADQUVGRnpZWkIQj3KysqQmJjItXkWoP5H+Ass9j+A+iDhP7DYB6n/Ef6CnP5XVFQEAIiLi+Mdj4uL484VFRWhdevWvPOBgYGIiYnh0giRk5ODV1991e449UHC15HaB/1eOWQxIYyMjKRBgfALWDKbpf5H+Bss9T+A+iDhf7DUB6n/Ef6Gt/vftGnTMHnyZO5vywsz9UHCX3DWB9nYdE0QBEEQBEEQBEH4NQaDAQBQXFzMO15cXMydMxgMuHTpEu98fX09rl27xqURIiQkhFMEkUKIIOwh5RBBEARBEARBEAThdZKSkmAwGLBlyxbuWFlZGfLz85GWlgYASEtLQ0lJCfbs2cOl2bp1K0wmE1JTUz0uM0H4Cn6/rYwgCIIgCIIgCILwDOXl5Thx4gT3d2FhIfbv34+YmBi0bdsWkyZNwpw5c5CcnIykpCTMmDEDCQkJXESzlJQU9O/fHxMmTEBeXh7q6uqQlZWFESNGSI5URhCEPaQcIgiNYzKZUFtb6zRdbW0t2rVrh9raWlRXV3tAMuewKBNBuEpQUBACAgK8LQZBEIRPYDQaUVdX520xCAWwXe/t3bsXo0ePBgC0a9cOCxYswIIFC/DYY48hJycHzz77LHQ6HbKzs1FWVoYePXpgw4YNAMCtF5cuXYo5c+Zg3Lhx0Ol0eOSRR/B///d/staTtA4lfAWl1qA6s9lsVkAezVJWVoaoqCiUlpbSvlNCc9TW1qKwsBAmk8lpWpPJhLNnzyIxMRF6PRs7SlmUiSDcITo6GgaDwc7hH6tzDatyEYTSsNjWWZSJBcxmM4qKilBSUuJtUQiFYHW9x6pcBOEKYmtQQPp8Q5ZDBKFRzGYzLl68iICAAEmTmtFoRFVVFdq3b8+MdQOLMhGEK5jNZlRWVnIOMuPj470sEUEQhDaxKIZat26NZs2aeT3CFeE+rK73WJWLIOSg5BqUlEMEoVHq6+tRWVmJhIQENGvWzGl6o9EIAAgNDWVmAmRRJoJwlbCwMADApUuX0Lp1a2rTBEEQMjEajZxiqGXLlt4Wh1AIVtd7rMpFEHJRag1K9nMEoVEsE1pwcLCXJSEIwoJFUUt+MgiCIORjGTulfPQiCIIgmlBiDUrKIYLQOGRuTRDsQP2RIAjCfWgsJQiCkIcS4yYphwiCIAiCIAiCIAiCIPwYUg4RBEFYodPpsG7dOm+Lgfvvvx+TJk1iJh+WOXXqFHQ6Hfbv3y+aZtu2bdDpdFz0m2XLliE6Otoj8hEEQRCEFGznKm/nwzpjx47F4MGDHaaxXQe1b98eubm5qsqlVTzZbrRYL1LamxhS1p2vvPIKunXr5lL+SkHKIYIgPMrly5fxt7/9DW3btkWzZs2QkZGBhx56CD///LO3RVMEi6LC8ouJiUGfPn3w448/qnpfsQl97dq1mD17tqr3FpssPbXISExMxMWLF3HHHXdIvmb48OE4duwY9zcLEzJBEAShXcaOHcvN/UFBQUhKSsLUqVNRXV2t6n2FPgL16tULFy9eRFRUlGr3dfRhxlMfphYsWIBly5bJumb37t2YOHEi9/ddd92Ff//7327LIveZpXzYYpV9+/Zh6NChiIuLQ2hoKJKTkzFhwgTeusqTLFu2jLf2bt68OXr06IG1a9d6RR4hbNedrELKIYIgPMqQIUOwb98+LF++HEeOHMH8+fPRp08fXL161duiKcrmzZtx8eJFbN++HQkJCXjkkUdQXFzscTliYmIQERHh8ft6koCAABgMBgQGSg/AGRYWhtatW6soFUEQBOFv9O/fHxcvXsTvv/+Od955Bx988AFmzZrlcTmCg4NhMBh83ndTVFSUbCvg2NhYn3N47skgGOvXr8cf/vAH1NTUYOXKlThy5Ag+++wzREVFYcaMGR6Tw5bIyEhcvHgRFy9exL59+5CRkYFhw4bh6NGjXpPJGq2sO0k5RBCExygpKcGPP/6IN998E3379kW7du1w++2346WXXsKjjz7KpZs/fz46d+6M8PBwJCYm4umnn0Z5eTl33mKauX79etx2221o1qwZHn/8cVRWVmL58uVo3749WrRogWeffZaL6gY0mKzOnj0bI0eORHh4ONq0aYPFixc7lPns2bMYNmwYoqOjERMTg0GDBuHUqVNOn7Vly5YwGAy444478PLLL6OsrAz5+fnc+UOHDuGhhx5C8+bNERcXh7/85S+4cuWKaH6ffvopevbsiYiICBgMBowaNQqXLl0C0PD1qW/fvgCAFi1aQKfTYezYsQD4X7JefvllpKam2uXdtWtXZGdnc39//PHHSElJQWhoKDp27Ij33nvP6fNKQcg6Jzc3F+3bt+f+tlghvf7664iLi0N0dDSys7NRX1+PKVOmICYmBjfddBOWLl3KXSP09e2bb77BrbfeirCwMPTt29euzqzNe5ctW4ZXX30VBw4c4L46LVu2DE888QQeeeQR3nV1dXVo3bo1PvnkEyWKhCAIgvAhQkJCYDAYkJiYiMGDByM9PR2bNm3izptMJuTk5CApKQlhYWHo2rUr/vWvf4nmd/XqVYwcORJt2rRBs2bN0LlzZ/zzn//kzo8dOxY//PADFixYwM1fp06d4lnulpWVISwsDP/97395eX/11VeIiIhAZWUlANfXO1IIDAzEtm3beMeio6M5qx/LPP7FF1/g3nvvRVhYGO666y4cO3YMu3fvRs+ePdG8eXM89NBDuHz5Mu/5rS2XKyoqMHr0aDRv3hzx8fF4++237WSx3r50yy23AGj4cKnT6dC+fXucOnUKer0eBQUFvOtyc3PRrl07mEwmSc/cvn17vP7663jiiScQERGBtm3b4sMPP+TOJyUlAQC6d+8OnU6H+++/nzvnaB1mKavPP/8cffr0QWhoKFauXMmVxbx58xAfH4+WLVvimWee4SmOHK0lpVBZWYlx48bh4Ycfxtdff4309HQkJSUhNTUV8+bNwwcffMCllbvOtcZsNuOVV15B27ZtERISgoSEBDz77LMOr9HpdDAYDDAYDEhOTsacOXOg1+vx66+/ynr+w4cP45FHHkFkZCQiIiJw77334uTJk4L33L17N2JjY/Hmm28CAA4cOIC+ffsiIiICkZGR6NGjB9eOhLaVvfHGG4iLi0NERATGjx8vaGWo1ppcDFIOEYSPYDabUVlb7/BXXe88jSs/s9ksScbmzZujefPmWLduHWpqakTT6fV6LFy4EIcPH8by5cuxdetWTJ06lZemsrISCxcuxOrVq7Fx40Zs27YNjz32GL755ht88803+PTTT/HBBx/YLbreeustdO3aFfv27cNLL72E5557jrdws6aurg4ZGRmIiIjAjz/+iJ9//hnNmzdH//79UVtbK+mZq6qqsGLFCgANX/KABiXZH//4R3Tv3h0FBQXYuHEjiouLMWzYMNF86urqMHv2bBw4cADr1q3DqVOnOAVQYmIivvzySwDA0aNHcfHiRSxYsMAuj8zMTOzatYs3yR0+fBi//vorRo0aBQBYuXIlZs6ciddeew1HjhzB66+/jhkzZmD58uWSnlcJtm7digsXLmD79u2YP38+Zs2ahUceeQQtWrRAfn4+nnrqKfz1r3/FuXPnBK8/e/Ys/vSnP2HgwIHYv38/nnzySbz00kui9xs+fDj+8Y9/4Pbbb+e+Og0fPhxPPvkkNm7ciIsXL3Jp169fj8rKSgwfPlzx5yYIgiDskbK+UesndX0jxKFDh7Bjxw5u7geAnJwcrFixAnl5eTh8+DCef/55/PnPf8YPP/wgmEd1dTV69OiBDRs24NChQ5g4cSL+8pe/YNeuXQAatlWlpaVhwoQJ3PyVmJjIyyMyMhKPPPIIVq1axTu+cuVKDB48GM2aNVNkvaMEs2bNwvTp07F3714EBgZi1KhRmDp1KhYsWIAff/wRJ06cwMyZM0WvnzJlCn744Qf8+9//xnfffYdt27Zh7969oul/+eUXAMAnn3yCixcvYvfu3Wjfvj3S09N5H6EAYOnSpRg7diz0eumvz2+//TZ69uyJffv24emnn8bf/vY3zpLFUocWS3PLFiip6zDLGvbIkSPIyMgAAHz//fc4efIkvv/+eyxfvhzLli3jbbtztJaUwrfffosrV67YrcktWJQfrqxzrfnyyy85y7vjx49j3bp16Ny5s2Q5jUYjV1533nknd9zZ858/fx733XcfQkJCsHXrVuzZswdPPPEE6uvr7e6xdetWPPDAA3jttdfw4osvAmhYZ990003YvXs39uzZg5deeglBQUGCMn7xxRd45ZVX8Prrr6OgoADx8fF2ih9vrMml2+ATBME0VXVGdJr5rfOE6zYrfu//ZWegWbDz4SQwMBDLli3DhAkTkJeXh+7du+O2227Ds88+i+7du3PpbB3UzZkzB0899RRv0Kyrq8P777/PffV5/PHH8emnn6K4uBjNmzdHp06d0LdvX3z//fe8F/l77rmHUxTceuut+Pnnn/HOO+/ggQcesJP3888/h8lkwscff8yZZi9duhTR0dHYtm0bHnzwQdFn7dWrF/R6PSorK2E2m9GjRw/069cPAPDuu++ie/fueP3117n0S5YsQWJiIo4dO4Zbb73VLr8nnniC+//NN9+MhQsX4q677kJ5eTmaN2+OmJgYAEDr1q1FTaxvv/12dO3aFatWreJMf1euXInU1FR06NABQMPC7O2338af/vQnAA1ftv73v//hgw8+wJgxY0Sfd/369WjevDnvmLXVlhxiYmKwcOFC6PV63HbbbZg7dy4qKyvx8ssvAwCmTZuGN954Az/99BNGjBhhd72lXVi+GN522204ePAg92XHlrCwMDRv3hyBgYEwGAzc8V69euG2227Dp59+yi2Eli5diqFDh9o9K0EQBKEOktc3KiB1fWPBMhfW19ejpqYGer0e7777LgCgpqYGr7/+OjZv3oy0tDQADfP5Tz/9hA8++AB9+vSxy69NmzZ44YUXuL///ve/49tvv8UXX3yBu+++G1FRUQgODkazZs1485ctmZmZ+Mtf/oLKyko0a9YMZWVl2LBhA7766isAyqx3rKmqqnLJj98LL7zAKTqee+45jBw5Elu2bME999wDABg/fryoj6Hy8nJ88skn+Oyzz7j11vLly3HTTTeJ3i82NhZAg1LDuvyefPJJPPXUU5g/fz5CQkKwd+9eHDx4ULZvoocffhhPP/00AODFF1/EO++8g++//x633XYbd2+LpbkFqeuwSZMmcWkstGjRAu+++y4CAgLQsWNHDBgwAFu2bMGECRMAOF9LOuP48eMAgI4dOzpM58o615ozZ87AYDAgPT0dQUFBaNu2Le6++26H15SWlnLPUFVVhaCgIHz44YfcewLg/PkXL16MqKgorF69mlPqCMn61VdfYfTo0fj444957xhnzpzBlClTuPJJTk4WlTc3Nxfjx4/H+PHjAQBz5szB5s2bedZDrq7J3YEshwiC8ChDhgzBhQsX8PXXXyMjIwN79uzBXXfdxZvsN2/ejH79+qFNmzaIiIjAX/7yF1y9epUzfQaAZs2a8Qb8uLg4tG/fnje5xcXF2ZmLWhZk1n8fOXJEUNYDBw7gxIkTiIiI4KyeYmJiUF1dLWpiauHzzz/Hvn378OWXX6JDhw5YtmwZN9EcOHAA33//PZdn8+bNuYlELN89e/Zg4MCBaNu2LSIiIrhF5JkzZxzKYUtmZib39dBsNuOf//wnMjMzATSYY588eRLjx4/nyTZnzhynz9u3b1/s37+f9/v4449lyWbh9ttv5y004+LieF+MAgIC0LJlS1FT6CNHjthtn7Otd6k8+eST3NfD4uJi/Pe//+UtLgiCIAjCgmUuzM/Px5gxYzBu3DgMGTIEAHDixAlUVlbigQce4M2xK1asEJ1jjUYjZs+ejc6dOyMmJgbNmzfHt99+K3vuf/jhhxEUFISvv/4aQINlRmRkJNLT0wG4v96xnf979uwpSz4LXbp04f4fFxcHALz5X2hdZ+HkyZOora3lzf8xMTG47bbbZMsxePBgBAQEcMqzZcuWoW/fvrxt8FKwfh7LtidH27jkrMOEyvj2229HQEAA93d8fDzvfu6uJaVa0rmyzrVm6NChqKqqws0334wJEybgq6++ErTesSYiIoJrf/v27cPrr7+Op556Cv/5z3+4NM6ef//+/bj33ntFrX0AID8/H0OHDsWnn35qZ0U+efJkPPnkk0hPT8cbb7zh8FmdrVXdWZO7A1kONfKXj/MRFBbO/a3X6fCXtHYY2DWBl+4/By7g019Ow2Tid47moYGY8Ugn3BLb9GJqNpsxe/0R/HquxO5+N8eGI+dPXRCgb3IUd+56JV75+jBKKu2dig3pcRNG3t2Wd+z73y7hg+0nUW/kyxIWHIAX+3fEHW2cRyioM5owY90hnLhUbneu801RmPlIJ687s6uoqcf/fXUQ565X2Z3r1aEVJj/A1+juP1uCt787iqpavtVCgF6Hp+6/BX1vc90ZmNzyOnGpHK9t+B9uVPMHNL1Oh9G92uGRLgm22bhMWFAA/pedIXreaDTiwIFf0bVrF97EodS95RAaGooHHngAf/zjHzFgwAC8//77mDVrFsaOHYtTp07hkUcewd/+9je89tpriImJwU8//YTx48ejtraWcyJoO3BbooPYHpO6N1yI8vJy9OjRAytXrrQ7Z/niI0ZiYiKSk5ORnJyM+vp6PPbYYzh06BBCQkJQXl6OgQMHClqyxMfH2x2rqKhARkYGMjIysHLlSsTGxuLMmTPIyMiQbe49cuRIvPjii9i7dy+qqqpw9uxZbnKz+HX66KOP7CYsZ20mPDwcHTp0QEVNPa6U1yAhOsxu25der7dbWAg5UfRE3Upl9OjReOmll7Bz507s2LEDSUlJuPfee1W/L0G4gtlsxqyvDyO5dXP8Ja29t8UhCEVwtr5R+96y0jdrhqAW8UhuG4IlS5aga9eu+OSTTzB+/Hhujt2wYQPatGnDuy4kJEQwv7feegsLFixAbm4u54tx0qRJsuf+4OBgPP7441i1ahVGjBiBVatWYfjw4VwgB3fXOxbrYwthYWG8v3U6nez537Ketj3mibk/ODgYo0ePxtKlS/GnP/0Jq1atEtyu7wy5axc567Dw8HDY4uh+SqwlLVY0v/32m8OPbnLXuQBgBnCtohY19UYkJibi6NGj2Lx5MzZt2oSnn34ab731Fn744QdRxY1er+e1wy5duuC7777Dm2++iYEDB0p6fku7ra4zorisGq0jQ+3GgFtuuQUtW7bEkiVLMGDAAJ48r7zyCkaNGoUNGzbgv//9L2bNmoXVq1fjscceEy0rMdxZk7sD08qhGzduYMaMGfjqq69w6dIldO/eHQsWLMBdd90FoHERNGsWPvroI5SUlOCee+7B+++/79CES4x9Z0ugD+F3jPKaejvl0Oz1/8OlG8K+UrredAHPWykqfj1XiiU/FwqmLTh9HaPT2vMUOEt/PoXNR4S1yedLquyUQ2/89zccLb4hmD6p1VlJyqGfTlzB6t1nRWWccO/NSIgOEzzvKb49XIR1+y8Inis4fR1P9bmZZ/Kbu/kYfjwu7PAsKEDvlnLop+OOy2vifTcjPqqpvD75qRDfH70smL6itl5R5ZBOp3No+mw06hAa2JBGzUHFFVJSUjhT3T179sBkMuHtt9/mrEe++OILxe5l2V9u/XdKSopg2jvvvBOff/45WrdujcjISJfv+fjjj2PmzJl477338Pzzz+POO+/El19+ifbt20uKsPXbb7/h6tWreOONNzhfAraOEi0+DZxt5brpppvQp08frFy5ElVVVXjggQe46AlxcXFISEjA77//zlkTyeXk5YbJzCTwcSk2NhZFRUUwm83cok+NEK4pKSnc11ELtvVuS3BwsGDZtWzZEoMHD8bSpUuxc+dOjBs3TlFZCUJJfvn9GlbsPA0ApBwifAZn6xuWqKo1orSqDjeq63FHmyi8/PLLmDx5MkaNGoVOnTohJCQEZ86cEdxCJsTPP/+MQYMG4c9//jOABofWx44dQ6dOnbg0YvOXLZmZmXjggQdw+PBhbN26FXPmzOHOKbXeESM2NpbnjPj48eM8a3AluOWWWxAUFIT8/Hy0bdvwznT9+nUcO3bMYXkHBgYKlt+TTz6JO+64A++99x7q6+vttnC5i9C6TYl1mBhS1pLOePDBB9GqVSvMnTuXs6qypqSkBNHR0bLXuQBQbzShus6I01crcWtcBMLCwjBw4EAMHDgQzzzzDDp27IiDBw/yfAg5IyAgAFVVDcYFUp6/S5cuWL58OY5dLAH0AVw/tqZVq1ZYu3Yt7r//fgwbNgxffPEFT0F066234tZbb8Xzzz+PkSNHYunSpYLKoZSUFOTn52P06NHcMeu1qpptwRFMbyt78sknsWnTJnz66ac4ePAgHnzwQaSnp+P8+fMAgLlz52LhwoXIy8tDfn4+wsPDkZGRIejp2xm9OrRE3p/vRN6f78TotHYAAKPN243JZOYUQ689dgeXvu9tsYLpL5Y2yWFJm/fnOxETHiyY/lpFg3KqZ7sWXNrpAxpeWusF3rSKyhryn5JxG5feoswSSi9EUaOMzYIDeDIGB+oFZfQGlnJsHRHCybdwZJN/GlsRLeU4rOdNXPonezdEBKgzuve1wSJLuG15BTSUl60VV1Fpw4D0x46tubTP9mtQXnq7bG/cuIHjx4/jwIEDKCgowPXr10XTnj59GgUFBXah2Ovr6/H7779j79692LdvH06dOuVwgXL16lX88Y9/xGeffYZff/0VhYWF2Lx5M+bNm4dBgwYBADp06IC6ujosWrQIv//+Oz799FPk5eUp89BoWGjNnTsXx44dw+LFi7FmzRo899xzgmkzMzPRqlUrDBo0CD/++CMKCwuxbds2PPvss6LOkIXQ6XR49tln8cYbb6CyshLPPPMMrl27hpEjR2L37t04efIkvv32W4wbN06w/Nq2bYvg4GCuTL7++mvMnj2bl6Zdu3bQ6XRYv349Ll++zIvuJvRcq1evxpo1a+wmnFdffRU5OTlYuHAhjh07hoMHD2Lp0qWYP3++5OcFgNp6+752//334/Lly5g7dy5OnjyJxYsX20VPUYKnnnoKx48fx5QpU3D06FGsWrVK1EeBhfbt26OwsBD79+/HlStXeA7Tn3zySSxfvhxHjhxRbY83QSjBjWrPhTMmCMIey9LO1GglM3ToUAQEBGDx4sWIiIjACy+8gOeffx7Lly/HyZMnsXfvXixatEjUwWxycjI2bdqEHTt24MiRI/jrX/9qtxZr37498vPzcerUKVy5ckXUMuW+++6DwWBAZmYmF2HKglLrHTH69u2LNWvWYN++fSgoKMBTTz3lcOuOKzRv3hzjx4/HlClTsHXrVhw6dEiSA+mEhARs3boVRUVFvLVwSkoK/vCHP+DFF1/EyJEj7ayh3KV169YICwvjnDWXlpYCUG4dZouUtaQzwsPD8fHHH2PDhg149NFHsXnzZpw6dQoFBQWYOnUqnnrqKQCQvc61pqbehGXLluGTTz7BoUOH8Pvvv+Ozzz5DWFgY2rVrJ3qd2WxGUVERioqKUFhYiA8//BDffvst934h5fmzsrJQVlaGyU+Nw+ED+1D4+wl8+umnnBNxC61bt8bWrVvx22+/YeTIkaivr0dVVRWysrKwbds2nD59Gj///DN2794t+gH6ueeew5IlS7B06VIcO3YMs2bNwuHDh3lp1GoLjmBWOVRVVYUvv/wSc+fOxX333YcOHTrglVdeQYcOHfD+++/DbDYjNzcX06dPx6BBg9ClSxesWLECFy5cwLp162Tfr//tBvS/I77hd7uwQzdrhcsjXRK49O1a2pv1AU0v/3cnxTTlfUe8qIlqbaPi4pEuTWl73dJKVGZL/tbpk1vLc5Jqeab7kmN5MgbqvbuVzBrLc/ZLiePke7BTnGh6y0vpwK5NddS9bQsADSaL7snSkPd9t/LLK0CkvOoF6uju9jFuSqEMJpMJzZo1476uiHH9+nWUl5cLTuK///47qqqqcOutt6JDhw64ceMGTp8+LZpX8+bNkZqainfeeQf33Xcfunbtiry8PIwfP55z2Ni1a1fMnz8fb775Ju644w6sXLkSOTk57j2sFf/4xz9QUFCA7t27Y86cOZg/fz7n/NCWZs2aYfv27Wjbti3+9Kc/ISUlhQs1KffL2pgxY1BXV4d3330XCQkJ+Pnnn2E0GvHggw+ic+fOmDRpEqKjowUXMbGxsVi2bBnWrFmDTp064Y033sC8efN4adq0aYNXX30VL730EuLi4pCVlSUqy+OPP875cLIOAQs0KEI+/vhjLF26FJ07d0afPn2wbNkyLuSqO6SkpOC9997D4sWL0bVrV+zatYvnaFMp2rZtiy+//BLr1q3j2pi1U0QhhgwZgv79+6Nv376IjY3lhQpOT09HfHw8MjIykJCgnLUfQRAE4VvYrgYDAwORlZWFuXPnoqKiArNnz8aMGTOQk5ODlJQU9O/fHxs2bBCdY6dPn44777wTGRkZuP/++2EwGOzm7RdeeAEBAQHo1KkTt1VGUDadDiNHjsSBAwfsPgwpud4R4q233kJcXBzuv/9+jBo1Ci+88ALnJkBJ3nrrLdx7770YOHAg0tPT0bt3b/To0cPhNc899xw2b96MxMREXnAUAJxLAzV8DQYGBmLhwoX44IMPkJCQwCkx1FqHSVlLSmHQoEHYsWMHgoKCMGrUKHTs2BEjR45EaWkpZ40md53Lw9zgIPyjjz7CPffcgy5dumDz5s34z3/+g5YtW4peVlZWhvj4eMTHxyMlJQVvv/02srOz8X//93+Sn79ly5bYunUrKisq8MTQRzDy4b746KOPBN+BDAYDtm7dioMHDyIzMxN6vR5Xr17F6NGjceutt2LYsGF46KGH8OqrrwrKO3z4cMyYMQNTp05Fjx49cPr0afztb3/jpVFzTS6KmVHKysrMAMybN2/mHb/nnnvMffr0MZ88edIMwLxv3z7e+fvuu8/87LPPiuZbXV1tLi0t5X5nz541AzCv2PY/Ls3Pxy+b27243vzg/B9411bV1pvbvbje3O7F9eYb1XXc8Vn/PmRu9+J681sbf+Ol//f+8+Z2L643j/hgJ+94r5wt5nYvrjfvP3Odd3zC8t3mdi+uN3/2yynu2OHzpeZ2L64395yzye5ZOk7/r7ndi+vNZ65WcMcWbD5mbvfievO0tb+KloE1y34uNLd7cb356c/28I6nzLDP21vM/+6oud2L683TvzrIHROrC7PZbP7jvO/N7V5cb9558gp37JtfL5jbvbjePPT9HW7JsvSn3xvKayW/vITqwmw2m0d9tNPc7sX15nX7znHHfjzW0L4y3uG3L7lUVVWZ//e//5mrqqokpa+vrzfv3r3bXF9fb3du9+7d5mvXrtkdr6mpMe/fv99cWVlpPnDggLmoqIg7V1lZad69e7e5vLycO1ZSUmLevXu3uaamxm2Z1KBdu3bmd955xyP38lcOnL1uPnD2uvm3i2XeFkUxbty4YY6MjDR/+eWXTtOK9cvS0lIzAHNpaalaYroEq3IRrvHd4SJubiT4sNjWWZTJ28hd27DG0aIybh4kmvD0ek8qzuTKzs42d+7c2cNS+SeWfvPr2RJvi8LJorV+7Gj8lDrfMGs5FBERgbS0NMyePRsXLlyA0WjEZ599hp07d+LixYsoKioC0OTJ3kJcXBx3ToicnBxERUVxP8ueQzHLD2usLYekWNZYrEwCA4TT2lqxWLY8BQVIqxaLRY1Q/hKdyXPPJPb8UvNRE6NTGW0c3DVu7bIuR4uPaJObD2QpL6mWVZZtZkKys1C2jjCbzSgsLITBYBA0pa2oqEBAQADPIZ7l61JFRYVgniaTCUajkfcjCFYxmUy4dOkSZs+ejejoaDz66KPeFokgCIJgGIYM7wk3KC8vx6FDh/Duu+/i73//u7fF8SvMbu/zINyBae9un376KZ544gm0adMGAQEBuPPOOzFy5Ejs2bPH5TynTZuGyZMnc3+XlZUhMTERUgJyGa38yeglXGBRDEhJCzQpHoIlKofqG5VPAW5EE7MosKQox7yFMwWWLRYlWzBPOdRwrfvbyhplkVjmFmWUO3XkLYqKiqDT6ThnxbbU1dUJRkUIDAwUjEBhyfPCBWHn4gTBGmfOnEFSUhJuuukmLFu2TLJTRYLwFtqbaQjCt/B2hF9CGbKysvDPf/4TgwcPVmVLGUGwCtMr3VtuuQU//PADKioquH2Ew4cPx8033wyDocEvUHFxMS8kXnFxMbp16yaaZ0hIiGC4SCmKB6NZnuWQRTFgm1Zs3rD4ypFiOWQ2mzmnd9ayy52SLP6ZbZ+fpamNU7BYP6cDATkLrED7cnHXcsgoIIsjhBRbWlg3VFRU4NKlS0hJSVF0oWMwGHjWfkajEb/++qti+Tvj1KlTHrsXoX3at29vZ5lIEARBEGJo8WMgYc+yZcucBrIgCF+E2W1l1oSHhyM+Ph7Xr1/nvI4nJSXBYDBgy5YtXLqysjLk5+cjLS1N9j2EBnNbszaLpY5OB+iFtgnZpXfN4kXKNjEjb4ub69XIbX1j2XLIwdYsISxKNutysVhvuRsgzGI9JrZV0BaTg61/LFNeXo66ujr8+uuvKCgoQEFBAWpra3H27FlOmRMUFGRnIWQ2m1FfXy8agUKv1yMgIID3IwiCIAiC8AVIN0QQhJZh2nLo22+/hdlsxm233YYTJ05gypQp6NixI8aNGwedTodJkyZhzpw5SE5ORlJSEmbMmIGEhAQ7L/6SsB7NRQZ2S2RIyVuKZPrKsexak+TPyOpaYd2QNC2IxXJISNnVkIv3v5qLWWBZsJXQJFCOXBkpZDkkd6ugUHoWylaMli1b2kWnOHbsGFq2bIlWrRoi6IWHh8NoNKKiooLzO1RWVsadIwiCIDwLvZgShHexXu9dLa/hnQsJDEDzUKZfvQiC8HOYHqFKS0sxbdo0nDt3DjExMRgyZAhee+01ziph6tSpqKiowMSJE1FSUoLevXtj48aNCA0NlX0vaQ6phf3ziC3G5FoOCSGWt19ZDjXKKFUhI4ROKcshEYfUzurJnTpyhqvbXoxGI2pqmhYutbW1qKysREBAAEJCQuz8q+h0OgQFBXH9KywsDJGRkTh9+jTatWsHs9mMM2fOICYmBsHBwa4/EEFoGJPlKwJBEAThMlodS60txc+XVNmd72iIRHCgJjZuEAShMZQYN5lWDg0bNgzDhg0TPa/T6ZCdnY3s7Gy37yXFB7RJxD+PGGJRtkR1HDJe8q2VQ+7oHcQsYVhyqGexbgrk+VYSl09IWdK0rcxNyyGLJZDMNmBdR0qVbFBQEHQ6HS5fvozY2FindWaJDFZdXY2AgABUVFSgsLCQO3/27FkAQHR0NG666Sa7681mM+rq6lBdXc0dS0hIwMWLF/Hbb79Bp9MhKioKcXFxvDRyZCK0j7m+FgBgMgdIbge+gNlsRm1tLS5fvgy9Xk8KUsIrMDR1E4RLBAcHQ6/X48KFC4iNjUVwcDBTa1JnGOtquXmweUjTa1Z5TT0AoLKyEqZgpl+/VIHV9R6rcvkjln4DwOvrR5ZkkYKSa1D/G51EkDLxiFkOieEsBLu4LNLzBvhWKXLnT7mh2b0BF1FNpt8e67KwPJ7RTdMhMcsh0fRm9SyHAgICcNNNN+HcuXOSHC2bTCZcuXIFp06dgr5RHqHtX3V1dTylkYXg4GDcuHEDN27csDvXrFkzAA3WR2fOnJH8DEIyEdrm0vWGL6VBATqgXL4Vp9Zp1qwZ2rZtS+2ZIAjCBfR6PZKSknDx4kVNRjctq6pDWXU9mocEILhZ0wvatdLqhjX3jRC/tBxidb3Hqlz+iGX9CADBVWFelAS4fL2Kc/7hbVnkoMQalJRDjUjxIyRX2VPvJOy5O2qKemvLIYHspRrIGJ04e2YhUI/TcpQgo+Vad5+n3kXLISHLNCXKtnnz5khOThYNHW9NeXk5BgwYgIKCAjRv3tz9mysAizIR7vHk2m0AgJtaNMPyJ1K8K4yHCQgIQGBgoKa+chMEQbBGcHAw2rZti/r6es6yQyss/bkQn/1yAY92TcBz6Unc8Zc/2IlL5TV4L/NOJBkiHeTgm7C63mNVLn/Esn4EgC3/uN9rcgDAX9f9wL3DeVsWqSi1BiXlUCNSlEMWfYxU3zdmmc6L5egKLNujdDr3toBZnonllxmz3HIXOKZTaFuZSWadNtWTeuUrNepXbW0tTp8+jeDgYJf8cqkBizIR7nH+RsNCPiTERHVKEB7G0ZZrgtASFj+HYtFPWaXKFIDzN4yoMOp5c+ClKjPO3zBCF+if6x1W13usyuWPWNaPALxeFxfLjahrNKDwtiyehuznGhF6dxfTI8h1GWSbt7PFm/B54cyVWgbay8gevIByEgS0LkeLoY+7yqGmvIWR1GZYLFyCIAiCIAhCVViwyCcIwjH+/KGFlEONWFsOeatBKDFhsGwB5CmEytGyDczdaGUEQRAEQRAEIYiTxTwtQwlCA/jx6zQphxpxxweZq8ok0flDpoWMrLzl5qNMNuoiwWJLqWhlYrhSTZooW4IgCIIgCEIWtutCy5pUKKIuQRBs4ce6IVIOWZCihDHLfJ1XdfxXTPnD/iSlxESq1LYyuZfTGoAgCILwGP68oiUIhuGUQ94VgyAICUj1LeuLkHKIQ3ojkNte7Pz5iFzviqJGqW1kdrkw3icciSdUjpzlkEmh+8tuA97ftkgQnoQWwARBEIS/Ib4pQJmouQRBqI8f64ZIOcQiftweVUPtbWUEQRAEQbjG4sWL0b59e4SGhiI1NRW7du1ymH7NmjXo2LEjQkND0blzZ3zzzTe882azGTNnzkR8fDzCwsKQnp6OkydP8tJcu3YNmZmZiIyMRHR0NMaPH4/y8nLB+504cQIRERGIjo7mHV+2bBl0Oh3v52+RbQhhbD/eNv1J61CCYB1/fhcn5RDhF1h8SpFyiCAIgvBVtLig/fzzzzF58mTMmjULe/fuRdeuXZGRkYFLly4Jpt+xYwdGjhyJ8ePHY9++fRg8eDAGDx6MQ4cOcWnmzp2LhQsXIi8vD/n5+QgPD8djjz3GyyczMxOHDx/Gpk2bsH79emzfvh0TJ060u19dXR1GjhyJe++9V1CeyMhIXLx4kfudPn3ajdIgfBVL36RlKEGwjz8HeCLlkANsx29nA7r88Z5/haP8bc85u5fULWpOn4mBWUzuswpGK+MshxQSyg1Zms55v2wJQi38d1olCEIO8+fPx4QJEzBu3Dh06tQJeXl5aNasGZYsWSKYfsGCBejfvz+mTJmClJQUzJ49G3feeSfeffddAA1za25uLqZPn45BgwahS5cuWLFiBYqKirg8jhw5go0bN+Ljjz9GamoqevfujUWLFmH16tW4cOEC737Tp09Hx44dMWzYMEF5dDodDAYD94uLi1OoZAgtIra0s7xs0sqPINjHj3VDpBwSwnmDEDMV5dM0Adikd3p/6f5plGq7dn6RFMpXLaRodAWjlSmkHbKtF2fyWJ/15wGHIAiCUA+tfe2sra3Fnj17kJ6ezh3T6/VIT0/Hzp07Ba/ZuXMnLz0AZGRkcOkLCwtRVFTESxMVFYWePXvy8oiOjuYdS09Ph16vR35+Pnds69atWLNmDRYvXiz6DOXl5WjXrh0SExMxaNAgHD58WOLTE/4EWQ4RhHbQ1kyqLKQcaoSF9RRNGI6RuugVKkalopURBEEQBKEMV65cgdFotLO2iYuL41n6WFNUVOQwveVf2zSxsbG8PFq3bs07HxgYiJiYGO76q1evYuzYsVi2bBkiIyMFZbntttuwZMkS/Pvf/8Znn30Gk8mEXr164dy5c4Lpa2pqUFZWxvsR/gGFsicI7aC1Dy1KQsohBnGnOfpxW7bDumPr9Z7ZVkYQRAPU1QjC89ASQDkmTJiAUaNG4b777hNNk5aWhtGjR6Nbt27o06cP1q5di9jYWHzwwQeC6XNychAVFcX9EhMT1RKf8BJibh085d6AIAj38ef3aVIOeRE1Px4olbcW5jApz8pitDJ2JCEIgiAIz9OqVSsEBASguLiYd7y4uBgGg0HwGoPB4DC95V/bNJcvX+blYevwur6+HteuXeOu37p1K+bNm4fAwEAEBgZi/PjxKC0tRWBgoKg/pKCgIHTv3h0nTpwQPD9t2jSUlpZyv7NnzwqmI7SPnbsGshwiCM2g92PtECmHZCB3PHfmlM4uvYqyyIUlczqhZ3UonaBD6oZ/3fU5pMSkzk7JEgRBEIT3CA4ORo8ePbBlyxbumMlkwpYtW5CWliZ4TVpaGi89AGzatIlLn5SUBIPBwEtTVlaGgoICXh4lJSXYs2cPd2zr1q0wmUxITU0F0OCXaP/+/dwvOzsbERER2L9/v13kMwtGoxEHDx5EfHy84PmQkBBERkbyfoR/oCeH1AShGfz5XS3Q2wJoEbl6EzXTK6XDceb4mgXkSmidXmlzXrXbAEEQBEHIRYtzzeTJkzFmzBj07NkTd999N3Jzc1FRUYFx48YBAEaPHo02bdogJycHAPDcc8+hT58+ePvttzFgwACsXr0aBQUF+PDDDwE0fNyaNGkS5syZg+TkZCQlJWHGjBkwGAxcmPmUlBT0798fEyZMQF5eHurq6pCVlYURI0YgISGBS2NNQUEB9Ho97rjjDu5YdnY2/vCHP6BDhw4oKSnBW2+9hdOnT+PJJ59UvdwINnH2YZglC3aCIITR4lyqFKQccoBcKxFVt4mpl7Vf0ORzSN2SpDmfIAiCIKQzfPhwXL58GTNnzkRRURG6deuGjRs3cg6lz5w5A72+ydC9V69eWLVqFaZPn46XX34ZycnJWLduHU9pM3XqVFRUVGDixIkoKSlB7969sXbtWvTo0YNLs3LlSmRlZaFfv37Q6/UYMmQIFi5cKEv269evY8KECSgqKkKLFi3Qo0cP7NixA506dXKzVAhfoykwinflIAhCCv6rHSLlUCM6kf/LvVYOtvODkDJKtoUKlDVb1YKyw64cBZ7eMimr9TwutQENlC1BEARBqE1WVhaysrIEz23bts3u2NChQzF06FDR/HQ6HbKzs5Gdnc0ds40MFhMTg1WrVkmWcezYsRg7dizv2DvvvIN33nlHch6E/2Brkc+i70uCIITxZ8sh8jkkA7EIBHJx1t6kbPFSShYx6yiWOoWQhFLks05jmZSNHp6UhRV+DBUuQagEOd0kCIIgiAaaPlLS3EgQrOPPb2pkOeQCUhuMRYGjZgNTyleQVH3FiUs38ObGo6isrVfkvrbENg/Bq4PuQFRYkMt5CM27EaENTd1oMmPgop8QERro9JmjmwVj1iOd0DoytCnvxn/lW5cp3wqMJjNe/+YIfisqc54YQF1VheIyEARBEOygBf+BBOHLiKl+OJ9DJs/JQhCEa/hztDJSDjEIy+3x3a0nsOl/xc4TukG/lDgM7Jpgd9zVLXYA0Cw4ELfEhuPk5QocPF8qOY8/JMXgL2nt5d3YQ+T/fhWf/FQoOb2pplJFaQiCIAiCIAhAPJQ9bSsjCPZh+V1cbUg55EXUmB90ivvW4Wd0taIWAHD/bbF4rHsbpW4CAHh/20n8VnQD9TI/q0g10f3nxD9gV+E1mMzOr1m+4xT2nilBnVG9SdzdnC11AQALRnRzmr6y/AZG5bp5U4IgCIIgCEIWFMqeILSDH+uGSDnkFURaHEsfE8Q6RW19g+JmyJ03CVr3uMO/9pzDb0U3JKV15LdHrBhbR4TikS7SZN5y5BL2nimRlFYuSmmjLXVx362xGNTNuaLO1hknQRAE4Vv489dOgmABsbU8+RwiCO3gz/5hySF1I0KNwD6amOM8bJ1Euzr+CzVH28lEqblFbja1xgaFRHCg55qOqxOpGv3aeRtw/LeScHURQN2YIAiCIAiCFWyXoJzPIdINEQTz+LFuiJRDQjjTFortI5aaXpYsbidQ6D6NWKxVPKkcssBUP7VrBPKSK4GlLkK8UBcE4Qxa/xKE52FqniQIgkNPPocIQjOQcojwCnbWQAq+TikX6p7/N6eQYMhaxd7CSxsTr7tyelNRRxAEQRAEQfARW3/ryXKIIDSDP0f+pLdKFlHT0shNPLGtTCndjhJlwfIcTtvKCIIgCB7+u54lCKYQ22WglQ+YLHDjxg1MmjQJ7dq1Q1hYGHr16oXdu3dz581mM2bOnIn4+HiEhYUhPT0dx48f96LEhK9AlkOERxFrb3LmC6WmFrF7im2ts5jD6vWe6zVyn5WlaVeofJUqOZPJ83VBEARBsIv11056CSUIdmiyHKJ+KZUnn3wSmzZtwqeffoqDBw/iwQcfRHp6Os6fPw8AmDt3LhYuXIi8vDzk5+cjPDwcGRkZqK6u9rLkhNbx5zcrUg65gFRTM8vwL9c0TU56xRqvRBWpmnOa4p7h3bHAEoso11irLAwatLwgCIIgrLGeu+gdlPA1zGYzDp0vRVWt0duiiOPko6sv9cui0mqcvVapSt5VVVX48ssvMXfuXNx3333o0KEDXnnlFXTo0AHvv/8+zGYzcnNzMX36dAwaNAhdunTBihUrcOHCBaxbt04VmbRMaVUdVu86g9LKOm+Logm8Ea3MaDLjyz3ncOpKhcfvbQ0phxph4WVfS3ijvPw5rKAjqFj8h+8OFyH19c3I//2qt0Vxiq83y8raeqTP/wGvfH3Y26IQBId1v/Ohd1CCAACs//UiHln0E8Yv3+08sZexXbM2OaT2gjAqYDab8YecLbh37vcoq1Ze4VBfXw+j0YjQ0FDe8bCwMPz0008oLCxEUVER0tPTuXNRUVFITU3Fzp07RfOtqalBWVkZ7+cPPLd6H15aexBZ/9zrbVFEYel9xhuy/GvPWfxjzQHcP2+b529uBSmHHKHyfiY5Yc+lZs01Zi+FuvcGtl9hvPlVRo4ZvxbKlmCLiZ/uQXFZDf78Sb63RXGKr7fvdfsu4MSlcizbccrbohAEh/ULKW0rI3yN1bvPAAB2nGT/A4ktvratzOL3EoAqlg4RERFIS0vD7NmzceHCBRiNRnz22WfYuXMnLl68iKKiIgBAXFwc77q4uDjunBA5OTmIiorifomJiYrLziLbjl4GAPx4/IqXJRGHId2QV2TZc/q6F+5qDymHBJCrLZRr0eIsvfVpb2lRlfCLpDbOysaTnubl3EmpOmWpLgjPUmekyvc2RuqABEEQHiU6LNjbIjhFbGawWA75otK2RKWtSp9++inMZjPatGmDkJAQLFy4ECNHjoRe7/rr67Rp01BaWsr9zp49q6DEhDuwtEPEG7IEuNGulYQNKTSC7PFcxQlAqcnF1ZD3anYau0djyBJIbrG7Wr5yYGcoJQiCIFjB915BCX8nulmQt0WQjO3aTOdjoeyt18MlVeooh2655Rb88MMPKC8vx9mzZ7Fr1y7U1dXh5ptvhsFgAAAUFxfzrikuLubOCRESEoLIyEjej2ADlt5nvCELK8GnA70tgBaRb1kkLZ0rCh+ldDQsdUgxGFIoq9YG5OAJxRNBEAShHcghNeHLtGjWZDl08Fyp4msrvU6H2wwRCFAhCqwlx0PnS3HofKnz9Drg1rgIBLHyxuiAn49fwc2twh2mKb/hum+f8PBwhIeH4/r16/j2228xd+5cJCUlwWAwYMuWLejWrRsAoKysDPn5+fjb3/7m8r0I79Gw9ZKNiUvvhZdOb9xTCFIOeRHRMPJK5K1AHoC6MiqVp5iSxJ0+5onuqdTCnZGxhCAIgvAyfIfUbCyyCUIpWoQ3KYcGvvuTKvd4tGsCFo7s7vL1Yh96L5Y2hFdfmX8GK/PPSMrr3uRW+HR8qsuyeIrPC87i8wLH27NMNfKjmn377bcwm8247bbbcOLECUyZMgUdO3bEuHHjoNPpMGnSJMyZMwfJyclISkrCjBkzkJCQgMGDB7v4JIRXYeh9xhvvVqQcYgxP1oeoPx9F8lbmQURDuTP0KVJIv8ySfOIoU0eaeFSC8FHYmMIJgg9ZDhG+TFBAUwM3RDZEsVJKCVpTb0JJZR1OXCpXJD/bSeKglbVQXGSIw0vrjGZcq6jFSaVkUZmIkECEhzS8UorVh7G6HnK9+5SWlmLatGk4d+4cYmJiMGTIELz22msICmrYXjh16lRUVFRg4sSJKCkpQe/evbFx40a7CGeENvD3dRUphzSI0l/hxC1enDcOZ4s+qUoSp/moYJUjF6fl7kHrJrk4Kl+l2pMnHW8ThFToxZTwRRZuOY5mwQF48t6bvS2KCP4zH+wqvIYvCs7i/x5O4VmUEL7PgM7xWJx5p6J5bj92GaOX7FI0T2uG9rgJa/acw/QBKU7Hj4PnSlWzjFKDX17uxymHxCgrK0PUbHn5Dhs2DMOGDRM9r9PpkJ2djezsbHkZE0zCiG4EgLccUnv8loKQcsgBYu82Ui1/LH/bO6VzQRZRBQg/M1fbsv11whmx9L6n0+k8/gbaVKfyysc6vWLRypTJhiAIgpDAhZIqzN90DAAw7p4kVfySuIs/WQ4N+2AnAMBkMmP+8G7eFYbwCFpo02IyvjrodjzaLQH33NLKswKphBbqgmhCr2PfGTorljNAU3RBj96TkTUFIzoqtpBbNYpVpWCnZaOh2OINaxUpd/TWZOXN8IsMjaUEQRA+S1Wdkfs/q1uY/dHn0KmrFd4WgfA0Glj32K6TmwUH4t7kWGZeAJWE1qHsw5LiRQyWJPRnn0OkHPImYtZACrQNtR1Sq4ncW4pa6zDSycRg9N2CIAiCEIDtGaUB63mP5hjC12BVKeuP+Ivy2VfQglKSpfc2bxhBBDDy/KQc8gJa8BEj7pDa8/cUTa+OGA15q9hBlbM0o4mZILwFI3M44SVYHX35lkP+gb88J6ENqD0SLKIB3RBTb8fesRzy/D2FIOVQI1IUNnLfxWWnl5dcEVy9p0cdUssQUu0yZLFOGRlLCIIgfBqWvmqKwfc5RK+phG+iZk9UqtewtAtAbbTw0dvfYWXLkkMUEvGtb3/Dp7+cZkEUefdkpI5IOeQCcitPLL1ch9fCeQsfl7smFHWwbJOPV81IxcrRC9HKZFs5CaR3d92ulUUD4Z/4ksn51wcu4Klpr6N9+/YIDQ1FamoqTh7e7/CaNWvWoGPHjggNDUXnzp3x3Xff8c6bzWbMnDkT8fHxCAsLQ3p6Oo4fP85Lc+3aNWRmZiIyMhLR0dEYP348ysubQhufOnUKOp3O7vfLL78o9uyEMKzqXaznckZFVBxW64JQHn+pakbeER1C/U5bsLJlyRFKSHjkYhkWf38SM9YdclMYb0QrY6OOSDnkALlf3aSmF1foiF8vPW9lGhYbzdMxwgoX785WUm6vtGaYFU0zQfgi5TX1GD9zAT54axZeenk69u7di65du+LNSaNhrCgRvGbHjh0YOXIkxo8fj3379mHw4MEYNWoUL83cuXOxcOFC5OXlIT8/H+Hh4cjIyEB1dTWXJjMzE4cPH8amTZuwfv16bN++HRMnTrS73+bNm3Hx4kXu16NHD0XLgGhACyOtP0UrI/wXNdY9ikWS9cN+R8tQ9tGCzyElZKyoqVdAEu9s8SLlEMN4apATtXhho20AsP/6z+KkJ2ahwFI5qgGLdUEQvkZVrRFlu9chomsGhmeORqdOnZCXl4eQ0DCUH9wkeM2CBQvQv39/TJkyBSkpKZg9eza6du3KnTebzcjNzcX06dMxaNAgdOnSBStWrMCFCxewbt06AMCRI0ewceNGfPzxx0hNTUXv3r2xaNEirF69GhcuXODdr2XLljAYDNwvKChItfIgGtCEZZwGRFQCP3lMAtpa9/j4EpT6ncZgRO/gECVE1LKRBCvvraQckoHoQKhiZcrdNmZJLnXQdlVBpWYDtrX+EX9W9XuR1IWInHpipO8TBCGB2tpa1BadQGi7btwxvV6PO+7qjZrzvwles3PnTqSnp/OO9evXj/t/YWEhioqKeGmioqKQmpqKnTt3cnlER0ejZ8+eXJr09HTo9Xrk5+fz8n700UfRunVr9O7dG19//bXD56mpqUFZWRnvR0hDC1Y5PBn95fWN1cogCIJgBFasUhyhhGJHz5unXZ8bvLErw3rrn8nkvXmNlEMqIndh5kozUKrpSu0DrC/B1Jev4Q5yy12NMcZvFv4E4UWuXb0CmE0ICI/mHY9s0QrGiuuC1xQVFSEuLo53LDY2lncegF2auLg47lxRURFat27NOx8YGIiYmBguTfPmzfH2229jzZo12LBhA3r37o3Bgwc7VBDl5OQgKiqK+yUmJjp4esIarTldJZ0J4auw3BNpbUawiBYcUishofVzuqNf8UZpWSvw6r2oHAr02p0Zwxt9RnwCcV8YpXzveNJqx1mOYufVkNETzUGpOtLAeE8QhAq0atUKkydP5v6+6667cOHCBbz11lt49NFHBa+ZNm0a75qysjJSEPkQfumQ2tsCEB7DE3XN0tqMZQWvt318EvLQhHJIEcuhpjyMJrPLFlPeKC8dT7FFlkN+hZqmakplLTV6mVdhf5wThJweEoR2iGnZCtDpYawo4b2YlF6/jIDwFoLXGAwGFBcX845dvnyZdx6AXZri4mLunMFgwKVLl3jn6+vrce3aNS6NEKmpqThx4oTo+ZCQEERGRvJ+hO9AoewJf0AD77l+BdUH+2hjW5myebilYPGGQ2qre3rTcoiUQzJQe6ElJ3vlzFZdy8eTE4GcZ2VvLay+QFrb6kAQWiIkJBjBhg6oPn2AO2YymXB49w6EtOkoeE1aWhq2bNnCO/b9999z/09KSoLBYOClKSsrQ35+PtLS0rg8SkpKsGfPHi7N1q1bYTKZkJqaKirv/v37ER8fL+8hCZ+B73OIIHwLNdfhSq2l2FuHqoOfPKbPoNfAG7/S28qMbihYvL2tzGikbWVMIrrpS6LzYcvfsp1KC4VoF5VFxMJHJL0YWlYveNJRuLM6FZNGaNFBEytBaIPIuwbjyoZ38M+Vn+KP9/ZCbm4uaqorEdO5waH06NGj0aZNG+Tk5AAAnnvuOfTp0wdvv/02BgwYgNWrV2Pfvn1cfjqdDpMmTcKcOXOQnJyMpKQkzJgxAwkJCRg8eDAAICUlBf3798eECROQl5eHuro6ZGVlYcSIEUhISAAALF++HMHBwejevTsAYO3atViyZAk+/vhjD5aO/6AJh9TW28oYlVFp/OU5CW3hTx/u/OlZtYo2tpW5n4dSfnu8UVzW7/RGL05spBwSRN0WIeo7RwF1gfoOqj3l8tkeW5mERFTaEaAajgUV+zqlSC4EQTgjPOU+GCtL8cacbEwuLkK3bt3w4jsrsOR4wxR65swZ6K0+y/Xq1QurVq3C9OnT8fLLLyM5ORmrVq3C0KFDuTRTp05FRUUFJk6ciJKSEvTu3RsbN25EaGgol2blypXIyspCv379oNfrMWTIECxcuJAn2+zZs3H69GkEBgaiY8eO+Pzzz/H444+rXCKEFiDHuISvwv5rLkGwRYAGlENKKLACrCyk3In45W1lWr3J5LV7M60cMhqNeOWVV/DZZ5+hqKgICQkJGDt2LKZPn85p18xmM2bNmoWPPvoIJSUluOeee/D+++8jOTnZY3K6+rIvxR21t7uyq6HuPYmYmbEnZfRmcbBUFwThq0T2GIg9Xy1Ay+YhAIBV+WeA4wcBANu2bbNLP3ToUJ4yyDZkvE6nQ3Z2NrKzs0XvGRMTg1WrVomeHzNmDMaMGSPnMQiF0ITiRQMiKoEm6oIgfAyy2NMWSr0r/H65HCYz0KF1c2UytEIZEZWxvvFOoKompGyJq6ipx6/nSnF3UoyiPqWY3oH45ptv4v3338e7776LI0eO4M0338TcuXOxaNEiLs3cuXOxcOFC5OXlIT8/H+Hh4cjIyEB1dbUXJXeMmg2OM0lzc9CWGxlMCeQ66la146paRw3/uluWNDEThPqQ7pWwoDVFPE0RhK+iZmAXpVAkWplGerEGqsPvUUJ5UFtvwh/f/gHp839AVa1RAan4KNOvm/qMO5ZD/C3aHuqHVveRohwat2w3Rn70Cz7YflJRMZhWDu3YsQODBg3CgAED0L59ezz++ON48MEHsWvXLgANlZWbm4vp06dj0KBB6NKlC1asWIELFy5g3bp1isujdtOQ5ZBaIWFczceT+4u9US5K4Ql5aE4mWIS1vqg0tBj2b7TQvrUgoxL4y3MSVNdMQXWhKZTYJlVT36QQKqmqdTs/NbAeI5TyOeSpwGFyLYd2FV4DAPxz1xlF5WBaOdSrVy9s2bIFx44dAwAcOHAAP/30Ex566CEAQGFhIYqKipCens5dExUVhdTUVOzcuVMwz5qaGpSVlfF+cpHavyzVKh4WXmw7lPQOrJT/IlGn2Tb5sDgXiG59U/FeSlg5uftFSCtflAiCIHwB63FfC6Ovv8wRpDAgWEIJKwOtfXzQmLh+iRLKIes86lWIpqWMtV0T7kQrs8bkoUnGVcWW0pHNmPY59NJLL6GsrAwdO3ZEQEAAjEYjXnvtNWRmZgIAioqKAABxcXG86+Li4rhztuTk5ODVV19VV3AnqLutTKl8HGfkFS/uNtMPRUdoQGuLCIIgCC2itaGWlCaEr6JGX6S1FOHLKLGtzHpKUUNhoohyyEosd2S0fg/2nHLItS1xSkc2Y9py6IsvvsDKlSuxatUq7N27F8uXL8e8efOwfPlyl/OcNm0aSktLud/Zs2dF08ota3erxuH9GFnkeWTfJSPPCrjQBjwpO0PlRBAE4U94zAeBG7AvoTL4y3MS2rKG83Vdk5bqggCU8FdsPe+5s2VLDCWsm6zbpTuWQ9bl5anp3uSq5ZDCdcG05dCUKVPw0ksvYcSIEQCAzp074/Tp08jJycGYMWNgMBgAAMXFxYiPj+euKy4uRrdu3QTzDAkJQUhIiMP7im6xUrhxSIlWJvda7rxEWZ2l8+SWLVEZXLyOBYeFDvV9CrUnFp6TIAjC19HaUKsFBRZBuITG+qKvQ+tQ9lGijqx1EO44exZDEXfUSlkOieSpJq5uiVNaOcS05VBlZSX0er6IAQEBMJlMAICkpCQYDAZs2bKFO19WVob8/HykpaXJupecPmO3vcmJMsn2vJztUE47s13ersHCwC5XAkE/PkopXMT8RImoe5xuw+OldVUqgiBYgbqxf8Oq2sV6jvIX3RApwfwHjxivuxtJVhkxGvJiuGmzLBthjyKhzhVy9iyGEu+iyjmk9u62MjkKH6XrgmnLoYEDB+K1115D27Ztcfvtt2Pfvn2YP38+nnjiCQANFTdp0iTMmTMHycnJSEpKwowZM5CQkIDBgwd7V3gpiFnlMPTWYSuiN+cCuRZdDBWjKtC8TLAMLRwJX4baN0EQDmFpMa8y/vOk2iXAOqCC2eySIsbkovJCKsoEsldGRp7lkBvyuIo3t5UxbTm0aNEiPP7443j66aeRkpKCF154AX/9618xe/ZsLs3UqVPx97//HRMnTsRdd92F8vJybNy4EaGhoV6U3DGqzheNmbu7cHVqsMTATMCACC5hsUpSqitrtRwIQmuQPsC/0VoQBC0psBYvXoz27dsjNDQUqamp2LVrl8P0a9aswfmPnsLpeY/h57lj8c033/DOm81mzJw5E/Hx8QgLC0N6ejpOnjzJS3Pt2jVkZmYiMjIS0dHRGD9+PMrLywXvd+LECURERCA6OlpQlo4dOyI0NBSdO3e2k4VQHq31Rbn4+vMRnsd6I46rugQ1IoFZo1fCaTZv65sysigdDUwK3rQcYlo5FBERgdzcXJw+fRpVVVU4efIk5syZg+DgYC6NTqdDdnY2ioqKUF1djc2bN+PWW2/1otSuowXTaNZF9CcHeVpoLwShdVjYckswiAaGX63Mh59//jkmT56MWbNmYe/evejatSsyMjJw6dIlwfQ7duzAyJEj0bzLA0gYuxCt77gXgwcPxqFDh7g0c+fOxcKFC5GXl4f8/HyEh4fjscce4+WTmZmJw4cPY9OmTVi/fj22b9+OiRMn2t2vrq4OI0eOxL333isqy/jx47Fv3z4MHjzYThZCOdRs0UqN9P6yNPOTx/QZrLeVuarYsbYcqndH8yJCUECTWqLe6H7+7kTxCrQqr1oFZJGCtbjkc0gzKFv4ov5rJExRSikGnC0exe/juRcmp06zRf0AqSCMTDyiwGHgOQmCIHwdFuYUOWjlJXX+/PmYMGECxo0bh06dOiEvLw/NmjXDkiVLBNMvWLAA/fv3R1TqEAS1SkTyw+Nx55134t133wXQMO/m5uZi+vTpGDRoELp06YIVK1agqKiIy+PIkSPYuHEjPv74Y6SmpqJ3795YtGgRVq9ejQsXLvDuN336dHTs2BHDhg0TlWXKlClISUnB7NmzebIQ6qCFvqgBERVDC/Xh71hHAnNVmWA9p9SpYE0THKCsQsaokALLY8ohF7fEkXLIg8hVOtguxCzX2yZ3ZQyVqqKx/O3uF0PxZ1R/tSlVdk980bfzuSTiZFwsvQXr9Jb/u+300M3rt2/fjoEDByIhIQE6nQ7r1q3jztXV1eHFF19E586dER4ejoSEBIwePdpu0SzHLJ8gfAlaDPs3WrDKYV9CoLa2Fnv27EF6ejp3TK/XIz09HTt37hS8ZufOnbz0ZjOQkZHBpS8sLERRUREvTVRUFHr27MnLIzo6mncsPT0der0e+fn53LGtW7dizZo1WLx4sSRZAL4shLJoReHpD5D1urbgKYdcrDteKHsVlEPWlkN19e4rsNzR6fAUYfVesBzyYv8i5VAj1tY6sqNmKSSDUDNg9f1DjRcjmYHZBFEuPLzM9Mrc1iVc3ZteUVGBrl27Ci56KysrsXfvXsyYMQN79+7F2rVrcfToUTz66KO8dFLN8gnC16B1sf/hjdC27qCFl7crV67AaDQiLi6OdzwuLo5n6WNNUVERL70ZZl56y7+2ecbGxvLyaN26Ne98YGAgYmJiuOuvXr2KsWPHYtmyZYiMjJQkizPZa2pqUFZWxvsRbOGu4ldJxTH7PbgB2n7NPgEK+NCxvqpOhW1l1n5+aoxGl/JQyiG1NZ6yHLJGKasnV2A6WpmvIxplS4logwrNKCxFKxNDPFoZ65OVuwsQ93jooYfw0EMPCZ6LiorCpk2beMfeffdd3H333Thz5gzatm3LmeXv3r2b+/q6aNEiPPzww5g3bx4SEhLclJAg2EID79qEmlhNKVpoClqQUQnU6pcTJkzAqFGjcN999ymWZ05ODl599VXF8vM3xCzyWcTX9SX+Mr74CtaWQ676C7L2OaS2NY2r29Z4DqndmByslUy1nrIcsvq/GpZZUiHLIRkotgARmTHk5C9l+5KkfFxUrHh2zhPzzSQ1pfcQtAZTuPA8tQApLS2FTqfjorVINcu3hr6aElrDx9f3hAys50UtWOVoQES0atUKAQEBKC4u5h0vLi6GwWAQvMZgMPDSm23SW/61zfPy5cu8PGwdXtfX1+PatWvc9Vu3bsW8efMQGBiIwMBAjB8/HqWlpQgMDOT8IdnK4kz2adOmobS0lPudPXtWMB3h3/i6YonwLq5vK2v6v9IRshpu0PRfVxUyPAWLGzJaP6s3HFK7o9hyF1IOuYDkMduZfxoF6l0pU07JMjK42FRKUSbnXvKtkpQXxpPjRnV1NV588UWMHDmSM6+XYpZvS05ODqKiorhfYmKi6rIThBrQ4t3/0GnMckgLUgYHB6NHjx7YsmULd8xkMmHLli1IS0sTvCYtLY2X3mw2Y9OmTVz6pKQkGAwGXpqysjIUFBTw8igpKcGePXu4Y1u3boXJZEJqaiqAhg8g+/fv537Z2dmIiIjA/v37uchntrIA4MliS0hICCIjI3k/Qj4sj79aUMoS/oj72614lkMqKEyUsNax/nBjckc5ZPV/z1kOWUeD895AQtvKHCB3gJfsSNklWaTmrWuUxT2c+v9hYWZmQARbpFQTV0dK+UdSJhtR6urqMGzYMJjNZrz//vtu5TVt2jRMnjyZ+7usrIwURARBaA4tvABqQUYAmDx5MsaMGYOePXvi7rvvRm5uLioqKjBu3DgAwOjRo9GmTRvk5OQAAJ577jn06dMHERWtEXbLXfh97y84X1CADz/8EEDD+mTSpEmYM2cOkpOTkZSUhBkzZsBgMOD06dMAgJSUFPTv3x8TJkxAXl4e6urqkJWVhREjRnBbolNSUnhyFhQUQK/X44477uCOWWR5++23MWDAAKxevRoFVrIQyqJqm1baqpvFRaqCaGV8IexxdcsSz3JIhW1P/Gho7lsOueNzSAlZ3EHpCGRyIOWQAHIVH0rpSYSUSyzoYDyNO76YlDb1l5qdr9aTRTF0+vRpbN26lfeVU4pZvi0hISEICQlRVWaCUBJa/xJCaGJbmbcFkMjw4cNx+fJlzJw5E0VFRejWrRs2btzIOXo+c+YM9PomQ/devXph1apVGPXU87i+fQWatboJ69at4yltpk6dioqKCkycOBElJSXo3bs31q5dix49enBpVq5ciaysLPTr1w96vR5DhgzBwoULZclukWX69Ol4+eWXkZycbCcLQfgyvrr+9TWU3rLkqt8iqdS4bDnU9P+K2npFZPGY5RAv0hoph7yONwY3T26Hch2zg7+UxrUHV2ORzlQViKB2KGWLYuj48eP4/vvv0bJlS955a7N8y4Lb1iyfIAjCV7CearSgeNGA/oojKysLWVlZgue2bdtmd2zo0KGYsqcZACCpVTgefvh+3nmdTofs7GxkZ2dzx2x93MXExGDVqlWSZRw7dizGjh0rKMvQoUMl50O4j5pWOe72GyW7Hct9WO01KKEsvEhjLlr9WCuVzpdUo7xGGeWLBev8XFfINMn46c7TqDeaERigQ3CAHmHBAejRroUkI5DymjoFZHEduZZZUupCan2RckgGKvujloUz6xqpE4qogsrJdZ5Unog7zWYfIdm5OlLoHq62p/Lycpw4cYL7u7CwEPv370dMTAzi4+Px+OOPY+/evVi/fj2MRiPnRygmJgbBwcGSzPIJQutoYZwhPA/LL20W/OXlTQtWXIT/wdaHXvXwk8fUPNbjZFWti2HirYbahVuOY+GW4+6KJUqli1Y/1jIWnL6OgtPX3ZalwsXykot1HUl5/tYRIbh0owYAcMesb52mN9VUSpKDlEMOEFfASIs2xjkvljhDOFrfqG1lJPUrDOuLMLWlszy+qANvschqajjHdvNhCwoK0LdvX+5viy+gMWPG4JVXXsHXX38NAOjWrRvvuu+//x73338/AGXM8glCi/i6PwnCMd6MJOIIRsVSFS9a3xNewtcVL77+fIRnMZvNvHHyWmWtS/l4ct67XlnnPJEA1hL269gadSYz6upNKCqrRuGVCpfyLHGxvORgNpth7dromoTnT4xpximHlISUQwLIj0Ol7HYo6/xcfwFRpgO74/9HacTKgo3tefJvppSizdU2cv/99zuUQYp8cs3yCYIgfAEt6CNq6jxvCu8N/MVCimD/AyXgRwpaf3lOldh+7DJe23AE120UDw/dYcCrg9zzWVZaVYd/fLEf+8+WorK2HlV1Rl67lKrs+ObgRbz93VHcqG6wYrFWRPw2u79bMgrRccZG7v/XK6TJ+MXus3hv2wlUNlr3WMv4ydi7uP9/vvsMXvzyIABgx0t/REx4sGRZrkmURQ5msxnZ6/+HjYeKUF5dj4raep4Cz7aOdp+6hhnrDuF6ZS1Xl5Znff2xzvjTnW2c3rOsrAxxuc5lI+WQFxB7lVdinFVKHyJqHaVQ/kogJKMWJmX6IEQQ2oReQgkLWnhJVdofBKtooCoIDaC0Nai/rPWYiF6sQV75z2H8ftnekmVl/hm3lUOrd53B5iOXRM9fKnNubWIymTF93SFRxUhoUIDL8onx7qjuyFq1DwBwudy5jNV1Rkz/9yFJPoHKa5q2hsVFhiJA77jdLh13F8Yt3d0giwrWOQWnr2Ppz6dEz9vW0cx/H8ZvRTcE04aHBEiqj1qJdUbKIRkovQBxz+JFXcsgZ3dR1RmgRBm486I+idyX0d2XQU+8QNC8TBDqQf2LEEILConMj/PRNqYZ93dggA5THrwND3WO96JUyqOFuiCUwdnWfsJz+EO3q64z4l97zuHc9SoYG6NzhQUFYFRqOxiiQu3Sny+pwld7z+FGTT1MjWYg8VFhGNOrPU8ZUV5TzymGVj2ZiuhmwbhWUYs/f5IvWq51RhO+2nsehVcrUN+4/ygoQI8Rd7VF25bNeGl/PV8KAMhMbYu/3ncLwoIDEB4SgA+3/47czcex4pdTKC6r5vpRUqvmGHl3Ik/Rd76kilMM/fuZexAU0BAx8ucTV5B2Cz9AjVI80iUB5dX1eGntQazdex5GkxmWYrs9IQqDu/OtY44V30BtvQnBgXp89XQv7r1vz5nruP/WWF7a8uqmjyXOFEMA0Pe21sj7cw889dkebDxchMiwIE4WofICGhRq//n1Ao5cvAGT2cy9Az54uwF3tY/hpT14rqGOureNxvxh3RAeHICw4ADsO1OC0Ut24fujlzB7/f+g1zVsnT5ysSGgQt6fe3Dz+umrFbhRXY+BXZT180rKoUbkTDTyt53Z3ku5Wc0+74Z/5S6WbEUStW5ScTaQWyxqLg6c5e1OG1DKIbUWvlwTBEH4IloZfs9c4zugXLPnnA8qhzRSGYQmcL81KRqvTMG81MGX9XTT1x3Cv/acszteWWvE9Ec68Y5V1Rrxp/d+RrGAVc7tCZFIvblJoVJa1eBPJihAh7RbWkKn0+FSWbVDWeZu/A0f/Vhod7y4rAZvD+vKO1ba6K+mZ/sWPMXRgM7xWPz9CZy9VoWPf+LndVf7FkiOi7CTsXVECLomRnPHOyVEOpTTXf7YsTWahwTiSnkNPrGRsVeHlmgd0aSUK2l8zptbheP2hCiHMroS1v6eDi3RMjwYVytq7WS5O6kFOrSO4B375KdCvPbNEbt8Nh+5hO9fuJ93rKSxfG9PiERSq3CrfGOQEBWKC6XVdvcEgH4prTlFnVp1QcohFZG7YHHokJqx+YHZrzYql5MzSyJv1BOrVUH4Nz7/wkYdz6/RwhbDtU/34v7//W+XsGjrCZ/sl773RIRz2B+AmV0nE5KorTdhw68XAQCPdW+D2IgQ7DtzHbtPXRdUNPxSeBXFZTUIDw7AyLvbIkCvw5d7z+NKeY1d+hvVDYqBiNAgSQYDZrMZ6/ZfANDgkygxphmOXCzDj8evoEJg+zCXf0gQ73hyXATW/u0ebD5SjOq6hm1Wq/LP4EZNvd025DJORs+qClpHhmLdM/fgm4MXG8rNDCz5uRB1RrNdlDWLLyQpMt7ugiIlIjQI6565B18fuNBQHmbr8rKPYPbVvvMAgPtvi8WtcRG4Wl6LL/eeE9zibd0GrAkNCsCXT/fCV/vONyjozA1Kp/pGSzSLYkhNSDkkgKcsWKQ4e/b25GIfgc2LyzDRsvBchDAxvFFPtCAmCILwDqzrWGIjQnBn2xbc35YtDIyL7RKs1wWhHP5S1VqIhunr/a64rBpVdUaEBOoxf1hX6HQ6vLv1OHafEg6Nbhlj7+/YmrMq+uX3q7gi4Dun3IFSQ0iBX15Tz/m9eXtYVzQLDsRnv5zGj8evCMriSGnS+aYodL6pycrmm0MXcUNAedEkY5DdObXp0Lo5nu2XzP29Mv8M6owCMtYIK1iEGNglATX1JtzZNlqWLIkxzfBM3w7c3xsOCpeX2WzmoqHNGng7klqF48jFMny5197yDHBcR/FRYXj6/qZ7/nj8Cv7XuK3ME5ByyAuoOeRbJhS3x2z25yUtiChCYx35+MRKED4H9VmiEWoK7KAFKy7Cf/C3tZ23P2KrhSUSVKvmIZKseyzKm9jmIU7TWixJmodIew235B0eHIBmwc6v4fJ3w+rHYu3kacshOVisd6SUo16vw7CeiarJcr2yDlWN1lg3tQhzmt5i8RUhQXajybODivq2ST6E+ubY0vNXShQtLKrklDtrz+MRaXx1ZiYIBtDCF1zC85g09gZoacUaE1sSHl43E15ESw6pfT2KF2vrbaWxWPzERtgre4TGUTnp640CW4QcNJcr5bXieQvUg2ULUrCMLUi2udQJyehl7MuxyTG352XhC2NR9oQFBdjJI9Re5JRvncl5NDYlYafGGURUKSHSgW3Tc3/K3Q4lcIHYIKzU5CPugFrkmVRE7j1kVpN7eTtZmIhvFVR+keCLi3yCIAhWsZ6HafwlCN/Cx3U5quGrH1DKGh0GR4ZJ21YlJ71FeSMlapYrsliUJnqJ+QthsVbRM9wxmsrRy4KgyVorXKI1mCX6nZQ6qjOScsgrWA9ucgc62ZGrZCoW5GVuycu9zJw9kzfGCilR37y1YJdTHDqF6siVexMEQRBKoC3tkFJRMlmEFHX+B8vrHmqPvkFt4wt5aGDTq7KjD71C6cVelowylUNNeQc4y5qXf6CE/MXeeetl5KE2YhI0laPn1Bli5V5Za1EOSasjOeVrNNK2Mr9BikNqbyNiOKMKrj62mEzuWOto4UuIr5v0EtqGWifhy9ALIEtQZfgLnlj3sBTRjyFR7GBZNiWoqWtQyIQEBThJ6Ty9bVkZGw8ECH3kFsq73tiYt/1ru1A9WPKXY/Vjm4/JongJYOd9yPZR5SjB1JalotH/kbBPKPtKsmxNl6IgrCOfQ+yiVNUooXgQVYg4OS81I2eKFU/upXb2rEwjILzsOnICS8pEgiAIf0Brfm6UtlhlCa3VBUE4Q1PrOi3JKoOa+gZlj1S/PRYFjpT0li1FgRIVLxbFk1RZOKWJG4odbssWw41RrgWWmnCWQ8HSlIkWv1OSlEO0rYx9ZG8jk3iFK+sbpbqD5L7P+CLMU+KpvfVQCj64xicIgtAEZLnJDr6o8CKE0YJDan8ZG3z9KWvrLZZA0qx1LFu/rNOLb4dq+NdaMeDovUI4b/H0cpQmYn3JxNC2MrFHNcqwvlFOFOF7WSKVhVkphxzVkcVyiLaVaQy5VSF3C5YcixhvrX3UdPasFJ6U0Xmder6itLAFjiB8Dep1/g2r+gjx+dB3WyyjVUH4OSwrsJTEVx+T28oVKNFyyLKtTEJ6i+WQVKucprydW6WYTGbOmtIdqx+5TrO9gTe3ldkixxIIaCpfKVv/KFoZA8juS3IvkJFcdtaNF7i7cBWNXubFZZjtVjaWJl45sugU8gxKC2KCIAjvwKpyyB+huvAfmoIAK78AZGhJqQl83WLPsq1MikLGWXrbkpKreHGkqLLzw2NVL4GyHDXzc+IUWAwoXizYtjmLQsadqGyuy8L/25GiStAvlIytf/VkOeQdpLzcqz0OyhlolZLF1WzUVMzYKqDkPCtrk5UnpGFJSUYQFnyxWbI1uhDexMTYXGOL6AcetsV2CdbrgvAv/K05qrkGNRqNmDFjBpKSkhAWFoZbbrkFs2fP5q31zWYzZs6cifj4eISFhSE9PR3Hjx93+96WbWXBEi2HuG1oEtKbHCiHBLesyZDFaOWEzZ0gXkJb31hDztYstZGr8DPKsByqJ4fU7CPXGbPc0PXyrFBkiSKej8hS0pOWQq4+i5iM7pSNs2vlW3S5LgtBaBGfWR9T3yV8AJ+eg3xmsCFYQAvBZ/yFN998E++//z7effddHDlyBG+++Sbmzp2LRYsWcWnmzp2LhQsXIi8vD/n5+QgPD0dGRgaqq6vdurdjax37mhFKLzbuyrccslc8ieVtrRySYjkk7heJHcshMQnqG2WUE5XNbVmclLt1mTsSSyg9KwjFWyMakav9t00v1xeOEpOAUpGw5Cq0vIO0EJBK4swySUr5KFVHbNUFQRCE/0DjLztQVfgRjR3Pp5Wd0MY3CU+MgTt27MCgQYMwYMAAAED79u3xz3/+E7t27WqUwYzc3FxMnz4dgwYNAgCsWLECcXFxWLduHUaMGOHyvWtlRiuzpA+SFK3MXjnkqE3XyMi7XiHLIfI5JA+55cX5HGJPN0SWQ0rgapMUt8qxHiwafQi5eA+3Yci5pVwzebkWXu7gTWef3h8SCcL/8OT4QrCHViMSaVVuR7C2nZzwb/ytNaq5/u3Vqxe2bNmCY8eOAQAOHDiAn376CQ899BAAoLCwEEVFRUhPT+euiYqKQmpqKnbu3CmYZ01NDcrKyng/ISxuXqQqcBxFzrIdo+SGYHe0fcp2+DPJtBwSy8fI0JYtC3b+lSzlKMFvj/II+2gSrCOBq01kOURYo+Y7Befr2M3Fkvg2M/WRKron3s3UWHQqVUe+tAQ5efkGukdGelsMgiAIcayGXA+7ACAcQHXhPzQ5pGYf+n7gPi+99BLKysrQsWNHBAQEwGg04rXXXkNmZiYAoKioCAAQFxfHuy4uLo47Z0tOTg5effVVp/e2KGSk6kYs45AU58j1Mi1eTJzFnDz/NO7odYxedPYsFc5ah4HO5qrlEIuWWeypq7yElKpR+4ubLMfLCsniqoJCjX6ohEJKKV2OUs/niS+aDIyJbvPUp3u9LQJBOIUMFAgLWrNWUSqSKUEQhDVqrkG/+OILrFy5EqtWrcLevXuxfPlyzJs3D8uXL3c5z2nTpqG0tJT7nT17VjCdI6fRDtNbFYjYlXLzFnIOLZq3lQWTFGWSWBqWLIfEZJRbjorIInLcokyzjj7mSCo51mOfjr8bhshQLH/ibqliugVZDjlA1NGxUukVcEit1PcTUR9Dtn8zuLJkUCQ71DC71cJzS+ViqXuOAwlCLXxB+Uoojw8Nv5rHF7fKEZ5Hqa3CvrQ28zZTpkzBSy+9xPkO6ty5M06fPo2cnByMGTMGBoMBAFBcXIz4+HjuuuLiYnTr1k0wz5CQEISEhDi9tyNrHaE6dmRpZJtcrtWI2aEVEz93Vy1SRLdsMbTtybbc5VpgeUIWKdsKAXn+ku5NjsUvL/dzQUrXYKfGGUKpSFTiyiLpN+BSenirldNoXcrcxi28v8O0CVkR5qCsHynyfUKwCC2QCV+GxQ8ljuACIWhLbEnQtjL/wdJ+VV33KGWBrkAeLI8znhCtsrISehvlREBAAEyN/l2SkpJgMBiwZcsW7nxZWRny8/ORlpbm1r3lhHI3m82ytpUZZVgZWaeXlLdRma1WLG3ZEkOu7yY1kRt9jHNIzWD5kuUQQ7A8CVjwiM8hkeNS+o/SXxBZrhKWZSMIX4e96ZzwJDT+MgTVBeFjMPi+KIqaog4cOBCvvfYa2rZti9tvvx379u3D/Pnz8cQTTzTcW6fDpEmTMGfOHCQnJyMpKQkzZsxAQkICBg8e7Na9Le9kfAWOiPsLqzGIl97Jli2p/nw4xRMvb+G0jhxjC+F865ukbFTFWfh4T/pFEqtTIcshR/3YJLOePAkph+Sg8ALEeawyB9cqJIuzbETvo4bPITELLGfh4wWewv2JVSHzYkVyIQjCW5ASgBBCa82CC4SgOcmd44vPRAijhbrWgoxK4InnXLRoEWbMmIGnn34aly5dQkJCAv76179i5syZXJqpU6eioqICEydORElJCXr37o2NGzciNDTUrXsbuW1l0tMC0ixBOAs4ie8aJgFFlXjejXJLytlRPg3/srw7oclBvfdldBStTAizjPblaUg55ALubjuT6t/HpbwtW5ZUGrNZelESLEcPySd3sLRO3hStzD0Z/GUBQhAEwRoszYX+DtUFQXgPNZUHERERyM3NRW5ursP7Z2dnIzs7W9F7W6x1BH3I2KW1Ug4JWNrYjlGW9bujj+LW5WpyoEiwz7sRmdUiJiNb8GVqUmB5WxInPoccXM+gboh8DnFI6HDOsOtYTq4Xs4hhSUurhN8ktREqRrWkc16nKt3YAQw1F4LwG1hcNhGew6RRjYRGxXaIVuuC8G1obaZtTDJ8wjQajUhOb1lASG0icnzrmGXm7TQfptuxMlZSSiDHwTTAdvmSckgAuYoP2enlOC+WaQqunENqL7ZWUaWZzd8eGA6kLjkZ7NsEQRCESrCqj9DCBx2lYbQqCBVQ84WKxZc0lmF1DFQKLvqYBB8y1gpqKeHmhfJz9N5lyZ7nc8hJ7pLf45wGIPJ+x5BTjmojdqt6wehuUgTzfvnaQsohllBwoGXTHNAxSnRu5SKAKZSRA9ytI1+fmAmCZdibzglPosU5FvBNRQrNhYSSuN2cFF3Ls4+vzoWcs2OZPodkGA7Jl0WSVYoyrUYLbY+lsd8SJS4wQJ7PIRYh5ZAMPFWNHnVI7eI2Kda/sLCyNc8TfZ8FrT5B2KLVl2dH+OIzEa7B8LoOgHRfhwShJVhyQOsMLcjoDowPgW5jGeMlOYG22lYmnN7WV47Fh5A8h9RCuiHbenDVus5WWcHiticx/0re6Gu2sjhyYC60XuBkZ6h8LZByyAHigbpEQhlKTK9kIxbLSe7C1XaAEhzaGFsNe7NDiZa7hOlSOYfUBEEQhDeorDV6WwTXoImDIDQAg2+MYmhIVDkYHShwxBQDgLRw8878AtnmLxitzElwI6nV4ux9huXqNTsrSDVwUqdS6r/hAofZeRWKViaAu9HIXEVozaZ29DFXUbMxu/OoSpeTaBQAG7xpqcSi1pkgWBuzCMJdrJv0hBUF6NmuheL3iIsMxRtDOiMiNEjRfC3TxK5T1/D4+zskXRMTHozXHuuM2IgQRWVRAynPVFdV4QFJCE/A8rqHpj7fgFPISNjKxY9WJsHSyPIfie3YJKB4EM2bs/hxs5MwZDkk9iwsRfzirMGkpm/8l5WdLtaQcojD+yZpFlhqJ9Yiqv2y59S5mpjFlgrRyhiqAlHo5ZsgvAdL4zThHQpOX1cl30HdEvDg7QZF86w1Nu17kCN3v5TWGH5XW0VlUYqkVuEovNKg8JHyTKaaSrVFIlRGS+seX58jWNtNoDQmAZ9DYlUqlNYasWjW1u81jpqLI59DdtvBXLT4sduexsnFTkMW30LnjXd423K3yOI8rfUxdkq3CVIOyUCpcVDczFD6DUQjkujkWRqJW8I4vs6THVFUiSaUlrFvNkLycHWk0D1YHFgIgq2eqAw+vhYmZJD35zsVz3Ped8dw4lI59yKgJNbb4BaPuhMBTpwKvP/D7zhwtoSLwMIiN7UIQ+GVCmTcHofHurdxmr6i/AYez1VfLkKb0FrKNXy13DhrHUmWQw3/SrEyAqwUOJIth6Q7x7bgtuGQAx86rMCm5ZDUNtAAi+VLyiEXUGrbmRIhZxULXS9y3FphxeoSUVgBo+49vbX10BrWFGEEQRD+QKBeh/53xCue75KfTimep4U6K8uhAV2cy75273nVZFGa/ncYJNVHWVm4B6Qh1MQTflDctYhR0qKG5Q8SDIumCE3RygSsdWyeXsw/kfMdEcLYlq3QFjfn/oqk9RIWtzXJhYVQ9kLKHmmB7Nkrf3JI7QC5g7K92aDnh06lmphTyyGF7iOE1GLzxIBmOwE4q1MpsisttQ+M6wRBEISK1NabnCciCIKQiS8oF4QQdAItltYkPS0g//3S1Dh8SylrxaJZK5ONIkgxYPA27uoMWIKUQwLItgpR6L6CDql14ucc58VwqxPD6VY251movfVPUTRYRQRBEIT2qCHlEOELMOQkV0208Hwsv9wqgdBWLrF6cbbtS4oLD0d1bnSgqLL3FeTadjBRv0gMNUaWfPWK+miSUEcNx9jdtkfKIS/CUiMXg++Qms2ZQNghNUOFqBZsVgdBAPD9hSNL4zRBOIMshwjCM/j41Oc3uOJzSEpawAX/NDJ8DikV3Z0lfz5iCDn29hayo5UxPFCQcqgRSVYpCg35SmhhnSmWJDukFknodJ+sB/uhJq2gGhFUXHHWYAq1JwYGRYLwWbQ7/BAEh3W0MoIg1Icliws18dXHNDnwOWSLqH8iJ5ZEUstOKFqZs/YlNW9nW7ZYqF9nvns96nNI5GaCPoccCMayQ2pSDjlE/mYuIdTUIiqlGJCmHPMM7lgoKS2jnEhpju6vxiKB3lkJtqEWShCsUEeWQ4QP4GjrBuFpfHuOb3ICLXBSxMesWLQy8VD2wti+B3GWSUJblkTfU+T1ETsfq1w+7GDvB9ZLggjd21GdCu8ra0jP4FhGyiEB5HYocY2mY+Q4L/bali6FBh0puJqjoIhuiif2fFL2DXsaBscVgiAIUY5cLMPm/xWrknd5TT2+3HMOpVV1buWz78x1/HT8ikJSqcPOk1dRcOqapLQshaQ3mcz4+sAFnL5a4W1RCILDVR+ftii5XGfVnYM1vroEFYtA5iit1FDz5ibNgKT0DhVVtnkr5ZeL/abHlF+kJismqaHs1Y+86CqkHPIC4lYn7vdEi1LD3ZyE2jZrc5SwjIwJKQBXR26KqoVnJfwXap6EGA8t+BFPrijAofOliuf9jy/24x9rDuDplXvcyuex93bgz5/k41JZtUKSKUtpVR1GfvQLHs/byQtTL4aRIeXQvw+cx7P/3Ic+b23jji1evBjt27dHaGgoUlNTsWvXLod5rFmzBl9PH47T8x7DpGHp+Oabb3jnzWYzZs6cifj4eISFhSE9PR0nT57kpbl27RoyMzMRGRmJ6OhojB8/HuXl5dz5o0ePom/fvoiLi0NoaChuvvlmTJ8+HXV1TYrHZcuWQafT8X6hoaFulA7hCLl+PbyJFmR0B1+f4y0RwqydQIt9OLaktbXscdYGdLz/i6c2CSiqnL1LSm1/TqNTM6B4cYYnJRS39mo8LzeUPYPFy7RyqH379naTrk6nwzPPPAMAqK6uxjPPPIOWLVuiefPmGDJkCIqL1fkaCSg/ELJgheLUukncdMhjOCt3ISUJK33Nx+dOgvBbyNeX+5y4VO48kUy+PdywBvj5xFVF8rt0o4b7P0svQ2VWllHWih8xGY0MCb+r8Drv788//xyTJ0/GrFmzsHfvXnTt2hUZGRm4dOmS4PU7duzAyJEjcUvvgUgYuxB335+BwYMH49ChQ1yauXPnYuHChcjLy0N+fj7Cw8Px2GOP8fLJzMzE4cOHsWnTJqxfvx7bt2/HxIkTufNBQUEYPXo0vvvuOxw9ehS5ubn46KOPMGvWLF4+kZGRuHjxIvc7ffq0u0VE+Dlaml20oDxwhaYIZFIcUktPC8ifS4wCiiql8hbNh6loWmK7OdiZ1+Q6AmdoSrYj0NsCOGL37t0wGo3c34cOHcIDDzyAoUOHAgCef/55bNiwAWvWrEFUVBSysrLwpz/9CT///LOqcskeCG01yQp2NDvfZy7mbXuZUDae6oRS7+KJAUspH0K8rwMKyc3wuEIQPgn1OUIr2Covb0+I9JIkzpk/fz4mTJiAcePGAQDy8vKwYcMGLFmyBC+99JJd+gULFqB///5o0f/PuHb8CkYNfwRnD+bj3XffRV5eHsxmM3JzczF9+nQMGjQIALBixQrExcVxeRw5cgQbN27E7t270bNnTwDAokWL8PDDD2PevHlISEjAzTffjJtvvpm7pl27dti2bRt+/PFHnjw6nQ4Gg0HxciG0Cc0TvkGTE2j7c7Z1bEkr6nNIzJ+PxPcBR86xRVzfyH9XlekXyRuI+m7ySih72zoVF8aByyEmPzQybTkUGxsLg8HA/davX49bbrkFffr0QWlpKT755BPMnz8ff/zjH9GjRw8sXboUO3bswC+//CL7XoLKEJkjvFijdfV6t1B5dlKjI6oZxU0uoqK4YMUkmla6OA7x1a82hLbx9QUyS1+sCM+i9pCrRssacVdbvDKwEzZOuleF3F2ntrYWe/bsQXp6OndMr9cjPT0dO3fuFLxm586dvPQ66JCRkcGlLywsRFFRES9NVFQUpwSy5BEdHc07lp6eDr1ej/z8fMH7njhxAhs3bkSfPn14x8vLy9GuXTskJiZi0KBBOHz4sIwSIORgbnqjYh5fX5r5+gzoyAm0fVp5VjbOQrDbli1nmSTJ55AyNdPU19htyCwpWORbDrFkmcWHaeWQNbW1tfjss8/wxBNPQKfTYc+ePairq+NN/h07dkTbtm1FFxQAUFNTg7KyMt7PFvmGQa7VrGgYeYENi94ahK1F9LYJnLPwgfy06sri7fsB3q8PgiAIQhsE6HUYe08SOhrkWRCpPc9cuXIFRqORZ9UDAHFxcSgqKhK8pqioyGF6y7+2aWJjY3l5tG7dmnc+MDAQMTExdvft1asXQkNDkZycjHvvvRfZ2dncudtuuw1LlizBv//9b3z22WcwmUzo1asXzp07Jyi7lDUoQWgJBt9tFcEssFVMbK0vpkgSfzeQpxjglE9wLovU81w6J1u2mK5fL1gOOQtCxQ9lL54Py3puzSiH1q1bh5KSEowdOxZAw8QeHByM6OhoXjpHCwoAyMnJQVRUFPdLTEyULINilh4K5CE3xLp4RiLHnfQ0TzZmpcI0egUB2ZWWWgOlQPgh5DCdIGTC0GDO4tdMb/H5559j7969WLVqFTZs2IB58+Zx59LS0jB69Gh069YNffr0wdq1axEbG4sPPvhAMC931qCE2pYCyuTpL3Ofrz+mPMMZVy2HrJCiSJCQv1IGPyzVr7hChh0FljNrMLH0TAhvg2aUQ5988gkeeughJCQkuJXPtGnTUFpayv3Onj0rOw+59SjZxEyuIA7ylrvlgaWtSSwNSGLCuOl2qjFrlh6UIAhnWPdZTSinGYe25imDlqeSVq1aISAgwC6YSHFxsagfH4PB4DC95V/bNJcvX+blYevwur6+HteuXbO7b2JiIjp16oSRI0fijTfewCuvvMLzh2lNUFAQunfvjhMnTgieV2INSqiLYu4JFMhDC12bodcHRZETGc/ZliLRj9wyXxCFXaDY+L6RqaSwuYUdLNWv2+WoJHayWCzNBJI6GFRYXEtqQjl0+vRpbN68GU8++SR3zGAwoLa2FiUlJby0jhYUABASEoLIyEjeTwy5g7JsH0Mix1lqJp5cdLr63EIyutvZXJbFrbuyey+CkAu1T4IghLBeyAcHB6NHjx7YsmULd8xkMmHLli1IS0sTvD4tLY2XHgA2bdrEpU9KSoLBYOClKSsrQ0FBAS+PkpIS7Nmzhzu2detWmEwmpKamispuMplQV1cHkyV2tQ1GoxEHDx5EfHy84Hk5a1DCf2Hpg62/I+fjrtR6c/XdSlr+CvkcstyTqbdSPix9GLFsLfSFrst0tDILS5cuRevWrTFgwADuWI8ePRAUFIQtW7ZgyJAhAICjR4/izJkzogsKqShVr2JfRUU7twMlh9QOYMna3Q7jrAxYmLiEB2x17ylap3JajcJ+pBioCoIgCIJwicmTJ2PMmDHo2bMn7r77buTm5qKiooKLXjZ69Gi0adMGOTk5AIDnnnsOffr0QZewJNRFdcLqvC0oKCjAhx9+CKBhfTJp0iTMmTMHycnJSEpKwowZM2AwGLgw8ykpKejfvz8mTJiAvLw81NXVISsrCyNGjOAs1FeuXImgoCB07twZISEhKCgowLRp0zB8+HAEBQUBALKzs/GHP/wBHTp0QElJCd566y2cPn2a9zGTUA5vRieSCkPvq6ri65afcp5O/GO/E38+Yr5UbQMcCeUt9iops48olY+aOI8R5DkhRetUyC+Uk7QAG+VrC/PKIZPJhKVLl2LMmDEIDGwSNyoqCuPHj8fkyZMRExODyMhI/P3vf0daWhr+8Ic/yL6PV5QdLJnHiWAtorc1tOLFYi8YS2WoFrQtjWAZap4EQUhh+PDhuHz5MmbOnImioiJ069YNGzdu5BxKnzlzBnqrMD29evXCqlWrMP7vL+DGlfexo/0tWLduHe644w4uzdSpU1FRUYGJEyeipKQEvXv3xtq1a9GjRw8uzcqVK5GVlYV+/fpBr9djyJAhWLhwIXc+MDAQb775Jo4dOwaz2Yx27dohKysLzz//PJfm+vXrmDBhAoqKitCiRQv06NEDO3bsQKdOndQsMkIDsPAR1TP45nM2rWGcP5/TbWWieUuVRbpPI1dd2djLxI4/Hwt24eO9GPHLrk4t/xEyXLD92+oAS+VrgXnl0ObNm3HmzBk88cQTdufeeecdbkKvqalBRkYG3nvvPdVkUeplXJl9yMpsShO3bnJ8nZqN2b7DiVnrqI+7NS4ku9ImmiwOLAThK7g6RhIEIZ2srCxkZWUJntu2bZvdsaFDh+Lrsrb48fgV5A7vhoe7t+Gd1+l0yM7O5kUWs40MFhMTg1WrVonKNHz4cAwfPtyh3O+88w7eeecdh2kI5WDJAa2/4+sfgGQpZGTGMfdEZCt3lZMsWQ6JwZJPZzlNwLrrsKhEZt7n0IMPPgiz2Yxbb73V7lxoaCgWL16Ma9euoaKiAmvXrnXob0gplHBGLIQrJppywrs7zsd5GrVNSJXoH0rJ6KyzyndKbn+FuxOrj8/LhMbxNcu2G3vXI61rCkJDQ5Gamopjh/Y5TL9mzRp07NgRoaGh6Ny5M7777jveebPZjJkzZyI+Ph5hYWFIT0/H8ePHeWmuXbuGzMxMREZGIjo6GuPHj0d5ebng/U6cOIGIiAi7CJ4EQRCEB/Gtqc8pDL7bqo7UKna6ZcsNtYb4liXLeffQQjNuUmB5cFuZ01D2OudpecFN2IN55ZA3kftyY2/uJi+9BZacf4k7XfOwIA4QdkjtuXvJOa8GLGqdCcKXqDiyHde2foxJU6dh79696Nq1K159+s8wVpQIpt+xYwdGjhyJ8ePHY9++fRg8eDBGjRrFSzN37lwsXLgQeXl5yM/PR3h4ODIyMlBdXc2lyczMxOHDh7Fp0yasX78e27dvx8SJE+3uV1dXh5EjR+Lee+9V9LnVRgv6Q2sZWfWxwapcaqOF9kNoB85np2IfGRXIhNq415BjlSLXgqXJ55DE9DKseORaMTnLh4V3UqcKGY9JIo6s6HZW/2fxFY6UQwKoZRnkSnq1ZRHNR+CYtxdits/GklJEzToVhRYNBOERynavQ0TXDAzPHI1OnTohLy8PIaGhKD+4STD9ggUL0L9/f0yZMgUpKSmYPXs2unbtyp03m83Izc3F9OnTMWjQIHTp0gUrVqzAhQsXsG7dOgDAkSNHsHHjRnz88cdITU1F7969sWjRIqxevRoXLlzg3W/69Ono2LEjhg0bploZEGzB0PQnGw2LTngZLWx1UQItPJ633wlUR8AqxZkDafHz8txj2BkbOFCDiDmvlu1zSNQRrsyMVISlUPZyZHHUV1hQvtlCyiEZqD0OyhlonVuwSMvM5XCKKjZmW9mVLBf5snj3ein4+iKJILxJbW0taotOILRdN+6YXq9H19R7UXP+N8Frdu7cifT0dN6xfv36cf8vLCxEUVERL01UVBRSU1Oxc+dOLo/o6Gj07NmTS5Oeng69Xo/8/Hzu2NatW7FmzRosXrxY0vPU1NSgrKyM9yPkweJizp+hOZBgCX+z5PP17ifLz4/UhK6+e0myHHItb7t8LPdUJjt1YEhDKc+6S11Z3IWUQ43Ic/IlN29poQpdzV8JpHrY94YMzhAO8ahyIcrMnxavBKFNrl69AphNCAiP5o3Z0S1jYay4LnhNUVERF2nJQmxsLO88ALs0cXFx3LmioiK0bt2adz4wMBAxMTFcmqtXr2Ls2LFYtmwZIiMjJT1PTk4OoqKiuF9iYqKk6wiCIFhBCwpa9iV0D19Xgjl6OntrHXkuOAQdUsu4n+O8LVvWpLVAV62hWECoHL1Fk7N8CdHtrNsLA7LbQsohB8gd9qRrApVxIi09ZxfyEehprE0DglvfPC6FfAmU21Xm/aclCDGodarPhAkTMGrUKNx3332Sr5k2bRpKS0u539mzZ1WUkHAFJb4qsrBYJgjC9/HVsUZWmHSZ2x3l+vNxxY2QUg6pWahe5863vS+lq5ZDLPYfUg4JItMqxEVlj5Rg9Nb/l+MgW6kXM5asm8RgwSG1y1ZPCrwFMFQVBOFztGzZCtDp7ZxPl167jIDwFoLXGAwGFBcX845dvnyZdx6AXZri4mLunMFgwKVLl3jn6+vrce3aNS7N1q1bMW/ePAQGBiIwMBDjx49HaWkpAgMDsWTJEkHZQkJCEBkZyft5C9ZNqwFtKOHVLEf2n54g2EIL4xrhnCbliJXPIRlpJeXtJJqZLcIf7oWdDsl9T7OzhtJAQ+ae3Rs+h2QEoXK0jmDxHY6UQ15ATcWKUuZ/wg6pvTtQ2A26HuhRarwYKFVHGhi3CX/GR9pncHAwgg0dUH36AHfMZDLhQP5PCGnTUfCatLQ0bNmyhXfs+++/5/6flJQEg8HAS1NWVob8/HykpaVxeZSUlGDPnj1cmq1bt8JkMiE1NRVAg1+i/fv3c7/s7GxERERg//79eOyxx9x/eMKjyNveru4EqOaXWJY+LhHaQpY1h0wsWSq2tlJASJanUX9Zg7pTjXLdijjPzzlyFVXOUrE8XisUmE0WotvwBLbzSVH+sbhtL9DbAmgKlQdCJS2DpGbF0uAu3uGko5QCS6m+KqWe3L4XgwMLQfgSkXcNxpUN72DNPz/DQ3+8F7m5uaiuqkKLzg0OpUePHo02bdogJycHAPDcc8+hT58+ePvttzFgwACsXr0a+/bt4/LT6XSYNGkS5syZg+TkZCQlJWHGjBlISEjA4MGDAQApKSno378/JkyYgLy8PNTV1SErKwsjRoxAQkICl8aagoIC6PV63HHHHR4oFYIgCEINtLSsY2FLjxq4EgxH8rYyWNI7j4TWkL+M90OFIvqxFBnQmZKFBQWLHEWVteGB9yW3hyyHHCC+hUieEkOu2aCclqJYfxDNyCzwP7YQHDTV9kctclzpbWeOYEmxxyLVdUYMevcn5Pz3iCr5L/7+BPrnbkdpZZ3LeZRU1qJ/7na8t+2EgpIpy7nrlUif/wNW5p+WdZ0azfN6RS0y3tmO97edlJT++98uoe+8bdhzWthxtFTCU+5Di75PYP4bc9CtW7cGK533V3Lbys6cOYOLFy9y6Xv16oVVq1bhww8/RNeuXfGvf/0Lq1at4uU5depU/P3vf8fEiRNx1113oby8HBs3bkRoaCiXZuXKlejYsSP69euHhx9+GL1798aHH37o1rMQBEFoFZb8oIhBazPfwNHOAdszznYZuPtu4GgbmlTn2FLvYQtLyj9PvmM5w77cG5Adyp6d4uUg5VAjPI/xcqORyd0zKitvuf6PlMHZbVlozF4ZDEQjEkiXRmm5GagKJvnPgQs4cK4UH/zwuyr5v/XtUfxWdAMf/ihNUSHEh9t/x29FNzB341EFJVOW1zYcwYlL5fi/rw55WxR8sP13HC2+gTc3CoeQt2Xcst0ovFKBv3yS7zyxEyJ7DMTP+4+gpqYG+fn56NjlTu7ctm3bsGzZMl76oUOH4ujRo6ipqcGhQ4fw4IMP8s7rdDpkZ2ejqKgI1dXV2Lx5M2699VZempiYGKxatQo3btxAaWkplixZgubNm4vKOHbsWJSUlLj9rARBEIR7+MvajIX3ATVwxcGw1HcBubsc5DheVi6UvXpbOJWCKT2sF+pILUg5pCFkmTh6+f5q3McbA5Taz+xO9lpwlOpN6k2eKZ86o+v3qa03KSiJOlTXGV26Tg0fZa6WV2Wta89gC+sTOkEQhC9DYzA7+EtdSPEhI36t8HFXQ7DzDRkcXyw9lL3wcS3Ur5o+yMQQ32fTIIteQh1ZFy1LllkWSDkkA6Vfxu08ncu5VqFe67oppPKNWTRHJ49qFvm/e7Io5TRa/dGVZa0+QfgSGlgrKUKd0YT53x3FrsJrktKfulKBnP8eweUbNbLuI6U8zWYzFm05jh+OXXaeWAU0sUD2tgAA/r3/PD7decrbYhD+AsMLH3/7cMduTbiHrHeyxn8ll4VMR8py2pRSWy9ZmvucOs1moBVavkdLszSz8jnkfdHtIOWQC8jW9Mq8Xk4jt83L1UZmJ6OQDAwNFIBjrbjafU12ObuxbVEMdwfu7du3Y+DAgUhISIBOp8O6dets8jdj5syZiI+PR1hYGNLT03H8+HFemmvXriEzMxORkZGIjo7G+PHjUV5e7p5ghE/A2HDhMiztcfcUn+48jYVbT2DYBzslpR/83s/44Iff8ew/9zlPLJPv/leMtzcdw5gluxTPWy5aWix7mudW78eMfx/G2WuVTtMq9vHFZ0YZgiWU6udKrPW8HSXYr3GgwLGtF2cWLPbGAAKRrRyJ4ihMuq3vGxetaeyeSUBGbyMWPt4rO0ts/zaLq+XsfVSxDSmHHODqnlC10nsjc7lOtr0BS3OnXFGUmPhdXWhXVFSga9euWLx4seD5uXPnYuHChcjLy0N+fj7Cw8ORkZGB6upqLk1mZiYOHz6MTZs2Yf369di+fTsmTpzokjwEQbBB4ZUKWelLGp2y7z3jnuNvIc5fr1I8T7dhaP5jjdIq1x30E4QzuBdWFfJm6SWYBUsIZ/i6claOzx2528Rcj26mvCyi+ci0bvIGao4HcpFVR1Zdh6Fhh4NC2QvghlGIDSLOi+VYBjnNzSa9Yh6pFcrHBaROOJ4Q0V4zLJxOlpNxJoYx4KGHHsJDDz0keM5sNiM3NxfTp0/HoEGDAAArVqxAXFwc1q1bhxEjRuDIkSPYuHEjdu/ejZ49ewIAFi1ahIcffhjz5s3jwm0T/glLSls1YHFCJwiCIAhPwpJSTQ2s1+zeDigjSRYZjpEBbQQgcoonfQ458dFkfVqKWKy8E1pDlkONsFA5Sr5MqeKQWu2vBE6323kOTw2G7jmkVo/CwkIUFRUhPT2dOxYVFYXU1FTs3Nmw1WTnzp2Ijo7mFEMAkJ6eDr1ej/x84ehQNTU1KCsr4/0IQivwLf28P2cQBEH4E1r46KAFGZXA159T1vPJVMg4y9t+q5gcUZTdOcLC+7GoY2eG2mCT5ZAM8y5GIeWQDJRuhO5s2VJKFLkDlAVPDhVOnWZbnZcbTlJtPNH/1XjUoqIiAEBcXBzveFxcHHeuqKgIrVu35p0PDAxETEwMl8aWnJwcREVFcb/ExETlhfcw5BNAGF80ORd7ImoDhJL4Yt8hCCVhZInnEBZeqgnXkbeVy4nPIVtlD6dNku6SWiy5Un547GYdL/rzEcO+HBvwRl+zW/dZfD0JJrb9kxxSaxZR5Y1oepFtZAo5jRaWRefwb8n52MroqkAexJsdSqycJUV300LhqsS0adNQWlrK/c6ePavavbRQzCxOCrawomgF2CovlmTRKlpQqrEvIb8cNVCkBEEQmkHQIbXUa51YvPC2IElYU/BD2TtJ6zy7xnRi4dbZ8ecjhldC2Ys6Hbc/L0VZyGL5knJIALkvQ1I1xa7J4tp1aiwQPbXoZGlxK6altsML9aRmORkMBgBAcXEx73hxcTF3zmAw4NKlS7zz9fX1uHbtGpfGlpCQEERGRvJ+BKEVxPocS2MWoV3kzPdqL4a5/FVo3KRYJVyFpa0uYijZY1ieWliWTQnkfLyQ67zZVQfWstK6OdBqYV0jHh/M88ix2OI5KGBwQiTlkDeRHQ3N8z1V3BpK+cbsbLIXvaUKxcJeVxVHDVmTkpJgMBiwZcsW7lhZWRny8/ORlpYGAEhLS0NJSQn27NnDpdm6dStMJhNSU1NVkIrQElpYWMjHyhRY8ChBsIGW5jCCYAHFnQ27kSGD74uiaElWOXDzOs8SxMmuAYm+cZqUSRJ9FHGiCIRJF91qJROxfBiqX/Gtb17YVmb3t8XSSiiUve3WP+G1JCtQtDIZKPWyo0QbFpXF3T2mlmwYaq2Stmo1pVZVFrkIyc5K2ZaXl+PEiRPc34WFhdi/fz9iYmLQtm1bTJo0CXPmzEFycjKSkpIwY8YMJCQkYPDgwQCAlJQU9O/fHxMmTEBeXh7q6uqQlZWFESNGUKQywudh8WsPQRCEL+OJjw4sbXdlSBQ7WConNZCjwJGvkHHio0hEmSAtTLoyW62a6pfdtQ5LCiw5xcW3HFJDGvcg5VAjsupG9rYzsf2c7ssidWBxmo9MHzosISSix0zu3UzvnuNR9yqnoKAAffv25f6ePHkyAGDMmDFYtmwZpk6dioqKCkycOBElJSXo3bs3Nm7ciNDQUO6alStXIisrC/369YNer8eQIUOwcOFCt+QiCFYR31ZmBssLKIIgCF9CjTWeUnlqYd2sJCy+3CqJ4PNJrGNnRSO36Phh0h2/W0r2OeTMd5EG6tej0aydvC9LqSNefgwWMCmHHCF3gJc8WKjXEJTKWdgszjNId/SmqhgA5CtvpHxJYWUYuP/++x3Kq9PpkJ2djezsbNE0MTExWLVqlRriEQTTsNKPtYwW3qG08HWcfQkJwv+gOcJ/kGutI7irwEGLkTPGKzVlsWQ3JO7bl53Zr8mKSYKlGTtiC0I+hwSQr8l13+pGrIFb581SW1JjsGBJeSrXybg3RWep3AjCAkvjlVKIPZMvPithD0v1zLJDXmcoJTnrC2xCDdSPoMRSs3LPulxd2JXMfcR8wjiNVCWWn1h6mcok4VD2wsi1SLHfyuZaPmpi+67s1W1ldn6kxMcme79QbPceUg55ETUXNkprjtlAu1vfxNCy7EQDVIf+Ay/8KDvrJWagrkAQhFZRTuHq/kiopflFTUV1+/btodPp7H7PPPMMAKC6uhrPPPMMWrZsiebNm2PIkCF2UXZdgT/XK28J0qRIkOiQWpb/H2UUqFqYz5vKnZ0OI6nvyohs5g1IOSQDxTqK0/2dMlqWS9da5SJmCcNQg3XFnJIh8e1QSgtPSgnHsNSGxWDpi4wYLkvoR1EEfa0vstQsWZLFAoMi+TVaGEcJZfCMQ2pl8lE1+AwDeEK23bt34+LFi9xv06ZNAIChQ4cCAJ5//nn85z//wZo1a/DDDz/gwoUL+NOf/qSoDPL8wOps/hZO50ynIeXdzNkOB6ntTzSZA0sYVuAihHlQSKflblVirlqaeRvyOeQAuQ6jvTGGi8oiUxg5HvClpncVpiZDmdvIFAoiJwstby8gCNaREtGRdRNhgiAIX4Jlh9RKoCWFp5qixsbG8v5+4403cMstt6BPnz4oLS3FJ598glWrVuGPf/wjAGDp0qVISUnBL7/8gj/84Q8u39fZjG4/58tTpMj9kC3rIzksebtXMSxFAnOukPE+chRVLG7Zs4YshwRQKhKVM6yVLUqFplcaTzr7cvVR1Xgxk9thWe3gBOEtfFFh4ovPRBAEQTTh7jiv5LKZZpwmamtr8dlnn+GJJ56ATqfDnj17UFdXh/T0dC5Nx44d0bZtW+zcuVM0n5qaGpSVlfF+tsj9GO7MWkfcV45zKxPrCwST2Pm+sWToID+hbETyYen1xk4l50Uli6iPJsG0wtcyVLQ8SDmkImITjMtKEAmzhGLRylhtsVZ4RyGjwF5yBaQAaNHgDKYs0ERgKdKCGCxJyJIs1migGtlEA+WmARGp/RF+A+tf3K1xx3KD/acDPD06rlu3DiUlJRg7diwAoKioCMHBwYiOjuali4uLQ1FRkWg+OTk5iIqK4n6JiYl2aayfjLdNSCRPV7/vy7Uc4imTRNPKVDw46Uta2J3gSQmd3ksn+F/hpIwWLSmHZKD0i5w7xkLORJEuKfurSmchIq3LQmgA9RZS2gst6rUPA02NSXyxbfOcVGpgwURoE0kfgjTc/FiYnwlCDKbmLpZkEcFTvfmTTz7BQw89hISEBLfymTZtGkpLS7nf2bNnHV8g4wHlO5iWhydHTrNDcyXP4mvrLabGGAHI55ALuLvtTMmFkVTnZ07zsfvbPiOeJl3FxZ1Uk15PDBVS/I1IQbLpqCv41phJEARBEARhh5pbe5VamykhoRb0p558wT19+jQ2b96MtWvXcscMBgNqa2tRUlLCsx4qLi6GwWAQzSskJAQhISEO7+f0A7zMrVxy3yXst0+JCyQegl70EuF8xJ6JIexl9LxDalFZHKYV2VbI6AscWQ45QK5m1x3LIgb7oMdhaTJUc+sf4VtQnfsPvLrWiRwnCBdRYqGo1MuzZT6mpk34G4q1eSWilWmgB3rCEnDp0qVo3bo1BgwYwB3r0aMHgoKCsGXLFu7Y0aNHcebMGaSlpbl1P+tyl+RzyFWH1BIvkOMcWjGH1OwYDonCopJFiixmxguXLIcEUKqRydU8C8riYkQcpbbAaeGlx5MiioaXdDU/N6TXgr8ab8KSslEMLWyvcL1tK4+3S4u3YPSiHARBEP6Imsserb1gehtPrUBNJhOWLl2KMWPGIDCw6bU1KioK48ePx+TJkxETE4PIyEj8/e9/R1pamluRymzh1YRCwWqalEky85MSJl2mNY0zP0osr1O94jRbzs00EGVNCFIONSJHG+v2vZydd0MWuQONqLJDIBtv6SLErDUdlRMLHU5ckaSsdCw8K0H4M1r4ukv4Fywv6AnCXdRs3u6udZX8cKeFb4BqjzSbN2/GmTNn8MQTT9ide+edd6DX6zFkyBDU1NQgIyMD7733ntv3lFvusi2BXEwvB3f7CKdkci8bRRDffqeBDuIAVqdpUg65gNy6VPMLgC9GJ3NnMlR6IhWb5OVr+8XylykQQWgEX7Rs4zmkZmnQ1ChaWNjxAh6w2qYZFUttWK0OQpsoPaS7kx1NL008+OCDomNvaGgoFi9ejMWLF6t2fylzvdPtTbKVTbY+asStgURD0Ms1FhA5zlZbFHknY8HnkEO/UMKwaiFIPoccIHfdoXZ6b+DJxburnUSVBbuL/dWT5aWF9kMQ/gC9pDZC5eAx2FxSUl8g1IWaFzv4cl/nRyZ1fL7hb7EPyc7zlyuP89zl4UyxwqoCA/BOG5Sz+0es7FjvO6QcEsCdSFSu5i93YJGTt6/C0rPK2oLKkNwEoRaMz31uY92Nfe1ZWRqiWJLFAo3hbEHV4X+o+8LKzojOjiQO8PEOyH/Zl57WEU2WQPIiGctyju32tjL3rvcELDqkloJSdaQWpBxSEWf9Su6WJTkdValOzTOpZ7QxCz2qWjIqPVYqkR9tbyEIz8DfVuY9OQiCIPwRVR1SsxTKXoE81IbZbbYK4OouAKm+ceQ6JHYYJt32bxerRc5WNk9jEUF0C503tpXJSSu69Y9NSDkkA6XGQSUag1JRs8T3mLLTZJs6P18mISWa0tu63PJ/pJwYwvn77rxM+AD+1D59eZFMEATBGiw7pLagxDpaC3MLO28LysHfViYlNLn0tIB1JDCpAlnSy5DFzfbHugKjAXYUWLKURY3/svSubQ0phxoRqiDxSF7yLHtUrXuF8mbBJI+lPuK0PJzFfrRNztCzEcrC/tKNcAfrxTk/lD11aoIgCF+BqTGdIVH8Eet1naArEFtLILmOkp0ok+ysgSxKEAl5i0V4FsPp6wzDbdFV59vu4NxHk/O0LEWCE4KUQwqgiCWQWN4uahWUsqARUngx15gZeDv3pjNt5uqDEZha6InAvoRsKTZZksUaBoYgTaKBj+LQQu1qIeobQSiBJ9q6u3dQclxjuWezLJu3kO9zSPn8OcWDYqHsvb/wEjXK4M57ThYlYF3xRsohFZFredSUwI2bKmZJJABjM4HjYlSnxymizGF0MCAIQjrUjwm1kDTLaLj9Ud8h3EWNJsRUKHsNdXBWt8a4g6hPWFFLEGf5CR/nWZk4qHNH+SsV0EgLoezFQ8J7Hl/+uE/KIVmwox1Rah8yi/uZ7Z2iNeCVzu/OtSqXLXs1RxC+jViXZnAYJQiCIFyApXUxQ6L4Fc62ldmlVyQ0vYP0Flmk+D+Sl7Xq+agJS31VToGxJLYQpBxyAdnh5UWOK9E4FMvbyd5VT+CqdtrazFg5R4JOzsvNT+K+YoIg2IW3YBQ7QRAuwtIXWk9bLixevBjt27dHaGgoUlNTsWvXLofp16xZgw0zh+P0vMfw98f74ZtvvuGdN5vNmDlzJuLj4xEWFob09HScPHmSl+batWvIzMxEZGQkoqOjMX78eJSXl3Pnjx49ir59+yIuLg6hoaG4+eabMX36dNTV1dnJ0rFjR4SGhqJz5852shAKoma0MvWylg1LY4EYrL/guoNsh9SWtHYV5/haydvQBLaKObtUqkWXs3QaaIoe7S9yyl2pOvI0pBxygNy9zVJTCzUF5SKhKdPQhB2wWc6x0ZjZkIKPlGpUetHNSHUQBEEQhGw+//xzTJ48GbNmzcLevXvRtWtXZGRk4NKlS4Lpd+zYgZEjR+LmewYiYexCpPbNwODBg3Ho0CEuzdy5c7Fw4ULk5eUhPz8f4eHheOyxx3j5ZGZm4vDhw9i0aRPWr1+P7du3Y+LEidz5oKAgjB49Gt999x2OHj2K3NxcfPTRR5g1a5adLOPHj8e+ffswePBgO1kI5VE1WpmXr9cavr4EFXwfUihitBhq5681/PW5vQUphxqR4l1c9FoFLF5E83Yta+XMCjXwaYAFEV1uA27IroW6IQhfQqzPkUNg19BCqWlhmLWWUWl5PfH88+fPx4QJEzBu3Dh06tQJeXl5aNasGZYsWSKYfsGCBejfvz9SMv6MoFaJ+PMzU3HnnXfi3XffbZTZjNzcXEyfPh2DBg1Cly5dsGLFChQVFXF5HDlyBBs3bsTHH3+M1NRU9O7dG4sWLcLq1atx4cIFAMDNN9+McePGoWvXrmjXrh0effRRZGZm4scff7STZcqUKUhJScHs2bN5shDaQXGfQ27kRy/DXkZUOSMWrdqxE2j76GOKiCN8zsUx226sZ3Dus5XRmyLKrkOe8AwWrhWkHFIRsReGwICG0aPepKzDMwAIaszbKJK3VAL1ekXycQWpi9HAgAYZhcpRqUlejYEoUN8knDfKlyAIBaDVu9/BkqJISw5rbbGWvba2Fnv27EF6ejp3TK/XIz09HTt37hS8fufOnUhPT+etsTIyMrj0hYWFKCoq4uUZFRWFnj178vKIjo7mHUtPT4der0d+fr7gfU+cOIGNGzeiT58+drJYYy2LLTU1NSgrK+P9COl4oguy1M8Bdj8E+vJHEetnkzLSuu7M2WoLkoO0XBOw3lam0HYwrW594uPJUPbSI6c5rSNGi5aUQzJQanwOalRq1NW7nqHYlZa8a+tNbuUTHNjQYuuM9vmo15Yda8VsO5FFEWYto3Lb89xHTBS9XscpiITKVy6sDi7+AqPrNkIFxKqa2kADvvyyYI2WFTNqI7cNXLlyBUajEXFxcbzjcXFxPEsfa4qKinjpdTp+esu/tnnGxsby8mjdujXvfGBgIGJiYuzu26tXL4SGhiI5ORn33nsvsrOzRWVxJntOTg6ioqK4X2JiomA6wjHq9EFl8lQmqq12xhgNiSoZns8hSR6pG9OqIw4HzT2EJyDlkAPEQ9GLpZdmCcQph6yVGi4uqm0HLaG8JeVj8zenZDIq7+xZKVx9ViUQ1RxLjLMoV4lHEIT3EXNSydjQ6DYsvZiwJAvhn3z++efYu3cvVq1ahQ0bNmDevHku5zVt2jSUlpZyv7NnzyooKUF4EF+b+EQQ9BMrllbuu4FcWWT4P5IPwxXa+NwsWdGpHaHOmwR6WwAWkbsYlbt0DQ6UrtSQuy52ZPEjB28qXqQSrIAFlrcICtChqo7t8iWkQe+u/gnVO0G4T6tWrRAQEIDi4mLe8eLiYhgMBsFrDAZDQ/pm7QXTW/4tLi5GfHw8l+by5cu8PGwdXtfX1+PatWt297VY93Tq1AlGoxETJ07EP/7xDwQEBDTJIlH2kJAQhISECJ4jnOOJl0Ol7qGkewOabzyLfJ9AjTscpKZ31sZ4fuTkBkdSpv1q4c1KSwoXa1iXmyyH1ESk8i3boWpFFAPuzAFNSh33Wl7T1jeBbWUqT1JSJW+yblJv65vtIKtUh25SECpgfkxmpgThIUQcUrM+0xMEowQHB6NHjx7YsmULd8xkMmHLli1IS0sTvCYtLY2XHgA2bdrEpU9KSoLBYOClKSsrQ0FBAS+PkpIS7Nmzhzu2detWmEwmpKamisprMplQV1cHk8kkSRZCHdRYh7KkgGFIFKf44hrUek7n+5ARSy983Lk/HymyCOenRN5S0rHUL8RgIZQ955RcQlqp570FWQ41ImNLqdu4apVjragQG4gcKUwE8xTJJ1jAn4/aOPPyb7c9T4YFllKyyMHR+6IWLLMIguAjtkgjXEMLOjUNiKgJGR0xefJkjBkzBj179sTdd9+N3NxcVFRUYNy4cQCA0aNHo02bNsjJyQEAPPfcc+jTpw9uD22Puujbser9rSgoKMCHH34IoMH6e9KkSZgzZw6Sk5ORlJSEGTNmwGAw4PTp0wCAlJQU9O/fHxMmTEBeXh7q6uqQlZWFESNGICEhAQCwcuVKBAUFoXPnzggJCUFBQQGmTZuG4cOHIygoiCfL22+/jQEDBmD16tU8WQjtwVp/Yk0eC6zKpTRydpOoHaGOtlkTnoCUQy4gV0tum96iGPjslzOwBKsyuRi1ylYSSyS02noTXvryV+itImNFhwXhr31uQVRYkH0+NgOOJRLYwq0ncKWiFgBQVWt0SUa1CGp8tpxvfsPxS+UAgOuNsqqN3OHZdjy31NOLX/6KronR3PHgAD1Gp7XDzbHNeenX/3oBO09e5U3Gx4vLZUpBEIQa+MsimWAHLb8j2Mo+fPhwXL58GTNnzkRRURG6deuGjRs3co6ez5w5A72+ydC9V69eWLVqFcb//QXcuJKHn9vfgnXr1uGOO+7g0kydOhUVFRWYOHEiSkpK0Lt3b6xduxY9evTg0qxcuRJZWVno168f9Ho9hgwZgoULF3LnAwMD8eabb+LYsWMwm81o164dsrKy8Pzzz9vJMn36dLz88stITk62k4XQBix1KS33b1/A9VDzYpGslA9AJPW85PswvJCxlCpbIsrd7qcdmFcOnT9/Hi+++CL++9//orKyEh06dMDSpUu58KNmsxmzZs3CRx99hJKSEtxzzz14//33kZyc7Pa9XR8cHHNLbDj3/1X5Z3jnQgL1nPLIFWKaBaNFsyBcr6zD6t32jg5vatEMo1LbSpCxSTlhK2NkqL1yyRvc0rpBxlqjyV5GAQWYJ5A6AdwS2xxnr1Xh8IUyHL7AD2V7o7oebw/ryv196UY1/v7PfaIDd2QY892YIDSLWeT/1gp1lhdVBKEFsrKykJWVJXhu27ZtdseGDh2KL6/fhF9+v4Z3R3XHw10SeOd1Oh2ys7N5kcVsw8bHxMRg1apVojINHz4cw4cPdyr70KFDMXToUKfpCPfxyFCrWNRbJaOfsast8kVFllOXQGbHfzvNX5YszlRP7ski5b6swpKMsupUNSmUgem3yuvXr+Oee+5B37598d///hexsbE4fvw4WrRowaWZO3cuFi5ciOXLl3OmwxkZGfjf//6H0NBQl+4r3ypE3hUZtxvw1uNdcLG02u5cj3YtEBoUYCWLvLwDA/RY8UQqth29xGt83xy8iN+KbqCqTpr1z7CeN8EMM66W21vi3NOhlSyZ5CK1r4/vnYTmIYEorarjHdcB6NuxtfBFKskitw3k/Kkz1u27wNtWtv9sCbb+dgnVNnV0qayGk2PyA7fyzsVGhODe5FgQ3oOhuYkgCB+ApQUvQfgLLG3Z0YIfH18epjgH0zbVIOpvRiy9M38+TvJr+L9wfs6bq7Q25Kytsd8SPSujHB9NztOyWbpMK4fefPNNJCYmYunSpdyxpKQk7v9msxm5ubmYPn06Bg0aBABYsWIF4uLisG7dOowYMcLjMlvjKNTh0J6J8vOTOBB3vikKnW+K4h07ebkcvxXdkHyvwAA9MlPbyRHPbeR2kdCgAIzp1V4NUUQHS6XmwvioMPzt/lt4x1bsPIWtv12yS1tT36AsahvTDM/2c98izm9gc8zlowUZGRLS2xOp2BisVHQQgiAIwru4O5orrTSh2cV7yDYWcOdeEtY3WlAaqoG3137+BtPRyr7++mv07NkTQ4cORevWrdG9e3d89NFH3PnCwkIUFRUhPT2dOxYVFYXU1FTs3LlTMM+amhqUlZXxfoC0DseSltzVlxHbL5IMPZIoFpG1Nii6XEc211XXNVgXhQYx3V0JD0Dzo3chiw5CTZjq3yzJQhCNcOtBFTqL0jm6JSL1P+8id5sY1y4dn3dJFKdOhyh0vTeQvZWQJeGdwPTb5u+//875D/r222/xt7/9Dc8++yyWL18OACgqKgIAzmmhhbi4OO6cLTk5OYiKiuJ+iYkOLHhETX/kpVdzwadU3jQPyUPpcJaOsGwzs95uSBAEQ2hnzmcKLVhcaWE9p6VFp5L46WMTKsNaf2JMHA4tjN+u0hQlWdoLn/jrosguBBlFxytnCVuWZNeKUvl4AW/IKKdOlah/b8C0cshkMuHOO+/E66+/ju7du2PixIlc2FFXmTZtGkpLS7nf2bP2TpvlKlxI+aMsWpxwlChfsTxq6hssh4LdcFRO+AZa6se+iPZGJs/C+oLHl/DUWCD3RVlKcrmy5/9+Ff1zt2NX4TWZVxKEdJRabyuxhmXKitAPadqxIO8C2dGsJVS09Zgqp10o9v6ogbbI1rYz6bKwJLU1TL9txsfHo1OnTrxjKSkpOHOmITKVwWAAABQXF/PSFBcXc+dsCQkJQWRkJO+nFqx9fWAdlvq2uGWQ+nUqFgVBr2eogAjCDxH3OUSoBUvzggUWZfJlhn/4C34ruoFhHwi7C9DalnPCdTiLDq9KQVjD1ou5ssh2MK2QFY6cXQj+FcqeHSHVimjOAkwrh+655x4cPXqUd+zYsWNo167BUXJSUhIMBgO2bNnCnS8rK0N+fj7S0tIUl8fbjdIs+odzxAZvLSiwuHLX2Pwju2jF6khTQwqhJr68CNMyGhhGCT+BmiJBuAdrfYjVNaAvz3tyy1yJolBqdefL9WKHPz2rB2E6Wtnzzz+PXr164fXXX8ewYcOwa9cufPjhh/jwww8BNLwoTZo0CXPmzEFycjIXyj4hIQGDBw9WTS6WXs/kfjET1Uaz9FAaQP7WQ+kXqOG3iPANqA14F1YX6QRBEIR7sGSBxo4k/omzQDhiFv5SLY3krCT428qaMlSqvYp6VaLljjCidSrodEh6WoZgWjl011134auvvsK0adOQnZ2NpKQk5ObmIjMzk0szdepUVFRUYOLEiSgpKUHv3r2xceNGhIaGyrqXUAeWrzlmu7K1AksDkmx/C6rIoEKmhGJQv/dPrMcGagMEa9AHH8IXsYy7arZvd9dcioeyZ3x68cWhhityiQ9ndtXnkCRZmhqAnNyVqxf2a5glCb3hF0ppmFYOAcAjjzyCRx55RPS8TqdDdnY2srOzFbunGp3b22hDRnaklCuJEh3cWUwEVgcRVtFCcbHU5sVgqd15XRTGF+lag/WXHkArW68JgnAXpuY6loQRwR/GHdtacLpmU8gMRzT6mZAhg0IVwfJHLu65GRJRfih7deRQA6Z9DmkdpduBEotUljs/0YBYHWlBkUAQvozY6KmlSZ/wDbTw8iiGhkUn/ACl1sla7qP+Dgu7Bri85Soh/Og9z3+e1LOQckgGLL0AMCSK6sgOKeljaOHLNeEZaK3JJtRDCYIgPIevT4Vaej5fXJeI+RBymt7muOj1Atsjpfgn4n0kdjFymtR0FiWTFurXkzI6Mw6zPi8e+dpZbt6F+W1l3kSu82bx9OpVvuSsFRpEPAFLL1qipp2iTurErH6c42qITMJ/aGh3LPUQ/4L0tARB+ALVdUZMX3cI+85c541rEaGBePPxLuhoiHQr/6/2ncNH2wtRXWdsOqgDRt7VFhPuu1lSHqVVdfi/rw7ifxfLuGmvuKzaLbmkIGecv3SjGv/31SGcvFzOyXihtMpr8shh35nreP2bI7haXss73i0xGm8P68p7d6mtN+GV/xzGrsJrMJkaBKqsNcLXEV3ri6VXeaHur+8BtHPCs5BySADZnY8F5Y9EWH65YWrQkymMkrKzXEcE4W9Y90cxc22y7iMIQkus3Xse/9pzTvDcxkNFbimHKmrq8eKXB1Fbb7I7t2zHKcnKoU93nsL6Xy8KnmvXMtxl+cRwZR2Xt+13bPpfseC5tjHNPCqLXF75+jAOnCu1O/77lQpM7d8RhqimwD7rf72AVflnBPNp19L15/QVON+gTs67lLeT9YVS28i0sIxhSURfDlpFyqFG1BiHWepopHVVBjXr1FkdMaU80wAMdT9RZE8WXmgDLI1jDIlCKIAW6tNaRrX7gqvztBpyaWG60UL7YZUDZ0sAAA/dYcC4e5IAAJ/89Du+PVzMWYa4ym9FZaitNyE0SI/l4+6GTqfD75fL8dLagzDKyHv/2QbFxfCeiRjS4yYADeugFs2C0aF1c7dkdIScpz9wrgQA8GTvJDx4uwFAg4yxzUPQvpUyCiw1XirrjSYcPN9QvrnDuyEhOgwAkPnxL6gzmmG0GVQOXygDAPS5NRbP9O3ArUf1Oh06t4lSXD5vI7qtTHTniLK+QvnRUIVRKgS9lt8PvfFhTlY0MvXEUBVSDsnA2wsRNRapLL34idE0SGurm/lTHfkzWp5YCXmI9UXqo4Sn0fKoo7W53Be5XtmwleieDq1wd1IMgAbrEEXyrqgDANwWF4HUm1sCAJoFB8jOp7SqQcY+t8VyMqqJK+2ypLEc+6XEKSqj2uuKG9X1sOjpBnSJR1BAgwvahjKwn9Au3agBANyb3MojdeFtOH87Mq+T7KNIRnrr9YU8xYR7bUhL/l5ZWIfLeVeV69PK05BDahfQcqh7uT50vAJDb1py/U6JISe97S2bJimG6ojg8KSpKLUAgmXYGbnVhfqhON5oA6wusFmmvKYeQIOPIQtKRYtuyjvI7pyc+fJGtb2MHkFGAXhCRjWWxJY6CgsK4BRDgFUbsLlpTaPvqDAXlHxaRuxFX65/USl1KEWpIPQeoFwoe3axFA1Dr4cUyt5fkVuPLFe8FhZPLInoqizuNAEt1JGW0EJxakHhx1K79LYoDA/xikJ1Tljwlzbvb6ip1LhR3WA51DzEvbwtMrqbj1RcGWssMkYKKMLckkXlga/MUkcS67+60X9UaKB/KIeYevGnQZjwMKQcEkC2GaEqUljyVjZ3lhVYWkbJerKtI9bNDwnPQW3Au4h9LaRxlSAILWGxHGke0qTUsFguuDue3bDkbW2V5MKXf4uSyeOWQxKpN5pQ1WhRI1XJwgrlFuWgjeJNrJ4sUedCg/xEOdT4r0SXQ1Zh321SyIxu7SjvhvytshazapKetV2evHw0sK7xiqWqjPc98Tpiu3BJOSQDuY6vlK56KVFzZOfJeAMF2FKayykvLZQtoS20YGlEEBaqao04cLZEFaeRZrMZh86Xci+QrnKjug6HzpcyHXGupLIWvxWVeVsMAPLL6/TVClxUOLQ34T51xgZLkKAA5eeUeqO5MW/3XjHqTcrkIxepa7d6K+faapSjBTVGJrllW9NoORQS6GevjXJdSMjOXp6CR07+Sn1M1IKPOJZElFVHqknhHn7Wyx0gx8mXiv5m5CK10zpLxVLHUmJQVAqlFDxSXuqVijxA+C56hvqpPyLWFW0juxANjPr4Fwxa/DM+331WOIEb5bbt6GU8sugn9M/90eU8AKB/7o94ZNFP2Hb0suB5Fqq255zN6J/7Iw6dtw87DfDnKbWVXFx5HRMuL2tuVNehz1vbkJazVVWZCPlYIpIFCEwq7q57jFzeTccsayA5OVvy0XtogSr3NiarviZUjizDla2N3GJr1Ro/sxxSGjXHZeWC3zAw2TmBpY/u7EiiPKQccoB8SyH2mwrLMrKknXZZFEWKV8TRHUPlQ3iHEFqYeReR/l1Tb/SsHBph35kSAMDnBSLKITfYcPAiAOB8Cd8qRe4wabnekh+LWL7y//j/7J15eBRV1od/3dkXkpAQkgABgixhXwUDKArRoMiAIIMMDogIn0oUxBVGQBFFGFlEEUYR0BkQZVRGRUFEFoWwBVBEBGRHSAAhCQGy5/sj6UpVd1V33e6qrlvd532ePEmqbt86ffd76txzjl4Srhk1HdjK6xsV5XU+v0j2Os1kxmNTaMspXjzdI9qUJgEeNlIhHy8rXtR+/3KR5ZCeCiw9Nu3llY4KPGfYLM0CdbSQMhNqa0RftyMa5UNVyoQ/hLIn5ZAcXFkG6Zc3oR161hO/6jzC2/idSTdn2BbI9hSXyl8nqjDBC0lzyMgwG+i9dmB32GqCAvYjbEOZWPGiVZuRs0pxx+dQuRPrJj1gPbZdIRr2tZZR7/4rWI7ZPUipnpR88PgqitHIFKOXMebP4qLCl6IjaQxPX5VljuNJbjlop6EjPC2GSMmkDXpWqas6oirkE292czOYdJvMup4JW8QWh+ulZDnkbXy4mfkMVEf8ImeV487RLznKZSyHav5Ul3tlZSVshjneOlYmPFtlOvFxYk+tpJyhxxJD+ViZ7Zny2iF/s2Bn/rY6RzRiKX/NfA5pk41HmKndMVkWcfq1zOVe398RO6R2c7ZQioTFE44y2qIAGC+LNz6r9P0JNswwmbCKKLYcmvnNIY2lqVqE92ubhDb1o4VrrKUYHGhFUbUlzbB3dwjXS8orkH3qCh7pmYIAlabpd7ZMQJfGsTUXDK7SohJ5JdBr3/yGW5rEyt4TPnu9UA+RTIEZRjCej1zb4GkqcOdltgmGZL9BT38+zvwZqUXc1r1mOcT4GPGxMq2LUe/gE6xH/wTLIerDbqGn8Q9H04LucDUHsrqe4Uh2V5ByyAmKjpEZw/7xcOaUohyx4aq8WMMTqplQXUUtoElZO4pKy3HwXL4QVcVGREggWteL8lix9PuFq/izsMThepv60YgIUTfsXi8pw6/nCiQLUPF5/39tOe6RjEps+/0SvsjsqSptQVEpfjt/VTJJxtcKwZnLVX5Jso7/6fCZJT+eUC3L1wfO44fneqtOz8L5/Bs4/ed1h+spdSJQNypU9jNbjl5Eo7hwAMCh8zXRo346k4efzuQ5fV5FseOzCPfx5fHQTItIZ/hyHZkdm3JArHdx5+iXfN62/GSsktT68xEl9LY1qtpNX6WoDPV8GaXHeKBklWX7HoovabUXxZSorRPWdmGxsOQtf521uZh5f2jESx1fsAxyBSmHqhF3DtaOomfHMmm78ju8UU/UFrRjwqr9WHcwR/beq/e1wfBujdzOe+OhXIz+YI/svfYNovE/lYqXh5buxq6Tl2XvWSzAIz1T3JZRjnP5RVj783kUFpepSl9RUYnB72zH0QvyFjG3t4jH4E4NhP+f+Gif8PeYW53LfvlaKT7dexbXivU5rnUu7wb6zNmCGzLHwcKCArDzH30QFRrkcG/tz+ex9mdHR7yuvg9QZTk0Y75b4pofhdUuVzoQBWEkkcB0ltjYQAhSXG1q2H1s6ABXDchceDtambt5AI5Hn/SC9Sk1Tp21l0/vTWXNsTK2z5l1s8sbZngBQKcW2PCl0iLlEEFwhsMA40sjjkrKKyrxwqc/4+ezjqGbWybVwty/dpAsGM9cvo6nV/+E/OulwrXDuVcV87cpXcKCApAUU2Ul8mdhCfJvlDpYk1RWVuLlL39F1jFHKxjA0UmxWKHTJD4CAFBSVoGzV27gp7P5yJi31aWMFRWVQj51IoMRFVajqIgJC8IbQ9qjSXyk4vdzh53H/8Tan8/j+MVrqmTMu1EqKIZS6kRIFo11IkMwa3A7JIgscGzKobQmcfhHv1ZOZTmaexWf7j2Ly9dKVMkCAKt2ncYHWaeETY8zfvkjX1AM2eoIAI5fvIYbpeXo8sp3SKlTdb1U5HVUnBaoeuv6UPfGePAW18rEgoICzHCZilCL0ksZC/xjyDTH214FGc0guo8jF61Mq2qRO7IkWCUx5mGfjzdQ7XNIx6N5EnSxHJJXbNX4HNJdBK5RPDnCmF6478HJEtd5K5xYYOzRijJyMF4rtUvhPgcy2lA+BeIoPa/zOCmHGDD6TZn0DSYbrEfhjIQn3w8OE6Se54BdOaTmafTTmf1nrmB19lnZe4dzr2J8enNh8w4A/9l5CrtOyFvZyHGj2nfMt0/dhuTYqmNCr679Fe/94Hjk6cSla1i+/aRiXr/8IVVg2fzSPNG7KZ6+qwWAqmNm6XO3CvK7oljk+HjLs3eoPoqmFWpktClXggOt2PTM7arzZn3LqkYWAJi17jdcESkHnWGTvftNcVg55hbheuMX1gKo8o9k/9zk2DB8//TtqvL3V5QWqfyM6MqwyGjUWMzTm1yleVqxDVRWQi+tkP/MjNpRIROtTMDDZiYbrczNPAAvhrJnfIzTMvSuKMwoKrZc7hX8q7cxHwvTuXz8q/QJoyDlkBswHzvTcSGpmTd6DhQPrqN1eU9GniKH8aQs8xb5N2o2+Ssf6Sb8PebDPbhWUi55qwgABdXpu98Uh8w7mgIAZqw9hF9FfmFsVFZWCsqBsGDX0b+UZPnbkp0Aas7u23CV95DODXBfx/qSPOwRH3cyIkLZ329phLvbJAJwImO1EiyMUT7WIwL92iVheNeGTmWprKwU6mne0PZIqBXqNL0tuli4Qh2FBFqx7KGbJdda1YtiktvMcPU2S2Ew5mDKIlxAdcQvckeitKovZ86O1So4xfOq16OVMfpF0ls+PdaA5S6chtvXk00G6tNsuH9S2HWdK1qoMDYXM9epEe9LWNZHXK2lGKBQ9k4w2lJID3h68+iLaFG8yiai/kNxdbSrmxvXRvemdYSfQAUnBrb0t7eIF9K2FUXckqQVWeWoUWzY0t8UHyGRRYkb1bIo5Z3eKkHIw/6YUk0eNVY5XntrKuKO1HiX39OmYGFVDqkMVFYjS4u6giyNq51B21NWURP2uHeLBNd1VK3YUlK89WoeL6nr7k3rYMWy99C4cWOEhoaiW7du2LVrl1O5V69ejdTUVISGhqJt27b49ttvJfcrKysxdepUJCUlISwsDOnp6Th69KgkzeXLlzF8+HBERUUhJiYGo0ePRmFhjY+nw4cP44477kBCQgJCQ0PRpEkTvPjiiygtVWdB5S3MMO2YYW40QkTFZ3pxfWTAEOjzyFmOCM6ItcrbA8VThQGWQ6wbuZoy1EEWnXfsSgo8xWNTlc7v+xue9hGhPFWWv1t4mJkQDMcEtc6DgUNNnWqb1ghIOSQDa2XpWblaNXitolAQCmhQT4pnvf2wzmwKmZBAdYoHlvQ2RRJQpXzxNG/7NzzFIsWOHBHBrg02bXmEeOLR0wNUlWOZ8++pBOtCP4ShjgAgJEh9esU6sjvG9/HHH2PixImYNm0a9u7di/bt2yMjIwMXLlyQ/fz27dsxbNgwjB49Gvv27cPAgQPxt7/9TZJm9uzZWLBgARYvXoydO3ciIiICGRkZKCoqEtIMHz4cBw8exIYNG/DVV19h69atGDt2rHA/KCgII0aMwLfffovDhw9j/vz5eO+99zBt2jSXZWB2eF1UETVoVUXethzxdcSKUD0UG0qRsAAGfz4GRitTS6WM9ZVZkIsoJ0ZpHcrDJtwbsPrfcbVO92QZ760XFzyfUqjZw/IjI7MBCT+iu4SUQ9XoMt5x1RDMM6Dz1IEcwnnqWKmuJmk/mZMB1Cge1CgGlNIrlVeFZNHpulAFRY0KpUNV/s7zDhKZzig9vcLgtwpqFD4135Mtb9aNXrCkTuU/Wyw6hhesQqHGUkcAMHfuXIwZMwajRo1Cq1atsHjxYoSHh2Pp0qWyn3/zzTfRt29fPPvss2jZsiVeeeUVtG/fXrhfWVmJ+fPn48UXX8SAAQPQrl07fPjhhzh37hzWrFkDADh06BDWrVuHJUuWoFu3bujZsyfeeustrFq1CufOnQMANGnSBKNGjUL79u3RqFEj/OUvf8Hw4cPxww8/uCwDHuBprFfEBDKaQESP6pqUQ9qi5M9HeEHlYceskI1WVm2VpDJrWx4WC78KCT2jlYnRY5xUiiinFMpeuK+9KC75448/8OCDDyIuLg5hYWFo27Yt9uypiQirxgrXXTw1FtC66Yrz47Rb+Dz+EMqelEMMGK1VFQ/W7k7ejhEI+FlWujo/681OpsWj3K4jTqqkvLwcU6ZMQUpKCsLCwnDTTTfhlVdekXwvvSZlV5Ydnqa3oaaeayyHtMmbZaFr1KKY5buyyqin5VBwgJXJp5FiHYnulJSUIDs7G+np6cI1q9WK9PR0ZGVlyX4+KytLkh4A+vTpI/x94sQJ5OTkSNJER0ejW7duQp5ZWVmIiYlBly5dhDTp6emwWq3YuVPel9Lvv/+OdevWoVevXgrfDCguLkZBQYHkx5fgdSNJ1MDut1EnQfwUiVWOXCh7Tx1Sa+CLR1C8eLHyWR+lZ7Qyvb+1UrQy3rhy5Qp69OiBoKAgfPPNN/j1118xZ84c1K5dW0ijxgrXdHjQB3myrtEb//mm3oWUQ27Aalao77EzbdLxPT3whx5twNVZb2/X0qxZs7Bo0SK8/fbbOHToEGbNmoXZs2fjrbfeEtLoNSm7cpaoJr1SXbBOJrZFVKBV7XDp/AnitqCc0tgpT813dXf9wboYDRK92lRa9LC2F1dKcXEdXbp0CeXl5UhISJCkSUhIQE5Ojuznc3JyHNLHx8dL7tvyUMozJycHdevWldwPDAxEbGysw3O7d++O0NBQNGvWDLfeeiumT5+u+N1mzpyJ6Oho4Sc5OVkxrVbw9BJCCf4lVCejt74H63M8aQNkOaQtFTWncKXKF42KWW48Zj0WIlh3GqS8UCOnrRz1d0itPUqKrZp/7RxSVxrjkHrWrFlITk7GsmXL0LVrV6SkpOCuu+7CTTfdJMjlygpXD1gVMI4OvqvQ5kW0/HXWvB1OSnDkF0cYP5Tue02SGuznNFdzXKXk7+r+pLVQGkHKIRlYK0vPytU6bz9SKHsVLetJcfDz8iiyfft2DBgwAP369UPjxo1x//3346677hIc8Ro1KWuJFmWq9BZcKW+WRxo1KavWg4G97bMqh4xQrvOwGGLh448/xt69e7Fy5UqsXbsWb7zxhmLaSZMmIT8/X/g5c+aMFyXVEpNVkh+itc9EQhvElkNy47Gny0Q5qxTWKhSOpnnTcogxvZ7HyvT+2kovVBRfUgr3vdsZv/jiC3Tp0gVDhgxB3bp10bFjR7z33nvCfTVWuPaos541ZrNElq8ED5ByyE8w03DDl/7Ke9IoWiMZVCLdu3fHxo0bceTIEQDATz/9hB9//BF33303AD0nZX0dvbG/8dFWFpZIBjzjrumyNxf7SrCIXqdOHQQEBCA3N1dyPTc3F4mJibKfSUxMdEh/8eJFyX1bHkp5JiYmOji8Lisrw+XLlx2em5ycjFatWmHYsGF4/fXX8dJLL6G8vBxyhISEICoqSvKjN+Zoz0ZL4BoWGfXexOk9joohyyFtEfsckkQr06jNODtupdohNaM1qNaoaa81Udn0lkX7wUkpWlnNM+X/93ZXPH78OBYtWoRmzZph/fr1eOyxx/Dkk0/igw8+AKDOCtceT6xnXa3T7W9rYhkkeb77ClclSCFF2EPKIQbYQ9trO6BXKvzNloe9qajb4mgOT8oRdyMSSNK6+WxeQtm/8MILeOCBB5CamoqgoCB07NgREyZMwPDhwwF4Z1JmnbTUpFeaaF3nrS6d/Bs2tu+hpcmxO6jZJLh72pH1mADLhoXZeaSKvIODg9G5c2ds3LhRuFZRUYGNGzciLS1N9jNpaWmS9ACwadMm4e+UlBQkJiZK0hQUFGDnzp1CnmlpacjLy0N2draQ5vvvv0dFRQW6deumKG9FRQVKS0tRIT47wimebHq8tZ6VzLtemopY5zye5nEx2m1e5K+b4bgijyhFK9Mqqq2cw39hrlWZt80qx6u+JhkfVulCweJNWVhRilYmOKS2S29UX6uoqECnTp3w2muvoWPHjhg7dizGjBmDxYsXu50ni/WsGdUmfjUq+tWX9R6uYyr7CWY6GibNW13uriZ9MyiOeRKR2aGmivRaKKS05JNPPsGKFSuwcuVKtG7dGvv378eECRNQr149jBw50q08J02ahIkTJwr/FxQUyCqIvOnPwtO8Fe8rVjmLsoOnVi8P87EyHb6Tu31EWRTpjYkTJ2LkyJHo0qULunbtivnz5+PatWsYNWoUAGDEiBGoX78+Zs6cCQAYP348evXqhTlz5qBfv35YtWoV9u3bJ3quBRMmTMCMGTPQrFkzpKSkYMqUKahXrx4GDhwIAGjZsiX69u0rLIRLS0uRmZmJBx54APXq1QMArFixAkFBQWjbti1CQkKwZ88eTJo0CUOHDkVQUJB7haID3hzD3G1dZlhj8qQM8UQS1iGALIe0RSlamQ1P25lctDLbU9TmXGG05ZCKNDWWQ+b1OeQQrcz2TE72CklJSWjVqpXkWsuWLfHpp58CkFrhJiUlCWlyc3PRoUMH2TxDQkIQEhKij8AqceXDiaXOlforu7JTXb5GIOyhOGmXALt1nTSYjy0tn3MbKYdcUFlZyVB5/HQke7x9Tthf8WjB7KKOvD2GPPvss4L1EAC0bdsWp06dwsyZMzFy5EivTMqe+P8yStnmyhpCjf9Poy0B9Dz6xmw5JHmz7aKPqMyTpY4AYOjQobh48SKmTp2KnJwcdOjQAevWrROs5k6fPg2r6GxB9+7dsXLlSrz44ouYPHkymjVrhpUrV2LIkCFCmueeew7Xrl3D2LFjkZeXh549e2LdunUIDQ0V0qxYsQKZmZno06cPrFYrBg8ejAULFgj3AwMDMWvWLBw5cgSVlZVo1KgRMjMz8dRTT6ksCW3xZrM1ckbzh9lUCyWbVnOWy4Aa/lAhGiK2ytHjmIpctDJ3HVKbwueQCRugkvKtxsCLj1MGPXr0wOHDhyXXjhw5gkaNGgGQWuHa1p02K9zHHnvM2+IShE9AyiEZ2I+y6CSIDnnzq76qweiNsRi1smhZT47ae2O4fv26ZMMLAAEBAcJxFT0nZT39WQhnw9UeE2M+TlqFUvZqHmtEJAPmt0xCObJ9To1uiLU/uXsMh8VpeGZmJjIzM2XTb9682eHakCFDJMoge/9aFosF06dPdxpZLDY2FitXrlS8P3ToUAwdOlTxvrvwNO94qw+YIfwvTyLq6RfOHrIc0hbbiVO1/mZYkY1WBvnjSq7yMDZamfNney1amQ79Xk6BV4VF9pnyx+X156mnnkL37t3x2muv4a9//St27dqFd999F++++26VPCqscN1BOQIYW59h3k8y5K1UFaztxcyjqzFuR/RzdcALpBzSEZ4WcmZooDyJqNT59axSxTqyveXzcgn1798fr776Kho2bIjWrVtj3759mDt3Lh5++OEqeXSalMUw+5BhSM9slaSR/yNfm1jYy1G//NlNdJXqiDEbwutQHfGPVnOWQfoBn0VQDChYjXiKbLQyF64NFPPwpuUQ46OUylErLBb99hEuLYcYj8zoxc0334zPP/8ckyZNwvTp05GSkoL58+cLvi8BdVa47sKTsQBBeAtSDjFgtLJH8mbTfW/H0n/dF8drVNa8sjAV7rYX5fPDHgjjBm+99RamTJmCxx9/HBcuXEC9evXwf//3f5g6daqQRs9JWTd0P1bGRx6eoKqpuevnh4OObIZxz5cwhVWO0QKogCcZvesXzvgxw5dQChPvnWhl6tqB4dHKVKSR862kjyza93wly6Ea31COLqkBY5Qf9957L+69917F+2qscI2G1RJJm7wZ81HIlweFl9JxR+G+AXMEq3VdpcLfPELRylwg1+kUrUoUTf/0a7Rqs3aVjIcNm5lQ43BMTXo1GDWI1KpVC/Pnz8epU6dw48YNHDt2DDNmzEBwcLCQxjYp5+TkoKioCN999x2aN2/udVnZnPdVofaNkCHHyoRn8tsva8qR7XN6DIfuHnFRPlbGb7n7Enr6aNMKE+i1dHbI7z7i/uWqHBcuXIjGjRsjNDQU3bp1w65du4R7cvqB1atXY/1Lw3Dqjfvw2H298fXXX0vlrqzE1KlTkZSUhLCwMKSnp+PYsWOSNJcvX8bw4cMRFRWFmJgYjB49GoWFhcL9zZs3Y8CAAUhKSkJERAQ6dOiAFStWSPJYvnw5LBaL5IfrlyOQt+zRNn845M9qOVRjlaOlZM5hHVP0tm7Sc4STqyNAheUQzY0AGFxO6Ji/VnXBg/LHTDBZs5u0v5ByyIYHTvn0rHytPZmbYJ3LlYd8vScAlmf64wCuZ1/U5gCSk/RKigeWo28G1Tnb8TxWn0PaHM+Tl4UNP+xSPo/bfYafaUcZjjRVzH7hRH/bV9HHH3+MiRMnYtq0adi7dy/at2+PjIwMXLhwAYDjmLF9+3YMGzYMjbvfi3oPLUBa774YOHAgfvnlFyHN7NmzsWDBAixevBg7d+5EREQE7rvvPkk+w4cPx8GDB7FhwwZ89dVX2Lp1K8aOHSt5Trt27fDpp5/i559/xqhRozBixAh89dVXknyioqJw/vx54efUqVNMZeNtbFY59n2F1Wm0EhWC5ZA4bzafQ5UKli08YbRfJE+QqyPA9XzOcXVoCj8jrRs+FXWSg0c4mhJ9CjpW5ifwGi5PjAlE1BVmizQfhvk7szikdtMSSH3+zj+hRpnCk4JUCZ7apdZHXPx9LNIaPdqK9k6zOWrQCvAkoZbj4ty5czFmzBiMGjUKALB48WKsXbsWS5cuxQsvvOCwgX3zzTfRt29fhN01HLtPXsGIBwfg+E9ZePvtt7F48WJUVlZi/vz5ePHFFzFgwAAAwIcffihEFwSAQ4cOYd26ddi9eze6dOkCoOoo9T333IM33ngD9erVw+TJkyXPHT9+PL799lt89tlnkmMuFotFiN5pBlxZDnnazmSjlTFmXu7CabbeqBmzKrylwNLDIbWCYkvRckh7EUyJy8iJikeK7Fx6KFgvO8ufNew9c2APBbcjPFi/CMcdOXp5zlruEs8wooiRPEKWQwywL4b0e767C1kHmUww4nMlojvnl1gfoePZZLOhpzNArY5DqZmslP52+Uz1STWGwVqHUUh2yyGWxGyy8DoxE66hquMfNf2rpKQE2dnZSE9PF65ZrVakp6cjKyurOh9pRllZWZL0AJCRkSGkP3HiBHJyciRpoqOjBSWQLY+YmBjJtfT0dFitVuzcuVNR3vz8fMTGxkquFRYWolGjRkhOTsaAAQNw8OBBxc8XFxejoKBA8uNtlBQvWvUpOWfHrnyG2GOIVQ7jo/RWYOn5UtemwFNqA47KjErJfX/B374v4T48vTD1FFIOuQFPRxfYHY5p7xPHW/CkHNGjDbialP0JLd7iK79lYTTR1bH8zWwt5m4deTLWKH2U+YiLi+T8jDS+gSmscvgXkS8ZNbLAvHTpEsrLyyVWPQCQkJCAnJwcAI5+Z3Jycpymt/22TxMfHy/Jo27dupL7gYGBiI2NFT5vzyeffILdu3cLFk4A0KJFCyxduhT/+9//8J///AcVFRXo3r07zp49K5vHzJkzER0dLfwkJyfLptMTV4oXj0PZy0TxEkLZq8zbiGhlYtSMWd7yi6RHt1eOViZfT+76GPR7dCwvreqCqpQNM7iG8BQ6VuYCLxiKeAVTNVCOCtKbZ31dmoyaqQ41Qu1XttWTmvTuOlZULYuGjht59jnk7gZCT+W6+vZiSy//CTMcwzUTSm3lSG4hjuRelVxrGBuO0KAAl3mqqSP7vGPCglA3St5ZsLKMV1E3KgQA8EfeDZfP1BOl+ehIbiGuFpUBAM5cvm6oLGLEdaRUvscuVjmAPn35GuJyryIk0IpGcRGSNCGBNe3hcE5VnZ7Pv4HrJeWsYrvNpk2bMGrUKLz33nto3bq1cD0tLQ1paWnC/927d0fLli3xr3/9C6+88opDPpMmTcLEiROF/wsKCryuIFJUvGg07slZ1NRYDqnNw/uWQ6xfX0nBohV6fnOlaGU2HA4Z+NlC1NX6Ru8XHp7k708vlP3nm3oXUg7JwDw/mmis5HnM4GlDxn7kSDvZtQpLSbhA5wLVxCG1CWqdte3HRYboJAk7HA05Po3StPPRrtP4aNdpybUm8RHYOLGX22OqePy8a95WyT2LBfh4bBq6psTCHqXF+PSvfnVLDj1QmhtGLt0lf0NH1EXTEX9APs2D//kVsFjxxPubEf5DMQBg0t2pyM3NFfz4JEaF4vcLVUqkjPlbUREagxmrdyDq5hrLIEn66t+5ublISkoS0ly8eFH4OzExUXB4baOsrAyXL1928B+0ZcsW9O/fH/PmzcOIESOcfuegoCB07NgRv//+u+z9kJAQhIQYOwbeKK1SquUUFEmuK1kvs3LofNVROcmxMlveKhehBUWlAIBLhcUeyeIuasS0yVZwo8xwWVg5klMoe13JKTnvPlKMxlX5OFpiyb/QrFrzyZttsVpOs58ssc+3Oh8e6lzBok247UVRbDiWu4s+Uun4JxdlKwMdK6tGncUBqxWJfpoY1slCrZM0HuFJC85SXqxlq1hH/Hx9r+FuaHJVadmy1t7ZsRqH1AbXuarxkDHPBcM6on/7ehjVozGbLGqsmBhlcVXAvE7YZsXZGB4XEYy4iGDUDg8CABy/eA1lFa5rVKmOxJ+NDgsS8g8OsKKyEjh64ars55w1CVsetp+hN+tr6aEki7NSEctXJzIYQzo30EU2QRY1yiFRHYnHRYkPtoAghNdrBpz7BeHBVRZCv53Px8aNGwWLnCbxNZZEcRHBqNWoFcrP/oy4iGC0SopCl8ax2LBhg5A+JSUFiYmJ2Lhxo/C5goIC7NmzR/g/LS0NeXl5yM7OFq59//33qKioQLdu3YRrmzdvRr9+/TBr1ixJJDMlysvLceDAAYlSykh+PpuH3+3a/JvfHdUk7yvXSrD58AXBygeQ9vXL10pqEjuxHNpz8jJO/ym1eHtxTVXkuYtXvacccjbsb//9EnLypcq0GWsPAQAO/JGvjzwKAu2WKS8lisvK8f1vubhWLFVg7Tp5GQDw32zp8UdXFl7+NjV6uhbQNZq1VvnQgocJHd1gcgNZDrmBVo5sWZFdjDFmbuYBn6fxS0/LIsU64qkAvIUOfc1dx4pqy9+lPxtVyg7+39KxluNf2tfDX9rX008gMNSRLb1+ovglrEqN0CArsqfcCQDIv1GK9i9/q/pZahbdP027S/j7//69B+sP5iqmVZLxtubx+PDhrqrl8gRX7VepfJ++szme6NNMY1mc31dSgotlFNeRkuxbnr0dOzq+jJEjR6Jf7x749lItbFyyDNeuXRN8+/xv/mRcKQrBlJdm4JmMFtjeJwK9evXC38J/Rr+Mfnj7jZnYs2cP3n333WrZLZgwYQJmzJiBZs2aISUlBVOmTEFiYqIQZr5ly5bo27cvxowZg8WLF6O0tBSZmZl44IEHUK9e1Ti1adMm3HvvvRg/fjwGDx4s+CIKDg4WnFJPnz4dt9xyC5o2bYq8vDz885//xKlTp/DII484L0AvcKmwGH95exsA4OTr/YTr245dkk2vFKlKiXvf+hF/5N3AKwPb4O+3NHL4rM36B1D2OXQ09yruX5zlIGPe9VLwwrbfL2H4kion5WIZvYW4rx3OuYohMuWlxGtrD+GDrFPo1TweH8iMY/ZHZZXqyQ/fURKE30KWQy5gsVrhycLFHp43mfbwVIp6WrDYwxqm0pfR27oHYOgT7vrW0aDTmaHb6j+26Gdp5ZcKVxVoXioK9ROowpOrFscz1aDUhgK9GS3JBUoKmYAA78vIbjkkT4DVgqFDh+KNN97AF0vn49zyJ3Dx1GGsW7dOcCidf+k8yguvCJ/p3r07Vq5ciXfffRft27fHf//7X6xZswZt2rQR0jz33HN44oknMHbsWNx8880oLCzEZ599Jnn2ihUrkJqaij59+uCee+5Bz549BQUTAHzwwQe4fv06Zs6ciaSkJOFn0KBBQporV65gzJgxaNmyJe655x4UFBRg+/btaNWqlesC0pnzeUWuE8mgdji1KRa+/vm8fD5iRaFCEz14zvvR2pRQmg92HP/Ty5JUIacAP3iOzUppxc6qY7tbjlx0kbL6mcIjFY420ZwJwHjrbqIKnvfdZoYsh2TQy1Gtu1gs2g1EPPcjnqYcQ9sAR2dqjYbdJFdHRYLKdJpYDhnQTyVHPVQIqa+I7rV2tetW19HK/LG3eR89ItdpDUe6IUWUnMoajRqpbLJnZmYiuN3deO3r3zCoU31069ZBSPPQq8uxfPtJyeeGDBmCIUOGKD/bYsH06dMxffp04Zp92PjY2FisXLlSMY/ly5dj+fLlTuWfN28e5s2b5zSNUYh1rxUVlYJzZ2W/He61o3JRhuKslf2vVApzjFdD1TMgLiOj+5dYFlbn11arBVBxTNfZMwH/s7Zlj2rrKj+F9Cp8FLmSRLPTBg4Z8WPBXuMPzUUCL6Loo0mFGxctA9foAVkO+QlaORok9EOpjvxRM67nV7a97SwqrVAnC2OfyXLxllHNZHC4OsrSuXz33vx6g32nqt7k8/Hml62OVu0+A6DqKJMcPCyGvE2FGxsITzFHMfMvJf8SOnGaagbhTYpYkaDGj5cN1vlXaewQz3XiapYoOzhqAEqS6BWNzCUyj2VVVLGWr9ImnBxSV+FK4eJxAEAn6e2frZUVl59XKTMs5W5WSztSDpkITxQ7Jm2ffoWrOqI6VIZFgWZzdKkHYsec4pDS4qpTU4/P/fdnDaViR01TW/C9fDQerdGj3duizHy+7w/tMzcpeo4vPPlRUx4qTKC8ULL44OCtqbvpZTe7HH1PMyNWDFSomCPdLd9yVXmL/E+JrgdwugsRr7cNUw5VIy0vRuUQY3pbPSlbDvlbJzTf9/Wn98l+9FW9CqfDsvfxm0WHCXoST5YyRkjC0dc3HD2cv+ddL3GdSANZyhXfphJ6oVXZ+mMd6Tnu6GE14i2fQzydemFSsGj1TIWC8cQfn5JFCaEtYoWM0nwkSS/8xVa54qzVhNUWp+Hpzbq3/JupRe6xrOMR8xqq+jdZ+jnHm/5IXWeuVTb8bj5qnOVzJCNPbUBjSDnkApa6VDxTqgPMoezNMKIrnb31rhQAnJ2Vd/VJxzOlDE91+kwT1KBmMJ/31kkOwFwDulbwNFyoEUXrOuLp+/sCeig1WOc0V2+8Fa2bOBp5uVoYM4/RSptNsaKIn7L2BZSOlTWoHeb0c1odK4sOCxL+VnJOztOxMiV4kpH5WJkLbVKtUDvXs7ZNuF06roYeL6D39/WGJZanOfPuF0cMDzIKdapKFL6PaZJySA4XSgr72y7PoHrYaJ19mjVnRQdanDZQMXyJaH/2lyW1c3g6gmE0Gh7X1gDXuat5vh9Wo9fQ7Aw+VZKm6GGVo3UNKSleVARU8xrK5cjT8TylD4j/rPlHTRvgSylmHiTHykQKnIe6NwYABAWwrWOUUDqy1qNpXE3eYrskFQ6WR/dMAQA0qRPhnlAeokbGu9skAgBubVZHZ1ncP+LmSrH1Uv/Wkv9rLIfsZODYqsSbKJVmpUIKd0dmcWkrvSDWatin5Q4bLMVl1qLlaNlD6IlZG6g/oRzK3v8mZZ72Au6Kotzn+O+NPLyFsWFE5DR+vr330NfqXdkux220Plam+Bh+WoPyiwOvigHAM59D0hDn/JSvryEuWrFfoLDgAADAHS3qyn6Odf4VH1kTf1TSdySWQ+JjZTXXxQqs2uFVVkddU2LZhPEApb6u1EaToqsssNrUj9ZHHpnHWhUUfsp5yMverkGVzLUjgiTXBZ9DDoFRlGXyZbz9fbV4nD/tGXjaK/gSpBwyExp0AjO8geNJRCNkUXNm319gDU2u50aD3tLwDxWtufAslL17H9botC9XmEBECeI6kDOE4GgJ4DPIKRIcIyu515IUnV2LdUNi5ZCCVY6cY2uj5kvp0TfnafUWUVwsVhflZY8rh9/246jwn5JDalrAuIWeChutcuZp72WPYNFmqBRSeHJ/oTWkHHIBS2fhuWOZYfXI0xtat01BPWgDiuaqPLcrgt3/lz5i+CxUXuZHxd7RcHg6sqWEoowGeM1mfdEkTq7knJrQFnE5M4Wy98AhtRJKtSw+9qTGabaeKHV1o6KVyfUN1vJiDmWv4HPIdsFfequr4U1tH1H2X+q5zxmXH1Wdt3xCNh86xuJNGV3Wqaq0cEjLE6QcqkYSPYOxtvSuXC019aRo0ActF7iKVcTrKMIBLLZWPEWZ4LVKuV0MuJho9X6OL6OnVakeihetIxnqcPDNbZTKS9Gps46yKKHcWuTviGWXRKsSrUK5HXd8AMnRL427eoWKvCWh7BWOFeopIytqIqoZcXxHrKdSFYFOSXZFhb3F+X0/76MuN/salY+4/dnamb+XPeE9uFYOvfTSS7BYLJKf1NRU4X5RURHGjRuHuLg4REZGYvDgwcjNzTVQYn4RBnyD5SCUEc56K5jz+iOsSjc9506t8iazbDZYikuzo3/+qB0S4a0mquY5in5ANJZF0SE1R01BzcbbW3iiZJf6pVEPR1VhCsTKC7mjXw5HimxWI4x1q3SsTNwsxU8Sy+XqWBkPte7Kckiv7ifrc4j5WBnbmbgayyE7n0N+uhI1vvWxY7RilTA/XCuHAKB169Y4f/688PPjjz8K95566il8+eWXWL16NbZs2YJz585h0KBBBkorRev+WanwtxrMtB9VMmc1AscJkuWzbLg6VuZPG1ZmKwY9rR40aIDScM2E1mi9cDXTeKkVeg6zyooX71kOuf8c7zUGd5+kh4iusvTEIbXY0oSnY3u+hvvHythQo6RQ9jkkyqecn12t1OeQsW1UyUeTGofU7h6Jc3hJ6YfrUC1Re7Tanaam7KeULTOerGftUXp5Ltz3oiw2WK3r5OqJ15fFgUYL4IrAwEAkJiY6XM/Pz8f777+PlStXonfv3gCAZcuWoWXLltixYwduueUWTZ4vt+lQNjGVR8+6Z81beQ43voG6DAfvzUW6S1nkr2vRBoxoR7yi9dERT9BKFn+sR09gW+BQ4fKIHmOa1psUMxyj0EPJ5i7sPofExyRqUCM7PyoD81KhEFFMjLt9qqKi5m/lo4+iY2V2d2yUK7QRb6Fmzq6oqBSsd/S20JATR6zrESv8cguKsHjLMfz9lkZoEh9Zk4fiWlXJ2kv+lIGZ/M94A7V1r9SntGg6egdJMUMAI2NQX6es+gJe4N5y6OjRo6hXrx6aNGmC4cOH4/Tp0wCA7OxslJaWIj09XUibmpqKhg0bIisrSzG/4uJiFBQUSH7sUexvBi0etche0SpFg7wJaFJJFMq+Bp7mJK1l4fXNm1gqoxeA2im93Xy+ttkRCnikHHL3s4yNhdf+KoZXCSXWzqJ/xMeQ5OqRNiXaIC5Flkhgmh0rU3iWUv2qiajmLZgiquncA5XWgOLyenzFXizbdhKDFm2XpHFl9eRguWJ7pt33lHO268v447qbIGxwrRzq1q0bli9fjnXr1mHRokU4ceIEbr31Vly9ehU5OTkIDg5GTEyM5DMJCQnIyclRzHPmzJmIjo4WfpKTk3X+FnxBA54JoFD2AqpD2TOkd7cHmGGT6O/o/SbNlzFiP+7NPuVunZqhLZhBRjFSh8TGyeHriDf4ZSqObLlbF4qh7BVQOqzPcvRND5TGI7F1mzcjqslZHYiLWqyo2nf6CgAg73qpJD2rVaFStDLhfz/vr8qWQNoqz+SiO6q1QnK3hZpDJy+yLjRYYE+OVvMO18fK7r77buHvdu3aoVu3bmjUqBE++eQThIWFuZXnpEmTMHHiROH/goKCKgWRjw94ZlqAcTVAeVEWrd7iEXxjhr7I0zlojkQh3MQUR7YUBnuuHFIrXOepv7JCSnf9kPh5ktttKn6ObdFRLj5WpqKvK4nCU7QyMRIn0AYrsCTWYCpksSoMYC7riXwOAdBxjrKVp45jt6dZ83SU0JUIfM2BKo5KC/2JT7i2HLInJiYGzZs3x++//47ExESUlJQgLy9PkiY3N1fWR5GNkJAQREVFSX7MghaTJU8Trj08dRIjJ0DyOeSGRl7Hdu0qa467lN/A87hGOFO8uD+oaT0cugrtzANmcMapJr1YUcGT8s2XURX23PaHRsfKpHmLtUPu5+M1RKJIwscbIKPSI1Uph1h9JQqRjTmqCxPD7KvSAB+LNASz4Q8v8k2lHCosLMSxY8eQlJSEzp07IygoCBs3bhTuHz58GKdPn0ZaWppmz2SpbKNN3JzB0wLXl/GkCQiTMr/NyAAYTaJF6bVWprE7pJb/gCS8L6fdklOxXL890uw5vJaAfui5GdBFqaFx51GS0crRKkkPJZu7sLaXSslxgJrrTG98eR0wOUXJKseGfXFqfaxMEqVTohuSdzwtd6zMmzWu9P3FfnvkIqrpFspe5pqrOrXHVbQy+/4nHCszgbWnnrhah9MynfBluD5W9swzz6B///5o1KgRzp07h2nTpiEgIADDhg1DdHQ0Ro8ejYkTJyI2NhZRUVF44oknkJaW5nGkMlbzNL21iFo4bDTzgM7TIKwcMlJ9WkVc1JE/bVi5UpBpLAxf5q++AYWy5xs9rCHd9keteN31BtdoeFJg6Wk5xNPwb25qSrJcRbQytfftURNSXVzNSsfKpBHVvN8KxDJKnabLO6TW/YWwxVEW8TMdZJSRR0lx7EphL62jSof7/oqr/Z4ekb9c+Xuyz9rdR/FsLSantDR6n+DJHMg7XCuHzp49i2HDhuHPP/9EfHw8evbsiR07diA+Ph4AMG/ePFitVgwePBjFxcXIyMjAO++8o7tcrIOjnoMpa96Kyg2ORnzlRbqXBYGTTQ1jPiwbDPvvz7NFml5cLy0DoL7O/8i7UfWHDm2kuKzCdSJCN1Q5Ga/uIlr5g+BoOPQauh7NVHwL7cGxMo0riacjW0ooz0cGWA6xLowV/uZJ+ebLqDkO5XYoexVtQVzPSsmNOLIlRqxIUbKGUqMI0wqbPEqPLFexNGE+tikTyt5tSz8fwNOxVTkKsfP7nuQt3Pcwn0pXWimO8KqFocJ1IaKfjEWmowKPb6dDXCuHVq1a5fR+aGgoFi5ciIULF3pFHqO1qp4831Vj5gGe5hwjZFGuo+r7HJWP3vxry3EAwNYjF12mLSwuw+VrJarzZm3zM9YeAgB884tyFERXWBT+5hWztbV3Nv8OAPiToR04xWwFYFI8KWXWRbu7i3wzNAUzyCiGVVnI0TLFVEitchzvK0Y/YixwJaW80rwnzl/8t5qjb3oidt4sFUUko2woe32wHQmTlJfofplcpSrkoYT93RrLIflnmmyoMR1mG8sJ34Sj0/TG4i8dktZY+qKFAtHfz3qLOXvlhss0OfnyaXjdUChFbSHkEW9glIrr6wPuK+4Ib8CPrxwleLLKUYKn8UJprlOSUUkhQOiHkiJB6zWG9NiT67yVrMh4iFZm06UofaeycnmliZ6ylCvIokI3pHysTCG9XCh7ybEyfoZDY+F4CDPakMFb+Me3NAZSDsnAfmxM39FSk/xpRNcVLYpX8a2p51kTOsLbeKEFZpBRT/z722t/dMCTzahSGs2nNCV/PhwdZ+ZJyebRsTKa1LwOSyQwZp9Dao6siY+VKR6TMr5h2CxtFI+VebHxCsfKFJRAYqWR0gjAOjbI+RwiXOPSj5cH5elKma6VMojnOq+JoscPngRl4B1SDvkZPHd+GzzJaMQbTuVH+vuWlU9YWwjpadkw5Ign1ZGmKL+l9sDnkJufU7Rs4cAhtatHKTqk1kFGV9+bddxTckjtKi3hPtLIVjIJVDq4dYXisTJFfysKljCyR7a8Oxjb2r34KylZN4k+pIssNT6HxNZK4mN4Ghwrc/CPIqiHRM8U3ffzdairb+9YPs6PbrKUprqcRfdVZu7qeKkZ1kPelNGlHyn79AxpeYGUQ34Crw1QDE068tBC2T1oQnMfbuUyWgBCUzzyOeSlxsBrXxDDq4zSucvz4zicfk1uUVIkKAcm8dwhtbO34zJ6B0l6bx7ZUiJAsNaRV2B58+ibrBWTK4WfHazRs+QshyorZRL4CUaNrbTuJ4yElEO6om3vVpgf2PIwkVmbDZ78E7BI4n4dycPrBsB42ArG6NZE1UjwiL7RytgsC3TBTascnl5acBVRjfVYmdJmUwQ/Je0buLQcUvqc9qIAECkeFB5mdLQyQMHnkAuH1HphGx8lCinRfTXH8FxZDik9U+oXinwOeYraVuNO8WoXyp5/pPOIsRIzP94MBVwNKYdcIFf5rsP+qUuvBWrf9AgDvokXZTzJqEdUlZo6kmZiRoWeUfDURhThVEhxkzZaREmUGyOOlRleAr6F0gjmyXEozf0iKT5H08d4hPLRNy8LAnf8LYj+5kAJ4G8UlZY7XGM9psKK/Thq67NK1V9c6qjB8nbbtkUsU1K8FMnJqJMsNZZD8veLymrqVKmcggJqtnly/c6hjuBYR5JQ9s4E9iFcDVFqxz8e9n+u89EkG33hSEbmSKmmKGApXIey9yaebEZ0r3ctnB3z1LNMhHptv+flq3zu13af8AWoL/KPCedyjzFCCW2GcjbCITUrZlt8sr9wJWWSO4g3uDO/OYSs438CAI5eKHTxOfbyfmb1TwCAMicmSs58bwDAi2t+QdpNcQCAg+cKmGXQgho/PzXXxMXx7Oqf0D45BgCw9/QVr8gijfRXc3/Kml9wS5Oq8iotl6+z+Fohwt9jPsxGTHgQAOBcnkIkWBdDidnGGq1R/PqM/nkEnzMq0gt7ANa9qYdrTd794ojhYl0t1JNrWSoZ0hoBKYcY8IWXXfZfgaevxFMf4bHDcigS4QSvRVnycYyY9KmKtEXZqpafklbaEBsRCUwJbzqkdgVztDIGh9SENoiVapcKS/Df7LOS+9FhQZL/5Y4UOaNB7TCcvVKlZLDPOzw4AIEB9pZDjnKJm8IfeTdcyqg3NmWwRCEjun/0QqGDck0vGeWPldX8ffaKY3nZEyjSbn93KNfhvkMbkHmO3H1/wd++L0EApBzyGzha3xIKuPKAT8hDbVsH/LxMqU1piyvnp+7gbh0pyaI4znLUFhSPvnlViio8sf5x5SqF5jzteb5vquT/4EAr/tK+nuQaazuKDgvC2Ss30P2mONzaLF5yr3Oj2pIjTVX5WwBUKioW7WUMDw7AwA71GaXyDNtRLiXfQvYy1goNxH0d9ZExQMaKSUmWxVuOIf9GKe5qlSCbtlZIIB6/o6nkWoPaYWhTP0pyTc4FBelyPYdZmc4wCmpWPxxXtJzS0mhpfdjlECmHXMHUQXWuei1y57jv+wR61hEXZpOEW/hxsA+PIUWNd9DVIbXCdU/qlvncv4v7Zhh3jfBrqPRM1qNHahyJUl/XFlsx160Vgsduv4nhg2z5j72tCW5vUdf1B5w4O05NrMUmo04IoexFp+Ns7bX7TXFelVE2lH31n/blZbEAr3/zG6LsLIFs6Uf1aKxKdsHnkDgPP3RI7Wo/p3b4c11c8n65tMhbdSh7XzhK6EURXZaXi//V3jMSckgtA0+LQUCbxsPXN3IOT84qVU8AmviF8lAIwpBJTE17Facxw0TL2xjobcxQR6ZCh+NQWlcROaRmg/mtqVg55OYzeaoLM6F+k8hWwDV+U9R9Tnj7L6Ps4GXMDZBRyNgwyjm2NHKaTRbnPipr0rM5rJELjCJ1SM1HPfEGq38ed5b1Xi972nowwVJcvPvRI+VQNXpMTPqGBnb7k1qKoSmKft68KkUVLnzOqcL9cJL8bADMDE/FpWQ5RAst10iDBVB56YWe46wex6E0bwmKPoe0fpAHcOS7yaNjEvwuQ3wS1nmGdeOiNndnUXN56WZyoexteHu+tskiFzmNxTpBzX0hnUzCShf3/Qv3CoB3ZQBgjmGZq3flHljP8g4ph9yC1Zxdv9FUi0m56j7/Iz5PIrKIolpuhToy0XhiCKzNwugBmqd2rIQZZCS8T/6NUkz73y/YfyaP6XN6OHv2luUQVw6pFa4b4pCa9To5pPY6rMXM2oxYrbzl1sK8tQSrTPh4o5qrzf+RmiOZwn27EmVuA7Kh7HmrJe9h1N7IkyL3xfqSVVr63tfkBlIOmQhPOrwZlD/+jislItWguRDXJ01i7mPE0OXvw6XS15/59SF8kHUKAxdu0/dBKpK4+9KFtSsa4uyZedNtLlwph3xxc2MENkUBu9KHLb0n+dvqmpcx16ZolYsQ5m0ZLbKy2O7Zp5XPQym9K/zdgl2rIci1Px/j8/aFvYc32yVruTtLz2t/IuWQC1jOyZthPeNglcKhzDyJxO5XwXPp7XPgsY54hdNxFuJa5fUomdSvAOFvqBm77EM4ewpXR7YUMMOLFZ6sm8QobTCZj6TRHOgRjMbLblubuExns46WaRe8NGG5UPZG4fSIG6MfBuY6olOgTvG0TBSVbx7mqyVU72wwjRmcFy4ph2RgnaT0XjzyMmnqDkdflL0N6PfMmrdW/JQPr6gZb41Y9EkeSdXIPbwq8IzG3VJR6nFdG8e6KwozrsZPpWGhVb0o+Rs64Kp8lcauBrXDvC6LJ/4WUhNrufdMggnmqY7VITWzEsnxc7ztkWzHyiTWOkYdK5MLZc+o/HHb96XCsTp/nxsV1+kuHKt7dkzM1bM9O0ro6ee8ibQrGCsws/EAd6OdMqQc8jPM1Dj9FR7eWJkJsynNzCAuX2XqfVm4+vo+gNKQdnfbJLfzVKqj0T1TAAB/aV+PKT+lubFjwximfPREaWbQQznkCk8Wxu0axAAAwoMDtBOIcKDmSJE+DqlZj1vZ5JDkbtv4cqJ0sMooZIyKqCYbyt5W5krKIIUrWtQRSz5EFfr6nNUobxPUKS/jA8AuC0+yq4WUQ9WYr+rYoAGdfxSthElXpBozNHMzyOjv+GMdqRlm3J1H7DebdSKDPcrPGcGB1upnhDB9zn6c5fHIG09zgRZHw5olyFsQKWHGRbaR6O27SlCaqEwvF33LKH8+StisdSSh3Kt/e1tEa/UOTaIcUrAicWnRovKZAbajbDJ1xJIPoQ7G04Ea5c6YiwkqnScRWeYpXuc0Ug65gKWD6h1lqlJJle92HnzCk18kB3NNls+6W0cK180wQBM1iOvLBN2OK8RvaKnd84PbTqB16ABav8U3xdxotAAiWOc3nmT3N/R2SK12WAgKqNpylFVUuJuF7tjKqpzFz49OyDnHFmRR+IySQlCt7IHVdVQqqiPJsTI/mZBd+5j1bEQzxXxjBiE5gm1/yDekHHIDB429yw94+DwnGfiSN3rXMnhPSldPcmwDTupI7TOVziqr/DzBL2ZYXJFbpBo4rSJd0XMdqEfWbvs/UhDGDOMsT4t1dssh9R/g51uaG51dDjHnH1htllJWbrw/HyUCZEPZGyOkfCh7tjxY0wfJ1JEYP5waVeFKWa66GmQKuOYoobq83W2tPM0v9tQ4Sudn7PDlwAqkHPIzTNQ2/RdGh4P+jhlKhcyy3YfKy0uoOlemuxSqYQ4aoI8YhIbwqjg3K64c2Sp+TnX+zv3f2BNYfU6qtFzGKoWTuhf8/MiFj/eyLM5C2SuVl6OiwHZsz4M6UvVJ/4C1DejZrLXKm4+eZyKYG4EuUugKKYf8BLnwlARf1IR5lUJ15h6crDUB2FsOyf9tNEoy8oS3xCJFrMaYYAzj+a2pDZ4kZH5r6smzPPgsoR7buKdXVxCsUmSOSfGCVbAcMl5Gwf+PClm0UqwGytSReGz09trgpZdegsVikfykpqYK94uKijBu3DjExcUhMjISgwcPRm5urmbP1+v7esPJuadZ1yhF+V8P8fRiQY0o7iruvQUph1zAYsLGcyQwfZ2eaQtP5cgqiSfrCeU64sthI88YUUbs4XypIlkwYtL3x76m57irR95+WEWGTNhKdefNuZFwFzbLnppxT11lsRr9CP5sZKxSeOnPNqfZEgWWFzby8rLIWA4J1lryeOqzM6jacqhMwXLIiPm4devWOH/+vPDz448/CveeeuopfPnll1i9ejW2bNmCc+fOYdCgQR4/U/OXBYz5MR3D1UhUGqLZcPBJ61JHYB5IOVSNJ2/z9R4rtcyfJ8WLPTxtyFgnQE3rSMmhoHaP8AvUh3olALu3g5y2Np7GCF9DzQJTaz8/nuCfDqn5EVJpnlIuR+eyL1y4EE8P7olTb9yH/04dgV27djlNv3r1aqSmpiI0NBRt27bF119/7SDf1KlTkZSUhLCwMKSnp+PYsWOSNJcvX8bw4cMRFRWFmJgYjB49GoWFhcL9zZs3Y8CAAUhKSkJERAQ6dOiAFStWMMuiJbPW/Ybb/7kJ+ddLVX9GbVexKUbYX3ioI9DqxMEyJ2N7sIwCy4a3RbRFXpSVhdH3qXoFnpzlkLrP6kVgYCASExOFnzp16gAA8vPz8f7772Pu3Lno3bs3OnfujGXLlmH79u3YsWOHrjIpFYmn7djZx9XOeUbXlx7wMj74C6Qc8hOoY/EP1ZF7GF1uShs2sVi+OFl7C+oW3kHSRDUudE+av1L/lkQD1MDZMU+KFyXMPI44k/3jjz/GxIkTMfDh8Uh66E3UadgcGRkZuHDhgiSdrc63b9+OYcOGYfTo0di3bx8GDhyIgQMH4pdffhHSzp49GwsWLMDixYuxc+dORERE4L777pPkN3z4cBw8eBAbNmzAV199ha1bt2Ls2LHC/e3bt6Ndu3b49NNP8fPPP2PUqFEYMWIEvvrqK0kaV7JoyaLNx3Dyz+v4z85TLtO6a9Wq+kgVs7Njm1WK/JElHrApZErKxJYzxshok6W4TL3/H0+dE8vWkcHW60ePHkW9evXQpEkTDB8+HKdPnwYAZGdno7S0FOnp6ULa1NRUNGzYEFlZWYr5FRcXo6CgQPKjFsXAMYq+Qj1H7y7C05EsM+AHLodIOaQnek56bmfN1zysCq4W7SwF76bYDh/j6OubCV7nO6mVIj9C6qkc0ApeLZp8AlV+LdzNWt9jZaqsnlzIztkeVRaeZNTS59DcuXMxZswY3HbvEATXaYheoyYjPDwcS5culU3/5ptvom/fvnj22WfRsmVLvPLKK+jUqRPefvvtatkqMX/+fLz44osYMGAA2rVrhw8//BA5OTlCHocOHcK6deuwZMkSdOvWDT179sRbb72FVatW4dy5cwCAyZMn45VXXkH37t1x0003Yfz48ejbty8+++wz1bLohZz1jT2sR7aU/B66zF+ts+NqqxSej5WFBAYAsFPIGOQfJEROOWSTxS6tkmw16dU6pK6uowrjLacAoFu3bli+fDnWrVuHRYsW4cSJE7j11ltx9epV5OTkIDg4GDExMZLPJCQkSPq6PTNnzkR0dLTwk5ycrJhW95MhHOfNu18cMTyIyLJX5WpfKwMph9yAJ62h6rPkrkLZ89CzqlHUwBshowayqFcAmKeOeEVVfzD2KDnBCLV776CmGburnNPD/6xtEwcARWXlHucn3oAZjVJxFWvwPbVCjSzisbGoVD59SUkJsrOzJW//LVYr0tPTFd/+Z2VlSdIDQEZGhpD+xIkTyMnJkaSJjo5Gly5dJHnExMRIrqWnp8NqtWLnzp2K3yk/Px+xsbGqZbHHE6sFd1G7BhEidbFaHKkcFgR/NrLHyvgY6EOCqhUysu3VuzLaxrgSmbFJ2YJFwZKZ0S+UJJS9gWucu+++G0OGDEG7du2QkZGBr7/+Gnl5efjkk0/cznPSpEnIz88Xfs6cOeOQRuuvrGcRaqVoMMNalicZ2f3ucSS8C0g55AKWqtS73rXIn+emyZNVgNtvyDUoYRONH9xhtpDxZpCRJzjZP/gkZht3QoNrlEOFRWUe53et2PM8PMXVBvlasReVQy76WiGjLEp1dOnSJZSXlyMhIUFy3dnb/5ycHKfpbb/t08THx0vyqFu3ruR+YGAgYmNjFZ/7ySefYPfu3Rg1apRqWexhsVrwFOZjZYLPIZUOqRkfIGs5xNm4E1KtHCnhIJS73LEyJWlcBTRRixBRTs66i4MJOCYmBs2bN8fvv/+OxMRElJSUIC8vT5ImNzcXiYmJinmEhIQgKipK8sOK2nbrbpmpelmjZC3GWOfG16pr5PaHRo0dRvqk9RaBRgvAI6xKCr2VGlrkzjrpE96nxqTbzgO+AbKYCZ6UikrwbkIKSCdaM05mhGeoaaOetIu+87cKf19hcKarKIvo7zvnbUVSdCgA4MLVYrfy+/NaiURGHqNt7zp5WZDR6HDglwqLJeXlisdW7EVqYi0AwFUNlHneZtOmTRg1ahTee+89tG7d2u18Jk2ahIkTJwr/FxQUuKUgYlnKqe22Nssh3RxSy1mlMOahNzWWQ66dQOsui4z/I0EWhc8oOkpW+czAauuuUhmH1DzUUWFhIY4dO4a///3v6Ny5M4KCgrBx40YMHjwYAHD48GGcPn0aaWlpujzfVbkz7x/tHYvLNDJ3j1760zqOp++qz8kS70LKoWrUdGgzbPCYIWURN7iONsHnIMIT4n7srfJi7UGeREb0R4xQ/lFfk4e1WJrUicDxS9cAAL/lXJXcCw6wom6tUE3kyr9RivwbUoVTg9phsmntX5AEWC2C/xZ7GWuFBiIqNEgTGbXCXsak6FAEWL3XXi2WmmWDvSxAVZkpYZ++Qe0w1KlTBwEBAcjNzQUSkgBUrbXEb//tlymJiYlV6UWI09t+5+bmIikpSUhz8eJFSR72Dq/Lyspw+fJlB6uDLVu2oH///pg3bx5GjBjBJIs9ISEhCAkJkb3Hghqn0awvA5VeUCnmz5Q7EGTzZ1Pu2hLGKGzRyuT8/HhdFsFyqMZKT9ntgqIZCROCdZfsUTa2vLTgmWeeQf/+/dGoUSOcO3cO06ZNQ0BAAIYNG4bo6GiMHj0aEydORGxsLKKiovDEE08gLS0Nt9xyiybP12v9YYYX9T6559URJpe0nBctKYf8DM7bIwC+ZDRicOR90CDYMVudkmrED9GhjdavHYbjl65hcKcGuK9jfcm9xnXCERsR7PEzAqwWfDCqq+RaeEgAOjSIUfX5lkm18MsfBRhzawp6NZceM2qWEInQoACFT3qPetGhOJdfhOf6tkC7+jGSe63qRXlVmdkqKQoHzxVg7G1NcFuzmmNaD75f5adHqbz+M7qb5H+rFejUsDaCgwLQuXNnbNy4ETf/rQMAoLKiAhs3bkRmZqZsXmlpadi4cSMmTJggXNuwYYNgLZCSkoLExERs3LgRHTpU5VlQUIA9e/ZI8sjLy0N2djY6d+4MAPj+++9RUVGBbt1qZN28eTPuvfdezJo1SxLJTK0seqGmuwppVDYPWzuS8UUsnz+jw9qIkKotR6HoCCdvTm9Dqtuv9FhZdbQub8si43Oo5oiXwocq5f9VW76R1XV0rURURwauys+ePYthw4bhzz//RHx8PHr27IkdO3YIR0TnzZsHq9WKwYMHo7i4GBkZGXjnnXcMk1cJPdeA9nm7+yyel6lyimujlVfMQRl4LmA7SDnkAk+CU2nv0EzcKdgww5twV9EWvAmrya5w3wMffqwOBgk+YHUAaYZjcEYjLiEjhi5/rCE9R5mezeLQs1kdXfLu2jhWVd6u6rRH0zq6yagVPZvWQTuVSi+9sS+vWiGBuKrgtyk40Oq0bCdOnIiRI0eiOKYxSi9FYOuy93Ht2jXBt8+XCybjSnEoLHe+BgAYP348evXqhTlz5qBfv35YtWoV9uzZg3fffRdA1Vw6YcIEzJgxA82aNUNKSgqmTJmCxMREnDp1CgDQsmVL9O3bF2PGjMHixYtRWlqKzMxMPPDAA6hXrx6AqqNk9957L8aPH4/BgwcLfoSCg4MFp9SuZNENhnUBa0gM9k2XuidEhVVtOeSOFfIyL9qOcsk5UDfqWFmR7LEyqTCuZFNbvnJ1xBrxTEtWrVrl9H5oaCgWLlyIhQsXavpcMyy7taoPE2wPuYI9KJX5CpgcUsvA2lF0D3Wo4QPMMOCZEW/UkfmGF+9g5omNJ9klzrx5EkwEr3L5AqrCwdMoROjA0KFD8cYbb+Cz9+bi3PIncOn0Eaxbt05w9FxwKQflhVeE9N27d8fKlSvx7rvvon379vjvf/+LNWvWoE2bNkKa5557Dk888QTGjh2Lm2++GYWFhZIQ9ACwYsUKpKamok+fPrjnnnvQs2dPiVLngw8+wPXr1zFz5kwkJSUJP4MGDWKSRQ9UWQ4xrvdYo5WxKpFqVR/RLCiqOQLK25LUdiyyQHRM1ah1M4sstpHZ/rgh68vFWiFBjs+0fwjhaAzgpgWc0pwqedHsptMnf1Ie8bQ2YVmn8iO1FLIccgN25ZGO1a/WXNjVfV5bqAieRGQZiFjf2hHuY0Q79sTnEMEn/lhHejukJghnZGZmIrrzvZjyv4O4p20iunXrLNwbPn0pPtp1WpJ+yJAhGDJkiGJ+FosF06dPx/Tp04Vr9mHjY2NjsXLlSsU8li9fjuXLl7uU3ZUseqDG55ANtWtQIZlOoext/rtkHZJzMrbUiazyB3Wx0NGxvbc3oHVqVcsi52RfwZGxsk8idc+MClOuI06qyFC0imSs6Djcjfy10l3aKxJ5NCbgSSZPTgtx9DVkIcshP4P3Bglw1vk5kMVIGf744w88+OCDiIuLQ1hYGNq2bSvx21BZWYmpU6ciKSkJYWFhSE9Px9GjR40TWIRG/hl1hae3HeKC4UgqCbzK5QvwMNYRBKEONf2V1bLH5tdcreKJdcyIq/YxlpNf5HYeeiMoh0QKGaNErBPhqKhSqlOLQt2xym7zA5dbUISKahMym9LAH18OePqddbUN0GiNa9ZqNS6Uvb7peYAsh6oxY+WxYIZQ9lxVgQENwmUdeVmkK1euoEePHrjjjjvwzTffID4+HkePHkXt2rWFNLNnz8aCBQvwwQcfCH4dMjIy8OuvvyI0VJtIRNyjWF3yFcZVOzcBvj4284KamcFKleF3sDvd9HyNwfEyxevsPnkZe09dsYvwJd9fy8or8NXP53Eu/wYqKiqx/difAICT1REDXWNRzBsAfj6bhx3H/xQcJJ+9ckP0Kdc0T6wFANh14jLmf3cEARYL1h44DwA4l3dDxTAwBQAAdZZJREFUZS76klInAgBwJLcQ/1z/G0ICA/CfHVV+qi7JWBPpScO4cFgtVYqqGV/9iqiwIKz9Wb68bGPzkdyreG/rcZSUV6CyshL/238OgDT6mjMaxYUjOMCKayXleOnLg4iPDJEcA/QfaBAi/BdSDrmCIzsxWjDxjy/V0axZs5CcnIxly5YJ11JSUoS/KysrMX/+fLz44osYMGAAAODDDz9EQkIC1qxZgwceeMDrMovhyipHAZ722mZoujyVl68h3tQrKjYNcQ6uld8Eajy6okXxqg3B5Cd892suHvlwj+y9K9dKHK69uOYXrNp9xuF6mUonQs4sh3afvIyh/8qS9Ud05soNdGxY2/GGHa3rRaFhbDhOX76O+d9JLYxtiiajSY4NR/sG0fjpbD4Wbjomubfn1BWFT+lDdFgQbmsej82HL2LJjyck9+zLy1Z3J/+8jle/PuSQ17pfcjDujqYunxkUYMWdrROw9ufz+DDrlOReeDBtGQWUApEwZsMyLemZt/N8+J87eRKRRRSe5BZDPV0GxeWJQQYdmqy5qn/rHVHNX9GmjuTf2lXa3fcWX3zxBTIyMjBkyBBs2bIF9evXx+OPP44xY8YAAE6cOIGcnBykp6cLn4mOjka3bt2QlZUlqxwqLi5GcXHN2zd7HxDeQGvrOT0cgxoNTxOWGRYmvoA6h9T8oJ2fBY0y0hGeRPQkgivBxqd7zwIAUhNroUNyDCwW4KNdVcqfQrvIcCVlFYKVyJ2tElAnMhif7v1DEgbdFc781ny+7w9UVAJN4iPQtXGsRBax82JnBAVYsXJMN3y06zQuX6v6jL0vKR54/6Gb8WHWKfxZWIyKykrhexrBmw90xIfbTyL3ahHKK5RlEa8PG9QOQ4+b6sBigaAsZLH+mT24HdrUi8bZK9dFysBK9ElNcPdr+AzKR7mcj3bs4ebVR6fWaw7jcfzmab522Eu4kE3WyTinkHJIR/Sse9a8zbXB4scpGvuA7l5agK8NOQAcP34cixYtwsSJEzF58mTs3r0bTz75JIKDgzFy5EghrK8tooyNhIQE4Z49M2fOxMsvv6y77AB/5WlD3Bc5FZFbvFWnVC/yuDuP6KnY9sm3o4xHVY2A6e2oVs/k5+t7hcO5VwEAL/ZrhZ7N6gCoUcjYW/ecuXIdN0rLEREcgH892BlWqwUx4cFYtFlq/eIMm/WJ3MblcE6VLE+lN0f/9vUksrAsdRrUDsezGanC/5cKi7Hh11yGHPSnTmQIJt7ZXPh/54nLOH5R7dE8bYkOC8ITfZoJ/1+8WoLvDjmWl7hvPNS9MR65tQmAGuUQy3o0IiQQj91+k3sC+xieDjmsY7YmVieMmw+u5j4F5GQ0amvIbMGlixT6Qg6p/Q2OlZU8jU9GisKLQrmiogKdOnXCa6+9ho4dO2Ls2LEYM2YMFi9e7HaekyZNQn5+vvBz5oznb+R4ajdKsDoGNQJxu+NpE0oQBOFvvLv1mKCQSIgKcbhfUSH+uxL9FvwAAIivFQJrtZZn2M0NAQB3tIhX9UzB76Hd9VW7TiO7+khV3Vo1snRpVHWULKO1+xYlT/SuOuo0pHMDt/PQm6n3tgIA/F+vJgZLolxeYn9wDWqHC3+Pu6NKyTOtfysvSOc78LIOJwgjIOWQC+Q2dUobJ8UoAprJ4n7erjbQZtgMcqXdZogS4KnYtknK218/KSkJrVpJFxQtW7bE6dNVZuCJiYkAgNxc6Vus3Nxc4Z49ISEhiIqKkvxoCUctRBEzyMgTRpSX3FizcOFCNG7cGKGhoejWrRt27drlNI/Vq1cjNTUVoaGhaNu2Lb799lvJfTWR/i5fvozhw4cjKioKMTExGD16NAoLC4X7mzdvxoABA5CUlISIiAh06NABK1ascOs7q1kL+0Lb5XnRz1P5Grkm4LmOvMVrX/8m/G2LICVGbDl05MJVFJVWOKRtGBeOgy9nYOlDN6t6pm3cs7dKeuGzA8LfcZE1+X/yf2n4dXoG6tZyP/hEuwYx+OXlDMy+v53beejN7S3q4peXMzDp7pZGi4L2yTE4KFNeVtFuTtwGns1IxS8vZ6BPSzoSpiVmGKI0s9jUKB9/gcmPFKeFS8ohGcQaeDV+/GxvaVT6/GOXxyo/YbuDGSwYzEiAD9ZRjx49cPjwYcm1I0eOoFGjRgCqnFMnJiZi48aNwv2CggLs3LkTaWlpXpWVd8yw2RG3O14nLKP4+OOPMXHiREybNg179+5F+/btkZGRgQsXLsim3759O4YNG4bRo0dj3759GDhwIP72t79J0tgi/S1evBg7d+5EREQEMjIyUFRUE+Z5+PDhOHjwIDZs2ICvvvoKW7duxdixYyXPadeuHT799FP8/PPPGDVqFEaMGIGvvvqK+TuqGXfM3C5MLLrfQHUkT0y4c+WQ2IrIXpEUERKo+sWa4JvSyVBQWySL1WrRxElxJIOMRhEZwo8XDrk6FStzw4MDJPd4kt1ncfES19GXqHofRTUviPV12O/Q7zlatyr5zeUJl3XK4EfKaEg5JIPVahHOXpdVuHbmF1idWG1ECFZs+Zd7kD/f024VtoHPk++pFTYFYbnKXX2AFnXEWSU99dRT2LFjB1577TX8/vvvWLlyJd59912MGzcOQFV9TZgwATNmzMAXX3yBAwcOYMSIEahXrx4GDhxorPBQbvNJMWGaPkfJsZz4DasYST3zVukcIi4ira0ZggPlp0D7apk7dy7GjBmDUaNGoVWrVli8eDHCw8OxdOlS2c+/+eab6Nu3L5599lm0bNkSr7zyCtq3by/ct4/0165dO3z44Yc4d+4c1qxZAwA4dOgQ1q1bhyVLlqBbt27o2bMn3nrrLaxatQrnzlU5np08eTJeeeUVdO/eHTfddBPGjx+Pvn374rPPPmMuC1UOqam9EoTXsa0vxDSJjxT+FnfLkMAAh7RqsVpcv+gMCXI/f0I/xG0glOpIN5h9COk4ZSqfYmHNx5wY5dSZdR1kxnUTKYcUYNnsW4W06qNCsGDLv6xcA6sU4/UuitQowQwWBDWyVKhU9gRYtFMQOjrAr7rg7eHl5ptvxueff46PPvoIbdq0wSuvvIL58+dj+PDhQprnnnsOTzzxBMaOHYubb74ZhYWFWLduHUJD3TczZ0XNwCueREakVVk+yS24teT2FnXd/qzNGWTjuHAXKY1jQIcqp6Q9msYZLAk7tiYzY0Abl2lLSkqQnZ0ticpntVqRnp6OrKws2c9kZWVJ0gNAnz59hL9dRfqz5RETE4MuXboIadLT02G1WrFz505FefPz8xEbG6t4v7i4GAUFBZIfwH+OlRGEmWlbPxoAUC+6Zo4VT4GBAe73UsHnkJOFYqDO8ybhHuITD2HBpBzSCr039vbZa/k8rfIyg26DJxlZFIi8unQh5ZACcsohpelSb6VGoBZHlhRClPKkLArQWcnGQgCjNVhAAJsySQ6lUPZGcu+99+LAgQMoKirCoUOHhDD2NiwWC6ZPn46cnBwUFRXhu+++Q/PmzRVy8y5Kk0VwQNWwd4cHyhsxSvWlNOSriVZWK7TKDLxrivIm32jiI6sck7ap3qxoiZK1kFYLgPYNYgDI+/Kw59KlSygvL2eKypeTk+OQPj4+XnLflodSnjk5OahbV9pGAwMDERsbq/jcTz75BLt378aoUaMUv8/MmTMRHR0t/CQnJwNQ9xaOpwUY4T/wtE4xmpQ6EQAApXeFnrz0sCqsE8UEBdC2gUfE+4NwshzyGK2HHJ6iVyvmw9XuQx6eQsCzisKR6C6hUV4BmyWIGsuhmrRSpYZW7cAqY5XC2onNsKbX+3geC7a3b/bHCpXKXc5yiLmOzFBJvMNpGRrfol0jiVbGaTkSymzatAmjRo3Ce++9h9atWyumU4oYqM5yiBoGYRxmNM/XGpvyR7xJEvdLTyx7avx6KI8GelvcEu5RXFazViXLIf1R2ug7+oJi+7wzHK2MNMpb0U8SPytXue/KWyh7xTYhm1gjYXSClEMKsBwr08LfjDNsigot8ueps9sTUP1GigefQwGMR/lYj6E5Q8m6i9bF7mOGtzaEPEa0e/Ej69Spg4CAAKaofImJiQ7pL168KLlvy0Mpz8TERAeH12VlZbh8+bLDc7ds2YL+/ftj3rx5GDFihNPvphQxUJ3PIddpeIfnOdAX0KJ0qY6UsfVBsaWIuF8GWN1f1tdEK3M7C8IgikvLhb9DFHzpERqg0uG0p1Q6+Y8g9IZGkGrsF73OFD4saeXSs+LMiklt3i7TcbDod2U55E0RXTkBt5fF6kR2tW/bfWHjZQRqjm8ZjZIpLEcimmL5YURxBQcHo3PnzpKofBUVFdi4caNiVL60tDRJeqDKsseGmkh/aWlpyMvLQ3Z2tpDm+++/R0VFBbp16yZc27x5M/r164dZs2ZJIpl5glK7NKS9avVMjvqaL6JF8fI0HvKKECxDZNQsLjZPLIdsH+Xp6AahDrHlEE9rH7Ojd0na7w94rDkzWAzzJKMvhLKn+IYK2N6+qDnixOqfhl0W+SNOLNg6Dg/OnpXQ2wKLBZb6B8TKJM/rSMm3FE+Dn9nQs0X54ltuntqaIZLYzdgTJ07EyJEj0aVLF3Tt2hXz58/HtWvXBN8+I0aMQP369TFz5kwAwPjx49GrVy/MmTMH/fr1w6pVq7Bv3z5R9jWR/po1a4aUlBRMmTJFEumvZcuW6Nu3L8aMGYPFixejtLQUmZmZeOCBB1CvXpUz8E2bNuHee+/F+PHjMXjwYMEXUXBwsFOn1PJo3471tdjTKXwvhxgpoyfRjUnJoD0BFufrBE+OfdmUClRt5qOE58W9CdG6D9ivE7XMXqu8ePZJa4MnkVjrtFLyN0/fxBGyHFKAJXx8YLUiQYsjRXIECEeW3M/DZmZaXFbuIqVxcOVziFFRFaCBU3Khjkr5rSMzwY96QxmeZDTFRs6g1yxDhw7FG2+8galTp6JDhw7Yv38/1q1bJziUPn36NM6fPy+k7969O1auXIl3330X7du3x3//+1+sXLlSkqeaSH8rVqxAamoq+vTpg3vuuQc9e/bEu+++K9z/4IMPcP36dcycORNJSUnCz6BBg9i/pI6h7HUN56tR3jz1RSV4esvoC29HzYjt1JjSeK2J5ZDbORBGUVpGteZNlDb39r1Py7HPIW+FdOw+afkfoOUkNGzJylpc/BevA2Q5pABbKPuq3zxbDoVWRy8oLuX37YKpo5VpILutjorKjP/+vkbVQtq4EdpsyzauNnOcyJKZmYnMzEzZe5s3b3a4NmTIEAwZMkT43xYy3oYt0t/06dMVnxkbG+ugVBKzfPlyLF++3LngKlFqo0UiZbWa+UOcvkhjRTerLPJ5VEhl5PCFSVFZOTcyFpWW25W7c1nE6YvcrKPisgpd25GZscgdKxONkYEeRBOT82dEmINSshwyFD1frlF3JLwNKYcUYFEO2CyHdHNIrcFxq9CgKhl5XAjbsJWjWifQesJ6TEyLo4W2OiqvqERpeYVDyFiuNuwcoVguXiovTyZu8g3AhrdKyx9rRakdp05Zx5SPXPozl6+7I5KqvLf9/qeqz14vrpr75m44grkbjjjcv3K9xDPhNMAmw9T/HcTU/x10uO9NJYltrTD/u6OY/91Rh/tXrpdK/i8oKgMA9Fvwo2NejEqizYcvMrc7f8HVsTKPopXRsTLTUk6V5hW0XhtoFnGMIW+j8tETnmRkEYUjsSWQckgB2wQ7/7sj6JZS5bth/5k82bQ2xcCf10rw1sajQiM9/ec1TWSx5f/mxqM4dL7q7fNvOVeZ8rBZpfx8Nh9vf1+z0LtwtUgTGbXA9j13nrgskbGgqFTpI7rLciS3UFpeBcWy6W3tZem2EwivDiN6tXqxrBZbHQHAG+sPo1ZoVff86WweUz7+jJJ5LC2bXCMuI14nLEI/9DwDf+CPfKb0B88VoENyjKYyZJ++4vT+YcY5VQ+U1hg2Tv15HV0as/qSco/fzhc4vX8k5yrQXttnXitWnjNDg6zo1LC2tg/kiMvXSlAdONAp8k6ja0Zsj3wOVf8myyHzMbxbQ3yw/STubpNktCg+gdC/tFoMqfTn446SQzP/ey7+NxLhRSpHQjn6aHIunPg+70OsaZRDr7/+OiZNmoTx48dj/vz5AICioiI8/fTTWLVqFYqLi5GRkYF33nlH8APBgv2mMqVOBI5fuoYfjl7CD0cvSe6FiTbxAFA/JgzBAVaUlFdgjswbSfv0rDSJj8Te03n4+Ww+fj4rXWSrzTshqsaPxRvfai+jFqTUiRD+lpUx2HsyNoqLgMVS1YHVlFdKnUgAVW9I7dPbLIJcERJoRUx4EPKul+JfW4873A/loI7MhLfOUXtkOaSdGD6LuB55ejvkayi1488e744WCbUAAK2nrXeZz8GXM4S/1aSX48o1eSuepQ91QbeUOADAw8t3Y+eJy27lqYWMeiA2PDVaxgtXa16EsMhyd5tEvDGkSmu07fdLGPvvbKfpxYitkcTPBICgACuCfThE96hlu7Bp8j0u0wnHyhRC2Xvmc4gsh8xKg9rh2DvlTgpjzxl6WodrZXVk2nWVQeMU697CjMVrCuXQ7t278a9//Qvt2rWTXH/qqaewdu1arF69GtHR0cjMzMSgQYOwbds2j585uV9LNKgd5hABICjAihFpjSXXwoID8NbfOmLz4Yuwb611IkNwe4u6Hsny1J3NUSs00MGkPMBqwQM3N1SVR9O6kZg1uC32n8lzGDjqxYShSyPj38i1SKyFGQPb4OA5x7fMKXUi0KxupNdkSYwOxdy/tscumc1HUnQYOtuV130d6yOnoAgX7SyxKiuBO1LV1b/FYsE7f+uErw6cd3BuXis0EH/tksz4LQgbRi92jX6+KkQy0nE3/0OpjUaHBSEiRP1SgSWtEkqWC2JZQhiV5eLNtBYy6o3RMpaIfN+xyCKuo/Bgtu8gnveM/v7e5thFdZbmQoAS8Xgtvh/gybGyqt+mCE5AOEAvEL2HYmQvHZZOQta0LiO8BPezb2FhIYYPH4733nsPM2bMEK7n5+fj/fffx8qVK9G7d28AwLJly9CyZUvs2LEDt9xyi0fPvSk+Ei8PaKM6fUbrRGS0TvTomUrUjwnDtP6tPc5n6M0NMVSlMskoHrylkdEiCNzXsQHu69hAVdqw4ABMvLO5x8/s3rQOujet43E+/oSSFt8M86gZZDQacRl5zecQ1YuAEUWh7LrNfWlov8uGu8XlSd/Ry2+jL2EzDNLD55BgOeR2DgTh27iroFHqU1qsNRTzZpwvFY+6sYmjK2qjxHkD1mWKbHpOF5vc2x+OGzcO/fr1Q3p6uuR6dnY2SktLJddTU1PRsGFDZGVlKeZXXFyMgoICyQ9BEL6Nnv5U1EpAEDyj1EesBixelDa+Hux7CUbctR7x5O02OdV1ja0/iq2sxGUeYPV8WU8+hwiiCk+nHOXPu/BPo2rNqM2EqJQLTxaEPE39isf5FNM7foCjopWFa8uhVatWYe/evdi9e7fDvZycHAQHByMmJkZyPSEhATk5OYp5zpw5Ey+//LLWohIEwQFGWJl4MoF6yy8SK2KpbL63vPt8kZ8hiSzeKS9e60VPtHSQ6SlKfYrM6r2Hu33ekxrifcHMA1YXx8rI5xBBeI5xXcDzOc5fuq/xL319F24th86cOYPx48djxYoVCA0Ndf0BlUyaNAn5+fnCz5kzZzTLmyAIPjF6sWv089XA00TLkyz+jjGWQ/LXSTXkPdy1HqFjZfpi0/0olZVH0cqEI2tuZ0EQfoHyESwdHVDrljNBSOFWOZSdnY0LFy6gU6dOCAwMRGBgILZs2YIFCxYgMDAQCQkJKCkpQV5enuRzubm5SExU9v0TEhKCqKgoyQ/A7bE/giBcQH1Xe3gqUyOsRXj6/t6iUsESwQjEigmxLEYoqvwVt30OedB66FiZa2qse+TLKsgDh9Q1/YvqgSBYcNVjFK1hVYyXroZFrax+FV/KcTTtKn9X7wvJqiCUS89R0Urg9lhZnz59cODAAcm1UaNGITU1Fc8//zySk5MRFBSEjRs3YvDgwQCAw4cP4/Tp00hLSzNCZIIgCFnMsKflaV9mtCwmqC7NUXT0aEBhKFoOiWThyR+CL+L2sTJxHTEqGeyjdBKOCD6HJNEla/72xOdQQPVHy6geCAKAo9KBeTrUKNy8bNYazc2sPnSMgKc1tLKPJoX0Mh/gqWzl4FY5VKtWLbRpI40WFhERgbi4OOH66NGjMXHiRMTGxiIqKgpPPPEE0tLSPI5URhCEOeFo/pDQIbk2OiTHIDk23GhRVMGTbxdvSjIyrRG2H/sTAzrU9+JT+UBpYaOFtQ571BTvK6o4avKK8CSjkiyetBc6VuYaW/mWS6zrasrcE59DIYFVodCLSsvdzoMgfAGj3z148nyjZfcW/vI9jYBb5ZAa5s2bB6vVisGDB6O4uBgZGRl45513jBaLIAiDEM8V3tpIqZmfAqwWrBnXw/EGR5s9JSzw/lsO5dCs+vLygDauE/koeobaZcUIfw6E8ZBuyDU23Y+SAtUTn0PhwTblUAUqKioF59cEQahD0QpHpVWJs/lWOW9twrubYd41am0oB7u1tWN6nl74iDGVcmjz5s2S/0NDQ7Fw4UIsXLjQGIEIgjAcNWMrvWFwDZWRf6O0wDTCz4+SBYkGUboJnfGkvVAIddcEB1Z1guLSCuGa9FiZ++UfVq0cAoCisnKEB5tqi0AQXsN+pHJleevJyKakhNAib3E+PGOzZudhimCN6mjGKJC01CIIwmeQhD330rsETwZ8/qdkoxz9iY5MiB5vgjWMz2FEkSspCXh6g0nIQ9HK9KV2eDAAIO9GqXBNXOaeGPuEBtYoh26U0NEygrCHdXyz9Uf7OU2Lka7GilB6ndXXm22NZ+/zjSdlhlw5GiWe7SWVWr+HNbLXXOPdZyK9FqiGlpwE4btQaHTXUAn5N8rHygxQDipc9xfloJm/pyei+7vlUN/5WyXWO3LUjqhSDn3/2wUMXLgNAFBSJrYi8iBamdWCyJBAFBaXof9bPyIhOtTtvAjCzNjWjJ4Oxe5ajahJX+Oc3rNxU055wRuuojR6E0GZplIUi0b15E1IOUQQhE/iPZ9D7g/4ZtgEGi2i2FqELEf0Q6twuFqgfMTNy4IYhBnM/JXwxE+NmRbPevBbzlWXaTokxyAmPAh510ux/0yew31PW849bRPxyZ6zOJdfhHP5RR7mRhD+jSvFgCf91aJglWR/3xWulEw8TEdyURrFeFNGJWswQRaG9BwUrSykHCIIwtyoGF39fM+hCh7eyNjgRxJ/Qt5c2whFhfIbOV6XUtpi5m/pkeVQhes0vkqdyGDMGtZF+H/Mh3uE62Lia4Xg26duw89n8iX91JY+MMCz1jNjYFv0b18PRSKfRra8CcKXYVkDqXUC7UqR4Orzzu66UpioxZWTex5wpQjzJqzlbkafQ6QcIgjCJ/HWBsszn0P8bwMNf2tkUfib0BRxOxYvwHjyOUSWQ/zjybGmcjOtnjWmR9M6uLNVgsP1VvWiHa7VrRWK9FbyR75iI0I8kiM40Ipbm8VLriVGhSKnoAg3xUd4lDdB8Iya4UdpzebKabS9IoFNESV/XfGoFeMwynpMygjkytEoZZZcuTuTRc4yi+OiBkDKIYIgfAiljQnvAzFBGE2lwj9chbI3sdKECRN/TU+qyN4hqj9hX2xrn+yJFTtPY0J6M1Wff2NIe5y+fB0dkmM0l23lmG5474cTePz2mzTPmyC4pHoo8nTKESyHdBjbbHl76sjfprzgWTmvZzmyYmEsd9b0PEDKIYIgfBMvbSQ9Ge7NsNetelNm3KQmiVZmmBS+j3hdKK5tIxQyZDlktATu44noPG9OvE3retF47b62qtPf37mBbrI0iY/EzEHqZSEIM6LH6OPS55DCgKnGl6Urix+1czerDx0jcO0XyXtSuvZ/pP74H68vvCiUPUEQpkbN0Syez1LzAk8lRNVlAArm2kasXcRvB8WLJy2OYXK6FpNghuOmSojLl7Ufm+jFquaYoV0SBOEc+34cYFU4Vqby82ryBjxb49ryqVRYA/CAVaEcjaCmvMTHyrRLzwOkHCIIwicxw1rbFBsCg2WUuBwyQ3mZlOLyGge04oWLFv5vWLPQM5S9UhY8KWSULId4av96lCNvGxJvwlP7Iwh/xJPxR9kvUNVvTxwpu8q7Kn9Resb8BQskHjQvCsiVo1HSsjrHrkmvk0A6QMohgiB8BmUTXf3w4/2MjlCheptrxWXC3+JFjLhLhQbVLBn0XEgqnc3XRDnEk4ZFATPIqIQnR+JoLCUIwijUDD+sQ7OekarE84QnyierCZQXis63DcDdaGU8RFpTC/kcqsbMizGCIKow0djLHVR2/s3ET37C0l25AIBfzxcI18WWQzFhwcgpLQIA3P7GZkSG6LOEmLH2ED7d+wcA4JBIFi3maTP48zH1csQD4dX42fBVTF3nBOFj2EYiTy36XPkc8sQ0W2o55Ji/2px58uejBE8R1Vh9NDlLb3zJykPKIYIgTI3SvOW9+cz92coMRwmMllBrnzOEMmKlkA1xPwoRWQ6dvnxdV1kOyciihWKHh4WuK/iXUBlP6qiiwnUagiAIPdDiBZn9GkXJKsfVs+TuOyodxD6HVAoog01Gnn3iaHE8TyvkrMGcSSVvPWb893AGKYcIgvAZFI+V8T0OcwI/hUT15X3+9ffOiIisBQDYcuQi3v/xBADlPvXhw12Fv0cs3aWpLLMHt0NidCgA4PjFQrz05a9VsmigNjGH5ZAJhFTAkzriYeFvFCaucoLwO9QOVYJVjtqw5wzjp1g5JD6KzXr0yjbf8BwtUq4cjRJXKC/VoezZ0vMA+RwiCMIn8ZaViScTlBk2BEbLSA6pvUOPpnVwW/N43NY8Hj2b1hGuK/UjW9rbmsejTmSIprLc2rxGllubx9fIokH9a+FgW29MIKIi7sq+cOFCfDV5EE69cR/OfzgRu3Y5VziuXr0aqampCA0NRdu2bfH1119L7ldWVmLq1KlISkpCWFgY0tPTcezYMUmay5cvY/jw4YiKikJMTAxGjx6NwsJC4X5RUREeeughtG3bFoGBgRg4cKCDHJs3b4bFYnH4ycnJca8gCIIwBFXh4xnz1MQhtYJc4rHWM59D/BzZUoInv0isdcqT1ZNaSDlEEIRpyL9RCsANhYx5xmTD4Gne4kgUv0S8GFW32fdOjXmiNOnaOBYAMLhTA42k0Q8zKLCUcMcy6+OPP8bEiRPx17FPIemhNxFdvykyMjJw4cIF2fTbt2/HsGHDMHr0aOzbtw8DBw7EwIED8csvvwhpZs+ejQULFmDx4sXYuXMnIiIicN9990nyGT58OA4ePIgNGzbgq6++wtatWzF27Fjhfnl5OcLCwvDkk08iPT3d6Xc4fPgwzp8/L/zUrVuXsRTMW+cE4WvY1kOeDsU1Idi1D7IgDmUvqzRRmXdAtSZAyeKIh5HJWTl6e7oMcKFMs5enJpS967S8QMohgiBMx9qfzwt/K42tNzeu7RVZOjZ0/zm9RFYRvHJP2yRDny+ePG9vwX95+QJi3y9qFBVav81TslbyxBpwyUNdsPjBzvhHv5Zu5+EtOF0vqsKdI3Fz587FmDFj8N6MZ7D8qfvwy8b/Ijw8HEuXLpVN/+abb6Jv37549tln0bJlS7zyyivo1KkT3n77bQBVm5z58+fjxRdfxIABA9CuXTt8+OGHEmueQ4cOYd26dViyZAm6deuGnj174q233sKqVatw7tw5AEBERAQWLVqEMWPGIDEx0el3qFu3LhITE4Ufq5WW1wRhJvR4QaZklaNF1C2pzyH3j1vVhLKvucbbCzq5cjQqgIFVUPaoO8on55Scp5exctDsRRCE6fj1fL7sdfG2pGtKrPC3HpOIzRKha4r7yqG/tK+nlTgeo1RCj/RsAsC7vlqUJs4BHeoz5fN831QAwB2kVGJCXPxqql3P8LLirD1pg1GhQejbJhGhQQGeC6UzpvY5xCh6SUkJsrOzkZ6ejsAAK+5qnYi6UVXHwLKysmQ/k5WV5WDJk5GRIaQ/ceIEcnJyJGmio6PRpUsXSR4xMTGSa+np6bBardi5cyfblwDQoUMHJCUl4c4778S2bdsU0xUXF6OgoEDyA/D7BpkgCPXY92M5Z89a5w149oLGDKHWtSxHT7HVA/uxMp0E0gFSDhEE4ZPovcFqEBsGwFOfQ5bq31pIpA+BAVXC1Q4PNuT5YmsRWzmpVRJEhVXFXAgKoKmOBfECTNw2ldq61mseaX8Qy8JxR9EQM39NVuuuS5cuoby8HAkJCZLrCQkJin57cnJynKa3/bZPEx9foyTOyclxOPoVGBiI2NhYJn9BSUlJWLx4MT799FN8+umnSE5Oxu233469e/fKpp85cyaio6OFn+TkZNXPIgiCD+xfOCoeyXJ1BMkhvcyzFI8viY+VyYVJVzcWu1Je8DAfOVNgeVs8Vz6aHCPWOZOdg8KVgaKVEQTh83DwssEpvMsH8GVmzJMsvojEckjFylDP9qtkOWSGPuMuZoiopoREmWicGF6jRYsWaNGihfB/9+7dcezYMcybNw///ve/HdJPmjQJEydOFP4vKChAcnIyp1sEgvAfpKHJVWpzXKC3VY7VUqWk0MIhNQ9WOUq4UrJ5E3cdUvNcvvbQ69RqaGImCN9C7z6thcafhzcyrjBaRHEZsZY5r29leId1DeNq0aOqnauwStKzPnnqi3r4XNIchQJjlbBOnToICAhAbm6u5Hpubq6in5/ExESn6W2/7dNcvHhRkoe9w+uysjJcvnzZpX8hV3Tt2hW///677L2QkBBERUVJfgC+2h9B8Mjrr78Oi8WCCRMmCNeKioowbtw4xMXFITIyEoMHD3bo90ZiUwzYhzHXSk1QE+Ld/bxtY0+5Sh86RiBbjgaJWFPmovJykr4mlH3NNb5K1xFSDhEE4fPoORDzPshrBU+LBWblhT5i+Cysda110xDvkyVv5/xkA+0rlkNqCA4ORufOnbFx40bhWkVFBTZu3Ii0tDTZz6SlpUnSA8CGDRuE9CkpKUhMTJSkKSgowJ49eyR55OXlITs7W7j2/fffo6KiAt26dWP7Enbs378fSUnGOvInCF9i9+7d+Ne//oV27dpJrj/11FP48ssvsXr1amzZsgXnzp3DoEGD3HqGFr4p7Ye/Gqscj7OWfTmghWWSOULZ82PdxGrFZMZQ9nSsjCAI06F8Blv+bz3QIn+e9oBqytRbKC3SWGWht/HuwbqE0WLJo1TnWjmkNhNm9q2kJrqdPRMnTsTIkSPRpUsXdO3aFfPnz8e1a9cwatQoAMCIESNQv359zJw5EwAwfvx49OrVC3PmzEG/fv2watUq7NmzB++++y4ACNYFM2bMQLNmzZCSkoIpU6YgMTERp06dAgC0bNkSffv2xZgxY7B48WKUlpYiMzMTDzzwAOrVqwkU8Ouvv6KkpASXL1/G1atXsX//fgBVDqgBYP78+UhJSUHr1q1RVFSEJUuW4Pvvv8e3337LVAZcWYURBEcUFhZi+PDheO+99zBjxgzhen5+Pt5//32sXLkSvXv3BgAsW7YMLVu2xI4dO3DLLbfoJpP9eklpDnQdyl6+36vVI1itAMo9C/Ee4EpGDsammnJ0vOft+TLAlbJHIZS9bHrji1YWUg4RBOHzeCuakmf5VHK9KTTPOw9HTPTChgtY33Bp/kZMEoWFHFL7OkOHDsXFixcxdepU5OTkoEOHDli3bp3gUPr06dOS0PDdu3fHypUr8eKLL2Ly5Mlo1qwZ1qxZgzZt2ghpnnvuOVy7dg1jx45FXl4eevbsic8++wydO3cW0qxYsQKZmZno06cPrFYrBg8ejAULFkhku+eeewSFEgB07NgRQM2cUlJSgqeffhp//PEHwsPD0a5dO3z33Xe44447tC8ogvBDxo0bh379+iE9PV2iHMrOzkZpaakkKmFqaioaNmyIrKwsReVQcXExiouLhf9tEQPVTGOsihJWqxHWoV8LyyQz+MThyfqmJpS9yvQaWo95C1IOEQRhOtRsnvTeSGqRuzk2u/zIyCoJP5KbC3afQ/o90x8th9yxvuEFd2XPzMxEZmam7L3Nmzc7XBsyZAiGDBmimJ/FYsH06dMxffp04ZptE2gjNjYWK1eudCrXyZMnnd5/7rnn8NxzzzlNowYTVzlB6MaqVauwd+9e7N692+FeTk4OgoODERMTI7nuLNIhUBUx8OWXX3a4Lp6CbPOOp2s0xSNbGikK5I6Vsc7HwjEpjn3iyJWjUTJaGMucNT0PkM8hgiAID9DinDoP8PQ9tJ84+fluZsBoyyHx21mpyyH/2EGbWVFgZtkJguCHM2fOYPz48VixYgVCQ0M1y3fSpEnIz88Xfs6cOaNZ3vYEBVRts4vLKlykdDd/i8f5Bwsylmsikx4EcSRjMGOZs6bnAVIOEQTh85hBNcD7mwSj5FPabPJsAu2rKPoF8tIz/UXxYOavaWarJyOhUiMIKdnZ2bhw4QI6deqEwMBABAYGYsuWLViwYAECAwORkJCAkpIS5OXlST7nLNIhoBwxkGVNoZjSbvyLDKk6oHOtuEw+ueonys9/kaFV+V8tcsxfbd62PK4VKyheOBicamR0/3tqJktIEACgUKlO7QSytYFCD+rI29CxMoIgCDewTQCe6Ch4nRjE8LTXYzXx1qKO/BHm8tLiWJnSdbHlEEdtUU/McdxUHhOLThAER/Tp0wcHDhyQXBs1ahRSU1Px/PPPIzk5GUFBQdi4cSMGDx4MADh8+DBOnz6tGOlQL5TmzFqC8qaULT+oO4JUpai4oaioUINNeVHAKKM3iXKiBPM2zhRyTtN7UEfehpRDBEH4PGZQDhgtoqsy8qaljppHVVbSRlQvDD9WpuSQ2hTqVM8x87c0s+xGYmaFIEHoQa1atSRO5gEgIiICcXFxwvXRo0dj4sSJiI2NRVRUFJ544gmkpaW5FamsUuFvMazdNCq0ysokt6AY9771A6yWqlnsWomS1QnbA2xKk9HLd6NVvSoLqHN5N9jyCKuS8becq+j/1o+wWPhbM9vKcfuxP/GXt38EAJSWGyOkrcwPnS8QZHFWXjbZF2w8is2HLwAA8m/wq4gDSDkkQPMyQfgC0o6s5ySnxUbVDOOO0SKKy5ndIXV1lAgN5fEHmB1Sa/JM10fW/MUhNU/jAmuZk5KDIAhvMW/ePCHSYHFxMTIyMvDOO+9olr+no1mD2mFoWz8aB/7Ixy9/SB3iBwdaUTsi2KP872mbhJ0nLqOsohI/n82X3EuKCVOVR2piLTSOC8fJP6/jwB/SPGLCgxAWFOCRjFrQsWEM6tYKwYWrxTLfUzt/VGpomRQllJe9LHLl1adlXSz54QRKyisc0tdTWUfehpRDBEGYDvbNK//qgarNMb8bK95KkDd5fAnmU2WaO6QW5y267ieKB56+p7tHOQmCILTGPnJhaGgoFi5ciIULF3qctxbTmP3wZ7Va8NHYW7Dn5GVUVFZKntG0biSiq6123MkbAEZ2b4y2DaKRd70EQM13iAwJRJfGsaryDQ0KwJpxPbDvTB4q7WRsmRSF4EDj3RPHhAdj7ZO34pc/8lEJqYztGsR4VRZX5WVznm2jc6NYfDPhVpz+87pE9gCrBd1S4rwouXpIOUQQhM9igX5KBC02QWY4JsPXRpX1A7qI4fOwKns0sRxScUdsxWIGha+78NRs3bXWA8hpPBM8VTpB+CMMw5X92OZsPooMCcTtLeqyiSIJ2e5csE4NazPlLUdMeDDuYJTR28TXCsEdqXzIyFpeN8VH4qb4SB0l0hbj1YEEQRCMMCsJdNyjaLUB4n4bZeJoZbRJZYPZMs9FelYlqFghWeElyyGe9uZKX9MIPa2iLIzpCYIgzILSmoGGN8IfIOUQQRA+i66bSS2yNsFKgycRmZUMOsnh6/BkleOPej2eLApZZfEXv1Baw1OdE4Q/IjfvkbKb8EdIOUQQhM+j5/5Sq82r0ZtgV4/3pnhqlBMs8vihfsEjjGiLSs/0R6svnjYkrLKQkoMgCH9Fz7GbpyP+hG9DyiGCIEyH2v2ivlOpn0QrM1hGi+I/Kj5rtPAmpUJRUeOd54trTUkWX4andkt+vrwDR1VOEH4Jy/zmh9MS4UeQcoggCJ9B2T+Nfs/UKmuejvLIwZsFB9NCji/RuceItqj0TN77hR7wpCego5wEQfgDnsw0Wq8xxNnR+oXwNqQcIgjCdKh9y6qvia8GeXiehWYoO2D0vpRKiyH2Iy6EOxhtrSOuZ39cGPNkRcIqi5Un4U0ElRpB8INt2rEfzvS26qThk+ABUg5Vw5MZN0EQ2qKn9YGv+BxyhVHiKY3NLHXKedHyhyFOhxQu+1HltW8QDQAY0rmBwZIA6S0TAAAPdW/M9DkrrSoJgjAj/jTZEIQTAo0WgCAIQi+qrF70mfA1CVZmAqU0TyIyuz/hSHYzYbjlkKimK/xowb5yzC04eK4AXRrVNloUvP23jvjpTB46M8pCDqndg8YqgjA/NP4RvgAphwiCMB087Rf90SeK2eDNXxLv8FRe/EiiPxEhgeiaEmu0GACA0KAAdGsSx/w5UnIQBGFGmOaaSqf/aoo/zYEEH5ABMEEQPoPSvoSjva5pMaoMqU69jxEWbVSdvgH5HHIPM1iREoTfoJHfQ7cfTwscwkBIOUQQhOHc2kz+DbXSRKx0PTLEzhiSHFL7FKwbKNpvucfgzg3QOC5ctb+Zf4/uijqRIXh/ZBdtBBDVW1qTOKQm1sLADvUkSWjtzBdDuySjWd1I3NkqQbhGVaQeGqoIwljk5hRvHxOjNQvBA3SsjCAIwwkJDJC9/urAtrLXlTaGzRJqyad3S6oq6seE4Y+8G3iyd1MmWVgxerPr6vnePD5ndFn4O5Ehgdj0zO0Oyjilerm1WTx2/6OPsvJOxYJXKe/gQCu+GX+r/pYVtCpnwr64Zt3fDpWVlWQBQxCEKdFijcN7hFyCUANZDhEEwR0dG8YAAOpEBnuUjxZzaWpilcKpQe1wu7w9z90Mk73RMoqfz+yQmt7Huw27lZZ2Ze3t8MGENlA9eQAVHUGYBnp/RfgypBwiCMLn0fP8tlY5G+3Y2tW+zpvWPGr2mCzykCUS/xjd/gmCIAg/plL8p/x8ZIQPRPI/RHgbUg4RBKGK119/HRaLBRMmTBCuFRUVYdy4cYiLi0NkZCQGDx6M3Nxc5rz12hjybuLLk2WL0vrDEOfEGjmDJEMGc0LVRvgbPM0FBEFUYdQagtRBhJGQcoggCJfs3r0b//rXv9CuXTvJ9aeeegpffvklVq9ejS1btuDcuXMYNGiQ7vKonbBtC249XrzYRPDkrY74e1Rwuhqo+Z4GPV9USOINVAWDQCxpCYIgCILwL7RYJXiqS3KmJKaXXYS3IOUQQRBOKSwsxPDhw/Hee++hdu3awvX8/Hy8//77mDt3Lnr37o3OnTtj2bJl2L59O3bs2KGrTGr3+sGBVUNccVmF5jLY8i7xIO+ggJoh2JN89ET4nuUVhps3BwXUrI7UlFeIBnVEeAfS3xH+DO37CIIgCB4g5RBBEE4ZN24c+vXrh/T0dMn17OxslJaWSq6npqaiYcOGyMrKks2ruLgYBQUFkh9Av42hFgocV3l7ongKsFoQaK3aFhitwFA62mf7nkCVgshIWQIDrAiwlZcKWcSKLcI8kGNjgiAIwpuw+TG0T8y/X0uCUAsphwiCUGTVqlXYu3cvZs6c6XAvJycHwcHBiImJkVxPSEhATk6ObH4zZ85EdHS08JOcnOyWXGr3jiGCAqfcZVrbsa6iUtdpq/IOqM7bM8UDi4xGECJSDulhgcWKUF6laiyHAlSnJYyFFsCEP0PqUIIwFvFLKa38HhKEGSHlEEEQspw5cwbjx4/HihUrEBoaqkmekyZNQn5+vvBz5swZt/JhPVamxirn/R9PAAA+yDqled7eyEcvgjk7+lZjDeRamUaWQ+aE1t8EQRCE0Rg1F9Exa8JIAo0WgCAIPsnOzsaFCxfQqVMn4Vp5eTm2bt2Kt99+G+vXr0dJSQny8vIk1kO5ublITEyUzTMkJAQhISEO1/WaB22WI3M3HEGPpnUAAD+fzdco7yrFw6d7z6JRXDgA9xwfV8lYin+uP4w29aMBALtOXNZERhacRSsLDrSipKwCs9f9hga1q77r3tNXvC4LUFPu/1x/GK3rRTvNx5b2xKVrWLDxqHA9J7/IcyEJgiA0giwSCMJYtFDIeNqPnX2eIhoS3oKUQwRByNKnTx8cOHBAcm3UqFFITU3F888/j+TkZAQFBWHjxo0YPHgwAODw4cM4ffo00tLSjBDZgaToUBw6X4CdJy5jp53CJSw4wOO8bczdcERyz2oBggLVGWYmRocip6AI3/6ai29/zZXKGOSZjFqRFB2KU39exyd7zjrc87aMidFhyC0oxvqDuVh/MNdp2oSoUFgsVYs++zoCPG8DhDoa1A5zmYbV2XnjOhHYfuxPd0VyICHKUWnNG7XDg40WQSAhyrU1aUxYkBck8Q1o40cQ5sHB45COlj5kRUR4G66VQ4sWLcKiRYtw8uRJAEDr1q0xdepU3H333QCAoqIiPP3001i1ahWKi4uRkZGBd955BwkJCQZKTRC+Qa1atdCmTRvJtYiICMTFxQnXR48ejYkTJyI2NhZRUVF44oknkJaWhltuucUIkR2Yem8rNIoLR5Gdz5ngAAv+ntbIo7zvbJWI5/um4vTl6w73ujSqjcgQdcPr64Pb4qOdp1FSLl0BhAZZ8XCPFI9k1Ir5Qzvgs71/oKxCKmNkSAD+1rWhV2V5fVBbrNolLa+Pdp2WTZsQFYo3H+iIHcf/dFhg1YsORdeUWD1F9XtWPtINXx04jyd7N2P6nJq3r8/3TUVlJXBfx/puSlfFu3/vjB9/v4S/dnHP/5k3mD+0Aw6dL8CtzeoYLQre/XtnbPv9EoZ0buAybYfkGIy74yY0io3wgmQEQRDuI14iKCtkSIlL+D5cK4caNGiA119/Hc2aNUNlZSU++OADDBgwAPv27UPr1q3x1FNPYe3atVi9ejWio6ORmZmJQYMGYdu2bUaLThB+wbx582C1WjF48GCJgpYV1jcjak13G9eJwLT+rZnlUUOA1YLHbr/J43xSE6Pw8oA2rhPqjLM66NiwNjo2rO09WZzca5nkWF77z+Th0PkC2fR/aV8Pf2lfT0PpCLV0b1oH3ZuqU2jEiKxiggJcW91FhwVh5qC2bstm467WibirtfwxWF4Y2LE+BnqoBNMKlvKyWCx4NiNVZ4l8AzpWRhAcQh2T8EO4Vg71799f8v+rr76KRYsWYceOHWjQoAHef/99rFy5Er179wYALFu2DC1btsSOHTu4sVwgCF9i8+bNkv9DQ0OxcOFCLFy40KtykJktIYb1SBLBH5Ehgfj88e4ICrCqUg4RBEEQhFZosY6weKhMsn1aThbSUxHegmvlkJjy8nKsXr0a165dQ1paGrKzs1FaWor09HQhTWpqKho2bIisrCxF5VBxcTGKi4uF/wsK5N82EwRBEAThPbxpnUYQPEH7PoIwFh7eMVmrNUAciEL4Mdy/njtw4AAiIyMREhKCRx99FJ9//jlatWqFnJwcBAcHS6IkAUBCQgJycnIU85s5cyaio6OFn+Rkfv0MEIT/QFMhQRAEQRAEYSyuVqT2iiStFEs266AKiX9HWh8T3oV75VCLFi2wf/9+7Ny5E4899hhGjhyJX3/91e38Jk2ahPz8fOHnzJkzGkpLEARBEARBEAzQmRGC4B69u6nNcqiC9EGEgXB/rCw4OBhNmzYFAHTu3Bm7d+/Gm2++iaFDh6KkpAR5eXkS66Hc3FwkJio7SwwJCUFICP8hawmCIAiCJ8i3E0EQBOEveFtla1M+yfoc8rIshP/CveWQPRUVFSguLkbnzp0RFBSEjRs3CvcOHz6M06dPIy0tzUAJCYJghfacxsNTFZASgiAIf4I2fgRhLDysOsjnEMEDXCuHJk2ahK1bt+LkyZM4cOAAJk2ahM2bN2P48OGIjo7G6NGjMXHiRGzatAnZ2dkYNWoU0tLSKFIZQfg4N9WNNFoEws9YuHAhGjdujNDQUHTr1g27du1ymn716tVITU1FaGgo2rZti2+//VZyv7KyElOnTkVSUhLCwsKQnp6Oo0ePStJcvnwZw4cPR1RUFGJiYjB69GgUFhYK94uKivDQQw+hbdu2CAwMxMCBAzX7vgRBEAThL1QyqGTs07J81hkW4VhZTX70rozwNlwrhy5cuIARI0agRYsW6NOnD3bv3o3169fjzjvvBADMmzcP9957LwYPHozbbrsNiYmJ+OyzzwyWmiAIvUiODQMApNSJMFgSwp/4+OOPMXHiREybNg179+5F+/btkZGRgQsXLsim3759O4YNG4bRo0dj3759GDhwIP72t79J0syePRsLFizA4sWLsXPnTkRERCAjIwNFRUVCmuHDh+PgwYPYsGEDvvrqK2zduhVjx44V7peXlyMsLAxPPvmkJHInQRDmglwOEQQ/KFkvC5Y9OilsrDaH1KQQIgyEa59D77//vtP7oaGhWLhwIRYuXOgliQiC0AO182CzurVw5vINsrnVAZ6OcrFKorfoc+fOxZgxYzBq1CgAwOLFi7F27VosXboUL7zwgkP6N998E3379sWzzz4LAHjllVewbt067Nmzp1reSsyfPx8vvvgiBgwYAAD48MMPkZCQgDVr1uCBBx7AoUOHsG7dOuzevRtdunQBALz11lu455578MYbb6BevXqIiIjAokWLAADbtm1DXl6evgVBEIQuWOhgGUEYitw6wl5pa5WNJqYdQrQyjtZjhP/BteUQQRCEGFo+E96mpKQE2dnZEsscq9WK9PR0ZGVlyX4mKyvLwZKnT58+wt8nTpxATk6OJE10dDS6desm5JmVlYWYmBhBMQQA6enpsFqt2Llzp9vfp7i4GAUFBZIfgiAIgiCc4yqamKcWgFbBI7Vc3rQCJrwDKYcIgjAdWp3vJghXXLp0CeXl5UhISJBcT0hIQE5OjuxncnJyHNLHx8dL7tvyUMozJycHdevWldwPDAxEbGys4nPVMHPmTERHRws/ycnJbudFEIQ20L6PIIxFzarSKuMTSEvkfA4RhLch5RBBEIaj9kgTLaD1g6elCOu6iJSF6pk0aRLy8/OFnzNnzhgtEkEQBEFwg9KKwlq9a7a3HNJKlyPnc4hWN4S3IeUQQRCmg16qEN6iTp06CAgIQG5uruR6bm4uEhMTZT+TmJjokP7ixYuS+7Y8lPJMTEx0cHhdVlaGy5cvKz5XDSEhIYiKipL8EITReBoN8Ouvv5bcl4sGeOzYMUkaraIBbt68GZ06dUJISAiaNm2K5cuXu1UGBEEYhxprnRqH1DpZDjHIQhB6QcohgiBMRPXEbLAUhP8QHByMzp07Y+PGjcK1iooKbNy4EWlpabKfSUtLk6QHgE2bNgl/p6SkIDExUZKmoKAAO3fuFPJMS0tDXl4esrOzhTTff/89Kioq0K1bN02+GyvU7wg90CIa4MCBA/HLL78IaeSiAd53332SfLSIBnjixAn069cPd9xxB/bv348JEybgkUcewfr16zUoGYIgvEWljCMhe2N1m2VPuYLyxlPH8s6ioZHhPOEtuI5WRhCEf6B200nHyvQjNjzYaBEEaoXyNTVNnDgRI0eORJcuXdC1a1fMnz8f165dE6KXjRgxAvXr18fMmTMBAOPHj0evXr0wZ84c9OvXD6tWrcK+ffuE/CwWCyZMmIAZM2agWbNmSElJwZQpU1CvXj3BOqFly5bo27cvxowZg8WLF6O0tBSZmZl44IEHUK9ePSGvX3/9FSUlJbh8+TKuXr2K/fv3AwA6dOjglbIhCE/RIhrghg0b8Pbbb2Px4sVOowHa0Coa4OLFi5GSkoI5c+YAqOq3P/74I+bNm4eMjAzVZUBzG0EYi5LCR4zgc0inaGV6WyYRhBr4WoETBEGogOZN7emdWhcPdW+MtvWjjRYFzRNqYdwdNyEhKtRoUQAAQ4cOxcWLFzF16lTk5OSgQ4cOWLdunbDZPH36NKzWGkPc7t27Y+XKlXjxxRcxefJkNGvWDCtXrsSQIUOENM899xyuXbuGsWPHIi8vDz179sS6desQGlrznVesWIHMzEz06dMHVqsVgwcPxoIFCySy3XPPPTh16pTwf8eOHQHQ4pIwB7ZogJMmTRKuqYkGOHHiRMm1jIwMrFmzBoByNMAuXbpg27ZtQh7OogHaWxkpIReZMCMjAxMmTJBNX1xcjOLiYuF/ihZIEHxQLlL4KE2fSpY9Ws22FjmfQzSVE16GlEMEQZgG28tVckCsPVarBS/9pbXRYgg8m5GqOq03Fk+ZmZnIzMyUvbd582aHa0OGDJEog+w3gRaLBdOnT8f06dMVnxkbG4uVK1c6levkyZNO7xMEzziLBvjbb7/JfkYuGqB9pD/bNTH2EQO1iAaoJEtBQQFu3LiBsLAwyb2ZM2fi5ZdfdsiHLIcIwlgqKlyn0T9aGXTNnyDUQD6HCIIwHLXzIC2gCYIgCLNC0QIJgk/kjpVZ7BadcpY9cvfdxanyida/hJcgyyGCIEwHvVQhCIIwP1pFA7SP9Ge7lpSUJKSxjxioRTRAJVmioqIcrIaAqmiBISEhqvMnCMI7lKvwI2St9kitxj+RO1jpDSjBAWQ5RBCEafA0EgThm5CukCDMiVbRADds2CCkV4oGuGfPHkkeWkQDdCWLWmhPSBDGouYoV4CCw2itdEVyx8rIfyDhbchyiCAIw2Gd+miqJAiC8A20iAa4Z88evPvuuwCUowEmJiYKztu1igb46KOP4u2338Zzzz2Hhx9+GN9//z0++eQTrF271kulRxCEFkh9DsmvMq0ujpV5Sk00NH3yJwg1kHKIIAjTILxd1eFNynN9W2D2usOICQ/SPG9CX+jNmneIiwzG+fwio8UgfAwtogGuWbMGbdq0EdLIRQP87LPP0LlzZyGNFtEAU1JSsHbtWjz11FN488030aBBAyxZsoQpjD1AVrEEYTRy4ente6WFHFITfgAph1RSXl6O0tJSo8UgCLcpKSlBo0aNUFJSgqIi9Ru8oKAgBAQE6CiZevQ0vW8aHwkASKkTod9DCMKklJeXY/79bfDGt79heNdGTGMIQbjikUcewSOPPCK5Zmtj69atk/wPAP3790f//v1l09uYPHkyJk+eLPxfWFgomQPDw8OxdOlSB1nE+ShFTBOnueWWW5CVleVUFiXUpqM1KGF23F2D6o1NlnIVNuk2y6HKyioFsYPDag9lsVkOyUlC6mPCW5ByyAWVlZXIyclBXl6e0aIQhEdUVFRg8eLFyM3NlTjmVENMTAwSExMdJkKtYH1Josc7FWFSphc2BCFgPweO7xoDIB8nTuQbKRZBMOPJHKgXhYWFAJRffNAalPAVeOx/QE0fVOWQWtRRKyqBAI2XxDXKJ1qIEsZByiEX2CblunXrIjw8XLfNMUHoTXl5OW7cuIHGjRurtgSqrKzE9evXhagu4sgvRmAzvddj3rTQpGxaUupE4NjFa0aL4ZPQHEj4Cu7MgXpTUFDg9D71P8JX4LH/ATV9UOoEWj6tLVqZLX2AbU2q0SvLmmNrNddoRUp4G1IOOaG8vFyYlOPi4owWhyA8ory8HAAQGhrKNDHbwvFeuHABdevWNXZS13FdLCiH9HsEoROvDWqLqK9/w/BbGhktik9BcyDhS7g7B+pJSUkJAPmpjfof4Uvw2P+Amj5YrsIJtEg3pItfIFv25HOIMBIKZe8E2/nu8PBwgyUhCGOx9QHdfB6wHivTZVKmY2VmpW6tUMwd2gGdG9U2WhSfguZAgjAO6n+Ev7No0SK0a9cOUVFRiIqKQlpaGr755hvhflFREcaNG4e4uDhERkZi8ODByM3NdetZcsfK7A31xMfK5NaKnhr2OXNvQFaDhLcg5ZAKqEMS/o7efaBMZdxOPaWosRwi7RBBiKE5kCD0xVkXo/5H+CsNGjTA66+/juzsbOzZswe9e/fGgAEDcPDgQQDAU089hS+//BKrV6/Gli1bcO7cOQwaNMitZ6l56ShWDqnxUcSKLSgjuTcgjISOlREEYTil5WwToR7TpnDWW52eiiAIgiAIgtAJ+4iEr776KhYtWoQdO3agQYMGeP/997Fy5Ur07t0bALBs2TK0bNkSO3bswC233ML0LLGyR2mNaVE6VqbRolTW5xDpiQgvQ5ZDhNexWCxYs2aN0WIQHFGq5rA3aiZOXRxSV/+meZggCDUsX74cMTExwv8vvfQSOnToIPz/0EMPYeDAgcL/t99+OyZMmMD8nJMnT8JisWD//v1uy0o4x+gytlCgardo3Lgx5s+fb7QYXOJLZbN582ZYLBa8//77uHbtGtLS0pCdnY3S0lKkp6cL6VJTU9GwYUNkZWUp5lVcXIyCggLJD6DOz0+AxCG1B19IKf/qNW6ZHpkThEpIOeSDXLx4EY899hgaNmyIkJAQJCYmIiMjA9u2bTNaNI956aWXYLFYnP74GvYbEF9ErXIoJLBqyCou0968h6KVEYRv8NBDD8nODX379tX0OUOHDsWRI0cU77/55ptYvny5x89JTk7G+fPn0aZNG4/zYkVpzk1NTfW6LGZE7Qbd15Yu9n0wLi4Offv2xc8//2yoXDYlg9xPTk6OobKZAXuFt7N0FosFjz76qMO9J554AhaLBQ899JCqZx44cAD33nsvAgIC8PTTT+Pzzz9Hq1atkJOTg+DgYIf1cXh4OCZOnIi8vDzZ/GbOnIno6GjhJzk5GYCCzyE7pW2AqKPKrVs9VfKGB1c56r5RUiaTN0F4B1IO+SCDBw/Gvn378MEHH+DIkSP44osvcPvtt+PPP/80WjSPeeaZZ3D+/Hnhp0GDBpg+fbrkmlmwRUjwJmVljhMOD6hVDoUFVU+cpeWay+DMESBBEOaib9++knnh/Pnz+OijjzR9RlhYGOrWrat4Pzo62mPFfklJCQICApCYmIjAQGM8AbRu3dqhLH/88UdDZCHMg7gPbty4EYGBgbj33nuNFgsAcPjwYYc27awvE+wkJydj1apVuHHjhnCtuLgYH330ERo2bKg6nxYtWmD//v3YuXMnHnvsMYwcORK//vqr23JNmjQJ+fn5ws+ZM2eqZFPx0tFqtSCiWoFTWKT9ejo8uGqMv1ai/RqXINRCyiEfIy8vDz/88ANmzZqFO+64A40aNULXrl0xadIk/OUvfxHSzZ07F23btkVERASSk5Px+OOPo7CwULhvs1b56quv0KJFC4SHh+P+++/H9evX8cEHH6Bx48aoXbs2nnzySSE8JVD1luyVV17BsGHDEBERgfr162PhwoVOZT5z5gz++te/IiYmBrGxsRgwYABOnjwpmzYyMhKJiYnCT0BAAGrVqiX8X1pa6jQv21uP1157DQkJCYiJicH06dNRVlaGZ599FrGxsWjQoAGWLVsmfMZmbr5q1Sp0794doaGhaNOmDbZs2SKR7ZdffsHdd9+NyMhIJCQk4O9//zsuXbok3L/99tuRmZmJCRMmoE6dOsjIyHBZF5s3b8aoUaOQn58vvN166aWXAMgfz4uJiRHeVNvk/vjjj9GrVy9EREQIUR6WLFmCli1bIjQ0FKmpqXjnnXec1pHeqPU5FFY9KRfpoByy5X1N5o0NQRDmwmY1K/6pXbsmmt3Ro0dx2223ITQ0FK1atcKGDRskY6rNwkD89nn//v2wWCzCnOLKqlPuLXtZWRkyMzMRHR2NOnXqYMqUKRJrRdscOmLECERFRWHs2LEOR57knrtmzRqJ5aztiNvSpUvRsGFDREZG4vHHH0d5eTlmz56NxMRE1K1bF6+++qrLsgwMDHQoyzp16khkfu211/Dwww+jVq1aaNiwId59911JHmfPnsWwYcMQGxuLiIgIdOnSBTt37gQAHDt2DAMGDEBCQgIiIyNx880347vvvpN83tXaorKyEi+99JJgMV2vXj08+eSTwn2LxYL//e9/kjzF86U95eXlGD16NFJSUhAWFoYWLVrgzTfflKSx1e8bb7yBpKQkxMXFYdy4cUKUsdtvvx2nTp3CU0895bOWzc4Q98EOHTrghRdewJkzZ3Dx4kUhzfPPP4/mzZsjPDwcTZo0wZQpUxyion755Ze4+eabERoaijp16uC+++5TfOaSJUsQExODjRs3OpWtbt26Dm3aWu0N2FW9AlVKjueffx7JyckICQlB06ZN8f777wNgazsvv/wy4uPjERUVhUcffVTy0vC///0v2rZti7CwMMTFxSE9PR3Xrl0DIH9EdeDAgU6tcdSu+9evX4+WLVsiMjJSUPABVWPKBx98gP/9739Ce968ebPi8zp16oTk5GR89tlnwrVNmzahYcOG6NixoyRtcXExnnzySdStWxehoaHo2bMndu/eDQAIDg7G2bNn0aVLFzz//PNo3749ZsyYgbfeegslJSUIDw9H69at8fXXX+PkyZP47bffAAC1a9eWWCjZrPhCQkKE6Ge33XabMI7k3VD3wrZWaBAA4KoOyqGIkOp1aDGtQwnjIIfUDFRWVupisaCGsKAAVQuLyMhIREZGYs2aNbjlllsQEhIim85qtWLBggVISUnB8ePH8fjjj+O5556TKAmuX7+OBQsWYNWqVbh69SoGDRqE++67DzExMfj6669x/PhxDB48GD169MDQoUOFz/3zn//E5MmT8fLLL2P9+vUYP348mjdvjjvvvNNBjtLSUmRkZCAtLQ0//PADAgMDMWPGDMH8ODg4WHUZqc3r+++/R4MGDbB161Zs27YNo0ePxvbt23Hbbbdh586d+Pjjj/F///d/uPPOO9GgQQMh/2effRbz589Hq1atMHfuXPTv3x8nTpxAXFwc8vLy0Lt3bzzyyCOYN28ebty4geeffx5//etf8f333wt5fPDBB3jsscckR/yc1UX37t0xf/58TJ06FYcPHxbqmIUXXngBc+bMQbt27fD7779j5cqVmDp1Kt5++2107NgR+/btw5gxYxAREYGRI0cy5a0VZ6/cwP2Ltgv/H8m5KpsutNpy6N2tx7H31BUAQKlGZ7NrhwcLsgxetF0w4T16oVD5QwThR5hhDlRDRUUFBg0ahISEBOzcuRP5+flu+QJyhw8++ACjR4/Grl27sGfPHowdOxYNGzbEmDFjhDRvvPEGpk6dimnTpnn0rGPHjuGbb77BunXrcOzYMdx///04fvw4mjdvji1btmD79u14+OGHkZ6ejm7dunn0rDlz5uCVV17B5MmT8d///hePPfYYevXqhRYtWqCwsBC9evVC/fr18cUXXyAxMRF79+5FRbX3/8LCQtxzzz149dVXERISgg8//BD9+/fH4cOHJRYGztYWn376KebNm4dVq1ahdevWyMnJwU8//eT296moqECDBg2wevVqxMXFYfv27Rg7diySkpLw17/+VUi3adMmJCUlYdOmTfj9998xdOhQdOjQAWPGjMFnn32G9u3bY+zYsZL6leN/+8/hib7tXcpl1j5YWFiI//znP2jatCni4uKE67Vq1cLy5ctRr149HDhwAGPGjEGtWrXw3HPPAQDWrl2L++67D//4xz/w4YcfoqSkBF9//bXsM2bPno3Zs2fj22+/RdeuXd2S04azegWAESNGICsrCwsWLED79u1x4sQJ4WWg2razceNGhIaGYvPmzTh58iRGjRqFuLg4vPrqqzh//jyGDRuG2bNn47777sPVq1fxww8/eHTsXe26/4033sC///1vWK1WPPjgg3jmmWewYsUKPPPMMzh06BAKCgqEF6ixsbFOn/nwww9j2bJlGD58OADgiy++wMiRI7F161ZJuueeew6ffvopPvjgAzRq1AizZ89GRkYGfv/9d4dnVFRU4IcffkDTpk0RGBiIN954Q1CAX79+XUh3+PBhREVFISwsTFX5vPnd78g6XWXldPm6sqIoKiwQOQXAg+/vRNO6Vevxk5euqXqGKyJDqrblH2adwsFzBbBAHyUUQTiDlEMM3CgtR6up6w159q/TMwRzQ2cEBgZi+fLlGDNmDBYvXoxOnTqhV69eeOCBB9CuXTshnXgh3LhxY8yYMQOPPvqoZJIoLS3FokWLcNNNNwEA7r//fvz73/9Gbm4uIiMj0apVK9xxxx3YtGmTRDnUo0cPvPDCCwCA5s2bY9u2bZg3b56scujjjz9GRUUFlixZIiw6li1bhpiYGGzevBl33XWX6jJSm1dsbCwWLFgAq9WKFi1aYPbs2bh+/TomT54MoMrk9PXXX8ePP/6IBx54QMg/MzMTgwcPBgAsWrQI69atw/vvv4/nnntOULS89tprQvqlS5ciOTkZR44cQfPmzQEAzZo1w+zZsyVyO6uL4OBgREdHw2KxIDExUXVZ2Oc/aNAglJeXIy8vD5mZmZgzZ44Q7jMlJQW//vor/vWvfxmmHAKAPdXKHjGJ0aGS/9vVj1ZMnxAlrwhVS72YUCREhSC3oBjZMrIk2MlCEP6GGeZAG1999ZWDIn3y5MmYPHkyvvvuO/z2229Yv3496tWrBwB47bXXcPfdd2sqsxzJycmYN28eLBYLWrRogQMHDmDevHkS5UHv3r3x9NNPC/8rWdK6oqKiAkuXLkWtWrWE+frw4cP4+uuvhflv1qxZ2LRpk1Pl0IEDBxzK8sEHH8TixYuF/++55x48/vjjAKqsQebNm4dNmzahRYsWWLlyJS5evIjdu3cLG72mTZsKn23fvj3at69RjLzyyiv4/PPP8cUXXyAzM1O47mxtcfr0aSQmJiI9PR1BQUFo2LChRwqCoKAgvPzyy8L/KSkpyMrKwieffCLZ4NeuXRtvv/02AgICkJqain79+mHjxo0YM2YMYmNjJdbNzrivY31Vcpm1D167dg1JSUn46quvBAsdAHjxxReFvxs3boxnnnkGq1atEpRDr776Kh544AFJXYjbio3nn38e//73v7Flyxa0bt3apWziF38A0KhRIyE8OuC8Xo8cOYJPPvkEGzZsEJwhN2nSRPis2rYTHByMpUuXCpYv06dPx7PPPotXXnkF58+fR1lZGQYNGoRGjRoBANq2bevyezlD7bp/8eLFwro/MzMT06dPB1D1YjIsLAzFxcWq16MPPvggJk2ahFOnTqG8vBw///wzvvzyS4ly6Nq1a1i0aBGWL18ujMHvvfceNmzYgPvvvx8vvfSS4A/q5ZdfxubNm9GoUSPcfvvtSE1NxaxZs7B8+XJERETgkUceQevWrXHw4EHUrVuX+Viv/brSfg0KAHe2SsCR3ELk3yh1WCvKpWehV4t4zN1wBMVlFZrnTRBqIeWQDzJ48GD069cPP/zwA3bs2IFvvvkGs2fPxpIlSwTzyu+++w4zZ87Eb7/9hoKCApSVlaGoqAjXr19HeHg4gCqnbrYJAgASEhLQuHFjySIxISEBFy5ckDw/LS3N4X8lh4w//fQTfv/9d9SqVUtyvaioCMeOHWP63mrzat26tWRxkpCQIHH0GRAQgLi4OKffKzAwEF26dMGhQ4eEZ2/atEnWqufYsWOCcqhz584O99XUhSd06dJF+PvGjRs4duwYRo8eLdmMlJWVITo6Wu7jXmHe0A6IsCu7xOgwtK0vlSm9VQI+fSwNF68WO+TRrkGMRzKEBAbgi8ye2H8mz+HtXJ3IEHRuVFvhkwRB8MYdd9yBRYsWSa7ZFBOHDh1CcnKyoBgCHOctvbjlllsk1hdpaWmYM2cOysvLERBQZRkpHrM9oXHjxpL5MCEhAQEBAQ7zn/1cZ0+LFi3wxRdfSK5FRUVJ/he/fLK9zLDlu3//fnTs2FHRyqCwsBAvvfQS1q5dK2yKb9y4gdOnT0vSOVtbDBkyBPPnz0eTJk3Qt29f3HPPPejfv79HfpoWLlyIpUuX4vTp07hx4wZKSkok0eiAqvWErd4AICkpCQcOHGB+1vBujdyWk1fEffDKlSt45513cPfdd2PXrl2CwuPjjz/GggULcOzYMRQWFqKsrEzStvbv3+/S6mrOnDm4du0a9uzZI1HSOOOHH36Q9I2goCDJfWf1un//fgQEBKBXr16K+atpO+3bt5es8dLS0lBYWIgzZ86gffv26NOnD9q2bYuMjAzcdddduP/++yVHY1lxZ92flJTkcnxwRnx8PPr164fly5ejvLwcPXr0kBxJBarWyKWlpejRo4dwLSgoCF27dsXBgwcxYsQInDt3DgCwb98+rF+/HqdOncJjjz2GLl26oG7duhg4cCDKysqQkZGBZ555RniRy0LVOrSmTQRYLUi7Kc4h3TN3tUBakzooFI5+Va0XY8KD0bWxc0sqV6QmRuHr8bfiaG4hxLFzLRYLbklxlIUg9ICUQwyEBQXg1+kZhj2bhdDQUNx555248847MWXKFDzyyCOYNm0aHnroIZw8eRL33nsvHnvsMbz66quIjY3Fjz/+iNGjRwvndwHHydJisches5mGu0NhYSE6d+6MFStWONyLj4/XJS89vldhYSH69++PWbNmOdxLSkoS/o6IiJDcU1sXclgsFgclhv1Zfftn2kxu33vvPYc3xeKFkLe5s1WCw2ZDic6NPJt8nZEQFYqM1u5ZaBGEr2OmOTAiIkJincKKTYEiHmPlxlc9sJ8n7LFararGfq3muuDgYJdl6SxfV8c6nnnmGWzYsAFvvPEGmjZtirCwMNx///1MQRuSk5Nx+PBhfPfdd9iwYQMef/xx/POf/8SWLVsQFBSker60sWrVKjzzzDOYM2cO0tLSUKtWLfzzn/8U/CSp+d4sWK3qjmuZuQ8uWbIE0dHReO+99zBjxgxkZWVh+PDhePnll5GRkYHo6GisWrUKc+bMqXmmiiNBt956K9auXYtPPvlEsCxzRUpKilOrEk/as9q244yAgABs2LAB27dvx7fffou33noL//jHP7Bz506kpKSoHgNseLLu9zSC68MPPyxYALIe3+3ZsyeWLl2KzZs344477sCaNWuEesvIyMDatWvx7bff4qeffsKcOXPwxBNPKPpBclVmatehFosFPZvVcZnOXW6Kj8RN8WzuIwhCS0g5xIDFYmEyqeWJVq1aCY42s7OzUVFRgTlz5ggL4E8++USzZ+3YscPh/5YtW8qm7dSpEz7++GPUrVtXtXJACS3zkmPHjh247bbbAFRZ2mRnZwsTXqdOnfDpp5+icePGTG8q1dRFcHCwxOm3jfj4eEl0tqNHj0rOW8sRFxeHevXq4fjx48IZcIIgCDWYeQ4U07JlS5w5cwbnz58XlPf285bthcL58+eFt/U2h9CeYL9B3LFjB5o1a8aknI+Pj8fVq1dx7do1QZGkhWx60a5dOyxZsgSXL1+WtR7atm0bHnroIcHRcGFhoexROldri7CwMPTv3x/9+/fHuHHjkJqaigMHDqBTp07CfGmzWHE1X27btg3du3cXjsoBYLZmBpTnb3cxcx+0WCywWq1C9Krt27ejUaNG+Mc//iGkOXXqlOQz7dq1w8aNGzFq1CjFfLt27YrMzEz07dsXgYGBeOaZZ/T5AtW0bdsWFRUV2LJli3CsTIzatvPTTz/hxo0bgrJpx44diIyMFEKrWywW9OjRAz169MDUqVPRqFEjfP7555g4caLD+q+8vBy//PIL7rjjDlmZtVr3u9Oe+/bti5KSkirrl1tucbh/0003ITg4GNu2bRP6Z2lpKXbv3u1UmZScnIxHH30Ujz76KCZNmoT33nsPTzzxhOBf1F5O+zIrKCjAiRMnmL4LQfgDFK3Mx/jzzz/Ru3dv/Oc//8HPP/+MEydOYPXq1Zg9ezYGDBgAoOqsf2lpKd566y0cP34c//73vyW+Azxl27ZtmD17No4cOYKFCxdi9erVGD9+vGza4cOHo06dOhgwYAB++OEHnDhxAps3b8aTTz6Js2fPMj1Xy7zkWLhwIT7//HP89ttvGDduHK5cuYKHH34YADBu3DhcvnwZw4YNw+7du3Hs2DGsX78eo0aNcjqRqqmLxo0bo7CwEBs3bsSlS5eEBW3v3r3x9ttvY9++fdizZw8effRRh7c+ckybNg0zZ87EggULcOTIERw4cADLli3D3LlzPSgdgiAIfiguLkZOTo7kx+YwNj09Hc2bN8fIkSPx008/4YcffpBsUIGqsTk5ORkvvfQSjh49irVr10osGtzl9OnTmDhxIg4fPoyPPvoIb731luL8qES3bt0QHh6OyZMn49ixY1i5cqVi1C0tKCsrcyjL3Nxc1Z8fNmwYEhMTMXDgQGzbtg3Hjx/Hp59+iqysLABVvvg+++wz7N+/Hz/99BP+9re/yVrfOFtbLF++HO+//z5++eUXHD9+HP/5z38QFhYmbDZ79+6Nd955B4cPH1Y1XzZr1gx79uzB+vXrceTIEUyZMkWInsRC48aNsXXrVvzxxx+S6KX+gLgPHjp0CE888YRgZQ1UlfHp06exatUqHDt2DAsWLMDnn38uyWPatGn46KOPMG3aNBw6dAgHDhyQtdDu3r07vv76a7z88suKbgzEXLhwwaFNq7UMbNy4MUaOHImHH34Ya9asEdaaNmWL2rZTUlKC0aNH49dff8XXX3+NadOmITMzE1arFTt37sRrr72GPXv24PTp0/jss89w8eJFQRnau3dvrF27FmvXrsVvv/2Gxx57TBJZ0R6t1v2NGzfGzz//jMOHD+PSpUuqyiwgIECoOzkleEREBB577DE8++yzWLduHX799VeMGTMG169fx+jRo2XznDBhAtavX48TJ05g79692LRpk1A2jRo1gsViwVdffYWLFy8KEdl69+6Nf//73/jhhx9w4MABjBw50lCLeYLgFVIO+RiRkZHo1q0b5s2bh9tuuw1t2rTBlClTMGbMGLz99tsAqs45z507F7NmzUKbNm2wYsUKzJw5UzMZnn76aezZswcdO3bEjBkzMHfuXCFsuz3h4eHYunUrGjZsiEGDBqFly5YYPXo0ioqKmK1/tMxLjtdffx2vv/462rdvjx9//BFffPGFcHa6Xr162LZtG8rLy3HXXXehbdu2mDBhAmJiYiT+HexRUxfdu3fHo48+iqFDhyI+Pl5waD1nzhwkJyfj1ltvxd/+9jc888wzqnwUjR49GkuWLMGyZcvQtm1b9OrVC8uXL0dKSooHpUMQBMEP69atQ1JSkuSnZ8+eAKqOF3z++ee4ceMGunbtikceecQhpHtQUBA++ugj/Pbbb2jXrh1mzZqFGTNmeCzXiBEjhOeOGzcO48ePx9ixY5nyiI2NxX/+8x98/fXXaNu2LT766CO89NJLHsumxMGDBx3K0qZ0UUNwcDC+/fZb1K1bF/fccw/atm2L119/XdiYzZ07F7Vr10b37t3Rv39/ZGRkoFOnTg75OFtbxMTE4L333kOPHj3Qrl07fPfdd/jyyy+FyFhz5sxBgwYNMGbMGPz97393OV/+3//9HwYNGoShQ4eiW7du+PPPPyWWIGqZPn06Tp48iZtuuon5qLzZEffBbt26Yffu3Vi9ejVuv/12AMBf/vIXPPXUU8jMzESHDh2wfft2TJkyRZLH7bffjtWrV+OLL75Ahw4d0Lt3b+zatUv2eT179sTatWvx4osv4q233nIqW4sWLRzadHZ2turvtmjRItx///14/PHHkZqaijFjxghh5tW2nT59+qBZs2a47bbbMHToUPzlL38R+nFUVBS2bt2Ke+65B82bN8eLL76IOXPmCA6bH374YYwcORIjRoxAr1690KRJE0WrIUC7df+YMWPQokULdOnSBfHx8ZLIu86whY5X4vXXX8fgwYPx97//HZ06dcLvv/+O9evXK/pYKi8vx7hx49CyZUv07dsXzZs3Fxxr169fHy+//DJeeOEFJCQkCBb+kyZNQq9evXDvvfeiX79+GDhwoMS/EkEQVVgqPT1ManIKCgoQHR2N/Px8h4GrqKgIJ06cQEpKCkJDyUu8Gho3bowJEyZ4LSywNzh58iRSUlKwb98+B4eCZqK8vBz79u1Dx44dmd+W6NUXnPU/gvAleG3rNAfWYLFY8Pnnn2PgwIFGi0LYocXawpM5UC+o//knDz30EPLy8gR3D/4Aj/0P4HduJgitUdvWyXKIIAiCIAiCIAiCIAjCjyHlEEEQBEEQBEEQBEEQhB9jzpAHBLfIRRgxO40bN/Y4lCdBEATBNzTO84svri0I/0VPB/IEQRCeQJZDBEEQBEEQBEEQBEEQfgwphwiCIAiCIAiCIAiCIPwYUg6poKKiwmgRCMJQqA8QhP9C/Z8gjIP6H0EQBOEtyOeQE4KDg2G1WnHu3DnEx8cjODgYFovFaLEIwi3Ky8sBVIXHVRtGtLKyEiUlJbh48SKsViuCg4P1FJEgCI6gOZDwJdyZA/WmqKhI8R71P8KX4LH/Ac77IEH4I6QccoLVakVKSgrOnz+Pc+fOGS0OQXhERUUFLl26hJMnT8JqZTMaDA8PR8OGDZk/RxCEeaE5kPAlPJkD9aKwsFDxHvU/wpfgsf8BzvsgQfgjpBxyQXBwMBo2bIiysjJB600QZqSwsBD9+vXDnj17EBkZqfpzAQEBCAwMpDeWBOGH0BxI+AruzoF6UlBQ4PQ+9T/CV+Cx/wGu+yBB+BukHFKBxWJBUFAQgoKCjBaFINympKQEp06dQnBwMEJDQ40WhyAIk0BzIOEL8DgHlpSUuExD/Y/wBXjsf4C6PkgQ/gQ/dn0EQRAEQRAEQRAEQRCE1yHlEEEQBEEQBEEQBEEQhB9DyiGCIAiCIAiCIAiCIAg/xu99DlVWVgIgh2SE72Nr47Y2zwPU/wh/gcf+B1AfJPwHHvsg9T/CX+Cx/wHUBwn/QW0f9Hvl0J9//gkASE5ONlgSgvAOV69eRXR0tNFiAKD+R/gfPPU/gPog4X/w1Aep/xH+Bk/9D6A+SPgfrvqg3yuHYmNjAQCnT5/marDyJgUFBUhOTsaZM2cQFRVltDiG4A9lUFlZiatXr6JevXpGiyJA/c8/2p4r/KEMeOx/APVBwD/anyv8oQx47IPU//yj7bnCH8qAx/4HUB8E/KP9ucIfykBtH/R75ZDVWuV2KTo62mcbg1qioqKoDHy8DHib+Kj/1eDrbU8Nvl4GvPU/gPqgGF9vf2rw9TLgrQ9S/6vB19ueGny9DHjrfwD1QTG+3v7U4OtloKYPkkNqgiAIgiAIgiAIgiAIP4aUQwRBEARBEARBEARBEH6M3yuHQkJCMG3aNISEhBgtimFQGVAZGAWVO5UBQGVgJFT2VAYAlYFRULlTGQBUBkZCZU9lAFAZiLFU8hZTkCAIgiAIgiAIgiAIgvAafm85RBAEQRAEQRAEQRAE4c+QcoggCIIgCIIgCIIgCMKPIeUQQRAEQRAEQRAEQRCEH0PKIYIgCIIgCIIgCIIgCD/GLeXQ/7d3brFRVe0bf+ew59QyM22RGSotVMYeJFAOpmUQtLYNxZAgitBgA1YIIpCYiBG9UAoXRsJBLxowemGRGxp6I4qoIQViQgoK4SD0oKKkAk4JwaEe6IHO87/43MvZnQ7tfLTQ/9fnl3Cx955517se1o+VrJTunTt3yoQJE8ThcEhhYaF8++236llHR4esW7dO0tLSJDk5WRYtWiRtbW391qyrq5Pc3FxxOBwyefJkOXjwoOE5ANm4caOMHTtWnE6nlJaWyo8//thv3aNHj8r06dPFbrdLIBCQ3bt3JzSfeKxcuVI0TROTySQul0vef/99QwZr164Vl8slZrNZLBaLzJkzJ6bfGzduSEVFhbjdbvF6vVJcXCzZ2dmGDM6dOydz5swRh8Mh48aNk9LS0pgM+stuOGfwzjvvyKxZs8TlconX6+1zLq2trTJ//nxxuVzywAMPSDAYjMmgvzkOVQZ3u24vXbokK1eulKysLHE6nTJx4kSpqqqSrq4uQ53odZCSkiKpqakxfdbV1Ul2drZYLBaxWq3idDrpH/2jf4PsX0ZGhixcuDCmV70Xu90uaWlp4na7uQfSQTrIPXDYrj36R/+4B/4HOkgH/9sM7peDW7duTbiXAYMEqa2thc1mw8cff4wLFy5g1apV8Hq9aGtrAwC8/PLLyMjIQH19PU6ePImZM2di1qxZd6x57NgxWCwWbN26FY2NjXjrrbegaRq+//579ZktW7bA4/Hg008/xdmzZ7FgwQJkZWXh1q1bcev+/PPPcLlcWL9+PRobG1FdXQ2LxYKvvvpqwPPpi82bN0NEsHjxYnz22WeYNm0aRARHjx5VGXg8HiQlJWH79u2YMmUKUlJSYvqdN28e8vPzcfz4cezatQsigqlTpxoySEtLQ0VFBc6fP4+lS5dCRLBmzRqVQXp6Osxmc9zshnsGGzduxHvvvYf169cjKSmpz3UQCARQWlqK06dP48UXX4TJZMKiRYtUBhkZGXA6nXHnOFQZDMa6/fLLL1FZWYmvv/4aFy9exP79+zFmzBi89tprqsbNmzfh8/lQUVGBbdu2wWq1QtM0VFVVqT4PHDgAi8WCmTNnwu/3o6KiAlarFVOmTKF/9I/+DZJ/58+fxyuvvAIRwfLly1Wvo0aNUuugvLwcbrcbFosFtbW13APpIB3kHjgs1x79o3/cA+ng/c6ADibu4N69e+F0OvHhhx8m1MtASfhwqKCgAOvWrVPXPT09SE9Px7vvvotwOAxN01BXV6eeNzU1QUTQ0NAQt+aSJUswf/58w73CwkKsXr0aABCJROD3+7Ft2zb1PBwOw263Y+/evXHrbtiwAZMmTTLcKy8vR1lZ2YDmE4/U1FSMHz/e8B1N01BQUKAy8Hq9ql89A03TVL+NjY0QEXz33Xcqg4KCAphMJly5cgUAMGHCBNhsNnR2dqoMioqKkJOTozIwm82YNm1a3OyGcwbR1NTUQNO0mHWQk5MDEUEoFFIZPPvss3C73ejs7EQ4HIbFYsG4cePiznGoMhiqdbt161ZkZWWp6127diElJQWdnZ2qzzfeeAM5OTmqz8mTJ2Pu3LkG/woLC7FkyRL6R//o3z/crX96r9OnT1froKenB06nEzk5OYY9UO+FeyAdjJdBNHTwX7gH0j/6Nzz903vlHkgH6eD9cxCA2gMH2ksiJPTfyrq6uuTUqVNSWlqq7pnNZiktLZWGhgY5deqUdHd3G57n5uZKZmamNDQ0qHsTJkyQTZs2qeuGhgbDd0REysrK1Hd++eUXCYVChs94PB4pLCw01C0qKpLKysoB1+1vPvEyuHHjhpSUlBi+k5eXJ83NzSqDcDis6uoZZGRkqLpz5swRu90ujz76qOp1yZIlYjab5cSJEyIi4na7xeFwiM1mUxk8//zz0tLSIr///rt4PB7RNE2Sk5MNGXR0dKhxhnMGvdfB7du3Y3odM2aMOBwO8fl8KoMVK1ZIe3u7XLhwQTwejyQlJcno0aMNGVy+fHlIMxhI3YGu297cvHlTUlNTDeM8/vjjIiKqz7KyMmlpaZGbN2+qH1EMBAIG/8rKyqS5uZn+0T/69w9345/NZlO9Lly4UK0Ds9ksJpNJNE0z7IF6L9wD6WC8DOhg33APpH/0b/j5xz1Q1HfoIB0cSN2hcDB6HH0dDKSXREjocOj69evS09MjPp/PcN/n80koFJJQKCQ2m028Xm+fz3UmTpxo+EsMhUJxa+rP9Xt3qpuZmSljx47tt257e7vcunWr3/nEy0AfK5oxY8bI33//LaFQSDRNi+nX5/OJpmmqrsfjEbfbbeg1PT1dUlNT1We6urqku7vbkEF2drbhOvozel+9sxuuGfReBwBi+ohEIhKJRAxzzs3NNVxHIhHp6ekxZJCenq7mOBQZ6OMPxrqN5qeffpLq6mpZvXp1zDjRfeo19WednZ1iMpkM/unj0D/611cG9C+WO/kn8u8eOHHiRMMYHR0daq66g9Hj0EE62FcGdDAW7oH0715lQP9i4R7Yf0Z0kA7q3A8Ho2tEj9FfL4lgTfgbg0B9ff2Q1N2zZ8+Q1B0KVq5cKZ988smg192zZ4/s2rVLzpw5M+i1B5uhXAcHDx6Uurq6Iak/VFy5ckXmzZsnixcvllWrVg3ZOPSP/onQv97cK/9E6KAIHRShg73hHnjvoH/0rzfcA+8tdJAO9uZeOngnEvrJodGjR4vFYon5rfNtbW3i9/vF7/dLV1eXhMPhPp/Hw+/3x62pP9fvDUZdt9stTqez3/n0hX7C2draarh/7do1cblc4vf71QludN22tjbp7u42zOnatWuGXq9evSo3btxQn7HZbOrkVb/3ww8/GK6jP9NX/8M5g96YTKaYPsxms5jNZsOcm5ubDdf6b8GPN8ehyEAff7DW7dWrV+XJJ5+UWbNmyUcffdTnONF96jX1Z3a7XQAY/NPHoX/0r68MekP/7uyfyL974MWLFw1jOBwONVfdwehx6CAd7CuD3tBB7oH91aV/9E+HeyAd7P2Zvvofzhn0hg7272B0jegx+uslERI6HLLZbDJjxgzDSV8kEpH6+noJBoMyY8YM0TTN8LylpUVaW1slGAzGrRsMBmNODw8dOqS+k5WVJX6/3/CZ9vZ2OXHixF3V7W8+8TJITU2Vw4cPG77T3Nwsubm5KgOv16vq6hn8+uuvqm4wGJRwOCynTp1S13V1dRKJRKSwsFBERP744w/p6OiQ7u5ulUFtba3k5ORISkqKtLe3S3d3t/z5559x5zicM+iN1WqN6fX69evS0dEh165dUxns3r1b3G63PPLII9Le3i5//fWX+hHHe5XBQOoOdN1euXJFioqKZMaMGVJTU6P+EYwe55tvvhGTyaT6PHTokOTk5IjH45H6+np5+OGH5eLFiwb/Dh06JHl5efSP/tG/f7gb/7q7u1Wv+/fvV+sgEokIALl9+7ZhD9R74R5IB+Nl0Bs6yD2Q/tG/gWQwkLrcA4f3+qODsdDB/h2MHkdfBwPpJSES/Q3WtbW1sNvt2L17NxobG/HSSy/B6/UiFAoB+M+r6zIzM3H48GGcPHkSwWAQwWDQUKO4uBjV1dXq+tixY7Bardi+fTuamppQVVXV56vgvF4v9u/fj3PnzuHpp5+OeR3esmXL8Oabb6pr/dV1r7/+OpqamrBz584+X113p/n0VVd/fV95eTkOHDiA6dOnQ0Rw5MgRlYHX60VSUhJ27NiB/Pz8mNf3FRcXIy8vD9OmTcOJEyfwwQcfqFcYRmeQlpaGZcuWGV5huHbtWpVBeno6LBaLym7KlCkwm80xrzAcrhls3rwZp0+fxubNm+F0OmG1WvHqq6/i5MmTKoNAIIC5c+fizJkzWLFiBUwmE5577jmVgf4KQ32O+m/77/0Kw8HOYDDW7eXLlxEIBFBSUoLLly/jt99+U390wuEwfD4fli1bhm3btkHTNNhsNmzatEn1+fnnn8NqtSIYDGLs2LFYvnw5rFYr8vPz6R/9o3+D5F/0a3wrKytVr6NGjVLroLy8HB6PR73Gl3sgHaSD3AOH49qjf/SPeyAdvN8Z0MHEHaytrYXL5Yp5lX1/vQyUhA+HAKC6uhqZmZmw2WwoKCjA8ePH1bNbt25h7dq1SElJgcvlwjPPPGOYIACMHz8eVVVVhnv79u1DdnY2bDYbJk2ahC+++MLwPBKJ4O2334bP54PdbkdJSQlaWloMn3niiSfwwgsvGO4dOXIEU6dOhc1mw0MPPYSampqE5hOv7ooVK2C1WiEicDqd2LFjhyGDNWvWwOFwQERgNpsxe/ZsQ7/jx4/Hhg0bsHTpUiQnJ8PtdqOoqAiBQMCQwdmzZzF79mzY7Xakp6ejuLg4JoPo7FwuF0pKSv7fZJCfnw8RifmjaZrK4NKlS3jqqafgdDqRlpaGmTNnxmQQPUeHw4HHHnvsnmRwt+u2pqamz/n3PreNXgcejwderzemz3379iEQCMBsNsNiscBut9M/+kf/Btm/Bx98EAsWLIjpVe9F0zSkpKQgOTmZeyAdpIPcA4ft2qN/9I974H+fPR2kg8D9c3DLli0x/ffXy0AxAUCcHyoihBBCCCGEEEIIIf/jJPQ7hwghhBBCCCGEEELI/xY8HCKEEEIIIYQQQggZwfBwiBBCCCGEEEIIIWQEw8MhQgghhBBCCCGEkBEMD4cIIYQQQgghhBBCRjA8HCKEEEIIIYQQQggZwfBwiBBCCCGEEEIIIWQEw8MhQgghhBBCCCGEkBEMD4cIIYQQQgghhBBCRjA8HCKEEEIIIYQQQggZwfBwiBBCCCGEEEIIIWQEw8MhQgghhBBCCCGEkBHM/wFm+04dGwsY+QAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "f, axs = plt.subplots(nrows=1, ncols=5, figsize=(14,6))\n", "\n", @@ -299,9 +871,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "0 days 00:00:00 0.0\n", + "0 days 00:01:00 1096.460463\n", + "0 days 00:02:00 1096.460463\n", + "0 days 00:03:00 1096.460463\n", + "0 days 00:04:00 1096.460463\n", + " ... \n", + "33 days 07:56:00 1096.460463\n", + "33 days 07:57:00 1096.460463\n", + "33 days 07:58:00 1096.460463\n", + "33 days 07:59:00 1096.460463\n", + "33 days 08:00:00 1096.460463\n", + "Name: setpoint_irradiance_full, Length: 48001, dtype: object" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "chamber.setpoints[\"setpoint_irradiance_full\"]" ] @@ -324,9 +918,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[13], line 3\u001b[0m\n\u001b[0;32m 1\u001b[0m kelvin_temps \u001b[38;5;241m=\u001b[39m chamber\u001b[38;5;241m.\u001b[39msample_temperature \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m273.15\u001b[39m \u001b[38;5;66;03m# convert to kelvin\u001b[39;00m\n\u001b[1;32m----> 3\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[43mpvdeg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdiffusion\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodule_front\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43mtime_index\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchamber\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mback_encapsulant_moisture\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m2400\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[43mbacksheet_moisture\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchamber\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mback_encapsulant_moisture\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m2400\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[43msample_temperature\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkelvin_temps\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m2400\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 7\u001b[0m \n\u001b[0;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# we should be pulling these from the chamber attributes but this works for demonstration purposes\u001b[39;49;00m\n\u001b[0;32m 9\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# these are the water values from the degredation database\u001b[39;49;00m\n\u001b[0;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43meva_diffusivity_ea\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.395\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# eV\u001b[39;49;00m\n\u001b[0;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43mDif\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.13\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# prefactor diffusion, cm^2/s, this is not the right value for prefactor\u001b[39;49;00m\n\u001b[0;32m 12\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_steps\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m20\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# numerical stability issues at small timesteps, the bigger the timestep difference in the timedelta index being passed, the better\u001b[39;49;00m\n\u001b[0;32m 13\u001b[0m \u001b[43m)\u001b[49m\n", + "File \u001b[1;32m~\\dev\\PVDegradationTools\\pvdeg\\diffusion.py:140\u001b[0m, in \u001b[0;36mmodule_front\u001b[1;34m(time_index, backsheet_moisture, sample_temperature, p, CW, nodes, eva_diffusivity_ea, Dif, n_steps)\u001b[0m\n\u001b[0;32m 130\u001b[0m time_step \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m 131\u001b[0m (\n\u001b[0;32m 132\u001b[0m time_index\u001b[38;5;241m.\u001b[39mvalues[i \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 136\u001b[0m \u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;28mint\u001b[39m)\n\u001b[0;32m 137\u001b[0m ) \u001b[38;5;66;03m# timestep in units of seconds\u001b[39;00m\n\u001b[0;32m 138\u001b[0m Fo \u001b[38;5;241m=\u001b[39m Dif \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mexp(\u001b[38;5;241m-\u001b[39mEaD \u001b[38;5;241m/\u001b[39m (\u001b[38;5;241m273.15\u001b[39m \u001b[38;5;241m+\u001b[39m Temperature)) \u001b[38;5;241m*\u001b[39m time_step \u001b[38;5;241m/\u001b[39m (W \u001b[38;5;241m*\u001b[39m W)\n\u001b[1;32m--> 140\u001b[0m \u001b[43m_calc_diff_substeps\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 141\u001b[0m \u001b[43m \u001b[49m\u001b[43mwater_new\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresults\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 142\u001b[0m \u001b[43m \u001b[49m\u001b[43mwater_old\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresults\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 143\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_steps\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 144\u001b[0m \u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mTemperature\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 145\u001b[0m \u001b[43m \u001b[49m\u001b[43mdelta_t\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mDTemperature\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 146\u001b[0m \u001b[43m \u001b[49m\u001b[43mdis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mDisolved\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 147\u001b[0m \u001b[43m \u001b[49m\u001b[43mdelta_dis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mDDisolved\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 148\u001b[0m \u001b[43m \u001b[49m\u001b[43mFo\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mFo\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 149\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 151\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m results\n", + "File \u001b[1;32m~\\dev\\PVDegradationTools\\pvdeg\\diffusion.py:57\u001b[0m, in \u001b[0;36m_calc_diff_substeps\u001b[1;34m(water_new, water_old, n_steps, t, delta_t, dis, delta_dis, Fo)\u001b[0m\n\u001b[0;32m 54\u001b[0m dis \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m delta_dis\n\u001b[0;32m 55\u001b[0m t \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m delta_t \u001b[38;5;66;03m# do we need this one, temperature is not used anywhere?\u001b[39;00m\n\u001b[1;32m---> 57\u001b[0m water_copy \u001b[38;5;241m=\u001b[39m \u001b[43mwater_new\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[1;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], "source": [ "kelvin_temps = chamber.sample_temperature + 273.15 # convert to kelvin\n", "\n",